From e04002337ba2f8e270ddbc1a80fb0e7225aeb400 Mon Sep 17 00:00:00 2001 From: rsnm2 Date: Tue, 14 Mar 2023 13:50:45 +0000 Subject: [PATCH 1/4] added torchvision pruning from scracth --- ...arsify-from-scratch-densenet-flowers.ipynb | 2858 +++++++++++++++ ...-sparsify-from-scatch-resnet50-beans.ipynb | 2589 +++++++++++++ ...rsify-from-scratch-mobilenetv2-beans.ipynb | 3210 +++++++++++++++++ .../densenet-flowers-dense-recipe.yaml | 16 + .../densenet-flowers-pruning-recipe.yaml | 56 + .../mobilenetv2-beans-dense-recipe.yaml | 22 + .../mobilenetv2-beans-pruning-recipe.yaml | 40 + .../recipes/resnet50-beans-dense-recipe.yaml | 22 + .../resnet50-beans-pruning-recipe.yaml | 46 + 9 files changed, 8859 insertions(+) create mode 100644 integrations/torchvision/tutorials/docs-docs-torchvision-sparsify-from-scratch-densenet-flowers.ipynb create mode 100644 integrations/torchvision/tutorials/docs-torchvision-sparsify-from-scatch-resnet50-beans.ipynb create mode 100644 integrations/torchvision/tutorials/docs-torchvision-sparsify-from-scratch-mobilenetv2-beans.ipynb create mode 100644 integrations/torchvision/tutorials/recipes/densenet-flowers-dense-recipe.yaml create mode 100644 integrations/torchvision/tutorials/recipes/densenet-flowers-pruning-recipe.yaml create mode 100644 integrations/torchvision/tutorials/recipes/mobilenetv2-beans-dense-recipe.yaml create mode 100644 integrations/torchvision/tutorials/recipes/mobilenetv2-beans-pruning-recipe.yaml create mode 100644 integrations/torchvision/tutorials/recipes/resnet50-beans-dense-recipe.yaml create mode 100644 integrations/torchvision/tutorials/recipes/resnet50-beans-pruning-recipe.yaml diff --git a/integrations/torchvision/tutorials/docs-docs-torchvision-sparsify-from-scratch-densenet-flowers.ipynb b/integrations/torchvision/tutorials/docs-docs-torchvision-sparsify-from-scratch-densenet-flowers.ipynb new file mode 100644 index 00000000000..f999fb24f57 --- /dev/null +++ b/integrations/torchvision/tutorials/docs-docs-torchvision-sparsify-from-scratch-densenet-flowers.ipynb @@ -0,0 +1,2858 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 11, + "id": "1ad80edf", + "metadata": {}, + "outputs": [], + "source": [ + "import sparseml\n", + "from sparseml.pytorch.optim import ScheduledModifierManager\n", + "from sparseml.pytorch.utils import TensorBoardLogger, ModuleExporter, get_prunable_layers, tensor_sparsity\n", + "from sparseml.pytorch.utils.helpers import get_optim_learning_rate\n", + "\n", + "import torch\n", + "from torch.utils.data import DataLoader\n", + "from torch.nn import CrossEntropyLoss\n", + "from torch.optim import Adam\n", + "\n", + "import torchvision\n", + "from torchvision import transforms\n", + "\n", + "from tqdm.auto import tqdm\n", + "import math" + ] + }, + { + "cell_type": "markdown", + "id": "3a128dcc", + "metadata": {}, + "source": [ + "## **Setup Dataset**\n", + "\n", + "Oxford 102 Flower is an image classification dataset consisting of 102 flower categories. The flowers were chosen to be flowers commonly occurring in the United Kingdom. Each class consists of between 40 and 258 images.\n", + "\n", + "The images have large scale, pose and light variations. In addition, there are categories that have large variations within the category, and several very similar categories." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "7d180bbc", + "metadata": {}, + "outputs": [], + "source": [ + "NUM_LABELS = 102\n", + "BATCH_SIZE = 32\n", + "\n", + "# imagenet transformers\n", + "imagenet_transform = transforms.Compose([\n", + " transforms.Resize(size=256, interpolation=transforms.InterpolationMode.BILINEAR, max_size=None, antialias=None),\n", + " transforms.CenterCrop(size=(224, 224)),\n", + " transforms.ToTensor(),\n", + " transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])\n", + "])\n", + "\n", + "# datasets\n", + "train_dataset = torchvision.datasets.Flowers102(\n", + " root=\"./data\",\n", + " split=\"train\",\n", + " transform=imagenet_transform,\n", + " download=True\n", + ")\n", + "\n", + "val_dataset = torchvision.datasets.Flowers102(\n", + " root=\"./data\",\n", + " split=\"val\",\n", + " transform=imagenet_transform,\n", + " download=True\n", + ")\n", + "\n", + "# dataloaders\n", + "train_loader = DataLoader(train_dataset, BATCH_SIZE, shuffle=True, pin_memory=True, num_workers=16)\n", + "val_loader = DataLoader(val_dataset, BATCH_SIZE, shuffle=False, pin_memory=True, num_workers=16)" + ] + }, + { + "cell_type": "markdown", + "id": "890cca4a", + "metadata": {}, + "source": [ + "## Setup Training Loop\n", + "\n", + "We will use this training loop below. This is standard PyTorch functionality." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "5f1b878a", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cuda\n" + ] + } + ], + "source": [ + "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n", + "print(device)\n", + "\n", + "def run_model_one_epoch(model, data_loader, criterion, device, train=False, optimizer=None):\n", + " if train:\n", + " model.train()\n", + " else:\n", + " model.eval()\n", + "\n", + " running_loss = 0.0\n", + " total_correct = 0\n", + " total_predictions = 0\n", + "\n", + " # loop through batches\n", + " for step, (inputs, labels) in tqdm(enumerate(data_loader), total=len(data_loader)):\n", + " inputs = inputs.to(device)\n", + " labels = labels.to(device)\n", + "\n", + " if train:\n", + " optimizer.zero_grad()\n", + "\n", + " # compute loss, run backpropogation\n", + " outputs = model(inputs) # model returns logits\n", + " loss = criterion(outputs, labels)\n", + " if train:\n", + " loss.backward()\n", + " optimizer.step()\n", + "\n", + " running_loss += loss.item()\n", + "\n", + " # run evaluation\n", + " predictions = outputs.argmax(dim=1)\n", + " total_correct += torch.sum(predictions == labels).item()\n", + " total_predictions += inputs.size(0)\n", + "\n", + " # return loss and evaluation metric\n", + " loss = running_loss / (step + 1.0)\n", + " accuracy = total_correct / total_predictions\n", + " return loss, accuracy" + ] + }, + { + "cell_type": "markdown", + "id": "b385497a", + "metadata": {}, + "source": [ + "## **Part 1: Train DenseNet121 Model as Usual**\n", + "\n", + "We download pretrained DenseNet121 from torchvision, setting it to use 102 classes." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "4d554578", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "DenseNet(\n", + " (features): Sequential(\n", + " (conv0): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False)\n", + " (norm0): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu0): ReLU(inplace=True)\n", + " (pool0): MaxPool2d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False)\n", + " (denseblock1): _DenseBlock(\n", + " (denselayer1): _DenseLayer(\n", + " (norm1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(64, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer2): _DenseLayer(\n", + " (norm1): BatchNorm2d(96, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(96, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer3): _DenseLayer(\n", + " (norm1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer4): _DenseLayer(\n", + " (norm1): BatchNorm2d(160, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(160, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer5): _DenseLayer(\n", + " (norm1): BatchNorm2d(192, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(192, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer6): _DenseLayer(\n", + " (norm1): BatchNorm2d(224, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(224, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " )\n", + " (transition1): _Transition(\n", + " (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " (conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (pool): AvgPool2d(kernel_size=2, stride=2, padding=0)\n", + " )\n", + " (denseblock2): _DenseBlock(\n", + " (denselayer1): _DenseLayer(\n", + " (norm1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer2): _DenseLayer(\n", + " (norm1): BatchNorm2d(160, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(160, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer3): _DenseLayer(\n", + " (norm1): BatchNorm2d(192, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(192, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer4): _DenseLayer(\n", + " (norm1): BatchNorm2d(224, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(224, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer5): _DenseLayer(\n", + " (norm1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer6): _DenseLayer(\n", + " (norm1): BatchNorm2d(288, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(288, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer7): _DenseLayer(\n", + " (norm1): BatchNorm2d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(320, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer8): _DenseLayer(\n", + " (norm1): BatchNorm2d(352, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(352, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer9): _DenseLayer(\n", + " (norm1): BatchNorm2d(384, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(384, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer10): _DenseLayer(\n", + " (norm1): BatchNorm2d(416, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(416, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer11): _DenseLayer(\n", + " (norm1): BatchNorm2d(448, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(448, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer12): _DenseLayer(\n", + " (norm1): BatchNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(480, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " )\n", + " (transition2): _Transition(\n", + " (norm): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " (conv): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (pool): AvgPool2d(kernel_size=2, stride=2, padding=0)\n", + " )\n", + " (denseblock3): _DenseBlock(\n", + " (denselayer1): _DenseLayer(\n", + " (norm1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer2): _DenseLayer(\n", + " (norm1): BatchNorm2d(288, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(288, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer3): _DenseLayer(\n", + " (norm1): BatchNorm2d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(320, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer4): _DenseLayer(\n", + " (norm1): BatchNorm2d(352, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(352, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer5): _DenseLayer(\n", + " (norm1): BatchNorm2d(384, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(384, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer6): _DenseLayer(\n", + " (norm1): BatchNorm2d(416, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(416, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer7): _DenseLayer(\n", + " (norm1): BatchNorm2d(448, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(448, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer8): _DenseLayer(\n", + " (norm1): BatchNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(480, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer9): _DenseLayer(\n", + " (norm1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer10): _DenseLayer(\n", + " (norm1): BatchNorm2d(544, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(544, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer11): _DenseLayer(\n", + " (norm1): BatchNorm2d(576, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(576, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer12): _DenseLayer(\n", + " (norm1): BatchNorm2d(608, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(608, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer13): _DenseLayer(\n", + " (norm1): BatchNorm2d(640, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(640, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer14): _DenseLayer(\n", + " (norm1): BatchNorm2d(672, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(672, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer15): _DenseLayer(\n", + " (norm1): BatchNorm2d(704, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(704, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer16): _DenseLayer(\n", + " (norm1): BatchNorm2d(736, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(736, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer17): _DenseLayer(\n", + " (norm1): BatchNorm2d(768, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(768, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer18): _DenseLayer(\n", + " (norm1): BatchNorm2d(800, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(800, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer19): _DenseLayer(\n", + " (norm1): BatchNorm2d(832, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(832, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer20): _DenseLayer(\n", + " (norm1): BatchNorm2d(864, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(864, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer21): _DenseLayer(\n", + " (norm1): BatchNorm2d(896, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(896, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer22): _DenseLayer(\n", + " (norm1): BatchNorm2d(928, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(928, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer23): _DenseLayer(\n", + " (norm1): BatchNorm2d(960, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(960, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer24): _DenseLayer(\n", + " (norm1): BatchNorm2d(992, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(992, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " )\n", + " (transition3): _Transition(\n", + " (norm): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " (conv): Conv2d(1024, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (pool): AvgPool2d(kernel_size=2, stride=2, padding=0)\n", + " )\n", + " (denseblock4): _DenseBlock(\n", + " (denselayer1): _DenseLayer(\n", + " (norm1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer2): _DenseLayer(\n", + " (norm1): BatchNorm2d(544, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(544, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer3): _DenseLayer(\n", + " (norm1): BatchNorm2d(576, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(576, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer4): _DenseLayer(\n", + " (norm1): BatchNorm2d(608, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(608, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer5): _DenseLayer(\n", + " (norm1): BatchNorm2d(640, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(640, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer6): _DenseLayer(\n", + " (norm1): BatchNorm2d(672, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(672, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer7): _DenseLayer(\n", + " (norm1): BatchNorm2d(704, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(704, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer8): _DenseLayer(\n", + " (norm1): BatchNorm2d(736, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(736, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer9): _DenseLayer(\n", + " (norm1): BatchNorm2d(768, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(768, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer10): _DenseLayer(\n", + " (norm1): BatchNorm2d(800, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(800, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer11): _DenseLayer(\n", + " (norm1): BatchNorm2d(832, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(832, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer12): _DenseLayer(\n", + " (norm1): BatchNorm2d(864, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(864, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer13): _DenseLayer(\n", + " (norm1): BatchNorm2d(896, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(896, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer14): _DenseLayer(\n", + " (norm1): BatchNorm2d(928, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(928, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer15): _DenseLayer(\n", + " (norm1): BatchNorm2d(960, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(960, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " (denselayer16): _DenseLayer(\n", + " (norm1): BatchNorm2d(992, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu1): ReLU(inplace=True)\n", + " (conv1): Conv2d(992, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu2): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " )\n", + " )\n", + " (norm5): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " )\n", + " (classifier): Linear(in_features=1024, out_features=102, bias=True)\n", + ")\n" + ] + } + ], + "source": [ + "model = torchvision.models.densenet121(weights=torchvision.models.DenseNet121_Weights.DEFAULT)\n", + "model.classifier = torch.nn.Linear(model.classifier.in_features, NUM_LABELS)\n", + "model.to(device)\n", + "print(model)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "b0a623e1", + "metadata": {}, + "outputs": [], + "source": [ + "# setup loss function and optimizer, LR will be overriden by sparseml\n", + "criterion = CrossEntropyLoss()\n", + "optimizer = Adam(model.parameters(), lr=8e-3)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "d4553beb", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r\n", + "# Epoch and Learning-Rate variables\r\n", + "num_epochs: 10.0\r\n", + "init_lr: 0.0005\r\n", + "\r\n", + "training_modifiers:\r\n", + " - !EpochRangeModifier\r\n", + " start_epoch: 0.0\r\n", + " end_epoch: eval(num_epochs)\r\n", + "\r\n", + " - !LearningRateFunctionModifier\r\n", + " final_lr: 0.0\r\n", + " init_lr: eval(init_lr)\r\n", + " lr_func: cosine\r\n", + " start_epoch: 0.0\r\n", + " end_epoch: eval(num_epochs)\r\n" + ] + } + ], + "source": [ + "!cat ./dense_model/dense-recipe.yaml" + ] + }, + { + "cell_type": "markdown", + "id": "5e132ebe", + "metadata": {}, + "source": [ + "Update the Optimizer and Model with the logic from the recipe." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "1749e00d", + "metadata": {}, + "outputs": [], + "source": [ + "# create ScheduledModifierManager and Optimizer wrapper\n", + "manager = ScheduledModifierManager.from_yaml(\"./dense_model/dense-recipe.yaml\")\n", + "logger = TensorBoardLogger(log_path=\"./dense_model/training/tensorboard_outputs\")\n", + "optimizer = manager.modify(model, optimizer, loggers=[logger], steps_per_epoch=len(train_loader))" + ] + }, + { + "cell_type": "markdown", + "id": "ee67c917", + "metadata": {}, + "source": [ + "Kick off the transfer learning loop. We fine-tune onto the Flowers dataset, reaching 91.3% validation accuracy after 10 epochs." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "d00d175b", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Running Training Epoch 1/10\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "c02f2af1dc1c465b870d978a25e456e9", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + " 0%| | 0/32 [00:00" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "checkpoint2 = torch.load(\"./dense_model/training/mobilenet-v2-dense-beans.pth\")\n", + "model2 = torchvision.models.mobilenet_v2()\n", + "model2.classifier[1] = torch.nn.Linear(model.classifier[1].in_features, NUM_LABELS)\n", + "model2.load_state_dict(checkpoint['state_dict'])" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "b4333b3a", + "metadata": {}, + "outputs": [], + "source": [ + "exporter = ModuleExporter(model2, output_dir=\"./test\")\n", + "exporter.export_onnx(torch.randn(1, 3, 224, 224), name=\"dense-model.onnx\", convert_qat=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "59702f10", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/integrations/torchvision/tutorials/recipes/densenet-flowers-dense-recipe.yaml b/integrations/torchvision/tutorials/recipes/densenet-flowers-dense-recipe.yaml new file mode 100644 index 00000000000..e5afb1d4499 --- /dev/null +++ b/integrations/torchvision/tutorials/recipes/densenet-flowers-dense-recipe.yaml @@ -0,0 +1,16 @@ + +# Epoch and Learning-Rate variables +num_epochs: 10.0 +init_lr: 0.0005 + +training_modifiers: + - !EpochRangeModifier + start_epoch: 0.0 + end_epoch: eval(num_epochs) + + - !LearningRateFunctionModifier + final_lr: 0.0 + init_lr: eval(init_lr) + lr_func: cosine + start_epoch: 0.0 + end_epoch: eval(num_epochs) diff --git a/integrations/torchvision/tutorials/recipes/densenet-flowers-pruning-recipe.yaml b/integrations/torchvision/tutorials/recipes/densenet-flowers-pruning-recipe.yaml new file mode 100644 index 00000000000..ec8a3b33b1a --- /dev/null +++ b/integrations/torchvision/tutorials/recipes/densenet-flowers-pruning-recipe.yaml @@ -0,0 +1,56 @@ +# Epoch and Learning-Rate variables +num_epochs: 13.0 +pruning_epochs: 10.0 +init_lr: 0.0003 +final_lr: 0.0001 +inter_func: cubic +mask_type: unstructured + +training_modifiers: + - !EpochRangeModifier + start_epoch: 0.0 + end_epoch: eval(num_epochs) + + - !LearningRateFunctionModifier + final_lr: eval(final_lr) + init_lr: eval(init_lr) + lr_func: cosine + start_epoch: 0.0 + end_epoch: eval(pruning_epochs) + + - !LearningRateFunctionModifier + final_lr: eval(final_lr) + init_lr: eval(init_lr) + lr_func: cosine + start_epoch: eval(pruning_epochs) + end_epoch: eval(num_epochs) + +# Pruning +pruning_modifiers: + - !GlobalMagnitudePruningModifier + init_sparsity: 0.05 + final_sparsity: 0.90 + start_epoch: 0.0 + end_epoch: eval(pruning_epochs) + update_frequency: 0.5 + params: + - 'features.conv0.weight' + - 're:features.denseblock1.*.conv1.weight' + - 're:features.denseblock1.*.conv2.weight' + - 're:features.transition1.conv.weight' + - 're:features.denseblock2.*.conv1.weight' + - 're:features.denseblock2.*.conv2.weight' + - 're:features.transition2.conv.weight' + - 're:features.denseblock3.*.conv1.weight' + - 're:features.denseblock3.*.conv2.weight' + - 're:features.transition3.conv.weight' + - 're:features.denseblock4.*.conv1.weight' + - 're:features.denseblock4.*.conv2.weight' + leave_enabled: True + inter_func: eval(inter_func) + mask_type: eval(mask_type) + +finetuning_modifiers: + - !ConstantPruningModifier + start_epoch: eval(pruning_epochs) + params: __ALL_PRUNABLE__ \ No newline at end of file diff --git a/integrations/torchvision/tutorials/recipes/mobilenetv2-beans-dense-recipe.yaml b/integrations/torchvision/tutorials/recipes/mobilenetv2-beans-dense-recipe.yaml new file mode 100644 index 00000000000..7636af2000d --- /dev/null +++ b/integrations/torchvision/tutorials/recipes/mobilenetv2-beans-dense-recipe.yaml @@ -0,0 +1,22 @@ + +# Epoch and Learning-Rate variables +num_epochs: 10.0 +init_lr: 0.0005 + +training_modifiers: + - !EpochRangeModifier + start_epoch: 0.0 + end_epoch: eval(num_epochs) + + - !LearningRateFunctionModifier + final_lr: 0.0 + init_lr: eval(init_lr) + lr_func: cosine + start_epoch: 0.0 + end_epoch: eval(num_epochs) + +# Phase 1 Sparse Transfer Learning / Recovery +sparse_transfer_learning_modifiers: + - !ConstantPruningModifier + start_epoch: 0.0 + params: __ALL_PRUNABLE__ diff --git a/integrations/torchvision/tutorials/recipes/mobilenetv2-beans-pruning-recipe.yaml b/integrations/torchvision/tutorials/recipes/mobilenetv2-beans-pruning-recipe.yaml new file mode 100644 index 00000000000..0d42bfc46a8 --- /dev/null +++ b/integrations/torchvision/tutorials/recipes/mobilenetv2-beans-pruning-recipe.yaml @@ -0,0 +1,40 @@ +# Epoch and Learning-Rate variables +num_epochs: 13.0 +pruning_epochs: 10.0 +init_lr: 0.0005 +inter_func: cubic +mask_type: unstructured + +training_modifiers: + - !EpochRangeModifier + start_epoch: 0.0 + end_epoch: eval(num_epochs) + + - !LearningRateFunctionModifier + final_lr: 0.0 + init_lr: eval(init_lr) + lr_func: cosine + start_epoch: 0.0 + end_epoch: eval(num_epochs) + +# Pruning +pruning_modifiers: + - !GlobalMagnitudePruningModifier + init_sparsity: 0.05 + final_sparsity: 0.90 + start_epoch: 0.0 + end_epoch: eval(pruning_epochs) + update_frequency: 1.0 + params: + - 'features.0.0.weight' + - 'features.18.0.weight' + - 're:features.*.conv.*.weight' + - 're:features.*.conv.*.*.weight' + leave_enabled: True + inter_func: eval(inter_func) + mask_type: eval(mask_type) + +finetuning_modifiers: + - !ConstantPruningModifier + start_epoch: eval(pruning_epochs) + params: __ALL_PRUNABLE__ \ No newline at end of file diff --git a/integrations/torchvision/tutorials/recipes/resnet50-beans-dense-recipe.yaml b/integrations/torchvision/tutorials/recipes/resnet50-beans-dense-recipe.yaml new file mode 100644 index 00000000000..7636af2000d --- /dev/null +++ b/integrations/torchvision/tutorials/recipes/resnet50-beans-dense-recipe.yaml @@ -0,0 +1,22 @@ + +# Epoch and Learning-Rate variables +num_epochs: 10.0 +init_lr: 0.0005 + +training_modifiers: + - !EpochRangeModifier + start_epoch: 0.0 + end_epoch: eval(num_epochs) + + - !LearningRateFunctionModifier + final_lr: 0.0 + init_lr: eval(init_lr) + lr_func: cosine + start_epoch: 0.0 + end_epoch: eval(num_epochs) + +# Phase 1 Sparse Transfer Learning / Recovery +sparse_transfer_learning_modifiers: + - !ConstantPruningModifier + start_epoch: 0.0 + params: __ALL_PRUNABLE__ diff --git a/integrations/torchvision/tutorials/recipes/resnet50-beans-pruning-recipe.yaml b/integrations/torchvision/tutorials/recipes/resnet50-beans-pruning-recipe.yaml new file mode 100644 index 00000000000..549ceeaf098 --- /dev/null +++ b/integrations/torchvision/tutorials/recipes/resnet50-beans-pruning-recipe.yaml @@ -0,0 +1,46 @@ +# Epoch and Learning-Rate variables +num_epochs: 10.0 +init_lr: 0.00025 +inter_func: cubic +mask_type: unstructured + +training_modifiers: + - !EpochRangeModifier + start_epoch: 0.0 + end_epoch: eval(num_epochs) + + - !LearningRateFunctionModifier + final_lr: 0.0 + init_lr: eval(init_lr) + lr_func: cosine + start_epoch: 0.0 + end_epoch: eval(num_epochs) + +# Pruning +pruning_modifiers: + - !GlobalMagnitudePruningModifier + init_sparsity: 0.05 + final_sparsity: 0.90 + start_epoch: 0.0 + end_epoch: eval(num_epochs) + update_frequency: 1.0 + params: + - 're:layer1.*.conv1.weight' + - 're:layer1.*.conv2.weight' + - 're:layer1.*.conv3.weight' + - 're:layer1.0.downsample.0.weight' + - 're:layer2.*.conv1.weight' + - 're:layer2.*.conv2.weight' + - 're:layer2.*.conv3.weight' + - 're:layer2.0.downsample.0.weight' + - 're:layer3.*.conv1.weight' + - 're:layer3.*.conv2.weight' + - 're:layer3.*.conv3.weight' + - 're:layer3.0.downsample.0.weight' + - 're:layer4.*.conv1.weight' + - 're:layer4.*.conv2.weight' + - 're:layer4.*.conv3.weight' + - 're:layer4.0.downsample.0.weight' + leave_enabled: True + inter_func: eval(inter_func) + mask_type: eval(mask_type) From cccaacce60a1396def86ce6a891e22e7b7120b63 Mon Sep 17 00:00:00 2001 From: rsnm2 Date: Tue, 14 Mar 2023 16:09:07 +0000 Subject: [PATCH 2/4] finished densenet example --- ...arsify-from-scratch-densenet-flowers.ipynb | 2035 +++++------------ .../images/densenet-tensorboard-output.png | Bin 0 -> 477355 bytes .../densenet-flowers-pruning-recipe.yaml | 4 +- 3 files changed, 632 insertions(+), 1407 deletions(-) create mode 100644 integrations/torchvision/tutorials/images/densenet-tensorboard-output.png diff --git a/integrations/torchvision/tutorials/docs-docs-torchvision-sparsify-from-scratch-densenet-flowers.ipynb b/integrations/torchvision/tutorials/docs-docs-torchvision-sparsify-from-scratch-densenet-flowers.ipynb index f999fb24f57..eaa66ddb60c 100644 --- a/integrations/torchvision/tutorials/docs-docs-torchvision-sparsify-from-scratch-densenet-flowers.ipynb +++ b/integrations/torchvision/tutorials/docs-docs-torchvision-sparsify-from-scratch-densenet-flowers.ipynb @@ -1,25 +1,50 @@ { "cells": [ + { + "cell_type": "markdown", + "id": "00e081b7", + "metadata": {}, + "source": [ + "# Sparsifying DenseNet121 from Scratch (Flower102)\n", + "\n", + "In this example, we will demonstrate how to sparsify an image classification model from scratch using SparseML's PyTorch integration. We train and prune [DenseNet121](https://pytorch.org/vision/main/models/generated/torchvision.models.densenet121.html) on the downstream [Oxford Flower 102 dataset](https://pytorch.org/vision/main/generated/torchvision.datasets.Flowers102.html#:~:text=Oxford%20102%20Flower%20is%20an,scale%2C%20pose%20and%20light%20variations) using the Global Magnitude Pruning algorithm. \n", + "\n", + "## Agenda\n", + "\n", + "There are a few steps:\n", + "\n", + " 1. Setup the dataset\n", + " 2. Setup the PyTorch training loop\n", + " 3. Train a dense version of DenseNet121\n", + " 4. Run the GMP pruning algorithm on the dense model\n", + " \n", + "## Installation\n", + "\n", + "Install SparseML with `pip`:\n", + "\n", + "```\n", + "pip install sparseml[torchvision]\n", + "```" + ] + }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "id": "1ad80edf", "metadata": {}, "outputs": [], "source": [ + "import torch\n", "import sparseml\n", + "import torchvision\n", "from sparseml.pytorch.optim import ScheduledModifierManager\n", "from sparseml.pytorch.utils import TensorBoardLogger, ModuleExporter, get_prunable_layers, tensor_sparsity\n", - "from sparseml.pytorch.utils.helpers import get_optim_learning_rate\n", "\n", - "import torch\n", "from torch.utils.data import DataLoader\n", "from torch.nn import CrossEntropyLoss\n", "from torch.optim import Adam\n", "\n", - "import torchvision\n", "from torchvision import transforms\n", - "\n", "from tqdm.auto import tqdm\n", "import math" ] @@ -29,11 +54,11 @@ "id": "3a128dcc", "metadata": {}, "source": [ - "## **Setup Dataset**\n", + "## **Step 1: Setup Dataset**\n", "\n", - "Oxford 102 Flower is an image classification dataset consisting of 102 flower categories. The flowers were chosen to be flowers commonly occurring in the United Kingdom. Each class consists of between 40 and 258 images.\n", + "Oxford 102 Flower is an image classification dataset consisting of 102 flower categories. The flowers were chosen to be flowers commonly occurring in the United Kingdom. Each class consists of between 40 and 258 images. The images have large scale, pose and light variations. In addition, there are categories that have large variations within the category, and several very similar categories.\n", "\n", - "The images have large scale, pose and light variations. In addition, there are categories that have large variations within the category, and several very similar categories." + "We use the standard PyTorch `datasets` and `dataloaders` to manage the dataset." ] }, { @@ -79,7 +104,7 @@ "id": "890cca4a", "metadata": {}, "source": [ - "## Setup Training Loop\n", + "## Step 2: Setup PyTorch Training Loop\n", "\n", "We will use this training loop below. This is standard PyTorch functionality." ] @@ -145,552 +170,75 @@ "id": "b385497a", "metadata": {}, "source": [ - "## **Part 1: Train DenseNet121 Model as Usual**\n", + "## **Part 3: Train DenseNet121 on Flowers102**\n", "\n", - "We download pretrained DenseNet121 from torchvision, setting it to use 102 classes." + "First, we will train a dense version of DenseNet121 on the Flowers dataset." ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 4, "id": "4d554578", "metadata": { "scrolled": true }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DenseNet(\n", - " (features): Sequential(\n", - " (conv0): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False)\n", - " (norm0): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu0): ReLU(inplace=True)\n", - " (pool0): MaxPool2d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False)\n", - " (denseblock1): _DenseBlock(\n", - " (denselayer1): _DenseLayer(\n", - " (norm1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(64, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer2): _DenseLayer(\n", - " (norm1): BatchNorm2d(96, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(96, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer3): _DenseLayer(\n", - " (norm1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer4): _DenseLayer(\n", - " (norm1): BatchNorm2d(160, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(160, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer5): _DenseLayer(\n", - " (norm1): BatchNorm2d(192, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(192, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer6): _DenseLayer(\n", - " (norm1): BatchNorm2d(224, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(224, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " )\n", - " (transition1): _Transition(\n", - " (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " (conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (pool): AvgPool2d(kernel_size=2, stride=2, padding=0)\n", - " )\n", - " (denseblock2): _DenseBlock(\n", - " (denselayer1): _DenseLayer(\n", - " (norm1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer2): _DenseLayer(\n", - " (norm1): BatchNorm2d(160, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(160, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer3): _DenseLayer(\n", - " (norm1): BatchNorm2d(192, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(192, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer4): _DenseLayer(\n", - " (norm1): BatchNorm2d(224, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(224, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer5): _DenseLayer(\n", - " (norm1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer6): _DenseLayer(\n", - " (norm1): BatchNorm2d(288, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(288, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer7): _DenseLayer(\n", - " (norm1): BatchNorm2d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(320, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer8): _DenseLayer(\n", - " (norm1): BatchNorm2d(352, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(352, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer9): _DenseLayer(\n", - " (norm1): BatchNorm2d(384, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(384, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer10): _DenseLayer(\n", - " (norm1): BatchNorm2d(416, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(416, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer11): _DenseLayer(\n", - " (norm1): BatchNorm2d(448, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(448, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer12): _DenseLayer(\n", - " (norm1): BatchNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(480, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " )\n", - " (transition2): _Transition(\n", - " (norm): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " (conv): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (pool): AvgPool2d(kernel_size=2, stride=2, padding=0)\n", - " )\n", - " (denseblock3): _DenseBlock(\n", - " (denselayer1): _DenseLayer(\n", - " (norm1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer2): _DenseLayer(\n", - " (norm1): BatchNorm2d(288, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(288, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer3): _DenseLayer(\n", - " (norm1): BatchNorm2d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(320, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer4): _DenseLayer(\n", - " (norm1): BatchNorm2d(352, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(352, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer5): _DenseLayer(\n", - " (norm1): BatchNorm2d(384, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(384, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer6): _DenseLayer(\n", - " (norm1): BatchNorm2d(416, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(416, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer7): _DenseLayer(\n", - " (norm1): BatchNorm2d(448, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(448, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer8): _DenseLayer(\n", - " (norm1): BatchNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(480, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer9): _DenseLayer(\n", - " (norm1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer10): _DenseLayer(\n", - " (norm1): BatchNorm2d(544, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(544, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer11): _DenseLayer(\n", - " (norm1): BatchNorm2d(576, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(576, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer12): _DenseLayer(\n", - " (norm1): BatchNorm2d(608, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(608, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer13): _DenseLayer(\n", - " (norm1): BatchNorm2d(640, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(640, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer14): _DenseLayer(\n", - " (norm1): BatchNorm2d(672, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(672, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer15): _DenseLayer(\n", - " (norm1): BatchNorm2d(704, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(704, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer16): _DenseLayer(\n", - " (norm1): BatchNorm2d(736, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(736, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer17): _DenseLayer(\n", - " (norm1): BatchNorm2d(768, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(768, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer18): _DenseLayer(\n", - " (norm1): BatchNorm2d(800, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(800, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer19): _DenseLayer(\n", - " (norm1): BatchNorm2d(832, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(832, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer20): _DenseLayer(\n", - " (norm1): BatchNorm2d(864, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(864, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer21): _DenseLayer(\n", - " (norm1): BatchNorm2d(896, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(896, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer22): _DenseLayer(\n", - " (norm1): BatchNorm2d(928, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(928, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer23): _DenseLayer(\n", - " (norm1): BatchNorm2d(960, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(960, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer24): _DenseLayer(\n", - " (norm1): BatchNorm2d(992, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(992, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " )\n", - " (transition3): _Transition(\n", - " (norm): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " (conv): Conv2d(1024, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (pool): AvgPool2d(kernel_size=2, stride=2, padding=0)\n", - " )\n", - " (denseblock4): _DenseBlock(\n", - " (denselayer1): _DenseLayer(\n", - " (norm1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer2): _DenseLayer(\n", - " (norm1): BatchNorm2d(544, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(544, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer3): _DenseLayer(\n", - " (norm1): BatchNorm2d(576, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(576, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer4): _DenseLayer(\n", - " (norm1): BatchNorm2d(608, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(608, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer5): _DenseLayer(\n", - " (norm1): BatchNorm2d(640, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(640, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer6): _DenseLayer(\n", - " (norm1): BatchNorm2d(672, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(672, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer7): _DenseLayer(\n", - " (norm1): BatchNorm2d(704, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(704, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer8): _DenseLayer(\n", - " (norm1): BatchNorm2d(736, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(736, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer9): _DenseLayer(\n", - " (norm1): BatchNorm2d(768, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(768, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer10): _DenseLayer(\n", - " (norm1): BatchNorm2d(800, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(800, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer11): _DenseLayer(\n", - " (norm1): BatchNorm2d(832, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(832, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer12): _DenseLayer(\n", - " (norm1): BatchNorm2d(864, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(864, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer13): _DenseLayer(\n", - " (norm1): BatchNorm2d(896, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(896, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer14): _DenseLayer(\n", - " (norm1): BatchNorm2d(928, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(928, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer15): _DenseLayer(\n", - " (norm1): BatchNorm2d(960, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(960, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer16): _DenseLayer(\n", - " (norm1): BatchNorm2d(992, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(992, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " )\n", - " (norm5): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " )\n", - " (classifier): Linear(in_features=1024, out_features=102, bias=True)\n", - ")\n" - ] - } - ], + "outputs": [], "source": [ + "# download pre-trained model, setup classification head\n", "model = torchvision.models.densenet121(weights=torchvision.models.DenseNet121_Weights.DEFAULT)\n", "model.classifier = torch.nn.Linear(model.classifier.in_features, NUM_LABELS)\n", "model.to(device)\n", - "print(model)" + "\n", + "# setup loss function and optimizer\n", + "criterion = CrossEntropyLoss()\n", + "optimizer = Adam(model.parameters(), lr=8e-3) # lr will be override by sparseml" + ] + }, + { + "cell_type": "markdown", + "id": "a2161b6c", + "metadata": { + "scrolled": true + }, + "source": [ + "Next, we will use SparseML's recipes to set the hyperparameters of training loop. In this case, we will use the following recipe:\n", + "\n", + "```yaml\n", + "# Epoch and Learning-Rate variables\n", + "num_epochs: 10.0\n", + "init_lr: 0.0005\n", + "\n", + "training_modifiers:\n", + " - !EpochRangeModifier\n", + " start_epoch: 0.0\n", + " end_epoch: eval(num_epochs)\n", + "\n", + " - !LearningRateFunctionModifier\n", + " final_lr: 0.0\n", + " init_lr: eval(init_lr)\n", + " lr_func: cosine\n", + " start_epoch: 0.0\n", + " end_epoch: eval(num_epochs)\n", + "```\n", + "\n", + "As you can see, the recipe includes an `!EpochRangeModifier` and a `!LearningRateFunctionModifier`. These modifiers simply set the number of epochs to train for and the learning rate schedule. As a result, the final model will be dense." ] }, { "cell_type": "code", - "execution_count": 17, - "id": "b0a623e1", + "execution_count": 5, + "id": "c1ad9112", "metadata": {}, "outputs": [], "source": [ - "# setup loss function and optimizer, LR will be overriden by sparseml\n", - "criterion = CrossEntropyLoss()\n", - "optimizer = Adam(model.parameters(), lr=8e-3)" + "dense_recipe_path = \"./recipes/densenet-flowers-dense-recipe.yaml\"" ] }, { "cell_type": "code", - "execution_count": 18, - "id": "d4553beb", - "metadata": { - "scrolled": true - }, + "execution_count": 6, + "id": "b4b0f03b", + "metadata": {}, "outputs": [ { "name": "stdout", @@ -716,28 +264,27 @@ } ], "source": [ - "!cat ./dense_model/dense-recipe.yaml" + "!cat ./recipes/densenet-flowers-dense-recipe.yaml" ] }, { "cell_type": "markdown", - "id": "5e132ebe", + "id": "11d180fe", "metadata": {}, "source": [ - "Update the Optimizer and Model with the logic from the recipe." + "Next, we use SparseML's `ScheduledModifierManager` to parse and apply the recipe. The `manager.modify` function modifies and wraps the `model` and `optimizer` with the instructions from the recipe. You can use the `model` and `optimizer` just like standard PyTorch objects." ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 7, "id": "1749e00d", "metadata": {}, "outputs": [], "source": [ "# create ScheduledModifierManager and Optimizer wrapper\n", - "manager = ScheduledModifierManager.from_yaml(\"./dense_model/dense-recipe.yaml\")\n", - "logger = TensorBoardLogger(log_path=\"./dense_model/training/tensorboard_outputs\")\n", - "optimizer = manager.modify(model, optimizer, loggers=[logger], steps_per_epoch=len(train_loader))" + "manager = ScheduledModifierManager.from_yaml(dense_recipe_path)\n", + "optimizer = manager.modify(model, optimizer, steps_per_epoch=len(train_loader))" ] }, { @@ -745,15 +292,15 @@ "id": "ee67c917", "metadata": {}, "source": [ - "Kick off the transfer learning loop. We fine-tune onto the Flowers dataset, reaching 91.3% validation accuracy after 10 epochs." + "Kick off the transfer learning loop. Our run reached ~92.5% validation accuracy after 10 epochs." ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 8, "id": "d00d175b", "metadata": { - "scrolled": true + "scrolled": false }, "outputs": [ { @@ -766,7 +313,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c02f2af1dc1c465b870d978a25e456e9", + "model_id": "fb1f4f772bc540b0b3725dddfa1b0f49", "version_major": 2, "version_minor": 0 }, @@ -782,8 +329,8 @@ "output_type": "stream", "text": [ "Training Epoch: 1/10\n", - "Training Loss: 3.618388310074806\n", - "Top 1 Acc: 0.3\n", + "Training Loss: 3.6993999630212784\n", + "Top 1 Acc: 0.2823529411764706\n", "\n", "Running Validation Epoch 1/10\n" ] @@ -791,7 +338,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "b464cab80ed64170a8d853500e7c7a5c", + "model_id": "4865f146cabb4142b9eb8b7a6a7c59f9", "version_major": 2, "version_minor": 0 }, @@ -807,8 +354,8 @@ "output_type": "stream", "text": [ "Validation Epoch: 1/10\n", - "Val Loss: 2.134434787556529\n", - "Top 1 Acc: 0.6274509803921569\n", + "Val Loss: 2.32899521663785\n", + "Top 1 Acc: 0.6235294117647059\n", "\n", "Running Training Epoch 2/10\n" ] @@ -816,7 +363,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "950e5fda34bf465a94f6ce90474eb17a", + "model_id": "d973db1bca35479c8e5482dc2a8b45e9", "version_major": 2, "version_minor": 0 }, @@ -832,8 +379,8 @@ "output_type": "stream", "text": [ "Training Epoch: 2/10\n", - "Training Loss: 1.3103822488337755\n", - "Top 1 Acc: 0.9019607843137255\n", + "Training Loss: 1.3755246959626675\n", + "Top 1 Acc: 0.8823529411764706\n", "\n", "Running Validation Epoch 2/10\n" ] @@ -841,7 +388,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "e97bc059e155478d8f9c815740be5d96", + "model_id": "2a896b5e2fe64e0f9353c2c0bb3ab2dc", "version_major": 2, "version_minor": 0 }, @@ -857,8 +404,8 @@ "output_type": "stream", "text": [ "Validation Epoch: 2/10\n", - "Val Loss: 1.1688878536224365\n", - "Top 1 Acc: 0.8598039215686275\n", + "Val Loss: 1.0808461774140596\n", + "Top 1 Acc: 0.85\n", "\n", "Running Training Epoch 3/10\n" ] @@ -866,7 +413,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "752e6dec2aa94f2984e8930f57cfc127", + "model_id": "bdd04f003b34476696b88bdcf3ffb8e8", "version_major": 2, "version_minor": 0 }, @@ -882,8 +429,8 @@ "output_type": "stream", "text": [ "Training Epoch: 3/10\n", - "Training Loss: 0.3958540456369519\n", - "Top 1 Acc: 0.9931372549019608\n", + "Training Loss: 0.4065576898865402\n", + "Top 1 Acc: 0.9882352941176471\n", "\n", "Running Validation Epoch 3/10\n" ] @@ -891,7 +438,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "bde611c736264aa4b09225ce3ad1b1d3", + "model_id": "2dffd5826f924b0eb7bca6039f439d83", "version_major": 2, "version_minor": 0 }, @@ -907,8 +454,8 @@ "output_type": "stream", "text": [ "Validation Epoch: 3/10\n", - "Val Loss: 0.7494302792474627\n", - "Top 1 Acc: 0.8813725490196078\n", + "Val Loss: 0.7663819249719381\n", + "Top 1 Acc: 0.8823529411764706\n", "\n", "Running Training Epoch 4/10\n" ] @@ -916,7 +463,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "41cda43bfcf649c99acaff23df2b8477", + "model_id": "1ec7462e075e446185eddbd2537748e3", "version_major": 2, "version_minor": 0 }, @@ -932,8 +479,8 @@ "output_type": "stream", "text": [ "Training Epoch: 4/10\n", - "Training Loss: 0.12264440068975091\n", - "Top 1 Acc: 0.9990196078431373\n", + "Training Loss: 0.13117457507178187\n", + "Top 1 Acc: 1.0\n", "\n", "Running Validation Epoch 4/10\n" ] @@ -941,7 +488,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "09dd43adbdfd433584e1ae345574a87a", + "model_id": "5ee0722460fb4916ae605a705703df8c", "version_major": 2, "version_minor": 0 }, @@ -957,8 +504,8 @@ "output_type": "stream", "text": [ "Validation Epoch: 4/10\n", - "Val Loss: 0.6009533200412989\n", - "Top 1 Acc: 0.9068627450980392\n", + "Val Loss: 0.5690533611923456\n", + "Top 1 Acc: 0.9127450980392157\n", "\n", "Running Training Epoch 5/10\n" ] @@ -966,7 +513,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "d70b0a06499844f0bd939aa8537dd8c1", + "model_id": "520064cc7f9a486391e6c8cf34dcc46f", "version_major": 2, "version_minor": 0 }, @@ -982,7 +529,7 @@ "output_type": "stream", "text": [ "Training Epoch: 5/10\n", - "Training Loss: 0.06395778199657798\n", + "Training Loss: 0.05944129719864577\n", "Top 1 Acc: 1.0\n", "\n", "Running Validation Epoch 5/10\n" @@ -991,7 +538,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "dea7eca69ba24561b550f0f767eb6042", + "model_id": "56b6421ee84d48d7ab9411a7fea5cae0", "version_major": 2, "version_minor": 0 }, @@ -1007,8 +554,8 @@ "output_type": "stream", "text": [ "Validation Epoch: 5/10\n", - "Val Loss: 0.5246470430865884\n", - "Top 1 Acc: 0.9166666666666666\n", + "Val Loss: 0.4922205451875925\n", + "Top 1 Acc: 0.9147058823529411\n", "\n", "Running Training Epoch 6/10\n" ] @@ -1016,7 +563,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "065b397dfa644e2c8ea9a6443299b3df", + "model_id": "9b3c98c1b78b406e8e61ef9b3c27ad3f", "version_major": 2, "version_minor": 0 }, @@ -1032,7 +579,7 @@ "output_type": "stream", "text": [ "Training Epoch: 6/10\n", - "Training Loss: 0.041063663142267615\n", + "Training Loss: 0.04032939835451543\n", "Top 1 Acc: 1.0\n", "\n", "Running Validation Epoch 6/10\n" @@ -1041,7 +588,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c0f04580fc3d44b98caf400499b7698b", + "model_id": "0b7d5076d9fe4f91aaf6290e20ed73c0", "version_major": 2, "version_minor": 0 }, @@ -1057,8 +604,8 @@ "output_type": "stream", "text": [ "Validation Epoch: 6/10\n", - "Val Loss: 0.5043302299454808\n", - "Top 1 Acc: 0.9156862745098039\n", + "Val Loss: 0.47672522626817226\n", + "Top 1 Acc: 0.9205882352941176\n", "\n", "Running Training Epoch 7/10\n" ] @@ -1066,7 +613,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "140c927f45994de8b5c947c18b7ce4b8", + "model_id": "b43f39481dd94010b65d8a4bfa2c82bd", "version_major": 2, "version_minor": 0 }, @@ -1082,7 +629,7 @@ "output_type": "stream", "text": [ "Training Epoch: 7/10\n", - "Training Loss: 0.03354773804312572\n", + "Training Loss: 0.03349028015509248\n", "Top 1 Acc: 1.0\n", "\n", "Running Validation Epoch 7/10\n" @@ -1091,7 +638,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "41fb0bf664aa4812a841a7c16a9d8a8e", + "model_id": "e31258f33c4b439b838a723a0b9e7787", "version_major": 2, "version_minor": 0 }, @@ -1107,8 +654,8 @@ "output_type": "stream", "text": [ "Validation Epoch: 7/10\n", - "Val Loss: 0.490260950056836\n", - "Top 1 Acc: 0.9166666666666666\n", + "Val Loss: 0.4664669381454587\n", + "Top 1 Acc: 0.9176470588235294\n", "\n", "Running Training Epoch 8/10\n" ] @@ -1116,7 +663,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "e4c73a393ba74093aef7479554cbf926", + "model_id": "45670df899134e2688a5fae7778bb392", "version_major": 2, "version_minor": 0 }, @@ -1132,7 +679,7 @@ "output_type": "stream", "text": [ "Training Epoch: 8/10\n", - "Training Loss: 0.03196021361509338\n", + "Training Loss: 0.03036679228534922\n", "Top 1 Acc: 1.0\n", "\n", "Running Validation Epoch 8/10\n" @@ -1141,7 +688,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "357e2a67205743f89e0c8fb037ea3708", + "model_id": "7a3a457626624ce587eac6b63928b80a", "version_major": 2, "version_minor": 0 }, @@ -1157,8 +704,8 @@ "output_type": "stream", "text": [ "Validation Epoch: 8/10\n", - "Val Loss: 0.4794748453423381\n", - "Top 1 Acc: 0.9156862745098039\n", + "Val Loss: 0.45540827978402376\n", + "Top 1 Acc: 0.9264705882352942\n", "\n", "Running Training Epoch 9/10\n" ] @@ -1166,7 +713,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0b8b2118712a482f8828d5705d77e867", + "model_id": "8a396321f97e4010aa079b7a2954d1d3", "version_major": 2, "version_minor": 0 }, @@ -1182,7 +729,7 @@ "output_type": "stream", "text": [ "Training Epoch: 9/10\n", - "Training Loss: 0.027999908081255853\n", + "Training Loss: 0.028963472577743232\n", "Top 1 Acc: 1.0\n", "\n", "Running Validation Epoch 9/10\n" @@ -1191,7 +738,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "e76c672c7cd84a1e8971a34b91dd8548", + "model_id": "51950b565767410f8ef9cb052fcb6fcb", "version_major": 2, "version_minor": 0 }, @@ -1207,8 +754,8 @@ "output_type": "stream", "text": [ "Validation Epoch: 9/10\n", - "Val Loss: 0.4790585918817669\n", - "Top 1 Acc: 0.9137254901960784\n", + "Val Loss: 0.4513796488754451\n", + "Top 1 Acc: 0.9235294117647059\n", "\n", "Running Training Epoch 10/10\n" ] @@ -1216,7 +763,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1cfc3d87fa604e80aea4483bf58da091", + "model_id": "1085b12cebf24a2a8e7f69e3d13c9991", "version_major": 2, "version_minor": 0 }, @@ -1232,7 +779,7 @@ "output_type": "stream", "text": [ "Training Epoch: 10/10\n", - "Training Loss: 0.027712288312613964\n", + "Training Loss: 0.027131778770126402\n", "Top 1 Acc: 1.0\n", "\n", "Running Validation Epoch 10/10\n" @@ -1241,7 +788,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c3894447ffec41518ccf903fce69e4b5", + "model_id": "aeb6b899572c49dab5cd0aed15ede593", "version_major": 2, "version_minor": 0 }, @@ -1257,8 +804,8 @@ "output_type": "stream", "text": [ "Validation Epoch: 10/10\n", - "Val Loss: 0.4804669988807291\n", - "Top 1 Acc: 0.9156862745098039\n", + "Val Loss: 0.45484112948179245\n", + "Top 1 Acc: 0.9245098039215687\n", "\n" ] } @@ -1277,12 +824,8 @@ " print(f\"Running Validation Epoch {epoch_name}\")\n", " val_loss, val_acc = run_model_one_epoch(model, val_loader, criterion, device)\n", " print(f\"Validation Epoch: {epoch_name}\\nVal Loss: {val_loss}\\nTop 1 Acc: {val_acc}\\n\")\n", - " \n", - " logger.log_scalar(\"Metrics/Loss (Train)\", train_loss, epoch)\n", - " logger.log_scalar(\"Metrics/Accuracy (Train)\", train_acc, epoch)\n", - " logger.log_scalar(\"Metrics/Loss (Validation)\", val_loss, epoch)\n", - " logger.log_scalar(\"Metrics/Accuracy (Validation)\", val_acc, epoch)\n", "\n", + "# clean up\n", "manager.finalize(model)" ] }, @@ -1296,19 +839,10 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": null, "id": "11fa4cf2", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ubuntu/rshaw/python-venvs/sparseml-env/lib/python3.8/site-packages/torch/onnx/utils.py:439: UserWarning: It is recommended that constant folding be turned off ('do_constant_folding=False') when exporting the model in training-amenable mode, i.e. with 'training=TrainingMode.TRAIN' or 'training=TrainingMode.PRESERVE' (when model is in training mode). Otherwise, some learnable model parameters may not translate correctly in the exported ONNX model because constant folding mutates model parameters. Please consider turning off constant folding or setting the training=TrainingMode.EVAL.\n", - " warnings.warn(\n" - ] - } - ], + "outputs": [], "source": [ "save_dir = \"dense_model\"\n", "exporter = ModuleExporter(model, output_dir=save_dir)\n", @@ -1317,32 +851,33 @@ ] }, { - "cell_type": "markdown", - "id": "8a7d6309", + "cell_type": "code", + "execution_count": 10, + "id": "4532442e", "metadata": {}, + "outputs": [], "source": [ - "## Part 2: Prune The Model\n", - "\n", - "We load the model trained in the prior step as the starting point." + "torch.cuda.empty_cache()" ] }, { - "cell_type": "code", - "execution_count": 4, - "id": "4532442e", + "cell_type": "markdown", + "id": "8a7d6309", "metadata": {}, - "outputs": [], "source": [ - "torch.cuda.empty_cache()" + "## Part 4: Prune The Model\n", + "\n", + "With a model trained on Flowers, we are now ready to apply the GMP algorithm to prune the model. The GMP algorithm is an interative pruning algorithm. At the end of each epoch, we identify the lowest magnitude weights (those closest to 0) and remove them from the network starting from an initial level of sparsity until a final level of sparsity. The remaining nonzero weights are then fine-tuned onto training dataset." ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 45, "id": "8447d074", "metadata": {}, "outputs": [], "source": [ + "# first, load the trained model from Part 3\n", "checkpoint = torch.load(\"./dense_model/training/densenet-121-dense-flowers.pth\")\n", "model = torchvision.models.densenet121()\n", "model.classifier = torch.nn.Linear(model.classifier.in_features, NUM_LABELS)\n", @@ -1354,620 +889,290 @@ "optimizer = Adam(model.parameters(), lr=8e-3)" ] }, + { + "cell_type": "markdown", + "id": "7a05d884", + "metadata": {}, + "source": [ + "Next, we need to create a SparseML recipe which includes the GMP algorithm. The `!GlobalMagnitudePruningModifier` modifier instructs SparseML to apply the GMP algorithm at a global level (pruning the lowest magnitude weights across all layers).\n", + "\n", + "Firstly, we need to decide identify which parameters of the model to apply the GMP algorithm to. We can use the `get_prunable_layers` function to inspect:" + ] + }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 46, "id": "d367905a", - "metadata": {}, + "metadata": { + "scrolled": false + }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "DenseNet(\n", - " (features): Sequential(\n", - " (conv0): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False)\n", - " (norm0): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu0): ReLU(inplace=True)\n", - " (pool0): MaxPool2d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False)\n", - " (denseblock1): _DenseBlock(\n", - " (denselayer1): _DenseLayer(\n", - " (norm1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(64, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer2): _DenseLayer(\n", - " (norm1): BatchNorm2d(96, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(96, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer3): _DenseLayer(\n", - " (norm1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer4): _DenseLayer(\n", - " (norm1): BatchNorm2d(160, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(160, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer5): _DenseLayer(\n", - " (norm1): BatchNorm2d(192, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(192, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer6): _DenseLayer(\n", - " (norm1): BatchNorm2d(224, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(224, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " )\n", - " (transition1): _Transition(\n", - " (norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " (conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (pool): AvgPool2d(kernel_size=2, stride=2, padding=0)\n", - " )\n", - " (denseblock2): _DenseBlock(\n", - " (denselayer1): _DenseLayer(\n", - " (norm1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer2): _DenseLayer(\n", - " (norm1): BatchNorm2d(160, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(160, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer3): _DenseLayer(\n", - " (norm1): BatchNorm2d(192, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(192, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer4): _DenseLayer(\n", - " (norm1): BatchNorm2d(224, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(224, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer5): _DenseLayer(\n", - " (norm1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer6): _DenseLayer(\n", - " (norm1): BatchNorm2d(288, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(288, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer7): _DenseLayer(\n", - " (norm1): BatchNorm2d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(320, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer8): _DenseLayer(\n", - " (norm1): BatchNorm2d(352, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(352, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer9): _DenseLayer(\n", - " (norm1): BatchNorm2d(384, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(384, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer10): _DenseLayer(\n", - " (norm1): BatchNorm2d(416, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(416, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer11): _DenseLayer(\n", - " (norm1): BatchNorm2d(448, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(448, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer12): _DenseLayer(\n", - " (norm1): BatchNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(480, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " )\n", - " (transition2): _Transition(\n", - " (norm): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " (conv): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (pool): AvgPool2d(kernel_size=2, stride=2, padding=0)\n", - " )\n", - " (denseblock3): _DenseBlock(\n", - " (denselayer1): _DenseLayer(\n", - " (norm1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer2): _DenseLayer(\n", - " (norm1): BatchNorm2d(288, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(288, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer3): _DenseLayer(\n", - " (norm1): BatchNorm2d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(320, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer4): _DenseLayer(\n", - " (norm1): BatchNorm2d(352, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(352, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer5): _DenseLayer(\n", - " (norm1): BatchNorm2d(384, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(384, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer6): _DenseLayer(\n", - " (norm1): BatchNorm2d(416, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(416, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer7): _DenseLayer(\n", - " (norm1): BatchNorm2d(448, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(448, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer8): _DenseLayer(\n", - " (norm1): BatchNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(480, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer9): _DenseLayer(\n", - " (norm1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer10): _DenseLayer(\n", - " (norm1): BatchNorm2d(544, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(544, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer11): _DenseLayer(\n", - " (norm1): BatchNorm2d(576, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(576, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer12): _DenseLayer(\n", - " (norm1): BatchNorm2d(608, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(608, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer13): _DenseLayer(\n", - " (norm1): BatchNorm2d(640, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(640, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer14): _DenseLayer(\n", - " (norm1): BatchNorm2d(672, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(672, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer15): _DenseLayer(\n", - " (norm1): BatchNorm2d(704, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(704, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer16): _DenseLayer(\n", - " (norm1): BatchNorm2d(736, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(736, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer17): _DenseLayer(\n", - " (norm1): BatchNorm2d(768, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(768, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer18): _DenseLayer(\n", - " (norm1): BatchNorm2d(800, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(800, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer19): _DenseLayer(\n", - " (norm1): BatchNorm2d(832, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(832, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer20): _DenseLayer(\n", - " (norm1): BatchNorm2d(864, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(864, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer21): _DenseLayer(\n", - " (norm1): BatchNorm2d(896, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(896, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer22): _DenseLayer(\n", - " (norm1): BatchNorm2d(928, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(928, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer23): _DenseLayer(\n", - " (norm1): BatchNorm2d(960, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(960, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer24): _DenseLayer(\n", - " (norm1): BatchNorm2d(992, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(992, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " )\n", - " (transition3): _Transition(\n", - " (norm): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " (conv): Conv2d(1024, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (pool): AvgPool2d(kernel_size=2, stride=2, padding=0)\n", - " )\n", - " (denseblock4): _DenseBlock(\n", - " (denselayer1): _DenseLayer(\n", - " (norm1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer2): _DenseLayer(\n", - " (norm1): BatchNorm2d(544, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(544, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer3): _DenseLayer(\n", - " (norm1): BatchNorm2d(576, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(576, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer4): _DenseLayer(\n", - " (norm1): BatchNorm2d(608, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(608, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer5): _DenseLayer(\n", - " (norm1): BatchNorm2d(640, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(640, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer6): _DenseLayer(\n", - " (norm1): BatchNorm2d(672, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(672, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer7): _DenseLayer(\n", - " (norm1): BatchNorm2d(704, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(704, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer8): _DenseLayer(\n", - " (norm1): BatchNorm2d(736, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(736, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer9): _DenseLayer(\n", - " (norm1): BatchNorm2d(768, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(768, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer10): _DenseLayer(\n", - " (norm1): BatchNorm2d(800, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(800, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer11): _DenseLayer(\n", - " (norm1): BatchNorm2d(832, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(832, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer12): _DenseLayer(\n", - " (norm1): BatchNorm2d(864, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(864, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer13): _DenseLayer(\n", - " (norm1): BatchNorm2d(896, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(896, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer14): _DenseLayer(\n", - " (norm1): BatchNorm2d(928, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(928, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer15): _DenseLayer(\n", - " (norm1): BatchNorm2d(960, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(960, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " (denselayer16): _DenseLayer(\n", - " (norm1): BatchNorm2d(992, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu1): ReLU(inplace=True)\n", - " (conv1): Conv2d(992, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (norm2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu2): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " )\n", - " )\n", - " (norm5): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " )\n", - " (classifier): Linear(in_features=1024, out_features=102, bias=True)\n", - ")\n" + "features.conv0\n", + "features.denseblock1.denselayer1.conv1\n", + "features.denseblock1.denselayer1.conv2\n", + "features.denseblock1.denselayer2.conv1\n", + "features.denseblock1.denselayer2.conv2\n", + "features.denseblock1.denselayer3.conv1\n", + "features.denseblock1.denselayer3.conv2\n", + "features.denseblock1.denselayer4.conv1\n", + "features.denseblock1.denselayer4.conv2\n", + "features.denseblock1.denselayer5.conv1\n", + "features.denseblock1.denselayer5.conv2\n", + "features.denseblock1.denselayer6.conv1\n", + "features.denseblock1.denselayer6.conv2\n", + "features.transition1.conv\n", + "features.denseblock2.denselayer1.conv1\n", + "features.denseblock2.denselayer1.conv2\n", + "features.denseblock2.denselayer2.conv1\n", + "features.denseblock2.denselayer2.conv2\n", + "features.denseblock2.denselayer3.conv1\n", + "features.denseblock2.denselayer3.conv2\n", + "features.denseblock2.denselayer4.conv1\n", + "features.denseblock2.denselayer4.conv2\n", + "features.denseblock2.denselayer5.conv1\n", + "features.denseblock2.denselayer5.conv2\n", + "features.denseblock2.denselayer6.conv1\n", + "features.denseblock2.denselayer6.conv2\n", + "features.denseblock2.denselayer7.conv1\n", + "features.denseblock2.denselayer7.conv2\n", + "features.denseblock2.denselayer8.conv1\n", + "features.denseblock2.denselayer8.conv2\n", + "features.denseblock2.denselayer9.conv1\n", + "features.denseblock2.denselayer9.conv2\n", + "features.denseblock2.denselayer10.conv1\n", + "features.denseblock2.denselayer10.conv2\n", + "features.denseblock2.denselayer11.conv1\n", + "features.denseblock2.denselayer11.conv2\n", + "features.denseblock2.denselayer12.conv1\n", + "features.denseblock2.denselayer12.conv2\n", + "features.transition2.conv\n", + "features.denseblock3.denselayer1.conv1\n", + "features.denseblock3.denselayer1.conv2\n", + "features.denseblock3.denselayer2.conv1\n", + "features.denseblock3.denselayer2.conv2\n", + "features.denseblock3.denselayer3.conv1\n", + "features.denseblock3.denselayer3.conv2\n", + "features.denseblock3.denselayer4.conv1\n", + "features.denseblock3.denselayer4.conv2\n", + "features.denseblock3.denselayer5.conv1\n", + "features.denseblock3.denselayer5.conv2\n", + "features.denseblock3.denselayer6.conv1\n", + "features.denseblock3.denselayer6.conv2\n", + "features.denseblock3.denselayer7.conv1\n", + "features.denseblock3.denselayer7.conv2\n", + "features.denseblock3.denselayer8.conv1\n", + "features.denseblock3.denselayer8.conv2\n", + "features.denseblock3.denselayer9.conv1\n", + "features.denseblock3.denselayer9.conv2\n", + "features.denseblock3.denselayer10.conv1\n", + "features.denseblock3.denselayer10.conv2\n", + "features.denseblock3.denselayer11.conv1\n", + "features.denseblock3.denselayer11.conv2\n", + "features.denseblock3.denselayer12.conv1\n", + "features.denseblock3.denselayer12.conv2\n", + "features.denseblock3.denselayer13.conv1\n", + "features.denseblock3.denselayer13.conv2\n", + "features.denseblock3.denselayer14.conv1\n", + "features.denseblock3.denselayer14.conv2\n", + "features.denseblock3.denselayer15.conv1\n", + "features.denseblock3.denselayer15.conv2\n", + "features.denseblock3.denselayer16.conv1\n", + "features.denseblock3.denselayer16.conv2\n", + "features.denseblock3.denselayer17.conv1\n", + "features.denseblock3.denselayer17.conv2\n", + "features.denseblock3.denselayer18.conv1\n", + "features.denseblock3.denselayer18.conv2\n", + "features.denseblock3.denselayer19.conv1\n", + "features.denseblock3.denselayer19.conv2\n", + "features.denseblock3.denselayer20.conv1\n", + "features.denseblock3.denselayer20.conv2\n", + "features.denseblock3.denselayer21.conv1\n", + "features.denseblock3.denselayer21.conv2\n", + "features.denseblock3.denselayer22.conv1\n", + "features.denseblock3.denselayer22.conv2\n", + "features.denseblock3.denselayer23.conv1\n", + "features.denseblock3.denselayer23.conv2\n", + "features.denseblock3.denselayer24.conv1\n", + "features.denseblock3.denselayer24.conv2\n", + "features.transition3.conv\n", + "features.denseblock4.denselayer1.conv1\n", + "features.denseblock4.denselayer1.conv2\n", + "features.denseblock4.denselayer2.conv1\n", + "features.denseblock4.denselayer2.conv2\n", + "features.denseblock4.denselayer3.conv1\n", + "features.denseblock4.denselayer3.conv2\n", + "features.denseblock4.denselayer4.conv1\n", + "features.denseblock4.denselayer4.conv2\n", + "features.denseblock4.denselayer5.conv1\n", + "features.denseblock4.denselayer5.conv2\n", + "features.denseblock4.denselayer6.conv1\n", + "features.denseblock4.denselayer6.conv2\n", + "features.denseblock4.denselayer7.conv1\n", + "features.denseblock4.denselayer7.conv2\n", + "features.denseblock4.denselayer8.conv1\n", + "features.denseblock4.denselayer8.conv2\n", + "features.denseblock4.denselayer9.conv1\n", + "features.denseblock4.denselayer9.conv2\n", + "features.denseblock4.denselayer10.conv1\n", + "features.denseblock4.denselayer10.conv2\n", + "features.denseblock4.denselayer11.conv1\n", + "features.denseblock4.denselayer11.conv2\n", + "features.denseblock4.denselayer12.conv1\n", + "features.denseblock4.denselayer12.conv2\n", + "features.denseblock4.denselayer13.conv1\n", + "features.denseblock4.denselayer13.conv2\n", + "features.denseblock4.denselayer14.conv1\n", + "features.denseblock4.denselayer14.conv2\n", + "features.denseblock4.denselayer15.conv1\n", + "features.denseblock4.denselayer15.conv2\n", + "features.denseblock4.denselayer16.conv1\n", + "features.denseblock4.denselayer16.conv2\n", + "classifier\n" ] } ], "source": [ - "print(model)" + "# print parameters\n", + "for (name, layer) in get_prunable_layers(model):\n", + " print(f\"{name}\")" ] }, { "cell_type": "markdown", - "id": "7a05d884", + "id": "e037a028", "metadata": {}, "source": [ - "We create a pruning recipe. We will start with the `GlobalMagnitudePruning` algorithm, pruning layers on average to 90%. We target all of the Conv layers (per the regexes in the `params` dictionary below) - which tie to the layer names above. We will run GMP for 10 epochs and then fine-tune for the final 3 epochs." + "We will apply pruning to each of the `convs` and exclude the `classifier` (which is the final projection head). Fortunately, SparseML allows us to pass regexes to identify layers in the network, so we can use the following list to identify the relevant layers for pruning:\n", + "\n", + " - 'features.conv0.weight'\n", + " - 're:features.denseblock1.