diff --git a/LICENSE b/LICENSE index 8e8afeb..1bdd6bb 100644 --- a/LICENSE +++ b/LICENSE @@ -1,21 +1,21 @@ -MIT License - -Copyright (c) 2022 : Ka Wai HO - -Permission is hereby granted, free of charge, to any person obtaining a copy -of this software and associated documentation files (the "Software"), to deal -in the Software without restriction, including without limitation the rights -to use, copy, modify, merge, publish, distribute, sublicense, and/or sell -copies of the Software, and to permit persons to whom the Software is -furnished to do so, subject to the following conditions: - -The above copyright notice and this permission notice shall be included in all -copies or substantial portions of the Software. - -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -SOFTWARE. +MIT License + +Copyright (c) 2023 : Ka Wai HO + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/Manifest.toml b/Manifest.toml index c3b0320..5e7f9bf 100644 --- a/Manifest.toml +++ b/Manifest.toml @@ -1,439 +1,439 @@ -# This file is machine-generated - editing it directly is not advised - -julia_version = "1.7.3" -manifest_format = "2.0" - -[[deps.AbstractFFTs]] -deps = ["ChainRulesCore", "LinearAlgebra"] -git-tree-sha1 = "69f7020bd72f069c219b5e8c236c1fa90d2cb409" -uuid = "621f4979-c628-5d54-868e-fcf4e3e8185c" -version = "1.2.1" - -[[deps.Adapt]] -deps = ["LinearAlgebra"] -git-tree-sha1 = "195c5505521008abea5aee4f96930717958eac6f" -uuid = "79e6a3ab-5dfb-504d-930d-738a2a938a0e" -version = "3.4.0" - -[[deps.ArgTools]] -uuid = "0dad84c5-d112-42e6-8d28-ef12dabb789f" - -[[deps.Artifacts]] -uuid = 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-uuid = "76f85450-5226-5b5a-8eaa-529ad045b433" - -[[deps.LibSSH2_jll]] -deps = ["Artifacts", "Libdl", "MbedTLS_jll"] -uuid = "29816b5a-b9ab-546f-933c-edad1886dfa8" - -[[deps.Libdl]] -uuid = "8f399da3-3557-5675-b5ff-fb832c97cbdb" - -[[deps.LinearAlgebra]] -deps = ["Libdl", "libblastrampoline_jll"] -uuid = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e" - -[[deps.LogExpFunctions]] -deps = ["ChainRulesCore", "ChangesOfVariables", "DocStringExtensions", "InverseFunctions", "IrrationalConstants", "LinearAlgebra"] -git-tree-sha1 = "361c2b088575b07946508f135ac556751240091c" -uuid = "2ab3a3ac-af41-5b50-aa03-7779005ae688" -version = "0.3.17" - -[[deps.Logging]] -uuid = "56ddb016-857b-54e1-b83d-db4d58db5568" - -[[deps.MKL_jll]] -deps = ["Artifacts", "IntelOpenMP_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "Pkg"] -git-tree-sha1 = "e595b205efd49508358f7dc670a940c790204629" -uuid = "856f044c-d86e-5d09-b602-aeab76dc8ba7" -version = "2022.0.0+0" - -[[deps.MacroTools]] -deps = ["Markdown", "Random"] 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+ +[[deps.nghttp2_jll]] +deps = ["Artifacts", "Libdl"] +uuid = "8e850ede-7688-5339-a07c-302acd2aaf8d" + +[[deps.p7zip_jll]] +deps = ["Artifacts", "Libdl"] +uuid = "3f19e933-33d8-53b3-aaab-bd5110c3b7a0" diff --git a/Project.toml b/Project.toml index 80d5003..d086fdd 100644 --- a/Project.toml +++ b/Project.toml @@ -1,7 +1,7 @@ name = "MHDFlows" uuid = "1d939cba-ab73-4bc0-975c-87d4c856e1f9" authors = ["Ka Wai HO "] -version = "0.1.3" +version = "0.2.0" [deps] CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba" @@ -10,16 +10,15 @@ FourierFlows = "2aec4490-903f-5c70-9b11-9bed06a700e1" FFTW = "7a1cc6ca-52ef-59f5-83cd-3a7055c09341" HDF5 = "f67ccb44-e63f-5c2f-98bd-6dc0ccc4ba2f" LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e" +LsqFit = "2fda8390-95c7-5789-9bda-21331edee243" +MuladdMacro = "46d2c3a1-f734-5fdb-9937-b9b9aeba4221" +Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c" Reexport = "189a3867-3050-52da-a836-e630ba90ab69" Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2" +PyPlot = "d330b81b-6aea-500a-939a-2ce795aea3ee" ProgressMeter = "92933f4c-e287-5a05-a399-4b506db050ca" +TimerOutputs = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f" +FastBroadcast = "7034ab61-46d4-4ed7-9d0f-46aef9175898" [compat] -CUDA = "^1, ^2.4.2, 3.0.0 - 3.6.4, ^3.7.1" -DocStringExtensions = "^0.8" -FFTW = "^1" -FourierFlows = "^0.10.1" -Reexport = "^0.2, ^1" -julia = "^1.5.3" -HDF5 = "^0.14.3" -ProgressMeter = "^1.7.2" \ No newline at end of file +julia = "^1.7.3" \ No newline at end of file diff --git a/README.md b/README.md index 7c5c46d..e524016 100644 --- a/README.md +++ b/README.md @@ -3,18 +3,20 @@ Three Dimensional Magnetohydrodynamic(MHD) pseudospectral solvers written in Julia language with FourierFlows.jl. This solver support the following features: -1. 2D incompressible HD/MHD simulation (periodic boundary) -2. 3D incompressible HD/MHD simulation (periodic boundary) +1. 2/3D incompressible HD/MHD simulation (periodic boundary) 3. Incompressible HD/MHD simulation with volume penalization method -4. Passive Dye Tracer (Experimental Feature) +4. Isothermal compressible HD/MHD simulation (periodic boundary) +5. 2/3D Electron magnetohydrodynamic simulation (periodic boundary) +6. Passive Dye Tracer (Experimental Feature) This package leverages the [FourierFlows.jl](http://github.com/FourierFlows/FourierFlows.jl) package to set up the module. The main purpose of MHDFlows.jl aims to solve the portable 3D MHD problems on personal computer instead of cluster. Utilizing the Nvidia CUDA technology, the MHDFlows.jl could solve the front-end MHD turbulence research problems in the order of few-ten minutes by using a mid to high end gaming display card (see Memory usage & speed section). Feel free to modify yourself for your own research purpose. ## Version No. -v 0.1.3 +v 0.2.0 +note : v 0.2.0 will be the final major update before the multi-gpu version release ## Installation Guide & compatibility -The current version is tested on v1.5.3/1.7.3/1.8.2 version. +The current version is tested on v1.7.3/1.8.2/1.9.0 version. Currently, you have two way of installing MHDFlows.jl @@ -24,7 +26,7 @@ Currently, you have two way of installing MHDFlows.jl ```julia julia> - (v1.7) pkg> add MHDFlows + (v1.8) pkg> add MHDFlows ``` @@ -37,37 +39,39 @@ The MHD Solver could either run on CPU or GPU. The scalability is same as Fourie **Memory usage** -For GPU users, here are some useful numbers of memory requirement for choosing the resolution of the simulation. You may end up getting higher resolution for the same memory. +For GPU users, here are some useful numbers of memory requirement for choosing the resolution of the simulation with RK4/ LSRK4 method. You may end up getting higher resolution for the same memory. -| Memory Size | Maximum Resolution ( $N^3$ ) | -| ----------- | ------------------------------ | -| 6 GB | $256^3$ (pure HD simulation) | -| 10 GB | $300^3$ (pure MHD simulation) | +| Memory Size | Maximum Resolution ( $N^3$ ) | +| ----------- | ------------------------------| +| 6 GB | $256^3$ (pure MHD simulation) | +| 10 GB | $320^3$ (pure MHD simulation) | +| 24 GB | $512^3$ (pure MHD simulation) | +| 80 GB | $700^3$ (pure MHD simulation) | **Speed** -The following table provides the reference of the runtime for 1 iteration in pure HD/MHD computation. As the benchmarks are running on the WSL2, the runtime could varies and does not reflect the best performance. +The following table provides the reference of the average runtime of 1 iteration in pure HD/MHD computation. As the benchmarks are running on the WSL2, the runtime could varies and does not reflect the best performance. -Method: compute the average time used of 20 iterations using RK4 method +Method: compute the average time used of 100 iterations using RK4 method -Environment: WSL2 in Win11 (Ubuntu 18.04 LTS through jupyter-lab) +Environment: WSL2 in Win11 (Ubuntu 18.04/20.04 LTS through jupyter-lab) -**HD** (Taylor Green Vortex) +**HD** (Taylor Green Vortex, T = Float32) | Spec CPU/GPU | $32^3$ | $64^3$ | $128^3$ | $256^3$ | | --------------------------- | ------ | ------ | ------- | ------- | -| AMD Ryzen 7 5800x 8 threads | 0.139s | 0.178s | 0.764s | 7.025s | -| NVIDIA RTX 3080 10GB | 0.016s | 0.018s | 0.038s | 0.211s | +| AMD Ryzen 7 5800x 8 threads | 0.040s | 0.074s | 0.490S | 7.025s | +| NVIDIA RTX 3080 10GB | 0.016s | 0.018s | 0.023s | 0.152s | -**MHD** (Taylor Green Vortex) +**MHD** (Taylor Green Vortex, T = Float32) | Spec CPU/GPU | $32^3$ | $64^3$ | $128^3$ | $256^3$ | | --------------------------- | ------ | ------ | ------- | ------- | -| AMD Ryzen 7 5800x 8 threads | 0.19s | 0.231s | 1.8s | 18.48s | -| NVIDIA RTX 3080 10GB | 0.041s | 0.060s | 0.15s | 1.23s | +| AMD Ryzen 7 5800x 8 threads | 0.049s | 0.180s | 1.490s | 14.50s | +| NVIDIA RTX 3080 10GB | 0.013s | 0.012s | 0.037s | 0.271s | ## Example -Few examples were set up to illustrate the workflow of using this package. See `example\` for more detail. The documentation is work in progress and will be available in the future. +Few examples were set up to illustrate the workflow of using this package. [Check out](https://github.com/MHDFlows/MHDFlows-Example) for more detail. The documentation is work in progress and will be available in the future. ## Developer MHDFlows is currently developed by [Ka Wai HO@UW-Madison Astronomy](https://scholar.google.com/citations?user=h2j8wbYAAAAJ&hl=en). diff --git a/example/2D_VP_HDExample.ipynb b/example/2D_VP_HDExample.ipynb deleted file mode 100644 index 5c737a0..0000000 --- a/example/2D_VP_HDExample.ipynb +++ /dev/null @@ -1,384 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "popular-brief", - "metadata": {}, - "source": [ - "# 2D Hydro simulation with Volume penalization method\n", - "This notebook aims to show the workflow of setting up aπ Hydro simulation with Volume penalization method in the cylindrical coordinates. ([Morales et al. 2012](https://www.sciencedirect.com/science/article/pii/S002199911400401X))\n", - "\n", - "We pick the classical Taylor Couette experiment in low Re $(Re\\sim 1)$ with the comparsion between the analytical and numerical result." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "prescription-module", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: FourierFlows will use 8 threads\n", - "└ @ FourierFlows /home/doraho/.julia/packages/FourierFlows/IWexK/src/FourierFlows.jl:123\n" - ] - } - ], - "source": [ - "using MHDFlows, PyPlot, CUDA\n", - "using LinearAlgebra: mul!, ldiv!" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "consolidated-workshop", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "CuDevice(1): NVIDIA GeForce RTX 2070 SUPER" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "device!(1)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "wireless-boundary", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "MHDFlows Problem\n", - " │ Funtions\n", - " │ ├──────── B-field: OFF\n", - " ├─────├────── VP Method: ON\n", - " │ ├──────────── Dye: OFF\n", - " │ └── user function: OFF\n", - " │ \n", - " │ Features \n", - " │ ├─────────── grid: grid (on GPU)\n", - " │ ├───── parameters: params\n", - " │ ├────── variables: vars\n", - " └─────├─── state vector: sol\n", - " ├─────── equation: eqn\n", - " ├────────── clock: clock\n", - " └──── timestepper: RK4TimeStepper" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#parameters\n", - "N = 128;\n", - "Nz= 4;\n", - "Lx = 2π;\n", - "ν,η = 1,1;\n", - "dt = 2e-4;\n", - "# Testing the problem \n", - "nothingfunction(args...) = nothing;\n", - "CPUprob = Problem(GPU();\n", - " # Numerical parameters\n", - " nx = N,\n", - " Lx = 2π,\n", - " ny = N,\n", - " nz = Nz,\n", - " # Drag and/or hyper-viscosity for velocity/B-field\n", - " ν = ν,\n", - " nν = 1,\n", - " η = η,\n", - " # VP method\n", - " VP_method = true,\n", - " # Timestepper and equation options\n", - " dt = dt,\n", - " stepper = \"RK4\",\n", - " # Force Driving parameters \n", - " calcF = nothingfunction,\n", - " # Float type and dealiasing\n", - " T = Float32)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "developing-quarter", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ProblemGeneratorTC! (generic function with 1 method)" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "function ProblemGeneratorTC!(prob;L0=2π,T=Float32)\n", - "\n", - " # Output Setting \n", - " x = Array(prob.grid.x);\n", - " y = Array(prob.grid.y);\n", - " z = Array(prob.grid.z);\n", - " nx,ny,nz = prob.grid.nx,prob.grid.ny,prob.grid.nz;\n", - " ux,uy,uz = zeros(T,nx,ny,nz),zeros(T,nx,ny,nz),zeros(T,nx,ny,nz);\n", - " Ux,Uy,Uz = zeros(T,nx,ny,nz),zeros(T,nx,ny,nz),zeros(T,nx,ny,nz); \n", - " V₀ = 1;\n", - " r₀ = 0.32π; \n", - " \n", - " # Setup: Uθ = 1 if r ∈ 0.32π\n", - " # Uθ = r(dθ/dt) ê_θ\n", - " # ̂e_θ = - sinθ ̂i + cosθ ̂j; \n", - " χ = Cylindrical_Mask_Function(prob.grid;R₂=0.82π,R₁=r₀);\n", - " copyto!(prob.params.χ,Array(χ));\n", - " for k ∈ 1:nz,j ∈ 1:ny,i ∈ 1:nx\n", - " r = sqrt(x[i]^2+y[j]^2);\n", - " θ = atan(y[j],x[i]) ;\n", - " θ = isnan(θ) ? π/2 : θ\n", - " sinθ = sin(θ);\n", - " cosθ = cos(θ);\n", - " #sinθ = θ < 0 ? sin(-θ) : sin(θ) \n", - " if r <= r₀\n", - " Ux[i,j,k] = -sinθ*r/r₀\n", - " Uy[i,j,k] = cosθ*r/r₀\n", - " end\n", - " \n", - " end\n", - " \n", - " #Update V + B Conponment to Problem\n", - " SetUpProblemIC!(prob; ux = ux, uy = uy,\n", - " U₀x= Ux, U₀y= Uy);\n", - " \n", - " return nothing\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "central-genetics", - "metadata": {}, - "outputs": [], - "source": [ - "# Setting up the Initial condition for both domain\n", - "ProblemGeneratorTC!(CPUprob);\n", - "Ux,Uy = Array(CPUprob.params.U₀x),Array(CPUprob.params.U₀y);\n", - "Ur,Uθ = xy_to_polar(Ux,Uy);" - ] - }, - { - "cell_type": "markdown", - "id": "loose-humanity", - "metadata": {}, - "source": [ - "## The Solid Domain and Initial condition illustration" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "planned-control", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "A = ones(size(Ux));\n", - "χ = Array(CPUprob.params.χ);\n", - "A[χ.==1].=NaN;\n", - "figure(figsize=(12,6))\n", - "subplot(121);\n", - "imshow(χ[:,:,1]);\n", - "title(L\"Domin\\:function\\:\\chi\");\n", - "subplot(122);\n", - "imshow((A.*Uθ)[:,:,1]);\n", - "title(L\"U_\\theta\");" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "optimum-brown", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "n = 2000, t = 0.4, KE = 13.6\n", - "n = 4000, t = 0.8, KE = 16.4\n", - "n = 6000, t = 1.2, KE = 17.1\n", - "n = 8000, t = 1.6, KE = 17.2\n", - "n = 10000, t = 2.0, KE = 17.2\n", - "n = 12000, t = 2.4, KE = 17.2\n", - "n = 14000, t = 2.8, KE = 17.2\n", - "n = 16000, t = 3.2, KE = 17.2\n", - "n = 18000, t = 3.6, KE = 17.2\n", - "n = 20000, t = 4.0, KE = 17.2\n", - "n = 22000, t = 4.4, KE = 17.2\n", - "n = 24000, t = 4.8, KE = 17.2\n", - "Total CPU/GPU time run = 290.482 s, zone update per second = 5.640959821e6 \n", - "292.189139 seconds (528.47 M CPU allocations: 65.469 GiB, 3.62% gc time) (1.13 M GPU allocations: 279.038 GiB, 0.90% memmgmt time)\n" - ] - } - ], - "source": [ - "# Set up the initial condition\n", - "@CUDA.time TimeIntegrator!(CPUprob,5.0,50000;\n", - " usr_dt = dt,\n", - " diags = [],\n", - " loop_number = 2000)" - ] - }, - { - "cell_type": "markdown", - "id": "continued-respect", - "metadata": {}, - "source": [ - "# Comparsion Between Numerical & Analytical Soultion " - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "comparable-uncle", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "TCFlowSolution (generic function with 1 method)" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "function TCFlowSolution(L,N;R₁ = 0.32*π, R₂ = 0.95π, Ω₁ = 1, Ω₂ = 0)\n", - " dev = CPU();\n", - " Lx = Ly = L;\n", - " nx = ny = N;\n", - " T = Float32;\n", - " grid = TwoDGrid(dev, nx, Lx, ny, Ly; T=T)\n", - " Uθ = zeros(nx,ny)\n", - " for j ∈ 1:ny, i ∈ 1:nx\n", - " r = sqrt(grid.x[i]^2+grid.y[j]^2);\n", - " Uθ[i,j] = (Ω₂*R₂^2 - Ω₁*R₁^2)/(R₂^2-R₁^2)*r + ((Ω₁-Ω₂)*R₁^2*R₂^2)/(R₂^2-R₁^2)/r\n", - " end\n", - " return Uθ \n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "muslim-earth", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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vgcyOHTvwwAMPpDKgCCl2ApZlWYUeBCGEEEIIIYQQQgghhLQVl156Ke6//34AQN++ffH1r38dlmVh+fLl2L59O8LhMH7729/i8ssvdxwn1iPasGED+vXrl6qfO3cu/u///g9vvvkmxo8frz3n559/ngokqcfLTJs2DXfccQfGjRuHd955J1V/3XXXYdasWSgpKcHxxx+Pnj17YuXKlVi9ejWuvvpq3HLLLejTpw82bdrk6G/p0qUYO3YsotEoevXqhXHjxqGhoQFvvPEG9t13X5SUlGD9+vUZY993333x1VdfYdu2bejRo0eLx9GrVy988cUX2Lp1ayq7TIdlWdhnn32wY8cOXHPNNbj11ltx+OGHY8iQIVi/fj0WLFiAQCCAO+64I+P9EWN2O8dXX32F0aNH45NPPkGfPn0wevRoNDc34z//+Q+2b9+Oo48+Gn//+9/Ru3dvx3Hvv/8+jjzySBx55JGp9Za8Xiu36968eTOOOeYYrFu3DuFwGGPGjMH++++PpqYmrF+/Hu+//z6CwSDq6uoQCnE1HFL8MLOJEEIIIYQQQgghhBDSqbjvvvvw9NNPY8KECYhGo/jPf/6DpUuX4mtf+xqmT5+OlStXZgQyAKTWaAoGg476v/71rzjooIPwjW98w3hOkdXUp08fY6AJAM4991wAwIIFC7Bly5ZUfW1tLX7729/i4IMPxjvvvIP//Oc/GDFiBJYuXZrK5NFl9AwfPhyvv/46TjjhBOzcuRMvvfQSPvvsM0ydOhXvvvsutm3bhpKSEkdW1meffYavvvoKBxxwQEbwJJdxrF+/Hl988QX69+/vGmgCgI8//hg7duzAwIED8atf/Qp33nknmpqa8Nxzz+Hjjz/GOeecg3fffTfj/RFj9jpHjx498O677+KKK65AOBzG3LlzMW/ePBxxxBG4//77sWDBgoxAE2CWynN7rdyuu0+fPli6dCmqqqowZMgQLF68GE899RTefvttNDU14Uc/+hGef/55BppIu4GZTYQQQgghhBBCCCGEEOKDefPm4ZhjjsFrr72GE088EQCwcOFCjB07Fo888gjOP//8Ao+w/fP444/jggsuwMSJE/G3v/2t0MMhhPiEmU2EEEIIIYQQQgghhBDig9GjR2PAgAGYNm0aXnrpJTz44IM47bTTcNFFFzHQlCeyWduJEFI8MNhECCGEEEIIIYQQQgghPggGg3j22WcRiURw5plnYtasWbj++utx3333FXpoHYb33nsPAINNhLQ3KKNHCCGEEEIIIYQQQgghpOA0NzejsrIS9fX1qKurQ7du3Qo9JEKIT5jZRAghhBQZb731Fk4//XT07dsXgUAAzz33nOcxb7zxBkaMGIFIJIKDDz4YDz30UKuPkxBCCCEkH9D2IYQQIigpKcGuXbuQSCQYaCKkncFgEyGEEFJk7NmzB8OGDcM999zjq/26detw2mmn4YQTTsCyZctw5ZVX4uKLL8bLL7/cyiMlhBBCCGk5tH0IIYQQQto/lNEjhBBCiphAIIBnn30WZ555prHNNddcg7lz52LlypWpuvPOOw87duzASy+91AajJIQQQgjJD7R9CCGEEELaJ6FCD4AQQggpFhobGxGLxVqlb8uyEAgEHHWRSASRSKTFfc+fPx8nn3yyo27ChAm48sorW9w3IYQQQjom7dXuAWj7dHSam5uxadMmdO/ePeM+IoQQQkj+sSwLu3btQt++fVFSkrsYHoNNhBBCCGyHy37l5djdSv1369YNu3c7e7/xxhtRU1PT4r63bNmCXr16Oep69eqFnTt3oqGhAeXl5S0+ByGEEEI6Du3Z7gFo+3R0Nm3ahP79+xd6GIQQQkinY8OGDejXr1/OxzPYRAghhACIxWLYDWAagPzMuU0TBfC73buxYcMGVFRUpOrzNbuXEEIIISQbaPeQYqZ79+4AkHEPEUIIIaR12LlzJ/r375/6Ds4VBpsIIYQQia4AyvLcp/iyraioaJUfzL1798bWrVsddVu3bkVFRQVn9hJCCCHESHu0ewDaPh0dIZ3XmvcQIYQQQjJpqXxt7gJ8hBBCCCkKxo4di9dee81R9+qrr2Ls2LEFGhEhhBBCSOtB24cQQgghpPhgsIkQQgiRKG2lRzbs3r0by5Ytw7JlywAA69atw7Jly7B+/XoAwIwZMzBp0qRU+0svvRSffvoprr76aqxevRqzZ8/GE088gWnTpmX/AhBCCCGk01AMdg9A26eYeeutt3D66aejb9++CAQCeO655zyPeeONNzBixAhEIhEcfPDBeOihh1p9nIQQQggpPAw2EUIIIUXGe++9h+HDh2P48OEAgOnTp2P48OGorq4GAGzevDnlfAGAAQMGYO7cuXj11VcxbNgw3HbbbfjTn/6ECRMmFGT8hBBCCCHZQNuneNmzZw+GDRuGe+65x1f7devW4bTTTsMJJ5yAZcuW4corr8TFF1+Ml19+uZVHSgghhJBCE7Asyyr0IAghhJBCs3PnTlRWVuJm5H/tgkYA1wOoq6uj7jwhhBBCCg7tHpILgUAAzz77LM4880xjm2uuuQZz587FypUrU3XnnXceduzYgZdeesnXecT9yXuIEEIIaRvy9d0b8m5CCCGEdB5CyE3+xY14nvsjhBBCCMkHtHtIvpk/fz5OPvlkR92ECRNw5ZVXGo+JRqOIRqOp7Z07d7bW8AghhBDSilBGjxBCCCGEEEIIIYS0mC1btqBXr16Oul69emHnzp1oaGjQHjNr1ixUVlamHv3792+LoRJCCCEkzzDYRAghhEiEWulBCCGEEFJs0O4hxcCMGTNQV1eXemzYsKHQQyKEEEJIDtAOJIQQQgghhBBCCCEtpnfv3ti6daujbuvWraioqEB5ebn2mEgkgkgk0hbDI4QQQkgrwmATIYQQIlEKrl1ACCGEkM4B7R6Sb8aOHYt//vOfjrpXX30VY8eOLdCICCGEENJWUEaPEEIIIYQQQgghhGSwe/duLFu2DMuWLQMArFu3DsuWLcP69esB2BJ4kyZNSrW/9NJL8emnn+Lqq6/G6tWrMXv2bDzxxBOYNm1aIYZPCCGEkDaEmU2EEEKIRGusNcAvW0IIIYQUI7R7iBfvvfceTjjhhNT29OnTAQCTJ0/GQw89hM2bN6cCTwAwYMAAzJ07F9OmTcPvf/979OvXD3/6058wYcKENh87IYQQQtoW2oGEEEIIIYQQQgghJIPjjz8elmUZ9z/00EPaY5YuXdqKoyKEEEJIMUIZPUIIIUQihPT6Bfl6cGYHaa9MnDgRgUAgNYvZxO23345AIIDx48e36niefPJJBAIBBAIBHHjggcZ2S5cuRSAQQGVlpauDrCOze/duhEIhVFRUIJFItPn56+vrEQqF0LVr15zP39TUhIcffhinnXYa+vbti0gkgsrKShx88MH49re/jVtvvRUbNmwoirFmS6HfHy+WLl2KYDCIyy+/vNBDyQtr1qzBXXfdhSlTpuDwww9HKBRCIBDATTfdZDymrq4OPXr0wOjRozv0/xHaPYQQQgghJF8w2JQjxeZ8Ufn0009RVlaGQCCAMWPGtOm5vWjrH/SF/jHf0uttK0dLPsaaC4V+f7ygs6XzOFsEoVZ6ENIeWbx4MQDg6KOP9tXuqKOOapPxAMBnn32G9957z7Xd8OHDEQgEWnVMxcq7776LRCKBMWPGIBgMtvn5ly5dikQigeHDh+d0/rVr12LEiBGYMmUK3njjDQwcOBDf/e53cdJJJyEUCuHll1/GtddeizVr1hR8rDqEfdO9e3etfVPo98eLyy+/HOXl5aiqqir0UPLCvffeiyuuuAIPP/wwVq5c6cvmrKysxIwZM7Bw4UL85S9/aYNRFgbaPYQQQgghJF/QDsyRYnO+qEybNg3RaBQAsGLFCjQ3N6OkpDhii/n8Qb97927stddeKC8vx44dO7T9FfrHfEuud+3atTjrrLOwcuVKdOnSBcOHD8f48eMRi8WwatUqvPzyy3j55Zdx1FFHoX///gUdq4728P540RGdLb///e+zOkY4W6666ir85S9/weTJk1tpdISQYqKurg6ffvopgOKxd8R5hgwZglWrVuGpp57Sjq1Q9lcxcfTRR+PDDz/E3nvvXZDzL1q0CAAwcuTIrI/dvn07TjjhBGzcuBHTpk3DDTfcgH322cfR5tNPP8X999+fU//5HKuJhQsXIpFIYNSoUVr7ptDvjxtPPfUU3nnnHVx11VXo2bNnoYeTF4YOHYpf/OIXGD58OEaMGIFbbrkFf/3rXz2Pu+yyy/DrX/8aM2bMwHnnnYdIJNIGoyWEEEIIIaR9wmBTDhSj80Xm5ZdfxgsvvIBevXrhq6++Qn19PT766CMMGjSozcbgRj5/0Hv9kAcK/2M+1+tta0dLS8Zqoj28P27Q2ZKmMzlbhARMvvskpL2xdOlSWJaFiooKHHLIIcZ2u3btwkcffQSg9e2dJUuWAABmzpyJc845B08//TR+9atfZbQT9teIESNadTzFTGVlJSorKwt2fmFTeNnKOn77299i48aNOPXUU3H77bdr2wwcOBC33npri8YoaMlYTcyfPx8AMHbsWO3+Qr8/bvzud78DAFx00UUFHkn+uPjiix3bfifhlZWV4YILLsDvf/97zJkzB5MmTWqN4RUU2j2EEEIIISRfFEeqSzujGJ0vgqamJlx55ZUAgFmzZuHrX/86AGDZsmVtcn4/5PMHvdcPecD+MT9o0CD06tWrxefLhVyvV3W0qIEmIO1oyZezIt/Olvbw/rjRUZ0tv/nNb3DBBRdg0KBBWTtbNm/ejDlz5rTyKAkhxYAI7IwYMcJVik7YRV27dsWhhx7aauP573//i//9738Ih8M4/fTTMXz4cHz88cdYvny5o108HseKFSsAOO2vJUuWIBAIYNiwYdr+Y7EYysrKEA6HU9nhAGBZFvbaay8EAgFs374dTzzxBI4//nhUVlZi7733xplnnol169YBAJqbm3H//fdjzJgx6N69O/r06YOLLroI27dvN17X//73P8yaNQtjxoxBZWUlysrKcNhhh+HWW29FPB7PaK+O55FHHsH48eNRWVmJQCCAxYsXp9qUlJSgrq4uo4/6+nrMnj0bJ598Mvbbbz9EIhH069cP3/72t/HAAw842n700Ue45ZZbcNJJJ+HAAw9EeXk5unXrhpEjR2L27Nlobm7WXpeQOMxlAsurr74KAPjGN76R9bEAsHnzZlx33XUYOnQounfvjq5du2Ls2LF47LHHshprLvfMX//6VwQCAdxwww0AgJtvvjm1zlggEMBzzz3n+f5kew3Nzc3o3r07gsEgdu/ejblz5+L//u//sN9++6F79+4YO3YsXnvtNV+v3dKlSzFv3jyMGTNG+3l+7rnnEAgEXAO5u3btQp8+fVBaWopVq1b5Om8xM2XKFADAPffcU9iBEEIIaTHz5gHPPgvkaSUCQtqMRAJ4+23gj38END8RCCkaGGzKgWJzvsjceeedWL16NUaNGoUpU6akfhybgk0t+XGaL+fDiy++iEAggMMOO8x4Xf/73//Qs2dPlJeX4+OPP/b1Qx5Au3a2tNTRAuTH2dJajhbA+/3Jdvx0trQuncXZku9FsltjxjAhbYGwd7wmzMjrI7WmZK84z9ChQxEOh3H22WcDsLNQZT744AM0NjaiW7duqUk3QPo7zjShYvny5YhGoxgyZIgje/OTTz5BXV0d9t9/f1xxxRWYMmUKysvLcfLJJwMAnn/+eXz729/Gjh07cPzxx+Oaa65Br169cOKJJ2LHjh148MEHM7IqBG+99RYGDx6M6667Dlu2bMEJJ5yA4447Dp999hmuvfZanHXWWRlr5Ynx9O3bFxdffDGmTJmCkpISnHbaaRg1ahQOP/zwVJuDDjooY0LK8uXLMWzYMEydOhVLlizBqFGjcM4552DAgAH497//jT//+c+O9tdddx1uuOEGbNmyBYMHD8Z3vvMdDB06FIsXL8bUqVPxi1/8IuO66urqsHbtWlRWVrpOzDLR0NCQen2yXc/x73//O4YMGYJZs2ahubkZp5xyCkaPHo333nsP3//+93HNNdf4Hmsu90yXLl0wefJklJWVAbDXeZ08eXLqMWrUKNf3J5dr+Oijj7B7924MGDAAU6dOxVlnnYWGhgacdNJJ6NOnDxYsWIDTTjsNH374oefrJ2w0cX+rCHvwww8/NL43N998M7Zs2YKf/OQnGDJkiOc5i50jjzwS++23HxYuXIjNmzcXejh5h3YPIaQzcf/9wFlnAR14KT7SQQkEgG99C/jRj4DkPDdCihOLZM33v/99C4D185//3LXd7bffbgGwjj322DYZ15YtW6yKigorEAhY7777rmVZljVr1iwLgDVhwgTtMR9++KEFwDrooIOsSZMmWeFw2DrxxBOtiRMnWocccogFwIpEItaqVasyjj377LOtQCBgDRkyxPr2t79tTZw40Ro9erQVCAQsANa0adMyjtmxY4cVCASsyspKq7m52bIsy6qrq7OCwaAVCASs7du3a8d54YUXWgCs2tpay7Is66mnnrImT55slZWVWQCsiRMnWpMnT049Nm7caFmWZa1du9YCYB188MEZfb7//vvWwQcfbAGw9t57b+vUU0+1LrjgAuvYY4+1SktLrWOOOaZVrtcvQ4cOtQBYp5xyihWPx7M61rIs64UXXrD22msvC4A1ePBg69xzz7VOOOEEKxQKWQCsq6++2tdY77//fguA9f/+3//TnmfRokUWAGvYsGGpuny8P9mO37Jadj+rVFdXWwCsG264Qbv/008/tQBYZWVlxvfnmmuusQBYl19+uef5CsXkyZMdny0v9ttvPwuAtWnTplYeWdtTV1dnAbD+Blgv5PnxN8ACYNXV1RX6MgnxzeDBgy0A1uOPP+7aTthFP/vZz1p1PDNmzLAAWBdffLFlWen/+UOGDHG0e+CBB7T2149+9CMLgDV79mxt/7Nnz7YAWBdeeKGj/m9/+5uF5Gd43Lhxqe8wy7KsTz75xCovL7cAWIcccoh15plnWjt27EjtX7hwoRUIBKySkhKrvr7e0e/SpUut7t27W6WlpdYf/vAHK5FIpPZt2LDBGjBggAXAevrpp43jGTRokPY7TbT53ve+56hfs2aNtd9++1mBQMCaOXOm1dDQ4Ni/detW65VXXnHUPf/889bmzZszzvHOO+9Y4XDYKi0ttXbt2uXY969//csCYJ100kkZx/nhpz/9aeoaBwwYYF199dXWK6+8knEelVdffdUKh8NWZWWl9dxzzzn2LVy40AqHwxYAa8mSJb7Gmus9U1dXZwUCAauiokJr/5nen1yv4dFHH029XiNHjrT++9//pvbF43Hrm9/8pgXAuvnmm7XXIXPsscdaAKy5c+ca21RWVloArNWrV2fs+/TTT61IJGL16NHD+t///ud5Phlhk2T7eP3117M6j3wuv/bPGWecYQGw/vrXv2Z9rmKFdg8pZsT9yXuI5JtRoywLsKynnir0SAjJniOPtO/fF14o9EhIRyRf371csykHxEzfYluv6dprr8XOnTsxZcoUjBo1CgA8M5vEtXzyySfYZ5998NFHH+FrX/saACCRSOCUU07Bq6++imeffRaDBw92HDtp0iTcfffd6N27t6N+3rx5OOGEE3D33Xdj5syZ6NatW2rfe++9B8uycPTRR6eywioqKjBs2DAsWbIE8+fPxymnnOLo74033sCf//xnDB48GFdffTUA4Oyzz8Y3v/lN/OUvf0FFRQUef/xxbZaZac2Gjz76CCeffDK2bduGmTNn4qqrrkrNQAWAL774Au+//36rXK9fxo8fj5UrV+LFF1/EIYccgnPPPRcnn3wyxo4d6ziHjn/9618455xzUF5ejueeew7f+c53UvsWLVqEY489Fr/+9a9x3nnnYfjw4a5jFa+h6X4X0nvya9zS9yeX8QMtu59V/v3vfwMwSwAOGDAAlZWVqKurw8cff5yR/bRu3Trccccd6NGjB375y1+6nktlypQpePjhh7M6BgBef/11HH/88Vkflw1jx47FCy+8gNdeew0/+MEPWvVchSKE/C9oyC9b0t7Ys2cP1qxZA8B/ZpOu3Zo1a3D11Vfj3//+N8rKynDppZdi5syZWX8n6s4zaNAgDBkyBKtWrcLq1atTa1Oavlu8slTE95l6HeK7pV+/fnj++eex7777pvYNHDgQQ4cOxaJFi9C1a1c8/vjjDnti5MiR6N27NzZv3ozNmzdj4MCBAOzvpEmTJmHXrl149NFHccEFFzjO2a9fP1x//fW4+OKL8eKLL+Kss87KGE+3bt3wwgsvaDOHdFlpzc3NuOCCC/Dll1/ipptuwvXXX59xXM+ePfHNb37TUXfGGWdoX69x48bhsMMOw9KlS7Fp0yZHFllLZXlvueUWbNy4Ec8//zzWrVuHX//61/j1r3+N0tJSnHjiiZg6dSpOP/10xzG7d+/GpEmTEIvF8MILL2DChAmO/SNHjsS5556LRx99FH//+99T9oPbWHO9Z4SUoUkFwZQ1mOs1iP769u2Lv//97w5p4mAwmLJ/tmzZor0OmaVLlwKAq500bNgwvPXWW1ixYkWG/XPVVVchGo3itttuy3o9zmOPPTar9gLVNm8NDjvsMLzwwgtYsmRJh7N/aPcQQjoLlgWIJN8iWdKckKwYNAhYtgxYvRpQTGFCigbagVlSjM4XAFi4cCEefvhhVFRUOBbKPuKIIwAAW7duxZYtWzJ+jLXkx2k+nQ/jx4/HkiVLMG/ePEewKRqN4sc//jECgQDuv/9+hMPh1D6vH/Ly9bVHZ0sujhYg/86W1nK0APr3J9fxy/3R2dJ6dGRnCyEkzbJly9Dc3IzKykocfPDBxnZu61O+//77OP744/G9730Pzz//PBYtWoQZM2bgoIMOSslyZoMsYyw4++yzsWrVKjz11FMp6Vbdd0ssFsPKlSsRDodTtpGKbvIEkLbnpk2b5gg0CXbt2gUAqKqqcgSaAFsudufOnQCA/fbbL1U/Z84crFixAuPGjcsINAkGDBgAANi2bZt2PNOnTzdK1Ols0CeeeAKLFy/G4YcfjhkzZmiP0xGPx/H6669j0aJF2LhxI+rr61PSfuK979Gjh+OYlqzXBNjrOT733HNYu3YtnnnmGfzrX//CvHnzUF9fj5dffhkvv/wyfvGLX+A3v/lN6pi//OUv2Lx5M4477rgM20Eg7mX5NTWNNR/3jOm3gml/rtcg+rviiiu0a2Bu3boVgB3EdGPPnj3Ys2cPgMz3VEbYPytXrsQ555yTqn/rrbfw9NNPY+jQobj00ktdz6Xj4osvNkpOFhrxeojXkhBCSPtj82Zg1y4gGARczFtCihbhnlq9urDjIMQNBpuypBidL5Zl4fLLL4dlWaiurnb8yNx///3Ro0cPfPXVV1i2bBm+/e1vO45tyY/TfDofxo8fjzvuuAPz5s1z1N9888346KOP8P/+3//LWLvIT+ZYe3a25OJoAfLrbGlNR4upTa7jl/ujs6X16AzOlhDyv9YAv2xJe0ME3IcPH+46EWbJkiVobm5G165dU5lFANDU1ISJEyfi/PPPx+zZswEAJ554Il555RU8/vjjWds769evx7Zt2xAKhRzfR2effTZqa2vx9NNP44YbbkAikUhlJsvfS8uXL0csFsOIESMc6zEJ9uzZgw8//BDBYDBjjUIRvBJrRKnHrV27FmVlZTj11FMz9n/00UfYs2cPBgwYgO7du6fqxTpT8+bN85xopE5YEOOZOHGi8RhdYO6JJ54AAFx66aW+19Z6+umn8bOf/QwbN240tunZs2fGd6WwDXINNgkOOeQQXHPNNbjmmmsQi8Xw6quv4uqrr8aqVatw22234dJLL8VBBx0EIL3W0I9//GNjf2ItqH322cdzrC25Z7wm6ujen5Zcg1AwOPfcc7XHiP1HHnmksV8AjvUz5ftVRfSzYsWKVF1zczOuvPJKAMAdd9yBYDDoeq72RkVFBQBg+/btBR5J/qHdQwjpLAgH/cCBgOarnZCiR/zc8rEMJyEFg3ZglhSb8wUAHnroISxcuBCHHnoorrjiioz9RxxxBF5//XVtsCnXH6f5dj584xvfQCAQwMKFC5FIJBAMBrFq1Srceuut2G+//TICKoD3D3mgYzhbsnG0APl1trSmowXQvz+5jh+gs6Ut6MjOFgHlZAix//8D7tmdAPDmm28CAI455hjHd+qjjz6Kzz77DLW1tY72/fv3x/z587Mej5hMMGTIEEf20LBhw3DQQQdh2bJl+OSTT1BfX4+GhgaUl5c7xu4lCbtgwQIkEgkcdthh6NKlS6p+3bp12L59O3r37p2SZZVZunQpEokEjj766IysJvm86sQLYU+ee+65jvPpOPPMMzPG06dPHwwZMkTbXrQZMGCAI1AlvnP9Zs/OmTMH559/PioqKnDzzTfjlFNOwcCBA9G9e3eUlJTgiSeewMSJEzOu7YsvvsD69evRs2dPHHDAAb7O5YdwOIzTTjsN++67L8aMGQPLsrBixYqUDSTuWTWAIyO+r8X3t9tYc71n5GN1E25M70+u1/DJJ59gx44d6NmzZ0qmUcWvtPdee+2VKu/atSv1na+is3/+/Oc/Y+nSpfjOd76Dk046yfU8Jv70pz/h7bffzvq4a6+91vF7qzUQtmG22ertAdo9hJDOggg2UUKPtFfEvbt6tS0LmaM4FiGtCu3ALCk258vOnTtT2Tn19fU44YQTMtqsXbsWQOa6Tbn+OG0N58O+++6LwYMHY9WqVVi+fDmOPPJI/PjHP0YsFsNtt92WEVQwjU2mIzpbvBwtQH6dLa3laAHM708u4wfobAHobCGE5I8vvvgCAFBeXm5sY1kWHn/8cQCZUrMPPfQQTj31VFRWViIej6fq9+zZg9LS7OfQu/3/Pvvss/HrX/8aTz/9NHr27AnADkLJwX55spCOOXPmADBn6Zq+B8V+06QS0zqf4vX905/+ZPyOcTtftlnD8jndJlHIzJgxA5Zl4ZlnnsGJJ56Ysf+RRx4BkHltLV2vyYv+/funyvIalkKuUDc5BrCv/9///je6dOmSuh63seZ6z9TV1eGTTz4xqiC4vYe5XIPXPfjZZ59h27ZtOPDAA12ztQGgS5cu6Nq1K/bs2YOvvvrKeG8edthhCIVC+OSTT9DQ0IB4PI4bbrgBkUgEt912m+s53Hj77bdzWrNyypQprW7/fPXVVwCgzZwnhBDSPmCwibR3DjnEDjBt3w58+SWQ/OlDSFHBYFOWFJvz5Ze//GVKzmrDhg3YsGGDsa0abMr1x2lrOR/Gjx+PVatWYd68eVi0aBHefvttnHTSSfjhD3+Y0dbrh7x8fR3R2WJytAD5dba0lqMFML8/uYxf7o/OFjpbWkop8i8nk+/+CGltRNBGtR1kHnzwQaxevRp7772347u6vr4e8+bNQ1NTk9a2kddm9ItJdgxIB5ueeuopjBkzBkDmd8v69esBQLvm0rJly1Lf5dkGm7yyeE3fdZWVlaivr8fKlSsxbtw47bFu/bllTIs26rXstddeaGhowKpVq1LrQZnYuXMn1q1bB0A/OeeVV17B3LlzAZjXeswlq9uyLE9ZQZEB3b17d8dr16dPH3z66adYu3YtDjzwwIzjpk+fjmg0iiuuuCL1ve421lzvmQ8++ACWZeGII47QXovp/cn1GkwBTYG4Rq+JNoIRI0bgP//5j+t9EolEMGjQIKxcuTK1ZtqWLVtwzTXXOCZAZctDDz2Ehx56KOfjW5OVK1cC8P86tido9xBCOgsMNpH2Tnk5cOCBwLp19v3MYBMpRvxpiJEU+XC+PPPMMygtLXU8nnrqqayzX1avXo277roLpaWlWL16NSzL0j7Ej9q1a9eivr4+dXwuP05b0/kwfvx4AMCzzz6La665BpFIBPfee6+2rdcPecDd2QIAq1at0h4nUwhni1gHyg2TowWwHRVAOqNNRTgqLr74Yk9nS2s5WgDz+5PL+IHWcbYA7veJcLY0Nzdj1apVuOWWW7BlyxZceeWVLXa2mD7Pbo/jjz8+53P6pSM7Wwghab773e8CAP7973/j7rvvRnNzc2pfPB7HH/7wB1x22WUAgDvvvNPx/3jFihVoamrCI488gkWLFqUeb775JgKBgGvmqgm3bJCRI0eif//+WLRoEf7xj38AyPxuEQHy559/3vE9u2DBAnznO99BNBrV9i++W0zf5W7f9ZZlpSZtqP2K9Z2mTp2qnSi0Y8cOPPDAA6kJMup4/EjUquf81re+BQC44YYbsGXLFse+hoYGPPHEE4jFYgBs+0JMZnnhhRccbV988UWcd955qXvCNNkml2DT9ddfj0svvRQffPBBxr6Ghgbcfffd+PnPfw4A+NWvfuXIqj799NMB2Ot9inUXxXFTp07Fo48+iqFDhzrUBdzGmus909TUBAAOm1vG9P7keg1+71G/k5+ESoKX4oLI7n7hhRfwu9/9Dr1798b111/v6xztEfF66CaeEUIIaR8w2EQ6ArKUHiFFiUWy4p///KcFwAJg3XXXXVYikUjta2pqsu6//36rrKzMAmD99a9/dRy7YMECC4D1yCOPWIsWLUo93nzzTSsQCFjXX399VmOZMGGCBcC68sorXdvV19dbJSUlFgBr/vz5qfpvfvObFgDrH//4h/a4a6+91gJgzZo1K1XX3NxsdevWzQJgPfnkk472//znP62999479fps3LjRsf+0005zPd/nn3+eOhaA9ctf/tJ4TW+88YYFwDrqqKOMbb71rW9ZAKyXX37ZUT958mQLgHXkkUdamzdvduyrr6+35syZY0Wj0Va/XhMzZsywfvzjH1srV67M2FdfX2/dddddqXvsnnvuyWjzs5/9zAJgHXfccdbu3bsdx/70pz+1AFhDhw616urqPMc6ZcoUC4D1gx/8wGpubk7Vz58/3zrggANS99Vbb73lOK4l708u47es3O5nN6qrqy0Anp/LH/zgBxYAq7q62opEIlbv3r2tnTt3+jpHMSA+D7W1tb7a9+jRwwJgbdq0qZVH1vbU1dVZAKzXAGtBnh+vJf9PqPctIcXMj3/849R3XN++fa3jjz/eOu6441LffeFw2LrzzjszjpszZ44FwNqwYYOj/h//+IcFwHrzzTezGseGDRssAFYwGLT27NmjbSO+O8Rj2bJljv0vvvhiat/Xv/516/TTT7eGDRtmlZSUWDfeeKPVtWtXKxAIZPz/Fv/ztm7dmnHOnTt3WiUlJVa3bt0c9qBg7dq1FgBr4MCBGfs2bdpkDRgwIPU6jh8/3jr//POtc845xxo1apQViUSsLl26WE1NTb7Ho7bZtm2bo379+vVW3759LQBW165drRNPPNGaOHGiNW7cOKt79+5Wv379HO1nzJhhAbBKSkqsE0880TrvvPOsoUOHWqFQyLruuussAFafPn0yzt+zZ0/PMZr4xje+kXqfBgwYYJ1xxhnW+eefbx133HHWPvvsYwGwysrKrN///vcZx27bts066KCDUuM688wzrTPOOCN1vx599NEZdp/bWHO9Z7Zv354658iRI60f/vCH1uTJk63XX3/dsizz+5PrNXjdEyeffLIFwHrllVdcX3vBkiVLLADWqFGjXNv95je/SX0uAVgPPvigr/4LxeLFi63Ro0enHvvuu68FwOrXr5+jXmff+H1N2hu0e0gxI+5P3kMkX+zaZVmA/dB8BRPSbpg2zb6Pp00r9EhIRyNf370MNuVAMThfnnvuOQuAte+++1rbt2/3bC9+uN57772pulx/nLam82HgwIEWAOvQQw9NBXx0eP2Ql6+vvTlbWuJosaz8Oltay9FiWeb3J5fxy/3R2eIOnS1m6HQhJJOnn37amjBhgtWjRw8rGAxaFRUV1pFHHmlNnz7d+uijj7THPProo9qg9MSJE62DDjrIMXnBD8LmGTJkiLHNW2+9lfq+ikQiGUEay7Ksv/71r9bhhx9ulZeXW7169bLOOecca968edaHH36Y+p6T+e9//2sBsPr3768955tvvmkBsL7xjW9o9//tb3+zAFjf+973tPt37NhhVVVVWUceeaTVtWtXq7S01Ordu7c1fPhw6/LLL7deffXVrMYjtznggAO0+7du3WpNmzbNOvTQQ1MBrQEDBlhnn3229cwzzzjaxuNx67e//a319a9/3YpEItb+++9vTZo0yVqxYoX1zDPPWACs008/3XHMZ5995jlGNz788EPr97//vXXGGWdYQ4YMsfbZZx8rFApZ++yzjzVmzBjrhhtusD777DPj8du2bbOuuOIK62tf+5pVWlpq7bvvvtZxxx1n3X///VY8Hs96rNneM4J33nnHOumkk1K2iZiY4/X+ZHsNfu4JYTt+9dVXxjYq48aNswBYq1atMrZ59dVXU9d29NFHZ/25bmtef/11R0Da9Fi3bl3GsVdccYUFwHr44YfbfuCtCO0eUsww2ETyzeLFtoN+v/0KPRJCWsb999v38imnFHokpKPBYFOBKaTzpbGxMRWUmT17tq9jzjjjDAuA9eMf/9iyrJb9OG0t50NjY6N1wAEHWACsN954w/OaTD/k5etrj86WljpaLCu/zpZ8O1osy/v9yWb8cn90tnhDZ4sZ8cX6JmAtzvPjTTpdSCfinXfesR2Yr72Wqnv33XetkpIS67HHHivgyAghfnjyySctANb06dMLPZSC09DQYO27775Wnz59rMbGxkIPJ6/Q7iHFDINNJN88+qjtoDfMESKk3fDmm/a9PGBAoUdCOhr5+u4NWJaPBWJIXpg3bx6OOeYYvPbaaym974ULF2Ls2LF45JFHcP755xd4hIVl5syZuPHGG3HhhRfiwQcfLPRwCMFTTz2Fc889F9OnT8dtt91W6OEUlMbGRvTv3x+lpaVYt24dIpFIoYeUd3bu3InKykq8CaBbnvveDeA4AHV1dY61bQjpiCQSCRxyyCHo3r07br31VmzatAnXXHMNvvvd7+IPf/hDoYdHCPHBsccei2XLluGTTz5JrV/VGfnNb36Dq6++Gg899BAmT55c6OHkFdo9pJgR9yfvIZIvqquB2lrgkksAmqOkPfPFF0CvXkAgAOzZA5SXF3pEpKOQr+/ekjyOiXgwevRoDBgwANOmTcNLL72EBx98EKeddhouuuiiTh9oeuutt3DzzTejb9++nd6pT4qHc845B8cccwzuv/9+bN26tdDDKSh33XUXtm3bhlmzZnXIQJNMqJUehHQWgsEgnn32WUQiEZx55pmYNWsWrr/+etx3332FHhohxCd33XUXGhoaUFtbW+ihFIy6ujr86le/wqhRozBp0qRCD6fVoN1DCOkMfPih/TxoUGHHQUhL2W8/YO+9AcsC1q4t9GgIyYSZTW3M+++/j0suuQTLly9H//79MXXqVFxxxRUoKel8cb+VK1fijjvuwNatW/HSSy+hpKQE//rXv/CNb3yj0EMjJMXSpUtx9NFH4yc/+QnuvvvuQg+nINTV1WHgwIE4+OCDsWDBAgQCgUIPqVUQszjeQevM8D0GnOFLCCGEkOKAdg8pZpjZRPJJTU0N7r33p/jii56YOxc49dT0vtraWiQSCdTU1BRsfIS4UVNTg2AwiKqqqlTduHHA/PnA9773NAYPXsH7l+SFfH33ctJRGzNs2DAsXLiw0MMoCl588UU88MAD6N69O4455hjU1NQw0ESKjuHDhyORSBR6GAWlsrISX331VaGH0WaUJh/57pMQQgghpNig3UMI6egEAiF88UUlAGdmU21tLaqrqzFz5swCjYwQb4LBIKqrqwEgFXAaNMgONj3xxPuYOZPfuqS4YLCJFIyrrroKV111VaGHQQghDlpD/oVftoQQQggpRmj3EEI6Oj/4wQ2wEz8a8Ne/3oYbb7zBEWiSM0YIKTbE/SkHnDZu/BeAk3H44d9DVdXQAo6OkEwKqt12zz334MADD0RZWRlGjx7NjB9CCCGEdFho9xBCCCGEENK2rF5tP/fqtRM1NVWIRCIMNJF2RVVVFWbOnInq6mpEIhG88srvAQChEANNpPgo2KSjOXPmYPr06bjvvvswevRo3HHHHZgwYQLWrFmDnj17uh7b3NyMTZs2oXv37h127RBCCCFOLMvCrl270Ldv31Zd5y6E/Mu/cIYvaYndA9D2IYSQzgbtHkIIyQ8i2HTccb3w3HNhxGIxhMNhBppIu6Kqqgo33XQTYrEYSks/RVMTsGYN0NwMtKKZQEjWFMwOvP3223HJJZfgwgsvBADcd999mDt3Lh588EFce+21rsdu2rQJ/fv3b4thEkIIKTI2bNiAfv36FXoYhGRFS+wegLYPIYR0Vmj3EEJIyxDBpi++eCsVaIrFYqitrWXAibQbamtrpft3DYLBBOrrg/j8c+CAAwo9OkLSFCTYFIvFsHjxYsyYMSNVV1JSgpNPPhnz58/PaB+NRhGNRlPblmUBsA3vioqK1h8wIYSQgrNz5070798f3bt3b9XzcKFskm+ytXsA2j6EENLZod1DCCH5QQSb3njj3pR0nlizCQADTqToUdcYs7dXAzgMq1cz2ESKi4IEm7Zt24ZEIoFevXo56nv16oXV4ltAYtasWfjlL3+ZUV9RUUGHCyGEdDIoIUbaG9naPQBtH0IIITa0ewghpGUsWbIHQFf85CcnoqrqEgDpABMDTqTYUQNNgH2//u1vH2LVKuD3v38J3/rWtws8SkLStAtVxxkzZqCuri712LBhQ6GHRAghpIMSaqUHIdlA24cQQkhbQLuHENKR2bYNqK/vCgD4zW8uceyrqqrCzJkzkUgkCjE0QnyRSCQcgSbBmWcOBgBs3dqjEMMixEhB7MB9990XwWAQW7duddRv3boVvXv3zmgfiUQQiUTaaniEEEIIIXkjW7sHoO1DCCGEEEJIS1mzxn4+4ACga9fM/cxoIsVOTU2Ntn7QIPu5e/eRbTcYQnxQkMymcDiMo446Cq+99lqqrrm5Ga+99hrGjh1biCERQgghAIBQECgN5fcRChb6qkghod1DCCGkWKHdQwjpyHz4of0sHPOEdBTEPW1QZSekYBQsw3369OmYPHkyjj76aIwaNQp33HEH9uzZgwsvvLBQQyKEEEIQCgGhPC+PELIAUJ2hU0O7hxBCSDFCu4cQ0pERjngGm0hH49BD7ectW4AdO4C99irkaAhJU7Bg08SJE/Hll1+iuroaW7ZswZFHHomXXnopY/FsQgghhJD2Du0eQgghhBBC2hYGm0hHpaIC6NsX2LTJloscPbrQIyLEpqBrd1522WW47LLLCjkEQgghxEFpECjN8wzfUiu//ZH2Ce0eQgghxQbtHkJIR4YyeqQjM2iQHWz68EMGm0jxUJA1mwghhBBCCCGEEEIIIaQ1qK8H1q2zy4cdVtixENIaiPv6gw8KOw5CZAqa2UQIIYQUG622dgEhhBBCSJFBu4cQ0lH58EPAsoB99wV69iz0aAjJPww2kWKEmU2EEEIIIYQQQgghhJAOw8qV9vPQoYUdByGthQg2iXudkGKAmU2EEEKIRGkQKM3zVIzS5vz2RwghhBCSD2j3EEI6KiLbgxJ6pKMi7u0NG4CdO4GKisKOhxCAmU2EEEIIIYQQQgghhJAOBINNpKOz995A3752edWqwo6FEAGDTYQQQohMsJUehBBCCCHFBu0eQkgHhcEm0hmglB4pNiijRwghhMiEkP+pGJSTIYQQQkgxQruHENIB2bUL+Owzu8xgE+nIHHYY8Oqr6eAqIYWGmU2EEEIIIYQQQgghhJAOgZAU690b6NGjsGMhpDUZOtR+ZrCJFAvMbCKEEEJkOMOXEEIIIZ0F2j2EkA4IJfRIZ0Hc4ww2kWKBmU2EEEIIIYQQQgghhJAOgXC8i6wPQjoqQ4bYz5s2Adu3F3YshAAMNhFCCCFOQq30IIQQQggpNmj3EEI6ICtX2s/MbCIdnYoKoH9/u8zsJlIMMNhECCGEEEIIIYQQQgjpEFBGj3QmuG4TKSYYbCKEEEJkSgAE8/zgty0hhBBCihHaPYSQDsaOHcDGjXZZSIwR0pERQVWR0UdIIaEZSAghhBBCCCGEEEIIaff8/OcPAAD69QP22su5r7a2FjU1NW0+JkLyRU1NDWprax11Itg0d+463t+k4DDYRAghhMhw7QJCCCGEdBZo9xBCOhjbtvUCAJSVfeyor62tRXV1NYLBYCGGRUheCAaDqK6udgScRLBp3bouvL9JwaEZSAghhMiEYEvA5JNAnvsjhBBCCMkHtHsIIR2MAw/8PwDAxx8/j9raelRVVaUCTTNnzkRVVVWBR0hI7oj7t7q6OrX9wgu/AnAtgF649FLe36SwMNhECCGEEEIIIYQQQghp93zwgf185pmHoLr6O7jpppsQi8UYaCIdBjngJO7vvff+MbZv3xsffAAcf3xhx0c6N5TRI4QQQmTyvUi2eBBCCCGEFBu0ewghHQwRbJox4wyEw2HEYjGEw2EGmkiHoqqqynF/H3PM3gDS9z8hhYLBJkIIIYQQQgghhBBCSLvmq6+ALVvs8gsv/CrliI/FYo41bghp79TW1jru7x073gHAYBMpPAw2EUIIITJcKJsQQgghnQXaPYSQDoRwtO+11w7cfPMMzJw5E9FoFDNnzkR1dTUDTqRDIK9BJu7vt9++FwCwcmWBB0c6PTQDCSGEEEIIIYQQQggh7RoRbNqx423HGk3yGjfyNiHtDTnQJN/fmzf/EffeC7z3Xj0sqwsCgQIPlHRaGGwihBBCZILgtyMhhBBCOge0ewghHQgRbDr22H0yAkpiO5FItPWwCMkbiUTCEWgS3HbbJbjvvmY0NHTB1q1A794FGiDp9NCsJIQQQgghhBBCCCGEtGuEhNgll4zT7mdGE2nv1NTUaOvLy4GDDirBxx/bnwMGm0ih4JpNhBBCiEywlR6EEEIIIcUG7R5CSAdCZDYNHVrYcRBSCMR9Lz4HhBQCBpsIIYQQGS6UTQghhJDOAu0eQkgHYcsWYNs2oKQEGDSo0KMhpO0RwaYVKwo7DtK5YbCJEEIIIYQQQgghhBDSblm+3H4+5BCgS5fCjoWQQnDEEfaz+CwQUgg454gQQgiR4YxcQgghhHQWaPcQQjoI779vPwuHOyGdDXHvr1wJJBJAkLK2pAAws4kQQgghhBBCCCGEENJuEdkcw4YVdhyEFIqDDwbKy4GGBuDjjws9GtJZ4RwmQtqAQKBGU1vq48hcPqJxn+2aMmosqyaH8xHSweAMX0IIaTGBwK2aWj+2T2uis32uKcA4CCkiaPcQQjoIzGwinZ1gEDj8cGDhQvvzcOihhR4R6YzQrCSkTZCdK24fu3w4YXR9ZDpX0uPwG5wihBBCCPGLao/4+dnRUjtIZ++oY6DdQwghhHQ0YjHgww/tMjObSGfmiCPsYNPy5cD3vlfo0ZDOCINNhLQJ5cln00eutWf6ivObnDB0vBCSogRAvrWNm/PcHyGEFD3lynZrT7aRz+kWdKLNQ4gD2j2EkA7Ahx8C8Tiw115A//6FHg0hhUMEW0WmHyFtDYNNhPgkLYVnylLSOUpCyrPJmVIcH8VA4M5kSeeIkR038Yx6SvARQgghHYtMKTy3bCXVPtLZNl5BpZbaQ8I+MZ2nKeMcgcAfobNrnP3p9lGCjxBCCCkWZAm9QKCwYyGkkAgZSbGGGSFtTXF4uAlpF5TC3amitoXLfl0bHbl+RE2zduVzyg4TVVKv1NBG3t+kqSekA9AaaxdYee6PEELaBGEPeNkxudhBprYtwWTnqONws1tM9o7f4wlpZ9DuIYR0AIRjnRJ6pLMjgk3r1wPbtwN7713Y8ZDOB4NNhPimu1T2O7NX3Wdq49W+JZgcIuXQO2LiLm3c9hHSQaDThRBCkuhkgL3WoXTL9NbRWlLCbudUbSM3m0gnzcdgE+lA0O4hhHQA5MwmQjoze+0FHHCAHWxasQIYP77QIyKdDQabCAEQCNycLOnk7vw4WLKZ3atr49W+GIlDzoDSS/A1Oeos6/q2GRohhBBCXElL5Omyl3R2jV8Z4WzXp2xruydTSs8bp80jsp8CgXulOrltuo5Se4QQQkjrw8wmQtIMG2YHm95/n8Em0vYw2EQIAPuj4OZYyTbgpNtvauNWnw/cJGW85PLUNrJ8jFu97jzMgiLthCC4UDYhpBOgkwduyQSbbG2c1v4ZYpK809k+bvVinyof7GUHUWaYtBNo9xBC2jlbtgBffAGUlACHHVbo0RBSeI44Avj737luEykMDDYRAsCWSFEDS17OFLdAUj7WbMrXItky5VK5SanXtdetU6D2rauX5WjimnaEEEIIKSzlME+2gc96L0k9tY2MH7vAy1byM5HFFPDxM96W2kEMNhFCCCGtjXCoH3II0KVLYcdCSDEgMvyEvCQhbQm9v6TDo5fIU50mpcgMMuXb4ZLNYtmmY/ySi0RM62PLzahSM5TaI0UG1y4ghLRzbIk8r4ztELKfaOPWRt1nauPWNlvynRmeL/spnfkUCPwRqrQepfZIUUG7hxDSzuF6TYQ4EZ+FlSuBRAII5juDmRAXis8bTUjeEc4Ut+wktwBTts4Wr6BSW8jJ6PrykpHRyc3oZGPUelMbKHUmWRl1PyGEEEJahtskGj8BpkLaOy2ZaON2Pj9yejop4WzsIPU4kw1EqT1CCCEkXzzyyPsAhmnXa6qtrUUikUBNTU1bD4uQNqGmpgbBYBBVVVWpuoMPBsrLgYYG4Gc/uwt33315AUdIOhsMNpFOgJDIMwWS/DpZWrpAdi5Ol3w7XIBMp4aQ1lOPibvsjyv1sgxfk3ScOoNXlZVRpWf4L4kUAUHk/1bk2gWEkDbFTSLPZBO1RE6vJRlOXsf5RbY73NDZQSYbCPAnn6eT3jPZOJTaI0UG7R5CSDtn69beAIBVq/4G4LxUfW1tLaqrqzFz5swCjYyQ1icYDKK6uhoAUgGnYBDYZ5+N2Lhxf3z5ZZ9CDo90QujZJe2aQKAG3oGkUngHldRtP21N7ZDFfrWNjmw/pvKi1bnSWjJ8prGlz5eW2jNLzlhWTSuMjZDi45577sFvfvMbbNmyBcOGDcNdd92FUaNGGdvfcccduPfee7F+/Xrsu+++OOecczBr1iyUlZW14agJIa2JLZEHuGcseWV1e2Uu5TKxJh82j9uxXvixf/zYN3KbbG2q3GwwSu0RYkO7hxCSLdEo8NVXvQAAjz12NQYNWouqqipHoEnO+CCkoyHubzngVFtbi40bewO4BIccck4BR0c6Iww2kXaOGkhyW3/Ab4DJr6OlNWb3ttb6BX4WuJblZHRtspHLU88pjvUrKyOPhzJ7pI0JJh/57jNL5syZg+nTp+O+++7D6NGjcccdd2DChAlYs2YNevbsmdH+sccew7XXXosHH3wQ48aNw0cffYQpU6YgEAjg9ttvz8NFEEKKA5290lKbR67TtXdrm80+lXyuueRl/6hj8SuXB2RmK5nsEjdbya+cMKX1SBtDu4cQ0o5ZvRqIx4G99gKmTbsE1dXVuOmmmxCLxRhoIp0GOeAk7v/TTvsn5s4Fli8v8OBIpyNgWVa7W75z586dqKysRF1dHSoqKgo9HFJAAoHbkVuwKRtZmXwGmrKVlWkLGT1dezc5GXXGrdpenZkr6kzH6WfwOredZcuaDtL5aO3//an+JwEV4Tz3HQMq/4Ksxj569GiMHDkSd999NwCgubkZ/fv3x+WXX45rr702o/1ll12GDz/8EK+99lqq7uc//zneffddvP322/m5EFIwaPsQgZ0BDJiDTSaJvGxtnJbI6rnVqce54SdTyQ+m4I3ueJ1N46feZP/o6po86jPtJsv6iWaspCNDu4d2T2eGdg/xy1/+AkyeDIwfD7z5JhCJRBCLxRAOhxGNRgs9PELaFPn+f/XVKI47DjjgAOCzzwo9MtIeyNd3LzObSLsgUy5PlFWZGJ0zRTeb149zJR/OFj+ze4tRRk8mGzkZnTxNNpJ86sxePYHAndA5ZSivR4qdnTt3OrYjkQgikUhGu1gshsWLF2PGjBmpupKSEpx88smYP3++tu9x48bhkUcewcKFCzFq1Ch8+umn+Oc//4kf/vCH+b0IQkibYMvludkofibaeNk4fuv8BphaK5tb7UPNPHLDZFPobJomTZ0bbnZLNjaRl60Ul2SGxXnt4yivR4oZ2j0dB0ockmJFZG0MG2av0SQc7bFYDLW1tcxsIp0G9f5/6aVfA7ga69cDO3bY2X+EtAUMNpF2Qnny2SQV41XOVVpP7Uduo7bLZqZvscnolSptdcGlJqWsa6NKz7hJ5kE5xkumT4fcjv/OSJ4Qcex8klwou3///o7qG2+8ETU1NRnNt23bhkQigV69ejnqe/XqhdWrV2tPccEFF2Dbtm049thjYVkW4vE4Lr30Ulx33XV5uQRCSFujkwqGYVuXvW2afGPqQ3cMDO3Usnqsbr+ujVtbN7LJePKSD5bbh5R2qryvaqeogSYvOTw/NpA8PkoLkzaAdg/xgBKHpJh5/337ef36v+Ouu9JrNIk1mwAw4EQ6POoaZfb2Nais/BHq6vbC8uV29h8hbQG9s6SdYAo2uQWe/MjK6Jw4bu1bkuWk+7gFNHWtgeqUUdUzZcdHOfQSMHJ9uXKM6qQRx6nbog9dgEhubwo8hTRt1fMQUrxs2LDBkY6sm92bK2+88QZuueUWzJ49G6NHj8bHH3+Mn/3sZ5zRR0i7pRzmSTTqdjZ2jZ8JNV6TafIVaGotO0icX6cWrpvMYsqcApz2jy5AJe/X2UxxH9tiDPKkHlGnC07p9hFSfNDu6RjcfvvtuOSSS3DhhRcCAO677z7MnTsXDz74oFbicN68eTjmmGNwwQUXAAAOPPBAnH/++Xj33XfbdNykcyAym55/fqZjjSZ5DRt5m5COhhpoAuT7/y0AZzDYRNoUemhJUWGWy8um7EdWJpsglO44ILcAU1sFl7xQx9Ha/wq85GGykdqT2zrLlNcjeaEVZ/hWVFT40r7dd999EQwGsXXrVkf91q1b0bt3b+0xVVVV+OEPf4iLL74YAHD44Ydjz549+NGPfoTrr78eJSUlLbsGQkirkJbLU22TEDLtFCDTpjFNvlG3TUEjr4ztbG0fdZ+gEDaQ7pzZ/oNviTyxmuGt9mnaL45VjwHU8QcCf4Te9qG8HvEJ7R7iQltJHEajUcf6OqoEIyE6tmwBvvgCCASacf31Z6GqaoZjv3C4JxKJQgyPkDYhkUg4Ak2Cqqoq/Otf/8Fbb6UzAAlpCxhsIkWGLBmjOkKykcrzkpjJJcCUjdOlFR0qbpNvc0Ydrzwj2CSp50cyRievJ7bFsSapGT/SNaYZvpztS9o34XAYRx11FF577TWceeaZAOyFsl977TVcdtll2mPq6+szHCvBYBAAYFm62f2EkOLAr51jsnnU7Vwn2rhlMLW3STVu6MaoZkL5tX3kep28nWrvyOdzOw6afardQ0jHgXZP8dJWEoezZs3CL3/5y7yOnXR8li2zn7/+9RLU1s7QtmFGE+no6ORpBZdd9g289RawdGnbjYcQBptIkSFLxuiCTX4ymLJxsvhx2ui2gawdKqaJyV7tWorJJ6HWa9vJ16gG4uQfcV4SMbJDRm0X0hyjk81T96lOH7FPldejU4ZkSQmAYCv0mSXTp0/H5MmTcfTRR2PUqFG44447sGfPnpSEyaRJk7D//vtj1qxZAIDTTz8dt99+O4YPH56Sk6mqqsLpp5+ecr4QQooRN7k8NcDkJY3nJbsn2mYjIay2yzGg5GbftJXt47XPOPkGcA5SN4FG1IttWXJYtVnEftXm0dk/8rabzDAn3JAcod1D8kwuEoczZszA9OnTU9s7d+7MWPOLEJUlS+znESMKOw5CihXx2VixAmhqAkpzTdYnJAvyHmyaNWsWnnnmGaxevRrl5eUYN24cbr31Vhx66KGpNo2Njfj5z3+Ov/3tb4hGo5gwYQJmz56dMVuGdFxsuTwgcy0mr6wmwPzDX1duycxg3TaQlZPFNDzdtld9W+LLRyFeBzn7KR8n1snImJwoavaTekxypBnyeg0AQHk9UtRMnDgRX375Jaqrq7FlyxYceeSReOmll1LflevXr3fM6L3hhhsQCARwww03YOPGjdhvv/1w+umn4+abby7UJXQKaPcQv9hyeYC/CTWmSTFy2St722TTuGV467aBFk+wMdX52dcWZGX3APoBq5LAXhLBXvJ8pswnOdPJZbSBe+Gc3GOXKa9HihXaPcVJW0kcRiKRvK7pRToHIluDwSZC9AwcCFRWAnV1wKpVwLBhhR4R6Qzk/afdm2++ialTp2LkyJGIx+O47rrr8K1vfQurVq1C165dAQDTpk3D3Llz8eSTT6KyshKXXXYZzjrrLLzzzjv5Hg4pWvxIxuSazeRndq/XbGBI+304WLxiXqZtU52ffW6YJtzK+0wTceOafbpyCjX7SQSfTOsRqDIxOgk+ub2fcpPSh59ZvZz1SwyIuHc+yVEm/LLLLjPKx7zxxhuO7VAohBtvvBE33nhjbicjOUG7h/gnV7k8v4EkN7sm2wBTC4JLbnaQV322bQD917nJ9lH3mZKBPE0EL9tH16maneQmnSe3VyWHTfLDKia7iRAF2j3EBUockmKGmU2EuBMIAMOHA2+8YQdnGWwibUHeg00vvfSSY/uhhx5Cz549sXjxYowfPx51dXV44IEH8Nhjj+HEE08EAPz5z3/G4MGDsWDBAowZMybfQyJFiR/JGPGcjwCTX2eNh3NF50BRn9Wyn21Tndc4svEZ6Np6SenpHC/qc8Zx4jWUX3tLaqh6eYS0npx5ZMpkcivLUn26oJOpTIhCETldSPFDu4f4RzeZJlubxW/gyU8wSuzP06QaryBTW2Y2ZSujZ7Jp/JQBZNo+gNNYM0kIq7aLV3tT2UteTw1qESJBu4d4QIlDUoxs3w58+qldHj68sGMhpJgZMcIONi1ZAkyZUujRkM5A3oNNKnV1dQCAffbZBwCwePFiNDU14eSTT061GTRoEA444ADMnz9f63SJRqOIRqOp7Z07d7byqElrEAjcDHP2kJd0XsjQxqtsCkJBs+3ibHELKBUy2NRWqDEit3ZaAsiU2/OSl8kFt5SuzDaBwO0Q6yVY1vV5HgshpDOSD7sHoO3TUbC/Z+TJM6p9A+gzjrItq8Eqtc5kf2URaPKyd1pi67SVXaOzZ/zaOKb+jMi2j5tknm6fSTrPb1mdVJPuPy2vF4dlTQchhHhBiUNSjCxbZj8feCCw996FHAkhxY3I/BOZgIS0Nq360665uRlXXnkljjnmGAwdOhQAsGXLFoTDYey1116Otr169cKWLVu0/cyaNQu//OUvW3OopE3wM6NX3JJdlHpTOdcgUw4BplycLflywpjw296Pc0WdLCv6102idavTZT4BcM76tZTGkPb5cZqYkO8rN4cLZ/oSF4LI/0LZnMTZKciX3QPQ9uk4mOwV1U7JZUKNVyaT3L+8z2cWd6HsnXwEfnQ2j1qvU6sT237LqonhaftA2naTEFblgbMpq/J8Ork+QiRo9xAfUOKQFBuU0CPEHyLzb9kyIJEAmGBKWptWDTZNnToVK1euxNtvv92ifmbMmIHp09Mz73bu3In+/fu3dHikzSmHd7CpVGoLQxudw8aPpJ4P54rfAFO+HDCmOrd6v5hiM/mUj8nm2Si1J94jC07pGLUMpJ0vfiTyygE0SMe5eYnaako1IaQjky+7B6Dt03GQbR9oyia7JtsAU47BJb/2TT6CTK1l77iRLwlhXTkbuwiAWWbYrzyw6NCtrB6vW9NSPZYQQghpfzDYRIg/Dj0UKC8H9uwB1q4FBg0q9IhIR6fVfmVcdtll+Mc//oG33noL/fr1S9X37t0bsVgMO3bscMzy3bp1K3r37q3tKxKJIBKJtNZQSZ4JBGqQ6RBRA00Ct1m5fhwuur6g7PMINMmnyza41FrBpnx8MtXZtvkmVz+Fq9SePKtXbqxejJ8Ty46XUqVeoMrKNMC5RkITLKvGx7lIh0L9bOcDrl3Q4cmn3QPQ9mlvBAK3wt1OMcnd6WwcuOz3OtZnoCkbuyaXiTamutayeXRkm9Xdkn79HGOkpS+AnBEu17n1a9tGgcAf4cz0FrbPNS0cE2lX0O4hhLRDli61nxlsIsSdYBA48khg/nw7SMtgE2lt8v7zzrIsXH755Xj22WfxxhtvYMCAAY79Rx11FEpLS/Haa6/h7LPPBgCsWbMG69evx9ixY/M9HFIQdNlLplm7qtPElPEEzf4WZDNlG2DKl/MlGydLSz+dJmdISzObdHJ58kRZnaye2t5Vak+WmpEl79R7Q81WUjHJ5bnJ6JV79EkIIU5o9xAbN3lgr4wkk40EH8fqyh62j1z2Ywd51bmVvfZ51eeKXxtIZ+eEPMryMzR1JvtHOwb5vcr1RZBtmhDsiTNetozIHCeEEELaH3v2AKtX22UGmwjxZsSIdLDpggsKPRrS0cl7sGnq1Kl47LHH8Pzzz6N79+6p9QgqKytRXl6OyspKXHTRRZg+fTr22WcfVFRU4PLLL8fYsWONi2ST9oZw2MuODyGLpwaLvIJQqtPFz1pOLk4WL+eKnwCTX+dLNs4Wr0+i30+qV4wkV6kYtWySknGrd5PW08rsye+pl8RMvdSRH8+QulaCqG+Q9jPo1GkJonUcn6RDQruH2IjvJFUGOBv7xW9wSlfOcnJNLjZOvgJObnXZtvHzv9XUJlcbSJRN9pFXvXHSTba2j0leD0qdyW5yi4iRTgXtHkJIO+P99wHLAvr0AXr1KvRoCCl+RFBWyE8S0prkPdh07733AgCOP/54R/2f//xnTJkyBQDwu9/9DiUlJTj77LMRjUYxYcIEzJ49O99DIW1IIHAz3B0lQGYgSd6n1ptm9MptdW00zhYvR0tbBJu8nC5un8RsPqX58he0tt/BTYJGm+3k9iKIrCedZIxOWkY+iSo5kylBEwjcDrFOlGVd7zIOQkhnhHZP5yUtnaeuy2Syg1TDwEse2DQxRy23YJKN+uwn2ORVp5Z126Y6HW72Qt5/yfjArxSf3/Fp7S0v20fXibCF3GyiEMx2U3rAsrQwJfUIIYQUG1yviZDsEJ+VpUvtQG3AY0l7QlpC3n+iWZbl2aasrAz33HMP7rnnnnyfnhQMXaDJlNmUjbxeSHOMej7AGGTyE2jK1hHj9pxLWbet4veT6uXYyCazKeTSxk1Sz1TvVg4ZyinE+xuCs2PAeW/oJGH8yuWFkM5sko8lnQ7V4ZqvPkmHhHZPZ0YNMuUqFRyS+hPtvbKfAM8JNuLZ7+Qa1U5p6eQav7ZOrv8fvY6TE3rc6nXBI7nej4yeLglJtWXc+tK1d7V9dPiR0cvGrhG2Eunw0O4hhLQzHnhgKYDh2mBTbW0tEokEampq2npYhBQNNTU1CAaDqKqqAgAMGQKEw8COHcDPf34XKiq+4meEtBo0A0mekB0uOmeKKh+jCzap0jNu9SH4DjDlGmTSlU1t4NJGt1+3barzsw9w9x/48Tf4kctzexblXKTzdGWt80W856rMnSiXQ8zE1derniXxLM8k9/IqEUIIIUD6u6jAUsEtsXXUZzdbJpeAk9c+U7uWkI095CWZ1xIZPbfnbMqeto8o67K4/UTLvKSFCSGEkOJiy5Y+AICPP34CwPdS9bW1taiursbMmTMLNDJCioNgMIjq6moAQFVVFcJh4PDDgcWLgd/97g3MnHlkYQdIOjT0npKcScvH6BwogPNHLJR20OyT25jqxbbibPHrZMklwNQWzhfdtkpLPq2yr6G18JNV5Sdg5tVHCp3EjF8tG910ZyErI5Al+Ox9gcCdEJlSlJXpwASTj3z3SQhp99jSqiLApE6O0Tn8TfWqXaOzewBX20duJsp+7Jts9rk9e9X53faqzxc6UyCXc+bST65zVzJst1ylhdWMcEGTS729HQj8EXbgKQ7Lmu5n1KS9QbuHENKOiEaBbdt6AwAef/wXGDx4DaqqqhyBJpHNQUhnRXwG5IATsATACIwfPw1VVccWbnCkw8NgE2kBukCTLvBkWjDblNnkNgPYZUav6KpMqc9HOZtnrzq/2yp+HBnZ7M93ZlO2M3dDhrLcxiRLk0KWmAGcs35NDhRAL6OnthEna0q210n0kQ6JGmDOV5+EkA6AblKMmtEk6v3YNfIxLczkbmkZLm1059Xt8yq71bnV+8XvnBNRp9uvluU2un1u9orJ3vGLah8ByLR9ZGTbW7WDdPZRCP4ymFp7xhIpKLR7CCHtiJUrgXgc6NEDuOKKS1BdXY2bbroJsViMgSZCJOSAk/0Z+X8A7kWXLgw0kdaFZiBpAfKsXq/gkVuwyUtuxoeTxW+ASQ1MeQWV/NSp9bp9XmW3Oj/7gOxkY9Q6v2VTEMor0KTb5xZcMu1zlZiRHXOmKcQiaKTuly9IFwV0a08IIaTzIGSDVbvGa71KeZ9XfY4BpmyDTH72e9Wb6nTbbvv81Hth+mrOZbKNXM524k0uddnaRAD0to+MuLdMQSf5hY5rjvGyjwghhJC2Z8kS+3n4cKC6ugo332wHmsLhMANNhChUVVWlgrGh0ArE47aUnmUBAc3PDULyAX81kKxIS+eVS7XybVSqeZa9EW6ye7pZwj4ymbJxtrg5T7INNvmp91vWbfvdJ7cxOVoKHR9RYzT5/M+TcV0miRkxm1fI4qkDkR0vafkY50lCEE6bQOBeiPWhKKnXwVA/z/nqkxDSLrElVHUTa+RAk4xs3+iCUG71LraP+uy3nMuxbu1NY1LL2ezzU98amDKh8nWsKaMqZNjv1adxzktA2iGeVVk8U73YNmV7pwdlS+rZ9pRlXeEyUNKuoN1DCGlHiGDTiBH2Gk0i0BSLxVBbW8uAEyESzs/IYpSUNOPLL0uwaROw//6FHh3pqNAMJFkiZvTqAkblcDpN/GQ2mbKiNJJmqrPDLZvJT+BJba/b53asqQ1c2qjXoyurZPsp9ZvhZJrZ29LMJtURYpqtGzKU1XaCkI/6FPJsX4Eqnad6a9T1xmRZGVVCTwSuRJ+EEEI6LsJG0WUkmbK6VXtH1yaHTO6W2jteZdNzNkEmP2Xdtle9F7lkNqllXRAobqhT6/3YPybbx48dBNi2r649gLTtI3aqcnlAZqaTjE5OWEW1jwghhJC2RQSb1q17Gk8+mV6jSazZBIABJ0KAjHXM7O0PAByOJUsYbCKtB72kJEt0DhdTUMkt2GRa50njaFGDSibHilu9rp9cy9k851KGj3ov/Dhcsiln85xL2a+cjJ/6Rmn8Dgef6g3yIxMj16vOGTpcOiwlyP/C1iV57o8Q0oboZIO9Akm69qJeDTZ5ZHHn067xsm38BJi8bJlsAkxedo7Xfq+sbd1+vzaPrmxqbyp77fdjKzV6tPcMOql2jWr/mOwgN3vJ64Un7QraPYSQdkI8DixfbpeffPJaxxpN8vo08jYhnRE10ATYn4lnnnkfy5YBv/vdGzj99OMLOkbScWGwiWgJBGpgDgjpJPJ0sjKmepMUjYdsjJfjIxtHSiGCTW4OlnwHm7JF9TMUCtUnYqoT9VD26XwmGfeV6UWVT6TKysj1mW1sST2xFlT62bJqDOcihBBSbKSlgnXBI7keyPwuMckGq+1V+8gjm0k+tLXsmmyDTbpnrzq17FaXzf62QhezyXZspswpP8f4sY8y7DhZVliVBxYTaEwXpWZFqe3jCAQegpATTh9PaWFCCCGtx+rVQGMjEA5Hcd11kzICSmI7kUgUYniEFA2JRMIRaBJMmTIMV14JbNrUuzADI52CYvkJR4oOtwwmU30ubQzOFlPwqBiynEzPLXG45OKA8cJrNq+67Wd2bz4zm+RgkdtsXZ1kjFwPpGf9qm0c1yvP8pXrdOUQ0llLar2fNsx4ateon+d89UkIKXLcJtmIZ91aS34zudX2GttHPJvslHxKCHuVs3n2qlPLbnV+9slkm92US2aT23MImfaLXA4Z6k1lNclIl+UEOO0juT5jwo14Y1XbRJXU87Jl5PblcMoJF8OMJZIztHsIIe2ExYvt59GjI7jxRn3mEjOaCAFqamq09cOH28979gxqu8GQTgfNQGJAJxljcri0JNjkEWRyc6C0NPCUTRv1uSVOGLeyW10u5CIfI5f9BpXc2rjJvbjt96pvlMq6IJM26KRKy0DqQFc2tZEdLiKbSXW40PFCCCHtC2HftGRyjS7IpAabXGwfsZ2NjQNNe1M5myCTrmxqA5c26rWqtCTg5PZVm+ukG6+JNqZ6P3V+ttV9bhN0TOPPsH0A+z5VOxL3ZhP0a1GqL5j6Jusm3RBCCCGtw6JF9vPRRxd2HIS0V4YPBwIB4PPPgS1bgN5McCKtAINNJEVaOq9cqpW9BW4ze91k9Extsgg06YbjdoxpHzzaqHVu5zTV6Y7xW9ZttwQ1ppLPfrLpW/gzckH2i5j607Ux9QMgPdNX7kiWmHGT0TM5VORB2IGoQOB2CIkZSuq1I9TPc776JIQUHWnpvHLkZsuo9aWafZCO8ZnJre4zHePWvlDBpmxtnJYEm4oFnZ0j1+nsFj82i65Ptd6tL63tA6QnzJQmG6m2jR87SN/GlhYWtg8l9doFtHsIIe0EEWwaObKw4yCkvdK9OzB4MLBqlf15Ov30Qo+IdERoBhIJ4SgRt4XsePGarSue5Zm+XaSyPOtX46wPwTkr11T2Cki51XtJz+iO17U3Pbs5XPIRaPL6tGYzuzfbjCZRzjbDKZtZvCYpvDLD8bo2aiJSo1LOcLq4SefVS2U/qJlNoi/+m213BJH/hbLz3R8hJE+oto9fW0YnCexmIxnWZmpJlnZbSuplE2xS26jXrCub2mSDyQ4y2TymfblkNqnlkI+yemyjtF+VCjbVQ+lTZwdl2D5AOstJZDPJcnoqudhKtH3aFbR7CCHtgFgMWLbMLjPYREjujBzJYBNpXfhLgEgIZ7nJmdJFaeclsaeTmFGcLX4CTLkEobJp4yfwBJdjTHVqvW4fXLZNdX7QOVyycbC4ybK41XlJwaj7GqW6kFLvFWBS+9GVTdcir22QsYi7fIAqKxPXPIs+3IJTbpFAQgghhcPNpvGzhpNXW8C37dNSWybb+mzKpmc/No5fO8ir3g9e9k8uZbdJNbo22dhFcr3JDlKDSTp7ztSnPE6H7SOv5aTaNkJWT9SZpIKbYP820NlK8okJIYSQlrNihR1w2ntv4KCDCj0aQtovo0YBDz+czhQkJN8w2NTJyZTOc5OJkW8XnTSM6nCR6wCjdEw2ZdP+bJwpfvoybfsdk+4adft0Zbc6v8i/9d3q/BzXmsi+DYG67YXa3m85Y6avBb1kjEA4XlTpmZC0rR7blGpHSb12hPq5zVefhJCiwCmdJzDZODp7x28bQzaTeDbZG2o7tU0uQSVo2prGoTvWy/ZBC8tudR0JOYDk1sbP66DaUG72lDpHBkDm/anaOKq9o2sTd21DSb12Au0eQkg7YOFC+3nkSHvNGUJIbojMwEWLAMvi54nkH5qBnR7hbJEDSjpZPFn+LuTS3iSpJ/33EnddmdRVrg+5H9F3LrOE1fa643XtTc9uDiO3sm5bR8iyn+M+vhX8ZDTJZT8zet3amDKZdNteEnlApkyMLCeje5T5LMtZVQCcaxl4rcskZvSqXh3TsUKihv9yCSGk8Oik83RrLcltspUW1kywAdxtFi/7RT02l8BTNjZOa9o7udg+2ZCt7SOXWyOzSWe7hDRtoGkHQ70qISzuH1VCWD42w/YB0ves36wldVACWYrP1IYQQgjJDa7XREh+OOIIoLQU+OorYN06YODAQo+IdDRo/Xd6TNJ5XsGjcul4k7PFZW2mbAJKuazf5CfA5MfJ0mrBpmSwKKR4Q0IJ6Cgx1Ks0xw0C6Wp9PDkYOViVTyeLKcDk1sYknefmnGnJQ+CQ3dOt4yROKs/yFfvkF0JuL9DNdlc9YKToCCL/345cu4CQIiIb6TwvaWG1TQvWpWzrwJPaxrQPPup0z37Luu2Wko9gk1+7R64ztVFjOTqbRGffmNq72VCm62qEMyDleI2yXccym+CUOiBSdNDuIYS0AxhsIiQ/RCLAsGHAe+/ZnysGm0i+YbCpE+ItnecWKQkp7eVneb9ya/kJxHgFi/y0zWcgyW8bt2t0CzApASRdQCnoM8iktk+owaVQwhmICiXsAFQI6cCTmIWtxkvairb4byQ7fNT3KOOa5QHpZGWERJ56cAjOtQ5CSntK6hFCSFuTm3Sem7SwWvZp+/gJ4HjZO6b+iznY5BVc8rIBhA0l8JPZbewL+bVz5K/6bPZl0z98nkM9n5+y47VQbRbRwCQzTEk9Qgghrc/u3cCqVXaZwSZCWs7Ikelg08SJhR4N6Wi0hXuXFB1yUMktI8lNHqZc6StL+RjdQzejt8znsTpnSi7yetkEmExlAI7AkhQwEgElOYgUVLKbQh4BJjUAlRFYUogr+xPxkFQOAog5A1HxoDnzyS1TSS03KnVeM3qhOTZkaK97CIkak3yMmNEbh15ST24PwCmrJwYnO19CSM/6BfQSM5TUa5eon+d89UkIKSDZSueZ7BtxnC7bW5EM1tkj2ZZN9pGbzWKSCs5WQhiaelOdn3ogM2ikZngDMGV5e6Kzh+IhZVuT0S3KuiQcUxaTbp+fbXWfzm5SbZ8yQxs3mWGxr8xHOSPDSbyBcmaTG8I+0gWh1BPwy7Aood1DCClyliwBmpuB/fcH+vYt9GgIaf+MGgXce286Y5CQfEIzsFPSEuk8sU8nH1MO7dpMuuCRnwCT1yMfMjTZBKG05cygkhpQEsGkkCPAlBl0AoBgUNn2M/U2klmVUD7aiYQacAo6noF0UEoEo8S+VCBKDUJ5BZtCSp1O6kXeF9KU1fa6snqM2o8cQDIdC02bOJCWlRFOF9lJ2SQ11Dll5IuQy2IbyDw5IYSQ1qGl0nmmNZtC8LR9dDaOXDY9TO11/Xv1k5ONo2x7tU+9BpYziKSZdAOYs7fVSTh+SaiBpVR92tbJmFyTKkv2DeBvco1pfzYBJp0dA5htH12Qyc2OUssCWVJPvZ7U/VyOdCBJ/vzI2UwC2a6hpB4hhJD8Qgk9QvKL+CwtXgwkEkCQ8rckjzDY1EnIlM4TZCOdp8rKqPUaVGeFrs7URt2Xi5PErQ8/7Vz7lZwpoYQjyCQ7SkIZwafksxRY0gWVQshxZm/y2Lgklh4M2v2LIFQwmEAiEUQwlDBmRgVDcYfjplk5Q0b2WuYgsqvXIZwkbmW34+R2pmNNbTIQDhb5ftfJx4gOm6RnQUg5DpTUK0aCyP9aAzTeCGlz0tJ5wl4BnF8A2UjnmY7VfBe62RFqN7mW/dgvuvatFmwySwXrsrrtbY3tk2tWU/JYNZtbRbZ7mrUtxAW1QKYvG9QJOqLO9P6rtpDY77esDQ4q/aUQr4FOFk/tsElq50dS706IwBQl9YoA2j2EkCKHwSZC8sugQUDXrsCePcDq1cBhhxV6RKQjwWBTp0ENKqkzdE3SeXJmU0izX+5TmdnbkmymlmQ8+X3IfcKlTWrbmcWkCy7pAku6oJIcSAoayjK+MpzgzGgKO+rFL75YuhyEHZAKJo9LZkglEkEp88keTzwedGQ8NSfrU9lO8kxg1bGhzuINQS+x15KHTi5PINqY5PJkST35PXcsnq2TlQGcM3d1/07lC9cFZUVf/FdcVKjO2nz1SQhpY9ykgtUAlNpOtYPkY0WmhkYyWCdVl2/7xa+NoxuPPCZ1nEb7R9pO1WcGl3RZS7rJN/J+tSyjZnubkLO3HbZPXLJ9NJncdptQRtvmeDCd9WTK6BbPLc1sMvUnP1Tp33yVZdtJPDtsH8C+5y04J6u52TU6qWCTpB4pGmj3EEKKnFde+R+AfbTBptraWiQSCdTU1LT1sAhpN9TU1CAYDKKqqgqAncl01FHAW28BN9zwAoYNW8LPEMkbNAM7DSFkBphM0jByvex06WKo16xRkE0gSeck8RNgamlASj02o01mcEkNLOmCSmpAKZjx7B5w0m2riD5UuTyVhDKtUN4WmU+iD7EvEQymA1ERab8jCBV0yO7ZAaggtFJ7qmNFBHwAZ6DIFECSyyYZvZBSVqXz1HYw9CPXq8dmyMrIgSd14Ww3ST25Xj6hHMQihBDSctzsGi/pPF07eQKOh+3j197xe2w2ZT+2j1e9Y9s82cZ+1k+4cbRRbCS7+0xbx8v+0SKZOg67R8SLkvaMvT9t0wBOiT1RdpUVloNQsp0DuAefTPUhQxsvCWE/Za9JOjoZPd11pCbcyAEnN7tGNvJ0knpqe0IIIcTMV18B27fvAwB4/fXf4JvfvCq1r7a2FtXV1Zg5c2ahhkdIuyAYDKK6uhoAUgGnkSPtYNNzz32OESOYkkzyB4NNnQZVPsbvs046T97WzOr1++zH8WE6RndsvsrCsaLM1hWBppAjoyntRJGDSGqAyS7HjQEmtZ0OnVNGrosj88shiLhnQCpDcg8JJBBMPUs7PPEltacOR95Ws4tMdbp+ZKeNrr3cRu3bq97xluhkZeLStpekXshQT8dL0aD+D8pXn4SQAmCya+SyKp1nMkLEsw/bx2Tv6Nr5sUtM+9z6y0uwKWkPSetSegWZHMEmyT6yu8wus1vGz0Qb0Y862SajXdDbPtKRtaRwrpjsHV05bihDqYtLx7kda7R9TPaLanx5Seqp/ZCCQ7uHEFLECAm9Hj2+wqxZV6O8vBFVVVWOQJNwnhNC9IjPiBxw2rDhaQBno2/fM1FV1beAoyMdDZqBnYYQ9DN5S13qQ0obVVJP+YFtymBqrXpdG7/tTU6WsuSP3iwCTHIGky57qXUymzKdKWFNO3t/TNm2kTObwtI++6oy9yWQSGU8JYIhJEJ2m2A8mCG3l5LaEzOAG0udTg7TrF65LKObcSvLwfiVzivLsT7D6SJkZXTOSz+Sen7qCSGEtAyTfQM4bRydXWQ63qft01b2i18bJ1vZYJcAk8kmAszZ3Zllc4aTd+Appq1VA0zyRBoRWAo72sXsbG7RVpIVTiSCdluNjQO4SApnm9lkemQriydsIWG/QCqXGY71017OFE8FnNKvsDOQpOIlqSf6IIQQQsyIYNOECT0waNBMVFdX46abbkIsFmOgiZAskANO9meoL4Cz8eWXfRGNApFIYcdHOg4MNnUaVFmYEGxZixAyA0nlShtojpWcLSaZGLfgkcnJkm29qX9Tm4xyOoOppCzmcKZEymLJslMiTwSQgjBnM3lL6eXL4aLHj8NFbqc+y8EmUxAqEUxeaTCIRCTpfElK7QmZPeGUaQpJgad4CGiU1ngyyeXJzi85GKWT1FODVLKUTEipNwWz3OrVPgHYnwEhqaeThhEDluXx5M9RvVJPioYS5H9h65I890cI8YH4nyv+x8p2j1zvR1rYw/YRdTp7xE+wKduAVEvLjkfussFuE27sUyWQS8BJ117FLXvJy+4RZVVSWNSnglAaGwfIg5ywrqzaQV7tVbm8kPRskhP2sndME3kcto94rfxIBcsnEJJ69UjbR7R/igLaPYSQIkYEm0aOBK68sioVaAqHwww0EZIlVVXpz1Bp6SZUVNhSlcuXQ7smGiG5wGBTByYQuBVOpwmQObNXRtS7Secpzhb5UHV2rPrs1qal9W4zdF3L6Zm7RseKlMGkOlNMThZ9faaDRTfzV7ft3Jf+QW+SgFEzn+RtVTZPPc5LekZtLwT3xKxgICmh0yjlWpUBTfJ2SLr/xCXICizyZamXqLZRHSxe9aZ+dMfo+nSgSurpHC5qWpa8z3niQOBe2M6YBljWNerJCCGEeBAI3AlnkEgnlScj20huz8oaTeJZ/X5pqT3k1iZrG8dH33mUDfa7ZqXcRqCze3LJ8tYh2z2qvLCwe9xsI6mxJ1nLCetsELc2OptJPd7Uj66N2o88icfV9pEPdpPUA9LZTLK0XlpqLxB4CHbgqQmWdYV6MkIIIZ0YywIWLrTLI0faazSJQFMsFkNtbS0DToRkgfoZ2nvvj/HVVwdj4UIGm0j+YLCpQ6OTf5EDSqosXo7SeaaZsmWaNm6zfnPJkHKrN7ZJy8OoThXhUJGdKRHEMgJJ3plN7nIyuTpeMtFLyQDm7CYhjSe30WU0iXpdZlMMEQCxVJ3oM4Yw4snZwMGuCSnTyX6NU7N/RaZTPASEAuaZuHI5l4wkVV7PJJEH6dlvmxQmSb165SBo2qj18gWQgqELTuajT0JIG6DaMrJNI3+4TRlMqu2k/L/OCNZIXbaGPHBrZTy52EKAWTY4F8lgc2aTave4f/cJO8krKKROxEkgqNg9sVRZLykcy9gn2ieCSbsnGErJ7WUtJ2xfRPZlL+m8Mk172X5xkw0WlGmOVesBZCepJ1+I+mWok9ojbQ7tHkJIkfL558DWrUAwCLz00izcdFN6jSaxZhMABpwI8YG6zpm9/SiAG1MZhITkA5qBHRpVPkY4VnSOGLmNkM5T22jkY/xI5HkFm9oi8FTmP8CkBpNUJ0oE0VRZndGb7fpNmWVvSRm/+JWQEc9ugSYRUBLbkaQjBgCiiEj1UUfbRDAts6eT2MuQnQkFxMWbpfNCHvUwHAufbZwvYmZ7NXgFIFNSLwT7cyRm8zYg/e9WbiMj2lBWhhBCckfYNLpAkptEnqleImcbpIX12bYxPtwDTOGyWItkg3WTbkRfok26LvegkwldkElXNkrnGWwit3rZzgH0csKOSTYAEDKsY+lWVuX1/ErnmerdJu/IUsZynRivL0m9JkM94LSJ5AEQQgghToQDfL/9tuCmm65zrNEkrz8jbxNCMlEDTYD9mVmz5m949FHgn//8EsB+hR0k6TAw2NTBsKXzvORjhDPFTVpGbeMiA6I6M6Ap59pe9zDtc633F2iKJGe7qoEmU+BJ52jJZs0mnQNG3u9VJ6NmMsmSePJsYFVCRm0vpGREO7lf3bFygMkVl4nIzUAy2JSsULvS1fuRm1Hb6CT1VPW7bNunUCX1BEIqRl4U27uNLaknZGUoqdemqO95vvokhLQKgcDtcAaZgEwnuFovP8tSepDqDdJ5uT572Tpex6n/m7zsJZ+BJjeJPK/JNCbZYLcAk2mSjdo+W1QpPNlm0ckE+5LOyxZPWydovxcIOG0UHfmSxfNT7/UsB58cyJJ6AvGZUg8IwWnviOf0CQKBP8K2feKwrOnqyUhrQbuHEFKkiGBTnz4b8dOfzswIKIntRKJlE3UJ6egkEglHoElw223n4dFHgS+/3Be7dgHduxdogKRDQTOww6HKxMhOFJ2knmhTrhwvt3GRzvM7s9Yry6nVMp5s531JWczhWAmXJYNKwXSmUhixlNNDlc5zBqFMgSf/Tpds5PQE2QabBLoMJ518nrxPSMkkpCBVOvDklM+zV22y66MIQ5aiiSaFa2KI2H0FgWgwgkTIPkesMZye+RtKoDm1rlOp9+xbuSzLwZjaiPtE1153rNxe/k+pOzaFKqkn6mQaks/ZtiFtRhD5Xyg73/0RQiSE3aKbUKPaP6bJN6JeZIUrgSa/No7ferWN33o//WvsIIQSKBW2TyiOSKrsntkNZE6uUW0iu+xs73z2n9nkT0LYTGY2Uyyj3k06T+zXZXkLmyaBEMR6lXJ7YTfFg7bMXiJkS+wBMUQbw0jE7T6bGsOZ8nq6h4xORs8knSdnIenqgUwZPZO8npsdlEIEnOSsbPkCTPWAPijFLKc2h3YPIaRIWbDAfv7JT47CJZccpW3DjCZCvKmpqdHW9+oFfO1rwGefBbBoEXDiiW07LtIxoSezw6FzuMjyMSYpGfkYeV8O0nl+yqKfXKT2PANY6dm7wrESKYs6spjUAJMpg8lUB+iDUKLezwxg3bNop+J3pq9uhq5OQs8r2OTH4aLWxxFEOOmsEY8wokgghEgyECWuNaFd1ymIaHJ2dZO8plNjwBkXlZ0oquSLm0SeXFZl83THmsqq80Xce1pJPTFwNbNJ7tgUdNJ5mwghhGQi7BYvWbxyZV8XQ73G9mnpRJi8ywO71euzmOQAUzgYTQ4ngXDKljFL54WVzG9R70c2uCWSetniVzpPZw+Z5IRFfVgKSMUQRoaknjQRBwBiQWkdy1ACiWSAKWpawzIeMMsGyzaIl0SeqV4um4JZpsCTro0YJwBnwKkJzkls9chcm0m1d3Sye4QQQjoz8TiwcKFdHju2sGMhpCMzZgzw2WfA/PkMNpH8QEu+AxAI3IzMIJH61pZqyrIHXyelp0E+xPRAFmWvOr/9O55lB4v9a1qVy1MDQNkEmvSBJ/dZwLogk5fzRW7vF9HelOUkt3OTk9Htl7HXbMpOfia9zlMUMUSS54k7Zj6K9ysRCtpyMwAQSt6TqpRLSFMHpayTyJOP0cnE+Cmr53KNCQnJPBFwckrGOB0sckAq3SYQuBNpWZnr3U5G8oHuX2g++iSE5I20dJ4qgaerg7RtktXzkA12szvy1cbN3vFbD2gDTapcXkixX+wu9ZlNYSXbO1vZ4Fwl9dRjdKh2iJd0nq6dPCZZTlitV9t6EZQDX8F0e7FGliBl78RL9fcNoLdB5HYm28dkv+SjjVZSD0jbPeKgUuVZPVj+HZKut+WEmwA0UE64taHdQwgpQlauBOrrgYoKYMiQQo+GkI7L2LHAnDnpTEJCWgrNwA6B+JGmk4nRZTDpyvKvVTEbUZnZ6xYAyvWRt6woK1mOZszi9cpmCiNzdm8YUa3TRQ0wiT51GUxqW3mfs07vaHFzsPgJKunk8+RjTLN4xbM6Q9eZ2RSBLLcnS8vEkuU4goghYsvlSTOAY4g4HDmyvJ4889cx67fRDk6hUeMETF9wbtlJukwlr7JALafePjHDNwTnQtiyM8UkGaNmQOnKhBBC9NK/qixeSNPGdKxGNtjNfhFt5KwlNxtH12fe2pjtIMCczRRBNGVTCNsHQNI+8s540k2iccvwFsjHinY6cpUQ1mVwp/dl2jWqvSPkgVVbSRwjB6tiCEOW1BMTakJIIJosA0hlOaEMGfJ6GfaOWNMpX1lIftvIdk1Okno6OWEgbduYjCg1+KReMCGEkM7G/Pn28+jRQElJYcdCSEdGZA4uWABYFhBwcbsR4gcGmzoEqpNFdbiYZPRUp4zYNqxTkEtgyG+5RX00QZ7BK0vmhYPpoJEIKon1mIQzxBRgkgNJssMlokjJuGU5meRlRDvns3ugKReHixpMktupDpj0mkzpQJRap8rlAbaknnh9YginXrcoIqlsprCUzSQCTSZ5vXgwmAo6JeJBRBsj9npO8SCACBCSFtUWAR7hCFHLQHZBqHyV44Bzhq/aEHBKzEApyxlQAv67bjOCyP/LzbULCMkzwo5R5YF1NpH8/9aHbLCfQE/epH9b2B7Q2kEAEC6LOdZjUgNM2WZ0A9C2k+vtsnkNS4HcRt3nVqdDZ/+oEnomO8gUbFLr5atW6yOIKtvpIJWwlyKIpgJPoWByXSeEzPZOKGiv5wRkSuqZ5IHlSS+qbQJkSghnMzHHT6DKMeGmHOnJNg2wJSubpEaiI90alXKbBjjXfCKtAu0eQkgRIrIsxowp7DgI6egceSQQiQDbtgEffwwcckihR0TaO/RetlMCgRqkA0ly0AhwOq8FOqe1ySmjaRrKsez3kfM57Jm88ixeWTJPdg+okjFqMEh1rOgkYCKKlIy6ZpPcr3qsWi/6EPsEfmb66pDbCmeILAkD2M4RMRtX7JPlYTLlZ9KBIfk8Uem8zrHLsjPOmagJZDqb5OMT0lhluRkhrQcAzSHhaZECTvaF6cumWI1bOVtJPV3Zcemmk6mNMw6USEvP2NJRDQCaYFk1hvaEENLxCARuhXMSjcCPFLA8qcajrcnmkJ91dW72ituxXvaQsX0ym0mRzJPl8pz2jv09kkugSbZf5IxwP/aOLggl9unL2WWyiPaqLJ6MbAflQhDx1KSZXEm//rJ+MJCIB1PvnaAZAELJ6wlJgVCTpJ2uDlJZNTX82jW688oYbR8gLQ+sygkDZglhXRshJxyHbftQUo8QQjoDIrOJ6zUR0rqEw8BRRwHz5tlBXgabSEthsKndYspmglTnlvGkPnvM7G3JI0PyzqUsH+NZtmfylpbFUusRyLN4dRlMumwmOWDknO2bORtYDTCpDpdcZvqKbdEm/fJnt36TOrPXJBkjt892Rq9uTSc5QCVnLYk2CQQRRcRxjbK8njPAlS7Hg0EkgskxxROIx4OIAWiOJxfTRmn2mUfyrFy1DKTvsWwk9UzlDEk9wOmJUddn0pUB/axf/utuVVQnW776JIS0EFX21yQJ3ALZYJ0dI+pNGUZ+baGQpp+cs6UsIJnBJNtBwVAC4UimvaNmM+lsGXlCjVNeL5YRSHK3dzL3yfXpl1o/CSWbiTYyqh2kZnDbdc6MbbFfl8mt7pMlgGOIQJbaixpkg0WbKMIO2ymBUNoOiqRtH2HvJOIhyUqIAPGAd+aRjMneMUnneckGq5lNJnk9re0DqSwHeeOGsqkNaTVo9xBCioyvvgLWrrXLo0cXdiyEdAbGjLGDTfPnAz/8YaFHQ9o7NAPbLToHilw2SeeJchdkSs9IXQP5Cwxl249rewti4Ws/QSZ92RlUktdyUtdv0s36dcrr+Qs2mQJOzufMLCd5v19MQSfdukwmCT2vYFNMktELJ9dvUqVkZIdLGLHUWk72a2gfLwekRKApoxyJIxEJIZEIIhSSnDChZNApHgJCgUxZGV2wyeEI0eB2bK4BrJSknk4ur146oMFQVk8I0PlCCOmc6Gwc2QaS16vMQTYYcA/6eAaA8lDWjcFRtkMQJWJNSoMdBDgn1KhSwW4BpnxlOeU72CTqVTtHkM9gkxwwUuuFDLC8rZXLk4JTTnvHOWHHzpiKOeydWGMYwVDcXs8plEBzYzj5opWaZfRkZHtHLucqD+wWnBKIgJQ4LsP28SMnDKWNLkhFCCGkoyMk9A49FNhnn8KOhZDOgLxuEyEthcGmdo3XNDSdc1stG443JVGozdVZv6YZwep+t2Nd29s/QEskB4uQzFOlYuSyHGgSroHMclpqTw00yZlN6Zm+6kLausCTWVZG9Cf2yfVq2a0OcDpYVGeMcGoIp4csoyekXIRcnl1OX0G6T6d8TMIxzrQsjwgo2a9P+m8i+RqKQJJ6rPwaGMtBpKSBACARCibXNYjbzhfVsSI/i7IsDWNyxIQM7dWy2q9b2YG8Q5aLMZVNfbjtJy0iiPyvNcC1CwjJMyYntCmbQpcF7uNQnU1TsHJaNi/oYQfZh2aWVXtHH1TKzH5yk9xLt9EHpLwCTOayfmKFXK/K/OoCUWq9LLuXDv5kygbbROEmnxeEU1oYQGrijWoH6cYfSp5blJMNHPYOADSLCTYhCylZPbd7Jh+SwG7l9AWkMcrpyY2F/VKqOUA9uFTa5iSbVoV2DyGkyKCEHiFti/isLV8O7NkDdO1a2PGQ9g2DTe0WdY0m8QNON3NXLftYp0nMWvSTkaR7+G3vN1sKAMqaUFKWnKFbFkVEzOoNpjOV1Fm86XLMkcGky2bSy+5lOlzkY/VrOTmzn0xZTX4ym/IhJeOW2aTO6lXro9KM3khSBkZcu5ypJM/QFc4bWSLPdsak28dcyzEpuJUuJ5AAInaQKRgXM45tmgGkZPXsC9JnHol94r5yax+HeRZvmaa9KENzvhRuHhqvsvrvmo6XVkN1puWrT0JICzFJAkNTr7aR7SCgVWSD8/Vwkc0TazNFyqKpNSrDQWfWklf2ts7esds4+/G7ppP9Ejon5rTE3smH7ZOrHaRmcuuymJxX78zSFnaTKhVssoPEdtqOCmbYO4l4chJRPGhLCQtZPWEfyzJ6+ZABzkZez49ZY8xu8pITbnI5AckrtHsIIUWGyK4YM6aw4yCks7D//kC/fsDnnwOLFgHHH1/oEZH2DM3AdouQhZFlYrpIZS8ZPbmszJBsSSDJTQrPbxudZExy8etwWTQlFyM7V4SDxC2QJDtR1PWb3AJMqvPFGWwyy8wAThk99zWbzBlOum0TXhIyOkeL2K86UACgHPWpGb0JBFEutYtJgSdxTFiaARxF2NE2jCgSCCVf52jK+SJmAMtOK3nWtXhdRJtoMJya9Stk9WKQZ/2WOuVkROAISp1JLg9KXb4CWADSaxiIg1W5PK9sRNG+AenPLyGEdBbkgJEcRAIybRxdoEn8/9UEmrKWs3M51m/Zq3/Alg/2EWRy2jhmewewM2/SgSF9cCoI83pP3sEmc1a3W6Ap37aPagPZdXq5PF0QSa2PI+iwiYRcXgzhVJ+yTSQHocR2+rVK20Fq0CpVDgYRDwYRC0UQDCWQiAcRbYzYsnrxINAYQepeVu0eP9LCLZUK1pVN/aAUgIX0bxeR3QSpsYxqH+naEEII6YgkEsC779plZjYR0naMHQs8+aQd7GWwibQEBpvaEYHAzUj/SPMji2cqy+0lh4uK7BMPKdtQ9rm1cevH81grFWgSwQWRzSQHZpyuAGd9ZhvVWWJek8B9gW2vYzMdMSaHi2lGr05CRt6vOlhkaRjRVnZwCJkYMdM2s+90ZlK676i2rbo+gX2OcKq9ecZyUFtOSO+XcM/IY89oE0ykZGYSyedmAAiFgFBAP/tWDjzJ917cZRvKceq27ji39gjAdrgATrk8tVNd2SmvFwjcCdshE4dlXQ+SJ4LI/7cj5WQIyYlA4HY4bR/dFHydTRSStuVMcBe7R8aPOSW2VVvGVFYfpv4dx8ZRkvyOC4biqe89YQcJW8NUVm0awDnhRQ0kiXr9upVOm0hn88j16rncJ904s55U1PUs5QCSl+0jprP4IX2s6ZiodB77vCKLSR2/KjOc3jbbQdpyUHqdQnEk4kGUhBJoFjLCgN7GyUZauCVSwbpJPUaENJ54FtlL8uBEIEqVC7bbBAJ/RNr2me73xMQN2j2EkCLisstmY/fun6JbN+Cww5z7amtrkUgkUFNTU5CxEdJRqKmpQTAYRFVVVapuzBg72PTww2vQ2Pg4P2ckZxhsalfoZvS6zdz1kteTHC662bQm54ifxbNN0nmmY7WzhO3ZvKVlsYwFsMWsXDU7yc5gMtcDMBybzmYylQHdWk6ZC2yrazmpzp50fdoJYb/c/tZt8kPC4bxQs5ucs3VFnZrdBDhl9GIIp/oQC2aLY2QnUXoNBH1ZZCmJgJSYGSxeE9mJI0vPqPXJFx6JUPL64kEk4qGkayIpMQPos5BM9WUwy+LppPNUh4wsMSP7ThwLZgP6RbPljnRlU3vO9CWEdGRkGwbKs5dssDhe522H/wwmt7LJVnKzfXxlftvfZiVlMYTLkrZGWQzhiFtmttOuUTOW5KCQl9Se2qdsz8jSwup6laJePU6uF+1Fnfxsl3P7XpMnxpiym1TbR7V/RL3eJgo76sSYnYEkpzywfLzYFrZPUCrL4xTX4SgHg0gEnfdvDMlJNvHkJBsveWC5nKtUsKkMOD9eZTDYPurnsVRt5FIW26WaekIIIR2FTZsOAADst986BIMDUvW1tbWorq7GzJkzCzU0QjoMwWAQ1dXVAJAKOIlMwtWr90JJCWeNkNxhsKldkU0gSbdOkywxIzmus3GOeAWVVGkYr/pumv4VyZgu3eoBAOFIzHVtJrleuA+6oCGjjRxIMq/xJLd3OmJylZjRzTYGgFBCcrDEEwjGm6VtaBGKcSYSIblckg7IBDOlZNJOlUzJmHLUO7bTkjHO9QvSknoRqRxOyc3I5WiyLIJQIkNK9KYLVMn18lpOQdgyM8GuCcSi4fS6BkJiJhRBKssp40WE3p9hqlel9mRHjS4IpXPcyFI2GY5T9YRuZVNAiuQFLpRNSBGhs32EbLDJJlKfRTlP6zTlFDzKpo29RqUtlxdPrVEZDprslHiGzZJp4+S2dqVdnxmoAvTBJlNWtym7STw7M4Kyn2jjnGQTctSpgRw1qCSOcY4+M9gUTtou4iFeHzEZR5UKlte3lMvpbHDbJpIzsdKBLKcdlLJ9IvGUpB5g2zuJeBDNoTDQKGU5yfaGatcALZMKdgtOiX4aYbB9ArB/i6gn91q/qRRAPdISfLR98grtHkJIEdGjx/8BANatewy1tc2oqqpyBJrkTAxCSG6Iz5EccHrxxVsA/AJAL/zgB/yckdyhpV7kBAI1SAeKgMzZvaaZuzqHC6T9CuqhuuZubbKpd+svWSdLxtjPckgk/fPfPjyRUa9mEplk8dzaqC4HuQyYs5xUiRk1yCTqRZBJDjDJwaWQ5GsJaIIlpZo6K5Q+VgSjgvFmJELNqddRBJ6QehIujrTTRdRDkoWJIZJaXym98HUC0WSrdPDILtvOpLSkXkJ6neVy6nqT9cLZotar5fQYk69z8rocEjP2QaKjtMNFflbb6GI62dR7SfA5kHeKg5rglJVRy2JGb9xRtqWmGgA0wbJqTCckhJCiJxC4FU7bR4ccSIKmnAXq/2z1e0Mum8wpna2ja+/ZxpYPFnJ5snywwM0OMtlKTplhs+SwSWZYtWuAzExus7yeu5yw2BZtZLwCT8JeEMfJax/J8nrpYE7CEWBS5fLkzCQ5+1pcl9xGJ4snQkvp7CX5NQ86ysJWSkhtBHZ9KPX+CAsJQOpeCIUSSMRDCIYS9rqVoVA6q1u1U0zbbm3UfnTtXW2cXFGl9mA8iS0nbAerLOuafA+EEEJIAZg/337+/vcPQnX1+bjpppsQi8UYaCIkz8gBJ/E569dvEj7/vB/mzwcGDizwAEm7hcGmdoGb58PkZMliYWwxq1buXjeL1212r1u9H+m8MtgZTaE4EEpoJWMiydm3IpiTnrmbOVs3mNEmc3avW4aUOjNYt9C2HGCSZwPrMphCiURGUEkEkwLy5E7hU8lRJS0g3kMk7wZRFn6QUDOsZOApHmxKZUCJ7Kd40Dl6e3auXRdBDNGkG0UOPDln4prKmU4u0SaWDF3J9fY5wo7AkkBtkwqQBZEhMdMYD9pRt7h03+uyk3QZSYC7jJ5XPaSy/LHNmOGrehplSRnTtGN5Vq/6P0Fd44BkjS5ono8+CSFZoNo6ugk0JvvIp+1TpmybunR7ZCM/7HaskM4LJVBaFkMkaQeFy2IIB522D+C0ZWRbRZe1FNK0ycyIimszm+R9dp/p/hx2jmYbcGY/qYEt57MUaFEyvk2kJs8k0WVv2+V0fWYoLjPrSdg3mdlJ0VSWtpyZLcsDiyCUCBTJ0r+inVyOOYJZCYddo06+SV9bwr7WMmd9k/0iACg1SwWrGUyA05ZxkxOGpr3OxjEd68v2kU8inoXNY5ITBmj7tBDaPYSQImH7dmD1art8xx3n4cknJyMWiyEcDjPQREgrUFVVlQo0hcNhnHNOP9xxB7BgAfD97xd6dKS9QjOw6BELYrfSOk0mp4jYrwaH1HqTNIypHIKndF64LJohGSOCP3KwpzwpkRdBFOWoT5ZjjrLsWNEFqpxBJfd6IFN6Rg4upeRmEtFUYEkElVIBJTmYJAeYTFJtJh+LOuNUJajsl54DyX2lIftht2+GVdYMoAnxoC3DJwJQ0aCQzgujPPXqNEiyMelyebIs5GXSQatISnpPdjYJJ05cqk/P93U6awTqLOOMBcEViZlYYwTN8QSACACDpJ78uurk8gD3gJTfetlBI5wwnus3yZIxoqwGpNQyIYS0Z3S2jsmuMWV7i6yocviyfdwCReI4nfydnzae9fZkm9JuSbumLJqxRiXgXHPStBZlNvVqG69AFOAvq9u0diWA1OQbABlZ3Y5JODoybJ+07LCd2d3kkBhWJ9QA6YCUaT0mwCmLl0BQmWgjrjHs2C/K8rEiA1z0KeyXBjjXrlSzvbzWtIwigjCAUDCBYNcEEglnQKoJgCPLSX7tTDaOrl62WQDvNS1NZflYh+1TDjsjWxd0UjOa1AHKx8h2ESGEkPbMu+/azwcfDNx7b23KAR6LxVBbW8uAEyF5prbW+TnbuPFpAGenMgwJyYWSQg+AtBY+FsaGSxO/z2ofXqcLGdqH4qk1mmTJmJDipJAlTOxAT9odINqq5cw5rOl5rWkni796tRxBTHLOxFOBpnCjFGgSmSwiqNQIICo9GqVHNNkukSzL2vfyw6s+KvWhO4dcnxxboNF+hBK248e+hoR9TckZvCEkks6nePJ10pfVwJ1cL/oyZYI537vM91d+38U9IbcFbIkZ+V4qCSVgZ80Z7lO3+9x0X7f0M+NANxhSMLJxRGfzIIT4RHxg/Mri6ZzVfo6TDvfznWBqb3o2tXM8rGR9Wj5Y2ECy7ZO2P5wydy2pT39PZ2YmqVlOuuxu+fs5/f3uzAYPI4pIIopQIoFINIZwYxOC8eaUnRSJ2pdeGrWDTAHVlpEfsn0kP+JpG6Y0aj9CCbtvYc+EG5sQbmxCJBqzx5KIIizZemKCktPeiab2ibWYnLZKPKOsbkeSfcqvv+hfrc/sy70+dW8kbR4hPZ2K2qXuLR/3ole9+j3mZkvpMO4zfV69vjR1ag4kZ2j3EEKKBOHg7tp1eWqNpmg0ipkzZ6K6uhq1tbWFHSAhHQh5LTTxOXvyyWkAgPffB+rrCzxA0m6hGVj0ZJO15DbTN4SsF8Z2y3ySyzr5GFe5PLlsz+YtKYshXBZFKJTQSsaI2bPC+SGXIw5nQeYsXjcJviAS6JLMhDJJ8DmznKKpH/0pp0tylm64sTmdxRRNviZqWczoVLOZdBlPUMoCNdtJtwCvziEg2sqOgSCc7xuAQDSd8VQatWX34sEmxMpKEAlFEQ8GkxlJMdjrN0W1WUvitVPr7UsIOupN2UzyrF8x+1hXTq+7kF71KR4MIhEKIlIWRTwetCX1yuAuqSeXhZSM/BqGpH26NtnWOyRlTNlKpgEK1DebtJjWcJLwrSEkS9QPomzP6Gwi9TkH28etjZtcnpzZ5FWfkeVkGwlCOi8YSiAcUW2QTLlfnR2ktlEnzuja+2mjSuep8n12P7HUhA8x8Qaws5ciSTsoQzZY97WmkxNW2+j+n8p2DoCAsGPEsyInbGdxNyERsufdqZnc4rpkGb1oMrMpgUyp4PS6UOmyyE4KAxm2jN23ud6+FGe9vDaU/VKlbR+R9J1Ivu4pSb2yUr1tKcvl+bFrVDsIHm2ATBk9Uc6Q0wOcnTYpB+jKcWk7BMrotRDaPYSQIkEEm95//z7HGk3y2jLyNiEkN+RAk/w5syzgxhs3IR7vi/feA8aPL/BASbuEZmDRYwok6ZwssmSM6ogxrFVgcqa41Wcjr+da9iedZ5LI64L6jMCQd0AqnrXUXsZ6T5JMXiQqOU9EUElkDEGpV8tusnqAObbghu43uSyppwadxHbEUC4DApHkHRdpTjppmhCNOGX2YsnXpx5dUs4XWSJPlcsTkjOmoJJzXSfnGk+q80UgS+DYi3IHgQgQC0UQ9COp56cstuWHKhMjXmu/9an+SwFYSH+W1X/Pbg4X02AJIaQ9Its6QFpS2GQT6QJOLrYPYLZ3srWJ3Opd7SPbBiotSwZ9yqIo75qWBzZNlsl14oxzXcq41lbS1dt9msqZk24ApLO6gXRQSc7wBjLtHtNXmXnJJhvZHAgpzzr7J2TLCaekhIP2mK2yZpQH7YBFrExex7JBCjbZr2gCQZSjPlUOJ5/tst1GtBeSwnL2dThpFal2jd+JOfLaT7LtgwhSQSeBHXQK6SX15G3TZCdZOk/Ulyn1XsEptY1jDF7rN5lujCalnvYPIYS0d+LxdLDpJz85ElVVP3LsFw7xRMLLOCCEeJFIJByBJkF1dRWeeGIVPvigL955h8EmkhutLqP3q1/9CoFAAFdeeWWqrrGxEVOnTkWPHj3QrVs3nH322di6dWtrD6XdEAjUIBC4GYHA7Zq9wpECZGYwif0ZPToP1/mw/dS7zSR1c9YYH97SeeKHuU4iT5VoM8mxyVImun7STpaEw+ESVM6TWqNJDjSJYEFUepbroppyo2E7IR2vyt35eajSMqo0n25sXmNVry0pVWNL09gye7Isniwx45TXc76+sjyNXHaT1dO9L5mSifHMfnSSevI966ds+hyodX4/S2q9K7JDFZpyJoHA7cn/ITVenRMNVglgBfP8oGhtp4F2T24EArcm/3fdC3//aNWy+r/RxfZx+1+c6/9x3TDV/ak6y9GFkM4D4Pge8yMJbB9j+p7U2UeZMnhyoCksfU/rv4edNlEkGnNkd5cK20i2O4QdIksAu9kmJqlh3UMjqefoTz6vHPSKSuVEWkY4lJBkhKMxmOxBWSpQDvrJcnvqa6irN0s1p99b8ewlOZyS1vMrqWey73Vt/NZD86w71nFOde1Kk5ye3LEqnRdCIHBv8n/IrSDZQbuHEFIMrFgB7N4NVFQAd931I22bqqoq1NTUtO3ACOmA1NTUGDMEL7lkCADg7bfbckSkI+Hp5mwJixYtwv33348jjjjCUT9t2jTMnTsXTz75JCorK3HZZZfhrLPOwjvvvNOaw2lHuMnECHS/7GSndKnmGOh/7KkPL1k8dVtu76ucXp/Aj3ReF9gzfdPa+pkSefKM3nTGk1lqT2Q2dUGDazZTasZwNNl/YzNKleALEkg7PJAsy84NU2aTmuUkyvJEnWySVkyONFU6LwR/mU0hAHuQfu8iyXIQCCSAskYAoWaEI42Ildm/KIORLkjL6HVxyM2IzCZ7X/pi5EwlXTZT+vLTZTGLV2RFpfuV26RfSK2kXmPEvsZ4wCklI2bf+pHRc5OekdtDqQec75FWTs+xQ3Ow6Nz0xrfqv3dCiAbaPS3BZPuIffKzKJdqjgUy/v/5sX1MwSGTTeRlK7llOYXiQChhlM5rqVSwryxtl4xwu41LfTRZFjYR4JykogZ41OwmwGz76JJUTBOYvbKa1PdU1JdpyiFbRhgASiNCRhgINzYilsw+C0fkjKS4NmtJzn5SM7PtDKlY8tTObCZd1pKwcUS/qQwmwGEfZdg+bpJ6sr2js2sA/7aMm42j2kTQlDPs2pC0Q3y2mzRl+VmNXNH2IYSQ9opwbI8bBwR1SwUQQtqEY4+1n995B2huBko4gYRkSatZ5Lt378b3v/99/PGPf8RNN92Uqq+rq8MDDzyAxx57DCeeeCIA4M9//jMGDx6MBQsWYMyYMRl9RaNRRKPR1PbOnTtba9hFghw0UstdkJbL8yOvV+rs1uQEydZRYlqHQOeIySj7k87TOU1EUKkc9Up7OyDVBfW+2quBJ62DJimXlxFgkoNKakYTNGU/jhfZ4QLkJqWn+62tSsh4rdkkHC/iuDKkJVlEOYR04AlJp0ykGQgB4cjulPxMOKiX0bNfX9sRI17rBIKoRxdpBm8XxeFi1zdAJ6MXS16O3lljH6+R1Asl0BwPAvGydFfq+6Aryw4UWUrGbxDK5NBxyOlB2qEbnHgIZ4tpsCQXEiH7ke8+Sccmn3YPQNvHacOE4JQKLpfquyTLcnsf6zSZAkYZgSGlvakf33ZTE0q7JeXyFOk8VSoYME+i8R+Q8gpCmQJSyrmiMb18sGzHmGwfP5J62axdKdDZPaZgk2zv6GwfYdsAqfcwEARKy4DSPcLGaUQi1IhEqATRSDqoJGTx7NOmJ9qEEUkFp1Q5YbmskxM2SQv7JmKvQyVjWwulma+rm4yeKJvsHZON4xaQkssZto8uY7tBMyi5LW2flkK7hxBSDIhgk3B0E0IKw7BhQNeuQF0d8MEHwOGHF3pEpL3RavHJqVOn4rTTTsPJJ5/sqF+8eDGampoc9YMGDcIBBxyA+UKgVWHWrFmorKxMPfr3799awy4i5Jl6cvBI3m9CdtZoulQPVet1XatDUY/TPbTtrbSMGWCUzpM169V9TtkYWTZNlWDTy8ek5d7iDikUp7RMWi4vJBwiOgmYRjh/pMsOFjUDSpZ70cnKRJXjVKkYk8SMV3tVykYeg07CRh2bPFvZdO3JtqGEU15PlXiRX9+05F5a5lCVknG+b3FkvudO2SG3+0aW1HMQsvzf0173OpSyrl8o7bQfZdXRamoDOJ2xug8eIaQtyKfdA3RW20eHSV7LS2pLg+5/se7/te7ZrR/fdpMFIWumk86zm6t2TnpbrtPZOtlK8JlsJRFoSknqJRJJablkoElnI8g2haleZwfp5PJkeychHW+SDtbZQG72jk5KWL4u1SZKHlsaBYJxJG1DWU4wLZGns2X0do27DLBq56Tf+0xZP7EvBMU+Tto8Dkk9VU5PvldlTHaRuk9tY+pDPacW9YPplbnoZiMRQghpT1gWg02EFAuhEDB2rF2mlB7JhVbxRv7tb3/DkiVLsGjRoox9W7ZsQTgcxl577eWo79WrF7Zs2aLtb8aMGZg+fXpqe+fOnR3c6aKTiVEdyjq5GbkuBF8ze9WHTi4PmrLb8VD6Ss30tRfDFj98Iy7SeeHkDFE7U0k/Q1e0z8xySmcq6TKbhDSf3Kd9bAxdEvXmbCY50KI6IUQ9pHpIbeNSO7kecARrHNuQ6tSyDp3zzDSzV2zLs3j3IP0+6rKZolIfUTiznJL7AlGgLAKk5fViSISCCAa7SDN0EwhLcjAmuTw1s0m4ZIC0RJ6awZRwvAjpvhKQZgcH40iUJevjoeRM3wgQD2RmJ4nXQ5Qh1ZnKon2ZcpyuvUDMDE69x/KC2aKhnMFkcsg0wJntREdMLnCGL8mWfNs9QGe1fXR2jdhnKqv2TwtsH/UYN5tI18aU5VQGoKwJ2UjniYxtO1PJOzspnQml2jjeWU7yscZsJp2942b76OydbG0fv0kqqp0jv0dI1u1JltXsbbletn3EdUk2DuJ2wKk0CESiTQhHmpAIlSAYiRul83RZ13I2k1xOE0uVVHtHZD2Jst0mB0m9eKk+G1ugy1qSX2dTZpNsB8FwrGoHaW0fIZFXinQmt5x+Zcrw5pdtLtDuIYQUmv/+F9i0CSgtBUaOLPRoCCHHHgv86192sOknPyn0aEh7I+9m4IYNG/Czn/0Mr776KsrKyrwP8EEkEkEkEvFu2GEQP6506zWZ5PVK4ZTXk5wtJueITurFzYHix5libJN2snTplnRqRGIZQSIgcx0lWT6mi0Muz3agdEFDxhpPpsCTWz+RaAxd9jSnZ+0KB8RuuAeY5HrAGZxSM4Pc1mySs5wEuqCTG7JjRd6WA02izrROk1p2k9ELKvVdkZbX6yrWPGhGsOsuhCN2gCmGGIJJ2aMg4tL6B2lZGVUuz1lOO2gAIJy65MygVdoR4wxsJSLJoJXO+aLKyQhnCpDpiDGVZeeLSWJG54gJSW1T6zfpnCk6/RvA/h9gkpshhLQGrWH3ALR9nBnaOm+1bo1KTaBJlrDTBZnUelN7P3aQyXYqa0JJUjY4UhZFuCyGYDBT8i49QaZBG4RyCyT5kdorVybaaANP8hqVwg6SbSI/to9c72b7mNZvAvzbP252j7xPbMuTbrxsH/Ee7pHqk+9panINmhHump5cEw7a0nmqhHAMMYh1l2QbxxmciqPBkcmkD0jFEEkFldzk9VIBLEVSLxEPojkeSk+yUR9eQSjAe01Lk+1jCkg5Ak6yPF4cafvHFLUyrXVJCCGkvSCyJ446CujSxb0tIaT1ERmGzGwiuZD3YNPixYvxxRdfYMSIEam6RCKBt956C3fffTdefvllxGIx7NixwzHLd+vWrejdu3e+h9NuCARqkLkOgRxkEnUq6g8tw1uqziJ026ebdagrq+3Vh+McCZRIUh7BkF4OLSQ96+VdksdDlokxy+XJciVqP2I7krA9H+HG5vQ6BPJDldGTZ/GqThOd80V1xIj2ot60hgGQ6XTxQrQXr7/srAlp+lf7NQVQhFNA9CG2ZccBkL4+sT9ouw3Cjc1IhOzXPhEMIoxoanaumLWrysGI91ptk5aJCaacL842cYcTRm2faiM5XkpCCTQDQKjU+Rq63f/w2Geqi2vKuu2MHfJi2KY2gPN/QRMCgTsB7ALQBMuq0Z2AKMSDAcSDAe+GWfVpAbDy2icpDmj35E4gcCvSk2VMJqlJOs8D0/9wr2f1eJNNZDqnrgw4JFyDQb3kHQDle1Anu+aU/FXtHLV9OPnFLAJTmfJ68dQ6TfZalbZcXqlJTtfL9tHZNKbJNXIdNPWizg1hh8g2SlDZJ/ct2kCpl/uT9wHO4KNmskhpFEiEmhGMNyPeNZiyQUQek13OlLmzD0/bL+p9INsv9nM8o71qQ8kZVTZh+1xSPCoYSqA5FLcn2MjX5VaWrtfxLLfT2TW6ftT2RvtHoGZs68pOAoF7YU++aYJlXePWOQHtHkJI4aGEHiHFxejRQDAIrF9vPw44oNAjIu2JvAebTjrpJKxYscJRd+GFF2LQoEG45ppr0L9/f5SWluK1117D2WefDQBYs2YN1q9fj7FCFLJTonOmuMnEyDN+TfVStc5hont4zc51K4ttKPvKmpKBpgRCSdkY4dyIpJwgzpm4Zuk8/eze9IzedFmdxatmNolAU/nuJoQSSYmYPUhnLe2BPptJbuMlqecmNxPXlE1OF8Djhzgyf/jrpGR02UyiXOZSVjOYGqV6cf2qvF483aa0KxBKNCEeBNCtHsGge9ZSZr2+jf0ymbOZ0jJ8wVRQKiT6CgKJYAiJeBDRRjt7oLmsCYCU3SReOzk4qGYtQWqrk85zk6GR+4dUH5c35LIu4CSX5UyoBkN74kUiFEIilF+nSyJkweQUI+0b2j0tQWe/iLJOOk/d52H7yGU/dpCpXmf7aDOY1LIFhOLJrKa4bQOVpW0fIeErbJawo2ySznPaQYDI0tZnhIv2qiyxnE1uB5k0EsIim2kP3LO6hb2iZj8BzkCVHGhyy2xqSVa3+j6qWd3ydgjp7G3Z3olK9V2la+kq1ctj7gqUJb/7g3GzhLDOxpEzm5DqOl0OI40sJxw32j5OST27vd1LuMwOKsbjQSTKYvYkG5HhpMtmMpXdsrdNdo0pSKU1T0w2jmoUC3tHF+FSy8QN2j2EkELDYBMhxUW3bsDw4cB77wHvvMNgE8mOvFvh3bt3x9ChQx11Xbt2RY8ePVL1F110EaZPn4599tkHFRUVuPzyyzF27FiMGTMm38NpR8gOFF0wySSd10XTxrBegS4wpAsSuTlaoBzrKqOXdrKEy6IOJ4suqOQmeefWxhRUKke9wxHjODZan16HQASVZGeKKIt61fliCkJBqldnAKuBJ83sXysOJJXd0JT87RxXnC1Nynap8ikOhZz1oSAQ0DldRAAJyAwwyfIxssNFF3hS12/qKtV3RcpxE+hqjymUkNc5SKTkZmxXSRet88UUhFLXbJKdMmLNA+faT3FHECqBRGr9png8iBjgdL4AaceKKKvOF6+AlFuAySQ3k3qPA9LBJseKWm6S2unaEELyCe2elqKzcQD9P0/VRvJh+7jZQX4DSXApq7J7KZvIXqeyJJRAuCyKSFJGLxw0T6gxSeG52UGALAmccA086ST4uuxptG0h1cZRg0rZBp7kslvACdDaQylymWgj2zmiPiKVZXtHtod0ssF7kLZ95Ik2su3TCKCbfaibhLBYr9IpIdxFsVNsGyedmSSGnWnLCEySehntk9cZjNv1MQDN8QQQL7OvQbZl/Ng1qi3jZteYglC69hm2j0Bdm0n+/5CcLKQNSBFCCClmvvoKWLXKLo8bV9ixEELSHHtsOth0/vmFHg1pTxRkytfvfvc7lJSU4Oyzz0Y0GsWECRMwe/bsQgylyNBN/XOTjNFNE/S5Wzfxzy3QpLZx6yv1SP/ACyUzm2zpGL0sniAo/TAMOeozZfJ0MjQmuRnHsUmZmEAjMtcViCvlhFSW26tOFtFW53yBpqwJMjXF08GlVLBJBJ+gpyG5P+WeE8eJYFMIKE3Y9YFQ+pyen37ZzyEcK5COE1lNQam9CDKJsnBYCAdDHAgE7XRcoBnBiFPyLoJo6h3VS8nI90wcQNjxvorsJXnGsAhBpftzytAEg4mUvFF6SW6Y73XZWSJvq+3dPmNxOPvRtdP6R+SDTXeEU0avQP/m2zWJYBCJPMvJJIKc4duZod1jwvT/KUfpPF2Xuv/lcr3bv0id7eOnnKREls5L2kC6IIJsu6h1rraM47sxNwnhYBxpCWExUUa2faDUyzaPn6xune2jBpXiUns1COWFyKy2Xzj7odo5qmyeihoAiSv18levfB55Ww7QKBLCCAopX7P8Xbocd9SnJ+BkygPL/cjIfcp2jS1l7GxfEkqgOWQBoUDmBBqTXWOyZfzYNeprqbbNKjbkR1KPNpAfaPcQQgrJZZc9BuACDBoE7Lefc19tbS0SiQRqamoKMTRCOg01NTUIBoOoqqpK1R17LHDHHcDTT2/Bvvvex88h8U2bWOBvvPGGY7usrAz33HMP7rnnnrY4fTtBdazoZvfqJGbU+oDzEJ0jJB8PYzaTfK5EakavczHs9Ixb4RBxLmKdlndRZ+XKs4FFhpTIYFJn/WrrEwmU726yF71W5fL2wDlzV85g0pXFsX4k9SQHjQgsNTQmg0sJ+6eYyEcRP8vE721120QqPJn0IwgfV2nUeceUJ2fulpchnfWkLoyty2CS64WsjHDqiHIcThm9rtLgJedCaQIoDdpyMw3dEogH9bN1TbN4E9LsXWemUjB1nGhvzyJO70/AXrQ7DrHmUzC1eHYqu0nM9FWDS+Ia1Mwm8QaIspfEjFc5/QIgPcNX3iHP3lU9QWJ2L2X0CCkUtHuyQbVxVOk8uay287B91P+rXnaNVxs/x5YBCNlZTcHkWpWRshjCwfTaSZkZ3mn7SLQxSefp7KBWkxDWZTPthj7jyW2ijToxRw5awVmWM7xlPLO6kwGngKjXyQbr7B1dNpOwd0LStQhbQNhBYsxiMo5s7yTbpCWEm9DQLZG1hDAApZwpD2yf0ikhLB/ryOQWgatgPJXVnYiH7PWbykJAPODPrvFrywhbSTVTQoZ6R/DKZPsIxE1UqpSFRS2OZbCDEEKKnc8/PxAA0LXrEgDpNVBra2tRXV2NmTNnFmZghHQigsEgqqurASAVcDrmGHvfli090dTUxXQoIRnQA1k0yOGAVNhAejbJ6MlljYSMTjoPWZbdAkzGwFMTSpNrFAgni+o0MTtEnG1SUi9o0DpT5PoMuTxRn6hPO1bkQFIjgJ3J692NtMNlT3JbXadJdrLsMZQVSb36ZLmh0c5CEkGlhmQTe/nidKBJDjLJP5H9BpuAzFClfJeUJx065VIQqjxoB59KQ0Cp7HwR0nnC+SIk8vZI5d2w5WN0EjPCESNmMcsOmlAy4yrpiAl1SyAY7JJymOhkZQRmp0xIcriYnTVyfcpZEww6nC9N8SBS6zepMnpyIEmuN8nruTllQsqxGcEmwP5sq04WXRhSnhJOGb1caUYQCeR3hm8zF8kmRINubSa3f5jqek0G20dno3gFi0zbJjvIOOnG/t9cWhZDJBlwCkf0do3fdSlbVUI4ikx7R2fjuAWhILU31YsJN8n6hqhtF8kTbgDnt1u2qBZ0efKrv7wsPdEmIOwawLkGk04qWK5XbR9ZRq8r/j977x4mS1Xd/X9rqvoyM+fM0YNyQCSC91u8YSDegheixmgkt9ckRo0xmhCNmqNvlOiMwxkUNQkvMTESMUZ8o6/kJQaNFzAiGIkKCUr0F1S8AYovB+HIGTgzUz1V3b8/dq2qtVftXV090zM9M70+z9Ond+3aVV1nuqp61V5rfZftkCLbJwWCuL6EMFDPCeWT1HPJ6LmcUACQtsxymqRIkxDd/PgbtDHYjso2Tp02IR1VrjHOfpftwzeQ9wfufAKKoBulH2r3KIoySrpdo5137bV/iYWFB2J2dtZyNPFMC0VRNga6zrjD6YILFgD8BoAH4SlP+ZPRHZyy7VBn0wgJgnlkj8OwZzngeAdbpgkW2d8H3/yN3LVsVy07D68HZNG8JJ9XyKAVD4q2dB6Xe/FJ5PXrd0vMhEgRJqlxNPGIWhllG4vl1NHPJfVc9QmoP+tbzSZTAONo4o6lZQCn9EbzIHZ1YB4o8wDSbJKJpPcatJJL55EDKWFtl1wenRP879z2jwmSbPeJifoFAC4ZY8vNJOxcsiX1fP1ceoYoyzZmUntRiihLCVuNUpgCWOLh23XeW39MNsaXfCS3kWNr+4aqDiSCzGoKgnNBZ2GvN1/3QxRFUYZGELwDhe3DkSETrrakwvbx3R59NpBrO1/btc7ab/Z7RBLC4qZeJYvnkhlei4Swc1uSEOa/z9yO4XUmub3D7aKq+kuurCVmK/VWjJNp6u4eplBUHd0slnYFmAT7Vefye1Iq2NUv7SAaG3vaNA7mb+6TEKbvq4XYcjrVtWvoPOiwsS7ZPaBZckjROdqNUiCr5VTLxhmkXWefa0LK6AGF3VM4noLgPShsnzes5wMVRVGUIbO8DPzHf5j2a1/7M5ib+yOcffbZ6HQ66mhSlE2GO5zoOnzsY5+Hr34VuOoq4NnPHvEBKtsGdTaNFCmLx/td0b088tfVL7rrvupE/VaNtyJ9i4heX50mO4o3dkb6+iTyXP08s6mJGJN51G8Hu+O7iijewygmQOq0pbyeL7pXRACvxsDi3SZadwnm8ZacS9zZtATglPJJsSn8EGaSh86eSQCTqZkfm4yzdSEwsyvLdKIJF1d7BUWkL8/q4W3AlrSB3Q4iYApdAEtIozCrb5CyKZM0ny4DZHZSmp9dXFZGSu0VZ6Hp5/WhzLkXIg2jvH6TqWOQ/Qfa2dSU/D/JzCaXs7ZKUg+O8bKdwLOBSyJPOph8Y5QqEoRIhhzhm2iEr6I4kF4fl3Qeb/vsJtbtcihVveqM4faOHG/ZRD1MtDsIozTPaqI6TXVk8QaRzvNJCPNt88ymNEVzZRXtAWyZku0j+wG3pJ5oU9DNalIE3TyodB5sDgePAFNHgMns+HdPA4HMcoocbZ6xTfYOlxCeRmED8HpRCSx5vcY0yf+tIGoXEsKAnYGdsHaTHX+VhLBrObQyoByyey0gTUOEUQK0YTKckghYyX7/XDZOBL+9U9WGp+0b47V9ir+Sncnk81pFFesUQu0eRVFGxX/+J7C6ChxzDHDuua/C3/zN69DpdNBsNtXRpCgjYHZ2Nnc0NZtNvPKVj8Hv/Z5xNilKXXTWcaTQZIlLFg+oltGT/aJewVBrD6CPgykb3zYZTRNZVpOvTpMto8cnR2I2OVJ2MPF+n3ReMfmSYipewtSRronglZMmh2FPmpBEnktGj8bDsZ+svXQEuCubvFhE4VS6i7WXHe1RcRPM1zcJ5mzK2rupnQKHDgMzMI6nyTYwRZMs07ClZHjdAld7BYXUHkVSC4dUkADTSRe9qItw+i6ErUJWZtmaMJmyJmWkLJ4Zk4iJl2KChk/ieCdffPWbAL+DadBJmbr1D2ifef0C/iGAPYnC+33SM1WTMoqiKBuNdBhJmwewDQ6IsQ7bR25Sx5G0Fum8ym3tOk1hlHolhH11l9YqIcxl90r9R1YQJjC1Kl32jpTOk+269S2zdi8x2Ut3HSnbPhR4Mypn003I7B0mJ5zbPtPCxuHOJupvobBfKNAGsO0aGYDjkBNuJ0CYrCKNVoHpIrgmRIolTELK4slAm34SwkXQjb1tYSOVJYTjzB7ptrNoIlm/ids4dM7z7PV+bbD9+GwfsHa+jbR9CF8gjS+dSh95FUVRtiI0gf3kJwNnn72QT3B3Oh0sLCyow0lRNpmFBfs6/NrX/gbAH+Lqq4FOB2g2++5CUdTy3rrw7CWO66msz5C6UYe+dfCMcXzmBMnm5RlNSZ7RJGViOFwCxtdfTzrPlotxSsVwSTx6SXmYFdHm+1gp2r2s3sDySlFzYBnG4fTkEUnk1WF/jWO7ikntNVKgkUUoRwkQhCgkZHg78rRpwgEo/uZAERWcwEziJGZaIUyMzAwA67yw21I6r2gTtgRf+dyi/ZTkbEIgilKkWZZTN+oBkSPis+p64JMlVfMdvomWvtAgWd2LPrgBf+ULvfVXYc6miSHvszvU/SnKzoEH0bhuqjVqrvS7r/a75fnuv779UttxuFJCmNs+wOASwta+PXZQ5OlvxR2T2c1tHtmWUsEu+4iPkbLCzLZajYHGnaORyKvDU2vYPqv3CNAguwaw7RQpIUwvLp3HbRzuaEntdmZeIEpTpGHZrpH2C7d3OD6pPZLMq5IQzm0fLiHMc6mqngW4fTNIm+9Hvks/Ud+4GJ69Te/UVgZB7R5FUUYFOZuOHLnMqtFENZsAqMNJUTYJWSvNLL8SU1MvwdLSNL7yFeBnf3bUR6lsB3TGceTQg5FLGkZ6fnz9IquJt9f78knsOTObiojeZruTPzTXkYmR2U88itc9vuOUzpvCcl4Au00ZSTKK924Yb1CdjKckG1uRzbSaDbkLRTbTUp9vfTtwEIXjrAFgMQZm4iwCOAamaHKFJqFoYiBxtFHRDxROqRRAi06pFaTRRF6k2zUVx6XzeD8AdNDM29w16cpmouUmr5eQncsAjJxelF1//aTzItFfJZ3XRvlv4Wtb2U18YgWw7w2+fogxio+NmXQZrjyNomxfyJ7hWU2AW06YZ3JLW0nYPv1eg4yV9o7ctpTZtApEKRrtDlrtDgCgGcYeZ1BqSQjnjiFPltMUlpi9Y9tBZB+VpIXTJYRJarK7fdJ5g8gG92n3EmMPLcbAfSu++e3AwcPAzEomsRfBZClR1hKX0fPZO6loZ9lMAKzf+yAhSb1VhO00lxAG7IztBCGmHBlJVt0lqz+1zjqyvV0SwrkzK0xzCeFGu2MshCQEkoZty/D/g7ymBm1L2wdiDP/bWrYPQfJ5DRhrlQfY0H1DZnUrPtTuURRlFKQp8O//btqf/vSbrBpNvHYMX1YUZWOQjiaAX4efAfDL+Ld/U2eTUg9p5iubiqxB4FqGZwz1OyRk6tRg6icHA0efT1Iv6gFRgglRo4BPiPhkYnw1BsoTKPaEy2SFdN704a7bYXQ3bFk87mByOaGk4ykGVo8U9ZgWARxC4WBaRJHZdFe9E2BLcxOYpB6AvTD/rwjAzBHzyus6zWQruHzMHthOKC4lwycZ5ERMljnWTgBEXWDPkpG2yyZPIhSSemZzd5sXZOcTMTFahUNJTNxY9ZtaWX+SmjoGAJBERlrGNfmSsPZaHE/92pakTIN1SLm8BGV5GTnhopMuiqKMErpBSieSywkl+z22z3qcR7LfZUd55YRNnSYAA9dpaorAmabTweTu99WunEqXMHn3KqIUxtHkCqJZS1vYR9zBxGWDt7uz6RYAh2ITVNMAMNNitZ2mYWwbkgfm0nmudsLaWTBNfmpn7QaAKO0iCbvAriUglHZNxNq2vWPXaAqd/Xw/fes3ZRLCaZTZPO0IQFC224ZRyyl3JLF+OMaXbB+wFSTOKPsJmfWtgTaKoihbia99DTh8GGg2Y5x55umYnX2ztZ4mutM0dW2uKMoQSdPUcjQRs7Oz+OIXP4NLLwX+7d+AP/mTER2gsq1QZ9OWxSej5+v34Ju4do1zPej5trEmYRIgk4zJXywHhSNzU8r9tiyeS36P+n3SeU6JGC4Pw2XxYsc4PoZkYrJ1VOCanEqr2NpyeevBJ7V3VRAUU34pMJkADfo7tlDIx6wgz0pCDL9jJmFjuAMq248tqZdkcbph/v2b/uJcK/cX8jRGVsZ9bsr9hEgQRkWWUzfXvGn0v/zkRIprvFxfV3qmtAMpl8dnaNSptBY0wldRNpIasngAbIfUAJtU9UWOd98kt2t/FbYRZYb0kxDmWU72rlPnb1OVHeSUFk5S42iin4CqVyraUmpYSudl9hHJ5c3A1HXcSZzisX16RwVGQpgcRtxByaXzeJscTdQOHe3EfFcRgDAxjkqgLKnns3c62W58/bRM74U0Xw0JYVg78V9fPnunqm1lLom2a9mJzOquO16RqN2jKMoouPJK8/6MZ7QwP/9m5xjNaFKUzWF+ft677q1vfSYuvRT4whdMRmIYeocqCgB1No0YOWvBo3sh3vmEixwndrWeVz/ZPOcrzWo1JSKrScro2ZMjPjkYGfXL5WZ4NhOX5rOk83xyea5spsMoIncPs34xfvGwcTQdSotdHsp2P27cgqLgdwST7TWzYuRgZmhSiqJ4KWtJTkJ4ZGWAbHsizAJrM0m9tFVMjCDfnE+/peDTfP1k9wCglX2glOGLwOooREkR6cudTfzyrZLXg2P8Wtr5xEuVE9rleKK6Tq6DUhRF2WxkphJ/dzmYIjFGdLvum66Xb32VjVOVCRX1LAlhCraRwTBk4wCozHIqssDtzG8uLWz3e6Tz6mQzcXtH9ousbm5PLR0BDh3Z/hlMg3LLIWAvlxCeQfFbH7N2lYwe4LUJggiYQhfAUklSryz9W9g71F9kM5XtIKDIZkq4jcMcWHntJ5eEMHcOieMu2UGDZG/zZblPJ3JH3N5xBeO5Mr8VRVGUrcLnP2/en/rUkR6Goih9ePSjgT17TCbiddcBJ5006iNStjo64zhSXPUJ5GRKQ7z4JMw6ZGT6OZZc+5R1miIA7VU02h2EUYJWu4NmGOeTLG5HUieXvKtTj2nKkstbdkrG7I7vMpMr5DCiyRGXgylBUYNpxdFP7cNA7wiwHBuZmDtQOJjuYMMP1fmadxg3wvzfZ2Ak9u4CsDcrdn3UbUZuZrKVRVVz+RgexbqCsv4/tSkbCsjPvTaAXtRFGpUlZjpoIcVytnlZVqZ/XSc5iVOMB4AkDJG2s30mEVaTEEDDnaFVZ/Kl3Wd8LWcTXftSbooflJxwIckZve33QyN8FWUjkTPKLqlg3pY20Dol9NbqYKohIdxsuWtR8iynlqhjyR1M1D+FZY+0cGEHWbYSl87jQTQu55Er0EY6pIQN1TsMHDpsMrupRuXYOZsALDMJ4b0rQECOpz0oftOljB7/recBONL2icyZPYWypJ4t/VvYOwTv54E23CFl6wHYjipr/z4J4ahCQnitjic5xuVs8to+VKcJfAA7KG73uD5c4ajdoyjKZtPtGkkuADj11NEei6Io1YQh8JSnAJ/4hMlIVGeT0g+1ujeZIHgrzJ+dKuG46hMQLrkHR+Rev0hATxSlc70c1zfKsCCMXJIxZRm9ou0ez7NWzEfb0jJlyZhuIRfDJWGqJGNIJo9J5OWvTBJuOQaSBFiCeaQ9aYfK5Q3KGzx/h2uDAEswsnrLyKJ/yXFEf1dq03fQglter10eH8CWmAHMuZCK88YnK8PHlOVomvk++XjePxCu64z6pUzMoPtN5AKv30TQRIyk6A+Cd2XtBL3emwY8EEVRlPoEwTtg7j+TsG+Q/WStBpS9GtBuKW3r25fsiwApIQxU2TjFi1NLFk/YSq5t+0rnSYk8+g3mNlMM2yYip8nNPQQAjhrwz7nT8Mnr4f6BZTuW5ITpHCLHVBu21J4IXHFL6vltGS4V7JPd47i3tWWtyfYJozTL6GYZThKfvSPH+OTyXGN921odDfYu7R2+kZ35HQTvAQlh93pv6HPgiqJw3v3ud+PP/uzPcOutt+LRj340/uqv/gonn3yyd/ydd96JN73pTfjoRz+KQ4cO4X73ux/OO+88POc5z9nEo1a2Kl//OvCTnwDT08DjHjfqo1EUpR+nnmqcTZ//PPC61436aJStjjqbRoLPweTKXorYMp9BEdFiMqrQ5Sxa78vKbMoietsdqyC2nDQxWU395PJSK7rXLZdnZzy10MklY1oUgZugLJ3HI3cXWZvL6B0uj1k8DNwRF9lM45jBNCi3IZsziYEoBo5KMlm9quheXxSriPal/qmokJhJw0JSj591zczVFKNViuKV2U1V8nqUceeN9F1pVNehckX6VkXu1hlvTbgEjp2tsoF8knbZ06+yMi7MuaERvooyPOpI5EGMcRkwNbKa4Nm0zsu1jS/b2yEhTLZNWUZPZnLHrJ/L6PW3lXjmdxMxojSTznPJ5VHWUj/Z4LvFmBUAi8DSYWDK+50qALB0GzDls3G404kQUsGu3/sgApqhsXfiVhNTKGds97NlZNUwmc0Uowles6mFON9Ps9VBGoVIkhBpu4NuEsIrIey7dtaSvS23A1tXcjjBs4FxKrkZtMbT+KB2j9KPiy66CPv378f555+PU045Beeddx6e9axn4Vvf+haOPvro0vhOp4Of//mfx9FHH42LL74Yxx13HG666Sbc4x732PyDV7YkJKH35CcDDS2ppyhbHpK7/ILWbVJqoM6mTYc/ibkmX1wTLlJeb0AJmTpyMG1Pv/dlR/SGUZUsnl8uT06mtPL3fpJ6DskYksXjkyYeiTwcRiETc0cxntdmOpgNvwPqbKrDD1FkgU3COJ1W72C1nCjiF6iu2cTbK2xMu6hpkIRdJHuWslWFBIwtN1NMrMRo9XUw8ThyS0aP+qNsv1GKbpRmcng1J1980nmosa2r7Zx0IeRkipzc5f2u7RVFUTYCn0SeXN9gy/z+5bB9eHstDqZacnmsn8a3VzNHU4pWu5MF20iHUeFI4tLCVXUppa3URFxpB00dWUErhnE0uWSDj6Bcu1LUYLLGi6CbgzHwoOovdey55QiwLwFmKJubssIilCWEHdJ5vnYDQJR2ESYrwDStcts7Rk7YlRPnrt8ENNHKAnN4kI1V1ykEoihFmmXtdaMeEGXXYJWMXpv1rcXZRG25D/o8BAB6YoXMcnLVb+KGEx+jKEodzj33XLz85S/HS1/6UgDA+eefj09+8pN4//vfjze+8Y2l8e9///tx6NAhfPGLX0Qj8ySccMIJm3nIyhbnyivNu0roKcr24DGPAXbvBu68E/ja14DHPnbUR6RsZYYbwqSsE3ooqnoAEuvqPLS5luFYlmPl/qz15YheDn/cNZvYch22JF7xiFysLz8y8xjNKHVIxqTs5ZLO4zInsVhOgF5ipPOWUxIXA57a6+FXez28XCX0+vLy7G/11F4PyzB/w+VMjrAnZXpWUP4u5Hfl+U4D4+dElEp5odR57gCFvAyNpz5+Tkbg56dDAjJM88LZE9nky0DXkGuMa5u6bQClDMfSvcN3L3FNxCgEFWQf9mstvPvd78YJJ5yAdruNU045Bddcc03l+DvvvBOvfOUrceyxx6LVauHBD34wPvWpT63psxVl83BlO1Wt9wyrsltcY1zLvM912WZ99HsA2BJmBP2OcPvHbG73++TypNyZyw4KkxrSeVw2L0b5t3bFMf5gDzMrPTxIbZ++PKhn/lY42CtsHJeks7R3fN8TewUJECbV9g4A65yRtgxgn3N8nTxnidxtxex8E2SG/nZPVV+dn0F5/Tq3cWXM1HmGItTRJFG7R6mi0+ng2muvxWmnnZb3TUxM4LTTTsOXvvQl5zYf//jH8YQnPAGvfOUrsW/fPjzykY/E2972NqSp+74DAHEcY3Fx0XopOxNer4myJRRF2dpEkanbBBSZiYriQ2caNx3XZLCM7uX9/OGp4uvqlyXhi/h19VVFAEcAol4e0Rvl8nl2RC+fMCH5F4rcpQfeZiax54oGtgtmSymZBJN3rxaSMZShRNG6PMupSjqPtVdjU/z6DhgniUrnrY+DMLkzqzBZTjgE7E2BRosNaqE4B3ldA97fhjMDKoiAyXAVyZ4YKSI0EedTLU00QRG9nawdIkQHrWxchCY6oEjeVrYtADTRySN/uYxeBy3jfOKRvu0OukkEtIO1y+j5JkWTPm0Ll1wePxD5AVI6TyddJCkm8nNiePscHJUsUXYOrhlkl2wwf6+oaVnHrqka59qu9qsHZJPwEdlCzMbhMnp2fznLydg/1dLCPjuoubKKBknkkQ1Etg/vl5nfZDPJTKjMJrrjDq3PtFYWDwMztODL3hYZ2/k6LqlHdSsjoJEAabSKZLra3nHJCdMYQzM/n1JEuYwet4HizNbJ5fUyOx8AVqPUzDIgKF9HvmwmsHbkGSPbPhk9+pvlSElgLovn2mDVM0YB1O5Rqrn99tuRpin27dtn9e/btw/f/OY3ndt873vfw+c+9zm88IUvxKc+9Sl85zvfwR/+4R9idXUVb3nLW5zbnHPOOTjrrLOGfvzK1uO//9vYG1NTwOMfP+qjURSlLqeeCnzqUyYz8bWvHfXRKFsZtbQ3HZpYcTmSeH/kGRvZu6p6yTFV0jADTbQU0Y7NdjEhwtXj+9UkoPVVdZqaiDGFZUxhGSES046XECZdM8Eiaw+45PJokoVL57F277BxMi2nxrlE0nkHoc6m9XALzCM9V49ZPQxMhsBeisQmx5Nst9mOYhQTNtwhFQGNEJiKVpBGE0hbJCtTRFJ20MIklrLdtDCVtaUTqqq2ATmemlmRhRQp0rapYwAAXSqanR1TLafSsCT1Er6BSy6P71jKxzhnbpQthkqWKDsLbvPwZW7vSLtI9rPuOnbPesdxG6kNoL0KRCka7Y6Rz4tSNEPbkUS/JM2Sgyku9bcqpIUnue3jsIPa0qnEnUfkfJLSeYfgdDDhsMlAPnQYOJiqs2mt/DAG9t2R2TkRiqwl7ngiG4cynaifB9qIuk7tCAD89k5hx5izjWo8mWCZTtZOc5uG7CC5LXc8pYiQhKE53pUmGu0OVpPMI0ZBNmSLkAONX19tT/+gNo73SVWucGVsk31UNUbZSqjds3Podrs4+uij8d73vhdhGOKkk07CLbfcgj/7sz/zOpvOPPNM7N+/P19eXFzE8ccfv1mHrGwib3jDpwA8B096Urle08LCAtI0xfz8/CgOTVGUjPn5eYRhiNnZ2byPMhE/85klvOUtf4azznLfzxVFZfRGTp0HHjlB49k8ciwPchhV21vtIqLX3oVbpsO0k3w9l/2Q4wi+HR8TJl2ELrk1nwQbl4eJy+0kNY6mVRTSeb/Q6+F3ej3sV/mYNbO/18Nv93r4hV4vjzddhflbJ/Q9kdyMlJFZgf1d+iRpYORlwqRbeQ6ZdmL1SQkal4wj75dSMxHJJ4lrwIlrktM1xrWNbLvGAnBnJ9X9MEXiEmYcxgtASR4kjmPnMWyWZImibA4+iU/XvWuAbMu6907XfdS37TpukfK3hfcXH5OW+n3SwoXdxGSFyQ7y2UKyPxbvjjG9BAju6OGopIeHq+2zZh7eM3/D4I5eIR/ski2sY8OKfpe9w88Rl1Swea8+9/iy7MvX5dLBmZye2Zkb3zVU167xjan6zMqLVmZQKi7U7lGquNe97oUwDHHw4EGr/+DBgzjmmGOc2xx77LF48IMfjJBVkH/Ywx6GW2+9FZ1Ox7lNq9XCzMyM9VJ2JjfffAIAoNu9wupfWFjA3Nycdd4oijIawjDE3NwcFhYW8r7HPQ5oNmMsL0/h9tvd939FAdTZNCJ4tG5VvyyUDZQKZPPN5G6G/Wr38qLYJB0ThmmehSQjenmWE38IbmYZTRTd28rfTcbTFJbRyrKaqDB2Cx200hitGCaraQWFLAxF7/IXZTh52r3DwOoicPCwCfS9DUVmkzJcDsL8felvfCj72/cow4y+n7tR/g7l9yokgRpHgFYMc25k54p5LWeZcx3r3KLzkZ+DLXbu8ih07zkdFhKSE1FqIt3bvTVkCNZ8EXKiJicQg+R9wzVj4+tXNprjjz8ee/bsyV/nnHOOc1yVZMmtt97q3OZ73/seLr74YqRpik996lOYnZ3FX/zFX+Dss88e+v9DUQbHJ4vnsnX62D6u+2HV5LW0l9b8KterbOWZ2sXvB5fCo8wl+u1psn4uu0fSwk1hE7X4i+wgsnvod1PaQYfZu/xt5XbR4SLDWxkuhw4zO4dsHdf3I/vo+xTfcSMu2zvSxqFzh+xusnHKsoy2XCPP626yczliNk9erzJKN86u8V3LTnPFVbPSdS/hSBtJ2QzU7tn+NJtNnHTSSbj88svzvm63i8svvxxPeMITnNs86UlPwne+8x10u92874YbbsCxxx6LZrPp3EYZD3o94LbbHg4AuPzy2XwimxxNBw4csDIpFEUZDbOzszhw4IDlcDrnnAV0OsZJ/JCH/P4oD0/Z4uhM46bjmkjhDz9ymY9lX1fdh7k1OZU87SyTI2QvuwZTVb0BV20m7miK8wfcJpPUyydd0rio0+SqxySlZHibpPPuQC4Zw6XzSPKNnCLKcKG/b16/CYWk3lF0nvJaTvz8XWHLIQr5GV6/KTX1m7BrCXFIdZlChEhyyZgYzVxWhiT0UkQgiRkSPyqmCY3EDNV2itGCiQg2+06jop5BN4/4bdgSeWBt32SKr53UHG9J6fEPBMq1nPj9JMnel6GTLmUoj2C4+zT84Ac/sCI1W62We4M1sBbJEkXZHPjNS9o7fEwE2w6CPcZl28jlYdpElj20mterbLU7aIb2JL2UwiMHE0noFZLDqccmcterJGlhyw7icnkkhcelhX22kkrnbRoHs7/zXmSSegT/aeG/5bxGJZcQDotxVK9S2jtV9Sq5VDDVcuIyemTrAOa3z2xrzmWS6UvCEJ2oaepVAuhGPSAK7P8DUC2dJ//Pg7RlrSen7UMss424fSNlg/URmKN2j9KP/fv34yUveQke//jH4+STT8Z5552HI0eO5JKHL37xi3HcccflzsQzzjgDf/3Xf43XvOY1+KM/+iN8+9vfxtve9ja8+tWvHuV/Q9kCfOMbwI9/DExOAv/zfz4Hc3Nvwtlnn41Op6OOJkXZYtD1ODc3l1+np532WXz2s8DnPw/oLV3xoZb2JhAEb4X5U0/CdiLV+fO7ntT6DOXLvr51fPM8otfsskJ6oyT10V9aJoJdPSeXlyGJEaA8mZ962g4pktXYls5bBfBLKhuzYbyJ/W0/HgT53xyp+S4a/Lvk9Qvkd8zbkd1H/h4eVc4fmvtJx8j1aTZFU/QlmfsqczJl534YJVjFOqLzfNfhuu7MtPEy6yMHEx+T5P1B8C6QkGSv96b1fLjSh7qyIGuVLGk0Gl7JEo0kVTaTIHgHzD1mEv0NjwFuhlW2jm9S27Xc72MdE9+U4SHhtkrRl1jrZb+UHOYvbgdZ23D7BnDLB6esXUc6D+po2gi4HGHvqMDUqvTZNfw7o1OF27wo2i57B4A4X2x7O0KaBdgkQGaz2GPL/RJ+7nvrVfqwgmMc4/td/nL7vh+22ncUAATBe0BPAr3eG+p+gDIgavfsDF7wghfgxz/+Mebm5nDrrbfiMY95DC699NI8E+3mm2/GxEQhmnP88cfjsssuwx//8R/jUY96FI477ji85jWvwRveoNfauPP5z5v3JzwBOOusP8Xb335Wfr2qo0lRth6zs7O5o6nZbOLAgWfgs58F/u3fgG4XmFC9NMWBOps2jX7yMXKmRM6QALlkxCBRu77xVfvxvCayYthR5miiqFw+OeKO6C1k9Mw2RQFsW9qMS82w4tlxB82VLgKK0qWI3rtRSI3cjSKbifpJtoRF9FIU7yGYx0uVzttcDqJwtU4CaBwGjg6zqF+K3o1RnKMtFEWzQ9ZOYEf7tky0b6edotPq5M6iDlr5lF2TZTDxaOAYzXxyhSJ5m+ggRgstxKVI3w5aZmImBKKsUPzqStNMvKwlWtfVD0+/q50A5t5Anats0KpjxwnsiRjeX3s2Z0fTzc6Z4e5TSv5UwyVLTj/9dLOPTLLkVa96lXObJz3pSfjwhz+MbrebP/CrZIkyWui+5JMNBnuXgTge28c1RPbVcToNZAv1wOtVhlHhDOIZ3mTzcAnWIlupnPlty+i5bCKHHRSjyFqiZZJc4xlPK472YTOGpPPUybQ5HKIMJ6CwZ4Aicw4oAmnItqFM7hbMd5eND1bK9g7ZLS4bp5VlObUoMzs7M8nGocxtk93UzM9LViUMAHL7HwBWoxSIIvM/qmvvVNk+MnNJ9vPxhNP2cd1LVsWGckf1nVM7GbV7lDq86lWv8n4XV155ZanvCU94Ar785S9v8FEp2w06VZ76VCOdRxPYnU4HCwsL6nBSlC2GvE4vu+ytmJp6E26/Hbj+euCRjxz1ESpbEfVBbgquhxw++eKacJFyeo56Bbztcib51ldt53u1V/OoxjBK8wmQIrLSrs3E6+FwDXmqO1C07boFRoO+kNSbSpcwdaRb1Cfgkycu7Xuuiy+08hcPA7cdMmp6B1E4mlQ6b/O4Dfbf/g6Y72SR127idQtcfdQW50QjBqaOdDGVUh2DOK/hJOsWyFoY3NnJJwF9tZzyou3ZNdFod0ztpkGvq7Vcv74J1fwe4ZLidN1jSjtwLCujZP/+/bjgggtw4YUX4hvf+AbOOOOMkmTJmWeemY8/44wzcOjQIbzmNa/BDTfcgE9+8pN429vehle+8pWj+i8oY41LNljWS3FJCPN+T51Keh/knrrme3IPyOrVDFqvUv6ecMeTuzaTtImWy3bQ3XDXqnTZRXejZCORo+mgO4FF2QAOpo4aTrKmFrdzXK8YVv0msnemsFxp4/BzzXUutiCdnDXrVUZJdm1g+C/0WWfBbR96l/cSsD5XzSaVE94qqN2jKDubXq/IbLrxxgvzGk1xHJdqwyiKMnp4LTW6Ts8668049tjvAiiuZ0WR6MzipsIffngfHP01d1e1zvdgttbJ7QyK6M2Xs4he0y5kYKxt8hjLQhLGJRtDY/NMqCQtpEe4PAzQXzqP+jIZmdWkkM5LAPyCSudtOlxS79NMUi/i3xtQSP+A9Udwf/dRsUxTDvL847KMlPUUIrHaZjsjJVMsl2UeeX8Yidk6OUniShSifu/ESUW/3EcJKZcn17mid3WSRcKjuYe3z8FRyRJl+zOIbHANpMOpzlhq+/zrVfdiBq9XWZbMK8uWyX7+OyOlhSttIp8d5JJlk3aRkGdT6bzRUJLUk3J51E5Em7K4HdKJAcy5gdC2cQCUbBwpo+ezcahGk8+GJ6m92gzdxvGt99k+VTYRHcSyZ/14oXaPoiibwTe/CRw8CERRgve///etGk28NgxfVhRlNHBHU/k6/TsAb8MVVwAa36G4UGfTplAln+fqk9kHgkEj/wYdU9pGyMeEdjFsV0QvzwihDCjKBuFSezyqsoisZFGWK93C8SBl9Kjtynri7dhkzhxKVTpvK3EHCvfrZGok9WYiGMkYKpTdRiGdl7J25Ohvmfbk3atI9sQOWZlO/iBNsjFAjBjNfFKPS8nQtgBySRoak9KETlghKwO4r6tELMMzRvajom3BJ1CozWeq+IZ8kkV/DrYiKlmibF9c9xSZueSzjSruR/3sH5ctI7cfJNgmSnIbiLKayJ6JLNvH9BfZSzLLqY60sENST9pBUjqPJIRlmySEKStGpfO2BIcOA0fRecdlgiMUsnohaydZ+wgKWyezd5orXTRbZO8U0nnNzKomG4ds7U62Rto43B4n2WDqt+yjVgcdNBFGKboUbFMlIeyTCvb197N3qgJ5LHunSiq4gXJNS2UroXaPouxcPvc583788TfjpS99U8mhRMtpqunXijJq0jS1HE3E7Owsbr75/Xjf+4ArrtC6TYobnV3cNFwyMbIfbL2rjhPKD191HE+Dvtp8uZCPaWU1m7h0nozCbbFJFy49xidZWkzKgxxN1M7HpDHCJC1kY8jBRJMsJA/jqtOU1SQguZjlGLgjNg6mBIWMmzJabkNxpk8CiGIgOgxMtlgNpxh2nSZX/SaqZ5C1Gy2gFXeQRimmwqU8n6mT1S0AkLdDhOhkdZqobSZqkNUz6GQlpIqIYXuCJkGz3QFWmpiIUlM0GxEQBeY6oslB30QM4K9V4BtP7cTRRoRiksWXRckdT3yMRvcSWyXCV1G2P3QT89g0pTFwj6tyIvVr13VIeV9pIaEXlgNqbMdRx2kTyWCcptMmEu00RnNltWwH9WtLqdnDpn3HHUbOTZ1No+UgBdcA5QAaCrSJPG1uL0TG3pk6soJOu4FO2LRsmRTLWRhXB7J2JbdxpH3EbZwWC7TJz/EWkCYh0iREF6h2Ng3ShuiXfb7lvJM7mBqefjKY9PFXonaPoiibweWXm/ff+73740//1J25pBlNirI1mJ+f9657z3t+FxddBBw6BPzXfwGPfezmHZeyPVBre0vh+jocEXfy4cy1qWuMbz9y4sWBlAvrJ51XJRPj2qa0nKQIk25ZIsYlk8fb4n05BpKkGPZUlc7bMuxn38WVQWC+owRIIqDhkpKJYPtJuMQM7DFh0jV9oU8OppDUM32JyFwq5Gb4eU5Ecp+ZtFLX9R+tmmRZz5yHd7u1RulWyc2MFykmNmDSRe89ilLgMzqor+I+5puIHniCGm47yHr1MJHd3zkum6e/nHCR4e0K2OHjSEYYgP2bR+8+GWGXpHAM4KBK520VuKQe9gVluTyfpB4/nSx7J7OZw9SyZQB+LhYSjsV5asvi9ZMNltA10Y16JsBG2jN1nkM4VuDMWsZX2T5VByIdUuOJ2j2Komw0aWqyIADgGc8Y7bEoirI+ogg49VTgE58wTmR1NikSTXbbFFyzHq5sJt82jgLZ1HYt+/rW9CrLx3AJmJaI1uURvS6ZmCLyt5DLa7LI37xvpYsWycTcDVsyhtpcKs9THPuuIyar6RCMbJuyNbkD2XcUG4mZvsWypYwQnRdZfyvO5GWs88suks2LYXMJIzqvudQjz9LjUe0RiqLZYXatmGsG1ZH0qFhfFXXPt3W1+b2iNMh1z6k7I6soijIoLqlgae9IWT1OYC/K+yI8bd+9s879FnJ8kt/fKbPb5TCqsoko+yli9hHtp5X97rRy+ydGi36rVrpo028b2UE8Y0m2+WsReab34mEoW5RFysbn35nP7uHfNzsnGrm9w84ddk4V9kxinYMRigw7n41jZ+MV++HXhCm6CXdQDUTfILYRX5btSlNFOqx5lpPrHgTHsqIoijJsvvpV4M47gZkZ4KSTRn00iqKsF3IaU8aionB0ZnHToKenKqdSA/aEi5gMrjuB4urr9/DmfbnlY+wXr8fUYe9FzSZev4kmY7jETCt7SA6RYipeMrIxFJHLaxW4HAzkmEjs/sXDxolBdZpUOm/rcgjAFMwptwxgkuo3JTATMNTmknok99iCOTdaRX+wAjQioJXGSEOSgzEyMUaZL85zm4x8TATKYjKiM0U9gxSRVdeplUnSAExuJgSi7Frxysq4SiZBjHG169Y2sKT0kP0l6V4iazbVkZsZX5LsTjfcfWqErzKOVNVgkpPBFeO9ziBHmy8PYhM5bSlWrzJyO4y4dB7ZRC3LFqLAhqLdgi23V9hHZlwr7qDBazDJ2pXc9uF1moRNtHQIOBhnkm3KluNgDESHgCk657g8sK9+k0NCuJEArXYHacucuJ3cTmkyZ1IhFcxrWhpJvWYuGyxtHJ71nasPRLJeZXYN97smXf28j/6PVTYRH5PbPQEbRLbPKoqMbVmniR8Qt4/GF7V7FEXZaGhC+qlPhSlzrCjKtoacTf/2b0CnAzSb1eOV8UJv8xtEEMzDPNzs9oxwOZ44nnV1vrGqMVUPgqWxZfkYW1ojyft4EeFivV+GoywbI6TKXNIwUh6GL4O1s0mZ1Uw+7ySVztvyvJx9R18LAqxKWRkpo8fbIYrzA7DkZkhahk+S8Iwll9wMtSVS5kjK7gFMVsb1n/RNfvaj3xhrwoVTJYvnv/cEwbkwkzKr6PXm+x+foihKRhC8A6wSX8VIWZ+pgki89xvrmsiuM77Utm0HE3Djt124TeR6p7aUFpZywgCTgpXSeamjzyUznAD4Xg9TAB5U8d9XRsuDuH16f4eknk9CUfaF2TnTKtsytoyeWxIvQooOinNVyvERvu3NtRLUC5yxP7jChqmBc1tp+9CgKpsoQhC8B4Xt84Y1HpCiKIrig5xNT3/6aI9DUZTh8IhHAPe+N/DjHwNXXw085SmjPiJlK6HOpg2F/rz95BoaYqxjZqVflF9VlKAvirdqXLZeyse4JTbcEb1SSqaVy+a5In3jor3SLWczUdYSk0rD3bAjerOI39UjwPIKcCjVbKbtyCEAu1Ng8oiRh2m0YSJ4UxTRvgmAaZjvHCgymyK73VzpIm4laAK5DIypx0SZeEXkboyWmJQpahvwSF8699P8/A4tWRmA1TAAyterizoTNL5rmLdL2U080pe3CTn5ollOAHKRoeHuU1HGFW7f+OQ7fdlPYhdVNou8J7qWfduUxvaAKCkyuyPbqVSWGXNnOdnZ2zH77bHlWyPen6aFjDC3eXj2diLW8cymw0DvcEmEUNni9A4DgS97m2zeKOunbKcV5OduKwY67RhJGCLEJFqIMwtlynIiGXuGsrqLDG/uoDLjY8SiP7ePwuKamIhSdKMESGpK0fkCberYOLJd+SFAdTbT+No4LtTuURRlI4lj4KqrTFvrNSnKzmBiwjiPL7rIOJPV2aRwtGbThuFyKLmcSnyc62nKUbOAt32Op35OKNTYLkos+RiSfeHyd6E12VKMIbm84r2YZCkk8xI2poNWGhvpGD7JwmszyRpNnloFi3cDi7FRX9M6TduPRWSyh9l3WVm3oKqWU1bLoBWbc6vJzjveLs7dWJybHSF3ZEtI8rpOEdJcVsbUbnLUbSL6XaNVY6ocxzmBYwVvy3sPtbWGgaIow8BlaLgkhKUNxPs9znqfc0huXmXfuA63tH+qV1m8jB1T1L1pMptI1rdxSw6X5fJ47ZxWJp/XXFlFQL9l0v6RziVPvaZDWqdp23HoMIwB1K9mk+fcCFaA5sqqsXnY+UWBXvy8c52bZKdT7UpZ14nLRxYBNkz9IOr1dwb3uy59y2DL8IzNpfTkoCoZz6oPUxRFUYbFl78MLC8D+/aZbAhFUXYGWrdJ8aFW9YZTZ8J2wK/B50TqN76OM8razh2TJuXEzEf0j1+TUnsl2b0kNTIgUhaPhkn5GM8rSU28oqqwb0+WUcScNnwSQSQxA9hfMh8fmfcw6SKNQnBJI9mWknqu85nk8sw5bwvSlqRlohSla59fczxbyVWfwCc3oyf0ptDNptaGu0+V81TGjUEc1mswRyud7n22q7KFauwrZDfjskxw4ZCiZSm/x7e1MkeSLkIuj0fQsnznrxiWHaRsLxKfNDTZO/K7j9i4yPSHCQB0EbakjJ5bNpjk8vi5yvFJC5PsXtFBDqeGbde4qGvjSFsJjvZARPBnMzXYuvEMtFG7R1GUjYRL6AWaeq0oOwZyNn35y8DddwO7do32eJStg2Y2bSiyJoErwlf28UjfwB7Wb0KkjgPJhXPipWfJxxS1CgrddzvKsZzlRBGSTUckJS2bdZmEXtItpGN4hsoKynIxnijfpSMmMPQumOyYxQH/FMroWUTxHS7CfKelqF5+DsQoR/xSOzXSMs2VVStil5+DvmV3dHoxiVgaE6ZW0WxnlC/hi9CX+K7pftG/+b3DlU3JB7qyClxZToqiKHVw3Tu4fRM5xjTEu2MWoiq7gbersiT6Yd2v06xmZWLZQFY2a8neKTKVpFwez3gq7KIik4ReYWIyci0Z4YpsllL7sPnN1Kzu7Udu7xyG+7uVdq88P7JzJ0xgn1P5eUfnXGLZM7zPPn/d2Xr5+jDN5YMnZHBavwwmONa7tq/bLuFSj+D9GmupKIqymXzgAzcDcEvoLSwsYH5+fnMPSFGUNTE/P4+FhYV8+f73B044AUgS4IwzPqzXspKjzqYNw/fk5HIqQayTbceufA9yckydV2kbU6sAQCGTYdUksCX0Cuk888Dayh1I/kkWavMaT63YyIBYtQi4M0k6nISUTO8IcNeRTIINhRybsr3g398izHfa88nouc4Jft6smHOqFSOXzismYMqTL00m+cil9qjPVafMJSszEaXmGiKHEzHIdVnXweSdM6m6n/RzQsGxPD6Uv+XhvBRlfJAOJJ8TSt5nPBmhddp1HU817rsTEZNGDX2yeBR84JbO4xP3XFo4YtsWNZ061TLCVbKxwg46dMQEayjbi0OosHeqzgNxzuTywcw2t8+5TkkGWNo23EkVWe8iYy9kNc2idG02Tr/+um0AxlHtC6KRNKDBNQVq9yiKslHcdRdwyy3HAQD++7/fZa1bWFjA3NwcwlDvF4qyHQjDEHNzc5bDiZzI//APt+i1rOSM72zilqLGg07dueC1BOx5tglZpKJLVkzKbfjG0ViXhB49tEZpioB2x+VjpHRehZQMyeetAnhqT6UbtitvYN/d1UFgJBFToMFlFfk5EYllsHZ2ygWJOccQsnMORhZPtgH73ObnrZSS4ZJ6XFYmjFJ0+cD13GnrbKt38qGSYALJkCdJEvuMUJQdjMzqrhrjWx4iA9tE9e0HKTMWit8LPjnP+/nEvWU3VckIy/XCDuqtAMEdPdwXwH1r/w+UrcIp3G7dF/il87h9TEj5vQxpa3Po/JMOAde5LJdd+5uQdk8d+P+nTv+6aFTslG4Sy8P+0G2D2j2KomwUX/gC0O2GuOc9D+F//a/X4J73PIzZ2dnc0XTgwAHMzs6O+jAVRakBXatzc3P58uHDHwXwKzj22N/G7OyxIzw6ZSuhU5QbCnlxXFF2hJyUcUT6VslG1MmCGDh7ggpjF/IxZpUtHwPYkylVEb0yupf3N2EKYlsZTVJGRq6jKM8EuXze8kohv6bsDBYB7AYws2KWG0wuBkcAtLOB1B+hiPBNs76WGRImKZphB0ATLXTQQQstxFjGZB79S20AzvO8aCelMQDya8WsZDUM8j4MHrUraxjI/spJGT6BQm0+KxXBrmHQ8PQriqKsFZ7dVJXNVGGS+uygfhlNrv4aNlHIbSBPBlNk/VbYY+wMcFdWFM8iybK9V7rF71YmA1uSTuN20N2wMn3vOgLM+P+CyjZi8TAwMw1j4yQAppHbMnk2WwuFjROxdhtornTRbMVIEaGJDuJs4yY6SBCig1Z+bjZL/Yk4t8u2Dx9D10qahMZRG2UymLWzkWr0u+ydWrYPVQB19bs2rnJIKYqiKGuB6jX96q/uxU/91AHMzc3h7LPPRqfTUUeTomxDuMPJXMv3BPAruPXWY3HHHcBRR432+JStgcrobRiuqF0u19BPPsbhcHJJTrjG+JxJVZIV1ivN9dfXKh9TluJw99MkS0jOJD6ZInXpXZMu2UTLXUeA5bSo86PsDA4h+05jYJEm1rhsjK+GATmkWOH05koXJJ1XPgeLST/fOSvrHPiuC1PHIKthkDucPC8fvmtVjqnMdnQ5tfk6OQEsGV9pmcJdPtyXoux8+M2rIZZdY6uCcVB/wnqtDibn2GKyOYxknSZX3T57jC0hbI9vsd+XFpN0bcUd83PB7Zu74a9byW2g7LdxMXb8iZVtyaL4bmvJBzO7KEqNlB6dg/y843LYrvO0XJdMnudF7dYIaa6CEObywahhn7C+ftcuara9H+R63qJxrnXj+Vutdo+iKBsFOZue8QwzSd1sNtHpdNBsNtXRpCjbFPta/gke8Qig1wOuuGLUR6ZsFdTZtCXYYGNcPpjV3YzJ6EnJDP4wSsvF2GISnm/PH1BpHABEaQpZWxhAWSKEy8kk4oVCQk/zMXYW9J0mru9dniNg/fRuJRvZ5548FwnuPHLhk6Rx0s+p5JsAreOMkvtZF+PrXFIUZbOpccNyBcv0282g90LP+DBKLBvIRdVvhGsczwqxpFqz36VA/qYB7t81Wmb2Ty9R22cnsQrznQIofdfOc4GTIpeljlJRY4kNJlud4zqfXeOkZLb3WvE5jQbNbtpwfA4pRVEUZT38+MfAf/2XaT/96aZGEzmaOp2OVfdFUZTtg7yWd+++GkDhXFYUdTZtOHUzmLiMjKNAtqtNy2t9OPNMclNhbEBIZbBsDlqmMfTui5SkNkXx5rJ6aYwwyeo1yYwmV7aT4301LuTz7sI4K67vPBZhvk/KWFv1nQvylbD3rN2IjZReK5URvf0jfV1Fsvk6W3ovyQtmT/gym9bCINHCOfz+0+9eRDtTp9N6C2L7XooyHgziKae+Ae49dbM81+J0inrg0S8mu7ucwSSlVH1ZTlXtJjpooWMkXle6xe+V73fNlfHNJPRUQnjnsAzznZYyueV54DpHsvOoudJFmBTnWr/zsSqbCbBtfLOcjQkps8lIcA9S88yizvNNnTaA6oylQe9P44HaPYqibASU5fDTPw387d8WNZriOMaBA0ZSTx1OirK94PXW6Fr+8pffCgD47GdHfHDKlmF8repNwSWlV/chJyivckUGusbUfTm3Mw+JVKsAsKNy7QdR7lwqT94XdZpiuCZZIqTFJAt/SCYpGS4p45PUS4282jKMM0JrNu0syMlEdSgW7waOms4W6FygNtUzSFg/nStZ3YPmShedNhCF5hw09ZtidNAEYEfwlh1N5ULw5YmY7F9fDQNiXRIxjv4I5eLh1j0kQhH3ztu0DNhuWq1boCjKWvDZPdLxTe99HEz97o0uW8a1fV17CCbgJrKCbuzMbJecGLeJ6GVkWTtwTcHmEsIwNlCUovi9kraPdC5wCbXDWcBNrIE2OwmSD959BAhSmO+abB86DwDb9lnJxmTnR9QGsNJFs9VBjCaaQH7uddB0npeAX4nAV78JQH6tTEQpusBwbBxXvcqqthNp7zSy5Uj0JWJZURRFGQaXXWbed+/+Uj45TdJ5vO4LX1YUZevCHU38Wl5ZeQfe9rZVfOc7DXz/+8CJJ474QJWRo86mkTGkP/0GSE6ELKpXSmXkY/pMvMtx3m2Srr1jlzQIfwaU8mmJkVdbBfDk3hqjKZUty372nV4bZM6TBECI4lyhNq1LWL+U1MtwnYspwnwyhUdjcgcr9YdIvBGblqQkTbwUKzcOvZsPjY2IyBVngqLscNYqSxX0H9KPNWeP9sDrNQG2rFjosIdcfXI7PlZO6hOBtHP4u0tSmMmqNe7s4b4A7us8EmU7cgq3Z/cx20c6YbjtQ+/ZT1fA2sZ+KS4MaZuT88j1uxciRTLI72GUAMkaHTZ1HE99kfcQOhZ1x1ahdo+iKMOm1wM+8xnTvv/9v4NnP/tAyaFEy2laLV2sKMrWIE1Ty9FEvPWtb8CHPnQTbrrpfvjMZ4Df//0RHaCyZdDpyQ2jjtaVK7pXTNDUlcyqI9NVFdGbL5cjFWWmEpePofUyorf/KxufqW6UavFIKTRHAWSS0FuCZjONA8sAFlNgJs6uFpnZxLOZ+KQMczyZAuxdhC1XVLr7xR++uVM1ZecxgLwvzTKbcqIEiBrFZIm85vpNoqwlAjjhC4D56zUcbbkjV8aToijKINSZaHZlQAnqZjMMmtHkG5MRZllNfjlhV1arnfnNM71t+yixxrfSuLCBXDKwFRLCiIGlI8BU+S+n7CCWjgBTMrNpJWu7bB9qt4AoAlppjE7YRIoETcSI80xubgclzK6xz22gaZ3btG2UObBCJAgj4aSgjG6fjcOzsSPRx8f4tqtqe6nK2HZleCuKoijr4ZvfBH74Q6DVAt773hdhctI9TjOaFGX7MD8/7133e793P8zOQp1NCgCdTdwESD5G9hENT9sznJb7ZTT1kYnx7ieT/4qiNK9VALgyQeyJesI9sSLbxXuUAgF3Ig3gaFo6AiyvmEdDfTzc+VA9ruVskqXBJ1x4W8roscmXYMVIy8jaYySB169N4817sZxmY/h6Kpi9GqUAGvb1JidUqiRmfBM1A0UA80kW3nZJzCj0zQ93nxrhq4w7FFgjb168ZqVoyvshHP1ym354nVMUkcC7uX2TlH4LXME4sn6lrAMYITW1mmCkhAOSzuPBNv0khFmtJnU27WzuOgJM8Vqm0yhLBQO27ZNlwAUrQDht7PkWOlgWjiRqu85f3k9w5xTQzPfRofVRim5+DWXXtcvGSVB9vdZxPFX15ytYCqDV73tqGF8JYbV7FEUZNpTV9HM/B6+jSVGUncMznwnMzgKXXw4kiQl6UsYX/fqHSBDMwzyoTGJ9MyEO+jmM1rK/AeEPn7Qsi2S7xvM2Hx+50qVT8S6fE8H6WXPVMUTZWawi+64TMyfodYvI8yWF83yPcieR7USS2NlMUd6XIMwnWUrnfthHCmDYd94NupMHwbkwkzKr6PXmN+ZDtiA0fTzcfarMp7IzCYJ3wLZ9NpB+ZtVabSIH/D5eZd9IXPLDrr7SPoTcq7Xs+Ti1fcYELhvM+/g6KbtYktGzHQl1z1Oi6px3spG3goGCbQbfeRC8B4Xt84Zh7HTLo3aPoijDhuo1PetZoz0ORVE2h5NOAvbuBQ4dAq65BnjiE0d9RMoomRj1AYwfHrm8HBHZW9dfVSUTU7XeWmceClyFsUtZG45IR2rzwtmuiN4808kV0ctffB0vlJ1Fdy6vAMupZjaNC/Q9L6dZdpMsoO4qri7PqdTUMWjFHZSj0qUUUlKaeKExQHlSpnStZEXmzeBedYZi1QSp6xp2rZf7rYRnXLruRRqHoCjKsPCFBvTJpKybzdAvc7vOixFGSUlG2OzSFXBjv+Q6Ka3XRIeNT0zdSvrNctk+Mss7y2jCEWD1iNo+48AigB63c1xKAOSYpPNopegLk65QGSifl1ylIHKc19L2j+T5HpL0ZIIJS0YY5Wus7vVY1+bpC7d3CM3iVhRF2UjiGLjyStN+5jNHeiiKomwSYQicdpppU2ajMr6os2lDGPTBRk72iuK2VZPUVYfgkp7psw/+kOiqzUTvPvkYWs/rFUgnU96mSRZ6MJYPz9xpwF9ZH3c06YTLzod/18spbGkh6ZTky3JCJqbJl6pJFtvp5DuXfRMx3AHbd+KFUzXp4hsr+ywCsZN+9yG5PJ5OpxQTnm95PS/9uVXGEYdEnrVcdZNzDK9aXs/tKgIQpfn92sgIl+WCuYxYWSq4XNem/CrGR2mKFrd3UrhtH4+cMMkIKzubZRgpPXIyWucCd0Jy24edT6