*.conv1.weight'\n", + " - 're:features.denseblock1.*.conv2.weight'\n", + " - 're:features.transition1.conv.weight'\n", + " - 're:features.denseblock2.*.conv1.weight'\n", + " - 're:features.denseblock2.*.conv2.weight'\n", + " - 're:features.transition2.conv.weight'\n", + " - 're:features.denseblock3.*.conv1.weight'\n", + " - 're:features.denseblock3.*.conv2.weight'\n", + " - 're:features.transition3.conv.weight'\n", + " - 're:features.denseblock4.*.conv1.weight'\n", + " - 're:features.denseblock4.*.conv2.weight'\n", + "\n", + "Here is what the recipe looks like:\n", + "\n", + "```yaml\n", + "# Epoch and Learning-Rate variables\n", + "num_epochs: 13.0\n", + "pruning_epochs: 10.0\n", + "init_lr: 0.00025\n", + "final_lr: 0.0001\n", + "inter_func: cubic\n", + "mask_type: unstructured\n", + "\n", + "training_modifiers:\n", + " - !EpochRangeModifier\n", + " start_epoch: 0.0\n", + " end_epoch: eval(num_epochs)\n", + "\n", + " - !LearningRateFunctionModifier\n", + " final_lr: eval(final_lr)\n", + " init_lr: eval(init_lr)\n", + " lr_func: cosine\n", + " start_epoch: 0.0\n", + " end_epoch: eval(pruning_epochs)\n", + " \n", + " - !LearningRateFunctionModifier\n", + " final_lr: eval(final_lr)\n", + " init_lr: eval(init_lr)\n", + " lr_func: cosine\n", + " start_epoch: eval(pruning_epochs)\n", + " end_epoch: eval(num_epochs)\n", + "\n", + "# Pruning\n", + "pruning_modifiers:\n", + " - !GlobalMagnitudePruningModifier\n", + " init_sparsity: 0.05\n", + " final_sparsity: 0.85\n", + " start_epoch: 0.0\n", + " end_epoch: eval(pruning_epochs)\n", + " update_frequency: 0.5\n", + " params: \n", + " - 'features.conv0.weight'\n", + " - 're:features.denseblock1.*.conv1.weight'\n", + " - 're:features.denseblock1.*.conv2.weight'\n", + " - 're:features.transition1.conv.weight'\n", + " - 're:features.denseblock2.*.conv1.weight'\n", + " - 're:features.denseblock2.*.conv2.weight'\n", + " - 're:features.transition2.conv.weight'\n", + " - 're:features.denseblock3.*.conv1.weight'\n", + " - 're:features.denseblock3.*.conv2.weight'\n", + " - 're:features.transition3.conv.weight'\n", + " - 're:features.denseblock4.*.conv1.weight'\n", + " - 're:features.denseblock4.*.conv2.weight'\n", + " leave_enabled: True\n", + " inter_func: eval(inter_func)\n", + " mask_type: eval(mask_type)\n", + "```\n", + "\n", + "This recipe specifies that we will run the GMP algorithm for the first 10 epochs. We start at an `init_sparsity` level of 5% and gradually increase sparsity to a `final_sparsity` level of 85% following a `cubic` curve. The pruning is applied in an `unstructured` manner, meaning that any weight can be pruned.\n", + "\n", + "Over the final 3 epochs, we will fine-tune the 85% pruned model further. Since we set `leave_enabled=True` the sparsity level will be maintained as the fine-tuning occurs.\n", + "\n" ] }, { "cell_type": "code", - "execution_count": 7, - "id": "9b17fc31", + "execution_count": 47, + "id": "b2add8fc", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "# Epoch and Learning-Rate variables\r\n", - "num_epochs: 13.0\r\n", - "pruning_epochs: 10.0\r\n", - "init_lr: 0.0003\r\n", - "final_lr: 0.0001\r\n", - "inter_func: cubic\r\n", - "mask_type: unstructured\r\n", - "\r\n", - "training_modifiers:\r\n", - " - !EpochRangeModifier\r\n", - " start_epoch: 0.0\r\n", - " end_epoch: eval(num_epochs)\r\n", - "\r\n", - " - !LearningRateFunctionModifier\r\n", - " final_lr: eval(final_lr)\r\n", - " init_lr: eval(init_lr)\r\n", - " lr_func: cosine\r\n", - " start_epoch: 0.0\r\n", - " end_epoch: eval(pruning_epochs)\r\n", - " \r\n", - " - !LearningRateFunctionModifier\r\n", - " final_lr: eval(final_lr)\r\n", - " init_lr: eval(init_lr)\r\n", - " lr_func: cosine\r\n", - " start_epoch: eval(pruning_epochs)\r\n", - " end_epoch: eval(num_epochs)\r\n", - "\r\n", - "# Pruning\r\n", - "pruning_modifiers:\r\n", - " - !GlobalMagnitudePruningModifier\r\n", - " init_sparsity: 0.05\r\n", - " final_sparsity: 0.90\r\n", - " start_epoch: 0.0\r\n", - " end_epoch: eval(pruning_epochs)\r\n", - " update_frequency: 0.5\r\n", - " params: \r\n", - " - 'features.conv0.weight'\r\n", - " - 're:features.denseblock1.*.conv1.weight'\r\n", - " - 're:features.denseblock1.*.conv2.weight'\r\n", - " - 're:features.transition1.conv.weight'\r\n", - " - 're:features.denseblock2.*.conv1.weight'\r\n", - " - 're:features.denseblock2.*.conv2.weight'\r\n", - " - 're:features.transition2.conv.weight'\r\n", - " - 're:features.denseblock3.*.conv1.weight'\r\n", - " - 're:features.denseblock3.*.conv2.weight'\r\n", - " - 're:features.transition3.conv.weight'\r\n", - " - 're:features.denseblock4.*.conv1.weight'\r\n", - " - 're:features.denseblock4.*.conv2.weight'\r\n", - " leave_enabled: True\r\n", - " inter_func: eval(inter_func)\r\n", - " mask_type: eval(mask_type)\r\n", - "\r\n", - "finetuning_modifiers:\r\n", - " - !ConstantPruningModifier\r\n", - " start_epoch: eval(pruning_epochs)\r\n", - " params: __ALL_PRUNABLE__" - ] - } - ], + "outputs": [], "source": [ - "!cat recipe-0.yaml" + "pruning_recipe_path = \"./recipes/densenet-flowers-pruning-recipe.yaml\"" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, + "id": "9b17fc31", + "metadata": { + "scrolled": false + }, + "outputs": [], + "source": [ + "!cat ./recipes/densenet-flowers-pruning-recipe.yaml" + ] + }, + { + "cell_type": "code", + "execution_count": 49, "id": "68646bc7", "metadata": {}, "outputs": [], "source": [ "# create ScheduledModifierManager and Optimizer wrapper\n", - "manager = ScheduledModifierManager.from_yaml(\"./recipe-0.yaml\")\n", + "manager = ScheduledModifierManager.from_yaml(pruning_recipe_path)\n", "logger = TensorBoardLogger(log_path=\"./tensorboard_outputs\")\n", "optimizer = manager.modify(model, optimizer, loggers=[logger], steps_per_epoch=len(train_loader))" ] }, + { + "cell_type": "markdown", + "id": "7c4ba042", + "metadata": {}, + "source": [ + "Next, kick off the GMP training loop. \n", + "\n", + "As you can see, we use the wrapped `optimizer` and `model` in the same way as above. SparseML parsed the recipe and updated the `optimizer` with the logic of GMP algorithm from the recipe. This allows you to just the `optimizer` and `model` as usual, with all of the pruning-related logic specified by the declarative recipe interface.\n", + "\n", + "Our 85% sparsified model reaches ~91.5% validation accuracy (vs ~92.5% for the dense model)." + ] + }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 50, "id": "601c8c21", "metadata": { "scrolled": false @@ -1983,7 +1188,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "2e512276a1b94d328a06e1c5d0497ad9", + "model_id": "181013fb564f45828d9cce72589b3846", "version_major": 2, "version_minor": 0 }, @@ -1999,8 +1204,8 @@ "output_type": "stream", "text": [ "Training Epoch: 1/13\n", - "Training Loss: 0.05704788229195401\n", - "Top 1 Acc: 0.9970588235294118\n", + "Training Loss: 0.043860748992301524\n", + "Top 1 Acc: 0.9990196078431373\n", "\n", "Running Validation Epoch 1/13\n" ] @@ -2008,7 +1213,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "a6610db1025a4e408e01777550481193", + "model_id": "a8cdead2769d4377b6cf53fc91028e3f", "version_major": 2, "version_minor": 0 }, @@ -2024,8 +1229,8 @@ "output_type": "stream", "text": [ "Validation Epoch: 1/13\n", - "Val Loss: 0.5254904199391603\n", - "Top 1 Acc: 0.8970588235294118\n", + "Val Loss: 0.49546412169001997\n", + "Top 1 Acc: 0.8950980392156863\n", "\n", "Running Training Epoch 2/13\n" ] @@ -2033,7 +1238,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ddead9b1388b47e7856a34c7e38aad28", + "model_id": "a92e647b8b6e413284659d33dbb5bf9e", "version_major": 2, "version_minor": 0 }, @@ -2049,8 +1254,8 @@ "output_type": "stream", "text": [ "Training Epoch: 2/13\n", - "Training Loss: 0.045509724208386615\n", - "Top 1 Acc: 0.996078431372549\n", + "Training Loss: 0.031713149510324\n", + "Top 1 Acc: 0.9980392156862745\n", "\n", "Running Validation Epoch 2/13\n" ] @@ -2058,7 +1263,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0137f5c63a3f4a749078a913f0cabcee", + "model_id": "e8af1f0eb7514408a36fad527f4119c5", "version_major": 2, "version_minor": 0 }, @@ -2074,8 +1279,8 @@ "output_type": "stream", "text": [ "Validation Epoch: 2/13\n", - "Val Loss: 0.49433585489168763\n", - "Top 1 Acc: 0.888235294117647\n", + "Val Loss: 0.380035838810727\n", + "Top 1 Acc: 0.9117647058823529\n", "\n", "Running Training Epoch 3/13\n" ] @@ -2083,7 +1288,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ca13cec88da1496e95c05201d51527b4", + "model_id": "cadd8b75f6a3468487921687fb7a1902", "version_major": 2, "version_minor": 0 }, @@ -2099,8 +1304,8 @@ "output_type": "stream", "text": [ "Training Epoch: 3/13\n", - "Training Loss: 0.05249260214623064\n", - "Top 1 Acc: 0.9941176470588236\n", + "Training Loss: 0.016048584191594273\n", + "Top 1 Acc: 1.0\n", "\n", "Running Validation Epoch 3/13\n" ] @@ -2108,7 +1313,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "9be1acbb68544497b2292273cfaa14e1", + "model_id": "b23ad27123a84b9ab3e9d37bcfd94fc2", "version_major": 2, "version_minor": 0 }, @@ -2124,8 +1329,8 @@ "output_type": "stream", "text": [ "Validation Epoch: 3/13\n", - "Val Loss: 0.4971598202828318\n", - "Top 1 Acc: 0.8921568627450981\n", + "Val Loss: 0.3518236926756799\n", + "Top 1 Acc: 0.9156862745098039\n", "\n", "Running Training Epoch 4/13\n" ] @@ -2133,7 +1338,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1bd3b6304db3419c95a294acd40659c2", + "model_id": "dd5bbfdb2df24c67b036c84f67258727", "version_major": 2, "version_minor": 0 }, @@ -2149,8 +1354,8 @@ "output_type": "stream", "text": [ "Training Epoch: 4/13\n", - "Training Loss: 0.04789798497222364\n", - "Top 1 Acc: 0.9970588235294118\n", + "Training Loss: 0.013376500370213762\n", + "Top 1 Acc: 1.0\n", "\n", "Running Validation Epoch 4/13\n" ] @@ -2158,7 +1363,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c961395abf764ec095859a79fce2bb8b", + "model_id": "c80d92282c594060bc65c655b0db0184", "version_major": 2, "version_minor": 0 }, @@ -2174,7 +1379,7 @@ "output_type": "stream", "text": [ "Validation Epoch: 4/13\n", - "Val Loss: 0.405253738630563\n", + "Val Loss: 0.37410336383618414\n", "Top 1 Acc: 0.9098039215686274\n", "\n", "Running Training Epoch 5/13\n" @@ -2183,7 +1388,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "761637d2e00344fab4bda339bc4a0210", + "model_id": "4352b279fc0546458ce3e0717f41b051", "version_major": 2, "version_minor": 0 }, @@ -2199,7 +1404,7 @@ "output_type": "stream", "text": [ "Training Epoch: 5/13\n", - "Training Loss: 0.03558145748684183\n", + "Training Loss: 0.01488300270284526\n", "Top 1 Acc: 1.0\n", "\n", "Running Validation Epoch 5/13\n" @@ -2208,7 +1413,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1d7b4d1526c547e282f9a75f58ca9cf1", + "model_id": "d0e7239ec24f4a5cbaf9d38b942358b8", "version_major": 2, "version_minor": 0 }, @@ -2224,8 +1429,8 @@ "output_type": "stream", "text": [ "Validation Epoch: 5/13\n", - "Val Loss: 0.40998171758838\n", - "Top 1 Acc: 0.9098039215686274\n", + "Val Loss: 0.3517874537501484\n", + "Top 1 Acc: 0.9156862745098039\n", "\n", "Running Training Epoch 6/13\n" ] @@ -2233,7 +1438,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "390a8c78d2d2414fa9d09025917048e4", + "model_id": "1448047bbf7f41fdbf84106aff303104", "version_major": 2, "version_minor": 0 }, @@ -2249,7 +1454,7 @@ "output_type": "stream", "text": [ "Training Epoch: 6/13\n", - "Training Loss: 0.043919957941398025\n", + "Training Loss: 0.020687898708274588\n", "Top 1 Acc: 1.0\n", "\n", "Running Validation Epoch 6/13\n" @@ -2258,7 +1463,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0a209b2b76c845428e21b54bb3a6a507", + "model_id": "9efe9031bf4b4ebbae2d992dc3266230", "version_major": 2, "version_minor": 0 }, @@ -2274,8 +1479,8 @@ "output_type": "stream", "text": [ "Validation Epoch: 6/13\n", - "Val Loss: 0.44851411995477974\n", - "Top 1 Acc: 0.9009803921568628\n", + "Val Loss: 0.38692406262271106\n", + "Top 1 Acc: 0.9137254901960784\n", "\n", "Running Training Epoch 7/13\n" ] @@ -2283,7 +1488,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f661fa461e094e55bc9cffb2d7b343c5", + "model_id": "d27c0cbd9d6e4e02b44043050c58c2c1", "version_major": 2, "version_minor": 0 }, @@ -2299,7 +1504,7 @@ "output_type": "stream", "text": [ "Training Epoch: 7/13\n", - "Training Loss: 0.06865048292092979\n", + "Training Loss: 0.029207701765699312\n", "Top 1 Acc: 0.9990196078431373\n", "\n", "Running Validation Epoch 7/13\n" @@ -2308,7 +1513,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "a81beb9cb8b1419da298f072304c8ae7", + "model_id": "f1752d47a0c348999b1ab92624ebca01", "version_major": 2, "version_minor": 0 }, @@ -2324,8 +1529,8 @@ "output_type": "stream", "text": [ "Validation Epoch: 7/13\n", - "Val Loss: 0.500796954613179\n", - "Top 1 Acc: 0.8813725490196078\n", + "Val Loss: 0.4347131696995348\n", + "Top 1 Acc: 0.8990196078431373\n", "\n", "Running Training Epoch 8/13\n" ] @@ -2333,7 +1538,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "b00986f389b6483c972f952b56cbe06e", + "model_id": "e764a1922b0740488b5ceb97a636f5fa", "version_major": 2, "version_minor": 0 }, @@ -2349,7 +1554,7 @@ "output_type": "stream", "text": [ "Training Epoch: 8/13\n", - "Training Loss: 0.08089102717349306\n", + "Training Loss: 0.05598480207845569\n", "Top 1 Acc: 0.9950980392156863\n", "\n", "Running Validation Epoch 8/13\n" @@ -2358,7 +1563,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "2f8dcafdd8604d0faa7b64c5f5e79913", + "model_id": "e28f85a917a94204b50687e4397313ad", "version_major": 2, "version_minor": 0 }, @@ -2374,8 +1579,8 @@ "output_type": "stream", "text": [ "Validation Epoch: 8/13\n", - "Val Loss: 0.4999986342154443\n", - "Top 1 Acc: 0.8911764705882353\n", + "Val Loss: 0.5028206340502948\n", + "Top 1 Acc: 0.8813725490196078\n", "\n", "Running Training Epoch 9/13\n" ] @@ -2383,7 +1588,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "72813826e9b44537bc5a538c8bab0d0e", + "model_id": "5f340b8a413e417ca9bad5a3201dd55c", "version_major": 2, "version_minor": 0 }, @@ -2399,7 +1604,7 @@ "output_type": "stream", "text": [ "Training Epoch: 9/13\n", - "Training Loss: 0.05980767833534628\n", + "Training Loss: 0.030482763570034876\n", "Top 1 Acc: 0.9990196078431373\n", "\n", "Running Validation Epoch 9/13\n" @@ -2408,7 +1613,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "3271f7a2f30246ccb4d0f7d52a5c88e5", + "model_id": "cd02f0a64301403bb37da14323dd4284", "version_major": 2, "version_minor": 0 }, @@ -2424,8 +1629,8 @@ "output_type": "stream", "text": [ "Validation Epoch: 9/13\n", - "Val Loss: 0.4825127385556698\n", - "Top 1 Acc: 0.8960784313725491\n", + "Val Loss: 0.4592747155111283\n", + "Top 1 Acc: 0.8941176470588236\n", "\n", "Running Training Epoch 10/13\n" ] @@ -2433,7 +1638,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "484ed067c6494cd2aaa6efebbc429ed1", + "model_id": "2ddef4c5bcba426784e011fc5a8659e5", "version_major": 2, "version_minor": 0 }, @@ -2449,8 +1654,8 @@ "output_type": "stream", "text": [ "Training Epoch: 10/13\n", - "Training Loss: 0.029828229744452983\n", - "Top 1 Acc: 1.0\n", + "Training Loss: 0.017036149831255898\n", + "Top 1 Acc: 0.9990196078431373\n", "\n", "Running Validation Epoch 10/13\n" ] @@ -2458,7 +1663,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "494926a49a0d43ddb0388a178d648048", + "model_id": "4f8d775853324429b9f7061478101253", "version_major": 2, "version_minor": 0 }, @@ -2474,8 +1679,8 @@ "output_type": "stream", "text": [ "Validation Epoch: 10/13\n", - "Val Loss: 0.45201362296938896\n", - "Top 1 Acc: 0.9009803921568628\n", + "Val Loss: 0.40747271745931357\n", + "Top 1 Acc: 0.9019607843137255\n", "\n", "Running Training Epoch 11/13\n" ] @@ -2483,7 +1688,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "dc469c3661154167b2b6a2f8d217f577", + "model_id": "2ce09a16874e4e8c94deb40dea6bdb29", "version_major": 2, "version_minor": 0 }, @@ -2499,7 +1704,7 @@ "output_type": "stream", "text": [ "Training Epoch: 11/13\n", - "Training Loss: 0.017061863880371675\n", + "Training Loss: 0.008050348522374406\n", "Top 1 Acc: 1.0\n", "\n", "Running Validation Epoch 11/13\n" @@ -2508,7 +1713,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "d740893d1cef427491c9f1b94dfc97cb", + "model_id": "d8834eae2a924e6d8f6aa9c713f2cd09", "version_major": 2, "version_minor": 0 }, @@ -2524,8 +1729,8 @@ "output_type": "stream", "text": [ "Validation Epoch: 11/13\n", - "Val Loss: 0.40311497752554715\n", - "Top 1 Acc: 0.9058823529411765\n", + "Val Loss: 0.36801655124872923\n", + "Top 1 Acc: 0.9068627450980392\n", "\n", "Running Training Epoch 12/13\n" ] @@ -2533,7 +1738,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "e6efb89313174a7a8b9509755e7ac5f5", + "model_id": "1343cce0b7d9417ca5cf9b788e5bbcf3", "version_major": 2, "version_minor": 0 }, @@ -2549,7 +1754,7 @@ "output_type": "stream", "text": [ "Training Epoch: 12/13\n", - "Training Loss: 0.01124472642550245\n", + "Training Loss: 0.005260431091301143\n", "Top 1 Acc: 1.0\n", "\n", "Running Validation Epoch 12/13\n" @@ -2558,7 +1763,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "b09c5f91fd804f89bd99e83ac865f23f", + "model_id": "5952900528a6494e9025afcce97fcef2", "version_major": 2, "version_minor": 0 }, @@ -2574,8 +1779,8 @@ "output_type": "stream", "text": [ "Validation Epoch: 12/13\n", - "Val Loss: 0.38544022431597114\n", - "Top 1 Acc: 0.907843137254902\n", + "Val Loss: 0.3571971161291003\n", + "Top 1 Acc: 0.9117647058823529\n", "\n", "Running Training Epoch 13/13\n" ] @@ -2583,7 +1788,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "8386e7eca94f4335a00b0f3ae5c21e37", + "model_id": "07cb82ea02634c619c57a823e1d2872e", "version_major": 2, "version_minor": 0 }, @@ -2599,7 +1804,7 @@ "output_type": "stream", "text": [ "Training Epoch: 13/13\n", - "Training Loss: 0.009475693295826204\n", + "Training Loss: 0.004477048831176944\n", "Top 1 Acc: 1.0\n", "\n", "Running Validation Epoch 13/13\n" @@ -2608,7 +1813,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "80b3b1e8c68446bb94be4cf4d0ff37e3", + "model_id": "81030fbb34a04181ae3cb25acc470275", "version_major": 2, "version_minor": 0 }, @@ -2624,8 +1829,8 @@ "output_type": "stream", "text": [ "Validation Epoch: 13/13\n", - "Val Loss: 0.38191458326764405\n", - "Top 1 Acc: 0.907843137254902\n", + "Val Loss: 0.3466116476338357\n", + "Top 1 Acc: 0.9137254901960784\n", "\n" ] } @@ -2653,9 +1858,28 @@ "manager.finalize(model)" ] }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "83dff592", + "metadata": {}, + "source": [ + "Here is a sample of the TensorBoard output, showing the validation accuracy, a particular layer's sparsity level, and the learning rate over time.\n", + "\n", + "![tensorboard output](./images/densenet-tensorboard-output.png)" + ] + }, + { + "cell_type": "markdown", + "id": "b9dea1bd", + "metadata": {}, + "source": [ + "We can print layer-by-layer sparsity as well." + ] + }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 55, "id": "df5afa94", "metadata": { "scrolled": false @@ -2665,157 +1889,154 @@ "name": "stdout", "output_type": "stream", "text": [ - "Checking Sparsity Level:\n", - "features.conv0.weight: 0.4670\n", - "features.denseblock1.denselayer1.conv1.weight: 0.7366\n", - "features.denseblock1.denselayer1.conv2.weight: 0.8294\n", - "features.denseblock1.denselayer2.conv1.weight: 0.7461\n", - "features.denseblock1.denselayer2.conv2.weight: 0.8658\n", - "features.denseblock1.denselayer3.conv1.weight: 0.7488\n", - "features.denseblock1.denselayer3.conv2.weight: 0.8242\n", - "features.denseblock1.denselayer4.conv1.weight: 0.8116\n", - "features.denseblock1.denselayer4.conv2.weight: 0.8263\n", - "features.denseblock1.denselayer5.conv1.weight: 0.8702\n", - "features.denseblock1.denselayer5.conv2.weight: 0.8846\n", - "features.denseblock1.denselayer6.conv1.weight: 0.8377\n", - "features.denseblock1.denselayer6.conv2.weight: 0.8414\n", - "features.transition1.conv.weight: 0.7090\n", - "features.denseblock2.denselayer1.conv1.weight: 0.9321\n", - "features.denseblock2.denselayer1.conv2.weight: 0.8885\n", - "features.denseblock2.denselayer2.conv1.weight: 0.8816\n", - "features.denseblock2.denselayer2.conv2.weight: 0.8591\n", - "features.denseblock2.denselayer3.conv1.weight: 0.8839\n", - "features.denseblock2.denselayer3.conv2.weight: 0.8458\n", - "features.denseblock2.denselayer4.conv1.weight: 0.8619\n", - "features.denseblock2.denselayer4.conv2.weight: 0.8654\n", - "features.denseblock2.denselayer5.conv1.weight: 0.8901\n", - "features.denseblock2.denselayer5.conv2.weight: 0.8490\n", - "features.denseblock2.denselayer6.conv1.weight: 0.9099\n", - "features.denseblock2.denselayer6.conv2.weight: 0.8675\n", - "features.denseblock2.denselayer7.conv1.weight: 0.8786\n", - "features.denseblock2.denselayer7.conv2.weight: 0.8752\n", - "features.denseblock2.denselayer8.conv1.weight: 0.8897\n", - "features.denseblock2.denselayer8.conv2.weight: 0.8620\n", - "features.denseblock2.denselayer9.conv1.weight: 0.9001\n", - "features.denseblock2.denselayer9.conv2.weight: 0.8787\n", - "features.denseblock2.denselayer10.conv1.weight: 0.8735\n", - "features.denseblock2.denselayer10.conv2.weight: 0.8839\n", - "features.denseblock2.denselayer11.conv1.weight: 0.8851\n", - "features.denseblock2.denselayer11.conv2.weight: 0.8883\n", - "features.denseblock2.denselayer12.conv1.weight: 0.8731\n", - "features.denseblock2.denselayer12.conv2.weight: 0.9021\n", - "features.transition2.conv.weight: 0.7686\n", - "features.denseblock3.denselayer1.conv1.weight: 0.9162\n", - "features.denseblock3.denselayer1.conv2.weight: 0.9001\n", - "features.denseblock3.denselayer2.conv1.weight: 0.9382\n", - "features.denseblock3.denselayer2.conv2.weight: 0.8986\n", - "features.denseblock3.denselayer3.conv1.weight: 0.9175\n", - "features.denseblock3.denselayer3.conv2.weight: 0.9029\n", - "features.denseblock3.denselayer4.conv1.weight: 0.9182\n", - "features.denseblock3.denselayer4.conv2.weight: 0.8827\n", - "features.denseblock3.denselayer5.conv1.weight: 0.9336\n", - "features.denseblock3.denselayer5.conv2.weight: 0.8802\n", - "features.denseblock3.denselayer6.conv1.weight: 0.9197\n", - "features.denseblock3.denselayer6.conv2.weight: 0.8812\n", - "features.denseblock3.denselayer7.conv1.weight: 0.9384\n", - "features.denseblock3.denselayer7.conv2.weight: 0.8724\n", - "features.denseblock3.denselayer8.conv1.weight: 0.9050\n", - "features.denseblock3.denselayer8.conv2.weight: 0.8814\n", - "features.denseblock3.denselayer9.conv1.weight: 0.9080\n", - "features.denseblock3.denselayer9.conv2.weight: 0.8771\n", - "features.denseblock3.denselayer10.conv1.weight: 0.9408\n", - "features.denseblock3.denselayer10.conv2.weight: 0.8811\n", - "features.denseblock3.denselayer11.conv1.weight: 0.9341\n", - "features.denseblock3.denselayer11.conv2.weight: 0.8668\n", - "features.denseblock3.denselayer12.conv1.weight: 0.9250\n", - "features.denseblock3.denselayer12.conv2.weight: 0.8906\n", - "features.denseblock3.denselayer13.conv1.weight: 0.9382\n", - "features.denseblock3.denselayer13.conv2.weight: 0.8583\n", - "features.denseblock3.denselayer14.conv1.weight: 0.9465\n", - "features.denseblock3.denselayer14.conv2.weight: 0.8806\n", - "features.denseblock3.denselayer15.conv1.weight: 0.9248\n", - "features.denseblock3.denselayer15.conv2.weight: 0.8868\n", - "features.denseblock3.denselayer16.conv1.weight: 0.9390\n", - "features.denseblock3.denselayer16.conv2.weight: 0.9144\n", - "features.denseblock3.denselayer17.conv1.weight: 0.9208\n", - "features.denseblock3.denselayer17.conv2.weight: 0.9015\n", - "features.denseblock3.denselayer18.conv1.weight: 0.9316\n", - "features.denseblock3.denselayer18.conv2.weight: 0.8972\n", - "features.denseblock3.denselayer19.conv1.weight: 0.9243\n", - "features.denseblock3.denselayer19.conv2.weight: 0.8959\n", - "features.denseblock3.denselayer20.conv1.weight: 0.9266\n", - "features.denseblock3.denselayer20.conv2.weight: 0.9072\n", - "features.denseblock3.denselayer21.conv1.weight: 0.9231\n", - "features.denseblock3.denselayer21.conv2.weight: 0.8998\n", - "features.denseblock3.denselayer22.conv1.weight: 0.9252\n", - "features.denseblock3.denselayer22.conv2.weight: 0.8816\n", - "features.denseblock3.denselayer23.conv1.weight: 0.9239\n", - "features.denseblock3.denselayer23.conv2.weight: 0.9144\n", - "features.denseblock3.denselayer24.conv1.weight: 0.9298\n", - "features.denseblock3.denselayer24.conv2.weight: 0.9119\n", - "features.transition3.conv.weight: 0.8484\n", - "features.denseblock4.denselayer1.conv1.weight: 0.8742\n", - "features.denseblock4.denselayer1.conv2.weight: 0.9153\n", - "features.denseblock4.denselayer2.conv1.weight: 0.8730\n", - "features.denseblock4.denselayer2.conv2.weight: 0.9475\n", - "features.denseblock4.denselayer3.conv1.weight: 0.8826\n", - "features.denseblock4.denselayer3.conv2.weight: 0.9251\n", - "features.denseblock4.denselayer4.conv1.weight: 0.9017\n", - "features.denseblock4.denselayer4.conv2.weight: 0.9404\n", - "features.denseblock4.denselayer5.conv1.weight: 0.9002\n", - "features.denseblock4.denselayer5.conv2.weight: 0.9578\n", - "features.denseblock4.denselayer6.conv1.weight: 0.8988\n", - "features.denseblock4.denselayer6.conv2.weight: 0.9595\n", - "features.denseblock4.denselayer7.conv1.weight: 0.9121\n", - "features.denseblock4.denselayer7.conv2.weight: 0.9608\n", - "features.denseblock4.denselayer8.conv1.weight: 0.9153\n", - "features.denseblock4.denselayer8.conv2.weight: 0.9612\n", - "features.denseblock4.denselayer9.conv1.weight: 0.9176\n", - "features.denseblock4.denselayer9.conv2.weight: 0.9655\n", - "features.denseblock4.denselayer10.conv1.weight: 0.9182\n", - "features.denseblock4.denselayer10.conv2.weight: 0.9652\n", - "features.denseblock4.denselayer11.conv1.weight: 0.9192\n", - "features.denseblock4.denselayer11.conv2.weight: 0.9639\n", - "features.denseblock4.denselayer12.conv1.weight: 0.9230\n", - "features.denseblock4.denselayer12.conv2.weight: 0.9637\n", - "features.denseblock4.denselayer13.conv1.weight: 0.9260\n", - "features.denseblock4.denselayer13.conv2.weight: 0.9638\n", - "features.denseblock4.denselayer14.conv1.weight: 0.9283\n", - "features.denseblock4.denselayer14.conv2.weight: 0.9632\n", - "features.denseblock4.denselayer15.conv1.weight: 0.9297\n", - "features.denseblock4.denselayer15.conv2.weight: 0.9655\n", - "features.denseblock4.denselayer16.conv1.weight: 0.9254\n", - "features.denseblock4.denselayer16.conv2.weight: 0.9621\n", + "features.conv0.weight: 0.4184\n", + "features.denseblock1.denselayer1.conv1.weight: 0.6761\n", + "features.denseblock1.denselayer1.conv2.weight: 0.7671\n", + "features.denseblock1.denselayer2.conv1.weight: 0.6769\n", + "features.denseblock1.denselayer2.conv2.weight: 0.8130\n", + "features.denseblock1.denselayer3.conv1.weight: 0.6814\n", + "features.denseblock1.denselayer3.conv2.weight: 0.7528\n", + "features.denseblock1.denselayer4.conv1.weight: 0.7571\n", + "features.denseblock1.denselayer4.conv2.weight: 0.7544\n", + "features.denseblock1.denselayer5.conv1.weight: 0.8184\n", + "features.denseblock1.denselayer5.conv2.weight: 0.8309\n", + "features.denseblock1.denselayer6.conv1.weight: 0.7914\n", + "features.denseblock1.denselayer6.conv2.weight: 0.7735\n", + "features.transition1.conv.weight: 0.6437\n", + "features.denseblock2.denselayer1.conv1.weight: 0.9088\n", + "features.denseblock2.denselayer1.conv2.weight: 0.8509\n", + "features.denseblock2.denselayer2.conv1.weight: 0.8362\n", + "features.denseblock2.denselayer2.conv2.weight: 0.7972\n", + "features.denseblock2.denselayer3.conv1.weight: 0.8374\n", + "features.denseblock2.denselayer3.conv2.weight: 0.7750\n", + "features.denseblock2.denselayer4.conv1.weight: 0.8064\n", + "features.denseblock2.denselayer4.conv2.weight: 0.8011\n", + "features.denseblock2.denselayer5.conv1.weight: 0.8513\n", + "features.denseblock2.denselayer5.conv2.weight: 0.7810\n", + "features.denseblock2.denselayer6.conv1.weight: 0.8767\n", + "features.denseblock2.denselayer6.conv2.weight: 0.8048\n", + "features.denseblock2.denselayer7.conv1.weight: 0.8297\n", + "features.denseblock2.denselayer7.conv2.weight: 0.8145\n", + "features.denseblock2.denselayer8.conv1.weight: 0.8360\n", + "features.denseblock2.denselayer8.conv2.weight: 0.7907\n", + "features.denseblock2.denselayer9.conv1.weight: 0.8567\n", + "features.denseblock2.denselayer9.conv2.weight: 0.8235\n", + "features.denseblock2.denselayer10.conv1.weight: 0.8154\n", + "features.denseblock2.denselayer10.conv2.weight: 0.8226\n", + "features.denseblock2.denselayer11.conv1.weight: 0.8305\n", + "features.denseblock2.denselayer11.conv2.weight: 0.8266\n", + "features.denseblock2.denselayer12.conv1.weight: 0.8147\n", + "features.denseblock2.denselayer12.conv2.weight: 0.8448\n", + "features.transition2.conv.weight: 0.6985\n", + "features.denseblock3.denselayer1.conv1.weight: 0.8672\n", + "features.denseblock3.denselayer1.conv2.weight: 0.8512\n", + "features.denseblock3.denselayer2.conv1.weight: 0.9014\n", + "features.denseblock3.denselayer2.conv2.weight: 0.8561\n", + "features.denseblock3.denselayer3.conv1.weight: 0.8684\n", + "features.denseblock3.denselayer3.conv2.weight: 0.8519\n", + "features.denseblock3.denselayer4.conv1.weight: 0.8734\n", + "features.denseblock3.denselayer4.conv2.weight: 0.8226\n", + "features.denseblock3.denselayer5.conv1.weight: 0.8974\n", + "features.denseblock3.denselayer5.conv2.weight: 0.8180\n", + "features.denseblock3.denselayer6.conv1.weight: 0.8764\n", + "features.denseblock3.denselayer6.conv2.weight: 0.8219\n", + "features.denseblock3.denselayer7.conv1.weight: 0.9095\n", + "features.denseblock3.denselayer7.conv2.weight: 0.8101\n", + "features.denseblock3.denselayer8.conv1.weight: 0.8529\n", + "features.denseblock3.denselayer8.conv2.weight: 0.8216\n", + "features.denseblock3.denselayer9.conv1.weight: 0.8591\n", + "features.denseblock3.denselayer9.conv2.weight: 0.8137\n", + "features.denseblock3.denselayer10.conv1.weight: 0.9050\n", + "features.denseblock3.denselayer10.conv2.weight: 0.8202\n", + "features.denseblock3.denselayer11.conv1.weight: 0.8952\n", + "features.denseblock3.denselayer11.conv2.weight: 0.8025\n", + "features.denseblock3.denselayer12.conv1.weight: 0.8779\n", + "features.denseblock3.denselayer12.conv2.weight: 0.8349\n", + "features.denseblock3.denselayer13.conv1.weight: 0.9029\n", + "features.denseblock3.denselayer13.conv2.weight: 0.7903\n", + "features.denseblock3.denselayer14.conv1.weight: 0.9133\n", + "features.denseblock3.denselayer14.conv2.weight: 0.8175\n", + "features.denseblock3.denselayer15.conv1.weight: 0.8790\n", + "features.denseblock3.denselayer15.conv2.weight: 0.8279\n", + "features.denseblock3.denselayer16.conv1.weight: 0.8979\n", + "features.denseblock3.denselayer16.conv2.weight: 0.8660\n", + "features.denseblock3.denselayer17.conv1.weight: 0.8712\n", + "features.denseblock3.denselayer17.conv2.weight: 0.8479\n", + "features.denseblock3.denselayer18.conv1.weight: 0.8885\n", + "features.denseblock3.denselayer18.conv2.weight: 0.8439\n", + "features.denseblock3.denselayer19.conv1.weight: 0.8771\n", + "features.denseblock3.denselayer19.conv2.weight: 0.8424\n", + "features.denseblock3.denselayer20.conv1.weight: 0.8775\n", + "features.denseblock3.denselayer20.conv2.weight: 0.8493\n", + "features.denseblock3.denselayer21.conv1.weight: 0.8743\n", + "features.denseblock3.denselayer21.conv2.weight: 0.8407\n", + "features.denseblock3.denselayer22.conv1.weight: 0.8802\n", + "features.denseblock3.denselayer22.conv2.weight: 0.8169\n", + "features.denseblock3.denselayer23.conv1.weight: 0.8757\n", + "features.denseblock3.denselayer23.conv2.weight: 0.8595\n", + "features.denseblock3.denselayer24.conv1.weight: 0.8835\n", + "features.denseblock3.denselayer24.conv2.weight: 0.8561\n", + "features.transition3.conv.weight: 0.7817\n", + "features.denseblock4.denselayer1.conv1.weight: 0.8013\n", + "features.denseblock4.denselayer1.conv2.weight: 0.8734\n", + "features.denseblock4.denselayer2.conv1.weight: 0.8007\n", + "features.denseblock4.denselayer2.conv2.weight: 0.9233\n", + "features.denseblock4.denselayer3.conv1.weight: 0.8141\n", + "features.denseblock4.denselayer3.conv2.weight: 0.8888\n", + "features.denseblock4.denselayer4.conv1.weight: 0.8402\n", + "features.denseblock4.denselayer4.conv2.weight: 0.9181\n", + "features.denseblock4.denselayer5.conv1.weight: 0.8396\n", + "features.denseblock4.denselayer5.conv2.weight: 0.9465\n", + "features.denseblock4.denselayer6.conv1.weight: 0.8353\n", + "features.denseblock4.denselayer6.conv2.weight: 0.9475\n", + "features.denseblock4.denselayer7.conv1.weight: 0.8559\n", + "features.denseblock4.denselayer7.conv2.weight: 0.9485\n", + "features.denseblock4.denselayer8.conv1.weight: 0.8596\n", + "features.denseblock4.denselayer8.conv2.weight: 0.9471\n", + "features.denseblock4.denselayer9.conv1.weight: 0.8662\n", + "features.denseblock4.denselayer9.conv2.weight: 0.9583\n", + "features.denseblock4.denselayer10.conv1.weight: 0.8692\n", + "features.denseblock4.denselayer10.conv2.weight: 0.9559\n", + "features.denseblock4.denselayer11.conv1.weight: 0.8692\n", + "features.denseblock4.denselayer11.conv2.weight: 0.9565\n", + "features.denseblock4.denselayer12.conv1.weight: 0.8767\n", + "features.denseblock4.denselayer12.conv2.weight: 0.9562\n", + "features.denseblock4.denselayer13.conv1.weight: 0.8804\n", + "features.denseblock4.denselayer13.conv2.weight: 0.9558\n", + "features.denseblock4.denselayer14.conv1.weight: 0.8836\n", + "features.denseblock4.denselayer14.conv2.weight: 0.9550\n", + "features.denseblock4.denselayer15.conv1.weight: 0.8865\n", + "features.denseblock4.denselayer15.conv2.weight: 0.9575\n", + "features.denseblock4.denselayer16.conv1.weight: 0.8806\n", + "features.denseblock4.denselayer16.conv2.weight: 0.9506\n", "classifier.weight: 0.0000\n" ] } ], "source": [ - "print(f\"Checking Sparsity Level:\")\n", "for (name, layer) in get_prunable_layers(model):\n", " print(f\"{name}.weight: {tensor_sparsity(layer.weight).item():.4f}\")" ] }, + { + "cell_type": "markdown", + "id": "c1522d44", + "metadata": {}, + "source": [ + "Finally, export your model to ONNX." + ] + }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 53, "id": "417ac105", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ubuntu/rshaw/python-venvs/sparseml-env/lib/python3.8/site-packages/torch/onnx/utils.py:439: UserWarning: It is recommended that constant folding be turned off ('do_constant_folding=False') when exporting the model in training-amenable mode, i.e. with 'training=TrainingMode.TRAIN' or 'training=TrainingMode.PRESERVE' (when model is in training mode). Otherwise, some learnable model parameters may not translate correctly in the exported ONNX model because constant folding mutates model parameters. Please consider turning off constant folding or setting the training=TrainingMode.EVAL.\n", - " warnings.warn(\n" - ] - } - ], + "outputs": [], "source": [ "save_dir = \"experiment-0\"\n", "exporter = ModuleExporter(model, output_dir=save_dir)\n", - "exporter.export_pytorch(name=\"densenet-121-sparse-flowers-experiment-0.pth\")\n", - "exporter.export_onnx(torch.randn(1, 3, 224, 224), name=\"sparse-gmp-model.onnx\", convert_qat=True)" + "exporter.export_pytorch(name=\"densenet-121-sparse-flowers.pth\")\n", + "exporter.export_onnx(torch.randn(1, 3, 224, 224), name=\"sparse-model.onnx\", convert_qat=True)" ] }, { @@ -2823,14 +2044,18 @@ "id": "22c96232", "metadata": {}, "source": [ - "The resulting model is is 90% sparse and achieves validation accuracy of 90.3% (vs the unoptimized dense model at 91.3%) without much hyperparameter search,\n", + "## Wrap Up\n", + "\n", + "The resulting model is is 85% sparse and achieves validation accuracy of ~91.5% (vs the unoptimized dense model at ~92.5%) without much hyperparameter search.\n", "\n", "Key hyperparameter experiments you may want to run include:\n", "- Learning rate\n", "- Learning rate schedule\n", "- Sparsity level\n", - "- Skipping layers\n", - "- Number of pruning epochs" + "- Number of pruning epochs\n", + "\n", + "\n", + "DeepSparse supports speedup from pruning and quantization. To reach maximum performance, check out our examples of quantizing a model!" ] } ], diff --git a/integrations/torchvision/tutorials/images/densenet-tensorboard-output.png b/integrations/torchvision/tutorials/images/densenet-tensorboard-output.png new file mode 100644 index 0000000000000000000000000000000000000000..a59171cda0a58029f63958691bb2c052fa8224bb GIT binary patch literal 477355 zcmd?Qby$?&)-X&+gCHP{bVy1gH6SI@-64&1Njrc@N=qZ5bhilNpnxFVrIOMh4Kpxv z-|z7Io%5XYobUOr@4c?~zwe!4uDNILz4l(U*IIk+MVyY7DhVMSAqEBpiP~c&Jq!$j zBMc0zY(~<$}un(k5sYmSy)A6 z-(_UPEFviYJr3&>J)Mmi?9IS^u)gd&HRTb8{5zJ>73!lC7CC$jt3C>KLQLktz|-%q zY-yuOoYie2$plkY`EcseR*7+zcrW9U9Tb1!hR4%o@qWh&e@<}nn$?PGy69YCpM8x; z8KXjk`C??Oa3DsK(UyLjE!w1PY#6S~vJ52?_T@0rn@+(=zTD@^)X z;_XNKy<51^if;Jc4cvmlkG?zE6TW;%)^j&f>kgIA8q4g)gCKGlYvT7 z@2AQ4KB1YuL&>g6Jo-uypIC30F@%$hqxZhQTr3f`?Oi+Xcu7ICo#Z@%lSlTSXnX5$ zl)VQV18rF>QV7Fj^et!@>jx+VM^~ejc~8D%MdEkkMucOQG&qFEG2`J&2h#_yLX@>1 ztY8rgU}3Ek+2g9Re-BYQqQQ&*Qb(UZyhN-E!b1_1lK zLe#|A2li=gfwupMcq zo~ZiUh8Uyb$0cd3I59)FZ^7T_#02EZJ;2@U#vSdaZO8UpA&r!$iN!i*#(5pH;MC(U zfSLZq?*ZPMNS_AE8mzr;l?I%BjLt7F#xat@DON<=F$5x9S8iL#{#wD=#y;$Jx~1?K z|86ncRV;yR+&tSTKE<(eWC}hzm72n2DxXr+j`HE7h z<^$LzctMGwkAw_JW>gY&c>UN1l}w!_>5`Kao5$6hg``L=U)L#APgpw324i)FTPb#q zQ#(U&9~f#-i}W!(;QaROU4sE1MY@ehqi_vY^|##y$H2GsHkKxW7k9YU{PH8DyYDi@ zbFIjPlFLz8N7eTPtegkZzrcZpU#>3W8$_~vDOgcnAxk4Ljrty?_Xy`H{VLfi<)^F; zg2Py)cLEc++n9%al(x6M>AdfF%X*U@OE#v%W9PM5Q_s{c*qQVw7J%!yv;T-4n(Q$_;^y#Hy;QoT~C?ud8(Y+ji+@x~iNEnJQiwOzAc2 z+f|oVs?AVUyBkZ_Jy$;<$#~NG?n+<3^3`*Mei)0QV@vIoKk zrBbH9^xl@rS#_CoJwk9 zqJ=K0Ej2BXEpW5bmNw_N)4@vp+navkZ&eG`m!CkC4`(@_nY;S7__hqS2Dk<|U+y^X zwC}R-YD`p4KdhQ6P1rHp@$ozL%i8`k*Hw4zl0ETY_Q98iS3SGYmiI2KJlhLk1@iS8 zp2XO(CTlyu<%kQ}K#9Fjxx99Htk=Lu%B;wk9tC_r6*70)q{-(yM#%ac8?PeGiCzTyvnfbKY&o*{* zVg6=*WAlQ>P)`T<412NVsxP}atp#HJ9rGQtS9K&a-^Lu%G+Rdu&EN4)iO)UnI^d9= z9vu<*Q8)SLo$Rwi55X2|&*g`a55D?FIV+vV(%*h|n=ghn#w-ResUzu55=RnAlAx;D zYYoPaZohLs#ZE#C ziS{MG_nnE}d55#R7c;+lEZ3~Ime!xHrvB00@P1i2^4d|rw&0vS5I1o2L}m>!G4!i? z+!Z!wy>xr&rn)i5LILY&&yGXRWdVpjq|Ul^SrO_B{S1nO z<$UHww_U0C9K!X(*;jPBL)xfAaIXWIsc6VesOImK+vSVB^T;a++46!qpEakd(M3w{}aP)m3ZekZ<~(kYFf#(ef&yFV&sD)FrJ z@8l`Do+(dvIqz+&O~ly63QY)Q2x;4@_Gu-{Qm7{9k$n*PV;L%sOoK}kh!adk%_^Pu zw)E!qUaCc?4W)OasdA1z{+wc)!m8n-!BNUt=AnMTL@)Y$X8w=phnC5fz4e-YP1*pD zPha4lj#arTv{$qwQ?wpyKUvNJUeWi}ZeBQf30DbU1-dOgTO#@lfpWl9SJ+Gh0&{oL zKgyh%W@^vI*A%$H_T%@hSj^kC;5=NSPIjZ$KP!G7e8dh?3ko?gJefMpQ!;yJq5DH= zJx-tVdHg|N=~|tdRl1SpZhDk@+g)aybwWC#*43EM&S{magfoRyPhE$JnD24vq#6_X zthtkNGakENE433|CP4F|wbwOW-+D-ejh^9&n23mvDLFb0yS;Ugb6u+Wv%u0EFkC$R z{q1Q;oc{Ndv=6@No8n_4xe_5u@2wxbsN^rrc=E(^__6@zjrm!=y~wV3=xZwxEaP}+ zG)p?e_zl#w*W3@7(}mR`{B689*OEB?sEhM)2;AlG`aJBpkhGCIl#m566LM5WJ^41+ zl;LTtY2sh^wbge0+2FIC-8!*5u5@!|HI^M0Lmm76b3E8Qmj<*({58R_0vK?D3zGQL zCyHl!B3snjcQ!XuM$Tu9X6~BDn#Z@vEabMI4|@(TKWn3P<6XY+?{p5COPXhN7rQ4W zCQT9`P^s)%+A7;Q`P_1mvAwf#wAkbH-Y?mWkS|s{OIz2ImzK*+pJC@1r}DoPhF%)R zY{v}lre0N^hmkChSSH?2e5?6Xvvy=@B<8mCy`>kuXOA~@-@aE*(oGtX79ZF9ISI80 z{dB1`8>d=JVRo3WAs5ujUsk(r0IzH=f2mz4(<3$IGrP5)>T9)?J1R0JVc`YSS^hKo zVmsi&GO2%iz_j&Q`+VT{Q$63U?NPfdlt5uSdEmyG;phy}9BaM5m3I4!Q6S-|GsrID)HR ze&U+ux~r{OFe~Hx;&};I`_|-X<5;J4taa!gew6;{SXGv|ASti`8i!c>SYPsfua1~Y zSlWgy0JG=ru24S^6@WODg9%<2flvEYH~U2j)8u4PG6pa*iXs2`vM zllBvBOk#0S5sL7+ADBgD81gaKB7-JDH$AV45MM8MO>Nl@tF z!-s+ogaw6#`OzczeS25d5FO{9GLWU%+m9{s#MtuD_R)xtUB#$0g9g z%|yw?9nESqYI4G2qM|Z?t@Hor`WL2ugBtoe_$Ye1qapp|{w1t`0RMaEe**rsrs==d z6c_(*Oa5EWzd_#6Af@Nv>*?ly!$U(47e6^+8NvUl`9Gmd{{K>yzQpAaVh zBgDVA{wIXCj|-X)Pj66@6Z*#r|K9eG@iKxpvi~<-_*>EbYDH_B9HEThe`&28p@j%l zEe3`>hMJOsK_KRS7g4^Wu_0G*)nt$uf#PGGeqELoPiFjeW!+;T!U~yh5w|vq*RUg{ ztR}&d{O7h>z>Fmbnz7RE*3)yQ4rVKt~t4_>(8Z%F`m|pxYtbmlWBLV)qCQPO-jUN+`g@*zOz|*EC=ZYnOYnnW5jqYeT%eC|Whm7H*fY@d z`Y^CPC8hwfjYuef>>%h-m`svoPDiq0QzWv`sZ$AAsHP0Y6f63&=Sh*z_43unn z1_KqBu;)G3oJ@{6TJcxo{lU355go{KW>M6~{`N1K9;g4o7DN6+u z+urhhu>Eynq%30j*!Lsgzj z7!wH@+oEhr3Mru&@whR%@h}T*nMKxGxbd+BrNZ%tHP61~cvve~grctFZUuk4a$qZ7 zYcE14f%LqW7t1YR1)5HXk9A-EyNl&^v-sA?n?~oVB9w7>5z6UZ%C60eN7rM2xLQFs z$={!S%NC(OhkBx#PX;kGcTE<*y$U09FtKcWC1r!FNhomt7kS`|h9~1S3DjOb zr#;VVOlTKv);H%TsD32iPQ#AMud?MHgTw?2g-FuSI;7wh{RpItNa@jO{f$h5Oo;Q2 z6!)|*iIlKi@oHgrq1*uBVG&&a_`}HEMd$-Ex3cN~5>Rh?WB4pkePR94L^y05sAeff z8Q%!a@Oo?!ItO%W;spcYrL0)a%TCikwcVW|CxQ2GvBO)yDwI<*)d6hMy4%hfoY*2e zfVqI)(wEj*J9acRwmc_0&JQ`CantAPc!XZ_2Ds-o^@YuIZSti_n$sJ7p_VBUDlBHi z?`>hq8?dQ_;$eDP5<+ckU@zEFY`2>r2&NlR1<=KwLklm)NhOTOdr2yZ7m5?Jm&_ffr*k)kN+8>Z z8?8W<@Tqg^WyS+z&0+1@pv7$eFvHdj>eJ zt^9sh%7hOAN6S>E!^i0?DWsoEtC5>s6_KpfKYCMIIgjt=?BgPgk~(ISt|SZ^^6|vK zT3_KQ7q!yfdCqx_O}?o*nQ%+sj2Zr0S>CY{nT+(*r>JUkO?(q>n=awaL_aqy9II1WCHr+VTpA5NA;H+Verwd`NE{J>Ux7dEgAzcFnH@ zKV9w)nCJe4IFNejGrkg$K%zdym}kYUlH2zNqevxCcX~)qTh~n>PMqNOSz7%`gpH;8 zLV8vubd@wQT|)JOJ@>#U+{zH@2Gc3`h>@TR(v0ANN3z`CGQBYNWe@ z5o~j}1$)+hajPGFy%*%|5jhZ|pj|uuON0<<%U$S``jjeiw=i}(-Hr|IKFSDgY>__p zRn(^2lzB@erA-7)^-?o){k7i>p3U7v(?;W-c6I(BS zQsy1MYL12HP>WUFx35?n=K975nLi09Lcus4<9p8&&{V!vU^)4S>(k`;sUo-2c^$V?kW$?P=HXw4ygj zF??tfw+}|lXIntbR0+?^Er!!4aNYRHVm$a^M-lwToX#{+@TiFf+PiSgW!}j751&EEVSfX@_nPU&C@CcCWgI2~pTD^!pDEalk5mlB zd(L0Rj8WPk*4#UXr8#P^H%vrOI3v<*_B{ChmnaM`k~`;u$YMJ~j+CAgS?kzB%8q!2 zS0zwU_8YJI^S;|avRB;+>_(3#*;|0^rKh5W&rs#(^|RJ&>Er(jddw^`B9x;jX`eD1 zA`d#L;?eH5Jf}S@s_}1IlE+z$Hc=n0Riv+5XzTRGAZJLs8uFV_ynopmbl(LN=U!=B z?Bw4*IqGfs)Kk!Xr>*D156Oe*^@4SO!%toJt~EX*qBtnxSyogl@SN^^+W0wWF@9pi zWj$;sR-byl*Cdl!vdct90NpA4D@x1Kf3?Y^k&p{*1;($cYlTKcoKfG8l=eJ-^xf!9 zH3GM<&@bs9VU33j!j{E|coF*K*42yri)Auv+I!(j*Pe^eDIo7AnE4j>=-M-z>L#R< z*jA|F8W9dXw|6=~n-JwOSf{%)_-a()#@0*#>cd$Yq2Gpo#pElb&fSQ-1+=}uq%gGs zzsun{iwPZn`~8D~wA`WPnfe^Zj~R@(9xA@T>zrp!GEKVFlp+t*u0y?>3R!O|3k z8_$=(Vk>j5ZG#_;M}oGVT-UCjmCzyR+$P}&M0{w`;LAefl&j;7rMcOBg&)7Qm6psd zV|=--BK>!0@cZkRIl_3@4qXdqBUOx|ri;FR>$$bO>))oa_*r4Gx-6 zbjTV_+}LI7sw}|RijHyq5ewDxJB|Y)tX$G9;OqN(hhT~4IKaz~HCBJ@G+2yM6<{U! zrgFiQML;LZPu2@)yo;l(zqJ^lO&i$A;>LIcQIw=yg!(a zwB{A+!5=J>Ya_9rbhq-ysB{!ic-#?%8&ME{PEi6nJFpbmz=~GKIEH zSA|UjcrVPE>w4@@!!L(idtX&SS3S*`QNGyT3ESZV!0ZW>kquG!XMF>DjVwpRc*fks z@jYDB=%{e=%9pwZmgU~#6|_v-^EvD~S|oEU+Y;0@J}}BT@GwTc%!G@;XdoJxVe`5> zZNQ@lhjGYS>3dav52@$FFJ?#A%G5Y&AuYfFjrpEnEv%uoaWKeePq0R!1$;@scKgOC zE#mA6UUBEQfKpIYzj8r6xLFS&=}4Kl(%yrmw*ux?ZS6b633;P3Qw4jyivDIo)842p z$eRX4jO%pW=hO4$K@lLQ9>gF1iZQzl^*`VC+Ip+XZ!hJ@WYE+~c6$Vx3yOjW5wj84 zCfOM>=ns%S%akuLy9D-FJW8FAzJ0U3i0tU=ME;6oZ~Wqj5iOO(+o#@BIZpWx`QA3l z#0PDT!m`cWUYLdeIf+m>R-v}q^R`_0ES2>8fWn$#k*9X^R(#3o2|g$BD$L&|kd%z9;oM;ndS-m*TyU1_Dwm3$80T z;~lCGqlvNby-{h852Uh;rTjOs1lrL)Ait5x?yfxJ>+9^zwH4y`IbxoBeK;fkh&H|66b>Sjt+zG)HIL1YAyxfi_`w@SIBarb}bK4 zz*H3IIHf3T$h!P<77{1Yv4Nv?odvA#Q0t_kh5!VE*uFBL4OpKtIq{5u*=%RPD?t`? zm~!bke6IzJ#JKN>UsvDg)zIU70ITT&BS|4|UB>cg*f4oxUSFH^Cew7hxburd4ocV6 z9TV@4-MjUmf-mTk@h5N2)k`vK;)sx)4HLv_k7HNn=@c}%-h zHnewG=LS@C+Bbhge?voo3@`%}yJQBX{VP)It$a!DG$mND(F477XGNojafU&mfNplec(T(%Sh zzKj3jKGq~N!USst?D(YkM9nyiV}5wTeyww^7j}X_SM!_4=tk!Q94R6t>u_Q=p*>%_ znK|#$#FXdH@#hQ9Rf$IWh;bp&i3aTp)j}Oc#ba)*I&+hf8}wK}JA4Dt-_VV}-a8ak zcHH-7zN69fyFruN*ta|Z{2~#t{8X@?vCT<}29&!tit`qB~X{pEW2l0b0sQ zSRH>!aNGSS|2BK)6Ohd0m(N~pPnB%8)OwA`0X@g)MR$)t*7|}ia!U1p^79@BB$5b) zohWzYbVw%rO_+){Ht&dp{F-lE8vJz1zw)D>)zcw(Goy(yxuR@i9chpoPqFvDIBo9zCz=vPJO$pYn}wKr=OrXr}sSM zs2{J$qibV!m1eyx?1E%-E0DqN*NW*Kk**;XcTqqAC&?-Ocf2;Y3VthvcBYG2^>GlO=)I{8k)b6?|a5!U^jcLsO*!d&{Q zwI!9svjw*NyVC$#6`W5>H4P=uX~u=ZJ(Xv%5sxO_D|d-j35TT)-V6mXdf7v9Z7~HW z_-piMfs2I%?*Lg)hA1QxuJAs?F0gB~6>EL@339!Nvn^?}N{lA;?t9wMXB1a4K#+-! zzuN{)Jx+e-;!sHYw+hC&%z%MgkKesXrOu-%jCZ39G`GUz+kq~z;c?&b&ClOzLDt)) zTW0ZCCDD!kCzAHy|0j}s3rvQp7h4^vbhbq)e&$tIkJ_=CwWK$Etne5X3L{Lq z)%}RnFH~n1WG_A(z7Fd_1jrT|xB6@eh0OZ;Wy^ubdAXOfhnp&EOfWDH3W(OQdPoiS z>!UWhra7&6v|n&YI%x+b3Z#pbK=p^8Cj+g#>mw&2riaG7#>k0c{6TM@;qFN!+w~ms z$A}WJ+*kojyC9%*iPK~~aV6K2@pCoe{z*4n-GGwxVp+X2H__!o`MQy_=-*4LQ@>kZ z=l-8Ww`qb$BOw8;0juMyj29k1tNQr5VQ54F2_|sfJh0*!X=LDr%GOXQf^w+COywhL z9n+il6#ATYf8j^>P#F9}^5 zvUqk(za#$}`b%%p>dL+pQEp>abL-wi@K1ALscZoFuoriEsloD? zH1y#)DJ+-%tpLm8_`?uu%U0)jSFcXh*Nt9Jt1p^A#^xEt_>L`%c`glgI1jac+73=> z0wd#|Qh%8D5`8fS4~q?5f)1Lf5w>NTb+Jdm?54<`jjMr#oRctHpJ?@5?Zxc1@*B z*n-DzJDDKZtx`W-midIjfc4Q|W;Iv-=`x6E!L(n4Up^eqEVFKEy@#^ zGS_ct=iWFF5Kw5*ke!@}a4z3047+e`+4{5WIoIe0Yw{be8}$1i1EM3SMr!yZeJ}ok z^XKds;cHwu_1tEB@0G}Uj5BPFkcqLAK(be*!wXyUV|smGI^23n=3n%rpIh)$2IZaMQbJ)BVfu^}}Bi(o-&rk6mQAeSPm?nQT2A-|#cO5GF3so;T0RF%>@MEP1V zBH*{0upOBT>Z#25}tTdC9w5TuogTzy~{BRN~HLh0Q6j<#x^E%e~oXN2P;E zuWEMn@d+G0>>eJ*8Y~Z@&07!<1u>Lykt_76at!Ab^4PH9r$P@+U?i#@-#H|ETRGIxn3H!;;<(Jr=g(JAl#9TrdTgTnpB1 z{VFee=Vk#aj<2{f~fh)*`rX)Hm<-980N0F>hL_LV@1G@$(Pl$Fd=H zRbD>o7ixDyM+!sa#zTo6ys4zxV2`({j1k_v-)yQcC_3Pya>!e6vUK0Dwemcl7NNb< zS^U9+XL~tWqwDn+rCq9n&(W7Lx?QGu_O%=-DaQ9v+UUgY*KnKCo7@>|O2JqEms(+s*noLafw=liIib;uco+4>Ue_;K&R z1FKEhTBoc4I65r=X!Z!deMkVzwF-_HUvZ(*fl|!@;9IkimdA980Y$ut$|+RicLBRk zE?7)&2A0SLnvE5Ux0EN2!QfPKd_2bRpLjHvTM%dORJhXw+|?h4>9g5!d))f=rTJBI z$kcH~z|v0NALuvQdnQH67;9giDQhaXUd7=)I;`a2)_!V?t>|tuR zQ4tRTg)-lJ1YU)x1^Gi^;)3B2voYPoK#x!q7m`t;7W!z%9{TigK}nb9!J$S7*KI-l z`Xk1VezsoL6^-+!T%Wu9KcpR$c5OWH7mejaY_^rUEN0s%kX}%+{Gna$?lo5D`@zKX zAi}_cL4X)JEYV~wV*;E!=&Ai_&f@}Q@x5jGk*W)+Em6O)>^HUJWN8X4F%?Ny2i{ftb$u*5_SkF?o}OlNS;N z+x`8pS-D3#ZjLgxTG1bmBn^>*-y$H}K>ij)&Q1E|{9|OZ4YD;Cg>7*-{fqph2^LMT zvf^E}&4k<2DBmBr{=?+E!@6Ooq z9xfkq`8}mnzfids$s#&JeNkgSLyV)4*e`X1`*vX~M&;q_AObyys|+9k{I5I6vK*!C)k z&eD!Ro~nrEc}V9%uj$nG3iJJ2fyeBk;MdBeu*%MbKZ@B9ms3GVk9}Fk+vDVV5mcWH zJ^xx2eu@{k$`*(D)C-D9bS$i@c&x3_8UC_Lp#dv@oVmed)?XDZ!@{!r@nDaYDA*D6 zAmEPNhlgn@eoT)tzdJA@n3yMPcviis6n5vogM*;BW-3@(+pRO1H2@A@k>gcfr}#aH z%RwIUIl9xaJ!b4o-+>~Co&TIN6*@`W1^H;83jt~-PSPSTwBn>=VORZKG49&{7a`Xa zPztRKo`mcahOjIYt}*pNj&PrI1HKHD=o=amO_Ni^Smg1Ta3tS1d3Z$mT@6T><|q3g zK!nqtj60~tp4hxOrR+l!31O#j=*vP+!@!_lXTIha7w==#*8Jx!h^a_t0_}YVQVdHT zcVG+{38(6Vw+q%O+LO|fSlGSsL5zW7ZynCy4Z^ub-%w3IRxT8FXcKfUId%18m3->! zUuXT}X($}6+a#3E-|Fn47^Qn!Q%ne^ew?Fu7LbS%9Zksnh8B|u9p^8dCO^b=#{LZT z3|V8sa5Zzpr1+uqWA@7=p=kYLp^#=-zcrOKOY*L_Ge9aWrV~l{u1IMTN4|~R$oU}x zx~6+R)=j7*yF>E?WWZdo=8mn7e)-7g1FuAToph}|Yxz0#N;>M}izutav^vE)=gpy3 za7#y0R7-pR$pxNC$Dj5Ww62lqNK&sf&>Kbbu)qY@pAkz>@;4NVE9RTR{pT~^uaGeV z{A8dTKk!wvx9j}cRS70(^)v`J=fa|kno;BPPN#* zvqCyzeG&m{mv)fP7EO<9XfPu8UL9s_eJDd?vyg||<8mRadz65zs);v>Kvv)Y_*GmK93JNX2;8pT8PucAg+6}y$`3 zb}TqS>>~0{k6VG#&+WU}R2(vu%1yAJ3YtoeLXl?0(+U>)S{HaldS6&GP`cI@{x|oj zzrxyW-N37u&pZ+0*L!17ss!kME5y^s zC!dB=&?hHD=d`saUact&w1(d2f6<2%l7sY&s9RwN)fv^4g;Jis1%K7SV+dE?yQ!T+kfG= zCEJWzSM6Lf{~C{31wLG%SBG=q*NK~dfUNMLunC(WMd6A!cNk(%gEPU>AW6P5_7hmc zn?DclLhtg$Q?SgPl(uAN5?u%*ma#0q+&@w;(%ANEg-w^Y7JzQz!1v3O{V-WqsR(63 z6~R^W`$ZjAN>{50 zyMmc}aVq|vl(grCDa_lN9hlFEPso*4569W>kyJ33KuPY*aV#u9Hk|CvUSkK-QwGpp zr%b?r>yZ^5I4H_O zL-07>ikfqew$87lY99$N0n>dA1Pr4;J*OFI{j&Gm3=q^z?k;H*=~Dv)S$2T>N-`AX z5QP$g36JZTTPO7m=n~s*^&Na|z>%1EU+V-y5Qj`&1E*i@Dh;T!O(NI-#`w7x5OMJ} zn*R$FxFAO}NET?EePG2-9}2vg3xC2^;q_GVhLAioA%kc_##O#*p~2HYe`oS!Tmv%c zZDwh%mJ3Q3d*$ndZjZYUTl!5Xw>rzc zeQR%4@~tL~*Zz+6>)|$G{@T~39L58zpJ{U39n8#Vo1fIBD2ECO{}^m(5q8Y5U`c@6 z+P7u6xHt^+e0)T8+&AFHJ2g3&ZRqogZ!IBp!Kkb>L#X;Up=mEQTXU_3IN<=PBfc`ow$a#O!(TQLVp`kIsAO1 z?Djf>_Sw9UfY;KytsCBr{$J0#|0A_ixF>1joz8fD=wnsAA(Z4Kvh>Ant>z&4LrMa? z;%@d?3y=gfw#OaD z210LPvyJ!217zs`$}Rv&QrruGbl@Fi!#$GNa`_!5Y7OU+7^@!1cI_HG8K-jh zO@3C#o13a6(mN?2V_ww8WZ*ZP6W9sNe{v^ylCrE>@0E>hiGG%F=|Rv=w!_C783Ftk zRE|AMD&kqCIc<~Z-Bx4sHqkV5XmB0tT-$=20lOhJ(Ya=nps_p6+Uee_(Hk;G#|i1q zOa>~45t>#JkI%+ds;u&7hFG)OEHaacA`4&bPgb`Oc0EfyxtXsbj_!ttlXiI&Mb<4< zxP!7iXp?{d_|X z8#nYnp!bk%=;Iq{$v~S)y+!rEJ0h;Q1PGFzqOZzCjkcmpY;!7)NN<&Zb{P#8JY((h z7pfNI`BUEk+u=ZQ%E5`^@HFNR$8aa<0?0(*k6LFX{a>R5t(umjZ%9_yubC8WKi=}R zAVc!8`$gDpab#4ox!stbiu>rRxqr@hg`SZ?q)0{lU859NFZqy$12iIh-}4``7y$lf zSx9D}>UpovZt_RTUENL!MvXNY9DXY-Ir>EhV;tB^f5wirmUq)&c(GqOst>caogQ;$ zMBLk$C)ZjBPx)Ho}BIEy}5a+2plJ8?KTbD?73pEKl-NCIC6^F*l3d}GM7DAh;5Kz`LXxWC52 z`OhH-3VX@lLv2lKAw>_uMlho$)1RR*MJI!Kaz1%LbD{dKJm})7=fQw3*zgo03S!2b zS>jM2K=Ccij5GUOFkEFKONFx-A(%RjEHu&=bDTgd>%KzGY(eVc^OB)OeUjo#(BgUk zS(*1}$$tmR%7R+fLIs4)Ah8+rdU$eV7OYuWuFCbok))O>3k5g^B&KZg zW4+dt&U&8&YdrWa?X5QbPCmg9TW^$h+`ttzFhX->u-C=w3pEg>a7BF;&R)x-Pct_ok*3#=**Bm?A`!S0 z<(BEcp__=p^Fr{JPeLywFANa%g?&1Fk%=oQ(-DbtR~8ov#g@?Wbm*>U4jA+j2MHbpEiZe{+b@VvKz4 z?g>AZfB96@P12g=Oi!>8i|rB5u5yx^Pz!6{CM)E6wj^tlZBH({Dv09E#BohU zO*jpJI@BFw_+1asHPoWL$KyzBKBQOIHXTJgIpKT62j=v}_lUXSiV&)8-QU^Hs5$?# z_rGPvhQO%P#$NB8Sod#Wel{F$*X=TnB^3d&GJ}O6zgzKsdz*i8=*WyZ4467+4CrLr zZjXrRL3Dj{`~&+C?t9jw1P>5>1>KE3tN#(VSvXC2Q|!F`=rTKzUHw>Ffz#1+eZFPV zDf5qUekJ0A-K?%p!Pd>iHwETgLY)v-4+uYHf<-QDLB3f(02aZ zk0!)a04_g8U@kmc1T-0rJi;%y^`hh|W8@nI`P8EO?XMysIh&@;ovLw)+kW#Q%^IO1 zObIp5Kewow!q`D6j*yR}G7Mil1mR*Ths!wc>xY?@!S|u!nMl1s?H9$j?WduNoGh-F zJhWdS=MckTn4z$*0o#ss1lwnxM25NgGKZ%D-5P&YjQrqZ`&End3{1O)&Ma;g))DF4 z9)a1(v;ch?W=R(7ipB#1rKW8Y=P?RzFYu;6umQ()6S-s1cBw7e)-(vBcPa3Eo9UxW z33!)8vCoD#K(gDfCExmqLodIzNMouX%K~F_bTb-R{iZK zOL+i-3UacWs`E~P@jPeL#7_c(T1W?zKaLB0e;Ap7&M@w+dV^<( z5dDq1NK*CP;B=l+1eY5Z=EKBIrgnlC2u9{^IOEHF=zvgX1X!y2aP&Ih*f8W}*p`)y zK@(MbfX&@vr)pk!Xhvy~;@wp3*0VplR7tOIy-K&M%u+o+3tX}iO*!y4J+nO@R8hIW zd67}hpmm@F)=?+1*swg$Nqlpu57&3Cl6z=$JMFCA+_KyrYG|Dsrkn01{L7o;S-!3j z+Ry!l>S=$w_}#$@VsoHxS*$+j+l8@cwN%KITD^LYnZ!NlR?-CPb$MOBPuj8e#K&yD zki`GT8q;D^>>vOhKE&8Hj(&Z_% z1MIsh1#_WK$xfi?H<$}{qkjv)9z3 zwVAqy1KGBOYSNMXC=q5X$(>~bV;RBgz08^W3)ZdF?Qh}}k=j=om719M(L=yI$;5-W z4s_*l)nMDTb-4O``CloN%%H;kC~etN`tF{R_F%cFK|Jjxhc^mRP_a4ZEfwim%DwK| zq6MQrEwUNgpO*5E2@A;`ZHpgs)5pD&S;So!%C7{li@Gb;v40Ydu45U{J-v^lVBWE2 zRp9udb}?79J&!ghh{~eMe(h6Ym zL@V1&A7lQ=`JG6l;}TW6FNi7Se?Yp3zO78&V_0L>se`J+l?=J*DYlsc$6F=ELNd_) zT>}ppzNBNv7qYu(os`*Tm%|{`UvrEn(*arv(y?p$2j`3(j1&g9ZND*`Kx+StHO0H# z?I(91ZJm}4$k3Nrk!2D3aH^Cp4IpNmjI4+C!7dy_!YNHcKz`;U zc$*w-`uXNvMahlV9(gBL&9II6s4fimR-mhVlJI3O8Gg{4wt}}Fnwhz~kfReNc)5qD z13~D`6=X%^_1%1Z{ejYITJP7Iju43q9-k9Pcs=6@q>^6K6pMbS8J}weD$kONCGVaZ zOHA5NVBh=|*QN6QwQu_x-?jQL=Rxv;0YEDZw7XogO?OX(3QN9xDQw+?XURJ*)N5p; zP`^*gkirjOjcu6V3#!cYssS)o>`;bBSiimQ@b$O8r7uy|0&dU(ApY;~tFPDvQLVCH zV-vOzKFj{NYMls{zX7K<9{b00l{QW zO566C=aD{!6gp|k0P-Cnzhi%(A^Ow!2h#1#9ge{l4B(m|Q&3#w8r02D{rfzo$JMLl z6BTEIIw`2{Xi?sjiVuB^<{E)961^7%H|gGKW=14$m_|)iHiCoM1XqU%T%72ePpspy zVsve@J_ok*0#Kv-$!Qk`^>}OVr8KE!w5t;t?^FGf{L_5Q`atoI`B7zR%j{~&lfCa8 z>O%DAne=gl&VeucD@Jr3+ahw-W-EEsZkwaVY(G#rMeT5lnA??^z+-CFz+4`AcYCn; zTQjbcz5e@Qw^uo9xE*Kp3YhaH(B?sOYsvpks}?p&+H0k#kGHx9I6eH@?ofS9%3|l` z_&8W*Q?hK5wniHUg4dUt4rVX7ifJaHx&10yY*|8s!?OkVInQJWpcTJ}<(p}=9=_*!KWxxc z59S3^1Q%Qo19%=S?cWP%50;^FBcg?%mj=;ab!}3iKUglH0WzLVJ=dhe^xdh+_L~>` z3dnx8-0kUMjQ&ZHJ~}8(*X*+9-6CPv`7x6`8HveCT}PwfvUYzSBt2!gCVY%%j4nS_ zD^a-lu46p?_9P4!$0i*Z`QL7p#=Htx>BjsP_`fK7^LQwu|NomJl`T}rGL-~Pd&p%N>L$u7WY6DCQv-0X}xUXR-FOLq4dmt5V15jMkuHq-t zIh))~_dBoTvoi~yU7nKs8g^-B1-Q8ATvuS4aXiHKwCA@;6}cu@@9wT2WRe5&oks(a zVwpT(k?0@zD0j2lO)_d*T`eHhag#zCgLz6WK zw^BL3i4H%ScFcmc@7#@nw?P-g?{{22H@Xt>g**rF3jewS5r^!bgiJ*yuf+gQzSv%V z_u)9aeWZzgEjw;rXu$B6pLftm+cL+R9Gw$0-&J&jXsxyT0UK-b`sF zDekoc&9*ER-_!G9GHPR(DI=qd81d9LjMhip6mPEq4b!gDTmZhuc9n zwHaxra6HdO{B6w5(SnX>j|x!U#u3CUwsP9yd~@b1!Sl8u53sUU@=Zg?W3m5X0Pqee z13pkFlND{AUr%GKhVdgkC&bcm~f zOda-?Wc#j9%#zqLgKCGY;S={&P4<0kyV7$(SwK4Y&_b?q`@qfd%YmD+N8@vCqt{*2>@efkYh z7Om-*v2#?xYw=WykmI8|p)<~KQPA7F6WM@(9 zIiSBXmc+#y2TXV??-1hsENaKpusAiBd@wQX`#OuJG~Mt&=B}fO8T#kOeEFj*cxLMc| zESiRztIDs+KBV%$Q&H213%>iy7IOOahgt1E9sl=)5?wmdf)>s@0Y%mwR$KxWW1ZM= zVz-ulR{oFajFFxNesKJIFDx2~1=HPVpI@_yODD_IV4} z&iK}ynhiYjWaNaP1Xs*Z=b#jqTU*?XM*~(na4*0xR!1;xne{$dXRCM~`J&~R8E}@G zseh<->?C9i&2ty`9oFKoTNo02>~)!*^|JRIJqa|DHVg(AYzy|WClcvBWG%B4Mx7`i zJosOjpjOn{`JzTd{i8PY_BRXYQG>8Z51NtIs*MD8aRVHj6>|`)o?z_D#2n^FoGT zODAk*80qZVsWK}F4X9c6D*0%Hc05y~Hq8c}$&P<-(rBP`LQ&$x4Q2B4$My}#2Z!p|!Wtz^G z&_|f~rD*iJ$1I?JIwW2EdMD)NW|3f+wI88&f~b4rRX>Go@fNMzw*N^`;<2HKni%IK zCa%D0%9SE!16$gyCtI**Og_gRl$*;6qC||(c>m6_&&{e5FHEysbWXcX#W6e4_(blC z%U7-9O65fEC^~v6-0tx>miApzmXS5GRCi+3=Fa^`4{k)<=VfF9VQ=o@X?F&MbnOES z2TLnfQdf&@corY?8ngZ`{Y%BV9eq6uSV-Ik*{&NtO8Is#svX`hy7M}e%+JxVqA1(x zD&&$z-;o~yu;;hy#>)7!3y4H%<345l%zAar z4#>Qj*a2Ed*aFU9Uw9EaqH&A?aq(biEdOaU3#h3S>2IQ+F%bj3a?;a_U?)>Yj4SR#O?{~X;SF*H!XF2aRmI?dN#D_yZYuXY%(tQtu#@?Rl z?yzOHb#gqF{U`dazy2gGHJo^P=FVd;qm=JAPyYaV(zTcWyA}XLfnd*Cn!gpkinICv z2_E!zbVAmC12hE_t~$>2e>79p4r&Pf`jf}_tjiN%q3gAq#TXA{rXUCv+#EYvHU6mG z&$`WW1w%a!N%F=1MMd_9`Slg-V13?4rivREx@Qu@%jaQ-KHDoDHadNuRp0U4ccAa; z2=YX(2FC9eB*$%3U)!*8HWm(kFSZm z#*Y?rt^=R6TGOHyW`W>vX2m1ebJmgkwxu+Zah{(gs9eGFA$Ya#KI&n_mt$cJoq+T3 z3yxTwR$j&*jS&7d+2wz7NKf1A`42>%PIv12-H4>fn)6mtc*3t7N7k_-5x$=Ae z82p0M4le)eml^`+KDy?a&D`r>tEoz9ZJR(Iz|5m$HltVY17a%Re{f#zwL9((^uKM{ zcKvCr$(Sh8%oon8U;CT;_nf_9+rDy)9ud!2`??r~YQ_h#zSUHqz%em#rTkp|RL$@y zt&FmQxrxFBgP7Mk}@2m73Q2W zI`v#K+3_;ZsSnwbVH%qSX0}Gz(k|z;&mq{Cz8RIT9vV66x0~f*@q6>aKgHyp}|I}vxONsB60$ybz4>HP)=Y93}uA!?4BNSPrSNsP*JULsIeprewC3uc-Oe+O>g$)FngZ- z?8eyb;sZ$g;`Mks>)F1~f3NDZOG1a=G4vC0i)Zo@P<&CVyZh5SqYpkYn47TMC(ZAC zADNLWw5oGC@n$%04D_p z;pY!I?>|gPjq_OOfR2c=+}Oom6N}_5LjTKyn+573CKN#Ys!*vB5*T^%TMp!K>iLLq>K5`y+<1pLpX+ zX*5mN7}Iz5YNX-D4@K>t2cL~bAV1-0n~7I6jKEQ`=oEmdrA8}sp=PpCQ9^X4AslQtCd*KJwFu+eA9jV=IB=PITGf@KPMS?({C|xxSwA2JM*j2>Rm$SF_>Y??7a0-Zvm9*TXoIp|7_7-0KnwNgU7Mjxy@SkWonQ<4+SxCzKDY8DdJSlQNQ}gHz8{^? zYyZ$00VxAiv>rXvP_fd9WyB!8Rzp>JC3n*9GM)WzHt>{?p>{-nKtk*x@Z*ue+L`NK z@eVSG-X3b6ck*56kRpR1QT`Fz{AauK-Cx*?M@IFxKTOOfcg1^@2Q5F%5gJ6VMFV}x zGq8YO$78aK(rBgoYhvs zh8D!;#Rcqev%H1hA3k=Vi~d)YLHYw2Ci)xS5Hb; zo-Wf8SVmnM&dZwdVSUj8V~UBrd3i_1h+lp@8+iNXjBRdTcKEXyw(!-s|87(UXS$}w zn^#eP?`ek{V?jLr;zQbv_%q>=Fo81oH>=#(_ry~_IzgtsMZN4l>++uGFb2E2mwsIL zI&Sbn;9`&!BhvULP3>~5X+~AgZp8c(L{7~w;0l?$C@9(4>S&F2 z`qdJ6`1;wu_mBBA<6@ngpyy?K7Z@>3)9D|%ISJJ^aMN!Mk(yPb#e+{{B2 z0~KKf+`c2Q2PHO7T+@%XB#<7$ha47LYv>ul)43lkMiO zHs!TU50;lqj;yZiPk!TfGt73GmiwHm$!}!p7QY>muhVA7s=sHzjLp9lBV-x@eW&Jo z$}6W&{|C=xd<+@i{!_0AT@v|1pe;+K*5%npnO89{S>|3C?n)e}kL>O>3l+g!C{sI5 zy-@1e_qWGH%2K6IewaZ^UL9iBdL|@vTtv4>@eAiIgy@sUu5|ak`iY()SUyIRvP1e6a`aPOz_Q!)t-Xy=gMOjwK|Ob%?~wT* zBag}iK5?>;=MVf}uNb>@Cs+YyA%4U@TQy!%EJB0f(|%EDhQ_q=MJn-4y>G$mV*d%J znyEuknI}@FpA#Khzi{$g`2^}idFN~tGmEwd>cXBDTuEaHctb~Lj6KvH0XAuu7Ui{x zxrVLPq7l5(ly%h!$jVL7X)xrXYawN&V|wg|;$BT(x^mcxHN8LYo6_Ykw*LnI`pDO@ zJ2ZE>W#qpqRz2wLJA-lt4NsEqIoxfJ{-eie(El}_5g1kN2N%Lu;3@%q*147Q0128c zhHpe4TR}z1HsRfrvv}~1^y~a`3l%adx0*T>%XmKLt1=EtD84ly$78`{hueMNXXE!e zh*n=SnboW!KlDsV?e64PFiv)(^so7|#tx#hnaah0Q)1Dqf@+t=_9Z35EqJPLrD1jt z!GuRBtW9sv6}{hST+16+;eCuPcG_M2^eD(A$0O%YH!jbDfhhx4l>ZG8nm|Wbqd&GkbNK&`f)004y$1}GIq{7vb;MqX9_xLa@VnmnOfWe# zymtyWS-piAZyjY;{DJt0w55kAiGmvuVuB(s@#YdJUx(h09z&@!=hdA{PxhS4Wf;Ab zQFd8#ESo`44mcTnPevKlGC)N0yZ_-eM{0^&2uvZb*hK$>RhIu*oMqsc+sBO@=NF8N z3hwSDe)=!Ya&Hnk%yz&YQ1c|#Aqvcm8_kQMz}pRm_QUpSE?v7Imr|9uZ*&+^8Wu1a z%)Ptt!~Z8a&h(^6vhUx2pd}My+|r!~7=-9j<^M5`qYslVGQii8|G^`tzwFmtV=%IB z{ufD^4}@CF7NZZ+?%mx30(AM3_Lu(svjD>Gkzds#25f0B;8M3_gQ+h%sE&`K7hucqDF5GS+WNf>>{gC<`&Ld*1Mo+8 zJddvyWCD>|3%*9AiM*u=>!98q1|N$UOKHq1=S?6w@0`A~^OCRde^6D*XLIN{Faf#W zobU`3O?WP%;r5~GS54;^T6-t2`U4j}GEU3OzL4UL_%*n%@AvYkL>E!nk9<_Lu@rNv zixJ5oN^i|+t$cK)B&%3PzFnPV;y--bU+=+~T{EIcUqxc6LB1Ft)+k+Z&Hv=cC1Z%` z1|>J=&VOnXO?c;ESA`jD>5VOJ%li81@RcRCICaP)wsar1!gO3HD1eO4=#<|eijA3> z4#T_WGB(aJFN+!8c4lOgOIx_2M(Zdu{#mco8@y9T zv?ccY5K=^kjcws(Im4ZiJN(-}knX-Si03eEoFBx9Ct0*0PHOI!#tE)_qYv7G_eLqc z%08x57>E(iuYf#~9#?iQZAY^jji5s9ye>jUiWlhy{RvjJCwncc@boy`1moNZECEjf z5q1zU;pMzx6U69-kf9%~e3)u8IFln3&RC{Qjl`;@3gH2Xl1jJ!crr3Pz-qyJV(*Js za1WlGvE2HaAD&;_9iX>&ib~ryvxn=5x$w`R9s<{xF30W1BK zSoBNwNV@Xs^$TCqmds{W?VdnqxB^TT1jMalBvQTrrwFuw>xZ=~4<0_}KHR8yX|i#)59_UA@++ z$_QJHI}TeD|zJ87Jx0p4Gd$t$`0XeM24ZpYf$67qUl&TIzzb^9Cp8iP-2sbo&h6lRLTv(g*X^YKF%!fd!IRR1k#uFUv*oukxfxww~gib1SLVp zF$lc}BPeS?tZ<`UcpdoE(cMV>>qEtFrwk%XTRR8QhbfYm>NDzxl{faE(Mi8R+((_= zD1?{A>;5n=O(!DCt1)R8_$<=*i4@C*VJof#T_Hyh)Q36un2dLpk&rco+g`Eel&o3|kj z`7VNyC!;gK{(Q(R%5P|Y$9KS(DsE~y@~HdrIxFN&jA8TbIlz^p`dGQ{A3c%%k!a z?yk%Uii}ul)ynY?Zrr<(8~p|3*HVnvX$3J7eMOGBx$9 z(6uc9P6@?{GU{54PcHyq8)kwOl(`PcG(yS~v&|>CGgo7%xoQfNV@M7&Z^_}IcW-Zeo@*!B!NS;AKdXrKn)xbEo4 zGC1Vr`h+q7JemrfybKl%wN*0An4qi4Kda!@^}NeH{G$l3h({ohAkdQTRy{+JjVzTDBpt*HC;WA2To|5!XuNALB77&%O%rha+B)}p6z+#zm6q%caf_s z#<7jD(4eXLxNWH0Q{feY;^{2-ZkfK^P4(Syy0q;6*3IRc?HV<-Y@3G@iwE8%s#^Cp zbyI_nD-*tA59b7Pxw6j4omBPFIRSjse!5>OUxisVX|->jhW?5pRz~K0*G$;oqauKK zu2+x8x_k`fPCsrJvO-q2FAXu~Kv49CxOMIr#VGJv(9e)GE1`)u!byH!wP|H&{)Q=5 zj4U`K%f&xh?J25x9Ge*KjOT!1#EfK#s%>Vr$<9@fDVjQn36yEtb3^$P{3*ZKK-HqG zJz%UbB3ymFK`eN}0+J0PBXQt#2o=MxcJas~0@zzdtnK^(Y>6JWX?eMkBrD$ zk+DIbu9y)hdE5YXZS?rMQ=GKj3x%El&B(%0olE|{#g)wGNe)+~M+%91SGx1DKJT8V zN@2bg0d&xYzC_f06X9!dH7g`0nlRd?Hi}0V*j}^594~m~@^u?0V{ozf3;vgvnde`R zq)4R^p(0h=^0=X|N#s;(^?o?jQU}`Ty-&Sd?fax9~{1qzCn+GL3=l>!Ii6L0`Iec7sv6@-P&IqCN9z&kkQ+bv2mZV{uNZo?H3zui=qeAW=(1NYDM=6s89wH+AHU&W z8WFFw4p`EZ1HtlS3brW(r{?BV>008R6nSJK?ODm>_vVuo;upCEn?j=E64fq#*4B(T zGxIon^xVy|*$2G0G&gLF){MXIne?F_)Vwq?WX^dIJ~{-Q!qr*(beT`SOrD!20L!@? zru2|NwRjT0{r8;%V808gMWe~m-t5e;S$gaYVsZn1OSskm=qY*2PvS70Uvn;YG=%T6 zQFt}DWFC>LHJ1{xKwFHvRjt(i>%!4xW2Oih-&8$XE*;n*Hu+H)lPYQ20lDpg;Rne4 z#Us$~QX5PbdO3g9K?trCKu!wi-1vqH%_VS>J2IvCdHVh&um$eC?G zK?Zn;f^HT;`$mDwH;$lYN@~L>#igL1WKd#6VCD_6H&VXW@Fn?rS?MswPes8KcGK&N+kGc2Wa@R;{N3`5Og{^C&M2#lCf15JG zsDZ#qTeHtnUG_YFbt3%$Xgh@yp0p;v9b-1mul8>j?84;I4iF;iJA!+{GW!Mk;S%uu zPR!HMYP@G{+7k$DMSuj1leD4#W<2_t4|Pu~&F0rpw{bT*Cx#ETL7C?B9`B_6D`Z$d zxl^RXMpr+3cXHdfHXCsW+&S|X(6x~P?YLfR#?%L%X-5j6YX$JLtXR?koUdCC-wx|eBG%6icC`pRe9QXWPX<$T&B;Odt#v|ORU3d&b^?$cy8J!XAx9Bjm| z)j>Wd+FY-dH_22teqEx%(X7(gyYzCoX&pXFJBw&duL|SLSgX`p>DmrqDXO;1*SD%d z-bgr2LQIkiC`QrCEYXztPxbcDCA(=a9DHm5&Tx4mmIjR>nOYWiKI*X($t$_PClra* z?q7ZncNYDyutGyQL3w~sBv26ZPdr6`3|j?(>Hw%|%%!BuGu8n5QQasxV#h%>9}xmc5IBv4XgFWg zRZ)&kQtQv2LVhk3xP(#)7|jK!8;VGJ%``K&Pe%TiW9f^Olq8;9Ys-{%hz|2Xw>2YO zrAJ~}jy%`rDFEE*S(q|a(6n)xI~)O3Ae`DBecBd1gXWHZzf3&$c(Ywokh&LNB@u!w zri2$`(_8m4@Y8e>w$Zl?Y1$048&*&w(dxPODi#*z!_#o>@|{5H2rf@V9l>|1;$aFTOb{rK)|&2no&A55lXxVG;t%9dD#$_lM9=|8yV7N~OXf1G1~H(}67oHAGOO zMxfAbu-GmX_3tm#<4Iq>`UR3faRjKj#kDr+$++Y=)O^0iVk@!%rQJpLQu74C7dC-`n2bsbt^rYR-14 zGO_5!{aADUP_mmA-@Tgree#gm$z@Oa`=>|vJ-2$4x!JgdgN0uLl!%t zn_?4G-uQV30i#Gv*5jXgaFR)7V-bL>$2eraQH<9bgu4Q32Y}ixw>h;G<}c$q!;Yks z(_U*`Z76PJa%@gC4=bMluLLzOB?zBEMi3+p0H=J$ky! zV)I3LylKPcqn@NbNnM){KK1)Y0&vs*(j~R~^X6uM5R>7kn0jsKNBu`~#7>!0g9e!h z2ZnFco>I;`Z{nVv$oyWaM{S;OfBrCx>dTL%}>e(bs*r$o!de zJKC+JpLTcd4|g?G5m*vyFZ7OuK|R%z^5Z@mw~NqDG>^U^GZ?)?Hv(NA0}p7VZ-J-< zPHz82oe0Ll@Tj4CZ5ik%!>TGrt^`4QwWkCAW{L9nctTr7aC(D}ud5@a*#Vl`sH&## zY*g>Q!QlfZ@DGPRz77^Lm}#8>x_V$ROY%?CQR-R(20fbF&MyKP647FG+$wz58K*u> zf^O5`PNWjLv>y}*D!`dMCuSMNleqh4K*X;aK2QQ1=jqUkcFsMegQ=WuHDBEmT*w18 z8OoSQ`gXPiCxeO6sy6HPm>+Q67@AB<2Gt}DDjwaX4V%Xnxsq-(U+ zGV)4wNA82;tKRG4Ze|~ENmqxE{ln4*fdW1i7WK4rqB6}Uq;8PxUtl|G^`&WrB;|6~ zYVCGt>M}$op-D?aJKQU?nmXZu+9T9vVMFtE_?WHEq_El8FfahOkQr+W8-sl+xdH7`5Kc?T z*s2&`?r6rz)D#a>*n+)&OMJ6C4C7UotG1%q;Wi5%=yERf9KbCO$4(w8_j=IVdEQbg z%I&>Acc$guMRS|8x7FM>GLG4?uZ$p-M#j!MG=tuLv@I&K)WO~r8ms2ZM+Y4cF8HZ# z=y}`Is>felfosPKFg(*OO%0u2TMIpP*jY#Y&UZ8SO- z9ND7V%LM|0n__{%CJmc<>K?l#K$9tN+=IU2Ep7aHi%S$ib>C{0Fr%!9buoeWxUmUnL(jOzW%@@721z=HSiWS4G( zV`?U^uo>2chi(&^=^Qy=*#H5KUfa(P6vL9xt9BUAD!Aut$2l%e+!rl-uLB2HdigXN z5zw*`NZ13ou(A6d0WkGm5uM`CsZvk6!QsS^xnj&wbV}V8r+jBef@?FHu zYGEMlCxsaHXBMDIs0%&`XRsfkl@L4|JBYNFMXIc#X8V(Nh1>J2wv#V4fbYfES-B~;dW!?YlH4Sc$ zx?Q(KROUv2R0(cwzrKaocI~#dj0Rs)!kT~>w-`>vhOqI5pSJ3@R_S^seWMlY-+43E zsZ*o{#{U)sNP9s^Ha_D-nR2J9kvRO9NN#!3G-Hi9$F4AyaU54ZFHs#I1w~7HXp?Op6(fh#HwL};4EUY72zK=M3)s@2Rg+Y=!2k$zPjrP zz_2V>H0AE|4%rww93&$Iv|coW`wMBx0ZU0if?W@-Y^V|WrAqEMIYNYY4n2J|7+yZo zN(YJpx8|{H*EjGfvirhY;+1m41ch|+VT?rJABhnJR`Ux%g(%Qd4Y!!QO^>@%_R()` z(hJ5xMY2PH1L4=M2x0#zCJsWvwKSkyz|W_Z;f|FMw3_|Os0-hF1VgDLD%+#)nkNc^ zkd7xkO3X=&O-MxPQNcN<*PUAJZ+F-%7ybJna>mcHlsc#u%xG-i`P)7;0OxY-74Vv% zSF_Ji#W*j>=FLhgzbxVQqpav6-fqB9%fD6H-WW#W{=JxFB$C5Etp zDw?enguxC`HX^iI5hSpwQ7R&W2^Y|Q3d6d4Y%&7a$IzEEg>NMzhUfqW)-*Yk7!l4k zS}jh~4Z4Aol{f%$1K%CpV<9x{I1@IVSs3*MFuQx1+`wy}#Aolie8^Eqjet>y0BX)W zTwKnGbW*aGd%c!m^gP8?ysbklMmMr+``nXB$^eLTBwW~(_x}<~%tTWArbpo0QU|JI zxQg-1_!Ri|Dy)p2#?1kdis_>ptf!-9Zq1Iio6uz!PVU;{t7baVf9@)CLoD%6_zzrz z7JT@KmiF@g+|}=a-M9mEJQ!zR!AZn+`8(5LIc{m1U;O$)MX#Ac%JN_`9T|KID;bJb zjjS9(QqFK%A16ibAh{<07}?PT{)|%LqELctW0}|okf8Fc^!mxqdNQ1{&B|^ky-aGx zXL1H6K;}iexZ1x#rI;Xk#93wo^{cumpyqrjWl8=pZg@-;V$7i?$k$bw0N3T&gX58@ z#d3)T?QnAjkloh16UWb%jqiuruq4j%9WT<%osY`D{SETshtPZW4rf+7VNe5@l!Oxq z8cIhrE{(!P(Hg*~`=;I)-qy{sJ&h^chO%(`{nPX2E~O6Vkjeq; z3jw{cql6VC6oJV!e~FlZYg*M10!d@oIG--z^4j0iLTGYIgf6yRW-5$P;2VQEfNwA# zWXuj?{23l@INT2dEKzs8t#`PIa@e;ed4#MsD!O;(VmrYOI;ElEy6o)w5L%-$u}(a` zR>ng^Btj{Zxdz41Z3pL&O&LP;&R*m4buh;!}|JEw_R&D8aO;)%DcdKC3UM zXL5=l=SRMqt8sV^@e=kYHnf^qzCwtiM9;VMNYJrK3N`-}8|%(T-eeya+GXpzdh`H8 zgW=HpF~IJ*jc4e$%Cp>@ob~IxVaDo{}7>J6dhP*b|VBidjU?U2fm^>3X!apIjoUFPZyb zyqOYO(~(*&itCJfDz-;ciW(EG2nz~u4+`TQ{o43#+VBTCl@iU)>C6hnD}s#U(b5py z@?D#01+ix4G0yhM4!5fXdLvA>B8>9et;Y$euF>-5YriziE_~X+)o;LUapPQh*Y|06 z07D4M^nL4dyY3$Zq5=Lp;a89!EWk;Ws!)6 z%GaUb>D)EeTCajXjD`&_&E?f_IjaY&394vjg3Y-*g}wJ<@}yXUxlkCIkzevc?F zEExkWRJe zjIs?AR7`nad={*^Z@H{gfUdHK-l2(~XrH9BcDMtbWD-V}TucmMhr3J|E7K33+-h3P!<^T21vRY?IN@YIc<&}IaASc>)^|yNpJgo|NZN29KA`w#12on3ut+uv3P&>_+XaVa(+EUbI21}b$* zzTA_Dg}IF~?K|)0n8kKDssstCE&w;m_Q^QEefeGDeI|L6pjWgwWCW+(>(mA? zi}-X1659w^{}Q`2el6SAxDO$tfnC)>T^k|06Xy#pBlX^RN{mrB}uNmfdDedk>1dxv3~& ztOjiYyg!2_la)vE`d#?I;rL(Fy-38bu6&gns#6O6h3@Ni@C0=PBud?g;6@xI=8hx@ z(ONe)2|*(p-n;Df=xu$ph6a6!fJt=wstm545A%9OYiK7fLo*a2yJh;`0Nf785yyq1 zb)qzA)M9jN&^opJ)gnf9Aypw@1k?1Af`j(;!*exuBr(Y0>h5Wsyg0^@j*BrJ7F3OM zzktP_5V>Jn2S&YGx}Sig&rL_I&S{D&foy@jq2Yvs34)O53-^t4{=VCGvcUdE0gTq{ zZj@QaX(4794PJltVyvHd@c>tow+yr!;0YVe(=$<|#tpiz`bNG0aP8Ag1#-#4}~LLg0@==xbZT)9u)`K9GYdlMomP_nler*Q7H zwS2kq;c3qwE%pr*FU^V&I6SL0w8+j!H&JR#(9@oKvn<#EabacVSlU}DzApUCWF5PG z`48itv8|$%U^Whj5(lXWYx?~SvR-0HdyOXsF4u&b4Iq5u~83kmU@)UAfUami+ zyps{XDnuQ~MR4o4j2EdM?p7^M2e)vV{6Q_*Y6#56Ney84_}#lVprs-Nrj^{?mvQ~@ zl)$<>~44i*+;?z}2Y)O6TZNKbokA^#inHt42MkCbV+xZ4}4m|npz3e>m! zOSKtrzO??)l7b%>&KliAUCdB*Y#DHlO*D?qO4ZprHGop`c=E$Mw@8lc)a%Hsk9_zigUpl?A zz0zLHNkp`8YP9MWn8*s3HY!kQ7Xm-0X^6Mn?Q<~4`u%vdc$4F4z?m#x5T)a^B(s*CEN}I@Ly|xLc$-ZpbJ7nTx|sM$Cdc)~ zye#Kn3mh0#m%gRAg8ugHyzysKV`-p82)300bd5ey>FIdoY>{*6l&iM2zu|BAz?EZt z^r1P~6(ExTH@41&E{hbfrRRD|@o&XlfKnHM>%WnY80_xWv-RKTO_t6e*E!iiIHIzs zoU0)0*1mYWs3IP^WdeR_{;5fuPQjAns^L&($iqsE`-Z$!*!cnph}5_FpR_KOoY!_=d@J$$=Kg6$1xl@#Dn+e< z%2F}M%*$U`SEMm+L@LZ&b4U$;P-{RUjf2q zSu`oYEnzlP@0-!3CZk=AUct)G9EEoY&sd4UzZR%_pd)k0&7&8SP4`C#IZ~?!k8}z9 zDI$S0dUH6R*wNk7DkR9>OaXBhINjdMe1s$MQj`hD(FER0pU_{Lb{yqoEZ&%<)qS`b zyD0nm53yS?(@P|p^(u0PipzMB0oQko>dKJ2JQCb7x1enEaDnakwQ)`#dA0qDu*Ioe<82N(x!)MQF{~;R{t3b2HTh+|-k{(nfhp<3UaDsOo zpVdUY$z`Tb55Pear!%8f&O(+x(_tGU{3!mc!D=_$?I8K(ZHFG3_}`yt(OAuv0SUtQ zZIbh?C-3GHg9J~1W4DcYcnqPqUB1tQ56<(9okfL^rLnp5uNX;_jgoLppT!u`!%YXr z`8Pp70cw1CFBadD!|mrtPT{BKn;N$o_~n_k{ppROwK6Y=SWx*Y(vhq*zT3S_ ztXU-AOxT0(Ec42NQ+#ngH5yTV3`e79-(ZkWF&rQ87kbkT-GpXD2$0bZ>_+)`Vfnfm zH6@9P{AE38c^6HxdKP2hmu^zqzv9 zG1S;na6i6vlu5c~)8S@^?(%#BINl9C+%yid>|a9nY~3IXed*IZ@<$4Kn0dbPvBFi| z=pbh~`pMUpi#Vo9wN~@PfdeXe$+YsB)B}tDIHK(LJD>H&^@l8ZSMDc8NLP(Mbm9*@ zXyQ}e5VVpD48pbKoG(=T>^}cFb^oyIh5U!0y$)J!-=X^p7hNj(^Ii*0;*RPvBQde! zB>h^bft2_o-kiOP<2w<|^A865y#MgHUEHiR5h-f<;u3v7R{Zo8_IZU&uI){*w)OKKQ@%)A71|9K&^qb(wEF7D+ zfbw?nS=*U>M(LZrdSgJ$Why^CNGb8^`->3@?`;)3kptAML4#P-78xPAFSdVq+ac`n zSLpp<*8S!OkyY)TmkKsiNwN1`4+k7_dav_LGM-2n0NwqX=QY_JHpQGAx-t6&biQZIxoOx%lM2AiI+G4oSmMG`b zy4TOLb#pIGBW6wS4Q`T-r8YG!=mjx{$WL0#yWM0ZeO)p&wrV^Eu)4%9nji0H4S1rV z(T+zJK$yOLNwiUO{e{4GycGJ`IS03*R@D#4%}+7|ZTtKWiGNl0L`sSmHf5jCi!JVz zt-H9)c|Vm*v-P?M+FO=eeRGit1|3R4&6U);#$;~CK#2GmZ49kcwASQxsr_FxU4>hd zZ@30gIs^piff6DO%IFCQh{Qys8w8|Vnn_D5NXI~0njhUTLUM!xQlmGzYh&BtT<1Ff z!uMV8``*uUSLDw-c^qGNI$smMcowq#`4(p0oWq-{BYOc;dM?<&fJsADuz_%(`E?P2>dH=_wBh>_! zD0Z2Kp^}btOFGPy`&iu&Q`I9cCHyd79;HNy7Az?ww-#6(ge73T{w10-iR@dZXwk*3 z1RjO!CBtD2X9%_CW1&^P2-`n>3}w%}Bgni^MQX?!zplaw-S@LapUyY``k|(@y8UgO-Ra~14rx`{`j32K(Rl`qAHq1ve>7My$O<@d<{c-{sa!DT^3Hd6wos;F#ooOj1w!1%v8xnx}?q9J(fRbO$sdF&Hi z=EU7U%yZiZYjg}9H7&OzlgI;w`AH*#AR)c<@Zsqj`03CCdGkok(9fTmiH3_OnX%YQ z1lX^1{Sj%+P*oysQymnsQgcb1S3lXNm0cS|Z}?Y}oivCl4swN{$qinxxbWmF@b-w>k;DzJlvn5}ACwF=*?=>JK=cm&kH0V^Fk}*0ebKbdi*4QcPLPtAM0sZNE zZe+f3uus7Vr%DN6yqpiF$uZn#C8JZHYl?;Ze-;2GmWdk;kAWH7aT=DUuR3q?zv?U9oTDC@ zKg(SSy2gGF!xNkr%Nt}Ul#O+`8vbwsI=+ZZvR&rdZpKZeM*R}|V%KGNQ~D~^Nl&Ui z-cJ?ohNdtMDbJyq;Cl5c&HMvl#1JPCQJ{{F+ZT|A3RjH+!RMd z4o>cRaLr>;5|1_8zw7R>hjd1Ag_Hk`6$3hl2ya2FkPB_|d zQ@Ho;<@h?4Cjfejy%K(<3K-r-UaPqf`e!a)rthC#C6Ufsrg@6tn|t}ql{{?^DNHZw zpAONX2g4nZkzLa%FXSS9;Q{`&My)RK;ew3)`7!ZGeR%&~F- zJlm}tst|Avtbfz8ZR`{=q2^0{FnLt`wgU&C+N0hW46ZnNa?yY4JKi`KA$!!O+p(N* z@^M3I8#Q0|RFE{}ag$rSJbJ(MwcS&JKBMySA8ZiUS{(6Oy@tr>IbI(Mgrypom7n@z zs+uF45&p7r$CKf^HcgIypUY8GAXO0`6lzXq+71(dh@y}iQs*-6_pUz{tVhRT>U_{g z`euy|p|^ijw&}0}cQs-sENsTxAy=KguvNuyWqQNOI~Mz*@1#XiEl7e8f*1dII|v{; z#_b>hu<&o`8&E6dC@W>VgIdPHR1?=O>A{H7h=7Y-W{#dftn5xdJ*<}YDeSQQh*72x zj9De3iQ8#-Y>bnv9`5kw;oDjSpO%` z=9K^n^eQx>ZeuXw@0=lfbcrNYDfBX_cKxk@-7bHA(z{{sG7s99Nq7NtweK}KK(zKB zT!BVc)O_{YZuw%C3S*sDq)cLHh9WUKCD0+gxu;^1Pr4ZxYANftpn4^& zo|Jo;84aMTR9TqXS zrSpK`bDb7;FP%H!S8>BR>*lI`v$z&*gL5zm%g{K3W|EjQy+)$JuXT%>yYKyq>RP{k z_8eclYvFS$B8Yz99Wk+GKi~J$BIUMvRHYhUa9cc)UlpdbemAI++(37rTL6F_#$tr+ z1I?J#&yEu(*WK>35^tk}L^*k|EC6LXcAY?NC;^_i&*iL?XBVp`; z#k6m`s`cDExm>G($jX^|o(xElUT8DjQO;}BrU{+PpIsU*`(J)PjXiZ|NB?)