Y2ap1zNPGs59J5toSwHJMTpeu7Rus4mn3tgXbKa+aOp71DqN2jKMow+fd/B5aXgWOOAR75yFEfjaIomwU5l9XZpKgVOHTqPKxswYi6qAdELEMpKk+s9N0Fi3KkZRdO6RjZ9snnZfQSIx/DX8rOZlW89+R5I0+3xPEuzqmwxvlaJSvjIr9mLCeT42Re78SooijKlmEE2ZHD+oia+xlERqzKZiqtk79lclPX+tRIyipjiMtmrlhPpkgROFMtHUzw9VLdQL4DNeSD18OG3E74Trfgc5miKMo2Zm7uKgBm4jkQcdQLCwuYn5/f/INSFGXozM/PY2FhIV8mZ9PVVwN/+qfv1Gt9jFFn04bTLzugZmieLyKwTpZTv7FsOWQSelUyYb5I3mJcVWQvycfAHdHL30VGCkVzJqmtjqbRvTsf+p7zd57dJKTyShG+jkjfqnO5jqwMIK+JYoYnz3CyHE59pPT6UTW27z589xk5weLKfho/z9bwo3vNS1F2JjIzIBL9nKr7SVAMWWs2Zw2ZvNI4uSpyTbLb9SltObFylhNtW8pmsmygFAH/jXJl5XJpPZbJ0lsxv4Fq++x8lgEs8+ylBPVsHyYdHCZ2YE31uenIVAKsc55jBe2wZ4hs8GBSeFVj+90TStvWSY9yrRvPrG61exRFGSbf/e4DAQBLS/9s9S8sLGBubg5hqPcHRdkJhGGIubm53OF0/PHAwx4GdLvAOedcrdf6GLMhzqZbbrkFv/3bv42jjjoKk5OT+Omf/mn853/+Z76+1+thbm4Oxx57LCYnJ3Haaafh29/+9kYcyibTTzpvwAeYQbXKfZMsdSdu+ARL6NZl9+GehHdNuGR1cdLUfJyrVhOXlZEP1VkfyccsA1iCTriMA/y7XkZWt4nOCS4rU1UHLHtFqZGVAew6TNXnr3+ChffxGgZA5nByTb5IBr1++Xau/dSmn7weaqxXlPFmfO0eSdW9wueEGjDQZi3zwH3toR4mrHqVRc0+VxYHjbE/orBzuKRqZNk/mRxrmhopYeksqHpnjqblWG2fcYFsnyWS0JN1mlyOJuGsDJOukNKzZbIJaQ/JOqyuQBvXfiaiFFQHNkdef/3snDUH1wCFHLkcOIgtM34OJ0VRlGFw8CBw663HAAAuvvj380locjQdOHAAs7OzozxERVGGxOzsLA4cOGA5nPbsuRoA8PjH/6le62PM0C3pn/zkJ3jSk56Epz3tafj0pz+Ne9/73vj2t7+Ne97znvmYd77znXjXu96FCy+8ECeeeCJmZ2fxrGc9C9dffz3a7fawD2mL4vvTB57+Df54h4SeezP+0Jl4JuETZ7svfDe+zYR8zCm9Hk6p/wnKNmZ/r5i4+Brl49PEio8+qi72uVpMDlI0Jm/L7ag/QooUESKk6PT/b2wTGqj+w+5sNiIiVyN8dy5q94yY9VqyFdvXtWHqSg33hcvoVUikTd3dw4kATqx1dMp25qnM9ukdFZSfEqQd5DkVwyRFxKTuqmSyya4ZhIHs/W3D+ATaqN2jKMqw+OxnzftjHwv88i//Eebm5nD22Wej0+moo0lRdiB0TRfX+jMAfAo//vFJ6PXKUprKeDD0zKZ3vOMdOP744/H3f//3OPnkk3HiiSfimc98Jh7wgAcAMNG95513Ht785jfj+c9/Ph71qEfhgx/8IH70ox/hkksuGfbhbHG49EzFA816pLdc+6qU0StPvhfL/nXUV6XxnmdJpWlZPsZVV0dG/LJITZWPGW9yWRlXVLjrVUNWBvDUIRBtGdlr2vYkSz6mqm7TWq/hqu2d+6Nfd55ZOZ4yMYqyEajd04813mt86p+0LNcP+jGebWTAjcxykrJjLieS/fuQlrdPUiMlLH+3fMvMBlqOB/x/KjuGZUemf6W9ky2HzPyQ56N5T5w2fyRsHv7Os/fybWSw2nqeVfr1V90fLFz2jto/iqIoG8Vll5n3Zz3LTEI3m010Oh00m011NCnKDoVf643Gl9BsAjfdBOxIIQ+lFkN3Nn384x/H4x//ePz6r/86jj76aDz2sY/FBRdckK///ve/j1tvvRWnnXZa3rdnzx6ccsop+NKXvuTcZxzHWFxctF5bG9eDzQZFx/VzPNWR0nNgy2iUHzbNpv56NbaDKSk9yPaVj5FSemxcLwFWYV7KeELff4/OEeFM6itFVENWpjxB6JaM8Tmj8j7uZKqSiqkz97EeR3Nf6tRvGg9s0c/hvDTCd+eyEXYPsB1tHxc+6TxaR/1DCnnrJ0NacQ81NSuL34E60qnUzx1PvLaNnKzPbaukW+zAERCRfxT1sVo9yyv9/wzKzmSZpPK40wkozhmXxB6Mkm+YdC1bRp6nvC3PdelYkrXMLDsoSgZzOtVxGg/F7vHdg9TxBKjdoyjKcOj1gM98xrSf+UwjnUeOpk6nk8tsKYqys+DX+urqnTjuuO8DKO4HyvgxdGfT9773PbznPe/Bgx70IFx22WU444wz8OpXvxoXXnghAODWW28FAOzbt8/abt++ffk6yTnnnIM9e/bkr+OPP37Yh73J+B5s+mQ3DTIZXfUxnsOYqJDPszfzj+snoVcpIyOHSydBNiZJjaNhJwp2KIORyAk5Wu4nr9eHKjkY37qqTMC611alQ3iQuk3KuiimjIf7UnYmG2H3ADvR9uGswZE9rPpNzn277+t16lXWwZUtGwnbpkQq3mlozZ8TZYfCz5UqW6fq3MrwZXEDNWUfBx3vqtsEbBGfz3gG1xBq9+wcPvjBD+IXfuEX8LCHPQyPetSj8NznPhdzc3O46qqrRn1oyhjw9a+bmk1TU8CVV74tr9EUx3GprouiKDsDXo+NrvXvf/98AOpsGmeG7mzqdrt43OMeh7e97W147GMfi1e84hV4+ctfjvPPP3/N+zzzzDNx+PDh/PWDH/xgiEc8bAZ9WBlwfN0J5wEdTWCT4WFYzmIym5S13vk6l6PJmQki5WPkhAuX0oM9ppeYek0JNLNpnFlGlt0ks+OA8rkjzykmKxMmdkQvz16ya5OVZ2u4tJJvkiVk9RFgSepV/OdcEfl1Hc1eGp62TgQoynrZCLsH2G62D1DcWxpY18TtRkw8D5Ax4apbKbOT3PUq/ZJjpfXSYQD4ZWBF5pPaPuNL4sri9r0Ay1EZJvI8rpYN5uOqzm2vkylKhhMkM8g4a2y/bEmXXTTeDidl+zM3N4eXvvSlWF1dxc/+7M/ioQ99KD71qU/hrW99K0499VQ8+MEPxj/+4z+O+jCVHQxJ6N33vjfgwIE3WTWaZmdn1eGkKDsM7mji1/oZZxg5+csu66CzcwqbKwMwdGfTsccei4c//OFW38Me9jDcfPPNAIBjjjkGAHDw4EFrzMGDB/N1klarhZmZGeu1fViHFNVGRfpVRAZHzkkWf1ikdDKZ8fYDaLlWgZCPoXfufKI+8UpSIEk0s2ncyU+JzAHpdFbKcwsoRYgXsjL+c5aoE7XrkpSJfE6mYV3f/WqZDMQmSoBuYdLSFNtwXsrOZCPsHmC72T68BqXsc42ryQDyvwNTcz+u2jScfvUqpVQrvQeu36kqB0K2Xp1N48sSUD5PAOd5wtcFWbskaV3hFK2TtSftIpejdkMdx2uyd/rdg8ZTQljtnp3B+eefj7e//e347Gc/i7//+7/Hhz/8YQDA5z//eXz84x/H4x73OPzWb/0WzjjjjBEfqbJT+fSnzfv97/8da/KZIIdTmmqatqLsBNI0dV7rf/3Xr8CuXXej02lCE2vHk6G7Mp70pCfhW9/6ltV3ww034H73ux8A4MQTT8QxxxyDyy+/HI95zGMAAIuLi7j66qvV8BmEtX5zA27XL0q3vHt/TYMSVd4ij3NAUQiacEvSbFogAUrPtfz8qSEp0w/uTEr0IVpRFKjdMzgDOrRHlIBZVyJv3dSxhVxZ38r4kgBoZe0U/muEnS/cDySdTqYvre0cMLZQs+bBrpENue4j6EWk7GRWVlbwMz/zM/lyEJgMv6mpKTz5yU/GL/7iL+Kaa67Bc5/7XDz84Q/HH/3RH43qUJUdyOIi8IUvmPZf/dVz8MAHPsc5Tk5KK4qyfZmfn3f2T0wAv/Zru/CBDwCf+hTw9Kdv6mEpW4ChZzb98R//Mb785S/jbW97G77zne/gwx/+MN773vfila98JQBj9Lz2ta/F2WefjY9//OP4+te/D3F95wABAABJREFUjhe/+MW4z33ug9NPP33Yh7PFGNKT0yDSWv0+3rMPl9OIO5xc63mfKzPEGutzArj6idTIpqmMnkLf/apDKqaUIQeUHU2JOAfhl4aR53okHK4DS8tI1pqJtCVqHOxMUkxsQITv0H9ulS2C2j0jRsqO1t3G1R1V2y5mU37fr67h55MjjuTvlMxokvLCTEpYp8rHl4T+8WVwu6SF+bkERzZSxbnOM/Jc27r24VJI2OxsxIL1ZCiNV3aT2j07g6c//el9ZfJOPvlkvP3tb8df//Vfb9JRKePCZz9rVEce/GDggQ8c9dEoijJqnpP5mynjURkvhj5V+TM/8zP453/+Z5x55pk4cOAATjzxRJx33nl44QtfmI/5kz/5Exw5cgSveMUrcOedd+LJT34yLr30UrTb7WEfziZTp3K1Sxd8g6N6q2oVMMKoevKkiqqMJz4pY2T02EoetQvW9tQq4KizaXzhMoqrCctsoqBVef54riE6F0MkzoheivSlyUWezSSdTs79UyZUlKKbhLShe7ZwkIDbYewjZ7wmVBRl2Iy33TMI65DQG7Rui2+81x5KEUblm2fZnkkq17kDEBIrkySS0jGujCVXEE7Wp7bPeNMjWTwulxfCfQ4JsyZKU6uPbB+X5CO3iezzutrBCgBhlJTP00GdwepVVZSBecc73oEnPOEJCMMQCwsL2L17t3Pccccdtw3qQCrbDZpQ/oVfGO1xKIqyNfj5nwfCELj+euDGG4ETThj1ESmbyYbExT/3uc/Fc5/7XO/6IAhw4MABHDhwYCM+fhuxlpkUxy6GUIB3YsBaTXXoK0Gzht0nWd0mnWxRgKxYdu3B2bsno2lT2XYZSdvugNcFTQ0Pe5/KzkXtnk1mk29Jw/6dCLgzCaztqzGYjRvoN0/Z2bgCt2Q/I2D9MmNpPXivjSjFmhzMm+JkamzWB20b1O7ZGTzkIQ/BFVdcgd/4jd/A+9//fjznOc9BEAS44YYbcMwxxyAMQ3zjG9/AG9/4RjzqUY8a9eEqO4hez0hlAUU2g6Io48097gE88YlGXvPTnwbGUj1+jNH89p2Cy281BCdUP3ySeq5xnEBOsNC769lPSqIpCljNJjlB58Ihoxc4zjWf9NEwcDl0S9RxHq/52uVFr/sVwB4v55KiKNuQfreptcjrAQjDwe///uzWin3V/c3SOXElYxUOh2MdtYANsKHXbCf5RCCqnl369anJoig5j370o/H1r38d7373u3H77bcjiiL81m/9Fo4//njc5z73wdOf/nQsLi7iggsuGPWhKjuIr30N+NGPgKkp4Od+btRHoyjKVoGcz+SMVsYHNc93EnxSZYjfbB2Ndtm3rsl6qUMPu70KnX8Zd7zfvc9ZWSO4ss5kIa9F5pLdi5AiRbT+4tk8upfaKiuzaRgX+nB/HlP1mCtji8+xvYkSnpXSer3KTfvZM25byC81FkpvgW/3UkJPbyEKweWlPVLT+TiBlATm8nhSOm9QSo7aqAckQXmgtGvq/NzqE+uGonbPziKKIvzO7/wOfud3fgfLy8v4+te/jptuuglJkuCEE07AKaecgokJjTlWhgdNJD/jGcBYKUQrilLJc54DnHkm8LnPASsren8YJ9R0VzaU2g+rrmH6jKL0YRXApG/lBjlmhpb1pHffLUs3Exka9j4VRdm+1MniXjOuABtF2eKMRIZ4TTQALI/6ILY0avdsH5761KfipJNOyl8PechDKsdPTk7i5JNPxsknn7xJR6iMI+effxOA+znrNS0sLCBNU8zPz2/2YSmKssnMz88jDEPMzs4CAH76p4HjjgNuuQX4/d//EE488dt6LxgTNKRlqzKiieiwj9TXejTeh/FQuqoTMUpG4ltwFFQfhC0zebIuyTxFURSlL+u8xw7VAbWO3y1FAeBXBsgoZdX1YUPtIbVvFGVN/Nu//RvOO+88vOhFL8LDH/5wzMzM4NRTT8X+/fvxoQ99CN/85jdHfYjKmPGTnwA//OHxAIBvf/td1rqFhQXMzc0hDNX5rCjjQBiGmJubw8LCAgAgCJA7oT/4wR/rvWCMUFN/u7CRE88VEjLkXKrzwFn3odTyZ+mkirJOhuGADDP5O9lXb9tk6NGgJerUJtFraWikGxDhu+HniKIoWwL52+F0SA2SycTGaMCNstlEDvtI2Xmo3bN9+PM//3N85StfwbXXXosbbrgBd999N77whS/gqquuysdMT0/jSU96Ep7//Ofjt3/7t7Fr164RHrGy0/nXfwW63Qnc+94/xv/6X6/BPe95GLOzs7mj6cCBA3mWg6IoOxu61ufm5vLlu+/+RwD/A0cd9SLMzh41wqNTNhN9elA2nSQEGjphoiiKoiiKoiiKoii12L9/f96+++678dWvfhXXXntt/iIH1GWXXYbPfOYzmJ2dxbve9S785m/+5giPWtnJUL2mF7/43tiz5wDm5uZw9tlno9PpqKNJUcYQ7nAy94IWJiZ+FXfccRS+8x3ggQ8c8QEqm4LK6G0XfMV/h7JvR/HeDIpmpOi0qujGNUWwqbtTWSeNIZxDrnO37vm8KRG//a59dd4OlRQTeZTv8F76c6so44D87UhcvyWReK+CjRnG750yvqTR4Ha68/xVdhxq92xPdu3ahac85Sl47Wtfi//9v/83rr/+etx555248sorcdZZZ+EhD3kI7rjjDvz2b/82/uZv/mbUh6vsQLpd4NOfNu3nPMdMMjebTXQ6HTSbTXU0KcqYYt8LYpx6qrEn6X6h7HzUCtyqjGjyOE027qFyGHIKOtGiEJFvIQIQYs3Sk1tG9mMjHcyKoiibxuqoD8DPOu+xQ52Ip12pnaOsFW73bFAgztDYVPtmC9+DFGXI7Nq1Cz/3cz+H2dlZXH/99bjgggvQarXwute9Dt/97ndHfXjKDuOrXwVuuw3YtQt48pNNjSZyNHU6nbxui6Io44W8FzQa/wqgyIRUdj7qbFI2lNoPqq5hW2TOX9m6NEbwmUObfFFH0pYlQbghL0VRti8beg0P0UGgjBlb6KclTbfQwSgDoXbPzuVlL3sZzjvvPMRxjL/9278d9eEoOwyaOP75nwfe8Y6iRlMcxzhwwEjqqcNJUcYLXq+N7gWf+cxrAABXXgksLY32+JTNQZ1NOwmeCTHEiWzfw4KrmGwht7eOBwxfZGbWbmDNSSvKDsH73btW1DxRfOcs70/6nN/F+nWenYmjrc4pRVF2FJuYbVCVKVohJQz0t2cGsXdShGUpM9/mEexsJ523VQiZve0zikPxjvL5Wkcm20ffc993bUm7Ru0bRdlQXvayl+Ge97wnLr/88lEfirLD+MQnzHuafiKfXCbpvNnZWXU4KcqYwR1N/F5w1lm/CeBGrKwAn/vcaI9R2Rx0vn67k8B8i4NOTg/ZGRUirRyTIkTIPrQXAfkjKH9Ydu1G/v8UBUVWU0STLFVzHtJ5GZlzUDIUZ6mHbh2Jyn7SeeuS1ktQTO7ytm/s+JIiGnotrk2p7aUo4wLdoqouqzVOZKdpOLBjR9o4vN5l6DuAOr9Zsq2MNQ0ApbJL3P5xSQhnbZfNU8WGSejJy6GO48ll+7iee5Q1o3bPziYMQzzqUY/CddddN+pDUXYQt94KXHONaT/wgd+0JpcJWk7T6rkiRVF2BmmaOu8Fc3Oz+OQn/wPXXHMC/uVfgOc+d0QHqGwaagWOlATFlDlvr2E3vm+y5gNYNwkRRrYRsN6HhLSfE2oNu48iIEqAhtorChyTLpWDs3exzUbWJPBeQ9tuYmTbHfC66DqyNoexT0VRNpgNypTYsN8J6RSQwTUiUCIKRyMfq2xB6gbZODDKBJG1PCj9s5r0N287oXbPzicIAhw5cmTUh6HsID75SfP++McDf/EXr/eOk5POiqLsXObn573rDhz4GTz72SYjstsFJlRnbUejX+9QqQq7I1bFu2zX2O2g+LIhRF+aDEdKo0qiw0jIsJWugtiReLkiNaETLuMMSSkCQINPxvFzpUbGE52LrnM+YQ/eieMhPKk450ufwyddvFJOlbuoN3ZN94rVtW6oKIoyAAPK5m1E5kICT5ZEfxlVs+yfoJe/I7btExW/J2FoZ5m4JNBktkroGKOMJYG0bbi9IxHOyiTsf85KRxTvTzzr+DsApMkaA202TVZvEyU8FWXIvP71r8dHPvIRfOc736m9Ta/Xww033IB73OMeG3dgytjxL/9i3p/3vNEeh6Io24OnPhXYtQv40Y+Ar3xl1EejbDT66LqpVKUgrWE3gz6M1XA4Fd0hmqKPMpXogVNmLfHJ9761bXh0Ln8YdkX0EqFxLCQREKXqbBpn6LvPHU38NKNJuRBlZyZ7l3OLPgk9WbNMOpnkdtxBVYu1SuOtS1JPqcJVj24Y+1SUncsqgMnRHsI674c0Qd5E9fWaWPd996Q82Ucyw9v6XfDJn0lpYbYcRGq4jzMR/eMKqJHnUGivJ5tH2iZV8sEux5Pp95+FiS+jaS3PLOu2caRTSY0mH2r3bB/OPfdcBIERo5+ZmcHjHvc4nHTSSXj84x+Pk046CQ94wANK2/zN3/wNfvSjH+HZz372Zh+uskNZXgY+8xnTVmeToih1aLWAZz4T+OhHjbP68Y8f9REpG4k+s25X1uq3GnA7qjfgjFx0PET46jc5JfXogdgliRdmxxpWjFHGmrxmk4zu9SEdTg5oEsbnKOJ1OOqS1MlqUhRFGRvWIRtMmw/rMIaAb5K+8qNDoMHrTsljCcW7dDwp440jgGYQeKbdMOgvqTekD6ojIKEoO5xf//Vfx1e+8hV873vfw+HDh3HFFVfgyiuvzNfv2bMHj33sY/Gwhz0Mk5OTuO666/C5z30OQRDgFa94xegOXNlRfO5zxuF03/sCj3nMqI9GUZTtwvOeVzibzjpr1EejbCT62Lrh0JPQGiZW6hTAXgsVD2uuiEQzwd7x7MpEPUbMG8QzO0KkVpaTkdGbQJh07R05ojBdRY6j0NRtasR68o4zk8hOj0hIysiIX8A+p2Q2UzRRGc3J++tkKg3kjBpWZpLrel7zfl2SeuMnN5MgxMSQI3JrZ7opyramnyNp1bHe1Sd2GTnafD0c/XWoEYBDtkxVNkeVw0lKk9F7LwICGsyzcflvWCLaWrNprGkA7vNEZjRxezpCLtsonUyuzOyqTCfZX8qScmU1bbRDaGDpPZdNw/uSbHm8bB+1e7YPF110EQBgcXERX/3qV/GVr3wlf33rW9/CnXfeiSuuuAJXXHEFgiBAr9cDAPzBH/wBTj/99BEeubKT4BJ6QVA9VlEUhfjFXzT3jK9+FfjhD43DWtmZ6Hz90BlUSmbA8VUPU/0mZKr2k4RGmw5AmoYIw6T0oMmzlqSDiZxO1C8n3a1toxBp1EWDHob5sfIH5pT1ZWOCCGikpksnXMYX+v4brloFsu1xPqWRORd5NhOfiOETgz4Zmb6ZUKnp7yahrdvX7zqWdUXqTKJUjvHViNOwYEVRhoV0Gq2iuPHytosecteLzPipa9esFVf9SiE5xifgKdvbLztWltEr+s2HpZkccO4Q4E4lbvs4gikmdf52bJnkTiZZy8vleMr6E7J5KpxKPuWCwllqS+r1lQxOIr989yBBMYME1NS2g3zrx8vBpGxvZmZmcOqpp+LUU0/N+5aWlnDdddfhq1/9Kr72ta/htttuw9FHH41f/uVfVgk9ZWi85S3z+D//Zz+AmZKE3sLCAtI0xfz8/CgOTVGULcb8/DzCMMTs7CwA4N73Bp7wBOCLXwT+8A8/icc97j/0frFDUWfTSPA9DVVE99aN3B1kglpM3HR9OuulzeqNkw6pvtt6HEzyYTpKzF9JT16lJKEnaxesEV8Eu69+Aa2rs49Kquqq9XNQKUOj6ntezz4VZTzYxPpNg0xYVwbg2Ct9ksAu+snolX8bHPcCeWxq4Cg+XEE2vp+XPudRP4fRQJLB/Jyv+TyxsbZLL3vv50BSAwpQu2enMDU1hSc+8Yl44hOfOOpDUXYwt912HBYXZ9BsdvC0pxVVvhcWFjA3N4cDBw6M8OgURdlKhGGIubk5AMgdTs97nnE2/cu/BPiZn1FbYaeij7MbAj3YyAjfDZh86TcR3c/55NmOpPOqIh9lJojdL7NFTL4TACRhiDBKgahbjtqVDiZesylbDqIsq8XzX1Z2PvT9By7pIXnuyPfslUYTSMJyxC6PZLclIIvbpTWp4ogA5qR8EtMVkTtIlO+gEcED4SqkrVG+iqKsBQqeoRuWNDfXaRP5AnC4vSNtnz4Zo8UEuZEN5lmuUZadRMtSWtiV5ZpkvyE8yynPmI0mkCTdIjuX/i9MLs9pB7WAybbrD6KMA5Nt+GX0XLYQwDK5J/JzkNs3rnOWr5djAIhrQdhBibwo8530z3Ty2Ti+vtq4Bqt9oyiKshaOOeblAIBO55P4sz/7/zA7O2s5mmhCWVEUhe4H3OF0yy3nA/gDRNEzsX//c0Z4dMpGos6mkUKyMn3SlnwPWGuZcO7jcOIPia5MDZLI43IwfLwlE8PkZszHMNmOKEQv6iLgD8aA/eCcwp58aRX9ky1gMl7D/1/ZEUzCnAM+mSHnJAxr9zIJPcIllWTey/UNbBmaQmqPk4+xpPPE9b1ep1HtyRce3Zs42oqkqo7XevapKOONb8J3SKbosGwiBg9CaFr9ZQlWyuR2TcwXjiduB6EsJxwCaAM4AtsOamU7i7LfPmUsmWzBnB++QJo2yrZQBtk8MpDGvJcDx0gquFx7zHZSWdJ6vppNa7021yq1N9CHKIDaPYqi1IfqNZ1+uslYOPvss9HpdNTRpCiKE+5wovvFPe/5AvzkJ/fEv/4roOUEdyYToz6A8cX3gNPz9G/wxyd9HhbzzfjEe+TO5LA03ctRj15C8e4istdfHQT4pyDAuVqZcsdzbvZdX82/635yeX1OO1f9gToyIq4sp51VCHm8I37tGhXDeynKzmSt94s+E71JjfYGUGUDVV3HZSeT/7eEBzsAsANuOPI3Lmsv7Qrw/SDAlWr77HiuDMx3vbSr5nctzxcrudq24fn7hqC+nG2D2j2KotThlluAa68FggA4//xfQrPZRKfTQbPZVEeToiheZmdnrfvFi150TwCF81rZeaizaajICRfX8gBPXoPKRvikKPpJV+TL7CE0tbOR+k2kywcLd/HhKH8lYWg+zpeJwqM1HZGck+0suwXAFDRFbxyg75q+90l+TtA5Qu99zq0kBJPQi0pOUde5XKfuBo9gp2soNR9WDBpUSqafdN4gxbO9O6hTOFtRFGUYrPF+UteWWUt/Yk/kU1aHaduSwdymkXLC/PekPKaQL0vCEGk04bZ5uO0jM1daQDANTE0Xv4fKzia3fbLvHi2UbZ1QLLNzpzeAbHBuo4tx/Hqg8fw94WOT0NSAFddUpV2z1gymvvaOXLnq6XeNURRFUSSf+IR5P/lk4L3vXcgnjjudDhYWFkZ7cIqibFkWFuz7xeHD/wDA3FO63REfnLIhqLNpw+nnYKoZrltngrofVVroGWkS5lG9LikYns0kX/bETMgeVl2vCKlLZ14+OHOpNOZQiEJ7jkYnXHY+k+IVcSeTnLCTkzDiPEsjO+vOdS7ztutcLraNwCdlOLaMXuCfKBlkomWQSVVrgKtdp07T+IUmdzcgurerEb7KjoZuQv0maqtuYD17Ubbr7M51T/U57UVfl9k/hAwqqMpk5U4n+zejsJvKcsIofqPod0vaPtwGior1ky0NtBkHSDY4mEbZ3uHL0vZhWU1pZDuY5LlJSGcUjefrpXwe3z5Zi4yevNb7BdnVsoOqVCJ8cp6uG8/4OJ7U7lEUpQ6UhbBr1+fyGk1xHOPAgQOYm5tTh5OiKCV4TTe6X1x44e+i1VrBbbcB11wz6iNUNgJ9Th06dSZm11kYeyNIApjTISuMnYSmqDCKOk21doOiGLaPVI5xSMTktQo8BFFReryRvZTxIpDnjXymlbJEQk4GEJMkQ3oo5tG9xc4d1896fDjj5/9RFGXbQDeoVRS/zgmG+ktNH7EBVmySmMzUMLRvtDKbw4excfw3acoeoRpPlr3jsn3otytB6f+rts8YUlNqkeCmiEs6mNqVso+O4LPSmNTjaBoGA2dsD/PDFUVRFAC4+27gs5817csvf41Vo4nXZOHLiqKMN9zRVL5ffAzAC/CxjwE/+7MjPEhlQ1Bn04bgmgWpcjBR5By5TyIATH7CF+U3SMKU/KY9D25dLqXHoiCbcEuMUdYHH2/LcaRiDCuSHU0AYZYzSZG8QBG9mzj6WXsyBJAWmS7KzsbKbJLSeVJyUUrJiAy5NJrIz8UYzXyihUvH8LYlf+SJ4ARQuhYA+5qqzGQaVGKmTgQwemInVRIy65T93EEkCBEMOSJ3Z9X0UpR+kOGxmr1Lt8g67i2+TdcqxUV9SQhEhaeHbBh7Ur4IwKmWXY2c/R200ELH/J6EIZJwFQ2yd+h3S9o+EWw7aNqM3T0NTMY1/8/KtmU3zHcNymzitg+XWpQZ3dm6NALisGWdgy77BfDV7bFrO7mzwoXNk4T9sw77PcP0s3FqCkP4P5A7xRW1exRF6cdllwFxDNzznofw2tf+j5JDiZbTtDrwWFGU8SFNU8vRRMzOzuJrX/soLr4YuOQS4JxzRnN8ysahzqZNhTuhuIOpxnDZJ8f5HuD6yVPwdZmDK5fBaPkjeXkGE4/Q5Q+jttPJId8Rhei1uwhWUDgCUtZuAzjC/v/t7JX9TSbbAFaAyVSdTeMAdzRN0rlAky6yXpNPhiirXxC3mvA5iaTDiSPPZXudLUmTJmFxLfWT0NsMiZkSq+y9r9dKURRlyPSxg3y2jCt4BqzfZRP57CNxqzNSelGRmRoW93r+7gvAIbhsHi2T3cQn6DvtCTSOdMvSaGT7pLADcFjQTdBW22ccmIL5ri0HE3c0SRk9Uec0jYxiOncOlWs1VcsGS1tJvqdpmMlwy7QqVNstdeygoZgjPoeSOpoURVHq8s//bN5/93f3Ym7OnbmkGU2KonDm5+e96973vl/Bxz4GfPOb5vXQh27ecSkbjzqbhkivN5+3g+BdGOqErU8yxjXxUnd/A25L8neyaLbZXfFA6pKPoX4+PglDlB70QvZOx0eTLJwIaERAEplAZJWS2fk0kMXHZ9+9F5fEDH/PqKo7wJGTM3wsvxasbVxyMvaHD5c1Scz0p9fbP/ydbgNShJgY8s9jP+ktRdmu9HpvyNtB8B74f5EHkBD2OZV8jqaqMXU/bwB81zNN1ks5YddvhbUP7jDg9h61pVRahto+Y4KjDhMAuy6l67ynmk2O83XQrBMZfNb3N20tNkkdW6ZudlQlVU6mBL3eGWvd8bZF7R5FUarodIBPfMK0f/mXR3ssiqLsDPbsAZ7xDODSS40z+8wzR31EyjCZGPUB7Hy4dBXvI1Y9bc9wWq6TDVE3YtB6cDORiVSzwPdwKWU0OFw+xt0u3pMQ6Ek5ENc7H5O1Gy2T4aIyeuPBbmTfddt8977zonTOsHOp1zbqLq5z0S0x4z6XgSLLqSyflDmiKMo3z26C+1r0yedVTajUzXLK8d1n5AbjK52nKMqwqJrIdd1jKuQ9+2Zkiz4ffTKaTH+U2UB2LT+ZsS3tHzsbxJZdLbJlo7xtybdGobGBuMOAZ6ZI2bQ2jJxa9to9XfF/VnYEu7l8njwXqmwfkckdo5mff8bOicQ5Wi0bDLik9OwM8DSX0GNOi7p2DWeQjG3n/ujZy/X81e/+pCiKokg+/3ng8GHg6KO1toqiKMPj9NPN+yWXjPIolI1AM5s2jAR2zKnrKYlqGdDDjUNeT0bp9nMaDTLG+TDHigcnoZHgYA+dgLuWk68+ge+Vj8k+riFl9GT9JsCuYUAOJxiJkd2e/7Kyc5gEMBPWdDTJaN/slYRApz3hcCQ5zk2nI7WYXORj+fUBwJqsNBOYbCd15fP4eLmda71zmU+srGIw6bzxdTqZCN/hRuRqhK8yXvSTCpZZTqvlsS4ZPdnmy9JWkjaRvH+WbKKgyARhMnpmdVk6j+DyqvZvhK+uEzmeUsRhC5NUt4nq7AB2jUqX4ykbM6XOph3PFDkXqxxMDtuHB9fQ+UhOJlcQmJTT80pgszFAdj4LJ20uHVzHQdQvEMe1XVXbS3U207g7mtTuURSlCpLQe/7zgVAvbUVRhsTznw+ccQZwzTXALbcAxx036iNShoVmNo2MIU3kboB8lozqdY5xZDxJqTG+3rtNJE5BLhUj36lND9PZchSaKaqrggD/FAQ4Nwj6/yeVbcG52Xd6dRAU05D8HHCcD6VXKMbALwfDnUiEjOw14/1+eq/TyazcOMbXNzR0+jnL1/pSFEWyzgleX9bTmvdn39v5vd732+DC9RtRJUPW4zJo/D1kL7kue63eI8APs99JZWdwdWC+095RQfl8oDbgtn0YFNDlssX5Ms/Ykwz82yXrNg20LYYQ99KrOW68nUsStXsURfHxlrechX/4h0UARRYCsbCwUFmTRVEUhTM/P4+FhYV8+ZhjimzJP/iDT+n9ZAehzqYNRT7I9JOo4ut65VV1MhwGeTm3M5MVvEA2l9awoxu5VIwdycvlN2K0Su1OJueRRiE67YkiUpPkZHwyIVJKpgXM7MqyXqBZTjuN3TDfK0klzuyCW0qGF892STBmkzCd9gTSKLTOwTiTzfOdv/y8lxlNMgI4X8cLZbsifAe9VquudTjeAdj3kH5pAa57laIoyqD47B6XlKfrPlPD9pFt11i+POA9tpuEmQyqtIHKmR/F+vKYDprokFwe6yvezfhOe8KorVL2krSB+O9bC0WWS5bx0pgBZloqJ7yT2A3znQZMMtGZ0e2yfbLlJATSaCI/1+S5WP2KSud6ObspG5OaayVJQnSt7KYBX5yqa7vffaC0oczq5h+g9o+iKEo//t//uy/uumsGzWaMZzyj6F9YWMDc3BxCTXVSFKUmYRhibm7OcjhRHbhPfKKh95MdhMrobTguKRkuH5OwvgZbFnrnrjZfXkskr+dhjT8s0mSKSz6GS8JESIXzyZaV6aAFILaiJ1OEiMMWWojRi7oIhEQegLKUDO/PpGQaLeOQiFDU9VF2BuRo2g3jSCxJ6PGJF/7iDqesvdoC0siccy7nUqfkdLLrGMgJl0RMuAAoxmQTlV1Xvaa1Rt3XnZSx4A7uqlopfGc60ZIgRDDkiNxBi7EryvbFd1OiG1iEsmEzgO3juwfWkRyuIgGAAOA2UBoiZQ89LjnhUAQhJOz3gNYnjn6giRhNTEUhOm2gEXcLh1MMtx3k6g9NXZ/d8Rr+z8qWZBJZrSZer4m/k41TYfv0C67htkzZrrEzU2SAWdHHM7kzrWIKsBmUfs5jOabqnlApFVx1cGs10LY/avcoiuLjqKNeBgDodC7BO995A2ZnZ3NH04EDBzA7OzviI1QUZbtA94u5ubl8+ZZb3g3glZiYeDpe9aqfH+HRKcNEM5u2BDUfbtY7ST3gPhLL6eSWj+GTJ8XYqPQQSv18X/lkTRgWczt8EympF4p+9iIpPXopO4MIxXcaOb730jkC0c/lh2DONcB/LhJrkZXxyoX0m9fwRfgOMh8ysBPLNVidTIqiDItNclzXvRf67q2e8WkSWTaQGeqXCa7CZQvx35aER/DJXbp+12iZyaYFkdo+O4kGzHfq/L49NSn5+dCjxOowdNo5Mhub90tcffJakNcKGzhYsM3AATWKoijKRkP1mn791xuYm5tDq9VSR5OiKGtmdnYWBw4cyO8nf/mXr8LRR9+GbjfEJz856qNThoU6mzYMlyyDlHKoyjIQ63zSMHJM1YOdzGTyvoqMjDQtS8PITA+XfEwhGdPySMi0LCmZXEqPy4D4pPOknMw0MNk2kiO7AeyFslOYQSEnM7MLhZyMr1j2LtiRvywCuNOesKRk7HOQyx61nOdyuZC2+7owkjKRuYZ8mU39Jl1816ocUzkpwxdck778XlS1fvzo5hNxw3t1NZFYGQtcNyWfhLDLIeWwfVxZ2K52lU0kd+/qz19MRjiR8qm2nJidEVtkycoM2Q5arL+QFTbbR4hbTaxyG6hKRngatg2U/TbOtKDsEPZyW4fbPFJKkZ8rFFzTNqZH3GoW5xeza3jblcldleUk5SMThNa1giTqb+PUsYdcwTf92tbGnH73H3mPGk/vlto9iqK4+MY3gG99C2g0gPe971fQbDbR6XTQbDbV0aQoypqZnZ217ieveMXRAArntrL9UWfThkJPQVWTKVI/3PFQ5JookR9R1/FU6wHPSGFQ3aY05RJh7ro1rgfSok5T09qWHnSpv4Mm0igs6c27NOh9jqcpcjhBZfR2EjPZa7LtkNBzOZxCOCVlem0joVdIyTTzSRdXbTG7ZpPf8SQz/Kh2AQAz20MTL8Qg1+VaJk9L8PsPtSuc2vn9ZzwnWxRF2Ujo/uO67/SpaemzgzbQJsptIE9wDc/srg7AKdquYIZS0E1VsI0MrmDOiN3T/j+fsr2Y4hJ6Pik9WbOJ1T3ttCdKATWxo4YYBeDYgTb9ZYOt891Xo3IY9g3gv94rzRT+TCX7fQE2rvGKoijjzSWXmPdnPAP4y79cyCeGO52OVXNFURRlEBYW7PvJ7bdfAAC49FJgeXnEB6cMBXU2bQlqPNz0ewDjYwadJ/ZslzJZDJfudh1pDT6Wr+Oa7wCQhGEu+wEuFeOS0nO9Mym9SQBXBQEuCgK8Iwicx6NsXd6RfXdXBQFIRs+S0POdE2DvjnWFhF5Z+rEsjxRZ6+T56huX90tJmfX4b+psq76hoeJ3Mq7vpSjjgQyiqRqzCQxsEwVW7coqUvHb4AvEkdskYl0+Rv6G0XtY0Zf9zgVtoHdUgB8GAa5W22fbcXUQ4GAQoHdUULZ3fDLCXCqYnRtpZNs58hyU5x+ndE6Kftc6ALWvGXEgg/UPhEthoupAxtvRpHaPoiguKMug2fxELp0Xx3EugaUOJ0VRBoXXfKP7yfnnvwJ79hzG0hLwr/866iNUhoHmt28YCWwFfR5l12DL/CtYRZGXQ+M8u6ZNfVkNa5KeoP4g23mnkMcIixoDHbTQQsf0Z9GSLXQQo4UmOogBhEjRQQcpUjTRyR84jJRMB82snWIZMWC2a5ngzCBFuRh2BGAFJmoTMJGeR2AesmOzHISmQPbMEfOXuwsqqbcd2Zu9KEtt9zQQ8AjfaZjzgUd5U38mIcMjfXsRELfM+RZn0bskLVNE80Z51HmcRwO3sgyoorZBlaxMEeGbyVAmEaxC2cPOaurrXF71tGlShd+T6nizFUVR6kI2zCrc0QA0BrBtHWH7uOwdX9t3b5Rj6rSRSehRdncIa/KUsjtMu/j9iJBaAQ002R+jiSZaCJGgiTjfNs5+Z0KkaLaaaLZWzP+esnOpTb97SdZOkNs+vB2EwN4YWD4CZZuxF5m9sweFjVNl+4hsJupbbZngGrJ3KGub2mTXVGVyV2U5FdeAkQ1OEp7RPeBLbsOpe62WTBVfNpNrXFWWk6Ioynjzgx8A//EfQBD08PGP/55Vo4ne5+bmrGVFUZQquKOpfD+5EMCr8dGPAr/0SyM8SGUoqLNpQyHnETmeEpg/OXcq+WZEIgA9AEExTL5XOZh80CHIvtJ+TWQvFf1NoxBpXsS6Y02mpNn0SnkihhxMRqKDnE4k69FCjA6aCBEax1Q0gRhdtLlTiR6mExQOBOZgyp1RmaNhKnM2RTAP7osVfwpla0KOpt0AptBHToYmX6TsIpPVi1tAp90QEyh2rSbXspQ/khM0pTGZhF5eKFvKyXCqnEq+cVX9pTG97N3lVOIMKjEzHqSYQDDkiNxUE4mVsUfaOwR3MAnbh29ap81tnCqbqJ+9lIToopDSA4A0lNJ5ZXvHzoSN0EELyJxLrqAb+l3KA3SiFQBAow1j3wDmt4y3yfaZhgnCoXbmhCA7SNlezKCPvVPD9lltFRJ6tr3Tctg1RT0xHlDjtXFk0E1m83hrVNahjuOpTjtH2j6u7KZ+Bzie9o/aPYqiSD76UfN+/PE34/d+75UlhxItp2m62YemKMo2JU1Ty9FEzM7O4sYbL8T73w987GNApwM0myM6SGUoqLNpw6nIUForPodR1Xj5Xudh0COJYUtpRNkuQ/S7F6RsEoa2SRAiRGoeXiOSkelm7yikQhIUMiIJW5eyNpfTS82i1m/afjQAt3weD46XLyIsj00j87DLJwll2yUx48MlH1mSCnFdO1XXXR3n01ATjTRrSVGUjYBnMvH2EPDF5dC6yDHWt59IjClNeFfLBPPfAZe8Ks9w4kELIVJrO96fIsx+r7pocGk0kkpzSOeV7KBsm2i4c8bKJhBRdlKVbJ7rHEDxntK7wxEqZfDs7LwiS5vjk9Rz2kiD1KisgyPb0DmmNupgUhRFGYSLLzbvr3vd/fDqV7szlzSjSVGUQZifn/eue+97X4JPfhI4eBC44grgWc/avONSho+GHG0Yrmg6V5aBlLeS7R4sfA9ycnkQWQrvK0KaRLlERpxlfiQIc6kxGflIBYhjNHO5jphJk6WI8n6KpqT9xmELcauJVYrU5Bkq045Xy90/swvYO11kyCjbC5LR2zsN7N0D93fvOwco8pfJycStJuKwZcniuSTy6Dylfn4uyywnGp9kGVEJiqymNImKSRdflG7d67Ru1K/V1/MMIlbFuy+baXwnX8gJOeyXoowHrpuWK4uyqr9X3hUf4voo30f3u5dW3ItJGjVNCrlUClCgrG0etEAZJGUbqdgmzl5827y/1USn3UCPZ7a4slpcr5nife8eKNuMvXsA0KvK7pH2Tvbea5ss7rjVZPaLsWvoXKN+25axbRw6h/m5yWWD80wodm0gCVHK5h4kwKZqm6prlq/32j6urG6gnOU0iCds56F2j1KHd7/73TjhhBPQbrdxyimn4Jprrqm13Uc+8hEEQYDTTz99Yw9QGRo/+hHw7/9u2r/yK6M9FkVRxoMwLO435OxWti/qbNpQuGOJ45N1kG320ON7Hhpksto391wxliQyiokWh5SG9cBa6LuXZcha+eRM8VBb1NCh/k57wi0bIh6ssQtOh1NjxkiRzIRas2k7MgPz3U1RrSaXg0meC55zpZCTaeaTKB02sdJhEzI+iRnuEOXnshzDr5WBJl2IOtfswPMifDLXNbG7FomZnU/hhBzuS1HGGxl0Q1RNCLMhdeygujZRFQmye3iUywmnWe0mtw1kAhhcNf1i5nziwQxcwqyoFZgFQoQtxDLohmwe+h0k+8flfNqT1f1RthVBPycT/86lDdQyksEUWMPrT3InEQXalM/Hci1KKa9nZUIx2eC8RmUVg1yjruWqtvcDXQEz1O9yco83avco/bjooouwf/9+vOUtb8FXvvIVPPrRj8aznvUs3HbbbZXb3XjjjXj961+PpzzlKZt0pMow+Od/Bno94AlPAO5731EfjaIo48Kv/qp5/+d/BhI1z7Y1agVuEL3efN4Ognc5RtCV4/sKeF0nx2Y+6kxo196Xqdtkb17I5ZmHiI43co1LxvjkY0hGryTVISXTgEIyhCRjuMyIlBxJgUYERClwbRDgNgA/BPDynsgUU7YEFwQB7gvgaJizvuGSyqv6vkP3epJm5FJ5ssg14ZOb4ev7RWmmNPHiok4Eb9V2VeudrHratOzesNfb3+eAFEVR3PR6b8jbQfAe+GWEZU1L2c9IsHZrte790zmZHZSGu34binWFTUTywGZ3tsyw/P2xZPSoncnpSbvGaQdBjKH2/QMs3QbccgR4kNo+W5LvBwHuuwdo7IXfvnFJKTrGkGRwlVyeD7KLeL0xFy7byeygIsBmUPtl3RMLPkdSdbZ2r3fGej9YUXY05557Ll7+8pfjpS99KQDg/PPPxyc/+Um8//3vxxvf+EbnNmma4oUvfCHOOussfOELX8Cdd965iUesrJX5+XlceOHvADgBv/Zr9rqFhQWkaVophaUoijII8/PzCMMQs7OzOPVU4KijgDvuAD7/eeCLX9R7znZFM5s2DXriqnoI4i/qS8pD6zzQrXV96RUWkb1pkQ3iy2YqMpUok8TIeVgyMSyykrJGYrSwhCnEaGKpNYXVTBIkz1zikZy+iE8uIzMNzOwBjgKTZevzDSmjYx+K7+gomO+OSwJZ37FPToYivLNzZzWL8iXJRi7faEs8luWM7Kw7+xznWU55ll7KI3zD+tcXao6pGgcxzrrPyPtJaTA0m6lM15GhsN5Xt4+jUlF2Jr5sJlrnexfjB7lfrsvmka/QkhPmk/JFdlJTXO8RCsnW4p3/psT5srSPsmzbVhOrXCqW20JV2S972PseYGovsK/l/XKUEXNUy2Tjg0vouWydXSi+e95uAb3pQjJ4CZP2ecRsnFicg3VtnKK/kNezZYMHsHnWc73CMcbC9Ywl7y2u8eMrGcxRu0epotPp4Nprr8Vpp52W901MTOC0007Dl770Je92Bw4cwNFHH42XvexltT4njmMsLi5aL2XzWV6ewY03Hg+gyDIAjKNpbm4OYajXtqIowyMMQ8zNzWFhYQFRBPzyL5v+M8/8T73nbGM0s2lTSGBH7vIHoka2LL8K/hTVQx5hW/Wg5XsYkw90g4zJpDFyeTAASWhHP1KUYwdNtBBnm9pjOmgBiPNJlyaQP8iGCNFCByRzFiFFpz2BNOmiTTIhQDHZEqOQD6Ei3zFMpGeCYkImAXZPA5MJkMTAMpStygwyR1MLmOQTKiFshxKX0uMvIa8Xt0yUL02mcOcRnxCkPi4xQ5JHPAOKSz9yWZkEYS4nU0y6OOo1+fw4/SZQ5Tq5nWxbNd5cg/i7T85KURRlGKzCtm1WUc50ojG0zmP7AP1NpUSM8do1jm1dywDAbJ80SZG2MpuI2T4py2KK0UITnaw/ZHZOAp7pRJkjNJ7ymjrZtiFSdNodAF00EuQ2Tf6bR7bPCkw2E7VjmN9DsotWsuANZUsyw2s08WCqULRbou20d1q5HW3L6BWSjdxZWsfGsaWFCyerLRssLkqXzbNex5N8L12r0vbxBdqssneOOpwUpYrbb78daZpi3759Vv++ffvwzW9+07nNVVddhb/7u7/DddddV/tzzjnnHJx11lnrOVRlCNz//qRycQ0++MHLMDs7mzuaDhw4gNnZ2ZEen6IoOwu6p8zNzQEAfu3XZvG+9wH/8R/HY35+AbOzbx7l4SlrRJ1NWwrfzIfjQU5219zUOaZqMjwjFdJgNFFCTqPSeKbVXUzI8MmZ4iGXy8fk20ckp9ct/h9SJobLx0hJkax/smWcTFFshHmuDAIcBHALgP0qKzNSzg0CHAeT1TSJ7KuLgIhLxZBDUX7HgPP7pjFpNJGfQy7JonJfcaFIGZkE5f3wyUKgKCJfYpDo3kHxbtun9okXnWwhzPc83AiaKvktRRlPXN4jQjqqxGZ1dl33EOR4a/K7LCcMuH5XyjZRWarV5agq7CA+LkWINAqRRt1CVhZw/wbydiralBG+L8AddwAHU+DhavuMlG8HAfa1MkcTOQ7rSAa75IOz7z+NRE2lUpZJce4VdVXr2Tg+6bxcNlhK6BGD2jiDXtel8VU2TNXONcgGULtHGS533XUXXvSiF+GCCy7Ave51r9rbnXnmmdi/v5DzXlxcxPHHH78Rh6hUcPHF5v3nf34Rc3NzOPvss9HpdNTRpCjKhsEdTo3G2wH8AMA+PPWp6mjarqizadOQEyeTjn4Z1UtjWGaUb0Ikgj1psp72CoqH2SQAEKGbpIhXmoiiFOF0WpooMZuajBCKfaQMJpLvoFjJZt5O8whgatP6ZthCGCZotlbQmGbHGLP/a+zp34M82jdIgKkYOCpBnt2kohlbg6NRyOdNAtg3DUzR5AtF+0ZwZzZF/vbKtJGTSRHl0owkAbOEybxN8jBcRo9LHnGZSF5oW0YAd1aadpFsmnhZQX0nU12nVFXUb2lBylfJaF/AH+WrKIoyDHxpDjLbm8bwbG9h+7jsHd6Gp3+9NlESogvkcsII7WwmXhNQZnhzmyhCKrK6C5vIOJy4fZSgGbaQTIcIE2EHkc2ToshsonabHXfLHn8UANwBZcTsDVlGE9k7MyhsmV0oMpt4mxyHlOUUGfm8pek2SP6ukM4r2zjpGmwcSzqPbJ64iXilNbhscB2bZpAxFol498kDS3tIHU2KUod73eteCMMQBw8etPoPHjyIY445pjT+u9/9Lm688UY873nPy/u6XRNAGkURvvWtb+EBD3hAabtWq4VWS7VfR8nttwNXXGHa73nPaXj4w5vodDpoNpvqaFIUZUOZnZ3NnNtLmJj4F3S7L8HFFwOnnjrqI1PWgtZs2hRcDzSuOgayz/MgVOfBzDW+7phSXwCrbkFaREtSPSaS7pASHFzvvajrZEuU0UNxoR/fKtrtCVsyREqN9KtbkNX8mdljHvB5XSBltFj1tEJgStTcqvXidSyy86TTbjhrEshJliQ/ZyPrHJWOJx4dLKVnqFZTIaEX1Ls+616/VZMszgkXWiFlY1Yd66WDSZ1OxLDrFvgiw+vw7ne/GyeccALa7TZOOeUUXHPNNbW2+8hHPoIgCHD66aev6XMVZf24blBc2qqubSR2Oax7al1bKbu/p4kJLujEtl3D5VnJwSRtIlmbyZq8F1KucT87SNpCVbUsRQ2nvSqpN3L28vpM/Luqa+swKeHlXQ3rXInFueiSB64KrpESwlw6L0GITtwsMrmrZIP7XVu+/n72TqVvqJ9t46vfpE4nQO0epZpms4mTTjoJl19+ed7X7XZx+eWX4wlPeEJp/EMf+lB8/etfx3XXXZe/fumXfglPe9rTcN1112m20hbmYx8D0hR47GOBD394IXc0dTodLCwsjPrwFEXZwSwsFPecbvcfAQD/9E9AFqugbDPU2bSpVE3mVk3yetZVPRut1fFU46GRF8kGClkO03ZLlHEnlN1nP9DSPvKH3ShEj0uGMNkQ6xlGyos4JEcakYmRJsm2TwcBPhAEeGvAakIoG8pbs7/5p4Mg/2oaQCETRK9BpWWy5R5JyrDzCYA1eULrbYmYSPSV5WOkrAwVybaommyRVI3rt713Xb/7iG/yVydatiIXXXQR9u/fj7e85S34yle+gkc/+tF41rOehdtuu61yuxtvvBGvf/3r8ZSnPGWTjlRRfHDHd78xfVjPbarfvbbGvvn9nsuommXb7nFJk9kyelHJjvLaRD47yPXy/DZSO4iA3lEB7ogCXK+2z6ZxfWD+5r2jAgRtOL+b2tJ5gNPeKU/0++WBpcy1pGzHh6Vzvi/rsXHq7NdiLc9WavdsRdTu2brs378fF1xwAS688EJ84xvfwBlnnIEjR47gpS99KQDgxS9+Mc4880wAQLvdxiMf+UjrdY973AO7d+/GIx/5SDSbzVH+V5QKSEJv797P5TWa4jjGgQMHMDc3pw4nRVE2BF4XLo5jzM09CcBh/L//B3zpS6M+OmUtqIzeppCgvmQMUEjr0TYRrELZCev2RQC6PsoXIVinvdJA2s6KXnuKZBvZPCMfUy56bUvGFJJ6hcSMGR+xdoIwnEI4fReaK10jI8Pl8hLYkjG8TRJ7aTF2JgF2JwAOma5l9tdWNgeq0XQ0zNm9LzRRvkEbJsWJS+ftgZlY2cParuLZWaTvagvotCewFE5lsjEtLGEKS5jKo3oLyZhCOo9LzHDZGC4fw7Ocisy8okj26koTWGlURMYP+QXRBlAUyObSeL6J3n4SM+NNggn01hiR6yNdQ2zHueeei5e//OX5g/z555+PT37yk3j/+9+PN77xje7PSVO88IUvxFlnnYUvfOELuPPOO9dz2IqyDsiWWYW543PZ4Mgxhphk/RFy24cY1H5Zd7uQE06SwgHUCZsIESJCIanXQSuXyyO7p4U4t4mMrB7ZRGbbuNImMrJ9lh3E7JrcfAQK6VZazyX26P+TyQvvBYDDUDaJ3NZxSQVThhOXCu4jG7wybWpTkr1DUnguG4eynkgij9s4MctuKsYUtk/M+tPUBNg4ZYM381WC2z70nqCcycTtIrlOnwTU7lH68YIXvAA//vGPMTc3h1tvvRWPecxjcOmll2Lfvn0AgJtvvhkTExrHvJ35yU+Az37WtC+//A+sGk28ngpfVhRFWS/c0UT3lrPO+lN87GNfw3/916Pw+tdfjS996ZQRH6UyKEO3CNI0xezsLE488URMTk7iAQ94ABYWFtBjBYl7vR7m5uZw7LHHYnJyEqeddhq+/e1vD/tQthh1JWN8HiMgf6CqMwHdr69qP55Xd6WJ1aw+jZHSi3JJGC7ZEbOHWim1R5IxJZmYXPKMv8yDcNxqYnlXAz3+8E2yIyQtswtl6RjSwWcSMkEmI7MXxuGxF8b5oWwOe8VrZlc2+cK/1xkUky/yeyX5GPrus+Ve28jJxK1mPjkSo5lPuJQl9YpzkMs+8vGFxGMhK0Pneoool9BbXWlizXULiPVcowDMvcG1sXyvIzGjUObBsF+AKXbMX3EcO4+h0+ng2muvxWmnnZb3TUxM4LTTTsOXKsJ7Dhw4gKOPPhove9nLhvtHUbyo3VMF3Zdc9x1ppEjnOPU7bB94hvrsH/mxA7+EnDDL8KbfCRmgwNen+aR/M5crk9u6bSKHHdSCX17Y9ZvJX8IWUjaH3NG0B+7vRX5vUjaPSeetThu5YG7vVNk4/FxL2HnIs7rpXJXntLU+qZANXo/tw9uDjAFQtn3oXQbU8J3AM2a8UbtHqcOrXvUq3HTTTYjjGFdffTVOOaWY/LvyyivxgQ98wLvtBz7wAVxyySUbf5DKmrnkEiBJgKOPPogDB15UcijNzs7iwIEDSNN0NAeoKMqOJE1Ty9FEnHXWowAA//3fD1MpvW3I0DOb3vGOd+A973kPLrzwQjziEY/Af/7nf+KlL30p9uzZg1e/+tUAgHe+851417vehQsvvBAnnngiZmdn8axnPQvXX3892u12n0/YfvR6b8rbQfAemAecSZgHHJ7xRP18GbCznyqQQ1zPUFXPXTVJk6iQk8neqqQ4zLtbsiNFiBBpdkimTXVxaH2KyEQOh5ncGv0/pdQIHG0eRJ3VG220gMkQQGr+2pMAPh4EOAjgNgBvYhOEyvp5axDgOBjnEv29GzDfQYPk8mjSTMrn1ZSWSfLzsJAi4shzisNrEsj+oh3Zy1mEb5qs8xbqm+dY1/yHa2LXNdFb9Pd6r17rhykDInXq3/KWt2B+fr407vbbb0eapnnEKLFv3z5885vfdO77qquuwt/93d/huuuuG9bhKjVQu8dNr/eGvB0EF2Dok7pkC/jMI95PHy1tpKp903veZrYPOs7NXL8bIdJSv9l1iCa4nWTLtiZiG8sOov+Ly97hcsMt2HYQG0+SeocOAwdT4OFq+wyV64OgyGiqkHjObSCX9CH/7th3nIShZe+U6kmyFwBIGb3y2OLCqKqzk9v/vlpNPlzPIj6HsG/MUDE77PXOGPaOFQdq9yjK9uCii8z7q1+9D296kztzSTOaFEUZNi6bAACe/WxgZgZYXJzBF78IPPnJm3tcyvoYurPpi1/8Ip7//OfjF3/xFwEAJ5xwAv7P//k/eXHPXq+H8847D29+85vx/Oc/HwDwwQ9+EPv27cMll1yC3/iN3xj2IW0xXLIyXC5PSsnwbVCMrYreXW97BcVDLW9nE+t5cWAAcdjKnEVxLh9jx0fmgmNOyRhyLgHIJmSi7C9RPAJ30EEahsCuJUTpKoKQHSufSOLSMjHr5w+pWf/eBEhSoJHJyCxnf1nu+lOGA0nnkbNpH8zkS4NLybRQZDSRrMwMa/PIbd5mWU1L4RRIAoak85aZjJ7pn0S1xEwhK1PI5znk9ZLQXSSbZIxWRHutkb91o4NzBxO/f7ikZOQyoBlNZdJ8xm/Y+wR+8IMfYGZmJu9vtVpD2f9dd92FF73oRbjgggtwr3vdayj7VOqhdk8dKLiG37i4CUoBONJZLgJz+L3RJSU8iL0j90cvr0RxYOTDAMQrTYRRijQ0wTItxJmVk2S/J2nuZOrA1KZoooMw2xmX0QuR5DYPjcltH5Z/YtlB/Hh5gPEKa8eeMez/r5J6G4clneeya7hUMNk1XFJvF0q2Ty8y9o5ts5TtlzjLcHLL6BVjyL7h8no8My/vT0PEK02kuYSeJ6tprfZOPzsIjn5rJbdvEk+/T0lCAdTuUZRx58c/LiT0XvCC0R6LoigKALRawOmnAx/8IPCRj6izabsxdGfTE5/4RLz3ve/FDTfcgAc/+MH4r//6L1x11VU499xzAQDf//73ceutt1op8nv27MEpp5yCL33pS85JlziOrZT7xcXFYR/2JsMfhHypSNLxRDhqN7kmT/iEyVodT+Roov6VAIga6EZ23YI0DHNHE69b0Moif3ktJ5La4xMoFNnrqlvQRBMhptBEjDBM0WytIgyBhvFvFf9HWceAnmN4DYMU+URMkACNbJJl9bBOt28kVKNpL8x04d49QGMGZjKFJl/4xIqsT0ATLaHonzZyMmlknJ68TpOvbgGvTVCnNpOz8LasW0C1mnyTLPD013U0wbFszZH0xCBZj6A0O1PRr2w0MzMz1qSLj3vd614IwxAHDx60+g8ePIhjjjmmNP673/0ubrzxRjzvec/L+7pZvnkURfjWt76FBzzgAes8esXFRtg9wE60fRyBM9Y6V10n6me2D1C+N1bVsPTdR13b9LWbQnRhZ3gnYZjVYkqsLNiY1aos12lqWb8uJmCnWVHLKdsXt4Ncdg/NFaewzUvueBJ/jwCZw0kZKpZ0XoRC1tkXRFNVp6lV1KXk9g7ZOORc6lebids2hTRwJOwcWs7eWSZ3Nw+wwdptGnk9VrV91zEAd60mVz0mjrSRlM1A7R5F2fp89KNAmgInnQQ88IGjPhpFURTDb/yGcTZdfDHwl38JhMONi1E2kKE7m974xjdicXERD33oQxGGIdI0xVvf+la88IUvBADceuutAOBMkad1knPOOQdnnXXWsA91izDIZC+fhGGbu2RifL4s3yH0C/SzHgIL+bCmNaSQ4uDSMACX0SsmYqR0DMnEUB9N3FhjogkAXTS4vEgbwBH2/+VSMm0YJ4CUJsmcUVFoS+pFAD4dBLgDRlJvv8rKrIlzgwBHAzgK5m9KWWO5dF4bxffA2xFb5vIyLtmZyDia0miiJBkD+M4/ec4VEjPyXOP9lpyRrFvQD9eki2uMaxvZdo0F4J9UcS2rg6kf3Q2I8O0OuL9ms4mTTjoJl19+OU4//XSzj24Xl19+OV71qleVxj/0oQ/F17/+davvzW9+M+666y785V/+ZUnGRhkeG2H3ADvd9iHZYIddsxa4oygSfdSGWB7kFpmvqz5Wl4wr9Re7Kv9Omd+fTr7O/k2K7N8nsoN8MnouqbYUxe/tChuTjVdJveFQks7j8nj0XUibx2X38G2y9zT7fvk5xu0TrifA4XaPHCvHec9fsnUok7sK37VVFTzjawNDMFl8zid1OHHU7lGU8YYk9DSrSVGUrcRppwF79wIHDwKf/zzw9KeP+oiUugzd2fSP//iP+NCHPoQPf/jDeMQjHoHrrrsOr33ta3Gf+9wHL3nJS9a0zzPPPBP79+/PlxcXF7exASlnPCiSF6Lf9WRGMymN8hDfA5pvojpBMeHQrtiPs11E9HZWmgini8hdekjtiIjeEIWMnk8yhm8fsTaNB4CwlSJsJQiTFZPdxI+P15vlUjJcrYGifSMzPoiAoyJgNTaSehGMpB45SJS1QTWaSDrvKHik86qkZCgaeFq0szEr08DSdBspIixhEsuYQoIwb0sZPTvjyS0xwyOAZZZTHhmcOZoq6xZUvYYlM5PDLwKXTIwr0tc1Vtlq7N+/Hy95yUvw+Mc/HieffDLOO+88HDlyBC996UsBAC9+8Ytx3HHH4ZxzzkG73cYjH/lIa/t73OMeAFDqV4bLRtg9wE6zfaTEJ/cMuWanKaOJ9ztsH1oeJJN7xTFeZnK7xq8AiAIAEVZXmoijBFGUAm0gCrlUcJG1ZEsIm34A6KCDMLNxmlkGE0BywsYeWs6zntx2ELCCdoIiu4n+H3TcbfF/onnfaUd/CASpsYcaKqm3Zu7bAmZcdo1LOo/L68nsbZ7tHdazd3jG9hKmchuHsqA6LBuqyPx2SfCx/rSFzkoTSRJidaWZ2TyBLRW8UbYOKvrzlTxL29cGe9es7q2O2j2Ksvm87nV/jiuvfB2AAP/jf9jrFhYWkKapt6aKoijKsJmfn0cYhpidnUWjAfzKrwDve5+R0vv3f9d70nZh6M6m//k//yfe+MY35rIwP/3TP42bbroJ55xzDl7ykpfkafAHDx7Esccem2938OBBPOYxj3Hus9VqDU3fefTIKF4pGePqlw4phxtETry4Jl+kZAwf229SJuLtom5BkhiJDYTkYCJHUmI5nlqZJyhGC00mrzdo3QKaoFnelRZ1C+hY6c9FEbzUz2uv81pO7JRqJMDRIYBDxRSXOpvWDtVo2guTzeSsW8Bl9LhTScrl7crGiroFnfZgdQu4fEzRV65bkOZnY2htmyJCmoZs0iU00pKuOk3DciS55kpKyFpM0sEk+zS6tx8JQkyMOMIXAF7wghfgxz/+Mebm5nDrrbfiMY95DC699NI8Q+bmm2/GxMTEUI9TGZyNsHuAnWb7JCicR2SMuAJt+JgK2T2XXcPXVdk4rn6XpB5fZ+03AM/wDpMQSUjSeVTH0pYQpv6yRF5qSQuXA3X8dlDUThEmq2jEML+N3KFETij5/+GOKYh2Nr6/2JXiI3c0+ZxNsjYTD6KRtk8L6E0bU4PsnUI+z+ckaua2DB/jsoPI1iE7Kc3PSFZVVWZyu2o11bV7iKpnDjnGNc7CZe/Ifu58kmMUQu0eRRlfvvnNR6LXC3D88T/A/e5XBDUtLCxgbm4OBw4cGOHRKYoyboRhiLm5OQDA7OwsfuM3jLPpH/5hCcvLB3DgwNyIj1Cpw9CdTUtLSyUjMAzDXEP5xBNPxDHHHIPLL788n2RZXFzE1VdfjTPOOGPYh7NF4RF2Lp27AWRlXBMlLhk914Mad9C49umbkEgAV90C/kzB5fLMJi55s7JkTJRPp9hyZ9TOx4chknAVETKpEvo/cxUIKStD7RUU8iVxMT6IgMkWECXAZCard2UmqXcIwMtVVqaSC4IAe2GymCbpFQKNCAgowroFWzrPJxvDl8W4Hs15hOXcOS7J6JKa4eeQlHRMxDmXiouD1y3oi2+SRY5xbSPbqOiHPCddjiTXAXDHlLKVedWrXuWUjwGAK6+8snLbD3zgA8M/IKWE2j11Iem8OmPIOcX7I1h1mwD73lgloye3kfJ6g9pHYNJi6OS/F00xnPpD2PaQS7bV9ftEgTs+OyiNVhGlzA4CynLC1G6jsHlWHP1A8Ru9L8DiYeBgDDxIbZ9Kvh0E2EcZTfT3c0n/Suk8aefwvsxmSkIjn0f2DoAKeydy2jJAcc5Je0lK7hF5Xp4vk7u8gf85o59dg4oxclxOD24HExz9LjTIZiujdo+ibC6HDz8bAPCDH/w5FhbuhdnZWcvRNDs7O+IjVBRlnKB7DjmczjxzFtPTd+PIkV140YsuxOzsb43y8JSaDN3Z9LznPQ9vfetb8VM/9VN4xCMega9+9as499xz8bu/+7sAgCAI8NrXvhZnn302HvSgB+HEE0/E7Ows7nOf++T6zDsbV3QvPSD5+qWoGyuU7YsO5O06kjF82SclQ68I2UNnhDRK8wmXODSRu6mQfSkk8orHWxY3mfdz6bwlTOXZUEUBbbsd7UoRJimm0DUZTjwAnEvqVUXx8ijgEJjJ/k6Nw0AUm+5JAFNQ+nFfFNlMEYB908AURejuRSENMwOTrSSje2dQlpURY3rTwNL0BNKoLJHH27xg9lIfiZllTFqFtLm8Hu83ky7mhZVWEeFbJ6p3WBlP1kQMTQDKqF2XTMyqo983y6qkCNEb8s/jWiJ8le2B2j11IGeRK5spcoxpsHdOZv/I3/VBZPSq2tzson6XfbTSQDcytki80kQYpaUMb4BslrJcHpfXk2ET3FYq5ISnnHYQpoFOO8VurBqr0OdsSx393DkXZmPaRf9MC5hchNKH46aBqb1wy+K5MptqjlmdAZZ3NZCEfnuHspmkLcNlg7lUML1zeT2X7cMzudMkNGoGPKupKpN72PZOLdtHSgW7Mr3lWIWjdo+ijCc/+AHw7/8OBAHwutedgLm5/Tj77LPR6XTU0aQoysjgDidzTzoXwCsxMaGOpu3C0J1Nf/VXf4XZ2Vn84R/+IW677Tbc5z73we///u/nXkkA+JM/+RMcOXIEr3jFK3DnnXfiyU9+Mi699FK02+2KPe8kXNIwCcoZTRTdyx+OuEOKRfj6Jkx8/a51vjZ9nKxbEAHdlSbiKEUYJQijFGlIUytJHrkr5fWkg8klGeOv/2ScUCEShOEUwjAFsITppGuOk2RjfBldKWtnDiYAxjnFJl9mIiA6DCSJcToN/ULZgRwN41M6qgVEETDFJfKq5GNccjMeSb2l6QkstfiEyyRc8jHFRIxbYiZ3IMGWy+PyelZ/3ES80kSaROiuNN2OpmHK6FVOtHDkZAsf6JLXk/066eLCTLqMXk5G2R6o3VMXlzeH90uPEV/PbR/WXSWjt17HU9+2mYRPo9TUr4xMLSUui8eza6kfQMneKcsJV9lKU6DaTyFSpGGKcJoF3iQoZPXoWLntw2taUmAOOZt4AE5kMpOVaqaORjlwZhcK+2UXLBlgtOGXzrOkgicQh61Ke2cZU85gGe5YkrUoC+lgHg4mbKK4mWc1GUdTuLG2jev5xPUsYw2gd58N5LoxyLpOCqF2j6KMJ//4j+b9534O+LM/+2O8611vRKfTQbPZVEeToigjZXZ2Nnd+R9E/IUleiUsuAeIY2DFK8zuYoT9G7t69G+eddx7OO+8875ggCHDgwIGx1H/t9d6Ut4PgPSgcTK4KQa6oXofEDJ9wqSsZ41Lvk8ty/qcPaVa3wGQocRm9TjEmj+dNLQkPKWlWHEp5DC+7DQBpFKIXdY3rjUvGxCiynaTETBt2PSoaT+2WkdRLImAqBpYBfC0IcAjAIszyIoy83hvGTGLmHZlc3l6YM3AvzNwKZYBNtoHIJRcjl6kOk5SPoXGivxeZ75pPjgCwJk3s88UvMSMlaDh8/JrxOYh8EyqD7Ne9IPBNohT9vd6rB/hgRVF8qN3Tn17vDXk7CC6A7fzmQTcum4f3iTGue2zVrVvef33bVs1X03sSAVHC5PRINq+Ttd2SZhyX1Bntp0peT26bRiGSsGvCkLgsnpTUC2F+exPYNSz5ePpdJpvo/gF6h4FDh4EkLWyfU8bM9rk6s31mYGwcqxaltHHIfmmzfikh7JLaiwqpYGnvrEcujyNl+BIxhts+ae5oivrbNVUmSdV159qXb1uLus4iW0641xsn6VJFUZRqLrrIvL/gBaZGEzmaOp0OFhYW1OGkKMrIsO9JV2JmZhGHD8/gssuAX/qlUR+d0g+NWRwpq6ItnU7cMxSJsQ2U5PQGjcolZ0ub9Ut5Pdd465AaWI1SpFEm9RKZKFuAy+gVEbrUX0jD+OT1isjdZXAZvcR6KA6RACEQTt+FMOkijxHnUbwkC0P/D5oImIYlGZNPBsSmP4iARgLsawGTh4HVBNidmkmWBGbCZRwLaZ+AwsFECnkzWW2mGV8xbMpUqisxIyKDV6aBNJrAUlhE93K5vGVMWnJ5MgLYJYvn7neMT0PEK010VlomwnelUWQw8WymzZCUyeH1CihCV0rFyIhfOV7xoRG+irKRkMOIfni5/SMzvKXRIWwf2p1s83smt1184wexffIxAZAYOb14pYUwMhuFLVtGryqbSfZHVn+xHxpXtBNrW4QAdi0V0sJ0jD7pPLodpaK/jcImJEdJAgQt4KhpADGw+wgweQRjx3EA9nJ5YC79Oy3aIlOpZO/wMR6p4LvC3XlGEs9s4vYO71/CpCWXZ2d1V2c5WTaRzOReYYFt3K7pZ9sMU2I4pwfbhnFJ5Pmyt301LBVA7R5FGUe++13gP/4DmJgAbrzxL/DOdxY1mqhmEwB1OCmKsunIunFm+e8A/DE+8hF1Nm0H1Nk0UuSEC3+Akk6nhPXzh6VGech62hD9tWo5hegCRRFhICtmTDJ6LXAJmPryeu56BnnNpmxMiBRhawphyxxwO4HtbKpTv4nafCKGZGWiopbT5BGgcaTIL+tX6nwnchzMHMtuZJlNcvKFnERVjiRXP5fO24V8gmZlGliabluTKeQUcsnl8QkXW2Km6ZTLo0kWmqCxIoPTcDApmSqHEyq2G9jZlIh3X50m7nBybacoijIKpFPJF2jD+/rYPnKo/F2Xu/e169pNubRwC2lWvylNUqQtc9xhKeOESwMXjiSXvQPIQBu37N4SJguHVIhcWjiX1HP9jXibpPOYveNtZ06oqcMm83vcOG4vEPicSjyIhtkvuYyeRy6Pt3uRLRUco4llTOU2i89h5HIwyf5SPaaSVc3cnZnNk7oymoblPHJdV74+C27TyJW+QBv+bKUoiqIQlNV0wgnfwzvf+XqrRhOvl8KXFUVRNhrpaALMPegHP/g7XHAB8E//1MGRI01MT4/4QJVK1Nm0ZXHVdaJ+IaNXRZ0JFr7scihV7TeBeRgFsgfUTNYjrJbRM+0U/SRj+ASNlApxSYik0QQQdc2HcUk9PuHPJWZarL/F+uWYzAHViIHJEGikxePr1UGQy8oAJuPpLgD7t7nEzLlBgN0oMphmUMjlkWReFGaTTlI+ps2WuaSMRzYGJLvHx4VAr22+Uykf45KJ8csOhWKbyDu+JFWThMV57Zt4ceFa77vm6radHwKUJ1H6TazopEs/0m6IXnfIEb5D3p+ibF+ko8kHv4n2sXcS2FnKcp0cg4q2z0kj1zG6FGiTmCAFhMbGccnfcbm8prVrLmfWcfbXkt3jkno8MZ7bNb42t5t4m+ygyIwNUgD7AiweBhZj840uw9g+211e7+rM9pmEOetmWiZrO6CsL8qC57YPl8Xj7bZoR6Kdvbul8wqbxWfvJCh+V3z9ADz7kU6nCGkamnM4q0cmdlJ9Tchx/dqubfutK+FzPFWNV1yo3aMo40WvB3zoQ6b9yEd+Db/zOwdKDiVaTtNUbq4oirJhpGlqOZqIv/3bl+Hiiw/hJz/Zi49/HPjN3xzRASq1UGfTSKEJF5dkTNWYVTY2giWlB7glYxIU0ii8LcfzaF1XdLAry2klACJbSiaMUsRh03qUJXhEr6swdjGuaFf100N1iNQ8+O9ZMpJ6XBqGcBTAzse0RJsmV47AeJASoNHOpGQSIyUzk2U5kVNmFUZWbhHbn/uhcC41UPwfGwB282wmHqHLs5Y8MjF5P8nrUdSvGEPSeXe1SEomxBIm80jfZUxZUjLLmHT284jejksyZhApmapIXpKVgWOML+qXj++3bQ5J6HEZmYT1+eT1ErGNoijKqJA3Nn5P4gYMBde45PWE7cN36ZPOqzsRzu0gX4Z33h8AUZHh3VlpIoxShK0k+82xpYXNbgrbx6zj/WV7x9dP64r+xJLUa4Zd46ZLUK7RRFlLR9j/VcroudqtbJsEmJk2dlAvAe46YhxP253jYBxMu6czZ12fjKRabcp4IjtzT9FenQE6bZd0nt/eoWxsO3vbztIuxk96s5ysbeNmOZN7JXBnK0kZvWHKBfucWrntw20bGuST0ePvdR1SiqIoO5//+i/g+uuBVgv44AdPx549pzvHaUaToiibzfz8vLM/CIBXvnIvzj7bOMvV2bS1UWfTyJEPQNSW8nrc4yP7s0kXOYTvUu7G97FVEy6ufrB3JiXTWWkinM7aTEYvRhOyflMhHeOvbeCu61T0c7kZtFBI6vH/G2DL68laBXwSSfY7nFBTLZPVk6TAzEoR3XsXdkYtp/vCTPORXN5MC5hsm2ymYNAJF5eziRxMFPnLxnPpPJKSKWRiWk5HEp806VuTQNRpGkhKpk6tgioHk2syRV5/3kmXnmdDOZni6tcJl7o4o7rXSW/I+1OU7Qs3VoAia4k7lKi9iqKWk5TaY7aPz1SSH1nX2VTVloefwAQjRBFWgbx2UydqIcpqWCbZ7xfZLDFawsYJ2bLZ3heAIwN2UjgcT5mkXhrFAFYRpUBAdZYSGGcR/7v4pPOq7KAU5vd7GggS43TavQNqOe3bAzQocAYoy+JRVlKVU4m2rbCPetNAEgLLuxqIw8IeqXIwkf3CJYRtu4bXaSLbJsr7aZuSjF4mGZwkIVZXmsBKC6YmGcq2D2D3r8eRVNc2smwfX/AMd1j7gnHU/vGhdo+ijBeU1fS85wF79oz2WBRFUerywhcCZ58NXHYZcPvtwL3uNeojUnyos2mkJPBLw/jk8vgTmGdbPsQlExOJceuUj+F9g0jJcKQ0jKufHprlflySaYDJiulFWaFskivhD81AIXdCbYo6TVH8rWSbllMjJdNIgNUEmEwKeT0AuDYIcBeMtAxJzFA7ydqjkto7NwgwCfNfaqCQxqMMpkk45PLaQIP+PlxOhtphRZvLy3C5PJKjiYpXL5LSea6qXbaMUOpY59uGGEhKhk+6cErOINHvWnat6zfGCZ90kf1AdfaSTrgoirJVIMcSBdlI46WG7F4ihrjsILkL1324qi0/x2MTpZm0cJiESMLC9iFpPP5bRL9DxmnklhnmUnvcDmqyffkk9ZIwRBqZ34KGtHeoTVnc1B+x/pWsj74WanN7itlHJK+3dMRkOnHbB6z91BHZPldmtg/V27Rsnyxju8EdSmSjtFC2WbiEnkMGuDRGrDeyedl3xOwPn3SetHcAOPoj6xyhMe42s30SsnnEReKycXwmR9227PM9W9QyU3gmN73XsYEURVHGl7m5s/De9/4xgBn81m/Z6xYWFpCmqTezQFEUZbOZn59HGIaYnZ3FQx8KPO5xwFe+Avzf/wvcfrves7Yq6mwaOS5pGL6O+vr1i+wmX0ZSnfZA8jHsMFYCAC10owQdAFGUIoyMtJ0rm4koonWLiF7KVKIHZp98TIgkf3gOM6dWisj0t0KkkZGSmYq6Rg6FJkVckjEt0W71aU8jl5KZioGprL03BhbvNse3mJqJFXIu8QmXJYyO+8E4keSES5S9z2TzETO7mIOJpO94hC5QL7OpRrs3bYpjp1GIpXAKS5gESclQ4WsjGWNLzFDUr0tihqRkAFhSMlVZUSQl01lpGfk8WaeJZzZJGZl+WUxrlZ0BUET2rjpesh+O/kSsV3ykSYRATrqtk96Q96co2xc5QczbDba+wfoT2PcuYfvQEL5Llx0k5fVouV2jDbY/fgi5TWRsoDRKkSYhoihFJ2ohDd0ZSSGzXYiQ/Qf4GFqXim3IUTWV9UfMaZX3TwNRmiKNVo28MDmNyN7xyehRP0Q/2T4pLDsob8PYQ1MrZkxvxTieAGA53iK2T8ss757OajHR38Nn7/Ax054xA/SvTAOddgNJ6M9g8knnLTE7KBbywGQ32dlPxnYC4M7wTkPEK010VrI/ykrL2PMu+0XKBvezbVyZUHVtnxxp+yTsXd5DpF0kx6r940PtHkUZH37wgxOxuDiDdnsZz3nOZN6/sLCAubk5HDhwYIRHpyiKYhOGIebm5gAYac8XvtA4m97+9ptx8816z9qqqBU4UlwTLtTPPSP8gSqCeyKGfZWDOphkzaZ+TijAMclC/QGACN0kRZIUxap5/aYqKRk++SKlZKTEjDkMmriZyidfIj5Bk0nJAEuYQheBa26L2tLn1885tYJCSobaCdCIi7pOMzGwvGIyn5bTcmbTqLgvUI7uDYFGJDKYeEQvn3CRUjK+iZU6ky/TJptpaXoCS61yjQG7JoEtMSMlY1xSMjxi2CUlwydfuJRMN5fPC6odSYM4mNbyyvFNmrgmXujdN0YnXKpIkwkEQ5eTmRjq/hRlZ5DAztJ2Sek1RD9tB3htH9lX9dsvt61jB3ltosAEKeQ1LI3jqX/9pkJmuOizbR2XfUTrCK/jKkyRTMcAVhAm5rc+dxJxG+cIbBk9snFC1i/rW3KbKLN9MA1TFyoBghUjsQcYmb3lEdZ12jdtHE2BtGUA206h/9cgdhDJ6FU4pFZbJptpabptBb/I4Bp3UExh15DzqJM5mEzbOJ4AWLYP7U8G11BtSgB2nSaeyT2obPB67Byv7QOU7RcZWKOZ3OtF7R5FGR+i6MUAgJWVf8A733krZmdnLUeT1mlSFGUrQfckcjj97u/O4vWv7+Hmm38Kf/zHf4nZ2VeP8vAUD+psGiG93nzeDoJ3ZS3uYKJlKaMnPSOucaxbtuXDnPw4oPyw55rA8fYHAJPjCJMwl2vpJyVDY1xSMnX6YzTRRIwEJEtTOLySsGtioHlCGGUp8YkTXrfAN8YlJUNtIiy+kYge2lPj2CFH09eCIHdAAUUWFFB+fO73uMzPiAaKz55k67hknuVsIpm8KHM0uSZceNRv5BhDUjItdkBcPoaPYfvoRcjkZGwpGZpYsaVkCokZKRnj63fJ6LmkHAHYUjJ80oXjmwyR10vdyUvXtrVxDfbvvNfbP8jOFUVRhk6v94a8HQTvYWu4HeNyOrnw2D60SvqnXJlJru0GafPl/D3M6v6FxuGU2T7czgEAqtREfZSRZGVpO8aYdmrth0vqhfkYs21uE0UTALqmhhP9/8mZBNiSerzdRiEh7LF3ciJHf+YDCwBMRUDvqADLWTAOYIJxXOFXdcMi+Blg2TvZ50+2jZNpspXVnCQHE9k1gG3LuPql7SPtIJd0XlS8jERwIRMcZwKJVTZLlUReAttutuWkZYiWLc1H2wDIz1OQo6GujdOvLanaZ6XdU7Vy1dNOrL5e74yqD1AURRkb4hi4+GLTfulLW5ibm8PZZ5+NTqejjiZFUbYs3OF09tlno9f7FIBn4N73VkfTVkWdTVsGOfvBpWS4d4SPcUnwMTkZvmuaHKgjr+eK3O0nJVPqb2A1SpFGWSRulFpSMpwqiTzq6yclI/t5pC8ApGGIZM8SojTFZLhqahcAtnwMl5XhcnkxyvIxvE37idn4zLGEFZPp1EAmKRMDvQRIUjbJEruFzwD5uGz3EdLJxPsaKOLCgSJ7CTCTL1GYTTjRZArgnnChMVw6z5fZNICszCBSMgBK0nlcUs8lJbOMyTyKl8vQSLkZKSXTTUJT8N0lGcOLZFdJyQz6csnN5PRgnx1LrD2IjJ5ShzQJNyDCVwtlK0oZsmO4EUG/WD5DBai0faQzxJe9zfvp/ivtnbryevyQogYQ9dBNKLsps2Va0vYp7Ji0wpbhcsJJvo1tB/ExxtmwnI8pakKFSFshwlaKTjvGZLhqnE4rKJxCR9jf7gjK2dtSOi9GYftkNg6Awg6SY7LlAMYmmuIOLGrD2EmAsZXqkJmahQNNOnvIngHKziJyKu2C7TCqm9nEs5lQHtNrGz/O8q4G4pDsETuDiWwZn83is3ekrURjbHngQmqPJIkBoBM3Ea80TVZTLhkcuO0dl43Tr11lG7nsHd6fI20fKZHnuj/IUC3N5K6D2j2KMh586lPAnXcCxx0HvO99L8aHPvRydDodNJtNdTQpirKlmZ2dzZ3jYXgR0vQZ+NCHgDe+EQiCUR+dIlFn05bBFcVLky5ykoV7eWTWUzbp4hpe5WAatC2dVtLxlADIpMhc9ZtCpOigiRAJKOLWbM7l80IUMnlJvp7KZbukZFw1niyJmTBFsifGVJRJybA/EyK4ZWVi1vZNytDEE03KSMcTinaAzAGVTa7MJIUDajUBkuy/tOqYbPE9MltRvdnxkVMpikw7dyzxSRiaZGk72jJraViOpxawOu2XkgFg1RvwTaa4pGRokoU7nnKJvGzShfbP5fRq12kC7P4qx9FaHFBy/wCKegU02cInVGQ/X8ffE+iEi6IoWxO6d9EP7Sps6TyXjF6F7SMDaoDy/VV+dNszZs32kV2/CTBBN2FoHEskIQyQ3cOdTcb2qZbdKwfc0LgqJ1TeDkMke+IiAIf+ZtIOIgeTlM6jr+IICtuHSeflzimgbAcljnZmD9HfkiSPGwDQz+Eks6qknUP9LUfblcHE2y5HknQ8ufqz9mrLOJkAYCkk+8WWB/Y5lXx1lzquukvCqUS2D3cwWRlSsk5TErnrNG3kCxV9ANy2j3Q8wdH2XeyKoijKhz5k3n/zN4G3vnUhdzR1Oh0sLCyow0lRlC3LwgK/Z12EKPob/Pd/R/ja14BHP3rUR6dI1Nm0pZATLkAx6eIbT+8eCT0+geDb1DfJ7Xr4cz278f1b4yIgi+jl9ZvSsJB64TIxBJebSRCiiUI6JskmYepKyfD6UJYMDUnJtIGAJji4/AlNrpBcHrWBYkKEJhn4/53/nfsF9LGMqiDKpO+SwvE0CeZwyt5J9o76G+J7jSK733Iw0TH5In15m/4OVY6nyDOmz/he25aS4VIvsp5SPymZKtkYiZSbyffP6jRZlJw+fZb7XT/eCRWxP9+6fEW/LCVf/SalLkkSIljVCF9F2Xg89kttGT3PLl02T+RYrrKPeHtQ+ygBkAToJiEmIuMtIadTEhZ2DdCxfseKjy2k8Oj3D3DL7tG23CZKHP3F72hUBOeEQKedIkq7JjeMZISlTcftI+onO0n+Dfrd6mh9BDujjLYlB1fdnzCZzURtvtwW62SWk5TOk3YNjeF2TSTeuU0YGdm8TnsCSVjYJ1RTyZYHDuGyg+xXZG0nZfGkzePaZ759ZvMQXSkZXGW79LNlXM8Hrj7XWF9fJXUymNQGqoPaPYqy8zl8GPjEJ0z7yJH34s//vKjRRDWbAKjDSVGULYesK2eWLwHwa/jQh9TZtBVRZ9OWgT/Ryz6XXB6xhEIsjT9xC0kZwM5GkpJ6a5XXk4fE/WRRAEQNdGGqNKXZhEs4XWQk8UwloCwTU+w+9Y4ZVEqmidgtJdOCidKlCRSSyJNZSzQZIaXzplFMkMgsJ7C+hG2DcjtIimjeBq3nyGV5FXPHEi1TX8vR9jme+k2+uCRjtpiUjL/YdhHp21lpIl5pIU1Ck9W00ii+wzpSMq6+utlMXI7P5dzKI3tXHa9kDW1FUZSthsvGkVnd8ua4KsbTe2b7SHuH20FA2d7x2UfSVpLjeTsS7QTASgvdKMkqVQJRlAJtIAqF1K+wcVySwD5JPaIIxgmtMYXt07QCfJqIESJFp9VBGi0hTFI0V7qmbmMC215YQWETkbSwq5/bPmTvcAk9clJBLMuvmv956jqbzH/aPh24Q8gVdMOznHy2jyuDydefZTN12hNIo9DKZuJ2hy3926ywZarH8CwnPt7OeGKZUGkLnZUmEpnJPahUXj/7B47xvu35+Bxp+ySOd5fHy2X7KIqiKADw0Y+amk33vveP8Z73/L5Vo4nXQ+HLiqIoo0Y6mgBzj7r++v+Lj3wE+Nu/PYy3v30PJiZGfKCKhTqbtgyuKF4uJSMlY+S2DdHfKIa6og59cziuCRTuB5M+MT7e65BqoJs5mpIkRCduIoxCICyk8Cja0ycTI+sZEHLypZhkqS8lg11LAGBLyXDJGJqM4FIygJlkoEkWKZ1XJR/DHVKAPdHCJ2H4e526Ba4C3f0ifflETF1JPcA94SKl9oYkJeNyPNEkS6nuEsr1CWwZPXPQMZropMbBFK+0sLqSOTx5naaqiRQ+OcLl9VxSe4PI6JWcTXJiRcriJaItJ1ZURm8t9NIIvXTIP4/D3p+i7AhkhULZJsdTVdCNw/bh3XXsIKB/0E0dhxRvAwCKoBsjqZfZItOUd2J+s2RADb1z24dL6nH4th3WXwTd2BnkPDs8HxOGCMMUzVaMqSPmh6zNa1pyZw3ZOGQTkTPPZftwh5P8e1Y5meraQNy+4e8upxPvl0E3PAPbJRvMbRzahxiz2rLlgQGU6kn2q69E482fsFWydwBY411OpZKDKbeBiuAaAHZwTV0nk8+RtN5XCZeN43MkuWo5uewmpQq1exRl5/O//7d5f+Qjv4anPe1AyaFEy2las2CioijKJpCmqeVoIv7+738dl1yyjMXFPfj854GnPW1EB6g4UStwi9DrzeftIHgX7Ccw7s2RcjM0C7AKI7LmGsOG0btcJ8fAMV62IcbLSQPrM0Iz2ZJESLMiRGloS+GZzYx0jEsmRkrqkQPJ9HGZmMGkZOLQ1E4oSclIyRj6/3KJF4oApr8Dd/hUzZ3JcTR5QePkBIrrbyqR0b3U12+ShdpSVob+r7zOgUs6Rjqs+GRM5JeSsSVe/FIycoyU1DN/Gltuhm/HxwNMci+xpWSQhO5Jxn4Tlr521b7kNq79lwa6JmVdH2rL6PV6r3btVFEUZeT0em/I20FwgWeUT1KvSmYYZXvHtdyvX5piVTZUZdv85oQkqZeagBspAwzA+r0zuylL6hUZ28W2vvHFfu3P4nZWktlgKSJ02g2ESYrVVtfUlpT2inQ+wTGGt0MxTto6/O+asG1S+P/mHG7j8GWf/cMdUdLecdk+UjavXR7Ds5lsG8Rvj7htHNtWKdsvtnSey4aS29J2acrkqpMQSNgftc45LPtcDiOXXVPVX/U5XupI5wG93hmD7FRRFGVHc9NNwBVXmPbf//0zcL/7PcM5TjOaFEXZaszPzzv7223gxS+exHvfC3zwg+ps2mqos2lL4nIyrbI+X3TvMlsfwSknQ7vmUjI8Ercqs0l+nKstnVX5f6cBRFH+vwizWk5hy37C5BG9doSuHZULgEXl2hG6NIYetiOkaGY1oLiUDO1DSskAwOTdq7aUDEXuygwmnrXE+xNHO4WdzcSzYKSsDI2petAnXFexK6MJsCdZeA0D4SByTsDIyRcZ9cvHRMDKNNBpl7OZTISuKXRdJXNHUby+7CdflLAdGWxLz8SZZGMnbiJeaSJNIpPVtNICksCdtZQM2Ab8UcGuZdmX04NfQka2q+T1lIFJQvMa9j4VRalAGg9A4Uzyef55Jjhty2SEAbd0XgK37SP7fXYTWLtOllMUoBs18yxvAMbxlP2mhijuDyHsLCdej8efnVS0jZOBSwgXzimyiTrooJllVJlfySZIZrgTNvMsp1a7gzDpohUDgcveWYHJYnbZRMOyfQYJtBmG7UP9Ul6P20OhkQaOW6b+ZNxqwiWLJ7OTXFK+lL0NuDOhfPYOgArpPHEMcRNpEmLp7qmsRlMIrAT17BSfvSPtGD4enn2i4nNyyPZZzpZ5u+o+oLbPulC7R1F2NB/6kHl/6lOB+91vpIeiKIoyNF78YuC97wUuvhj4678Gpqf7b6NsDups2pK4onhpWcrlJWI76qNQUFG7ybWpq79qwqWq7ZLRy9sBgFYmJZNJ2UUpwjBFJ3twtms5FciJGFnXScrK8DE+pxVRkpJBimRPjFYsJlko26lKLs9Vo4DXbJp2tPmEDC3zfonMbHc9y/FTxpfZxOs0yZpN0tHUr35TNmFTZ/JlqTRRUkjJ+JxQttxMdc0D34ROHjWchohXmqZeQRIaRxOfdBnWyzWx0m9MTk8MdNUq8MnE1Iv6VSrQSRdFGQGu7E0uJyxTVrjMMDdUHA6nfvaLb4x0QvUbQzgdUu6gG7Sqa1Tyd2pLu8bV7u+QKre5cypGE2lrGWgBnXaMZmsVYQIjN8wzg6SNU9f2IZtJ/j3531HaO76/sU9G2Gfv8Cwnl+3jqmOZtUkur9M29ScBZJK+IbNTXE6fshPK5ZCqsneAIojGtGvshwXX5DZPEvR3KgFrcyrJa6RuPwDb9qHBUi7P1a6yiZRaqN2jKDuS+fl5TEyE+PCHTcbSi19crFtYWECapt6sAUVRlK3I/Pw8wjDE7OwsnvhE4P73B773PeCSS4DvfU/va1sFLaG1ZamaEYFjmeOJ7HM+2Dn6Xbuuekis88q3DczDbkaahEhTt3Ra8dHFOgDWOPtdSpLQujB/8Ldl3KL8wZweyq1toxBpNGGelbj0Ck0c8WhX3sczfNqOdij65TjeJ19RzXG+/cnlsOI4XZlLvv979rdJQuNoklIyNPHB/7406ULjeHRu1Xcpv3tzTtjnjS2fyPaVhpl8HpePCYZ3fkO0XfuVOC9lmiypmjCRY/rdMxRFUbYj0gnlmlB23YAdVJlTg7yvxW4Cst+b7Pcpk9ZLU/v3zJYDljJp5XG+30dbus0tU+uzlTrW73FoZHCjCXTaE1gl+0DWNuI2RST65XifHVRlx4Qo2zUt8Tm+bavsHZnBLaXy2LbkaDK2YWj9jbgjyfW3dcnmVcnrye+zOB/4erd0Hg+uIZsnJWdCIoLQ5Pk7yPle953vu9I08V3HrkAb6lcURVF8hGGIt7zlX/CtbwGTk8Cv/qrpX1hYwNzcHMJQncKKomwvwjDE3NwcFhYWEASFE/0tb/mu3te2EJrZtCWhhyiXTt0SW6bXqmM8f0hrFF3UzeVg2qLfFaHrk5uBZ3xVO2qhC2Alm3CJohRpFAKtckSvjL41/QkbY0vDpAgxBV+0rml30MRk9nckZ5NptzCV9TfRwVS4BIRAs9VBK40RJimaK100KGtpGkVkLkV2VmU2yTYfLx/MZZYTR/b1k9HjY4RzyIpOlm1XZhNvZ/vgtQrisJVnqZHkHbVlNlPRdkvALOdZTlPOaF2/9IxbwmY5nkK8Yj43l84DhieXl8AfJewaI/tzXIWu6UVSMssoR/OqjN7QSINiQm6Y+1QUpYIq20fWZqL+Zcd6+gFzZHZLe4eGyzHc3qExVXaQ67AjlH+fI3OsqwDgldQrZzaV236JPLtdOKea6GCKtTtcOi9rc9m+ZjbK9E+i1TLtZstkfgNAc6WLaBoIpL1DNhD9nWUGk8v2cdk98ieMxshnSNcpw6XzfPYOz2DiMnrZmF4WRNNpm9g8mbFdBMsU2UZLmGLOu7I9QmN4mwfm9Mty4rZSHem8eKVlbJ4kNNl1g9gydcfIfnjGul453G5Zhm33uGwcesf/z96dxzdVpf8D/6RJ05ad4tBSAUEHxYVFQBjBcRmZARUHVFwYlEW+rqAgLixOSmnZ3BF1YNRRdAR3ZXD/IYKMisgiKoKoIwouBQShbG2a9P7+SO/NuSfn3tykaZO0n/frVXNz7snNTaTJ0/Oc81ww9kkAxj1E9ZLP58Prrw/EJ58AnTp9gWbNuhiJpuLiYl6jiYjSjv65VVhYCAC46iofioqA//2vA2677QH4fBOSd3JkYLIpJalKyciDMKpphlajHsIgjNXsRbFdVTpPLiUTUSLP5nQijuOq7u+GvzxUVi8ruwJ+TxaCbvNgSvjVBIXb8DWXxPJ6QWlQRh6ICfcTtz3K7YgSM2433O4gKrIC5vJ6+qH06zvpAyhiST15YEW8D+G+/F5BaIfUrmJXUsZq8EVMOsn35QSTkHzSPOZyefKASyyDLHJCKqbBFP0aTLYDNFmRs3ujlZGJNjiiGlhx2t92sEW/VoGcZFJ1Fv8BOSmvR0SUyqxiH31SjXgLxbZ8fafMyMNYfYzqcQxs+tQ0VjL18QCB+ErqhbbdQswSjon8UMQv1dvhx+qJqsjSeXqySmwPnVaFse2FF/6s6mSTnHiqTtwYpYeB0MQceaKNvi3HQpDaIG2ryIkmt9Qut0Upr6dKMKmSSnp8IW7rMYu+wshJuypuAtQJKccl+FTXpQSil8WLJfaJFtM4OU4EsVEuCRyQ2uVV3Yx9iIhkfj/w7benAQA+//w2ZGWthN/vZ6KJiNKamHCaMWMGgHcB/BGtW09I5mmRgMmmFKRpRca2yzVP2qv/ESVew0DfzkHEAEvoiIi4foG8CMpJewCR/2LkQRjVoIzqOAAQ8KAqEBqNCATccFevdAq43UYSKVg9MxcIDa6EVzeJpUM8RqIpgPBjxe0ggqhAVvUR3NK21xhgCW+Hj6n/4R+6kDZC15zyuAFUIgvVM3p1+vujz54WBzjEbXmffgwxGRSQtp2sBnUyu1d18WyrlU3STF+telCmIit0vQIAxsCJPtgRa8kYVfkYddmfyPIxYrk8y+NUJ5oCgdCtUcbRyb/XaAMk8iCZ1SBKtPYIcnkou2sVRNK0icp2csjy/0sNj0lEljRtkrHtcs2HOXkEqK/NJG7LMZG0ugmw/n71KA4p93faLh7Hso8L8Ggwl9QLrW7S4w9V7CN+7+kJIXH1dqhPOH5RxUehfhURsZLcridSwivLvcZzibFSRRbgCQbhzwZQXhV6idnCaieRHo8EpLag9N6pVmZbsVrFLe7zIDIOEifWIBTf6OGBvlo7VCrPYyR95PhDLj8orlDS39to7aqyeeJziduOSvDJ5YKNmEex0s9JzCLHPNHaobiV2yKeU59oA1iXB5YPIq9gCkDTbgDFiXEPUb305pvA3r1AmzbAr7/+F36/H16vl4kmIkp7Pp8PM2bMgN/vh9u9GMHgH/HUU8BttwEuLq5OOiabUp4qCyRnhHRHFPtyhD5COT27MnrR2sXTsCwT42TbBSALVZ6AcbFruaSe/oe2uIJJLitjNUPXusRM+I95v1RWJssoK+M3BhfEdjeC8LorQomnxn4cbhyAJxg0Sux5gsIAi1hST3/f5X0Q7gP2f6iLrErJyO+1auDFbmUTYC6d5wmVyQPMgy96UklOMImrjVSzbwH78jGxlIwRZ/qqtvXSeXqiqfxgo9CgS8ADHHSF/18kqnRevO0G1SxdsVxeQLHN0nlEVB/pySKP1KazCi7EyTZ65kIYZBdjGbsyeqrYx6p0XtzxkQvwRCupF15dZLdqSVwNpSohDJjL4plXLYXbK0yl8wJCeb1GyEKFaTt0TH/o29YdhMcdhLd6xZNeehgA3IEquAMwx0eAddwTy4pu1fuqWtkkteurl/TrLwEwSgGH3mtziWUxrlElmOSSeuHrg6pXP6lWSEWubMoxHTPaqvGopfMAZ3GN3EduV/WXYxwo2iyTW5rQ6LQ8sFU/IiISPf106PbYYz/CL78cgdfrhd/vR0lJCRNORJTWSkpKjAS63/8sPJ6H8OWXHmzcCJx6arLPjphsSnl2JfUA6wGXHEQO1kiDLqpZhlbXb7Jrj1ZKxvZUQ4MtVQgNpMgl9cS5m9al8FTb4T/23UKCyeo6UKG3QT1AI16s24sK03YW/KHrOrn9qMgyJ56A6sGVcuPkrJNN4vvk5LoFVqxWNoltCZjdKw6IWG2rBkqs2qOVhlFd+0lPSIW3w+egz+7Vy8gYF8Yuz1QnfZwklVSDKbFew8DyOk2qWb12gyyq6zqJ21QjEf9/EnRMIoqB+Iuor1YS96m2VQkpi9hHfKiTxJPeL1pyShUfWcVE2QACHtiV1NPX6cL00KDpflb1lB25XZxoY9UubuvxUriknrm8HgDTNZ4qkGVKPFVUt/vdXrjd1ZFUdWwEAO5AEO5AVfV29WupPjWX1f9S86lHsrh+kyYt7Al69NuM6tXpMGKbyJVDHmWCSVydJJfFE7flyTjihJrQYyPL39m1H7GZmGM8r5PSeVaJJCfxi1U8FEuCyTLRZJdIUm3LfxvxC7bGGPcQ1Tt79gCvvx7a/vDD64zSefo1mwAw4UREaUm+9lzo/ssALsfTTzPZlAqYbEorAUSWyLOil9rT/3rQRzkUj5e7QLrvtF38Q0XsIz+Pqr9FST23O5xkEgc+xFm5QSFpJJfIU5WeCZeoccMLGIMmYrkZsXxMEB5UCM8vb4dWWnlDJfbcHmShIlROBgDkaxiI742qjF5A2h8U+sTCamavB+qyMlnmgRn9WgWqmb5BaQBFLFknl9ELl57x2LY7KbUX6i/+fw///xT3AzDKyAAIl84LeOwHS2BxG0sfkVV/JflgTliNzBERpTs9XpHLBqv6yNtW13WSHmr1vSrHRGJcI+636hNLewCwKqkX9LgBdzjeACJLC9e0PQiPcT2m8La4kjyyvF4o2VKBANzIgt+IuYw4CB4EEUAW/NUTeNzG9Tjd7gA8HnPiKeipTjxVP62nuqSeS37fo5CTS4B1ggkwxyVAeKJK6DWGkzhyosk8EUlVDthtxJDytvXxw3GNql1+Pr3daJOvS2lXOk/ktF3Vz6qPFct98rWZoj5A6stV3UREKs8/D1RWAsCnKC6+zEgsidc6Ee8TEaUDOdEEhD7Htm59FosWAY89dhB3390EmU6HzqlWMNmU8o5U34rZAg/Cf2TpCSW9XJ68LT5W367+41OfaZstdJdn4kLoE0u7+HSqv/8iVuBUl9QDUC6MFASz3QhmRZbC81bP4tVXIRn9Yb+aCYBRIi+yPTxb142gaTtcPiYILyqMP/e91TN6s4SyM4fdOfAYM3pDbZ5gEO7G5hm9ptm8AeMFhMWTS7Ba6CaVjwFglJABQgMxFVmRiSFxlq++EgmAbRk9qxIz8uonuQRMtAtgW/VxfGHsaKXzgMTMALZql49v0Fc1BRAeNNF/7wMW23bXcNL7UNxiyfnFckwicsgquaSTYyK5TZeJ0GdiDiJiH1XZ4IDFNqT+Vo8VT091OqjuH9HuArIjS+oBoTgo4A6vQgqRV2+rSwWL7aGCwBXV216jBJ7Vdqifv/rZvMZ2KCbSYwE/9NLGepwU6l+BI9Xb4lQSAKGSewgCbsCdJfYJv4H6SiiZXppPTxzJ9ERS6LWb3wdAT86ok03iqiU56SOvcgptm8vlWa1yslrxJK9m0o+vugamqj0AN/zBLPjLq+Ojg42qJ9ZIpfMOIjKuAaxjHLGPVVxjt/pJ1c8y9jmCcOwjlg3WtwFzXMNV3bWGcQ9RvfPUU6HbgQN3RySU9PtBi+9bIqJUFQwGTYkm3ZNPDsOSJQdx6FATvPMOMGhQkk6QADDZlCaspg6Kf1zJIxvitoNrGMgzdsXuEPrYDb7YtUcrJQOEzskDoDwLfmmwxV09wxcwr2QCYJRwMV/LKbLsnnlVlPkaT3IffVBHLOEnl/PTS8aIgzihlyMmw6qHGdzBUEkZY2DFvqwMYB5vcjn8g00TfqOdzO41v3ZzcgmIvG6BOAAjltSzulaB2Fd13QJVn2jt+nEiyvEFs6qvVeCF3ygfkxWa2asa+IinFF48CaaA4if8f0xoVF17wGrb7jOBaqw2xq34v4YoRvIvjZxEUi0TyhTuR4l9xFtVGT3A/Lktl9Sze6xdrKT6LjASWJmAxxP58ZMNo7QwYI53gHAcpMdHeswSanObJsf4AWNbTyOJ22JJPdWqYjEOEsvoiRN09NhIP1cxPnJDnWDS2/VElNxefSdCUGqUVzqHtiMTcGK7GNvor0V8jVarn+RJN5HxUZYpVlJNuhEn5zi93pO+mslf7kVFdbxTFXCHYx4ncYqTSTHRkkpQ7Ld6rKPYR/ULJv/NI8ZJTDIlDOMeonpl82bgk08AtxtYuPAvyj5c0URE6aioqEjZnpkJXHttEzzwAPDkk0w2JRuTTSlO04qMbZfrfoRn+2ZK2/ofbR7FtrgKCggPyAjkhwLmBJRdaRgg8o9Ju3bxOBZ9qqRyMkCoRF0Q4WSNOBvVrdgGwoMfcruqv74tlowJwl1dFiZcdk8vo+cXSsZkoQJ+ZAmDIl7TAIk+2CMOtATdocRWwO2OKCsDIFxaJnTCMQl6xG3r8jH6uVnN9rUqDSMOsshl8fRtcZawePzIknlWpfSsS+zJ5xmEp7qETKiMTJWYaVMle1RjGKoBESftkNpVx7Wk71QNtlgllNQJKE2baPdERERpQ9MmGdsu13yLXmJgIcdENWAXTqnGwp2W13PcxwVUf5+5PcGI0sJA+HvbKvbRY6UAzAkXsQyw3kf/bhdL4YmP0Y/nF+Ia/Tihbf2xMI4nHgMAwiuGwgkmfV0WEC5ZLE8UEhNe0cjJJbFNlWCyareKf1R9xBJ5qtVM1jGNagW5uh0wx1Bi2byAUC4YATeUZfOs/t1Gi4mg6Aeb7YRRxTjWT6JpNyf6BIiI0t6TT4ZuBw0C8vKSey5ERHXl6quBBx4AXnsN2L0b+N3vkn1GDReTTWlFviCuvG1VQ03+36zfzwwfQlVST+wuzsrVf+z6qDgqJYPqgZZswKOZJtkFA24Es91wu8MrksTrN8nXctKvQ2DVHtr2GmVgKhTbQLi8Xmg7XF5GnK17BDmm0n7iait92MBqRq8b4Vm8HmH1k06ewRyNPMvXPJiinulbgcgSeqH28Ixep6ucxJm7Viue5Nm6+ntovRLKa9GeFTG71yidp8/utSoZU9MSM6r2gHQfin0GVTkYebauvM3yMXUiiOgXpY/nmEQUB3lFZw6AwzBPoIFiWxy01ssPC+X05NjHalt/WqttnSpW0rfFBJMo26JPIBNVAQ+qPAEEs/1Gd7m0sCoOEldmV8BrlPk1b2cZySNxdZJXuAaTuEpbXLUkxjPRYhyP6b64P5xw0veLt2Ifp4LSmyvGMmJCSdxnTuaoJuHYJ6DEeMSu7J64ekmOiZyW4zOeq7pUMAD4y7NQVe4FAh6gXLGKO5a4Jtpj7eIaJzGRQS+fB0SWDbaLccQSe2J/SgjGPUT1QmjGfyaefvpOAMDo0eF9JSUlCAaDlqsCiIjSUVFREdxuN3w+H045BejVC1i3Dli0CDhwgJ97ycJkU1qRp7/K23LJGNW2xfWb9C5OysHo/eSyePGUjLFNWoWu41QJIMMTNJIJbk8Q1X9zQywBI87qNbO7tkF4W5xZ64F5lq04QCEOmuilYvQBm/B1DswDM6GXpk42ie36vvC2erDFWB1l8ZrFQRdzgqnms3tVAzCqARe7axXI2/ox5NIzkQM0Up8Kb3XpvFAJPaOMjD7oEss1mKDoL/dRtVslmFTHMaiu02Q3yCLfqraJiOojMfYRVzCJiSTYbIul9fRsjiL2ybbY1g9lta2Klay27Y4pJqeygdDEm0xUAQinm0LcHjeCbj2eCEUvkdvhlUPiKiIgdJ3J8HaFEdsE4K7eFy6pB4ixj5xoikw8hZ47MtFk167fD29Hfqd5YB65Vq14sot95MSSk/ZoMZA4USdaaWGxf+zXvQzFOwBMpYKryr2h6zOFXkBsiSRV8iie49jFRMrYR2wUE0bRJtpAumXsQ0Qkc7vdKCxcAwBo3Ro4//xQe0lJCQoLC1FcXJzEsyMiSrzQ514hgFB50NGjQ8mmOXN2YudOfu4lC5NNaUTT7jS2zWVlxAtpB6Aulydui/01mAZdxH8RAaFN/NvQSXk9+RhWxwlI/eTjV5eTqdKb9JIhHrdREs4dkSgJJ2L0drGP3k+9bS61F7pfAUgzgINwG0kuvYxe+PHhbX2wRx9E0RNb4n49qRV66eELgLsRlM5HLMsX+aurWtGkU83qFd8ju9m+4gWzxZIxqpm7kaXzYisjY74+hLqEntFHKCNjJJr0MjLyvyvVoIfcprpVDpZE6WPXH0Dod05XadHJarvStM3yMbVE9f8wEcckopiJJUJdrseqt+SARY9r5M9Oj7BPTFRZEA/rdFsV48RTgs+q/HDAg6pAEBmeoKm0MAAjDgo9TL2tinfEsnjiyiZ9HwCjVLDYJsY4InHSTrTV2HrMI8ZDYrwjb6teR+Qx3bbb0WIgfZ+cZJLb5ZhIdY2niBK/wjHF568wHUcd7xjbwXC5PFOp4IDHOvaIlgBSPS5a/BLrtpLddSjFBJK8aincR9OuifYkFCvGPUT1gs/nw+LFW/HVV8Dvf78amZmnmxJNvE4TEdU3+ueannAaN86H8eMD2LkzD9df/yh8PsaNycBkU9o6glA5mCMIDaDoZSXE1U12K6DE/sIsX9tZtrD+w0HVvzxKH3EgRhQxQJMJeDJRlV0JP0IzfAN6ST1PsPpaTuFZueZZqpGreLzwm7b1AYUsqXyMWFIvC+ESeXJJPSBcYibUpxHk2b6hdquZvuqyMrpoAzcyOelkN8hiN6NXLiujKqMHWCeb5LIy4oxe9cWzIy+krZzpW51kUs7uVc24dVoWL1ofVf+AYlvV36DP6tVLx4jbYokYeVvVn3/FE1FDI2dpgHDcc0TqK/cJIBQ3BYQ2mGMbuxVMTrY9MW5bJacgbodKC1d5NFRlVxjXcsrKrkDQE9rWywvrsYW8DcB2pZKY3BFjHH31trhaW2/T+8irtMXj6sdUrWAS+4jt8nYsrJJOYowj7lPFQapkk3gtSqvV3/IEHEC92jvUnhXRP1q8E0o0usNl8/RSwVZxSipsm4iJJbGMnh7XiNtHLNq5momIyM6uXcC3354AAPjoo/9DVta38Pv9TDQRUb0mJpxmzJiBQGAhgGFwu5loShYmm9KWPjtXLCUj/gEWrayM3D9T3axvx1o+Bhb9PcLjnPQ39ck0VjjpBWA8nqBRVs/uGgb6H+9iQkreDq9QCpePEcvrAeHnCL014Vm5fmQZ129SXctAbA8dx/66BfK2SG6Xk0uq9lhm9/oVs231djnBFNr2Qp7dqxp8iVZixq4En7FdXTYvEHCHr1UAhBJN8SSJ7PqrEklQ7Ld6rDI5K87cFQdPYr1OE8BrFdQizvAlSlGqeMfJClGx5J6Y7XFFf6i8LccvtbENmEvv6WX1kIUqTwBVnuqYwROIiIPEBE6WtArJWbxjLqnnh/kaTGLySF6dJPeD8FhdtHhHjnGiXbtJda0mu2151ZccB8nXroxczRQ5GSdaubxQH/U1m8RVTrbxjrF6W3F9JiRhO9qPiVwKT/w9jnYtSqt2SijGPUT1wjPPAIEAcNppwGefhRJNXq+XiSYiqvd8Ph9mzJgBv98Pj+cZBALDsHgxcO+9QHZ29MdTYjHZlNb0vwys/jeK5WLkbVV5PenQ0crHyKeg2obisQGbx4rHhdQeQOiPbABVgVA5GV3Q44Y+fiBel8BqOygMZgSrB1fEC2OjunyMPiAjrlwKl5jJglhOxo8s0yBJeOaw23icnHgSB37ksjJB07mbj2tFtS+W8jF6u91M33iu3yQe06rEjFWZPWPbVDavuoyM/m9A9e/HavBDNRii2mf5bzDiDY6+bfmASgfb0Y5BRNQQiUGGfM1KOcbR4x458JDiH1W8I3+uOymXV5Nt2G27qvuGvg9FqjgoALdp2/xS9fvmeEdUgcjV1qJQMsWcTApHN+FVU/o5iLGMqqywvK3fd8puZVO43Rzv6PudJJ6cxkFivCWXB1bHPtJ5SPFOaKdeOk9RKjiW7XgfZxUnqWImS2JHVeJYfjBXMxEROaVpwBNPhLbz89/A2rWhRJPf70dJSQkTTkRUr5WUlBgJdr//bTRvvh+//dYc//kPcPnlyT67hofJprQlDrJUKraByHJ54vZh4TEQtoU/YhNVMkY/Xbt/bXqmOWqJGX2gJRuVATcqPaHrGAQCbmN2bzDLIwxyWG3rZWXCiSTxugVi4slfPfMXgHE/tB00rmjgpHyM07IyOrsBHnFQRkUeVJITTfq2PMBh1W6/ysm8skl8TLTrOsW1mkmf3auXzQvA2WqmaNvRjhPPtkEvnyeWyDtcfWtVIk8srwfhPsDBl1qmSiom4phEVEPiL5LHpk2+nyO1VUr3bWIffYWRvAqpHLGXzgPC8Y7dtv6ylHFQJuABqgIeVGVXoBJeZGb7lXGQmPjQSwLr38Riabzwd7s53hFLCKtXb1uXB7Za1W0V5zhZ2R1NPMmmeCbdANHjILGPHPtYrmwS4p1gwINKY/V2Vmg1E+AsBtHv6/2ttuONa8Tjy8+pjH3k+MWubHBA6hOQ2vllWisY9xClvXXrgC+/BDyeSrz22nCjdJ5+zSYATDgRUb0kX5sudH8eAB+efJLJpmRgsiltiTMCVVNiRVazBuXBFv3WFe4qDqzEuw2EB1ESes2DTMDjQZUnAD+AoCcItyf0hG6PG0G3PlgRHjyRS8boK5qAULkZuXwMqgdj9IEDPWkFmEvqOSkf46SMnrhP3o6F3YCL1XULrAZcVLN7ow2siH1UK57E41pdvykp1yqQB1Bqsm3QoL4+gXir2pZn9Iq3eh+qFUEkfpAkvl9lIjLRP/f0VUqAOZR1et1KwPxLHiX2AdRJKJ2TmKgc9rGPfI2bbMVjTXFQqKweEHpXgh63KQ4CvPBmiSXywrFAFvyIXH0UWuct9ldN0lElnvR26wRTbNdpilY6z4oqvpG3rSbXRIuDAHOME+9qb/E44qQaAOZ4J+AOJZmAyLJ50WKWmiaPopXLszsHg5hoEv8gsCsbHK0PY59aw7iHKO09+WToNhB4AcXFtxqJJfFaJuJ9IqL6QE40AaHPub17H8bcucD/+38aduxwoV275J5nQ8NkU5rStCJj2+W6v3pLLyUjlszTBaAuKyPu10nXb0pkaRj5qaJte6JtuwB4UBUQSq4I2wG3PjgSHiwQB1wAdR1/wFw+RhzAEB8vl5ixKh8jlsozD+yE94WOHYA5saUupacir3KSZ/LK/eSBlfD5W5eVkQdTxH5WfeQyMfL+gOp8qhNNwerZvcbAi55oshoAScQPErAt/Z8wd1IlkpQPFIT7a9pEm35ERPWXpk0ytl2u+cIecQVoptTuseij71PETKpYRrXPrr/8veCB+VhOjqN6rKm/niBzG9e0BMJxkFhaDwh/11dATzi5Aal0nkzVRy4b7JQeIwHheMeqlJ4u1thHbrMqJRw+n9hWeIvt4rWcVP1UJfIi+lfHOwCkeMct/P+N8gPp1kk/+TFQ9LN7rNUxTCoVt3LCSE4eqZNKmnaz6gmIiAjAkSPA4sWh7ZEjtYiEkn4/GGQWmIjql2AwaEo06R54YByWLPke33/fAU89Bfz970k6wQaKyaZ6QVzlFECoXIw4sA2oZ/halZXR9wuD+rGUiUnkdgDh2cNW29kuIJCNKo+GKk8AwYAb7urZvcHs6j/gs8LJET+y4EWFMSSgKpen7w9t+42LPYculh0aXHAjaJTdU83ctZrVG3pp4Ta9j7hfZ1dKz47TMnp2ySZxMETcp0pC6e+PvFIp/J5HXr9JH6iJOrtXXM0UQO2VhknUtkGrvrUqHxMQtlXl9SDsg9Cfap04uJbIYxJRAh1BKI45gnCCSc4K6f0g9akE0Eh4rH4saXDfalWRXF4vWkk9edWSmDjKlvpDOLYqgZWt6pMJZHtQBaAqu8KIg8TSem5P0JiAI67SFpM8YuwTWsEUiokq4I1Io+jHibaCKbJscPix+n6RKrlklXCKlmgS78vxjr4vWrJJteJJjo/0Fduh98pBeb1gljGhJiBOqtHjHUC9mgmwjkHk+MhJn1j7O4p9gPCKbjHO0ct3i8kkuY88GUeMkahWMe4hSmsvvQTs3w8ccwzwxBNXKvtwRRMR1UdFRUWW+4qLO2DEiND17KZOBTIy6u68Gjomm+oFPZq3WtmkKpenb4slafRj6YMvirIy8lOK++IptRfLNQ/kwRqRXlLGkxkabPEEQzN6BUGPG253eJAkVCRPTzqFZtuK5fXEaxnowwvi6iR9ZRKgLh8jt+n9wv3VJWOsSszEQjWrN9SuHmSJtkpJf6xVgsmuhIxVkgkQSu0JJfMAWF+bKdaBkmgDKPIxnW5b/RjsyseoSupZlYmplLb5lzsRUYjVKm6dKvEkbsvJez1z4wo32ZXLE8viRSupZ5eoctJHjpXEl2i06+edhSpPwIiD9NJ6Hk/QOM9wmeHQ97leFk+MfcRSwd7qsnuAeUKN3BbaDkIvQazfV8U4cllh/TiyaJNu5Mk1odehXs0t95fjGrmfVVlhwJxgcnZdpyzTqu2IJBMQjneA2JI+Vu3xJKGs4iS7OMhEnACnutaSHBvJ8U5A8VhOtCEiUikqKoLb7ca774YSSWPGhAdTS0pKEAwGbQdiiYjqG/1z0efz4ZJLgJtuArZtA5YvBz7+mJ+LdYXJpnpA0+40tl2uedVb4sgFoC4lo/fR/5iLUlZGfoiqzW4bim2nZWWsnkveD0CfFVqFUEkSwFxaD24YAyShpEcFwtdockZOOqn7RJbQk/eHTicotYf7ioMiiR5wEbejlY8R252seFK16ckp8zUPPBEl8wAIJWQ81kkd+d9UtB/VY1Tb0fZHTTTprMrHiAeSr1EgCh+Y5WPqmOX/0xoek4gSxlxS7zFhj/7Lpk+aEdv1OEe8FduBiISTeEg5bnESE6EGfYDIz46o7S7or7tK6uIOCBNR3OqJKGritS/1p3ObYiA9dhFL44WP746IdVT7VHFR9HMzH8vqvlU5PasVTHqb1cqmaCueIu5bJZr0/ydivAPYxzHRYiG5XXW8RPYxiCu6xQepEkoiOR6qPpp2g/wEVFsY9xClJbfbjcLCZwD4kJEBjB4dahevYUJE1JCEPhfD16i78krgkUeAiRO/xKZN/FysK0w21TviqIXViia5lIxOvNaBoqyMuLIolvIxdv/KrJJT0crKyIM8prIyoRVO8GSi0qiDHy6t5/EEjfJ6bnd4dZJeXg8IlcsTy8HoiShxiCHahbHlWbuRM38RsV+nSixFW+WkKiejWtXkJNmk39qtbJIHVACbkjGK2b0A4C/32s/u1X8SWepF1T8RF9U2yOVjxBJ5ViubovUhIiJr+mcuYJ5Yo4qD9FLDOQiV9spUtAsJJ/0zPt6SeuLT28VHVrGP3G4Z+4j7w3FQVXYlqgBUeoLGhA6xzLDbE0SFO8sU14hxDhCKPyqMEsJyP+sYR1VCWKeKg6zuO2WXbIol8RTLRBvAXDovWoIJACrLvQhPqLG4DqXVqiWreEf12GjtiVgtZdBXdOvxix7XyKXwxMRSpUW7/lgiIrLj8/nwzjvn4sMPgd///mu0bXu8KdHE0nlE1NDon3t6wun//s+HRx4BNm3qhEmT7oXPd2syT6/BYLKp3pFnE8oD1eKFs2PpI7Tpf2A6LR8jl5uRH2vXv8YDOqHzFkvrBaXrGIjl9cIF9cSVS25ErmTymoYfQk8bW1kZvY/+WFSv/BH3i+JJNsltNZ3Za3U9gwrhItmxzuytNBJMWTAuhh3PgEi0PjVJSKkGbZSDLXblY8TrE8Tah+pUbVTt4f9GolokJ5rE7Uypr0fRV74vJZzEpxDvq2IcVZxiFSvJp6KKa+R4J1t6rHj6qp9AZvW2x/gYCnpC37/6BBy3JxSDeLP8yokz5njGbRnnWE3A0eMbVek8/Tjhl1Gzi5dblQ4O3Y9c4W01ocbpyu+I0nnV12MCoF7FFC3JZBf7iNvREk/xtludg+NEk2oVk9wuxz1yOyfa1DnGPURpye8Hvv66LwDg669vR1bW2/D7/Uw0EVGDJiacZsyYAeADAKfhd79joqmuMNlUz5jLysxHZFk8eZavqnSeqo8GZVkZJ6VhxDan/eXnkbet+li1l2cC2dXl2bItyuVF5mpM9FRSVvXqJ7FdHzgxX99J/29kWZlwUiuc3AqdQsA4DoCIxzgll9RzUk7PbgWTql1OKon9YykhA6OEjMv8/1H+kdthcRtrH7FvPP0NYvkY1SCKKHoflo8hInJG0yYa26GSemLQIcc4YuChl9ED1GX3hISTHMOoYptot+KhoWiP9jjVY1V9lFyhSR2eQER5PV3Q444aC8XKqoywdVm9yP6xPJf8PKpteVKNvt9J7COu2BbbjIRUdZwDoGaJJlXsgyj77eIXuT3WW9vYR/WP1KpcniruCbdr2jWqJyEiIoWlS4Hdu4E2bYBff10Gv98Pr9fLRBMRNXg+nw8zZsyA3++H2/0kgsHT8NhjwMSJgMsV/fFUM0w21Wt6GbwjCJfFE+l/3Imzf8XyXY0QXmXhgWVJvWilYeSnjFYiL5Y+du3iAEw2oM/urQp4UOUJoNITREb1jF5xdq/bEzRWOoUOEzSuVeBGAH5hhq51ST116RjVrF6rGb3xlpHRqQZWQu3WiSdxwERvj1Y6T75gtmmAxu4aBfqgS7kwkOe0NIzcpzYukh1z+RixdF4AofJMQGRJPXH0plJql8vNUFIEq38SfUwiqgPiZ6iYxJdjHDFro7ep2h2W1IPQPd52qxgnWh+P021X6H3wZKLKo5liIQCoKM9CVnZoQo3bWPEEIyayKx+stznZp1Ov4o4v0aRTXeNJlXQSYxj9cU7K6YnteklgMcFUUR5e2RQ1wQSo4xdx2yoWctq/NlZFGaKVzou2sollg1MG4x6itPRY9SUrO3X6AL/8cgRerxd+vx8lJSVMOBFRg1ZSUmIk4P3+Z5CZORdbt3rx4YfAGWck++zqPyab6jV9Fq9I/kPOo2jXt+XVGHq7VFLPqoyeqnSeXZ94rnlg125VISe7+loGqL6WgSeISniRme2H21M9OOIJwlu9AiroDiK8YklVPiZcUs/cHk486WuprMrn6e3imiu7ZJP+eLsLZ9uV1bMqp6dvOx1oCZ1zZIIJCF+PCYC5XF7AHVppFjqQ/aCJuF3TwREnJWOc9jFRlc47LLwAsV3ctrpWQW3UMqGYBJH4MS8OuhDVkWjlhMX7VoGCapV3lJJ6QGRM5LS8np5AsuojxjiqMnrxbBvXdQpNwAGqyw1L17gE9MSTG34gYjKOHuOoSueJ+3Sq6zfB1Me+pLBKPGWExT7REk+qGCfqCibAOskUS7JJ3I72E23CjpM+cvlhR4kmVek8q7J4cpvcTknBuIco7Xz/PbBsWWh71aqRRuk8/ZpNAJhwIqIGSb52Xej+vwGMwWOPMdlUF5hsqsciS+rpJfN08nUM9L8yxPJ6eokZ8b5FST391mn5GHmf1WPs2sVb+fhWfUzb4V+BynKvNEjkNWb1wh0u7SLO7HXCSbkYq7J51o+zr3NjNciiP6fcL64BF2NoSUhIRbsYNlA9+GKcmPNteYBG3pb7WrVbHcfq35XqMQZV6TyRqlyeuE+8DbB0HhFRDWnazca2y7UQ5jJ6Yiyj0z+DxXhHDDjE+1FK6gHmr4FElcVTxT6qx8rbVv1NXBD/HLAqsWcStexwOLaxugaTk3J5Yiwjx0PR4qBocY++Ha2knirGAcLXYwptK1ZtA4haLg812I4lpomlD2zaDVal8+RbOS6qhHlCTehW00bJT0BERFE88QSgaQDwLoqLRxmJJfFaJeJ9IqKGQE40AaHPwe3bn8DjjwPPPluJBx/MRIsWyT3P+o7JpgZD/8MuB6E//HIQWn0hXq9A3y+WzgPCgzI5QruipJ5dGT2rFUkBRXu2RbtHahcHZSxL50nPE7Gtr3IC4MlEZfXAgarEHmBdVgawLp9nVzrPrmxeIsvoyfejzfBVrXxyUj7GcnZveab5/0V5lO1YZ/fW9koo8fgGVem8aGXx5BIzcjulBOXgWgKOSUR1TC4nfBihEsFiICAS2+IsqadaeQSY4yBVTCTGMlal8+ziINV+q5go4jyqX5MnssQeACMeAmAbE+nE2Ch033kJYblfLOKdaKP3FZNKRl9FjKO3VxkxTlb1QVzm7w+rhJDV6qF4fmojbooa+1jFL/q2Hv+IffQDqUrsUdIx7iFKK8FgKNkEAJdeuj8ioaTfDwa5xJCIGpZgMGhKNOkeffRqLF26C7t2tcaiRcDYsUk6wQaCyaYGQzVgIrJql//6kKfuZkZ21QdMYikfY1dWRudkQEfvI5+u1XZEoiqz+vihsjJViJZ4siorow9kWA2+hMvLhPapB2BEVrODdQGoZ/nazegVH2tVUi+h5WOAyEGWRCWenFzDoCal9kxUpfOclMWTVzrJ1zAgIqLEUZUTFhP7AelWJwcMNiX1rGIZwDqucdJfTAapHmu3rfoRn8cq6WVKPmVWJ59Ciaeq6tgn6HEjKCSeAJjiotCtOxzfCPFR6CnMcRCAiFJ7iWAX74Ta1Ikl8VZcuaS3265eAuo+2RRvQspJf9tEU7TSeaprVELRjxNtiIhi9eabwE8/Aa1aAf/+9yXKPlzRREQNUVFRkbLd5QKmTm2NCROARx8Fbrwx1Ea1g8mmBkMfcAkIt9FKxojlZhyW1AsonsZpu0jMjUXrI26r2uy2VfcB1LSsjF46Ri6FF0vZmMiSMbH9uka7hoHVdZssr+uUiPIxqIVtuU2+dXIOcl/VsQxWpfNUAy/ygazaxcdT0on/DhJ5TCJKAqu4BjDHOGJSSf+FdVBSD1IXMV5RxTtyf5HdYxHDdkJVx0MBD1A9Cacq4EaGcH2naIJwm1Y+WfUBEr+q23J1U9CcWNJvAUSsYAKgnkwTegLncYoq/nQap8QaEzmNj1SPFfsZYimdJ6qUtlVxECUd4x6itFBUVAS32401a0KJpNGjgazqxbUlJSUIBoOWA61ERA2V/tk5dqwPkycDn38OrFkD/OEP/OysLUw2NRgBhFddyDN0IbQHpHaxdJ5IHFXJqW4TkguqVUSqEi86q5IxAZhXHoklZgIW/Z2WnRFfhnh+VmVlAFR5NFR6AoCD0jL6rVxaJvRUsZXPi5ag0qkSUjGX07NJKultRukYPbkkD7qI2/IARl2Vj3HSX7VfdZ4AwkkmuUTeYYt2sUSMakavXHqGf5UTESWW+LkqxzWViCypl6noD0SuPs2BKeFkF/sAkSuzrX5iiWHstsUYR4yh7FYzyX1M94V4CKEV4FWe0HdilScQ+iarXgWuc0urn4DwCihxv9V9oz1akioYObEGMCeP5PsBYVtOKgFREkv6rSqOsdoHRI99nPRJxI/TVeMmsZTO02/FuOaw9MLk/kRE5ITb7UZh4eNwuf4OwIVrrw21i9coISIis9BnZ+g6dpdf7sNTTwELFgDLlvGzs7bEnGxatWoV7rnnHqxfvx6//PILXn31VQwZMsTYr2kapk2bhsceewz79u1Dv379MH/+fHTq1Mnos3fvXtx000147bXXkJGRgUsuuQQPPvggmjRpkpAXRSrybF25Rro8QqJKSIl/NDYS9ovZGuEP8nLpofpASLbw0ESVmInnR/Wyow7E6Nd4EkrLAIAniKBeUq+63J5xWFMCygu3J2iU3hPJCSVz2TwvYiWX1ZMTUVazeuVBGMezeuXtcqktVQZT7PqoBn8AhAda5AESuwEUMbmrGoiRZ/dyZVPKiPj/n6BjUlpi3JPOVJ+rchJJp//i5yCSKmiQEk76IeTYB7COcRK5nZAYJ8o+U5urelu/7qWnOh4KvWi97F4lvEYSKhiRYIr8YPQ4WCllJxCITD7pCaXQtpRUMh4oxDdA9BhHFTfY9U9ETCT3r8l2tOcxyEklvU0V14gJKTGuCUiPlR9HSce4hygt+Hw+vPvu2Vi1yoVjj/0OnToda0o0sXQeEVEk/bOxsLAQ11xzNICrsWhRJQKBB/jZWUtiTjYdOnQI3bp1w9VXX42LL744Yv/dd9+NefPm4amnnkLHjh3h8/kwYMAAbN68GdnZoSzD8OHD8csvv2DZsmWorKzE6NGjce2112Lx4sU1f0WkpGlFxrbLdb+wx2nJGFS3ZUqP09vFW4H8R7kH5j8+PDZ95L4ycb/VthNyX3EQx5Z1qT270jL6Pn3AQ+8nl5lxUnJPeXzF/wfVNQnkbdUKJgCRq5gAGCXyAPXAitPBl1gSSLH0l/uqHguLW8u3XDVQIu6zK5En3poHVjRtotUTElEKYNyTvjRtkrHtcs2v3tK/5AFnJfVUJYch7JcSTvpTiLfitipeEZNTcqLKLr6JFiNF62NFPA/H9ORMaDKOSI+P9PJ7doIBjzIJ5YSYVAq3mZNPygQTAOUKJn3baSwTbVtsS2QMJZ6r3bbT4xjEssHiwawmy8i3qseG2jTtZtUTEhGRjcpKYOvWPwIAvvvuDmRlvQa/38/BUiKiKMIJpzFwuXoiEOiGgQOfhc83IMlnVj+5NE3TonezeLDLZZrhq2kaCgoKcOutt+K2224DAOzfvx95eXlYuHAhrrjiCmzZsgUnnXQS1q5di169egEA3n77bZx//vn48ccfUVBQEPV5y8rK0Lx5c+zfvx/NmjWL9/QbLJdrJkKjCDkIDZ54pFt9Vq++Le/3KPrI+6WBF7H8ndVKI1W5PI/isU635eM4WeWkmt0brQ9Ut9W/VkLJPQDKEjOh7fBf+TWd1SuSZ/g6nt2rmtkr38Y7UBJPKZnyKNuxzOhV/YjHMVGtaFKVv7MrnWdfYkbT7pSflCzU9me/fnzctR/ITvDxy8uASfzeSnfJinsAxj41FZpoo4pfUN3eSNi2io/0W/mxQjlhUbzxi10s46QsntwnWrvTOMdylZOiXXULRCSiQm0WySWn8ZBiNVOoXTUJSlqJFuutk3iotuIju1ipptsmctlgfdtqRdMRRf/DiseG+3CijTOMe6ghY9wT6aWXgEsvBfLzgT17GqOy8jC8Xi8qKiqSfWpERGkhKysLfv9oAAvQuTOweTPgckV9WIORqO/emOct2tm2bRtKS0vRv39/o6158+bo06cPVq9ejSuuuAKrV69GixYtjAEXAOjfvz8yMjKwZs0aXHTRRRHHraioMH2BlpWVJfK0GyBxNVMAkSVj5JEDVYmLIwjPBpZn++qPE35j4y2XJz/WE8O2/lj9dJyUm4k12WR1K1/fAAA8mrLEDGAuM+MPv2uOLrytYjuTV2dVMgaIPrBi18fprNxYEkyJ+olWXs9Eg3oAxa50TLwlZogoHdVW3AMw9kk8eSU3YI5bnJbUE+mPDwj3Fd+leuwTbdsulnEa18h97NpVfcT7AUU7YrhVtrki+1RfBypSpvmunqgKOPiLUP5OD8SwXdNkk7htlVSy61Pb8ZF8PiZWZYPtEk3iQe1K58ntREQUiwULQrfHH/9frFoVSjT5/X6UlJRwZRMRURQlJSXw+/3IzHwRlZX34KuvmmLVKuCss5J9ZvVPQpNNpaWlAIC8vDxTe15enrGvtLQUrVu3Np+Ex4Pc3Fyjj2z27NmYPn16Ik+1QYssqSeXjNH/IIxWUk/8IzJTeiwQMUgg/4EuDmQo/+BNsJo8hzjgIm7H8ji5xIye5NGTTwF3xCxePUkUreyM3D/yPKRSMca2zQxffTuWwRYngyxOBj7s+tbkR/U6LQdcVG+IXEJPVVJP9QTm0jKc0ZviLP9N1PCYVO/UVtwDMPZJtMSW1JO3xaBAiH3keEdul7fFfnaxkZzjqg2qWCeW+MfJ8WI+RgzTDuX3Jtr7b9fmJE6x2raKNezioJrER07OSXU+phNTJYlUCSM5PlJth/to2g2qJ6RUwLiHKOV98w2wfDngcmlYtepKo3Sefs0mAEw4ERFZkK9vd9pp67FuXU/cdNMmfP75Kck+vXonocmm2jJlyhRMnBgenC0rK0O7du2SeEb1yRGE/xmIySF5tq88GiLTB2b00QS5v1COrVzaBdiX17P7ER+rH8+qxEzAot3JyibVfvk2phm+4oCJOKNXPbu3KrLJGbvBFvF+TQZZxH1OBlmiDY7I7fFc3NrqR7WyyfSeaEKDXP4uWskYuxIz4uP413fKqwRgkbet0TGJYsDYpzaJsY/+GZ2D8Gd1I0RmR8TP7hyEyoTpcZO42huIWOEkrkxSxQSqbf3p7eIdu1jFrl3VD1G2rW6jvR6r/U7ux8tp7CNuJyIOUvVxmgyKJyaKFvPI/R3FPmKME0Do3zmgjnfkdvvSeZTCGPcQpbxHHw3datobKC7+PyOxJF74XrxPREQhcqIJAB59tCd69AC++OJ4TJp0H+6669Ykn2X9ktBkU35+PgBg586daNOmjdG+c+dOdO/e3eiza9cu0+MCgQD27t1rPF6WlZWFrKysRJ4qGaKV1APUIwbiH5PiceweK13/R1VKRh9csdpW/cRSOi9au5iYUg3CIIY2uV21T7UNB+3RWP1NrxpMUW1bDbo4GVSx2lbtc3L9pliSSfIxoyWqTKKVjlElmPT9gH2iiaXziOqj2op7AMY+tSvWknqqPnbJKX0CjmKVE2BfNhgIx0ZiHCT2lcMxOV5Rtav6WcVBqm2r21hjnGixT03/MlHFP05jH3k73qRTohNP8VzrMlqsZCLGJlbJIzneUbU76UNERLEqLweefDK0PXz4wYiEkn4/GEzctZ+JiOqLYDBoSjQBwKmnAr17A5984sX69V2TeHb1U0KTTR07dkR+fj6WL19uDLKUlZVhzZo1uOGGUOmE008/Hfv27cP69evRs2dPAMB7772Hqqoq9OnTJ5GnQw5EL6knl4zRb+XSeR5E/gUrl5jREHEtg1gHAFRPY8dJ0kW1TzVgY9cn1sdbnU8szxPtWLG0RRtY0bejDbSoBjqiPTaeAZpEHN9Evxi2anBEboPQV2yzGlhh6by0E6z+SfQxqd5h3JOe4iupF08f/btFin3EWEaOa1RxTixxjxUxwZRI8cQptXU8JzFfLNvR4hwnfaxiGblN1Uf178Dq+Ko+qv4mmnRfFePI27H1Yem8NMG4hyilvfQSsGcP0K4d8NRTVyj7cEUTEZFaUVGRsv3664FPPgG+++7PCAYBd6JXeTdgMf85d/DgQXz77bfG/W3btmHjxo3Izc1F+/btMWHCBMyYMQOdOnVCx44d4fP5UFBQgCFDhgAATjzxRAwcOBDXXHMNFixYgMrKSowbNw5XXHEFCgoKEvbCKB5iWRmR3iaWjBGnyYq34kxf+fFAxEzfckUXeVs/vNXMXLuyMgGH7ao+qv1O2uR2uzarPipOE1bR9lkNYtkNtOjbTgdeYk08OR1wSVT5GBM9oQRELwcTsLhVrWRi+Rii+oBxT30Xa0k9uY9H6CuXE/ZUt3kQUVYPiPz+t4pD5D76tlw2OFp7IrbhoF3uA4s+qvvR2lWcxj/y/XiSTVa3Nd22i5USsQo8gobIVddWMU0s8Q9jHyKiRCkqKoLb7cabb4YSSddeGx4MLSkpQTAYtBxEJSIiNf2z9dZbfbjtNmDbNuCtt4BBg/jZmigxJ5vWrVuHc845x7ivX09g5MiRWLhwIe644w4cOnQI1157Lfbt24czzjgDb7/9NrKzs43HLFq0COPGjcO5556LjIwMXHLJJZg3b14CXg7VjLxSI1qJPCuq5FSU6xkEYF1WRt+vD6DICSexr1x6Rh4ICUA9gKJKZIltUDxGbrO7dbqtul9TtTXQEsugS00ST/GUjym36G8SrWye04EWsbwey8fUC5aDczU8JqUlxj31naqkHuA8lolGDyT0MsU2sY/YXYw15PLAiKE9Wryj2rZ6LIT70doDUpvcJ1qbk32A/Werap9VTBRLDKRvO0kkWe2PJ/HktN3y2kxAeDWT1TWYappoUiWeKOUx7iFKSW63G4WFrwLwITMTuOaaULt4/REiIopN6LM1dJ27MWN8uOce4KGHgE8/5Wdrorg0TZNrKKS8srIyNG/eHPv370ezZs2SfTr1UqiknjgjV3Wrb+sDKJnCtlW73EcYdNGbrGb3yiuY5Jm7qtnAdu1yH7v7sLiNJckUa4KppkmnWAZZxG2nAy6xtNXGIEu06zE5SjQBkauQVLNyrVY22Q+0sHReYtX2Z79+fEzZD2Qn+PjlZcBsfm9R/Bj71D6Xax7ii2XEdjlGEm/1/jaxj34/1WIcu7jGaeyjum/VZtfH6SB2tDgo2na8yaZo+50kqqyuMxlLe9TYB3AW0+j9ncVKmnaz/MQUJ8Y91JAx7gnp2fNTbNhwKrp02YTPPz9FeaF7IiKKjf5Zesst8zB37k0IZUZOQHHxlQ36szVR372JXkNB9YZdWRmxXZzhK/5VazUqIPeRysvofxyrEkwBmAdf9H41GXyJ1ke1HctttDar+1ZtsajtZJN+63TwxWlSyUmfWBJPJnarmYDoyaZY+jgdDaOUE0Ti//fx2gVEaUAVx8irmcRtsZ/+eLEEn1xWT+8vrXKSYx85XrBLQonb8cY1qRzv2O2L9jmdqDjIqk+sSSgn8Y7cpurjpN1EtZop1lJ40UoHi30o7TDuIUpJe/cCmzefCgD44ovrkJW1Dn6/n4kmIqIa0j9DCwtvhsvVAcCF6NPn3/D5eif1vOoLJpvIgviHpqpkjN3gi1Ufq9GHSoQGXqTSMkC4vIxHuK8/XFVST3y83Wxeuz7RtmO5tWqz6iOL9zfU6g9Gq7xftO1YbmsyyKLqoyqJp7dHO46JeG0meVAl0WVjxMEaIiJKD5XStpg8yhHa5YST/KUjxzhyfz0+EibbyIfR458A7Evk1SSuESfuWPURc2R2t9Ha9G3VW2U3yB0tDoo14RRPsinW20RuR4uPVO0mqkk2gHmCjJNYxslEG8Y+RESJ9OSTQHk50K0bsHlzKNHk9XqZaCIiSgCfz4cZM2bA758H4EJs3twbBw4ATZsm+8zSH5NNpKRpRcp2l2t+9ZYH4T8oM6XtgEUfqxEBebRDGniRByI8wr50Ir5Ep/vkQR4nz+F0X7okm1T95Ndhm2iSK4VaJY/EfbBpj+yjaTfIT0rpLADAXQvHJKKUpmmTlO0u10KEP/fFIETfFgfY5XhHFbSI8ZGUcFJ1tUrQREvUqI7h9DFOjxcLuzjI7jH6c6ranTzWrq2mySZ9OxnJJtXzm4iJJkC98igA+zgIiHyx1UfXRqmelNIR4x6ilFNVBfzjH6HtY455HZ99Fko0+f1+lJSUMOFERFRDJSUl8Pv9yMxchcrKLThw4EQ8/TQwdmyyzyz9MdlEMRJnNVrtAyKn2ort+h+ycnkZ/TH6tQ6qRbvQdV2UkknEyia7bbs2u3aZ1R920QZckp1sstq2GmRxMvgCILbVTID1zN3DFn3EQRmqNyoBZNTCMYkoTemlhcWYRY5jAHW8I/YHIssPe2C5yknfbRWPiPuTEePEGuvIsUy02CYRE23k/U6STVbbscRA8v14Yh+5Te6vx8cR5OSS09VMVn3sruVE9QLjHqKU8/bbwHffAdnZ5Vi69HKjdJ5+nREATDgREcVJvv7doEFv4Y03TkRR0a+48caj4HJFPwZZY7KJYqQPwOcI90WVUl+rMnpWpWpENgMvYps80CK3Q+oj75PHieQ+AcVxAsJ9u3an2/p9q7/dnfym2v3dX9Nkk74tD6yo2muSgIo38RRBLhsDWF93STWAIg/QiNtWxyQiovop1s95J1/acSSdAjCX1BMfGi3eiRbXQLE/4KAdijY556baVt2X22PNZ1j1jyfBJN53EvtYtSdy2zbuAdSxj9VKbvk6S6pEUrTSwUREVFseeSR0W14+H8XFk43EUvg6I0w4ERHFQ040AcCzz56H3/2uAr/+ehRGjXoGTz11ZZLPMr0x2UQxEUvMhEvqiaMW8uomqzJ6qsyK1VIfm/IytU1ObiWqb6yPtxq4kffZHduuLdp2LAMu0ZJNYlsikk0RrK5PIK5yEk/ernyMqn/1s7B0Xv0VROIvbM0LZROlLU272dh2uR6r3pLjGjl5pKI/Riw/LLfrwYAi9rGblIIo+6M9Nt3ZvbZUSTZF2+8k8WRJg/kBqskycpJIlWCyTzRp2jXRToTSEeMeopTy3XfAW2+FtsePj7xGk34/GOQvGhFRrILBoCnRBISu03TttVl46CFgzZpeSTy7+oHJJqoBVVkZfWauSJVkkqfWyn+pq44nDL6If3hbzehNVlmZeLbt2pzsA2IbaJHbnG5bJaJiHXCJZdAlpgQT4Ozi1vL+gKKPk/5ERNSwiCVWgXC8IpbV09uB8HeGHPdA8RjxmHHEPjXdhk0fROnvdNuuza7dKauv55rGQbEmnmJNMjndNlHFPoB51VK01Ux6u12SSe/D1UxEDdkjjzyCe+65B6WlpejWrRseeugh9O7dW9n3sccew9NPP41NmzYBAHr27IlZs2ZZ9qeQoqIiuN1u7N/vg6YBf/kLMHdu6OIhJSUlCAaDKCoqAsAVTURE8dI/R8X7brcbY8f68NBDwNdfd8a2bUDHjpGfveQMk01UA1Z/dMqDKTp5gCUAdek8+Tji8fRbqcSM1Sk4LSsDi/6I41ZuCyi25f6q/bKaJJtU++3uWw2mxHprl5CySyRFe6xBE3Y4LQED2CeSopXLEwdoqF4KIvH5RE48JKon5GSSHbmccLSkk9VxLWIfq3ArGrs4SO4DRMY0tRXvJGL1ld3jkx0HOW2zjXsA69hHbIs2WcZqYk60dqqXGPdQFM8//zwmTpyIBQsWoE+fPpg7dy4GDBiArVu3onXr1hH9V65ciWHDhqFv377Izs7GXXfdhb/85S/48ssvcfTRRyfhFaQHt9uNwsK7kJ19O4Bs3HRTqF0s+URERIkV+uwNlSb9y198+H//D/jHP4BmzfjZGy8mmyhu5pJ684Q9+oBJQGpTjTw4GbS3mvUbJeGUaqINCjnZr1MtCIv23HZtsWwnOtkkbkd7rInVjF4ngyaQ+qqOA6Gt+hmFUkpERNTwaNpEYztcTtiDyLJ4Oqt2+UvdapUTpH4JKC2ciKRObYg3eSYfw+k+q/vxxkH6ttMEk2qf1XMbrGIf/QHyaiarEnlyrGTVHmDZYCLC/fffj2uuuQajR48GACxYsABvvPEGnnjiCUyePDmi/6JFi0z3H3/8cbz88stYvnw5RowYUSfnnI58Ph/WrOmFN97IRqtWe3D++a2U1xYhIqLEEa+FN3x4JwBX4JFHjuDIkdn87I0Tk02UIHoJDo90C5j/mWUq+sHmsfofzZmIPGYtlpiBTR/VbbQ2u227tlj2Rxs4imdGr7jtdMDFyeBLLNsmVoMsVhfAtko2yW1WpWTsElVUbwUAZNTCMYmonhG/OwBzDCOuVrKLj1QZFrkcnxz7SCud5NhHvo0Wz8RSLi9aXGMX69RW6TwrVp+7dgmdWBNO+nassY/d/gjRYh99224FExT7o03MYezTYDDuIRt+vx/r16/HlClTjLaMjAz0798fq1evdnSMw4cPo7KyErm5uZZ9KioqUFFRYdwvKyuL/6TTVFUV8PXX5wEA9uyZhpycx+D3+znYSURUy8IJp+EA+uDIkY4YPPh5+HwXJvfE0hSTTZQg0f6ikEvJWJXRs5rWKs74jaPEjH4ba+k8+ZTEY0BqV+XWnCabnJTQc/JHW00STrFs13SQxWmSyiCXjBG35YSR2EeVPNLbow2yiIOHLB9DREQy/ctLjmXsqAbv9RhHj5Wifd+Ik3AA5UpvMXax2pbveyz6yXkyu+Na5cjEc0OUdhU5borlK1nVN9Z4yK4tWkxUoyST3kkV44jxjyqhJPaxepyqjypWIqKG6tdff0UwGEReXp6pPS8vD1999ZWjY0yaNAkFBQXo37+/ZZ/Zs2dj+vTpNTrXdPfWW8A33wDNmwOHDy+G3++H1+tloomIqA74fD7MmDEDfv/DAO7D999fCE0DXK6oDyUJk02UEJp2p7Htct2v6GFVYkb+I1ZVgk98fAJLzKRqGZmaSJdkk93+CE5XMwGRAyVQ9LVrjyxJI5ZMogaiEhEfIwk5JhHVK+aSeno5YVXZYHnCjFWMo8tEbB8aitgHiqeJRSJjJKt5QjU9F6fnl4hkk7id6GSTUiyrmSDtsysPbJegCu9n2eAGhnEP1aI5c+bgueeew8qVK5GdnW3Zb8qUKZg4Mfy9WlZWhnbt2tXFKaaMBx8M3Z588mp89NFv8Hq98Pv9KCkpYcKJiKiWlZSUwO/3IzNzESorS/DZZ43wwQfAH/+Y7DNLP0w2US04gsjprzUtMQNpf7QSM/q2YqWTvku/jVYiL5ZSMvGWkUl0aRmrwYt4B1yczOzVt+tskOWwcBCrPkekNq5mIgeCSPyFrXmhbKJ6TpVAEmMW/TtLFb+olgeJbZU2j9W3bWIf8dDi6em30eKgaG12207uO93nRKLjH6ttq9hH7mMXR0WINcEUUGzbxUROVjMx9mmQGPeQjaOOOgputxs7d+40te/cuRP5+fm2j7333nsxZ84cvPvuu+jatatt36ysLGRlZdX4fNPVl18Cy5YBLlcVPvpomFE6T79mEwAmnIiIaol8fbxevTZg/foeuOGGzdi06aRkn17aYbKJaoFqlqXTcnmqgRbV8VWDLx5hnzzqYbHaSewql9lTnYo8tmNXPgYW21bjUbKaziqOd8DF6XYss30dJ5j0DtHKxTjppxpAsRtY4bUKiIgoXnbfF6o4SH6sWGpYTFLFQ1FeTz+silXco8qJqXJjqm1Ij7W6L56u3TnGI9YEk6otllhH37ZqV9KkDtFinGhxjJPHAuYSeYx9iMia1+tFz549sXz5cgwZMgQAUFVVheXLl2PcuHGWj7v77rsxc+ZMvPPOO+jVq1cdnW360lc1adqrKC4eYySWxAvXi/eJiCgx5EQTADzxRA906wZ8+eXxuP32ubjnngnJPck0w2QTJZymFSnbwyVmAOtyeXriyMk1C4DI0jPySId8nacEl5lJZamabFKSB1tU23bl8pwkj+zL67FkDBkC4IWyiSgmmjZJ2e5yPYboZfGclhqOVQJjn3QsPVxXySa7fTHFPrGuZgIi/404naRTfQbaNXYnSA0F4x6KYuLEiRg5ciR69eqF3r17Y+7cuTh06BBGjx4NABgxYgSOPvpozJ49GwBw1113obCwEIsXL0aHDh1QWloKAGjSpAmaNGmStNeRqvbsAf7979D21VcfiEgo6feDQS4ZJCJKtGAwaEo0AUDXrsCZZwKrVnmwZs2pSTy79MRkE9WhI4g+bVYvwafP8o1WUk/cFlc6ieVkxG19v2IARk6I1HVZmWjt8XKadIol4ZTQARZxEARwVvJF1U+VbIo1IUVERJRIYuwDYVufDKPHO2KCyenyoWjl9fT7chxkUWZP7CJuxxrj1KR8cLR9VqINbMeaeKpJHGQpWuwj33e6kttq2+nqJyIie5dffjl2796NwsJClJaWonv37nj77beRl5cHANi+fTsyMsIZy/nz58Pv92Po0KGm40ybNg1FRUV1eeopq6ioCG63Gz6fD48+CpSXAz16AI8/PgolJSUIBoOm94ormoiIaof8vaR/Pt90kw+rVgFbt56FigogKwvKz2eKxGQT1SH5L/No//z0ARgnfcX+8rbq8eL+KOVmouXHrNqgaIfFffE0nMwEjKWvLp4ZvrEkl6Kej12pGP1+TQdZ7Gbxyn1Uz0uE0HUGEv1PghMRiRoouxkfYmwiJp3khJSTbf3x4neaKkkFaZ9NqT3xME5yX6rYRz6mVfyS6FJ6TifaqNqcJpocnadq5bbTFUzR+iZqkg41eIx7yIFx48ZZls1buXKl6f73339f+yeU5txuNwoLCxEMZuCxx+4EAIwfD8yYES7nREREdU//fJ42LQNHH30nfvoJeO45YPt2fj47xWQT1RlNu9PYdrnur96y+8umtor468eWZ3Qqru0U79M7zY/F+5h4zidau5PBlrhm8gKRF70WDxLtugLxbIvHsx5Y0bSJTk6eiIgoLuL3jLqcMGAOAKwmzkTblr+M7coRyyuhLGIf8fQSoS5L8dVmssnu+CbxxD6q/fLjnWxbxUAsG0xElArC12LaBADIywP+979ZKC4ujCjnREREdSf8+fx3/PnPf8BPP52LSZN2YudOfj47xWQTJYleLk+19EdcHnQE4YtqW5WJcbItlpo5AvOqJnkKroNyM/K22N3ptl2bk3127AZBog201GhgBYh9BZOTPk5n8lqtZLJ7LJGkNioLxXnMRx55BPfccw9KS0vRrVs3PPTQQ+jdu7ey72OPPYann34amzaF/mjt2bMnZs2aZdmfiOqa/B1kF7OoVmdbLR/S4xpxnx5nqY4jx0FQ3Hew4kmUyDJ6sfRz+lVekyRTVJqwbRf7qO47nTgDxf1YJukw7iEbjHuIkiJUQu9H/Pgj8Ouv01FcXMSBTCKiFBBOOA0FsAM7d+ZhxIh/w+e7MrknliYSfSlQIocqERrskJME4rZ+nQPx9rCw74jD7SPSMSql5zqieD7xfiVCAwn6j4WA8FNe/WO1Xa7oK7er9jn9sTuGqt3unPUfS+J7E8t7WqnoI/44/f98WDqu+Hyqf1fivz2i1PX8889j4sSJmDZtGjZs2IBu3bphwIAB2LVrl7L/ypUrMWzYMKxYsQKrV69Gu3bt8Je//AU//fRTHZ85EanJ34Pid5nV95Xqe9Lqe1X+jhX7HZYerzp2HLGPTo47rGIiJ7FPLHGQ08c5OR9HMY9OfG/0B1nFPqr/F1b/v1T9xePbxbOqOFr174soNTHuoYbm44+BH39sC6ACweAj8Hq9TDQREaUIn88Hr/cwgCcAADt3MtHklEvTNAd/QaaWsrIyNG/eHPv370ezZs2SfTqUQKHyevpMXHG2rXyB60zFfUA9Q1e1T+4XbYavfB+IWnZG5mSmr117vKwGTexm9DpidR0Csc1uJq/e7mTlk9U+q9VM4naA5fLqidr+7NePj0H7gcwEH7+yDHg9tnPv06cPTjvtNDz88MMAgKqqKrRr1w433XQTJk+eHPXxwWAQLVu2xMMPP4wRI0bU6PQp+Rj71F8u13yo4xx5WxW/RIt7xHJ9Yl9VXJOpuC8/Fog5/lEdIpZ98bCLaeJe4KNawQREj330Nqt2pyubYlkVFYCm3WDzWigdMO5h3NOQNYS454orgOefB4An4PXeAL/fz5VNREQpoqQkdI2mzMwTUFn5JQA3vvgCOOWUZJ9Z7UnUdy/L6FGKEcvryWVjxDIxcskYeeAkIGyrysvI++RyM3KJGVXJGSCmgZgaJ3eSIdrAithuNRiib0frZ5c00vs56RuZbCKKSQBxj6XaHhOhL29RVlYWsrKyIrr7/X6sX78eU6ZMMdoyMjLQv39/rF692tFTHj58GJWVlcjNzY3/vImoDjgpLQxEltfT98v3VXGO3Ff8jpaPafdYsb/cDth+eNZKAiiRVPPvYo19xDanE3CcJptUfaJtEznAuIeozv34I/Dii1UAMnDjjQE88kiFMbAJgAknIqIk0j+P9QkAJ5+8BZs3n4iRIz/F+vWnJvv0Uh6TTZRi5D+o47lINmBOVsnH0/eJ/fX98uCN1eMgtEHRDqFdlOi/5BJFHmCJNrhi1R4twaT3jXXAJZ4kk7xNlHzt2rUz3Z82bRqKiooi+v36668IBoPIy8sztefl5eGrr75y9FyTJk1CQUEB+vfvH/f5ElFdiOV7So5h5FhGPq4Yv8jHACLjIPlY8cQ++j5ZqsRA0ZJKQM1iH3G/k9VMqmOJj3WyyomxD6Umxj1Ean/724eoquqHDh2+xyOPXAtAvEYIE05ERMkiJ5oA4PHHT0TfvsCGDSfhjjvux913s3qSHSabKKVoWpGy3eWah/Afzh6L7Wii9Y3lWPFKhcGXRA+yiO1Wgyxi/3gGWZwNqmjazSCqsVqc4btjxw7TcmTV7N5EmDNnDp577jmsXLkS2dnZtfIcRJQYmjZJ2R4qrycTkz36favYxSqukY8Rj3iOYfVnR23FQVaVwlXnLb9PsU66cZpU0vs46e9sYg7L5VGNMe4hqlOHDwNr1/YAAMyd28G0Tx/YDAaDdX1aRESE0OevXNL09NNDP6tXZ+Hjj3sm8ezSA5NNlCaOVN/K5fWAmpebsSoxA6FNv38E6lIy4jHE48jt8n6Z1ezkmrIaiIo24BJtUEXVR/WYWJJL8nGcbhOlvmbNmjmqfXvUUUfB7XZj586dpvadO3ciPz/f9rH33nsv5syZg3fffRddu3at0fkSUTKpyutZlfm1WnmkE+MnJ6WCxTYx9rGKe+TnizX+EY9dE9HigVgTTfJ+u7J5YrtVvKO3WR3H6Som/T7L5VFqY9xDFFJUVAS32w2fz4d//xsoL8/BsccCgwaFZtEHg0Fj1R9XNBERJY+8Alv//J440YdLLwU2bz4Lhw8DjRpFfn5TCJNNlCbEQQu7kjEiORmhKjdjVVpPVXIGMM8Stislo+qj9wPMgw7i+VgNGjj9VXUy6KAaiHEysCL3i1ZKJpZrFOi3TgZlWDKGalltjN3FeEyv14uePXti+fLlGDJkCIDQhbKXL1+OcePGWT7u7rvvxsyZM/HOO++gV69eNThhIko+8TvOLkZRPc4u5lH1tSqXJz+P2Bbt+FaliXWqkn1WVDGZU04n3Kj6RYuBnMQ/qjZVDCS3x7IinKgGGPcQ1Tq3243CwkJUVQHPPx9KJt10EzBrVrhcExERpR7987uoyIWOHf+ObduAp54Cfv2Vn99WmGyitGBdXu9+m0fJAzNO1EUpvdrk5NydzOqNt4ye2B4tyaS3xTJzVy8Zw/qoVP9NnDgRI0eORK9evdC7d2/MnTsXhw4dwujRowEAI0aMwNFHH43Zs2cDAO666y4UFhZi8eLF6NChA0pLSwEATZo0QZMmTZL2OogoPvbl9eIZHVbFOHZttVluL5Z4y+oYTh9v9RqiJZfkxyYi8eQkyaTfN+9juTyq7xj3UH0Wvh7TJwCAZs2A3bvvwqxZhRHlmoiIKHWEP799OP/8Xti2bSB8vj3Ys2caP78tMNlEaU5VYkZeSaSvihJL5KlKwliVzgPUZWXsZtlaldE7Iu2XWa3YOmLR7lQiyuiJ+5wOvqj6OR9YYckYSoogEn/tgjjKrl9++eXYvXs3CgsLUVpaiu7du+Ptt982Lp69fft2ZGRkGP3nz58Pv9+PoUOHmo5jdTFuIkpXciyhKjGs75e/T63KC6sea1ciGDb75Lgn2p8b0VarxxsDxVpSz8mEGqt9TtuiTagRn0N1HKJawLiHqE74fD78618/4IcfgIMH78WsWZM5UElElAbCCaehAH7Enj2t8Le/PQuf7/LknliKcmmaZnX13JRVVlaG5s2bY//+/Y5qQFP95XIVITL5I96322d3XzWAokoyqfohhv1yHyvJLKNnt78mgyvR7lvvs1rpRvVbbX/268fHH/cDngQfP1AG/JffWxQ/xj6kc7nuqt5yEtOoYhYxPgLsYx6xTW6321cXMY8s3hhIfqyTSTdWj7E6jpNSePb3rVa6Uf3FuIcasvoY96xeDfTtCwB+AB3g9e5BRUVFks+KiIicysrKgt9fDGASzjwTeP/9ZJ9RYiXqu5crmyitOUk6uFzzqresSrYkokxMqoi3jJ782FhWPNmVj7EafLGexatpN1ucH1EdSYFrFxARWXGSdAiV2otVrPGQ1bUrrTjpU9OYLNbVTKrHxbPiyW6ijb7fOiZiiTxKKsY9RHXinnv0rX/D690Dv9+PkpISrmwiIkoDJSUl8Pv9yMz8JyorJ2LVqkysWwfwkpGRmGyiBuAIIsvFiPdVpfHENvli1lblY1Tt8jFh0UfuK6tpGb1YrlcQzyBLTS+MzQtdUwrhoAsRpT29fJ0qxrGKiVQlhsX94mPkdnmfVUyk6iuK9jiVRE20seobSxzkpJyw3bUsiZKAcQ9Rrdu6FViyRAPgwk03+TFvXgVKSkIXlwfAhBMRUQrTP6/10qfdu3+Ozz7riquv3oTPPz8l2aeXcphsogYggPD1DPQLXuvEC2Cr9kNqE6+LILZb9dH3AZEDN6pfP3nQI5bBFrvjqEQrnSf3iZZcsmqPduFsDrYQEREllvxdK8Y4VveheAwQW7wjxy128Y5djJPImCDe61bKfWKJgzjJhoiIwoYP3wBN64HOnbdi3rzQatbwNUCYcCIiSlVyogkAFi7silNPBb74ojNuvfVB3Hff+CSfZWphsonqPU27M2qfcKm9+iKe6xZEG3SJt4yMeK0llsijNBAAkOirGcZxoWwionjVXqk9O07K5NWEasW5E7GsapL713yiDUvkUcpj3ENUq0pLgY0buwIAHn/8BNM+feAyGOQvDRFRKgoGg6ZEEwB07w786U/Ae+95sHr1ack7uRTFZBMRAHOpPcC69AwU/VTtRxT7AfMsXidl9RLNamAlWuLJ6Uxfu9IwnL1LRESUOsSyeXrME2u8I5caVrFK9sT6Z0i8JYVjTTbVfHJN9OcmIqL6rKioCG63Gz6fDw89BASDHpx+OtCvX2iWfDAYRFFREQCuaCIiSmX6Z7Xc1qbNCQCG4csv+6KsDGjWLLRP/oxviJhsIgJgLrUnt4szda0uhi236+QyMao+ej9dohNPdkmempSQiWcAhigN1MbEQk5WJKKUUwl1eWFAHe9Ylc+D0A7FPlU5Ybv2RLCLfZyW1Ysltol27UqiFMa4hyjh3G43CgsLUVHhxT/+EVptfMcd5nJMRESUntxuNxYtGo6jjvozfv31KDz2GHDrrfyM1zHZRASnpfbur4MzqQ12iZ5EXRg7AE2bGOuJERERUZI4L7VnN/HGKvGUCmK5VpOqv93q7NA+lsgjIiKV8PWYSgEAxx8PfPZZCYqKCiPKMRERUXoJf8ZPBvA4HngAKCubheJifsYDqfvXIVEKEsvNANblZcTye7DpA4t+Kk5/VZ2uIHKSZFL1c7KaiSjN8doFRETVVGWBVTFMrHGQ/Bzpsqrb7hhEaYpxD1GtmDzZh3vv3Y+yMuB//7seRUX/5CAkEVE94fP5EAjMQnHxT/jpp6NRXPw/fsZXY7KJyDG53Iw4m9dJuTy5j1U/q+dOhHhm86r68FpMRERE9V+ldCvHOlZxkNWxol3XqSZ/mjhJANVkRbfV44mIiCI99xxQVtYcwC8IBhfC6/VyEJKIqB6ZPn0qZs6chGDwLgCTMXVqp2SfUkpgsonIIU0rivuxqVOCz76kDEvhEYEzfImIqjkptWclVIJPJJbiUxHL88XLSTLI/BwshUcNHuMeooTTNOCee/R7D8Lr1eD3+1FSUsKEExFRPVFSUoJg8B8AJgHohL/97SU8//zQZJ9W0jHZRFQnjkj35V89cX+yS8kQNXABAFUJPmaij0dElPKixT5W/eONg5yuOmLsQ2TCuIco4d55B/jiCwA4gClTcjFrVoVx4XgATDgREaU5/TO9uLgYgUAuiouBF144FiefXILCwob9Gc9kE1GdkAdAnJSS0cX6a1qT6zYRERERJUIssY+oNpNBjH2IiKj23XjjNgAd0bfvJsyadQcA8YLyTDgREaUzMdHk8/nw66/AvfcChw/3wLRpk+FyNexVrEw2EdWBmpTgI6I6FkTiy8lwhi8RNTA1KcFHRHWIcQ9RjRUVFcHtdsPn82HtWmDbto7IyAjiuedOry6zFERRUZEx+BgMstYkEVG6CgaDRqIJAB5+uAhdu56Hjz/ugw4dHkUwuNDoK34HNBRMNhEREREREREREcXB7XYbK5a++CI0+HjllW4sXBie/a5ryLPdiYjqAzlx5Ha78fHHQ+F2f4/vv++AgQND+8UVUA0Jk01ERESiAICMBB+TM3yJiIgoFTHuIaqxcIm8p+By3QkgA02b/tNUZomIiOon8TsAuBqzZwO9epU02O+ARIeVREREREREREREDYbP50PPni9A0zLgcr2FRx65vkEOMhIRNUQ+nw8331wOoApLlwKFhc832O8AJpuIiIhEgVr6ISIiIko1jHuIEmL7duDzz3sAADStGF6vt0EOMhIRNVQPPngjXK4lAICMjCkN9juAySYiIiIiIiIiIqI43XMPUFkJAO/B690Av9+PkpKSZJ8WERHVkZKSEmjaTABAVdXlmDjxoSSfUXIw2URERCSqrKUfIiIiolTDuIeoxkpLgQULQkv6Ro36CRUVFSguLkZhYSETTkREDUBJiX6NpiH4858BwIMHHnA1yO8AT7JPgIiIKKVUAdASfMxEH4+IiIgoERj3ENXY0KEfIRDoi3btduCJJ64CIF4wvtB0n4iI6pdwoil0jaYVK4BlywCP5zoUFrYF0LC+A2Je2bRq1SpceOGFKCgogMvlwpIlS4x9lZWVmDRpErp06YLGjRujoKAAI0aMwM8//2w6xt69ezF8+HA0a9YMLVq0wJgxY3Dw4MEavxgiIiKiRGLcQ0RERESioqIiY7b6nj3AJ5/0AgAsWNAOM2aUoKioCEBocLG4uBjBYDBZp0pERLUsGAwaiSYAWLmyCG3b/ohAIBN//OPLpu+AkpLwd0R9FXOy6dChQ+jWrRseeeSRiH2HDx/Ghg0b4PP5sGHDBrzyyivYunUr/vrXv5r6DR8+HF9++SWWLVuG119/HatWrcK1114b/6sgIiJKFF4omwSMe4iIqF5j3EMUM7fbbZTIe/BBoLLSi1NPBdatC81ud7vdRl+fz1fvBxaJiBqyoqIi08olj8eNH38cBwD47LMzcMstRQDCK6DE74j6yKVpWtyL3F0uF1599VUMGTLEss/atWvRu3dv/PDDD2jfvj22bNmCk046CWvXrkWvXqHZH2+//TbOP/98/PjjjygoKIj6vGVlZWjevDn279+PZs2axXv6RESURmr7s18/PprsB1wJPr5WBhzk91a6S1bcAzD2ISJqaBj3UEOWDnFPaNDwXmRn70R5eTYuv/xFPP/8ZabZ7URE1DBNn16CoqKLAZyM2bOBykpzqb1UlKjv3phXNsVq//79cLlcaNGiBQBg9erVaNGihTHgAgD9+/dHRkYG1qxZozxGRUUFysrKTD9ERES1gjN8qQYSEfcAjH2IiKiOMO4hiovP58O5576K8vJsAFvw/POXp/QgIhER1Z1p03y4+OJvAQBTpuxEYeHsBvMdUavJpvLyckyaNAnDhg0zMmKlpaVo3bq1qZ/H40Fubi5KS0uVx5k9ezaaN29u/LRr1642T5uIiIgoZomKewDGPkRERESp7NAhYOPGP1XfmwGvN7NBDCISEZEzzz03GMD3APLgdt/YYL4jai3ZVFlZicsuuwyapmH+/Pk1OtaUKVOwf/9+42fHjh0JOksiIiJJZS39UL2WyLgHYOxDRER1hHEPUVz++U9gzx4A+BaZma/C7/ejpKQk2adFREQpYs6cEgAzAQDB4K0oLJyd3BOqI7WSbNIHXH744QcsW7bMVOcvPz8fu3btMvUPBALYu3cv8vPzlcfLyspCs2bNTD9EREREqSDRcQ/A2IeIiIgoVZWXA0VFBwAAgwdvgd9/GMXFxSgsLGTCiYiIqq/rV4jCwg5o3x4A2qCk5JcG8R3hSfQB9QGXb775BitWrECrVq1M+08//XTs27cP69evR8+ePQEA7733HqqqqtCnT59Enw4REVFsggBcCT6mluDjUcpg3ENERGmNcQ9RzC699E0cOHA+mjffjxdeuBAAjPJIhYWFpvtERNSw6Imm0DWa7kRBAXD99UDTpjNQWBgqsV+fvyNiTjYdPHgQ3377rXF/27Zt2LhxI3Jzc9GmTRsMHToUGzZswOuvv45gMGhcjyA3NxderxcnnngiBg4ciGuuuQYLFixAZWUlxo0bhyuuuAIFBQWJe2VERETx4iAJVWPcQ0RE9R7jHiJLRUVFcLvdxsBgZSXw3//2BQCcccZHmDVrDYqKigCEBw+DwWBSzpWIiJIvGAxWJ5pC3wk7dpSgWbObUVbWHBdc8CqCwTVG35KSEgSDQeN7pD6IOdm0bt06nHPOOcb9iRMnAgBGjhyJoqIiLF26FADQvXt30+NWrFiBs88+GwCwaNEijBs3Dueeey4yMjJwySWXYN68eXG+BCIiIqLawbiHiIiIqOFyu92m1UrPPAPs398CTZocxBtvXIw+faaa+tfn2epERBSdnDjKygLKyqYA+Ac+++w8vPzyeQDMK6Dqk5iTTWeffTY0zXrqk90+XW5uLhYvXhzrUxMRERHVKcY9RERERA2XWB6vqsqFZ575OwDg4MEiFBdPZXKJiIhs+Xw+BAKzUFz8I378sS2efBLYvVsstVe/vkcSfs0mIiIiIiIiIiKi+iCccPqyumUP7rzzKPh8k5N3UkRElDamT5+KdevexptvtsUNN/wAoKReJpoAJpuIiIiIiIiIiIgsTZ3qQ2HhFgCA2/0QZswoSu4JUYSqqir4/f5knwZRSsjMzITb7U72aZDg5ZcHIifnZwDHwO3+v3qZaAKYbCIiIiIiIiIiIrJ0xRWvArgIwG8IBh9ASYm73g4UpiO/349t27ahqqoq2adClDJatGiB/Px8uFyuZJ8KAbjnnhIAvwJ4EMHgHSgqmomiojuTfVoJx2QTERERERERERGRQlHRDLz00qUAgBkzWqKq6jYUFhYCABNOKUDTNPzyyy9wu91o164dMjIykn1KREmlaRoOHz6MXbt2AQDatGmT5DOikpLQNZp8vll49FFg584OmD79O7jdJfXue4TJJiIiIiIiIiIiIklJSQmmT/8awAnIzQVuuglo1ky/hhMTTqkgEAjg8OHDKCgoQKNGjZJ9OkQpIScnBwCwa9cutG7dmiX1kkhPNIWu0TQFLVoAt94KtGx5LwoLWwOoX98jTDYRERGZVFb/JPqYRERERKmGcQ+RqKioCG53uEReZaWG3Ny52LsX6NFjOe6//78oKioy9geDwWSeLiH8/8Dr9Sb5TIhSi558raysZLIpiYLBYHWiKfS9sWfPTDRuPB6//dYSF130EoLBT42+JSUlCAaDKCoqStLZ1hyTTURERCaB6p9EH5OIiIgo1TDuIRK53W7TiqVjjy3E3r1Ao0aH8O67g3HmmZOMvvVpJnp9wOvSEJnxdyI1yImj7OwqHDo0HcA9+PzzwXjhhcEAzCug0hmTTURERERERERE1ODpCaTCwkIEgxn4979DF28/fLgIxcWTmGAiIqIa8fl8qKiYg5kzd+N///sdFi8GfvhBLLWX3t8zvGoeERGRSWUt/RARERGlGsY9RDKfz4fi4mJMn/4dvvsOAHbi739vlfYDgESJ0qFDB8ydOzdhxzv77LMxYcKEpB/DiVGjRmHIkCEpcxxKTzNmTEb//p8DAEaO/AaFhUX1ItEEMNlERERERERERERkmDTJByA06Od234eSksnJPSGqNUVFRSgpKVHuKykpqbVrp4waNQoulwtz5swxtS9ZsiTly5+tXbsW1157bZ09XzAYxJw5c9C5c2fk5OQgNzcXffr0weOPP270eeWVVyz/PybT999/D5fLhY0bN5raH3zwQSxcuDAp50Sp4ZVXzgWwB0AnuN0j6kWiCWCyiYiISBKopR8iIiKiVMO4h0jl0ktfB9ABwC8IBh9OyUFsSgz9Ol3y/2P9+ilut7vWnjs7Oxt33XUXfvvtt1p7jkTy+/0AgN/97ndo1KhRnT3v9OnT8cADD6CkpASbN2/GihUrcO2112Lfvn1Gn9zcXDRt2rTOzqmmmjdvjhYtWiT7NCiJ5s4tAXAPACAY/DuKimYm94QShMkmIiIiIiIiIiIiANOmzcLSpV0AAHPntkFx8RRlMoLqB71sovj/WE801XZZq/79+yM/Px+zZ8+27FNUVITu3bub2ubOnYsOHToY9/WSbLNmzUJeXh5atGiB4uJiBAIB3H777cjNzUXbtm3x5JNPmo6zY8cOXHbZZWjRogVyc3MxePBgfP/99xHHnTlzJgoKCnDCCScAiCyjt2/fPlx33XXIy8tDdnY2TjnlFLz++usAgD179mDYsGE4+uij0ahRI3Tp0gXPPvtsTO/T0qVLceONN+LSSy9Fx44d0a1bN4wZMwa33Xab0Ucuo9ehQwfMmDEDI0aMQJMmTXDMMcdg6dKl2L17NwYPHowmTZqga9euWLduXUzvteztt9/GGWecgRYtWqBVq1YYNGgQ/ve//xn7O3bsCAA49dRT4XK5cPbZZwOILKNXUVGBm2++Ga1bt0Z2djbOOOMMrF271ti/cuVKuFwuLF++HL169UKjRo3Qt29fbN26NYZ3klKF/hnz97+3QOvWAHAcpk//vl58zzDZREREZBJA4q9bwBm+RERElIoY91DDJpdQKykpQXHxDgDHoGnTMuzaNUOZjKD6Rfx/nJWVVSeJJiC0qmrWrFl46KGH8OOPP9boWO+99x5+/vlnrFq1Cvfffz+mTZuGQYMGoWXLllizZg2uv/56XHfddcbzVFZWYsCAAWjatCn++9//4sMPP0STJk0wcOBAYwUTACxfvhxbt27FsmXLjASSqKqqCueddx4+/PBDPPPMM9i8eTPmzJljrAgrLy9Hz5498cYbb2DTpk249tprcdVVV+GTTz5x/Nry8/Px3nvvYffu3TG9Jw888AD69euHTz/9FBdccAGuuuoqjBgxAldeeSU2bNiA4447DiNGjICmaTEdV3To0CFMnDgR69atw/Lly5GRkYGLLroIVVVVAGC8znfffRe//PILXnnlFeVx7rjjDrz88st46qmnsGHDBvz+97/HgAEDsHfvXlO/O++8E/fddx/WrVsHj8eDq6++Ou5zp+QQk9klJZNx6qlvAQCaNbsXhYUzI76TaquUZ21hsomIiIiIiIiIiBocuYRaRYULzZqFrqFz4MBUZGeHBqH1ZEQwGEzauVLt8vl88Hq98Pv98Hq9dXb9lIsuugjdu3fHtGnTanSc3NxczJs3DyeccAKuvvpqnHDCCTh8+DCmTp2KTp06YcqUKfB6vfjggw8AAM8//zyqqqrw+OOPo0uXLjjxxBPx5JNPYvv27Vi5cqVx3MaNG+Pxxx/HySefjJNPPjnied9991188skneOWVV/DnP/8Zxx57LAYNGoTzzjsPAHD00UfjtttuQ/fu3XHsscfipptuwsCBA/HCCy84fm33338/du/ejfz8fHTt2hXXX3893nrrraiPO//883HdddehU6dOKCwsRFlZGU477TRceumlOP744zFp0iRs2bIFO3fudHwusksuuQQXX3wxfv/736N79+544okn8MUXX2Dz5s0AQiUHAaBVq1bIz89Hbm5uxDEOHTqE+fPn45577sF5552Hk046CY899hhycnLwr3/9y9R35syZOOuss3DSSSdh8uTJ+Oijj1BeXh73+VPdCwaDpmR2796fAvgRZWXNcf75S4zvmboo5VkbPMk+gXjoGeeysrIknwkREdUV/TO/JrOOnNFn5Sb6mETxY+xDRNSwMO4hqhv6YF9hYSEAID/fh9Cv3w74fAXw+aZG9KX6qaSkxEg0+f1+lJSU1Nn/87vuugt/+tOfTGXhYnXyyScjIyO8piAvLw+nnHKKcd/tdqNVq1bYtWsXAOCzzz7Dt99+G3Gdo/LyclMZuC5dusDr9Vo+78aNG9G2bVscf/zxyv3BYBCzZs3CCy+8gJ9++gl+vx8VFRUxXfPppJNOwqZNm7B+/Xp8+OGHWLVqFS688EKMGjUKjz/+uOXjunbtamzn5eUZr0du27VrF/Lz8x2fj+ibb75BYWEh1qxZg19//dVY0bR9+3bT+2/nf//7HyorK9GvXz+jLTMzE71798aWLVssX1ObNm2M82/fvn1c5091T16pVFw8FRs3voHXXmuLVavOwAsvDKyzUp61IS2TTQcOHAAAtGvXLslnQkREde3AgQNo3rx5sk+DqE4x9iEiapgY9xDVvnDCaRaAqwEcjUGDvkBx8VTbx1H9IQ/s6veBukkynnnmmRgwYACmTJmCUaNGmfZlZGRETDyorIxM6mdmZpruu1wuZZueDDl48CB69uyJRYsWRRxLX40DhFY22cnJybHdf8899+DBBx/E3Llz0aVLFzRu3BgTJkwwlepzIiMjA6eddhpOO+00TJgwAc888wyuuuoq3HnnncZ1kWTi63e5XJZt+nvi9L0WXXjhhTjmmGPw2GOPoaCgAFVVVTjllFNifn1O2Z0/pa+XX74AeXl78dtvuWjefCqCwdlpmWgC0jTZVFBQgB07dkDTNLRv3x47duxAs2bNkn1ataqsrAzt2rVrEK8V4Out7/h667faer2apuHAgQMoKChI2DHVAkj8tQZ47QKqmYKCAmzevBknnXQSP0vqKb7e+qshvVaArzdRGPcQ1S2fz4fp0/chGDwawA946aXzk31KVEdUKwjkFW91MeA7Z84cdO/eHSeccIKp/Xe/+x1KS0uhaZqRXNi4cWONn69Hjx54/vnn0bp16xp9f3Xt2hU//vgjvv76a+Xqpg8//BCDBw/GlVdeCSCUGPn6669x0kknxf2cAIzHHzp0qEbHEcX6Xu/Zswdbt27FY489hj/+8Y8AYJQp1OmrwuxKcB533HHwer348MMPccwxxwAIJbnWrl2LCRMm1OAVUbrIzATmzs3FyJFAMHgbMjMfS8tEE5CmyaaMjAy0bdvWKC3QrFmzBvGHDNCwXivA11vf8fXWb7XxeutmZq9+oexEH5MofhkZGTj66KMB8LOkvuPrrb8a0msF+HoTgXEPUd3x+eYgGNRLmM3E3Xe3S9uBPoqNfP0UnX6/rq7T1aVLFwwfPhzz5s0ztZ999tnYvXs37r77bgwdOhRvv/023nrrrRp/5wwfPhz33HMPBg8ejOLiYrRt2xY//PADXnnlFdxxxx1o27ato+OcddZZOPPMM3HJJZfg/vvvx+9//3t89dVXcLlcGDhwIDp16oSXXnoJH330EVq2bIn7778fO3fujCnZNHToUPTr1w99+/ZFfn4+tm3bhilTpuD4449H586d430LIsT6Xrds2RKtWrXCo48+ijZt2mD79u2YPHmyqU/r1q2Rk5ODt99+G23btkV2dnbE93vjxo1xww034Pbbb0dubi7at2+Pu+++G4cPH8aYMWMS9vootW3bNgPAJQBORGXl2Dot5ZlIGdG7EBERERERERER1T8lJSWYMWMfgDbo2BEoLDwGhYWFKCkpSfapUR0oKiqyHND1+XwR11epTcXFxREl0U488UT84x//wCOPPIJu3brhk08+qdG1nXSNGjXCqlWr0L59e1x88cU48cQTMWbMGJSXl8ecyHr55Zdx2mmnYdiwYTjppJNwxx13GEm6v//97+jRowcGDBiAs88+G/n5+RgyZEhMxx8wYABee+01XHjhhTj++OMxcuRIdO7cGf/v//0/eDyJW0cR63udkZGB5557DuvXr8cpp5yCW265Bffcc4+pj8fjwbx58/DPf/4TBQUFGDx4sPJYc+bMwSWXXIKrrroKPXr0wLfffot33nkHLVu2TNjro9RVUlKCoiIfLrvsSwBAVtYUFBbOTcvvIZdW+1ccrTVlZWVo3rw59u/fX+9nzTWk1wrw9dZ3fL31W7q+Xv28gU8ANEnw0Q8C6J127wmllnT93YoXX2/91pBeb0N6rQBfb7pg3EOprDZ/r4qKiuB2u43kQqiE2v3Izv4Z5eU5uOiiV/DKKxen9cXZG5ry8nJs27YNHTt2RHZ2drJPhyhl8HcjPYjfN3fe6UPPnsDGjUD79s9i+/a/RXwPlZSUIBgMJjwRnqjv3rRe2ZSVlYVp06YhKysr2adS6xrSawX4eus7vt76raG9XqK60tB+t/h667eG9Hob0msF+HqJKLW53W7TqqVgMIg//vF1lJfnAPgC3bptBhBa0VJcXFxnJdSIiKhhEkt5ZmQA+mKm7dsHo1+/S0zfQ3piyu12J+lso0vrlU1ERESJEp7h+yFqZ4ZvP87wJSIiopTAuIdSWW2vGBRnkf/f//lwzDGVqKzMxN/+9jwWLbo84c9HtYurN4jU+LuRnjQNOP10YM0aAHgQxcVl8Pl8tb7iNlHfvYkrbElERERERERERJTC9EG6wsJCFBX9DlVV16Ndux145hkmmoiIKLlcLmDmTKB/f8DtHovCwmMxY8YM+P3+tCjtmtZl9IiIiBIvUEs/RERERKmGcQ81TD6fD5mZJ6CqagwA4Omn28HlSvJJERERAfjTn4CzzwaCQQ8yMqbB7/fD6/WmfKIJYLKJiIiIiIiIiIgakJKSElRW3gkgE8A7+O9/S5J9SkRERABCq5tmzAhtV1WNRGbmifD7/cb1BlMZy+gRERGZBABU1sIxiYiIiFIN4x5qeELXvXgBLtfn0DTg+uu3o7CwEADSYtY4ERHVf++9VwKgJ4Dzcdllm3HCCSVp8V3FZBMREZFJbZR/4aALERERpSLGPdSw6BdY79z5K3z1lQtDhwLz51+DgoLStBjEIyKi+k//rrr++kexYAGweDGwcWP4eoNA6n5XpW0ZvUceeQQdOnRAdnY2+vTpg08++STZp5QQs2fPxmmnnYamTZuidevWGDJkCLZu3WrqU15ejrFjx6JVq1Zo0qQJLrnkEuzcuTNJZ5w4c+bMgcvlwoQJE4y2+vZaf/rpJ1x55ZVo1aoVcnJy0KVLF6xbt87Yr2kaCgsL0aZNG+Tk5KB///745ptvknjG8QsGg/D5fOjYsSNycnJw3HHHoaSkBJqmGX3S+fWuWrUKF154IQoKCuByubBkyRLTfievbe/evRg+fDiaNWuGFi1aYMyYMTh48GAdvgrn7F5vZWUlJk2ahC5duqBx48YoKCjAiBEj8PPPP5uOkU6vlygV1cfYpyHHPQBjHyC9YwEZY5/6E/sw7iGqP4qKikxlh4LBIP7v/57AV1+dAJerCnl5DwMIDdoVFxcjGAwm61SJiIgAhL6riouLMX/+NbjsMkDTgEsv/Vr5XVVSUoKioqLknawkLZNNzz//PCZOnIhp06Zhw4YN6NatGwYMGIBdu3Yl+9Rq7P3338fYsWPx8ccfY9myZaisrMRf/vIXHDp0yOhzyy234LXXXsOLL76I999/Hz///DMuvvjiJJ51za1duxb//Oc/0bVrV1N7fXqtv/32G/r164fMzEy89dZb2Lx5M+677z60bNnS6HP33Xdj3rx5WLBgAdasWYPGjRtjwIABKC8vT+KZx+euu+7C/Pnz8fDDD2PLli246667cPfdd+Ohhx4y+qTz6z106BC6deuGRx55RLnfyWsbPnw4vvzySyxbtgyvv/46Vq1ahWuvvbauXkJM7F7v4cOHsWHDBvh8PmzYsAGvvPIKtm7dir/+9a+mfunzeitr6YcofvU19mmocQ/A2EeXzrGAjLFP/Yl9GPcw7qH6w+12o7Cw0Eg4TZtWhG++GQ0A0LQnkJf3m9HX5/Ol1IAdERE1TEVFRcbKpRkzgIyMKnz99fEYM2ah6btKXwHldruTeLYSLQ317t1bGzt2rHE/GAxqBQUF2uzZs5N4VrVj165dGgDt/fff1zRN0/bt26dlZmZqL774otFny5YtGgBt9erVyTrNGjlw4IDWqVMnbdmyZdpZZ52ljR8/XtO0+vdaJ02apJ1xxhmW+6uqqrT8/HztnnvuMdr27dunZWVlac8++2xdnGJCXXDBBdrVV19tarv44ou14cOHa5pWv14vAO3VV1817jt5bZs3b9YAaGvXrjX6vPXWW5rL5dJ++umnOjv3eMivV+WTTz7RAGg//PCDpmnp8Xr379+vAdCA1zVgRYJ/XtcAaPv370/2y6Q01VBin4YQ92gaYx9dfYoFNI2xT32NfRj3MO6huqf/+0zUv6Hi4mINgFZcXKy9/bamheaIH9FuvXVuQo5PyXXkyBFt8+bN2pEjR5J9KnVu2rRpWrdu3Wp8nCeffFJr3rx5jY+TCK+++qp23HHHaRkZGUaMTPFpyL8b9c111+nfXR9o06cXa5pm/m5LhER996bdyia/34/169ejf//+RltGRgb69++P1atXJ/HMasf+/fsBALm5uQCA9evXo7Ky0vT6O3fujPbt26ft6x87diwuuOAC02sC6t9rXbp0KXr16oVLL70UrVu3xqmnnorHHnvM2L9t2zaUlpaaXm/z5s3Rp0+ftHy9ffv2xfLly/H1118DAD777DN88MEHOO+88wDUv9crcvLaVq9ejRYtWqBXr15Gn/79+yMjIwNr1qyp83NOtP3798PlcqFFixYA0u31Bmrphyg+DSn2aQhxD8DYR1ffYgHGPg039mHcw7iHUptedqiwcBrOO28DAOD00zfi3nvHJ/nMqCHbvXs3brjhBrRv3x5ZWVnIz8/HgAED8OGHH9bq83bo0AFz5841tV1++eVG/JJs1113HYYOHYodO3aYSmAmU3l5OUaNGoUuXbrA4/FgyJAhyT4lamAKC4GcHADoh2nTPkFWVhYKCwtRXFycctdu8iT7BGL166+/IhgMIi8vz9Sel5eHr776KklnVTuqqqowYcIE9OvXD6eccgoAoLS0FF6v1/hDRpeXl4fS0tIknGXNPPfcc9iwYQPWrl0bsa++vdbvvvsO8+fPx8SJEzF16lSsXbsWN998M7xeL0aOHGm8JtW/7XR8vZMnT0ZZWRk6d+4Mt9uNYDCImTNnYvjw4QBQ716vyMlrKy0tRevWrU37PR4PcnNz0/71l5eXY9KkSRg2bBiaNWsGoH6/XqLa1lBin4YQ9wCMfRj71J/XK2rIsQ/jHqL0EEo4bUYg0APAAfznP39I9ilRA3fJJZfA7/fjqaeewrHHHoudO3di+fLl2LNnT52fS05ODnJCI9lJdfDgQezatQsDBgxAQUFBsk/HEAwGkZOTg5tvvhkvv/xysk+HGqCCAmD8eGDOHMDlmgO//014vd6USzQBaXrNpoZi7Nix2LRpE5577rlkn0qt2LFjB8aPH49FixYhOzs72adT66qqqtCjRw/MmjULp556Kq699lpcc801WLBgQbJPrVa88MILWLRoERYvXowNGzbgqaeewr333ounnnoq2adGtaiyshKXXXYZNE3D/Pnzk306cQog8dct4Axfomjqe9wDMPZh7EP1DeMexj2UPoqKZiAQmFZ97z4sWJAaKyYo8TQNOHQoOT+a5uwc9+3bh//+97+46667cM455+CYY45B7969MWXKFNM1ALdv347BgwejSZMmaNasGS677DLs3LnT8rhnn302JkyYYGobMmQIRo0aZez/4YcfcMstt8DlcsHlcgEAFi5cGDHZaf78+TjuuOPg9Xpxwgkn4N///rdpv8vlwuOPP46LLroIjRo1QqdOnbB06VLb1/3bb79hxIgRaNmyJRo1aoTzzjsP33zzDQBg5cqVaNq0KQDgT3/6E1wuF1auXBlxjL/97W+4/PLLTW2VlZU46qij8PTTT9s+f7waN26M+fPn45prrkF+fn6tPAdRNHfcAWRnH4GmnQy3eyT8fn/KrP4TpV2y6aijjoLb7Y74cN25c2e9+oUfN24cXn/9daxYsQJt27Y12vPz8+H3+7Fv3z5T/3R8/evXr8euXbvQo0cPeDweeDwevP/++5g3bx48Hg/y8vLqzWsFgDZt2uCkk04ytZ144onYvn07ABivqb7827799tsxefJkXHHFFejSpQuuuuoq3HLLLZg9ezaA+vd6RU5eW35+Pnbt2mXaHwgEsHfv3rR9/fqAyw8//IBly5YZs3uB+vl6iepKQ4h9GkLcAzD2ARj7APXn9YoaYuzDuIcakkceeQQdOnRAdnY2+vTpg08++cS2/4svvojOnTsjOzsbXbp0wZtvvllHZ6pWUlKC6dO3AeiMVq2AqVNzUFhYmJKDdFRzhw8DTZok5+fwYWfn2KRJEzRp0gRLlixBRUWFsk9VVRUGDx6MvXv34v3338eyZcvw3XffRSRaYvHKK6+gbdu2KC4uxi+//IJffvlF2e/VV1/F+PHjceutt2LTpk247rrrMHr0aKxYscLUb/r06bjsssvw+eef4/zzz8fw4cOxd+9ey+cfNWoU1q1bh6VLl2L16tXQNA3nn38+Kisr0bdvX2zduhUA8PLLL+OXX35B3759I44xfPhwvPbaazh48KDR9s477+Dw4cO46KKLlM+7fft24z23+pk1a1bU948omR5+uATl5aFJE23bPoHCwpkp+V2Wdskmr9eLnj17Yvny5UZbVVUVli9fjtNPPz2JZ5YYmqZh3LhxePXVV/Hee++hY8eOpv09e/ZEZmam6fVv3boV27dvT7vXf+655+KLL77Axo0bjZ9evXph+PDhxnZ9ea0A0K9fP+OLU/f111/jmGOOAQB07NgR+fn5ptdbVlaGNWvWpOXrPXz4MDIyzB8xbrcbVVVVAOrf6xU5eW2nn3469u3bh/Xr1xt93nvvPVRVVaFPnz51fs41pQ+4fPPNN3j33XfRqlUr0/70er28dgGllvoc+zSkuAdg7AMw9qlPr1fU0GIfxj2MexqS559/HhMnTsS0adOwYcMGdOvWDQMGDIhIqOo++ugjDBs2DGPGjMGnn36KIUOGYMiQIdi0aVMdn3lISUkJCgsLMXr0WejRA5g6FZg5c1L1NZxSb5COGgaPx4OFCxfiqaeeQosWLdCvXz9MnToVn3/+udFn+fLl+OKLL7B48WL07NkTffr0wdNPP433339fWY7ZidzcXLjdbjRt2hT5+fmWEyDuvfdejBo1CjfeeCOOP/54TJw4ERdffDHuvfdeU79Ro0Zh2LBh+P3vf49Zs2bh4MGDlsnob775BkuXLsXjjz+OP/7xj+jWrRsWLVqEn376CUuWLIHX6zVK0Obm5iI/Px9erzfiOAMGDEDjxo3x6quvGm2LFy/GX//6V2NllKygoMAUf6t+rr/+ekfvIVEy6N9lf/97Sxx7LHDJJcBtt01Nye+ytLtmEwBMnDgRI0eORK9evdC7d2/MnTsXhw4dwujRo5N9ajU2duxYLF68GP/5z3/QtGlTo6Z38+bNkZOTg+bNm2PMmDGYOHEicnNz0axZM9x00004/fTT8Yc/pFfN4aZNmxrXZNA1btwYrVq1Mtrry2sFgFtuuQV9+/bFrFmzcNlll+GTTz7Bo48+ikcffRRAaAnyhAkTMGPGDHTq1AkdO3aEz+dDQUFBWl588MILL8TMmTPRvn17nHzyyfj0009x//334+qrrwaQ/q/34MGD+Pbbb43727Ztw8aNG5Gbm4v27dtHfW0nnngiBg4caJQTqqysxLhx43DFFVekVG1ind3rbdOmDYYOHYoNGzbg9ddfRzAYND67cnNz4fV60+z16iVgEn1MovjV19inIcU9AGMfxj7p/XobUuzDuCcRx6T64v7778c111xjxBwLFizAG2+8gSeeeAKTJ0+O6P/ggw9i4MCBuP322wGEBsiWLVuGhx9+OCllVIPBYPUF1Eegqgqozv8b17kIBoN1fk5Uuxo1AoRFL3X+3E5dcskluOCCC/Df//4XH3/8Md566y3cfffdePzxxzFq1Chs2bIF7dq1Q7t27YzHnHTSSWjRogW2bNmC0047rRZeQciWLVtw7bXXmtr69euHBx980NTWtWtXY7tx48Zo1qyZZSJ6y5Yt8Hg8pkkXrVq1wgknnIAtW7Y4PjePx4PLLrsMixYtwlVXXYVDhw7hP//5j20pbo/Hg9///veOn4Mo1YS/y6bA5wP0PGxKfpdpaeqhhx7S2rdvr3m9Xq13797axx9/nOxTSggAyp8nn3zS6HPkyBHtxhtv1Fq2bKk1atRIu+iii7RffvkleSedQGeddZY2fvx44359e62vvfaadsopp2hZWVla586dtUcffdS0v6qqSvP5fFpeXp6WlZWlnXvuudrWrVuTdLY1U1ZWpo0fP15r3769lp2drR177LHanXfeqVVUVBh90vn1rlixQvm7OnLkSE3TnL22PXv2aMOGDdOaNGmiNWvWTBs9erR24MCBJLya6Oxe77Zt2yw/u1asWGEcI9Vf7/79+6vP+98a8HKCf/6tAdD279+f7JdJaaw+xj4NPe7RNMY+6RwLyBj71J/Yh3EP4x4Kqaio0Nxut/bqq6+a2keMGKH99a9/VT6mXbt22gMPPGBqKyws1Lp27Wr5POXl5dr+/fuNnx07dvDfEDl25MgRbfPmzdqRI0eSfSo1NmbMGK19+/aapmnagw8+qHXo0CGiT4sWLbSnnnpK0zRNmzZtmtatWzdj3znnnKPdfPPNpv7nn3++8V2taZp2zDHHRPyOPvnkk1rz5s2N+y1bttQWLlxo6jN37lytY8eOxn0AEZ8NzZs3N8Xxov/85z+ax+PRAoGAqb179+7a9OnTNU3TtN9++y3i+1Tlww8/1Dwej7Zz507tmWee0Vq1aqX5/X7L/j/88IPWuHFj25+ZM2faPqdu5MiR2uDBgx31Tbb69LtBtU+PDWv63evSNKeXryMiIqq/ysrK0Lx5cwBPAIhhSpojhwFcjf3795uu6UBERESUDIx7yImff/4ZRx99ND766CNTuc877rgD77//PtasWRPxGK/Xi6eeegrDhg0z2v7xj39g+vTpEdd10xUVFWH69OkR7fw3RE6Ul5dj27Zt6NixI7Kzs5N9OjVy//33Y9asWfj111+xbNkynHfeedi2bZuxumnz5s04+eSTsXbtWvTq1QtFRUVYsmQJNm7cCAC4/PLLoWkaXnjhBQCh1Q7HHnsszjnnHCxcuBAAcPzxx+O6667DrbfeajzvwoULMWHCBOO6of369cPJJ59srEYHgMsuuwyHDx/G66+/DiC0YvvVV181rc5u0aIF5s6di1GjRkW8tm+++QbHH388PvzwQ+NaTHv27EG7du3w9NNPY+jQodi3bx9atmyJFStW4Oyzz7Z9r4499ljccssteOutt3DMMcdg/vz5ln0DgQC+//572+Pl5uYiNzfXtg8QKh24b98+LFmyJGrfZKtPvxtU+/TYsKbfvWlZRo+IiIiIiIiIiNLflClTMHHiRON+WVmZqXQYUX2zZ88eXHrppbj66qvRtWtXNG3aFOvWrcPdd9+NwYMHAwD69++PLl26YPjw4Zg7dy4CgQBuvPFGnHXWWejVq5fyuH/6058wceJEvPHGGzjuuONw//33GwkkXYcOHbBq1SpcccUVyMrKwlFHHRVxnNtvvx2XXXYZTj31VPTv3x+vvfYaXnnlFbz77rtxv+ZOnTph8ODBuOaaa/DPf/4TTZs2xeTJk3H00UcbrzkWf/vb37BgwQJ8/fXXWLFihW3fRJTR27x5M/x+P/bu3YsDBw4YCb7u3bvX6LhE9Q2TTURERCa1cWFrXiibiIiIUhHjHrJ21FFHwe12R6xI2rlzJ/Lz85WPyc/Pj6k/AGRlZSErK6vmJ0yUJpo0aYI+ffrggQcewP/+9z9UVlaiXbt2uOaaazB16lQAoZVD//nPf3DTTTfhzDPPREZGBgYOHIiHHnrI8rhXX301PvvsM4wYMQIejwe33HILzjnnHFOf4uJiXHfddTjuuONQUVEBVcGrIUOG4MEHH8S9996L8ePHo2PHjnjyySejrjaK5sknn8T48eMxaNAg+P1+nHnmmXjzzTeRmZkZ87GGDx+OmTNn4phjjkG/fv1qdF5OnH/++fjhhx+M+6eeeioAKN8/ooaMZfSIiIgglpN5FLVTTuZalgIhIiKilMC4h5zq06cPevfubQxwV1VVoX379hg3bhwmT54c0f/yyy/H4cOH8dprrxltffv2RdeuXbFgwQJHz5moUj7UMLBUGJEafzcoFiyjR0REVCsCACpr4ZhEREREqYZxD9mbOHEiRo4ciV69eqF3796YO3cuDh06hNGjRwMARowYgaOPPhqzZ88GAIwfPx5nnXUW7rvvPlxwwQV47rnnsG7dOtO1X4iIiKh+YrKJiIiIiIiIiIgiXH755di9ezcKCwtRWlqK7t274+2330ZeXh4AYPv27cjIyDD69+3bF4sXL8bf//53TJ06FZ06dcKSJUtwyimnJOslEBERUR1hsomIiMiE1y4gIiKihoJxD0U3btw4jBs3Trlv5cqVEW2XXnopLr300lo+KyIiIko1TDYRERGZVCLxX4+JLk9DRERElAiMe4iIiIgoMTKidyEiIiIiIiIiIiJKTZqmJfsUiFIKfycoGbiyiYiIyITlZIiIiKihYNxDROnN7XYDAPx+P3JycpJ8NkSp4/DhwwCAzMzMJJ8JNSRMNhEREREREREREVHa8Xg8aNSoEXbv3o3MzExkZLCIEzVsmqbh8OHD2LVrF1q0aGEkZInqApNNREREJgEk/loDnOFLREREqYhxDxGlN5fLhTZt2mDbtm344Ycfkn06RCmjRYsWyM/PT/ZpUAPDZBMRERERERERERGlJa/Xi06dOsHv9yf7VIhSQmZmJlc0UVIw2URERGTCaxcQERFRQ8G4h4jqh4yMDGRnZyf7NIiIGjQWMiUiIkpRjzzyCDp06IDs7Gz06dMHn3zyiW3/F198EZ07d0Z2dja6dOmCN998s47OlGSQiF8AABfhSURBVIiIiKhmGPcQERERpTcmm4iIiEwqa+knNs8//zwmTpyIadOmYcOGDejWrRsGDBiAXbt2Kft/9NFHGDZsGMaMGYNPP/0UQ4YMwZAhQ7Bp06aYn5uIiIgaCsY9RERERJQYLk3TtGSfBBERUbKVlZWhefPmACYDSHT5hXIAc7B//340a9bM0SP69OmD0047DQ8//DAAoKqqCu3atcNNN92EyZMnR/S//PLLcejQIbz++utG2x/+8Ad0794dCxYsSMirICIiovqBcQ+lMv3fZyz/hoiIiCh+ifru5TWbiIiITCpq7ZhlZWWm1qysLGRlZUX09vv9WL9+PaZMmWK0ZWRkoH///li9erXyGVavXo2JEyea2gYMGIAlS5bU8NyJiIio/mLcQ6lHnxMt/xsiIiKi2qF/59Z0XRKTTURERAC8Xi/y8/NRWvpArRy/SZMmaNeunalt2rRpKCoqiuj766+/IhgMIi8vz9Sel5eHr776Snn80tJSZf/S0tKanTgRERHVO4x7KJUdOHAAACL+DREREVHtOnDgQPXq9/gw2URERAQgOzsb27Ztg9/vr5Xja5oGl8tlalPN7iUiIiKqbYx7KJUVFBRgx44daNq0acS/o3RXVlaGdu3aYceOHSwRmAB8PxOL72fi8L1MLL6fiaV6PzVNw4EDB1BQUFCjYzPZREREVC07OxvZ2Ym+bkHsjjrqKLjdbuzcudPUvnPnTuTn5ysfk5+fH1N/IiIiatgY91CqysjIQNu2bZN9GrWqWbNmHDBNIL6ficX3M3H4XiYW38/Ekt/Pmqxo0mXU+AhERESUUF6vFz179sTy5cuNtqqqKixfvhynn3668jGnn366qT8ALFu2zLI/ERERUSpg3ENERERUP3BlExERUQqaOHEiRo4ciV69eqF3796YO3cuDh06hNGjRwMARowYgaOPPhqzZ88GAIwfPx5nnXUW7rvvPlxwwQV47rnnsG7dOjz66KPJfBlEREREUTHuISIiIkp/TDYRERGloMsvvxy7d+9GYWEhSktL0b17d7z99tvGxbC3b9+OjIzwAuW+ffti8eLF+Pvf/46pU6eiU6dOWLJkCU455ZRkvQQiIiIiRxj3UEORlZWFadOm8RpmCcL3M7H4fiYO38vE4vuZWLX5fro0TdMSflQiIiIiIiIiIiIiIiJqEHjNJiIiIiIiIiIiIiIiIoobk01EREREREREREREREQUNyabiIiIiIiIiIiIiIiIKG5MNhEREREREREREREREVHcmGwiIiIiIiIiIiJKgNmzZ+O0005D06ZN0bp1awwZMgRbt2419SkvL8fYsWPRqlUrNGnSBJdccgl27tyZpDNOL3PmzIHL5cKECROMNr6fsfnpp59w5ZVXolWrVsjJyUGXLl2wbt06Y7+maSgsLESbNm2Qk5OD/v3745tvvkniGaemYDAIn8+Hjh07IicnB8cddxxKSkqgaZrRh++ltVWrVuHCCy9EQUEBXC4XlixZYtrv5L3bu3cvhg8fjmbNmqFFixYYM2YMDh48WIevInXYvZ+VlZWYNGkSunTpgsaNG6OgoAAjRozAzz//bDpGIt5PJpuIiIiIiIiIiIgS4P3338fYsWPx8ccfY9myZaisrMRf/vIXHDp0yOhzyy234LXXXsOLL76I999/Hz///DMuvvjiJJ51eli7di3++c9/omvXrqZ2vp/O/fbbb+jXrx8yMzPx1ltvYfPmzbjvvvvQsmVLo8/dd9+NefPmYcGCBVizZg0aN26MAQMGoLy8PIlnnnruuusuzJ8/Hw8//DC2bNmCu+66C3fffTceeughow/fS2uHDh1Ct27d8Mgjjyj3O3nvhg8fji+//BLLli3D66+/jlWrVuHaa6+tq5eQUuzez8OHD2PDhg3w+XzYsGEDXnnlFWzduhV//etfTf0S8X66NDHdSkRERERERERERAmxe/dutG7dGu+//z7OPPNM7N+/H7/73e+wePFiDB06FADw1Vdf4cQTT8Tq1avxhz/8IclnnJoOHjyIHj164B//+AdmzJiB7t27Y+7cuXw/YzR58mR8+OGH+O9//6vcr2kaCgoKcOutt+K2224DAOzfvx95eXlYuHAhrrjiiro83ZQ2aNAg5OXl4V//+pfRdskllyAnJwfPPPMM38sYuFwuvPrqqxgyZAgAZ/8Ot2zZgpNOOglr165Fr169AABvv/02zj//fPz4448oKChI1stJOvn9VFm7di169+6NH374Ae3bt0/Y+8mVTURERERERERERLVg//79AIDc3FwAwPr161FZWYn+/fsbfTp37oz27dtj9erVSTnHdDB27FhccMEFpvcN4PsZq6VLl6JXr1649NJL0bp1a5x66ql47LHHjP3btm1DaWmp6f1s3rw5+vTpw/dT0rdvXyxfvhxff/01AOCzzz7DBx98gPPOOw8A38uacPLerV69Gi1atDASIwDQv39/ZGRkYM2aNXV+zulm//79cLlcaNGiBYDEvZ+eRJ8oERERERERERFRQ1dVVYUJEyagX79+OOWUUwAApaWl8Hq9xgCfLi8vD6WlpUk4y9T33HPPYcOGDVi7dm3EPr6fsfnuu+8wf/58TJw4EVOnTsXatWtx8803w+v1YuTIkcZ7lpeXZ3oc389IkydPRllZGTp37gy3241gMIiZM2di+PDhAMD3sgacvHelpaVo3bq1ab/H40Fubi7f3yjKy8sxadIkDBs2DM2aNQOQuPeTySYiIiIiIiIiIqIEGzt2LDZt2oQPPvgg2aeStnbs2IHx48dj2bJlyM7OTvbppL2qqir06tULs2bNAgCceuqp2LRpExYsWICRI0cm+ezSywsvvIBFixZh8eLFOPnkk7Fx40ZMmDABBQUFfC8pZVVWVuKyyy6DpmmYP39+wo/PMnpEREREREREREQJNG7cOLz++utYsWIF2rZta7Tn5+fD7/dj3759pv47d+5Efn5+HZ9l6lu/fj127dqFHj16wOPxwOPx4P3338e8efPg8XiQl5fH9zMGbdq0wUknnWRqO/HEE7F9+3YAMN6znTt3mvrw/Yx0++23Y/LkybjiiivQpUsXXHXVVbjlllswe/ZsAHwva8LJe5efn49du3aZ9gcCAezdu5fvrwU90fTDDz9g2bJlxqomIHHvJ5NNRERERERERERECaBpGsaNG4dXX30V7733Hjp27Gja37NnT2RmZmL58uVG29atW7F9+3acfvrpdX26Ke/cc8/FF198gY0bNxo/vXr1wvDhw41tvp/O9evXD1u3bjW1ff311zjmmGMAAB07dkR+fr7p/SwrK8OaNWv4fkoOHz6MjAzz0Lrb7UZVVRUAvpc14eS9O/3007Fv3z6sX7/e6PPee++hqqoKffr0qfNzTnV6oumbb77Bu+++i1atWpn2J+r9ZBk9IiIiIiIiIiKiBBg7diwWL16M//znP2jatKlxrYvmzZsjJycHzZs3x5gxYzBx4kTk5uaiWbNmuOmmm3D66afjD3/4Q5LPPvU0bdrUuN6VrnHjxmjVqpXRzvfTuVtuuQV9+/bFrFmzcNlll+GTTz7Bo48+ikcffRQA4HK5MGHCBMyYMQOdOnVCx44d4fP5UFBQgCFDhiT35FPMhRdeiJkzZ6J9+/Y4+eST8emnn+L+++/H1VdfDYDvZTQHDx7Et99+a9zftm0bNm7ciNzcXLRv3z7qe3fiiSdi4MCBuOaaa7BgwQJUVlZi3LhxuOKKK1BQUJCkV5U8du9nmzZtMHToUGzYsAGvv/46gsGg8d2Um5sLr9ebuPdTIyIiIiIiIiIiohoDoPx58sknjT5HjhzRbrzxRq1ly5Zao0aNtIsuukj75ZdfknfSaeass87Sxo8fb9zn+xmb1157TTvllFO0rKwsrXPnztqjjz5q2l9VVaX5fD4tLy9Py8rK0s4991xt69atSTrb1FVWVqaNHz9ea9++vZadna0de+yx2p133qlVVFQYffheWluxYoXys3LkyJGapjl77/bs2aMNGzZMa9KkidasWTNt9OjR2oEDB5LwapLP7v3ctm2b5XfTihUrjGMk4v10aZqmxZ8zIyIiIiIiIiIiIiIiooaM12wiIiIiIiIiIiIiIiKiuDHZRERERERERERERERERHFjsomIiIiIiIiIiIiIiIjixmQTERERERERERERERERxY3JJiIiIiIiIiIiIiIiIoobk01EREREREREREREREQUNyabiIiIiIiIiIiIiIiIKG5MNhEREREREREREREREVHcmGwiIiIiIiIiIiIiikGHDh3gcrmwcOHChB73oosuQk5ODn788ceEHjdR9Nf9/fff1+rzrFy5Ei6XCy6XK2pfvd/KlSsT8tyjRo2K+/9t//790axZM5SWlibkXIjSCZNNREREREREREREREn27rvvYsmSJRg3bhzatm2b7NMhycKFC+FyuTBq1CjLPnPmzMGBAwcwZcqUujsxohTBZBMRERERERERERFRkt1yyy3Izs7G5MmTk30qDdrs2bOxZcsWXHTRRTE/tlevXhg0aBCeeuopfPbZZ7VwdkSpi8kmIiIiIiIiIiIioiRatmwZNm3ahCFDhqBVq1bJPp0GrU2bNujcuTOaN28e1+PHjBkDTdPw4IMPJvjMiFIbk01ERERERERERERESfTwww8DgG2JtkAggCeeeAL9+/fHUUcdhaysLLRt2xb9+/fHQw89pOy/YMEC9O3bF82bN0d2djY6deqEm2++GT/99JPl82zevBmXXnopjjrqKOTk5OCUU07Bvffei2AwaPsaAoEAHn/8cZx99tnIzc1FVlYWOnbsiBtuuAE7duxw9kYkkHh9qRUrVuAvf/kLWrZsiZycHPTo0QNPP/208nGqazZ16NABo0ePBgA89dRTxnWiXC4Xzj77bNPjL7jgAhx11FF49tlnsXfv3tp6eUQpx5PsEyAiIiIiIiIiIiJqqMrLy/HOO+8gMzMTZ555prLP/v37MWjQIHzwwQfIzMxE3759UVBQgNLSUnz++edYvnw5brrpJqN/RUUFBg0ahHfffRfZ2dk455xz0KxZM3z00Ud46KGH8Oyzz+Kdd95Bjx49TM/zwQcfYODAgTh06BCOPfZY/PnPf8avv/6KqVOn4uOPP7Z8DQcOHMBf//pXrFy5Ek2aNEHPnj3xu9/9Dl988QUWLFiAF198EcuWLcOpp56amDctBk888QRmzJiBHj16YODAgfj+++/x8ccfY+TIkdi7dy8mTJgQ9RhDhw7Fxx9/jA8//BDHHXcczjjjDGNf586dTX0zMzNx9tln46WXXsI777yDYcOGJfolEaUkJpuIiIiIiIiIiIiIkuTDDz9ERUUFTjvtNOTk5Cj7XH311fjggw9w6qmn4pVXXkGHDh2MfYFAAG+88Yap/7Rp0/Duu+/iuOOOw7vvvmv0r6ysxA033IB//etfGDp0KL766it4vV4AoaTX3/72Nxw6dAgTJkzAvffeC7fbDQD4/PPPce655+LXX39Vnt/111+PlStXYtCgQfjXv/6F1q1bG/vmzp2LW265BZdffjm2bNliHLOuzJkzB0uXLsWgQYOMtoULF2L06NEoKirCddddZ/m+6+69914sXLgQH374Ic444wzTqieVvn374qWXXsLy5cuZbKIGg2X0iIiIiIiIiIiIiJLk008/BQCceOKJyv2fffYZXnnlFWRnZ+O1114zJZoAwOPxYPDgwcb98vJyPPLIIwCABx54wNQ/MzMT8+bNQ15eHrZt24aXXnrJ2Pfyyy9jx44daNeuHe6++25TUqhr16648847lee3ZcsWPPvssygoKMDixYtNiSYAmDBhAs4//3x88803eOutt6K/IQl20003mRJNQKhUXufOnbF//36sW7cu4c958sknAwA2bNiQ8GMTpSomm4iIiIiIiIiIiIiSZOfOnQCAVq1aKfe//fbbAELXAjr66KOjHm/dunU4ePAgcnNzceGFF0bsb9SoEa644goAwIoVK4z2lStXAgAuu+wyZGZmRjxu5MiRyud78803oWkazjvvPDRt2lTZR7+u0UcffRT1/BNN9R4A4eSe3fWr4qX/v9T/3xI1BCyjR0RERERERERERJQk+/fvBwA0a9ZMuf+HH34AEHltICt68qRjx46WfY477jhTXwD48ccfbR/XsmVLNG/e3Dhf3XfffQcA+Ne//oV//etftue2e/fuKGcf4nK5jG1N00z3RZqmKR8jat++vbJdf7/Ly8sdnVMs9GP/9ttvCT82UapisomIiIiIiIiIiIgoSVq0aAEAKCsrS+6JxKmqqgoA0L17d3Tr1s22b58+fRwds3Hjxsb2oUOH0KRJE2W/gwcPGttWfTIy6r64l56Qa9myZZ0/N1GyMNlERERERERERERElCT6NY727Nmj3K+vzPnqq68cHU8vtbdt2zbLPvpqJLEsn779/fffKx+zb9++iFVNANCuXTsAQL9+/fDwww87Osdo9GMCwLfffovu3bsr+33zzTfKxySb/v8yLy8vyWdCVHd4zSYiIiIiIiIiIiKiJOnRowcAYPPmzcr9AwcOBBC6NtLPP/8c9Xi9evVCkyZNsHfvXixdujRi/5EjR/Dcc88BAM455xyj/ayzzgIAvPDCC6isrIx43NNPP618vvPOOw8AsHTp0oSVpMvLy8PJJ58MAHj55Zct+7300ksAgFNOOcVI2tUWr9cLAAgEAlH7btq0CQDQs2fPWj0nolTCZBMRERERERERERFRkvTt2xdZWVn47LPPcOTIkYj93bt3x+DBg3HkyBEMHjwY27dvN+0PBAKmpFJ2djbGjh0LALj11luNaz4BQGVlJcaPH4/S0lJ07NgRQ4cONfYNHToURx99NLZv344pU6YY5fGAUPJkxowZyvM/9dRTcckll2DHjh24+OKLlSujDh06hEWLFmHnzp3O3hQAkydPBgDcd999eOONNyL2v/baa3jggQdMfWtT27ZtAVgnBUUfffQRAOBPf/pTrZ4TUSphGT0iIiIiIiIiIiKiOJSUlGDBggWW+//xj38YK5esZGdnY8CAAVi6dClWrlxprBQSPfnkkzj//PPx8ccfo1OnTujbty8KCgpQWlqKL774Art374amaUb/6dOnY926dVi+fDlOPPFEnHPOOWjatClWr16N7du3o1WrVnjxxReN1ToAkJOTg0WLFuH888/HfffdhyVLluC0007Dnj17sHLlSlx44YVYv369KXklnt++ffvw1ltv4YQTTkC3bt3QsWNHaJqG77//Hp999hn8fj+2bNniuLTclVdeic8++wz33nsvBg0ahJNPPtlY7fTll1/iyy+/BADcdtttGD58uKNj1sQf/vAHFBQU4NNPP0WPHj3QpUsXZGZm4oQTTsDtt99u9KusrMSqVauM/69EDQWTTURERERERERERERx+O6774zrH6mUlZU5Os64ceOwdOlSLFy4UJlsatmy5f9v745doY8DOI5/bmFikHSKBbPuL3CLETHKIJvFpgwGZVLKLmWQlMly6phInRCd1a1G/8AtPJOnRz3D4zfcqef1mn/9+vRb331/31xfX+fw8DAnJydpNptpNBoZGhpKpVLJ/Pz8l+d7e3tTr9dzcHCQo6Oj3NzcpN1uZ3R0NGtra9nY2PhyX9OnarWau7u7bG1t5erqKmdnZxkbG8v29nbW19czMTHx1/19fX25vLzM6elpjo+P8/j4mGazmf7+/gwPD2dpaSlzc3MZHx//p+/xaXd3NzMzM9nf30+j0fh9gqtcLmdxcTGrq6uZmpr61juL6unpycXFRTY3N3N7e5vn5+e8v7+nWq1+iU21Wi1vb29ZWVnJwMBAR7bBT1D6+DN5AwAAAADQUR8fH5mcnEyr1crr62sGBwe7PYmCZmdnc35+nqenp1QqlW7PgY5xZxMAAAAAQBeVSqXs7e2l3W5nZ2en23Mo6OHhIbVaLcvLy0IT/x0nmwAAAAAAfoCFhYXU6/W0Wq2MjIx0ew7fND09nfv7+7y8vKRcLnd7DnSU2AQAAAAAAEBhfqMHAAAAAABAYWITAAAAAAAAhYlNAAAAAAAAFCY2AQAAAAAAUJjYBAAAAAAAQGFiEwAAAAAAAIWJTQAAAAAAABQmNgEAAAAAAFCY2AQAAAAAAEBhvwBg7H8kpSxeaAAAAABJRU5ErkJggg==", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "PyObject " - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "figure(figsize=(21,6))\n", - "A = ones(size(Ux));\n", - "A = ones(size(Ux));\n", - "χ = CPUprob.params.