!fo+r!!5bZ7J2N!q@mqxN(=nmLC!HW%XR5d2MG&!(O$YCjuEqTh|CQRw3{;6Gfia0Q$ z5aI>9n5#%Sc{$s{B57{U>iMj4gY`k87D1fgCrVE!*A2efloZl7K~< z_|aG!MBLt&qfU%#hNzXbVbzW!3kiE-(BkLps;8el`24?)KIfBqy?iR@al-)UjoX4S zH>WNWIJv!kl_gNqQLntfDkp)*-@qvdbz)Aoc?^%1-gu<&4um`>H3a$Cm|De#>@Ehw zkVFbYQE;Anm~y^aD7n$rTNGrsVQ2o$Iq6_&l8q43snWzs$c>@Wq?eOo$i-Cd{z!f#T z_uX4O7+okBl5jHlzM!K+W!@f8&C1RjEgP$w(spTSd~e$V(YOb4*zV^eU3#R z*bGLC&cRp*qNrI}LNZ_K+KgXVVvkT0h5{z^PPQuN<#=s&St}0Y;$+kE<=TfIYh$4* za0tiOEz<>b893eSvjef`;z9GybGJ0ShFJGmPdLpg!9v{H3?bB-ddI$U#^vEcey74o z1ih_aNru9rx_G16-hrkNvz^})?7@QT<2IioMqUWMb0K4^4xC>Uhqll85O42+dpzSy zDgse=7)GU|u@LQ8@Ik21 z7OSWKp*-YRE^2OtLj-@{)+mP5)n_Qgb(P-(r^RF~f;9RNnB+Z>mo%=#C4nwBR859PC(wtT+1__ zcbq{ap7Jze2SxgMe_s0BukJ2R6xO#GjGm|VrV~`Om_vr)sAca)nyRQiH3lXnW$1J_ z+Z<@+!G9gXGF-$q1ma9-8v*Oamz;MGc~6)j#{%*QVggxp zJcJ|xv{gcJWjasAI8jLns-w{}qD=nVJBOLcA%iqc?TSnv;$I;XiPFbf#ZS7nwoUr< z3@pN*jlNRVx^-3Zvk$VM99*H2J*c;7p{1Xy{}Cxw3Sp6?|9mj3$F9jh$jt`<VN(fi^HY_8QeKySl^L zrq3&_$jIV7p(^(w7>%+~NeXz#%4Xxv#>J={Lq_3Q*cB?Q7M)%f8pF!g%3PkI@R;xt z;RX^~Q4isbxTsaMpr!-EEiHp)E`U*0V(*fPrX1!sZ^&fEyy?aApS$a5zkvNd0-p%N z))x)!_0LJH#2kOd#%t_>AZDCjY|H1o+>!A^I#^n}$bIM(PgA+A?~#cEanO1r7t3(o-Plzf6L* z#$C{qcixH_&sH*p(KKqk;U-ovyD5x24d7@PL-E#ecGtAIALMKa5RF(H3ZDq+N za066z&VvH>+@se?Mhwq?N|m-(bHlvpIBUe=@5PaTH{418$sT_pN{D=emyNIJz`LMn ztj17NRxfJk2*;vW8%9<$BT_aomixU<%R7dWEyKk$lAWE)$b)0_UX4@Avgbv*t{gyf zXxynZC*aq*P#;rj4tJJ3V z9@}b-rheaGhy-zT>Fk>+*6Qm`E`YG1;GGtiM&9$ZXqXi61#Z!I;JZ|<{I=U2Mn{S} zx7i=!Jx8kG2%*%ZBmmDh`65qou?wkRZDrh-K9%F#4bxniI3 zbQ^E*SXNnAHp$`y3b&4%C_!LKGAyN@jcBa|p23mWbFUY}6dv#(@8T?evKui}0Ajo~ z-}x)M6tt(sLekGYef{d(UYb#8$iat|1e80)XP$WQ&*EsV2FhrvWj>g(v59-|*p!pv zPf3ip^DTy-lI{G#pua^#G)K_0~1isLS@_6uG5t!IP{s zRN##t>QKyqU^ouO77f{s!ancSDXjUSb_ zpdRAztsL==|HH>0x;TgZ-DuXSN5+&RNIBILh?pAVL$MU|q4Jl*{J{*x%U14aUbs&IW9a(u};>HG6Z?sVy|dHgdmyov6Ouk_cxcdGrA z`Dft&y%M@a&*90+3ZB@)nPRty3VdV|sP^^|;!lYcqW^M5D*4nH)aSx3Z#R1)ANSleVurW=^|FB?iV?(Y9i!jDT1 zATcN4m{WT!%@Y`4x9r=X7(GbhaUmrq#W?7J6B*r6*eHabB#3GFI!^*^3R_b=I6+#Wf9#1`I zpz45K8wVmHB5Tu~3**lCSi(iAnL@i<p+z2KXp!G|^O|$=bW_imL1S&my+PNS z&J$xld$@03I1236bW&mzkdC*ltT}l#1J6L(%d{0JN3GIeMcJZ|1p)xP4meNy^ejBP z`G&COKS8w0UD~fP(d!!wbF}X!8xsJoaHc7R-2cz#qDbY`sKn<{b+PvW`Vkrp-W8RL zad*Dqr~LetlR{z>x&5M=V!En*CE%;qy^@6Vz=ESlqT~7?b3eH@ zyXpGBpaIf%(iF=eCWyC~Fxgs4k~Qdp?Oa#Z2=ua^7v0f{lsbPI*uBDP%Wyz)6OJ>p ztFEwf^6wd=`i3pU^^=|t1#J54U}92`Z*h0-{>%rsR$;ZD5b0wPOZC=#w^RE)(AOW% zFVnlxRPT^npt+8gsc|Hr%qdY>x@4p6yR3P*%$GgYYnx8Uy*;y~NvF3x6!~8DxZf2H zHC?+|?yTEX_bNO5(V3tE7eZH@e5l91t|+?p(OmJ8;tOLXdn1Dl$5w$fvVh{j2D^-@X1xe49@6RDRa2Kyw2gjj;2nF1S&bV5(K+hS$xsfH> zE2KqG0f@tML+bine01E7*V(!u+w91;#}n;7S`v1e{0lX#(JyoPAZdaTsafY%+;5@; zxrge?fWwS5FWTF{$I%scDKWf@nnFdlSSmvZmhts-*hq_GOB)(&qgeF&GCF%W-6Bub z>509xfYG;CH||U~DeyO-@ULaR3c*sPB2WTm^5%y-@M_$DLL+AT@G<)vdo_y&dXBN| z`wx3S7uuZG*Eze0(eCE%ey5uamTQ|4kStb&@}?7C(WPF!`!lHVE4MFuJ*jYL2J9A^ zd;5g$WD;s=p^138ik@108Ic_RSr8&|e%0*K>C)7D zKuAe!T|SEV9_}mpjwMzbxXfkvEkn|$ZF7!4hVC2?q1PZ==U+pahH4S3R-uLdBKjU$EwVoKFKe_C?tVIOPLrFEbC5>x^HIVFR_ebT} zPZB<_c}5dmpzD4z@YrFkZ}X+m#aRD@+`JY--ZUY`(v^FW!Q1b75kSyp>irxp1H~Kc z>fCYIw)aHO>Dy5&lEbB+3oHM5(M(@pCEQ0c@0(+s8QS~EN+*`jO+5YkxLj?(amM_T z?VMSk_^9C1cLQzT?pDI%ToUvqmQO-vw8RX<7oFgp9?LpHxygL+2ijjfjUVSg2qk}Y zM$M4eN)>n|3+@C*P;&u4-bHGZuo#+p3^43c+Px(XrpC$m>_(_`y1Dxtc`mpQYke_g zYgub!?Rzdz#m2i9EBZOBYoJeO+YrcY=Akp@{}Yb8eqqJHx>bT}75zQ%Qw#X-b$FVF zJNX1Sr!y+Sx3njA0}jGfj)%`-k)XEe%<%9;H6QYeNq+n2ME%K62k@L{zXKH*zn9Tx zc_Yht@``M5UT0f&*)GHaP7-yBr?EY~Kz5<7gQij8)3ZOrey+q`-rwzw$u_s;o2UYd z8PROQ8sGS~!ictzyi@wwuIs;kBYrZ~PI>LbEARK+oEi{nvK zg)lKSKwB%+edG{Mi;!Cja9%I|;YpNP%RCof++qA_x_=iM9J%{2baRax{Z$%P^ zpAoq}#&K3y8~I!7)yHcV_$x>nHC#d)Byk>89=(ugJD*0d<=TG02n&e#e6T2+`bK0; zVY>KL&V0VG!r+%8NzDYP&vs_t@G0af*EiZ{&YVvZ<8Lg54?AmomnZh^H`uM&b(u$` z%45lMbi6Gu*2Ut#?QxZEgBpV(A|4GCJz!LYqDM!fK_Nqy;5ng^T!I?!Im4#AQJ9?CIU?eAX1<$6GNJPpwzp61glfjAE(o^uyi*(%FYP1$1@Ri@6dWe1WxP3Ne7vvvg z^_ueP_Z$6Br=nLk*;A*o!VrPn0mk28S2+(c!9Efi@wof}vtQvA??sNzTWBZY|tr)3X*lZ{amdy=N^?pkXI+u}|yTzNKGKxU>(PMicsPeEj978rFAd zv8tn42!H5?57PW88nu@M7rzi-?U`n-IlsBHHjrt!=aTXQYfk@zE;HL803jK4S*x4q z2S{kN$FWAOAKqGuHf{e?Zy3dgr6mbUM!xKbt6J5{!0v=E}t<(T}?=jv( zYcy}#!xAK?ud`=I0R1KM6a0Vr3|AMAy8fzGte*^B&6mxQQ7|uc42k=}&8|=crXp+# z8{6ePqVP$I7x-|ogsHgtFoW2h8j{-K#I*l1yG1Thv>dROHeIB4hU_nfPdf=)5MDvz z-#mR;&F9z1rp4M5dOx!N@HmW>4oZE@E9eo2a_552oLPc!}ypyR6Tj z?M`AUmWa`sw)b%rY!;>vn2+H*Ln9I*@ZeghM{O9iwkXH|LunRx|8ZT5`T_PzVe$ZK zu>R#^U?QQqrtsNEMgOm%!Jrt59~~F@;`^OQ^Sp;g9k)iDsDSm~OphfKd#gwq`Ydfa zy_9_8FWL%nav}u=91?zlq0QpjEw$Uvn51YMlKQq~w#9%nE5UQiOfwLs04tqS!zF4R z6aVNl6t?1>;>gpKdG zNhgKIBcSP!bZ*o8qrh6v8%VnOTggHRG!_G)(^lB}X!!j0LGOe^&3QrQMIA$EyAAN#6aMsnM-)gi+efLvla7 z9&RTd!4~L&`W|MEKqf6tCLyo?;F_f$zgN#eIM`OX_O&b(GqQVyCuTV{@%xaOd+c+( zlCXs_+jO(2E?;mJ{+6t{_#qNCWz!HNI@fl?l)eq&N6T@~5Co@7Oi0Oh5NKH65mpu3 z^-goY5*BMqq6Kh1DkTCVuZCb?J~l`WI^E~4@MSd9O!P27H8@$gl$cj1KM0Ph>D-gmqOfb1KIJP4NCsMoZgh0L{YL7c$^W531wWOHKXb`rho8 zJS#&`$O`d>-s;*KeKr0h_RoxH*KafCZ5Spx1uUbIeYMd0{t3-*uR>klc&&xzMe~h3 z);cR>F^9;&$7%N;i)TH3q?{IG5D|!Ur_#;K!}FrN!O#>m-#1eG4KSvKJbN_CdTa=H z2&2h<*$Jz?agcU>6W&gZg3&(Y*%=d8yskHt=yef+R zr?0!YmuBLUT2N~!_mppYwT_89993R#8CZs`(IXUum z_cu*4w6NwhF2 znrV+mY~Z)(J-{|>4yH88v%;J{Bagw;Ogxm z71&;R*P-IhI4JNM{(30Q-*-}x#QF@r#h8Hf6xxFY-7tt&b#ODPaF7ELL0(dHM2V`a zk%teQ&!1o!rmQ-47b+g8RkA%ij0I6kS{y91vVP7Br4}AsC$PR7q$Mcg?(g?cPN5^( zDJhfvZn9;398o3o59S|5sQ^VZUIcb*&6-3uuk031AQUkBDWf9EQ3qt+ZJ!ttEexzD zYvC)H9($Gr>o_6zmnb69feyE8wmG;tVO&g=$J?-zB6#mTaQ)nXWrfpRsj|Pn^!k|2 z9bvujE*l`dHlgc^%=67d)tWlGnctRr!^ewx}(0vng1t z*hdM}cCEWTK~H0nZ|`Pf)dB|1cVL{A`1xs>_Qcfl`?BA(p?o$it17wvMRoaz#9EL_8xoVCvmiHA2Kv@^RzxcG>ZfEvK&H(uM^@30U3Y*+B>U$je(Qb# z`Z0Nb>=6Q?T~Qe^1L#owYnq3@y*$;V;56mTlC~*f%*T1IhKfzR4+e&GX!E?sw;$Bm zHxR_Mytx!Z#d}u%^&GF9co_H;!6^+B>^n^Gn#;2=N-Hh5|fqZP6AZTK?XK=6#* z#&^-iBZ7h(V5Jnr_X0YwIjAC4{zk{Z(BXk;^ni-_B7vI1zqHD_ZDaD$))Go##S-40 z3|wpZ1%u(c)$)IVqNEPtO`~QenoQ2Ef78}#VK^3rzMVXQ$&k-qQu}S)WuB!Y+*1@D zuW74FOB$5#WnQWHJI;j!ZXyNE2(<-RIgT!%2mz0WQ88qBMH@=AKoxq4lUafmiZ z^&P+G;qa(MUWMKkUx-ZMnnQ}{eXPjL6$0cK72s}Gghr~j$HtQDX1(R>JTt({8ELQ- zqvC4oCv1?Q;DYoI`cdz1ywK-c-<*{Nxsjtb<lHgf8MyU`?xmzgKlB7{JLQ?~Xh2{eS?woz?#lX+=g$!rwaiHke!)A; z8D(ak!!q+sUh>s8!Au5iZ0!2PY(D2al~re(5@#`S9|QO6)Lt9KC?G=HjO%@}U8YLO z+P0(U_q;neqHMzq)+g(3t0KlVohn;Px^BKzjzG}+?S>&LtG$=dtfWF(#UZ+AsiJ#A ziJ*3$Kx6N(3Fph>6}JHE-q@7RA5hjy>S!K&ua-7a3aaM%;lN}yM4CO(-2~8;Pq0??PkO?&+O2!}W*+CGN`>)>T6ug{w8JkOXBV6{9DfGi!)z~+ zT%C@}+e%Lmn)j4QC+3zV2~0JcvmS3|@gbxWk=E>(B@4@?fr?MSrO92YEg9T3{l``t zz0}@As~y{2GNBp+d3qA3PX{=eAHC5W0i@ZdG8=Ep^}da;?M%Il-*6#sjfqokG3dB)(5#&HuFX{v-yos$u$&W?v zZ8+Tz-43JmNOx!1k>q{{Y>#JnwQybBSo(Zr;|UAf)YQfuHzOe_>;0(D z+nRz(BCQ|I*nb2u9mFHWc4khr${h`Z~gNtH` z@N)Guk2bw`)DDf|2h3+sFSgr_Tey=U<@ymu<+0g)6{8xDzW$SiFY0>|4f*~QjC18Y zr}a2uR>#7gUJ^jOlh2*bY0YujR40z!b@K(|$iD>8)33+=AzXDi=Xdm4Bv;yv1pzqO z^RQe2PbG}Qsk+1V9N3i{zjp9g9ZygN<8bYx{2zX@Q4XjsldA|lLrY2ukWdxoOoR9E zVL!oZmE1ydXd*G9Z?buFxBfy7Gy~Doi6wP_4%c+oSS9HkY8)FYyW&cqzeboj@UzYWBl+#4IwymA(@0T<;;kEVEit+#60Z z@`ebho@UY%V(6-6tY6)4_a8dBSUXq7$|oK}UJi3)oRyK`SmwVyKLcCwop-j>O>J2~ zU>7jrZ#T7ArnQ`I4_L^qUA8m%XbfL8fEWKIT{ITlP!qtsZYv{ctmu=N3C>eDVu}558U&47*F{PGtO*1gkJGIDE_d^1CQRl& z7;hLCmASQg#;Pnlr5O_gEi*^%&Z9`GcM^;AUbuPhifclgA+- zt0$Gj9h{FytgHz79+=y3-;{rgcM83qr+WP$rH5gwf&}Nz*nVer7REvd9w{8)D~_3jg0KkDu=C4GeG+J#_q^x*(p|&aceO~O+E0=^Vo-LYnLP$? z?=Dun*)umCT1os2BhOAdF3@tyhP3LEZyyCgqqii#v6IgpmCyo zG$^ob30ofO6K%w~Np)kBAhTV@S^<>eff`Jl=nM+#16fZ)#Y|jVZ4JrdD8}%Q-5W(h z`J;;a!l(sbO`beo3Ml{Q99cr6G4PERrbd^*sJ2r8HI&C+6!*NP>Njv{%R+%hb%CVd zoo>=RzpMl+w%-ixL^^P{POQEl?>l>qev~O5bM%;GjT86p3z!zr8gri6Qy)+Nj`869 zW?~VfN-U^}~LiL^CUEqVjtgwdf6m|W8`WM3YE~R4ss^=I2rZ3eDZLkvZAEH7Hzy2Co z>zGQvU-p@Icpa_Q8BmRuecs+L5P6N=gR*MNtgjMR9ZpichK6S2Yx=nz9hyIl9${;4 zWN~6z^P9w*>Ez$8POc2<%2X@W^#(0|nd=WdVbnh93Pcn?6&ItQdXk_&5!6oc8tje!`_`8foT37JE{pA?|0(~wWYe~(LCqi zssMbrLGSs1Ure88;UnPDlnA9xNFH_b$%ePlm(Tkh^=YN64#kzq(bQx##JwroCN4Mj zThidnnGI=mbnyt3OC2SlOfXz(HI9&0jOLH(@%@4KbT&11P&q$H{e=6CUvA!bN?|*1 z*c>pSz1g5wp`YQdAjTHcWMj+r`^kwlTJysaz74a|{tc9B6*;IidFXvVqEwu&p`oXu z;*XKRw^0{^^(6=%Qp}x3;kxqQpQtDt2xdLF4OyUEOO>hpFT&FqcaimGG--tMrNyIrfT7Yq4}`qu-CEbMK|S`NK!VBK zP?g1iQ9&1$*A43WWC94a=(c&km%(W723W0<`6{U%bH)%=-5Ok%`AufEl$}vg7mi{t zDgNpdoZ*cdnl|)r$LC@GkT~4WfeaCAZ4^Jm>=ohq$#48ytlOvXwFesurVJpv_IWy`TOAq=MR`g1hwxmog4CpPAjh6 zS|^rqZytBIY;2vEvX5q*xdnby$LhY~sm{UC0w2srtx?ya)9*gb3q@8*8cnn7w&H+~zG zo~N*~`flZoD}l25GK>2ia~h#6GdM{k*I9Y z;5xmvC_5jx_eq%~^W*U(Sbzf-MI8#amcx4)Z71C-M^O$CpC$d8wD^Gml!W`I<0%re z4d0jHpKrlWf41O(D6f*bj_byAA?%ZPxOiH*iZoDE@dZRN6*Q+(V&rEXgNNqBiG0)w z@O=qJ-Z_wMpTG{5`(iAk`KBs{!QIjw@37$fF)xb^80p zNNNjuZk^3zz8#OVhf=-jK4QOsO!O;qAv)66!oGGa7i+T{7Akii8C{aCehrqP1ekgb z7qdWe-0wlcb?wiuHkQN|dSWtUIi%^lhI;IcN9UmPYM`6`?x!BVz$q$Nk)oP7tq34& zn)U9qwR-2+AXG`nEQ@KC9zOCRUS_rM*862(c} zZ|wHEvmlS&i@a0~Jx1$sxvw8rgf&D6h1*_E82zjLLmFkjIQ!e+MToP;r`&{z9WSAz zXLH7ZT1*-98po==qJLBnsX#k1XHLlzh8mFg(hhx%w1=a4zL+M(_EnM>oqXU$e@;JL z8vdtoYS$<<0YC7=V^F}Pn_2$(lFwZ38Y(eYnWwsD>%h?7XXi<4jHk?Of^g@i^&hNk zt*dv~u>P?i1!mx)_sAoBo^&?2?OFFsjVsn;_Z(Wse{5X^%KLf}SpCw97JxZw7D*MN z*nR4e;8CEgy$V@8XqwxWPZ^t>>?V}_Cpp9=GXih(5~NmH!YY2Yh8%n66;ev~yu+4c6w2Rk6aONLpP3kvi`k#j^b5Ip8{IsOWx1=& zpk^z2p$G5+TZ~LR6bia|Jku;=XLP){i;oL6bldg&fQq`|tA==DW1O@NHi&838oZgi z2jGvaCr0pnWB3NVfd97Vt*-1MDTkhpKE>T(=Aq zGs*2oWT(F|yw4Wb`HyAG>Z9B!Ibp_6s#)DEV|fODQ8dSd(qpUTQD7PU=Y{j~ zTT-nw3x)lLQSG&Vhwza{5?U#&92%Gpb9`d2vSRjx_wsEf2J*$dlS>4Iz+6%~>qXMW zpI=NhMK&!qPu)uO(p;QXTNzo^Wi?!16?o25qHLOD|5F*pa6^*bl+Ow_aXd!wis^lCT_H4UHxujuzM z1q_vp}Rzcg9%Gagq-uDob?CX)19 zaG<(n`r?)X&s?(phz@9;7qIJ)$53J?=RX~Bdeku^{8d@zM8^;(wH7kB+;Yei@N$fB z4jp7O*Z<_=&fOJn{}WI7Jc3?ZMr^-hPg_Rk#}43TG;qrdi?ra;bEcm8`Ev>N^fVd}@?H=?Jj%zu64RW~^^rK3{3ru4 z*iQ@OoM!h#_4=g=Y)Z#bpXKy6#;Zu^u2zUFv8_N9EqaCe{i zmV4;8Osz&fFO3`O5Kwglm^`75a3L4OQ^SLZ>ovK6wz##zic$p!Nt(?MbLOm$9Lm}%>=(uybjr3yl?2R^LI~A zs1oS-=l5@hbI=b8iiocCtVlha)CoL=&p8cZHM52`z{lBY+X!HBMc5kGjB^uKzOXqX zUl-I+>m^(L*njoU9{Kf)bTX#nJ0y|D^`aPa!yD)ph36-oe7MuS;phwe&gdvWNMpY- zU90JrRLq)6JJwbq>%X8}&<4PAlahwS<`%04=yUwB#mkr0smeIh?AY?@56JGECZ*KU zvzuYy6~@N%_`~H7eoz6wl`F#2e;H=}lFNSF!#w>OH{xBRwY zdVd3OdK3flJ0db2e?bVfZ97eIh|D7(cmbJIVyv0h3*kMFBx!SA^7H@xGVckoa)Cf1 z$xkq5+3(z8nJY0)H%T7N#K;W!v%Y&%`^?@To32c}vf=dYyp)~(wj48}(_E2bbuQ1S z%)?@^I8Ki-ZSY<%i&H}c&kf=Fzw7lBYBz3kYW=tUppk%;h5JGshxeU`uU3LZw9{$o zxC63GrvW?mVz$Q5wk{k6Ar0|xf!_C6`ZVdL{rb`Mk&QT}+5sP#WIon>5;|NF&BK|s1wq`M_$q7sr{0qKwu5fBiR zW^{M=q(!;}B!+Y&9nvrwfsq^A?*D!d{!jPp-s_I*I-hgi2RHVqfKdP@x>-dyeVzfrw{EIoD+}qcQCSI9EAC&Nc0s!Y>n}^UgJ*9wPS6+-OXw%7n`G z;zG4HkJ?P7-uM0(Xk!%nFI`~#Q0WS%_P9m9Ak5};jXZ)GJ<-~ePmUq0DBDWQ6w3yb z9HtP(`UotXu=!I=`Y^ULlBHe41qvokgwm-IiYIevYG1iW!1u2_`AOp#$s+X4dAM zb&=+Xm!?`{9AKcNI}Wzr7UR&#BV3xJR&4cM2vv6YU-+)@YT@hW+UG1;(Bhj7lLvLA zRVcCYq|XMCee6Fy^pIkL;N`ZMh#?$X(=ohMTRP7_jp7fj+hAu|p@^vMYmR!Eq#Z~* zJ9q#NYms_0>}CigQ=ELS_xLY!+!PH)z^rTwjGX^AJDE!YS+%XwpVFOT@b@7RHhtS_ ztfgioff3|vD}9a*Tw3{myh{ke?;1X!RK&|+DB*qdVY*>=behc_dcPb%w(b3#I|I#1 z!Sp~_CxZtl%1>@?7fbFuV8!!y0Y?uV$~w((<6(b!V2@_~1JEBkdT9^!J+uh3Lk8ab z?hI3WknGxpEv$OljreWL#1(tsiOF+j;;k`d8|4{teS3WzHCEfEbQ0-7Y$*tKHrdpa zfBK7{m*e1RRGCD@R3Ard^wkBYxLx)++3SXk-^E2437Oer=7bBw2l`0vrZ-iOXmwrs zq8=?~uTeGuxbd4|vKCt*6wMm^CEAVz6GM+u1OjpEh57z_8w3Q$NkMrQq0&4SF*3Nj z&R&r^WHz6mR5L}8*om}_AZNtU6==_ly{9?TF~pXy4BAJ|R{x2Rv@u$27UjwP!XtaC zG|41z@OyeU!tPb+*43r7e0qc`+1-C{s0n|F=&6Xwew^x8kgWMvCtO0HR*|iIAGv!m zDpWT!KSu8ca}zvDw)Q2FiQ>t!614by$kRA^hM1bLJ@t53pWVGnsg+SbZbbe75u#J4 z3QO`~G+0C0b(J-U53>@**Ss`SeQp|wLZbK(rJ0N? z+52}Un=m&C^o9knW=fy3ST@R0lXKRxn12Qu(MqE$?0gTCXb2hqagHYdZb0+B9eqF9 zmh<<5!tZC~?>y7M6dZbpH0P9Av9(roszD!7uE;=&61bG+i^wBO9^8ARu8w4U z)9X4XU{<+V_O25|OgV>teW9L_#@1P#VdI?{C@MK|_l-uY5NOm5uGa=a-{C0ysBh~5DfF^X&zgNf@{t{4lUDkVK@IZCmzSoo z7)p!wOKXb>&121yZl*FFS1HFy{bKzqz90~;0+YZ>(-`=u^z_D+t6~uUaMlI!zx-1| zf!LML8@^`7u?Xb_aBibpoB@BiwZC9X*2LXS_Q+DQ>ZZf-w3kwWQ2(x&C|FoZcHOJw z07Oxh4IXIG_F8pE*g$XJ$`DH_BCWyCUMa8;6a-2g<%xenwVEsiPo@vUAuc|cIGn#v zhwE-8{yy$8Pt8_4g&>%eSr-V`JZN$)Qc%32-y{$NPu{^92FBi3BB>i! z6w#qb$I62485)+qzEl1WumClM5xVf-TYtm}uH%^V(@+pGq~pR&5$e+3P}NtJzwSG~ z3Pjw9TsZ22EpFh96Y%|!o@WUe?1x^(MU8ShR2bZceGMO=g}l8=!o^?_6(QvR)*Byi zUG71-5Dbf;_bx`CGe$-jx}Qmj0B9!%u0fG#_!OSHaWTq)^v&eo&~I*Y`z5I7#3`NV zEU(S`#YC{QO5t!_Cl{ND%a)eMn=IQ9j8YW%7(NvlvHG7F2z8Dhph}MNg!^EdO^KW7 zd5%r3tV&j`)TAmc`Vpx6`#Za&ALvVG@q$`tL3h&tCQIINcz5^ED^mDP2YvMbTLs3N z#{n+MVbB1Kz(Le@^a_3N^>o`V{Z_KDgiG{X${kBV0`R_}PPhK!0S&`p6;Kkn<}R6k zXvj$<^C zf3}d}K=!G7XSXw)i_0?`Nc#ia+r(ycy)`zMIWmnmPJxb|aePzX^kdW1O>JEbka}9P zMgubzXXpK&`J4yfw-7o$#rZPf6+qj`q{eVPC4slIEHlNrtN^_o@A zpPU6E3(W4>bbS45_sM4eLq^?ySOM*V`4ak6SoS9bTkSi8DW4a8cfR`{^WuYb0>GJ(P(Xt3f+NKi06 zh*g-vy(oL}B7h|BaVYNRJ-aX1Cp`kew-4J$7JB&QU_q5xY(v~DB;v)d^lrlcNWyce zZIwbPQFOv`-v4~0$-Q(JTLz2=(mD&zG^gftL8R^q<(>fA{Lup0et7r0C+1vHP5B;D z4k8v=0iFD`fB3`)K_&B(a$Opbfa$~AMO4{=XSEC|T#HPL6XEoz>`XCx7I8G@{+n=r zOn-a9+zmUGd_~Z1WNmlFyAa~2n_ZQ-A#wKYfU6HCXWPGs_Y;MtRVK!)4>3?Ljt2Tx z;A11g?(F%SR)IjcP*j^Of+>wh-~;fes0EstKXr6qTx`uvWY0AZl|>kv@~{^+_V*`K z(Yi)T3HS>6DFaOxAUmxG0;0!-y}p0A@NA z@$Z9UoAAh^z;aKCCxE0}{$3)|n2h6{u$??na8k;`N4iC@*5e2k_VT7F0;Ug)zTXu& zo_nl)H%L z%49CkB!r03&4?yGwI|Dg7k}K;^jxelQErO$0oSsko1G;I{hCkMjBE*XTIavc?!3FI zT@cMH_SbpfGB`v+xV3cZ=M;9dk&Mrv-4j+{Z8p?gEd{ZwsqI?G`ZQst@1kd0H>{ug zKDUp(iZMG#(QPKndxks3T_Uc|9d%)Rx%ZP^*f3IjkV?yxzwSek2mPWeOqh|08oVEG z7B46a9+%sa*?l5fhowDrcBdC_xU`fn4J%5=_nxUnJ}H|*(FMkpU6~^Gmr}1%fR=CG z^1<@#_h0SV3;TJIjxO{&uSrHB1N480a4R5a3~oFTxzm@a19KoOs4w}AjV)=ynecnj z!zxr0`FGJCGh`G;B-S{FM%-;Q{-KI%LTG`COOtb0$vl}3>9nbjJv=#q{d$+D#70+3 z40OFq82+lqg$UA6)- z*KO^|P(y^dHfX-`*mTs&2T4S_TWp9pUPn8*Zc2$7SlOwV8(u=+VK%M~VR|xT0aJ%} z6+c_Ilti?-FQ9LA55n2NUuX}b=n=DNg4zU??@*PMSy4U2?{*k0e>;*b=tVxsemzis zGx3{onb1R=^`j~CErNUII}bF8v5Io_qk#UQNA{h?Ndatl zo-@6q$fkP!mp9dEww;ui4j<-d_m}lKHjEgJ%=#nlmz*w}jPFhidw0cja~Vmd8wlns zQAGsJznPOCSVi{s9!BLEAfTb~;Z}teB~L8Di>1K(i9EZDtr7PLEEQni%7-1UOFZ@L z*1`v~y#InNTOX^Cfh!3$XO zX4Kn174q7de;&LOJTbQMxvenj6B+#gvU8qKzAG`t*DEzTlhMe;L)G}nZs zmt7d7Vwh|p7`xgNV0*pqDR<7_!#4gkEC{^glodbPpfSn=gaI57(IQGIRLAna=%9{F z%i16ls?Q5G9qGD<^}!fo zkx}A(fMtrJEijDG@CeWP7sdt%=Qmd5m;dq(M#ukQ19dj|98OAD=)#NPN!WV*jAI*o zTZdz8!gt@m(PEXyhevl>r0O^2gtli!CFOJ&h5MB?>w7@C0 zK$7Fr<Bt%M81k!lM-daqUlKw|^UJ`p-11yJf*enwu}xB(ijfol$ILvLfgQz(p{c2=&z zaLCd?%*mXQqy+x63e1)S78aN{u_fD`N(RqJVj~C12bV~I*%6H&m0~F+s^`Jm+LHqV7tcwR+-C7Mknt8#|_(8XQ=L~dQcyRFh=WKV* z>fsp0ogwh%OYm2YB3tIm?HIY2sS&gRgQdGRUttjVVjtbNPDyT8ppxRo!(M_@|1oBD zf&SRL zrh^m8K+Zxkqo+?JgEO2BFo|%FM<9mlqtLg9zft8wTZ>`WRC50gLB3 zN=}W{ixS`(Oq!Ob%=8o`m+IQDFaPUmVE)&6S$ob;@7ZQ^l+e1~vyt~dYFmbCNJ*0X zgQ%IW;q@ptLwkuw;qPrP&e>QCJrT3Wicd4TVyEZgqXK#2ky&{Lh<}<8Umd(F~Tfvw=Fd zoj~ZVepE+17{y$OKY{I6-U+=+I73~EJvLFZ=16}7OUV=hCo+;KQ0!qv0L@^UwA+G`()_i6#ags{!9IkP#(lnN&#Tbi zieA(g{qN8*KgI*BRrFP9<9Fy2#PLz=lGI{eimQN1bE$n#9SR6seb0CJVK0fyrjy*BrvCkb>0Ohv9c z9$zPSD~*;{11~8X`QL@&kD|$jI4pmN1*uCMM0j?RpUR0Wq>Q_vL17YUwfsD$;)X3i z#B(}}9j-FSnA<7GK1at^uIBoS23hjPnKDVySor=5#`OvdLC&bshXGP9!Yv5v4+4Ut zV;c&`wFdt|3@1A$MYgY#I%h5legep~!m5j@&Ki(!nfCE}0d$`3z(+c?6lezNQlI(y zat_0JmMzLfdri|MO?rdk3$)VHll9yqtA2Uyki7Zh7;s{X5uXlBYTqeIRMIzYl#=+{ z6q&#rUY@OpeY5LkOZ%qoB`#xfY##10mGb7fhs(y;DH>Z~C|~<{S9UWRJ$8MFxV#_= z=3?H`I#B$yrFn4tnPJB9FB{vT|3;RI+2w@>wKzAE^r1QW<*SFtM_JC%zTRg26Ancw z;a^QUa${Qhh&Tc$)kIf(^gBJRvKROB{XhAjrq!oUWl+~yl^jOB*#irX?<=vetZ_X( zg$m?;jit5}d*J%Rz&B5Wi+^Dl5Lp>7dY-=v>NN%I=vWJvHH=b43?KU~wSq(hMjxj7 zBkU|la!00m7#)?Bb0}vjS(jS3;we*VdQsk14Vky|loz^49qQvioJ5n6Lllg?%Z!7pAt_7rQ zwn!;bt*Zj={~{~uyqEA@9hj`dPLA!c;+)KY*>AUgJudITh%Cj%v_v;<5C!XhMg%cD zyxJE!1+gqdT<9ON?;ctvTqPuuvW_4f1F%_q`M?dZt)xlsmD8%d?SS5Mjam)jB0`9S z&)2IaC9xG?`^v()UyEV>1IPF#UZ^U>^CjqK$$)fz5cgfx!R(Qbw~3S;8)rrCzV;|& z4@&p)NAPd(qMk(H22R@|yZ_eD$W_5lAqw;oh#bpGzO<22i& z=#M#R$XkRXc^FmUHvrdna7Rt6Fr(n-L+Zl0e1j~)9t|Nz%vuLjy(vUY zfpMk7zVW^BmcEyaq~nKav=@x@TEe6V_M=(_k(5aN^ z84OWR2d>j--Vo^Z$UkKHHBLVvQ`vf z4=BjRZcpftSH9*IZHo4Bj)Sy^m(s+(s4;7D{_*xFNbQTev?ND7%gBHW4w}6vYNjdo~JTqugdB>;W-Y*nIzggxxyPC$7(3qzVHMv zqW*9{L-Z2+SY3i4SW&%2HEV}?ty^IPeyIntqXI}Zscx3m9rWB0Gj52CqCQp)ZJ_jgEzJBoT6yn=&tc zNYQ=ef{z_y1iYe-*jt2oTja=49a3&%O0u1F>SuF+-J^Y_t4v)z^Kr!`+Vg zPA}H+rVMGdifMalf*GxU=;db0C}fJM{-fe%gt>G64|T6DBK8rMR1y@Cj|pYOctg2e(T{^6V>fqnusI)AIUh=IMjH3E6d*!7UT zge}&IQKJytg88j?y3*43AV{W|#*>#`8ZDm;*}+lxr2DgvyD4qM%*fon;YOOSQUyP8 zzh0h-Z(XeO;Kf}@uwgAcvb~OCz@DCk@)>=e9~K+II@o)JSJ$o7q?PptOX@e#?`x@( z@SJ>ht8}#^KPX+X$(VHmG~GaBQAR{*Pg1rLKP2NRT|)7SiGsB3csjo2`@X2Za^Cfp zK3#F;SZQ&tkoYo{@~MX6sqEcdxB@Q^t9Nh9RHmWi4Gq8(R~*UqMV)filson-Bb&NAsH!JKK8Ld8Hl z^Yt_{uTmz<%t#*`r)#lrU6bs?xym&9bHC0zeIIno`WAlv?w;+I#}Ip!vz?yeX>)WL zweO$*PW960ayK=PNF&Cwr8}JvT$SUtx#AiM2fYVcJ;NH49I{ZI* z>_UWeHlD*#ZZqL_&%UV{dyXaJ7W+E-AqAXG3)Rs-`+M$jqo3BS3kW{i}zmgJjfB_`G!*I-ggKHb4+9&Ou)_ZGbSCCQAma z7#EwsxkdHyzZ-Pk4fMO``{dO#6~KPZ>+bI^P^<-Z6Mp~I|CgdB!+T=vGoC#p3@+T6 zgB9liA0*@e$^yjQ6@noXf1$_(AZGXrN!{W2ZMG~>3l`Q|2gFY)$yHF5F{1nZ?kFSJ z6!>z$GabT|dr1_zJjs1Zp=wggIm9lv8Qd^5z+g$n0TVY(m;0$B3P_HLrm4>Av)-q2 z*!|1S3z~ekzgmC%sl(<|BHEe@Gu|{6j!k0|eqTz=o@JqUqfeCEoxWI#Y8V%+sd(_t zUQEwm4nzHTruDt>jW7*@N%TikQPL-_;P|uVuhOQ0K{yb*q9(+8b#iRc z&VyyXZWlgk@1+U_#IJ*KO2jmXnv%kU-h|JTx9ydo16hrZG$6*3vyX8t6KOb9uSO(f zjX$+*Jy1>NCB@s)9CJHX`+koN?3kQadrp#coc$!KZLif6d2DLxbJOnFi$z_Nfe+#8 zg1!i?miU?QN7_TI-qoKvwgQO$(${KTFrR+^STj@*Kz+_7l>_lg-#C!Uh7I?MP}4pf zqfjC_6ynE|D&Q+csVY2wv7XI4mR8?9lvkQBP%(x7JrA3z>30;H6iTigtu8U9m2bd6 zROn}iaGzR5vCg8zeMyiP2?V(%60D_lj|T6sW*-4PTf=mKN~e(0Bl9UKo<$LAj>(p- zr$=jsgQA307H+<%BSuUUxxXdXpfNjtmwXpKlLRV@dF8du{Vi-9>D?I)x;o&o<*L{{v@Vz?~ix+&ASugqg zD+;_{(IP}YYlf<)tcE_3gE7P_+u9o$i%2sWH+e@i!?j+S|SrMxjj1rsz!q+SEmQdLTbUu_@q)$kTFdz3itz_-TBI zPtfVqeH}3iyY;r;uaVt|M_u&yGZ+2S|MG}}zz{J@ke>nibj}p!tZLm`dfESaBTCII zn4h%ju+&s!SCvOMEI!uaRaYB1_Q;A04W}0=bGPTA7BUP>;TB+nX@w&y+TeG)au$PJwvk z81XTOhaZOEUIR^fMB&|m8!+RxqguWDNz+(Z3U+*=s@b;l9CDw3P%)F@E|At1}7eRTrLlS%lHilP7!p5Eb>!`s!Y< z;W0~1d$aSRZrqym><{hIU#`xM&HmdHdvD;qqrCkPcwyAzl>k-Yiv3}a^WAEkEy_I zU{h1a+1i&Cyo46t0ZC$?V_&iQ@g7>dm~PVC)OOw*GR z!Hfs31>L7HDdB-B529G_=LSK-Q5}OA8?hk0Xd{OfvNFwUQ(!J1=_w%;(~`P<*~Ub#>9={eZ}!=Gc<7z`E4_kmsWof z3u%`bdNK`zb3L~If@wMu{H}M9TcP2e*eXHaW7aMVX-Kz4{_93d6$q_-&Z?#AIy!&b z`-6y$k-YZ|ESK|-)cWoTy#>HNsdPMEkG<@Oc_VWjrAP`l_4e~+j`*^lOWS>Zn^p@@ ztzt+`DCe(jOr3bRI-)r7>#eY!dKjF(M<7JOqq`iOAZv(Y@z@>#%bI=t#BDRYcc`9f z)^Y(F9WuDeQn6#e>z7!6BDr)&*OxWaz-X(b+? z^5D!Jd}SF$^Tu5UF;04HA?y)zeWuLN-S)Wa_X8FUWys-4>qfUi&3={Kh4qxzFg*;L zfSz}6Jh$O4z%TzDQG@ zeSRORZz`MJ&{{#-hknr{2OV&8<&g#MEzRHqHDxb}%d06pNo(JM43See|5ae3Z1hF4c+ig- z(`n4o&+M1Y3{%dm;H&o-yNb@M0L*|4QJUVP$$kL7t2lO`{eEp7Mo`S&zyc)T zp9)DGxP+(t0L*0X=V&^t=Z8b+tI;h1OXKy_Hf@Z9zOxVd;{~d8yioV%JA;=0pl((XV2>eeylss;DYv!s}tGF z?%ty|KCd;Ps;VVfqu7b-0GgpHE0!tTZJek~3L(8CSTagTN?B4NfBMT^d2~Xe-&f5ubV_!J(4;92fZQ`yJgW!M>m|*^@7NX-ahajYOSBl-WZ;&Y_`^Bm3 zBg8Fwf8*mlHwc!VHhr`6i%LI^=zP`=_$hj=et{(K?jNlCB;n{)-C-#7!f1bk7qkLd zftG1qQ-)c#K!0JzZuAhOc3e{X;wZm$9oe<-Vyx#d#<3E~B^4moSwg}^av9r@J%VZmZ zIAMmozDc05v9juJ;-@$WbEfdr(1gU{vCm_Xd>7Z%`;fT2E3;wn4Z^V+hY^5ZP7FSt z_nLEEgo~(;zDtE1bt#@Ekx63`uc@?tEhP{1?UlH89TMi3p84Yc7gAx~tr^2k_RGA} z#4S}myZ#8N1sbXQ%Q0ZGjQkH+Djoa0A}4sjeK% z(K*TUuIn z3_9f!{@s93oU8%F8}6Y^@vg9fEZTci1cIfel z%(S+)9ukCu?NV>CuL<*Vc*;~t@~lDqHs=-Z(v~Xv9vs(1O>v<4p5{}M%boYs z6R^u=!WZ!;l$Thq(PsthK7xzj`pP5AGrz3q=Qv*!2nm;+D%fNgv%dLMjzLdm#tbp4 z9xwjRL%W`iC+RqTF6+t8Oq)M_q|Ez0qJ$9>MTF91Weo38UfX@oUN`7~O zTl?*Rr3u&;xtyJn!*?n_B2Xj0S^2wCf~M%HXu^aR+#Kgf^S+VP@)voU>_PK)MviSO z+b+pq?hj8^q?>wr(k)TLHD2aTRNF^s18fq2Vry0_&HaeYX@NtAWbuSd&8*oNUV1vL zii^LWL*!;xL(9%aT7Y6whMGF7SeiORZ$awDBJUzJe zPw|X=aqDu#&!1LyH7Q`Xq!AdF%#3LduOg+S4tw31agzl_@hF86a;NsM_VU?h|3Y7$ zN{Mn?cu#!UVir#AR(7IZ8JZLK`5n=>kUg%zK;x9pjydD9ndyIhuz9}F&#zRU2v-qS zUl}o2mk4kHmjy72ve0aM0z={UB^3Rgz-6B{?PR zU2ERr$dM6)?}s*MA8(`_$HPwyXFq=<6wHKB4Nlkgn+W4>#uMPmr7*Hxq+6?b7J1?* zyD5Ev8!p`@*z6>1zu-%wb>d)Ae5y387xEm#%L1+QMA+*xsAejejbK|rQ3Pb8DS(a8 zBOxC~E=NbI$@O|($)i#sgvP2wu2OUa`MJ>jhUA%NQ$Xf3Cjr4fS2l}Z8pP9;m)G9> zmXJ|uOPr3ml)eUac0Fs}Q8ylSj5A!5C>FX`zq%Uc^Y?y>=)XxopVqG>hCof8GZ9Z}9Kv#yCCXg01BB^ONxdu*62lNp~*r{rd@cIBiFHy$U9zHqd+zG8ZkW znbgLN^MhK}UjU=r*P+^i>vd##P1MWtM_z+VkTK{M^0=?6PKV^o_tqaPrFTk@zNmKK zb!_9u-*G|hylO`U9EP??B2ERiY8C&H=#FXHdl%Q+$W*r*aDVCt)5g=Zrm&<#@+pkGO=;t>jIIRp27G*#MAxwFNaLAXN zWh_72`jus;;(1Y=#W=YhDdK2aJ?hxRx~`k~QwRE{p6}`Tz=ykVZJX#-mTNjul#)nXVma?I#p!dVAco9=P&R3*t|<01xTz^W^|VYlxCpKxiqc{ zACAe~Q(Qkz)ms%3gECLb?RZUqlz&aA@090c%l2P7G;t-O8g-Ap1%p;GL@t{sV0=T~wr?10-y;oA52mEIkDXQ}jO z?mb!eLar>}?}k+vV(83WaxHah$u3C-k1ECXIb+xId%0;_D-?ZL&=gt6X}8eRyspSJ z2Xb--;E1|_UJza!y1Yk@nBhcnKh+~px*gh&q;jSYjDY_()Sm0Ycr)r5Z&^?%bYA}i zZO(qo6O@_Ff={^gWR9yZFEN z#bT*OZ~|v?A#I#DJ@^zoQf&FJa2+elA1KcvXmtgY(Eb~wI}JUa)&b=&W8XF$o?{!q zNPypt4c7g>Cle|l@HDGD=-=ZH(;y6#Na0pCzRIit@OR7W;Pm47aqx@c67;cD#|NBJ!mc)k&sH!=a@*1FbjlOjmwq^Qxv}UR*p@L{ z@}-VzKIcZuW6)DOtg3pttWTwgM%T%;GK0ffJB;AQ(Iv+P?2fsfW@ZbBh#+ z{{o($c~sAgVq6ooKMuaH5Njr5CHQU7E7H17t>z}70FRdzP3;Usz0FFZMIBe8RnqMwMASXW{uRy$hV40k4#`f#ZJPx8w1SuFN-!Z-6os6uomcLt5#BXDS-e6g3%p zt?tk@4w9OEi&p0Nt}XT43ND}~K>+H!>?IT{T(|FrJnq!glRc4i@)DPWVf5>%y^vlY{)OS75px<2X!OB z`l2N5oa+5y{7W0~ICq=hyAp+adc0YKX)Ci4tAGfN(JJZWvpS$gHeFIcR;ySTYIM*r?@Sb*PEKzH;0OS8y0Lr9!l4euL& z@p&OFpQ^Wv>FPoC|D!XuD%wo+>8|iiQ}2~UNa(Sj`#4DKua~gR&R}vf2~^E0>gr`e zgQ@_vZsS+gB*xvw6J&n?Ds@(-+Ce`Wa~3FOsU4le^EP2xD!0b5e1#+2p!=HjeC!^& z?e`RzrX4>D_BJ(4g(#O9xfJuKboA3{%078*pmry&@0vj1rJZ+O#%g}Vm|#fH){9m^oFuh$p4L5Jr$g<25 zVQPD@z14X+IiEyvn)0^&;GtDu%Y2EY_H@{nMS#1L6O3(e41WK7DbTw!BJ@?kJTP`w zI{Ao^*dzV+4ePx!5RjeBgMMT7_S|fVyA6576~6dpK3JoV+ds&bA_Ds@Gs4bKZohxg z!o@nzd)-fEpl>aO6KC&-11rn2dU+c}RFP?rdINLw$Yz)w@@Qp|!z#ip zzpksofd~{}@l*+ig}C*1MK-;Q02o8~t!enu>>&PC8Cs_h^^-pOI}zrhzdQR|@>D)T zEc9v)Gh(5ws^UZZG&IQm*fp49E7jVPwa}lv!U9|0>RWmP%d!?_%2zr!_%FSuQ#3fC z4{sXyU(u?BqA5nor|-P^EJ$_)5=yA7P&Skyp9^AN#Ee#n`Fp&2S=@+1X!!SuCbpV= z{d;OxjGnI(CDGfYRhFRjPJ4cSe|NQPzw}#4PQrGmz$N8p`q`j=;voCXHG{q)}xLVlc09>n731=155vwp?tY)uqLz?OUpf^ za$pqHS+f>9{Nrkr_rWW=`Kk+FF3?=_xOll@?+d6D;#pZ9WRFV>S8084-Qv zjSx&n4kYf>F>!(_>3haofxw~ohxh-ac;iDr?>8g@YXOOrTjl$IEc|0@<5fUT1wiFo zUG#`w{Tdq{8gAChFN4J``&7xOZ)h;6NX!6EcgXzw@L#g;0FrK%Ir9RA`izcGM$af-dae zuyE4Gm{&#p^zgmBsi%q_81!gWUH?`5L@45^%n&3X=1?a;lGo~D^vUX%p@JdhIW@aqx;`ji*$|wGPrT*$Jj;^at+;PO@l1(r z^z7l$Eui-CDt$s0 zEc5y=vu0v4(|cw$*L}kL%H!H!Y`VJ0p>X#W7p?riY>xS0EoA_<8RS=R`|irt_c~S{ z)CMNVO%73-#=pRtlZO)^cyqjkbgrYoCwfHY2>D`!ZTh$_yZsfQ_oo19?Q+3sljr&~ z(@LzH(X(s6Fr!T$bGhSMTR~O?EI#=(&JL>S!uARXa11piUTl95LbR@Z6+-54nEf#M zIk^WB{QM@U19-*rANX#^(O^pPtkYe&@OTxQo8Qd4K7*^ro6J9_eQ&i~Cb5Qvu3uOF zi1B%N)lZ`r%acOVKLmq#PRje_Tz_?R^t!(1*wszKq`AL-|NRs2e4tp0e%eZ(@c4A& zgNTavk+t^rK=W)1iu@KZL;P*f*k$@hfe;3p`OJmuGK-}+5ZTw5H=1nBKYV4k+WtF)9dp5H@65|3?TEY2pl}& z!lWx`&4Hx0jRedW%cjOS1~g`v^JQ&lIP?;_Hc_PFZY%6QZA{$OzA0^u=v#edx33MB z-T@dKOu25%$sd5TW}xY9aLflg;H7Qk7pbzZ#jH?(Z;+>30n>Oz?aGjnn$?bJ1&LYH zEPtmV+8y3eg)K1h+GqJx`+jv|XHQw z(uqT;J04SrTJL-;*FmZWZ~1&dkd!0eYP`xo5b2xVn9YIYW0_`CJEni8PU-mtdHqca zwbi_nDXap;IqrTI=n5Q!&%{aS*%uB!`f6AM@YkhXGmLKR&)%2P%)GoYmSPr_{;V6SwjYtY+KyX6S^?0Y> zj!|?D|JX@-cGLfhZpNJqBs$5`G#PNQ$i{8Of>$yfvhW8Ac*YqD#=ey&uu| ze-q%XAA#K=)JfylCyL77%w31UT;^$ zO``e|vB)mkewTWFw__rN&rq44Q}lAvtFuRzkcDOcH>aSY>y+?|wmw^IJ^P6n2J~-R0wdy$f&Q zz$xM@^m(%SNPaZqRUXQ?;p>Ovr24HjxqYcls@M$p7K6~+x7`AL0@;Vckfnudtef?4 zL>|K$&j|nK?B<-bd_;jr7nf;nZT%f($KL2j={{H0iWN#(|7Akv>=|>6 zo;lLl-D5j8p;b5P%yja5(|7`Lwp%yqF1JUJ^d?<|^ZdJG?QF5rk}pMp$WD~q4J=>; zY}d)G#A2A3Ul}mD05Eec5L;v5Su)-V6fDhS6D3Wqhvk;7-iRVO1dJlTp&Pd{W8>0 zsJ6cIgRfMO%c@=Q#Z$ruh`qgYNG3|3;}xUGEhVcXTSw_07A|h;_~|}fu=HmOWY$354r94T?sU7J60r|P6KrE1J`O91 z=ntL!>rqiaJBIrQEl1Zgd(v`ibvP@BS{2rF-MsiezTP^n$?*FdR}qmGX+e-2ozloe z1w=|3=}-}+yJry6T@q7Jx*G&WcPX6%#^@Xj7;L+L^YeY`_xnB1^Y31}@2k#z&UKyZ zyx;HS!1lg-!_hVz2);PjhNt0Qc^ca30wPv2 z&ohjK_%goiR@yibNPSavad6LxLn*&a&Vhd#p}}$CM+8&>J43y5YGD3&Na$nFfWtat z6J{6fDhqv(&q{50<2gACeNmErr)cmo`L>l>Fi87#dke*FGnW&ZtVLPyV2HcT-(G!H z)zycO3&fhAi#Vd!(6F=l4}ApwpD<&pmo<39QwAi6Qb*S0J%7t_+@5ATuWaHzVb^}w zc0N)*iVYlBOW}2^Gcy<&n0e=S#&l(~A5j57@(ear#gqjwp0@kB#$b z06N9EOHx)I_&X%h1?oF%|9*AM4d0!seltUFWTK2|BoJWzeQVPId6Aoh)2bTa9NI)t z6QqdRNjP0vj~Q+q{N6V4ZhNKjjnT@VpEZK^>8#N!ybILzhV}>L0OL}NJpYgqs}_7u zOd10!Vxx%T9DB^h)1YIX@L|}7?q!~n9&Zj3)~(& zb3wR7Lpb%>0kOvM&*Y(YaY{z&?0&BuXT8!ax`?RpGwNLgk@qj5GbdebSNq{wLZGnS zBloXqK?{O;5Bzm=& z#_fB3&yIZtWIP81A4gfel#^>%$3}{B-w(d9Sxq%_CVunbybcjdPA()X+k)FznB8hJ zYuxUI+hy^`gw2R;!e~U}+)77f&UF-5pA8IWwR@SKiFOF7N%4d2daK?OT1Q`1K=2^e;Mvt;GbMJoYZql%tTOD5HUoGg-R`lRnBr&Y8ghoi1IUVU@sn7P zm_)_Zz%8BjTrx&VyVs}BFYL1#@u6c7#5)DTzln(ZB)3< zL92}3HxbXCUwc4wh3?+Rkz0x*SqMPXrrh<93Znx@5+^+HL^vq*>|Iv%^FHsc&>KFr zFhF4ks1%Po+1>2w^S%m^ZcYR@c_c)PsUE-%gR^#&`1TSvW}Y*lp$D*0Iy^z$;7ilC z(Z^fX`tyFP`I#;PwohfrSce@vFnqy58ptr&%_hPR(`Lv3CL)FmzFh*zHsd#-IG0v(TL*`c^c$3K&f*K%Ov#F(Co%obs=w^l}; zW^a`eDdLHiC=83Tamq3pyaeM}eDgh4$BqXOAZ40PZbH(u>;CFGt&Wi|pR`4J{m%Q3 zWq5eaS%4VHl0Hg~{SENQrqdTeEf=SVt<2%d4nz&?gy#hQy-3VRgP(AR{Ivc=FM1Lb zaejODgo_%?=@)Ga`1}(e99ucfbPGI|VmQ{3b+9Ag1t%YUmLYxG*S{6v<#voB@6o)& zVSlC;|854X?C~>7_$Mt**a5d*QOP-EApH~SRjhLgRK}d2BQ=!t*V48ixXDwa?Y7^x z6~>XaEC+UKj4LtW(`$K}9=n-)Y40@p0u3Ij2Q!n2;ywUDW_T=Cxk;q@U_YWTXBaYg z96ld?0DNqJ4!guv(3$ra@Ggx|Tp`ll6QDlfQrT`cLL0K?3%X3ZWQblR5nonUS}R04 zR|r80_NCp8R3Jf(ts~vqIB@?aLTQ%B3o~4!gFuF#bm4tJ#qY}ci(6D(2W^(e)sY9} zm)Q3)H5_5Y`V7+$maQZQ3py(XyeJ#s9HmilJy-AmGO-0{;LJ>ae;dqOBgd8Cxqh6+ zMGd+50onP1HBzyV7w4EU_M5+%z8>$h-0OpXd3vi6-zmkTL;|P2^v9}4cjZ6DTThM< zV#MdYL-k>oVAKROU#Ql`=}pF)RKpV7qv?Bvkl3rn>Gm}4v%bcSbEdTBz*z7ua?>MV z6oB^4Uc4D%j&|b7UJKUXY4p}!{Cd60|RYd$9g}`=|_!HDPKN3#KvVu)YtS!HXJPEDT z3A&sZUr4xDLp#z!;C%(i0_-eLrz+TDFqE4WZyR72$gwJsMuj#ZZ&LoGn#9?u9QDO7 zPh~DNZLgkj;Q}^t169v@PM~NR6CILBF_QOJCNijc2=h#gm=Rln7nh)#;FZ3myaQyn z40hc!+KZp>q|ZbRp*lAV=#7vzMvOchcf%$4Hh>4WopDh{=60~_m}S7sJU`u~4b#OB z$Hbm$FRXaP>sS6cBcK&$E?JNs&T5%BSx02puCsyCG<>CX@fyb_+G-hMa&8G&KDMP& zz`6!D``Da{yI2SJ*Hs79j%t2Ot2F9m%=G&!xqtYqG=U67>uG&A_Vt zM!UE_{v5~}_yxKGLJLJ4$=zn!!P`G5UvXfOo9zoatATd>P?*Vk)Y8E>yvn=XL^tEH zEe-dS%)a?*9-eA~uyPAc;Q<~il3x&ZoQ3!>6lMV4dPXQ}VE*cN!4|MbTDlFd8AGLw zcG8%|MTh*tYVSg8heOCei)I&LtrsJ1KlQn*?(N!|G?u)+;D@0X{3EH>wppop>z~J=PZOezF|qb!KA$o0j7#=97%AR9Sj(9H=>8Z?|>gr-2Z`vnFv$y)0cqXVE52QWqDyW)^jD6FP={U@i`;*Wr-~Jd49T##aF&u_!{36 zeB0FldEfnWsjck~Hot5H!|h*|H^4WZ(7^xZ$Q+%hv#vM&UYBSIz0nu*IN4<`x6ZQ^ z60DSVENI=ea(QS09guJI#~pqgvkcr+D6oF4BzHvDhNyi0w6CR7gsS`JfdhrA67hYi z-n9|3p$ev)_6K;%mhDj)vc|$jM(O&Dn#JSOLfXo4_dW5xTREroJq&s1>8Va~;hzok zymlR5S+cajClrpe=92kRhcAzQ<1bk}ZAlo#+dehyVEo>QJgk}&tawNvA0W^og}FcH zV(>h1jMeiEP+;piIMA!$qBFgo9Tl!f>?Coa+i|#b)XJ2Fr~lGFP~9Zqaq<`h2bRyf zlrLV7Cdt`huetC=I+5=* zurU5dT~>UBo8l+Qs6xN=_-9n>;jhuk4l4AE01>3*n4VDiGJevHqjQbv&_dM4qokru zo;TQv5-z{GARqC$KxZ^gCVf1}dSZ_y5quY#ifWjP&X|K2Up$*qu3R8oA#o{&VqN<% z#+55QlpjqO)$TimNWf#R%jh4C6f`f8MZJRbC2Z1KKC`NpyG&I1lg8?Q`!Z4IOLCBG zxn^mn|NA5uw^D@X^qjrJpY>O#~=$$t>W5mcUJ=~WTqA35*oQehg_HxDN zKyJLnN6BLBTS$B=v4FAM>?IyiCwDakF1rI}s3e!!Oof?l832#Z`!4jcf(UpqcJzry z6yAOY<>CB2wL5Yr3KM568zh^qncU8(jvb}pLeirinev~!dAkhAM?>QKw5u~DSvf?k zv6qqXkHOaOy0+ca>~d7-7hSu&E|ZxCj9$H=Z(())8OCjIm#{)0#-#FD4r*Zgcoi{H zHVEP0pv)?9j&R#1h(Jv%*K-xx4!MZq3q8Lv?Bamw*{|O1pGd;k*HlU&2o6AvW~0E5 zp_9l=$r^bP!Qb|I0#=XdS2L$rZUjskcN&a8(5^x8pOcFF7V{b^;2jr9NcL#AmHFLr zT0G_)@&KMBbzV)ot%+a3Fph%)Tz;eLUHh_q-s>~!_^c3l#0nNQTKLQfXA!Py=7qXY zCp^@nj8>hzOdIc&qbCMV92_5d8jHe?1WNT!wJFylGd#9Z)U;0$9ZaTy|=P-8eK1lj$Tc$hySkHj))Rw|D-Lm{2DULTlM2c8bZA%tYC-rn{o8M>S=ewl*&O!$H3H zz&i7;ePd6L9x7%0G$hvcSx|+_B8NVn+lXB1W}QjjM7TPO1$~Z6c%k@M`hup#JjGmd zOcC|aH7C7&V!w(1NGnSKpki!~hZElt{Z4{g-yGeCI=%3?`KI5t6_*{B#7cG9xmo9y zNN#R*buWj+`coW;sqITlgitpL_(ECHO15Jz-?pxy!GR0mmTm=Hfq_n}Klw<71DDQP z=)?SiGFQC*XoUr^ryv)X+iWM!^Tk8KIX3WyQ<6tMfx<}DYe*;9En!SGh=@qWo$VZ5 zQ71ujY}bS-+JxYCt=5Ky8ell5*+q?2_KW7uzGFQ&)`Smr+0eB7XLSKy-Nd#4)+zb^ zs5N4fA`3YARSH|aGCta@q1m|U7nfmtpWW43b~C)t4lT*9e4n~#%5A(;XxA#%%kGXG zz3UV2Yimh@D_XSn&=aEU{Qe$cC7D$hrpt|joKDGXpGs@e>t8l9WwK(LzJn)@FTvPK zQH19is7shod5^z(k6two-0+BHw0h0{P^wZ1)0qX+%$LybdMUO5b1W%rXQ}#eM!2bd zX|){2c<6W{&_?!2YuI?rBZ=GMSL-9z2;%n}F=O8jdU31Hj%OR3MQ|>8Iz>)RB_gBX z8AyJ^a3jt>FsuceOpw^J`yD2~2t-wz4dPSa*(gC0?%}v2fzWR`C?7SYP;?r87d3+a z8k!_?f*va!E<`m{0|r1o+1rA(`~rL#u-ZO<0K6YJJRlnxMoALI1PUk{{#pIojOTKD z|KhfO1cju)n!+h$E$428N!HgLBv!-8G*H1(QDOK_-@CFsXwhXgK7)OkR&H9VXb#U) z(9bJlaqK5>ys%OtL1L|WL=;WxD|>yDQG_Qe zDkAP66+o~9H>cT0XWnYIF?H%UUJ!$t53S2Sjm=_ikj%VoZ0kK{mzjGBu(bK)9Wgov z+kJ(O8eDzF*js;S+4G>%9^(oIx71c0!Gh5A>nq8LyUFK&7pP`B@gkY z*TW&2o%TY1qi+USEDoV*mvdC+rtfwx^bB?O7&NL zDGf4}>Vth(SZ)y5tK@RKJ#!2^x%1$UP?h18etqH(lMUZX$r+RqWL)`^=$AmUOC)1j z>eCFMz^kNTJe6bz8P}4UMqW?vd3g>49z{cJo-nmy-VG-)QiT(eA4l7*V4hqkb{(`z z-QaOzbK5L>nKO`SjHZw!=jbF{;UNB-5_Xk3bVPbVGu$YU91+NN1LZO-HEZctZMtOP zKlh8NPn*(=a4=I}x2@v?b8!?IVl>{__gwD`DlzXzEn;AQdRaojc$y&c=&v}P zZ9QBKjw|;!+6rZjaZn+I!o!Z$2aFbh3DU4fQ59C%F@857S-YbO@03~#dobY(ayrSI z4vod0mML;{;VQXLlFcroi4vLP+@6NpmhF|+RK4|o?n^Z$?O5hWljW*(6NGwHe)`&N z>qmH4_FO}hMmezL1ESu0EClPArQfk*WyzW3kKnz2S`7YV+?*Npor^iM=wk4$9fC8D-Z=L0Yq zZ+1~0_z{XX%|fhlv-(gxW3tWeWk82uYHb6_AY zvj2uW840i2c{x@+&SEwjND<}y5j_kiHAwPXp~`6B_kjJWnUHMnMN*<94%uI8 zUMVSP7{_wsioGY5{8oE13iCsuuSR~U%XrS9COHj#{FpZKy~({xUd2-M?Io}$`tzY_Bz_JKiMIV5+HpXk>2(*GZYYj;iPaWhcL-I& z+Bi-qNz84G6-jLsMQS`x)@e+D>+X|IJjH3Gl^V!aSg}K1nL8@{g>?i2aRc#plR0lO zU9q=mh00~H>L1q&Ue4oWMqm<>N1QeNuDr`Y@)yfN_NLM2LXU-i5Ep7m&vg&R>cz0u ziD+N;c22Hz_+mmt-P(WbEn+39+1T7`pxUPgKe2&Dt0*h0^4EdtxnDe{I>rQ~a4b%f zf-SdGLRN=NY8!7td(9bH4sO{HG3z|o;N=pDZ=ptBC^0ac0mFFus*_>Kmn?Nk;k0=h zeMEK=IoMG;#XYu=G!^M_azT>dgOBNNi=}_W=O_QGZnCfooTu0{VJ#3;+JQE&l3tVF zry@qY<#1j`*mmBU?e3+WZgeO#1UAnKC?@yDT*W^e`RfPgv(=0-wZ5+TbBkr?O+iG3 zR_8{meNXy{w)65DHmW(1z%Gq_Yw38;lr2hXOVrZ30x- zIyQ6n4)n2l)M~dfmVx*KrvW3Amrbi-EVb%!E~BtdBaYZfah;ZpFMudp;O&ja_Fbw%)cK-DRr>s58$mo-jKd{f1wOXjfu22g`?kja?S(Az;TNl~{L^ z^)6cpr#EcLKEf@5-p4$Qp~4M|5=EL0{9wF+g776YY0mPt2mV-*VIDjz>?IZ!!38De#h(-3dXaht~tn+$%Aet_V?ns{C~1mhZWJkuk8tM8%cyT$XL zy+N5RaUOAp9~K!k4taWu97%R>I>bis!~4MdPW!S|n3f|V*4~dEwa*|8V1-+>#woeg z)$+AqmDM$FFN`f~LK8M)nQ-6E#i96wOwLYJcLYxt6E$PI{@{I%Dvn5zg}ojn77EWg zy=9pWAzziwrWmO}HwHQ@Mczdw#QADHRoXNOU#)dXY>k|t98=t-7+6E%4!cadL?NH5 z(59VD_%tSohk?YRTdrlFM7LeBd1&UO^!19EW~IBJ4!2;n>$FuOeRA4^Ajj~NRFAQm zD&qjN%&muKo#_c5VzUsgdv)TyG3rI}X}#>i`=aXo^uO-DtaW&+P>RlqkXz6*PkOxE z_*Rw~f$I^MMnoA*{+1h;B+cdth3-QmiWEE&#CUc2)Kn9TOdBqRr$@b?;3!v{>9v^< z>SNqX*F4@k|5Uu4IU_GCwr<+*&Aud}KD8N3e?83>1Ur;Azq!Bcgp)+SYo zdky>=Z+H+{Kaf*WRwkSU>A=kM6$r^g?8)F7WoMvXTjx7#*#^z$<^dyhtK*_aGmEi**GenBQZ9VTmRL11ZHA~J918NSg589VIS?1Sj`$(p zG$1&T@{?%4TU)mr-^?HzWY6tQ5hY1|AYvCjPI{p|mP~bm>ElU1clwgHXVRd^sygO2 zj(3=uIg%UgPgtQpq}D4(#wij?sTwee6R`^Wh1D@VidjKQn?+`h()X+cE@Cd9ro9^6 zJmJf^(>TzZ`7RiJw=J2V6#vB)_R6D7s!K#kt&lFDrZF&QQO4Oufa!v3l~RC;I3j7=$NH~~T4^Z*1z0yAW z8zqX+%B`9;mu3ADr}8m2MHlo;Gh*!l@&}+)dVMHTu&nTUCCFT?Jp;yces+du~&*ni-dB zY?&)Djw)e)2v_w!Qc2n+95#cN5?!+F)LR}O{GMGmMxJo=%l2C^u)Is_%b$E7N~cLS z{>o5SeEs=(wk(F>_=YytmldjRLVQ+pn|Ecv@Gt$R+trXDGSJ?mC>fpw@$HrMsVv$D z2I+QdET1-W0&aoy6e9+<^=wqK9ObUjj+%7QOW(htV#M_CnEONL0`-ts`<)Z(b#3j< zHgSP+hSfg@pwDETH_R{A)+lu1FyI#50hym$0zcW@e_lmY5&io^0O4Hd`oAvhx><y--4$k^(+4Yf;9BR#n-2)A`oQw6wyUb(-S=N?Zu_%e^OACSe*60Vy~2N_ioM2=rS zBX(&iE@UEfM%C2(pONX@q<==k_qd=e*Y-A>&KUtY&N>md(NF7u85-SEEW0A4J^5}B zZ`J-!JMgW&s@q}`vLzpPDEZHu9&Fe)D@+4^n-=lKH4h{c|FhO7?vqMuVEQ~O768>@ zcz1;`9)p}|oT(=TL)HJ~b)PrS8r~9exf8C_?Y^B^fBa0(v+WIC{>_0CJ^j;IPk2O< z3k}Q|8qqS3smQSW5jJz)@^Z1`<9cDKHwADm*N$sBc9Z7!znZBZv`@dv; zd;{tGnhPLWB6I_vn>H7J{Wk+|Zgl)-z5dHMCyf4wm2~V9_Mi~jb8qKq4JsOJ>E?ng zhmF{By!U=3wnCX&v1g!nK~G%;_}Pk1HS0f4$;Sa60>7QENb_%(#e>m_IVUbB_{ zonZ1F0VLEV>_O`^#Ksn0^g-pkzg(1cItP;Ay^E`ELAhR9LW{#u;l*=dk6)@A-@K;X z@u560DnL>DwF^tV9#iwWp33}l@_AHmHe-TlN~J# z|Hu4C-iwV#WE)QfOKTH_ugOhBvXUPq=_}I2W`2EP%s~v7IdY#Qx>)4Xu{C*H^ebsQ z*`eiQ&U8=#hP}6!R!q%`$V(E;76Rh+deUw1UlZ{kC$#PHbmPkftEA3HD~FzxF3zaS z!1f~f+q5#h?j0ebz2Y(iuEFNInAET`?p(W!EJ<(^R#tkjtnKo4t#C`}77eH94Pq0d z0l7*uDJ^gNXrBWY&*p7&ZgKmYqoYBaPcTU~n|9)H*`Fu)^fTn|OjqwP`^cZu+K~tm zO!M5t-fs2ZCy@%BwxA$?NN-x;!Je?#t!m+_Ki4_CWwrx*P*TZHWPWWD^jf!~q`dk4 z&P1_;U4Oy>OWxZ1e^$cDcc(%tPzrnA5$+ke9VxhyL8VP2WT8yvNud%~08_;FcNIgN zDTYUH|Cgz!7f+bW0u$svRZcd^9bMKW-(r?+NUZ|sgNQv#)iQ{K*4R(BZ5MTp|Hnr| zXzZW6{ybwQ?jmpq`pv0}oHGr9DvHHS(mmoqKAG};i{VYr{Z1F)!RVE8`a_l;Ab z|F+Tu$M~N=+f{xQ{*Nd4Z-XMNfqm@){N4wf@(|^}X9|wtZvEdIM^H7AMI?##p#m&f3t4qHdH&5~~J>_|3S?Ikw>2cA|=+g|V#?*#%xuarb}L&~Efo zarKCKcIrjen2l3M4Wf2VMs;))M`!h)KstX{1%rUHRBUQ4wol&2jM-VB-C6=0D5Q6U z@`9A1-^2={GZ#3b+hgh1au~C_5vIFVd>E;z{|*x=3l^693g+_J@qqpLicVSZkRc1&v8^C$C8){ivYJP zagUt+KUqZVS|d7Au;Qa3_2j_0qHB>Um5wr8j}TjERfu(OlKuBUrkxcSb@cB1!yj>z zZieswKBb#3(4fA;^m<;lqr`4Z&ds)e0f|=m-$SlY@vAigSs8mYgxmFh`mEXat@QuL z0CyjG)-ZkVgG2Q1M;rSeqT5*oq%8_${;MZi|C^pLW0>-i16HR{{HI|miE@9wlaC< zWN$;7kZB$3iSqozBQ@*6>qtdk6p2^k(%Ay?3?6khv%JivgpXJ{Hkwyi?IedV_%?rf z-DrOP0VOQ!M364D#PfWw;R%b5WL@>j!)MP9xvb_4Y;H?pGg7m;unzs3Yf?I}^@^Ql z5QKm)>oM~)f~B^VPqKPj@X(Iv+NcDwMZubP2l48=iWWXgRe**_+f5cH=%27I)bqei z8^0|}OaK?m5W`=S;PTA}cZIW(UK%Lj9PZfPFtZTNp%*oT38q4{sJ)?Pf-{TQsaRKu|G8s~8`tbVaay+9|k zpy&&Hu^~IK@4n*pt``94h9SP-UI=s;(jJbZ_WLW}n81Gyrn}K+eCkIVdV&`n0IAy; z5vOxrBJhHkLD#!P-xE{lb|M1XTHC&}@kM4^d}qlC5xbpvsprO3DJG-G5GvBn4g7Jl zBhu-czY8MvS#0Smu9f>$Fmf5^XC0)*p`9s_nD=Zr5ap5aE7J%=GAdaiJ%xNIm2c6% zNmN~5FO75e4=;U|JQfpo7(Dj-QSMqm##iDbU`8~ARV}5im?yle3 zQ-?39D(1ia0OscIcriLq9BAeVU@@Sx{oRW|lmh1Iwp#MbF!w2&XV)QG&-K)6AUaUX zAMN^Vh*=Vb2x69;0KXG9kMX9!9KJ#JY{rh0<@*>#N?SC|mc3$?Y*RPW){{2<@xxer z_Q?}+;aq)%q(!#=%_6@KC#Q+ub|V7+x+6e30*1$An3HP_E7owj7aaM2LXVC-{O5t% z4Y+Rf3#8XOmAw|c@N)SZOqr}D-=%BoJIFpEpG=wxa`V6HqQzHs+iKkGO({QX2M8OkYefXqBW=fq2RUz?#^g0oST=s$ z{zc#c$#Rk_RTqwerVQ{H;PBPpiY}u|QI8c=TIWz4wn%R%b#e&h!voDU#pHQ7`4r$8 z+l}X!an6c;$IlL;k~E^PJ1m`9@hQ`_+glSBNjurZOHE1U8&%&%Z}Pi)DE^l>Vy&XZ6e7ogJ%~-S{4-<>bg+0$zg@L)hD=$i+h9Galk2 zep>SCDCEt(vAK3H1t@7XYl5F($DMf*V;&AUC35HB@w{Y6U4lg-uoIDL-L04(=E93 zqd>g1*Srm`Ap8WXEI~EKb2Z4r_+R~AlfrtCx`n0A3AOJBU zb4u#st!;(d(YXv4M_k)KoTLx>51WhtIr zQnn0r9*Ro{@BKKL7HQ98*YP$akjyJ0-=2Cz5yLxIj*JMLqk1As?efCw7Z7y5q;~Hi zk>6v#qYB(BfRLR?nYX$JJmq*FC#KrQ(?hFusjpO$J8{OoTdam^ z#dW_w$iz^iZU+oV@=1-qla%eDA#NWU=GKe#;!yAQdvt@yxDKWy3PZMcKR0*oy9*{C zWGB?zUziInIBdJO1sDJ|HkhkPd?w0X67-Wwsa~$<;eJI6AcdpW4B`Fcjd&D0%pK~8 zwULDhe7cc(%jP<9S<=HZl1IAC26rq%Hosz^3z~;JQ0P=MCf`h8%xb1*b8DnYib0y* zPBWaxke_|K(6;$qlKSS8QT59>mD6KJvON`@_Qh$uiKX$4Ug*`qkegxYNiKd2eE9h_ zL)j%v+)gOltT8b^iu~&(2zd9wp>%`WqYz)wS%BD{jX@rR4I)vfhbQ;z<3L+uyh!_2 zH(dDCyN%9kf`3X2`cBwU*Q0VqVX}P^0k5^q+gNBb{vs=NIfOp?#kgrpWNty-G}e5eA=8>AfRu!q@w?wl;*)T8w?^Bl4Rs|I+cdb9E%{Om}Bg~$|T z^sH~m)n!3lbIto_CXaszg0}PV0~5Z6a>hH8d6&w;#gOHv@#mu(VDG|Dj3Nw~mg{|x&X_JXOQV3JF*gr^}eGK()zhv2DG`4Pa=sQJLl|Go(n)=V2So6-Z zleKf5R0pn4)`Tnmx@^!ZVY1kVO~_Te(N8a)R*%Ix{JPuuc=bu4GVV$^?iEz3#KcnGS;g%f&#mEiG*yNAZGLSoRfs1qhz|7K1Z+_~;=qAa{mLayMta|vl zLww)p#LoAIedzYg{ZLx*V^#K5U0GewZ}ZJZ&HyXq9fj@U#`+bE@{yg&#f3(XH*O>d z!OkA^f~e6KH=&IqB(Mw1YOcV2u*tGHOICn$Z=0TeO6k!VJOlf8L!*%sES;Lc1sz0y z>+aLj>>s{xJQ(sDy##svOul4FPZ@MU#=m)BWqE!YAPz*}s6iI@_eI}RlK)Diy@GLD zy{ZgMXOmPUV00cTP1Vi_;IfPhj!yZ&T~8eOcduAay9;55{P|~ zNk|Fz;xo_Sr;zgN1kzZ0Uw;CTWm4+0YU+d}o>}hweJNx2!IS*$-$4FxxIz5TqA}7w ztTi-3;YL1n2;FMc@MFkOU#FQ9mR|D5-*Z^t*Nh_MAs=`OT#~170{zKfA#>?>_Uj&Z zg)cC6#$Klol>!Nygc;>%YIt4!CWG=0mBaSg6E7bV2vF4C8Udz2Mh=F$W_kj{IE6(0 zdN#xUXP9xRbQ0iGkgNhSYu4dW6KKnHF^;UDGwM!4Q6qyk80UGP>_4~rL{zd52xRe9 zTN(K~lLxKm%L@l0LDoR6z^)9b$`$C{-J4QpGqqsmClf$n=+EgtwXp3iphywVIA-44na*sA1^^!K$ zdIDdRw7dn*AiAa_isP*VJ>Gg&5pR`m1*qZRx~o1i%XHISVdbZ^X@|XDqudqV#b~I6 z^0IW%QpIE8A{;&9-_U@Tl^8)E_8Ig^(Je_QKDu653yHQNaX(3s=X6K^*1VbP#NWA3 zrGy!wMCb&QMaEvPW(DBDX=gLDf*NTJh7qaYeSfbDxPZy2ae@%2ni%}e_n`+;f-_;O)TKKWshCth)n8@#n(<7ZNyGYXMSO5RB=6WbkjWT;O6 z&^~_gCElrFNm{68v3m785f#Px@>PTDAskPp@|ZpU-nRY82$-%7Q-&Y{OYw&{(owdf z3mWHs;(mR;c7zRR{SB6x1f$23AqP%?hYPMC_B~ZSWV#$ZRRohZXt`Ifun!?E6{mD@ z2`_(QVjIDcp;2)KNg5RF1A8tXHiP@nFd-0qy7@T)WD)0g5+gvnf(F$Ol+r%%%+;wT z9ahAYO%pJ_WgB4h@$*(}kT{UbyLhk&rQJLHM8Z}$8@a%ahE3m-c5%NtcK;3jkP0E| z%_ovC1x~&3l6*2m^(56cT^*taRO`dT6cnEwzW=4V)k!hVA#{hKTZNyJN1!aGrRB#f z39SpEx^kYTo&=v>Q@*tpZ_}UW+MPjM4(l?PE_-oK%EGtP4r*a<(#({Enzw9ijyaiC0wA zIhe4^9_7Teihw14Xo;^p9GB!S&mQvm!Q)qf{F0Hj5QKn(QEH{)oSMi__Dc9~9jG!# zZ!er*(^A7Mo*zPjDTcHu*;2c3Ox;Vp)X2-}jOOgzAFEW|5JNosX_?;Qh#fN4zs32t z7iMXzf#eWvxMEQFGDvMBGK0g%!@ABE5J@^>igc#(-d9h3SFV+>tOuTk2hIlw6p~sS zt+y;5ut-lx!gjji+b0ZWIaW_cA$(tO)VNuj!DXh&O9sy2ULop1TCQ!eGKqy!>mI=v zQUT`r*Om;RU3?DAgifbx z!9`CPLNq3T*O~nL;jR;ao=jCm!qj8X5v{ZI9>k=;^WJ^*Cj!8!fu+lLzXnf&o6K^C za2fTr@S7U^HTy9l*NR0Siy9^z7?(n}d(F({0CDpIgbN?7J^2Il=@?AUEDpWaWFtCW z6gciLx7e`W^pQ}MG38e7*+67_S%UXzFUYwV08PMBzPe9kBTG*+15+r|sL(p*F6%V{ z$>TZX3F?F!OP;-BY(XvTpd9>XjoWd$98&zWE_P_R5+?TwPauViOKXQP;yusVt3DmN ztXctBdlT!UmCBv>C1Ei#^L&nNn0E}YKVZ*s`+ci>by4T+gb&4~O6=n6yFJ(+h#h2N z2B;9XeKt!_p!ow6jyGLlox{IB2WA7hhHw#r-+v?7r~L+{Xvkf0c*=B0qz2k*7dTq_xQJ(BRLH(g3u+Zn zxG5_38dVtEKj(Irfmlp9CPb}c!v5QJ$JrHy7G)qh}?n4$E-E3wnZMOQn!aq@5x~jjtQT#6PL9ytbPW0|# z((KJi{tW@lKRMi6Y;F(lpqF>>75+nH#NC&Z)AXNObUsAWkUZdNjgxwzqM$wfM+@^b zjDnO)Emp`~x2%gZ_Z9=8zmGG7ztBh#z+RDpl@G4tp^L6dPdjYjTnXaU%Qy|GfqrCoqmYrVzc{lDv~R3Z9@*KvBmv>P)|jBe15_lMtl;dB~` zYuXqQZ3Ky3C&X)<%oz#G(L&$^9*ZZ3&1;$XB$ivK@)o~1Oiko|?D?kf4^WGSoQyO) zc9HbP>l^U3AH;yu!wPaM6x@?}bm+6MtqzUvnF7X^1B@^8!|vC^I|jd%t8Cv*|0tJ_ zEo!{~F}IX3di~&c-zQad_94S<=`x=>49XQLxj}Zm-8AVkWgQbkeHtv?O?-j(xvNsTX)m1>8Ab2 znTC+K-M>S8{y&WXynh^?VNz5_rE2_uj9?u984Dy2$iQHKSHa|F@Xl@9Zl?4bl_CMiGqsTjH)9&EwcgsG5%(oYq zAaXs$hy8d#S&QZ!!xHUc+52?d0s9Mx-X|$uccqW2xJsN?JfyyoCixVfYOXpwTVAtG z<_RLt4Jp$-rj%#Z#v} z9q)-w-xmg?8V)H@J>FVLw39{j&IygrQd~FI;|V_?YM0YqzgLz^zpY_F3i^E0#Bt_f zM56=brOE`py6*O1$7?>G;t*Qp8$$ITzCBZ1I+O9?4>v5f(x=$Kn-i zXaUh-8K}*N#XEgenmwnyctS0ay+I!zlv%WkVNGZH~cClwhXdzo)&?2gv z@M1|&IN`Oe<-(z6d=-R_O~1ZPy=HPESl+pzi(P^ML^hxno*u35s*h9uI~TxD z3pqrJ9NAz;axLKj&gUQh4ee{0RfMr^3RT)ME$UWV2y_$=(vT`tz(F^(`p3q9rG^-d zcv(nC?SJFl{Ha~$`u}c!-pay^tl_04VO~qs|689@{-<`fMRm}`}M(q9nu=k#EQ9aGVARtjP2nYxxl7ozaj4)(Ga!`T@0wM?~ zIfnyC&XOf7NtB!f2}6z|l5@^UG7KfE_dkZ4r*+?k_=s5rpVsj^F%*2fY66*=ihJiuA>* zd*j`wMl6tF0)-)V5;bNv|I?)9{i~tKW!c}+^f}+yP>+pa{&rfBwTtLw8q@+}5UC5C z61Q%Cu#|kYb~LQ$-6P8#nQKH^8>ZpHa`$VP4X()1w<@}=+z~#su4BjS{>lyu zy{e}nWroJDaU4kZ&zL{m_rQbEnMLmCxf&xQh8Z7f>E7d0`+%bVxYyWS;Ws^-qN|oB zM!i+=QjShDzQ^)0I!dKxb4=@FkMlDvj(fP4crBSrD(jAao)6pfIIt#sXDQEc2p7W* z(VX~oV7bhvE}VE1*Sc?EGh05cO%AIEhhM&WINoJrO&}G0rKC%qw8eB~yIWR)EWoIf zOQ;8aZxQ?hIr`&J1~q>(ZNK&+?q-RK1>u>P*9j?dAG@A}omM3#JHF$iYMtgs>g|QF zl$35kX<*qFv_1+BYAiBS5yGpfyeM{Z8w-!JK5-vs&z}Lb+|7JjEDWF1z``vc4YbnO z1AOv^q7cO!F21jjf7{!i{ej*!6BMeTjI9ZO0xrv@@O9H%2ODuyzppEO-F)-qQ_+u-0F#F&Xik5 zdPW;Hy&Ib9m@BfBX7P!L(5i(=fd4AxBlq*Z>9k}K<|}7aXTXT*A1=H`-xrmJ>KILZ z%>i-tETk7)-qX+hB(Y=%%_gnZL;A6`v`s7L^wyTV4pznt7g8DRzEVWM6nMmX3<$ z)Mjzl4lrRt?g^b|uY>7!a#&xhmlw2`4sxr%wa$^+gGObXCDqC48;g@8f5g1BfPys& zzJVig(%*78zMs|h@x&i`{^j8@4di5{*uU%J^Jp(HzYrO zFYUpRnL}l7@8^@|C)P8KDcb{ByTq)d(RxQ6S~!7zx6JxL>2%qUN9@=v_PLRzWsi>3 z>?7#VZ`M~gG1OSoFkk>P=#n6m$kp$R&6mymQWtFF%88y`!^ys;4#`_8_zGdlW}>bN zZc^4~eYsaEdU!j8vt0a_w^^sfob|JtKy?izWxD+@Pg>D^;j`>?tRZ4q*r?JYytiVHP<9pZXP;4{T{B=?=Vdt1MHY{ISKLq4S2 zuG2~4^J@xy6oKC>p2XJEF0n_(sYCQt<<_@dPn9s2N}b9TozDuEsRF|CA4TL?KJt8y zIm2cNtXbXE3+dN+sHgM&#to9M8EHoi(oY5?1$U|=dW{CP3icF+GIKJW*|X=Ai-L7> zOF7#uORT=+(HpDBf8MdCOgA;rrNPm#tiz(^tXZ^)zwtuZdlG$=7LVh=*KS$F$X7(5 zpOCjHG2OnNGLeYyugfT?I-sR;w=RuCabk#71ld@?fs@haU}zKa#HMwOgZIZjWC?TP zF8)utNK3g?hFq&d2jFGABshf+jFZzo#Tz*Yt3;IMO4<2&s;l6LB`sBsk|m7>epAtL zVc9b~?zeq{*HT25lK=YutE3*1%pHOxFPf>>szT-mfu6aw`|=s>2gjZw32l=4UMPGp zRcy*2Opi^ijl?JKj27io^pK?h)_$$qkyQRGX}Vj~5X zy`|x!TPX?8?nh(l$E&z1OYi7CHT?fIEB{|4pc$f$*jjvTq}SfAC^S41cXbDKHOJ;o z3&Rsk63|EZ%{D3zHY!(L)6~YAjv~LZCnQ^Q+pdo2Jh_`%`eNm^GOJA&asXZR5vVjh zO4h2SZ=J6gy|ZminR0i~QTz>ELjG%>5v4Exy|VsIC6Ee|iUq`;AGea;rRi?V`dM`I z4|qvCk%XUm;E$-IChwmnjTSeTr92uY7{4==%_u@n8v54YIKZ)U~P{bidJKt2Y z^79mK%+Iav@vlx~+i33G+I|%w*FvD&SZIw+1y<^Qt}bb)T-yA1kLn~Gtw#RcHW${x zky&7hR!OqFSzCXfi!NB^A$X5Pv8k>r?U3Ou`}4T1{6?i375f2{?RpII(g|F-i^D0m zkfRxr`&FEOnAy6LQ>j6i)cK9{>pwwI>UN+Zw@ zsZ>*w+^H{8!spo^y`eWJ3!A3o+R>HukiPd_*VW%qLaR13BzOZDWIgtU{gB|SQxMLt zzbgBSNWSgm0_!PKD_82ytE+EiP+ga|D73YAsjCaU9xTOlfp5~)uiU-wAsa<7FyWW& zp#{*sHl*3vn>g8ZkQhKl|xSwSvcICsWqG;E%Y-CQrUbdV=dha8y4(ApQqq0(PW5zv|o?gX_ z1Byh0)@Za6BoxyH=HOR{&HCphj!vhYO`IUM?idzS-apowlQYbu8X;S^?zrXO+b&$h*mVqz!8wjrCT9t%VJcidAfdp(Bnd_$3 zKL;?HM*R`tTH$oFvryU<>}_s6BuipVjkO)TuDenU9A~?Hx9vjMuvX;WWB%Y29}?6* zP}n$fQ@rf|=r?K|v?yU0z0J#6Q(6FhbiRT;djJ$)(eEI(xtqX-htSpo=^mNApP7l~5pT)Y+7ISLlOLR2yeV>E~SU)~x(mDNKX&Cc{q(7~6GVf8^!(r&TJ zG8cF9Lw7Hg;csa&XkEz*Eo=5F}kY1rA>NW5UgvhVzXiuKI z8&4erJ1(tYyeyB&9YKQP&W|E#7n+TGIxG*!dHMOcji|IE`fIV+)2=it6JLX{8SISK zu;R@r?mFu#$NSHQ5)(*hj+`JyAKN@FWtCS^F?3glW=@d3I%%N(+hFp}tM~$FYceG@ z-U+tM617vj1xRiS%ys4E6*n+WK{n)H)-Ge`th|N(P7kS-ip=CsUgW#*huToI&$!f# zk}gyl%s7P&8##~sJq;jsg0T|#6G*$D^uAX28np7VUIzxyqDFFsJBX$Xh-{TZ)%mvH z;+yOC2v4;~IA$1J6()^DyHb4oE`h+Y=S#Q*PF=Ll;AtNp0pUggRv5^~q~74NNhzzBILk zsY9x^VWL@()&5&=&i>Nla%cPVpVkGTT#6z^49zM&v~s2By!g)sEkB1 zdJu9d{v62xJhC*mBR;IkOXK%2XcOB}yWKX#GgsD-=D4`cU(HT2K;8T4M!dY?9q-4# z;zrs({;3z;@f`O$GilhK|MT4S+qqngRQV zS1=q~fhuy^8HJhg)*+JAl)XWk614?jYM#VVFE)1_D%ZWnnMXzQEl1yVe;4zN3v8kJ`4|8sS9!h!cI^*d^&f5=I;ms4xFpd{yBgHZTm` zx*poKM$o`_bxj~s@)umysHF%^>A(lApl{yN6nHNY>VG5V2oaDVzmmhzux;)K%CC-3 zLdNeP0#3Q_rKYr(orgdAL0tJMcv0}CktKv}AunlE{mlr#N&c1Dm3@SW ziL5I4gN&nG1LmarpkV>Rn?EQ?5{fPg&mawg!jOK_<0k`1|NNPlD+VkTZ=i9=EubBn z8te?weOYe|{!EB&#>F97xJ8Y+9mc`naW-s1NZGa<;c^m^+NQ~R*-d$u^<&J}Zd9Ub z61yHG?)mA(t5e&&)qIA&rx4DQoEspA%Hg0{OZ{$HJ!fE`?gi|;gq-SSJiA~DL?6J6-p4d2s7Mkz8hWwv)<~W$=g5*9~ zQ_{IMm-|=n7h(E`UPHi>Ck&H1Q>uR`#T{Ar^uUQY9*Eh6*eMZWV|^!K2}DZgULeG& zgGl`dRMvnX(hoQss$xlyuv#A!&lG)Y4G34hFr8EyK&U!LjxU%AX9|daTF-tlfHb=9 z0Ue^bY4jH$G(bF&i3w$HC3E4;Aji+G#G_7|8uGmd8 zuyn2gKdv0i?ffwErkptg;N?Gaa5kMSD$dfNeazy>F;usrolx_Zz|-RmeRp%Ouf(JAFFK5++! zWU)d_5xr)801qB~^7uN0|DuiefL80-7Zg$6-|yU1A8ig3(;ZF&rOHq#IjUlGP!BbA zrwmqBb@3lhnOa)|B%E6zBxrxn z@2b5Dukm*%h9+*28lxM-(Gx^=`mw^}2#b9eE-UJ<7=@omH!TT{U4Gx;=l#G}Ri`&W zD*N{{Dm#Zc=Z+Fy-*q}DAQ2}Zbrt`P?%gaW+ESD94LXPh+iQ!ajNzwcSRBpmPGlvr zBlwkqT8&4ay4xCox5-5|c4XL9C4T4g&BrO{NaeHOHI1K37nF31C8EQhZ(hbAiS~eT zPjFP4%95r0O7@s_3XK{nJ?ApG-?9yn9o#KCU?A2=@1KD=2!go5m53bwT(stesa4x@ zJsLjHZgxLD5em+C88o~q3sQ8t^H0|W|8%|ZA566_J>!+Ty_U!vQl(PjSrUO zezB?v{j5F5teAJnz%hC9vAwU-IxFp9J{VrG8X6 zzt*^y=#11-XkJEJ6Y$#G`~r#7{XXCM0!bKt`~#h>7TeM@$+)ZsYR0)h6FdrtPM-h+ zu)CF-m4q*14Pd(S>)R3H+S6BdWR83g`{O=n6f`yN(Fl6;;By*qi)m@d|GHV|G36vF zb1e>ZF{A1MI$vO7YeEk1)GZ!!zqrOnuC>(WaId2XU3ME=3K7&d&WR4nyr-^&UEH6j zS;@apxorZT1Y^KRm~%ZEl6lG~CZAyg(sBqxV`y%{SKMtvjM@VLMf8ESOt99mrhG?z zbsO4ZG82RDHo}`H7A%Lvy|(`JuaA{4j)hJH=Y2X;O}*#Wb@~7M$G^>k>e@e#fKcyrZWDJ~_A8h%E5&Xw znmT1cNY^;?UTMYT{Pv&z1+(Nc^*(cp+0;)VEEXY!CEm}l+?M=rZvWfd{tqb)_SlHo zOW*Za9#1Gq-gkWT6+^*F`>hr+FDG!Oe7F5c*#&y*58q%qdib*b6vi;>JT2@Uf89tR zya?s>d0Hpch%rIuzkmE&JP7WTbZ<7Zj4gOxYrlN;X_lu12_4!mwhxLgwM`2BD%|6C zrf%=|{u!Hs`pqr+pf8d*O|0hIQNia{;~Q%$F9n$^@q_!S>AN^0i|X&Q4=24L7pfq+ zTU4lUzb3!@k`n(q^nr$+*0U>W8RkeWW(h=dzp&Pk>mBLf3|<5JAgX{PWUh*VTGzwZ ziO^jrojdbaf>LT0$Mx0@o=DZ}Z@jZ4xeV2kx}zTJ7ciZPjAl5|)f(62Yta=~-S0L3 z`slSD)SgbWwJp>tQ~6>U#}HUDgMk$lhO|VjBOyl>v%|8fKg8jk z`17gSXZmL;nHn1^>}r}c!7>l}mgC!A!koIXV?Roz-s;n9FCnV^VjO%||1IyUH-jt* z0tI~*O4v&w_%UV^9bDCUSu~wN`E6|oDjqO4u{^a0J7^3wL%>7stH}E+Q(AGk^0@K0 z-3~E>Tv>=Ak95AY-(O~Q18bKndMH|QE=}sr`>Hn=0iq+|2^LU+@MtzTMVwyD=9-gqwmNxpffGXU;xpO1$+f2%VEM0 zF40A4kje!lvVlwIS(yg;D=n+ia*m?8Ic&g`u~%Kil91%rawHnvT~v1o5(#uwT!N&& zryH7cH}X!Gk#RhreLVDQA`S3=e=}JzKM6w;UWu$koHI?Ck7oi+`A3KrS^B>pAZnVw zVq7=TL$3>3ai1?R(J7<#=b&4#sebqF*GrRxOJWkTo0ayzGMFs{%C@jK)E0}CDP%-;D)aJ*k*`N>6$Xi&!dKgh8Ef<~*J@?n z2lP|CUV?kkLo}Khw>-CQ@J7l`nJVX@HID_j>g=i_$bR}CF)$nPs`5hY9(_| zEI%$f{k7!oWxTw0EoCmF4;n|WoH%Iml`ZY|%#Z2P57sMOEW9@4BJMpxEUM+Swpd!} zTx3_F2j6Ey_)a^!z%yU4IuE|zklhbHq>rBBsx#gxI|5!lE)V!i@)2Nlf$*dYp6jB| zH~u^hi#EgpfQ4vEJFdx=7R&E>M~F2bgY}Qfns5foRD)OFvUmy)G$YWD&t?b`WsnHn ztlL$aE`ADA@9!NaSp zA_8n8$jF5e1_R1f2Mo#)z?_B+NX_2|B|-!YKf3MiB-lU+ap8vJI(9}|4^_|kvkZ>y zyNh#I->|~}TC2oja0!djHVAbLLk6yGAd;KcL94Y5&9nGL!7kG??z1=R4Mrdx7>uOi zxgw&m1eWFB2gX_Z9n2a?ja`oTZ}O|Yr2RXLKjWj?M?$d^=#k=*anqpB4-3$m4!P(u zT*of7g*Uxj?4rt|a;2%EE7T6_BADGKj6TFos8Q1o&T`0UpHEj@PQOUCtT`QK?Z4!_ znBbl2_kG+>-MdGCO#Xd!9ypY8hj<90(zke`S&v?2*v?TqU5KN8rLO;k2i*y1|3p63 zxj*~`m9iLC_QWFM_*;d*E=6h*CJC$HW(4H_)S~S@XmE9oH3txxq_>p^knF5AV5eFd zMaf|+9ao|8+6xzqnN~mOf5~-*m=`uWzM$0Kc*B*s$(=pPT*iuFFUUn@58cxvtIb=& z85ue{No@EEmVBi46*9#{Mv`GwuqjuN-A`;aO&qn0Y$Zy^cJ9WQC}W#F0FUpVZjqU! zCtNk4^`9WQ62uRfYoL&i+e2viB6iTrV-|@*cfUZ0`5s~@34@rv?IK7029Px%4&X6* z$-bm@zL0Kd9Z_;>bu$8|=+vqNA;};U^8*rI4(QZBW~b1aj2qT{H-Lyy--FClGDSb@ z4Is=U@m?t%Q_kWe(G*lK(J=w*u!7XN7HBy4(JH0^^|h(D*%{8tXGq%U{*tb>YJ}FO zxlgV~RfPA7M2K2b$=j(k5yDmJ zgWSqy@;|^k!s+u9Jm_Kw#qOvM5%+^ZBVkrku)1ZAkHMHJEzw%&Qzq7r#eDB=^Us3= zOP|^A76=Pwp-Gckq(x+?VMxg@V&Df?v`O>VE=s1PX zxh%&jx#9=dTlrnjECURYOn`PbQ5|PSH<=z&xd56#>rnG?9EVsEMwmxJWDR&sj%RLw zuPhA# z;=4y_H#rJ+i--DBacnG5OKa1;vcLh^$c-a)t0tCBr?MSeC=WuSDmG7R5YfrC7Sz$H z7Nv(okMf~kk%TI_8iU96O&7YcTpET+X;3)x{hb!v)GUpnzg`LIJalYa&YQ&>%>?Fy z{E)mgahMtPO;;cP^nWNA`-g&R`!lPC^oLoH){@9YX)}b&ox!k!0PwsUqtl>kq@nCn zH*OzwR3h5t)(PqYC8dhSvFg7w#P=8(UHYoD6kF^MVmLDf?E_$o>KA~&T>4hXwU==j z1wlv98l)I^1jz*|1?r-ng-H$4+JYqhcQjn}Hys;15NM*k3)6crId{<^B zb!u?shf*>&1b~luY z^h(i`i?+%aFvr{voaGf_RSsV-D0zr^aYpIG!wwuWZj12S#TBGk0u=fg{a^Hq-jrGr0 z>~oldF8c>C5h}SL(sMvYRHe4*NldYI#($g~jMgbKzJRq%#GImIOG3$>o6>#a#bFr) z#^<5pLv*j`yZiK;btjbfn66Xds7e9X1pE>)q$D9bQ%LOy4pl#4v=Gx>kl^}X2jgGs zLH8KG!IWhK?ir-&9hZ$$y{#nk5%?vLQQD2s|MRg0Fnx4?6N`KjYIHgGKGW;Pk*G!3 z-q`)zpv+YDG5&SOL1*SZHsW95vgbC;y z^u5brfS7Lhm!Q6@WjX5*YLI_eyRJG#ezI)(9Uul;Jr&DK$Oq_!N%lZ4_7RC z2GgDX{FKV)g~7nzVT1jv;@p;tqf~~a<%x4La8Q^B=lP-i$447^WPd^Fk}H`vJCTG0 zFZsc{2^$%S0lM<9>f3bOt~H@1a&YXPFD_(Cy4Q7kW4!=}9z7EE9arwP1XZf*!OM>E z;g@Gpf6VXSx@re@f-26=?DC#(^CCPgUA1wDf*yI$Kjo@KU1rmrh%^=J-wwY0AVNah zo=jklQuFN03rg0A+oAfs!)3(cS8PpO$w2A{ zcG5+jK z`PpA;&JZEQnIt|$zeySx-#ZBO-Gx+p@N#2JTV8Fg0R+E7&~W;hfE~ksExk*0_+b9Q z08j&#VKgVbkFzZyg&ef$1yI7i$gLg{UTye+TC?ahg;Dhw#ziU`Cbj;7zU-8NjWkNa z4>uuy;!+iRaQtgb?Nkj!?E_ReQ446iwbLvFOOwmF;B$ZPRze(Rc#kz*h?@?I(p3;=N5R@_C=6?}%Loy4i};Z<5O>))H)Roa0e`2)PVf5Y#M#y&`a+SmBk_>Q?Pb_ggj~J7dp>03O`f|2zs% zoT3vEA8?B?jOM_=LBk1tK=tNJEOE?o_KFtzf75`d58;!5pL*DlP{uBsqfsP6*oCvj zFa^c2yBVEc(4MJ_y_*qD$#yS)Yq@H;6B?s+n^ zRlH4nv&h!Yz6(6I;><#G`>IzHUY?$!iBxV~BSm>k&i&RrrS!NC_{)42$czBYT>owp z$;B(JBx}IhGaK*|LqIGG+HL?@o|6VJc;f1zzg&D@H+^76xaO&BJ)BPZ-)=K{G47OL^^B=tQaR&5w=J%mSU90*8boJ;(ig zkbH*RTNVN3LbN9PlTa?~5p|%)7E{#`L&TkkT~E)CDedys7t(-e>=7zXJ}NwS+!V)L za7XhI)C#|MNE|AY;NRE?E~2g-y~(C7o{M{$5t&Ak*9?CBR13^u}Ng7 zSwMvF>?5m3><>Y`W~@CjQBSp7aXU{#;C>N`LFtw3RCd*8thu&uKsjKq;6oh82+VCH zLVE`IUi3kF;P>|{dTB#wd5R7cwU)6vbnV0(a(>ky?3+w79_q_Hqroh8g3S-%NNz26 z1;;Xqn$Vv+EN#x~mxr6yn_0ftv==ec^wn-&1>c3)LFX1>kbojwA=&tBWAdi5Lc(iN zb{ke&7y7S0f1`N6f?viGuvvb_4~?U(w*+ETrc95yqeWwWdeFNH>}K#^?fgSjVt|u? zEyh9&Ujpk0pnVUua&eDveRwm6(X3X^GI4+iuI)FjbJkDiNL=lBT0$(5i>^9`czv=0 zSMGSY(Uri4LS@a%xI%c=2Sy;%*%DxhloIVZA=o2yG+`}Fdt{0Dt9QyJ-`@j~+N?0eG@ zxl45s9y$f@oT>yqMQtMw;9&5O%dxrKRCcQtXmyfF%@0Lxm8@rfxaGq9Xbk;)C))@b zyG+qIA``9G+_7&`BkHaR$HWTfVg^;JqX&{3`V2HPCT)EUOqUS-LF}hi<}RO_-;|zq zi*+je#M80;=`!n3dJ&4#`!o5a4k2%Fs=d0l<5IquQboCV#^wiK*` z#HGjf=RVUn3kKGFBB$L&%%4Y|LjvSMwSYOiv>mKr??`Zn>oXL(CV202Jd(zm`Xust z2>{O#aVkDVy!N6NSz_!f1sP=b4%-k0I%xi@Yji)}{LbzPt#dv!xPaxD$wV)TDf~Pn zvrK_ra6FAofyk3_Xu?>Sj#O@$a}Zp2j41os^SSX^rEwG`@s5)h50|J{MRD_dX8)d5}=J+eU+H8$B2)`i`KZ09TWoITsh+JOaCQs@*vOjdx+4IYc7LW;$FS5D#y&ytZv5BoNT8KQ2CqV1UOHSp z${1VPNJ(!6j$wfM!G5UzTkLW3B~bh(Cg!+`tzofll2$sW@=NDjiE0tGi8W+lxraQz zedG5|+cEd^sIRWLg~E!Z`Hw{DH(R^es0+Oj<2!Kq4lN!uCoB`hvE1;h(Uv z-PCeEkdfnGCcMZ3j;!=3_IQO$Aq>$3D>{iO`fHXe%@$p_4;7u%m4CgM2y-SlhNt*3 z&q9;*0`#995BJVJ@3KHIDGGP*?Y1|DA|F``-%Z!c$>$m7p{AqiN&Nh1xj41&>*MFM zpK(Y%Qx)JptdpDk)8q#IPHw<09j}i8@=9_`unb&TiNeZFEjlPD=30S4Wsywfu4xyi zl3|7eXR%)1ZrN@uvH$J4f=UCB2qy`mlYE?_Kvhqp>0Zp?o%z?3*owV4QMVA#x;PkR zfxT{A0ht|@{0e?0Ko>V(ZC%%hS|DjVq!lypJGx@J8j`t?#!AJ zNkfHnhEoU`UPvFLeDt`s@-y`9RKElvyyCCo`Th={r^GL*e6;o8b{l|>53rh2~*dLuREl`}425)m+A$zXeyNf%*qY;Y;q^Dr)SDq5*!N3b!@u^iYg7QW5=8oiHcYW?)`oHo*efu z@$IHy%Umx+CQqMZ;A;B^l(Q;a|+GscwFvee;SuZd-ay;>vVE z8D#)(f|gi`(GSu|v6_VivCx>gOo}QWtSnO@0!siBxo#gp6cI`9k4NhQrdHq>YGV(0 z0_8&ve(f30!Lq^NHHe`=`GKO_`*I69&Y8<=pdzPX-<_Dk&eTuFqd)gt>JKRO2uMEA zydzHf^gE{nW99!0O{?2O5qawercvp93 zb*zPHbXaywK6>APDO-&S==rMDz;&-a$x4k|^QrHlhS?!piyw4t4v-*JT}dEWrZgP0 zp1|k&eiXH}TJ#k@&)diYiD2)IE=)p;&Kk-dvXr5iyc;X5ON$r1yfQ9FFS_t zyS|J2Ep^8jeOLbik_WV93mJ&L?E)i!@D~HSXmrT*@y@b!ijEKoa}Uh{eR7SJ8>~6f_7~o(o($a1_4!ZqLf3MZsC1V9p_dLKCSZJ3_)@1`3&r+n zH)V#e*#ei@0xrnG|`1-suv1UjsP>_d`N+!*zFoa>Edq3J-QE&O#J%EGmr>jUlVcG2inE91ACP&p2_8x;KpmEWn$A$ z-RpK8=$lEMf%iP_Q!Z2!U6W_JC*C>}$aPR7#cyvaB)g(uf}px~vHTn*AhCWPKSa}i z7J|-~8EX^%A}u&@_5F84Pjs*`W}gPq^xfW1XVoas^jR+ZF;AfYnO+>}7c5*ABCRI; zB$`%O_A~sp3;iN|_`tV=VAj>PegWd@QnUbDS#59R`8+!L-bE##JlizSb#dMn30E8R zJDl3W7AM7=WSuvL8r%B{14bxOHUHn78`;3wp!C~8nb?9@a8>hnc2r@I>k^Xs3OJiW zq?vduJ@48-kKafQnvGXlm3oE}EiLOsV*8pX+-Sahdb$4{xw1#d|NE>f%zFu`4K`hF z^N);VV|Gt`W2HrWQAL#5vfFKtEV><(?Z!r6awH~yy~mR#Uc2HuS(}qxwD_ubQ{@05 zw!6z^;dG=D_QDC29hoP(G<>9EI?)K^0OrgFsD>4bO=4vjRJ3QMX@`gk{h-_}Dln)m zNeb8{X_|VI!@gA=oxP1LVE2&^hd#|s2<%N>)!zoQFQYXp`rVs$l$-W{hhkq^Ez!^6 z7c99%Nzc81I22zeO97e@Pjcsy^&N%zE0)CH+>E|MM=+`qNgchtu*4}RMh9ZA^C8X? zkN7iQt~8tf4S;q z7xT>$wq5IuXU%&Cn;mN@VJGLbyC1fJ_%acq5Wso2y|22N?PakED{hSIndz5_X>sS5 zj}^iPVzMztRX1s`y3NJ9VjKN(AZh6S+&J;2R*L@FaI#Hc_KW(6i6nIq*qAHsPoi;8cM`9-%1nhtKdIx>!EbYE5BoA%#+k#yYyh{}5pc&C@{9SW~ z0P#$tsJB;s&^bz$8@BYq9^cE~Z+Lt9%SE+o0@vo)?MzP4UcJ%rY=pkonmM#j`^47J zLDcchvz+t6>a2hedWxDE$zqUvk3xBoGef|}!|ROLF80L@0C>Fq_LPG6bd&x{d4x%S z-=PM)`qJPsbZGw>@(*SI;DfpBj()Kj%w;drP%E+A=Y(InfRfZ?d0!HXc-P{}z%N<< z8T9op)yUfTjVM1&PtjiiaEl%G{B^grKQHuG^a)oWj%n}vdEOv%lV0hzF4KTktKGw$ zZ|P4Uy>7KLp2Vh~Z?HbR3Dv0?$SmWoXmT#`ZZdo>aXmv6)l&^^SIo&(QE5IBAlz@? zxJ!?f9{4ySYPwfd`E~WU#dy{p;n1Ll;oe~?c05jT@p?IFVQDDC~m+z@PQ9wLgHnY%0>fc0^jKRqKZ1 zyO-b6PF6ePqM6IAU?!eL;Z>wWnqF_7NKM{;NCs^>Un#v2^jsM66K(G4HPiZY9acw@H zW6;-uF)0bYmCt)>&7Yc3IeT5G)fr}7KxZ;czmusg&MoW5NclPILf)I|G)OAU3$S-6 z>P&PE+1xuD$2R%);XgO|VKgq8>!i`=WUmsxAzc^M$65-m*&{Gpn$GtSZ{Ve<`(=mj z>QB-ZP}vvlRs{|4xlCzP0Hs-GD~^^}4mws(_X zqoex7dHb6^@nav8OtiFl3)`%V4 zTC&u6tEE>-=WtXub{v-V-#OlV-vRzunL{74q0MbCk5)`9IX$QNy2B;IG+;;|ePcvn zNKzvnt)QH!6RTvHRQ081W6GjkN@N*gG8wKKJjife1V_R#@;g5mf@=>M(`q64K$g0P zJ%_gkm+P_v#pWrizjH8#5~CeIc-bG|Gt|mK-JdrtDpca;9Xhj(AgrX?&4CEhW5u%_9Vh(I?+M-fA?XuMidO>- z#+TW&P+9x&`8&0Nl8;2+uCkA8Lo|sB-qX?iL9`!vj))KULCmk_SVZ!S;+M9Lu&a!P z6?y`xH%J;oH^-tpR0o0G;V5mt7qXR+y8wDf;gMJ%gUkz>hF}yI-ocCr&t}JUR3RF( zA`QB3Jyu|ptiC!hkh~IJ+9mKT%IbMg;`J@yTk8^B@{0+F;o{qTuGBT|n(>6jj0str zQ~R5o2SEl;rf-7Q4F~Sy;oY6chbSu!T+K8H_mw5Ibl>t*P=|)hbwQ|@Jt^7_zTp~& z4=#-)K1zempGj#uU6?9AG!t;|FI22j&H?M6W%wJFi0&1aA65%#?ocz*g*(zQ!|uDSsr}(} z(-nO)eOOV@Z5M&3AeYHWgXf5gt!V$jfbW_4B75wkKDR$jui@8qt_4F+(Cn+rNa?pu zBH-^gi1^YwL#KMEvLHkSEl8pp5tF|%{lT3#Y3?SN4}~0Q9B4|+J%xS*y*Pyv=s_VJ zPiK$;td|?2sJ+k7Fp|C87MyuHdCoX<;dG9C{OR`_Eq?CcM)+}dX_Mj_Y;RXq7J^apb4q4WehxDDoG1wmbaY%Ic z`49U^RY%Z0W0iT9boSM}dLNJT$Qe<$Xl~24? zVyBT&K%Dn%0a)LFu!2hFSp8!d>?WUv@oA6u-?HgU>$qx|7b^QGB~$WvE#*mS&<~IL zK}yF{&=v-W|U~T?Pi{$`L8uUmC@+O|$2G z*0%5w8))MON2Y|E-L|opytt#p%*-jYVhzxrFVCG!o{}eGB>PBqsNe$#r(0r$$@tzQ zua}T2=)gIzLcMTu>1+U0!84);^syz~hb4Ajuo^)k&=9VSX7jXd15dkC35N1wKkOj= zJcnmzRp<&b0~HNV;0m0HkmJIx)n{6BqZ%qnHaBW;MX|yA+$8gWc2vx0XQ-#?s>}$K z`eP5DhRD4G_A9zsYwRPu&Am?6bJ1N*`X-*8Cisn3lncvMPHz*6S)1fL)4)(nw?pur zIs73w{@A5%6hOwc6eL+cEh`01s{6r>7^t+{^wM4_MbFXoEJZ?nIq4kEK(&-~9$T^U z1te(~JlL>fbY2m>gk$!Tp;AB~;ZTzT*GPO7qwLH}R0T4C?O;_=dk{7vQEWTi^b?Hi z3QrJT@85nb+aUPP3u0k0&_eITF@Vd@%l~X&r0m9KGC)NUQot$lH&U)_zdgx(ha_C_Gs~pNZ;dkp4k+4PL6w0?Tm2-@Y9 z$WVd0&mP{?GVXRUSwU`Jz`o)6g*Ud6{Ve+dX!(>}gw`(ANa`Ei309p!ey536f~V91 z4l~m-DP`5?o-xy#MfT89Ri&*yDM6J2iCQ?!X2uFf+IoKyGq|atyLnHhs2REG(QF&xA2+r z81c0t7W{t9PxgzueI4*_Min|Sjm>r~bl-hra(S+OMRZs04@X6i5!5F~9C;_?=V|$0 z9rt^%p%yyMh9-pxp^z&$bmQ<^ znRqPn1mTW>Z62SmZ&pLLB01y<{`(&flyY|2y=m{U ziW?}uWq!>e(|yK(Th`|HfLM9v{o&5u$F|+Nj)NjrU8Azld2_1dFc71)>G|l}%_@P< zG3+md(bFD9c6}qqQ{D&LW55#JJOEf!k4;cjVkqFLM{R^9VuINZ7Z1>srFH0qrzpg% zn*Y`2t)Y{rDEn)`J0r6Fn0j_oR6|*t=kX3qfIpxPGX{M4{(v{5SZ=?QI0`u|@qr^cRSWL`}(BFo} zcvF~uBV0@`-7W3jUx03D`SN#I5<~B5!^Sw5NXV!TCm`Pjs zJd2Q@L7rlZ8JGIu0J4FKd|bdeX~#K&?uIeW5t&b%$JcAYnyjO=l?w0Hb5)$7KfUQ63^WG z>z{v0jU%1^btSHuMwBgHmk&w~s~d`yn!&h+zp{!}7^{7z=OMFo<}T(d$>NL*hy4>y zo0YUn8xi#%_Jy}=MK0raDx4Tqzdzm|JGeKgq`voqYzk)PqWevnFPt>&^_J;0LOnF! z2c2@)SMr>GNkSnQ33Fbv4gSr+rwF)#w!wI0spG6Qnu#fq`JhSdT}|57i+?XIELZz2 zsQrxdX!s-HS;|%XceRjWu&C|GtYYr)XWf1RSr1OtYEMIK3>lDKoT)cH3rB}&QnuMr zP4*wrRi4oDCLh_Bew(01m)FslnfVki<>6h-@YLhKZpV!Z~lV>l~~k)5i(cloILrE zU6UCV!6dkr5Pa8gfs7Dv@@yF$w4e%#OLJ;7b71HM@azesgAQ_e%Qg(=$H%ywL(2yZlnk{&4)TxeRsV5};bo#JFv zRQONI?$cUj(V}yCW@thK_^?NAJ@A5Y%n<5MT^W2(U2nE$dK%X^_9ZFod{jb#WSr%f zvfMb$y7dbLtUIBV)P!PuUwVD}RC+x$y;-|IrLh!(tTKd#hxNCaOk2!qS0{_#1 z3eLA=;-obu?^hn+Uo|DKk1DRK!@)_qrBIX5CnPNoX*sU{snuhXDxnn4SGhIchHv=T zEAxzWXalkb4q%X|=2u*~(RSc*AJC#3h5ektauSB&8WKv2j-Exo$X&%ZupJ=jPWqyq zfZd9uK`!eZX4|XZ)PAtOlSIE@hXOLy&;0+_hA>)FJ2a}pz;Hjhy@`Ld=K$9>W*x;> z@M9tRMGxg-R_Ksf3tR6CoVEOmly0< zhBJEDdgtX3@MT!}1}NCPnw1A|gkkB1Yf1T#=+&ON9zOE%Edj~?XNRmsTHT)Jq&EAb z=b=Q0)@{5-5>i-02OaFFdo>FRU@MGIRrStRNBUuvLd4f0PhYuAz_}?h|^=|^`D>w9V8g;zm^Zay= z25=__m+8a{8c4i-Z(s0v+`~Ap#daLUyJwm63;2gEjtD;^9PioEqxSi!>RZ@BHDS|f z1F2};o@)PbHA&P32O7Ra10xAtsB6pv^wn|>RURC~)*R1@1DVsv1F@K+-JF;)MLmO(Ro|o>)!rrw;WwBAHB&q5OS;vrgnJCjXrBsrik?H(AqKUnenL{h zkXch3G{un?N@t#=p9N^&HV6=U&J*in3D#cxF@A1krt#0BdJrvH{g_o>K@O};@P(vE zck`7^q99OT#7vFu;`6}_D%f}w%a`X*3C!8q`z{Xx=HR1wSWXE+4kiUNtSOl38!S3h^cgk2*1S3Fb4OsX$V+uDc*&xvvgj zlh9=3XR)o_cslaEm*vnZr{oF1W?pb~R;wJ$Ldp^SsJ9CYae+K-4wtLL2|xfryz~yX z`vQ$hjZJ)f|NJ7%u&ZO@%1<#ioq7@`gZFBkwJ>||ULuU= zT2s#{50|nUC-{PB<-@b5_lvyTia1-!U+9?B*ZFPc@@J4G{K)eSIqBHFoGSei8mHRc zxtE*O>pa}h!r#5%_r>dr7YRQp5@rgP(3jYG=*Uncw7+RidlPpdxql8ybq?g(P8y)U zWR~{L_A;c?>&`QjfxuQx2C$96esNKN@no_woxQ22No{CT79vIi1iX%su=t~r~t0aMEKRw;XF;28L63_fs$jU z1$&;Ve_JYI_YZn5&A4=Gya7Lc7@p(dC%r6kCgCpQ1i7(C{x#5gA5#m6y@y6;8((B6(_j;s<6;H-12BmcK~ zAcz)QG47Rmvmh5TjBVI(yH7xWTQOfoKlEY{sCs9A<)mq$NgGU@%`SQfK~I49yu93V ze#Q_lhJ$1hTinG)H(lSP7Hz8XxYwW9Mz&Vu8lBC~2ftzc{W~u~XlLS{*W|8Qm07LY z2!7QGrtcDJsjt~&8^5TrvY86&f_eNO5N-GahS7#uwYel*)eG5D7E@VlceC@LsEscT z-OMVPOi;{(xAle8pNjZHPpX!YBL{h7?)n(V3jY`2XE)f# zO7LfgW0wnaTgW2N@88-!83pdzwf`u^O5@78n@$n6&zAIJFHJO3*lHC!ElO%3l1ef> zT{@4N1}L-i1H?9HCTUbF?4zG!p`#TI(4B4`!`vz+%Xb$?S!bf ziz5iPWuF{U`x{X*gCPE~)>_+^mih)8jDM{TH;SQMI>*Ht|6BN|*Gb8?{|E%Z3)qR@ zwL91#V5RRU@bd2=sh^i=!%7RqU?Xq|PIlWYV<6qq*nzS-Icz`oJ>c1geV9~bh!$m) z%AX<3-0v9HR6}ybzZ62!L~=kxu&n(pC(mQEl)zrtE_*?5jQO73ZlC^1gvGsIIl*YK zvh3fXAZh-qU!ByqTPuiNMX`)qn5a-Qm+-yN^2V0?xYonlN2;v4TcTdqT;Na@EA$20(n6&ppTlIs8 zp-an!do9==7>t}QYI0?l+l<)fAWf@y@K@_P-SCKl`I|mDgtp}q(r-PEGg|JfFaAHM zg5^-L`-51~^9*Doiv15(b3#D=)z^ViY@Y?g)55tC-VgyD!c3rQ06)RT314{(m z9d}a6Vc|G#ZQ}gBxmT0EMm$h{mjP_n#+N=niuklsozJz3&YwerfSjV(eTVP zh`Y{&isE$pABI5$MuYPE^6Ing;+lun*psn1Y!AyNKe6FDbWfGz;r0w(nIK^vbF1yl z@qEATVXQV8X{!ML0&H;R)hb|h@CXgI~A%k7U>v7MfzmYnL_rDX~tpk{%UhFx|}hyHo5 z7u-Gs;yYVc@q*rOY3Z#u*}1-Wv$Rmj3{ak8NT1&jE#{5T{!1&>{o5YY4o8=K+eAI7 z3~e_>>6F*=p1Nt82H}>mkklE|DnXyKGATXJh#fechPwt)N^fDIW7o8dFMQLPH$9d7 zy$*hWJ;cviV2!ps%P+k6#=Bfs=b$pCLrLTvYy(w+d-wEayoa%LRL#=Z;Xz5Yn$4zH z1G&jc2qt-RoTPkBrh1b-Rwr^a0ckiAPelbXCE(=!4nGM`?_D!toenSK6-=-NNTQGz zP&(DgTBi<`S+d+iLy&V`;(X5-RL(4NYxlW9c9+qyeDJZ_hC_O+v+!k-YfN6t7OL@( z@qrxiPZ3$TXIUk!aE67qve5)8s>j-hsYve}cK4>-F3m=IHlg>d-UCBWxbSfQX(MY$ zFk~As2uWHgQjp8rWY*DN5h`5Mjn4!bhi;KW0fE+8TH2kQF|elM-BAUHJ>ZlRma~dX ztH?|{;-Qi3K9;~FsMNq!N@a2hH^n-q8?Dm=6IzLX#zf#cs15VnuYDWypH9G`G4L@Z zHY!g8XW9H-!A)`$6QSyw?={GojnJWZqa_Og(0h_f5Yt70@K4p&%|Qv=^y0P)8^?#%a5K!TFAfM zVkPRYIKFR9dnWVf)YY%h%xSknpf&lj-1)p&2Uf=2lM>BLUG)r0Yr&q}C?%m`ex7i$ z)rsJi!xSu&33=9vtu8SzMAXU~Z4kBZy4#J6k%)KWhVP@E-_5&HC20Mo<)MGqNC#sj zm6yNy8h>iuqQjeGPt#K5PegLc!anKFq7Khk0e(Ysz0qdMhpNa0l!);xItYB&$@Z%0 z*_N2;-#;30DFOAZ!6g7)T*(^O+bubkxk&Ed#DCm@|H>m zXh8wif?x|e(o_F5@qOvjU$P0Ky3h9}^A2PxdlIm(^p)B+eVM9ZF_Aw$@-}RI-dSK} z@^9q)5BT7pJPUl#VOSg1vVdAyhn{1e*-p|cN_Vt4VanjS_T7bZT6IhncfC2%XV>b) zqI&dujKPC9)qljFj6DVZuPkI~ny7na`m(fwaHAX*C-sNm#WOofTV}253hGC>BWNgA zKUE#06g_{IAB0Bz7fUa;g|<-kk2uROGlUjGStaSH!7iupGbfXWV~)EEwGSp6lz#Cp z@V*V=r63m>ghkFF&Kba3u|#XT?K~a$x=j>I#BzT>IF1AxztS7(8)3vGkh8Om7-0F{ zxbI;I~VsW3gbW?ii z()5)BheUES$XI#=w&eBjv)3Uz=Jh?aHcA!npjSpHMYMRI0#}AkE+bhc)aYW|L-22p zvwAo761TtG5$D~m(^vK1&kZpoO4Iqq@l-@c%kM&Qz@)hk-MI&@-7&+x?=L|DbD&Y* z4@yY*O&ku&dRa(>t{f6BBw~AwAo#EDG;IsXO1QBfieewUXr3uiw2*Wy68&%qPllKb z)J|fuNE}U?jxakM(~mmYFDWy=1F3^tgRaM5{fPJ^bn6=~E&3aX3p3VVLAE{3r|P-J zzJ+~p5Z_2z76!#CIFvOiQi+M(8RguK?p`l?ZC(-nhAb?#A4|dn{y}`y=j6HgVYr~OySw_{NePTbo8JUN8 zxIho|Au;R`Bb+-{{#9gbryVA9%Vf+c)BeR1K}sqksoH2)Zy$G&^9DjuZ6Y;VLEwiO zg*|KruR!H|jQFpjbl;;SGQ{vq+vUu%y1FkrjjrT&nUQHH|9h@;3t9Y6&yRf}XqME7 zmr)GT5p|RS&OU%Zq3fXp;fG;Xu3UfSVE$e7#ol|HnkJKP%#w2!D*7wx`EB0bpm~5h zO-btcZR5LPBa#ul}@CcAz~RYd(7FtSr5}E6Kum@X&(cRr!h@GOkpZhV*5cY zh>*I#WalV!+68Bk8L@6k;!`U#KS_AL zbas$O?27hZMta&*VsC{ivs``(5v-Tt(oFV9>N4`f0!3(_4RE%-@_X*&1c-p0WxR)& zcI#i;ll}uDd`!yw_`Kk?{CCiN_TtQHH2Dm6rkrMTkRBxgpYLcZsH7nI!d@`@KEL-$}$T+tkRFX~4)$~xbw^&!#7%wMz$<|(<$^^bCL~^&{gK%5fX0>^dY)OA zyP(3ziZh*I*oz1Kl@0-(CL4;~2u)Mw*yEK_DHCY=U^I_nN+U)|Ee%>1+LJX7Se=R? z;T*SVt7E$;TZD_j6qifUANs{zVygQ|dS$&fV3Yexvt*jaD(!ZGaFyDMAD5HOi%(%U z7`~qgZ6h+4l_L9;<`v+dD;PpF9KI(XqC`+fpn25n(U87=wKg=IWEgfb6vyeA24qK!Qeif``$YY$8%mxmdA@}$3AMuWQT&v*%SXm5d8QLLBKRBa&6gb@#=F!842&3 zIg`RxDM7}v8oez`acIWg!67~4?a@b>Y--fmd^?*|q;Z=yZ`v8m3$fIr+7k3qxd z4c9JSo68NTD{polj%vn!%u~7*@%oL&+qSX|*LJmikj+4~7w*;%Hdm);x9a}aIUZb~ z;jqAQAb9mgI@bsm`Z{7Y>u<>|_7{PvG|u$-UR0~`Hs*X_4a{HL zimtzFxI(-_ird1y>;$>uBUSgDBCdKKzS9FQ>5!Ru*~8gM2Y5I z*6&C%CnQPjwHvc~Ei*MbvvfX{@I8Z5E#x1L&%yY_y|dziXQGx4sv-P2HDC?V-l-Ox!&{f__MRq-*8_>Jsvd3yoNB$pgEBd58s_uNr0r6oZx` z<(FH?sE5)IpTDKka8=`L$o$oq1wBW6X>+9`5DH{B+MBzrWg4YE27>A1_>6keYU(FD zEUAbY>_9sL!;5hzG*p?dJJ9rG)TR@n#6eQG?cG0u(}!;nO((Ifm77evNr>yzb22PM zs!n2)GkhEqj^FE zx2>;{44zN@h9#l*DV2#C6TfL(M*OMa917B$ABNl~+i>oVKWczMqVduuiJcAY{hW-+%O#ebyv{*cY#$qxT^lJQ&6?ZPoHQHmOn#Uf%-(Q>e}1Ks+fng;mfMI0 z;o5dl^c~fmgOcM?o%yxdCD08o4ST+SHsD3%*!Vvh=h}?^qRfirqMO*S-*6q)9?e(8 z&GQk$_H?g7pE*}kSI5bT&ylk@p=rpnO+V$Ws9L$W`29sZA+$Ho^V}e9p@D&Pw!F$% zfC;?}@Ttw!=f*hi$LEk)>FM)bpXZ|ZZkj0!R*IcuU0-Cw+)lFv6*&P_aJ|2j)-xgX z4z8@v>J$;WS90Uoroel)nctiEkdrssF1ERbV-$f*z;MtKTE{IeH@H)&;mz-V{O=8R z{;gsN+vRUzvKGia$rG{B6JJ^dOo-IvZ8b^)*R*>uRk|3>4`WG_sh{Yjlb9UZhT(uI ze)sXfsZ%zsi_gmxT_+A_C#q=pGS1F)?Ia0tk0{P4KNk*-BqMo~X0=E_uIroapDAt3v>R$zYCN04<#$pvnw8*-jD4+jGt;=H@f?YWA(P}=MXmr2X3QL@Io zPeOdm3Yc1M<>EI?Bw|&$Qv2QoMUOc?xz^7psJ^L7O-2`>^DXPkXx?11}!$}QhQOTM>Yw*;Ao8m1!H{F zbGbz@IoxO6Y=^RR_-XxheJ0oI!f8x^X$DA;$V>ybvY)K#&tnBpWb`Xl{mVap>aY9f zjI5sjLt?NCV*Ov4te{%aG|rYdK757vsV9D+H0R=$s~14kxjuqRV-40wQN8ux=y-o*@L^pKv6 z!dc<3fZpSay;>JQoFXw@Y4DP+YrqHQWR44VN%zDUUI?#L2k(?7ZCX5M8j>;b$0|^j zC%a!~Blk=6uUU?z^$naqIlna8pnr@y913-~jfK*b5P^)K9$uAY>&7eEAXi%EWY~3& z_sv!-nEj4lHAWVQ^Ok==Ol}m%X!?DA64o5_X^x_`g!y6=?(20n}ov zzyA^y@neBuY6Cpug(fNQ)N6eUaQfL}!^t((WuMX#k7|fTDk?h@PJC=jcoayAclxO`BJ|(b7PxiEHK+`RV zC9M(VX%b=a|332HZ$UNM-&q`a$Ls@TM-4TnUGF?khJNrBsJeHXM7`t!y4wha0mXAX zp52g~2fMWpBaYfu-%%jK;@#+98#(*mx#m$#_IF8{;sHUA-k%E2(OSB(rKx18~Hv7)cehx`b5MEnh4*gX!W^jc)t{s8s}w-15sD@hF@0C(h>S5=Kz&;vP;>N0q1xB4PrS6XIu(5lF&?^BgLMgj0F*FLjQk&x_HK@mPtp|c4|_>5-~`wp0o z889Vgxs##^IDU$Szs;{5%2A7{w;Wg2%4iY8tRG`ApPc|rLVM@oifHVru)qlrE}#3> z>P@0n1~}CUjUA3^N4e#Zh?mcaDIR4eb0`dj2f_F0hu0s3#jPY&GNE~F5?*koS;mMt zzA;Yc5Bpt2LDPtgB;RV*e0y2Ne2$T%-bBSgkMUqcZ;|$eIhB|GA?Ak7IkT zs@UfnNGm4!iC+6cQRxSu1kv~{Ni>`;j-uIN~L#zaG;=kGqY`>!i2hKcBG zztj@e#Syf$4YkNC(^C^gQ z8r+!~bN8FT4SO)0d;LFZ?EZ|$XveYytM!X%sqkcbH|!4%R2rfx9;GnZQ=R5Pp5=v6 z`EF<7H%~*Pm^D4_Ib7iG!NUsk`-=C@%Z4mIX}eEFFxIMBiFvS*!D|18wymsT?*Yq} zX)54HQ+h~a%wg8#sqV7E7+5mJhgbzn7Ml*Re4aC(bTw^0#W5>_aLI6b=gl+I8;xJM z&$9G*e#bj?;&i-Uh{x02j=mmeM(3eVE^E!!%0he0&oHCM^nU19+*!htw0Y-0K=CPB z3e4ecM3{^gbNrPy*d9VLLZ`4YzM)HO(Q5BY1z!i~4xu{Pbv{gPQrIE9@@Q4Fh7Zg0 zqS*Ip<(*!-&U`Yv&=vgyXN!*3=i3XSsv2)IP04*Wgnt#fXz9Im1qXGQ!+ z4`(_%Pr>mQyQBJ45-V8585G5XrtO(BHphx@cvBZNC8EG zs_4rgTQk<+59arMT-Oozz#1&o(6Q%w@c#a38g#f}e}s&sq_cB`mtNCXM;-z~VE;}} zBKV8l6dSr-DTH;`$Rzi)A{bPpQJFmyQ{()^5`Cb&5w;s#(5r=(n0?oC35R(v?-_O& zHpO9t(?%kX2)u8cO&Jcl=oQzrCAu5>Makd8Qpo19$;9<&1DTMf*KMn<#3q-8lZhB{ zGgh9FolOmtLGs`yYNCKjyfBZx_{9vk@OTQLPMqJ)0Oq*0_)Yc*rF)=ZZ@r~24iyyQ zQ%vy)tRoX$?xp{@KEGn2_j`}>4JVPnkJgu7UOIiDS0o@$Qs}S&+s)#5aYSj?z8533 z+wngt20t%(-0%4*IlFnsyes~3S>hL%U3fVvl(){AkYuqLmfO^XG)m+`1YY}VXcki` zfk{4T^Ah48fVR20t=g(qF>+@w{QkxfF+@PRMhz@Iy-=wk+xw+DtF{BqKK?vdfyqud zT3^H#I(>XW9=0W%?cZ%na#@51x)1+L1d-s~250_&!8YbC&WeM5>AO8_&ys z{25tY_Mb_Jti5MK52hP9)U15Ms-2v>IKpb^)cNGqEJ4ErM7GGN-a@0oUY@)cg-z3& zp0af@IAGAvJ@BXUkH!i%$)$u=@Fo{pqzWGo+)_@@hfceRFi`W_L0o8i6*<#glmy(w z`LBtv!KpGY7ZUHk%aCTq(GL4|0^`)tec>w&Y9GQC93{?f!dM%RQ`H0EyQn9x^FCF_ z*7Z?wm>_drkpkFTu;Ol z=5q7#U+c%Jd0c_e-bemsH-VzdL>j!>!!_W_B;YgQ0>A?7u+m!p=$~*fE3Afu|0Rub zQ2laf4K@DWNZP-^bkb`CR=U;w2LbU}#8nk757T==9i5!*d27UIy)Gc1F&@3SBIsiU zEelOskX-rQiGzW)MTHxvKt;Hhy~HVz0ClUW)G7xxb{kpP=)lmxHXb5jVBd!T4SZqU zC?vI)Zo332`)zc?yH>FBT|6iU;(^ya05BgJ3EOSp3_z;5(AUwPp0ko7?$+RerlIoMFYl-5NGY7yRyQe`aluyWAplKUlQG@k!2IZD!>=n=#13u-V|0`@^W(a2U^EcTLyW z?lKyI0$KMK&~+94?@CU{{B~E$j?wmeAC_H57x)+fzG<$Q-4lu4nM19UQ#lgwv&rzk~bMHIje? zH1k1Y*Jt-8?olxm%WY)5=Meui4wAG^|0DO&dcHyB$bJXeA0c|m215ZzU<62I)$cnR#nL-^E z3n+OKGor~GeC9Y|_XEvU|3F<~1Lj{%y>CCX;^obxOMM**y|YhdWcJL<_NV#`r<7!nE z;TmlUTKb%Uifn6y6~>a^X-h|=vtOTt9J|GRp6~s_%jSrzln0txBU-(Hj=T)#0+P8!n=@?os%0jU(jtuMv+l%c_LsVWah6T=T#ZD^c>{iDl*R zBsdOonLWUWI6cmv^eI!(<-TH<*mEs_B~=5uLa}AQ4#A#AkcPU0dS3@0T_x(EthZYO zoq0xYf#ug$-KYpLI(B#+pJ`F4%!cm?B#2KPyQ*iYM1_+q!nW(YeA`zroUDCo_U-E+ zkUuZ9_^;5>D-s*H2Cbt?5h#2`rM#g0Gl@G?W=-bpUV+x|rs1H=<9ey02z+h(ADsji zv*a}2J^>!D7YdhdR2sxvNi7sviC=EjHhFb}XsP2UBL~?w^|70bnD%s6+}I($(lR

gz;PChu+tlslHfr~I-JA!@RmJtD1KGOk? zedtb-dgy@X9vY!Y;#ud86OCp!&J+a0I)9K-BAR^im`YfH!=BEKL!pc6Eh5qO4Hy4O zp38FHf*9&wVj(ti(f46rSb7gFx;;^}H97E51oy)4M(84kP|caA-(7|*+5a}vlaYHQ zS)8p>c@ffMh8XQ%e>p3AuYVV8%Bjk?rI&o%ZhF-PF$-cE);jrNf%PDN(_d;<+V4W_PSHDTr5b@p8_O4;nT(;785sHQ0eI;3L9UJHs1h)^Q z%m3sx@64kfGL3loc5D%<%A-kkHdIq{S2E|}-9*3#s4ymO+4$z#I%IUqGfG^C#>zk5 z0-t2m(wytPVdbHH1H3MPJ0K&PTODj_{F=_L6cMw#zv(`mx0B6FHGAtwT2d<*U6g`b#O&hz2p~@ ziH8|#XOBO8n%$lvHuwUG1GLYr<*8OBIOJ=De>g88@HJiE(|4!8F*kp?3Aq|Bdg#B< z@%!WoPWh#Y6aM=0f>*4_oYW$5b3M65)CM@Rn0J6|C|ll$TOGeX)du zn?tX6a_Bdt92SSFda5?5>qTKVRAI(Hb^4Zx6Vh)lyZPA#19kB7Nu%ybc30o!BU(nr)uGxG@ zTIlG!m}vVH(-jGO-v(hNC67+uQZxbPKY5w-I)~7AzVV&l_7SCE&gVTuI`D68^6B65 zauB9U-CA~fyoFYLw6=(=JDsYg^n(405cMeZ(pHwXG70O%gj~|{5ms05+(&;FPSNco zn-h5-Ts1t9AkzQCZWs2>Jj*Fr*Ru7Nx@4ybOSZIY?5>#ckmL%1Px^30kV8kGZv?l; z*mvxcXH?p-u#?JnQdxto)ty=+>D4n*)|*y!F*riWH+WDJuDSMbd>6ltXar0z(*_e~ zeVTM7eXe81JSERsb^a!zf7MNvg*`~p|IADpJMELxxj;lJ!ZTv;e|E^SizIMYhTH=( z@ZD!1t9^pbQqcdqNB`t6)|OgS1+C!p_Th0r z+Rcx+Ht+-{tVSDseEqTO3L|gd4fPHw;m(Tb3fTA&pFraU<5t-=gBQh_$?l&szTAI2 zynq!*(jNApgnNavQ^dU{T0E^_ZrF4<2m+hl9pXoKg+ed-YAEc^dWYTuWID?k#SzPh zl6PH$|E^%hjd@;V^%?#jn$A0%>i_@$WkkeDvgOFgCdnR$5G8xhlZcA4lI>LqS=q@v zS;-ca%wrRBLUuX!9>+fCIOp~Ho%iQ^{r)@Gxvq1a>%7iuJfHV*d)%9VmNu)a*5N&p zDpo7Vw=*>Q?e=SEvJZ{Rey0d?423c^KgvH#pXn0Fhzh@Jy@|6~0n**Bna5nhtXBgE zr_e79(qfxJKTZ_qIVZp!l}za5o#u}Cvl{TtgG;Vf)B=o{i{#=SQSngTM7lqQ=UoMy*Kc8c4(q5E#d^i4zGvdiZ!hpgF+umB zv6h6$;<)X3X6o`agr5YY&kk)5A~~n+HiKe+?lvb^I2b9mD6xv{@(O+708WvQ zTYo3|-n_Ca52+U*ZGm!4pEox{bPy>t?K-}bYn@>CnKrGGV?+TIOOK!~MKrw5_(=vH zf)5?X{dCmLNQuO2>I^FESJnyDwGjV={33#z>IjumMF)}CDjX{02{P@SA^kz>_{0Z^ z$-zGnwO0hI2>$QU1VnV(kl;2HM|xPc+FY_QURV)3sK`!e(z;mY>;$-%^B|9n3LtS{ z`FkH4*f06c0`-G(%yh}?J3x_CQIqni%mL>^i1B*il~OOKo=^1E4$x=ga<3RwYW{-BG0tad5x?~OKwLwB;=CZKT#A4`hG zRdCSKd%Y9w&++VkKU>QVDD*2oPsbr3Hn&lq}kqA+K z8LuZr`a>akk%TCw-*GpWdIotCqJ0iEuEDN+WIk_;CFNAPX1~pJy9(K|%O%|k`RcOw z;RK_^=%Oo@aK|7&r=@$|fDvJ1{r;YR+Pewv3q%C@XJQ8}61r^@Fjn2cZvTvnS!FG$ zW@`<7fsSv@i$ax$uz&Zny;r#0qx?6=BTsi*WVY(Ct@Fh)VYY#@2jJ(}qSrj*)kt`& z|9s?pFM{N3gZ6Q;X>>IW{Au9C{+=)RkpXGKu|+y`!yI+v&*LrP;O7EWmSftMdi3@- z)iYJRA7^Nc3{>urX1vH=tY9LQ@Y7;egy3?f{wZFnXZ0{Fr=yW~dLG3V2XdUkbs&*z zil2|^noQ&TPFYjSd839wxA~TaL%N^n2ILoBgZ&QCFln!qeJM#N3A+27gxw>O@r7mK z{WB&P6@GIfDVx%=fh5P)3ut{GlFQFW>&TNm5vPJ?Q_BI;L^r|MY?gt?p%Tr6H*;)V$2Gg^-=Bzmh7yAJI%qO zAUu%MDfa7v+$ExnblPBPtB!&k8>c^^-20bP%11#e!C&Z~D2^!|l;DKejS*6W;aE^V za^t*654reJlFdF#t&?x0)}1Mcif1nW$J!IKL>8 zouxTJ75W-m0Qrvq-wr7LwgMBy-fL{nZ-(CalrzG=6M9!|%{6kShtb9O{1vn2ghbd{ zrBXCvp_zeHepsZwQ0^mx(+PFTkRjOA;$C{Mbx?O+0!ov{u32U_)e($$fwOu}qu+I1 zval@$%QiRC>l4x8si{Z9(@jrP0Um!(MOLDb*>rHhZ$+{>;Q*A2SPUV_%A7B+Zf0-v zXY)PF4OXkIzOLc*S~aJi$v|s6;ppO-qweR9!`DH?ekeweN;c+4*oc)bl{o^4rgV<) z&EBKZZLVW;pHB96u;}qV#vA{Fx;c=SK%y6TP3^Ev+j*dJHEO$lMx&y^*YL+2 z>7Y}#mybsyv_G0wZWSOCXF3Lu#~gv)Uep`UI97gTb4WwWGMyagz!yq{rPNL&xQt{t zBd*a6Y)^liCmmoISr?xlXZ4!yiJ9b~@I@k#^=LL2F8S@n>C50}H|i1d@GT}#uF&|n zukPFi0^uVj?iM`G2kAm35$JYxvtz^+aQ!h?@Ft}1_nf@TKW_}**wLm*(B1(Wt|Jq4 zRVHj(C&z=Q%kc2&sLv9X@7Jc96W=VC(>~4wFJ5K0)mCfnMc%OGr-;As0`$w;=GkfZ zLv?{;I?{8pp0kO#_}hnFe{|D(-q{&PBLpUpG!Qo>jxs>j6K}Q^NuxXk3J7_6hGIlm zE?4?yHPi9#1X|2JJt*AuSu*r!6X9>aoMSLs8%v_-k%aiOkX5BEhgDuVY~NJh2V$&m z<$l<#_rrIADyX4%zYzKM)S9kzAo_l)XM@5DG1`L%#pWk<3%S0O zHp&?Xtw%z8x!8R1r_q@?$TL}2GcX|+}bB6E7g8Se_*h`Bd*Mf z5b9IekCSM%6VQ%OpWN1YzVuMVm8(jp?&ghAnpFRy=AW{dbfxu(&*CYg_w_3B9MAEb zA=dv5X5^byRrYM!elhQdI(1NbzMjvys)JuqghZMTa(6H60?=vad^DWz`}7kDUm=nL z--nRhmXjz}BQ;sIH__1S-cWtCHG1Wn^Xb#?OdO8;|GWkEF&e9$>#Kc&i5ERV+;8pq zYNyl2n($5{E&w>m!}Tb(+IqJhrWkbE&+bp$Iw>^{yE_@O8zzqTnyk@sJ$+wKGE~~f zIPnK=1X{Swc-AGv19te)Tk02LD9@vi!nw6hr+6N*3j+C9M-cVrd6a)?FL8|C%bGSU z29|R36-hHM(_Fj7gSD~r6R$NSZF$8W+IRmm?ek*p( z{SNs+{)a{UT4yAG=l%nk!ag+hO+io@Vi8fhPuEOuEOLz4b5?)%__eBl+DAQfqUfr9 zFb_Zb~bdItoVM}f{tL^12}GDmyJO&z$bT**Ys3oA0wapdVH?I zXH3ZJ3x|B$*t0InBI`8~#n4gQ-^A~S+SU69&K2hq> zoc5)w3GNVZ=X+&-J}^0Id9V6bsO9KdF55NT`dh)s&ITc@^ka&u5NhZYg>c zkSxzj3cj(1$JKA=%e4j>Q$6=sR$kTq;4+WLU(=AfBn!)i1_;~lK~}!A?xP@@03yys zey8}4_ff?I?5#syR8*{>_fknpP-jfB#pTjS-#YVuH+?dCLd+ixsCbrRF5ZZ0yLWzC zrZ8vJ^{blY>+vIYq05VxeEO$FUkE<5OYME6R-tg_&^mmc(U~;7hqJB*9F;DkD*Ztu z?ls4oLZ?6r{I=I_56|v>$(~BzjxQna*ejh{uKo3&$aN0*dp~&79?SjWuXFTukD)Ef z$e-}=z;y#Bfr{|ef;a)F+^V|A{Y5oH$o4nuz|rhk-mAdSJcfzl*{bd-wC&;cj6m+ynHkaajm1PA)4N^HbCh!V*rG66BH}ZCCd;Suj;!h^5}+*)+0WKCE{?$S(BM4Lsa?Kqr8N|%1+ z(yO|Hz`L9(ZL@Co4`uwalbN_&xkHixH?hJ`&<9pW+E|ivF-^W3QO1{&QU}Qyi0bmM ztx(~?;8%(m`WM(U>?YnU$-1=%{nVrUPU@xFq!p8&Z#?Dc#A4odcN24K(GWfn6TLi; z5iL{Yz@;$jqxa*uakB#m-Km>@SRELIM|qK}N3zd_p}`_GB|7tMC|9_0Q)=!00|$YB z^Vm|=Z~A_6>viyY#EdC@X}%LAToVh4uv5m2bB=NI{ew)0bir5yO2UKQJMV>1ESdV^ z5nsHk7K?Arxo+q{t92Aw{}*_DS9kxtdX^eBCSkMM5+B^zga{1&Z{rrp>b+u5ERq&y zKq@^q0AB<(sX^2~f5b;QlZ6>xQ^WrhJ~J^U5f@|qFffUs9__FKwPcCM0%Cj)UnDmU z60K5h>1@`6S+T$aA$CvxyHBDh)_cy(91fy#mi=i-SojycTN=Y;9Z{JVj1W9O(<)+=Mvm~D=vAKQX4Y{ z!~^*VB*E-8_#R2nHTmcONuqifL-#IC3!OZuPhVe&lxaq6KQ@Ndxevs#7Bdgzo&N2l zg=Q2zUClbm2CQH0RNzE_eUX%*J;cg~hYKW`7QC4l>*sjzcIzux1LF&%Nq)7z$?uot zm+rX)5SPFak2{$Pgc&yn$%9i#N8v`{5ci{kHk~ zxJKCcjtE5lD1%B6xcf=Re-Wj?x?RGtUt%8pAl6IqbXP1)?uk0ndoo4t6oa(4<^B~g z;t=IkKklY=e7u3mymP1Ee3Oj;(}S{cP;Uk0^B^D0;JI>krTj1BTIRh@Er{939k=pl|R!OLBw34L( zr!zQF;Usa1mEGra3uzweQgwkG=?J6s!g0FIc;H)*zt=|R?MX0>q)4gR(&>UVF@pyB z7EEu3ZAM<2mmeio6^A}eCz=%U+=H|U2fEa<`Zp8Q-^YtW;&pw+=bI5Ek+%n@h_nkm z5$8jKPf@>`pruwhfz)#%WjDl$2>pHQ`-Zb^*^|a}kbStH0Uj4^%sk`S^c24<0|+}1 z|HXA06R67)0X4P#XuS@)+0#}Wf2&frk#3IA7{9gfXSOsAi9qU=N1roD=|DX~z(fXY z_m0T>^9~w>*a;KX(E8bBFnUtE0jiLD{gOq5&9D^n$Jg$Hf6vC_WVgFkRt5!juPDF8 z#LJJ2dGMD*jS03--p#0P}0JN{` ztju>gz1olp;RHCmQrydpM85_+TCy6zv!;W?>mX+E7~yx=16Nt}Q1~KiCF@u7w$xD0 zo=LCn9+Rt`ri1jCe$AV1@wJBRpAiK*DPEBe#_pQ$`pVy=auzodu1_(cGSl0yn`Sy9 z>H>>B2_0>()!ENzU%1;-95EBt{;cEpT#ypX1tW7W>03NhqOn{$a!iN7hX*bt>vi%r zhhaK(u`TouS?3=c>s?`-aPX6V!0Nm{Qk;@{fd2PlCOS7@R{3vuZx0UF3AA|()N5K6 zQzA0wO3`z&iR}kDtn*Pk&*&N1xA<0mb(Z*XaZ}i#*Y@U=`D1jZmjtA7dgq0{3F^w zf9xxdVAr2#0Bc|HDGwlp?Cw;LxgtEPiq*y+kWN8cu|lMuTC27OnW9B;vaa07ZYv)W zwj?FK{`7X;=Qh~Oo0!|&WVMg{vM*_SOj<;cv?qf~a&?UAdfXyUT2ET$J&=&fY*v7n zbm%|MQZ+b+RnRq6&w-)DPjDs)DTC~=DiIw)SHSKvA;o%3?PfxoG=i81{ zF6mJjE_!yOiSbuIK)!hgKl0TWNYx#*)*I)h1Q8_rMm)c=wM~`K<(H;&Kp8oDI)2|S z#(w>UcDSKx3_8?_10#sj zYN^9bnYS(#ZtVJ0X5Ppcj`rSWQjGSfLfcB8NcG4I*VcqiF)E9zP0XQYXiGM3#+&AR zYDcIB1aH-6lSAUyTpKB(1BchnVB1Bui;a%>wO%zuSyR`WVeDgY=tkpF=u0nF(r&}*Vnk zMu8&>eJ{3-i5(9FJ zPB88nGnR%^n1K(}GwZ1X{a8!ls&c#jgZ7Kb`ARRVn1jC zb4Tj-Q&3{xOBhJMVGv6m;`(E7=UV!RQ z8!e@R@02<&cTMM$`UI1saR%YJ43E8@$Zr+>G2_}ZE^V$_3QiubKHT7uRv39!+;B6K zot*O|_T+td=Mmk7!ums2ET6=oBfZjzCZrQd`#fE<9bJ!?*jS&mCjA2%G!8YPORL*Lp76)T@le*`);v4qSm5JRyk_v|Y|RWcPNi(JgE zJ_?lRrkU0MXgu*Gk6-L%fizs=tLK9uSgyYLFDt$KVe3)xwvGQ5OlR~tf;FSmN;zjz zFJ8(UD!XeT-ur39WqR-`_IzJv^y~<5*{eSUpC3(eCI-K?TdXJkny02=ozIWPWqF^w z;3E!V)D{PERRL&;Q1AdnS)i*(cs49s&A+09(}(OdSSuYsd0fZSAu`)^y}EH60}|Xa z4fqG^ioK|6F*G>6*{PIwCU?wx(Yy0@^D9^&@-R29!`$1&!}@O$aS9X8P=dbJd?+l# zw2Jf&SDM=cm8XPwBBzTzI!*c_LH`Ly335LVJo3&4cWuSHwTLz3B}JsO1X1MmSB+A} zM}i{4u@^QjJ(dVN9#A0_5^*XK7gLl(ziC0TO@lB!@=v)pU~`at^waNotW`}rDuSLR z(j&cZWrx5$%0~AD3m|k9SayCKyu+P_07zAE3@UqeLU~Ifo6BGIqTse1Wz^^k0(>=lv29u#z*CQlOqkWt0xL|^P$Jd~s4Y9|@?QDXzRSnC z#%7QsNwdtHl5axgZNhhD8o-$AeV2sa0QVEXX!j_6)E?jdZjtN7ur@UE&^PI^^#!8$Jqr=|%PZM>IvqQu`a&nc#f#??vxwK5oUg zf0AZfRp^Vkn}?se+o7&wmyf(vKey{)Bn|f$Eay!>x5KGBuq_#$%6PeYzzMkc=H(UJ z#|(m9P?kguf}Nlpb><;q7$5l@wFjps{&6S4{Rwf;;z;dPJi5u~*Yo=&s(qdGQ|KDY zCBzXi(Wvcd#7j1Up4#QC;Vj602q6I2tFsYK48i7c>8|y(dZN)Oz?ouq6Rt4`lw6S znIET~%9O?{Slr%I9%&Bdv>?ekIcFY=gw9?6M=trwV+K0jrJ}mzyOMuxpTo#Ubl;l# zb2-U!*%IoefAR?u2#_Tvp8%w;ozl3xGj6>dWfBvSbwgm*50bp~!b3L7U;&Qn?mrPr zd&Gk$%`J(}OnkHU%C8hF^O;xUg+t}w+_l)^k!p+7j$+1bk2g+Sx>LV<%NOOj3d)>w)zA2%ej~~U^pDEXQa;cWC3YbqlN|MyMMDEM9NaDf8eP!~xX8M_ z^}kz$>M?5v){a`6nK#9cw+9;PRE#u-)DDxOSGExS*Ne1y?>j$u+N9+DJP06KoKeaC zP<%#j=IZogk@Pp+agRRhXq9NT%i7C@nY{nQ62iq}YhT*?gOS@uVni|@bIvKBJ0U%} za=Tf6hCk43$d+kfS0haR(iJ^MVpmFJU_t?n&eKOy1oUaZ$(y74g{NWkq^@m+8Bamf zj}{J?>c4l!M|?PZuK^d#xO?W{n38nf|2~vz zONVQinHTo!uMT%xPoHtQ$*lW*y+B?-!w>HqyrScyKUu7XAJTe1c!v)D4QB)b@yWOu zy>M0UW5rnfK>W*~Z9XEab?rImWR4nECh?V!0ej2=)p3FF*ym7Kpc20Ii#Mn!9qGJz zudDPest|oze{x}oBv(Pi_#ocErE!U`o@k^J0&EBzpX#(H2y`Z_i;LfT`swYzZXPBu zFYDSRINv3n<||0l$bx|nk}8}kpgX4H?^X75K+4HK!pOYk-a)G0r-f)$HlS4KOKfeA zAXb@-zi&&^_sZFjrkc0V_O_Gsl-+w>|AW2@XYEyo?bN%_#)l2a1-o!CG*qRY7E;~% zQP^jUHQ8aiQQ;fPk^%DXo}eM}ya@i)<<(8ut!nl~Kgvjj;lwCv*q=D3(RSof;u{4+ zYu`V_@^LsS4rwsfC-5^}>uC64(rR9@8;X>nmFT9TInElB?8 zGOY<*C&7R&3NwMD9VP^R6}C=#a#LKQ*3#>!kNuLG*lI=8a-0p<$qq}sz^}43MA^E) z4a@!hwOfU@=ji6{D7(u`0>Ous$%*p2h?H6tNf%sEj(oB%T|d-kBdc_!IHu?|I{h#e zV19L|j=!Hg{^)(XN?w|uRVSs$#3Yy@<}LfkZW5Iq_>UJ$|E=Eb>T8kZiWo^1KeFCL z!MRyLDE;B{)YjBJKc;o-y$NzW_HvOoeL^+%LsD%i#mn-8?hrAwLrSj)^oFwf3gjlx zchPq#T+S2aW!qGCYn{KYmxZ;A23*dnXcX$JKd2WcNZZ|h>!P@~m)+#!`}&B$ znr@G;aPn%RBvf!uIsh@D4_dyDBgqwG3c^l+mRf|-l}|Km=-(1Vvwl&E(Rx4NmhU~vDUP%p2FW;Ng)DIA3Nv5*XM1C@FUG0UG|NDbH!~y9c9qz|c*bb21PxShLrC7`-~E|ceB6m6?AQ3 z_D6G2bymz$mU7u_#^L~o}&Gew?v#OOv+>g2+-S6%7gH&!F0H-}O%S?fxHeSoI zZ1b7;9O=%dfgg9DdYxwDHmuPqq!~2XUTFi9c&Vno$9{20>0l67o6&kRlnS<-yO)W1 zGv&APCYmqwdNVFk=0Zm3?nsUN?3^N95TDZcs`_pa{#4La_+$O-6DOtRCG(E|oa)vS z@@}La?t6x^{p5$4HdKEt7ChBcPRhG?&T~Ks%;ClmTWK-QOf;oM#px=43`Y^AZp7Y1 z<(Y%Ig489ck~%SBz^sqEO_LFVt9i4kDN2O*Wyy?~$>9hi@jQ!f`*5|UlUY?98(wi1a{X3dKctFroP*A){dqp~v_3Lu#`6k5J7qx3F&FUQ-WH?i zh=4kFA*M!#uPQGdlo@yMfT@XzZYs{Q9ctZz9;n804_5tWD^=@qBu zISW=dfNr!XrA04@e0;$klSwZfvOfhQmBRRlx+uz2CKvGY!)?2rUOi*5Ytr8iv-AZz zR;1q#AQ$=xT=SS%Pl#0d&Qb#jK*xtrJKbIcKWCqz;w)#6+umcNHv&LK;fOjBcOMq{r*Ufa!0m{##? z#b*@~1Sk5k7m)kE>2ghLiI7s%!{?#}LqYcqW#DOKV}<55Na-%TJYKyHVHjP*dTbb| z9sL(-1fzIds}2>^^r{wn0+okG~sySaf_uIkPAQ4s_*~n zNYSziI3UIirK>#tEMt1py4qIc6gD(GD0U#D$=ODTMp7*|Mj_K0s4?Ha%0XV|{{_wP zykmyKdm84qs}U-mF$2||;pFA}Gm0_CX31Qn3NhY>o_;x&fYoI8y4IzT{1TV5f?vcu zl)q3))pGwJO`VJ7l2pY3&Ev)i@=SN~rqYr0!%E8G?}L=t&PwRGPU3z$MW9$YpDbkU z7AG8j!&>yW3c+lR0|9t)3phUIiRU64k7cG1}w2SSegbB84e3$#Z|Ck28H14pObl+|1 zR74Y)n*Dd1=0mWjeC)>uopq?A9NgCubt&E#lc}BI1}D0|%19!G=z*%HH!UYqstzH) z4 z)qN%8FUF~!kTcP@=p;8>qW&B5Y&lXJ<)~b&Bn>(wo=$~$XspWb|CqRUm^s>byRM=o z57kn?;^!oo81f4oUe#t;3LMIj5}2*jQ_3Qh(*!4=&2r&zlc%4cKb_1>kpFD`uZj3b zi3ulrQsSeHL-KAe-cuURw>a~}i}>p)gT}j1b$p60U9`J8`406Wr1ZnN9vuzuarfIh zgZ(e!x1#uqP}#tfMsVlc1CmgZtwB~FB6+eJdjvRw`eZSSP9;+io?B#W?Hg46PV;s` zMd%@)mj{_ky|n&rxK41oVZ3is!zo;t_8!YT`cUqYXMT;rXg%%~d$hpSWmyBgNqaDR zyZYSWQ}o>~uI|guBOjkVdaak9|GwOFKlqW9W$%)nnc|$=PuV~}f?9~5GF&CNR~5@A z-He-=7lgNG4;%&^rW^2k1W8=JuoL++& zJuCJf|F*qyNX4}gpHsqF|g}rw2z4ie}8+MozUX6#QAyD(8 z(8eKRG0+@r!4GRyuffVF1>63E`MqQ7h7Z4^(jfjxo|C099JzFdygPeJ%p%6fBuA{VH#m-`g5J>HORCA z*0Yil7qx~?of$7Z=>z^P8ykEyUNX3_@%caY$Pg5PPg$TSl|ld}tml%7PV?^t#RaJK zv<0bYe(MJ@Dtk1i+(^3$?Gs}e2KG(>p4~?o#3@C-L`=27pCC{eico^$+o2K}7s8X+ z&FY`4=-!=HKRgbLwjFmD^dTp7X#H+Tmt97W5mSpVyuQq>^guT8VIOLim{B>#=23AM zXgoo!;N%bv0tcuI4|&~<4hPw!kJR1p$?)0_&W~?&l|2&Kr0Tj9SFxp~^5uXiD zEX;88HvPm?uKHHSoZb#rRN!at4Tn9_k6v~5FiCof_-i{C;XdQ#RV}2)g-AZ_w{A59 zCzIC5yNYPBIRu#tqsg%0{-bs~>|~Z>W%sMg(z1#Xrw!Ru0d(8+=#FkFwxq zbk8OG?@6Z6{D|Y=dr8!V#D6@abhRB1Yz3IKW|quI)olhhFRl*~Gt_&WD0ZX;&iK*S z-w09klZpqTo3L!a4^nL*!%hoAeXOnyWS$BacifW78v6mIFnoD$k;WoW{-8wYWs-rl zA9rF<0y}Bq59B;1SgWs?c=_NfXhs;!RJE6#r2&a6`>U31*e9En9bzS+N)DmtXC1(n z-Dm`9o+ZeyL7#?f_!P1WpKEtu)TFK{9yd;z3O($LkuO8f_-aalSqX>UvR&NvepqXcWrd=p-^;>U? z5byJgOSA4Ix>sOCp!rII;_T(`c}*E?iQOqCWnl6H?p+RXWvW*pu+YPVk&QkgC0xhX9s`;I8lw3|Lb?6j(^bg z8lTSmjTAhEXn2UL`($_JfIHV78h~lcJ)0`@^m7%mgj5U3nCH8Q^LO~JG5(v!h8!KZ z{wcq-!3$EVtev-!tKM_3TJ#A^kTa?l_bj1K<1=9Ucks)52m z;{extvau^~^78GZ!Cm>Feb=!NXL#J>DwKCkA)h&;#L1 z2R^PM^n)p2;5bdHGFht?{46O(J(>y7B|}H`Pw4}&9y~HeG_vkSt z6ZSV^?5me}gvgXc2`0XE*1@vK@aM}f3l6xF5&wQDM#eqbZ9BOCTf>|TZtk}%c~Sgq z%{5n%b`*_iT*;Vq1!Eis{H?_>Wp?^^kXro+%i3mw5Y|NL@WLFQ^EcJrA4xJF2FCnv zrGB+IP$&jI7c=V0eb^v&+7;SQEWJhx+*cZSe2&lU{Bl>&jl`@Yu=Mi+tmE*3z zS(Y?mZP+jG&mP9K1{(cd;c;7?&x%YeWhU-6AF~3M8oZ}MK#8$rj}O@+`{^GzJ7M6m z08aB}4Wqgnmq4BKF_b_=DDW`63`#}4Ua;n#ZUiT)C+Af7}AWfB>;^X{>*mvB&d@%aZGIX{lHi^#`j6cWlZ%;pP|6%)T2n#L$S(nRJk`YWnzL%fDg;>=ElTYd)yZTXiKSnZ_~SFaV++80Vvx zqfYdVI4@}NU|N=S|M3-(w>(jy!h!}td!m4T+|aGpIdweWX5VM=x6A2Mh;K`%z2V@& zBuJL)@gq~UyOC!Lpfc+#BAmHL1Wfd4I7V^u>Pu+G3w;GPNVfivkT8gBCdr7CpyOw) zUv`-*J$gmvQ|r5y44@-ng1_z%#DT^|UVqm;z0e&;NhF3pl{*iie{8KfPst8+NGW2u z-@}2>4~dwLV15u2H01aDg=CK3&eZ&i<}24>Nafw~TaYp)oLM^0Gx^cSl)Ix3`{U;` z5b|b9zTdr%KhG_wy%UAVHR!doYxZkb4@__}MC;+`BKVVxO#jBG{XuOjaAsBxguDa9)^#Se~}oV!TkkWmrEXEQ(47ivyUl~U#gMksIP>WQNeev5Eol3& zMyZ{1X zkT}rpi2)zwK6}6I0C)yK4VPuwl`bPM*w-eVjBZ788hu`a+SY(HgkU!XNf7)9xRrFx zfReX{#@_t{GqZ+3J*0o+?YgDz_nryRE&7=o7qi<^ou&QI#cf}k9tz9+`eSNu-yJ0{ zudi-AZA+|UZbpocH`>KiPaY>dhzT#hp>;=fZ(+kbSReXn9PX<`!XX&Yc1;S+BsLis zM68CmHG((vItTWC&qgIs;`V%}{WWJ$)ZQQvovnolU8&nU8KmsPgZpkZIE9n;YYu;l zEco3}j4Dwh)ZnVnVb)4)WZrQ6{CvFJ5WW3i?th&Yu^t)Dn;`nA(ks$MYf;QN>`7qv za5cSkb(2c-N!TuvNRGEaS)h9N!I|dsI76>sm%zDKbkvCRNAK%fg+u>K15^Y5HapxA zC$rQ!`dW?MY+c9->W6Mme8Jutc&!jPcTW(XU#k6 zB>?D59wk!mDnJa34qUJ5c@$fUkYj8-zmiT-;>PdAi6WXeiD+>v#}q`uXC@NCJM$D? zKI?zFc^(oPIS1u_1Ju&MF|UCReN7tj@_^Hyn^1x@q@DxlpwHGw3tTZ9bF^N{8$d^s z7<-pcEbc$9PHBN*M#ptjv#P|q82kYZVTT1W@~y-7daHhi=3oAJ@dor`Ds_%WM6m=K+}TH*?DIz{j6k8EpE#ukhRxm_-1wqOJB;%((YyICcvdacXij#1-2NGp z;{0f65a1cig?;xfI1vl&jcG`xPpoDSpa>Q2kpLkBh$*gutml3$Q^Yg3KU-7In3j_f zU!GuTs2MSmc$&yvjR+%mk~6xP9P@meKd}4A37kD+5Op@8`ED%}Nwo?5kORinp|1&k zf`*-^igRiq7KcFcX^`9M^yJkl=`un4qZAqb z^j32Jp7?%sDyU6&pI;YLL71Fy5tpGHX^fAK90j@RrKcCX-d2q^rnG6ePJHM&d1G9= zSS(ZDtB(9|*LK={*37w3; zStz#%wlfT8uD(l7`r-F{bolu)G4<<+wiEKSpTPy45LWPR-gsJ>oH+}m81wtJ50rp8 zJm|E++%&9y(vPIUbGnr^9~;JDjSI8^>oQbJ@|l&HX2Sj@M?Uv#?;`CPnz)Y&kAAt% zMy+cV04tfO^OU}YM@LUWz#HRG(&GFm3Va@jhruFQjg_ua0&8T!Xb8L}Ix4dVq(cH`nCxeE9 zxzJ{H6QAPeXY|p$zTSc4O|0kk1VAU~f{0P8=*7WH-jY`> z&KsN{%u4Vm1`C?I^A9AQ-7*Ozzs_nPf^Mx^SL#UeHDX*fy9>PrQ6@KyCnp(D$P60# zW0PQv?mXhakF9WMpY8MGO_XXR1!!3M;t3>psFicLY|8swdK2lV;9CG@L&@uG(MnG7 z!dhl4SR)L&%&N?NAW_xm*bEMJiC9=E1dz5w5KI}!@Ss4d@ZZlToulut-c9vw*o)#} z89TOeoORG}ANLGWCHBl5{aTjB9JB`W&DLtLGXpz*lsC329U)35WC?4LB3Sz|lqnwM zg7*J1FKXOFWOIJF_b_W6-xP1AEM6ancsLtzB%`+lMk6HkUACFR7D}Akmb~zZjif7K zk6!6ea5l;3$Qd4KPEmCoV{f?RqJDyrXO$^9rl_AsC_hbcseR+DR1?!H+?Hex0%P4= z-6UY~a&~|+dxSz5(GfM#*uYW*?#rJTZaP6nNAS$lBjgyEz0S(K?P76+;_bQ4PXsnA z>!ax4fo)N=r7jK=*g$Hbv$S7iXZ=@m=XaWRhgH6V8atNNDddURbcxQElf6v~JHpV+ zEQ)KI1X4$9DQP{jSnpMM3ffld*CDE)qK+&A zK7Hu8Bs2aG1{r4&$g9tx=vF<-&X1@K;qi{giQty4U&kFd>HgfzX1L#gSB>nHz*g(&P7hPk*{C7tzlef_dE~IDmr8rEwe@b(L28#g7>VVIcxABw$FxAYQgf(#-kZPJ7qpU zVxZA=-qU^;T!7~f>S_h_YCW1MWV?x@N6i{%eEGNFTTgD_52v1lN`i9=`V9SbrDyXF z%EFIgpEi-~54bnc+|N$;QEej6<8!FN2S6sr=N7EgxaA znGlaZaYHWVDMKY5*@$ne+0VHNRkiL<$GT27szU>@W;_cw8^hfcZb=Xe1%V+%M^Tv^ zztZ#Jc4sjS(=F$(1d-jP%XAq{D5jT2`^a(NiOXJ}{={Ahf38VUMNr;9LBgg|?PA+# zwD%)!-;F^q`c(K>@f@A{S^LzZ>WgQ^=CpW*jrm-5bnRw+r4I#dt{Jo65T}a~5KdWX zzylBRCojUN4Ib#2CB-HckH;_V&vc0bHLFtI|=%*kbH@Unp=s4u6El zu47PO7V4_QyY;E1e%?6RF-3gyi-{jpQBtl% z#)!Jr8uADRXO)n`jg4(ow%dr=4T}o>T$OwmzDjlN+s@tO+!+jo$SOklx*|47Iz07M z+}wHFa5}#l(n^lUJ8g9${^hTzv<-DU|^50~l(0Hs$itwh z@UZ`5)veEN@F5{}1F)K^R?O_vY|A0c`^xuOL$H@fl4)BLAEdv44PNZ8cY0~h`n7RE z`<^5t*4Vz%b&yC#HM)5zI-mC%LryJ7!q*)NG^gGY`zjcrO;vMrQni!)#6IDeuWybY z_lC%|l$rR-b{<0B*C*NMew?T@;n_~GRKYFoWAo26i~-*aCi z*r5Saqa7bC`eoW@Qs}`K?zSj9M)5 zdWZUd=T&wjXYPQLe9l?^&&B^1tUr!JJ=LwCNK>l$PwCNVa3#3hMZp(sTPG@%1U0Z}Vk% zCl2n2L|{qV?@drk8Njr39}SUpNIAX7J{hw9riFhQ`kH5?zTzY||~_kb%-m54dP*|y*JhUP;*d{MenwIEX|R@gWW3%X#t(^+uE*3V!M=))d$ zr9l^>OZ)JH4+m32L5xAYW9v560ZST&`^0qG56_&7Y--;7`}M|iPD5f{uC2S7HO0E^ zE5sh&fCr~FOU6jN-M7sJbPrnX#SClRq0g~HSdx;L(VX*GTe-MlT{(ddOw(5R{OMmx zc-I!!S~E5F;|Tn&ro@)4R3={V0#SSLd;(?I4nF+j;zOT&+cS%RwA7Y@$!B5&XOoV^ z)%>e@8Gh#aZo2dBAapRoDB|FTkUU1{ZAt^7`W z#fA$9u{8XmnwTWCp&x1UqC9&0TljTkn)Wc-Pwi zh#zZ&JE)!}w0gX1*+kR>!41z&DPBefUb7;%W5#=4XJ+M;vw()HTF0XxvV6sK;OC=X zXMhx>?x%6+){cK+F<2Sr_;VFF@g^4epx@|t6K**(*vu(`JIL$i5=c&cE*U*x1sCg0PQqA!GsUb<-6 z=I^H4ixrGza}UFBUe4@+_Cm9Ck@%m2T?M{0hgEJZ!n-XCcQCyVwE2>9i6!Nkv!S-u z*um=Q-_7Q)WrU{ZeZ8@g8sap4w=G!zb#LScy&Y3rau3)OmMa%BQZ@gT!K&$8!`r|I=JS@{xiRUR7-Y0{Z2@*K$Dfe*J$4!A&?C=QVx3M9e@5ixp)}KL9hAeq-f)zS z%T(OPP#`@<2C%Wav+n_nxdT=dI>Z&^cj{6VR6%xi{mAgg&yH}O+)?;au7X`icu$vz zGtgYXmGq{hKUNmj3=07zL>7Ic}mM9bd<(r!6fZyUh$-f?u)`wTl(5-XB zMq0-{M+L1r^b}n049@?aiT8B*c~0{gZg^KgW!3MnWe2RD1gW2K3;Wmaw4CQla0L8* zR_9QV;vIgpD__@j@fT9UwyvdGjE`kkFSvrxg}YHBE~9}))+Yud(&17 z`?PU|;muDS&;W>P??*hz4adZ{jP*!s+rxPc`U9 zv51y~-0I^`A+)zDwf#kbTYV&2*9~#hrH5ucC|112s7&Gxq7TdV#K{aeOKcyP3iN5< z=E3>Tk|_KdAkd$)F?D?SbU<;4k+q;wrnXyt&7ep*LJLrh71By-@t z>(U$>X6kHz9;B<|MlGkSv!mtrP z4#2_YZDp<#GXOgAp}3(neCx~VE9|HY9zJZq>Z8cxcQetWqxjxbzU02E%^AXp_;5uR? zS#KWPf^R4)A#Y-HTsYiLs3z6vsndl_2 z?mYV6M=)z<$*xBBu6~&&jFC$T{HztYB4E_Eh$4&4nS5JRcho;gF;lPSPNiiiJu0J6 zi>C=txPR;fCJb19lpju-LJZ5*rbBsbZSPK6mI2O2*)cZDbJFQIi<-Of_t(SPZ&q^) z^r5ww3B{huj!Rh$x&F6zP@x(gWmcJxo{Zn|j6JL60i%WxsBfSdB~r2)5rhQ{>9tFWE)Wb_me3_iyL$r7 z?~0;yU`Ba5;9HSpp{yA2tLRMFwDU~9x;Y?jHB51yNxVn;eEs+Tj~ItNU&~XV3oauB z#+%WC_>i60l%063VB?-B{ML)>m zLsG^42(O67g!u?TascAx$!-MyLlirSseY~^CYb=C2UU6B{>^Ga7kdCjc>4f+`@LDJ zV_LWRG(<-W%0i3);WE?nCMvDr#6$L7;NXSeX_vKHoJXS2l^lVW5(ry$J}XJO9c{o*0#R=MocMBN8+63#T_FS`XtfEtVhA2b`yXx zPj-W$_5FNx5Q8S$cXltx?HD?)hcCN9nt@DhG-L8jMjim~^R=C%iZO>h7MdDN7 zaW4jJ0MTl?T*2du5vXV@`klHdn6-|m&+9$i$4BoiFUoT6%?uZM*yIuX2%YuBazdd# zJ|UJhW-$JVZEMt`nBgjX5?6)U;0Z`HSVfa!MZtmBBrP0kx@Yiff<)KN2v|5Yh)4YS z&v+BErJ4ZHufikuBwLZ^AwI+!xD3K!BpnJ=7S;0MG3EEDHLGLLlZ0A63QoTd8bnh# z*lIqQO&}iCe+WI2*=wLdcnfYZZ;znR5D%k!9(hBqy{2Y({?;<|AtX=w@+^Xg_?ZQX z_-RMZ5d+ak#~QmYS?-;$C0-K3GzT^<&+Gy~x-5U1i;u zXGV06qHOM_O#V#rLFe1TRP*3M=TomeYNA3dCCSY|rVOz7&_Z{b2>-h*klFZXSBss^ z(^y8_F&XHAa;vr8QiD$LW$XI|07l~B4;kv(b9Ch<^5!0#!R06P+u%K*1Yt6Vzlv6w z9_Dga6wKE+)xb;F?Ni^1%6xy$bR6*q?9E%~j>I3uBl)arDczb&si0AN{Wbm1B0F%& zaqC4ipT&)H-3|2jx|VYw1ERd4@{%CgMI^Pj6N;f1i?#|k>KY{Ac{=Z~i0$hKUKsA} zVAL(%*RzI@z!Dq{eAC{%9nSn_`FpCIp7%8lhKsWk`e~IXUCee@&WUir*;jab=+^@trogVe(kY0u>=co{P60@8uCApjY&8UG z##xakBGQ%p*8b_<8Gc~}Bo=2P0B!sZS(s&cK3TzSK+0?vy^HEcZW}ld(oPs3_N&$a zYPQT9aF3Z)=-uaan#=cR!y!v7LscGFMqfW|O^2;=REA;M?~g2;)I=g%3HUg z8Oo4ZqGzh+2P$td_ut_;AESB?-8CRN&`%Uvy=TMjWY*wLD&+Q(%Sal9O08}DtZKj4%HBe2}3w~ zYUj*Y>6H64WDsTV`m#Q9{Jrb3Fwr*BOqFK|VX#%U7qI#31KfIlT6FqHk0A_=XihD* zNd?`<{e+Am#qkj8zGBuAym3t{lGXPx8FTj7#9-3p@8`2TzszkiupQcD3+&6SI_|Ml z_kIa=FS^0ErLfOb}QqQ~7G|+-3 zVk%6@eNzy`^O?c7&a$AEskhi@ea{VLgIb9wP=B6-6H>+Z*}I=*P<7_7c!W^@z46M* z^di4^)MXDaV1rVEr*2LUgUuts(g%P4W1g^7amw_mk7B{uHH~ZYxg@&#ste9e;{>-q z`*48^;|0gsPYh{54KODRb&-@kle^)qec#m7oo^TI=Yf9WK-AC_3-bk5b>ZcjL5{0E z(2j?C>iu>8p9bo`q1c@QeKjyJ38joCHnBE7AGh3=fUd{>NU2D)drbLog}v-;pzk#? zL!`gB3wu&%D}9-`AX58}(kIvQohMQ_Yl~4M*ypA4Cmeq~zAjo7GJN5z2&;coTjQUi zf_~1cOf~i3t3m8NaGVt6O~dy=jBhH*pdW8~y;%2dK=@9B8q^oZ=1FfFqA}*fR|6XG z&kX!noJ~UN)odi7#?D-`HWwaQ*_`~<}`GXV*E5B1RdmY2(3c5*`MT9%9 zG(b82n)BjQxNkX3=us$*nx8Uk?9J{ z)OEyJr?p^7VjPzrTK`C@{JVA$R9WHi_@HqKFvvLZQ+ycw_Mf6pRy&c>pSQ1Ba=kSk zb&lo%LfSSFRVQOxTg{96zQ=>$XKNM!S=YJ`m`{lx>7&=gcZjs5f0d}OzYz1lC1{%f zI9~a~3tbtScf!&r4Eeb*HKt zl>)PRAxC2x9ZNnamE+1okzc&W#@{F(xoF5_$QP`4G!R zu}4S5W}_*i{a`axbNk^~LzKfr`7SM&DA?DL*$p0Knl2;pLS-BGihK`I+6PUq3urEY>CHmz*9TsI%5E~Z zF;6n*);}>}Aqz%MJa`zJ_`R6X5N7j;@u2~&A6i=f;YWd9whqS|C;T-RuRodIP-(-Yud~+nL~PNY2-v`Pk>jt+TWSW|(ko__JUcHB!>ugPb zyLQbfPMO7UD90~5=WpRj!~-{RNI(>=m4*+yB)QeHoy++Ze2XvDeT;NKhGYX0hhbv~ zyZf8bhaDe!ibOS22(3nxTv57ISAvD!*c5ccyX(6}L(XSNiHp)fgpulaLwm7FQx|4m z;l34iD#{xw^=nH6e7^~AqyE8-gx}~TK)Y1M{ixL{wvgQcg+D(kE1@;0aH;lW0_;Q3 zPVGNS#?O{Ohj^GrW*|sfD&`N$KaO`r$nWWJy55;u+&bPJ(^YZ$(De+pOIbW)J<2hK zj|ynd?a)Er?Y#0`?cadz5bu&}m{^G2K^-2F%X3%1d4AJaE`JtU)-p79pS?;PQ?rRG$2O8MCG&{d|cLp>5)ddrhj3oQl7 zoNwSfx5CbLzmdqQURBe)669on+rKBn&YzzgQ7pSh^ z5N7RaS_rY=7~LQ}D!MTTlw|a!Zfv>Y9Nkk(BN-f@A)jL%T66r%?ZXkYhwcsg+KN zYub6S1P5F*dkCCsY}nUqnB0T~i7(GV)8LB48O$o^LqNA^9}v%I_HY30{wB@c@jU)@ zdB z2WGJj8l&*K?IwM~!s*8TpGkX?Im?TwY`IpcPyL4UK!a=O-gkZS4%VkhNI*jr*+tCijc0gbN zLBny(Als86e4CJ!Vx5MVv+BNT=A4^DX|LgUN}o1`*Plmq&fXm}w8(>a|8Z6>jeVE; zGOZJf+1?8ISo!!B^)c4}yKOT)DBgN(Z4S&wa8xs;tvGl&RCb8(-m!5GfBaY3ghA-B z?IVD7FA9&u;?v~OtI+YA!?3qK-ku4pFf*U^r7k4=s99aF+8FIqSB!7 zdU}l5pjWL9n^FLjbI(!E8&ynCzw3Z6;t9rsBEx?>10(&I?abubf8EQOVt5G-Ow}Se98fkONyNUwYm2jOm;>lexg|UA5KA+9!`B?yG3r@E)vI6K^>E z>l}Nmafa;4B9ok2yl+$1^S$lEJ>|vhdWL*Bjcf*>=No(O#!TR=*9`y7JM-?XCL~7( zRkLup-Mpd%Ej1itDS}thTi}hGSQ;=<9bcK#zheo6HBwL~Z=dG+tzTUxF$SUp&=pMo*B z-tOqvwNJ9klIGnrIr6cw%I+rd%f5CWSoMaC*njml#a3IKPhJ~#EJ?j3!=dZNAmn-? zpWw(6NFne-g>P!R9*!@yS%`$6&mhpgDUhV|&7ciS;7eB{Xz77$&EjH!u#2AEuFi!} zoY9X^O8y8*dgw~lncy!|k>4~>*906LeScF}1V2^;XnkHvqYnaa9oTYcULdyHkI^yj zcih^Yprm(tmnWXr9$12cE3aOiE<7fp{4}hS`n8Pa{J^(q=V`y|p{2|=4h-CHt+kWt z-Q~GF!VyR6h5lwLn3YTwXR#kQfb@{#J~J1|$XNqSWaTde)x)V!58sPOib1njdLlsx zTK#h_w^4nugBXDC0;W(y*{O_5LUH8WdA>%2HrDjYx@}*@?Wf>u^~1RX-Slf(Xn>kn zUkQA)-H!Urvw?g$hR6_d_$2OOLX=k}ie2tu&rf|^`&gy^lrg9HHnL9loo>ci;c#`wVNBd9@$ zLzdEI;F2yC(|RKo6n!~{!v26AwM65S_GOO5@mM_UXzl{!xR>7R#cH5d;frkhE2Z1ev@qxd8E<#-ACxCW?}U^`>Ta8c0Z1k zlPJee%lU2wZ#&|z0wQaTE9jK6Vr|IO1t=y6v~kkDmv!0uIF%bvc>osz`<4si$(`m( zNvzJ}Wn8oGzXx9={H}u9VB81VJ67sx2<%2Sc_r!i(|yW&rk1U|P}0+GIhJ2I&qFml zmDQA^M=Jtf*Y^TtFA@g*COln$ymLb{Zz0Z&BYZ0?q1S?LA^TKal{C3os+>d}d}5ZH5;*&lfTA(~{_Glmj1E{w zr1LtCQrO!WxV2O9II-w*HeHTB0_kGC02gig6 z`)S3ib&7H>ICcn+?<33L`L(Mw2Co4b?0&(aPxp4PG%YtXgf#6m2FAQnQ1?qs6WK1cjZ|E@Mt1W#9y25&Kh6*@Cv>(5Hd(T#| z|MDgV3N3X0eXj|?%h?lL#$ei@vlT=fK1_2*c)`q;>1agYk9F? ze_kKR4ug+=@SuxQM)GKUAeu~s3{el$dCxD2RKG9GeBw#7+Od6IJ>Fz>8mv`yW{8b_ z?239@Z*8+zPOsDOrFc{gU9J78oEEULIM131D@p@LY5*as6TYiUMba;!^{gMNBscjZ zugWr*lqo)S+VP$l#Z`aA%_`}QlWNaS!fR=L zZZd|h7zh^Mr+T1z;EHf3sntCi`*a7Q;iS#EW2B);Cf1fq=mW)LM-FdWoL8Ac$6<4i zW`F)tlN&54KcE-Oc7QPClSa!wPhn0ii&(*TF_+|iVwuR707t#M3C%lIgZy{M{w}Cx z*?r}6rf&qDzdpXBE=ODlA4hftgZkrSnc=*uU6Xe9e)U?^WW`lxjxL_6(tYS0QWahIvRB`Sb-=1jzD?*jN-HQV_ofGjop#nqR zhp_W~Kae-_d2nX>h%0&n=4BHfHj3~MmWlomw*!&)1GfJunuEF5hVF*uZS|U7pa}g4 z+PAIgoY1p#P5n415z-_T5QMrF|MVnd1(}W4;rl3oI*^}$Y{AC@<{grO2LqS`YJ2A4 zMhnr>{<0mgVDGxv?sJCHo-rgA3lVd6srR7tO$i3At4T3w^2^L*l9(f7*?OHD-ly~n z&kuVp@$2C<`GQgozyEo6i*{m8glG1m=hDOG21l#DgRp$;+{EW+SGTeGuzTvSJ09J6 z|BsA`=V+~^yfgH5J5+Qq{p2}`n|tB$%V9HO{JvrJSs1{+ByZ) z>WlQ8Tz%iBRd;~k2hZvJ%QHA7S6{u?sOS43%S zqqA1E(RPL8NYJs-(0z9Rann^BCKpuY&6g!?Bffy!WdnkTq z@|RHFKKVfNF)YXA>ifOng~npd4v*3!{Ui7%^>f%Y`OgH%kx=;K*iSa35MpE+QI(l} z0>WQh-u;+sCA81Z>}?r83~?ocoA`&7j8!?=arl8P*8^Y~Q#QpNs%;ZB`OVp%DRS|9 zgX32NjDGs1K4slYC&NC!fR&!LQ5G<%#_Plylzo zcOu=US@6ktDvezCIUL*{L?R)_%b$9JH(;7m#sBEP?R7rk95#z^%T@j-E%=?J~&{)tORn7rM6YzWozFTc@8qugC70T#E}oepBej8u-3O0542V zs6EQuG-gRn1dQ`1QLfRC>JVj3@F`=X&AT*EoLXN_Dd`H@E4x6R<;LqVVQ{NDojGN)wmA_okwywFMwR}Eso2P`NF z7*jOD>DZXOMRNA;)>XbH4IE{wqi>X0E1W_1ZZ{t8=NxNd1#5mmjqqD7 zG=lA8qe*8BR}JVBPR(?nxui#65$WXfTL=Fe^uY9;8w^*bkq0^Fe%1J9zRJ zbVVhYUrOZ~J049&sG~PeXH3Q?N$Ng=bU>^1of$|P4s~+=fp#zOb-_nZzkRnl1*~ul z;K(fSk1dxZkM`2*!43Ui=wxhhn{Ebi*8f~X6^@}7RM<99rsIr91k`8GK}aqg4@$r3 z=5|J(!7R>xAT9>NHS}L6frkJ5!9~=woNuL&upB9PY<%9vyz+U z$xH!BINuwdI%qHZPXyA`P@$L(1#qy@Qasx59R61~H`9xY>PVgjoXl(Q#aLK+y}Gu2 zU88%=5SHcrIW=WtytNelY_qs?+JuB!E>-Camdytq!1wHICZm_)tz~l}IL1%{uRU3z z)Um{-`jjkOxe-`*4wDHim|a8d9FNFpu5~)4xokp}NBiVk6CU^~44z54BkJ;sLU?gp zc4oQChTveoU^Hg_h^?^aD9wt&A|Pzy$&>zMNUnr4O_}H(fP3+MlU!$3K-zEi@0Q@} zVh?1@tQUrfR6a;*82xSVdqogI#&gbbC8FdBE~fy+ zH1K(aQh7J_?oDbRFG9f+FMUId;0;EZHU0TCd}P1>F>Ef2JuwI+r^Y_?lsy+LYbUfI{o{synKap@F3FgEF7|V?`EvX1o z>kEBV2ev)L8B%wcA6PQLx&8X5{h?$ReQjRtVngcr8FHl}dlC}fhVS1u!o(E!0~ABe?%q3Lk0`?qmQCj zeK$J>t{FJ}eTxL?&F^SD&hGoB{}c-LjFuMB zh8aNLOg74*#f`Vc?zFC2Z+BX&!*;~WSaQG6=l+nz6`e!FZpeG`eyjh!!#h~04I77= zSE81ZE(Vj$z0E4AP4$sGuyAtyvImf3P9EgnK{oXKROQdi>&V3K~l`W zsF^@~=j&I*m;eFnOXx>FI+ybVcQ=3;W7!yNFj{^Tu9Jg$Oc7`xv1WD*7S}xgQ)s0d zS84gx>oaOniu{pmKNJdTz0U(=Es{!O3Z8uwdtX{BDB-1~$=>!ja??zB=Ji7S4V zfF|EBqi4Fs0zqzW-wXVHI2L*Sp6o+*H?HZ$xjs<`d`|O0x*YBf%^LnVWmj)r#ZrhL z%)8ivk7emq>)l*}4Lxs!)S9mFuB$6%m&&%iBg8vMAHU={J=xzQDQQO~W{StQl|M9BoBN<114YiCu+v z_@_hA{mOS|Z!nlL_5Xsy;g^%6CA;O$$nZh_hm3E9JInp~}V zhj1)tJOH%d^hZ_|xEjCjU7+45uK}m~z%twOk}Ldx)2DhtlYy0gT~9u}E}DV!NcEQQ zj@?T5<@INN3^ykGW9p%a>%h^NyDP?vyldk}gt4sG@YZzZZ?{j2eP*86}r6hp7EvSaR|Jd&9c+mmMCfIoNX@riZ1=Nj7|O;p8sRM+sE`D z8MX?Rc&+#nw?e!X)J*Ep%~@XgwCGKL0f~-<-WEdL7J=CqxxVa>Mf+uBzNGqqLgKsq z@wPHfqxc^PS9ZmfiD+3)_a53?rWM+{Ck$kWXz|&JVqYqDJ z-Ve*ti%_rY( zf5FNA*EE>q=+X>Mz=r$1o$;vkwzcyt>RYc(*9Qvf;DZQsOKdK$Y;$iroIY~tm@e5=op^MTh1y9u_umz7{boK(ky5HCh-v{SYv)QVxNkc1}D}fR_ z(;enL8@F647At0avSjG_$fO{Kf`Hf7(~g5fC9mj%gT&{h@07i(h)Qm_YLr@+7Q8%? zyI8wP!}ZWR{XC?jaRBY*qz*;S#8}sq9E-nUU<|dRe|(V&+{nkmI3|AlfEVN)e>kT9 zO#cUz910wQdp3oD=${KIzQ~>U_R=t}iP)X}NYTncp%m!WjiPSf=0hjDYQrOZlhW$` z*U@$oov?}PYg#uVnn8DUzKTokw|VaCq7MYCeDq?WYljmD`ht(GWCK}847`!bOZvW- znd2kb^LW+q86leOP%_W(Vo??Hv{>EI>7wl>A4CZXy+5_*XtX22?%ugIKQX zh67R$+zE2nh*hyW*a+*;q?mVoTM{!!1GO$R67pSI-XLbJP!gmQism4x)e5pXAC^9h zEA1LbXxW7EbHP4Kr)b6+LBg41}!0qk;bog}(N$;m&{DJ)QhD5={6kfuEr@d#$e* zN#{&&xmDgUyjWNK_u_n~eTi?nnoJ~Cg!acu&c1)So>B$}LrNJ9W}<E6H~eZQhlcr714N%G!axmf-P2g2TaSr>U7*kXnaGBfD|7y8u|Bzyhjd7byER`BFjAIenDKP*Ezb&Ux;zpx~UaI z&)xiXo8wC&e1h_Iy3`{xh4!BUH}WTn_5qvIOsVySqRP9?c2q0Ya%5o78=9E`cst81 z+)KhAED+A{@y>fF#heCx-ow`o6PMS7RQy{sn6)h`sSkA-$5?#5`*qyKf`Cph^TXHm z#1QiA%<=JtHm**19cdM`U_Vq&uB!*~f_bz_>%cY+fe|MZtG;LY1beTvdkQ+N5|Zbc zq1gj?*AY@}48BKqHL%BqGS$TK7;j3Qrcf&)P4`@wqaY7Ar@xB{Q}Uj^-4=LktBQZc z`NelL>TcF1rsggs&8}-~(Q`WcAE)XSMV(hG%FM}0dT679l#R}js?eq6z%bcl`C~tI z0*+&^5GZ+rubf8Uxb~qh>SRCJdh%-g`_2TDJDbFSY80UIcQcy|y0G?7pwg(7 zm)$J3aV9vkKD><`3B4M>CD|y>_IIT+Jj<(j1{!bfvV;OHHb<`nGZ>PGL4${KW`x$N zr!}C8ZW0C}UnJgs1p~661Gsk7mCNN#jbDD?p7S+=m)%tUsdp7k{Xo)QkgZ1p&mR^h zv{1%Y(tj}SzTXb+H$&InX?*9$AE}ZFR{65U{yyfo+z#=x`6;A7w8XikheFA9kI11v zjErX8qBqn7D*!HrDM1o}gX^In!=&eL=y@NV0u)L1H*Wap04ndrY0U~wU!X2H4PVR; zc!*+K&qT0QdZ4AE5ZRsKyE-lQN|5|HmZHG0H|7+J7hdmpJg-=7nPx-2&i%3}>6Wsny-C^*EASm3~eU2nL8J^w-=^`<}I`oSm=vvdbgNKPI zMlGo9>u|oa+=CcZ>P``uriyDf&09g$w;OQi!#L|bXpZLHbzS&jXxxiS$%I#ducJs? z1ga<9@&|nKYly@=uPc37O`SjEJ~SN!RaiN}RKE(fhv#;VYAuOZI>vnGHzrwlWGWew zkIub$n&^F>77LOeNJno!Y~+ht`J! z*mxYx*4(z+?z_dn=3dwGXB{wJ)o*hZ(IBbUT_T>w?V42e+lu_pY5t+i;jyly5;5gA zr(+-_igOk>}P5DPdcHR=lkq!MRxD+E3r{IF!08Q3faJGxCTN)vP zu=fL7wgA1_)wy%`RhSv?UkSnjEff;*c*KCj;(5vm$ClMkXru$FEI4i~)tXh%0UO$I z6w%N_YT5}!wO=!Q!;E43>--ZgX-;e<3i84T^7kPUg#Vat3g!!E2y{>Oi`Z9NT~yUo zz-{q_2c)1$T!)#@rE4by`WJI(tl%l&QZTx-{uy;wX*))Q$w%G~NjvC60Z3lQM@pxD z3C?~Z8S?4?-55>M*L_~hAe)-St*ZgrJ)1RIqhHqnNmRP0rh$O(a#mogq^>O?Y2Wq} zp4dM0QtX#Psa{q?{2dYVBf?nS9=zwFZevX*_1w+cDE4H0S|F%<&pWJAg6X``PNe@N z48{A1P&blMf5E>8>l&f6$59T)v6da0Minma{Of@1q+Le#hEUNeR|l{791UO~Os(K?qW+$ozA ziDDB`{*iLgH9W3Y-bM$#OAN5U#=B`G_}ahZFJg2Mn`cZ)18y=%x|=9e$6Q}a{VhhI zZ|7CwfXaCls2EohqDNP##pAWT*DihYfA)pPwL#MK9&l3ktE4u+s|ZaQuv~(LYvaPp z?HF!q{4SD20@z#iTr#uDTD8Po>oNI9I&07}AIfi*`8QUO>+v?(>2R_Kw*U0~bq4d( z|8Wvgwg=Ha=3#PrE13`L^3)0516Xp7TJeV?&$WFdT6$l7Bqc48%{dME`6- zZ^@HlnW@PB@#P3c=$brpUd<1(Tv{^}PMj(9-n23nEsL$;InCLXyrXhQAzn19{SDO{ zYN$w1al(j-UzElw>YNtW7pOnC5o6;T1}Yw5#aU46ba8a?{@qPt-O$oL#Bq=_cl!eE zgN^vBq5CQ2YFqrb$QN}7Xl6q6k$y-iNyaCafmDfdQqO(jI^`oVp-g;BZ+xR{e(!1N zUJuHlfw*QTYe{+LMmwGQeCy?r;Ixmn!+ONV)vV8D>Dt*1b~?M95c!9r;*z6Z>3fl> z+7;!ut7E>c?o;mefuv9nxSM}7cX$uNGhMWPs!&Xi+Byft7XV6WMZjoB$jxZ~PTmvj zZl+iYo@?{tDKFqAYQXfrJH*(wdVnXUCbo_COAB(*|Lt2r0cW4|g$+oanV5hX)3h)& z{i<&L_$<#k;G`<#cXO;sx1He@G0|^p-LS&5nt$}|$54S3`MR<#+L@nrPk|c8Yu^9m z88;QAhGsZ$GZM$E@>;TWrSiB=w{8GJ0Y{X*cJuHzl+79ssIVM${E+tm`T!XS*6m^` zHu%!LF}uabGZl)Ufbaq}kDFNG@;a^Vf?ttBU^%QQE)S(Qp%Mox^(BUD3}toDMU&3+ zvdLn4Q-fy3MWul{>iL@#jLuzX^r|&Spa?^y+7^@C6u_T3>RvwHGYQXUxRIJ<*qBZT zgO*C%QwXF~9qbAkmONHCjk_wd9#Vs>Q}8YsoX6`v|3Bwrv(9g&$2q+=ekjE_)rrJA;KL{m zn;tD8@7|Nh^I0RDNr4W>EzdaaF@^y*-32c6Z8~Q&>lzyBnWxUP4pB?dn*avem;AX& z`KA%CWM;hT|NSjZTf(F>3^DNtZeaP~{*Z{UNE)j!Pb8=Or<+cMOH$Dd4G7&Y zCm{L&mJL|a?e^zxOGj*D<^-&9#Bw#Zi9HQui0DudEZD6+c2fe~q0+G}$E~+QGhL{O zjreEu)zqUeqVUFYGm#K(%Xpg~7|c6HDoxy#daUSbmM!}xKXEQpU*@I0VIWt#b#iB zpekN#QpzBpH!+NkeUo6pK9oB~^BJIpo;#J}dMx5Rr z5gP<`{e#_|XJOj)a3D8k%qInZU!iOYii7XEj~&4ZzWu~HOdO>#x4iOpXeiVM>7ulD z;X?c6^i#>iET_zcGj+AX1-%KcE8i)fM|3{=E)$gw>@T)zRsZE}!p^m10#_j+L-hA0 z!V0tR{=h!`m9@qqAR7*3QU0LXf$x7##$SxSQ9Xuo_t9J%^F!I0@;8DqxY2)}vXfH% zz5QNGY462h=`q)P-yZs&Z(T(+4Nf0p==1xXW2v=2Ro6d#^f+u_JpV!X5&mzJ08@&l zNSubJdhsSx1aB{Vm1NK&1in!Yzw@qpcv}9R=7VP*`VY5IH=p%_zah$#fBdvBW^)za z>2+Ht&i>WeugDV9H;QK!pe5$yr92=`=fp@ZrzHCO=LYg7*=M8y5(*apSDE8l%BoTvO%|y~Lu0uma=W z3H*D_pi@icGu(RkRU6>{BkjGTqKKAtaTNs>35tjW8Bq`cNs<*9NuuPSB5^=OauSgs z(4qn&;E+MmNRS{IB!@vV2n#O=|JOKG(C61%8X66sdK9*cDdm`E)ptv^QmO44cI6LwI|I{GPemf%x`ZLP+%osjjzq!GJ^`N->KXpjE@5DB5MLK~Y@Mp%M2TisV5vH@| zO7GazeqnV%KL*Kdx*d0c8z-$v(T4r>8p~shfv0wAWwUH($VkJpP}@_~i}NOF=4xan zTC7GV(;RkAm~P}W5i?K3!6+?7P>>vLga6vre6-0 z5$Yd|-v&uXE_2)&5*Pk`-*gGDNMc#$!$)rDoZoE3?xMXJ4Mr|+zwk1C1|(&g`SD)Y zoUM9S^3~LB82e@KU@it6a9A$mA-fd>6@gvrNEj!P*E#ph?ua3ki4k#v(yPc6z@)bO zSe}Q}?Ab}ypH^)^?j-=FB<*cg1=RDxUuf=CrQds&{UDxN`MzQA6?QG0K~v9aMpr+j>$@dOacam5BU+P*d?tbD~GVw*b0hS)JTI{C=l zvgmpA-m@+J-7~n;+D&#bhezydT%QFSFi1f=65uVpe&8ltjTqwBc^vOPf)o$go;X1nkKbWgM{bep^0ygcBrt!fBC&6ujzD7un>o(=!?zgg zzgrx8tNIrAoEG3J69MV)?nKnt9&XgO2hZy-8mdrtxjLB01@+!-b-WL!D#yM7FMdWY zSS*;|iF_e$M(>k0PJkvx0^F6116r__*Hw}#$rR8S3+cdhNUHH&CszRcM{VM%Wx_7xbTcSf~#vNU~A@4z2)9aH=)y3QZ(8(%0M{sbfkyoZS!b};ij z$hN)EU>c#i6x)eSi%8dx*FP_Z&r$d=|S z)ENv3^&8xKDG*%zWySq|(IQh!cLTCMCqk@$p5YsJsgU%eFRR{t32=#B7Wk_?`$#Nq zMN<8Z=@Me==@fVfmnJME%rp3|22Edy#a=r8FiZh9*V1Re7K!&w2gt$Ik&6$0DgBlR zDjmS$c@91}JUi8@e)Y`|zNcw>zoKrN_cn=}3T{bQzrRy;F=q%9x>KHqG`0a;AH=7D z9UmrxE<)=eUEjV*oSJ8U0VMr_!$d|(SA9B>KDr0U^_mW3kMXOAM&7fb^VI{UkMprn zQ@|ndeXO$MvbP0Kfl%k}9kI&fO=J(Y2c>a$T<|5n(Wh{n1JpJNjytefc3O!u^%jL4 zkE07?Kv$JE2TzU(>`IIi-_XtrdnG)G^3&^j*uw+ZR-ZZ(=S3=f6a6M3_iK}lJSrcwrtEKuT7 z#G=X8uh>R|mw*X?k@4J(R;1y&yrVbSgLwBW5AglNQu9+$?<&2Ta*)_l4Vz1!=51b? z{9kWUAeYqg7ViicyOOi{Q?Z&OjDOVlGZdvQ+$s{?$vP6Zm#imOQt4@#jP6={M&oCU z;p$hsG144!-*H@%Z$6YO*IWsL8}8V9Qr~}Q_+-XTYU$Rm3uKATSRoRXHFt)Pj+ zw2tx)l-r~0&o{+p$PJr>eE*D$#Y+x)9sr5sMTCv>#7b z{LwZ7zW_B5V}jZ%NngkfMnY{@m&hxng%p~W;et{kX7osVoEsqG7WxOe)IrUCjU-L5 z8~QmCY_8}!yM~=(m`4?Z2Rj=JNATTcrX4T2vPmNG7Ui0&`JLwiZ1P|LjTMNS%WpC?X|VBVK54$ zm%H$Z9Se^9TJJrsDcfB;hkuT1hHq54$DY^4;P5-+)^x$(Kj0qOYk+wcS~1z&#BkB5 ztLImcO6-J>r@csCcv4!h$n^F1EQ3i-+;|{%%C>PLm5ub!pkx~O`0C4jLmPhUrG8|C z<-(x1+Mn$idM4h0YiAQ$7zSX{SBtc3bJT!t)ER~vc9@|+1ZQb zt)Pf*V(wOh3w8x>@aLQOHlQJ8`I#;byMz0kXz4%)ITj?9nI6rfYE^lgQ<-@SD~-r) z;A~0AmVVPoWtI!$m0&Zu<+%%+EW35xtARQ6mlm?jW33;n_z!{My`eK)_nwqwL)}Lk zDilCt@#}t@YbftPyUaPKA~Jx_pF`m zGh)?@)FhtF&+PxvzSI#DE&v9fn#c4Y3Qj888f^z@G15;f)X(C6Ak&|XmD++ES2mhy zeFp6-AXT|Pl0e=G$s8kygj7vJX}QCkW!2}=lwO2TyWVspjr}Jsjpi$Me*OHrF!HAuR%f$griRSdeug@f#FB0Ml(A zAhd{bVf~Qp7|?;2+smLJIV{Y82eR4iO?Zt$Oiu%~{-qzi*x|4Pk zQv#Siha$0%XvQb(Q+^o7-c~k}nvC9C%O90cQa3ae4il|=E$rV2Fo1qWeRbWQaFP{~ zAYBvx$Y#EoRhynWC;Y@SuuYwcKR7r${4v=Y-80+zX}#$AL;KVF?Nk&HqC|Dv zxxawCpmr0FB{xAuNSa-RHeL3KPqfgtEy6EzJ(p7tyv+>L>`&vA;b5uxB1af#8pv{} zWl#C$qQ$@~jO}cBDZblLV*lO^LEP&{62SK>+T$ELlaBRCb%%VEAXx)j=-%%@F*$|T z5Qsnej{Meym5Yce`?I%fYkuggCrjL){%5%)b4Gybw(WehB+J1sD@O zGcX(R3FKAo2lV1f+kB|qiEWf2{7{IkK_&km?>^;r=GhmbG1T13_sw|T9%2pybU zR>SMt+F&SfjR~VC=@)ij^YgVsDJNuK8m|h?F>jOyli&&|2T3Pe6mxWOq!2XSBg3gG zDWoVcr2+16C+jl{RzufrkKcqIZxy=UxCLyZwxt|jN)(-Q)wQcw!yEqiebqS+wn47( zCFB-h0@`fxQzK#FlrxZoi}Bqjp8=kavub%2@8HsKm|YXQSoz>jKTgTxZW_LVQvEV* ztbpTbZPdRq^O5ntGv+tQ#G(m*4ej6ieERgE>(T*ZM(pz@^L4ucN=@J#r1-sM&S_n3Lk}) z+nBA`iz8B|;fUAkqES-P&S2QvM$=))S`M1Op3@>V8SbTc4KyVLxMt|qh=7VeXabPM z@qNf8*EXBsJ!b|e+5H=R44|+vHQ6Gf(6jt-^3j>3D_aju$QfZ1eHxJAbzBhRllOAg?ED-xUX4XVSL=h_u<@1Kd{sB zL$Ukn5~loiJ!CldkG#Z_t)~$$UbjFIaVJGfQ&4easp$G>?aiC<-^n@5=>zs^){CMua{~Y zA!2g-jW%a42`eYpGbal?f5TqBNLzCqrp~csEB8HA_sD<>+&{{?3zgaLu_;xp%_8HA zFssVzH(^M1_Q4X(0N<1$sUe}9FRqta!qurGc^V8B{Cbz#3F7PJabpyh^tO@Q&*RX<>B}Fe9%> z>3hy91dJF7QR$GJ+ypUk9B8SQfi_O%bCnI3i~;d^Vp@uE_0l$aVCKdj#8Yi|h-Y$Z zC$8uoV|>@+a+v@&rFqpF5V=AWX8QdaJcUT8aUAd0_ywMB{jv(vVj(Sp?zt*%m^>_( zf-SN|MHwl`crE=1O^B@h9Y^+1g;S2_VLwHx&`(HMXCHXFzd;*J`y6$E>YdLcV0dsS zQ{H_$r4FcQ4$HFQ#k0}?Y{PD@{f{F|w8k1R&pYAhZYojK^9nStag+yO(3JpHJIyvV z6&*Rk34%TjrIdV23hl&Yc3-F3X{hPo%dedmHEWP06%f^IG>nJ?29C%1dA6CFLXw(b zGX~p`@rzmUMaS+10)qTOC@d*`ES@d&;prra`%SUO>?Mup(-OzNi{9B3xNFSzu*T<{ zmH78D&+mQcAq5n1ck2x%vpZKJ<)MoX6td6VJD`I4c$`}GPxuyZ%vux1*_sy9j}#NR ztTUoBz@Ez*l(&nu!3q;gU3*=ibbnf)Nvg=zGv7t4@+vqARrH;OK5tVm;VD8@6%M^} z10n~f>QBuJfALU~U>>X9!I-*;K`^jQ`-mTwPPe|I~1s9%4>vh!CV8K?=Y`E&32G&Px(kE@NbVA2yQW;D* ztb&4%d4*X>u(M^~c>jcO`_a^!>vprR6pYYx4M_PbcOHX$S2}36;cRa$u*7?DU}**c z;FQ9G1pBcsuGs&;uEhecm&OTzqyl(5F24+l1W->5vLKGq{BgbTFK=T&kITCc^A~aE zDWyT7*bYqMs+dWT2Ii4E7zk7dU%l}4)*JA60f)Bb`VP6J)t5f{TtOtz^wqNT4#dt# zyW;ip&KAvD2OfBNG|SHJ3i&_jcmGMp9Feup)<>NLjIR!Pg5loIf|N+Ox|eSSneWp{ z9{7~i4T+|tCYBzYOnWj&ry^9C0-R@6wYH}Ks3G{8ZVwSDv@)_{2t)xv+q(Vwi%OWD{th|V!sLeXS?DZlV*4BrklyggXdnsMI0eo)Rv87L^2 z9Xn|V9_Z|9KWI}`j(ZB(FdL2QPdvXAY_%o~*Il;*yC<$URE6Soq=TR?Bjd|)4JbxS zkxq+^#)T8{N_hKQWAFBGW^7+fYp%4EZfR@SL%gTXh@xMi*%+Axda-hrZe+d{d>WZ4 zxAOiGng@rxEU*hjqq~R0LqCl(0g7?({o{8lp@DtF)iD?fTl)N`AK4+~$v$V=AG01z|gDGtgX&!Ow0?WRkQ!#Yf1h)gG~p@}|rm-hBa#-vrLe zH?JD0cZ@LqeLNB=X9BO4ZRq3Z9`m!H@Xp4kfwY|M!lPgwsACyuM{$~?EhTnF%Jy(o zigV|j--5rSX6_Hlp68e&H*JZ(sD`w_u%0P`cHX$#+6b7nL$JA?@Eu~gWIc;$_yD#@ z{?b(!IV<)Ly9)<$n4Yw+DvnJ!KO5cZDE;B zBE*^k6`48idx0{3cg${>3;UTU)phV*IK-WL3$3P|n8uW3&&e8HG4d?cr`K7Zr#ch~ zJAHrW$*pH4204zQGgp`;NV978??hTdmkp(|PxTn98utm31lsV;cLWAg@Q=uQWpxP) zhx)f3CH5mzdsinlb5ytn0@l#r$#_*Hef&U#06DnpoX)LndoD8Z_Hp55Zz4A42&tGj zj99MlRgRY6Ca~3OlZi2lgTUut3BStchnda)CdLn`c z%Cwku;UalaX7xrIlutlwyHRpWem%&E_Gu(2Z4wvG(8Hb!UfTbHL$&Jb^i+*OjC5z( z%)gvriA0`i`E}B&IOe7a3+M_yWud$^&)>BY8utLb+n9m%edky>$#^TQf%u)Gs&w69 zuWP@;cbg%l@pU!i0SDA*+wlo(v6qHOsv57~P-st`VLvPQacAQZF>dZu=Z|?|%$+Bn zby%MUK30aKagG^m^0}U%f(H6Z#egpR$Z_O1nnyHpka>^Zmd5)>);*}F=U!AQ)z4{v z(Rd7Hf#l+G%xEhoZ4SlS&2UCwPT598tcTm7{mxS-fqhK8oexa!iTt}#hQu0(H;V@n zavt4!PQlEI7=qm)h0maxWP-NO*QfNU<4px{I}e{IGG+#gAt1xggP0W}(`R$Lme`?G z){4(+{DX;PF1J;))p>=ARJo!s`PaU3@ zho!!&*47zK)4qHb#vc&7;ZU{}OpH^_2*aDfN<~ON^XyfW-HWqv(Ly{1-+|^ts!3Oe@H= zE7gT|8#9bNXMz9Nrt6Dudn!C3^UXII5TTix595=dh+#U|bDy+TMc!;(K&=69mEN{W zf76fDIbU>BuYCSeG}c{`Ea4E^3IB8Z!6Frnai26FBhrp^E&gNXT*RjEdbj+CCbmWN zJ=9weu7%NCS@wl-hpCHcLINk=sd1Z1=%_;nBiQkuCk|<%{k^2t!)<1;VIhG+z%A2_BDa6&6}?=C;HujVB4 z02;vuI?vRSEL`A(tf(dTKZxA`a5#=?SM%FBe9Mj2Fzq0aVI06RpgCG(yJK_6n)bvnYtSIDIo&- zc{ode7Tf5_mbd%xI3l6)PB8oRH%3{hmqqK7&qS5k=^SIGps$OI9nPNX9R^1SwT~(^ zil~e?`$bmMPM&zI>}WqD`1`?<7RGUPnXv?LX5Ujmy1?P^X#Fl_J;ls9Z9%wE#wap| zO1^pG`)#MrQOGl*mp1>|t!_2ZS9xUgdw1%iS%b>s)$6LGva=%t^T3tPx5^I$(}A`i z{l)S;xERKFOC+Ac#oM_y$82D6BS}@`*0X3W704G#tqYp$jwyNv{JBUHct!sfc<*IP zOstHJfief2kC4Z%9O@%;QftowZ;SLOv*yZDtMY#u0W8US1vB${dI#NeuYr@0@fGe& z{Kj$ODRXikiI$Y02zR;E4ub4dzSHIM6Rq=(g%va)Y~mnSjSSsatZG-o&jxT7>kd~X znV~@PgHhT6rFMsd zpc}ozl&s7>9;oQ#DD~|c2dI>kb%ZvPRsomhc!dGDR?d{YAb1G|0E9tGiwGq}r2_~9 zkttBq1#1k{E6ySdab&5C8)(&pG&S+mh&I;7^etK)vT?AQzW$(ZFN_SUCkIpglhfvj z`kr+H3(Q&bp@unkr(R+Ftp3qW9fx#fs1n8G+UF5H9Et>PI8A(*!G06y zDeE?f3T;rc1XDfW4)!v3N57Gsobt-f%rzUV*RNE4qy?@O{{VG$k6V!E-s()=JDROE zi4t$&bVw&}Nwmhlo}~#6#~hCFg0hh#-@P3?+hPoi4L0sF!=cqrxmzb@YkUW&IDSG_ zaV9ngZvGDrQTa$ZgC`su!0~mxbHr2Y=V>T>Yrq)D;Hez}EVuM^VuUN=rOs5JX93r( zaK+Hmd14S;zuvU7Ey~%O!3Z`Rh04F>Kr)T%!~F_CoD${=|>B^FzDR7hW-evgZS8 zrJtzt{aW}R^V%@|Kl0k_5K?1jp%QiBNKeHl<)TUvRIJ5eQ>Sj7x#sfFNTM;n1;w;+ zgg)9CKhvT8;^V}fdw1Kgm22Cy_1DYow()uwK#NZ7KCrX9A+ohWLcBy*>dGk+qZTCl z5cxp7=Qwc73*>^@{3{$Z{AjZH4v=H2Y46<0v{KBXSeI))-i3R`4$9BPZ+H9Ub=K)oDn{`$irZeIm;^Xg*uWwXy?=l>M$&{#F{1q^-;uWy&^RK;PR9}{&LCx+}7 z(r#JBnT0ASu&h)7G$($I6`sqS_Q`1}dL>Bo#i895 z=WxOf!VKO`SEWB!4es#v(p9PEb#PpQBr6qzDi-fDt~A5sSzjpbEwbE4!W8Gz4r!EM zO!m)sASFX6VRwAH`X`7VvVvKOhFMQjtRChqCFj~~)Ja-F!&!(wljdZ{l9fhaib6Pv zYC>D_0I6@k8VA^d`zsJ%$;sn)d7nQrApDpE4oNU=4d43)xo3Ao`cZRaw^b6m{O>ti zr6U(DuFj{O+D0v5;!geATaF6no6Em^zQXXe0K0xibCtY&r1Asz^z{s>kuq= zJtCt|Rn|#TY}-&ke|)fj$2e_~%0IN#ZxfiIMSU>yIZ3551Dtb7F!D~iKC}I?qgNvH zE?1WH=L}0y24)x6Iv>x$uHtLL|DcbCy1^gvx13?Pss`EcOlpPSIvQBM@w5|qz-6Lf zE<6v+Bd<{BiPwNo)n|1%#@lU6=74XX{gror0;` zNyew3`?ng!z17Q=`)E$EhBY-q0m7cCLy7nM&d~VUGT(;nD;NBI?R+F{0dfXdnrIvr zo22t~@U#LJVml%8$HI{D3d1=Cd4C0%t{>#+BkjO#seE_{holovipZ){IJc z289UpZjiH90Jm6+Yr&$@+$eO7@{Xmxckpe|)^`H(n8gA}tnY z$<+z4HR4s?J|MOaWAI}TM;{oZ?mLPa#oJJXA$^d*0a}x5&uBe=MZAV9iFG(r)>UP- zkC&C&q9pD(xr(KC9j7EzKp$_DYP<*tziv(sq3TMnKF_XM^pWh99&?`ZVwrqjMD8B* z^7l5g@H*)W*C58&))jyBFKR!&-=$`3YvFq^m5mXtw#)sgz@0OkX|FljDwECoXcVu| z2MM?+zP38tIb!!Uv6B_P861rve0rr@{QKRBD}AbgR!{Q0c5?f9fLA)q*t!p`?6So= z%qrMTVM>%?G^Hab8uk%jfycHP0o@4Cr$^|$b!??Y$Qt{BQ|!=J{}TC zv;9Oh{1rFFcCF0f_86b7W3!|4P{&0|I5acMaF)LI+G)5Eb^*|!7(YlX?7_N&g-3|u z=03i5(LtD-1DZWb7y*7$R2@}T$ioL^8fBDXh3*^BILK6)ze=VG z66~S^nq}pZ_s9YC7s7s7-|A~`scPl!)cfW=#D4$obCtxFS^qZ$JxEm#&~+;`Llgmd zgR@U{b-(46K{*udHJ}S$(^N=7twCSUmO*PP{QBcRAjc!^&WNbOBOns?^|Q}a_LM^k zW%)FAU*26GgKz~%J@dOOHfHh%6j@-~d3v_l{m}*c)k6PfHv3KXu_b*Ds``*V$&C?? zYYI(hPPk#3Tz^*J&TJyL_45IJXw~3Yxrom@l%3xVzJ}%9F)QHjUxy-m2ugll{ofzlH`uSp-M7X!!2Oh#x}5^`gOk;7onwExO189S zuVu}pibQAJydNO3)TIn3T+8{d?+pWbgKc<|9+^Sd;A#^wrhCZAU-5*GK4>^-{g1x^ z`Z{<@HMHM)9`$to|AYTOjG{Dn-(#(8_+6C#A$7fRXbJ?!&Vo(pw}PYe2v8ReBk$g{ zmj-~u3eB&{tlg$RQCB5Q)$#-k$rxKH(`|;ykJ5Ro8Xp6!GWTJjiJkTQ57C79-EZk_ zx0t~Oub_zdQroqW@>0n-3XSA>_B*pC_w!bs!n2itJY%9 z8+-Zc&5BEoS+;qv+4_{|ys7EJw`%Jg+T}%49xDsM?d8LEhSJ;xNoSaj4Rfh_;VyzF zo3?IJXp@6S-UgdY4;~XZa?}3J$PdlxL_?Z)jyEj{vCPZqgK_54ob!N^^)*TJYb??d z4V_RdH2->3x4mO>3p=e$eGgd-W485^{f;3)+~87+TvFyM>JtjSCZ8QYX0%uV{UR36 za_&H1oSitUzx-JrL0RSq-|c2p19<@NcQ9BHbmdbCl)<#gVxq97=!N@wniV$;B1J;} zb5!pq4NdL)G>UhHElx~Vcc#`_t3js&XLa{k?l2V}XR2z*IbNO$mn#qFs0>)Y^|3q= z3>R`Ohq%(e1aA}2jPF_V%o<$<4M{ADpZ@cW<2sadaeIob9uphP%`zqSJ;Y}TFu&xw zgmmQVJuSC%_R$ftDU)lkfgg$z@&EHG?)`QOAEYG0f!@ZZik)W{iJ(nlGcSW&@Du-# zmP0ypMGG@SM0=)To~{y^%%*9@Cz=*hFHq~ox*sMnr%}gB5n#|Rsw5=fF!kpAnhi@+ ziJ7kiwGq)nw!9!eHSX}RPG0!jeL+P;XK8WYRXG#e6cvQ|MX*1lA6c5`gtEA4_Gi=# zwLe^Z8fWQB#DuC6@ew>K)QrDLR3e+0*N?#A+J^^xssHgau);EeLift{kuGSR@i2l9 zDn&x}G@J(C-@^sNiy8(wF{JbCbK37)w`R$&<;TQnM{bE+Dxu@ssM zp}(L2p6-OlYuK(r#<(%yi`0_5RffboU{8tAUnA+RIJYVG{`fkCr#^L|4E!u>`~0m& zKK2+DWUE^9156~0%B-LHr}RCjo(bWq0U8$Aztty!1GnTxwM zQ+a&vJ%8r~lb@(yMozB7_ndy=VWIoqfWQZ%n7fP(x*%_@O>B9c2l=N-N(Sts z1N=Co!g}_**mw#x=gx`umY6&X#>HMgd55 z@+QPWGIymnb$qT}2IWyIE-I+$uHZ)O<{rEaWjq@{c=C%8U`OFPQNWTa!++0kPOvAn zDbsHr_ytv;P!N=yf)vBn&eJW_5{TM1utX87uTxdon)Q^FzMi-kqP6F?!=fb_!8C|m_Pu*(t3<6# zwx*}ta{9jkFTAaQ!IV6hQ{XFWclBSb6Vv3trVASAaLd|Ja`uL$E|)>>S4l(aIVRtC z)ecb711>tDRh>KN1=bY|r_0P-vtqoTd~Jln(G&WV{J{{Fbb&bjIz8|qzMYv8`iezC zNRaHWzJy8!Y&geS8?IGT=~|3Wet=eZ-;F_Mk^&iZH8!oZ)A@5Z9vX9Xf}LPClNE3* zm8|{ps@|u+Omk{-6FN4qUz=w~nUN;X!aa(K=qDw;SV|HQD+?sklcMv_uhoQo#jC4< zxsk}Np{IYBt8){67u3$zF4&Ijl@eF|sZ7Mfishsp4K-!o|0v>#W$<4H5WsOMe=lw< ziup9r8#Dojue1lQL&Wc9_4M1|6|?EmHp#Zl`0-&wrgWPfNkN|jH_NfJUq zvvC`#!sA7SfHp#}@@aN1vgBGOhvSBoV>(UZj~^Fi0aFdWdx=|inMxS?^XrH7~6y>y8~3AVLj)$=kdjAWg3Vu9>m7HN4xo-{oo!iKHpc6Xn4==-M zN8!g{T(~&H%%RA#{l~Kh#ZcZJuldRd+_jdtB5cLY9?m-A0~h_hN(#D_?0-n5o#kMY zL-o$GeFbs4n2tg1(7E}%z*^Mw@Ud<7TMoIQjW%rym0fY;hZcD=zXzi=xKd~GLO8!0 z5{4{sl|z4NBtqnMJ-BJ1e&lz>QHI47*rp4nSb|70q>KThGoC9A&ls2 zI#>y4W|@3}6#-)z81Fksx?Xzur@2-+kwIMg0z}(1Cw@qIlPd#-i@EqyMYYb2TyLHG8H`LGv;GGNpX zgU7ANC@H+s;dD1Yle}>{%hUv@{aN{038NH=lpv<)rQ+{G&$!-3< zNa%Tk-L2Xw*(VJr3dIXTbD`J6OGF{c$zQBLKJ=+XClXDrD;I z4^QZc!OJlZB;NLX_QKS{HXnKHXVS;_7l|qPdx)olq?NNX_aChkZf5Vrl^++rvto>X zMxiUoy#sx)OVrWCN0d8Hmv%}^Z57xdffnTn<;z!2LEK74D~(u~cIzAL70&}hr7(0T z2pNMFWaqz{;I(Y3RM83t0d3=SfF%>rENKElzfTXlVF3DVGGC9D7COW7rN->{BkkiS z`c8APn%(%`5WeS^tOWLHq(Ap6P1|Jfych=_53Gik?&$9GUR?$Ye>N2Dquva`$Hj01 zn{g%C!Rj@NYrsP1h~aH`?{^AIS(<5L33U6+-X0bS8LpGx4}&I)ZH_v1={?s33&89% zmg%WN_W9I{w#sXX2R2G%cRXwNmLJTS@Ty{??&AsZ5+>A*v>!%aeeIU6-!2*5t(Kw3 z8Ru$>--5flzv8`kLQRiEi0$uE^Wu86ZvbZ5tE$C7JeMa!21%A|5s#Xq8gIV+{?{ZK z0jeqK`-mBiW9l!j@vF%HzCn0K_h#}q8D`2rCPXGXjb+FHTK$k`;b(>)o@RDkcYH;y z9r*aBMo?9w4Q%_>RGX+HJiXHlzUU@}>f&GdCaBCQ6H#fpE82_7`B>Yfb2=B*RTXu6 zv)7>uImbS9L~C9Bev$Yn(WNY~u3%SKAGTLx z)REG=BXd6H8pbZl)v(FT0F?UYSHAE4efaN2c*qiYKIiW^Ry*NoY$MN9f6zZb`V+pu zw-IkJ_+Wdpo->fzT}Dzbwf8Xp;>G00Ik&j^bj##PlJ{Q8d|TdE2${YwN`)M;9h7Oj z&m_U)YbJYj`%~?__sD54~9U0=zld;JuYJ{OViH_gX+;9OF}b%k%wi5Pe=kBOLw?;nc!Ug&_lSNR}) z0@NF@s{H5@eAv(mOrGLjWs6()g2vR@?>9rFHJ<yr==cM0?F{^>}U}7Q6!&4?tuS3FH;!Yg+lODtvK~ImDM8mj(WacUIn<*Sjr& z5@NMfNxIL<^36mobKw_{W!}euo3m-r>K%hVRnJ42UD>QmqF?fTNf3?;g)5nL3#t|p zX3*dvI_RM8psvY%*i>p_>D^s=lov#Ej=^V|s{4L|#VytHy|Zw2?E;-urM-6?tcZ*yF)jPud_S&*veHAVT6A71yg{3`kdmV-^r zD-Kvh)NKDwMB3X_h{J}>6|5HKl>U7oZ{Py3){w&YF zppJUk-9dWel9ZUlPQ?A^FrP&cLfGm2+WELi@em(IUHOl1K{^a6DK|lq?Ddx! zKEfZ=&&c3>h4zOxIOK^P+Vm`Do->;Vi0$y14c`H&ZriZ5uk5aN693$e@Oo$I{=1ps z4YtKF#MRAlEG2XX2d?6%JD1BVz5V+9#{T`{{p%p>qq4Si=6Hm?IyMswu-=EcSklT&Y(@3F%S@dxo8Po6npLQB z;FM#M#zNf&u(4T7kae!yHr?PTIAR~!Q(>WJARaNW)-P>zSJ*E%h<&Ak6R4jZPSZ>w zC)U6zFG2HJ@COD+{+Yuy;kbgB48$yB#1eIzd~BnlXZbCY7yb<%DSP0N^4|IaWn#BmTFTe$uGF{D zjOPjK|96{EwJ3(6>~4wK;4`4tM3l=F+Z!8q~PECms|UB_h^<|FMRqeKzh1vZt>UB zIR1;J`ETMpzpr!CvqK$qyOtDF$O)3_T%D?24*d~_$K?t&O^vsGr7e-e8$l*PM_dQ> zn`tv#48(<*#Kwa6AKQqlWItJC4NZ@x4`C((51TEPE6_7`DUvup&4Xt6yr%xU^ZGBA zQA?38W&cMO-LTm>PSf@@4>GKD)A`RWpHu5WwTJ_yzZ>&jCQ5>QJt^@sqOFQga?NRK zb@!7&?K5fD?YT{^q{Kzky4S`VdIri+&{!2;ALd(`i#%+_=tTaV+Nh5jHrWyVAtyO; zj&P$6!B0L91DP<5i}>?{ZrPXJ^{EcHB8{<2q@=CQrIBL&<)4u&g-!2o`dnFE>mf8Y z#(GWMT(Yt&;*EdbpLES#-|M>rOkQHICCo=+4UyZFYS!!iawl8%@n1%eKJSi&KM>1? z7j82byPw;H2fOj~sFzWR=TO@`sM|h^N(eSBU}kVLpTT!=vkrfRzHsxwr<`U(_44K? zTh3j3RZ=eq7jv}cb4qxO|KyR~iVt;b#a~mIl@R-dDg84GQZ=KS^#@pOFi6VG>vEL@ z1E+7L;%~Y6Rs&f`d)cz zK&8uzu={bZXRvbQu8W}0)&^y2vyr9F#S?!th4%kU=L{SfZ|Y1U8p{2(m2lXvEbpLW z46F5*84TdnoAikM4_Mny^*Y>JM0noPWvsY%ath=Rm-Yqm~ zN^GHaOw3*9Kh`FFFOo8Voe5+QM79QpCaGZn9 zwp)`h)Gy4iK@2%Khk7~7KGPC+_Z)@{CkJa^nOqFPdLAO{=ZyogJHJu+eqKU}T|naa zmm5ik2(h8N%KXpDL&OovqP}jN*^J|(FNiy6y2b&0B-5Vj(f6~ZKY8<{nQB@Y($Z81 zuchc`7{z3D!cgr{SzMBrbb7ooiDTg+v+vcbCKse(m>~dZe!E7Ev|-hsdeP_jo9psl zJ(twY__6N8HB;_~B156<1+xjR!!uHTv%_un_h&XfHy^CPnHkTn?`|}WNRfs1>3sOm zQn5?W6gX5tS5ejN7`ZD*B;o)k&p&86*XeqHVe5&oqd*2<&q{jx8PoNbgc&JdRx0pK zbNx@a)4UYc>Tm`D&ddOmLNr4Kv48wrMg6>>OZt&7+h&m8Vo)Fg+Cn%>7Zs&jinq-q zjmfAi&+aC^sCX^dXR{Z%)Cc8a$-id$&|aZt6L&XicLML4xn#`<<9AppgT1^fS>?%F zu)1sAd`lzS&|>~Tj>@W5ff69>V^O)1yzvgsb!L^{FGkZ7CU-NNfI~FodPoCJBSOg= zs`A_CYtJ1%ty^?2O`LjOdCV7FE(GlkIea?b*RQVxqDb?oA9VISld{!Xhtd7`pTmfhaZuL3RMx{m(GQ|1qZ|XzK zsNiIP7==88+_K5gOu3a|iqv{dDVWJDTB(_)s;^aTr@6{Ns-|JU9)>`!l}lcS$LNKl zeP;&wCak^Kyx@p zeJfbQXmuhvmEo?^g7W}e zk{r|Ueu&Y(mJnI>jRnWYPr7%nlG_Ew|8DprH_9l@+T`ZVNTlbPLpeDgne{^7#U@1Y z8%K|yb&`0oAcM6qTQH=Ra07=0^ZE~ zD17832XR7&GY_>J!A}OSicA=oe3{GPeObL9DaK$;MTph1)6&g~`@1K~6F}6TiQUU7 zi7v5qeEazx)dN?8u;dVILtTWvXX?VG!>^sr3=E#rl;Z)$k|Tc9^4xp7S#s`&vMGl6 zQ!k;xEMz_bAq87r0%c;bk2R3N64-n1$-1fLvl(WcOS|s#b94C6g$}2Q3XH|ag{pb9rjMUo2e z0e3d{@S9kmTWpw?v3S*M?`h2GJ)W&2NxHQX=>pONLX#fIqy@H?p$6B)2>{0+Nw+ zdOqyIDgRdD!+}Zt`cDQnzbyh_F4^!zWf94{ty0y+J(`0Ec>`Eh>(a8Us6p4` z>*Jw99Xw~UU}RP^Cr)D+LWK}CYn?v5F(VQg97Q+bLZ$cU>uEA?NbYBa@qPMj<|ge# z>6IU4j|7HPSf)P8_@0aLyP^cRox449o=b66^h!*8A7_y5uK<%_ zPk;{dbG4vhFxu;_d;|;dz6TP~AaM@HzG1rolKvl$mL*`=CCM9qa}EPAOWI}2(Xn{{cka{cIrJXjh{JTVW?_7= zfWKiBGGzfx6VWz@$5^a5Gv-8}j2>Aln_E&0RBv`&fW0#yJL`s=CqFCckPS3S`^#Ak zo0Zf-W?x~!D?n{7uF6gNz$X99W-rO|Q13*` z2Us}2+Wp%>n)6TIL1M7_x*C6K0Wu%q;vOfHyA2n6ILl9x*t&2xIs@P_nLHHe5gr1n zZOGn;5#jJ+>WM!WRreY@di2q7{cT}e6~lG2Yy9aU>yYN#P`=00C2Y=c!j(x-74h~8to8owYkC$Ip}>0_{x+n|`N5nn7TvzwUNR3sb$tjyn7!Nc~O=Li4@ z=lS1vScy^_{peQ0YT{uWX>RNeX3y@l+&RJF&|U;jZ19wAs8I_7(SNbev58uD!V>Bz5VH4PSL|#gCm!6b;YCKHB*1w1 ze*Bz2Hu%P~yT*R9FA-1f3?B+c<=(R&VpDTcz7h+nc}1f-nRo>pvs zOoL=Lpn(z(*_I9Qpz+xKNqn{c#jV2V=<+2*NKZ>e7sj9dB(kQNcQ5k0GKH(An==Br zpMVrLnoT|YA~4$z`w8E&e|4qhexXQ-Und{}uC1danvZCZ>0?kVdmi^6FnM?Zs#=92 zw~FTB3=~l9Dq;i4OZt;{N=b5TcO$YGeqT%j4yuk*Q^{?+#tZHDN`Q7!Bmpyfr%AnU zL#4!@O8zz0=u=D3-iSh-^Z#Tyxv2VCYt0&Zgdw+bA+6Kxp(boPq0Ij9=b+F7lu+yaQB2}ouMkb% zg3X|^m&iy*r1^D|!)P}-v4-%l#L0yph*@pj^i;CJO+?`86E4uB+oco}aKS4QGrCnU zj-er2vVA89VP znBKJ#`#{Jc36rDFJndX?if-@FyZzpvo+Y=|$Ojc*T;M<#2l6|l( zL_QDO>%&KB@1W<>`cMiXBD?HSwh2U7!nGLc*o5}Arw_o;&c`bdmel~LGKr}(-;pzO z+91T922=6dqjR!b)WIl&L{|1d*ZZQNNb*L< z|1g$$useAV1K}0PSAufb*R1;|=YD#b`yczQ9t;c@YMed%#cm3kP5jfiT2&&p5$Y)b z{CTUmp|e?s6#?gJ00tRevcEzubc9D|d$TPLxzvX?3>$1?%9RU&gXgl((mXrZY>)2P zIkLBTm$j5Q&c@1FBM(RO!YN%mcD^qrzWi7jOi|&1kMbyYW6a2l=rp4ppNNj1tE&{j zs^=@K2fqKl=%*=h{in~_iu|eb@|kC3?p~&M^bJ0;bJp|FpkWx(o8rZ+mF{(&-$)up(|2A?G1LXF-b+F#L8A-lp~k z^B|1YGj|N(_ttFyvk{AQ@rm`&8@hY+sZ<7MqtMdn2uvoIQyk4KsAwC(8bY@3vnF2U*&t{?1PKyY7mAIh|z4E$29S$&as~yhl^2u>TAEOU29I9ix3T= zXO3c?6=P)G+vi>|uPm=`?VLo=Fd5&`&Pz45K|89z4!INs@fCTLw8|tLi}#qrAeo59 zg+tAf3nXf}3VhDHz-;>EV!ShaKVZ269mPIGkPrp4TSDg=?T%f@oQjWR_lq2?hpa#d z*qz~Qsrd0*Vl&yIP2tOp($Jr8X41bLjuQW1bMwNA@V(<_j4rICAHN8O$7laEZ_$)G ze+K$+O#86liANsqo;*INYb90s$|f{@AJBPbF-@KEeK)ODrI0(6c`f2;jj_D_SU{Px07x%EFGAHgPdF zEnF=1MuNx?5CKyzs`fkAZ=8{Ml%<$)INbls(lk^vCppv%(aI@E$Y0#DZOETf$TzGC z7`&6FnoT*@C(<<+>A9vmmGdRhzm~K08SV2J=lF%Uq5j55Z$Td(n#&|-!;pBuN@g3u zn&et-#0I*#?!4C&j584)LmD}SS7W&lHFzKWfI;q>_V#xIIH$D_ou9@o-qxQGwK?paDVc-}v<`o!WWglSwylDp=*;qx0eFQvb3 zJ5~-}Xlgwol56`(=dxkOHB+C31_2iyQgT6YoyPRuSRgJVa3g~+n3OpL^(_=nL))#e zn+n#1u9EwG?P=1B!UcMTAskLop9%1`AtI;PbuZTdUeH)Iu? zlP`@&b?X#Na7t+(Q*1$W7OP|G_&paHP>NEd(=4WkgfB8tWi9ktrVMCq!f|XkE7qcO z>%!$U6_v@#NgE&Vj?mU&?kSWuRe)y4JXF4@93`7xxM!Bn34-`%#>jL($h$;)?;c9? zDdx)E#HN_SRGo8JeDf}Kr%Ik&C13F(zd0>3_lO2v+1zs-^<8fBwv*Espgd|=Gwtp& z>DC~W8?O^|-lwyz{um2e!q3FSqR+#_7kcaVmJRL4XH>V!r{_DdRM*=Tj;F+-QFij?1rY5P|SQ)yuL9id>0=9@w+ zM7VJy=qYfh8Q2M3fX7wiLo_qO*S`7>Kh~d9?>V(rtfpr<`i)1lxS9ToVoak?*STp> zuG%hi7P{h&N&NN39Y!{MH~%vwyL?kNzYa@;fT zerJ$g<&pk_T(`gVB&%Qe%sF}AS^F{p|Ke%0OXt0)tl+S)n~oF?HlN5O$!%Av@jlM^x*M@f)DSaqY}4h(~ot!l?J7`CFEIWK-3cr7FO8b?@D6ZD)L96A#)# zGzM{CAYR`5u&48XOB|4WH~Qa_QR)rO29@;7Fbxwa7F@o){;yfoHV1INvXb82In0Ld z@XjpWjCdW!1U8p<6p79`JX*L_$S0X6eVo}af^o))A8gc~e{z?)Vl%utZ!i(=OXqob zOV_UBFzd^4<{cs4inrXgiLBK`TKL?)-vs?Y|lEyS|5N+JC;LR(I0!_j0u3 z*=vo&gp#0$GlNAnGs~VHo|#Yw8qLLMgMv;fW{7{i(bD@R4H#!OtOE`M!x1A6H0D7# zmz=J~V*&=)^Hn@CdTV0tkZ>ks19d#M>Y1_f8--6IXde{bvf6%Cw{e-7U&o!ETqik) zgK{rA5L!o~?!v36c#m`|hfaEljkD9+isO@T_{eKQx^K3-NGw8gqcYwrCtZox0mDK{ zYP=@7*2q(t(GN=N%`xVsKN%_Z(A3~u0Rgxm_Qt=xo@6yM%S3M2-F`{HS|z^u=hkGQ z!zhpL6Zyq@vM5**loRw~|C<@@N9;S&R>6G63|I+)47qjzwXA))j3MIB)Ntq3a4P#B|RIJW7+;o!#knz*kx zeq+niPT8^VFTWaZ=dC*i50VC<4=QE(7lpw^K5u3Y3VsA8h-h^Lcc)xn`PIWb>EnT$ z!6rp(=h_}tvpLSg2Pu1UBgMfC#(JLC>YHtblF!sJF_VkvXBI-}#VXJdJZ zng+PjtBy@5mr>ilAfpR>wjDkk%%vhHGMJKcJ7|1V?c~^yRW`H_D#mLEoX-QJ%fZ&{0!!1G@6A+apC)l{7P#7Wfw|LKpG|oEF zGl$ygSB*FPmAinOP<9+R6iLeMByKcpc0~t@^uXkcAk(*yPlERofUX>3_vZvl@#@9X z8{_A=NPsUCul52{zV>JgZld7g{zN%<@u0xV=N7*{T+m$4S9{S`9wXa!_c50&$AveF zx;8!l-}CCX(zf)yYC$AM8`292xNcj^%3ne=mT&DQpgYAzoDx*zeU` zgF+db2qtBvcznZK9^5{Z@HOD5$E@NnnMX&L{wlr7xC7Dd_il#lX%e56OiBQ>4x3%f zC|hL38^z<9NbinJWF`!UqWttyw4BS=0{ptyeRI0W1{XyFC*IDX&7!wTmVm@juul7W zaJz~zGM;ud$+G>*!vCyFWXl zm)Diu6Nuz%D)7p~_>?yg;rWK$!}jxUCCRF<5An4E!TuA*xE~P9J%~u5yBfw!U%m6x8?iBDrMz;<;Q$;R`q==|}^} zp-sPR#PAx5l69Ut4erfH1_iw?-5Jm%^bF>$ zD2}SxuRdLpw3dJPL!yPH54pSsPsCVXURs~>VEhN89?PTN14CnqBAqu0M>Ry%`eQ*fA!B_~C!o=hmg^Kzx(O z2Q~q~Kzf!8{##R;tvaX#U5!}D>%Q)PYr-S8UvoJXg>NQ1tX@k z*I;rN6kE-OTX$ZiNv;l3OWNU+FR!VgV4K1%J6?Q2_5KhswkWAR&P04MX#G1Y`cGqQk5oe94|5PEXXme)GsKgz6>9 zgp@g)V{W#m`S&F$`B}%4WJph%HgyD%=36Z65m{85w}98Ib-G;Hvs7h7t5zRZDquL^ zvKm?D_5t)gn*1p&r&i7D3hE36Icm7+5A*o}&-F)Ksd2{#@7-rKtXBuB*9kL2`JcM< zJT3H%GaKO1YF=#GUGW}<**X4bc-#&ff03FqMUQU|lhNcwJ1VpmKYnqprn0T=@(rG` z5wek7fZ@EF+zEoNRK;E&rbo1(`Rjt@EQ*ByK=U8%{=6n`#Z>-^~GX*>Hi z$-##X)oC`xEvp6PmphQWCO=QP6niILllk4~B;oY*(069Q>a5<( zdqk-Axdb|$1GqJs4!TxPI5;aZFB1nRDsah;8Oh=uz46>z+~6iMsO;6HrdGO0_E_WY z$Xox9K#Q6P^)*RCB5B9rywFFUU$|RCes+LbTj}2@;224OboL$;UUEkdQtPUnEpuK#D0N;J z`h6z~8Zov=rw#S%1g?io)5cC8?Af-Tu?*@VsFUU_AM%YJA$(m^Y}oHx6DErlJ}0Dp zKg&D+r0B0m^O^Gj3zMqdf-JP|!FR{ga}(LIav);^;W%e-pk~U8+voTs!sl7VZruVW z{NHu)-CipeB8Ao2Y&5 zq=|EYKLa4K&BOwkb0?$K(3P0=FOP_7R_76S6qXBFK7Rbr^+SI78Jx_0Gy` zcU?nWtY>bQA@bul5s{wG#i?qL!x7}nJZsZE#!)5UizuYpHJO}vT^=LdNB;qN%JTCZ zLWyvE&Fpn>u`cFnzFz&g-|zE-#OphFdZ!SMu||1Z5jNi+Mn}u1rChu5Z#^N(|Wi zOd(wLzgO{m+LTAF#`Lz#D}61Pic)jzTC~tAh!bFR()r zn5a9ZZ(bZ{1+JiAt&x;G0NV4!jVqCI^!RktTsfPXnIGirwu8x%TzN z4iVshKJ-=0K?#b0N-!Czlk`7UD}~Cf@X(e#KlC<&8@HV5`gs6aH6HqA_DZrdr}}Qf zWM+aO4W7#CWg_BU(Rp%D&pvsc#*FQ;b?!WMxJ4o+m1mKdlqz?O#dTt)$Bf=xr}9|& zYGNBy8r!_rv}w}{+67D>L_KI~@_WR;gR)9;Kk_a7aTk1^<8`7vO9~&;7X8g$tMhgm z+V|_tvqgV?oSANsOzagg1fp6?P(u5x%8&Fr(X~>_ z1rg-SKcPm;jKGNO9r_Y;J+1_OADJ7>>MPtoVR@$*-N3P9yhySUih`lvr-$uO_Y^k- zM38~&RqV<)_N)Fg*|~p>tHn$WIQVH;B=}^uHdqv~FN2H+J~Z13)`bw`9lC$3JRMD$ zfVh{jh)A&zzZ6xJxQ;zth)A{lq^|MDNb2nYzN25WSbHrY`64sdlJIi7Mh%wI^d>8v zQBj)eFJH==9rR$<*y*}EG`lnH_c{T45|mK8w-s*?k~YI$bL9mit4k<{*PpH98J9nC ztvp$bX{*nfj5u}Dy;w@Pqxhuaq9{kmXGQ4v;8{rD(>#;~XZ7I*p+m(7S08mrn7o*{ z-}cMe-sH7U1!$c&sJIaRt`eMAIXB$yEbFN;;RkwWDvy0UXKL!QOsmMHLh)y? zYLHlrJFG`Oc!kPtM^=WDAda)|Mn=IM(ce5z8(t_7{~WIO5$|F8N{$+OrD-?HUeuMV zT($3uK>KYw4^(IpkftNq*$Kk;pln{(o3RD*AocRnEm2S<4+p+u(D&!XedR5E)0K!) z68raBF))&h+d$dCByH-N(N7lGd2z~k&VLAbHO{j1b*PsuD#JFOR1%@tQl>DFEQkDH zW^C|dSso%`i(+ech1$Ac@Q{yD?RkiE1WdP|{;ln&h-D(HG;q zY4tlzcq@o@aHix2{;|C`Q=;m0m*Du?lfOlGe|yIhdatU)feGc-(3)sxAqSV=slPoh z2QVR?OQ@j>@H*)xkk>?Yy`kiT9E?Rjhvy0i6<2Fr!Mk_1>>)h)1>2h2X_-8y&bZ)PD7FcG&_-d%2@Q6|9H@;^SJ z@bp5ExK~B9&Y!$1(w(sP2mbSTsdlZJ#L+K(XK^tptfj(7*KOrN{ZWE>wgKassPi?# z_Eg0i_Y*GDOZU!C!kCEjF-LR244F7|@s%NL!H9*T+~`ad z7k0KDwap(&5Y+{t%t(nYTFOwzmcWppv3Z8h4ja7#LN)_&zRf$+l%d4tQw?vmz6~%+ zpkIC@t7kY45m+X4yVZH{J00#gurThd=S!Tco=r8H=25M=`=>3kL8F7I=XzZ(`5`4i zp(~{#F60Kwr4KT>P5pYxPQ-?B3iUF)@%dm4o_VIEKyXas z%7=8jp9MV}NG?>=Dm^;qsePM{X2(Ucu-!TI`7tFW4r;QTDP(+@c{n@B=^wK7t4Z}5;>&ZR z?{2TPwjZdH$KD2&Rvv(5(Z1hr5JhkM(>_z!Sh?hPR`!<=P^E=l(*(X@ky7*s$p8Ga zf>oiRBa5{^N&x9Sho!CCFl79r()t=DFXgK`OqF zyJVi<%H98Zp%2prsTJNVJ^(TL<~xbuu(WfU>*;hTKTiRH$wg@5rvT#1*dTR-*X>@;la=fd zEa2AAVIWNi(ZAd_B;VOJ7=MEu`b-4U0cY(({;GR5&Y10$0QVeo=$KG~?7g6d#JB^TngmJF_kgNa*_-scK=SjcGxI%%JpH;XNq z>WSbDX0;cc&(3n~ejn1@(T#lmr=(zb&e8Z>$sXI-CUEGhBX8W-B@xZhuX;}6*(YFU z{fe8VItJ}NO$B@|=xO`!VebQ#QqNRG-jqJ5Ft3!Lsg8uzA6(bH9lU`| zO9<~d|1zsyZ|6MwR9)kUbH?2oxs)Jsv-KAAtqoK=>EHdhJ3ATYn1j=Ce=+G}HZ|-^ zi|;$i1s>+UW9LjkDak;xA&VWuVMs}|`?9b`+&%3^;k?t5AiIh2j_dsiRFL0%;3Q0- z=}-4Ngg$Syx@B;Qd7YRf-e=lJsGM1lIDkCDS|CXC1-0uEGvG7v&0q{SPG!tIU7=}h zh>}`R{J_k$>RABeGYSD`O<+6jaC#k6g1&!AWx;qM4ak$aPXOje>TVv zUFvg{o$<$we>Eqqotfyg)Qp*z(@?d;lS-=EUn&w< z)Ne6<;J7%d9+ zB;^RD4qUyF;%x_!;Df6b`nxp!LvoT00flc4#DeEy*V3>leb1}rg##XQ9f5Yo_^9)s~)kvgM{v(0E?h& zRG~!hJZsk%W0(lems1oan2BCQMMcAsfRTbBEv=tdAzZY|HH(uCUqiKjHeI}*sc!lE zlayU6?CSL{*tKjcg=1uWcjJ@Wp6@}~8y|jeS3`(&RzBr~&cfbcYs6$&?qds`>15U>8C z5*~RV|E|vh5Ew{VN^xA&zg%~@$mn0+4ss*6^Xk<47<&=GbHI(WvSe)I+Dw|$f_cMjLOtM)IWOWJSV@{*|kE`6-sEpyW#b_n3SF$@ch#S_J; zGlwpUf@IFd$nxy{O{c=tK5dH4n9%@mx>s*g>z!cw%@@Bm@4K}7#to1DfTG^mWOfT? zLL}>HuZf(*T)btNH!jCqHTVR!IwZl8^~>0H`np8$FTzl2ZSVDs$lniD(LY51b!h3I zhD%A7kNh5D_G#^m_-i)AL&j^Ea`~hTyQukZ~aM%;PQji&(9J(t8`Mwhqq06>^%+I-tTe(Bh|TJ5e8(BdsEL% zyvy@}sh8gr;g1L2{<2>|x(gq=%m41gd`>AQuT+J^UQ%y(VYM-c%|M7TlnO@0<7B|X z$6GQvl4MyvgFFD)<`@M)416AIH&8gFRawdcn6C1B?_p8DK_``JCWF5giZxM*l)?$W ztt({g8L!(`P9|T#sFIer`Yl>a(a}CVh6^4D%AdLyGTX{^)qN<%hRMm-37in<%n=m4 zqEfTUwj;FomWxgL_DOq}<-DoAr;vW#zh{y1KdN|?Vp+&es!)EQe$IcEM>y5*;jb7l zhOE?~pcE&&m^6S~Z)Z8q)@W7!kr8m;(smw5Qy+?0C!sZci>$nK~a0#N8OT3iDc=)0feiEw=*moN}J3-r9-;`4xkEITx=M0X^4_ zsZ=~r_;?w!*ATD~~} z9Iv%`9Dq=u)5)2N;t*fKff-5B$WsQsCoJwHodjmvvAmB4Zp|X3pX)L7;X|X@P#Vj% zJZgYzSu4~(Y;hDMBn-4RhW03h?i@L^Y?P#CIlL6rZF(e>ny+r)F_TtD%eFyH`ensP zi-D*mI>u9nT>#o8z^m(Z-5c9_*Vg6MukP|nT=~=a*mG@SgOwIQ#E5DBZf#z z0p=QOrBeKGUY~vy%%yci+C4ZPo$=e{{iJyQ*JYb-oe;j4?J+mvp3K;BjERy@BD7{o zfeh)u6c@gCQDm_}=(bJgDrBfS9bUDkihFM6_W8!N7p{wyr!Ss7An*XD^%^||)bBM1 zE-`O&{RLv-pL7I2-Cnxcu)Gtwwa^vCij}}_aR$e*vxDLoXyX31=`vV((x=>Ha12GL zxcd*R!>ErD6a>l>bg#q^|}eUkb>a2hE$y*Rab@ zTAk-@eJ0aapsz%Y^KaF+QQ|tF(Dgjz`IAvYL*+-EZSK$hLZ9a$9V!u#7hUEyX&bAJ zOCEm{*17;cuDJfOU27$|6Ok9;pLj#S29B-RM_DRXR8AS_j$vERCb#avck(%3-Cln7 z8~gHHxfX3#{X*Q|ZTP7k<^Hs$v;UCIx1*nrQawFW7d~k#hy{#iIxiOr6H^LGzU?bw zUFK!TJ1b$bue6-z;HVh^XUfW8DTy}+lIf{PvGjkA+W>Y&#|(o8+9jq;gi6*(68G0V zrzvbfuas-u(l_T1g{kB|P=ggnI~g>`OG0yj^f52(j3s=aB75WvTxTcTV)|3__8#4s zIfKoSgoiX1rxW_ywJU8fYp(0=J@J$0@OmQmX}whro!HM7A$Rkl_a&6>I&Vea^4$Zc zos>){XL!HznV<^FJ^pjz5ICZMyx(KF==pmW$pZUEaTyH|pTucC+n8uVbr6 z$dYW;OYg34HzXZ&amoJ%`fd$|%wn$7Ro!f74z0HKKJ;?q`Ss{&uVY5Y1DQJ_bD@4P zx3e#fvZVNX9e`jzeURrVOt9n{&2J>;|{|NL%KKHn7H-FQ~#3QD{)H|17?64run#s%4UOWB7 zIgEB%b)ck%H*WF)!wl@GTUot4{|!2zDddYJQNDICcm6`s^nD46Om5uMhFRD z^&PQYqF`jDMl9e5P%w#ZsAl=$kZORiv(`-gadCrzLUZC9=S>i3xia-vB!n zzCTInNgV^&tBM?M#rlgy(a7;8wm9aYNX$Pqsi<4R(8w0u|Ihw|oe{Hof7S(M0qiI{ zBrwvK73Oo;LDbJ-D(>yhgKZ}P*0}ZiLu1d^5DzBk(O$d{qHjAe%zK;z;`+=7D=YvS z<|Dj}a+BNVLxCd~XqxYFJ&msFKV(PIMFda=^+l>gz^VSE-D~dghCTOr92tYq8}B=P zzzXy?UzF{V=ZL$M`T#$WVJNmzi7{1ncrP(6O*(KP*J%2ww4-hDAYXJw(6#>7UeS12 z!y#|Ygs7qayd4>Gi*)_h452iriqfeVr0!b7@*zee!D~KpI!?TfhJ|8gnK>Tt=HUQglvXj(~n zE`VT*d|tZ`E&lO~Lio<4);o`eni|5tPfts&Kk2@atfr1Obww5rB7Zh$VBL^Ea?NBD zU21+$CSI3Y=)Cv&^9XoY$o$Qp*8rWwg5|dJX+NBe3q4?U2E^BrMTqB_P5b>QBS&f@{sr25VnLphc*GR+CH2))kbFr1(z<{ma$O(Hl(Wm$pVfHLr?H|GIzXtVwI+hX;8Ww-Xm){#QW*JBX&)f4ZMbB7f zmLRHs4dTfn`pj;Q6#wltgJcjH=d~Y=8Rj@k=JwX->$5ptUm;;rx;|2MoQ1j24>?Fn)_D0lVKSw03tKa6B69)^T) zyNYe~L<8i5>eL_+DBpz3owq}MXL-CVrgf4~9~G?S-Z=2tNjud|Jy>a{*nEoFYS%r;jQIm@yXMY7Ul^R=&-}+oM+}%=-z5it4g(5ls_6AKfVLtgi zn3ryseZWBie(bH^cLF^3rm%PhP2DY}_jRvhtynM+z{9=(Yc&xp7$ zg>*Pzl_}2MH~J*+`s7eJ+s!#$ORZXJNz^2+zf3r>M*7;MY9j}9fhd80k=y(_v3%MW z-}Lh|brS|KrF0hJh8$8+mNWysa8TY9GSZ|95X+I~DVB`-v0NOuj@Pi_WkjCl4TBgR z&Uv|cLfX%^`g`sJ^a*T;!j>xtvoc%G_v-}`EqpF{gaUgs%(RXba?+@Om*Wa{Fe0eN$Khzq z`pyMD=D~J;GJ$D(u263El40r%`QU@90km6WrEbx9nb|vBI3N~~&#IFW1n3Uu&yB%F zNfJIMWlHzXGiSmtRPkLH)$SUNk9)ij==kG*`Kpl2SqCCtl5fBtM}BbJL^_Uyt{?@_nv2x zNG`L6ZugL}r7GuRq4Fu9VbKw8fYw^@qKtV8AeT*Hip!=>H5lqB*1&hhU%!6029uEJ z&!i_}?&UoXgp(VKY9tMGdQ(*_e&v4XN2|hFTkNH>?Pz~QuCp45xv7$) z@zvHCLaEB4aELFfiXL|Kj3xsu-`8%?2-Ff{e{ep@o#YPsI=Y*Fj(@rtGUpwzL-))Uj z>W&(6^**LulwpVpdZMT5)>a>7{ZET)XJ?a7kpE98OsW+;((JLs*G+}iz8DP2BH-HE zz6FFoy;`Iq<1xeaYIUw=_UMG$BqvY*&uJtF%0H$$6BNJFQjOj7Tz2iaV7{l>mu!8= z+b3tIAh6W!1q`(BIaQeYTImMlR-i!f63ilxbsdUn0rTcD+og|%Eq!1s@h8XB{yu~q>@ zgT4D~@JJA$KJkK9GX@&O?YPf1bPdRa=3mFbb!IE0993{Y)^Bmez<-pS8v2#i8ccl*X@XTFX1%A625rhrnk-M@BK} zJ~Q{-4otguixKA{#W`MIuBk0iWUb}F1??xHgpyM?J$a9~DLXiT1+GUx!RU|TKOl|G zMz53Ak<)?bCR`mMLr!t*V#|^9|5-!7kO%%=?K^rI6MTK;M5$ha&?B=Yf z#23E1DS(J=qRerO4Td!&@_9zIAt4#$0)_9~en%LZ2Ug7Rm;c2=Y)_pBH8UOt8~Gvo zU*+IZodK57A(sTrkX^K~1aPbKNl3&J1J4L~QTh6F82eZuiQvB;?(zB8bPqYpNz0Ka zvgHKsSUFR%6XCj!ws`i3;$sF55#T_^0oN1AScDIr!)&(A-7)a-__d-hIj;D{;69^% zplVXZk-4NI*yKINI^$EI4qG7pIE={kZDff#8%%YW36!7{wf<6tF1{Ow{xd%E;d7iR zbX}3eckP}M@RtfhyhRi}iff3nHk8rr`P_YK^V`*P=bw!tzg$wcdig2a2F&_?6nx-t zNZF+5_jf&W$^PJrKkBakcfZZMGz-@BkD47Rf$$n#pj8Q{cO#X+UFL1fd_{^Sp=vFc{|<+y z`%X+KTxkNmOWO11#}JstwL~JKR_Rj0kMa3Dp}dlyeYx{{)iq81#9MBHk8>M;I5o`y zp?Y^6&oJ@ceg_G9&~^z;5X$zNi$Hcqzc4}RaD$P56#E%$k~tKR5{b2Z@a7ZwPH8j- z3f}MAU|YZ3U0SH^Je``?v^yoIz5QE?IKOFO?)B!Sw~kK+veN0X#^U#|9hmR7x3&R8 z3FOcEh`UOGqnLsX?If2Fz~1bIe6q?k8%*NCfs8$N{=s>udt|Z z1t84{&O^I?e>TEqfcdD6%zZtMm5pI z2at;Vgb`x{&r=p;2*!yleo`*nHY9;>_B$Zxuds>N;rMW{Gcn)17zC^t^cNZ)xr zsdCv`dpNXdw`+2ObTb3kDsV-3toM22>Pgop#{#(2mYW@y*i<`&FAF==uvr#aoN85L zF0v&Iw(bizH@&aZZg#o}4rnekpLvb9*^wWb3G|r0&g;Vp9{%qihWw+1R8M@vIrPGX zP<2&fwI!_7?G|$#70kV$pV5)EI1TLqw9Hd%x~^+V1{%=nR}jB`8!E7t&jAzJ9`j#! z&)=x{N9HQ-JH<>++`LInikcWa@qX|UO%&&z%|XO!m)*PEb<tylc6`hm3Y#O8@e@ayhG@=Am zgz4GG>ye}9Pyj)b$Y$h~O+A|Ou1U<+CrAH{E|Vd3ZfMGi#(E#nc-ohhW$OvkhdAG_ zPH0-aAnw3vaG!JFs_FdKov3C(MO5%YD*g-CaTr@GZ5g<633D8jw46N?p|n=J@JYY! zGIlxy+DAj`!E_w@n+T3ejB=#$+zlOzkj^FIt{KVzfMC$M24uzi@PrW7yx;g8PD@PM z!r4VgqP4hXGhnX)heN=_Qd?4U0Qerwc;fL=w^HpqtpCs`NxpJkX z1IXb(K^+){fEw+`{idCe<+!s$SjV;s}wKGRlQ#adU zm4J7Vq9O}8MSU@EFADsm$$dJMj19UW7HTp63BJoo%lrf68LwmD;-dKY;>LN^D0GMR zN=w*~&baF>4hnF^C)f|RMi*sEm$zDoEu8o`nUAS)3f*qIH8Vag^hgY9Lgl!4;942G zOLn^_3s4rl5Z$PwFmM0yf%lPKa)=PvFJ%x1C3?iP3A!1H+`s= zlASd_B@zl9?}iN7+>A()4D%xMv%Yv6w^&1O+P=PtD%EP*Yig^TFra&CA(jS?3_|dK zER0^68=Y>UmXSd$SHEM_}^#Pk#ZlW|YTpZs`LAGU5RJIy6gF-~4OZ^{vZy6Nl zwgieIL4vyk8QcjToFPacK!R(4!99>52_%FMcXtS3aCahvB)EI<5W#{&f@gqXzW1@u zIs5KYb?>WJ_1>>{Z_S^nsWof$>ebz=ZFTRI;WoxiwH&NoB_)JhY`iOlo+(F+`lSg^ z*!-~tdnkcyRo`&iLtv`>YwOmQB<)U_56Hrlw*&*Gc~(nKaPKeq?oO2Nlvz!-i9C00 zJshf@?DUe8`E)u{e>ZNQaTaMu-_9uE1TmF-<=ufJq;4I)k*VQ9zBQXSzwVo;4*}u>|oVp&a|t}tFv`Wy(#|`13e94@@f%# z<$E}|)w)yH?K8MxPk{b9HI6Zz8*B1x`Voym_@R;WjyuVh;}?m~VZWljO>9nm_}!*$ zy~_-z+$rmR-+AXvL)ec;6#1_(l2*^QN>L<#icy8f_aVpbmo2y5{eEZ7KvzALV_@!5 z#N~+kO#s$IILNqtUhe!Olvf{rrpamgYKQ!>|oiR&Ng*Ddnr`BO^%&dsdy_rr)XSz(LrH)U(JL2l&)~a{M?AvEI$BKca&{wh#@86>zB8+qQ zVM&iAxjCORwLa}z7~jxRJTs)1(upVUvyk`K40G#pe6);~4HD&}m0K!|A=wWGF%0C% zPNTUw`PSdEW?2;l_8L|bx2%3Y%R*D#R#t>{9!~Ed{+#>%`ThGo{Blrt3jT2)X6gQ_B(pI!Z0&i_gSTbGj^Vv+{&6P%g#O*a z@!fwxkD$8)IVt+5KK=O-S9QLuG21KBPp%36rY!ka8IV(O+A9gSV+zRzj2!QiC##Yy__e;^1NJZwyQA$0kD@e`K9n5V#Q2oUM; z$PBMO)*N_tQ1_v%-$^mk^W$3C;c!Q8{Ytabs1^*fAEgE&pJ~AtN531~S3G%rCGhCx ziN(TCYsrUW9E+M`Z*E?t;W&P4oEuxn=qs-h5w!1s`&BGTTnW8Vurt zrsj=`&&5+NBj$HF*NMqXG?vwsVxDW1OSi8f_bEt_hPU}f8EqSl<&;P15q!!p#4mSlh?0wQ2uF z(ob(akogy#r5&x%{|==WWYv~l^|{HkoR%X_Es?_P(;u7^__KTKoqxgph+$lhy?2!G zb_d+<$C8)ALd=Wb&ll6IzMXY3%q0dkdbMZ$&Ki^3(FtH2_?e55{_xf0!uV~Pfxe)q zS=+`tNB1kX+l_nY@?RiT-$NQfboy2H>32WpXSl3nvwGa9q7Mjg(XZdiA4|+c?LGAX z@3@S_0sAqv50c^s>R@&1>*7J8@9xE7)a$Wj_fP!agD&>AIC=B4F^5_3awT+Z-Vu`J z$-L5w(`KahgB72V8x|or6+Gds!N_7iFE1X}7+HBH}7S{FE>#`>i~m zvAa)KZc9ErTswC*L{p%weg~Q^xNfkp7q)dThzRI2ylJ~t`cK;Tl-{2Fr|hwtvwm4J z;PH)VgYCnQ`4emwS;BA{2k9MHB@PsDR01rbts>7GW)H_-%83;I3v#h~=j4Ka&dFNx zu<0KZ9NzmGQ$Wb47KS_XA8G49F-!0p{NjK2%;973!Gl00pJkOFf2LpgL$ZL{O#0Kv zj2RO@B*x{pZdLws=KmSASM>Dvk-lS6Kkr595ASNgdZ8G?H?Qx6d1GfHzuyHxCARvs zW#)L^FUFpuFHLIS-cpG@s`hEL9em9=)dPBCKEc|0d{51tZE@4a&N4FV{9In0{EzFw zWbXFgBI1f`+`0 z3P-+QqMd$G`;<)32Voy!nB4=SPa!h`~TtqlL#&ER(Wk z(huLP(bc@YCT!15{DIXvy7;8og`Cs0;@7DBVGB4O0+yQuxL#5ff)re2ja1xfK1;!m7C6ReD zNM(TnyhSyy2w=d%-h%}#lJwKPujt2E?@Z!CC&f!0IFn-jEv&+OS>BjL{uf-gAjCzp zj-!4uZV4hT+|E(_X3{LRJ3I)y-%)w~9CKYjiXZjU$#0P7YTtg&XL23#*EbGDplHi| zl%Q0WS5I*?M}9)z83x@(l@w2;vdhb0^X^@sDt$Z=O8Lic1uj5;0I*jPE~wn zZggFQ>eJC9c^iCxgQ(zW@)zr?)Ruv$VMGOEt5$mY4i*H!X4?zlMFopJ&f3e~IQsI7 zUmsxhTRihWSkg?fiwc&N#aZnmJK%lr%`Wd;aJ)-oq{8kH2kFA(mFf6O;*zQBoLBIc z+eAjXkv`c_H~C7Vx+2qXYoa88QhS*ljOe3%mF0bAnK^ah{$TCe?VmoW*=QGp=yi0Q zK(v<3y~0e%lSnyss?(Gr3LLQP}D0@aZiII3fD z|9#dQ-?>k_*14aY`4i|@+C~>y&tHCg-5=17mu7JTEOsu$qZ-+JvTe^S z!8BCfUKsFP`AP3f8Ojg0vqb$bl9Wzep4pM@KC2eq_rq73J$Cluj}t4mXkb%3o=_!a z;d>7)?)pOA3fP3ndu^gbvfD)!j|UbfO&)mU-07}s7F2dL$?9Dw4g8WM*Fg`QVKrYJ z;b#yJyE|O0yWCyeX`0r}O?E&K`tw{w}Y2ib#~H zv+m|Dd4sPlFcVx;PHL?>Yqu)BnkuMvSC$<*PzEzF+dj3#y=rjg<1?WvsA&1#h$q>e zxFdbmFOELl3i>h-<=yMP5B+dfU3aYcKBz6&2YRtCy*yQIO_0BL4(qMc)*X2TF-m6B z*H1-n&$obM_=Qe)7`amRtOfB-*NI_9!Mpg=+*#sm&K=)NA205J~h{bIw!m9<5##By421J4dIW4Pq{bOyTNeqI;gsH z9c02tqrF&RqLwwkR+G^C*LPsw?{Xvo0kz$osdLilC%SNeZ9H`4=8W^~n}na6{#KD@ zL&vt=(PsvpUDrUW2BKaR(@|13P$3L`Srw7G-E~70lTI9Sfe7YEYA4c??L*P8BH{rt z%x8EHs@*Lfw3PlVlJsKiJYfU=y$(Q$v%S?Z=B6J{ayB@m(89+fBWaCK?L_3uTqhF#UyehZOZ4p&5Aj9(OQV`UcUvgrV7)v*h-D)Z{r22b?rGNeB>%N&ao)18~1Bvj#= z#VUn}UQ*TyxS0~#(g)oAa{Il>kK?hGiT3yfs$(yiIe1S#bapj!VODlrOUvmcQtYop zF8cKt%FPxusD_eN*}0&1aV;pBW28&?rL*Dy4>d;jAr~4r&DGuqo#3Gsk3T@rp%62b z>tbk;1JO&dcKgTkhd3f z8xyufTwbRsx-H{yPk`Y@kVE+8bs`xfBbxeni+LEf+cnjp-7z~_98X&SC&Gn-%sh=K zG7`pU3;bvCTO+6a+gjRsmMiT-JFxsufgD-kLh*Vpdzx;gjcsJ?k1xE*Mux^>cptH{ z-22k_jl0B*EE0Lf5-0WHiKx5d4An+ce2v0Z2SU%Kpvd2GI`Ru<-eO6Y2Fi`6B-pl? ziJgFVhfg@ja|sft4x#gVb4kyH*tj3N%-O8*!_NP`J8`!V_+PLd{{?H|{{mLJQ;pyo zoyp=Kn$04DzaBQgr(IjOkzm7U-5gxz@$8qGbK<=PzXu;J>k)!kt6H7#1rfq)7@~-+ zPrXA{_fHWMBEPtIMFj1Zey4{uzlx8GUy{+>RT~K!Y!WM_;m~#Psbm20NC8pw)lo1m z(VwJ%dyRM7vio11p1+q%lT_P(%ZBT7wq9_vE!{LpU|f=)m5b*)WeLwC zcKv5x4wCIZTsBsmQ5ljP%Hckk8Y;13=K4iLBRkqHwlGeJhf(LPU>}o@!c@kFU&ibV zoK7ZIC@urhvGbHa5(K&TM z*v!073%UAWx*G%rQa6g5CFDTCHTKz5NYxo1JCgE;(E-UGAMrMCkHs4aZ6c{tmjOF8b*&58t`zO6?$uQ~5z&WoXN&G;Sh88wVtIsr19;y@sf68&#IU)# z>>$Vb%&TjX^$Oo4E!u?a4w84g#?5)Sk@GccsH)$-sjLf(0Et13II5Qwk?bZ@3fWdU zm;9b$phuA!7qLo*;TBJW6fJb}x+vs6)RDNC*Q9^`NtNbHgzyjJ7w-4g#d&zuyFem= zdp7O@eaH-1%<*mc+7}?2SFkA#sxhzwYo>l8j>&Yp#ABj*RS~PDWPR1V&~ zo9{%vIrT~z*TWY~KZ-}=sztivDeM#I&?d&`EQfQYYc*H*=~tAgfFoe|r4&t=+ayt$ zsqu0b21`GJbJbCXoe@$fG+q}yv*d9XxH>{Vb}@`3iE2$*fM~k~%dcowU_bR+@Hnt! zb&Xzt29xP@SuC=jL7>qj9UgQRD53PlPQ;Wb;O0<8TdS4agJG*X)i+~CRMqNO zjrHyu=cF3OYHN|_3NuxO*;3tcldmH(og8$k8**iADtck_vqPeXSrAG%j7?y_wnk~- zH@KQ%JbKNIDjgc&6pq1GBgik@F)IX$ZrcJ?Ol9m?>Y8u3>qT%(`)Ve&D)Tbgd3VX# z4tPP?BJPx7qP6y#MAjC-`W)iCDQ7Z|tQd=JfPcR8 zS!=}$uCncR$@$6YMfIma-Ocq3S{)59bVKi_Gm44E`dPe>%?-E{el4Mb= zWJJ}fpi?E#i!gJYsd(k_x&X9^GeeLK1o3)>OlKL*NIZk|gCgW}nd<`r)b|GY{67(5+qa79-IDE6tz2 z^T@6EUZVKYt0D7<(|dS@`*6nC{r3C3HZn77!3gSQfbdQqC%XRcVe`@Z?fYCfSSM

(SyK(fvLsJf-55|4_?C|;wA`P)U)Z&5O(&^!w%Hg2#cfK129Yo-c zXh@q;7IDzMaH#7UW72+mnFO7nXr_1`ks)A+5LLIn3fijYY|YzjA9HNA#6R zCA4jxd6Ko1-e~Y@{xoWlLt258+Tnq?G4#OG^UK2XquWMg_ z-a9?JYnI=5y_?zUm*CU<&q^JH=-x5elH~BdbBi^hTF%xX*~+8HS-5>t=t^KL06Yl?#x+`Wam68vhGE%^;S1B z&=c$7@#)GSo!tGvqGP1IKHbpZ!ka>nHV%4Apga%Yl1i{JI&0%_h(UFPRpevOqMoH~ z8;*cZ_fZJ3s#r**(-Qyoa$tBGpAAR}4N@udp+!16fNgyg;!T;GVHsaeTACF63fA{b z+XkHWy%)$%NZtH-Y?<}!Qi5csK9a{Ar<@W)V6z0D;YKIjxF^M8m_9N%mTJjLVyR|0SiNXm=s*1_*}$fYMZeL%|8$fTtA28;#H9bA z{GD_12HdI+aKQC`A((QZ!)GMf#QO1i#c!O+!y$20 zvjaE;2C6;JiyMZALuZxVdmzGkpLu#4iJQiUTLrE^h;e}$-D1kfZ(J0+Wml2EQ54kM zM9d?g%ceavIDq_w)LT-T-CVN=mBvzeC(cKRP7w8Vfww+I%F=(PFr=ou4QT~WN^UTEF9VfKVwh|tm)#`uhdudr z=!64Pn%n7i88D!ruT`x$;T;mp?tA(Uvvqow_Py=hY&Y2C)dl8W{b3o13BJE*hmJXL zmbw8{wAc+DKR)~D<8aD~LC%MR(l7S&7yXyPk-#o63LGa(uk(w51B{I4{aFDqO{`ll zT!7;{-xYyW>Ajz|W*=YAz4SV1Rx#oCBICT}Qn@rK`h(+VHoup$w|k5=x-nQSeJHkr znsae7q9#@)GpH@Lh(pJO)4y)Q#mp@kSLO{)x?pXX18cSS-b`p|f`w%`@gm_ktsL}7 zypkCz5rR#pPpYZRKTCIYtui}(j`onad5?66>=qip$H_)5y;tc+QLmEIa`nN2vEnMo z)Rg&uaQ7h@fF4`A1O^-QGVv3m;$JBzNNRyS}X1Jsk%ZW?lh8^>)t3x7bKFX%f0(42R`v~UtCh{Anq z+GG79KvIyCtl32kg$U_dzD=G=klg~l45?79*Mo+~w~Jv6BzoctC})Dh&1>9gSpZa3 zKKbxpJ#P))eGZd8Y+p^%}kW&9eFj&uGMC7 zi8(%eb=$G_nmUoNTC+~&okOG4{yzH#7kD=_syZ?p6LI;OE4NK8q2!$6ZWQF7sE$n` zC@LF+m|;|Nq-^1Se7j#_N&BM$sw-DRy<8dtFvChi3e+g6wFr8kGZsZVjUcWlKGJz1 zMm{_4XKc;Z2ySsYlBE(*-fO&6n5MweC6?q6n)vCF^7(eF9sQN-<8!(h==411K)MfM z9Kiq#Z>Bu#E|QBR@c)P^>+O3D71DyHYo~S9(SUf zwIdRgGW5izh&J*v;xd8eBJC@o7-pVLNcHhN0Da&(p|+$*ARJVMMS;>3T_7>lGHB`t zj?2b=Q%Iqn!EB$N8H&Kf2X92f{I{p7MtP6fguw|4#}>UV;30G4#2HtMJM8KH)Ppsf zT;^U%U!l+EK2Cy@;s&qiQli`}TB4s!3!3c*pPIc*PdZh+5z@Y?3Mtc3!TRx9hBJ{( zXAzf`&D7y8NX@Hk zrvv6Lj1L?;UB|JjkgJ3!SxDBPpv3Ny)8GFR*No99K_Idah*h3Pm{1s#;;Ea>)J-o{ z{YuZvw2W^L7unT4;oLFitdc8<#YeCnAtF@%g2fgHFWpYurZ*GL>jEjt_u*AA(*Csa z+s0ARG^!|Me40vefy{?0uKe@#4S1*}{SMOc0nkYO<=sL%+xFmKK-495WCJimuAf-L zNmrRle~E2j3o`OX+}W*o2yK)N+Gs2$9Mrcoa$mv3ZK^_d4x|d$(UCG#kwb49S9NPZ zV_GArbk77qD6=rrO@12zq2=}VDEK(^%70Z0Jlpem-!v*)*M_AWE3e@Y$l#bs-q<_La3A$sj zvxFB0#uY*;JmX@Z^xgM3G;8VyY#G~Rfw|^EoKcwi9T9m-;i5I~i^R424UbA`7g>D{ z1G4o{2sTQLbhWBU;yyeyD);_8;;SDQ96z`!hW5_3&u4xIt$wJxYF) z`932Ymq?`$P#eNx-*O=+dX)0yJ(($OO+X<)CKqM6iQJ6lCsHQ5C@y1Qvjvucyqhw- z9F`?kbw`2%W=CD195lr;pst~#k2NW<0Ytf9auOAon#SWRrVfrG_X*mC-TL;>V~&?q5Eo@j4?mlKagU+oS`aSw$o zo+M}l4P@^0(BQENe*pJ7BiE|3AtIl|ws@{@5!<+j{^PNO^vs86z|;z{UE4k%62x!@dw5X8Ql#3y>?X0FbiP>KX;kMzt6xRwD|{u!UX z^I_ZNyyz?3jlDK%SdRexCS>!(gYap>?^IppD3P9`ohx==&!M(nJB4nznYF>cmg{JY ztVXHwU7IT0_&Gmd7il6LvglvbN^`HXi|m%nVyClka15O?woKYLye`{rluREk^i`Fl zpVP{TJ|(5P`7GgPa45S1uGqe*3rP}=5swN;#8CyMuaX*z;ihFr?Zff!UTI-v#6MyP z$K(0>U=e-$e9Dd-eaO)0ZG(9DzsE5EB&l*3zMI{UeS(+a7m8`S%R6)Ico-*GC1eq` zcRH9jX~l`OaLM1oNNS|8fl`_e=y;ycH8K*HU(kX>LuHLn-$^%1>@L&Cg6ayiezR<^Qx~#<8)wbkLh$L+;?0X7#Y0sdn0$ zL89-<_Y^45RhP*#T*|!F^MSMWW}KDqy-aP{$(W}a7FKj0EOLdiyi2HmC%$eKdh$ln z{N|b_?++GNKl5ET*Z^W zP@bUqThAt;N*y{Up^%9YJ?nQGS7_D!KWP1bLnt|UQp7tv;f*_r<>`}Bi98QKb@%s} zSiro*GUhb6aVM>y1QgNqjeF1BPRtg@d5wIAWCe$>rTlM4q5q#UH^R+(wk9We?=DnB zgzIio#C zpIYiRW*#{eg@YZH`5uDs)8+0=#kNR&*K{j3FKEl~kHJhmsO1;5B+&-rf4m zyWB);dItGhsl8WLF(J+}@RBDaol#eU^UBc*-!xL>Co(iIQ;`%ayq6_J_jT$U4>7;s zw~>Ls;n%Tm$g0P@g>SxxB$o+Rf|R+Y`LffU*CH(pGFT1C5qvd6gLaJCU&a)i1*)Nq z-0HJ1E3Au1Z%TjS4O92NXlgm+jq=VcozyfBlHfcNHq4#oC{-5TE|HwuZj#Azi22t_ z(WiJ2sQV(%3}RGd)6<<>9UgBY8o%>!X)^kc#y3D0`fuN=e42<#Awzb7oQX1RI_Eum z&$NhiTF)yKSoD_SRet_AlpMA1@6j2UwB%6k5#PioYY=o`C#v>t%C>cVyo97Ay!5KN zW>BU8%?j`A?O?onnpK}O9@*q=#8<(kBYb)8ERzq9ImoQzQ`7%GH0b8u>d|P_p*jyx zQbh@+tpiDVSzeb^0$RzwRB&Nr>alwi9GA%a8p{WtVOKM9JW(GZWVtuoWv|bYJ ztH3OdEpRVGc__U+2a4oDXtM>>bp`bKqEZiavV_P$YK#VjS=wd2!1IeU-FG{%j~!9! znawqAthWlZ#Y;6;b-5)z&LEFowP9FakSFIT^3|7DXlUJVBvwpG%k_78TVHO+ZKUaM z^L|Q5@@u^ywyp)s=QegqC~hULqXKqeK0+aZsl#&3NO0zH>9Zs`x?a@OWY&sVLiE90 za`eGFi)34>Rj>GV!RKh*Lf38s4@eTbp1fhV>f8k2iNA)`wDM*6CJo{n!9k<=BOcsZWvbvOW6|wft!E$D+hXB?ny~1JxB_SIq6xQDdA- zzX5_(^F2Vt4)O=<$G|ya;tlcW!t$iX$yS-2ZtZ|ap(x)vfUQ@Y#Ft1hRN0T(i6o?y4Lsamb}(-A|T0po4n>NHS2btj3VIrMwec~49y<(+xSQ|Ex~N4Qk3&1 za*EoR4DL6S_k`xul=3=gs6b3uDpr*pg3b4$u~0LF8q>c7`>Qqsmcg>^18F4*#o55GQXKBRZ*tZJw3R2+y3NM1B^*p;uCZD3LMS z9+cE|U3Gnq3%i&4{?%R@{kg7(cpVl0y_;tt?HyO4?vNDojNVkKrB3beOWI+aLa3be ze!FB|4Jj3W?K%xcx({Ydep0e7WhDRcsqy`bP3|s`ZWzZFB8$Q?2T3ji3n_l|xH1N+ z^#wZoY&8c-PRQ``|#7 z2qVC$1GIDW4$`{qd6ur#Sk}v}fAu->I#|;#6fSr-_{--x)(S1W;UE%u%_KYFj=)<} zTq#qZWNZ%YHE*cXiG(CC_sp8_#)Gt6_j0{emqm8_O*~8?FxKQEYzwSNbb-+~jgToP zIN$c$rzv_l`(Sp3w@-@PbWGA~M8z<24m!{6&=HKr<0^_n{4sVIQ@^sJ5`}wF;NTcR z%8CIcQ!Hq%v;(V>IKP{zwhwr_z4`Mq?bCph?%S`X5`>rapDNGCe$){Pc>WaQYtLlR z0^La!)}KJVO$2j8+P5?}5pN(@jt&%=2?tAW8YP))+V-CJv!`j8KN78(PANU7b?ieu z5Ub|n*PU7hy1^SbRrJR8CgI@c4fr$sSK~m(Z|_TqpBuXVcON-g0`o{$WI~{z35WxB zEK(3&@KV_VW#o87Aw7Krqod8`*#J(oTr<}#S#JH2_G&5P^z`yA1|arLFIu~x;s!N_ zcjpcYfhE>~3X>wv(m3Wi=KN7l;&;gj>*M}5OCp#?pi^OPN&CRgChUzA*Wp-TYQ*H} zWd6W5|JD;N|My7>ks~)nP_%a*BJg}3WZI0JGPzcdpl+H5o%M>R$D9(2T3_@ zdOP!7s|HymKlS;WbBCEvFxVBNnCSCIHNb1v*|JsG`2B!_^W8Mv$=p1}ug*g%o9!C7 z6Vep4CC3w)f`s7ojEc*iD>jw6h zX@%m-SAN`g+oAqx*#ON`4z&@;{bG#AkE+Q#$QlQHr&m`or$;cq%jvCB1h^k+X2-W9 zQVs80%m(xTt{!yvGR2?8ILCPkrlWBWK77p)xIM<)FJy@FPkXNaqeEkKG*0@%0jTXm zAFP*W7JOY&C0%A9hH>~RrhI1tr7F$-a*-0py4}uZHR+L!^l|%&e&+sF8Fdlc@lR;I z>rw-saA`{NPyQVIF^<0LZ0xWwZSd0B`iX-|bOTfkH0Y)$tM1M)t=S9X%-Vvy4=J_} zQ+}_hCq_{fy_g~HO>Q83k~z|N?7Spmv3hd1(I8m`tePcWqguZm{l0ps^*~ z*i~&FaopaFnE)98SBhouDomYpp!<>i-tCPD6{$JFJ%#o4yAGM2+($;kE;3h7vgx{pQxqs6&u;LrMv`UK z>qIESZAJawQ9#ktE*E>PyWt~bm$(#+Efei;>s;h^>n%)5p&RkjM5(_=7nqH3{YsOf zGO)Yf9%(q0ua>ofNvjxYxIlyoHb7wjUnmHW5!4mZ{!CoDBkJzi?izc#qW>h14{PaO z_4|U1mpiwO4I(`wW-BQ9{;mU zL|DWPGkgrb-X@ZrU8_rV9uZPx2i^Wgs*tnZTth%CwyY529gVj;91LyVyN!_xrSfj4x2$0pomsCHn|m3 z0sPdTJ1m@chvF|VUuE2rJCgW=QgfJHx85ho4T72Oi96%_YM|*SzGRx2$^f~y^gz|! zazj3<)%GQxY~v+Doi*aCM1gvKO%zO3MJFt3_krf@$9*_X0@lBvSSiz4mXa`g9pX5T z#C~1%1!f|Rs{p2u^)JaEpOE{hoD^Mb=uWfNa`u7o5nan3u@w9gyX0os0hDz$@)@*8 zSKbKH>ReEGTOiln*;S4iBl6V;)t(uo2Sr<`X&Q6fWUfVeNOOflulu}+s4$Dk6r9WK z7bdAvx;YRV1&iN-IvWS@H$Wj^JY#=8=mIf!d7P!lKl~1>QM7yG@f!`jjQxO#(eraI z*xm4;=%Z34QU$4Bv*qO$iQauQw`3>Q%06b+c*)Y)j@nq2zIZq|!x7gbl)RSnz`~@} zXiMwP1*1p;4ltEaB*X~4K5l?lg`U&0-ZKmrtSjrpevo}tZFDdKWDn#H2gSbg4W%~T zwrIkDr)_UOcz-oBN$o%N&#TGE8@YV*9ySJ!I&i-~RoI=M+^hP9bK_?j_hX0gY8Ud) zE|S>4?EG-=89cY&I3wpHY{|oySHd!kqk;a}T&~y0-_c^s#BP+k+SARb9)A zfqVIqpuTq`7HwlBd8=oq*iRF^5Yq$l8_}F#=*_+PXudmcb{nY06l|sI?ATf@geEI; zr?`_&8z_Xo<1$Lblcb48N#B|J$tk>mtpqFiGKtT|^uggZ+J2;pZHtk8;;PpHH*r7W zv3+vs{$unB8dt!m&(&RPGF z$i|Id3gCSql|yv3R8O`LF|wlh`iJpVjGzzCKAc`xX#EIDeKx)${d=X-0LzyeEHeD) zoZAkthVjW3F??{j$H#8`oH>l{<9yWK-VW@`_;405C6IXDrae46a=&?leFe)G-SKeC zr*c<*UMlH!8rS(eE0FX(#i`S`ayMySiU~ZFI`Y!Pe%%QEezl?8jG8w10&8$*EqDpw z5_LFX_6B_l%w^sfof7Qk5^Sz72IDm30M8GZUFhx$XIx@`SjTQXlP;jQ1{S_f(zgt7+{!_4_Bw?MwdTVaCjFUU)ltJHm9@sUIJ6_ zovc7H^1-P0fWa4wu@kUBx^UxHS|>OI=kSVkz9V9d&hf0;fTMMI50TB|$RB7_?kY&0 zFWsBDO23Y~RAt)uK>^8z+2LJyra^do0!S># zU?v?2?{KW3n4(3q*^IDQI9>}gXgGx2VKpc_LWvW9T21P}{+I~gde}+CrCX!$5F;^J zQov>)fL8NLWb_-T3C?(VU|fGHe6V4x_H#&WAx~kb>cSg zHrDnc?1^jeLC4Z<1b&iCpY>>UVMo zeoSY)Sd~>NUZuy&B0a-$+U#H6IWWAmxvrY%sTj2K7RwGjm=eL4W=*i|`Y7o&a}v?5 zRisS%Q|e;83b(`+Wku3oDVeMKolamAdWKLpzqI^EG>8T}FS6NnCk9EX~4JL); z=YUFjC~qw8iDZk0MWP1Y%d;$*Y=8?_wuz#2DdvAnbDFaM8&;2@EcbqKVue^DLnV;_jd2?-d7J3qzaf2_ z6b@j}0e&rrn?}|=yX1cZ)rN@)+kmHrFq=mk?5jO4$jASqIebuIBLPwo93?rhY0wqX zDCjd+ly@pldMgObkF@u6qB$7{AVlEl()>ODts{}gD7CXFuT(4vYxLGQ7vatFn-5=z z(oMj*Kz0qgKl2;911}ps#e3a^FU-HY;g`COU{BqA)Q-j7u?rG3=mh^8cNlImqzk$_ z4bWTOX)l!5lK|u72g!cX7wNdM{0&4ru(E_w{eO(%uLLWLaPS}&@$}Cna)loGi0lL% zwZZVAe;t0XfWTb4$;!Gce|dby=2(94cGD{8_A{DVMZ|e(=^4J6T6T*K zj7x>=g3Q3@Beq|Myf0Ma$=1(CPZv{Bj4sK@sBYm^|G*BY^fFFN)7Kne&F>W6k9_qM z{kH4C)VBACyqM5#m&#cY>c;PVq(32+pcTzR_G&SO6g4{5mkt#aJC(1URXiLWsOc_1R5qF+lbk)(PI zU{rsP+41L=%LfSbtsT;LE)8Auzk7-%;)=NX z7q8zp*dopa213r!e0=$%0Ms}VK9^Fv<(0GaV&LoiQ|%?u(}DJF=81?yk)eE$5VwO` zt=kK#YR6mQ>-lAMfPe0@eteLV{pktb0TMQk1iIN%_@+yx*_e3LKNfZnX)3rWIKWti_>}~(z1R~97>c4WkD|1Jmf?O064InRX zZar<7LHqaOM$EmjFCY(Hgf$KKiE@U^0vM~NKM$r-pSFwLBW=IyFspcDXYp9J9~q-w zNUwf35l)@=Gj-KVR-Y!ZeK2N`ACtHN4{pV5osnNk?DHzh1`Ry}fAK8h3rQ#T5F4=i zQqR@4IqJ5$+}2pSB_E&qwvdSlztcTL|L`kMk*#wv{`~2zr{<(kZFBi9My216?xaMg z``FX95I@NaJ=*S_yJc-O58~kWBc-00j2_TWz1%=%Fq1HS3&5P5_wT^#0Y)y7@WCY4 z%i63hik5s1Fvc?-s=vIb`BvO$_SwoU>z(d%B5g;s~g}tfqwS)&uXNJ?e5`w z%4ZnE9;$KpD=N;V$jKw!346S99@qpAwn6rnoXTaz74r9tMuYs)+ocwmOc*E&cT@`o@oLa0Gtz+ipLCd;#1ADA{P7m;p&KV}2WE zV2-4iy7!D8XN#wYPFdd{L+USwXpIZN$mT(MQ&7?A(i!=J>rn@KWBq>n)41Y&KT3rg zrkvp@*zb#(3!o6Ua24K2zd;Em)b@NON_P9wicQbpr`JZsKpP*2+lO*3Pg>+~;TNbTfyPlPLT23vIAjh;^>b$f#Tp6WKs0>p6# zUt0-}45W%O>;b)0$~cczRFz^>YXTE7QCV9J%RX>( zOm|PTtVNfAUUiRY`jH4)k2ztyd7;JMnzX;Y)kaX3x?z5}d}bHLi=kC(=`?uRzyV^< zdlW^8>KxVN0RI5w7WlR#*YBv_3`djgzRLjb#}Fr<9bKHi1W$qfc9N4fpxG*X zRubxh@x=PVM7(k{NXupu%RuKy%>rPhtS0fLgzJwUXcTfizFVhxKb;w10Xn1C1vy4> zH((#lo}$sb=Zb0IHCY%E=rvP#dI6mKe<<@lf6LJf;?nfP`{DZqXG5H;$T@^H;MRwo z_AHb`pp^BZ@-bRifiV2iOH{QBcMbvV4*E!R1&JR>qnX}MSpvPr;ZP%wo^_Bs0Q?n6 z(D*K%?deG5ba5LCM;`Y}`*4N`P$FVj|Lh@^Ek*x2aDCV6#qc$PNU8}^Vt0G(jsTJ8!+P!jE2jQ#9&mqCn$NU$t+d0V;EX$GJ zcE*{H!`$C$7a1Fkzzb+xC>RP2eAQS4R`Z0Gpxj*Kb zL;`H(ShXUe^^BKGi5|0-F#!1R*{nRhD zzGxrxOLX#2)StrD#nG9Emho}pz$3S$5x{fl&so|#znIl!1AP2x!>G71;_G;J%JT%~vGYnK>7 z6I+k~M7J@j{Y{{8Afs}F(tg#fkbxkY=Bbe!hQ=)sKDDTv7wovtf9)VD@5XB;oSE)? zsXc@0)n56Gbwr^P=3ZNf9QN>%A>j(Sxs;3awW=sZ_k~iE{n%1-CMp>>;hNXz`dV?RjcHW^w86- z8f&U^aJl^K#0H6LRS&}L6rc9NWC-EQb(1K1_dKxXK;DKCLlcTpMc(lIFK_`}%<{5} z(u_G0wAr0HBUhTePyhr5Fwx^k)1~g^-v`jz1VpedP^|7i8tlM1s`p?eUeU@$Ie=d$^0bR24`BwOfFp$aQ>fRwNtaR0jD3mrAfz}d|k zEXDi+48bAdUDxorc;mmJFn_P+4hCE zF}6PUyMuh%#l4*Mv&2L7_{7n2-8W%B<-gvGq&rrc%d_VA#BSObB>1hCoDYp|yGc zAGNo&cRiwHD3$=2FcPH$u}*&^Jf$l3^8Z#q`B6z-LD1=q5i}q%y@IywTRZn;TP+KN zU(Q+TAvTD1jA8N^>wa`5DYlF^`OBmuZLgh0A`HzYbv~@1sy>Bx+O#^9XvCEg(FfVI z(k&Q`W)Mk~e{0uCvw0v7zm5sIp!42V?-ca3A+;~(wwT9*BJ{~^s_^@$Yn;ZjJ$g}J zeu}+N`_?7>Q=mK9sa3nU-+6iA)Gxb~M6ok{@3QohG?bEyG%xiNiBc37~xC$6@z+nW=Igz-eaWH6gc zM&-_)>}(5D4fR|gqp#AbV4*pVr>f+;Z{Hx?dr)!@b-2r%s3SrM?PIYs5x;N z${&jrl3&|t9{>?Lhm%y z$0=ln!Wk(3Ahq){oMWOmBl)g;)Wo7La+6RI+!A`sP{)Y|)aMbHmA&MkxwDPh^SIkZ zlx^)KVu|4guvuS&e{kEB9)DI24Npvx0zSjZK+(&1%ZIx`&rxKmY)l@jVIV{$5GkB5 z>YA!f*GL>951yn8B`fqElnQs&^fWNA&UIym_qpsKG1z&kc z*?B|cbRHW6c=Vf2KW$DOq=FhPYkX@_eel@lBGb@*EwwtIHL{untDb{DhvUgkqPaLP|;;P|TeeQ1%CaE7>M zNO8V&6+G(BzIx_#>;1%s>UBQH-mNN^I%6wdMbff>*;fW_j)^NwQ)GkzZ?@4Ht6Lt;#yPPrWk*iM^X7?1?{=MWeffOhuYt>z8{{}UMw`@=_lUCL zgP6HwA)ZQGE05)brqoZVzgP*7)34u zt-`GeLeTpSWW}pft}(*Y#G5`&hUHdKDzjui%Xtq^(DM{vcb}!Z{$jmzQ)Lfza_4-&keU1jI!BNI0ok&Ujd5ML(xL(>u4YRH zSq>X4QPs3Q_eu4tpF4Snh8|~mAi>!)XOH#EJ;vdCFUt62j)lC=HALOc6IGB-q0!1e zk?UO386{o!#^L7^g)*?ZHSl-j|F$c|?050MH=0K+MC3#-lh!IACIy2n#+k)<>QP)jqF1$_m3>DU+s^PUw4(UzZ)c6tC8b?5RP=oY=3zi zH-B~U2i`_B&g|0pz**N*!4B7`aVa0U&N4Oz*ZQiMkOC?NSiVDiO`<@&An(Co<1j3e zl4*(cz~WRMtHX1ABrU%}5-7=kMZhJe5j?C_EV$lq#+@vM8>epTZAmWdp?p5?uLWXh?_im zkceeeZMvjI{olGRUg-f5 zCq#j16Ps-+v;XC9Ms7_RyOoz&a)y8irFsWnBfPv5S-)+@=A}U@H(T)L4>CD+Y7m%} z*0QC)*%S%#Tbz?QQOjCQKYr&NgHJVK}!t)~ioE`4ItZwFH`CT>Ed zE^-^*OXM%aKL?Hq7 zIUTnvnU=*7w0l9!F>_narul~*_<%Eb@|o)UKsFkhp4)IkmO*-k;HwiB_p~^$XgVnnaZwcb zeC^3fs@&tJ%l_fi5|>9de$WGa4tDIG0R@W%@Bvg=h6S8zehm*@B#rx0H&kra3ieHe z4nO_-HSfVJIFnL0?Kr&jOOVh7@dkry)2r62S(e>*(Oeptonaa(ML7?(v9 zM7~(v^LF`+@Kr+Y{?%%7DKi{Ycqx=0P=Tpyg^jYXRZ z;5{h8t-1`(kk%X)P+n1PpNd85@xSz=RJ~6Rz7pbHxbkDcgRY&DbHcGCB1n00oR5D5 zQ+bde%x9FD9&5Ixv?u;8euOwibk3fKYk2QWIhX}iP1GM)IEn&_xxPo{M1c;D5!9@4 zVYJ6z4^VI-i+V;fmk&v!@~RK>ahz(42Bmt@1HkYp;PbCLS-;5{et5FtDesA$Y>a_K zQ9uQt2Spi?I8)C!n`YLL>W#qPWKMrks3%37@;HQ=zo!N2g3ffOuhP2En5e_lu7Oqq z?VZ$9>nM|lAtPw=6ER$RR?+s&Wha!5Nl{dYmZc$ke8_Y}23Lp-F1FhlKA9XP+Ror~ znyE}^vz9Z6hgl)CLpAH==j~B94ZH64)i~Wu6`j;xmD{OTyF72SMoI{`40Y8ZPu9F2 zy*5M4LTPz|%q;6o8zKVR815VUd6EIyUcOn1SzL&LYL{70-lw}pWA@u{wp#G(I#om> z(aZ`VDOUj)WRHuhL$l298ncQw3MicTf?fh+eP3B+X2zF%%`#u`oMf<~IP>U>uwy>^ z`G6DML}de(oIvV8M91_rb%5mYdB&6E5sp6f#SyvW`EZtkh$Vwk(SszL+bINeCT9h} zkfQ7jCc)`|7GQ>AV}E3uOZ+bEd6?hoF$eRPz6i#nPBq{I+(WS*jUCjH%KV%3dZCcd z^$%ATwHl{2mbwl-68C{c-&N)gqq1f*Ny)@j{ia-rD53>)&v9F^3>%~_TcE|S^>V*? z_OupnLpMWSA+y70TEQ8P+Og)HNa(ox^Z?d$jA$x;_ef|~G}STSE9rqf-!=YUY$^wJ zB50gI6kOChfZZTeg~rQ?sGMFmJlGsT?6EHLK6_A3v7Bs>i+&iCMAyxR~ z#MsAYy5PcBh7&A9>k1wDCvJn>@G;z}i3BwKFd(GJB_|5-rjN)&vuc%aDj>Kb+7S#< zg*uh(mqd!&RT|(zq!_?|i$6>ZNa`l=0g)nUNF|gQT>Sj|-=v+Ak~&R&n7d9zNSG!n zIob|t7koHjk#+yuWtXmOQ_^_KAf|Cf+fnveIhH1<9AlJh~3##IZwq0tuk4WU~_DeDg|i0fH}(-vM8W3%!4r)-s_ zvoI8d!Z`FWaB3%e#W}?H*jfa!JAZBEPBq2UC;2~*LB(*n|z3lAas;RW;?Cz za_ow0<`j|BXMB*V7%clWDB?yo5LV7maM$vxoShY8>cb>N=6#aQ>?exgCH|W8RtJYL zChedzlf`vuIY(=ZWlHJP;bS7YBbe9`u!t(>eynHCmgkt)8`4^$YWG11?Q9cm;?OFoDGsyJ2ui4l2p^+$>+VW^|jc=CCo6x{}!k9WuTGh1*smFi) z9FL5mJ8GMWvhV_r9vq*9OkE`9#!C`s@9EOJRTm+!dIyb0(a*8PBNJKpq#dZ5i;6p#`f0~S1V^7N#0>WHPa z<k&Sl08NBa4`8fdXRbqS>f!sf$>!IqR?#D4$w6)y-cc3M8`U(Mju;i2{tg zSP%Qlxn0B}cxTe7sRykt2t3CO_{p4q+esQpxevVJ>m#mEY~+z>sMQ8Mikm5s)(#Cm z4KFtIi3FTig8BU@&mm&C(iyf#HG80Oh8*jFOud0csr0AVo4Q4?Q_00SKOV!(ow1j7 zk&ft=+(ZAaWXsbxt>nMJ+ik47hm7UvsQnAdQ??M>L*qvdA}unjJ)jd#tc&Xy3YFjn z@;1a#-nj0a!so!(7wKA+u1R%i4dNMf=^2{(SrzjhYAip0#dSI_`Q;E)ZE0>#hl3@FaY50jVun#bmyXI&nI7Kjkhgc!BG|egi%C z)XQ#UV>sR>=i`$+OoBf-JM@*@3InmGU>RFQ;UtRr3b^BtW{)ol-N31m@ z(12$j$S)osA>CtFqjLp(h2DWQCop7z@`apGBNW@E?0ibm2BLfl$d+*-((8lF>&8A* zW~0vwG#aN?DPYh6BKR7$;bA1h`}z*ndIk8}_k+jWq~!6MbL&ZDvAVLEIx(V(Fe99S3t5!zZ$= zdgo=jbMX{SE{o$6kU(u;hYJj=k}}_4?t7BNO=|LaBSDL+iCDT?rV$il-rQXRI!Ph; zMB#WO$SoZLTDVmxK%PdAGjai3LB{oNRj`L&PUKM6C2w5y_&BcB*>K(b#EyZ;J}LU@d`@L-Vy zXx4~R@@s#Z9whxo+D=3n(C$tSy-Ah*hilc^Sj*aU%^K(FzAEfirb z#DE^=U2_U+Sg<4(muMPsu+owoODwuFO~mqB9M=Vv9q%Q)>>eheC5Ti4#l~&XFi}T4 zkAV66(RHdCY!`hmkahJq3QDVp)l5gsp~f0;tywkVW>ekVkpg=1sra`uhP?ijHQ~GJ zELnaj3u6s{_pkYZqW4QLo*6o7)SVl>ZtcH7Fxh(iV(Ufih39EQ)Uuj3$Jg#o=ju*2 zm7sY?i#~iCsJ;G5MuQYmwQE0d`~11*-@1Kc&N_N1xGLAxj@}<197$U~iDqJ;9(GQZcxAOAi3>_y#j zV`*ob#_JakZEGAaZ#LFeJ^B4D`E#9$j?gSu^7ZQSw&RWPOMr90V+q4^{St$YX+{!rddX+*z*$}B|!@9?NxDJF>Ke?)Syv`djJ^?wKSIMmJ8#wPH zf4YOLg^#4@9eDcARtFbwmT5ISB*#z_VLQRvTlbB7$!ffdRlDnCqfWBT0ajiTY%3TMIU-YGI!e?e z+&iql;5J9O(pALmax?PxGGE?8e9YYmwR^h+Q~*8qvx^C6PJJjMiX3>e0*X!W za_;IT0)vqTr}G9$$d6Z}4p%Xa07ji8OzRW1g;grLrW4vFp&!lSNytW_Njyn8^CTK& z?fmhaCX|#&feNTLZMQ-CLtZX|k6%KptZ?>G`Jw4f@k>&`_8gf}bk6f)!7$Mb-iT{~ z-d`8R@nn+WZw!Y*JsG6|y?K*ew05(zEAN2kySCFM!7^8xiT3VH9pt4c(0~nl$=J3< zhC$70G2*JMRh^QFx^bnf}Ojzcn%@S)%@5_5wG6@nY-6g>QeoE`*Gx%IM9>(WgJUVLMc z_xPy`TDge=rrxZER>4$yV>S)}dD(zdYvc@+*6m$tbuQjpfS7VbE=rlFHqM_VH=H8K zk<8z~&dGVs^o9SK^KV7hHrxxZ{>b4hr*QhSISa@ev%e?G9$fGs(kHcA9xXlo`)v{} zAi{}7UKch+XHYtalKt86U>LWazu9MATa&lC`03=y$>`=lI1#`fpBqZ0zw$?jd{N+d z4;mK(I`ozI1LAwsYvJ#MSKl;4;YtTy8k8+(V^BYKp-5|fddp)O~; zvbU~ZdhL5gJ<--F%x%;~-OSHvwSIZ8S?1-r>Jw*jaJk&KdvR313g&<&NX1tR%w<>e z6`r-{l$`&+`Xg#W7Ac*a(Gi+iao;dq<}kQJ#1BAUlfK#vz@Y& zKF-^O?MCBdA^LK>j>^$=GS;EgIR`Z%GSqT+lK6#V5Q;pRzt-}dx1*aw$NwqXOmAWL z3g`HkmQp5U@`aoswSe2?9YJ{|!A4PTIU%*c^)wj#lKb?$hPul0!4jX|dycok@?z^h zZ}h-=9La4h&ZJ1q+MI&=)y7c}E3KbO_%wo^J=(!Zr2GQB(7tV`LZBB%W~bjnJ@8MaovS|Fb$9D1g*lWgXc z%yYObxXf<5Mf!vA_XwD$gb$Px=^Zu)ZIkjEJ=?V}I4+k`#`(-v9_xQ!ke?ru?-_{x z=&86B(GeiGK)&X3`Dr{4UO6mGCfaY_BW6Zud>@-6Au?vkhF1nNyeQA_*5;WmcqBY* zQ^>kMH+JbfMeM{&Xg`iQG-BHlMtyEBX`lzeDQP!4Z9S+SJ}fAshGCYNS#XKA0@BOOS-hAEYR9KqzXXUez(nSn+f zD>;YF@+BD2oNCZ4#b)?+#1tkP%zuC^i-D1;oQYE6`M^_P1mh0GqNZBGt6F4mZ~dTk zlRHrOkcF!O^&TvP6^MfTdKfbrxXpMfH;yd1))CO%y%dz*wGGpP4XQ(%ltEi11>qU* z5rbe^r|>ckp}r>KBtX@wDH3=wdi3YHD1y7bW4d_6n#3Wdk>59AVw;`OafPbm7Z%p9 z))|<_^?o)f`4!e8>AvkOR)e{gVK>`yOUn4NA@0|;lpo`IF&mO9OiJBnM-?LVvry;1 zPzqd*n!{fAR(=A~@kj>pEXJ9`@0u9Dbo>Q$_YlqW&eP=I%#s=JYJtNwx{vQEcc+Oz zE{`}DcR;JkVibmXbYAQE0wU_AE!tS1jGSF>7~ZKAEGvDH?=z$Dwop7=}#0tpzsW&(MUOZJCtc~iK~~ngOuBoxST8R;+4wqFZhMuMDv>_G-r~o11HI}G zL>$rCKak4LBehr%@Zi*>{n8evEvphtXW;z$^wG^5?S|}y+bH@?$}Vzz-H~Dwd?=FZ z(H!n1SXJBC%Ro&y5Q?u8cM5<@GMxgGjV(V$T!LJU%aEY4V5Y9+3U1WThevIo%DW3De5sA3de-!y6 z!GpggXrg#{YYJAtL{IG89+`?LGj}foK&EYPWCg^Yk@%3pCt>-Rrrel&hrWJx*fEj@ z*DExl{E6Wo?+uQgPw&bG=0~ytk(gM`Y=|!Dl$sc#-QdR)CM&DrF zUO$H6wDgWbtjK~W`M@12BKaD%m`X@a6KM0v!Ok9QHy@lO1d-BBoWEW!^7s}$uwB!8 zOK>6Lsj_C7aNBcbo3Pc$-V=ov`|wYq#Iu`bo1#F*u&hg1S zam@OMPI87wf>KfroV;P=SFOLK{KR&^_T^P0>-i~8%agiTWV@yY7P(LIYE089Z6r|< ze2IK?!WkxxEl1CCr3fA}pUm6FB-U+jqxK(yAwSU|QMNvMPR8awB&Tg0o9@zuxY#@` z6s%a&UPnf7bmswvMYsG-_@quYg;3Y}=+KF|bVuEo6obU}=&!vDp(?k&2&4*X9yrgo zPw;}%bGBUebbTxddwVNql`ubmxyEl6 zjeG3l=UY8N;tHbEiJ5-A`NnZuZ1q02(t;=2KL>;TZT|AoTgPp))%#fhw?!BuM1i*^O zfxQJ(VrKt&i4uy-tlVejXFM;pvr~yUI5&WY;4Dnut!P&A7hS~CD!`bo+zmz16eZT5 zBv1lCZ0G~lS@vS!7qktvKD8P_OQw2)U-ZRaxEl4s)VTM4GMiI}fsZ#4AH}<#`)YeX z^*=_~1wNL34B6?QhL(|enmuX{1(iW7%~29E<_S#Rn}DO_n5ZElgcvFH8X&Th=mSUV z#xGXba6wzVH?&^u#nx@rPoObnKUdZanQa%^0VfTg8#6Ew&vgy9SuX%9oe5RwA?_zR zobdtL>my@tf*f*mrIcpbkvQM|2mdFGJsSK$@>kXAt)^i-U)M`Dc#UVL;Z=!2e} z-dQ#~TpLzN04WR3KthSHh}-^4#&@uo*7VDsu^dLwy81b(`{Z2@Az$>hQbev1*ZCfm zu&E1)rjqDOip53&5U*D8%^}RD#vby# z;RzmY0xFIrfz=D~Q66(XgH7pr81<-k(x-i~-{TwFBdf?6J-23VFHuI8sDviC)au5D zgNFu&gx=WUM*V_J+KD4Xj}?~g{@fYK%TC@$Pr3t1FEh#9F9H*^{LUW^YrwFa|NGTz zTSagfzQ0*o@Fy|jAPG7$m0M5_eFqGs?GA}-$F9dS(WMD`Z?c)aV`ui@dKM?)*VVFn zS@DA%u(v%l`lF%Q8KA6q)K}==F?HB}o)D^MBmBXCK1Ss${fpu)tmT>JnoA^dS^`n_ z@E~RrS`s{+BPRfrEF;bg5MkcQ5V4w^zd9Xr0Qpd0lJ{lC?ZLF};~74W=&f^Q)1#v{C|dW; z(2Wz`xWKX*y%YT(KFuZx-1a-6Q%p!H+|$faPJ|1cf}j_aZ|t}pNTuh>#>|WKq`S}A zd`Rgf1+Ui_~=S z^Fbh{=kavh_Z>9v!TtLzGIKA>S0cXgdVFlJOqZNZolXDH7=0BC(ST-2PlO0RY*4ah zns*w2(DQoG9gvd{8=wI>_K+ZfqQmBTP>w`HAgbeySupipiZ-YNI%Nh?Z`et7tWzDP zuJ)O4Qc016sI?d{Z3L*$9|)Kn=-;IM#JmHELz59tm}J>p) z@$u4xo0;jc=E+HqhM(^v2R?W}8)J11ZP^HicN~J!*_jNSe+4IIee$JRE28##@Rw45 zzq+WtLGDGt3&#W$f1t?NBsYOW&{YhOY;!l25f%kb?uo|EQBvBqVEIhB-Uz|i8O2M- ztMC+pJ^}3!L)lu!5r5qwCll9ZCwFe%BsW{Fl|v`i$Ees=1s(;xsoCa|F>O2{bcrkl zUiA3!6Aa$^eR0nE0lwLy`%Kc3P#aujFXxeH%d}Fjw3|HrP)CQ2fJSKPfZw4-T|qGz zpVVD6&}Wi>OYH_yf}{poEMNkM!n0mrZ)33CEZeWWI|E}_}kiDf;8--F6A#s`XtQk)V1yUev#3 ze3?v&o8`oxS^bc3?&2Bs>+d2c%ZqZW@bWsq#~M5ib!8l{x(w->>>GwJnsX5bGhKo) zFe;?A2G|HtdcZO4HnoRTSGq#QSGxfcy$eyKahMi$-^{W5X~6j9U%N7G!>w&T%I^pj z#`7+sFS9dWPpyYIdH^D_g2@nth;r5|u zN&(3&?b)?0Ufj=hRgMn0!iJ+|kW$68`N-%G$>+b4G!0eH)Nku!c-_xim zV1y*}Hk)8Q(gxm7fnrNf%f`W2hrG=3{p0gGRi$YGx;gzD$bpJ4B@x*t2!_V(~ zgI%6K3g)* zH8N{WX&nsqLcclK8{J8j<$bxxOB+@~+#6p=`Pxjf)GX`z^+;X&f9M(h@a*aPq9VUt zU*A8EyvuYiq@}#zA7+}r`Sq!J{^hRd0VlN;>%P&j z)rV(p+5fY-cXrj1|Lg_rsk4^yTSN@;P{it!s z`=_*`|BIEMJtH*hd@ts9_|}uQr9&v!Jt`$cFIp#Rf2Gpiqb^mGw}Vdwq?2OAaWx>7 zqUk)c&Wo9Pjl90^l0IUQ|H;-HpW7dw`G>JSw@atc_o$|00`tLb4nhx@a$s$;0P%9DH5>i0r!;m| zjjgq~S?*(MGgE+F=kZ%aK_|ygZQqGk&Oeljirn3TcOaN|yYm=`gEsZ?PE<1zO3x^t z7TOlkSgqPgz}Ir)Kh&GF`LTrPMPv{WLh6b2hjNTcv6>*vv`~i6H)iSKcj8yK^{O+) zqUo6>=oPXtag0}I;d4_O#*ps7X~#L_>k~SrZXX?asx%rTSSH&bVfI~{IZ!R;$#z{p+rmpx@Dp#nhn1ciFfGnPDx>Pr;P{$~ zpqvHoOp#=%AHIYuyPIV1Y>kFRy?cv>x?df+8<&U%_yuA>0s$^o=|M3%B;^Go6yQld zBo};EWQ9|SzYLPB3_4wS=j^UKbm@krTq{W2wQ(ckzX1^roXWpv1g~Pi?a52CT@{d? z4D<#@j?X+iaws^%a^arCfKZyLhBVi+-b2+)!4ma9kEABX9-g7{s4_qsG8xV-$tMNi zfN5cERfG?xRQ2(TzTeLiX~=2yHA{|XWq?=S67?ll&EoPN>_jVjIBtP5KnJ=7{-RD& znn?i!T;GxFNs9#B8`F9>-T^|M!@WacH=D8p!6oV!O7j}ZyWnb5=Z;4d)U$(DcL+X2 zTV4Yo45TYF5}4bnpK@LuL!ozaNv%w}MaOl+E)L~+nfu-Dou{`WZ8#dM5AQ7`Y{!%h zUYdpRz)!v4O|B>)q$TB~181y=)Riqnku^LxT{d^WtOPt^cRTi3*^59;2-JdR@3T^* z*Y}0crAZd&DqqMIJk7cILYoN((U~r(4P*Ka_VN&r`$m`xy|A-THM@t=4&o{rkEE4E z%ngVfk@c*ddp1kaoRa-Xn087UL$V?m)5nl>551I%xuHF&j?$hz6 zPFKL$M#W^N)1m+a`&-M1l)wA-@-Y?W{itSRH(#;l!mW@49B%~hUFTZC?Ok1qj?b_|Ko_b%Ect|mfQw_Uwj|)%Ag&B10#2%^IDWrRhcP9F-EQ0v*2%~z zxlRl2?(&1IUVME0tS_)57%FvS1jnxfZ^yWU;vRHTQb;*2rdp7Y-&1)l=%W`ylO&k) zJn`AVnpTj?G=?U#UUWZKcE_K}($aWj-PfmJ%tfo|h?U)o61MMOPA?bxU)+fx2ZM$8{0+LiW$qa;Z%v;oi$j|$;W=F#KCO^p~DUx<>#XL61 zleFLaa9?8f9dnz8h@cNpCWB|_X7+3hlW(mZnp&q-hjQTn&ksv`Fu>&39&|9X4Vv9k zR?!T+Epeo!aDyg@17>u13R)T|VE!8F|8emwi3MVy{vF)U9q@8AqlXTEe8$h}E*(DA znnF*_wws*7KUdk`y&VWoC>8OsAgQyw`^L*@EavJm)exX>L56R_7VO)g>3#jas#=^a-QdOnpQo1gY}%l1 z*MmXTJv+E4XlMr+4ZRw=-v%x3HN?fPp`dRxLPXr!8pK|)UarGJed!<76;qZG9G~W0aLESBP6%-vxfJMXSX2rv36$67 zSpLI}z|F|sKh>#LEdKWx{WE>5N_zF=4j>vZtVxCT!@#~W2M=APpNA(AO`~{*M++R@ zW!41hmmN$L6tJ7tDf{E7LX9pI2+mM1pOq*(H7%rqxvD_iom>eB>{zjhZ3o-|23F?O z_@itMC=s{0togi4Fv8a+m*{>h{>^65{p1f9zH{=dB&OlQb=uo(XaNGE=8WI zowHlXD9@5R3oS0s1E18|_qt7c6`5^_&}N4`TJxljJ)yKkM&Z$$GxqTE`)(f%+n&Hu zkPU+~^dM7%XXjGKkg-+YE~av^@VEo~hvIr%t}&FdRJj8O4!OhAhPhx|%H|NPo-)B> zodd?-vkqg*fjux`4U<{Wx$lgBJhEfQgGyz0pWX|ghm{>2V!{ENG-sxy+b&6^{_tWe zH2tJ?4Ydc}(Mm+45*5i5MkA@J&Rc&Bfw}{gE3fC-b{tn4%)dl`RZBGHuKj%_J8WS9 zS1?D$+Rirt1fIYaBqF-JC`kz3PFLPzXAa056-m`O^cdb*7;@Sk@IC=^&G(O}NM|{J z8}y9Wq>8X~3p0}7ncRYPm65Xn(+Y0xPQr6n151jzOpAByG(5Dz*V}iHv*$C`Fmu1W zmF{0B(PVKz`g&|h=MMTm#?PnyL1d?9RM-X;*FAPa?Sih2u-f@N~v$(#iZJc(8J$wEDy)MfM!Drd6zvKu0gqP34b%EalmlGTYz} z(`7tx25g^ml$!Q=rQw46ZCZ(1(ipDnc;o$B@E{t1$3nnVl)>3F22F7;2_dl;0wHqZ z<5FH)`!gmEh-)B&u-1Prm(F%a_3O)6r|wUZ@B}iqXVYZ6zHbR5_jv*)1}yhuLP1zz zR`Iyc`(|O)MCUp@Y@a>6a_xnb-~RJ|dwb?VP7JgQ(K~wiB2q(Z^6B6|i_>RK>WwbN F|6h`&(+~gv literal 0 HcmV?d00001 diff --git a/integrations/torchvision/tutorials/recipes/densenet-flowers-pruning-recipe.yaml b/integrations/torchvision/tutorials/recipes/densenet-flowers-pruning-recipe.yaml index ec8a3b33b1a..f73c5455c47 100644 --- a/integrations/torchvision/tutorials/recipes/densenet-flowers-pruning-recipe.yaml +++ b/integrations/torchvision/tutorials/recipes/densenet-flowers-pruning-recipe.yaml @@ -1,7 +1,7 @@ # Epoch and Learning-Rate variables num_epochs: 13.0 pruning_epochs: 10.0 -init_lr: 0.0003 +init_lr: 0.00025 final_lr: 0.0001 inter_func: cubic mask_type: unstructured @@ -29,7 +29,7 @@ training_modifiers: pruning_modifiers: - !GlobalMagnitudePruningModifier init_sparsity: 0.05 - final_sparsity: 0.90 + final_sparsity: 0.85 start_epoch: 0.0 end_epoch: eval(pruning_epochs) update_frequency: 0.5 From 4ab73544c4d5aed01b11a12800d4e82ef1590506 Mon Sep 17 00:00:00 2001 From: rsnm2 Date: Tue, 14 Mar 2023 20:29:13 +0000 Subject: [PATCH 3/4] added all --- ...arsify-from-scratch-densenet-flowers.ipynb | 41 +- ...-sparsify-from-scatch-resnet50-beans.ipynb | 2233 ++++++---------- ...rsify-from-scratch-mobilenetv2-beans.ipynb | 2364 ++++------------- ...