χ;\n", - "A[χ.==1].=NaN;\n", - "subplot(131)\n", - "title(L\"U_\\theta\\:\\:Analytical\\:\\:Solution\\:(v\\:= 1)\",size=16)\n", - "Lx,nx = 2π,128;\n", - "TA = TCFlowSolution(Lx,nx;R₁ = 0.32*π, R₂ = 0.82π, Ω₁ = 1, Ω₂ = 0)\n", - "TA = (A[:,:,1]).*TA;\n", - "imshow(TA,cmap=\"jet\",vmin=0,vmax=1);colorbar()\n", - "\n", - "\n", - "subplot(132)\n", - "title(L\"U_\\theta\\:\\:Numerical\\:\\:Solution\\:(v\\:= 1)\",size=16)\n", - "Ux,Uy = Array(CPUprob.vars.ux),Array(CPUprob.vars.uy);\n", - "Ur,Uθ = xy_to_polar(Ux,Uy);\n", - "TN = (A.*Uθ)[:,:,1];\n", - "imshow(TN,cmap=\"jet\",vmin=0,vmax=1);colorbar()\n", - "\n", - "\n", - "subplot(133)\n", - "AA = (A.*TA);\n", - "NN = (A.*TN);\n", - "title(L\"U_\\theta\\:Radial\\:profile\",size=16)\n", - "plot(NN[:,64,1],\"kx\",label=\"Numerical Simulation\")\n", - "plot(AA[:,64,1],\"b-\",label=\"Solution of v = 1\")\n", - "xlabel(\"L (code Unit)\",size=16)\n", - "ylabel(L\"U_{\\theta}\",size=16)\n", - "legend()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7e224bcf-6e7c-41c9-a7fe-f449c98f450c", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Julia (8 threads) 1.7.3", - "language": "julia", - "name": "julia-(8-threads)-1.7" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.7.3" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/example/3D_HD_A99TurbulnceDriving.ipynb b/example/3D_HD_A99TurbulnceDriving.ipynb deleted file mode 100644 index 540e1d5..0000000 --- a/example/3D_HD_A99TurbulnceDriving.ipynb +++ /dev/null @@ -1,383 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "compatible-chancellor", - "metadata": {}, - "source": [ - "# 1st Spectrum Test in periodic Cube\n", - "In this notebook, we will test the spectrum of MHDFlows using A99 Turbulence Driving Scheme from [Alvelius\n", - "1999]( https://doi.org/10.1063/1.870050)" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "nervous-while", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: FourierFlows will use 8 threads\n", - "└ @ FourierFlows /home/doraho/.julia/packages/FourierFlows/IWexK/src/FourierFlows.jl:123\n" - ] - } - ], - "source": [ - "using PyPlot\n", - "using CUDA\n", - "using Statistics\n", - "using FFTW\n", - "using LinearAlgebra: mul!, ldiv!\n", - "\n", - "using FourierFlows\n", - "using MHDFlows\n", - "using MHDFlows:GetA99vars_And_function,SetUpFk" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "enclosed-eugene", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "MHDFlows Problem\n", - " │ Funtions\n", - " │ ├──────── B-field: OFF\n", - " ├─────├────── VP Method: OFF\n", - " │ ├──────────── Dye: OFF\n", - " │ └── user function: OFF\n", - " │ \n", - " │ Features \n", - " │ ├─────────── grid: grid (on GPU)\n", - " │ ├───── parameters: params\n", - " │ ├────── variables: vars\n", - " └─────├─── state vector: sol\n", - " ├─────── equation: eqn\n", - " ├────────── clock: clock\n", - " └──── timestepper: RK4TimeStepper" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Declare the problem on CPU/GPU\n", - "dev = GPU();\n", - "T = Float32;\n", - "\n", - "nx,ny,nz = 250,250,250;\n", - "Lx,Ly,Lz = 2π,2π,2π;\n", - "\n", - "Re = 1e4;\n", - "L = Lx;\n", - "U = 1;\n", - "ν = U*L/Re\n", - "η = ν; \n", - "\n", - "A99_var, A99Forcing! = GetA99vars_And_function(dev,nx,ny,nz;T=T)\n", - "\n", - "CPUprob = Problem(dev;\n", - " # Numerical parameters\n", - " nx = nx,\n", - " Lx = Lx,\n", - " # Drag and/or hyper-viscosity for velocity/B-field\n", - " ν = ν,\n", - " nν = 0,\n", - " η = η,\n", - " nη = 0,\n", - " # Declare if turn on magnetic field, VP method, Dye module\n", - " \t B_field = false,\n", - " VP_method = false,\n", - " Dye_Module = false,\n", - " # Timestepper and equation options\n", - " stepper = \"RK4\",\n", - " calcF = A99Forcing!,\n", - " # Float type and dealiasing\n", - " T = T,\n", - " aliased_fraction = 1/3,\n", - " # User defined params/vars\n", - " usr_vars = A99_var,\n", - " usr_params = [],\n", - " usr_func = [])" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "capital-netscape", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ProblemGeneratorA99! (generic function with 1 method)" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "function ProblemGeneratorA99!(prob;P=1,σ² =1,kf=12,L0=2π)\n", - " # Output Setting \n", - " x,y,z = Array(prob.grid.x), Array(prob.grid.y), Array(prob.grid.z);\n", - " nx,ny,nz = prob.grid.nx,prob.grid.ny,prob.grid.nz;\n", - " @devzeros typeof(CPU()) T (nx,ny,nz) ux uy uz bx by bz\n", - "\n", - " SetUpFk(prob; kf = kf, P = P,σ²= σ²)\n", - " for k ∈ 1:nz::Int,j ∈ 1:ny::Int,i ∈ 1:nx::Int\n", - " @simd for kk = 1:5\n", - " nothing;\n", - " end\n", - " end\n", - "\n", - " #Update V + B Conponment to Problem\n", - " SetUpProblemIC!(prob; ux = ux, uy = uy, uz = uz);\n", - "\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "twelve-johns", - "metadata": {}, - "outputs": [], - "source": [ - "ProblemGeneratorA99!(CPUprob; P=2e1,σ² =4, kf=2, L0=2π);" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "usual-region", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.5" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "CPUprob.vars.usr_vars.b = 0.5" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "unlike-short", - "metadata": {}, - "outputs": [], - "source": [ - "function GetU²(prob)\n", - " ux,uy,uz = prob.vars.ux,prob.vars.uy,prob.vars.uz;\n", - " dV = prob.grid.dx*prob.grid.dy*prob.grid.dz;\n", - " U2 = sum(ux.^2 .+ uy.^2 .+ uz.^2)*dV;\n", - " return U2;\n", - "end\n", - "U2 = MHDFlows.Diagnostic(GetU², CPUprob,freq=5);" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "perfect-poker", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "n = 500, t = 5.12, KE = 14.4\n", - "n = 1000, t = 8.53, KE = 19.8\n", - "n = 1500, t = 12.0, KE = 21.4\n", - "n = 2000, t = 15.1, KE = 20.6\n", - "n = 2500, t = 18.2, KE = 20.3\n", - "n = 3000, t = 21.5, KE = 18.6\n", - "n = 3500, t = 25.0, KE = 17.2\n", - "n = 4000, t = 28.4, KE = 18.7\n", - "Total CPU/GPU time run = 2237.474 s, zone update per second = 2.9504530458e7 \n", - "2239.103483 seconds (147.68 M CPU allocations: 12.244 GiB, 0.81% gc time) (433.54 k GPU allocations: 24.253 TiB, 46.33% memmgmt time)\n" - ] - } - ], - "source": [ - "# Set up the initi0l condition\n", - "#CPUprob.clock.t = 0\n", - "@CUDA.time TimeIntegrator!(CPUprob,30.0,10000;\n", - " CFL_Coef = 0.2,\n", - " diags = [U2],\n", - " loop_number = 500);" - ] - }, - { - "cell_type": "markdown", - "id": "european-balloon", - "metadata": {}, - "source": [ - "# Analysis" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "warming-theater", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "PyObject " - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "function imshow_with_sd(A; cmap=\"jet\",Colorbar=true)\n", - " m,σ = mean(A[.~isnan.(A)]),std(A[.~isnan.(A)]);\n", - " imshow(A,vmin=m-2σ,vmax=m+2σ,cmap=cmap);\n", - " Colorbar ? colorbar() : nothing\n", - "end\n", - "\n", - "Ux,Uy,Uz = Array(CPUprob.vars.ux),Array(CPUprob.vars.uy),Array(CPUprob.vars.uz);\n", - "\n", - "figure(figsize=(18,13))\n", - "subplot(231);title(\"U_x\")\n", - "imshow_with_sd(Ux[:,div(nx,2),:]';cmap=\"jet\")\n", - "subplot(232);title(L\"U_y\")\n", - "imshow_with_sd(Uy[:,div(nx,2),:]';cmap=\"jet\")\n", - "subplot(233);title(L\"U_z\")\n", - "imshow_with_sd(Uz[:,div(nx,2),:]';cmap=\"jet\")" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "changing-stuart", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "PyObject Text(35.2, 0.5, '$U^2$')" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "n = U2.i;\n", - "t = U2.t;\n", - "plot(t[2:n],U2.data[2:n],\"r--\")\n", - "semilogy()\n", - "xlabel(\"t\",size=16)\n", - "ylabel(L\"U^2\",size=16)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "perfect-argument", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "PyObject " - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "U2T = Ux.^2 + Uy.^2 + Uz.^2; \n", - "y,x = spectralline(Array(U2T));\n", - "loglog(x,y/y[1],\"ro\",label=L\"V^2\");\n", - "loglog(x[5:20],5*x[5:20].^(-5/3),\"k--\",label=L\"k^{-5/3}\");\n", - "\n", - "ylabel(L\"P_k}\",size=16)\n", - "xlabel(L\"k\",size=16)\n", - "title(L\"Energy Spectrum\",size=16)\n", - "ylim(1e-8,1e1)\n", - "legend()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "bb45e7c8-02ff-4954-a588-999ce1ca4d51", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Julia (8 threads) 1.7.3", - "language": "julia", - "name": "julia-(8-threads)-1.7" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.7.3" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/example/3D_HD_InstabilityExample.ipynb b/example/3D_HD_InstabilityExample.ipynb deleted file mode 100644 index bfbc3ef..0000000 --- a/example/3D_HD_InstabilityExample.ipynb +++ /dev/null @@ -1,723 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "unique-miami", - "metadata": {}, - "source": [ - "# Example for HD Module \n", - "This example aim to show the workflow of HD Solver though analytic example from [Antuono (2020)](https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/triperiodic-fully-threedimensional-analytic-solutions-for-the-navierstokes-equations/0444128148C6D5217F6F78B8C9BB0219) and also explore if MHDflows could resolve turbulence properties." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "promising-silicon", - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "using MHDFlows\n", - "using PyCall,PyPlot\n", - "using FFTW,CUDA,Statistics\n", - "using LinearAlgebra: mul!, ldiv!" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "conceptual-mozambique", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "data": { - "text/plain": [ - "CuDevice(0): NVIDIA GeForce RTX 3080" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "device!(0)\n", - "device()" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "hundred-limitation", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ProblemGeneratorTG! (generic function with 1 method)" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "function ProblemGeneratorTG!(prob,L0,U0;N = prob.grid.nx)\n", - " R = 0;\n", - "\n", - " # Output Setting \n", - " kx,ky,kz = fill(0.0,N,N,N),fill(0.0,N,N,N),fill(0.0,N,N,N);\n", - " \n", - " l = 2*π/L0;\n", - " \n", - " for k ∈ 1:N, j ∈ 1:N, i ∈ 1:N\n", - " kx[i,j,k] = l*prob.grid.x[i];\n", - " ky[i,j,k] = l*prob.grid.y[j];\n", - " kz[i,j,k] = l*prob.grid.z[k];\n", - " end\n", - " \n", - " pfactor = 4/3*sqrt(2/3);\n", - " \n", - " θ1 = asin(-(√(3)+R)/2/√(1+R^2));\n", - " Φ1 = asin((√(3)-R)/2/√(1+R^2));\n", - " ϕ1 = asin(1/(1+R^2));\n", - " \n", - " ux = @. U0*pfactor*(sin(kx+θ1)*cos(ky+Φ1)*sin(kz+ϕ1) - cos(kz+θ1)*sin(kx+Φ1)*sin(ky+ϕ1));\n", - " uy = @. U0*pfactor*(sin(ky+θ1)*cos(kz+Φ1)*sin(kx+ϕ1) - cos(kx+θ1)*sin(ky+Φ1)*sin(kz+ϕ1));\n", - " uz = @. U0*pfactor*(sin(kz+θ1)*cos(kx+Φ1)*sin(ky+ϕ1) - cos(ky+θ1)*sin(kz+Φ1)*sin(kx+ϕ1));\n", - "\n", - " #Update V Conponment to Problem\n", - " SetUpProblemIC!(prob; ux = ux, uy = uy, uz = uz);\n", - " \n", - " return nothing\n", - "end\n" - ] - }, - { - "cell_type": "markdown", - "id": "amazing-american", - "metadata": {}, - "source": [ - "# Re = 50 Case" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "global-ceramic", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "MHDFlows Problem\n", - " │ Funtions\n", - " │ ├──────── B-field: OFF\n", - " ├─────├────── VP Method: OFF\n", - " │ ├──────────── Dye: OFF\n", - " │ └── user function: OFF\n", - " │ \n", - " │ Features \n", - " │ ├─────────── grid: grid (on CPU)\n", - " │ ├───── parameters: params\n", - " │ ├────── variables: vars\n", - " └─────├─── state vector: sol\n", - " ├─────── equation: eqn\n", - " ├────────── clock: clock\n", - " └──── timestepper: RK4TimeStepper" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#Simulation's parameters\n", - "N = 32;\n", - "Lx = 2π;\n", - "Re = 50;\n", - "U0 = 6.5\n", - "ν = 2*π*U0/Re;\n", - "dt = 1/500;\n", - "\n", - "# Testing the problem\n", - "# Declare the problem on GPU\n", - "CPUprob = Problem(CPU();nx = N,\n", - " Lx = Lx,\n", - " ν = ν,\n", - " nν = 1,\n", - " # Timestepper and equation options\n", - " dt = dt,\n", - " stepper = \"RK4\",\n", - " # Float type and dealiasing\n", - " T = Float32);\n", - "CPUprob" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "injured-courtesy", - "metadata": {}, - "outputs": [], - "source": [ - "#function for monitoring the energy\n", - "function KEfoo(prob)\n", - " vx,vy,vz = prob.vars.ux,prob.vars.uy,prob.vars.uz;\n", - " return sum(vx.^2+vy.^2 + vz.^2)\n", - "end\n", - "\n", - "KE = MHDFlows.Diagnostic(KEfoo, CPUprob,freq=10);" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "hairy-bible", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Effective GPU memory usage: 11.07% (1.107 GiB/10.000 GiB)\n", - "Memory pool usage: 0 bytes (0 bytes reserved)Effective GPU memory usage: 11.07% (1.107 GiB/10.000 GiB)\n", - "Memory pool usage: 0 bytes (0 bytes reserved)" - ] - } - ], - "source": [ - "CUDA.memory_status()\n", - "CUDA.reclaim()\n", - "GC.gc(true)\n", - "CUDA.memory_status()" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "parallel-purse", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "n = 100, t = 0.2, KE = 3930.0\n", - "n = 200, t = 0.4, KE = 1480.0\n", - "n = 300, t = 0.6, KE = 554.0\n", - "n = 400, t = 0.8, KE = 208.0\n", - "n = 500, t = 1.0, KE = 78.0\n", - "Total CPU/GPU time run = 160.24 s, zone update per second = 102450.859 \n" - ] - } - ], - "source": [ - "# Set up the initial condition\n", - "ProblemGeneratorTG!(CPUprob,2π,U0);\n", - "TimeIntegrator!(CPUprob,1.0,1000;\n", - " usr_dt = dt,\n", - " diags = [KE],\n", - " loop_number = 100,\n", - " save = false,\n", - " save_loc = \"\",\n", - " filename = \"\",\n", - " dump_dt = 0)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "northern-recommendation", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(0.0, 1.0)" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#Plotting of KE change\n", - "n = KE.i;\n", - "t = KE.t[1:n];\n", - "uu = KE.data[1:n];\n", - "dV = (CPUprob.grid.dx)^3\n", - "uu[1] = U0^2*N^3;\n", - "nn = length(t)\n", - "k² = 1\n", - "v0 = 2*π*U0/Re;\n", - "plt.plot(t[1:nn],uu/uu[1]/2,\"r\",label=L\"(U/U_0)^2\")\n", - "plt.plot(t[1:1:nn],1/2*exp.(-6*v0*k²*(t[1:1:nn].-t[1])),\"kx\",label=L\"e^{-6vk^2t}\")\n", - "plt.title(L\"Re =\"*string(round(Re)),fontsize=15)\n", - "plt.legend(fontsize=15)\n", - "plt.xlabel(\"t [code unit]\",size=16)\n", - "plt.ylabel(\"Energy [code unit]\",size=16)\n", - "plt.grid()\n", - "plt.ylim(0,0.55)\n", - "plt.xlim(0,1.0)" - ] - }, - { - "cell_type": "markdown", - "id": "indirect-graduation", - "metadata": {}, - "source": [ - "# Re = 1000 Case" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "sorted-merit", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "MHDFlows Problem\n", - " │ Funtions\n", - " │ ├──────── B-field: OFF\n", - " ├─────├────── VP Method: OFF\n", - " │ ├──────────── Dye: OFF\n", - " │ └── user function: OFF\n", - " │ \n", - " │ Features \n", - " │ ├─────────── grid: grid (on CPU)\n", - " │ ├───── parameters: params\n", - " │ ├────── variables: vars\n", - " └─────├─── state vector: sol\n", - " ├─────── equation: eqn\n", - " ├────────── clock: clock\n", - " └──── timestepper: RK4TimeStepper" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#Simulation's parameters\n", - "N = 32;\n", - "Lx = 2π;\n", - "Re = 1000;\n", - "U0 = 6.5\n", - "ν = 2*π*U0/Re;\n", - "dt = 1/500;\n", - "\n", - "# Testing the problem\n", - "# Declare the problem on GPU\n", - "CPUprob = Problem(CPU();nx = N,\n", - " Lx = Lx,\n", - " ν = ν,\n", - " nν = 1,\n", - " # Timestepper and equation options\n", - " dt = dt,\n", - " stepper = \"RK4\",\n", - " # Float type and dealiasing\n", - " T = Float32);\n", - "CPUprob" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "judicial-english", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "n = 500, t = 1.0, KE = 8200.0\n", - "n = 1000, t = 2.0, KE = 6420.0\n", - "n = 1500, t = 3.0, KE = 5020.0\n", - "n = 2000, t = 4.0, KE = 3930.0\n", - "n = 2500, t = 5.0, KE = 3080.0\n", - "n = 3000, t = 6.0, KE = 2410.0\n", - "n = 3500, t = 7.0, KE = 1890.0\n", - "n = 4000, t = 8.0, KE = 1480.0\n", - "n = 4500, t = 9.0, KE = 1150.0\n", - "Total CPU/GPU time run = 1457.469 s, zone update per second = 101195.098 \n" - ] - } - ], - "source": [ - "# Set up the initial condition\n", - "ProblemGeneratorTG!(CPUprob,2π,U0);\n", - "KE = Diagnostic(KEfoo, CPUprob,freq=10);\n", - "\n", - "# Set up the initial condition\n", - "TimeIntegrator!(CPUprob,9.0,5000;\n", - " usr_dt = dt,\n", - " diags = [KE],\n", - " loop_number = 500,\n", - " save = false,\n", - " save_loc = \"\",\n", - " filename = \"\",\n", - " dump_dt = 0)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "signed-ambassador", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(0.0, 9.0)" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#Plotting of KE change\n", - "n = KE.i;\n", - "t = KE.t[1:n];\n", - "uu = KE.data[1:n];\n", - "uu[1] = U0^2*N^3;\n", - "nn = length(t)\n", - "k² = 1\n", - "v0 = 2*π*U0/Re;\n", - "plt.plot(t[1:nn],uu[1:nn]/uu[1]/2,\"r\",label=L\"(U/U_0)^2\")\n", - "plt.plot(t[1:10:nn],1/2*exp.(-6*v0*k²*(t[1:10:nn].-t[1])),\"kx\",label=L\"e^{-6vk^2t}\")\n", - "plt.title(L\"Re =\"*string(round(Re)),fontsize=15)\n", - "plt.legend(fontsize=15)\n", - "plt.xlabel(\"t [code unit]\",size=16)\n", - "plt.ylabel(\"Energy [code unit]\",size=16)\n", - "plt.grid()\n", - "plt.ylim(0,0.55)\n", - "plt.xlim(0,9.0)" - ] - }, - { - "cell_type": "markdown", - "id": "hindu-tyler", - "metadata": {}, - "source": [ - "### Diference between MHDFlow and Antuono (2020).\n", - "Instability doesn't arises from our simulation at Re = 1000, but we are always further check if instability happens in higher Re case with higher resolution" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "extensive-postage", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "MHDFlows Problem\n", - " │ Funtions\n", - " │ ├──────── B-field: OFF\n", - " ├─────├────── VP Method: OFF\n", - " │ ├──────────── Dye: OFF\n", - " │ └── user function: OFF\n", - " │ \n", - " │ Features \n", - " │ ├─────────── grid: grid (on GPU)\n", - " │ ├───── parameters: params\n", - " │ ├────── variables: vars\n", - " └─────├─── state vector: sol\n", - " ├─────── equation: eqn\n", - " ├────────── clock: clock\n", - " └──── timestepper: RK4TimeStepper" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#Simulation's parameters\n", - "N = 150;\n", - "Lx = 2π;\n", - "Re = 5000;\n", - "U0 = 6.5\n", - "ν = 2*π*U0/Re;\n", - "dt = 1/500;\n", - "\n", - "# Testing the problem\n", - "# Declare the problem on GPU\n", - "GPUprob = Problem(GPU();nx = N,\n", - " Lx = Lx,\n", - " ν = ν,\n", - " nν = 1,\n", - " # Timestepper and equation options\n", - " dt = dt,\n", - " stepper = \"RK4\",\n", - " # Float type and dealiasing\n", - " T = Float32);\n", - "GPUprob" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "chemical-sacramento", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Effective GPU memory usage: 16.44% (1.644 GiB/10.000 GiB)\n", - "Memory pool usage: 435.679 MiB (512.000 MiB reserved)Effective GPU memory usage: 16.44% (1.644 GiB/10.000 GiB)\n", - "Memory pool usage: 435.679 MiB (512.000 MiB reserved)" - ] - } - ], - "source": [ - "CUDA.memory_status()\n", - "CUDA.reclaim()\n", - "GC.gc(true)\n", - "CUDA.memory_status()" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "professional-suspect", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "n = 500, t = 1.0, KE = 9980.0\n", - "n = 1000, t = 2.0, KE = 9500.0\n", - "n = 1500, t = 3.0, KE = 9050.0\n", - "n = 2000, t = 4.0, KE = 8610.0\n", - "n = 2500, t = 5.0, KE = 8200.0\n", - "n = 3000, t = 6.0, KE = 7780.0\n", - "n = 3500, t = 7.0, KE = 6540.0\n", - "n = 4000, t = 8.0, KE = 2940.0\n", - "n = 4500, t = 9.0, KE = 955.0\n", - "n = 5000, t = 10.0, KE = 433.0\n", - "n = 5500, t = 11.0, KE = 255.0\n", - "n = 6000, t = 12.0, KE = 171.0\n", - "Total CPU/GPU time run = 287.897 s, zone update per second = 7.0349284019e7 \n" - ] - } - ], - "source": [ - "# Set up the initial condition\n", - "ProblemGeneratorTG!(GPUprob,2π,U0);\n", - "KE = Diagnostic(KEfoo, GPUprob,freq=10);\n", - "\n", - "t0 = 8\n", - "# Actaul computation\n", - "TimeIntegrator!(GPUprob,12.0,10000;\n", - " usr_dt = dt,\n", - " diags = [KE],\n", - " loop_number = 500,\n", - " save = false,\n", - " save_loc = \"\",\n", - " filename = \"\",\n", - " dump_dt = 0)" - ] - }, - { - "cell_type": "markdown", - "id": "brazilian-termination", - "metadata": {}, - "source": [ - "From Re~5000 case, we observe the instability behaviour in our solver at t ~ 6.5" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "heard-entry", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(0.0, 8.0)" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#Plotting of KE change\n", - "n = KE.i;\n", - "t = KE.t[1:n];\n", - "uu = KE.data[1:n];\n", - "uu[1] = U0^2*N^3;\n", - "nn = length(t)\n", - "k² = 1\n", - "v0 = 2*π*U0/Re;\n", - "plt.plot(t[1:nn],uu[1:nn]/uu[1]/2,\"r\",label=L\"(U/U_0)^2\")\n", - "plt.plot(t[1:10:nn],1/2*exp.(-6*v0*k²*(t[1:10:nn].-t[1])),\"kx\",label=L\"e^{-6vk^2t}\")\n", - "plt.title(L\"Re =\"*string(round(Re)),fontsize=15)\n", - "plt.legend(fontsize=15)\n", - "plt.xlabel(\"t [code unit]\",size=16)\n", - "plt.ylabel(\"Energy [code unit]\",size=16)\n", - "plt.grid()\n", - "plt.ylim(0,0.55)\n", - "plt.xlim(0,8.0)" - ] - }, - { - "cell_type": "markdown", - "id": "light-cycle", - "metadata": {}, - "source": [ - "To see if the instability caused by turbulence, we check its spectrum and strcuture in below." - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "opened-vampire", - "metadata": {}, - "outputs": [], - "source": [ - "#Spectrun Function\n", - "uxc = Array(GPUprob.vars.ux);\n", - "uyc = Array(GPUprob.vars.uy);\n", - "uzc = Array(GPUprob.vars.uz);\n", - "Ek = uxc.^2 + uyc.^2 + uzc.^2;\n", - "y,x = spectralline(Ek);" - ] - }, - { - "cell_type": "markdown", - "id": "contained-firmware", - "metadata": {}, - "source": [ - "## Conclusion\n", - "One can see the structure of velocity become fully chaotic from its initial state (LHS figure) while a power law relationship can be observed for the energy spectrum (RHS figure). We may safety say the Tri-periodic vortrex settup caused at instability in high Re and a turbulence behaviour is captured by the MHDFlow solver, in particalar both its structure and its powerlaw spectrum.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "announced-version", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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8s802w8svv4wXXngBW2yxRSP/O9/5Tlx77bW4+uqr8c53vtOnP//88zjkkEPwxBNPYMKECTjwwAOx1VZbYXh4GE8//TTuvvtuVFWFhQsXotPpDHQuAPjtb3+LAw44AEuXLsX06dNx4IEHYunSpbj++uux2267YfHixXjooYfw/PPP9/SsvsMOO+Dxxx/HzjvvjN/+9reYMGFCI8+hhx6K3/zmNwCsp+899tgDG2ywAZ577jncc889eOWVVzBp0iSce+65+Iu/+At/HBFh6tSpeO211/DFL34R5557LvbYYw/stttuePrpp3HrrbdCKYXzzz8fp512WnTO0bQbADzzzDM48MAD8dxzz2GDDTbAAQccgM033xzPPPMM7rnnHkyZMiUi7q+99hq23357vPrqq9h///2xyy67QGuNj3zkIzjssMMGvh9XXXUVjjnmGADATjvthJ133hlPP/007rnnHnz5y1/GP/3TP+GNN97AwoULI7P2XmUvXrwYG2+8MdZff30sXLjQz19nPProo5g1axa23357PPbYY633uGAdw+rzw1ZQUFBQUFBQULAu4oorrhjYk/U999zjj3vyyScJAG2zzTatZU+dOpUAZL11v/baa/TlL3+Z9tprL9pggw1oaGiIpk2bRnvvvTeddtppdM0114zoXIxbb72VjjjiCFp//fVpww03pDlz5tDXv/51evzxx6mqKpo9e3bP45cuXUrbbrstAaBf//rXrfkeeOAB+pd/+Rc6/vjjabfddqOpU6dSp9OhqVOn0oEHHkhnnnkmPfXUU43jHn74YQJA22+/PRERff3rX6dddtmFJk6cSJtvvjm9//3vp9tuu631vCNpN4kXXniBPvvZz9LOO+9MEydOpPXXX59mzpxJJ554Iv3kJz9p5L/pppvoHe94B2266ab+/nMM8ZHcj+985zu0xx570HrrrUdbbrkl/dEf/RHdfPPN9MADDxAA2mmnnaL8/cq+/vrrCQC9/e1vz+7/wQ9+QADoj//4j/vWrWDdQVG0CwoKCgoKCgoKClYCPvnJT+KSSy7BRRddhE9+8pOt+f72b/8WZ511Fk4++WRceumlY16P73//+/jABz6Ak046CT/4wQ/GvPyCgoImyhztgoKCgoKCgoKCglGC5+5KvPrqq/jLv/xLXHLJJdh7773xZ3/2Z63H33DDDfjqV7+KGTNm4J//+Z9XSh15fnYvJ2IFBQVjixLeq6CgoKCgoKCgoGAUWLBgAfbff39su+222HXXXbHJJpvgd7/7He666y68/vrrmD17Nq688spo7jJgPXiff/75eOGFF3DVVVdBa40f/OAH2GSTTVZKPfvF+i4oKBh7FEW7oGAtxkknnQSlFE4//fSe+c477zwopbzX04KCgoKCgoL+MMbglFNOwcSJE3HLLbfg8ssvx4MPPogDDjgA3/zmNzFv3jxMnz69cdwvfvELfPvb38b111+PQw45BL/85S97xtle0Treeeed0FqP2MN7QUHB6FEU7YKCtRj9YkKm+UpIioKCgoKCgsExY8YMfPOb3xzxcZ///Ofx+c9/fiXUqAmtNRYvXrxKzlVQUBBQFO2CgrUUCxcuxOOPPw6gEO2CgoKCgoKCgoKCVYlCtAsK1lLceeedICJstNFGmDVrVmu+xYsX4+GHHwZQiHZBQUFBQUFBQUHBWKCYjhcUrKW44447AAD77LMPlFKt+ZiQb7DBBth5551XVfUKCgoKesIYg+eeew6TJ0/u+Q0rKCgoKChYVSAiLF68GDNmzIDWvTXrQrQLCtZSMNHup1Kz2fjee+/d94NRUFBQsKrw3HPPYZtttlnd1SgoKCgoKGjgmWeewdZbb90zTyHaBQVrKZhol/nZBQUF4xGTJ08GYDszG2200QqXNzw8jKuvvhrvete7MDQ0tMLlFRSsbpRnumBtxJr+XC9atAjbbLON/x/VC4VoFxSshViyZAkeeughAIMr2oVoFxQUrElgc/GNNtpozIj2+uuvj4022miN7LwVFIwU5ZkuWBsxXp7rQaY0FTvRgoK1EHfddReMMZgyZQp23HHH1nzFEVpBQUFBQUFBQUHB2KMQ7YKCtRB33nknADvvuteI2x133AFjDDbYYAPssssuq6p6BQUFBQUFBQUFBWs1CtEuKFgL8dvf/hYAsOuuu/bMd/311wMADjnkkMgR2h133AGtNS6++GKf9uabb+KAAw7Avvvui9dff30l1LqgoKCgoKCgoKBg7UAh2gUFayFefPFFAMB6663XmoeI8P3vfx8AcPzxx0f79tlnH5xwwgk455xzsHz5chhj8IEPfAAvvvgirrzySmy44YYrr/IFBQUFBQUFBQUF4xzFGVpBwVqILbbYAoCdq92GSy+9FA8++CA22WQTfOhDH2rs/9u//VvsscceuPTSS/HAAw/ghhtuwE033YRp06atrGoXFBQUFBQUFBQUrBUoinZBwVqI973vfQCAX/3qV/jGN74BY4zf1+128c1vfhOnnnoqAODrX/961qPvbrvthj/90z/F5z73OXzzm9/Ef/zHf5R53AUFBQUFBQUFBQUDoBDtgoK1EMcccww+8YlPAABOO+00bLPNNjj88MNx2GGHYYsttsAnPvEJGGPw9a9/HR/84Adby5k1axbeeOMNfPzjH8fb3va2VVX9goKCgoKCgoKCgnGNQrQLCtZSXHzxxfj3f/93HHXUUVi2bBl+85vf4M4778Rb3vIWnH766bj33ntx2mmntR5/+eWX4+yzz8acOXPwve99D4sXL16FtS8oKCgoKCgoKCgYvyhztAsK1mKccMIJOOGEE0Z83I033ogPfehD+Lu/+zucfPLJ2H777fG1r30NX/nKV1ZCLQsKCgoKCgoKCgrWLhRFu6CgIMKDDz6I97znPfjwhz+MM844A9OmTcMnP/lJnHfeeXjllVdWd/UKCgoKCgoKCgoK1ngUol1QUODxwgsv4JhjjsFBBx2ECy64wKd/8YtfxPDwMM4999zVWLuCgoKCgoKCgoKC8YFiOl5QUOCx5ZZb4oknnsimL1myZDXUqKCgoKCgoKCgoGD8oSjaBQUFBQUFBQUFBQUFBQVjiEK0CwoKCgoKCtZq1IYw94lXMP/3CnOfeAW1odVdpYKCgoKCtRyrlWhfcMEF2G677TBp0iQccMABmDdv3uqsTkFBQUFBQcFahqvufR5vO/dX+OClt+P/PVLhg5fejred+ytcde/zq7tqBQUFBQVrMVYb0f7hD3+I008/HWeddRbuuOMOzJ49G0cddRRefPHF1VWlgoKCgoKCgrUIV937PD713Tvw/MKlUfqChUvxqe/eUch2QUFBQcFKw2pzhnbeeefhlFNOwcknnwwAuPjii3HllVfi0ksvxZe+9KWexxpj8Nxzz2Hy5MlQSq2K6hYUFBQUFPQEEWHx4sWYMWMGtC4zs1Y3akM4++f3I2ckTgAUgLN/fj/euds0VLr0JQoKCgoKxharhWgvX74c8+fPxxlnnOHTtNY48sgjccsttzTyL1u2DMuWLfPbzz77LHbbbbdVUteCgoKCgoKR4JlnnsHWW2+9uquxzmPeE680lGwJAvD8wqWY98QrOGiHTVddxQoKCgoK1gmsFqL9+9//HnVdY8stt4zSt9xySzz44ION/Oeccw7OPvvsRvqMc8+A3mCiHZZWABRBaTt2rRQBClCc7o6x6ZyHEwdwikJhtJsonx5BnkMRlAK05qVBRxsoRag0oaNrKABDVY2ONtAgVNqgcteiQdDKAAAMWZXEQMGQAhFQG40uaRhSqI1dEgBjNAwUiBQMAeTqarfdutsmVxYAGOPWXRoZ7Y+z6a4sUiCjAOPaoVauQEDVCsoot454nQAYmwcEKGPTAUDXbt0fZ28tDKAMQbn8/jwGPk0ZsmlcPgGqJr9PD9v92hBUl6CI8xNgAKoU+EExlQJVCqTcsgJIu6VCSFMKpgNQx6abjsjTgTvO/RQAXipeZp49d2+Uu8bokeLr5vTcfmT2p+m5Y5O07P40vVH3ZFuJZF537QEF23auvcwQgA6BNKeTbS9N4US8lG1jVKhHrg1y8NebtDUl18T5kusgFis1+WshZetr94uCeF0T4L4Bdhm+B0rbm1pV5L4ThI77BlTKoNIGWtnvAn8j+PsBAB1l/DcCAHTm4o34VsnvSLpfft9M9N0TeTPHxWWoaJu/SXIfkfLlyLIllArfwDRNJdcoy63d9dVGoeu+X3WtUdf2xTO1hnHfJDI6fMeMsj97kfY8pJrPNRDuuVuHAszSpXjuS/+AyZMnZ6+nYNXixcXtJHs0+QoKCgoKCkaCcRFH+4wzzsDpp5/utxctWoRtttkGer1J0JMmhY6sJNq6hWhr23tikp121qQlOmU6V2mHMJdHlq0UL20HWiv761RMtA0mVtp1rDWGtGWcHW3QUbXPL6fTc+e1ayq7JI2u0b7j6tdJoZYdXVJ+adMsGef9vI9kuiDdhsk1wXZMeenW4TqxTLRRK0d2YckQk2TD5Drs9+TaBDLORDsQdIrItS/HH0eCdNubo+V9ILJkXQOaXC+aiTYsaSZtybbqhHVJtE1lb7Cp4NNUFYi2ckRbkkgowN0qS8rcrWTCbR8W+VCFZUSAJYHsQZJHQrKzBDp5pttIdmOfzCavR4lrVTHRhmg7TCBQx6arIQIqewJVCULjz6vi+lI4aa/6pulKHJtr6/iktsqk4Qfy/P1U9rli8qX4dfXkW5Bt2O+TEgTcf4cq475nBKoMarhrrwyMIpA2vi062qB23wejyJNR+U3rR7iB5jdNIRBp1ZKPL8+Qihx9qIRga7euRH5ZlhJl+rRMneV1yP0R+fffMqCuqzCIWLvvoVagyo50Ua3898oOCiJ8u/h7lj4HpOKHSz7TfH/5uSpTmtYIbDF50pjmKygoKCgoGAlWC9HebLPNUFUVXnjhhSj9hRdewLRp0xr5J06ciIkTJ/YulJCR1wZHrl/EaZJMK0VR566tPyVVF0m4ZRqTaL8O8h1KuQ6EjqYhZTvWpKCVgSHtyzFwohmvu2P9MQAqRahdh1RDBQJDyteP3HquA06KIhalpNgjOpp2O84bFTRSpGWnSMkVUTvh4rAuaXm5ejExFDeaL4kG6UwLQsf9dHLPqqKgkLYpyel2P+OLrDLdo06t5xzwfG0GHaGA9vVY2XfrCOtMTj2JiapLUFDZ543rpNq+CZzOxypRokyLym6vv2ykqK6Zemfr4tRefueCZYn272RtlPvWaMANFsLYd5+YaCfqrwb5gbY2mJYKpmS8X3pEeFvW+yFHsPudS57DiHZjkm2McoOFKijXhKBcuwG7VpKd1j96uDgNK/S/p2DlYc7MqZg+ZRIWLFzaNnaGaVMmYc7Mqau6agUFBQUF6wBWC9GeMGEC9t13X1x33XV473vfC8A6OLvuuutw6qmnDl7QYP0yj0B089vtx43sxJJUa28iSqhUMPf0pqCCcHOahjUn77gONZNuJswAYJRyKrRNhw6qNAwAZZVuRQrapfvL0Map30ClbQeVy7dm7oFl2GtXIATSzFYCxEQnbR9BSpiMKM7vjxdlcB5xLLl8pELxpBRU0vb9iac1He+X15NmT6CUW1fJtYR8cQHuGogCcXKddXL7uVWVEe3Cx7ZWLCwHItFjjFTEi0y3U+Q4iQr7IvN5t86KMLEJdrIuVcNG3ZhsR3UgX7csx3MPFJNwngqhciXKa/XPhVCy5TUqBHNxkc/XKVMPP4DnRl4IlkPXZBVRIvu9IE3+NTOGUDunTZWOB+r4dLkBulWBlFQPQrL9d2eEZQPwU2J4vXYE2xjtyXVdK6t0kwIZOHUbVs2WFjgp6UZ4fyPwtyCSrwFF/I3seykFqxCVVjjruN3wqe/ekR07A4CzjtutOEIrKCgoKFgpWG2m46effjo+/OEPY7/99sOcOXNw/vnnY8mSJd4L+cDo0bGRnKhNLWkzIe+N5j9leTwr2ICbfwnbodRuzqUk2ENVjSFtTcSlubhdd0RbGatEJ3MsjWNqXdLQjnB3qfKdV0XkzcmlaTiMtuatrnOqoWwP383vVl4KlKRbCcWQAEd6A5lSgWC4PP5YT1btOhGcTamjF0xquRhBbFkx94MdqRqJsM4dY0VodJLZPDzPeZRfWiKoHAkMZDvMw83efl92RKoliaO46p7oCSIaVyouN00bZJ9MXxGS3iDbQJ5Up/tEezHBBhDNWacKMH4uNkAVk2xLMHPnkmnkGt2bIPdTF930A1K20vzoEvsCUOSnSkTnEsTZm74DzoQEQcmW9zNtk7Z77J8bBaOZtAFEBkopGEPQjghoTVBO6e7W8ETbkm13Kh7kazG3Tvel6Ec52o7NkuG2cwiLmbS8XsRbTnth3xK1W1r12hLpuutMx40zE4/MxWGnsiTk2n8zKPO88/ndfVTkvg/o8YwWrBE4evfpuOiD++Dsn98fOUabNmUSzjpuNxy9+/TVWLuCgoKCgrUZq41on3TSSXjppZfwla98BQsWLMBee+2Fq666quEgbayRzp8eXRk9OqmZzq3OdITD3OsAVq5Z1bbHWpINwC8trHF4bEpO0ERRp4/NyQ2C+bjMTy4tNgcPnWBeV4q8uuxNNxtkImE5CeHKkTVPosVhXsUW6d7sWhD8Me3b8rkcyc4qqKIuEYFsA/lxh0C++VyZvCsF7qS+/dNBih7HSGTvHzLXnw4cZAi5bD/IdkzTM8f3Rb/ri8oT5uL8LPKxmYttDIqwuq2omY44Ty8QOUsNR/6J1WlWSSHNyQGt7TFaG+83gd9lwL5PWgE1hekgnIdRi/dbQivqa6wwqDn4aB9pOU0mKq8HybZEWzv/EiqQbPez3vZUcHRG8qeC1YuRJxTrhUiPaxy9+3S8c7dpuOXRF3H1b+biXW8/AAftuEVRsgsKCgoKVipWqzO0U089dWSm4jnkOuRRR70pDebI8MgU7Uw1IgJPvhqV8y6uFZwncePTtSJ0lPMirIK5OJuOM7FO52vbNAXjVG5DWvpKs+o1tDAvV4AJ8zEp6cjaTrrt4GvIDrrt4CuFYObqlHCINKs6O7ZiGQK8is0kLyVQCOuRGTUTLrGuZP6Rdn4TZTtCCwn0dVfwXsMh03uVkzuXqAM3jyff/RTYQTEAoU73+fGStA4tderJr5J7Ga0zuZaKtncSR36dWB32TsK47BaGr+QmE8p83aOq8oXYESZblOF3A5GiGZFrvi5hIh6ZiwPe2ZlXwVtgx8P4IDkNw747BFiHak51J2MrxQo3AGitxPer+S1TaFe1wyAgorSaL2OUangvpMQ55wcizZuSawA+sgJgPYmzmbhxTs+8iTh7Ek+dNHpF29XDRzFwgw+Z94bvjXytrDEFv0woZHwNR6UVDpg5FS8/QDhg5tRCsgsKCgoKVjrGhdfxQZEqoxGxVtIDOEJ6tBz0PPmOZtrB5fnYrGBX2niTcRnGi0PzMPEGrHqdmo4DQYnSynodZ4/DHIomzNWmiHDb5lCOoAdPwVKxBuySTVdj1V95wq0U02rL3Ij3ZUh0qmozcfYOwWzFPLmIyDXfT6k4qlhdbVW2BVnK7lYq8jbuG9WZj9uwXvBztHNKbKsZOXMtYkIF3xeP6qZEJz5tt5Yym9eRJwYR2Q58Lt4n0vzpR0gYUpU3ahNJruV6hUCo03nbkmxzhXIDGUpUPPfctVaYB4UApZUfBCFty/P3JXNPfJ1kOK+UZPtrp6gdetcpPASecPO1+udeeaLH3xlj4m9ZdrCv7VvHVW4ZdKyhGqbonD9SyjPljATSAWMbmGS3zcEmjrJQK4AV7C7fWyXIdSDaypFtAEHFbrkE/3+FFEgTrxYUFBQUFBQU9MRaRbQZkXIzYF5JskeibufOJedNRttinePgWlNxE5mSa2WypuMAIsLtO7cEH0NXC+bZZuLJJuRsTsrrOZPx5rWqmIQAedJDcCawKuxXiIj5oJDzIsca0glahMZ2yJdt1rHqeK+IMpaS9jSNxTfZlskxkcrdVsWWtsqS7jR/bl8ygOHz5SqRu8aRQNSFEKwzuMzGQARCekNB93VOKpQODrRAWoSERuJEsamCAi69/iuEQYP0RofBs0Bk7UCZ8gOPQPyN4FB4nMc6SUT0TQh1j8m2tI7JYSTex6WaLc3ECbyO2JO4U7E9yeZ42IBbt82ghIrN4QYb1iYC2StxDwgPohUVu6CgoKCgoKAN45top53yRMnx6k+iZsuQW0DcgWzE1e5ThTZFqHLqF5uIKwBDVYiLnTUdV8Y6RhOm45JwR+eFtko2gGFTYYglbS0cpWlEXsm7RruZ3WGOdhr+h8k/q1bSA3mYm+1Ub6dEc1qDPStHZpxKrHyDurwatoOshaokCFjqdbxBxHqhhZDJeniP5xCKNauVLqSXd9qVEMJU6eYymicMS66S50ptHfVcesLD0mvqlS17ipSA86ognG1os1ygXutp21aUXfeOxZKyw8nldh/G3Xo/lN/v1W2lfHwokkVH35iMip0S7rbns8fIRRQ+0D+QzXa2yrYYDJHvnqySJ9IqMSkP+3Np9rqVHxAEXAADzk/KD0zxdvr9GwmhzoEdNkoVm9NrZxouPYmbro2TDYJTsVWsXBsFVSOo20y6XRtDLhPIz5nPUoh1QUFBQUFBwYAY30QbaFe9UtKdIdnZudqimH7mkOnxqbMzDumlxa+j7JxtORe74xTtIbcOwJNsVrubMGBb3CFdY9hUdh0Gw7b26MCg64zENQXFvCZhAgqeo23naXO4HM8DvbwXeyD3fIc7/swgA5tu3A8mtgox4eUy5LZXXiUhHaGSGZUpj7WeoiKSbevJ5FkJ8iTTEe/vW4FmUzC8yJ8Sqn7oQbgBQcKSaqSH+42kHModmKtfo+0yxFAheBpXsCbjQAjf5faHdRJENlGFpVVEr3plLzTdR554QdvyCGRNyfm6E8Icx8dG+O5osS4JOET6CBBZi5Cw/JADILKa/H4m6UyYw3snBxYDSefvoVWolSfcsok1EFRuHviDioi1TqxhRgMZD9s7OHNpda0d0QZMXVkzcQKoq+0cbJMQ7K7y5uERuZah/qK2RnLvEnLNzdymZBcCXlBQUFBQUJBgfBNt3/GlMI+OyRnkvvxcRt6WRaWkdlAP41oQdxnbln8qWUoSHce9lbGzA8muECva1lOSSyPtjzNUOfNyA+NCfYWynZINgkFznmV0Xa6j3nb1vRwZ2QyCGLWAFTrOzzGMI9PmXhikc9snD4UbHxFFH+oLsaItj4tIT0LMVggjva4eKrdKSEGateepWnb2MgUHEEJfSfItCamIjx2ZjKc/f46k1j0fzB7H+UpxvvgZ9eq2KCRS18Wzml/vd+6RIzIvtxWCv3iFQG4jI3Ll3if4G2CPkvQ5N1oRPyxMutn6xdZHmJUjEOtcnsGuj8m18uuSZEem4t5cHMFMnEk2OZLtTMIVh+wyglQTYoKdVjFtHjnIUYh0QUFBQUFBwQgxzok2BWItCTWTWp0q2omq7YphAuyLTQh047QJeZXpbCbuCbI2keOzYC5eN8zFtSIMOcLc0bUn15KMewUJNQwUaheQeshXKDhJ43UoR+BJWyUbgXQDjkPwIACUV7xN1GGO42sTwpxuxaoZF+bln7Dq09mjsnLrYr8N2xViG0sSp8SyjWg18kX7LPlQTElyBFs5gl2F83MsbSaFpMV1pgRcLlOyOCgyxHXQY3LcppGk2vf34kat9ZH15XVJtL2ncWrE0fYqtiPhwYO3WEbnEvJ/Wh9JiJO6JVfiSZe9oeSTuexsgKucop2SbwhC3AMNHwcD3Gzp9d+TZ3Fukg99i8rtva0rEubnoRxWtIMvhjCfW4YRY+TU7UHJtiTYAFAziaY4Lna3WzmirWG6OqjYzkxc1QqobRvqLhKibX9e0Rb3OPuu8H3l8RcS6b4RxQHiOWhMKSgoKFijcOGFF+LSSy/FnDlz/G+XXXaB1rr/wQUFBQWjxPgm2kDc6QXAnnn9bk+wmyRb+84xtZLrXGcxNy9bq5i4M3lnks0knD2Mc3pQt63pOCvTFYKanarSEchAqtsVlJ+7DUeYeWlIDCoIk8+2sDu5Odwhk+yNho6/r12qCuW20bKuRFZ5XC+RPCWQoqOchVZ+Tq6vfELu2xRt3o5U7FF2sHPqcAODlE3I8rXWQ3uo4D0h8qSDDGl7MHGhaJsHLFwZrHT7wYmEbKd1VpkLbVOd0SS+lrC6e00UnGb5E4iLkw9Qo37hPKkFTRaizlG4vDak+z3ZUyKLu8ZIeoUf9EpV7hACLQ4sFt5faaVCYOdpfF1+T4ZEB6U7JttcrszHkE7PpIod4mHroGLX9gdSkYqNGsFcvFbWfBwQ87LhQ7dFajY3l/zWp20nvjvRt60NhWgXFKyxuOmmmzB//nzMnz8fF110EQBg8uTJ2G+//TBnzhx84QtfwNSpU1dzLQsKCtY2jG+izR1fse37OQ1y3STZ0nlZWyib6HTJtifqyTYr1wC8kg0gCuMVk2vynsYluW41G/cVYrZiyTabhWtlYEijcuQ61Neak3O9WN1uXCMJtRrwCjQTip4m47JBHEgJ7865fKJDOyikup0KTbJ8UgrQZFWtcDGW6bCaLZgSCbNmsPm4CmWlJuSSYBKfLzNwkBsIaOuUt+7r1ewt7RepcQOU1ar05Y7NkW5BsIGUUMsfJdvIttNAlYwIviDYmYvxFg18AIfsMuK+kThWEvcRnKe1zkKNzqnU/vwpRJVDmh0M4Fj3YdK/zWffX6e4kiPkSjg9a5BleHKtZLlw73yLai29k6dk2x8rkPMqzqG7WMkOP+3jYvt42EZF5Fo5RRvSTNyvq5hgp20r29Xd4tznLTpMvPMjem4LCgpWG8455xy85z3vwbx58zBv3jzMnz8fixcvxn//93/jhhtuwJe//GWf91vf+hZefPFFzJkzB/vttx823njj1VfxgoKCcY3xTbS1I9DO5FS5mNVQBK3tjwmi1sHJmDeTFuRaqttAolqnp82QcVkGOzwD4D2Ke8dnwgkax8qWnsaHVO3L5fVKNYl2TdZld6WAWmlosvOuh2FV7UrVMLVyCrmO5mfnrsX2SbmT7HyFJaTbt0eGeCkEZ2fBXFwQCEFGfWdWkGW/LyFvcn9fMOlm8pyRDT0X8R3lQJ7ZTJwJNSuv7IEcKiGOGRPplHjnyGi0RPO4tOM+kNLMx60gBhrrSIh2qDfF1yyuNbpu4QwtxNImQb6p0QbZwZhexFchJpKeRIub79Ybzq2y50gU8pSIAw3iak+REGipKucf0d5I68akVarbA5BtrpsSx3IDp2QbaIbySkOByevt5X2cyTWvZ2Njd+2gIRkFM+zc/neVI9qwjs6cszNVC2dnTsVWrGJT2G60nYQSu9Lvg3w2+JuQvt/+J09WUFCwJmHbbbfFtttuiz/+4z8GAHS7XTzwwAOYN28efve732GDDTbweb/1rW9h7ty5fnvnnXeOTM73339/qEZHqKCgoKCJ8U20AdGpZlLG6nXo+EqHZ3Fom0Cq+xHsNnIt03Kku+H4zCnJkVdxt5Rzsnm9Es7RGAbKpQdF26AK5TvSbctx8o7bz+bjHIc7VbRlaC9pPi5DffmYvHBhvuS9yLG9lCD1w0jzQ5DyNM2TO/gQYraWguVEpFbxgxIXmBJhcY7GsZxHdMijTnmKQUn2mvB/vTFwQGGd92eIiONrWSUw9ujdvCd+O0eAZVJKslVzv733PLgUiCVIkF4msPJb0FK/fk6/okGqzHM9KrLNyLxuEZmW+6N1a0be9jilynZIb593zap2a1UT4p3GxmYF2ztB8zGxw0+xZ3HvSVz5ONmWXCMo2AZNgp2rOt8aJtd+QKfPR0g8+wUFBeMPnU4He+yxB/bYY4/Gvg996EOYOXMm5s6diyeeeAIPPfQQHnroIXznO9/BNttsg6efftrnve6667D11ltj1qxZZb53QUFBA+OaaDOJSp2hpXOy5ZxpVrKlF3CgOcdaLu25mkQ7yotQVkeYjndUiJ2dhvHSylhVWzdVbFa5GVLVruAUbZ+mfd6KDIxSQmIN9ZQqk5ynDYRBCN+ZzpiPjwlU8C4ep/fZziBHrnulN+uSOEJjlVUqVyoo3JEyq6VCKxRvmaeNYLeQ9qh8JPszFzSw0j1WSIhF4xp6EOzQFhS1M3K/9HyJVUTYH/L5bwA7VIMg3vIQT6LgFO2wGmdNGbEsIz8YEFljRGK6IKuS+cobmLyPDchBgOx+1bjWUJdAkKU5+EgQnB7aKuRUbVaqdVJJqWDLkF2GArmuazsf25CyTs+YaEunZ17FhoiTDeH4TPlPoiLRZvJeJI9Ua7vKe5w+k8nzmvVMX1BQMG7x6U9/Gp/+9KcBAC+99BJuu+023HbbbZg3bx622morn4+IcNJJJ+Hll1/GlClT/Hxv/s2YMWN1XUJBQcEagnFNtKHJm4sr18lmc3FrOm6gYOdM5wi29BDeZjoekWrEedJ8knQzeZZOzyLv4hlz8SFVY4hJNwiVU7sBS7RrQZ61cl7HBeE2pGAUm4e7+eCOdXrHa8pAi/nc1tN4mDfJJDv1FSYRvI/ndop9CmBCYRU0SSzgSTcw+v6pJNXWYzmJdOcAyqVH+0U9pCfxiCTq5jIi435dZc3I20h3RO5TAo+w7cvwdW3ekFZuNtYd/n5EX16TTBMEOxqkcIQ48jQuSLJ0MuZNmyNimuTTgexwtAGtGuw5KocVVVdMX2V5IKdnaV73gAbjiVhNt2lsvk7hgW4rPn312l7FHsR7RRGJ42JAjlEnp03JdQjZpVG7edfG6BAbe1gHFbvrCHWtoLpwpBshbBcr3FLFFiS7rQn6jWs0D4h/YZDNPbOawq+goGCtweabb45jjz0Wxx57bGPfwoULseuuu2L+/PlYuHAhrrvuOlx33XV+/4knnojLL7/cb7/++uvYcMMNV0m9CwoK1gyMa6KtEFTroGiLn8jLXCpHsn15LSS7H8HmJefzsbAVxQS3sW6i8iIHagnJlksAnnRXLmwXh+ziDiabp3dH0J5tHshHJZ3K43oRh7HCIFXkerQRRKlKJ2ikSfVKkOKULPdtuly52XxCFR34mD7nHiGy15K0QZoem9ZnjstBkOzs+SQ7FkvpsE9F6XERYT5zqFRjIKhH3dLq5BAGG9g6pD+RX5Mw0ljYveanGzGgwWbigI2NDSbeTpUmlwYxxxrCZBxiXMbPxxbrOfXanlis93z2Rve5y1pkFBQUrNXYeOON8Zvf/Abdbhf33Xcf5s2bh7lz52LevHm47777sMMOO/i8r776KjbbbLPGfO8999wTEyZMWI1XUVBQsDIxvom2hleyg4odiDR7+660XDeRii3JtSTLPZXthIBHxDoph52eSQdoft2F8Bpy5uWVMsEZGpPtjCM0hjQhN66HN6TqiCxL8p1eD4fu4vbi7TCHG1FM7d43o/fumORSk/30QqqQKQWVYy3KKoU8P5eAMEcbQdW2WcmXFanWyh4k1epWRVuEBMvGjpYKmEZEwhtKtuikewUYaCenbQQ2l7dX2goiuguZgYeGCW56vZxHrKcm30yAic2txX4/fURLsm1Zl9YxYU+VV6KwTYSoIXt51h+EgPLRRCGsVrCnsM+fNCPPXmNKDnsYkqwqSBPy6JuQaS9y+VnBlnOx4VRuqt3+rnbzrRVQu/nYNfJOzwzgPpN+3rY/oVxKpIMtfQZ9clM/SPzsFAjB+tkioyjaBasYtSHMe+IVvLh4KbaYPAlzZk5F1cthQsGYo9PpYPbs2Zg9ezZOOeUUAFa9XrZsmc9z9913wxiDBx54AA888AAuu+wyAMCECROw99574zOf+Qz+5E/+ZLXUv6CgYOVhfBNtRVDatJqLV67TY9eD13GpavsQWglZ5nVGjlSny5CH/PxraUY+JMJ7eXKN4HU8ItrKOEdmyJJtA0IN61V82HQwpGrUpH39Zagv9jquEULvGNdhTkl06gwtbe++ob16IGs+zu6pVEMsHAyOUEOxihk6xwrJeuQQTYXjU5LNHWof/gtNM3JhLu4JOJKyBLmOSHYfb+Xeeze3UY7P9CAKjWZsu2W59FHeA3+4uAbe1xhUYLPxiGDbX0SyfblCFfYDYeE8XsnmdfE9CI4P4wvkcZpAtBWIyK9H86qTNhlkjMibiisX2o7P7B5K99S7dOWv0bddG9lexbDtk3oiF/XM5kdErplgEwFkdNhXKxu2i2DnYrNi3Q2OzzSbjou52Eqo217J9hVorVoT6XMrSHSUBggTcYQpDpzXRSBgJ5wFBasKV937PM7++f14fuFSnzZ9yiScddxuOHr36auxZgUbbrhhZCZ+2GGHYcGCBdF873nz5uGVV17B3LlzsXjxYp/3t7/9Lf7qr/4qUr6nTZu2Oi6joKBgBTHuiXYjLZNHeh3PeRiPCXLbvphgN/JDHmuEV3Em8sHzOCvZvExNxZlk91KzJSoRHzuquzMrzyFrJo7R8ayxBPOLvkgIqD+21wWomGxH6anH8KRcuUz3peS31bQ7ydsQBJMOflqXfiQ7qy6n6/2wAkShlWSn+3PnTG9cow2pWUDuZgviHZmSN/JyWTkmK0m26kueUs/cNo23cwewfUV6epdOaCfbK4jREsGcE7XcoJu0EIjVbPgBBjJuH6vRfmQLzqO4cqbi8GQ6/qlmmwzYRgOPEw7y/kTvKYVfQcEqwFX3Po9PffeOxqO/YOFSfOq7d+CiD+5TyPYahi233BLvfve78e53vxsAQER4/PHHMW/ePBxyyCE+380334xrrrkG11xzjU/bdtttPel+//vfj+22225VV7+goGAUGN9EWxOqilBV7OyMvOOzyFxcETrCdJzJrVS1Y8LcrlpznjhdqOViHjYQq9ieWDtFm8m1X09U7H6KtoaCccxRCxNyQwpQ2tfJht6xpFtnOoJaETiGNoDRz8vOYRBVroXgjugcacfY9cWVsuzbqonOfNyNPSgDUBVINjkiLtXspkM0FcpPPI9LJRtAq7l4XtHOq9g50t2PUMdmsX0IrEQbRxjkWZDnyQ00SDKtpJotyIknKwl5FQTYW0Tw8UCYQuKtWux6VRl/ZO65T+cOpySRz9nPiiMm8al5ukijvLrN3s+9egzOw+UO3v6NMGSN+sER+v6QCjbH1O41kJC2oZyDbZwCTUao2LWKVGy4sF3W2Vkg24qVaxm+SyrXme9L9lFue1cSwszvMnS4T61x3526rYRjzoKClY3aEM7++f3Z55xgH9+zf34/3rnbtGJGvgZDKYUddtghmssNAEcddRQuvvhizJ07F3PnzsUDDzyAp59+Gk8//TQuv/xy7LPPPp5o33777bjqqqswffp07L333hgaGloNV1JQUNCGcU+0tTYNc3HlCHflOj0dHYh4R5nWMFxAP1W7Sax5f07NtueoI4It52V7oq2ty7IKlJiO91C0FQDSqFQNUAXDRFr86+X52ba+lTUdh/JLzhOF/RrJDegHSbITwj2wcj3Cc3AnQ54HfC7FNMYpx42wXEkYLx3W0+2sB3IgDvslCXMmpFWkYmuRtxe5zgxKNJRkeVyO9OaQNpwsjlf6cYhsnRCuVWxHP5euMtdtV10byZstybiyU0iUQky0vbrN76bNbvxhTAqVfdPcgAwTXlZjR0qeUoU7JqpuByu5ivwVKkVW5XXvbZNwc6FisCE6L+L0qI3E/hEg51Xcpsd5OI3bjOdgg6yjM6q1TXdzsOHWVe0INc/BNs6ruGujYC4uCPYgwnHuWvs9n4Jke9GcyXX0HSBPxG2MM0eyNXh8s6BgpWLeE69E5uIpCMDzC5di3hOv4KAdNl11FSsYE8ycOROf+MQn8IlPfAIAsHjxYsyfP987W9t333193ssvvxwXX3wxLr74YkyaNAl77713ZHK+ww47WMGhoKBgtWB8E202EUUwCU/nXqfzsVPnZ0DTdHwkBDvdH1RtlxeBzHuTcWU8yfYexSMlPSbZUo1jUlzBwCDu1VXKYJgqR7D7m53b+dh9s40dVtG3npyK3cop2ZlaQkZzJuLeqlV0zBsm3Om+5MSNtFyHv9f1pMel9exHsAdpd86TDobkrBFyz8wIr6lnVYQ6G8WjVs6BWFInlRyb/jisH8PHeVYy9rOFcRcdPGmH0rP+9/pea9qAbtBAxc0ZKfWIBxU84U4HPnJ1EMR6ZSNyJIeYZHvT8CSdw3YBCI7MmNU6Aq0Q1iNS3fatGsG15t6L7POaDgRxvsbAFfsHAIrpeMGqwouL20n2aPKtCIoztpWPyZMn47DDDsNhhx3W2LfLLrtgr732wpNPPonXXnsNt9xyC2655Ra///HHH8fMmTMBAI899hg23HBDbLnllquq6gUF6zzGNdGuKqtoS3PxocoqwpUKpuMdbTyh7QjTcTbp7jfXmtMZbfulyXlOxZbk2jpDC3OxwzIm5v5aXdm1owQ1NIbQdUu4NOXJtq8rrNO0FIN4Em8SjQH/eSpyLKl3tlGp2qwqQfleuUJTufbqtrJ/CCEvwESmqTRnPYxreJPxhrl4UkbDuVmS1ytiSPbLTrxsuhzBByJClSXVIyS+Qb32DRSOpSTfoDctN8CQqV8gNewxnO+bIzGC0CkEdVHOv2YP41qTt2DpVCYaaEvBMZ0BoDbapQUV2lDwGG7PH194qnTnmsVzRDFfGQC0DmGuIEysUdnrVSBHTm0p1kFbUnDmhFGdRBvZ7TD4FFkD9Lmf+bnY8roQyDXgQnTBh+qinIpNcN7F7bWwoq0IUTxs5cpOb1/fZ7qNPGeO5/cxev/9e0vhW6Cdp3FWtCurZEPBW1dBD+ZXo6BgRbDF5Eljmm+0KM7YVj8+8pGPYIsttsAxxxyDp556yjtZmzdvHp599tloLvfnP/95/PSnP8Vb3vKWSPXeZ599SnzvgoKVhHFNtNk8VJqLK8DP1fZENyHUTIp53raMd223Y/Nvn6dV0c4TbADeRJzXZdguJtdsLi6dpMmY2VqakEcymAYor2wDGhUMuqh8nbvIz1XlthwojNeKYiUUT4JQ5Mi7TbPEPOWToVMtPIwnJuSR2aggzpHKLW9BStxlGlqOEySUTVbT41K1slVZB/KkvAek/u/JtGwsQbxXVLST5LWpEIZK+NOywg0RHkuJdE+yA7FmHw3alZN77lVSF0MKlQJq97pVTtn274TIK6sty07Jt48l7Y7nslJ13JJVO4eb+bVyI0OR+XrjAU4uSLZPS505/Fnj8D43tjkf262b8KUkowLR5rnYTLQBF8LLXocP00XCXNyl9yLZva47t92cPkHxvnQASJBsv52YjwcF25FsxQ74+tS1oGAMMGfmVEyfMgkLFi5tNTCaNsWqyysL48UZ27qiuCulMGvWLMyaNQt/+qd/CgAwxkRm44sXL4ZSCk899RSeeuop/PjHPwYAaK2x7777Yu7cuT4/ERWT84KCMcD4JtpAw1xc/jot8a1Zyfb7epDs/up2TLLTdZ8PlCXZFZrH+VBjmTna2pmMV8qEcF6wXr0qxIMDjKpvTzWPNgW7Vdlu6/wravZ2pTQ6GnXKl40sIeRtSQw9CU+ro5J6SNKbkte0U+7SG6blSb6ILOcIskpU7AaZ7kGyByXYaTtGbZW7R0melQVBWnK7QrvEztAkceRpJFoMvGk3EAfE0QbS59eQsoN0rMoqBSPfcZHPp2XIdTYKgiPrTNohrkdrS161Boyxj6Ex8WPtrTI82Ye7hh6kro1ci31pfPGw3lLmICDxEPtRJYg02HnxlOTtURw/ltHgTw9i3YtUN/Zn308x0JW+ywnJVioM8nDcdq+OFxSsRFRa4azjdsOnvntH7t8eAOCs43ZbaYRyVTljW1GSvK4r7lrHIsw111yDRYsWRfO9b7vtNvzud79Dp9OJiPXBBx+Mqqoi5XvmzJmFfBcUjBDjmmh3qhqdqsJQZY2jO86M3IfMEqp2TsUORDw1Ae+tXstOtiTJORWbvYoDwJDutpqKM8Fmcl1lyDpgTcYr1KhJ+f0GNp62aQnlNSh6qdmDdh+jebUpect1kNtIcnp+VotkR1sey6QaQaG29aGwzwgTcibfMla2CtveDJzTnPlozkw8cmTW4vRMmqfmyHhPFXtQcj2IUuwPStII/n71Uq0b6Zkenr/tOVI0ANjvggzLl55OqrJah8gDncqgU9kY9UPJ9yAFe+hnE/Ku0WDzdVayayPqIZ5l6WBN+n3IkW2vanuTdJtWOyXYzgfn51VH8bz9u9TP0iQ5bxuRTvfl9rfVX277Oddw94Q4Trby6+n8a4g0f/ukYp2q9fxM8qly5iqpOi2PT9eRacb0HfRTQ4RjNCbQClbZdj9VGa9m8zSmQrQLVhWO3n06LvrgPg0iOW0VEMlV4YxtRUnyWCjua6MavtFGG+Hwww/H4Ycf7tOee+45vPzyy357yZIlmDdvHowxuOmmm3z6pptuijlz5uDd7343/vzP/3yV1rugYLxiXBNtrRCZhnplG4nKnczHBuI51amCnU+PQ35Jgs3LyIGZO847O0tiY7eR7KpRfkK2fWfUatu1INeDxt0eKcbSnJykKom47yyJclvfP85vMzbycueZCZ8sj82ioonHIV+qYDXUafRIQ/MY7rTLekX70zojc4w8Z6Y9Wgl2r9uWDlZkyu1rCJEj3f0IfR+EudnUrACprPrqFW23zt+EXCg/IDzP2tVNK0LXhNB3zAc13DMGO3c7cqgmzs3HRevi8r2K7Mg1m6dX2ljCDVa3lSVrxHPHyQ1cxTejTc3OK+q997el56xWUud0Pp8n3qF+YbQKfskDFUqq3L0g3g8lSHd0/pRc595JNPfJbfkO+vep5XvAP3aAplzlQuz2Aa6roGCMcPTu0/HO3aatcjK4sp2xrShJHgvFfV1Sw2fMmIEZM2b47fXWWw/3339/NN/7rrvuwssvv4xf/OIXmDp1qifadV3j5JNPxl577eXne6+//vqr61IKCtY4jGuiXSmrWMnwXdypTp2eeSU7MQmXsa9teruDM39exKbnaZok19JcXMbGbiPZOYLNx+ScmrHzswp5p2cAUJNCLVS1HAZ1dBZ5Gh6UgCsgsF6ZlssbM7Mc4ZMm4I36SdFLkl+xbU+hfP5AslWWdMs8DRIOkYY8yW6mxXXzdfTrlEmLl31V7EFuTQ+yE5EhEmnpcdE9pZAXgz8evZA682KiZ0lNIDeSWFcqDuUnp44YUhHhZnNxrQhwJJfzGAQSqpMG5fRKhAhUQOO7wOfh/cFZlg5zwQHUoWTkpd18m7SbgDcHJHL1b0M8Hzso7KF+1jokbMXz58kTY/cCO4eEyvk/4OeDPcmz70QFWCWZwuGNqR7Rhbg69iDcQI9HPX3/HMkmoWxDy3zsAI1Nx41/Fq2iXZyhFaxaVFqt8hBeK9MZ21iQ5BVV3MfL/POVBa01dt55Z+y888740Ic+BABYtmwZ7r77btx2222YNWuWz/vQQw/hO9/5Dr7zne8AAKqqwu677+7NzQ8//PBGnPCCgnUJ45poaxcrO3SwA6HuKIOODrGx4/naZsQEO6dgp+kRsXaf6DZzce8AreEMTZDxRKG2HXJHqMkSbwOnxI3QYrGVcANCUYsJeC68UQ5KEsQMwXZd66iT7M3CRb5oXaHReY5UYaEmSfU37cCrpDrSBDxLsp23cd/5Fp7I/TFabEvT0xzBBnoQ9JVEsPN8rRURB5Mk2xNt1czn0uV9TymjJ8mk0IgNDcQqtrJzXm26OEWDaNv335qL2+kjQ2w67papXwZ+9g1pdN2NU4ZQkxb7lCfGqaLs6wp4Uh9Z1IjvCJunc5na2HPoqoZzMY7aKMBoZ1VNMEY783UOM9ZoKl8HqepHS5cn6wQuScsNsnmnbWK/jZMd4osbF/Nb1cpbqtisNqY0q/J+JIQrpsl5kHfxw8l9EfgzZhA/x7nnVmV2t7wHPQd8xDsHIJ4Oopl0UyDcLp2JNcdtryo34FuIdsE6gJXpjG0szNJXRHFfVfPPxxsmTpzoybPExhtvjH/4h3/wc76ff/553H333bj77rvxf/7P/8FXvvIVnH322QCAV155Bddeey3mzJmDt7zlLWW+d8E6gXFNtFlBkg7NJHGG2B/WBaEeA5ItVex0HmhKlBvhu+Sc7D4ke7QwA0mb4wxMnlNiHuQ1oYTZmNnMlRqcqaFoJQo3mmo2pXkbZYnOewthbhCBpMOfXq/P17Ive+ygtz4h0D5tJCQbIa/lV0yyEO7JgOjJiwSxlEST50qn34OOG8TqZAmQ8Uq1dsQWCjDuIrQib0YOBMKpGt+UQLI74r1Viux0XkX+PWQv57VQ1mtYk3jt0nmOOJeRnrutLbjt2ryg9zMdl4Q7jSvOIFG/dMll9XKWmE4d8e+yYn1cDJiJQZUU0ZW0DUYB7Q9qcmxzYIuidz5StP0+MdDR+ywFBWsVVqYztrEwS18RxX1FiP7aOKe7H2bMmIEzzjjDbz/77LPeydq8efPwtre9ze+76aabcNJJJwEANt9888jR2v77749NN121lhkFBasC45pos/OzSpJqoV5Jc/FUyWY0vYyPTMkGYlKcmoun3sVz5uJDquvKpJ4exwF2hkbZvewMjZU5jrltSNuf+xfol6R6zr82rpmkqgUMrmwDiDupUt1udIaVJ66R0zMVVnMkmZTTxaR0mp471xEn+PN5Up0h2ym5bijTbSQcohx5blnHFqIuz5En3gPegF7ZKF0KAu1+SuZJ96flxNzJ7bKDHADEVIPB6i7nu0oiGe9300Sq2noNdyo2h/PrqDqaQsIwft61CizaMUtFyu5PzMgBkVUFvxBaUcMBI+fhcxhSbgBNwzhCbQRB1QqoezRL/O6l89TFOtdNtJecS87Iqdy+PcR5jBNxfVxxAKpicm1gjFO2AWiy77aBNRshF6IruudkK0RwYcwU2bjafnCGkoEayNkI+baRxJgbAcl7JdJbEb17Usl2+0W8bF5ySDnp7R7rsDO0973vffj1r3+Nd7zjHbj88sv7pheMb6wsZ2xjYZa+Ior7aIn+ujSnuxe22mornHDCCTjhhBOy+/fbbz/cfffdeOmll3DllVfiyiuv9Pt+9KMf4f3vfz8AG4qs0+lgvfXWWyX1LihYWRjXRLvSxpmIh45uR9cZlbvpVRyIlWzetsumYp2m87b0Lt6LZDP5Z5ItzcWliq2TGNoSNcmwXjakl9+XkOgajmwnPU5pxirTDFkzTl5nkp0S8b5OkiLZWCW2w2iQzEDKYuVK7vPblBzH/XfnFA1KKKqSqHrZM0PIFYKncZ6LKYlzLo3XhZlpMDmlZj4IstAg6oEgNFS15Pob6EcecsiRZEo8PzPJbiPYOfFdlEs8bkKWbDNb8ttEYvQkX82ILOoc0Q6huzhmduUU5QmVjVc/oarR4XdRHM/vRNdU0BUFwq2FZ3AVm3zbGNthsM1/C9w3KPULESoKb54uz+Hft/zli7bsf5PZERyT7Mqb3Mdqu6tO7/O5ZYj3HdqhNiqQbrKe0tljOpNuDeP2uWsj8oNY4YKF93/+dvCz5tcprlBbfaP3PJMODD4wJd9NTUHW53Vl52drbzoe1juVHfTFSnJIOR7wmc98Bh/96Edx2WWXDZReMP6xMpyxjYVZ+ooo7qMh+qOZ070uqt/HHXccjjvuOCxduhR33313pHw//PDD2GOPPXzeb3/72/j85z+PPfbYI1K+d911V1RV1eMsBQVrFsY10U7D6aSht1Llptec7EHO1Wu7DXJednOf8eQ+R7JTJ2hVSwivlAy3bafLQR2gMfrl92ajnu3yDibfGEzQlCKYEv3k5PhI/ZZpad628yp48/A4zabzJUglW6bJpb/OtuuRy/S4NmTJtbzYJE+6naKFZEdp1LyMlGS3EeyozkldImVyBKJfjmDL00gv455U8sCWnAbiTmoQCLNRsXO06BzJDWJHamm+dG52ahljXKx7Pk8v5XpQpKp2DrnY3lz7Xt8u75FdqPiswGuFEF9c1MFaF9iXzL6vbs62clYNjj+nZLixLT4TIqk3kneroXDLPCna3pc0zW23hUWTz2K/+7I247DDDsOvf/3rgdML1g6MtTO2sTJLH63iPlKiP5o53eu6+j1p0iQccMABOOCAA3zaq6++iilTpvjt+++/H91uF3feeSfuvPNOXHLJJQCADTbYAPvttx8uu+wyvOUtb1nldS8oGClWLPDyakaYh2nQUULJdmlaqFmpuXijrBaT8RS59NQBmlSx5TGRybiYky1JtjUxt78wf7t/582QRg2FmrRXs6XJeFCqm6SbKI4nnDpCk2mDgsM0oaXjS8oyusj8GvEyp1alhDfanx6r4nVSysXEdj82F+cY2clx2XKQ39fLu7gnGY3rorjegyC9D+mjQYP+lFeylQnpSuRRzqxX7lN8DuN+yfEw8DGSuWxlVNhnknpkrkGSRDbP9Wba/NPGxcw23gHaUFVbFVvb5cSqiyFlMFHbtI6uMUF33ffCYEjXfr2j7Tekw5YnymS9lufMxSXJ5vP475CuowE+iTSutnz/iCDWrWLMP7utRZr21iiyPKA5OJbOLedr4evpuCgOVdLW4UeRBYH2ym5wDKZcWUrDmlprgqoIMga1dDTm1WOXbtPgHJKJn0q2+b2t3DF8jsqVV7lfWg7/Mvui+qhQV+9pXMN6GnfXKtuP22M84oYbbsBxxx2HGTNmQCmFK664opHnggsuwHbbbec7yfPmzVv1FS1YJ8AkedqUWF2eNmXSiDx+H737dNz4xSPw/VMOxL/8j73w/VMOxI1fPKLn8Uz0gdYxt4joj2RONxDU7/QYVr+vuvd5n1Ybwi2PvYz/uOtZ3PLYy6jN+Py+DIJNNtkEWgdKcskll+Cpp57C5Zdfji984Qs47LDDsMEGG2DJkiW48cYbsfnmm/u8Z511Fo4//nj8/d//Pa6++mq8+uqrq+MSCgqyGNeKNof2knOyBzEXBzAiNTvFIA7QZLzs1PlZxfXLkOx0braNlq0b4bssgdaeWNdQTVLt1muxbtz8bXJpvoOPuFPuO/kjbZzGEDQhcv0t1UKXV4rd7LFc8X4E5TpSuxJy7WNqJ+WCy3ZpaT84hPGB77hHZFnuzxLsJkFvkGxZZ9kush59yHYkskYyP0akEDecmQnCG0i1yu9zadGxSPYDoQ0Izvs0YL3MO1/jxB6mKa+sI6iHqVl0CKsV1OSONpiga7uuakxgYu3INBCcHBqy86QBBLkWbuBJA4as47Ku8wLe0SYyHWc1OTIdd98dJthAPEfbTvPoPaYprUyYZBuTJ8tsVc19ErutobWxztRIwYCso7cM8ZOWQBExlOo3K9vu2u07RD4cGqBhyG7DaPueyEeSYOfni0fJWzXIKhk32GUIihUqEzKTf3nROmgXD2JRkrdx+aKSmTR5DibbCmBP4+wAjU3G2TdAJQaDxiOWLFmC2bNn46Mf/Wh2buUPf/hDnH766bj44otxwAEH4Pzzz8dRRx2Fhx56CFtsscVqqHHB2o6xMksfjeI+EjV8JHO6R6J+X3P/gr6qd20Ic594BfN/r7DpE6/goB23WGvMz5VS2HbbbbHtttvixBNPBGBjdj/44IN46KGHoljdV111FebNm4ef//znPm3WrFne3PzUU0+NSHxBwarEuCbaweMwNTq4jNEQ6dHCx89255RKdIVmrOz0uJUB6fjMp1EzTe7rN2jaf542mp3YBgHnpfv3kjumDYPkbcmTJbSqmU6NDnyvcw1QcTFoMDD4P292H5OPETzfPdTwtJis5a3M06JGc7tLfuTz8a2mQL5zYb58UeL9ZpKtk7SUNKaRB5pODi3pNbAEWLsBJ+1ZYChfvh+8HXkcz9Q9r1zrZFtBWpJ49ZmbKmtV0mwXm8b7mx7ADSwR1rDctRLXpGEHMXKm870cJIY60AgfZnkwss8NO0kLo268zDwjKZFOSfYgVRu0+nIAArHFBYDomRyvRPuYY47BMccc07r/vPPOwymnnIKTTz4ZAHDxxRfjyiuvxKWXXoovfelLY1aPZcuWYdmyZX570aJFAIDh4WEMDw+vcPlcxliUVbBqsN+2GwHYCABg6i5MvWrO+46dN8Nhs96O2596FS8uXoYtJk/Efm/ZBJVW0fOz6fqDdaM3Xb+DWx59cSD1++vXPoSv/+qxxmeSVe//73/MBgD8/X89iAWLlgGo8P8euR3TNpqIM4/dBUe9dcsRXu34wU477YSddtopugfnnXcebr31Vtx+++247bbb8Nhjj+GRRx7BI488gt/85jf41Kc+hbq2D86FF16IDTfcEPvttx922WWXQsDXUKzp3+qR1GtcE232LBw7PwuKdehk59XsXrDevQcjwKnZOCDJdpifzSS7oWbzsT5fOG/NnsRdr7BmE3GnZg9TZX+mAwOFYWO3Ddn1mhS6pvJqdpe0V7OlOXlqOt5uyuoqlutkK1jqRKwuq5CVO8zSpXhCZL1qrVxcXe4wk9iPoHZLMsx5CXHRpOFJXsT75Lkjp2aqVb2WynW0RCY/BJcYoEMfK9bimBzhldcxIFuIHvmEJHslGwhm3vIYQvDxlFW5RR1cYnS/uEhSUIZi5+MURmiIOLKyKE6QbKlisxm5VoQJusbETtc6QNM1JuoutCK/lE4NDSnUTDChnYqtUSuFjmInaDW6qGzUAgOkM2z4W6OS707Puc/ufesa7S1FaqNhiJexiTjg4lQnhFvePqmwAhpEtk7k1FYFgMj4tiPXdgREBJt61ZviyARtJumrFI1BsAzBTpXtHHoq2giexhW8l3HlTOS5fStWthOLi7UJy5cvx/z586MQPlprHHnkkbjlllvG9FznnHOOj7krcfXVV0cK1orimmuuGbOyCtZ+VABeBvDLB5r7DAEbT6jw2nKg7b/0xhOAl+6/FXe+rFxpvfF/bnjUfZ7i8twXG1+4/C680eXUkGfBoqU49Qd34aM7GczedO37FvXCjjvuiB133BH/43/8DyxatAiPPvooHnnkEXQ6HfzXf/0XADsg/eUvfxmLFy8GAKy33nrYcccdMWvWLMyaNQs77bRTCTG2hmFN/Va/8cYbA+cd30Q7mR/JnW+5z+cdUDVOFZ6c4tNanz5m4xKp87McyU7BpNuQRk2ObCPMw27Oz07MyZNlajYuO8+cDsRq2iAIMXGZIQvmmJJJSSqF6stNHllJ54oUpM2H+lJxsf5UkuCJc7WZfzf2IewPpJoich0aIVlG+wZo0KSeUZpIH1G/PiHbkkjnzMWjJSXHufyN85NyJv4UX4OTVUk7Yk3xMWlBUWxoQbIrbW005DzpSgcfDROrLjq6dmHzwiAcQysCDFApYBhABQXAYEgpQDtP5IpsuCrFg3TGDR65MpCq6Cb6DjFyMeylPwSeSx3eP0QDW8io3Wlbc9vVxKbk9nqUcs7KjPbXYGN1WUdlFZuZJ0XmnL7x+QeJQJCDH2jJ7oyVcTZPb3wbomPC0vp6EOm9SHdU+XA/Wy1tuDxHsnlQw/sOUMF8nKcuIRuvfXzj97//Peq6xpZbxirZlltuiQcffNBvH3nkkbj77ruxZMkSbL311vjxj3+Mgw46qDU9hzPOOAOnn3663160aBG22WYbvOtd78JGG220wtcyPDyMa665Bu985zsxNDS0wuUVFADA0HYv4LQf3A0g9zlR+PsTZuOot26JzZ94Bf/vkdv7lvdGt9e3VQmS3dynAPzihfXxhT89dK0xIx8rvPnmm/izP/sz3H777Zg/fz7eeOMN3HPPPbjnnnsAAIcddhiuvvpqn//GG2/E7rvvjo033ng11XjdxZr+rWZrq0Ewvom2MhhkdHAQGA6ZNUaQZeUcoMm52IOQbEY8T1v5tDqan+3WI9VaI6tgI+5AS0dKQKxgjZRwAwgd6TZTU5XmC9uWOCMm1Bky3iTc8Wmj/KIKWVVapEf70v2t1xufI4sMsXSX3Cw/R7hlem5f43wt6y3n73tsSrKT4+ytSK4xUc+Dd/re9bKk2q2rOH517JMhbFeJpYu0TKmhPfHWCISa+y3B/Lz/vOp+CjaAxsAWp1HjJ8m2axIx2JV76Eg8MAqAMZbUGqNd+Cmbx4YvsyMd1nM4AM6TEOsGmRZp0solcrgG5AcKuAw5UIN0PT4fzw1v5O/3jKfvaUq6G+jxAgmSLT2NR6cQlhUFFtdee+2I0nOYOHEiJk6c2EgfGhoa087WWJdXsG7j3XttjU6n6jun+6Adt+jr0XzKekN47c3Rm8sSgOcXLsOdv1uMOTOnrnMhxHphaGgI5513HgCg2+3i/vvv9+HF5s6di0MOOcR/F1555RUcccQRAICdd945CjE2e/bs7HeqYOyxpn6rR1KncU60m/GygebcyZRA1yRC/LjukwZ5su1D8Tjz8TTkjYSfly1Mxu0veBrPOUBrzOfOkGxpNl4752eGNJZThWHqYJg6qKEwbDrBXJwqDDtv48OmQpc0ukb7ZU3am6oaUqiNO4fRPk6uNBeVnWe7nSHcjtVK5crOvnWEjPvOPo618kqwgvL8mhQiE/DUHBzMwwXpjki1sgSPVW1wXgcSx/k0Hcqx3sjdduoEDWLb1yfuyA8i8PnxhpRoinKyAlyvQvuR7pQINxTrOI62LyJRvVnJjpXwuFxuY3vv7AYpQDkTfiIA2uU1KqjbCs16KopUw8qRaXaANuScj02qhr0DtIlVFxN0FxVsrHp2hsbQztlZSHDm5I6Bcsgvq24DHR3eB3YENijBSuNwh3dQuffNeQs3CnXtTMo5VrW7L5TeK0CE91LiXbHPkwKcubiCMQStVVBgHSFP57zHIRKFIi/eebsd1rnubO4uvaOTSQYQnAk8EazzM3KVNoJUE+y0BbEdIR1wit5DXqdg5a+lst2iaJM4LlN+ULFFe4nY2ZJsVzzo0/tNHZfYbLPNUFUVXnjhhSj9hRdewLRp01ZTrQoK1iwM4rxtkNBlJx+yHb527SMrXJ9r7l+A03901zobQqwfOp0O9txzT+y555742Mc+BgAg0bn93e9+h5kzZ+KJJ57AQw89hIceegjf+c53AFiS9ZWvfAVnnnkmAMAYxz3KfO+CDMb9UyEVqNy87DbULazIePPs3qwpmpfNZLlB8KmnSt2LZPv6uFskPYwb5D2NS7PxrlOwu0bHnsYzarY0YwUE/xKKG29LRNs5hdYTUcnGxHZDhRqsk5oS3l6qc0SWW35pnkjhVvH5onMDA5Hr3hcit5EnGUAcMkv8mmVmfkkZPl9ah1bVsf0cUV2SdTZJl9uKz+kfDeXzRdebkD8ZisqGnzJRekfXGHLv5JCqAxF35GdI1f4XlQcO55UO2qVxscnXKwqRhd6kO7Ugqd37VBuXZrQNzyUVYddGJNrNv4tuDr0ns57Y8jEKZDRIhAMLocC0r0Ptzlsblfx0GATw9YRdin1c9zT8mBwoIINQX77H6XPpn5sWkk3pC94DknD795nNveNfnCf3oyiP8g92OJVWbtCC09TaOUd7woQJ2HfffXHdddf5NGMMrrvuulYT8IKCdRHs4fw9e22Fg3bYNKse9wtdduoRszB9yqS+Rjz9cOlNTw4UQqwgQAkTpj333BOPP/44XnrpJfzXf/0XzjrrLBx77LHYdNNNMTw8HE2lufPOO7HJJpvgyCOPxF//9V/jiiuuwHPPPbc6LqFgDcS4V7THCgZqTNQIjt0t68ZO0KQDNJ+/xeEaK9i87p2gkVO3HaEepso7RbOqmVWxa6eg+fnbJpBvSbIliY5DDGXMP8WyDd77uFc2Y+do/nBPXMk5QVNeWPLfuoTUevWO66RE35fzEpfFinksXLURcVKqMU9b5pN1bqRntgcGH5g+y7l2zpyjcdiK/nduQc9XLSXlKoiEdqki5Tre1+e8rByiacHSce9aRxlLslUIsWUtSSzBZrCSXSnjrUUA+LzW8iWkS0Kd+mrIexdX/h6lUzbkoFUtCCqbihOH8kJYZ4IdtXF0g0MdyKhADN17ZsN8mUAubYt6RZbzyOshFbyWR9fFdZPfC+G0LWc6TnIQxYgXSg6sMMnOEWwk2yo8Q1lIAg14ks3rslxr/SLSerw3kfm4INOpt/vxjNdffx2PPvqo337iiSdw1113YerUqdh2221x+umn48Mf/jD2228/zJkzB+effz6WLFnivZAXFBQMjn7qdy/VmwBsvP4QFr4x3Pr/Uytko8fw5/NvfnYfJk8awu9fX1ZMyvtgs802i6IyEBGefPJJTJkyxeeZN28eFi1ahOuuuy4akNxqq60wZ84cfP7zny+DkuswxjXRBiA6yO2Q4XVkXqlqV4o82R7JfG3N5FkJb+LC03g0N7tPzOyozk6xBhBMxJ25+DBVWEpDWGqGMEwVljnT8a6psKzueJPx5XUnMh2vhaLFHf6cuTh3nHkdQEy8BUGP4GyHI7INQGnuvJN3yBR1mBM1yRNkVpPCaT1Z9odLHiLzake2ER+PZD31Ms5xsykXU7uNhPf6/yQGHTiv7JNTrnI59GOlLXx9TEGJiXmiTiZcJvI6DihAE8jYVT8F2iudkvSQvyTv2Vux+bhVtDvKYELV9Q7QJlbW6/hE3cUkPRxUbG1nXxvSqGDf12GqoJmA6xDr2jtG07U1I4eC0bWbZ63RzXgfzyFSsWEHxrrG/oadiXjXaGcuDpjaqsuAU4ETMhoNbqUjP570uQENRWEahQIUVWCTcqPZvC0Q0Jg4Zi8nnjMu6iSdtnkybmLVPTIT98+LXVdRWri2NkvvsAH3TsakmpsEyn5zfHrUZOE98lERMi+W0pSUIRyhIZBrvy4sIcYjbr/9dhx++OF+mx2SffjDH8a//uu/4qSTTsJLL72Er3zlK1iwYAH22msvXHXVVQ0HaQUFBYOhV3zvfnG8AfQk4r1CtBKABYuW4U+/NdenFZPywaGUwsyZM6O0U045BQcffDDmzp2L2267DXPnzsV9992HZ599Fj/96U9x6qmn+rxXX301vve97/n53nvuuScmTJiwqi+jYBViXBPt0XRqmHSviOOznKk3z81O8w0SSiyFVNv6eRo3ECbjbtsr14i9i6fxe3MOjRht64NKplFc7WwGycRD0a2l838QlWwn61LlZi/k0T8iEqRZlN1modqXTA/SHBHbj49JyWl7GZmD0nMMWp8VRapgI66Sb+PccWnPINqf3ymJjZwq4gmO+3V07dVp9oNQgVBDRe+7d1Tm3g8oHXsad4N3hqrIWVi6nkM8L1tHA1j8jkXzmYktS2wGSbJbCXZ06pgsKtfAxKNR2lmSKPIO0NhpGs/zDvG3g0rrT5V8B7hOMvSYcS9PmI+N8EJFRBpxmryWZBAnhb0qlX/2PcmmfHq+sPyu9LkVg0apt3Egfg60VNDHGQ477LBofmIOp556atRhLCgoWHnop3q3EfFjd5+Gb9/05IjOxSblF31wn77zzAua6HQ6mD17NmbPno2Pf/zjAIAlS5bgjjvuwNy5c7Hffvv5vFdffTUuu+wyXHbZZQCsA8i99trLE+/jjjsuUssLxj/GNdFeEaSEmx2kxap23RpPW3bmZSeeCUBwdhZ7Gk/DeUlEBBvBAdowVVhOlV+PfqZC12gsM53gAM2E+dm1ULNrCg7QmGR7M3Kjs16Dc7Gze4b1EczRO0EDwM7Rgskmd5oF2eZNr4RSkEWjc9i8XvEWx/n9fGK5HS4BxJVLnJ71coIWL8dWucqq3G3wkvEK1MG3t2DFfL2u2WX72UGQNgbN9Qr5U/NwRa5cErezcV8pUmgtoQ7ExpJp45cdZdXnjvux87MhVaNSxs3HthMwvFWLMtBukIrBFihG2QfAmp4TjJJzsAPxTsFm5XIZhdWjZO4zEM9nFipwmJstXp629ora3I5SsSWJfPfA75FCcKSmyBNXtjhQ8n2Up0iVdf5G8Kafh51eg/sZFTk+807PDHx+bx3RuK7MNecg333xHMEPKMTXAm4XaYGTlqd8s9mkpC6pCXlBQUHBWKKf6v3O3abhlkdfxNW/mYt3vf0AHLTjFpj3xCsjJtr85f/ST+7B3/zsfixYVByorSg22GADvP3tb8fb3/72KP2EE07ABhts4NXvV155BXPnzsXcudbCQJqlX3/99Vi4cCH2339/TJ9e2n+8Yq0l2oPGv5aEW3ojT8uQjpMYrHxVYIXN+E57ztM4I1W+JcFmk3E779qajAcv4xWWOXPxpcaajluSPYTlpoOaFJabCstNx3ful5sKRArDiYOj0OFvEuxByHXflhXtxHOzFWJP45JcR+au8lSC4HruJzq/npSHqob9SnT+EZfpSaUg1m3rDZItyxkNZH0yZfQ1nZWJfZ7xNl4ccyrhIZ5TxBhHOgjgSbgUEjMkyZNsLke7chEIYfZBUk2vzh1tfLzsjjaYoGtM1M50XHcxMfI03kUF8kTbkEalajsVgzSMMiEooLbvX3B85qaBkMKQrmFqhY52kQdMPA0FCAN1MckOViW10RiuK9SkMFyzEzHrZdy/e7WKzayTdy9t12Z7iX2OVJNI9wNcOgxi8EvmHYOh/+NMok4yZBcJdZukObgn1OEdVEbBjzGavAf7yMojfVdyz7xKliI9JcG87RV/QbajkyO0jWr5AbGTvIKCgoJViUorHDBzKl5+gHCAU57nzJzaM4RYGwjAa28MA4hDi7HafcEH9sYmG0wsSvcK4uCDD8bBBx8MACAiPPbYY5g3bx7mzZuHRx55BNtuu63Pe/755+OKK64AAGyzzTbYf//9ccABB2DOnDnYd999MXny5NVxCQUjxFpLtIHensNXZC4dq9kSMqRXG/rFyZbzsnndkPQyrhsxs60XcuXU6iRWNoKZeC5ET065lvMuOZ0xSIu1cqeU74qOLZPvtKNMgjCvEFqOl8S88Rvg+EFOG6m3K3AdrebYPdBTfE75Su4EQYRs5zgjfY0SQjXQM5WY59olex030SCYBvmBr3CMI9sgGLEtoRWhIgMobS1bEoU6LSuHYDYuB87E+yPMxn28bH7XIjNr0fCDQKq/OXbKZuH8riO4JbT31r3r/W5mNAAnvg0p+W67hmgQobnMPVsDP/Pie5I13277MLUV1yDocTpbWkiM5znaBQUFawd6hRAbDfj4U79/ZzT3uyjdKw6lFHbccUfsuOOO+MAHPtDYv9NOO2H33XfHfffdh2eeeQbPPPMMfvKTnwAA1l9/fSxcuBCdzlpN49YKrHV3aFDv4XHneWQO0CRkp547WTw328fS7qFm2zo342Wzil2TwnKnZktFe9hYJ2hdsg7QWMVebjo+XvZwXWHYBGWNHZ91RTihWNEGUrNQAH1kUbGZLMPhrJg5JRtO1vS9V1sWOfNVVuD41Ky+enU1UbH5n4n0Vi65RwqvVAPB6ZlIZ96TrqeDA40T9BIgR0myW4lGm6qXHtOHbNsVblfyz4AigIxoU3ZcxjcgMyCRVonvnRcOJVNvUeN9swo1m6didFxoL+vozJmNK6tsD3nT8a73ND6kuo2CNRRqqpxqre23QlnF2pqOBw/kHQC1UugA6EILEtXDiaEbBON3LI2b7R2guRBcIKcCGzQV7egmtSAyN0DmpbAKN+ylubZNB5nE29J2OjEg57cjgp0MFEhFmxDHyHbr0hKiYRXBdcte8wCDAiN535jRK0reZ2fnkajYKQkv5LqgoGBNQpsztRVB6mBtwcKl+OR378Bnj5yF7TbboKjcKwHnnnsuzj33XCxevBjz58/3jtZuu+02bLXVVoVkjxOM+V0655xz8JOf/AQPPvgg1ltvPRx88ME499xzsfPOO/s8S5cuxec+9zn84Ac/wLJly3DUUUfhwgsvHLUHUybJcp41gIhwm6TnFe3zypUGYACFnmSdY2jL+dm89GbjTLJdOemcbCbXALyKzebiALypeE06kGtnMm49jNt52V1HuJfXFQxpLK8tCTfOXHy4tqbj3VoHb+O1JNqqSa6lctUC5dUz5AlTam8M2zlm78jKd5YFaWOiINfRTPO70m1JzuWpE9adEm1vEu5ItzQfb6jcGZItyxsRBiHB2eNE2+YIdi/yL7Ylv+L7bR9jYeJPCXdTfO9zlU6qCcH9mMwT2p8tfpzcubRCRLY7qo7mZU8Q5uITVdfPy2aCzUp3De1Zpn07bQWMMva7EJmO23d5CNaArlL2m9ABLBF3yFnLyHnZ5MzHa6PRrSsRN1vEvq7dg2cA1PJhyrRnKwHOjO740Q3ELwM/176R+aa3v8dt54umlkiSLJ2hcX2Sn0rX02sV1yI/M406pm3S652Rn6PcyxWZjMeEOwrvhfBcKs6LQrYLCgrWLKTO1DbbYCI+9+O78cKikZmUt4HL+Nq1j/i0onKvHEyePBmHHXYYDjvsMJ/2xhtvrL4KFYwIeRvIFcD111+PT3/607j11ltxzTXXYHh4GO9617uwZMkSn+ezn/0sfv7zn+PHP/4xrr/+ejz33HM44YQTxroq3gt3SrJ531iByXRqOu5JeB+T8lAnqWwrFzvbmYtDxs9WsedxCs6XpKl4WIaY2c04t67jDHj5ljKd4+iHHmSpH1RTEQr7Qjq5vL061u1qr1CifTn5fL6c5Jhc2QMpxYM+VqMh2Ypa26NBsuVgQtoeiNPlcblBg1H/U+5FogaAJ9lomuSyxYh0PMj+EOx6fiqHVqZhuRI7LiRhmULRgFu/ONoS0hEagMx7JzKnD11O3W15D7NIzbajczXzxaR5BA9m3204Mi2uN/tiDXj+MUBPR44JJJFmj+MFBQUF4wXsTO09e22FQ2Zthr853oYGW1mfMp7PfdW9z6+kMxQw1l9//dVdhYIBMeaK9lVXXRVt/+u//iu22GILzJ8/H4ceeigWLlyIb3/72/je976HI444AgDwf//v/8Wuu+6KW2+9FQceeODA5+J5yDL2derQrOfxQvlOnafZcmPITr3dlibhwUycnaDxtkSd+cSxir2crCpdwyrbS2kIJlG0OWb2MtPBm/UQDCksrTtY7lTs5aayKjaAbl2hWwfTcY6PXddMqIWHcRKd0D6KIwjOxJuTgzoWkWhvMs7HKaGokZBGVUT00g4tkz9p4emFOlllFubSYylJVIjItYyd7QtItsmR/pSI9uINjcoMPFDQNhDRcmyOLMty+vxXlYMmykhrBtvQ3tqbFUYjlEYVVzdSKJUvQhBEG99cpco237vEZJzJDjtEs+biwSkaK9qT9LBVolUwHffvHgFQbhDLndN6I1fQ7iYPqRrDqABqeiAfgrFztmtn+aKsSbicvy0HvThmNnv6Z2sSq2Zr72kcUtGWZtaZB6OvqbRoQ3eAuBFphqbiTayEi2Mb72FK0uW9lso2JdciBgYaanaOgPewlGnOQZf74ku018XXQkmYwszxKqjZPvyZMBkHpI+AomAXFBSML7TG595oIpZ2DRa+MbxCajd/gs/++f14527Tihl5QQFWwRzthQsXAgCmTp0KAJg/fz6Gh4dx5JFH+jy77LILtt12W9xyyy0jItoMafrNZHsQMCEPZN2yrsp11HsfG0zDZUivQdVrAH4+toyVnYbxMqQjk3FLurWdi022Q9+lYC5eu06+oZy5OEJnHwhhhQD4uaKMTGdXeub1DpUGIYuCcNsPsYoJK5Nu7hwLMm05uNvfeq54mfLqBkGVwpmYow0gay6eJdmyDJm35bztJLk/qc4f11zneraeu639SK4Gck0aUCTmbYMHQvj+x5fRMANmQuXWG+G95MGQxCYm3B3nbdyaj5swHzsJ41WBYoWb30X34HGoPrYcMSAY9hruLV+YXNcYBjCkawybCiBBrigmWjJ2dvB/oMLcbFIwYqCLDBIv46qp/DaaqDmKRL26RJ5wtpNrb2YOkVeW70fSYgLOxcVKdHK+lGQnar1K0yHe+fRSWtKzIBdIMHxs3LXkXtAeSL57Ie44GubihXQXFBSMF7TF577m/gVj4kCNADy/cCm+ds3DOGTHzcq87YJ1HiuVaBtj8Jd/+Zc45JBDsPvuuwMAFixYgAkTJmDjjTeO8m655ZZYsGBBtpxly5Zh2bJlfnvRokVjUj8m5KkCPhJVfGTn06iUicJ5AWKONgLxZtPwGsoR7uBJ3JBTykS8bG9STk3T8ex8bKEsBXPxnOKjRBJ3YC0TJhJkm9mxgHdolmlKpciqdPKcg36L3X+CVFGllnVf/zZyilBWUxVGs6A2wpvL00aw0adcgeZx8Xqrgp0OQLQ8054ye2IiY56LNoXkadSUPKNKJ/Uc5euUC6fH5tzsK0GG2GPLkkEHvNo8kHsLF+I8VU+P4xKsbAPIhs3zUzYidTf37gkIvuzVf1KDKd2AGL1C8znLpaXHDnSO3rv949lrfGAQUi0HcloHjzLXO0hTJaNHbbGzCwoKCsYrcvG529RurZqO0AbBN/77UXzjvx8t87YL1nmsVKL96U9/Gvfeey9uvPHGFSrnnHPOwdlnn53d1wzBM7Jp514BF50xrSzZ1tDQA6jbvVCT9mVrmIaKbYm09S7uHaBB4w0zAcPOTHypGQqOz+qO8zauvYfxYWcubkhh2JmLEwVzcWMUjDMhBymYWgUFWzovavuYiqYlt60Ar2yDSArSzcM9j6NADhQ7RIMji04jZWLLCjaXq4QQx+cnsR98DnjynXbYJZn2BFuHgxuO0VISDrE/JbGyrXLkut/c6kajtW83FPEMsaY20p0BsdppN5wS6RyiGeWtdf0lGNHmbp8ozOdlkh7dE0ryp5epYjU7UrV1jSFllx3tlGyQd4CWWpX4wTIyXs2G0n6/hrI33Xkg5/IMKUADmqyZuIa2nxUDGEUYNpUn++wfgdfZj0Lt3sXaiLjZtQ7vXGIuHv0GhQoEnaSpgLwnrUSU8yWEtN9xQLOOab3T65HPTsv1ZflrNHIWv9PRIEOjbIXI5qJXm4r3JCjWCd9WsddxTgOalg29QkoWFBQUrMnIqd2vLlmOT3/vDgCjGy8v3skL1nWsNKJ96qmn4j//8z9xww03YOutt/bp06ZNw/Lly/Haa69FqvYLL7yAadOmZcs644wzcPrpp/vtRYsWYZtttgkmm65bFMy/B0Nqbu5NyUWoL0MKUBod2BBA1Qp8G7yzMxLxsp06HczFO5Z8mw6WUQc1m4ebCsOkA8muKz8PlEMIWdNxS7AJ8B18IucMLfV2TBBEG+2sj8mcCR1fO1832RaHS1NLkRp6y8zrJakOu8Jc7bTz36L2eeVVlJPmiU2s82p2HOqLWo/16VylNC0l2K1EOX89KRrkOnPOBsFutEFPxhHO5awUFCmQJhuaSZOfWqAy15q9DOLnxLVRg4AlN1QUol2Z0hka+z7gedkahCHdDSbj7PE/c53SkoQ9kXNc7QrOhJxJtyLAxdS2RMqggoIRCrem2MmidH7GUzjCYJcOXv15ukY/E+tGQ4o2omSJDPHM3ZAcqR7p9ywltZESH64j6wCtQcaVvzyJaJAsqaMcrLFe8dOXPjSUNK1vNb5ITF+UeO9Tc3HlljlT8dTHR0FBQcF4RE7tvkiPPlQYfxWLd/KCdRVjTrSJCKeddhp++tOf4te//jVmzpwZ7d93330xNDSE6667DieeeCIA4KGHHsLTTz+Ngw46KFvmxIkTMXHixOw+2cEZNIa2PNYikG1fFmkYRQ19vHbK10iQmopz+QB8vGwAzglahRq2E19TmKs9TJZsh868Jdmpp3Hu0MeOzgLJ9h1ckyyBVhLrO9A67tRahRoDddhtR5cCkfadfkHwpKot66IER3AEnIl11E/uVQfBbdL1SOUWBDnKgybJFgJak2C7MvLqdrNuKZoDBRlC2qgfNffJY3veo0wjJtet3KBIdC9EfaOxBflMsBrZ67SyuglhaYtvH8enH9w3Qlp2GGzTolyNmuDmdFfZ70qaxvOA+X007prJk0PhaI7bKF3PISGD/pjRkuVVidx1yUe55bqzZDu91oi4K9fIMdnmwtLpKxHxzo1tZNTrgoKCgnURqdL95O/fwPnXPgyg97+uNjzvVO6PHbIdjtxtWlG4C9ZqjDnR/vSnP43vfe97+I//+A9MnjzZz7ueMmUK1ltvPUyZMgUf+9jHcPrpp2Pq1KnYaKONcNppp+Gggw4asSM06YTII/Outqnc0rkRm5wPAxgSnXaOrZ2q2XWkemsYjterAOu52JHrhCRIgg0gMhdfZoaw1AzBQOGNegKWmY5L72C56WDYVFhad9B1cbSXGxsje9jF6jUEq26z6XhtnTCBrIrtzVZr5c1WlY/fi7jDnxBRH/PaN5UjXS6P8nJ0XkVS7nhLkh3zUgpKkzcltxndedgsXRA4pJ1jIWRF3FxUI0uugcjpWaxoU7wfyBPsLAmnTFpSZ6A3iU6vM5fm70eyr43ky7rlypfKIzE7VKDKqdl+YAURaVZG3LccMmRSUSDiSp4XQTnkpZY/kDcT92bjIm62d06oQlivOhkmq5S1eTeonBk5AHLOD6kCdLcxB9sohSHUqBW5wS/lTMh19F1h/wnewsQo+0766RvahvKOLEjQUH5znM42jxINn2lnhf5ztseaMMoBun6WRIOcusmP7TcA9lkj/0lVwerCKP/OwllegHjpykpNLhzxbnyf3HuiRFq/kF78DFSKQygOcJ0FBQUF4wyp0r3ztA1HrXIzvn3Tk/j2TU8WhbtgrcaYE+2LLroIAKLA6oAN4fWRj3wEAPC1r30NWmuceOKJWLZsGY466ihceOGFIz6XobizG8/VHuR47tHBd/K0Csq4VLgB23HXqB3Jrl2a8rF7JbyHY0fIZQc+dXrG5uKsZDPxrmFV7K6xXsW7pP01s2mqD91FUsVW3vGZVbMh5oaquLPP4wAER6rcppQnFaAUz62GMyEHBus95xUh5dIpY3ecE/DiCZoIBFsQal+MVMNScpsSawU/rZ9Uky/IvK7omHTLdmqktdVhhMQ62W5Vrrnsxvl75I+QyNCw91yxiu0Ju/LX2WY2Lqvjbxsru6OAjG/NSN+71AGaNxFXFDlzyX0nrKJdObNwbdVqNiNHCAuWQ2RCLi1KEJRsuPcSQI8HLQ/fhumLMVo1u9+zMJoyGengQVp0WztSZj2ph7eK4LYADwohfmwB0Z4Uj8Ll2rFPRXlmSzENLygoKLCQKvdNj76Eb/z3Y6Mui+NvX/TBfQrZLljrsFJMx/th0qRJuOCCC3DBBRes8PlYcV5hKJ7jbRUu9u5t52Xq2Omagt8PT7hd59x1+irUXlGTpuM8HzuQbGsaDsA7P0vnZQ+TFqG8XPguxF7GjfM8ziTbm5M3SDYCqXYKmzf1TUVPy4a9WuvJtkbo8To24cN98fFCmYyX9jiKThTfB7/knyTTUYe5ZX9ESuOymTj3i5EtFW2vYst6IRzXS8HOkuskTwMNDtZHvZblR+0n0lQmb/aEogF51V+n8m3h589LEtMDkek42WcleLrvXUDkedwp1nF4vfzxqaLdKJMDggOoqfLE3ShjyTMFB2oVOW/nyjpE0868XELO0abGD5GSbduknZD2xGgJ9srAyuSeFN5ncg+aAnj6PLwjRjfwR1o0jOH3UjxfI2yzvJ+JlqoOQt4LCgoK1iKwyj1n5lT8+x3PYsHCpaP+lwYAf/3Te/DmsMG0jYrDtIK1Bys9jvbKRJc0KsGaRhqCIJ37aaDQgbFehZWBZlNR5Yg0EaC074QzMYdzpGTge4DxeVzs3uBpXDdiZLOS/UY9AYYUlpkhvFnb9OWmY52fkfUu3nXzs4e9wyUVxcv2YbxqBXLO0Ly5OAGqa9eV8eMElvxwc0iiqp1Hcc3xaZUXkjzJ1LYzm8bdjRwJKQB8PMjP91WgQFi9zWgiUjlC5zvdch1in1SyGZLs6lBWlmCrZL8oI0euI+Va7pdtI8tI27Z1gmqfbS4/V3aOXLeY88uywvRWS14CIXQO0ciZ65KyjzgFsk0akVf4XFUl0fQDO7wPYR+JG5gS6PR9bZu7naIWZbL5uD25tqzNXiYMCDUUNBSG4AbetLLvvQaGyb7n9ryVLzNygAaI2Nlh0AuEOHa2RG67X/9idZDtkfagMvmzfJTiZTrsA/+suT2JWTibjisIqxv/EQkDRM2RxCbsadpNxmW/z5ByTvHsFANFxet4QUHBuodKK5x13G4rHIf7lSXD+OwP7wJQHKYVrD0YWSysNRA+tjQyXoB7/OyxwRQ79WBuUhVa/CKFmpVtUZ9GHZGYjZPyMbIjx2fO2Zkl4trPCeX8fK18nmas7MD2IiVNmIorp2wHFVtBOdIdmZObsN9Z0QaSMIKvaK7TKj37Ng9I1qPtQIob6nFaRo44D0qy0STZJI5pU6TDfpFHJT9Ygt3wDp7kaWxH15cQBv9rV+6sOieOlz+0EXBkryVnAR21XYMp5aveBqJmZZhUyznb0f5RO0OLy6lAPia3LTdW09vIfeovIlWzw7uJsBxF2/SbC6367B8TiO+C3e7BWkdSZuYQ/1hFFgEqHrARbduwEpDtLuuZ1lm1vAMjuQT5DS4oKChYh8BxuKdNmTQm5bE5+VX3Pj8m5RUUrC6Ma0Wbw1ZJmAF7dwZi/rVweNbRJpBZKHRN5cOA1c7c1JCCUVaBrsgATv3WfrJv3myVSTQr2RzGi83F2YzcOA/jTLzZZFwqZ3kTVXgFjVU0GSebzcWV+8EoqDrpyErw0KR2c3Rrcute0nYqJMesjZXTpude5edlM/ELyrjoIKdDoiqfRgidY65Oo/6S/HlFe3AVO6jtYjtXdnZuNNCIZ52r56AYyIQ8XQ4+KuId1fHBss3FtSpFIO0GZ3hdtGPj8ihZ50EfFW/7gSHADyIxZKzqdFANEINZbFfsUPcgPt5TuVO2K2XcFBAFkPYm5DxNgz2QR+eVg3SN9zE1Ge9946WlxgojVw6fwKvBLefqVYfRShUZSMsG8CkTddvvk/UxNsFaUPD1uLbWboqLM/NvfDeS57ln/VQzfrYhJE+AeFbV4P9/CgoKCtY2jKV3cs7/pX+/B5MnDeHA7TctpuQF4xLjmmjXRkMZN496FGCibRUy6wCt66ZeakUYNhWGdA1QiJMLZedWwwBDuvbq9rAo10BnFTaei21IR+biS82QMxfvYJnpOCIu52VbL+Mcl5fjZsdm44jUMyKIudmw3sVrWPXaLWEAXSMQH9GMnhNUCB1vJrdQlrRqCuHBMvfAOxIXndWQBrCXp0DSKHSgBan1JsrcsfbxvRATywwpbFOwG3O0EZfnPRln9odt0Zn356RGWc2GGeHzmisnIu4jMTHI5JUey7Ln4bBsKhBrQyClXOhpZs3gUNShfoI4BadeNg8puEEfFaZqe0uNeM4zEFuZSPAAFs/b7kWugTgsGNetUm5wjOw0DyiDIYRwfrUj720xlKVjwtrwexiuJ7IGGUvVc6SkueVdbeRdUUKdEtx0OzmvJ9nyO5Qb+AOsHZavpxvZ8YOmyif5gS4tLkpcf+p5PJyn98UbUtZNhQpO9ZR/RktHsKCgYN3FWHsnf+3NYfzpt+YWU/KCcYtxbzoOAA3T6SQt/bUh9R4sYU24dbSv9ubdnN5GBLQ41pqMt9aBgml5ao7aUPEkMZYdeqC9Q8/puc6tJwQqtiz2eZPwQ9H5Wy8pUbab26OCJNMyLU2XTSJJcUKQJYmOiDXivFmSDS6/mRbXmdo78W11G+t++2iJQHpYdN2Z+9CrqDYi5QrJPUvZKRmZd8mM4pMmiTebh+ciCTDJrnJkG6p5OX2+N2sMxriOPUOMtR6EvPJM7T/+foVvV+a4EaLEzC4oKCgYOxy9+3Tc+MUj8P1TDsRHD9kOwOi6NcWUvGC8Ylwr2l3SsM6JclJsD/gOvT3OKEJHu5jY0Oga26nuklWubcgfglGErqlQaYNhVBhCjWGq7DxOA0B3UVMFA6uQAzH59t7FnYk4m4tbFdsq2l2yarX3Lk6sYGtvRk5oDiTY63HpBsJ03F2vUw7ZAZoiBBNyEnO0GZ4Bk1WvwUKyU4QMoDSbxlJDsYpUbJ8YJGf2T0TRfGEXTortjznNKW3B1BxRuZScO1Wme6rYGk3yjDbFOyHSrJjlCHHbfOlB/sMM0teX6n30zCcHO3kvclQn8iu5j/O3CZ7KObPj9laxgk1aFC/vkVS1wUpvGMQBH+9UbMXWGk4l7prKTukgawGiFTmv/faktdIuHJ8O8bF7IDufWzxDxj1/Gso5T9NNFRzwA2KsZhunxA9MsEU7stqaE5zjQYzMzUlUbR9Pu03tTl8Yfob8lBCRnp4nex3imZJF++MJrd/lBmEW676u6THinZPqNpR3lMbfKe8gjffzx4TLGCX4OfWfEfe81matGLsuKCgoGDOwys0eykejcPNXvJiSF4w3jGuinZqWDgqdkCBNQNdYwt6Fdo1ihPMxDUPGm5IPkyPZqJwncmNJtOuLGzdn29YxJtqsgg+bysXJtvOxeT54PC+7apilkrjunDM0JuGRmSohhPZyjtCUc3imahU6tpJLeEWVy7KEW5KiQQghk20OjUZANPcxiqPtz+nChfE2iX2A74XzzHB5LwEmepl52OwQXqZJcp3mh9jfj1y3mYyPVCGT7eHTeuVPE1RI9+a0sk5x4Q31mJJlDqI9HQ+1JNs58VayDVKS59KsubgLzUTOqzl7yzchTnwtQtkNi8GmYVV5j//DVCXzrcOpUoIsSXakTJOx8e5d/Ho2IbfxtbV3ilbBRKbpqZVJ/E66qvRpy0BMA9keNQYl2+kxvjKyLrm8g1WOFDUds8lrlVY1SEi2EZYz6XfGX5vbrsh7vfeDiprcwI8CjAhLOIJ27aVsWx8T/A2ySK2PCgoKCgqakPO4Fyx8E3935QN4dcnygQ2Qiil5wXjDuB5+76Uc9TIZb8z9RLOTJL18S2/f3MlmZ2fshVw6aKq9N/MQR5t/ftt5H68hvIsjruPI2iKXKEgXmpzPm4WLZaODG6mdg9WFzcMlyVaK/DLK21jJFRhvyqZJmyki2e5Yr2hzWQnJJpEn6vmPhGSnx3O6vIbcr3GtqZyZyUMtv8Y+FT8Dg/yQKytTUZUsRbpUtHs+xgnpAoXnWA4otQ2m1fIdY4KM2BGhjBAgkTP/HgmiSAMI5HrcIPk2rFa01SE3mJd+q8SyQeJ7lTvaqop7nP5PKSgoKCjoD1a437fP1viH9+0OYOQGRs8vXIpPfvcO/Mu1D6MeaWzfgoJViLVC0R5YAiIVmZkbV4ZN084ZmvbO0Hz5Chg2lU0nhUqRj60LuHi7pOJtQbrtuZQ3/2Yl2y6Dis0m42yS2nXexaXHcalgt18nojZRpGIy7cN3iXRhOi4tLSUTJiIXE5mJUcrcEfVuPReTZuTORFVxT9mpQ8QnFjFvya0rV5gUezl/YgndU8UmHeonTcNz6ra8dukYTTRqk5hHF43+kCpjjlCk6f3ueetuFddxkPqlBJvQHjpK2TYirfyzRBphPXM+aTbOjtFgrJptlIZxTsVq7aw7VIXlzlkgNKANYUjVNnoAxao1ewcPUQViZVuS7EgJBwAy4njjj+VpH5LE5zxMs1VJK9yzDWfSrNKHOn2gGydQ4T6mz0+yHqnajTpAnCdX4z4PSNtFpkWKAZeeYxvp9ylHoOU5XLnafZfidxN+YE3BxYHnfD3fk8FB7oKYYEf/LwoKCgoKBgKHBRutw7SvXfsIvj/vGfzN8UXdLlgzsXYQ7REe472NcxrvVNbqMCjdGobncTvVGQp+yfO1Pcl2c7troEm0Wb0mNoOtIu/iNVnTcSbXqUrWVOThTbFDSCT4zjOlnVSvcKJBuCNliLMrcbxQkEiuA9kOt4ydHdRs2LnrrkPq4zorZgWIO+ctff+0n0xin0/jeZtCXbWkO2NODpvuy/DEICHdQIaIN49L2YQPP5YlGUJVbLtmW5nmBUvOnHkHGg6pFDIjFQPA3//w7IgTIzLxF6RKDpBALsVzBFLw4Zm4fGdSboxyZNvOve56s/EKlSIMkZ3CYaCgjR30qkAw0h6ZjHsfdYNsA4Jku3VJou088PZmkabCchqHb7Z0oKIFkYk1PwP9yHZUAPqSbT5P9hggsOC2sgZBrs69nmk+h3imlHgOogFAIHnuwqmUq79S1tcGwY6ZELFnfHFs9C0cwbU5GDfIKrc1EJmRj6LYgoKCgnUabE5+62Mv49PfuwOvvTnc/yCBBYuso7SLPrhPIdsFaxzGtel4P7R1fNrm08Wm48Js3OfX3vt41oRcEGk2FU/j7MpY2rb8vEKW1iVX3+hax0pJkZ1et6169SDTvrXYzoVC6llGRpViM/AGoVZJvugYeFIu1eoGyU7Nw5UlJJSk5fLlt8kPIPiBBNEuaRqAzECIigmINPFlpc84R0zGxUYnsZ8HT4zK/mSe+DyZn1cWVVyftG58CRnCTWI7um+IB3iYZIXwdDGB5bnZPOA1TJV/z/g9qqFQgz32xxECVhQ+vB8w5mWvMGiAdd7uN5gj86xK5sgDL7nzZa5Dmo6nA4LRoGFC5nsOYLDVTUuWXt+zNeZZKCgoKBiHqLTCIbM2wz+euAfSbsMgIFhHaTc9+vtiSl6wRmFcK9qD9gPbyDarq+zjCwCMUoDRUGwKCA1DtpPVsa7F0SWCFip2FxU6ukZFBl04L+jUPF8g4to5drJKHZuOs2LH+YnCvG3uyI2KUKed534NxWTbrdMgxwJibjagtfEm49qla2cuq2HVJ+XIb6xsU+jp+q+tTWORzTdB2hQRiUZDxfam4wk57znv2pebHhdU+4FMsvt19OVogolJT0x03WlknvQcKSLCr+Jq9Ku7qHdDZUzP4RRusNk4wZuQZ8tltdG4+24A1PY+17VCXWl0a8Jwbd8JrQjL6o4f5BpSdSA/GgBVMEq7dANQxy2NjZNNGlBAhbqlofKQ87ylX4d0DrkcHMhirLiYLF+akfM5MuvsNrBhSi7r5GViypc3Eoz2OGQINBATZ/Gq+GdR2XfCPYHOeMM+V+RkbUV2f+N8Le9ylN4D0jlaQUFBQcHosSKm5MVRWsGaiLVO0U47v20OlSjJy51jSWilEzSpcLPjMvYWzuvskCk95zBVfj62VLJ9WaJsQHTiEeoy5pBlSq7VqniJZZqnod5SY8km5PFPcGpZnVwlJK9UmZ8WXFXBzqtW1iMxnFds9kbM+/kXhQhSZPNxmk62FUFpCoMDrkylOb35k/VHrvOeI8ue1EoV2inTdUjz4dpqQNWq5YceP5fHtBzr1XDE5Eeqhv6+IRqQ8CKpin/yWr2xgHEDCt7zuIYxLmQSWe/j1hO/dlMsKh8mT4bL47Bf9p1jpVtHZuESOjtq0FQo2YFhbl9f5AaEcsvRIG3UPuq2N1NPld60zFwZg2KU15MSbP/q5BRrE6/7NPe+8PhcOCb6wIyugn0w7hziFRQUFKyB4Njb//axA7DxekMjPr7E3C5Yk7DWEe1+5sqDmF+nJtyResWdd5eXiYDMw8S6hvYmrv5YpORaZ8qPz8/LUWsmqVoLDKbCDlqWKFOK0QCgVe974p2icZ0ipTmo01GhGaItCXisYCcEUDMJR2+CLUh0RLAdgUdCrLPkX16jqH8ct1osDV80ElNvJsIQ5HoEhLqr7E/k1bzddcd1Q/7IvFwS+ijuuqunvIboxjbbwV9ybqCBVDBnd3HgwzztEEueybb1bVC5wSvlY9KHQaxgPs7wXsn53UXstTzN58uJvgeBbLfNz25e8IDLTAP5gYjMr+2YflYOjTn9OcKdltdmlUAt+XshyZu9ngya19ysS9NkXOXbuQ8hTgcO+Rsmles0LRdVoaCgoKBg5EhNyUcC/vz/9U/vwfJufjC9oGBVYVybjreBTcLbwGbjJLYbx6m4Q2qg0XXOzrQmABrDdofdrygattDCiRpjWJiFD3syINVvPVDnfRDVRKlMf5fNsnsoaYMKMjEBtj1cBdcp1bZjWulE0SYFogoGIS/YqFWTi60MS4YNq8ZugMHth0Icwzsh5pGK7RVpV2cmzlxnPj5RYnl/ZE7Kj0W0npSVNhDXFWjeDCaWbALOpBpwirUz1ZbKHcc85/KEwsfn6NXPJ9FWckmZZ6L57DSvQwFhzgXFeSOTcalMyrLS6zDKt4epFWpl35fl3Qqmsu/skB5Cx3kZrxSh4xRp6eSwVhqVMs5svPIx7dnhmY2NbR1bpeTbiLB7NWJfC2zBMkxhCog3FwdgyF0OicgA3kImbVBuk5TQqrit5L7owGYeajSsa+sc2WZrmfxOV4Rkm9ROoHMfjSRvWtcV4aPeWl6FavE7QW6QCs5Bnh20gXDAh/j5y5XvCXRMrFNLHbk+sD+KgoKCgoKBwabkf/Oz+7Bg0bIRHfvKkmEceM51+If37V7MyAtWG8a1oj3SUS6JHIlNlWRpTh6pWhDEWJiW1+In1Wv+ybIacbpbGG66ry3fSJWUBunqhx752Ot0FMarpQPKc7Zb1Z8GAQ7nji492e9Jtdx2pJgUNUm2I/TeNDwi3MI0XAnlWhOU5g542C+rk17HIHM8pVmvV4qZgEpF2xNSWPWZ1WZWqaWpd8YEXDdMxJH9eQWbMj952SmBbtzL5j2iRkMFkhRMhC3hZtJaG0topQk5v29d9w5GUzbAofQsWZawcetjcs0w4nMo1WwuXx4jp3mMCeQARkapzebvRV5TE3E089tj+pNkX94go3Bp3ZO00RrS5JBtp7bBpgE+j25cz65LMi22dabShWQXFBQUrDwcvft03PSld+CzR+404mNfWbK8xNsuWK0Y94p22u/h16ifqt3WOeL4qAyplFmzURfOyylFNVlPx5UidE0l8sblSrKezsvOOlgaiw68JzhknWAJwqMA74jMX3JyyqzpdkJiAzENBDU4QRNL2DYnRV4ElXnZMVrqCI3rymyMvBaX9PtTp2eOPJNQtCPVWijT3jSc012aitZDGRHfb8iKrBRmIEikNxV3Cq6fd02OOMt1SbrdUjpDi0IgZUhNJEz6P/AXld5jEtc60ICMJNzJO+fvnyjDny/z8ioX3ouMAtXWGWFtrFM0pSosryp0oLDcdNAxBhrkf0Ypa0niLE8qMhgCMAwb+ss+9MZP66icozTAkmyeh+3V7ETR5gGy2NdCM749OfXUDhQgvEhyIIGARsg0UtEAhmzbgaCSe+6tc4Tsm5anAtn26jbny93zAcl2NBdcpI8arqkUDVaFlHhT7tqj8qVKzcv4O8ZpOrceqllQUFBQMMaotMJnjpyFnadtOCpHaSXedsHqwrgm2h1tGoTZCKIj943EgZH3SA5l42rz8QoAhdjaUBDk2nrg8WborlcnCTOHBmvM+0467bk6U7qduZ6gsqq4UykJM5NGDYAIpJSNO2sr24Q4lnmBVIrDnOZAnLVTrSttuAgRP5t87Fnv1deVp5gsa3KeqO0+9mStjNtuuTbvVVzOw+byosEB+I51lly3EOtoPjlCHlkff1dIOQ/PMcEiJteeaDtS4hyTeXJdu2qywkxiP4W0dF6qXPfg9WiEwFczJtfRPuXbq0G4+71Ogqw1HtU0jZvf8V4FR7KVHdjqdrVv4+VVhdroQLBV+Ab4QS6l0NEGFRnUZL2QV9p6vWfV2sbJ1j6Wdi1MxpeZIetQzXRih2um8gp6V0zzYKWdlXdvMu7uPYn731Ca/SBKko7oUWtHRKzh74scOAtPcO8CG+bkObKdJd/xesNLfrLdGExoViSc3r1CuUGj7HMpd7vxhYaq33JNOUeGCvxNA9oGDxlaEaDLfMCCgoKClYUVibm9YNFSfPK7d+CzR87CqUfMQpUzUSooGGOMa9NxoF2ZTl8f7QkgDWTq12rKnahYnJcdpIW5nrGCzSQ7LT93Hkmi+zpaakNCCqN0LnsExebIUrSpQkfVbgelJ9fm8TxHQWxFPUPYLYrrIAYN4jSK9sVpMcmOzb/RJNms0ENclyDnrTGyk+tsm5sbLlNFZESRJZwKcGSc09x+4Zwsym/EPmdW7s3BpXdysQ6RR7sflwdKyoycoSE4LutHmnpffPNFjYioiuY7G0doDQWTcQ6RJ6dzeNLMjsughAfyYGYOIIoUIJ2j5RRrGSXA5ml6mZZxwPvCkz/VSIsGTNp+vcrMlpUZ9ch+Ipr1ibbb6kHJsWOIyAqCfz0PsItBa9P4/PQ4MPf/o5iPFxQUFKwarIijNMCq24f846+KV/KCVYJxrWhXLlZzxUSMQmxsoKkIjxaS7AbTcHcOJYiB91Ycwgal5DqNi5126NMwY2MCTxxVIKfadcC1JQdeEBMNRQresRgrxUE5DunsiZsFUCbW0bpbMkdjhUgpFUisUk7VVqLeri5O0Y5MQKP9on6VGGSoBJHWgnkwsXblpAp22EcJqc4/SVlixdYVrGSTAseKBmAV6trm010ExZqJMAHamZT7NK4+rzP5BWLFkLd7gdtOEhcVtiW5kWkKzbyN8pJzNM+XN0tXZFVtOIdWVCvUtX2HlCIM14Ekd5Rxz5UzIXfPmIHy76VRCkO6BoyLu+1ONowKFdlj5VxuQxpLzZD3YL7MdJzK3bGezk1lPZ8LL+hWzXbvsAtLRrDX4S0Y2NmdVLDdYAJbKPD1Zwl4DuKFlQo2qHmoig5TzZc9gRJHZB2mybwpMefsPC0iUrJVpC431O0G4w37W5sjfQ4z5Sjid7TPtfjvkv2/4tedUl1p0/iuMbQiUFG0CwoKClYJ2FHaX//0HryyZHBlG7Dq9qe+ewcu+uA+xZS8YKViXBNtrQgdbYSncEuyK0UR8TGkko7mYEoHm4trxPO9g9Mkg67RlnwnfThDVVyWINit87KTNEnwvUk8KT//m5AneIqvnwm2X4eflw1Y8ko69MoV0DDL5mPImZf7kFlMWp1zMEmmtRsA6bDpOJNsd398TG3A5XX0RzsVWxPYtJo0OdWXQFp03BEIG5N+kibiPDhQJebpUrV2hfnVhmod1mXbppAd+NgagW8SAsn2yrQl2aqrvFk4k2urMLt83UCkNe+XpFsSbQMoCg9HVNW02pIbRQMWYZCDx4h4YCZLwHWzDBk2jcS5SLR5dJysoydj5AckqA7OyJbrYB3R0Z1onqwcBKt1INo1NKBtLOxKGRhlPY8PA6hcew2797UmjWXUwbCpfHg+DiO23HTQNRrLjd3vHbLVWoQjs4Mq8gdJqv20AQRzcTENwBPvtvsmoUIDxgNQ5Im3P1x89HyTk/PynzMVl/nlTUrvF5JtMUgQrikl2/nLIRV/rtIqtT3D6XPZd4wyKce/655YB7JtSXb4tlXJwGFkOu5NTgoKCgoKVgWO3n06jthlSxx4znV4ZcnyER1LsCHAjthlS0zojHsD34I1FOP6yQrzNPPm4GkHnDEIye6FnKMyGSe7LX+qUqdxftvKZgxkjtoG2QFVUX84kFW3LzLN5P1yXRAmaaIuTcdz9yMlqTpzXOvlJ8QwrTc1riGpJ58/Ur0GJ9k5s/g2pKb/YY6qCmREkqqEkEgzcd8sicm479PzsUyy+bjE/FveKtWWxwDKEJShprm4ScoycR3S62jMix0pfHuFOc/eLNu1a5e9kZskVB6Ud1gmzcjZGzl7JGcle5iqkM55wCbqVYgiQPFPmoiH7eSa5T1vuc5W8tmv3cT+7CMZv57t5ZL4OKT3rY1Mp4MB0XbmJU7Jba4eLaDctykh2T2PGwPI71nu/dejesgLCgoKClYUEzoa//C+3UfVt+cQYMWMvGBlYVwr2pU21pSPzbqlyajrDKdUdjQm2QbKei1G7CgNzgt5A8kpUlW6zQFaajYuHbulaJA5oKlG85JlIUWAtiqW4oYhPk5oRxSOJU1O+ZY/R1ilmq1t/GyvAAFZtZFN+72qTcF0XMMSZq+ya1snIvY1numtKwinbK5eFdm42wpuadPZdJzrZjcoItN2GXem0/nkcSPJ9neEEIB0fEZGWXWWYEN1cZzsyAGa+xkRdovTHZnVkWM0OCJFMdnNmCD3GReIFW2/TmGKANx956kHbNXgngG2eOBnikiQHPdYsel/Q3HkQR8pmjqSTbCEn2q24qjQ7RK0Vv4edk14w9m810B54tMhja6q/DOnFWHImQNUQn1kz+IAnJm4VbKX1dZkfLnpYGk9BEMKw6bCcG0J+HCtMVxXlvDXGsQO0Wrt7j8aVgxW2YawRBAqtrxvvW8b/GvrMrOKHZTqkMHvAyLHaTI9Oo4QHpxBOCRbxSTX0VDqKbmulrKlqt2aLX1uvdVFOMlI6G+kZAP+WybNxSttvKWOBjW/cVVRtAsKCgpWNVYs3vbyYkZesNIwzom2mJdJys79FR1PINDgnHSfzrvuBeLyBVG0HXpBvltIfJNo60i5znkaT0k3m5EbiokdJfkjePWHnMk4k2wbPonJcmxfyqu2F87k2sec5jI5/rSbny1Jds7xnHY97FTF1o7oak0wxpI1Wz+4nq8j24qgEg+RwVmavUY/H1sTVOXOo8kTbH+fE3LdJNqBcMvttHG983kVT1Vg9RWELNmKvIv7MF5iPnYPB2ZMppWhoCxLD+RZot2DMHmiovy2Fzd1yMMe3cmvA6SVJdAqDML48RBeN4FkUwVPutoZliiDJ/PXdvDC1IDRGsbws1NFlgYVh+oijY62ZNoSbePJd0fX6EI3BoCYsNewpLomq4q/WQ+hSxrL6w6W11b5Xtbt+LnZ3bpyJuMaptaR6ThkyDb2MB85tXPklC0T+HakanHmfvlVvleS4AoCHQejCwNNvClJN9Ak3miuhvOndUsHd3ydVDYEXUTK02ukhGzLRyZ+1fw3gEl2sHgJefuOryaDbDr5lnXEdBgeoMk51yxO0QoKCgpWD9gj+Td+9Si+du3DIzqWUMzIC1YOxvXTxGbjQN45Dae3Ht+ybyQm2sFLcW/iPFBZLRrW2DpGo1j1STqqlHRY/T4kndccUUVIa5DstuooahBbvy7vj3Jqd5KWM3mP51iKbE45T/dzPeJlnN4LOesCu5HcNwo/JcixVKNdFRs/RMugYiPZr9J80pw8V7YngiR+YV9E4BPTcZ8345U8Io/iOqO2QJKWtlOUZh9C4x5QY6yX/2A6HkJsdTnWNazlyDBpq0K7dJ57PUzCsRnPxzYujBfnF+H4fDxtf054B2gcNzsyraZQ78YPom0gnlHZLr3aJmm/7BdCPg/chkmb55T0tno2nsm0TmmZ7pzyHJLkjxgJcU7JdPrNir4NgxTf8q6rzL7cQCL/CgoKCgpWDzje9sUf3AfTNpo4omOLGXnBysC4VrQ7ukalau+czKhgiq1Iubi5tpcllW1JXHuRbWkEqJ1qmaYBlmxb78XKpzfnYyufN95W/nwyr58HKtLSUEc8J9TPDWXTZe7cM7jTyZburEpK2Uh2TCH63NLTuAaoIuvV26nGSls1Wjsz/srFNrfxsmPyqsmRcMA5FQIMm1+yoq1smUSwaiYcg6mDvBV5QfZm7E7FVlbBZkVbN8g1ojr1Itbtjs+a8PcCsN6mKVE1DSKTcW8+7B2gqZiw1snSAKoWpDkzB5sJMyDIbbKeg0o2eDAjVrSVT3PCcTSNwFQuHrtyoYTZpLwKz44/GbkVHuzxD7lNY8KqDJuPK/cYaJAmGK2AmqBUhTpREzn0V0cZv+zoGl1dO2JkMCQUSUYg01bJZoK9tB7yHsbfHB4CAVje7WB515qjd7sV6q5zhtbVIHeP0XVMUN736L6p3mb+vfiaCnkiM/Akmyf+rqnZrBxhAe84Lbo3STktRDWraIsDooEkmYfQHHxJT9IcE2jsi6YhKIqnNKjwmAXynSktGTWIY2eT/57xr1IGEypnLaHqhmWEqrq5GhcUFBQUrEKMVt1+ZcnyEmu7YEwxzom2JXaGHLElHfU2a1LeZDkl173MvHPkW8775HwAAMVeybUI6dVWdojrK5GS7BQ5cjdq3YSbyZn0BpIDO+c6PQfPe9QUhdBik3FLko03HU898zKsqX1YAky6w3xbrQGjDRRVlmlrNsl25zVJO7Dpulhnos5lKi2UbUGu2zyJR+tJ05HYH5vvww90kHEDHd5kHJDeppUwHw7OzVISllnvs98r1ymRAa8LAp4BRe3B1yb2iY0ozJojcJoIVDmuVrmBHzHHW5HjlXweDZB9MRsPneL2JTuHn3hOCMG1LwClUdf2fgy749nbvfU67t5FrTxpZrLU7UG0DVknaxyfe1ndsfOy68qlWy/jtQvjVddB0Q5hvATJNgnJ5vnYBrHSG5HO/D3KQXDu5j4mqzl+6ds7mZcNNB6SvkYd4uHJKeRKlk3N8hrlS8Kf+5TydTnyHMh2C8luOb4N3n+ECiEKOZRcR3MouZiAA/b/ABWv4wUFBQVrBFjd3nnahiMOAfa1ax/B9+c9g785frcyb7tghbBWmI6HX9yBToneaJAS3xzp7eUpfIXOlTmvDPmVqtk9Td6FUhmbjVNDDZJmmYFkw5FuJth2vySvWqhq/eYtRh3UhPiG8mU94cl9+HE6ApFWTLCNHwhIw/W0eRLvRbIlsvPiZfsL4h2bDst1JleJ53Gk+xE9CCk5U+m+hKz1JNkJGQ9luwsQ9Qgm4xSdO96H+PpSc3J5PdIMXaa7Nsq2iQntyYSbn/+azcmdSbkNw8Vm4HbedQjPZRXr5aaKf7XMW3lyzY7P7Jxs7c7Foby0j5cdYmYjkOykXfxASO4+J/c190vvW3SPUqIuiK5qOU7e+3C8GtEvOj65b9F7lMnT+lluI8iSZCf7JOGOv2/xsYOi7f9ISrL7Rb8oKCgoKFh9OHr36bj1jCMxdYMJIzqOY20XU/KCFcE4V7RrGxfX2U12SUc24l2jnZQWpFoD2zn3DtR6kNMQLdvBq3OZYxQQbG3hST8jp2ansbMZafzssA5vTi7NyP0PTPCQl3IUfFxqGT/bnTRcMMn84ThiZ2MVQVXGOy6rKoNKBY+8bDaeC6/G66TYeZpBbZRXtKvKkjwCnBdrK5+SrJcvDMGTeGWsKTsApY0tB6xyustJyLS7xAbSzrJ8RqSHd++wzig/d7hBuAjBAZo0886p1AlBjYiZoWxe3sf3TY6lNAi23CchthXCY8FO1EghONJTAHG6hnWIxgqkDvu9l3JO1068dtMCgrrtDpZESCmQsZ7m2fO4vYlkTbOVAmBgVAUo8veiVoSalH8Ga/ee87MpzX/lvY4cDiKEDfPzt41GbVTkXbzuWnWbamsyDlLWXJzJtTQXl1MFkoGIiGxKk+v0Fvl7IjIkr3DYH+6pJJ/ZLx3Fr5VqrPRAUs+UVMtlbpCgLydN6iDNxP129NzYH7l1ub+Rt+2U/psFr2ZHJuRwqrZfZw/2XKe6z0UVFBQUFKxqcAiwT333jpEYjYFQnKQVrBjG9VOjQRjycy+pqTKsoIrdywO43M6XoaMfMJjy3WZGLr2Nc77IbNnvyBSaU3rYi7QO2yRCNTXCeUUm41xOHAqHkTqok8gR8FhtJl9upEpF5xXpYh/Xw5uxO5Id1qlRRO7ZGQniufEIgxzREkF1ZCImSXSq8CXr1qkZorJCGRkynSPSbYSntdy0HqEOcSzvvEM07yyN88sBBkKidqtGW4TzB7N7a45tByzsgAYvNepaW8/fjhwb5xF8uK4w7FRp/zPht6zu+CWr2HyMVbMtye66c9ifMxc3NoxXULF5MCWQbD/Qwm2WOItT4hqzqrC4b0rkT9Xk7L1E815m7zfyr1bfZ2SA/K1Kt38OmQX3RpZkA55EZ03GFbUX3eM9byrYsdWUJNmVG8gpztAKCgoK1mxwCLCpGwyN6LjiJK1gRTC+FW0V5ssBgCYlSJyBdgzTKOKQzD3JsctijxGqd2NOtwqOvdJ0oLeXbS57UE/iMoQX19Gbiyd1z3q5zpXpVG0b2otEaKBMnRyJJTbb5rnQHPpGh/nYlSOzgFSG4kqw3pM1OVfBtJvgwnLxTWEVXkApBEVbW3Nx5QRPzSG9dBjeGAuzzubc7DDg0SDZgG1nSW7lEpntHiQ5Wx+lPNm2J8zkz6X1ApMhwKvVTk92KrO7X26ev2Jp1d0uGLffOU7z0wKcI75IeWSyrRRUHSwZyPCZ4Pz12RBvXt1W8CHqyK3X5E4K+GkSHHqN2NJChdjb6RxtcsvaKdqGYMN3OVPxurZzsW0oL3e9UYx0JtliEEEMrDQGUji8V3qPc89A8zPj7o0rQ7RV7l7LN3vQR2GwL1SzwGgwJ5MnVfAb6fIw1czg1eno4ECyU5NxSrZHC28eDuGLIho4NDC6KNoFBQUFayqO3n06jthlSxx4znV4ZcnygY9jJ2kXfmBvHLvnjJVYw4K1DeOaaA/pGpWuodkZmvOqbeAcH5HtXGlF3jEaO+NK5zPn+oY1WUdd0pFSZEZOCsKwPEAUzaS7l5rtPaMLpZwJtd2WhE4lanaQdOS2517KkSC/dNepyF9sMIWnRqeevJJMQIe8d2+tCLoywuO4VYuDs6C8OqzcoAd3VDmt0sYRImuKzs6wTCXamevJ9dbW8RmcYl1VwYM5E2zplG1QL+KpVQGJdO8TzJEvXx2+R8k83VjBjEmXV3LFreJlg3z1gb+17v7ZhW1DW2i+PJWO2PjyRF25PP6jXYLwYg9HtpW7dCaT1kEUwr3j2RxAyNu1ZdgoAXanhiOxzuaGXF2og/AMO+99hgyo0s663MC4qQimUsGiQYUBoVixtO+XPYcLFybesUCuFUxd2Xesdko2ITYX7wqnd12paAuinSj4vo19w6c3KE73RFqFe8M7SIl7FG5JXK5CltBG5xoUuXLaSLffP0JyLTJKFds/A8LhXmomHszFyW2LFwxiACh3OvG8hO+ZnRrDSnZHGWhlPOG2dR/BS1tQUFBQsMoxWjNyADj1+3fiG1A4ds/iIK1gMIxz0/EwN056u5YdozTE1CCQijMl6Tx/OheWK1sW1EAm4/Icue3UCRqnybnCfeE7mvGPtI1PTYoa62knllVk680bXpFOiXXkJAix8hNVCWgQoMiEnOutZLqsP5uuh/3SW7BSTXIVnb9lMKAXIosCP7ChPHFqKpJy5CIsVZq/F7nuVSVZ/AoodlGRLQTcniQQudw1RGnEAwfCjJyXGWdouWNz6fFPeVNy49atszLtnZYZR6BrE0zMjXNuxmbm7EgtOq7V6Rm8czZrGu6YnZyHT/4RjeqaJdnpc4BMOpL8yf5IKfYWFaKNZf7cs9qzjVuOaykrOmdSp8a19ENLxsZrJdTrSPXOKdkjfE/arJQkydaOeBcUFBQUrNlgM/KRxto2BPz59+7Av1z7MGoz6D+xgnUZ41rR7ugaHVUD2oXyIuU6OloQOwOteI40h+Kyilfa8WsjuanpOAt5AMBm5DUpF0A4RmqempbfNt8754BLrkfexgFhuhx4UASvhDFJUnFns0VFCpOZ2QGaMxt3qjE7CvKqIdpJLbcH3wc5R5tjamtFVk2Fi60NA0UKRiPcL56X7MzW4VVsEWLM3YtK9/4QGoI3L5btm3eAFlsUgJS4D0h6/gpZp3mNNkakNrYS6vReedUaEG7Dwm32S7tHycSRwj0GFBXuzsoKqX8IbTspIDYVd8ezt3r/83MJeN2p4or8MKCqlS2bn1klLoPXCfBO0rSrFIXwbj5Gu0o83PMlkrj3JtxXY7Qj8gDVOpDsrg51Y2dntd32Awo8kMD7Cf7DkQ5QNJXf0GZ+W4WmElkiyEuj5KWO1O7MuVYYPZ73UQu97sCUOEt1m0l2fByyx/lvWpKvZxXEYK5GMBkf0nUU6quCgSnO0AoKCgrGBUYbaxso4b8KBsf4JtqqxpDr2GjoYDrubFON61F3lEHX9dpriolz6n08pw7XjpizCTqbkpMiO/+b1VyjG450cnOx2+ZopyQvJeLMZbIhvRoddVE+s6yo007tnUzZK3am2cqZjCs2Fa8MtDboVLUl2gAqF9ecr12qO4Zi4wkm5BpBedZQ1oTct4WBUtp6uXaqIoDgRdzF7wbgYnnLegTSnULea2k6nMKLdsKSQDqgY0/vXlVtUQkjVda3cf6cESkVBNzzSAhiYZvIkWAFZSjs43TEZDuYF6P5zKRVIR704O24XiTLcOSSlCOZgkx7fuyfuYQxumvzJufamZFXlDUj57pTJa5D2zncRNrO21d2GoKti3gOehBtP3DC5yNeqmQutvMiTwBqR7DJkWxW7GtuExU7PkuJdh/IZwCEaLDD30dZlCTkuedtrEwe2jBqQj14Pkme5bvAanZ2W+QL63FlQ9zxZmVk6Eg5V7uja1QIHu3rzGBrQUFBQcGaiRWJtc3hvy764D6FbBe0YlybjjOY1EnT8ZAed6ZWxCtsL9WZkYbmGk25I8aAZuweUYeT4p/07s0k220rT5iaRebMxuP97XO3FZK51EA0YJGG52rEvBZ1y83Dbc7L7f0MpPOy7VIMcPA+YETEJc3a91B5n4CmOueWfqyFG0Gmp8ePrMqDmZAjcBb7GMWNFA00iJ9K0hrb3tt42/G8Xy7DPHkfa9uZjts59Nqbf8c/HQazmGSTSkzF0Zh/Hzk9S+OIZ649usaoneNf+/0I7SqX0TE5Ek+r6LcS0Pq8pumOVOfyR3Onk/0j/frKQcQq56OjoKCgoGBcYbSxtgnA3/zsvmJGXtCKca1oD6kaHW0AA1Sut1QryxCHdG09AytrYs6Oq4wggdRDcW7AqdisbnvhyOiGsq0p6yKtUT7H7ZVpOWU9xMgWZsv94OVHX4rYly4dwZXFchqHzlLOgzfHzdbGK8c8wNFRJiLSbYo+w5uRq6BuW1Pv4BhNKeP4nFO2Rduw+bpdN96EvdIUKesMviexszNJppuWDU3v4k222vN+sKIrlMhIrXZ5JDg/wS2V88DNac6bN6ucrCSz2moVbQqitQIix2g5pLsGHbMh0RT+pXD1cksCYpUb5EdGSDnFWsXH+jJIwSjy7aG7IW43uWJQuUvzbew8lDuVWyl4j/VKWnfI8QBhGcIqtm9PdmRnHLl3JuJWuU6cnrl1zfuZlCMm2P0U7UitTuqaNlOaHi6qB0ntgz5jUX0x0HllHkLzAlTeAVp0rEuPXks/yMTEm5L85PepzLevbepLY9DWfe8A+79IKyqm4wUFBQXjFOwk7ZPfvWNExy1YtAzf+NWj+MyRs1ZSzQrGM8Y30RZztAE4c3ENowimVpZgk4ZRCh1Vw8Cuk/NGbhy5y4Xw6mlCLtbhju9oY0Uut85Tg9sId6781AEbhxhqO96bLkc7ZI9RFJZ2NOE6l16KFB1Ml5f3K9h9VccR2UqQbEdwPVn2ppWB6ObItp0jD2+Cz3Ot7fx5OO/kbA6swOQbooXYwzhgnRKxubivT3JO7hSbtJ0QSLZse7uUJDtw1dS7ey8OawmDCiRP3AdLol0ZPC4iSEUg3cqTAwjeEEX24nBbTOgRyrPrroxBSFRKfJif8uHyMZNpxPWzwcAQqmyJqhjcIaWC43IFN9cZGc/lLrQbAai4HvY9JmXvgXLep0nDfQ8Ux+BzREv5dmiwSCbVfE4Zt5uvx5mOK3LX0TIX23sdj2KNh3by6jafqw08mMCDMhnS3Ua4o2JWkDBHJxgBae83kDTachtm47K8iIhTeI/8LzS+EseMxFEmOzzz1lNiULFSBlVxhlZQUFAwbnH07tNx4Qf2xqnfv7O1/52DneNNOPWIWaj0KEe4C9ZKrBWm49J8T5ooV8LETyLtWPUyJTYUz+GVqicQOnvpfGr2Nt4rfFSqZo8J0mvJdDbZ1Fp2RlW03iTZ7FQq/cmO5qDIHaPEPv5GaXl+BTRNwhHVJb3sUF7vujVCvQmSndufQ3ber1TSZMVyxSXKXPYYsY+Sdf7Br4/dM9XTfDzKly6pXbklVy5zn/SHNF2QXpHuya7fTkizJM5GbMtflE+QbCB4FE9CdKV1SOsY7RPXotK6Za7b7xdtmUWap62te6GtHm11GjRvpp4MwXdHVtW2d8MVSpn3pPVdA5JvSW8njjnw/50KlmBzdIWCgoKCgvGLY/ecgW/8yT4jPu5r1z6CQ/7xV7jq3udXQq0KxivGtaLNztCMUjZmtpPHakWW6LLpuLIelQzZ9K6xGY1SkbrJpuEyfjVDrmuooGg7E2W/m9hslWUsUb7LJcN9NUyV0XSW1jRnDnURAldI84oPNdKkcyBLoOF7vTphSoHIwivZShE62mDIrVdu2zoGMpBeeH17OaXaDoLE12bNLcnnYUVaORVbufuhIidp5OvP4d1YXee0HMGWijUjMheH8zLt2riVcPcxFU/Noz2J1iHZr0szcJfd7xPrXjImrpxd9aSPswhCR1r5vMpnEFUleeAYg+AfTgUE044GCbIZWcVWZJtXq/jalbbXY1VsWGWb70OFYD7PiraCNx0H7PpAdZZknRCcnrl1r2j7NEfGOV2GL4MYCBDlc7pPk+3Bt4TXFYKFQrIuj4+ujvKP6CCkfVSQ5xLltL4m/P2h+Dp7lp88N/w6+ILkPvnOycEuScRduh9QVCKL+B7mBgVlSC/vCA1W0S7hvQoKCgrGP47dczou1vvgb352HxYsWjbwccVBWkGKca1oa5CdG+eWPE+ugkFH1S78l0FH12H+NMRcavFr6+elIZ3YnJvn9tZGe7Imf7VzrhT9EM/J5l97iK+4HikaKq5XpSVRDp1J37nkONiVMPd28691ZT15VxW5pfG/jrY/bzLuSLH3IJ5YEPRSk1OHadG9UByiy/58GLHknlWu3trPzQ5zxJl0p8q7bM+off29DiRbzsmWnt6z90F01pHr6IsOviQJqQoXk4R4CUckSStLoh0ZJR1Ipj+GTamFg7SxNJwAmGxSJi0s7YmFiklhcEDOafYklR2M1fan63hb1Qq6VtDddJ9yP0B1FVRXAW6pauXTQr7k11XN47oq1IPXG/Wz6eA00/v6VELGlWib1Nw8VfpVrj0R0lIi31b2oEp0WkYrWsqMjk2eh+w5ByH7yTNM6TuHtm35HraQ7BZinZJsmS5NxouincfXvvY1vPWtb8Vuu+2Gv/iLv/C+NgoKCgrWZBy9+3Tc9KV34LNH7jSi4wjFQVpBwLgm2jwfrmohd9J0PBBs00r+eiElXRJSEaXkmFSZbgvt1eapPE+w0wRqdECj3rHoZAaF2iVp4zubNg41QjxqbRrm2f4HNIjxaJEzIY+9hCMizPK8vN/H5E7KyyHnaE6mx/c6fw98fRvtjvh+SLIstuOLzdQxIudomIdLEk1Jmbnq5tOEjNcDDbIerfc+uNXsnJp5GqQsJe3RT8WEVHj/liRXeRNxDPCzjScJP9h0XA4UJEQ4IqIJGW6QZLTkF/tat3sc12jbAYh0ep5+xDqXZ8Sv/aD5/berbf8Ax6b5MpWV3xt+lNuMH1bkG7eu4qWXXsI3vvENzJ8/H/fccw/mz5+PW2+9dXVXq6CgoGAgcPivz47Q0Rk7SCsoGNem40PKYEh3YUhHSoKB8jG0NTS63nRco6s0OqjdtoKG8utsuqwUZUm1zR9Qk+UZWsEq24L8yTjdbL4qyWNabuqIq9+8YKXIO88iUsFLtbfVdefgOgkFx5NSTZ5USxNxLp9JK++vdFCLO04xthYD8WAGX/cg0LDm/OxkLt4ZHKApxW3C7Wvbnb2Ls8KeI/75gY0wECKdnUnTcd+GYju+CUwGeNSCPX0re4ABAOc9XXM6/L2CdvfRPYPB5JvvqyvemZb7KkjyxKGo4O6ZI4C+vgSQcY+EI+HcioosiVaUGaiBIOJ+O9MGg4IJJ1ddbNuLtO3A9YSvn1tXPOjhrkHDegdXABkKCr4O9VZO4bfPv+p5DUq2KammMu/ItV2qYBounKFFZNyE8lJnaL49kFlXCObhIalhYc6Hycvpd38ar2Qfkt8L8lwqqUhq1g6xOzUVl/e4L/i7Jrfdty2y/gCvuwdMhCy0URRinxNafAeldUylTRRJgRVrOT1GKtlDuotaF6/jKbrdLpYuXQoAGB4exhZbbLGaa1RQUFAwMpx6xCx8f94zWLBo6cDHfO3ah7HztA2LCfk6jnGtaGtlUIFjaBsMqdrNk3PzhZ2C3dG1V7d9OvqrsCkZlktJhlPSJklzaiKekuhU4R44FrZAUGXgO5QAvIl4ZCYJ+I4mh8fSct21nTcL96biofPJ+5hsB5V5ZPMT5VxI3m548hXnkObgck52OiigM+X0cnSUDqoMRLKj64CvB1z7NpTrDCkAeD3kT5Vr8uQRfu5xpGrLOcktZaQKdKSuo0momxeYEphQli+31+FCsW4zKbbqMyWxqfPr3nTbp6vYvFyabkdm5YP+mufx5fC5knr1UrrTa201707yyLS2/f3Kaz3/APt7/VqPFfWIIPb5bZk2ApLfE/wuARH599sqfA/DlA85xSQ4YWTkpsCk22urt/EbbrgBxx13HGbMmAGlFK644opGngsuuADbbbcdJk2ahAMOOADz5s3z+zbffHP81V/9FbbddlvMmDEDRx55JHbYYYdVeAUFBQUFK45KK/zN8bv1MwBsoJiQF4xrog3EZBuAd0pTwXhHNey8hufXSVKYI2b9IMlxjjjnyLY8Lv0Btp/Zy/t4aroddpDvMLIJuHKKn5yjzWRUCWLNao4nskoowiImtWwjJrTpYEU633qkyHVklVz3BDsoTG2m5IMgDY+WhulqHfAQgwKSS0syHXt0p2R/M60nUU0IriTYkYqnLGHmOdsx6VZizjbACnxqhh795BzwhMS7BrDtlCXg8TXRIGqyX6cmAWPiJggt3HZMtlVEkH3YLT42nUedEOaI0Mo5zclc6gbZ9ReaLFvSskQ0bYsBiWgbiY/On6RH50/3D0K0M8e1Ee5GXUaJdHAop6DHz5y8YFFBQbDD95K8E8V0iopSYd51OqBYwfj/N3abUI3ZiMGagSVLlmD27Nm44IILsvt/+MMf4vTTT8dZZ52FO+64A7Nnz8ZRRx2FF198EQDw6quv4j//8z/x5JNP4tlnn8XNN9+MG264YVVeQkFBQcGY4Ojdp+OiD+6DaRtNHPiYYkJeMK5NxzuqRuVcDmvAex03UKiVdvGsCV1UPqZ2Rxl0ob1y2zU6cs6iFSE1/kvjW8t0HqmoDVC5DeOq4uNuK+vNHGiKLJJgyzndrJK3gedSW7IYzK7TOnpTcG8qCT/3Wjt1WqrE3AZSbeZaeHNxbbzlQCDcZkSDFTloRb7tGtcbbTRJvSTgkUMilXMyF7aDAzQFY9RgKja3aVpBUoAmZ6rtYj/bCjhzZ+s1WymOC638vFASpuMgsW3cOtAkOiKNyHFfNiWvHNE3AFUuHRTyKwVlrGO2iMhlCIxNbxLr3Haa1joPnLjNxG7iZLL1lSMZCuHBcINH3oxctpFW3rKD3PNMyle/WW+gSZYjgquahN/dF86vkn1tadG5ejxfSmZx7aTEuh/IoJA5at62snMDAOn15/Lm7h3yAydR3RWypuG5tJ5oyUvp88HLdFDLE2z+DjrSLHxSsGPFShsM+WXt/k/UzoTc+O9cGMSVkRbWPq/jxxxzDI455pjW/eeddx5OOeUUnHzyyQCAiy++GFdeeSUuvfRSfOlLX8K1116LHXfcEVOnTgUA/OEf/iFuvfVWHHroodnyli1bhmXLgoffRYsWAbAm58PDwyt8PVzGWJRVULAmoDzTqxbv2HkzHPa5Q3HR9Y/jX3712EDHfO3ahzFz6iQcs8e0lVy7tQdr+nM9knqtdKL9j//4jzjjjDPwmc98Bueffz4AYOnSpfjc5z6HH/zgB1i2bBmOOuooXHjhhdhyyy1HXL4WvWwDgnHblTKWUCntVG/LOrQy0KQis+Ia8HOE65Ye4CD0ka1DNGzYMK0sEeaul1Y0UDmps64UTILJEXlLTTLkDwikUKg3fl42LNkG4OdfN8y5IbzrJnOxR2oybqhJoZUiBD6qouvT/jjVSuDlfYycqinKtl1uUGOQOfFxnR0Rl4SbXCgp7ziM10Wau05SgdyQat4z3s9Ewu8XBEUSGr9fEA9/rBKERCk3J9xlY/KMMJiSI9dReguhbh6LkYGJKQTBRGhKgiC3Kh6YIA0f3st/DsgOdvhCFAVyGl9aOD8XT+FicuS5oRwngx68npLqVJnOPdKSQPtnILrJ4dhoX2agJL2unufu9WHK7ZPPcOa8ilrIduZaWk870meIK5Q+h5J0i7ypo0c2G0+nndilmzKTkGwGq9lrm6LdC8uXL8f8+fNxxhln+DStNY488kjccsstAIBtttkGN998M5YuXYqhoSH8+te/xsc//vHWMs855xycffbZjfSrr74a66+//pjV/ZprrhmzsgoK1gSUZ3rVYnsAx2yt8IvfVQPl/8yP7sadd92JvTZdd/5HjAXW1Of6jTfeGDjvSiXat912Gy655BLsueeeUfpnP/tZXHnllfjxj3+MKVOm4NRTT8UJJ5yAm266aUTls3k4d6w0nHMzAJpcZ4mc0ukcPlXKxW0GRY64BkEgtm4bwumZS5MkWJJtIIQSzpULBLPzXvAkD5IsSGmLkvyuoygVbe5MuvnXTLCrRucykHSpFqfbvRygtXlZb4NWFBFu+v/Z+/uoW5KqPhz/7Opz7p1h5EUgzgtrlJEMKuDwKgq4ljiOvIwhGvHt9zNZBLMwUSeKkxWFpZBABKJrRWYRUIQVEZdCQr5JjDFxFIYYYyAQYEYxA4pLXhScQb4EJ8ww9z6na3//qL137aqu7nPOc597Z5479Vmrn9NdXd1dXV3dT31qf2rvBZJd3J+zZHuHbjWJ34Y5S3ZNzPy2EVVlzSQpnmQTkrM8UNX5l6cneSc8hByH0rjSKHnVhOgYUfTMNeWJEOdnSkzl4LazNzndDIGeT6dJurc+FpbIxvEAQOzov7sNI3AMcxJnRLyqPLttHWTwZa7blLuZgiDXJJlR87XJ6SYW8gbmmnRNXgtCjSmn5klCdcIdy7XjJ3CeMPvj6/TGq7e3Vbs4uLFdDwRRtU+t2oF1zMmUPcnnRA5Z6J08pjCRKX1l1uvSOdp9NX72Zz7zGYzjOBkgv/jii/HhD38YAPB1X/d1uPbaa/H4xz8eIQR80zd9E/7m3/ybs+d88YtfjOuvv96277jjDlx++eV4xjOegQc84AFnXOaDgwO8/e1vxzd/8zdjvV6f8fk6Ou5p9DZ9z+GZkXHzv/jdneJsMwhv+uMBr/muq7plewfc29u1qq12wVkj2p///Ofxvd/7vXjjG9+In/qpn7L0v/qrv8K/+lf/Cm95y1tw9dVXAwDe9KY34au+6qvwP//n/8TXfd3X7XwNszxw6uREBEQwBhoxUpCY1QFrSl7GN3HIMj+m9Auy87Ss2Uvhtrx1sJCRsxAnTvNdjZxv6Vn62M4tK2sm+WKZZM4exxsd5dqbeItgq8dwlYUX9QoU5NWnr1znco4Il6HNwiRN71OhJLvwGF6dc84pkQ4A1Hn0mc6V0Xscnxvk8HF220iKAiIGYkju0GWusR2RRl0Kq7ZanAGU8uZQkUoq1+2qjnRKMZJ11xolgaM8wwhZlwGjAJOOw5+jvK1cTy2HaTPNeSsxXyLcel+N+ySkaiV/vzpYIC8fB6T52UBJQGsCVkgF6hvI1y3Oo9euCCvV+xtoEvH55pSfrRbZ1Yk9X09iWyS7cU91WZaIeb54e5OrNK7KUAxsLJVpV8I9N8hT7bf52c7DuP4GSuvDIL4qiLEaIlZDcpi5HpJMfD2MOBE2aT8l7+PrMGIVRqxpNIv2OmzMkh0ogu6DhHsbXvGKV+AVr3jFTnlPnjyJkyen8x/X6/WRdraO+nwdHfc0eps+91gD+Kd/89H4B7/ygZ2PeeG//QOsVitce1X3RL4L7q3tep8ynTVnaD/0Qz+Eb/mWb8E111xTpL///e/HwcFBkf6VX/mV+NIv/VKTm9U4deoU7rjjjmIBkkUbKOV93rKQrQ1+f7bcah6PfYwsNp+3kVbnW7JU7y9d5mJ9eSlJsg/TpelT7+HZWlM7BwJKZ3JnMid7F4SqXJN9rpz7zhE/bMlLJ3Owes4Zqu3mSabbNfHket0vkubT2f1yYxviKE0dnHHIzs8mVvZQOker99fXKa6Jspz1vUy2dyBjNTktLMlCcHWx03pi3Mo3sxTnWSDRS02tuW+BiNf5inNU91qUCzPbPt0dX5yzJtwzZUZ93S3PpHmOs4TJZ9PaH5fbgDkp9JLxJaeKfmqMd4A2B1NY3Ufw0Ic+FMMw4Pbbby/Sb7/9dlxySbfYdHR0nP941mMu3SvGdmTgB9/yAdz4h39xFkvVcW/CWSHa//pf/2t84AMfwKte9arJvttuuw0nTpzAgx70oCL94osvxm233dY836te9So88IEPtOXyyy+3fZ5sp45ODveljmp8PsUcKZvta1bzeWtizJiG/lILtS4+fZc8HtZ/lDLnudYwhz5+GYaYFnESNoQolptkrVmJ05/1MGIIESfCiLVbLI6sX0iXcZb8KkpP6zqH3qe58Gg7DG/462k5WgMB9dLyGnwY5HpvDW7455FDqJnFuiDH7MgxT2XfaJNqTbfFeRe3dU+kh7TEFcArQlwR4kq3gbiGbaeFikWPtWWYLhwWFiq3fTnnBg2aUvWiYtzvHAFsEGnzLM4ovIlbGLBdCHhdhjNFi+Q27mdyL/WggL8Hf5+N+5sdWJiph3rgolUPZ3mcbRmOTOdBJZ4OCgVn1XbfSu8ATUMWDiIZPxE22ZIti3731mLVXtNo/2+OwhnkccOJEyfwxCc+ETfddJOlxRhx00034SlPeco9WLKOjo6Oc4frrr4Slzzggr2O6WG/7js4cun4n/3Zn+FHfuRH8Pa3vx0XXLBfw5vD3LwtJdNZghgQkLwhJXl48pI0ICISFbLxXeDDP+l2vV+hMvJ6zrbHuMM7VV/DS61NLeo6c7WcWXMryVQnPz4e9XrOe7hactxdFwoB4sl63bEs5eJuHbR1vna9r7gepvc8dVg0reBA6sl8um+XVlBbrCfh1aqzUWAhcyLvtw4/Ic/ZZuT53MgewynNSzZyjpzNwMXlyvY5OOIjUnHi7HCcYvZyTpELC+ne/GBb/qqcBVqW7opwz3kr16rTdb2WXS7q8flQm67OyC+RS5+Uq7q3iXUb+9XX3pbeRrovmr8PuwdvuW2dd67sO9yHfwTcSrSCbT/X5MR7HjNbXCXY/rxGrhkUZDB2yN/BlazrgOOKIk4Mo83LTjLxiJPDBqswYkBMsnHkedlrmaeg1uzzzaL9+c9/Hn/yJzk0zUc/+lHccsstePCDH4wv/dIvxfXXX4/nPe95eNKTnoQnP/nJuOGGG3DnnXeaF/KOjo6O8x0aY3sfCbmG/fqRPazhHccTR0603//+9+PTn/40nvCEJ1jaOI743d/9Xbz2ta/Fb/3Wb+H06dP43Oc+V1i1l+Rmc/O2gnRqBooYK4/WAxjqfD3N414udx3y6bCo+5u1A7XFYxdItmJbyWrP26GWSVp6dmTm5eLpHFPrf72+j+WmtljXBLxO2wcTsg1etJATdi/71AEaV4McSpJT2qTdLNxSTaBtzvaENTly1TpnxYI8caWQyDbUK7fO32akONkxkRMjr/uQx+ZNbcnQsty79EO/dsKxWvO6i/vTMm6zmB+yDGdyPqqcLNhAgx8cqJ9VzYBb9zU3aLBn+c4Ih/+cbj8fVe1m8s66NKdKaUnGgTKiwuDS1dO4zs0OyB7G1Zp9PuJ973sfvvEbv9G2dcD7ec97Hn7pl34J3/3d342//Mu/xEtf+lLcdttteNzjHocbb7zxUBFEOjo6Oo4rnvWYS/Fz///H47q33oxdDdWvfscf48ovuQjXXnXZ2S1cxz2KIyfa3/RN34QPfvCDRdrzn/98fOVXfiV+/Md/HJdffjnW6zVuuukmPPe5zwUA/NEf/RE+8YlPHEpuFhAREQqynUJ+bXe5H5nM0qrhnnwcay9vVodZHololVZtAIVlO5VxN+xCNlsdutrCHeQ03oqt0kiVPmqn8UTY2Hn3IdHeQlyT5Wh1me88uvqtJeNz990K60VVOcsOsoYfy87XdD+LF/oihJgbBKkdypUW7EyyC4fass2OpWo4LbkKVD5e3IWzRlKL4DryoNbLeUtete0IOTOAAQijrLNUjqxTpHyN+gItq6qrIHZ5Dk3eaoJt224Ugsr9ZzAGluFIa3H9VhHPBn+akN/GO13UdUm6m9ZtSZiM9Wx5rtvurxiAWar7xgBQs14b6cVUgrpQlPeX7xDnY2Q9y8Y5WbNlUSdoOqUmTfNoS8ZXYTTp+ImwwSDfyFWIZtFWK7ZKxs2arQqr8whPf/rTwXOhGATXXXcdrrvuunNUoo6Ojo57J6696jK8FoQffMvulu3r3nozXgvqztHOYxw50b7//e+PxzzmMUXaRRddhIc85CGW/vf+3t/D9ddfjwc/+MF4wAMegH/4D/8hnvKUp+zlcRxA4dQMSFaHCMIo1HZwMbY9aotnHV5L50r7/a2+hkl+gaaM3K53BOygRTj9r5Jr7+BHLTI2R5tSJ/PEkOSP2qkEsiVnXyRv6zxLmr1k3Oq3kXdJNl7fc0G0Z61Kel9yLW/Vd+tRJd7Fb3k9b8muBzV8LHOAQZS9wBcEmyRhztLryYQn4C3rJcrtZvPivFj4aU5O0eu5uezzu7zFudLdNZ2EJcLHRTl3aUo1wU5pfiQDW9f93O6ivJUFu7BqV3l8WZl2K/uhUdWfEeqFa/oJLOxu1jW7qUfy+nr+fNsGRvwjaJD3RSy001beJunGzHP1x1QDMCVRRyLY5AbmhGjn72H6PprvCfd7ImxsXrYS6TWN2e8HRRc3+/y1Znd0dHR07Idrr7oUP4fdLdvqHO3n8Phu2T5PcVbjaM/h1a9+NUIIeO5zn4tTp07hmc98Jn7u537ujM87NmzHU9lyDjMVORRWWIU5JAMOJSNvxdveFa2r1XLwel3l4Zq35UVXSXaWjMdCPp6OXbbGxMagxVLe2vlZub9NzP3+uTnX07Rpub31uk5f6hgvxcuurdn622wjfn/rqU4YUaswKMl2Ay2yCs2uBBOOUAshsTEoJd3+enpeZ8k0668vekH0KBPCmvgtlbtI04PaxxSoSNqRWLqxQLIPy6XqgYniWjuetBgUcO1p7p4X2sxOnHCHptk8bK4tzg0uLW23ztlsM9U51KoNt+5UKQCK72PpTDFOfDnU34uWrwcAIiePNp2po6Ojo+O+iW7Z7vA4J0T7d37nd4rtCy64AK973evwute97ozO24p7PSIgcsAIwsgBIwcc8FBYVQ/igA2HtMT0O8q+MQaTkXtLdotMJZKl6zlPTb52naMNLKs0vWV1jlwTYFZqb8VWi00Qhz9q0V7vEwvb5cl1H5okWi3Zus0zaXMgR5TnCHchF58h0IFTZ3sVIkaO2MRk4w4EICTHePm+SnYyJx/XnDljaQmf3kzFXBxJNZl5YZHL5nCzsM6RF3ccK9FwmYxkOys2GEVYLPsFCst2Kw16LuRjdd2eJ2cSyWWVlnVgxWwQx8piuY1wzZ17Ik9fgM9zRkbKmWOXSPzW67kBEB3QKKzbPmujzifnX7pePYDRsjK3nk9laS7G5ao87XNzeZzf788R2DzZJ3k4RDae1lUurouPxrAaRgT5HhRRFSoHaCuJme3l4mrRrj2Nd3R0dHR0eFx71aX40U9fiVe/4yM75VfL9uvDE/Csx3SyfT7hrMXRPteonaEBpTVbCXhLyjzGYCQ7ciKRas32obbqsFvlOprp/rhdFjumuhdP1pVke1n4QFkKqaG5NEyXzTkcNjgxjDgRNjg5bKxDeXLYYB1GnAwbnAybIsyXdjg1rJbGra5l+1bnlRy8JtlF2sxS1+GS9H4urFcRAxfeku9j5+ogxXQwpEWygXme15KZnzFmSGJNOpkyUWGCC/HF4IER5ZcHgCW8l4X/cr+6XizB5XNhxHwosQmJIuT42yjT6wrkiYTAnQ/T9QlJW9p/BjgqC3n75MhS+5pk8/JCxTqX+wV6PuWeezXHmmTP3UJd/411f85mG262h+qYFoGvrsVKsI14K8mGzc3O30uYrwqNuuCl4/pNXItkfKXhEe074qXj22Nrd3R0dHTcN9HDfnUA5wHRjghGslUOPkJ+HbHexAEHHMyarcRa19ukOl9njmCfLcyRuUDltrdqe8v2inJnUteVbA7yqx3KAJYYsakTuZIQNpp3oNJyvA21JN9bsnPscLe/Itn1usIftws82Z6mTYl1JtW5fss8frBjOY54OuDoPpaT255sc2EhrIltIsUVEXeEuSDts+TZ5WmQ3qKMLcI9uScq89fY5zWbIWu75C+O2TH/XthVrt0gyHsTZX9K/6xqtAY/FgjvIjGu213j+FY7ag0STfIgW7NzhTgLeKPN59j1Kb++1xOp+Kx/B0h67+x0dHR0dBwOGvZrH2jYr47zB/fIHO2jgpLsUeTLB7zCAQ8YQTjgwZZTcYVTcYUNB5yOA06Pq/QbB4wx4CAGHIwBMSYJ+Tgm4s5MiHHaS1WZuJeIq4y85RxtG5YsoL5zqHm9szMgyyABYEUxW