> densenet-flowers-tensorboard-output.png} | Bin .../mobilenetv2-beans-tensorboard-output.png | Bin 0 -> 161928 bytes .../resnet-beans-tensorboard-output.png | Bin 0 -> 102164 bytes .../mobilenetv2-beans-dense-recipe.yaml | 8 +- .../mobilenetv2-beans-pruning-recipe.yaml | 7 +- .../recipes/resnet50-beans-dense-recipe.yaml | 8 +- .../resnet50-beans-pruning-recipe.yaml | 8 +- 10 files changed, 1360 insertions(+), 3309 deletions(-) rename integrations/torchvision/tutorials/images/{densenet-tensorboard-output.png => densenet-flowers-tensorboard-output.png} (100%) create mode 100644 integrations/torchvision/tutorials/images/mobilenetv2-beans-tensorboard-output.png create mode 100644 integrations/torchvision/tutorials/images/resnet-beans-tensorboard-output.png diff --git a/integrations/torchvision/tutorials/docs-docs-torchvision-sparsify-from-scratch-densenet-flowers.ipynb b/integrations/torchvision/tutorials/docs-docs-torchvision-sparsify-from-scratch-densenet-flowers.ipynb index eaa66ddb60c..171c56d35db 100644 --- a/integrations/torchvision/tutorials/docs-docs-torchvision-sparsify-from-scratch-densenet-flowers.ipynb +++ b/integrations/torchvision/tutorials/docs-docs-torchvision-sparsify-from-scratch-densenet-flowers.ipynb @@ -71,7 +71,7 @@ "NUM_LABELS = 102\n", "BATCH_SIZE = 32\n", "\n", - "# imagenet transformers\n", + "# imagenet transforms\n", "imagenet_transform = transforms.Compose([\n", " transforms.Resize(size=256, interpolation=transforms.InterpolationMode.BILINEAR, max_size=None, antialias=None),\n", " transforms.CenterCrop(size=(224, 224)),\n", @@ -170,7 +170,7 @@ "id": "b385497a", "metadata": {}, "source": [ - "## **Part 3: Train DenseNet121 on Flowers102**\n", + "## **Step 3: Train DenseNet121 on Flowers102**\n", "\n", "First, we will train a dense version of DenseNet121 on the Flowers dataset." ] @@ -196,7 +196,7 @@ }, { "cell_type": "markdown", - "id": "a2161b6c", + "id": "eb400dc3", "metadata": { "scrolled": true }, @@ -227,7 +227,7 @@ { "cell_type": "code", "execution_count": 5, - "id": "c1ad9112", + "id": "5f6a53f1", "metadata": {}, "outputs": [], "source": [ @@ -237,7 +237,7 @@ { "cell_type": "code", "execution_count": 6, - "id": "b4b0f03b", + "id": "8653c9bc", "metadata": {}, "outputs": [ { @@ -269,7 +269,7 @@ }, { "cell_type": "markdown", - "id": "11d180fe", + "id": "c31aed1b", "metadata": {}, "source": [ "Next, we use SparseML's `ScheduledModifierManager` to parse and apply the recipe. The `manager.modify` function modifies and wraps the `model` and `optimizer` with the instructions from the recipe. You can use the `model` and `optimizer` just like standard PyTorch objects." @@ -300,7 +300,7 @@ "execution_count": 8, "id": "d00d175b", "metadata": { - "scrolled": false + "scrolled": true }, "outputs": [ { @@ -865,7 +865,7 @@ "id": "8a7d6309", "metadata": {}, "source": [ - "## Part 4: Prune The Model\n", + "## Step 4: Prune The Model\n", "\n", "With a model trained on Flowers, we are now ready to apply the GMP algorithm to prune the model. The GMP algorithm is an interative pruning algorithm. At the end of each epoch, we identify the lowest magnitude weights (those closest to 0) and remove them from the network starting from an initial level of sparsity until a final level of sparsity. The remaining nonzero weights are then fine-tuned onto training dataset." ] @@ -904,7 +904,7 @@ "execution_count": 46, "id": "d367905a", "metadata": { - "scrolled": false + "scrolled": true }, "outputs": [ { @@ -1043,7 +1043,7 @@ }, { "cell_type": "markdown", - "id": "e037a028", + "id": "322fa136", "metadata": {}, "source": [ "We will apply pruning to each of the `convs` and exclude the `classifier` (which is the final projection head). Fortunately, SparseML allows us to pass regexes to identify layers in the network, so we can use the following list to identify the relevant layers for pruning:\n", @@ -1126,7 +1126,7 @@ { "cell_type": "code", "execution_count": 47, - "id": "b2add8fc", + "id": "b8518b39", "metadata": {}, "outputs": [], "source": [ @@ -1160,7 +1160,7 @@ }, { "cell_type": "markdown", - "id": "7c4ba042", + "id": "da0a5909", "metadata": {}, "source": [ "Next, kick off the GMP training loop. \n", @@ -1175,7 +1175,7 @@ "execution_count": 50, "id": "601c8c21", "metadata": { - "scrolled": false + "scrolled": true }, "outputs": [ { @@ -1836,6 +1836,7 @@ } ], "source": [ + "# run GMP algorithm\n", "epoch = 0\n", "for epoch in range(manager.max_epochs):\n", " # run training loop\n", @@ -1861,19 +1862,13 @@ { "attachments": {}, "cell_type": "markdown", - "id": "83dff592", + "id": "3be34fe5", "metadata": {}, "source": [ "Here is a sample of the TensorBoard output, showing the validation accuracy, a particular layer's sparsity level, and the learning rate over time.\n", "\n", - "![tensorboard output](./images/densenet-tensorboard-output.png)" - ] - }, - { - "cell_type": "markdown", - "id": "b9dea1bd", - "metadata": {}, - "source": [ + "![tensorboard output](./images/densenet-flowers-tensorboard-output.png)\n", + "\n", "We can print layer-by-layer sparsity as well." ] }, @@ -2020,7 +2015,7 @@ }, { "cell_type": "markdown", - "id": "c1522d44", + "id": "18fed85b", "metadata": {}, "source": [ "Finally, export your model to ONNX." diff --git a/integrations/torchvision/tutorials/docs-torchvision-sparsify-from-scatch-resnet50-beans.ipynb b/integrations/torchvision/tutorials/docs-torchvision-sparsify-from-scatch-resnet50-beans.ipynb index c57b5c7776e..f3726bb5a39 100644 --- a/integrations/torchvision/tutorials/docs-torchvision-sparsify-from-scatch-resnet50-beans.ipynb +++ b/integrations/torchvision/tutorials/docs-torchvision-sparsify-from-scatch-resnet50-beans.ipynb @@ -1,251 +1,83 @@ { "cells": [ + { + "cell_type": "markdown", + "id": "00e081b7", + "metadata": {}, + "source": [ + "# Sparsifying ResNet-50 from Scratch (Beans)\n", + "\n", + "In this example, we will demonstrate how to sparsify an image classification model from scratch using SparseML's PyTorch integration. We train and prune [ResNet-50](https://pytorch.org/vision/main/models/generated/torchvision.models.resnet50.html) on the downstream [Beans dataset](https://huggingface.co/datasets/beans) using the Global Magnitude Pruning algorithm. \n", + "\n", + "## Agenda\n", + "\n", + "There are a few steps:\n", + "\n", + " 1. Setup the dataset\n", + " 2. Setup the PyTorch training loop\n", + " 3. Train a dense version of ResNet-50\n", + " 4. Run the GMP pruning algorithm on the dense model\n", + " \n", + "## Installation\n", + "\n", + "Install SparseML with `pip`:\n", + "\n", + "```\n", + "pip install sparseml[torchvision]\n", + "```" + ] + }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 1, "id": "1ad80edf", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "1.12.1+cu116\n" - ] - } - ], + "outputs": [], "source": [ - "import sparseml\n", - "import sparsezoo\n", "import torch\n", + "import sparseml\n", "import torchvision\n", - "print(torch.__version__)" + "from sparseml.pytorch.optim import ScheduledModifierManager\n", + "from sparseml.pytorch.utils import TensorBoardLogger, ModuleExporter, get_prunable_layers, tensor_sparsity\n", + "from torch.utils.data import DataLoader\n", + "from torch.nn import CrossEntropyLoss\n", + "from torch.optim import Adam\n", + "from torchvision import transforms\n", + "from tqdm.auto import tqdm\n", + "import math\n", + "import datasets" ] }, { - "cell_type": "code", - "execution_count": 4, - "id": "4d554578", + "cell_type": "markdown", + "id": "c421a838", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ResNet(\n", - " (conv1): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False)\n", - " (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " (maxpool): MaxPool2d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False)\n", - " (layer1): Sequential(\n", - " (0): Bottleneck(\n", - " (conv1): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn3): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " (downsample): Sequential(\n", - " (0): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " )\n", - " )\n", - " (1): Bottleneck(\n", - " (conv1): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn3): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " )\n", - " (2): Bottleneck(\n", - " (conv1): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn3): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " )\n", - " )\n", - " (layer2): Sequential(\n", - " (0): Bottleneck(\n", - " (conv1): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " (downsample): Sequential(\n", - " (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False)\n", - " (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " )\n", - " )\n", - " (1): Bottleneck(\n", - " (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " )\n", - " (2): Bottleneck(\n", - " (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " )\n", - " (3): Bottleneck(\n", - " (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " )\n", - " )\n", - " (layer3): Sequential(\n", - " (0): Bottleneck(\n", - " (conv1): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " (downsample): Sequential(\n", - " (0): Conv2d(512, 1024, kernel_size=(1, 1), stride=(2, 2), bias=False)\n", - " (1): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " )\n", - " )\n", - " (1): Bottleneck(\n", - " (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " )\n", - " (2): Bottleneck(\n", - " (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " )\n", - " (3): Bottleneck(\n", - " (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " )\n", - " (4): Bottleneck(\n", - " (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " )\n", - " (5): Bottleneck(\n", - " (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " )\n", - " )\n", - " (layer4): Sequential(\n", - " (0): Bottleneck(\n", - " (conv1): Conv2d(1024, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " (downsample): Sequential(\n", - " (0): Conv2d(1024, 2048, kernel_size=(1, 1), stride=(2, 2), bias=False)\n", - " (1): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " )\n", - " )\n", - " (1): Bottleneck(\n", - " (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " )\n", - " (2): Bottleneck(\n", - " (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", - " (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " )\n", - " )\n", - " (avgpool): AdaptiveAvgPool2d(output_size=(1, 1))\n", - " (fc): Linear(in_features=2048, out_features=3, bias=True)\n", - ")\n" - ] - } - ], "source": [ - "NUM_LABELS = 3\n", - "model = torchvision.models.resnet50(weights=torchvision.models.ResNet50_Weights.DEFAULT)\n", - "model.fc = torch.nn.Linear(model.fc.in_features, NUM_LABELS)\n", - "print(model)" + "## Step 1: Setup Dataset\n", + "\n", + "Beans leaf dataset is a set of images of diseased and healthy leaves. Based on a leaf image, the goal of this task is to predict the disease type (Angular Leaf Spot and Bean Rust), if any.\n", + "\n", + "We will use the Hugging Face `datasets` library to download the data and the torchvision `ImageFolder` in the training loop.\n", + "\n", + "[Checkout the dataset card](https://huggingface.co/datasets/beans)" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "3f49303e", "metadata": {}, + "outputs": [], + "source": [ + "beans_dataset = datasets.load_dataset(\"beans\")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "4115c9d8", + "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Using custom data configuration default\n", - "Reusing dataset beans (/home/ubuntu/.cache/huggingface/datasets/beans/default/0.0.0/d5abfbb94de45599d871182cff389bc870bf145b4829c4b0fe20f0cccd637cbd)\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "631d7dbbd3b7461da9fdc14f1130f89e", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/3 [00:00" - ] - }, - "execution_count": 34, - "metadata": {}, - "output_type": "execute_result" - } - ], "source": [ - "checkpoint2 = torch.load(\"./dense_model/training/mobilenet-v2-dense-beans.pth\")\n", - "model2 = torchvision.models.mobilenet_v2()\n", - "model2.classifier[1] = torch.nn.Linear(model.classifier[1].in_features, NUM_LABELS)\n", - "model2.load_state_dict(checkpoint['state_dict'])" + "Finally, export your model to ONNX." ] }, { "cell_type": "code", - "execution_count": 36, - "id": "b4333b3a", + "execution_count": 37, + "id": "4a44061c", "metadata": {}, "outputs": [], "source": [ - "exporter = ModuleExporter(model2, output_dir=\"./test\")\n", - "exporter.export_onnx(torch.randn(1, 3, 224, 224), name=\"dense-model.onnx\", convert_qat=True)" + "save_dir = \"experiment-0\"\n", + "exporter = ModuleExporter(model, output_dir=save_dir)\n", + "exporter.export_pytorch(name=\"mobilenet_v2-sparse-beans.pth\")\n", + "exporter.export_onnx(torch.randn(1, 3, 224, 224), name=\"sparse-model.onnx\", convert_qat=True)" ] }, { - "cell_type": "code", - "execution_count": null, - "id": "59702f10", + "cell_type": "markdown", + "id": "7960612c", "metadata": {}, - "outputs": [], - "source": [] + "source": [ + "## Wrap Up\n", + "\n", + "The resulting model is is 90% sparse and achieves validation accuracy of ~99% (vs the unoptimized dense model at ~99%) without much hyperparameter search.\n", + "\n", + "Key hyperparameter experiments you may want to run include:\n", + "- Learning rate\n", + "- Learning rate schedule\n", + "- Sparsity level\n", + "- Number of pruning epochs\n", + "\n", + "DeepSparse supports speedup from pruning and quantization. To reach maximum performance, check out our examples of quantizing a model!" + ] } ], "metadata": { diff --git a/integrations/torchvision/tutorials/images/densenet-tensorboard-output.png b/integrations/torchvision/tutorials/images/densenet-flowers-tensorboard-output.png similarity index 100% rename from integrations/torchvision/tutorials/images/densenet-tensorboard-output.png rename to integrations/torchvision/tutorials/images/densenet-flowers-tensorboard-output.png diff --git a/integrations/torchvision/tutorials/images/mobilenetv2-beans-tensorboard-output.png b/integrations/torchvision/tutorials/images/mobilenetv2-beans-tensorboard-output.png new file mode 100644 index 0000000000000000000000000000000000000000..97ba818a9420a1bacc90d4acf0e6821d7e1acde9 GIT binary patch literal 161928 zcmeFZWmH>TyEclulv1oXMOvIuC4|`&NCQ6pmrEAP?MA5R(!4OfF3NfO!*N4&^I9 z!^PNm&bKfCtr_*+lTe+a@$XmCZ2OMsR5IxX4s#E*zRNkV2lt{m(|JM>x-kg*YwxKZ zO0DV=bLE#nbJtM!wlpz5gV0%qBQkSYdFgV@6KqD~BVxW+!^xqnPj5A3j8LiP2=-nc z^zUMY%GlvJS3l)>{&LvzJzj{&gFdnkY9!eS2V&$u2S0K6%Trj^J;C;8 zp3>31Cx0-6C(DS6=U@I*^C3;yInO8$WhPJKGyQK7Z#VBgEuQ2>!cFYOE5!o=6bGMQ z^uMBIo-+NvoSZ;ESVtMZmhW ziPg+=6s^$xMam8gAibo?9P$k8C4I@Z!MO1_FUraGL$&OwW-{;v#SF359Mjg2-n!Q7 zX+q*||6I|xgYM4g>p^Y30L~R+d5;iI{j{cXc2G_|LMVj3GIT2TKvsUZ@7w+Rj2wlj z11kp^_F6rJ4!v9@l?=>+7t@1<;&1XP${%UuvL%f63Q zMDI|*LMH{EnJ~jfi7>7bUx#_7OY&mvbYp>ssG89o*NH#8pbSSlVZa21En4=ubE78o zxbb2qesHONRF1aaEnkg!fYR0zFo6;iM7l1}jKUpkyG~>v@naox5B<2?5<^-Mhb-?2 zJRH|7V&MrGhxA15LmUn>xsvo$Jg4kO#dyd!g8~}em~t7RCxYK33vfk(Gi5~M^}nGP zV0%aVz2tjKI4d9hn!}BGL{`@d@HjR`rfx#Xicgf-5L78$Hfd-j;e*x@WF*rzL186@ z#rsZ$f`5R9mvwM3zxpjFX@UuV>}!vO#FIg;!RUiJ=b91qs`xTV}9WHyKSN+q$^l zLrGHOk5zr1>o70s0L;Lk%Z)Xhw;vdLve)I-AAH8u{W$#b%}Y#E>Wv2*kJ?jOagW1g z^SLL}_fU@q9+?q2KXxW@mT)FM0n{X1g)gWx#h)u(Fw?(z6rs${ob-9_vq!w1Vv5p_ z0%G=3c2;&Udk=dFJ5$obB)p_7_Mx}jW#aFyRpuDG$*`k!FNu(bHlWhi?v2pLvmK?D@94h&xpu)L-eH)i+vY&G^U;?d`Y;Whvw+uf39zJDy{;(YJN2cdZ|7@U-=`x`bFknxV{4 zmC2GBk<#hHD2N`!#qG>3W$$Rdqw>Z&b&_|Ex2O73A2igE?!w5iIlC+SMU{$U?5bdg zI-KB+;m+XB98L(oByd6(3!w}d#-b)rqdF&=r#q6!6mGY>y5DFb)Q}PD)9JGg)hAdc zyom-yzXbKm+eWKBhCSYYd_%oUStTH8u>yQ4d?HAaUM^tG=MA1Pt)}z_34(;=b4v28 zzn09n)meu@EctEgFzO!GNmyKdf3~A?rgE0FQ?cVu&PopCEYhFRTWMt0f6i6MrLCV` z&*I~rA4hne2sB(S#OSMDC}I)lfCMlDNicm~4Ft8QP~qMb92 z=b#s}Kl%(ejdoYJOgG|>G`5{XO2$AI+-BJ@W-lx+@TvIb_2lS}vI*O+dE-^0)s|JU zj-2R5Ixfl%_wy(8{PdOM7CGF;p^mM`tZUp-no^a<4Qn!iu7RBhAw)5!z7~-!#lCrv zW)SoG>u%ph3SX=nF9veThdSg7Bn4!N59+!10;+YLw4CgnjKlT6)yHk+eVq6;VV)-p zkf)(54xOghArX2~&Sk(Q&h2M-)rZrDqa=Gq>87%fN(MZV*OQNAqRxNuh|NZBro(D~ zPiZm?7|u7zm&B)TrZAuuD?zFdoAIED|H#nq#qH-SFSh~^!`hwV5QN7 z*3Sy8aW()?mtlvRP0<>Iz2Ca4)?NKwOPgQlnP|&QdobY!|jz0NoWy2(@j>Ni!9H! z>pF-$Fk;kiR=Z+n6R-q=Z&tpp9JZi)D|!2#zB`>h%aGN}H_%v?-HOm;^@uziDBP@6 zGD^@=g(iGdZX{#C+`@Z|->?zp*ES;$k2;r*choSS3>%I}AXb^oWJ;fsoOOWqmZ(RC zL;O>)#$)p4)vZ7|!i z8L@#tD+NhxAJ6NR8@67IwjQ|8v!k9js-mFXo8u+ze%Fab7RFLW&XR1hg zH*ghIY`wiIsVfdq&k^qvopzbqJ&1QT+D!-Zj|&?(b-i9YnhV(TY+56BZ}yxqK5t&| z8a{jDy1NGkrrdGoG(Ys(K7R+E#h+)YayL?M4mguvimuGK%@}vs{^8@^ws)~BR(JgH zDEY^9v$pfvuK*Z*W8eYA%rcYWAGCYk)@q zTl4PJS;#W^WtlhPd;* zK9=m_xyePC4k_#m@#lP&l(-YW#)piiS2Y@EbbShJ6N{7LW!QPue5#I0ASA#~8Z^I* znp=eOBJ75LL}%b$-67m;oLymE%5;EE!{G>Jrsw!F)#%FI6+Ng!f8zolT2_quKoyf= zl{A-|TgKk0igitU1cY;mnvvgS@zXLW5Ev=3OYDvC!+QQs``6jEF}t^)*DL3$1!O!C zX|AJWp{k0)j!fgAV4yxm!9=D|k(VSY^}o~ds83PQ|9Xywf)Zwpg7J4AHRS#GCk}c2 zF7vND`sYv-Y~;6x$jd7i?Z0y4Rp+ArR~juJ`3^-|Q$|S%dDjHGn43GeS~b{P{h4Nkx6@V zH&X^LdpieLQ7;LmzjBBo)4w0{Ffsg<#m!cNNk{cHgN&n#IfD>4FE=lfBpw3;gSg9k z3(+^S@_!dcev@Fba&vPM<>B%4^yK#B=XP|lyv*~@?Z7Hn!5sBtexDf9UT~c*K2C#={{w3$Xo+1S;i6_qU?@5!y z6XD5iLe3+NwXFJE<9obsl6;F4=Y^d_x zzJD1Uq#ghr`SLz42!ojc6<6^E+Qa`>$?j~N%slk{Y{iV||5*hu7<19f*gpKv3U?df z?sd0nuUN4D54w&VF|z61|LMU0x9R`4So#00z^k>f=f(pr_#svI(5fj*$+I-K^TqL3 z#(%Cg3udRmG|QqouqcP&HoLZxWw!SmNaQfP-pAQ9wCIoJY4S8!W-4k%X$(+r9?kYo z{F`{9-OPY|T}|$yx~|;dWnH(UKOm|9$07rSXw&h%b9Uksz{h=Uk7mmAr$f7jsm#*D{z0&XpN&9ms9G=HV_C;RO9d2{@%c0AO?|YJR0sPavJLdG!yp zMKM*Yj{(}yZNEqMzxJuHHB=s&mCLdrm;Z-I0kk*_&k+aX_vI>_nZC(CDYKyieDxrX zfA-462Tgf4YUb@2z~46`{~vu|20fyK|taW(045`CP-`D6c3s=V02g%CODSBuOqg{qqW=yY7S z7n-Z>pf0Tr(BkLfBEaXUWjCg(L*b8UiR*rkA$dKlUc_<6+{aShTWXY9uB)o}M^#{q z8b6+}{8LrX@CLW^Z|g8W zelqls|IhZkaXIC9-Y5%hwcFc6{}{sH!&GH{Xt!u13y9~R=vfcK{m#NY#574MlAQWy zd*78!p83S|E`EdFfo?BQ=5CEE;oFE7pf zAu^?ZbK&Isv%S=m?l1`K-*XbmDJqUN8PIuDcfJw*j4d^A9_3Qi3rPrEE_%%7Tgu`pbW4nFRs$ z$Nz0GIFo|XolCfYEzAtT{};38q(^dFk;Qf!VsK*v}nyV z`W*kTF~Nl-NY}eUjx!d6xtim*a{SZNTHF#6lM2u@(lwGfAp^9JH7n%Mly!zgxm zHl6UdBeb5#6m-UpcJ`om%rW4sKSvtvVQN_S`2E2+>%D_}nSK(%k$aVIMdx_JmUsym zIpAcie-7CC_ke9lMxO*HJjpf6%nO!hHXCr@JO$65NCl!`m3kOknjBC;-74-XNi)6 ze4G(n#YQVquC51cxkd-Ob)!bKI-YsEHUFiTID?TBf~d%~_&blq!7iz_UOP11u@y7-uuV2YhsDBtmK-7uI(R-2gx(F zNmA`M9%L1|o7mebH7UJ7Q)Y2;b4$!V%iJxXzmBI@LcqH2=iTnFcX=AVCfl;2UAC>= zO)XmHWM$v1>=x}CUAFRXo7FyCi0Ph!EliCz5yJA8%r%!X1g46%h)of%wK8;6lE93- z%S9mQfc;lOF?sAc(@YRc@H1RLsAkS9#D3si)p<(bb;`D?F|_I#Bt02}*-7-FPAjXv z&vm1SWhgX7)!K1NDI-SedF1>fNQow*MP~Wq9mZWYJw7_53fv>d)Tkm02QVbUms_p5VdpCHW)NP+zLdME_ zJ`T4qm3?uht4=Io0$?zh7~-F4%M;QsL|R9NMlBzY<&02!ZV(IKveQX=ne#}R(; z4?I^N8eRo#lIAFCw=K<%tS!Z$N(JnN1w1`bFhRqF9Po3hCK!7xnnMbC{H>UyU zpv3{DfV!iEFmI*Y*lrphm5v1k@gz&s@espaMzxpAMV*?E_L8Z^BBC%SkdJex)>N>& zWMh%IRIuTB_idqAb|3xSBz@uWP3N&P;#vx^I}7eQ^SoDspU@*tW*xhb(cUuY`s17L zmXZnF?Z0|8!S@nFlxUav3KCEa%qv@?v-EQo<5QO9KB?NUwXHSMc9f|ZNX33oM0yeIq-dNw2 ztttIA_#AM%rzD;#P`GVzY-G(Jxtz@U0p!jb)LxjYA@sNF8ijtdWk&Cy;?P|5sN3ID z1<@V%(SmRC+;7T;xjj=WAG?5SBcR5Gj#r_MlqxBUrI*b^5>q*Mi#bU^K(c@udplAi zD60pYCQMg2`tO_JfLv}nx-KuZ%t7`i5tHZnQQWU6jQyNjr?ZaU8jT%t(1fVnu$i4> z@_0%6EHAGnuOb&Nt1M0M?gW>EbJTgo8oa{gyLhvtlgd@0F}(0xtm{lnuD`DLVO98D zkt4jQ-~XPuZ)WrJS&(+<0|(Ex<-_*Kg_&(Jr8#?VVloNmgFKOk@-0nwG$WRzDaaXX zq*Iovj2*8)s;`e=KtV3Lt*`ATqxZ+r4sKu0`K8YIzrgbm_iKn7x9jbcs)vY{oST+S zr>3RqI3DHMKvi*ZMBt@oU{iU!cS_qzVT&&;<9=@5|Hph%z?|W+&-^)(NbqeK=Lu71 z$duJ}KO?L1l7q->O}D^6JeCj+OSS$#42tQVc#Hd5`;&i^=kX8E;qL5r5YhiVZmb z0+GCIQQtK1zuPy?sdTTft*ABiqca>EDI=-$?AT|a(V1P4e!rL#2-6Ns+Dqv?O{!Aa zE2ilD^{E20b2E}-s_U)^(dcfxCche5`^eYcSR|$K7%4RE8gImfBf$jD|4LgoqiV#Mb45Zk|}CitUrY8mo*Kn6+|z^i2SsdxwhMUj?_%wYpV|Y z{boQpY@T`|)%RP0x3SaIYgdCzj|0zy1JBMLsckt@-rVo3-DX5+znswRrL0c;b+~qa zSXkFlBJP$-QcGD;6p)0;bcVRiK_pZn#amo;onE#0Hc{gSQXX(OA9(i_xO!eBOm-p( z&HW@d_$-Nx+F)Pj76r0$9lZrfkI z#0Pg9osJ8qJwvEhaydqxb=>_1X2$)n)HNF}BRwj%akerEz&OpM$A5#lcLr;?u-Nk< z=;ribf2N7HNlCVW*7e(R=;>m=d8r#wnz`}fjl}^w_suuhv3@$=^K-LAxH*rnE_^xg z#&KvoI>-2K*4U8MOjee4>&Mlga7>O^paWEac-UkZUd1hS_u*y@aS!=`&#h=x+bP+N z)CfF9$5%1OPs5CVlbMczH_M~W?mhuhDrkV^wL=F_<#L1b&nfN9cR!FCTAM6lpAcQR zl|*4ub)zQM->$bN^Hi@a9^plmveE7ZcFopgMWaLC#lp=*2`=1kD;f1f3-_&~DFrgctF}Jf%wo^^ z8yUrT^A-{_QL0SScSfxi2W8Lnc8qVM0^@%>P%t^M!wbPf&I}Y@Q$lJiMmZ=dWbcYxIk~lMMUU zRH~6xj`@70%8*?O-0xljZ`UuuLxtNJP0xM1(dpuxM)Y6dU~AE&8J*`-RFFlf0jj3q z#E1>4#CP5c5vWl~M8yPa*I8?6>mha9Jh#0(Drs(|pG3jBfDH#c;|p`+HWeY-mK8r$fLHR;tZqE{bGRwYKrFwT>{$KNw(JI0YbW6FY~{5G=@5n91zbE=Y7- z=I-9N>(bYJ(B=Er_hcGapaZQ@d2cGirP)-s9?F8CHTOwk7Tpsw5bbo#So zSY-CoGgcC^6Sbsq)|`@kDNlIV43R3ihKH6(PXsLP14ngZlh$-_(yT)EW&3V}f`gqo zOC+|$p0urgv4_cznOLLI_T8a3Fk{2_l^j}xJ$$eTbw9I?{RK|~+eu>+wv)a*n9h4) znn%F^Vx9Pp@64bUu;)}SKNs4#T;=7Z%0{50rzf5;gQzUhw>G^Bxu%fK$b z?4Q&u`!2L2o`dy!=nt%j2TL8iNA;7}&ab<6eLLCw*U{;pb}d&9*KWPI9}^6%E<@*- z#{#x}OsMDi+?7s($41c#hZwS?>+!p9*CigRN@~sr9-XK3IxC8#b8b=!0^<~wkXtWx zzm|J(KB99FxrE<0{-Ovxp%|ciM0{T&#^8$gMepnMi2_b0k!eDWT?qm7BJ%l^g^Vn9 zjMtcSX@Z*xA@C^&iqvJxcr-L|+{wgzVB@y~uDh&_Fln&RqG0hG(Dsvq59izt`&?Qh zBtVDdXrZJ#QdiiB+$7xFEq5*effQ6D)+XAs)ZsnsomM08MM|r1R*^1C%rF@ae0lYv zar+&Zt%oU_FJ71<*q*eR;@3R6L%>-E+kGRhW|Ct@`=zsrc33CJamm0tZAs7(XcFxH*AQ0Xejb$ORQAX3V84fY| zl|s>K`RinOM94_?6ZE`_gE3=u8U zQq}>$Q*EA@JVEiJH-f;NvB;%7Wy;5CDE+#5^=Z~N`~hSK>g4FL_JYS>pjl*BqV z$*P`mRLz;_ScUTuXI@Y(U;XydeVW$zQE7EzbFgd%w^TyytZkB2hg2%kgtk4WZZiCe zDiJG?9Dy#r>oO|gX{7tl{{>7*kXrX)L&!7*I82OAi#4liI`7vywI=ix^81?tMB&U!kyBxDp^b{zYgyDwUbZ&4Y_ zrQ3^P8Cl#g#ypV4`65c-Zn908Nf@|e8Bjz+M2vOR+MBvx$ra6b8N)blsJ~QWuSh4e z$@^kBa%3h=8W{-m(1SQ*{9V>w7MSH)!Xz;k<9G{bWU7W4ukA@K6{(y*?})C$&DYBh z-@TTCX-YNddD};7cQ|OKln{Jg{weV@wJ^m|kruuwFraE|aG}ao`G?S^1p{eymh~mI zkPGhoH@dfVCHtlE!q~Bjyf2>f-XYz|viH15g5HYWVmaVE&eBCJe%yY0)*=JmWP#n#^l$ zvvTgwi&KQl&qbKel0%xh?hYXbb>nKse!F76+FPLg4541WEbUg0PkG;q+)V5nw{)=Q z@-9iB?S~x&Q55M|7BYih;ZrZlh+0DFuD>Z1&37ERLpGy$)Es@LGg?2pwP9Syn?QW* zAlu6gdFejpnm(HQg{s$C=l6f>X|}Orx3R!yJ|y>H(C$}@&N`9vFV94;k)i#O-4Ov0 z?m8x$?mxT}5ODlia)@{ssF=9~p4#nxY#vHo7P<$LuU54P{#b$V z#O^^f^8eZtc`{CKgxbp?<#o9E8(hpr9nsSyv;ZT|Ns0hSN(VsB z91jx9Qi-v54c%@a4CmMKy-9YwPChLauo!WE*}f;o!=ClJpNIHFnY*QcGdPAXR2zH! zwLFz~gD}TRjky0^>9408p_zZhE5E~%bSH0QT&YD96@FQp(ox=iku{5^M8Vhx(g3w_ zx*~+{2iL-X#`sU^S_nRh388l%R3hq;z3xPY?o~8>Wkk^VE<)t;F%b=P>NNrN)KNX< zQ3*f>6|UwWi$+SYFYk`~EQyyQkduj5Gg>@3aHzVM(Y%xXy=M|ry1zboz-9Hu*8#K-y-w2Q`(r2#yx>2}8sUG9X;@@Uu+pqgsVsPX!yz)5mtN8`frF823oa3EV zi&hIcVBVX{-=MAx{glEYw-Z@Ly{UPCYswYLf7Pawsx{XSvq_#r{KbEmH$s7QXQ{Jy z;jWpBMO_!RUCBDzQD@0Q12y^fJK~r10M8a-N1qCTONC4x97?nOeeZAlxiqN=(_aHU z2{(dj!ZW)_%7Hz^w;W|zP!SIs8b%^DLSjA0WZXB29wFteJ|8rVjuX|*e zX6ns?2WG3+UxvE#Imzo!a@z;nW?E7P-}J2^ZUVcwmdckm@5$2a+R$uiq+q*9^3B#i zW79&@Cvud2`J>g$Ju6~5`uM31_9O4#+nqgcqT{VF+;G!lEuRs+IXSQ`dvZs@%E@;H zPb?NUpH)9_F){y@C5cwmyOX9WmEMVaX9Z{YNoA@c;MLdU%|x8i{NhC zE$@!^D(?w^VF(?o z^v7jg@UkZ*vuvUfC#Y!d#YQB9=lD&KFa=3qs)>oT?L(c(b0iC?&0KdeOpWU#VBY)W zZbX%6(kT~lsStRsVE##!W_bDK;foP{!q!uT={hDtEFuCwd;eAY)Y)rcZTzA@RjG_$ zx4TkOKaf$igcha%(VhM|!R`Yfi{tdAK2{laG|T26@Kz zqHJkS2JuiI%_nHM0FYw#1;`g~IM}f--dOX6a1vcr$n|c=K&Ch!wns5hiLu13)gaf$ zFVxc#&CQr=I`Q1y#9Rq10&XDo-;*gcq~tK!o?9wm0+!L7`@o=k3qS6q zuWHm{)E=+FRTS;(n6S#zEMV6Obyv+oWlKte5pAQ$P#B2OiQ7bBXC>eNgwbRLI}i=b zm-^|4&`6(`etW~IV3oIO&E3{`Hzi&Gu3-SX_*S*L%Q*0RT(^$x6_JzuOaLSDrw%#F z^Y4{;)++6%XE-yaGW7WW@H&fa@BcbCp^&KoP&8A4FAPb}`8@g%tET2k_EHqRyjwv5 z6=<%XoA7EVDM<$U081pZ&?)n!tgHz+4N<7N&s0L>i=P`&&Hb+xvd4lnAJJlb)Tiye zCM{+Vr6PgGpfZsaOJLaXn|yqUvsExd(Ej)n7@IcRA{QuanNEa{8Zyv;B+A~^^AVL( zBKFGb$9fAiL(UxZslI{4A(W@-u_r;}$y zuRp#zkW2TWHik4N(oTlbnTP}scPBj*+1iz4kK z3qHr}?WXPJWq_PYb%amFM%f)m}MmxO4;z*Y-H{3UDq7ZK>f-rlEsA`g< z?HUuPIjf#z5uGWCRDYH-e+dHWIEEs7oq0JqNRT=UCID8oJylp4e?SbF9V$y-jAg(d zGF?JvvppKM4|a`vmtmF+?BB@T$?jXn4`D9{&yqjLT>(1FANrUR?LHlxE1Jm5G@xEd zp!&MRLg0-h3kQ7f=SVWszl+$yfmuGNA*%VzJ&r?zzl65y`@PmY_t{6cyUcaTA=k>o z>yQ^iX_yLUqP*TA(r>X``yfrL4)ZXtVp%kh-KDN1I{M` z-lp6~x%~QmtS_Bi%ZFMFF(CJkR4l$$LeM1pJKE>wNasAnHe(&k^gU`Bd#}|s8LKkI z_)+?kBZa^{9@jCjICO01%xrco|Kem~w!bX4Ay2&-?QWsU+=4A(Gd&;a*-{OH!PX3wl4A&+`h9|o_3Ez%pVUHYYHToV#6O$Nu$ z`*?r^Q}oDgGp_TKtqT4c2}wsJ=Ri*VazPI$mID;juGoOOZTi|5XO(8%fLTs|G~Qd8 z(qQ(*b3sWJj^WDsxcc5SO{Y21mO{*$e@3li zhH$P8YcQ$Vc=qyG)%rQnU@9&!-kzv5Q`z|kk{Z1?OS3X8jxZEEC~7!Hac-0tx*2@n zCBFfRK`4n=K~H&cla+8l@dEzhP)oW1x&^ysKlJnf_66!R*(owg+Y*Y0&`9C!i$dF4 zWGFS?XoUur#P+D?M*TnzEMp?$*`4#|J^1}GXxboWC>sN9uP6dh;_Lb+V{Yl ziNSfQuO%wY#q=v^i}KqL)dRj>6`50$izlc+_N;4BH!9x!7}OKz&$2TQbI5o}XmDge z*p!L9oU_4TR4jIolN;TG@1|D+rV$zR9Hp`gbHQZJ-w&j(gtMHSnflT|K__vi#y*fj za|;GDx(#_t%H5{{z>nraOl6Pql^x0I@yuwGj#u9FpUL2PattkH`BRWGN4K8J* ze3}NMBEEA1#Gnu1!2mJiB{VupQPNn=6N}~-?1v*FAz#htvj%sd(i<4zJ-7;rU`?&U z_n0NW&*I8;yL3Je>h&J!#)gpW#qp=U&>vXGq#bZ7Kic1Oc~SrzyB@MLu9N|LTJX3? zY_yMk*TH&CX;4DzyN`-J!q>R!?(2NyvTBOKyxzaSIaMIDUmhxUjJZ>6Tdj^a4>_-y2+^T40L(Or8=c3TD{AsNvDA)GSDI2! zqWMu{h;J*k`J!A?ZUG7+XNy-79Dngcd~TF=x+|kIB(cPa=89t zaGO11_@|83#0Pi1dFiYppgQK(Y^9*`)fb}Y!A^~GVw<@tBB?)Rji1$Ty(KD7{9zrn!6ppc=~-)#8?Daqx2CsPZ)-PL-a?WW?G z)@QtQl}itJWulLU+^Qc|bv4kevU}xj(^3DdD`9o*Ut}Pn;5w`Fnn#YOH?Sn#IUIc- zxn+Z>*hB6WcNvaILZ=a*&%+4Ymr=bDpola75<`DCk|I2muDMloF}6RW>-5e$ zyuV<12rrSeJw=Ts6B1fV$Mss!Fzv|@sVRHllsG69W>1DKUra+$9Iu1)9%j$oRiLzZwa)0d`6=~)rRA{+-Sb!VFxKVXPrlDv^ZD* z&2Dfm66E!XAiSwnB`POCVn2n)(QW}>`N5+#Iuk{}7RN2$Ak{2iZwaH`4k`pGD>doF z#R+S!B84#~wD&~3cmnqEH=V(UafH2rALNKnibl!v-r%FJSSJN91Cr6M4g8vex68Z5 z1*&nmBWbpDJ|uC-J{%Ejs&(E8v>8l8byVyu(G`+4R?S>|bo_R4?dKN@@ppP2t3Kb0 zsHCn-IAV9;qu>aITP~KLVF-_>H4qo6~QDX+HyR7USer+11Ds6n^Sr2Uv!@ zj7W&CLORzHr{nV98vJ#`%csWjVNaqB0eHN`|hzW&TL!kSJH#p_@9&%Ocuap=z`rN zJ+Wl^7NF+EE*M_pZ}*L2N8`vO8PGzy@R*HScr;+?xo5AI^Xa~tmiI1pkIhXSkM2x) z%vcq~N`l$*R?E4z+IV0%CZ+6f(far)^{Lj)rm_b>e_)u2T_|O|y>-&Yn0&+b<|^Kp z-z72n2a6iH{?LUb+d*yBzE8N&u-c^UkOgp6!>F*32LJ4Url~Q9zJ=fC5yUdSrZEu7 zT^wR2aAIhAn{Pq&j82|ZF*KMZ5jvZ@3aKR9FHSt3ytqgs>|r?;51LN1G)OSqb)`wg zcG9{OiYXaCG^}ic2P9{~^{bW-Ug$x4t~2D+9$CZEvY542>i7q2#EdsP`~8D&Jotak zeu>GC4)1dxZPCVtj$981938ux7}G6q+?;kRb=a02%VeW^ub+h9aBdIx)(Pg^wtlXa z5<{im)|Rgr7)A$~)5DJNyq(JW8DrBGkj`!UNbi--!^H@oyWLrK{D9lyP+b9!Y=%lt zJx@-h|KiET*L&Njp*zc?i6jL>q0XFF!Iu2v*L;EY<7b)?5$+$Lg>YlG2xt53>us7i&tj@8a27^CtU3riL0wN1#U`Z;Gf#gkyLH3H!W<0 zC~T;d>~6v?9FSin!7PgqP}f_g>;QK~bEHdDwl(hCP*^k^eJg{MCp9?IZwFD$Yh;Tz zdC*AJqMn62$F1vK)_BqaneLFgY22#dnnm6Yc5T<&Pj~gs+4XvxyfHI&XR5o-Lh1C* zumz>Gr2wG?N=RVi~tHYH4m%lslT$mv#g{BF~KZ z=x_bChrtd`I`C?N3eRrUw1MpBfi)oIrp1H36nUxVV)1g$S~+_&l*)tm@50)vN1-}X zj?}&iqw;XS9ZVl6^T_3Ga`n4Rafp+BpuOeddx}vtv%+x|$wd;+B=7@$;&>TtJN_dH z=2%HFy&O87ckhXfPua@~x%PyGZ+6@-Ol6L0@lA7zXeYE_*EH5Mt>xZo2l*|Efyglb z$fJm0c}_|_$Pl6-pu%rLK}`PvPUAR84X4%z941mMKlb@n~6=x_S9eHMA1Cs8}6oY>f(_zOvB zy~W;hlR4Uu_I%Z|>QgbEvMzRCF1@dwl(cZskx9n+_#ERdzCCT|4ncnuJEW_sA0GT7m zz3!;SpcC%kU5s`0p`;~wLgV_7sNC&-xNToj{<@DO*ESa|#=Gc} zMD52U-5An`+vh&ARKZ#ox5Hn-Z?0UX&$U zd&Y+}TlCO+Wn-OIbPjY(oOa~@B@n=7`F8e}JY_PTeye-QGd80wS_Lt~G9f(S9Ns{b z)fhdPahm#c=nZ8kx~-9Q+auherU@@Voe=uCKb%v1G(Ye$Y3Rb7n@Pp=u}kwv6($d4 z<6!=vtpCg{0o~SEDpK@gXuh#=7;nLwT_G73=SlII=&p93Zs;$?y6f^-oIP&1{H>t7 zaerQ*LMtVv5atm~Bc_Pd+K8p`K<3N#I|{voCAsN-*`oGMd)p;DP$v`VFD8}k?j>QN zYGo-ueb&s;No`xG7Bq&G-F{Yl?St~NB|z3QOC82%z~(*s<1;p?Pez_lb`$K2hbeh$ z3LHuI%Zc^-7b?4IVAIrX(GYVDUlxbviNQG zkDWck4ICdQla$5`8S4Spxf*{3(HZBd$g_cS8a&{kxx^vlS=%wT{mrAZM8~`i=5%gU0Jo0v6V81-SB*hj<2f?@ECA( zC*4wu>hfGG3AGZfjhJ!gtKZzb<|G2U&cYbW`pZ|OTF?Pm43wjr<3f)ApdBO z5yyM$WeFR7s}c)p0@aVsyncjFU6=d!86kFJjc!vu{9P61vsw-IX`=kY0>~Z2o=Qdo zC;)cHNG?@+dFgLSz|0ybb?iN^AN9CV70fo+Up;w76Wv_^sm|IF?ik$J{MtS$xGEUh z-9W!$w&Ip#4Pzlk+jljg-7kK58uqih)S_H1Jff?ViVe%gMW6IFKhZSuM?ge?fm4pc zQS{_6{}dUr;g7C5Dbh6@9GM%NsA_CqiTIk=3{;V18Idt^1I1X+(db5vjrFv9T_cQF zNQm%N1LctmN<|i)ZI6K`9-KxA>LN%>3&fmz>N(FAW0mNh@f!a$rSrUS=<@fFlcG27L zPdJQ37l+*=f&>&;^Q~BwPl15yse8XF1m#n_#*@XyNR63>{kr2;Y8R>fS52$nbt?0p zk1J&W)r}Qiv?r%!+}bd^Rh}o{QRDm5cbPt9KatD{0f8BT!woQ~jwmA=HIb)swv#MU zk>3I=q#gakJjn8!>xcHX%6%D6lfn*LAd7nz|BUzSUA&LjntIa2eA?R2iIEyCTot9D z0L6Ll`T6;*S^~`?GWl*pf(T6->h088hqeMTq9Ryn>@}J9c3P~3jcB6T>n~lw{Ca@b z1451SMCI)wOqqr^*^3+f!zb5CQMR*-GqH3_vCyeNzKJ`e0Gznic8IZZA-lWUgq0q0 zQXwwD^6qYap?>PFk!mKqMTjww>k!J1prC{`CV&cbwyE0bVE7sG?@wd6ILVn z)REu@M>~d7DEweQ%yIN%`zeP8z9YPFuLg&5*BbjC&=eNBhc5Nk=}N`(wc#!yu#*#| zM%!v>?XwU`i-yS(p|1%R^PPIy&-to3W)l3DwFHkuV-Ed+DhF$BJP>FbkT>$euCwHm z+rAU>40cDqc@k7qcKIS}2*8w}eu!dJ+~Y~Zp3iB>5iSsW(uA?YG*LJ-6Xi;RFlhaM z*n7{YsJg99RDuGEM9CQhBqzy9B?$-!2t`gsh9XE3$tpRiiD4>FfzWf;C{%ECO5`RKXKfPI|kQgz0wvxCaqu7*tHHA)9J|>E;xU$ z-XiF3mPesutV3&Q@uM}3fHMORxvc%f>E-cRgANSYT5_;&`C5{|>@SkwV4qqgWL%ho zk^|f8Egfnuas<^S0d3JOl*IJ=$?3>MrAzlqS#xV4k{*FAq-T@I^P1a+tb&yD7B9&x?|B z<8A`drO#F}eVh;>@!xP(aGVjC9KRc>Pd&Oax|To!Ip|zC2OnS79zwEfeo0@PW6)L^ zm7K8mR>F$CF&_FcUQ&|7i(BQQ@rxaTE@`x)t}3OH>HZRd6M_p=0vj{kL-2956!97F zr;a`I)_vaOa41cKp`H0t$KOT?<~|_4QgYD!b ziYq=}O*t;M2=I(IyUK-`&n)zg0S7KJWWV#&o0O>#zH@%ksPahO4HbBE0p{-@& z_h1QBlqdE6dy18(i<*A2=eA83x(Ojn>GEXr_N0-Q+_udJhGWA4$N=ef;YH_Rx(!L< zIoI*`MhgSlkChAVh=KfE0&m4hd!I|z$f0-;oHy;|iiq*$Itc2Ov|~KRc$~YrYB)ay zl%%VphR(+;rc|p)cPq9W3!pmw&aZE^Ca+*INtWhp8tF8Dz3dg50FBWOw$?&rwq0XY zQKy{0n-WmO*<0WDE@s7_bVCD`ZPHy8Ph}RxA9qOUGcD=lAOwt5$7XBOV&M<8sh57svDSLeO!uylYF9F5)M-&*DsPr`BAfHX9;7v2#2%mwvtR0^$ z`O~B#iVgo&$?4sgVdr2%zd|Wut6)wVD@0YGzi;M&9&GF^|B*T2h8QqdOL; zx43WoYA)CcSjL{s&sK#ospD;|-l<)#e!eW=y-Z?XN;r20F|Z+qj>6%&I~nY+5`L~^ z1^CaOs>$9|uNiQVr1w+w#hj`?DQCD$$Z%0L<&(t9Z>%Ry8+#&R#+u0@T0ay$j7FUD zfeszFng9y5w<7q`W4Z0RRKm@Rqh{JB#xTcz`1^xE9H~#lEM%9#1T2;-YYCaN$9eut zuFO$ep*wBwr0Qh-e~$SX_t2LHEi=luP~T0u>#=4JYA`@GubGN?=5MxUh#V5LWNgwl zu7{4UU{7T2Qo)TYgV?3#iDSd$V*FyP6fsXBcR8R1I>QKpdWX~|2U9-+;(S#NSB>!V z+rE?I5Fxm{x#&;T`iI_`jH#4zjFxi4D#!76qXWF3Jff28QJi=u62reJWlj6`{L%jS z)3+LXg9HOs+MWbYQ5;{Vx4iH+6CS0}Yx50^VXt?dj;HP&0gY0VRg><(F#$HM8w7Y3 z;z3QS2chM4onrR;$q+a!G^X<-g~-E)#FsD5Ixjwp;*GPPfYV#(S@H?hP1Cio4}$zd1VoiOQ?{j(Bdq^p>3!ZN$#IUu1UnTgHRCWdhi~HzC=igdTXcAC7AP}Zx|lED`0QwIxBQ}Cav3fqLRgMYj*|T9xlE{uVL8#Dm~m#Jrn5l z(xU;=D1oE|kG&I8Fa%^NZYtr?7ZJN4S)yI)7cl%XHjMJcr04IYfr`0fKpiW!6GIl= zvsXlNR_-d@UIeuVtKqk~Ttfot@nwLJ74k7oqrMJn#GR{5+39= z5|?$!vI+dcHL_xVS%Lzb%&@>5DeuIUb>E^aJTZfLm-iqLCjo)66=5F!MaaHCXi6N$ z#k=xpB9ra-!BrlsoP@S2c{*Vck>M^9p4GlY7fH|7E=GdO1;S-vd@mp@C}W;KTA zzt*B&!H-!tW^$(hn;OLuheWyFbu}wxS8D-IOtq+f%KI)_fPFY;ftpM)IJi+OJ!%q* z8A~2l1&Th*17G)LNz9cf%{XgwhCt5Ih3yFEN2~pUaOnwJ zJvrzx+xPMCTeBC;0Lmoh{~KkRuDKe)kbD^VY_5-5ga@`DKcGiS9aT|a+|El-BGxF# zL}nwGE?RNZiL|~fT+NQ>vGcIH(H(3yi}_Xk*rkUQOp`D2U&|gF!+Cx=w?0mEjodK3 zKJ$qGHnYoRzWFvBR{$lGu8>mOi#;9dyU5b{fhzRnf#fmr`^2+bR`Xu(e(&~oddWr3 zyR-x3J8B#-5jH7#5V2Z@ocXZ1ejHeERX!vney zES-`*xfP5qN$X}td;J~~IrE>yr5O>a8Cgtk&*ktF{6b*7Sj$8LQ&y|g_Rr9{%&Q@) z1<3(TFQ9Ynq@LUYc8^BjY1R5lzmsQ`PP*C~-#Gq=1atoK&WQBl4#Vc}9CzDQlH@FV z&AUW0;<30woCYW`xm2ANh^k8~@ZXA7wd!@=wh3$|QcphIoHoXxt)IBVt{hdJGkCkX z?^&4w0hc#ir6KY+^q-^~%jsPy+{2V(2ZIV?L9?L1psHM)xodg<NUL2%c-o2R4 zhT|f?LWtQ=B7sl~9w=zvRTbJ7SwNkfdl zhl@NP<)qzkozLL5TXBsW6$$m5zOi^1YH~W&kQu{}wgRLPS>6CvJ|X_@yJgE&iOd<+ zazadFbQ6d4WwXpFtWJE+)$k=fh!mKy(MaLK-5Ej!p_oDxFL+W8Zs8qCb}TaeGRP#? zS*e9qn&z`Zly6*9)WVRZc4@1Gr+LzY>%Stu)tAT(^tP>&6(=m$&W?TM*3Q6XZ3mFUtKx|j6!`iq5N^l2GMK*q`3f=Atx8OY6S z)}pgp+x$)Oj4cpy+<&|9fJOxjI_;y| z&b}zxuDs>|!jp;SlMgmhrF#Kus;1OwpsczD(2-3=&4g}14?%@hfXE&)4aaXVq*`Yh z^+0AdIV?U}xEQ>@9$ewQB}5Yma;?GsmGq5HGlnx53gKnqK^(4g*NZ}CNm=a!Z; z$(jS--kj8;QGdpDwv?)?PUy1q+gBG>p;J1j<*Sbw*s7U+TXa_4ZFwF2x4On3uDgwG zICWog57P2l^$p-ErN=>-B!4A{8MS+K$KfK5xChqz9cHS)3gL2+OJs>-N1d_F4*Zg> zWicxfQ}xw)55V|p4r>z|ma8#A`GfgKw2^C(So=+@3Sk2vKqqI5hz9|IF zgK>iWpmclbj1`-&41gNKBCIit^gCo9uK)Ed><2y0sGb*z=ju;hoB$t*|SzF;h=}Zr6SJ9=%0@0hg>a(sz;?_YNk?)K&yO zRP7egrbR;>x{$IKzJcchJ;JZS0Rzp-qx_wiswt10n>I zw&WIp=75H~Vt!ayo2&|(wv7e`Wrn*jdK2krnIivV$Vb! zzYn-d3quY(rasT?zx(#lBvVZK;5`Wxrnz)eQju;ls&Q+4SnI&rBpk-yN6?gO@BKMv zFU@B|1VcJ2Lrs-BN_1XUK%twoRW)_h8lEQ}Tf2iiYCsplI}WN(D}6gY0{TCQS4`+U zrMnt7&!SS`Ku6@n3!AzlX~%IXiVgn76pBOUtUL&JZTU`)W27bn&})`_t=%ss3w9ev z#|c%|&*Y*bCp!#_YH2rG4P+VjD^Ifrx-VYWj}a5d|s5{?3i@p=TW zN@-qK5R~LlF_)C?f3OiOt@ZSH#$S2!973zt{xs?{(PK%rP3DocRr$IG{CqdDaxK|( z@16#Y8{gy z4PR%P*6_-$-XLMP;e0Zp$!v-9o4 z*+*_SY{P;?TT*LAga^xvN%K9L#aI_XD~YeX6OgaRh~GMtx6PVHPD%^|zFpXyOT69f z??fmg+4N!v6VzQ7p+uEWatt{=fK1-!6&Hb0k0o{7Kd;}T)M{3~UH)F)9s}V8q*WCH zAM<5yT`)Z)JiWN{cjBmd!bMvKNQlrTnYQR;DoOp=Tfeh(j&9>)n42;PomeaJG-Fkl z8Uxr0&XJ+`SIvdL3yQ3Fjhv{JT&x$oRZY2|nJ5EZTJHVzs@$yW0k7t&jvg*;+9e$_ zgefSXYI!)FmI~`h>wKD-@rWTCP{0L_k zeFgJ!8N`nzu?B$put6KKO~h zkeoOHmU_CI?cwtM>8EZWYd^)cGQZV@?=eZnp8EHe#%B=Ll=cLR#%LV0*Ii%g1`y)fw-X#qJ=$ zPfyp~2`(F6?|wJ@<%$eO5C;~ z(|yiqJZE%%k+R>$ANjzgQv^CFm1xq`4KHe84-C0YejId}ec?HrHDLhb_bcDbY3dap z*fj>@o~n_t1|V8%zLQyS7uw0v?)6FP(CV50$X%(gg;X_h5ehGeJd{?%TmblDL>&Mc zJe+h8WvT^?G2>+7)pLdzHwU*{>P;%9X>ae-WfGA{wWbY-%iTH-rQ`&A+}^XLc4ofL z!*Cmmc}z*M7GLAB$$u3rN48|K)F?+mRY?HD+JZrNmRIU!@oHLj0C10 znW@F>#Oy5-&`tJO*n3l*uY!F*`&I@n_;gMy%X|twAh^vBnkt2h?2S z-wLTH9V5wV_3X}b+J-wPhkHdm8tmR1u}`E|d~NnRHg(Hy@xfCwr@=JGo`MI8EeUAG zK-T%Y1c2o z{L>FTlz);#E*XYbhaZYfYno1E_YWmq*--}YGmiv~GK-VbO^~ne=hxL=<@wJ6yV*Ed z-q>QE7@o<0;;vR31)h*`VDB#zWv-?J(J1L{Q6T;59e!`$X1_Vx-nto)p*nG0EunFb zC_Ja%;W~TFT^pRTPIL>3qXan`qb5H}$Lde86V2$lFVYbt41d|(3otUVmAgyB4))Z3 z`mc9-d~w^TtNURJjcz$oV052|pKzY6{=$7;be`vX_HZE&3=W8@auR|W$98&(m&5Jj z4}#O~EI+^Hs4%`cKI41dUAWv@-&=cJc9bI{O|;Txl!Yb<(V9qd!*7^)PXzm#Ck?1T z(DgA>8WTJpZ%?+>o&4lAYP1Nr`wg+4)3B?kOPA8!<8Ori{4QmFGHc2joae4iGr}E| zPiHXY`=!uqF(ruc!^GHS0l${7bcW3RxvOetqSg9S(3G48wJ?|hjgX0eN0=yKuyhv8 zF(kQ!HjcgCF>Eq(VR1}2BoK-Td#xuplswblx(?kHp_^XR3I%dKGC0WB6`zxuHmy8{ zeXg6`)qYQinLQks5QqBzG9fSt=teEjMoY$mLD#7ka2WBa=G)x`is>O@m+f!kq_?Q) z3y5WamZlO~+O?;R0JDfx+b_5PrPsXh*ieuk;Gq$RCJz1)x&!B01co5~C->*8?-&6F z&c-c>Ggn4JfoRsGSUG06x>8PiG3JH~z}8W>nGJE_z3Nty(b9c=d75>7njI>&$W*)_ zMh`X@;!oorw$5W7cu})YzMGAuB9-o$lA*xJ3r}^i1V8^|V(tv`hBst1* z9Vs81s|NB2)w<|Lz1$bi#p1e!();<5fRAq8>${&o8?LcXq@ zpP`Git~k3_CcPuu1WodUq?NDB-0^_=BwUtE>ziiNHf#j8=N%P+!g8b1O(9H(8SAH= zOgC(#bq|ZM=r~|*S>ZQ?2BfX?Jo+bC)YI9~y{Plwrw4(Yp0aP!Z~r}g!Mx`%m_>XH z8|rQqoNw00&Lul)Zc0!hCCl4%Fs!3bdGa}VJER_@?GE|37aG+dzO zOHAvL&zk`97F~krDbi#q;=z2_e$2{?%`WAK+uD7vmKwt!$IcpRI zm1uw|i680gsGT|rDhh^kW`_Fismxjz&=CR5I8rq26(4N);+$4ViC$d^tWpoU@7YtQ ziX3K#9%OeH_XZ{Sp;LgWbQ}zRgUO6f1KzH@7E2RhS5lBozqAc3kR0@%jv(@``~v=& z^s1A~M00N;!7=R#B>u~c==~1+x@wBcQ``ny>L`yPFN+(^BGaGu+bd!K9C)ORzw?#CL{iwqJ-RF)L7U#o;7+sdiW4n66io z6rSct07#e&CH1ns!8ZSe^nv6t7F>nWEn;t9A3y;m;MkEsmD=iCQIOe^9$fPKWc)@i zKZPsHTCq&5Yz3?cD6hxn!|aCp}NDVsWs>r z-1MB8NTO7=Ys<|i-pbTtCVr5uzjp1_Q7GG|!H1rX4fK&)K*OP<*cq76cNVMngxAmS z?9=$*lOM#P3Flw}_wa@f^reMk)8bw=I7#OQl zW<=OLUd$tG_b6ZXa_w+=dMAxmuYzg{Xj0}~Az!#Cd8XWw9>{}zu4gL%XIlsAOqes& zJSY6B_hE-CrP39FI0m>hj53(m0|F1VZC97Y?vT>x?#NfBbRT_#G_P2B#CmT3h8~H`xoRl8eMVvd-kcKZY1u#Ep?Q< zzS#c(FfOI-$@!774-%;8ca-_>vl15M1EGm;%~na(fJz-{?OBH84hN8l+i}cMLB0Aq zktCVMA^A8DNPm(8CA5c0n;nUjfy!fz%fi~8i$z|g%`2dLYzU3+`3D&Q30Scoib`N< zz!^dJw&taE{?B-j70>R=deR1C)|BZq@AJ`IX=Q$h|ILkLdVOeW3UT%iT0+zG zd?awKiUXsmUR0{5?4F@MxQtpmmYl9og>leC^j_ge&0=uesjpe&&=%P)foV2x5+zs4 z{jxU{8P087SK@GRZ0u2U`dC>ZVuhuS>hOMYZiQ15_OVhx$g2ItX~s=sgy_y_Gn47d zuChfMR}RDNs9bJxM4ls&Y8{JSv(3UP=gt(zGZc{y%*ORY^VVcD&quxUzAr^N3X+!J z8exRI-lNF}zZqsESAL)qn(-MsTI9%FNYztbS0q87Y$b~;;*DEPib!wO8&$~)fykqH z$>p`zV+|&VkVc)x6U?p)>b6l~cYuH*@u*j{hXmj|s#8G__;5%@bulfuq1`pU0l9%_ zsc!AP1(Odq*9@pm9ybsH)sV4;av~;qj++_)*Sobi--6UK{fAC_aW9|=I&0m5?@lk8 zAt^__$Twiaa3*!{(bM|5yUxh~ABy;uUJg8jn_P?D<$+Z`!Q?xjP?_miNYAAOff=CF zcvj!Mrsixg@OYprlDEEKij>)c+?@mZ$Y7fowRT?w>Sw(Y6i+A63)_75z6@Z*gKn)T zk(Y#@OEXD&C;I50YF_qQNG^Q~ez77a4t2}exIfS(;j(@4o$&Jcd>#7azA^7cxZ>Y` znc)Hu!U_M}v=-%>T*!P+hpXi&ZzoMy3*Wz?C!QD(&$4ZLF~H1c#qQdiC&l<;K(l#l z5Km8=V0+6qKckkN7|j^J=W8d!GJZT1>;G^GmBAsI@T=~qHyOG(7{EuzOUTYFEID zy{3|fhFIGZQw^PMM(mt?{Ue$*Fg}a*JAghg^(0!d@jfzn*~7Y2mx=SESLCeL)+lp_ z`1?(%!8J*Ru-8i%2bJMhc=%PCTwm_-D7T0Zp5;ruZ0$X?vvqZ*2`n$u=RhIzN~>T2iuN+;keJ=a|Nqom*% zTlZN6N6v~sozs!ZA50f%^%WzLXtU_{msvy;WFJaD>=(<4_N1CD>#}HY^gPJjfA=Y& z|AXLAi=`w6UFcS5vn&&zzt$#>Z@%L=Gp;TB!xutk8*)`7l;;C6s{Id^M31Pd?;fdd zW)h2_^qEa&R-PLY+Br&YOFxX|Mb|?=Vp&QMS0!_hB=Ll=UVowZzFlpY*{B1*Q{F!0 zRBZ!lg~hR_CY*R{W+q4%arrxT!Bat8n>BZ=*hei|A}cT+;xCXNipgC1!R5<5Yl;u#i1g!Tn3}$WK&oVim z7%Q8<>%Ba>fCcgAJTX}mT}*sf!S~X6{wfXRXS`Gu%lAk3^av!!+K64^YhIe<<>ADM zgDJN4k0@=Q4&++!7{vbu4|B(6cQT}6Ee^%g-&!PAqDw54_mqXOC@Dqp)Osw+#9t`x z?O0>yW>t3*D8r^JpGCJYY*aKkR}075k~k}OvZ3vLf~UF#P-yAA{i{TGGpgQZPDgjX zN3m&iGwG~`g!a5VRJvr-p&5RExK!3H)H;DcD097aJ*RIXyz$gBgprHhYS-%?7l%MY z36CX4oq>5MIAse-o*bl*rf5i#M5Y`z$VHlJ{v#r@{{+&K;yNh>)gwy~6v`G^ms+}A zqDf$FClI&q3Gn4|GUysu>N; z@J=7l)H6>^uvbyBm^6J{GswAMF{ycfH_M?Rq?)3*Ge2FqFwT+gR0#YBg1cT8rHG< zoTlTy)_;yC(Q%69ypwvb33HqF47OE@fr2E97RI34ed;HNWi>l}PV9h&nfycvA_E6I z#^j`p!gIipZVx{UzlV$F8we^KeindA@QZ!V7Nl0DX_uA_W}ES|;s{i;{Az#4tOGH?ia6fv z{L49KbT=sdsXp%$4>moVj@MZ2Ll_ ziU>}QoIy_BgPAi-XmeEMVvnPrX6#nvDD9B)A*YD^lk)Se?g)}Ml_ z{7Yv&CT%L0V_P7Z$}G|4XNayD>mcNOPIKBg`TZ?t-f)<`kCokG)tZnlDo7~_X0M9X z{NcJP^RNW=pbG}+EpgV#ZT8c=F^%7TNV2qKFeek}KNyladX&e8vWg0C1nPW3Z1)_E zILCyKdmqSVt%jDJvv?B@iMsYzwz(Pt{XWhQ1)rMXVJDV#C7LuBPCjp{Rd;ui7WF#Y zsM#HB#(k$Qi5ETICxobk);l9?;;g6KeK%)*d*fDQgJppt*|Ns5hn0KuFdCD>sD9ov zmjgqVbbGFHEhwbx4_7>Bvp{d!0G@oqc{eOD`h!S&b4MLR(AS0`6Ju(b`Q4s0nXoj9 z=Y^uq7tMAzkxv8nzU(YS<1PlPMT<5JY3vL;P1=`rd;KKSbgutLZ; zvlohHPw#quSVq)VFl5AJu1u#=5J&be#qIrQ24DRWE|kl>XAqMQ9VN4^svTTlA0o45 zM+|e@7+ydIcGbYRQRXfIvpjs??q@2GgTQ37%apC}fj(%-4{Y`MRJBK`M<`=>QR*7u zWz%oS;O>&t!^~9IjFG8Sr|p9=hXtq~F>VHO#JS;0rc~D~V|Y@`s}bS&aM&{8uI{s` zdwV@vy2u{FYe6{yUC@;KRAFTn%Bqe|GTg5BoUr367MfI}}Q=a#TcNQs?ymSYcPXjjRB)ixHtd%NA zbfl{)`OI}Wtq$jDre<#iYtNJnmATgv=yyhtMcF1TuO}FH@pwzF7`U-9ELrI~7>R27 zZ*%B>iYLpoF!WspX#(_KeNN!zd&P8F^5Z~SU(2LSRF`@=weQx00>j$X5}zsvRQ31k8>u^H?eXC^a{JvnkGuLKhtq^etx6T%9BZQ$XlJrn&|GLlpURHIQ<8MbtI zU8nihjyO434w4jK)#X1y-GVDv2lJF01@8|^a6u0<9~j1cXtmP_9Q(MKz!kY*e_1s0 zgFfm88!OQBBw@#P=cyy7tFq4Y<+d05t@ZW5eLs^r*!08o^Y|s2gk3y^m;q@N7cW`T zxx`&>o)MwU-6-T{o(SewYr$OrcmLgtK|D(a_Re!cINyEht@ELD_}8Z;VgP(0kIn+c ztD$Rkyg1EFhD42BJIOjfklEP0#okkq4F?&{bDzUSn_WMI7#Xe|u<+*s8OLq^s{)EK zssU*xSM;3H1P;Zx=11S3;iHc+WVr`@({-;C3eVhao_DuqXeNk~0Fvix1 zPiU?@ZGRnwwpXL+!DJygAK^DXnA(*q@X|B?rlx0Cc!Y!8>ek@U<@h$T1_2dc(&g3~ z+5Eg0u;C+n?GP8Y^kU6drb~N+W}q0i59SgUGa^wAtI3%Jc>9gY2vh#J^YY7Rb@jhVc_+edWI=b zat|rQ+Td4*PrPY$Fg>3b-ZewwbM+bnTn%ezVh{Z<88~z3;;fIH#aq9z*Q25+p2`EF z-wHqD0Aj26^=-7!Ev^lsS2C5D8@!KQy?2a%(Opz%hqo0Di@*9rN483uL|fVOxRwP) zI$46X5&l^ejFTx(4rADbRt@kikdIGIpw# zyAKeiH@W8z@Ey+kqDSfLsHXpi_yNCYP%m!-chf;GA5UbuU;mh|TKxjuPBOqcZkU5! z#cTNhEAJ2IOQdrGv(&{Lp@zn*HqvF@f$&_YwUod?DOEAmSjDs7l1qj8Ni*z@r_m?FkrT3SUek05{ zqLXQWs`CJ#$n{M?QuxnNkh65u0Q}&iFyj^}piq;GAQGT#&MK>&k8rOkHildW^DE)G6D7;V7E(x>5ssIb7=@1HgV&SO*cR0i)H7BJ z51L|QU%P%y)D_x>4`%-<(!j13D7rV_jd)|z?}F5~$wg0>+RUNxjEBmGuQ0f3N#p1% zaBv4?B^H8?Hh5R$~2}-hT=Dw!j`U1Sp8ffxhguNS@AnF4eF*vws`s?Nz zSMxlV@6Fj~eQLVED{Ga(ZQL;4QQ`BQyQ8W*voAdp$6LSp#m}3P_x^N=3O z0om&d_lC)zPCW|gIgaiJcw*($_sjV(jh|%d%n?97^^@rxdmxhm&Ous%8`aM85d@R+xJ?|MZy3d~u^fZeV`*ptH+m5V09RX@TgrnD*H(Dj=RJH$7 zi<`B?1(fpWSEYL`pBSUGPK9rsM3 za$riG?6I3Hh_mZh&IAMC)YRUmtQihWz=7mG_5a8v!hxpC zm<20GK;8s})`0sA(CAkVlBxdni&lPg#}S~6fq_SR>kk31(4nhDt-th9Nbmn*57=W5 z2PKi5G*`E7xclX94;ysuJvFQQtqtc;@-I4J_YTf3(v6s|?{kGJgNa`2CCM-aj&a z|0qoUb&>#zI{zq4{)_t8Um{!o{}VsG2sj$Ro{IU>cTV;M*Ze~{UV&rC&qw3#^c3G+ z8So7)@gp98yZcR3R`+no)trpP(#Xa97TLj%6Q-!Z?Ad|>U(7e31nl`833>yia1oU6 z`$YXm!aX!H*4Z^Q z#mwdcm7D?-ayKyl%U4A2SwFGzO*GsWLLgJ8ng00wU*ErAWlW$V)+^S1bM)6=0skBN z(%{)6P9t4~HVaD~i|Ww7Z}j_DjH-`RO{%?=t>a6DoBr)?1uBm?g_z5AOR=~9?OxT% zfiG%HBHnd&7j@VY{(kJg@A)V(FtO2g=VRXkLxKKVfq~o@Jl;dotSOo>(QWea0EM24f*SkH^!PH724yv(d{r8c5>cq}zv(mZGt*FbY z=!1S&e-HWwW+is@qJmG7r6S7UhvdKBEvN`PM-a@8jcmDC;?waKo$#Niwu?3~U7x>R zxxUCU8AGdC@OgwIkIvf}uD(nCYQ<{W-D$bLvX10|*={xQ|LP&Gy*!%i2RLFZmitn` z)`OYSb$8rykt8SkS=Ww`Z+YUX3Ru#YrbZ7+yDA}CQWju@rPq&51aM*)>r3mVLuq=0{|(b6hr5x zQOELcx2%DnNBug)&?R(H!B3$w%Wej^JKSHl@p#&2gT_or=>T~Asf*))>#r%I&h*#O zAVD0oyjn^Zy-(jJY|_aZS)#9^I67@^+Y_0{m{QTS|A4mc(mD0AvHME2-{0inKvHiM zTBNN@Jj3nJ{qy^syvGjmJ3{3Toxev!Wf19Iqq()C$)W3=`5IX!hw-}AUUMWt!iK!q zNN&=jd!&!dc&z0kA7gSqCD@xa7RSUbSrQv6(zp>+Gx%g95m@T4TmGIAX3XN|x`@^y zC>w6cnf()!5fCZ1uAguP%M-Iv5Ct}}R(R+m#g_30ss$vhXS(FX`PwF+&Uwo8ms`rv z?GiP<3DF*{^$Aa&%VAZ%Ee~gant@x7(W7tx;2y`>93(#SX}w~`H{Hd%0BXpEk6OT! zP7S3f$EyB$(@zW1AE}nuTj{)}%<274%)!@&Uw7d&y{6@0&Ehj+L?ZoUmiBnhT*(U;aW@k6^eyQL1{mgn$Q-C;pxw$%m#oGevij za7$2vOy$-o<@w1sFdYO~4Dd-9js929$);&RxvWE9vOxCn*f%&;WN#F1$-;Lo8JwV+ zWX+%CxFsHV z1}4oG@)|LhTSrE=rdqXSS^)2_Gs;%rX`qXE_gk+eT*mUm1^Hqb3~Z##ol-*s^7}oJ z1~yNH7F0O+n9D_kLifrdT2qzsQ^2?-{VszIoZbSl>Ox&adTDbe?mE~=<|lEoF|E`| zb!fX5(MS0ergmfeKEf;Jb<%X_j)tUQHA5DX3^x z`Yq|d>9NTa>Ae>}O#cAc0EQ6x+z2>Q=A>*}Ec(QZj>dS6lvqzSo4S|@b3<<&nJ!;jg2DGq+qhQVte>1BNVxZ%bSE&! zkyJw#?{Cb#e2=q(AO_4sSGcYpu&n&Z4Zc=$KmABiGw|LTo}gtSZw9d@STZIH68>w+ zWP0iBS^V`LnpTT&OBCL*1<(cw^SYr=F|rf^CrH|6zl`7E=TLeJQ$4@~6cAjl-CnPD7g@!324;gt_(Oh}QKV?@@~A>({J85+pC7xFs(gA%nOj zmA;T2;4_L?&*2yAe}~si&F0oLQ}p(PA`U2oD874vQiFfg=+ zlR}uq+@_O~z$X|RN$rc5Bs|Od>W^b+9e4RH5#@;(A9!06J1 zSkI4Ia1woO47F5Lda_Lxq!UxRMHQrz2;HIsJ_Rrx?l!;crT#@CH5#mnjdXMc=JnaQ z_A|g+NG9gFg-67T9(WnfvpoZpFLE2-`w}s+`zZ9HsV-P0A_Ld`7~ga z_g5df;Rn@FZF_@Q`Tlp&khk6IBGy|F9Q)gw*lMZ+TwP9WWo%ulGJjxI%G^zX zps&k7g4rxgz{2J1LLNo6a`uiL#Q>j_K{dBb+pO-s!pmH5W5slU)#8@uvu$#)0Y^z+ z82MXl+@!ZsuRt-tTNhWaUI)COt*Yn6M0nD9p&mUc{Gi-$q9w`F^lm*Ex@YG3h5I; zUypI641IVHEZhXJgAcI9mK=PP%o41kS`FUv%~jrN#Mbcm?U)(;n`8E__c47Vml80= zwCo0lz|nZ5Z~Jq&l2O@YL_#i=3Z&uV+%d zq4m`Ot~$sPURwk4asI#L*n>5RCIR7{6=!%WXZz?5S zGJ#*5PD}%zR4nDlS=IlJ!|fk)`j0vN$DICSPXCXNBK|R_|LddT|I|B0+WQ7HUm*MN z+K*17{ja~vEdvEAZI1P8dDa;z8z-THlfC|Rf>jznVyt>W&+e`q-XVObMDPE7;X8`kE`nSiWYnm&S}XuE2%_| zgT>!YS?Yh{l(7Pk@HC%y1!qO|WIoy_KkU~*qfUZylk%a$P?+z}q)f zBhot@eb-p<2f}Be^bUA*UckY1`11cUXz(@)8tp0E9>ps%ey@F;+|c_-^XL^a25YBX zv?XAbX&+FhGZ*>ku3a_I=h4=VwX@Ry(|fiFCQ99P+$DQ8RAN*&3`mH|M9+Uj0P$&b zVvQliAGoF0f8rj0yq%=8lZ1xohn=#}NX4iq2v|6y*ytg4NB;RrJmrD6v;L-)`YYSt z$k2ai9QU!2<{FxixKGp(c}M-M{%C9fs6 z?f@2t{02huSuGHfHGzL4b`G)sn-IJIY#Xf5IGv@`Er*IGdmvMQSK}xI&dQm1ms6x5 zlJE&|wjbBbumd5o!V*uLm6fG(*6)1*>-$f3@c*8$s7&DbikO%_kg>bDWtI^dwMGHTg z@3C*Ui@_P7bWR#!Og#Dn&fnO?MmqZ+=WTwA@R@QBt^HAgyAfcvoaj(>ihQbZ>05k`a~AsMjp`(<$W-%a`=G6zf)4ZJFEDPj`p6H+f11?KA?oG9V zJHNy52moyPw=jGi4S2DTTnht}+*1_y>SNKq<<#5xbczL&>w|pR6f!Q|}>2qgsDJ&g{^pAZ9Dg=`^@*e?YSTCWYx|@T31h z*_DSw*|zjN}6S8k1`=f=*7P4$xcH8VKTd!8}N-bH9fZ8ApS9=09;Xj39!dBEM#ln{Xm*12g`W zQo}R&bS%4H2Ym$bJm5fqfB@O|R*#0CP-+nE)K|Y$Nvd4^F&xT5=;ahPZ-}w-tvTRz zM11@3$K42!>3!O|;N^DQ^Z|uAMz-%mqbv`3JU zQj_QcKv6fo>{UhU46_M>6lo0hDP1)7UQMw-^hfU)mof)-&(qv_@l&WnZ9Yx;KiV0X zEu@>asL^Swu2+Wp8DZE1wvV5E_7JulUCKfo>;WcabGb9_jth}W zgvUSY9?|W7E-}UrD>Lk~@?9=ek3|y>zY1R2?~~=SY{v9vUQ9WI!a9CDD)ExaiuGvUW!ul_q;>UYzJ$9njq4Sjv9Y4onpTD4^8|zk4URa(W$4qvbep_4 zl>fKAVN0hyV?l-Y#pzHlx*d`fV+bMa?+_w}THULZe5_nXq{7T=@0p?o^>bu6p@)sn z9%$=D7&iUB&u!4#Ji8n(#FcdCdAAihQ^;)t#M%vqeb?v5K=K~yzFKc2>*7UR?o946 zzsH3gYuw6(?GYo)RaA7}2;^Oe8)wTy@f7hF&d_8JukRaLqcQ5=%cQ~9$cBGMn1|Xu zq&W+1LC;sJyXvtLT&Wvs#MCTr++pMbAh~UG;2L*-7F|irhy6Z7oBQgValUFE)y5Jt zau(xobluINSJo=Oz8>mr_Uu_}SMy{TVnFq-m4`pBWR{gF$vmG!*s%%FAqVe}aK?vVA#%;9vI99?r zO=7laxS{F+O{1=Lrl`x5c>nDPWVpGxEXdR2R~I{_6P+fHu&6_gt!#46X)=w&_WgeC zdfJbVG7DyEl(G{fUuN}9COxZE*G+%&*zO4S@mG~x=PI*s$m%;qsp4e&O5x*C)_VW7eVtoUBu6qa~zAK)6AEp-0i1fH(LUTDJylX z7SIp+>bs&VK&st{Yyf3f;a0cEvE z_Qw~&OD@Cv$t=?{?l{(5VP#}zo+_#GMnx?#rDl1;=T43g_jz=x5Q&>&>c@162j@^O zIx^dBkP5T>!)4wE4r-0g+#|8NhV4e~{l7MbwJnpjE#t~YS*dDKuv!u;iUMs^Ggc_~ z5j#VHKEZr>(6%gn|8|@h?&$iSi^jVjiEOa>iQ4T(v^f72;1@;c9hX)L>%??SkI|Jk zMsW{1uxeD8qhUYbO$-Y!!}=^+Uhlgis-Fd|SlOKSoN!^EQ(&yH#g)0&Xm&_uYLFOD zFx?}w^!f4AlD0lF9n_dlgXyMQd5J?VOeyK+9jBI2{oR`x?$V8P;=15$N>Lf7H!!Qaw(qAbC0g?4AD zjo7TuhSeCgdryvb9|D|Uig0|tw)zv;`tix8DV0_zf}YnTb>m*l7!`Ce6#LJx0-1jO z_xE}*FSbWnv#!5uSVszPSD>P*(}>=KXeG{o#$(vwa0d;=)JdTec(@(w za0~D76ZKUqLKGRJPvNW{h$Z^nO5l3Kk>`IrphCfzwdp~5DsX)Yc|#v=!DDScEhTP9 zUt|U;KOdC6dOh1y7ryy;y*)fwe+unO(7zn7B4kijNr+hxG8@yIiFFzMuWSZg1q)|X zjdv%r_2anY10rArkGHOSB4VP?zeE4w4g&ex36v+Ylbd6vwN6)AX`iCRJ-M{L0#|43 znhZj~p0;y4Mc&EM%db^MfwI4L@p8ZAEE$Cwd%X)oO6=KAM=*PUgKp+WfKy?Zj>7Oc zW7bChW7Y7W0nR4&h=j&V_HZNpS%6ns3KU?+MlU=ska*@Oy;(;H(<0!)9SU?(+-*f; z+xWBHu!HwM?5*`}cRPi=<;EF=CpP>Yo><2ep|yYmouWeHsLozeydk5@wHDj*KQG6J5_-dCC5?5&jHl%g;%S?ppjB<4s6saF*tT<^M>}cWz??bI_OVt;4a*Qh6SwsF@amqa zU7RniS ztPnvJ_It3|<^xVr;*$AF`!Q11{eBfuYWR#R+Q^>1DWu))$!`^aym}Jw(`&Sg9`J#s zsypy3!}+5tu=Q>=(hlq}PVzz&ZZ}qfj^(*3-n?kcDr?^*6$dgU5tfi3p!Fr=b}RS; zkI&k4vCWYDtQS>8?W?uP;)peKeZB3tYpMdY56Z+In@IaZ(`&rZC#gy zv3jZTRv!7w8aZ)vlsN6<0V`12Cn&uxCoid5n{h@MB0p5Wgkb#XSA+T-P({3i(aU)@ ztB=EG`nD3Pbti>DHG&q)HiOfsKKywi=rcRg-?<)wH8wjb+A9yI(WHA$_vym9$<5Pf zF*}pO`s9GbHJ5fD?-7MiDnA#Ictv*Vi`CAm-qEpAZnG}}j=Gj#rBpCJASct2L!@o? z^>{-JvYUU+rOawi*a0>CE{@-Y({pRTU3%}id(o;psb5{QccDJkY)+|!l>#kdV!H1q zAs_EiR5nx43u%cXNCIf1KZ~9Az3bvvHdPPyu&E=;WbpUCBejEj7^uqZqa17w!X+wj zdYYU3aXuVA3WxBMhi_LlztOeR*`61EHgTEA<1$M6iRyp374c-;d?(-$Ez{N~nR{AZ zaANnA))h$aev=9J%n7(!%qyBp9b8~}HE_Rq#XMTeCXGvq@gI;WtEWcesnODAE?y)M zW#(~va#C39s14`K8MB7!&0(HakGgakbmrB~y(QS?t&YXV7naZ1mV5eqf48%7X`-zW z6mM$x^y7XW(ELCwD0a(e+|(pg8(c`6wOkw03v+Mu=mNoX1x2Ql+l(&CP^NU!+1Mq@gCbX-Ys0{UE*FBzgKCJ8dJcS zLJNu*DLFZSW>#{w67}b#{alB%qUMf{B-{kLAl?x2#kkK)x6 zyExX}>{Fmqa@%r_7^c8x2?9pC#mH>08cYRgP2ILjpcXmOrfram^>s-dUrE;n?EX(x zgKD`nzR=j)6YWnP#cIN9;nEk{S$h<|^*#A^$@eNVDoDsiXb4uT!fS0t=McNss9vdGHW$n3o{9E>)2hec@Q3>sznu-5dbVbJKmQ!a zSv*0Qu{K;@80T7nvOu;SQ{#v=`TkTECfL<;ZIMt|Pb1FwOJ-_QoJ)($Xehe}SK6t?XV$=e_iR&Hvp zP-+H#*=>L4Uhy(cuMvPk_I(q0J@VzfxCLIp@!F*Ji<*?UgLyCXy!Y{yYRqZ71y(W# z-gH|77SPBVIqsp2jO>*8**z5F#Gv-N&fD^x+TWHK@y*WlJEf+=^X|^?iWT-cx1V*p zq+4)uVWU=)tP1F>vj^n;L=)8CdZE_&dJCDLjBAAA7BD|@3TvC^6DtZu$`!TrZXk<0Cpsew zAaAD@Tmx3_*L+7^LVunRS@{OWtawT}I2#r*!N+z%?B8}xz4-5*X}fQju|V_al(kk4 zOCK5Ig_PVuzkA)?_+fp>vBQH3&%IyE01A|l`wehG{S>^(uiFBqpsY?49mvQl1SnNu z@mQR7+ACTH?Pkd-o<&F%Xj=bKhZ55R3&wvut(xbj#~4>XhnA|<3|Ml_*E->L75D3J zTXVZxP+`Jvw@rgG+t&brQKA4wF#^?`K+f1` z8<0B`JBO-mNRSXN=ECY$4c+*PokNeE7F_>i%b?x6_M&%aNnsA^iN>_o$AIbl_*+sw z>!6VLU#w$9cZO!UYaP!jao)EHrTkJS2LAvZrDzQ7dj7KS=bhIk(&Hf=kwu+-1gc1) z!rUL*_6UT^uDvRT3&Q%d(%hy*H6M|vh7CmA{QwZVj8f}VvO}z)3YVh-6(-_Y0!|cK z^#83WijhZti+JL&J&{>9F)7cG;_v3l|QKSaXfExVT&9BqI`@9p(cd*6cE?sXKge16I#a<$fhI8{?FujdWOmss zUD{?rn=eL|IgA7gi{cgP<%k16-MtB2o!nUha%gFWI;)4%| z&cU83Kpm1y-@h$jpY~3NS9k6~RZIJOuVk2+erQ}UBy>Y^)5@74@LRrF|$|DS;htoo;qcs0N_@H4lYN zjzhc|+O-gmyCy}(LbG2lsdt<=wteiiQDU%PTkf42VMPV`ME0@am%fo`ZRQxE!s~%0 z{5`>ht9x*Z&kpkSzbnA>n{|KCqe{vB)^8H2FfCU@rlGt%9(QslU=+s6n~)KYPVRd$ zP*y?cpG%`^Op@s>gIrA^d+#Z|Fs<}gOX7%HVMf?d4>>(TItw1cqe_k`#ml#hI&`N= zTC%`_Qt>KowI8pm6h!U!ZWTmfdk%dTq4yI{_Osu{ovG zqYF_I%M16W@Oamv-nJgHBtn%5e}n>rn}eIMP{vosolGoD0czkGPTqTm^5Y28#*hnKx$q z3jsR>*YkxowoDFKtu&q1keu76^b1lsW)6aCMr!hft@4C!zZAj(hrEkBFbk9^V zo5Iy}8BHbtoNhe_0lvJP#G7N3xD@T@vlonm9}Bk~qOjhfxXKFjbf=MTxqJVVp#>vU zCyYGWSJ|%C>28{lq@gr_R4Ze45m%F*BoH=q410yrS&eDpe35d7@nt*UFcpvLiqJy! zRfDi>k!7!Z<-Z-=WZCKx78F`w8TRiAOfo)LU>_k+%b-m>)YIU4(#aLT+6wy{C_yfB z(Ox(#7Rt?@t$r+Uv4-j?+IW2tQNDNlMqkqTwDVv*wOwhNG^_o2Vw+IpY3q=SVB6Jvb)kmQ9*EE)2A?sx0!U zd8L^^nQ=6%2;gb!?>3%AUJ&zQ@fJLOjPzJkd$w-=Crs&ViFs|%A@!M=03EMoYNUqh zvG`g5SMwv+@;wYXGXYEWQQ0vibRV~0pv0YOuz7m?$&Df&_bCzdIgr=yC<{pfb7RGK z*sHxsP+R~4^pm6UgiA>-1^bQKf9QPuaVCvP%|m|qeD6HQ15_K{B%39WNN%^!8}FX$ z59e7kL@Ri%=OGI#|24t;!c5#J{!<{wS3aS1hb88)mq7aAnWYSX-DJN5q4{QN+7JGf}wQZ zn_EL(!uGRGq}d+0o$~2iv+g~uG8=!~`DOPptQb|r%V>nqI|BvuFGBC=4MRln;@l=H?l2ap)Qf& zs?@lplEw>#R@3iP6+Jl7TCs=d5J5mMjxPR7XF&%$Ab&^O{;JUo4Riy8jsZYh^;Vj~c6YS<%6ma~K$I4O)JrMg)_sgrSVy74a`pVFq7a|!If;#O z=eQYPgV>=eRI8eKF_p#NKWoMO`%xfub_gA?!an63*HvwoTA2}P*3bje%om5!L0oy} zumL~33)a1{EgBEBlq$)`!0I1=)0FfSh|0$kqKHl}bqc&5ls-twj`K;O^K-fN==lts z;{HxIp)5YuazO&x?QN!)hZZbQgjk8ur|J!#BDourJZCMNpxMZ4yCSvx4P3DC$H}q+ zcf{iR#yiyDQrVq}$YRv~PNE-}g=X?@E)3i26(vX?%{mjb1?t<=)AisxjZ;vl6NIk= zzy;Pw+m(}>XyVv&SHJv_hs>mj*#ha+eSZ1fa}nPkRcOWxnAOcl9>eOc+5Q-?1dz{$ zuQ9&VIgdgA$0QY|>W{i_Y<@1ZwN7eW-w@R2&}rN^KLq=v_v^bNO0)CriE`#=;^Itz$}+7zxClZ znMs`)e9-Al+-V?R#W-_;vRdrYooaJR5)lFyp}C3gyalf$t0hp$fICEysC0-=ad2VChpz8(H4oH^XahusrFT~7)(O>~aO z?5D7fSPDRSzp-`~)bE322U)J_bOo)jIkb^VGqhkHRzvc4p>}!ij$G#bPYw;Yi$of3 zn!`^1*(?7thoNx|2hF9#4L3AOizaKqhk5Bk*}tyF_k)P%SY*_}l4%U#>Eli)Ma5{K zHJ1Sx8&hQ@A8`r$px9LFS6`C59l4!>5_jF=QJ=Tv?r0}B@HDBtB z`R4_7-Q*z0ykUlVF=#>DDXib=J0hMq8lXe!k1xwyL|uE~K(D~eafe?=W7EfqkT_?9hQJhQ zyNiY@Mt}s=dqur`G*@H_tY36OA5<-l-B!P0>O)609Q4`qwRXIsU^I`;x4{+RFX>l+ zxzSIm_5e&+{=@*VU(7tE`}wr8^evOt+SB8L#d==t$a(YA@CO1Fo(R6_oIrUd{_<8H zy|*{M&GbB|zeqD4f6Z4CZ1N|?T*vl(rss3^|8Nw+7!NRBTz#@nJCftw~GoljFqyj<50l8Jg@d3!31 z;7L3I;aMMk2qKnX&4S1)2)E^bu3-L0QF%i5BjOtHfPD`BZ>{QY%k7NKWAGE*dF8$w z6^8Bz<88l6-7T-iOyFs^{LRjK+fp^`gXClYAVYkO;b&HQZWaYO?_6r7gtLb8RUrYS zb8A!3(SrZdH%r-xym&aprUa+XR)jt_=-@gS5>8hiW|?(B)z~(~`=m-~^Wl;hCWV|^ zS(5j(a6H(8<-w$LRm0^74j(_F0}D9uI}2#d5SzpOHN!OMA3wRL|7r7AWLmjT!zFvq zMAZ~5$kf0ho@E%yZ78~x8oz}CJ-c@6Ft8rA8MGmai0jo6%V*#ly~(Aqv*|!wF-xeo3U9y>>{>@~MQ|l^vSrsX3hPV9XFXwM zr2oD$E~+hU+C&r=RLdPYLL_fhA^i~4<)(Id_>T21E`{y{z%7{U{9kU4R16^_i;^E> z)n|2ex8trREiM`sOX;=2p|Oj%$Ny`J=cK*X;*B4~;XAitPC*kZ>KKuQFhN6;#A8@Z zizqjLFlf|WGH*a%UkTZC^?Lrz)!V6PR?Ff3XBQ`@gtXoT&`kcHKJ?aQnW6LMAF4?X zq;(5az4XF|V-OA_VUC~fHenc$J0fSSHYDV1;`$~I)PU&v&JSPcv{~L6PCSQ-|6^d} zrzjX;LRJz_WM~-gzF6hB9fwU8dw5gYFTZ#$;#!qCJXq10j0tL4cyg0u9ZL_V%q2Ib z|L?Rj@-aGYoKQQL#KE4+}^j+ifGTnz3@dEsw z^FTkz9xPCxf3hd~7=MGGCS2FHF00Ikpl?0a#cgmM*?>7}-Qo5Ln;XyodXfhgG=Ug9cPWD!-!= z(l{;bpKMt))m>KdvyrmXT7WJg_r!lSaNnd3TH88MF#UD!yw3UQQyfPQ@C9bo&$}Y4 znJK6x?Tv#RDel`2V%~jItg%6j*MB}cBCe##{u~IX1+5w%C`?d3_Vs*D` zW|sMDiIWT|aX*x&@DTnK{pHIlQcWL-b;ODp_>Ln&>;`3|o%w5;LvVTRL7%9hEK{T2 z@5TP80c~gpb1vXHa9 zi*y#1!00JQkyCBfh5DB|f0v&|xLv|qz~sZ3hTDZB4S#a(FM(DWW1wApalyMoTbLuM zvPaphYWw*O;ro2!HPU>I*R2{gM0a6q*H<`Qcf()6kU0p{hPS`ZUgU`wVq3Cld&wnY z19>z4#rEGB1G~+5mKopC{F+4KLy{n%C;u-&1re%8^aZ}_EsAI+@935Fiy3O2i=KG{ zLf13{qerE3#*xpM3suP*tjGoI@tYeg@7m@Dt6muDh&FhZy>H;*K5dzU41KgUmcAy~ zdZ_-SGZ!z6#EiC|#9Emhi155-^iRPj|A)sbIPy@n^3Ymmcy-^MxI1tfyhJh#{!5a9 z11Npson;+!iiZnV_SjDIU)XJ1+0;b$@Bp9G&a7eapvs$MaZ3Y4o`yiAmIFujPL2#jz*;60(m3 zk6^Fdb;`GfyJ%RWT^H`6;p4)L8fd*b19IBI-|r&p{)RJ`_4A2&Y32Sx6zF(c#P{$^ z9Y0?PD2~8C=7?w-dyj-EGz_DIi>Ko|V?d8}^U7CC%%S6n1J}g$U6~C7?AiSCt83U7 zaUdY16o1!7zM8nSml*YbwkK7VfcsvIKd5?$dQ{3txm}CS^bUkMXnc&=TbjfqC&tWp z6}H__g=mkN`=dD#N=@pFiDJgkSF61_V1X$dy>r#V_W}r%UUOrOTM)?+041o zs3cB!7PE=pNC!IO=koJ1@@FRn#=4YWOmygWaW#1B3pJ6JZyCfvu!i;?Zw4??(Jy@+qVmY4=OuS*`^&B zn>KJG!68@2umMpEVz$tfkZ-7S4F~bZ)WETSt$}aH7S61s+O7l0bKsnDqy>_gQgqpz7M1#40oQSONcbRN z3t&4)0Na7%nX%=&NH`b?upVaGzZH%Uly)|$(yDn6Q~ElaJ2P4}RjOB`%FOMRL;6MN zQUa+QrNO_&Oy9C%NWSDqec0BC_`!8^Q>Gb<#yB&We_#=V#OQTh3}Y($vV9D4+}`N; z5|?TCZxVE{#(p{3DSbXI7HPJ0R z7aUr-*2Yo92^s*DYnmwUkC3F9Tm_IVt%kIL!S+nMd~z!ExOCx%6gpoADr|P}vVT7o zVjIrzh!-u!H)+`&jx&O<2z~FLzoJoWO*5r^VJk1FTB#I=-0pVtumU`3OJW6PIFJS$OgAS zU6R`U{tVav?%nWVr^2jyO|n4|dhW@8c4A0Q+|vWvwyHzt?+upXAE@|ZY&wr!-Oo3* z+|>OVq^&CXxlSt&AQ(tYvzc7rFP~luK&`)%hOq{sZRx7w;sbY5b=>-0(k0()xK@0- z$S(xyi#89ANwNimrw=>Mr(g6L@(0C0zL0h3jMuyEOfkaE(rt%byG+Kwo}47<`kqc9 zW-6<+3FyujToonTLQ$k5cQ_O5r+1!0K6y{?64Q&>NF{-LZly{pV)S#-<_lbTg+N@9);DqWr=k;aW4y zOV1xHHkK7jmD=5DghMlK8&}m)N*vWbni3F$Zn?fF0Nmvt{}kl(43H-e8m7Zwk!0pG zT&?T6a__8Rk@E1KVj5}y66mkD%`!kc=uNKmrWzxyv&(UZA&_ni^jt3`U&)wU3mXo*Ns(asZ+C)Y?V+((sUbq_KPq?j%??bZLNX)1&si0b$gL!OvvTX1 zb1a<$*NHF+w9E)aF742SeDVUCz37kUXn*RgkEb#LfWMx zjC%tTsggR*@ItwfqB#R0hgM}71%St0Zm?D@S~A93l5O`_c91LO{R{^cjPuLsIUjeY z_1w@dQeHMJ&b|ZR@o>)cWmNzF(roeu@eyuth3#xby#8l$bFD2jFd(*!c`S z5a9pf*!gvd0NU`IuJ?z8Vp)deFF?6Y_ErJ!Y6fltMMI3Z7EEbrj)Ay<-UNp#>an8X zkow#BS+|N_eV^6Q^7Oo(^qi120N!NHKwfvlaAU1A9+^TCYd))()v50s+-)9j8)VQP zC*_vq{`C=8!*20DV=;(~^>aqvUc70j4DPVghocCz%z7qjg%i0};%n!w$3B#vX6-`MuxOl-)aR`W<2`npcc^|SShJ9V3y?%4sW$p zF{H^6jLq@tFZtX`CPA!_IJ>__+pSp#A@*o5%ZUTCpWD%6%}3LAyuPyyu#hwV1q(s4 zKwT&`J3Wi2hVZ>w=lxZW1>2(Zb?5K%Q$2+T+r^t6@XpHIW6RXZBbbfsQ#ElHGI8R7e-~wU7wZC zy)D%N`l>xtVtH#8FuB@~T*{Ym!tpk_ipL5GQ-ggbO=niB{H%@EW7~ENbb32a92gXi z_Rib5IU;AYd?W8mB~#~&=7<;fyA4=%VPT6V5nw%vKZt&Nqk1I4w{&(%dGYOV=&bl1 zr+U6ugT5O?^O^ikviz(vC#ziNcEgv5MpNHx%^~+@nUxsJwzOD8pQmvpum?x#H5-3I z$aSu3O3Cs8xsG>vvU?K#P5S)cof8qD=VTK=9PWBHIS*n5P5r~K1*2#^*;RZjA+>jF zY|h8nXLCK9GzaJf{v%zqBTF!8-*oP!_mO@fz z*SE`w(CF`K`!0XKen`Khq?0U{rA6ej5NGIjkOEzP84x_6CeP0s-)h+fi<)^dqU0P0 zHiP@o+Sa4k4F0f|pC8H%YM2q3cNb0UZk3f-W+x4?dn}B?kRX{wm|y={di{H~jD#tS zSd)4EF{H=5RQ-xXjSVbCtt_=`r-9oH(RF!TcBME;#JaZ(2KorpvHO*ti|t|{qmr%LtEwfRwaCIXW7yNf_(Xo#QccL<6}lr zA8Fb1iH7+NeOjFr(F2}67Ka}XpoxX`B$iqx$|L)dE7g-0_U8?UNY&02oexF67@^pl z^FxxK+na+3(|M{pXYb?|f&#J`NTeiSO?if!eJ6xKUA)ozIq*pKo*FfGV3W;mMqYtv z)ce*LNQE>t;r6Ddu(rJ3?SH=>fcH5v#UMq4&?gXOcqFQFGVAu&ol!{ZSyZT=jc*ek7wp}daX_`2AB3%h zr?_o<&K!}J{yyMS>5B;AP~a$)QS6ZQo&(>%_~Ll;oQ#SK$izfJi$biFU|;(j&~TB- zpuM;7-42$6gz-vzW)SEP3Uo zm{b>3bAIW0r(VS+HoN-t7MHcivxo{k5A|8+aGv@km7e9jAT?<0+U;2SdPPu76H`{7 zK%D2l;*!4@(i^Wn;6BpssltMXee$GG^^^7F>!P?jmqJHbHe7>OYYTk@Tw?ES%sv?V zvdvIrdB9HF@*OEiz9-N`O4^Q>P3zc!c8v!Sh(wt%qUROmXEJtM{OZhn`o_VkA z597ItMf^mIw3)YB`(pOuXSu!0NgU-9Y4KNxRT`v2C7~r19-rG!BEqbVo3&}?eoa#) z4Idb^%_gCg{!8Y7=-jzW57CaXh+63o9!$dYj}ZH#ta^n4B9yAJtuni4{78H=Gv?OM ztN9_g;kc0qfX3)3eDbc5(7XG-w%r;Bc?skxEWHBLUDjDbRw!sd%zqwIYKmUZX|^WZ;<@o9DD(9&EH& zojh|<)U&8iBtie+#~|Kh<*<8 zcF3QYMOHvrmxGN{ms*|bAnqLt{)P5a?qI2RC+OJM#1&%TDT(Zgv8OS+` zoy-izg&oCOWh(pXlUIru7nHY*yce>@5KNi^Kmj-1HmOnM*494dQaV#mf0#dSSZ{DG ziY&GNB|EKBpI+HO8!n%AhSq%LLKlP#6n#J3x!E{oWQ^xq`gNFNB4j^r$VN730I55c zm=<=Q9DoS~$z}aIy5H zXZ4`03D8})g9^Hh^)#`>s^j$HW3961D_n19)OG4VykauA9k%*8K=$Tzn~^HCjIEuy zyUD`p$jhj(S``{hiuB1-SpUw}l2`8;w7G#Z-@NcX!;SWq)kl(CX{NdF02u z?B9vZAMbhhNn~S>U;Zld{bOgrn%wT0jpRoi5yqj-tSm~&QLZ|FA$@RX^aDn>bS{$b zh{@4radM){o#0EL|L15p3dt#Z{OH}8V1qq72iVQlC#UVHqcv{9xJQULh_{E-rLoQm zQa%z&-jG!~Yh}0?*BP`t-cPR0am>IUBjMIBwrfh=Eql`X{;P`M0o@Tg<8wlxd+OxD zBFB2spO^|#$Fsbo!Cji=)Hvr_+ucWK*kLJP(`0z)^{8CnfuJ%=(y)&ONyb+!ga{d>e}zU1mFv8leb1mO5^dyD94qVX!QV?9_a&w0 zR0SAttw;N=GUb6==;=hpic%y#ntLXi7|4dV*iEPpEf~yelC1CY(jBcwLhDYqe*#%8 zZ?jcj6sTE#%?zm4^-tz15)+f-gHmQXci7b&YHupco}fx-+_qfLR-)A0>;IXP0==)R z!WH}=n~}u+s^tKwdHRMpftctDhV6$N4sc&faQbvgCam3O zqr0ZkeQ_)n5x3YvC;NrN-o0M00dCY|i(nzcm4W8%@EJS|u% ztNTD0?3f4mXVa$-ALlpM@n2Ydfg;?}HMU(NjIFl>bOR_2iJZ z(64ZAL^1zojQGz;Zf4mI67?r!AV~SMwGg*5Q)3aavYvg`zH$pNv9z%=r%aqI06X<_ z#ziG^7Cv_vs%L-6eq)_zGj;TAQM-DeSTLnuzDh@{Ab4+BT|TfpAfJVXks0iHs<}B8 z4{yEHD7|!MvYuoXYy$r~5ev;yu%zubl4H}Mo|XtH@~ckG=<6eKZpSI2-U&3=v{p?Q zX@J2dT7P-5s^-Hr=euPwW-Ph!OXF;?977c+qMBYLpN-Fa7$O6*_{lG!6d)wM=8I4< zZs*N0M$H*AMHM~sFnP0a8d^p5^xh55nZiMzTG`;`(m`TYH>AX*h3xLd`qs=xB(L9` z*DLl-vVHu%1_!rFPd-cW}OklWOhwD4^z?3%3TwO=NG z>0+Fq1+(TL*U;UYMN|{==M8TkU&}sPs^~kGqG+7BRK9|KW>2%3+xYK>wdVtx*@pcD z>%%PeWjV!AUkg=y`2oWzKj`0Xxmf$@HEg33!j&2hStOY3L9KuHE3im% zH=nc2DrkfPN!WpBE*Q}Rxj(H%`BzHHmgZVOeA5Y0A1T1VrsXr2!w;bygSz2z6>;?1@!^WqC_?7^>qo$l5M-&DPAH7JEPVYQC$dUxe^IIHIzXEqg*OB{+%l4# z^REQXK#x4%mTFlu7dUr>wG7?O(u#@bV0^ZC6rE}XX*oL{ksg=95TiL_zCuNwR@v7B z=A)k?YYVyo0$rCYCKJ_TH<$@W$Q^q!bnMI>UBGJBr_}2WvYyE9N%|Nx`U7YApi(!$ zaK0EB(=u5AO{tQ=h8L17QLK=EzrNX*v{*dc?)n{&QY)`ZAZSPDpf2_9JLCiXp}|-U zzmMbGM-1K)V^%>fZ0O~Ff&gjoF;|(;)e)al~lir;dHv>aRyeX15`h z-@5W}_?mg$9rZ&Jn4-@jabTjeeGgmW0hCr#6|hk&;?@I!Ztjc8LT+vjaBJl4sYvEr z)lrC`u)Z^x`hI+$S(W5O0Xos?b|_4j6pJTa#T$l z3Ard=c8AKXwQqgC-(wenSg&W~qCo5I!huEAjU`p{Xam;?#azIEG!4bK)gcrMYbE{6 z?tc@4_W%iZ_A*`UVucpJ=jbP%0v13qhVzB);mHE)wfu@_Gkz z*OOeh(c@fjI&~QBoEu+aypb|Lo(aU$=DoIsqJX)s2-hjhe6JpTB{mHMyLuGA+zreY za9hU@G<-=eo@r~;V`Po#Zr-yw@#?G=we;vI)d?b|e}rhQ^Q1kTDIT-EbC$uuUGRa? z9k4TXYSe40gCE>cKrB5iOK%hem*~$Konrgx6lB66kaQ@adiwwbst)mUt6qM~Zn)JO zq!&mo>Awq7cqeBd12xAT0AkcaHoqa_4@=KRxQGPzvDl0Kv4q*u=B}OiuAQS$(C4ju zK3qz=mAtS9qmVx#L5mN(e}F{n4F$Imc_7r);6DtiiL-m{*-D}a;Y7SBzxUAF4#^jy zXOG5OuxW zHRa(gPp}l#imdy@y=dre2VR@nCwxUeQ?l`mJTk6lb1=kp6leZH9q;2%zzCq7uh{r4 zBR46~tr+ASZ-4@=)6;1XY7=Ytr}!dL5J(RnYJMf6k8t+fCaHqRqX}CPanH{gn%zaF zmEB^8{Uc~qdw1mE=luycHm1?u6jNZw5B7fV{9_bo%wBz$4vnFqusH*Az}JXMi2D~{ zi&7BJwui;9kz@z+xUNjm`}Nva^#8lM?6jSC*Vh=9t{05f{mXY6>AyUZBu|_8&i
CZ+cVZy}#%qD>)VwNKRyN2oDmqTCKVC3!8!w_~ps z#g8x?Q|LI-2do->n7fe~TR4+K=aHu^3W}Afo(Jb1GWta}JMVz^EcrpM8qVh;jen)* zyedQ(s>6=&>BhG6-|;K{_B>Fiv7bSEMqL-R5Egnfgdmkwj@MmG6EFX$-Ms`EayE0$ z7d`tfXWD!ALSV!62Yey03xxDhyV8bR1RIYQS+{4rGPl_6Zcn_7#>?Ax2EZV%&#h7| zQqvoxxeYP=_(LebdK==!Rp-v?N#_od@P*~+RoxXFr2rG<|G4sXx6Ha%2#`4G zmJ)(rM?RL7&fRe&9qrS?3zWE!E7Q+=A+;;HpOE#hNiJs;`2P>MKa zw2}PeroZMV=Tk%a#BqQ&5||K{tAMsb94Y&H` zpUzpwBZ%gSSiuU-oX`QJ??5=4ZZNnsiocx?R$gH;ypuww+LDSVduU@I|7eGPt!o_#C`J8vw->QC$_PO3T3mbB zd#PpY*}XkNFyC(AZ$;%FntmO@()w5z0#~uaRMy8SW{Uet=2d5a|Ef#D&45c9%>78M zb8SOEc4X7K9g!e0n$>Z?l6jZCMzW3CY?FWCE~X3-a{&mH$`33TZy0r_i5#hESwcG; z?pInqrb30W{jriN`LW0XijC1jsbEz+xS!yScq%U3to1SA%*h9QL)dLrfALMaOk)?< zD}N();x`3PRdt!+AmN6g0CqOEBoBKOQ*P@d!tHo|iuI05-+&v|EtUzi9Oc#qz#EZL z`fSOsQZU$ipP!4(?U$-Rga=zq`%_`8KR;Nl*%=p2O?0g;_!w0E>V1Cz5^~oCz1^kb zBu_-1M`S}H|FNvl8WKsM(L-Lw)JTKQsX7+un>`>SbyiV zCJMLXw38+0j5W0A@BJm%Cu(8_5^9r*p@wT*so3x~-JmSoaOpA$hy{kFyK7o=$wH~$ z$h{0HBLPF4aT8vq#K8vc^a6;Q1<0~mq$!oYJj@Qd>|}#(VW^10nJZW+tVt!)U)5C) zvd>0Xg#Xs0vewsdc_(*+)vFOq)E+WDdu3U835ULB7H%7Y~?!X6}ZUgS9FpdhCpZj&wY*;%n=h(iUN^}X1=Pv z%hW^hK8Je<*l!JrgPqRH9a?*Dd%~Bu2P4sQ&)%2N+o+*sU+;#7O2Rl@o><5A zVja9PQvTIi!!^QIc-jK=DJdG|;9hevSGU;5mwr_w*Ks&l98U_W12pmWBIuW%F^T+{ z=}aZ3#Q;+~U2cWyE zi*NOSZ4bNymYO1{D6+qJaq-mQcgU&`kS%WdnKNac66X;0sVtkr0H!!u@8hFV{hAk~ zNX9H5DSuVWTOC zP9nUo9?fqA!7Af0A{A~9`z4Pz=bVre2BG*GN(YwtOsl^s8Lg>-u#9%Gf6k|q9KNGf zfV!0Ivo=v~3>t(`Jl-A#QH%xKd!-@=Qd&=BzXKuyR-*lRAoXx!d!(2TJde}<%*&Zz zNK<9zA)5G}^(dkZ)$IgS$B3++y-0L63*WTPUU3?GTB_LwTIYpZC$Y8qZ%!-7Q~<^( zo2;!M=O?Nvf1H0zeJ`px=Kad`HVW?K4%%b}WIaWSAuf>5`%k-UJ>Go0QjsgM-Sb-` zk`pau8*f`6NT$jH4VRw#+3^*9xjPV{I}BFJUvKdw zwx@I#lXqWY&x0_;<>T(`=306uSosf!Lx*lDl*k#+TuM1M0I^aRV$K_or(NzkQ1r5Y z)0wMMrML^D3qF!DzDG4^$w&~Q$Yu8x59#xS(|ruA(MMCgt0_NF81n`!KtAF}2bt6@ z-)^U{UKFKLK*V^jSI7Z`=gcu$^(7X1Df573iy-WEw?p-A1y`ml3IE+Q%r6W~-}q9u zl4?G{k-}}GHc57Ny>!s9gQDV)&M3n^ZSG@euk+EAIDth1_Qe7!wk4hC=S(iLc@13m zn?p1IQSo0x*>f7UQXY-vpS4!1+Pl-vDSKv*=(}RS(b<7VkK%oZiyv@tU&sv4+W4pA zo7oSEBMqnAG67!Vu*CMUUbjEMXKq;!exD9&-DO%Ncm8p200sKZ7YR#n*{os!#k zq5L}&H)bL1a?Cq9?IzwLxP^=N|MfgP*pgD3hyho5>t}Bh=`IT zVj|f>C4`WKlRazMCHpptHe1NPRT9~k?8}i|)?{C^?@owgJI?QZA2ajm^O>gR`}=2R z{;1b$p7Va5d%5oGzOEr_<(!iy!StJR(iW;lBFS;tn;e{(rg*`4?i|^7l6o=3T(IJ3mtr#4y{+>J3@8bcBc6I?#Th#DQ}YrL~A1Ma&?zE2k;R9FI^?bdD(cT&)MG-^UnrtK$IBG7)L z^*(A^zunmqA{FHHRE;{z$YTi;$*8CxwtXa>uM&3!(>JIZ1P!SNA3&uvhuwYGX6_AV zO8*yU0xikmmf6tHue+|*`|>S!60Gi!-S7X|{{Jp-`8lzgOMWGt3$ynt?{i)LU9KSV z34*1}iod{$2mPu)K_k&Gl#TG3G>pCcZ3sj)`^;I(F6c7`TQq z^2XfiIqC0qE5J@Y~7v^2g?`D|6p}`?_Qg4LPZ4 zE75~XH_l(FI_~x05UK9S%7ZHMs^6stNcDev($^bEbMgMZkx3A4craEcK6V^+@=}t> z^*s_n_a)9Z=JI#-i4}Lv#ER8U2{@;lsNaOyO;3Dr+!UfT9v>DP=Gz5iXL5+xxjp8vn@GEQkM<-G z>>c{)sW+E#Ca0lZ0TkUg5*v%{S}4cUH~ZwWb*k@*_vVImWa(+=rb zuuFy$?sn&L`lu@wVS}QS7dvGL_NOrvY?(9GX==cTZENk}QP%UbE#*jzxEN~p zu(80`zY#RD_?YNbFT&rJwv+&)(S|(eZY^#&FR*E?66c<%yab{<7U!5ebL+jt28iVj zqHr;_WS2Z^k}us9!nf;^hN)mao2IjP+6nY0y21=#b07y9F29pduPLbrg5|i`aQ?)h z!WtTs!7b|!_*ql9$3bn^-PU0$33cVGT~Tb3tj?T_%iccskf?b0W1~_wpcKHH>;g5- zS#zZ6TzxO6^A)U8pU=;?r+C9GIQf$-3>(rrl0hwjQKT<{G<6YsPst)=sH5IjWI0a* zbfe`Y-4TY*9W8(?PaN9>rpE)0VZPluo{t_PDj(($(1J-_ib$VxXKoY+&};4vRDGCZ zO|Iew<$JDeN-3-{bu7h=^nljBL(>OnKtFD4F)Z(sN3_EXnxow(871}n63&qovNwY$ z4{k!9H2z_u%#uF7xi;H5jHw@e*KI7BxKp(OYqxI|8vEW^QgD`0N*$B(PzT@pLB&#y zIzY-rVnEh>SR)M>qX{o_w1dhSC!LhcJJ2Sq{4n zSg(ftjwDAI5!5mVfMJCbbJHiT6_wABR{2aYZhq>Rua$RoSLJ~m44P7wd=m2xmNN~!I*p*Q(DM`3^U<6LMc%7hYa$rmU zLxN_8b^f5e%kF(jBzIVE7Co>oJV4391IH@*Wq&a}u(-7!*EH@S9MAZT*Ap^MVP-sPr8Q>yeMy-6}!5AB>w=gS-$Du{j)tG{<>yF*Yq{gPhp*P$omGMbsMgXf()v|wi<8;hnkz!n@N~KTy1y86fAQ`-#jLGul6bK0wu}QNUdenHN!k z@<~)Mplv(XPFZi|2A#K%yie7@fM(O)igD8dC0r_K?_xf$bp^nTYq_1DaFRFn>2r(h zh%uUrt*WM;pV38mkM}%f=eT@yK|L5dc|4S6^E`EUNqA@QngcDP1hyAE)s=!2*vvf6 z!UH-2h0)I*kjg>Ss5$i%sva}!T<7cQ1>~rdBbvIf#Tb^6;SX=<5JWlN??t)Pl=7MS zcc-)0a92`eD@G)|8mi6L3=wB*`1k7=#2<)W-i45nPB%U6(3O{kQIFlqGG`f)g{MF$ z$?4O4)nvCAgR~oqTOb07KYtkTWb!!CtaYf5zpqE$S$CF~r!)O+D1FuxoFIvmF8rI* z96*g?#you!hPb@U^!?5}YXz(04ue@PNLWiN9dHrBme&}(!;Q*oeRMcixJFrvTMcdaVlglwG`9L#K4W0qcc0&h}WQBKncR&@Pw` zR()zQL2Bjj!Q!9*Lb&dYdTX#R)y?RA7U+5SOZ7H8jYzeY*&=_Wat%w}cE2F6oRO?x z>qx>76F61Z-f2_@_V>HAA7&phc29w33(v>*-t4tw2j_8`17XlGXg70URfs#a?hn+m zW!m$9VDK!DycqDk5KV;=JXGzIJxtqhkymRpJj1Ku%$+b>9#C;{7VeAzrj(TPno}xL z^*q96R8f$k8~8sp?F zRp)Bl3CWvSvEVo5rYmT2x1Q9yOhmJ%rt{-K?I@<9wN!2C722I|w3R2+NsEwPad4&n zO0Qy|5xvcG>9v-j8DM#47=&Kr`vvh8|jU+UudtYi6!4!5@05c{@4J3w`K zF5QXKtoPYYuJ^rD%H?)%r%Zqu!hg;I{zJ)2$(TbC$|i$5!MYAM7C-R&ae)B$WkXQp zGyZb?JMRYG`-%9xYBq_d-r>xtd&8Q9DONFCT}gqAjf!B-IG;hb_&Uy z>6S-Mi{ylsGxDCl*~Gjz)yG&mV${UaHTkyrMV>xz?rh zUu2gwvQ!)UF9(h~cDQ%rvndeD_<))U8V29V_wZvftXGH2 z=j#kxmd>x%yeRW=@Y_w+eX)T1#S^Xq65`H-7vk19p#l|b{cZ&+ua_GsFe1fA)&&)< z)dB^>L9$f0>dQ+bRK3mBcpBd^qOT~T6xDTil+4!vxPB(l&cA}pkA6cfa=%X1`!=|M zEcQb}LGAQyK^;ocDHP^H6x4I^(e2VxV6!JV3W6NJcKCtl%C}Y9Kh$besA7g(l1m=X zy-E5OQo>j+7Cbj8qBuy6>U!CbjRo?3gGziP;hsr5Bx>dmvcJ_4Q_@sPsrOl=clOy! zV&I0KEF7<`R_eS;Ofj@{EBB5AB8Ei=In@QuGuGHWK!F}8ew zgZzy&*+HiJlo*zp$K}38@GU~2c^C};2!$r{;429l_ z>zy!Dm}*JOlV)GDY6o#?A)q=%QZKhVWJBO4Qh0W5W-nm=s0x;0Bc`2}USO)a0(t}Z zG5r)p=_d!Dm&ofd4F-o7x3_d7eyy zzdG%_Ku5muVb*B%!h3A7%-7xj#=3)3) z=T7CV5)RTENuN>{Nocf_O;nb*z@mxUYlC0I4_50@+g~gZ_UG(|+!iMOIG$*U|HN16Fn{!`X5V z=F8x!Z3gLULFdMJrQ0o+(AbE|sM#1H&!$tg@x}OLI~^+V8T;9>qVe`H4|wO%Ev-tn zV-Vo3&4~K@c+^~vbuXT3gd67?!x^;vYE~;B2UVU3Xkq-Uwb6uasStIy+PeQMUVz*& zjk6WfCb@c9t=(M!*Wx!4ls0>{-27W}kfrHR4yA98Dya@S)=YC&IK_Nxy!Nuh+haKGySTszKp zhh~Ab(;K(bS^xbkjPmzY>L?d4MS5v<1-NgXB<{555q2>U{@8U%ujy!{z4;dZiKCC? zB%lIgeq1H+M){Nh()Nf0>i@I0Cj}aX^HdAg`_R05yLwkXFdERm+-jjlEi>?>K->S{ zAl92&_X;D*D`sbp6Uv59|0x@yl;fxui4=v5JIIQLMUDe<6?C>Mk&b9~|WUYk!t5Q@jzKo5|yFrzAX0>#?Y;YB#|t@C(+U9;LYckcw`&%PtM<5f4(qV54JIIZq7_-ls>~`RQ+(;~tzMDf z&2tsQ2zEAIIjXv6h-Q;TTix6Vr&!QQ`}7zIa4Dq`T%4IT_j_;9C5%Yrs`}&;zK6{l zg{JJW>aEzZRn{^hV1xF0>>hE6X#dUI|Q;>B|kw^6rg4wyr+T`?Pq;e}tzWHvgT(}`r3|uIP3L01S2!NjY z&cE-ekpz17Ue&8F!nq_fYult@XQ&6Uu)^H?h{k{*k#W}CQWL2HdZSrVijsGdr}4*; zWjWH+ELNdhS1MinDUx%sW9AWL-(|hHetj@QQnKt+gz`7o zv}&k{rT~)D?`~3|_)-7Rf(ph*Q@eXkwxxmku~l)YS`F{@IO~3^B1y`g8+{Vqf?f@r z_v!})jzJUlWQ7ZW%)z6Rgm(LXh73HXJ?%n>Zlgsr0-lm|s`6wW&FpkxTjbHXtZ?u^ zy$_AHwdFpd+4eD)h~_#N41^ePs*=Kpam-%?xqOWOSn?c!3eh$f9jt0>#vC*c0Pnok zaWIaMYcuZzW)av_02fB#oergEZZq37^DrN&`r-ou$eYLb2ik^&1zF$QWbtJS?Q|(P z0a_k0lI_=sG6#DN0Dhac<=^Xrf*_YW-hcTT)fKQc0%f94&;Iq}v2l{bQqT!4&DV~7 zsCt)steV zh+iaWRwBny&Tmmk(b>TaHqR1w9=-oLxt=vMy=b>H;8`68qOb3AXHwt>JfD}JvJ;a; zJ$Kv>kud#VB+f`8vp$hwk@}P}gVZzs$8iEYmZmFrFPC&5HdW$$LBk{2<*0xNgIw~- ziUr+DoRc1cNZs~G_jU3n6l`Zq6w$V_FhJ1nxOOyc=-{kx&@-llbYBkeUhh}tXiky5 zd&)^Uor4DVMV;*^C>|Gvv6b}70a7;`v@Z#mVxC8j>W;}L$20ZTN|dGWjGK~&&Z zsBliTvt$b$@@HNSu@*itf43P(_KLi2QeL0zIbu7oeJ&W)M|k>kMlBTTKEk;uZ?bmb{yB@iLW&AfpE=pta2MsRH6^e z${8X&ndazBYj#3EO2(h;PF@JMCW|@lCes*wYT(VpysT!^hv@+A{d%A5n2@!b!Bi;r ziHF<~)9TPOb%7bs&!V*^>_BN!YNs0%jIiqVV?kIIuTs^+~Ro8sq;J$rSu-`Jt7`06Gc7Zp zb!P*ZTl$QFT|`6CZwDp-A^*R?T+Qoxejb#cGaNsl$)2$)8b5zgQ1UC$>|OD~I55JY znG**=xhUo4y)cV&{@yH(@OW%5_o;+$tv}?JyQ5>0d+uL1J&gxZ2Gka+ZIesIbJ({b zuqHU)l~ERd{J7MTzHTqBrkZR}(p~)-S7r@5AB82sy2s2O@rKuWdyX0~-l`vCyr`iUE9JK;sm{*U(Mvif-R+#lVEZYmC4`sKAZx+A~ zCjSFe&(7?0j{lo}yX^=y@2}p=H_5ZPuRNq!jJyQvx88IHV!I$*FGIKyd@*%yX8^eh z>$QYQ5R#kx&b+cv{t(wSQb9F**Ox(gP#Bmnvu{^{&}K^8oMB~j@vb&tz_p$6e*lls zP2kOe*`z~HCQ=2^kHT)vR1XuEfK0v563%ZNdm{^_p=b0_`%Nt}g=bG;g=BfJ`Nvb# zLa4ODDpi-nocECO8H7_i0~OoZ+|3BWMp>B%%o_~gR+i1uz!+;&A&4+GDM7yL4t5&# z5yiH3fB4TS>iqLgI^Y}Uu6}vL0r@KS#i4V61B=MqvWL`!e7YRk_ubwhNbTyUkS@c+ zA)|MCp7i13{r+S=G9|r`O<_WPpv}4MB!9355HLrbH5d7Vw-cP6U#En^2*!y&EsU6; z&RaN=PUR%<%-UbzA0brH6>BGuE-K{8D9H}~9e*AF`2l5-*lKs>e9>(B^5S;b&8;3* zDj12+{u-R=4Vc20ox9j6WH4H7;h~0Rb*->LPg95)eiEY38sqkAV7Feojrc=)-(J(( z1^*_|+drR|%__W7ayuzON=t4h^gn-o0F_wgcu?K~D*6etnS<42X>WrJg;<=F5;g!_N0!I$tAgDX1}#PE+c zpEb>hS$JWAlBK1m<@aC;HIr!tP5fO}c~ zMhaN7CvgTRM0%Cmeu8-l`YR^+RQE{3Mw=c4H3RYPx?pV~JrEUzCZnt2d$up@D^d#O z$-Y2>Xzv^*8N2@=s*f&9&hh@O1qm~rk4mv1jBX?2C-i`#DRxY%FxE@15KmqYz43%p z0lkhOq!!D}%xsWI>m&W~=$I1R6U%ZoQx0#?@3vcLl!naa&H{B4jP$;(n_|G?6TIRF zKxRSB0oe3~x?9z{_b{%Lq60vKZDm~oYH4N6y*AkeF^p4yOHYH&IlL>(g<`F8hP4PI znjVO?e}S560>|7x$QAg%BzrQv)~{Y+#PfdTJUA$bZN}Pm?M)T_S|i*^_#H-s1~lSw zp6~Sdnw*}w&p8f3-5eD!tbUyRR1m#wQRZ6r+T`hRERisgS+f)U5P6&<($XR7oGJSgvt>u3c)Q?h{Q5Od z0lMAl>)JX&8m_vWmtxxO!1a(bsJZ&pNNXZ-F#Wjm^|S+cOV)8Tn=};5&6yN~ z;$;^zNJ#NR&5S!Ci+pVboo|oa!8YQZY%P|uuiUGlb(f9`+|DFE>s%UA=Q@wRR0(NJ`m>Vw8wbhc&hQeflh`AqcN6?F z`oekeAL-W|T%vPWZW3H3?mV(g0Ip7O|3RfdT3N$emtpvre&^uDaBGIC<-g@v!#hqN z-6t({Z|y`ZEm%*^6Z11lI&|CbO0=?CpaMu!8cUs5QW>jT+gImvhPn{DIN~^j4~6G{ z`n=Ii|JYKf!&jZ}{~R~P0tErnux+Xq=wo+sN|l{|CW{Y-%k?lO$KUSsz$fh|&peYk?AL8g)f@$eTF1oS2lk+?KxQ$L3y?J@l z5*sL%Qh!`54S@YRI%<<^dK0HLnVhH+A|Q>^0p=!*^u8VLY2GdPO18|h*ma&ZRp{n#ydua~^J#?g2HWv|V80Nn?;KQh4mVei5SA>E>eOqxnT3GDp# zj~>Aa*C}+ zS6m(&egS!b0t*W>Ly6F!IIPmpgOH@U1TT9!tBx1a^Cznq)U`x=l}GY(+`DoWjqr*8 zO`qrkkQ4fvntpTF%Od5Fe=d?VoeQ=$(Rde!k5cr7=*?oZEh31^cO|WMhikU!_f57; z^?yuXRcU9s$GF0XwdwC8z=TPt+~0TpQMosr_7DJ8EH{a%hmtNy*4mNU(0)gvl&f6^ zoP3D^V^R^Z+{rZf#+CIj)OE-eLjqr&+Gbyw8GDFAX=Tro((eNnL_0!~y#|)OF`6M5bQszdmcT z!`N^Kld?Y;8-i>NY+Ds=f0ep?0`#>YN!(sCjVQ8loP5{>1C3_o@PW*1)|<{cXGM4U z>Y#Qa=<$YwDBIT;T+Z5SDRaZdZvX@oel|Lkt)bM?tE)W9D%ugSbHXfqRN5Y(v02jlW79 zfGqB}=Hh0Ju)1x)4qh#K^7FI+dq*wq!)6Pkni8Lcl)D_h)a;rIr)A}DR!*{D%}jn7 zbMSvcrZbQ`6{463@2v3Xf4*7#TbK$&Y}rlni02K64rlxA+bn{-Zcjb3j0lBatr~QJ znE>2OmzaDvDFUG3VtX2t8QA&#FynN40a%*4G$?STMRiGEM`DACxnWUTNnG(DN@W&X zXk2p^KKZ$bRA;aVHQ)1NE-o{1XVmsO1vVhA@QqDSI%ddkcegUz1>@A=Yfj)Ke&0^# zfTx}RB@2+&B%eb1U1|%EgwZmcA;ou%`aJkF(IHxHVk^n5J6i5V~CPnE)77`-)_zZF+W=l8-gMypi z4hs6nQsdTYJ??h7uD_`vJ>J#JSlwl~2Sy(s|33N%J;DR3a`=vQUH=lWlCnnx>-fJP zQr?_9ro&Cy#d|Q7G|cnlADzjWPOz}Zm7oMHIy4p-@5GurW6)fI{H=~Lkk%fmPE&qj zl&`gZW@Q^%nI{6Zi65Rd?OPEWs}`a3bFgVCa$mSh+?n3Xh|T8_fU%q%j6;7mfG_(Z z8CKMyg+nt|%Qvm~9abH@Xnf<>tt&uuK_;Nz;%o90h^r@V?hyu5obG~4LY&K|sKK*r zc0+F1LPQ-%Y&9#OiB)~#k0AOdVHe?1yb(I4)4C7KN}UNOKJlFsN5hGUT>dz*AbJB( zjrM8G>oJZ)HTeFuaO~6aNW3i#o}{k7@rq6(MmBCAr-TD1QOZ}>DO=uI5!f!(nfz%N zy*{6J9@7#O6+D)4ujpXC?*^C}A!O=r2XXmT)=r>dQHZGC4uG7HEnkaMvu%H8nx+Xx z>HOkl2Rsg2?6LO9!y0_WyIl7lZuUk(Pc-?rHFq-GyW?sV<2OvIOf#Ux$lXeGvQm=y-;7W=s-?;@`-l1UegClXpT}K?=i7s~Vnu(o- zD?FQhZRqI@Ltu{WmHv2aZ|W<>KhWYgMDGg<24La|gZ?N&t0HlxbE5Bu04z*Q` zQ+ljPIgU0P#@g+ zz%KvwfzRs)Rz=blK&*|WPALYYx+5!YCIW7u15kbbxAdOn%9JDXT)onsaXSPHvRIhv zXAW7J;hV(TOC!&CUbE1e;EWj189=A&4&xb0R0$J|C)-3f&eRZU(H(l(f7PNI1^p#XIh&vNNC>$Q&CcrL zo%6xaun>{U=Z_FL@7XcB5i_*TobR@2?@&oDXxPeyX$_(~o=}VoXYPs3z-rFWq~k5F z{>9eM3I+R#|6bE&zbmbaXgqu@1X( zTUARqG#Gv=gW@5cH|0)5(~WdkfYC|(X{}l~zgC=?vGpN7z}m{WGG$!xQUb%S&O<94 z;5GTb1#5zLgCMLEH{j3hE8 zjM(!Zy1HTB=+)VjBa2&=1F{@tZMd&W_;-!6Nqig^jHBbP^7^X$^SNPJMqq>8=gH(;X~{)dqmJF|i2V^P~AQ@uP{C zPk&f-Bk3%=G?$Die!k2G14tNs{um|+L^GQl)3y1e5;v!Voe3-A5SxZ3ZvF9LK)=md zsfWN%#Q&WdIAuPR9Ebj7U#F8Yai{RpuYT~dK{RM?aB~n_q~x*jY2le9MZ~TrBx-n; z(s+N74`N@+cQ1hYi{c}-FVuwkA_|Oc{wkj27^!)a9=T|~Ydt8Q0ZWM~XS)~Vp&sPr ztRaDh-_vVA9VsxzrHYy3YC;Ie=X_Hk7+!KePphQeKT3i=lb{Xe1#!VbEN{jtq)blm z0_hHow!*`Yld>fo%E9mV6so2Tub)*-V^*~cgX-r;PiNRkY)rb58!Oa=$1Ol{j+iB;P$i#yM! zKx5bTB?hyHk;6d73Vzj6WxsP&o~m@YKMLzhd3~K9wy>Y+x0hZvrU=18bKRTv}3A1kJWh-sn)6t)vVU&CYI9d{&4(3Dl+b9iSb=BB}$W%+X zScowJ{?c)C+%41*-inL%PuY(Tt!mc?)b}xLgJ=s6ELFUVk;$&&A;EZy|o<_Ex43xjS}zR73Rh`8n>YeaOt0F?dum>oZRTB32Qv#i;JERP7~3WU?YP|>6@Y6~*eZTCL9QldR@ zzu*7;e$PIG`s`QHKSCUTMn%Z$eW?br(Zd^R>x{hHryFR4fL$Fa!%v5*ylY443^eylY+kI!uMYk#DQ*JDSL(FgKZUM*mSJ?$z zVST~c-VK<)^Z$M3)9caJg~ZK_?gt1WJ#9CoqIA~Soa=4JoU(jMwkEZY-R+`98SE-8a^&^M zy|Evr3A;%}VXBl}nh8@F5pDhS_i48LU7 z4HNiV{Ts+QGOYaz($@B@2tzYOnLuJ7M;3<2V)TJ%4t@W8%>ovU$1Q+DkPYaUuGc8$ z?ZEl<-@^Hwx4bCl|KeHp`8_DcgQ<&TRa7keKf2u4?~VrFWhU<)@|}pCLmpSRGpm|c zC^`TKcX?MT8dQ9YSWP(8K=moTWx@ovlT9jxWi$sJoHtiqZ(hWG^s2cm5KKZ|bE<$W z;zNTZgvK*_l>cG+ml;wogc{F}%q{-diF<8T>*3U({usXm$hJt=bGABP&UX*}K&!GQ z4Wmq;E3*JyIa)goc*4NL`|XXFwG&cTBl@SHwwrECdH&1qF3q;Fqy9o8d$E0JT%RRe zX7kcz#3lxbQtS8!!!5shBFXxHpDjxt-QcMA)e58aK=m|3n&clYtOn*WdswZ?6V;7R055r)cU`kD2Q%EPn(t zV+gFErHkLh=viniU9ni*5EN^U~W1wiE=j*0+1DR;;MKEFx}RA^#pe}*iV26&*r zfaZR`zEG`{^>OMXyt8DR1($gnnPOU9T=p;te)Gzb{<(@VqQy(D0_aVB_#5d4!MqQ5 zJ43fR?`QhX6J9{lj{xG29>u3~cs^W!@kAj7gRC*rrPK3=;Fr*O3t>y;NkV{(o`Ol} zU1A^vrrn-vuiU9yz<#>G1nfr^+EtY75HZ-8Fd^}kw@QW3uT)xsV37l1`~?!@$-Oab znVr^+LkI*UBEvUyK`$m=kIfUZ0#T{}BO|Zzh9;$to>zlFIRzVJCkXG+P zNb27Lco!4<2Y5H%R4N6Nm`mM_7erW(huZb#pRcDOr#T zOfo)^^*GRw{Vm$Lz!m!HF>w%zFNUjL2>QgS(j(xU?T{E_9|`e%vmbH$a;RZ2X_SCf zzW5{p`lV6H=K}Myze>1HyUR>dVtZI-hFn%P`$6~j+$Px}5GbuH8W}F51%&4WkwF3Q zRwPIPaZnV4A<)-%>4Y77Q>%s3G$^P0!~QzeL^02)3e91N#S@>il_P|aUGb@|8}H8* z_uIVb7TL}RNxqO-@_d*6Z@EQK&xt(zSv~i)&!4|o!t~}g5H@PkEq&))xuwsYO zS#3+uZ?cC@$~RdPsb|&R&UJrVzRaFKrbE2U9lQSZ!2mC=;so~H1CQpTnd!@OSBjB` zspAWOnKqml@daABevI{IqK>;;^r(%7NrRtJkrGB7C{lcs}(TBxChBi!B1b4S>BRRD!2+H{k@5U+4 zFC0{RVf9*oD$osz-SHkZ06+cYHp|v{&DWLP%9f!XUVh#yZ~XjNVF3lvto}KgIH0;* z)6xMw4B@zbC18f_RTR?#Ik?h=I<|m&I@iP&t7zdixA7LT`3t=Yd90h{Q7bw)EDkVE z3n4Uw?}UcQk)dzUV>anIRw~{rdwAT4JPtL?ZXh53zgM$>12N*rtQo-nM`zb_4roYJ zl6ttt5*vfe&!nlg{j!Jmrpgwa;1_D1yLikBMoGe-t@!p{aW*pkPR#MJr(fVnD>8U4$W7T8=^TY-%ZD2s*-fP<7X3la)uy4Ndf z;988H6HWHAo{md)2I0RV5WX#+2bJ;#QE(5rehe{PK&GcA@YiOOzWeRZ?X4oyAErHy zRQo#=z+3oZa0Ptox_f}1lOMt`?* z5fr9rDpuT05FxP#!u(%U ztTV3^KgYA68*!Bq?s;X)fey1JsG;BA`~M0p-LEwE_dqg!{ujf~21sc*Cbj$Y=@FWp zZLc?m;7VBW20en*2PIdMnjUauQfvx8iDTl97)SXsb<#eGr^5-pRnY5*-c5terVs#- z-VPwf9|O*}hy2mA8_Jv!dtgB|rCoYT@cTCg#b+7z6eB{6 z^Y1<>E`Tt3l=g+b0$`B8cCopU0k#%t!@n(p@l+l;GC%mI^|srVwfIw>EP+LqQ0b4I zDty#rk z>TBd-fWBQQfOu)f_KbjhMfPA*Din;*i<8@#?73aSi)UAzq%t4JIPQ`WM${l-ypQ$gCmTl%!j+ zOLr|zMiw0ef7YX9Wigv5Kq>H&apk~=DxdAK9XFnQ?A!t~=7%*1O z{?kqzHQNkvZ-r4G@18AXNso)yB-k)=K!MV@L|L@8m3W>((r0EnnaNAzXA*yuF~ux}As`-K3{LnYi;eV>bH))WY4 zv!(^SqVV5*BGYjQBmP6Z?=+5U{V{>3T=buHW`kP$Xq&CUXkTQnm%A|0!cRF{JU1F9 zKQSc#J>dG$!C;fjF-wFgq4YL$b7hJJq>8*vgT)yt)M@(!cLf5duu_(~S-kV*dbAFr zB&-(``_u9V#L-uXGnr40cvnVCRSNgBL*A7C%)NH9*`m$KLRm-4T6j*4wROryN^ig@ zztmJIpmUo+wV+gA4nCY2`%gcdf#^1wmb;arG&mpdh4urN@^z068AMl~c33Lr4Dy+U zoMOy|WYu4#zNf5#5N@g-i+CCh^XZ%Mk(Usa>*KRGNl|m^;u!-UM)yCNX@6i-TYYNQ`~0ja8u_hTEqX) zr5C5e;%rwrb2u`$aYnkS^;j4M>}_B|%*T|o_YtKWSD5_Kn0Z*M&ta(F_d&Ua2{+Ea z@ub4Lo3I{JfB7!--p89(H4p~c>(yhK#?Ssi&cRaJH;Hy?U)Z8bSjERHsh(BNK&VMK z8M0k~F5}UlP%S~5#{U!MZFIs8b-t6tbEOQA-Q}>o2XE=_xmVBjKn^)V0yl#qGR^Mt zr1MBzC3K4mBW2AU88WJXU;?}Phf8#Vx8J2n$&NvFOkTsNscq)VIH{E%30Dx*NxvOV z{eubuL4Bf?Ln{wAQm%ecKP^Wq5vYx`?G_Or2m^`iCU93_O(v(|Q;POZ{Kwxf-}tDc zHNK7Uz%6VMvD4K}RPXC-g7PPx&57w#yz zM2fC<8w`MXTrVXmvx|337v{_hNcRt=UXDv=PVBg%&@hNaZ*S%wSwz^~==CVH4VZ)a z6a!*4(6T+(QiPaEE`U9aUmxf+GuE09l?}K}NwS#EQHsVcJx?q^%&IA^M0E+`GBNW< z+%8a|hPGojqC@C@kwKpsrmZ1+5{cgj%r1@P5!W|Ie|s}l{Vv7i-agNQuI=tPm$qFC zLuH#dCx)iDrghnF6u61m9gPfe`@Q^>&)}aI#6m6?LF%%{5U%PGY(Z_I3AhO?fVpld zJZCqR4~@0kAWeL4+hj#|dtA34haJKoBbap)H$j98J}=L00WwrOytEjz&2+8^3+MwH z8@FqpF>K~AiqIhH7w)x3Ggn8S^Y4R)tb+w4ZNQh#pH++Ja!x1CxP}o^Y)1Kvy40pS{f+>2LlFXU$8~6rt^p~~309V5kIck)fNX@RZ z{z1J6v1uXHlB7zG_cyn(4v+cVU*4VVOj}S6aK5oZg+;s;aKkLyw=8s5nr=N}p4fV2 zG9*FZAeU*gSVhAmzHosnV2idtE+X#6-9U4ldn1rZ><=F@;rCmQilm=!i`)*WR_gP^ zT$v$Nwb35LvH=Vc@F^VjH;nH51w+iMG?~=#Hw#rFQtUbCx+%Q=s}>)fwJ!`E_=MU- zfY{vRnrdCaa>)+5Z2#q49Eb>f^R#=dbE`!D^4~z}v*w-cy|m;K7jN zUEh0Aevm+o4?F8D#p2|-lInmnf~}7>G9#`cfsdbRhHwH5FadhkS$#K4+Ug;^pklpy zxf5i z<08lFB{p*;Y&G-DBaAwIc*_d9rb|+>E@-UF!c0nrJ%NzZpgA}KvgNH2zZ}Ms)QgiK zv-5dLE;pDHiR84ib!zKbZ2EKI=s^iv#l)!B@n^J8Y97t3)cIz@Ok4%#zyI~gZo?diEsmB7C4M#jt4~>uiCnI^#cl# z+wPA&@Wnvdo--k9HtC_M{?It@aMPlBIkPGZ(ZVxstZy;7`4-t9`f{E==azGKKp+&Ok9;@&S2XGptVya$7e z%oXvyp1Fd_?{`z9_QcQH!AzU?>imPfVe?v@c2@d%$$6&R($zp1A zK^0_8c6(K9EV6$qcY`2>nCh^sn&BK$44&`<61Yzig{T>TqIc}ba(Hb)lx5M|Q2bUF#<5nke`tGtsA#!GVyJZFU>%tMov$XD5Hm4n5T$Y$=9$H-SXAD^2JA4!DkQ%x|#Cr5Gyzj6^T z4Lo2;|C4jtMV?ysJTc>r5;E;=;S>-qux@i3aEkh!S(4_ zdKg7v2n*-4w&RFz4CI-z$&v%q5)m~LyJ{s!YXcDTu$ev5m`lvO@y?vN8?_!DTOGPM zRR{2gC`59q#J*ZBkhw?7g#ALCR8`#LM z664hjhqY?^I0hK#l}E5@9`0XOKvogOJlQEE^%RKD>8$~xY=JNOz0*O1xN{dR|1cGw z0a2=_BwYUcvrdPI%#^M%RKmLd=M^CU7xuiClH42SQ>@1$DRz`>0)G|A?OE`|j=uRywWh^QguP7O4 zuTFZ=Dq8E}X4D73CmI&{XOenbS)fK)pm!gpkM`JT>MC2!T{mG_E8j!dVTc8f=%P1(pi{9;wlC)DBHr$k*J zZuy|s$dCb&5PI7VoF|$k+`!gHY;z7tjIO$Igk|4v-^BqGem!q~Aq{U}OWt7?Ale(V zHWSvdDhsaaA;)@j9yNA1OWox~x-ny*P@JHh2Be_v^6Ux#u;+sYsd<8}4@w9Tq-IjS zk(xmegX5J(C7JUrRr(q+4xGprn;vsSRDq7nzBD1!$^BC=bWZ|%{XswY5l$d920zMe zmj<6#I)~iaf@86y57OEH7ASR_6MN zsTS#`nAa;RCow&T;>yu(*iFlZgt)gcYtcDj5-X|a!UcnmLyX&q`hp)=!sA9LiCM4l zc*bqj$6ei^NV`}8l{8k`xP9u&NaQxJFx!Zf@BT%?Bh}8pOa65Br_{p)W(6=P{wufz5v64KR%uLX z&WI9sUKdSq&_&j36Hb|VH?+^P@mf-WNIQ;JB|v!M5O$OW-)%8i(o_01f!D5V5-jO@ z=IWE&(e#QEkTRQjKO>u79vg`sGh4KFNE~mBZJmkJ7)Fb(dDkLYX*tWiva0}i0sUzF zCb}5R!8>wDWYKuol#&<#$Epd!s1zv<7e;(|SBqV6q!90N>3M!-r+PdtLDv{s>60J~ zt41X?YtMzx|7sL9`Ivqy5M#0WB<23^#{uIMQQ$L(d9*4DsyIHGWwH1!iS&YzeF%HZ z-hO@CLE6f(^02Xz(Mkpw7TaU`fRrL#ePM4n>t{SoYztq9glk+{o8Dm}f-T%{z8BsS z&EhG4`2~-U@4UeJr!?|hDQP#eR7Ae+(K%w0T~g27NcEymp5#AC6!&14z%HWO)~t2< z($ZSbnm&>d8y(!Wi(c?&fkKm=xP}X_02eHey%WhF+C!EL?`gBeck@{<=XbIwCJbWchWxuSM#; zuyXK_KD+`hD9O<6UPBB+21==#OU@91|1(a)4u-bLU?{9uIw6p8XRd%L>AWXmb#~;e zj$JP2xTw@^SskrkRkw?K^nFgZkJSfvK-r&TB)aV|y}gN1hb*`Jq6u*t?ss>ogvXl* zxfJ^rsLH&i9jfZ8kO@;G&)x|N;TjWeb9mJUe>ualbVY3iTD8ka^nQSM zPiO&G<0lt4!DQ!JjN`}?+IgANb+{FDEr5VXhbtXv(wp=aR6wK&2uN2c3S7E$DT?$ay@N>g(xl6!z584< znZya2ufO+?$$XNTPrT=x=h_@*+Q?+?nO;oJkjBMjZ?p0%4zplpONeCG#mkE>qKDQ9p%-pJIrf~QH*=;G_+bR zH7i$5=RW@4wyMZmceK(c#NauF$M)A+`Q?d;t&3kTxGX$MP5#{W)gqCiraZ=NV}v0U zad9)oE`8phWq4{fFgz+a0o0iIydDGE+`2QV?et!5+fv6u-<*1R)xdNm@5zl*J(iI3 z6vH*0jAlQoXu0O{K>+N4_2IKMj|%rj5F@;TV||DxqU89SZ1>=Bgg==J7N;o|u2X6~ z8YjYS4W76GGk%~ZZyJ5`BluG06pcrk?4=*e@d3-gV(hUcDhZK6;hJ@VH9wI-@ujuq zrnA;*S=stwBN^_SCQRD_X5dz|UzkaXxq&-^>p-C8!`r29qo}ab zaqJ8D&dITB6e)s-ud#7zT3!klo`yQUp7{t&yA{>U3lmkraayCXM=PitvhzM$*mTa@ z(!8i_02^bf^8wEs&G7hu0WeMm|B1+~1ToZ(#)lNl9;jjKr|(X;Ap=~v*Mro0P0Lg^+a<&o zkJ?^ipZ2LjWrLRV!{eyp$lyo1W1>^ms5B9g(uc>l1M0(N^9Jnt_6r)(gg~KuqiDGb z{A;SsP#KB~FQOU1=pgiyDey_$(@$O~#VBRSYpwToS?@y}3)|tPq7jzWvInWlv3%j; z%j3J4u7WA%+0|ov$ZQaQ?zd$Y!D^ymY>O{>PT-kPt9JAq%TzX0&aEy003zw|%`EFg zjotXlQP;acZ3Y!98qb(XAxD@G)Kj{89T2f0IYDl~kC(bn{9WR{H%IL{5Z4|p5J49p z&ntl0M-g?)yORfb)O$lxur&mDk=N`&S*Td8IIjup6xbKW0;B34fUy9&C)Rm3*=->t z?iJMe5@uk?S=9tSymIu`HH^lAf-ABJV3CzkS4YSa{fwh{nmg2We-qNf*uwro3Mp8m z-rw#SsU1zY!PgWgthKobD42G>i|lcRueBk+DT6m{v9A;24fJwa=2ZQL|i+~ zNk!R2#sFQFdea1QS$o|oc&0a}Am&R&qjk$ywb`qaGmi{sAFS^-Z%1CfJJGSf-;D0z zLp~j&1K~i}ELF@doD$JC3$PtHk;u&`p?Qw=l<@OYGP44JU$sYHvhj-nGvg%e#)NPN zQX#)3SM-lzQqjAub@G;DWWd%fkTg8PP zCp6}q!VjH3zn-sG8|-n1Ri-6KH$C&+{+@xW;pS`2ai7fI@M+|R=-ZEl*&4V2N#glU5R1?)8)d33%WxTE?SO*GWSTbj1sw6I zQMhnU~#x9mF%5^2o08d>$&ky$*I z;<_LhQ(>2-^{;?l)FA7^;-lbDh<~i$o~n|3S|RBGjR1Iw8F!*@Az?}3!jMajDl9Uv z@YRKwjFuIGpOne%sFGs~z5;9GV9+Hizdqfjl9;xkH_{NnvrncZh$YE9yOx>!YE8n} zbMK>k4%|(^Ep^SUqA@wJG60kkV`%MFSkqp&e)P$jLgzGHV_1`rh(PxPg1k3_oS%-! z6%mIIxP76Zk764HUEbywRyuGtlcVZ8uBi50vGQ}Ov5KtmwWiyu18N|gzuGV;8e2K+ zVMpIOx-L%=6rk3Esq2;5)r*^5XKgU>XUHErEBBHV6axT zYp!@sC>K;OWL}5HESytW<4(Ad?Y>s8rQ8R7z_Y;X!3$HzgU#UHqY&FfYF&TTmI#QO zhZC`&4mXv<+Ltp20$h9KhZioi<;fey-c`JHZE)rws)Q_n?)Qd^hh!ed5TGxgC85U$ z7&%g#{~+rAb2d7FUJgnX`ah_*j;=}!#eKd<-+jKMcT9&;YfGj~2+$fC+KUr`<-G!n zDdIPfFZVQ~|Lr~ofrD4_yKnn?9K(VUC28#SMS$s33T-A*0^K)8$YVw;9wAG|3f#Mn zJ054vlZ;2q?J!`wD!ULXClpOytH^vzlr4Ar=B2U2%iv8dSF50awEl0~?m|h=yo{LN z-cLH7xK$y%alb|SK{pV;MAEYB&fMo3t4)W1QheyMQl2Y>GKL$sX=23COE`JrQ+F$h zP01E(R%bKp+!r~B<3v|U3~hYp-_rryy6VZE$)S0+%w=LfdsLn8k()--Q6M7h2$3R5 zg%ZCrlUD-1pHdKYMQ2{aodu>^r0Kvws#8X4_fKCj z=7gsdnsbO)Hvlw_Z#)Iz>a%p>{?OJx3fLCHS9bSG2Sr7V2OHo%Na-jtV_6 zgBL4-aKNME3(EAVQDp2l@T9$@PAZ4EhIavrM7_kW38*skvq}MxNP^+g;*DrH7_kIk zx15a7+UPS60gYvFWR>@3a4TrJ9D4`x@s;oyJtK3|wN^^=_B186a_oZ>GIxIkS0k6r|xSO%HXLN!3St&yB{?VbKd7YpHIlNUIIXQpNw7T z%<*!hr@e3TnB|M&+LQty0%`JV4racwTh_xp47{=2baRsfM*-l5bEYXcvwm@$+%K}h zcZO`HGl&f0ALT#9zX0ad-$%>UEJ~CR-1@#bt$D$7KH!SkXg!P;cHjEw8yu`6y!4!O zjD%5_&V6HE@&Vmih}QgLt=}#UKOkpzvpv~mRI@h*z%lRN7W)0bGAHxest^&{&g(E8 zmvsUW4_>P8;~_V0pcZkLfb*zq%FteqTrjd1L~KY?xIH1poiqVSJ9MrY$mx-cRn!%}#oH&v{PddnEo5d9wXZ%~W4mA1 zeBvST!uuG+1KAjgCr-iVUy&{YL8$Jtq}N^Q`r~EV?0Yb$>+2q6{<;+VW#14;*x}`F z3JF!cKOv*dF88qPeAXOjL0R`>TVaIM2vhg}Iq#S|!57A)f)+;GVUynV&MGv4%4u&F z>aMQV2e8CCTmg9{UE_HF^E58=R(d0h{I&qP)8p0Hz*}M|KQyoomV6PSvhN$%<7I&) z_F|+grz_3k+^EfSf>sENAZ1`q4WRD|pRPwoG056u(P%ktPf(Jyh(- zSy0ErD&53IpRJPCQR)@swx4&LI3OIhx#+n#-Xx#l+L#KHvlCI>x-ueFPhGBQ$CL|N zzim?BvQeaUv>L6uBBOk~g6QEB>oy}^CJrEG_ zytmGmoU;B(z;Cb~#VBzb2APNS&)&rI=qMj935JIuV&riO&r#Vu39Ab%Uft+tJGegPi#T)~%my{a!aX2{4;X2*59$WRpvY&6g_Jd`W|jjN+)w>8=FUgN+-2r?fP{vfE5zLu@npIGbSnrwU%rCrkQ&>pN70O8?O}8w)+Cr zg%Jf5)+I&9GQH9y5UI#V4ODq~8Vu5gFr2#>3Q8yyy!^&P_?<8M=|{Twvkz#%N8z~Q zwqEP!wo$hvrpA^5@b^da>jT3n?Q;--A^-6nDv z$g3XU4^dJ+m6qcVpm2qw9JUIL1GzqCj2s4FTSnIv11-Ru~gj zpjxx~mPcx897I)go`eQfMbzMcT3>o#64G2m!~Lroj-=1EfYpDcQPr#N^IY{A4cyRn zNG|ui7OX~XHx#$QA8(#^5cS_QXmp~zEtIS(8*Ba~)5%2h*AxhwED4%BIc;d=wJv|4brI_r0}x*}AM-n7<9 z*U<(g^0xp)Pdqem2{uxfO#b;{*kQI!VMCMK;nsWr;*y?|exC zCrTM!=+91+7M!T)LwuYDg-W-ex4e?-)TcO3l^W-0?*w+?X`phgUdj#hICW4BI10My zJ6{gT;nvuLU51f$`{=PQ4odqyLW`dvs>vzuBQ4^P?~%3E`_kpT5Tb8yH+RmNd&VNk zEKvyi{C)=*U{{kP$I7kjDApBZ{EDeWR~I5!=*MPJIiiw|S>sGg>EIO}36c-e8Q{>V zV}jiF)Z;u}X=YvGZMe|I^hfA|LCjVzNo_xujbzw!6KanR(HaZzTMg8TfGtz~Qymt- zH;U8fiG{zB=m6_x)xf@Ils|}J*V)y3$+NMhS7idGtQ^zCA)_75x0;0!xZCnS#IQBp zBhpEXnd6rV^Sbd&CMCeDPi4=O>_z!Wnr_3#uu|M?K?hN%4Gk~#`v#|2D6$ErC{|~D z%4xh!?AnE(5x@ClY8}9W)X!~62AsLM`rx)aS?g!DRyPU%M-Y^&8e@%zzk=KW2E5}w z@5=DjumxItBPA%CHa}oT3~tQDUY{jQpyHU3xaC@P9UXaX9roL1x}KRB;sUY!{|4eU z-5wCPNixeEOg^vk2{}i`-)Xmn^=^4@M7`}a9SGaDDXY8isa2a`+XE8 z8R~DeOR?bQ3?Dt74M6~$2`g_Q}Lg1c_sLd zyix?cdc_AV>xS%axFP(KgOv1w%WqJ3n_Pz=1{-+7O-UufGwF^@2&NoMsqxb> z>055O3ze9^f&?T+^_+M+C2jV|{FYn%&aS7~;3lNuMR0LwQPYDVHWYvbF8X)juV8Z} z2Ttd{r^n}X+ zMhxPP#jIw-GDH9ZEE`*YK0?$nrlQH;a%t2VbXvg2hjM!T(kQv5FG;T_JjtNzAo3)( z|LRF{ZG5&8L#A^Rv;E3x@(<}%{rC6(+q778h(q*t$#k74CY?#jpXmD9eX@~j&UyFB zdvorcx4Z;Km?A3z*UpfG$xZW>6|{34cng^DUodQ;eE#|i+>8unc&q}?N&TT_X}#y^ zqm>6;in;f~H4nY=^WZBA!B>f-@aU#!%m3R$P;mGP(HY(T)R|C4gU7lmq6BeF$%l7H zD3lPG|BJaYYY%Z%<4nI%`~zVqb$BlWGRl4}LvGdP;k<9vq^c%ckyoi1B+{H01nAEl za4AfstAS3~Rlf2dZKaM6w;|xOKV0 zAFGj}uC_J=LcBLTgTJt@@q~ z&geoo(JI3oqt8RE(y=BoEzPU?jKxqewnm znBhsmXU0q6bkq_Ud2txpf_qRvr?d z&j)2rK@N4K@b@ZLy~flJf)}J=52Q#P1gBFF5vNiBfE}4ltpM+_<$2*L@ho+?HH>UD zrRa-}k3?B903-ux8fu0>yrx)NsK!BCs8WNG57`L9og2e%S2gWeJ%wodTrXpVlei_{#i&HMZx1B(mRN;F@v0+FG%eWaz)rh3^{&12sr|$; zAB#bw8N9e@rArA3R)WtEl3Rntu@BUf=7afJ1uI_3pePbM>>pudl`HRW}bCG1I z&9A&I{J5J!-Z9(6g$r6yWpmT3KHzR{ter!=JQ&528IT^tPU8JZ2=hv#**88tEfo;9 zHZ*WEe|ofFB{cl%*v5=YOi5CE7!+R04;rZcYq?l4OQ80jbJ9+H=yh*Isq*=vmp^0P8Y)fWBH)aXytEI z!8DM%ldW$=AHbW!f22nNy-3*c9eWWX=tZ_iH;T^zlO(ca8BakP9-5kPuwCG#AR;oQboc>;{y$S9&?Oo}>5`K=H4D ze2FT70r1i231sFB)3b+fSLR&joQ=mqRXAL?aCa~WYWu&U{-vH$&fFSW?1xgB$;QEA z^FXx~4aBoe<9`4Io@Bd!%DfW{XoH*dv`@qFQd_YJ@QqLIxx{jKaai0%M`mc@#gtQV zCIqWS5Y+xz1t)z=JJ%*RdiB$u#hjNzK1gq%f1KyP9l`$~P+`TfR#nuPdqf>a*DB!t_o6123}}_4q`-o)2S-} z`X{xJ5?l{){?_tRV8=_Gy!NJn%xuB;&xD?B z-tEyb8uSk0Z}*uU>$@bt+19Q$6`oQt%wXz3o-vg1$Il4do>EKz|E%oL*QyKcK<+ex zXLO!(9^!wjB6^#B{Uws*Vu6G9SEy>z1dz+$MbqCT`)Gz(Z$sW*S83~3c~DLhmAU;D zSHfed7E6nH%nIcL)R&%6;VYL#HarzO!Pd}F^U=-TMJ z?DKjE7OpmF4#(`mGa(DL%V*5=8jIVhdyRZiuKFaoSRmuyh9r~1DTLf{)ZybUCWe}{ zQY@yb2O+T;$GNV^wT^?bHrI|{^pg7VtjJuFLVzlR#~u8TjyC4|j<#{&(u!VRW}K?H z_Hrt4XBo;;02xj_G-ct8M53QVKDxBtBOg*4a)KbH0Cwn z;#bpD8Sp!e-=yS0N|a=46AHC-oUf!bY&x@9i7;B1L;3-W4}B9<3Y!o%6AP(Yo027; zr7dU#B9vmQR99q>3QU0O?~~^btFWYD+{xb#r|VSk2oD4jY%aj5+@Wutx>Z(<{DIOH z8_v|`=?L3AEXSyXWJjmcdBQ^M%Oh8*j=H_pcgDt2hHDtvhaq_pppc*C#dZKw)}H7@ z@Hx|;hPYalMzT{Yl7u)Eq#lvGQb(a?`dnGvN;LQG=T`NJ^|>;w8Ia>caA$egdbYP- z_cr@5Y+XE)N871qnlB8)Ldn6U+96={ron7`EKC2bXE@6-a<^vT?KeotsH)?6q|QEJ ztozWxeLB>g%sz{ke_NS@DsDeY7@xJs+9BEVapyZuzUi zOtJ%rKcllEzFF|EoGAlta7ThfNIQ)QnrlVi(Qh?+Qc>=36_SD}`_Ox;HN`|GDurBz zVLW$BLzlDX#ZYD~)RJYA-Q-b>Zt@^~Q^35U;F;I~@yVBV-(a1dp7yg{URSk=f8%<0 zkN{2g%!vfhD#8z#Shx>u$9YsMsTY-y@x(|!f}sO;D=neTUPsSpt-0dVhl0~174xGy zLv@-)P20@*U8(46IvN~pi{{vuv?#Y%<^^lsg(o&QX|+=A2G(*5XH0(we%yzX9tgYa zKBq6Q(A;s`pC`W-7p};w!gv^+BZOw;k zo7Gpfmkp_O@sUCAX4N(AVFu$e z62^}FFjP|%*O6mK3DF@eGDkNU{9Mmq3DK?Npb(N&;yhVI5)P7gQyp)CgVpK1jFCN6-U zvQoXu77CBZP!NXs35FL5l1}xh)&Ui6jVGPAG>{LESi1h87q;&D53@%>DvV8TA>?h3 z@S4b-@rDRvZ+bgfEo^IecCi@8lx2@MVQmnls_q165@|4Tzt}+5cXl&oRh_*{&4VMx z?ftZ95M@>+b1v}K%#`MA0p#}u6&oV1;q+=6?=DbRyntyDXHY_BZ>okdwpGKyg<>*z z3;M5swWh!h3tJduLu=yB-N4Joa3#1O#?HP$Xsj~BZ8=r4^x{ePKbU1M_Cz6HBKkti z*3Nwn4)Z+$}fwJyX z7so5HuOmN$=<0!q6mjV0CE45{$7K2;l$(ES+7)0mMV<0fy-$ycsWUYU5BAjj2pAnp zM{1s631sJ3x-o*M`eGDt>l9qK7UNXJ>206zZG5Tlca2xZ^@|E%-1*lEeuRd@TLSI6 zZdrx4D*$xJlC4_*B%t%GG2e|E{M{$I=jPPsra&It9jd&WFvw04JpoTDM?C}+CZkTk z{eFhZ_d#pIJK8ViN_Nh9Rs(=}f3;+*7+pW94mx@$naG@AR&=gq18@jOX2$$unNA;& z_JpW?87Ls~Ch3Jqs`{Zydr#Eui$e&F?NziEXlCiibKNk}3{0*KVWAbiycN%|dEMtu zQHQcxa%y^!q;v$g{s(2ZD-J+Kk;L}9EH)Yg&7FOxFHZ_z{zHM@zL1X&>5Q2Hh6AqY zusG(e$>WNvAkHhyrPJXUZ@gO?hGiKxB`+aXX81Jr+rJ25$)xCdPvPl$iIO4FVX9!F z^7fe-b5U)x@a;^1vPn*~4T8>W=Jbx=z3(t;hSQ_Yad}<^Hnsm9w6Uvb&~1Ij7)J66 zQyFEYK%tJ>`wsK@Wn4P!C~k>@(9oPbOSI)ZC*WDP(++(V%LQV1Dl%#>0kUlD#RY`_ zF_~XUq4sLPen>+QbVx9egOx~yzCMfOw@=4@triw)$!oZWpo@;My8KrF<#)^ECxY`F z57gh?m$2G^(y}^Zyi^4cd#ST-+uzz;lYzt&I6g;J+2Zu-U5;8X5GrFnZ!=VT6TkCQ zWH(;wT!^`Ep!}QAH>ifh#x!swZe?&Yg$B{IxA%TIO_ z-69&OVv_~IPgMHkG#@f*{x7kw<31BI2>Cr7Vkk8M8sRr!d%H@{Q_UkC1Hun;+Fl>Z z5c>L-G^LusT^%tWGWI;8EQ>fuA!&v=fXyO720BRFM&7PhEO9Q@nXYNMo$~wW?>)H;vk3CM;)2cdgZlpgW2c^W9;i>=5w8g@mMch-U<1$ntT1C_Colm zcR5BYXm1nv13Cp$tg{!P-CP-MoK7%gUss2xjI{ zR7dM`L`B`|%aW4dD9B5vB9z0Dlu_bEq;vvqGfQ3%(dv-2`UhdGaZZ@iwx9xtYr&Hh){fvOKaP=s=(+9Mw+sZJHuSNdSKdj00aVl$o{Qni z?izXzb7l3q2Cg48!aLAaMGDS2)b(Kzn-UoOSVjs_?>5Yv&MAbztopct>D|Vh18FVYWUm*5AC*O z(UltzY|phqHAbxFz2lE(-qZPFT7YDco&ep$&#?iFZ~+D9Yu{+Z5Y+{I#elf_;*dEl zuwtZsz=}aWgPl`8=Dk@mpT_*v`54DVd+Nn=yb;>;)Hji+!`|K9=4--cU9buxOc zJQx%v8M@KgrMmP80CrEacrbAYco9-nin|L&{iMm!qPPLTo8r3I2du0xzVk|!(AW|c z7uRl7$l9Y5$I?G8Zg0WJSwzh{faj5G^l2;rMl%5lApjItv?4vmH_qO7BRw-oZFVQD zanE$L;1CCxa#W?!{OV=CL+ryV19c~W=J7y;4j2!4H;DWBr~8RNM_>K+^VjPrHtKG^ z14tv;XH&Ch!dH_3Z6N)KIf4u&EjChs%)L5(KKDA$l-a8#Ko|ZpW53BCIqK3cQgo0n zz-8JP`?PDug?VzBO2b7|d**gWub?524%WgiIpJ_f?hcx`^SJSm)vTJ@msD;-Z{+N( ztn0z(jceCAS_< zH-qNfR3v$@ivK8i>@aZo-O^}*Dpz^wa^UOLhy(`PH&1}KoTMIet{LjS#v;AuGq}bg z?+hDmxLs8k=Nfw)iU8#JtBM}aYX+Xx$=eg840+=b^-LKw)2GtgCq1I-@?9v7+1!Gtzmgg<90s_kCuG6?rfL)ag zG3>@AgRQ31PBM88Z#P=^UD0Ouuj{ddF_>7?8QU5=m_N13)`@>OFP>5+ripImPzD7O zl-_2QC_o03@fV;9OGyUD!86>t-Mx0M=Wq~+B7m?+J(2~HNx`p;&TAaRk0jnZGVvfx zD###GCpO^w{B@*vRNw~$9pq}r={IhD5yuA9?-PM>>g?g({Xo!Jn!As?*nb&Je&q*S z_|#HTfNE4=;$_K}bE3yF-k*gjh%)Dhgf8@2{(Rkr9_7a5M(!|ZHznS2u&TQsZD$ZR zk{5J3yQ{AXey=*_SBBaI;mm<4CMyZqvqP(-_h1D+(UBbyu4hYL>BZ$T)48M9=WB3x zdU)>ax+|&!nmXjy7gN{{5iQ~?=P*BiuWi$A442yYP2?T0g2EreRDCdSuO!SOhKf&Q{@%gwa~7c2T)4Po%A4m>_e$JuL)4W*u2#_?7%SFKz0)RhXMno^gZUVTS^-ZGtWev|eRj@70K zwG-fIAFfsSK`i#tt%2(GYOCUz9WQxUxv}uw_%wl_lFmG20vXKmqoKeL>bi7QnAU$8M&PfguFpUvhCr8jP&>e~h#QZI~@K@S-B z+yozAnUb+=6Zm%S#R3E|1s;i%Y zY*uf4d*V^v0=}cwEou2%@D36WjXNI8j1-VZK_pP~+_C7R0=y!8YCPxv`GzodPS+X; z8mNUdVZSoM4Y}G%7nlV-K!(ltIb%A82jL2f;4AMIXJxgMrhvM8O#sXS7;{)+rus+f z#Zt?z{a<74^F7Mz^`6$~yzFZ$e0}N&;2ifOzsxw zzduZt_5p&7Dyv4^K(SMo)&n#tQvjhOPq*Fqm*mYmFj~=fb$TThrWOi_@|o8u`T7A_ zd^stCNb8phNK-CN1|KB*DOuJbkmeLfRR>)wl3J9-H%cAt-zjxS6L(@Xl3isoYyHb} zFjPxt&d`V2FN~=}vly2mW(IbjK3a%tq=}=aC5+$%HH2i-fZi@ z@hi8%>oCgqXo}oKI9K*Wmp6isE1mqs8~s3&mN~2Q2>X>dt$}$MJ_gecxgjb08+Yh0 zDSNhwkWsR(2gH#rd4qzkwC{mIhP0_iZkmtb!l&%Wgly>IB$*l(MWCTg$b>Oj-u@la zG$W+xt4qU|X>KXohJT}^1U8@oLS$I+l^L97OA#7oDLc?S2m@vV%lRUkYf2u}2RT%k zzr^v;TK~R{g!>d#k=N1T8im&fa`lqA-dso9Of)FAy_Dw7v)9?r(= z_F=#jj89bmapx@_zFJ95_k=JhPd7dNDrPOUruV=!igP2N#g z&CN*z(uEhbCp-a)J)H7b7=$PVLh=9!^-2@j5ePd4Ax2F{;2L7W3Pz9rnvZVighJa1Yx{2B+kPVDqh!ZkuK-!?Z)61RN?3zBM zunLG?xcVD7q4RK;02I8+c~c8wf%=XG$yJ~QyFH$F#A3MXAZVlBqhONs%s2qplnVqU za7-ibxCtOH6w>sTZNzVbp&~h@7D4GK|F*Sr&9%Is)B12XkCm(XF_*slxVJKk9|(P^*kijfQ329kVw>9*Lg1KKbE9k?>#pHINwoJ5g8mWx7tH+(|a((G? z9kvU%m2S`XLGNs+J^@om+gFt{2)=5u)3Hj)fc27QSzd4b=9huEdm;IY_u`Iq+GGXO zB{xdsY%$M0aiar)_f5X7GjuHeegRl4#v_p{r z5=RYpdUM7Tz2;OI+>frM)BP{e_rLUVr!NRMXs5-y2T~#8Z6+F_DA;!?RVZ?YQ@3RD z^t*}3a+%E)DM%GtyjkL3(#Vi^{VIdNw5!rE=FQ}{!+ufS6{y0?OjMW50&F~|x* zol)jeHX8B&dV}Nrb6;3U);lI_c)+4Dt-WM^AgnLBZGO*%-?9&2UtSZs1xAEr%qs*d z;W;T=*|2sfFWU30G43}e&R%=R^(h>ie)7OUl<%w8#n7U&ZSPnq72%o4nSW`l=~=|I zA>Flc@Gl~Jy{fF(a)~A;C7&aZu=o>;s}ZjC_Z6#h8Gp4~#^FyeR7?e1O@J>b` zkJ0~rsQcS&%_9nI#V3(9p5@{!Q?5f$S{tGV?P5Ue)V3Abvhi1g2JRdy_$2*o{Rkx7 z4fj%W=C0kJ=FNkLpvlMkRhT#-)4<(XHBLd2;R={yr+iUG_V#Yc&*Vzs@X0~J$Dh9O z7B^?lu5ZdcToncT!3<{6k{O@&lo#{g35K-4xVq#Pm4Q!3bI_6NoZL2)Et}L;R4|g* zt5gP^+2+@t5+omJ>WLNejg+M0CKl@u;}C=Z0s%jRN~1>4NMHqWrq2Azsvd$C%iqdj zNndtUa(xs!ONj-D;atlW(h9oyf1eE8?3?_07X5Ys>`f<;)}5>RM%(T4;#F;>x>!FF ztBi0Ck;_*XZtr>$b^#U{)PHC67Khczq{>D}fx|C%YKTA=dxn#^4rONOHNBirfP9`a zzX}#S>68zHsH9M&umfJBy4{q;GI>Q%!;2-eGo$uZECD)xvH)2X)mwHkdx-%|GJ)MbtQ`S2YFc7L4sBu@e9@x%qz|iI(T0QRH`l zns36L@=_z?jLdG3vXJb-vpnJ!kCC@$aLnQ;bl8OLxvXVsSbFl-jE0g^r*OyaQyDxw zIqmB%noW34=O%!#HcdYFufFWVU0xDsGq++;U9RNcxqHUi2Lv9xgn5O$>GmPRu0IuY zj77jvt-J`ZGx_P;yvI4Kj;pzYkO+XUu*>K#kw4gttRxUmA@#)K2_BNvRtNJg+|t)3 zbpEifswxV!2j!^6-90APT@i@J^H(97+WHx|9vS%)Fm_FGSg3x>AU;NDZV{b?~rwAc&_SAs3;y&Tb*ygb;KSf|F!B zFSX#Bh%w%^$CzwZ%H-lOw#FEPHU?!Nuu7KiMI2G~J;S&AM%4IdaDDPHj@mdifLb}J zas4^)={2R*p`g%s;58TMSVk(0nFLGX7MI>`Fo@l2y9!Zhz%SC=18O6OA3RRz%M62L zB{g97Rizr6aO*1F?ttP7bY>FwA-i77Fsy{duRH*{ZprVNAqd|iTjdafYl)&Dy#1B3 zk7NuDRE{vZbwYjYvvQHl0KiQ}qgDApCdKB;e77mxS!^@CD#%#&8W8Uc=5$S=L*svs zxyCtVXFnFDGq3b5SX|dBo?Q!}oC@}ZJp$gNYH>kiz{jur>(`lYG6-(l z*oTkx17P>WOTOfMo&#*11;h(-(aU#p*za9a9nKyd>Vmz#m2}60wW5$V-V)> z$UQ~*@-caK*JCUag!ljIz@jMc{EgfGo9w`2Ox$r( zuVv>hw>Wa_CP?-yM?RU+Awui3pg`T`7P4@~ayESId<)|{JV!1(#b!oWJKH6O0nn8Y zU7ZQN%$NN|NJMV0@!PY9W<(mdgH#Bv4@eNh9D;~k=-E`+WAk|md62qatqqF`l$Y2| z3rW__n*2egc*_Z`#KqP@(ua^+e7?`-9dmTfFF0N|z=*MgS>L%mZJ>Y%o%dC3r8ZZ8 zO8zCiV-`tnfh)3^oyHH85e@5kEJQK=sGZt7J{Ut{`-SgvG{s73;VwqluU?D}-nFw+ z5Wc8oOk2ASja+4i1%~jhY$y=xgN-vZaH!zQtjFQNeq;!vx=E6wU;1Ir2=K421XI%W z&xLcLPn7J(Yd96_0y76-St}07(0t!_maLSP%q=64 ze0vzm7ZGF)0awD9T*5*Scio*<#i9(`agQ@|Gh4ruirf~eTx0n}UL;_0zBc<5o8hJ` z8ALfH>)Qv@e2$?apiOl$QD#6OMCI*xPb!cy@p{|`ElfkKcpUDtg#YSi@#a;d`p|V) z{C_>`qhf16y4MMduh5X zF5cGd9B=KsdqQlvV$W5Oqf$E(Bu&Kw^G%p*^!(8iUWP`Qhlsnnx zkS)gco$7&c@X1$^jR+@miA|vbo+#>Zp8vfk>WrLW_#N6j;3K7@auEz$_MnJ)VW*mi zZ>LF2?scfWE`4&meP}%!PG%!iD zLipI>_Q~b2B)bl#s_-vNcK%IG_t1l(UP&TJ}K7wHm=C>#1vp6`4u>SyI%oSWNS);9|Si_WRS<#c>gbKat3?OleJXWcS0XV^%)9`w`9M&ZKXG3BT%oePR&QagT*4mg|Y2U$rCo1f1izz*w; zUqquO7bDrpCQZ^78DYAURK4RJVR!fLA-B_iU%e2|Y2s5}h0@{afky4`^zmF9x#fgF1C!UaSFyxs5>`QF&rMTZ0Rs<$rw`75EAl6ku76a-75Vi8veJ)S z2+(83^7)~gu{jN+Qw2g`1F&9dELiKSnaQ-dtg~ ze>G*Xv7KG)fK9m^zqKFF#MMsU31s197fkM#W2&1wXp!^nE{vBdTpqAYXHB#NOqseDSJUiuw4%Ml*J7lW?3) zN{REa%5Sn2VZ{|lgg$poo7eKLd1d+pY|@BpRut?1T`=6pfRr@PJ9-!dri|IWwF0BW|B%lR| zJhbENu*226!}0b@=k{TC7#dohf4%}U#uGl!29T#|LZplwkAc7Z1j|#x@60dVjLVKf zPF#ii9zi=I#HGen0uY2^G1~9{B9J?z<3Kq;SUK1M5iGv4+LEo+Lb60h>1buj`%n3xlhs_%1YzQja*b_h$M7JvHK)?C zy_uh3cwv4?>Au%CcxWNl7#G7tL4}ndz)I8|8U$EBRAV~*od4D0a-`NdyE??pJk2nrE%r6-Q4~5fWdE%Rh&{6FiR$$ zFQQG~$nt(L1yaAO2Nq7<)sLjydmXt5s-E3Hmbtf*+Vm`rRZR@6>H}li&)|`w47zpda!k-E9jcp+fD6e2G+HVIAk+9lY2Y8b@fMyqnJknPSy-VEv z;pt2#?or@0|If`?k94_X*Awd7t|1jRE=zaTFpST#OmJ@>7Cl zSG8@s-sgL6KG~jLuYHkKEvKE!lBO%{SnzQDmD&HTZ&nI4b|2=lF0Y<TUw=NmI1 zq-qSR-se|}l@a+B+n|(u@cKEL&s{Q2cg)oRYfNqZhk$V6z6fBUJDI@{+={giJnPt! zu`}O3K5W7sNMtm_(%?*cSP3PM2ZE09X}7lqxR_%3_nmU&LcRt5bDrh1)tU=$4L9Pt zl5;iRMD|)%5O?rRq2ul6_j^2tbLIU)!ay9(GVI&d9xl>lX+;h*A9g&aOrY(3h~Yt$ zc-P7In$Gf_N?leipdK3AS9$81MvC8MP4t!2h&%#xqh-3&VMMA5xvs?Z7ynEK-0`5t z?Jh6Q;JWmYQ3!VNl%q_ueZV#f%gOYvdM~Z%GsLGLrSZbhn+Dm!^Wj=lLv^ytpdF{UC@z-*e4bn(eia%1-4=QCtnF)YLT@|#H+g{^-1)ombE1eWJanWq z(g3mcz>4_EQ-KBuVjy`JW-7akP$8vWQuv)ZM;J;paQm(-|9d$y4Gv`{-k%wM5sCx9T+CYm=gJ`G%q z$I;V1H__7F-lG<(pqTD_l3l^=gRaEu14P{Xm1Ml0s#p8ks z!{6Nb7EnCTj5foFsyShX9qI(u$N#~D(o9~1hQ6kB44+b3;dtck+Pkd@5@O-xG6HfM zU|)in&S_Q#`@8Tgi}t#Ao22qvG0b{Tz>>Y4iDjAr*B{q{PN<%b}Qm>hX~K~JMDKva`WDy7g4f=E`n zHITT@ypA+NaATW4>#y_{kePVGHo$V>J@gCPccn_K8m3Ot1p8~X_>*VOsbt2jLLC%1v za@D0$Cjb~2=bZyZHJ8MwTwsRw@%sG(P;TSvez**~SDzIByeLIt#fwe+9YX8V@q=Hy zF1!L64z{k1N37|x44aeUIO*L{Beee3Xl?2OzH*SVeUCn+E%;U~f_mIX)jL4Spm1tg z-)@uHc#N%&i-p$9x0i|-w_obnKt*R{4pSw%;AgbRpUMW)8&H7G^oNLgYMlm_@23V1 zyGA}ni)%Y@B1?4LJkel{YI%P8G_yzn+xWZA7JLf#^bmFs zh!MuL6ilX(SAw+{iTpbE?o)S@TogeTlQE#*P|I6}#iZ_&(Td?Q4B&%*YP~)~j7Ti=fyZ+@`c_VR z;Y2KdH@&2GZeS%JzWj-^+u0`m&21M3?zr+=%%aLsHq*+)HwVdUeTqtk2&VX~qp^X1du$b*sd5&2)okG|~@ zP20v7wATKjLJ@yV$;=sOs}PR@tZm>Cj#N!YcsWWWuiZUFa4^TbhFLwl`pW2{Hy!Eo zuQ>Vr*U3R4b-R90VYD(kArfR5d+Damh{MX;w}h;7>CY+g6b*Yq`5BpuQHT)(*uu9j zcWGrnmPva%46_X-ZFdHOn)}CqV!!3{=FA~hcbr=b^04KIJ}dD(sJ;l$yyjkIcAwiG z=n3LgI77){SP?sn6b?B$GF-cuPa;|4+%EP^^MYY7OcAZQQn;3p+t(!L3(Mr?Scf-B z2%Bi2cajHY`%r+%*^KAXc;Irzr(Oovjc>re-TAda50=cE+JQx~W2fUsm@}1woZ~5s z-hUjeB(qfQ1+(x&4%Iqjz-&WJ#>pr@i6E&2kVH_GM%4%l3xv(?r-_voyrVz1%YY&kTO3v%I zmdb@=dco!c7hm0f>^oBOhKQ=`{6GMpsu89Epes$xDQjnm$E?BtSBEMPgo2>w*>=?v`>WPDcAmA37Acgm zW=PdMWrn++3X_&=EBR$5gTD!a_Gs_OC$Tr@@H-z`I`f?y&VK3X?{X`zJcZOy=H1i` zmUhf3rfVLILL=Q8q0G_a=Kik~ZsX9Um6MunbCf`zDP_*egT?fa+#&uciRn+BGp0^$vF4@&}65l(#w{bWV2%83`7|7DH<=NK9eZsP&f=jY_Q|}j`mI`g~MpPS&U&h$UgNsU5FBmwo ztOTke^4@=%D6|RAaGKYxOs~5E&VFVP#;XE(+_0(n=Wg>~q&5VJl`yrXk@$SyNYW~3bZ3|6n#F9t@LeL$MO$h2vqdi}&Im*%s;fvvD) z<9Vbpr8Bp$T0>g{s7ln){&|d?=N}cf!#=o_j`15ZJd=@{n0?UK9#3gUHp^I~4bX~3 z$NYs?3!9U{-Ac*_eMSa0@Qhlu`yqo$mn_E2DMne87OK8+$g*OqeRli>Ca>zI$=GO! zj51VhL4082)()nCw`b@}QecENb?2t-D!fOgd~{rlXSR%1C}Myn{TIkaynWQr9xe9DfHIAkJozw9$Y26xt7(2uwnB{^p2Q-(IQxU zmqT15l@U3bXE6f)%TE+;QWIn@oa=%#G8Ru_HjNwl^Gd3H)elb^6GRrVxVolUmVobG z_C;StuNo~Lngy8i9o{wyk6h{|rNDcLWcJ1iL`dpCivTr)*GP2?<`fpRF3;zQEgbF# zvt-w`DS``L^t$ zb>(v^=vk*SjQq#pz^eiEcR6UaP)%5lyQ5^`Tdo?@bB*-f82)~WEy-t4K0hadm=!tc z06R*2M{P+QLm$*XK38ps&c;hUnC0oo#cv>iIT@>ntO(z^zXsK8w*5MOjZUqVd zfmjD8u=7m~Rnc_3EwZ*f3zm7JY59XryUA<|$HJnz4LPq5U9uT}g;=T$IE?sL&8{s@ zq=Hz1{u@IJVfnAXhuZM}oOig?lUfZ;=Td&OIJ3b1()=>f|GvNSZ)0goX}&C!ZVHeT8|Qk5yr8 zDPo|peIe3@b_a@K49J5~nD9+N8u*~pt`o({^JeCVS~N=&FlfbX=A*`Kt*DBJ!VsE0 zf+$sqtR2^}bU%_6#6y6JC?Wp>O-=2HRQZ5$De}lStFnX^JLMAj2km^;7oBaUO>{2S z5oD2hOW{D$YCa*JgZ5GQ*k3jM8Di1ff{@YUZtXRODVjzeb5FW}HqhzY5iYymZSsAT zJ@n$yfVpgO&`Ibythz()T~;UK8Ml1{hM+?@H{0E|Ud z^K=!wuN4GtQ68YYv{!rXZ9XpXdCl$B526CZSGm*qYJW^m#}bDdBXX=a5x#AnCR;#hbRQVPvXB z+1?-UlDeXsoVI8(c6oMOn!lT-`oX**bifUa?3lfEjuyhJ%a^4afh8J6rZz!)p_Y$B zOcRaBL^i^;Pp@7!>kL@pUav`gcP}j0$~TVEC4803jPeW{3p&~Ttl#|TfZFBq=cRKQ zKCN`BBB$!2g_Nt+T}ojJA{II}X+gggO)F%=4%m*Gpp!P_n*6aG_Q-I?$ho_@z|8xN z;V;-)GGgX9`&ubG?!WLOvKPe_KS~Zo3UQg7@C`6IgRN-|Bt30RKkUEgrXRpRgD}(n zyR`?lO&{)t>&?$LF&FCRvEN{7h!8^t`Q%=q@@4J=2u+l*I&K~=acT}G^wm&1Lo-q= zv^P>9yBx&mT`lWAq$3wkTDqrIZ1TB6v&6sz+wV9Zn}z0(qSRR9gI`uYIg=Q{Qn!TN>u>_&^r{q_bX&@tb)OzvA`2D#F2Kj7wTZ zep_4H{0GN|G{k9Tzzj5G0*HThmK{fe#MDKnhLQypea+n={&8H~Z`b{5+;2md7%VXC zMU?`d-bZ_H!kSR62){zbpJdMGPBI`554j@`ov{fpHVo;6?iPsse&}J$g8;Sz zL`&@1R)~V>OL{ZNnRXJULEBW5`;Kr-fAD_b9E!}$KZoX(|Jf}QQHyJHD3)uXiHeMK zf+XV}rB)BuiG2t;GDa?CZk#ftWW`IZ&NfrL)acd&=rE-LBS)9F9vOXJwrb0&rnUFw zx%j7r*GDeOZhO%eERLFxXJ`Yb7hc?O18g->xYH&HnVKi-%;lIY#`Es-F|XCb2)9Ax z@ml>@v866XT-mm;afxn>bN0aor;}q#p$~X?g=3xd*Oa#^P-v0~53~(sF#;m>Y_jFC ztx(*yXWQi}O}jh&JLBsD!MYka47JYDffX=($qtYVzGvN={UcZzI)$M_4l~nOc&fwRuD#GoT6GN;|4OPM@_iCcx;wsYP=}fspA`cLd5r&}=CVTavfv_47p)z+#dQ-_Lg!-qM@}`q@v)vR>E&dxx$%I&nxgSr4}#_{X$8+Hwq|jKMfHuLp&J3o7-0VME@KWwr$=cEw5kT@2WZ)(Yv-LTnJl#TsxWV<% z*9kcFqju}_c0@=K=n8o(T_>Pl-ty;0=8(4}$_KQ-=+q=6;8e4T+_GB>fhcn?X*{oe zmNp%_8~(3`f)xIzxn1VR+p8W}D;^r|;$F5CoSs^N(J91tPWOu4dOQ}WCnwlVoH&km z`uKDh>9R+^^?PX-s(2Y9?LOb_hZtqmhg zI|tRgkM5)W`X$6m;>NA$V(HP>4Mcjw%Ws6&kjc3X5;L_QBR6R3TnP`3^KeTAMd%)= zBAA^F5pFm`Ha;5QRI7;f5>4*F3m@GInFRmiZ=t2xAqKylr_Gq}v9;|)63IJ|o*5Oi z*P%=N`Pc#o${f$Uvpb|8VJ@_ji`*?sYyS^J{aw0XfVh_Kt4(o)G0#dFHbW}td-23l z7YEWo6{U6xnS)4-GLMhif3D)}ZcaHR1YA2V*VrJ_r(57~X6_Up$73F{d-Rvthib~x zY8PHlipYMSb&g1nQ(YGC<3V@+;)C+PFI3mjIF z=}Oa{4Thr{Gurt0h_E*p>bzn8%oM0H(;j zRM&wSzIFbYS?*n9Ev6xo!Z$k7SLH-jH*2~&jA>{Y2sOSTkfZLU(*#@0oceK=t`2n) zn1!*ja{O|Qgwu6so})LYvKXM-Ux{C5xeY8m^yU5x+=s9Es5n$*@|?;=pj-XDS__id zhgR}@569ymtQfK?dlMO-nVO{pih(D)7J%^KHsb%kRVpGpMa3TNImSI6!>J3&64hA^ zp<2LMW2=u=63DlB&E?I90!Jdmxspy*jONdv#k-41IV366kRkI{>#GY|$K$RyRm=~? zyQ?DckkxDIld)}@d54!uXZw(+h}knxFl(qgk8B8uW)BZ~hVY2ljbO!{Sc5l)nAm6IOAI%s7c zjLQD)fP|ZR&^wNnx$7XtNiZSQoig(1m%uJnvb#_Iktktco8V#myQns`(Rc9%jScl? z3%Rj~!_OPNa9x;u!UEFOZIMyZDcy6KF26)sbRdmIkp{$5HXQboqYFj|#p5SvAohAn!vcCI~V#t;`1 z(4SHBPq{aZ?YP@{lQtXs_M5poiWhDuuHB7HJG9CNNxydYuL-LE=)^-{ZcW_E*QR6M zb_UWSZ*O;kq(AsdFY_Wf^=BZ|N+znZy}%ujY2my>hp1eezv> z^5eUzLWx_l8Be`5GBF)JecNkZ;tf*3v?~6sckCl~`D6ExfzzWvP#1))ud%7crH& zWQSn>wyS|0*h9Q|JA!hm&x9mBzWb3o_+Ia(6E6~<9St~IdpCoVTTKOf`dSN->6f}MO{Vi0#kV}zjw0!P-7fwnkv`eP zqU!Vvm6)ux0u|1Mv9{r(un$05hD~rRSSbq{7YSQy~~9 z;e!YD`0z`QMI=!u(ufWF^F!PmyQ$N?_eC;j2h;^)2ybu4T5V#`#xh|6p1q65s4RH)xv}wy@es# z#Z)BH58&PhdUocIHRhRBKu<7MKD?%*kWlcrvG{WO!^(2@J+HVKpv{Q9fbRfDBOlap z1cJiD$UhkVHKoD{eLcc$T|V|HQ&-;v%_Yo@A|0V~NT)=jGtA`tB{o)EiQoE*_$FHh z?PN3Qf@vlvQUQHBM`m$hUZU-OVG-?Fq3v&&z&}-iqkw|*FXE-gXM0^>oexXLtOe; z1f^Ma-?TBnLDNE^%(ipRLRY{9P2C*Epl$9bG&PZ&H#TEQh0A4JZo7veZmk^Qdmq@` z{zVVzyThu;@xy zKjk6r8HqFPyDe(U)2+>;4_+@_3GCW@KV$4Zi4R}Z(~(VeCXv2xibI8jS99A5 z@;vW!o-nTF+qNcIlGmnef{v>vwg_KzI1mTNR?O5$j~BmmMCZWPI_>&Ob8eJof?z;4 zFKofr`j_RSF&0t>P$UVO)IGgTlv-0etnK|VgtivAj_2N{v3X+%(YslvH}8scJ@9mV zTLl_T6cSR|AZFwlopN_vm=wbb-=Whz!^}lqo ztVB-XBAmii{*WJS5Z92EmHsb6Qy!8il0%i0BbdaeI)Qi0IQhTC`Cy1A8*jp|c0F(y zwp;dmTt!8>nDM7#-xt>vNMkH{FW`*Zm{H;6+4?Whm6z+*-KBNibhk!==A!dv69N3F zu2x-@+vlbdVz2z_3Uh|pt}!(#Ty}o#Q$zAiI&S+a`XbmmSz-KAbX3*C)Mk`skK9CW z6pA!1GquYM9p|*>yg7#Jj-gG&^SVY}e8+jKQYsW_FiMLBZr|R+&nL2n< zY~|`wWN|1jwY;))6)m*2=wR+}~eR5N2@Az1XI8k9pYzJJF_kHRXNkG(PM0g zH#=_)CoR-qFKi%n>D?Np&u%ZU0 z=Q%>l^8Pn1i(skZs!m`~Gi0;ej08=Ek_uUQ0c4A~gAL7H{QBJ&A>cs0V2izuzs312 z->!@Ek2j{!1WhzopTBm&?m>dnK|wRqY(rI8iD={_2UEuTay(Tn935H83A4TDsd1&| zsbAVTkeh0Gu%?)&CR$`!iUModT^C;@`O-`|kv?X?)=`iOC;Tv)2i%71;5TRV*47=i z#VW|`x^+=$Bq*4T)ZO`g8=~!B9cf`gkMZ@S+y0VAja6?TC?0q{|zWjwL=uX z{>X`Az=w)66e4bPEPW?Kv+_~oz@0#&OVCtnkCT_5$?j}(i4C^jQo>+_MWchVRGumz z9tU>Yv-8-GHpuA}v4tiMld@()R^kCvv=;OTJP;(P>P%$QKlxzY5%d!M@UV|$I98-h(s>vx`Qq3(mqYW;< zm$J})fwjiri&NR~G8JyH=8_bu*zpj>vG)NRACsuSzp<6e6q%x_H|Hy81N8bBKF$OX zA^i!XGLuEQ&Nrw-38&~q^uly$X^J<1KauZS^SAJu0b&RQr9Y+5%r$T`Y`<<$^qCGW zPR5=Z?_+L!Yo$$>sln0k;WMKrR*>7Cv!hM|094eCTURT}3%A?RPo8WHIOVl>aCTjO;U20CMkb&50E7=&FJBHoN3r;KQ3) zel=1QSTeU#s3^Ch{SpJdEYe&DPVSXUD+6%3Ueem@z-Vz7A{ngN{}`+d`(QNc^Q?q5 zT_3D{Om@ds2JGv=JZZTE*gZAT-%OU1B5b(QqEK$n-jN4}%!wFc?31e24GCHG{s0lr zE{HTQDfF15kWkq`j{l@UzHhM-3)8fOfKU>7wmMTczDB<&B@#8R&R>(*$^ zwU_G(TQ>u~dDC_N?8N(kFG6ILCTDdUBUI`PNb9+Z$&UcFmWuc1(LU988|Tw(`S649 zQD@Omisr<;r%ps+x6Kv`Yu-FdG^}%xyjn(6*dY49vOzHzjRb;a%KOEoRAH@QLFowq zH3V~_W;Geq*v@&2gmfM+5fKC%Mw$_o4a(|%2e9c(;TyiGf>}w@eJUK^n(9NsF}LhM zr6O0b69du{aHUg2EqM-7V2$Ph1c-77CiUb`xCv%3LO^4AmI|kI2fU{)Sb;~SF+umB z>gDyiSahSby1)^X=7YOEf)G|n)Fc9sPU_`>w@4lFSA2~THO^t)O;}T>toI#uK=JDC z++Xe6z=KB+MvU1=@!15C?VGIK-PD~3x)H!fqbeEd+~C2N4NfjY%r@VVIQn+DlKpg@ z-J9|b3CEbDCTIfiIgDW3Tz>!t0K^Iz)$VyGWo{IHg8_#5wZUd+ms(WeZ?cM^U_uJ4 z`PWd6fHJDMLVZK>gGPWd6|S-h5a8w0szMv7aKyk9p~t;n)Xp5bqWHK0rKuvbU#I3A z?jq_amhH*{9R-#pRalv9(rj|+D_q8r=zvkXPRHsd&Gh2%x1fZ_S9BMSy51um;}mV_ zB6X{70?=77VImaJS(sHmGm2#9+R02!fu&|$=10&OUvy(>m+$$D-%x=2FiKOs)vBxa zfiQypYrq+E4fS%+*9`~s&qB18n)@Xiz%s!`Bbey(W>*7~ib#jnVhyGd4D<95En9iy|@aq@~=L8-mmJEF8_n5Sdqk zzqlmgOcUvAp5?{(VF(6m&B0*Xn4;#V!PQB&$&xaS@ z);WEiL7VH8&b|P79wn#7z=$B>`zGH!%tt`r(L9guG!ej2&UV>cqQdDgt+h4=u0=)f z=EFzJt)##!7|_`V*NJhj7hFMWyxdpYL-GTJUak0ED!xwP>zT>1=U1#r!G-oQ`E0q z4nH|fV_4{N+>F>Xv}fr!iuC^W*qac<4rrHgE$?|kM%JYB6dq2?aA6BKk4@MCwqSic zG+r_TCY2*1!H@z+ivf78S@1}fZ6JQL?V4B=E;gx{-jE6R5{+Tc;s1I+Sl@-Tb8 z9Y54TSX2x96EhH!K@{*$9>43bsN10$51y?7LW#c6$x8M-`CW9qVx9;D1qUratgvc< zNM>?sIcg|2t6pm1mObkd#HC(5r+0dXVBB<1@wjao;iE!nhVV-IzA7KxostR%P!dzj za}HUH&u=1XQ8@~%>lF88+0uvpz>4(LDO8q6Cx7x{sT)p6W86)FJzHVN1hzi@3WR|X z7rsQo1w|?U1v>{AI{txW`CB`UdyG2a@Gj@?eQo;2q0KAd?Kt=NfpcXv< z+(v}sm+%0yS$PLHW-1&IQ*A&@ZLMtQ;|1%a?!p0>dh=hv)L^^^V$U7*)v)91zWtfN3LUf8jZ^ZX8a zZk&tv-Fe}u-KN6MF>UVy*h1$4pmf^#Z-LjGS>fGw%X<%Gb2pM7l_!XdQ(3*5#mzalF#kpnU6kBA&F z^Yv$I8O-C{pA>>qP2I=Mq~+;%cGi zZG3`9-NxQ04BE(Ma0M6&`sXE7m3MgVe@KL5%NXuF18W%gk>d%&5Q5sZl8OKHRuKA* zCG+NFn!qb8ZOGH$Cr8nGl85U15Dxccxz*0Em1|Lebtl%lV^E~$C7-rAl@Zs~z8UBj z_|@%h=@?N84v6#6TbWQ4*0Izfe}*~XR2hEBwSHqnv@)63uoU_Yhz{iYn~^~|@c+N) zSq&psroDUDkQ>>7iYzPY5fBG@3q!DGlcd7g!l>F{>-nfsCT*3ZtF;1jYP#k`Cb!08 zO`bp|E!&>gq(CB)j=I+no_K-n`W>_3Z~{dVE@J~8;UBeIfW~qz3M*)~XQe$~sTpNB z0w{G`x~FLsLOacNW*UT$;8JV`(A*T@5dnyI!su|Vj(a3`yR4*hXW1ALR<_f3*}`}> zk>;K!z^S>KW-UPkST6+tEI6p_zXu#;;bX=-n*!J#Ly)GaQZdy4r?HNHEczyQ03;I< zxW30Nf=SX5%}0#UaSByxQYcMnW^?(Mf9(0DNd4t?`cZmOa5p>c&Vn z0F|p=3iK3Xxb9tV^2s;de%4Rh3b?d37i3Wn%8ZV)c%9=kNXt9Gpsk!O7!6Lsn%?td zPTYo)N6EY2fFl*@c!}Erc>c_?CBh3F`fpx96kbr;l{=Ro@R%ZLgMTjUL=IPVO3V2` z9D}y4n{3gQZ$7e<#zfpLVb-LF8aEgyWWYNDG35HmZbAIjqB+gc$3v4%V~pBGpNm2# z7>6r4gG7+TLgP*|E?z)c9co}fJ5m1~&Qu=;8%@gjXTce=Ar4$uqD9`#(>Ke~n_mX# zMT)i`_{M2qjq(g)z6Ag=vDs$bp7$_Lh7N1<0_NhQNf=^rnf0{eQz_l;CBr_6Jq$>U zJG&Q9KTp_NFPyYD7mrjzVvgHF;YoQSC6ejTp!>4yxD7?>isY<0WvyESNcj^@SUHph zj)|Ozwhuhg1_?d1MRPeU@>jw}*N5jXpk;3iF}S%nc}au=+^MU(tmE>x7$&o>=-N|Q zg4BL(6}rUPjJ-8#A*BJ31WEF*-Pq?+I+EZn1TG~>y_urdNsqBaJM!`RDga3H(W4L} z9^A89RgUlx|9#*@DKZ#| zU5-&$@AvVXnT3SY%=wuz8kFYxIS&Ono~5TF$M+$3(nFD)MOlRqaZI3A;V$6(xc7nW z5yl4O;A`nLawu!eY;SUH{71uLp!LL6OO@K0bOvsiFo}J;+;>WMPOY8x$B(bHxAA{vZYVIv!kytGHRh##pf!$+41^# z4mUpKqrpy8IQu*wogGxTZ*XNb|I`mQ1p->fd5yzuRjsuDyj$!qdMKeC4)S~VQ&)!D zkUP&2gPYq#-XOiH?H4p2lNYAh{J6F1agPKG*foikl_|$T(V?M9TW2Vhuqrc`rl7!j zwK&Sl@zmep8dhb1veYHMcNt>&TqEQmwp6Gz0=UD(`PTrYbL{De(GDCeMRpz~olRz$mn<7f<$xv| z$6^RJr0C3AUO?l)9P$ZpaHbUXe0rU9nM$<%3?BhM<@-tZB+y-jn^z&7PULCUo=uG1 z8{KHv=`0yd3WRH%cNu;xyZG)u4d}r!vMCiX=_IRe<>}JnGHe+)cZC4AasMa_Ikjn0 z;ym8jjW92Kc<1WJkdzJPfE>R_hp{f#`+(-Rd66L)g5-Q|a3IEMUz~HkF?dGF|Mnd1 zS`^mjc%qH}aj%g!axv3PlP~98)9onO&gPPrt2f98sjD-y!F~2D&pff*%G3EvMPG<* z|J1z@Pk6msE0_3cU-oew$Sx3DO6CD1FT9+ivMTV40&iWx_Y_U#t=&V9>HDl9()dE~ zZ`np+eRJZEGy%(2&{y}(KkpLLGA^2I4)xMn8P|2H4A;`qlr^i_VQU7yrJX8+o}6oH zbJMz;z6tinLkM3r-CpS`1{wp`XLs7)j4K|z(VATXat1+ODZ82{^h2!lSEZ?7#t6wj z5R}O!yvvYWtr7acW+_r&7dOS-*Mn3W?*^_!;M2S><-(nb-oW9kD4@Av8qbJieg#fL zys`03GaD5yUPhJD2jjGzA;zX6nL7E?!$va8T=!#^nT#cUFHWDI$2s!k@#iRc$VTaa z?|#4Etd%Tv=pA=v>L4NR2Gk4~>BapHO<&$zPl*BMHZ=`a)V$A3#3r1R$`HDomo9z>M@L0kt8+#>pj)@~}CDD#D5 z5W3j<{=g<21e?&6^v|XM$eS~W+$zyXvD{pE3ZY^eO*?1AT<6jxIZXC7Hc#} zMOgYyf{m+Fdr*HBGosfR(A=H}S$u1~e)EH1yKSUwZ6J>s>GlIZV}~LMG>96-c}#9G z)wXRYW#0=(_-Zhk1MK+|6^f+4k#K@A-#NDMqLrZlHa1~m987cH6!kZ<;$NZ@*cVO5 z!RX8=2n~f7J0+I22W6(?izc52OZDR0#pO#iCbJAdWz(ly#VaC}8Tfj;TjNGeS%d)G z-0_8%K^yu%oo5DL^Y#b6rWD9t`XQ4Wl)xbT3~PR*eXdEFM*}H(BsV+(Az5;Mx0^M& zp8d{_E@>|8pRt_?ep9Dct}`_YpV_1C%h^l?RI|Fog>`x|#W8xd>Baz19Lr|t2_I1i zg8Isu)M@TwoY!EtJP&AIs%Qj2qLab7*B=DuYf9L{K4ORizd$ z6P727#EBOX&RyQ-kEjkpU(4LZj#~C1d$5h-ajK;E?BZ9S*J+MIWxf_RtF*8KW>m+S zTzJ9w4O+xllBa09W!sUrox7eJoM}77zrB+PG6;T&)6c(ETCoohc}bUgU+Rq4h*XmT7HH07YM@R|6Ne&VrT^x*$-ADQNwsRBNoz2a-%772%Q?1!wM-pU^n=HR>+c|I-aT_P`Ri8)XTT6p6#Bl8w z)4=>6$h&^f>Fvg4Umu1O{BC@^+L&NrByaj_T2#1=pXwQzD8^zxri>%-A?m~bD0E1RDP*15*GANXF z0ZLpG#3n_S8;UJq;X-}_D!?uN!4YV_ue8XYw_U*2Dtyi-a*|8BX^SJ4ZTFx#*?99# zbP}H-OBcpF&ox8Nudk3F!~j^y>$dL$qU9tY$penHJsJ&pm%FAcAVYJ8sOR@Gw0YRt znVKs<89q-VL(ngr?75j+__a5Hcx%fJ2SUO0I}RdJE)YNa^!P7PX+&o-Xb5Hav1kYh z=%@=GGUyKU?3FIcCsAdvy~Y*H@pWDezgo|vmpe9C`qZ56n*gUM&NrU`j#mxX=&kGe zo{Hdj-)}d{=UG*HFdA@}zT}ynU_7GPu?(7Q`6=Uy?wDOX17HCMdiq zADv%jD9l^bY4C}dOxh`m?s@M=O)EWr$|3TB0#D(4s}xR1GKv%(fIJ~b_U8d4IroE< z&p2>gH!pDK^W23b_Fv?E`1jencDoJ{MFIw0JSH6zI#*5!DDDZ(f#x3Rpg{Mus=T*1 ziVLfG#f(H>`uUF4Ox;N>sK|CUUe2T9;y&4i_OX;l#dx(ExFq`;Z^U=Ijio^ek0YK_ z#NK_=!UxBYC1~c54nk`#q*Y4i)S2p+wD(`~?0$sJ$dA^AhFDu`Fmx_QuR-$z_JWi5 zmv4bu{S5=}(;yKs(XM8~jtq)M-jWH9R;6pYwd4flTVRf997MM;|<{Q-c`6A$>nj~12n3^p#?po47h zf4D5oQHSp56q~StoX*aL^du8>#*vm4XNWDMevt4ex{Bs%&dM(F{_C+FOeq_f9;mU7 zm7gi%*2#Ig=wlXq;>ZjZZ!ZAhuc*Hi%vB-M4FIhAWCj^4c#A8mNj0l_Mv#ZEFmJroa=6-F{grCzEP@Ms3UT-FUQeWxvWK8|= z4XA9Rw{n1*n`iW8Un@sH(RjUBdaEdPu}z9gHlW6`v)b=p4V#b^d$T>R%LpS4YOV^@ zVT~Os%L}dceV8K|J+^;7O;^&kecpm5eeMW~bR+sL^M*j%c_w;LYZ_SG;n5QozxXvt z*zxxFn`E|gaPb6{f*We|Ff&S%W*5b6VBj`b)!hdccaxy=n{ulShZ(6ieiKoI!9rb( zayYlLDXfBkqE+q`EkIl}%T{@T;0v4eKsifg%fx^P5olT9-zr3dctr-X+u#~!-^&uA zpfRmpbci`wdNmz;eRZxCn-n6Y3)LacqhI?%THC{=2`@eXWMHq^nNd#T`I*8AN=K4Y zOP~}q9qi8yi)|u3qT4<|rIym#8A$|m?YF_dWZvC&#bWbh!O#IGXi1q4?FN;RI%rvO zk9rr?P5d*3kEAXS&IJi~Sk#{w7e2OWn!g1ql)_7?kP3*C4x?Izb2T6AJw4~Lszz)N zlqA1P@p7JXvg%Z{dopj-)GcY*>GhnTS|r+P09>P$^S67{d6L0-z>oDAE-!Ardg1Nf5Hrw!~Jx4|Kfc*aoC3 z1x^$+@o^N@QIN>{|%0qggUxJ})&*=eA0JeYp!G!@7|V|8BK+6q}Wa zlsCSc-eVC@#%h&=ol=8GA!p>dHj|*W0QD#L+^fS_t)O8`Aftz6SMA1fZm)d?s=Fwx zEd`!OFG6jLj)!HX*WA1E4q}v+lcEd{=)qP1rK{;(wua2gHx|&d^9Rz*_A3zj&)wIa z1J?9s7&1cf81!2-hGHTQWiGw^bCNSr4YkBUDB9LAf~FBIYs*tv(B`M?L%t3r8OZ+f z$3T`YnGGof(XJ@mM~+!Y2bxq%keCIHo_M$6v8^4TOz08lV1h0gjJ9q8EYSk3dSb+R z6{D3ll!)wAvEI*%&-e8l#6Y6CqWK*ZvUq0y$nIK!5U6yI*zp5iHV=&y;PU<)WDQq4 zhZL5pNvo_?oh-eO0Zm&hgC>h-RObdymWi&~ELI;+7@z&c_|Np6WWaht=rE#1JVGLn zGdJ1u_nk+HkhxK$u*Ok%=a=mLc2ywxfoOx?2Ykbz1W^*VB1i$C#Tz6uRvm)>8>=}J z%R7=Id44V|;kjj?1|2@;pv~DO+x&JjE9lyB{)i!W(KtWZrsU=vxbYFAN+1_~?B4&! zVC{kx$cM*n%j2xcQMc*D;fWS3fU+?ZDTmPpQFg`!e;R?*wFj(ZhAJj@5EETkqnKeW1J8{sEmo{A}FFW({2G#f_f>o^PU-V(zbj! z=?oo$yddfNRoF%P7ywyxSYhSOL$^L7aW;gW=d6zDk8_$B z1dv5`)-;x>h7ceaoWw^bpd~Cuq(<*k%-g1#-VkF)#Kw}o;Ls7}$*}ydU%WwND6eMs zY)1-^7VbdZijvcB3#N)J&_V?3@tj&Eu`yZSob;=sf#BcN*8SLQA_7>*R=6e<2`G`^NwX~W2Xv4D zKR()M=g7MNsDJz?HGu!)y&J?zjk@{(nDr~A!7mjYEd&>wXuHL)Pm<~a_9FPFW z*l@`a%6ynM{MAI+A9*_s3TrL%?Cg1zaG)mr=ZD z?Lxwt>wh7f`70$=e|Es>!6qgc>m&7FVzS;4R8wytn4JORyAjpKQo`^(@}kNUN0DUE z*0&)|MqyZ;2?srmDLVTp1{Ir3uAYc{yaPEX&J$Qrg8cuwod>CK2K%?+MnM#e-6m89 zG2ToqHu$a~?i(>sC-7VpbQ1fO>LS3$M!NjqbnifsOhd$V4D1JprW*{RJv7*ZFisz? zztjZGBO8NK_&Wv2e|A;^fGt1t`Cs)A&*SQMeFRrXA(O!fkW0mTqq8Cp%3D|97?K^N zn1Hh9?|iXVjy0?z-PerM^6^IVZ$+%f?{<}2)t9pGDV!&Qfbaj;aS!+=l@YqxYL-*2 zQF;uV_-3UV9R_W^tKMO+ljxNn=f&Q^5C%|>9DwInFVA~~D9u-XK=F>FG-r})xIKmb zKU$b*41q?V{nDH+6;1<&PeL_4QiLYQqq*D46OQ^|R3|eC9;lPeY7kkP_zM4X{?T*foZJ1!Na^Fujy#mn!XCNSq=oplbOPV`dFnEunK;@3xnB(AU8)_=hEp$CXsJK?WXw*NI%FZGw}0 z8s|25mdClSyu(k8PxEh_7%X@-4~=@y%IW6UGTWFzS%EG;3wOhq@o%SO|H%Kdf_#jj zjrb2dH=!mP9{6XHu73vrfP7fZ2b1dtx{F^+#dCx28OF+|#(|)-^OKh~6?>apDjLoA?|u?LTQ2sehaB=iuDsVY8=%HB zKvldGNR!tdqzjD!xx;z6P@E$E0Sl-8Ul(}k$^ppt{jO#wu(8|?L|NF}h7$D6R|fGO z8mgNp#$Np5lL2W0Ut#J%GpZUbD7vPu`5m+QccDP!H}qls8MwZNn`_+0@*$54T?6`qp^>9OI8Vt^66#!2&4u z3bxm5xbl-XxkK(jnPk(}ijRkDRwrGgSyRNT>5q;ZXmr}W(XG;NM6g4^iGMd(&|&3&w!O$u z5sc!R14>s-B^~JdFE^@)knvQnUhPCiNgXS*s*Y$Cc>ZqYh(AwfMN45dTg=lcQo6QV z5u#=k+Fd4X%8#G7hcX2&2>h3AzSk*3%aiQbeUubqg8ZIHrQjzK4p2hrTpzVV%KZ-i zMFI04F~~qg{hOhyvO|FEe(&)c+o*8RXX-?-q0NSzzQg2BInO{z>MJA8474N#XFwtn zL$F6TCcc!Q-#s%5-Tofb-)GOwGNT{aZ{l$Cz0Uzb;e4~_=B-`}MLo%9e<^~5r1{BT z3Qm>*TTfh_^70};`f>mfF90HN+Lyfeyz(-+%ISmutns{t=wT{cff@Bbr{Mm>7l4Ld zCwU_^-XHV2p^40|HCY{@AlmvLT2A4{igNbcq<6Tq!6PX&e9tq>)|RX?2qgZKA#!TfT)I2!GwFqlVy(mby3xVH*&KEh*hym;Lt_I+~t`=Y2s70ETYhENvtgLYDX z8l(gLlqJw{Zmi^cp)-tPNM&Ix5eYiyz6d_rRC??!(p1RO91-|@_?6Mo+p7{k^Z}Y* zr+vw@F}uW<^-h{EtDYaP$)Z?`HR-3D8AXP>Y1}L(i^5Hh8ETn8g(r{R{D?KgmL<;Z zO=zUr;zo^}fSatS&@L1y&7#-_l<-^nY7ZeT4bn=WaRl}4zfdmyXX^{>D(@I#v`v{a zgtEBr+t?f&Xc()IQgRcDS+WzHE<-O3vR}sYr;Rh8GsW1irIE4= zmI^Un&N6~XkowT>V|;jp_uCZqz7Ig%-xkK8ebnN17&~ZWFij31Iqi68lY&C8NpKA zAX2ye-#K&di_qRu7RzwjvWmFo(At%B-rV;Em3)4TJ>kW;*+iPqzrS_E=9OI*%Xc!* z_cn#^bZZRPE~`nRU+yZ6W%>8_c(ZJr?Y&J0eL`*#s*j1{z5gRwU4EZ(Rztu9&Ek-C z_3H=5`!)jX8GTJ zCMa|0A^frqnLhh%|M@fU&>VAm9>shDHPHsN&NdgBJ055HzUm$BA}SxR^|Hd9wl@0 zX-hCdnOvt_fA5WAx+ zXxf&~CidHX+o-kai69iswMIPt{f_RWLk>_VFT;pZ;O`gkik2);gSIsJLXE%Mw->bA zlA(P?VgBad@96bMGAHau?%n=dN3vma1dmZ>DF~U;krwKbUtiK_f{-&qY#jf(1%U4G z;+fk4apf@oAQNf3jSO;3qc8rrMIGx7ZBVgZtF2xdpej-$+Ii0GCsgj!d&c72c8Ucu zt5!imq!V3Jxe2Q_9SxZ!^ST58PwyL)esMZJ13jHJkRdxn9?vg3=3xAbs^shw8VzKu z74g(omWT5RIRXWXn?L*{B!?YH|-<2c!Iw*7yex`yV9$C=o)d?-LoQ`$(p%y;lu?bF9fbyFytW^?aGqR;Sd!W&?()Gx|<8O1I zLFzM@6z4VSq&?}l4jYrQQ073x*|%cLja*!kuwJ++4Yb-HK3V!DXr$6eMq=d?jTT5@ z9xT-uttB3q$NQxrr*s58^!PCK$NqtkAPJZk@SeYo%L}(t>MME<=1&u5#|K_wsq)`> zH$iL|!$e;>dvtZ=7d6*=h@2~I&AwS&x%5$BKbvfA#*rgeOBcP`Nl_zgO9o&tsy#G-NA(Q#RSHR+Qw0Z-U>Rka|e0v4&N6JFa7*R zdW|n*1(xOD1QQg7RBv0W?A+?Vyp7qlKXf#}XvHL&wmFT#J14+3BXpyWG`xtkk8Ta_ z-4B>vWEL*G_ZSY!ibd#jp&6#p@(VaC#Ytj8JtuJDkboI#QQ_5_U$!wUr zeSvw{*rSz_y$?zyZikHx@V#MvAa(cNBJ+~wNj{I&KIt{nr41UWjFWKsuYZ)8^t*gs zVeP8qqnsi0M&x!By%?LL(e z!KJ6^cC9fAbd;KITy#OdENpN{U{m-E3Mj!YwfMB0bH@?a$&|>L`n>u6^S4f?)~crn zhL@S;;+^iTg)MvN^fSKDZ$0?gd+XB&Z-#SLYU!?d?2PS+xfD^3%;|ChU7A_0!x)cy zdrea|OI)?bZMM+$5jW|<4nM||8fgbVIVLRYi^ZQv5zz7c`ubo>L(X(YHaj$czWIdL z_aWEu2F=Sh7kOkSI}^JuGp~aca$a&7-5qj6Zt3RvH8%f|acCK@4o#4sDTJ>*r5U<* ziEWVa_|THRzmvYqWb)-4$tZ8NeXjBB@teNj?^aL0KDdT=s}hJ0z1qB9uvSmAD#p2V zscKh$^q~gVihk~etQ>AO&8R)E_4_-HTfx}$d*mJ zPSBp|E@ouS%?OU*)Zth1eA&FIT4nJ>RJ+YXD%!v>X{yS&wUBsI zyi{wY6KH6exjA8N6cce4RjybabXu1?$^-qdwk>+lYc}a%-9${WP~;#oLNFy^;O%vR z&_^E>LtJZ36{^qqCRIoXOZm%b2hVr8^yFn2&82Gv&0JxPN_KfzyCUQ^ZhBB$$t<49 zPWhaLCG&_&b&N;fO8=*x;i!h2gD3c22TOsQ2$^}%?yjijIsKs76g-eL<4`WGGzJ-b zb*^)QQtig86O7)fSu75#XS&yz5nW?=jF1rlP zd-tXoSR=DnQdc=$t4$tCJY}3Z+8Pa$I?=Px3g6>l@nybxwF8fWXmc;Pc^zwIiQwIw zr@AAV!nSYJ?Y5|L;_1gao2qN)k}mUFJ!B|XNF2L-wpJktW?@VuU9OtBFpV#3-%h<^ zQSI}-5vo8U*Xoq0T$B1gSt}iL6%kP~{BU*#QR@XgWmb0I3|FKB+l~+B>^S6lfp4{B zSKT$3j2SF9!^)$wbBEk9bB-m$*{?}3N3{`|?0u<>mFH%V)Y_MjRNG?>v;*xM0=zb5 zHjLcx>@B0Ny&DNV;ZN|{goH7UDOA_ArujY`GD7A})+Sntxndlyw_H#R3Zr*Ytk$xq zx)P@2qi_(kh6?`1=!cJlsupn%>E4UgX|~?sOdY#usP5o*PA2nZJ1gI&r+tm>%k+&K zzzDAngGf-7pp!2#MhAZwbKE`0jP}00f$P=iM_7ew`aL_=X&-dlpr1Tib;5xobHOwx z*ZSarr5BddwCB@LKFxx*;36#251k4^qVwOjb=^yNnDlLcGXohNW% z?V4};rmI^wDnuJk%Lg^`crDiO@#s8(ds2I@RzQ_|V}VpdMRe!0<PnU%|?+&KnoBlcSz z-J2~lnr~X48W2Yd$7fz|#)}--TqtvBvBkv-9lo`>U7mXyahwU=68B!1jqqUl)gvtR zjtd+O4pVar32WcjB)!s1g`3{RwwPBA!+_;QUq9IuCT->*%jt1^*>6m=!BsUn;pV0z zTf;mfUN=U`@lz;w#5>Gba8I9?Tk>YOm|FudYEp2W;^0>qVR3_2pM`3@mwmR=-ZH)5 z4={ZaB}WD>$Be&eV%fxh?dSv>4SlWr0tV)*U7^l)C=ClFBl@o1|A`83y9Jr^c9Nxq6@y>R$F z^G3#F;qV z5TptyRf0&75)_dVTU4 z9Hp*@xnzJAlHJ!s|Gs{+t^OrPfEP6|qn@5TqFuI?!;(9^IVRuZAMM*;d-QR;2ERxt z0KAHyrM3{=);HRDFV7*=dQMg?8ipZZ%(@t@xRnI?RkBsDf`F`%mfERm))laa@9hLo3zg1`+f4NvT1=Bq^GYu{j6pIH!Yb|zOW+F=HAFA#=i^-za6X6t*}wQNnc8bUBX&t#ukBw_~PyfW83c!swDo3K^OFR*j}_++A61 zVVD7}f$>fOnFFsbVmnxuzbHH*B*n{ z(=IkBm9LM4bl%aoUUwz9ANpX$ z|E=YDPO%bVZVM7tn|ZUdz_*i**USeXxBg(;u%g$tF*-AWY77#~_Rf9JGJIFW6P4=o zu-9?xy@7xobTo)Ke}mTB+l{M9!knyLGT1N=uL`>ou$aw~YkeWs-xcW8BwkPeW%@lc z8%NA2#zk=fD|oEs^)!Fu#~FAGCF`bx3r0?~S{bMf>n*mSyQAv_sanHbPk1GcyfGs^ zALf-9&_u2>PLTYHt?xVOt@g{sv7nz89398En6*nMZKtGY5gp)0XLh6xIc1ZP@+ z5<9e12b#K-X$GiI#+=U82m#P_IHah~XLFD$=MaJ2-KjBl+BFb|NE&(9#sf2jy! zf%YCaXt{irHzY7n8_qySmaKVmNNsR1F4HbyZ)H$47tAd9;xnB`4sRx*Lj9|!fco6E zeivI~J+l(Ug=hBzM`8=460}UM1WVE#RgntKV-&l!222IIM3}kYnxbysndLr?D^YK^SugKOw)J$z^J9 z=>%y@gN42>@d!!Q1IOeOI>LnPkegpQaA;|aYsgzQD1J7|{qDV{c2N+*MI2VXu3+=T zWVan#uZdTlwl5>Xlsd-!zHtw0&DkePn)hzLRlM)*t!-L%h+} zT|N|jba?c>afuGLikY$jO(<^bDad&WWU__29Ib0&&AeY)0zEc;bfohu?H|VQGCi2U zlNk}TEN-=~P)nrk7yhSHif(6+**lQ!k{ zCH*#LTsZ(zcUX1&0WlLPqh?uy)h!&0wktY4VU2zdPK;(#W%^XxD;%P$!-I_K`USSk zL@GZ4aM$C3S-OC3mbdE7bm8FAjTr2a003uH6ff~FcJWp8z10JmEj_UCEkd5m2;e_I zR$m5O0Z*vnr?c6uPw0v*krC0<&zyCqo_i#_9C!pe=Bp8c;J0Z3rZaP7IGv)Weo#tw zq$T{z6mqrdi^s^Gg~PAdti3ZeDlwAg3Yh1!rty$6=pSc z&ey&Ka0C(LnW1T1j0U|nHpc&Ku zDs?(GIXUBmT{Du4zeCExsrYPgtrXTW!Cw$Rf`Wq zl?77$jL>M5Lt5a>)}=)`?lIQo@nLetWv{LcqXKWE4LSZiX1>*mckB!UA==p_d;-lm zm4R%31H^3GAw_Z&tMom&zGFtj$)!0aqJFYdtk;2DYore_JcW&heX3_XL~6!51-FG9 zQpd9AF2wbDgkq1&ImZOD^xLaBIXR(H&mBR>dPL5c0#s|06M$Im3g)S_KN6el8>-VB zSPlrbrSt1|Yu{M%PpR?o_il z;nR6ogRM}OGb?iwLSkYDqv3L}<1wAd;>iv={=|Ga%OQQj8l(~U2=X$qbLd|5%G zXvyLBEvHqlPA#-1yU_jirg-*?P(vTCVO7AV=9qq5eiV6F?$AVo70U*-SV7cu!gR za>BtH@L9uRd>-)U^~;u6I%2@f?YYy%zVlAQRO6^xoJ?NISWK|31-J395-r~1rm3ARcwriV*200JWH&!>=@&#&AY1;E;+ zb@G!ntNRa+zU>E+d#7jWDb?G>iM0}`%c|U6%X3_P zBTTgb$KTCzHR3iMbxI&j9llb|wI>y`-MsJ;|`{f6>a_WTvR;wFSQdy&DKD$t=pqI4&F+L7m~h3d&f`$ z@2EPdt$)1591n3Q&Fo{>Wi@3!v9qdM-%22*jLy_gUqz$xs(L55Oh;u)yjf*SE%dX| zsQ4)!5MKUn1@i&H8V}%jdJu(5XUG=%ueVuAsT8IK8S%a^D!B;fU2>>Bsb-ce`o%k- z%lANtSCh)hC!vqAcCs36duo&oKiMT(1~cI@@Y~>o62|dt*9MFljMR8B2WCJB!@dew zw;s|aixx186GVO5Ml4(Z#|E+H$FWzG98Ti(^nE(zMt`~A*{jrHH2m;X!4zzQVT8;~ zKL%RQoSm>z$Vz}&VCl-Qb#(F>r?C_KN|St-faeyGq1yj20`y=Bp}Mu<`k+mWPyo)( zR~uQ=gSY4@7xlHB0Vl=u0P6-0Enc-b?x#R(lQWXLf@F`Ja$`?78nC0yTLldwCg(Q3 z@$IaAIGVfazLh$zl-r``-&&i;nKzoj;dSuCL+LqSu+TzGU1IL#f6qzd^la2LrA#!gLm7W#HIVi@}B+x+GPybiip)hgr7rNje%Jip;Wi&)gYqC9UIur zDY|tLE!f4}cU;f9LhbDh;jIg*9?Rgsv;3+)k@GfS)?cm*UbV#lNC$~5Lz42BL-_pH zIJ1503|Mm6>YbxW4dmnRN;AW*Y}Nd}wSQ0(5`;gqq#fSqEe9^Xz2s^cp|&3=Qr2W; zZWa3x7InW^&UyE()s;^hBK#vYOJKB%gH~~G1&Go#mFHUgu|H?LNcMv-U`07w5GIsj z)+Z`7c|8`(mX9b^QY)o6@?pjsbUEABQOc_c)C7msb?d6A@h=jWAX4H9E1^h$KQ@S< zQl8}h-_0N*$mn?sy<&GgpcSk#Ur!DkX@+1+c9xwW#=)xl*&+RVmHDKISmNWhWv^qY zU(a#rCJe9U*4=^Ly9GJhjZ8}6GpG{%J|#=zMKwpDC}n!2=ll9V zv_g!#DN=x=&wh}^xqmbh)gPt~dMa2|ZGmirK2ytm?$go?>BSHIjWsj4y(m#v(9&@$ z>_CYvaM&zFO}04G7LR;&8LF|7m1lvQoShcUrJytZY= zUNZNES^n6ge`B^3X2!6ACBJ29!NthBi+3D17@_38K%-+7*&L zc1&EpLC9DI_ibH!F}1O`L98z~5>V4GOhD_A7a+e;u>RO{^U-x&<@f5tqaKz@5pmyr zL{Om1GNyE}oS^R(J@xvdiIqx>KEC)U6NuQPH2E(diIPqW9h0thNzkWlQ?cl6Xa#Fu ze%IPJck-x=0HNlajHQ`kr`)&zN-Xy2ipxz@hD*WoQ}`VhkPvwRDTbevzKSrPc+*2@ z@4O2!vdSrTo;hJ1p``0c@siK;$a5s_q50qibl>oLx>bl>nd69rUxjnDs}ENnQT0en zvE3?%9aTOa_dAHoI!0DFe1>rvxVK4u_=+2c*)8w;mxsNi-u|^mmKa=h9gRg5HEd4JB(@eV_iGZqL{hq}w`BP>;HG#4sFL z(R+jK&6d~ey&Ny^`wD7y1XwG@PX%)RVwZC69kHsn25eD!JF2Pv8sx|I8IZ@6MUEO_x_Q(er#lUh={wazY9UVzsKckIADzAOH-$NDM zQY>v2SNKBLI$R=I_DOJyexu}d63sV?*3&;FM58jCjJGA%{>0?s35SVp@gQTe4yn+f-_tn|jp zsnl@eupAhA2XM2m8YENH`8vA`t$vt{Gto%j`{cJ)yEcGuHhzl^VmMa1@px9m!?3)^J72>FnO$gQqQH8hRx=AT)=XUm7ZE# z^yIAzssSQ5#WWcu8SPWU2kEufLH(H9Nlp7&!hj(ZTN(b%3-rF2nvNc%mjr=Jt*YJd z{y2R=r4s}kB)HC?CJzRg)P6T|sIFb_aOvbq8`U%^pY#DV&LER(Udsr7v;aQ?1CSTO zB2zr_ynsArGScK0SW2!ZW!z_q-tkVVskl`*$N8Ve3IKf=h$46OGTvl^(&}%s^FxO5 zLdWU*1^BU-14wO1;|foxSqHbIWtDrJ+(NnGn~@XC5Un=x16y-zk)9~O5n`L;(yy+6 zRNlOmg_%&3LA1{4^q#?d+|Rd8xV+)kctYXGRw;XzD~U@{V`qvZ8Uki_zaXlt-eyB| zkwabhO_p5H;mW{UUt|?6b6{Rh-)URO@eiV1akEBP?<%AW41}z6{j|XT{Sj?qk zq?JIZ4%T2u=NL}CVOg=T=zI&6ae^4wmZ;Y5qp-Ey1d`V;Y>cuz|S7Er;Er%6<^}rzz zj0(w=ru1FM6d3_dS~lU*)Y;+Vx8;~#(MsOk8YMcA_o+;%2Svb58Ql}%f=NcOZ>c); zB|56_^3vuXh`zGj?;p={JDdFV1(cYJXZh;BN}p9J8$@Q%5oVB$=R9Hro3fbP2GJ-+ z39wB@lzn)Z_gZKV>J4qajF z9HPL!TVyJ)9O)K+d?MNz;?Z7`It4ahn4^Mz=sIUoapUXJs`#YY_z6N&SoC%pRIBC) z6vy=!m#UQKbkOW#)B4R~P$5m$f#hhUnI^wXrr5e)LV&k+oenN0$WM5HTz9FgWtd3b z`+Z4qMTmFdk%d<+pIZDKzk@9JJG3zL>aQF%aN*3O!gY*XAtcZcU(Gjh_{jW_Y=pb%(eSxKA0LhwoIHRLNN~ zTCh?k3miJVc4ijzfLTHsmpvKk7}_^}{6)G3R5n(c&OknM_>@o-;y_*um#Gm`?#LVEr zPgBFVjTTf8%kfVVSC0uL9mu+E2O0Qzv1mL!*-M?mqzWkvXONz=lQX{CqBobeCCn3+ z=jkD>+iTPxo0}CXL8!GMc%s}E-TQ%sweA?t>lG+&Or8=4?pB7Wg?yNjdyQd5!v-Co zQ@0t*QGZBnbAC*0s7MI(v);>{Tx64q8~y$`>q44e8|Nd=J+?J^vkqiZoW&v2OsEt< zS*5$MTx&GVMbPC%`lAj}myjVH;Yz&ka?HqGzOt02}-wL#2u=0A+hCX+6 z!z}T-yoDvGnr~iezKq_BHzRlGV%9Gqh&P8>NFNemcqW1e93f{d;X84W&+%iXg%euV z&PkD`&ndiJL|E32kn+&NsTH%)egN#@Q-mM&dv_lO`Wjs1g}1;RNOZONPxmc9*h3$D z89v)W-Vi2o*}`KoENLmfCJmaj4YSD%x?%@!`CL1ZIxcGT;L{L02d2Ny#O2!!8owcrtDQJJ}P}**5r}@$) zMFWkSe1l*A@VRxF6#lG+=OpnYSsZFbbU)A2b1Ri^!^1R>|e_!0PAP)X}=#jiihF@IJF|F%kgRtWz;sSy4rr}ndG{b$ko@Adfq z`J(mtoq_86pHIc`Gd>GfDO(UcxxFJEeb|X*r7-{V%y}8lvqlrHTn9;{{6vcj@itYo zc=B6U9Zb=Ar_W4>`Qd?kXlUsf5A#RuFM++-+w0EuefQPELb$j^=1D0bLz!jhQ-6GX zVt;!K$Gg*Z&9k{4qJLZje}#*^Zw)(U+N1qy_tl0*+PvGCn2IpO+Yd+n{u})8XX0mc zkvzCKu4;U5>hI(D@nczVaoOuAJ<;^E-B+2JOB(HTsLE-ad-fdq2=xN^3WKp5>i_Ww z;HyFT4H90iPp_hzr`;8#E)Cbp6iSoO*=0o*Tb-}9o^B@JRw=p*1M2x6=ZS4C(BKot9r7wVPU@PK0=EuFTI}np~r9wYh9mR#)Q*N@q3& zc8wHnfO^pS?%lhYk)0hb8{eY&*)6|?a4#n>8Tm!}-Or5_FT8-{v5(`jI`2T-jhgv6 z6kxKv#SKb~D=yk&Jpc4Y_XPFrfBM_2=qt-omXkD30<8{GZEciZ9L?-aslic)z%()~-L^Q2+Ut$v`tdp7@Upg|Yu zB?@^Pr-lE1=l{)rsss1-S~iOQk5lw-M%*9(X5rA^R@na1=qwv(r=&(=|Hmo%Hv|20 z7|cS*86T#eH>VPCdCwX|K+$RmgfT0V@H-nCTz{Fa~gN)*nrsqPNe|McPhk1wO3 bfITKx?QbgHuj}6f{%K#jqLF_A_3M8D443%# literal 0 HcmV?d00001 diff --git a/integrations/torchvision/tutorials/images/resnet-beans-tensorboard-output.png b/integrations/torchvision/tutorials/images/resnet-beans-tensorboard-output.png new file mode 100644 index 0000000000000000000000000000000000000000..420638f0879ffbceb9849916755588fb8e8ff3ab GIT binary patch literal 102164 zcmeFYWmufcvM7uvKnU(G!C`>l?l8Cpg1ZD57~CZUcL);P0)Y?+?iSnz4Fq?0ceuk^ zYww-4@44SO`_K354A0E;^xM^4RbAHAMVN|`3>pd%3JeSk8cSosCYGvuKIPfDB@u{?C$xyp^I9!#CqvDC z4}7OtuQwqq@cuX8QtkARcQCO4#*dxB2yF4{YJ~ZPFt9U6GVo-21_3F!q@=LfXqk_o z!%_)*D=iW;oyWb$vVuN*oFf>~TuR6i{?Q4g@N*c0E^K)eSc-o4)4m`R!eBHjd879j zfY@bb#M1cX7l;c?mtisH5_3rY;Y7(yeQ^G+$S09h26z+M=VE&_E2vU1UtUvO3=L=X zhVYV_5N}ZjYZnX;UWw7|+NTmqr0RhtG2RSHffxgRz=6r!b{^kGKiXY;jI|TI`Ceo$ zFK%k?6ztOYNq}81_$S2yuDPVNSPA0sGfKk)bauJEq+nY5J5>n-SmMbSTjG12n@GVD zw$H)e=>Z(#eU@e@fqWPpxbKxP@f=quCj;FBvMK15wkv@g>~9EBzYTx<{#NdRS&J%$ zDZ<4tHLXo;rxk+d@bQM=8?S&cvI$Bjp45*{*-&c?0lc;DASNGae9KDeXFfDz+HW85 zFnUlVDPd83O6b+GNWPu{1^@)2~C8C--zQQ=K+O~K*30G;iaG~^R;vnImMQbZ|mf4RE}rCuzG zkD$690clw;HUP35EX8!vp8WoK8&ZHjZ2ot1|1gSY&jmb*J(oqKl-ZWxkbB|ama@%| zWN7-lB##K5g|}y6Ad9w-)WLX^!QhBJ>|%W7<@ZY=#crX_pZL_W00+t;g%3f;1K)8?d zKq_+wenK zhuhM*JFzdKpa13Z;&YAnlIQcD=|$ZtRNeNYoeG$vlgSjK5eZa_W^mCR)wP2GY$ z?7}g52_^z#f`!27$GqhUSE0X@sp8In7c}H*IAQXPG>P$(@vd@FJBUK_+B1&QgV~+;wS3%8dg-HtC_~u?!Ghq)#4`dIf`cK|*bBYfNqxstE-t@;G zN%~3piR4Jvan@Paql$}*KNT0gi!4@gso5d=*<5U?N&dxGV_dCL-Sq3{BH&NFuXb7j zrLOY(Xo+&wxi{+SML`o?6GS_}9iN?NL>U{ht0PxcZ>!{Vg!Vc1Kl8txSIhV;Y|yOT zEPn5QBXw?oRuPXKm)lm`bvraW3Zq36e8uCR zBer$69i2~|leZ40noDo3Q%2b)+1kGcb?gM|lU*3t*JZY5ik2zZ$1HF)E8o1hr?}U< zH@`u?LW%I~S+v`z$SCp1 zPHCGcC8BepU7}m!O@cB`VT(Caah_u?%+wN2YjzLFi1Bv^ zA={R(Z7LBeu_}cuE(aMl6iyXR6F0tX_~6mvnKBpXPUy_l(CBioRI+I4W|n)~o7*Lt zaV-|N?|iDx>yX@-6052 zWoW<1_nz&C(+4Zb^HAcK?_M&8P=)A(Jd19K#*BUyjTQ}%(TP+bt+!qK6t|c@mwu97 z!#_{>nTyd@qwmXxYFWm9x(6f?qNV?ZwVkz6k4WF3ex?yckEd?IIj=DaoOU?5bMbS& zLx06!b79qZIqpDp9UNFR6luX~l6g+!j^qwG5nQ<*9hm<*V$(WhxbSkJenFr)E2@T! zg`nBxjGFv4dFil47OP>feZwK`BCCkHNU34`AXN6xWxTXivI?~}(#JQq4bnm1lnyq%XfTJO% zq3omViR{WIGF?hBLfA4fX&AMy5A?l7@8Yinkhzh^K1@oUcUE<#c3uJlfCC8)@iMf- zvMsSDu~Z7y3a>uX7J%gU$%#2#fBrh)tgRZW+FdQ_Q6zK&HML(g9m~*tQC?Ewja8CW zmRtPv5JcSdZR5hyfuoq?#@%+|-2!Thh~KMLnI&p%R`=BHgnGf#w@J#A;U$^2t$X2n z29&yWN>_|@oR+4L+qo}u`}Oc1Ko74I&6DxdG)bLYJ=Iys)i8Bh*YN$W&nu-sgM>GV zI|(1;Yj7zLS5b&itCvH(8z-c1BF@C(>{ZQ2L;AuJ&=p40sZz&;e}Z;?6e&jpM);)# zE3YcrWPtd6AZO2BYrp0mmb9=Kw9POVwpl1Sn5L|B8_XH(%Q*E4Q|~*8uXRe;;2wUR z%Hy?=XDIGl#PT^&PR@StGP4y7+ag+*ZJIOiqZ+j}@pu4|ERd-6(eG`iuJgl`YHR7W zixGHZCHmEYJU8#pH0-%dF~T!mY7o9*De-L0Y<)OEdPH*}j^a+TzpDb)ZEtME4xRse z^AlG$R5!dva5}Z_e9(Sy@m&p}Ez{zKOQV(7RP--WJ1#OVE&((*)*>mJ&(%VWW3Ku$ zq;-wukQ~q{*}TxYSG&RX!shMRrT!v$OY1qzsp!1eK%i#GR!IL&+)dHB585=EeiTDg zhN7|Jx1oihke32v3%;Favg@iDdGgV!(L(~ zzO8Cp6;&1nDrX6H@Q*uAZtlf78EmFPUJvu=Ikc)Q9!&afxz#SByVSW&7@pPra_>7; zbK2a3m?qz|X4PT2ub*i`exgoMmAM!w*ZH1G&qS4`-K7nK*5^H48n-Ss1u74*4wB}_ z>$Jd&N51FeHGX^Bj)(j=6h~sW9d#jYWXEL9?s`X8@|R6?6Lh%BikXvwPQI@Bbak6! zr{%+qhM|Vu2Q2sMr^Cg`+yL~4^+zo)Lr23)roOKMQxOYWtmPzHsX3^U3si5Pd0se%q*CfW}#Qw*+LoZ$VNb(b$tcfJzsA79z=T-CApA8(2m1Z= ziiN(R(0_fy#|OhagZ{#TzCUEc{bMxpQ8xTP+Hfh*XE0*w5A7N|z^bQt<&t)cC#t*F3nYH!DCY-Vp_&gyRG@H7vMpgTXb zX=m43v%Lj7oz%O1V6O>)D57b_+yB(jS!W#q6&qCy`wn=H!B+}8&1-C8@8T>(MfJ4MKVN_1Y3^?Qua!Vfe~|?x5b*Q_ zz|P7B_^-g6tu6i^U{6o}1p9-oKbI4Hnv7q?+TGk%ThiJN%4#TT!W>+joPvL>^M5`1 z7p8xLYC4%aO4!>$A)ST)wOM}w|Nijb0smO@?Z4LK=KkA~zdiX4@`(n1HFGC>TbCyu zYJ#ktg*gNP|5f+DL%sbMm@xYjd4B-?-uv$m+W#fQ@4f#Hq3mc4<%97PYQpS)t?+x_ zU*iP%pW7>RmyuR5J z6QA?;UMleUvh;+VBeDHhNm?3Z>KDmZaguVM!;q}WJ|YbTdNJsK4#2_9`C138ZxAOM zyu0(u(p+5S+byXM;o95w&Yap!ZyuhpDO+xyT-dxW-MkgF`D|0#d@wnf>ko%QpZ!1o zpvKka7^|-5K*UiIh5es@^dc%Ool5>kASy;L;AoGcVCOX%{{#F`=#AjAHvi}J{6V}a z23vsri>*?%|9~PWE!bCr&;Bzu5Cr-odz*^7CH_Y|M@ebh`Jc!g3OySVl;Pd}2aLG?kr-*uaJ8ST z*P8JxdONueu+*B>vKlU&@94Gs4c}PQk}5M`%}GC#rF=5$P!jW7k6g{jG}@b^I`D6M zHCW;g9v>vraZ~u6OFCEtQgc;fTvG;aHuAHLM(jKb?h>x2iaabS2MB-D5u=ZA@>*|S z>AL(h&(m9P+vNZerSud2PEfW4>}tVFuzuC==nZ}l)dH(qQXkDb+`C+V@!BeDx!IYn zFdsOH16ZtB)nWgJB0bwNTqJ^T2O5vrl)jt(LU|}=d-AuM8%eub@VF%DOCITep&lSb zXEax}^|D@|)tp~`>Ba`O?}b0y`+b>_OqhV5hL1N>O@XRf zLU}v3-@xjmT#I?XPo)2xfX5|ghvRnwjgk-=BGZzp(5k(!S)6KzxID`2^pgvJ2kSs# z)^FfE)b6|mwQLterkKxl)mhKUw4F2krUaslMspwEUFrRc8fZ(Ke#Crk!V`{sIv59( zHV~})H}wnvqhh3CjJaTD-FozmBVe%~Nj#K<%?w5;FP@rOf2YzR-&QC@0X zPil>^D7T%i2=ZFS`5jEfNC6HrPjZl>V5nD%cot)p6JiIR|D9XeqR%BGvDoDm$a_p} zC2YreYua7@Zq}p%LRG0O7+MTA4=1s&K>96$i!WsszdG@H$NVk|&aW`oad6wx=`aZE!=XD@uzW$LU=eU6fqaMogOA)$s6FQ^uZw`zu%H^ zt7lC9_BUhs5ru#!v4U6i@8$=a4V0R96b7A4h0zGkkRby5FYgW$5CLd$e@C%Z?Q-a~ z==H8<3Qf~!2BGDmy3G8}w&}S0xzFwLxYovjBoO9ptD4#^~aIc7mbSmbZ-iQ)yUTsE|YHySGgLlfY`i8ZSa*p zwG4&4hP@UN=8vP@(yNA?ydEfx<~VQE+v}_yPHR>&ptD~kDNm($D~`J~&FTE*G6|ZY zQR~)FR2mYGJ=21<4PT)Bweyhm+{CT>v`=mAutKZnPfe|%vxj;os1M|W8%PEW`(8FK zn)^XHL}!^t>mdJdw<%)zc`?V@==Qf3}hlB79>Wr-Y zZf6%Oi0zxe?Pp@NO}F!hnYym?<}WHTi#@DVD8PlK_-xBx3!|UYS{^VsTrG!KnzC}j8Zw(`YfI4%~v={e+`)Wm>Qkr-`XxgtcmnnUo+a0aeRMltXRo+nj>R-5B zxP%NT>F*x6wcgGxCY+e5t!C$`29t%apmvGkV(~~)T==oJw)Eeg$`KGPTx@uunN0*2P zx7K()Q43p23u9j|ldO`)eu+lo4=`-Lp1sU@__qRaAj zyjUfFbhltGSWg`v^e_8`3B^Zd{Ga#~)m{$L9kHik;`5_@1PNeTt?``>zCJ}xc*A}( zVE7PEUN&2EQDf2gE@J)<{x`&S`Y_=Jy&veuT9k8uLJZI`E6g@Wr09`JN)K zdCCJPysiu%h9B>S;ST}lP7C;-_xWv!&-;MUfj^>pp#F|YdC#)5Iz(`da$6oXGvT8Y zJVDS}X5dSHdh#N>_DH1^epq4UPGTIaeuDjI@fFVU9q3$-Yl}nA$h{ph>62T3t>Odg zj|qLC9$?lKvH?)-X@0obJZX759Vp2yd914 z{m2735#i(aiu9V*^K*miR-B)1Fhgv>Vgv2SxmF~lbt{_dc2}$LZ=XEgP?KNFy0*bS zGaL5acs*dDUp3zJauJe4cfEZw02rR-Rai)~mz$Fax&B(#!tWPQlid&`hWv0U^7#68 z1-~`L@M~6nT*L0cc-?}`7(>PcuUnWUgY!*lB1hj;IssSKqvA(W*I$&ncGW*Ef`nd! zQa?#-M>A7Fg?Ztb*9O%296qdgCn8`H!947?J}}+Z`rX!sNg8!Z!p&7l;@xiwU)Fnb zqA(84DQ!xS->C5Gu5M=Ct00wM;iG_QX<|E#cUrEtvUhplkE3P~k;l6`lI8b<_$^04P0703 z@A0-f?R|E2r{xV!;v<7^|8Q2<1BRJGSMBH!V&eLs1E?KLzEq($YCA1;YqnYV)%2_G z`If_q;0hILt&Hi13{5S4uG=nvZ(Q?^W?8>XvDc7|K?0r1+$z~+if1loN_d9xjL7}C zNLQ9H<%591DP8a-H=@zRcOfkRHrvRhtVs617=2-1P=i&wIIXLZhnR|{GP2zky0 z0xfpWD=tv6ydIvsta5xdJReYUPCxK*HO6Dm)B-j8bMrC3w~#EPIuwzvI;w0Tv--4j zs`cUAsn5$LS@u0)Ue0(XjvHQaV@cP8Fp|^NmW)X1qR+Q|NM?eW092mpPD#sYf(U%x zU|m5ITie)dX|rm$k7u*9#g~LU_xg~!qDw+EI79oaPd^M}$tg);vktc63u0+0K zZ&KG@XqEreEr#YD>yBz2L2R_6q&RWZr8YRg|8&0%9zDI)pW!xQb|XGipE)kw2f9e( zRlFZlb{hh+LmEYVDZ>k}Qfya@xhtYoi&QkivcyXZk{9t?~L%yknn zpbc5Bjv`Dg_ktoo37ErzIzMmVx+As6U$Y!;sc00-GD>MJP>LxAO0sgG| zVWc!2Xn4-0ewFkvg`H!GGf9zWo>MtCt`Iq!0J{>oO*5^@@C!T%CpKjch$92 z&(Cj-n*6OjPQggPeXZskD7qVVb8R9>%sk>CK_QnESzEw~5KcoFp+0=DMR!aE9 zhyi4Rx0#Ue7x7|_YbA-m)(uYi1*pI|bIvDs(HqTa_)I7+eXU{e2|`(9{92-RqthCu zxG+#bs2b4r-O#!rvv_?<{~&u-zj|TCS-Ox)%xc!IcF5jN;`FJDL(l-Wcgfd z14qv0wk`?ZHQa5TPwbwuZ&`*S06|;|)Ap_R8?O%6u^*37Wu(zOt~$swc?7XE(Bs>9 zdR<504X(Mr-tl9dRBkUdq2Ru@!n zURImb^2RN#=u+k8r;nW0jDtz*s(|c#`4sI0*LL-wn89kLOol5o5z8!;v|HK;S|Hr3 z8dn-`bsKIP@{ZTB$FVAr1d!iccb>|R)c zlf?1Xl&B#T{l-V+at36WrU$kEeL~!zPjG?IvmaV+74Jq4tFon@Z|En8;OXEUzhPOk zy;>n*zVJ`8YuihTT>`UA1Eg)6iKyV_mm<*(whcpho@9YIBYcI1q!o+YTta{wmewoJ zg!6NO*1Fr_oDj0qvXjpMA8Xe^_8zlHY3L<9|9;!!P1$3ru>zgf4AIJr3^;4%su8Fc zg=#0zJmYp_M?J8lS8V#zemYXTVSu%9EeZVXy((5=5htJh*NX&G2)oU@g{~S+yHgrP z9#Cq2-f|5+TN6|{s^31^e&4xdP1Pcx3{%ao`^H$ypI^}qlvT967+-%AskJ7&Zc6D(W= zlHVCEM11Isfkv$J)7ynvnLbaEEV0cmX;8JS`14u=Gp`79XdE->WtSk>!FHfZfEJ;9 zt`aS9Pg#SmAbg2r*Hf*7rvLWiFgqeIDD=TIt#98db_HVc>& zTo$0#%J92;4ISLa4s;R0Rqk>ekl{eR=-o)=h;uWV~u{HR?D5!5%nThl&e=;yPb zBI@6ZvBGKPSPE8hNSioIs&elRrFc4Yow#5xISA4}9b{yD1wKEw-A3$Sk>AA=uAQ~5 zRP=oqmDR!Hbv>Vsu`8|gjMSberG}d4h~j$ zAo8lcm(?8Ev4_md_Q3!o@UsjY>y$D~y}7UKdy;VHbIc@UdEK`jQw^RHTi3rge1n=|b zMW-lQfGh^(#WnQsnT*ME){xTsXb_+NMP5aQcekX{voui>7wb~wI81r%(XdE)3_k6# z@b;k5-nGnY-sa%GV}fq=k;4TkliXu1?wTGyQtlEO#__gt389vT2X4G+SV1P`B$y9> z+`dDn1yNi~o5l!vayO`6z5=cJ2}U`08t=_Q1P;@uB9Q7+Am3`}@1++_GgB^s%ARTl zF{Z?Cd0ZCi=po*k<|z$6V8Tx4iCf;J2>_o=ox2>}SFNTMTvTa%<4(3chKYSyaYnoy zdv^Xgs9W3H;~VyX%rOUc_OhR{fsLBz$U@k29^?k4a+Kcw6boIG!`k1vlJo&X?~KYD z#$-t9a5+9teVdg1WmXUNnkznkTnG5|36Pfy?qqb1b&YkF)GHwg$|b~r(q$UyoK&_wbE_%LRK3;;H-V9mlb}llGrWwJ^*~5c0MBJzx%l<#O9=G z9AkFmWn1-pMFTB(@PO$cRh-fz`hw1csdQ1zGM^RL!?Hu8SDUW_$jOwCr((ykGkQw= zoI;T9rNbfkBdc0JU9QB+NY&{+gZf>aP=_mi)PxXc6tnjey%b3)Px>TP4|%IkbO zGV!Zc9ro(+l)ZG{>J9K=1d=$&8=5Rty_k*W9`wj84H+#C)3h$kRZ@gAoIg2)W~2y3 z^plKNcbs*faw_XnnsvTnO^WH){?7y{Vv4L{vhxhf^Rv>7XOZj4#BUK6Z8X`5;SDfO zRjibwYPxx#S->tu>pPxBo;ikyA6sYUq!fgr?=Ju?yDN7JT7#FkcJnwOz<`^T&dwUr zS>s0M=HXMUzu?+`DQst}hrZhIGK<*O`jnP+&*iIP%WXYKin-52BMIB#dOdk~J|{qc zS8`b(^ZbPD;Dz}gH%TeX&>Myu5_CoqPAV1lFma3y5gA{Ci{$?HRGU&lz-Ek|vtN(E zLfj*DK^$X0*OXoYodV`}uopE^(;Gvdb9X+!{L!F%3dT;2PU^lueCwrLhk&%~2o(G% zLz=|z5c(#ik>mSAKM{L>Ic)uu5EPi(B<@)DjCHB^xV6(caGej*?EyZt#}P|0ag^af z5%V-ZI$1p3GjeRNm#GB8V#=eP(;^18FWqR+M~zgOBiTexOd8MzCB_Ivo{r^Cepuf0 zds?>Y!p2>I64M#lG+V5MO|ofa&nETd@b>~DoC~8Wz0b|;aHAz`mD8VfnUBX}oJx+7 zoGy`!*Heg6NUXD=M3o|3@1Y0qp{aEJ;P^!sZLDLGbxc9{(Tt)0Dc@1=(tXFKKkK5&zBs)88lnCIE(l z#hXWJsiP~W>PTPayV5e8(%bir{3635563b1bnAYVS>-+mIW&F+o6a}&s{;NAnyd)< zLArt`9kSf%Q(dUf2IWo2U|I1Ki&60DeSY8OtgJ5;^KIHe)lNn zDnvzN;`i^#cM_aw!=*EgcM^{MK6$=$IjUQKy$f6oD(0oH2|>M^Sci^Eyb2+&iHer% zS|cLjvf2Zpp3gri{584~r|TI}b1MHcEgR%S-yKr7k;;WHz1^#cN1Ovk7@(ZS3q2sxkvYV;JKkBa2u&74DP@sZnVkJs8u3g^1yb6y3f4IPOsvvMP$*_E-x%vyk>^%&v1{pk zF+G*A?bHtqKd-I252nH3Cy~5WpTQH?51?tQvokLVY~Y<@yj~{a+m%H<@BWg2t*)Bf zv=Yv=VL_?-K}qlhcbkhof1eW?pW@4$XqhJQCNVk|-_(zF2bl&Tg-Qgo)4Mb5K&3$~ zZUS*z?5SYWx9oQDO)<6>V?;cYg&n54nOOK`GAU2S@$ z1fW%z8baH0849y`*4ZAJo0U|zAo+}?loB%mFGinVq^~!9bI>86ik;=7BjA}P!BwT9st)AicSHJIO%dcu6vq)JgLql>@#La#0st*eUVjnVs) zK~II2mx>_*AqCxg3El$$!)SQ73P5rz36z5ipi7h@Dy&Z|EF2@LjVh^BJSKw^ zXAH+-^(_pNqYa-)_+FFWksSN_@rST#zqDANq4qJ8;)kWX>OU_ON2+1M-q3_f z%8>K#Yv8hS#J5QrS5*}&(H{Fsb5oGz3Iof`h1XX*eGHUyTLz@8SfkZtZ6o6vPm!5?M;&m{h&ny@sPPSo zwCrnF-UxhjuB!1C?<*rX4{%w0xTpnuTCD-H16*e7*p$%iY^~W$)4URmcQ4ABO-i2f z86J65Xz?_9YPIil8bE^-oUO6J@Af-8p5N z^oBm`#C2vf!Ff*fUX~;p3vKM!EyMi_#0^*i@UdmOSW5ZcO0$T?GXhRHY`I!k=U0Ch z3xeO28tl1DkoxQ5jaG|-G=&lg%gCk(;6xg?TUll2AVa$2+toS!Brp$lH<1fj~IInCg<0?*lu@N*85F6EK@2NaI)U1+h@a#KKd;c|-Y8XJu|t z`kW`W334K9Fg9}LBgtpT>jY4P8eRgO73H7-k+wydO%MApvrxC}o(mGg7bgP@OX(GC zJ8|=%Uzy@0WNtw#hukxxo*A1Zfj`dukj}Cl+;Xfsdg&CF%4oq{$kmNy1Y%L#f-|^Q zQe)?9 z%N@{y4|PzcQh4zrf^2kfW>Cjp#x|9KK%!vM?Zq{C$rCa+KxhpOzbMx1sgUA{L76y- zqV6~aAFN(h*oC&^i`)^|xNYwm=06H066ltmdkaM)hgosTerr5vxbFICC25TF3Jw=* z!YZF4mXg;*7^Ph^@=QwN&CKeDHCEp*%oyHr1o$0yNp>h`z$K zK1sNjdAt~$agjW>#v1hTl_t*gp6##K*ztdTQldtSLa{YWdv{(`M` zk20tH*Q#xb9X0P7oOfiKCJAl2f0TFywb00qpxNUii8457O8!y+S@;YmLbte^8tqw^ z0WouOFd-bN=fbL(i7C!S9FhQ>7LkpWUUuAv;3^=4yF>a|oW_^E(W9Q;FcMAM4|V!%Lj5L^S^Ty8(dU{%Cy(zx^wPV> zJJj8V8>J%Y6P;fR7sh48b01w0g}r(>Jj$%-)G1IF&zUl0|J1O*Pt?Ufv#?PxKt1aB z>xb7>YmGKa22%sGKA?5L?$BhKhWH43lOPJ=xGCbie(?Bt><1bBFn)nYfqIN##FdJO zvQ7k?c;FW;NuRH_1HdN!z3&|-$)R+01VllPixb0P388>GcVMJOtuQboo%3br`I#rp z0d;panIvWe(qp^KiahSAXWF4diW_I|QH?>ja?6xiFBjs9yy!FiL3 zH}))M45yN$49d=Wx!|PoU00Wv;3}L~6M$@YVt=)nrhc?9u#<^jW<(S_$mer;u#y0c znj?E^9Ly}MCc9$>FI&yGQsnNYFH9AetqYUFU-?Xg*{dycQ|%?Il)>1FF#NEdB-;|9J?IJ%@aNmVT| z#bO?}V*|-?^=G+}PB}N3NJ?zJToA}oIQ(8g8SW7`8|xVP)i*p! z#C*5tb(GmSFVEN|c9jf6=IgVCoLC&-d#!Ses)PyI95_)xERYc)j?*7QyP(G}#V+6Y z!z_L*O)#b3xIvQbJ zY1Lz+NOldO7qC1I?NlSW3137kNib{P@{v*gx?<;-W~_oz9TZd^20l1QO{WpdGw?4J~SAE>FULt*k^DKUismiA>RBk z8pRweTDBf{Cas2ftM@a2(L`V;VEZxu3;d|IibAYO#+mcR>krnNLZ5>9OkS|&O9M`d z_g|?p@k`<+oUPci8sYDrl{eA4+`0p9f7IZi;%DX^MIA{TlEP6>rRFwT8l1ov=bh*dR4lD zJl)hL{KG=k6xG-La=OPV(-pUhHm@&?CekVn2~F6Eniw>*3=JZr`2|fikPCEab=&HS z8dufnkcv+;4=&nX4TnRENJ>chEN+oR2~{>?|c zQgsK?XOGSfvCf$_Su!i6cH?n^1iPUKEkYN+sIzeVdUgkgZ|SR&rL5zLF$UtYchVDRSZpP#Fl+WOZRDvk$R+wT8C=MUisu;T z6sx`>r6s{9N(~Q+dwo^JsOnMT*?e$TyegN+kSIaqKDOHLY2t3pN~S^j`n@CQEq_>0 zrfhl|4Z|DKO6NwPEd2senn4`c_cZ|59PYIzX#3`y$oT2~M0=)$ks4YTEfuJ$O(8V9S1&Gix`60n(b&x| zy!6k)_X#e_ZPQE%IpyMyLh+l&EsA36;%EVpCX3p1$S*lP3u^Jnx*BAfUow7=W9Axc z@IZgeBEhvI;M&}$i*?mtfDG_yCCwS854RS|P{bb{I2Q`6qsh=9vX7C4-ETh%O5f*F zV;?`q&tSOIe-`q&Wjl{eB{p|e{j(>Wsq;e?;H zY}1Bg@519Yk-~JZ6ymG;z9ddWUC-qo8+iLA;NaED$-mL`_(r{9O(f9cxDuz!d+Z~+ zecnoaA1&MJHWMCV;uY*+`}!i(Dc|-!eKoQ~EwXRiW85h)j;pRZ!`u;iqu3zC4Hd?l zhO=dal}FHYBeYCTqri)Z^j-MW9nd7)Cb8UY5Su!#hco_q>_bZmSqzO1Sm-09M3dA% zB{{CIAB9vfH$i54S0T?QJnn1wY#PK+GfTPb=bL$-&>NJ~(Hwr0Q0M96rURENcafOw zi~MoReZF%mX|ci=SUh-_t$iM10&~02TDB(E;V)6v-o$y)$jx*Y>a zzxdIcTEv6wjWg2|Y!?Ap)LzBkB;Mr8n+5ljY*BP){2<^Bu@QI?e+n%*;V}JdPZHXy?sbU6HO~ zvT*uS6(0cmiqYFdL-4_vLl2}GhI(QRXUGo_!$4!EvDb5*Hos=U06K<|F>E*4i6{e{ zYn%794N|`+5Pdwq3%z`CqfK%i+waav&rvMhibUk;3YI6U=-^Y*gNYe^hBO~sacv^9 zZ8yPW9V-1S+9_SW%X}1-c0W$T+eagD&bb*3$?r*&Q{Qu%QHgDd*`(2wj!9mzS$z;7 z;)|&LSUkfDspOp+^Eje3qG2=c{7~Gjzc3Ds)4#6En7%DDqTB%5xo7%X46qI!T{EQ_ z=s~jmuv4VMbjQ0FyJT49;@Ws@V}@58ckYH{iSE#4YkBmQZam}*@w2q*p)BoML`cVU zjyCb>a*5@YwHNob_=X{S?Dtja#6a8OI6)eWeJ$SE!-{Adx})YMIH0sEI^hCbT74wI zml((NHpS7ys;2Uw@v(0>pGc#wkBO_QPtkcZ)=j;W<$`t9pCr&*wUxN=wPnDu-vq<6 z)af|60jbYvt|dg*a4h9KrALrf*EEXD69fnDcZ1%F3T~I#eylnh>cnGL^Ny@ZZc%z6 zX747PM)S7iZXJ-7%r>15B9|^H(`u4wE-{>Ep5Lg+LMML4&2Btv-ANG;(*W`$p07Jn z4iUi8dd9*Tta6jVQ!WT0#JbXc45Q0T*>Bh_y_WB612cW~-Te98qWr*^oVs+)rx}tX zmNcs=s8M}T#kzQS2g36D*tOPWC$~DnYZ!idb!qnWZ!B&kP<5+x>6?H0vC0qm>?j0~ z?qUT!Lw2VLa(G53T^Rj%*mX?+OpX?f)Ki?r6v5qkbXBocrYNXKKZ2kAeBZ#%D{)d8todV(a%LlvgO>j8M3X{nuDRN zWVbw!Fzba#&)Vmp4i4f}rQyUNtbwVs2s{lLNE^nSA9&{ZuGPd!(7J zJ39NR-_~qJYcN$g`r4F?HJ5|)@Tq3c8%qo=Q4fo6t6s9q6OKc!9P6WU`VYe*u`&bp zz&#?|k?#@LMd@QO(irkax|8nRP3}*%!b8y_4_AD;@dLkTLDqfj&0DzpW`U0-6CDu>mJ_0xe~uV%Ta ztozdBMVrN&<|J+!Dbe_rkO)*xn!@+;9dBrSqI%~MXofvRIJJymDykok&zxy{`b zk28zgr-HWHE6%oPR7)oSt@4;;r~$PLjs5X94yp?KdSMjSz;bTi7eIPd`8}&?1;X>Q zui<$@Z~7Dt&#H1lXBkJ2Bm z&}{cECb?vWaf-PkX4>pS%Tv7(z+~JwKo$AQSW=V~@38gpfw0z+g{dhSiIY|El33_{ zgGMLY=#iQpEtoFIJt5*(iHKZ6gAYM@3BOV~n!eCv6nt9BcYrtgNr&63C<1}QCa0E& zQLCd5bb>i&ll_`6M=54(sxHo&X(C4bWh%&ow5bCQKVU2M4&x?iCGGWb?4*9)CExJS zAwO^{)nakeJ079wBHRAfFutj2p`>Lr39Xp5*bjw39te1bAmt=x%3Hm6pN73H7D{N8 z9ili&5g}gXN6+l=?cFNzF6CKR~e%K#c41&;K+iw8Tbv@Z?MlL z3KB#K%DdPGKu!y^(4xz^Xlre}%@>~`TVCaUiV##26s)Ti?uN)8mrplFtphllzU%=2 zlbeEltMdIWnH6=Un`{#Aqjo1!)QD5XnMJ5R5Rl{;>OQ|!7*v8YoZY8%Hlhvyfbs_1 zQ1=D&#+L+`n;+OvZe^G9I{fCsSoz1hzIliB0hde#poUFHZVu%JS^{|1G!*Fy+OQsb z5U|f-dI(*gj0%hxIJHMa!ej#xN%nbkL(8rwbmtLTP_nGfvg6fBR+{!$tPkB88KH%? zTABXR6mBD8&(?*$jp@#F#3NF>s}}Gv30KP!gFRp6=N}So@JUeqQTy8?d{N$%+r<(N zEmBECj4-mY0-Z`NzcJ)wED%~lX0wXSpD5qt9ZUJ~g~(R9RXlKkGx@CU%{gQG+I_@q zTwEK6)hbe7qIpO7vr(%ndROLs^&%+Pc8==&(X=O5Skaz4EuuQQkFUZZ-R`+9Pdof6%bto)TuQ7SdwnJ?*k4z|ubN=zkxyO?9UYRT=alp!CSF4*L zh4h!2F{>gI(%~{z%MUy?JHb0eyYCIthI^QsBAq1a9^` ze1wveGlX}}zkGbT-x`NFDS+bjoS<^3oe*tbaG8B?J(?@s_D+Lyr(~F>Z6eNzN-&Gs zuzByso$kn?GuO!*IfpfeuCYIf8dqoL?#3|L+(`Fo60mG2)!;JFS0J_KRis*6`|=a} z9IE*pWU{wB?-$DkFH~gqb|GuAd|fuw=KD&nh$uPYWXwYR+==)H;B@VauNRpQML z^%n$JMW}PK288fBOy=`}-o!m5DBCd;g{SjsO4+`9rBqn92NN&FgeT<@7Dc4wOkl{7 z9n;+N)RZ*`F3Y$MU8*P!P}o?1f6|wvFHGQauaV4bVgA98Mp|L;zB8%k4Kh^;O&&>> z@5-)dNdaMQPaxZ-X>k$QMc%?bbaEjrOqe@tuPr%nAW4^Y;~aq zM3Y(Y@*ekH_a6y-h>7yt(?p+k(HB2zLH=87>!!|ipT4#)y(W2W3^9!f*@AeTuLP9t zq$Bf73z11Bd)`m*{DeRxa%s&KnelclEj#;^3R9l|kMx;j)og@bp|)gf&|_NP(S+28 z^baF<8hO@SaU6G)?*JmyJlr?F$S3wphk|A5UI(O6V&VeGy*aO+Y;FTSc zhK@8Ws~yr%Eg1LW92)(k5FW)SQHg+Te~0lCj})v@SqW}gqVe`;cnm9_#qp?0tw_Z5 z;+p7s6~7MKGv$q-x}YjGFr>0LbeK*cjD_|-9kssFyiR}9JT1?eis0q%vR5t#lXHdHU`7_b4;sFy^}3J4U%-`+Ekq*D zH?Y52+?OH5(31p}Ej#>v#<&3iYFeg?a_6&y5wYqlDe{poGz5a zD@lFSKQ<8WZ+-X&3jj`nb+vlczsV4IFmE{1Vqhr+Rkf5qUKg3Yr>PPh^^w);ovCTT z%_W?r9S+0T9fg?u7LF55ZY#S>bFQ=-Pt>_{2bw`i1J}913=tE@9YEfSQt}8FA!LTj zK{GOUaekA|g0ae4Ft&n@lOze{#@$;p`&r#EN)9}M14sTh-v#3V!H!8vP0hvL(hEF< zeRw975jQpu$ zOGOnnt`$}Ld>evA=s57O*0y4o9A$;&5$@G`FRaFiw0M`79@o4j-56%M+|ok_jy`N8 zPu>~REbDmOi9bF`$3q>V2$MWHI$BCd&`G=PI%%pVB;vOr8;_2`as!zR-7<=l#AWZE zEQWfnhPn(U-T9%(%U6A1ru^md#|<@Ry0pe+jeV1hmtHUXbsvcZDjrOMf)pcAPa!wO z`~F6k`>YS~j|MsencRee{=xXV*SK8Wg7Ar|(yPQ>5{mtGL71@Xj=}-;s3@fBCeL3C zHW1eyHl<`Oau;*H;7fwqeJWF~xJ-|aPA3JMFfZ)lmttbgDOl_A817)-l#i=L_mY}P zV#G}{tl9mT`?W9%I@MszS!0VvLUr8h7f}JhoOIfCktB`oF1PBqU25x#vfo6b@Ua|i*fs}lu&h-yuiB_jEt zllnMc)`3EUUC}A-e&>;z^!WkwWb;97ws*D2Ol-38WtPXe?)u&&pLglmo!h)|p~$)u zb2wqrjT%s{)4hDT2UUY~^-C|`+j=I9Cd?L2`3KFC?sTGI$=}WFO!4CU!zGu$d^SQ> zdk_yKTPARG;Seh|X_%AQ-wPYQ!ME_vt=g1j;2*XK!3w^`MXKO9Kh%c1XIXm&d&JZF z)c6HKi;0rI{l3dWEH&SUs|4ax1}GvJNpvdqOy>GSW*RQl;+j$rW}!hS)lsViEZY5> z*?f@Sn7<&=xp8#P`! zX-}UY6zh-<=MGB0rZFa>annhTvJ6SmNjPdH{8_^D_(fbym8wQoMMC&{+U8~a8 z^Mm)iQCRT~%TVvNrP;0iAZOUT9lA-6-_#tAv}>14@dy07v1v zfZ>$|5{gYHo%}a8aT8v11^uHWV!wRZ`cYVN1=j8x*4RsW29;rzarO{ClcQ zrjGhV?z=o#R?gbp&Q@>k~q*|pzQ5vN{97iz~_8e;-!akao5>{xxu9nuBzF{3O%5zEmRA)uVW z*3X)kYTH^Z=-xKx(|@LR=_7>C3vM~fpQ|zEvBMyNJ%qs%K`crv!eF$*vUHULcQIPw zy^n-K;X4#Mnmn{5ijup5kE`u&x@pgOO1f<&=gRl*DbfuE>r;fkSS`8EuwAtz$S&h~ z)pdBrHl^dokv3aSUZhbwdBcRfEfldm#xNq!*Y_j`A}#pfj{EtB1k&)p5!#NHk4K&?fT zx2?2pHsaH{Djwf&RAASwCRlHvO;Fekr2F>ViVN0gZodYjTX;_=t~Y2KqMC0#dk)_6 ztkG$FqF8oc*3NCNCjFc(TJ z>7cRaD#F<=RzXD)Rj?I#PyU2p-=a(n3ZDB}V>rMdL3G8>qyZdAi*EY+{VbWtQc-sW(62 z9MF%!_1~=84VyGb&kyiVt?X7fbx+o$BXC23g6UAK+SlwXdabw&e;8R%XoZQcZ%ENI z@8UqbVbT~~^k^Ssjl7~WY^rLKgB6RK)#OWQb|v1nVfE$?EpRZK+sF3Uetk4#qcNW; ziv7~kK=jLP{U7HBvQ;qEZafK^XX^bO3r>Rejehrh)CA-7SqV1W##M%G@LDt9Kf?v=wF(XQ3z` zmxK{VNB+;wB9#QMVd0#t7s?A=Nm8W%g<`h%1_Ea-9V<1?c`kFDcQ)9h@SwE>(u5^_ z7`4Tu$H2PQ*-;*TwE&qBvuDuyfLvZ2=Pl)SXNTm~Ym`p9Q&&uKt6|ZVU4(l)x5>=& zM2W`5lSoPk%x`|yn|6nHNpP7Kgk-`ufp5i@_MCGJjW+EK`sK^Cx5Q}`)#eS%d6q;p z-TdK&a^A)ffg1ZBdi+T&ch%7ZQ~Gt^*ymG{x@Tgnee=h>W%#H}wK}(L|CbTdR@35& zjw1QBDbDtF&!tj4MyG(8*F6+VELcZanwyw& zu%U}?M9nCzT4cqv9BATLA#l;V`|wGSN?I+7aJczmeEt@0DZ#j5q}J}nEJBLwPTCf{{8w>r5}t1Ieeajjr@7=XPkj68 zYY%2FAKksdJL6SV>M?j?QZxtSIo+Cfcp7v_e&BnG#q4pACEx63Pjw_rA-MZ?%m3iZ zc^kqQ51yX&^pL81xr~6#AD>Er#3x#g)rL%a6;&7%NfngV9AqD@alL$OWy$ca%8wCU zqwn&qg!~2Kwa^zik_613ET)o2s8+{xL-O(L%k2oX=d{FWlBXnE z-bykB9*9>5jjraX#A39Twnhvm!f&XmyIxoE3NJP_%c=}pnpk`+>o3_fBzhAUl zBv-ItJIr*%^f@k%fR^%R8Ay?C%@yuPUjQm>3{Syx zwG*-0>?MA)509_~x#lgU8Z{?G{kogk-DWYDKmxEO-tg0T!NPsXUA%ns#hKUG@n%`G z6`X7!nS?ctH#L)^f_DR_=?z&9&%L-ZPK*#I{Nbl97Fmz|SXN>A?Di3pKu!n>0he%O z7C&on7KH^#3{Uln?2$dZp!=YKCCyxW>;|8N&{3N_n^QRm4DT#GNX3z`)ned>a|FYz z_!)O4W7;HycHfIHUGHFFF1p;8{|+x9feqxuQZUZl+H`0vCYz%df*0+i`8XJeJJ4<} zsCR)Z)4RhFvE9Q!S=Ex;;d>j|_bHg$0(N`OA%w=FrYOr^`PL1iqXm}jqqxPb^Bi)m z96(qc7*H`=Of9w>wp;riK6;Vm{!eBTZe!uRs2*4r-LfZrd3Y^eTOpN(k>XagXCs{f z2Y(YF&WH`*7ILP48}JB}ur*jP-0r-`?BmOLCxNcL*ILZ*z4-Mz5GAzq8LPZoxWO1N z!s}n%Tm;#HPp`Zcu<1|<^D&`rjA`caNFVVPzI^vG!MKu9534Wl4+8H|fr;50H-lwY z{Bg(!WZ0{@l6KxUb9tm+vWai<*N*3ycP5b_wY7W2}tXY%wGxRvx%eK;x&8| z$>p?oaA+w%+~9a^>E_$g*n24Ku?d=upRMEXk(!}=S#h1`OTeCLKw!c`o7IOXrup{w z7v^O1t*3U~#lj%dWaa`(cgB0*m_E)BtXrY{k%Ii9VCH<-(OuWICMbhd-&5jf1D=@YM#^jV8fh9Ra+ zXCE>j+{7C`tffFyj^>gmzCMQ7e_38`I`O;7%1>(H&srwdMeT#Rta*uHbM{P;%JgYz zn%~`g$|VSGH7DeflmRa7GsI`MM=a#%G5Ohz7+_3_62E^}g*=A|?)@9!KZhH}~UmDO2fm~c!uj9XlDVU8fT6%r=s{^+q~q0ikb z{;{*M^_^X>%U;ZMtml-;pmgrdJSsY&h~U8y@dtwomC2^-iuIiPbaSiAPRITd5A>Je zCs+T09jL7ny+-jN6w;JsN4cW5*{@WY!johcn9ZRIF zasFj%X!(#GxryMHQ3p>Nss^db&rg8wfsKmA>loj{t6gMler9A$QeZikna}teZ#VEh9 zP|4-_z4qY<4a-le6&WJ~=?%i%ckH+xRxgXOtLHV)srAj^3(n9U&QWo+-Qt?Ud80^D z;1+?AG|}fzNXSh(Z<0J~RSt1$uGMx5zEyNFST$kKF4dd@t6P=I$h~#VReJB?ZF^A z32TBS!g29kN>Rq~PUr8+-+UAwlC-@R`RL0{s&ku8?A3KiO;%>Q(-f@deV0i0UUj1B z=E+FJ>hf1RmwDkNMcQbRXn8-R7YKRA5-1Vkc->uIm%kmEbhfrwYS`q+KpS3A&3T8R zEj6}~{2p68&P4bEsbKeNP7EfyX6uZt#4QRe_4idR@EfIbpzupurNXJiXUoa^u275H z5c=0oataMiIUclW)|>q#vc1yQov2jZqN(BUjz8wQ8E&5BmEpQMEa$f&@WW8ihYs2F z__$nbKl^FN5d9+8W>yi3cL?PVWht9^klOeNL5U#)B*4W zF-wJx`>StcFP~8J`8|g|zE=Wu;Xcq>CDJ@J;yMWdZl2(@|O2*gz|wT1wSdxvi0L9MBrYJm&0WV zUEsjWUB2HfW~5JtcT8fMxURxQXZDnR4pu`DBEX4ywb8$k)J`E&W6b}`TC+fY*Gm4A zgqF3}51wKN_u*&E@ABO&O3vr*Sa!_ex=&_T8L$V^*M_ejRw{WWb;AIEFs`5Kq3dr7XBsAe?c&ZY(S+HRD(5s z#iW$N097&7%wh1Tw<`qtx5hATlUWogPQCSAt1#SA5E^(_%d0Z@QBBx>ks&2}&wK5- zPv!L$8(rm_ssifYLF_q09zS#jujQV5^~&CJqat_0NL8L3BfcUje8++Ou)XMRo%dA| zF;^`xY*-V^rb^C##0HJy+Qxm!y1Q%>aM|s!3OL(CStn!n1$aW_SAv)shPtrQ)hP$c zyBjaz6@6?zxIgx~jG_KW{+p2%b)}uUqL!A<>mFD8u@z4)Nqh)!kW0kQ|Px zI_Y6e*U9XL+U#SBVeLJ*Mz6TH;z8^H97FU57At|JJ6Ef)!revmyu;7>F)F)h^16qt z3?vm!O-#<~0&njV`1&lBgwYKa^L=m{9m@9rMQT-F^emzte!<0Z;JT%VOMf#h^YLA> zrL(-X40WU0mDp$dbxAbqY>wqJwWAuIaR&n(L3BxI9w*svM7&X+vpt=8Y)!BTDsytiOveWvwpEdY?;{~4l$Aft>JoB&KCbn!sOBaAK&;pC_jb

<*@5Kl3zFG5IyjyZ3-g~Bk)_9chY;3HCe~q%mRq`-s{GqK) zat9{e{79|daGRsMdfE1v5z=O~Tw{tLT+-Q}q35HI57j@j$fmVaw5c3d)p=oQrd1tr zufyh9?wOoU(h@u3mxzW4Dux*Llm$0{e_uA*s_#rlA z3}IhM-dazj$W6vuFo-w%yIe<)emzu~m*V(9D!lRD>l!PCG?2IPH7Nw0){>*2hG_cq z2akc`BVqk^6OXd6UZPSeN*B>bRiCj6X;gT4%rx)SeN~;Go*+BlNj7~jIOHfbIg(T+ z{Q6Y(3TE)PASEeACh_y4Cm|vlHs}eS9_;}(&pt^X6{VN%X4*W9(4mz{0oa1Uu!NQ) z;`}h1XZPmSLSxEqNLKUad`cbeh-o`Jo3xV#DI0WAADb8~z8aH8h^~91zQ*jW;W3#k z%%t#Md>o^?E^M!qgNa?S?xgdbcIOst8Ln{uY<714LRH;+ATpXs25BrY`CChZlPI#M z9h51iJ+{ae4hn3O*WK;sUq&>!-s}s$;aX&Hccg_Sf-Ur!Fnf?+7Z%BjPntYmu>ARj zHoj=)(zQiDoUg>XZUb%O!RUwVk*6~;Ke)xa5MGfP00l9 z^^}>`49t8&-J33DLfmo+ct3s>HIc^qaf%|nJywO5R(GU|bOuW*p*V!Z7cb2kTC?_4 z6Tz{TG38^BXpvtsRO9g`KrwJ&>El&gO56gH_mU|m|I8s#IUqvlm zzsnw%do}o4|6(BdGc z-V0;t$v(LLNPcOG)vO zVX>07q^ku6T#{pjc2XEY>HwT(aIP?4XpAsgJ9M2Mm*S&qSK)JQT89kVjp9s-FHu!~ zwDyA~VQ~MO8O#Hpj*+#aS$-KH6K5Bz&9!K0zXHp2^lB(Le{+F;Q{@((xU|hZKmg`y zzX*VK=d<}};oam9N*=3W^uTmqItdTV6eb3R+Jo(<*%gRA6&E>^qeo5*aD&txspU&rBc z@s~>F=82|0AhBU;-47NlQZxo5Kw6JR7+acj;+=C&%S=2n^9q{*UAb-m2KgGjcQkt% zzN;(q(uz%d(_l~#W7t~-AgsWMHp2*_Y%Xushy?Ypb_b%nOi081X+v63%aSJ2uLXTl zahXpw6?`>NI0;g&$eBUdA%|i60Jig;2G!$uAi-$=`ds}kvdUa=_kCz5GpVY!vtfLZ zO}`Z5qRhmr4%R{dNM+HQB2bC+DAW~U;wXt(-3^DQo|#mfVZ1nEjgy_(djfFEn(owP z8+!oY6eAFXQilawxzQRYKGGng-M%+=^=&+GzsnT7#unl|>5r`WU_&!qaEMZ7IDiC^ z3ax<`r3qT3kAGkl${rmxm`@$$i`aY%K^xg=+XJv^smfj&mhk`k{!O(#-4DGe^3A zmrZQ(Nrm(VkCBDYqwggsKTY2~*h@fE9i;iD4jjUUtA5-cMfzP&O9nXaG;nSDjXwYh zUIW(J-Pv_?AZCE~EfHOq_Cj{)!SWtDwjts%gpQ{TS| z3DWk$g)JYw_*H?+Ugz&*mQ!vtWfmW}jx0bwho6>5pB2NWT#d7GDqhAnwn&;sG%;?+ zOrJ6&(bAP_&S?V2G}!;+ma(#onz*g6AnKsd%f@}rj%n*9fobP59{y4!i32t1No?KiwAi~g z<4VP%`z7kvOBaJ5-?7qAw`bt3#)N_dedm-w_k%2*IN5O~H&sm=u^RT$$}`fG6Rym+ zz=a&W-$+fw^IGcnbB1A}(TNeCMwD1wT;tg;+N^(iEhdlsN|i%s<*XCf5P( zer+B+Hsya{7N3JP74=R@jnK&61W@`ZZAF4Edg>kGc*_7?e{l(L6}j> zSXoOqznlWMemfQ83b81a@V{)Ee`@T1PwfKqCkHE-@4&0%2{}{(5qYp=jZ{HqN9UsC1&ukfhr&r#*bS)6uR%br)a z&pyZjw`}ng&x+M?J#o!DtGUAXgRfH4gYn~zKq)s?)p55M>H*MvW#${j!<&4y>~f`b zT|CpVaqh6u(f$;WEmtz4U*XuCO(i)~wb$K|Q+s}FJ|N4}g;ckpQ}a&-n5}o3h>eko zatQ!uG)AiRX^s*TyHJ#zvblhDpvze}qzO#k9@l-1b=4*G9#YIF5k(D^tsv85x_Re= zV%N0c6{;m0CF3E{mVMb<0P0E00RWpA11w!_hvCX8`@RiCy5k|pN49kUSw2R{#A*kC z2W2&wrSoA;0D%7No=v^X$|hPo4|Pf7tL5uK{$riQ*gorm^G;8@g=$m~A`vtTkZ?2_ zCFW|#OilaByOB9w5O-9QLX8?XXK{^@F#3aLqPJx$0CG`&`hf5CZ!WJ}$Lt(CNcto@ zLyHrYS^)6q!I*!ZHA)dY8X@z_i8^qVx5|5a~;U+N;hFkXTp%OpGnT z9^g&2BGpXMsUHt8itbn=HF=&%yJsawKVpotz7|MlbvWo@T)%}A2fLXFg_5#h1U;(T zs<%n+Ip;U#hW5NE8x?k*eDs%e{`Wf&+D4>{B7}EH0u7}T0t(9?y`hshok#BA)bKF! z;&1=_{lZh8h*zZ%r#`Wi+h6Jk&~qTu5AoA3eDW{a|7S1}OvuDTcr%$*r{qH6#Shm# z1UNNB(Y*iE$^T2s`S&$kMpei0*H{i~HNMy<0qO&w{#m(f0{*w@7g6Js_S&P=5OHX| z`Tg0tC!i+_Pq^RrxL+#a|2^hED%U9_sLBx#y&>p7vUkYS%z8oI=|WH=|Nb&NBx-kB72Ds9GcL^Pzg!E*jKx1} z*NV;j@22?oApbfhku!+^iSa-I|U%YZ-X37M3k22*}?tDneo3^>M!a0Ut9%5g}`9GA9`NC6dxma zwj$qyO!^(t^tSqc>Rj`@6Wj*h9~>jw3y}DPO8liy{1JEm-4o~vMFGPq6hh4UQN_o( z?Y6l)?tw6Q8?voH(9!hqP-%CU=W0e8$lOMDr?_w-)tO^zx*vQWm12zhkX^BwIeHHu z^p8%d!R7vkg{vbkArY6Z`@=6(wd|GkULGWXwq6DYfi-t+A&3)CRl}t-xY#JE*;md| zD-H9Kz6slezXn~$?ESoUP54k06t%gto@_eS#)Nj)0NARo^N>ovzb5$Ci81veTOOhI zBg+v+k*JyL@LGg>32;#wBbygEgt|^7ai~Vbf!+|K@vfVnfS*-wG(3Jk88ufx4~8N+ zbrOo;zlT^Ub&Rnp*{M?Fp0;Z^-QpT$cNelU0xr%!Ylglhq_){YR<7h!?Y6s-4XYW) ztpnuZF3Huu6s^Cf2R60=Xg{hrw5D4~Cz->bqJ$w5@3REp`Wpdfu}%q4P>p0FSU$zL z0>DY&EH0OQ%1=5zaa~Al5V90|GQ9^AJ{Q_NwCaqBXE=VpKrH3H!~5@Z%f|%axY{-q zZRf>xA9goA7y#}T6gb--C`6`>0j>LJq_hj`;&T2h?B^2{KwLv}7osLN9ZEq(_t@|c z+BMDsNYc8ESuzs3zY=k_B@DkoYGPS^FjQXa{-rJt@_wY{#3`QPQ0&!oPS2E{Wj+I} zOY!jWpKpfdqdhptknaLz!I9?3o)5#GAk?$i=GyFQz(<~=^yicR_5{s9(o+k~&qx5i z950Q)k0^uP1f-LE9O!lh08^u~rP9qb0(Gc*oTAWvsNA5$ZpDHsjtf0^r6#XD*iNbW2^b zhb`fmD=TgQR^)(CV%7FTjZ(+bU&Gg}qsMxFL%fL8I!_xN&qp6mGRryA_~}_j6dkGK zmlz@vs$HQGS$Ec3YVjXB-IR9nrOvJM(WN#-Khs#fqLwFut59^G=}iEakV^Kh8Q#9J zYapr4N0c?}*`?efvHB#bw~11{5dq%*lFm#7xMH;Lb}^o7@7|?Gtbbs>{HQ~Bs zLzz&h62+J64m)2jZ;0ia9+j})WqRj9{Go+E)jlA1E3O27ET>f==((ij=!ft)U9qG} z-CfMpL5y!_xo%>fY}`xQCAx%$LoMQU=`sWb`9O_;K-?@~eRXvrW&8ay4Ir5r2Q&=C zL%Pqo;YDhMsQoxv{0W~1Jvi?1puGr@9 z9X^%xZfh3U-^xp(A0&S-3HeY?h%-YbHvA-(moxTN`|V=f5oF<(9}@2}X=FSVB^q_L z!Tz9UK0>XG9TR3KTK(f`bmU-YzpC&<9haaVf~+)uwkS~t0*cR!Yi|htn3qcsa-Xje z`-*68C!T4G#!5nKT2X}yDR_-VWCfH0IGs#HA+)G2@?bw=m=(io&HI~}j+hoqPM z*t}LBU0F*R!n;2+WoIcCIwx4=NkP@HCFUaEmVASMIdMJX;%=hhq|7PL66 zvkW@U?tUk0a8ZjZ*w*HzqGDIC$%L^B@$l;?ap3-@*;c>0&QJID6yI~3*=$wAeF0*y zadEaI0C!jTNoN!05x&?3d*u^Kd2a|agwsN1rE+&R9e05@M^ixZeRkk}sTzWG+VW(h zy1DWY58)S>Yr<45nH%mKKy31(Y5I(9y=-zwZ+D?hdmMF@N16T)B~W`p)EMZq)!Z%V zwTwOX0p}!f1=gZ?Y=67fu-79j+%9M#mnZ-kjnRiiRXdkp?5Esstw|3~+B4K4?~b$W zY{otA-{`{sy%g{u;)znQSGv9&NZi#E@3J0N_r9fP?P*&8YoG{>;>l3_;iR$R z#_0Z|-mestmFzPorJH2J@Cn;l*tpf!Ig}jw4=;ONg0^E0dI~Eb9@J03!YeCQ!##{g zzQ6uXNLhQO?d~1>KtT#Wa16ZL>(bPrV45#rB#3Lc4Q@81n_U7Lkv>Or#BXid+cUZj zu`kdMkQ3?tbzeWZ`Xx*p1qNpaFAaCU=XvGy)EauI9^z=)nrf+|&>HgWd&|0OX=aH| zCHe&cqksZE-qt$Xdk#O|Gg@*ITke|suIQEPuQn8 zLg2F}awp2$>8%z|E-*AS1mnfhE49x+g3-FJzP|(&!btXvDKy5~&*z>OCqlgYl0sFPWmP27?y_y<3 zpVxSQok};VcJbDA+U>=v&||IYWA?KXt;jw~;S)=fqLWc@@+(bW+^@k%+-YEcy@raq z+LN}LAQ5nE`$|}PZ8MPe#_gm*r>0hG;I*kvi-N-RB9 zdpCCX5Yl(#u}}}i`y!Eu>4%_04&_je78#|}40QV(URzrN2UXAHNFB-qL)SA}C@}^-KTR|= z@Do6D(66r-yOym*!p&KPYldG;V_9e}qyJ4qBxxcKraNnfFeLiU3zI?fcyW#{;H@4^5uqOpT!!HTeKzyS*{nmVG`t)e80U(hR zogXD2_{@vHtB{rMyb)1EE#T0B3HLj_*H70oF62m1JPH^aUzPob3;?4|q4v*=bh^Vj zT|dew)~cO!p+$Nm5yCi(5fvoIuV zy?Zs^{S0HRn5>a(&DqV}A^q!Fx>hwYxNW|jf?6J|y&qke*n;~CBcMG@Lw*Y-8C&&! zzi+kNgPq3hCC~GvS*!COR`p@@GNePFXcS&RSz3w5aS#%&K=RREJ(?@2cT@cK_|L4t z=wd`s_ieX)SJU*eeLot3W8rusLRvrNDB@*>b|>%xuQ5f{^&2vq-KVq^N!;NwEu+?E zDHZZkMYug^DPo6uprdUEQzJqVhoQyW+T_qJQ2UCG&+r5dnJGpF<6lirsyEX)8MB_W zAHL7R^C^==y>?ToFe`;@Al7p{|CI&e7|FJ$niEK#VH7$G4vD7Zdvf{V#>iod`t(_?n+!jh};{Fl@Z zo?ZX&2@PktRs?7}2-4u%tKui*wR%~2PlrEUaV;7Hea|k;Vqa6_dG6A}4M|-|K<+fA z+UhnVdVW60c0WkDj(xIK>)DZQ;IxHIY#A|%v8XRH9Zh-lL( zbF-JMjSbo$USQtK5*h!^wBSKO2rB3}K8ohHxHgni#8kNBFcnJWujNkZgZF28$r%7t<4I!Zq|1q)SC|`ShwS(nWp9S@L|l#KS{fO%9KDao z|DZ<&K@n%92Dxy>5;`8e=&o zZpuxgzzSXWToqr)QmHj#y+A*4xRMe_(fNLtbc|n≫~1*l%=;!EX8J7N81PHz7no>!8hj@NmyL;_gtduV2))^KiEMhRYPIJo3usyR70aF9jX zgC#!|6wpGC$^kGpC|nXKQuFRYQ_`S5p{k+QDb~5BE`LGfKyRTZmsUP`q#^b)umX>| z*A>dO&-`ZcM9BK_9|{&DYJKP$SB907r~O_BeN`J3P%-EJE+Eo}r(lD1_aWYHNj!xY zx#T<7SG?JOumA{gNU|)a&73_@3vjUuNSgzx8UB1Z^3Zy3L!C4xjul~Z&PygWw0J{n zO7cv8B3mecUGubSJ=`@)o6kVj7(otjg5>IV+^?kTvAM0roQ8yb*xLV2JTx@d&<4aja{pYS-@U>#PI^s4KH zB%$xd0m8A~MQ_2R zA##oBtBA{cS+vSLt&F)p?^ZD2ymrlg=$d`wIn|KuWYx!ahA08d)OC^jTI4ocNCDpv zec$Y*8G~#z0WwTER=d~{>4$6@q^GM(J=(!?88T03!q`eIT-NC6?Kc0tMEC+NqM#Kq z=YgA$8|5&lZa7ENz9dF4t8AJu6b&!q9h>+!LLk~UL za*WV%mc2wOMQg@AUa3Y2fHo?ut6t@|E=n~Zub?p0IY+#MaE&{|W==vM>O4+5NnU+Jr3JhtPsyW{gbT~Ui_1fWD`=zDLs9pYIa`vV(LFn8^zblzSVZC?k- z71L>~(pUF^m6A9BDKy%o@OZVv&P_x%?fM1}TuBcvvX>2dV;^h|``g&foe2}y`7b5+ zpbs(8w&^F~I*0=uJ<#ZWl4L4N$Gw%t?~Rq)JlQPrre2D7wRBp~Z>dKXnRD38H6C|8 zU=&Gw4N-f??vZDDVD^Tkb%_{_;;|~hg~Kez0fJ==s0z7M6!-FmEon|q?8&g>U>(hb z@k-)}ae-`N%{Vh_PqtEM*3V$0N%v5heg23+=mcia52A9Lx@d5TPu${xS7&;oR3Its z5SXDMvj7T5I-=%*fW=r*p4-vxHt46quKB8sz8Gg3i764uvmJB^nu8YWR&P^`&H4!S zNWYBzT)?&uQj51Gjm`Ao&q$Xc-w8$-uO6P zC{V6-0ow#YiIIkv7X(EB8^>Vry2{2~5m{!!4m2fI5ijXgM2u1O!B%p508LD`;d+Y>BMZ6a zdPzkby(;O29Yvn|wlHKR{pC(28vb8@P*T<9O4=wFv$WS?RF~7G0}}D^G63DNvUpKl zd)iTZ9ofYKU~$b-`65w=M(@073up90_JVSo!%sjX*0NI^aKQu`M7)TD#^hm&v->-C zGSqJt_LauDFD|Uvh4Ee7{0oU#zC4NNrIuRUYx$uNOU^L~H^0rYy02$OZ)9qBUgfW} z+OX&D1YO)?lrJKu+SKQPj{auGcgM5^q)TWNEWj+25stv`m*=!IXAN4E`gxwVcz*TS zL*@Z9XjF3v0AkzDkaxe+IKCMV{Ism4`R^`4H_?F>^4a%R2vyWvWVh`S`Fu&m3}6vB6G%?qo68Ou&e4i#$;`aCgBBQ#YyCUNw#Ux3 z-#5j_%~JGlUWPmZYHRU3KBRWKK3doiK*(GVgqyl~U)eIUGfWhptx*|}x@4+Rv?7U& zkcLSW9uFt=vRR#~kpic_)A+#_(Tn1v*YtAf%6ifAa(j%RS>kMmGwpV8ckUC7wAr!4 zF{WcKvmaAfvL;Ipl^Sj!Rqfx}k%B(74{(5oCw>q9{DB#A+Tyg-bv$o|Kno=D^Evi& zegERFz)%3@^us3t$c%eXbFP|0F_$w7`$CLH_Jq&}9@@Ns^pkcBnJE8U;6H}|5NXM! zk-^gvQE15!S1@k=ps3-(Iw$(PlJ;EyCyK>w$sSwqKR`XB=P zW|EGrgn5m4SbW}AWAdSWR{I}wHa%A4*r*f~ zkwkaEJg{tYDK8Nys`x$9Y2YIvEKA9h`y=f|Zld(-c(&L^7n==7d^Q~eBi=xra}64Q zyp(64biud;N_P;9sC=||F@#)`1{|=-BOtZ0=wg5(PYHDppLc~PRMC^?ZRISQ76AhL zy#@s)sNIL$hsrgLAA@VFaiFQRxTdpaXqx13;S~ieXkQ4Dz`i?anb1S4 zz@4{P?Kc<-?g;co_O#rp)2cjOYpDjYD5tvn@Cjl-Te*JNu@&XGgcUzNufH8Bmx!B7X2^!N7n3P4H50+&p(uUbi&=@nHgH9i0W2q!Aa zPdfby;Nauic|b(Gb63d9ZDHR!&mHrtGIv@$wvWFc#6$p1$5W1B@z!f zZFfRoRUA+}Y5}&DPW8gtY?w^039rLxU8!|L?IBGM`(09#&I{+&Yj|1buH#Lopr+Ca z4vyw8>naM+f-{TeM76Uu{;PfML(SS%gKu12Kd+Pgp0hIX^P}u7A7uorI^z0h+_2_= zMVkT5We6Ye$9I^vq!V3+oZ<7X#I?N1=1w4~vE2xLSQTt}_JXU%1*_)*fl@0_Toz4T z-M7z*NKMKt9&5e}$wsMiEP9&%=SHg=L8&R(9iKJJ${~Ga{5t=-lmT#i^8p7#hx4@z zN-z>`RQ?H@UP844cIo+kysrjb)7Xooow#xnsLmI7nk)Io-wZC2fx0SD7l1{0&SdXs zrYVYQv?W}ac;BjaOgzkNx;^6e0#VTHRH>`AEM2(1{h}u^{HW(e7+LIq7F=%Q_^E`5 zR;vsE?xFE`&UI0Sd5PRd>F~7N2|OSBK;@Q@DBYt@l@cqYG!s} z_A)KY)J5Rv`~pm1!s4aDm`l)jz$JO}*J}44%6=88O4;=OM*mGLCf?rf%AawVibY&3 z`&J($4_@N4npju6f_4ANNtRy9r>E%2?r}9l?Y$#hb&=rkdd2^;e0U+8WsVCwd(oQ_ z5yf@suAkn3P((X5b)BlO_TW{pv|C74!4XC)i4JNWmTvmXmjOi74d}i@f$2y#dG=ty z4h9#hAhUJW;!gBv!k-;xhR%vl3Y;EX^V>V$%nhy>#^?s$g2Bv@k#}F!2Ix2YqSQBP z$!n8qt&djUo#6?(1|{t@wc&KRFO&Gu{gHQg(9~^-yK@>+(HS>U&=!=aLykYW_uyuc zOozWAv>j8+6#FfH6W>4@P~me&?RD{$Z(e)W+Sr}q-8I3x3?U@InaR>kGrJ2+A$)%w z%@)sWA(3Vrom1s=z=((5u5O(d?kxo=q==QiwNTc#qseiyqw+QNyxqn)gA^)+hNcI< zJW2DLa;0f{S1Zii8w$o3g?3wMXF*ImLuZi>5Qj9)3{geOvUo5s5vU+G$<->QgTb{* zjxv)T`~C)h_?Icc>wWI-WZD7k$HmIjmpt0gqTG(-Qa*v32lud&gNOSrx=wH;QGGGD zn#}T5wLRhm5>rfokY|eX!abB8P9c5lCBlxXKKYbKz=QkFYmHT-TYo7Y3g*xP-;#hy z=E>Y@91VDI$E!DXN^)B_4Oi4QeqS%kzIE2$s-3FL2dgc~H9i40XpI5Rg(;WE?jWWU zD{^|5``qk+=3ZsW=A76b<}e%K1u>lnhbZ4%%z_t$NG94s3gHQ(<@K+$pOQ*;INK|S z{-%seP;a!NikxU=Eo=7hZJ>#NM45P4DqWqO4VXbT_pAglb__O3|DgxoIfhr)~@zn0{$qeIy5)s zRSOGxk;FBiGCp;jozbV_ubjGa<2RX!B$h!;aagbd2ulqYbDY7sp=hm;U}d_z(MvBpO2+g3E}RY08ERbF8U>R&xi~N&_K^tPo(J7Iku4;s|f!RDl|m>t)ObF?ngtUIKbOL&Rkq9FZD zNORsA7>GU;juV`n(f65=!A-pwi;|nl2Ub-(&3Wdd1$jnY(Hy4z$s8OU3e1c`(a0eZ z`5_HHa1?mv9)Iss2#PPUHRj~3`&SU!0==Ax*rRn$iY3)Ws(SGo+*gPzR~#(F)-XnB^EOH~OA2m*( zm;%WxzB;FK#1_PGM^Ct;UUw|tEa)hY4eGzF4ncj7I_4gQ`+nan@II@LFOIxJ5=HdRJzUEG*R)hQ*t-1rT=tgIROp5hZz~1(<1UGcGUN0KSOnWV19k42|MpEUstkd9v73i z|0U=-T5{3CH`j3$tEtdJ<>sibdHkSG~&*J=CaQ=VCBdVIq$*Xvj*@HvUrc<6?GBo zMsM?<#O{MnVmVmtls%a4>a+F~uy3LSB;3W0+z$}8NDAs)_o6>k^c0T0xZ5HJ$L>+5C9k=LN?i!RrTSin#Gz0Fm!58%b)$Chtz(ldxR$T zSVcAWyvGD9{s+>YCFV?>q=&I0szwER;fg743afP2Q>*J}|cwbQE{5lB4%7*V7fBz%bImDq{mm;n-G=3gpAZJLL}6qWGka0?({^ z6a@Gj=0dWJmA$K#W;2Yj2GUp0t9Lat^6ZXR>LQX>$n6f|ig6*U+H`#E)-Tx- zk84N&)yBbD{lzWpb|&Cr(h-73eQFzv$7`MRe%|aOgSo3;?8KDKQOKku9>3hx7b3IY zkaGeVx&*v0M#%Bftkv|Lu9oL60B+hYYmX5f z484Jh=!Bux5ao3?Q*O&Ho8J(Pceb9pU9r#pQj1}bfM0vZNise9fLMi8Lb3Fhs8f;| zzdgT(Uf{_PB1@(G=VjWtw4Z`Z@}2n*lS^UuayS9^Yk}8A5t1*7)=f_D<+i()?!y=8 z)e_%A7__zgUg&Z;)OXf!1kE}9k(*u*n$tp>dbKm)@$SLrc!I~j@Kj=2p z=QYAkI+mL8xfH!r)(J~AaByQY`m@u%Sy+%+^_@B?(bayZrm6`FP}Qp-UP)5p4-RiO zbM3u-*euBCs$tv_zZt`l0sH91j*k=i9RuK*<2W}cFEi}gaL&64;uj~>3h-1m?slO$Vt7z)tFP2`N z<2jlEX_BKC{_s=o(XJg#JC*aHoXV$(Q|h19=G!lwDJL_Fb(>7|jBRg+2gVJClt9if z-@Y=P=GB=_210fl%Xt{cw%B=O2?uvOLk4NKigYX4y8T*^g!Fzeq|Y1x)@b9$>rvQY zmZpHm{?s?%J0)nSW$7k1tnVZR_zI5a9aM%--JBm;>HsWh83LBwxu&&|PHiuh|S5=g#Pweo86Mw0D5KC&1~`X>MBq zd7F(4_R{qy;+EQINNk>c=u(Jn-(86&Cb}IvWG+vY-)1O-DXDsXUqfm(DV&MHDsL#E zEgkK8(?|+bsNCb&8vC<9QRth`7NQx|C0_Gmwczj|D+W_X#UVG3zO+Qdh(LI7Lf)mw zlbKnUywh%fBtx5#t7u`@$JP%qqs)SnkMsXd-jxUMdHkr=eneTG-VfFFU?l$JuYI+O(2=ls~Ls3vzRz(w!QC>XKw{)Q053mE@? zw(PrneLQZfGuEq2f<<$^Hr>SSek{X5ss*V()2~;V)xNtwXLfAm3|g>U`lMp%r|P^> z3?J$e^b#*!{{p+~>JnKz-NfDK1a0nuiBj4g;LXuKJgj8ZI>9m;q}p+Vzrka+Q{r)_ z-8-eFel4f}_WFa@^vgs$Rf#=A1^9ivGK!OLqtiOe2wuuAziuBclPGd@OqFi+f+9xH zt6himMBvwPMO60{sh0wSmGO|mui}rkc0W946Qe!z)GOpUJRH8P5~@57s@cTio4VlB z#)sJWzMpRa%Re5pi?$FiQ|7=kh%aU+OK_oq7oQmvB-N($!F5f3+9iew~0O2G7#s3hPh-9rI3*KveIdNHx>VQSXw2AyW0k%Zw_F#KTc82gujra%`Fa zxZA2n3?+mSr4k;({0M{C0USm6inzobQI*gmbg?u^cV7>v7T1kgnnNy_QsN}tHSMnq zHRvhz&FqF@uAWB97vRS*ArEvPbm;(HXi$5_`(0V!&*9hKkf@Xv`n$E(Q(V`vQLQI> zWhmNgq>pp=xNCEMDPg6b;CI~SKP-Fw;)1e9$wr97BaR86QbJ6|)}mj|dd4~|{-;A$ z)9+XK@p>fDFZi`d>*!C>W`cE?h70&hn^*5;VQFFcQPno^R+nsYoO2~l*mLsD?;6S3 zLR+tepL(UM&J&{(xk5!