2zEOpO8iycLdQDj5LAx68yaxmaHUgmt1m1AQCQWyXhAnscZEcXDu/c03rJc157dW3c9MuV+fAzQONgaB30Jrf16byuM2IQAxGAW/1ROIEjZQgCicHLvjdw8jqPd+SbAsSGy4yaZGkRUY2drGiGTDJOML9x2TVJastsiv4yUUkwLA6BIE2k5I+/X/OkEyN7VIkBBz+vK3rDSzpHtWctnReJb+xct2fX2zDW3WW23cS0vn08Hud/ayjxjeW5K9WeKzJN1nq9bX6w9By3agyaYPheXPqn70DhfcQzPpMs6YEPB7OTiLPLwtM62jiFZsiEycQoRw+CcoEm8bALsG+AHIFW9s3bfTfUmrrGz1QlaCzpLu6Ojo6OjA+hhvzrOA4s2UFo9vTVb52Zv5HdkynOyoyxi2Y5xatneRpZb+3f1b7QLalKnUmfd17Jiq1Q8WbPHLIkMoxHvNB8xzTtchTwHURd/7hw/NmZrOGVP5S2oZN9LxgvCDeFr3JaOT7iL7nMMaRcv5b6edL2QgItCQNcBVIMayGnunDnU1yFl4vuQHoedrK6VpXCyqBXbScPjwKV12xOaBSJUWzu99bRF1Jrlba237neX9SrtTEj2YdBqCu00npDpCcneQTpenM8de+j7ahHmBpn2gzotkl1bwG29UEpwsy0VJLtxLrNUhyotSOWobJy4GCQL7l2fm2ZSq3fs2yck22Ob48iOjo6Ojg5AnKP9/56w1zHXvfVm/Jc/+IuzVKKOc4ljTbRPmwU7mDX7IK7Mir2JQdLS9um4woaHwgFaItxkztBi9EQbTeJ9lGR6Fxgh9AQPVYcRpSTSnPsYuU5ke02ZWBvJDtVSkW51CFSS7cNVgh7VGtTwYdb0tybUhex8D+I917n2TuRCiCYdry3Zeo4WsdZrtWJtz5LMQ2DnKq/JcS0Vd6SbB0kLLNZBNOdeTwgPptbmYr3e7/O00jEla/V5mxZVl39yvbpO3LG7ktGjJ+PVQ6zJcz3K5PLNYc6Z3C6Lbxs2EONJccCk/fjpBgXZnpvDX5yfbQpDXQZUbS6Tai7KqM7P2JFrEAqCnSXjbANptQW79NtQEud63nXtA8RHYBhVWcWh6Suko6Ojo+O+jWuvSpbtsGOfQp2j3fiHnWwfdxxr6fgBDwheLh5XuCueQGTCXfEETscVDuKAOzcncPeYSPYXNmscjAMOYsDdByuwWLnHMZhUfC5udikZR0GofEivet+u8NZWT+pq52e638vF18MIADgRNmbR1niwgRgnw8as2CfDppBD1pbpSGTz2wMn798jAhCBkWSbUo93AGODqXXbz83WOtb0Om55XQdBJOpDiOV8bUpzzkm2NYRXi1Tbr9PaJnloOucgHscBJe9AjAEIZQe7fhZzFmxiKmpAO/iWpqSBZEMIRWon0mCoKO5O0uVpQbQSsuWwIK7eYirTIrQcDIBGBrnpEsTSnlVS7kiQSc9RlXtmvbh+9X4UxNrfS0W6Zwk4GtvYLX0WzkJ8yHGldJn6WE+uUf7OXYd9Y2qVe6meGnmb53f7WgMZ257F1IrN8+fyx6HaH9ituzSVkQ+c36chLUQAiXQ8EItkPGIYonka12/LECTUoTo3c34rtk1PAZJqagCnbyLLFBQM6bt1vMeuOzo6OjrOEg4T9uuf/vr/xjc/6hIMuzL0jnsdjnWvgDWMF5JcXKXiNmfbh/FSS7YsGsZLf8tFL0CF+atFvs/UMdrE4dYO+1ty6Im11lmeg3nSHQsPuoNYty1sDcUJAR+EqKuM0jztOiuQJ7p13HIgW5sZWCTZQLZYexl561x+fZuDNG+1qj2Pax2bYgBto6vPp0uNZDmrj5k+Qz4T1mYnaSRRtcuTbCU1oSQvtaxXrdv1sRPrtftt7fOPpHg8jYpdJHm7Yh+SfZjz71OUuce7JC1vkPHaQdrW8wMNi/B04XqpneHNtZcG8a7zeJI9UUH4bT0nqvM08pbXEpJtv3AWbHmsDWUJVe98qH499lHreGLdUuB0dHR0dHQorr3qUvzoNVfunL87Rzv+ONYW7bt5hRjXuDuuEUG4O65xKq4QmXDn5iS+MEr6uMapjThDGwccjAM2Y8DBOJgVO1m0AcxYWdWsxdIzbFm198GSR2vdbjlA8yTRx8hW64yPl53nZpdS8LV4FVeiXSNQROSAAMYBD0jmzJC99IItPrW3ACnBb5Ftjzxnu70/QAc2CBHOco3kh0vT07mClJcQzRPdUgc6IlCw/QNxstIjPcshxEkMdK8s0DRfzijkXTvZaX/pLM9iY3tSScmR1aSosm9Ot2y7uMymBvzpAWgTTtY/lB2cEcy6jYBstZY0KyvlQyeWX0ljvd2qjB6L1uiK4C9ZRptVNUeyd4W7t+Y22tbupgV8iWTX21t4XklGKRNk5XyhyuePKy5Y/s7Wp99fn9sR62Y68rbdWvMZNgaFlFDLPRnJJi7k4ghOJh6ihfNSh5FDKJVAdTSC+lsRmTC4+9fvmcrC10ivSxDLtneAtjmCMbSOjo6OjvMX1119Jd763j/DbXfcvVP+7hzteONYE+00D/tEItpM+MJ4wryLf2Fc465NkpHfeXACB+OAkQmnDtLc7Shy8SgelzkuiAaZCrJ9JmhJj2vJuKaplVXnFup+Jdct7+IrijgZNoVcfEBKU+v1yXCAAdnreI3IAQcYUn6OSaIvtaOdzkipZ78KIw5sIub8fTNqT+SlGsBL76OeKIZEVokBkXyvQsSGlfRHkacPWGFsysgVaskGktR+QxEBhBgIK7GcB0pKB4CLQQB9DkDZKY92bgITp4EAb0kjtQxTJq9KJGoCV5GivcAEAhtvJhJVuLcKOjmuHOJYjhAYY8OSxAwOlMZZPDlCJvjuDAX3RpWuG7NkD5gl0k3CNjd4UN9j4zo71XM1oNAcRJjLs8t5/S+XJHsyxsKORBf3TXnOvbcoh4U6q+5/llDXz6Eiz0Z6UaYbEUfjHEC+0fpaxTa7e8nrRroHJdcADTF5vnck2xY3OFmofhY+VBFpQG9EcNLw9D0cKNqDCBQx8oCD6vi7O9Hu6Ojo6FiAhv36B7+yu4T8urfejNeCcO1Vl57FknWcDRxr6fhGHJ2p07MIwkZjZVcy8ez4LJFsZhjJhpcoe02lJh1RebeR7KV8fl+rs1hbaVJazJJvLwsXkp1C1cTJosfagnx861oqI/fy7H3gY5f73xZqaWZrW+eGL8k4JwoBYGK91qVFslvbLS/k6bxuQ+/5DAds8ol2yNIiokZouNpuHNeoxn0UshPS1yBXS9bqvXAUJPsw1z1ibGsecxb8Obl2TZa5rmNNqwn7xEkZl+TXnzvYuEFjf9nWJtfy+WqP4hX5BsHk4lpZ+p75SAH+10+3OSzUbwWQBiNzKMPglnu44XR0dHR03OuhYb+6c7TzH8faov35zUmE8SS+MCbL9am4wl2bNSIHfGGzxqkxWa9PbVbYjIlsbzYDYhSnZ2rF5hxH2HewLaKzSIBLCbl3fkYFwZrO050n2HCXVPLnrdk+9EztLVsl4+pVXPOtwmj5VyGa13D1HJ7WN8Wc6xoB0nEEA2FjIdPWYQSieOWlgDVFbMQimq3GqSzMmbjNfUtqT+PBp4dkdR4LSTbSYIl0yNVZm+rKrTNNeh+lJd4GAyQA9IoiYqDkGM05Q2tOH0A+v5Z3IMYYA4aQPoQEIARGjJkMJOLhiYKrFJpagfNFxTzd4AcTqydQ5CNuHFYRXLPEWqXnhQjJZE8S55vyNWtLrv1i/n4WKU5FqrfKxRfIdJOgV4XZxoUW7686z65598HswAgyQVVrdhwkfYCbe49mfWxTBtSW54mVus7bPBc3zlX+1nLxSZm8+sK/N4OQZy8XH+SbQ2yS8RC8TLz9/fXQ0I8gYGRCkI/JJgZEomLgMIKansU1/dQ4LF6ro6Ojo6MDOJxztJf9p1u7c7RjhmNNtO8cTwCbC9JcbC7nYt+9WeH0ZoXIwOnNymTicRSrAxM4OkLlO8xInTOGEI4zkIyXBHxKroFpeCgvGQdgpHlxXnZIEvAVRfE0XsrFfciuJB1XC3fEoATWyGPEaV4BlEh1ACGCMZJYdEKSVgZmRCKswpjk5s5qFIgTGRY5t8q6vVC9cIwmaYVFKAawDj6wSjqBIOubGCysWbJkB0SG1cWkol19ryjanO4VnPVbvKO3LM7+VIMSaMmrczaDtRuZo01IXtLF2jYhh0p2rd3BSMqExNXlccTXfJz7fJ7x6nkrCXny4J7INDGQ5lHIwJPwCYrCvJdIpBJszut2mdmRBJ+pQQpnSOJOBNvlmSXWPt3d1xyBtvurz7HLp+EwBLwiw0ay5R9sEa5Nibam+zqcq09Ppn0+tw0t9mQ/T8pXnFvzVPcyJd2eVFfn9kQ7uLBdgSHjZOm7GPL308h2oU7h4lF7ZAVMItdp2gww6MAcGANHexdaFmt1vhmZcGo6E6ejo6Ojo6OJa6+6FD/66Svx6nd8ZKf8f/FXd+O9H/0snvKIh5zlknUcFY63dDwOE5n46TiYRHyMhM3oLNjSGWKdl83ktI4CWdd96mmcNQ057SjQItk+3csdp9LlWKRlCXdOV7m4pue8JcnW43XbS8gH5HMBUwdorfLY7xZ2MYmTPZOviJ/t15Gfa5Z1lnm3QS3xtZQccP19n1+fmeZpDKZM4mnXaJDFewJspCaTrsUq21LWOUnz7HF1eiPfkZLs1gNtXHeuDrhx7N73vIQJEcWsdbgpE6/jnzfiXE9iWdeWcCXven0fw5qSNbmIuz2Jqc0lWZ7E5k5+F9h5Dl8k2QQj2RNCrqvUmLbRSPOILcs0U5Huo1hEJgklmeZvH/BgkS50fcPdot3R0dHRsTuuu/pKXPKAC3bO/1v/u8vHjxOOtUX7cwcXgg4uwBc2yaJ9arPCKbFiH4xDlomPeV42R8rxg7UnWXTYAKN72tlVKe2eaMVe1tPUBDulobDGDJRJqzo+01+/qBUbyNZvlYsHcGHNHhBxgjZGste0aZY9pMiwAIADJE+7Iwhr2b+m0eZCrykiilV5g2Rt30TxxI18T2bVbpDrwjGaHKPKg0CcZeQi72bArM+BGF4Bvwop/rcS/7l53UqwI6V5637YKcwxLff8ivOKt/LI4otcLfFEtp5IiLQ3sXLLD1QmzmI99c7TSH65rfJfBFVGbsi5JtvS7jlQdoImg1Cs5dFXhZAHpMrXZ3INrtL01pt5q9GNnQh2i5gu3eccaqs7t+939nD3zPwnRMto59Fz+d/69I16MAI9UJKLk1ixB2/pRibMRoTzt6x2qOYt1bmsPCX29f4qvRzY4LIeW3U+Z+nW9JDzkSu/Wa6D86lgHsYlm713Ka8Owun7GuWF28SAMDAiDwiRZRoKAQHJk/hIOKAhDTQSY4Mpgc7eyAmbmHyEnN4c67Hrjo6Ojo5zjH2do/3yuz+OJz/8Id0x2jHBsSbadx2cQDx9EqfHZMU+vUmhu2KUudhjsqfySOBRJMGRcq/W5KHaS4OKaNNuBsh7ZKbludke20h2HcM5r5eWVQCZXMOT67FwSmbxsqmMl21xssHFXO3kJC3ihPM6rnMPo8y/BotzNEppI8g8go+U5i8m607y+H1Ag8nIVyER8U1MobS4QXiXwI7BRSYQE0YGhpD2jUxpPrXIyy32l2AVYupEc+kgroavZ+Y0SKDX3B6fG5ZXBxUCpec1isf0TLCRyYQwMlaCoGy7QW50jjQ5UpYK26o0R2S3qS4qckRB3gtxrEzRzc1ulWvunI5IT8qMtvV3ntRN97fyTs7RuMe5a9vrWdetI8D1fbA7bnagYQl1Pc3kKSTjA01J9DAzR3vIbW4a37okzFxYk309cpGen0WDaBflbpDoyTq399s3MV+f7Dfv1znZKa94H9+mIBHkQbb8bdpIJeqAXaTsLBIS4aAVAizNy06DaxtxhHZqs/s3rqOjo6OjA8jO0X7oLTdv7b6pY7Sfw+N7yK9jgGM9/H46JmKdFpGLq/VapOIcnVRcSbYt2ouVE5pWsgIXP2l9z861J9nN/VTOK2zlr0n9tlA1Fvd6Jl5sjexVXDyQC1lfPMaxW7X+TMroO8iN+1Aw02QBSot35NxZVjJsC0qP437+ZSkHbTf7Zv3OLHW+Gvle85IvhIKQzFl4PSmaSJYdeZ+1/PqNpUffIqw7QPO2LMuavnQ+rsq+jWS3ylvknznXUjm2lbEog8eW8tTPK9cVtc9JmD5TKu/NW66bIbx8uvMYzsWxnKXfgzvG7UsLbDGpuU8vCHn7OPjz+TzVvSKoZRrm6GxCslE+YsCl7zDSMTedpI5SsBHSrNOSRiYcaJosp+KAA4tuMWDDAafHAafHlZH2jo6Ojo6OfXDtVZfh7z714Tvnv+6tN+O//EGXkd/bcawt2v/31EkQncDpzQBmwmYTEMchkWq1YjOSVLy2Ynuooye18kQCiM3JFBGbfDxZsyjnZWy1pHjSXFuyyRE3I9vIcnE9biAnGUf5q3OzvWdydXa2DhsMSBJxTVPLdp6nHc2aHSgCvAIoApzk4uZhHGOWkYtjtJFClpFTQKTkOChZeEZEBBxA7kWsvDXLKEh1paFV1cAo9a5ezUcQhsBAiGJVynkj5fMV6gAOBSluWazz4ASbNHQOOY52tmqXMlZnaSNx4CSWbIjX6HSJJNVWR2TJ41vKSxrKNzXGLWbZHTBLOEXJoWVrEL+tlyEU1uB87uWy1GS6yF+T1pqc12nAfvWhZXSFppxo96Sig+L7QW7bl7HO4+uFE9kmJLJbKBCqgQaW52CkmJIFm1eOOJuMnAsZebZ+19Ztrp5rZbn29bdrut+Hxvewfh7VfqrO6+PQk89TDF5xkbcm2zYwhxQVQFU1o0w3OY3kBDFAJOUiK1q5wca5gUn9bmw4+QeJTImUx4DNqWM9dt3R0dHRcQ/iGY++BG9618d2yquW7deHJ+BZj+ky8nsrjjXRPr1ZAQcrbDYBHJNXcd6kudiIBIzSC4tbmHDRW5aOp1q6aRraa1eQI822bdZdFKQbQEGyC0uwk4xnx2bl/kH2aSzs2kkZkB2gBYoFydZ9QJKPD2T6YQwISUrOwAGGJKfUmNqSN1us07lXyGGzNlHILsQLudwfE2HD2du4J9h5vrZ/LulZRCYj7GNMd6+daC9TV63GKpW+mKepZaih8m/bbjxqHyZMYeHHJH1EJvmzzLZBFo3JOabCQCboAAjt9jexePtLTcc2pmVhT7YdsWysw5NOT0QXbrdZXn/9Rto2a3eZZ0EhsAA7zFVScS/+15d3Dy6v9ceQR8vlPjun+2WiTKKFUKtc3IjzoESb83xtqKWas2WbkK3NQHZCpvdd1HODTM+RaP8OufSmhbnxTObOVZBrt28aI3vmWg3o9BM9d+AsHV9JKC8AKZxXY1DOn0eXkbOTNJ2+NG662/GOjo6OjsPhyVc8GJc+8AL8xV/dvfMxPeTXvRvHmmhvNgEYaiu2NLSRSoLdtGTrPulZ151rVOuaJB02RrJW1lbtOW+3LZLtZdU1Kbf0hc7k4vxjsHkMX5KND8jkcKA4K60eEBGr2QZK7kHBrOuAejgfbEBgZC1vdobWdIzmtnWAI5HwkmzneNtiWY4hzY3W44WMbxDMSs2c63Lb/Os6jvY2lCQedr/qEK0mqvUYQkFgpU3pdtEc50heTUodQZqVptdp+xuCi2OXxqGWyjBLupuEusoD7HefQJPokgyq7cXSl0DuudV1QhBPENPKYqcm8JbpYl0IuMq64Yl4SNZtb9FO65loF+S6IN1ATWotv+7XpFmSPVcf7YZRXKY4Z5vc15bsyXGC+huRfimJRWRQbqXfi4DiGxEXvpUs8nIAyYId05GnNyuMkTD2ONodHR0dHYfEEAj/5Dm7O0YDesivezuONdE+OLUCYZUk4hGJWCu5jpAYwZhaowQ5tJEcS5x+g3a6ADIWoR3nNpuYc4xWxnOVIlDp9Ixc3toZWmHNpqk1245zhFql5i0MlMk3gBy6y5HtyT2IQ7QDTl54R/kFkoU3WYDEki6KgIFyrOrkmCx1aA/GoVlPWTo+Jd4pvyoLhHxDn28EQNlLOYAYfHiz6YBFPWe8vNfDss0SebCFbFstmmZhZGlj2uZYvI6LVVuqtRz08b+Ti8IInmJv3liT3uJk0+y1JXvpes19E9Kcf/38ZMvTslw3iPoiGveV70Oew9ygwS4DEo08XhWQ06rCKlHW56jW64DC03hcpXKaMzSCScd1PVmyhVzrr0o0XExqkLccy081gDEZv6grpto+kwgN8/t3O4bdyImS7VE+hZEDhsBGtkdRuWx89IIZ6Ldl5BxOcCN+QRjAOCb/IOPdhwgN0NHR0dHRIVDHaNe99WbEHbukv/W//6IT7XspjjXR5jEAYwA2wi6YMsFO3GweNXkhlCY5dttCgMy6KnnT9oLncb/uLNUtK3Wo0rc5Okt5SudjtXXbZOFidQ7YrRMYEDEiYADjoLG/Tk/XCTYQUHjq5Sx9Z2br4Pr7n5LrvJ4UA36/Y3WU518CqUMdKFma2NUlIUvH/fU1ze6bpvOyj4p4F6gspyrZNokxKTGnLBvnHQiMI9k7W3ePAHtZshULBNvSlXA64teyfs9ax1uXLd73xvpZxkSWLtfn1n3PWbTVSq3OzJSU65zswVmvB84W7OD9BWRy7T16W5XuYV32OAzJ3he7ysUZ2bKt32r9tqQvFopv0dxZ1f8DkL4tozjaHJkQZcrSOIYURnLTLdodHR0dHWeGa6+6DK8F4Qff0kN+HXccb6K9IdBA5uyMImUPVUqUgQXZolhR/X5/HHNJcBzHkwNnrTm+w1qTbMBJxDG1pCx5Gt8HIydHZQCEOAcMKOcQJmdnpTVb5eGaFhHMWVoNT0SzpT2HG0sEPCJQKOZoaymK6nQd4VI2PsmZt5U4C2nWkFlqLVSHcmpRHkX2b+TcrXvJqKUtMNTa+3lhJHWMr5bZmlXbL4zU3igNFCVHWWyx3ondAMQcMfTEU8mVtwLvQoJqCzaXTZx40uRT1h0GASZ558i1pDUJ9i7kut72r7d/ZRcINtX1sPRbY8sr21QB6P1a/Gs05eKF5Vpk4izpGJwVWyXhQrQpsItDnW6QgImTMbv/hbS57Tr/7P3v8UnbZwqHOaz0x6jSRb4Pat0myt+3pWltkfW7JERbyDUzEGPAOKZzp0gXQBx3L29HR0dHR8ccrr3qUvwcesiv445jTbRxOoBCgLE2ISTTOZHeeogpOY6UrERpK7VYIz/Omg2ZV8kkVsg2phJl2HYrfFftdVyt2YV1m0oZ+VHCk2wl1JpWz6Gu8wNCtinJw81DeZDY2tCY1klGPoSIOA65Lsyi5J6R1Hn2HI78DJx8HCIZ18cb5Zy+bseo5yjjlev+etsfi8a6hyfaaj1LS74PA7F4qxcLdhDCIQsHGfhhgFXLbPtVKq8VpL+NFqjWORc/2cuvd0LjdsmVdS5PyuhOQ+30kkTnfbsQ60PLxa1QW8ffJvmLvIziG0N1nczkm5y2HlCQJc45QFsJoV659BXn+dgrLsm1hswashU7CKn23vDLgcBcPk+ii3V3D4f9DrX8I8wNUuWBtyp/kSe/4+VAXbnPX3dpALOexhI1VCTLusjFOYpPEJbfSIinjve/1I6Ojo6Oew+uveoy/N2P/Z+dPZFf99ab8VpQt2zfi3CsY5GYBZsJFAkUIdszi6IlLd9mndrDslKUsSJzQHuOsLd2HzVqYuwt1UW6kmz5nXOKtgQNLWbrM/c9F47HW7XzvjLPXH6Lvw0Y8R1jSHMqRfIZGVn6KaF59LhYHbttAUqS3YoBvoiKbBY+A5Rskt9fkjKLT1wswCLx3LEZ09y7s8P9WDndvZX3Wd6XHqP3wDQ9bnLv9bl3KNdkfRsO+Tq2XuNJ2g71ohbu5ro+ax/XWtuEWq8JBcmmwAjFEhFETp5+Nc2FEpR32JYQbVGSbscsLJqX5Byl3wkux4SIJ9/NyXT2RiXX710arCv32bsu3wVdLxeyZRxVGk6ZZDMZyeaYFuj/oj5Fu6Ojo6PjCPGMR1+yc161bN/4hz2+9r0Fx3v4fSTQSNa5meOpDJiFmiAdVdVvqmUKlCyJcJmZUPS2GdmqDbGauP2+MxiancWpdLwmnYsOeZAJXvJyHZDoMiWJsws3AwSAEqnWOM8jQgrphYDTSHOtgyPbXjIeOWBMwcAwyvqIsDP5tjBkTBLqa0SMyTEac445rd661VpdwHea3bMprdtqvcr76855rJ9DVdfl80GRVudpwUg6k5F4P6+zsLhZwRxR0rYYpA0SxM+ASser+thlgKgmZErkizxcnJOUzdo7URLuiVW7dT070BXRp7tfry5hKvdPrOH+fDP3O7eTtuwvwDS1WOtxLSs1o2ntntTbzLW5qIu0mEM0kY8X0nHvVXzIFm0MbDLxsIomD08kV9p2yHHeg06pQLuNl9+kVtp+oxDemszuuxqtnst3xb4JxVk0Ty5Pa0BrzrHiHOrQgkbOxUmapTEysWYl1vK+RBns3RzrseuOjo6OjnsZDhPy60X//oM95Ne9BMeaaIcRoA3a1uZK7ug7bNbnVk/jdgjlGLNCdPRoP1e75ZjKkzVy24GmIbys/LsSbEeui7Qt74/OL44cMFKQUFwBI2SAgSLAZRPwJHtkMpKdCHyw/Uq4/Rzm0vt5xAACwogQVyIfHzHQIPG1A4KQvwmJbclCbRuA62Dn55CPKQkDZtIzGZ8MiLj70fQW8Uh1W5ZTvRDX8ncPCnmAx0gHwVnD3KCPkTUd/JFDt5FtT1q1TVuaO8CTbY+KKKpaZHYwyxPFihhvlYbXZFPLXd9Lvd5CTai1qS8dY8TYDWTU5Lgi2bOEeiatdc2WRVtJNhckm/N8bZ2jHTjJxZVor6LIxBlhYJAQ7GGIRrL9d0iJdivUIDCTJr/7frf8Olf7PbHWdyFKe9cBqxbhXpaSb0mviDgXaSmBdcBJSbYj1EVkC10f0wANbXqnpqOjo6Pj6HCYkF+fu+sAr7npI/jRb37kWSxZxy443sPv0hEiJQOF9WiPDk/dV5yzQO1zTpQErbYG7WIp3QXR5N7Jqp0tz1TsV3inZpN90pVWkp3zpfPWmHOQBkxJt6bZvh0txa11r01WeejUKkWO7CLPr5xISP0SCgm5OTmrpKZjzEtLLr7kRX0Ca7hwiyfCMLLMk3yytOZj+2UP2DtU1/fiQdVvY58n2cU+co/Tk/XWuavzM5XLzmVaQD0GkS5U/dbrLczsL75RWwujB6Coq1Z7sQEj0u9O/v6YRZt8+MBMsn26ycEpS7pVNh6IsXKy76GShNdLSyI+UJaJh+p69UDYYabT1FJxTVOngly94yYDZ4AjCil4KQt3iw6iGPkuB1c6Ojo6OjqOEhryax8D9Wve+RH8lz/oEvJ7Gsfaok2jzMsuEp2RTiW5qAx3bFlT54tgDtAmjtHUqs3I55Lz1B3ZutOo1mxLw7JjLZVR66W1GP4Wk7w7pWwkjNYBB4RkdsnScQop7rWSXc5xrweOBakeJJyX4oAHI9EHPJhkPK3LcVtI9qDOz0AWUxshOUZDRJ7nyYQYGaOrW3t2FZak5cD2Pu6E1FfP0+dpWrqpzDNXPrVkt6zaJH8YyCGWtOyeHHpy5waPatve7CCRrxpPcqmRVyyILSs2KYlwZEJvv5Z323bAhFi35OMFuW7UQZOcL6BuN6Qnlde4+f9phljXJLsm4FQ9H6sbP42Fp+u+bPp5mtxdNQCh9cSB06CKehcnznOyB7FoAwhDNJn4MCTNSXrfcnseQh78ssfmBsLmBgb1e7LLAKFv91ldk6e/KOGNLM4l5Z0xa7Z+u6AKHm6ee/reobBa21FMkM9gtlgDWQqeCorSEWFOt3dEn7GLckHqK6RbtDs6Ojo6zgL2DfnFnOZrvz48Ac96THeOdk/heBPtyjrku37W51bJbd2pdWQmrUonKrB1qHhg66gvlsOTbcBI9r5WmTqus3ZOB2QCHokAmZut8vEk5U6htCJna/bIAQcY5NwBB0hEPXB2WBaRSLd3jObl4ge8cqScJpLxkUMhH/ekPRBjhRErGoCQQt8o4R45EW3EYPXXquydDURNYl6nlHkK+b+SaduXWdK2sEfN4jiC7Tv+dk5QSbZJD6LSNQBX69i2XhWM3Pn9b6tiHaEvrHbeYufz1nVA+fCtnsMb64XFts6/Bfm1yaMA8nrkJMCmx0+gF6nucYl8N0l2K3/LQZaWY27sSOvBkWyNoW1TAQJAFr4LhcMzlYyvxOocCGaB9oN+nlQXihNHqFtKFGB7jPkWufZy8Q0HEBMGpCkX6XNdEu4xyjunjgu1eqh8v2uSbQOWnlwLobb3Udu0WqZRppOTiPu5+za4G2k64FJGT+zo6Ojo6Dgy7BPyS/Gy/3Rrn699D+I8kI6fwbGH2ScgYErCUMoh6/wtb+O1lbb2al3niUziFG366HRfnlMtnVtQSZI5S8wTURaHZxwKku2t3P56S9ZsRTmPM7rQZDGHL0MejMiDFVphJfGdRaUbnkjJeX7h6PJbJ7x0ZsYxZGmpdebFAzFjYXEkuwVtOwXZ9+lcEC0UaXW6W8TC2fRCPkOMy/p0pLpB5ieEe+bcW0l2495rku2tuYsLqrxw55m7zwW0LNATzA10VJeePU9rIKU+dhv8gIQ872K6CtqDfnMkuw4t6CXkRYhBMFY0yrscsQqjLZpm7zym55g9t7OuK2pHbM0my+7XEXkl1SoPh/s1R2YmBc/pJI7NzIs454gWNpgSqXxPeNqkOzo6Ojo6jhrXXnUZfuSbrtw5/1/81d1470c/exZL1LGE423R9hYkVFaOmR4PsSMB3vpkBi3Kmm21OHE+uCaG6tU3iBQayA7QaKbzWFuuWw6zRibzlq0dXGZG9B3TGNJ5AoC4Sp3bmOTiG7Fk6/FAskAd0ICTIXUuByTiW5MBdXoGJOl4ngceCkv2HDSW9sDySwyEERGEE0NAiIw4ENZxRIgBPBA2Y5qDnDrGaR6lOj0rjJC1XLyyMuZO9jT/HOklf4iRF5IfaQRU5kX1XPeZa2/Nzw3UUDE44BqpWy/K37rcPiTNW/H0WEeyjfMquQCm0zTsPmTFk1yX1pSN67Yn2DWxxuRxN+GJsb6yusUQQlS8xyjufWKpRrVd1RM1jqW6/qJuc/u5kPzRbxZXxWoNZui6qy8ER1pdqC6dQz2ETG4HKsmuJ88ACjm5kWoZGPPpAIxAt+AH+HRb0zZxsPRN5GzhDgAxITABMZhle4xBoiq0IxQUv3odsWIzk821nliva8t1a91IdEmq7XE0Bkm6Rbujo6Oj42zjH37Tlfild38Mn7vrYKf8b7/1NjzlEQ85y6XqaOFYE23tDBXdPU+iF8h241S2r0nIHHkgsR5px7aWjLckmjXiDgxCqWxEJucrRFOibniQudmpcx15SJ1pTuR2RJ6nPXCyMEUkS02gmDqvVSUZqbZOcshxtUGlM7VGBft55oEY4IgVjQAGrJxle0UxzdcGQDFgkLBfkZTM8uxcbWCGYDtyXXsYXrJAFpcoJApC1Ix15rw2l9wOc4xZ04rTcvE7ubAnp+xGjFx7LJvRzHk0qUnEq+v5bV+fRrCpIJBzRffbhcCgJtn+UQR3nAxsqWdtS/cW2xasihJhJS6ShWDPkO2jQOu5eLItJNsPBKQDZLMi6ZY2R8wbhFsdoKkSQmNWF98gIdn6vpmTMpRTW3R/AGMVEmMsSTebY8PBEfQaeTAuf0NUbROIsZGwWQiOhMc0LcZLzIE0GJUmxVD6JS4cNQIwybiRbEZpwdZ512rFBrLFekK00SbW7v1YHJjpcbQ7Ojo6Os4yhkD459/+1Tt7In/b+/4cP/Etj+ry8XsAx1s6DpxZx9l1ahcNkkL+fKc2x6T11qFMpPbxluvl4n7Z6LxEJ2feCPG1fMjpiQgTNnHAQRzSLw/YxIADWbclrsptWUaQWbEP4sqs2LuQbEWgNAd8IjlVmamXlgoJmHotlqrfoR59KJ5yDiblzm9h0aoWLyGNPv+0467nyXJU3Ua+rpZrS7n9/QI1MdeVnG93uXiaq0vWblEMFhQX8xeVshdPlre8G7ug5vPFjZYDGFkCvnC/NXn356j3V2U4Sp69VSe8QMjIEfEmua7a0pkUqxm2C/k75d/RLAnPHsZXOt2DItay5DSupOMyiCb5BspW8VV1Xi8rJ7ft78MPBLS+BfV7Z3Hn/fvpyHYpC8/r5vgvOpm4HzRxeSbflLnBkY6Ojo6OjrME9US+S0/h86c2eM1NHznrZeqY4nhbtE2emTaZ9jBaWSc4H0GoLIEECZ2UiAwF6fg5h0MrsyDxTpZsYBpTdm4+NjAl7ir/3FDAKFbqTQhYqcV6IGykQxuZsBLr9gEPWFPqCK8pW6sGylasooyNV7clFx+cnngotMUB4IiB5P7EWfqGIoYhWdY3vMEggwmjyESzt24Gc0B0zpASSePUgZYKnMS7dWQ43UjFsJbIS8Ni6NMTkdMRgERkWU2plpctDwVuCysa7YLEwqytkfVS2qgBtMzUc07ZWM2j+m7IudXilmLIY0IG1bpHxYCDy4eyCnfmguROUZFpixGtgwaSJ9d7+z0ir1aQuuFIpsrmqKfgaUHdvTPtMZgg9+GtnHp8Scx46jxLjynalrQXbVYx1Yeei33912U0AiqbFaG2udkop7KsKH+nViHau69EOZPimCMGAEa0dR2YfuPK2Nl58E+t2msQDuJQRFlIx6ySLJwJMZDJyDkGRLs3sveknEZBNvBloblGygRb27SkkRBls177+PDVulWzDkJtaSc8Hm5wpKOjo6OjY19ce9Vl+Lsf+z9407s+tjXva975EXzFxffHtVd1D+TnEsebaIvETyNwLcnF8zHl8fZLPO3IKqTDqnO0lWin9WhycZ3jWJNsL6f2JNuHufH76ntUuaR2pP0c70BsHcJADIwrYNikznNcJbkmGBhSxzdQCrsV5H7XblLhrhJ3n2/kUBHsMl9kspBeCMCKAzZxEKvXaCG/0jzuiDEQKCbmpZZY5kxEJyVsPk+UhLtZr9U2VfkYuVetRKhK87Jo9R5u/sSNJFdkuyJHdjl3bnL34kkm+cZdPSt/upqk5/rztzitEzslN9LsxJPDtr9zrby1FVrTXJ1ytV2XTUOd1fXipeL2aVAuuyuh1mu6b8tehFyupWRbilbeAudL+B3UGBfYWlTKv94CXM+vbs3PLizYYlVeh7FYB0pJuSpWpgXJ34xR3v+AgCjfsE0csA5jkn9HYCOiqhVFW9fzRuRvKUu567BetgCZZDMmVmyzYI/yHNRy7QdHhIDrMzAJuXs2S/8jFvd3dHR0dHScBTzj0ZfsRLR7uK97BsebaHvsQrKBqme7JR+Q49RW4XOCkEPvbMgTbN8JLULbuDTv3TqlTS3aQLZUqYVKr2dWoUBYCaGOMv8iUEQMlPOAzEoVKZhFKjrGVw8O1LCQYEztTrbPa+Q7WbbVor2W8F4RhFUYgAgMNAgZD1BHct4xGlBasOrQPtmanbebJLtlFQTKNlEwVirZ0VL7WmBh9WGLocEWLe5tct3ycM++PMI02daRSW19vZp4zN3IURjuCqu1O6cn2ZPKm55GqHVhajay3bpmytLep4Qabr0m26gIfH0uX3d1PXL5CFjLwvmafslWbS2AK39BOhv3s4DCsVlBuhmTKAGOjBdqmJkJySMJYeb03RmJsYkD1HHjJg6JkBM7CXs0fxFBKmMXPxaFLwatq3pe9ohsua6t2IwsB2dYSC/yzwHTZ5gSp0kdHR0dHR3nEk++4sF40IVrfO4LuzlG6+G+zi2ONdHWTlMy2eWO61Yu7TJMrEcEkYsDGDjFqVVivYoIIWI9jOJlnLEeRiPYSoA9vLWakQn2GIMRayPcLr8eW8tB9VoqV/cSUABYDyMOgjhAC9GsVGkOZSytUlTKQoeq4ws4yTqikXJ1cub3A+24uoHGZEHn1MkeMSLIsQchWbajeBkfQj7DGHUAIjlJGxM7z4RR68qrEpR8aLsAHGGhrdaoQqJshKxuTS2mRrkhLQ1AbDOHVgqHpeK24nzPtb0kE8+qCq2ngnhX9TNX1IIQt8om9W2HNwYx6nOUMnLJ7GcpzNabe1eEnFnsY7CNaDBS3RTkW5qOxdW254eSbCM3Af/k7bC6LjzB9gSuJmqUj6eYyspBjtH6kedCnGXorN87yZC35dQLTayeF936LqyVUJtFO+Jk2ACATT0ZhHy3lCwtx4k6bSUyIYjDxpHTwGDgkEMHRiAimHQcId3vJoZm29b3P8nGpZ2bZFws2SNAo867Fou2XMss2lWorppkA8uvrrUj4vM22gABAABJREFUYNYzf0dHR0dHx9nAEAjPf9rD8ep37DYHW8N9dS/k5wbH3hka+Y7RbKb9z8t6YrVWC9k2a7bOyUZJspcsvd6K7Un26Ei2xmjWOM26npZyPvMYCZsxYIwBmxgwMuFgTM7PTsfB0jci1z49DjgdB5yOq+wwjfP+5DAtWJxunVcJwGJr633MYaBYLEU6ouusS2derGZ+bnvLKVp6ju269Q6QCktfi2RXFkNLg8tXt6fqfEWaL0ORMFdDu2ErtbS2iaKuykWdqEleCCFYeh8W3qVCHKDn2fJubSMocCR7IhO3smO6+JM3j508onJ/I42psb10vvqaM6BW29N0Ln+LsZ7627aljc1NQWkNABbO0GQ9h//KVmzv18F+kcm2Lpq+phGDHOfXa6drei3vLC249br8Syit2mTk2QYqjFCjmJ89cX6m5NtJyqkaMGktW///dHR0dHR0nEVcd/WVeND91jvn/63//RdnsTQdHsfaog2g3flsdHy17+ktWmq5MmuaWNR44MKirY7PhiFZfddDNJK9HsowOApPStVarc6+IgObcTByHaObayinmJOQewI1iqVnjIwhkFm5R5F2jxI2S50b2XqM1qHdcJ4jmazaoZCNDkjW6EApJjY4HTcizEpHFUF6twOSpWsdRowxYI1k5V7RgBAYmyFgwyM2Ma2n8qeBBSZGCEgxxMUyW1r94Qi2aw8W+7ki2UWFojJPuvSa4LdIoOXlqWWTyuweU1IulldnrW+yRJo6V/NtQrfzdahcDxEcAwgkA0k0+75MyhzyLc+Os1hdpnnqjPa5iRd4SaseF6/HlfkZ+XnW55O8xS17C3Z1Kj2dChYA2e9Cz1sMdmoXk6q257etqAwQq3UaRgqnpI4kn7tHP8jkatV/SyITBmASzmtCcIVcp1BgIwYkRYwSZiXSQBo4s1Bfct01jUVYQA0nqETeHCxKWK+RJG42lXG5tUzMbL4ZUjowuoaTppakOrMwXlUoL3K/njQryW4qDxqNs8X12bU50t9u0e7o6OjoOMfYN9zXL7/743jywx/SHaOdAxxrok2+AwouYyvXhEh3ud4whdzbtRi+AwCVi68ihtWIYWCsVyNOrEYMIeLEMBYEtoZ2KNV6PZpcPFulN2P2sD2OieUb0TLi5crq7idZJtkInlrZNY7uIPe80gEBchYkJycn8iF8RpOfryQMFzCkUD5hxADCCmNBtj28lQvIc7SVZAcaU70EJy91ocMiEzaUw5ltYsA4pHOMMhhRx662B6pEQ2XDrhPtLdy+yMZLArs0xoSYAdutqC6d/DkWe+ey6WXijhy1BgXIMz7ALNdBnfA5wq0nYccGYhSJrZJsK+OUIqpxEEoguSp69Sw8eU5Vm99JG8cgZJJY3Vu6ZlV3WsdNiyY5Qp0ZMpPM15ZzzMXQ1vK0vhVFXG4tW0XAlJxZHbWK6J5lTbjh64WFbMd0QoqZ0KscXkOBJVKevPLrQ1LCab+NotQwkl2Ra33f1SIdiHFBOLD3O8/RjhiQ42orVAY+UlLFjCAcRPk3Q7ABMP0W6DFjGC2W9iamb1WsiLdVK1O5OG/jBckehVCPmWTTZL62I9pYGBhpwQ2+WbZdKr+jo6Ojo+OIoeG+fugtN2/9VxS5O0Y7Vzje0nHfGfLy3hbmLGOOUDC5zj4lTqnexdWruC5eLl7HQy46hciEO8vGXWzs6Ei2dhoZNudQY8GmbUmTc0Dym6xcfkeTl6vE3KdlObnG407bg8XtVum4InIoQvQoxh2bj8rIVWY6mCXNyU+dtJTqukVFIM286C5SkJqSZKsEdHJMa1vaxCIqgt1ybtZ0eNYg2cbfKpJtc1CXylldbxqLvGyXKZ8fqNlyb7I9K5luoVW/u5CPXcpS7OPteRqo72Uih3fnrgcWlsvTLt5s9qrt2u3MtVNN8wumeVtKmBo1cVXfDCrj9nn8fOzgFiXZA8rF7weStdtPI/HvuV2b8uBgXcZtsvFW/RB7b+FkA0X+ezBbl8jbxbNoLH7/PsXs6Ojo6Og4G7j2qsvwd5/68J3zv+w/3Yox9n9gZxPH2qKtHRyzms11Pn3f03FDk2kHiHdxACsGrSMQGMNqxHqdrDonVqNZsk+E0UJ5WSgaJb8o52Ib0Y2J0Coh3mwCoKR7VMc+cDGis5mEW8SO2BxHUUgefPNccrEYD8l5G0HDj7lBA+nExsHFsw26PiZTNAcgbLDW2FzSWR4RsHKycZvvCReXe0ZDGZFkrCMlp0cHPGDFIcnZA2MTRowhYEOMA5HaA1Fk8mqFrAgowzwNk7dozXWkAdSnydZTvSlHRAtLa/UcGvtbJLuQcduKmypQSNx9XsrnVytm4Eo+jmJQorhPYnEqlbZjlDxm0daFLc2ccgWYxXcnrizFy9babOr1Fu8m6p3byP3SgNou5+L8WyjPvZnZX0cJW2W9JFc/bO2zXJ+F/255AqcO0Tyh01dQv3dM4KiKAe9IkZ2DxfRe1yRWMfE2jnIuts21Dhsj1msaLbRXa+pIlokv7OM0ipkcpAWodHwVRvFOLsHEBfX8ckid6WJqFvahvFDMuSa/zdW6+0b49W1WbXvGkHdmIW9HR0dHR8e5wK7hvoDuGO1c4FgT7aJT5LYZmO2oT8mVEBGdl71ihLV4F1+PuGC9wRAiLlhtcHLYgIhxYhgnHrY3lbOwTUw5xhiwGcVyvBmyY7NxyBbqMXvdNfmzdiDtxrTMZPPKTbYqIciAtE5CxJLcOhHUwZHu1TBCY39rqK4hRDCPqVM7ABjVUdIABGCNmOSeKgPnMsRXTbC9rFSt44OL2T1SsHjekQmbMCCCcDoOGMIAYsY6DEIegrPMVvXjCKrNuRyVdLt8XmUQ8uPXOizag64HnqQX5Br5WLUQT/brNf26e8Z+YMXW/QH6jOU2J6G8nMVaB1SK6zopscUlRx6smZh43YADh7y/yNUiE646fNHtfZR1k49zmfeMsAO5NjLtCsd5bMF4d3Gsrx5md4+5zRWEuh6MmSsuM9hfGLmtKpH2BJtdW04DMly0f31OLB8+HeRr6U1qz+PqkHAdRqxCJtkTp2YV0U6W7imZHuSqLbVLoIgYKV2TWd7/KN8UxoAkF0/fhDwQUDt3K9QeVicoBt2STFzULCodH0mk48iO0YBCOl5bqvMzK+/Ft6dS5t+o9I6Ojo6OjnOEJ1/xYFz6wAvwF3919075337rbZ1on0Ucf+m4X7ZlN8udX+AWIalmGS7l4ippznFlt/eqIufQXmVIGuTwVGqx0g6jzjX0BZ/NCzc/UevCy9C993KRhouF3UvKWSTjJkuv72Nfja6Drysj4pStYtM4vnvSr7odFJ1lN8KipLFx+kloL0+kdyTZ+XhH6lE1TU8QXNmKudm1Vc3v9+fYglp6P53Dne8BVFRR6YGbdr5kCSn71sd5rq2AM/fC9X1SuUxk5nVeVPXWygdkkn1YOLWLJfmBOUsrt+c9jzt1isuj3zmFysPTvqSKqZeQAnTZ+12jHqDUKSTb0po1Vk+vANx7Q8vbPn/93XDrVKVZedx2t2J3dHR0dNxbMATCP3nOo3bO/7b3/XmXj59FHGuLNlBZsTlZeyYGLu0ki/U6p3G2XK4TuR5OjDhx8gAhMO534gAXrg8QiHHh6sA8c5eWlmgWWyWrOg86OT1LYbZiJIybJB3nCESRjmOUBRBLi+tEt6x0Ku8lTm54pRI4kPyKhRsADwCFtD87S2PwQOatHCg74ErOAg0InJylRQ4YaDRv5gCMJPv514Obm+nnaeaTJ+uVWrbVqr3mMXkkZ0qO2CgCQeTuQvxLb9qwgQT1MpysVanukhMk17FWayOlvBwWPijBtRNyll9Pqv3zsHrTlZlzK1m2ARZJ8wMktUXbkzRx1mftmJNfb080fBgnbRoRua36EGB6b2yMguy+OaQy8ZDaWRISlFbDltVPt+39ozK9NHVPjzcnX9TIO7lO9Xzr88094tqK74kxl6cur+eszeBUVsAc9JGew5Fy75Hc2k/jnSb7fuXrTOo65ry5HJqHXLva/s/Sh9Cyudlgs1av1RmaSMYtnUasKcXUHihLxwvlCskHloWUU8Aam+SNnAMiRYTk+S19QzgiIsnFA4uFG4Ocl4vfWeiAjvMi7r2Mh+K7INUey/VaWWDnhUvXZPsWoGjL8u+go6Ojo6PjHsU+jtE+f2qD19z0EfzoNz/ynJTtvoazYtH+5Cc/ib/9t/82HvKQh+DCCy/EV3/1V+N973uf7WdmvPSlL8Wll16KCy+8ENdccw0+8pHdAq17tKwP7YworNcWwkuXFSOsR4R1xGo94uR6gwvWG1yw2uDC1QEuXB3gguEAF6wOcGIYcSKM4pk7FtYX9Z7t41xHJoxjwDjK/OxRpOKbAGwSyVaSSBsCNul3bkEjj5F1OSfLEjcBUX/HIZVjE7DZpPKorH0zBou/nazcMlCAbN0edzBpequ1Sk1bDpRs24UMWlH2eLyS+tW42trRNpJbEBHKYX1cbFz4zrYnK46YZGLFro3kdZXkU7EgL0KmKCw0QKdgMDIkTu5Yn1t0v4X3ZH9v2buyKhW0x8/VQISNvxAjkP5WDtLkBTKyQBCSDfFZIERbl8CyYGLdbYHcezn1QOaeAap1X28+bwvbOeVCAdNSN6W5BTIuxsERZyrTivx1HVF53a1oDGbQpLD5tw55N1c1nmCXSpJSWaKDZiodVyn5QIwTQri9rDzn3cgAnJ6jnEri3/tM1NnmkedY3rmczeopBqzyUkQb8DGxK/I9t9TzuSf7eZp/p/9BHR0dHR0d5xD7OEZ7zTs/gv/yBz229tnAkRPt//N//g+e9rSnYb1e4zd/8zdx66234l/8i3+BL/7iL7Y8P/MzP4PXvOY1eP3rX4/3vOc9uOiii/DMZz4Td9+923wCwz6dGuv8cr5rcYJGFi9bYmUHxqoK4WUd0uqiyQlaMGdoeYGLkQ3zJA5GtmJOOoWUrStV565OM6c/XK7XRE1l5SyWX3PUJuVS2bjO5a2duvntOfg6WZLT11bu0nla7mjn/GVdl164yXVw0/0WAy9w9eatVDuisFZ5C5ZlKHvWVC0TOGIwkfk2t116NTAAtzoXd701l7u4N3dfhbpDBhmM+y4Qx0PJyWtwtT5jUZyyX38Mlfkdgadtz37uHlrpRX2hfNiN9jKRnVfNt7U+W8zWPRwhqcvv37IzwzM597755kj2NjgBSkLVpmrFwEQ9UBHn2TTMnLOjo6Ojo+NegGc8+pKd8jGncF83/mEn20eNI5eO//RP/zQuv/xyvOlNb7K0K664wtaZGTfccAN+8id/Et/6rd8KAPjlX/5lXHzxxfi1X/s1fM/3fM/O15rIKIHU0SGfAUkqHIRMqNOzwKAVi3fxiPWJDUJgXHjiAF908hRWIeLC1QHutzptHnGVBLZCXamHcf3djEO2Zm+SUy8eQ7JiqgWTUUqenTM0TxCKTqNyCkJWaQZkM2ZgIFCWlgchTZGy5ZUJIImrzISojtRowBCSh++RAiDO0tL9tZwb5YEHLxv3oX+mDy0VOIIRC0dIMTlHMktbw6kXl1ZdVQMgIslCnRM0O5zddYNL4wbBKdgylw7O1AqsWWfIgxJecpcurW+EYi6+k7ib3F3L6AlwpHxSeZ4xQOTW1SCAIBAnxbEOFLhyU4igII7StM0wi2qXYAGvdRAI2nRSOvl61fIuQNsza3kYSDGu2dbBKsmWe9Y6q+X6jkgX9aV12ChLU/rrz1lBXpG8re+iPQOJ0a1EWo9JYeaT/F4LIu0x1fW0HMW9tVAMKsCIHfs0K9Y8a/dSbAuvZ2oTCc/lrNnFPnF+piG8NGyXx9j4RmxDIE4VptvIvhp8nkWy3rBs66BkEAdo3pKN1vpkkCb9UEOKr3PsSd47a6bkvjsdHR0dHR33MJ58xYPxoAvX+NwXDnbK/7L/dCu++VGXYAjzfYmO/XDkFu1f//Vfx5Oe9CR853d+J77kS74Ej3/84/HGN77R9n/0ox/FbbfdhmuuucbSHvjAB+Jrv/Zr8e53v7t5zlOnTuGOO+4oFgDTDnXdWYK3xrFYsGGScVpFhFVMYbxWI06sNjgp3sVPDhtcMBzgREjra5k7XDsQihwKJ2IavzoymYfxRBCRpcJjmk9IQroTSYTzlotF+SI5YqmedMPGkU23D27hTSL7cVSyGqyMPu52jqUtJLvBADyJ1hi7KX3aMa07yrV8PMfV5mb+4hEXFl4h1lpvnmRXss6mddtforBCshFuC50FZNl1qDTpbqEWo9NrOQl5bZU1ghjLJd2bJxJ+XjcVFu055YGNwVB2iEbu3sxPgQxGqEScB7ZBKpWVe4t3cYv7fpO5JDel1bAiy96SHd16UbcVyfTnnCtCZVUupd8ilbdtZEIdXB5flImsnNz3J/8Wx/j9DeQ6ygM4+f7cQ9gy0KGo42cP1XuXbiP9Jkl4LPIvWbq9Ndwk4zsyz9rxmmJJmQEAqOtA3gv7Drh2MPstLcg5p4XTb31c2s77vJW7W7Q7Ojo6Ou5NGALh+U97+M75NdxXx9HhyIn2n/7pn+Lnf/7nceWVV+K3fuu38AM/8AP44R/+Ybz5zW8GANx2220AgIsvvrg47uKLL7Z9NV71qlfhgQ98oC2XX3553uk77Iq6809uXefdDowQslz8xGrEidWI9TDKPOwNVhSxFnKdLUDpYt7C64mpSrOzBTZYGK+iI+asKdY5dPxtbq6gETBHKDNhp4KAK1FDhJsDjCQlH/NAgHokZz9IoBLzQ1mp1PJ1CA/irk79unpPZyB7WQdK0l1Z/CbST0VBtimnLcA6+JUEu2VJnuRtkca6LJOlYaVzi9YHXN0swc/bzgQ7kWsyku2JdUpjJd4VUfT63FpSPou5Z1H/tgZFZs43Iee+/uprtE5RkF7fYMq0yYCCJ+BVei0tZx3AqPNXxzbP10AtW94XLcWIYldi3IJatCMHC+81VsqffTDxPL7jt4R8G3DfgybZ9gTbPjB5XzF1x6czivxoNJ2Ojo6Ojo57GtddfSUedL/1zvnffmubi3UcDkcuHY8x4klPehJe+cpXAgAe//jH4w//8A/x+te/Hs973vMOdc4Xv/jFuP766237jjvuSGS71eGsO8JCFCAEglYRNDCGIcvFL1hvcNGJ01gPIy5cHeAB67sRKOJkGHEyJC+72aoboV5xIxM24jhMF/U4npyfUZaMO4dXZs1mZCu0dtQk1DTJnGqg7Lx5UsAkt+s68UyUJeVDIkpEBF6xScyTZ2cGmJOBULyPhxBAADZDxCoGIGQHb+k3oNZGemv2tpBnKhNtxditibX+WugxVQe4gQPaULb+j2XdeRl2qic2z80YElHNHWWRKwNp20hpqmdyPehWiCzzLq3n4eScrJ43PQ3hRaV39Ogk2ZxOrKSWQAV5Q5SQcSGHOGIpQwRjoFznUdJ9zO0Q0iAIByAOsZg3zgQ3IKSNjItpDeZ9W8y8rtp2s3K7gQ6K0pZjeb96Dp5hL9miW5aX6nqur9k6n+flrcETFqk45+8KsbxfIdUHh3QNJiCHMyfYCBGh6ZWaZUCjGMhYKMthsG3QazI/euY9jhxsXy0VH+UbMULDBjrCDZ1us33gzk9JATCRkutg0eQ5Mjmrs/suFCogv58ngz9zEvJ8cffLSP9XJEGff0dHR0dHx70FQyD882//avyDX/nATvnf9r4/x098y6O6fPyIcOQW7UsvvRSPelQZv+2rvuqr8IlPfAIAcMklaWL+7bffXuS5/fbbbV+NkydP4gEPeECxAFssCLVlSR2fuWUYItbDiNUwJnl4GHHBcIB1GHEypJBTJnPGnCO0bL32TtC8A7SJXNhZR0zm6Kwnll5ZseE7jiOl+YexIpvFMZTXnXdzJfwsTtKs/DHd4dSxW/tl89avlmS8yFsxjG35/Rx4rVOrv2JecyJopcXK1TO0I92wcNZF2NJJ9iQ7S68z0Z4lAHDXb12jsrrVVjKVyLesv4lcL5c7l62UwBfz0EP2sm7WanlnCk/j9S9QvGs7EUNXfqrvXeuqqANqLovW78nz36FYjXsq4C3bdVplxa6XpX3Zol0ODu00YHEE2FfmDSTivLRd7qsI+R4qmekAQCNTiySzG7xsWLGT/Ltsf2a9ruZuF4vLQy6PnWPnO+vo6Ojo6Dg30HBfu/yP+vypDV77zj8562W6r+DIifbTnvY0/NEf/VGR9sd//Mf4si/7MgDJMdoll1yCm266yfbfcccdeM973oOnPOUpR1IGLjq2ShpELi7W7JXKxFcjLpC52WlOdpKNr0MKOeUdB3kUnrlB2Ij02ltfVdbr51CSJ02+46adN7V4N+dkV+s2N5sQNl46DgRZaKP7YPO3jayOec52HINJyFU+ngcPqLBsK/bpME8622r9kkXr8oDzHPEkZZewaFomC4EFN18XJSmFq9MZEmuKAes0+3OJZbcm6IKSWJfEO2dyBGGWfPslt5G6vHpfnlyym6vMM0uNQLCQaRpTnQLbLwLnkHeDhMDzZNvP41YC6WTlLfLYvOd6t3+GJufNz2brYvU39TK+VcpbDxrUhZsMKvB0YMH/hvybF8r561BgFjaMlutPbmSH8YK94WXeCrU8+/d2ZMKIYJbpEWRLTkvW7IggeanMr+868vdzV+w0DYUpf/aLwTe4qTbcnpLjyXVtGY9VWvVdKWTkHQUe/vCH46qrrsLjHvc4fOM3fuM9XZyOjo6O+yT2Cff1pnd9FGPs/9COAkcuHf/RH/1RPPWpT8UrX/lKfNd3fRfe+9734g1veAPe8IY3AACICC984QvxUz/1U7jyyitxxRVX4CUveQkuu+wyfNu3fdt+F6vbgO+kBkcUVtEk46v1iJU4Prv/yVIuvg4jLhwOcGE4DSDLLSMTTnGuKnWAtomDxZwembAZpWMZQ5qbzRUp1I6eEWnKcnFGtk47i8nEWuNvXwmf/EmSVsqd/ZGTfJyAwGQy1wgksgSxooXkeXwcA5gZmzBgM0QwkIhuCNhERhxIPK4fzm4T644651jdBzxgwwMiB2xiiul9oHG+Y0gDAZuQYpCLRd8GHBxxnp0DjFS/RpQcieMoCUEqNXJ6XiEfnMk1HLnOv0psg8qIpcPPpjWuylQNCBTPWsZ0iGHPVb1Zm4ScOSsSIqVbiSSe28sbN78CAEKIJrlmkdCne5CBDCIwpXZgbrFUEmvuwqkcohOSUXhN112NpqLScyK5J613cL5fbdTUPs/sPGVe2DcpiDt3Ra6ZGu+c5pf6IEJqP05GnuTEqOoHcrNIbatCegcd8XbrrYGASXm3YBeCqu/0KNNDRhCCjBiMlN7VE7RBmvoxYCAuiPmoA48IJhk/kPe5IONIg2ilrDw0HS4G9361Fkb1kPx7VKh/8m8Yta3m96xoM/X3tqo68s9CnjmRe/a9X9LEu971LnzRF33RPV2Mjo6Ojvs0nvHoS/Cmd31sa77P3XWA9370s3jKIx5y9gt1nuPIifbXfM3X4D/8h/+AF7/4xXj5y1+OK664AjfccAO+93u/1/L82I/9GO688058//d/Pz73uc/h67/+63HjjTfiggsu2P+CVcem6ISSEB2CSWODxMYeAmMIyeP1ikaxYMfCit1CETMbpXS8UZxsFWWg8KY8kcdWVpiaZNcEAtV9Sj7hZlIPiTSSWCERAUYi+QwWKw5l0sbGmRCZZCZ62+v4iICAsVlH+8JbzWYdywG5A+1lob46XOdY15tjAr4TXXeotQLrdWRiXa/7bW9Jbs3TbpajeQ+ZRCgxnS0n3P4d4Odpp2fOGGWcIcoc/jRfWhOzRRZGglG0P+XfxT1sgzVWuEbLllSUuXVsY3tnkq1ZKoJd7yt43Bz59oMp+i5W1ul8izKwIQ+MiRo3N4PDjW8demDMHx+UWBMQEDEyFeEOgZJkqyU7HZ8H1pavs6fAakElMvmO8nRf/X0tTulO7UN8Oe8B+Zur7YIZrXBgHR0dHR0d9wbsE+7r7bfe1on2EeDIpeMA8Df+xt/ABz/4Qdx999340Ic+hBe84AXFfiLCy1/+ctx22224++678Y53vAOPfOQjD3exglTDOrXJEVgiCl4yfmI14uR6gwtWG4uTfb/VQbJkD6dxMmywphFrGnNsWbMIkv225jF7x13eKzQavy1pcLZ4w6wuwcnEbZFQXmEj0nH5zXLxvC+odHzjrDut8F8iGy89kAds3MBCjh+epd6jk4XWmNQPSsnpAQ9i9SKciiucGlfYcMDpccBBHLAZk2U7ipf0ZM2m7E297kQDqMnVVEKa560nS7jOcRfHZLKoVTrPYYc5FMvtuLU4r97SPL01fLEpT8gjlfdVLGTWeJ2eoAMS6itACZZaAHWAKRCwGmRASbzuDwMjDDENREnoOwxsXvrZ5OTI4b+8BTbkyi7DYklafe9KbNy95feACglv7aegkPkW824bdVQvO6C2HvvBu3xP1SVcnUyl466OLFQaZUn5XL7G9aeS8p1uqfC1oCR45KxQMXKM/E4f8CDvarB3deSAA17JMsiStk9XafqOq2Q86jsfh+qbQJOyKqZztHn+lmsiDdj3NH1LeTK1xr6vlq8M7zUN8VWm+d/zEb/7u7+L5zznObjssstARPi1X/u1SZ7Xve51ePjDH44LLrgAX/u1X4v3vve9xX4iwjd8wzfga77ma/Crv/qr56jkHR0dHR019gn39Ws3f7LLx48AZ4Von2vkzq108JVkCzkIa4mVvU4k+37rA9xvfRpftD6FL1qfwkWrU7hoOIULhwOcDJtMtkNpsdVOaWQyefMosvExepINcYTmyCAwJdjI5KKeB+gJthFqT6IPFhZPwA/0GEr7ZN62zdkWWTtLbG0l25tR7k09qosMtBVjWzvmfinmdtp8zSwnPYgr63Sfiits4oADDrh7XOMgDjgYh1SGMWCjknEXxsyTbSPTk4bh6trP0XSxy9WxHI0o568b4VZremmpzqR6bkEulDe9e9JUl9XKTG6AwA/MyLpOQ/AEu7b+VwhSriFErIYRQ2CshuSnYAjJZ8FqFTGsIsIwJq/kqwhayXskcbWNbBvphsXYLmXPFeFuoX4PivmwznmfW/eLf046Xz/7OHBOBn2FtApTE2l7ZvlgI7utRQl2qy4GtwQgDu10X49oEHM/kJjnh1dmWFXVVL8eU1Ib7L02EiyEWN9XT57v5rVt3x3XuDum7Zy+qo4Z8rsuRD1/D6gg/bUPCI9aZTQZtGL3mhmx9t9RNoJNRVoizmFMS+0Pw85R+8xoOFM7H6Xjd955Jx772Mfida97XXP/v/k3/wbXX389/sk/+Sf4wAc+gMc+9rF45jOfiU9/+tOW5/d+7/fw/ve/H7/+67+OV77ylfiDP/iDc1X8jo6Ojo4K1119JS46OWzN99m7DrpTtCPAkUvH73HUhEa8KFvMbFlWIVqc7DUlq/WaRgwUzftu5GlD9CTT0hY6ts0itqSL9X6f7vOWPtnsVlnymaxRLKwakStb19mZ4hjEEu7LWQH1PuqBrDyPU6xRFLBekI+3wnil9Nyhtjnb5lCpUgqYU7nlOpuAq3W1KssgiMrsa4KbdlbpC6gl46SnIAYRJWvuGUp3VZvqFcq2SzmWW5+D+hvQdZUxDyGCY7D7IaIUnyoOwl4INmFc3yuGpbHcd8GRlsqiVezrWU49uQfa4VmfbTQqnqW8taXZ0jWN7fEV28VpHXletFDv0YyYXdtTRQ6TtYFoIwPT93fkgDWNznFZcgY5qvm9UY7sPE1DfGVnh9G970XovmLKSKjOR0VbtSpYIttFBeRVYp4oiFTiPTsXu25z+t1Bfp72/TjD1/vejGc/+9l49rOfPbv/Z3/2Z/GCF7wAz3/+8wEAr3/96/Gf//N/xi/+4i/iRS96EQDgYQ97GIAUkeTaa6/FBz7wAVx11VXN8506dQqnTp2y7TvuuAMAcHBwgIOD7VLHbdBzHMW5OjruDehtuuMw+M4nPAy/9O5PbM336nf8MR7x0AvxzEdffA5KlXFvb9f7lOt4E23tnHpL0CASzhUDKwaph/FV9jB+0fo0LhgOcNHqlFmwLwgHWEsg5jqMF+DnGYpF2zxme2siEKOa9FCQV8Bte3C5WIew9nLrPZU3GJXO9dR6UMJnsbQ3kPDfBBo49a8J2cGWxqimNG935OTlWr2pb6JKPwMCc5qjzWneZhRGHygCPKROOQ8Wwmu0TnZw8tNkydbfL4zr5ABtHJJ0XCzaUazaPga599rebBYVydY6NYIDCHkEMKr1mcTzdnp2HMgcdXHUGLlcyMfn5mynus+970y8jqBXboMl+TeNDbSsmalMXm6r82qZvMf0UMwnJ2Jx6McS+EmIuA7YDMgsR7g4R5g+ZtcoUUY09Vl68qoDCGdCsmm62hzz2PWx+IEBfy4dJAgS71zrIr0O5mNPHcCZAdqfxxFtk6B7hcCOZLw1qMOSnqMIiPMxBjYcEDhgACFIZQcwBk4hDc3CLO91hHxUkGJte4Ks5BqAEWyTjMdB8ojzSLFob3gorNnjglVbU4O13XrUCfl9B4qpONlCzZlsx+rY+nqNNIYMXJJ8h+Vbr4N39/ig0DnE6dOn8f73vx8vfvGLLS2EgGuuuQbvfve7ASSLeIwR97///fH5z38e73znO/Fd3/Vds+d81atehZe97GWT9N/+7d/G/e53vyMr+9vf/vYjO1dHx70BvU137IMv+isCsN2qDTB+7P+5BQcfG9vhNc8y7q3t+q677to57/Em2sC0gyqyzBTOKyKsGKtVxMn1BieGERetT+N+q9MyJ/vASPZJ2kzjyEqnyUJ4Cdne8DCxvI4W3it3alvncsUuyGIxl1g7gTr3dESaFwhHvqvzqdM3duGEol4jlNYfGpHer+gyyYAAR9gc81Hiam84gJhzJ52j1ckBD1hz6sUexFXSrHPJuLyFy4i2SsZ5wKmYyPWGB5waVzi9WZlsfBwD2OaR5zqZzF9uwQ9coCQ42RopBJukuKNY+AcCYvJsrNYrKkyw7jkWCWIRhnhGFhPYomO0XS3eNbdw95/J1NTSR8hWQW8d1LYbhhGBgjmfG4mSH72Y2F4EwNFVXpABGRCI2Yh+GrRB9sCMeYuhlc0T18nKFqvl5GTl5px1fOKtWq+5I9lOahEhWUqIZXAMBPGirm0m14e2I023S3urtp/nbWnybiMdmNJ5trwlqU4DZnU4wihlV78LQHqnDzBg4IgDDMn6LWR50EE0cP5OCuEuwoKhDOE1ikrFS8UP5LhMskMm2c7/Qwtz1u1886lC6zn+5u+iDtE1B9d4inwyKFeoEO5D5NrjM5/5DMZxxMUXl5aOiy++GB/+8IcBALfffjv+1t/6WwCAcRzxghe8AF/zNV8ze84Xv/jFuP766237jjvuwOWXX45nPOMZeMADHnDGZT44OMDb3/52fPM3fzPW6/UZn6+j455Gb9Mdh8EYGf/Pv/hd3HbHqS05CXdtgI/d7ytw3Tc+4pyUDbj3t2tVW+2CY020vXzTd1a1E0omG485Hjbyog7PtPMYHDGsMbqOqv7WHsfP/Iaq39b+ijwWlkDlQmq5lY5/cw5hfQ2zjM7Dz8sGknVqhSjWsYAgioARhAFcyEkBWMzsCOcYzci7hPHi7Mgr2hz39IALr+2C2c7yQl2afByODGnFqZVKTeAt9YCzap9rWFmtMLk8JiPf0h6V9CtpGeX4IPtItvNCOawRpUEdErLKpGHM4GTzuWz5oo20xr0B1bjDUjXXt1ldb8KBPJl2kuq6DDu/zrVVVb49LBfXiF6+LFo3xZWdlZr9L1V5zhBR3kvAf8fSwBnkfczvsMSTg849SWRb3/XWuQFsJdkqFy/ffV+WdvjAWYK9VC/+G+DW8+DP8jt8X7JOny18+Zd/OX7/939/5/wnT57EyZMnJ+nr9fpIO1tHfb6OjnsavU137IM1gH/6Nx+Nf/ArH9gp/5v/5yfww9d8BYZzbNa+t7brfcp0rIm2EmyuJOM8MLBWx04RJ1cjLlwf4OSwwf1Wp3HR6rR5GFfJ+JrGLIV0kkgfqkYdBaW42cFZjbxF0TmjMs3nFvh+o7MEZqsMl/G1fZxlzvUAAAhIElByYbkYIImnbcdT6kcr6SzKovfh5nPqvSapacSGB6wwQj2Pg2KyVEnZolMHeBlpLRdPDtBW+MJmnT2OjwPGMST5slq0OZetZdFv1edkrrvs03nrAIowTEGcmoORLNt6iIS3ikGm/DceaU1a92JGM/mzNFlvpCahjko6kq1E2s/P1fINIRbnHAAEcXjHxFgNZNLxOOSLscjFGamSxJ6d5877e3B1a/vnbnNmIGQv1JZsY7VuIK7iZpqHGsfkhC3X1HePcztKg38pgUN+R5Vwe/ZfDCxQ9asO0Aprti6u4AvF9N8kPy97ExkrygOGBxwwgBE4OUIMYIwYLeKCTanRNtOYG2AEm/MgnB+UVCt2UrWkvBv5nnrCXUZ0KAl9CjGWzrn0jqk6qLBo63fUrTcHguoKrM8NFG3f5OP3QTz0oQ/FMAy4/fbbi/Tbb78dl1xyyT1Uqo6Ojo6OXfCsx1yKH73mSrz6HR/ZmrfH1T48jrfXce2YamdUwnnlkF4Rq1XEidUGJ4cNLhg2RRgvT7KTdZvNqq2oLTL1Unp8loMalted4SzPJiVXmaOTPxZhadQzedOrLpy3bV0obdv1nBlN1r11lK0D3LZGWZgvkC1qvZ54IJZlw9nb+Om4wmnxNH56MxSScTaP0ihl42j0jesBC1eHvh6L+e4a6syFDbNwUnJNdpb1ybNewF6yZzsoFX5Csuv7bFrrlsumIb7qRZ0DDrI+aLz5IE4EhwgKSLHoxfM4iOV9Y/fe6TYK4ui9Zm/lJHyIxT8vR7KKdwmuvcO1I1+PyMdP6q7O1yq2I8q+DsyDeLVde2qHnsPNyy6VOn7wRW+oURbWJatDGGW4vQ0PKXKCqEkOYtoehXinKADDxJdC4W08Ji/l6nm8eL9jmLzvG06RBaKcf45keyzFAJ/Ec588kLw0w3PNtBX/TlEjX/qdNoRdx1XPF5w4cQJPfOITcdNNN1lajBE33XQTnvKUp9yDJevo6Ojo2AXXXX0lHnjhbtbZt99621kuzfmJY020fUc0d1pTT4iC8zROjFVI0vBVyMQ6CLGuybVi5Gn1+I6fWbM5y8d3dd5kFqqdbzav5g6fi/nqPId7K86EfJwh6o6vD9UDlNJRH3dcZaQaN1tj6W5EMs7s45CHXKdW/mydr+tjrp48PFGa1MWkw+3IvTSyOQK7VKVn5MhrCQskaxf46RPq+M+TcECmYZt0HNmKqhUlxNFCWhXEMDNbqwJX5lkyUtVXTXKWFju+1ea5Ondjm6q0ybkb5cuZq3tsbTdI2ISYTY5ly7eILfvVou1/FUV8beRpHD4KwNxAo5Lo1r5W+K6aVM+R7MJhG5bJ9q51MMk+Q6g7Snz+85/HLbfcgltuuQUA8NGPfhS33HILPvGJ5K32+uuvxxvf+Ea8+c1vxoc+9CH8wA/8AO68807zQt7R0dHRce/FEAjft2Nc7be97897XO1D4NhLx6ExadUJ2sDAijEM0TyNX7g6wP1Wp3EijOYEbU1j6WlcyPYo8WM9MdQYzxuxxIwczFFY7rxCiCE5a/BMmettJyc1NMiDt8oUlm7AJKupHihtB5jEUqZZludu1ml753SAISA6aTkoeaVehxF1WLSDOJi34dNxhZEJp+KAu8eVOUA7NQ7YmGxcyLY5QcvW5tpKnZfGPrnXFtmy+ev6DFjqSx1XqWM0cLJqjzKQEkmU0QEh5F66r59Zq3I9WFCvezi5uB7KjnxNTu0GA/yUBlogKTrXNaC8jxgimAkDBWCQuw1JNm6O0aQ+We4hVaG7FkkbBRV5tK71LryVub51zzC3kSDy2T1BJZQOydwjSG2A5Di2spgVeYdrM5X703soA37aLuW8xK6M9Tk1mw5g6POut7cMsljV+bYAtjaR3J6l6S+BUtsOlB/ISJQ800f5JnLAQHlAZm5QUhHdQFv2azEl1ym9lIpb2sIAJwF58EfWlz9nObRXPQCp0Rus3VJ97OKtTv0lnOEA2L0R73vf+/CN3/iNtq2Oyp73vOfhl37pl/Dd3/3d+Mu//Eu89KUvxW233YbHPe5xuPHGGycO0jo6Ojo67p247uor8Yb//qe489R8uF4A+PypDV77zj/Bj1xz5Tkq2fmBY020fUeUVbo6iDV7iFgNI1bDiPUw4kQYcTJsCqm4zssGgAFxNu4zgInlpZCOa3kKAnUEPa7K2uLnFlrIL+Q8aQUpADZRzqM9fGe1mXQSi5O04b0VA2k+cnDW7IGmKoDCis1DtmRHkZPGNGixGQeMMTlA4+hNpGVdzMEXnap6qy1X7PMREpGWGEwUOft/4kTuOZLEaBLP4dpB56lTtDlHZIsOylQNQQuPYKk5LR44czqXPwgLjkxm1Y4AQoiI42AS8uQKK4AC5xBWnArHwcUqltBonrkS8vvRdJam5apI9jbJ9uRYysRJhkmK80hxc3mUiNtoS3U9X++uDc0RZc2mjtB0vral+/zVNTyR5uavb+TT+295nNc2OiWzsk6ZdG84yD+E9HADq8O8FEN7ILZBNB8C0Yfjqsm17m+R7rpMtn8fSzaQH/wcHKkuSLaNZUlMeR0wap3KjXsxysdnO85DPP3pT09RGBZw3XXX4brrrjtHJero6OjoOEoMgfA9T7oc/+p/fGxr3je966O47uq/fs6doh1nHGvpOOpOqJsnGgJjCJxk4xSxDqPJxgeK5tBnQMSAvK7InrGn5Lp2EAZkIrVIqBodakW2xu1w2y0CbkQcRUeyKZ2dO6Hb3ja/uNUJbklMNU29jKvzJZWMj87TuHcmxzbntiTb1lFGvi9fH0v32czn6sfP3baY3b7+dFCFZUCgLnN1PVM4FInL9ZoKWP5OqnrLs7HyuLLVkuGldur3qJScCBbVCASJOS6ZVSquMvJiX9pfDIoh76utx0U5WiSbty/ZapmeoXDFyfswaUNuMGoySDPz3HYZ36gJNFM7bfI9O+T/sfrZ2rdJtv23y9QpblvnaufvXp7HrRLwA3FqduBk4T6CgH03nRV7I4Ns7e9pWLRk27249Ynnf19/h0F1LPvtxsBHfR0mSoS9o6Ojo6PjGOGaR+3mwFKdonXsjuNt0VZv4wODV2k9rCLCwFivRlyw2uDkaoMLVkkufiJscDJscNKcoG2MSHiLiveg672NawdSyYvKx3VOcSZiWsBpp8sZhM3yVRMruE53ixBmi7Y308EODlI32SqbiUMrtrApJ4t1NpkmUIbXqZFDAQFJew2rPwBi0U6d8hQ7O+D0uBIHTMnTeLJoB4wjTZygUZP0ejLU3jfZtkpXK6b7dQ7jwAANAMZUQRwJGOVUIyEGQkBEjMFkrKRWS30k7KYTyHULZ3nAoqy7OSgj5IuLkZZ8iJJr73U8SvxzzaaKhCBy4sKyTYzRrQe5VqDk6wAIYI4Ig0rjI5iDtT+W9kqUPNYXpl1mIbsSl1xjTiMTb4r5mUzgB0nc9lK9ZWdZVBB+s3xTbq7Zczg5csXzRHrbs/PliC6eujvfZGDGD0oQKqdyXH4X5uAG/FiefZBtfR8DS/QAMAIzIlGyVKtKAQAisIG2AxmINA3+/hbtpjXdEeuWFbsexGyiVR/E9syZaKZBoZxOU5/TYdtYSj1Q0tHR0dHRcZzw5CsejAdduMbnvnCwNe/bb72tex/fA+eHRVu99gaWebZRvCenGNkrkljZSJbsASwexrmwYnt4p17AdD7h1JKNymKoKwtl1yyuU76LNaboN3rOpYTGW+AaeZdO6uc/boOXeU73+Y516VzJ16W3rLGQZh20qMtrVsrWBSesZSFPRdrK+qSZOeAQsuwt2TBCW1ymTivWW4VvZ02Fq9Z3eDa7OG3T59YiMaFoC+k9SYMJ2TGaDco4T/9aRnaksBwoQEEk54jjpEj+OdVteyatOdDiiW6Vxy5ZDMrMVPYOLym7+/LEvbBou7w1yd6LsFUPt/X8vf+Sqb+Fkhzr+5n355j33qIdQTtZtJes13Weuky147ZZ+Lo7RJ3tjE6kOzo6OjrOMwyB8PzuFO2s4FgTbetYFZLxaLLxEyHNz1bZ+CpEm5fdcuqjc7R9J3OsOomlB18pR0XUFi0wQJNkbyVUrTRv1dVsFfGu9/vrqjF4cjBgBEvXAfFWPWMdmvNMPEI65BJKSCXjNjc7Bowxh82KUjB2JGjJUq3kifz+Rl3MojovOatrkh5DrOkkTtmShTt5R1cJebluztC4iqleX3cLfNvgSftw7NDdoLeoazvN8nyyOi+IUIPotGBeyOWahUdyef90CocP+cUS8svCXLVCgDkLbkHI9X4nlVOVrdVWas/7LnybKRf8uraDKhSePX9ZJtLyRnnKZ1WSaV1YQ6PpOpX5mzL7OVQDUzYIhNIyPDf9pTWQuLEBsiwpz0RalD5ue+MiCcxNt1ki2EDbot0K+zVbDUA5mGHr1fHa3iD7qnetPketUigs5pjm6ejo6OjoOE647uorcdHJYWs+dYrWsRuON9FWj+MDg1cMWpWxs9fDiAucZNzHzda52UNFuEfkmNA6r/hALDSbGGzO4RgDYgxCsNIvwxNEmna+taONugNXykVbHcXivlsWv4JQcJOkzqLqTHrZuMVbXjhBy0I2ImSP7UKyVSq+4SQTP1DSF0OOnR29bDzHty7qtCbWrTRfNy00CFJNvmhEKsdIIPF+ziJtj2Ny2saRxEt6ueTwZHV89W0Ps52tkA5bGpode7O2Q6Y3KOGeId/1UsOH+QqBQSEmK/fAoCGm2NriiBC67qZ1QKIBpG1Ptrlo7y25dJNf1YNJ9XNzC+Q5ltsyd3ski8Gtsec1Vrsn3ajPueO7VQwU+Pfbv+M2+AAZoMjbJVF09TKDYoDHLygHXvy2klgdfNnINA/bjsEGyCIoD5ZVy+nGQFpe5Jw82DmW2l4xCNBo4H4gk1zd1vU8SfPEeeZ5ZRKdFw7knpekVSTc9s8/no6Ojo6Ojnst1CnaLvjF//Gn3aq9I4410QZKiw8oOUFToqgkcagk4nNycY/RdQYBF7Zmsae7ozmDyt9Fy92up9RY2lXa1nI4ApfnG+92zRpLXtsBL0OtpakN8tmyWNbFXyA6i1bsufP449hVT8OKDl111sLy199Pte3StxduJm3PZ9SeI9ueBtEsRqF2wKSCp4RHKxRZSg5Ye5sQnkPcUyr0cnoxp5ur5+sJtSteMWiF8vhifYfnN/tu+/ut66HOt3gB+dlSlvrZ1uqcYp97N+vfbYMz02OmKqE6r9+e+74yT4+foPUZqb+xto+KY1qnLQa8Fj6M5aDpfPE6Ojo6OjruzdjVKdpffaFbtXfFsXaGZpYzkV+SeBtfhSghvTZYUcSKknzch/OqJdDZK7aXPbq5xZjKxs1CZFYkzHe+Jx1oTj00R0yYZP6xt8qI06hmZ074KAHg6gKLRHOpQ1jMyy3PuhRDNzKJM63Usd6IA7mRKVuzG9LxMUpdqyTbnJ7RxJI9sWLXONPBtZalMuaFSMoHTpZtotT+JDwSE4oee8sh2qGK5Z/3jiMIZlEnxhgJQ0jWbYRocuLWNACdLqHn8L819HaT8zXkdsVA8qTGSRFAAEcGhfQcOTAIqW5SCC4yR30U5BcAx7S/GR6LfSHmKkGyMPI7BFhYvPT6kWW2/e79YM+vlq6FLfv0+NZh/vx+jMnee6dmmJsHArY2qyHomIEYCSGFuE9TNIiK95qYEIkQuCLB3ivaHiiJtJOJbyHYxe3M5F2sXveNNAdnbtscn7lvZjrGfYMBs1b7Z8Wt594JdUdHR0fHeYZ9nKK9+h1/jK+45IvwrMdceg5KdnxxvC3ahDwXdEhS1iFErIaIVdBFCDZYHKJlJ2i1bFzhHaEVc7Qrsq0Wzabzq1avUDt+7lct8i0ZYp1fO4b++DOtv2xx5GbnMTjSPQdv7fd1pc6RjGQrweZEsg/GLL9nIdww2XgiAZlYU7Ywestyi3hz9btLVbQsndH9jpS8kIuUHOIZPY657NHJtKMfeHFW8KZkfZfBmclADVxBkZ/PhOirVNyvlw6s6iVLy6dk28vISQa3iJB+Zd37TGjP20Yxb1tl5AjV+2BS6vac7qVnOalTfY5+4MSmB6TnG1RSXuepjsMe8nF9JM1F71/rzH0PsnScp/fbGnBxz4lluy0fz3mKOdqophOA8iDjgtS7NQe7GLBcINktC3ZBsivVS8v6nuojj6h4su3rN/+S+8ZSziv7JtL+us01vuH+u3zG3+SOjo6Ojo57CPs4RQOAl/2nW7uEfAuOPdGuoVY6I9YmH0/Eeskq69GSQXuJbeH0SsFodwRny+/IrfKwatvWq06cz9e65GE7fP6wXeLR+3A+iky8yw46gNyxbxDC8gb19x7ouToSb2Xgap9Pd2mLnOsovkU7VEftAV+hKozlY8+wvpssV/c1CGKxDyXZbOTx2FbUWcLN03zFOpdhuCYydE07k+fZGESZ3LeX2WOHV8Fl9N+muj1E11brtMmvkd3t/ypa4brOBpbDfenDcvmtWqjY3lpEN8DRCXRHR0dHx30B1119JR50v/VOef/ir+7ucbW34FgTbbM0iDVM4/1aaC9x4pV/JR5sQw4ZOWRHaNKrsnA1zirTIirqeGq6o5EmVipvJfFWmMJqYtYVKiwz2fJCpRXGLDhqtSF3zen16n2WfYsFG8hyUG+52vBgDo/MAZqTi5+WGNpqUY3mDC07kiuk485aXc/HXuJzO2EHkmZWUGfVtnjeGu/bHLjB4n97CfxcqDKPpU68WTWxQFLnjpXrq/M+tWyPJtsvl4MxeY1WSX9pnc8DJc3K8m0KmLS5Uv6c07wFsc5TtmuurNxlnppYLVoXa+s2NyzdMVu363w+Lv1OztEm910udoi/7/rbsCs5ZPc94tIxnzpw9M7wdApHrdip1SmADpyFCemu03Yl2XMRDPQchVM09ws0BpNc22lZtdUJX/n9zHXtHZ4VVu7qu1nkOawzi46Ojo6OjnsphkD459/+1Tvnf/utt53F0hx/HGuiDeROj0pXA8FItob1KuNn72bRbkkc8+LnZ+decNMRVlFWbzpDse6Jhu9oexlpQSqKfOTSpx5xF+tuD/g5l6M7uJYel17Gs6dx7dQfxEy2TRlQzM/WAla/mG7Pztc+JFpezCEhv3S9DPeFTK65vAfeQrDzBbGTpXpy3NKzVYmwkwqXZHtKuP0+T8bYnXN7uVDOaa7LSfIezBBwa+dAkZ7a+0wM7i0ktOX0LN2QI8u1V3FHuMEV6a5I9ez5Z+rHW7Dr+8zfgUZMbbNwVxey9obcTt27lcg2TC6ufhHmJOQt1YkOptn2DOk+CvjrtJUZZZpvb/WgpRHrycBN7UncHVO3u6I9Y/93taOjo6Oj4xjhWY+5FD96zZU75e1xtZdx7Il2De9x/CiwTWo7wa6dbVQWE+S0Oo/fzpYVqjrnNDnfVsvejvAWzUnnW63axeLmtiN7GvcdeC+9nziRO0SBdyY5/nfP80+9j6OsZJPqUibZTG2C2uqw1x36swBvmU4DRuUy8Z6OirC755ZP6hswyvV6sGFCdufYcf4t3hE/D9e17da75NP3eQ8KT+WYaVszAzy7fnYm2ebawr4nnrmGn6ut2y0P9AAqQr17DOs5+G9x/V3e9Tt9mK95a1CmuJWGJ/FWG5oc19HR0dHRcZ7juquvxBfvICHvcbWXcX4Qbems1XGf/RxtPzdb52u3oPGzgem8xMIBGjBPNqxcZfkm1jexXqlVi6sO4cQqo/LHIS1xIERbB+KKbN3iFVekxBOTOWTJcDlX08fc1fjYJg3ngFNxkGWF03GF03HA6XHA6Tjg1Ji21Zq9GX3s7GRNNUdowMRiWDhCO0psqw9/3ZjjepOWNcIco/EY8j1E2q13rm2gNQgg+4p0nzYpa3kzJTHOxEqt19FiwedldGqDaHlaAyNZzVE7fSu3c3omrgvk292bt/gyoXKOlmJyw70PKCyWKN+3OXgy3bBSl5LxVBCK1B54md7C5HkWWev3XZ9t41vQOtfsLdkzcEoLbQMmFUdWLrjBL42f3SLiwNSy3YJ+e4s0+Q7X67rdQmve+Oz8bK2vOha5LHGg8js6oLJwu+8tUbFYvS59I5jPfDpLR0dHR0fHvQRDIHz74x+2U943veuj3ao9g2NNtKnqoKsnZCXWSriVVGvaLqil43MdvK1y2omFjaed5zmrS9EBh83VVhKeSPd0jrbO3S4t3r5M7UK37kWlpVoPPg62bh8I6Y6cCHj2MJ7mbI9FOK80/7eQjcuFJgTtbMDVw1YebMTVlUdJYxV6TLc5ZjLqSWlr3i43SbRb6jLvwNtbcb0La7QUu/Cm7xZ93iWxLtfhz+Ws+LuN4sys12gMSk3IJ3HpkdwRLJtu4QasZuuvtlw3BnkmBFzucY5sN++ndX8FwW58Gxr55+/DKQ3cc9F2WEjIdbCl8dy9hBwop87sAyXcnnTXhHsOtaU9lw2FyqK8ffcga+m9/2Y69Q8XzwCFUigPws3f95E6yOvo6Ojo6LgXYde42p+766A7RZvBsSbaqDq9NXb1MH5WMGeZnMnDfnuWWCBbbbwlzJyiZYLdJBm7EDX5bTkhqqXgyQFa9iyulu1k9XaEm4NzyuXDYHkiStPn2CKoRwR/qcn6nNHMky+gJFhaVt8eW/c0OWk+eV0Ne/KaCTwR8YS4kIXXyxxB5zIt318+uJgGoBb9oj7Emu0GKaZyfDe4UaPxfmTC3UhvKTrq96EgVLtUql/f8QHt8Rxrkm0kfJ9yaZK103KgsHzGM3OyK7K9D1rf3Rbhbv2eKYp3Z9szr7+twPRZLdw+FS/YERR+B3z6058+Nxfq6Ojo6LjPQ+Nq74LuFK2NY0+0J5JVQe7ARYufPezRG6o7fnNeuLMjHvHUTWg7gyosK9niUpPptM91FCtrtcnFV0CUZVwDcV1tryTPQIXVu9lxrOpRvYCrxDg7MUtS8A0HnB5XuHuzxulxwN3jKi2bNe4edVnhlC6bFU6NAw7GAZtRnKKNAVHiaLM4FCsth/UoxJ44Sx3f7CCNsgRayaOLAY7qfqYnQTFwkkhhNpmyiz+9y0BJTaQmztCq9ZZsXGXieSm3k9O3HCucvSM4vXeJMa6SepXX00hFLPLkwR2VEzInyUZVb633oZCOM+IqLayLvCcmFfb5a6/TVF2r8bjOFDaY1hgomCeAXKW5trNwIfUR4K2/0Q1yqaLBO8VjoPRCbgNrNLFqe/l4kLCJurTSbHFW7hbJnvvOmjWbZ8i/1RHnwUindIhD/o2Dl5JDHKNR6SBtS/0Wl2a3LBx2FHjuc5+LzWZzlq/S0dHR0dGxX1zt7hStjfOAaKt1JiUFyqGphkanbUBEkGVXzFlbFqO7zPXOGyS8bcUqSbh2GEtSjiyTdQTCp6HRcSw6kdxKzMTNy0r9PM6NhPXa8JCdoCHP4R7ZycU5h4wyC3n0c3w9Kc0E9jAE59CkqPUsPQEAXF3l34Js19bZbdcR4sQ18a6JtSdYc2WtilakTazUQG3tzktLNg57Towyb8FMinrQxuzrCEamS2k2TdK31p8n3o33RAetTFoeZvK36n1b5VZtcyIfrsta307RBvI3oP4OHOmE32IgBnnKhqXNhzDcx6ptPjKqJe+Pk/xLiFU5m2WqzlEoHYpBCqoGLQgTp5LA4dnyUrs9Ivzf//t/cd111zX3nT59Gt/3fd93dgvQ0dHR0XGfwnVXX4mLTg5b83WnaG0cc6LtO+el1FnhLds1WoQ7Wb9j8xj1aK6/eYdsk1hkirmC1a/km0gVPcn26SiJgZ+DbU7QnMWuSHPxYguSUZ3fruMsX1qXZvESsrzhTKJ1OR0Hc3x2MA4S1itUc7OzNa12rpWtv9NCNa2b9wCaRumaFHrdak28/X47AdrkuiaOLVPZjmSgPWc7D05NybULB9Ug2XpfasHO1mxk53B67+Y0Lq9PrNjqWKwOm4XyNZnce4tc13GTzXmgOk/LpLvlDGvOqjwlwOWjXLKGI99OcUNmrW7dF6pr1hVRE3G/rzGqZs3PDZ7k7WQptm2Xd25ediutJtRL+711W/cdGSZ17L6f1XewqWhY+D7ODqicQ/y7f/fv8G//7b/FL/zCLxTpn/nMZ3D11VfjN37jN+6ZgnV0dHR0nJcYAuF7nnT5Tnm7U7QpVvd0Ac4EFAHWjn3kcv6og3eGljyOcxEHeoBIHhsxYc2DeWNOYTTreeqgkvCLRLjT8fkyLIksGWCdQAoMjpR2myWG7HwUElfRjh6HtO7v1fZ5MuA7lgOKzmZRj0xg5kScAHAMGEdGCBGbMY1iaed6EwMCscUq91CP1gBwYHGZxcM4J6K92QjZHkUy7shcc9KwR9HRpcN1dnl6/2VlABNis3QuuPoDEtk0YjxzEt8mZIMDt++nIFxcls21MyCRZttmAiM5CPTzs61dTqyWZfrEii2DIeod3gZI1Eu8I9hGrnVdrddOHl5Yh311zIEaWRZIkb8ncutgho2fecu0b0/brOlbwNUz8r/5/eQyzZNCv9/yNEj15MJuPwOM9PAJOkgi3yoZTCNKTvEQA5gYRElNEogRmRCg4yeEwGl9Gp5rPwt1ifTNjSA7zpN430a9g77WfgDluxvs9IB+P8c0AGmDOgsglm8zwzyKp4vmfaja8bmwaD/iEY/Ar/zKr+C5z30uHvOYx+BpT3saPvjBD+I5z3kO7n//++O9733v2S1AR0dHR8d9Dtc86hL8q//xsa351CnaUx7xkLNfqGOC423RVlQWw1284w7EttSYs85kkp3TlLj4uYVtq3ajEIWVisvboOrXH+OtMXOLz0flUlrA2r9eXuodJjFypzd7Ec+LxtDW/RoibDJvWM47kV23sMPz3AlnsxPcGhTY53q0Zdl2uGt/xXjEzOATqjyT7YYVW0/eHhhpDZQ4ki3btWycUB9TLa2bAqYW3tZST52o3p1y39RnQtOKjIoMz5Vpl21U17N8W857luDf833Qmms9Lx1vfFf3fDHbc7TLczAwGbxoqgT2udXZ79Me5zgEPvaxjxXbz372s/ETP/ETeO5zn4tf+IVfwFOf+lQ89rGPxbvf/W48/OEPP7uF6ejo6Oi4z6E7RTs8jrVFG3AddSd3bkkeBycJrzFQxMARIBTxtVMM7ojAVHQmabLkzrpZj3Q7JssiQEhmoWQKYQIIlK3X2lmrOvcMIfNBSBNVfUrO+TyaxMKFPTILqZ6DkwSYAkw+DKQwQCNgFlsNnza6OlEo0U7r4kxLCbfKxd2vSZDnyNoRYG9V6mGuq5ZE+3VmRSsI2us2skHLnX7iPCxWTEnwAzwLRWyVye1reajOagN9TpXUv7Jok0sns2gjE+zobl/XWwMUVG7mgyp4ArVk8dX2rdl0Ce4CETbiwFy/Y/VL565bXbMmzhPC58pZH2/7a0KIxi9mtmeQ7j19i/LgC6d3Hdq0nCVbCqdNLoImziS9NbtJtiW/t1hPEREbSqJDww2W+MFGkufNgZBH+vIxLVl4q8h+/HTSNvcl7jviy7/8y/HFX/zFePzjH48nPOEJeOITn4jv+I7vwP/6X/8LP/iDP4gf//Efxytf+cqjv3BHR0dHRweyU7RXv+MjW/P+x1s+hZ/4lkdhCGfhH+IxxLEn2ipPVRnyGGXusuu8Jem3yMcRJ4R71I4gR5OXpw5nsnhHIZcriklGqQQbQjyFnAazSgupZunkKdkmR7YJIu2lwrqifCsdJ7dIAA+ZJEz6fy1rm9unx6eOJjeJudYla11SQGTGKP1SotT59gMNk8MdSVOpODMwjsHItabZ3F6RImvBJ97GD0F8dyHXJv/019r2Tajzu+OIKcl7/XlUX+pJeH0+y7ul0J6E6SCOHDv3LAgpn5eUl9JbX06UFmzA3ilPtG0utg6MROSQXTrfeoTtN8INSF65pnsFW89LSRLVA0mO1HhiOiG4VV2TI9Em/9Uy6nvqylaQ8qVGWJBkV7aFshb5GwS8PG5usIax2F617VmTJGv03hleGrxjGZwEgg7+Ib/v+qsDmXOkWafZ1GlzagQj8xTTdQVjlX+rhd3qSwYw04dZSHZq/H6wMbXpUg5ur6oNluV9hSpj9trLRTwTvPOd78Qtt9yCm2++GTfeeCNuuOEGjOOIYRjw4Ac/GHfddRfe9KY34aqrrsJjHvMYnDx58uwVpqOjo6PjPonrrr4Sb/jvf4o7T42L+f7fO093+bjD8SfaFQ4jfayhc7KX4nAHUuu2ElGGuUizCX6wHjuB8rw+oOzMzd2LnELztoyezVud6/w3CEl5Msknlq/cKU8FsM73XHnZycuVUKsEubYYKVFr1YHuO1/QJNkV02+ReJ9eEasihNzitcnItj9uKhenajuT7DzvAJNf71G8sBZzlokT3H53f3nb35gr2LbBD8nr2zlTuc9Xg75AFB2xikLOog4yACSW7snlW8+lKn5rMKVuyovvYAt13qapdftp0hz9+Y8OS1uJTNjuXzRj+1Sb9Ft/l5XEnxFooZE0kv031YQK9p3G1m9yOsn8Jc8Gnv70p+PpT3+6bZ86dQof/OAHcfPNN+Pmm2/Ge97zHrzxjW/EF77wBQzDgIODg3NXuI6Ojo6O+wTUKdouc7XffuttnWgLzg+irdaZCJsrnLxjl6Q7EJsc3GNAEOl4SBJziiZ3XFHESIQVjdiEgBUIQ0gWb7XsBmGeLKYiYkL0bNSsZ5AJ3mxW7cKSresQKyVJ599LXPVeGyTaUK2zWXbQDm+k52VCmlRN4JGSE6ExgDndJ9s9z1tRzSeYJ9oS1ivJ05Gto56YoVrfBqmfFppK35roZwPf1Lrt60NORHDPcK5frwMUmM9jZbd7aJSx9SwdgUztRMrVsGwuXXrWii1pJhUXpYHNxx7d8xKLdnZ6Ri4Wdk4nIFuxK6sgRVfKYvCJ8rpYQzk4LlSPzVTvEAKjfC/KB09+0IelLSIRbrN0xzyVg73cfcmi6XfXxN9bskPOUwwKUOvY6bNtXXdRNl9BrbmpDpITP268MJEpqXlmSPeSx/BWpIfIIeflHId7iWwT5Wssj5+7duHbApAt2ezWoxygDgjdYFDz24F2mmLrAOYe+NjHPoYPfOADYGb89b/+1/HYxz52kufkyZN40pOehCc96UmWFmPEhz/8Ydxyyy1nVoCOjo6Ojo4Z7OoUrcvHM84foi0yVw1JlaSQOb6zysUHxMlcw4gkFwcDaxqTRRts3sjXIhdXaSQBGEIUqTrnfltg8egr3JhTZ46jzNwO0nEnZ0pxJNvINpQ0GNcoplP7/bYusklDg2xn0l3lL0g8WRlZWD4Z0c6S8RbH9Z6rC4dansDpXN9ifq8jcXJDu8i/W6g7ynMd55wBmXQj/3qrK1fk2og5+wPb553vuVe/9bpeyG9WxIzsN6fbal0JdfG2EGwAOWwXu18l0vLO0ShEdczk2YfqMvIt7aGwek8KleuBtFw2wpHJ9gQEG0hKPgi4JD2uLlSpYdAwFHKvLOU3gi33remL8O+uXrcg1FWebXLxFnGbkPJpjRTe59NNGwmlKl95HCEym4xbd2eJ9/yL5Il3M5SipOmUniDsVqXogTmTb+T1FvI3qCpPXS8+RraXjiMP/iQ1g3uFy3EZ1B7H6+v5pjQn0NkFzIwf+qEfwhve8AbzhwEAj3zkI/H6178e3/AN37B4fAgBj3rUo/CoRz3qkCXo6Ojo6OhYxpOveDAefNEan71zWTnV5eMZ54fXcYUjenMxYOdQx9Oe7Beirc7AgLLDl+fLwiyOBSl1+ydWK2DaaS465Nlq4q0neZ1zHGB1euY6l0bK6457TfYqsquWeEYmz544TxeakmygJHGO1Nk1PQ7TU606vDuBp+uTfvthe82HAfF0QW5PZsX2JPuQaIb2qp5HkQbkCvZE2adZvvxr0vGZ+lW42y2vgSpN87dPU2aoyG6xBHdBe1e48FJevC+Sfy7WtreiNq3UVaELK/fkHFtI9p7Y5nFe8+ySbw5LBLwV2WHOC/k27+RzoMZ3c1LfxQH6rKjYf0Yq9jM5FsAv/MIv4PWvfz1iTP+HVqsVmBl/9Ed/hGc+85n4b//tv53ZBTo6Ojo6Os4QQyD8rcc9bKe83ft4wvlBtJlkrmjylj3GgJEDDmQZOWBEMAv1IMuaNrKMGIixpk2yYIeUtgoRa4pYhdGs2asQMYQUi3tw6yFEDENECBEhMEJgUMjknGTbkyX/OyHU4rgsLQAPblkx4orBA8s6wLLEAYirtOT8kj4gHTNwSm/E1AYg6gCYwzIeU73GccA4BsQxYNwMiLLul3EMydu4ehp3C9xvSzZOVU93l772bOe40bmenNORQb9QIXeurLAtcrkPGhZJCiLHDzxZ4BZLV7IdSgJup52pOPaDH0j34r2/188KkZJkXGXj6llcHZ+JXJxcOmk+T7KZinjamk5V/e+a1qx/s1y6d2twy6pa1gysI7CK8svgdQSvGXwiIp6I4BOMeIIR14y4lvdu7d69akHgyftlVlRb/Pvvyk2cLfH1e0ntY+Yk44ve5/W5u6kDCg3DF2VQbNtgZVs2LsqhimDrtjmlnGmju6bbIKYllO9V/obC6rQOgWheyIuBmZmb9ZcvBlSqYw9JuH/xF38RRIQXvehFuOOOO3DXXXfhwx/+MJ73vOfh9OnTeMELXnC4E3d0dHR0dBwhrnnUJTvl+4+3fApjbP9Pvy/heEvHq05Nkm0HxMCFdLxGy3o9QOdoJ2l5pJiJOQgrIdwxytztEMExYAiMyAzEADbLdjTLbpSCpXnbBO2xcSVtBCTMl++02dzCtsXGYgEDExl5XT91x3BiVbNMDJMKExLp1v3qwRcQJ3DlA6gdntl+nesr6UZY3W9Nsj32NuTlat56PnbZvZzUEz3zVK11rQedCZRkz1hAZ2WxQHlMVZQlkg24amEyeXQzdNeSXNzmaMM8jXuP4rqt16mlt0aaJ4Usb9eXVW4iJy4NsBhhzaSb9B3yx1m50lzldO9sdaBTBtIgHttc34lGeKZMXD2nFqHj+l2tCTbQ3j933NLL4qYx5DnaEKkyLR8LDfE1DyXDnmC3ZOCBUkgv3ady88jp7ETpJVQV0SgVWbft4ltp3z2S77Dcj3gcF6V6juYg30ACkmXbDVTpoKd8lmfhLeJMVCoa9sSHPvQhPOYxjynCdD3ykY/Em970JhwcHOCtb30rfud3fqdwitbR0dHR0XGu0eXj++G8sGh766M543IWGe3ojdXtDs66rfCOfPy8bNsPJx2Hs6yo5ZqyszC/3ewYTzqKuZNXr7dkqkayzYKTLV8qGefGeZokuwUjmdKhNHKMpnTcWyzrvOkEjqC48/rreakx3GFF3VXpPHcfFala4hG1FbW2dlOjbOTvYZ/BgLqsjmRPQqe5ezMJuV18P5KdE/J7ki2b5f7J8/HkeN+BjzNBs86Ry7etLPb+pcWrS7xqwNQDYplOUzDSLw+cpeWSbmoTfdeq9y2/i+49WyLZS+/iPmR6B8zJxFn2+cgNmnYm3sH993NJRj6Hyeuy9UWeOcncN7Z1kV0Lc0S48847cdVVVzX3XX/99WBmvOtd7zo7F+/o6Ojo6NgRXT6+H463RdtDOt8xEsYxex5X6XjkgBTgF0as1SnaKJZrcLJsr2kEeBB5+YhIhHUYsRHr+EARatoZmRAoydXVkk3ilRxIlhX1wA2OuQOrcgoWKwsnywuF7BGY5LYKkuMJtlqxRV4OSZtY0vQ4v0752JyWy2TXi5QtPAQUIcyaz6FB3NTpmSdHLYsgtqS58rMWgVDWjd7CnIGuStNzqBVbrV1qvSbA4qBni1jKrLGXa2dpc2WuL5xl35h4D68Jdes0TcJBrgIqsKSXc+ZReoFXabgewEARwkut2fUABMpjiutS+azUkpgL1YYYNvP5pa79sQxCYem2hwZ7jia7l/qmqu58/HBmgIc80MAx10t+Z/2AES+qMVL2hfewddNL+XaxctfXZ3HGSCheDO9bQW9IvY3bvO3qnPr9irQcUxvAZIAS8N7GswW7yEN53VvCk28MIMp5ygHOVM7WwKQNeiDH0ia590K1Eim/k/6WdLv6tjQHQ88Q6/W6mf4VX/EVAIBPfepTZ36Rjo6Ojo6OM8Su3sff9r4/v897Hz/+Fu2asEkHcWTCJorXce0cug6xkuwgHscHsM3fDrqAC6t2va2O0bz1OoRsCVdrdgix6uSjdIpG0hknnlrHIHl0TqFLy5aznIeFWKCwwJVLssRxeeykXj05hs2vts55NaeXq/12A8Xc3GrdP79djXRzpMPt38n45gkhZ+OjT/dksrSk7lDm5mCH1vcM8YJvG2z5iqbi2lo+Jxf5524XQGnJ9s+puL+cRvUz85eZk1AvYTLgsFDg4lpolNM9l+a1WMhTntseiBGGWFi0g/lWED8LqwgaGDREWTjN5db53vp+6Ts3OAt3Y/HvZ9N6XTxDt69Yd5VR5zkMWgMxXrmCUhV0plbtJdRxuH387VaM7qIUC9+ACQl26YeyajcHRqr1s1BFF110EQDgC1/4wtGfvKOjo6OjY0+ofHwbPn9qg9e+80/OQYnuvTj+RBsoiIDNjeY0R3sjjtDGRg/Iz9U2so1s7c6W71h0+pREr9QRGqljtGR1UbKtTtI82SbtMBfO0dDoiOf0Ca/zeeA6jcC0M+6I/IRct0jrts5ioY9dWlASoJbEuu4j70q2tZx+fReCXVXkhDw74pZjQgMFyUS53Rw0WCprkS5E2qzaVbo7dCopXybWTUwGN1zB/D0tHbuEmiC6AYPW9IUmGWpeW07bGvCwtB1JfzEoVi1CwIPsS2RbCLfJylH95ve5fucmS1WORWl56908Q9ggyyTdOUeTNDPeVwS7dpJWrwOwOdVLIbqAqWxcBzcBTNQaU2dofqNVh1zVJ5eEuv5eEGye9VJ7ZHfsUY87vOc978ENN9yA//pf/ys++9nPTq9dx2Pr6Ojo6Oi4B7CPfPxN7/rofdop2vGWjjesXczZ8/jpOGAVR2xiwAEPSRJeYRDHPCMiQBDv4yMOkGJqr2kEArJ0PAIrkkDZMcXTDmI9R0jEfIxBpJEAYjAp+TBERKJkHQ4iVx0A9ZrGdi8AnFaRvDMx5UpznUYl7AAm8YQV+0hZ63pu5Wu9PzWJ09+6d8oopbdzvVdClg3nqinXd0FlBaX6PFUYNDfjAECSDxMhyatdTN6t8vFKEpzDwTmS7Ql2Tarr080RAa63qaweeUdUhl3Mx64GDQprdl2Mqt7YlclXhU1pKOTdpYO0Qh5enx/5eSWnVnKsI1IcCRQ5FcCc97kTI9epxrv3vhQm9cWZfEZVacTgQtehdCBndVbe495YItSt0x2CjGuM7SQn1/aSnpiS7RHp2Y+ujW+ixL8eGIHzQCYAROb0XUOKkx0oYhQJ+rbY2G1nacmZpamGkMh7Wk9y9WjPr6oDI8qUvhkhOZlEAEi9jct9UdQ2VX0H3LeUQRPSfrak4x/60Ifwj/7RP7Ltyy67DI997GPx2Mc+FgAwjtP/Xx0dHR0dHfcEdpWPf+6ug/u0U7TjTbQx7fz7GM5qbVEnaLUHcrVYJyt2OV9wUMs2Rev0Jem4ysqzV9yI1Dm0ooSIMQYMlKwQetXUOaTcQQwsc6DZOoZFh07nANNMP65pJZOqaJHsiuxtPdcc5nY1SPTsMbxl/w6wetnWya3ItUJv0RM99r9Kqhh57rZyKXbHFOekck5ucUH5oXK7kWVaSH/cYcBUkvCJNRvTbbfsbFR1ZNs2hXnnNJ3xPt0/uU7B2vP7UA8AFF7ti+OpyNh0WFhkZ0e208gLM8AUZWqEElIpQMw3NiHd/h4OgyO2mLagxLteX4J6H4+gYh72tmOWoOTab49umzSPO8YGq+yP3ynfh4oUT7YlO1PZ9mpr994DenvibW97G97//vfj/e9/Pz7wgQ/gs5/9LD75yU/ik5/8JH7zN38TRIRf+ZVfwU033YQnPvGJeNKTnmS/X/IlX3L2CtbR0dHR0dHAk694MB504Rqf+8Ky93EgOUXrRPsYIxMist8xKtkOZn0ZiaZkG4wRQroZEt4rImKwmK9A9kI+IEnG4xhSmC+KZs1BdOcW63Yqg4T34mwKjUqEhwiOgzE4c4wmxyRLoSMmS509pswUW5W0QPAOLUOepM9sL1n49rn0nuSjvi2ThldEzYhezB1y5XiklquYFlLFgBIuT1QbHf7Fgrn99niIizxnRLCBou5tbramF+Rw+RR+YILkAAZ5Hpzq1g3wcF3Plsb5IGfhnhB091sMgOjzUMKk6/KMkucskQuzUHtPupHq2XvB1nr3cukYMvEeRxmwiwSmRDEpCCHXemRXSe42fdq0ctvJe6Fmina99N6zWIQ1nWXEgmRgAcj3mcqdyjpGIFBI1mRR7igpjtIQCvm4l9QgTryMt+DDfCVJQjpe59TXwRh1gKS4Jxk8KSzMJNZsI9mpcZoVO6T2Qhq2zR1PWqVA0SizdPxoR0G+4zu+A9/xHd9h2x//+MeNeCv5/sxnPoNPfepT+NSnPoXf+I3fsLwPe9jD8IlPfOJIy9PR0dHR0bGEIRCe/7SH49Xv+MjWvP/xlk/dZ52iHfkc7XEc8ZKXvARXXHEFLrzwQjziEY/AP/tn/6yYX8bMeOlLX4pLL70UF154Ia655hp85CPbH1QTNodWzi0EW72Op2XAAQ/NmNo1skO0RKrXNGIdRov1qg7RVmHEimKam00RJ8KI9SBLiLashhHrIc3fXomzpWGIGFZjmrdtTpfY5n6y/przMsDPdbX+uiMiU0JZNeaqA2qLd+zUWjz04i1r6Owyn5+YKtn41sdT3s/crhaR5urXtRuKLPGh3TK6X5bfEQgjJSm55XVktSBVemGUdTknA2+OCJQkuwwZVzlFa8DLxrl6JsU2crqtz0GzeDKjXu+FYxXO/IJbhpklMOLA1t4LSW5xQ/75kMTxdtsjgSLZevKgLgt7a3S+FXVguBrysl6NOLne4MRqxInVRpYRJ05ssF6PWK9HrOR3WOkSMawiwjoirBi0iqCVd6wmaepgrQovtvU93PZuFs99Wm/5GVfJDal8jMmZ5ChyeXWGpmljTJEcNlEWHsTxZAqlmJ2ohXSMq/Ox/i41UPvD8H4xgmvzpkwIYi93Kh4u1pHbpX1P3feVynQbK7A2TNamPckubqV+n84QX/ZlX4Zv//Zvxyte8QrceOON+PSnP42Pf/zj+Pf//t/jJ37iJ/CsZz0Lf+2v/TUwMz75yU8ezUU7Ojo6Ojr2wHVXX4mLTg5b82lM7fsijtyi/dM//dP4+Z//ebz5zW/Gox/9aLzvfe/D85//fDzwgQ/ED//wDwMAfuZnfgavec1r8OY3vxlXXHEFXvKSl+CZz3wmbr31VlxwwQU7XyvP8xRLkreYobS0AMAImsTSBpI1+0DCeek5hsqOMoh1JpL3Ph4RxLyZwnwlS4/OKwSy3NGIkexX+XjqIAJQU6DXilNpMWxCrXtSHzv7yzmKQaW5Dr1t3wtGriryWxJwZ83kUs6sPFmttHV9WV2Ty1dfr0ZFtlskeTFG8NlCPUCAxkANkI2mUkGFxc+pLoB289LqppqgFBVOeRtuX5EvF4hEUVBIx6ul9U54shYIRuLKTJxUKsSInNYjIMOT+n0IiBIaKg3eUCZ8TpFi36bS/p/uQQcv/OCM7NsLzqq9JANPohdCa9An58nWbmZK3zAms1Cn6TRktRBl8rNauWtJ+eiObaGo+0Y2JdtK1I1Ye9ggIvLHVcmx1ocbKCL99WN9JG0KRXXm87fWzxEuv/xyXH755fi2b/s2S/vkJz+J97///ee+MB0dHR0d93kMgfA9T7p8p7na91X5+JET7Xe961341m/9VnzLt3wLAODhD3843vrWt+K9730vAICZccMNN+Anf/In8a3f+q0AgF/+5V/GxRdfjF/7tV/D93zP9+x+MSFORp4YyTFSSPOl1RozMiVnaJycyYwpGDK8Y/okIS97T2bBlo5XnqOdybZKxwMxNjYvO1t2gORIKAzp2kSMzTgghCQhZ46gkKyhySN4YhOpAyjMQjuNLSJLXM1RpeQyeEJK5LfVQWxYDot9rf5xg5wV5VrCvudr5WPXCWa3XS00u57Jj51HOuks8+jBSE6TxsyjMKb7Y2LQgCRVFsdKIJXkwvXiZ25mqYr2kIx7C61vAy1rNnt1wcQCX16MZVAol1PIhw78OLLdGrhoDjx4i7kuabJvasMRyarLrv6LQuVfT+mZ2EgUbSjf86AjUEAcCWGAKV5iTI69FN5i6m4PgzgyZCaTkUcGolpwg5/TnazBAOy3fhblu5r+qJyftM1o+Z3Ue2fUZNt9AGwgyUvI7V4ZMRKCTYvIQwlj1MGALBtPlZa+iZso02l4QJCbiyCs1OsYYA7SatRzs9Np8wPW9VgNjCjp9nG0TRruCTal7ypBnlHgpEIR2bhZtrUNu21bl3fbMPM47H/ROcTDHvYwPOxhu3l+7ejo6OjoOGrs6hTtviofP3Lp+FOf+lTcdNNN+OM//mMAwO///u/j937v9/DsZz8bAPDRj34Ut912G6655ho75oEPfCC+9mu/Fu9+97v3uxhDiGVaJycRjSJrTBLHASMHWQhx4bY1xJeG+xqclDzJyhlrkY2vQhQJedo+MYxJHi5y8nUlJx9CxHpIcnKTkA8SSijAyUgxibnblNICRpgsHFVBJisy1cIc8W5Zb3bpRc6RAk+u4CymLq24hB84kO2K802P98R5C8kmIXc5fFfepsiFdDyIVDw4ybhKyMnaHfard73fHb83O1u6laj5bSPZQI5zXu5vX9T92iJScSEhJveek4av/DZXCwpZucWBtwEPLWMmMUZmnLw/jISwgcn7aSPPRuXjm/QbxyyDrr2x63xtAtKUDzf94+Qw4oQsJ0VGfnK9EXl5lpavViIrX0X7HVYRQd51jdUdTDYOe+8LGTlp3G8tXOMBNQaVijbgCXv9nF07YKS2kbyqw6TjtohcPMaAUaI5qGR8dL+nx0HSSxn5xvnImJu6M42bnafokBvUJOQBEXViZ9MnzJKdPxTs5Phlm+WpVFy/swFgmcftJeZFXjQ+c+eYYHd0dHR0dNwbsGtM7fuqfPzILdovetGLcMcdd+Arv/IrMQwDxnHEK17xCnzv934vAOC2224DAFx88cXFcRdffLHtq3Hq1CmcOnXKtu+44w5bL+TjWZ85iyWSvYSJrBRTeWSdTy013jN5kpjDOokG1eTOWZD3RU1Yvca5tnbPYZey1B38w5Rxy/4mx9RBlh3O5eXis/s1ixoEWSyNlPOokbEkqjAieKZK+X1l401rtk+fHfTYsr8oFMq6s7bjrKJbTtPiJDYc4O+BUDiha5e9USxtC8xZyh7dcxKLM/l1KutPYRbt6lkMKiMXjJBRypAchgHJOD/KsTFmM2kI+nycv3V23ulrubxDKid2a2C7vNOMpEoorj3f7lj2R07+FKJMkWGofFy9kKdzRDMRR8vroeG/asyF/yry0NQzeQ6T5zIq8ZZ6LW6RcnUXqgxZLF3vn4qmvowt35mOjo6Ojo7zDRpTu8vH2zhyov22t70Nv/qrv4q3vOUtePSjH41bbrkFL3zhC3HZZZfhec973qHO+apXvQove9nLJulmxQUq6w6ZtUYtKwc8IILMsh0Q0nxtiilNelf227C+BGIEThaWdRhxEAeRTBK0YxnFYq6eyDeRk0WIyGLXAqlhIobkEE3WSawuBemG6xgCRYc7E0TKfyOSTJIARAaF1LkHIVn3rAPKUwJV46g6jRXpnzhA86TZEdeUF8Uz9pZ7amzrOWoZebZyc9Ehpnq9qIfcWbc8zkMxKdsKSFMWwOCghE/qfY86LLwoA1XopXYvv/Zq7Ul24UHayGh1nrp8xaPJrHbead32G2SfTcuhXIuyrHcyh7Ym3cW9ls8bA0CRksR4ABApPatIwIrBm5CcrlFEDCF59RdCzMTpfSzkyVlGriRwJZEE1MoLpGkhPOS0lUrLhRSmMRu1osMIuMbnBov1VG9a2mcOIQarn4Jszw2CFWk6nJHPY5nYZ5d7jwEI0doQESHY9w3pG0Vuio3bFwOVlmmkZ6z1uJIHnsjyPNkG6WBH8j5ug5TIz2MIEWPUMiZFUIxJGQBXp2AkqXgQibwMeBCQHE66d1s/hznuO6Vj3StctDfXVuH2n+FYW0dHR0dHx7FDl4/P48iJ9j/+x/8YL3rRi2yu9Vd/9Vfj4x//OF71qlfhec97Hi655BIAwO23345LL73Ujrv99tvxuMc9rnnOF7/4xbj++utt+4477sDll1+eNni62HxJznO0028i1yMIAwIiQuH0rEWugdTJs7BfMh8bDKzDCMRkxdHwNOmaYt1hSvMYKc3fjsHseCBKncigElGZX+h/Uz8wd6y1rw33q+sF2dbOpJHUFC4sJZqJrDzRhGQeESoyMCcZ90UpVAqN56uWyfl9eZ1cmpLsmpTXBA4kBF4LE3PFkEqlR4AGcp15IduRXWcd8Nxm5/rdYmW0bL6egOm8bH9/jnhvtbwpiWuRbmC3+6jzsH/2OeyWFVafJ82c3rcNX/Y0xpXegQAEknB6AcCGECE2ZHtWhDgEEDNiYIwcEy+vLKXqh0FJt/epGZmwkgYyhGBy9I2z9I5xOp87vfc6gKLzuRPpJnt2LqRfzI2nSbZn6mjS5mw6AU8GbmQ4SAbn2Mh0aitqmY8gGRuJMsDQipqpjiKj1l8QwgzkEIicyXaq6yjEm8VC7p3SZWeTOjAS7PkAEd77PuVbFfk9AjJhRvpFpDQQw454U2o7BMgxyNEeXPivunp9vXtnih0dHR0dHfclqHz8s3cux9RW+fh9yap95HO077rrLoRQnnYYBsSYOlxXXHEFLrnkEtx00022/4477sB73vMePOUpT2me8+TJk3jAAx5QLIrSctmw2AHWqfPSRCXVI4eJnHy6XZ6ztsZop9zWC8tOXrcyA+bp+LDYScaovy1ixdXv3PFHhS3no7o8POWanoAvycE9ud61TMW16jLsQOabeaWsR16XcES6udMNZhwWtcWOzmCR45k4y6V1cKle34aFdmzqBjdnXufiJwZMQMxqFz8gp4MUdaSCpVBTRMkZYiDGIPO6CUlmPohPBn3PB9mnFtgi8oCOeUljKrb9I1h653d8j9WK3kyvtr2Tt1Ykh2gEHtlhHLKqIjmEDEXeFvR76r+R9bztGtO6yXWaEsqF6/YI95pQe/H5eebYArt8czo6Ojo6Os4zqHx8F7z91vY04fMVR27Rfs5znoNXvOIV+NIv/VI8+tGPxs0334yf/dmfxfd93/cBSJacF77whfipn/opXHnllRbe67LLLivCluwCT3Am/W+Ta+ZO4SiOeQ54BdBGJJDJwn3AK8knBBxh4oUcSB0/DfOlVm2dd+0JffS94pgsOmOMQFjodGonGP53jwrxknAz74idjMWqDWQJedqz/SKeNO6DijxPrNkNMprJKhXkNZOo8rkX0vGI6fkXSHJ9TV8lHJE9WY+cyb2zgtEmbatTK7OExyTdp4gsUVVmp/Utq3UYppZ8fL5+syXbqllJEef0nEYo692dy5QN1TPeyXrdKGRtVfXlJTYynFUXyKTIHeLVB8UAirskJZUxQEA4QHKyJm08OfoCmAIwMBgBURyPjQBCSM7dxhgxxoDBSaeBauDMGky+9oYDBk4Nb6SA9eAciDEhhuRtm8XKParXc8oey4nc9yImx2SF+oRTe0yX1ikJNP/qFs/Vb2s7Ed/xDLHkpgypzqAGXbN1xwiJgBBtaHYzDiligtRNpFLarV7XAzEQgVUYi/LU5NlbtotBS1HiDCFihVS3m5jyIQAxpucXU/yxRLbF4VkqGNKoJhg8kDnOTBIFtnpWRYSpUSjVRxIlZaVQGlXYUucdHR0dHR33MXT5eBtHTrT/5b/8l3jJS16CH/zBH8SnP/1pXHbZZfj7f//v46Uvfanl+bEf+zHceeed+P7v/3587nOfw9d//dfjxhtv3CuGNoCys4024QZKYjsieR4fECzMl7duj5qu+Wc95UroGscKBipJtzoDCsIENJ5utogt314rlvFWOC7nJeVGTgrSkzuaBUE/m5iMiNBUxu0t1pOFCuKN+lhURNy3kZpso7Gu51K5qFkcRRoapa2J93FGsqCaZFzIUdExr0knZxI4q2qwubiN/a5dFN6zneUxk+yKrHPOmyvGpS+R5iXUeVrEPeaRDCYhe5RGGhiVxZZcxU3aR/ncJlJ3IVK0EaK6AmiUdyEwMIr1OuZwXIkYRyAGrEN7/rCRRZ/O0QbYNsRm8Q1+XUh3eueDkG4CZH64stfUHgCEmByPQYm1r19Gfl93eDCtOmJxymafhnQelYzrNYWe2pqXkbMOYjBhFCIcId9amettlm+aqgRaMLINtqk4+u00Ak4uFJuUWaXjIaR45yTh+ZKMHFk6LvO4mZHm8JMMNOiv/6RzTrNwX1qfc9VeDQB1dHR0dHTcV9Dl420cOdG+//3vjxtuuAE33HDDbB4iwstf/nK8/OUvP+rLz2JEDjNj29KrikKuR6T53HXebfAecwdiixerc7lTpxuWpt31poOrQ3TWitNs63tvI9P1/sI61ujc72AQT4d6s63+NtLgLJhVuVry8skxrbIwQA3T8LZjtACZ9KfY0hyz9ZwikrWRHfmuiS1Vv/WllNzQDrM8K5LdzlP9Vsc1se3CW/dXN+aJoV6fyqRFVOVtSfSNy+vlZIWH/CxMnaDceSCb+8xDJtqMFC9aFSfRl7fC1Bo7pnnbcKQyAgGEDZRM621pwYMpTJhYPJMzWEzzDGlrbkAiOynT+9Ybxvb3sG6HyO3OWGQ9tsEaMz0PCqmTNpaBACCNnxCLB3Ito0nJ1SFlIulady2P5KkupwOYwdhurn91kubDfMmF3SLnkPj2JKG70j2VRJoiTDJO7jfJzuXete4bY0gdHR0dHR33ZXTv420cOdE+lyisWmhwwKojp3LwJBPf4DQPybItcwmVfEch2yOyx/KxMZ3dOoUQsm1WSG/dDi5vgs5nBMQiKfFqWeeWTuIyu1+HkmBvZy/acS9PYnsbzKV5kkyaDmO9qUjg5N64vPfCMs00lY6781Gjzoxkz9Vl1Ya8fLyQMutxBFBIjyhspJM+AmFD5hSNxmQ55VFpjBIZJSmO4FR1bQRnTsqNkmCzy1NIxtkdOzcNYekZL+XZ5TgroGN1WiazYrNIkv3NOJ4UYY7ObN0/f5NTI8+hZSDk1zI9AyXcJKpfCimONwFjGBCDzJsGwBxxEFSanK2yk1jPVtj0k+Yj5/wbSlEO1kw4GAfZTwjj4KzbmcCOMRiRiyYvj6naYgCCiMZd2DKTkVsFlPU4fRbFw5KkqYycGclTt77rIsuOkWRAgOBl5DGmQYNB5NpDiIjjkOspAmFIF4jMyaGkK8wwaTeZbGtUhxVFxCAhxkKWjwdyz0bl4pzitKfV9C7qi8ziCM2mcZDkl2+a9xOpPvosxJov5mG+fR0dHR0dHecxunx8iiN3hnaPQzpdNcnODnw8oS5J9sjZM3mSflcyciHhQKtz2OiEox1rW9G2aFcd5rqDtyt2abtnapLZ9/DqPloW6mLwpCDMLYl5+7xL16z3TaTlfr0g+brOmfC5JRE/yueM5I6jPICgl97Saff+BVppk36/J9l1+rZ68PBygtYSXKW4hULp3MsWy6/n4PJ8kxtfTvNz9YvBmPp5+O1RFpZBkKi/aXCLRUKuc6t9xII5b+S1c7QVxbQEXUasaMSKklO0Qfar0zTvMG0IbL4faLIAFKKra/m2aV0eFq226NqPhR6DDtyoYzQ9JvvA0IHDMeY6Y2RlgNUnnCO1LR+PIE7mJs4l3bpastUzfK4v9xtyXXHgNAAW2Ob06wBN2ofsDE3WYfmobLP1e9HR0dHR0XEfh8rHt0Hl4/cFHGuiza6Tw4Aj2TmPJ9zJUp1DfZ3mAQe8woggcbbTry7JI3l2ouYx8uF6V7kDL+tivdIOv1q0s+dkR950u0YhTUXZ8TuTzjjQ7ki2ZMK7dPyXquwoLEQVEZ8U0xP0ilRP9lVp3opKzCWxU+JXkbzmgID25AEhLyWxqauiduo3vWdCQxW/fRClHlXwclshF55UK2lpEWmaId/F+9hSUri6oUad5/pGUac1qZ4sIxDGmmgTaCPrGwJGpLnassQxYByDke2xJt1w5Ns15EQIoxHDFUUj4quQ0pV8D/WvI9tBF0rWdb8QOWIZSrKtz2QygLHTQFtuJ0tkO63n30y282nslBX5rusOmHcGGZAGMQYZdMh1zBPi7ZdBvLhnb+5+cCeR69ym868S7rzkfGW65CcqvZF3gt3R0dHR0WHo3senONbScQCFVcI6UiFbORQ5zEwwcg0AEdFZsZOs/IAHyTfgIA6ZiLNYv/cg2bmTmTvtDBdbV8m2hB4y2XjExEIKlHyllI7P1Etr32Gg59Drq6yUUPa0NV2P2UagZ/aT31/05GeO94StKA6XpLvkgBXZa5DBWtps98SgIM9HHCpBZOOB2CTlgBCTwBAvebB5o4FTdWURMGw+bl0Prduv1A8mGdekbXVfW68ljaja3yoIykGsFnQ+bzqcZpuCEWggE+nCCp0HMMKoearnCrVAZidXAUKUBhnfGKQ8gcCjvGoUwAEYZbAgxjx3eDWMGOKAE3L+lVRMtqomsqyqlejJYRzkmIiNSMo3cTAnaSMFEKU8B1KXnsyOMYCICq/kFm5Lryj1xm6AIj3z6mG13pnifaYqH9u6351ifaeDYwRSFMdU7lH2E42AeG837+AABtH5R5GPp+Inx5EAbHBCY2kDKaIDosQtDxFxTN7YBycjH+wdCCl2ucjHQ4hghFRF+s5V96OOCy1eOUE81Kc2l2XmMAt4ep9z5RDQyXdHR0dHR4dgV/n429735/cJ+fixtmgXMr56VyNNLdkatks9jCvJtnnZIhmPoEIuHiXN1nd0lmbXRxluDCgtSbVFtmn12wWtNntU7bhlLa+fw5la0c8WGoRjUtRJnXO+zQWrq+4vLdl5oISUBG8ZpOEqT6t5pISq/cyekKb3rVgiBhUJn0qaK5LeIBsmcd5WPl/Ouo6qAZJJvVfbFFkWTBQGJINX+itMG4gQRUkwL+5RBi40NvRSHGiFWmQTaYwNK2zeJrN4l7G5i7jbtYTc/wI5/Jyz3hbqgaWBtkab8G2ppaCYSyt8BrjvG1f5ajVAC20Haa7+UMUzlzylfLyuL5Sja0qaZfEycjapOUw+bjJyyvnsvjq57ujo6OjoMOwqH//8qQ1e+84/OQclumdxrIk2V52hFNNYJa6pE1Z33KIQaZWH383r4vdUXGf5eBywiSnvJg44EGu2hu6aXUBFvk0csHHHqOMjDS/E1uEns2RnQpDJQUv2XNfHhAgXncIdiM8u2IfIG4/idr6Z49jvL+5p5vgqvVZGT6ziBYHjwvLdkpIXc4MdcVOJciFV9pJlyW8KBcCpFrR3j4k1ukW2Z7EtQ11/vk4JJhE3GbjKk/U9cuQjpbuFpsvkmq3ysrRrqQcdpLB2X0u/bZ0RRi73jTlPsG22dXs2Y3JgpxLytE5JQr4JiCNhHAM2mwGbccDpjbz/Y5pGspHvwCbORyXQ781ard06d1sl5DJve+Xmba+HEesQsQ4xWdFDkkMrER+GJCtPv/qcUhqpAz59RoErOT/ml9nno4M47cGhSQg5WddmGF179I4fddv/tlDOhY8VwY7FPHmV4ueBCich198hSruGtXUOyWEaDyzztpGXgZM12/1fQSElpywpN4JO2+u1o6Ojo6PjPMc+8vE3veujGOPWXu6xxvGWjruOEA8sXp/TkudIZpmiSsDvjuskPyQN9ZWt2Ilsp2o5Fb2MPGAjctA5q8xonchghHsTAzYcsImhmPsZZeEYwKOSbEpOmhjZYRNgsZuBklMR2gbSRUl5UX9H0Li9VNwKVedppAHmgNo6qFzlL9LEP7KmL5w3XyDv99Zob9wyj+Quj781ELLcO7rONCUyl4gngTTWLiHF8dU5n/I8eUgFKiTUGtOXKcX3hZOQ+4erhZ0hPM1bd/XWntefz+vn+HordFNCvgMkgJIq7F2h5B7Y+SDw89nnCLb9spOOI4fs0nOrtVHCNUUkiyZHssG4CCCIdDx/PxJxigRQjNgEmVYyEE6P0W5hEIIcOKZvAEMiC6QcmQjC4kEHECKlkH+BVR4dEWJAIPFAHrNsOl0n5ScKGAJjjJRfCWlfyZLMNliTPJnDOcXL7dk8aZt6oHpg7p1i1rZXpUFCZMlL68N9MefpBn5+dxFPHAR1Cm7p1ccpFA8UAALWSHUd5XueBjhKD+SRCRQi4qDfy4BhiOINPYJ4gE70Zw52/wxAw/UBLI7OCRhhHtdTO4J5vwfklbJBCE5zt71ztY6Ojo6OjvswdpWPf+6ug/M+pvaxt2iDuJiLrJbsFlQ6DiDHza6k4krIdVG5uM3xFmt1aymu5STm/vrqCE09+Fqf11lYaw/b5Pab0WQX7uOKNAnrdS9F3VGdWukPc9Lt67PVw9PfQkKu+2ZIvSf3c6Szedki7zTfomRcSFeBJWtmQ+lQy22XDKO7GPLaDtuq4lX1VKsL7LclGfd13fBMvnQun6+QkKt0nCvnXjtMGVHSqNZXtW4X0ue59UpObrJooCEnTxVFUmETObk+S4+5hzV5+YCWXHy+zdZttLRk7yrBV1gdimU7pZUSfE1TZAk5rI58vdQLU+WFXG+vbtiU00sZOeUBiU60Ozo6Ojo68OQrHowHXbhdPg6c/07RjrVFmwcAA7LULzBoSLJKneMYwEaOg1i0T/EqpYuUVy3ZgLdiE07FlVmxDziYpRpYDk/jZeSn44BRrNoHMWAzDmbNNtm4WbThLH2ULdmeyLmOn5LwQ3fuzKQs57aeuRsBaJ27JoFz+/aFWtL8dZ0xl5CsTExuN5VFZIJZzianr4hx4SiNqzweEoc5WbaTRdok4XBWV5Y2qVbXMZEcBrJjNLGcpV46W8+egcKqrbtbvga2YqIycNu1FVuKYl6sXboSu13ATO6ZcLtRmhUQeYrE6KZIjJTqiUXWrTLwTZaKhw0cueaivREAVmdoYomkCDBzkvaK1D0QkrM08SSNAaANgSkAAyOuIkYKYAZOhyFJoVfAEAes5C7DmNUyCBLuj9NGJoVqoQ353Q1jIuoFV0+f4UG2NjEgcLZiBwrpE8HJieJIeRBArdsac1ut2+roy6zPro03HaYB9txb7W7fthg53U9kmoRCTAMV2Xo9cnJ2ptD8Xi0wIHl0V2v4iiIiEcYYrS5HlTMgIrj17PcgIIq3M4uLzen5s8pR9F0niBM1/d7DrNuBrWpznQ4wx3sdHR0dHR33ZQyB8PynPRyvfsdHtuY932NqH2+iHSBEG8CKgUHCvQxssWmVKEQOiMRpzqV0aU1WzmTkWqXjkZUcD3uFqLFrIc/HVrKdliQnH0dK0kYvGzeyPbXSmTRWrkFuvSDMRsQrBuJ/i0pspE8IeOs4dxDXv9W+fcl3Rbh9ESckm2eOm5QXlWWzJNlU30PjtAQY2YaQOWKxnKkH8jEfQCNlojq6s0Qho5CbUWKqVtUAE5gXt6eWs2KgY+Z+JX8hIXfn8FZsHyKqINeFpbBx7aqO0v45gp0HkKhu635gwofo2sA8jZcycs6Wa18PRo7k2wCR9AIIGyHbQOK9DPCGEIYk3+cDssGNuAmyTtgMJQFkTl6xN2EwKXjgNHIQ3LfGy6BLOXmSQSMCIah8eoOAwQbvdHBQpdn6TJgJI8Hm+teeyWs5uTkqk7au5DJPUHDPp/XM/DdARvQYuw++KJa+m3VdKckOMtg00JiIOICRkpdys4xz8m6e2C8wxACEtBFjGnAFAoaBEWVghgYAzElCLveWbo9kgAhpoIyS8ohikv+7cYFM0lUJQZ1oL+HP/uzP8Hf+zt/Bpz/9aaxWK7zkJS/Bd37nd97Txero6OjoOIu47uor8Yb//qe489S4mE9jap+v8vFjLR1P83blV4mD6wS2PNgCMFm4J9cHnMJ4bWROdmR1aObmWsfs3CyahXu66JzsyISND+tVdH7bRHUiR/Zo3c4uebZh32OWTOit+wLS3M5J2p7XPQSIt19niWTPospbcNPqeVqaW4r6UBK67ZKHqK8ypny9j5uk2m8XDs7c9s7WzblBgaqd57jxqOqJM6HhTLKLPI1BKR/fPC+sU3WzZNyvG4GSuPZOLp69kbtBNzf45iMSbEMhhcbUo7YqcQoHX4Vk3MnJJwucXJrRlJP7fMBuL0kDdXvclYD7qThz9eN/lXx7Eu4l5ID3TF7Wm5bJ1w8IzsGfDGhZ3aDtZVwHbxrbtZy8o8RqtcINN9yAW2+9Fb/927+NF77whbjzzjvv6WJ1dHR0dJxFDIHwPU+6fKe8n/6/d5/l0txzON4W7TWAFYPFmk1DTNbsQTzRgkurdRwQsMaIPLqineQDR5JPjStHrgdbzyG5lntTvgOePBaLZXsjlu1RYmiPBB6lVxeRvVGrFasm3ZSNnxOJ9aRyWhappfyt47flcXnrdONvVGzb/RVkqp1e7Ieer72u554dqGgQ3poUN8+JsvqSoS09BBKZKUVk67Z642btiKcjSeXiUBmzdOz1oRLSNAJiUMyWWJWRW1nq8tVWfMubEwtSrFZsuaaSMhuUUjKieRaRT8xaJ8Tl+6Ey3Yg8oGDe2Ek8hWfrdtjk3yCScU2jyGmdU0V4i7a9F2o8D8nyzGKZZkrPhUkk4yodDwQeABrSfkjdJ1IdsQmD3c+wSWG3gET2PCEOYLOsJoJYWmoBlZKnB7tGljwjAmFoO0ljJmyIEeT7MxBjDGTW7SRjTnG5zWocRS3TsG4TxIKv0x50oEcfF+8xiLKAXRRgsfWNseOjOZTT7RUgioDQdIyWrNvBHKONMVnCeaBJ6LJ0+yIjR0ye593zgGs3AWzOz/QJqnScNa/Eao/doj3BpZdeiksvvRQAcMkll+ChD30oPvvZz+Kiiy66h0vW0dHR0XE2cfVXXryTU7SHXnTy7BfmHsKxtmibVC9AiDYjSNibwc3589Yn9R7+/7H3/8HbXVV9MPxZ+1zf+w6/QghIQmyA1B9PZURoSZNB6RgkCJGiKFawWFN1sE/fyfvaiTMVpkWqb2cYO5ZBNFOmnVpeq/bBWostthliEOkogsCDTxV0pA2oaBIxhpjE3Pd17b3eP/Zaa6+9zz7Xj/tX7m/Ya+bMOWeffc7ZZ5/9vb7nsz+ftdbptMLptMIpWf4yHtnySFzhkc0RHpHtU5sVTsUDlk1eTsecCmgTJ2xikGjjktIrin+2Bm4ykNkHm/mB82oJ/2zDRTWD6jvRseu9+y0tlpqqYbD983RYSkvp1AHZ/p6E+rgHBB4gU/s8rTXHWwLXX18BXLW467TsdMWeJi7bEZUsuvJDtvRVVNJ9MVUpv9jdo0Q33vKM+mzVLATqbcdqGsiWVEdBmc+QUyPp0kvdVbPbOxpl40jHCmRMkIFsY5U1DZdLz5X9s4EgKb1CzNvktoOl+5K1XMdvV6m+NiwgHiZPDxs5Z0NSTiXlVwqImzw5tokB65hjLZxOOeXXaUn3pRNxUX5jjOVumFufX1tTgK1CrFKAnQgbnAgbS111FGJOAaZLkFRhkgpsNeVty8sdZLJRJh7DlPJiublhqa9sRs8pGPrv0BUxbVVX+HGxpCrqmTHWzsddFwsmR4yjqr/yc+uiqb6mkLL7kJZJn2hfVKns5P8HJOVXifuRY3+kCUhuX1N7pQngFSrZ+GNROv6BD3wAr3zlK3HVVVeBiPDud797Vue2227Ds5/9bFxyySW4/vrr8eEPf7h7rY9+9KOIMeLqq/djOYYNGzZs2DG2fSfuH8NqsOMPtC03qgMDro5+6EUD28HyYa9FAr4R8K2S7w2X7SjHi491Ll/vWJTFVr/smIJgN/eRuoMZnw28heot2FxkdavOa/cXWOlq6YDrpm6eMJgDbHSAd8tkW7RotMdLne4ERLc+suy400dWvj8G2Mv0upUSdzZBsfAMs+c54FdnCfxS55gBbnfYsdjVZZ0kuS7f3aSSa7lz3dkkBUzSjV757L02+wKi7Z23kx8L1/NpxcpSJjyyhDz/zaY0d//w+bST+30BtgdL9BbcS2/lzwq8l6KSTwIo8z4KqCQWUI0CrHUypZVQuzHRlYsc+M/PjxXdPgRsL5lntkPzh+tVBfPI7aVfy2SR7AfpnyZPPBNb3mxTnti++78D95PYlD+W7KGHHsLznvc83Hbbbd3j73rXu3DrrbfizW9+Mz72sY/hec97Hl72spfh3nvvrerdd999+M7v/E7863/9ry9Es4cNGzZs2KNsn3vw1F717vzkPee5JY+eHXPpOANHCVgxaJUQpohJmR4HEMyvmhiRCBNlIKwRxTcccFrk4qfjZAHQVPbNApqTAeXdX58++I+C681mAqusMwZhtBcYS/mA691p6+05n0sMcNmQS5JU6aGfHReegdqGya5AYx3l2MARkJ8XDeBBU9dF87ZreT/cVK5pACuVOj4idZc9R71fQHGnX1jigHvAyrlcA1Wx3p/yWt9biCWGUs6PzmWbuEK7PKFEPAZyTniVmktgLH23XdNyxgwYF7k47GEJkGBRMPY615kD63mXlJzNWreVi1uZuUXIc1tAMxS2X/aNaU4826YkMnJhqvM7byYANDe2giamnLopaZ/mJ88pnXKHGEBa53digdEgeHsjEmwA68CWq5lIU3bVYDIFQqCAFRVpuP7ItgHSvIw8aZ8ncT2hkoN6RYRNmMwdJVIwd5aVlomUOv9WcY5QTkVmzkyIMSd7T40Puo5LdV2wh++9e8yHoAH5qqwBw66v9rF53YQjaN9kVlsnTwFRLU0lJzmkneV/gHsGv02EhJTHQhJETQ5IJ51Yyr9DiRhEeduUJwB4JW4K8ewnFS42u+mmm3DTTTctHn/rW9+K17/+9fiu7/ouAMA73vEO/NIv/RJ+8id/Em94wxsAAKdOncKrXvUqvOENb8BXf/VXL17r1KlTOHWqfJg98MADAID1eo31en3Wz6LXOBfXGjbsYrAxpoddzPbUx+8HM9/98c/iH3/9l1nk8Yt9XB/SruMNtIOwEiIFDEEZnvmHWkIGtIkz4NZAZQrCTyu4ThPWcZLyLBVVoJ3xVQHOrXmmrzB6pT4bK1Z/pFWgtX1GBdvyhbsPyK6+hrWdrpzYRdht6y1dt21nA1q3guul4+46vm4B2lQfb0G2325AdRdIN89Tl8nHub63pX52fWZdKPdhIAPJUN6vTRIkQGdAMiinHCHbnD7n/ckoADiD2z0+4rvMtG6UHPPUYzxR9tuu8YDaomEXjNbvJ/csJaq6Msaw91ktkd0+N2uANm4SJXVu61haZbATStowIpRUbJ4JF9APZCBvacJi/gNUl4/se82IEuE6piC/NQkbniQCOSyl4CS/NRk0z6ORy1aONM5UACQHbOReSSYrEgIS6UQVIQTGhkPelt8r1vfIlK8fg7jHs3tXuSyHWNeIXpCJBt3u9C1jNja86SEL7u7GW3nmw4DoZDn0JCWY9GGQH0ZN86XXDsRgzpNFK/HZjpQjh08hud/wXC9PpFlAhFxGdiuJ5g75W7U/RpfeSyZlVD5+rP+jHm6nT5/GRz/6UbzxjW+0shACbrzxRnzwgx8EkPv07//9v4+v+7qvw9/7e39v6/Xe8pa34Id+6Idm5e9973vx+Mc//py1+4477jhn1xo27GKwMaaHXYyWGHjCasJDm+0E5X0PrfET77odX/bk+hvhYh3XDz/88N51j/VnAU9svnZkfqWFkfOB0ADU7IdJP+s0Xus4YZ0yuF7H7F/NQMl7bUB5edB4QGSgXO7Jmjvb+SQzcQGxxMJEl49aw8+GkjD/EGYBcQwLliawoSBC30bU9+8+Rwus2/UO5roG2vZ4dd0Z0O77cJvMFwVAmR+0B26cgdgy6K4Bdb5n/fzVqyVq9rtdVVtzbwV9UBbYAXRmyr9EQW/s2qKg1GYlyvVc83Zbh+FrQbYvn53uAHUB2dz9G+DemHH7eYKk8c/2iwPfcyDOBrIFMfnHg3vI/OcQMwAyGTlIQLvmQmfzk7d7krZPmPBE4AggKNCGpO3LoHtDGiAt52jepCkDwYlNRXMUIsC7QWaoJr9y8C8NGJZBZMQmTRYIbJMCVshAc5NKgDCElCfTWFJU6WRf0MmSIqNOymbLi7a0coe4Luyw9rlb6fdh10qYhNXOfZoQcqTBEvwyJATOkwnqr80yeaF/AxxYwDbyew6Qv0P5/c0Xz30lQfPsx1WDHeoYFAZc55O+kOxzn/scYoy44oorqvIrrrgCv/u7vwsA+LVf+zW8613vwld91VeZf/e///f/Hs997nNn13vjG9+IW2+91fYfeOABXH311fj6r/96XHrppWfd3vV6jTvuuAMvfelLcXR0dNbXGzbs0bYxpodd7PZb9Lt45wf/YGe9B598Db7hG/4agIt/XKvaah871kAbKwaOEqZVZrSnKeFIIo57sJs4YJMa0C2BjJTFPrVZgYEMtDfCaMccBImZkGStzHQBl47eBAo55D8u5butBLYqTK0dJ+QP4UlRTQHCdT7kLf2hQK25NVjAogfcHqx16avm+eAYxAoYwwX1wgxcV4AXpW4PTFfX8MC8BeU9GXkbkKwFagqy27Zv++avIn+5rum9A8HC+R5UWGztmgRx9SQkDcCkebY1L7d83AvdWIC5DqBdALvzMB5cqy92C7Bb6W9XDq5uB3tgJJuIYhJfZ5h0vDDXflvXnBlr2TbpuAZGSyoblzzaKtP1451k4iqQgaiSU1tnPSTyuwIkDapI+W87rTIDmhjgieRPKiBNEziV/kpOj7wSGX4K0YDfSjIfIClA5C0yctvLgFHBJHJ8iYDJrrlJ+fobmizI41EQ9xaRlGtasknAd0zB+iu3PRhDnSQAHyOUd64TGn4ENBN/PatSj6GAbIvM7p65N/GgYFmZbKvDIhUBENhJxxNlVhuU+56TpGiMFrEdKL/7gfoy8pQITAGJUvHP16jk+vssTaBNEy+CkAOlBVRjYli2F73oRUipIz/p2MmTJ3Hy5Dz67NHR0Tn92DrX1xs27NG2MaaHXaz2sq+8ai+g/V//n7vxpld+pcnHgYt3XB/SpuMNtCXSuEVLVuCAjnTcAWwAFuAsQYKWCeuzicE+VGMMBrBTLEx0DbRl7aOwKXjSbTV2YKX5HmPKvn+9a/Qkm1vxYYs/jNR2bdp2AQ+ul0AwO8Cc5nVrBvoMwHVTXoH8nnzcB75y97D9Wft3PvpBx0ol2Me3sl7aBh9NHNJv9ioYwjyy69+6kYvy8QWADewPsnvXXWKtDzaeB8jzzPUSo03t+2LUIJuBKrCddpnMTDHp2NNUYCTjpDDbhelGeSdJQFXK57Pkc8rMJ5myJQJYceaANykYqAUgAdK07/P+RHFRRj4RZ0Dt5OTVpFiI+beLYcz1KkQJwpZl5spkI+TfO2JCipOxvMpwT8TyewNjt20Cwr2zJRXFoXamUchbU/CdiJB4yj7y0JzkoYB6zv8Lcmnx2db3E5DfAWufqB92SCYj59xYm3DwMnIK0k+p/J76aORfSPa0pz0N0zThnnvqQDb33HMPrrzyykepVcOGDRs27GKx6665HJc/4Qj3PbTdr/nPHjqND991H174JU+9QC27MHasPwtoYoTJpbOxCLz9wDuJhfFR32yNMi7RwdcCsqMw2XEzyTrkoEjrvGBNwDrMl9Nl0bq8DuBNCX5mAdCAgtyoLMaeBGR5o0a6rXFKOQ9oAGapaCBlJsOl/hKpMI2xWTaEsKHM5kSSdEiQ9Etue0152VDZXgNhDZCsw1rq9pZ1fyE95urSBqANWyqoKj2UA28KxA/6xtdJDv9eqv3CdHVPb99Bs5Aw3CqxV390S39l77K4HizfqAwHWxQ8k7hWCKD27hV+m9rzrRv6AHyryTNWE0oGrskk4zPZeAOwK99sVSNIeq9qciXJGEj1EjYM2iQbz2GjacHa8e3GT8ppvpR1h/xNQHLecwI4ySScyyhgWQZkAs8yGci2KmeUge7ZRFyluPLRxyeStFZNKrC8REsHdmKKOR2YpL3SdGATMVZTxNGUcjowTYM1pZLOLRQmuowZNxh6r1rf8w7TvOP6bIea/z23COMCoo8oWcqvQGwpv7TeJNHYCbDtEJIFs9NUaDpZG0L+v0JTAk0sqb8ya40VI2lKrxXLkrehyxeQnThxAi94wQtw5513WllKCXfeeSde+MIXPootGzZs2LBhF4NNgfDNz//ivere8Ym7z3NrLrwda0Y7HEVMq4ijo418SCYciWzcp3pJglxVVpnz3ZZUXZsUsN7kCOObzYTNesqM1SaDZCQAmyCRo5E/vnvMqIFktikMnrh8qAZe/miV85ThdN6SApQbf+ily7BjruHA5S5GygBRh32G23ZAcTEiOJq6PD8f6NTtbJe6XLWr7X9y967Y9Cb6uMeIi3jR+2X7yQ8HsquJEak3s/a5RUoeosiYowAZluB0KjV3DKPIM2Ceoywjw92vAsXyUHUU8bIdxE83hJKAyqI0Nwx2Era2DoRWgFVbn5nK8FyQjpdt1BM6Igsv2z4QGgso5xnoVoY7N1g7QgpWQdor3CYVV/iSjokq6ThS3g4kAbM2EkwNIcuDOUelJvHxXdMkUum6H4nyb0AAIaSSfmqXjBwAjkQKPVG0siCh0zNTnrfXLk/3hgNWUr6hYJOKp2P+LTuayII8xpBANJmCR99jjDnYGotqR4dv37WEqiB5ral8vJ30bKO07wO6NSBcJSMX1v4oRKzTJEx/DvOfGe+Yg8VR/jvTgGmIk42PSEVGTkQIgaDJAVIiZOdsQgpUvHKIxHcb0BgWmg4MgcGbwycRLnZ78MEH8alPfcr277rrLnz84x/H5Zdfjmc+85m49dZbcfPNN+Paa6/Fddddh7e97W146KGHLAr5sGHDhg37wrYbn3Ml/u2vfXpnvV/8+B/jn7ziOee/QRfQjjXQJiAzMSgfdn7trZfXVoGEBkfjZkHKTJaxwsqORg/0yGLkGDBSFpKyHJwVYO9DdtgHnYKwcsjUnL3rOEBt36PVM++4uYJmreoAbAWMuTCTnp3tAesu8O0A8eo+DUCetaGt18jWy9o6YQ6ytwDser/XTfPCiu1uLyn3Nrd7N27QPCN35OL1jfptyk2fn+cjiet6Scbb1lUA7VvkgfU2WXnx8/WF5XrGWHP/vc/Goa+LUq8C2T5nunZSZPOxpsQOIMHGZwmAxlldQKVcg6FR4qIqkLHMtkjQMbD9jgTpA5/iz/d3KyP3ZvmiXedl0O1nE0paMBViraRegl4zO6dbgLQUZAISRb4u75GY5LdK3FdsWkd/zvQHaXls7oqKr7/LPZu2nKdm0de7x6RPuASU0z4IyO0KXKKSJ2lr7g+Rkbt2AnkcWB8piE46U5M7hj2VH7gsjzH7yEc+ghe/+MW2r8HKbr75Zrzzne/Ea17zGvzpn/4pfvAHfxB33303nv/85+P222+fBUgbNmzYsGFfmHaofPzaZ156gVp2/u1YA+3pKGKappw3O7BJKT2b7c0D6o2Xe4r8kxmIsfhj80aAdgJoHRwLN4+MnYG2MBzqq0fI6V50e0It1rcTdR+OnmRHSwKGvnV/6XuuAiPuev4+PK9fAfgWLC8x1wa6tYMxD1SGFmg3ALizXYFqLNRBuU/e7lx34bzZtR14njHZKO+yKnfrncy2v6cANHJrAGD1F6Y83lhfHqNB6fUFdZLJ9kkBtT7a3Bc7k+Q8A9fWBwJEFJSdiXl/dEpl/CCVSZoSdbxIxP3kDTG7MgZUFs4MiFQ838y9fylgErjNDJqyHzMCg6j8HXMgcMwTBmkFy3tOMYOrQIQUc9+zBK8DAxwD0pRfYAqc/bOJEVMBclMIwq4yApW0X5nlzv7Y5ZXm1FUTZfVNGzTMO/4G4jpIGgvAJ7kmgACVqCcEzawg7zu/26l6Vz1lApAyq6vuCzpW7KQzB5TGZu8x89hjw3Mjc2SyoOm4kHBEJBMPtb92mWxAznMuEw/ebx1JUp5NuSwEIMacOi0hIK1S/psNoUy2qYsHIccLCQx6DErHb7jhhnpSoWO33HILbrnllgvUomHDhg0bdpxM5eP7sNp3fOLuAbQvFlutEk6sNjixitmHcYqYzE8vzVghQJgmSDAj8c3exEmiiwMpTkibkNnsTQCtM7Od/YTFn3bTgAegAmJJffoCZZ/OCSW2lYJujYDcMwfehCDX1oNBMyDZO33b8Rmg1jID2CU4VDfwGKPkH9ZtOODU5DnuMdpdllrb7wNcwdVZeKbZN/+u475q+wo8O12BaoL6zutxwz9+gqR7E5hLgG0nZPYwZT987TvBOEUJIUG8EHSihef3MsAMk4bvAtgqd7ZLOCY7oWzr43WHUTV5I7Lxxr8cHmArgBZ/6EUfbTdZo2y0ScmZ3bXkWUVCXnUJUWazpY8D8mQGNNG5/A1m6TgjrIWxTZQnx0iyPa3k2ddAWkl07k2+dgqEGLMcnym3Ufs359nOYHIjAFx/K2w7ROvcQLC827lOsrrBScgBx5AjDxzN2a0ycg2slgOuMYCITQo4TStjcz1DnKXm5V3n7SARyaXLeu+8HQ+dspbJNsb+LIC6nS8S8pxSjZEo4AgJiXTyQdj9uDLp+Mr/8bi84yojT+JaxIC5SaTAiDGP5xQyWLcxDuQJLgHa2NTvatiwYcOGDRt2mHz8H3/9l53/Bl0gO9ZAWz9qNahN6xMYKNnHp7eWpTOsqZJvAwtwIFMZMhQZqwcEDqAROZ9aYbpJP+KNwnQNODPSsAaiB9TtAlx5RqCAHd2uQLKBn7KuAo6153G5T7XWe24D1fsA5t5Ewx7f8F280APZcCC7Oe7PKdfd42W2cyy8o3xPa1N0Vaw25iB7Z1AzbJfs7tUmBXDu76kc2/KudGy1TFoCqghcvVxNri4F5L/EhMw46t+2u4epomU8GuPu2+yl/upaonmYGdAXp9JxjfptZcJWtxa5H4V8mxWQmn/fgk2+CDi3mbmUt+ECiBEXAIoyJgIKKGbZtnzp9kOWbZ9x02vz2YJrfy3t08jld14l5CbJZ4iUvqgCAvJ78JMNXkbOTslRZORcftP170qGg/7NurANw4YNGzZs2LDGDpGPf+Qzf36BWnX+7VgD7ROriBMrwtGUo8xO5KXjmqe1Btsa9VcjjcdEOXpwzGuOBGwyi00aZbsK2pQja1cg2xkBkruXxJ9PPsbV4Vr9/DT4EoAZuGoBqZajw/42x2fbwBy4GohoJPAePOv9oiuPhZVU5lr7BmhBN9AGImvbX9pVN/hcfI/PmWrqH6OmTPdDAc3mBtCw3N0yuP2qQe44Sj9YemDOEz3qK+xzQVuKIQYI4mcsnVgDaqDHZCtLSsSYgo/+PO/oDFXkuWnZJ7u7zS7PvMY0UKl40rzZ5MpRTdZoZHjSCRj3d1DKuIBiZbKN5S7Pk8Gz/r0JCkoCsNYJPBHCOqsJAkPSM+X2pw0gym+ETWb4AyG7kmgQtU0+MbOdmdXeiB80Uw445uXJmxQkB/aUgV9WixcpOANAsABos/RfKNtWRgAoIoo/ShIWe5oKo62B1YKyvkz226iANEiQNCAzuzbhpmASofyJdiTEOkGpY8TyqJ9j0z6IIg1PTLmMRHqfXzJWAGLO14UVkrDZCaugkz5kLjxeRp6fWXOQ63MRYqCsWmAgxvx3qZMt+mcdJGp5PBqM9rBhw4YNG9baIfLxX/7kvfjr579JF8SONdA+mjY4ORFOhIhJU91QnPn1KelVBT0DEJNEIRewzSmn8NFIyRRzmiqNkuy3KzbXmxJfkpIrMCFJrtoEygybyIAzgFM2Ssw+aAvzRr7M1atAdsMU1teqr3EwuFapbuQu6C5Am0tdZR5RX7s8k2vwPsC6890+Y4+9qoBLWWbkuALbLXs93y4stvfRnm2781rme5Heat6LBMU2v2FjTqU8bws4WJiFKACbRUKeuiz2ZICiZhiLHFlJ4/2AktarAqCZbJzsOWysuEVVEH5yCTqx4PvK1SE5TjGJrrkB3NofgLwgFkQKIGiQqyB/o4ywyX2eVkDY5FvldHbSF5s88ZCIQRvka0WAowDKSEgUwJzBdqIsI48K3lL2j7aI41P+cUicmWUwKn9t3fZuLxPS7DfNm/p/J5ABbwXda8fkBolS7oOy+fdf2N0MNkl8m7lh7ts/pXYs7CrzbPo+gdBam5AMbOeb9P21EzHWaap9tIXN5yist14jKfJO1m79XxEYJkcPgRFjsDraF9OUs13Qaj9VwrBhw4YNG/aFZvvKx3/+Y5/F8x4jSPt459EGHIgo0khgWaqoH5T6EQXIx+BMLl72CQ4YNCzbHCT4a8h6JkUlB9SpOY8KGEZT7vfhjvs+WWyHu27LJHrgt+AzW/nTznJWM0J0OYqVnUztflkMrMfle7agrFqQwfpMWgwsYdH8iNRsO0yoYLkCzJ36/joVyIar7/HFAeQete+7afSunMU9ANRKxXsRoM9G2mvq/97pfty6datsoHabMXu3ymhXY34mJUeJm+DKSAB7Ncmk490FXSN2E0az8df+rSrYImuC/q60EcetuUymqinb+/8M995R+5unwDxQstzcwdY+WGSqfjerRfJQtxM4AOBdEs6VnUlubW/5mfOzefDeXtenYNuWdqzOYgFRg0jqyIVc9OdSHj9s2LBhw4Y91kzl47vswVMR7/2jc6+MezTsWDPaJ1cbnAiEE1M0JnsVyoeVT5/jwbVGG1c2O24C0iZHGofIxU06buCSFkFha0lStapCUaXjCSyMNjJ7Lgwl+bzNYhUQUTAOGPCvAScWgIwD7MmVO9m7AW0BxUABwGAgKIvtQDMYCBt2LCW7a7ltFxW6y7g3Npd7u82kdWpAy0HuSYClM3NgNwNhsrp2nwZc1/Xn61kZ3Lmz+/Xrzh84N4ag6aNc/zAkEjlyLnY7nhlvzyq2UnEgB8Qy6XhoUt/J7f3fhvUzsbHaWTrcMNaYg0t9FAWeVSo8N5mjAQSrsecmUZStrpQWfiyZmiJZgDRoBPIW7SeAQ2a0aaISfC6m3FcTgTcAhSw9CaucM5tZlCskEcAlEnkIBN7kFE8pIAdaSwSeGCnkPNsx5vfAISEkQqBggdEScQ6OZuxzZrXzNhmTnUF3Amg+C6rvy8vI7R26ARYdu6v3U0YbAE5T8U/2Ka8AYB0nA6peRs5MOQq5a5WOwVkqRQZIfm/P1Mc/Sux0tVY6b/vkIrKrfIIDViFKXwasRD6PAKSYA+EFynnQg7wXYhL1UQ5Il0QWo08WhfGeEiOmmvUGslJkCoy4GtLxYcOGDRs2rGeHyMd/9e6AmBi7YfnFbccaaK8o4WiKOBE2hYlB+fDUjzxlkPTDKDGJbzaVKLPiRwqm4k/aMq4dX+QZw4wCri06DufCQPnDHAnASsE4lXpAQehwgLQFYVK2eNyf70BNy8h3JeBSFiILoG7AdSMj99teCmygSdvhg1b1LFj2YwdOHbiTPlJQDek7F+doqxlrjXydArqpih6+E2BTOa/rk+23F4x4NmTsXRrgFtfTAsBJkI12hoyTzqxFzVxjBrJb9k5tFyCyYIGzA/mh2Rhf6QQbe2TPVPlmu7FYTRbVN5X+yaDa8myXRNbii+2AmOTMppQAInCEBfUiytGhGTlCOwsjTpHML1vTexHJtq6riSj5W44S3dz1T0oBHBJiCphEtqwBtozppnY7A+zsH5+3V53X0crIJ5mBUnV85ICAOA+8prMnQP6jRpap59/GiISADSVgQk5XZmMhy+KTXEPTPOVAab3X1c+n3eYM70UiP1Pb5q8dmCxImsXuQO5z2LspP56kcnHXvsRZRg9AJq78/xPUjHcYQHvYsGHDhg1bsn3l4w9vCB/5zJ/jRV9+xflv1Hm0Yw20vfyvlY6DMf/YRJF26uJzxZpvtgIAuc7MX7oFq813IvvzE8DKcCvokLRNTAKm9LoGolCDDr2W3/cgW/tD2toC8Bm4duDbM9qz6OG+jpfTsrDfWjcqENJrcAWuZ9/d+qy+SIF4KO1nMLpf88DW6N6V5FvVAhVILkB5kYHexn43LHWXtT6cxCv9okC6LUdd3Jqx2kAX7AB9kO3ZTQYsH/NiMz3L7djtXFjOpXYs+rYuPEcFuu1vrjNho5JxWzcXTGzvkJABoq71b4B1YihQGb9cWHeNQD6bWEt50oOSn1xAZrtTQLD8zGzMrvZHTp+mEvKCfjWllpfIFHY7g+fWJlfXl0UO1TsFgElSYWVAShapPEDzTDNWnINBrmSSQP2VYyILFXCoXDzfr2zrOK62z+iPRZ7X+Wv3Joo0+rjfb5l27Qt7T+4ZFXT7+uwAuUaWn0Rqnw7sn2HDhg0bNuwLya675nJc9rgj3P+X26OPA8C9f3HqArTo/NqxBtpTYKwoukjjbD55iSdZK4MdsOFgsvGYQs6dnQgpUtZJRjKJOBIJs0sWAE0/uBVkVtLr1hw4CowS3TggR5NOyHl8FWz3wJpeBx1gXQH/OYMN9JnDfVhsy3PMmcX226TgeiMASEG4gCD99reo0brdPlYbmEz3ma0vKFANtluArsx0DzhLhGENSqd1fT5sX65128BoreKgAvGl6+tn0ba14L1zTsYBBGNu9TkZmW0VyTNbBG2Rjdf4YWZeMj65wGjKbgO1dFwZVz03AIgdAORBtUaXZm1zolnEcTig6v39jbV3Y7bedhHIEwORZXyxgNzkpOOpZrRV05wpbGAK+fzA+W88JDBCVmJE6feNMtoSII3IBUOTv981SeA6zrm0A4CJwJsADtkthBKDOSBOSQJsJUQZi0EY5MCwPM/ggE0SlxcG1pxzQQMiN+cAzaOd5MfCg+4qaJqBbKlPZNLxKSSseYKXk+v5p9LKficD5ejpaSKElPn1NAmodDJy7zbQznnZcdQsPgBTF83VFD7i+vy4tbejwlAZeSIyNl+Dvq0BTMJyB3fdwMWnepMCAmsE+O2g3z+Pl46bb3eYT34MGzZs2LBhw7JNgXDzVz8LP3bnp3bWfdoTTlyAFp1fO9ZAe0UJgWgGstV6gYgsdQuUCCP76AdggGHmO4oGyHqQ3X4TMkwxTspcJ0DUjKYE1jQzmnO7kpA312u3C/BeZrBn8lzPUivQ6bDYFuiMeRbczBjs6EC3AnR2a/8qPNCWD1kCF9YY2U+5bDfgdCnMcdtNNF97sFuBbAeuK+m4k5R7P3A7vou1Xji+CMirB2i2PYvt3ndFdjcXVkDdmg/yhC11ltjsVjZubLa0qeSgh4xJmo1FP3b9mCU3dqrnd0x1qcOOxVbHfYf6IGDXuxOIvJwTgUL54zd2O3IZ31QmBrhZ+79hlZGzTCboNkt0+JQCKCRjPlkYUWVyLce2Gwi6nUAVgFb3lyXw6ZntiuUW0C3TLDhCjkg+cc7OoGD0KEREJqxYc5oh+yFLH+rkpM05kUjJD2Cimcm99PJcu8yD7qUx68Fu2U4C3rkw1jI7ZYHgHOg3VX2/i+v7yW+Rz5WubeMBtIcNGzZs2LCtdt01TwWwG2jv+Jd8LOxYA+19TT9UdVtl45gtKMC1BdW9NVwdZ8o2EgQjygc6B5icvAbVZCdu+/b04LreL22wCQLdhgPZCTPArYy0gmstL+x2kYxnH20uwNyBlApge6lvY+w7S1NW7TIfAK0BzC3rnIE1GWPt69h28OUedO8A10sTIe0ztgDbn7+POUCax6lKVbm0j/u+sGreN5usjLtrQF8b7WxiHQhNwLaOPx9BPwE+oj65xbPWfjh4ybbfr+ThCYXNFnY7M9zVLIAEkaNyXjvOLGd3zns9+zuvXCZKIESQTEKlDBzNVxslBkRIMEZXy0j6tsiV62BhZTszu4lzgLRDoljPfJ2V4bY/9gBwEuY3d+xRiFnRQ3niUllwIrYc1DlgWD6fORUVQ2PzoGg5sJhOBvWAdZQ6dg7o4FQYLdgufZFM2aR900rM2/02X7x/puILrvcgA92h/dEdNmzYsGHDhnXtcw/uJwn/ld/7U3ztX7vyPLfm/NqxBto5PU3Y+jHq03llyXhepyQBbZSFYpg/ZgGkc9krzcCq/8BHBmapEyhIPtAt1pGUWdArAYj+vA4JNGP9ZnLxBnQb2I4FtHj/6rCRbUvNxfPtjTBBGwE1kQsQt6jPKOgCBSxVTSdyzL3IwiNAEzKnT219dEE2q9MnZXDs5eI1uJYyD7Cl/wsQL2Dfy8lnABvYbxJk1n7MnqtrzXtVP20SLGllChqlTMHctnk/Lxk/JAWR+WIDBqyNPBawxUnKff55DSzo/2ai/o21YLtsF3Sqk0B1Srg8HiUMeBK5OEtO7Xa8qU+25SX3PtqiobC4AjpplJ82RMo5tiMhxQyiOFCJxB8IvOKsfNEI5IwsIacchVxzLWPKEchzNMSEFYuPtg+GtiUCucrHIzHAaeZ7be/YvX9jtb2MXFjyRPm9GMBMACZhrT0zjLlE2lhbzjJyjcTdG00+4YAx8txIyfcnxGc290/Pkwj5upm119zaZWIpy8chk1AWkb2dINArNiB7KV1k3bABtIcNGzZs2LBt9vQnXbJXvf/y//wJ3vTKr8QUzuKD4VG2Y51HexdgqHwD3baBE2O2US0klWaycG7W1QXLdsXU+eu20u0Og2b+q67+0tICFmq2q2sLyC5l/YBnZd+BEO8b6yOMK8g2ZjGXUUzCPtZLScGEGhh52X7HugBXQbcDwR4YVyDXM9eO6VYGu+zn47WvNyrw3l3c/f2yJCNfsmqSpBo/7QyErPaQ3vbyZR9i1d+N6+zlvx+qx6Nrb8tmk5VzNVHhlRhy42pNylKzH3vN4q1Xpvdy1662bYyj/hvx+9A6pQ88298u2p9+u/cb5fNqt1L+Fti1gHNRRi7mA0b6TA0+3/aKkqVLzGmrUhWx3ueNBsrQbkfjPuPT264gfNuea6K0OLbVpWhaPD7Pqb20H8DVkvsqlb488O9r2LBhw4YN+0KzffNp3/fQGh++674L0KLzZ8ceaHvpX+JQFiiTHWYfuf7DF0ADkjs3aoB0VeZARA12uTBlHSa8/YivAPMCwLZraB3vO9oCguhY6mY7bLiUbfRYZrfDJm9rvVKXJTAaI8QE2iTQhk06TpuEsJHyHhPJEL9udr7cTT975jjnzGkYZupve9DsmGpls2fLBGOyeaqXJAuv5sdmiwfnPSDunsmeqynbau0YNSCrC2DS7XNkeQ6EZgB7BiAB80+21HhNGq8SCK0Tubs3vrme4KkmeiKLbzQbm00aBE0DovkJnp6kfA+r/8a4ZuXd35YFSIyUVRkSTJFj7g+29IElLkSUVIK6WLpBeHY7ryOX3y89Ht3PtdaPO3LbTZQyCAXb9kQJRxQxIUm6sGSg8ShE+11VsL2iDLZXIVkaK5/Syudmb80/r/9NLvthb4C9jwViS4Gmz9YeX4rpsS22AaCTFPmaqxBtCTIxocuwYcOGDRs2bNk0n/Y+dscn7j7PrTm/dqyl495apmeTHOBGljkqiKglsIAP3gSgBsGd7/QuE+cZOdlnQv4gd6xqJSkXRSkHuaZjZbuxvzwz2OzbN6Nn3mbbXEA4F4CtZSV3NldycQ12FmIymbiy1vnaqdx7McI4AwFZwEqwHNEEqglbBdl+34Cz26Z6e0kuniatJ+CYMsCuyp20fF/JuGefudn3Y4bba/g1LVwb2jcwH/9KHc6QwF4Q+XMZz+eSTzNA7Seokvv7UZDtwHX2Zy7R+823uVVPuAmjalvHkKooNDJ4Slk2vokwuXhKFaiWRuc/nsjlj6gOk955UDQSfWkH5cmpBIACm/w9BFjU8TDlCORQCXkQAD2V+2wCZ8kyokUgjykgTFzk1JLqq8STCBa8KzIh6HEQIoWc1kqk4ZFzWjAvHy/ZFzIQnyhBAw94n+1VSEACosjFkYAQ8uTlhgOAjfiY52sf6STMFAFoZgcGUujGDNAgaGUyVJ6PAxIn+3vI0vSdQ9LY7G7ubSqpzcwnW9h6SNTx3DflDyVov1AJvNbL+e19vLfloR/B0IYNGzZs2LDdtm8+7V/8+B/jn7ziOcdWPn7sGe2eVZF8F+TjAApD2JYdah7wcrtfLkhcr6tz5Do94N4y5+09Z6xgb9uCPzUAx0lkPWtn3+KeYVRfbJOCAxYFWgFSZ6nAdyMTXuzSBRC6rU5PLl7vU7d8dg7K9lLdqhzlnG7bzuK3obzvEuG4N0YrJf45YAhb2W/zCsvfjtv27SPWCSeaTVxVY7Z9nqrefIxZA5x8HBqB3EchPwujpj3t38xMkeKfRyYePPvfWts6z+4CqBjuJVN2e1cOamVgvSlYnSjV7C8Ky+ul0L0FQAWseyDbfLy3trCWyp+t9WTluVzBcf18Z2sqIT+X1xw2bNiwYcMe67avfPzPHjp9rOXjxxtou48cZa43IkvcpMlth0qqaRGTe9YAp161XThmBn5Fgupl4jPJdwO22w/6Xpml3orbFg1ehpz7euPk4huVi7Mx12HDIN3fpFoqHjOTqAtUKh6jsI0qKc8LIkv+44Qq77FL29QDRRVAFYCs8nAvB4eLPm7HiSqZeMVaL8nIVS6u+ysgrfJ6tizIx03N7e7bY60NoM8GTNsJzRiq9gXMpcIwlxRbyhxC1vXNegCukjHb4l0tYGx2UlbbS8Yl1zwSSi76jmtDxWxzKSuTPC7NlsudnVntCEoJiNGx2amA7BZwL7HXwnLn90D15EvV/1z9zc1cMjbub2yj7H3pD44iG085MFpiQkpBAjIG+03S36haWi2stwPgJrNGLT8HarCtUnJ1ofHmQWjNfhcp9UTs5NBZLq7rSSTkU8j1bDsUv+3iv912Z18u759hXxm5tt1L4VUeb8/aTCDoc86u1TDXS/W2tQOA+WqvFoD+sGHDhg0bNqzYF4p8/HgDbSogGyj+gJvk/BpTMAls4n5aGrOGzbSydhFjp++eg+uWMeaKMW6BxozN5vr8tsxAS5qDgAIGit+1AmwF1tOaBSxInTUjrAVkx3pNBsIVWBeAXYHrGAvQEamvAWzzrYWBmOplKBlq/a4ASMF0AUQFJHVAbUDFRFcgfJtPdnDgegJ4xUi6TPWaJ66ugRbYN0s1jtA8ZzsE235pxpalzHKpsxRgqz8wowNsKhBeg+q2jvfDzn7GoUjGBVyzRBVHzA9ZJONlbJKfCPKSce/7zAVYl3oy5pJO7EQZQzLBE6P4ZEcgRnBK4JiXGcD22xbB3nW+jrGF92BBAxMsEKBNcG2AsBH/802RzCPlKOwsfZcEbOd81GS/Q7GZAJz7Mwfz1VbQvUmT1YkIiFwWc5NxALsHttVfW32VFZSqX/ZEjCNyvttB/I8d6F45sJ2DpuUlp5Wbj2t7TvSes50MCt0JoV2B3vyzAXDPVdj6qdrfn332/2O8+UmKnnpg2LBhw4YNG9a3G5+zX+qun/vIHyEeGHPnYrFjDbR32VbZ+B521gpcGRMz8LTAYs9mAfYYU4tScZcqqWbFfTkXn1jfJo0QLnXaiMx1rmxf3lkOkPHyEhBqR6lP+QUFtNSdHGEHpKr3uTCZUgFkXXoMNXEB851JmP7zNXX2GV8VHd4eK8er4bVl4O7HcPevw/5GfhahGWczVQY6E1G9Ma/bLjdU+RvhGkTLmr06QveBIiNfskDzv+8tkx/tJBiafQKMrfdLG4E8t3FZGm7ycf/bhcJwA+gGRdsmId8mza7AK2r/Z41CruYjb6tUPM95bf8bP1NXhrjnv6eev/a5lHCfC1eMYcOGDRs2bFht+8rHHzy1wU+871MXoEXn3o490PYfVIUpydJMZVB0u17q67A4lbIQhRAw1WUoZ6CraVQHYFRMXvMx3pWINzbzE/WyXM+ySY7rmtmuI4iX6OES7GzjzhO5OIl0nGJZw+Tj0cqRUg5QtRE2W1hGY7ZF5qvMNjVAvfNC5X3AZOAVCA7Nun0fM3k4GePso4wnL/u2KOPCVq+4kotXkci1TOonz243917y6a7GzAIgIJQxUVwOCCVPNYxZ1lzwyS0+Z3yJYJ3HfnQSZhYFiOZR1jLLNV/lnJdFpeLRBz4r8umirqA+q90uOl4TI6xTGYfropjAJoI2wmRvhMnWKOO5A2B5lLsdqjJxKpMv5F0Nioxcx1/1t8z6TC5iv5eRb+R5N3nBhnJe7UhIsbDamzjZe9mojHxBPr4R+XdkZbKLUmfNUz4fAWueELmsldXWBcCM+W7NQLaTTysLrAx2QGawidjKVsZopyr1FzUgfcbYcx193EdZ39cq/2gnJ299pr0sXoOj1SnO0gysz+T5TmWgsv+anT/2/0qHDRs2bNiwC2qHyMf/3a/fdSxZ7cfc10GV2ktBNvTDCRWzZObBTofd7AXCWiQ5WobOAWTPNFe+2guge9Y8Pd7K0pMr936k0QFwWWq/7iYFV3Qy3uSku4kNLEOl4AqiFUjHZtk4X1qt1wuO1uvCWX9TA07rd8UGnubvqQLoTU7skuoL4MB93+sWnOv5ld8312VL7Dia9mOhzLOkylob6KaqTH21taxKv+XHPFAB7ko6Du+njSZCP6oI40upvLogu/K/hhtbC9uxHnfqm22TODZ5EyXaegJSBDzb3f4IN7LwHHVeALW+K913EzjVJUz50fwdRfesPsq6yOlNQs4FbDMwc2eZy8dDDfB8ii87PvfX9iBbZeTA7hRgrW9ykUGzgdMgvts90K3AVcH2tqBgS37a7e/2Ylud7F3N+2j7NGYAXAqzegLBP2+vjb19D7b9xMiwYcOGDRs27MxsX/n4/Q8fz5zaxx5o+48goJZQno3kzz7BOqCtW7+D3SsAjQYw+/1me3aNqkELDXUgvgX7M7k4F/Awl/wK47xkeqzNVdxGGwfqY9ae/oMsBqWq6gA+mJUxk0D9nqxuvXRZZQJUBm4LSh0O0jmyrlKANSC6d89KUu6fb8ezelt0MbDGAl6p0ao3ZsxcD2y7dX091ynthI8tVO0vKTa6Kg4D1u68WMao+fTrOLJUcs242tqBVAFurrbbuluu03t+lGcmf0xjKOifBFyfQj0r3IQInA+98weufs9QAKkdl3NUZt0y2gq4/aL17Lpn8DtJDTinpnybVc/qnuFMbCnKeO9YNyXYnrbkR15PGMwD0A0bNmzYsGHDlu26ay7HZY/bLR8HgHv/4pHz3Jpzb8c6j/aGA8hLLX2gIPkQKjJZCeqk3+fcMNsehAVomtmyn0/J3+shfzgTy3HUAKgF0LbLel3O93dlTCggBZh9ErZgqzDkjhF0jBsxTI5LnBk488m2wFMKth2bqKDGb6vkO3JmtV2kZ2OtgRr8GHMoa60TJGm4MNu9QFQ1u1jYRqCA4Z7CQL9xTTKu12ijjpPbVum31p1QAWp/X5KJCs1tbQcVYbErc+9Kz/fP5s2OcXPMj6NEpV0ps6cc2FhTCoyUCBRz/4ZA2CCYnJd5MjmvB0MKsKMEO9ukYH8nKWUm1vJnW4TxPOjJRRi3tW6LciJstAzm0mAuC8ltR2TZ+FoUEesIWmcmm5TR3uTAZyYXb9lrH4UrhApgMxEwyUIoEeynXCdv+/GW18Tl3Stuy38/uQ/CpoxV2gAkPwi0EhVGRJbaM5AQEGPIeaqJERODieV28m5SlmVvMCHI39IGIbuH6I+SbB8BWENYXk42bZqYhI1OSDx1AWYLuJUdV/O5pzXvtLHBBAmclvN6TyEByQH35l4WtJLJclmr2iiEfB9l60F13vB9CONACYlDAdYc5im3OCERWR8Gkrza8iyJcz/umqjVvg3E2KTJmH/tm80A2sOGDRs2bNjeNgXCzV/9LPzYnbt9sJ/2hJMXoEXn1g7+KvjABz6AV77ylbjqqqtARHj3u99dHWdm/OAP/iCe8Yxn4HGPexxuvPFG/P7v/35V57777sPrXvc6XHrppbjsssvwPd/zPXjwwQcPbnzLyrXmWZNtAaKsPmmAK64AXJcZxQ5GsgXeDnRVknJXxzOBS9LxGaDvsIienS6gnCsAXjGKka1+iQrOBpw1P7blyY4OZGs9k4k7Ka9IxqkXDfpA82x2eTe0/H48WPeLK/OyctjiZOATi6ScpbyWiHevodRmMwnQAmwdZ4tjSN+x2569XyfhViCc5IZJYxTIdn5F1Ew+hQpke1bcIo0DJh33knG9N4mv+FwiXiaD0Cmv5OI66bPRKONcZOLm+6/ScQHZKh3f5pet1k7mePDtxpBXVXTfy5ZntAkG/XtLZH1ksnug+NB7FQHKhEc3AjkXxtT7MnsZc0TxHVbQvA+rvQ+bXIFJF7GbnKzcM9u78kn3Ar35POL7WpWurGGv62OlPRp1XOXuBZDX9ZfaXSZ1S//rBO9G/O6HDRs2bNiwYfvbddc8db+Ke0y+X2x28FfBQw89hOc973m47bbbusf/xb/4F3j729+Od7zjHfjQhz6EJzzhCXjZy16GRx4pdP/rXvc6/M7v/A7uuOMOvOc978EHPvABfO/3fu/BjbcPHvnw3PhANY0sVuu3EYDNll6efHRx+wG+78tuv9m4s17YnknH/bU64L2q35wzB/JcXW8WpEyYcCtrfGDJ58H2OYyZS0C0Drg2sL4HPupa2+9Uv5uKzd4CwDMI5wya7VwPpLmAb0IDxLnepk472gmApr2L1r5z1NszWTYAn+oLBq6pAnXJgpyRrXWxAGl23jwAmr+HBmPL44Oa4HzlWA2+2cUQcPmyFWRrmeZdj2VCx7spGMheCoihKgrtNlNVAJWE3AU+0wmZMkbc+Z13VU2c2USWe14D2/JOUr4wNxMa2veVfB81sG7lyQBsu8qz7QC2bq95qgB3u3jZ+dnIt0vX89Z9b7U7g2uLe8ZtpkA6dMD2Uhqwpfb0Iqu3VueoL2uduPBqqmHDhg0bNmzY/va5B0/tVe/OT95znlty7u1g6fhNN92Em266qXuMmfG2t70N//Sf/lN80zd9EwDgp37qp3DFFVfg3e9+N1772tfik5/8JG6//Xb85m/+Jq699loAwI//+I/jG77hG/CjP/qjuOqqq/Zuy+m0wpTyI7SS8XWcsHbgQtm7nGsYJtuekazEmeUKDJLcy0DeRsKMPW1txl7n3Sw9Z8dQMoOZrBzwx5oPfA+WUykrH/pcg+jOh3/FYFtAtsJma5uoup5jsyvgkxyoTsBmk5vkAVCgfC4RMIX8nDvep4Ecxy568FOBaYsWLSf7QGQhBy4DybojH0+r/DIsFzZpMDQt5/47TgAxgb3fgLww0l19UtaHamwPP1aVLEO6kAXgMgEEzuCXsoS5NCEgIYFClikzQ6S5GetZRGjf58ggIiUBOjEUuXjsSMYTgJjbkiNt57bmyNtUAoWJZDysIRHtgWmdx1bYANPaycVPS0R6JxfHelMk4xoArQLezUxNA7AzuBb5eFDmWnOvZ8m4KRGaiRgr9+b+3jhkGTwzEDZUxtEGIMovjSLKWNZ3RPm+kYEQCJGyPJooiHw5y7ADCAnZNSaAsEIs/toJQIiIsp1kLB2FiMCc5dEqJQeQZFDuYmkBOKAeLOharlM6I6ikHFlCnYXYbO3Q59Cx1d43MYE4n2tpzsi3Q/2cE4KbAJi24NcJnPsDRUYezCcn5IjqFDBxKtJ3cJGRg+25Ek/1a2/Yd/lzyv3jnjmvA9a70soNGzZs2LBhwyp7+pMu2aveL378j/FPXvEcTGHLR8FFZudU53bXXXfh7rvvxo033mhlT37yk3H99dfjgx/8IADggx/8IC677DID2QBw4403IoSAD33oQ93rnjp1Cg888EC1AEUKa5JJrtlsL8dUQGHBnbbY4uHOqd7H2MvAlxho23Zraut2zmmZ6i7r2Tvfta3kvG6PscnMfSAz9NjnKjAVy4QBF5Ctct4kZZ6R1OueKzZbm1SBpLmcvD5es5f5254rIF7lzS6dl7eV7XbXtPug3u8/Q+n4XeRXNUEC1JMrCuL1cgqCHXOKlqFuGFT7G9FyqVfJyD2bjTzJYKy1stnSlkpG3ciqoVJxk4w7JttFGzc22yskUkKJMt4B2b7PPMAuhYXVlnRv+V2WSZ0qGJ+99+bi/m+uXdzkVp2Czdcr0v72N6llSesyF4XcGGwXpdux2xthsdc8VQx3T+mzBLLPJJJ2nS6Lq+7rXa163obFPhNWeAJjamTg3k+7pC9LDljPJedLVkncUd6RpcKzv6eDmz5s2LBhw4Z9Qdu++bT/7KHTxy7y+DkF2nfffTcA4IorrqjKr7jiCjt299134+lPf3p1fLVa4fLLL7c6rb3lLW/Bk5/8ZFuuvvpqACi+piKF3KSAdZxMBmu5hCsQgQIg2C2tOeDUVvHbCl4XgS9jBpJ761YSTM1idTuAfck/uxzjcjzV1y9AzdUzIJ3LyIPuFjyr32yMQIoulVcDtoEiNz/AKoDswXQvyJnLmd0uJg926bjaaxQ/bM4B6wIDE1ey8fwgsDqeZffB8wqon7/InXM9nTFULwp0UYO5VFjoFHXMB8SYczjHGLDZTLY933egPEq+bF1SDnwGTWGl4FnzSDe5pX3+9rJdlpynXXO+a0q45KTjRTFhAdC2GRFALgCaBDtT0F3lza58salhtMnecbV272Iui3cTC14+r9uc+88HYdQJjcwcw7bb1FfFF7iAZc27vU5TJV1epynn3ObJfIfXPBno1m2/eIm5guySQowq8Lskje6ly2rB9i6rwD9cWzSa+p7/qhRsTx0Zed2+JAHfAO9nvk/qr6qdDnTr/6Nhw4YNGzZs2P52SD7tOz7Rx4oXqx2LqONvfOMbceutt9r+Aw88gKuvvhqn04QYW+l4/uhZxyBBoDLIMKCdXBTlFsCokezLNzK5D/He91cf6JbjcilAcGypz2BD9ChAWO6v37Qt0C4f+TwrN5BtoFqDoDk2kR2bmDyQ1nosEml2AFwAUAWwFQTFwjR6QCTR1bFaZfAtGmi9H2vbGytAiGQfBQwtgmgq0cNNDo46V/bKAWyry0UuvhJwLSx39W2vWu7oBgm7colGDiZQQOUmwDqeeraERLg+zICTkJf+AEmbdBhJRWZGSnlQ8EQyhkuEa7sNq/RcJqGim4TaFDab1pnJpogsEWeANkBY5+NhDYswHk7DoopPpxV0M8I6A+twmjGdzmMpnE4Ip7M/P60jsN7A/PxNOi5jS1nt1oKAbAesTToeBFhPCrzJxotJuzUSvXdP6M29uUkp/V2oIpDLe0iQdxTzD4bJ+2OewKCQAXhKBKIsQY6U38tGbpJIx1/KAbZCBoSbhAoUpqhRsFMGmRxmjO1EPBt/bYRt8412ALsHuLVO6XrOUcJFMp4DpOXfYy8j98ZSLyHLyMt9s/Q9Rx0n1yYqkctBmGZXrG1ClrRr1PWpIxGfQCYjTw5g6zNpu0kk7tqO3trbJu1q3bBhw4YNGzastRufcyX+7a99eme9n/vIHx0r+fg5nX6/8sqcdPyee2pn9XvuuceOXXnllbj33nur45vNBvfdd5/Vae3kyZO49NJLqwWAsT9FOl7LxX1EX4cli7xvgck+W+tKx71xvaZm7ct7ZTNJ+lIb2mvaNrt6CqoLC961NviZL3fgmk0i7kD3Pn6LS/0u5dWr8mxjxXSXMs8st/VgwIrrYGfULvkFUGADqn5h4nLdTtvsfuhde8szLxm7U5jqSSJbpFxwaZGSo0S+dqwcQ8oT6sBnCagijLv7FXm0W3hhu5KMw9jwIhXP48nk4hrNvhpvWwKgUfMT5tPK2X7TjT4Xe+ujre9qof/tNq7PK3UIlz7ovhv3/izCuyvX9+PzmbdML9w7LNui4nFseFuuC1Ck0FVZJyiZr3uIpLvHCG8Ljmb3au7h933u7933r+XjxnAj1TL35gd0SUreA9dtvvpukM1hw4YNGzZs2E7bVz7+4KkNfuJ9u1OBXSx2ToH2NddcgyuvvBJ33nmnlT3wwAP40Ic+hBe+8IUAgBe+8IW4//778dGPftTqvO9970NKCddff/1B99uk5iMyBaxjwCaW9EWZzaYc4ElTFnm/U+d/CmAZHDvrSrn9x7a39iOc63Jjn9uP8jTf9rJv7xO6nHKIy4e/Y6i9X2zNWBfAM0vp1fpmK5utPtkarColcHQMd09yrtYBTi1oVaaxsNm1bDxNEtjKBz2bgNSw25Yvu2KyYem72EvFJwZNArAltRdC3m8BORNXPt4e/7Y+4WdknQmTIl12OaxlMYAcCdgE8IbAm4C0DrbuLxN4HQBdNiEz1+u8hHVmr8OGQLq9zgHRwkYYbV1Os9tnTOsc/Gw6nbJcfJ1Aa9neZMk4NmmeCi7GMnHTGgXHYk9AyOww/DIVdjsrHkKJSC/5tPOYcy9n4T3N4hu4v71q0kH/3mJ5R7XPdknDZv7wgIsCX/tVb7ikaVMZ+SZNJaWUZlsQqbhKyNccsJby02mF02llx0/FlS1adjqtsJFz1uIDvkmTydR9docayG8f2CUtWP89tlJ5APCpy4Czj4puYBsObFcMduO3jXmb/XYbgbzn8z5s2LBhw4YN298OkY//u1+/C/EM3FEfDTtYOv7ggw/iU58qMwl33XUXPv7xj+Pyyy/HM5/5TPyjf/SP8M//+T/Hl33Zl+Gaa67Bm970Jlx11VV41ateBQD4iq/4Crz85S/H61//erzjHe/Aer3GLbfcgte+9rUHRRwHhF1wfnH6ocqA+KbmyMsp5g81Fh9WZflKyiJh7jxbQTuwkQc8Dii3PtIsUX9JzlEZsak5HTgnoAQKo1I+Y7PZsYTtfaW8AtjJycGTl5IX8FxFGrc8xijgeKuftgZDy4AbIYBjFJFnBK9WBbAD5fwlU1AtIFvBaguyZ+B6lc9NIhVHyGWWxkt9tAVkQ3Nka4RxAdjKYvf8c4tEHHn8UH5nHGD9VwUpc6fOxtO+vxFyMiU3EZG0qwimU/f3nUj8w5XZ5Zphr54JdmED6wyLIm6ScfXJXuc6IWYwbdHFnVxcfbOn0+KHvcmgW4F22DSRxlUurpM0CrL95E5rlrqLQCFkqfiU12xrAouE3KsZZuqHPVhtA9uJrI65cLBMeMjUZe4zljoSpV5+dwjIYFuuk1JAhEiWQ5ZiMwCkAISEDUL5XYADfckxt1QDRQ2bvsvn2FsdcK0Gknm7BtmAAGXsDzB9OypJOBMSRD7ORT6uEcjLPUQCDq78r/O1k7Wz2pcflKqPKFnU8QkSNZ21fan0n0jjl/rLR1gHsFh32LBhw4YNG7bd9pWP3//wGh++6z688Ev2zL/9KNrBQPsjH/kIXvziF9u++k7ffPPNeOc734l//I//MR566CF87/d+L+6//3686EUvwu23345LLimh23/mZ34Gt9xyC17ykpcghIBXv/rVePvb335w4+vIvGgi+Sqem0ca3ycy7B7fpWd2ToO4FJxp0iXFSy0IqxlNduc266a+Z+JmUnQF0kANpqv29kGxZxrZA2ggA+5pAjNnINhe71CrFbezfQ+c7DV7eXhz3Jf35eJ5m9qmIx8nULlGZ0ZGi1hxLrvyA8F1u+9vWSZqZI8V1EEmTwTgBe0ozBugHaaYRVjXopQQRjbCwGQrG9eAbCFiLik3ubioKEwergC6yML3CpanSLZN5wXYPnek4z4YGsSvxwKjtV2/B1byE2X6TrpSfszLzH8f7req2ifxMWbb1rRd+nsXxMe55CGbS56tjrZhh7XRxj149iD7XFuVQquVjoPOqezK+19PDaheqkv2gocNGzZs2LBh58uuu+ZyXPa4I9z/l+udde/9i0cuQIvO3g4G2jfccMOynBMAEeGHf/iH8cM//MOLdS6//HL87M/+7KG3nlnOa5ollxbBNwmLLcHPzBcywYKgFSYb9gFKng3sPZ4HqkuL1StfzgQ2VrtitrkGS8QKCGmGH0obha1GATCAsIySDztHfWbJZ5yZRGKfRgkIMTl224GcWIByAUIOgFtgKi1PJiPX89gmAaScqNQ5JCJvA4xnbHZAkYwTTC4OALzCLDAaAzkYmpRBZOMmFyeAppQZbQAU2HL9+kaxvkCNVg22wFgMEoCeJ04seJmhqgZsdyZU/PuujmldYVH1nrnfpYJM2ihjmvuQyuSBXsjfV4B6rYJowHQkhA2szFjsDSRfNlfB0IzFjshy8QjQRvJlJ/HB3iSQjjOfn91Lx6vAeh1QLdJxCgGYJpQAaBJpXNnsJnWXjqeaze7NqvSNIO8XKG4ccBMPJJMLgYDocmoneS9ADjoXsgwipYAQOMe0SwQg5KBiAvRan2LmzMDWLDYhuN9lz3Tvay2wBpbZbWWye+WHWAbS7Lb1niEHiWNCQEAkzpHHOeXc4Mg+296nOrl9n1sbkMBoyGnPTM4uv7lVTm3rrwzAPTBvg7t5NvtMn3/YsGHDhg0blm0KhJu/+ln4sTt3+2A/7QknL0CLzt6ORdTxJYvi76jS8TonsEQYByzQk6bZ8XLxmczXfyg5YL0U/Gh2vGPEXDNn/lr5y9IBKQ+KmnYABogUFBk4Up/QyJlZZAFBka3cZK5SZj7ZufOKvNv7bXv/bKkH883msgaK1FcbGkJmtVlYo1Z63ppFhHavogJHsOMGvB2gLseApJHEp3KubsMijQvIFv9rW5DBMgXXTpVWG6B2CFrb2QBwqVzI6SVgvY8159mEjQJuQo4+7uTsGmXcg0gd3n68mv8wHLhW328dW5V0XB5/wxXontb5Yad1jjCeAbim8dL0XbrEPPYksjjFVAHuKqheax5kE2WQPSm4FmAt0nHYWKEspzcf7k4Xb8FIHq/m9ylgWyc9pI4BbekrlgjjiNmPv0yKFP9sH4E8Y/KYo26nUCLEpwCmDLBXIcn5InkGKjAOZOBtjRVrA3+pbWeyaxbbfJMbAH62VqKUByROddRzAbiJ83s/QjSAnjhg0hnHxjT6uI+wPiEhImBCwkbil+c823nGJLjgen6igzlfo5WSV/86VD01bNiwYcOGDTsju+6apwLYI9jZMfl3+5hJ+pnJPP9BuM9JZ/iWtoDqbeZBeRvcqv5iq5cei17lwzb/an8PlgUClLWeK/OSbweuW39q2uYn20YWF2BkPtv7RBzvWBUZ2oAsoKx/z5/WA3MD6HrcfJS5ulYlEVfA5F5QOcblnJ75+7blh9iuccXNWrf1sTJeKL7VFkU8LyVomqbronkQr+hSeZlkvAXceUInyH5wEzlVTACVi2tcAGmfKZ39JM6SeRm4mzQgv++3Z9Jxv1/GTYkD0NyundRY2J9F6W//TrWu//uWib12rkkl5Lrtu0Q3W2ZZ8zfXLjTz4FyV73Vv6dVt9oukfdknuw0Qdq6s9XuOjm0HUDHXrS1FEddjS5MPQAmKNmzYsGHDhg27MPa5B0/tVe/OT96zu9JFYMea0e6ZfbCyzw+sDBLQZ7HLUrHVKGXthzMJmO3KezumrHbr26kf/h4X1A9U39uz2CoX99thwwgbKY9lO8RkTLamTyrstnz1GygSdhGoo0BrJGjnV6uAWtlsTgwKWSaeA4Tl87gF8PI83e4ycKvI17HSGtDMApuhYqxBmc32xzUquObGLgHQOLPZUwIICCG3PWM2Nuk3QCIBzy+MhM1mfYEOrClwI9neKRP377kaL9vrslzPmHKU+1o7mu6sruvHsUrF2QFrhsjCYYw1vDuClIVNHlM67rJMXKXjbHJxJMmTnSBsdnQuBTpJw/OJGcpyYWOxgZrJduw1BwJWUwmCJrmzWf20A80nYzr91e0rV8bCWOvampiyX7wJHkQyTimPF4oAJxkzUVh2BpJIxYkIKTCQsmR5DWAKkkYu5H5JccqMNmDycSCDQhWnBLCle6c9gWLLxNZ5s/vb23yrz8SSSAMSExJpDu/MSfvUY6AMtidKJh/PoRcZPse3Nw2gFohh8nMuQdGC3DvYH5U7T5QEQV5dEpcSZbwHFB82bNiwYcPOjT39SZfsrgTgFz/+x8cin/axB9ptALT6YAHXCr7LsV0XJgfAaQa4vR0a4MpYPbIiu24l7XXnGcBXZtDLxZMAHC5gB7qtDOOGjT00/+vIIAPNcNsOWC/JvdVHu3o+YbMVbGMqft0Lab2Iue5SBxrZlgZwN8DbZOXKUFbb3AD0ArBBELl47nAiRgi5NQq2C0JWsI35OGvNv1dDvp16i5MyC9d14zc3TQdNtwnd870Lqh9TBq4tz3XZRiqycIrqiy2Mtk7kbLJMHIwcVTzqWEs25jSavffLNrVE1c521qEB2EAB2eKXbQHQxDfbfLVDZrQt8Jm6J3jZf8dakN17J9Wkma7lcUjmBlRdYHLylEXn0PgRKU/8ZOk4clyJIOOHKXeTtFX9tjepRMRmaZiXkHuQvI2xVeuB5LZsBsQXgHWvfBcrnEAgpqqepfxSiTio+GgLEM8+1H3ZuDcF5FV7uEjDJ2qijrP4i1MSv28B24D9DY4AacOGDRs2bNi5t+uuuRxPefwR/vzh7QHR/uyh08ci8vhjRjq+L3NTTthybAlML3x0m7x5n+t3AHTrdz1Pz+UXbradZNeiPnMB4C5XtjKLmbGufbLLdgOqfbkH4mrenxaowbf5dSerW44t9M9St2kfu6XqczvOlWChnCOgpLoGlzUwf7EXwppxNWuCn1mYndvOPJRFZePk5OKV/LuRgoelY8JOa+TxEL1MvAblsDEnz2TrzphqzQNuLwH3i1pPFt4u1j0OUDfd6N0TZu/ErXsqAF+nGj6d47aYciAPUDawLWuGSbT9kv9si0TcLufk3V5Cfi6Wtg1o7tfun88c0ruuu8Ri72NLkwAl/3f9Q9WTkw+4PWzYsGHDhp0bmwLhm573jL3q3vGJu89za87ejj2jTcQg+ficya7JpWLaZb2PawXC3Kln9yhloj4Eg6BRxO0cAnyqrbaxPg1Uvn+pW7VFA5pxLRdXFjv7zgr7uEml7kYkuhVz7bfZgHAlF2+k4xwTJLrcjKVmB6w5BVBIYBbpbMqRoShxZpW3vYo2yFgFrkte7QKuHcgW5tqz25pHG8Jca/AzUBP8rGC0xYmbJTabZayZP8DWByzremw1jPXSeQtls3HajGVAJnHQn9AxxlrHj2O3VSJeR7gvLHblprAucnEdd5nFFgVFbOTiHaPZHzNgUcV9sDPAcmZj8nmztZwsGFoeIxoQrXN593dcvZumjxmwv3tiiUzvAHWV+oyQfeIh4yuKykbl7LKdKEcgjxFgZgTJn03EloYqghAImEQ6nqPbZ/Ng1APB3XxvbV3f6wOvoaZX8pHT97m3rUnyaRNLYDQCKCAiSMTwHDRtgoBtShLUrG8aeTwKSz1xDoxWRx3Pa72MRie3fN8oKgFTE/A8SNqwYcOGDRs27Mzsxq94Ot75wT/YWe84yMePPdDe17JL3g4QZB/WFe1VM1ltXbtBqb4PSJp59i0AfQAWrMqCmrEwh5K6S1lsJPGN9TJxx2JXknEPpAFjq8mzj36pIkFz8c9uGW7VV6u1ga7kGjPJeNtdS69JQbfb5nat5xNbWXuOstkmERfpeA9gd90SDjX3PvvHF0D2ljE3A4KdseP31WXBVBRum1x6OC1XiTh0W8adl4tXbgoyrswnOzqQnVKZ1NExsC3I3iw3GgrIbphrA94mJZcyHRNKeDofbZ2o6Vmv/9th0SqHdULOA2+Tkbf9DgCJzF+bZZuCbFNO+UVSOQKARCBPYNsOyIHCdMwqGIw8y16/05aG5qEstQfUvV/bfUF3dQ6oYq3VlztywBFF89fe1yZKWHOOOO6jj+dj+WUlSQOW25ssinuV6ksGgYLspd+PYcOGDRs2bNj+du2znoInrBgPbbZ/gxwH+fixBtpBQJJ+EJUPnYx2iV3AKrWGOd5mW7+ZqNnmhf0W8GBe3isz5pEL2Km2NV+2ge4CchTAGKMNFJDN3i+7BtPkQfcsnZfWT31g5CXjnD9WOQXQlBk6EmBOdlzXuz/kKyBtHdRsU1vGFbhmQ0KuygKoXmazqVrvZQugt2xT2fbndLa7dVog2AHbdYR6dFhsN4ETm3Kr6+TiIhP3Ezwa0d7cFGIqsQg6sxTdSOPKWAOwHOxAKTMgndfcyMbZb4e6vHI9ONB2YacKdLv+ZwmUluMxqLKDQOD858Ikk2AiHwdn32Px1yYi6xL1Dw7EOTAa5+dSX2EP9rwdwiT3bN+xrvf1QFS7gzAH2Lw4I7mtndKZ5Fnk7Kftg6L1bKIMnm0fSQKuZSA95VZCcwu2ftxqPtWX7qczmNgYNmzYsGHDhvVtCoRrn8b41bt3/3e94xN3D6B9viyD7AyiAvJHXQj5Q4g5IHH+CKUgXDb7Dzya01LetnwDmkRcIk+Tli2AeA+CluSouYyLv2cqdbzfawWuLeq4gGqGMYnEADbJmGva9OXgBq49uy3RxXWbDYBHA9ucNa6wnNoAZsHRtEzrtGw5UPvmdvq5yj9uHeaPo4BwD6Zsm2sg3t2v79+miWOG5WRX4LzIcG8ZTxWzLHUr9rkFza5sdry5f3XtZrsLriWYGVCDa/W/VnbbuymUVF8yBjepBOfbdCZ4dFJHFRTeDUE7F8jA2fKvS/9NBRTVPtuNXFzYbJ4EVEukcWOvNdr4pMAbFZutr8sk4Y2pkqQqE3cUco9S9bkCasFuGrQwUe5T1mMapA8AI4ADIwibqsCVBNipuwWHhBQnFwgtg2uVles5aiodXwLc58qv2ntJkwOngYqOqAXbS+y2Aurs9523gwRGg0QfjxLqPZELmMYq/d7WziZYnAJq5N+FEnW85NRW+biephHIVyFhk0L17LzQz8OGDRs2bNiw/e25lzN+dQ8X7ItdPn6sg6H5iLokgLeyJSlfW/EM3s1WaXPdhPojHGW7MNRcM4ZVoDMu7HX0ZfNtA9kqFVcg7NhsD3YXZeLeJ9tAUUKP0eZFxIk58OZUg5az1mN3zLOWM5Zb17slnqULHJXuAkPpfgG/ZbvXpPkN5iC7wvw8X+y4u0/FUjMsAFk/kJ4fVygg0AKdsdsGeix2NS7dfukwB049m73Pu17yywZK0DMta9jttowdm+26/CDrgeyt1r6X2eQHNYAcIAmElhUCIh2XcafrZGVSjiwPjylgHjQN2BXIbCl4WS8Q2z6Lv75eZ187E6AfO/+20oE/4hrsTLd9uW03f9Dt/xutP+Tiw4YNGzZs2Lm1L7mU8ZTHH+2sp/Lxi9WOP6MdcniaxMKeSAAuFl9JhgS+QmaSKjabHDja4ztNmezSAFn8d1YDnjzANrJFmeumXPNyF+Dk9zUYlZaVNF3KaOdrlW3PaM9Y7NZHu2WxvVS8kY0X3+wCpDn5TpDrKcjxAD8VGXl+5t39XlnDRO5jFm3cn+9ltkJPZoDAdlybXlLIwQGmLQ3ogGI/4VKB7BZcoynz5foIvetiDrjnjHaRiOec2OV4kCTMpACblYllKzMA71UVAqireABa5tdV/3Reus5EtoRkA7B5cjJylZArm00ub7YwxkW5IO/TfLeXgySeFW7iepllEIjSrkg5/zYjp5qL2i6RRwdGouwZTPIbl93WfQo6VeqQSJr1GctxKai6c8l6av4l89fpuVto2Zn4ZJf2KHjPgc6i+wHWwGhHiFVO7dy2Pqut+cV9nvH2uK0J2KBEGW9TfeVnZEkDVtKsnemzDhs2bNiwYcOKBQK+6XnP2Cso2r1/8cgFaNGZ2bEH2rpMIvdDCplIMwk5AGYkJUEEL2bNOQrw3nkzt26Y0hkAl/sU1hoVuDYmW+uphFfAjG6bFFzBigFtBUICriXYlEURV6mu+lrLNrltK98GroFyXMGx+GuzL9/yhc4py4fVT7u6f8YPZwdsmvfQ215uXK6oI0A8DaoLFOYOdTomYYQ9SzkD2IrvK+BFZWLFuQdUzKd/vAaEt4z3kmS8BDvjGdhrZeGa3guA89eeA+w8SeOOS2yA/Cwy8QOU6OLQcdss9nCdlxQ6x7zftfpri3ScNY+2SsOdbNyijU9FRq4gu2f15AZX5b3xVPll0/wdZN9skYsH5OCFgWQSCtkHO4hfNlORh3OQuZ8kWRWm/DdJDCIqk1RUQHdyzCo1PsWlGxnRP+NZWHIDNT+SMNud+7ouWjRmKnMsnYqesU7uB7f20Y5yfFlC7gH5hOxEP6kEnUvUcZ0g0HXQFypgG8h9vkKOZJ4ouy8NoD1s2LBhw4adG9s3+vjTn3TJBWjNmdnxBtqAsQn5g0iwG7H78CT7UpbvWQtobBc5D99GFYOp1gKihrn2sltlDfW4BTUzmS4yCHf18z1cRPElmbjflnO6DLZaA7KNydb6+1hq6h0iKb4AZqxc5Z/dMNlYaC4vbDdlXZbaH/MYtDk+q7MEspM/3o4rB+49KLeH1P1ynrVBJ3f8cafQKM+1sL2vtSDYRxdvylgjjLdl3eu099nShgZk63rb5A2xe1Vt37k6+h5YtlkmXjhw9V70XEb+sUpMGUCHZM2rfseqKH9sJZWvdOcBzlT27FnsrCZarnMoq62+2AqcvUUmrMhJzgnmo32ItcHRAGHClRVXdptqf/OlOcVALDHvLo7fs2HDhg0bNuy421+/+rIqjE/PCMALnvWUC9amQ+1YA+1A2S97CglU+QsCQRgiDYwGFpklCbsExYjlg83WIivPoJzLR3vLZrcflw0QMXmtABLLT5wKU6iSXgAzcG3rWAC1AW9lseW82XYqwJjctpUrM71FIg6gAGzA2O3qHMCtd3xk6j0U/DvFgU4cbEdAqIAp6/7e7LUuJOOBKpRQtd5LxxOV83RbfWshDGLDblOiSsJNcty2UY712OqtcvL2OPt76P3dWIpzoO1l5OTb4eoV6bcytG7MViy1HivvddFUwh1k3C+wy3VdKoC7ko7ndZGOAxAm24Kg6WsSJpuXolJ02ryEmbaqJXQ8Sh8yQQNl59+TmDeI2KUdQz5J0zerKwPkhyowMCVRzgRrK3NhsTOzrZkXZFw6CbnmeJ4rbw4DwR5IbgPby4HOCmjdxzLohuTRDibhhrHXJGqmAtAnk3mnKi2YmgfZGn08B1OjJr2XXAfs2O2S6kvBdXC/QYPRHjZs2LBhw86N/d9/eP9OtzYG8K/e/7/wfTd+2QVp06F2rIH2FBKmkCy9ivkmMoEF/GUcl792U6Isw0yaX1m/iOXbVqMJA7ZW27Xvzfwx2W8vSHEZxe/aMdc9cK3+zeW4AzeWI3uLL7Ztx60AuwLXbtvOAQBOWyXj3ljBV8r3NiqOOQPWc2Seday3ycaGgmyIP7aBbX3p1mgZNwKwuQu0AWN2FUQLyG6ZZPPL9mDYg2wFuyjH9Tl6QHzGaAPFH9qNuwKa6wmeeoxyDcBjDbLL+HKTPPD3d2NVxnW1vWAsyKyn8uUSQttNdBXAzRMV6bhGGzd5OUpKL+e/vThB1tgZYyX3njSftvY7S/MhfvGBstwYAcBGxqQ+8+SGYtA/UfHRDjkCef7pqv2FVcGjueFLtxXgrY9WRSZfAuHOyn1qED8D26BFMO7waGW7QHm9L/7a0jGRgkQET5YNOzqwvc08W60y8sAawZ0x2R93qBjzIGPa2kwMpDwpMoD2sGHDhg0bdm7s3r84tVe9f/frd+GWr/vSizLy+PGOOk6O0XHsjZYr412YHchXMMqyzeQ4N+tu1QY41ce4Ygu9FFdZwkqO6wCOna8MJUr5IqBpt/2yKOEuLHZ1TPyrDwbZ25jK2b13Vz0n1naRAOkCqMtiZU3dqq0M84etGGF/vw6oblnqmaR8CWS312vOqZQU7nh7b48PZvdsQS/z/F7aKbvY69Zav+sF494PpY8wvu26QA2q0fzd+r/lC/F77N7HrL/9uLAAeSR//2TbSsuzO0/HZBVDwKl66m10ypoI+tj+Z9iLUP5YtWlPsNz6vwfwwRL2YcOGDRs2bFjfnv6kk3vVu//h9UUbefxYM9qBGKuQiqyPCZtUomtFKmpXQD4uE5XAaEEYTf14TcICGdNd8uVui3ZdS3q5MIOMOjVSLwe2SbtRQE3LYlsZO9aSAWMW9VgB1DO5OJf9Xl7sJT/sRYDtfbMPAFvKblNMOb5TkH1jmc/SWkBbLVTJ0xVs5eDzLZBAaY+XhadSpsw1RUKRiJNJhYtcW+qZT37dxhakV