#-16$r5vnIR7sgjM$tKs^ZXJE<-G}`ZoH%(>Q0xRGD@D0( zwp)Zcr`rd|Kh(AKGT$lU;nyC&TU7Km%_zE}DA>aape$5`Q8`@TB#9?Uf4fFrr1<$q z;=b4#IM}~*A11^M_|=_IK*1=z1Z4+g;({CRV6+ZlD?S!^^!kOWL)8%yLSG^!v-`y! zvMdC}{{Aqo2g3-RMUt34U*%7yZ|Qhi)Xv8wBJ9BMtk0}#8~aYc%|1W}!n;EDDLi^v zmY1|&Tz^n;8=aE${58u4mtOJ5rfnIfMy&!8i%UTBG5#b+YKL$HvvA%t{E{pe?L>cn zCff+T*9RAX2AdeBOye)i?VLkcu*KZmvt9+YiE3wer(MX=y-PIF(4&2d;& z3*3`)MEoI~zi5c+j`X;OJjW5UARy%XJA^_#4W*tCBfq|=%onT4i$8sD1)W)nvD|ne z=(o+0*VX6By+>J z*t5{XAd=c%WM?`Mff{)iZgDKdyevf;P)n@>k5|A3S)nNhgl6KI;^eI?93k28uPnU+ z+%Anq`T0t(kisixmajaDVs$$;Vts$##h2RAi3WzTzFD3E@q#aPMhf}=S+?VSN zYUWgu?#Ur(e4$709omZP?sOeqtIIu4jiXvyGEg(MG^|lfGbs|$%j4E6VDRob9Av|> zA;gtNC;wVd86wo7=+tX7H11L%DK0n*S!RX0d{?ck`|@w+zsGk}aR#qNN6$jPX9nnz zMr?HE18h%2`gb5w+`6b8oX4Cdp?`D!=6`Ny$FEMqly`zmuA9%DSzNpul%qS+yp~7G zROHz+Mc&M2do5=7OqA`~6}|8+(Tq)I>g$;vxQLq?;-eSiey^p;yA=BzzMk&+dS(|L zA~6dj&3=F(C%DrRsE`5rnF8OR`CZFDg`x4e+wLX{d{jV`phfNZJIe)f-J>k7zp5#s z{roY^_P@fU#82lukexPhB2HydqKg%S_0tH?SzLRMQ|{Rjg=v6Sz5qv-d!!S@(-8O& z;R~g{Oe;Vvs8ItuDWV8zX{Tz!C2Ae(LdPefrk5?XW}+c}2rUgoub8?ZW-S5{5Rb*j zINC$}OSFuPJ6zfOMf^7)MT+Ex0pnlJ(uSKc$oSAsioMlb4-nXs0c-S&qO6|jU`p(E zRTkoY+Bkz=hq&DR8i%v}%^kT!vqRNHP=$@9qYKpK_TOMvN3`v$y$d$S`Ld(s>faQm>`$NFvLiWZ#`* zW~+#GDGob0_Gja^n~I$NWRtYhEWP=FZ~75xuW=RS+6Pk)h5bBX;m7+2!cB_9v(8=E zW)S*soe9|qoXJA_GqHQOw5PLa{xch!U)-5+>afn{cROfY9ZC;9Lpmz46K9AHBhj6j zg(yT=uDjo60pe~p`K~IOFQsm+?mLF#dkQV|W^zE!LNk7yWk2`M zT|sDyW8QB^+Sm9$12Qi18;73@4(R(1W@Yi3X5@BPcv}`+t}mXSa(gNs_~sAElNd}( zHSYNA3K3RxFb_(>=G*M(U>7o&?CA}XXYL)*<2Vl3>-vJD|9GTSl4RCDqAKtwj3~=( z?I}DulPnIiD8wn^ok|zq&8d8Z$kHomTJu)HG8l@+=be8Qjd)M;a5?J>at>8W3XO5> zTVt~_W3NR3hv{Ht{J7Q{hiPM1@Z@_>=(oCQE^bz<8o-%LdR6lI@V@4w<<2n2lywjF zP&3)Y8S(om>Py04&e?MDO!Ij!I!o0lvFuJy<1-A&ZOv8;ofAh*!q0EJ`%eaKoc83*^b|gCf?CXnH;B+Y(Io)+KX05Ld>X{$GgXl3p4xl>t>PJoS^b0Zsi@Pwxb@&< z<~5kmZ!9$4id@^{eN;r{ODbX@jp*Ivtko}p7fi%Az7F4blNm>$!VmY0tG3xKpri0DL1PUeX}TPl)1V1OUy;1YY7 ziZwI~OgtOxfKaina+x1LCBf&{X2@CCIZ!kRa;=Gu|y^C zX-3G!x+HNnu6yF5kBX3NZO30rPQGyP9_f&JK&s5Laz<=IS0-cX$}sGfwQsrS1z>PK z@T3z0KTeR)-puGALw_YtFszvE!UYA$R9{7i&t=_hb1b=vf<^fLaK=ITHDo-_8}dtx z|4}H^jB1>83Gw549;wf6{h4bf1;7S9ds6!tHSB))%SQ_!JyLl)g7*f$z*B z%7)kzxpH59l%{{)dG`3wpoM9%)9m1dalaDF?5vndb1(d1aES0H_WW zyyxfGF#F$&Y^CMR&-}&3Sr8WDsZ0wi;-GW&a`vtmceFU4ve7ZtNa;RXr6G1j)Nc;x zMmk+@>UXTKdkifZa)K+{qoGTW$Sr<|ezQE&E>!S4a(o8>Fyl$VP8ICVKI85Kl33$_ zQq()++MV_THFOOL3g%ih;8n-6vfQm>4An?eD(&`tHh7H1wo_`N)!s4n)_LkV_V6tGvT`V?8nX6&=F<)BYJ{-dNNB8-hRk2OZI{&7Hz9jrW_{;Zf+b^#Va3UMWJoxk0M0C9>5*E=GTQ?_0Mh!KN?igK7dB>~@Ov(i}vV%rG-xvZ%} zq!&yybM3x!FuFsHx}$i$+PV~wFLv;lX>P0xh70kY7XcNRzXJe>9=5Kzk8;yMv=-<9 z;er877-*4JuFQv;!EA&y;V0n};{N?$=E)B@gJp;R*N7p&F(iB8?!lE0_qRa{cID#L znO8(VN?M|r4WsL!v36OB8+SsLZkd|eSl;=-_Iv*Q1gIo4 zvp$2cnv^kw$hmFl$MXo{blJ<)ho33aPNBPHs>IVyebgEII0R~D%dxjBG9q)#iT?Xt zlRV$Td=M&ePU6(e8&j85yn;&Oei|0vcm6FqH|EMbFYyIzP0BrmE@L&=7VJld(|Og5 z9S-Nme>lq}4v9;yza1k+MA5UXMOfHN9}ElQr>zmQRL<^3-h`Gv(V-i8Tr}kXXXn+a z+u0-42|ZcS(5SXRTVIOW3eUy%t{eG2$PhAf!1kXahswv-+v7&68Ik~=wLV&@Q5X!* z{9S>QE-8N8;ATqN!baSNeDMIkV_XkLH>#n1pWI5_6!=k*67vYE^7v8pyHIwO%u)1G zzlVZCbPuBvXYXyFjpPgbYnBJ?*B&a!?x>D$`1VrOJgAL&VhkoonU>ao!e=}|;-RL; zozN+6C48hFp?hN#%owR1&$PJ!li6CL)oz7X%T zJ9sD;dl|F$nx5?T-c||#3Nw=b`^APx=NbG4kI*>r=ul?k-Wl6Uxtf&frCKj57-UXB z)JPYXu37GP*9~`Be=&}}ned!uR>sEbNqT<*T~+;4ll_Ts>vVIEMDe^rUYol= znwt^$MDjwW78Dl+{YvE863ZF|)NF622YG;&#UVZR-RvWlDL|BiE;lbzp7Klb6rO|1*=v$HlT&}6-Z*ft zlTL*g6oCFs?9<1XGX-<|&zPh870r7}UCc?VE90v>Lr%?Tx_sc%uY2Q>e=Nj`>I|bL zT+x;)uAUn(-K9A%Ep_{S?ZS|RlJwp-u{+Nr_+3;9egmEK0X-p3iwQ-PMy-jStGqJf zVV&V_`bE{QQ_;W!G8$fdF|8*_>^6?Nne|-DwurF&P5Hib^__uJQk3%`AB#>Vye#|3 zNeCsRgbrKWUBd||7;q#$P5+mI@aO08gXrV>)elfcfmA@&{f~TLp7DvWfo#BPy2@q0 zpEai(|{iUxgW`qBgAGEJo>MPGq*p~u^E9>Dc^m^6bYtDZnE4xtO zncL6Yo^klw%i_*IG+W$f|3#z+lq33BcUhI*=f1kwwF_M>7!dmcsKiSbTVQNvmV#!~ zNYW=$j_X0xSY)9vRzG7@C#QY8=aWl&_i;P z4WpbiG!fFrt#k}XXNwdt)4GGRD?7Tf%@0oVsaLwWMyS@JO-7IrSZEC3x>rX zFB7AZ8xK>`2db}n%930cYr}VT1rx+Cs4q#H8ZRc?(iG+;jyko7EY$_ijxHOE>v}(h zP_MIiH~I3O)*SY6E9G+Ol;}eWW@+Oivq$QGk7niCes8%i`(Ewc-j^KXIlsf`A_{)q zyT$fHr@Fj$SDibs6MmDv(j=8t_44?OlrVQyElx+(_Z&JByw*za5b;aW-KG60Y&Gmg z?|SFI1HFlAJTxXm3=tEIkV-z~*)qy_r-}UKVNtqh&X0(dzL0@6l+Qj~tGbDkH08>A zu*R$LTZ=&B)EI~c({0jUKnnnk+KMf%@0kAZ(sS|n zh3-ZTf?mGk&#l|{-LuS_6ro({b!b%6xO=1|`z@yu?_peVlEfYYRxbnzPnO=f&k)#{ zW||{D^KyurIF;F9mVrZYX}uqz+980em0;Q_Xw}B)dANH)n;{5Ic#@u#lvieI-a?NI z#Mwl@Aabg|KXlC=p>?cd_cX@uz7*UWYbjUB7?1-91lEg4w zyYt5;*LDr}QK*~eYvZ+(HZrOoy> z&A{O3Z@6`^X~wJ8jigH333Z0)XQt|RVAE#*d z4_H?kCMb^48}{r0I#Hlg!3`7`8OTJ+ndLiEiX9cjcSrXWNpii~ft^*L{~}xSeXfJg zd*EgVYLTSb1c|~U<@k&vAv<#I&lFT!il3S+XXrtN8Abw_1yzZkqiqC??}Kj0bMg4<((f}JD`2Ee4fa5$b1fCpOdwla;g|gWvEu#v z_cqJZ&HhzF#RW4iQ+4vq!INpL3u!%*6&$-j*(E;*Q98rcO^GUFw{WEfUudsTP;6!+ z;nDfU+&KY$FWTW+%c`!n$!uZDx#Z&)3|Ms?fZbU9_|Zn^#*+f=w3eHCK5VkDH@6;~ za3ozp5}~9=-uLHt8#`IoTKl|1Hb6A-m050(q1z=rcU8c97RLYFQgFka!OGHn&%@}Y zYh|{FLAQl0%F!rN_~x(g@YnwUZy;)v6a~J|-VbsAr`)C!RqP34=@cS4*@*CE|Kkfb ze@EbO50tosfb1^{i9-#E{-JytelUVc7ni-dgHn)CB!z}gJ$mD=8p!a&Je#C2drZk2 zKTYoQKCo**ZAT(qv-y8!LPJyoJ7;;{uE!C8P#_Uj{Ue3Ie7q#!(dP1>#nG7(eg%J` zU;o>65ZmMor{6DRX4zH@QNBs;eF}$TT2TOaLLAkFsSy|HfW*%*MUg8Kz#?#%y!V@9 zu4H>D7z@4UYEI+>Px)-zHa}bP63u2!e?6zx`0L$5oz1}7?%#u(;dSZ~$KWeNiF0Fa zhq|qcjlb>O=mB}|z#A~gyKoi`+dVeoj~;S6Rk1y&PXIY1%k8vth4HVk5Wv|*mj5%) zyus48fz>+w^C5vUH{1L=pV^P;9_nE%9qrKEoq1)QQn!#kCbjz*S`a{#^&AA%m_5riIemQIr!V}m&f30s;k_lg8KKBj4ws;BF?vL^ ziE}~^ak5h5e1ul(jcP?X%Z9E{k0T~7w*m3H*pVB)UXtNJGQVRyKAPF+zDPmX3g?Yy z{^^qF;~rgtm~o9g`2>m?*$^{|-AWK8WbM}m{&SDADDaB2qb1W55V;sU-$K|X|Jt~| z=)&UB=FoAK{(9QrRKZI#NxVC;3G&*qXpl|1_rhdG%y+i;#A;|*^x=ZA6w>9r@av#7 z^xh~9c{1SFJ=Z1wetVMNW?_u&0QHww6uoDf{Nq@^XGRh6&=Ht@C$TSLEs=75C2U}F z7s^Kr4@cYRu49YdB{oo=lnrUZs2b?ROaX_F$h!C4xU&9pa9qvJ@&3$HOdxYSQtMssZ-4 z)=Ty)_(8rz_G7Y{$xO0r#Ij)(s<{XbipK~Y#8!u!9*WoV@@ABdeY9H~W~~`#uCXa1Z{gu)eXN&(guWq*?N^ zp(s$o19+Ys^$m>0%98Jm>uMPrJ-_y3==bAA$m=J<>N*4Ktj$`Z@Qr6GP%o#r*~{_7 zA~?GT^bg_TPCs5yaOtle#kywVB+{SD*A}6t6E@q*RiyH;b<^Y|<{vWCdwg`Rp>a<` ztv@1$JEdu{#4FKkWehpSfQR%x3?i)=Z|2%O*N*eLb8O&@^UE#zy6;4FvVIc9T5X@;{#TNviT^QeQgTTovS760ou&1@IuQ-v0R@7JK!TmPg zOR+=bRE+01*-wdjSo0~XUil+RD7i;AY5x-`aYp(Edj5h$s9=|PZ|)LXYO2Y*LA5oT zFOz}+RG++>(`wlYM29KyWzr!)31Qkp#|sZ%BYA0h#7MH%XP4u zxSxt@a(YWE*T#>K+a0+_S!kzqK9n^ZLBJ<|9%cNh2TQ+XxpO>{vbp|h`-Gd$CX$VZ za4S;KJnXLtMRc0!+Q<;-faG&|&yz2qbIcNom+Coh{hmQ6hMz_EXtJHf#=HZ)JEA8o zmDhCsb~$JFo_BRO)ozYV9e7+AQ2zEzIpDA~r{BxKE)FeFgUE z>ZYhJ&*x9*zs@^<9X>!=8Id5l^hm|`tUWY?O!cK@Ea}G=a6X<+q!_V24nQPdK^%Ad`%KXm_4*s;ps-on2>9C=lsq(` z-BY;RIVS-g7bcKo?k7eW)gTYy8!3F|l2>THdai#z#H$ZXI5IxP)%a{Lg)-9*rnkeL zR3VrHanWkO;>OMe0Fn`QP5gxZu0r-e6y&r4oXm83i^+Kx_=T?o2t}RyYc|ZN5OZY7 z;8EHO$L9+W#}D5NJ`i415zPPo+=drGqvi0Cji=s1?4T((S7a6-G%6R*Y0Z9T2sYQe zfep_9?1!}1URsGDL!t<62F>ILh9g`>A`ja(x!*BLD585L`<2bWk@}#pI!i?|pmI2m z$G^S!CU9f)Kc&Ly`O$n2WTJ%iOw+TV)v-?amw+=ii`=zM`EB4~)%H8I_RtdkA z9Qe6;FCQBVYUA8%)+rP~(SV4vHf`BLoTNqzM3B#o{5hvPw&{fPm5nG`(*FW)-NEi# zVnPl&CwtL|_Q#vqY73E!1`guxdi$w|KlbqzXp|IPxem+n2dEW5;QFJ2+u03D4)b;R{TOxNoXQrOvo%BbWCe+T3L*E zoaf(#RzVn{0sA6Z#RMs+sJ=sGBV^3};v{wq3SdeU{}4yu{loR(R3bCA;iGfvfBAa2 z{uFV_@oVA1Be@WOly20rnm9LCT8B}#)Ca|cZYNtiX>elifesMf^+TuuJOv9hgnE%4 zhYE~rywi}84LXoUOlaPc;Nd&BejeBNV@wEH=~a(%>)&6mbBMiGpp3W+Rml`o|Mcar zHqQKaB~H%-*iGhQCjYLOrOBa3|7&)QkGV!R8MYz|JcujR8)^QLCMTWOqnwxFaxq^) zOm63Eb%}#_yzup|!JV5aR2byi&+=?+Y#W?FU)_)aTnhBjUxgt4cz%{dh!oYGi}(O* zU3aIAXTc4|df#td2fY$`1ja9$I!tii{G=r^4~louD8m#IBC!NN_gXA@vI$o_hafR_JNrYb`1Py&@t$} z#47jt!dC&y*#Kqn_4o#LX#`5|3Kh~YwFlst7n_dbi_r|Qb6YUhH}(Ov$i^HUxsgoa zAqF4dSt&1;8S0&UWe9Z2H{LiW|I>T0$_jn;KAO6oaox{U=7uV;5VLOKwI|m7tSc>g0DVL&f* z^YMh8h@x*oDf2$+r=Oz6v4r3ox_-POPBLnI_J|;J&+gKq_Rr`HHOY|MU|P`}z{w0G z0*fxWHq!pmY3-PB^ox|$;PocY6gZ)>I1cE?bM>^M+}vOJv2C?>TI>!8OH%uuIQ;p1 zg+-E_mV8iEh|LMJ2P@Sy24S&;%>UL-FHa(VX*3IVrfMJX*Er|s<<<}w&U?q;S3GkJ z04_5&T7V$;fgyXUYIc%CfqLy_pil5)nwYmYVKb-te!hgFux83{wxH%X?okv0-|(N@!IwK*#&Vl(VPgk;0tBw2w_1raZY82Pfjk&bLd7i@9yq4GxzPC8yLa zl3WeT#ZzbD(}hNN!W<8h0Bre@(2Ty#XM*TN6Zia$sOV!W5SRdahst0eMdsUD!b4vy zpCF-mHh*yJzhJ~jEXStVjClCWEs=47*b_@5A^@z|siOb>#CZgbV!KAJr4t-8@;EWp z7OngL@VdBhGR=uSg)RRbUg3cfj=2IJ?U`n1dN(1Vs4u^?j%mOCbH?Wo% z$MYWy8R%Wlv!ml5bCB$e?_AA%MVe!r`(KO^T+PY}bCB7i*#qqE=$dH8J%1A6<-53m9iE)@G~8w^7Sw zP5#@D=ez7xr`+@zu$t!u4tvd8W3HKtQKkOJIhJa>kL2Z(YMEsoA6&GuZs2K!EpiMW? zzp?3Dd63dK0Y{LUXXqUe%m4jQL-Lf9&Vq?MyGm30 zzlo>IGa~y`-$|@36&!yP@?PV2>M$matXM;7{?Zde-Tw|RmD}!CtH(CO+-u$~{0EBg zE;&wKZ==b&pH05b2{?p7WU?)Kaje}rRTZ-OX7MP+t(YqcPZbJmEAR(}<%xKH5PTcshP_7hlzvI|Bp z6Yj2;Z!ibz-kgIuC|xCW7)8*)lOMp?tJsHM-A5)UcxPK$cYckctf6VZtL|#mj?DdwVo<`=wSzMl^9dXbU0k$ zDmt_qV=-arsttE;o3^QU%H0Eyr}50>^~KeK`(FGyo4~9YMDrl)ARRALrrxIUAy422 zPYH^w7ow*jf1u@Qhm2#X+KREnDg|vyQYdBjIh~61nY&C6NZ00$y#q)9jPR>{Kd~NP zIQei!fxxHw^;Vcj%Ma^}7$Lb0P1uElIEbcgmzEj5SPpO2SAQ3boWfQ_m!8uB)*W|f zHo^k-AcAll@*j)1KfXBkpGGB5GQ~K)ah(xB!z~PZbn?Z#ubKavoe8lHoo2bJEcA%V z)DWjHIK10TdU?F}f=SmNrMOOX_DCIftf>0*vo{f5K&{5 zv67HjLycUL1kSimk{?|@T5K<`_6K$c_7B53A@O*w^z=*(H!4OwPP*0vud=h&(F+?9 z$3>ZIRnuNdoEyh%aAOHY`J)X z@iTmBh#j8fu%y-kbrRd-ryEr>E-4Go`UNNtnS@v|zA)hP=sT$d=zSJ~Uz_!Mb5)%b6539#x#X$s7A7Nvy6OOd5t}om%Jl{j zhAVLYD+4T}{t_kj^^NwESHxJMW2Vtl@w>TCn6TPh+-7su40MtQrXM43J=0C`bf$M_ zWhft}Iz*HM8&FsHXBSPU_8=>*q+K^b5b2MGlLjy+>4A$v-RBVZTP4h3I~X+_!O1uS zy|?A^twWFA6=z~?xgT=cBvojyWiC$6^5znQjj{rJ7ryl8tVhEAYG@j8d&XXRt6Xub z9J>mAk=E7e;YKdX|DQtIiOz@xh*V2gH8V_9o}6?voBMuPW^WOw%KX(*SjTPZorvP# zk#l7|TB}AtsTgDW6w_kiV`yOas|{YaL>0yVjcr1g9TzJB&H)a3uTFy>9q!yMt06ao zAU%F8T|J}L1x80Es|Rw;LPPAad8GcTfD6%uVYF)lw;cF@nl(RF+iT36ka9Q68FNwt zwtFW1+>P2O_AKzN&zi}mhp_?^2E$NBfk|Jty!b|`c^1lk-uk+5tQCvg0|8;G_uqoE zUt!-$x^c#DmU@heAlmUANsqd6ybu>!r09D2b|6RGr))<7!{$9=C1Fh<>)=r#pM;i7*$Y(grJR%o~iYDKq>g=)6mTQO1^V>FI8;mAvd` zkr@ewPghh??Rw8sJOmPI=ZCd~nhgE|8jVrSR_GnGWS78ciGWH_fWTcYVWmZ}8OL!v z(RfvF>#|+mmq1^)7+0KmWTmcZx5LGwqM?y;YkG@prJ^|+ta39Cby1`HqiFTRxgJ?g&QUHoKZ8BRNc~7C)bS@_Lz`McA z9XrvAZ9}RIXe7-)8*WBJ6b0-s4Z+GWdo`KRwZpy4^oh(JP13bOG3|2!XrI9dPpw_t zZ>!Sr9v@5smt8n!$rU_`u@ez(O(4VoKDM6;Le+69*=5FYhil&pUFk6+nV4jFMzsOq=47~cT|{7mbKz^#9icZprnEaJ^SE(@s@7Z^ zDY=sm^s<9fbg_JVr{q|zlq#ReLj`eDt?szo=6a7dV3j4GthsR<>pSCr2je zDp|<1ysbgON(Cc(=Q1!RE=7i}$VdWMe+AE-_&SkuG+F*WU1we}Ac z_XDxUAV?sKrTS+UH#nXhZ~L||JyHhNa%UvRw@=2bE={LI1hc0l#zk{Ph^KqwX^C^I zPk@|r*a8u0W;>m&-};^<&l3`UJX`v+xspCm@G5!Hi`f_~6$95EsO8#R;2H2YUmh9< z9TPTyWh~Now+6%bPnc-4RuIdNe-k zyoZZW`v6kzOp1eq%gq|19&`E!keTwlMA!zUZ_JI4TN<_6)yiT#8v=`iRSoZz%!!!Ht*Mh^$O^V0hO@FjtAoy(m zn7shj551+GyC&r%>4w1(#K&j==XLtAqU}G@%tDvz3J^U;+EGSy!kRikZ@6m^9+=k!I4s!C)bo0 z1wiSVP4_ikTQ4KB$$v7`0<6If21xZs{vy@m-%|KgE;M_YK1ufyJJNhVXuk_XvOx2Q z3h4P+3QNF~L9>16nSIU6yAQ%b(WT=)h*XS}cRew;c2+Vq@Am=%k(dP=bCgXfwE>9Z zX^|?`ve?4krK%%`UlF-fuD#o*B|t5Oemv||eE3?JI(Zmi-4hqNvAjd1gu0h<=P~Sw zv66~ch*PvFIt<^CWX2}9B1~^0U(#iP%pLLI;XMw7Kl9j$RL!>sp20OkJ*z8St8A3p zx0eCCjMO$}g&6S?qO-JwIa$ojwri=nOO!t(cK*Y1?>V=_kq(#V<|<_N7fr^Ft7?0!Bos%+L2SS#|_q3|5xOn8Ac5_n!=-2kD^CK%$c zJu-fhqMp9dM<%cF%;&bJaXEr7Lwn0pNQUI5?7 ziE4FX*D5afM1qJnLw59WTf-J$3`8V*fj@?C{KYUoM0bE2&l}0yk=6}#cqDox5k@46 z1P|!rK%zJ)`0tPdnl>&!dt$XN^uMBa^>X9Zj5V(+2OUnox!y-B!xoTluYQ`d8sXb8 zu>wCi@PQ(+x84u@N7$`w(0clG?OdL%NXofWNw2RnC9SsK8H39uevq2P0pr@;0-LgI zeju8ocg(79%ocfUVs4`mwQCAg2@9an3N&-red6kA?^aUL;Q_5phfTp#$E&Lxnn6pRF&o z7rCKw)xVs3Fdo4DZsTq88aFQYW$enc`x?j;PD!fA>z>sTMVP!VW5DTr6lFe5=r<)j z2gTUJ+?-qStee5dJ9|srrg@?mc%I@5n(lkf1c8ps`_=<74g0khTmit`NyTLR+Jk9B z%*hOj|Fb=zlTE<8vNeldYpOQl%Rdedmr7ity$(^~>u{yV9yEnS1JoD=m$bCb-fr~6 z%EHjk|L6E*7=0Hyesh7HUS=3>3}0qZgrU;?I~n2~MNM!lApHyt#tyj|X|=s%-~82F z>)4rcdF?G20a|a&k#H>fc<=F5<8j59{^a3um2sbcb{yUQbU!YEiX~?vO!R^TU4Znn z2f}kx_2K1CF*+LN<}$L`7pXtd>~z?j-<;m=bbFUCRpiv=`&+UoL*L82-^ueS?!h@0 zqb*Olh(y1Xl6$&yVDH800sIogk0a+`Bf>+d*OyfF6MV{~l>CBPhT+I@)b?h|e4 zmFMQ0{SD7+e0YCK&Z)XzPBd|?T~gLbdG1lNhMVOE#3og*{f+p; z6ur}`tOd*?%mvM#Rg{rc5E$0uw-B`CF3X^|6QfKvxvNDqKxpMTUqG62SrRs1L^U@T zMLj;1Ygg7gV+!&xN6*1R@pkhl%A$Cp?O3YEXgqBKdwwLSgD|*)#E>%<+~sp@Kqz@+ zu9V{Ua8~PjH@8EG)7#qRp#0kRWl>S}n$xDpZnlI}-?i}*n#TT#JnxMn)l}Ngkr$}T zzxd9wwm)MuCu0(%@P>!V^>SY-MlHm-g}3rZ=A{N(ioWry9J)5Pxpw9LOlvwQNu?0T=UjqPWhgRyz)t0Z+hPbjO##HHx;cB4n3`hX=B_!fFN08sv}<mo4!~q9`Ow?Z7&V+Oixe9o14AswpZ*Qb?kta zBvFu0+ztP-2EfN;l1(O*z)LKB`kT3tQ8%}zXIB?16CZZwE)y}s>37k~7A`~aVWlLu zadu?lWQgyokH1)kTG5He*#+1CJyneCy%xJxSKiq6edND74lN6bUvjOGP#_dp)%{7|k2%j%UUr=7d;yRhRsLN+v&YHFj^%$Bq@7nejk)$#1?M{I9m?~4yN zuJ)?!88OZE_GfDT^`P*ZjBGAk;>wyksmX0`&Z5V{yqNlshR5bJci1(eBL~RW%o9>Q zko!7mGT7PYxWd@4{<7^EULcO4t(E$H$pus=`-4yXcyj50;&ZlJW2Cu{5`M^}2(kRP z$$~&g2l+0SNiU8vtbk96_#HM0!FFeGFYycUTI$n^FvJ<;m0NfMvu_tBJMx?>m8Md+y)OSNUOgK(l?Q)-7IvkY@KHPSv`J zwYjnAVNUO~6Eema?nQh|Q!e9VJX`yU@7RjLsGmH05FNHEyNS`OO9NU;$ap1hzgpIZ zORi-C$l=ZDQv|3L^3JRdr>*d|Gre0>d;C0D2An70?T(}s7umVYNGeV)_6vEPKqhMj zlf55W$HTY1ntFx8vN4x~`@dvE3WBxK^lwiD;M>WU3OmKMDb_(aZhFo1(aOB2CnvLm z%PFx4Ck&$wccTP*P_Dv*nS_);6cXFfD`~%S;I#V~mjrfbaJ*m&gn*=3z8PGa+BXtXS0DcJE)3dTT zz6&%bGys0MxqzLE?3eG%@5r^Ot^gLQ-MA=q=pGG>Z99h!jR@>MXIUt&LoRtq#N#|u z{R@gu@nakb`DikTm6X8OORP~yOOf%aIeekhIC4!99?66&X*RW;UaLdtA=tBReQ*Zb zr=nyc=d7TwGI>&Ml^E$%xp3mamLj-MrKoBG`A|qBDA2gf270!sDldAv=)ZL0rMwaqoV3u$cSaoau7Bsa@(B zF>jk_d2GR`is@2X-TlfF8)Wx|YTbkLnmSW$2O zI`>ckT%?wEVyXV3P<0bu|A$Z)cU`0(7C&7=(W3h2?pdMLUqZ;B zks3)rF_dgF#A}}+=T+U+x)4uBWbHQGD>s#MvY{(Laq!n^q2eXGC&E3UA$tOwR@8sT zw^HrAS?wv-%BG`25DmHL-Z_=$%qQi~XVmxcZYx(^Ap zZT}QGSH!E19|>@F#g~8aK^eRDG%va<5VVW?i2 zy@Yud0iIO}CCk6UiuV=4-+g0mfA5K7H@`1bEV9b|IHdk7{w5t zU67!h_;AP5h`O8YJjeFmLmy{`?=BP(u2m< zf6RHa>yHvm*sJ?S@=vy3OW|da@YGdMG2gGryfZ3~P@Sc(^YYqfv&O~qqN%Xz#i!D$ zhffAh<@}1;9o^N~dPAqqe=2w1Ej1mn*Qq95HrF#^Q$@BBmQ0)7Ds4Q5GnYkvqimUW z4658){SXjDA zbYYOZ@fIll6{SGz4pX?Oqi6QT9nL&(%UyrRgmlehWnX_f*(;it-C=i8yl@OUc^0tk zh@hAlgOWyUK=J8OZp@cYoZ=^%5WEsVPIZ{n&(N=Ec_xJ}p%s*x>A(4&&L-2M>lxEy zl2M+_KP}U?C8hFFQRDR=^R}bL&&-Ys!nz6>2j0A?JI44m&9yOWo2qEG-H!2MsG_Vo z^Kj7>h?&k8q^`b=i0+sH&EhGpqMy4!SWYP~nhhO}C$qX5h1W+Bfwo1wJ=wG|f)ZOl zs-MuEBJi2<&KE1qRoS#W-`;33(jPjv6kPio*?f({jX#!&CXG2+dCw<*I84_&55Bj& zDe!T2d`^0Qn&}K|>0#beR<}z0=-5ifvb&-vg7$Sl8^YIAYiJJ8JftOlYJ?l91rgq{t^O$|vP79oRZ|1h?uVtp2g_ z(d3M(ad%WRT#5*<^)o}Hq?0^2>t7#7Cquc5H1-R6re^KL>-WP{AX?6F2+ zZ2Krv5+|<@`be+!Df;x#eN7%ZH@(|Bpj;*iQQ9ECB#|L4f74X-%2cAG9!RIJXITz^ zd%OMLPLM?RK)k1u-)H;pamdpn!{;Q*FL{Hx-$44+QkWMN-f-p?7QQieF$}b=f)OOq z8)HEYnOd&$-C2^J?UIp=4Uehgh?k<|1!C23=(>l~EwLwC*H~B3i#?z&H;=Uz%zu%f zVLRM0H68{v$9hq#Kugta9MduP z^%#-SCh-56n;=3Jg$m~FJEJL;WG$eBECsH@$XMbBQ4X64|HwS2%AViPemFF`J* z0jh&FPmdigH?`ucQdK&&2VKK)z@j5ZL>Ju)zSt{5Sf~$!j%X_O4JzD6-__n|7)SNe zts7lBZw=4R0oEDCz6!>0esJ5HA3EMW=u(mRN@AC7VAuTb0smt)#}6VCN>q|ys(9>{ zI=H^NjJSP23jpQ2cI+Dmc#)iv;oPmy^;h4$uX*QjjqEHn6PuRxzD7l&=;HN-HVfm< z$_)Y-P@cZ!-eje-L}`Jj&j3fr{NU?iv;~z}x1M&7-+O@_`%*O-v#!l)WJb(Z1O^q? zwz|-B-^dFh+9B5k4I@zy(7XZn3ggqBVC$9K%B+EjL7|1bcG}anvR&@!RI*Ya(G&S= zZs%~fK^B9hAe>_5Rqa>j(6}iDZ3sV)Fy$`+y*$zO0uZR)c<(>(%wEytTS8^7XP7D{ zUBT`pl^WZo6hqo6c2}FXk}=cRLBYaq8_(6@4)I>za5T=Lx`W4W>7u%~Z>=-=#f!T& zrzq7w75?LM`9@?0PTH+sh7&qVxnSS;j^CwGYc@Hb{#|z`6joe{_t|PMhCQ*g?#Qtn z`f<7$p_2Z{ap2ZZ>x@2lK|3+$4!FMdsY1Ub=%Or=yW}d`V0#hY1H`4}xW%Nv^w1Uu zVS)CbL%8Uw&|)Q{_J&K&H;0s_&4sf*n+ppaj9mwY05rK2*?!*AajlGXB~DI9tmkO* zz<=J@yf4W6@iF2bk5!B!2& ziA#5*9?EP3{J{jPu(l9)(og|*nw5VJ|AiQ2o;>*VsrGxvhP=}8xA)9nfI%#eyI&pv|cMTDLV%R$lY+sP*Wg%u<<*4}?c6 zALA34`*I$_b=Zc7H%MjQXg(#Wj~G~*5Ji(NHRU`n92JPdlM?qZD{B@EJYrh!O;Q=2 zNO;)_J6erMt>63-4*6d~wh){rPoiq_pj6&`8H$3~4C}RXA>T8A+p&bZ>hl;(Cr`8Fxd~(p{ByG7fG}geKP*UtN^vmJhrr3yhh@##*MU*q; zb8n=gcL@u{|6%LB<7)2z|8bp$wxp%R!G$yw?GguWp8m49ibdnReNq+T0z9?kmAZw z<<~5b^%b&E(#jT}21&X8jrqoDyPPp%Gvz4t@LLH1frB)Y8p8MGdb9r-Owy?|LN^V} zsArEtdVLFzS&!wLFuDaFFYH7wmuWG&reo9%5v2(xMs*Rl^7GWP%8{`Yu&k!t6nj@> zKA$d71PwHOB0D!CL-hkF9Qu)j<&qZ8|Jj-Gl&sI7YJ4E>N>uNAR(4`90{W<)W|B2< z0r54uR(Y%LP4q=gxrrV?^88F+EH3ia04~A~Fd3(vqpIxfifzfrEjX>iR0FN~qo?9M z1SZm zkRF&%-gT?Q&6!B`f{c#p>+3I`Af_b*Eat%q{V6q4|DO24Er1%==63tuA|<2m1okCe z@6k^*h!a-{h*3{;azw!B1q|0*j>MQHkL6E}KBZ(+;{ z8r*&wX}x1i_yOA1Vu^SaA=N>p@681}O1h^T?02;+4HtaiCPSZrd_K{(+H07Nw1E`J zn&GS+*%8VeWO|hi;hF`+#v&L55q9Kn%l?ZwYbv6U3ZzjWGLij18tbsK|Q6=4$lC~aX# zK@F*jN;QYv0jHlm0j@UWE;~!FyyL1H9vU!@;J!Y*52EgVNcy-(nh=V5B(Nq@Z5&a0 z_3#QPo>8vTxZa!0Y4?$Gp8__JatKe(b{IzY?)PT&FRH+OLHd2;pCKka|7~6U*N2h6 zyOHoCB}^q;V(+-B*KfizIK0x9m57P*2ii8JyprhOezQ27fix(ar`<~9erzwRZ|`f6 z9gi08t|`fcLS>4-aM8?zcBjsruD06)Qq@PE6>gV`K1tgiWH_XI0K)`P;3JIr%q0eY zO@KWLu?1d-gy z<#0MVhoJzyMxb#91x-%=JyE zwvDWWa)j7Px9v-3c}9lE#CQ2@Pd6uju0FGnhQDjz}r z)Ew&&4*(b7-rEjHA?)Et4`8ci-lz3dH5=x&t=3_axtIDpxAB{Yosp)((_a}s_S+)V zN{G+1>_fDe1(gh~d6ErP7%Ix%a&hrciu-Teb$+G z`$|H|Wv9lmb;+Hx?!tmP_vA;{Jt1!Ksow7@h;T~3xiBjGW02Pk(yj|dKAq4`{R~__ z-Gkf(Xip91o0(1|Guzb|x#m2^X;V=dh8q91=uL9(T#7#jVrwl+ly?V;+fS+8ULqa& zDO!kDp1CSn_CRgre8kc$l2l|FJbXtV1%R;f9;ot2p0AVPu(?;dTs(c(sSfZZ=Qo^z zgNC@2=_+}|()fIk%BV3@D)WH9B>kY|tjj^abgt+apsyoZAxL-QlEqjArYGCa zV2s%kYLjxE*EAVO_XjbIX7g*WYFpm%{#@Vi_+ZT@UQg_sDba?5w7^q3^S-&7EkH9= zxdSQlo>^F44jib{Vvdw^bpUA59=%SrMYGkpA?;42dI}4cG9j)Zu^-Y}!WYbJ;KJ+s zgte+HY{{X(gj{lkl$K2c+xvHN$%)2Vw&;tCty7@w(DHZuo9TkKuCex8d0hlO@)?q) zekE9#nYJRmDf(~Y%ue6HZ8@AkT~AMBBZF!lgFmM*^L?GNG2^x*4dQ(M3KXKXi}R;u z5jF~Bx?f^L8ptWK2G`ftGB?v*d&b8a@`x?3C&yW`CM&}qwJ8-n-rX{Glelci&e3oN z4O!mfaiz6WCrsr?r_Nfj^;j9Dw@0>@No!ws-F%a{OF8Ib|A&f%krYcdbN$h;1p&wXV*3PQ==-1!aK>U4s z{M)ab-T$1A-%I)_nDc|&II_lcBLt%ydGk5i2Y@OMedbhS@J@#iH$4F#dSL7%z%GEDKmW5CV!9l@zx&!(i$P4Kl4pMCltN!`n`@;3( z=r4x9=4OCe{s;e5;@@B!p{+7^TE^3&8{u#dNC-i|5q@V8-%8YMK(tk=0&P5A{mN>P z5vVvoG|%9h5M<|9YfY1O1pl4B)!62gim4^uwJ2MRHnm#Xu9OOMa?oG!+gubKNuNegma^r6#ClY z?AA9MQoRvg+UX*eDdWY^I6F_EyztLeQ5VQg6PQ{3t220&ld`%8#lE#EaZ~9Qr|$`D zS!-Fcf6p|Az5s2u4rHmR92z7j!AJz$YYp1T=(x;z1J&)P1rGEB$%j9XJFak7)KWEL zv*4SI*^dLcu`-S&_ZX=Mg;kTs%d7vc5}rg26TbmfjoNK4a}p?UBmr0C{1HjKWT(L#pTj^zFO-EP*HFr-3g#L4Lnj*dBZ=gg;@;IUx zZ)$^wzauqZ5y>UxNLdq^W2D{v0Y0?0Ud;?NH{q9miGqIJM!;hZ z^y-0rzB<9Ct2OKyoqTdXSBs*BOx*d1R#yCJ>MzcBbM7dxqusz?f5VPR@1?CLZJ`SC zwyaI0bs-jjAc=x-rit&vXpc468I;iGQ0o$TVe z0qqiL-j)iaVif*7ys1Eii1}Z{HyufXH=SBbM(41q6q+!2F(vu6 z)0XGhV}%EDp+`SzWTBJQqF7DcZ1CHfdM0);ZgNcODLpxcH)0X7pWW8l4t0^ypI9{xyjX`Ile~b^*+p+$995$70A2B+O39M=3vun#1N8x&o1)`gyU&XF^{r(g_Z4!4YffM@k|qwPcwR)V zD~FL!7bkoq{#+g`T$-?3<*d@ALI9g8Jhb0O*_-sxWhCWOV$omrJ%`SH;3H_i^aj7g z^BIaZ6S7$yu7w39Cun-q^QJhIo&~!Q%O7Z3S;y6~8Wc0wjqiRmH9pv;HFkRpv9YO$WVOE};^>HCRv49_{1<4!y z=yVA3Q3hE!8D2|nL7K<7!xY-WJc%7>z46yo!nf9Z+cnc)9}>HWR}qw`&Vjl8F$~&P zs8%O0W}yEdSPNU<`&X@&bG1$*G-``++#;bR@wp}PN62gYM3^Q04ctH*_gg86??vUGv&Wl0 zb@U&L&ai7C%_+D%%Hd|hjmDQIms(fRMJ+_4cWc8TqTS)$5JyujWk#A*=L>-2+sqjI zjBK$GhCM|5?1fz?{w@?JbJ9b%R1HD{Ud8G&#Lrec0rAuj_myJOEtAgzX|2Cu6D_)D zOqfxz$V|x`3hn3OkaFwPs|rxj9}OxojoUj*|DCsc&Q{Qk?6MlbI8aD<5;<|^m`j#Y+-WiL ziH7AbttOt}bZHbxwB2UbO5N+szMMampmSaDzG3Tg~asnAJ5c|I* zP_vqZx<~s7ZBWidtvOf&Ta4HG?vb0RZ_aW@pjK0J9@9e~v4^pHqvJRlO_-%av7>uD z85DrvwSqu5$jx~_?_JW_fU%|ut@(mGbd_uD_!xri>uMfm=UpKVb4Re+>e?9+jZ+;Vq8saF`VsquAA z&U^PxqOV_Y1PsjjYjP+tj{S8BcF3dZyb|fjSLkR5#uNL$YZD))26d)dt$x`U%6yIy zrOYqRTSG1%#nPZQmBH|*HszuQ=Ri(sq<};M!3tkW=cj?bj4fPOGN!5M#4Z50%)K-$ zm9%uy85UH+buK_L*C*QKNY3R+3+CJx4EO>@@ClLr4(4bp9??vSYnb#YkRe?wTkzpS zHpF%H^cX6@Q-LR*{{v zLKamc0@rKdaJeB)(%^V{8GP&OjtJC4WnY6e6%Y?WD@xfHh?W}k{h3S%Ow`~r>0`8& zTb4UAmu{AltPZ5}@J^fa^~PG)HM9Dl)99gTjYhF9S73>!1M(3B2>jby^cA~~a-4Xr z)tqba?<+|EQm?myI z_5eodm9BPs(ErKE7JR_*{98MH#NsE(Pd&?iJ3)-(3m1xT+y-s)*d1N`ScSX4iuA${ z=Zy_NH{YSlZO}fJOZVVzPQo1Nd+;Vy;CP?DC54VSX(*e7*xp(s&BL%EC(h7U6>EtrB)&SK4K76;p(G+v2}E(` z;L=p~@T2_%vk$m13YD2l{&@CF1Zs@C@BSYTuCaY%qS!lE@GeaiHLL%z3V6AHUDZMi zVio%wBFXJ4mX(({?x#n)BjV-XP|5I83DFiRH|}>Q?M@{-oUHrRs?&);75YrqLR)dpkG6wJRm;E(zDT1K-OA-Lvq)w06?kh#;lR`tZ_^ zBAZQWq>m*ojE+E%YGD}7qnuocSauDK@3;{x!+Bvt#f>Cu^z5sID26Q6446@((HrQ`Bomnb56l9XV(B)EDbr?0bVx$?b z`_VwpRX_tR`Ku{_pL?`VA^^2A8U_Rt_x`8J+uy|bAvn&86xt;^iHU-k$=xHe3qP0G zQd*xu3*CV?`3CB_ci<)H;BDJO>AD`K61g+5YWLu|)CX|&q#Y_2gg&GR-~$iCjdAHV zBKc1IP82Eb7J{V|b#0>b0hrj50izl>VM(01YM)JnlCSC+n zFOM*E?4@enQ6koK!e+8>0wjI3Uj*aU@KOo=P09MS4cV4yjIowk106} z8Kb__mn``Ky*;?zls$aTJIqJ6kNZ>zK5$?mzfI|uC+OdOj@s_b9;+waK}0M15{u&w zenpcyl=+R?07S{-0FrQsloOE?dIBKjMpL6O$oU!6bUTT&&Co%Y-Ul;>Mki_? zL;vR9Z1d2;&Gq|G&p9oj5sohMKKj?^C4If$Uq+9MCDj1a(j$i9HuhYXdT+x|@6+4v zlIo76;{=BNQ>^p%oW%LAmZvywwn&pY%eV+eUJpNLH3Osuf`@d&%-%ZOb1UfWRN{9i8+y<;EXYdxK!lVedgB=sDpN8Q|M z0H?XG#NciFk_BobOTB@ZoP}+8is%=`NY)3;VnP{hz2WQ zi&YiUk14il=pGNktrZEXwcPyP+KSXyUWKF*8t7vv?9IzS^)6ZhF@=wFH3C^>#fUgY zKO(#(pqWC8z=)+b7h1|Um-`N!SIU{ z^g2XG3bFgp;tQK5wwFyO`{&c3Ub{d^-vPG5QKqub4%h#U2NaKCrBXcc zjbuk;K9H&Ct5M@rAoSzczHc;?g}a{q<+6tvqW1$k*rW?f*t4ibq!xugp2KrhEQe7p zrzT%z(dT`P<_%>gc(D~qXdth`+4?w?6`~`4jbgg^aL7OVke3pe0XRHS=GzcpL-fE0 ze@CSsscPGRLRvXugUA?Zn0t9@MWR!B{&1LxxML!${qQBt^{ggArfQio#b z_u+9a^H-MgcN3&z)G(7ZPmi%=s9m89fOvi<1{7Orb)XyK`j9Il^aKKw&NZLx${9^N z*M0zob`co9N#{D!xE;Cgz`~b=i=J?WIs#jcY!_PRu)7KYDd(&P`Hz==)>o_SnvPhF zE2t^WpP)bIX3tMbe(=5Q3Y4+UxTM~YZ?>2oc7=Gp`L2m6C$XEZ-1~ac$_lgJnsiSh zq#(g61lBT6(HU_a1P^RAZ-!a9J);LeaRgZbgA*+YH@ayd#at>rzbmQ=jfClxzi3#B zkth0_4&ogfTx>gB=6Cv@G)s3$OlgEWYS9G6=^{IA2jyT@CGYlvX1)+sJ}*EDU>IKj zwQ7(6k%Yjq5ka?P=yzjKeE3DLoOIB`=jE^%Mc0S7&jXz_rg*EB92{J>7s_N(9|!MYC1-D6Uq{P%fw4dFgt^E(z}^4hJcL0Hn_5kax!ysG8b#5;aJW;PS~~ zET#VaDn%vqYLuX_2$!BcX3~>fV#s!&dcy5wStC=F1hdzB(htBtp8tG zy)>3%o}8J*^yKcP<5Xi9IZ4wG*~re8HDOM6oH&6{XO~kVph#llwdngJpd zf(p|JdeYdoej0%$tjte2mdYXmi3y#ik8r)j=3U(5*;>8(uQ>n2^?Si(){jV&$^a~U zk!4`6t<`#w=|w{L4HuUrcN{erL43kY0Aj?feJS#e#T%-b~^*Cq_(WiwIRt5N+hlgEH) z+$Qa^S&>rRWe>50$@=Y?s2wFf%8&ZELPCZAjZ6?S)}!Leiypalw8Y*;G8lp@?l;AAGavuPyx?vf5*W*3c;sx&s zoAmpCdI;)fbz{2VK89v|N)N!0(L|MId87n~4wfnCAN9DVa_yBW*RA4H56y!(!?moQ zZ16F?u$Ex3aPiRbc%Dk+-<@Q00>y!s?z_hj!THy+j@A&{tptjAZf#6V$Gz@3y``d2 zyfJ@v+t#Tiyq68}$w(N@7wa|QN*;VbB&=D=Lc`xRq4zwrX-IjzlubP`Q-X-eB*XvB z@)o(-^J1Ym~#$Bnt#olo)s zzy7($v5yz#Iih9|0v*cEBLmk}5q+>MiAwC}cdwAqjffvK^GZFZ;Y!-bGc5cgQsmUZX1u{!5gHd@_B7F~n-bw+& zfQr&^WU>jl_}ew?0Nmq?H2ML?xpASVM4o4Wlc1Td7iqj;ncXLWac1`u&5ZFp+%THX zWL9t4or4xR_>i*N?WZp_(T~(+^OKw~0s%&E5f3xl;f;&XjhB*0I*N28k?2e&6QZ+L zdo!57tIbW-EzGsnFX%^0Ozo#~qA zCAJ|CT79VG=r5z(#W-sd{q9vN49z6;EbZodR3;g!d$lDH?yL(go7Zf;&_222Z&gn5vesvkd zBU6S8RHxs{|Ht6wqPJ56M9tjadA*mxkAeYlf}CskSj*`XcpNuZ2#sn8!M^}U2*TK> z*PE*|bnXh+uSaO3aI((WWiv%?$9%v=H@Xj|2%#-CFPs4N(d;y}o$taONzzT&grKj(}sx7d)$fHDbLf+0(|ALoET@d z9B5Ezzxv$q+U$Dv(ym8b-ipbgD;u>Jw%zWo%JD1VvS|H_z;*90LrQT+S>kk&1ci9ZMM2sD$S=C13OTs(` z0f&4XdGG%j86GDN&myA>+G?L6RO2WCq97Bdq_=U7;AHx}D4D-t77@HOFjxgXa>`n+ zKD%{a3ea_#)h9*ng7-QwQuqHL1u464&i;fO(p})msM%f^P%Ou}U$olB4Zhq7ZqYYP zNZ9(Vy!4e#f4oEwb8aF9|EeP6uiEmJv-5RX;?4Kvc1N<_>RyHrAZRgH@k#|IK=a3d_O|XF|i$fyDqSMAv%m%QBpZ~>rSxMP6HBHDf9$W z8-?5bZ6rUxH~00JFOp&QC+lxoAbdd%4Nv!q61m@y$v3N;v2Ot=dKQ6K8}@&GMA`Y9 ze?4qdH=8Ht^v<&I{U4$qAX z(9{uT={tMdBy;6V2FSo=mpr)o>f`28PGhaF$F}dS)54cJ0}k#=zjK6VVlfwHD!xZ- zL$q9A2McR8ujuAc{o9%NKY5`S^s+oZj!P!*44YlB6@K{fZnn~C7?o-a|MXV9tvYA@ zzT5V*>A~4e*^)pQcV`iu245&q_$+zrl)S4YsgN3c8Eew#AGN3{JS(dICp6`Sq`3#Pd+DEWv2n*g!d?9G{UW$y9q8$`4U@ z?!vsd(dTgxvttomfJrhBO2nHHvw}|P4-q^zMfVN#8OQvU7|r~<0Wa2`vAq?|AcJU` z(bNch_I@2Q0l{ru7`Nywd+O$ez3DphYV}iRJHnbn@)tNJ;zjPE*8>ow?5bzvZLfvQL=a8ZTsr&p>IM7Igb8* z+tpP&O1P9YBd_M%JalO*3M%t%%W^AUURSN`Z2xh+<@Ky|k8*=r9?adMlu#^53 zbm9C)qTWF8$NSQ2BWnhMuS13qrST0>mDvDKb~Jbkp`5_fAJEFc=Cn#`%I#ZVDq z@$7|g)K?f%7x8r@Z6)l*FPIp*Om-@FHXKnqitnCUxvS#X+^&i=aJ5jypM0tEF4+)cTMtDkQDeMMVH~m>a zFlQxNCkH;!o*rNo9SyM02L*Sc2rLnS2k=won{{vn+5H-tMS_ERE;kr4etXxN!=H`bN2=OQ$(Rr;2V@jkLe8wR zACZg#NyEI%#Kv9_tJIV*Ek#N}f=2rFRdzQ?WUg_|@- zlW`p*4{;kW9M)pfAg_|SnnRko2K{i3Abh&-PW^UL%7Fh)EE*4z{OB(Ch94VQ2y~7I zyoNJ$k@0$LNP(psvO!K_)6xb}ztbV=X zv&((tLJ0rn)Iq!$mY?bM*g<;TBT!UY$a#}oWv+aas+s5a;nct6gqaxknM*%I0W&Tj z*=ZXmno>6vH9G&J*Oh++p*#VyppRaRZoJ2|NWBlNngia+n~!EpyrBO8<@!LL6r_;Q zY7-zTPy(jd-4M!m+B=${oB^hmH~bTZA0C1eIzyy#XpXrI6M;1_RKSYF z7lL1=fwaYG1+)_nJUhF!QZUHRbDPjN)|OoUY3G4`NTxxe8S>rNWis)`rx z4Aoj(o9eON+H-dkFP@QC5D43Cc9EbfTzWL@gCmiVp9MQ}32!&{|fBSE}aG z>o<2#w7q@BFMb6RP;xyae#soYCJ=e@i(XsiJyn7Il%cqrrpKq>Jo$jETmaa*1@NVv@8y*%(Cny#0pb~d2P=%zDO^LDuL zDt}`Kg4tQ+RDjmY@~@3$9Gddt-vhJJ@__wg;Q%&!u^bYw2OHAmpRH2%M{WE89mLM^ zeczv+bBk*g>M*b%E^V+L?p1p8uKVv~U-#maqtZb#P9)$;*1H&v@(63kb5zZQ(Qh;} zvDNWI><`b8xr>+~YVliev4s`~bKZG-G)@Pz;AkNX}bD z)Y54gk7t;D+RGH*8i0Hb?~4XfCmyD-D6aAvYSO_#aI3LK_vy$t zjM(l?O36#b4_(8$H>!w^LDPyG#b&VSU_Cw*xI7k3h-v?;ZT*jX&AtE|B6}UdYYT2ES|Cu75lSQB%Aiyi1(8b33SKQbJR`1kQHrqs9BH;?J-re`SliTI;*{gmJVOji2pSqLA|S}y?i2-0e8-J z9c&1@O@5RevPzPzZRAx_pi)i@_qsts)abG(WJ!LVYkPD~4VdlZgo9{$W2fuoc2S{A zY6h>XAM?fo+NNd&xBif|R`J8wS;{|19htcF**D693xsGikS+`Gp2d0z>PJ)AI%&cB z+K$fW3Itf##*WsvwG!&v1WIZ#hnapV1@3v+GlW-{BmRpokONM*rk%7sZGh^^x!~Zf zcQIz3Kv$@emCIVO2Plz*HGQ-H2*D7HF{1&MVjqccZd@o;6}M9;O;%ib$O-#PIq0f1 zP~GXP?esEZCb_jB=qJzrjUEEfkTgg*ZVxSyCn7dm1N(AyUXqL$`Ppnu!inUrcRTZP zG5@mZ0wQU`RZjee3<;n|kL;Vsh1hrKFH5JZc)I(7@u2K%aLWak3t8}%Ni zJ4apB1?)rGR4LjYPPS?|#8Wpf_ljld#dk-e_66Oe`z9|Jrc2;FblM6lH>k%+OiaC*=cHC2lZg313g(_F;&!wqeBAfL7=K24q~J6rsWBSoB6^02 zs?I1p2aTXcQg9KSF)ojz@(WB7IA&4Y#Ku!_aR1OqXfU(tMhfM|iB{n`4~YH*#CryE z&V#XBobV?@m4^Ufqt$S~jmSt3A!P+7b2h~3o;{J(rQoO<=f?9pQsX-1*OAC$KXe8O zans-A6yDdOo3@9Dw6b+5`X1z-?o&aYKQ)HbPGT)|K_()5HcsLO5jFyu6G0_AYctws52~RU zl1I3W+qR3Wr7SP>Os`KbqlSrX5<+^vFSLl_OGwVZgqfw}>s$fq5(UKH@Z})PSFMq4 z`OSbY9XTDSB$_RAiUvTpMmSs2Zh{z8^xn&m%JVs=+mjLFNnr5rpG7#3zuJezuM>gd zSUEkka%0lAB7uh}L0P4>jCmLBF9qU^!}nmwh9=d!esk{-h-Fm}9gLxHi5*L6Ko=ND z6WgE9iZ+cM@z4y@Gy3mms34y~uB*al1Ym5hgomgkcJt95?A_t7t{}E{)Pg5GhJ@51 zZr5QBg?JVFa{CH9IePKsgl5Y zH7uP-KLdN6k2}KCr-pZnYZF?1iCaeA*5C$(q@&M~e?Wc5rKs_=V@1y`8 z3&tw4Lto;XND9S4>UgPSg|)m$_&vOW_2};zqq_6+KZ8z9vY3;&cc)UVqxDSjZg54k zj7cS;RYstFB{ zvY!71IYYZy0qgNPXCRY7Il23w4G~WS0+r2P@sMMk6>4L}EMnYS;=WrcM>UGeGUUEk zIx=bbsUSMvh(*EXV?5r)h_CrL>Vz*-bGxrfd6;*SjhXL>*Ks@lQ`fr4fy;=Om$|*H zR|-A4O*>%Jw|Vqhi$R(p!#&&;+E!{8>xOJHqQylCtG5dREjZ5;LR7^lfS6twI=KD5 zYCFl7QYyQjbFlONhFZ1 z7{J$8Es{iz?HS3yg@rWC=a*9w3ep&8N5EaXsDT&pCJq z2k|`P%YT(cK%e|W0eIXXlhTB2KGm!D2ad-x{7UvB&AvS1P@sHI-?KMh8f0*Xjh|CA zmpI+!a2BiXT@n)*yGP+VI%|~P`3BvL-BeIBvhBI?@OcZ#bK|h=aCtwufuc%5c4Cj; z0XL1fHuf)C)kb8{B0&ISTr4epD@ao-LnBNHFE)NhTYpb}MLP+!)?^IDkb=`YlF+B< z@Qb{QjXh49v_hOkE42S_Y&<>?RB7`u?#BoV^j z_5w|N(3$kYzW3kqu#*=6g&8eeu{Rds|*!;aY>;oM+O%P-no=k zlfR@0lEm6|T5}X9g#!!)W|dw*liaN@zgH4kE5s9 zQTzO*k8N0aequK3@}H#V3;4tTj3lyrd4t=?ujvy-k#EvJZJ4J?Y#3@ziKF+dfGl7M)orf|0Fyj~lD)C| zZ|3g>uT!T1ANm=bXcnRL)3YqJpMq_IxrU&dMW4(MB2$bX3tl*1VR6uwzd_`E_9~mf z%+7xrJEFH8*G~JN#GXwBM!Vk!y#A9OEB?iD*3AFx1>;}-J*jtw{0}rNs)X|k=s$i- zSpfG1-kL6kLe+f7^}McFJxnT#U*q)q-lkjb)8*n+vt5nN-I!5ZX{I0JcX^9Ru4jnz zBk<-Fs5Xp7UCpaUOA%gx!UCgoULdRXV%1pj->Bv)c^poP>N95h9rzwAxuAIdJrDWp z?S?96UM7|J=2S`7j*{Jnr844ykzl#?-nbxQYzrBxX3)e+VhBL5W15 zQiPl?-zJ2%uj@Z8HfQ~rrNB*9v&OHXT~_7L7Ox2 z=yduLw_B*WDLLji#hAG8h(4}L7Yf< ziHRGXh{-L`5n@RXPZE9k!=c*drtYITT00G_hhe--ZOm^cE#C`6#D{KCesQ6#9kEfsS$O?PEfP^MXu z-UJxkXBJoX;Fig*_9ANn)w~8~^>%klxMSO9{&;)x`Hg&ouk3N1sXpW^moEh8a@aOu zJo=jbEmN36z`8Sep`Y+XsEKdA7d$}aRPgtIa{@r%Q9aW|mk>dgCV)wNN7{{rS9zDC z@>h?YnB^%9*|qs&qE=x8aaC{kC~Wu5Y@chCqqdXsMPA*h-h{kPEF*Go3%c0UEt1lk zg#x(9^*m|BMz*2D#DP@9Gh7zOM1VOBAsBs#P?Q*gtcT^jY!&i8PSK0;)N$SvCZrb{ zB{-16Ap+1y%Bl0d<}Uq(70GedI`Rua{vnkOH!*nu)OqC6Bg0Yk_IFcK<}Uuo)l9iZ z`p2Nr2CHem`)r_wK2Rt31FwgU)9O%Y`BdRF5dl2~?YE5El~5(=Et>i5x%J!GDp!J> zWt_r`y`KJTqsJj(Rr2<7R({MabBB_TrE{MMJbj6;?BQ3i>0@amG=wwVkVu~3ib9I3J+Xkvs3{hI6usV0S0W5%z1>fLZYKo6X9 zbb)8Kls~Q&glJbMiMEK1nHzf=7xXwOZxBR!anFp`$}*mZ-6gFy3|tT7C=SUS&5iZj zyW-)fe|Lv|o=TfOBczv=T*p#Lp8xP}KbQhQ?yqJQbSQxW6AQd~S_KDrU47F^*2Xd_ zIc`1#Jfbt!N%)lmFr4@fK9fCxz}Na=Jv~3u9g7fIQjGW$?LH_ww^NnQ#(Dm}c6~^S z5;6>C`_eVRq%ypJHhzxjXN}5dMK%4?S_XY;50+pnu=<#gZHBoven6RH+3&fB{2Q&o zTr}h`VCg5ky^h&?Mk)XqyLH9B|G%~xd?_8`j;-OxuoD3-#Fd{|~zpj*tMXvJf z5wg%DvP-%hRK!9E<&>(M&)j%53k{)I%%0;mGVd<3Zcj%+lr*M7E-z3iA{DRf3$km^ zh#-s|eZV9=uG$L-lPq_nA=Gn*hkT`8~u*OsXU=AB~nWTL$*t_DPCul{eKSH&&qwZGK~4&%fF_DIk*ARSumNbAel{FOuY zWo${5R+>KaTO{8DKHEC^-j8p-re|j#>i5~&IP|jjZAVQw8q3|>J9M_~z~7qt0~h4i zivk;%ck+Im=CiEp>sOCc{;D61j$H;rH0_Xl%QBc?S%5Q8z%S&V{q@NKt;FWDL6Fn9 zJ)6IeKLE`>yZ%yx`wtNQd5=>fDoX&xrd-x&A z{pL$!rxtJO6Ri~236nem>$Kx&kS@ZCullBQSi0q8EUO=d3-CeFd#ea((f#ap8BeWl zoqlhs^SEVLGwxfDQJ~zZEqWZ`zOJ3p_QH(*#eh#=t zU#mp^xMkkZP>73=aNJy5Gz1JnecZD~SJ#|$X*?5;#6#1!&PT0s+BEw$(p@xc9|ioJ zc$em^neJ>xc<4Iq>hyDVdMdeoX{~TwPult?p?(*DdoT8<@CRENx9QvSLNP_A|vCP~WI(HBQdBnBn`*i~;TmbuX!NFUW zCaKb(Wb6oyOvQxT?CTGLmw4@4Z>ZMROKa)7FTw;0kgtbPul|a=&)xhF9*o%sfe*Si zAiz%{VSW7S9z+E((<==i(Z=V_tXjU~$hr0t8huOvp6(dNB^);d)?{Ri z0E71&z4CV765uJ*ax;F0UeL`^Cow}{MNZ*M>d)DnnhB_@xmvl$j4i=5X=orInuB=v z<1OHtP7)`6Is|hr+6HdIj(UBTz{-Asc9kk<$Br|Fm;XL@o$-giwng(1Yyb7z4*cW{ zij;bh(j!gav#++Xd}7I#qVX>#4+iuYzLaQ<^tYhOpM*-xshJ$E>@Ss*K+;2O_@5O0 z210kYT0(a2cfu-1NS&-0H4;K&05q8aKH#`f!Lcvq%QvVH_ydclAXUvF7SSmU(>H=j zr3<8K!G-t8zDSL&q16M%qgcv5gHv)JHygJm8Z)uQ2(LK+aG5AEjc3-a{92T%7~OzJ zxT4Hq7un6C#{P}!&MJSGpZT;IRZVbCnzH-edM+6UGrW|F-QtThGE52}#Od%WS9y7e zVq5UC1qgKB@rSMUI81A>!-d`cuq|237a)9Mt_V&2BZzwh5H2<4s55d%Gd$m_P@WuM z{CNi#T`Wy8bohjgq@Zej{vWrklwH1bH?41e$+fgwryj5^n%iTu!LVRen$Jx-d9u*` zvGh$kMG6w}hmfJgxsjZAlL*!Q%GWC}&4z?Fpyia}gOIu*b7%bt(a$U{1U&gOJW5J0 zBln0b-u|7^*2;_LY6@0m?}>c%v{>_;wo#tI`kS`KfU#=h>AWrCJL6B$!RE$&Yvn|P zGYvQiI!Cl${8JTpAc}gt(yJI`1NbWz@8&J0{(ixjZcVfmbW^=>hp;>TqWGXgk6$U$ zgHrvY@!ERHzFQw9EJesaQZ@n~#uFJDjeb}!G*{Yr22aQ7SwpaBB-4n_#gVE=5FG?! z%r!GhF6?SB5+(P6NS_r8GraE`Ara~-83Vizai0xh0H@+Y7~I-knxfRpOe&#V={avB zph3;fLiNatilqXh==Xr@@YTO5LKN5vJ=l)3hWy1==w`;zL`cA571aM`IY-Sv&vy}f zDCGf`*C8~vs_*2oac_~cac@JByXd@JRO3|L506sQ-bmMm)jpC&6ZuvDb9nxIE$9cj zG`}g=ti7P&a`Axt09tVpA;7xQhz&;mN$&su9}=hdv*KkVcdkJ3G}GV=I-|^G01+i+ z#HuPeSw#yXj4#Uk4%$iTcm}EV<&zt2Sr!eV;@&_2Z~p2a zGnr%*eGJRUvoZ~>J`t;OZhxQqE9AdL79F2PCl*@0v;5StOL&7}gvOY2oVTjm|6f65EqKqX`oWZRcdPG3m>7Ei%yW-Y=^Pd?y>!ITb_Bw%|dp&*L?Vr;q!q z7}9hgWase9n)bkkxEu=KN1|UMSs3ykGWam&ViwBbRz-$`mq>L5^0T4*USB*ND|pl^ zouNqrjei%iVKLq|oY_fYUizOkAltLrQuA8r-8_>N&d!St?NaoK^i`=D>XM9)qZLMXvV;`x~k3RGNc|sh# zxAj=p{~Dx-5LH^invY@ihtVn?#`Otu$&_U5AbdRS8kv=i(uEMVsZEx*kIP&joksLP z0Hy=jzO@h%%ba`tpDjT1tnHeTkVfjqfhR*bk%NtE^TYMYnZ+@&p?U>jqNb|it`6ge zX5bpsSt>O6^k57?WXEewOSNsX7XUpTJlS4d@au)rEB9Zo|Im~m3%ih62B04OShwIg z)talvf5#|8#F~<;s+6B7lvbj1W7^d{BvKWf>3faAe^2F9&oC2JXLuBfr}S|q1x3IX}#;(Mc#xaXq~v?L%fr{<5rlYjAvv>+kC?oVEHy&yc;odiK{ z3KbJ*RAo^O8?S0;YRBq8X6idB++7UuW3umlmjuBmqk4%>IHk;)rX#+C~B5HQBSO7xT?ezuSsRUoPHiG%`i&rFOvh zrEe;Cm)tBN*+3VY!j4-mK&Qh@7p7$6aGB1p5b)WEhC;fI$s1$EvL83X8yu#9VKdVM zGdk8glQ~I6Yof;;F%~QzOT~25Z2IyQmu9sLy$AEBihFI0g!go+KG@W}Vfg6Xem>T} zUiWTgx;>!YVAQCe)>q0015_GvkYCzI_zmhqKAaj^L{iR9Yz_S(mW z-YFjtJ}wz>thH}`v826kb$o*KllUpxx`_spyF|ry@;|1cRaVAQ*wQ)GX5`p|f}V0y zFX%#PVJ0%`oQ{{v9^n!mZ~f$|ee9FNn^(bvGMOVkh0nQZ=YEJUt~%%_%4TC!bEcW$ zB4%r>DrG`+{I`>+5R+c>0;>Y$3-Y-G8z}3*EC%HV3`M4VXjT*m`A5A*&6!|c6!Syu zt(s?J`?{Xz@ANFR=vi=>u(M?9V;BFQ^Njo-Wi{+MJGviAKX2J8s@-z=SbJ(P)C(oLdqqv2cB>oAyPUaFTy~VlMru(u z=hD9`Cx;E1ySiV;LiPCcFT>d2=rP|nVWD4t7evJVXjL>7i4$M;DEU3^u>a{E$5-fb z<1fOcnn&xTNp9tk0=kQw3WHZLeLB>Y#(La=r#y>-7qhIA`z*_284+J=j)Tl&%Wvp6A ze``0Kv8TRVJ>0tJQ-=A!M*S3U4wB6kBz9%8ZvrP=VCtiJ&gD(0SJ5}_=iIwQYh%A1 z-)=T*eVsX3XY=C{H=#=LP1N1k=SlaAHOE_P??eu}=jrrjC$gLEKkxW5;CoaTWrpN` zS4u>)GdVJ|(=0yehgg{Mw({B8Us*npPkWdDbB}RBr=u@H%;f(BE@jtgpRy~2mgRpK zmfWw;9X>|$u4;5~eRwj4BFR~&*edrWu4sct*hzT&&guv5!m-I`i!M-R3KVzMX}Aek zYu{&qB#1zIdwlg~EbV_93m%?B$MaZsn6tXm9 zD0?xO5mUo7+28A_bIz~d`&<8fKcDxUzdFUtGxI$6eP7r2`YyuCO7#8{(x}Ldr13j= zHL8@hhn-Kmk~Rb1mMXS1nJB)6`uYan=P^vc^IJ(rPmVw?vXERmCx@BTRj{VEoR{2o zK8>T~#%;5P!iC}i#fw8rT*kgJzALpnZR3{q7>bcsPX*R|B+kr;_FCNk&7Z4xaBBc$ z-}Fbe8wI3dayv@fq&44Rsvl)}o1x5u{8L*E>r(yi{?2RO)3tdmHLs!I5DGKePpRoQ z_o5Hh`i%YYXnL)mv#oM-K}BErn_KB02kJj5puYXnE?X_W;ERh%-xU~IVjCuL#3*@k z!FM;ZYX`h_$-};b->u7#{arNgSkW&FlWp(Jzkibdco6^B{{Qtt!K52NS|f+!rhj|9 z{`@xn=^rM=p(qQ9OE&srp8D@z{_6+DBK}s4v3T*nTczJ!`Tu?&U_?T#tdmUpfA}$6 z*d5s_rX06*M!*T71c4>#N;?$LLp+;P6us&E)m<0y!r(H#U9#mW#7Gl>j*_XHBhe#-z49%gesF&fsa*KE z&x7a=l|xg)Z1y6Dl|!I2s~8}7T=h>I>sL7^QArWO#~oqj+zu*Ip#_v42! z5F(p{NCAr(!SPsvAZaPz)~oWBJUxOtxEWem8+!K6y=|COSGmP(6lPUEgi0 zZ-Mx55a36uYwuRvrNR10lHr)Q*Hw2exk#77>zB+8UmIKb2w|5?`H~6BBzEnDdeeAi ze~0`PXR-B579#*z%1l?dtvfdI)4FCwH};Bk`f5^|i}HGd9M5?W=@1aO#ZR8iGqNX`N2pqVUkrL}ra#zOoVb2*an zS{c|JzbZLp$ft*tq(RQeBYT`IZBKRH0VtH_Pe_Tk$Cead%>Kj&p)_ zo?^-nL`zVRa=8v{zl-hyqT~)zYL6;e0ae*(58rU^m|-OCh6SmA=78|JVnA9ERb8fd zh7wj&{KEpMOl+9)voS=sG(#t+a0N5DYk;7|Hy7j8r`;%!9N-9FIks5&qRmcDM3P{M zWSr?`A6&a{!$=KejJk(3wiX)*+FOq2wE7h8R)_%6OsLbSy)u=rKYlQ)y zk%aU#F#MotIJ>4Qbm9VKfGq*l zyVrs9Sjw*m`Bm0GZ^rZPLv=2@V2b2=>o{OXU`O&UJAseavx`>FTyi} zZoUbrJEq3TJbEOV+zjt(s_E+PPJaj^qAxSTR`Vt2*dYF*I^Z3$2K^GS>O{_c(H-)p z_-j4ZuJJridK|-+4`KEclP=9~8oJ(RW`4TkY7WwV$AT_{>)kNIF+nmx4m@FKuFh(zmaFzB zpTx~M+>68i!oQxB#-C-4-~Nl)e4^y)>QuuDp-@=d>>axqRsZP9DBRz`@)n8IZbE?l zCXRxi)j=PlzwVURuOw|3tln;ELkUMs5GKWs)FH8ODj*STYq#?HfXHSNw7v#6P?s++ zD%SaM&;*s9VpxXfgtYmcR2}rtO4iD~pDd*||BTUVx)RPN9ZRKJSv$w`$9;s9$6C8p z@;ZI&(|bTeX--;-#N)GT^L9Sp-lL!%pXg?wNsTirM6`?AJY=sGkWhskdKyF%6yN-! zGi1i6tpW+lumoNEq8?EY@d4OiD%f`mLDzSg;0APZUFn>$xjWw@k-Vq(o#5T@v&QHh zg+j%jczqeKcJANoL&F_0elQWr-a!mF{q`dff?k*-ClA$_$t=&|H3ySL`dZiHKoJ>s zFaZ7BKtN?*bWjZvYn+=cLH)#OfarKj#6@0<)ZdG{K(^HiXMdHNA!a`MjH^f(Q`=mu zkxD^p2=S&>M2+E?8J(N|YRYg6=V^(gBYZrO34PLKcPi3Pq=&x0C22XobCh$8ifg^W zyYp`Ay~WtM^W|`2Brep(Et3SAk=@<2;#E1a0$rpQqpG(lKo#^biIe|T3{Nk)>9R_? ziE&ku{Eu3Gww0N65QcRn(D==pTTd_bS#$sV+U>4*bXFd!j%MgQ_TWe#9hW$6_&8{_ zsH4HUYr+NR*Pl=p+9w!m>a_v^ktRc^)!t)2rdCj0L^59pBpn~(7#G-Ojx%?VpmOiq zf!0-U?Kl#jT3}+tWgNPcI|OXbJv1fh9scdB%-AX6f_aDQld|!K`30Yg)F$NFD5bvuQE>Lgr6unDStwis zZCUokUX0_OwHV#`MWc@nrYqb6YUvm1W9Y*lnD2l8 z@qO(WM2@Kz-?}(gpDF*N=uB+2c=XNv0VcnzE*~Lv#>1TVP8& z9tLfQvvbRh*UNf~q&;mKv~}HOS`dOeT=L|8AEYGeJ;cxt{HSW_4rggk1@|?F8J!-$ zteLh+JiN@BV>WvBhM|WO&;NJ}F8xUAP>)$y+y&pVJMt@+!}A38Jbc1MfBo|omB~G< zxZA1<+)k^QMUcdM_LPd&ecJoQuiu*cr%ov&lReW)flk+8j8)9s`Wl=A+OPFq`Ff5% z$ywK+RpZ&VR{x`$XV;LU3%@?61^l23e0=(LdG~TNh zTTlBFiYpEocOza%k!7`vZMf}PB<=oFLhDEZ7fG5cqndY*)j$wfwt+rlC+Yo;mq+z! zed=o~1p-a+gTd{FcG!bwfAfmCY)U$<$ zMKhRj_&YTL5k2!PVwiosKBx@mA5v$9qnnG>?31{K3KlusPPKG76h|oNIqX;Z+;}W` zNq8#7#BtSrswT7dGcZ5U>vPiL;)Wijm@U^NpTQI;a3HZoZ44*EyETr?n8diO&z#9r zwlTd{t5vWn>Xo)gV1N$%58V;TdNw^{Y#bv+&>s}Y7Z$D3xD%Ianj3s?;$X z8jPD8@dGo6M5n1Z$7Ve^ZSIuUok&X@a#JWhL+5GcO(>djClP`O9`jH%o?ox9p9ts$ zjwTU3e1~%c-=VtJA`&X02NCRa{(J_Pz=(!}5W&b|@ofP1y1FLcOX_0m7I{;KBad2S zo_zA+#H0F5`jSqpXc29?LRtqeV{0%bRNxu-u--Ub#TF)$F^|*h`Olv6CAA(V4lwgB zP%NyZXQ$o?xACm9e%6W@*Ui#dZc2HlB)@y+@@5AX-!(#3=Jpga?|J(y+J>Jr)L(u& z= z{rSQTDZT8fG7e2BH3~UjRl2`2G|?u3QJ2DFvI?=krJ)%Up*$CcraM?u{mbrj!on-m z3jZy})Y9Fk$`YU04aQ?NfeD?l+mU!b+fW`PsPOKaXUHTXA|B}h^ob|Me>i&K9_QBr zx-R|F!E;TwWcaB`hr?DEhl%4I>9)&c&1Ewwt6a$lMN^bUmfSe^t1J3hp$Eqi_kgNU z#S%NVd-{k5EI&W`0iiar*0gC`*GNlh)9Z>j`K8x7V)hZYyvhyi8&XA=_ru;`fWj>Z z#d{gpbat_s z(RYe?BXUX+ZJZuf_R=ZT3%|*VSII$KLHdDGPXmP|&+@1%s-W6DpE?B{tKq2@`E`=f zjdyb_jh$Vv_PUCFT*uqalFjy@uF#Gj-W-K^vI!oNGq$;OzIl_F*+fXl9BZ=!fxGoc z?8&p?Ym{WVf2{k|=T*M~r@EA6!je}!_$8T1^r9{nC&+nz+SnZ!o56B`M#$3k%A?bQ zLkG2eM6NyG=KQ65Vf_^2MZmmt7U2h5HDZC53LKcN9m3azBx1wng);$(?P3It3Q~sG z%@5|k2YCDX5fjZ1-N)vFALwvQ&t5eUne08*x!AEWEp&nAd>x@4xT3Cj> zgn)J+Qp!!>KE-sVZ_V!)Y5;p2bELQstdizy&5gaq2w?;@`JG#hh+@|jS00C^gd2%z zXmqI)5YzwKoRqnCTv?WkIkS?3tzte6Q{QW{x;{@U2!e~O1pN+yQ8#H6%mJh~b4JeF z@MX#k`R_duY|2>wIF-m^vW7!vlk@P&`-iW)B-3WAWJZ=hS2jqmtt_~Dw#h<>z~2a- z0gIbOuH+qPVeE}@n;(aMph%`+iAh%?1{!X7R>D_0xYYL0bG~0hx?zg8Qtxqr2#c#) zD}<=lw|q^#&cUmzt{StF=zw)&-H;8=wgCIE~NOvJV)K3i_Kv3-Y?-8rhy>~%kTjhy=7CFnS2+(1ZmnhA3I!7!!ey;T^*!&y@sVWvWT?8oSt~EhxIoF?Y6l>N}%udfXVEetrsXP zv-TJH4%ODrCrV3vQI>>+9wlxul7yX}R2x&0<^D(eID{ z%IdERvz%b4lBHp3&XY4&9{a98S804;W<-P$po3|Z!f%?cu0PY$`z%{h3GK%i?codF4O)7Oj4Y$5tET>3^fmR6SXHb7 z+?tya6QNVK!#2xMt$Sb~vn`P^4_QOqgX;vdit&<^>ckAi<~$urs#kS^p7ABOJLl1L zEbg;S1zSoRAymvUg3BN(lV*MP8&BrCO!Ua-i+7Lb4G8BQiCdV<;WW%eajt*Pw*V$}y8MO*yn8?K8l3DT$VdSUvThAMCurPkL zix-`9XD)Ri<0J^tbFhebcXn$~_}ko$4P#QvbFb1$-vi-8#n3WoKmcX^OZ#MAi6@G8Y%$>+ zfw{*}q&Cr++4Tl|?@XyfFcp(25CtQ?QujeGd57hnuoM@!%>Esh*)~bkS#<59=Wx59 z&od_C6;ck23G>LOLFZZ?&)Hz1ptC>#CtM-%-e?G4{9-Us2$+>h?g7RltDFeT#w?lX zdn_nnd_Xc%*(Gq6slkqD1ZOnsEsAv?DN;KEbpub!1p`!RfdsLUIlDWS@*rHZa%PE=*89sS0Jcy5%SMTk?R-LGz&sDjee?O=98G)QO zwcWd*lGCyA()sru#JUPBP2bT5yH6k8&T6O@-J`AJY$FoT^HzLUZ84?y*MTS{JYqc) zSBVC|cc4fhF;&k~s?H1z~@w*2*00Dd7<%_Ns@A68{Rn?Ju zVrytjK$4u}7lzd)@lUT@ZQ$)l(~@1^%{qq(xil-+OP->pOe`8?nQ_eDEne>B(eQT6 zSe(uIG~@O-6Qeim*SuJwpa!$QM;gLaO zs|r97%_hbn?QLJw)VTo2e3Z~B=#rG3L$PwKt6e~2H;mB|6istY>n)ruXNOk;=F_Ln z#w=y@1;e47WoF9uHlk{eygfFOk)L<(hXC7g0*IWduHoG-i#B_p-o}E<>dzr<2?;#Oj z3Ojqx=+H&q+eo|iJ?A8?N7%bof_f<9QWSn}{NB6!Q{Gjj*pal|F-(MES?x z%6n`G-RLFQdx}iOEHwvIemo)YgSC^qbHeGNg3a4;ig~&07CS4jQb6;$E;_*2YMP65 z_g)?E5wBK|Ja@-c z?E#dZWV?~9>st;PCr=d2j?Y~eTgo!9aZSfWxTw!2cOGGcfu+wTL&7jHecfQgBuEBM zZ~MBNtpKS=TDw>|!$pWl=G6-iC3)Z!)wuwj!PDW;z0l@?ogEHk%EwmLm#k2` zYN6+mot=^-==3Mh1O#4gRnWyaS&!NX_9#6iNImG)mQdNTlHq&2x3x)TmZK--SmqYbk+fyvm;j_S1s8~$9ia#-!eAoy;*c1b=vbx2! zc@267@$RZRGXsd8c;ByNRT={J`St*m%(MyPDVOH^nCQZfm-z|Jf7w!S6AU6VA;w*` zN#I<9pdjq zEtmzcr=j{?gm6S2erJPh2u+{r6Plkp#D5v(Xtt;Q<4GWf*$TSke!4=|*U6|3fM8(z zj1jN2iRC#^6p8?xal3GCqxtG!k4^%2q507q4o&S`iW}5JvSpDQt~S2;B9qEOWUibehWPgwl6Wg#gX@~=e zbRNeW5iAw3e1A*U(rc)`c;ZKnQMLwrwd4WKjqrF$#x7_%0(apsF&aPMk4i!>A0J%=$Wx5PJ|D1;^6Jg z8Co1)yg$`_d4HR*sW+Y(PMJ|toaKt+%yXT)Ajt)8G-|=Q2x0$mgftCE~rl&?<{cmT$;F9nqi1u zZy@0~%qsD>2)r++?E)w$h_+%PrWm2@8Va105g}--_JxOcnZRv1g2QfjQVYj;>+m!T zg7qIb9s20VuI{yfLXEanFCtHWouyC(|C1{4nT^|X11V#us6Dt#r0(^*q5QDGI<^dZ za-7zf%jPQ|xW@6=%q_0lYbAHD4{YJmi@I43p~C!cLJ$bq;Vfb^Mml`4O(YcJ`j#_;O$Fo7?4WZl;RQp5oVgtQVng%lToS0&Wt^wYP!44F=L&9Jry z!zAiL`cxn`Micz_3afl3ETOWygn__TUl-R3`8=%}=L9*F%lH!xVAWg^43)2&o>yY(>#NU365QYr%Ci|k+87K;S27;^syi~bHr|RAXO=Fo+|ckis&3j7 zP2fM0qD)$9YZ7tWshfIUbi8fyAST5?Rllypieq}?H&oO9LR*w%^qPq|lN6O-pKry^OByw@tETiO;(ez+BTHCmigo_l$l&hB&JKKzZbkLO7G zi6ga350QRMya%#B&GgVaY5UZqxMJsOufDl(GoCGOdGx}gjbjm$aN~-Z`xk+Sbd3H8 zO00sBL3G1%Ayjpb=0=iQ2RTD>KlMfTJ&^YgIfKp7{q2O%gDo0gM$WMl-&v7&#kWRm z`Yj%|Wl~Ll>gob#=%Hz0v+zo!_c}Cai)Yv8sL91q7;VCALNkS8H)oG38gXFJ5?n^p$)fy>SXeX@Ib(5q`pbV6J8r95(hDudYC{U)>qFdCi7H5 z2{)D!qgB62H#TnStZ2uVNgd6;(mO+M>-c(lNTYMW3A3i38t=?>G}3U+Mskr4oDBe9 zmEuqWtG#ZV!ow`{CTqFW#AY;e!0^#3@S&RaiJpdG*q5$Fus&wz4lSh)FS)pB z6T*0zsq-*pBzC7GX0GBLB`~bnCVce52$wvEjf%eRRvJh@P=z`*>`p-2aupxkXgt-Q zpipQ;yiEMNvNQniChVCT($HotkYfNxEi99c5Ww_HK&LsnZ8SC zlrGTZj3I_Cjf%Ck6hQ$b9`0|G?tI7*CT=VI&&j(#klh2xSnaIAV8a6~nJaU6{>O=; z8*_&E&mMKi_{AEK<3eZ;JqNBEn>+)%W%FFg=(%8VRzl+?rfgl*rGvlB!2l~$3(spF zyMw|+})xuDd*e3F5`u|GOvHS29MO3@|~+A0NHP+Q0bp_e9fw$GQ*& z1LaP5niI3259E1ZS`WS!RjsHNj`s<BfHlK+lEeDP0CMjW=ls47#hm~K`aw*x^R*10kWDN(>5hw!eh>8hR`GUoU<7kz z%DTxrUwC}|fx8zU8h?L`DDrkY$5p=~sfEdBs){zEK$PRXn|G&7+N)3J|4w^mzwPTg zjp)|E0-jcfRNM)wokBhg53Lofz{(Yl)g-qarJ@>)vLPik`m*RU(ft z&S?EX6z1e>o;;-s{y=2AdQ=Z>le=P`t&y%FV|4=JmfFR!6VG+pSBa z8vS8Thn)y!RR!A7 z%HND6zkVl;`!*azN%LpMe^)u}f;m-uYPC>fVsIc3T3U}*(;^wSUWkePROJ2Zcdu>0 zgA-J6wWMLtpFg}M|M+I$kwIK)GfD1uo5Qa+zzbd;qu=BA-OEqz#1+6_s{cfEly3_B z{*M0Hf&H^T;EXoD`Y_gf<@e;2|FA=Sy-!I=pozP6-1?jA*?;p+zK}-fsB_%&?;hIk zKJq`lhJgVv0G_8E`Q0-3AAjH<{ze5nY>5xjl)sIJzk4$OUcLNB;M}acjeptbT-- VO&%)h!W#Hb_q5Tel9Nv1{{sUYEI Date: Tue, 14 Mar 2023 23:35:27 +0000 Subject: [PATCH 4/4] updated densenet example to include quantization --- integrations/torchvision/README.md | 4 +- ...rchvision-python-transfer-imagenette.ipynb | 39 +- ...ratch-densenet-flowers-pruned-quant.ipynb} | 1127 +++++++++++------ ...rsify-from-scratch-mobilenetv2-beans.ipynb | 59 +- ...parsify-from-scratch-resnet50-beans.ipynb} | 0 .../densenet-flowers-tensorboard-output.png | Bin 477355 -> 700598 bytes .../densenet-flowers-pruning-recipe.yaml | 4 +- .../recipes/quantization-recipe.yaml | 29 + 8 files changed, 809 insertions(+), 453 deletions(-) rename integrations/torchvision/tutorials/{docs-docs-torchvision-sparsify-from-scratch-densenet-flowers.ipynb => docs-torchvision-sparsify-from-scratch-densenet-flowers-pruned-quant.ipynb} (61%) rename integrations/torchvision/tutorials/{docs-torchvision-sparsify-from-scatch-resnet50-beans.ipynb => docs-torchvision-sparsify-from-scratch-resnet50-beans.ipynb} (100%) create mode 100644 integrations/torchvision/tutorials/recipes/quantization-recipe.yaml diff --git a/integrations/torchvision/README.md b/integrations/torchvision/README.md index bc58efbf18d..bc895aec666 100644 --- a/integrations/torchvision/README.md +++ b/integrations/torchvision/README.md @@ -39,7 +39,9 @@ pip install sparseml[torchvision] - [Sparse Transfer Learning with the CLI](tutorials/sparse-transfer-learning.md) - [Sparse Transfer Learning with the Python API](tutorials/docs-torchvision-python-transfer-imagenette.ipynb) - Sparsification from Scratch with the CLI (coming soon!) -- Sparsification from Scratch with the Python API (coming soon!) +- [Sparsification from Scratch with the Python API - ResNet-50](tutorials/docs-torchvision-sparsify-from-scatch-resnet50-beans.ipynb) +- [Sparsification from Scratch with the Python API - MobileNetv2](tutorials/docs-torchvision-sparsify-from-scratch-mobilenetv2-beans.ipynb) +- [Sparsification from Scratch with the Python API - DenseNet-121](tutorials/docs-torchvision-sparsify-from-scratch-densenet-flowers.ipynb ) ## Quick Tour diff --git a/integrations/torchvision/tutorials/docs-torchvision-python-transfer-imagenette.ipynb b/integrations/torchvision/tutorials/docs-torchvision-python-transfer-imagenette.ipynb index bdf0a4d5685..69cc1f0138d 100644 --- a/integrations/torchvision/tutorials/docs-torchvision-python-transfer-imagenette.ipynb +++ b/integrations/torchvision/tutorials/docs-torchvision-python-transfer-imagenette.ipynb @@ -276,7 +276,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": { "id": "KCMRFLFN8024" @@ -358,7 +357,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": { "id": "nrgF_ur_B66y" @@ -764,15 +762,7 @@ "id": "eJv4S9fkGjdO", "outputId": "df458b06-3ff4-4a0d-c1c2-3689799abaf5" }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "6\n" - ] - } - ], + "outputs": [], "source": [ "img_path = \"/root/.cache/nm_datasets/imagenette/imagenette-320/val/n03417042/ILSVRC2012_val_00001144.JPEG\" \n", "images = [img_path]\n", @@ -800,30 +790,7 @@ "id": "79Xj9eqvJXaD", "outputId": "2bdfbe4d-ab3c-4cc4-c54f-a6be6cbb2b2b" }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "

" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "from PIL import Image\n", "import numpy as np\n", @@ -857,7 +824,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.6" + "version": "3.8.10" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/integrations/torchvision/tutorials/docs-docs-torchvision-sparsify-from-scratch-densenet-flowers.ipynb b/integrations/torchvision/tutorials/docs-torchvision-sparsify-from-scratch-densenet-flowers-pruned-quant.ipynb similarity index 61% rename from integrations/torchvision/tutorials/docs-docs-torchvision-sparsify-from-scratch-densenet-flowers.ipynb rename to integrations/torchvision/tutorials/docs-torchvision-sparsify-from-scratch-densenet-flowers-pruned-quant.ipynb index 171c56d35db..725441a825c 100644 --- a/integrations/torchvision/tutorials/docs-docs-torchvision-sparsify-from-scratch-densenet-flowers.ipynb +++ b/integrations/torchvision/tutorials/docs-torchvision-sparsify-from-scratch-densenet-flowers-pruned-quant.ipynb @@ -29,7 +29,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "1ad80edf", "metadata": {}, "outputs": [], @@ -69,7 +69,7 @@ "outputs": [], "source": [ "NUM_LABELS = 102\n", - "BATCH_SIZE = 32\n", + "BATCH_SIZE = 16\n", "\n", "# imagenet transforms\n", "imagenet_transform = transforms.Compose([\n", @@ -236,33 +236,10 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "8653c9bc", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r\n", - "# Epoch and Learning-Rate variables\r\n", - "num_epochs: 10.0\r\n", - "init_lr: 0.0005\r\n", - "\r\n", - "training_modifiers:\r\n", - " - !EpochRangeModifier\r\n", - " start_epoch: 0.0\r\n", - " end_epoch: eval(num_epochs)\r\n", - "\r\n", - " - !LearningRateFunctionModifier\r\n", - " final_lr: 0.0\r\n", - " init_lr: eval(init_lr)\r\n", - " lr_func: cosine\r\n", - " start_epoch: 0.0\r\n", - " end_epoch: eval(num_epochs)\r\n" - ] - } - ], + "outputs": [], "source": [ "!cat ./recipes/densenet-flowers-dense-recipe.yaml" ] @@ -277,7 +254,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "id": "1749e00d", "metadata": {}, "outputs": [], @@ -292,12 +269,12 @@ "id": "ee67c917", "metadata": {}, "source": [ - "Kick off the transfer learning loop. Our run reached ~92.5% validation accuracy after 10 epochs." + "Kick off the transfer learning loop. Our run reached ~91.8% validation accuracy after 10 epochs." ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "id": "d00d175b", "metadata": { "scrolled": true @@ -313,12 +290,12 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "fb1f4f772bc540b0b3725dddfa1b0f49", + "model_id": "e3bff056f89743c3a030bf38186113dd", "version_major": 2, "version_minor": 0 }, "text/plain": [ - " 0%| | 0/32 [00:00!&jf?^U(xH^VfHX)5QWAq8lF}_Ogo<>7NQ|Ng0s=~RcQ?}A z-NVE_d+_%>@AI8=zCX_Oeb@QxWnIJGd#%0Vj&^hVir>Tj786czRXYU(<~AGS#EX?74}SOTw-?a=(VSIm|4dZu$QDoRJqsSarZg z=sK-e>v7Oi1ILOTB7|0Zc?kT^o$~clgKhAl`8ea7-(TjB)z+f>mW78uv8PDDWMmTX zk?Qts{Lf_Rfc&v*dY+pwKX#s!aE9wNB+5c|ipW2dK8dU2lE3@agK%aO>fz7FGFz+* z*W~fCh3=g6^dZ`VMQ@uitg*b;|K8VqCd0nz@QF_Llac-C4c%^ed(MEyOHNE48-PJ1 z@EYkg*g&gW_`^c=vAKoId$+3OM*>FgNAB!US;#5KzFwp(D4rsBeI!zR^Y^cNd?;H;+U6CS&dqUl$*3Dqrb+!}gG83z&C*_P>Olo4%IF zmw=1XY{g19tI!Tp++tNE?S030g;cBi_8Ybv_nPm!Nqx9RU`A!`6e`O1d_5}V>cQie z)pX7Igz`?EzdX(E8by=%N@yF=-Y#gTks@oy8@WAN;?M@fjjPfP{pEOG1$eh)u$wn>MaBJ}csa!Q z$nkn!a+112?6p_-OiJa!EglMq_u+exfr`R?(^{{>j&nc~+U{qmA0478IN0!k^jJp2 z?1n%ztqLjI!~#({-%f;L{a2`6uPEgyV``fRypi%T`~2N``Y&OQwt5 zx}(gCZO`X)HHXN^>wQ0qKWlY!BAD~9Y82(3B3Ez^;x z?ABXemQlJw^@Zj9!&S48ahBdIl>735(N|chm1PEFxaHm|#jLj*ePc9;%##&ndDt%X z?W$Nns;qd7VLQP$Vy_6F#{$pDMie46xm;O07ycLi~5zV1jNaW!}Dcw2aK&G zy)V`Ho5)u6(^x@?_;sGp2(>Wsv$eKn6h7moj58JbC75?9w{@fNm1kOksj)ua2?hIt zYihuwdMd_H_Bjckn^Kgpw*^febH|mK z4D&bUZ&fE%Ufum5m%%&mX$^n3<(AoXCweCeCrKyrebHZWXCKBjm}8EVPgo&Zw?b4o zSrcMMW8Gt(Dm!O5I(Gl3)_jkE0;Z?1$6^2z8O!`Pbkr!S?v zIK8fVaaAPy#7wDSpA3A{*Y@Gqk7w*;?4(z@y?kq#cR3;_Cnq^4%O*TW)2(!aexxSH zQU{Xl_iRY3NZUL&^M~>Xb?$4uNBQom+hhqUB^l@1+CSb6w+z#7C~x>~5YwlvC@uD% z6&n<*JeS-S+|Cp?nAS?mlrpK&uX&8|KbJo?A^ZJ4fygi@S3vu#)>q}l_X>4v#xC)% z;$PLSF!!W=T77`9jw#M74lF)P@PqQ%I}V{*%;co6uT66 zm3Y{CSe>q0t(R}GZaf+IF)Wrdlo_`EeBIgg&^2joXRIb4W&Lr0f0VzW@Lki!dt;^( z6NmEjx^(G+Ck|0F4{J2eNilaYMi`58vh!0?M}kK|v_Tz245aFGN7u)gb|h0ps_o9O z^JQdDWgj)^H(9?oB%LHfMTAE@4sTYljZmjQrr)GTF|5)SJdk=dW&T)X{~^Vvya(0- zUcLP<3TeHsn>?)xiG4xbz*to&T@rDmfx z=l*Uu{CujE)liV9h)2&b{g;n}#p{HZ4`*{4Hj+!yAGTGFSB{?NlZ~|Yy^2*U>CrLF z;29DgbFbOH_h`7chj%i6a3@33X4jst80Ii57RcY|^43c3_yfaro9o=c%)!rti6bi` zDI)Jhl11_D)k_>RD7B)^C73*vySYQrv+)-sb0May?VykybZiX zM)bxe6%$n?Mk3`iu3xJnoKkj2H%>;Tn~WDsR%aGp%*X6JU3Lok(G&iP*DU>*)sx7x z_dsF+InXto+izPp2AjD)Q!(?X1`$!p#6w%-cEkb^g5>wTLh!=gJ5=tn&GJIEq4}_q zSy{LXycQ4!vbYU(uiMgWTKH@Gv(9POzbU18Lxl3YLrr^ApL(3)8&&*`V%{~sLIX!# z$JdUq4~Ff<(TiW+_V4vud=U{tlS@bfxNwvfLr9>yz=1 zROUMh&lN(M88W1AvD?TG*H~??DGvmje-IcDND$C4Q*2R>lB86OO1V)cv}5cejgCEg zbXEB3;M-BT$(YrK4bu;JK&WjLpooS}6Qp zo#GseKCkDe^|%U&LxV(((a^kfySlB=Et9*3<=u>dr?!_Q`;2;Udmo?4s;HN z4pZcwXBa)5lv@nZW^)hSZpmE8S2l^$RojSrt6EBRhj5XE{#wa=uus*n!g<({OpL=* zi-F*dkT~)u1F6iP2Bk*qHyVFvgaw7cQ{HPVs@bO5i~IH-5ew-H3HQmpdev>0W+7!e zlehEdZjnd#m+p?V!#5$?9S5;xE^#ZueL|l^-pqW3J@)&-lbN8R;?RAXUgv~gD_#EC z{7YA3$+fzK{jT1mM+tiIaD!$;SM1o+x_qRYsng0rnLVeWgpR6I4c-41^ump^rd zB|)DHypqSLw08bZaL`lJcgt@qFzr^d68 z+PY)BL+NRmt{|P@wcyT;nDZaUzGQ#Mj3e$xq^Z47``I(o6MX#<(~Mv9k<#+hw6Cg> zPa}IC3HNJF4Z@9ls!!!cLll2fKHp7!BIQ-W^Zn=Iv$G#XSwR{Ii6-$O=h4-z7#EY( zPrX8YB1VpNnzK8jerq0Ov*d2&9>cJs@^R0OLoJupwO;ci3@@VmrswjJPVdOIG3Ej{ z6OD4eLxqWm{1kLbpZ)T*w_DZP$?Bt`-J3g!(?jKYPP2P{$BL28@NxtkwO&jvl|Zg}VY659F>?9Utm5@S;s|rA-JCD><-fC{QhuO;Pb&OCh|+&-694meJn3MRP^W$iR>S^-Ss$n39P~vC(^LB$ zyy1r3(~l-+ZY~7=HHPyi*EVvq@NcLQ-kG8N%*!kL+OdFbRS(Uw(K2Cv%Y&K4H-E>;e%Uwa4&z>2GmN(L@?c+~fBKYV2^);)0iG3#gguKH?E z#LXRE^S*fLU}nMV`PvaT4xWUkIC%To!u7=+&)0VLF5;e&%olHngZH>6&;{E@n<-cb9kDmJf)l*PJNccay{zudQ+*QZL!dcegH8`iM)PK?IpU(f;_)kX( zJ{;)(fr`I)zNiHeEkz>1_iv&}k%;kqE(7VvXf3Dl47`F|hWo>R3jX8xdj;T_}vgmMQKQTEWHZT~`65;A1lJKAIp->oXBxuJHEBus9DV>jS z&k#;O#!F9oU0)PKR2Y2HD9oQhy_jGjW7BJMhjclUn?P2E;py8i)cn+QPC7A+?iR1& zrn`@jA7+ss-t6Xfj*S>YFjd)=tD7_wyJ-wg%<5Aqr`vseQk65?OS7UUZ(ih|R&fp7 z4>RYB&W)>CWAx*pZ3@k6kE@Blk#_renyH6gqmoR?Smm=an!Lu#cYrjZ4!Kedpa>Wd zXxeW(YdY&f1|JsWQ5`|XAV%;%mphKx$7Z{sAK?PPORS_I+qC)|mf#dt4m4v#cA(Bc z0;+EcK9+J#)Ds9eg?R!Yr?cEl<7A3*M6=p)wGAkTYM>S6Ai#Z;D7gz9B8d$Y53tvE zq5D{dUFZRlPYU?HNiYLn#*A5d0B&$Urypf+6hz|hJ<{F&jjT(e@c#MrXd;e|fK&ha zb}9QSZ9l24*iftrsmYf#w{3HgL^)fAuIGc>`yX?|+z;Pv4*^?n!8@W@Zk1utrVC&c z%?Va#>1llKH690Z-><+foC}SPmFA7=HyoEOQR4txC(*LJt|6KX-$=b*>*&D`tYC>x z;pIRJ2D$@x20~B{rQF$G!l$$4Kr2SXfZJAmJ4JoD8^gW>bpj$z;a&g(14-%6&%a_( zQB&|GEEfVke+Zp|uV5eTLc}3h<42SN}w8GX&Q{ke3Gp6Aj-3e*MjTI$!kx8Lb^$d7w8 z1prfQ3px%da_F!!+g+CocLB8F$B%Utr{MG0xSuf3QBVr_8IsBCJP5AteruBn zG$8}POjGfg(rn?*eD%2kDpbW?%ZYJEx|%z z7>i9}Lp4XteJ+lW1S5DD8-Lj(&4-qQ46RKRn3q(JeTDsk@kfp+i9}ch{y6-O zw#5FJ4nmgY-yWtIWnb#X5br>h?DnJ@Ffzs@zLh%2ULHsJ#b| zlOm_!3s{CzNCf~=yeAWP0qMUXI)}}DOE7K!Favd^(q8M`-nqt@dQ;9@l*6K4eh>Q; zTu?;6ZSD~2gH;?&nu15)>A(b+V1hBo7R8Jtx)$*ehlS10A;}7&5%*96T;yRI(!!MM zjXH1vc^)Dv%Up#`S2H{ju9tUSjM6>%bpY#JZ*DyqF<5auOe)$LdLaNss`z8|`U(N- zzPYoZ+WND_UxE92s7BgbQWC`;j#vRcN9^%(NI2DBj0~-)<%8_a5737Z^*9_y-w#9< z6x??avrzx_@eB0|Y({UGrW;yazz_7--T{Ii72B=}WOO=4(No8d8Ej15WI2KRhPqwgv#$gXHI1%ny|9D%a{GM& zUTazA9((faDgXB3mOc_P@=0VPwSOT)_(FYVL z80K+|f|LF1DI#7#m+qA*_#((He?=o%FzzWO4+OhyTr^sM!UO4MHy(SjQI-z*e6aVJ zgMtY!6Gu_di@wcMz zQW^>U)VpFi!f8%rb-&cXL^J7wM!X)P9~AYB@Nj5&9Zv3TEVUmKkHJbs>A6_f$xGiC z=QkW%RM=CyBvKEkfpjNq^y76v*>qblih8+P7 zvjqhii~Q|IoIr2{0#M`@owRxHRR3xO)cF@u3J60tG#Rdvxzi&Bz)E7&OvWZw;b zZKV9}oJQ|t?DF@xaWl$@_;5nHNfApN{mi!<(IG4kxX(Izcj$3q{V#0&d!oAP^c;t@ zE?352wVxNjE$OfV`4k-C*??A!(_BFe-bDvg3xs)=7kj-$28$|AH=>))o7V2G{3F;s zU$#5FXlm9lf=7Lvrz9DhHG;c<%0L9i?!vIYlup6%^Bgwp`<3#r`Srl%>o~zjc{=OL zu@-8b$3WZ$+BYDDd)nSEQwsBTf@T24{iA@&ByV6Feek&U3vowzQ%C_H3`=sDy*^BJ zV6JtdaPz5^BAtAXg!&t|Ps2Z6VZMr!mR@O^NXL|<>GA@9YTx7|wG-Vy6^^(bBarV} z?}Qe>@?#@q1{N$xZ-%Ad7}@4@?mTFdFCY5reSgB+aFV}rEY|7s<_7^LSLA0(1@6*h z&=_07ZBrE`Q)~}NN6<`3Ld`PWn)Ftt(e!f!5U0=!V}%R^@nU~Q%Q^xPs3`L~5DZ+^ z*UPN}Ob^_wkeC0h;?1^~@B{mx`^c7|zeEgZ@qy=i_{(k1beBWMr`-PDLYh`PNT>D9_O$WcH z6=`a)lJe}_rx~fZN|UVW>OGG(^hl||7S1=}_N@^h1iZk`+Y-Ml=&t(+@0@A}w`LMg z`aN-ea9djch;JrbnUyl0_${N6?vNFWEISYUhkS%;7iJjB0a?s`3NiP)P-S*^t-BOq zYMsfabrrZxyi?~0v@9^6BJ3LG#2%i)sx`)o*M+`w9iN=m#~q zBF+MTx^U?fGIG@%*0acpfG-|8_+ZI4t!`7Y)Xhx5q0qYOnJxl>v9S|%l)y(#e2&Cr zsdoP1!grLqm@p3G`c3G4Z=PM~4Eb~dreyd`I(ExAH*bXN{a;g>_T}7obW=IO!?0wZ ztq7+FO!HSaX>A$d3lvVb7s(g-Rw0NuF(4FT2bCuvz&Q*~pw_(DW;hAr0tBI;Q^0TE z%ahLawFKD)-ATagBkEftS&QJ2871-gz92EIK0&Z+pJh-_5ExWMrkp<*I`-bDyjq^&fi3xS9-Dr}nd)hu(YNr2J(U zxq5ueUKIsROntiZ(8RVkn|KxO#Jmbm^A-g>i$er5n`E(*N({2sP<&ncBK0blyD&7z z#!;Z-gL4qUT~&`EPG)s<#I)e-4cJFi9SXx$r3V`U3bxf*;mwB#w;lteKHR4I#)~(Y z`lWlI=AH$Q;dIhJa|{|^B&IlLs|4dP2OymOxqT~tyxtcOEsYjR$+dpm|r|m2cypmLZ4dlVveIXM9rg=r&~E=zzGiDByx& z!B6gkjX!C@z}K%Dfj(f@ae+E$$gg09P7w~306GUfzqnZdHz4k}j0H-F_1)%glKY=C z+K16;oGuZ7?!p!0rFOG1lhChWCTVLAIwQ(VC$l1k{7&PddY6CZVu{j*_+}?+u$g?5 zl$H2bUp>fiE^MI9QJMJWcYR1lc9?kOGsT@Rgfw>i?{jZXW&wWy&;@53uGeG^Eh3H} zGIy#Qd@(!RKw|=@?*8~0(;leotHjGvPJH&X$?<54R5|Aqd4I2fvf*jI2N63U}fnMiC`+12vXaV#TF2Q#4LQvsKy9|r;<7>R*rlflJ z@-Ox)Kk)lvSsedb7U^P?=V$Mr{iOZVqR2WZYRSBhhL894yf3qZIp+6L*u+lU3{Yi_ z)gu;ner$XQsRYi3y27UWmbP=xf2R!@mbt^u2a}eVzOIJ*4(o3-WC>OVl708%UTrxt zK*6zF$3u>2T*Sis?Qp;^+Ub8`YM<`{Q!hXkeS!YFt-y$bmT%?+~JEuO%lR zzN0Ey)m5aktxi4a$%PJy6sRnqTpXr;jdkXDJ+p-6)bCfQE%Q9HT`ux{eeTp2{t7jd zykI})XnO3moPFO*K+z2-$H^0<<(n3WaPO%rRD!{1o@AvpIeEFY& zqB7bfGuL=NE6y&L`F^QP1j4k{5hi%Gv4uv zRq1$e!seC+SpzD^cySiqj*}(^)QJa|FS~Pejgc@xggnCXau@!z920; z0{-vSAZ7rNLvHz<%||WEKZxb)XEM*{)#^PW;2jP zylUv`u6H1C*_B5eUS5)@X);^Nd2cBQ?&`&R;CH%`;t)}mzrYpbEo4lu#?Zjd^}#gg z2jSbeHV-2xo#>Z716mzCVkX0UEo+$z2(9pN@r&)l&)*ry`WwYtk@7HM= zgy>yH$>Z_eo+a5RM}kqS$hyRwwu`3uvLlipvf(iI4!6QW;1^gDC~n&EyVYN*%haQ_ z`)pFInjiFTad(*!j_`3VK@CLtaU>aFA8XCHo_B^wap&kwzEL&-77w6saUJhOoe$45 z{ZK(l+fHX4*ZZIa%L!7Djuh8h$U}!(F?%^@Ow0bMb7bA8ul!hD2hXLBv!>0yV-32y z4Mf_H!uJfl-!%|z$X6|i>w^XhRutQL<*M*Uant_1sgOqxF}Yk zI<)uZlWl(DH`*t~CZ(z+;wR7(D9-5NreGd7wW&8ni}9xjVKe&ty~ozIw$)SNCQC>~ zh*?SMQ|ElXF3Hw7%8I0NCt&v@T7${7Cc2j88q3Rw{Ry3?lbcRvf2^8*d;Bb3uOCL7 zjT_SOR83-z77<%giDd;diR6CX-fi`s+b*Ll(zZTUk4f3SP>xZot+_~YUK^}Uy76M! zJn`$88EkMXt~MTTlEQA5cw$f8CGraB{M3bW{q+gD@2D7l=3e+#AWt+)fphQ9ZuVCy zZZa~1Rw23z=PO(#bi+zQ;l)+eXpY%N8>h!IEU%RKWhz-exo4B6s2jOpiND%o*EJsP zEWOW~a$wxHWzY)Xy^;_EhbACyBbTxuyY^`_6VtUkP_aOgw}y|Xx38Jx7JsFaH$@A1 zIAeJ1Kd5I&X1c{Qt9$S2Y)?_(Z1k2hO4(ep>lCzbI(VjwBX%C$ge>D_dH#9noMnpQ ziJR`?qrlCAK68wlpC2!BA+zS)amiR+JaSaK9k9Fa*MuILspUMSby$~do%A?3EbhH~ z31|G{VoOPHFXclw9!y-iHwKxHG|efZp9QD%VcLxH#$SV{36_1cWZ%0f^Xh1*pwF>t!LG?09cP6qrGw=7L=?R3Vh^8ZZn}OhV_e?OIeE{B+*h;~ zV0u!bFsM4@&u?J-Z2%>q8istL~1|f8>9=^;v zHnP3k>GsFQnW|=@AMfbXU{T33T^vVg0h3YzyU0|^%XPV;9-DUcO|jezVE*2zvbSW# z#!nqZa_NHml7^B{^P4RvBLwTmOYh&rai>|88j$_5mbBD4f>tj{DHpKo)s$?k;jcZ+ zw9H+#e3CI<>wTvteag`xHj}bPIQQEU7iXnA=8GBBei_(Tzjp!bfmoj|)#J5r4R(+6Ddpshf@-i^w_S9g=tB)hm zX`?PbDLBTKbu{ub^cd*j{aRT= zw{wXHH#^8q*$l)7?271r4|(_Itie4yd}B>C^1W?G1_=6XRr+-M`aa4@&ThjGguK4? zlEYaYV3L2*{E)*tVUdqwSPVC3m)MZ787JQZ^x*Bi++Exw82@4Mij&?^M-o4-f?d$|95xPvB^ z6=L=M*7whs5~g2!iABux8CC&F9o=!O@DsdT9kx>v%oiPHv4pk)|Ms>)B8?+UnN|ac z(R5n7@{jcR=XW!64jH0oRw1FU>mF5keDCZbfG5lvS-5#qSawy6k4`FTUt-i?k}XpB zBgG4=&@u8clGshE9AATPn-Atb2Ne0VQ^E-uDEoQtqaagl*j4h^N|5{J-G7{Ug(IO( z?~$@Z28UshLM6D6AGf*v2tQU3dw$ddCR_XT^AakWaW5jwSwB_RZ`PqsA?hubeN2Ccmj))XIUUa=oBeVX@yst1l zK8oetW>L{<6jSnHZ|@F?Rs0B%H<2bMN8Ws>9U`x+&P2_NRCwdcE1wAFF*eRR|7R^$ zUvo0JC!;Ks&e&+Pmr#~K_eGX?0rRU#j z(2t^+&|+LDyw*dr{1Ia6_T(8G^C|=v(-s9(IOfiqn#@yi8R)Rh0vc-!m28=yTZQ>~ z&fIzMCL|wTj*Y3`BOQg3GfkDD;2!GtU=ohN?sp`@L?goaJTv_P;NyyHH*$2R;p>?H zcNhMfs^3l1yD%cxybgc(ycE$P9D^GHPMEf1gxq_}LhK^;(Z%w2)fRSxhz}H_oYx?d zJDHzP5bhs5pJ3U^3;kI8I5roQIHwWqVb17PrsD>Sk#t&?)XoFx+OPfb+U!wfPl z65>Z>kG(5>j=rp&RJ}P+xc#$huaN8e?MOUzwFcs#OY$%By1Yl5CPa9h=A?V3)a`$q z%mv8=Wblt#NNzTqOp`B@w3cwE6Ik^h-9^)kn`(aJ2zN8+^ZqO`sR0cjaMKtmGR%=Y zGxg^qF*hD9Vmhir1z`A4S4A~FIez?Y;r-jP1>YeCojvwB>G?0;E~de+{5w`5PyrbS zek1$|-UY{2W=;f=6RrKT0PL!tDbVG2>G~}utsL?~o9mvNy?v4+=sp+u4$@57$Oi%k zc$=Atzid{r5gXp8YYS7n$tz*r&6Z@X!y|&y*ZYf@wt$`Bg@(Q5#svTCawWtN()zzJ z2Vp&+{lFiM`hZ4R@ z{sHy>r=h2}cP1rU)6kt?CF)6rU2)dF1Ki2W%l977(4ZWOyV#*Hq3aoQb#4(K7DCYw)Od#KS5+#5F>rHo^*E__uu7(VAZ#4SOga19*dEZ=sAzhL|5mPGe31KNphP7ctIMx@{T+x-4EavLBrO;SgN@^t5E^OPLE+1R#!8Z3zvW_vbPk3H9eZ{|o9+R&ny2)=dXS@p#jEs*71 zHS)84z|Vb$;}VH)rnPGRM1n|HqtPw9S-!m`QO_%`f+-(MmtLhBP_JZs2G#)qgW=jB zrc2LX&kZFq+I@ay@G&e969pFXrh6O;SFC7B;!2l7|L7NScgr_iIL{*FDf)&fVL%-cWqaDk}@~Cyz95hK1 zPPWOJ-bq%iI+zk(^31et%hr9;(Ibi*eV-7d9G4%ww=NaFT1Y{WDHp0ny4Y8m)cu>E zh7iopkT3SVvb)b>LD_Uxw0-YlL135_e4sPzR0=6upGr)L0pmc{bdS>cfgy(Q_G3`X zNI=2dQj???0oNj|My2UA=%d98UXoTQSn8y#ROJ5O#{1LEkF|T#!F|o;DL+XVs)|8&#ygfOfSM5vc^)-_A zB&(QMn=(@=G-}?%;bvEu++E%1&t>@%U7;NcE#ut&+_|jrDz3d)SHlD1* z|H?e-m#Y4$L2KN^uGacCmr}$1X#p|73A<~XM0@A(&ZlLy&pfY772M)MEsQ%Bu}`x< z#$=kH`O?93WNknG0D4W1zUru7Ggy?(dhxj9cxUNc?isFnBZwo1ONd!?+m1lz>L_Sz-W?dZ zAk98ruKkLU>Oyt}N2%KhTNL}t`Qn%l^jF(9P`Yl9Pn7A9dDGFi=8`eh!GR+UpY}*t z&N=LGz%oj6EE=GLW5qksxi`XAkh-&w8&B7Lk*^kJ#5^Y(%!9S||Rj zjI4>VcjnLx^8=T@61Q0j0vluVT1A z=fMMxZ^exK6*)@pc=i_chY6qCtmiOOmDWd@Kc%tyk(nF%Z2S^5Qr`G;W@0|4){ARs zQEIn<#OIa&-Qj=5(rq{JOkY13WhKbf8~HSFJDBAFI++*CO78X}{M$e|{|8oNR$aiz zq5MZ`#CL{B)C|YFO6e~&6FTyob^(yK4Bmb%RXwU7g@k^LVU^OVJjOcT8mZ5mxHm5G zl(_1|kQmOj{mQ;pJUsZ{9sVC!VtoOT@G)&4nmoX>6%(v#dM#PSLsu~j#=8k3&sD;- zl9d>ct1XK=0*QTPrUO^3@c$c`|KB+XtAFwZJ@9n}o>k_+;J%HW6+ptg2yADH59_`k z)v?#JA2JSV4}Z$GF{_w`{RtMz^OaFEDsYeL?b}XVHum~@y^~{Pu@Iu0$CZ(Gg4vDU%_eb zbpkPFaVU}TT`I9*F3zHlwHHIF;fCUfoOM6Z#UG+EFKp-s7Ib>+e7h}n^-pRer*>jr z{R&li-9U6Wby|m7j1c#h9YkGal2n^zj02ElT}Q9HOgOpAG;E z_=l=a>V*wB=Rg$urn_T?A}F7qYm_R1ir-fN{4@~-!5zsw3Sgv2<0Eh=q^kHS7$$Q~ zYTPtqdbkj?aqS#_QXlFO+UcNR($&*0@{Q&7Mdl=!&E6T^=PeBN;`h=*bW;m6~#y~O+(=x_@n)c(bMFXqZZnWCXUFunbqGOa#>v6AkA8^ z>`eT1w^lDRkhUSp*TbZ+5|&fj_EAu8qbeYn$tCV@K1HOglUyk@xFpcl%c30X`i*JB zRdP~QZ`uB9&C@AYI?^rOEaTgJLfs0y%lM@3K4Y4;cbaITZ`x=-r z_Vs^Ae)L?k#GhF0s9Q&FIlvqMGEU)sa9m#L$g`a3ZUweEHS-zy+123^+ttu)iNaLy zd;lF-B$;rFgSF14x)f)9M);cv8w`T&(IN;qQ#(Y$M$KF3p#Q>QdcLZ5r~!O!tC=$2 z5@V?~_EveQv5Fe|G-}gb%H_NgP+0-ks@XxRuI;Tp$qnWtXTxt^?oz-rwI|23p1p29pT%3Olc#qU7GmTvLZD$E`Lt+#`@RwF=!D25$J1-i z!=CObJo)*4du*xTT&$Y4_NTX-Tgi0$F;V1TV?S_I_wM6_P+pK6Uk8>t$JBlX`CGUZ z;>6Mh!Ij4L4_pd1;Xk}vbQwCO#3BY89nqjoihi**>_q*QwaqX)P^N)lfP)8Qq^LTq z!fmIl8hRb??{4a+;{wQ8CDIxux6)?ypWAX3^8n>^1?^u~_fqf9h)AI~iq1Wl+l|ph z&iaKXrtO}vqAoNzsafloBu|*j^Q(3|^?Pgg zTdHFulIdLjLX&3rcLG4ypF?{*KIiDi1yp;op3)NP?Fu}fWXO72p~HGK%?Afi=(}Aw`Jyn#C`9Uen>{@MNLSd^Zn98yC--_UKrel)`UD zLc34rV@>DEFVJ)0uaUp+qoq?Yi?4pLzZy`@s<_Lwq3WFe3d`zFf9avvx%zDsJ1yMixr53EgHh&N1y;#nAh70aPnIhiy8Cp~S$a&r!Z|0Y ze|RGAmdyPc{0YPa@4b5Z4@d82Su-@+I-nIet&F6tAB+? zH2Z!^q4bA9@T3%IAhWErdzzwe*WNJObk2*UkO&t9!`KrD#zZ9H?Pi^mv6#km6=!R6 z6}C@VF~D}dYjpk*bYMG^40DTVAgwA|q;TVl2n&k+RwjoiP*FCl*bQx_F&8|l)$%6Q z|H_4N_)|5Uxh+lgtnmtU2=XLGJAnqS3?~Yl?9sbQiRbE?c8z zAZYp%A++ew`rL&A1g%c+1ApX4FxD-ep&UYM8u8bZr*Ue^G9-s-eAiFDIqh9I`Xl#r00899zs<+ix$asW`r+lVVU!SY!)fj${6#5*v+;816 zn?7`0*vazqATAn8{S-c9UL8QSNIh(Gr26~g$_CYe%A{8SB5!8o>)o=)mn~2WH0Q8K zZ5hyCK!nwTtfdqmdIXQw^mEe{iugqh#-{zO8uI~!D44FddnjbqCP$6Q{6k?X9ZbQ@ zu^1)#eqZqo*cW%O*hgleF9-!r8vAUf7DLn+fbMV2>I3qZ1@xa;JylrPDM7#Znse%I zE^z5r1k{%xcYzzW1o9^;FdX{NNo+|4SlEWAmBw0127(%E^QxQcVi}uor*M?dyvAQQ zrZijYU5n?B)(>11R#PMt4;)hgYV1q2m;GXtWIdxI}p6)Gokp+!4bw-OE$iGGapBgY z4qd$bb!vmCM`gY!8o>r&s?0ygb2f%%&)@6Fuj>hiujhT}II+>EqPhb)I5>z|#?N&a zruZ;I5n(L@&DnU)Cg>Zj8qW|~I4eT6GP7(>Tyo(eIxFFMR<9+D@gkQrLwAi~A0TH< zZa$t49)8;|Vieyd;QCddhr6$DndZ@D1Ng5XFkTV7zq%X=rS`c&&3(z#P;HSI1qDmp z^{9_YUHbS{7t@)YyO`jvb^+Jui1~g;0Z+F z(F%4E8GL}3>yub@5X%V3{Hi#r&YGkA5(v`JWz^PTg!j#!F-TU&c=!BvVSo98CT?Aq zRHtRL4?Ix<8H3X++ZeUCFHAKG-)9>jNw#m%)cLEj!=d#2Hb#5dajWlMYdy)JdN3XO zC5INCu8ywY1EVgF{Ibqt86PEH#O+RK4v2K$bmh2{cPSj}X6P{)E3|3+`eDNNJ56PD zZTYBx_qc$sz$3|9R*T77vPxv8KF8vyzfu>GUtrwk@BEmcNNw}}t9O(0ouXr>yu@;O zc90nkS9hxfE@)_8w&T+&R?Bl}6~9Cewh#QEDri7+jZrhl$g34{SRblN3!lF4v;rQ5 zAXZh9qyNj=W)HTwE8+#5y}b=xHTZy`vb>%AZ&KiSBf~g-yX4GBs4r#ijoY8vp?pm1 z1bHB(o(E<R2+Pr3JqQCOS_5tjtyZw zVTMi^XgGUB42xOyf41eDzPbZX!$FA zr_p!&^z5G7-2FGX`V7CsYd-p1i95~<_LcbZW1F5}B#tVca<;MQoK z_Ltx8Q-f5AMJZqcKWzDkamm%RoEfIZa$h8~z-*l2mcVii3{c8xkg+ z2U{Ow()cW0ex!;5x3XB@09apCLWCixmvFS({DwrZe{TYqZNx3TYfNmIkgF9l;kVLe z!-ogiyz%i#CL&)5B#*&r1|YKeH&I-S5nEyQCGS_bX-U-K61tq2O?oGe;+ zjYGLDCp0xvZp7ORt)s|&{coCYI6Fu7WjnQ&M7}<)^0l$Lm20OF-rWQ|=(SIpLRhI1 zSMta=wW1TxvAy6fYt^P^w(0nA;PWSJ_km! zejVQP#O^l`bkN}8W6%6)b5J#mLL?Rvd=YoGJ~VDCMnqT0GXUjYRa5kvvWDkvaHkStK5B1uF< z1j!OavXXNVRFIrAl;oUqEKxEdl95#83`HtJg}r;D=REIu?|6H3_Z|JA@9k&Qx2jcZ zuQ1nK=|6w_;W72IrVfP975kZBgXhq=gFa>%oF9EJB!=wV3FC~Jh`0Dk({x)tgBhGX z=g34rZb&gDj^rek@|NEAAN&P=rCk#}K$DW9;K|oNXU}=S#gsWu4hS;rEx}YmO9mtu{n){(I-_p?@=~lR{cDZ4gp4Ph&vmET zfgF98^bAbiP2M1Z?|(wcgq~i3U%&ij%n+|f+DEApl&7LarxpKgbpw7jw+=tWC=@y(9`+8_j3{0Ah9cA;;3e$zY*+jceoTgtsS2+Xpi^j z5eFmy#2^M`_wWu-6+iMmtA=jr%6>3Zq;_Q7E#MfMK{Z)zQDyGDZm!FJW;%KLxP#g} zg5&#Xg`p6WQH4w6Df{6H7ShTpxE;+nn|C6?7g%mMg)M|gGWzvxr7B7&t29yHx};rY z!|a&wxsf%?GwyLgPSF9$?R!>8H%6Ikut2l1?~7Q*e0(H<>Or*|87t!;KWRooS!xz_ zhry=#_Vo?}OrSHv5owb$H?%1*SSKCl-q@ZN!am-VJjF#TJ+I1Q{`T^`>hDCa9hlXH zpyi2ze5cKfp4^XV9SFOl$4Py`Ep@){0YOoLu->U&ckTG{9!#0NjZ=FuM(V1&kr-DS zTRyefT8XxS#%`DnPbJu**bt5$?DQCl z)fO~W&G)#m#k7==Eva>mM!+%KFGC#EEOBx6v3>qbpXy{!JVIHhxzgp{vvQ|u{q$Ga zV3=cOi&`*jm}lB_hAAd`^knkQaU@x%b=&<@E1$R2|EN@?OZU&eSpW=2k8UhtR(6)j zA_el#h_R0zfLZSsbloBcc0t8m816wk(-LAi43dRMmnEygqN^p?(#^mUO~z0outa~y zh6I(H*~r=ij`A<9sAbb(e7)$TaRwM+<~BgHi6-TSZ#-5Jx+G=_TqSi5N^ar|0p8ot zjM6KQ;Ez)KjEbtM_^#>MqewE_aE z3)qR@1#kIRG5ila?@n4QlfEY`hQUt!#0DsIP8?9yHNpFliPoR_9+p+qcn%8lc?Ww- z`0rF>_RI#{CFzH?XHuxXd|kF*Fgp4nMl}(9sl;`rF-Ynq;L3k^1ru-oNImot4kbJ} zB;fXH<1KouPU4(XC`eh8>Bsu5YWLQPEZD%N|K&(b=IGKTeK4<~V0jFb2Y04lEsv;` zyIcROfv_mTmm}l<#U}l>JOpmskQhjxHXib?hI|-H6xc;l2#~&L2n#@XFdL|R(qD!G zSnnn!mSU^Kl;zhr@7Z32v=nQ14h}a$BrR1Z;^w$CpSKiOvyJ#Ye$jIfr;4K=&B_S0 zgEa3-ph3O4N|cQ$bR9mZQWwI0x0~h*G!xXs!{eq*RHCN-tWErPocWXj_(|Gmz8o)S zrNV{lhLk<9AMuWv2Yz;1u{CZ4HUwxcGF^0;2PVXAA1|G$zNR@c5$>^b-{z5$PldY~ zOWC-Wzm?*2v-Zio-#k9Y*c#L6Q!Z?eZyMS`@r#!rRUh_D3#j{x`ya>k_SS(7OSxJ6 z4YYsXK=B*DHy3)!OB9Uk8^+Izv16D zMh|IfBsr&|;uZ>7eiey>Cu-V^dGp`Tgl2rr9p^np{*uW6q=g~g82U^w-wlR0k7<9p zHVKCRXdyt?feKBymx2{IbC%4)W1}&Vy?+E`t_YXpPhn7z&e%za&hC+URn%=@Y{m$R%8A)2lX;kFAOC8&`-rFC zbn4EDZ0RjEOA+O_R_)vh~4pl0bgNwkNs-TbQ@35AL{!+$!M*JOb&7*fX zr^?o3+S%4MgOQV9#6L<=!I03l&Cp>0$*JBAO>Iutj@`)beL2Gv2q|8)e?bRqo{FKY zo0NqZk|HOzGXb)lOO)otP`wJ#g-%!7+1O+y_hZRA46r6uxRd+nlkH;9$>!2HA?D6U z`;!p=W11q^CS>y!1kJmT=4g-OywonfpA-fs5C;04DRO(!!><_fD6c8PvZ{GXM#*A? z%i}ss=9jX^Xkb_KBke|?Egv8I`%a^quZwZWQ(UlE41B6JG@|jqm*(=!XB%$@2O+95 zEeZ-NP0F)MPrd!>iC+Kgl4>>L<1N(_;oy=by0AtXFUz?{9aL5N#c4SF^XW6LPj(jDa_;*JCN4HUlGZm|pF!0=Kn*CChD&&_MuoP|u70Sy(Y?!6Mf(&st}hCB-JqRjmU6 zGx#28S+Ihg&CAkY_n$VuJks46qKI2pi0J#Vbs@ud|7jyC_WXtOxw9jx7k-iQ^Htnj zocZEiEM~3kZ$%Op`!dSzt>L|2KsMQ=+(f9h_G^{y79XN1E0!i_rrOHyiP3%}B;5yM z(lh+yPD2Aimd`F+IKT3Gy%E?-x0dJoE4KkKiS;eL^<4||1QBjBGE#>M#{;-?e|1Le zU-_?sDpa*W)htziZ8*e*5!2_>Tf~zqI52zRG0xKnNj97&=CH z5?Oy-U65a>hJE|LD;er!>3&NP9V?=;=Rt zRCD}8_kW~)DqMa4A3dsPPJinkY5T|i{ZMG6|J}T21iB)U)x4@Qrqghh(B=U@_iTMz z^25=5u3Xw9Pvswf$R>fg-P_-aOQb>r_d6aeP!@*C2x}156+YwnjTN5JkvS+~N*^^% zwInL>-ecs=EOyjM{buo4;p`hsZsKNA4yJw(EE>d2lbo$|$ou+nI6nLZwZ)(xbmyvy zCGIddf2JKCc3#@;9{|JcPb?Jf6P6s>5b-B3u5o_0zpKo}t z+wPp98()jbyfA~bq5l+)^wX5g661ka4?E55-^+b|6 zKrap$alOU6n%v7=c{W4(qNlUPqKEC%Qy$u!q(z{O;xpM)mYc*$NXwBn0&QVKd zxkJRiK z4}!iVg=Qc_p9KBjp%rMTH`=aGeKjmre#_1SwMPYuj;q{)c27WNk=H|sk9wBdf%2{~ zVxf+wD?c}FS8)uFH;aBfz>Eh!nEU`JfI+GbBsZH#1VrjXz3D1xBLv(2g3_G;BO#S# zF{~YXFP1_V9zq+(mohS{>L^lmk}{T>&7OdHc-;4mZL$WB-apvPNd)x_jf&MegH78DZ63bKQZ;%xA37co?}A5Z?+ssCk4G`gpdFKg3ZCqlaCoxli^C4&E;)>=?;~<; zp(7XBg5n`_=|0{;7REN+t`ezK9rQlT%>*o9oq?zzt_<_42k*Y${cNrlN z-JIZgz9m@zDRz589@;H;0*cSLQTCg^*YtoJn z;99aUvo*Ayl|S87ma8+ZFPqnXKL7ArQbe={>#2R%*P*1yXV0!;qc@N1paTwOGw4>U zg-O1e!<*Xo7gvnM)ha!Yhgt7VQ3w7IwkL0K*bY3+@mnQhLf+#&bHw9AOq8B`YvTL0 z)9PsjQsLWo-*^*|%b6ugyf>6|kt3$r^d-IQ{nQ~l;Q@KJpC-rEe*QQ2{x3>^=e*_| zsXJYU?-?mg2x#N$Rw#b7)3FGzH_xXX?|W>g5#kC2HT*8QQZ7l@yFmPu=fNczxko{0038?}rVaiO&2x!T)*fU>E^)qV@cb zl)H&j*3;mF_Cx5xPlN+A%>hb5(UcfqUb?O$08Por=7B5ttk|Q{upNJ2&GmKu8+zfZ zVR`w`IJues%jl$HK4kyy;Q#YF`0vq3G*;q7-gHAEgB8;He7_nGZLFafU)oCT8w@cc zn{2nINX-J%jo$H6jCarxJp^lHa~IBQ$%v$MyV<2>z>e~dUI!BWCL-n+Se z>zSjtu)*`AraO4%Or1tj7?bxX8^1fTB>twt{DQCnsQoFUB6vJ86bem=n=iSL(6KEM z8yt11gYEVEtaa@|hNbKibk!^T%L~aWAz`c{Oq`r2I)WmWNjgh;goR`~O27l}xxJm% zM&s_Sao3-inS1fa{dg2cY{I~ zc06#;ft7cya6P#>PmS0K~!q)E%j`@g+!3zT9J zzFBxs%tdp;!TM`eWh|IR`jJL0nlR&sj0E9)esaLst%`2YrXDC~R+H(Quw^&kHGm)} z8#)@Fpa7(>9dr;q$lA@MB~pMZpA6n#M|y#M#2>FAc)Vnop8A#PR2>%6$_vc&%h=HffOO;` z&)dp*rKorL`Q6`A9f}3{EGPd$P2tO*{8#9q3vk@9NLGx_Kk-7x2lqy>WT?>ApOQh|Njsh<#aUBWTV7W^Q;yk zBZ>I@=0;h;4`RE%xw?2`_NxJo%+^mi)bN2lM(6#*yR2;BJ{7CT(iD^JAOl;;3k?^j zg*ZGOB{lvtgAI5^&13y{`Vclt`s{By*8l|A`rq-53=?SCe5BV!k8mJlAV!+|?r6cA za0RIXFW@i!eioF*Y~2dptbMaYw-Ew*VY2ohKvvhYJL3y6Uo|w23(qD)G%)W)45G<& zH*haMe|J^!SfUe0#i80T4dHE&W7j^K)qz=%WXxk2SSj=B{B($pM0G-RF};6L!%90a z?_L!BXCpZHUnffaPjaXblOXJ;docXw;gzg8ReMlC$7`41%x8>RKD*cFj3QK(r|0qU zA45Q^hH{^R{9Q^DU#N=ZLnns(7U~5{;@`+C1RgtzJ?Um+93fN`GH)~6gvPm<{Cs@* zi~q{fWpIEq3Rn@ee?*w%w8K{R!Ga-SZ3ZRq_Jh~(MPz%8X3wW7-=Pb}?L5CCFCA#x zC}Y1BRlVN@EJlLlm)j93Q%sKBK0UHiLs`W19x?}Mjy?Ymp4BTz*2sF-2&{;>=ywC+ zL0Nrw`5Zq~^j2UZOFI+_dk&i~k@4s}R-NB8^K{|vGcpg09Vy3AU_mLyPOn(ARLZDH#DTp4LagL zYTr(c=Wun&>)6$J{vB)%nK&e^l>idpG2{$Zw;A|@Ck6^G{)PYAO%Fw)y)<{**npXY z1$eWpEky~Z1-R)vJ?)7}!FcS*Vc?r`T^Tt(>2cBxm>Mr%zQ(e zeF!;t;mSW-^DW-f3u>R49r<1A0{yUk@Bq8~b59e2!LDyQ1AbF?(H^vHl|MJ9TLChZ z_uQ>J;E*G@dt|hXOcVfSaiFeUJCgl@84@=>y2v_@if|8JDxCHoaMp2?`$D>wRUa+F z4VbsWAx-v>!!6|Q(Q^b`99bLQ$3J~YX&jcbhMj*{TUKN1(>|h`0f~uU z>*NG%aTg+|2_lUjFm0P~ufb){THUyqx0dt62v+zZT2@}YsanS2f2esR*jYWiDmc_x&g=egWo`E}LBpAhcR9gmB5uw6;*FHSTnf=t| z>^kvw@RV={d0!cLCw;hNs`=jWNSD*;IW{EH^|OTkD1u;c6aE9#1r@lCD)(U5-%{!sG1w*)W_g$tUpC5*sQ z58#cU=eiD(olU%0ThV=-euc$$lgBG`kIJiTJ{E5z?`5|N_8Eda;K~mFGFu(vJ8A7h z*J=Vv5_5+cZiN^{wu5Lmh})H4-n|#VV*R<1ddJygyT0`z?I@dSB-{hUfrnf4UbD97 zCky()Y>j}xICkE23q%n#BkuqTTY@qlaB!{jh0Cx3v?KWnrJ!lB=1bSAF8Jb<#q$Wv z)8ojUl1t%E6W=oRl2>eoG=%#dMVQ->VRz${^l56q!W2({By*B z63i6O08K4a8nDohQmzg8jjr-wV)>2ik=(f~PwqLvA19=-pq)o44UnF`)Vvql{8 zF(mSfB~p1~#_iwer~iG}tmeHGbg*2U@y164zg2d|Xtc;^EW}i6EQin{c?or$TVacP z=1sY{sR-TsPTGA{k3NUmvQ=RcclU-)(z)SKNA0$qhy5YPWxlQVpBYZ9_r)qD!5sSG zk8#*KH|wL=`*8+egDV(!&87fbuX(0}h$Yp+&D4N4&Hd2^)bR+q*u%l2duog6MVQxm z8GzabYrN!HM?6BYu;RyFmqzbFPvuIx%oW|DfoQ6$@Ylp#8>s>gs}855LV^zyb)MQ= zGt}cx>qQmaj2mmgTz{2%LO!dY-(iY`7PnZ^7t*OufMtWMSCq!20OysM_eQ; zp@-)GfuX;Prz|`!in?PgJsYHvvR%PwM_Br4+F#uDBI? z(UUl5XImrzjeeryJs8VI+*nBbazR2?+6(@%lO8}N-I zPuBq2;~FnE@X6@z=Smq~!t}PT8;56nvNyJ0kM0k4Q2yd8Z#%u}MCPB+X5e5o#qSWj zY%q_IDR<`rdwNe}`l6=bQgLw$Z|bn5BY?_o(y* zMO=HXRbep#GU{I5#a;h9E2nFFc*WXtWgP*n^xchi9%rV9$hSqk`rT}h@f7#irX*`O z??GhUThA{vfjb2|k<6p3b)(Vc>+2Fd9Dg+ze)8w3?-rd^rYn^JOTp`#Y|Wqu3OpWh zaaAnRS@&-oZZ@Jhb5@g30RnFXM^RYwkqNNfHn3zrs8bLQCW3_G1vl}LX3$pQ$4c4T zM|B&Uh>d1U5u6cmy7P0c_+>5~q@vr%EJl~&pu4&m&iBfzGn(&lQ}+BgScC$KrVPB$ zxMw+AtgAQdKa@BY0X$wl3i2IN2siDnwkrJX9~|#!H7EizqViNo--n!C ziH(NXKi@LB2|Hx4u_jC`$CWuvw9Vqi#@kG+mKGL%ly)G1p~Ru~L;(N=-?Mcpfr#r{ zQw?VHLGx_i#5zD#8En@UKmctI(S#yo)kIK<_GOnx^I#Zq4_=9Zg4FU`mepGkR5C~R z0CICAZcP&vYq5)SPmzfwtjAVV7=I2jgz&&AaPBVCm(b33tE72*-T?Il>%VJY>z(Jk zQDE`deFLjLT3|^qIoJexj&SX^3U&;mFeI}1coZDyMZ##TU5o)BHdFso zjrEozvg8=WYBM+~D7FdcQN;V`Ak*ULEt0sk+PgQwJxg|a_&#it)NOT%u=& z@{Nw25C&}@ShV_Ed#ZQ~c!P*I0NjKFn^Q2XE!e*``;9CT#2tZ6AOTwG?y?a&>@-&3 zlqO3b=rcjjy(G}&uou1y8#}^H8{pfvFrx+t|J1HNWe``nj$pil55gXSB|s81&3V^e)NdkZ-*fx|*Hr3z;!F5&Z`4{zH#VaXa!JsQr0bs>o z0|4MVhgq}hQ#kk$um!_6z@0rVc<^TdguRLvI=f*w-~jW{KE$~#_ud5c0VxU`g%d`d z;k%sha$JnTam*AN1ke)$twHOL?=b6(zpYLV>P61?j`!JaO)e7%{Qw)jg>3_9fgO<@ z5Wtl%;LTwTe73+K7fl6|;sN0!oABkk;IsOi{pB*i^>E6$-y}oq7=UA140Q0W^1E^{ zliSeSf1Ji^pB9Wignb<1qHeW~J@@doBvkT)Vv?VM+U8`Z%bZaagAXs4UE^{h;&E!> zS5PaZZ=IGy7?HVa4w=cHDZ5I3P#oaP6}VDCp&&ml4IZipb#0{D3&ior5hy2nH%x@0 zOe)-k5=;it7k|Kyfy2iz*1>5iM_vQ4ODxJ34pa}m(e2%&qAJ8~`N@4qo04j(dwpf* z(Uxp-OGQEgsmIKN$9cD5eFhIr7M_yU{^&T=?3tmg=?ul|kM3dOb{PqM0*09Ti)$@k zvS%8n&DZwXr%);2{7Z^tO^?+W}_^ zo5R?<_hB;d5gPasE=P;Q#McYHPq_3VW(d|4axsZjA}-NZD@L`2_WcI}9xOy7MHMyH zVML;d8nxt)$5}$~s<`E5Od1Fdf|Ug^!3E=>)SYU<&)*N_+e{|FwSp3-nrXKJ9pey@ z+mBq9RE^=Q6NlWRP43RmGrl(oZ{Khs*Msfxt0YMF@>Q8oYT9>cH|IYy(COG+S0x}v zL*hy9vBN`ApA&B^ouYe<14Un@>zqXe1nT>I;D*6~`uzdrDbK^HWkxZZ4OY*6wHoLP z{~f9%JQxQsxKm>X4b1V^*29ea=kDr5N2oA(QAG&7DOh1gTfOVwDAfuJx(%2UrSv1W zmeyLrS;XuN05p0O6&!Pjgs{A~gf8hE?ZcYb>T~ zdn=Eu5kwR!VR{^J3KOw%udriGEmc+#30y? zS<1#VpS(o)6NVAIYF-45Lz4!VV@0rf6Yk92@xU-?JX*-b0J98(Vd&L@?g1LoW!{** zKDDZWgHiXb#V(ff@DS{Jc8BR(3warcfGOZ=xadwd?%R~Xn0iaP1UoGoagg`n(G6+( zJj*XlP7l&^RNA%_O1B%>yC`JGwDei^9Qdx6kqbbSB$^ju~?G+%w8 zd&`Au!8Zm`;2MphjKY;50d1Gy)w*(>;>z7yHcgHrj_X7Eqg4{y_eNdj+kchs@Q++0 z4ypnbiL$twr84BhoaC9`y%!K$GeN%Md4?=&7q&t6aAQD^-ki&RocjKW<|Jq#OQdhxm#z3N#9immhWXHjNhaIoEg7brge38IzET;crI#x8o7{?x zJ3{TO^s-rsYGGU`hxgz2M)PBX>HY8$6=n?ux4ZVcc}nU94Lnzu?tjv9Tg{pzrDUpi zl4qU0AXTcuwT7<(ee=Pdr_&zWyE;{GxaX6sa39JqGECeiPB;KJYtC+Egnd+WV%#%r zX%@QkQmXs9(kRLuzhiL))k#<8akIpGNq=#1{yI$%7oR~-UFkF&X&Lq`7{8Ijc?ZaR z6)>;5cU5S!FWSzpsF?cY`v?I%UtIX3=ih03KHNemrLn-(1*5P9AL+UmVi4)RcQkxm zh9X$3taL~GtsXZKd)QhTAo>g_Q@W{`IrQENw!HrSRgQ!1qKVe??@il_@+DuQ5$kX! z>#?7Xu)RXvnmcD`e@=GTEqg=d(JIAgF5121ii`f5({yzoIR?JxVGJZ05qcPK9MXAu z@<~o}K)At|wN*NOf;2cuJ6HSGdgbS}w8KQNGv}Kki>ulbi=C#%Z8AbcBj3%I_wZ8O z{K!uyK}>-mj5^&yyymC*!RphJAYyn(L*(> z)?+d2%1vVe9^{U~!{^T4*G%tRzF|Od!FrX?uOi!WJ zpu9=iEc~;`fbF9tWp%x8ML-)0qx3u<&DV8Qt-KJ|*$g9IyZf*L!Q z@RL5smzMJrogjQy|7` zIOezYA2-~Y>sTaazJaQKW$ITc5S<=Z$``6l;Z0|pKs#eTT z!BacKzjwZ0iDK?hj7P#*^ZCOduG$Pq2Zs{l)N0S13tQ>Il*T*Nu!$}JU?C3+Ld^ zg?>Ra17$+loz(g0Fm_j#3;SY$~r`t=0ose2bJz3`W3*`;w);e2(| z!j!EzbIL4sVPRCdLdTF>E&S;CxTqAo`W?JwiN39jOo2M zkg5s2Bh`X>-N?>u&P7E^7@is8P4o8;1`Nmc%dvI6q7y^C@iM*E0dk-F4$y3S^4u4< z@q7jbW%)gtq1}UlYaZYGZB}Nkt$3}x)NSnquNtz25W=oX^2YQjyX}X|-P=b{qW2+}3zV`5;t6%jV*rUTgv%`h#OR!Lt)fKY*93zU1l zKCCaGcucbUa^&(emP$M;Ngz2_l`Q!R+ST+YUNmFL@Vktt{SvQciI?8!=}S8@9IPpV zvts)ikBRxp-s5Jb4p}CqZ=b2NQ@_1vz}wozrDzIz)mT4=7m zG3S1sSY6+45MP~~Y1pJHvltz&-&-Y}8`6-!tdVx=lm8Nx5ns~zqDgYKZsp{q8its- z_Dsvs<`nmNj96I!=Dzcg+U5<;!J09vJ7Nqdo3D6a0*HfyjISbgvZVQ2W@>5c!kNjoi4Am<22_Mc$bJ^K;i&0=d~`*I;zsA z5l5}(oCo4r8{TDvOzIs@2N}DAw0rX7Yc>HA7OjghE-mCYT-xy z6Sdd<`PkZ8#J@dNNRKm^ZMmM=IT<%Ypqe|hHRs(Xc#a1{Z{skKc&Y7q*6W(zls~1DPmxRcF8-}*mqGIyW&-hv^g+Hdb zbo=B7XL+F`U;!6nn^0Txy!%>rR(W9Aa?5)E4Er~)FSMTE9;xDz>CfF9ZO%^R9fx0* zktN6M)~AL2|27*%3*X02RGCYD7vlm%*hgROVxRr5IFf0O{r$e0!XPUWem z(^Fb9SHGbVUSRfpvR7nT&7IUej6|{%(f1b4x|qhJusB`l$!I$(O);05&qq*9_@XEL zg@LuBGbvqtmHFUnpRTasP;Y@e^8}?)kU%B#mW<6IT!+>gCmMWR+0d%U2hxd7IWZmb zNUastcjs>zSs6__9!{0cl*N|x5QmrW3cvWpeZVc6vKzr&0JoXj5dTvnMQp-BtE{N{2lWPr39U+PtRgX3{wZMPYbk;^)8x zBo@2Am3tr$z11j0Y--`)YoikPv0C8m$EGF0c=lEj9=cM|Uz5_utx;(&KKaMOVnv93 zhUgRqo=tamY69K89iRNO<;yPqWd5r+_a;66A3liF5ihJOM6I;+NWWQI*kg;=Q&#dAv*CQ`Yt2n<6gLo9p_F!asWxC72`% za`&VEW&xaY>G<(h?-xP^AeZ-^{L3ppklR)H58L~X=JfwUQV@*vnK|-jVpVyPrV{tN zXHMaNVN~g&WP5B8Q6qB3s^%qs#+8yS_3w^+?zQ}c#S=Hr=n<57K&Ej8UY^YCH!zqx zn`{_#`RrfyTol;C_9@F?%+>bq6MB;1%{Utucg2|dloc5CP#t?@5uqceLZt{$Y#LmM zu2!N)7!9&B6J?418H0JbpPpO`kI>lJp8BcHapnp?>;CCRp@qduIlRI*`I%^_dfCj`XY7M<7)|oLrPwx?{OdRrehscs z278huq%rnw|LD9OhFetn>&2&bzs+r&RV$DY+%iRqQP4-j9 z;fzFChXH1YO|%!n$M)=It$3Ed7HKak&zMZ?a?qruVeu-96<*ghD<<&eF>kF~>Wk-) zJ8b>iuukenHm`Vzvwq5HVk(3QENB4gnI^q(I}X*5{aU8RCj@h}Mu+n)nwBqVrnZ`2 z2>I0W@sH1WbK!4K5;b%>AvslCA950qk^C$7JH2Qow`gbE8Q=AIhFSF5?+%J~D#|h79AHsXC7$m$*BHU%iO?6J<=1oh;F zvHNQGZoT~NS12j~eP8ZyZwh@G)yRk_dF4W+Ik~^SL;lrQ*Sa{-T0P`05jV32Ho=0i zD=9jRPwen}Eh18InB7;+tZ{q^tVqOl<_ldZITba{Ji+^LDX{@ z8=p}JMh+iER!3p`fQpNX*6452)G@J$J{=DfW{iI;D~_~>)L%0O4@ zLHN0R26B+wbM!HIdVLSIP_}HJ3iFC=*`qn=Re)oz?TR{Xw;K0~8$3GXnclr?Yejk4 zOL-kf$g{Q(528=ktrs^KhQk{K;A%R=EM9Mxa|mH~0hhz;<2g1>ZZ_MWWd$uQGEc=s zo8@xoee#g9YgMS}Yj(fe4Bwona&|Y8k1xsGeR#hZv<>~_mo>wZ$Hir-!sS}hNo|%f zSI?IT^rhU3x~byi&*oIyu(8`SV9C~f$EcNjG)I-K<4n4BKPN-w!r7mJAH`{&JCr=U z_T$l`fZbC*=3w6=yOy2l1T*2=HO4}*N^;!9hyLI8zE5mRW%!O)n^S~EX=dG`UF_