0x1ByC32/W4c3U67Hm9rt+bgmYP2POzuvEonVNhERdpfGa1I3EBxcy2PSMeWz9rJxc3v2wXAE0Dn2VpeQbZ7CTlOqnWIzgPJiDJjZ2e6fBy/ewBsvVrzKw2J83tDCBlCXMO4ibnBncuUcVoG7NNALnc28xJmqlScm16noBkiVeR6zYRwzsdoo+6xDy31+hFIW+tyLTn5RrsLKAEPsty8TzAErROwEoGXRSJNygtgt1JfLDNp5sattqComXZeDDZkt92Uc1dYLRcCzufe9iwYcOGDRu2n137rKfgsscd4f6/XO+se8cn7sYLv+SpF6BVh9mxZrQn+ahSwD2FhJUsky2MiXJ03hByqq9AkvLLrQGUD3LPdhliWjCer73Pa5V3WFJvVTmwNyxRmmWRPNgUSz3LhZ2Qozk7NnEWXVxBtoKbFmSzAOsmLzaLpLxisWOSsgSOMYNsPRco4L81+7IPOcqydo2CdvUd751/Jt+p3HlFBiYF5HpZQkIGzLLmdokkszTI6+jOYRSQ7a5DflvqaD2dcKlAP1DJu23cpIXyznaVVssdq2TjXI/FFsAXtpU7ExMFUFcxA/y7SrwfWO1EEe9Jwncu6pddychDAdyW5kvqaaRxF3F853xO8562PxcwY8abPpu9Wx0PqV7nSTnKecw3yCnANnmxcSjbvCHwJoBjAMcM2HO+bUJKASmGPKmYfB7ufKww4LDylun2jLXvijPNl90zdtdKmDPsrfRbAXZ09Xr5wHeZB+ITpSwbb45PoojyQdFKqq86B3e7DBs2bNiwYcPO3qZA+K6vefZedX/x43+MeEie0gtkxxpom0Qc5SPIUn4BlYzcL5DjM59NQvXhfDDZ1YCQrd9cDrRU7KRdC4uM46JMfNexXr3OoKxYbOAwFnsfybi/hjHuW+rte8kd/V0ddyDcFgE9hf0mV09ZaYn+LOUFyJJ5Jczkwu79zmTbTXnb5m0strfeGNpl+2KCtt4ZY4klSbjfbtls56vNXcCdD1vMhR7wPRs7x7/ZPXeAapw49YSfKKpVGWU8moRcxirL+fnnI9crYLoG1tuk5bq/yy6EhPxQMJ3OYABsA8pLUvLQsOfBqQeGDRs2bNiwYWdvt3zdl+EJJ6ed9f7sodMXpXz8WEvHiYBVEDkhZwCkeWUBIKScDzVNkmYmBdkOiEigkD9IwcihYxn2sc76zd9huJ2KMFsDoCoWUWXjCXUOYpWBu3Rd5AGuB9UqF/fW8aU9UzPJ+Mx/uyMV3/c+ymZTcMGYTK/qQHZhVLsf7RWQwk4QVaS6BIAlEBUBgUFJgqLtExjLEBxgjLgDQqTvFijScaCwlALKPcPdY6XrdFz+fk25tsXKuGyn8uwzUM9NfddP/vkqFtbXcfneIc+X9/cYBwE5+JeXj2ueho6EvNzYgew2lZcD3Dy5ei4YmubNLmy2/k23f7jOtj0Oo3+eK2uHLnEpI/lpsXchj40kjxqpHJDLsrivkLZf26BBxwkSp0t+wyY215ccGE1/w8gmFm2SsZrPIJGTw8me5w+rgdT0SCsj30cufibm7xPdD29mu3MO60g5MFrORx4sV/a0kEsbaGTkVOcX1zRfmlMbjGbbP2fKEneUaw0bNmzYsGHDzo1NgfDaa6/Gv/21T++se+9fPHL+G3SgHWtGe0XJWAgvGadGSq4S8hBSlo9TkZGT83PMH+NcAeutQZPab6oZ86fyaEBluFXQMw+WnD92AUHNBVup9RLY2ZvVXvgQbfNj7wuyFyTj7T2LhLyWj1vf2PW2326xGeiwri1gtoXmi8nCM1im2T6cbNyzj3AS4abcrT0A1rbtBbI9aG7qzphSAPPx2OkXf7wF/b7v0APru8dZlde6Zam13B9vQbZew4Nst11SeJUJMs9uq4zc2mH3Xe6H/Gzbj5+Jte+4HjNUjS2VkSNlKXmWlBPgtxPVLg7q9uDdIBiyliWFep+xyHDnbarXBzyvl5hvY6R70cW31z/zf1st+FZGekKSSOP6PyXXC65+KZv3grLbIxjasGHDhg0bdm7txudcuVe9T3/u4fPcksPtWANt/3Hj/edWIWEiB7JNFogCsoUcKZHIFU3oPuaMVfvtd4ZA8IxtifnbVm+blpHO8+unkAFTCMvtcMz2WdsMXHuwSw7kOLDtfaeddJy4BtjwgFvBkVsbsyz3qsA0d9rWa/M+23tarbBoJ2wOv059fqfwbDSzW8doM5a9ZJxcuYLtQHZ8xmD3btO8m+qn4NB+rybsdtRdmlRpJ12clNxUEn7cQo67GAIKshVwq8TcLjuTkWMGuLvhE/YA20WQsz+w7t0DqCXgPTn42QDufUwl44G42tb13F87VcB8WLZv/uZvxlOe8hR867d+66PdlGHDhg0bdgztumsux5WX7o5A/n/95h9cdH7axxpor0LCiWlTluCWKeIoyDLFzHjLegoJ05RAwn5TYIlkzNWHck+ubN+BB+CKfT7YFSSU61MFMipmEChvri3fF2T79tk15aIi+T4j0/MEZJP51HauZxHOAQ3i1gOGbO+EKuK5ruTWLWvYBCvzrCC5gFN+G01Z2AC0yecFLTfmsSxBgllVAa7aIGVNoLKe3267bd3bSrsb9nlxrM0mIdi1gftsdu/Hah/J+NLY1WO7zEnG8z4Km90GQFOpuETq1jWaIGjojZsFgF09yl5/u0vlezyrn4hxQfaqsRORx9xG2O1mrNLGsdubUAKm2RLcdgmYpux2SgVcp4rtnqcN89YGRdvLp3uhPDEtgGkXMI2DBULTuhHZPSgiIArwbtetaRBNZbcnqtlsY7XBlX/2JEx3O7Hrs18M6fjcvu/7vg8/9VM/9Wg3Y9iwYcOGHVObAuHbr3vmznp/8vlHLjo/7WMNtIE5s2AfPJ0PoYk4S8hJA6NB/BZRWGy19oPJf6SfZya7+l5VFg9N2bb9tuxCROhx91iUjftyF4yN2nRRzs441lIDuGtmm2qAY0AnHzMJr4Ifq+OkvR7AV9duwHOHsQQaEL0PYPYTEAug8KxVq/78nkx8F1l3yK/JPmMEwL4B0Jg657pI45VtG1Pte1syawNV+3tZ993KZTrMNvk6lbzcKyyaMa1uDcZq1+B5KWAagGabusHSylzM/g/u6x4aKbx3nS4wP/DHeZsft1ov6Fm/3gDaPbvhhhvwpCc96dFuxrBhw4YNO8b2zMsfv1e9uz//l+e5JYfZsQbaq0Y6rj7b2V87YiXy8RUVf+0sHRcw3vXTdoBbtpcZKz3Hs67+OJV0Qq2ctZXA6jEBCwYi1NTPdIkpRKnPHnDotsi3M8MsUu5As+MIErxMA5kpu63nNG2oIys532xls0Mo15Q65QG43la/9QaUnpVV8nHPLlNnccDZp9nyx3V4zOrO5eJn883dG3Me1J3VBMSB9WfS83Nhh0h7lM2GA9QaAG0ieDVIYbUVgNO8v5oJjyWf9kVlgQf6vnrzW7D427Dw7ko7aAa220mfMtGjgNqD7VKm56qU3KTlusYcbPcY6p7f9tlaWmDK9di2/bjj+NlGHteUXxXAbsB2O5l7HIH2Bz7wAbzyla/EVVddBSLCu9/97lmd2267Dc9+9rNxySWX4Prrr8eHP/zhC9/QYcOGDRv2BW33PXR6r3q/9qnPneeWHGbHOur4KkSsQjR5n//4CpgQiEvU8ZQ/go5SADCBOSGEHEmWEyMFLtF+DQjn71TqfTiHDLD0I5rko57ARpoS3DkQppcZjHyQAmfGKehHthybCMQ5ijBI00kxEBicqHxC+n0FuPqRHADLHR2kPIQs1w4EpBwrFxSACaAYwXY8gFLKjGAKIInszklAMmu4ZDEBz+Qk5wayFdy3x9Qk4jmljB5UYt1VfVJn8YdZ8BDDAl3nMgLg5NGlm+w8yHl6cMY+63X1GgZ6yEAPgIbhrpnKXQCcqT5mY4jlWVnG2C7g22t3B1zOJwakA7kJynemJpGz67Z1LroQeVwDn1kAtBBEMl7ANBOBVy4oWiCwZIGoQHYLtDF/771+1b/V5WfEHEy3AN/fvzNumxvqaLW+0oDXgPzp6cCwTAkQoMz5b4sBi67v2yg/ZhS4fivy+xSQf4GALCHPUcTzNTQyOXBYdPE2Ovkh5yR5zmpff3hdXY32nZgwUQbZmghkW/TxAM7nyh92KzUPlJA4YCJGkmeYdMZDrtAO7+MWDO2hhx7C8573PHz3d383vuVbvmV2/F3vehduvfVWvOMd78D111+Pt73tbXjZy16G3/u938PTn/50AMDzn/98bDab2bnvfe97cdVVV533Zxg2bNiwYY99u/yJu320AeCXP3kvYmJMS8rJC2zHGmgDLmCNaSyzJSoRYJVpYM6QayYd90b5I5WYCtCBgJ4eI9WyWFzKwAJ4XeCi+pr5oxdRy/UkqaCpkOxe+XgG9BDwjXkKpX0sUD5P7xEIiJzBcYxyOzKwXUUhJ//Vf4AowjPoAChxBgTeFpjOMyHRCAou9AJljFS3dQDbjnkW068r4EwzQN1l43uPtO1VdfDpGdsF+O5vJwjO7CIdsN0zgtXzio4ZmPZ/l1vvK9UPZO1r5Yq7dwvs2zb1trUdvbZyfdyGhow/nZzyKe3yMKcMmrkZTFwmoKrfK5GSE9B9mecrfdcuS5Zmy5WpfzYTVmf4f3TqAGsgRx8HBWPIM9gu+TsDGNG9qHYS4bgx2jfddBNuuummxeNvfetb8frXvx7f9V3fBQB4xzvegV/6pV/CT/7kT+INb3gDAODjH//4OWvPqVOncOrUKdt/4IEHAADr9Rrr9fqsr6/XOBfXGjbsYrAxpoc9Fq03rr/oCftB1vv/co0PfupeXH/N5eelbcBhf2/HGmivkEy+BzRsQgACZ0YifzTlR12FlDkJJoSQwBxMPp5BmXzwz5goLmy3fsSbnLvkrUUgcGCRb0se5yCfvYqyYwa2JOw2TQAShM+mwj5xxrGcpBzILBaQmWwB18Zy9mTd7XYIBip4mjKoVuZ6ApA4l8u1jdnGlD+0q5RgTQJ5jTIu97EgaCY/d8HRWlDlGG1lV0mA7KGfrgY8GlDNJi1oaGN3ngc2JOtWwtuC7Bkg39o4OHDjyuR8A63t8R4RvA3gdsoLi83uWUpud62zr6mCY7mCXlNeiPPL3zUp5NN4mZvFlMcNE2QbxmIr880TzHViBr4XzPu+1wd2nVjuYbL12e8DnK+4q9uC8QMmBUq78++A/pFQQu4f5Ak4Qma5bQBZXbL3zwHlXQjglum8cl7DYpvcm3if7j0v1gJwZb935c9uLQPnbJMD1SoNT0zyPyZZlPMSIK2U9dKBHXc7ffo0PvrRj+KNb3yjlYUQcOONN+KDH/zgebnnW97yFvzQD/3QrPy9730vHv/4/fzz9rE77rjjnF1r2LCLwcaYHvZYND+uEwOPnyY8HHd/ebz3f3wIf/bJ8zfx/fDD+6cRO95A20nHPchOIARO2KQJiRgbDgA2AFY4mvJnVZYZMjiUdF8I7D6G2TG6AmqytlI+TmUJGcBlcF2O5+8vQpryxxwHkSgmAZmJRQaarw/9Bm6iP6vcE5pnOwSojNy+zKttMmUjByoqSy1XgJsyL8TTJCBXH5JBIg1nAe8GzBFh4LrHPKtfNmAg23zCJ+fnLRHIzZfcZNhs4A+RHNtY36bLXvasBSbVBTr12NfBDGADyH6wcO8N6IDwfruL/LvanT1CD1/Xx518vAXhzbYFmrOlyMJ9Pm5/7k6wfYB6omKKS+6n+fnbJojIycQVVAdCWukxzKOOAxV49c9Uqw/Yvdu6SRax3E3aAB4wF7BfwDVVIBseZAdXjua8dnvWj/W40W4ku1D5/TE2m2SbuChXVBUD/VuHTNrlG7CsW6m4gutHg9XeZokDovhURwQEgc1RpET7SLkn8VVRpnxCQkIB3IkVXIuGn0WeLmU+Mnm8EBKSC2Sf+9znEGPEFVdcUZVfccUV+N3f/d29r3PjjTfit37rt/DQQw/hr/yVv4L/+B//I174whd2677xjW/ErbfeavsPPPAArr76anz91389Lr300jN7EGfr9Rp33HEHXvrSl+Lo6Oisrzds2KNtY0wPeyza0ri+63H/C2//lf+18/ynXP3l+IYXf8l5a5+qrfaxYw20AcxAdlAHX8ry8Uzu5OO9yLH24ag0omeZvLmPY5ORN9tKmOYAaGyXq/xqafbdXny7IVJy/8HvQY3KuzE/3vXdVR9ZH7VZwY76Y7N+hAeAY5GUA3miwd2DFHxrW5Lb9tam8ur5SbRlwrx54JPL56faoRZw77K24/31l0C2s5m/9a7b0R6gtbpB57q9sl2X2dL2RTuf+MAD60Mk2n7SBsh9YSoSX8+BYvf322WI29svgGy7tPxtaTuWAqC19+ux1+zr7Jos2mfgNOPZg/GeZHw+9vXH6Py9/OMmpVZf70CMiQW8N/JxoPh3e5CtQTmH1fbLv/zLe9c9efIkTp6c++EdHR2dUxBxrq83bNijbWNMD3ssWjuuv++l/wf+f7/xGXz+L+dxQbz93Ec/i//Pjf/HefPTPuRv7VhHHT8ixooyq30yrHEyrHFEeXtFESfDxljvE7I+CjHn0aYcfVzXhEy4FroP4MCZ5VYmSvNtE5AmKZvykiaybb+kFdk6HUmU5CkHaONVyMeDnK8BnlaUIyprXm0f+IlQWD6LuBxc0CiRamue4SkIyybHpmCRwDFNoBDyMgUgTHmZykKytPtEBJryeSSScJqmOnr5pLJxgsnK9XgrHRfGvjCvNeu6m2XdUtyytr0F7jia/X3uLzdrwX9XLuzLlPH0smPPgi5ct21f6a9Sbn3X5O2uzkntteQCh0QFn7VJgHXy21y220XP8ebk4nkJ5e8j+HLU5b4vgfk4c31GiZtI87zcN94IhTmv3mWezOIJtva/EdW7XlyyymZxLDTtmBV1xrMFRTTJOM3GeZXGS+ueY/Og+0wjdNcpwub/vhLTYv7s1lqJ+S6QbHm0natSm/HiuE0sbLOnPe1pmKYJ99xzT1V+zz334Morr3yUWjVs2LBhw75QbQqE7/6aa3bWu5jyaR9roL0KEUeUl5Wk79LlyAD4BicrsF3SfU2hzaedfbXtA1Yl4AKw7UN4Qv74bUG1+6BOCqYNhJPJXXN9t14FWdMMTGDy4BoZcEzkwLMyfM12s/DkAK4HwAqiHXDOYFtA+TRlSfgUKsBdLQrc9XpeMq5LoCx777TN+wdnn2EW0MMzQLC39c5bANiGYRvQ2rvG3t/RHbDdgmt44EXz7V1+u7OAblX7uXqOWpqv/azX2bOfd/1apHqbtoBse8fAHGTrmPVrTedVScTd35QDq9X40uu5Pstyei5BCqv+4sXAaF2W2t83uAk4V9a+X7hjti1uLLOx0ZugQed1NeBZ4wjMJpOaMm4vdgDA3laTHOj0cvP2nH2l6B5gt6m9ACAuDM6E/YC3B90GpEWSbqm8wCX4JrVpvRKOZCL3sWInTpzAC17wAtx5551WllLCnXfeuSj9HjZs2LBhw86nPftpT9ir3r1/8ch5bsl+duyl40D5MJrcl34iArj42nmrPvyIC8j2TpAWkSobAxbwrOdbSf4jOLsH5g9syYRVl+d0Y6zelITKr1IaZrLVfL4ERFuSh/ttlZs7f224+5eOQ2Edu1JynwoMAGKRj2t9u+/spVTr2ne7rl/lA/fBzble77LzQMJ171ENDW2bew29gGZt2TmJ1I3+NbZJ3M/6njv8s8mz1K1ZuqotjeiNJTfhYAoPD1yljp7f88uet8W1ty0/cBx5AF61d1tZdYzrseuf1e1vR7Z8cLsPtfZ3s3d8SaXVstmHWnuOTxt2JinEdpn30563Jcl9g+1P5/j+F8oefPBBfOpTn7L9u+66Cx//+Mdx+eWX45nPfCZuvfVW3Hzzzbj22mtx3XXX4W1vexseeughi0I+bNiwYcOGXUh72hP2S/O1b73zbccaaJ8IG5wMmVGYRZpNQKSAwFxJDFcUkQIhcma1mXM07RAYiSX6eMhf2zxxCSCWyiZL8DJEwQ5yDBKJOhm6Qq4ovuIgCU6mEcKVXdzIYbtBZtAR4QCBgHY5PQOS/MwZuwXZTtImjURes4pMhVEseX4AxJIbm2KU8gCOqq2F+WUT7wGwVSquwLqKQN4s8r60rRRd/2hO7QWGecb67gIlDvxuOy5BjM0KnpZAUnoLxZ0C0BTcmousA9R2Wx0SOi/SHKdys4Zt1Pp1gDNjplO9XcvFHYOLznqHbcvfbdc32bkD3FEmb/yY8+fKxFN7Lw7BMdgETITk1BymCNkSaZxd21rXAc9mz/qB0Phml0Ul4rUMnGqpuNsGUBQwAW5igLtB29rxW/VWe2wJnBuY59L21hb/PmR0e6UP5mu1kiqxD8L3YayNFZan9UzxLst5sGWbcx5tLcceEchngdCatF9BfngTUY507iZDJyrstUUmP2ZRxz/ykY/gxS9+se1rILKbb74Z73znO/Ga17wGf/qnf4of/MEfxN13343nP//5uP3222cB0oYNGzZs2LALYnuSCr/56fvwNV/2tPPblj3sWAPtLOsLOKI4/6AKQGDGGpP41SUcEWEVEjacgXkgFn/tIG7E7sM0CNgLwiYHAJyDg/GkH1sElmDdQTAEJyAwISEDmwQYwE6Qj1c9LoAYKwUCDp3p4yTZ90yb4mfkVF12iDmXpQRMAEdtpoJyWgbcUyiAfJpkO4GmkCMOJ5lRmOQrPnHJ7mXA20k0nW82Kcj2UnYPwhvLTaujYxc/U1k1p80CUW2zJbDtun923JcJAKgAt95bClr2ugvEm1v6exlI7JkB7nrbfNrRHucm6naD7Hv36QXe28cUcHek4jujjTt3iOKjHWaS8QJqyRQmFcCmft9VknlG8cmGm+xoxoCC7a6E28vDdd+BarRlBJnEK+fkm7u2w5X1tuHP43n5tgkm6wRX7M7pzZvlcp4dJ8xZ5uCAuQJwuHpU1eU9QfhhwDUiK3Gm5ln2Sfvl03tpG71k3af4sjKbHDiePto33HBDCXC5YLfccgtuueWWC9SiYcOGDRs2bNk+9+Cpveq984Ofxv/7JV923gKi7WvH2kdbmWz9gPLBafQDSH3sJvcRpMeqb1n/MWlMkKydf7Z9PFfMUfPRbT6kZT9NcGBBtxt/U2XmHHjIDB5KpGUFIHZ/ahhjZDaQSPy7i69rxS63gLd3XK5DVh5gnRQcSFY/7PxS5gHQ2i/4NhhaZxRWsmcDQ1wfn5003+8ygrrtwE3vci2A8+/FN6IFYFaG+tyqfFu7l8wB6X1k0TWjveOcMzDyAN4HPgPKpA2w7IvdsVmEbxnjZZyXv4XS77S9f1FPSrT9WE9C7GrfHN9lfG8AALJKSURBVHRXfvfNb0Jd5n5P9HwF6SiTNHDnVb8F1XV4Vqd7L0KeVOt2itvsgOGq6hbGeh/ArNdtwWgLTC+G9GE6Ceut+G2n2f8YBdkTEgKOF6M9bNiwYcOGHSd7+pMu2ave/Q+vL4qAaMea0T4Z1jhJyk7PpeMTJax5whHH7LMdgBUlpBCx4oBVyCLvEBJCyIwtpxzEDMzgFPJsv34FU86XHZCvlUJOeUWquqZcLwSANgAxgTfI12aIj3Sur2WUCCFCWD/KmJUBihDwIvcVVpeinseZceRMj+rHNMWMb1mZRAWDCSXvM6UChJbk5HpcpOyUNNm19Iml9tKLO1OADdRstkQ8N3DvA7QphpdnY4IEzMp9on3RfofPWLwG8FoZmjJo37pdt+9d3w0AodzfMOOMHSarV+qgZrhDAX7KvrYsbAWOGXmMNVHErTyVfitsrZ7L1SxCdY2ekYjjtU0AqrzdPfMsdkL23RfJODnpeAW0K3rUT+7AxgivwnxCykcaF9qykmTP+pBdX2qUcXZ92zxXS9tCx1gjF7eAiAQfXTz5QIkmI+cCgIMbT9X1eXZf697OBFK3jfrQHnQrg04QlY6sjVnXGBX5XI1XEUKRjvuAkT5QmB6z+TaqA6AtgdXWVDbeMuC983TS9HyZpu0CJOaHTiCy25YfUt+uI4oIxIhhAO1hw4YNGzbsfNl111yOyx53hPv/cr2z7h2fuBsv/JKnXoBWLdvxZrSRQfYRRUxgTOCyLcyDfgBZ5Fjn/0eUxb8l+nj+yDQJeYD7OJWPVvlwLn6YnPdb/8xOiq86QnkBDcmikLtUXw5MVKy3fUC7qOTKIgdJgyTHs/TWpQCbqDDemurLAeF92O2K4Tb2OpRFo5RrvdYXG5jv+/LWOhGx+2w2zwEKsAyytawHyNGAoQ67uFyex9BMZtxlHeVevQkAt23Py3b5artla8u5ZYfaY20/nKl5oKqTAUupvJKboOkBd1VZNGMv/01R+dvSMgW924AnYCC7ZrRhILxitWfAG9X7MmWJe6cegHt1S0nXhUpiXmUwmKUQnC82jkxS7+7TjLt6zPn9+d+H/blpVy+8Yg+4gcP9sglYAOjLUmvvs302tm+qr33uNTmA7QNwmmpKtocNGzZs2LBh58emQPiur3n2XnV/8eN/jHg26WrPgR1roK1MdvHBziDbtgVsl48hXRZAN2WmmdyCwMCUwTQmFFDtwXYvzdcKSKu8XgbbcCnAasCdpjoVmH2ca+7tldZzAaIUbK9CyZ+tQaU8YDYpugfLCmp2gG2VkwefPzsz2D6n9gygB3d9tVbW7owcKzsDlFusceWWi5VjMxmuHu+BZ73OGQLung9uz2qg59YNiF7aNraW59fbm/w7W7C9LdL4EqgGqvHWpqlT14kyBgvQ7UXw9uC6BdJeFXBGhGhz725QtBnYZgPHHpT3wDX84oG0X+waAtCJCzvtzs95uB2wdoy11ic5X3/3PJtd/iS5XrDsl+1/R+HqHTqstgHvfep5S2cxqNUdydJ7OWCtaz22Cnn7sZbea9iwYcOGDbsY7Zav+zI84WQ/M4i3P3vo9KMuHz/m0vENLqEMrD2TcARg7R7tKEREBMQUcCSRYVchioycMHEOkhYhADjlL80IZACQMp3ETk/LCaAJGVgyQALAKQEUs2ScOF+PYi7niYrUN7JtcyQDAqzScK0rcnESR86wyW0gZpDKsxNXknJSCW8gsPrJhmRMI0HAdvIxe1FJyUmjkLdScukTABWA6n7StmDdQHdm03mqAZYBJc/gpnrpMrdLwNkdy9vzj/Oa+Sy0HnG5xhacWMnD7TwdJiKBz+8LBt5bhto/K9A8q4JDVzbf5gpMasPOBGznZvrY6h1TdliZa/HPJk0Pl1ItGZ+x2NrJMi5UWaE55VXJIfnlk0w02cSTA7nVO2/eAfn+iSh/F9o3qUjkEahsA4U1VzWJA75oGXYnHbftFRdwPMHArgFxBb6uO2bb2F3O7TWqa3GZSnVycZtEJNmGgOrA4kKT3Wl2ycX3CXwW2vLmehYvoymHO79XfojlXzneGRAtgBFR5OMaDK2SkAMI+T9D8csmtondSANoDxs2bNiwYefTpkB47bVX49/+2qd31n2082kfb0YbBWQvpYTR4DW5fpp9NAYqH5rBsTnK7OjHqLFGxMZUmWw8cPkQr1jv8qE9Y7yDsNZT/YGenIS8SNHdvtVtgICXmKtk3NhqZNAtDDdX4NYxiYCtjSFXU8Cs2/suvr67/k4TlvZgI4fBl0A2NQtcHVl6Qa/2YbsXJeHbHpub7RYgc3PMA8kOoKb2eu09UADfVnOuCjvN45dWLr6N8VbrjpnSnz5IYHUMTft6zw4U33Sd3HBSona/3z532fadB99OyG+Er1dAdilnmBxc16G9LpeFOovPkuDfkzLXVG+X3zaUfcAx2QX07iMX9+W67buqB7J3mQ9YeWjEcW/7SsZba4F4D/Tr4v+fqHrqXMjdhw0bNmzYsGHb7cbnXLlXvX2Dp50vO9aMNlHChByIxluV2oUn8+NORFlWHiI2HLLsjxJiSJgkGFpgwjRRTmmFHFksM9o5UBqSAlEYuGCmzAYRZQI4yEcqAxYsTUgR0qBkcj4lkuBYXI4zEAKV7ZiDgpWAavKdLtsckIOnTYQQGWhJFSMSCYgJpMHeEEAsldkB6UqD26AsOVcOLgOUDiivUnpV8vLCKnb9lSXgW5FIU/9ztgdse6xh+4jdB2C3VWpQU4W1jKpT5vsOHPf8ritGm+EYa3bBzkp9PacF0otYxren2WbhsOv2+/e8cMn8J1MmRDx73T2hGVfOvcAmhwjZ7cHny/apvVRS3oLspq9tzkTY7DJBwcZkt+ZBfOsK4BntSsrtQbbEbKh9sblK7wUHjmdsdLu9r/VYbWL3HDJp6AKfGZPtmWuLVZEZbb3UpNuOyV4Kepb/jGuArfW0bJb9YWGStL1G3j/3PtBt7mxrm5RrLu1e2zzAPgobxCEdHzZs2LBhw867veBZT0HYAkOADDde8KynXLhGdexYA+1LaI1LQkBAwkSM6NBTRC4/AqqgaUeUsEEG2CdCxGkAEyccTRHByQOZCUQBKTFSIqQggJuBFORLOoqPJjOQCHGS79uIDGYTQCuVrQK0KeCZ5eOfEhA2AFgAedTjJYJ0ilTAll4rzbcBABsAk8jZKYGCRIzesEiZA7BJWYpOgtxZZO/I25hCjhqNDHoUcJWo5B4wLYxwV4enUMoMLLl1CAKyHc0GFGCd3GSFl49374sCapRJ3AFkuuC+ekS2cpWCg8qjswJlcqcvta8B214CDgeoiytAU8cByOoaemNpEG3rI60W3Lmub7a3n+29+Gjj1EYaT1sAEUl+bJGNqwsBQqik42mlEnKIAqQGuO27tL4TIG2ScYvGzuayMW+Te0SVjVObgg8CnnsKEyCJksXyfGu08YmNra6igGujm/sv91uvbAFkAwau83aeyAP1ATYAB7RzZG8Fx5O7Rg9ge3ANt02dsl0gu8TPSLOy1s4l6PZgu92Wu1V19Rl0kveSsEYY0vFhw4YNGzbsgthHP/PnO8WIiXO9RzPy+PGWjlMykJ33S+oXHwFWWQe1/GFXR5DNZFZmbDTntqa4CUHqBGGdfaA0C2xU1uyZrFA+xPWjvEQd1g90V0c+5lMrH/cy8Wrbs31uLQxx3nassYBd74s6Yxr9urVe/X0l4/68UNpV2uHvI+ttBGnFwC5sY0sdWqi7rXx24/3Ns9i25nJsdlzP4eaWCyCalLHdYiVPteybz/CZUKl7WNueNq+6VzwQ5tvS5jJeMX83vUfmdjkwCJq/jxsrvWjy1VgK0pyKUda6NcuMnvR7adHgZ7OlrSuy7yrYWQOytU61roOeeRm5rtuI4b1XsRcrjfra+1pwALe9lrd4Fv/WzM2o+Z9hwdFcG3xZdmHKmS+GDRs2bNiwYefX9vW9vuMTd5/nlmy3Y81o5wA0hCPaAACSsRBAQkBEwBE2CLTKjHaIWIWIBEJiwipEIAEpRGymgJBEJogVEgsIDwnMhBgys61MN7MEZoohY4ko0mjOAcgoUmaKN8rGUmYhLRiaD4yGwl4qSx1hDDrFLB/X7TYXd4gkUnWCYdd8q/whHTm3G6KA1G0AxAxOOVK4ghnSizSEEbey8X2sBdsiE7aGGqhCKWsv4ZhtL8GefdKSK/NstgdM+iwdYL703T/D80r5zqjw0rayphlzbcddDmwdF14uDi139b3vesVa99ouL1nFC2W/nxfbl2u/bX3LvRRevbzUqoLopIvjEMAaCX8KOZq+jzkw1RNLM4UC6v6mxJKXHsZm27tQptue0U06OFm6Tjx4aXhXOm4stVt0f9JJMzZm2wCz3lOBsu7va5UkuykT4GxjWtloYCeLTSgy8ZbFrny15Za7JOJo6gFzkD3zgW58s880AFprGhDNW6Bk/zOAwmRrMLRJ/XKsfrR6AEQhFW17QsJG/hcNGzZs2LBhw86f7et7/XMf+SP8k1c8B1M45EPr3NnBU/8f+MAH8MpXvhJXXXUViAjvfve77dh6vcYP/MAP4LnPfS6e8IQn4KqrrsJ3fud34o//+I+ra9x333143eteh0svvRSXXXYZvud7vgcPPvjgwY1fIeKINpjAOCEfPXWqrxIR9oiiSf1WlAH3iRBxYtrkdYg4udrgKCScWG1wydEGR6uIoynixCpvnzixwdFRxOooYnW0wXQUEU5ETCcSwskIOpmAkxE4kcAnEvgEI12SkE4y4iUJ8STn7ZNAPMmIl/gFUi6L208ngHiSEE8S0gnYEk8Q0hEhHrn1Ckiyb/6tKsfV3NvqL20+0yhr3fbAyOXQthRf+y563hSyTNjfr7kPG8BxoN9F4vZA1cuoW5DZpn6q/G19aqRmsaB2PaayA8wX/byNRaXik9+JGm6y8IQMDn2EbF0aybwP6rX0/JW1bXVA0ra9DLt91s4Pk+XKBmBRx6vn74BtTTWnsnFbKEcbb9LUWV55U3r0QbZNvFR9ym7RPi3b1XPoZdw7N59qrxyZmu1q0aCIbnvikhZQADemeqEVgyZd0gFL77y8H3QdGNOUEELCNCVMq4hpymXVEhJWukwRU2CstHyKmELeVrWQqn1WWh5SlprLdhswzMCzLG0O7bZeGXa1L3cJOqYA/dzIxvX/hZpnrJW19ov+L/HLybDGEUVcEta4JKzPSbuGDRs2bNiwYct23TWX4/InHO2s9+CpDX7ifZ+6AC3q28FA+6GHHsLznvc83HbbbbNjDz/8MD72sY/hTW96Ez72sY/hF37hF/B7v/d7+MZv/Maq3ute9zr8zu/8Du644w685z3vwQc+8AF87/d+78GNV6mel/B56d5EddqvXkTZyucQzj8RkI9HkZOHnJU1hCQLF0m5SjNNUo7ycS0f35VcvN0XqXnJg1uYsUp63krHPRgw0ER9gKngCh2w4nym2/IqqNmh5oH0FjNgveMePWn18jX1JA+i9jiRavB1kHF9CyMZe8DYLeUY95/N5gK4KtvalB7Zvut5LsRkX+tKMJtscTLxUMZs19o+cL7pxZd/QTKuZbO/BTnsx2NnEsIHZJtNyqDZN4k312XQMm7qb1+8zLuUSXO99HtRIo4K8BZ2GTPJeMtgt/mytRxNHdt3L6llsffNmX0hrAe2AVSTBAq8Q7NYTm1Zhg0bNmzYsGHn16ZA+Obnf/Fedf/dr9+FuMuh+zzZwdLxm266CTfddFP32JOf/GTccccdVdlP/MRP4LrrrsMf/MEf4JnPfCY++clP4vbbb8dv/uZv4tprrwUA/PiP/zi+4Ru+AT/6oz+Kq666au+2HNEGR1SAduQAEDAhy8ijaF9zxPEg5+To4wjA6bACEnDJKrMQCTlndQwBibO8PKa8HTnLxhMTNiFLxyMTUgqSOjggxvz1nRKDE7K8PBKQJBd3JAucxZtcNzOXksPXRUgOGyqScsdsZkk3IUT5WE6KB/I1ArJMnFnlxyIHDpSZRgUQAhRIpb1qAnQq/GHTMQciscYXl4ksJHyVO1vb5KS4FTjvAFNN7z2TTlcgxreF92s+u/PZ9cUM1FEXNBeQRxWLXbHx4h5gTDYDXi7eBkCr7uOa1zWLyMZFFdA8npYphCKwBUYz+fg+feUxhf8B8+9dUwD4AGirKcvFJVd2WoUcN2BFjXSc5uOVy1ofJniJePQB0ITJlv6tOqGdeLI4BlRPZjXS9UoWTujGXCgTZDJInXScTE1RgKfv64PmsxQUw19rN7gm1BLxEvSsxK0g1IB4X0l41bxmoC7lydbzW8l4y3JPnfPP1HqMuJalTr5tPVZSSjKOaANN83VJWIt0fADtYcOGDRs27ELYjc+5cq9c2vc/vMaH77rvUQmKdt59tD//+c+DiHDZZZcBAD74wQ/isssuM5ANADfeeCNCCPjQhz6Eb/7mb55d49SpUzh16pTtP/DAAwAy83Ci+qaPiMh+dkcUc1Ac1jzbCQGEoyDlCTgRNvlDLq1wYtogcfbj27AD2iGjzE0KBrTXoWxvooLuhGnqgO4pzEA3JKUXwBl8RzbQHTaUgXhoopUL2AbB0oMFEDjlD09zj2XxBWe5x8QlOnpigHIqJxYGLANJyuw7C+gOyH7bbYTxJdtRx1hJ88lWUINKvm45vTv5m5XRJaYa2MKtqzbpvYEKZG9rKrvj277lm/sSUEnc1Zd8BphbGbhFGudu3RnbjRpgtnjDACgAuAkUA9z6fApWm+exNHG0/PzU3juVtvVPKEDbXAkUZIcSYRwGcAuYNfk21Wx8qw6oJilclHEF2dvGiY5Bc1vwEnG573bf7JIz2yTj5EC2uWNwCaIIFNAN293bKgBrDHQpDw48mw82CmBu03T54GbbwHUbMbzbHmfz1Fx9gJ336+CU7Xm9QGjTwn2nM2CVJ3CemHVt8cfU1D1pgrgnSUBOdWE6muVWHDZs2LBhw4adD7vumstx2eOOcP9f7nbb2jd42rm2g6Xjh9gjjzyCH/iBH8C3f/u349JLLwUA3H333Xj6059e1VutVrj88stx9939yHBvectb8OQnP9mWq6++GkD5AGoleyYll4jkmXXISwC7aORsH3Gh2V6Jv6H65nmfxImKT+JqkqWSlCdMEyOIj6T5TobsP2l+mtT4cKqPp2fFTIZeQEclh/ZApAKXDpxUzC72futbZbte9tuc0y6V77c/X1N6+XvtQhwe6HkQ1W3jwvpcWgvk2omAXnuV1FQA3dbn+vpbgew2m70bLW8eQf21F873IHcmP1d5d2jebRMEz3Ko+zpeubA0jrV6O7nRgG3tp5n8vgeyfT+0rhZo6vk20byse66/vpNw1/Lv6haVHHzXYh1gTLWev7CN/UF2aMp7vtZo2qvW1ve2DWRvrbMHe71XnYUfCh8p3FyRmiXfo/hy19ks5P8Byv+KYcOGDRs2bNj5tykQvutrnr1X3X2Dp51rO2+M9nq9xrd927eBmfGv/tW/OqtrvfGNb8Stt95q+w888ACuvvpqrFQ6Lh9DEQmBM+w+ok1mKBjGaB9BpOPycZ9zbYsUkHIe7hQCNpxZiY3IxgFgw5Ox3Cdc5HIvLbftlCXldlyilceJwMqMx9w2jkGilQuLvMlMJG0IEHY7s2GZKU3IbKcqwTkBgXOkcyTHuCn77UALBQLijo9SY5/lekS19LgF3y1oXwLnCtomQwAG8EqgK4307BhGf30Fp4nBgWa+zyx16vs62tmvW3Nsb/eY3ivlC8yihwuRNYsi7+XiPvBZy8Q2LLYx5C6H9yKDrc/EcyBcvb1GTq6XKyz4lj5oymfuBUB5xypD9/79GhCPJDif5cuuc2dbnmonF7fL6/0tIF5+6SFy42bBOcL4FrbdxlpGuS7gGeXUelNOsZdEGm7p9iyauFsTCgs/AUyMkvoPIheHMdoKrD0bva95YFvmMQrg7UnEe+Day7BbYA2gAtRaz9vZAOCWxfbt8Of5ehMtycj3B7YW6MzJwMv9l6+jcnEg//84IZHFczC0jcnIT1BEGnm0hw0bNmzYsAtm//CGL8Xb7vz9rdltAwEveNZTLlyjnJ0XoK0g+zOf+Qze9773GZsNAFdeeSXuvffeqv5ms8F9992HK6+8snu9kydP4uTJk7PyI0o4qlBgQASEZSBMnBHLRAlHiFgDto0AHHGEprFKlLAiYMOMwCpTnABk3+0VJwPam1BAd6SwFXRvYkBM+RMxhICUcpowolzGgbP/OBOwkQ9/+eZLyN/iiXPaLoqMIEAvQUAFHLhGkbUW1puAwIv40tss7ZP0zVZw3bKUC9e18yq/WBizaayqy/FdrosOe4k5W+lBZ3s+6mOswKSHPP2pS2V+MV94zIDzTCa+RS5egeweK7vLqr8FfU7X5tYf353H8Km9snuBnr84dgJgSlkvEYeOQ0fdTi6NV3Agu8kFr9uzmzoiF2gmKZyPNiQieqUW0CYyF5UFYG4LhZ322yh/R14qrn9XM5/s/PIyyJZznWRcWWwDn8Y6ny3Y7gNsA9ShDnqm7PVK/LEr5tqB60Vf7D0Admu9tFrt9Xog20vGff0eKN5XLr4PyO4d0wwWJ2hjLLaC64BkaxrB0IYNGzZs2LALZh/9zJ9vBdlA9pz96Gf+/LHho60g+/d///fxK7/yK3jqU+uHeuELX4j7778fH/3oR/GCF7wAAPC+970PKSVcf/31B90rR3vNzLSVyYfRmifLg6qycvPV5mAfchMnJBLfbSaskH2fE0ioxxwcJ4GQKANqZYs3PMl1gZgyiCAmIAUgJANxRDlAWd4GiEiCeRFSoPwhzsKIMTIAULaMkSOaM+oP+FTAwEEBlA41Zce3Mddue1FuHpq6C5HIK3mzLt2KLeBdomJ79zgQLLh72dqVU9OWwka7/eTrsmt3aXY1ebBv05TVbs2x3FU9BcJge4b971UAeLkPmfphNhAb+XidRk4nVlxbF9519Xye4U9lu+7f/nNVEnnSMhQQXfle13m0W+l4kYVDALYrd41WyThRKVsC2Uu+zt0+6Zzbk4kvsdieqVaQ7QH2IUHP9rUeaO7t73uPbfX2lXBX0cYXwLf6Y+d7ZlCt9TPoTrYe0vFhw4YNGzbswtm+vtePlo/2wUD7wQcfxKc+VfKR3XXXXfj4xz+Oyy+/HM94xjPwrd/6rfjYxz6G97znPYgxmt/15ZdfjhMnTuArvuIr8PKXvxyvf/3r8Y53vAPr9Rq33HILXvva1x4UcRyA5MomTEKrRUoICEgccAQJekbIkj5sEJGDpCl4vCSsscaEFRJOyUd7ZqozKkzI7DQAbNJUlSUOSLypAqepvHyTAiIX6fhGGO3TmxUSR6QUEMIEZiDGgEhTlpMHAlMAEoMVmTKQCfYMEngS2jbPMBSMuQBMjTll5CkdB0q2fs/qFzxzAUjNsYqpXjq/KSvBp4rfrknE28BoFiCtPJcCKXbt9+Aqk7YCurtga4+PeOnUGbhOeZKFgLzWYHWpEyHebe8rF6/XDkTO+rFu60wBsFw1lwngVrAtIyrvhdw+RkbmJBM/rDJseV8UkGX0xmAHAe5ytcTlfcpxBMmVPYW8EEqE8YY91gaXa7bvQoMFcsk/zpB82b5+3vaxAIr6g4pUffKsOiqZOIuEvCrzQdBcHIWMdLlIxkMT8VuDk1VAu7zkfSfN2nOXWGyLLt6w2ivqMNodybba+Ui5tSwVL/ef3DGfS9vXVTbbb1fXa/6Ipub55vvlegAqFtsHQTuiDY6g2xETEuIA2sOGDRs2bNgFs319r4+Nj/ZHPvIRvPjFL7Z99Z2++eab8c/+2T/Df/kv/wUA8PznP78671d+5Vdwww03AAB+5md+Brfccgte8pKXIISAV7/61Xj7299+cOPblDAmHacEGKMtgWw4I6QjihkkU0JgxlGIQIIxFgmESAV0B0GR08QGsAMIifJ+YbeDbQeasEls/t1EjJgCVlNETAGBigydmZGE/WYOQGADPCwMufe5ZmG3SRhtZcwyW1c+KLeBL287v593MdctU710rrbJ+d+WenWdnYHRjBWmuW+2X58F019NRNhshgI/D+5lDHQYVc9kGwOr5VyWCmQf3NBmv7lGHYkcBsy1bJERt+sTFjU5lVyc6/ftpOMWZV7989U9YHJ5s72ke+F5SPsQOkmh2zmNl9W3CZgtD9bEAdA2aMyAHpPdBiOsjpFM4jjWGsocV0x2Dbx9N+bt/QeBMtj5cfostgJwD7pXlOw+GvQRqH9Pz0YunhZ+fLYGSNsmL98i8951n5ZhPgRk23YDso/UR1tAdg6aputzPyExbNiwYcOGDevbdddcjmc8+RLc/flHFv8DX/b4I1x3zeUXtF1qBwPtG264AbzlA3bbMbXLL78cP/uzP3vorWfWftgk5A+liJwHNUlUpolFNulSfR0BWFOmpxRsqwQ9ICIxYSLMQLcCbAXcCsAD549Zk5aH8sEZlSFnAkJCTCF/9KYADowQWKTk2ceTLJIzcm5tBdEzae5y3/jvewAAe7/VFo3JB7+W98DVEovd+OZWl22LXJRxkxW7qNWeuS6TB/PnJP8IDlCTA5FV66s61Ge1HfCtyuRBiJs6CSWNlwPLrWKA2IHCpt78HWkb+39DO0ExMOsrz3iT9kN7DU9rtxMg2qe6r/JqaJo4mYCYCByb2zuQbam9tIzchIuC7abd5LZz+9kFneOqD2lL380k4zrWNICZgugmsr+x3U5Wnq8HB66137gC3uS3AQew4QCxdlPd5n3BtoJoPUeDnvWihts+5sd6APuQqN+H2AxsVyC6Ab0Ncz2Xnu/PuE8uariVOZDdsthTJQlnA9cqD9co48pka8C0Q4KzDRs2bNiwYcPOzqZAePMrn4P/86c/tljn/ofXuOMTd+PlX/mMC9iybOc9j/b5tBwMLX+tJiaAYmaykb/4o2g6cwC0DYAVAuVcpwmMk2GNxAFrnhACZ79s1MBYwbeCZi1Tifla6m7ShKDbNGEjwdNO0wqbxPKhl5ntjfs4BvLHfkoBnHK6L04ofq+BwIGzDJchEZ0ZFevrQUoLCBvWtGxzH3R7mzHS1AXYFUjq+F5XTKUcL/mT4RhCYRSn8ly9PMqAB7C5npdjZyWAMt0OeTuwXTfQrXuScQXPgAtqRoXFju7+0cnEVUa+j1y8Z735gC2TKz1rh4aC7bxS5Milm8TnWvs1g+x8kBU1SsR3nsj6kiWygQ2nRDWrPYmrgCz67iuw6hpK4Oq9lP6Tvx2dvFDJeEcuPu+7Jqp9E4gtTTou5W9S1h6Az9LuUeOfTYAGRqvY61Azzq10/JDX6kHlUsouS2sYSupC/Q3y0vFViBWo7gHfQywx7X1ezZo7n+iKYXdguGHelXX24Niz85bmsQLkhcluA53pdp22K4NnH/TMRxpXJdQJucZmAO1hw4YNGzbsgtpLn3MlLnv8Ee5/uJ9PmwD80H/9BF76nCsxLcSIOl92rIE2kD+YIuTjjrOftvpYm3RcuO7MPKQMqAmYmIV8dggNgEWzQjB2OzulinGS/cyMW+C0BAmaVj5YV+ITvkkhM96OSWIi+TCGSUw1aFI38ragJJWMb40IraelBeBRMalskc7LiTtAtjHc2lVU1501xF+raYpjNT37WAKjLQDjdt+B6dlxWjjOzbp3jwqIS5OayQvPXvcmN2b7KNfRa59xvuwt1krH3abtFJC9DPp7Y42JstrCt9sUD1xAtguAV0f2ptnEjP0Zcl1m/eMmihRk7yMXr9sAm8SpALKb9GnVFe1x60v9u+z+veoxBdQFXOd9tqr7Wg9kb6szj+JdR/NufbOXwO8209/b9t49CXkPhC+B7ENsSS5epQjrXHMfkD0LeiYgvc6zzUM6PmzYsGHDhj0K9uG77lsE2UD+XvuTzz+CD9913wWPPH6sgfYRJQT/mSrgOcvFCQlBvtxFJiiyv5g12SYhD5SwTisEyvmxFXDr/kRAYDY5+RpTBuAgrAGhUIEkYD/7hGdkEohNVq4fskw1uwUAXkrqn2cRPGIO0nRfv+0rEJJY6nABRmn3R+EMNBt4kn1lqLf5VVe+3bKvEuRWNu7BtmMfDeDYhcrz+TW7Z1Ywyb4fe49s5zRsdmpydRsbTXO/bAuM5sC2D9LlWGz/3qr1rN8Wyg8xLv3WYpyupNyDUCYQcS4Okqs9UJaJywQOT2Rsvwbw8y4IXjo+881v2kmcWfM2FXHFViu4VpUAtMw9nIuSX40lD5I1d3slD6eKsW5l4z2ZeM1mczmGMuznAHsOsg9hj9tAaC2bTUANqhu5+IpiRzruGN6mLT3Qm9yLnNwLi+6PdN9JY3+/XkA0reNBs2ezezL3Hottxwwo15HFW5CtbHWbxqsw2hFHcu0jk5gPRnvYsGHDhg27kHYxRx4/1kB7BcYJSohGgQYkYRUSQo4Ay0Gijucv5vyxtMFprAyUgwMQNkicM2frB10CSSbtXJb0y1m+pSLlAGiRxDc7oARIC5IWjAiBElYANhTkOnPAXb7OlQncgrCBOUhrQGfZ57rcsYPGDC7douePrSDbA2zfzF4ANH/MRXxmuwZqgKegqAXZC2BbXyOYHBATyT27Riw9qwfZ+p2cqAbMuo5UgW4D2bqdYBHIQ6wl4125uE2O7A+0FlOodcyn4/IjqhpdTQRykKTxkneQXRUy2IbkoqZQUtbld16gF0v/+2j15R3TbIxoX2icgvphC9DOfa3jmeu+a/GNA9t2f5OKk0jDCUkk7MlFFs+ScRd93EnFbR/6PJBxyfCAuwXSxTcb9jffguy9fbMdwNb91i/bJOMCslchYSU+xCt3TAF26w+ttsRqexY779Ps3LTt9wtzAN+Ca6CVkXcClVEdaTyD5XKOyccdC60gu40qnrej1TuijfljX0J5pvwSWotfNstELwswz9NMq8FoDxs2bNiwYRfULubI473ETMfK2gfYHRSn/oicqg+42qdv9iHY+RAFUH3oPSrG/e0KtPRAzLZLLoDsbh24OnbMgeLmXG7q1ddwoMzvLzYUDnDNHqILaufnU3W8O4TcdVomfdsER88uFMju1d/Wl/5YdZ4A5IoR7oyHyvwf5r5tbsexEsTav6nuU1NoLPz5+ZRelVG9XbHSbT0dGp1xObtWa3sA6DMF2e2+gW3Uv091buwFSXX1m1jKt0nH9XhPgu7vsW2przd//l0y8tnv8EKk8qX82PnYHNTP7oPm/wOKEsCD7GHDhg0bNmzYhTeNPL7L/vyh0xegNbUda0b7iICJAIivdYmElT+OJnUsZflYMsoOla+2MuGQayTOAdQih/LBJvtnai27U9J76SIHBBzWqAdWNpMeN2CkAiaOjS15mRWcuI/KpLemLN9dANBeLl5Hcm6Ot+e3Ml7ZbllGLxvXwFNdSblvWgNw84nCekofMeurdwPA+raOKF6YcQeoe/myVSKuzHYVAI0dOCxMd29CZB+Qvcvnfef5UlkDjLk/C7uWBUYjTSsH8JSfR9PN6Qv2Ocy1/zLUyAOpwjLON3r2CMyAl4n33q3zw15ksbs+4u6aBJdaLD8XW4A2dJYOm21jsNl299DFIo6jBsaVqwgOA9ltHd+dwV1T64ZmWTWB0FZBZdGpAteH+Ejrb9pE0STjvl0t692zGfD1oN9Ngupzeia7DYambdbI4P763kdbz1mSi2tZTy5+CW2MyT5BCQH5f1AAMAFYHzYPNmzYsGHDhg07S5sC4U2v+Ar8v372/95a7//7S5/Ay77ywgZEO9ZA+wQRjgCA8kcOmBHtY4qhbvEaDC2Xi9ScgDVPdq2gANvQVrYWXAcwGhfSnaYfnNyAay3TdRUE3IOZ1hzgngNNBYHs5MxcgW5Az5vfYCuT3crFewC7+bZumVFjGTWvspS3snFjULUsOEbVLu6e2b02EtkwszyH1gloLoCqn0mjiWv/WP8VWbmXglMTXVxlzgbSnby8Zdb3ZbFnzLKV73V65YGgKbn0se0S1IJumIQcE1dtV9l1nqhx/tquUQz3rEtt1QYwbNKnIpp9X5l0fAFcS32WSbfiHO0mdHzE8VDGVh1xXMdlB3wbkGbHbus21w0pXVm2G8C9ZPuA7lYynsvKeu57XaJ0lwjk5fiRgO4esO2ZycRtP1jdfXy3l5ljB7IdUw7U+a11bYC5kpo76TilRcn4YuAzK0uz6OIqFz8yaTny/x8AE1G1HjZs2LBhw4ZdOHvKE07urPNoBEQ71kBbrXBp5992+R1aPQ7GWs+PtSBbDjTlnt2uQPWS7fpGP4uo1qVJ1C3vyYOXQOJOn+42ZdjZGCtLjwZd1kYM95Ao4LICx2Xfg+dWQj4D1sA5BdlbrSHt20jiqlqo71PX6V2L1W9bAC0FAlLx10ZavnZdUIC7Af/ey7Z+bkC2u/6eauv6ebRNbjzPmGlX15/L7bGlMX2GdgjI7p3XyretHO64AE4PRsu1d4Nsf6z4ZZdMDx4s16B7y/VmMvL+r3kLsltrQbaVVwDebcOn96qji7fRw31EcZWK60TDRGTbQ0I+bNiwYcOGXXi7+/N/eU7rnSs71kD7CJTzaLN+UMoHHfsPo8MguAZWSxxKPm0QIgf7cPS5tKuc2ikz5GsF2chAeyP7Gw6ISc5LATERIlPOoc3CaifKgaRSAX0ta61sacvmmkRcJbYMaBoks3ZfOy41+y5kskm8G7l4FUFcL9+JPs4VwyhlmlcZhSX1snFluKvo0MYqura2QFdYZE7yCAxwkujZTdoowJ9bgp8RUOXLLvmwXT+3ZaIasPN0ewbQ2do9s4U+K2X9ur1jFbhuyi0ftmOSTS4edHKHLY97vgDnAHGQsGkMIHC5XoC5HRCQI5R7S2xjiljeD7goDvxz+ckIB67LZEX7Et112z7UsavKCGGrQTWL3Ys03srGlcHW7bpRdVk1R3IeSE4fAA2oh4Nns6sAaHBsNpUgaCthnltp9jbTDAwAEBEQHHvdMt77WhU1HHPQ38uXreDar3OdArh9vmy97uRl8gKsVXKugDuz2MmiixdGOz/bCQHYEwhBXvJqENrDhg0bNmzYBbf79vS/3rfeubJjDbSJCBMoY1JmJALWh7JcHfO+hS2DHTk4cE0GshVU53VwIHsyYJ2YsEkhg2sF1iIZT0nk5IKTC4gurLYHbe0a8OcU0F2+/Rlbv517wauaCONdkK23boBhj40tgF3OdcB5BrKrY015a26ywdJScU5LhQRQEPY08Zx5VFm4u47J7DW9VyMZ99LxVlJu2831tgLs9nG66oBOX269Rtm2TQGipO0oczlGXpe1j9ouVyE7ksfoRDZWM+NMdm/qPKj5/3NJzeWV3vUDLIDr9rLUXKQJgFaNHZsscsC78c3OwBzVhI5eowqGBlRjdNEOpt1329xfu0jCidp0XrVkXNlsD7IVtB45wL3LArED1LFS7ngAvq+1DHU3ZZePNO4CVhq43sMvW+t5NltBtuXIFr9sOwYNeMY4AptcPAA4oiDXIQQEHJ0LacOwYcOGDRs27CC7/Im7peOH1DtXdqyBtjEJzJiIsN5Dkqsff63v9bbAPcpmx0YOngG3Xo8qxnu2QEA1CsCu/LVZQYt+1aNaiGvABDTf8L2ys7GlCOPtOvTZ13IdPb9eb7tvAdU0BzMdwJMvXNYkkxUKGpWlNvl4a9p37vxWEr5tkqNKoabNbCdBgP6997CZZLm1pXLFpgUjV2DbgqRx6YAKbHtgTlI/FJBskgE092mb55hmzZWt5ylH3junXJiX+85NGJj5QGjWtjJGC3AmLI3P7hhztzwfxkx7Rx8/E7M0XlR8tIE+e7wtk4L+hnoJeSsn33WN5TZyd7sFykANsnt+2b12FFDel597q/y7IRHGSa+TJ3kn6GTDEI1fbMbMWK/XSKm85/V6jdVqhUceeQQxHhptZdiwR9+macLR0dHuisOGfYHZlZful7pr33rnyo410A7QvNe6L5JB+Y6PEGm3LEUKnllpBcq5noLkUANrKV+nyZhsDaK2SZPIxAM2Ih1XifjpuEJCZrC1fJ2ydHwdAzYpIKWAGANSzJ+JnAgcFWRTDszl2VIuLKsBQA181gGGO8G3go+WVvR+q14y3pGLt5HEyzVQXSMf99coDGKR89bMtZfuVoDb7VdyYX31XNhtUozGyOqAFjylUkQRRfYdqWavZQkuAFquy5nZlm82O74FhLfWnXxoJyYIXcC9deLCwG2ZZHBdVbYlPzYg/abnkpvwAduBtJIxCc4B7VLOqZ3PFfguPtyVwjq6neBfWv8hDorIvkSN+4j2vSBnPtheW9aMuXbC53yYxmfYNxK5Z369nNxyZVPJoV0CoCWTix8Jo71NNq7gVH8/g4SDVFA9ub6INAecvTgVvfvY/TrA37ejBdhTw2DP0zY6Vru6dmHC1Tfb1uT8tqlO43UkIPuIQv4fRAVsH41gaI+6nT59Gvfeey8efvjhGZhmZlx55ZX4wz/8Q9B4V8OOqZ08eRJPe9rTcOmllz7aTRk27KIxTfH1J59/ZLHOZY8/wnXXXH4BW3XMgfYkjNoEsmjjuywyFcAtIDv5/QZka91lubj4XDvmepOKdFxZ8CggO6aQ2Wzxy06JDGQjFZBdwHL+4p+BaHTAW68L1Fd2G3mz5FDa+GW338t1PuzCGFZ1gwPtLUOtYHqLbHxRRt4+NzfbnKXiku0tn9tTAFTnKEAu/V/7Ybsyric4aHaNDshu308LhJeM5tutT/aieTbZNWG+7RqjExi+ngOZxDKJkVACo0X3cP7iQNPxmcXW+ksy89a6fRTURaAzgdKMFR1nPfA8K0NzbLFRO5uNrFThpbmEXKXDZB/Cbpc/tSIRBzSKuGOIHWhs6/cY49bm5R0Wl3tByvoy8iVGuQeutf2+bAlk676/h0YZz+ezKy/XND9t8Ew2riB7QlFSKchWNjuAEM7XDMywvezhhx/GH/7hH2KaJjzlKU/B4x73OEzTZKA6pYQHH3wQT3ziExHCUCEMO16mKo3Pf/7z+OxnPwsAeNzjHvcot2rYsIvDpkB48yufg//zpz+2WOf+h9e44xN34+Vf+YwL1q5jDbQBleztJ1GM7iOoZVmWQLbWU4CtLHg+ntlrPV+DniUWxlrPSR6kQ8A2ShA0AdgmHTd/3zra+AzMoS5T636f+24KBE6Nz3YFmtH1y7Z1IxffBrJn17c64ifr7wE4sE31tTwgas6xWwgY0z7RbQOUDmzb6YzKp1onNdQ3e9bv3he7mfyo39UOkL2H+edd2l7qC7snlW1P6DeHyoQD1WW2DjLZQxrwTNYEMHz08RZlt21qQDdjkdFuzY/XbQB4ngcemI0xOCBO8/LZ+Xvcd5t54MwyML3keukcoM9u7/KjrtJ9wftqu6BoqMEogJkUe8kSqALBxnY37TLWe8tvdO9ZWlDfA9nl/BZcs91zKUJ5fe3d/z80X/a8vIDsYY++fe5zn8PR0RGe9axnYZqm2fGUEk6fPo1LLrlkAO1hx9Ie97jH4UlPehL+6I/+CJ/73Odw9dVXP9pNGjbsorGXPudKXPb4I9z/8Lp7nAD80H/9BF76nAuXS/tYA+0wC1kscnGmIhtXabhIvNe8Mtn4midjtFUOvubJPhrXEshsFl38ELl4nLAWFnvTSsaTMNvKZkdZAJMul+jXZW0g0AHBilkFurLb1oc2A68G0AJ9uThQg2wHmPdisQHHElK1nWXitW+2st018+2O6/X00jJRQRBSLQCUCEzCJgqoatyKSzAzRpHqM+rc2LpdvQeeHVeWuwLneo+OGVNcvSOqmNRFgL0ECr1pNznUrBJyQ9Httt0YBopVim8N5nwhIi5jaPEh2a5T8Azb+OT2hXhrv4PdZA8xcmTzbT+UQV64jrMqiv08INqM5a7uvbB9gGngQw+cFWwfIhmv5OK6VnYaZb0KsYk0nmx91EjHfWqsHqMdwHW6Lncsch113J4N1AWni8/VGQdbGW0HrH3gM58vu6rf5szu3c+x4vlaXLVrosxmTyBhs2UiQYOiDbz9qNlms8FDDz2EZzzjGV2QPWzYY8WICE9+8pPx2c9+FpvN5tFuzrBhF419+K77FkE2kL82L3Qu7WMNtPe1KGBbrWWzTR5u7DTZut4OAqQnY7R9Gi+Ti3s2m3OwMy8b11ReRqklFwgNqFhSsMNWHXZ0T3WpO4FE7gvJg+yOmS81zcFEy2Sj3m6vYefYtjvHgDPNgI2Xj/e367b59rf+2lbmmiCkbDFjpmnGXndVBOqXvcBko7l+l9He92O8fU4Hss9UOl7rwefbdbGAPxmEirPNdTvUExeWa7tnqZn88fmxAfRYbU6uLMg5KktYYsFd7IDuJATVx7Yz48vHdhlLP+9zCc9sb5OMb59TmEcbt3JLfVWAeDnGFZjdxmi3ZQq8e8z20jX2sSWgX7WvAdlWrzl3Z8CzJZk8uALiU/75s3Re9TUGM3oxmAKOkycvbETZYcMeDdOAaCOo37Bhxe79i2X/7DOpdy7sMQu0lamugpx1gqApeDZGW4Ke5XMKk73hSYC1k42nqeTITlORi4OafNk5Z3ZiqljsxARO8lEubGoGJOSCngmqSW4bKMBPthet9Z9tjzW2mCtbjwEzVnmJyQYcQPQg0TPVDkRX16PeNlXXqphye4ACehnCUocS17rtM2Oy4dhqD55b/2yVhDdB6vRYYX4B/w2v9/WMcut3zE2fteses70TDJK7d9tVri2e3bZ2sU5U5D40QK0B5FwbTJYeAGz7v29purhfDtjYIQHUTPK3sQ3PLABv7owbzPqzM5a32a6/O+vYhcM288HWnN5x6oDvdj3zy/asdsViFwl5K6n2IHYbqz1/kPkLCRRnKREPtZ3Mdgdk19uFzS7X7D9PZuPnx+IBzxA5DbB9EdkIcjbsC8F0nPMeQUOHDftCsac/ab+I4vvWOxf2mALaCSXNViUZV4CtDLRIxddpZb7YFrQMWd4NqHRcgLhIwRMIp0QinphmcnEAJhdXoL2JwUB2LRkHOIYsFxe0QhoQLSH7aDdycd2uWG80240p2FB/WlLw0dZvAbZs75SL+6ji/vwKPFMFsk2629SfBUZz9SsgNEMneSHoxEVhXimLm+WaHvGi9sNW8AzU0vFWuu9l5Ha8sNx2DdbG+C6mOcDtgMAeyJ6V6aNv+bDMuaub+8E9s5Rxc0zXrM+h4xKc30WSnNg99rWiubmw2bossNsFLMu1hcUmojxGZNJkp0+39RlVfdcuaJdt5iZmDvmssfR98gJ6gdEYtcpml/81OYDuc2dPwflhE1uk8RUlHIXo/LS5ko4vBRfbZW0dDSp5rkW7c5aaq/KKefb+5i6SOLBfSq8IsvmcvD1/FxE8Y7WHDRs2bNiwYY+uaeTxuz//SPdbjQBc+eRLLmjk8WM9DZ/koymCt34++bRe/evUEvF8zTromTHV7oO4ko03cnPNkZ04l2XMVdCpycdlv5WLAy2g9siqj2/02E7r+Dh3vxtdGi+7/E6QMz9es+T1NbYx2q08ugXZLeCsmtFOQjQ3rP3ZUfWpZ71riTjP3w1QpORSXqTknZfBvPzuug+CxT5hZXu3gMbKn73pw17f53Pq8lk9wECsXT/Q4rsojemw2C3g9vtLf9QLM/hb2WgPvKtzLjxg0r993tpg7Dy+ZG3kcV++FF18G8huo2/3fJv1PL+crbXX8fduQbYy9f45z9SSY+pnQTPP+KrDhg0bNmzYsPNpGnl8G0R68yufc8ECoQGPAUY7CdyOzIicQbPmxS5sdgHIESVvtmezffoulZErk+23NfCZysU9qN6ID3YUJlvTeBnoTnlhphJp3BjsArZJmGzL8cwtsHMd0IJuA0eZbWRCTr9ELJHHKbPaWpEA7/PqpeLboosvycUrMOxBXXDXqEBe2V9mcqkLNFuA2LKOlF9cvndLhPq+dCqBVj0wA9tOLt7z587HuVxb342fHNA2zsCrY1xDXQZX1k5ceGNyTLWW2YQOkKOFwzrIy8StzVLXy8etHXKD6kesAfZb03W17DZQUtDpD1+PxZbbcPvAjdnkA+b91mvvknn3g2rChppt9tvyN6wDUPuK802JeOaDrft+mLTRyLPfdd5u/aupWa+UtYYEQ/M+2k4yrjLxat1hiPO9ej7TxVJHQg4AUydA2iGS7F5beu3ZBeoTAgJS/h+gEm8GIAHREoLtBw6YKFbpyPL/CVTjJoIR2KVPk7RmsZPebNiwYcOGDRv2hWnHGmivOWLFArIh0nG4KOHwftgqDy+LpvHyLLRnsr1c3G9nX+wcdVzB9YZD45dNBroVXKdEYKlvAdBEIl4AttsGuiAQwBxgOzOwBWSwolJcAjABFIEKKvnUXcAMYOdrktvGmcnFNaWXgcn58RZst3V8myprQbSCxLSlDuo6Fbj26zbKuEnIud7nUgbU78cDKW5QPzeTCX6poq27lGtLEvpKAt7cnLgB3a2sHM25up3KPkmbKLmJAnbtWbKuhJzLMaDEEnBKin3Ade9w255KMi7nLLbZ9YdJxf140Srsusu/a57jcSsnfQc1cmsDoPVSf3m/bELtn11AdpGHlwjjyYHu4q/dguyWLQb6QLe1HqAG+qB6HwmVB+5LILrX1rzfb68H25pHPNlADvZSjyiafFzbH0D5T4BVPSXnU3L+6Kqa2t1fw4ZdDPb7v//7+LEf+zG8733vw2c+8xnEGPG0pz0Nz3jGM3D99dfjxS9+MV796lc/2s0cNmzYsL0tJsYP/ddPLB4nXPj0XsdaOr5kh7Im3hRM236z3UoJuZGPM2q5oQIbjTLOKLii/vJHYcdmQIn6AGiHVbJYD4KB/MVfHV/us1bqPbM9fGZ3SXRbkD1rr7vW/Fy/I9Xa/vL9ujBZUUnI3bFWGj5rkp3D9f5Se3ZYLQ9H3X9NH3Gz6Dm999SbCNkWxb2u69bNtXa9216quQpk9yTks8afGYDpRtBfrNwZN84OkvwfaPY7ccA5bUovoMmbDTZQqceUzVaZuGeyc53Cai+xyftKxPeVnG+7x9J152XLwc7mZeQCXtbH2wlZ/V9S1hlst5YW7j9s2MVov/ALv4DnPve5uO2223Dvvffia77ma/DqV78aX/VVX4XPfvazuO222/AP/sE/eLSbeZDdcMMNICK8//3vf7SbMmzYsEfJPnzXffiTzy9HFGeU9F4Xyo41o73hhDUIa2Qy7LTkuPYRx1UWbmt4WTlVsnGLRi4fvZqeK9+rSMs3Lr+2gmx2IHsuGQ9NSi/BDQsLtdv7mAdCDRDLAbgynUZg8EQO/HgQTW3RnMkG9oou7oOdVXLxAGO/fR7jPoCk+riTU5cGdrqCC1+ozKNnXrsguNP3ntluWe6W/fb5syk1jWKIpFpu2QHSFWtfPTPN3m0LmJfMmFj3nD2ZOM8mcjzoLf3CEEaWyrU4AEpoMpVx5SXkvrxuYNtPbj9xmQZMVE8Jer9wPZWkfFvftOO4urerJn+fhLIGN/3pOiGvuBwj7VNx0WASBQk1j8zGcPdk5VXTnUR8akC1ycaFtV6FWEUaX4WYATaKrFx9t+f5p8u22pmkyIoLc7j7SM7z+f2BvQTWIwImJFMC6P0npAK2q9+NBC8jjyBMCPIsAREpt4ED1mAciR/PBMaaGYnkGtWzMdZDOj7sIrd77rkHN998M06dOoXv//7vxz//5/8cl1xSR+D96Ec/ip//+Z9/lFo4bNiwYWdmI73XObaI7JedfbOLf3YbcVzNcmF3gt0o2C7lKisP7tzdyzwAGgxkl/0CuAuQIfto7wHvqryxnkxWwZpF3g75w5+JQBoxGu56Lbh2ZR5gV/vU7pdzW6l3AZTUBdSVXLwBnx6Ut8/b/RxXkCTHe+DSzm+l+W2k8ab/vUS8gHB28nPuvqOqQdpMPzHhnz8sgO6m35Y7oPQD3MSCTe4oRnRtq2TuTl5uaFPBdiptqJ5NI40rEAcktVyvXVxvt4Bbc2XvSukFGW89Rr2S2bs6TVXiHLHAntcu3NQVcG2QuW12tU1VAbO4gYi/tm/utpTgPdA9y4EdNMJ4kYZrpPEgkvEJCSupp2z25JjrpRRZ7T0PseBefKsCKg/YL04c9ma/++cX2X0F+P0lSedyBHAzAEpY8woRpT+iRC1fIyAxY0KUjIn6I6MB2AgREevBbH9BWkyMD991H+79i0fw9CfliLYXMtjOIfae97wHDz74IK666ir86I/+aLfOC17wArzgBS+4wC0bNmzYsLOzizG917GWjmef7OKb3YJsNS8V9BYdiC7XpBnTsvSh6KMCK8heqlPk4m45x1YxnWotgIUD0u54ucYCyG6tA7L7beqD6BZQt0ztkvR5xpw3z1Y1cQFca1nLbC+am/Co6nPnOg6kG1gH+oyuPRfNgHQBiOVZe6qFVjpe9UUPlHeukdvQr7eTFT4f35JnIhM/l9HDO++5exzN2Gq3Fwj7XtTxbRHGA9VgV5nteb3CVAOoZON5P6GOQr5PCq/mGsKMLy1L1/CR0HvXOtfmM0GoRU3zKAonQKXiXs0UpC4Zq54s9aMG0fTX5Oy3zXkZOW2/8Oz23/4TvOhH3odv/ze/ge/7vz6Ob/83v4EX/cj7cPtv/8mj3bSu3XPPPQCAL/qiLzrovGc/+9kgInz605/Gf/7P/xkvetGLcOmll+JJT3oSbrjhBvy3//bftp7/8z//83j5y1+OL/qiL8KJEyfwxV/8xfiO7/gOfOITy/6Uf/7nf44f/uEfxrXXXosnP/nJeNzjHoe/+lf/Kr7t274N//2//3cAwPvf/34QEX71V38VAPDiF78YRGTLO9/5TgDApz/9aRARnv3sZyPGiLe+9a3463/9r+OJT3xilXtdz1uyJYm6L/+N3/gNvOIVr8BTn/pUPOlJT8LXfu3X4n/8j/9hdW+//Xa85CUvwVOe8hQ88YlPxEtf+lJ87GMf29p/w4YN222a3msRugB4xkjvtb89woxTXCTjKhvXQGgJAae5ZHVtI8luM5WNz9N2heojrgXYXkZe+WcDczRoLDbtD7wrUIwZcFIJbWZFffonAk+y6LHOUrHIBP3KN7m4SXQxB2YGGCfZ97LnQPARxn37eiy2b8cM+OniWN+6X8syk3u7st7xVkLu82MXRptL7mxhtinKdizl1T2qd7iQNzzA2GwOBAQgTbI/5SVNZZsnOWepzF0vNfv1vXYtVLa1zXDjwAdso/KefZ194wHsNDf2qr4DLIhfNZ56l/ATMAzzwfe++a2ffhkTXnVC7ljZ9n/LmhFu9ltgx1s5efu4bOsp5LzYKhWfKDPVq2odLW/2iiKOKGIVEo4oVgHQVCau6yOKOKINJiTZzsuEhBO0scUz4r3F1z0h1/PLETVB2eT5POA+JD2YnxStgLQsa54Wl0fSEU7zCmteYc0TTms5H0nZCo+kIzzCRziN/P/lEZ7wCBNOcf7/U5Zky7AvHLv9t/8E//CnPzbzCbz784/gH/70xy5KsP3MZz4TAPDbv/3buPPOOw8+/+1vfzu+5Vu+BadOncLf/tt/G895znPwq7/6q3jFK16BH//xH5/V32w2eM1rXoO/83f+Dt7//vfjy7/8y/GqV70KX/RFX4Sf+ZmfwbXXXovbb799dt5v/dZv4bnPfS7e/OY341Of+hRe9KIX4Zu+6Ztw5ZVX4j3veQ9+5Ed+BABw5ZVX4uabb8YVV1wBAHjZy16Gm2++2ZYv/dIvra7LzPiWb/kWvPGNb8RTn/pUfOM3fiO+6qu+6uB+WLJf+qVfwt/6W38Lf/Inf4KXvvSl+NIv/VJ84AMfwEtf+lL8+q//Om677Ta84hWvwCOPPIKv//qvxxd/8Rfjl3/5l/G1X/u1+NSnPnXO2jFs2BeiaXovYJEnGum9DrENZ+ZhDc845I8rz2onJwtf8v1blDdiHhDNbzPXQdAWmSp2ubMXgPVB/ti9MpG7ZukuAcQZeEUCAoM0tVcgcOtH7K31fbV7dMo9oFGQjAJ4tK4BsRY8u2vUjDfNjvXYbkJ57q70l5vu6rCOLSvpAZgvIwVlCRUYqwC7z7UtGwwq7WnNTzy4Z+/7a7s+8IpY7Sp2+3K/ShLumlA1x/UduwrVcX0EPyEibS1+2c39xC9dQjhnIJz6/trer513/QASzfN2a6R8Qj1+951K1PcImMRet3WMcfMOTT5uY007ie3vvUp1Jh3ko473Un0BNWvt67Qg1QKfkYBmKoHQTEruAqAp2PYgW0GtB71A8b0OZ8M4N68ycqgY7IiAQGy/vxOSTYgGSlv9uNX2qTM7BwGBkksJWdp1AsBp5OeeiDAhYc2TRRSfhMWGc0xK8pzrg1sy7LiaRrft/SfVn4QLHd12H3vVq16FL/7iL8ZnP/tZvPSlL8XXfu3X4iUveQn+xt/4G/ibf/Nv7mS63/a2t+Gnf/qn8brXvc7K3vWud+Hbv/3bceutt+LFL34xvvIrv9KOvfnNb8bP/dzP4frrr8d/+A//Addcc40d+/mf/3m89rWvxd/9u38X//t//29cdtllAICHHnoIr3zlK/HZz34W3/md34nbbrsNT3ziE+28z3/+8/jN3/xNAMBf+2t/De985ztxww034J577sEb3vAG3HDDDYvt/4M/+AOklPA//+f/xJd/+Zcf0nV72b/8l/8SP/VTP4Xv+I7vsLLv//7vx1vf+lZ893d/Nz772c/ive99L17ykpcAAGKMeM1rXoP/9J/+E37kR34E/+bf/Jtz3qZhw76Q7OVf+Qz8q+/4G/ih//qJahL0yidfgje/8jl4+Vc+44K251gz2hGEtZP1ef/r6IOiNR9ivUi0ACwQ2hLoPpMPukNsC9afM3QzwNOAXzR17Ro0Y6qBzv6W9vRl3Q36rUD0/ASumMkO+HbXmYHsXr1uQ926/Rrq7begG3MQ3l5TwffBrgDtc7uy2XNXExBwzHL9Lnp92SoCuL1W9Z76dbeNy95z5TVV625kcj9xo4qKxesuHNtS3gvuV26IalIF6Gy7tV3WTa4s2pZjhyqLff5sQtkuQLoEOANgkca3McItY+zZ5CWQPYnv9z5LdS/RFtm9Ftp1Jn7g28yCXm5ZSmRxFwxTVFA+JaSy26cx2blrBJzmILFBgDXD4oUM+8KwizG67T72xCc+EXfeeSeuv/56MDPe//73401vehNe8Yr/f3vvHm5HUeX9f6v3PucEyAWSvLkBIdE3KgHhkMSE2zg4hKsTEBTFH5cICDMMNycOKt7y8KACoyOCIoz6oPIiiihgYAANkcswQoCEDEQu4kwgEQgRI7mSnL276/dH16paVV299z7JSU72yfo8T2f3rq7urqqufdLfWqtWfRCjRo3CQQcdhBtvvBFpGl+278QTT/RENgB87GMfw8knn4x6vY7rrrvOpq9evRrXXHMNBg0ahF/+8peeyAaAj3zkI/iHf/gH/PWvf8Utt9xi03/wgx9gxYoV6O7uxk033eSJbAAYNmwYZs6cucVt8LWvfW2biGwgrxMX2QDwhS98AQDw4osv4vzzz7ciGwAqlQo+//nPA8AWeRgIglDk2P3H4tHP/h1+eu7BuPbUbvz03IPx6Gf/bruLbKDNhXbuxlfBJl01W4fn9kcvUbSFQtxFGi++idNcbbJg+4HSnCW7DG7Z3qppew3EVEGgKiNYSIyR228F1hW54DaukLuT82taN3J/KxNmPDq45w4euh1zt2jlp5EbuHUJTor1KwjEkjbwH0Rki7mIR0R0Yc41CWu2rrZ1F9fGXTxwQY+JrqirfOF5wbmOc7dxFhyu6RbJh164jXPX/DD6uTd/nDarCv3nY9fF9j59IW7bJhTbdA7onordX9nre5HtIz9LbqkP+wYFtwN7vtF+Ez7TsjTAWrr9Zf3c34MyV3JO/hPMXcbz5iX38QwV4ypu19BOUnQoPzCadQFPUrZf95bb6lB1ew1yDe9Qdec6rjQ6Vcpcv+vRjbuHd6o0P4eJbzeZJwzG1voc7UaiuZGL+OasI7rR/xubjXv45qzDuIp35v+XmHS7ZR3YmHVhY9aRb7qKDWbbpCvYqCt4m01VEgY2O2J021Z597vfjccffxwLFy7El7/8ZRxzzDHWkr1kyRKcf/75OPbYY9HT01M4d/bs2dFrUjqfu/zggw/i7bffxmGHHYY999wzeh5Zn3/3u9/ZNHIlP+ecc1Cp9P1valuuD3788ccX0oYPH44RI0aUHp80aRIA4LXXXttm5RKEnY1KonDIO0fg7w8YBwC455nX8Nj//AVpI4/ebUBbu47XdIIqnMs4X7oLMHP2NAlltyZqs/nZIQ3dyu31e3fNpoSXi4lIk56LDO0LUOT7edRxs3wQ2JJL9vTG5Y5Wi4ltb53igghXEVEcCKJgEKFgDS/U1c9vv7byuymxTpYFtCoY2bj45pbsIJ3O1abMXmRrVq+iez1rGxK5SdBOYbvxNtL+bqgtVbBf0ixeXgXXznl5i7mp//F6KGjfqs1Gm5xLucpNgDYCvnb5CwVSri1CMW4HaVx61POBVZi3BU/38phn6H1SleAf88/1r567kCt3gSbW21iws1gwMZ5ul/NiAtZGKCdrt3URL1q07fWQu5/7Ucd53mIZUqiCBT1jLuIpEmvpTrVyFm5V7l0Uu0d4/UZ5vLnbJfdItVnOS2VImWt4B+roQTVvC3JjN27k0LQMWgYwUU3n1sSivdOwI0a37S3Tp0/H9OnTAQBaazz99NP4+te/jp/97Gd44IEHcO211+LSSy/1zgmt0mH6n/70J5v2v//7vwByS22jAGMA8Oc//9nuv/LKKwByt/C+ZtSoUdh11137/LoEzYEPGTx4MP7yl79Ejw8ZMgQAsHnz5m1WLkHYGbn3mdfxxV8txeoNbtBw7HZ2IW9roV23VouqsWpU7ZJeNV3J3cCZxZq7kYdiu6W5gGBB0LyXOmed2pKBEq20DabkiUcjmPOX7kCoKX7ciWoSYgowQjeXeLoCqBSe2AZa06fefWP7gLfGdTMX5jIrdUFMxq4XQLqlBf3iV6VBXiuiKZ8V0X7QLAA2OJovtJh4tBeNfFLdyYLMBTavN1l0g2PFgvv18kQ1tRE7xvtZ2BE0S7bzsvkFWfn43HCVmAQS11xMK3b3mAgPA6aVWL2pDJ41m0hUPH8JnlAOGyf0SGCDKf7SXspdiI9OBAo8+BUXuolS3nCMDXpGW/idu43bAGeqODcbcGKbLNn5vlvyK8/jRHaZuKa8XLzy4yR26XwS3HZda6Xt4Gcz+OAofQ9pJq753+mY4M6gkBjBTTVOodCBFBVUQakV6HxfAchgLP8pUq3ytbVNnWWO9s4DRbdduWZT6WDlmO0c3XZrUEphypQp+OlPf4qNGzdi3rx5uOuuuwpCuxk88n6W5b+f//t//y8OO+ywhudtC1EdY5dddtmq86lOZSRJ43fJZscFQegbrrz3Ofz7I8sK6a+bYJU3nD5lu4jtthbaG3QH0qwjn0tnhDbNr+uxAjyxUWXzpVl8ize5jwO+uzjN1ebRxgE/yjiPPh6NPB6+kHO4SQxGAXFBzYRnbsUz5yWw6wvrJBd6nmBTyN1vtc6FmRUL5oYaeeQea3mNKLNG2DK5cjqRqJgoVJ5A9NzLWXntcX5eiSjnZbACjwtIT8VQ/RrUJWLB9I551muznwEgwZ36efLztPsM5ycz4cxFtOcyruAiiJeJcHYtjicaWf01K6OtIhfOoQKk8zLXrnwgx89Ix5XxnjBrtSfGip8pgAZ5yJJdgSt8Yjp32G7B1AUbzTxh+9YVHdbl3POgMP2urJ2obWggwoYIVwrIzO+Lkvh3nf++aIyAtzHMMWhXFbDL2kI26JiKiWoS32Gk8QTaRhonwd1h9sntm9zHKQBah0pNk7v9TlWPCuwKfAEeUrBgk5BGIGgpn6lubJnFGMUlFstFd5mopu+xZRxdPUw9dT4YkapcdNdUBZlKbFulSqGiNDpUBZ0qRaJzF3k3hz1DRWtszOLzWoWBB0W3Pf+WxYWxSupp2zu6bV9x9NFHY968eXjzzTcLx5YtW4YDDzywkP7yyy8DAPbaay+btvfeewPIXdVpma1WGD9+PJ5//nm88MILWzUXe0vo6OhArVbDunXrrKWZQ9Z2QRB2XO595rWoyCY0tl+wyrYeWqvrqg1ekxprtRXESErnXwNF60Yr7uThPG1C27ReViBGb5+3YuKCzldMYHjuyU7scsEcRvgubAj2m5TZa3LF7stFUNk9yq7TQnqvKBHi3lxtnlc3yQM0GFWJEKm772KP8udhj2tvK5wHv19EXfXDsvDzwr7FzguvFQr/6HrsiUsPlwiLLgPG85m53YXl0GKR8Nl9e4UOPsP96PewoUuOm/1Gc7IBFxSMB0FrNdJ4CA885gloFviMRDblsfO3IyI7XMrLKzcLesaPxVzNW4WvY81pJLLt/wNmQJVicdCAanT5r6xiz6HzSNjTco40WEteUzSoWzOtmJrB3R6Zo71TQdFtxwzz3cPHDBu03awlvaWVtd6XL18OwBfNxP/7f/8ves7NN98MAF7E7yOPPBKdnZ146KGHsGrVqpbLeOyxxwIAbrrpptKgbCGdnZ0A8uXEtgaaS/78888Xjj3zzDNYsWLFVl1fEIRtS5ppfPFXS5vm217BKttaaPPgZ/ln/qKzSdP6qBV/LdWMXpIqyLRCPWMvYdpZsVPtLNvWoh3Zp/WyQ8t24b+xFl6wg+zO89QKIO0LLRbwqnma8qzONr3C8inlbR6BgOKBsJzV0F9n2wuqxcsWBMryxTe7biACve+snbiQ22IBHnnvKLiIa1pPm5mFNdg87ZKXF1s+5bcNay9vPjYPVha2WwLoRLPNb1OdGMGdaHu9uEAvtlv4LBoOrPCmC+vAg6SROKZo9jTPOknMWt+UpgoWbG6x9gOfAb6Vm7UtW6udt3154f3Nf97xjR8Lhbm3ljY1TouQFZv2bRoQCGzfZbzCPwNrNrmUUwC0PD3zAp+RJTsPaKbZMmAmTbHgZtD+FhHeMbENFC3gIW75xcSzXtO+FyWcbRmUmSYUrJmdFYOi1bMkuvF1tTdlHdhs1s92AdNcMLRNWQc2ZHmwtI1ZFzZlndiQdWGj7soDqumOlp+5MDDYkaLbtsJ3v/tdzJ492ws+Rmitcccdd+A73/kOAODUU08t5Lnzzjvxs5/9zEv7xS9+gV/+8peoVqu46KKLbPro0aNx0UUX2eW6nn322cL1Nm/ejHnz5uGFF16waZ/85Cex11574emnn8a5556LDRs2eOesXbsWDzzwgJdGgwK///3vmzVBQ8iCfvnll3tzpl9++WXMnj27pYEKQRD6jyeWrcbqDa1N5NoewSrb2nV8o+6Ezqp2zh+5ipP1ombcyOlFKs9T8awb5BZOlosMCvUsz8vdxkmUayPQtXbCW0c3+JHH6Z+Y1UwBGjoPFmJFQu53qjXYcIi2pi5F6xLDiWloWAGW77vT3Nq99obuPiQU2LuwbqRSFLs2F81Ujui+s0ICvtgus3oXisCPsWZUbMf7XkbUGh3fPFHlia4W/rNlgs8XxWwgopJ/DyOKh4Mh9rnydghvRy7MVCHN+pNpGJWZc+l7xGLLBzUUfxbBs6GBAz4IpElAU7810xvyAQRlxKhJ0Pk674pcxysK1t/acxeHE+RWVMO5i9M9wdouGBACGuhecv82WW0bxvpDBuYm7trca3tN9aC8FBwueF7K/8z3tYs2ztzHK16E8cxGGifX8SoX2MZlvKIyT2TTnGzuLs4FNkUEB3JLdLP1s/NZLOVu4lC0brYuBDPjkDt5mcjmK0UA8Kb/ePvaTQOqZ/70ICI2z5sGHwAgU8rOb8+g8oEKFq09H8jI/3+gNuZeAW/rrbOmDVQ2btyIfffdF6eccgq+8Y1v9Hdx+hyKbtsO1Go13Hzzzbj55pvxf/7P/8FBBx2EkSNH4q233sJzzz1nXcBPP/10nHPOOYXzL7nkEnz84x/HN7/5TUyaNAn/8z//g4ULFwIAvvGNb+CAAw7w8l911VV4/fXXceutt6K7uxsHHngg3vGOd6BareJPf/oTlixZgg0bNuC+++6z87QHDx6MefPm4fjjj8cPf/hD3HnnnTjssMMwePBgrFixAk8//TSmT5/uuZV/+MMfxg9/+EN85jOfwQMPPIBRo0ZBKYWzzz4bhx56aMvt8/nPfx6/+MUvcO+99+Jd73oX3ve+9+HPf/4znnzySRx22GE49NBDo4MUgiDsGPRGPG+PYJVtLbStFdq47nnroTL3vzR4USu8fLGXQBulHE5k03FthLg9L3hz50t++ct7tW7Z8ghO06Hw4fkiOtpGf4YTSIrrL5afC3M775vniZQH5h6NymzvHX5nYtGLXB6hWfPpmGAszdxivsg5RTdzvWXXC59hYdDBF7uhS3TBuh8+I/uM42Kbf9K1VNAXvOttCSofrFHQ7vkkCjozA0owgpoHQgvntduBBZdmvQIC1/QwX7Ny88GTsH8pbeaZlz1e1h88UU6fW9BmfC42wF3I/WjjSZMO5wc3o2tk9hjBI4tbcV0ismNrX9Pf0gQZm59dFNQVlTWMLF42Z9vFxHB/uwtzriMim/9N5tfO2DkFdD5k4B1XCRKdj6zUdAUVnXnDDonK58lDm/9PjOt8q4Hedja++tWv4uCDD+7vYgjIl8yaOHEiFixYgIULF+K5557DG2+8gWq1inHjxuHjH/84zjzzTOu+HXLJJZfg0EMPxTXXXIN58+ZBa42/+Zu/wWc+8xn8/d//fSF/tVrFT37yE5x++un4wQ9+gIULF2Lp0qXYbbfdMHbsWMyaNQsnnHAC3v/+93vnHXTQQXj22Wdx7bXX4le/+hUeeughZFmGsWPH4oQTTsBZZ53l5f/gBz+I73//+7jhhhvw29/+Fhs3bgQAHH744b0S2hMnTsTvfvc7fPGLX8SDDz6Ie+65BxMmTMAXvvAFfOYzn8FRRx3V8rUEQdj+tCqeR+zWuV2CVba10N6YdeUWbbiXMrKApFCoZXn1uEV7c1a1L2X1rJK7HmYV1HW+FFjd7GfBfpol3r51NzfW7TRTTqRnzKqdGanrCe+SCimmi/i+sVyTAHYWPaOLMrZP7sfaGg2d5c1YvVWmnVWTfNSVs9LGYhlxCkG5yErNApn57urwLZ6eiPStjlHraUlbhZrDG0AgEY9yEc7FFv/u3MSD73B5mwpsOx/erYsdXVOc1jDnLuMxSzZvD143sO/aJZr4TrnQhVvETZv8YZtolsFrw4gQtfm9wQFlgvPpvJ9lFO2eCVYNKNOXYSzQuc3QdLJMWZHr3M6T/LNC/cTt235nXNA9aztrs4b9yFbI1Tf87lmtAbvWNv3OCkHolGkgG2nNPZ/CuFTwIMiazYOh+ZZst342BT+rsOP5jGFm0TYu33ata+tenlteKaBXxczP9oJ7NerkvvuLZ9luJq4B2MFRAN7gKP/7Ha4S0Uxge4Et2SApF79lFm3ofAmyTCfWwh2zbqcqQU1VrJs+tREt+fV2JnO0Q1566SW88MILmDVrFpYubT5vTti2DBkyBCeeeCJOPPHELb7GKaecglNOOaVX5xx33HE47rjjenXOyJEjccUVV+CKK65oKf8nP/lJfPKTn4wemzBhQstu3/vuuy9++ctfRo/xdcJbSSfIU6AMcUkXhL6BVoR4fU1jy/YVJ+6/XYJVNn4b2sF5O+vCxqwLm7MObMw6sUlX83l1Zn5dTVewWVexOcvna9NnPl/PfDdiupZVrLDO5+65fRLZqdlPmchOMyOyyZ3cfjo3chjRbYVtIyioVcL2ASbCNFs3mAkzu68C0aYiAk95QqnU3ZZfn208r7bXUOX5Y+ebcnFRzUWRJ45ISAbfPcswy9OKUSkaBA3w1sbm83K5IG8ostl8YusirmLPAE6Am8/MRBpHpM2858wHW8K2Y4MaTnDqwtxr3nfCdowJ08KzAZy7v1c3U/dKLog1RQmvqNyiTfOxuYA2+6jQdwBJ4s3ltm1YcfeE/c77PBvgsXUyBS7pF3zuNT1f6geK9QXv+ZsfpkLZcT9fI68WPhcbACrGNZw+KcK4/WTztDuY2zhfrisU2YlxE6d8NO+6Q9XzT7j9TuuGnpVufJkwIB6ZnMMFLony0AMpJrK9AGVQ0fnXfJ51PWN/2/nfdf73PdzonDT/v2JzVkWP+Xw77cDmrIqNaSc2ZmxLu7A+HeSnZV14O+tq2A47Go888ghmzZqFcePGQSmFu+66q5Dn+uuvx4QJEzBo0CDMmDEDTzzxRK/u8S//8i+48sor+6jEgiAIglAOrQjRSAr8w/sn4vgDtk8cjbYW2hQkx87FNkKav5hxl3I+55pcBF3wMx7wzAVC0yyd8kfnZQPe3GwA5ZbrVt0LFWDnv5rvnqgCPAFVEEhRcURpKpo/z1OmSCL5mZDh1s1QQBcEWnDP6PURaaoWm643FKzVCL5v6UBzMAjgBiiK+7FnHAbAs9eMfYZFLzwr7aepIG8JvfKE5dcOnnHo9q0LeZT7DNI9V3B2rcJvILgfL39Yj17VK/R6KBx3F1O9uDC3ZtulvAoW7mJaGSSyKSp5nuYijLt8fuAya8UOXM0ryLytjEbLgKXaX5aLrMvRNa0Dd3F+DW7FdvlDK7bvHu6Le2Wt2+FGx3g5bEDM4P8PCrxG5bHfNYn99vovdcOGDTjwwANx/fXXR4/fdtttmDNnDubOnYvFixfjwAMPxDHHHONFkO7u7sb+++9f2F577TX86le/wrve9S68613v2l5VEgRBEHZyaEWIscGKEMN368B3/7+DcNnxk7dbWdradXxD2oV66qK80lIuAAruhCSga+aliKzYLgCacRc3FpJcgCc28FndWLK1JtdxIGNpWUbW7Nx1nFzFtVa5a3fMsk3vz55AQS6KrOo1m3mHzV1vNZQ2rrrkIs73KyZ/aFnjk04pLTNijrsda7j7KziXcmYZ9IS7dR1nFk0qB8AsjE6A07m8/qXCCZHvzaA6cWLfI1bIWETp5vfzBxugYCzVJtBZBcgqyq2RTZbswKoNu6+96OPeYArgFJ92ItQG6lKu+grunNCN3GsKcwIds27p0br65VGAe74V7S4Glf+FMeuNq4qya3NrEwBNIYEm3+yM3dEGN1Nm7ew8zbOY2zWwXN+i4HLOmu97bzTrR/TsuSu4MvvWdTwz+TIz59xO0VAA84iw32P34ZHF2T65iZM7OEUar/JAZ0lqoomnqCapiRqeWpHtB+6i43UMSvIonGTJdi7lvvszULYsFxPSKhekjQKdcWFsxXAQT6Om3fSe0JLtfWrfLZymAoUu4k6sO/HM0+mYVytvwMMENtMJMjOAUNMJOtjARV3l1yJX/Tw9H+TYnDXpYDsYzdx5v/nNb+Lcc8+182FvvPFG/Md//AduuukmfO5znwMALFmypPT8xx9/HD/72c9w++23Y/369ajVahg6dCi+/OUvR/Nv3rzZi/S8du1aAHkAr1qtcRTZWq0GrTWyLEOWxQeGyD2X8gm9p1H7CtuPLMugtbbLmTX7fQhCO0H9eWv69ZHvHokjJv0Nnnrlr1i1bjNGDenCtH32QCVRW/176c35bS20N2Ud0JkT2nyZLS+iOHsJo7nYtE/LfNXZkl/2xc4s/wLAjzqemn2AievEuIsDoHJ4Ipu9jJegFQWKAijqOAAgMQLJRIzOX+w1VJJf3y4LleWn5HNc+Qu/2TIX/diKsITm0Oq4yNK+wLZY4VKcl22FNksvCEV2PU9wR443RFEZmbXRU5nBMQRC2tTRcx8232NbS+Uxz4Bcx/lyZ5kV1y6NXMDD6QHWamvbUhfbhA+eRDwRNCVTO7AnrQoZ/XYJ261wbaor5VXI+6kppzZzmFFRUKl2/YBuRW2emkLaydDK9itdSQoi21vGi9qaBnWozU17hOLaWtOp/A3I3ceVGzfQrNxZ/ju0AdG0mV+uc6u2bmGEJhfZphpceMMFQePiOxfcmRXfCbR1F6fvzl08tcI5X6bLLcnVoeroQOrmZSuyWsfX43aNl5SKao4vsHnUcP9vc77yg/LyNRLZsYFTPgebrxwRphGxYGj8eKIV6qb9U6UKojtRGTIjtGs6s3O4Yc7ZnLaX0G5ET08PFi1ahMsuu8ymJUmCmTNn4rHHHmvpGldeeaV1G//Rj36EpUuXlopsyn/55ZcX0n/zm99g1113bXivarWKMWPGYP369ejp6WmYd926dS2UXuDwARUaABH6j56eHrz99ts2Avr8+fP7uUSC0Pf0Vb+uAPgLgF8/3yeXs8EWW6GthXY9S1DJIlYT9hIGwLNcx6zYtHwXAG/ZLium6QXPzLvmItsLfGZeuD3rNeCUSCMCcehZCwEnvJloInFjz1eB4OGi2oqiXNDY21gBZiQYN5SWmDWtAKRqqeInYt95XWP1b3R8G+EL8BbEUTPhCWdRpfrTPG0uDG2beAMSiLZbmeU/LE9DYcxFtHICMhYUrXEd8wtR33QWbZUPFIEENvU/IzpzNZmnGQuwAglhIzKtCueCmr4bF3KyaMfaEpFPwMu/RfDfcewaZO32Bm94gzeHlvXiuKjhza/jrWXNXb+D/cQIap6XRHbhmg2s1TF4QDRv2S/4LuNuGo5z+eaBz1oV2XTdmBWbp+XlYWK75G9xorQNepaZEa5MU4RxOidBDbACHMiQoZILcw3U9cCx9L355ptI0xSjR4/20kePHu2tedyXXHbZZZgzZ479vnbtWuy99944+uijMXTo0Ibnbtq0CStWrMDgwYMxaFA86qzWGuvWrcOQIUPcoLYgtCGbNm3CLrvsgkMPPRSPPPIIjjrqKHR0dDQ/URDagFqthvnz5++w/bo3g41tLbQ3pJ2opZ32e/jCRS93FF2cC2juIq618iKK05xtCnZG7uIaKAQ6i1qxyf3UWLJdGn1nleDv48ZSDQ2oTOWWbG0yZcgzZgqomPf9BNbF1Yo0K/iZxZCLALpeuDRVxoSPibJd0ApM6HlrGNuAX7DRsjNjteUCMhSMBUIB3ygv0YKWKViz+XkaLoAys2YXnlPDG7BmNVHGbRtUctfxrArnKk7Bz6p5HsAcN9ZsHqQst3jnBYlN/6T7KuoI5MLudn3RSW3AxLbNEtS31IpvR2lc3a312g4qmb6qaSRHAXVaxNtcgpaRo1Dk5PcO3r8UdNV5B2QsGJqbmqBsHZ0nhWL7iItywPWzMtjgF/8dKW3KnwGq4n5zXr/h7cEs1iBLtgKzWLv9apJZl3IKgmat2SrL3cWVWUc7iDRO0bCdyzgLeMbcxek4t2KHAc44KZSNzh2K71wYJ94+zc22c5yZyzgPfkbxNWi+MwCT1tyKzS3Y+b3LRLf/WYZn2TaeIokR1HU26GHby3gR2PwAeuoi3sr4xCc+0TRPV1cXurqKAeU6OjqavmylaQqlFJIkQZLE58qTyzPlE4R2JUkSKKVQreav8a38RgSh3eiLfp1mGk8sW41V6zZh1JBBmD5x+FZHG+9NmdpaaPdk1VyhGGIuhIBz+wZgXcQznVu36Xjpkl0Ze3HLVCC0AU2WcADazM/TmbIv25TWUGRH5tvqROdim5JJICROoGiVaxTQdxhrtrU25mKdjsOIIZqDTRZvKos1eMK5voZdkUSMJ2zYvGzPGsvcyGOWxlZpKoZ6fcH8wxORPC2S3hRePxKC1j2cu44rbz625w2QaPecbBsGEcNL6kNarhUrtRPXOkzodX1prfa8jxqvCFuf/Noqy3uTSpS7vEY+YJSyNqO2J6GskLuM20EcJpQD8ex7VIRW7yAf3LGWqsrHpJjgVkBRfGsFtOAZ4V2fPRwqEl8/myKM09xtEngUpCyPKE6u4i6d3MRp2S7uLs5FNhfYidKe4CSrdivW7fA4iew86FjiiWUS4WF08fw8J6z5XOy62adlGAEURDelee7iJfuNyLTy2sI+C2gkdB/2fKBz4V1vs2BojRg5ciQqlQreeOMNL/2NN97AmDFj+qlUgiAIgtAa9y99HZff/Zy31NfYYYMwd9ZkHLu/RB1vSl2bJVnM1mOWZXHLtiToSWlZl0p+PK2gllbMsi9Jvp9WUMvcUl58yS5rUUkT6yrOrdhk5SZxbUW2Dt/qGxAeVuGmmWDw032BEXx6VtFYHtVUeGjlb1zEhMKa0rj4LtSlQXN45SujN5bmgJhlmwvrUKAWrN82nV/I3woB4fg87CTIy54Tz0MW4vB5h8+iqQBHcKwFjdHKPPSybu33j4goTnjfUf5gjDnXE9k84riZl+0NYDQQ2fDS/LoX+lcLfZPP3Y/1wehpTdqyLBCa8kS2E3j8k45REC4AVjhTGs3XJrdyf052XGTz67YCn2MNwLNmk8jOkBTmZZPY9laH0EkgyP2VImyUcCbMC4HO2JMoXoOEfNLSVs8qhfPrWXF5sJ6sapcH68naeuzao7OzE1OnTsWCBQtsWpZlWLBgAQ455JB+LJkgCIIgNOb+pa/j/FsWF9bTXrlmE86/ZTHuX/r6dilHr4V2K+tuEv/4j/8IpRS+9a1veemrV6/GaaedhqFDh2L33XfHOeecg/Xr1/e2KFhf68LGeifW17uwvm72a13etqHWhQ31Tmyo5dtG+9mBt2sd2FjrwOZ6FZtr+bapVsXmWgd66lXU6hXUavlWrydI6wnSegVZmm9pmkCnClmqoFMFnSYmEjFZu0lVoPjSbSNswVkxE+2l527E2ggwnbvKkmuxgo1ObSNX80jWNs0Jk/jazCqSxs+LCBy2kYU2qwC6St9VpBxMdJIIDUWj1z5+U1mRQwQuujHrdNQyHbr46lw4q0wHaXRvzc5zpk0eM8oFPlPWVZzaIKsqkOOFZvvWldy6lGsv6jgSDV3R7pnZAZdg4+0VDJpEpVKzQYxIe5a6j/OBhbI+ZNrAs+5XnBt4Vkmgq7SpPPhZVbHvKm9D6lNVcz3e7yrmOIvwXujHbOADwX4zke21A2/6DFBZHqSwdNpB5KLkMu6+RwKfIfhUJtq4yiOQV80+uYl3JLk7+CBVQ6dxDc9dxOsYpGpmnezUfVcpOpGhQ7mNRHcovAkSx3w/1QlqqBjX7yp67PrWVfvZw/b5+te0HGNN07rX+ae3LrZJ22zEbL6+tVlLm62N3UNrZGdu85ZzJPFsln/kW3RtbSaie7IqNqUd2JR2ePsb653YVO/Apnq+T1s7sX79eixZssQGulq2bBmWLFmC5cuXAwDmzJmD73//+/jxj3+M559/Hueffz42bNhgo5ALgiAIwo5Gmmlcfvdz0fdgSrv87ueQZltouesFvR5+p3U3zz77bJx88sml+e688048/vjjGDduXOHYaaedhtdffx3z589HrVbDWWedhfPOOw+33nprr8pS1wk0TXIF7HxrwHcf9CzT2gU0S41rNi3TRfvcNTyz7uDGlqQjc7B5utm3NHuGdjI0fBGk2XcrBnTuqmsCo+XuunCfQOA6DiCBjVYOk04izO0bN3IdHDPl0KwcVsQlrswFl/GClbGoN8oCrfWa3vxGyizWfQEbPHBRxllEdhvgi4lA25Y6aL/QU0Hbe4R10SqoB+9PPDvPp9Bau0UHiErO57c0EcS12bdTFEjQmkj3+Rft0qGgEs0s1SSQ+XdVbOuSvla2XrvXPKHIjg36lLWNYvvWi4Xan32yZkEgsBvdiuYD83nB1mLN1rZOjDjm62OTa7gNgBYEPaugdas14LuFU9BJHl08DH7G4cHLSPDm5yhrzXb5/PnY4VzsRm7i3GpN9/LKEVi7Y+VsRjiPO4xi3m6u40899RQ+8IEP2O8UiGz27Nn40Y9+hI997GP485//jC9/+ctYuXIluru7cf/99xcCpAmCIAjCjsITy1YXLNkcDeD1NZvwxLLVOOSdI7ZpWXottJutuwkAr776Ki666CL8+te/xgc/+EHv2PPPP4/7778fTz75JKZNmwYA+Pa3v43jjz8e3/jGN6LCvIyetIKqce8DAqHNXrq4uM4/0TTAGQBjmVZNBTaA4tJdZe+w0Xc5XcxgJ9wC/rJfsELDxCbK58DSMl1m2SGt809o2LmyIDFNW+auBxN8jTSRDopD+5rdP7QM8gBVhTWgS2ocm0/cCG++bOyCwfeCNZxbJAMLdpl7sG9EjhSAtQdvk4KHQSVoL/JIiLiVu80JUU/Y8YfUgnCOWvwBQKtCW0TbM8AO3NBPwQwAWW2Z5KKT4gGg4kZxqL9Ca7teNq8TdwnXFWXXybZz26mvBQKblyvuVh60IxfVYb9r1A9Zv9BBH9HsMzYwEoMHQvM+mWXZzstW/pJetH42D4DWqZz1muZlkxt5ojJ0gsS6uT4rXGz5q1Bk2znWcFZtchev6ap1F+/R1Ybu4jVdsZHFeQA0Cl4ZzsWmmBokun13cPosF9c8X7gf+66b/DFKI2n1tL2E9hFHHGHXli7jwgsvxIUXXridSiQIgiAIW8eqdeUie0vybQ19PqEsyzKcccYZuPTSS7HffvsVjj/22GPYfffdrcgGgJkzZyJJEixcuBAnnXRSy/faWOtAtdZhX5A0e/HigpovyUXfae3rPG9jyzVdj6xWxWV8aL/Fgpe91Gs4JUlCxOznS28ZF3AACkxcV+CEc2L0swYybeYGWEGm8kQSAyQ++KCBhrtvgBdpvEJCiPaVc4Mm4ZmwJmL3sdbsMtEcCpRAYNoxiOBkb9415Q+Ec1Fg6+hxT1QHbUJu42QxJes1FLlD59+di7gybvWB4A7dnCs6GLzQniU42i4N+lxBJgSDB870y66jg3aM9QMF5w2RuHNon4LuQStk0Ma1mj9wKrgy0fQNmVvjOw98ZlzMq65tdSVwA6dysIGoqAcGb8NAlNv9oOE8izi1DW8S6itZ0A4asGtp03cF7+8GXy+b39Z3F89c1HH4ruTcZZwiiXeqeh70jEUa7zRB0jqRMrGt0cEavqK09ehJ4Ky0ufB11ugeVFi08NxNHIB1Cc/3K3aetY0oDhddnFzCgXzZRX4eF9iZFeAJuEW7kbhuJKpjaXyfe0K1mjd2j3p94CzvJQiCIAjtyKgh8SUetzTf1tDnQvvqq69GtVrFxRdfHD2+cuVKjBo1yi9EtYrhw4dj5cqV0XM2b96MzZs32++0fhlZpUNxTfv0QpSyfW651laIwwjoEus1YIWDhae3SmMDiac/PIXJRRV3G6fbM+ETs0B7+owsjzwrF8IKsK7kZeXnFkISOSXBu8LzEIrkJmKxABPbXlq4Hys+F9OxcyMUpkOX5Q/qHm7xY7qQrtkxum7DfhO6irfg/troUvk1yjKUf8/LzdzEtZ8v76eBGzkf7AGg+HILhaBmKt6OcMdcOYr7tryRfhmzahdENocNVJV6WPQCHvysEYlZ3ovyVgJ38txF3AU/S5DZdbJdADR/Ca+KvZYT240gizRBVu38GEvX8eji9jraBT2z+a3A58LaF9n8+jZvCwK7UXpouY4tB6Yjad5xW68t//0JgiAIgrD1TJ84HGOHDcLKNZui72gKwJhh+VJf25o+FdqLFi3Ctddei8WLFztX5z7gyiuvxOWXX15I70krSOoV7yXIaoVAXLu0cnGd54ET2DpIJ/pCZJe+WHuyGE5VKtCSXzoxUjhxl9EVnVsHK1TuYDNrO6vM1dHbkuC2oRslEylkjXVWRngWWiCwOEZqVxhP0EGGRjQT0TGrbHCcrNl0vahV2wa50va7TQsqxa2smQ32BRYcDX47KQSu0GxeNi3zZds892aINmLkxd6zRGv/uxPTyhPW0UGIWHtTmdi+8tJNfyWrNmW2a7PTw1b2GdiZyvQ4FAJ3cR5IjfVFch9nbRK1UpeI71CIR+d0q2gTB+2jbB+Jbi0SRh3nG62dTfOzO5LUrp1tl+tS2gZAc0t5ZZ4luwLngh4jA1mxlYkcTltiA5oBMEHPqg3dxWu6YoW2dRNH7gKeu4i7tbPruuKWW2Rzs2nOM0X8zveTUsuzV5cm6aEVOxTY3EPKpsXOZ9/TNOZQLgiCIAjC9qKSKMydNRnn37I4ZvsBAMydNXmr19NuhT6dUPaf//mfWLVqFcaPH49qtYpqtYpXXnkFn/70pzFhwgQAwJgxY7Bq1SrvvHq9jtWrV5euzXnZZZdhzZo1dluxYgUA5JHBzfJcPfUKavUK6vUKarWqjRZOEcPrtYqNGp6miY0anmXKRg5vHj1c5XOZe/MCzV/mmXk0jzxc3ArRyO2++bTRw7WJVK098VtwSQ7ck11EbBU9Hm4ZRXa257qNR4KOzUUus+x6AicihgqUCUDWXKFYDrdwXja5hYfnO5Hti2uV8XNItcIJPiMEMy/ielxkZxV6dvCDo/F2swHmtP2kLdY+YTvZQYxAdOefKmiLYt4yt3HX8Lz+4RaLQq78fdsmyvVpGqihPMbtnqKOZyyqfZ7G+yIKEccRti+LG+AC+LmI8aWeCDEi/UaFbWvz+heJRhxnxz2RjTzaOM3Rzt3FjchO/Oji5C7egZTN02bRxZGViuzUWI35cl3k8k2u4TQPu0f7UcXD6OKbdAc2Zx2FyOI1XcGmrMOLLF43W81EDd9slsmqsyjiPWkFPWnV5q1rF9zSjy5eXMqLCNM1Wcnhn5PaJR7Nco9a2aUfaTnIutlqaYKeegX1NEGtnv8f1FOvFNpWEHZmHnroISilCtv+++8fzb9w4UJUq1W8+eabuOOOO3D44Ydj5MiR6Orqwjve8Q7MmTMHf/3rX7dzLQRBaDeO3X8sbjh9CsYM893DxwwbhBtOn7Ld1tHuU4v2GWecgZkzZ3ppxxxzDM444wy7HMghhxyCt956C4sWLcLUqVMBAL/97W+RZRlmzJgRvW5XVxe6uroK6TyIGX23Rkq2T5ZrAJ71GiwvFyF5mv+d59+WhHM5uZttXpzcmu0dY1ZGG5EcJNzh7efXgLUucldezS7rVTUUw0agODGIojCJiJTw/d66kBduWNI23OIZXC9mtS0IcO/m7DPYL8z1Ds+JFk75bVAywBBaWTUfREGw712/yf2blTPWn0vyFto1vJRS/mBDg/7qn0f9DiA3cheoj+6njfAlEezaUwdtGfY37zNW1SAPn9ftlT8kHBwqw/Qdzb67uenFRgndxUlYl0FRxQHYNbEpMFrFWqtZHhZlvDeEc7Ntulkj2wZBY9HHeaRwglzFKVgaF782qBqzCnO363A+Ni8b/2ylLiGxIGex++jI8dj0JM+TqqVSCcLOxw9+8AMvbs+uu+4azTdv3jwccsghGDlyJFavXo0jjjgCl156KYYNG4Znn30Wl19+Of77v//bW99dEAQhxrH7j8VRk8fgiWWrsWrdJowakruLbw9LNtFrob1+/Xr88Y9/tN9p3c3hw4dj/PjxGDHCD5Pe0dGBMWPG4N3vfjcAYN9998Wxxx6Lc889FzfeeCNqtRouvPBCnHrqqb2KOA4AqbE+O6ENJpSZsAZPd4ll86+jIru3hKd6VqzyY9DKRHI2govUCQVHg4LWxnWcRCq9yGtjEYRxMSfjiknXCs712exnUEbcsHJx8cnEeRhd3FoIq+44D1AFfj13W1tcPs+1tBnZuYWmZaI46vYN+GLbpulowC8VnJ+3lTb72lm16ZaJ+yxEGg89AIII5DSnHcxlHIkTr9ZyXdYFY4MA3oBR0B7meFl7FbwGSp6JVtQtlR0UoG5q3cUVTH81F7JtrEDeAlZgUx57W+X6GLd+W48B1w+jQpuV0+KJbxUV1tGfOj9Wls+2HxPStj1NQLTwlMjNuOgO189OkK+dzYOgkXU7Udqsm51vFUVRx+t2TWw+Lzu0ZluhizzwGLdkkxjepDsA5O7itM+t3NylfJOu2vnYNU3BzSgwmrJBz/JrFCOMhxbmumaRxnspsmPEln/kq1WQe7pGviwkHU+96Ud+cE2XDqRtFnVcELYX++23Hw4++OCm+e6++26cccYZAIBPfvKT3rEjjjgCgwYNwnnnnYfly5dj/Pjx26SsgiAMHCqJ2uZLeDWi10K72bqbrfCTn/wEF154IY488kgkSYIPf/jDuO6663pbFGSpMq7cKiqsNRcVtMvFiMmXpxfTPHpjqmhVZMcUpkkjq7UGE9lMsOhE22W8oFW+XjZZ03Qu1BKqq4ZdrthWLbOnsTYpqlrPQk3rGSd5NG0oWLddAM4VOrT+hYJYBZ8I9iN4ojwiCPncadovztv2hZBXNiuwNRPa2qapFPCW9uLtwgYZMiYKyR3aF9zaBY6z0cXhzcsmd3HvPmF7BWX32jd2TAcuzTGRHfl0D8AUIXx+lJ4gX1oOpk60dBzyvqsy11aAysW2rU/wg1GmTyllXMJVYVCnzMpcGsSsmbj2xHj83Eb6zne/L/6eNH9G4bn0m/fmZ5to48pfyst95gHOKNJ4BTqPMM4Cn1H+Vudl05axqOGpTtCjK9aaTYK6pit2PrYV3VCoZdWCuKb52LR0V82MUNE+zcX2Xb/zedh1JnaB+CBFozYlvEjh7GG7JR/d/x88jSzYGSsHL4uL+UFCe8sHAQRhZ+fll1/Gs88+i1mzZpXmGT48D15Uq9W2V7EEQRC2mF4L7VbW3eS8/PLLhbThw4fj1ltv7e2t44QiOyacUfKC1hvLSBMh6OXrC4yyjLqSW5M0S1MuqJTy0vNdEiUqkm6LTGmR+pA7Lwlt+tTBvTzxw418ygn9UhfyEBJzrEkKx4O00O3bE0DmnDLX8OhcbRLdsT6vnLDTbJ+3RcHiysd5CgUoXr9Q3wYUjOBl+WNCutWfdOTZFp5zZFDA9j/t7/sF5nmVZ7kO+5f7LIr0ZmXvrcD29iPivpRony7r7EXs+tmByzgA5zbOIo3bPEZsNyOclw3AixQOwNzBuIDDuXeTK3gKZwXP87t1suk4/8y8a/uu5mEk8VhwMpvX3K+Rqz0RO6+RW3p4XnmwTZ6naTEEYYdj48aNGDp0KAYNGoQ1a9agUtl2MQZOPPFEvPnmmxg5ciROPPFEXHXVVVY0E3fffTcmTZqE97znPV56mqao1WpYunQpLr/8chx//PF45zvfuc3KKgiC0Ff0+fJe2xPNlvYqzq1m+fgLVEtiOVQIlL5FxWzhfg3KoeFbrmGUSqbd+tl0kSxXOGRMy6DzwCOZy6K1sWIncOtBA2YtYGVvS3jCJnSPpmMVdtwKEqe8SNRpwLjFO8Flxw2oHWJiOiQU0XyfiWMAnru4Z7GldBZJ3LqHZ4BKNZJU23RvvWc2+ECWfuvqTFGyY0HmeAA0BWbR1iaNKeVGfS2wnNq6ateepdZsjcLgQ4u6L17/hB5s3k+hEVi0XTltJ9DmIhrg65O7vqM8z4CsGvQ78qwoEczRPlMmqMv2S/LagSR+f6q/hrVcc+8SelaNrLHkOh6uo02WaLJOO5dxPjeb5HDuNl42LzucAw2gobs4Xy87M5btTbrTnFfx1sa2EcVpXyvfXZytnR1GFXdBzZzApq0sMnjsmXHRHZ2HHXnAmt8LvjU707DWamo7igsC5FbuMCaIzrbVfxKC0Pc8/fTTSNMUU6ZM2WYie9iwYfj0pz+NI444AoMHD8bChQtx5ZVX4rHHHsNTTz3lxd+ZN29e1Jo9YsQIrFmzBgBw9NFH4+c///k2KasgCEJf095CG4CyL0AskXYbCezgRaxgObYHSkT3FqI1inO0vXL4hdBGfdKqSJrUsvXZNenmwkprtjQZ3dCVPRfU8NuDrsOEtysQnHXWLOnFozfDE9260ET5LFVVfMWNieoYMUMye9Z2P2MWXe5GHlnCq+BCHYhuK7hTk49dWwfl5sLLthUT17ADFNrtK+QC1bSZJ6ybiGy7zJf9ZAXhApq1TVRkB+3oKtRAeJNeJqMstYVyxxTLy89RsX3qlwWhTX0qiAVAEfO50I21VbN+FRHXpT/tMoHeILu9Pe9nLRDO06ZPEt75El7ONTwPdmaW7zJrZxM0P5tEdwZlhWgsunhm3MJpnWxyF7fLeGnnIg40ENpZxVqvSWhngbDmy3jxJbtoKa96lngCu9Gc7Ewr21a8jo0oiPjAUk3HvPnYlNcLvun+j7ECuw/+jxCE7cWTTz4JAKWBaEN+9KMf2cC2jbj99tvxkY98BABw0EEH4aCDDrLHjjjiCEyZMgVHH300fvrTn+ITn/gEAGDt2rV4+OGH8cUvfrFwvYceeggbN27Es88+i6985SuYNWsW5s+fv00t8IIgCH1BWwttYovc9qwPK0uid6VSoREc6OOXqlBkU5pb/Ec7lUICTbv1tQGdW/syl82KGyYC6TLePoxFMoCLGrckEtsnEYm48MkHQ7awQYLzQmHY1P05FOSR873529qIbP7dmaxcB+HCGrAu4rSVibOCtT/sPq12p4JQVkXRHArwkmt4t2/0nCIDDPlPiAXT0yh8ll3HHufF89pT2cEcN7Dj0hoOSDQbxCkTzw3aXwfPuyGFfukKlA+CNf5BkNt3OKeaRyVPlBPdAMqt2FCe2KY0Eq9kyab9VCeowYlsLqTJ2g0Y924T9IxEth993J9rnZGrufZdwu0+s1iXiexQcFuBzcR2M5qJ9kbwgVt/36W1OodcEHYESGhPnz69pfwnnXRSSwHN9txzz4bHjzrqKAwfPhxPPvmkFdr3338/Bg8ejMMOO6yQv7u7GwBw6KGHoru7GwcffDDuvPNOK+YFQRB2VNpbaIcvNS2+XNt8JS9nEfurf5uy88tesii9wcugCsQXt3oraBctXeUFsNGTtQbSfM1hlbEox5m5mMr3M+Ri3LqLkyXXvPeT26tfqBKhbayL1oIdztUGfMuoYlZtZQ977uMFQV5idY0G9AI8K7YnnGNi29Tdzr824jpJ8w0aUHVApSY6uYlSnkeCZy/YhQEHFNaQtoMbwVJonihXQMMo47buypU/qAellbqMI6h/rF0j97Rlin23z5ItEweeDheJXJsDGs7dPBwUsP1MuSB7CZBVlZ22QEH4ALgI90F5G9aFlQ9oXWh7IlvB7++sz4f3VTpfJSAU32QpjYlp/ztZsDNrtebzswF/3jafm50yFwJ/aS1nxe5BxQrtTbrDWK+N67hWyJBgU9Zhg6NZi7ZZH7uRFZsCneXpLgCatw62zc+Cj6G45nXhcSjtW7PNfmzudiOXcXpsYQRychuPRxfnQdDc9QSh3XjqqacAFIX2hg0bcNFFF+GHP/whDjroINx+++145zvfiWHDhmHYsGF9dn/F/j+9++67cfzxx6NabfxaOmXKFCilvNVvBEEQdlTaW2ijqXEoTkx0e8cjiexFqqnlu5dl4SLbBTLTQTYSzUa0Jtq93Nm5sToXY9Y9PFeydu4svXWTsAbsXFordJmAstUmAeS5jmsnEhNERYodF2DWzVJLZ3gib4KIUOTfi+naTw/OVcE5TnRrP9I4E9nINFBhIpvV2bOwhtbWyL5udLxRm4Ti1Ihp71goOEvazl6jN3BByfuMEd5cfNqqcHFpB1WcFdy7rLFa88EJ/um545sTuWWc7qd5OdkNIk4sfps3aP+4Z0J5fvtsqBDsQ7UgysI1tX23ct9FPIZnyWbWa/okwUxW6QyJFdm5BVsZV3IXaZxbsbnopqjidK/Qil3c3zqRTemh2G5Gs+XBnKt4IMTtJ7zP/Av7m4De/6QEob9Ys2YNXnrpJYwePRr77LOPTX/mmWfwsY99DC+88ALOP/98XHPNNd486r7g17/+NVavXm0FfpqmuPfee/Hd73636bn/9V//Ba013vGOd/RpmQRBELYFbS+0G9FoiReXqcEFPCseU4r2+sFLV/RNvqxwxVey3L1bx4uljEz2lvoKLN1QdvkoT4BlyJf/Qi62FVliSORx4c2En29xhWfFtmt0q3iV7WCELVpg1W71jbREKNMxP1376Siea69JgptcxW0QNHY8MydkDQobrstMt1Dxz6Z1DfPZ+itWflVsh/Ac3k+34u2fhGzpYIkV2QqFyOwkhKlq2n33BnNsXhXxEAhEdsR7wmtbXSwbr0tYvrCupZSd20yol4iy3tCqkExNw6UUiEFlVnDbqOAm+BmJ5x5dQQ1sGS/N5mXTEl8gC3XFm48dLt3FLdn5vZRdI5v265nL10hk8/nTZe1BYjsGzdcOrdnNIo2H2J+YFdlOfEukcaGdeeqpp6C19qzZN9xwA+bMmYOOjg7cdttt+OhHP7rV9zn99NMxceJETJ06FUOGDMHChQtx9dVXo7u7G6eeeiqAXDyvW7cOxx57rHfuMcccgyOPPBL77bcfurq68PTTT+PrX/86DjjgAHzoQx/a6rIJgiBsa9paaOtQYDQRcGUvZaXXb/bmrFXRut0bsW0L5s5VvJysvFbUk+siALsYNoldrYF6Al0lV2fTIAmAulE4CZAZVZ1banPRpnnVuNhOtLNqs+WWuFWWV9eKsQzMOu+EllNdaPi8PGu1qSql8yjbVmAHwpNfg9K4uzVFFE9SIKmb81MNZdPNPquffbR88IEEIheHLA9vK6+qbFDFIxSJmols8/xdpHTlXMfhBgu8ukcGF7z7lFH2bKywNo+fDw6UPG82DuRunRR/I7z98kjjxoW86kR2FhngCacc8J9iw7r2RmgH5+nw2TY61/5u84bTgP0N83m9MdHHXctjgb6cuFZIjLhOkId9T8nN2+ZNPKEdiypOAntz1mEF9qasI7+ODYCmPCs2BUUjN3IS1bGgZ/WsYgU1BT0LBXazedmtWrFjLuPecdbuPNI4APY31n9GPAAaeLr5LsHQdnw2bNiASqWCJCkGJalUKhg0aJCXt4wkSbDLLrtsUd6NGzeWLpOqlMKuu+7q5eXf+woeCO2tt97COeecgzvuuAPd3d34+c9/jkmTJvXJffbbbz/ceuutuPbaa/H2229jr732wjnnnIO5c+eiszNfxWDevHl4//vfX3BLnz59Om655RYsW7YMADBhwgT80z/9E+bMmWPPFQRB2JFpa6EdZWvfc7gllL3M2ZcrLkC2RFRzlLuHjbPFRLY3T9uoFhsaTefiTilj1abMCb3Mm/MTBW0s2hQkTSem6JnLT9Uxl7ZfeAA0JMz6SO8oodeAeQDKayd4ysuziJr7NXxvLhHOnhU7ljdIs1bs8HqUnrl9bsW27RKWi1uzI5bNWNfgAxQNibWH9udce/m0n6/0WIRWxXfsOfmW7nhgtEbn82NWp9CW+PteXwR84c6TeD9G4+bu9c9XlTzDmIcKiX7dYETJEJuvvaVkOolWmkR2yj/JHZxcx+26186K3XRtbBsMzVmuw6Bn4WejIGg8b6ydQpFt52c3EOC9sWSXBT3z85SeLuzg7LXXXqXHjj/+ePzHf/yH/T5q1Chs3Lgxmvdv//Zv8dBDD9nvEyZMwJtvvhnNO23aNCtsAWDy5Ml45ZVXonknT56M3//+9/b7+973Pu97X0Hzs9M0RXd3N1555RWcd955uPbaa73Bhq3lsssuw2WXXdYwz913340LLrigkH7FFVfgiiuu6LOyCIIgbG8GntAuodGSWpzC+xOJMuauGLP2eW7kMQEeCGr+Ikwu48rkU0ZAh0I7t6bkhcoyhYRsXLlpzLmRGwsaKoAL4KXze/J1Xmm9Y1DdXNls8Zm4diJDR614SrtrQammS5mVUSaEnQim47pgpS2IxvBc2k9JXGsXEI02npe1hzNkqXwuMdzx3tTNuu2TANOAMoMoYd9S9LzCoGfGE4GEpaubrz5btmBHC1tyXnPdyAZX3O2567jm+UyxvfnYFWWDodklvihPad+D+w3AtUlLYrqFPJ7AZ/vMwBk5iX1qN2WDLKMZELXg2nnV2ll7M0XHciGdURRwleWu4IrEdIZKUCGah20jizOLNrmD16xFO5/DXcuqpWtj5xZtWurLBT1zIttfE7vOrNuURtcE4Fmy+XJbZY9oayKNe0K6wTnRZbzoGWruWQT7bEWAC+0CCf+5c+cCAH784x/jzDPP7JeyvPjii/1yX0EQhG1Newvt0LoXvny3YHUKUVYAuWvyNbpzwcssmcx8VhDbsWuzY8oIVmvVTjIkZqmsJNEFazeg7fWVSpCpzEzXzveVzl++qVgkkK3uz3L3VZXmL4xKw4/czOoMagYuqlVwLKgqiRwrqKg9aN+2r7tOqWgLRLaNKq4DgR2Kcn4+4LlS0zWS1InrJAWSmoYy7ZLUtT2frOUFUc0GHQpW2FZFtxXb7hxvHnbQBrk/NQ00KL99eB0jgxOlbRSWh/K0Antu9ueg4c/V5s+W9x24fU9o2zWzc5GtzZZVmAinNdt5Uaiv83rDF90t1adV2DPny9vZ6QGNrsVFmlbQ5u9JphUSK6oTZFqzIGL5j5Qs0OQu3qOrSJChAvcjrgEmjUUf1+TiXTWfFfTYSOOdVjiH7uJkya6xoGUUAK1uAqaFAptcwwF487HDNbJj7uKxKOBEoux6Cr4FG/CCotF5PBo52HkxC3Vs7WxK59HF7adxg8/7nPL+f9iiAS1hu/KnP/0JQ4cOLXUd56xatar0OuH5L7/8cst5n3vuuYau4xxuCe8rVq1aheXLl2PChAmYNGkS5s+fjwULFvSb0BYEQRiotLfQbsCWiOxCXvPCxQWjJ7a3qny+iCYLdvid5zXfjKWYjudKWillhay2Zs48IXcjV86amOQikiwzoXsvb4NYlGevjQBYd3FzW28cIlp5li98LK08piBP2TXilnHtn8OEu4t4xNK29DGH5zW6FhejYVrkGdkyRvL1GS08h+jzA6zgVLxe/HkHgyuFgYqSzQ1q+DfNo5jDF/IImruknL3CG4DaymtFaOTOnCJBbqvOhWtFpe6YVuhQuaCmpb5IXNPAmxXo5loZEmalrpr0/Np8XWwesIyvo00iO7+H8r5TXcrctaNrZjcQ2XS8VQt2q5RdLbSoe+tjs3IWRLbQFuy2227YbbfdokI7lrc3122V3sy53pbzs6dNm4abbroJ73//+3HzzTdj3LhxuPLKK/v8foIgCDsrbS20NZQfebZMzLAXtN4YHLngLhXb1iqpbT7AaTZ7Xy4QzIu6dRlPMpNH282zaMMFAaL1lvN65/XPX8Kz3DJTySdkh0vQaGioxJQrg7VoQ+viO2IoqAPrY7GxclGq4eqfn6fceWWW6+j13KdnlTUCuNRVPLTKsvOtm7hG7jZu1shO6tpailWqXaTxGMZlvBDwrKQO1k2cTkf+nSyw4fFo/Zn1uhAAzdaL1ZulhxbeQnWaPY/eiofIMw7FtQ77EhfRxmWc1mmnIGjO0g3oSqRQpg+rYFCi4EYenrY1gyhc9EcGBAru7aYsWud/SMjNmJaTSpkVta4TJDpDLasgSbSN1o0EqOjMRgKn1QQqyIAsD5xW0XlnSFTmCV+KIA4APbpqhbMLcJZ4EcUbrY0NwLNcUwA0wHcN5+7jFAwtXDaLC2wA3jGvyVV83ewyGg1aeHPEPas6kGaJGXNTyDK2ZnbGBgRIYPPBIluPPhzsEoRtBM3Ppkjg9957Lw455BBcddVV2GuvvaLzpQVBEITe09ZC27qu6pJlXkoEdkvRx9mLGolbszgVs5hFxLY5N2pRD63VSiNRbk52kjiBnSiNChPggFm1i7+Q0wLayF+kczltJl6TVYbUXcqsL5kTe2WWPs3bqNG7o4Zzec58cV2wbLO0ZlbvuFjWRUFdIrrtmEbmzvXXy4Y/L9u4k8faQ+cjHYW24KKxkWgjl25vCgJICCqXaI8rVz8uqmleNhfQJL5LRLYrbHn5YgMUfQGJbE9sh3nYnGs+L9uKbBLdlbzRomu28/bVfjt6ojukwSBJKZ5VW/vlj10zdg/z3HMxB8+NvK4TVHSGuq6grlMkOkGSVdCZJEAG1FBBTVWQ6ASVJB8kSlSGFIkV2RWV2TqQZdsPYOaW7aJ52NxFPFyyq8xNnIQ8iWuA3MVdOuBbrilv6C7e23WzFTuHhhMyxJdCKxP23F0800BmRHaW5QOVXGjb82jgi8oa3q6PfjuCsC0hi/aUKVMAAGPHjsV9992Hww47DBdffDHGjh2Lk08+uT+LKAiCMCBo7jvVJrTqyt3qEl88X0NByK3UrV6XW7fhhLdn0bau5UZkq3yj4+68YDNlUQmJeb65subLdun8M7LZc5LwGiV1jVnx2LGyx7OlVkXvMZY90iCPZwXW2o8y7l07fsGCNRZbWH7rhupEuD/hOxhEoHMiYjpsh2JdEG2fVr1wS/NF7tX8YvHvngWYfVL/8/pjo34Y6YM6vF6jPhxcp3F5XeV1mJd7gYTErKAlojPfZ8HDkItf69oNFx08PO7mcyfMMl31RLaLFt44onjKywNetvKluLh7eOgyHv6ttuMiuvza2xr+LOiTBz7LE/1jCH+37PcrCDsyJLSnTp1q0/bdd1/MmzcPnZ2dOO200/Doo4/2V/EEQRAGDG1u0WYWhUYWxdIDDZQCs5JrrYwV1ghcbtnWKA+QFhTABT8z7/FKQ3ErdqJRNVbsJMlyixVgrN75PShUS6rgIlIDXiA2lZqAQ9XMrZOdKBNxXLvI482EUthwobg1ddYZCX+VW/mgTD3zfcWvZ02c5nuDMjgRCi8AWqm7eLBP1mtyu3ZWbEDVndimtbNz13JWIIU8EFqivOBX0bbx2sVt1tKawT576NwylrePuZwKrkH1yJQvqk1dnKVbFV3HAX+t8aBNo/cJy4+gnfn1eyOwqb4K1qrtCWET/MwGOmNu4lkVXtRxT4Sz333BW4C+82fZmzLzAkYHjuJry3uDAiaff13zwUQcD8SVZgnSLEGiNHpSoKoqQAVAVkU1S+3yXxVkSJRGqhMMSvJVsjtUBYl96EAF2s7JJgszuY5zF/HeBjuLWbFjruIAPHdxbt0Oo4vH5moTYXCzZvDzeXC02GBGagKzpZmyLuNZppBlSW7NzpzFWxvPA/t3D3AinA+69HbwSRC2M8uXL8eqVaswfvx4jBgxwjt2+OGH45ZbbsFHP/pRnHDCCXj00UcxefLkfiqpIAhC35BmGk8sW41V6zZh1JBBmD5xOCpJ7AWv72lroe296GgYUcdedIOXIL5GdVM8N3DtxDYd08pG0gbg3MjzL/6lmCWZz8tWCgV3cbJMVxLnOk6ukvCEmYZSiblnhjroBT5XdXl6ko9FGIFj19hOXN1axhO3VE8j2smD3Vr2tKccNZzApNs2egQtWWF1kB4IcM+VOhTZxl3cimsaKNDaznst3tw9W62c8G4KLxt59CrSiiq/dzjgYOuhnNUdKCzx5R2PieAykV0msCPnRPO2QiCGvUszA6FOFHQFVrRaoW1Ft/bmxOfCVts+aH76xdsqeP2oaVf3xlcaVzZmIdcsvWBFD082v2NyHc+M2KskuThVSgNJLnaRAqgAPVkVVZUhgcZmVHMRqXIBnEDn7uTQNhga4YKiqUKQMz4HG3DzrssENn0HuLj2g6J50cOZJbuQxkQ2EXMfp7+dsQjjzR5p7Hq2m2t/XrYd7DCDlNoIbpqLnbuMhxZu9kztTbfPf9yCsKWMHz++NOI5AHz4wx9GmqalxwVBENqJ+5e+jsvvfg6vr9lk08YOG4S5sybj2P3HbvP7t73reFkwqd5YFijadytrPjfKwt26eRqdyNfL5q7iBAnt3E1c200B3r73nbmMuyBq7NrGaq7I0mb2lYJNd8cbbawBvO+NFLP/teBZGQiRXntd6vjtuRU8agH3xK92x0rq4AmnyPHoaaHoD8odDgz4W35DWw9+HZanbNwoNlARiuxCecrK35ewNgzFqiah7bW3LgjasNIFQRtcs3h+sIVl4/cPKBPQJOz9ujZpwOAGJPqsAOdWYk1iV6Fm3MFz9+/EWqRtEDMT3MwGOQvSwvWw6bNVke0LbCaSmQD3PqEKYjq0WvdmBYdGecuW7grv68pvBDe1eeZ7GliRrQORXfi9tlx8QRAEQRC2E/cvfR3n37LYE9kAsHLNJpx/y2Lcv/T1bV6GtrZoI1PuxQcAYFyV+UuuzoMMRTVSJJGn5ZZgY+20aQ3cyO01zBuz8q/JxS93F68kuStokmToqGS5RVs5N3KydmfauY5zC3ui3HhJnZWDu5fn0bJZWbmVx40FIKyMC/ijg5dNU0cKDqTyNlHM8pt/atcAOpJGeRUav7A2EYqeuNRwVmpjzYZ21uykrl0EcibKAbihJwVmuVbsu4IdKWGQkZWuaa32ZtBHZayCyjYnlA7aQfvZQot4I0t2KwK7mRW7NH9s4IDn8X5yZi1tVSiOrRi1o7Vc8/0E0FVt97MKrOjWrK/Ydc7ZwIPn+a/QfMAtVndbD/84F/Pcem37TKJ9V3Ll/k54f4BMOXWW968sU0iVArIEtTT/hWdaoaoyZImzIvcojU5dR6YTJCpDPaugmuSWpw6VlrpXe+7SbO41ANR0MXhZTFzT+W4/ic/D1swNnAnzmFU5dBkvE8rN4mrwCOThNXjZUp27iANAPU2su3i9XrEiO7MWbTgrdqZglyX3/r9h0G3Foi0IgiAI/U6aaVx+93Ol9iUF4PK7n8NRk8dsUzfy9hbaBh3otrKXs1Ze2jixF/WCG3lZXi6ySZSThVk50c1dxrm7eDXJ7DF6ieRL23gRdpOMuUnm51tNq1xEY7LS5AKO8vsR0t2YBYlj7aw6IOd8PooApiz9tiokkfhg+33dtRUTYE6Eas913LNmc5FduJirR8EaG/m0xCxeViA7wahYdr6j+H7mzqdBE999nF/AbwevPDytkcCO5Q/SS+8Tg34ovI8pZcWptWAnka1CfSUQsOa6ZHGk4SMvHgDgpkygQT9jP2SNIG9Q7kbWeJ5etKTHG4n+jmRZgiTRSAEkmcoHzpIMPVkFVXPTukrM7z3/k11RCTKVObGrmi93FVv3mruD1zIn8hsJbLpG7Lhm14sFeIsFOGsW9KzR320S2Vxsh9e13V3H3cXzedn5g8sopkWmoNPE/b5ajWvR+n8vgiAIgiBsI55YtrpgyeZoAK+v2YQnlq3GIe8cUZpva2lLoU3zi7K3N9kXWStorcDV3prOdpf5ErfiKu6CLDGLDH+Bi1iGOf762U5oo5LP0dYJzdfWUJUMylioVERoEzYKceYsUKl5SU6ZpSYP6gM4N0jVsD62Tuy4dZ8khRy6UJK1x3xXqXKikJbTqjM36BT2PLvcVuoEpUoBbfJ460Wbda/LrLj8k6zVeYM4gZ1bsvNrJakGKD3157UCyOcOmyBoGRIT6MpY55L8RTwzQiwlC1hink1q9jMmGutw84srvhgLu02Z0EYToa3C/eChbpXQjl3b/dwK1/QGLxoI7YzNy84yt68zDV01t61GhDYrk2sH5bWBVz80oFD24vn8It6zM4MEAPI1vo02g12OTOexERTyaRtV8zfApCulgWoGVTW/90qKJMmgkwxJJQWS/G9CrVJHojR0kkEldaTQyFQGbf5eZCrrhdAuWq0BMyccvRfa3vJXJUKb/lbR3GzKy/M3cgvPAwdqu5+xv+nhQCSvM+DWKM8yE7FdA2lacfOy68parzMjrrXupdA2h7O3N5m6iOIWBEEQhP5i1bpykb0l+baUthTa69atAwC89i9X9XNJBEEQBMFn3bp1GDZsWH8XQxAEQRB2SkYNGdSn+baUthTa48aNw4oVK6C1xvjx47FixQoMHTq0v4vV56xduxZ777231K+NGeh1lPq1PwO9jtuzflprrFu3DuPGjdum9xEEQRAEoZzpE4dj7LBBWLlmU2lolTHD8qW+tiVtKbSTJMFee+2FtWvXAgCGDh06IF8QCalf+zPQ6yj1a38Geh23V/3Eki0IgiAI/UslUZg7azLOv2VxMa6W+Zw7a/I2X0+77Zf3EgRBEARBEARBEATi2P3H4obTp2DMMN89fMywQbjh9CnbZR3ttrRoC4IgCIIgCIIgCEIZx+4/FkdNHoMnlq3GqnWbMGpI7i6+rS3ZRFsL7a6uLsydOxddXV39XZRtgtSv/RnodZT6tT8DvY4DvX6Cj0R8F3YGqJ+rVpbPEYSdnEqitukSXo1QWv5XEgRBEARhB2Pt2rUYNmwY1qxZ03R+fb1ex0svvYSxY8di9913j+bJsgxr167F0KFDkSQyc05oX9auXYtXX30VEyZMwG9+8xscf/zx6Ojo6O9iCUKfUKvVcO+99+6w/bo3/zfJ/zSCIAiCILQ11WoVu+22G1avXo00Tfu7OIKwzdBaY82aNejq6kK12taOqYIw4JFfqCAIgiAIbc/IkSOxYsUKLFu2DMOGDcMuu+yCSqVi3WuzLENPTw82bdokFm2h7dBao1arYc2aNVi/fj323HPP/i6SIAhNEKEtCIIgCELbs+uuu2LixIlYtWoV/vrXv+LNN9/0jmut8fbbb2OXXXaRua1C29LV1YU999wTQ4cORa1W6+/iCILQABHagiAIgiAMCDo7O7HXXntZ61+WZfZYrVbDI488gve///075Lw/QWhGpVKRvisIbUTb+k5df/31mDBhAgYNGoQZM2bgiSee6O8ibRFXXnkl3ve+92HIkCEYNWoUPvShD+HFF1/08mzatAkXXHABRowYgcGDB+PDH/4w3njjjX4q8dZx1VVXQSmFT33qUzZtINTv1Vdfxemnn44RI0Zgl112wXvf+1489dRT9rjWGl/+8pcxduxY7LLLLpg5cyZeeumlfixx66Rpii996UuYOHEidtllF7zzne/EFVdc4UX3bbf6PfLII5g1axbGjRsHpRTuuusu73gr9Vm9ejVOO+00DB06FLvvvjvOOeccrF+/fjvWopxG9avVavjsZz+L9773vdhtt90wbtw4nHnmmXjttde8a7Rr/UL+8R//EUopfOtb3/LSd+T6CVuPUgqdnZ0YNGiQt9Xr9UKabLK1yyYiWxDai7YU2rfddhvmzJmDuXPnYvHixTjwwANxzDHHYNWqVf1dtF7z8MMP44ILLsDjjz+O+fPno1ar4eijj8aGDRtsnn/+53/G3Xffjdtvvx0PP/wwXnvtNZx88sn9WOot48knn8S///u/44ADDvDS271+f/3rX3HYYYeho6MD9913H5577jn827/9G/bYYw+b51//9V9x3XXX4cYbb8TChQux22674ZhjjsGmTZv6seStcfXVV+OGG27Ad77zHTz//PO4+uqr8a//+q/49re/bfO0W/02bNiAAw88ENdff330eCv1Oe200/D73/8e8+fPxz333INHHnkE55133vaqQkMa1W/jxo1YvHgxvvSlL2Hx4sW444478OKLL+KEE07w8rVr/Th33nknHn/8cYwbN65wbEeunyAIgiAIAwDdhkyfPl1fcMEF9nuapnrcuHH6yiuv7MdS9Q2rVq3SAPTDDz+stdb6rbfe0h0dHfr222+3eZ5//nkNQD/22GP9Vcxes27dOj1p0iQ9f/58/bd/+7f6kksu0VoPjPp99rOf1Ycffnjp8SzL9JgxY/TXv/51m/bWW2/prq4u/dOf/nR7FHGr+OAHP6jPPvtsL+3kk0/Wp512mta6/esHQN955532eyv1ee655zQA/eSTT9o89913n1ZK6VdffXW7lb0VwvrFeOKJJzQA/corr2itB0b9/vSnP+k999xTL126VO+zzz76mmuuscfaqX47M2vWrNEA9Jo1a/rkej09Pfquu+7SPT09fXI9QehvpE8LA5EdvV/35v+mtrNo9/T0YNGiRZg5c6ZNS5IEM2fOxGOPPdaPJesb1qxZAwAYPnw4AGDRokWo1Wpefd/znvdg/PjxbVXfCy64AB/84Ae9egADo37z5s3DtGnTcMopp2DUqFE46KCD8P3vf98eX7ZsGVauXOnVcdiwYZgxY0Zb1PHQQw/FggUL8Ic//AEA8N///d949NFHcdxxxwFo//qFtFKfxx57DLvvvjumTZtm88ycORNJkmDhwoXbvcxby5o1a6CUsusPt3v9sizDGWecgUsvvRT77bdf4Xi7108QBEEQhB2ftguG9uabbyJNU4wePdpLHz16NF544YV+KlXfkGUZPvWpT+Gwww7D/vvvDwBYuXIlOjs77QswMXr0aKxcubIfStl7fvazn2Hx4sV48sknC8cGQv3+93//FzfccAPmzJmDz3/+83jyySdx8cUXo7OzE7Nnz7b1iPXZdqjj5z73Oaxduxbvec97UKlUkKYpvvrVr+K0004DgLavX0gr9Vm5ciVGjRrlHa9Wqxg+fHjb1XnTpk347Gc/i49//OMYOnQogPav39VXX41qtYqLL744erzd6ycIgiAIwo5P2wntgcwFF1yApUuX4tFHH+3vovQZK1aswCWXXIL58+dj0KBB/V2cbUKWZZg2bRq+9rWvAQAOOuggLF26FDfeeCNmz57dz6Xben7+85/jJz/5CW699Vbst99+WLJkCT71qU9h3LhxA6J+OzO1Wg0f/ehHobXGDTfc0N/F6RMWLVqEa6+9FosXL5YlnARBEARB6DfaznV85MiRqFQqhajUb7zxBsaMGdNPpdp6LrzwQtxzzz148MEHsddee9n0MWPGoKenB2+99ZaXv13qu2jRIqxatQpTpkxBtVpFtVrFww8/jOuuuw7VahWjR49u6/oBwNixYzF58mQvbd9998Xy5csBwNajXfvspZdeis997nM49dRT8d73vhdnnHEG/vmf/xlXXnklgPavX0gr9RkzZkwh+GK9Xsfq1avbps4ksl955RXMnz/fWrOB9q7ff/7nf2LVqlUYP368/Zvzyiuv4NOf/jQmTJgAoL3rJwiCIAhCe9B2QruzsxNTp07FggULbFqWZViwYAEOOeSQfizZlqG1xoUXXog777wTv/3tbzFx4kTv+NSpU9HR0eHV98UXX8Ty5cvbor5HHnkknn32WSxZssRu06ZNw2mnnWb327l+AHDYYYcVlmT7wx/+gH322QcAMHHiRIwZM8ar49q1a7Fw4cK2qOPGjRuRJP6fikqlYtenbff6hbRSn0MOOQRvvfUWFi1aZPP89re/RZZlmDFjxnYvc28hkf3SSy/hgQcewIgRI7zj7Vy/M844A88884z3N2fcuHG49NJL8etf/xpAe9dPEARBEIT2oC1dx+fMmYPZs2dj2rRpmD59Or71rW9hw4YNOOuss/q7aL3mggsuwK233opf/epXGDJkiJ0fOGzYMOyyyy4YNmwYzjnnHMyZMwfDhw/H0KFDcdFFF+GQQw7BwQcf3M+lb86QIUPsfHNit912w4gRI2x6O9cPyJcnO/TQQ/G1r30NH/3oR/HEE0/ge9/7Hr73ve8BgF03/Ctf+QomTZqEiRMn4ktf+hLGjRuHD33oQ/1b+BaYNWsWvvrVr2L8+PHYb7/98PTTT+Ob3/wmzj77bADtWb/169fjj3/8o/2+bNkyLFmyBMOHD8f48eOb1mfffffFsccei3PPPRc33ngjarUaLrzwQpx66qnRpaS2N43qN3bsWHzkIx/B4sWLcc899yBNU/t3Z/jw4ejs7Gzr+o0fP74wcNDR0YExY8bg3e9+N4Ad//kJOVprAPlAV19Qq9WwceNGrF27VtYjFgYE0qeFgciO3q/p/yT6P6oh2zgC+jbj29/+th4/frzu7OzU06dP148//nh/F2mLABDdfvjDH9o8b7/9tv6nf/onvccee+hdd91Vn3TSSfr111/vv0JvJXx5L60HRv3uvvtuvf/+++uuri79nve8R3/ve9/zjmdZpr/0pS/p0aNH666uLn3kkUfqF198sZ9K2zvWrl2rL7nkEj1+/Hg9aNAg/Y53vEN/4Qtf0Js3b7Z52q1+Dz74YPR3N3v2bK11a/X5y1/+oj/+8Y/rwYMH66FDh+qzzjpLr1u3rh9qU6RR/ZYtW1b6d+fBBx+012jX+sUIl/fSeseun5CzYsWK0r4qm2yyySabbP25rVixoun/Y0rrVuS4IAiCIAjC9iPLMrz22msYMmQIpk+fHl25gvO+972vYZ61a9di7733xooVK7yYBAOBZnVv5/v3xbW35hq9Pbc3+VvJ2yjPQO7TwMDt13113S29zo7cp4Edv19rrbFu3TqMGzeuMLUypC1dxwVBEARBGNgkSWKDg1YqlaYvXK3kAYChQ4fukC9vW0OrdW/H+/fFtbfmGr09tzf5+6pfD8Q+DQzcft1X193S67RDnwZ27H49bNiwlvK1XTA0QRAEQRB2Li644II+yTNQ6e+6b8v798W1t+YavT23N/mlXzemv+u+re7fV9fd0utIn95+iOu4IAiCIAgDnrVr12LYsGFYs2bNDmslEYTeIH1aGIgMpH4tFm1BEARBEAY8XV1dmDt3Lrq6uvq7KILQJ0ifFgYiA6lfi0VbEARBEARBEARBEPoQsWgLgiAIgiAIgiAIQh8iQlsQBEEQBEEQBEEQ+hAR2oIgCIIgCIIgCILQh4jQFgRBEARBEARBEIQ+RIS2IAiCIAiCIAiCIPQhIrQFQRAEQdipueeee/Dud78bkyZNwg9+8IP+Lo4g9AknnXQS9thjD3zkIx/p76IIwlazYsUKHHHEEZg8eTIOOOAA3H777f1dpKbI8l6CIAiCIOy01Ot1TJ48GQ8++CCGDRuGqVOn4ne/+x1GjBjR30UThK3ioYcewrp16/DjH/8Yv/jFL/q7OIKwVbz++ut444030N3djZUrV2Lq1Kn4wx/+gN12262/i1aKWLQFQRAEQdhpeeKJJ7Dffvthzz33xODBg3HcccfhN7/5TX8XSxC2miOOOAJDhgzp72IIQp8wduxYdHd3AwDGjBmDkSNHYvXq1f1bqCaI0BYEQRAEoW155JFHMGvWLIwbNw5KKdx1112FPNdffz0mTJiAQYMGYcaMGXjiiSfssddeew177rmn/b7nnnvi1Vdf3R5FF4RStrZfC8KORl/26UWLFiFNU+y9997buNRbhwhtQRAEQRDalg0bNuDAAw/E9ddfHz1+2223Yc6cOZg7dy4WL16MAw88EMcccwxWrVq1nUsqCK0j/VoYaPRVn169ejXOPPNMfO9739sexd4qRGgLgiAIgtC2HHfccfjKV76Ck046KXr8m9/8Js4991ycddZZmDx5Mm688UbsuuuuuOmmmwAA48aN8yzYr776KsaNG7ddyi4IZWxtvxaEHY2+6NObN2/Ghz70IXzuc5/DoYceur2KvsWI0BYEQRAEYUDS09ODRYsWYebMmTYtSRLMnDkTjz32GABg+vTpWLp0KV599VWsX78e9913H4455pj+KrIgNKWVfi0I7UQrfVprjU984hP4u7/7O5xxxhn9VdReIUJbEARBEIQByZtvvok0TTF69GgvffTo0Vi5ciUAoFqt4t/+7d/wgQ98AN3d3fj0pz8tEceFHZpW+jUAzJw5E6eccgruvfde7LXXXiLChR2WVvr0f/3Xf+G2227DXXfdhe7ubnR3d+PZZ5/tj+K2TLW/CyAIgiAIgtCfnHDCCTjhhBP6uxiC0Kc88MAD/V0EQegzDj/8cGRZ1t/F6BVi0RYEQRAEYUAycuRIVCoVvPHGG176G2+8gTFjxvRTqQRh65B+LQw0BmqfFqEtCIIgCMKApLOzE1OnTsWCBQtsWpZlWLBgAQ455JB+LJkgbDnSr4WBxkDt0+I6LgiCIAhC27J+/Xr88Y9/tN+XLVuGJUuWYPjw4Rg/fjzmzJmD2bNnY9q0aZg+fTq+9a1vYcOGDTjrrLP6sdSC0Bjp18JAY2fs00prrfu7EIIgCIIgCFvCQw89hA984AOF9NmzZ+NHP/oRAOA73/kOvv71r2PlypXo7u7GddddhxkzZmznkgpC60i/FgYaO2OfFqEtCIIgCIIgCIIgCH2IzNEWBEEQBEEQBEEQhD5EhLYgCIIgCIIgCIIg9CEitAVBEARBEARBEAShDxGhLQiCIAiCIAiCIAh9iAhtQRAEQRAEQRAEQehDRGgLgiAIgiAIgiAIQh8iQlsQBEEQBEEQBEEQ+hAR2oIgCIIgCIIgCILQh4jQFgRBEARBEIQBxsaNG1GtVjF48GCkadrfxRGEnQ4R2oIgCIIgCIIwwHj66aeRpimmTJmCSqXS38URhJ0OEdqCIAiCIAiCMMB48sknAQAzZszo55IIws6JCG1BEARBEARBGGCQ0J4+fXo/l0QQdk5EaAuCIAiCIAjCAOOpp54CUBTaGzZswNlnnw2lFKZMmYL/+Z//6Y/iCcKAR2mtdX8XQhAEQRAEQRCEvmHNmjXYY489MGrUKKxcudKmP/PMM/jYxz6GF154Aeeffz6uueYadHV19WNJBWHgIhZtQRAEQRAEQRhAPPXUU9Bae9bsG264ATNmzMC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- "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "PyObject " - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "figure(figsize=(12,6))\n", - "subplot(121)\n", - "imshow(uxc[:,:,5])\n", - "title(L\"U_x\",size=16)\n", - "subplot(122)\n", - "loglog(x,y,\"o\",label=\"Spectrum\");\n", - "loglog(x[5:50],y[5]*x[5:50].^(-5/3)*100,\"k--\",label=L\"k^{-5/3}\")\n", - "ylabel(L\"P_k}\",size=16)\n", - "xlabel(L\"k\",size=16)\n", - "title(L\"Energy Spectrum\",size=16)\n", - "grid()\n", - "legend(fontsize=16)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "quantitative-excellence", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "@webio": { - "lastCommId": "02182625-4c3b-4ac3-8b89-13ff33536a83", - "lastKernelId": "42c7a332-2f19-45de-9027-9f7f688734aa" - }, - "kernelspec": { - "display_name": "Julia (8 threads) 1.7.3", - "language": "julia", - "name": "julia-(8-threads)-1.7" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.7.3" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/example/3D_MHD_OrszagTangVortex_Test.ipynb b/example/3D_MHD_OrszagTangVortex_Test.ipynb deleted file mode 100644 index 94e8068..0000000 --- a/example/3D_MHD_OrszagTangVortex_Test.ipynb +++ /dev/null @@ -1,490 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "dangerous-worcester", - "metadata": {}, - "source": [ - "# 3D MHD Example : Orszag Tang Vortex\n", - "\n", - "In this notebook, we will reproduce the Orszag Tang Vortex using MHDFlows. We follow the setup from [Morales et al. 2014](http://dx.doi.org/10.1016/j.jcp.2014.05.038) Section 6.1" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "presidential-contractor", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Precompiling MHDFlows [top-level]\n", - "└ @ Base loading.jl:1423\n" - ] - } - ], - "source": [ - "using MHDFlows\n", - "using CUDA\n", - "using PyPlot\n", - "using HDF5,FFTW,FourierFlows\n", - "using LinearAlgebra: mul!, ldiv!\n", - "using Statistics" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "formed-syntax", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "CuDevice(0): NVIDIA GeForce RTX 3080" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "device!(0)\n", - "device()" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "little-authorization", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ProblemGeneratorOhm! (generic function with 1 method)" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "function ProblemGeneratorOhm!(prob;L0=2π,β = 0.8)\n", - " # Output Setting \n", - " x = Array(prob.grid.x);\n", - " y = Array(prob.grid.y);\n", - " z = Array(prob.grid.z);\n", - " T = eltype(prob.grid);\n", - " nx,ny,nz = prob.grid.nx,prob.grid.ny,prob.grid.nz;\n", - " @devzeros typeof(CPU()) T (nx,ny,nz) ux uy bx by bz\n", - "\n", - " for k = 1:nz::Int, j = 1:ny::Int\n", - " @simd for i = 1:nx::Int\n", - " ux[i,j,k] = -2*sin(y[j]);\n", - " uy[i,j,k] = 2*sin(x[i]);\n", - " bx[i,j,k] = β*(-2*sin(2y[j]) + sin(z[k]));\n", - " by[i,j,k] = β*(2*sin(x[i]) + sin(z[k]));\n", - " bz[i,j,k] = β*( sin(x[i]) + sin(y[j]));\n", - " end\n", - " end\n", - " SetUpProblemIC!(prob; ux = ux, uy = uy,\n", - " bx = bx, by = by, bz = bz);\n", - " return nothing \n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "periodic-federation", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "MHDFlows Problem\n", - " │ Funtions\n", - " │ ├──────── B-field: ON\n", - " ├─────├────── VP Method: OFF\n", - " │ ├──────────── Dye: OFF\n", - " │ └── user function: OFF\n", - " │ \n", - " │ Features \n", - " │ ├─────────── grid: grid (on GPU)\n", - " │ ├───── parameters: params\n", - " │ ├────── variables: vars\n", - " └─────├─── state vector: sol\n", - " ├─────── equation: eqn\n", - " ├────────── clock: clock\n", - " └──── timestepper: RK4TimeStepper" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#parameters\n", - "N = 128;\n", - "Nz= 128;#div(N,32);\n", - "Lx = 2π;\n", - "ν,η = 0.005,0.005;\n", - "dt = 2.5e-3;\n", - "# Testing the problem \n", - "nothingfunction(args...) = nothing;\n", - "GPUprob = Problem(GPU();\n", - " # Numerical parameters\n", - " nx = N,\n", - " Lx = Lx,\n", - " ny = N,\n", - " nz = Nz,\n", - " # Drag and/or hyper-viscosity for velocity/B-field\n", - " ν = ν,\n", - " nν = 1,\n", - " η = η,\n", - " # B-field & VP method\n", - " B_field = true,\n", - " VP_method = false,\n", - " # Timestepper and equation options\n", - " dt = dt,\n", - " stepper = \"RK4\",\n", - " # Force Driving parameters \n", - " calcF = nothingfunction,\n", - " # Float type and dealiasing\n", - " T = Float32)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "present-newport", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "PyObject " - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ProblemGeneratorOhm!(GPUprob);\n", - "figure(figsize=(12,6))\n", - "subplot(121)\n", - "imshow(Array(GPUprob.vars.ux)[:,:,1])\n", - "title(L\"U_x\");\n", - "colorbar()\n", - "\n", - "subplot(122)\n", - "imshow(Array(GPUprob.vars.bx)[:,:,1])\n", - "title(L\"B_x\");\n", - "colorbar()" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "pressed-disposition", - "metadata": {}, - "outputs": [], - "source": [ - "function Getjmax(prob)\n", - " bx,by,bz = prob.vars.bx,prob.vars.by,prob.vars.bz;\n", - " j1,j2,j3 = Curl(bx,by,bz,prob.grid);\n", - " maxj = √(maximum(j1.^2 .+ j2.^2 .+ j3.^2));\n", - " return maxj;\n", - "end\n", - "maxjs = MHDFlows.Diagnostic(Getjmax, GPUprob,freq=50);" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "wired-cartoon", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "n = 100, t = 0.25, KE = 976.0, ME= 962.0\n", - "n = 200, t = 0.5, KE = 888.0, ME= 1040.0\n", - "n = 300, t = 0.75, KE = 746.0, ME= 1160.0\n", - "n = 400, t = 1.0, KE = 633.0, ME= 1230.0\n", - "n = 500, t = 1.25, KE = 598.0, ME= 1210.0\n", - "n = 600, t = 1.5, KE = 610.0, ME= 1130.0\n", - "n = 700, t = 1.75, KE = 631.0, ME= 1040.0\n", - "n = 800, t = 2.0, KE = 646.0, ME= 934.0\n", - "n = 900, t = 2.25, KE = 629.0, ME= 859.0\n", - "n = 1000, t = 2.5, KE = 577.0, ME= 812.0\n", - "n = 1100, t = 2.75, KE = 514.0, ME= 773.0\n", - "n = 1200, t = 3.0, KE = 459.0, ME= 731.0\n", - "n = 1300, t = 3.25, KE = 416.0, ME= 681.0\n", - "n = 1400, t = 3.5, KE = 381.0, ME= 631.0\n", - "n = 1500, t = 3.75, KE = 345.0, ME= 590.0\n", - "n = 1600, t = 4.0, KE = 313.0, ME= 553.0\n", - "n = 1700, t = 4.25, KE = 289.0, ME= 517.0\n", - "n = 1800, t = 4.5, KE = 272.0, ME= 479.0\n", - "n = 1900, t = 4.75, KE = 259.0, ME= 443.0\n", - "n = 2000, t = 5.0, KE = 245.0, ME= 412.0\n", - "Total CPU/GPU time run = 98.34 s, zone update per second = 4.2651072872e7 \n", - " 98.340027 seconds (43.23 M CPU allocations: 5.533 GiB, 0.69% gc time) (120.88 k GPU allocations: 957.817 GiB, 0.49% memmgmt time)\n" - ] - } - ], - "source": [ - "GPUprob.clock.t = 0\n", - "@CUDA.time TimeIntegrator!(GPUprob, 5.0,50000;\n", - " usr_dt = dt,\n", - " diags = [maxjs],\n", - " loop_number = 100);" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "continued-personal", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(3, 150)" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "n = maxjs.i;\n", - "t = maxjs.t[1:n];\n", - "j = maxjs.data[1:n];\n", - "plot(t,j)\n", - "loglog()\n", - "xlim(0.1,4)\n", - "ylim(3,150)" - ] - }, - { - "cell_type": "markdown", - "id": "another-acrylic", - "metadata": {}, - "source": [ - "# $256^3$ Case" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "equipped-preserve", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "MHDFlows Problem\n", - " │ Funtions\n", - " │ ├──────── B-field: ON\n", - " ├─────├────── VP Method: OFF\n", - " │ ├──────────── Dye: OFF\n", - " │ └── user function: OFF\n", - " │ \n", - " │ Features \n", - " │ ├─────────── grid: grid (on GPU)\n", - " │ ├───── parameters: params\n", - " │ ├────── variables: vars\n", - " └─────├─── state vector: sol\n", - " ├─────── equation: eqn\n", - " ├────────── clock: clock\n", - " └──── timestepper: RK4TimeStepper" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#parameters\n", - "N = 256;\n", - "Nz= 256;#div(N,32);\n", - "Lx = 2π;\n", - "ν,η = 0.001,0.001;\n", - "dt = 2.5e-3;\n", - "# Testing the problem \n", - "nothingfunction(args...) = nothing;\n", - "GPUprob = Problem(GPU();\n", - " # Numerical parameters\n", - " nx = N,\n", - " Lx = Lx,\n", - " ny = N,\n", - " nz = Nz,\n", - " # Drag and/or hyper-viscosity for velocity/B-field\n", - " ν = ν,\n", - " nν = 1,\n", - " η = η,\n", - " # B-field & VP method\n", - " B_field = true,\n", - " VP_method = false,\n", - " # Timestepper and equation options\n", - " dt = dt,\n", - " stepper = \"RK4\",\n", - " # Force Driving parameters \n", - " calcF = nothingfunction,\n", - " # Float type and dealiasing\n", - " T = Float32)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "emerging-english", - "metadata": {}, - "outputs": [], - "source": [ - "function Getjmax(prob)\n", - " bx,by,bz = prob.vars.bx,prob.vars.by,prob.vars.bz;\n", - " j1,j2,j3 = Curl(bx,by,bz,prob.grid);\n", - " maxj = √(maximum(j1.^2 .+ j2.^2 .+ j3.^2));\n", - " return maxj;\n", - "end\n", - "maxjs2 = MHDFlows.Diagnostic(Getjmax, GPUprob,freq=50);" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "overhead-increase", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "n = 100, t = 0.25, KE = 978.0, ME= 965.0\n", - "n = 200, t = 0.5, KE = 892.0, ME= 1050.0\n", - "n = 300, t = 0.75, KE = 752.0, ME= 1180.0\n", - "n = 400, t = 1.0, KE = 646.0, ME= 1280.0\n", - "n = 500, t = 1.25, KE = 628.0, ME= 1280.0\n", - "n = 600, t = 1.5, KE = 660.0, ME= 1220.0\n", - "n = 700, t = 1.75, KE = 702.0, ME= 1140.0\n", - "n = 800, t = 2.0, KE = 734.0, ME= 1060.0\n", - "n = 900, t = 2.25, KE = 719.0, ME= 1010.0\n", - "n = 1000, t = 2.5, KE = 660.0, ME= 990.0\n", - "n = 1100, t = 2.75, KE = 597.0, ME= 955.0\n", - "n = 1200, t = 3.0, KE = 545.0, ME= 905.0\n", - "n = 1300, t = 3.25, KE = 500.0, ME= 849.0\n", - "n = 1400, t = 3.5, KE = 454.0, ME= 797.0\n", - "n = 1500, t = 3.75, KE = 409.0, ME= 752.0\n", - "n = 1600, t = 4.0, KE = 373.0, ME= 708.0\n", - "n = 1700, t = 4.25, KE = 344.0, ME= 666.0\n", - "n = 1800, t = 4.5, KE = 319.0, ME= 628.0\n", - "n = 1900, t = 4.75, KE = 301.0, ME= 590.0\n", - "n = 2000, t = 5.0, KE = 287.0, ME= 553.0\n", - "Total CPU/GPU time run = 714.921 s, zone update per second = 4.693445319e7 \n", - "716.721306 seconds (95.49 M CPU allocations: 8.228 GiB, 0.39% gc time) (120.88 k GPU allocations: 7.426 TiB, 27.89% memmgmt time)\n" - ] - } - ], - "source": [ - "ProblemGeneratorOhm!(GPUprob);\n", - "@CUDA.time TimeIntegrator!(GPUprob, 5.0,50000;\n", - " usr_dt = dt,\n", - " diags = [maxjs2],\n", - " loop_number = 100);" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "impossible-cornell", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(3, 350)" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "n = maxjs2.i;\n", - "t = maxjs2.t[1:n];\n", - "j = maxjs2.data[1:n];\n", - "plot(t,j)\n", - "loglog()\n", - "xlim(0.1,4)\n", - "ylim(3,350)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "silver-egyptian", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Julia 1.7.3", - "language": "julia", - "name": "julia-1.7" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.7.3" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git "a/example/3D_MHD_Orszag\357\200\202TangVortex_Test.ipynb" "b/example/3D_MHD_Orszag\357\200\202TangVortex_Test.ipynb" deleted file mode 100644 index 94e8068..0000000 --- "a/example/3D_MHD_Orszag\357\200\202TangVortex_Test.ipynb" +++ /dev/null @@ -1,490 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "dangerous-worcester", - "metadata": {}, - "source": [ - "# 3D MHD Example : Orszag Tang Vortex\n", - "\n", - "In this notebook, we will reproduce the Orszag Tang Vortex using MHDFlows. We follow the setup from [Morales et al. 2014](http://dx.doi.org/10.1016/j.jcp.2014.05.038) Section 6.1" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "presidential-contractor", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Precompiling MHDFlows [top-level]\n", - "└ @ Base loading.jl:1423\n" - ] - } - ], - "source": [ - "using MHDFlows\n", - "using CUDA\n", - "using PyPlot\n", - "using HDF5,FFTW,FourierFlows\n", - "using LinearAlgebra: mul!, ldiv!\n", - "using Statistics" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "formed-syntax", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "CuDevice(0): NVIDIA GeForce RTX 3080" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "device!(0)\n", - "device()" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "little-authorization", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ProblemGeneratorOhm! (generic function with 1 method)" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "function ProblemGeneratorOhm!(prob;L0=2π,β = 0.8)\n", - " # Output Setting \n", - " x = Array(prob.grid.x);\n", - " y = Array(prob.grid.y);\n", - " z = Array(prob.grid.z);\n", - " T = eltype(prob.grid);\n", - " nx,ny,nz = prob.grid.nx,prob.grid.ny,prob.grid.nz;\n", - " @devzeros typeof(CPU()) T (nx,ny,nz) ux uy bx by bz\n", - "\n", - " for k = 1:nz::Int, j = 1:ny::Int\n", - " @simd for i = 1:nx::Int\n", - " ux[i,j,k] = -2*sin(y[j]);\n", - " uy[i,j,k] = 2*sin(x[i]);\n", - " bx[i,j,k] = β*(-2*sin(2y[j]) + sin(z[k]));\n", - " by[i,j,k] = β*(2*sin(x[i]) + sin(z[k]));\n", - " bz[i,j,k] = β*( sin(x[i]) + sin(y[j]));\n", - " end\n", - " end\n", - " SetUpProblemIC!(prob; ux = ux, uy = uy,\n", - " bx = bx, by = by, bz = bz);\n", - " return nothing \n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "periodic-federation", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "MHDFlows Problem\n", - " │ Funtions\n", - " │ ├──────── B-field: ON\n", - " ├─────├────── VP Method: OFF\n", - " │ ├──────────── Dye: OFF\n", - " │ └── user function: OFF\n", - " │ \n", - " │ Features \n", - " │ ├─────────── grid: grid (on GPU)\n", - " │ ├───── parameters: params\n", - " │ ├────── variables: vars\n", - " └─────├─── state vector: sol\n", - " ├─────── equation: eqn\n", - " ├────────── clock: clock\n", - " └──── timestepper: RK4TimeStepper" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#parameters\n", - "N = 128;\n", - "Nz= 128;#div(N,32);\n", - "Lx = 2π;\n", - "ν,η = 0.005,0.005;\n", - "dt = 2.5e-3;\n", - "# Testing the problem \n", - "nothingfunction(args...) = nothing;\n", - "GPUprob = Problem(GPU();\n", - " # Numerical parameters\n", - " nx = N,\n", - " Lx = Lx,\n", - " ny = N,\n", - " nz = Nz,\n", - " # Drag and/or hyper-viscosity for velocity/B-field\n", - " ν = ν,\n", - " nν = 1,\n", - " η = η,\n", - " # B-field & VP method\n", - " B_field = true,\n", - " VP_method = false,\n", - " # Timestepper and equation options\n", - " dt = dt,\n", - " stepper = \"RK4\",\n", - " # Force Driving parameters \n", - " calcF = nothingfunction,\n", - " # Float type and dealiasing\n", - " T = Float32)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "present-newport", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "PyObject " - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ProblemGeneratorOhm!(GPUprob);\n", - "figure(figsize=(12,6))\n", - "subplot(121)\n", - "imshow(Array(GPUprob.vars.ux)[:,:,1])\n", - "title(L\"U_x\");\n", - "colorbar()\n", - "\n", - "subplot(122)\n", - "imshow(Array(GPUprob.vars.bx)[:,:,1])\n", - "title(L\"B_x\");\n", - "colorbar()" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "pressed-disposition", - "metadata": {}, - "outputs": [], - "source": [ - "function Getjmax(prob)\n", - " bx,by,bz = prob.vars.bx,prob.vars.by,prob.vars.bz;\n", - " j1,j2,j3 = Curl(bx,by,bz,prob.grid);\n", - " maxj = √(maximum(j1.^2 .+ j2.^2 .+ j3.^2));\n", - " return maxj;\n", - "end\n", - "maxjs = MHDFlows.Diagnostic(Getjmax, GPUprob,freq=50);" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "wired-cartoon", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "n = 100, t = 0.25, KE = 976.0, ME= 962.0\n", - "n = 200, t = 0.5, KE = 888.0, ME= 1040.0\n", - "n = 300, t = 0.75, KE = 746.0, ME= 1160.0\n", - "n = 400, t = 1.0, KE = 633.0, ME= 1230.0\n", - "n = 500, t = 1.25, KE = 598.0, ME= 1210.0\n", - "n = 600, t = 1.5, KE = 610.0, ME= 1130.0\n", - "n = 700, t = 1.75, KE = 631.0, ME= 1040.0\n", - "n = 800, t = 2.0, KE = 646.0, ME= 934.0\n", - "n = 900, t = 2.25, KE = 629.0, ME= 859.0\n", - "n = 1000, t = 2.5, KE = 577.0, ME= 812.0\n", - "n = 1100, t = 2.75, KE = 514.0, ME= 773.0\n", - "n = 1200, t = 3.0, KE = 459.0, ME= 731.0\n", - "n = 1300, t = 3.25, KE = 416.0, ME= 681.0\n", - "n = 1400, t = 3.5, KE = 381.0, ME= 631.0\n", - "n = 1500, t = 3.75, KE = 345.0, ME= 590.0\n", - "n = 1600, t = 4.0, KE = 313.0, ME= 553.0\n", - "n = 1700, t = 4.25, KE = 289.0, ME= 517.0\n", - "n = 1800, t = 4.5, KE = 272.0, ME= 479.0\n", - "n = 1900, t = 4.75, KE = 259.0, ME= 443.0\n", - "n = 2000, t = 5.0, KE = 245.0, ME= 412.0\n", - "Total CPU/GPU time run = 98.34 s, zone update per second = 4.2651072872e7 \n", - " 98.340027 seconds (43.23 M CPU allocations: 5.533 GiB, 0.69% gc time) (120.88 k GPU allocations: 957.817 GiB, 0.49% memmgmt time)\n" - ] - } - ], - "source": [ - "GPUprob.clock.t = 0\n", - "@CUDA.time TimeIntegrator!(GPUprob, 5.0,50000;\n", - " usr_dt = dt,\n", - " diags = [maxjs],\n", - " loop_number = 100);" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "continued-personal", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(3, 150)" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "n = maxjs.i;\n", - "t = maxjs.t[1:n];\n", - "j = maxjs.data[1:n];\n", - "plot(t,j)\n", - "loglog()\n", - "xlim(0.1,4)\n", - "ylim(3,150)" - ] - }, - { - "cell_type": "markdown", - "id": "another-acrylic", - "metadata": {}, - "source": [ - "# $256^3$ Case" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "equipped-preserve", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "MHDFlows Problem\n", - " │ Funtions\n", - " │ ├──────── B-field: ON\n", - " ├─────├────── VP Method: OFF\n", - " │ ├──────────── Dye: OFF\n", - " │ └── user function: OFF\n", - " │ \n", - " │ Features \n", - " │ ├─────────── grid: grid (on GPU)\n", - " │ ├───── parameters: params\n", - " │ ├────── variables: vars\n", - " └─────├─── state vector: sol\n", - " ├─────── equation: eqn\n", - " ├────────── clock: clock\n", - " └──── timestepper: RK4TimeStepper" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#parameters\n", - "N = 256;\n", - "Nz= 256;#div(N,32);\n", - "Lx = 2π;\n", - "ν,η = 0.001,0.001;\n", - "dt = 2.5e-3;\n", - "# Testing the problem \n", - "nothingfunction(args...) = nothing;\n", - "GPUprob = Problem(GPU();\n", - " # Numerical parameters\n", - " nx = N,\n", - " Lx = Lx,\n", - " ny = N,\n", - " nz = Nz,\n", - " # Drag and/or hyper-viscosity for velocity/B-field\n", - " ν = ν,\n", - " nν = 1,\n", - " η = η,\n", - " # B-field & VP method\n", - " B_field = true,\n", - " VP_method = false,\n", - " # Timestepper and equation options\n", - " dt = dt,\n", - " stepper = \"RK4\",\n", - " # Force Driving parameters \n", - " calcF = nothingfunction,\n", - " # Float type and dealiasing\n", - " T = Float32)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "emerging-english", - "metadata": {}, - "outputs": [], - "source": [ - "function Getjmax(prob)\n", - " bx,by,bz = prob.vars.bx,prob.vars.by,prob.vars.bz;\n", - " j1,j2,j3 = Curl(bx,by,bz,prob.grid);\n", - " maxj = √(maximum(j1.^2 .+ j2.^2 .+ j3.^2));\n", - " return maxj;\n", - "end\n", - "maxjs2 = MHDFlows.Diagnostic(Getjmax, GPUprob,freq=50);" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "overhead-increase", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "n = 100, t = 0.25, KE = 978.0, ME= 965.0\n", - "n = 200, t = 0.5, KE = 892.0, ME= 1050.0\n", - "n = 300, t = 0.75, KE = 752.0, ME= 1180.0\n", - "n = 400, t = 1.0, KE = 646.0, ME= 1280.0\n", - "n = 500, t = 1.25, KE = 628.0, ME= 1280.0\n", - "n = 600, t = 1.5, KE = 660.0, ME= 1220.0\n", - "n = 700, t = 1.75, KE = 702.0, ME= 1140.0\n", - "n = 800, t = 2.0, KE = 734.0, ME= 1060.0\n", - "n = 900, t = 2.25, KE = 719.0, ME= 1010.0\n", - "n = 1000, t = 2.5, KE = 660.0, ME= 990.0\n", - "n = 1100, t = 2.75, KE = 597.0, ME= 955.0\n", - "n = 1200, t = 3.0, KE = 545.0, ME= 905.0\n", - "n = 1300, t = 3.25, KE = 500.0, ME= 849.0\n", - "n = 1400, t = 3.5, KE = 454.0, ME= 797.0\n", - "n = 1500, t = 3.75, KE = 409.0, ME= 752.0\n", - "n = 1600, t = 4.0, KE = 373.0, ME= 708.0\n", - "n = 1700, t = 4.25, KE = 344.0, ME= 666.0\n", - "n = 1800, t = 4.5, KE = 319.0, ME= 628.0\n", - "n = 1900, t = 4.75, KE = 301.0, ME= 590.0\n", - "n = 2000, t = 5.0, KE = 287.0, ME= 553.0\n", - "Total CPU/GPU time run = 714.921 s, zone update per second = 4.693445319e7 \n", - "716.721306 seconds (95.49 M CPU allocations: 8.228 GiB, 0.39% gc time) (120.88 k GPU allocations: 7.426 TiB, 27.89% memmgmt time)\n" - ] - } - ], - "source": [ - "ProblemGeneratorOhm!(GPUprob);\n", - "@CUDA.time TimeIntegrator!(GPUprob, 5.0,50000;\n", - " usr_dt = dt,\n", - " diags = [maxjs2],\n", - " loop_number = 100);" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "impossible-cornell", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(3, 350)" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "n = maxjs2.i;\n", - "t = maxjs2.t[1:n];\n", - "j = maxjs2.data[1:n];\n", - "plot(t,j)\n", - "loglog()\n", - "xlim(0.1,4)\n", - "ylim(3,350)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "silver-egyptian", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Julia 1.7.3", - "language": "julia", - "name": "julia-1.7" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.7.3" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/example/3D_VP_HDExample.ipynb b/example/3D_VP_HDExample.ipynb deleted file mode 100644 index 63944c1..0000000 --- a/example/3D_VP_HDExample.ipynb +++ /dev/null @@ -1,370 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "martial-chain", - "metadata": {}, - "source": [ - "# 3D Hydro simulation with Volume penalization method\n", - "This notebook aims to show the workflow of setting up a 3D Hydro simulation with Volume penalization method in the cylindrical coordinates. ([Morales et al. 2012](https://www.sciencedirect.com/science/article/pii/S002199911400401X))\n", - "\n", - "We pick the set up of example 1 from ([Morales et al. 2012](https://www.sciencedirect.com/science/article/pii/S002199911400401X)) as a showcase. The result would be slightly different from the ([Morales et al. 2012](https://www.sciencedirect.com/science/article/pii/S002199911400401X)) since the IC setting is not excatly the same but we show similar result, which a vortex has been developed during simulation." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "southern-dining", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: FourierFlows will use 8 threads\n", - "└ @ FourierFlows /home/doraho/.julia/packages/FourierFlows/IWexK/src/FourierFlows.jl:123\n" - ] - } - ], - "source": [ - "using MHDFlows,PyPlot,CUDA\n", - "using Statistics\n", - "using LinearAlgebra: mul!, ldiv!" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "configured-allen", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "CuDevice(1): NVIDIA GeForce RTX 2070 SUPER" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "device!(1)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "expressed-landing", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "MHDFlows Problem\n", - " │ Funtions\n", - " │ ├──────── B-field: OFF\n", - " ├─────├────── VP Method: ON\n", - " │ ├──────────── Dye: OFF\n", - " │ └── user function: OFF\n", - " │ \n", - " │ Features \n", - " │ ├─────────── grid: grid (on GPU)\n", - " │ ├───── parameters: params\n", - " │ ├────── variables: vars\n", - " └─────├─── state vector: sol\n", - " ├─────── equation: eqn\n", - " ├────────── clock: clock\n", - " └──── timestepper: RK4TimeStepper" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#parameters\n", - "N = 128;\n", - "Nz= 128;\n", - "Lx = 2π;\n", - "\n", - "Re = 150;\n", - "Rₑ,Rᵢ = 0.82*pi,0.32*pi\n", - "L = Rₑ - Rᵢ;\n", - "U = 1;\n", - "ν = U*L/Re\n", - "η = ν;\n", - "dt = 5e-3;\n", - "# Testing the problem \n", - "nothingfunction(args...) = nothing;\n", - "GPUprob = Problem(GPU();\n", - " # Numerical parameters\n", - " nx = N,\n", - " Lx = 2π,\n", - " ny = N,\n", - " nz = Nz,\n", - " # Drag and/or hyper-viscosity for velocity/B-field\n", - " ν = ν,\n", - " nν = 1,\n", - " η = η,\n", - " # VP method\n", - " VP_method = true,\n", - " # Timestepper and equation options\n", - " dt = dt,\n", - " stepper = \"RK4\",\n", - " # Force Driving parameters \n", - " calcF = nothingfunction,\n", - " # Float type and dealiasing\n", - " T = Float32)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "sapphire-algebra", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ProblemGeneratorTC3D! (generic function with 1 method)" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "function ProblemGeneratorTC3D!(prob;L0=2π,T=Float32)\n", - "\n", - " # Output Setting \n", - " x = Array(prob.grid.x);\n", - " y = Array(prob.grid.y);\n", - " z = Array(prob.grid.z);\n", - " nx,ny,nz = prob.grid.nx,prob.grid.ny,prob.grid.nz;\n", - " ux,uy,uz = zeros(T,nx,ny,nz),zeros(T,nx,ny,nz),zeros(T,nx,ny,nz);\n", - " U₀x,U₀y,U₀z = zeros(T,nx,ny,nz),zeros(T,nx,ny,nz),zeros(T,nx,ny,nz); \n", - " V₀ = 1;\n", - " r₀ = 0.32π; \n", - " \n", - " # Setup: Uθ = 1 if r ∈ 0.32π\n", - " # Uθ = r(dθ/dt) ê_θ\n", - " # ̂e_θ = - sinθ ̂i + cosθ ̂j; \n", - " χ = Cylindrical_Mask_Function(prob.grid;R₂=0.82π,R₁=r₀);\n", - " copyto!(prob.params.χ,Array(χ));\n", - " for k ∈ 1:nz,j ∈ 1:ny,i ∈ 1:nx\n", - " r = sqrt(x[i]^2+y[j]^2);\n", - " θ = atan(y[j],x[i]) ;\n", - " θ = isnan(θ) ? π/2 : θ\n", - " sinθ = sin(θ);\n", - " cosθ = cos(θ);\n", - " #sinθ = θ < 0 ? sin(-θ) : sin(θ)\n", - " uz[i,j,k] = ifelse(χ[i,j,k], 0,(rand(Float32,1)[1]-0.5)*1e-5);\n", - " if r<=0.32π \n", - " ux[i,j,k] = -r*sinθ;\n", - " uy[i,j,k] = r*cosθ;\n", - " U₀x[i,j,k] = -r*sinθ;\n", - " U₀y[i,j,k] = r*cosθ; \n", - " end \n", - " end\n", - " \n", - " #Update V + B Conponment to Problem\n", - " SetUpProblemIC!(prob; ux = ux, uy = uy, uz = uz,\n", - " U₀x= ux, U₀y= uy);\n", - " \n", - " return nothing\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "suburban-midnight", - "metadata": {}, - "outputs": [], - "source": [ - "# Setting up the Initial condition for both domain\n", - "ProblemGeneratorTC3D!(GPUprob);\n", - "Ux,Uy = Array(GPUprob.params.U₀x),Array(GPUprob.params.U₀y);\n", - "Ur,Uθ = xy_to_polar(Ux,Uy);" - ] - }, - { - "cell_type": "markdown", - "id": "vocal-mission", - "metadata": {}, - "source": [ - "## The Solid Domain and Initial condition illustration" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "steady-speed", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "A = ones(size(Ux));\n", - "χ = Array(GPUprob.params.χ);\n", - "A[χ.==1].=NaN;\n", - "figure(figsize=(12,6))\n", - "subplot(121);\n", - "imshow(χ[:,:,1]);\n", - "title(L\"Domin\\:function\\:\\chi\");\n", - "subplot(122);\n", - "imshow((A.*Uθ)[:,:,1]);\n", - "title(L\"U_\\theta\");" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "political-temple", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "n = 2000, t = 10.0, KE = 7.88\n", - "n = 4000, t = 20.0, KE = 11.0\n", - "n = 6000, t = 30.0, KE = 13.3\n", - "n = 8000, t = 40.0, KE = 14.9\n", - "n = 10000, t = 50.0, KE = 16.0\n", - "n = 12000, t = 60.0, KE = 16.8\n", - "n = 14000, t = 70.0, KE = 17.3\n", - "n = 16000, t = 80.0, KE = 17.7\n", - "n = 18000, t = 90.0, KE = 17.9\n", - "n = 20000, t = 100.0, KE = 18.0\n", - "n = 22000, t = 110.0, KE = 18.1\n", - "n = 24000, t = 120.0, KE = 18.2\n", - "n = 26000, t = 130.0, KE = 18.2\n", - "n = 28000, t = 140.0, KE = 17.6\n", - "n = 30000, t = 150.0, KE = 14.8\n", - "n = 32000, t = 160.0, KE = 13.5\n", - "n = 34000, t = 170.0, KE = 13.1\n", - "n = 36000, t = 180.0, KE = 12.9\n", - "n = 38000, t = 190.0, KE = 12.8\n", - "Total CPU/GPU time run = 4204.205 s, zone update per second = 1.9949408633e7 \n" - ] - } - ], - "source": [ - "# Set up the initial condition\n", - "TimeIntegrator!(GPUprob,200.0,50000;\n", - " usr_dt = dt,\n", - " diags = [],\n", - " loop_number = 2000,\n", - " save = false,\n", - " save_loc = \"\",\n", - " filename = \"\",\n", - " dump_dt = 0)" - ] - }, - { - "cell_type": "markdown", - "id": "relevant-answer", - "metadata": {}, - "source": [ - "# illustration of the result" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "raised-cargo", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "PyObject " - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "iv,jv,kv = Array(GPUprob.vars.ux),Array(GPUprob.vars.uy),Array(GPUprob.vars.uz);\n", - "Ur,Uθ = xy_to_polar(iv,jv);\n", - "\n", - "figure(figsize=(18,6))\n", - "\n", - "subplot(131)\n", - "imshow((A.*kv)[:,64,:]',cmap=\"jet\");colorbar();\n", - "title(L\"U_z\\:(r-z\\:plane)\",size=16)\n", - "\n", - "\n", - "subplot(132)\n", - "title(L\"U_\\theta\\:(r-\\theta\\:plane)\",size=16)\n", - "Uθ2D = (A .*Uθ)[:,:,1];\n", - "meanTA = mean(Uθ2D[.~isnan.(Uθ2D)]);\n", - "stdTA = std(Uθ2D[.~isnan.(Uθ2D)]);\n", - "imshow(Uθ2D,vmin=meanTA-2stdTA,vmax=meanTA+2stdTA,cmap=\"jet\");colorbar()\n", - "\n", - "\n", - "subplot(133)\n", - "title(L\"\\nabla\\times \\vec{v} \\:(r-\\theta\\:plane)\",size=16)\n", - "civ,cjv,ckv = Curl(iv,jv,kv);\n", - "cUr,cUθ = xy_to_polar(civ,cjv);\n", - "cUr2D = (A .*cUr)[:,64,:]';\n", - "meanTA = mean(cUr2D[.~isnan.(cUr2D)]);\n", - "stdTA = std(cUr2D[.~isnan.(cUr2D)]);\n", - "imshow(cUr2D,vmin=meanTA-2stdTA,vmax=meanTA+2stdTA,cmap=\"jet\");colorbar()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c6d54646-d208-4e84-95f0-bf151160b5fc", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Julia (8 threads) 1.7.3", - "language": "julia", - "name": "julia-(8-threads)-1.7" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.7.3" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/example/3D_VP_MHDExample.ipynb b/example/3D_VP_MHDExample.ipynb deleted file mode 100644 index b454ec9..0000000 --- a/example/3D_VP_MHDExample.ipynb +++ /dev/null @@ -1,345 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "understood-update", - "metadata": {}, - "source": [ - "# 3D MHD simulation with Volume penalization method\n", - "This notebook aims to show the workflow of setting up a 3D MHD simulation with Volume penalization method in the cylindrical coordinates. ([Morales et al. 2012](https://www.sciencedirect.com/science/article/pii/S002199911400401X))\n", - "\n", - "We pick the set up of magnetohydrodynamic Taylor-Couette flow (example 5.4) from ([Morales et al. 2012](https://www.sciencedirect.com/science/article/pii/S002199911400401X)) as a showcase. The result would be slightly different from the ([Morales et al. 2012](https://www.sciencedirect.com/science/article/pii/S002199911400401X)) since the IC setting is not excatly the same but we show similar result, which B-field has been curved by the flow." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "brave-worst", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: FourierFlows will use 8 threads\n", - "└ @ FourierFlows /home/doraho/.julia/packages/FourierFlows/IWexK/src/FourierFlows.jl:123\n" - ] - } - ], - "source": [ - "using MHDFlows,PyPlot,CUDA,Statistics\n", - "using LinearAlgebra: mul!, ldiv!" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "successful-intention", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "CuDevice(0): NVIDIA GeForce RTX 3080" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "device()" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "mature-marine", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "MHDFlows Problem\n", - " │ Funtions\n", - " │ ├──────── B-field: ON\n", - " ├─────├────── VP Method: ON\n", - " │ ├──────────── Dye: OFF\n", - " │ └── user function: OFF\n", - " │ \n", - " │ Features \n", - " │ ├─────────── grid: grid (on GPU)\n", - " │ ├───── parameters: params\n", - " │ ├────── variables: vars\n", - " └─────├─── state vector: sol\n", - " ├─────── equation: eqn\n", - " ├────────── clock: clock\n", - " └──── timestepper: RK4TimeStepper" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#parameters\n", - "N = 150;\n", - "Nz= 150;\n", - "Lx = 2π;\n", - "\n", - "Re = 120;\n", - "Rₑ,Rᵢ = 0.82*pi,0.32*pi\n", - "L = Rₑ - Rᵢ;\n", - "U = 1;\n", - "ν = U*L/Re\n", - "η = ν;\n", - "dt = 5e-3;\n", - "\n", - "#Define the mean-field\n", - "Ha = 7\n", - "B0 = √(η*ν)/L*Ha\n", - "\n", - "# Testing the problem \n", - "nothingfunction(args...) = nothing;\n", - "GPUprob = Problem(GPU();\n", - " # Numerical parameters\n", - " nx = N,\n", - " Lx = 2π,\n", - " ny = N,\n", - " nz = Nz,\n", - " # Drag and/or hyper-viscosity for velocity/B-field\n", - " ν = ν,\n", - " nν = 1,\n", - " η = η,\n", - " # B-field & VP method\n", - " B_field = true,\n", - " VP_method = true,\n", - " # Timestepper and equation options\n", - " dt = dt,\n", - " stepper = \"RK4\",\n", - " # Force Driving parameters \n", - " calcF = nothingfunction,\n", - " # Float type and dealiasing\n", - " T = Float32)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "emotional-evolution", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ProblemGeneratorTC3D! (generic function with 1 method)" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "function ProblemGeneratorTC3D!(prob,B0;L0=2π,R₂=0.82π,R₁=0.32π)\n", - " grid = prob.grid;\n", - " \n", - " # Output Setting \n", - " T = eltype(grid);\n", - " x = Array(grid.x);\n", - " y = Array(grid.y);\n", - " z = Array(grid.z);\n", - " nx,ny,nz = grid.nx,grid.ny,grid.nz;\n", - "\n", - " # Define χ\n", - " χ = Cylindrical_Mask_Function(prob.grid; R₂=R₂, R₁=R₁) \n", - " copyto!(prob.params.χ, Array(χ)); \n", - " \n", - " @devzeros typeof(CPU()) T (nx,ny,nz) ux uy uz bz U₀x U₀y\n", - " V₀ = 1;\n", - " r₀ = 0.32π; \n", - " \n", - " # Setup: Uθ = 1 if r ∈ 0.32π\n", - " # Uθ = r(dθ/dt) ê_θ\n", - " # ̂e_θ = - sinθ ̂i + cosθ ̂j; \n", - " for k ∈ 1:nz::Int,j ∈ 1:ny::Int\n", - " @simd for i ∈ 1:nx::Int\n", - " r = sqrt(x[i]^2+y[j]^2);\n", - " θ = atan(y[j],x[i]) ;\n", - " θ = isnan(θ) ? π/2 : θ\n", - " sinθ = sin(θ);\n", - " cosθ = cos(θ);\n", - " #sinθ = θ < 0 ? sin(-θ) : sin(θ)\n", - " uz[i,j,k] = ifelse(χ[i,j,k], 0,(rand(Float32,1)[1]-0.5)*1e-5);\n", - " bz[i,j,k] = B0;\n", - " if r<=0.32π \n", - " ux[i,j,k] = -r*sinθ;\n", - " uy[i,j,k] = r*cosθ;\n", - " U₀x[i,j,k] = -r*sinθ;\n", - " U₀y[i,j,k] = r*cosθ; \n", - " end \n", - " end\n", - " end\n", - " \n", - " # Crypto data \n", - " SetUpProblemIC!(prob; ux = ux, uy = uy, uz = uz,\n", - " bz = bz,\n", - " U₀x=U₀x, U₀y=U₀y,\n", - " B₀z=bz);\n", - " \n", - " return nothing\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "turkish-relay", - "metadata": {}, - "outputs": [], - "source": [ - "# Setting up the Initial condition for both domain\n", - "ProblemGeneratorTC3D!(GPUprob,B0;L0=2π)\n", - "Ux,Uy = Array(GPUprob.params.U₀x),Array(GPUprob.params.U₀y);\n", - "Ur,Uθ = xy_to_polar(Ux,Uy);" - ] - }, - { - "cell_type": "markdown", - "id": "decreased-handle", - "metadata": {}, - "source": [ - "## The Solid Domain and Initial condition illustration" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "forward-liberia", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "A = ones(size(Ux));\n", - "χ = Array(GPUprob.params.χ);\n", - "A[χ.==1].=NaN;\n", - "figure(figsize=(12,6))\n", - "subplot(121);\n", - "imshow(χ[:,:,1]);\n", - "title(L\"Domin\\:function\\:\\chi\");\n", - "subplot(122);\n", - "imshow((A.*Uθ)[:,:,1]);\n", - "title(L\"U_\\theta\");" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "effective-feedback", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "n = 1000, t = 11.0, KE = 8.59, ME= 0.844\n", - "n = 2000, t = 21.9, KE = 12.0, ME= 0.844\n", - "n = 3000, t = 32.8, KE = 14.3, ME= 0.844\n", - "n = 4000, t = 43.8, KE = 15.6, ME= 0.844\n", - "n = 5000, t = 54.7, KE = 16.5, ME= 0.844\n", - "n = 6000, t = 65.6, KE = 16.9, ME= 0.844\n", - "n = 7000, t = 76.5, KE = 17.2, ME= 0.844\n", - "n = 8000, t = 87.4, KE = 17.4, ME= 0.844\n", - "n = 9000, t = 98.3, KE = 17.4, ME= 0.844\n", - "n = 10000, t = 109.0, KE = 17.5, ME= 0.844\n", - "n = 11000, t = 120.0, KE = 17.5, ME= 0.844\n", - "n = 12000, t = 131.0, KE = 17.5, ME= 0.844\n", - "n = 13000, t = 142.0, KE = 17.5, ME= 0.844\n", - "n = 14000, t = 153.0, KE = 17.5, ME= 0.844\n", - "n = 15000, t = 164.0, KE = 17.5, ME= 0.845\n", - "n = 16000, t = 175.0, KE = 17.4, ME= 0.858\n", - "n = 17000, t = 185.0, KE = 16.6, ME= 0.925\n", - "n = 18000, t = 196.0, KE = 15.0, ME= 0.868\n", - "n = 19000, t = 207.0, KE = 14.4, ME= 0.76\n", - "n = 20000, t = 218.0, KE = 14.4, ME= 0.72\n", - "n = 21000, t = 229.0, KE = 14.6, ME= 0.713\n", - "n = 22000, t = 240.0, KE = 14.0, ME= 0.709\n", - "n = 23000, t = 251.0, KE = 13.6, ME= 0.703\n", - "n = 24000, t = 262.0, KE = 13.5, ME= 0.704\n", - "n = 25000, t = 273.0, KE = 13.4, ME= 0.705\n" - ] - } - ], - "source": [ - "# Set up the initial condition\n", - "@CUDA.time TimeIntegrator!(GPUprob, 300.0,500000;\n", - " diags = [],\n", - " loop_number = 1000,\n", - " save = false,\n", - " save_loc = \"\",\n", - " filename = \"\",\n", - " dump_dt = 0)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "bridal-administration", - "metadata": {}, - "outputs": [], - "source": [ - "iv,jv,kv = Array(GPUprob.vars.ux),Array(GPUprob.vars.uy),Array(GPUprob.vars.uz);\n", - "ib,jb,kb = Array(GPUprob.vars.bx),Array(GPUprob.vars.by),Array(GPUprob.vars.bz);\n", - "Ur,Uθ = xy_to_polar(iv,jv);\n", - "\n", - "figure(figsize=(18,6))\n", - "\n", - "subplot(131)\n", - "imshow((A.*kv)[div(N,2),:,:]',cmap=\"jet\");colorbar();\n", - "title(L\"U_z\\:(r-z\\:plane)\",size=16)\n", - "\n", - "\n", - "subplot(132)\n", - "title(L\"U_\\theta\\:(r-\\theta\\:plane)\",size=16)\n", - "Uθ2D = (A .*Uθ)[:,:,30];\n", - "meanTA = mean(Uθ2D[.~isnan.(Uθ2D)]);\n", - "stdTA = std(Uθ2D[.~isnan.(Uθ2D)]);\n", - "imshow(Uθ2D,vmin=meanTA-2stdTA,vmax=meanTA+2stdTA,cmap=\"jet\");colorbar()\n", - "\n", - "\n", - "subplot(133)\n", - "title(L\"B_z\\:(r-z\\:plane)\",size=16)\n", - "imshow((A.*kb)[:,div(N,2),:]',cmap=\"jet\");colorbar();" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Julia (8 threads) 1.7.3", - "language": "julia", - "name": "julia-(8-threads)-1.7" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.7.3" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/example/DiffusionExample.ipynb b/example/DiffusionExample.ipynb deleted file mode 100644 index 4b645ac..0000000 --- a/example/DiffusionExample.ipynb +++ /dev/null @@ -1,238 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "combined-forest", - "metadata": {}, - "source": [ - "# Example 1. Difussion \n", - "\n", - "This example aim to set up a simple diffussion problem for demostrating the workflow of running the problem on CPU and also ploting the result" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "sophisticated-harmony", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: FourierFlows will use 8 threads\n", - "└ @ FourierFlows /home/doraho/.julia/packages/FourierFlows/IWexK/src/FourierFlows.jl:123\n" - ] - } - ], - "source": [ - "using MHDFlows,PyPlot\n", - "using LinearAlgebra: mul!, ldiv!" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "straight-official", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "MHDFlows Problem\n", - " │ Funtions\n", - " │ ├──────── B-field: OFF\n", - " ├─────├────── VP Method: OFF\n", - " │ ├──────────── Dye: OFF\n", - " │ └── user function: OFF\n", - " │ \n", - " │ Features \n", - " │ ├─────────── grid: grid (on CPU)\n", - " │ ├───── parameters: params\n", - " │ ├────── variables: vars\n", - " └─────├─── state vector: sol\n", - " ├─────── equation: eqn\n", - " ├────────── clock: clock\n", - " └──── timestepper: RK4TimeStepper" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Declare the problem on CPU\n", - "CPUprob = Problem(CPU();nx = 32,Lx = 2π,\n", - " ν = 1/10,\n", - " nν = 1,\n", - " η = 1/10, \n", - " # Timestepper and equation options\n", - " dt = 1/50,\n", - " stepper = \"RK4\",\n", - " # Float type and dealiasing\n", - " T = Float64);\n", - "CPUprob" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "executive-canvas", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ProblemGenerator3D! (generic function with 1 method)" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# function of setting up the initial condition\n", - "function ProblemGenerator3D!(prob,L;N = prob.grid.nx)\n", - "\n", - " xx,yy,zz = fill(0.0,N,N,N),fill(0.0,N,N,N),fill(0.0,N,N,N);\n", - " \n", - " for k ∈ 1:N, j ∈ 1:N, i ∈ 1:N\n", - " xx[i,j,k] = prob.grid.x[i];\n", - " yy[i,j,k] = prob.grid.y[j];\n", - " zz[i,j,k] = prob.grid.z[k];\n", - " end\n", - " \n", - " sl=1; sk=1; sm=1; lamlkm=sqrt(sl.^2+sk.^2+sm.^2);\n", - "\n", - " ux = @. -0.5*(lamlkm*sl*cos(sk*xx).*sin(sl*yy).*sin(sm.*zz) +sm*sk*sin(sk*xx).*cos(sl*yy).*cos(sm.*zz));\n", - " uy= @. 0.5*(lamlkm*sk*sin(sk*xx).*cos(sl*yy).*sin(sm.*zz)-sm*sl*cos(sk*xx).*sin(sl*yy).*cos(sm.*zz));\n", - " uz= @. cos(sk*xx).*cos(sl*yy).*sin(sm.*zz);\n", - "\n", - " #Update V + B Conponment to Problem\n", - " SetUpProblemIC!(prob; ux = ux, uy = uy, uz = uz);\n", - "\n", - " return nothing\n", - " \n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "cultural-ordinary", - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "#function for monitoring the energy\n", - "function KEfoo(prob)\n", - " vx,vy,vz = prob.vars.ux,prob.vars.uy,prob.vars.uz;\n", - " return sum(vx.^2+vy.^2 + vz.^2)\n", - "end\n", - "\n", - "KE = MHDFlows.Diagnostic(KEfoo, CPUprob);" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "threaded-review", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Total CPU/GPU time run = 7.531 s, zone update per second = 274123.163 \n" - ] - } - ], - "source": [ - "# Set up the initial condition\n", - "ProblemGenerator3D!(CPUprob,2π);\n", - "\n", - "# Actaul computation\n", - "TimeIntegrator!(CPUprob,5.0,100;\n", - " diags = [KE],\n", - " loop_number = 100,\n", - "\t save = false);" - ] - }, - { - "cell_type": "markdown", - "id": "confirmed-istanbul", - "metadata": {}, - "source": [ - "## Result" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "environmental-cambridge", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "PyObject Text(30.000000000000007, 0.5, 'KE [code unit]')" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "n = KE.i\n", - "t = KE.t[2:n];\n", - "u0 = KE.data[2];\n", - "plot(KE.t[2:n],KE.data[2:n],\"r\",label=L\"U^2\")\n", - "semilogy(KE.t[2:n],exp.(-2*3*(t.-t[1])/10)*u0*0.8,\"k--\",label=L\"OffSet\\:predicted\\:KE\");\n", - "legend()\n", - "xlabel(\"t [code unit]\",size=16)\n", - "ylabel(\"KE [code unit]\",size=16)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "israeli-gothic", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Julia (8 threads) 1.7.3", - "language": "julia", - "name": "julia-(8-threads)-1.7" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.7.3" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/example/DyeExample.ipynb b/example/DyeExample.ipynb deleted file mode 100644 index a871025..0000000 --- a/example/DyeExample.ipynb +++ /dev/null @@ -1,375 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "loaded-ideal", - "metadata": {}, - "source": [ - "# Kelvin Helmholtz instability with Dye module\n", - "In this notebook, we will show how to work out a \"2D\" classical HD simulation using MHDFlows. The Dye module also deployed to illustrate the flow. \n", - "Be careful that the Dye module itself serve as a passive scalar here and the result may not be physical due to the implemention we are using in this version. ($\\rho < 0 $ for some pixel) \n", - "For the video illustration, netvigate to this [youtube link](https://www.youtube.com/watch?v=04psrwxXwbg)." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "chronic-mentor", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: FourierFlows will use 8 threads\n", - "└ @ FourierFlows /home/doraho/.julia/packages/FourierFlows/2BZya/src/FourierFlows.jl:123\n" - ] - } - ], - "source": [ - "using MHDFlows,PyPlot,CUDA\n", - "using LinearAlgebra: mul!, ldiv!" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "numerous-battlefield", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "CuDevice(0): NVIDIA GeForce RTX 3080" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "device()" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "palestinian-hammer", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "MHDFlows Problem\n", - " │ Funtions\n", - " │ ├──────── B-field: OFF\n", - " ├─────├────── VP Method: OFF\n", - " │ ├──────────── Dye: ON, at prob.dye\n", - " │ └── user function: OFF\n", - " │ \n", - " │ Features \n", - " │ ├─────────── grid: grid (on GPU)\n", - " │ ├───── parameters: params\n", - " │ ├────── variables: vars\n", - " └─────├─── state vector: sol\n", - " ├─────── equation: eqn\n", - " ├────────── clock: clock\n", - " └──── timestepper: RK4TimeStepper" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#parameters\n", - "Nx = 3000;\n", - "Ny = 3000;\n", - "Nz = 4;#div(N,32);\n", - "Lx = 2π;\n", - "Ly = 2π;\n", - "Lz = 2π;\n", - "\n", - "Re = 50000;\n", - "U = 0.1;\n", - "ν = U*Lx/Re\n", - "η = ν; # Pr = 1;\n", - "nothingfunction(args...) = nothing;\n", - "GPUprob = Problem(GPU();\n", - " # Numerical parameters\n", - " nx = Nx,\n", - " ny = Ny,\n", - " nz = Nz,\n", - " Lx = Lx,\n", - " Ly = Ly,\n", - " Lz = Lz,\n", - " # Drag and/or hyper-viscosity for velocity/B-field\n", - " ν = ν,\n", - " nν = 0,\n", - " η = η,\n", - " nη = 0,\n", - " # Declare if turn on magnetic field, VP method, Dye module\n", - " B_field = false,\n", - " \t VP_method = false,\n", - " Dye_Module = true,\n", - " # Timestepper and equation options\n", - " stepper = \"RK4\",\n", - " calcF = nothingfunction,\n", - " # Float type and dealiasing\n", - " T = Float32,\n", - " aliased_fraction = 1/3,\n", - " # User defined params/vars\n", - " usr_vars = [],\n", - " usr_params = [],\n", - " usr_func = []) " - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "appointed-learning", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ProblemKH! (generic function with 1 method)" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#Kelvin Helmholtz instability\n", - "function ProblemKH!(prob; T=Float32)\n", - " # Output Setting \n", - " x = Array(prob.grid.x);\n", - " y = Array(prob.grid.y);\n", - " z = Array(prob.grid.z);\n", - " nx,ny,nz = prob.grid.nx,prob.grid.ny,prob.grid.nz;\n", - " ux,uy,uz = zeros(T,nx,ny,nz),zeros(T,nx,ny,nz),zeros(T,nx,ny,nz);\n", - " bx,by,bz = zeros(T,nx,ny,nz),zeros(T,nx,ny,nz),zeros(T,nx,ny,nz);\n", - " U₀x,U₀y,U₀z = zeros(T,nx,ny,nz),zeros(T,nx,ny,nz),zeros(T,nx,ny,nz); \n", - " ρ = zeros(T,nx,ny,nz);\n", - " ρₖ = copy(prob.vars.uxh); \n", - " for k ∈ 1:nz,j ∈ 1:ny,i ∈ 1:nx \n", - " U₀x[i,j,k] = 0; \n", - " U₀y[i,j,k] = 0; \n", - " if (ny/2)+750 >= j >= (ny/2)-750 \n", - " U₀x[i,j,k] += 0.1;\n", - " U₀y[i,j,k] += 1e-5*sin(x[i]);\n", - " ρ[i,j,k] = 1;\n", - " end \n", - " end\n", - " ux,uy,uz = U₀x,U₀y,U₀z;\n", - " \n", - " copyto!(prob.vars.ux, deepcopy(ux));\n", - " copyto!(prob.vars.uy, deepcopy(uy));\n", - " copyto!(prob.vars.uz, deepcopy(uz));\n", - " copyto!(prob.dye.ρ, ρ);\n", - "\n", - "\n", - " #Update V + B Fourier Conponment\n", - " uxh = @view prob.sol[:, :, :, prob.params.ux_ind];\n", - " uyh = @view prob.sol[:, :, :, prob.params.uy_ind];\n", - " uzh = @view prob.sol[:, :, :, prob.params.uz_ind];\n", - " ρh = prob.dye.tmp.sol₀;\n", - "\n", - " mul!(uxh, prob.grid.rfftplan, prob.vars.ux); \n", - " mul!(uyh, prob.grid.rfftplan, prob.vars.uy);\n", - " mul!(uzh, prob.grid.rfftplan, prob.vars.uz);\n", - " mul!(ρh, prob.grid.rfftplan, prob.dye.ρ);\n", - " \n", - " copyto!(prob.vars.uxh, deepcopy(uxh));\n", - " copyto!(prob.vars.uyh, deepcopy(uyh));\n", - " copyto!(prob.vars.uzh, deepcopy(uzh));\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "martial-allowance", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "PyObject " - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#Setting up and Plotting the IC\n", - "ProblemKH!(GPUprob;T=Float32);\n", - "\n", - "figure(figsize=(12,6))\n", - "subplot(121);title(\"v_x\")\n", - "imshow(Array(GPUprob.vars.ux[:,:,1])');colorbar()\n", - "subplot(122);title(\"dye\")\n", - "ρ = GPUprob.dye.ρ;\n", - "imshow(Array(ρ[:,:,1])');colorbar()" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "about-aquatic", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "n = 500, t = 102.0, KE = 0.00162\n", - "n = 1000, t = 104.0, KE = 0.00162\n", - "n = 1500, t = 106.0, KE = 0.00162\n", - "n = 2000, t = 108.0, KE = 0.00162\n", - "n = 2500, t = 109.0, KE = 0.00162\n", - "n = 3000, t = 111.0, KE = 0.00162\n", - "n = 3500, t = 113.0, KE = 0.00162\n", - "n = 4000, t = 115.0, KE = 0.00162\n", - "n = 4500, t = 117.0, KE = 0.00162\n", - "n = 5000, t = 119.0, KE = 0.00162\n", - "n = 5500, t = 120.0, KE = 0.00162\n", - "n = 6000, t = 122.0, KE = 0.00162\n", - "n = 6500, t = 124.0, KE = 0.00162\n", - "n = 7000, t = 126.0, KE = 0.00162\n", - "n = 7500, t = 128.0, KE = 0.00162\n", - "n = 8000, t = 130.0, KE = 0.00162\n", - "n = 8500, t = 132.0, KE = 0.00162\n", - "n = 9000, t = 134.0, KE = 0.00162\n", - "n = 9500, t = 136.0, KE = 0.00162\n", - "n = 10000, t = 138.0, KE = 0.00162\n", - "n = 10500, t = 139.0, KE = 0.00162\n", - "n = 11000, t = 141.0, KE = 0.00162\n", - "n = 11500, t = 143.0, KE = 0.00162\n", - "n = 12000, t = 145.0, KE = 0.00162\n", - "n = 12500, t = 147.0, KE = 0.00162\n", - "n = 13000, t = 148.0, KE = 0.00162\n", - "n = 13500, t = 150.0, KE = 0.00162\n", - "n = 14000, t = 152.0, KE = 0.00162\n", - "n = 14500, t = 154.0, KE = 0.00162\n", - "n = 15000, t = 156.0, KE = 0.00162\n", - "n = 15500, t = 158.0, KE = 0.00162\n", - "n = 16000, t = 159.0, KE = 0.00162\n", - "n = 16500, t = 161.0, KE = 0.00162\n", - "n = 17000, t = 163.0, KE = 0.00162\n", - "n = 17500, t = 165.0, KE = 0.00162\n", - "n = 18000, t = 166.0, KE = 0.00162\n", - "n = 18500, t = 168.0, KE = 0.00162\n", - "n = 19000, t = 170.0, KE = 0.00162\n", - "n = 19500, t = 172.0, KE = 0.00162\n", - "n = 20000, t = 173.0, KE = 0.00162\n", - "n = 20500, t = 175.0, KE = 0.00162\n", - "n = 21000, t = 176.0, KE = 0.00162\n", - "n = 21500, t = 178.0, KE = 0.00162\n", - "n = 22000, t = 180.0, KE = 0.00162\n", - "n = 22500, t = 181.0, KE = 0.00161\n", - "n = 23000, t = 183.0, KE = 0.00161\n", - "n = 23500, t = 185.0, KE = 0.00161\n", - "n = 24000, t = 186.0, KE = 0.00161\n", - "n = 24500, t = 188.0, KE = 0.00161\n", - "n = 25000, t = 190.0, KE = 0.00161\n", - "n = 25500, t = 191.0, KE = 0.00161\n", - "n = 26000, t = 193.0, KE = 0.00161\n", - "n = 26500, t = 195.0, KE = 0.00161\n", - "n = 27000, t = 196.0, KE = 0.00161\n", - "n = 27500, t = 198.0, KE = 0.00161\n", - "n = 28000, t = 200.0, KE = 0.00161\n" - ] - } - ], - "source": [ - "#Actual Computation\n", - "TimeIntegrator!(GPUprob, 200.0, 80000;loop_number = 500,\n", - " save = true,\n", - "\t\t\t\t save_loc = \"/mnt/c/data/Pipe/\",\n", - "\t\t\t\t filename = \"P1_\",\n", - " file_number = 199,\n", - "\t\t\t\t dump_dt = 0.5);" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "automatic-windows", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "PyObject " - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "iv,jv,kv = Array(GPUprob.vars.ux),Array(GPUprob.vars.uy),Array(GPUprob.vars.uz)\n", - "cvx,cvy,cvz = Curl(iv,jv,kv);\n", - "figure(figsize=(18,9))\n", - "subplot(121);title(L\"\\nabla \\times \\vec{v}\")\n", - "imshow(cvz[:,:,1]');colorbar()\n", - "subplot(122);title(\"dye\")\n", - "ρ = GPUprob.dye.ρ;\n", - "imshow(Array(ρ[:,:,1])',vmin=0,vmax=1);colorbar()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "pediatric-organic", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Julia (8 threads) 1.7.3", - "language": "julia", - "name": "julia-(8-threads)-1.7" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.7.3" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/example/DynamoExample.ipynb b/example/DynamoExample.ipynb deleted file mode 100644 index 3891ac0..0000000 --- a/example/DynamoExample.ipynb +++ /dev/null @@ -1,322 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "bigger-interstate", - "metadata": {}, - "source": [ - "# Example 3: Dyanmo with Forcing\n", - "This example aim to show the implmentation of force module using the MHD solver. The idea of force module is coming from [ApJ..626..853](https://ui.adsabs.harvard.edu/abs/2005ApJ...626..853M/abstract) but more simplified version in this notebook. \n", - "\n", - "The result of interation between the force and velocity field would resulting the amplification of weak magnetic field, which usually called the dynamo effect. The example is running on GPU with the resolution of $64^3$. Beaware that the result may not converge on higher resolution, which require the modification of the force module. " - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "second-bacon", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: FourierFlows will use 8 threads\n", - "└ @ FourierFlows /home/doraho/.julia/packages/FourierFlows/IWexK/src/FourierFlows.jl:123\n" - ] - } - ], - "source": [ - "using MHDFlows,PyPlot,CUDA\n", - "using LinearAlgebra: mul!, ldiv!" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "imposed-inventory", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "CuDevice(0): NVIDIA GeForce RTX 3080" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "device()" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "adequate-daughter", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "AddForceGPU! (generic function with 1 method)" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#force module\n", - "#GPU version\n", - "function AddForceGPU!(N, sol, t, clock, vars, params, grid)\n", - " # ∂u_ih∂t + Fv_TG, here we assume F is some constant\n", - " F0 = 1.37;\n", - " N0 = grid.nx;\n", - " l = 2;\n", - " T = eltype(grid);\n", - " fx,fy,fz = zeros(T,N0,N0,N0),zeros(T,N0,N0,N0),zeros(T,N0,N0,N0);\n", - " # Real Space Computation of force function\n", - " for k ∈ 1:N0, j ∈ 1:N0, i ∈ 1:N0\n", - " xx = l*grid.x[i];\n", - " yy = l*grid.y[j];\n", - " zz = l*grid.z[k];\n", - " # f = F*v_TG\n", - " fx[i,j,k] = sin(xx)*cos(yy)*cos(zz);\n", - " fy[i,j,k] = -cos(xx)*sin(yy)*cos(zz);\n", - " fz[i,j,k] = 0;\n", - " end\n", - "\n", - " for (u_ind,f_i) ∈ zip([params.ux_ind,params.uy_ind,params.uz_ind],[fx,fy,fz])\n", - " @. vars.nonlinh1*=0;\n", - " copyto!(vars.nonlin1, F0.*f_i);\n", - " fk_i = vars.nonlinh1;\n", - " @. fk_i*=0;\n", - " mul!(fk_i, grid.rfftplan, vars.nonlin1); \n", - " @. N[:,:,:,u_ind] += fk_i;\n", - " end\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "fresh-rubber", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "MHDFlows Problem\n", - " │ Funtions\n", - " │ ├──────── B-field: ON\n", - " ├─────├────── VP Method: OFF\n", - " │ ├──────────── Dye: OFF\n", - " │ └── user function: OFF\n", - " │ \n", - " │ Features \n", - " │ ├─────────── grid: grid (on GPU)\n", - " │ ├───── parameters: params\n", - " │ ├────── variables: vars\n", - " └─────├─── state vector: sol\n", - " ├─────── equation: eqn\n", - " ├────────── clock: clock\n", - " └──── timestepper: RK4TimeStepper" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#parameters\n", - "N = 64;\n", - "Lx = 2π;\n", - "ν,η = 2e-3,5e-3;\n", - "dt = 1/50;\n", - "\n", - "# Testing the problem\n", - "# Declare the problem on GPU\n", - "GPUprob = Problem(GPU();nx = N,\n", - " Lx = Lx,\n", - " ν = ν,\n", - " nν = 1,\n", - " #B-field \n", - " B_field = true,\n", - " # Timestepper and equation options\n", - " dt = dt,\n", - " stepper = \"RK4\",\n", - " calcF = AddForceGPU!,\n", - " # Float type and dealiasing\n", - " T = Float32);\n", - "GPUprob" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "driving-lithuania", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ProblemGeneratorTG! (generic function with 1 method)" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "function ProblemGeneratorTG!(prob,L0,N)\n", - "\n", - " # Output Setting \n", - " xx,yy,zz = fill(0.0,N,N,N),fill(0.0,N,N,N),fill(0.0,N,N,N);\n", - " \n", - " l = 2*2*π/L0; \n", - " for k ∈ 1:N, j ∈ 1:N, i ∈ 1:N\n", - " xx[i,j,k] = l*prob.grid.x[i];\n", - " yy[i,j,k] = l*prob.grid.y[j];\n", - " zz[i,j,k] = l*prob.grid.z[k];\n", - " end\n", - " \n", - " ux = @. sin(xx)*cos(yy)*cos(zz);\n", - " uy = @. -cos(xx)*sin(yy)*cos(zz);\n", - " uz = @. fill(0.0,N,N,N);\n", - "\n", - " bx = @. sqrt(1e-3)*ux;\n", - " by = @. sqrt(1e-3)*uy;\n", - " bz = @. sqrt(1e-3)*uz; \n", - " \n", - " # Crypto data \n", - " SetUpProblemIC!(prob; ux = ux, uy = uy, uz = uz,\n", - " bx = bx, by = by, bz = bz);\n", - " return nothing\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "rotary-efficiency", - "metadata": {}, - "outputs": [], - "source": [ - "#function for monitoring the energy\n", - "function KEfoo(prob)\n", - " vx,vy,vz = prob.vars.ux,prob.vars.uy,prob.vars.uz;\n", - " return sum(vx.^2+vy.^2 + vz.^2)\n", - "end\n", - "\n", - "function MEfoo(prob)\n", - " bx,by,bz = prob.vars.bx,prob.vars.by,prob.vars.bz;\n", - " return sum(bx.^2+by.^2 + bz.^2)\n", - "end\n", - "\n", - "KE = Diagnostic(KEfoo, GPUprob);\n", - "ME = Diagnostic(MEfoo, GPUprob);" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "graduate-ocean", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "n = 100, t = 2.0, KE = 391.0, ME= 3.96\n", - "n = 200, t = 4.0, KE = 402.0, ME= 197.0\n", - "n = 300, t = 6.0, KE = 377.0, ME= 213.0\n", - "n = 400, t = 8.0, KE = 374.0, ME= 210.0\n", - "n = 500, t = 10.0, KE = 367.0, ME= 207.0\n", - "n = 600, t = 12.0, KE = 364.0, ME= 206.0\n", - "n = 700, t = 14.0, KE = 367.0, ME= 204.0\n", - "n = 800, t = 16.0, KE = 363.0, ME= 210.0\n", - "n = 900, t = 18.0, KE = 356.0, ME= 213.0\n", - "n = 1000, t = 20.0, KE = 350.0, ME= 220.0\n", - "Total CPU/GPU time run = 60.307 s, zone update per second = 4.346808769e6 \n", - " 62.111720 seconds (69.27 M CPU allocations: 51.789 GiB, 5.48% gc time) (86.14 k GPU allocations: 82.377 GiB, 0.43% memmgmt time)\n" - ] - } - ], - "source": [ - "#GPU for 64^3\n", - "L0 = 2;\n", - "ProblemGeneratorTG!(GPUprob,L0,N)\n", - "\n", - "CUDA.@time TimeIntegrator!(GPUprob,20.0,1000;\n", - " usr_dt = dt,\n", - " diags = [KE,ME],\n", - " loop_number = 100,\n", - " save = false,\n", - " save_loc = \"\",\n", - " filename = \"\",\n", - " dump_dt = 0)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "corresponding-globe", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "PyObject Text(30.000000000000014, 0.5, 'Energy [code unit]')" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "n = KE.i;\n", - "t = KE.t[2:n];\n", - "uu = KE.data[2:n];\n", - "bb = ME.data[2:n];\n", - "\n", - "semilogy(t,uu.*(GPUprob.grid.dx)^6,\"r\",label=L\"U^2\")\n", - "semilogy(t,bb.*(GPUprob.grid.dx)^6,\"b\",label=L\"B^2\")\n", - "legend()\n", - "xlabel(\"t [code unit]\",size=16)\n", - "ylabel(\"Energy [code unit]\",size=16)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Julia (8 threads) 1.7.3", - "language": "julia", - "name": "julia-(8-threads)-1.7" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.7.3" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/example/GPUExample.ipynb b/example/GPUExample.ipynb deleted file mode 100644 index 95b44a3..0000000 --- a/example/GPUExample.ipynb +++ /dev/null @@ -1,459 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "aging-failing", - "metadata": {}, - "source": [ - "# Example 2: Taylor Green Vortices on GPU" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "indonesian-remains", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: FourierFlows will use 8 threads\n", - "└ @ FourierFlows /home/doraho/.julia/packages/FourierFlows/IWexK/src/FourierFlows.jl:123\n" - ] - } - ], - "source": [ - "using MHDFlows,PyPlot,CUDA\n", - "using LinearAlgebra: mul!, ldiv!" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "static-louisiana", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "CuDevice(0): NVIDIA GeForce RTX 3080" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "device()" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "egyptian-windows", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ProblemGeneratorTG! (generic function with 1 method)" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "function ProblemGeneratorTG!(prob,L0;N = prob.grid.nx)\n", - " \n", - " # Output Setting \n", - " xx,yy,zz = fill(0.0,N,N,N),fill(0.0,N,N,N),fill(0.0,N,N,N);\n", - " \n", - " l = 2*2*π/L0;\n", - " \n", - " for k ∈ 1:N, j ∈ 1:N, i ∈ 1:N\n", - " xx[i,j,k] = l*prob.grid.x[i];\n", - " yy[i,j,k] = l*prob.grid.y[j];\n", - " zz[i,j,k] = l*prob.grid.z[k];\n", - " end\n", - " \n", - " sl=1; sk=1; sm=1; lamlkm=sqrt(sl.^2+sk.^2+sm.^2);\n", - "\n", - " ux = @. -0.5*(lamlkm*sl*cos(sk*xx).*sin(sl*yy).*sin(sm.*zz) + sm*sk*sin(sk*xx).*cos(sl*yy).*cos(sm.*zz));\n", - " uy= @. 0.5*(lamlkm*sk*sin(sk*xx).*cos(sl*yy).*sin(sm.*zz) - sm*sl*cos(sk*xx).*sin(sl*yy).*cos(sm.*zz));\n", - " uz= @. cos(sk*xx).*cos(sl*yy).*sin(sm.*zz);\n", - "\n", - " bx = @. sin(yy)*sin(zz);\n", - " by = @. sin(zz);\n", - " bz = @. cos(xx)*cos(yy);\n", - " \n", - " # Crypto data \n", - " SetUpProblemIC!(prob; ux = ux, uy = uy, uz = uz,\n", - " bx = bx, by = by, bz = bz);\n", - " \n", - " return nothing\n", - "end\n" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "found-kenya", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "MHDFlows Problem\n", - " │ Funtions\n", - " │ ├──────── B-field: ON\n", - " ├─────├────── VP Method: OFF\n", - " │ ├──────────── Dye: OFF\n", - " │ └── user function: OFF\n", - " │ \n", - " │ Features \n", - " │ ├─────────── grid: grid (on GPU)\n", - " │ ├───── parameters: params\n", - " │ ├────── variables: vars\n", - " └─────├─── state vector: sol\n", - " ├─────── equation: eqn\n", - " ├────────── clock: clock\n", - " └──── timestepper: RK4TimeStepper" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#Simulation's parameters\n", - "N = 128;\n", - "Lx = 2π;\n", - "ν,η = 1/100,1/100;\n", - "dt = 1/50;\n", - "\n", - "# Testing the problem\n", - "# Declare the problem on GPU\n", - "GPUprob = Problem(GPU();nx = N,Lx = Lx,\n", - " ν = ν,\n", - " nν = 1,\n", - " η = η, \n", - " # Timestepper and equation options\n", - " dt = 1/50,\n", - " stepper = \"RK4\",\n", - " B_field = true,\n", - " VP_method = false,\n", - " Dye_Module = false,\n", - " # Float type and dealiasing\n", - " T = Float64);\n", - "GPUprob" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "white-action", - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "#function for monitoring the energy\n", - "function KEfoo(prob)\n", - " vx,vy,vz = prob.vars.ux,prob.vars.uy,prob.vars.uz;\n", - " return sum(vx.^2+vy.^2 + vz.^2)\n", - "end\n", - "\n", - "function MEfoo(prob)\n", - " bx,by,bz = prob.vars.bx,prob.vars.by,prob.vars.bz;\n", - " return sum(bx.^2+by.^2 + bz.^2)\n", - "end\n", - "\n", - "KE = Diagnostic(KEfoo, GPUprob);\n", - "ME = Diagnostic(MEfoo, GPUprob);" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "lovely-mathematics", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "n = 100, t = 0.725, KE = 92.9, ME= 201.0\n", - "n = 200, t = 1.43, KE = 105.0, ME= 127.0\n", - "n = 300, t = 2.53, KE = 76.0, ME= 71.6\n", - "n = 400, t = 3.77, KE = 47.8, ME= 40.4\n", - "Total CPU/GPU time run = 88.179 s, zone update per second = 1.1273083666e7 \n" - ] - } - ], - "source": [ - "# Set up the initial condition\n", - "ProblemGeneratorTG!(GPUprob,2π);\n", - "\n", - "# Actaul computation\n", - "TimeIntegrator!(GPUprob,5.0,1000;\n", - " diags = [KE,ME],\n", - " loop_number = 100,\n", - "\t save = false);" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "raising-sailing", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "PyObject Text(30.00000000000002, 0.5, 'Energy [code unit]')" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "n = KE.i\n", - "t = KE.t[2:n];\n", - "uu = KE.data[2:n];\n", - "bb = ME.data[2:n];\n", - "\n", - "\n", - "semilogy(t,uu+bb,\"k\",label=L\"Etot\")\n", - "semilogy(t,uu,\"r\",label=L\"U^2\")\n", - "semilogy(t,bb,\"b\",label=L\"B^2\")\n", - "legend()\n", - "xlabel(\"t [code unit]\",size=16)\n", - "ylabel(\"Energy [code unit]\",size=16)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "affecting-contemporary", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Effective GPU memory usage: 100.00% (10.000 GiB/10.000 GiB)\n", - "Memory pool usage: 988.253 MiB (9.312 GiB reserved)Effective GPU memory usage: 21.73% (2.173 GiB/10.000 GiB)\n", - "Memory pool usage: 972.253 MiB (1.031 GiB reserved)" - ] - } - ], - "source": [ - "CUDA.memory_status()\n", - "CUDA.reclaim()\n", - "GC.gc(true)\n", - "CUDA.memory_status()" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "voluntary-printer", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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TMhAdsP48VTpwh1GpvYWbQO1ZErqOXwkeU4JqACadEkJYG+DaOPT8w8Z7GR42HtnvbHs6Ni7nx33uPe2XVBVQFfBq+ieRySKi4035JGOsLI4IOo9Opd752aCdeGFchLB2APkbO7vpPgTkTZJp2dllkkIGTT5LIOjbr0kG5NkKkMhVvyzZQZROMBC77EGEiWUaNyUHKdm+wcaBa8Ug4++DwJ0Alh9k06EMBHODSK+uPSQD2I0juXYrMq+PwO7PJJOmv73GUHdNIIXj8agBKPb1VNSueNWJChtw2Ljfk2d72PiTt3Fuj7vHJ/2SWr5VUWpDvdU3M58FddXldhLQCl2+AVo1xtl0H1jB2xoU7KcGl0vEg1AIEfSYbSKnPByKkPEV0e0+LlhmXCF/CGyeGthy//XtZMdnYHcDSXfjjQk5s5zaiwCuIEbCLgJamjLMIliWCmZBKQ0LtwCvj3JdmwVjxnVZibl7nMXFEI0PoT8XWt4//e2leI7OIzMmc/vapQ5K2ySyyW0BxEAMuazdT2yxl72YPCV6jABUm9WPbWvOSGWbX348cpZJKlsxq1ksOg6N2m3fdtj4YeN6yvOxcazrhYIZ05N+SZW7hkKKTGECL2SyiI7OrJ/qvbq7qyTB59YhIhALWpouGU0Zq3sAbTqc87LQ4xlnBrMbtQGZ0nIGbR50MpgnMLEwdz2WbtCD1WYQo2v0Bl7mhmVp+sstpg3P8wIV1jmFfKRqtUlGDY1jevadRocEG9b2mBSAy4/sy+nS4zalwcFKMTXCXrWM6wNdGnAHfT6D10FepQM3AxnYgtlZMdloDoUAaiAiSG0BZmpFZZEqh40fNj4WyTOwca6PG2H2Sb+kqDbQqkYmLGhgsEfrE4X7rqyiTNLdeUl/abWyFOpR1DZwZOjD7AxHuyQ3kfmJZbphDTLBnnHnlEGf8unbxks9rmD6X2aY8RsdyVp2pQgKK2gLC06lKs6nCwoJ9kjZeBC2jcx07w89h7eXu7JHfkbBpm3N52/1mnzMdUnkUmMTDesei9xjmiaRTFfXH9PuSTrjJDCkNVAhfQupyH/Y+JwOG3/yNu4u7A+lJ/2SKt9eUdoZtBYF6Lmh1gIhgE8Mtg46XoG6OqMg1FuELMIVaBZr1RpATGgwWYRJP/eL1abFqyhR7V5Bzn8ym4mAQjvWWgrbRlujzEa/w84C6Dv1GrsSaIXsGVm0j6JAf0/q5cSL4HSqyixLwxs3ZxRuOHHDqVSwP5NJOvet4GyXX6tPvy39wum+/d6zrLO3X59NBqAM4I1GECGJDEWQjnUK6ef0U2moH8GYb1DPXNYpRWdykkBCm28ysEtarXlrzV3C+h/6+T1z//oxIBMBZwYx6deUS38LHzZ+2Pizs3Gu99uK3klP+iVF5wqiFWyfl60VxVhMc8xqtDZkbysmjRBp9DNb/3IjSBGwBaCRzywpAIoaoI+P5jWcPVEzkJUVUTA6HU5mnyhFumA8GwnkaiaYWCUs+hsh+4BG+aOUhsINN0vFTam6zFUBnG5mnI6bUFhwrjuM2xuadK+Zre0934PP4+cZiHWzbM+dWWdex8g295jpbsrHZOB557Ek+cO9oZxVtqb7M2hnHd9vvQLRU0/NAiAJ1IpGQLZ22HjcyGHjz8bG62vQJ4W1grjFwzMRGmvtBBjNsykinQ3EPiEXFWVDssKGnUqyiHlJhT14h6yoQcwhEwrUFKlBBJ9SGcZqB2ZjIHdGGp/+6ZjQ4dEH+cxJvKFIwFWG6YM72nOwREcys4CLssmlNNwsK26XFYVUr7/hFUwSwG1grMRDB3q+ATHAkncmO4AzoZpB/BgApWfcAG4i3RvQpnU9gHbB88op7n8HlJe25fU2Hev3BlFphGiQRrSx4MPGDxt/djZO7UFhFcATf0nR/b2yzbUAhYG1gdcGFAJV0X2kb3H3zafmyxKf6mLR0VTN2KGyCApB0JRlFiDoIquxCiTcWOOezE5YBOKCQhhRslur0/hUF1uygEifd4Vgde2f5FOK2TEJnVESIIs+ixQBFgGWph5Op4plUeC+eXuPEzfclhVvne60Q5l0HdApwddW0EBoIFQLyMmd6BLMkmIUBA/U3MggaVmBfgFQA/CQ2KIXnZVRFNAWtHsgHvT/3JDm624KON2nSxpeH63/UpY/WgPVJIv4su3LeW2fnfTriQhUa18/bPyw8edm4+1xw6A/6ZcUagOompFbtboOD6iGTwCzBuR5pzL7cPIrYluz9gBQNkrVariZLOKeVF55Kc1sMyzDWRnrNml2cOq4zn/ijQG5i+9suFNK58WyMWFxnZ6h7LLoOIelqATi8scNV9wuK16UFQtXFBLcsAJ4bUVHNhDGQhWMZdPRHDc2AHNaxsgShywuET9r7DZsMZ/qHcMPgHjDUi/kdy3l/oUO5PHX2eQgfwzLKo9I3jcn9meyWrc3wmHjafmw8edh46/Dl1S8wa0iBQjffBCBuAKFwWszCQSQVV1NWxG0lcCsn/x8BlzWbYt+lYoQ6tK7M6X1DmWfDG7+RqdsQQzLkO0zVyszxgOTBD69+U6DjLXpUC/oIJlTuBw7q7RGaUngXRp4UeCelqrgXVa8sZxxwxU3ZcUb5RwAXsxftZAAdcEe34l4kgTevc5lB3L+3Wb2YE3rYbvM8QKI9871CsZ0blp+tJbvKWJj9i56Abwhh+yAtLF+dbDZF7O37IeN47Dx52Tj8jq8pOR+BU4rnJKRF5AtMwChBpGixzNBXYAa2DqeayMdSZ30870VA3hTEAgTZIEaB7tswhAeP2kjct0AqHWn12hN0GyIlUZab9IIQmwdkBYD0qzOvW9BYDEkms+mD5d0Y8gh7uHEMsofNytOJ5U/PvDiDi+WFbdlxYdvvo1bA+9b5U7dc5MD7p0Nuc2t4KUFP0IcvHavjeDDx7i05DKIrvsz2LL09QA18O5AbOfFJG+WybS7KxwSRZk+ApT1X4wjeRVGmrV5B6ozRrdNjw3JQB5S08a+AcIFQAUV18UOGz9s/DnZ+GsQJwVpkKoBYmCNbowoZ27A6vEmDFqVdVFp4MLKJCvFFydVlT8YJosYKKgRpEno0EpUrKM4yRRzch1f2xNlsyL22cxOiXwgUAOxDV2jOCEnop0JzfXtMogzTQcvYZI/LMq+qPxxYpNAyoob1r9b1k7lnM5SwBAwtW08SbDM68xSD94B6qswOXvWQXd/1fP3zpvAGVNkX9j/rtMsfTzENCvMAFWfk4rDxg8bf1R6UjYur8VLSvRF1VLQWqNw26WmwZDCBmQhjSup2unbFunjSK3GIAU6NhpDmWcVMJwdOmpJI6ihx+RadraZk3c0++ymzRhmI2cUBKGm9+7xm2KUyJhnZpqdKRlYGRASoNgfAXyq4KIeTjenFbenFTel4o3ljDeXe7woKz64vMStgfdNvg8Ae+fxmQruqKFMzZSPCh1f+gbijdfTFWBH7MgE7seyzkts02URPz1Uptjg9eatY/qLdfc182vpxZyV0nvmRZXA64B213JpJqEBwGHjh43j+dn4I9PTfkm1ChdMhdj0c1K3XXjBW4EzQGxDy5CCtRgIpVhMCQRtAWTR7c08nhoAhoJWFtHAk6Z8pDHZJJ/KJJ2NcQKyz2jZxIdbIbTWUCvbe5YV1CYriAPZvYmkNxIbsyHRhowEtGgQIzGwnFYsi8aIZPnje2/fwVvLHd4oZ/yy5R284DNOVHFrv2cpOEtBE8ZZCt5pNxqjA72fJoQW98uIUa6tTHzqhfh7ANjDdk+XsEHjfklY9H1DnAk6JkNqynlFQ6hM3yeLc23fJ28jCKIvxYFLJl8xbJZWSo3Dq4FwkETyMrf0VXXY+GHjvuuZ2PgjX4JP+yWVkzRlcZMXCqCMRl/oDdTYvFfMw0kM8G6I4WJqbYMdJ7GsDNT7MfeSg9cBHL9C2mlIOp4aALSm0f8ENk8nAcAds/47G7lfnBOAS0vDwCh4l1I1wt7lD2OVJ6p4wecA7gs6D1JIg6BQQ0HDitKLWfpTi//nNp0Z4rycGeR3mkZiP0oc076cHpRCGNvBOOf8aCef9ziJdPsYdxw2ftj4dl9OT8nG5bV6SVlHMgClhjb/C1WLbBYBtQYBK2hXAQostkRRwlUgqw4RwxXqlkqIoEedCiERPtfubeRkB6mDt7COFTan2pxxAisVzaoxahXrf9SRAQSWt08kJ+i0ypNJIWSjWHOpKBZpf2vyx4kbPnBzZ/LHGR8+vYM3yhlv8j0+UF4GcF+Q+jcxGprcblqnJhpHEkw55g8iixXpDWCWOPYYpssgNGy7ULWZSQ7PPh037cpsc8C2jaqg8zFZ+dm6ej7poKsi0JEYqjFNtmDTBnOLQ3ezZoF74AGWVyPzfEvsk8m+jGxfY0BcDutPsP+COmz8sPFx11O38f3Q7W16Hi8pANFRR6Igbhyftz7qLkkFVtKx0YRAK4GZtQwX69QFoa3KAhkAr0CDApQW+xy2z19nG9kLsw//ryyPoKB2iSQi3IVQlxrywlr76Ms6EjNMMqHQxgcAe4PBPdhyWXS4l8KCN09nvFjOuCkVH755Bx9Y7vEG3+P7Tt/Cm+UOL+iMDxeVQgDgRBo38q12iwbGvSw4JXegJoS1cQBYQYzOyDNw04jXMQq2/8VwK+kv6vBK9T5gz3m32AbX173RCNJOsK8F67h3OyHS/o6a5A8GBO6O7c4EpC8AcNSDyiKkz5tcxHWnWJWJertpiW5BrAV9pRAOGz9sPGXzHG18Jz2fl9ScMqpErAJHKxg/3ZUpZGYkO2xJJuO7NnVBBq+z0OLAy7KI5SFCqMYqxdaJHMC0+Tx24CqIBQu3YLenUi26vuKWK254xcINL/iMF3QOnd6BWww9/XfHIyfdl9/vgKzMHDfl27dvyunKvsemPTkkb8tTIVDaJ2TH+7G2HHE+NBFa8hNzvv6Q03FJ24/liVHquoE4739M5/Jh44eNP2Ubf2R62i8p8gDCBwAdPv1akMN0yE0XyEeLJunz3difWGyE6vowGQDpjwaWyQTVyi3uYuEWWnhmmxFjAmVwzjLPLTPODhbfll1lmZsVgeCmaGT9Qg1vne7w5nLGLa/48OkdfKDc4QWf8aHyDt7iO5yo4oP8bdwkJllBOFEBo6GqWxkqOCSQ2nxk6FQGmFil9O17csju71ytAY55xwPV7PsNiAFQ6QdQk2Gbgra7RkNo7GD2qbBT49CHGULYg3rWJdZp/tsE2NeP5kO16lBEQj2ehAGgdOD27hHbf9j4YePT8c/BxmU29P30xF9S/slppXkNzMY0UXUoFQL0s9xcbsNTp+ofs6BR345qdVMJVGTySppvS/MvNk6Yj7wMAAtvYwNUWuhACTBPwG471/JGgklwW1a8KGcs3PDB5Q5vLXe45RW//PRNvMn3eJPv8H3LN/Em3eGGKt7kOxQIKvT6FYQzLSgkOpWD3Vv1+3MQNx0iwD20subeJY++Pev0u+C9AOSxUFNVPvSRkcFr+fdfA1I4CqRMlUIPGehxFHjy9WgAWEErYJVRfMQGf2kQ6Zh78y3WCimWaRN9S7jL99yhfNj4YeM7xz55G28PPaSmp/+SepUUuqkREdf4fSwpr2A3OiCMS5C2+bJ4PU0Bchg1el1um+2eFJxiHbcaG9OEVCLhfExnpvr4mtdCCuIbrsMAmip11OR+u+JEGtDI1FAgIX2ES9eF1KYn3JWAMmD9Hh8C5kP758PzZS9VfwLvfP04P0kjIYN4niaFkEkhw7nWwYzatxFo7GB2zR6wPoEdWcQklJC3/CUk7dXtenjAw8YPG/dz3+c2/kg7f9ovqaIjaYY3FBF8BOmrhSDSO0MFKnFUiikNOuPssohLI3AXTgHc8yfISUpMOj50sWkBbmySNR87jCfLbWYpPiqzb+sduRzH5LRQjUbhRTnjjXJGIcGHl3fwZrnHrckfHyzfxgs644Os3k43aLglvZezMF6KPjwbu6zCqMLGLnloQHqfhRunlwU6+0rMkRKw8/IgR8xVFEBL6zvgvcQ4Q07x/7zRzt0QIdtIHMsh9sOYpR7jw/IAfUw7AZRBioDApoQoew2mCb+uMU4fSdqArFJJ68deeKDDxg8bn9OTt3F6DeQ+YtZPUXbxNIGWE6hzSkzTtXvXb/UTXkJ/9k96mbR7NDLNVsII3ZKYuibv01U78ztxjd95KJYsc6z23T2D+dy2ldrzErxR7hXAaPhlp2/hTb7HCzqH/PGCz/geugvgniD29d1w3mGYPn3BKhzgrW07VEwGq5ZF+o1jRpQO4J7SRfDOoJ2rNq/v3M+g3xO6jBPSh5uHgkskgTnJXkEMLe9Yb8ZOhSDg4ZmFpAOW0YEMdOYJ4OIcO4eNHzaet+d7SMtPycYJl79qc3rSLylwYpXz9leIjiY3MKGtIcr22GE/AHejcWUlw6zLIS1+fQTm7P5adm6RwUkKYe1DmKw2NwhZ+uh/Kn/cUEVBw4kaCqkE4tcs1gDUB4Vwe9wd0P1ipYu39ADLHKSQoITpXAMzpXVQbyyGaHyRdIwuiEXnj+OgGRDTMUOUvu/zX8bQ4Qygv4w2z3vY+GHj++c9XRt/XF087ZfUYhPneJpAK2Vin5M8Qs4QEhMS60jMIxxz1c9iqlqpHrFPRBboiPBMAkxrT0hfSIHDJBENDyiATzudzD6uWBNSzyOTIeoO8ziZFFLQQvo4UcWHyzt4k7Xz+IP8Em/RPU7U8IIqbpNtFGAzTUG1a6kc4p3KY3+B7DRur5LEiR2NjWJmkFn+6FLEtJ3oqq1LYriS2bCxTMckEcWXhx6cn49M3rCRvwsZQ6ShgxnsDLMhXK5NXAmpw9mmjx7Ntu+xreJh44eNz9d5qja+89W8l572S2qW+oBwpxwAa6xTaFvTEVsiUK8nwqjZm5TqGn189ntHoVX0ni27Zu96+ok7+2MSvOCzavqJgQLKKAEFctfx9/V6Z5eFGt5kBXBBU9DyHU604i26x5u0opDgloCbqRx4Mp7mjQbc44mHBmqOG9lj46+SNkwxgTgvx+WZdrfvJVU4KN1nv1E/LbZ4vXqFCoX+7tq9ez45KKVQdzrY0e7nSH0YcIU6aIcJ5K6lw8YPG99JT9fGXwe5L7FGmfX5mXHap+clEG+SbP/I2CREBoYqJqH0gERc7AAHFNgO2uyF5KlQRQWBqanbrDCYKvL01nEuBCdeTc5ouKEVjBYSyImqyR4mf6Cbxtz7UWGeVyntuQSPhYcRaPM++82Trw3756LfAaR3D+wBe9PZPKWsz7uernlInEfpWPL8JG0b8jOPKTvu4qVtxAYiH7VB4BLJIH2IxJTvD6XDxg8b30tP1sZfB+8+YYYs7txvDzyzTEA/XYNxwgA95uWA7DJI/+VKJoVYNhZnosOREHQaAonhXcLVVgiNPDixu+cG8IJxttDucxS8yiCc1reVejIdnknwFt/FOGVv8Z3JHxVv8ooXpBPknYhQQKgTcty7qlojcZZlkGTmRDRib+j4TYDzIqK0PbO7OWfZyUMoMctp+9x4DDp9bLQf91rzBwh6iABtdCrHpwMBHjcC0XpnwMct8zgU94qLDmahzjB9TLSKHk9iM0oPEsmlNPc7HTZ+2Dievo3La/ElxdwLZAKys0rfJkkWFALAE4iNOcLBa8wxez5FRaXjxD0rTbevoprtXmBiyCImf8wAzuAt1BRAhNDpPb8cg+KsspDYUDD3OEFHfH5Bq0owEJwAFAMvG/oaBFUEGsfZ7zVfz+WXQYYJtyVsQJm3az3YIhlDIxmAu2maZ5CmPtaYnXUH5H6tqM58q9KXx+t5KyTdndfzs5lj9Tq9gznGyksNFATWQYwNkxSCeqCKxEsAQMgm3kBcZZV7X1A4bPyw8XSrT9HGr8Ss5fTEX1IJtBm4QLBJQL+4MpgVvNPxc0ryR/aKUiZqn/VN2YTYaNEIKaT7w/TBNhnNXXFBm5FvPOWpBEIugYJ53zuqxbAvJ1pN9mjhzVS2ENlNFRQMUzuwrzSacyJYQVEHVWxHkLYM9j2G6edk8Hqn8QBe7tfIAN9LThQdvDTfW7om5e2S7nVuoOZrJHlEO8pT4CsjgiJfOeXx+w4bB3DY+F560jb+iPTEX1Ksw25kcM4s07ZFhRcO5oDiBuc70UHboCyj6Scsr0Cr5qhSnS0QsAKoWl06HYF1CDeOmA+PwXAPIgCj7g6d06ZYoGGhLeiyK6+f49v9PB9Us6DhBa04WV4nUobpqYmgQnBvDPPeOo7PsqCBQ4LJnlaMPn8QEewzHzq6MqlnkP4JCDQMxyLFQOBxGKkzfk5d5qAO1AnA4QWVwB7nTslZpgAx4ADlxsQRnu/JWGMc3/r1Mug7xZxAGxe3fIfnc3ffdLMzoXzgi+mw8cPGc3q6Nv4afEnNIAUwTnk9yB62PUkgQhQsZsw4gxiG2l6R4RFly84yVRbRqQd8oEpnbd2LiKKTWG8ndS7D4ztabN9LmTn6EDAFghuquEGNAMoysUwlPIICGjqUGzqrzA3LpdQnujNAefFnhmg2GC64bvwM65hHD/SLjDHURwbrhmVyP8bP9fXB3TftA9CdAXzZnyPmZLLrYGSPnXGmTuJXSYM2P3Ww733pULZZHDZ+2Pjzs/FHpif9koqUmWVioQ7mMAoHdLzckIxuvxDnzuZgHQ06SVzo9wrk1tTCqoEYANZWlHGydxRrZ7MPegmCgXoftHtyRvacKhDwBPq9c7wtqkmnP4vLIBxyiHcuzylPx0AkHTzWearaNIDEooQxEibpeBLeKfNZ5uC07PV1TQqZiZ10QItp6grE1Oi0ThhDh/dzLizPySe5034fP0G6e5m74uZ9Oc3Mc3OBw8YPG++/z9LGL6Sn/ZIyhhkMslAfdj5JHkKIcHfJWj0jWKd+xifGKdax3KCeTqy/bOfxShB3rTyTXvssqEuBcMN5KbivBYsQXtYFN2VFE8J9WVR/B+OWVhTWDt9KjKI+nYMu7/r7+Nh9WoQTaoDY2ekM3gagmsG4oHIG8NLkmbMwzlJwlkU9nhIj9uQyiA7yIaBijMkmUBNop6k4kJ2tNcW3A48dYLIPhiGgkTGwzC5nYWC0e1JI5O0NcJJenFk2Py46T3pHcr6PuS2LgVrtd5zOHREnEmD2YWBqori7LuE7ID5s/LDx527jD6Sn/ZLKKTMZA2KwmNIlj/6rx/XYE/0ZlIBkaLP8QeblQmLsk0S9nxrUJddYJpFG+K9NO7bPreCGGSwSEgQnGWJmihm8PjBmmUDq8SM+4vMew5z7Nauol5bfQ03Msg2FkIs1afZwAIlq9NLLlRK4iHqZhgwhaXlKFwGcQLXV611imOrONvYvBQx6vbWXXaZJ9x+dypTyupTsK2PcZgzTH7JN+4CtFPTQRIeHjR82/txtfCc97ZfUnnKQtfkkkQT7TMwS1hkaxxh7iTSXZwIzXLtPHczSCFL1e7tWxmodzPet4NQWACtWYR1Qk4GzFHCTWFZU6Fw3Qy8osGGam6IQpcEOwhMUoCBotD0paD2dQTibLHOWggaPG+mNyVisEr+qOGlnMgJUFmfh5VkMJRkAe8xvLmIDFpCYZXwFeN7QhuMCyxzccANIupPQGxGQfj1I6jT2xucS2cs6e3jF+XVsXZ0RnI2KsktgHHBzr/VyrSouYFR4ZxLEw8YPG3/yNv7IPq8n/ZKKAhLRjt0M5vCcUfDK4gBOoA02ipGBuiziyVlm1Vonho51JgCYdAiqBlAhSGFIJaxFcF8a1sYxUvTKjIUViDeikfKVGScpKBA0Yu0kloYKUmnEXG49noR338yalLHq71kYJ2rmatuZpwP0DJ26wD2eXsoJ9yGHFPjkdABiyJtCArBOcMdF76MV6xchQJbOqERI2WcDGBQsL/o3cAXAeyyTtZHYsEz042HLAVDbJQYmaQDXEZkClWoc9DLEjrhNyHi/3vg0A21V0FJtem4VnZ20QUd8rlZnaboCAPDZc0dbc0puw9KQld1h4wAOG4ctPwsbr5frOaf9b97vIH3uc5/DD/3QD+GDH/wgfsWv+BX4sR/7MfzCL/zCcMzLly/x6U9/Gt/3fd+HD3zgA/jUpz6Fr371q+/ugheeUxIg41OaMmuZwGvAzh3MmbXEr/2FIQ7Mk4BKJokQWuOQRGrToV9Wc9tdW1GgZDkCfdDLPHTLq8RzzNH7OgwM9UE0QQFO7zy+lxLz6uwN8OlpwzQNUIjfDrrMAL1zWNLfXCfxNx8Xy9I9njjVJc/nSO+M5vEY+P7cCKDfS2ar8lCR505iGQHe44tsX/rzmXKptu22Nh0flXrhFg4bP2z8udj4lfSef0n93M/9HD796U/jh37oh7CuK/6z/+w/w7/5b/6b+Lt/9+/irbfeAgD85E/+JP73//1/x5/7c38OH/rQh/DjP/7j+G2/7bfh//q//q9Xu1hryh5E+iduEyAPiJiTM8/oeE7LCbwbA0yVSdbZ3JknIsKaV6CeAIAgK2PlAi6E+9KwFAXriU9YWNnfbdGRom+hjLMRoxEDrJ3FVThohE91XcG6TKvdEeNeTCqRBaAV1WSVYkbQoCwxBzBWEO6hjcjZfu+tQfHJ4IYYkqTTEwmY9budi6Dap740CXdcWaCdzQQwJFgmmpbdRSkkASvASKl+9JEV0H58VI5nkipf+jVj3epQWNdds/dGIDrECftNZ27QmzfgYlIH1C6dUdZm6zvgtBlz+/33+BJhexkwgZgPGz9s3CrHM3n6Nn5x7rQpvecvqZ/92Z8d1v/7//6/x6/4Fb8CX/7yl/Gv/Wv/Gr7+9a/jz/yZP4Of+ZmfwW/5Lb8FAPDFL34RP/ADP4C/9tf+Gn7zb/7Nj7/YqughQEfqhRl8bRAu+gJLLrnOPDXwrgfnDaBFZkEUQA7jScCFQGWRlSBNr8WFIUUgzKikY53dswLonvsEcIstv1HOWG26kRc2BQEAnKnocrPhY5IpjcsNNwRjiC6hCCo4giEL1KA7eJVRvpQTKggv240u2zaXQnLy4W4WblhKw9oaiIDKDbKgT+cABsS6MwwgWCncYtFkYOubNAM1mKr0eojtEo3skBJGqFE0LKiGSLFGzRpiadqYI4BLY9405k3e+ARwVZOnqiCmtaltirHJai28M0sgvKH6c3P/ZZtwEIBP133Y+GHjQ3oGNo72uGEqftH7pL7+9a8DAL73e78XAPDlL38Z5/MZn/jEJ+KY7//+78ev+TW/Bj//8z+/+5K6u7vD3d1drL/99tu6MLyxMYqXIsglP7JGSpXjwEY3kOmYDF7PMirQmQYsGts8olwOAUHlECGgqRQSsSXCWIXBLpGgdzafoEZWieO6PmAmo0WnLw/gZnP9NcpkmysQLsEuldxLGTyeZla5F/DIJDHsjbNNYlGgwjp5WaxhRfI2sgh9a/Cy91NOe53E2ph2tpnB3OtnzKhP923XFmvw7d5ous4siex2KO+4QG2CHfN6ZpSZYdaaDrGyJNLtHgNltqxTJqR8DxvHYeNeN8/AxmfPvwvpF/Ul1VrD7//9vx8/+qM/il//6389AOArX/kKbm5u8OEPf3g49iMf+Qi+8pWv7Obzuc99Dj/1Uz+12U61gqhCiECF+7TX1tmswBIQU3yi64luHJ1d5o7krCcPzCZrvEAYCTXDWAWo6udsW1QOkSaopeDMgsoNS9EiP5UaksiZCwoJzlJwK2myOPNkKhCcaNU4E2qoQhG1X0EoIsZEO5gLBCzbz2kdEiaNAg3Cy6bMsoKHDuUcQ8LUgmkW61hG05lUhRsaEWhpyjINPwFm0ngb7YDVPK+750pfZt8u3cuKZPKCGzOKfAXdddpZprPbAjTpwashgYT0ouddlEOSB1PEiVRbrq3r8WsFVq1TaW0AsN9o99TjkEKcdZJ9SR02ftj4kMdzsPH3w5fUpz/9afydv/N38H/+n//nd5TPZz/7WXzmM5+J9bfffhsf+9jHQu7z6DkC1FiYQdxsdkm3JhjrSMBkqNfSBOYBvG4omX1aXgSMsshKatCk3lE6bBOhsgBYwNzwbdK6XxurN1Rj3HAN/f6ONSByYR01WgfdbDiZNKKxIn3ag5NN9AbBJtBxz6XXWWUTVn0ejHvzfGrCuGsnnKPDe2SaRIIFOqzNUhrI+gAAa0yF0Kw1kzMr0xYLBg3ZQVvSkEMicytWQgdk0uXhwA6GmJbnJNZwwK7nNkB9Nwuppxyp15w0Y5irgdmPjzofGeTgYFClezk5k6zVKnqFrBUQ84CS7qI7sEwAYIK0YmyTNb9SgCKHjR82PqZnYOPS5vmS99Mv2kvqx3/8x/G//W//G/7qX/2r+NW/+lfH9o9+9KO4v7/H1772teFr6qtf/So++tGP7uZ1e3uL29vb7Q77zKQ2zQLpjCYzyweSzKBNjLTvpw7uKQ0artW39isI5gDI1hhn6ACdlRj3AF5A5ZK1FZy5hLSTtXOmFh3G7CAFq1EAAHWt3I/NQY8xRA28c5qNbZZhmJg97yd30a1CsezTEviAnCqNQCUgk0e6LGJ1Am1sVQ5JBRluQ6nMnVn6fl8OKcQBkOpRLBMbHBQuaU15ZyllrMidYy8kcoZpywDCHgf5w+e6MPCKs1K/5/hqys/Z7G1z2Phh48/Uxvc+M3fSe/6SEhH8xE/8BP78n//z+Ct/5a/g4x//+LD/N/2m34TT6YQvfelL+NSnPgUA+IVf+AX8/b//9/EjP/Ijr3attQJYtaNZbA4X5s4uGxsTtEK12SG3skjuYEZfBkIeyYxzkEriZqBMwxgnr4Rmn/LCrIpAFaxmdKU0vMPKMr2D+YaLyiMgLNRwyytaUcCcqGpgJPo8PUwNdzjhZF5QbPIIsGWY6i/FocOH7GEAftlOaCaL9OBHipgTz7+5FGLbF9YYErZyospoLiN4n0W1wpLe1miZ7Rhp1IuBNLFMiuU+vhpIMSoJ/3odvaY0aIeF4Tl0fPfCKlAngEb9vWCd4d6oe/DjZU8o2f419XiS2tml5A7m1jYsU2xOHrKvE7G8yZ0pDhs/bBzPyMZl3bvSJr3nL6lPf/rT+Jmf+Rn8xb/4F/HBD34w+pk+9KEP4Y033sCHPvQh/K7f9bvwmc98Bt/7vd+L7/me78FP/MRP4Ed+5EdezbMP0M9MVAOxeUAxg4QBZlBV/Zi8Y4/QUWcVPnQwu3bvbruZeU4MZXDh9c0NJgkIqEA9aC1CXaAeUSsXiBBWC3hcC2OxoMFTWXAyWWThhjsuOAujkOCGV5ylqAzCNUkhFUzLMGyMp73BPDObDHYpjDubpVTHN1M3XZ+GIacc9Ejc0GwQttoYWMxrWqCuxmb1LXRyA7SX/x6RCvZn0yUYkIn7OkEZbWaZQ39uY2tsBa3a6AxW7wJj/w1Kx6WDVu2nAxgX6n4q0A5ac8UN8LamunutCtZaIefVb1JlGi1Uy5t753Ip1hiJevEdNn7Y+DOzcZH7ncLZpvf8JfUn/sSfAAD86//6vz5s/+IXv4j/4D/4DwAAf/SP/lEwMz71qU/h7u4On/zkJ/HH//gff/WL+eelLw/b+4i90pJMIbJLF0bvpwvgpenYnRQM1gyWmvRbM2Yj5gXVGqGSjn222hhoDNEhZaB+TCs1NNteoJ23LpO4HHKCbyI02xayyZS6FEIB3nMEOlL625dD/NdjUjy2pFgHOXNDayp4s92Xu+mKt6EOjguaUkgbziaN6cXo1NzimGFKBc/POrzFr+2SVNSrLusMqrQPVIwsUy+yvd2LKdmjJNapGwy80gDiADJxQwwpES8d0TfDlOdh44eNP3kbf2T6RZH7HkovXrzAF77wBXzhC1/4zi5WqwI42CdrIQnpIF6tgcA6mrFAO/8W6iAGIs4k7t8r01nkTkfzIIPkX+qZaMQ1VH5ZU55nRhWAiuBMC9rSUBtDhLCUgvtSsQpjoYaTLTMJvk0nvFEW6DTcDQvrVNwLN+tMFpuvx6SWYdBO3ZbjQjTiv88FFMxSClYpMXndPFK050ek8STRNok2TJW0Y51Z+yVY1D0Ztt9BJnssM0CJDZtUhzcHa+8j8PWcr853pNsaGG1pINHGJOhkU/mDmkAKQaq5EFs9jZ3K6ePEXWh3KfJOahOQZ2+0tC6NQagQYmvobOgZ4LDxw8afnY0/5l0BPPGx+6RWoJgOyqTjStWmnjatAZUhUMahMSeE+ASf/4DOIpN2755Rg16f7XlmnIlJkaBr+ES9MRCGVMEKNfy6snpytoa1KmAKCU6thp6/UFMwQ7BwxS2bFMIVyyCLdCYI9NlNPeUOY2eUMf+PgfrcHMx9MjtPzirdtbgJAdzUs2kBuDmQGVIafII8B29rPa9duT6BMjqq5+X0fM4yHcBNtC+nNS3TSqJ9CGJ9OjYWmdgAmSCCrAjpJOpJYHKYDEBObXRv+HeDTlKaxjMLhjkXgNh0fdx0Zly28Aqmw8YPG392Nr55mV1IT/olBcD0UvuEdN0UtCmc7A3lHia0+ym+sz4xjXxc/nyeP6Ujid1P/Po2aMcrq8ERaf9nbQxwAzdGZR3ME6W79GqEvj2fySKegmWKMs924dPagevLLVgnDaAdwAvZRuknSURjLlSO8e3KEDsr86Dz8FCai3tij5lZjuOqjQB2pllIYvoIwIMata6JdMoFWADq3pfDbBIZtNqKTHElTCbLXQEx8+Dp9MrpsPHDxvHMbfxKetovKR9eY0rUJDyj0JxdoNM/cbbpY5RZxPb0eb6RRaYKz8fohX3dMrEfZ5sQJK8tQM6q1Qrr/dZKYOYAxFIqzk07lZfacC4lGN5N1c5JZ6CqoatMAiDWgQT2KblXU5Y7Ooi7fq/HdFAzqYspkwyNB6EDqroUIYgIfmeAXbbYB7D/ZjbJ3HrfawIzpWcTu9/CgmrMVvcXCOuYBGKdBlLFbEciyJUARECr9C8Nr3/J9c8OZg2sDSlOb1YdH1qDFHNysJ5v8XsW6p3K+fmZoOMQUc/rsPHDxr2+npON74QB7KWn/ZLyROlhxd745pHSP38l4jwogA1s5JDIEyPzINh4aNgCOM5J003n7QK9Hom6BgHqCmrf3MI6zbUUQmM3WGVLrTGYG4q58no0/Jk7mBcD6sI1pknwyHkAV4GcQay/HchzRL6nPHQMQ7QT1/fZOVxqaPj+TA7oDNwZxBnATH3dmSUbsH1bTn6vVQhE3BuKoo1za2QAMY2+mUY/NdBieMS0nP9CCgn7SED2PwMyatMyco89ar1xmSUPe0FFXnl7L7TDxnHY+FO38YueOVN60i8pLTBOyxOwXzW/PSBfSB2oMq3nDC+dnPY1O1AoRirOmnZlggajNFRnqI2xknpDDVJIQzBU9v1QUKk0cfl5MnDzui/PnlAhgVgHRTOD5HQOe4tp47i5dxbSvdBOo3KJTTp4M3D3QOyyTLPzsiyyceV1qeZawwwDazaOvO4T4Xl8E+sQRqgNRKTTvIt1YLt7ea3WR1D8xvvLCbAvKD5s/LDxZ2vjj7XiJ/2SwukEnE4WQ8JAYS0s/ywlGryaABj7pGCWlH5lZ9mTUPo0JiAPADkyzfF3Y54NymwgoEopqE4rv5k7bzOG1WywyFIa1loUmNxwMlmkGNMEgJIYp09CB2AEc/aI2gHPzCqDfe6YFBtIWJx5mhSB7gkFKLv1fCXyHfPzY2kCZ2aUM5jzM+xeN+VdhVCKxrA0IlARyCoGOCS2iLFep1+te1LPKZNQAGiA7cJANUmlidqks0+Pd2rdW49Siyoe4KgPpb/Fhkgq5bDxw8afnY2TEPByU+Sb9KRfUrQsCl4HsxXY8AfsavoAtlJItuc9RpbBy1OF7502M08xZiKIQSHVJdQkkmaNBFj3GQtxILdiTI4Zrem4YoUFK9tyY5ydjTUZ2GaWFK6xtGtpHIyzdyZ7k+BABhBgBgAycGXvpAxqO2hzT/neHLSxD9M+aH+C31ewZm7B1JtNT6phJVqHsFgk1d1H6Uvrm3qjQtCXggddMgHF+iCK2h9ZJcqiTg4ERMczFfPGEwG4dBlEekMVNjvLfoeNHzb+3Gz8uzWf1C9pKvaCWpRPSOHoaBZnmGwMLta70exJolftOUkYQyUPGcwZbmWT3TwD3OTxb+HIJVC5tzljQUN1a0taiNjIzT6CtJDq6plliiStPYHoVYA8J88nx3Ls5dmgIH7oWjNwfdsMXpoBLn4dGp4tHxtSyPxlYHJJDx4Z08ZWAuwOfBtwFQwUATVWJqpz9PW6J4thatFab+JFgm3ml9Jh45rVYeN2nadv49+1SQ9/KZO8uIUstwifz2KfowCkFGCxMc5s7K3N5+7FjCeJBP03Ugavu5yGIUzp0rW8Tj1anEn9c2EExKQRkHU8i35mExNqNXdebuHC6h3OWhSpE9Z/8bCkkBlp3v5QiuM87wxk7wNIspRLF3l973qXQLsr49jvYqMWOJMtrPISc1OGbvno6NPU7WH+Kgim2X9d/hCCvhz8hSAEORWTQNBbigZg2ZkQTiSkkM2cPfqgaUw9Omz8sHHNw36fhY23awba05N+SeG0AMuSGCQAZl1eGG1hLXgfo4wT25wSOVgNuFkaIdlnpLpzAm5moReOj+TMEmrw4mOvWQAevNEIFtqsMSnqtUOCxhr9TsYoO9vrQLwG5grX2hObQwdNFboKmkuaf97uwCroLFQllMuM1K8fxbbTqFxqXHwU69zBXr3xIx8fDZuGNWSQS2kCNsiJIoEKQSKMHwFgqhIBsijFYpk64weAi739+SV12Phh4yk9BxuX+jp8SZ2K6qIGSNdM+7INAVIomIHkgs8V8QAT9OUN28xpzuchEF9icAnY2pDQGKDncRBCKpHA2zEFOZH2AXQDb/1zncS8fSRUmCYUHdOD2ZCCyF1JHyubzDJE7vjN0fMZoHud1g+l3FDkWJe9tOdh1XdeucgOyAG1H7IvAe0wJoBER4cgBlYLWvLWvwHEKbYp/wJTwSO+XOzmDxvHYePPzcaF3weTHv5ip/rmDeh0oysOYu5gjuUlAXghtKWzzgHUM/OYGKez0GCjsOPdKCf2cpWxzEkA94iKjPM1BF0LZ/+Mh3ZwSmdd1fRjZ55EGovCLpFQ3+4xGs7CZrmk0aiR9/HRRlA+hn1eYp5x/DV8XQHf7Eb82BQfGqnu5rN7P4szUI/o151tgQHTxrFzLV6g7rkAPHapZzo9y/W2MK6fb/qw8cPGH5Pe7zZe18cY/xN/SclN0uejs9mWjV0CBlQfXDq72E6AyymzyQ2zzCwwThh/L2r3mwvN1zVPKKeA3oDE0CTQQSP9Vvw/0lANEmU2VZxw20yqwuato2OQcbBNLa/ojLbxygDECM/5XgPEF4B7Kc1s8FKnL9AbqqvM8LuU3G5CTmFE34pOQke97uyE+Sl29flHXfuw8cPGf/HTL5WN+0SID6Un/ZKqJwbZS8r1+84MKMkeCcCFbEBNikE2JR97gSEGs5S0Dlt3QL8KqwQuHz8ZAGZAo5MV3WX81KQSgYHPAifHL28OGcQ7dRvSGG+NNyDOQGognTQ06eGvCubdR95hiJeGlLnEJsP9FxSxJO6qO+cVGDLAPXj7uaE3qcltjKzTGou63pLggbEzX9VQLB02ftj4M7LxSq/BS2p9qwCn/cElY6I3IDxWAAOzM02GTmhmy4OGb2mQPbyiG8KF1lmgwMZPE2zrZ6++HqrDQQYx5Lo3DPdlETId2FgO6Q00148B7YCOYVu6FCIulwAQaabld4YXNu3M14eGISRX2JExXgPyJdliBtdV7f6K3JE1+2ojANQAshapj1adnQY80QUgiwHW2aUYuwQAWawOwtvWys87jrMDQ7JD9EPfdTps/LBx4Ona+Hp+3LxST/ol1Vx7z4WeCmXDOJGACnSPqATai/Yh0++0TUGwcx5Nv5fSg4BOTDZLMYlFOuPU41MQpZD1PPvkdA5+xImdoSnjdBnEb+u9ijd5KL2bzmVgBG8OqNRfBdkwz48nSX+PSPpiUIapbtNmf5NeFvVA6bxhHQ/X+XDhtHzYuB1/2PhTtvHH9q897ZfUiVBPj3hQQgJwB+04BAwG9ulsszcC6G66MkshdowYmgQW9JZB1/N5T5MDcrg5GPMFyPfZ/UncNJl7qAO3yx46kZqui7HQZqAOKSITXruVWYPfS3vsMoP23XYSy3SeT8fgk+35PD95cjq0iW3uNNLxqNT/OlPsBa1fGeN5fsjei2TY7lltHurRj3/Y+GHjT87Gc0zZtfSkX1LrC4Lc0OPBPAEyV0aMUZW352M9OXhFNfKBirWUb0gl1MdAs/MfDeI90MezOmtJ4DTlHrEkge/egvkNOLM0MDv4fJ4fkBHTMbJ9t6M5ySJXHyeDzBuOiRHOQMzpIUBLOs6BWxthteXWGGJTbqOR3rCoUVCAmXblEKAzwzwxYAyWmUhmHLf5pQ7+2Ran62zu4bDxw8bxvGy8ltfgJSVF/zYAfoQksVe4wTinfXupyw4OICSgyAS6nW3vJu21Xo9pEMTHUHt3ycchm5c3lxHCnrfSHnA9r/w7SxjzMnC9rc755CkT+p+dH2xbk98yYSze4VEo/WFinxgZ48a23OGBL9jWDoAftOnDxjfnHTb+tGxcHtcl9bRfUvVEwIm27o7XajkKnIYCHAo2FfTmk3VOAu1QdGwZUwF6p2zIIoKRjlxqHGyH0NQ4oOf9Smh8F+BtAmSik4vUpZJ0w5HmWJBZf9/T1Tfbp21+zf373B7TBGipU7lWY5mVdZbYRjrYqRDIBj1VxtkfdAbvYA8xRbtsbWN6GTgr3TDU9BUzdzz3B0qbDxu/ng4bf3I2/nr0Sd0AdIvpFd8Xr/V9bj5DE1DHwsU+iB1DAkTwI1xkMBBmwIYBUM/X9wMYQBq3lAMfp/17x1PPj2gL8hgu5RVSZo5DhL3lt5ErdpqKfZD1UZwFuMg0Myjn+9pb9wYga/QKYAW11A5gBy81LTbKIN5jmGz3CoQcBl/2Y4DJcaHb0+zEcI1pbtJh47r7sPFnY+PX5v7K6Um/pKJwLoD2wXiyjPu9wpzAu/viFzIEj9l2WZxGkNoBvQ+Y+o2PLYA1EtTZ5rtIe4B9N0DeS48ZSmYG70b+wAjWS8CVKZ9L18nglZBCAJc/xDqV9c9PSMtzomk7YawjTPYxATT3A+3N6bN5kVxKh41ffsTDxp+kjU9zTF5MT/ol1RaAliugfYzd03Z5YAwTmC8mZ5o+nBWgoz0HiGFUpudL+fqZfWI8lsQNILUA8c2OLeO0e3XWSXDWKQFenbNH82BWbtgH50xZPdB4XGKhj5E5BmaYANvdaEcmupd3XpcEdo8VkWadyQJIpZBA0KBMM7FMr8PIl3r1BaCk7xvSDF4LoEUE0yKWAWy/ZB5Ih43vPMdh40/axtvjhu572i8pd5wQ4HFgxbaCrh+8D+B8Xmj0QEyN7eeRgauDlTrQHNDTtQLUMU6bHcOISeR6Bp75BbnEwcttA1oKMOsxPv2BbwP2R2LeG89sE6i4wyR9fQats0jX1zPI9+I+LrFNGYCP8HCSRgpcsd9Vr0OVQDWBt2n5wmWRBFQFMdmQML3oc3kryG1lB7QbANP2/DkNtpoL8oF02Phh48D738Zfj5fUBLANIdoB9WNY6y7DfKUbS3VMaXnCWQ+GkzhnOMwpTpJJYtyznWs+NmWmCXRQZoaZpzzwW3koXfNYmvdl8O5p7b59Bu5esOJmmzcCQnCpQwSI0Qwyo7RjMmh3k1cidQz7JWJ/arxzPNJmLD309Th3J0luKOy4w8Yflw4bx/vfxh9pc0/7JWVfUrMc/irGvJumwtst6AxyA5njbDhkYiP5t7dBNLFPIKQQQrBTsX4BgsWlgFQ78HtxI6SJ0FIHbR45uiTgzvPxAIgRo305p3kwTU+XmKVvr2moG98uaX1kiyOAh7HI0LfH9Xy5KbvUZeryRyXQaoD1TmWBdSZ3IHtW8cUAeC96PNgwNNA10CZm6ev5HF/epMmGDxu3ezlsXJefgY2/Fn1SIIQ3CoDvHLjXrjOlDVtNIPZ7ycdsOnGp/wgBG4A7qBkdzNKBHJ3NTIgAy5nKAgHWDFyXP/J0BlkK2QPuY4aJ2dPjZy0+Sx4hmbR0TFr2zmBdplTPGcyI/V2Sos4oqy0baEOjX6l7OjX05ZRcvoiGebpmgNCBvid/ZGB7fWKynyv63Hv+crqUDhs/bDwX7S+Bjb8WLyn/tBwk7OGABzLYAeZjr/uYlBnLtXshoANeAB8cuLv92o6chxjbfBetFmHsQHZWuQfex45htid1jPuRgDxKHtgs+wLts0gBBuD6AQ7sJIG47BHyhwE1N7S+/JAUMpvZAN4E5ix55G0js7xwsQnMfvxh46+WDht/Ajb+yHJ/0i8pF1lDjtjsf8T572W6gOxHXSYBxyvbpyDQx6M+74BAo7XJB4ZBMFGxCeF09OfpEtRB6fLH3nTbWb+/+rjT8womL6ckfzjjHFxx3TvJwO3ga8n6HayZRY5ATtudWbZ+DBq65GEdyRCy7RiBnrInoH+lpwYDefESy8zMcpBCUmDkNduMlkKml8Bh44eNPyMbfyQReuIvqfGt/RBQLrLDxxTWTt7Xrjfsu7S8dxMGXMDu18dE46R2+FLM+QKVRNzYOy/tcn/W4HfAW2hc9zTMNDoxSSLRcc5mIMt2yJZRl98BsEkkg0bfOrCkpULJgBqYZGecVHcAPC37kAIk27qMRpSBzGpzVc3scRi0NSYglAHkkfdO2rMnmQ44bByHjVsZP3kbf11eUjkJXQD6dwLcvWMTu30lovqIr9xNHSbjEQd3ADWdIOmPpow8v4k9zuwyp2vTZT92OBNPM3gRy6NFxxWHZ5qsfgarj12TgEx52bX6xCbz3ecvFZILdTo/bm5LUidxlkViP43nXyu6uHauv6kuDxvHYePPxcZfi5cUsAvii8c9sO1a4V4CneT9bgHzzsxiEiD38qR8HwRQzIwJNNdFih5E1O13GIsNChAykO+NSjCD19eZJKbPnqWQAFx6xLrDMNvEMDt4+1/z8cVgAM+eSga2waU2Mc7YBljMR2aaVjauy3tsSBybtu/VaS5Dk0J2GSj6MVkK6YxTNoB+lMSX7+PKi2o3HTY+Xuew8fe3jT8yPf2XFHCRVQ37d5Y3gL3GAK4ddomd2D5KoN2se56XLuAGJQALAQS0aAFgn/TWuTwYMUYXUs+OtCM5g7dww2KeT4ytHOIp5tSxfF0OgWjQ47lt3XXaAFz1bALQNXog2J8I6bMkRrirwcsIygG0QBqfzKYkaJ2xU7BS/+0FZMUbm/ycPTvJ8kbIIealJoTRw+kagKcX0WBHV15Um3TYeM/usPHIAwDe1zb+iPRIJ8AnkC6xyGtv9ofOv7D/FZWAMZsJvKEVp7/NMCbTCMbjIJHUDXrY9ribHLT5CbzBOtP63rmv4sILJLYa69O2DWvEFrwGzAGoqWyopW1I+SD9Ah0tO41mBulG6tg9RgbAPlgFcmH50rbDxg8bf242/oj0PL6kPF0rsEsAfAWmmVMmB3kb7dKSdEAGb+rU3Dcu9A5mY41iNIihxsJkRIwAqqRMp0m49kK2rrI9diR3KhvLJAnGmZNPCsckWBvHdAVMspFD4nEzg3NWKZ1Fjq61ti1P1DZ7MLULywFeivK7KD2l8nVG5+wShKEDmazMx8JL1TuAWLbA9mPigrvFtGnQr6bDxg8bf+42PqXn9ZJ61XQNyNeOF1t+lcKejh3Ype0fjC5dLwws34MP7NgkARcarGGoVpdWzUzBIoMGP7PJWL70YNTPa5EnwgOqJmlkeHRb34sZCYYZwEZimZ1t+phjALr3kgBIbHKXUeICKKz+tGzdV2wHb3t2kZmktWQD23xsunaP75J1btJh4/F72Pj7zMYfmV6Pl9QlhnkhXarvYcVA7FjefF6/ol6yJ5FkHMtkoCIIyUQ4NwgEeXD+hp4yYEcgj0yzCYMhaOiDbjaofOKeUJTyrNiCWRuPS4zUF8ZyUKB2QAejnH4H8Ka0AcbcCMeiHRiiPfYb6YdsaX7EK1WxC9p3+3I6bPxiOmz8fWrjj6zCp/2Smit7LtBLhX1h+VqZbS6zB2LfJBiZ4SVjyPsFG5Y5VLA/q2VKNkUCMYFcl3Bdn9LxO9fMwY7+u3ADQ8DUdvX3JiaFAFjR530WkWCdTDo2gC4DVYyRGnDndkXme/R+BgNrSB6CPrsodHkjI8kFQOTr7dS7nyNeZtwrb2hvZDzvInj9sIcA+B68jOb1w8Z7Omwc738bfy1eUtfSdwreuYJkXBxAbNegneVXThdAR44M+9zWiPvOLmX4pZAXABmA4yNAEzrDvBY/shtLkibAa4mlziPvE8mmr+Dyc9MIZGR2iZFZescx0PV6YN/o6Ur954Z2aIzFdtPoaTfe3ngZSdtflVleSA8W3WHjh43bgz5JG38tXlIyFdzeIb7vMcC9ZmuPqJxLVDMAbeB7Vyw6Mx6/nExM7YIh52h8Xe8sMmJHEsOcvaGGZ4PJJKLDAzAJfOTq3PHsMkieu6ffh0IkDbg8Pue8PgCZOngfUReho0/b50sMXwQPpAxCSRk+Bpx7x1yy3zTc6GHjh41v01O38Ue+3J/4S0rRQfDx+9BBggm8jwHtQ2WWatqZG9Hubr0GpWPSPcWLldIlKZ2fbjCYqy9LZ5fiO4KBuaHLxhD7VAY6PMzCDSUBduHal8MLqmv2TRjN75a7NNKIAG4gITSjsE0IjVXNrx6/QQKyMdcAeZiBGqsOKSQvT6xzk2is+91GfDy8ly+l5fl+dtb3snzlL4w9GyQAkgaYPWz8sPHhYZ++jU9dghfTk35JPaqgphJ+1+DNxzjSDCcxjEs+LjNNJKaZ979qStf15SyFPOb2nUFmpulySGabnkrctAIS6B3JmZH6ekvPzCQQomCf481cueEZmDPTnE/P5YppmablfA6Nv4+SsOaGce8+do67mPIXyHwaDSZ0NY+Lt3jY+GHj72cbf0R60i8pZxo+TvIGzJlpzNvS8qs4KdFexaOzzbClYI0SO2XYjnCpNdLcs+We0XDfzphm1jytx/4E1k0Hsv0u1LBwxRKMs+G0Q3EcnFVIjYYVtAtVrChYuEGqeUVxQxNChc7hU5t2Rgs3i8Y3tkk+Z1C60Aa44/rMwuN5sS0f8W07IeuRz05j6qDMLHYbxT8eew15g3SyS0v7vvgikX7funrY+GHj2/J5yjb+2K+xJ/2SIoECgCcQJ4Dniox1yhn07VeTAyqhLYNZOk71ONZKF7cU6eOMOSukavdphhnau3UeD5WYjTPf1qbRSpZFWjZso0EzNxSyIWIogZcbbsua2GZL7FJTFUITxkLAKgKWpi67JOCWXHSbREAjCyngC+lspY3RWPV9EbaGK1GsVNbkneJGRCgN+zI+byqHDNwY502GOg9pSTAERsY+Y7RhW7FtAnTehn7MXA1z2sgyqV7dtHxbSDN02PiQDht/FjZOsxfKhfSkX1KvnPbAuwPcubLjuKCQCshZ3ggQy3hO1ugv7fcK3Jw33dPmOYbnu/xMnkbX3Nbljwm8m2BHAgpVVAOmXqOBpceUeN4N2ExxwKRg9U5l7z8Q0Y5nuaBr0QSMq2lglr0sMsvMVRhldS3/PfBecg1+BIA3wHWbyQ20N+gPvVQu5H/Y+GHjuajerzb+2Gd+2i8pD/QDzF3VUdQBE2lYli0IrgC5b+inO2V01pnZCwyo4myxqUGR3agkqcMrP7bJeK2B3dp9bqZq5r4NBhQwQNyn1S7cUPyXGm5KxU1RCeTEFQvXAO7CSnFKH38aFWzSh2r4zjq9HhoRmlQwC1ZhiFSstl8A1MbBSh3gIAFJ8mF7TKPsrDKv7zDLXB5efruyxQRAaml06ZrAOo8zl0E7ARvYB3C0e5Qac4x1F3ab75sOGz9s/PnZ+PvGceK//C//S3z2s5/F7/t9vw+f//znAQAvX77Ef/wf/8f4s3/2z+Lu7g6f/OQn8cf/+B/HRz7ykVfK26PRAYT0sJE+bDkAwDKAYfiUHjLfsp4BpEACtMRYXcOnNvfDXAYRMiB7bboB5AE1M/NJhpCloD4rpsRsmVIAKQm8LCBuKn2UhlOpuGEF7g2vuOEVJ5ND3ihnFCjrPO18h1frUG5COEnFWYoBsmGlplH6UPAuSRbxDmWysdJ0FGjus6qSdEu+lnrbvK03L5MiHdA+jUBKIX/EhrH8KYNWAE7LVBOA83KTyOtBRpzsUJj6M1gD7HFBcEDPz3rY+GHjz8jGHyv3/aKOgv43/+bfxH/33/13+Bf+hX9h2P6TP/mT+F//1/8Vf+7P/Tn83M/9HP7RP/pH+G2/7be9cv4b/fSVTkav+DCk9Ads1vuxKY8hP+nHIBGQ3IDEbzewbITDJ3G6v2v7sHdPpNENw3TagEkU40ylhSTAO/+dzG33RHXnmBZ5DN5T+S9tz95WuRIpMa6HmOaGiA/1ty0jzOWzk6KKvQFOTHJgoUaK+rL00bz3/uqVfU0U/G5iKe987cPGDxt/rjb+Xf+S+uY3v4nf/tt/O/70n/7T+MN/+A/H9q9//ev4M3/mz+BnfuZn8Ft+y28BAHzxi1/ED/zAD+Cv/bW/ht/8m3/zo6+RP1Ut7k4tgZTN6Q4MRj0DIANpA8ihUZBY7yxzQqoA5INdEoLRRKQ8MA7pYmJtENqZcSL95oahwOQPgSzOUgSyiA55wgAVAZeGUpRhLmwss1TclFXZJq+45RUnqrjltQOV2qjXE9BAqCZtnKXgJBUVjLsm6v1kc0mzqOShw8sUrKRjoa1NtxUWNBHV+Zlj7h2vnxlpQcYJwdqBPgXPwCzzcmokyAsuZy00AtMH9Mygq/rnjHMAbQJ03PqFl8kgY/l9+xcTBK2o2YrrevbF1PyeuZ9z2Phh48/Gxr/bjhOf/vSn8W/9W/8WPvGJTwwvqS9/+cs4n8/4xCc+Edu+//u/H7/m1/wa/PzP//yrv6RsfC+0zjrI3F5DB50ZqBck71T4NZYTFUQdgDIBOoE5anLysPG8NGBRYiDNOJ97ntEOZSNgNVb/hG6LglaKAPZXSsOyVANwxalU3JYVL8oZL8oZtyZ/OHhf8BkMwYlXFIxxJIAGOlYrnHNbAtAFDRWMtVXV+oWxNgXzyg33tRiY9UGqkGr3TbBSlkOko5UAge+zznukoW8y694DcNSz5ikW+Eno9RMfEA3gSgFUqgCvusyrA1q2wA42Kn15ruNkFpv7ZuovEwvPEdJnnGWSeAkdNn7Y+DOycfluvqT+7J/9s/hbf+tv4W/+zb+52feVr3wFNzc3+PCHPzxs/8hHPoKvfOUru/nd3d3h7u4u1t9++20Aqd693pzJJeN3UOc0yPB7y3sgTgRIB73fPyjvCXujNEw+YXDl9WzDSKecwya8soHQ6B3Mw+e/6b4hMQARL+KSRHEZA21glQ7ePb2+UAXDOpJ5xbktgHVIuwGepaGAAK44C4dXVARA7iS/xyibYacXTse2Pv+0nzDq84/RxWT7N3ccU2aV8583CvmcS5fNdhUOBQKwDZ0zOP/oNdVBoud92Phh48/NxqOv64H0nr+k/sE/+Af4fb/v9+H/+D/+D7x48eI9yfNzn/scfuqnfmqznVb90yA62+ZfVkTacekHCwxECd2ZXebeuSyPpPP7sk1l7dsH9ukdzOgtBSHRRj8fXRO266tkks5PtzNIOMnTSRaBnEQNeGmgpYGLYFlU+liKejndFu1EfqOc8UY5x/ILdqZ5Dk0+A9gniqvC0bF8loIzVTRhWy4hk6ytdzh7HMraij1fxZkKwA2VCcyC1mBeUOjM3Fs3Rp+SQZKHVP46KKk+GR1FXvZN+vIEVGWOpDZkLJLPZlcN4HNnl7wiGGUwT8vL8ybJRuK30Vue0SmAotHR+kwecSZtARSSyWHjh40/OxtfN1ntpvf8JfXlL38Z//gf/2P8S//SvxTbaq34q3/1r+KP/bE/hr/8l/8y7u/v8bWvfW34mvrqV7+Kj370o7t5fvazn8VnPvOZWH/77bfxsY99DFwFvJp26/XohWRsQPzNvpco/yXQsozHABgBnNYTUMVprnQww3dLN8oYd2wGs+1yxpwv51/xALqHE0HBazo9nRp4aWBWGeS0jBLIjckfb/A9bnnFm3wfAH6T74xtNtwYgOdxzTKA70VN566dcJbSZRIqWDwI0kEtDDa9fuEGNAYTbJQALXuKvhSC6/bq0jxVQGaUDtqYQnUqtNyIWkUoS1Tpg21qhACu/fJZ66fcd7AGgBvANTHM5Pk02Eh+c1AHcv466B5rpDII671FAw0JcB82ftj4pt6euo2f8aj0nr+k/o1/49/A3/7bf3vY9jt/5+/E93//9+MP/IE/gI997GM4nU740pe+hE996lMAgF/4hV/A3//7fx8/8iM/spvn7e0tbm9vN9vDdTI7Tzg2BOoK6hscMNcSPWJZrxTgi3XYehCaJGowlO0Ao1Riej1EG6IgSHav+bIO4tzYeGdy9vphA4VH3ftAm3ueSCdeLdixBXi7TDIxJtvvuv0Nrajmnst2M4XUTVfHOFNZZPaI6qNFz/lPf5P+kTuJhwY3gXkYDWFL+HoduT0kaSNvC5uSDtosicCZpkif/2e+3kR2afAttkdzBwN/yXgfU2LDw7E4bPyw8VRez8DGH5Pe85fUBz/4Qfz6X//rh21vvfUWvu/7vi+2/67f9bvwmc98Bt/7vd+L7/me78FP/MRP4Ed+5EdeyWkCMEaw2AyZxiQbKVFpBBAr22vxBod+ZuZMglliMIohrCHXjjNKAcLIgv7JYCBDrIlLNS1tbxSNjUsolCpvvs+hI7WYUS8CnJqCdmlYTtqRfHtacWudyd6R/EY5463lDi/4jFtSlnmiihekbFO1+rWzzBTo2JA6lWXBvcsd0nAvS0Tdv2wnMAvOUnROHgB3bQEYWFofT21tGvQIhkoiDkbvi7DGt3fISjL2BNoim8ZAok6iNYUHMHqHMFXqncdnY5kVKPfOKHWZqjHLVboEktgl1b3K2qk3KJt0u6Iq4SDRls4+SToDbUKh3x82fth4Ts/BxrE+7i31XRlx4o/+0T8KZsanPvWpIZj3VRN7n5QBlI2aCRt4L40bZql7OxlyDMSUOihDS+5npfwo1tXDJuU/u9j6MdxZrw+ymc8ToS1jAbqnFhDBjGAFLy8NxMByUvmjsGr0L5YzbkrFm8t96PQuf9zyGW/xHU5UcaIVb/FdAHjQ6w3EGo2vrdA9Kk6m0bO0CHysUNbp8gjbVAfe8eyDfDaiGAxUgBg+BiZ/gFO5pqFfNqAlaDAnJvxUzbR7j1EwR9fbu1eTLvNZQgopsSwK3AbQKiqBXAIw3MDsgTwxVAYBAActFMzRx2SOEm6rLvEBur3JYeOHjT8/G2/n99FL6q/8lb8yrL948QJf+MIX8IUvfOE7ynf4PAV0iBYZ/xyb7m3krG7wfrqUvxvJdKzk/QKI0QMSuwdAjTDmvKF+ZnZBbSaMENAJnQ8gGt/Q9pv+HLx2b8SwoWGUxfnQMC59FBKczNOpUDPQVpU+TJ938BZIgHaUQ1o8RoF5QFFDEUFDQwWhoKEZiAs1BTFtx0jL0x9EOdqzkjVUksstSx0mp5A3tna+N6hDcecKc3tINkJpW/doGo/tMoiBV2zdZRAD7fAhkp+39anPBaRgJQrgC9kxZhs9TkZA1hFFRIeNHzb+7Gw8dQdeTU967D4+A1ycncA0UdJAQEoMk7UQo9POJAvFXwcImfatQ61gMBA9xqlgtxAZvKAoPHUkxY3osp2TPXHIri8EFIysNN1X/GapZtF75ZN2IDMLbpaKFzdnFBK8sZzx5nKPG654q9zjjXKPN8s93uR7vMkqh7zF93jB9zihBstkarixqPucXOqoIJxRcG+eT4UFL+WEk1QFrxn22dwutSO5arCjMIpNZVCswfFRo7k06KkqXM8YHOqDW2KmCJfn1sikr+Ql1SgmliOLFfFfPgNwNnlW76dyL8E4y30DrQpaPjcDsTFMd8/d6RjQ9jc12vHFQtF+oxCkJsZJ+qudymrDKosQ6LDxw8afo42/n76kfrESr/qpmj2gqBo4CeCCrtMnthnLObMEEGdtwCVjGQtXQgYh+EycwqLAhTYMvhwR1wAiniD/Raa0ZZjOLEszOQAW0KjeTqel4raoFKIavUbb3/IZb5Z70+gVvC/IpZDVNHsPcBSc0KcxcKZZSackaCA9zhilp3sUvCB112lEOPGK1shiVHQm1D5UjXdyAz5qNDuzFI1O31RNqgdmGeoDUPDmxjTLSxQgTuA1qVhlDpNDqoRNKcDFACwgB7AAVJUCRhs3g5iMNWL6mmHq4G76hRT2QwRUQTux2rN/OVnDftj4YePPzcb5/dwn9V4l7/DTz0aJjkNAQqOFIAZWHPT0R5SPu4/mX93ej3HN3plOVGbjrq+nz+F8bQd1986ivj+DF4gOV9/mOjWzDHPokIOF+phkCzeTRPrgmuyeTiZ9ZPDepO/wDlFjS6JSRrEhBBgNLA2F1NuJZWSoWQrZk0B6+erXArGAswxgxzPLLoB7Xrpvd7pua7D3pBBK8kbIH9Z5DJM8xoh76bd1yb0qbc9hq+IavxZijwuqZlMM0Gr1vLANG5PlvsPGDxt/PjbuL8KH0pN+SZU7rUwA3TU3pBCJjjth9HGrir7Ywg0yp2RMzmpKaTuGNqZgls42AbQmaZmCgUoReAe0NiqUwCt7hEWTj/hMUF2+NDALlqXi1jqSXywr3lg0VsQ7km8sVuTNcocX1nn8gs54YZ3LL+iMGzS86UPFADiZMpOTDuulN/1SBAUSnlBgoEjDmRY0YjQoc23EqMQhhdy1osPK2KjV2qdgzHzRsnC2qM/ePdCYVR5xF18Hq4i6A4NhQZNeKaQ6+CR/0Krlvu1IVtDyvajsIebttDbriG69A7klcO3hLMcs1Qzm8ZhYZzanAZX2hAmyCuiGVe6zPv7Dxg8bf142/hq8pHhtKvcVBFi56kteCvpYVcm5wsESUe9zSqxSGVw3mDyTZwayG1zzTk2gs04ARAydqVOBK41tv820aoxF16fbCUmmNyBs8geRWMS9yg03rK64CzfcpsE1FairRdyvodE7eE/UcIKgKA5wQxQ2WECoEBQA1R6oWqGyEM5g3KACBJxoRSUNiHTtv1hntndue8zJQsqMdfptncm0QRvYAcAwdsoNTL1MfHqEahq9tIwar+de33rLFJ5P8ddUAulf5Wm5SnQoU5UO3IgbGQ3INfrBG6obybg+M2mywm8CFFb5hmCeUnzY+GHjz8/GX4eXFDVjAYsK98xexhSgDdk7f/7K5a9YzbiDNv4wskxOSGvxeZwYErfoiAVaB68AQtqBiqYiAamIu3tTlIzWma/LHwQ1fg9mdG8nn+StmGdTBDMmLyf/7d5RI3iLNSUc/QsSN1OgozyDgCKCM8bJ4/Q89Yoatvn1RAKEACDc0CSVX0hOvbwL9+OjDqCgaZBNw4edOh9kkDb9mswRLrxRWZsq6ZeYXeLS9gB3LgP3lpoTm3Zvz07S0BZWWWTBYeOHjT9LG+fXQe7jOzVSMKEVM7hCNnoyoRUdLl8KQO5ZFJVIqYIIoCx5INilurs6o7POxGR8ObUEYF9uAjQbLkXJJMXQ/S6XZAkFsHsDEC6pSKAl2ARvFYUFN6XijdMZhcaO5DxumUsg2nms8seJVrygGgzzBOBEhALCyXxEOaIzYS64HbiAAvFEDRUVkIITKiqt4arLqSPZp/FeTIxfhHEq1SL3R4nJp9v2+YEAYLE6yHr86szSgyaBaCS1fk0OcQ0+x47UHtConciSRoPOOr2Yt9q1Fv+BVL2Bz0w15RmVTMCqY8DxWiAnhlQGFT5s/LDxZ2fjVB83eN/TfkmtOtgkrWZq5r3SEssECXzOG2cbvZNRNfK9FHKIyyAJ0PF5PoG4uXZsudbGKiGQ15cO4d8/91t0So8glnQf9qzcolEp3HAqXQoppHPp3BSdkmDhGnEiHsjIaPHLFkfCUN29UAcvE4HBKJvAGXWbBQEsquv7coGgmuwBQbDXItnLSSZASwQ95vLzZwV62c9l3RKIq4F9vNf+R0OjnbY7m5wH1KwOWjvWO5RzsqLApL70G/T7UJAG42ytA1dk2yg0k8LMUwvWB9WAw8YPG5/uFU/exl8LxwmYlsrVXEWLAZf8k5aiInpHctLIL6Tu4WReRexupd2Y9phmQYq1aAziZlKHoDbtxSYStKatT7UOVf3b99rJHdrO0DyQkaDsa+E2ub+mid0MQDozqYR+Xlw/R7dDNhA7eDlbaBRgM+nDntmlFCtQDXDsp3Fcb5zhdKGKlVnriHv59fP6sVEXJDZvj7oJN9tWU51FmkCc5ZBtQ46N9q4XtawI2PSkzL3uObHEiAAbQ3NQ17bd57EvZLFRK0EWgBodNn7Y+LOzcdTHTSj1pF9S/HIFY4UQaVAvAbLoJ7AUgFYARTua/QuUGgaWKoKoKI8jCU2cemR7MUYXrq6JCeXkAG5CaWh/NgD3CdEABbmzT5kYqt+O5z80JMYo3QX3RTmDSfBGOQfL9NgRH7dMY0XWYJ4lMcwC4ERsg2X6v7kx4QBxQbNRuSXyaZCUZ+8nKJJZpc2OKr1haMLwATtdFvFy7W69bTh+FVYZhIFzLYMMEnE8op3NXt8xrpnJIh6w6IAOwE9JCqsDAtDZI28bWrs5rbcG9b5rUB0eZmi1gVYDZq2AM8kkiVBh1+J008qQKoeNHzbeTeWZ2Di1xw2D/qRfUvpp2fSNTdy9VLzCHKATowDgkvNuomxE6c/BmxnfPByKf9o3oRjXC4xgSBpb0g2STAJpIvAh+7Pnj/+y6fQA+qjP6KM/e9yIyyAKIgk2OTNMTgwzs8pCFOAtlIFWbZvuZ1F2dym5LOLLuRwLTAZhQrMyaslf1QG7LzcJWtPpEDyafZMk/U71HvXv26dtQzKWGJ3EPibZhc7kKC7BdX0/9wG0BGJnpUSKzLXqr0sjh40fNu7pOdh4ew2+pLBW9XzyoDQf0qNCPzebRuWrJtvjNgLYMABlfdx/aXTLVabZO0YXqgMjyskZU2dQOiKyCGElARvLJCjrBBBSSQzome4DQDBdX3amu1AdAhuV3YnJIi3A4ID2NE9TUCZWmcELwECtMfiXEhtofWTp3LHsckie5bQJpQZvy9pd2vEyBbSBXJv1yewAPOSkaLindWC/4VZian8UUgfFKb18dhSrvsO94OIzJh2cdXqRkDskafNUDMAAiN0zjg4bP2w80rOx8Xa5nHN60i8pWlfgvILORQHLBD7bAJBVBzj0aP34mp47GPfype6O6+D1TltldhU3FumucRLbjM6thNH5p/vwGZ+OESG05M6bc/PqdwnEger3clOqMUsDM9vgmrxuOpV79L01BGanGaqDRv9AKkQxVQGTJPAW67xWHf9EFc0YWgWDIThZHEkA092BcaVRBOHcChZrBBz83sjF4JtCE8OkQbPfJAMtkQXHum1QahCmYzdZOHME2RQEzTweSKUNPzCBV2oDpKkkYg2Y+Hg5y6I2uGhtHTZ+2DjwvGxc2v1DxQ/gib+kUFXqk2runV5JNvwHcEGLvQjc/ssmP+TOTQevduS6NKCf9ZvEnUF2ViUDw3LPH5dIXC7Jnj1uyDHic74fZ3CDzGAeSFPa23YpzQxzsx+ErCYzUmR+5CEo0lludHijAazTbSsLVg1+T5v3hlHLkbWBCFmlgR+4T08zaHc7kAHrryEdaw3KLAkyAtZJ64zhzGYZKtG51sTAoBuF91Prvz77KapqKrUCy6I2zoeNHzZ+PT1JG3+ky/vTfkl5n1RrOpV2bQOINWrfdPDMOq6kOcDRtfBioHUvo1OSH2bNHgBOsMEqhRXktrxyM8ZJWLnEcv7k3wOwei+pcXsDwun+3MPIwd3HK3s8cD1VaVdBXC+1gJZyY6HyxxodsmfWOXgKN7Dsuw/N8sdCwCoF51ZwQsN9lkt2KvSqVJ5A6n3bwoAsUD9qEWCxGh08DhAt/J4UEi+Opg2/6ypUBaCm3lM5VsTzb6JsM3R77qx5XUHLctj4YeOb85+Fjctr0CclawVK1b4pKIC5NjTimJ1SMnBn5pkSEeJb2WNGNFbDJlgz+UO9isyDx2IxvIM5pwzEsxSsUlCFcN8WVFYw3zfvWCWsUpLOv7UQ7ycAEJIHQxsQb0QW61MY3XJHnZ4fYJsqJJVdEF/T6gEEwz1LUeDSigrWCeZYxz7TfNQr7FZ0fz4/J9+nLBzB3Llu40rmRC6+7+5ElzRYNEhWlNyROXhpkVEcH85akxQSg3FWP0+lENYbR2sMXtWhGOk8iY7lZrJIVYBXax5PJxBT9EkdNn7Y+Jyeuo2LvA5y3xw0Zq6YufNwU8eP+8IcUv/07mNzLakD1w0vG1QDoZIxSAgWU6obmSWiYSHCakbKIsAFe4t7SFp2BAxOEsIe4/W0J4dUAKcLx2cQt518q8gupH1MMxiQ3X0X5MGQjhIGX/Of8vkqSGUi9baiq8C93OPrDNNWfFn6sgDGAOfWPYF2bhdiRRDxSX48GWY5HZfjSgYJxEDtl/SgyMPGDxvfnPM8bPyRat9Tf0lZcIi9sX0sKoo/q4odVukpT69tX8nJ00lZ2kLNBrTM8RlrePLkqagdQM6kvCNUp6bWof6DcSaJ5N60ekC17Dl5AwJ0KUTddGt4YTnLcylkt8gCPDqSCRuBU26j4NKGgeyYifmJP1/Kc6fl8bHTAOBExcqGrK+CNb6G9s/t19LyYxGsYDQLxHzVFMB18LG2Ia3YV4pLHi6heed+gJ0G8GcA+xcLNWhok8laJC7PMcAMQesxUHOndBuBrA9fDeBVb/Sw8cPGr6QnaeOvR59UhViclFhFZPkDwAhcf7kTJsYhxgikz12TvJ3c0+m2rBGs98KCCP0PGGWGZt/OFYQzLThLUWMkQZNV5QKS0PSZmrrzisZHXJJDvGP7NLBeGbX6rN9f6GSO+4SzRS0D5b/OhPNxzY5raBeMy72qql1Txzdjm9tHG6hi16mgKKM5eQf1uS1aZhCcuaA2nRU1N2YA0ogGU0ZkwCTpIGRrzxkxu23zYwC4l9QIWBqkEDtsiOinqhI7Nb8kAU1lm2ZzQwkzwBaA6ZH3MHYpLebi6QWhzdth44eNP0cbl9ehTyrkEE+unYrRy7lTcC/l3dMnNmXJgcYxuXxcsD768ihJNJg3kLj80eWRM3SgSnUv1bBtlRwMOBduO8dU5G0hyTzSu6mCLsofDQ3l6ngoD6dCTSeJg8acRNAjMTy+BMIoVDceU74PABo1tAsdz49Nl5QRlSrEOnuhU2J4uVtwY5Y9hLFlmZL/0rTqJoUQ9XzA1jpeCJLcvKAAxORBh40fNn4lPWkbf0R60i8pfzsPev010A7McvwjzgxTIuLdGeaJGm5Z57F5wWfc8hkFCmRdVsN0EFXhkD/OsgSrYkgwTgA4Sd0wzlU4XHudieVYlfB0Mikku+xmhjl6IEnID4CxPPThuSq00StEKndMjYEzzArRP9mPxmdqqFJQqEUntPVUoICjnKr3A0wIq+Bo/DTqX6Ub9+Jap8Zlj40DMBfbLmmQ1bPKH6akNYAYaN52RqJROiFjpRP4fNoDAKAVkJX6ujFPqgQ+W9AjmyxSBFSKXpzbwDj7vPH61SSissph44eNz+np2/jjCMeTfkkBCPBSk67N7z07bZclgdllVPZxzMyLaGHV5G9teoATV7zJ93iRxgl7wRpR4dHngGnSJie8bKdBrz9LwbktQNFgxwUNd83jRxgsHMDdi1J3TycHqksNHbz92L0gzJxcs3fWmXX7nBy8uFC8eo8NRXT4F5U8VnjgZCV9NgduxNcQ0PwYa+AsVFWvRTzcSy/fXqGXQKz5dxlELJ5DoDJIyCeC8GAaOo+NWYaEMl0mpnIX6DQZbC8RWHAtA7wS2onBtUEWm3ZD9J5QGLutoAikpfj/w8YPG3+GNv6a9Ek97k2cUwZtJFLRdXc8M6S/kEZm99c0NIuDxz//obN56nDWjOLaOK994EixWA+TQ7Tj1J9ta7y+PLuo7gULXkvVtHDE1TrTzCDKybX6iutAZmmoiREW73n1201AZruaSyYqxjScUYy19vtow/IWxGKyxCaZdp8Zp0+vrn08HbiwLBzwgLPMOU/79TyMxAv3vLukkt4SOx3LxLSVQ4a5wh+fDhvv6bBxvL9t/BHpab+kPDUBSmcKeyl3JIsxDbDYn4GWPQ7DhmVxdll0tGWXQHyCNYbKIjdUo/PWAVzRR4hmOeFGqk053fBSTmqIJXWckkkk0odhcdbpKQ9K6Rq9Dg9TQwbx0Z+1sekdy8DontuEjOF1ILo00gMZ+/E+Gdwc5Jj19nDDTRq9e49VYRRwnH+CavUnckYuKU/eZY49poSHeJthqJi9uncwObDsuYcge+nHDnaSOpMveTyRALKiZyyC2khn0a1AWxlEDe3EoMV8ygoDxRq4UtLIEtiA2x76sPHDxp+ZjRNw2ZwjPY+X1KWUPmvjd/5jY5gxK2gfx0y1ep0BNE8LoCA+g6nFLKAAtgA2g9Pgv0UBzRrwdy8L0IDCfbiVImroMbI07X/m5+Fh3D24SyNdIrkkg6hHkvYPaD+BArQQhW4/lBswgHeOHXGmeoY1MsLRkFQ0sOiIBBUNJ0I0bMUlkHRNn/HUGfk8mH+f8qDPBJungtgY/VDXmf0p0Q0vJ0tZ/nDPqK7bO8r1BGqIAEfrowYM0GRAbAvQFp0eQgpDFn1mYo4BZGEeUWh+Qw10aaqEOR02vlssh42//238sel5v6SAEbzzdsd3Zg9ZBrEK6wGNfSgWB4tHv+tx0mWIFKuhLKoBZCBFnnpa6QxDws23uXVdSLM7rgNo1OmdkT7eGKrpyC5g7LnhXstNAUs722BMl/XZJ3nD73N2180uvM48q9hkcHadXa1eEHEgkQyEZBg3ZaR/ffiprukH4KVvJ827a+mpwchSiHtVTYw1PJ+IIEwgZqBNncpDoVy2gfnZht+8/bDxIR02/j6z8Uekp/2SchDnOVD2CKhtE5r/VAYBdxnkVJS5+fQAGtzYIlbEJZEXdEaZWWYCcHSUGqNzTRoMsDTciI5yXNB6RytIPaGoRJDfbOgAejAj+bAxa3hhnWgdZJASx41eUJ5cs6+YvKB2Uov99rtzmOvyNwJUaqhg3KCzRxY2bb6iooU3VpWtR5MHRJ5Fx39bpWBtttx0X22MtRa0ZpJI22eaYl8UUsxWZCKNATTpTLMkcHsDYBIIAJuK21jmqgdy1f3NtrcVaCcdiLMtDHaWeVp0BH8AUop5QlmvSUVvwA8bP2z8udq4e3g8kJ72SwrArn6fP2cvyiAKXmIbZNNkkBhw06QQB65r9Tfm8XRjYJlnAQWUBaqnUJ9cbWZRFYIXfA75Awxz27U87LfRCOJgj+ieTs5O/X70uN6Y9MngLgMz4O1eOako/Zh6pT8k4luCgLn3lLJrBmIkgGLArTA33uSCDCkhIel1lVFWsE77AMLaNOhRZ4M1OaRx71CeJBEBYugWKV37CILI0gFcOqClyKDXxznuglsJTFpkDIE0dXmmovIHVR0zrRUd3aAtBCnp5cOsUpxr9xGsS/pSCinvsPHDxp+fjWsw8MXijvSkX1K0B96dtAFy/rVlsnYhyyAR6Z49joy59Xlr2ga88WsW0jDGW/Aki/gyyDRvUAe8MJjy2ZqyK+5mcjcaGeZ3ki6dvccw95LeWxtAefFaxkCbKGC9Y76mTuQshVSbZK+DF9NIDObpBHSm6Y13TqmzWbgDeuxU7ueQSyCsoCXM5/syGWu1IEiTQPS+NCIfhQFilUPYfpMMdtj4YePP18YfJ2c/6ZeUsk3uBfPQM6dKjE5ClmCaPpbZQi3+BgmE7oNdjiwzReMnMDVKLNOlkLxsskgzllmtM1Y9oDjiLraPPfYPuHZ/YxO/FfOIcgkkGh3qbsR7aWCaO6nOx8GlD3Wz9eWBaUJljmKNFoQ3mr4CVGNuVPrQwNC7dsJd0+F2vl1vcNcW3LeCu3XB3brg3BjnWlAro1WGVAZcCsmPwNAxxlw/N60+5PYM2pJYZ9Lr9Xns3Ka/0tTklGUSWhNQJR2m7AQdJmYB2gKACO1k8SQMyKlATgtQq05s2BaNg2rWE8Gs8shh44eNP1MbJzHG8kB62i8p4tDq+zbquv3050wz67M+QykPMkiN6QHcs0gZWwJGYngFHgnfGV816+AwapUBTlhtfwtD1gj3HrEOAA0NJ8BGmR5B3AHcR6h2sN5Q1XsjnUYAyIw0x6CMIK0ClPT1PQ/U8rhRtlLe4udRdDaX1Ij163pfhY5A4OzyLGX4W4Vx3wru6xKjFbhO35q56TYyAGvZD4+Y1RG3B7sVKdI7kovouh/HU2MmvREgInVSMjBrfsoqWzH5pwBSCA2ijcNiHloLK8MEVAZhdYymYhbk3lCHjR82/lxt/JHDQT3xl5R9Tu4Ejl0+54rmTD3YcS/FsDCQYfnS1AE+DIwfB3QXVmVeMnhEKQ1y11qLmZD9wTOzV5aD1zV6l2r6vU5SyYX7zSl3Mr9XadThTeIIyUOj+B2wTVSfP1tH8tk7k0WZ5bkW1GYySEudyTuPFnKIJ2/MHZyD/CH94Lw8ZOh5qLxBdg13/R1eGBRtt0oilH9Z456Kv4iK9koLm13r9sPGDxt/jjY+j/hxKT3tlxSXDl53e3wMjkkG9uns0tnmNgq/xV+AJbYbkMjZpqfEVKThTOqCW1EBGYMOK1pIIZUogiKrWd7MzAYvpnDVHb2ccvBlxJTsgDknZ5r9vrbpkpBSqI8AvTugZuRpGjz6eG8v2wkv5QZNCO+0G7xTb3GWgnfaDb613mIVxjvrCd866/LLdcHdedGO5XNBq6QySDWW2YDBEFg2w911XV2AQf6QAdhz3EgAVABreTXvBkjVY2RRzycm7Vxuiw7CWRagnRggQbspoHPTAj8vNuOuQKSBqHXHCZP6Dhs/bPy52Ti9FmP3MQHMqtUDV5nmJWBr4HOXQca/HmEfk75l8GAEb2yPCoYukAcKuqZd0SSN/WUuqgyNWL+Hd167TLAFXZ+ErvcVnGhNnlHjvXdt34MkLwNZoz32t19LNqPM5XwlMUsDsXckd2a5BNO8bwvumrLMe9Pq1R1X3XJr5XDJ7TIIdEp1K/oAW2J9QJc/glkOANZjyIJgu18ueleGMVplkBR5dY2fopFw9ikMG08NaiQLQ1ZoLElhjdgsidu71HfY+GHjz9HG22vwJUUTw+w7XjGjhO6rAzlOKU8HEODEZa+gAkFMbwDT3e07OSZqE+CGlHH6MP98BTrZuym74BbqoI1r/SKnDN46LbsO39KvjlBAuJdl0Oa9I/muLgrcqsvnmuJHKqNW1cvFmSUwSiEG3tlFe4gZmb44YA36kEguvwGG4xScIYs0TFKIySD+W8wNN9xzm0boN+kyH3DY+GHjz9PGrwRz5/SkX1JYiv6Zm6MkIG+HnN+Vcgcnn92xtFKnZxNGo64xs52jEebXNfA8LfaNNFS7oUp9kMuTXwcqieTrX0oZtJlZ5k7kHOPiDNM7wR+bMvz3Gijvl1DmmJe7J9NZFryUE6owXsoJ32q3Jn/c4p12g7MUfHO9xdvrG2hC+Pr5Bd5Zb3BuBd+8vwn54/5+wboWjdk4F5NAAKougyQMZmbpLBKJZQJd/rBjw3Qc3IJ9EA8NgbJLgjFONiKaOpVdFgER6g2D1gJiAp0XZZit6dQIeaQJosPGDxt/ljZOjxwg/Gm/pGaG+bgX826SqXLywJfX9OfvJAXLzB5BxjR16+VJ07KUkQfXzOANxpl0+sd2MF+SQx6bHLzh3SUpJgTWiSwK6rMUvGwnNFGX3NU6lO/boh3LtWA1htmaueI2Un3cozTN2+lSCnfszCaxs82Rnxu3BGLCdngXITETpLRNzfJSPImzTIjFjgwBkDPLPWz8sHE8Qxt/Hb6kig5o2DuZydws9wFHgl7RMbNpB6/AgduD6ZpryinGoZINrCnWmerMioziPObWkyTiur3mad/NUE1e55+5ks8UT+Lnjeud4QKd8XZ26nn1fB9jPg0IMAKdYWbwnmXBvRScURLLJLyUG7zTblGhHcnfrieLFTnhW+sN1sa4Wxd8+6zH368F66ruuLUyZFUQoxrF86L3Ok5pkEKuJUnHxEkyrA/hNYH1EbgyNAhWpa7Xs9mbySHkun21IEdjmsNtHTYeeRw2judj46+D3CelaKdyMYf9PeDK+Ef2Jwm8AgnWI0I2ZpYa5rkVnQ7btOSChmLMCATb5sOl6HD81ySGCAYEUEQ6ixRGQUWlFpJIHL+Tsv6eXYV9X2aVuRN5lkC+E/CO6x28FYR7aCfxvRS8I7eD/KGa/Alfr2+gCuOb9RbfOL/AWRjfPN+Gh9M75xNe3huAs/xx3+UPVNJOXQHQaN/7emKModHn5Ie05D2X5Y/s+RSuwInZug+wNQJzRzKgv20hgESlkArtVL4pYBFIFf21oWP0JDlsHIeNP0cbl/q6yH3+CWmuuZcG4Jz1+mCc6L/iDNNYZcwcmj/niWMYkwKxASYpKo7RpwfwFDN0TqkHAAq8YzkHBeqN7j96DlrMwJ3zzymDd3QlfvfJh3Cp6a+zchq8nKpMAYwtezhpAOMqJXk4ufxBFm1PvQPZ5A+Krwbsgnco+kssUy7syyfL9PuYRCPr7Cyzr6P0uBISMVlEYHMzaD6HjR82/hxt/LWQ+xb9kkJRzVMlEduXyp5y4QtGMbqpjtpaHyZfDcmC6qao8GKBiGeUqEwH8o3FihRoPMUwfMwF65lBrPfJaf9Wr98Ac5I8fJkHsMrF8x/LML0z2SUQf64sgZxt8MyXcho6kl2Tf6fd4NwWvNNu8M16i1UKvrne4J31hFUKvnW+wctVO49fnheczyZ/rIy2sjI8jxXxunR2uQMuJX40tOAEmyGUgQitd5fezDBzyiwzMUxnuLvXz7bIGKSQVgTso1Wfkkdf1Sniie0lZV9Sh40fNv7cbFzwGow4oWNDFe2cs7HNJAc75gK1YHdqVtjGVlzzrVVjE5gEa2Pc1wKG4K4tEfh4y6cA/6lVVFrRwPCRjRsqTqg4YwQQ0EFzqYM4u/fOHcmXQDUDFsAAWj3X89yyy8cAd++DPGv0Z2eQoACqyx73BtpvtDe6/LHq8rfqLd4+v7Agxht84/4WtTG+fT7h5XlBa4TzuaCei8pVZwZWpWxUSaMwhYYukoy5TBADxH6gwOa38RP3vkwc0DJmZucraGns0JYkxUTsSW+PtSNZ1PQWQr0BuAK1at8PVf2CoqJux9Qautx32Phh48/Mxutr8JICJ5fcwQNqp8D9Ny2T0NBJ6FKIuBwSn/WUBsTsn/Y6VbRKGEx92oI9jf0h76ncyezrj00zeD3tgffdpswwPYVElOUPYZxRtCNZFjRza57Z+rnpWGXeWFbvI/FxyszLaQxiTMxSOrN8jJexkkwDcWDTWF4ul7maroFXpu07KWSQJIdA0D2ifBQJny+qsE1WJxDokDKHjR82/ixt/IJEPKcn/ZKShdRrpBi79CAy6gU0eFt64VsAmn9GiwXNrY1BVXDfCk5SNcCuLSE1vGwW1sjAqa1oxAADLyE6yZvPOmrSSJFXA84M4oeO9bTHZuex1mYvp8ckB2uVUf5wZtmE8FKW6EB+Kadgl++0WxsK5oRv1hc6BEy9wdfOb2IVxrfWG3zzrMzyW+cbfPu8oDXG3XnB+X7RRvTMkJVC/qBqsoPHjGRZYkoxPh313TryggGFEMbRg2ZzBlOGM1idVXq3iow2Npxq7xaXQgBoXMmi99kWZ88AVVZVRlTiiukPDhvfbD9s/GnbeHsdvPvaqaAtfcgYWShkkaECZvAagKlSjEXVLMKbSHBfCxbWovl2PUU277SbYFY63YDNIcMax+EBkCo3NNxAAV2TJ5KnS6B+FSY4s8pr8sfmOhfaib2AxuyG20A4C+Pe2KMD9oxiXk2LyR8vcNdOeNlOeHvV5W/XE75+foG1FXx7PeGb5xuVP+5PuDf5o65FgdsIOBtwRaWPAPDEMvdTsoH4TQwT6G7cV4Ab4N9jlAm0ZNJatAuS8k4MU+1T0ApAizYe7QYAtDOZrIEiETSfbQ44bHw697Bx4KnbeOPXQe7zT8gpAn/vKzJccrHDBqzAJWSQvT/vdPYxuAggd+NlgHQQTbYYEEaSP4a4EL3oED/yLtJD4H3VdMkZtDPN0cPJPZuyd5NLHhU70ocwzsI2Rln3bjpXm+yt+fhk0EY1WBwFQMKxS/LyhRunvo/iUMvX2SVix9jHk+xnV2bZ2BGN+e2dkoDsBwsRYFN5qwuvBz8i+oWo+bmHjR82PqUnbuMyS9YX0pN+SbUbBi/cgRssE32o+KkyyIxBSLSDuWp0dauEWgmARn7fWc29rL2IbvkcsR0nutVprNliQaShEgN8Hx2rLo2oLKLss2F0o82dyQ+lfJwPy+JA9nwaaAPivWtcm3U0QJs7j8EhgZylxNAv78htaPPfqC/wUk7ReXzXFty1E752fgP3reBlPeEb97c4V53U7eV50c78c8F6Vk8y7Ty2TtaVQGtnlrteRteKbmKPA5Cn/TQfj/0XQRw/XZ/8xZILMOXjfcwqhWjnsjQApJIIBOr0IKTDyDQBrRKBvYeNHza+m56wjX9X5b5/+A//If7AH/gD+Et/6S/hnXfewT//z//z+OIXv4gf/MEf1AcSwR/6Q38If/pP/2l87Wtfw4/+6I/iT/yJP4Ff+2t/7Stdp94waOkPqnq9AXj+DM4F3vQTlCrUkkmZTWsMoOF+LSjcgHXB/ZIAXG5wgz7J2il5KBU0vOBzVF54RaGhOBOzoVyqRb45qGZQe9qA7pHM1EEc8/yQJID3FB7K0/lZ9nBd/h6dQboO38D4VruN4MVv1hfmflvwtfVN3NUF364nvH1+oaCtC75xd4PWGPdrwf3dqevyZ+6Bi+bhxKvJH3D5A68GYE+0s5q2bYBK+8dt0iSP7Gr3Kc+s1wdom5/nzJnBq71cktwXlzls3PI7bHxIT9DGr40mn9N7Ees2pH/6T/8pfvRHfxSn0wl/6S/9Jfzdv/t38d/8N/8Nftkv+2VxzH/9X//X+G//2/8Wf/JP/kn89b/+1/HWW2/hk5/8JF6+fPmKVzOpL/4QBTV8dnrygh22ebCcTypmrNN+18bhBVWFsLYSkoh//mv8hM+6SQG0LBMAiGFnPOUO5L0ptHNe8/Z+Hu1u30vzfu+6mK93eQgYkztQ0MDGLrceTXc2HplPhX2uKn2czZvJR3jWKQjQgxdN+gjZw0Fgy+Fanf7oMX8OEtnmmUG0e3xLf3L5b4xTok3DInsNhr1o1CGiyyUKdDI7Pmz8sPHnauNXqzLSe/4l9V/9V/8VPvaxj+GLX/xibPv4xz8eyyKCz3/+8/jP//P/HP/2v/1vAwD+x//xf8RHPvIR/IW/8Bfw7//7//6jr1VvKYLFAESnnRDQSh8ufsMyvFPZKkoqAOtgbqTGdSaNXbgrfVq0G16xxrQAOs127mRuRMEsG3FMw32iNQDK0kdxBlQm8VQmupNZqCdno5lx5plR/X5yLMkI8i0tm6cfGIMWacMsXzYd+qWCO7OUgq+vb+Db9YT7tuDr9y/wsp5wbgXfuLvFuepso3d3J4gHLt6X7tV0ppA/2OUPAajGTUZn7SxDPFJJ2jZvF9glAA//SPtk2LezOXZcZMEGThLEqNHUgCYAiGxuH/OAahpfktkrcNj4YePX01OycR8F/6H0nr+k/pf/5X/BJz/5Sfw7/86/g5/7uZ/DP/PP/DP4j/6j/wi/+3f/bgDA//v//r/4yle+gk984hNxzoc+9CH88A//MH7+539+9yV1d3eHu7u7WH/77bcBAO1EqEuv0NBD461NvTPP08Q0qNrxNvNlQ8O6lghHOdcSYLipJzRWi1pYAQtoR+6ZCm5Z2ZIef6/ni46LdiKXUGxofyBkEsDBZyAPkPbkQ8T4lNyeLskofkgDDR3Qe0zUAev754Ezm0XXv2wnVHDo8graN2PgzK+d38DLesJ9XfCN8y3u1gVrY3zr7kZ1+ZWx3i/qEr0ScGbV4FeVPSAqfTjD08Z6kkKwIzOk5d1O4AfS0G5ekEHygK4PYmvva8by8xiSVgAWtU9qKlGR+Z5rn1QHe87vsPHpOXHY+GPS+9HGZaee9tJ7Lvf9vb/396J/6S//5b+M3/N7fg9+7+/9vfgf/of/AQDwla98BQDwkY98ZDjvIx/5SOyb0+c+9zl86EMfir+PfexjADpg8x8yaPfkEEuX3C3VAwoQ6XJIbRweUavJIquNyeWjSbssonKBTxtto0obGPIYXwD6evIiykGDWR7peY3HAhjGEdv72/fk6n/zte9RhpGd76X/vWwnnEU7i+/aKSSQu7aoV1Pt8sfqnk0peBE+/YAPmumyg0sge9LEJHsMEsQkYVyTKy7KGG37tyuX7Fz/oiwyNzKYGgp0+xxtmJJd02Hjh40/XxvfN9tNes+/pFpr+MEf/EH8kT/yRwAAv/E3/kb8nb/zd/An/+SfxO/4Hb/jXeX52c9+Fp/5zGdi/e2338bHPvYx/ZK6Sa6a1AtJCqEV9Dd7ArO76oY3DYl6QLFp9Y2xKinE/bqgmRxyqicsNlEXQ7CYVg8os/RO2AJRL6nGOgYaFZVFpOnozR4ASQ0xT04SPIYgRtnpbKYLxw557DDPneT9B2fr6PZoeh/2xWcW1UnbdNqBb9YXeKeq/PGN8wuTPwq+cf9CZxdtjHfubnCuRWWl+wWtEmRl4D55NZ0NsOuWWbonUXTUJpbpdQhc2DZt310H9ht3tx+6sO6bdrbvpQ3bdBstFspkLwoyTzwhgIqWB5Xp+fP5OGz8sPHpQZ+YjT82qPs9f0n9yl/5K/Hrft2vG7b9wA/8AP7n//l/BgB89KMfBQB89atfxa/8lb8yjvnqV7+K3/AbfsNunre3t7i9vd1sbycCudwnGAo1/PJ9mXYK25kEkYqmTUVaqe6pJLhf1bCZBHd1QeMKrg0LLYNWn+UGd49tpEPJnFB1RGlqpteLekBBa7JAcJYOTJdJNJmXVALtOckhw7FSUh49UO6SB1V0djtzFQ49HsAgf7zTbvBOdQ+nW3y7nrC2gq+fTZevBd883+B+XbBW1ukHVu1Ernc27YDr8s28mpLrrUohtOkAzt5Eu1JI3ra3Pqe8fQcjbiNEO+t52wTwTfLt8/XSeVLQ2ajJd0wCNHvBVMCHpjls/LDxZ2fjj+MY7/1L6kd/9EfxC7/wC8O2/+f/+X/wz/6z/ywAdaL46Ec/ii996UvxUnr77bfx1//6X8fv+T2/55WuFfLHBGAA/TOTgJja4JoskgzA59+R8IJSOaQJ6fD6XNBkxbkVLNRwFh2ok0VwEu31PkvRsc6MvYFgcSUrIA0VBQXKQl1zz1p8zLVjFtyEBxbpWn4hzQvwDmTT/HeOzclBCyCA60GcodF7R7KwSR9LTDvgAL5vS/dsqgVrdc8mG5vMgNs9iKhLHxmkQhuZYeiGkAmkO2DeY55XNYUdMJPbkSBiP+DShC0T0n7Pau/lsHdJyzPyBsLLyVlmBPFm2z5sXJcPG+/7sbM8p/exjX/XvPt+8id/Ev/Kv/Kv4I/8kT+Cf/ff/XfxN/7G38Cf+lN/Cn/qT/0pvUki/P7f//vxh//wH8av/bW/Fh//+MfxX/wX/wV+1a/6VfixH/uxV7pWvQHohLFy0VlAdCwXfaNHp3NKBGOtjYBqtlF1nLQK9YICFNQLL6icpBCuSQppoX8zCV7wOYB94lWDIgGcqYRMwcY2gZFFZvDpvq01ZKnjMfEnUWZJ4/dGoqb+Bdffm3BMO9CEjFnq8jfWW7xjM4u+E9MOEF7en3Rm0cqo96Xr8meOIV/YPZwaQCtMZ7d4ngCz1U3DAGqafrViRuC+Mog9zY0/RjY5LDvgqG93eWSWUPaSEED+5SOdwQpDnSb8OS0adXaeyPdz2Pg2HTZ+Ib3PbDx7ZF5L7/lL6od+6Ifw5//8n8dnP/tZ/PRP/zQ+/vGP4/Of/zx++2//7XHMf/Kf/Cf41re+hf/wP/wP8bWvfQ3/6r/6r+Jnf/Zn8eLFi1e6lg5gqNH5cx2JTbMNIKSQzDw3n6qZ4fioxIQAMEHjSQCAqKC0Fl5Fd62gkHstSeRZSeWP1np0tcsjgEbx9+UMyP40BQ3nHQPMgIdsQX8puXcVANyLVn/vBKeYbqCKyh/eWfztesK3DMDfPN/i2+spph24WwtaU12++sRtZw52qfKHAjiAWgFO45T5dmAE7p5eH4++C2aJZWBs2PP2SBNORpmD4hjK4JR0LvdloQTGS9fwRsAX/VjqG8Wfi3SnAIeNHzae1p+Hjbfv1pcUAPzW3/pb8Vt/62+9uJ+I8NM//dP46Z/+6e/oOsEaaS4xxFsbQP+0nMG7yTD/aUnOY51VIbDJImtjrMRYqaCRzsezknYcr40BNrYwVQY704OkZU77kzYfMscIUJVarrPPOTmrdAZzNgA7cH1cspfthCaEO5M8mrB2HNeC1YIZz7Vo4GdVJh7TDpibc4DXf5MOP7NHZHBmNpk7kveYJhABNiQygjYVzUXt3vP1RfKXQzrRgCVEXbNvCOBRXk7ZUcpzs3HnenG+x5jMbPmw8UiHjT8PG3+sb/kTH7sPoNN+Bc2frgHgtDz8hWH0QSBBOqWzp/NaUFnHTiusE8UNnk+irrouk9yKuk+dWsViEooHPwIqp4wSyA4gd2SOOP7Kvr3kWr53Jp+lhGuxuxqfpQRo72wssrUxXtYTvr3qEC/vnE+4Oy9oQrh3ZtlIAxdt2gE6U4CXz92TiVd0t9y6zyYD6HbOLIFQS2CdO51ndnmJbU4ptHdK6wFkQAzMvt0BPcgijEEeyawzbiXl6dfxexSkF5SMz3DY+OPSYeOX0/vNxtteR+JOetIvqdDh9ypnKPzEODNodzNFMB8hGzW6ERrZUCqNUUkDIBduYBLc28ymngYpg8S08aodyNQDDwvadOwWkLz7cPvpEtir9EbIAQugx8AI4c68nXTATNPr64KXVRnnt9cTXq46B87dWb2bfOqHYdoBjwUxl1sPXCTrVM5xIxmYGcjxGGm5g1q2ssjELq+C94KtDKzQ1ocvEk7bGZ2B2gHizg4OcB5Z5569ZW0/OpjzSen3sPHL5wOHjT9FG/+uOU78UqZgjNiyiL0OwS4Ppm27GXspetCjySGNAW5gQYCZSFCIbfrtEtNw6+iKwAqL3G/KPpladCav4AAwk0Qcx156bEzIXspjqTkrdkYJIOQNlz/ubfllPalLspDKILWgNvP+Wouy8TrOKuoA1UaQeoMo2LDFWebAtJ2mY6l1OvZQZ/O4PBsHRkDl3XmepqmhD3C3vE9nznVvPAdtXJ979tcAPfQhG6Dn/oHDxi+nw8afno2/Fi+pmFRLki1MBeG/XiD6YlOGkGNMNizAAiClkfspobIEo2UCKvXObCZRwxYF5UIVa9GLLs0CHA3cHbQdlHveTe9FqqlAfKBQQNnmuTmA2QYZpXC3bSDcrQvuq0kka8H9qmO9recS8odOO2DgzfLHSiFj5ODFYJt7zHJ3WcvlYmzJwFblAoAfV1Yqhwi2DT9111lKTJJgHkxi7uJ6IjG04fe2wM9zgO994UwNxXzLh41fToeNP1Ebfx1eUmAMb/GcLr21hUXP8YZgrzAjk/4nwMA4a1O9lkkDIoXE4lsMoAygmo5PhIUIK3Q9vJ3cWwpikyN8Z+nS0Pd7IG7oHeVrKzoUjiiDdGZ5tiFfRCgi651tB7us1NnkMAQMArAzW8xlu8cW95Zn8A7glw5yz/td6fXOPqNVRqeMhM5AuRNVcbw3v7DaiLcDkvO05eErCYhGwZeH5I3JhXse8jhsXI85bHw3ve9s/JpdpvSkX1LiD34J2FEY0penTmUhACyxvnuRkEUIrQFEhGryRyWgchs6l6uo1NCYQhrxQTsVwB247yY9dh6WOQ7BAavLyogBdTuuBuBz1ekGFLQ6qrMIqS7vAHbvJgetJBYpWmYEbKl/BueUdrV7kUkK6b8zs5zlkFGjl36NnRTgBdBnwE0NgttG1uiTvTjrjGMDqfkBdbO0vvwQ49z9Yrp0zGHjsX7Y+Da9L238tXhJMUzO0NLfvLAykB2wSMs2rbEv7xWcuJFC0CqDuAFgHWUman0BkdhcPArswg1VkocT96FnPO251+a0B8DHHDfef2KYyADubsfV2GUz9rxWDZOstc+JE7EhzcYn8+mvreMYHqyY5snJcsQMqlkKGUBqzNGnrMgSiTLOK6DNoE/X6gWyLaM84rPYwTlmhGxA15A/mnRZJA0C26knOv30zxnfnmS3oeM5NQCDvaaXEHDY+F46bPxp2viVKh3Sk35JAegMcnjLY7Mt6o0z8NMf/DzJK9jUuPQRpAE1fjJZBGBwqdHhHJckiViH9ggAZ0DKTk3OLPMagOe8BgCjA/lsbsjNgOySR/NJ8jz40w0yphcw8F5ikDvAneWQ+bisu2fmuSeVBOMEtp3O6R769bdlnqcMoL4xNfoCAoUqMgDPiWdij5GRdAbrx873cy1tvpIOG39UXoeNPx0bf0x62i+pDN7MQIERtMN+GY4NV8vU2ZwsKS7lY52pAQuaeT0RKUNTMDbAvJ8ajfEl1eQPInkUcP2ae/s2x10onr38fJsu23GNQ9N3l1sAMTbZBsDNW8kLF86JuhFfPCSDMzHUTVS+IOSRMXZkZJbjcm6QL11fut0I4PPqkJ+T7CYeivIBUC+DOKkfxjBHhExlZzv10c5p5xYPG9fjdnM7bFyXn7iNP5Ce9kvK0hB1D1wGrO3r8SSShpWRXrAT8+xUgSAkIHHdXi8qrIBlIbQmBmxBYa0OByw9IH04YPdYZhCoKwz0EtscCFcCsKQ8fb01ghhDdm0egt6B7ABOjC9fJIN1AO58axNb7GxSkuSRgNtkJxiyA3cD2sws23TdOc33xjLsIyioQwqxghOm0N+lZVktTZXNAIrWvQhiVt24F7K+a7fdBvWcmovrsPHNeUO+O9c4bDyl96GNP2AqkZ7+S4p2fi8wSiCxynTsZnnO25KSEfskhoTRi7m3iDFLbx9qMzde0blUvOYc0JdYZZPttswQgX1Qzmlv+wxa3xaANolEmaVdSKj/7d3AI5PQtog97ckcw3q+7rQ+Si195UHg7u2jfl5o8LD6Bo1qRxOA3R50h6R7pLTsHyi+3cfni+OvpcPGDxt/7jZ+JT3tl5TQ+AmZrWNP8vDtKTJfOGpoArYuU97ul0UGQjJ+qDzSDLCE6wzzktQhad/MBsffy/ldSsM5c362zYflEQOtrw/JLdnKR1grgZpgEyx4Ic1A3WedttzmbdKX4fukL18B755m3w/tN6zTrtt2RpdM0qCcEOkd0GJMdGKczcqJrbEXgk6rXVL5iLJL9/JFOl/L9LDxOb9L6bDxp2Hj9DoMi6SVSlqIMOPMRCgFN8bnrQWmjQxzWp91+50kpte3ZCjiwCW9EaI+z00G8ChnjNs6c00gzYwwTtwH8VXGksG0c1zcV4CiM88xn1TQUW4duMKiHc1m2JlhD1nMIHVX28ETStJy3OggfeRztw+Vr3mlcKLtnlvFXhaRj9VlH8esA9dfGsK9LDRI0qbTaG6yYstW37bPZRGkItbG8bDxnuHFWz5s/AnZ+IURrjbpSb+kAK38GbjjATvLMxsd9m0oybAq0klG35aowkWU0AZsl7VzP8B0dOT1MeuBWV6yT3pg/3z+1HhcTPMuB6wXw0PX82tm8A6A27lkAvxwz/mYRxr/7vnzurdTrtH7aOSENExMl0niK8juMeQPM5yQgwzILqlFX5Q/GyGVzWHju5cbnuGB/fP5h42nzPy6v8Q2/piywxN/SfEZoBPAINXMrWDD08StPdu4M0pgZJd5O8sIUmdKlq1bqYjrt9IP9AoBQCmTPfBeAqokzyKP7MZ0/FDB1yp7B2Tx7L54AaNqq+nZOC23xLRMi/LGLQai3Gnsstxx6feSJPJgR6uBZWBpqSERoi3TvNbQZCBNQPZtziB9qJl4dvvC0WWLM2kS8kpbNOZGSJl0KzTcv6RhZ6QcNn7YeHq252Lj5wee1dLTfklVHRa/Adp764G9jPDpF/Mi2a0jwiCR7Gr0Cbw5xRYDMdAble3BGcjUz8/sMoM2liliTzbLuzczPdtmW268KNbFj8/Pnw7zcwfb94YM5iLdvJz7GGDkBklD9v2eHwLvfM5eimuM4LwGYs33QsYzvmV/+3gL3U3cAZr7iUKSKx3MZJq+sHnRlT42mh6HLpHIYeOHjT9DG38dXlIRb5AqSgRhQMAV8F5Le+AlXGRjrtPryv5Be3r70FmbmWQwS4zxGrPsce3BMjuKFmamVLZ+4bkG9Ah14h7Hp5V8nSm/B0F48fLv4sQM1gsgfvz108oD9xJMO4rDDS+VcUvLYUwahxTF2HqZiiBeRIeN713QnwWHjU/bH3/9tPJLbOOvRZ9UuQO4AO1kb/MKLUEGIKqhqs1qoTjbGeSQlGgyQErHjdLIDuucgDscMejf6diW5I2IyzA2mTt4BaAMahnz3U25H8IZDwnCK0lgDNvZZmKY7MupnOxGCYiAx37vdv92rjRv0Lb3t8cqZ8njIaCF5p0bKQDutZQ7hvNIy3lwzoGV7oC7s0sZ14HRf9r2xVAzvtECHyOWBNCy8fiS9McFaOYFVU8UA8TWSjFn2mHjO+mwcd32VG38/nFv1Kf9kroXcJEArU1vo4UihAYxV1wzUv8szczOUxj8aLwPAnfvxjJg7aBXAm1LgLXtg8HnW5lvwI05MRePmyGi7vmVDDvyNABSANjOmy9DgLj0kZireEOzWybTvSfA7rHJPWYaHdb5PvLxE5D1EInrB+ucAT9dP4M3lptsynyIV0nbQQCqlUmuh0LRiIqBGaQvIDZZxCWSVpTSx/iUh42ne/RbOGxcD3maNk6vw0vKB2fkiujApAJjPYlVmL5PTRmSRvTby03gNGHfauJijyvQi+B1O5J+TIB32jYyyjRmWGJJFxmmPU8GnevoF5qb3lCRjyTQT4zhbfL17FjxhhHdSOOCecMlCUemUx5RxMowzdfILzNX396j+nGv4Pp6LeV4lUvbgskOZYP+UjFZhPzrSCQcERg9Lgd02Ph4fRw2/gxs/LHm9qRfUqeXapb1RoJl1mqM84T4PG8nBNgh5pnEgCzJ+Eg7TQm0Lb35M3dKcfQlyUPQO4ovMEvyEZcFfTDL3AgJDQC+fi/URyIm9V3SRmuybGOVYAGVpkXBAuamjWEGsz8XgFYZjfQemz+nBzheKhxvhPJv2r45jYDo+LZ7pXQKJZmL8jn9cNtGaZsxv+SVdK3R0DqQfiwMpGK/rRfKLJ3ke/ByiWcClHGaXMILhUTSTn2ZV8RX1WHj870cNv7UbRznx72lnvRLiu8EhZRtCNsw+mIM1CqnR+F3hqKWRwgNG9Q9pYYPaWzAG0FuFzuP0ff78jyycgJqsEpjGiTOOtBB64BNxn5RKvBnbc4cKTVOGDuFXe5hAZlcwtxQSh+bjXl83lHGIQhzbxRzQaXn75JHv/8BxI9Jlt1Mep1xpsM8+51tifVJ3xnjP+eTMhAdsP48VTpwh1GpvYWbQO1ZErqOXwkeU4JqACad9VVYG+DaOPT8w8Z7GR42HtnvbHs6Ni7nx33uPe2XVBVQFfBq+ieRySKi400ZEIiVxREBUkQHkfTOzwbtxAvjIoS1A8jf2NlN9yEgb5JMy84ukxQyaPJZAkHffk0yIM9WgESu+mXJDqJ0goHYZQ8iTCzTuCk5SMn2DTYOXCsGGX8fBO4EsPwgmw5lIJgbRHp17SEZwG4cybVbkXl9BHZ/Jpk0/e01hrprAikcj0cNQLGvp6J2xauo0wRw2Ljfk2d72PiTt3Fuj7vHJ/2SWr5VUWpDvdU3M58FddXldhLQCl2+AVo1xtl0H1jB2xoU7KcGl0vEg1AIEfSYbSKnPByKkPEV0e0+LlhmXCF/CGyeGthy//XtZMdnYHcDSXfjjQk5s5zaiwCuIEbCLgJamjLMIliWCmZBKQ0LtwCvj3JdmwVjxnVZibl7nMXFEI0PoT8XWt4//e2leI7OIzMmc/vapQ5K2ySyyW0BxEAMuazdT2yxl72YPCV6jABUm9WPbWvOSGWbX348cpZJKlsxq1ksOg6N2m3fdtj4YeN6yvOxcazrhYIZ05N+SZW7hkKKTGECL2SyiI7OrJ/qvbq7qyTB59YhIhALmgWggaAMwLbriYSBbuRlocczzgxmN2oDMqXlDNpxBlAadW57FIi7Hks36MFqM4jRNXoDL3PDsjT95YalNGOcvVO5sM4p5CNVq00yamgc07PvNDok2LC2x6QAXH5kX06XHrcpDQ5WiqkR9qplXB/o0oA76PMZvA7yKh24GcjAFszOislGcygEUAMRQWoLMFMrKotUOWz8sPGxSJ6BjXN93AizT/olRbWBVjUyYUEDgz1anyjcd2UVZZLuzkv6S6uVpVCPoraBI0MfZmc42iW5icxPLNMNa5AJ9ow7pwz6lE/fNl7qcQXT/zLDjN/oSNayK0WnAmdjladSFefTBYUEe6RsPAjbRma694eew9vLXdkjP6Ng07bm87d6TT7muiRyqbGJhnWPRe4xTZNIpqvrj2n3JJ1xEhjSGqiQvoVU5D9sfE6HjT95G3cX9ofSk35JlW+vKO0MWosC9NxQa4EQwCcGWwcdr0BdnVEQ6i1CFuEKNIu1ag0gJjSYLMKkn/vFatPiVZSodq8g5z+ZzURAoR1rLYVto61RZqPfYWcB9J16jV0JtEL2jCzaR1Ggvyf1cuJFcDpVZZal4Y2bMwo3nLjhVCrYn8kknftWcLbLr9Wn35Z+4XTffu9Z1tnbr88mA1AG8EYjiJBEhiJIxzqF9HP6qTTUj2DMN6hnLuuUojM5SSChzTcZ2CWt1ry15i5h/Q/9/J65f/0YkImAM4OY9GvKpb+FDxs/bPzZ2TjX+21F76Qn/ZKicwXRCrbPy9aKYiymOWY1WhuytxWTRog0+pmtf7kRpAjYAtDIZ5YUAEUN0MdH8xrOnqgZyMqKKBidDiezT5QiXTCejQRyNRNMrBIW/Y2QfUCj/FFKQ+GGm6XiplRd5qoATjczTsdNKCw41x3G7Q1NutfM1vae78Hn8fMMxLpZtufOrDOvY2Sbe8x0N+VjMvC881iS/OHeUM4qW9P9GbSzju+3XoHoqadmAZAEakUjIFs7bDxu5LDxZ2Pj9TXok8JaQdzi4ZkIjbV2Aozm2RSRzgZin5CLirIhWWHDTiVZxLykwh68Q1bUIOaQCQVqitQggk+pDGO1A7MxkDsjjU//dEzo8OiDfOYk3lAk4CrD9MEd7TlYoiOZWcBF2eRSGm6WFbfLikKq19/wCiYJ4DYwVuKhAz3fgBhgyTuTHcCZUM0gfgyA0jNuADeR7g1o07oeQLvgeeUU978Dykvb8nqbjvV7g6g0QjRII9pY8GHjh40/Oxun9qCwCuCJv6To/l7Z5lqAwsDawGsDCoGq6D7St7j75lPzZYlPdbHoaKpm7FBZBIUgaMoyCxB0kdVYBRJurHFPZicsAnFBIYwo2a3VaXyqiy1ZQKTPu0KwuvZP8inF7JiEzigJkEWfRYoAiwBLUw+nU8WyKHDfvL3HiRtuy4q3TnfaoUy6DuiU4GsraCA0EKoF5OROdAlmSTEKggdqbmSQtKxAvwCoAXhIbNGLzsooCmgL2j0QD/p/bkjzdTcFnO7TJQ2vj9Z/KcsfrYFqkkV82fblvLbPTvr1RASqta8fNn7Y+HOz8fa4YdCf9EsKtQFUzcitWl2HB1TDJ4BZA/K8U5l9OPkVsa1ZewAoG6VqNdxMFnFPKq+8lGa2GZbhrIx1mzQ7OHVc5z/xxoDcxXc23Cml82LZmLC4Ts9Qdll0nMNSVAJx+eOGK26XFS/KioUrCgluWAG8tqIjGwhjoQrGsulojhsbgDktY2SJQxaXiJ81dhu2mE/1juEHQLxhqRfyu5Zy/0IH8vjrbHKQP4ZllUck75sT+zNZrdsb4bDxtHzY+POw8dfhSyre4FaRAoRvPohAXIHC4LWZBALIqq6mrQjaSmDWT34+Ay7rtkW/SkUIdendmdJ6h7JPBjd/o1O2IIZlyPaZq5UZ44FJAp/efKdBxtp0qBd0kMwpXI6dVVqjtCTwLg28KHBPS1XwLiveWM644YqbsuKNcg4AL+avWkiAumCP70Q8SQLvXueyAzn/bjN7sKb1sF3meAHEe+d6BWM6Ny0/Wsv3FLExexe9AN6QQ3ZA2li/Otjsi9lb9sPGcdj4c7JxeR1eUnK/AqcVTsnIC8iWGYBQg0jR45mgLkANbB3PtZGOpE76+d6KAbwpCIQJskCNg102YQiPn7QRuW4A1LrTa7QmaDbESiOtN2kEIbYOSIsBaVbn3rcgsBgSzWfTh0u6MeQQ93BiGeWPmxWnk8ofH3hxhxfLituy4sM338atgfetcqfuuckB986G3OZW8NKCHyEOXrvXRvDhY1xachlE1/0ZbFn6eoAaeHcgtvNikjfLZNrdFQ6JokwfAcr6L8aRvAojzdq8A9UZo9umx4ZkIA+paWPfAOECoIKK62KHjR82/pxs/DWIk4I0SNUAMbBGN0aUMzdg9XgTBq3Kuqg0cGFlkpXii5Oqyh8Mk0UMFNQI0iR0aCUq1lGcZIo5uY6v7YmyWRH7bGanRD4QqIHYhq5RnJAT0c6E5vp2GcSZpoOXMMkfFmVfVP44sUkgZcUN698ta6dyTmcpYAiY2jaeJFjmdWapB+8A9VWYnD3roLu/6vl7503gjCmyL+x/12mWPh5imhVmgKrPScVh44eNPyo9KRuX1+IlJfqiailorVG47VLTYEhhA7KQxpVU7fRti/RxpFZjkAIdG42hzLMKGM4OHbWkEdTQY3ItO9vMyTuafXbTZgyzkTMKglDTe/f4TTFKZMwzM83OlAysDAgJUOyPAD5VcFEPp5vTitvTiptS8cZyxpvLPV6UFR9cXuLWwPsm3weAvfP4TAV31FCmZspHhY4vfQPxxuvpCrAjdmQC92NZ5yW26bKInx4qU2zwevPWMf3Fuvua+bX0Ys5K6T3zokrgdUC7a7k0k9AA4LDxw8bx/Gz8kelpv6RahQumQmz6OanbLrzgrcAZILahZUjBWgyEUiymBIK2ALLo9mYeTw0AQ0Eri2jgSVM+0phskk9lks7GOAHZZ7Rs4sOtEFprqJXtPcsKapMVxIHs3kTSG4mN2ZBoQ0YCWjSIkRhYTiuWRWNEsvzxvbfv4K3lDm+UM37Z8g5e8Bknqri137MUnKWgCeMsBe+0G43Rgd5PE0KL+2XEKNdWJj71Qvw9AOxhu6dL2KBxvyQs+r4hzgQdkyE15byiIVSm75PFubbvk7cRBNGX4sAlk68YNksrpcbh1UA4SCJ5mVv6qjps/LBx3/VMbPyRL8Gn/ZLKSZqyuMkLBVBGoy/0Bmps3ivm4SQGeDfEcDG1tsGOk1hWBur9mHvJwesAjl8h7TQkHU8NAFrT6H8Cm6eTAOCOWf+djdwvzgnApaVhYBS8S6kaYe/yh7HKE1W84HMA9wWdBymkQVCooaBhRenFLP2pxf9zm84McV7ODPI7TSOxHyWOaV9OD0ohjO1gnHN+tJPPe5xEun2MOw4bP2x8uy+np2Tj8lq9pKwjGYBSQ5v/hapFNouAWoOAFbSrAAUWW6Io4SqQVYeI4Qp1SyVE0KNOhZAIn2v3NnKyg9TBW1jHCptTbc44gZWKZtUYtYr1P+rIAALL2yeSE3Ra5cmkELJRrLlUFIu0vzX548QNH7i5M/njjA+f3sEb5Yw3+R4fKC8DuC9I/ZsYDU1uN61TE40jCaYc8weRxYr0BjBLHHsM02UQGrZdqNrMJIdnn46bdmW2OWDbRlXQ+Zis/GxdPZ900FUR6EgM1ZgmW7Bpg7nFobtZs8A98ADLq5F5viX2yWRfRravMSAuh/Un2H9BHTZ+2Pi466nb+H7o9jY9j5cUgOioI1EQN47PWx91l6QCK+nYaEKglcDMWoaLdeqC0FZlgQyAV6BBAUqLfQ7b56+zjeyF2Yf/V5ZHUFC7RBIR7kKoSw15Ya199GUdiRkmmVBo4wOAvcHgHmy5LDrcS2HBm6czXixn3JSKD9+8gw8s93iD7/F9p2/hzXKHF3TGh4tKIQBwIo0b+Va7RQPjXhackjtQE8LaOACsIEZn5Bm4acTrGAXb/2K4lfQXdXileh+w57xbbIPr695oBGkn2NeCddy7nRBpf0dN8gcDAnfHdmcC0hcAOOpBZRHS500u4rpTrMpEvd20RLcg1oK+UgiHjR82nrJ5jja+k57PS2pOGVUiVoGjFYyf7soUMjOSHbYkk/Fdm7ogg9dZaHHgZVnE8hAhVGOVYutEDmDafB47cBXEgoVbsNtTqRZdX3HLFTe8YuGGF3zGCzqHTu/ALYae/rvjkZPuy+93QFZmjpvy7ds35XRl32PTnhySt+WpECjtE7Lj/Vhbjjgfmggt+Yk5X3/I6bik7cfyxCh13UCc9z+mc/mw8cPGn7KNPzI97ZcUeQDhA4AOn34tyGE65KYL5KNFk/T5buxPLDZCdX2YDID0RwPLZIJq5RZ3sXALLTyzzYgxgTI4Z5nnlhlnB4tvy66yzM2KQHBTNLJ+oYa3Tnd4cznjlld8+PQOPlDu8ILP+FB5B2/xHU5U8UH+Nm4Sk6wgnKiA0VDVrQwVHBJIbT4ydCoDTKxS+vY9OWT3d67WAMe844Fq9v0GxACo9AOoybBNQdtdoyE0djD7VNipcejDDCHsQT3rEus0/20C7OtH86FadSgioR5PwgBQOnB794jtP2z8sPHp+Odg4zIb+n564i8p/+S00rwGZmOaqDqUCgH6WW4ut+GpU/WPWdCob0e1uqkEKjJ5Jc23pfkXGyfMR14GgIW3sQEqLXSgBJgnYLeda3kjwSS4LStelDMWbvjgcoe3ljvc8opffvom3uR7vMl3+L7lm3iT7nBDFW/yHQoEFXr9CsKZFhQSncrB7q36/TmImw4R4B5aWXPvkkffnnX6XfBeAPJYqKkqH/rIyOC1/PuvASkcBVKmSqGHDPQ4Cjz5ejQArKAVsMooPmKDvzSIdMy9+RZrhRTLtIm+Jdzle+5QPmz8sPGdY5+8jbeHHlLT039JvUoK3dSIiGv8PpaUV7AbHRDGJUjbfFm8nqYAOYwavS63zXZPCk6xjluNjWlCKpFwPqYzU318zWshBfEN12EATZU6anK/XXEiDWhkaiiQkD7CpetCatMT7kpAGbB+jw8B86H98+H5speqP4F3vn6cn6SRkEE8T5NC/v/23j3Wtqs6D//GnGufc2yD7ZoI27fYwW2poIQCheIakJoIS7zEI6WNQG7jJAiaBiu4SOHRYBLSUNM04kehCJRIzUOB0EQibopaKtemoaiOwQbT8ggPxQIaco1ay762r+85e805fn+MMeYcc+61zz3XNvbd565xde5ee62113N8c33rm2OMSSqFNL/VDmakOo9AbQezafaA9glMyCIqoRR5yx5CnE/dr5sTnH189nH77Wnu4wf0881+SEWppFmioYhgFaT3vQjMtTOUIRJHojKkQWWcVRYxaQQWwsmARf4UcuIskNSHjjoswJYOsma1w0LnuVk9xaoy27zakRvKOt4GSqVR2IlLnBWXiMQ4fziOs+MetlX+eHx8EDu0xOODRDttIWOb5FiWHHCC5eSDssvEAYmDssvQNCC1z8Kc064FKvtyzJEcsP10I0f0t6gAzX2fAO86xlnkFPvPGm3fDVFkGy7rhiL2Q5mlrGNleYBa044BYZDMIARVQoS9FqYJ268yTqskrUAWqSTXddec0Ozjs4/3tvE+TmeA3EchyKtoMPHUgTY4UHtzTNO0e9Nv5RWei/5sr/TcaffIpJotFyc0TwpUNXkbrtqY3yKk8tmXYvEyx6jv3T2Yl3n1ptZtMc6KewJgZPyVxQM4O+xhh5ZF/tgJS5xLuwW4C7C+fWcsJximDV8wcijgTXm1VIwHq1wL91nWaVHagLuzteDtQdvfWv994nga/Z5QZZwifZh7CLiYHZid7FWIoW67fM/KTpnACM05M3EFbEAFMlCZJ4C1Y+zMPj77uJ/vj8FNb5KPE9a/1Xrb6IcUgmOV/fxTyI4mczCmVUfk1XWb5QAsjMaUFQ+zKofk8mkVmH34a5w4xIDgpJAgfQid1/oGwUsf9U/kjy1KiMhYUEYkkUBsn1EbgHRSIVxPdwJ0Pyhbe0gnYZmNFFIoofutgpncd1BtLJpsfGa3jkywZue3ddAUiG6dJkvfltlnQNPhDKA+jFbOd/bx2cenf7e5Pn6we7HZD6lBB84x60DLsWOfnTxCxhAcE2LtSPQVjkOS12JKclMtY5+INNERJTIJUK3dIX0gAU4gLtnwgAB4MdHJbHXFMpNEHqkMkSaYx0KlkIhcpI8FJZwfj+PsIJ3Hjw8ncA7tYUEZO5Sw7XwjAivDFCTdl8gh1qnc9hfwRON2KsZG7KhtFD2D9PJHlSK6+UT7+jo7hsueDSvLNEwSUXnzkJX9+ZHKG1r5O5IyRGo6mBGMYWaUkGsVV4rUYWzTqkcHXXbQVnH28dnH+/1sqo9PvDVP2SP+kEop4Zd/+Zfxe7/3ezh69CiOHDmCn/qpn8I73/nOoqszM37pl34Jv/mbv4l77rkHL3jBC/DhD38YT3nKU05tZ73UB5RwygawyjqZVu90yS1hSNQTodXsVUo1jb689ltHod7oKV82zd709EWo7C8QYycsRdN3DBQQRgkIkKuOP63XG7uMlHF2EABHZAFt2MWCRpxDezibRkRibBOw1V2H0DlPtkYDFvEUmgaqzxuZYuOnYitM0YHYT5fdB5qcP2WicJA7znqg9rMyx+6r3VCmor+bdm+RTwZKjlSDDia0+z5THwpcpgraZgC5/Wz28dnHJ2xzffwxkvv+9b/+1/jwhz+M3/md38HTn/503Hbbbfjpn/5pnHfeefj5n/95AMCv/dqv4QMf+AB+53d+B5dddhmuu+46vPjFL8ZXv/pV7OzsHHxnjjVyr8/3jFNfPdeBeMV49Y+UTYK5YaisEkpNSMTaDnBAgG2g9VFIZpESEgiBsoTNckCgBD+8dfktGIswqpyRsUUjAnKRQBaUVPZQ+QPVNfrejwSNvHI2FRLcXjy0QOuX6acffK1Z3l/6CUBa98AUsFc6mzvz+rzp6bINLr8jty7Z9tjNa7anEVO63tpda8UGIqvawDCJpJE+mMuQ7yez2cdnH5+yjfXxxyq673/+z/+JV73qVXj5y18OAHjyk5+M3//938fnPvc5AAAz4/3vfz/e+c534lWvehUA4Hd/93dx4YUX4oYbbsBrX/vaA++LQwAPFtyvJ9yzTEBeXQvjhAK63ZYBssog9TMkUilEN6N5JlKOhCDDEHAp71JCbZmQyZITa3huAV5hnLlo9z4LXmSQ4L6v3tSF6vCBGOeE3VKn7Jywq/JHwtlhxA7JAHkLIkQQUocci65K2kgseWgkmd6IWuw1Hb8OcHaJyM337K7fMk9sg8kxy25+33g0On2ZqR8WtWYnUOghCmhLp3J5dSDA8kbAct8DYHXLLA/FouJKBzNTZZhWEy2h5pPoiNKNRLLO+n6n2cdnH8fm+zg/Vm9Sz3/+8/Ebv/Eb+MY3voG/+Tf/Jr70pS/hs5/9LN73vvcBAO68804cPXoUV155ZfnNeeedh8svvxy33HLL5ENqd3cXu7u75fuxY8dkIoR6QTogG6u0eexkQSYAoQOxMkcYeJU5+sincqPcemyRlarbJxbNdioxscgiKn/0APbgjZQFQISi09v2fA6KscpIrKVg9rCAVHzeoVEkGDAWAKKCNyj6MhiJGZLHWY/V78/kl0aGKWFLWAGlny/3QSdJGRpxA9yVprkHqetjLaOzToDc9lVupz9UrtPt/qwV4hrOa9vTkWNlP7WDudTKcw0UGNpBjBUmyQSJQGUuDwEARTaxBmJfVjn1BoXZx2cfd4e6iT6+T86at0f8IfX2t78dx44dw1Of+lTEGJFSwnve8x5cddVVAICjR48CAC688MLmdxdeeGFZ1tv111+Pd7/73asLphhlYZuo80JowCzg7dbvzckfPipKmKi+1mdhE6zVolGkkBoPU4ttBmQLxQWtVL4x80MJFLkEAubp6Khcyr4saFTZI5doprgKkUlLoMIwpQN7n0azN4JeKKqgKvNRSJsH+xTDtN948FqncQPeUPfhAT5lRhQNvNQfm9sn+fnsjrVvoPp9OHlEOspd4mtASYo8ZfP1+2YfBzD7+JRttI8fwB7xh9Qf/MEf4KMf/Sg+9rGP4elPfzruuOMOXHvttThy5Aiuvvrqh7TNd7zjHXjLW95Svh87dgyXXHIJEIKU3fDg7Fmmzis3PIbCHBDN4WwhKmgzhGVkeYUNI5CTBqokYwsEjACS3C4ZjkA7hHMoOR+Wg2ERRABa3R0ypk3URMNIq6Dzobz2G5tvv7OimhEZOzRiodtakDBMs8yMBMaeMsw97The8oCMUCQYH2kVUMcPIoK+5kOqK5NEBskfg0BNORaOCgLLw3Cd8b1VmYMqUDsAlygoB/by286MZTJQCg6Qb0wM4f6YlDWW9XPdnwd9pZgdaMvOdbvN+Vm4rzvYnlCe5I1p9vHZx71tro8/Rm9Sv/ALv4C3v/3tRbZ7xjOegW9/+9u4/vrrcfXVV+Oiiy4CANx11124+OKLy+/uuusuPOtZz5rc5vb2Nra3t1fm9yAF0A553cgeOt9JIExUWEy7YQ9iKGrrjSwRUTptLFNkERl6wApVGmurUURUOonlcFznMiy/I5f5U+aZo5WAiWBsUcIWUkmgjB3LFMLDiKCmQzmjskrfsKyzOtCdAsouv2eI6oMlBNecP0A75lET/cqG0dwPD9YVlhnqOvZb+96E+7plAGowgE3beZQxmXQ/aNljZZyuk/hUrNHmuw72qTcd8j6L2cdnHz98Pn5AO9ij7BTs+PHjCF1CYowRWbOML7vsMlx00UW46aabyvJjx47h1ltvxRVXXPHQduqZpfvjSBW8BchoGGZ1uumLaCyFtDp0AbLL1hdnFCDnLENPJwXxmAPGHLHMESMbg6MCGmNz+wHH6o/5OmSRcv0DI3Sgn5JAbGlyOv2STQYJRQ6xzuXe/HAMVOKUIYzTgctHFVX2qX+OrXGg9s+YpfuDA7B9t+0wrW6//33DSD1r9Q2KTaNu12zddG82yJ30+xi95nrRLRTXlvcNwMkahNnHZx8/7D6+xh7xN6lXvOIVeM973oNLL70UT3/60/HFL34R73vf+/AzP/MzAAAiwrXXXotf/dVfxVOe8pQSgn7kyBG8+tWvPrWdKcMsDDJSCdP1kgcTSro7e60+oIBabrZjnKwdyxkS6RTkM+jvwkhgC61cSoPAS0YaIjhkLIeIvRQxMOFEGrAVR2Qm7MVB9HcEbNOIGKTDN1FAlJjORpc3/b097ToswgKpgNjYaQ/eDCCpg5igsgRwQuWZJQcsOWLJg0Q8OUZsZjKIFPlgUFTGpAOoMaTTlJmq7KHMO5j0EKSbxcKapwLaCuDQArCAD5B8Dg9CB75yvLZtxYrvXDZmmW290nlSO5L9cfRtWSnUqp/tcO4oeSIFzFYGJjngToaEdxIJMPs4Zh8/9D5+EnvEH1If/OAHcd111+Hnfu7n8P3vfx9HjhzBP/2n/xTvete7yjpvfetb8cADD+CNb3wj7rnnHrzwhS/Epz71qVPLkerNkzQFYskriZVp1k9Zr+aeyEdD9pyj9fIHaZQLsYTxMrFEP2VISK6yTCLJ8B9zAAKwzBFbISAwF6YZnAzRM0UPXiuMGTuQWv5Iz0S99f2aiSVKy44hOWaZm4vgL6vT7GEAYtHouV5XcuAiqtfU5914ScLbWgA7UK3q9SYxdPdOZ9ZgADR6vbaXVaZxx186lclta53pW0Y7TxmmnWTulgGrUtDJBjqcfXz28cPu4xP2iD+kHv/4x+P9738/3v/+969dh4jwK7/yK/iVX/mVh7ezKUnba/NOIins0zFLaGdoWUfZSz3QbtsOzDDt3nUwcyZwCgAyUgoYtYN5L0cs8gBgxMgijSAAS44Imcu0oELGuml6QYEVprlyKVhosIFwAQEoCJJtTwJasyUIS5VllhyRYXkjtTFpLyuXT1GapDO5ShWaZ2HXMypKPACmmF9/iRVYgGOW5S3Atg1pONawzCYMtwBJFhJqIwKStwd2ncbW+Kwje15nL1Fxth/9LsEIxkZZ2CXQFtycar2sb6jsQKnwxCCIs4/PPr7xPn5A+W+ja/eVC8QsHbsezCVyRrXgwQDsQFvYKFoGarKImbHMJHedAqTWGQMIJCWoMkCRwDGAE2GMjL2YMeZQKkWPIWAIAsQtlkz5FAIWHBHByBSkk5gzEkikEQ25tXySMPlkFhPGKp9LDlhQ1lDbyjwNoEvI0AUW8XSCF9grckiEDU4HoJS8icRAkAHuQpTjyFH7RQjgoTIqZhL2mYEAKiyv9G9gHwBPscwgjcQKy0RdHzpdAKqLWMHEGQipRSZDuxsU9NzkjphPcHu81vhkBW0S0FLK8tvEMjpphlR8TnrP3HAFAGCj57a+ZpRcy9KQXrvZxwHMPg6dPhQ+ntbfZ28b/ZACsMo+1dgBsrwyw7EW6sDrEx8LO9WvRvq4OkdJdis3E0AmQB2EtXMZyEg5IOUgINaw3QDGkiMWnJCpSiLBOpgJiCpgCJgPxjqyk1OajuGCLdL1aufxHscyrs5UgU8zqyJdmKYCqmadOyZoTE2vccv8uu/OeinEOn05cO0ADg647t4CgIVaGdiYlUmyMcx6rKUx6Zilb0TWmuskrtOo8xzL9Bo9TbBM/wIxWXli9vH2csw+fjh8/Ex4k0LOwh6Y6ytuZsAXRPRWImsUZNFNl9dual7Bewch7WyuzBMlwzqMQFoAAIHHgDFEhEjYixlDjMhMWIQFhiDsbztKpehtCOPMFJBJdP0FkgBZAWFDXScEmaZRjyhgj1Uq4QGgEUlllahOkCEs0ScwJhD2EKUzWT/3OJbw4dSBuWj1gHQuB2k5Q2QkfdXnzCUclwdIZzMBAVxYJrJcu7VSSANgnuxUhjFOW7/cHNuIu/lc91m+6z3kIN9NszdWWzrEaQ2OPUsuEXCsUgfEL41RpqzfHZi9Xt8l7Fp+CQd9GAQChTD7+OzjenNsI5vv42vHTutssx9So6CHAKnUC3X4lMEhygOMnDav7FIS72pyXgNaOOZZfuucxwEXymDCSOAs+woxgCODQ0AiqXW2FwRAe6EOADfo9FlxiVGHG9nRIQgAYElRprOWj3Gu1E5nbBGUIebCSBNCSYaMEIeu4BVGeYIXSCCcyFsyrfNMCvFm5W6GkDHEjDFnEAEpZPCAOpyDUsAMuTZgACOJowNAtjBWTNPMHqiFqXK9D2U+l0a2MYcRylQaFiRFJGujpg0xZ2nMUYBL7bap3XaJTC7AFU2ekoCYxiy+ySKPIGkLn5wU0gPU0jZCkAdT1rRJHa579vHZxxs7BD6OfLAyFZv9kGqe2GglEWb4K9+yRnI3x4CN6iDdOh68tslyA41pQLOxNSJKoqBkGzlLGCw0pyRlOdCRA0YOCCzzl6idzQuIkyUKZb9WMDMgl07f0IA7aOivUiadnYASEmxRTXscm4innlVO5bQE4lL2xtgmBRagQjt5A2vDChdtpBn62uD56KfmdnaAqdFOlW16MNf7026oDveNEpXFqMdG3X7859oO5YkQqJVkR//dM0rPMFNyq+i1JJL5lv+kvixDJrjtzj6O2cft3hwCH+8j/9bYRj+kKCUQJTARKIY67LV2NguwGBSovKLLD805Krv0Hck+JLRhNu41XVZEYZ0MqCwir7N5EDmEMyPFiGVgpJAxRLnki5iKJLIMEZFEv99mN1icRjJFMBY0Sp4JZSSmkrWfQIjMykQrmCMYgVdfp6UkjKsCDcKJLMwyITQdyj6HJFAuTDNqxzKyjKTKISMTgYYsLFPxU8BMpDq5XB8AJwnP5Tpt+r/q9QWwjQTSbqhsl1FDp41lGruNQGYNrfYSSNN/w+vlEKe7lzyRpNMpC7tkFrY5yj3lnBsA24HWSL1QpBBjnaRvUrOPzz7ebOMw+PgZ8Salcp9lzxEgzhICKGQdXdK8Cco6HDADJGqpA3MDXnMUzz51WwS0sshI4tAk0VGSXU5IgQEMCCHjQZJ7P7pO5q2Qin6/GyQhcghSNVqKbmYsVBqRXJE67MFCB3oDYyXRcSqk11hl5iD6PAL2NPIpc8BuXmCZRb/vc0mIGAOkrM0QM0j7AABtTJmQtTXjZRCmzZoMWmQHaUmLHFI2rpeVUAHpdHkYsAtDdNO9sTYc0P2ZD1BdHJgkUo4kao41SIBGlE7w9p63DNLLOSKBwGn0Sf4yA+MIHhPAGgHFuYC/YZmAhI3nqGwzyPZiBCLPPj77eGuHwMc59+MlT9tmP6T0NZNyNwqkMRrPLE+2qR60jpHW5VTB3Vmj4er9ln4FRp8AmXPAElKgM1HAHoAdiFwy5ohliEXa8dp5oFw6jIOBFEGcAgCoauW2ro+YMuDKdBDGyaGA1ev5vVmIrkU+BdKGyjqbCSqNQCQglUeqLKL3BNLYihziLmQJG3LX3JilLbfpIoUYANx9ZN2IFgeFSVrdtr2U0t7IiXXXWCn/otMAij828oeNdaHgZWOldszlrcmfZ9anzezjs48fUh+fes2csI1+SPGYAIzS0cw6hksIlV3moExQL6qODrkqi/gOZtRpoMb3k59nv/MHA2EayjjDSMj6Ks8hiCKQGKM6XYwZx4OwTOtg3gpR5BEQBsrYDiNyFMAsKEliJOo4PYEydrHAQqOggsojwCrDlHipWj+tyB4K4BN5gayySE1+pJJzYtvPJoXo/CFIDknQ60QpIJuMYH0WSS8W17ZGrtmEk5b7oiB1LJPKdK2vBhKMssO/7Ef2yRnSYaF4Ljq+RWFFSBBApvpc0M5wa9Qt+XF9JBSv/mWJeOJU2SX7DuacV1gm65g8pG8nrNsmC6aYfXz2cRwiH+dxak8rttEPKYwjGElBrBFQIYA4ACGAkujHZB17hIo6veFNB7Np9xa265lnx1CaEF6bnaGSAIMiJIJWM9QZEhE1hghmwqgJj2MMGDRpcBEHLFQWGULGbohYckAkxlYYseQoMkhITgpJCDQ0ZWPMpqpMezZZ2CUH7OoopVLfTMJ0bRgGbz7pkUJG1iJsKQdg0KhphoQaq9fnopMroO36TxGpwv50uAQFMoX6nSCM1rPMpj83B21sGTlpdQa97wxl/xlCx7mCVvynAhhr7n13QStoNRS3gDdn0d1TErCmBF6OdpAi08hF1W2H2rkcozZGLFF8s4/PPn7IfJx5b+LirNpmP6Ts9dKmm/m1Yi9nJ1MwT9KFNvppDXipW3fCCoNVh6XM9dCU2bBGQeVMSCS1z0atgRbAUlIGEsc0UkbW+RHSeWsyickhC9gsQtZ5RTbprEohVMC7LImO5P6m5RD7tJwUyy2J2kEeQpYET5LBoX2YLlsbauBYoykVacPYpDK9Up065LJOM6SCbU87vNn2bZJUua8yLSOo0jRQ0bJM2cnq4a4154/sWKfMUPByBigUIFPIKCUlykOHUTIhZx+fffww+fgBbbMfUikJgAv7DHKRmKSIV84gBKlmzJDOv4EqiIGSZ2LmNXt2zLMHMvc31d98BS4liPwyum0uAxIDFBlLGpAHydZnJgwxYi8mjBwwUMZCpwMxHqQFzooDZBjujCHIUNxDyNqZzDpej0otTdFOmefzQhIHlTpcbTP9HDmWwev6StG2PSLJJyltE0vDlEg61kOQfonAEp4MXW4g4ymWWUCJFTYpAW8G1tpHYN/9dmW8I5mXEZCHDGJpTAqdzCJ/UGZwJHDSEGK9T22nsns5sRDaSYo8YbkDch+N5r5zDiAkMAVt6LT0DDD7+Ozjh87HmQ+2/Y1+SHFKQFQdNJDUlUpZIm1yBlIAQxiH5JwQyit4/wdUFum0e4uMavR6788943RMihhVwyeqjQEHcGKMEMdPY5BIzpwxJgFMJMYip6LnD5QFzGAMIWE7qBQSEoZGFqlMEKijm5r5DmNjlGX8HwX1MhuY67hAZsYqLbQ4MwEhS2TTAIRsQA7gmGED5Bl4c67bmpTrHShLR3U/7c7PWKYBOLP05eQs1zQRSx8Ca5+O1iJjLZAJIvCIIp2U+8RQOYwbILs2ujb8k0knzrp6ZoVh9heAdbi+kGVk3KDpFYFmH599/ND5+MrDbI1t9EMKgOql+gppuilo5eL4aCiLMKHJV/GJ7x3T8Ov51+f+VboY6/GUT5sH6XgN4nBE0v+ZcgBCRsgBKUgxT8Qa0isZ+np+KouYFZbJwjzzmldrA65N58I6qQFtA17wapa+k0Qk50LkGJsvDLGyMks6LxFK/eXu2KNnlm2V6hbAxjQjcRk+ArCkRrnXRDLkAjQBderNoXcJD1ppRbq8kkAqy+0D4hCaSKdTttnHZx/HIffxfWyzH1JWXqMzylwio5CNXaDSPza2aTXKNGO7ez1fkUW6G+7XkR3bd92IfhjbBMNFbQG8FK2WgxxvSoQQQgHEEBOWWTqVh5SxjLEwvK0knZPGQEVDF5kEQPkOOLB3ZlFNXu6oIK76vaxTQR1IQkwDcdN4ECqgkkkRjJLBbwywyhbTALZPzyZDyLXv1YGZ3LmxHm8MjKTMVpZHcJCaBKydBpxYfYdLkisBKAmtXN807P6zv//BwCyJtUWKk4OVwIecwVGDHLTnm+2YmWqnsj//QJA6RFS3Nfv47ON2vw6Tj0+kAUzZZj+kzMidLOsTXyNS6usvlzwPKsAGVuSQsk20zIOg9dCwCuDyG17V8aHbzupMVkY/A6zv3BxkmGuOhBzMYYUt5RwQQkbUUF7Lhl+GCuZBgTqEVIZJsMx5APsC2YNYPiuQ+4x8M186JoClE9eW6W9CTEXDt3MyQHvg9iD2AA5UvxuzDApsm+fNjjUxgSjUhiJK45wzKUBUo8+q0XcNNCse0U37vyKFFP9wQLY/BTJSlmtkEXuUa+PSSx76gCrb8vPrRZt9HLOPb7qPr43M6WyjH1JywYKb7oB9qtubAvIaq0Dl7rvf4Lofu2VZV2QqlYq9pp0CATYcgjHUHDCSREM1UkhGYajBlkNAJdLE+vPxwPXfbbqPhCoSiHZQZHXI4H4TrMXUOm4WnQV3LDTRqKxjkwZeD9wpEJssk/V3XhZZCeU1qWa/hhkKVu8c/rsNhGf5TUFKGCFlEJEM887agW3h5SlpH0G0A68PJ0DfoMLs47OPH1ofP6gXb/RDCosFsFhoDkkAYpCLZa+lRE1UEwBln1SYJblPnpg2Y3KvxgT4ApAt02w/V9wzQ5gNGJTIJdXJzc8azpuVYWUtFhljxpiiADNkLFQWico0ASA6xmmD0AFowewjoibA07PKwj4nXCooSAIb81QpAjUSChB2a9vlst12e7YudeD0jLIHsz+Hyf26bScmxCg5LJkIFBk8sgIOji2iva/dp9x7ksgplVAASILtEICkkkpm8Uljn5bvlGu0HrkWlS3BUU5KPqOWSIpx9vHZxw+djxMTcGLlkq/YRj+kaBgEvAZmvWDNHzCp6QNYlUK8P08xMg/e0N3wqZ/1zJOVmTBKUUgJCVWJJGsjgSDLlIUYkHNUJhcCcpa6YjEwxqDTOWBpbCxzwza9pLAfS9vP2mKctTPZmgQDMoACZgAgBZePTvKg1pVWjskfm4G2LEO3DNKfYMdVWHPIhalnHZ5U0krkHkJzkUR3b6Uvud9UGxWCPBQs6TIQELUPIor/kd5EHiTIgYDS8UxRo/GYgRCrDMK1oSo+28t+s4/PPn7YfPyMGE8q6gNqED7BMZSOZjaGGZTBle/VaaYk0X392UkYzU1uNtBvcFU2mdxmATdZ/lsJ5GKI3JuNsSAjmbc5LYS1crNVkGYSXd2zTGantTsQnQqQe7Pt+FyOqW1mCIhPtq8euDavBy/1AGfbDzXn5tctUkj/ZqBySU0eaW3FVwrYDfhacBUBiAzKQZiojNFX7z1pDlMurfVKvkhhm/6hNPu4bGr2cd3P5vv4GTHoIe9sg4dtlJjPqK+jADhGYNAaZ1p7a+V1d+2GO4kE9bOYB6+FnBZH6GzdvuyeWrZ4IOho2kJAVBoBacczy2s2BUJKGs4bcglhtQ5nuRSuE9Y+cXJJwTNSP/9kVtazbXsgWx+Ak6VMuvDfp/a3DrSTMo5+Dlq1wJhsDCIvhZCFoet2pPo0VX/o3woK06yfJn8wQR4O9kBgAi+iSiCoLUUGMEwMCMdcpJCVMXvkRF1NPZp9fPZx2YZ+Hgofz/s5aLWNfkhhMQDD4BgkgBBkegjIQ5ALbzXKgmObnZGBVYHrpRHiaUYqCzvgeha6Zv1ixiwhDs9We00T8GCNRmGhWRuTKFE7xMhBst9JGWVlexWI+4E5wbR2x+ZQQZOY9gXNOs3fzzdgRVQWKhLKekZq+y+XbaJRWde4WBVr38GerPEjq4+GlYa1yCDrrAM2yIgigSKBSxo/CoApcUmQRYyay1QZPwCs7e33D6nZx2cfd3YYfJzTmfAmtYiiiyogTTOt01oCJFJhBuwvvL8RJ2GCNr3CNr312zkZiNcxOAdsaUioTdCzPAgmkUhg7ZiAnEj6AKqD5/q6TqzRPlxUmMxUOqYbtyEBkYWSHlQ26WUI3/Hrs+c9QKc6rU9mvqHwuS5TNhVhVRfus5MJkAPiP6RvAtJhTACxVIegAIyatGStfwYouNwm/wl0Fx7lzUUPfvZxzD5+2Hycwxkw6GE6ewu02JIvBuJQwVymBwfggZCHyjobUPfMo2OcxkILG4Wub07ZsZd9GUtvDFhEVNmw3wejauHBXuMhHZxcWVdS/diYJ5HkogSTSKjOtxwNY2G9XJKp1chrfbQWlAdhn+uYZ1l/P3ztA74+jPigVl403L3rf137WYyBWka/LMwDFJhax860eIaE5wKw3KW60e5c9m8Ly/79Qc8+Pvv4Qex09/E0HsT5N/whxVtOny+dzTqt7BJQoFpxaR9i2wHOm2eTK8zSs8Dyg/ZzrXa/sqN+vxoJZRTQGpBSmgRSNNIOxf4jSdUgFmaT2Ai3jqTKQaN1pAZZKGxTrlfpjNZ6ZQBKhWd/rAXEa4C7zno2uK7TF6gN1b7M8DEy85sipwSUvhUZhI7qvdMf9Gcxqc8faN+zj88+/oO3R8vHbSDEk9lGP6TSIoD0IWX6fWUG5GQPB+BIWlCTSpFN9uuuYYiFWbL7Dv1ugD4VVgmsX79zAPSARiUrskj5qUolDAWfJk62b96hyCDWqZvharzlsAJiD6QMkkFDnR5+qmCePOUJhriupMw6NlnCf0Ell8RCdfttFQwp4E56+L6hV6nJfIy00xqDhN4S4yS1M0/VUdRmH599/BD5eKIz4CE1nhOBxXRxyTLQG1AiVgAFszHNABnQTKcbDV+tkT3sRmeUEFpjgQytn8ZYvT9T9+tk97CRQRS5Fg0T6jQzqQ6sLIfkALLpx4B0QJeyLVUKYZNLADBn1fIrwys+bczXSsMQXChsyxj3A/I62aIH177a/T5yh9fsk1YASAXIckmtWrUPGjCjNUBmBayxS1Z2CQA86D0o0bZ6/azj2AcwOD9EXfUh2+zjs48Dm+vj4/Jg40pt9EMqm/buL7q7KCuMEw6oQI2IcqBd6x/cfXbzBAQTv6Puc52dFNCOyXopxrFIY5yyvkuiZNKeZxuczsCP8sPK0IRxmgxih/VI5ZuczB5K5zLQgtcnVMqngKwZ58eM3d8BTB4MwjAlbFr9r9PLyn0g97vmO05+z5sdu+nZx3X92cc32ccP2r+22Q+pBSEtDnCiBAfgCtq2BAwa9mlsszYCqGG63Eshug4rmhia9OZBV7fziJoBsjk4KPMFyJbp8XE5aNLwUANulT1kIDX5zspCs4K6SBGe8Oqh9Br8lE2xSw/ah9pJzN3vbDgGG2zPxvnxg9Mhd2xzopEup0r1rzLFeqHlLaP9na0y9SBp5tumVk7qwKc/+/js4xvn4z6nbD/b6IfUuEPgLTo4mDtA+ptRalT5+X5dMwMvi0beULHstlukEqo10PT3BwbxFOjLuRprceBU5R5ligu+awtmB2DMUsFs4LNxfkBKTNvM9smOZieL7Hs6HmTWcHSMsAeit5MBmt16BtyUCaNO5xzAOuQ2MskBszgFFTDTpBwCVGboBwYsxTIdySzrrXxSBX/vi91+Vo5h9vHZx3G4fDzFM+AhxVH+VgB8AEli6uIWxtktm7IqOxiA4IDCHegm5j0Um2q9DtIgsNVQe2hmdcj66ZXdMGEqWmkKuLYt/9lLGP00sH9b7bfjh0yof/r7wrbF7JAJ7eVtToXcHzr2iZYxrviWBTyENb41AeCT+vTs4yu/m318s3ycD9YltdkPqbQgYEGr4Y773eVywam5gM2FdRd65ZW1N4Z0KBq2lKkAtVO2yCKMlo6saxx0AVPXOKBu+5TQ+BDAmxnwRMdfUpNK3AEX63NBev19Sldfmd/Ns31OH+fqOpmB7DqVU1KWmYKMEptJip0ygbToqTDOeqI9eBt/KEO086pvdA8DY6UrDNW9xfQdz/WE3OzZx/e32cc3zsfPjD6pLYC20T3i6+R+fZ8rr6EOqO3FxTSIDUMMlORHmMigIPSALQ5Adbu2HEAD0nJIPvGxWz61PtXtEa2CvJRLOQXzzLHJsNftrcgVE03FNMhqFWcG1jJND8r+uKa+WwPgNXoBsICaUwWwgZeyXDbyIJ5imEGPFShyGGza1gG6wIXqT30Qw35Mc8VmH5fFs48fGh/fb+wvbxv9kCoXZw1oT5pP5nE/dTE78E4++JkUwe1mqyxOLUh1hdoHTPXA2xZAGwmqbPMh2BRgHwqQp+wgpWR68K7IH2jBug643G1n3X48eLlIIYDJH6ydyvJnP3DTvVE3n9DeI3T+0QHU9wNNjemz8iBZZ7OPrz/F2cc30se7MSbX2kY/pPIA0LAPaA/i97Q63TCGDsxrzZimlbMCpNpzATGUytTtkt+/Z59o1yU2B3AtQHlnxyrj1GM11kkw1skFvDJmj2wjBOGGtTin29RJGo91LPQgMkfDDB1gaxhty0Sntu2/swO75Ypw1s5kBjhRkUCQIUzTsUy7h2W7VG9fARTXZY314NUEWpRkWpRpAKtvMiex2ccnzmP28Y328Xyw0n2b/ZCywAkGDgZWrN6g/VeeBrD/XdHogTI0tv2OFFwVrFSBZoDu9lVAXeq06ToBZRC5ugHb+Bq5xMAb8gpoqYBZ1rHhD2weMF2Jeaqe2Uqi4gSTtO89aI1Fmr7uQT6V97GObXIDfJQIJ84kwGX9HGU/lAiUHHizXF+YLOKAKiAmLQlTL72/3gJy/TIB2hUA0+rve2t81V/Ik9js47OPA6e/j58ZD6kOYCuEaALUB2GtkwzzlA7M3WNy0x3OajIcl980qxnFcTJJqXs2sc+DmmeaQAWlZ5h+yAM7lJPZfhFL/TIP3imt3eb3wJ1KVlyZZ40AE0zqYAZKNQPPKHUdD9pJs5tIFcO2i7LcNd4+H2mllh7q9/LbCWPfUOh6s48fzGYfx+nv4wf0uc1+SOmbVC+Hn4ozT1p38SYvtAe5gsxw1qzSsRH/Wdsg6tgnUKQQQmGnrP0CBM1LAYl2YMdiTkgdoaUKWl85Ojrg9uPxACgVo23aW19M02wds7T5yZW6sfnsvrdssQVwU4sMdX7Zn01nYZcyTVX+SAQaFbDWqczQzuQKZNtUeWMArBe9nFhTGmg/0Dpmad/9b2x6xTofnn1cj2X2cZk+BD5+RvRJgVCiUQA8fODut5/OVtiqA7Edi19npROX6gcTsAJwA3VABTNXIJfO5kAoCZY9lQUKWD1wTf7wwxl4KWQKuAcpEzOlx/davJc8imSS3Tpu2jqDZZrcffZgRlleJSmqjDLptIK2aPQj1UinjDrtzOSL0jB3+ywgNKBPyR8e2HY/0fnPPvrcI/5wWmezj88+7i/to+DjZ8RDyl4tGwm7WeEkG5gA5kH3exDzjGW/YyGgAp4BKw5cw351gd8GK9t8CK0Woe1ANlY5Bd6D1jCbkjra5XBAbiUPrEzbBE2zSAYa4NoKBmwngZjsUeQPBapvaG36ZFJI72YNeB2YveTh57XMcs3OOjDb+rOPn5rNPr4BPn7A677RDykTWYscsbL8AL9/JG0Nsg+0Gwccu9k2BIGcHtVxBxiSrU1WGAaFibIOCCfVn7tdUAWlyR9Tw217/X7f0+3Ol9FFOTn5wxhnE4pr0UkKbgNfdt5vYPUssgWym2/MMtd1kFElD+1IBpPORwt0t3kC6lu6azDgJ9exTM8sGynEJUbu55ulpeDuITD7+Ozjh8jHD0iENvwh1T61TwaUtezwIBdrYtv77a9Ztm566iAUuIAer9VEC07tsKky5gtEEjFnr7y0yv1eg58Ab6T2u1kz0mjHJIlY6pz1QObVki2tLj8BYJVIGo0+V2BxdhfFA6phkpVxUpoAcDdtJQWIV+9laUQD4Fmtv1U9e2yKtpYBCLkBedn2hE35E3crzD6O2cf1Gm+8j58pDylvTGuA/nCAO7WuY7enRFQP8Ja7cg+d87CBuwDV/YDdH3Ubsu117LFnl972Gy77oOVMzHrwoky3Hl322JxT5/U9WK12jQMy+WnT6h2b9Efv31SI19zT/nR9W+I6ib0sUpZT+/v9Ll3Zt79/3b2cfRyzjx8WHz8jHlLAJIjXrneSeftd3HWgY7/cPKBf6FmMA+TUNskfBwFURsYEsukiUVYiqv7b1GKDAIQU5FNVCXrw2vdAXIbP7qWQAjh3immCYeaOYVbw1r9s9cWgAPeRSgq2JqTWMc4yD9CcD8809dqYLm+5IWVdN3/qnvprqFLIJANFXcdLIZVx8gqgDyTx+ePY50E1abOPt/uZffz09vED2uY/pIC1rKpZPjG9Atj9GMB+q61jJ7qMHGhXvts21+3AHIqBwAQQkEsLAH2l187lxonRhpDa5kg6kj14Y8gYNPIpYFUOMStj6uh2TQ4BS9LjMq+G6+QGuBLZBKBq9EBhf8wk5+IY4aQGzy0oG9ACrj6ZDkmQK2Onwkrts14gvbxllv1myk+8vFHkEI1SY0Ib4bQfgLsHUeNH+zyoVmz28bq52cfLNgDgtPbxA9gBgwA3wNaxyP2e7Cf7/Zrlp6gEtJvpwFu0Yve3Usakq2DcFomk6tDNvIMdZKPNd+AtrNN9n/rtqYTwAo6tlu/dvBXWiFXwKjAboLprQ9nNg9sO3CdQ0TLRaHqQrkgdk+twA9iT3gJeM71u3uzjs48fNh8/gB2ONymz/S7YOgCeAtP05smBn0eTtMSt4MHrOjWnnQu1g1lZIysNChBnCaREjABKJEwncwntBa+GytbcEd+prCyTuDBObzYoXCDGmEMZriAQr8gh5XQ9gzNWyZVFtqG1Os8P1NZHMOU10wW8VK7fWunJXV9jdMYuQWg6kEmveXvx3O1tQMyrwLZ1yg4nL9NKg76vzT4++/hh9/HOTvlN6jOf+Qxe8YpX4MiRIyAi3HDDDe2xMONd73oXLr74Ypx11lm48sor8c1vfrNZ5+6778ZVV12Fc889F+effz5e//rX4/777z/VQ3n4NsEsTrr+1I05iHU3xtgldezR5pW/hJKI5+dRolqHy5L5Gud3YEEFk9fgp9ik6fWTf24dv52mtMyEB/blXtp5Ol2ADccyK5u0c63n666DH5LAs3KXL7JyWJ4JKvh6VsmEEl5b/mx5Cb/lFfAe2LrGojnGh8g6V2z28fI5+/hp5uMHtFN+SD3wwAN45jOfiQ996EOTy3/t134NH/jAB/CRj3wEt956K8455xy8+MUvxokTJ8o6V111Fb7yla/gxhtvxCc/+Ul85jOfwRvf+MZTP/qD2jqGucZ44m9ye/6mN8tP/U5QtzP/vZ/2r/3UOWnpYD2g+U7kVvbIzR+AlfV6XZ/cNoFVMO+Xk9Jk13eNNTlAt5FM3bUBVs59ErhrWOKKLDLlKyfzpX5/U87U3cuVh9NDeUDNPr7WZh8/TX38gPfwlOW+l770pXjpS186uYyZ8f73vx/vfOc78apXvQoA8Lu/+7u48MILccMNN+C1r30tvva1r+FTn/oUPv/5z+O5z30uAOCDH/wgXvayl+HXf/3XceTIkYMfTH+iK0Byq/aMcmqdk+yq+QnpTCofZb3m9Rp1vX1fhf2N9CDu1rGNkg6RQIFApksYsyLs6wg9AEnlD2GSeVJ/z6xSCIARddxnZtlG1vVZDyEQkFglFJIDXxlctj9Go3oK1sIuuTJLOXfXgdw3dPvYlA/Yb9iuWag3j/ob6353MvCetA1/KA8it/+p77OPV5t9HKe/jx8QA49o4MSdd96Jo0eP4sorryzzzjvvPFx++eW45ZZbAAC33HILzj///PKAAoArr7wSIQTceuutk9vd3d3FsWPHmr+T2sMFb/da7I39OhP7eDidzvsykk4SWWGd5ZMqGIAGOFYBmlAZ5lRn8VqZhFpZxIf19naybP72vB07Ntmm61z216Ccb9cBP/V64C7Fyj1t3hI6xrniN/uAdy1T7O+jO96T/Z3UZh+ffXyDffwH9ia1nx09ehQAcOGFFzbzL7zwwrLs6NGjeOITn9gexDDgggsuKOv0dv311+Pd73736gKujG6dTXburQPufsDr2cbJ1nFU0zovixOcgl83B9odH3HH1Nit69cjrOjrQJc74hhmHw3VnBtEJgFLeYBADKtc7TueLWzXj91Tj0PCcl3B5fY8++8NkJV1Tq3bnLT+vG+AJ+5xc2kPcG88WNlt8CDt1dQ66/zXlRudfXz28VXbdB8/INPZiOi+d7zjHXjLW95Svh87dgyXXHJJoQ8Eq9+HaTbQ3cS1oD3ZNXN32pgb0eRi2Qe5ddwxlQcruV2S+707wPKqbtOs2GFdrWGY5ui84oh1KAMpDzOEjOgAO4RUp0sUVI2AyhyQ7WhDlUYyERAyiAlZKWxmQg4ZQECy/A1ikNZcA+Q4+oislWvtpRA/3ZzzxG87VjnZiLer1+tLbro/nonvU5s8FXK9shF/rOwKzM4+Pvt4c7Kb7+Pu0u9rj+hD6qKLLgIA3HXXXbj44ovL/LvuugvPetazyjrf//73m9+N44i77767/L637e1tbG9vr8w/VUkEeBjg9esY0hQnpYyLX88zTTim6Zefqrn92rS9Ok9l3E8dft/h20sbxjbNYjloASQgzNPYpG3Pvmd3zoEYTFTYZ3sw+xxwD8yeafY/99cV3TR10/431H4292i/Y1t3Guum9zP/BtL/jBoX2ncbaw9x9vHZx09nHz+APaJ9Updddhkuuugi3HTTTWXesWPHcOutt+KKK64AAFxxxRW45557cPvtt5d1br75ZuSccfnll5/aDh27mrzwnmnAMb/uz8IuD/LXbxfddst65ZObZc1nmJhHKKGf/fbQTZfL0H2v51bButKBrJ8DZQwhyadOLyiXPwvNXVDGIiSEsp5ug1LZljUEMWREY7QhV7lFp4XxQplnd+wrwO3ud79Od0+nRgn1obXN9fT30m/ONxLGaCdDpN3f2H1364ZU/ya304dh6/76N4jZx6fu+ezjG+vjB3xanfKb1P33349vfetb5fudd96JO+64AxdccAEuvfRSXHvttfjVX/1VPOUpT8Fll12G6667DkeOHMGrX/1qAMDTnvY0vOQlL8Eb3vAGfOQjH8FyucQ111yD1772tacW2QfUTsUAWEF/k0Sa0SH1s3wnv4E6f1/TVWX7hIYdKMtrZJEgN4PN47jWGTNWSEmPUx2zaO8avdTcxN7xbD/9cXvvI7k2IVQARQWVB+wQMrbj6NhmduxSLDEhc8BAwMiMwBmZg6yfK4ukzCWhMTAhMWGIJKOV5oAcRN9nDnLOnmK5a107xmujvRa8QNvIAa7OGzf3vEhLjCYxsizzD4Sus9pLL40cg7pOfxt6m3oIeFnMN+RFmqHZxxubffxQ+Dil6d/3dsoPqdtuuw0/9mM/Vr5bX9HVV1+N3/7t38Zb3/pWPPDAA3jjG9+Ie+65By984QvxqU99Cjs7O+U3H/3oR3HNNdfgRS96EUIIeM1rXoMPfOADp3oop25T4J0Abn+zy3r2XV/3e3mjgJjb39h6TOuX2w1c+V13TCvn0Zzf+nMyayOWcpU/OvCGHikEREpICkzZR0ZQCcRvOwMrQxwEErBap7L1HzBLxzM7CWXllA7IuHxjzaFeCz8CqL+F5Vrtt/0p8K4LDT4AgFeAaz7jG2hr0E/2UFmz/dnHZx/3l+p09fGDnjMxH0TpPb3s2LFjOO+88/A3fuFfIe7sdINvcWUbNh/oiiHyKggO0iB4huG+F1bibzJQcx58KK2rP9aEmfrPvLovz044or7aL4C8YHAA8hYjbzE4MrCTEbYSQmBs7yyxNYwYYsY5W3vYjiO2YsLZwx4GlTi2wliAOwShOLHWn0ZCKGAcORbWuZsjxhyRQdhLEZkDRg5YpoiRA1IOWGb9TAFjishMSClgHAM4B+REyKOe0JJk+GsmYCSEUa9Jova6ewBOMEtfudmu36q0QW7a7adMO7Dm1fuzcs9dR/AUgLkHrx1bN/T2pFQ2+/js48Ch8vG0ewLf+P/+Be69916ce+65qxtT24jovnVWLjxQpIcV6UOny8UL3FzI5lW62fgq6/Gv0TJh87nU6mpetUNdzWQQJi59DA2jcH0QDfNxjuCloNpocQVzhIA3ABRY/7JIHzFjERO2QsJWFMBuhRELlUPOiktECOtcTLyHJ20BMxMWnLDkqFJIxkgZGVJrbeSAwcki1qFMWitNqkCHOqoqGc06iRmL1+leApHz9403o2+Ui/xRZrTXnzxouerrBcw8MZ25bOukjNj5IYf6CmH9CWT31Rqf/lxnH599/BD5+A9M7judrNdPT0kecTe+bmxqB2rsw4GxCjSdaTkFBlgAJVeC/G/McfW4yzpu00DnD56dmNO67/U4ZPuk+y7yB6AShXb+Uv008PY5JJEyEgcEJGGZVKOfgIwI0min6fIzlq0P3bctK/5JtZN5atiF3vzltobavzn012jyx51RAd9qpelG6vAdvlka7sIspwDcn09zTKzHWvsGynJN0dFV6jnPPu6OA7OPb7iPPyYh6I+2+VdVzbsTTyBoZyXai0gTVXztxgOrF7u54RWRlWVSWVRvNJdFxmisWjMDbUkXCIhL4+MYzwrL9AwlQl6ZA4MHFAmIB5aSJwGgyAgxI0ZhmENQlhkTtuIobDOM2A4jFpSwHcbCMKNGPPlrkUFIKnwvOWLBCQkBu1min0YdSzpwkHwTJgREjMTIIIxZ5sXAyMyi84dQxt6x+9OjrpDx2nYAqEPwNMzST7tGiJqW123Yg9GG3PbRSRrFZIxTgMVVFnFA6wlTfw4r99DemMDIURswa8X1jSnbMYf6m9nHZx8/ND5+RrxJ2QU29gmZpoDKRleAiHohw8QN34/llBtEFYDcAdqBudzJLsLGtiUJizrkQHa/D3WbpR3yThDEWe0VOg8CWo4M6F+MGcOQFMAJi5iwHUfsxCV24hLbKn8YeHfCUsJww4iINo8EkETHpBdnmYcC6IiMhIAxJ9H6OWDMAuYxZNXwqTQIiQkpB+TMGMnLIVzRShC+rjRZZnO9zo5JTgK43GfZJmviJ6HeH9ulhM9SASollD6CYCG3mVeBXdgo1+n+Hju3WDnuQPVhouk5THKOvUxSHkKzj88+foh8nM+Ih5Tdd7tvxuSc8xuovTWSydT0FIgdARLBY3olv6T4GzmJhNCE8tpmi5N2Wy4+YTcbKBq9gbl5/Vfdt0gMQM3xIC+BZETkhlUaeKf0+kgJAdKRjDBimQdAO6TNAZcs0ghCwpJDiYoqCZATZsdYrk2z0C5Oxbacf7ec0Orz65DkjVf/+o5j8qyy/7NGwf9m3W69X9lDBwwELZ2jDx/T6ymzPKi4bnv28dnHD5uPl76uk9hmP6RG+QuoN7W8WRFJx6WtzFAQOXR7dhn8hju2ArSexTqUtc1v2Kd1MKO2FARHG+33aCKcjFmS/707nEbC8cl8A4MXLA48ZNCQESJjGET6GGLGljLMrTDirLjEWXFZpneCMU35NFCb2UBxiUPpWF5yxJISMgedjkUmGXPtcLY8lDFHPb+EJUUgZKRACIGRszRw5dZYP0a5JpVml0vi3w6iu58BFUV27TPX6Q6owhxJfEhZZFiqX2UgLCu7DCMKoyzMU7dl2yb2TmKHUVueNiiASqMj95PqW5NF8IGKZDL7+Ozjh87Hx5VNTdpGP6RCYoRRtVu7j3aRlA2wPdmnjPyfA23gdh0ALYDddwdUNprLFcywxVydstQd68Gsi4wx+93ZWzyAGuFEEPCqTk+LjDBkhCAyyGJoJZAtlT/OCnvYDiPODnsFwGeHXWWbGVsK4L6umQfwHovr7OYFlhyrTEIRgyVBGqg5IKheP4QM5IBAKJn5woitL4Vguj0Hrlp7ucGOURpoyxCq3UXzjajeCAvLpSQSiGnuYVk/w1LuT9yrYC0AzuJ3lYmuNuR2nGUBVSC3oeQK5kgigwQ5ttJAgwu4Zx+ffXzlvm26jy9xINvoh1QJnfTBE4YNhoSC2gwDzL4bPMC07KmAr3yHfi+ExokaAcJ2gFYqUb0eLA1RIUh6rH63BmLf2NScmcq6goLCsu6t0ObUEASLMMIGfDPwVpmkY0y63HT7LRolIooygh5M1DBdqXEmssi60U5Xhjig7q/TP3wncdPgOjA31RBWCV+9R+YPTtrw84pPcQWtl0RgTJO55gn1++vILjWxxXpqPtrJ9zE5Ntysi9nHZx931+sQ+PhBbKMfUmEJhIGRQCUqJpMQlUwABWF7uTzBIa+ZfiOFWaJxiiatwd8dY5QMFCcr9I8bB2lyTUyqyW5+ptLYmIRC7ub1x9l0pEZ16oGBRRbQDhnDQjqStxcjtrUz2TqSz4pLnDPsYicssU3CMheUsEPCNkWrHyvLdImOGa5TmQfsmdzBGXs8lCTIE3mBEBhLjgh6ort5AAIw5FpPbcxSbgYBIokYGK0vQhvf2iHLztkdaCOvNAZc7klpTYVZug5hSjWJUpilLIt7xihlmpIyy5GrBOLYJaWpmzVx3yBs0vyKEpcAiTxU9klcGWhmKvr97OOzj3s7DD6O8WBPqc1+SFmflAI0KDXjoOBdVzdMrUY7KXIUxOQ6KIuWXH/ltkflu0TYuO33Iba2Tqisl/TY/O+YpwuJlkgtoCQzIgh4w5BBARgWIn/EIBr9zrAsWfem05v8sR2WOCfsYkEJCxpxTtgtAG70egWxZONLK7SHhIVq9IFzSXxMENZp8kjQoQ6s49mKfGaiUpCTgVI+Bip/ILjr6kq/rICWIMmc6PCTZKM1eowKczS9vUY1yXRYcpFCYplmAW4GaGSRQNYBGOZgekJmASKDAICBFgLm0sekgRLmqybxATI/8+zjs48fPh/PyzPgIdW8ngJg/0prINE/izYyVtdEP63bvjlJty775Qyw0gNiPQZAnLCMeUP1lz4ENaswQkAldFZAtLxD66f7M/DqsVGQYwkqecQgMohJH5GkwnOESB4C2iTSh+rzBt4ILqBt5ZBcTiNCI6AoIzIjIyOBEJGRFcSRsoCYVmuk9cmU5BpS0oaK/XXzUofKKWSNrf7eGtTmcvsbZv7gfITcvBrR1K5bZRAFL+t3k0EUtM2LiD/fXIc+Z5CAlagAn0nXUd+oeTIM0o4oIpp9fPbxQ+fjrjtwX9voh1RYAiEaO4FqoiSJgOQYZpCLWDrtVLIQ/FWAkGrfUmoFjYPIOkYFq4dwEwVFJVKHXd6ITOtvfCQO6f6ZgIiWlbrjKp9eqhnkWMNCOpBDYGwNCTtbS0RinDUscfawh62QcE7cw1lxD2fHPZwd9nB2EDnknLCHnbCHBVJhmYEytjQz35tJHQmEJSL2NPIpBsYJXmDBScCrjr3UsEvpSE6S7MgBMWTkTNIvoB3MOUhSpvxUhOseg839CNkxU5SQ55xJpS8XJZUJNrAcaa6IfYYlAGOTS4l+intcGGfcy6BRQBuWWUGsDNPCcyc6BqT9dY12eWOh0n4jEjg5xknyKZ3K4sMiixBo9vHZxw+jj58Jb1JhlFdVHwFFScFJQNAilaUjUK97mfYbcwAx1gasc5b24nKRQQg2EicHFuBCGgabLhnXAEo+gf8rG6VVhmnMMmaVA6AJjRLttBgStqNIIaLRS7b9dlji7LinGr2Ad4dMChlVs7cER8YCdRgDY5qJZEiCDJL1lFGa7SFihyRcJxNhEUbkTJqjIiOh1lI11skNWNXoYMySJTt95da4+xACN/cDEPD6xtTLS1RA7MCrUrHIHCqHJC4+JQBnBTCDDMAMUBIKWNq4HsSkrBHd20ygCu4sb0jFf4iAxMiLIP5sb07asM8+Pvv4YfPxcCb0SVmHn7w2cuk4BLhotGCUelSNnn6A61MHL+MVEJuZZl/qctnNzKHq6+512O/bQF2js6gu9+AFSoerzTOdOoR2DB0ysBDrAG51sDYDzoKSRizlIn148G659/AKUWVLLFJG1BICARmBMyJJtFPglqFO1Tqbvr7ytkCBEbwMoOuHwJMArtuSZZPDdWuDPSWFkJM3ivyhncdQyaPNuOd6WOvCq9x8n7bKpvHLRax5QUl9KgA06n0egpaN8XLf7OOzjx8eH7cH4clsox9ScVduJoAamlukEC4ddxxQ61ZFebCVMEhvzpmM1cSYJxyttcIsjW0CyJndNBUGypFhHdDSqJADL08RFjGr+EwQXT5mhMAYhoRt7UjeGUacNUiuiHUkb2muyNlxFzvaebxDS+xo5/IOLbGFjLOtVAyAhSoz3qSslxz0CWZEcImEQgAiZyxpQKaADGGumQIShSKF7OYoZWW0arX0KSgzH+RaGFuUc68RaCGIPGIhvgZWZgkHRoAmTdpNIdHBO/mDRrnuqx3JAtqwxyJ7sEY7jVk7onPtQM4OXFM48zlLyYO5Xad8D0GDBkTa40DgkUFbQeQ+7eOffXz28cPl42fAQyqMWeS+iALWkOQhzxG1VpULrjCwlKz33hyrFAZXHcaP5OmBbA6XrVMTqKwTAFGAjNQpwOUcdLmOtKqMRb53h1MkmdqABJU/iFgz7kVu2AoSijuEjG1XXFOAOmrG/Vg0egPvgjIWYETBAbaIig9GEBIYEUDSE0p6UQMTlgjYQgIIWNCIRJIQadp/1M5s69y2nJOBhBknADFIJekMaWAbAEPZacgIVK+JDY+QVKPn7FFj97nebzlkKpFP5S+LBFLfyt104tKhTIkrcEveSOtAptE30VDVSdrvPZMmvfiZgRhEviFopFSYfXz28cPn42fCQ4qysoBBhPsQ7BpTAW2Rvf3rL69/i5UNV9CWP7QsMzik5fJ67BhSyKUjFsgVvAwwSQcqsogEJCLu5EGRc1pjviZ/EMT5LZnRop1skLeokU0lmdFFOdlnjY5qwRu1KQmlf4HLwURIlWcQEJmxRDt4nPxOoqKaebY/5gJCAOCQkdldvyI51esdw8RwCBDQZPBKw4eJe97IILn7VJmjhPCWm7VyS+ou+pA4N7+A218Di5bqLah2r+dOnJGHILLIgNnHZx8/lD4ezgS5L+yKkyIQclSHi6TVkwk5Srl8jgBZZFG5ieRuEAHkJQ8UdinhrsbotDPROZ+37ABs05mBrOVShExSKd1vcomXUAA9NgAlJBUOtAQd4C0hBsZWTDhrsUSktiPZ1y0zCUQ6j0X+WNCIHUqFYS4ALIgQQViU8XQsVhQagluBCwgQF5SRkACOWCAh0VhCdYPrSLZhvAcV4wcOWMSkmfutxGTDbdv4QAAw6D3wevxozNKSJoHSSMr9VTnENHifO5JqQqN0IrOrBu11etZotf1a/JNYsgbeM1W3zXKTCRilBlwYI3gRwCmAYph9fPbxQ+fjlA5WvG+zH1KjFJukUV1No1eyY5kgho15Y2yjdjKKRj5lRQ4xGcQBuryedyDOph3rVlMOIiGQ3S8p4V9f93PplG5BzO449FxDLo1KDBmLWKWQSDKWzlaUIQmGkEqeiCUyBuTyGTSPJEB090gVvIEIAQFxJXFGwmZBQGDR9W06gpFU9gCjsNfIPsqJO0BzSXr018/OFajXvr/W2YE4KdjbY61/1DTabr6xyb6gZjLQ6rrWoexNLwU69aUeoB2HgLQwzpwrcJlXG4WsUphGakH7oDIw+/js492xYuN9/IwInIBqqSFpqGhU4JK90lK5EbUj2Wnka6xGOGlUUbCw0upMU0wzwuVa5AAKWaUORsrSi03EyFlan6QdqvI3HbXjO7SNoVkiI0HY1xByF/7qBnZTAMnIpFz082j6OaofBgWxgTd4Dy0XMKv0oedsUopeUElwrD8LZX+5Xj/oIHIhyD0K9frV39V1y70g1nF7JEw467zk7lmxDsReDlltyLGivctOdVMErPSk9L3u3gKXigArjmagTnl1meW+kOZGjQQeAMo0+/js44fOx5EONqDURj+kwokRASOYSJJ6CeBBXoE5AjQCiNLRbG+glNGwVGaUG2V5JEUTp5rZHpXRlVBXx4S8GYAzkyvtHxTAdUA0QEBu7JM7hmqHY9tvGhJllBaCuxOXCMQ4Ky4Ly7TcEatbJrkiY2Ge0THMCGBBQYtl2r++MQkFxBFZq3Jz2U4Gu23WfoLInlXq6KhcG4bMAVaw02QRu641rDc3648cRAYJwDLFRgYpeTwsnc12v0tdM5VFLGHRAF0A3xnHIAEIQGWPYbWh1YOT+5Yh0XcZosNDHS1l0KjATAkwJukkEYrBtDiZNQZw4tnHZx+vrnJIfJzywcqgb/RDSl4tszyxKdQoFbthBtCOUQAwyXnSyDuR+zPwesbXl0OxV/vMVOp6IaAwJMktqQ5JKoFkZljJfh/5Y59BdXoAteozavVnyxsxGURAxIVN9gwzOIbpWWUkKuCN5IGWdJ4sDyzsbp2ZLGLT/jpGqAwSCFmvUXbxqgbYabmJkbMMh2DZ7CvG7rO77+X+2/xuXmPKEksnsdUkW9OZXC4XY3993/cBZAdiY6VEgswxyadJI7OPzz5udhh8PJ8Bb1IYk0Q+WVKalfRIkNfNLFn5osnWvI0CbCiAvD5un9SG5QrTrB2jA6WGEXkzxlQZlFREZiaMxAjKMgnCOgEUqaQU9HTHAaAwXZs2pjtQahIbhd2xyiK5gMEAbdYPUxA7VunBC0BBLTn46ywoaK2ytO9YNjnEj3KamVyDt8raTdqxawpIAzlm7ZOZAHiRk0rD3X0HphtuIab6R0XqoPKTen0mFKu6wKLgymuMW9nr9MxF7mCnzVNUAAOgYJFxNPv47OPFDo2P5/XX2dtGP6RoHIHlCFpGAWwghKUWgExS4NCy9cvbdN/BOLVdquG4Bl7rtBVml7Clme6SJ7G6oWWOxens1b15jXfrMBOyC+f1W7PbbxKIAdWOZSsmZZYK5qDFNcO40qlcs++1IVA/9VBtNPqTWCQqQxUEYgfeqJ3XouMvKCErQ0sICGAsNI+kANPCgbFPowjCMkcM2ggY+K2RK8U3mTqGSY1mv2IKWiJNjjXfINcgdOuubMKYI0iHIMga8UAibdiKDrycMsBZJBFtwNjq5QyD+OAgd2v28dnHgcPl45z3Tnb5AWz4QwpJpD5OGt5pN0nLfwBrtNi1wK2fQeUH37lp4JWOXJMG5LV+xUJlkJVVccOwLPLHJBKTS3xkjzlyqfjsj8cYXCMzaARSZ1Pz1lnPMFeWg+DV5ACXmV+2wYhcWW7p8EYGggy3LSxYNPgpbd4aRrmOQRqIIqtkhJMcp1kP2skOZED7a0hqrUGYJYFbwBpp7THs2WyASHSmNQWg0Y1K9FOunzb6KZJoKikBwyA+HmYfn318f9tIHz9gyPtmP6SsTypnGUo75QbEkrWvOrhnHftYn+BoWnhU0FqU0cLJD71mDwALaLFKDgJynR5DVsZJGEMs0/6VfwrAEr0kzm0NSHDHZxFGBu5ar+zgwDVLnPcFcVrXAqr5xkLkj7F0yC6DjMETQ0bg6fChXv4YCBg5YpkjFsjY83LJxA3dVyp3ILW+bQ4AD5A4amZg0DvaRBygtPBTUkh5cGRp+E1XocQAZYme8rkitv3MwjaLbh8qax5H0DDMPj77+MrvD4WP8xnQJ8VjAmKSvikIgEPKyBTK6JTsgdszT2dEKO/KljMiuRo6wJrKHxJVpBE8mothHczePBCXHDFyRGLCXh6QgoB5L1vHKmHk6HT+VQ+xfgIARfIIkAbEGpFB+xTasNxWpw8nYZsiJMVJEO+n1QMoDHfJUYBLIxKCDDAXpPaZbEeiwrZZlvvfe7NlwsJRmHtIq3klvZGJ75MLUSWNwJIky0LuSAO85JJRWb8Ea3VSSCnGmex3IoUEOXDkHBBGCSiG+x2XjuWsskgSgCdtHhcLUKDSJzX7+OzjvW26jzOfCXJfnzSmoZi+83DlHh/sDbOx+upda3MNrgPXHM87VAYhkTJIMAZVqjOpJyJjIMKoThqYgTX+Vo7BadklYbCTEKYYr9mUHJIALNas70GcJ7ab9B+osAAAMOdJREFUmCchbTXNoEC28F2QJUMaSgLCfvFTNl4FiUwk0Va0L3DX9/gaw9QvNs11mgFlgH3r7kDbtwvlC6PkJ9n6pJgNbj2fV9JIIApq26UlRc4+Pvv4ym8Oh48fUO3b9IeUJofoE9tqUVH501sxwSrN/PDa+pbsIp2EpQ2UtaClz88YSySPH4raAGRMyjpCZWhqKfVfGKeTSPZUqwdEy+7NGhCgSiESpptKFJaxPJNCJi9ZAY9UMglK4ITbCLikYSBdp2N+bOfntjnR8ljtNABYUNRrQ9pXESS/hqZ/W/cl1y8wY0RA1kTMU7UCXANfkDYkR31LMcnDJDTr3C9gpwb8HsD2xkIZktqkshaxyXMBCAGMXHOg+k7p3AJZTj4pwJMc6Ozjs4/vYxvp42dGn1QCa54U643w8geAFrj2cCd0jIOVEXAdu8ZFO1mk03YcS7LejiYR2h/QygxZ350TCEsasOQozkiMzKPIBcRF0w+UJZyXJT9inRxiHduLhvVyq9V7/X5NJ3M5ThhblGsg/NeYsF8v63oZeY1zWVRV0n1KfbOgY/tIAxV1PwlUrlFv1kG9zINcMzCWISJlGRXVN2YAXEWDbkOkwCSuIAzangeU0W2zrQPAoqRawFIjhehqTUY/JZHYKdsuCcgi22QdG4pDAIImYFrmPZRdci5j8dQLIc3b7OOzjx9GH+czoU+qyCFmpp2y0su+U3DK/OLuFZu85EBtTS6rC1arL7eSRIZGA7HJH1UeWUIKVUp4qaRti+SgwFlz2D6nws8rkswBo5sSaK38kZER962HcnKLlGWQOEjOSUl6pADLLwEHREorEVO2DAAyZeQ1Hc8HtXXKiEgVrJ29kCEx7LprcqOXPThglWWy/3PDqqsUQlS3g6Ct45okyZUHFIAyeNDs47OP72Mb7eMHsI1+SNnTudHr9wNtwyzbPwqeYXLJeDeGuaCM7SDj2OyEJbbDEhECZJkWxzQQJQ5F/ljyUFhVABfGCQALTiuMc+RQQnuNiflclRLppFKID9n1DLONQOIiPwDK8lDLcyVIoxeJRO7oGgNjmAksfzydjR8oI3FEpFw6obWnAhGhXKdk/QAdwhJCafwk61+kG4viGrvGZYqNA9AQ2yppkN5nkT9UScsABSBb21mMWumElJV24LNhDwCARoBHqt+VeVIihKUmPQaVRSKDYpSdh9wwzjpuvLw1MYusMvv47OO9bb6PH4xwbPRDCkABL2Wu2vzUudPqNDswm4warI6ZRhENQTT5bR0eYBESzg572HF1wnaCZFRY9jmgmrTKCSfyotHrlxyxzAMQJdlxQMZutvyRgMChAHcqS90inQyoJjVU8NZ1p5IwvZlmb6zT6/beDLxYc3nlGDMiS/kXkTxGWOJkIjk3A27JryEg2zrawGmqquyLQnMs9frWG7oOxLL9KoOw5nMwRAYp8gmjRDA1ncfKLIuE0u2mDOXOkGEygj5EoMm1AQgjIS8CQsrgQYfdYDkmxIDJVpAZnF3+/+zjs48fQh8/Q/qkDvYk9uZBW4xEdJ2sZwb3V6SRPvzVlWYx8NjrP2Q0TylnHRBNGw9jLRzJmuuhcoh0nNq5rTqvTfchqlPJgvtZUi0cZW+VaXoQeTOtPmF/IAfOSI4RRut5tcN1QA66N5NMRIzJWCIqa63HkZvpVRCzyhIrptq9Z5w2vLr08VTgQjdhgAeMZfbb1E/bhpJ4DnXbVVJxT4mJjmUKtCqHNGOFH9xmH682+zhObx8/gG32Q8osMxArU5gy35HMyjQQWP8UtMHyMLQsi7HLKNWWTQKxAdYCRBbZolQ6bw3ACbVCdOAFtjjpkNMZJ3ghjhhdxympRMK1DIuxTjNflNI0eikPk4oMYtWfpbGpHctAG56bmZThVSCaNFITGev6Nhhcn+To9fYShus0eoseSxwQEcrvFxCtfkHGyNltM0wyx5pTEpp8m6ZUzNS9NzAZsPS8myR7rus2fuI6k9dFPBEDPKJumBkpk4yim4A8BhBl5EUADRpTFgMQtYGL0VWWwAq49aRnH599/JD5OAHr3bnY4XhIrTP3Wls++7+gDLOMClrrmIlWLyOA+mEBBMRLBMplFFAAqwBWh5Pkv0EAHSThb48HIAMx1HIrkcXRS2Vpmn7N9+VhLDy4SiNVIlkng0hEkvQPSD+BADQSFd2+uW5AA94+d8SY6hLayHAoDUlCRmCpSJCQsSCUhi2aBOL2aSOeGiPvi/nXIQ/qSLB+KIgVp2/utWd/QnRLlJOalz8sMqrq9oZy+QFllARH7aMGFNCkQMwDkAcZHoJjAA9yzhRCKSALjYhCtgPKoHVDJfQ2+/jkZZl9/PT38YPa4X5IAS14+/mGb88evAyiN6wmNNZSLAYWy36X9bjKEC5XQ1hUBkhBCj/0tNCZAC5hvtm8a4314bgGoFanN0Z6cGdIqiObgDEVhrvf1gSwNDEPynSDnHsnb9hx9uG6PoTXmGdiHQxO9zOp1TNKHkgxBSEpxlUZqW8f9lPT9Avguc4n2XbV0l2D4aUQi6rqGGuJfCICBwKFAOSuU7m5KOt9oD+35tPPn328sdnHTzMfP4Bt9kPKQOzHQJkioDqPqf8TGQShyiCLKMzNhgeQ5MZcckVMEtmhJWLPMh2AS0epMjrTpBGAwBlbLFWOI3LtaAVJJBTFkuTXOzqAmsxIVjZmLFFYCxobGSSW9dooKDPT7BO6KKgJy2W5fk6sZrr8FgOJMhICtlDZY+Cg2nxCQi7RWIlXI5osIXLJUv9t5Igx63SWZSkHjCkiZ5VE8jTTZH2j4Ki+wh1pLEDjyjSjA7c1ACqBANChuJVljrJiSLI86/w8AnkhhTjzEBCMZS4GqeAPgGPUSCjtNUmoDfjs47OPH1YftwiPk9hmP6QATOr3/nV2rQwi4KWgRTZVBikFN1UKMeCaVr+lEU9bCpZ+FFBAWKBECtXB1XoWlcDYCcsifyBAw3Z1G/qZqQVxYY+okU7GTu14ZL3amNTB4NYDs8DbonLcpbR10j79ISW/pRAwi54Sdh2AUgkgKnATNIzXhSCDY5GQZL/CKBOCDPsAwpgl6VFGg1U5JIfaodxJIgyU0i0cq/ZRCGLgCuBYAc2RG72+/MZCcBMhkFyyAAZnCXmmKPIHJamZlqNUN8gDgaN7+IQgUpxp9yVZl+ShVKS82cdnHz98Pi7JwGsvd7GNfkjRFHgnbAXI/lOnSdsFL4OUTHcfcaTMrY5bk1fAWz7VQzLafIvQySI2DVLNG1QBzwGB/K/FfCjuyuBu1DLMh2Prfj3FMKdMji03oFy7L2WgmQWw1jGfXCeyl0KSDrJXwYuuEoNGOgGVaVrj7c11NnOogG47letvyCSQIKAl9L+3aVLWqkmQKoHIcUlGPmIAKIgcEvTTyWCzj88+fnh9/GBy9kY/pIRthnphTnbO7iaWTsLAhWlaLbOBcvlrJBDaK+yyZZkuG9+BKZNjmSaF+GmVRbKyzKSdsRIBFUrexeppt/0Dpt1v6cBvUSOiTAIpjQ7VMOIpa5jmhKV+PZj0IWG2Nt0wTYjMEbXRAocVTV8AKjk3In1IYuhuXmA3S7mdB9MWdvOAvRyxOw7YHQcsc8AyRaQUkFMApwCYFOJPIUBqjJl+rlp9kds9aKNjnU6vl/PR32b55CwuJyyTkDODEkmZsgWkTMwA5AEAEfJC80kCwIsIXgxASjKwYR4kDyprT0QIIo/MPj77+CH1cWJlLCexzX5IUShafZ1HVbfv/oxpen3WRigNjQySyvAAFlkkjM0BwzG8CMuEr4wvqXeE4tQiAyww6vJcHFky3GvGOgBkZCwArTLdgrgCuFaoNrBuUZJjIxlGAPCM1OegtCBNDET39t0XajlYlS23bbbfUelsjq4Rq/u1vgqpQGDscsmx+Rs5YC9H7KWhVCswnT5nDdPNpACWa9+coldHzB/0UDhy7UiOLN9tvdA1ZlwbASKSICUFs2xPWGWOKv9EgCMhg6VxGDRCawjCMAGRQYIERlNUD7JoqNnHZx8/rD5+wHJQG/6Q0tfJicSx9b/ZR3Ommuw4ZaUsDLiZXjd0gJWBsfWAGsIqzIubiCihQRZaqzkTPF0800dlGXhNozepph5rJ5WsOV5vvpP5kbJWh1eJo0geksVvgM0s+vxSO5KX1pnMwiyXKSJllUGy60yeOLUih5hZY27gbOQPriv76WaDtg2RN0j3YaG/zQODStstkgj5zyB5T9EeRFF6pTmoX8v82cdnHz+MPt5X/Fhnm/2QCrGC18IeD4Jj4oZ9Grs0trmahZ/LXwFLma9AImObZo6pcMaSJAQ3IQHcJh0m5CKFJKKSFJnU83pm1kQxlVDdNsrJJ1+WnJIJMHszplmPa9XWCSmRagXoyYKaZZuqwaPWezuRFzjBW8hMOJ63cDxtY8kRx/MWHhi3MXLA8XGBB5YyfWIcsLscpGN5GZETiQySlGVmoHGEwCvl7qquzkAjf3AD7D5vpACUAW15ZdsZ4CTr8CCRT4GkczkPUoQzDkBeBIAYeSuCllku+HLQEXcZzBlEuQZOqNQ3+/js44fNx+mMqN0XCAhBtHpgX6a5DtiS+FxlkPavZtiXQd88eNCCt8wvNxgyQZYoaJp2QmZX+0tDVAMkY30P1nltMsEq6OogdLWvYEGji4xqj71q+5YkuR7Iku0xPX8/0xFl1m+XHbNUEFtHcmWWQ2Gae3nAbhaWuadavYTjSlhuSqGE5FYZBDKkul76AjbH+oAqfxRm2QBY1iFNgq1xuahdGcpohUFS2VbV+Kk0EsY+OUDrqUGcZAjgEZJLEoNkbEbH7U3qm3189vHD6OP5DHiToo5h1gWnuCGH7n0LOXbmhwMo4MT6qKAIRhneAKq763tyGaiNgS0Sxmll/sM+0PHRTT4EN1IFbdnXD9g8eFM3bTp8dp9SoYCwx0OjzVtH8m4aBLhJppfJ5Y+kgJREL2djlkArhSh4+xDtJmeke+OANuiNEa9/AjTrCTiLLJLRSSEqg9hn1DDcEp6bJUM/c5X5gNnHZx8/nD6+TzK3t4Ot5ewzn/kMXvGKV+DIkSMgItxwww1l2XK5xNve9jY84xnPwDnnnIMjR47gJ3/yJ/G9732v2cbdd9+Nq666Cueeey7OP/98vP71r8f9999/qocCDFH+NMyRHZBXS85Pb8IH+UzW0nKdniV8FDV6x0JGT2a+gOcWJKJqCz56aixJkzu0xE7Ykz8/b+rPrbNA3Y5t0ypIR8h+jWFaJ/hBzcN/qoGyayDM0U8LUAWcA07wAifyFh7I23ggb+N43sb9aaf8HRt3cM/ybNy33MG9yx0c29vBfcsd3L+3heN7Czy4t8De3oDlMiKNEXkZgVFkENI/ZHe/lfnBGF8URsnWeRxQ5Q9lmsWNDNzAtAM1DYGx1X5/kE7lwWQRSXxMWwF5EZG3InhrAC/kD1sL0NYCNAwC6mGYfXz28cPp41sHe0c65YfUAw88gGc+85n40Ic+tLLs+PHj+MIXvoDrrrsOX/jCF/CJT3wCX//61/HKV76yWe+qq67CV77yFdx444345Cc/ic985jN44xvfeKqHssowT/lsqnEHQl/4cj/9+eFY6KQKr7cvoKDTSKv+b4uSLNMOZC999Pq81+kP2sH8cDmpgbdEd7HLCbFOZKYC7hN5gWWO2M0LjBw0FHeQjuUUMSrDTFlDcTOJPm5Zml1yY2/sAWmyBdy8nmF6wLp1p9Q2YarczUNhmPJJkyxTvqsUEib+Zh+fffww+/gB7JTlvpe+9KV46UtfOrnsvPPOw4033tjM+3f/7t/hec97Hr7zne/g0ksvxde+9jV86lOfwuc//3k897nPBQB88IMfxMte9jL8+q//Oo4cOXLwg4lS0LB2MpOGWU4Djhj1RpeRTSt4GQbcmkyXTVN2OQ6JtLAma2eqMSvSWM2DHLqTREy3T0ZNXPitjD+zz3a6fBL7XftdjqkkYXZgDmVbdbsHcZ8MFDAClWF68C55wB5HLFFZZmLCCd7C8byNBOlIfjAtNFdkgQfGLYw5YHcc8OBS1t8bI8ZRwnFTCuBRQIykFM8uvd1jZytJruuM3TrlR9x8b9JrCtbrhrmTWooUYnp9UH9TEJPp9kmTHHNeqXQ++/js44fSxw8o9/3A+6TuvfdeEBHOP/98AMAtt9yC888/vzygAODKK69ECAG33norfvzHf/zA2+YYpVM5asD+JAVo/4wQsAMvgwvrYSatmSWOucxRhsNWLTkiIyozAkHnWbkUKce/n8RQkgEBROaiyYMDIhISae6IQmgdC/T6uw8VtmWeVfpO5F4CeTjgbb9X8CYQ9iCdxHsccZy3kTjgBC/wQN5WTX6Be9NZSBxwf9rGfcsdLDng/uV2iXA6vlzgxJ4CeG/AOEYpy7IXNcoJIoFYaG6macmrY4zsJQ4zWyW76Dmv0/vIpxIK7JitxQBrI9B3JAPymQcCiJG2giRCjgBtRQRmcGL51NIx8iOefRyzjx9GH+d0GkT3nThxAm9729vwute9Dueeey4A4OjRo3jiE5/YHsQw4IILLsDRo0cnt7O7u4vd3d3y/dixYzJhJTd0Wp7wNMkmXO5d+d7fHDaGqayyjBzqX+cplDImEawFJqncuIA6PIDZOj2/JgAyrGPZJwXKgU7+tC5HC9x++948eNtQ4oduVsIlub/KyqmJckrcJTBmH+EkCYwjRxfhJPJHzqTZ9lQ7kFX+oPLWMC2pN5d+HcvkNcv8j7n7PIhRyzory6zfEWteCTFLXklk6NgMsp3Zx2cfP4w+fsC78wN7SC2XS/zET/wEmBkf/vCHH9a2rr/+erz73e9eXTDImxSiap7Bgddde/IXn9HGn2apPZVzLZMvjqRJdV1WeNRExCViuZkG5C3NFYmQfIqmfMwa7+lBLMcZ3PK00l+wAsxO8rDp0ICV1/7+oAzTOpNNArHz8hLIUotnnuBFkUJO8KJo8sfzFpZ5wPG8hfvTNkaOuH/cwvFxgZEjHlhu4cQo+SEnltJ5nDMhjQF5DMLwLFfE7qWxywlwCfGjpgUn6AihASip9RbS6xmmN88yHcM0hju5f++LAY0UkiMjWLXqhYvoSzJEPAV9SOmb1Ozjs48fNh9nPIYVJ+wB9e1vfxs333xzeYsCgIsuugjf//73m/XHccTdd9+Niy66aHJ773jHO/CWt7ylfD927BguueQSrQ0VpTS91jZjn+zoL6gmu5NFxShbMc03JclNCMQYc8Beighg7OahJD5uh0UB/yInJBqREWCVjTMSFkhYogUQUEEz1UHdgBio8ojaOlD1gAXQgFZ+a9tcZZcHAe7UC7nX6JfGIEEFqCZ77Clo78tnVfljlOkH0jaOLXc0iXEL9+1tI+WAB5cLnFgOyJkkumkZRa5aBmAUykaJJAuTqeki8ZjzBLGA2FZk6Pg29sOpNxMDNLcb098LaKnt0GYnxZTck9oeS0cyi+sNhLQFhASkJH0/lOQNiqKEHVPOqHLf7OOzjx8yH0+P0UPKHlDf/OY38elPfxpPeMITmuVXXHEF7rnnHtx+++14znOeAwC4+eabkXPG5ZdfPrnN7e1tbG9vry4ILiS3iYCauOD26aaJqekkNCmETQ4pr/XkCmLWV3sZKlokjEB12IIpjf1k0VO+k9m+H9R68JpNgfehmmeYZkUi8vIHBywRpSOZB4nJmmDryyy1yqyxTNZHYnXKcmjLwbh6ZVUGwVoJpDchmQrigk1lef669LdpP/ByN3/Cigzi5BAwakSUVZGw8aJi0MHqGAwpKTP7+Ozjh9LH10jEvZ3yQ+r+++/Ht771rfL9zjvvxB133IELLrgAF198Mf7hP/yH+MIXvoBPfvKTSCmVfqYLLrgAW1tbeNrTnoaXvOQleMMb3oCPfOQjWC6XuOaaa/Da17721CL7APBAEjUSlV1a6CPVC9REW9rF1wQ0e41mTZobcwAlxl6OWHCSBLs8FKnhRNa0xgAs8ohMAQjACbAM8majjqo0EvnUgNOD+GTrmk2x2b7WWh/ldBAzsCZu5Q9jlpkJJ3goHcgneFHY5fG8raVgFrg/7UgJmLSFe5ZnY+SAB8Yt3L8UZvnAcgsPLgfkHLC7HLDcG6QRXQbwSEX+oKSyg88TWePspT4d1cWSF6JAIRTnqEmzfgPdBnuwGqu0bhVufaz5qT5bTAoBUPJKiFg6mplkcLkURJVhkbjK8Aezj6/Mn318s308/6Ci+2677Tb82I/9WPluMtzVV1+NX/7lX8Yf//EfAwCe9axnNb/79Kc/jR/90R8FAHz0ox/FNddcgxe96EUIIeA1r3kNPvCBD5zqoUii2FBLxvBARRZpbkAPXgUwJSq1qLJmeBMx9lLEEOTSPJgWZTPH81ZhVjLcgI4hEwAbmsAkjYCMLQigk4tEMlsH6lNhgj2r3E/+WNnPmnZiKqHRh+FmEJYcsKfs0QC7RNSopkHljx3s5gVO5AWOjTL9YFrg3uUOxhzx4LjA/cstkT/2FthT+UOSFzX0dqnAZZE+CoA7ljltzgfKp2OYQA3j3ge4BfxTjNKBllRaK+0Cu207hin+ycgRoEEaj7wFANKZTNpAETOyjTYHzD7e/Xb2cWDTfTyHH5Dc96M/+qPC7tbYfsvMLrjgAnzsYx871V2vmr1Cdhn4U2+RJSQXE2xALzgXGWTqzzqdrQYXAWRhvAEgKaIZNAckwMkfTV6I7LTJH3kIdjLwnqqtCwatTLONcLLIJh/dZJJHwoT0wQFLDlqjrEY3LZMO9patPhmkUS0sjgpASmAX++k1B051GZVVdbvGLlEWtH08zn8mZZYVP6J2e1M/cUC2lZlIKgOUEF59ADFKvxBl++3s47OPd7bhPs69ZL3GNrp2X94KCEOowC0sEyil4rubQeoMTCwdzImkTUiElAiAZH7v6p07keol2g7LktuxoG0ZxjpoLghnJApA2CsdqyaNiCwi7DOjDaP1ncknM7+elWUxINt2MmgFxFP72G/U0QJauM5jhCKBLDlqwmLAcd4u2vx9aQcneFE6j3fzgN28wD3Ls7CXI06kBe7b28YyyaBuJ5aDdOYvI8alRJJJ57F2so4EGiuznIwy2u/SdeyxAXK3nPr1Mf0gKOt3+yd7sPgL6LZjfcwihUjnMmcAJJIIGBL0wAQKBMoMGrkk9s4+Pvv4pG2wj//A5L7TydJWAA31REWvVwD3r8H+gmd5BaUE8WQSZpNzAJCxN0bEkIFxwN7gABy3sIU6yNrCRShFZOyEZbl5JSoKGdGYmJZySZr5ZqDqQW22AroDMlMDcRnnh9gBvFqJUO5+72UP0+X3UBmk6fAZodQnW3LE/WlHw28j7hnPxm4a8GBa4NhyR0CbBty3u4WcA/bGiL3dRdXll6EmLmqEUxhV/oDJHzg1AJvRxFc3bwWoNL3einXyyKR277bp9foC2my/M+YcEEZ9uDi5r+xm9nHd3uzjjW2gj+9XTd7bRj+khDp0VMGe5P6108wubDOPVCbRCBtS1snyOeaAgSQKKjFhzFGAyzJ2jkkkRRbR45GMegJKaZmkVaBrkqJnfxY95W0dYNvf0QrTXGf98ingAquFNKv0oXIHIjKCssvViKZdrUdmQ2Evk0gfS41msgrPcs1RkxdV+ijZ9d1fI394dncy03UaoDrJo4bUTqzfgXBqu802TBrpjos9y23kEGhABJdjMiYK5jokgz+G2cexzmYf7+adxj7OB3uR2uyHVNqmkiwGoHTaMQE51iKHKyzDOpX1Cc8JgHYwZxLnWpLkLuzGOizaVhgxlmEBZJht38mciQqzzBTKMNwLGktmf+BaJBMQmcQsdnTHs1AzA7kHtx8Z1Y7H55L4ytdT4/b0ww+0SYu0wixPZCn9khAqs+SIe8ez8GBaYC8PuHdvByeSFNS8b3cbyySjje7uLsCWuLgXa1TTkor8EUz+YIBSOcjSWdvLEAdUklZ52xp2CbSAk2XcLJuYXRasZcEKTmKU4bYpS3EJEOnYPhoBlSW/pGm4MPv47OP72yb5eKKVo520jX5I5QUhDfWGFj2ULEyXameemWcuWR2EBLycJH5pHGN5QVumWMCwlRbIQTxqCAJYQDpylxSxHYQtyfp78nuWumgLMglFS/sDRSYBDHwK8gLSaoWZah21cg0wLaPYKhnUdEBPhf8aYG15Xzgza3b9ibxAQii6vID27FI4857lWTiRFthLA+5bbmN3HDDmgAd2t0SXHwPGvUFCokcClkEY5SiyB1ikD5M9pLHupBBMyAxTbO8UrGk318ggvqDrSbE19Taj27MckhyBwOKflEWiIo09lz6pCna/vdnHu/PE7OMHsdPRx3niPk3ZRj+k2F0Q+w4P2ik5RG1duKVEQAHMVQ5JOWCgjMxSTmYBkUQQgAUr07REPwoAZywxlPDYgAzwINWcGYCyzKwyiRxQR5fVKpj9u7FjpirHrGyjuVDTs80sggkQScYXzlxCOsj3uCYvLlk6i/tB3MYcsZeq/DFaZJNLXoQNP2BFM02v1rIvxBWs5IHQTU9KIQ8BvCvbUH8pMoiXS2zZQbY3sdIqc9X53oetH8rK2WSW9WYfX92Gt9nH97XT0ccPeiob/ZCSgbVcqCZVxsCRkCPqk92B2UJ1SzQNsURABdXqc8AopBB744CscsgiLTBklULAGEyrhzBL64SNYImSygERGUsSjT9ylurNlgBJMkYOMF1MExDppLdIa9ZttrEu4LY1axiW2tFt2fRW9sVGFj2ug7clkMgfSeSP+5Y7Kn9E3Le3I6OL5oDju1tYpiiy0t6AnAg8BmDPRTUtFbTjKrO0SKLSUetYpt1DYM28bv7kd2C6cfcAnvpusybmT9kK2zQfjZrKpA8K0kg8JoCiXA+K3fn732P28dnHuxPdMB8/aFL3xj+kyOQ+zwIUtOwA3IfqyorQq6iMNQsN4GSRSoy9URw7EGM3DcghIaSMgYZGq/dyg4XHZpKO4gWSDpWdVa+XQeDkJom0seQKTJNJxDRKyoF26eSQZl2Obhs1UW5dBJWNyGoJmolD0eMBNPLH8byF48kinLbxYFpgzBH3LlWXTxH3L7ewNw4YU5DhB0bpRE67OuyA6fJZo5pc6K1IIVQjgUzmctFEk1JIzzan2Gd/z80mMGI+QjTx3c/rAL5iNr/fn/sdR1TGrPJdIAayPmASYKVpZh+fffzQ+fjBOMZmP6RKhEgHYADlYllkyUllEecANv4Os0VBiRySmaS8fojIPGKZIwbKWLIU6gzMWLD0ei85Sq0zZW8gaF7JCHBGQkSEsFDT3L0WX8baUQ/OHBoWaVp+JNkW0MoiU+t688ODG3AtibNo9NaRzAG7eSERTTrsgAF4Lw81silFjMkim7Q2mQIXGfpHjfRRQMqObHTgtfuyVgpZA+KV6d4mwFwkD0bJ/QDpqjpNcMttU1MPh6ld6jbLtoGifJXEXUvi9b49+7hMzz5el2NiurfT2MfPjOi+LYAWaG8uKgsoHctRnuilD8sZQVlrJiCpbySpk5YgUVCAgHoIA1JwUkhITgrJJXM/EGMnLAuwF2GUpEgAS4pFpgjKNoGWRXrwybJVb/BSx0HyT8o1c7q8NRIyBs7QZNFnDmXYgcykzFKm7xu3cVxHFj1ehh0gnNhbyMiiKSDtxarLL0Mp+RIswikDNKIknpKPZDNAZjSgpu5TbkwL3FMGsVnf+KNlk820AY7qfJNHegllypgAsjcfrgyWAyRows5Ts1H74Al/PLOPr9rs42vsNPNxH5G5n230Q0oKGEp2fn+PWIfZBlCkEM88V15VPcOxqsSEAmCC5JMAAFFEzLlEFe3miEgWtcRlm4lE/si5ZlebPAJIFn+d9oCsZxORsZxwQA948Cro15lFVwHAHsvtzwXAVIYbSCzyh3UWP5gWeEABfP9yGw+OizLswO4YkbPo8skGbluGwi5F/hAAF6AmILg6ZTYfaIE7pdf7XJJVMHOZBtqG3c8v1uGklTmorEMenOx+G+o0kwPjun1YI2CTti7VmWznRbKQgdnHZx933w+Hj+cz4U3Kh+NO3ZjCKO3Vsgfvygb9n1zJvtZZYkJQWWTMASMFjBSRScbjGUk6jsccgKBsobsZwZge2E27aCcHxmWROVqAitSyP/vszVilMZilAtiAa3XJTuQFMhN2VfLIHKTjOEWMmsy4TFESP5Mw8TLsgIY5F/Dap9Phe/YID07uwNs1sCtvFUXP5xa07tLsG7LbvZ34CCc5GFmHiapmn1GAR37abY7cNldmTuyv/N5yTHq2PPt4sdnHD4eP9z6zzjb6IZVV7pu6Qf2rawGwm27+imPUIpAgGdLZbDlGpCC102KQgeKayCeWMismk2yzhE8tcsKgEoolPwIip7QSyAQg14XcYk3uyD5mWr51Ji85SrQW14KiS44FtLtai2zMASfSAg+OUuLl+HKB3eUgpWSMWWaSxEUddoCWVMAbljWSKYyoYblpmk368Fx4xlnWdWDtO517drmObXZWtHdy3wuQAVYw23wDdCOLBDTyiGed5VDcNm0/dowM94Di9hxmHz+YzT6+3k43H89THYkTttEPqaLDT92c5uI7xulBO7lRFObDRKWUTCYtRJkDEkkC5BAyAjH2dGRTs0bKIFZtPEkHMtXEw4jcrbsKyHCAqvL7/R6ogAVQAAuggFYYpUQ7ScFM1evTgBNJGOeD4wInRhkDZ3cp0U029EMz7ICWfLGQW0tcJO1U9nkjHpgeyOU03HQFNa/KIh273Be8a3ylYYX6vXkjCW5+QGWgugJbsIMBPLSsc8rfvLZfOpj9j9zn7OPrfw/MPr6JPn6oAydsOJC0e6JhFo2tATBHxzgHBg+yPCcGRxbZZMxAZCAyaMxAyOCYkUahRRQzxjgCIYNiQogSnkthBAWdphE5JESSoaxzSAgK2FMC8OTJTdsU6xRmWSlLC+DaEb6nP93LucoiKWOZGMzAOMr5MxPSMqv8QcjLiDwqgPdCBfDSAThVALPX6B2bbGSSKQAXcP5gAFwWe1bYvak0by3GJG2cJ8csiwznvk/JcL7feOoYm/OYfVzWnX380Ph42j0hkychKcQHGQDqNLP/83/+Dy655JLH+jBmm2222WZ7mPbd734XT3rSk9Yu38iHVM4Z3/ve98DMuPTSS/Hd734X55577mN9WD8QO3bsGC655JJDfY7AfJ6Hzc6E8zwTzhH4wZ0nM+O+++7DkSNHEMJ67W8j5b4QAp70pCfh2LFjAIBzzz33UDsJcGacIzCf52GzM+E8z4RzBH4w53neeeeddJ0Ddl3NNttss80226Nv80Nqttlmm22209Y2+iG1vb2NX/qlX8L29vZjfSg/MDsTzhGYz/Ow2ZlwnmfCOQKP/XluZODEbLPNNttsZ4Zt9JvUbLPNNttsh9vmh9Rss80222ynrc0Pqdlmm2222U5bmx9Ss80222yznba2sQ+pD33oQ3jyk5+MnZ0dXH755fjc5z73WB/Sw7Lrr78ef/fv/l08/vGPxxOf+ES8+tWvxte//vVmnRMnTuBNb3oTnvCEJ+Bxj3scXvOa1+Cuu+56jI744dt73/teEBGuvfbaMu+wnONf/MVf4B//43+MJzzhCTjrrLPwjGc8A7fddltZzsx417vehYsvvhhnnXUWrrzySnzzm998DI/41C2lhOuuuw6XXXYZzjrrLPz1v/7X8S//5b9sarFt4nl+5jOfwSte8QocOXIERIQbbrihWX6Qc7r77rtx1VVX4dxzz8X555+P17/+9bj//vsfxbPY3/Y7x+Vyibe97W14xjOegXPOOQdHjhzBT/7kT+J73/tes41H7Rx5A+3jH/84b21t8b//9/+ev/KVr/Ab3vAGPv/88/muu+56rA/tIduLX/xi/q3f+i3+8pe/zHfccQe/7GUv40svvZTvv//+ss7P/uzP8iWXXMI33XQT33bbbfz3/t7f4+c///mP4VE/dPvc5z7HT37yk/lv/+2/zW9+85vL/MNwjnfffTf/8A//MP/UT/0U33rrrfznf/7n/F//63/lb33rW2Wd9773vXzeeefxDTfcwF/60pf4la98JV922WX84IMPPoZHfmr2nve8h5/whCfwJz/5Sb7zzjv5D//wD/lxj3sc/9t/+2/LOpt4nv/5P/9n/sVf/EX+xCc+wQD4j/7oj5rlBzmnl7zkJfzMZz6T//RP/5T/x//4H/w3/sbf4Ne97nWP8pmst/3O8Z577uErr7yS/8N/+A/8Z3/2Z3zLLbfw8573PH7Oc57TbOPROseNfEg973nP4ze96U3le0qJjxw5wtdff/1jeFSPrH3/+99nAPwnf/InzCyOs1gs+A//8A/LOl/72tcYAN9yyy2P1WE+JLvvvvv4KU95Ct9444389//+3y8PqcNyjm9729v4hS984drlOWe+6KKL+N/8m39T5t1zzz28vb3Nv//7v/9oHOIjYi9/+cv5Z37mZ5p5/+Af/AO+6qqrmPlwnGffgB/knL761a8yAP785z9f1vkv/+W/MBHxX/zFXzxqx35Qm3oQ9/a5z32OAfC3v/1tZn50z3Hj5L69vT3cfvvtuPLKK8u8EAKuvPJK3HLLLY/hkT2ydu+99wIALrjgAgDA7bffjuVy2Zz3U5/6VFx66aUbd95vetOb8PKXv7w5F+DwnOMf//Ef47nPfS7+0T/6R3jiE5+IZz/72fjN3/zNsvzOO+/E0aNHm/M877zzcPnll2/UeT7/+c/HTTfdhG984xsAgC996Uv47Gc/i5e+9KUADs95ejvIOd1yyy04//zz8dznPresc+WVVyKEgFtvvfVRP+ZHwu69914QEc4//3wAj+45blyB2f/7f/8vUkq48MILm/kXXngh/uzP/uwxOqpH1nLOuPbaa/GCF7wAP/IjPwIAOHr0KLa2toqTmF144YU4evToY3CUD80+/vGP4wtf+AI+//nPryw7LOf453/+5/jwhz+Mt7zlLfgX/+Jf4POf/zx+/ud/HltbW7j66qvLuUz58Cad59vf/nYcO3YMT33qUxFjREoJ73nPe3DVVVcBwKE5T28HOaejR4/iiU98YrN8GAZccMEFG3neJ06cwNve9ja87nWvKwVmH81z3LiH1Jlgb3rTm/DlL38Zn/3sZx/rQ3lE7bvf/S7e/OY348Ybb8TOzs5jfTg/MMs547nPfS7+1b/6VwCAZz/72fjyl7+Mj3zkI7j66qsf46N75OwP/uAP8NGPfhQf+9jH8PSnPx133HEHrr32Whw5cuRQneeZbMvlEj/xEz8BZsaHP/zhx+QYNk7u+6Ef+iHEGFcivu666y5cdNFFj9FRPXJ2zTXX4JOf/CQ+/elPNwOBXXTRRdjb28M999zTrL9J53377bfj+9//Pv7O3/k7GIYBwzDgT/7kT/CBD3wAwzDgwgsv3PhzBICLL74Yf+tv/a1m3tOe9jR85zvfAYByLpvuw7/wC7+At7/97Xjta1+LZzzjGfgn/+Sf4J//83+O66+/HsDhOU9vBzmniy66CN///veb5eM44u67796o87YH1Le//W3ceOONzTAdj+Y5btxDamtrC895znNw0003lXk5Z9x000244oorHsMje3jGzLjmmmvwR3/0R7j55ptx2WWXNcuf85znYLFYNOf99a9/Hd/5znc25rxf9KIX4X//7/+NO+64o/w997nPxVVXXVWmN/0cAeAFL3jBSvrAN77xDfzwD/8wAOCyyy7DRRdd1JznsWPHcOutt27UeR4/fnxlsLoYI3KW8dAPy3l6O8g5XXHFFbjnnntw++23l3Vuvvlm5Jxx+eWXP+rH/FDMHlDf/OY38d/+23/DE57whGb5o3qOj2gYxqNkH//4x3l7e5t/+7d/m7/61a/yG9/4Rj7//PP56NGjj/WhPWT7Z//sn/F5553H//2//3f+y7/8y/J3/Pjxss7P/uzP8qWXXso333wz33bbbXzFFVfwFVdc8Rge9cM3H93HfDjO8XOf+xwPw8Dvec97+Jvf/CZ/9KMf5bPPPpt/7/d+r6zz3ve+l88//3z+j//xP/L/+l//i1/1qled9qHZvV199dX8V//qXy0h6J/4xCf4h37oh/itb31rWWcTz/O+++7jL37xi/zFL36RAfD73vc+/uIXv1gi2w5yTi95yUv42c9+Nt9666382c9+lp/ylKecViHo+53j3t4ev/KVr+QnPelJfMcddzTt0e7ubtnGo3WOG/mQYmb+4Ac/yJdeeilvbW3x8573PP7TP/3Tx/qQHpYBmPz7rd/6rbLOgw8+yD/3cz/Hf+Wv/BU+++yz+cd//Mf5L//yLx+7g34ErH9IHZZz/E//6T/xj/zIj/D29jY/9alP5d/4jd9oluec+brrruMLL7yQt7e3+UUvehF//etff4yO9qHZsWPH+M1vfjNfeumlvLOzw3/tr/01/sVf/MWmIdvE8/z0pz89icWrr76amQ92Tv/v//0/ft3rXsePe9zj+Nxzz+Wf/umf5vvuu+8xOJtp2+8c77zzzrXt0ac//emyjUfrHOehOmabbbbZZjttbeP6pGabbbbZZjtzbH5IzTbbbLPNdtra/JCabbbZZpvttLX5ITXbbLPNNttpa/NDarbZZpttttPW5ofUbLPNNttsp63ND6nZZpttttlOW5sfUrPNNttss522Nj+kZpttttlmO21tfkjNNttss8122tr8kJptttlmm+20tfkhNdtss80222lr/z9Ez1LLavHSbQAAAABJRU5ErkJggg==", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "PyObject " - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "imshow(Array(@view GPUprob.vars.ux[:,:,20]))" - ] - }, - { - "cell_type": "markdown", - "id": "enclosed-projection", - "metadata": {}, - "source": [ - "# Comparsion between CPU and GPU runtime" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "frank-bulgarian", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Effective GPU memory usage: 21.42% (2.141 GiB/10.000 GiB)\n", - "Memory pool usage: 972.253 MiB (1024.000 MiB reserved)" - ] - } - ], - "source": [ - "CUDA.reclaim()\n", - "GC.gc(true)\n", - "CUDA.memory_status()" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "changing-nicaragua", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Total CPU/GPU time run = 1.482 s, zone update per second = 1.5570136113e7 \n", - " 1.481688 seconds (2.89 M CPU allocations: 155.894 MiB, 2.09% gc time) (619 GPU allocations: 6.987 GiB, 1.63% memmgmt time)\n" - ] - } - ], - "source": [ - "#GPU on 128^3\n", - "GPUprob = Problem(GPU();nx = N,Lx = Lx,\n", - " ν = ν,\n", - " nν = 1,\n", - " η = η, \n", - " # Timestepper and equation options\n", - " dt = 1/50,\n", - " stepper = \"ForwardEuler\",\n", - " B_field = true,\n", - " VP_method = false,\n", - " Dye_Module = false,\n", - " # Float type and dealiasing\n", - " T = Float64);\n", - "\n", - "ProblemGeneratorTG!(GPUprob,2π);\n", - "\n", - "# Actaul computation\n", - "@CUDA.time TimeIntegrator!(GPUprob,5.0,10;\n", - " diags = [KE,ME],\n", - " loop_number = 100,\n", - "\t save = false);" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "straight-yugoslavia", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Effective GPU memory usage: 50.48% (5.048 GiB/10.000 GiB)\n", - "Memory pool usage: 1.518 GiB (3.906 GiB reserved)" - ] - } - ], - "source": [ - "CUDA.reclaim()\n", - "GC.gc(true)\n", - "CUDA.memory_status()" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "unusual-vanilla", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Total CPU/GPU time run = 10.831 s, zone update per second = 2.129778933e6 \n", - " 11.121642 seconds (9.53 M allocations: 3.636 GiB, 2.26% gc time, 18.06% compilation time)\n" - ] - } - ], - "source": [ - "#CPU on 128^3\n", - "CPUprob = Problem(CPU();nx = N,Lx = Lx,\n", - " ν = ν,\n", - " nν = 1,\n", - " η = η, \n", - " # Timestepper and equation options\n", - " dt = 1/50,\n", - " stepper = \"ForwardEuler\",\n", - " B_field = true,\n", - " VP_method = false,\n", - " Dye_Module = false,\n", - " # Float type and dealiasing\n", - " T = Float64);\n", - "\n", - "ProblemGeneratorTG!(CPUprob,2π);\n", - "\n", - "# Actaul computation\n", - "@time TimeIntegrator!(CPUprob,5.0,10;\n", - " diags = [KE,ME],\n", - " loop_number = 100,\n", - "\t save = false);" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "material-hanging", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Julia (8 threads) 1.7.3", - "language": "julia", - "name": "julia-(8-threads)-1.7" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.7.3" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/src/DyeModule.jl b/src/DyeModule.jl index 13b317d..bbb291e 100644 --- a/src/DyeModule.jl +++ b/src/DyeModule.jl @@ -106,25 +106,25 @@ function DyeEqn!(N, sol, t, clock, vars, params, grid) # ∂ρₖ/∂t = ∑ᵢ -im*kᵢ*(ρₖ vₖᵢ) # Initialization of rho - @. N*=0; + @. N*=0 for (uᵢ,kᵢ) ∈ zip([vars.ux,vars.uy,vars.uz],[grid.kr,grid.l,grid.m]) # Initialization @. vars.nonlin1 *= 0; - ρuᵢ = vars.nonlin1; - ρuᵢh = vars.nonlinh1; + ρuᵢ = vars.nonlin1 + ρuᵢh = vars.nonlinh1 # get back the updated sol in real space using fft ldiv!(ρuᵢ, grid.rfftplan, deepcopy(sol)) # Pre-Calculation in Real Space - @. ρuᵢ *= uᵢ; + @. ρuᵢ *= uᵢ # Fourier transform - mul!(ρuᵢh, grid.rfftplan, ρuᵢ); + mul!(ρuᵢh, grid.rfftplan, ρuᵢ) # Perform the actual calculation - @. N += -im*kᵢ*ρuᵢh; + @. N += -im*kᵢ*ρuᵢh end return nothing end \ No newline at end of file diff --git a/src/MHDFlows.jl b/src/MHDFlows.jl index 107f124..61b8347 100644 --- a/src/MHDFlows.jl +++ b/src/MHDFlows.jl @@ -2,15 +2,18 @@ module MHDFlows using CUDA, + FastBroadcast, Statistics, Reexport, DocStringExtensions, HDF5, FFTW, - ProgressMeter + ProgressMeter, + TimerOutputs @reexport using FourierFlows +using Random: rand! using LinearAlgebra: mul!, ldiv! import Base: show, summary @@ -21,31 +24,53 @@ abstract type MHDVars <: AbstractVars end include("DyeModule.jl") include("Problems.jl") include("pgen.jl") -include("Solver/HDSolver.jl") -include("Solver/MHDSolver.jl") -include("Solver/HDSolver_VP.jl") -include("Solver/MHDSolver_VP.jl") +# Data Structure +include("Structure/datastructure.jl") +include("Structure/HDParams.jl") +include("Structure/HDVars.jl") +include("Structure/MHDParams.jl") +include("Structure/MHDVars.jl") +# Solver +include("Solver/VPSolver.jl"); +include("Solver/HDSolver.jl"); +include("Solver/MHDSolver.jl"); +include("Solver/ShearingBox.jl"); +include("Solver/HDSolver_Compessible.jl"); +include("Solver/MHDSolver_Compessible.jl"); +# integrator related include("DiagnosticWrapper.jl") include("integrator.jl") -include("datastructure.jl") + +# timestepper +include("timestepper/timestepper.jl") + +#utils include("utils/utils.jl"); include("utils/VectorCalculus.jl") include("utils/MHDAnalysis.jl") include("utils/GeometryFunction.jl") include("utils/IC.jl") include("utils/UserInterface.jl") - +include("utils/TurbStatTool.jl") #pgen module +include("pgen/A99ForceDriving_GPU.jl") include("pgen/A99ForceDriving.jl") include("pgen/TaylorGreenDynamo.jl") include("pgen/NegativeDamping.jl") +DivVCorrection! = VPSolver.DivVCorrection!; +DivBCorrection! = VPSolver.DivBCorrection!; + export Problem, TimeIntegrator!, Restart!, + DivVCorrection!, + DivBCorrection!, Cylindrical_Mask_Function, + DivFreeSpectraMap, SetUpProblemIC!, + readMHDFlows, Curl, Div, LaplaceSolver, diff --git a/src/Problems.jl b/src/Problems.jl index caedd2d..d5a175f 100644 --- a/src/Problems.jl +++ b/src/Problems.jl @@ -3,42 +3,31 @@ # ---------- -""" - struct Equation{T, TL, G<:AbstractFloat} - -The equation to be solved `∂u/∂t = L*u + N(u)`. Array `L` includes the coefficients -of the linear term `L*u` and `calcN!` is a function which computes the nonlinear -term `N(u)`. The struct also includes the problem's `grid` and the float type of the -state vector (and consequently of `N(u)`). -$(TYPEDFIELDS) -""" -struct Equation{T, TL, G<:AbstractFloat} - "array with coefficient for the linear part of the equation" - L :: TL - "function that computes the nonlinear part of the equation" - calcN! :: Function - "the grid" - grid :: AbstractGrid{G} - "the dimensions of `L`" - dims :: Tuple - "the float type for the state vector" - T :: T # eltype or tuple of eltypes of sol and N -end - """ Equation(L, calcN!, grid; dims=supersize(L), T=nothing) The equation constructor from the array `L` of the coefficients of the linear term, the function `calcN!` that computes the nonlinear term and the `grid` for the problem. """ -function Equation(L, calcN!, grid::AbstractGrid{G}; dims=supersize(L), T=nothing) where G +function Setup_Equation(calcN!, grid::AbstractGrid{G}; T=nothing, Nl = 3) where G + dims = tuple(size(grid.Krsq)...,Nl) T = T == nothing ? T = cxtype(G) : T - - return Equation(L, calcN!, grid, dims, T) + #Compatibility to FourierFlows.Equation + L = 0 + return FourierFlows.Equation(L, calcN!, grid; dims=dims) end CheckON(Flag_equal_to_True::Bool) = Flag_equal_to_True ? string("ON") : string("OFF") +function CheckON(FlagB::Bool, FlagE::Bool) + if FlagB + FlagE ? string("ON (EMHD)") : string("ON (Ideal MHD)") + else + string("OFF") + end + +end + function CheckDye(dye::Dye) if dye.dyeflag == true return string("ON, at prob.dye") @@ -79,8 +68,14 @@ $(TYPEDFIELDS) struct Flag "Magnetic Field" b :: Bool + "EMHD Field" + e :: Bool "Volume Penalization" vp :: Bool + "Compressibility" + c :: Bool + "Shear" + s :: Bool end """ @@ -89,7 +84,7 @@ end A problem that represents a partial differential equation. $(TYPEDFIELDS) """ -struct MHDFlowsProblem{T, A<:AbstractArray, Tg<:AbstractFloat, TL, Dye, usr_foo} <: AbstractProblem +struct MHDFlowsProblem{T, A<:AbstractArray, Tg<:AbstractFloat, TL, Dye, usr_foo, AbstractGrid} <: AbstractProblem "the state vector" sol :: A "the problem's slock" @@ -97,7 +92,7 @@ struct MHDFlowsProblem{T, A<:AbstractArray, Tg<:AbstractFloat, TL, Dye, usr_foo} "the equation" eqn :: FourierFlows.Equation{T, TL, Tg} "the grid" - grid :: AbstractGrid{Tg} + grid :: AbstractGrid "the variables" vars :: AbstractVars "the parameters" @@ -122,36 +117,43 @@ to the time-stepper constructor. """ function MHDFLowsProblem(eqn::FourierFlows.Equation, stepper, dt, grid::AbstractGrid{T}, vars=EmptyVars, params=EmptyParams, dev::Device=CPU(); - BFlag = false, VPFlag = false, DyeFlag = false, usr_func = [], + BFlag = false, EFlag = false, VPFlag = false, CFlag = false, SFlag = false, DyeFlag = false, usr_func = [], stepperkwargs...) where T clock = FourierFlows.Clock{T}(dt, 0, 0) + if EFlag && stepper == "HM89" + # timestepper = eSSPIFRK3TimeStepper(eqn, dev) #For SFlag + timestepper = HM89TimeStepper(eqn, dev) #For EFlag + else + timestepper = FourierFlows.TimeStepper(stepper, eqn, dt, dev) + end + sol = zeros(dev, eqn.T, eqn.dims) - timestepper = FourierFlows.TimeStepper(stepper, eqn, dt, dev); - - sol = zeros(dev, eqn.T, eqn.dims); + flag = Flag(BFlag, EFlag, VPFlag, CFlag, SFlag) - flag = Flag(BFlag, VPFlag); + dye = DyeContructer(dev, DyeFlag, grid) - dye = DyeContructer(dev, DyeFlag, grid); + usr_func = length(usr_func) == 0 ? [nothingfunction] : usr_func - usr_func = length(usr_func) == 0 ? [nothingfunction] : usr_func; return MHDFlowsProblem(sol, clock, eqn, grid, vars, params, timestepper, flag, usr_func, dye) + end show(io::IO, problem::MHDFlowsProblem) = print(io, "MHDFlows Problem\n", - " │ Funtions\n", - " │ ├──────── B-field: "*CheckON(problem.flag.b),'\n', - " ├─────├────── VP Method: "*CheckON(problem.flag.vp),'\n', - " │ ├──────────── Dye: "*CheckDye(problem.dye),'\n', - " │ └── user function: "*CheckFunction(problem.usr_func),'\n', - " │ ",'\n', - " │ Features ",'\n', - " │ ├─────────── grid: grid (on " * string(typeof(problem.grid.device)) * ")", '\n', - " │ ├───── parameters: params", '\n', - " │ ├────── variables: vars", '\n', - " └─────├─── state vector: sol", '\n', - " ├─────── equation: eqn", '\n', - " ├────────── clock: clock", '\n', - " └──── timestepper: ", string(nameof(typeof(problem.timestepper)))) + " │ Funtions\n", + " │ ├ Compressibility: "*CheckON(problem.flag.c),'\n', + " │ ├──────── B-field: "*CheckON(problem.flag.b,problem.flag.e),'\n', + " │ ├────────── Shear: "*CheckON(problem.flag.s),'\n', + " ├─────├────── VP Method: "*CheckON(problem.flag.vp),'\n', + " │ ├──────────── Dye: "*CheckDye(problem.dye),'\n', + " │ └── user function: "*CheckFunction(problem.usr_func),'\n', + " │ ",'\n', + " │ Features ",'\n', + " │ ├─────────── grid: grid (on " * string(typeof(problem.grid.device)) * ")", '\n', + " │ ├───── parameters: params", '\n', + " │ ├────── variables: vars", '\n', + " └─────├─── state vector: sol", '\n', + " ├─────── equation: eqn", '\n', + " ├────────── clock: clock", '\n', + " └──── timestepper: ", string(nameof(typeof(problem.timestepper)))) \ No newline at end of file diff --git a/src/Solver/HDSolver.jl b/src/Solver/HDSolver.jl index de2bcad..1b3da7e 100644 --- a/src/Solver/HDSolver.jl +++ b/src/Solver/HDSolver.jl @@ -11,42 +11,40 @@ export using CUDA, - Reexport, - DocStringExtensions - -@reexport using FourierFlows + TimerOutputs using LinearAlgebra: mul!, ldiv! -using FourierFlows: parsevalsum - +include("VPSolver.jl") # δ function δ(a::Int,b::Int) = ( a == b ? 1 : 0 ); +# checking function of VP method +VP_is_turned_on(params) = hasproperty(params,:U₀x); function UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x") if direction == "x" # a = {1,2,3} -> {x,y,z} direction - a = 1; - kₐ = grid.kr; - k⁻² = grid.invKrsq; - ∂uᵢh∂t = @view N[:,:,:,params.ux_ind]; + a = 1 + kₐ = grid.kr + k⁻² = grid.invKrsq + ∂uᵢh∂t = @view N[:,:,:,params.ux_ind::Int] elseif direction == "y" - a = 2; - kₐ = grid.l; + a = 2 + kₐ = grid.l k⁻² = grid.invKrsq; - ∂uᵢh∂t = @view N[:,:,:,params.uy_ind]; + ∂uᵢh∂t = @view N[:,:,:,params.uy_ind::Int] elseif direction == "z" - a = 3; - kₐ = grid.m; - k⁻² = grid.invKrsq; - ∂uᵢh∂t = @view N[:,:,:,params.uz_ind]; + a = 3 + kₐ = grid.m + k⁻² = grid.invKrsq + ∂uᵢh∂t = @view N[:,:,:,params.uz_ind::Int] else @@ -54,49 +52,52 @@ function UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x") end - @. ∂uᵢh∂t*= 0; - - for (uᵢ,kᵢ) ∈ zip([vars.ux,vars.uy,vars.uz],[grid.kr,grid.l,grid.m]) - for (uⱼ,kⱼ,j) ∈ zip([vars.ux,vars.uy,vars.uz],[grid.kr,grid.l,grid.m],[1, 2, 3]) - - # Initialization - @. vars.nonlin1 *= 0; - uᵢuⱼ = vars.nonlin1; - uᵢuⱼh = vars.nonlinh1; - - # Pre-Calculation in Real Space - @. uᵢuⱼ = uᵢ*uⱼ; - - # Fourier transform - mul!(uᵢuⱼh, grid.rfftplan, uᵢuⱼ); - - # Perform the actual calculation - @. ∂uᵢh∂t += -im*kᵢ*(δ(a,j)-kₐ*kⱼ*k⁻²)*uᵢuⱼh; - + @. ∂uᵢh∂t*= 0 + uᵢuⱼ = vars.nonlin1 + uᵢuⱼh = vars.nonlinh1 + for (uᵢ,kᵢ,i) ∈ zip((vars.ux,vars.uy,vars.uz),(grid.kr,grid.l,grid.m),(1, 2, 3)) + for (uⱼ,kⱼ,j) ∈ zip((vars.ux,vars.uy,vars.uz),(grid.kr,grid.l,grid.m),(1, 2, 3)) + if i <= j + # Pre-Calculation in Real Space + @. uᵢuⱼ = uᵢ*uⱼ + + # Fourier transform + mul!(uᵢuⱼh, grid.rfftplan, uᵢuⱼ) + + # Perform the actual calculation + @. ∂uᵢh∂t += -im*kᵢ*(δ(a,j)-kₐ*kⱼ*k⁻²)*uᵢuⱼh + if i !=j + @. ∂uᵢh∂t += -im*kⱼ*(δ(a,i)-kₐ*kᵢ*k⁻²)*uᵢuⱼh end + end end - - #Compute the diffusion term - νk^2 u_i - uᵢ = direction == "x" ? vars.ux : direction == "y" ? vars.uy : vars.uz; - uᵢh = vars.nonlinh1; - mul!(uᵢh, grid.rfftplan, uᵢ); - @. ∂uᵢh∂t += -grid.Krsq*params.ν*uᵢh; - - # hyperdiffusion term - if params.nν > 1 - @. ∂uᵢh∂t += -grid.Krsq^params.nν*params.ν*uᵢh; - end + end + + # Updating the solid domain if VP flag is ON + if VP_is_turned_on(params) + VPSolver.VP_UᵢUpdate!(∂uᵢh∂t, kₐ.*k⁻², a, clock, vars, params, grid) + end - return nothing - + #Compute the diffusion term - νk^2 u_i + uᵢ = direction == "x" ? vars.ux : direction == "y" ? vars.uy : vars.uz + uᵢh = vars.nonlinh1 + mul!(uᵢh, grid.rfftplan, uᵢ) + @. ∂uᵢh∂t += -grid.Krsq*params.ν*uᵢh + + # hyperdiffusion term + if params.nν > 1 + @. ∂uᵢh∂t += -grid.Krsq^params.nν*params.ν*uᵢh + end + + return nothing end function HDcalcN_advection!(N, sol, t, clock, vars, params, grid) #Update V + B Real Conponment - ldiv!(vars.ux, grid.rfftplan, deepcopy(@view sol[:, :, :, params.ux_ind])); - ldiv!(vars.uy, grid.rfftplan, deepcopy(@view sol[:, :, :, params.uy_ind])); - ldiv!(vars.uz, grid.rfftplan, deepcopy(@view sol[:, :, :, params.uz_ind])); + ldiv!(vars.ux, grid.rfftplan, deepcopy(@view sol[:, :, :, params.ux_ind])) + ldiv!(vars.uy, grid.rfftplan, deepcopy(@view sol[:, :, :, params.uy_ind])) + ldiv!(vars.uz, grid.rfftplan, deepcopy(@view sol[:, :, :, params.uz_ind])) #Update V Advection UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x") diff --git a/src/Solver/HDSolver_Compessible.jl b/src/Solver/HDSolver_Compessible.jl new file mode 100644 index 0000000..2f75394 --- /dev/null +++ b/src/Solver/HDSolver_Compessible.jl @@ -0,0 +1,135 @@ +module HDSolver_compressible +# ---------- +# Compessible Navier–Stokes Solver for 3D Magnetohydrodynamics Problem +# ---------- + +export HDcalcN_advection!, + ρUpdate! +using LinearAlgebra: mul!, ldiv! + +using + CUDA, + TimerOutputs + +# Definition of physical parameter between real space and spectral sapce +# fft - space parameters -> ρ px py pz +# real - space parameters -> ρ ux uy uz + +# Solving the continuity equation +# ∂ρ∂t = -∇· (ρv) => ∑_i -im*kᵢ(ρvᵢ)ₕ +function ρUpdate!(N, sol, t, clock, vars, params, grid) + ∂ρ∂t = @view N[:,:,:,params.ρ_ind] + pv₁h = @view sol[:,:,:,params.ux_ind] + pv₂h = @view sol[:,:,:,params.uy_ind] + pv₃h = @view sol[:,:,:,params.uz_ind] + + @. ∂ρ∂t*=0 + for (ρuᵢh,kᵢ) ∈ zip((pv₁h,pv₂h,pv₃h),(grid.kr,grid.l,grid.m)) + # Perform the Actual Advection update + @. ∂ρ∂t += -im*kᵢ*ρuᵢh + end + + return nothing; +end + +# Solving the momentum equation +# ∂pᵢ∂t + ∑ⱼ ∂/∂xⱼ( ρ*uᵢuⱼ + δᵢⱼP_tot - bᵢbⱼ - 2νρSᵢⱼ)) = ρFᵢ +function UᵢUpdate!(N, sol, t, clock, vars, params, grid; direction = "x") + ν = params.ν + cₛ = params.cₛ + k₁,k₂,k₃ = grid.kr,grid.l,grid.m + u₁h,u₂h,u₃h = vars.uxh,vars.uyh,vars.uzh + if direction == "x" + # i = {1,2,3} -> {x,y,z} direction + a = 1 + kᵢ = grid.kr + uᵢ = vars.ux + uᵢh = vars.uxh + ∂pᵢh∂t = @view N[:,:,:,params.ux_ind] + elseif direction == "y" + a = 2; + kᵢ = grid.l + uᵢ = vars.uy + uᵢh = vars.uyh + ∂pᵢh∂t = @view N[:,:,:,params.uy_ind] + elseif direction == "z" + a = 3 + kᵢ = grid.m + uᵢ = vars.uz + uᵢh = vars.uzh + ∂pᵢh∂t = @view N[:,:,:,params.uz_ind] + end + + @. ∂pᵢh∂t*=0 + ρ = vars.ρ + #momentum and magnetic field part + ρuᵢuⱼ = vars.nonlin1 + ρuᵢuⱼh = vars.nonlinh1 + + for (uⱼ,kⱼ) ∈ zip((vars.ux,vars.uy,vars.uz),(grid.kr,grid.l,grid.m)) + # pseudo part + @. ρuᵢuⱼ = ρ*uᵢ*uⱼ + # spectral part + mul!(ρuᵢuⱼh, grid.rfftplan, ρuᵢuⱼ) + @. ∂pᵢh∂t -= im*kⱼ*ρuᵢuⱼh + end + + # pressure part + P_tot = vars.nonlin1 + P_toth = vars.nonlinh1 + @. P_tot= ρ*cₛ^2 + mul!(P_toth, grid.rfftplan, P_tot) + @. ∂pᵢh∂t -= im*kᵢ*P_toth + + # viscosity part + Sᵢⱼ ,ρSᵢⱼ = vars.nonlin1 ,vars.nonlin2 + Sᵢⱼh,ρSᵢⱼh = vars.nonlinh1,vars.nonlinh2 + for (uⱼh,kⱼ,j) ∈ zip((vars.uxh,vars.uyh,vars.uzh),(grid.kr,grid.l,grid.m),(1,2,3)) + if a == j + @. Sᵢⱼh += im*(kᵢ*uᵢh - (k₁*u₁h + k₂*u₂h + k₃*u₃h)*0.3333333333) + else + @. Sᵢⱼh += 0.5*im*(kᵢ*uⱼh + kⱼ*uᵢh) + end + ldiv!(Sᵢⱼ, grid.rfftplan, Sᵢⱼh) + @. ρSᵢⱼ = ρ*Sᵢⱼ + mul!(ρSᵢⱼh, grid.rfftplan, ρSᵢⱼ) + @. ∂pᵢh∂t += im*kⱼ*2*ν*ρSᵢⱼh + end + + return nothing; +end + +function HDcalcN_advection!(N, sol, t, clock, vars, params, grid) + + #Update ρ + P + V + B Real Conponment + @timeit_debug params.debugTimer "FFT Update" CUDA.@sync begin + ldiv!(vars.ρ , grid.rfftplan, deepcopy(@view sol[:, :, :, params.ρ_ind ])) + ldiv!(vars.ux, grid.rfftplan, deepcopy(@view sol[:, :, :, params.ux_ind])) + ldiv!(vars.uy, grid.rfftplan, deepcopy(@view sol[:, :, :, params.uy_ind])) + ldiv!(vars.uz, grid.rfftplan, deepcopy(@view sol[:, :, :, params.uz_ind])) + #Update momentum back to velocity + @. vars.ux/=vars.ρ + @. vars.uy/=vars.ρ + @. vars.uz/=vars.ρ + + #Copy the spectral conponment to sketch array + mul!(vars.uxh, grid.rfftplan, vars.ux) + mul!(vars.uyh, grid.rfftplan, vars.uy) + mul!(vars.uzh, grid.rfftplan, vars.uz) + end + + #Update continuity equation + @timeit_debug params.debugTimer "ρ Update" CUDA.@sync begin + ρUpdate!(N, sol, t, clock, vars, params, grid) + end + + #Update V Advection + @timeit_debug params.debugTimer "UᵢUpdate" CUDA.@sync begin + UᵢUpdate!(N, sol, t, clock, vars, params, grid; direction="x") + UᵢUpdate!(N, sol, t, clock, vars, params, grid; direction="y") + UᵢUpdate!(N, sol, t, clock, vars, params, grid; direction="z") + end + return nothing; +end + +end \ No newline at end of file diff --git a/src/Solver/HDSolver_VP.jl b/src/Solver/HDSolver_VP.jl deleted file mode 100644 index 55b3e83..0000000 --- a/src/Solver/HDSolver_VP.jl +++ /dev/null @@ -1,127 +0,0 @@ -module HDSolver_VP -# ---------- -# Navier–Stokes Solver for 3D Hydrodynamics Problem with Volume Penalization Method -# ---------- -export - UᵢUpdate!, - HDcalcN_advection! - -using - CUDA, - Reexport, - DocStringExtensions - -@reexport using FourierFlows - -using LinearAlgebra: mul!, ldiv! -using FourierFlows: parsevalsum - -# δ function -δ(a::Int,b::Int) = ( a == b ? 1 : 0 ); - -function UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x") - - if direction == "x" - - # a = {1,2,3} -> {x,y,z} direction - a = 1; - kₐ = grid.kr; - k⁻² = grid.invKrsq; - U₀ = params.U₀x; - uᵢ = vars.ux; - ∂uᵢh∂t = @view N[:,:,:,params.ux_ind]; - - elseif direction == "y" - - a = 2; - kₐ = grid.l; - k⁻² = grid.invKrsq; - U₀ = params.U₀y; - uᵢ = vars.uy; - ∂uᵢh∂t = @view N[:,:,:,params.uy_ind]; - - elseif direction == "z" - - a = 3; - kₐ = grid.m; - k⁻² = grid.invKrsq; - U₀ = params.U₀z; - uᵢ = vars.uz; - ∂uᵢh∂t = @view N[:,:,:,params.uz_ind]; - - else - - error("Warning : Unknown direction is declerad") - - end - - @. ∂uᵢh∂t*= 0; - - η = clock.dt*13/7; #η condition for AB3 Method - χ = params.χ; - - for (uᵢ,kᵢ) ∈ zip([vars.ux,vars.uy,vars.uz],[grid.kr,grid.l,grid.m]) - for (uⱼ,kⱼ,j) ∈ zip([vars.ux,vars.uy,vars.uz],[grid.kr,grid.l,grid.m],[1, 2, 3]) - - # Initialization - @. vars.nonlin1 *= 0; - uᵢuⱼ = vars.nonlin1; - uᵢuⱼh = vars.nonlinh1; - - # Pre-Calculation in Real Space - @. uᵢuⱼ = uᵢ*uⱼ; - - # Fourier transform - mul!(uᵢuⱼh, grid.rfftplan, uᵢuⱼ); - - # Perform the actual calculation - @. ∂uᵢh∂t += -im*kᵢ*(δ(a,j)-kₐ*kⱼ*k⁻²)*uᵢuⱼh; - - end - end - - for (uⱼ,Uⱼ,kⱼ,j) ∈ zip([vars.ux,vars.uy,vars.uz],[params.U₀x,params.U₀y,params.U₀z],[grid.kr,grid.l,grid.m],[1, 2, 3]) - - #The Volume Penalization term, Assuming U_wall = Uⱼ , j ∈ [x,y,z] direction - @. vars.nonlin1 *= 0; - @. vars.nonlinh1 *= 0; - χUᵢ_η = vars.nonlin1; - χUᵢ_ηh = vars.nonlinh1; - @. χUᵢ_η = χ/η*(uⱼ - Uⱼ); - mul!(χUᵢ_ηh, grid.rfftplan, χUᵢ_η); - - # Perform the Actual Advection update - @. ∂uᵢh∂t += -(δ(a,j)-kₐ*kⱼ*k⁻²)*χUᵢ_ηh; - end - - #Compute the diffusion term - νk^2 u_i - uᵢ = direction == "x" ? vars.ux : direction == "y" ? vars.uy : vars.uz; - uᵢh = vars.nonlinh1; - mul!(uᵢh, grid.rfftplan, uᵢ); - @. ∂uᵢh∂t += -grid.Krsq*params.ν*uᵢh; - - # hyperdiffusion term - if params.nν > 1 - @. ∂uᵢh∂t += -grid.Krsq^params.nν*params.ν*uᵢh; - end - - return nothing - -end - -function HDcalcN_advection!(N, sol, t, clock, vars, params, grid) - - #Update V Real Conponment - ldiv!(vars.ux, grid.rfftplan, deepcopy(@view sol[:, :, :, params.ux_ind])) - ldiv!(vars.uy, grid.rfftplan, deepcopy(@view sol[:, :, :, params.uy_ind])) - ldiv!(vars.uz, grid.rfftplan, deepcopy(@view sol[:, :, :, params.uz_ind])) - - #Update V Advection - UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x") - UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="y") - UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="z") - - return nothing -end - -end \ No newline at end of file diff --git a/src/Solver/MHDSolver.jl b/src/Solver/MHDSolver.jl index 3914026..0249cf8 100644 --- a/src/Solver/MHDSolver.jl +++ b/src/Solver/MHDSolver.jl @@ -9,82 +9,96 @@ export MHDcalcN_advection!, MHDupdatevars! - using CUDA, - Reexport, - DocStringExtensions - -@reexport using FourierFlows + TimerOutputs using LinearAlgebra: mul!, ldiv! -using FourierFlows: parsevalsum +include("VPSolver.jl") +# δ notation +δ(a::Int,b::Int) = ( a == b ? 1 : 0 ) +# ϵ notation +ϵ(i::Int,j::Int,k::Int) = (i - j)*(j - k)*(k - i)/2 -# δ function -δ(a::Int,b::Int) = ( a == b ? 1 : 0 ); +# checking function of VP method +VP_is_turned_on(params) = hasproperty(params,:U₀x); -function UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x") +function UᵢUpdate!(N, sol, t, clock, vars, params, grid; direction="x") if direction == "x" # a = {1,2,3} -> {x,y,z} direction - a = 1; - kₐ = grid.kr; - k⁻² = grid.invKrsq; - ∂uᵢh∂t = @view N[:,:,:,params.ux_ind]; + a = 1 + kₐ = grid.kr + k⁻² = grid.invKrsq + ∂uᵢh∂t = @view N[:,:,:,params.ux_ind] elseif direction == "y" - a = 2; - kₐ = grid.l; - k⁻² = grid.invKrsq; - ∂uᵢh∂t = @view N[:,:,:,params.uy_ind]; + a = 2 + kₐ = grid.l + k⁻² = grid.invKrsq + ∂uᵢh∂t = @view N[:,:,:,params.uy_ind] elseif direction == "z" - a = 3; - kₐ = grid.m; - k⁻² = grid.invKrsq; - ∂uᵢh∂t = @view N[:,:,:,params.uz_ind]; + a = 3 + kₐ = grid.m + k⁻² = grid.invKrsq + ∂uᵢh∂t = @view N[:,:,:,params.uz_ind] else error("Warning : Unknown direction is declerad") end - + #idea : we are computing ∂uᵢh∂t = im*kᵢ*(δₐⱼ - kₐkⱼk⁻²)*(bᵢbⱼ - uᵢuⱼh) + # as uᵢuⱼ = uⱼuᵢ in our case + # 1 2 3 + # 1 11 12 13 + # 2 21 22 23 , part of computation is repeated, 11(1),12(2),13(2),22(1),23(2),33(1) + # 3 31 32 33 + # Their only difference for u_ij is the advection part @. ∂uᵢh∂t*= 0; + for (bᵢ,uᵢ,kᵢ,i) ∈ zip((vars.bx,vars.by,vars.bz),(vars.ux,vars.uy,vars.uz),(grid.kr,grid.l,grid.m),(1,2,3)) + for (bⱼ,uⱼ,kⱼ,j) ∈ zip((vars.bx,vars.by,vars.bz),(vars.ux,vars.uy,vars.uz),(grid.kr,grid.l,grid.m),(1, 2, 3)) + if j >= i + # Initialization + @. vars.nonlin1 *= 0 + @. vars.nonlinh1 *= 0 + bᵢbⱼ_minus_uᵢuⱼ = vars.nonlin1 + bᵢbⱼ_minus_uᵢuⱼh = vars.nonlinh1 + + # Perform Computation in Real space + @. bᵢbⱼ_minus_uᵢuⱼ = bᵢ*bⱼ - uᵢ*uⱼ + mul!(bᵢbⱼ_minus_uᵢuⱼh, grid.rfftplan, bᵢbⱼ_minus_uᵢuⱼ) - for (bᵢ,uᵢ,kᵢ) ∈ zip([vars.bx,vars.by,vars.bz],[vars.ux,vars.uy,vars.uz],[grid.kr,grid.l,grid.m]) - for (bⱼ,uⱼ,kⱼ,j) ∈ zip([vars.bx,vars.by,vars.bz],[vars.ux,vars.uy,vars.uz],[grid.kr,grid.l,grid.m],[1, 2, 3]) - - # Initialization - @. vars.nonlin1 *= 0; - @. vars.nonlinh1 *= 0; - bᵢbⱼ_minus_uᵢuⱼ = vars.nonlin1; - bᵢbⱼ_minus_uᵢuⱼh = vars.nonlinh1; - # Perform Computation in Real space - @. bᵢbⱼ_minus_uᵢuⱼ = bᵢ*bⱼ - uᵢ*uⱼ; - mul!(bᵢbⱼ_minus_uᵢuⱼh, grid.rfftplan, bᵢbⱼ_minus_uᵢuⱼ); - - # Perform the Actual Advection update - @. ∂uᵢh∂t += im*kᵢ*(δ(a,j)-kₐ*kⱼ*k⁻²)*bᵢbⱼ_minus_uᵢuⱼh; - + # Perform the Actual Advection update + @. ∂uᵢh∂t += im*kᵢ*(δ(a,j)-kₐ*kⱼ*k⁻²)*bᵢbⱼ_minus_uᵢuⱼh + if i != j # repeat the calculation for u_ij + @. ∂uᵢh∂t += im*kⱼ*(δ(a,i)-kₐ*kᵢ*k⁻²)*bᵢbⱼ_minus_uᵢuⱼh end + end end - - #Compute the diffusion term - νk^2 u_i - uᵢ = direction == "x" ? vars.ux : direction == "y" ? vars.uy : vars.uz; - uᵢh = vars.nonlinh1; - mul!(uᵢh, grid.rfftplan, uᵢ); - @. ∂uᵢh∂t += -grid.Krsq*params.ν*uᵢh; - - # hyperdiffusion term - if params.nν > 1 - @. ∂uᵢh∂t += -grid.Krsq^params.nν*params.ν*uᵢh; - end + end - return nothing + # Updating the solid domain if VP flag is ON + if VP_is_turned_on(params) + VPSolver.VP_UᵢUpdate!(∂uᵢh∂t, kₐ.*k⁻², a, clock, vars, params, grid) + end + + #Compute the diffusion term - νk^2 u_i + uᵢ = direction == "x" ? vars.ux : direction == "y" ? vars.uy : vars.uz; + uᵢh = vars.nonlinh1 + mul!(uᵢh, grid.rfftplan, uᵢ) + @. ∂uᵢh∂t += -grid.Krsq*params.ν*uᵢh + + # hyperdiffusion term + if params.nν > 1 + @. ∂uᵢh∂t += -grid.Krsq^params.nν*params.ν*uᵢh + end + + return nothing end @@ -97,19 +111,25 @@ function BᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x") # declare the var u_i, b_i for computation if direction == "x" - + a = 1; + kₐ = grid.kr; + k⁻² = grid.invKrsq; uᵢ = vars.ux; bᵢ = vars.bx; ∂Bᵢh∂t = @view N[:,:,:,params.bx_ind]; elseif direction == "y" - + a = 2; + kₐ = grid.l; + k⁻² = grid.invKrsq; uᵢ = vars.uy; bᵢ = vars.by; ∂Bᵢh∂t = @view N[:,:,:,params.by_ind]; elseif direction == "z" - + a = 3; + kₐ = grid.m; + k⁻² = grid.invKrsq; uᵢ = vars.uz; bᵢ = vars.bz; ∂Bᵢh∂t = @view N[:,:,:,params.bz_ind]; @@ -120,38 +140,193 @@ function BᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x") end - @. ∂Bᵢh∂t*= 0; - - #Compute the first term, im ∑_j k_j*(b_iu_j - u_ib_j) - for (bⱼ,uⱼ,kⱼ) ∈ zip([vars.bx,vars.by,vars.bz],[vars.ux,vars.uy,vars.uz],[grid.kr,grid.l,grid.m]) - - # Initialization - @. vars.nonlin1 *= 0; - @. vars.nonlinh1 *= 0; - uᵢbⱼ_minus_bᵢuⱼ = vars.nonlin1; - uᵢbⱼ_minus_bᵢuⱼh = vars.nonlinh1; - # Perform Computation in Real space - @. uᵢbⱼ_minus_bᵢuⱼ = uᵢ*bⱼ - bᵢ*uⱼ; - mul!(uᵢbⱼ_minus_bᵢuⱼh, grid.rfftplan, uᵢbⱼ_minus_bᵢuⱼ); - # Perform the Actual Advection update - @. ∂Bᵢh∂t += im*kⱼ*uᵢbⱼ_minus_bᵢuⱼh; + @. ∂Bᵢh∂t*= 0; + uᵢbⱼ_minus_bᵢuⱼ = vars.nonlin1; + uᵢbⱼ_minus_bᵢuⱼh = vars.nonlinh1; + #Compute the first term, im ∑_j k_j*(b_iu_j - u_ib_j) + for (bⱼ,uⱼ,kⱼ,j) ∈ zip((vars.bx,vars.by,vars.bz),(vars.ux,vars.uy,vars.uz),(grid.kr,grid.l,grid.m),(1,2,3)) + if a != j + # Perform Computation in Real space + @. uᵢbⱼ_minus_bᵢuⱼ = uᵢ*bⱼ - bᵢ*uⱼ; + + mul!(uᵢbⱼ_minus_bᵢuⱼh, grid.rfftplan, uᵢbⱼ_minus_bᵢuⱼ); + + # Perform the Actual Advection update + @. ∂Bᵢh∂t += im*kⱼ*uᵢbⱼ_minus_bᵢuⱼh; end - - #Compute the diffusion term - ηk^2 B_i - bᵢh = vars.nonlinh1; - mul!(bᵢh, grid.rfftplan, bᵢ); - @. ∂Bᵢh∂t += -grid.Krsq*params.η*bᵢh; - - # hyperdiffusion term - if params.nη > 1 - @. ∂Bᵢh∂t += -grid.Krsq^params.nη*params.η*bᵢh; - end + end + + # Updating the solid domain if VP flag is ON + if VP_is_turned_on(params) + VPSolver.VP_BᵢUpdate!(∂Bᵢh∂t, kₐ.*k⁻², a, clock, vars, params, grid) + end + + #Compute the diffusion term - ηk^2 B_i + bᵢh = vars.nonlinh1; + mul!(bᵢh, grid.rfftplan, bᵢ); + @. ∂Bᵢh∂t += -grid.Krsq*params.η*bᵢh; + + # hyperdiffusion term + if params.nη > 1 + @. ∂Bᵢh∂t += -grid.Krsq^params.nη*params.η*bᵢh; + end return nothing end +# B function for EMHD system +# For E-MHD system, the induction will be changed into +# ∂B/∂t = -dᵢ * ∇× [ (∇× B) × B ] + η ∇²B +# In this function, we will implement the equation and assume dᵢ = 1 +function EMHD_BᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x") + + # To Update B_i, we have to first break down the equation : + # ∂B/∂t = - ∇× [ (∇× B) × B ] + η ∇²B + # Let A = (∇× B). By using vector calculus identities, we have + # ∂B/∂t = - [ (∇ ⋅ B + B ⋅ ∇)A - (∇ ⋅ A + A ⋅ ∇)B ] + η ∇²B + # Using ∇ ⋅ B = 0 and vector calculus identities ∇⋅(∇× B) = 0, we finally get the expression + # ∂B/∂t = - [(B ⋅ ∇)A - (A ⋅ ∇)B ] + η ∇²B = (A ⋅ ∇)B - (B ⋅ ∇)A + η ∇²B + # For any direction i, we will have the following expression in k-space + # 𝔉(∂Bᵢ/∂t) = 𝔉[(Aⱼ∂ⱼ)Bᵢ - Bⱼ∂ⱼAᵢ] - k²𝔉(B) + # To compute the first term in RHS, we break it into three step + # 1. compute real space term ∂ⱼBᵢ using spectral method + # 2. compute Aⱼ∂ⱼBᵢ using pseudo spectral method + # 3. add the answer to 𝔉(∂Bᵢ/∂t) + # + + # declare the var u_i, b_i for computation + if direction == "x" + a = 1 + kₐ = grid.kr + Aᵢ = vars.∇XBᵢ + bᵢ = vars.bx + bᵢh = @view sol[:,:,:,params.bx_ind] + ∂Bᵢh∂t = @view N[:,:,:,params.bx_ind] + + elseif direction == "y" + a = 2 + kₐ = grid.l + Aᵢ = vars.∇XBⱼ + bᵢ = vars.by + bᵢh = @view sol[:,:,:,params.by_ind] + ∂Bᵢh∂t = @view N[:,:,:,params.by_ind] + + elseif direction == "z" + a = 3 + kₐ = grid.m + Aᵢ = vars.∇XBₖ + bᵢ = vars.bz + bᵢh = @view sol[:,:,:,params.bz_ind] + ∂Bᵢh∂t = @view N[:,:,:,params.bz_ind] + else + + @warn "Warning : Unknown direction is declerad" + + end + + A₁ = vars.∇XBᵢ + A₂ = vars.∇XBⱼ + A₃ = vars.∇XBₖ + + # define the sketch array + ∂ⱼAᵢ = ∂ⱼBᵢ = vars.nonlin1 + Bⱼ∂ⱼAᵢ= Aⱼ∂ⱼBᵢ= vars.nonlin1 + Aᵢh = Bᵢh = vars.nonlinh1 + ∂ⱼAᵢh = ∂ⱼBᵢh = vars.nonlinh1 + Bⱼ∂ⱼAᵢh = Aⱼ∂ⱼBᵢh = vars.nonlinh1 + + @. ∂Bᵢh∂t*= 0; + for (bⱼ,Aⱼ,kⱼ) ∈ zip((vars.bx,vars.by,vars.bz),(A₁,A₂,A₃),(grid.kr,grid.l,grid.m)) + + # first step + @. Aᵢh = 0 + mul!(Aᵢh, grid.rfftplan, Aᵢ) + @. ∂ⱼAᵢh = im*kⱼ*Aᵢh + ldiv!(∂ⱼAᵢ, grid.rfftplan, deepcopy(∂ⱼAᵢh)) + # second step + @. Bⱼ∂ⱼAᵢ = bⱼ*∂ⱼAᵢ + @. Bⱼ∂ⱼAᵢh = 0 + mul!(Bⱼ∂ⱼAᵢh, grid.rfftplan, Bⱼ∂ⱼAᵢ) + # final step + @. ∂Bᵢh∂t -= Bⱼ∂ⱼAᵢh + + # first step + @. ∂ⱼBᵢ = 0 + @. ∂ⱼBᵢh = im*kⱼ*bᵢh + ldiv!(∂ⱼBᵢ, grid.rfftplan, deepcopy(∂ⱼBᵢh)) + # second step + @. Aⱼ∂ⱼBᵢ = Aⱼ*∂ⱼBᵢ + @. Aⱼ∂ⱼBᵢh = 0 + mul!(Aⱼ∂ⱼBᵢh, grid.rfftplan, Aⱼ∂ⱼBᵢ) + # final step + @. ∂Bᵢh∂t += Aⱼ∂ⱼBᵢh + + end + + return nothing + +end + +# Compute the ∇XB term +function Get∇XB!(sol, vars, params, grid) + + # ∇XB = im*( k × B )ₖ = im*ϵ_ijk kᵢ Bⱼ + + # define the variables + k₁,k₂,k₃ = grid.kr,grid.l,grid.m; + B₁h = @view sol[:,:,:,params.bx_ind] + B₂h = @view sol[:,:,:,params.by_ind] + B₃h = @view sol[:,:,:,params.bz_ind] + A₁ = vars.∇XBᵢ + A₂ = vars.∇XBⱼ + A₃ = vars.∇XBₖ + + # Way 1 of appling Curl + #=∇XBₖh = vars.nonlinh1 + for (∇XBₖ ,k) ∈ zip((A₁,A₂,A₃),(1,2,3)) + @. ∇XBₖh*=0 + for (Bⱼh,j) ∈ zip((B₁h,B₂h,B₃h),(1,2,3)) + for (kᵢ,i) ∈ zip((k₁,k₂,k₃),(1,2,3)) + if ϵ(i,j,k) != 0 + @. ∇XBₖh += im*ϵ(i,j,k)*kᵢ*Bⱼh + end + end + end + ldiv!(∇XBₖ, grid.rfftplan, deepcopy( ∇XBₖh)) + end=# + + # Way 2 of appling Curl + CBᵢh = vars.nonlinh1 + @. CBᵢh = im*(k₂*B₃h - k₃*B₂h) + ldiv!(A₁, grid.rfftplan, CBᵢh) + + @. CBᵢh = im*(k₃*B₁h - k₁*B₃h) + ldiv!(A₂, grid.rfftplan, CBᵢh) + + @. CBᵢh = im*(k₁*B₂h - k₂*B₁h) + ldiv!(A₃, grid.rfftplan, CBᵢh) + + return nothing +end + +function EMHDcalcN_advection!(N, sol, t, clock, vars, params, grid) + + #Update B Advection + Get∇XB!(sol, vars, params, grid) + EMHD_BᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x") + EMHD_BᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="y") + EMHD_BᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="z") + + #Update B Real Conponment + ldiv!(vars.bx, grid.rfftplan, deepcopy(@view sol[:, :, :, params.bx_ind])) + ldiv!(vars.by, grid.rfftplan, deepcopy(@view sol[:, :, :, params.by_ind])) + ldiv!(vars.bz, grid.rfftplan, deepcopy(@view sol[:, :, :, params.bz_ind])) + + return nothing +end + function MHDcalcN_advection!(N, sol, t, clock, vars, params, grid) #Update V + B Real Conponment @@ -161,17 +336,17 @@ function MHDcalcN_advection!(N, sol, t, clock, vars, params, grid) ldiv!(vars.bx, grid.rfftplan, deepcopy(@view sol[:, :, :, params.bx_ind])); ldiv!(vars.by, grid.rfftplan, deepcopy(@view sol[:, :, :, params.by_ind])); ldiv!(vars.bz, grid.rfftplan, deepcopy(@view sol[:, :, :, params.bz_ind])); - + #Update V Advection UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x"); UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="y"); UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="z"); - + #Update B Advection BᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x"); BᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="y"); BᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="z"); - + return nothing end diff --git a/src/Solver/MHDSolver_Compessible.jl b/src/Solver/MHDSolver_Compessible.jl new file mode 100644 index 0000000..7c5729a --- /dev/null +++ b/src/Solver/MHDSolver_Compessible.jl @@ -0,0 +1,138 @@ +module MHDSolver_compressible +# ---------- +# Compessible Navier–Stokes Solver for 3D Magnetohydrodynamics Problem +# ---------- + +export MHDcalcN_advection! + +using + CUDA, + TimerOutputs + +include("MHDSolver.jl"); +include("HDSolver_Compessible.jl") +ρUpdate! = HDSolver_compressible.ρUpdate! +BᵢUpdate! = MHDSolver.BᵢUpdate! + +using LinearAlgebra: mul!, ldiv! + +# Definition of physical parameter between real space and spectral sapce +# fft - space parameters -> ρ px py pz bx by bz +# real - space parameters -> ρ ux uy uz bx by bz + +# Solving the momentum equation +# ∂pᵢ∂t + ∑ⱼ ∂/∂xⱼ( ρ*uᵢuⱼ + δᵢⱼP_tot - bᵢbⱼ - 2νρSᵢⱼ)) = ρFᵢ +function UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction = "x") + ν = params.ν + cₛ = params.cₛ + k₁,k₂,k₃ = grid.kr,grid.l,grid.m + u₁h,u₂h,u₃h = vars.uxh,vars.uyh,vars.uzh + if direction == "x" + # i = {1,2,3} -> {x,y,z} direction + a = 1 + kᵢ = grid.kr + uᵢ = vars.ux + uᵢh = vars.uxh + bᵢ = vars.bx + ∂pᵢh∂t = @view N[:,:,:,params.ux_ind] + elseif direction == "y" + a = 2 + kᵢ = grid.l + uᵢ = vars.uy + uᵢh = vars.uyh + bᵢ = vars.by + ∂pᵢh∂t = @view N[:,:,:,params.uy_ind] + elseif direction == "z" + a = 3 + kᵢ = grid.m + uᵢ = vars.uz + uᵢh = vars.uzh + bᵢ = vars.bz + ∂pᵢh∂t = @view N[:,:,:,params.uz_ind] + end + + @. ∂pᵢh∂t*=0 + ρ = vars.ρ + #momentum and magnetic field part + bᵢbⱼ_minus_ρuᵢuⱼ = vars.nonlin1 + bᵢbⱼ_minus_ρuᵢuⱼh = vars.nonlinh1 + for (uⱼ,bⱼ,kⱼ) ∈ zip((vars.ux,vars.uy,vars.uz),(vars.bx,vars.by,vars.bz),(grid.kr,grid.l,grid.m)) + # pseudo part + @. bᵢbⱼ_minus_ρuᵢuⱼ = bᵢ*bⱼ - ρ*uᵢ*uⱼ + # spectral part + mul!(bᵢbⱼ_minus_ρuᵢuⱼh, grid.rfftplan, bᵢbⱼ_minus_ρuᵢuⱼ) + @. ∂pᵢh∂t += im*kⱼ*bᵢbⱼ_minus_ρuᵢuⱼh + end + + # pressure part + P_tot = vars.nonlin1 + P_toth = vars.nonlinh1 + @. P_tot= ρ*cₛ^2 + vars.bx^2 + vars.by^2 + vars.bz^2 + mul!(P_toth, grid.rfftplan, P_tot) + @. ∂pᵢh∂t -= im*kᵢ*P_toth + + # viscosity part + Sᵢⱼ ,ρSᵢⱼ = vars.nonlin1 ,vars.nonlin2 + Sᵢⱼh,ρSᵢⱼh = vars.nonlinh1,vars.nonlinh2 + for (uⱼh,kⱼ,j) ∈ zip((vars.uxh,vars.uyh,vars.uzh),(grid.kr,grid.l,grid.m),(1,2,3)) + if a == j + @. Sᵢⱼh += im*(kᵢ*uᵢh - (k₁*u₁h + k₂*u₂h + k₃*u₃h)*0.3333333333) + else + @. Sᵢⱼh += 0.5*im*(kᵢ*uⱼh + kⱼ*uᵢh) + end + ldiv!(Sᵢⱼ, grid.rfftplan, Sᵢⱼh) + @. ρSᵢⱼ = ρ*Sᵢⱼ + mul!(ρSᵢⱼh, grid.rfftplan, ρSᵢⱼ) + @. ∂pᵢh∂t += im*kⱼ*2*ν*ρSᵢⱼh + end + + return nothing; +end + +function MHDcalcN_advection!(N, sol, t, clock, vars, params, grid) + + + @timeit_debug params.debugTimer "FFT Update" CUDA.@sync begin + #Update ρ + P + V + B Real Conponment + ldiv!(vars.ρ , grid.rfftplan, deepcopy(@view sol[:, :, :, params.ρ_ind ])) + ldiv!(vars.ux, grid.rfftplan, deepcopy(@view sol[:, :, :, params.ux_ind])) + ldiv!(vars.uy, grid.rfftplan, deepcopy(@view sol[:, :, :, params.uy_ind])) + ldiv!(vars.uz, grid.rfftplan, deepcopy(@view sol[:, :, :, params.uz_ind])) + ldiv!(vars.bx, grid.rfftplan, deepcopy(@view sol[:, :, :, params.bx_ind])) + ldiv!(vars.by, grid.rfftplan, deepcopy(@view sol[:, :, :, params.by_ind])) + ldiv!(vars.bz, grid.rfftplan, deepcopy(@view sol[:, :, :, params.bz_ind])) + + #Update momentum back to velocity + @. vars.ux/=vars.ρ + @. vars.uy/=vars.ρ + @. vars.uz/=vars.ρ + + + #Copy the spectral conponment to sketch array + mul!(vars.uxh, grid.rfftplan, vars.ux) + mul!(vars.uyh, grid.rfftplan, vars.uy) + mul!(vars.uzh, grid.rfftplan, vars.uz) + end + + #Update continuity equation + @timeit_debug params.debugTimer "ρ Update" CUDA.@sync begin + ρUpdate!(N, sol, t, clock, vars, params, grid) + end + + #Update V Advection + + @timeit_debug params.debugTimer "UᵢUpdate" CUDA.@sync begin + UᵢUpdate!(N, sol, t, clock, vars, params, grid; direction="x") + UᵢUpdate!(N, sol, t, clock, vars, params, grid; direction="y") + UᵢUpdate!(N, sol, t, clock, vars, params, grid; direction="z") + end + #Update B Advection + @timeit_debug params.debugTimer "BᵢUpdate" CUDA.@sync begin + BᵢUpdate!(N, sol, t, clock, vars, params, grid; direction="x") + BᵢUpdate!(N, sol, t, clock, vars, params, grid; direction="y") + BᵢUpdate!(N, sol, t, clock, vars, params, grid; direction="z") + end + return nothing +end + +end \ No newline at end of file diff --git a/src/Solver/MHDSolver_VP.jl b/src/Solver/MHDSolver_VP.jl deleted file mode 100644 index d409f0c..0000000 --- a/src/Solver/MHDSolver_VP.jl +++ /dev/null @@ -1,303 +0,0 @@ -module MHDSolver_VP -# ---------- -# Navier–Stokes Solver for 3D Magnetohydrodynamics Problem with Volume Penalization Method -# ---------- -export - UᵢUpdate!, - BᵢUpdate!, - MHDcalcN_advection!, - DivBCorrection!, - DivVCorrection! - -using - CUDA, - Reexport, - DocStringExtensions - -@reexport using FourierFlows - -using LinearAlgebra: mul!, ldiv! -using FourierFlows: parsevalsum - -# δ function -δ(a::Int,b::Int) = ( a == b ? 1 : 0 ); - -function UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x") - - T = eltype(grid); - - if direction == "x" - - # a = {1,2,3} -> {x,y,z} direction - a = 1; - kₐ = grid.kr; - k⁻² = grid.invKrsq; - U₀ = params.U₀x; - uᵢ = vars.ux; - ∂uᵢh∂t = @view N[:,:,:,params.ux_ind]; - - elseif direction == "y" - - a = 2; - kₐ = grid.l; - k⁻² = grid.invKrsq; - U₀ = params.U₀y; - uᵢ = vars.uy; - ∂uᵢh∂t = @view N[:,:,:,params.uy_ind]; - - elseif direction == "z" - - a = 3; - kₐ = grid.m; - k⁻² = grid.invKrsq; - U₀ = params.U₀z; - uᵢ = vars.uz; - ∂uᵢh∂t = @view N[:,:,:,params.uz_ind]; - - else - - error("Warning : Unknown direction is declerad") - - end - - @. ∂uᵢh∂t*= 0; - - η = clock.dt*13/7; #η condition for AB3 Method - χ = params.χ; - for (bᵢ,uᵢ,kᵢ) ∈ zip([vars.bx,vars.by,vars.bz],[vars.ux,vars.uy,vars.uz],[grid.kr,grid.l,grid.m]) - for (bⱼ,uⱼ,kⱼ,j) ∈ zip([vars.bx,vars.by,vars.bz],[vars.ux,vars.uy,vars.uz],[grid.kr,grid.l,grid.m],[1, 2, 3]) - - @. vars.nonlin1 *= 0; - @. vars.nonlinh1 *= 0; - bᵢbⱼ_minus_uᵢuⱼ = vars.nonlin1; - bᵢbⱼ_minus_uᵢuⱼh = vars.nonlinh1; - @. bᵢbⱼ_minus_uᵢuⱼ = bᵢ*bⱼ - uᵢ*uⱼ; - mul!(bᵢbⱼ_minus_uᵢuⱼh, grid.rfftplan, bᵢbⱼ_minus_uᵢuⱼ); - - # Perform the Actual Advection update - @. ∂uᵢh∂t += im*kᵢ*(δ(a,j)-kₐ*kⱼ*k⁻²)*bᵢbⱼ_minus_uᵢuⱼh; - - end - end - - for (uⱼ,Uⱼ,kⱼ,j) ∈ zip([vars.ux,vars.uy,vars.uz],[params.U₀x,params.U₀y,params.U₀z],[grid.kr,grid.l,grid.m],[1, 2, 3]) - - #The Volume Penalization term, Assuming U_wall = Uⱼ , j ∈ [x,y,z] direction - @. vars.nonlin1 *= 0; - @. vars.nonlinh1 *= 0; - χUᵢ_η = vars.nonlin1; - χUᵢ_ηh = vars.nonlinh1; - @. χUᵢ_η = χ/η*(uⱼ - Uⱼ); - mul!(χUᵢ_ηh, grid.rfftplan, χUᵢ_η); - - # Perform the Actual Advection update - @. ∂uᵢh∂t += -(δ(a,j)-kₐ*kⱼ*k⁻²)*χUᵢ_ηh; - end - - #Compute the diffusion term - νk^2 u_i - uᵢ = direction == "x" ? vars.ux : direction == "y" ? vars.uy : vars.uz; - uᵢh = vars.nonlinh1; - mul!(uᵢh, grid.rfftplan, uᵢ); - @. ∂uᵢh∂t += -grid.Krsq*params.ν*uᵢh; - - # hyperdiffusion term - if params.nν > 1 - @. ∂uᵢh∂t += -grid.Krsq^params.nν*params.ν*uᵢh; - end - - return nothing - -end - -function BᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x") - - #To Update B_i, we have two terms to compute: - # ∂B_i/∂t = im ∑_j k_j*(b_iu_j - u_ib_j) - η k^2 B_i - #We split it into two part for sparating the computation. - - # declare the var u_i, b_i for computation - if direction == "x" - a = 1; - kₐ = grid.kr; - k⁻² = grid.invKrsq; - B₀ = params.B₀x; - uᵢ = vars.ux; - bᵢ = vars.bx; - ∂Bᵢh∂t = @view N[:,:,:,params.bx_ind]; - - elseif direction == "y" - a = 2; - kₐ = grid.l; - k⁻² = grid.invKrsq; - B₀ = params.B₀y; - uᵢ = vars.uy; - bᵢ = vars.by; - ∂Bᵢh∂t = @view N[:,:,:,params.by_ind]; - - elseif direction == "z" - a = 3; - kₐ = grid.m; - k⁻² = grid.invKrsq; - B₀ = params.B₀z; - uᵢ = vars.uz; - bᵢ = vars.bz; - ∂Bᵢh∂t = @view N[:,:,:,params.bz_ind]; - - else - - @warn "Warning : Unknown direction is declerad" - - end - - @. ∂Bᵢh∂t*= 0; - - η = clock.dt*13/7; #η condition for AB3 Method - χ = params.χ; - - #Compute the first term, im ∑_j k_j*(b_iu_j - u_ib_j) - for (bⱼ,uⱼ,kⱼ) ∈ zip([vars.bx,vars.by,vars.bz],[vars.ux,vars.uy,vars.uz],[grid.kr,grid.l,grid.m]) - - # Initialization - @. vars.nonlin1 *= 0; - @. vars.nonlinh1 *= 0; - uᵢbⱼ_minus_bᵢuⱼ = vars.nonlin1; - uᵢbⱼ_minus_bᵢuⱼh = vars.nonlinh1; - # Perform Computation in Real space - @. uᵢbⱼ_minus_bᵢuⱼ = uᵢ*bⱼ - bᵢ*uⱼ; - mul!(uᵢbⱼ_minus_bᵢuⱼh, grid.rfftplan, uᵢbⱼ_minus_bᵢuⱼ); - # Perform the Actual Advection update - @. ∂Bᵢh∂t += im*kⱼ*uᵢbⱼ_minus_bᵢuⱼh; - - end - - for (bⱼ,Bⱼ,kⱼ,j) ∈ zip([vars.bx,vars.by,vars.bz],[params.B₀x,params.B₀y,params.B₀z],[grid.kr,grid.l,grid.m],[1, 2, 3]) - #The Volume Penalization term, Assuming B_wall = Bⱼ, j ∈ [x,y,z] direction - @. vars.nonlin1 *= 0; - @. vars.nonlinh1 *= 0; - χbᵢ_η = vars.nonlin1; - χbᵢ_ηh = vars.nonlinh1; - @. χbᵢ_η = χ/η*(bⱼ - Bⱼ); - mul!(χbᵢ_ηh, grid.rfftplan, χbᵢ_η); - - # Perform the Actual Advection update - @. ∂Bᵢh∂t += -(δ(a,j)-kₐ*kⱼ*k⁻²)*χbᵢ_ηh; - end - - #Compute the diffusion term - ηk^2 B_i - bᵢh = vars.nonlinh1; - mul!(bᵢh, grid.rfftplan, bᵢ); - @. ∂Bᵢh∂t += -grid.Krsq*params.η*bᵢh; - - # hyperdiffusion term - if params.nη > 1 - @. ∂Bᵢh∂t += -grid.Krsq^params.nη*params.η*bᵢh; - end - - return nothing - -end - -function MHDcalcN_advection!(N, sol, t, clock, vars, params, grid) - - #Update V + B Real Conponment - ldiv!(vars.ux, grid.rfftplan, deepcopy(@view sol[:, :, :, params.ux_ind])); - ldiv!(vars.uy, grid.rfftplan, deepcopy(@view sol[:, :, :, params.uy_ind])); - ldiv!(vars.uz, grid.rfftplan, deepcopy(@view sol[:, :, :, params.uz_ind])); - ldiv!(vars.bx, grid.rfftplan, deepcopy(@view sol[:, :, :, params.bx_ind])); - ldiv!(vars.by, grid.rfftplan, deepcopy(@view sol[:, :, :, params.by_ind])); - ldiv!(vars.bz, grid.rfftplan, deepcopy(@view sol[:, :, :, params.bz_ind])); - - #Update V Advection - UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x"); - UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="y"); - UᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="z"); - - #Update B Advection - BᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x"); - BᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="y"); - BᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="z"); - - return nothing -end - -function DivBCorrection!(prob) -#= - Possion Solver for periodic boundary condition - As in VP method, ∇ ⋅ B = 0 doesn't hold, B_{t+1} = ∇×Ψ + ∇Φ -> ∇ ⋅ B = ∇² Φ - We need to find Φ and remove it using a Poission Solver - Here we are using the Fourier Method to find the Φ - In Real Space, - ∇² Φ = ∇ ⋅ B - In k-Space, - ∑ᵢ -(kᵢ)² Φₖ = i∑ᵢ kᵢ(Bₖ)ᵢ - Φ = F{ i∑ᵢ kᵢ (Bₖ)ᵢ / ∑ᵢ (k²)ᵢ} -=# - - vars = prob.vars; - grid = prob.grid; - params = prob.params; - #find Φₖ - kᵢ,kⱼ,kₖ = grid.kr,grid.l,grid.m; - k⁻² = grid.invKrsq; - @. vars.nonlin1 *= 0; - @. vars.nonlinh1 *= 0; - ∑ᵢkᵢBᵢh_k² = vars.nonlinh1; - ∑ᵢkᵢBᵢ_k² = vars.nonlin1; - bxh = prob.sol[:, :, :, params.bx_ind]; - byh = prob.sol[:, :, :, params.by_ind]; - bzh = prob.sol[:, :, :, params.bz_ind]; - ∑ᵢkᵢBᵢh_k² = @. -im*(kᵢ*bxh + kⱼ*byh + kₖ*bzh); - ∑ᵢkᵢBᵢh_k² = @. ∑ᵢkᵢBᵢh_k²*k⁻²; # Φₖ - - # B = B* - ∇Φ = Bᵢ - kᵢΦₖ - @. bxh -= kᵢ.*∑ᵢkᵢBᵢh_k²; - @. byh -= kⱼ.*∑ᵢkᵢBᵢh_k²; - @. bzh -= kₖ.*∑ᵢkᵢBᵢh_k²; - - #Update to Real Space vars - ldiv!(vars.bx, grid.rfftplan, deepcopy(bxh));# deepcopy() since inverse real-fft destroys its input - ldiv!(vars.by, grid.rfftplan, deepcopy(byh));# deepcopy() since inverse real-fft destroys its input - ldiv!(vars.bz, grid.rfftplan, deepcopy(bzh));# deepcopy() since inverse real-fft destroys its input -end - -function DivVCorrection!(prob) -#= - Possion Solver for periodic boundary condition - As in VP method, ∇ ⋅ B = 0 doesn't hold, B_{t+1} = ∇×Ψ + ∇Φ -> ∇ ⋅ B = ∇² Φ - We need to find Φ and remove it using a Poission Solver - Here we are using the Fourier Method to find the Φ - In Real Space, - ∇² Φ = ∇ ⋅ B - In k-Space, - ∑ᵢ -(kᵢ)² Φₖ = i∑ᵢ kᵢ(Bₖ)ᵢ - Φ = F{ i∑ᵢ kᵢ (Bₖ)ᵢ / ∑ᵢ (k²)ᵢ} -=# - - vars = prob.vars; - grid = prob.grid; - params = prob.params; - #find Φₖ - kᵢ,kⱼ,kₖ = grid.kr,grid.l,grid.m; - k⁻² = grid.invKrsq; - @. vars.nonlin1 *= 0; - @. vars.nonlinh1 *= 0; - ∑ᵢkᵢUᵢh_k² = vars.nonlinh1; - ∑ᵢkᵢUᵢ_k² = vars.nonlin1; - uxh = prob.sol[:, :, :, params.ux_ind]; - uyh = prob.sol[:, :, :, params.uy_ind]; - uzh = prob.sol[:, :, :, params.uz_ind]; - ∑ᵢkᵢUᵢh_k² = @. -im*(kᵢ*uxh + kⱼ*uyh + kₖ*uzh); - ∑ᵢkᵢUᵢh_k² = @. ∑ᵢkᵢUᵢh_k²*k⁻²; # Φₖ - - # B = B* - ∇Φ = Bᵢ - kᵢΦₖ - uxh .-= kᵢ.*∑ᵢkᵢUᵢh_k²; - uyh .-= kⱼ.*∑ᵢkᵢUᵢh_k²; - uzh .-= kₖ.*∑ᵢkᵢUᵢh_k²; - - #Update to Real Space vars - ldiv!(vars.ux, grid.rfftplan, deepcopy(uxh));# deepcopy() since inverse real-fft destroys its input - ldiv!(vars.uy, grid.rfftplan, deepcopy(uyh));# deepcopy() since inverse real-fft destroys its input - ldiv!(vars.uz, grid.rfftplan, deepcopy(uzh));# deepcopy() since inverse real-fft destroys its input -end - -end \ No newline at end of file diff --git a/src/Solver/ShearingBox.jl b/src/Solver/ShearingBox.jl new file mode 100644 index 0000000..2ee4ed9 --- /dev/null +++ b/src/Solver/ShearingBox.jl @@ -0,0 +1,297 @@ +module Shear +# ---------- +# Shearing Box Module Ref : The Astrophysical Journal, 928:113 (8pp), 2022 Apr +# ---------- + +# +#Note: Haven't finish, check the name vars for the loops. +# + +export + Shearing_coordinate_update!, + Shearing_remapping!, + HD_ShearingAdvection!, + MHD_ShearingAdvection!, + Shearing_dealias! + +using + CUDA + +using LinearAlgebra: mul!, ldiv! + +include("MHDSolver.jl") +include("HDSolver.jl") +include("VPSolver.jl") +HDUᵢUpdate! = HDSolver.UᵢUpdate! +MHDUᵢUpdate! = MHDSolver.UᵢUpdate! +BᵢUpdate! = MHDSolver.BᵢUpdate! + +function Shearing_remapping!(prob) + #Shearing_remapping!(prob.sol, prob.clock, prob.vars, prob.params, prob.grid) + return nothing +end + +function Shearing_coordinate_update!(N, sol, t, clock, vars, params, grid) + q = params.usr_params.q + τΩ = params.usr_params.τΩ + Lx,Ly = grid.Lx,grid.Ly + + #Shear time interval in sub-time-step + dτ = clock.t - t + + kx,ky,kz = grid.kr,grid.l,grid.m + k²,k⁻² = grid.Krsq,grid.invKrsq + ky₀ = params.usr_params.ky₀ + τ = params.usr_params.τ + + # Construct the new shear coordinate + @. ky = ky₀ + q*(τ+dτ)*kx + @. k² = kx^2 + ky^2 + kz^2 + @. k⁻² = 1/k² + @views @. k⁻²[k².== 0] .= 0 + + return nothing +end + +function Shearing_remapping!(sol, clock, vars, params, grid) + t = clock.t + q = params.usr_params.q + τΩ = params.usr_params.τΩ + Lx,Ly = grid.Lx,grid.Ly + + #increase the shear time + params.usr_params.τ += clock.dt + + # correct the shear after every shear period + if params.usr_params.τ >= τΩ && clock.step > 1 + Field_remapping!(sol, clock, vars, params, grid) + params.usr_params.τ = 0 + end + return nothing +end + +function Field_remapping!(sol, clock, vars, params, grid) + T = eltype(grid) + q = params.usr_params.q + τΩ = params.usr_params.τΩ + kx,ky0 = grid.kr, grid.l1D + Lx = grid.Lx + tmp = params.usr_params.tmp + + kymin,kymax = minimum(ky0),maximum(ky0) + + # Set up of CUDA threads & block + threads = ( 32, 8, 1) #(9,9,9) + blocks = ( ceil(Int,size(sol,1)/threads[1]), ceil(Int,size(sol,2)/threads[2]), ceil(Int,size(sol,3)/threads[3])) + Nfield = size(sol,4) + + for n = 1:Nfield + fieldᵢ = (@view sol[:,:,:,n])::CuArray{Complex{T},3} + tmpᵢ = (@view tmp[:,:,:,n])::CuArray{Complex{T},3} + @cuda blocks = blocks threads = threads Field_remapping_CUDA!(tmpᵢ, fieldᵢ, + q, τΩ, kx, ky0, kymin, kymax, Lx) + end + + # Copy the data from tmp array to sol + copyto!(sol,tmp) + @. tmp*=0 + + return nothing +end + +function MHD_ShearingUpdate!(N, sol, t, clock, vars, params, grid) + U₀xh = params.usr_params.U₀xh + U₀yh = params.usr_params.U₀yh + U₀x = params.usr_params.U₀x + U₀y = params.usr_params.U₀y + q = params.usr_params.q + + ux_ind,uy_ind = params.ux_ind,params.uy_ind + bx_ind,by_ind = params.bx_ind,params.by_ind +# exp_terms(iux) = nl(iux) + fux - zi*kxt*p + 2.d0*shear_flg*uy +# exp_terms(iuy) = nl(iuy) + fuy - zi*ky *p - (2.d0 - q)*shear_flg*ux +# exp_terms(iby) = nl(iby) - q*shear_flg*bx + @. N[:,:,:,ux_ind] += -(2 - q)*sol[:,:,:,uy_ind] + @. N[:,:,:,uy_ind] += + 2 *sol[:,:,:,ux_ind] + @. N[:,:,:,bx_ind] += - q *sol[:,:,:,by_ind] + return nothing +end + +function HD_ShearingUpdate!(N, sol, t, clock, vars, params, grid) + U₀xh = params.usr_params.U₀xh + U₀yh = params.usr_params.U₀yh + U₀x = params.usr_params.U₀x + U₀y = params.usr_params.U₀y + q = params.usr_params.q + + ux_ind,uy_ind = params.ux_ind,params.uy_ind +# exp_terms(iux) = nl(iux) + fux - zi*kxt*p + 2.d0*shear_flg*uy +# exp_terms(iuy) = nl(iuy) + fuy - zi*ky *p - (2.d0 - q)*shear_flg*ux + @. N[:,:,:,ux_ind] += -(2 - q)*sol[:,:,:,uy_ind] + @. N[:,:,:,uy_ind] += + 2 *sol[:,:,:,ux_ind] + return nothing +end + +function Field_remapping_CUDA!(tmpᵢ, fieldᵢ, + q, τΩ, kx, ky0, kymin, kymax, Lx) + #define the i,j,k + i = (blockIdx().x - 1) * blockDim().x + threadIdx().x + j = (blockIdx().y - 1) * blockDim().y + threadIdx().y + k = (blockIdx().z - 1) * blockDim().z + threadIdx().z + nx,ny,nz = size(fieldᵢ) + nky = length(ky0) + if k ∈ (1:nz) && j ∈ (1:ny) && i ∈ (1:nx) + dky = floor(q*τΩ*kx[i]) + kynew = ky0[j] + dky + if kymax >= kynew >= kymin + mindky = abs(ky0[1] - kynew) + jnew = 1 + for kk = 2:nky + if mindky > abs(ky0[kk] - kynew) + jnew = kk + mindky = abs(ky0[kk] - kynew) + end + end + tmpᵢ[i,jnew,k] = fieldᵢ[i,j,k] + end + end + return nothing +end + +function MHD_ShearingAdvection!(N, sol, t, clock, vars, params, grid) + DivFreeCorrection!(N, sol, t, clock, vars, params, grid) + #Update V + B Real Conponment + #@timeit_debug params.debugTimer "FFT Update" CUDA.@sync begin + ldiv!(vars.ux, grid.rfftplan, deepcopy(@view sol[:, :, :, params.ux_ind])) + ldiv!(vars.uy, grid.rfftplan, deepcopy(@view sol[:, :, :, params.uy_ind])) + ldiv!(vars.uz, grid.rfftplan, deepcopy(@view sol[:, :, :, params.uz_ind])) + ldiv!(vars.bx, grid.rfftplan, deepcopy(@view sol[:, :, :, params.bx_ind])) + ldiv!(vars.by, grid.rfftplan, deepcopy(@view sol[:, :, :, params.by_ind])) + ldiv!(vars.bz, grid.rfftplan, deepcopy(@view sol[:, :, :, params.bz_ind])) + #end + #Update V Advection + #@timeit_debug params.debugTimer "UᵢUpdate" CUDA.@sync begin + MHDUᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="x") + MHDUᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="y") + MHDUᵢUpdate!(N, sol, t, clock, vars, params, grid;direction="z") + #end + #Update B Advection + #@timeit_debug params.debugTimer "BᵢUpdate" CUDA.@sync begin + BᵢUpdate!(N, sol, t, clock, vars, params, grid; direction="x") + BᵢUpdate!(N, sol, t, clock, vars, params, grid; direction="y") + BᵢUpdate!(N, sol, t, clock, vars, params, grid; direction="z") + #end + + #@timeit_debug params.debugTimer "ShearingUpdate" CUDA.@sync begin + MHD_ShearingUpdate!(N, sol, t, clock, vars, params, grid) + #end + return nothing +end + +function HD_ShearingAdvection!(N, sol, t, clock, vars, params, grid) + DivFreeCorrection!(N, sol, t, clock, vars, params, grid) + #Update V + B Real Conponment + ldiv!(vars.ux, grid.rfftplan, deepcopy(@view sol[:, :, :, params.ux_ind])) + ldiv!(vars.uy, grid.rfftplan, deepcopy(@view sol[:, :, :, params.uy_ind])) + ldiv!(vars.uz, grid.rfftplan, deepcopy(@view sol[:, :, :, params.uz_ind])) + #Update V Advection + HDUᵢUpdate!(N, sol, t, clock, vars, params, grid; direction="x") + HDUᵢUpdate!(N, sol, t, clock, vars, params, grid; direction="y") + HDUᵢUpdate!(N, sol, t, clock, vars, params, grid; direction="z") + + HD_ShearingUpdate!(N, sol, t, clock, vars, params, grid) + return nothing +end + +function Shearing_dealias!(fh, grid) + @assert grid.nkr == size(fh)[1] + # kfilter = 2/3*kmax + aliased_fraction = grid.aliased_fraction + kfilter = ((1-aliased_fraction)*grid.nl)^2 + #@views @. fh[grid.Krsq.>=kfilter,:,:,:] = 0 + + # Set up of CUDA threads & block + threads = ( 32, 8, 1) + blocks = ( ceil(Int,size(fh,1)/threads[1]), ceil(Int,size(fh,2)/threads[2]), ceil(Int,size(fh,3)/threads[3])) + Nfield = size(fh,4) + + for n = 1:Nfield + fhᵢ = (@view fh[:,:,:,n]) + @cuda blocks = blocks threads = threads Shearing_dealias_CUDA!(fhᵢ, grid.Krsq, kfilter) + end + return nothing +end + +function Shearing_dealias_CUDA!(fh, Krsq, kfilter) + #define the i,j,k + i = (blockIdx().x - 1) * blockDim().x + threadIdx().x + j = (blockIdx().y - 1) * blockDim().y + threadIdx().y + k = (blockIdx().z - 1) * blockDim().z + threadIdx().z + nx,ny,nz = size(fh) + if k ∈ (1:nz) && j ∈ (1:ny) && i ∈ (1:nx) + if Krsq[i,j,k] >= kfilter + fh[i,j,k] = 0.0 + end + # for rfft, the complex X[1] == X[N/2+1] == 0 + # Reason : https://github.com/FourierFlows/Fou/rierFlows.jl/issues/326 + if i == 1 || i == nx + fh[i,j,k] = real(fh[i,j,k]) + end + if i == 1 && j != 1 && k != 1 + fh[i,j,k] *= 0.0 + end + end + return nothing +end + +function DivFreeCorrection!(N, sol, t, clock, vars, params, grid) +#= + Possion Solver for periodic boundary condition + As in VP method, ∇ ⋅ B = 0 doesn't hold, B_{t+1} = ∇×Ψ + ∇Φ -> ∇ ⋅ B = ∇² Φ + We need to find Φ and remove it using a Poission Solver + Here we are using the Fourier Method to find the Φ + In Real Space, + ∇² Φ = ∇ ⋅ B + In k-Space, + ∑ᵢ -(kᵢ)² Φₖ = i∑ᵢ kᵢ(Bₖ)ᵢ + Φ = F{ i∑ᵢ kᵢ (Bₖ)ᵢ / ∑ᵢ (k²)ᵢ} +=# + + #find Φₖ + kᵢ,kⱼ,kₖ = grid.kr,grid.l,grid.m; + k⁻² = grid.invKrsq; + @. vars.nonlin1 *= 0; + @. vars.nonlinh1 *= 0; + ∑ᵢkᵢBᵢh_k² = vars.nonlinh1; + ∑ᵢkᵢBᵢ_k² = vars.nonlin1; + + + @views uxh = sol[:, :, :, params.ux_ind]; + @views uyh = sol[:, :, :, params.uy_ind]; + @views uzh = sol[:, :, :, params.uz_ind]; + + @. ∑ᵢkᵢBᵢh_k² = -im*(kᵢ*uxh + kⱼ*uyh + kₖ*uzh); + @. ∑ᵢkᵢBᵢh_k² = ∑ᵢkᵢBᵢh_k²*k⁻²; # Φₖ + + # B = B* - ∇Φ = Bᵢ - kᵢΦₖ + @. uxh -= im*kᵢ.*∑ᵢkᵢBᵢh_k²; + @. uyh -= im*kⱼ.*∑ᵢkᵢBᵢh_k²; + @. uzh -= im*kₖ.*∑ᵢkᵢBᵢh_k²; + + if size(sol,4) > 4 + @views bxh = sol[:, :, :, params.bx_ind]; + @views byh = sol[:, :, :, params.by_ind]; + @views bzh = sol[:, :, :, params.bz_ind]; + + @. ∑ᵢkᵢBᵢh_k² = -im*(kᵢ*bxh + kⱼ*byh + kₖ*bzh); + @. ∑ᵢkᵢBᵢh_k² = ∑ᵢkᵢBᵢh_k²*k⁻²; # Φₖ + + # B = B* - ∇Φ = Bᵢ - kᵢΦₖ + @. bxh -= im*kᵢ.*∑ᵢkᵢBᵢh_k²; + @. byh -= im*kⱼ.*∑ᵢkᵢBᵢh_k²; + @. bzh -= im*kₖ.*∑ᵢkᵢBᵢh_k²; + end + return nothing +end + +end \ No newline at end of file diff --git a/src/Solver/VPSolver.jl b/src/Solver/VPSolver.jl new file mode 100644 index 0000000..9e37a23 --- /dev/null +++ b/src/Solver/VPSolver.jl @@ -0,0 +1,141 @@ +module VPSolver + +# ---------- +# Volume Penalization Solver for HD/MHD N.S. equation +# ---------- +export + VP_BᵢUpdate, + VP_UᵢUpdate!, + DivBCorrection!, + DivVCorrection! + +using + CUDA, + TimerOutputs + +using LinearAlgebra: mul!, ldiv! + +# δ function +δ(a::Int,b::Int) = ( a == b ? 1 : 0 ); + +function VP_UᵢUpdate!(∂uᵢh∂t, kₐk⁻², a::Int, clock, vars, params, grid) + χ = params.χ; + η = clock.dt*13/7; #η condition for AB3 Method + for (uⱼ,Uⱼ,kⱼ,j) ∈ zip((vars.ux,vars.uy,vars.uz),(params.U₀x,params.U₀y,params.U₀z),(grid.kr,grid.l,grid.m),(1, 2, 3)) + + #The Volume Penalization term, Assuming U_wall = Uⱼ , j ∈ [x,y,z] direction + χUᵢ_η = vars.nonlin1 + χUᵢ_ηh = vars.nonlinh1 + @. χUᵢ_η = χ/η*(uⱼ - Uⱼ) + + mul!(χUᵢ_ηh, grid.rfftplan, χUᵢ_η) + + # Perform the Actual Advection update + @. ∂uᵢh∂t += -(δ(a,j)-kⱼ*kₐk⁻²)*χUᵢ_ηh + + end + return nothing; +end + +function VP_BᵢUpdate!(∂Bᵢh∂t, kₐk⁻², a::Int, clock, vars, params, grid) + + χ = params.χ + η = clock.dt*13/7 #η condition for AB3 Method + + for (bⱼ,Bⱼ,kⱼ,j) ∈ zip((vars.bx,vars.by,vars.bz),(params.B₀x,params.B₀y,params.B₀z),(grid.kr,grid.l,grid.m),(1, 2, 3)) + + #The Volume Penalization term, Assuming B_wall = Bⱼ, j ∈ [x,y,z] direction + χbᵢ_η = vars.nonlin1 + χbᵢ_ηh = vars.nonlinh1 + @. χbᵢ_η = χ/η*(bⱼ - Bⱼ) + + mul!(χbᵢ_ηh, grid.rfftplan, χbᵢ_η) + + # Perform the Actual Advection update + @. ∂Bᵢh∂t += -(δ(a,j)-kⱼ*kₐk⁻²)*χbᵢ_ηh + + end + return nothing +end + +function DivBCorrection!(prob) +#= + Possion Solver for periodic boundary condition + As in VP method, ∇ ⋅ B = 0 doesn't hold, B_{t+1} = ∇×Ψ + ∇Φ -> ∇ ⋅ B = ∇² Φ + We need to find Φ and remove it using a Poission Solver + Here we are using the Fourier Method to find the Φ + In Real Space, + ∇² Φ = ∇ ⋅ B + In k-Space, + ∑ᵢ -(kᵢ)² Φₖ = i∑ᵢ kᵢ(Bₖ)ᵢ + Φ = F{ i∑ᵢ kᵢ (Bₖ)ᵢ / ∑ᵢ (k²)ᵢ} +=# + + vars = prob.vars + grid = prob.grid + params = prob.params + #find Φₖ + kᵢ,kⱼ,kₖ = grid.kr,grid.l,grid.m + k⁻² = grid.invKrsq + @. vars.nonlin1 *= 0 + @. vars.nonlinh1 *= 0 + ∑ᵢkᵢBᵢh_k² = vars.nonlinh1 + ∑ᵢkᵢBᵢ_k² = vars.nonlin1 + @views bxh = prob.sol[:, :, :, params.bx_ind] + @views byh = prob.sol[:, :, :, params.by_ind] + @views bzh = prob.sol[:, :, :, params.bz_ind] + @. ∑ᵢkᵢBᵢh_k² = -im*(kᵢ*bxh + kⱼ*byh + kₖ*bzh) + @. ∑ᵢkᵢBᵢh_k² = ∑ᵢkᵢBᵢh_k²*k⁻² # Φₖ + + # B = B* - ∇Φ = Bᵢ - kᵢΦₖ + @. bxh -= im*kᵢ.*∑ᵢkᵢBᵢh_k² + @. byh -= im*kⱼ.*∑ᵢkᵢBᵢh_k² + @. bzh -= im*kₖ.*∑ᵢkᵢBᵢh_k² + + #Update to Real Space vars + ldiv!(vars.bx, grid.rfftplan, deepcopy(bxh)) + ldiv!(vars.by, grid.rfftplan, deepcopy(byh)) + ldiv!(vars.bz, grid.rfftplan, deepcopy(bzh)) +end + +function DivVCorrection!(prob) +#= + Possion Solver for periodic boundary condition + As in VP method, ∇ ⋅ B = 0 doesn't hold, B_{t+1} = ∇×Ψ + ∇Φ -> ∇ ⋅ B = ∇² Φ + We need to find Φ and remove it using a Poission Solver + Here we are using the Fourier Method to find the Φ + In Real Space, + ∇² Φ = ∇ ⋅ B + In k-Space, + ∑ᵢ -(kᵢ)² Φₖ = i∑ᵢ kᵢ(Bₖ)ᵢ + Φ = F{ i∑ᵢ kᵢ (Bₖ)ᵢ / ∑ᵢ (k²)ᵢ} +=# + + vars = prob.vars + grid = prob.grid + params = prob.params + #find Φₖ + kᵢ,kⱼ,kₖ = grid.kr,grid.l,grid.m + k⁻² = grid.invKrsq + @. vars.nonlin1 *= 0 + @. vars.nonlinh1 *= 0 + ∑ᵢkᵢUᵢh_k² = vars.nonlinh1 + ∑ᵢkᵢUᵢ_k² = vars.nonlin1 + @views uxh = prob.sol[:, :, :, params.ux_ind] + @views uyh = prob.sol[:, :, :, params.uy_ind] + @views uzh = prob.sol[:, :, :, params.uz_ind] + @. ∑ᵢkᵢUᵢh_k² = -im*(kᵢ*uxh + kⱼ*uyh + kₖ*uzh) + @. ∑ᵢkᵢUᵢh_k² = ∑ᵢkᵢUᵢh_k²*k⁻² # Φₖ + + # B = B* - ∇Φ = Bᵢ - kᵢΦₖ + @. uxh -= im*kᵢ.*∑ᵢkᵢUᵢh_k² + @. uyh -= im*kⱼ.*∑ᵢkᵢUᵢh_k² + @. uzh -= im*kₖ.*∑ᵢkᵢUᵢh_k² + + #Update to Real Space vars + ldiv!(vars.ux, grid.rfftplan, deepcopy(uxh)) + ldiv!(vars.uy, grid.rfftplan, deepcopy(uyh)) + ldiv!(vars.uz, grid.rfftplan, deepcopy(uzh)) +end + +end \ No newline at end of file diff --git a/src/Structure/HDParams.jl b/src/Structure/HDParams.jl new file mode 100644 index 0000000..72030c2 --- /dev/null +++ b/src/Structure/HDParams.jl @@ -0,0 +1,76 @@ +struct HDParams_VP{Aphys,usr_param,to} <: AbstractParams + + "small-scale (hyper)-viscosity coefficient for v" + ν :: Number + "(hyper)-viscosity order, `nν```≥ 1``" + nν :: Int + + "Array Indexing for velocity" + ux_ind :: Int + uy_ind :: Int + uz_ind :: Int + + "function that calculates the Fourier transform of the forcing, ``F̂``" + calcF! :: Function + + "Volume penzlization method paramter" + χ :: Aphys + U₀x :: Aphys + U₀y :: Aphys + U₀z :: Aphys + + "User defined params" + usr_params :: usr_param + + "Debug timer" + debugTimer :: to + +end + +struct HDParams{usr_param,to} <: AbstractParams + + "small-scale (hyper)-viscosity coefficient for v" + ν :: Number + "(hyper)-viscosity order, `nν```≥ 1``" + nν :: Int + + "Array Indexing for velocity" + ux_ind :: Int + uy_ind :: Int + uz_ind :: Int + + "function that calculates the Fourier transform of the forcing, ``F̂``" + calcF! :: Function + + "User defined params" + usr_params :: usr_param + + "Debug timer" + debugTimer :: to + +end + +struct CHDParams{usr_param,to} <: AbstractParams + "speed of sound" + cₛ :: Number + "small-scale (hyper)-viscosity coefficient for v" + ν :: Number + "(hyper)-viscosity order, `nν```≥ 1``" + nν :: Int + + "Array Indexing for density/velocity" + ρ_ind :: Int + ux_ind :: Int + uy_ind :: Int + uz_ind :: Int + + "function that calculates the Fourier transform of the forcing, ``F̂``" + calcF! :: Function + + "User defined params" + usr_params :: usr_param + + "Debug timer" + debugTimer :: to + +end diff --git a/src/Structure/HDVars.jl b/src/Structure/HDVars.jl new file mode 100644 index 0000000..e09fc58 --- /dev/null +++ b/src/Structure/HDVars.jl @@ -0,0 +1,51 @@ +struct HVars{Aphys, Atrans, usr_var} <: MHDVars + "x-component of velocity" + ux :: Aphys + "y-component of velocity" + uy :: Aphys + "z-component of velocity" + uz :: Aphys + + # Temperatory Cache + "Non-linear term 1" + nonlin1 :: Aphys + "Fourier transform of Non-linear term" + nonlinh1 :: Atrans + + # User Defined Vars + "User Defined Vars" + usr_vars :: usr_var +end + +struct CHVars{Aphys, Atrans, usr_var} <: MHDVars + "density " + ρ :: Aphys + "x-component of velocity" + ux :: Aphys + "y-component of velocity" + uy :: Aphys + "z-component of velocity" + uz :: Aphys + + "x-component of fourier velocity" + uxh :: Atrans + "y-component of fourier velocity" + uyh :: Atrans + "z-component of fourier velocity" + uzh :: Atrans + + # Temperatory Cache + "Non-linear term 1" + nonlin1 :: Aphys + "Fourier transform of Non-linear term" + nonlinh1 :: Atrans + + "Non-linear term 2" + nonlin2 :: Aphys + "Fourier transform of Non-linear term" + nonlinh2 :: Atrans + + # User Defined Vars + "User Defined Vars" + usr_vars :: usr_var +end diff --git a/src/Structure/MHDParams.jl b/src/Structure/MHDParams.jl new file mode 100644 index 0000000..e1fc8ed --- /dev/null +++ b/src/Structure/MHDParams.jl @@ -0,0 +1,127 @@ +struct MHDParams_VP{Aphys,usr_param,to} <: AbstractParams + + "small-scale (hyper)-viscosity coefficient for v" + ν :: Number + "small-scale (hyper)-viscosity coefficient for b" + η :: Number + "(hyper)-viscosity order, `nν```≥ 1``" + nν :: Int + "(hyper)-resisivity order, `nη```≥ 1``" + nη :: Int + + "Array Indexing for velocity" + ux_ind :: Int + uy_ind :: Int + uz_ind :: Int + + "Array Indexing for B-field" + bx_ind :: Int + by_ind :: Int + bz_ind :: Int + + "function that calculates the Fourier transform of the forcing, ``F̂``" + calcF! :: Function + + "Volume penzlization method paramter" + χ :: Aphys + U₀x :: Aphys + U₀y :: Aphys + U₀z :: Aphys + B₀x :: Aphys + B₀y :: Aphys + B₀z :: Aphys + + "User defined params" + usr_params :: usr_param + + "Debug timer" + debugTimer :: to + +end + +struct MHDParams{usr_param,to} <: AbstractParams + + "small-scale (hyper)-viscosity coefficient for v" + ν :: Number + "small-scale (hyper)-viscosity coefficient for b" + η :: Number + "(hyper)-viscosity order, `nν```≥ 1``" + nν :: Int + "(hyper)-resisivity order, `nη```≥ 1``" + nη :: Int + + "Array Indexing for velocity" + ux_ind :: Int + uy_ind :: Int + uz_ind :: Int + + "Array Indexing for B-field" + bx_ind :: Int + by_ind :: Int + bz_ind :: Int + "function that calculates the Fourier transform of the forcing, ``F̂``" + calcF! :: Function + + "User defined params" + usr_params :: usr_param + + "Debug timer" + debugTimer :: to + +end + +struct EMHDParams{usr_param,to} <: AbstractParams + + "small-scale (hyper)-viscosity coefficient for b" + η :: Number + + "(hyper)-resisivity order, `nη```≥ 1``" + nη :: Int + + "Array Indexing for B-field" + bx_ind :: Int + by_ind :: Int + bz_ind :: Int + "function that calculates the Fourier transform of the forcing, ``F̂``" + calcF! :: Function + + "User defined params" + usr_params :: usr_param + + "Debug timer" + debugTimer :: to + +end + +struct CMHDParams{usr_param,to} <: AbstractParams + "speed of sound" + cₛ :: Number + "small-scale (hyper)-viscosity coefficient for v" + ν :: Number + "small-scale (hyper)-viscosity coefficient for b" + η :: Number + "(hyper)-viscosity order, `nν```≥ 1``" + nν :: Int + "(hyper)-resisivity order, `nη```≥ 1``" + nη :: Int + + "Array Indexing for density/velocity" + ρ_ind :: Int + ux_ind :: Int + uy_ind :: Int + uz_ind :: Int + + "Array Indexing for B-field" + bx_ind :: Int + by_ind :: Int + bz_ind :: Int + "function that calculates the Fourier transform of the forcing, ``F̂``" + calcF! :: Function + + "User defined params" + usr_params :: usr_param + + "Debug timer" + debugTimer :: to + +end diff --git a/src/Structure/MHDVars.jl b/src/Structure/MHDVars.jl new file mode 100644 index 0000000..1b70248 --- /dev/null +++ b/src/Structure/MHDVars.jl @@ -0,0 +1,88 @@ +struct MVars{Aphys, Atrans, usr_var} <: MHDVars + "x-component of velocity" + ux :: Aphys + "y-component of velocity" + uy :: Aphys + "z-component of velocity" + uz :: Aphys + "x-component of B-field" + bx :: Aphys + "y-component of B-field" + by :: Aphys + "z-component of B-field" + bz :: Aphys + + # Temperatory Cache + "Non-linear term 1" + nonlin1 :: Aphys + "Fourier transform of Non-linear term" + nonlinh1 :: Atrans + + # User Defined Vars + "User Defined Vars" + usr_vars :: usr_var +end + +struct EMVars{Aphys, Atrans, usr_var} <: MHDVars + "x-component of B-field" + bx :: Aphys + "y-component of B-field" + by :: Aphys + "z-component of B-field" + bz :: Aphys + "x-component of Curl B-field" + ∇XBᵢ :: Aphys + "y-component of Curl B-field" + ∇XBⱼ :: Aphys + "z-component of Curl B-field" + ∇XBₖ :: Aphys + + # Temperatory Cache + "Non-linear term 1" + nonlin1 :: Aphys + "Fourier transform of Non-linear term" + nonlinh1 :: Atrans + + # User Defined Vars + "User Defined Vars" + usr_vars :: usr_var +end + +struct CMVars{Aphys, Atrans, usr_var} <: MHDVars + "density " + ρ :: Aphys + "x-component of velocity" + ux :: Aphys + "y-component of velocity" + uy :: Aphys + "z-component of velocity" + uz :: Aphys + "x-component of B-field" + bx :: Aphys + "y-component of B-field" + by :: Aphys + "z-component of B-field" + bz :: Aphys + + "x-component of fourier velocity" + uxh :: Atrans + "y-component of fourier velocity" + uyh :: Atrans + "z-component of fourier velocity" + uzh :: Atrans + + # Temperatory Cache + "Non-linear term 1" + nonlin1 :: Aphys + "Fourier transform of Non-linear term" + nonlinh1 :: Atrans + + "Non-linear term 2" + nonlin2 :: Aphys + "Fourier transform of Non-linear term" + nonlinh2 :: Atrans + + # User Defined Vars + "User Defined Vars" + usr_vars :: usr_var +end \ No newline at end of file diff --git a/src/Structure/datastructure.jl b/src/Structure/datastructure.jl new file mode 100644 index 0000000..e41ecb6 --- /dev/null +++ b/src/Structure/datastructure.jl @@ -0,0 +1,148 @@ +# ---------- +# Module for Setting up the data structure for HD and MHD problem +# ---------- + +function SetMHDVars(::Dev, grid, usr_vars) where Dev + T = eltype(grid) + + @devzeros Dev T (grid.nx, grid.ny, grid.nz) ux uy uz bx by bz nonlin1 + @devzeros Dev Complex{T} (grid.nkr, grid.nl, grid.nm) nonlinh1 + + return MVars( ux, uy, uz, bx, by, bz, + nonlin1, nonlinh1, usr_vars); +end + +function SetEMHDVars(::Dev, grid, usr_vars) where Dev + T = eltype(grid) + + @devzeros Dev T (grid.nx, grid.ny, grid.nz) bx by bz ∇XBx ∇XBy ∇XBz nonlin1 + @devzeros Dev Complex{T} (grid.nkr, grid.nl, grid.nm) nonlinh1 + + return EMVars(bx, by, bz, + ∇XBx, ∇XBy, ∇XBz, + nonlin1, nonlinh1, usr_vars); +end + + +function SetHDVars(::Dev, grid, usr_vars) where Dev + T = eltype(grid) + + @devzeros Dev T (grid.nx, grid.ny, grid.nz) ux uy uz nonlin1 + @devzeros Dev Complex{T} (grid.nkr, grid.nl, grid.nm) nonlinh1 + + return HVars( ux, uy, uz, + nonlin1, nonlinh1, usr_vars); +end + +function SetCMHDVars(::Dev, grid, usr_vars) where Dev + T = eltype(grid) + + @devzeros Dev T (grid.nx, grid.ny, grid.nz) ρ ux uy uz bx by bz nonlin1 nonlin2 + @devzeros Dev Complex{T} (grid.nkr, grid.nl, grid.nm) uxh uyh uzh nonlinh1 nonlinh2 + + return CMVars( ρ, ux, uy, uz, bx, by, bz, uxh, uyh, uzh, + nonlin1, nonlinh1, nonlin2, nonlinh2, usr_vars); +end + +function SetCHDVars(::Dev, grid, usr_vars) where Dev + T = eltype(grid) + + @devzeros Dev T (grid.nx, grid.ny, grid.nz) ρ ux uy uz nonlin1 nonlin2 + @devzeros Dev Complex{T} (grid.nkr, grid.nl, grid.nm) uxh uyh uzh nonlinh1 nonlinh2 + + return CHVars( ρ, ux, uy, uz, uxh, uyh, uzh, + nonlin1, nonlinh1, nonlin2, nonlinh2, usr_vars); +end + +# Functions of setting up the Vars and Params struct +function SetVars(dev, grid, usr_vars; B = false, E = false, VP = false, C =false) + if C + setvars = ifelse(B,SetCMHDVars,SetCHDVars) + elseif E + setvars = SetEMHDVars + else + setvars = ifelse(B,SetMHDVars,SetHDVars) + end + return setvars(dev, grid, usr_vars) +end + + function SetParams(::Dev, grid, calcF::Function, usr_params; + B = false, VP = false, C = false, S = false, E = false, + cₛ = 0, ν = 0, η = 0, nν = 0, nη = 0) where Dev + T = eltype(grid); + usr_param = typeof(usr_params) + + # define the debug timer + to = TimerOutput(); + + if (B) + if (VP) + @devzeros Dev T (grid.nx, grid.ny, grid.nz) χ U₀x U₀y U₀z B₀x B₀y B₀z + params = MHDParams_VP(ν, η, nν, nη, 1, 2, 3, 4, 5, 6, calcF, χ, U₀x, U₀y, U₀z, B₀x, B₀y, B₀z, usr_params, to) + elseif (C) + params = CMHDParams(cₛ,ν, η, nν, nη, 1, 2, 3, 4, 5, 6, 7, calcF, usr_params, to); + elseif (S) + shear_params = GetShearParams(Dev, grid, B; ν=ν, η=η); + params = MHDParams(0.0, 0.0, nν, nη, 1, 2, 3, 4, 5, 6, calcF, shear_params, to); + elseif (E) + params = EMHDParams(η, nη, 1, 2, 3, calcF, usr_params, to); + else + params = MHDParams(ν, η, nν, nη, 1, 2, 3, 4, 5, 6, calcF, usr_params, to); + end + else + if (VP) + @devzeros Dev T (grid.nx, grid.ny, grid.nz) χ U₀x U₀y U₀z + params = HDParams_VP(ν, nν, 1, 2, 3, calcF, χ, U₀x, U₀y, U₀z, usr_params, to); + elseif (C) + params = CHDParams(cₛ, ν, nν, 1, 2, 3, 4, calcF, usr_params, to); + elseif (S) + shear_params = GetShearParams(Dev, grid, B; ν=ν, η=0.0); + params = HDParams(0.0, nν, 1, 2, 3, calcF, shear_params, to); + else + params = HDParams(ν, nν, 1, 2, 3, calcF, usr_params, to); + end + end + + return params + +end + +function GetShearParams(dev, grid, B; ν = 0.0, η = 0.0) + T = eltype(grid) + + @devzeros dev T (grid.nx, grid.ny, grid.nz) U₀x U₀y + @devzeros dev Complex{T} (grid.nkr, grid.nl, grid.nm) U₀xh U₀yh + ky₀ = copy(grid.l); + iky = copy(grid.l1D) + k2xz= @. grid.kr^2 + grid.m^2 + Nₗ = ifelse(B,6,3) + @devzeros dev Complex{T} (grid.nkr, grid.nl, grid.nm, Nₗ) tmp + + return SParams(T(0.0), T(0.0), T(0.0), T(ν), ky₀, k2xz, iky, U₀x, U₀y, U₀xh, U₀yh, tmp) +end + +mutable struct SParams{A1Daxis,A2Daxis, Aphys, Atrans, Atmp} <: AbstractParams + "shear rate = dlnΩ/dlnr" + q :: AbstractFloat + "built-in time" + τ :: AbstractFloat + "Remapping peroid" + τΩ :: AbstractFloat + "diffusion Coef." + ν :: AbstractFloat + "spectral ky at t = 0" + ky₀ :: A2Daxis + "spectral kx² + kz² at t = 0" + k2xz:: A2Daxis + "spectral ky in 1D at t = 0" + iky :: A1Daxis + + "Background shear velocity in real/spectral space" + U₀x :: Aphys + U₀y :: Aphys + U₀xh :: Atrans + U₀yh :: Atrans + + "Sketch array" + tmp :: Atmp +end \ No newline at end of file diff --git a/src/integrator.jl b/src/integrator.jl index 9194905..91f19b1 100644 --- a/src/integrator.jl +++ b/src/integrator.jl @@ -3,6 +3,19 @@ # ---------- """ + TimeIntegrator!(prob,t₀,N₀, + usr_dt = 0.0, + CFL_Coef = 0.25, + CFL_function = nothingfunction, + diags = [], + dynamic_dashboard = true, + loop_number = 100, + save = false, + save_loc = "", + filename = "", + file_number = 0, + dump_dt = 0) + Time Integrator for MHDFlows problem Keyword arguments ================= @@ -14,14 +27,13 @@ Time Integrator for MHDFlows problem - `CFL_function` : user defined CFL function - `loop_number` : iteration count for displaying the diagnostic information (T type : Int) - `save` : save option for saving the hdf5 file (T type: true/false) -$(TYPEDFIELDS) """ function TimeIntegrator!(prob,t₀ :: Number,N₀ :: Int; usr_dt = 0.0, CFL_Coef = 0.25, CFL_function = nothingfunction, diags = [], - dynamical_dashboard = true, + dynamic_dashboard = true, loop_number = 100, save = false, save_loc = "", @@ -47,44 +59,44 @@ function TimeIntegrator!(prob,t₀ :: Number,N₀ :: Int; # Declare the timescale for diffusion if prob.flag.b - vi = maximum([prob.params.ν,prob.params.η]); - nv = maximum([prob.params.nν,prob.params.nη]); + vi = prob.flag.e ? prob.params.η : maximum([prob.params.ν,prob.params.η]) + nv = prob.flag.e ? prob.params.nη : maximum([prob.params.nν,prob.params.nη]) else - vi = prob.params.ν; + vi = prob.params.ν nv = prob.params.nν end - dx = prob.grid.Lx/prob.grid.nx; - dy = prob.grid.Ly/prob.grid.ny; - dz = prob.grid.Lz/prob.grid.nz; - dl = minimum([dx,dy,dz]); - t_diff = ifelse(nv >1, CFL_Coef*(dl)^(2)/vi,CFL_Coef*dl^2/vi); + dx = prob.grid.Lx/prob.grid.nx + dy = prob.grid.Ly/prob.grid.ny + dz = prob.grid.Lz/prob.grid.nz + dl = minimum([dx,dy,dz]) + t_diff = ifelse(nv >1, CFL_Coef*(dl)^(nv)/vi, CFL_Coef*dl^2/vi) # Declare the iterator paramters - t_next_save = prob.clock.t + dump_dt; - prob.clock.step = 0; + t_next_save = prob.clock.t + dump_dt + prob.clock.step = 0 # Check if user is declared a looping dt usr_declared_dt = usr_dt != 0.0 ? true : false if (usr_declared_dt) - prob.clock.dt = usr_dt; + prob.clock.dt = usr_dt end - #Corret v and b if VP method is turned on + # Clean the divgence of b if VP method is turned on if (prob.flag.vp == true) - #MHDSolver_VP.DivVCorrection!(prob); - prob.flag.b == true ? MHDSolver_VP.DivBCorrection!(prob) : nothing; + VPSolver.DivVCorrection!(prob) + prob.flag.b == true ? VPSolver.DivBCorrection!(prob) : nothing end # Print the wellcome message WellcomeMessage() # check if user enable the dynamical dashboard - if dynamical_dashboard + if dynamic_dashboard prog = Progress(N₀; desc = "Simulation in rogress :", barglyphs=BarGlyphs('|','█', ['▁' ,'▂' ,'▃' ,'▄' ,'▅' ,'▆', '▇'],' ','|',), barlen=10, showspeed=true) else - prog = nothing; + prog = nothing end # Actual Computation Start @@ -93,43 +105,44 @@ function TimeIntegrator!(prob,t₀ :: Number,N₀ :: Int; if (!usr_declared_dt) #update the CFL condition; - updateCFL!(prob, t_diff; Coef = CFL_Coef); + updateCFL!(prob, t_diff; Coef = CFL_Coef) end #update the system; stepforward!(prob.sol, prob.clock, prob.timestepper, prob.eqn, - prob.vars, prob.params, prob.grid); - - # dealias - dealias!(prob.sol, prob.grid); + prob.vars, prob.params, prob.grid) #update the diags - increment!(diags); + increment!(diags) #Corret b if VP method is turned on if (prob.flag.vp == true) - prob.flag.b == true ? MHDSolver_VP.DivBCorrection!(prob) : nothing; + VPSolver.DivVCorrection!(prob) + prob.flag.b == true ? VPSolver.DivBCorrection!(prob) : nothing end #Dye Update - prob.dye.dyeflag == true ? prob.dye.stepforward!(prob) : nothing; + prob.dye.dyeflag == true ? prob.dye.stepforward!(prob) : nothing + + #Shear Update + prob.flag.s == true ? Shear.Shearing_remapping!(prob) : nothing #User defined function for foo! ∈ prob.usr_func - foo!(prob); + foo!(prob) end #Save Section - if (save) && prob.clock.t >= t_next_save; - ProbDiagnostic(prob); + if (save) && prob.clock.t >= t_next_save + ProbDiagnostic(prob) savefile(prob, file_number; file_path_and_name = file_path_and_name) - t_next_save += dump_dt; - file_number +=1; + t_next_save += dump_dt + file_number +=1 end # Update the dashboard information to user - dynamical_dashboard ? Dynamical_dashboard(prob,prog, N₀,t₀) : - Static_Dashbroad(prob,prob.clock.step% loop_number); + dynamic_dashboard ? Dynamic_Dashboard(prob,prog, N₀,t₀) : + Static_Dashbroad(prob,prob.clock.step% loop_number) end end @@ -137,80 +150,90 @@ function TimeIntegrator!(prob,t₀ :: Number,N₀ :: Int; Ntotal = prob.grid.nx*prob.grid.ny*prob.grid.nz; Total_Update_per_second = prob.clock.step* Ntotal/time; print("Total CPU/GPU time run = $(round(time,digits=3)) s," - *" zone update per second = $(round(Total_Update_per_second,digits=3)) \n"); - return nothing; + *" zone update per second = $(round(Total_Update_per_second,digits=3)) \n") + return nothing end - -function getCFL!(prob, t_diff; Coef = 0.3); +function getCFL!(prob, t_diff; Coef = 0.3) #Solving the dt of CFL condition using dt = Coef*dx/v - ux,uy,uz = prob.vars.ux, prob.vars.uy,prob.vars.uz; + square_maximum(A) = mapreduce(x->x*x,max,A) + if prob.flag.e + # Maxmium velocity, For EMHD, v = ∇×B + ux,uy,uz = prob.vars.∇XBᵢ , prob.vars.∇XBⱼ, prob.vars.∇XBₖ; + v2xmax = square_maximum(ux) + v2ymax = square_maximum(uy) + v2zmax = square_maximum(uz) + vmax = sqrt(maximum((v2xmax,v2ymax,v2zmax))) + else + #Maxmium velocity + ux,uy,uz = prob.vars.ux, prob.vars.uy,prob.vars.uz + v2xmax = square_maximum(ux) + v2ymax = square_maximum(uy) + v2zmax = square_maximum(uz) + vmax = sqrt(maximum((v2xmax,v2ymax,v2zmax))) + end - #Maxmium velocity - v2xmax = maximum(ux.^2); - v2ymax = maximum(uy.^2); - v2zmax = maximum(uz.^2); - vmax = sqrt(maximum([v2xmax,v2ymax,v2zmax])); - if prob.flag.b #Maxmium Alfvenic velocity - bx,by,bz = prob.vars.bx, prob.vars.by,prob.vars.bz; - v2xmax = maximum(bx.^2); - v2ymax = maximum(by.^2); - v2zmax = maximum(bz.^2); - vamax = sqrt(maximum([v2xmax,v2ymax,v2zmax])); - vmax = maximum([vmax,vamax]); + bx,by,bz = prob.vars.bx, prob.vars.by,prob.vars.bz + v2xmax = square_maximum(bx) + v2ymax = square_maximum(by) + v2zmax = square_maximum(bz) + vamax = sqrt(maximum([v2xmax,v2ymax,v2zmax])) + vmax = maximum([vmax,vamax]) end - dx = prob.grid.Lx/prob.grid.nx; - dy = prob.grid.Ly/prob.grid.ny; - dz = prob.grid.Lz/prob.grid.nz; - dl = minimum([dx,dy,dz]); - dt = minimum([Coef*dl/vmax,t_diff]); - prob.clock.dt = dt; + if prob.flag.c + vmax = maximum([vmax,prob.params.cₛ]) + end + + dx = prob.grid.Lx/prob.grid.nx + dy = prob.grid.Ly/prob.grid.ny + dz = prob.grid.Lz/prob.grid.nz + # EMHD have two non-linear term, which makes dt ∝ Δx² in stead of Δx + dl = prob.flag.e ? minimum([dx,dy,dz])^2 : minimum([dx,dy,dz]) + dt = minimum([Coef*dl/vmax,t_diff]) + prob.clock.dt = dt end function CFL_Init(CFL_function::Function,usr_dt::Number) if usr_dt > 0.0 - error("User define both CFL_function and usr_dt"); + error("User define both CFL_function and usr_dt") elseif usr_dt == 0.0 return CFL_function end end function Restart!(prob,file_path_and_name) - f = h5open(file_path_and_name,"r"); - ux = read(f,"i_velocity"); - uy = read(f,"j_velocity"); - uz = read(f,"k_velocity"); - - #Update V Conponment - copyto!(prob.vars.ux, deepcopy(ux)); - copyto!(prob.vars.uy, deepcopy(uy)); - copyto!(prob.vars.uz, deepcopy(uz)); - uxh = @view prob.sol[:, :, :, prob.params.ux_ind]; - uyh = @view prob.sol[:, :, :, prob.params.uy_ind]; - uzh = @view prob.sol[:, :, :, prob.params.uz_ind]; - mul!(uxh, prob.grid.rfftplan, prob.vars.ux); - mul!(uyh, prob.grid.rfftplan, prob.vars.uy); - mul!(uzh, prob.grid.rfftplan, prob.vars.uz); + f = h5open(file_path_and_name,"r") + + if !prob.flag.e + ux = read(f,"i_velocity") + uy = read(f,"j_velocity") + uz = read(f,"k_velocity") + + #Update V Conponment + Move_Data_to_Prob!(ux, prob.vars.ux, view(prob.sol,:, :, :, prob.params.ux_ind),prob.grid) + Move_Data_to_Prob!(uy, prob.vars.uy, view(prob.sol,:, :, :, prob.params.uy_ind),prob.grid) + Move_Data_to_Prob!(uz, prob.vars.uz, view(prob.sol,:, :, :, prob.params.uz_ind),prob.grid) + end #Update B Conponment if prob.flag.b == true - bx = read(f,"i_mag_field",); - by = read(f,"j_mag_field",); - bz = read(f,"k_mag_field",); - - copyto!(prob.vars.bx, deepcopy(bx)); - copyto!(prob.vars.by, deepcopy(by)); - copyto!(prob.vars.bz, deepcopy(bz)); - bxh = @view prob.sol[:, :, :, prob.params.bx_ind]; - byh = @view prob.sol[:, :, :, prob.params.by_ind]; - bzh = @view prob.sol[:, :, :, prob.params.bz_ind]; - mul!(bxh, prob.grid.rfftplan, prob.vars.bx); - mul!(byh, prob.grid.rfftplan, prob.vars.by); - mul!(bzh, prob.grid.rfftplan, prob.vars.bz); + bx = read(f,"i_mag_field",) + by = read(f,"j_mag_field",) + bz = read(f,"k_mag_field",) + + Move_Data_to_Prob!(bx,prob.vars.bx, view(prob.sol,:, :, :, prob.params.bx_ind),prob.grid) + Move_Data_to_Prob!(by,prob.vars.by, view(prob.sol,:, :, :, prob.params.by_ind),prob.grid) + Move_Data_to_Prob!(bz,prob.vars.bz, view(prob.sol,:, :, :, prob.params.bz_ind),prob.grid) + end + + #Update the density + if (prob.flag.c == true) + ρ = read(f,"gas_density",) + Move_Data_to_Prob!(ρ, prob.vars.ρ, view(prob.sol,:, :, :, prob.params.ρ_ind),prob.grid) end #if prob.flag.vp == true @@ -219,38 +242,47 @@ function Restart!(prob,file_path_and_name) #end #Update Dye - if prob.dye.dyeflag == true; - ρ = read(f,"dye_density"); - copyto!(prob.dye.ρ, ρ); - ρh = prob.dye.tmp.sol₀; - mul!(ρh, prob.grid.rfftplan, prob.dye.ρ); + if prob.dye.dyeflag == true + ρ = read(f,"dye_density") + copyto!(prob.dye.ρ, ρ) + ρh = prob.dye.tmp.sol₀ + mul!(ρh, prob.grid.rfftplan, prob.dye.ρ) end # Update time - prob.clock.t = read(f,"time"); + prob.clock.t = read(f,"time") close(f) + + return nothing end function savefile(prob,file_number;file_path_and_name="") space_0 = "" for i = 1:4-length(string(file_number));space_0*="0";end fw = h5open(file_path_and_name*"_t_"*space_0*string(file_number)*".h5","w") - write(fw, "i_velocity", Array(prob.vars.ux)); - write(fw, "j_velocity", Array(prob.vars.uy)); - write(fw, "k_velocity", Array(prob.vars.uz)); + if !prob.flag.e + write(fw, "i_velocity", Array(prob.vars.ux)) + write(fw, "j_velocity", Array(prob.vars.uy)) + write(fw, "k_velocity", Array(prob.vars.uz)) + end if (prob.dye.dyeflag == true) - write(fw, "dye_density", Array(prob.dye.ρ)); + write(fw, "dye_density", Array(prob.dye.ρ)) end if (prob.flag.b == true) - write(fw, "i_mag_field", Array(prob.vars.bx)); - write(fw, "j_mag_field", Array(prob.vars.by)); - write(fw, "k_mag_field", Array(prob.vars.bz)); + write(fw, "i_mag_field", Array(prob.vars.bx)) + write(fw, "j_mag_field", Array(prob.vars.by)) + write(fw, "k_mag_field", Array(prob.vars.bz)) + end + + if (prob.flag.c == true) + write(fw, "gas_density", Array(prob.vars.ρ)) end #if (prob.flag.vp == true) # write(fw, "chi", Array(prob.params.χ)); #end - write(fw, "time", prob.clock.t); - close(fw) + write(fw, "time", prob.clock.t) + close(fw) + return nothing end \ No newline at end of file diff --git a/src/pgen.jl b/src/pgen.jl index cfacca3..208ad14 100644 --- a/src/pgen.jl +++ b/src/pgen.jl @@ -22,9 +22,12 @@ function Problem(dev::Device=CPU(); η = 0, nμ = 0, # Declare if turn on magnetic field/VP method/Dye Module - B_field = false, + B_field = false, + EMHD = false, + Compressibility = false, + Shear = false, VP_method = false, - Dye_Module = false + Dye_Module = false, # Timestepper and equation options stepper = "RK4", calcF = nothingfunction, @@ -46,6 +49,7 @@ Keyword arguments - `η` : Viscosity coefficient for magnetic field. - `nν`: (Hyper)-viscosity order, `nν```≥ 1``, not available right now - `B_field` : Declaration of B-field + - `EMHD` : Declarartion of E-MHD - `VP_method`: Declaration of Volume penalization method - `Dye_Module`: Declaration of Dye, Passive tracer of the flow; - `stepper`: Time-stepping method. @@ -58,22 +62,26 @@ Keyword arguments """ function Problem(dev::Device; - # Numerical parameters + # Numerical & physical parameters nx = 64, ny = nx, nz = nx, Lx = 2π, Ly = Lx, Lz = Lx, + cₛ = 0.0, dt = 0.0, # Drag and/or hyper-viscosity for velocity/B-field ν = 0.0, nν = 0, η = 0.0, nη = 0, - # Declare if turn on magnetic field, VP method, Dye module - B_field = false, - VP_method = false, + # Declare if turn on magnetic field, EMHD, VP method, Dye module + B_field = false, + EMHD = false, + Compressibility = false, + Shear = false, + VP_method = false, Dye_Module = false, # Timestepper and equation options stepper = "RK4", @@ -86,89 +94,143 @@ function Problem(dev::Device; usr_params = [], usr_func = []) + # Compatibility Checking + if cₛ == 0.0 && Compressibility + error("You should define cₛ") + end + # Declare the grid - grid = ThreeDGrid(dev; nx=nx, Lx=Lx, ny = ny, Ly = Ly, nz = nz, Lz = Lz, T=T) + if Shear + error("Shear haven't fully implemented yet!") + grid = GetShearingThreeDGrid(dev; nx=nx, Lx=Lx, ny = ny, Ly = Ly, nz = nz, Lz = Lz, T=T) + else + grid = ThreeDGrid(dev; nx=nx, Lx=Lx, ny = ny, Ly = Ly, nz = nz, Lz = Lz, T=T) + end # Declare vars - vars = SetVars(dev, grid, usr_vars; B = B_field, VP =VP_method); + vars = SetVars(dev, grid, usr_vars; B = B_field, E = EMHD, VP = VP_method, C = Compressibility); # Delare params params = SetParams(dev, grid, calcF, usr_params; - B = B_field, VP = VP_method, ν = ν, η = η, nν = nν); + B = B_field, E = EMHD, VP = VP_method, C= Compressibility, S=Shear, + cₛ = cₛ, ν = ν, η = η, nν = nν); # Declare Fiuld Equations that will be iterating - equation = Equation_with_forcing(dev, grid; B = B_field, VP = VP_method); + equation = Equation_with_forcing(dev, grid; B = B_field, E = EMHD, C = Compressibility, S=Shear); # Return the Problem return MHDFLowsProblem(equation, stepper, dt, grid, vars, params, dev; - BFlag = B_field, VPFlag = VP_method, DyeFlag = Dye_Module, usr_func = usr_func) + CFlag = Compressibility, BFlag = B_field, EFlag = EMHD, SFlag = Shear, + VPFlag = VP_method, DyeFlag = Dye_Module, + usr_func = usr_func) end -function Equation_with_forcing(dev, grid::AbstractGrid; B = false, VP= false) - T = eltype(grid); - Nₗ = ifelse(B,6,3) - L = zeros(dev, T, (grid.nkr, grid.nl, grid.nm, Nₗ)); - - if (B) - calcN! = ifelse(VP,MHDcalcN_VP!,MHDcalcN!); +function Equation_with_forcing(dev, grid; B = false, E = false, C = false, S=false) + if C + Nₗ = ifelse(B,7,4) + else + if E + Nₗ = 3 + else + Nₗ = ifelse(B,6,3) + end + end + if C + calcN! = B ? CMHDcalcN! : CHDcalcN! + elseif S + calcN! = B ? SMHDcalcN! : SHDcalcN! + elseif E + calcN! = EMHDcalcN! else - calcN! = ifelse(VP, HDcalcN_VP!, HDcalcN!); + calcN! = B ? MHDcalcN! : HDcalcN! end - return FourierFlows.Equation(L,calcN!, grid); + return Setup_Equation(calcN!, grid; Nl =Nₗ) end function MHDcalcN!(N, sol, t, clock, vars, params, grid) + dealias!(sol, grid) MHDSolver.MHDcalcN_advection!(N, sol, t, clock, vars, params, grid) addforcing!(N, sol, t, clock, vars, params, grid) + + return nothing +end - dealias!(N, grid) +function EMHDcalcN!(N, sol, t, clock, vars, params, grid) + + dealias!(sol, grid) + + MHDSolver.EMHDcalcN_advection!(N, sol, t, clock, vars, params, grid) + + addforcing!(N, sol, t, clock, vars, params, grid) return nothing end function HDcalcN!(N, sol, t, clock, vars, params, grid) dealias!(sol, grid) + + addforcing!(N, sol, t, clock, vars, params, grid) HDSolver.HDcalcN_advection!(N, sol, t, clock, vars, params, grid) + return nothing +end + +function SMHDcalcN!(N, sol, t, clock, vars, params, grid) + + Shear.Shearing_dealias!(sol, grid); + + #Shear.Shearing_coordinate_update!(N, sol, t, clock, vars, params, grid) + + Shear.MHD_ShearingAdvection!(N, sol, t, clock, vars, params, grid) + addforcing!(N, sol, t, clock, vars, params, grid) + + return nothing +end - dealias!(N, grid) +function SHDcalcN!(N, sol, t, clock, vars, params, grid) + + Shear.Shearing_dealias!(sol, grid); + + Shear.Shearing_coordinate_update!(N, sol, t, clock, vars, params, grid); + + Shear.HD_ShearingAdvection!(N, sol, t, clock, vars, params, grid) + + addforcing!(N, sol, t, clock, vars, params, grid) return nothing end -function MHDcalcN_VP!(N, sol, t, clock, vars, params, grid) +function CMHDcalcN!(N, sol, t, clock, vars, params, grid) + dealias!(sol, grid) - MHDSolver_VP.MHDcalcN_advection!(N, sol, t, clock, vars, params, grid) + MHDSolver_compressible.MHDcalcN_advection!(N, sol, t, clock, vars, params, grid) addforcing!(N, sol, t, clock, vars, params, grid) - - dealias!(N, grid) return nothing end -function HDcalcN_VP!(N, sol, t, clock, vars, params, grid) +function CHDcalcN!(N, sol, t, clock, vars, params, grid) dealias!(sol, grid) - HDSolver_VP.HDcalcN_advection!(N, sol, t, clock, vars, params, grid) + HDSolver_compressible.HDcalcN_advection!(N, sol, t, clock, vars, params, grid) addforcing!(N, sol, t, clock, vars, params, grid) - - dealias!(N, grid) return nothing end + function addforcing!(N, sol, t, clock, vars, params, grid) params.calcF!(N, sol, t, clock, vars, params, grid) return nothing -end +end \ No newline at end of file diff --git a/src/pgen/A99ForceDriving.jl b/src/pgen/A99ForceDriving.jl index 741add4..2e5e1f4 100644 --- a/src/pgen/A99ForceDriving.jl +++ b/src/pgen/A99ForceDriving.jl @@ -15,13 +15,19 @@ mutable struct A99_vars{Atrans,T} eⁱᶿ :: Atrans end -function GetA99vars_And_function(::Dev, nx::Int,ny::Int,nz::Int; T = Float32) where Dev +function GetA99vars_And_function(::Dev, nx::Int,ny::Int,nz::Int; T = Float32, C =false) where Dev A = convert(T,1.0); b = convert(T,1.0); @devzeros Dev Complex{T} ( div(nx,2) + 1 , ny, nz) Fk e1x e1y e2x e2y e2z gi eⁱᶿ + A99 = A99_vars(A,b,Fk,e1x,e1y,e2x,e2y,e2z,gi,eⁱᶿ); + - return A99_vars(A,b,Fk,e1x,e1y,e2x,e2y,e2z,gi,eⁱᶿ), A99ForceDriving!; + if C + return A99, A99ForceDriving_Compressible! + else + return A99, A99ForceDriving!; + end end function A99ForceDriving!(N, sol, t, clock, vars, params, grid) @@ -37,35 +43,68 @@ function A99ForceDriving!(N, sol, t, clock, vars, params, grid) eⁱᶿ, gi = vars.usr_vars.eⁱᶿ, vars.usr_vars.gi; Φ = vars.nonlinh1; - # Work out the first conponement - eⁱᶿ .= exp.(im.*randN(T,grid.nkr,grid.nl,grid.nm)*2π); - Φ .= randN(Complex{T},grid.nkr,grid.nl,grid.nm).*π; + @. eⁱᶿ = exp(@.. im.*randN(T,grid.nkr,grid.nl,grid.nm)*2π); + rand!(Φ); @. Φ*=π; @. gi = -tanh(b*(Φ - π/2))/tanh(b*π/2); @. N[:,:,:,params.ux_ind] += A*Fk*eⁱᶿ*gi*e1x; @. N[:,:,:,params.uy_ind] += A*Fk*eⁱᶿ*gi*e1y; - # Work out the seond conponement - eⁱᶿ .= exp.(im.*randN(T,grid.nkr,grid.nl,grid.nm)*2π); - @. gi = √(1 - gi.^2); + # Work out the second conponement + @. eⁱᶿ .= exp(@.. im.*randN(T,grid.nkr,grid.nl,grid.nm)*2π); + @. gi = √(@.. 1 - gi^2); @. N[:,:,:,params.ux_ind] += A*Fk*eⁱᶿ*gi*e2x; @. N[:,:,:,params.uy_ind] += A*Fk*eⁱᶿ*gi*e2y; - @. N[:,:,:,params.uz_ind] += A*Fk*eⁱᶿ*gi*e2z; + @. N[:,:,:,params.uz_ind] += A*Fk*eⁱᶿ*gi*e2z; + + return nothing +end + +function A99ForceDriving_Compressible!(N, sol, t, clock, vars, params, grid) + + # A99 Force with the support of compressibiltiy + randN = typeof(N) <: Array ? Base.rand : CUDA.rand; + T = eltype(grid); + A = vars.usr_vars.A::T; + b = vars.usr_vars.b::T; + Fk = vars.usr_vars.Fk; + e1x, e1y = vars.usr_vars.e1x,vars.usr_vars.e1y; + e2x, e2y, e2z = vars.usr_vars.e2x,vars.usr_vars.e2y,vars.usr_vars.e2z; + eⁱᶿ, gi = vars.usr_vars.eⁱᶿ, vars.usr_vars.gi; + Φ = vars.nonlinh1; + + # Work out the first conponement + @. eⁱᶿ = exp(@.. im.*randN(T,grid.nkr,grid.nl,grid.nm)*2π); + rand!(Φ); @. Φ*=π; + @. gi = -tanh(b*(Φ - π/2))/tanh(b*π/2); + + aᵢtoFᵢ!(view(N,:,:,:,params.ux_ind),A.*Fk.*eⁱᶿ.*gi.*e1x,vars,grid); + aᵢtoFᵢ!(view(N,:,:,:,params.uy_ind),A.*Fk.*eⁱᶿ.*gi.*e1y,vars,grid); + + # Work out the second conponement + @. eⁱᶿ = exp(@.. im.*randN(T,grid.nkr,grid.nl,grid.nm)*2π); + @. gi = √(1 - gi.^2); + aᵢtoFᵢ!(view(N,:,:,:,params.ux_ind),A.*Fk.*eⁱᶿ.*gi.*e2x,vars,grid); + aᵢtoFᵢ!(view(N,:,:,:,params.uy_ind),A.*Fk.*eⁱᶿ.*gi.*e2y,vars,grid); + aᵢtoFᵢ!(view(N,:,:,:,params.uz_ind),A.*Fk.*eⁱᶿ.*gi.*e2z,vars,grid); return nothing end function SetUpFk(prob; kf = 2, P = 1,σ²= 1) + AT = Array; grid = prob.grid; - kx,ky,kz = grid.kr,grid.l,grid.m; + kx,ky,kz = AT(grid.kr),AT(grid.l),AT(grid.m); Lx,Ly,Lz = grid.Lx,grid.Ly,grid.Lz; dx,dy,dz = grid.dx,grid.dy,grid.dz; - k⁻¹ = @. √(grid.invKrsq); - k = @. √(grid.Krsq); + k⁻¹ = sqrt.(AT(grid.invKrsq)); + k = sqrt.(AT(grid.Krsq)); k⊥ = @. √(kx^2 + ky^2); dk⁻² = @. 1/(k+1)^2; ∫Fkdk = sum(@. exp(-(k.-kf)^2/σ²)*dk⁻²) A = sqrt(P*3*(Lx/dx)*(Ly/dy)*(Lz/dz)/∫Fkdk*(1/dx/dy/dz)); Fk = @. A*√(exp(-(k.-kf)^2/σ²)/2/π)*k⁻¹; + # Reason : https://github.com/FourierFlows/FourierFlows.jl/issues/326 + @. Fk[1,:,:] .= 0; e1x = @. ky/k⊥; e1y = @. -kx/k⊥; @@ -85,4 +124,13 @@ function SetUpFk(prob; kf = 2, P = 1,σ²= 1) copyto!(prob.vars.usr_vars.e2y,e2y); copyto!(prob.vars.usr_vars.e2z,e2z); +end + +function aᵢtoFᵢ!(∂pᵢ∂t,aᵢh,vars,grid) + ρ = vars.ρ; + ldiv!(vars.nonlin1,grid.rfftplan,aᵢh); + @. vars.nonlin1*=ρ; + mul!(vars.nonlinh1,grid.rfftplan,vars.nonlin1); + @. ∂pᵢ∂t += vars.nonlinh1; + return nothing end \ No newline at end of file diff --git a/src/pgen/A99ForceDriving_GPU.jl b/src/pgen/A99ForceDriving_GPU.jl new file mode 100644 index 0000000..79b8010 --- /dev/null +++ b/src/pgen/A99ForceDriving_GPU.jl @@ -0,0 +1,132 @@ +# ---------- +# Problem Generation Module: A99 Turbulence template For GPU only +# ---------- +module A99GPU + using CUDA + mutable struct A99_vars{T} + A :: T + b :: T + σ² :: T + kf :: T + end + + function GetA99vars_And_function(::Dev, nx::Int,ny::Int,nz::Int; T = Float32) where Dev + + A = convert(T,1.0); + b = convert(T,1.0); + σ² = convert(T,1.0); + kf = convert(T,1.0); + A99 = A99_vars(A,b,σ²,kf) + + return A99, A99ForceDriving!, SetUpFk! + end + + function SetUpFk!(prob; kf = 2.0, P = 1.0, σ= 1.0, b = 1.0) + AT = Array; + grid = prob.grid; + T = eltype(grid) + + kx,ky,kz = AT(grid.kr),AT(grid.l),AT(grid.m); + Lx,Ly,Lz = grid.Lx,grid.Ly,grid.Lz; + dx,dy,dz = grid.dx,grid.dy,grid.dz; + + k⁻¹ = sqrt.(AT(grid.invKrsq)); + k = sqrt.(AT(grid.Krsq)); + k⊥ = @. √(kx^2 + ky^2); + dk⁻² = @. 1/(k+1)^2; + + ∫Fkdk = sum(@. exp(-(k.-kf)^2/σ^2)*dk⁻²) + A = sqrt(P*3*(Lx/dx)*(Ly/dy)*(Lz/dz)/∫Fkdk*(1/dx/dy/dz)); + + prob.vars.usr_vars.A = T(A ) + prob.vars.usr_vars.σ² = T(σ^2) + prob.vars.usr_vars.b = T(b ) + prob.vars.usr_vars.kf = T(b ) + + return nothing + end + + function A99ForceDriving!(N, sol, t, clock, vars, params, grid) + + # A99 Force parameter + T = eltype(grid) + A = vars.usr_vars.A::T + b = vars.usr_vars.b::T + kf = vars.usr_vars.kf::T + σ² = vars.usr_vars.σ²::T + + kx,ky,kz = grid.kr, grid.l, grid.m + #ky = params.usr_params.ky + # "pointer" + ∂uxh∂t = view(N,:,:,:,params.ux_ind) + ∂uyh∂t = view(N,:,:,:,params.uy_ind) + ∂uzh∂t = view(N,:,:,:,params.uz_ind) + + # Set up of CUDA threads & block + threads = ( 32, 8, 1 ) #(9,9,9) + blocks = ( ceil(Int,size(N,1)/threads[1]), ceil(Int,size(N,2)/threads[2]), ceil(Int,size(N,3)/threads[3]) ) + + @cuda blocks = blocks threads = threads A99Force_Driving_CUDA!(∂uxh∂t, ∂uyh∂t, ∂uzh∂t, kx, ky, kz, + A, kf, σ², b) + + return nothing + end + + + function A99Force_Driving_CUDA!(∂uxh∂t,∂uyh∂t,∂uzh∂t,kx_,ky_,kz_,A,kf,σ²,b) + #define the i,j,k + x = (blockIdx().x - 1) * blockDim().x + threadIdx().x + y = (blockIdx().y - 1) * blockDim().y + threadIdx().y + z = (blockIdx().z - 1) * blockDim().z + threadIdx().z + + nx,ny,nz = size(∂uxh∂t) + if z ∈ (1:nz) && y ∈ (1:ny) && x ∈ (1:nx) + # Reason : https://github.com/FourierFlows/Fou/rierFlows.jl/issues/326 + if size(y,1) > 1 + kx,ky,kz = kx_[x], ky_[x,y], kz_[z] + else + @inbounds kx,ky,kz = kx_[x], ky_[y], kz_[z] + end + k = √(kx^2 + ky^2 + kz^2) + k⊥ = √(kx^2 + kz^2) + k⁻¹ = k > 0.0 ? 1/k : 0.0 + Fk = A*√(exp(-(k-kf)^2/σ²)/2/π)*k⁻¹ + + #e1y = k⊥ <= 0.0 ? 0.0 : -kx/k⊥; + #e2y = k⊥ <= 0.0 ? 0.0 : ky*kz/k⊥*k⁻¹ + #e2z = -k⊥*k⁻¹ + e1x = k⊥ <= 0.0 ? 0.0 : kz/k⊥ + e1z = k⊥ <= 0.0 ? 0.0 : -kx/k⊥; + + e2x = k⊥ <= 0.0 ? 0.0 : kx*ky/k⊥*k⁻¹ + e2y = -k⊥*k⁻¹ + e2z = k⊥ <= 0.0 ? 0.0 : kz*ky/k⊥*k⁻¹ + + eⁱᶿ = exp(rand()*2π*im) + Φ = rand()*π + gi = -tanh(b*(Φ - π/2))/tanh(b*π/2) + gi = abs(gi) >= 1.0 ? sign(gi)*1.0 : gi + + @inbounds ∂uxh∂t[x,y,z] += A*Fk*eⁱᶿ*gi*e1x + @inbounds ∂uzh∂t[x,y,z] += A*Fk*eⁱᶿ*gi*e1z + + eⁱᶿ = exp(rand()*2π*im) + gj = √(1 - gi^2) + + @inbounds ∂uxh∂t[x,y,z] += A*Fk*eⁱᶿ*gj*e2x + @inbounds ∂uyh∂t[x,y,z] += A*Fk*eⁱᶿ*gj*e2y + @inbounds ∂uzh∂t[x,y,z] += A*Fk*eⁱᶿ*gj*e2z + + if x == 1 || x == nx # the indexing need to change when applying CuFFTMp + # for rfft, the complex X[1] == X[N/2+1] == 0 + # Reason : https://github.com/FourierFlows/Fou/rierFlows.jl/issues/326 + @inbounds ∂uxh∂t[x,y,z] = real(∂uxh∂t[x,y,z]) + @inbounds ∂uyh∂t[x,y,z] = real(∂uyh∂t[x,y,z]) + @inbounds ∂uzh∂t[x,y,z] = real(∂uzh∂t[x,y,z]) + end + end + + return nothing + end + +end \ No newline at end of file diff --git a/src/pgen/A99LSForceDriving.jl b/src/pgen/A99LSForceDriving.jl new file mode 100644 index 0000000..14485ce --- /dev/null +++ b/src/pgen/A99LSForceDriving.jl @@ -0,0 +1,99 @@ +# ---------- +# Problem Generation Module : A99 Turbulence Module (Low Storage Version) +# ---------- + +mutable struct A99LS_vars{Atrans,T} + A :: T + b :: T + Fke2x :: Atrans + Fke2y :: Atrans + Fke2z :: Atrans +end + +function GetA99LSvars_And_function(::Dev, nx::Int,ny::Int,nz::Int; T = Float32, C =false) where Dev + + A = convert(T,1.0); + b = convert(T,1.0); + @devzeros Dev Complex{T} ( div(nx,2) + 1 , ny, nz) e2x e2y e2z + A99 = A99LS_vars(A,b,e2x,e2y,e2z); + + if C + return A99, A99ForceDriving_Compressible! + else + return A99, A99ForceDriving!; + end +end + +function A99ForceDriving!(N, sol, t, clock, vars, params, grid) + + # A99 Force + randN = typeof(N) <: Array ? Base.rand : CUDA.rand; + T = eltype(grid); + A = vars.usr_vars.A::T; + b = vars.usr_vars.b::T; + Fke2x, Fke2y, Fke2z = vars.usr_vars.Fke2x,vars.usr_vars.Fke2y,vars.usr_vars.Fke2z; + eⁱᶿ = vars.nonlinh1; + + @. eⁱᶿ .= exp(@.. im.*randN(T,grid.nkr,grid.nl,grid.nm)*2π); + @. N[:,:,:,params.ux_ind] += A*Fke2x*eⁱᶿ; + @. N[:,:,:,params.uy_ind] += A*Fke2y*eⁱᶿ; + @. N[:,:,:,params.uz_ind] += A*Fke2z*eⁱᶿ; + + return nothing +end + +function A99ForceDriving_Compressible!(N, sol, t, clock, vars, params, grid) + + # A99 Force with the support of compressibiltiy + randN = typeof(N) <: Array ? Base.rand : CUDA.rand; + T = eltype(grid); + A = vars.usr_vars.A::T; + b = vars.usr_vars.b::T; + Fke2x, Fke2y, Fke2z = vars.usr_vars.Fke2x,vars.usr_vars.Fke2y,vars.usr_vars.Fke2z; + eⁱᶿ = vars.nonlinh2; + + @. eⁱᶿ .= exp(@.. im.*randN(T,grid.nkr,grid.nl,grid.nm)*2π); + for (u_ind,Fki) in zip((params.ux_ind,params.uy_ind,params.uz_ind),(Fke2x,Fke2y,Fke2z)) + aᵢtoFᵢ!(view(N,:,:,:,u_ind), @.(A*Fki*eⁱᶿ) , vars, grid); + end + return nothing +end + +function SetUpLSFk(prob; kf = 2, P = 1,σ²= 1) + AT = Array; + grid = prob.grid; + kx,ky,kz = AT(grid.kr),AT(grid.l),AT(grid.m); + Lx,Ly,Lz = grid.Lx,grid.Ly,grid.Lz; + dx,dy,dz = grid.dx,grid.dy,grid.dz; + k⁻¹ = sqrt.(AT(grid.invKrsq)); + k = sqrt.(AT(grid.Krsq)); + k⊥ = @. √(kx^2 + ky^2); + dk⁻² = @. 1/(k+1)^2; + ∫Fkdk = sum(@. exp(-(k.-kf)^2/σ²)*dk⁻²) + A = sqrt(P*3*(Lx/dx)*(Ly/dy)*(Lz/dz)/∫Fkdk*(1/dx/dy/dz)); + Fk = @. A*√(exp(-(k.-kf)^2/σ²)/2/π)*k⁻¹; + # Reason : https://github.com/FourierFlows/FourierFlows.jl/issues/326 + @. Fk[1,:,:] .= 0; + + e2x = @. kx*kz/k⊥*k⁻¹; + e2y = @. ky*kz/k⊥*k⁻¹; + e2z = @. -k⊥*k⁻¹; + + e2x[isnan.(e2x)] .= 0; + e2y[isnan.(e2y)] .= 0; + e2z[isnan.(e2z)] .= 0; + + copyto!(prob.vars.usr_vars.Fke2x, @.. Fk*e2x); + copyto!(prob.vars.usr_vars.Fke2y, @.. Fk*e2y); + copyto!(prob.vars.usr_vars.Fke2z, @.. Fk*e2z); + return nothing; +end + +function aᵢtoFᵢ!(∂pᵢ∂t,aᵢh,vars,grid) + ρ = vars.ρ; + ldiv!(vars.nonlin1, grid.rfftplan, aᵢh); + @. vars.nonlin1*=ρ; + mul!(vars.nonlinh1, grid.rfftplan, vars.nonlin1); + @. ∂pᵢ∂t += vars.nonlinh1; + return nothing +end \ No newline at end of file diff --git a/src/pgen/ChoForceDriving.jl b/src/pgen/ChoForceDriving.jl deleted file mode 100644 index bac0723..0000000 --- a/src/pgen/ChoForceDriving.jl +++ /dev/null @@ -1,210 +0,0 @@ -# ---------- -# Problem Generation Module : Cho(2001) Turbulence Module -# ---------- - -mutable struct Cho_vars{Atrans,T} - Fk :: Atrans - s1y :: Atrans - s1z :: Atrans - s2x :: Atrans - s2y :: Atrans - s2z :: Atrans - Φ1 :: Atrans - Φ2 :: Atrans - kf :: T - P :: T -end - -function Get_Cho_vars_and_function(::Dev, nx::Int, ny::Int, nz::Int; T=Float32) where Dev - @devzeros Dev Complex{T} ( div(nx,2)+1, ny, nz) Φ1 Φ2 - @devzeros Dev Complex{T} ( div(nx,2)+1, ny, nz) Fk s1y s1z s2x s2y s2z; - return Cho_vars(Fk,s1y,s1z,s2x,s2y,s2z,Φ1,Φ2,T(0.0),T(0.0)), ChoForceDriving!; -end - -#=function ChoForceDriving!(N, sol, t, clock, vars, params, grid) - # Define the parameter from vars - T = eltype(grid); - eⁱᶿ = vars.nonlinh1; - Φ1,Φ2,Fk = vars.usr_vars.Φ1,vars.usr_vars.Φ2,vars.usr_vars.Fk; - s1y, s1z = vars.usr_vars.s1y,vars.usr_vars.s1z; - s2x, s2y, s2z = vars.usr_vars.s2x,vars.usr_vars.s2y,vars.usr_vars.s2z; - A,kf = copy(vars.usr_vars.P::T),vars.usr_vars.kf::T; - vi = params.ν; - dt = clock.dt; - A*= exp(-vi*kf^2*dt); - - # Actual computation - @. eⁱᶿ = exp.(im*(Φ1.+Φ2)./2); - @. N[:,:,:,params.ux_ind] += A.*eⁱᶿ.*( 0 .*cos.((Φ1.-Φ2)/2) + s2x.*sin.((Φ1.-Φ2)/2)); - @. N[:,:,:,params.uy_ind] += A.*eⁱᶿ.*(s1y.*cos.((Φ1.-Φ2)/2) + s2y.*sin.((Φ1.-Φ2)/2)); - @. N[:,:,:,params.uz_ind] += A.*eⁱᶿ.*(s1z.*cos.((Φ1.-Φ2)/2) + s2z.*sin.((Φ1.-Φ2)/2)); - # Large Scale Forcing - @. N[:,:,:,params.ux_ind] += Fk; - return nothing; -end=# - -function ChoForceDriving!(N, sol, t, clock, vars, params, grid) - # Define the parameter from vars - T = eltype(grid); - eⁱᶿ = vars.nonlinh1; - Φ1,Φ2,Fk = vars.usr_vars.Φ1,vars.usr_vars.Φ2,vars.usr_vars.Fk; - s1y, s1z = vars.usr_vars.s1y,vars.usr_vars.s1z; - s2x, s2y, s2z = vars.usr_vars.s2x,vars.usr_vars.s2y,vars.usr_vars.s2z; - A,kf = copy(vars.usr_vars.P::T),vars.usr_vars.kf::T; - vi = params.ν; - dt = clock.dt; - A*= exp(-vi*kf^2*dt); - - # Actual computation - @. eⁱᶿ = 0; - @. eⁱᶿ = exp.(im*(Φ1.+Φ2)./2); - for (u_ind,s1,s2) in zip([params.ux_ind,params.uy_ind,params.uz_ind],[0,s1y,s1z],[s2x,s2y,s2z]) - @. N[:,:,:,u_ind] += A.*eⁱᶿ.*( s1 .*cos.((Φ1.-Φ2)/2) + s2.*sin.((Φ1.-Φ2)/2)); - end - - # Large Scale Forcing - if minimum(mean(vars.ux,dims=1)[:]) > -1.0 - @. N[:,:,:,params.ux_ind] += Fk; - end - return nothing; -end - - -function Set_up_Cho_vars(prob; P = 1e7, kf = 15) - # Define the parameter will be used - grid = prob.grid; - vars = prob.vars; - nx,ny,nz = grid.nx,grid.ny,grid.nz; - Lx,Ly,Lz = grid.Lx,grid.Ly,grid.Lz; - dx,dy,dz = grid.dx,grid.dy,grid.dz; - kx,ky,kz = grid.kr,grid.l,grid.m; - T = eltype(grid); - # The 22 conponment - k_component = 22; - fox,foy,foz = zeros(Int32,k_component),zeros(Int32,k_component),zeros(Int32,k_component); - k = 1; - for θ ∈ [15,20,25].*π/180 #anisotropic turbulence - for ϕ ∈ [-25,-15,-5,0,5,15,25].*π/180 - fox[k] = round(Int32,kf*cos(θ)); - foy[k] = round(Int32,kf*sin(θ)*sin(ϕ)); - foz[k] = round(Int32,kf*sin(θ)*cos(ϕ)); - k+=1; - end - end - fox[22],foy[22],foz[22] = kf,0.0,0.0; - - # Set up vector set s1 s2 that ⊥ k_f - @devzeros typeof(CPU()) Complex{T} ( div(nx,2)+1, ny, nz) Φ1 Φ2 - @devzeros typeof(CPU()) Complex{T} ( div(nx,2)+1, ny, nz) Fk s1y s1z s2x s2y s2z - - kr,l,m = Array(grid.kr)[:],Array(grid.l)[:],Array(grid.m)[:]; - dx,dy,dz = grid.dx,grid.dy,grid.dz; - for k_i = 1:k_component - # index 1,2,3 -> i,j,k direction - rkx,rky,rkz = fox[k_i],foy[k_i],foz[k_i]; - kx = findall(kr .== rkx)[1]; - ky = findall(l .== rky)[1]; - kz = findall(m .== rkz)[1]; - ryz = √( rky^2 + rkz^2 ); - rxyz= √( rkx^2 + rky^2 +rkz^2); - if (ryz == 0.0) || (rxyz == 0.0) - s1y[kx,ky,kz] = 0.0 - s1z[kx,ky,kz] = 1.0 - s2x[kx,ky,kz] = 0.0 - s2y[kx,ky,kz] = 0.0 - s2z[kx,ky,kz] = 1.0 - else - s1y[kx,ky,kz] = rkz / ryz - s1z[kx,ky,kz] = -rky / ryz - s2x[kx,ky,kz] = -ryz / rxyz - s2y[kx,ky,kz] = rkx*rky / rxyz / ryz - s2z[kx,ky,kz] = rkx*rkz / rxyz / ryz - end - end - - Fk[1,2,1] = -10/dx/dy/dz; - #Fk[1,1,1] = 0/dx/dy/dz; - copyto!(prob.vars.usr_vars.Fk , Fk); - copyto!(prob.vars.usr_vars.s1y,s1y); - copyto!(prob.vars.usr_vars.s1z,s1z); - copyto!(prob.vars.usr_vars.s2x,s2x); - copyto!(prob.vars.usr_vars.s2y,s2y); - copyto!(prob.vars.usr_vars.s2z,s2z); - - # Work out the Φ conponement - randN = typeof(vars.usr_vars.Φ1) <: Array ? Base.rand : CUDA.rand; - Φ1 = rand(T,grid.nkr,grid.nl,grid.nm).*2π .+ 0*im; - Φ2 = rand(T,grid.nkr,grid.nl,grid.nm).*2π .+ 0*im; - copyto!(vars.usr_vars.Φ1,Φ1); - copyto!(vars.usr_vars.Φ2,Φ2); - - # Work the Amp of A - k = @. √(grid.Krsq); - k⊥ = @. √(kx^2 + ky^2); - dk⁻² = @. 1/(k+1)^2; - F = 0 .*vars.nonlinh1; - F[abs.(s1y).>0] .= 1; - F[abs.(s1z).>0] .= 1; - ∫Fkdk = sum(@. F*dk⁻²) - A = sqrt(P*3*(Lx/dx)*(Ly/dy)*(Lz/dz)/∫Fkdk*(1/dx/dy/dz)); - vars.usr_vars.P = A; - - return nothing; -end - -function Random_iterator!(prob) - #random generator ∈ [-1,1] - vars = prob.vars; - grid = prob.grid; - Rand = typeof(vars.usr_vars.Φ1) <: Array ? Base.rand : CUDA.rand; - randN(T,nx,ny,nz) = 2 .*(Rand(T,nx,ny,nz) .- 0.5); - - T = eltype(prob.grid); - Φ1,Φ2 = vars.usr_vars.Φ1,vars.usr_vars.Φ2; - Φ_changefraction = convert(T,0.02); - - # For each time step, slowly changing the amplitude or phase by 1 or 2% - copyto!(Φ1, Φ1.*( 1 .+ 2*π .*randN(T,grid.nkr,grid.nl,grid.nm).*Φ_changefraction)); - copyto!(Φ2, Φ2.*( 1 .+ 2*π .*randN(T,grid.nkr,grid.nl,grid.nm).*Φ_changefraction)); - return nothing -end - - -function SetUpFk_(prob; kf = [2], P = 1,σ²= 1,Rᵢ = [1.0]) - grid = prob.grid; - kx,ky,kz = grid.kr,grid.l,grid.m; - Lx,Ly,Lz = grid.Lx,grid.Ly,grid.Lz; - dx,dy,dz = grid.dx,grid.dy,grid.dz; - k⁻¹ = @. √(grid.invKrsq); - k = @. √(grid.Krsq); - k⊥ = @. √(kx^2 + ky^2); - dk⁻² = @. 1/(k+1)^2; - ∫Fkdk = 0; - for kfᵢ in kf - ∫Fkdk += sum(@. exp(-(k.-kfᵢ)^2/σ²)*dk⁻²) - end - - A = sqrt(P*3*(Lx/dx)*(Ly/dy)*(Lz/dz)/∫Fkdk*(1/dx/dy/dz)); - Fk = 0 .*copy(k); - for (kfᵢ,R) in zip(kf,Rᵢ) - @. Fk += R*A*√(exp(-(k.-kfᵢ)^2/σ²)/2/π)*k⁻¹; - end - - e1x = @. ky/k⊥; - e1y = @. -kx/k⊥; - e2x = @. kx*kz/k⊥*k⁻¹; - e2y = @. ky*kz/k⊥*k⁻¹; - e2z = @. -k⊥*k⁻¹; - - e1x[isnan.(e1x)] .= 0; - e1y[isnan.(e1y)] .= 0; - e2x[isnan.(e2x)] .= 0; - e2y[isnan.(e2y)] .= 0; - - copyto!(prob.vars.usr_vars.Fk, Fk); - copyto!(prob.vars.usr_vars.e1x,e1x); - copyto!(prob.vars.usr_vars.e1y,e1y); - copyto!(prob.vars.usr_vars.e2x,e2x); - copyto!(prob.vars.usr_vars.e2y,e2y); - copyto!(prob.vars.usr_vars.e2z,e2z); -end \ No newline at end of file diff --git a/src/pgen/ShearingBoxProblem.jl b/src/pgen/ShearingBoxProblem.jl new file mode 100644 index 0000000..de8d98a --- /dev/null +++ b/src/pgen/ShearingBoxProblem.jl @@ -0,0 +1,30 @@ +# ---------- +# Problem Generation Module : Shearingbox Module +# ---------- +function Setup_Shearingbox!(prob; q = 0.0, ν = 0.0) + @assert prob.flag.s == true + + grid = prob.grid; + T = eltype(grid) + params = prob.params; + usr_params = params.usr_params; + Lx,Ly = grid.Lx,grid.Ly; + + τΩ = abs(Lx/Ly/q) + usr_params.ν = T(ν) + usr_params.τΩ = T(τΩ) + usr_params.q = T(q) + copyto!(usr_params.ky₀ , grid.l) + + return nothing + +end + + +function Get_shear_profile(grid,q::AbstractFloat,Ω::AbstractFloat) + # U0 ≡ −qΩ \hat{y} - > - qΩ x + @devzeros typeof(CPU()) eltype(grid) (grid.nx, grid.ny, grid.nz) U₀x U₀y + @. U₀x = - q*Ω; + + return U₀x,U₀y +end \ No newline at end of file diff --git a/src/timestepper/HM89.jl b/src/timestepper/HM89.jl new file mode 100644 index 0000000..bab9e15 --- /dev/null +++ b/src/timestepper/HM89.jl @@ -0,0 +1,225 @@ +# ---------- +# Implicit timeStepper for EMHD simulation (Harned & Mikic, 1989, J. Computational Phys, 83, 1, pp. 1-15) +# ---------- + +struct HM89TimeStepper{T,TL} <: FourierFlows.AbstractTimeStepper{T} + F₀ :: T + F₁ :: T + B⁰ :: T + B¹ :: T + Bⁿ :: T + c :: TL +end + +function HM89TimeStepper(equation, dev::Device=CPU()) + @devzeros typeof(dev) equation.T equation.dims F₀ F₁ B⁰ B¹ Bⁿ + + c = (1//3, 15//16, 8//15) + + return HM89TimeStepper( F₀, F₁, B⁰, B¹, Bⁿ , c) +end + +function stepforward!(sol, clock, ts::HM89TimeStepper, equation, vars, params, grid) + HM89substeps!( sol, clock, ts, equation, vars, params, grid) + + clock.t += clock.dt + + clock.step += 1 + + return nothing +end + +function HM89substeps!(sol, clock, ts, equation, vars, params, grid) + # we solve the equation of + # B^{n+1} + (Δt)²(B₀·∇)²∇^2B^{n+1} = Bⁿ + (Δt)²(B₀·∇)^2∇^2Bⁿ - Δt∇×(J^{n+1/2}× B^{n+1/2}) + # using fix point method + square_mean(A,B,C) = mapreduce((x,y,z)->√(x*x+y*y+z*z),max,A,B,C) + + t, Δt, c = clock.t, clock.dt, ts.c + + B⁰, B¹, Bⁿ = ts.B⁰, ts.B¹, ts.Bⁿ + + ΔBh, B₀∇⁴B, ∇XJXB = ts.F₀, ts.F₀, ts.F₁ + + ΔBx, ΔBy, ΔBz = vars.bx, vars.by, vars.bz + + # check the mean field condition & determine the k₀ for later usage + mB = ( mean(vars.bx), mean(vars.by), mean(vars.bz) ) + i = findmax(mB)[2] + checkmB( mB, i ) + B₀ = mB[i] + k₀ = ifelse( i == 1, grid.kr, ifelse(i == 2, grid.l, grid.m ) ) + + # get B\^{n+1} guess from RK3 Method + copyto!(B⁰, sol) + LSRK3substeps!(sol, clock, ts, equation, vars, params, grid) + copyto!( B¹, sol) + dealias!(B¹, grid) + B_half = sol + + ε = 1.0; + err = 1e-4; + + while ε > err + + @. B_half = (B⁰ + B¹)*0.5 + + # get the ∇×(J × B) term + equation.calcN!(∇XJXB, B_half, t, clock, vars, params, grid) + + # hyper diffusion term + @. B_half = (B⁰ - B¹) + hyperdiffusionterm!(B₀∇⁴B, B_half, B₀, k₀, grid) + + # get the term B\^ n + 1 + @. Bⁿ = B⁰ + Δt^2*B₀∇⁴B - Δt*∇XJXB + dealias!(Bⁿ, grid) + + # compute the error + @. ΔBh = (Bⁿ - B¹) + ldiv!( ΔBx, grid.rfftplan, deepcopy( @view ΔBh[:,:,:,1] ) ) + ldiv!( ΔBy, grid.rfftplan, deepcopy( @view ΔBh[:,:,:,2] ) ) + ldiv!( ΔBz, grid.rfftplan, deepcopy( @view ΔBh[:,:,:,3] ) ) + ε = square_mean(ΔBx, ΔBy, ΔBz) + + # copy to Bⁿ to be B¹ + copyto!(B¹, Bⁿ) + + end + + copyto!(sol, B¹) + RK3diffusion!(sol, ts, clock, vars, params, grid) + DivFreeCorrection!(sol, vars, params, grid) + + ldiv!(vars.bx, grid.rfftplan, deepcopy(@view sol[:, :, :, params.bx_ind])) + ldiv!(vars.by, grid.rfftplan, deepcopy(@view sol[:, :, :, params.by_ind])) + ldiv!(vars.bz, grid.rfftplan, deepcopy(@view sol[:, :, :, params.bz_ind])) + + return nothing + +end + +function DivFreeCorrection!(sol, vars, params, grid) +#= + Possion Solver for periodic boundary condition + As in VP method, ∇ ⋅ B = 0 doesn't hold, B_{t+1} = ∇×Ψ + ∇Φ -> ∇ ⋅ B = ∇² Φ + We need to find Φ and remove it using a Poission Solver + Here we are using the Fourier Method to find the Φ + In Real Space, + ∇² Φ = ∇ ⋅ B + In k-Space, + ∑ᵢ -(kᵢ)² Φₖ = i∑ᵢ kᵢ(Bₖ)ᵢ + Φ = F{ i∑ᵢ kᵢ (Bₖ)ᵢ / ∑ᵢ (k²)ᵢ} +=# + + #find Φₖ + kᵢ,kⱼ,kₖ = grid.kr,grid.l,grid.m; + k⁻² = grid.invKrsq; + @. vars.nonlin1 *= 0; + @. vars.nonlinh1 *= 0; + ∑ᵢkᵢBᵢh_k² = vars.nonlinh1; + ∑ᵢkᵢBᵢ_k² = vars.nonlin1; + + # it is N not sol + @views bxh = sol[:, :, :, params.bx_ind]; + @views byh = sol[:, :, :, params.by_ind]; + @views bzh = sol[:, :, :, params.bz_ind]; + + @. ∑ᵢkᵢBᵢh_k² = -im*(kᵢ*bxh + kⱼ*byh + kₖ*bzh); + @. ∑ᵢkᵢBᵢh_k² = ∑ᵢkᵢBᵢh_k²*k⁻²; # Φₖ + + # B = B* - ∇Φ = Bᵢ - kᵢΦₖ + @. bxh -= im*kᵢ.*∑ᵢkᵢBᵢh_k²; + @. byh -= im*kⱼ.*∑ᵢkᵢBᵢh_k²; + @. bzh -= im*kₖ.*∑ᵢkᵢBᵢh_k²; + + return nothing +end + +function hyperdiffusionterm!(B₀∇⁴B, B, B₀, k₀, grid) + # + # hyper diffusion term from HM89 + # + + k² = grid.Krsq + @. B₀∇⁴B = B₀*k₀^2*k²*B*2.5e-1 + + return nothing +end + +function checkmB(mB, i) + @assert length(mB) == 3 + + for j = 1:3 + if i != j && mB[j] > 0.3 + error(" Only support single mean field driection! \n") + end + end + + return nothing +end + +function LSRK3substeps!(sol, clock, ts, equation, vars, params, grid) + # Low stoage 3 step RK3 method (LSRK3) + # F0 = dt F(0) + # p1 = p0 + c1 F0 + # F1 = dt*F(1) - F0*5/9 + # p2 = p0 + c2 F1 + # F2 = -153/128*F(1) + dt*F(2) + # p3 = p2 + c3*F2 + + t = clock.t + dt = clock.dt + c = ts.c + + equation.calcN!(ts.F₀, sol, t + dt, clock, vars, params, grid) + @. ts.F₀ *= dt + @. sol += ts.F₀*c[1]*dt + + equation.calcN!(ts.F₁, sol, t + dt, clock, vars, params, grid) + @. ts.F₁ *= dt + @. ts.F₁ -= 5/9*ts.F₀ + @. sol += c[2]*ts.F₁ + + # reuse F2 = F0 + equation.calcN!(ts.F₀, sol, t + dt, clock, vars, params, grid) + @. ts.F₀ *= dt + @. ts.F₀ -= 153/128*ts.F₁ + @. sol += c[3]*ts.F₀ + return nothing +end + +function RK3diffusion!(sol, ts, clock, vars, params, grid) + # LSKR3 for diffusion term + # F0 = dt F(0) + # p1 = p0 + c1 F0 + # F1 = dt*F(1) - F0*5/9 + # p2 = p0 + c2 F1 + # F2 = -153/128*F(1) + dt*F(2) + # p3 = p2 + c3*F2 + + t = clock.t + dt = clock.dt + c = ts.c + k² = grid.Krsq + η = params.η + + @. ts.F₀ = -η*k²*sol + @. ts.F₀ *= dt + @. sol += ts.F₀*c[1]*dt + + @. ts.F₁ = -η*k²*sol + @. ts.F₁ *= dt + @. ts.F₁ -= 5/9*ts.F₀ + @. sol += c[2]*ts.F₁ + + # reuse F2 = F0 + @. ts.F₀ = -η*k²*sol + @. ts.F₀ *= dt + @. ts.F₀ -= 153/128*ts.F₁ + @. sol += c[3]*ts.F₀ + + return nothing +end + + diff --git a/src/timestepper/eSSPIFRK3.jl b/src/timestepper/eSSPIFRK3.jl new file mode 100644 index 0000000..abeb71e --- /dev/null +++ b/src/timestepper/eSSPIFRK3.jl @@ -0,0 +1,116 @@ +# ---------- +# TimeStepper for Shearing Box Simulation +# ---------- +struct eSSPIFRK3TimeStepper{T,TL} <: FourierFlows.AbstractTimeStepper{T} + L₀ :: TL + L₁ :: TL + L₂ :: TL + L₃ :: TL + u₀ :: T + u₁ :: T + u₂ :: T + N₀ :: T + N₁ :: T + N₂ :: T +end + +function eSSPIFRK3TimeStepper(equation, dev::Device=CPU()) + @devzeros typeof(dev) equation.T equation.dims u₀ u₁ u₂ N₀ N₁ N₂ + @devzeros typeof(dev) equation.T equation.dims[1:end-1] L₀ L₁ L₂ L₃ + + return eSSPIFRK3TimeStepper(L₀, L₁, L₂, L₃, u₀, u₁, u₂, N₀, N₁, N₂) +end + +function getL!(Lᵢ, t, clock, vars, params, grid) + q = params.usr_params.q; + ν = params.usr_params.ν; + + kx,ky,kz = grid.kr,grid.l,grid.m + ky₀ = params.usr_params.ky₀ + k²xz = params.usr_params.k2xz + k² = vars.nonlinh1 + dt = t - clock.t + τ = params.usr_params.τ + dt + + @. ky = ky₀ + q*τ*kx + @. k²xz = kx^2 + kz^2 +# @. Lᵢ = -ν*(k²xz*ky + ky^3/3)/(q*kx) +# @. k² = k²xz + ky₀^2 +# @. @views Lᵢ[1,:,:] = -k²[1,:,:]*ν*τ + @. @views Lᵢ = -grid.Krsq*ν*τ + return nothing +end + +function stepforward!(sol, clock, ts::eSSPIFRK3TimeStepper, equation, vars, params, grid) + eSSPIFRK3substeps!(sol, clock, ts, equation, vars, params, grid) + clock.t += clock.dt + clock.step += 1 + return nothing +end + +function eSSPIFRK3substeps!(sol, clock, ts, equation, vars, params, grid) + + dt = clock.dt + t = clock.t + getL!(ts.L₀, t , clock, vars, params, grid) + getL!(ts.L₁, t + 2/3*dt, clock, vars, params, grid) + getL!(ts.L₂, t + 2/3*dt, clock, vars, params, grid) + getL!(ts.L₃, t + dt, clock, vars, params, grid) + + # Substep 1 + copyto!(ts.u₀, sol) + equation.calcN!(ts.N₀, sol, clock.t, clock, vars, params, grid) + eSSPIFRK3_step1!(ts.u₁, ts.u₀, ts.N₀, ts.L₀, ts.L₁, dt) + + # Substep 2 + t2 = clock.t + clock.dt*2/3 + equation.calcN!(ts.N₁, ts.u₁, t2, clock, vars, params, grid) + eSSPIFRK3_step2!(ts.u₂, ts.u₁, ts.u₀, ts.N₁, ts.L₀, ts.L₂, dt) + + # Substep 3 + t3 = clock.t + clock.dt + equation.calcN!(ts.N₂, ts.u₂, t2, clock, vars, params, grid) + eSSPIFRK3_step3!(sol, ts.u₀, ts.u₂, ts.N₀, ts.N₂, ts.L₀, ts.L₂, ts.L₃, dt) + + return nothing +end + +function eSSPIFRK3_step1!(u1::CuArray{Complex{T},4}, u0, N0, L0, L1, dt) where T + nf = size(u1)[end] + for i = 1:nf + eSSPIFRK3_step1!( view(u1,:,:,:,i), view(u0,:,:,:,i), view(N0,:,:,:,i), + L0, L1, dt) + end +end + +function eSSPIFRK3_step2!(u2::CuArray{Complex{T},4}, u1, u0, N1, L0, L2, dt) where T + nf = size(u1)[end] + for i = 1:nf + eSSPIFRK3_step2!(view(u2,:,:,:,i), view(u1,:,:,:,i), view(u0,:,:,:,i), view(N1,:,:,:,i), + L0, L2, dt) + end +end + +function eSSPIFRK3_step3!(sol::CuArray{Complex{T},4}, u2, u1, u0, L0, L2, N1, dt) where T + nf = size(u1)[end] + for i = 1:nf + eSSPIFRK3_step3!(view(sol,:,:,:,i), view(u0,:,:,:,i), view(u2,:,:,i), view(N0,:,:,:,i), view(N2,:,:,:,i), + L0, L2, L3, dt) + end +end + +function eSSPIFRK3_step1!(u1, u0, N0, L0, L1, dt) + @. u1 = exp(L1 - L0)*(u0 + 2/3*dt*N0) + return nothing +end + +function eSSPIFRK3_step2!(u2, u1, u0, N1, L0, L2, dt) + @. u2 = 2/3*exp(L2 - L0)*u0 + 1/3*u1 + 4/9*dt*N1 + return nothing +end + +function eSSPIFRK3_step3!(sol, u0, u2, N0, N2, L0, L2, L3, dt) + #u0 u1 u2 are the sub-step + @. sol = exp(L3 - L0)*(37/64*u0 + 5/32*dt*N0) + exp(L3 - L2)*(27/64*u2 + 9/16*dt*N2) + return nothing +end \ No newline at end of file diff --git a/src/timestepper/timestepper.jl b/src/timestepper/timestepper.jl new file mode 100644 index 0000000..8e07930 --- /dev/null +++ b/src/timestepper/timestepper.jl @@ -0,0 +1,6 @@ +include("eSSPIFRK3.jl") +include("HM89.jl") + +function stepforward!(sol, clock, timestepper, eqn, vars, params, grid) + FourierFlows.stepforward!(sol, clock, timestepper, eqn, vars, params, grid) +end \ No newline at end of file diff --git a/src/utils/GeometryFunction.jl b/src/utils/GeometryFunction.jl index 7931b33..3f8bdcd 100644 --- a/src/utils/GeometryFunction.jl +++ b/src/utils/GeometryFunction.jl @@ -5,12 +5,12 @@ export xy_to_polar """ + xy_to_polar(ux,uy) convert the vectors (B-field/velocity) from xyz coordinates to rθz coordinates Keyword arguments ================= - `ux/uy`: x/y conponment vector - `Lx/Ly` : length size of the problem -$(TYPEDFIELDS) """ function xy_to_polar(ux::Array,uy::Array;Lx=2π,Ly=Lx,T=Float32) # xyz Coordinetes -> rθz Coordinates diff --git a/src/utils/IC.jl b/src/utils/IC.jl index 21b43c0..a80bba8 100644 --- a/src/utils/IC.jl +++ b/src/utils/IC.jl @@ -3,13 +3,14 @@ # ---------- """ + Cylindrical_Mask_Function(grid) + Construct a Cylindrical Mask Function χ for VP method Keyword arguments ================= - `grid`: MHDFlows problem's grid - `R₂` : Outwards radius boundary - `R₁` : Inwards radius boundary -$(TYPEDFIELDS) """ function Cylindrical_Mask_Function(grid;R₂=0.82π,R₁=0.0π) nx,ny,nz = grid.nx,grid.ny,grid.nz; @@ -26,16 +27,19 @@ function Cylindrical_Mask_Function(grid;R₂=0.82π,R₁=0.0π) end """ + SetUpProblemIC!(prob) + function of setting up the initial condition of the problem Keyword arguments ================= - `prob`: MHDFlows problem +- `ρ` : density in real space - `ux/uy/uz` : velocity in real space - `bx/by/bz` : B-field in real space - `U₀x/U₀y/U₀z/B₀x/B₀y/B₀z` : VP method parameter -$(TYPEDFIELDS) """ -function SetUpProblemIC!(prob; ux = [], uy = [], uz =[], +function SetUpProblemIC!(prob; ρ = [], + ux = [], uy = [], uz =[], bx = [], by = [], bz =[], U₀x= [], U₀y= [], U₀z=[], B₀x= [], B₀y= [], B₀z=[]) @@ -43,15 +47,40 @@ function SetUpProblemIC!(prob; ux = [], uy = [], uz =[], vars = prob.vars; grid = prob.grid; params = prob.params; + if prob.flag.c + if ρ == [] + error("User declare compressibility but no density IC was set.") + else + @views sol₀ = sol[:, :, :, params.ρ_ind]; + copyto!(vars.ρ, ρ); + mul!(sol₀ , grid.rfftplan, vars.ρ); + end + end + if prob.dye.dyeflag + if ρ ==[] + warning("User declare the dye but no dye is set") + else + copyto!(prob.dye.ρ, ρ); + mul!(prob.dye.tmp.sol₀, grid.rfftplan, prob.dye.ρ); + end + end + # Copy the data to both output and solution array - for (uᵢ,prob_uᵢ,uᵢind) in zip([ux,uy,uz],[vars.ux,vars.uy,vars.uz], + if (! prob.flag.e) + for (uᵢ,prob_uᵢ,uᵢind) in zip([ux,uy,uz],[vars.ux,vars.uy,vars.uz], [params.ux_ind,params.uy_ind,params.uz_ind]) - if uᵢ != [] - @views sol₀ = sol[:, :, :, uᵢind]; - copyto!(prob_uᵢ,uᵢ); - mul!(sol₀ , grid.rfftplan, prob_uᵢ); + if uᵢ != [] + @views sol₀ = sol[:, :, :, uᵢind]; + copyto!(prob_uᵢ,uᵢ); + if prob.flag.c + mul!(sol₀ , grid.rfftplan, @. vars.ρ*prob_uᵢ); + else + mul!(sol₀ , grid.rfftplan, prob_uᵢ); + end + end end end + # copy b-field data if prob.flag.b for (bᵢ,prob_bᵢ,bᵢind) in zip([bx,by,bz],[vars.bx,vars.by,vars.bz], [params.bx_ind,params.by_ind,params.bz_ind]) @@ -62,6 +91,7 @@ function SetUpProblemIC!(prob; ux = [], uy = [], uz =[], end end end + # copy solid domin data if prob.flag.vp for (Uᵢ,prob_Uᵢ) in zip([U₀x,U₀y,U₀z], [params.U₀x,params.U₀y,params.U₀z]) @@ -81,24 +111,25 @@ end """ + DivFreeSpectraMap(Nx,Ny,Nz) + Construct a Div Free Spectra Vector Map with power-law relation Keyword arguments ================= - `Nx/Ny/Nz`: size of the Vector Map - `k0` : Slope of the Map - `b` : Anisotropy of the Map -$(TYPEDFIELDS) """ function DivFreeSpectraMap( Nx::Int, Ny::Int, Nz::Int; Lx = 2π, dev = CPU(), - P = 1, k0 = -5/3/2, b = 1, T = Float64) - grid = ThreeDGrid(dev; nx = Nx, Lx = Lx, ny=Ny, nz=Nz, T = T); - return DivFreeSpectraMap( grid; P = P, k0 = k0, b = b); + P = 1, k0 = -5/3/2, b = 1, T = Float64, k_peak = 0.0) + grid = ThreeDGrid(dev; nx = Nx, Lx = Lx, ny=Ny, nz=Nz, T = T,nthreads = 8); + return DivFreeSpectraMap( grid; k_peak = k_peak, P = P, k0 = k0, b = b); end function DivFreeSpectraMap( grid; - P = 1, k0 = -5/3/2, b = 1) + k_peak = 0.0, P = 1, k0 = -5/3/2, b = 1) T = eltype(grid); @devzeros typeof(grid.device) Complex{T} (grid.nkr,grid.nl,grid.nm) eⁱᶿ Fk Fxh Fyh Fzh @@ -113,7 +144,8 @@ function DivFreeSpectraMap( grid; dk⁻² = @. 1/(k+1)^2; Fk = @. k.^(k0); CUDA.@allowscalar Fk[1,1,1] = 0.0; - + @. Fk[1,:,:] .= 0; + Fk[k.1) + x=1 + end; + if (x<-1) + x=-1 + end; + return acos(x) +end + +function t(a1,a2,b1,b2) + x = (a1,a2)⋅(b1,b2)/√(s(a1,a2)*s(b1,b2)); + if (x>1) + x=1 + end; + if (x<-1) + x=-1 + end; + return acos(x) +end + +RoundUpInt(x::Number) = round(Int,x,RoundUp) +RoundInt(x::Number) = round(Int,x) +getind(kll::Number,kpp::Number,Rx::Number,Ry::Number) = (RoundInt(kll),RoundInt(kpp)) + +#================================== Main Function =========================================# + +#Auto-Correlation function for 2D/3D **periodic** Map/Cube +CF(V::Cube) = fftshift((real(ifft(abs.(fft(V)).^2)))); + +#provding 2D/3D 2 point structure point function for scalar +#functional form: SF(R) = <|V(x+R)-V(x)|^2> +#Note : R is 3D vector +SFC(V) = 2*(mean(V).-CF(V)); + +# provding 3D B-field 2 point structure function for vector (iv,jv,kv) +# Global Mode For strong B-field case +# Local Mode For weak B-field case +function SFr(iv,jv,kv, ib,jb,kb, mode;GPU = true, r=100,Nseed=500) + print("mode = $(mode), GPU acceleration = $(GPU)") + if mode == "Global" + SFVr = SFr_Global(iv,jv,kv,ib,jb,kb) + elseif mode == "Local" && GPU + SFVr = SFr_local_GPU(iv,jv,kv,ib,jb,kb; Nseed = Nseed) + elseif mode == "Local" && !GPU + SFVr = SFr_local_GPU(iv,jv,kv,ib,jb,kb; r = r, Nseed = Nseed) + end + return SFVr +end + + +# 2 point radial structure function for 3D peroderic simulation +function SF₂1D(Vx::Cube,Vz::Cube,Vy::Cube) + Nx,Ny,Nz = size(Vx); + R = sqrt(s(div(Nx,2),div(Ny,2),div(Nz,2))); + + #get the structure function + SFVx = SFC(Vx); + SFVy = SFC(Vy); + SFVz = SFC(Vz); + #get the vector structure function + SFV = @. SFVx + SFVy + SFVz; + #declaring the output + R = RoundUpInt(R); + Mask = zeros(2*R); + SFVr = zeros(2*R); + + for k in 1:Nz, j in 1:Ny, i in 1:Nx + # get the k vector + idx = i-div(Nx,2); + jdx = j-div(Ny,2); + kdx = k-div(Nz,2); + kk = round(Int,sqrt(s(idx,jdx,kdx))) + if kk>0 + Mask[kk] += 1; + SFVr[kk] += SFV[i,j,k]; + end + end + SFVr./=Mask; + SFVr +end + +#provding 2 point Global structure point function for vector (Vx,Vy,Vz) +#Note : X-axis means prallel to B-field, Y-axis means perpendicular to B-field +function SFr_Global(Vx::Cube,Vz::Cube,Vy::Cube,bx::Cube,by::Cube,bz::Cube) + Nx,Ny,Nz = size(Vx); + R = sqrt(s(div(Nx,2),div(Ny,2),div(Nz,2))); + + #get the mean field + mbx= mean(bx); + mby= mean(by); + mbz= mean(bz); + + #get the structure function + SFVx = SFC(Vx); + SFVy = SFC(Vy); + SFVz = SFC(Vz); + #get the vector structure function + SFV = @. SFVx + SFVy + SFVz; + #declaring the output + Rx,Ry = RoundUpInt(R), RoundUpInt(R); + Mask = zeros((Rx+1,Ry+1)); + SFVr = zeros((Rx+1,Ry+1)); + + for k in 1:Nz, j in 1:Ny, i in 1:Nx + # get the k vector + idx = i-div(Nx,2); + jdx = j-div(Ny,2); + kdx = k-div(Nz,2); + kk = sqrt(s(idx,jdx,kdx)); + if kk>0 + #get the θ between b unit vector and k vector + θ = t(mbx,mby,mbz,idx,jdx,kdx) + + #get the 2D vector parallel and perpendicular to B-field + kll = abs(kk*cos(θ)); + kpp = abs(kk*sin(θ)); + + rpar,rperp = getind(kll,kpp,Rx,Ry).+1; #prob2 + Mask[rpar,rperp] += 1; + SFVr[rpar,rperp] += SFV[i,j,k]; + end + end + SFVr./=Mask; + SFVr +end + +#provding 2D 2 point local structure point function for vector (iv,jv,kv) +#Note : X-axis means prallel to B-field, Y-axis means perpendicular to B-field +@inline function SFr_local_CPU(iv::Array{T,3},jv::Array{T,3},kv::Array{T,3}, + ib::Array{T,3},jb::Array{T,3},kb::Array{T,3}; Nseed=600,r=100) where T + #println("Excepted waiting time ~ 0.5s for r=100, Nseed=1 ") + t_s = round(0.5*Nseed*(r/100)^3,digits=1); + #println("You waiting time ~ ",t_s,"s for r =",r,", N=",Nseed); + nx,ny,nz = size(iv); + x0,y0,z0 = div(nx,2),div(nx,2), div(nx,2); + x_seed = rand(r+1:nx-r,(Nseed)); + y_seed = rand(r+1:ny-r,(Nseed)); + z_seed = rand(r+1:nz-r,(Nseed)); + mb = zeros(3); + + # get the size of the structure function array + R = sqrt(3*(r+1)^2); + Rx,Ry = round(Int,R,RoundUp),round(Int,R,RoundUp); + + # declaring the output + Mask = zeros((Rx+2,Ry+2)); + SFVr = zeros((Rx+2,Ry+2)); + + p = Progress(Nseed, + barglyphs=BarGlyphs('|','█', ['▁' ,'▂' ,'▃' ,'▄' ,'▅' ,'▆', '▇'],' ','|',), + barlen=10, showspeed=true); + + @inbounds begin + Threads.@threads for seed = 1:Nseed + xs = x_seed[seed]::Int; + ys = y_seed[seed]::Int; + zs = z_seed[seed]::Int; + iv0,jv0,kv0 = iv[xs,ys,zs]::T,jv[xs,ys,zs]::T,kv[xs,ys,zs]::T; + ib0,jb0,kb0 = ib[xs,ys,zs]::T,jb[xs,ys,zs]::T,kb[xs,ys,zs]::T; + for k = zs-r : zs+r + kdx = k-zs; + for j = ys-r : ys+r + jdx = j-ys; + @simd for i = xs-r:xs+r + idx = i-xs; + kk = sqrt(s(idx,jdx,kdx))::Float64; + if kk > 0 + @muladd begin + ibi, jbi, kbi = ib[i,j,k]::T,jb[i,j,k]::T,kb[i,j,k]::T; + ivi, jvi, kvi = iv[i,j,k]::T,jv[i,j,k]::T,kv[i,j,k]::T; + #let the θ between b unit vector and k vector + mb1 = (ib0+ibi)*0.5; + mb2 = (jb0+jbi)*0.5; + mb3 = (kb0+kbi)*0.5; + θ = t(mb1,mb2,mb3,idx,jdx,kdx); + #get the 2D vector parallel and perpendicular to B-field + kll = abs(kk*cos(θ)); + kpp = abs(kk*sin(θ)); + #get the 2D vector parallel and perpendicular to B-field + rpar = round(Int,kll); + rperp = round(Int,kpp); + Mask[rpar+1,rperp+1] += 1; + SFVr[rpar+1,rperp+1] += s(iv0-ivi,jv0-jvi,kv0-kvi); + end + end + end + end + end + next!(p) + end + end + SFVr./=Mask + return SFVr; +end + +function SFr_local_GPU(iv,jv,kv,ib,jb,kb; Nseed=1000) + if length(CUDA.devices()) > 0 + nx,ny,nz = size(iv); + x_pairs = CuArray((rand(1:nx,(Nseed)))) + y_pairs = CuArray((rand(1:ny,(Nseed)))) + z_pairs = CuArray((rand(1:nz,(Nseed)))) + # Define the output array + R = √((nx/2)^2+(ny/2)^2+(nz/2)^2); + Rx,Ry = round(Int,R,RoundUp),round(Int,R,RoundUp); + Mask = CUDA.zeros(Float32,(Rx+2,Ry+2)); + SFVr = CUDA.zeros(Float32,(Rx+2,Ry+2)); + + threads = ( 32, 8, 1) + blocks = ( ceil(Int,size(iv,1)/threads[1]), ceil(Int,size(jv,2)/threads[2]), ceil(Int,size(kv,3)/threads[3])) + CUDA.@time begin + @cuda blocks = blocks threads = threads local_SF_CUDA!(CuArray(iv),CuArray(jv),CuArray(kv), + CuArray(ib),CuArray(jb),CuArray(kb), + x_pairs,y_pairs,z_pairs, + Mask,SFVr,R) + end + return (Array(SFVr)./Array(Mask)) + else + error("No GPU have been found!\n") + return nothing + end +end + +#CUDA kenerl function +function local_SF_CUDA!(iv::CuArray{T,3},jv::CuArray{T,3},kv::CuArray{T,3}, + ib::CuArray{T,3},jb::CuArray{T,3},kb::CuArray{T,3}, + xps,yps,zps, + Mask,SFVr,R) where T + #define the i,j,k + i = (blockIdx().x - 1) * blockDim().x + threadIdx().x + j = (blockIdx().y - 1) * blockDim().y + threadIdx().y + k = (blockIdx().z - 1) * blockDim().z + threadIdx().z + if i < size(iv,1) && j < size(iv,2) && k < size(iv,3) + @inbounds ib0, jb0, kb0 = ib[i,j,k],jb[i,j,k],kb[i,j,k]; + @inbounds iv0, jv0, kv0 = iv[i,j,k],jv[i,j,k],kv[i,j,k]; + for ri = 1:length(xps) + @inbounds xp,yp,zp = xps[ri],yps[ri],zps[ri] + idx, jdx, kdx = (xp - i), (yp - j), (zp - k) + kk = √(idx*idx + jdx*jdx + kdx*kdx); + kk = kk > R ? R - kk : kk + if R > kk > 0 + ibi, jbi, kbi = ib[xp,yp,zp],jb[xp,yp,zp],kb[xp,yp,zp]; + ivi, jvi, kvi = iv[xp,yp,zp],jv[xp,yp,zp],kv[xp,yp,zp]; + #let the θ between b unit vector and k vector + mb1,mb2,mb3 = (ib0+ibi)*0.5,(jb0+jbi)*0.5,(kb0+kbi)*0.5 + t = (mb1*idx + mb2*jdx + mb3*kdx)/sqrt(mb1^2+mb2^2+mb3^2)/sqrt(idx^2+jdx^2+kdx^2) + t = t > 1 ? 1 : t < -1 ? -1 : t + θ = acos(t) + #get the 2D vector parallel and perpendicular to B-field + kll = abs(kk*cos(θ)); + kpp = abs(kk*sin(θ)); + #get the 2D vector parallel and perpendicular to B-field + rpar = round(Int,kll); + rperp = round(Int,kpp); + @inbounds Mask[rpar+1,rperp+1] += 1; + @inbounds SFVr[rpar+1,rperp+1] += sqrt((iv0-ivi)^2 + (jv0-jvi)^2 + (kv0-kvi)^2); + end + end + end + return nothing +end + +# Fitting Related function +# Contour function +function Getcontour(V::Mat,levels;cmap="Blue_r",Conmap="winter") + imshow(V,cmap=cmap) + Nx,Ny = size(V); + A = contour(V,levels=levels,colors="black") + axis([1,Ny,1,Nx]) + Conlevel = length(A.allsegs) + x = zeros(Float64,Conlevel); + y = zeros(Float64,Conlevel); + for i = 1:Conlevel + if length(A.allsegs[i])>0 + if (A.allsegs[i][1][1,1]!=0 && A.allsegs[i][end,end]!=0) + x[i],y[i] = NaN,NaN; + end + x[i],y[i] = A.allsegs[i][1][1,end],A.allsegs[i][1][end,1] + else + x[i],y[i] = NaN,NaN; + end + end + x[.~isnan.(y)],y[.~isnan.(y)] +end + +function fitline(xx::Array,yy::Array,label) + ind = findall((xx.>0).&(yy.>0)); + x = xx[ind]; + y = yy[ind]; + line(x,p)=p[1].+x.*p[2]; + p = [0,y[2]-y[1]]; + xxx=curve_fit(line,x,y,p).param; + m,C = round(xxx[2],digits=2),round(10^(xxx[1]),digits=3) + plot([10.0].^x,[10.0].^line(x,xxx),label="α = $m , A = $C, "*label); + loglog([10.0].^x,[10.0].^y,"o") + legend() + return xxx +end + +end \ No newline at end of file diff --git a/src/utils/UserInterface.jl b/src/utils/UserInterface.jl index d846801..320e6bb 100644 --- a/src/utils/UserInterface.jl +++ b/src/utils/UserInterface.jl @@ -25,6 +25,8 @@ function WellcomeMessage2() end +# Function of computing the KE and ME +∑²(iv,jv,kv) = mapreduce((x,y,z)->(x^2 + y^2 + z^2),+,iv,jv,kv) # Static dashboard for print n,KE,ME function Static_Dashbroad(prob, step_over_check_loop_number::Number); @@ -36,20 +38,24 @@ function Static_Dashbroad(prob, step_over_check_loop_number::Number); if step_over_check_loop_number == 0 if (prob.flag.b == true) - KE, ME = ProbDiagnostic(prob); - KE_,ME_ = string(KE),string(ME); - for i = 1:8-length(string(KE_));KE_= " "*KE_;end - println(" n = $nn, t = $tt, KE = $KE_, ME = $(ME)"); - + if prob.flag.e == true + KE, ME = ProbDiagnostic(prob); + KE_,ME_ = string(KE),string(ME); + for i = 1:8-length(string(KE_));KE_= " "*KE_;end + for i = 1:8-length(string(ME_));ME_= " "*ME_;end + println(" n = $nn, t = $tt, KE = $KE_, ME = $(ME)"); + else + ME = ProbDiagnostic(prob); + ME_ = string(ME); + for i = 1:8-length(string(ME_));ME_= " "*ME_;end + println(" n = $nn, t = $tt, ME = $ME_") + end else KE = ProbDiagnostic(prob); - KE_ = string(KE),string(ME); - for i = 1:8-length(string(KE));KE= " "*KE;end - for i = 1:8-length(string(ME));ME= " "*ME;end + KE_ = string(KE); + for i = 1:8-length(string(KE_));KE_= " "*KE_;end println(" n = $nn, t = $tt, KE = $KE_") - end - isnan(KE) ? error("detected NaN! Quit the simulation right now.") : nothing; end return nothing @@ -59,21 +65,20 @@ end function ProbDiagnostic(prob) dx,dy,dz = diff(prob.grid.x)[1],diff(prob.grid.y)[1],diff(prob.grid.z)[1]; dV = dx*dy*dz; - vx,vy,vz = prob.vars.ux,prob.vars.uy,prob.vars.uz; - # if prob.flag.vp - # χ = prob.params.χ; - # KE = string(round(sum(vx[χ.==0].^2+vy[χ.==0].^2 + vz[χ.==0].^2)*dV,sigdigits=3)); - #else - KE = round(sum(vx.^2+vy.^2 + vz.^2)*dV,sigdigits=3); - # end - - isnan(KE) ? error("detected NaN! Quit the simulation right now.") : nothing; - + if !prob.flag.e + vx,vy,vz = prob.vars.ux,prob.vars.uy,prob.vars.uz; + KE = round(∑²(vx,vy,vz)*dV,sigdigits=3); + isnan(KE) ? error("detected NaN! Quit the simulation right now.") : nothing; + end if (prob.flag.b == true) bx,by,bz = prob.vars.bx,prob.vars.by,prob.vars.bz; - ME = round(sum(bx.^2+by.^2 + bz.^2)*dV,sigdigits=3); - - return KE, ME + ME = round(∑²(bx,by,bz)*dV,sigdigits=3); + if !prob.flag.e + return KE, ME + else + isnan(ME) ? error("detected NaN! Quit the simulation right now.") : nothing; + return ME + end else return KE end @@ -81,18 +86,24 @@ function ProbDiagnostic(prob) end # function for updating dynamical dashboard -function Dynamical_dashboard(prob,prog,N₀,t₀) +function Dynamic_Dashboard(prob,prog,N₀,t₀) generate_showvalues(iter, Stats) = () -> [(:Progress,iter), (:Statistics,stats)]; n = prob.clock.step; - t = round(prob.clock.t,sigdigits=3); - iter = "iter/Nₒ = $n/$(N₀), t/t₀ = $t/$(t₀)" + t = round( prob.clock.t,sigdigits=3); + dt = round(prob.clock.dt,sigdigits=3); + iter = "iter/Nₒ = $n/$(N₀), t/t₀ = $t/$(t₀), dt = $(dt)" if prob.flag.b - KE, ME = ProbDiagnostic(prob); - stats = "KE = $(KE), ME = $(ME)" + if prob.flag.e + ME = ProbDiagnostic(prob); + stats = "ME = $(ME)" + else + KE, ME = ProbDiagnostic(prob); + stats = "KE = $(KE), ME = $(ME)" + end else KE = ProbDiagnostic(prob); stats = "KE = $(KE)" end ProgressMeter.next!(prog; showvalues = generate_showvalues(iter,stats)); return nothing -end \ No newline at end of file +end diff --git a/src/utils/VectorCalculus.jl b/src/utils/VectorCalculus.jl index 8f23a82..a74ddfb 100644 --- a/src/utils/VectorCalculus.jl +++ b/src/utils/VectorCalculus.jl @@ -2,6 +2,16 @@ # Vector Calculus Module, Only work on peroideric boundary! # ---------- +""" + Curl(B1,B2,B3;Lx=2π) + +Funtion of computing ∇ × A⃗ using the fourier method + Keyword arguments +================= +- `B1/B2/B3`: 3D i/j/k vector field array +- `Lx/Ly/Lz`: Length Scale for the box(T type: Int) +- `T` : Data Type of the input Array +""" function Curl(B1::Array,B2::Array,B3::Array; Lx = 2π, Ly = Lx, Lz = Lx,T = Float32) # Wrapper for Curl Function @@ -40,6 +50,16 @@ function Curl(B1,B2,B3,grid) return cB1,cB2,cB3; end +""" + Div(B1,B2,B3;Lx=2π) + +Funtion of computing ∇ ⋅ ⃗A⃗using the fourier method + Keyword arguments +================= +- `B1/B2/B3`: 3D i/j/k vector field array +- `Lx/Ly/Lz`: Length Scale for the box(T type: Int) +- `T` : Data Type of the input Array +""" function Div(B1::Array,B2::Array,B3::Array; Lx = 2π, Ly = Lx, Lz = Lx,T = Float32) nx,ny,nz = size(B1); @@ -81,30 +101,30 @@ function ∂i(B1::Array, direction; Lx = 2π, Ly = Lx, Lz = Lx,T = eltype(B1)) end function ∂i(B1::Array,grid, direction) - # funtion of computing x/y/z-direction of ∇̇ ⋅ Vector using the fourier method - # fft(∂_i(Vector)) -> im * k_i ⋅ V - - nx,ny,nz = size(B1); - dev = typeof(B1) <: Array ? CPU() : GPU(); - T = eltype(grid); + # funtion of computing x/y/z-direction of ∇̇ ⋅ Vector using the fourier method + # fft(∂_i(Vector)) -> im * k_i ⋅ V - @devzeros typeof(dev) Complex{T} (div(nx,2)+1,ny,nz) B1h - @devzeros typeof(dev) T ( nx,ny,nz) cB1 - - mul!(B1h, grid.rfftplan, B1); - kx,ky,kz = grid.kr,grid.l,grid.m; - if direction == "x" - @. B1h = im*kx*B1h - elseif direction == "y" - @. B1h = im*ky*B1h - elseif direction =="z" - @. B1h = im*kz*B1h - else - error("Wrong driection declared") - end - ldiv!(cB1, grid.rfftplan, B1h); + nx,ny,nz = size(B1); + dev = typeof(B1) <: Array ? CPU() : GPU(); + T = eltype(grid); - return cB1 + @devzeros typeof(dev) Complex{T} (div(nx,2)+1,ny,nz) B1h + @devzeros typeof(dev) T ( nx,ny,nz) cB1 + + mul!(B1h, grid.rfftplan, B1); + kx,ky,kz = grid.kr,grid.l,grid.m; + if direction == "x" + @. B1h = im*kx*B1h + elseif direction == "y" + @. B1h = im*ky*B1h + elseif direction =="z" + @. B1h = im*kz*B1h + else + error("Wrong driection declared") + end + ldiv!(cB1, grid.rfftplan, B1h); + + return cB1 end @@ -112,6 +132,16 @@ end #∇·(A1,A2,A3;Lx = 2π, Ly = Lx, Lz = Lx,T = eltype(A1)) = Div(A1,A2,A3;Lx = Lx, Ly = Ly, Lz = Lz,T = eltype(A1)); +""" + LaplaceSolver(B) + +Funtion of Solving ΔΦ = B using the fourier method + Keyword arguments +================= +- `B`: 3D scalar array +- `Lx/Ly/Lz`: Length Scale for the box(T type: Int) +- `T` : Data Type of the input Array +""" function LaplaceSolver(B; Lx=2π, Ly = Lx, Lz = Lx, T = Float32) nx,ny,nz = size(B); grid = GetSimpleThreeDGrid(nx, Lx, ny, Ly, nz, Lz, T = T); @@ -148,48 +178,4 @@ end function Dotproduct(A1,A2,A3,B1,B2,B3) return A1.*B1 + A2.*B2 + A3.*B3 -end - -function DivVCorrection!(ux,uy,uz,grid) -#= - Possion Solver for periodic boundary condition - As in VP method, ∇ ⋅ V = 0 may not hold, V = ∇×Ψ + ∇Φ -> ∇ ⋅ V = ∇² Φ - We need to find Φ and remove it using a Poission Solver - Here we are using the Fourier Method to find the Φ - In Real Space, - ∇² Φ = ∇ ⋅ V - In k-Space, - ∑ᵢ -(kᵢ)² Φₖ = i∑ᵢ kᵢ(Vₖ)ᵢ - Φₖ = i∑ᵢ kᵢ(Vₖ)ᵢ/k² - Vⱼ_new = Vₖⱼ + kⱼ i∑ᵢ kᵢ(Vₖ)ᵢ/k²; -=# - - T = eltype(grid); - nx,ny,nz = grid.nx,grid.ny,grid.nz; - uxh = zeros(Complex{T},(div(nx,2)+1,ny,nz)); - uyh = zeros(Complex{T},(div(nx,2)+1,ny,nz)); - uzh = zeros(Complex{T},(div(nx,2)+1,ny,nz)); - mul!(uxh, grid.rfftplan, ux); - mul!(uyh, grid.rfftplan, uy); - mul!(uzh, grid.rfftplan, uz); - - #find Φₖ - kᵢ,kⱼ,kₖ = grid.kr,grid.l,grid.m; - k⁻² = grid.invKrsq; - ∑ᵢkᵢUᵢh_k² = 0 .*copy(uxh); - ∑ᵢkᵢUᵢ_k² = 0 .*copy(ux); - - ∑ᵢkᵢUᵢh_k² = @. im*(kᵢ*uxh + kⱼ*uyh + kₖ*uzh); - ∑ᵢkᵢUᵢh_k² = @. -∑ᵢkᵢUᵢh_k²*k⁻²; # Φₖ - - # B = B* - ∇Φ = Bᵢ - kᵢΦₖ - uxh .-= kᵢ.*∑ᵢkᵢUᵢh_k²; - uyh .-= kⱼ.*∑ᵢkᵢUᵢh_k²; - uzh .-= kₖ.*∑ᵢkᵢUᵢh_k²; - - #Update to Real Space vars - ldiv!(ux, grid.rfftplan, deepcopy(uxh));# deepcopy() since inverse real-fft destroys its input - ldiv!(uy, grid.rfftplan, deepcopy(uyh));# deepcopy() since inverse real-fft destroys its input - ldiv!(uz, grid.rfftplan, deepcopy(uzh));# deepcopy() since inverse real-fft destroys its input - return ux,uy,uz -end +end \ No newline at end of file diff --git a/src/utils/func.jl b/src/utils/func.jl index faaa9b5..18bad47 100644 --- a/src/utils/func.jl +++ b/src/utils/func.jl @@ -13,15 +13,15 @@ Construct a Cylindrical Mask Function χ for VP method $(TYPEDFIELDS) """ function Cylindrical_Mask_Function(grid;R₂=0.82π,R₁=0.0π) - nx,ny,nz = grid.nx,grid.ny,grid.nz; - x,y,z = grid.x,grid.y,grid.z; - S = BitArray(undef, nx::Int,ny::Int,nz::Int); + nx,ny,nz = grid.nx,grid.ny,grid.nz + x,y,z = grid.x,grid.y,grid.z + S = BitArray(undef, nx::Int,ny::Int,nz::Int) for k ∈ 1:nz::Int, j ∈ 1:ny::Int,i ∈ 1:nx::Int - xᵢ,yᵢ,zᵢ = x[i]::AbstractFloat,y[j]::AbstractFloat,z[k]::AbstractFloat; - Rᵢ = √(xᵢ^2+yᵢ^2); + xᵢ,yᵢ,zᵢ = x[i]::AbstractFloat,y[j]::AbstractFloat,z[k]::AbstractFloat + Rᵢ = √(xᵢ^2+yᵢ^2) # S = 0 if inside fluid domain while S = 1 in the solid domain - S[i,j,k] = (R₂ >= Rᵢ >= R₁) ? 0 : 1; + S[i,j,k] = (R₂ >= Rᵢ >= R₁) ? 0 : 1 end return S end @@ -39,39 +39,39 @@ function SetUpProblemIC!(prob; ux = [], uy = [], uz =[], bx = [], by = [], bz =[], U₀x= [], U₀y= [], U₀z=[], B₀x= [], B₀y= [], B₀z=[]) - sol = prob.sol; - vars = prob.vars; - grid = prob.grid; + sol = prob.sol + vars = prob.vars + grid = prob.grid params = prob.params; # Copy the data to both output and solution array for (uᵢ,prob_uᵢ,uᵢind) in zip([ux,uy,uz],[vars.ux,vars.uy,vars.uz], [params.ux_ind,params.uy_ind,params.uz_ind]) if uᵢ != [] - @views sol₀ = sol[:, :, :, uᵢind]; - copyto!(prob_uᵢ,uᵢ); - mul!(sol₀ , grid.rfftplan, prob_uᵢ); + @views sol₀ = sol[:, :, :, uᵢind] + copyto!(prob_uᵢ,uᵢ) + mul!(sol₀ , grid.rfftplan, prob_uᵢ) end end if prob.flag.b for (bᵢ,prob_bᵢ,bᵢind) in zip([bx,by,bz],[vars.bx,vars.by,vars.bz], [params.bx_ind,params.by_ind,params.bz_ind]) if bᵢ != [] - @views sol₀ = sol[:, :, :, bᵢind]; - copyto!(prob_bᵢ,bᵢ); - mul!(sol₀ , grid.rfftplan, prob_bᵢ); + @views sol₀ = sol[:, :, :, bᵢind] + copyto!(prob_bᵢ,bᵢ) + mul!(sol₀ , grid.rfftplan, prob_bᵢ) end end end if prob.flag.vp for (Uᵢ,prob_Uᵢ) in zip([U₀x,U₀y,U₀z], [params.U₀x,params.U₀y,params.U₀z]) - Uᵢ == [] ? nothing : copyto!(prob_Uᵢ,Uᵢ); + Uᵢ == [] ? nothing : copyto!(prob_Uᵢ,Uᵢ) end if prob.flag.b for (Bᵢ,prob_Bᵢ) in zip([B₀x,B₀y,B₀z], [params.B₀x,params.B₀y,params.B₀z]) - Bᵢ == [] ? nothing : copyto!(prob_Bᵢ,Bᵢ); + Bᵢ == [] ? nothing : copyto!(prob_Bᵢ,Bᵢ) end end end diff --git a/src/utils/utils.jl b/src/utils/utils.jl index 00bfde5..f498b12 100644 --- a/src/utils/utils.jl +++ b/src/utils/utils.jl @@ -12,8 +12,8 @@ end Base.eltype(grid::SimpleGrid) = eltype(grid.k); function GetSimpleThreeDGrid(nx = 64, Lx = 2π, ny = nx, Ly = Lx, nz = nx, Lz = Lx; - nthreads=Sys.CPU_THREADS, effort=FFTW.MEASURE, - T=Float64, ArrayType=Array) + nthreads=Threads.nthreads(), effort=FFTW.MEASURE, + T=Float64, ArrayType=Array,dev=CPU()) nk = nx nl = ny nm = nz @@ -36,4 +36,141 @@ function GetSimpleThreeDGrid(nx = 64, Lx = 2π, ny = nx, Ly = Lx, nz = nx, Lz = rfftplan = plan_rfft(ArrayType{T, 3}(undef, nx, ny, nz)) return SimpleGrid(k,l,m,kr,Ksq, invKsq, Krsq, invKrsq, rfftplan); +end + +#============================Shearing Grid=====================================================# +function GetShearingThreeDGrid(dev::Device=CPU(); nx, Lx, ny=nx, Ly=Lx, nz=nx, Lz=Lx, + x0=-Lx/2, y0=-Ly/2, z0=-Lz/2, + nthreads=Sys.CPU_THREADS, effort=FFTW.MEASURE, T=Float64, + aliased_fraction=1/3) + device_array = FourierFlows.device_array + + dx = Lx/nx + dy = Ly/ny + dz = Lz/nz + + nk = nx + nl = ny + nm = nz + nkr = Int(nx/2 + 1) + + # Physical grid + x = range(T(x0), step=T(dx), length=nx) + y = range(T(y0), step=T(dy), length=ny) + z = range(T(z0), step=T(dz), length=nz) + + # Wavenubmer grid + k = device_array(dev){T}(reshape( fftfreq(nx, 2π/Lx*nx), (nk, 1, 1))) + l1D = device_array(dev){T}(reshape( fftfreq(ny, 2π/Ly*ny), (1, nl, 1))) + l2D = device_array(dev){T}(reshape( fftfreq(ny, 2π/Ly*ny), (1, nl, 1)) .* ones(nkr, 1, 1)) + m = device_array(dev){T}(reshape( fftfreq(nz, 2π/Lz*nz), ( 1, 1, nm))) + kr = device_array(dev){T}(reshape(rfftfreq(nx, 2π/Lx*nx), (nkr, 1, 1))) + + Ksq = @. k^2 + l1D^2 + m^2 + invKsq = @. 1 / Ksq + CUDA.@allowscalar invKsq[1, 1, 1] = 0 + + Krsq = @. kr^2 + l1D^2 + m^2 + invKrsq = @. 1 / Krsq + CUDA.@allowscalar invKrsq[1, 1, 1] = 0 + + # FFT plans + FFTW.set_num_threads(nthreads) + fftplan = FourierFlows.plan_flows_fft(device_array(dev){Complex{T}, 3}(undef, nx, ny, nz), flags=effort) + rfftplan = FourierFlows.plan_flows_rfft(device_array(dev){T, 3}(undef, nx, ny, nz), flags=effort) + + kalias, kralias = FourierFlows.getaliasedwavenumbers(nk, nkr, aliased_fraction) + lalias, _ = FourierFlows.getaliasedwavenumbers(nl, Int(nl/2+1), aliased_fraction) + malias, _ = FourierFlows.getaliasedwavenumbers(nm, Int(nm/2+1), aliased_fraction) + + R = typeof(x) + A = typeof(k) + Axy = typeof(l2D) + Tfft = typeof(fftplan) + Trfft = typeof(rfftplan) + Talias = typeof(kalias) + D = typeof(dev) + + return ShearingThreeDGrid{T, A, Axy, R, Tfft, Trfft, Talias, D}(dev, nx, ny, nz, nk, nl, nm, nkr, + dx, dy, dz, Lx, Ly, Lz, x, y, z, k, l1D, l2D, m, kr, + Ksq, invKsq, Krsq, invKrsq, fftplan, rfftplan, + aliased_fraction, kalias, kralias, lalias, malias) +end + +struct ShearingThreeDGrid{T<:AbstractFloat, Tk, Tky, Tx, Tfft, Trfft, Talias, D} <: FourierFlows.AbstractGrid{T, Tk, Talias, D} + "device which the grid lives on" + device :: D + "number of points in ``x``" + nx :: Int + "number of points in ``y``" + ny :: Int + "number of points in ``z``" + nz :: Int + "number of wavenumbers in ``x``" + nk :: Int + "number of wavenumbers in ``y``" + nl :: Int + "number of wavenumbers in ``z``" + nm :: Int + "number of positive wavenumers in ``x`` (real Fourier transforms)" + nkr :: Int + "grid spacing in ``x``" + dx :: T + "grid spacing in ``y``" + dy :: T + "grid spacing in ``z``" + dz :: T + "domain extent in ``x``" + Lx :: T + "domain extent in ``y``" + Ly :: T + "domain extent in ``z``" + Lz :: T + "range with ``x``-grid-points" + x :: Tx + "range with ``y``-grid-points" + y :: Tx + "range with ``z``-grid-points" + z :: Tx + "array with ``x``-wavenumbers" + k :: Tk + "array with ``y``-wavenumbers(1D)" + l1D :: Tk + "array with ``y``-wavenumbers(2D)" + l :: Tky + "array with ``z``-wavenumbers" + m :: Tk + "array with positive ``x``-wavenumbers (real Fourier transforms)" + kr :: Tk + "array with squared total wavenumbers, ``k² + l² + m²``" + Ksq :: Tk + "array with inverse squared total wavenumbers, ``1 / (k² + l² + m²)``" + invKsq :: Tk + "array with squared total wavenumbers for real Fourier transforms, ``kᵣ² + l² + m²``" + Krsq :: Tk + "array with inverse squared total wavenumbers for real Fourier transforms, ``1 / (kᵣ² + l² + m²)``" + invKrsq :: Tk + "the FFT plan for complex-valued fields" + fftplan :: Tfft + "the FFT plan for real-valued fields" + rfftplan :: Trfft + "the fraction of wavenumbers that are aliased (e.g., 1/3 for quadradic nonlinearities)" + aliased_fraction :: T + "range of the indices of aliased ``x``-wavenumbers" + kalias :: Talias + "range of the indices of aliased positive ``x``-wavenumbers (real Fourier transforms)" + kralias :: Talias + "range of the indices of aliased ``y``-wavenumbers" + lalias :: Talias + "range of the indices of aliased ``m``-wavenumbers" + malias :: Talias +end + + +Base.eltype(grid::ShearingThreeDGrid) = eltype(grid.x) +#===============================================================================================# +function Move_Data_to_Prob!(data,real,sol,grid) + copyto!(real, deepcopy(data)); + mul!(sol, grid.rfftplan, real); + return nothing end \ No newline at end of file