e;o~IyS2- zXA)%Xe?rt->U$1T&f&aEznPP2|;e zfsl&uMR0pQtk`i~dTOC7O0C9XtJBH90g?@pbi`S0tsMfQ2#zGqBKZE8*| zkW2;JEiHI?DYg6x-2jfB$?e)GG98Gs1#NO1zp3SJzj)e|cy~Vd&SVQ2+s2ERuBL~W zv9e;$$yIwZAq1=`a8rE&6L0+i`p<=AQbo;lt2SDl?pltJO z>kg+%+f!M!gYR1kd02x6;07W>lsJEcVg5#<1^o-c-X>al?>+IG!NlFmhh#U-y%W9V zRSho(%qC#-O#zM<2roFx=QE zf3Lovy;+f8$?tAsK9-Oas&eNsou}F^S6KYFQyjOil?KO09tNI=vY(rxB`u1(-Oil_ z-^T5Jqk`4G`u4G|gVp_eZ>orV;#%lkwD;)O7jlgrG0UoeFP;F~JMR+Vu`B5OT~KdQ zVmUeF_5BC_bHTu_a?RbF``lqcj4L11z9MD_4QK$z66R^FhVooyxx%h_sMi^HTd&HT zR()4L0>F73JE3j<`?~ZBT@zHASzP(n_Cpc0<#DxPAY_@9(kk4sFmhyzCWbRQF z_SDXPgAv`t%~WY}F`kxr55VbeQn0z>-_?xgzarvEy3KYyD*WkRIcr5YoCLnxEZC*C3QQOHoBroMre z-rfGz#M;=lq*Kc|J1Y_S=$`8-wN(_`!Z8UZt}sXoP?wV24<1}RR1Lk5m9zes1(3lY zBux_=7Dtk1tk=vBp@XDj|F*RcD6nEi&G!N+@C36wnFY7M^6Hy$L5gQnRfj)7cYQC? zC%B~%Wc#{zYgtN!C(6}`Om!=qI^jr1Ic^}PvtysSV6*QS{%iY4Yz@AzyTlZH@zx6? zJi~Ljq2|N}PUO?UN@TUJTEoXB{;wV9eeV4kIbPapAoa}j_JA?Lo*{9HNO9?)?QL)F#_CMZrFnc=G zVZ!V#KOLc+=81sbbNtMTm^cdAf7mywVp;!Yy)Q}=;euBj^++n3gk)E@8O6Ggn+H02 zeFeqs#wANOAH<%x8HJ=h#Hp)VRBPN3)1$MsT_8PwWu~jjBC&3v>3WpMK~1wAR>k>p z!6`DG780K0886~?kA0f%USiHKbWI$hX%=i6YBW5SavyQ}T8-VXQ1~NHnP;LmCa_VO z-x+%Rq>CQ>7{br&sa1m)Sanwh6wQ7q5D(M(2~> z_~q>2y&J1a&%b<%ir1`PcviEdZTY#k?B;39^MS73&BwQRMkD*WL_t2zwfE-pICFl9Hyz|uKFaHdm6A%9UyE`iqeoNcPw5SvM z=l63jtnxF>j8wNuh0RhOvugzNdD|ndUR9pv5o-OFdzy-RAr&6M%;#6mzw9+xvi;>8 z!8yS+PW8hLcVn<15Q1!LWi8CUDzh!;HRKDAruZzQ{8E@{KzwE1_tSHy*nn0U)5KeG z+t};EpPq8KC`S8zCdTVETF`|U`w~6V_I+IL{aB)!LaOwFTNfX69r&${q#(`U^lk=l znc^_a1J(EQ>Wy*m4OjSNMEP7GPp2>9r@GPl#ds0R*t=Ut^QCu8$P;EdTc>RhO{>Gg zOqp3K_PFPMT-Ol79bXlMsiy_kMp}qpYz*+y(!`x!T;;eCCuO%lUgONQe&#k~0hvgW zX2lz;!OKs~&khKO+{ohkb+tPW`Rq+0-YR*3#$@oUvXa7+z`j>ohSlK=iFlgMl|I6EJFbkiq`+Iw_@1qLyg?~U8dT(*<}YV5>@``l47^-M~%C0nlwer3}qRU;3n-cw}n!-OsO)XHUf+Yi`aUQ*aTQJaHgiLKU4 zPg>JgZOV>#UonI_OXhC2*o<|s)%DJpuW|D_R9zdsE-RW+ntAyK)59BUFcb3gUY+S^ zm2wqO zw}4_Aj6paGarLs=jP}{%l(O2u&61v(fuliqkf(d(9re=1dU*7aG|??&jE(^pL&pP^JFO{28BV=i-P zIdW0-onm-al8murFu6`0!(g@zgU%Ed7!z6YbMT+-j(GmE*=|U@FYb_=Pu5jZky}YL zz;3PNGUM{`3l11#$+nWmLBiped{|9t*la!Z!bEu>2fK}0HXT=7UC<@WXo{EQ`B8FRsWLA=(qk(M z4X=EbR{n(p5FaEknL5_kbsUy8vly7Vq+MmfunxZ|%4b*1$5z=T{3B;iChG>5DkryG z7ik&w8ahnpq2g1sa_AC2AuiW$wzMVc-als)dT;y$0HLMMLmERMgP zW!v*qsd<$Cf#p5Gw;0|`XiIux;c?k^X9TX+4F+ScKiQl)3`^ZUn6O0_HrHNBg=?&r zFtNsc5R9A;+lS7Bi3nk?zoa|+kXd^pupE_n#aCyLWxdf4wc>-K1!;vdue1_dz}JEu zA~P_#M7F86Ex6@d;=g=RY0;RwLaXx%OGt`52IZC~Ye*egC`c;y3RSd82Li!ghW>lbtAOSY2>@9^( z&oX)2>}wiyYXut%@ujubS#GZ_xC^k)z~*?o!;PxR)09KqQCSbC&G2=A6qO_rvpC^rH=R z^M+}D>_!`Iu8_pO8G{n!)y-tAA;GjFG&`Pd=`vnG^7Vh7f-WYE<1Na-D($)0Szsbu z1kRg*4k9!}eqXAt^FaNrI`7^ra#81%<5d2_7#e)0@;{Gv_W^GG#3+L>e^OoD3J^V* zzhcC>&G}mR@ko~)^#|01m8R8dDALjs`DYF8pi9})*@_zdRe&t-HUviJCCk*lA&rmyB zAmL^F9hK9`IJI@R4v7d^4E8voU=a5NjtL*DrD?>*&wq9IrPBX2$vU;YsK0Ax%}u`Ujv8lhohZ8M&}PjvmcwV}=|hx5!`z z3pw!cYr{A`?1_m6mn+>;XQoYK*5zZETfts6`r79-^EEYa6JDYyhQ9?7B?39aQ*(Iz zroRdlX0yK!L$YxyUmhRq4^g;wnmqaMCbFwL;V6VztF?4|#(KF1B$HMPI6s%lH+9{? z`~iqgDwNNqd{_resp|EQLwg{FGVp&S|7!O}R&Qzp{Yu*$`_GJink6zjWbu5R3|A%d zHP02bEtP;YGMW+RzUPm{_~{rAW^8BOzphJy=qt2e8!=X6%4Rgkzz;|+*?sC11YV$4R{;!S2z+|UxVPH z<<$8?n9K6tg9$Y;#h}9JyUQB+b_QbjGIwj31%{r+L|OEqT2D<9Lv|qC?&vxb2MRei zERA~emvpxy4!n_e(zl@VS=NSAyF1XpuhTge)F63iS;EZ9qArw>b)?Sqb%nG8ydpv@ zc`57jS7_;r_t@uyd1e__qoY)>0YZ^55tFl%df9G)Z||_dCW+ttIh)1}m?-YA4f8d= z7bBQ+_j8p#58?W0e67u?{*E{U+`KoXqwYubZFd&$p*`^@$YntCpP$o1JpKe?Sd!6z z0O3^}g6laos{~Wb)W0n~rGR`pnhRSWCM(=a!+Cc***iIIQ`n0v{FN|w(r7v$3NIv} z%;20_&vDE9IV*Ge##+OThvbuD_t_NbdFltzyQ@9zmvItFAjc=KP+MKx8n&Jo?bubG zNmO|kRR}Ji_=-wgfzwhax~!RwZi__~_sYSD_>4l$2=^xo^2XhFEcAvjDHGX;qCjex zEaiRfLUj02i%!>e4TY#VK88wBQluVJd6hzmoix^85P0&pXbB}?^c9A#ZMV!OC2UUe zmbkfsLf_wS2MS7BbMfi8_*1LKnZ(I1^O>vl!w~KeC5S#6s^XvOI9DDU@SNuBa$yT% zx}VJh!p@2x+#3Q~SGsvU392X|(<|r3dxA=H)s$5c5KU|yKG*lROe|@$9LiD24>5hx zlMhLet|9=uf(%W4zR5pI7wRit-A-e&ctQ z=8S(sZ^#g+T_y2A&ljcK9H@}@=(Ib*K3tVl**AIYQba6VNF zS5RR9eL`xEjNDQutkPt?FyKPh3T`JuR-t@JvcP!=M?N#hNaYEtd+4G zzKT;wdVw)S8C>P=VcGsbaYd-{S?(e&!z8ZShC@q7BUOVF<9#5q(C;L-%}864*XruM zYD?&`spCGN=zEf1(p=Ot1vDFNdFz%0M`_;94C=@r1CynFJB|u=kk1u^v zw6F?=ghJF4WWeokdhOhX_XueSrxx4r`(2EXFS-jdxRY{nh}nXqDM=)z88Q&A9Q3ID z0eKJq=1^D)?OKmE&eus8dpGiA(TUh|WfH;0nb>AhK*(m;A=6!OXd*%tsGRcMZ)8+i zcLI-!+~yhc_xZl#w6lYoU##`ulQ$BDB{sS34JXlik>bsMgdQ2Hs3^`WTCi&Zb`EX3lLB3m7Ph(WUQ66f@uojw?O=kiw>H($w^h>Ng+9$ z4V`lvZXOTrRelTE@x{@e4dz>COSV5 zB_By*&5FS7nRcAEF$YYV`8>XZR?6=soW;snD0#}ij zE*|SuvLVY!wcMwrkomP{9W8suUi|wjhu{fjvc=rW_;T`RGVn*Iv|c|y7(Ay0<%URO zNuQMh_jw;~m9Nk~&LDW_U*=IEe>tv{hG~6z{1wly`}H|T3h#SAmP2Xh@eFfwESfL1 zgA^%m{%*e$0m=qPY2(@hKX%hPF|5g`pzBSAj|zw+nAyIno!rP8^X8EEddw{U*@x@CksfZb^N}>V?Lc=|}YXK20FDn9CObW8@WZiP>)bf!SScgD)J*qAs-^9C?enll1M{Gv zTd+)T5af#WviB~tHnME{w62w&#cOT!B}CA7|G=YlsdXzjoFOht-s9Ld`%kOeKGc_M zwexzaV_i!EyzkueL}av}*Q({@tAB=Kh9*s8!zH()f&?d@AQRKhnryvm&aH_O*!Us( zrf#;#Cq@3>zLIzQprT;6HK*2s(;&=WjNMo6|F*i)EcievVX(#It|JtG?n zL_UFm8*@2iy08(?i!&@@syN2+?Cdh}J&zB)F>Cgqf(>LhY}hGwPvd*1+KlI*MIvlY z>T(-hRQ^)WNK~8xYuszmWa+%^>F%ODT`P^QnM-=Ds6#{a(hkW0KS#P^+%p-}>T|dD zVbP549rSmTYKguPdL5y=z(*N&5z%}z6#)K&D@yNA$Mw;1;S1wZ_mi%3$9XHE;%)@7 z>?qY6da0-9i}<{4qh3cdB}cFc-m3jcb5T|Iy+je*qBWO}ji-RWLcIcfMCE}93X8zh zPNi(K%>k$9yxf6E7VZ4ARfd0BHU;PdcjP({m$RU_L1r45VLC;OQDq$8I9GMh`K;@X50>E{zxsOc%D@wPd#v~2(FX}HLb(a}U>Vt# z!Ub3PP64SPYoTYUhSK0+%4haARo|rZRl3N#hQldo5Lc_1H{(_e=ux<{&ovsIF!z?G zcvG|nAmYpL7YJ0^RY~ZAu9(o@*-H6ufB%PH9=v4kQNM=lMUPvxIGFw>hHqZ~O+xDf zo!ff}k+T6SQS&{$rNiQui<3fwiieVX7__Go#G5<0cULTzBJ09@82SC{MdFhA$h8Z2 z(KLV?y2{zW5>BbY2K4Z?ERZLzGmLQKBnM>B$WAl9o)+EHxa4k&zCs9(XdP0fNMk*f z5_c;;Zo136Oyvu-Zi=6_(|NCN7T|#EYj;(`DZ>JJp7~w0gVuZa*!|Y%eEy*NTKW&@ z6p`+7e$b1JAo3aQzNP`69f|v$#^iMz-+!OmVLXm=zN9{@C@6t1Pv_6#Yuh*QP}S)!#0V3LYuw-vAg|+bnRj27o*f6m+_erg$+1E zXR-^}x0UF@&qG7BFj7^(-;DI-&NxA~se5b(!$`&@C_Y{u)olkqm-p)difnoQi7-{dg7(%m(Pgi461Y2%$91mHyj3>iF= zWnx`8XQpE)K9Z3mw|YzG3k^g5V6e1_9z)5=zs*nzK;~bv?eYFF?|R_-=p4Ey(6J}c zVVwFnuMIvdjN;Eu*O>0Pe{S^f;$%9n=u)ETyyZUXZR%D{m+!CY>JV(gu-qGcYx5Yj zEep*oj3UDwIO{kKesn^D@yu%~yi>me(UbbY&PRS&f3JB)&*cGl(Q;Aiq*oxWPcUQY z4*2xMzanMuntTXaRRb9+i?>HU-lv1(9c7;p&X^x*$N!lG?{eBcFY zrzmT2O`>XLNN4ImyuE1;F}WoP6ycZT-Dv@-e36K(b$!D`ub4 zL2=SfCwUc+EM+P|c?W@1EBtm@GB1P}*%ffp7x)9FcIth;DP$Q{FyBRCIP0l+kGoOnQr{?+SpO1M{`+(`xTVuKU`B?ws)c8T&Z4t z*PS?}h09S=|FUnu(KUaJDVJr}wmfuOfw=7;%VH`hp`F5i_ZT0XT~ylHGoYu3g8Z)& zt$~lU2FI{-33KG6DS#f2JsjkVJ*ea=wac@3X5;wx%??s}|48?SW^$=|Ztrl89m1_jnUJgK_SwczOU4fd-1LvgR8{mozy_iPVb z`pU*S`D_(=Km`D-N${~yI$ z>SsBAXhIaWh4^JQluX>Z70I?foxPjNoAf&U5$?z7n<#$ue$vE>C^A%WM+7F5ZNVei zmTSKibeHM>kfel%M3_a+%YJEWh!snZE}nOD=4AR~|E>~Mhqy_(fx66K2{j(spg*!W zV!C{;%6E@LYWaPA$+3k#>2eH(THGg@Z=GU6```?1V$1so`osRLNYLIReEO~^1eQ{1 zSU2E`f{4e5qXi+txIjn>w|&9}Nb>|{9dy~xmJYqm>}fpJ2IM&b{Xnz5D_5-QeM{wk_T(!SR}lCe zh^wa;a@~b3NUyVmyVR+6*OMX_AT?wCuu1md(fcuzSX9I6Hn9 zcjzjKB*=NM+S`@%oF}dEC;4fSA8v$RE&a}+ppSSMU6&Zn%O9{U9+CHN*w48jI8reN zt|1oKMZIBUfHl>0)^WoMx$r0f1PWMe_RF_lo5!*rp$w;Ss#_prv7~LCQ{%KIYA=-7 zy<}VuzLaOC`I__Q7vMQ*>A4(sJ25|2$yC5-Uv#md1|Vw})FY9v?D`n6Y!%&3pKWn? z7jbbtL}Af3KrFRjhBd-?5cT@PC*hXf@8%_~9x?~+PcWSL^K)F%sxRQArONv8y@a7X ztVb5ug+#z-4|&_b#XWARY( z)ECWn7jYg1&_+#_pb*x(J5RSt-*#J2b3FJd+cQ9Z&vv8j{0Kj(<##@;+uAU06mjb0 zKNFZiqjqkS3k;-XG!I?@?mvM&J?(s{2HG;wg7kuWp9)UL+)meA#^slzEtAdD@Jl_w z7VlpZdo`Z(v0hE^_VjlE4UAOGPhi(f5f@cu#0vByKMuxeEH6=Gq383uX^>P(;YH+wl>*^?vRFj+leV+2n@0SWZ1Etc`O06 z!a{{hy%x{{Z(cxTes0r327Kno5ywC?5T{-+>0Q z9o48)4%G>kB%Ic>B6-8WA~_Ytz;oj0(TjGWl5p-|J*9{a;kV8@98RK(PaN>rz-mNyBA_ufn2fLM zLG%1g68Z$rbLoB+zy;E#kC+m8(NeaH~5Pk?Vbr{|~r+Z*fpzBb=BQRD(ndlhUTfftQXHR35jJFFoao z>BpGiI1yEPTO5Kfqnwy=?y$Ldfs%3D9atvvFS6Uq=}u-wvp2%Ox)DFv@kjfeF{Pxz zD3ixFkX!O{BWcJmvfs4)%1y3w5!0!|sx0b4RpW5pwXayU1Aw+eVG+F3;?&KZ;J3GN zq-$~Cf=wv3qx;9-xfseBzg};Rpdg7PNyjL*C_b6LmCg|R< z*(e|pPgav+BUVkqGu`NGcNW3zuhvO}7%0L?uiZutsYLZd1PPjr>8Dl9(QK+d_@Z9R z`$5-(u!%j(%l!Ba3-%Z?{$aZ0NS_VM7cEvyWY2nDH-GEcF1BTE`6#8rS?D*>V z?B_JO_qvo)BqKvxK&w=OKY^f{;MQlFP*#nc?Qd?4MCSP^zB@1qt4VxtxDFExRNzy1 znh-m6KNB9vF{bPzz1jsC=X?`=?sVxKKU6GO>V52oqox@U#lL>zy-nHvh{duEhfF_%h$mrYmc~go*nt9F1`W|+c zFZZvfd$y(NuGkq|XQ5!z1^5@P;=8^HZF<9k0GxBxhHp3K3IqD4f=-xNIZxn^l)z(z96do*{uMxvX`1%aXb#|oVcB-i*LZp!?hf-Ea-tUN2UQyU)3 zp;kr7M*Y_oNkv2Q#8}jsK7FMIgimmp(42}6byp=YIs}eQO&VO$L3om$@ zz87PtCa1GR?jaX3J(^6$_uR`d~_>S+8|{6Bo<_Sam6A`tv4Loaia=s)C|JnITxP8`)AP_|?M>%+VfOnWU3o z(YLSQq;XF`B`(M)vw8G$L6pUYVaz$eGVDB_*UW?VTw-VGYWJ^_>aB<@n78}hnv3#+ z)LAdy_d7MY4g=4vMO^&Hk37518|^VS_C})c!#tN^rs+{q^PqE~i^V+W)TqNSFC^!o zO%p$ml`VWk)_ugIdaFpNsTesW0mj+XlcU{lm1yn?*sEW%wN6O)BQO?h@1v926aLZ` zS{rrYu?c%*Iqo=Sukrl!hMI=OD5Hn;;IEH`J-X5BuaHTR@A87e1kG$7cCrdQ#WI@% z02r6=qe`TlpS@$u&;Pk>E~JC{&}O5H(8{230xHxNgZKPFjS`STPd&U3s5QTFjjvP9 zq!G^eKFG0JFvSNw*e(W6QWvdI=K_n&&(^?m~;JMZG3FOEn5z19D_=HXOGROi=X z$lS8)Sm|T|8lm66-d+dVV7>21KjON=Pf7&8HK-onYHsyBPDC-qLmIzVT$x;qAopp% zd{UtVqP}BpvB2~uiPkk+^K$G{7YA=5Aw%hx@;&*w@goL3{+B%~m3eAcZ8LBbc~WG3 z9PQJO;V7E{e!UeFQfb`&4#aG!sL(K>J6%IXtBfh<7cqd6M^iNBEmlBKc}Tb zI%nkglxWuu3=M{_Gu%VX(bSJcnf62z^ZL8{KFglV&dJD|WqnU_Tm3{?WyQ#fPUt6L zxx-~o33)JZqWrP|7#3OnH5w^GAhqLkP#jK7zHEMk+5Lv#%^8rjD6mxG6-^$KtaNfV z@G>-d+swnZ^~rm!BlzjTKFtxQ_zf(15&7n5m;#_7L6H})_7BybMnopcCAZ&x@g#a9 zsCiYON*U*NFt%(n)IGAjB~}!fSJT#*V{T39>*%C;bSxZ*k3JLX#8)I&&^`D_40`t? z6Gm{dkFeLEl<5<4TKu@|%D95hD;xblCjPP5@=7q@XA>sp^D!aWo)3h@CV{j%5OG+X zy!G2g^L3nqRH_m8U)7D!M@#3-{*_zAn3W&5t*7V`s=gHo-2b_FaevQqHoEL>SBdZ_< zkSMKS?u-4NL{iD5lVx*)vTr{W_ky0VZa2`OGB1RGqoKh9U0?_S$?M5?&8~9Jt|f0S zEjzLI8fPyo441EP4)IPhau_VFy0SMn4K)zFT&01yG(;n9Pfa125SMn?XJ5+=(iHYY zv`^;Jhy3|V7QilGcZp(om#!-hR)qog)IY~=7Q4pY ztn8)ixt`*tP41l^hqO1M#P|EKJn5x0vCyblZ_wGP{+B!oQ#*j8GHeu2a{0fS+| z35gXGphE>AuuD$zO7n5n2jshHX+}Rw%upxfq?xds(I;;G|Ieg(ap&@g5{HtKKor`Nsk*H}+ZhL`BF>0~? zW7hxshX1FVX`uezDJX1;aw^!a>-TQ*?F1q$Ion(O$urQusC=dZIi^l=PZfKww38H+ zp>Yf4#mSTAr72^#c=;c{hw)!um0Vo7+DFKcpLg*rfOa69a@x6;#swoh9wOg~Pwwe{ zMROjs(5{7ZUA-IniM+A7pFO$o=r9#Q{q4Qu7w^tK%*yqQy|pco;u$R1l0~#)036Jz zv5?g!aQM@wcU|K4&C?Tjrn;=-Qu0V)w9_NLfbJGsoJ1$DgnOdCb$$0o6oA-b?D8Fe zew+R~tH>sIC}u|!ovh{t3VMbWqL5e?=p9<$;>eQpWiY+`)tBvt;%f*-hArPFkb>qk z3s;McAQt=0{@xA)U|=z{6e)>V-V+es#rn$`aOXL}+e#}u)`gzOCE^)1w;YBxaYd#b zS5B8erlD0r-KnY{op?^L-1mpcGb9)WqnPap4$)(%Me^ka>JJ|W)2h3~`vFlYo#9aj zw@C^{OCqOjKCj53e2_u@dGUKz!0di?W6#%Z>y6p69?v!FK$WME!mC?2aIJo`P-8W? z@3VM;_ZlA}(}1rNIMEQet#w5$hvr{x6UxCo5DZ`sM*1NJqvuW0wU%{%9Z~>8vW?m77J@cC{49}ZP{NAeQ~mcE!C5+aOuuf9&Vz`kLRzDmn#uQulRZU!NrG*j^vJqXJ=n zY@yEU{I6a7k8xp9{4*k`*#{TlJt_$Ey((=IP|W|o*H`n=wIle2{|5oPgFdD|nhxZU z7@(n+p&|c2miZqWMdcX(SKtpUd`;*40Xfsu7AT!Tft|%1j8tVTdHyu*YpKagShe1H ztSe^8_RI=%h0yAsPPu}w5J9kH7W5vSj@Y9hF7_k2^(U0_#PfH!KmucLV0KTI3U_Fl zX_!dt%LLhsije>={K(IuwpOOeV9{_#K6a8ZVtz+G zxAQ&q(3#MeYMovJbz1y^?nfb8eVzVK5YJ7=`x$|drd5g`g*jDWSQWPa``7qd5It3< zx?2ixg&{^(hHjBs*)s|jejS9r*NLo^_~`Fts_|1K0^6ne$@U6hM3p3Ezp9ZmtC4_z zA#sMarzJ%1APZPP;o-0tOQ3~U;sg#iDR-QmiC>J`&?iwEK$IL&k8+?eOMlWt%q)^f zd=*v=%4l(s>^snvjmV}aBZ(9-M;2XUPJ-9Q=QXD$nrq9e8`!M~V8dgY=mlWdld|~B zHZ7lJ2v=vmfNgV`yDE|Ci(yQ&Q!9!MGXXS%5TEH+>nF&EY~E)v(y)Di51Y5xT*~iv zt5H~U{$36pO*)tDDeinHvanWbep(7lffT46-`PbMbo03dh64M48++{T)SsVj zHtbtHB?{OB1Ih)obl%|pcW=AqQu25#ZN zVs(6GowzPe`z1h5vvwx~?)0$23B;gL$__~je4g+wASRoPy0+o4e~Ne$JIHIr><=A_ z{L!b_N4BDo(b@TfO<#Rejj=`+NiCjuT=b})Q(=8C#;-Ws&^S{{RNLSk+~iEb@k9Hy z^)2EA;S`pwU-f9|WRzKGczVvD$VZ__hAK4*^o?+eU@%b(7oMaEnG^KjC;fq)7R zoPWwfg|_PWQ*+~^@81<69!o`e>+F)ASDP9Q?Uk%)wPU4WtEd06f*~iI3bRELxb@vW zrWu!n3AKUK^#1ofm#*&=Sd4GF^oA*{Lr)a$3w4f&g|3;K-S2V*AfB@zZ+NvL_b_HYzeMy6J5$6)^ z6A}OE*z4YeE2ga^8~R$|0k|WD#0>IT((h<1k(1f=8XS%;kXg#a8=j! zv6wVEka#Oa zky!ZEM>Y}>yLI=8ziD7~4U*>b7$5?Mmg6d=YIp^$5*zovlyjQhYW3V2c(<{4bp2#$ zV^`lcW_`Kc_d}e#trmmYyS*6x?Cky^EH>C_g-HshI$veUS&i;{cJdaN(pOG>YlSM{2hdVcwcf4U8HM%`Mt6t!@DszqT z6Np)ck!w+W?4b-IF;;5pgzV)OLG1JJB+2-R!Zx7mdF*oxnLTZ%GQ6;l2=dSW!Gsa7 z8BqWG<%q%fB0#>sT-vI`J&fD7H%qo6+JOXhD^&fdsNyf)4G@&7 z?A1O)adZ)yn#}@`H!34V8S?Gxm!rO)X#bt_#|SP@#sRo|(<%FK2K`wzIMQu1Ew!tM zNBxc&>PDj(f|>Ga?qMZM*$Tuv@@k7LW8W-bX-2%lKX)ndH<^@X&;{K$k_eeiO&3T3 znig-1689*1giDhKHIoTi6_l$@8hDOstOoX|-G1(|@?p{Wi+bfBm(CX?xCNkkIQ)fh z@~Th04(!R@@-G-E6Ksr6V<}zcT;UR)W#YwE(r@8Z8dmu34Xl7K6*J*Z}&Ge)JxUzy@c7gv2g2T7iO|J zbkidnPE}|}nd3#~na%9b2amJNhda%^pOtB|Y~mS?p@@JbY!x#~5izb6A zQR*)8+t3x3!NL#$(z~me9O-n#WzQg<9y+Ru{HXEwSz`N={_LsEl(1zVv=K|3h>gfS zITUr>Weug}Sr4pBh(7I&bq8&57K0x3IvCg5)p@!EGZyU*^Z!~!({TjFV%_Mujw^47 z-!_JxJNP^iUJ{^7<)Ij8#@+*A&w>yX5twzW5epvB_1fPKVVD`FXJbRn>yHDnV2PzI z*PuytT0%GN-nK5h!=@wd(WrKh@$G{H%44LYT-BQWhE3mn&E>rq0eJGCfd%2f4qLU% z$TYTf!bGuciCwL*uSk1wBZ{yL3Q8ny>An z>EhHyNb*aP1&Zl)tZ|u-g;!uhrdjzz?E3;3`BwO8z!lYX2AWLvuC{6)p)}F7)F7wQ zxBsmL0PWmzq>KANv6)C52C6UMXBcSbpw4b@O9Q{5FqMvjYORGql83^KsFP~}XQP9z*59-Qx45fgs<+{4z6uO|IPVd- z={AQeumE)`Hnn2J_rR$#J`~OAKQKg(DZv(*eGab3QPW@Vv5cNGSN}KE)>-tIi__p@ z{mMWydwz@j)GeZ9J+Rljyc|JMEs4^zW%)91Kk5Aw%m7}Y5G>e}Ns{qx2nBy-fASC~ z@6tuoG-9ggu%zZ47nJez5j~)F)f>AB!~f+8!?4VUlatQp^?=!=%L zf7|E5ZTXKvScUW1Mm1Ua=A&1`D8V`|)^y#^G)He2V8#PUZXDXUa@+P66PRlgijEQaj%n@k$}R=k*hJ`HNk92i2*%O>vBq)!D*M3%PFSmcd7`TOz z#pvzjyJ!Yr#ubCe#wD!CGptn+Pr>ve(z!SN{QeQzH--+kVtiF#e`zCI_>B+4pMxfh zRpI@HEcFMTLc(57fAiyuFxC}eCt?zKT;*2{`N;O!jO**)R@fz7(H^TZPd8%Z14!egEHQDhz}Q=YfRrwP7>z*s%}mcT>>^9br{oF zG>K8}39nlQ>A0euj_u0ExT_9D4w&AL+%+V5t~RztN%?V$29^ALAq_UL?AVciHRo}r zO0$wAafTCcDAKqg$;o=IIU@N?YGTd7~+g;|=4+|mxw7!e@TX zF~*b?SK_zY{y|b0-jH*jb=+%GfMW7qrK*Eni|sMKRB^zvCoJsl_#OHm8Mj Vc)yPzOU2 z_rAPA93{){)h&q<)jftL{tr6V6zc7K`vHf{5twA4<$G#KmYlFu*7egr3jKEb$w2bM zAmRV~G)?k}Z`dzsUKfcj*Dy_7)O0C{GL37reM2O|y-d-RaRw@XpefXrJ_GV#IrXYkizen4Hx8$^ z;i!Gp?0x}RY-sz|Rt;=8bYjbsSEe*=l;|M6_- z{oIrUay>>{*2rpv&WB?G-GvrN5Bn-k_I9-1AVjyx^@&h~O?DRY{v*w!0BWavwEr4xhK5ULeE9%4Y@#}bGz%x53_hE?%? z6B7~%sW1XadK^yn7uK6h{9JQrSbW(4DG`hhfsNVn7o}Zct53l4Lm*n^q@#hJI`kH2~h>< zJW+eVR~ZO9cuxLrr`vodO`S)dKldILniC!y({<;z=`h>GG1>mM@%{ith3fbwWQF_S zIh?VpnQms%FMbE`IYuPF(MVZ{Fly7yr@;32d0B&XJ>dF7g+JK4~i z9#ljI+XsTXpjf{^t{3f(pJ8C;p0ztz`g3|myg;RlX$0{APtgZQ4}k$DU9>2jV>=U< z4arOB%dIOc8pqdu9bOWD%U7t`{g_}SA{UFK}m?Hzn+1S&L{I2h>56{T6ezAdO^K9RIx=c@C(b_V_x z`f|DboP2AX!3s-L&lxbBpvyOy)!(nC?+5#qCqTBCv;NDGIsg}S=~MP}{)(T8Vz493(uRkpZdUkts3}v!A?~>-%76SdG#c z`mnZ+=TNsE2T-@Ns(3`vdEgD)Wlb&Lh6hQ9e*llur2@=99j#oCKOadRdQ-%y-E_ak zpj`LL)$#WE67svmhn|l?FO-NwKP}zdmjkWene0#`R9(xN=m07?>)fQZ|Fn{k>&HRX zdK|KOAT;Kwh!WZ+H-3b0<(B@qPMoBq3oN!@p+eLsf6jq`m~=+-n_7Eg>dT`K3$~G{ zcGCoy7nrADZDA}pPOq$`RK^u>!V~<-bI1CAyLg+nWXuQ zqRK5Fa8OFT8{x2w3^MJIB;(?=3D8%xS169jB{=WM!oxXPC}lD(`$SRrMw8kTgg=!G zvHH$FDg2O2f=GR^2)h0BHV^P~T80-Pz3#nMuPY5tTvWGxr=LGOXoa2(if>v+A;x7t zvLsLo)ijFTe5T8W@f+=iL>8wpYzE(Sqt+wf2|i2mPl8q2dg1Hh6KC z9srMh1AF2!p-Z|C#QU^_hr#L#<=s}1-!bcvLqD1ajPYRQ55IjPrVo6pbztrdI~WDQ zErKsX2MseULQ1qz(~dto%yMVoZl%+CFPj%4&1bT!eb_82`ogxCkruQ^x2}~|{FRqB z5&)})lz}$G-Z0!gkyYQlepF)_qw^rgay;sa=$9AXh;@>}K;zB;v&m`n{hrLF5 zKQ*axA>UiIV9L|0yndJV3O3GO722B&@wY|C52B4?zh^u-rz-C4GztmELz|=lC+{<= z?3c?aCpJ38KsCV`o$Nj(u2b!H%HISHK1F#KnfEpoqsUQXq-j8~2A=5tLigl-hK5M9Lv0t|5A9dyFO_qtvr zlGWa|Uw2o6@434-=cR}b!zjkU7p%UE_aAzC;5YnfK&IO=x=SAp=Yz4E-&X$&}2@7HPUYL!y{Q$Q^ikFPKiF-NPfU@#2VM{ zB~t8HScKH3zU{O@Es{p#s(Vbl#6~Cs-sranCJi;=u+~y|H;b3{)8WyHdtx{#Q}tx? zlKOv+HQgLhej)=E*~g{U$`GkVtBNIxONeR7>x@a=-jdi^3W|b9M~m>*+R}=_r*1diq3<@9J(>LO;mM4BdoIt_r?-3%QxIsuUSeS4eO}F7GX7N0 zGchhjBii_0G*veF76d4sdv;AUDMI=^-3PHRlL-=~b+q`sZgSgujJ`75z3{3GaQ@F} zw7EkF-?{YT21xS8rAITS2e?3ZBCEZ--myd|seRDfEq0A2Q(T+F{|)4OTa3BzqQu!aemQqlWl&9p z%JXQWkj@(zJ+n$Q|1)nJYwn`a>pJoCBP zcZp=|gROb*%xJ)6t-0&H7lYZP(c$ir7h|L~7d`rU|KZT#;oBHush_=Z=(*ajQ#P1}5B@Gsu($GP%Xc%l_( zx5M|;*9;aIbbTNW6|sBTlO+oVk7sA6E0?hE)A+7Ri~?f;hm%yPA+|TCBqwBzM%=r< zrQi2f$KRCvZT<50SU9mU*iMu}m!r3=`j^bPjWiQcwneZJn?XVUOv%{i2C{|7re*Ve zmyJN0Nt(}IfTq|ItvV!Om;bBS=$=-W9HI$#F~TtD!#tHk zt{@Mw-8EC&#~&GL7d1%ZZX-OPL0tOKiX`rTtR)V(kIY>K&P*&&VNY0?v(8tEe4fln z3;Iy>MR?J4(AcnAO$InVQ`}DJu(Cj2W3OiN-?(NE`!;UqVQ)%5b*SoEZOWdxjw-p> z?LU^SQdX0Gh$f=}u&$EDpC`k%WF}SyGPAY))$2R|Yj+jX!~Y4LnI|r=uQfv}sBq_a z{Ijv5vGKzbqXoRk$-#-vk?Bf!xYnP1+mmaR@;9@P{=@DvDn7DPXu|dE$`J~54U%w+ zPd74Wcn?y11W`&{pA(go2`;N=ZIh?c%h*)hqb;mD@FbZwO1G1A)6dYkt_pOWAGeF;5_(dl9}b{T3QdwRJ$ zNq!tnBGvLgGE&hO;it&{-ca7L{>4$MkbaT73vP67A^{}y9GPOEhlk1IzrXE;e7YlM zSk0)E=P3`xItcGT_Lr-szbc63{c~hZ#W&aZrf(D^n~8^sy<`3>n}1u35>xaj>aj#2 z3M<$M_8)n9hCqexg8R>1ZVNf1`_?3c{5~mL_~F_daTzF9xqdLHOd|eqI8Tr#Q2def z5=jOez%S~zyk2!^Aa4}!k*%q8LMI74N#b5j{xG4W<9>Z&Y!x_9P$b>orziZ zEo1+5SBdsh>|g{C*+pDl)Y#?RBh>{Mmjlq+lb$A;jm44gah^^JpZeKqAJEQq(bA@} z3#c&O>T@umQh0%J@K#UJ{;8Wiv0tztxraOx15XD*9QCSI{NKFMerYv(6i>OcLDYCS zrOJO;T)k$9^yP)-6b#J-@HWzGZ(lx3FKqy!{O!kxJDNj(fY=cYpRpA3(F4vFvLj80-C3qQX5aPF$jrKfhLAnAFH0b#002o8Spe_yG7-xuC3 z|22+7MxKIV8wI|K2)pwp-C$*PLL;p!51g*lOh{x3`d8w>(_qA(hGDLRrj!oD-p$%E zGch;V1B9O&K!`S&x#Aou%Qdfh?6AAFRWyKMJluu`drq`0$Pwa?H&n-3etwFoTY;YW$s9$OF@j$~ITyB7O(1-V5Uq(xtKBWi3W0f^hEP4K+7wq2s$P)rB9Qae3N z4pbaBNXj`R7hbk8u(^u@S||lh5WcYi{!ZI8m`fU@mZ%UkGub{1D25gX-~3&OPPz`- zbwCH3B-w@dN80>=hJ?Ik8NYmR^}y*EEBEZD7n#?AY=Y?3nUqw2^mpH_vq3q>kb4J# zn<4V&$Bn{_Hjf8{+NM3rOG-Z;sFK>R51E-ZlsP~HQFJj=P&$rLWZ6yhofa2zIFVLS zqG)%y`I$TdwGO-wS!78d7szPk=CHz}kB@lnd+5t6P?W{bd7Ck2S&yIhL5k?<=`JUA zQq6r(F+i7U$5x*y3@x_(yN9U_=GYq~IPsUE8smRa?N0hO9~PA=YY14fM?kSO>b&*i z3io)**>fEMYctO^89%&zOpHIWzUzF`Dc;+YA_Mv!?LaN6v=uoV4}-71C{IGaAoy;N5PiwR@CfK(BsnY5dNewfS#U zt$IX`q2DFt{S#7Z;-^}Q!t&P)iZ3fPKJ=W6Abv0gyIdlEI1CQMuCI7b53%eWmD58K z3Z7q~mNUQLj%x27y3^5vWb&X3%O`qRu*`|w#YNP@K{2$d>$mY33xvAuH>~AJN-&w!c7t4q1B+D&LG>dFE5{EGbrM8_0qG$x=e4HSZ2qLyNR1(!?hp_#eLfpoL}Tq<%7j_p9RAq2GvxSE}lhnItU#P9F@vi@U~4 z6+z37AwQmulp~8^)4y&ECBfBV8ZkFAu|TG;@nnVu>5B6aWOl}ki<;NNC*=RBO61T@w6&$!b~ENv$U znfui*FkC_I{KrdNhY<pfx(LRvf%2Oi;SyVp-l%|2VIAHl`pX5rU(!|KA$Y2t>V$IYPV|PGj9G zAM%&5{-`+L$n|FYM*b)TA@G8PJnU+|^Vv?KDFNkj#5AAT+m{15}ns zN3rbGHIVo#8xtUqG4#7A-qM8f^-fMm(~x0Y;$CQh(91obyjxUHgm=(ZC^iS+V~Gp7 zE~~YB(&>97wXnUK+Ms0C7qtYomDZ1G!p>Z&m+QV8 zJ|L#l>0dz+US@J#VanMps#OJ2MN>WFx21@ZFOC_=_e&$g|7NWcR1Dv7^~%qrc_Hln zIrF>UxU5khEzA#D9_~BiM6+j`O)Pu4v$rllEk@>aXB^qai zARzEy3k)glXlsaa&bDkeu5zfq$noxJyIf9(lb**$dt=LU2JP|}Z&Z2?C*=_ZZP?vX zBb9daSNr=jSN&%JC;X!3s>R#LrAMMSJRkPXLl_#4n`OqkjSJuEH?neD*DnQ$E0HKS zT9+&ZP_62}FJHnpZqQIAr3(uyEyckwR6?)7>0dv;%Ns?hx2Dh|;`flG?VZb`_Afu) zp?qBGoU*J5RspqtJ(lZ#$3x&^$j0OXuMUF6S<(5XR#Y6zdmN20&n23u>)MF8$#{W0EWXg+L zmNq=0_ZePB_VB0Bef~FuACuH#khrHvsQqh^C*9A%mebjbNWLUEHgQc=9~bV7ph0(? zKTG-qPGx`UhKVw@a^TDB96d6XhK)`w&S#zm?fLnxoUMkfM|h?k)GBp-cA@fB%A$PS zzQ)u6Sgq1cUkXfzj2*2rqu&TM4G#XICwHg#s}qhRUq;bXmXOAc7fr^_vRD7cvTOqA z&vNx3={VsO=19FiyVIg?=HNX97w9Hlm263uG;HcM3FgMi6Gi(lkq*eVmG`WYk23us+z!!bDP{k2De zz?e{ly&51()P%rhYzK|dk;o!lbj(d$6&Y{fTCrO7$T!x|&etz&^yD=iJ8PeERFONkV6r=+w=>XF|=yp^>ktoefCZeY8 z5x zg%FaIDytZhsLLec@$9Qix?kdOH@MB(R_1h7II_MS$%Dd!GW+ut+Zf&^_=K475%p5j91-*c(}} z8dYsCv_cq$pog3!{R=ZgA}|#xxoxqD5@b$|9XpH|L2Md*sc>upYMipXqClVO8Llva zNNaADEHaRx3?s;tpND}wX#PDJ=q$kv9bNB>YHM*wY&%YxT+#t$qc6i&?hNdxvM6Hb zUQhYCCJQXvfTb5b#s=j0R6#I)kNmh&6lGR1Z1v-rYW-+P75uIUS|SW7qE1q1uW^G- zC)jX(k281n9f>>QpLmaG@m6~R#tv8sBHme+-)ZI{JyEeuC6o&)b(0t2?p4>n2_7Jl z)}#==ExC_>1XI|nOo7ghP7=cv0!+~DA2o>kU(Hjv!nAMzLXuTB{hb4)VllSi z&D)|J*D&?C)Hfxq_csSB5}C<2(7+;<8k4_VC6d?@_;>E!R})WbQI3F6kuHU-r`5J|*Ua=U=_Iq~NV!LAHsOmY**o(suFqrf zqV2mcr)w4&2Xwx!MMydK_S(NVSdi;__`p=6nme!o0!Td^vhC#vuU6N0{V*m4jYA#> z)ycbNfqn`!FNywB$I%@=U_uOWiYqD%)f#W9FyE&~p9&n?bKEoe!a)@U*JG-F(CDJt6Z!u@5#1N8gc8#rnuC2V=PJ!SJ8Cr?3ZU-1~; z8#Xuw(YCDKWjz&*@+!TZ2K~mYUML!t_2L``MA3lub^muA$=YYS9)~0d8e!8@PKWAeni7%zhvu%AdA&8zH$CenVhJf=n?HhJS`? zk2fZO);#92O2YqDE&XIBMiV+o{s)jfNT&sLZ`)KF$M~r~kX;BAXH=;Roh|>`hv{qO z5k&6x{{w;EBh2VwX>8rM*I?9DVd+ z41;NNm5IC_*oN1)9+4&Dqc}KQp`Vjg^oafv*dccA(Qg2^U`W&h1eR{De1#=0t!pLe zwW9=OZVEjDGX`fj^>wAFyc8=^2GdXtR!ByMKa4v9;dR z7QDu-l>zc3`Yr(&o?+}3(eTXIfezJkyb}4)wp1;AP@4|sM0)8{DOMpCl{#KNo++}a zN;>u*(JotyjVef&6fFzvPV2|+c%oW0z5=v&?2TU_yq-k-_oMxB2s^*i7rQ>QgZ!Yk z=4cUJ0NhSJTta4)OKac(CcCoZef@r8?VF*&4Ib*hu&i+m!}_I#gumbx1yhcY<=td? z;NDvWj#fmF)by#Yww0l~nvfNlD@63w6XQX_$$<6w0|JRMM{gf9V3jy^>g}>>qCTvL zN9OH~ZsCR+B6{ohl$)AY=a->x>YGW>;Y56At|)ADk^zJ>61$%)mdio^qzcWB28k3{ zDY_+V$rH?(93FTtxe#}gtPudG0gXld_Gr44dihcR+YytA97DB##+B*&v&c=*I7>SR zzX~fmYG!bEB7O^f^Z9iC`OkPlIulhn=)FLV?h!Bd9Z2O#QTj3F|F(mSbwud2Fk%iv zqQ9>&5dyz2OS&vtKzv&zm$k-y+T0ld8Dx*Lu-_X!N8Vd0JTI(%?}dvn?-$)E54|_w z;KMf}*fIJn;)Do;aJv_LUJz=Sd&RO%&dLQEdQr$3B1^HR=!dU|Blzo!QTak;!Px`R z;lYo3z4f4fm#U0k76C0M?1xc3zjbFrcW{xk(F!q^ zCs9}$$F@7c$r-AB2)f2b4A_x-v`u)tJ@#Pe!jwLFz;vgO$oh0aZ27_BI!)W~^$B$X zSY%3O{>JZA4BMe-KxjQQ`X>Mu{B*PEUi)*wTk_>_|B`AX8=dOj|vp8NI*vK2Hfi{xGWE_l$^Szr1=sUAZ#eI&oTc<%OnMT4xMHnfBsp+W(r0ls^}q(tv2#CyE{&>TC1vT^%hJZ zC(C~J>p{9?v`((U}W$rQvZ?s#P%zNxawMqwClHKp7Y0p?;^*zi+fs_MVs^Q%-pcgRgfxZ^k=bCQFHhEIpEt}etp{H7ePz5hLUVq9 zb$8C4a30MVv{c}^hI^LlT93QO4$cP1Bz0I-B6q+@#zZw;UjwHJT>{XX9cslD#wzMyiXLUOdKe%7ab%Xcc!Jg4pK$P$2 zKL#lJ$zDJvn*ja4fXVYyJL=T|L9L$0Giex`1p+bg6qMA(v_yDP%#1(OkA- zrV~xdCP%X4^@JNz65dI-+5c<+6OZ&iLIrN2MGWzDW1V7j5=Pu+pOjCqkC}%B{srD* z%aM(OM#`L{*9FnB<8oM(E2PzG_JN0PV1dLX&?hezkA`wus*o!ZT+ovNqgZI#wkRRGF0 z4Dy`;p0>viaG(Sc$jf=IT!<0>m}!acB?#K*odTW&kByCAe&q6Xf&IIy^h#6dp_i+? z{29PW60LFsOP((1px8Rl<0(VrYX{xJ4yd!bMSjDqZ=573urQ>=Z|>S$=D!hH@?QkB z8q^t=uplyTrokXDS!BYk)iC(}ZV%Nj{pI2Z+qqTaCCV%<@#)W808)yGyBXQIjScp} z4aPV8W1A-Lj&S*DLl)i*in##sznB75aKxHX2z6x|^d=({SfHr-Wx64`U*pJ~grfqy z;^`?`zT$WlY}JVOb{Y0$;kRc%PcTFOB8vzM^gZk6`@lPnw!bT~Mo7(|%mxGiai8Wo zV@>5^1^o62MRqG(VAJR2!%2$x;#B0*+VV+6A#lOov>HuS= zK6798{Vv|BY#vgC)*Un_?(q^5Kab9mtG#k zI=a{2_)Y%oTX{BX9hlhBm1IFp^$Yb@h+&>7yC;zIWY?UQE0vE2{j%Zr>h2z@Jt8sw z0D7^49d$p4ENFC$DDxBvJng$U&GB_BO!I0QXf|8DekcA=K7UrvR7 zhH5Drg#jm3u3WBmd=AZ%Kg~}t4TbSe?8c@U8u%A~-Ozmfnjvo)LZC-?!HXn4C-zlk zi2unAM|?V7_#@^%M=iMmsRv*Fl76gdW{^?9bxunZ&lGB#4u1TF)hYg;HrxC?hMpF^ z40>l2P=b1FZ0sK$kM{B=z%Arc8R~{1ZvJ?=a{YGIT|mb3q$V8VJ~~_J!36mnN)m|F zZw2mdM>8DsUzqPVkR*JrhV_FOd-9YzQ6h@9(N_287=ryi*o-5e5h<3Y0=lD+;Xa@K!K#cDWY)C3nUhg_k<@7C^dtvW8Pk|0Ztge}bGB7EPI&yg)!%f{%z zFPFK$`;JBG;mLR-40^bBhjJZqu2LEImPxo%L2t>0CveLU1oTS+q_%;F zmUZaHtB}6}zXljGC^|C_h@%F|EgO6N zFf#?^7)Mdg>PCvf&`~ldG>d-fL$ccvIaqK=^Ai(iC;+lIkSrJGVf5upJzr|3@#3ir z?&dRHrC;g)1l)0N-+tMGd(-cg_W+sUWnsNxVRB|cgNUyp46j7uNCX%q<7X2wuM*4qv*fUCFc+QeL6JPH(bJ2PCOF@n6e^KGZa}R zlet9%F;|rYAVlN=zAW|OYd0B1vbmWa$){-xPsDRQA|UYdQZeVHF(LrP#We3uAe#D{ z5d$a2HlM>U3W^g8$!Nf`9+kTiKPB^*jqG@0kDljLqQboE(zE&tioK(Cqt+BjM@O-2(32P5*O5ud zqrtvn@r&N7h_mrVI|gu3qeTQOXPM)qR==W%@p!z6Cp0 z-2PeIMU#%9l52`4j%LOxQJ8s|by?)Ha9C2@T`EckI$D2a>a)u5kr9l{xq}IOK!&#X z+Vq|?fsk~H;=8`t{wkRZ7>oSEdq1Cbn023=k)O_<;eQ7#_Kj?wfUTF#$1a>+tF!{Z zNH`xi!Eo;xC?6bz#B<>(Z+bwA!1r|=2VD}GPt0C0xf;8^efo}^7VQ#9`BO9y5&BwX zWqj*}n~X{KDLgM=15$rxAG<=`4Pkc&CYnp}{61vAx8&W%kX4IWx>EHWraHGgh_F1wyYI-GtlHd+1 zDS6kOG?h<7HoqKGowUyPQgKN1oTdv|j$ZI%zGF8bF;0!39#m%oloJT8IWKiH^I>n< zxoSo|$j831Q{%tKe@m47&z1z%<~G|;IE>-@9Y7-4U|eH+v-#n;c8y1%yI&YmMPMM6G@p_9P|GzzP+!qw#aDs-VLM5@o)F^OO6MCgvk zvF#SKyRb1`QCWteAB+FQyC;s;+d8yMqBLE%=^bM-$I{Xh=!EOJFyXo6x&2a?x4b$E zl!&-lea%vfHztP)3=AWG8&ugyIy4x(O zIFD^Wez*6(s(LkRLY>}QYC|6h%`mj28UA#=mIdv3fsp(#Bj&LoGZ6jOjhm^lZ1yIc zwDcxk0BgmbF1n0{T{{>)-=hJ+-lXl3z&$Kt#S`0SA`BlbdzQjXTCI415t!c2TGHRsQIWTvo|P(-t=t&rWI( zt+%a2W%!+y?<@zZ4MC;X8kSu)v&q@a8473#KV-3of1V(XY)%r^ zf9q{SwI!$i!)e+|!k3`Qkss!$bGOx~chWx9P!0+$;sY=nle4OD^i#Z)gOHM8XDTE@RW=8>EC(-yTUjn$tw zzI>cHuFOmz&@f1hNQDgC`D9H!3)`3~dD_+;>$^@d3rZAQ!yZt5@ewKA=p4rO-kx=Q z=zzkeH}_z(+GyIk_ce*iu0txR-_z-Fr^|e$?PWs`C-~Y=HHn_%tuY-)GK>metgQ@} ztgAXX+Bf3~gaUAOPD6sxZGxEY-ca$scEFUu-=+&pNB{&Mc%?hvMq>WDtPJHM?4z+9 z_LyAQ_?{fkZq93hI+b0l1EpIGWDxEh732h(XQ^^@;~w9T7W*ECbkq&r@PTWJbco=F zSX93{Q&HIL#gHJQV{u=7U~|Z#ef`TO;HQz2=yvIuGp~hgr>ytVTT>1L1Q zpx?7X%w0zPbXHs;&V7LO7IO+Q6ND-#?HeK-B-rai82yXJT{f zg0W(Eui#T%SC@IjcpoGG^TB(kPSb|2+lkKJIQGF}Teux9W%4x+FZPJ+H%?_T9Dnr9 z?+1-Q`e*9BOIL0nK1oY6D-hXuij86!0=Bt1z-+HK)57d0Oe4mD^<;3<*4UH)@LvZx z?F2WzQ*k{{m)TgMld!6*7LuV>*I+mAoxjFoIa_0V&jsJUZE#`dqwI+4Oe|Y<8N0 z8*rk!#eOL$9A;)CxfB1{L(5q}VE0 zN((shoUq-Z`y&H{W-k!m4*@&hR3w&TKOMbg!c#tdppN!pEWzxxKz5Q}S4m$QD-)a< zh3zDVdgCVrEXv50-SRT+)+!M_Grvc8gkSb{uC#cj zvnt7B>IfCos!ZMD)0vq!emLL);4)oR$}>nHEpaf-gd|^DAQAK5Ki#^yYtDNNhYd5K z;^#EO%)5A4+$Kz+tX~Wg+H_M>o6@MazqI{et1CmU0c$AEzWSz5SR>j%j2(J)_*szi`XA{BGo1Krf68jTBT2w$Lcy zh0KP8Xv}Uhk=P-N!p;d~ILY<@dK1}`T=|i@8vJYz)rnDS>QyC(&fld#Ty(K*5^jA9Re1MB6na4+?Bdh!9kBU;a85Klp>biT#$)0g`}HW^nv-Gi>C9nVdn?uDMb)@ zEViIJWB~z8>PKBTm6^o;_4KDxbUGQ6o^Ty(ZnyUBeEi)AR3nt)w=SAv5?(gdxzZLS zPK|>%;k>w_$ibeVwQPkl{vb(2yGp#w+x}@m;1c?k5dKC<5H^fx-%BGAncg()eL@)v z-sKv}p8UlQ$0m%*S9$o(Z1%Zc%~F(l6_7a}!$9Ste!m(*jniQekny{KM?fG80E`-+ z0N+cG=`6#qMI&P`V{>2;)Ggm{&I$ceh0C7x;BagJXxxODrW35_TS;9#phZzNpST;o zZ-Vci$n{8>>(ZR+QOl9-Oz8q(3f1fxvSt^j$IgPq2Th*sjippr=D;4ek9j>HUFmSu*-cPN>b~;B zgq2Ni+~dlO&`xI5_b1#5S-iskT@V2)2;1Jccgbt)SKA}Rihj3INgvj->}&|kUzzQe@4-~3Ti zBViS*BIg+696I9duuQYH>g>FomgpIzXqW4fC$XDmr_K$J5R3LP`XSo(sqy~jb;jP8 zJI-%*mtt%-8J4yn5BleA;`{K2Cv6B`LAlOCDFQ0*w&jY$royHUk%j1-$HG6YDRx&@ zsLy&6Kvmrd{<}o1Ku9i=O-1~0_&^TbUj?y>yNQQtP9wla-{=Mc#is^tH@&a<91woD z%S#Qhgz1@#(gP$xO&m%bA(dj-#N9jW(OSO7NZRbXx{m#o?0`D!@-s!kRZ z-*qU5bjzZ%H)qzi2EY^}^|vy+OwULi!d`>yTcU<@C6p$={!2Zf?~(8}R|WqEdapYn zo%Q^mJ7HBL2A{a;?A=j^a{Zib&ks$CLG^9u$U0(~EqAm{ZiCElmTNlWyJcn#9BsGe zaZYHTNm>Hi1i;X&;A3m1oAO|33?$BQ~Q&IeBjpEhaoo zoXhv8Q`8eu*bVjLumS?JRbD{eMY<|{iwzg}71I9Y0_7F>^{1%r<<<_Y$Lgt<0YM zzw<#$0`luLcxlNi?=6(BMood>p?S3kt27jV_1-S<_*LLd2Ho8sVAt_$jU7o5={!w~ zlhC_2N}(O9=y)}181lb`t|EWJj7%oIjSLO>J+HFdcsFgAK+dr;iDdB6a2uCa@JK>8 zi%3{bD=+?l07nstXXArwoUO^~PBZ7GRjH}icdHi+W$4*4DFK=`|4rw)8t_GIj(Sy- zgT*ki9)@VyeQg?hN%bkA2Mpvn9R6=BmwIl9n&<|GNF)xXVO_)fYWL&HUmLbpst*X| z&#}h>=ef2lKW>!E@shn?@C1ZO(qZJKXV=H=s?BE?XupjlCCnujk>K4UvlFNIdVg5g z>~46(9(aFC^=w+87kVIhMj97VqmvuK;}l%@=jbAEnMpd|F!b_eq9ndzVX<7BY<(?n z((Gfrf4GU~Q-=tJYK&U+WRVfN@=)xBvBLfGQ(=jUfijK}?=!Qo~i8AJ@uB z$$qr=JUztr39cgdj4b>4t3RUMg+eFpKu$QWj zhHwT2s`?8r_TM)KB%fUkMj{Hfbd~VP{($Fe+xmc~j4sLZ+OCNO4UmpR@fFSsNUFQw z?^We{D|zMK(Mj3Q8)TR4O6SyTp>s^bEjb|{PMVJSm-Zw~z68&)Rr*`}xzrZGufyxIa=!(l}V!9Z3xQUw4-t?aYxS9{rfd z>aXyTs*RkD)e_c2x?=8-f-f(AkK0y+w|u<}CnI}n#SL;9QTM2~S5Z7rSqd7TTMJ%2 z-Kk}MVZ>@W<(aqv7#Nr(XQiJd*JvyVVA%fC^eO>!G3pg1edSp*$HmF-4O#qTK2+s8 zl54V+`U-)ITKX(5C4XX8RfYYh$a$U_h z|8RAkbqWv+lz7hTM3|7K%=R`)*NMF7+SS%pgOt=upiCp$++LEmxMM#pc46MY6y0ga z+Z0BVD$lx9T}h{$?oh(#e2r=<+A{xMD=9vH+@6KplLvV47AG*>QFP&)QprSrW$DHR zpxcFs6>BmIVW5UqF5|4`w`gIkq=Y@cTF8x@_YF7k?-v{(;KJUP90$3{_ws%6{3zv@ji7 z2Z~VsbhhSC_nhno$!?u)f1r-=Y*ZLKNpznEqjgS}=vaWB2vPBp7ZV~Emu4Q3=+!9v z+wc4Aa3GNr1EGKm`DB^E*3A)FW(UhI@pV7=TJ zJ}5HT9mGB60C7*fY};EfixX0zelC$#(TytqIisThh~G9C3X2ksyiysT$Ijc;=R57~iC)?;tDy$yf;e%Az_tMvYM> zjXdxl zB}i6zzEj*`jKH}3>spuD)Ez(RhLY>J=bsE>x~2{5o#wemsOH)wEBN0&YAC*Se+xC1 zq`FBblqm!_^h7tpd<@+DOW{>)bH>h?0_soK&}2(R%Yl~?^!QvpSU2Ae*On!ZcH!4k zJY!ZGXDbjQzRKj zSEjQ_y6pRG>oRPzjJZAP1Y_`FU4Lt)8{Ue2Rmcq2NCX6f#G~>p@ak8`r5E4 zr=33;|GjIY*j+=%#QHV)!98m7$5XGts-D)fz9?Ppox`X3{`m`jyWv;$#K9Io)4~~i z#A8`u$HPD#xp)jAL)-_0(7ShTv;+Bhm6bYCZCxsW$C?*>iC8r|je2>I0!(GGjDobD z9QNxEbzC32NC}uq&o{LtL+zQ|9t!Y0Mv$iGRu|&U1u5iXS1elg;cOC#SA_LuZAl}T zCm8+#rjyf)wFI!+gO_Wni~-L!Am1D4qfjU0%eFuWbnvV1Mu5>h07cTpn)-K%dkED5 zS&1h-N3i8PY}iBJ4Vv-e>R^>%|G|R?91UeXFFXJQ-sAXA%&Nx1<%zL`K~DQ5Es3DK zr#w3NgLOhAq7si8Y1z)S}sEKcq`r1RZb zHyUP!E+@yr%FwN&Yt8R9`7cr8szI2XoF`xj?rr5Nv);>WA z-8+7accQ5F*m;VMeNbaI9gQ``i^CO?<1|Xf=t}|z?uAQ~-6@*o*0h(Ep`zklotG;p zxY@`!`1v})2#y|tnXSN2A?_aL>}vR zemj2%XoQSa2!Qe53xdcCbQ8vxgtQSi{mxI*!*tyXabDypORH7F!l)G`2^v4VISi(r z6UJY$4X8=22~F&TBeIPeC6!tj5bM z;#I_gp=(+0bo_i2R6{pDc!MqSmYsuT;6t-{m|~5Rz4BNBEvqAADa~o$SsYazX#4(A zWOefc(&z@cnFClH^w-z5w1>~ykxQgIk0dwVOC@E!q4K2m6JE#~zDs5_UY`E*L*9ry zh#$Th*)sP)?ALr>NRf)XIxkA(*e31Hi)ha5n#h$>982-Hws^RC<%&BtR=DfVh-oy$ z<+al=3`YLew+NX0d_NgMO1}?Ew>wdiqOBRlCDg0t-igf^&ZuFQ#X;3TqR5y42%Z`j zAFcctY}BS5(RZw{0$TmGI*KL1MbE!#*PU_=n5zE{7{`)L4SVI_=~FV1ff?@RpzI`x z{#sG;A5Nusm~r^J=Ud7ItmIJDIXaJaMrCF6GGRQxEk`g2PjO7qA>2mr@EF@d+fcln zp$VNZEXe1%@Z-tPWIE~Kn$B}eH?n@m5xq@7KKSo#2+?s~J$QC!i+d<`*f-DFb%bl`!#phEkT7I$ehP>Y9@T<~oX!;|{kYNY#a8u@ zD6#cy(C#T}Qm5(J>(01O1N+Mty?9SQBcE*UC9u3H3lQm7=6-bId+U5Y(}TKBS{~hW z`c8kPzdmTqt{1EApahq(uO(di+1pg@4p}bF#al*gnid`)4@Ixt$1V-Bs^i|ddq^+6 zifOY7reh3E3Xn)u4ElIA$zlEc>K9p;AQ+d;1|MFB!9 zBOiLqBvZ=~5d(U4sN$Th2`dv@Ntp5zU#9-J|7f-9W|R_H!m~i{-1|XZyvYKH?&;FI zA^~(gti4iDqXM+Bu$<=DD^Y~N_$c(}!F&TUgst>WuOp{2 zN9UU(OGm2s;q#y>eahDe&iMLd@`#NvI|}?qSdW2rzXd@;z!=ir-OIetg)|EM*d%WRgJlEy_wVRW>3JDw5wFL8HwBLxrt45uG5m5_6((g(unA+jo{SF;&*bEvp*KmPrb1J5@WM-m9~{Ccr*nT|p^U?gS! z!6)GfTU>@!gwo|J*!8h`!dN*!dXBTTX%`^jb9-VxJYj-MXyP>WKnQC7n$rxcoNnGK zF(^zG$CQN6iw=g0#NW#aKowN4rnJ7n@9i+C9&l@xE+HD1Xf_;gNp}C4d=-_=Vztj` zFX1VajqJ3qQS+Rz)3a=rsnYNKqGoGv13&LNPAc!}k_j!&naGir*nOwrP^^HsXvs>? z%7E7MhVG1!i1-pLJj43hj|l;>@KrQ#$~~4&IH*?}*0#`;Ad>-%3>AV|wuB&1_M9>do9M6}x4mC- zezD3itn50ZMietF`Hjxou^I6iRHl0hO>{50>^KtC{qY#@OKxcn=mB;R@!4_Hx`fo^ zAmE38bv6JHI$PU<(i@tmsyCw;l=pHM|3S^sr@W=0{}%K>)T4WPFUYYP`c^ ze&MTIHrf0;oE2s?0a0hd26;g?Ke7lwnqA~4aq^uR9RC4F(k1pn?X-1TbM=sIQAC8e zg4TqdoZfGfkbJF6dMn6Z$MqRqyfiW(_6tY$&pihlQz3&lanR5Lk2z67h$s#S*#G`l zPNQyW%lVAf%5zl%|Et_Plnz~eY-aJ|{nuV+(GL{R3ZP(5`jwaF`ltEHQ1EZFl^U6& zh1yOB?(axSGk1P?$;9XdlKM#*5g6@xq8|m2$yKv*Gpn~0er#JF6 zwqUh+ldIl|ze-UHcKWfG=9Zham>xHT&r)Jbi9QzlDxdjdKVm8xepm0_{aR0z*An=0 zEPPSHJ(7evW2d{C;|6>+RxPUk9(0A=jvjrmP%^tcoDFAY;wA&SQzAb9-Rh>g8Vfgq zVhQL8BeqE;LM0Yc7QbH*CBG7$YA6m#$P`hx?&bEx*$OMH2Xyq({n)yAyj!JryLuA? zyQb;s=$OV;fK9+j>GXxuhGYsLp|l({b}0wG`SMWr^{D6Zl+C5`VH0h< zdX1ZmTAtk)C#%WYshXqGm#f{@%BMDIJXcIYW2?i^bA)M_yx$IGF+|t&5=%7-8lJir zMC7QJP~dj8s#^xfH_Wgt3sbRTFsW+31us-rZ~6@MHOkBxUT7*QArJH;)s@2vdizmS z%Y-0~+53PAx1JY=>fB!lT7f8}h-hv3{wcuvO+OeN^D;W15Q)te1(oo8GeXO%r1Yc_ zsk|p(|0V)%1GMNZ0)uxw_VD4{IpEnpv_q(WKvd+T?L~B`br>|3{DeeX%Vn1SQvd5d z;yj%)L?|gBUSBkEn&oWX3{8c0$vFhPuYSJKU8Ybmi@HF}^l@3(1P(&AbA{NQn^z3_ zG8Pe`i7A?{v_5JjQ4E!|1ioQBUU0fS@K;dP<=t{+KKP)2vkPHtPGwTtvSZ<(F(^vKEaQCTYa5ryp!Ymw2i zTjLPrT%~-}*aePqYRu(9J1RcqKexGLU8QI^V#Izy&2bG#lE)wGkOU2EGvKKoAzzmy zL*KVl3#_t4)5rN|*c5ts$Dv)ZCYScy_%5-`_Yde;PWdfU>L{^kn`fp!>(e2^+t^m6 zXCyoObEtv}x}Gw}b%iF2#Ti)puNp!!L&fjtx zhu-U+6r<_Zi75@)h?E`H3DV~zW=Z>Ie?M-TaUP$ndSFj7ZPgRcNp}pe?(Kaude6f= zUSYcd-))32W%%pf_NtS!FeNQ21=!W1c~T3ZO?4@U9TaK%-R3xz1C|hW;QRhpiiOqL zS-*c+XsqC<=3vx)f_{Cv7$7b|eqN7T)<8*6C@vU1@p#N;s&H z01jk`&w6Pti&T`&Dj+7*52pd|NPkVNcAFW6;bW2x+-s$QZa2vmkUatCH@IQ>thlZn zIDkYKZ#=Pol7Fn*$;~6cHoV`FREDS|2&akC8EZTtb@tW^F8IxK`6W8zxRRlnDLjz{ zmS!ZU6ID^O#N?o{XXsM%!XWqks#sR(J7|5b{N>z)+)Emba`Xz}zr>h*kz=6zX8kV{ zBa!KBEOgunSFF40V|l%7lN?9L86uFvQ-)EjxaBZXzz+#U96TsCUPez|W(XsY69}Z& znEi;$|4{bUZ&7{!_qT#H5`uJhr*w>nl(a}mN+S)@G1AgqQX-{N64Ee~Gz{I{(hNB; zGv}Vy`+I%_kHr>=F3NApwPgoCsHW4PI%d9 zoFov*Z0|{8Gp$G@FDZ4mp?L1A<9W`EnBHIYabY@nyxsAHVLLdNlV!w}NRGYP zZcezLRPq;q)*n&c5i_Dti~+!a;(WPvv8?~r5N9{j-cOIY!b{A@(DMH*;ITtP%s>6(~2h;0u* zdx%~^aB`kEFrwAWC4uvg(_a=eeeIVnZ@{(vZ!A-#j&%(HJa+k|cd8<@nY_vr1$ zCN*m2xd$SD?r`SE>&1HsnSX4XVBEE%x5y+t<=3d)_c_>8Uk+5?6?$v9VtYpfgjd%2hra%^XE4w z9)uH^BZsX&FX%Os35)i>ihUhBTPUj>fA{S(xDq%P+?{yK^;eSN!iW&X+?4#T^%Vyj zpFi>^F}a);9^B32DhWzCEsWAUa?>=f1o$;^7N;D++qLnK#+pVI>0$J_#c({KV~vAW zIQjwvL)j{5d}rY#3iQfXQ7WOaSV7>bv7`(@d!nFfWtJsxF!iZwV|!BiE8o5N)qTj< zmErO3k?=cqSrJ!ult!uWB0=lo-jv<=i*i{mw%4M#{`is5*Tlvm#N5?XzpYY@2(T+3 zXAQx=C6gqOxX;jYWM{iGpKWy4_HdPIUL~^!e69d%biLc`RkDxbGA;-N&C6)K^$2=} z9ZDv)H&8niW^#-HrDR!{701#ncr3EH@QfRDB!r1wSyZXI?3E-J2^bsYQ8q)}qSSUk zG}x7Ydmhe+vl@#mhZrUB27x0%2!|N=mq#Jo5nGaeFpRJP!+c9cHTY2t#O|)idGRf5 zKKyOPyXJ?}Kn!5N=u5^1bv!&MevW##Jaz8XD0*A*1Vzr5%|RK%rgk*lh=_l`e5V~RnqCNbYHIWr|K-aab-tkAfbl?al9cptso2wIjqct{!3~L*{Yqmy zRYh*bUaIma>|`7X;dFeQmkQ$^f6#fIoX;;a>=?45I@``V+cxO^XHpzR?xt1q5lwxs z=o6m~pG)+aSa!Xk>jc-zUg3*NA7l$?Z!ET}Vvz~gt&+tRjDkrh2)6HgD|qjpuRK4~#1K(stFcO>p)a(C z5enG)=U-^U{@-MItjDrF#7g-^pocvp6{+v|RS_?#Z!9?rCo;kTo7sk+nmJ%F)t_th zZ89IVnD3WE>koUl&*Du#uwBzV8Ay&yIVZ6_pA56U%{(iVAf$Gb{gpn#t`A3LSDZ$4L(CI{ zX_v%2j*`&=6e7moqfeUF*Pzn^M2p{TLdBNIE?*!}dUICqM~5B@Hd?`dfvz*p_ihe!zfD|Eb%2O||ii z@(kTMDXJ3meDUv{iF})O?!D;V8zC*lHq+ogHy#?(R9$gt<2j!xd22R24EG?;N!{T^ z2z-s=A6@a*0rr3wYQW#Eomv1|C_=susU?g|vnY{sUqL?{DCm7B1(w5m#-QwS6!Vfs z=7|b4W4nq4kU6#51#o6ooHw=U_eU>F`F2-DX5wHfd5mqVw(%#~X)4_FuGp-WiJEyV zDRx7`R1zU{=MEZ11@1&HLz1(~ODWrD;lwJcA95&2o}{85PSd;E9AJ0bNr9?iV-v}d zlQqZDNy@?Gb?$^2Sqem0V-+DAV2o8iDA(1l^TC|9^&C!P-zeNL)RPl(HGX4&-%1Pw3OXRCl*e$LH1>@w~NV( zaI3Aqo`iZ_lFt1qVP<{uTHoUr3~W?^fheW4=#dG~?9q(=yHxlt@j)=bb>xF(2mcN$ zz7fsMsxRmt(5su(m6~#Hnf-4ybyHa43ZS(9**xcLDw87r2x0{jz36@2(J1ChLB0IqxVN0NUMNXbJzT%mMe#-t`-2m%M_FW_D7v^sQWK=&>5QvqfOU*| z95P^5xZr2t?OVfHFg4gE6!IO3=9=pn6YK>DNo=9g(ANC~t%6kP7VaW|z_aiGuR}oB zM#DQIEeoJfL6wB(ao>$xIqr2U2L}kMa(qke1hI%(q4a88i^gMVuce|FFps|7u9fEo zyNi4faXD-t1Y|5fIY5B*AVti%7YFZ!_O&MO`BO!`hhwC0keQvL zCGV*#7GXcHEO@kZhZ=l3JK+*^2(lY1&}Xv`)AWLH?&k#(?KRl5OMcK60bgBk3DTNI z!;#QA`W!?nv-W)9KOIh@6CoA*4lXxaTGsxlJE{Ew-b-z1+8ow#CEP6K38$G5Q>ZvR zt#w86_|L7m2zV14&ZQm&WD8rT)@u-BV;W(*_Ps#TYSCR(62KvMTXEk(ZLnVz7|Yb6 zc9xx`FiNdi!t-q4%xiz>t_V>|TY>SOB?|1onfEIjBk~UnaE?E8l|;Q6lY>yMKHYQ4 z25&`>7g;0z9YiCO$nf6Yw=CE@q>0=ANkJ73*D_w%Up;ZP!35A%l>gG;yd^eKhk_&? z^6f7AQb4Di?!{7~B6b$ulLMt{$uaFaM$bWJ7P8+3f1G9o+!1}IgoVXpk~eppE(TqX zF1?+(w%ec(hBEuPW3@R|?@9`#;dC|@*3Tf@(NAe6sTxTC_hD&FHVCtDvCo7f2caSf z!+8H_9;Gn`9Vl3!aro7xW?>@f6;LQVHJuv4owkFyoN?)!*Y`FZEF;bGD%f{HxMHA` zxjC~#wk3@A3S*iJf1%mK+!Y%zacdFlE%2l~vW;5k9E{y&)N)qFoP#}K_$2CYZCYLE zUPu_HzELEnlAY1&E5S%%w^+y$ZUFyFt|4(Y8+0MSc=LsvjqG!(E%DCe6IuyfpMxM9A>UDU zQynQG92r$)&Iz-zKKy4B^L$SbduU=*mfVVxP4F{hD1PRGTukeFNA!g#v3fs5$k#(P z%66}a1j3Z_$ng^xeK#d3(f{2IEW4$)XU7&%MLJdXGBptT$Y+L8d@G!4z^pPBf9t!ZvEZcmrYu67F#^qw(m{3@#tHG z!%dRLHPxcYOGEdV*S)Vq;JL5lig@>91c#KbaGsODDvI`RQ`D_s-s@@xkFWjK zJ0lp1wmwO%He=)(d~?P-rsc{ZSqbPIf2uzx>#+Nx^DdKzo^SGQ)1Tl%U@Ie;6gYjC z3inJ3dn;n0oZ3pbM$w{pYDra*VuL`PHHh95IPSmveQT5R7st;sBR|kq$a1&3IbHba z`5nrGj?umA@zng+uUiuYFXW_agPziymYEkOYoP49hA)>f-+cvl+zdh6(u+9;7xIVDd;DY^A7dFy`UA?&`%&9_Jwdali=I-eyJNWg_J zkaAFa+80Iz0lA=k*ow094kmmgPf7%2ZR+C73$=>jd?&J<^7bAF3F+7Nz%*AVo0S#> zn#)VTW%_0FuBmZG%@t>p;O?b zdPcGRJ!<27;ah93GML1pT&kD7?e2jrp3{iuTV|<}CAz=QpRmmVYR3x{3|wbqTUC56 z87d6HFV4%0&`eS2o$p<~Rqpa#;aNs=-^4mzm3>IJ#=)b1ky&pA-Bw$Dpa0IpCkR+r zsNDslSP?R{`LA?PFQg^!e-yJLb^J18F@;q*JO3$uQu2JS*CQ7~^h=6w?ELK#`Pw}( z-2s*)vTAyUT*YyxTD6)GW$-;aU=)4S$ybb*^Y~1Ai}9X+_$uVa6z7e)>qR!oOVWMRds_KK}w$;MeR^u zkC!YB2Ze2i%mdHzQ*tsmYoAdy5%mOMlUEWJT#!@cFG{}>YX0+@mu});O!TFjuq9UB zcG9rlPu@FuczOVFY#nZ{p?R>>Mm+VUv8C)sw%y|~8`R>OI4bg;Hda%hZ~@Hv+>@&0 zE$TyyTl+Ft%%ybH}PwqpGr|FRVduch~!q*z#!CFJ%-!zDQJ zNWlRQFNjrC=t8nnp1**P-)TZmm}q&up~9`YjrH;dzd=|SE(&XPF26LJn z*$x#Gn5n@)zkNJX)l4e;@wHF4UQ%k=B*(v$Gf{02nb*^c#dGky7EM-wZ`L2eog2x5WGbF|QxMvmE6E?|U>XmcjCv?X8xE;a9y6eXd6q zFAgR*;6s?(D5=29=FImjlfRQq7rxdlM$8D*ENRZ6F zC{E?q7f;ac8<}d%i*@>GOs7uZ%VsadEw6oyo6EpF|M9$GC)5MT>+m;K=TC7kQWfY2 z5$k`_R%f7sP9^Hae1{s-4bfPjSI~Dae>q1?OBO`8b4^gCTx4Tz8!vf$jLrYcEK8P* z@cjXP&%rOK%~vE`+JLts{nX4<(UWVDCc^z#`J^6op94`?Gi{YR24sswuMTp6hb5I4KIiR{dNFobH-M}O= zAtzVA$KkhFLLbMl{VYo-b4Iy`h3rx9(}Gu9U#Zw$x{aHVACn;yq?0QwuT+s)Pr9o9 zI}S{nkf#l(BLC&kKK##~%ewWZp!B5hojsoHwQAv(`$={pt`W3)FGX%kn?cZuKl`3B zpk^PND$1?%nuuRWdtdqw_LQb01cpz??uR6Jsz{wJO?K&!;x9~jkMLT>WsC8NxkKC5 z=`S5C#liu0N(-Brr)0iRZKilbwuciOYpIDc0bZ?AL@%83;mzFW_G@ijEqcsxg=o4R z=5~Fys^5)WsC80gH|kCJvm63rco!xy$&&0Clu9&Xjb*Vj50j_S{@6`A2Q6WEvo zzNp7JLj3A;(!T~Ckw^M;9& z&ONB{+@9Je;)2~VV)~i&yKXHZi(40L`R`}Lo1?i8GFPMgy@5{Sv6aYKRsD79<-syG z9?LHL#lHE_I%`v<>c{Sg*zU@M%$1k9uQsm!=dBeSaE#6?3nBMELL*xlE0t>30_8Z zQlmVs3y-yjaYf8Ykrt|CtHp~McD5t!NN(BRJYl%sbzWez7yFw=cJp+=NaT5&(%!nu z@r{*7Rq+u%FDCa9O&E{H_>5z_QIu47!0ne}t(@7zo)l62NAtu6ad&}o%Uc<^@XzbM zlE-9Fpw0&Laka&S|Lv8;gpHOL{-U)g^YVS3aPP;)IQ_3>rYFlNyZT>;+Y5&YCjYYe z>7gq}h$@5DOzsOuK7Si#O51G=Fx^e$d0#_i1%fIZyYeboZ|QT!t^{#qB``{D92)aR z941+jQ1~SPR`ZR)biw}pWN}fb{hPmuG0){Sf-ND|Zy_n}duMq!Ip2 zxmlrBVh(jtW`JmvKX#%)i-%$J36z*qJ0yYR{e~5cI~#!Sr%G?l{{SeajW?&q@yoQ z(QKA=g{O;+YXL_)xoSqqmeEY{D4S0kf??mHojwNeW25Nb#78})jb$3N)>}gZ$R`$D z7Xo`zML$#y`q;KCGn}mnD8=t{n8L~?rV&HdrX`X@u2d4&No2kMO^NB>lL)U*1m4ef#No{pDlVdr?2)I)tqGte<^?K*n3f z%a_~BH)w=S=93XO;vH>iH0DunH+Do_h(nS_rEtY}9r=dbu*~BEN#zIA7*gR{M}pJxg2Up4jFP|~bpozeThbqr)& zYg0=*U)u~^sv%x$vl~;CfuZA%J0IJIK%48Q6TQdC=e_mwA$q6+H4_FY{zRfqGGP= z3_PukZU^@jS;2$bb6*^M$VM(Z^ED^vhP#|^zEZ@bim9vG`kmxw$={1jxY|cj9x2%= zCYzcTBpLFrYN*|HtY0EDjvRpvdssj1S-@4|)x_cfLl(@@bm+(}Q%bFJt=vq)zUIY3 z6=Ha6stV%i&RKpiklkObJEljQRB?<%T>gqsSt2^mbGn|d;|0*<8jC~ddYlS_{}bgQ zh`NXbm%FbV`n@}FHLV@ZBlwZ+a88K^@NdloGx^Yc4Rt^@2^4aMG$Jsz6(4tni=3yw z!gG(^u=ZHog4x0@iyrAnAqeny9%CKjKZ+Xw>8lphO{}IAIRnv$jE6g{-Jk!o@DTBL zd}|?i6gP+Be_zsHOKwgnM*f@k5g!epw3{`+YiaoC4#)-VzHk-a8KV73w=cmX5Q&bS1r-LW|s}9;?k+uKdwc7zD>K0tsKv=90+SYDLSI(!1 zsj>MKbtSJ-+;4Cm(K9Camd$i6@)P)`%41fvQh^a0yV^|NTV;o0VgS~wIO$H z9n&s3_se_QQXOp50*-39<}3H>?#Sy<;QC9_p0WRDuJ9f1_8dGAncbX1Z1i+tbc8RS%!R>8fQjFXo(WU+++rm(8etQ~E+Aw82U5yh5p(`RR%?i5Y$Lnu*hjt&~G?rMh;vE>+G?uX5;0!tD=RtcpG{_VyVq(l(~rw!$F zwX|JNq9w%HL1H28JNvhZv`3AR_9AIu$DNNe37~b+ZKxZLcHHEP%F=k`D;v485nt^7 z4howpeB?kw`{Rm?LMQ!n@E|Ck(U5I=V$Wpb)3XrB531c;_g0Izd%WGUfhCv5wKr=L z)fIiA%B?tCR|GepT}~REOM06P=^^*?5?_PNxLns3l zOHqkRk{=Yq)NVy}Oh!&l6zExYY0N-t}Cb zh}K)+>w`a4&S&0dyb}0IOqmB(;9|6mSZAsib}vA^I@?zQhGB(^QC{4o<3~lwPbHIt z7Q5P^o^(&CVc4IvIB1Va_7+OibF$z>PG5)HBTT-G00+I_ zAA4n2SWIw9=t+D$(T4LfhB4n@Xt9@= zcHJ|^-|{|z7DCfk9e!xb%kHwt2)s&syFvbeS(yF<1NT-9iDrfqwlMp9j64=Tw#*^u z|J#vrPd@vvO|3?VJozKE&VZvk688P@Vn&xJSA5!(!12gx=zpV>FW|vxu_2!C=z9c) z57uX;eFzrC>+i}X5Qz=0b;~|#0^-ni5~nVp}-i~0f2PKkR!p=f3$JK z$R35~`=+TIZ!<^{N($4DD#NH;Uvp^G2#b(?N#^M8eZoN2bSiy>F=+I>FbnS04cqO4 z4fZ@g7mPB(RUhIwZJ4Vv13HoT$wrJnA+M*Td;BKpgJ*QV;-Z8`y>8dQh2d;bbowh_ zovJs{Ovlr2d@1&GwblcPM6aAT6i`C(pMbU_t*m!S$j3&mExU9a0grLgETW5_l&ZNM zeae+NKJR_CgnBsHx5PdCHt244diLxO_@#%?w@*p(_t|JhWox(ytLDqm!}XR+xzkLo z{0I=mof#UljA6d5oUjssM@H|1_dO3FaOY~FON75%W;^|xW$r1tRP`C;(=SDrk|3*Z zI`2x{%#n~Afryu#_*2n#5k)&`cUg+6sBEYUXF6g!_@-XbjLvAB`2gcR0l|t>TxV%2 zq7WooE8jvfSASJhAIj57z2!+ugnZ_3X@SZ=NFPUdRa7;8rMmtt zE&o@4w9v2tSsOR1F!YG#`DwOwlE?W(>N90Re0m&PcPg-$fywO2+V7%p1^2G-uHB_Z zIcRs6nkC=1GA(LZ!O{z)jilz+o7JyrjBSG)VODnwv_%CK2Ek&&lbO%@O0&%Ov>ZL& zsE)jT6A$K!plfd%Y~Hk;)pwHQJ8fInHB1yej_|ffe0X~Yx;bEV&BA^fK}n87v}O~5 z<@2SL0=?bBWVecE-KS5dA{zGfySpx42>Q-y!ilXHKLA;0x{fblZ6?aUW?lGje zFVRQSzxiMk{B%^@C4y6Q`GHu`D!MowqkMMK-WfziPC$qaIsIqev4Rd0IYB>EL{n&lRyDKeNl%XnBk0L53B>O`p%!`++spPC+tG%}=?mZ}+f?8NP7LtuxYj z?G*TJ;Wc3|`Sg7ueV_3I^~92Su$x3Lw(s^+X@;RP{W)Vp70O7`i(cjvdDl0E@C*Ls z*N#f_jOB=fafjeCT44lo^wu7|tMv^crdCbTcWzcu^xZ%4Z55k;ueaf|NQ``hsrMh( zukC^H;Mtu?>uPPyKW&Q|8N}yYoF8$!5=@MvRE)qjmTw6M z(39%8AP6y}Gk{h`Piywd^qzs%A+S1638HnQOyA=LK{I_sf$+I6hKd?j7gK+{`i78E&*$}CLbHnGcvpYeC};VODl6)^W~ zL1;4KsIpD#>)?XL6|y^uY#w3(i5zBJ?6E5hkXs$`c1V)K2m!t}Id5(}eM=$L);*Mx{Y$38#N|U`8nd{jp($-EDE33@7{=n z062`FaQ7TRc6%TWz_npgxtgc{FB%lL!jTR75dMB}WYBp~M`$8~4vT@xq~f#6)4`Pm zLh5r4%eDIT&Ig6EK3U8Ue=`hI{RMUf=K|6aB)lbWCdMM$-HGGt1Y6$2_jKGr4uwbfedj(EWwbFgkAi)$&Pu3WEP*0Td?s z@V>g4>(moBg*HQL?9ZQXx7SPWG^?!#(Vq*TkN(s1nUeCl;CL`TaSD8hx?sm^TNU=K zmbX3;B4gc`gf?7>Ui9d7=AmjLyiRPxE!Lk!>$?X8`e5eA2id}(;*>dUF5bGk1^3s8 zuC(m`$q;)?UHJ`u2Cm3UDCUa9nYWfy5tqs>EdCE}D|bKG>nb-`PFoEL4Y$%e@T_`N z-l=Lf6y{~?eD$ownEL3C;=>IQzI@ZodnYuQf{|jW-+hfrq_6vq{L+7r1$Xv>9&P>l zBUHwD|K9L#w#YxDyxG(G)UUf`~uWnzASRU+9Fg#oT+ z6#E;1GcqJbM5XW<=UFfSmfjQfoe0Ij7a~T zn(;|?TSw8Rzaz`5)5fZ%s=%8Tdojp9^iR6i@_R=0l-EREd;SvF_Jb_nx^E%sSvcqU zi|pqiyBUVe;SDM1XxISVxnFl1LvN0Q2LlFl%#{yfy?+`J`9D-OO@i#P7)GoU60MJ% zD(!zK8374Qdh*K;QcXm2>|0%}4US$EHs1xGXix`FCrEe*y>?$H`O;W&H zY~bsYc@C;2t4eqJc!U(A%gm3IN~w((JUEdZCRj(V#mXU1{G0G&YhVzYQH!atJw1_a zP(DEZeV6%sXLo?nq`pVYwJvK$EQu4U9t!$bW^?^8l4@iLr^2X% z&zu=2r|3PxfbQ9N5_p^WmRuNfuE7dHFo|0&KGIvk1(pv`lqEGhb+|Lu4L1olj7s1ZSzA1>^5^ z+vhL#cfWl1J~(pM@RM!wNk}%V_`&;L@O8?%n`Df8MP*&AY<*Fu5}ez~Qq=5D>xc6> zzYXT>HTfX+pk|Km-8tzgdTT_QV~B@cmvhe;l*1Hd-;{NZbRoR0~f=elS1GW4sMUaS&)6Q{DgwzD~Veqg0zT87(0X(^oEjWFxJO?qA2-?l;uX4|bT|k7rm2)4*aND071kn#Y4c0d{DOyW zk~B2eqk)!UC}(0P$i^(o0At)G-qAg<5J>9)t^1{Q-1(mOjiEQDreOk!ilVm!OxW(5 ziJ_?$2kUC3O=SG5VxsY{8Db-+1?-YMi66R%$@2-7v6zj+`XiDGo?sPM;x*uMeQGkk zz$ByB*m}ABXqAgaLw_>C?Cg2S>4IOO3t__U+u5LwaM`YT}ldTkZbaeJ2Mb=HZN z`ayxUKmq?R5X3~K+dgvU$l~ngB;RFOpt2OPjE;d0zHl*kW+Z>@3wc=e96groJhbTi zHUF5|a&Nu{cmS`DD8T)k2n*Z$mP4Vz)g6=f-ms{0L4MT4F0*`YLK*#;TNdcLo?@;%GCkZ_%e^L9kF!;CHpde4|dYw)kJK`9V za#2&YmTZ^j1XCZPv`2g578B8#2SnK}q4h|}4!dBAOQ+B6ADFni#rvNuG=~BT&~)g} z??B*WTqplxab5a2(tQ{>3pxjuG8mg1f=={oAO5T&kD&*-!_bVTNe{#%(5JMHkp(*u zRi2y{j_oQ}IUk}pGb}-Eo}7SDQ(%F5K2XDhV8{-{rPIlGx4(rG6>1m+S#tB6tEaeS zeBItMy1i3x=ubo;(c*t(JEGZn>hb^`1zy>aDFJS^za_G&I^~V!ckg|7L=VGd6*;+)Z7)!qZfPQse}Iy1-k;&d#R`?Vl`-19uGQmNEFcX2d_Xp7(>voq^ahD{O;h#@wfe zg|&N?(%Y_WDBKfp#yZPy=-uUs>gbo)ixoHxaN^u#Yzh}6-s4BMC$ihdQwY_vb zDBfBX0oU8SkJ_4BkG%lO%M_UKw$!+jy(mi6KLRFP+@BzFbZ0p19TPHc5>xKoNIsf) zM_9Ygx^EyL3H>k^FuIbc&038Xz$Y1t{qD$CBc2BxDSZ5?^au$P99h7d#}mnof_Ak& z1CRQ6U200;WzAEFT$Utyn6E(32GaoykNha%w9HV?o%`kLX>*?XhavB;L8qy^BbtKC zyE^in=bx!vvl%=TZ#+`6;&*7aj}pQ?k`bWoe_*HEQo-P#rksUWP=Q0v=Q;01HjneN zl|=cA5Dx1$KniNiEnr%}ZYc#v#vAaq*rCCx4@WH3bbu&67!3mjXK?#g(1GtjLp`q!ZGlU*L9TNle;(E>{A(6>?`y#FBvOB7Sa#T@kSlGjS#;o?OUCWn zc<@ycg*{yt75+T9+0`P~gLDzJdtZKVy)GH`>fasm@irY&lWB%^lq3Aezbc&fLgn5f zRr=0((H=SWo|uI{d9aiBnv9mX*8^2@xdBQm*jNqOJpjsk44KF_a*9+-5Bty)AO5!T9>@q z>RlW77BqYGVf2Tzz*+G6!%}TNv}-sRF!V(Th9JPE)yM}C!9w}bu3y$-+<@HKKZ|GI z0Ros9egkk+l60R_2&evWxCOxv#p6v@3#*pD zw;)?4{C;(b)hlOE{{qL2=pBEghqW|)__tMpGvXz_0oI>@!L?0ps8}B(JP4K~&mD|v z8gg#3D8AUg+oy*5^`BPkh*nE#ds2@KP+h24To<<{$fD*MI$Uq1p#F*Duh}FVbKaGd zqUK?EmM9c6@$)AjuJT>q3gY{0-K3af+I}dAw?1R(%;2t%uODh5QKA&^fIjPEBpLq` zpmElbB`VugMLC&VK5%StP%(+)4qQBh$=(&!2O{-z*<=3QyYUo(KBoZ%UQaUby{59< z0bwtf_pctp&0Kem+|++y!d}L>N!(i_u-ODP2hYY%?o@9C?;9x{AJTHyxlQycgKVZI z@=!=?VOLlmGiCtD7C&Xi| zAUMCe_Iwr>g&Hi9IuvO6Wob@&>w`fBSpGvo})_{bzx54c76A;u>kgaHj zKp$A8v-w)l#rc~>w!=eIAPW_3&|NR%WYuQoCPCJMuW9jS$QKy}rlHEVX4GTKd9fP* zF{c@j4h@;37xtY9=9HCzu73-k?a6KTd9DO3Ya3`N-;!Sdtpu+J?#eGXJC??FjXnT6 zow8wq_~$6mkP3hk_BS&rBz@kgp3ug?fck8hFt-upgAhKQzo?E!Lf(XUb=_@y*95w} zalTC}biRF7f@oxq!Bk=}O?T366O0vcNB+EZ-RWep3q%U;O7_UN-MqFMy6VQ+S=+d6 zZ&;;mIMVKrxa0S9I}bjIV+c$a6eLnd`4o0qG_iP@%r%;HxHkfYcQK4vLDjPtAUjUY zpSN5~1@Kzo&gPJY)TL{ZWVs` z5Q1IMV@bS8%(E+t$`N!Uv?6d{u$ z8gYsjuMALD?7GV8{8nOxJQgf}X!7M``KeQ@IoyaykI4NDIs*O1tAa*9#)9LQ&r$_Z z)%-^$KCZig{=C;`)ospvPTR^Y1I-OWpDJh<=~(8t&np9N&l_w4Io#l}M*Kx5pn>@2 z{pV-G)n$sZ8#|z@#i_S(4i5dzMh}ef`+k6%xZRGq`}(}^cs9WU^n#_otZD7OYSe?n zupax8ZumCL;1Gn=muIbIqTEUnX6^qN;O4Q5LeCONmCKNZMMaLyza;gzIx&|a+6=$i za?nMRuMv?(-H@F|kc}n5)X8u$Y6l}WvS)z=Hu4}v3G=88#0BeK47aDXg3gejdp5C^l=p-k6 zmZN#&lOQ|XCE-BS%AKD{sDSrh2Q&%kY;7-aR@1ZDmE@@f-J;DwayK4^+z-*_@Nkjk z;pH+;*-gCZGt@eSmN)l4XRgi_{S|Y8P^p8m*YLvTGqUNl&ewKU@VDa;3Ns15E*m~m zh`6|tNDPYU-2FnW?5VOjli9#-6U8z~WNTS2dLOcw6`V5~8}x^g#6ikL`o;XWCkyyH zW!0I5qT@fa>DfD^rZ-$jyr0$+S>u`K@E=^lGK;UMU&QtW1}}@qP}uRF#E~)}5c}md z$gedi)H$fP_WV801Fb^HA8Zd88CYp5jx)c-aaObC)aBWw}7Mq2fQUx_?qP{)3D=&l}UoAp| z-j9Htoe0c528*xa@kSLS*gFV||8>(cwM<4(H*Q}ijf)ouID7Jxm6qIgYOjD+Z-*Xi zeEW*)4H`6FXE4^56{{qrewE0e5iN0c?(7&ks>yZjG;W+P-t!ls6^+oqV3W%Is?5qh zBrv8RvAf~=@f=&#Ra~qJZ?rRZap3n3wRe11L;C2Y=OWO~m3^d;yzS?IKX7s81r4{Fk0Vj5aNwxL zkeE@P3-;q~!VECn5G-tVksY2{$KJ&kkxkmr@oAZOi28=nLaeKjYW*&uNdp8=t6^Q< z{q3*0YYnd zDad}lUwn%y3R2tby0R5X>@yTyklv$})-24TesvLvZxR51&)w5Mr2bo4@4Kw?-hBEe zy+)0w<{ZlTAa#iS&i}{WdqzdoZ0({d3i^Ts138EwpnznN*a}Jxl5>!pb4F;9oF#)~ z$vNlH$043H9W9a8bUq_o?}wp8eA zc*SJ5N-(Rr+)oKyuwVA|qA79*1zzT>5nbUlgBmT>s{qe$C#Z@v1p}YM1qWJ7mgn2mO|X zh&HQhbV`{Q7UfH7k0E-)9X;5=H>KFvh!0D~|@(I{R|$os=< z2ge1li-K6oXY>r$Kb_ID>rb%Ny>O}5T+p@fsJ@h?tjMTrbAOSIW&LqgB&un&M#WQbwcka!9(m7ZBAq+Vm0L0dDtr<^n8n`xp5O;&aoqy3Qd zW{AOUiI1yB3Zo{Ow9{Fjhy4JSU`(2S%8_o}gBApCv11fymT)M4iGDLk@5&eVpPjk) zY*+Bo8O-oKf86K`aMc)$Zy|r7J$JYb?I+B+aw6C4WxPcwpM3vk6a902k(hwx^dT^L z{Wd(>xw~Bs@*;a@7Su1TwU?@r;;FOZBz3_hWYh3BOh!?r@bDfYK7$O07s<`GQjbv; z-vJE16X?8YNeFQ0l>Gfn0X9Ruwn$paQk^{KBymbF{O$%V_rLQIpNk^!1v$Fs68qgKD$a^HYd*OG7mxJn_*{U37^K1Jd)W?t>8{DWs9EVsD zqx*G132AHoN2n$$lyH-5{^?vZaYeJFFOBS~Y~xHr`}a>bCplUDR{Bc=dy`Ba zoG)&yrDV@twoLwEyFWNWLOt|i9y-@hWmF6(vyhmQG);Gug}=E+K*mE&|RCC)=H^%JUyQTL2QJ->!DoLpY2%o-3>k6+D2@O7Q1F>xI^ zgC9<0bM}E|s?w7F{(%0#r(|CI67~NaZ2Ub|_!n>b6w6t`oBNerMV=|AeB{muX!*E% z*_faa{Y9C{=cMmydtE$yie8XHe-B5C9G$VBOe(cK!z1-#_e{X^o1l%|=|m9Z4Y=B5Q>(n{xm7k!e&{*VNurkxunU z^s;-mp5{hx{D&41HTnU8jI8aj+YJ8f8D`Or%X1v+^?Lyy*$H3jW)$Afz)Jnmo^vZU z3_|IH2HArY&-tI`t5GJ_fN#y@L3k_KvWz3-poUXFTg&;)tDZK(Ou30b`$3bx7jxlEF~h~y*%!8^Z05tC>caw^>zwY8CH!LjmK zCE4wOk9JI)KmIaWVOO6Iuf`b8K6Kgtkg!YXG?|VWoI*FF7Y!y=mg8UrC3SA~O9|Yo z3WmMY5BewV&O?xD(eahCZf=4s^843rWq~3Pv=+KbS)ng}Z0#EJc34{C0~N%- z&`YrE5Bdupng%0+cKc1E=Br(SVbIlv?p!GO_eHv0{@~#eN70+nc^!qsf5Qu7b5XwK zHNVtk>I;F5gH$W7KjPog#|`IOLPUx3sMHnnU{?Tgh%lG4PSDOyY+wR?A`qB zPc#E4x^cnWu5r*wIZdMIiT^aAxv(eYg8GJOk>!=^ReDxQogcIbrK&X!A z-1kMZRbUrfvA(=LQ_1s8`X&^7PNQJCSR1m0hmKuPap&jP4e1Am%2wcx{Z8++b*Hz{ zsdR5VJ#7+{SZGfmiE~hX#87n@EZhf6)qU^iuz!REobLpO*MFIBO@=tSzjV%I@h=yr zE-tmv9;3$Lz~yFxVLzje(!1V2mGs}-{*O8Tr;8@{CW{WAgl)oxwN&O-h4K?B+6v-Sg{f{2DcXDnIBfjz`v8{-JhjjjI3t;*JdD)E)w9 zI*cia#~EB+tOuZ^@>UEh3Y?Z>BY>-oMPSrvNOMI35+UPRZY-BU$Xg zBe%<#aCwY(8-s3*8=}2(5MrYsZv?t)Qr#eH(a0>(8wn<)1kFR3fp6Kbk;v}8=%zJz z_KltM`JHt!bJ>iRs+RP-_atLrrbq~iJ~gHJAhFr@V%-{TbbcL`HA3xcM8AZpONAC_ zzCoAzoy9?b71sBGSUuR${x16jko~ldBH@r@*YIGsJReX!x^0R6_ zFk1;!oUL(XnEUrtz52R45(v1@U#4vGA=ZDy_P4m@^tW8Zyoa){&T9o-T65E82~=*U z8uu-h*KqEU7|vUp?LD+P6>ttzvon$Ix3Y=69+<^5_!VdXt6BM2Z`z_9N565K;@Wo3 zv2>nsJa}f9bLK?q(4U=QEn1BVza&3cs|1=^>b)DluRMHzp58rCyWjG2-s^SxNNjBb zJICN|Xy5~E#QsOsC!2{5k8a@-uD>;%u-(-L#U};DC+zhXCuFaPEn43;KYeCXbe~`4 zthB!miZIt^u3(s-O+_dMg(f1IwIum9+ygh>HCsil?zoyh9b+(lOCS5>Mezq-4Gz8l zHAtsza~Jd=OLUgB5B0GFo5R%XN!vgrzCNb%6mH*+ceS(Fc#`ojz@swyX!pax4+a}% zd{gfZ`L*q`+%tD2U4))=nVV4PNa4y%(;u4HoHLKg6j22i^p5E>socJ1&9|zB?8V7p*EVoiK@g$ndg9@L z9u?G0>pjLdzHHJ{t0dUi*F!@fMXTskB5&R*hwsO8E07dnAd&1g$vIy|ktPwOFJPLne)c18q zP0wf~(W+j&S@+DCJ!3X;ExjO7T{y|!9orWVyIR&J6vqF6-+;$$jDgFgBF6n;Eujl2 zCl7D{1Vex}htUe_iD?z+1z48DZO=Z{{O#t&5{r&`BVl{F(1E9)%h?I6H_k;T^8hB= zd`Jw1)`;5~=yUHt4~fV2?xge`z%Gm3SKSIA0D>IaqKwho()C9&s~V9xQlr!4l1-YJ zqgj$t_boCNirqYO@Bw0Y-u#17K0~TuHwYAE9bJa>&j9%1R!Z>Vt1qD^$W#kn_ULWs zm_`_I(HHc7@|C%R`@1UBFY`$&XQOmI1oM6fNZfoMY-)R(nbJ4H!3aJFJU;$nj+0k&9jjOSfejvayNg+%np zf@ik!dc%I5sG#YIV4hIJp-4AJj?P6ElsWa<5%X$ny(UlFvgntG))YWK;1VjlC0Yew zFQ5wm4~Hb^{85TdLh}(HO!9IWJjfr|BpE!@_>?uSWrW%nI9vV7a(J@zZIICN=xERz zPmmQ{69hSzF1FPMFY-6H3aD7lnOPW(Us9hQ+RB7Z>TnBOX7|+t@RoZRQpfv8WUu3N zQ0)-|*yg_C{4Qn~V$;sl`@K~Ui=prN?%w%gVjV$cds>g~!)r5p+|z2N&Z2YZ+L!pn zaqrf?ojDK!`~Df3yR*cKj+lBp@xlC9ej2!+%9p(Y^Y+KB+RHqBYWKjFfhZiX05r5P zTuUzKeFJs$eD&Um&Ysze3erEn9-SC*M53x<7H@!G^H5_ZPVx!5kGuTB^V&E%93>ml zE8+0GVjFMlxX}jo6w7)SF!Vr;y8H5?gPYnjO3_f{3RP4>fgn3--5QAPC%4;h*c!{* z)X+Y|%Lew~P@%!-8DTNU>Fo=a)5qCGW309l=QTC$9hZ)*>)t}{m=Y=Xxf89F z_NT?LXMa|=jW~tWEIem<=C^HK1eZ^C%CaxD%^WW}UNoI~JG(z?)u2?k$ez6F^}+98 zgW`}!OpA6pBM)eu z?SQ*}SSHI0Rx?8*QSU90^m$A;x#WV&t<8?o54F7P)te7%i?rQ0%iO)5pPcv$xNx3A zssKl%8UQ&dlkJXs3E@W(7HjN(ICU^Hc6VFCh8bQQPyuX}_xA599z47hkZ@)Q*abXb zC+4HhA1)!uDQ6w@()%uOzHE9yaX~q}SUN2kDtis1Aqf%%Md1Dl3+xcVk>s--!3zKg zozxUCAB0Gj>a+O~QR8ClrX%EBoo9oI3g*HYM^Y)@^}rFy(zQ||Duz2rqXY~nHp4Qf z+!_{4>56hbWdE$e!136;RVV6}3V&4-5xA z9e)-EL9B`QSU+i7el4JRASks$^|X|kDK63}%6%6|xJdO3CvY7+9iqfHs*6^BKDi+; zc$B93^!1!E5uop~Dd(hatQ)gZ?f}T1%2x!tKHrCIrw)Mi6lESLGVvc8W;O?|m*SM^ zD~I5yt=+gbc}@M`X7|aaLiH?o@Q}&mCVX!-CM%BirV4ps=9Uq=T(OmV)WDY%0egw3F7WfD4RhHKCvx^7RzhQ1M33FmWQk8? z>|$0bC1k}uk@42r5Yv`N%W^~u}1 zPn5W$dQjO8n0KtYAAxOu?s?sQx5s(eFLURJ`Os+fXcZWq1LoWc=049wzRtpVV0Rf+ zz#JHXY|TndyZydjMZK*K{Ek}3#LA#K7gd3no{J;hq+bk8m#8q3EdY+5WrVsSk1BJZ zoyUi99{c!EYMNJ!lHry3nzp5p`H4LS4H>`sZV|l0)3bOe!K@She&Ms{l&g(~T>+6R zpbvOc6-A_b8r?(4a!Hc2amyO(K0IBbarqddys}?K7j-GUX)0zTjM=jr(blG_Zp`O&0ox{)o`^WjQ?i z`@~|CCV*C?)3J!ag9qyqN|iXNkkj&Z1*?Wp3T!!nIIM*%Vq!Fs^c>fFC_ZoBW+7u~ zmUO1%rb(p-R6oQ;MHcpIXhihXD)6TME1tR^xoM&_q7N<>tYYs5db<^b5II`pIj>E? zQ_asq*0x_!Q^mZSA!ipjO&m#}t)=z`jo~#Ni^-L`%3F`xx>7;g2Mz{DQ%)*34OyUd zyX@rsg&3-*n(;ns@@|j+K4EX$F$x)0dKpWii};}{5N5GMift-=LtKkE=2GiEjKVY2 zMnL0nH!7QUUn*V7eJcoK(CF^xE5nlgzXoO`?|+giCvx#WTIRn)_E!TKwa}jrOXBCz zCpG4P{|OYOP#h;7I?pC>QWpLV)V}EoO^KWrZL+YXyQAhhr}dj)#(bjZCK1%ujh}Ko z(s#2WvT#csMEQS9;75LOeRYI*tk4*#T*MK$VLpDVbNtp3`Q-V_xUJ z$2b31h8h4KJJs`P0fnI?`nXbqc29fifcvN0TqDC7qNWm&o8v!%ygSz72}H(7=JaVn zGjkLA`z-ylSzYIE39_Z(Y&;HN5eUPMD%F(Oi1-iK(%O-8JpT?Xqu_jdCM=AP5kkr} zHSQ)HH8v{OsYZrvk74zbYVT(A-(D2WGoCMwT`=SdBVdL$F6dv@hb8_XV#@ zmAp_Pf3x+N?#dmg-M$#djR50I0_+Ri%=Wfp#bvNGdEJ)ovx;qu!Y}U<*ok9C44Jj_ zQoe9d2DHp_$s^D2Go(v#jgm(s@QvqkU{#Lk@ zY#sXP=)(C-Npec)AdkeuIU8s9{fFZeVVINB7IV@e3b*z(RK9o5YR%IF9* zj?ClH}-jcFEOuoAAN>Og%Ny%)6eZ;FhSQNyG%8Lj7nOl|^6y;emI5Bje~j9N@0-VkzG}?_VNJ$j(w3rX->b8-*UrDTYS}Mjr1PCBZWo5nlCbpu#MtmOctOk&c@K(l>k(FQ? zs9+bA^wAhma5O^tJs?-Gxc2Gb@ek3}U-|ZyBKAxF(THT9|oaeFX726Rzi*5&Wu;QjOz8~n4Er2C{X&aXKTpf*Nm zeq~_|^PAXm*kf&ImbFpKhFy+Kr~7j!3txQ%7a3D7DmUF>&W$7_c)g|4WYL53BK9%k zbrY}^dKnX~5iHe+r-TCNIpwI*&OctnmRL#8DcflyE}UaescK}a#qDrcvfx>7C6(Z+ zXx@gL>+njWhTF?fHXUfc{)~Q}nDT}?U)TYi2jqbT{urQj2kTr939U9Xva}&beDCv{hcF0nwW8+B#RAIbjAVFxp@$>F@n}P z`v&N`?W|DoHSJZEjMl%X{_0S;eP(`BUMe3g>F9ZOvCyzesf|RTzzDuRw-~Y)n-J^@ z+?T7}3^{#ObdvV?Y2oyV_*N3Te?{v$Klq4W0(1t*jZj!el)QbGML@NL(jf)( zMknK%y@L$a$~43bEJ!$(DOdOwo=_(&Ks{zg;qD>WBz2}0hnKHS;YAd_(x*B)Zqb&! z4)3(x-e?gN!WU}p`=P>t5sboI_FT^TN>sKqw(xb`06fdH%0>(9ymnhfCU@FdZgJx= zg0`i0*_Meq4~k=5$!z983~55H3B#(l@WPJ*$zBvLxD<-#_q>QhgCN_mZsPcN88~~J zI6E!&KVG@Y6`ZLci-4jFm0j6-|8WJ29WEhf4sWlGq1KFMpcSX^vJPGLb2+Ws_Z}`T znl{NTH0z;q|7~jxm!d2)Y(C5GTcdlamgg#c(%WQKjp=Ji;qN(~2V6CMF4sUj0CAoV zBoo$P$6&;a#ctr7-QvRCdB0E28^7kjwgW`~ySZ!aoaC#Zlw_cknJeL-KcKdMfp$Ib z(=N6a^OL%@&R@=A28!c#FT<&Mi;7BDz~RT|>MYfvY?SN*BWG{LHXvgO$z0nGy|o~R zWm|z0T(AYuC;+zC22@a^-ln386Git=+xK)06wj4_0+givFkxh(xV3zRGDmGBDZA|t z-B^VxfEO4$cWy#WTW}deQSIhMQ$r@g&o4;;gpr5S+RA7o_uNk=aqwG=^E(s<91P3# zV_~pw*%eRlN(PKa?(k78u2lhU_$n&zbtrginZkgr;&AtkhFx8QodWcN6IpZEV`yY@ zGrrrk^WG2}(?;T6yB~{5y{Aq^b%jMjYPb|G=kx}c%E$M@BN8Jf&}&(04w&sI2;C`tN7?C5qB`wpdQsVX`B_u^4!=KcG)a|Y86erfr_eUfo*#9C~a}RKs@YC%gx05OPo$xxp45i*N3aOZo7iro`#^ zRqE!&MnogpZEmGF#VXo8#LegMeGpdFe!p&V0rh=QGRi9H8KAM>`RUn$)1_su;o)E~(`d7bkxnO5VcZCs3gQWVxPVHx6P;ADK~?Q6 zvw8G@l->`!NNG7+wl`=lQu|)3P8cC!r89crrHx&@8D;a zD)ovG8SVLFQdN&#_&#y;C!6P!I!?loc%|wm%H>)%>BxGt5dJEJi8L--l$@cbfjb8z zF^w6w^6zIn)uVsO3id#6?oqI^kdc*JK$&Y2GXUVAlITFK}97TMoB) zo^9nDQ%Mu>wR*XpuD^60Tp7et#iMMar_K^j@<->yh0r-Up{TT7-lRHbehVo(ZBB-v z!a?FTs%K6K3cX+O-fF}md^<-Y{tH=U zB-|vg8NU(4S~Rj7#J;=eEPPnrgW6^Ifo(YLuZAwWJAmfPy~Ll;>Pg6y`u9}P#S2Lt zm&Ww(Ar|jv`KpPa$jf1xp-?sL>bE-ALK2s1 z`1jA_R`>DX;S_PUGkc(`_)sP+gcL)geMwZ=w6(rSmr{eG*~%RJVUDaRtvE@{GjYUdAzfASX5DCwV%>It0!Yg zZ`?;!%i&t)e^Rz@XV5o$jOfFLy|MTuPyJ@Ni|H=F=CN58PEv+&@juc`g_>}bE{jA9 zXnF~MzX0ubsTD4K$;3NqO5%rYs$y|sV=i@_Nt1dfX-*j|oEZ^IbhCgwtFD~zN85h5 z$0KXCq@9+XX6*`iM?w_WpxCPzodfuwOuFAo2Yg2G>l#jD-ZW=+GliXsN;bEbB4pm$Er zVd(m$E;9PL=p+{Yk?5{&btxq{gc2GWg4OpLCw`HO&*WH6eWWlUH02p=0E)M9j%O|U zHD<++c8lIUUmJKq2JF@Vd|52~VcawYK;DVYF0f<)m~1$r)yT?J00opR0x}NxP>!Ty zG$AD-2G?>ARTk%Xs+QU1vF)5I(A{?XAIn2XmY%UiFjB+}@c#j)aL!HLQ)OC>%CjyFN05mu<6gya{liedZo*#!aTg(8jVJ{T(uwtouJ zx7_^pZNh~|h5}#Wgpfz*F~ovzG4K!|_Ug+(Z{ie=6i`H$@TW{(c}b_tng}l%cp7>N z7LPcXLbnUnXVtD+N!(!eo?({ut{kmwA9UBX$vY3iZy0Kev_CkK#PUjfFVlnZ{bkQn ziI@_s@?{-F$&Aj9sJv)8D)z*891!~~FG}H^{Zh2}LZ@NK{JlhL-qGNi9U3)7;=vpnaY zW1(jOA8^a50`L!TSmMr3DFyeO<{KI}vJJbkG{Cs>Qt3^}$@!0ogH+K+qPbhpP{KP}YKuA>ue+mf+>t2H25=0#jI7TKvK& zi06)vRNXTc0c~o1k-L$ZejRv`*Mib9+UbFob)`E-nw)DV19?U&Rp-NNJv;fl!to!F zFPuV{#NwN9I7T{?oMu9JC%fsXH-!hL)a@=X4JBdZo4NL6z2b8MU-A+|%w->cWU4^O z^95OS@&q=BayUlW?uy_1Y*?*rCK^%nlHT^zB-@I;SRn9PdH;muE<^dl4ca}*Z)4J3 zRrCa}VyE5mDBe~tCv|+!NT~0rJ)ynP&91>xmC>!76jkfaslZJ#neyhEn$dQa(}U?C z`+LseMq6|%Gf}r6^;tBHg+11=m08{!milg>>3;9JK|)d7jGO`Ez<&$({}6J_f!{xO z%tpj}J?uLt0n}v9oUodg(vJ?ii6>65@EoQX@R^tzMh9LrPrc_TJ!#q#OSbK#2!7F; zk>ECGKjSuHv61woMiLk;%{pi}ugrBWH14ts^~X^<>1&jGUr$QoZPRW1$^z8T>H z_SKu~Dz9j}7=C_yz!E;RMT%D}gJp0l@L?w1C!f2FbDu*vwpyASZInMMDsjrLkl}1E zYCKO}yDgXcBdeLI-~(mzPh8mm+ki%jt;K?~j4<&g2}CLaN6-{|hR!6hFCU7dGY*0J z(^Rr~zo+;xj;19h#WOW{`rO3$r_yBs+IW5g+|-cOjZ0!P@q@s6tLE*Y2N2#k72Kl3-tMYKr4q4NK5^aDpun17{=)KMM z@NhZN*#~Q%G6*|Wb)`Op7GcQ~eaO2wwK;~2qccA#0i)__2$&=KwfkpGIh6Geq9Oh* zq{0T3DUoNfiPrj~6L*x(hR&Tdc;x`Z*dDzk8IHA9K(W$x2~7+Ej;||!!$&kyV3Q{^ z=Z(j^jt~5y+fm_-8p|Cl)ia}bE)=*gW0e|RL-PdNov)n2_8Z-LXNPx^+}Cu}7>RTW zKN4rl6U&nO)7~Z~YsMSlm=XvV{Ikp1Gc=l`5e|Pn4!Qd_z<)CFdOySPyWNr*ssTB9 z;~CSe$&@W6FR&qoytxYy&Ii<#!rQivB7uIQrwF)hf;5&#e@wiWWB9MM zl%)@T4Ex4N*TXS!fm`IwBHC_aSrlZt5ChzNv^j$iKafofR>CLdLG z;ag)p{vFj^6cHqjpW_ZUvFMq*9^pNQ&oqWc%^zcE}b#q0wpUDGREHSch3yS z=q_HqGS3TBWwYy0-j$(uu10)*-x$zYGw$^zBPSx{BUfxbKpW}BS0}z1D#X;`1v|qFL9hxCNuhwT|DgEP~f-cud?47+cSNtMkU(G7}ezPl&YSj)HaCx zNA*bz|BpYOr4%V;XMS(JD?WS~!Yd^ulkp|sl95pDM5+1bXf?~GQuD36WoyT=t=s0e z3W`-N^DgM$^Uj{IP#2uQzf=sxQ41EDj-&HYn?3A)@6!jw1oBRDEQ6ShCqyecdD2M; z9Z3`Wzb+5{bdl-=HFzuaO-q3vhH@mG=;c=#{U|jbq4*s9e6%Smah>O*0Uaby?U<}k zws|e811gBF(D!GKyTu}8wfS9!;m~>m;%aQS3?}MmyZETVgTEL-)-+d*g`Gxtj60q^=jsmTzBe@x?mO6`#P-B^Oi>vYSKCl&%&ZWuPF`OMspw zSsi<`?T!WCV`CJX_|@O$pc6sg$)R|GSDnubFr`4ll3TFDN23L?>TIs`3(~LvUkv6C zKHIkdnMYmB2{kCu(LGHVjOO<3!XBnMCK-)^$LLJPrJAfoNBkWM8_>I(W+B8j z^qlR#20eCQ?82X|mwTatkbS(U)P9{&JSxLOE~l)ANr<{%;kFXMNgSdH!G8!mxQ>Uv z9o9XKz!#S`l0$?qz1Q8o0Nv{rw2I4R)TTvbWYvV~cm)n}wsnB>&mpDAG@iE|zm^jR zOyzH-T*|oCg{S7>89@=2YE)k=y&om=!Ku`$?zUft>ngvnOZ1i;XyM(7-oLHaa^qur z8*Oy!TInUPoiWB%LY;Sd@9Ds^t}ueHA%e?$+W~?Si2k|OcLybBHBq;=acIqN8y*ul z>xdr95?o_IvJpSOdj>>Idc=y zrpapF)kC7TfHz2pp?O`_lqk(bv}h`q&hShf-(L_~QOY*dw{tUeQm<`ehu^@XDkD*i zsD5IbcYc@Aj@SJWYpRTekFLuDD(GF2U1&0N8_Bo*a!UB!z-_%B&0!)bZbo~$xgfn! zGP5vc(P-%#TizSUY)h+j8MV%Zt;eePn}E@;kwb;Q@mb*#WBRak@Odtz<2!6V__h#* z*(snqd5f-=G~!$h`W+4xoAvPHyfYe1z7MgohGc5kyfM-(Lc?y=`U?E<3lyFM{AHCqr7Zb|sE1u4)WJTN1|^NBzgcFIY5^=3ax0SqbPE zSsdA$+~XY?$AMM!lrR@w|J?E_Zaz?S6-ixj54#?EZ}jPTw+52=)(PpIA7$2~ix05i zIv3XpaK3;FRw<5*zlzdk8s(_Vbl-LLK5g&%j?pmc^&Lac?B>CKQilbv#^{oHanB@~ zl>dhjcISTPr(REm@-KA2kP)gZ+$F)em7=>B56a~A`4?Ar;UCr327Z!N?v&OZekG2N zA~=OQRWLJXlfrG2oi`%i^ZvYW#h}HR0rto@rbJs&&AIzTg7 z_b%X)7igN_5o zGSq2h_emUc1}N-zw(|%JL5x(Vz{X#6=%{|DyqGm$=YA7cIKHEb!b@Ow)ytwky~mcnx3f>drrB zC?+iJVu2S>ehR#TrP|;6NKWFmZAGsTTa6rZi?|F|_D92W7^Xlck7v>opFg z7}ZwANvI=={^9kF8~1Yws{_)nyih)12!^`0*NcHE^!;@$?NYBl%svlR*dwQiC73$`157whA&Dh5Xi&z}d*vuwb zD0AWRuGPPf^+W}nXwYX%h(4OUyF*#2UpkQ9MRkv;DRaa{%*PD5F|Lm(bc>xBr%2G0 zbv#5V8G03Tr;08k?U6o>#|#u;>e(7&xLbq(SfZonY!FNU_G70BOOdNgz@sPHVJq2L z+f>_qFx01>IwT*TKv!E+!u5x~w<^TQrzluZY znj>=R4h1lcQy8oC%&7e!6|MT%n}7XQvbV_FJ$&h|RPdGkP@>H*meNiZ)eBOcjSQwl z3DU2zS%gm>1IjVEZ)YW?v*QTV%SXpl~_n8}rP-J^`lsl6X zHezR|$l35ZEE+mW#!%^}+e#JO+W(Zd%tA0!>$CXM;T=M@O>q};%G2bO={Fe-UK8&z z!;|p`H^Ns(T=b4|~avTt(gH`g&LRuM;-h){F;<37K*a4!6o>rED^EPM9DH2fRg3dCKvO0+`sjfFh^ z;p!*5gEpE~F8`7Uu6L?>%evKzm|zD)9>|qF;=S3u=37x0W0Xm_6k}+~w0DVaZ`eTh`Vi~DP%*=n+t9y@=sDPleGC7hi{cG zYO$K$_$B(Uqr1x}-XV=QUFl0)#0lGU2nMd76udv}8nSxB!IyKw2~-1QSf{^rYt@ms z#wcbYeh~&`0jN3X9M98JVo=Gs{KKbYSnro0nu;4F;|apuVL!Bfy{>}XQLKV# zZn*9Klpt!k8XXwbr`g_Vwf&Jclj^fMJdd{Me<|%hBN;Av3aILzaG;~GRGkghmCrwB zz9A;r>5U#gbD$->NnxJsptSd5i|E$a1RqAzc%CSHgtI0{;qcmaai(B@YnIAdw@@?j z&BRc?2$JoGx`9-qC(OQ%fm&-S$O5#|WrenWoj({bG`QT6+stoKmTDA|z8Mp5|aUZP<2?^*a++Gm9Jl}}#ZwWeBc*tJMpSl9!DcC#*q7RRX+Zz0LnmxSNau6Gr4$uqPcWJzD-zadYUE(e7xWSFew4Ro=*Wz7!qQyz}I|5 zSA7yA+`j{}`)7Erd(KEx76Gdsfi8Zd)p>+itDWZwWW6$4pM{TIRB8gfLS>(Sc)opO zg{PM|9Teki5}~369Y@3=u=)hvT>VmMcGDF|U!691PD7)|zI_!FTxHj690~%u{Q)HA zxRi}%2sD)&92EvsJIQ!l7s$ogRo}?}`W{s^QQEkgn;?7m>KSJCnfYK{_1&PHmzfFK z$;nYO+f=b6s&$n~JZWmK>uE(Z>I@cLP~FkLifhNwQ=yffZ{P0df2ElFp+8d*m!kga zZx@{O_>PoEW)l<1S(lnK!KQWxXLM5JMBDNdG9@y#FUgAy(WI^k!?-rqA{%e$qB zWJJ$&n%oUS^qY&9SX?y7?@T%BMR8LS1jKa zbPBAX^KPjK)T-c8fX5c;^J0z>S33_2&vD8~W6jn(x|3Y`%Zy&dU%x+_ zP!l;nKezhv&gm0@s*hKg<)g~ZD`V5!G{mbQDfh$85L5Aj}7* zu@TON^lLDPu#KG$e)T0DKNHp)mhn?o5elVNta}HnS7B32V^`Q@5dT^owpq*xt~M_U zC~I@<$6FVCNuX%pt4Cc_?%@z5DdRO|YVN@FV%YPrZI)y&CETub#)E4GRr^`LIapQj z<+QpAlyUj3!*SeXFRr_{OHCu+|K1O^+hWhCniFHHOpF63&C0@xS0j|5(c{ZMu;x>7 zx4!3wBNXF^2G^Wq=(P3JX6#*qwbgCQXJ=2uL$9_E0`+49ka$`w>^(L;scHuR4-H!5 z>h%c)6KP9g(t#nnBU?$k_UPhT4ZoJB1O{q0>gCh+<;mKvnOEfrjK3})QCeauS8GUo z8^-O~;Uo(GZ1`n@1HD+4zjrGk?wMf>i*4RnhF$-b!Z>UqQFWALvcl!b4KiXwd-<%w z6MC<_6aN{u0@*8l+8meK=EGzwVCfme^(*JelUD|4yzCn{I4 zOdzm4^()QgD*carnn@4M2uoJiU45^5nn1vAcIgQQ8(;Al8XF5^1#b)|w7-sCKHN9y zmy8*4bwnq2R)9uU4Gd$cX6Bu`}a-Riy(mR|mLcs*KgO_(C0UTy<6VY99`p?%MHH|VPC6F=1}x{MSUKdU)? zJPv@g`2eg*04H|<){bxs!ee1&NQ`=Bs09_%ecrzh1-JeksGtIa{#rZ0I_h9y;-s3t z<=N%O4wDC}$g?0170gJNcMoNu`hH5KrG33}iF9&WIexx>e6m>0Q=oSwFMXL2_Kp*e z1?P@sV73-d#L{bZreUl8=9F{H_B1o0D(078^Lk6pRKSqNAD89?yJ>@s^XRVM>+v^c zAm^g+Tj>-~c)TG~EUG1=lN<}W#ER0n)we`Bm3~t?an2wk&|ynazH~&X+KB42O6@zd zmc;Zqqqv75blG|_`(cXN1g|A^dZSz|W%mM2-xZ+Q=&-#4v(2DHI+x~L{DCh0Zfkqd z2|Aj;21^0(q8(8xlh7aHdaxmPLgC+CW&UNb<3L(_0O}Kh*F)eJNX(I>Vp#zhw z!WLdjMP~FNf0x{&0NtOl+FQiXFoV?-^>uB-AWA&#g$&XcdK7A3QSa%L2~56_L-&$8FbbD~DNH~5ll%EK z>Xt{o`(vuS7!4(?CWT5i<({xG8)$Z6J_Kc{zok$G!44|9ig}D*S}FmIMPMdP+0jFf zop%|Owg?!hm+xm*zx7DR-#l>Q)?7^?BssqZ5@9!<{YGMWY z$zk^T`Hc@$3$)A_>vE-(6rfbVBdzd>kvMw`ASHr}UFEJzU%`UT(CfdcU|l#EhRt-S zKE?l9CLHS4!JLFmxBmXQ+Ev!qpz8P)9oo=>3J)czS!E3OH;AW4jkNvRIB3k~tX@|h zD9`s6?%xl>l~*1)w-kThfHg!gBb>M81w({lEl%DfR$pFHsuWQPS0>=N+IX+V}EH=eKbn zrRHcb@IIV&OanX$!PwS51#D=+u)Bh73Eh>d^Er+(VxTLe?D^Qi>1`7@bwNG)=jS)? zCaD}za+6g2)@H`k-!h6JmEl7QLB+>z*ww^&q=32wr!pzE2%M>Y;@Oh|Uce{KLG|}y z?vL_wA{=?Sgjk}*WlOqag{ zCDZML?2jT9Bc5F+HwCKlGW(}FYKYW#7lge^m5>`T#+{K{it_7sjI8k7#vypO+LRI2 z+OEn>c`{E7Q*_r)(je>zS;(EIE0F$NdqFt#kUH!|wQ0HUr%P+AJOfK)oxPn#ALJ_w z{~vW*I>A#3xAgO=C42dI`|k>C0grBbFocyVp@bg{n29?+dwR6W;XHm7^a5hSd1!dU z4F|GuV1RG%q2!iA6uT^|z57rB+LZynIv;w}TcP*sk((SfSWR20{x{w?h;1+2sUxXl zygx(UC;=Ml>1k;KxT`whLknwzS&(}D0f(tJ#8Io2pT9keum8aHx90fcDXRru2bs#R z_ZV5RR4(tQ=bq_Qq81uOCQ;#I*-`A_6aBj}%`-6nuQSjpAo%#gdj4wxAnBnlzdrn> zu4z~W*htSs@0V`@7MRNCy({UA2uf_+eXs!P)f(87tZ-4A*G%C>7I;QI%_M&_|32ZS zc$HCW)%bipXL!OUrqhu{iaTE~{wr9$Q#EHtbW2#qVxjcazS84uZ^8)6g zfsXtY92%{D)Zm>D_wHGXQbvaO-QE*v(@M;ug50awFzT8adt99 zB|`uR#f@W3Q1Qoon}UI~u-ofuIG20?eVR3!S6m<9h?xSCiJ zGI6o2>|L!4b!n_r0jQ7ud%fSZkGlM}4wl}f2s)DCD{$zjW z_-sD!8RavrmjrwPKc4s-bql>{G?DQybSRW>$Aor9#E;PwK*P<0xJ5!-;zpa%Wt1=W z_rVGR0m8ibN-qxmB=c5-!7MkTq>(%Cb$05d>?^eopzA6nJOXlTe}D0-OaRLFY$9Gy z+r;;7S(@y3GM@a1r}=A$?$>Jw1EO;F;y1P1&y9qAI_U4KQ4p$+L!$1CL(0ialy#IG zzEf6P{R|b&Nn*a35>WKS|KEt&Iy0Q%QpkE z5?;kueOb94Kb3L?!f?c@>p$Jt2Hqe!6TGnHzi_|*2fU|El~I0PS(f*vX>uH!N`Ifb$2-H?zTbw^9?JndU9vtxGlq(`?so4kmsiu5)1$q+k z=|GXt`q@<=3hr$^t{BeF^!7;C=PiV@J$fzWHtE z*4#AewNp=H1pH=07psDAatl+W|79AcB>`qYG!A$fqtEBI#GdFuJ{s}(HZIs8Jet;L z(Ke4mDqzvgmOll->y(j9;hF`2tMnB}ZC!W1WKv`E)SS&%U>&b=!Ik@s-)5?A#QDM= znE#`nNI;O#@zMHt$q-l{^=mb_5*TXYuPn^12RzZvf`jpa?P$D^_c5FJlLmk|mC0ZX z1A>^6)| z3NelY`hX#J&T+aJhZ1~8gL#R;-npTS#pxme74f1uzoRhj zqI$Vye)YCc#{2r+^aLs;{wH0-{f0l;it{UWC$By1M(Tqb6!Y|*zvzOs?1)3TcP3>V zpv5elJ-mZCuncJ4y%8Zp(+Xxkw%#(PpQWb2=$JXA`<~9qoG%V!JtVG7qBo*sFdphX zhQbAt$u=XbRn}{^r8(ty#4RDEKM#qG+(qB^uz2B0_ux*#_VIp}5Betx-uLBWAotil z(8zDWpGH;vv090rsQMgo+?e^1vu_RVFGbU7h>e>7?P2|h<##A$hlBIJX(zB~+9mg~ z)laWW_b+$P*Dg4PgRAnFUxIoO;8I;ZBSiesC#wUzTa0W5t}2rUusTS&Y}C~v42#n( zd;h)sDOg;e)xlXE7#QV`q3bIkYnW0q+XKK2{mV<8tu_=v4!n0$Qffst7*Tq0mZAWi0 z2X1@@39h}?7y8e*m)ZZ~UjCEw`hT0H^}h=E9~|}nV{890%kuwAZ~TjP`F=R+R``4R z#A7U^>PQqf042=+lW{qZ*yzDMkmPr+{onFR|5sY){|xef$YlNRj%xVtcY|vpfpykP zXIU>W<$pk$kaZ>Gj9|F8Ak+KnGOAjj_EKV95EWIiWjvt|1EC{Bqj0gS@{6G3ZSjvJ zR5aV0@ABC3)s_S*f1||}q%Al2n?f>4ALn?U|L%H7#-Cih6)8hg&HrHTH9(hAR$VS9 zcKnkuxY5L)2~IlfpR@cY5A0Q7{DRT*2?Fsyd1_4sTGxQTD7ssc0bD;R~jIdHsrs0a)_Kil?FMm+u{ycZ_!h(DqVOC8|N3EwC7+UR8 zuo&YQ^YU#TeQ1D8sj)2n#g1(Iiyiqde%e1tSO0`fPs;c^{p;(&qTd)(qY24B|Hejo z-&XH8iq0NmJMJY=;MK(NhY0#1{@q@gk$bOsuj@iIGZk2Bx4h$y4%qRM@8a=MI+?FADm7mK+T7uF+W{>MKFVK+T$l_?RzM#{|fzyTk`b5i=Wd@&JL)rOwtF1iM z3m|$nds6+s@qJ2p{95PlxA!?FZvTd_meZ{0%HMFWMAqH^4WElD?Tz2wDp?8W{ic=& zBVlU4y^S~epKkxMiNBO=k;up(I$|h$O7^uT7U~&FMS5Ue}gI>8% z|4OL-(>U+h-Op_EaS@-$%Z`v&li{*dJXtnkksb5FvAiq^MFrQ4wc`m@Lei6*##4rD zulD4f|1fXqr3sV!xMYq+=r^?-D&l+T_g9~NMRR`oxagpA0#ZU+hc(tM!XgjJ{I>8& z^n{nbly#&nT6_{-$~^?R{$4lTKVfmYSO*Me5$oOYN?R`%X-{>Wl#04fJKZ{1|UagDoB@|K= zfDH1XqD1k)1C;~hShqh=Q^2E{aD&+7#RRoVjy+Uby!0lQ^ySAI=-)wZLZ1-rUupbX zzAEz=mw+)`;UPqi))BDQe0>O+5?yR1=D6RTWLI<1I^o%^-lRC(I^4JAgJGR{PgK{= zag`0Oa(V}`{H}RtMJ$fqVIhlYx>}X|w6|KE;_MQF+h>>T!Cl}cB0R;W{dJD&XHDtg zkDWl!Y!iMvYURKII$}yS5U2X_>8tZh|4wc1kW;uK!LdU-&DRQmJt{bxE!CrZYUE6> zN#`a?t7GD(fH7ReT8HQ%#OFu8vOM*~|q^V*d`3cO5{QYUzCOo_vQ1xOwV*2#ZvSI=-0i3XtPaK$li5;QI z^V0Ks=^sYC-W?%=MO~B?N!RX-;p%7MYuLhB_&(0_70f^H*6WS-DN7vGpFYGXP3)cX zI-E}Q+C$=rvJ=)2ZW=VVYfQTmJJH1Y>%LDflWESasi(>DsBuWqWycyEVt zJd4VNsg{2#m@ZT1|u&{L&aZAU`b=byOe5O!c zKMB!S7SR#!b`?9ea)^l9uSh4RYu@A{u2)fHGrRu`-{M7P-yj!V;ew0{FjswEp{SH;u!*z2CukrXgP0hiL`4Isf3tF_h|!Z!Lz3OJ|zx6LT$ zUsifwW-1hBXK~qsTV2jOdQoWtmk0}f8l{I#;XYGVJ2IC(W@H5MvwH*`AS>A; zQEMi8c1v{#H*sTvoNS~jx$!&LOsyvpyJ%f)fv?&?C z{u>n!lb#_x7E*CuTC8j#y8J@ReW@zE1~=a5x5dy!`}ixj^yIO}5c-oa^EVQU>_4 zy88M{_9y=`rhmi;5EnBgzsi_2e_*M1{a8Z>0a@GYJ%___3d!p{nZ0>SNWKS$K(I9! zOb>S+3q5G>kGVUSk;h~GBt(m9;XK_fiNo(3Wjf@dJ(r>;>eL#1mEPu(!{mA3J6*#Ryxd~G&qqNRq{S`Cw7;)R{ zdzI3Id-s=R`pC~DSl@2hMvolXBVJ>DU-SgyQ@wKu}dZ*}|R zg`7!7%mWSORLEGGbHcd>1hH@b#5MZ>(lN9?UL}vUT$6{Sr&cel=4(5^TQLyni6;UM zuQJd2ZEvl;f}7l#_rpA$D{))oiK7jC(O7$B^;M;Sv2_Y3@a!ed%yBe;!W5bqFN1SL z0Mro&H-RN4ELblqhTK=d^CdQD7Ix_PnVI@p^vW+$ELz3L4qQ{X-2H~POY}?g_&-Jp z=X%zNh6Htxl=ck;qjw>qlI)j~R)nM#6h150)Igu-GTZ?SN4FHS;-ouv!&OCc84b#N zLPfG0vS)E~@=Bi3N$s=pPsHgfa%$03BdKUu_AMB=SC*a1R(moHN*^OV6q)xvXcz-c z+PqTu=DvJvh5kVC5v-}+sOI~!E&|d}XrcTA?#P|%4Pb|SB*M3Xj;>Z*f=YjCrW!P| z<|s>Tq6cOgJq=HVNR9IO!LudUEZ=S7D3~T!Ck|2*bw}T3Q&aX4Ud$l4pO^Oyj|9d~ zx|=f;-_7{eB%EHDEYe#;b9XwviJfnG45*>}%Z&_s1++iM~o9G)tyZ3vJ|QhhF!Ls;P#PCy-Q z?_M)$Z*qkQSh#4Y;GgVci1VPMdsW;e6KLVA;eYP39DOwFf4ptk;Jd0r2Wu8&^#3Si z5r!CZ-8-4+O*@^5Ex zgqr>L1bfBGT{!|@ymc24%83&A66FIP`irYca1iJ0UtxvS%F_NU-ZGXEGNmKKk zrslLd*vpClPL-hcJnDIx9TV`~idF{qot9bpW0t#Q)>1#DBC!~ho;kP0WTiLnKBviI zO1t?I`U(&DJPsT>YXCJ$SqUR7h^f)83T#9;gAJ zZHKLOyI~f&-4L)^XzE*0Ft>F8?TxDc5!Rd9;qCu@IF2TN-{eN6q2Fw3%dTSm%-})8-t~-$9-)KjOcOjwCp6pSP^p$JK!jag&v>w`u0I-7of8t$-Sk!BkWYp zuk-8g8rXz`sXg{bkTu13=$kVmlmF?k8AQ;HS*OvIk{`6e#7_SjK#A z%ySnTT?s2ZEo&cRaWbeRf!ee39|7wV<+O>R6Fg)xqN3Ey+Ww^mF=1Z&(~m7BGDRE( zgbQc$Q<;kulB|2E1U%@|*udUtBd>XYo|oScN+TFav|j>4NK@Np|Cpbn=GMATf834y zUyLj0NNC~qH>Q7CH$}T4EbyvAGtT()yFjPUccSv9Z?^lF{L%cu4R8eMKzkB)YZ>~Z z!+(6Tolt;6UJE+y8?TBFLdv;)Q&bysUmAZg znPHuz>0ut|r8SFwsQPbOtkYp;y zWJd!Lz_7xUM0a%b`=|HMECT{&U{;HzKr+c*@Y#4J@IUT~db@SL-^tjt9zIVD4!7U}c- zj2%YS0q00^C$)=|?$X`wUQD1c9EA=9E#y9x9-!O0IX`_+_+wM$a9Q?ku2yUxC(Bp+ zV<7NL$U(uwQ>o3OngK2jWp*If9M`%GV7xM3E;4x?j>O8mBXC;ztTR0*+$iS1>6*0b zN}aIY(^*={oY29Xf4W|CD|^ATpKLt(e=P)b-x2;YIspq66`%9S7t9RW)AG{h)1c2TTpgS*Q}3ClK%L;sj61{1u@o3VzR;6d zr6;;pMD!7KEVm>GO4wtT`v+fK)-vEv4-Df^@a{6nhwgaNJsE!YmGu@)K|#R>TXIduUT}_RrG^Wf{giN>6<3lsru1u(5fHAm& zrfW#(_K>V=bHd=o7yXeMI*@4h&zT=7pPAw89F((ONjl*1jgMNl5R_`D*k0m9$*FcG z!3Q#J`sqZIHDc*DcI#V=3!;T}`))pkkf6o4+SRBNUOC(zanzv644neXeSzMvngp!S z$O>Uus_$(NEN1&gAeD%BgGp=IES;`_Y@%nE{X2-0>)5q*MfN6cPjZqwpK!j)Sr2Ln z*43LGhz+K+xd-MiEY95sdO$gOT0a5LdMT%jIxSsFe2M)8jPFEL_Ia{i5_G^T-Pav^ ziyoyO91T&3oowOl|_)<@yH~Ep!wUY{WPI)hA*9@A17+ow(EZCpjCejwdh` zG#s;faNHd$?~dm*8dqiA{AZl?9=stos6|c-5 z#P-t4_Biy)2I0n@VUTu=fa(;;95$*RH_h9i71Dq3Fctc=>%j@)Ef9Emto@D9!pY(F zaCqdUpRcu;jte1JRd3?y)2yuzKP`A%3euxg*A{`^IA$FNUCXb>n44|cG=&9f?A3#x zXho3NL+E4IG}5^*wP7?Z1+)(W{W<4Sa1O@pGPGK4fg|Fv@A&~yyV+dAvK9iT3$DZD zWu=o{gk8gwE@;U~+n)D>NWS*8h0KS>nT0r2O|!g1c&fJrw$lzA%6Bfc!Cuf=U>wJd zX6MVyFNYsF5KojELddU4xLllj!uhkkDSFkZd}9U>u*L2PTpySh83)1&fNi|Zc7J-= zsu9KowmM{30raQa*WQr{NNWL32#&kB-#C{=QHoxw%56!%z>=PuY4qc2W|rq&Uvb#o=XR2!RX2ip7HY8B%dH3KUk$I+u)#ArCHF1?!lpiMulk z1Tc3E<}RG5*{B_y6%^- z@*UW*u-`9HFXkG`eL(#pSgv5v7~v5)OjuUWL6rS+Mu|EB<2ksShp5mIjn~mM9W-aN z;d+y=cgJ82#aoi0(2}R1Y7WgjO4+`$IOPQ@PPVE)R%TySMP@fGVM88fMWyy8M{3(s zZ+>ik2<+16SC_Pg?&G}UU4D<9Zc_&D2S;q^hLfjh_d}3Oe(|%hrifOi^d}sC^6q_x zOpIS|#iW%2Xz7nn-aolwu4A_A|F>BAIOki>@zlJ)w)(hPs|ol7ECik!J@nHcS=JR4 zCK;CwR6nO7N>!cY_(2UzPbo|Y{&X^O&;I+~bz8ylm&uqKLRKQ4@q9h%mEn$+TZ5** z(2?FI`%@!fsAp+kN>}WaW9RxFAg#Y2uqzWc;T{mZKaRewT>DE2g7+zJfJm9aI%h#L zQ2S7N8S)b9gi~*ht@i%j`Dj3l3+GL|^_u-;_Y z)VUC}hE(9MAvVjox{m};pQO?W#K{D%K@vr67s$)n%GeOigXex5T)lOw{}{3#-g>!^ zYrm^pZ|st6)v|DYT3|mX*K3-Tww#Rk+7i6d)ymVoIlDZ57F zrO4Tz*p%2mYNi0xb6v^3IS0;$|vNo&ZYzQ*N_C8pX&;7eWN za&EsJ)7__`QzP7io6SDPH;q( zL~PAd5=HgcODt@qxm=30GwEJ_Evhy$yN0!of(?@%%`}AQyjcNK(8$M=CdbEd-WFK}v~xeSBmGUyY8m_j2t%n> z&Kqj)p7tp#>~)M+z0lG?cj>V|pUkN*EmlS5l3Pzxl)XTia=PCzH}>&qe& z1ih3yoT2c7;+cd;%wF|gOG#GwHDH~a^_A?J9?%TEtz(nSUy=!q6A1S z#L+&I+%Y~yAwo|v%$w~^aQNr9=`>XsZoAc2PC)8O*UY2Anq%ZE9EyrRZAlBTWHhx> z&RWt!erRjGYPbccKLG@=csL(mhi8DDxh`wx6i&89#=Lpi2 zJLHE6U{oOCP3Dpn03*1Mnk7aCD3!|~PoOz?b_$@XvRh5IL}Phc7)X#z3N_JY9W@pd z<_nnU-dR~(L`ZpMsN}YFCs)7yx#5g|r7;D0l#WSb6m4Ia8!d!tr|gF*Yxt>YPwrCK z0XxnOs-#AZIF={Rz~KLTSlLIiJ81O?R_WSoSgEf7TykhZLQAVZ2tGPOduJF|IZP}2 z6Z|{enpT#r>Y-)kZ6Vs)T7i}l)}1~PgpZLy5r?M-!3x3wVaU(bk4(8i!uZs2VC|6) z^JQSJVaKl_a9!&&HX*3Gb5a@wDaSQtPT~-Z+$vwUXV%Yj6;h1o9=dW}y?-6Y}C_ZXXp2W#uFE(ex zn#~yPbS2JyWxR4LkeV6d$0#xU^ZDFsGgE9xcMUXq@H~#=r0KxP=2VC-Qg^t&sir1* z74b%xy*?$8dyY%3eI9LSJ&3}Z;I>+Q?gjKhmmo4bT$}9}Q&=rv*#>NHK|LB|mL1Js zG8t6@AvD&mmq5?GbHBp+uE`pZGl`tJIz-xEg1}q{j*$6GMiBH}Oa;MQlx)?T%ft;> ziWk828gfY3oNRq!#E=>GM0_IId!!P(b^Qb;|1psI!0yM0J>I&s|2yW~#u@G9JG{pOSJZ0ZkvURAnL~9rQ3v~20*208x^x$ z8u?rylhI_{s3Cz>$n*75pd4y!kL^^ClS|>D7z7SPaEV~vlJ&?_@206lfS0viNz2|1 zF~7}E`CMKnDr{qlG*4EZtTU)oC9kTff|cAs`H4 z(`BKTKA0Y7(p1g924{giZdO0#aH8oZ@r+v}zSb|?riX(+NwR~kEChE_XReHn+W*COBeRLV^`2&%F=6C zuvB9dD|vv#JQ=8iR))E@HPV8)etwIXtK8ge%`pczu(rAdxI*DE3T}sf_%qU5S#_iCpxMpFDR$q(|W zstV0k+n~92w*YJ8Wuo6deD4&2PPqBp(Z(XvaHutT63EGtYiHJj`i>po=LK+b3B+t* zr5v2F^$LuEWj>M8)vZ9Q=Ss!(h9B-|8{){;XaJlT2uyNOhPUHKffYGfVk^T&l3<}@)ZnSqegcp1&1bwE*e zZNvXNI>{x*oISNh_d=-%0{w$C(6ltFv48^RU-&#C>$Xucda&06gW%>s7LfD>im^6I z|17G>Ty^3!ZakgbZ|v||fn!^U1uVe)8B9Kuu#A^{jAi`(X^-3Hawl)7emW}PdP^_s z`64!~ba%*hxHysTUl7Hyi`;HGYrJrSsQPOx=_q6a<AwrDvrI^8`a#*RZTfBCiZ}U#ixs59wC4+Vfj#ypDuiT3PGeNBD>Cl^4;BlD> z`<)vvr8FMJO3|w>VD{=t0eK@_}Vf`XW$0&PW;HovplfZbKF}QdVlG}xf_QoP9v*9?x zor^F_5B(-Lx10~EZya~L7h>?H{t$m`f1IK%yTdw1ks~AE0zf}Om-B~Oi971^0bbC! zV!*r~7(hCmlP;9HY%cy#jL7XT9sS3{2pfe4;S-l+@7mS*${s6I*o*9nK<|MO;2k-7 z64K9CQmo5xc0$|nr{~G_HgTDM^!n|uUMnACU|?ORq=OGK6u;&DdMF16JCgCt0)l7gpytas!aXa-9GEpvBj zjG`86S%1KCE(V6J(mRNQSuNlCN@TJjHFpZD{}n%QJ5+PTvHN^lS#?4?H6G~ze(!If zAo6d*iqn9l6D-mXhk6)N?4123z?hmX4-vb{}{wd}$Y?QpLCeF@2TJqYg|N7Y~ftGUbyA`EGm0+5YG#Du#q2w;5hO&+M80jIO>~7`tF&|?B_&_aZm7DZB`z*s!Y#yMo@Hc&W3mi zv@)q8z#|h?26vC(trLKrVPnv%F`d*ev6;(PS*9|8k%&cl9{@W~v{}?iYP6d8viUgC z1$UGCo=qv4O`fy^uPA=Q{)6=k6?obxK7u4}G8X~3hxtVK2T{}y_*d-+2#Km}6?33G z*L|!|?9kULs{@v2>S&IKsHHhZz~Sq6jgj|4w`2Q63}}ADJ!EU?yV!%!-S1#8wQ1q8 zq|2eba>wYtgk1#Qn|J!*A|sh%3(O-YNSj*J9(>J=K}ZL^M_$I$*!3{q)mWsQaQgtS zUvA-(#Qe{NT@>;&rH{pU!5jK_8kg*F<(cnmmuc_4u_ERf$*dh?#V0ccJU6Gj7=+eH z)af!A1v~u;}3_$}H0KSi)$)KOMfv1VMw*J2sGaLO^&|^&t=YN7XK)3kf8jBEXyT1wmTlSB6A9 zD5=^F_DAqI7DxdTbkb3T2~@|r+qJq*w#W&tAl5CaE>##&u#KQz~Rj1X_ z`t$KuuE^)XmnV_rP+MD$a7k$91r+E*BD4HK7w)Q?Qmn>VVNvU3(&a?}>}x(@8T^>v zdG4LS#+Mpy>6Y=iKGPGH-EJy*;A^3fq#5=&vC3hzXZzx2`we9$KSfYYCR1d1FLqsP z`K}1R$p&FU>89?@5Ci~zD&UbvO@lB$FimpI7nh*A`1p8lj$gfmPF)X>o%GSW_hxbT zOJjOFqIAVk8Lg z%t>;G0EGukY4gRdq!}=(}F8bWK_>-E}zE>n;m_qo>?y{loI}h*AZi2+_LqJ^}Z_s!a4HUr6hsE zIdFwl+yG9hY)0oFB3cV#0!N)N&0 zQy|L8R;rntl=RhiMZtU?b%IPofF|WYT2PaOPpdeV6A36dVHd!J_el?8G&B#^o}nh} zUL0+Gz_weqT7TsHbrN{&^3&f5`yc_sO==|cDON^IN811RLVkS9minXnTgc2;dQns> zo(^fCv<6kU9rCgbATs7vp6_utn&0 ziHGeZ4&Z&XEI{~ND&Lp;A!VSxkF+iwZ@{1#%Y zT|;T@i6_QP7zA}#8aHlq@DlL@3K6`tk$c|D-6J<;yPq!tQwPT#3vGe!#1p=EnBz|; zS19I0Xbb?B;YTvG5HRpwaK|f+!*@}CEZ8QY(YbM@4k!K-zH!_4Lakfr^S+b@D(@p3BC5{Un)JqCo;Fg1tpHBiV zy;aP%A8wx~99x0xXmrYJ33D7EdZSH=kMot`VEq>=Q~E3~z~*`E+D1=Xh0#z_NVb|+ z`+R*Fu@}r3l7ik%3w`v4h7V{VSg%9v5|*t_Q5l-Qx5|h0G|!;7diRl_+agR`8Nh|m zM`H4T%1x>|X7Lxjyy1Dkdg=)*!#YoxUBIIJ0ERF#*hRx1*-B)BYx!CNr*dGz+@J~z z&bOkE5i3GkW#*eSRXWgcDtwpqnFIlMPOUS6%Peq9CWbs%3L&iSvGisGX1IG!S6^j; z!gm>hV*%8UD}hoLBk80d8+s#DvebJH3o+U5i%amvHDokBZ!`7&c&u2@!f7EIvITFg zC`3WPz|A3+(AVa3I+d%&i>?Mi{echopz)dhXt^Owv%s&Na-5d&rkPR*riQWbK&={*q9Ord&jqF z`bL((-gG>z5R7aAe7gVI5S{q4TifxX-vJgk?wHA!e0%^v}mOknPq42DI z)erB8YfNzHT&I%#*lVvbuCi6Tpd%@!T8Hj#smWIdrofHc)fNQ4gd`K2M~UGQg&BP= z1Z?}p`W1*dXFd>DMnu4rN-kW-Ucp}e7|b+XzY=rd`-cn`%{#h@5tkzs4{)Qv5evjT z$$ylm-_}7=JVsH6g1Ge*m5sd~fL>y8Ahu=}l7RU-_j&1zV<2xgVKh}i2VS3>;jW*X zY@AA{v-z%R^Im%g3P_eohkwccWOPu>b9yY#`I@8!dIe0O52SWX9W3Eb*gks2FyLhc zy4&GQg2&}X@O{R;oYxJ2eMLs&0Rz3z2(9cxVgsO?9Dn?94nV;SJOf{6B&35{?!zy- z2}PquR_KNhvS2yocP67z-)aS*?%18=RH!&9%;NZrAS`o!IB0)#=WccI z4uYJJ85)kO%T7nNq1f0LCVJ9AN z+xtjNg^0^$)V2QV_&U0tZ!4`Bgi&oowMT|t0kd2uod;De)3H@{DD^AclkXn$dtrDv zmotjR#r-bCUl7y4&Mjj5ws*$kI=TGufM(Dc%-K2-a71SiFC6FC%gG?xZ^-ONYyc-S z#`3+Ls6Rk0TiJ`ocPdkidU@OP+Hl^m8E_l@G)5;Se4e2I$8A$qu6#K0ffk)gSXSeH zR?lG~Q=KHx4}ubQvjR^Qgec2a;Al-+)S4@H-)n|s^^(OvaD{MSE_4Cd{O-2>?fuQR zpq7@8qAz0$>R&M^*{)FTBL{^OsD1IA&RhowtANxImd&Jp)PCQWs_>@1_iilTLv8%( zoG>GYouE>=>m#=)Cu;gbIq(kln8}veR`7&`O`%CuCKNiy`!?4H`0Qkv1o3UMo^~o; z=`YN{ojpT$n9`28c${_YM{y^-Tp997|qHW!lQbVUw-9yJ(ppP;DXr&p&+%{>PnE6bL4XGjG z@k_}19#V|=0Nkd=Z5K_L9-SoQ{o|30fu-X~P5+w;H*!nvTcC>HHvvOFKxBHlBp_iP z;O_Iek(6|BZ4Zu=2h@!nmrQqX@bI1}+M!Y3c$lwTfDwkJxh>(=30v!1Ey_K1Nh$3; zhuWz*@Jt0c`aaa91!^&RUW&`$L#WIk$zMy$YSkfcjH7ZOuKWNPD;^z*=woD`VNHTQ z8^_I^98`8%Pl?A>V!9%!Ej1g1ucE2XODYw98gx8i{B#Nm5YcE&xd&VY?8 zE?ng-ymq-<1KaFMY81s}l}Ih2pXC$E zj=U6WqQ`hmqanDk4RDYmLU@v(by#=cWDg0r9CtS(hnoZwb!RjjM6b>_;;@@A;O1#F z%LWBSK|#k+@fHIMOsLH%^BZi3ulM^EvT*R~+;u?KXEk4Wck}ps;F30jpC^t2ryK+O zaGEP+WUfZ)qU4&~^efnA+WzUX!*aYv>s#kaob4 z2Pp46CmrifD9v0nBHoHoGR+Z8F zd0nsvw*LRTht}$Uv>Ogt z?}!wpU%2G?vgH-IkVQ=HYnn3B38pi!KmLtGN{9Rc7Oj4XG*u(-7rIv*T0S3y*xxcc z|9>z5q_)E5Gf>#Z=a%%Is2>T|d$;fUiD-H7SN$It!Mr{Ni~NODL38qTU*d^pa`dag zs17#D`?QAt-Y|bNn}0S(z9$Prt=qmQ-oEZfKdVYzTAu$sI{&Qpe_`@xEhkyM7u2>E zGnaE*P$G77c8zSh|D3e8JMRXu+rM&_=dGScvDdjJoFB7}a&h&XjX#iX{U-YyW-hs@7T? z2>7;A4kuo@uHsMp%K`q)#yM4eEU^5}(`^D9-wDf59@kC&SNd(=8clswVcrT>mpme? zWRyC0Fv<%8Vf|x<_?Hqq3%u(YP3sWrj+HTKH~HCqQEVPREZhD+A4=F|KA5BwAnPyf zTo-hS;_r#*Uv}f_9KGIwrsy1;Npw3t=(Id5b5qWaPGp>Z@J8^;Jid!?aX%h7ll|TR z?B+=g499gkZ-^YZqUeOePgAKTm-q}jo~=57&PY?$!_s=$_C4Z3)n~UH|@>A#{=`3p&U)f(jQyrC-(Hvu6u&FKT zV)M5Xn@G!0kajG_Ae|84Q;E5NtA{_QS>Azbk>!mpx>U8U_f|X0UF^B}N}M#qvLJx5 z{XT7Vecam2qLZh$RW!j1+A8xr)RQuB^;-T+{kmDXz4rJnH^p;Urf0Nx!FTxKgSRhe zqjaO{lsH4~ZbkPnSUYfPx~|S0&!4RzuA09g>0?TJnWSPi*uzj`zpBoDLoPqQu$I5N zi*Dt90bj1}7k2hHe|2tTqB{BtAQlGXSp8xZNcspo!QGnJ>nyXhB|9rLPEl&NpU=|A zi1&=BWn{D+b#FH0l0#M20v+9Z;7u0d=&3^9z4)@{#DxPwaw1>btYx#bb=lg9V{fp& z@wsOmQ@q5|nl6{n-_rCp|ui(dP)xuGzWYXIfXZTtyZ7+JIT z|HIi^$5r)p+rxsQA_9tpv`8Z%0@54-5fB0CF6k1b`+$^mNr=)V-2#Ffq`Mmh>Fz$9 zbM|lXJokHF?-MuPfBb;#y=u<2_F8j}G1gYsD?ZIIF=mc2($V3eb{>Xz@9YKoS1esh zop0Q`@P@l`4=k;aGh{OmKnm0ztPC*-hf!a?<-?r&Q2*f=AXBU+FGiaez=g;KrDLN% zv1IfezyS&Hjn}Upn8M(;hX_>T)vi#)`o874=+fv5|HJyLhyQGufRp-t&;+$l&}?>z z^KP-}PE7*MZQ>8jZu-Oj_;^4zoC$1T9B14Qo@%0h0#0Frg@u_$y^2)vxM;XJl4%OVOVxtVL4qgt!mOMs_bjD!G<#WKF#uf$LLTGXX*#lWtt6kAy^8@ml*ktdVbG`#6@eW3Ze9FX@G-0|92*)Dxj z*wbXAu4~VURI6;wBX>ng{j@MUAhKEQS}!vx;JqmTsD^ZsI7e>BB8Gk-h<$~))>0Wf z7nK%_YIulN=o zl^E$`tocPDgffDTH8 zOZx`6Sil6+0meL{I6t~6h$Zzp>B8uXZ{lF~abNl?R(w}Ep%ai5H-C$@0r-pB9>gt$ zBe`pCY2V~%6?fj_5|{DiNxRZ?{7{6)jD6HapPqoiR0IYld`DL%51M1)Be;t!xnlh( z*Q_kN3=sRSf`xh~RNoIzwO`nr4M}hBdtfYbVf_4(pMniJuNpM#B<+`Ag06WcA9$9h z0(i}eMarfVAjO3|c4wXDk?^&b*-d+2BrDo<@Pq(<25lxF;`B7O@j|J47Ic{9b~&dIhfr*4wvPvU8A~8 zqTpB@)gdRRoT6|4;RhoeTR-PsC+T=?8{WQDkC8-T(l@T`1_1nOy=_b?S~MM7Y86UK z7kEE*oM&j7*M#33PyU5G+zs9DCwB}9*ZWi1juLi zpBc337D5H5y{!V6&l$8CB02J!ZPJ~sXL@zZuI+vMuWarin*M0fx6dGAmA(~&D z-dV)5J_{l|4QS`G3o(eGhQ))JgMr^_8$_XabMCS_)W0(CW;+x9U=Z>I+e&YcrL(NB z0Vju{)^3t>`>zEIq2oLQ(+q|h%y{xW&leFnwC5;J6toLSeQTL=;x2}wGE2!;@)`k( zzt^E{G#6d{!qpatzoF*#>)8x48iOfn=QeqE&&O8hCmgKq&)&PSR^3%0AGRI7Qy;*T zLyLw9^HBB~>;fR(gJUwWdq;>OAJ4}ikvkcQRlM#yp=k2f<b4h^2ia zyKRi5aa+7`)INOqJI`EaZ2O1MvfVKQqigEj;&R(5#pMGnBgh>c<-@RB2SkD+8`g_Wds*ijXawKRge4zymq#83z*!bV?| zm}j+?{^k`OkhlYoCbQ}C_BHwkOoE|;7=R=K+zr3qD zBwatk z@$V)(+v;!vH56zy(A{*v?6vsRe;rJMmeD5%@MT4bnHzNmKRN2w$5*(D1hqAE!?7MX zR-Vsld2aybMI5dCe1uRHI{jVckw}ArpfHYB{&{3QwXCfCz;Ao*cDPYIXVTT8@N=%U zHWr>uoGsH2pE9U5&wh8xjE$@qybVg}paUCqP7>qu9}s|g4sbb#fh1D_w1a@eYn(RZ z*h*@5uZEKufW)iub>ftP_~UUKJ@swFTR0{JkF1XD#2~`;9mV~o1^$yJ%=h!=WsYP6 z*TN-(9oQGB{1d_V-BYTqr+ZWBl0%F)td%n8Pj^|tqmv_)yD8yDDWLO;sY z*k0X-fHL)s8hSfZM-5ky$H)%NvI>`utr+CNzKBRjZ=4w{-({U;o*k68*M`G?_nBPU zh5?y{JGE1^-`(yPy7z50KG*t!Ks>jN%wFpvE*xkrf=;%#<& z02_;X6ar3{`dtnraM3`GVi^rF!!V({DpO8Q4GZNUxb!eAGE&ZW1j8IBTa6~Pi)p?F z7-SzSd!e%LfCvcoY|CFI@R<~N<`pDkBT@9&@F72!4x_3|+ z34V&Hm;UKXQbeTsYUB!sSNM~mN@mAZD%;=5@+H?b3im?E*WQgCc5-yDK*Kvj1cj9- zMz5O?k zs3@o5uWA4vufmnBd@!K-_TIZOOe9r>Cpxv(BLEFJK=_;hVF9SdRs9}^+K_I-qNd5M z$}!m9rJq<1XE*mg<@#MXX^bF_=<)DD&O8?YD-3>HBZyb%Jlv&bd> z7uj8jI$`8zD~PyFpbM9yC^3{41Hbf@>HGBsgrGY<(e3%S@CXEn#5(tx5givCfLGr> z(l6|XZ)O#097$w0xMu#+h=I4>ygl*;?FI>YAuCZ9Ui-EbT%_$Ri|~ehkPO<=sWxF= zFmCUn)>LXt8+5xReqN7S>4v@}z)Q{$$CF39M;a$h4QLVlpD#!x&l8_{RzcKf7_u!z z=i%C?b!#xdoe8w=+B9~lz2;888g;rsJx&|_JSP%B`twJ!Km?!A|{I6r-xQs)$tYYn65Weo?%Bbdjf?Mr-8E=P(W zMX8A~;gS9^xOA;LTrF$oHHsO*Y}8TFxW~NH&>qyw9pZoUU5NeQet+30ay%8C`Z|V( z%*Bv;b05C*{iMlw>SH)kVMI3-jEAh7p{8Y`^Wq%}t}Fpa628 z*Vhme+^a{lwS1`(bb?#OkZtJYK|Y&+j9ZL}tDxGd7!1rQN#8XKdD1706qJGMb?{p> ztFzpAdvCv=Y_bzVwMKxYHwL~MO5Gj_xDF}(vtkZ3?BVf2uG2GNKj3pjO#l9 z)RLg^6#b+2(GirjsS1gtoCU)1r0AZ%8LYZn4~~tl2n0#92nWy3rsfy@Rty}qdRzXP zeg>B_NPL$7jPGr$mLS;x>t!?ay;y(CD?J;^98eq=qz{Kf^Qm?NqFspH#P!P#KtAxm zzzymYb9lbcI)yneK_B2nqDni3OV>{ortJkU4oxKqK;Os?EZ%zE&QlD`bqJD^IEfDt zUyfnT#NPcx4p7KwDcm#I$6D0`=IQ)?iU{))?ZMN8<=_;~rk@W! zxJFRQ_N>?@lqInBIf4(9AwfJpkPGepXnu2cBb`iC`%T6t{KlL9vlKhw;P45&baJu0=oZ7 zx$9B2d*+-}%xlb=9XKB~UF_mi0vHsA_JXAz6nHECeJ?i)&73s1wD@akr*S`Ba2|eH z89<^J`lBE)8#9{&R=GC2cl@2vnPB+9wQ4pYU^kOwKPZUl!$j| z4+rs6aZs=0<@Be)XO=l$mKPgD#HSCBMfn3>K6P!GTR ziOzn40E_>eG70Ijg{<1;12e8V!Fgn|E7iX;p4qmy8ljD`;9tzlK<8!K80#O4%+rNT ztEl3?gJ_37NhPe}(<3tbSe6iC@I!UT?kAv^^1AKKZ<8HRI~8v8WNx+eZDZ_8-68Ui z7;|ScPTjO>?{*8`PFPZhQa7Tc%iwB)BkiZei6^ZUt_!dkQ@$Q$Pn0A!naB~&qw>Z5 zm1ND}-K{$d{dwp0KBHb`^v8@;s>Up@zfxJIV=Krz7NZr1r7sU*6im59z7ji!TB&wH z?C`RMZk?e=KnvyoFn0itc4*8BolB6hNq;p9lgW8*A0F^iDd3?xUI-=!PAcPoAAH{LfzneISn99=bpY!(i=Sc*3~*b#ZF? z)4nxA0=Ds|ynK0hnjqE^QgPrj3W>A8oxfA9o5*~$&qhI<;pDXu^p>lIR8e7<_cF9h3#Ub^+(p$H$4uILN*RbLT#r(XrkL=f0^w` z!I|Vos1W;D77escVGR_3lk~cT>XcJ2qY||ak!(UVB3Xd+ZqZW{-xgLf$RvpQ(hsRh zoeAcMbX{En-uH%s?NG}qqoNL4t2h#rtwV2IHT4IhYPY8I+WO3V368-Ao3&)zAOpCb zzA`tgQ-yO~_6T;eF?m}r1ML3d3ypb^i6r?swY%V>MhHU_!o_(TCK_+Er(yI!;$>K6 z?zcGjHh6x%JZRv7q%swXdXyRLveo|(PsX4O$P~3FYOB^L@D0`~4vlj!+yzIw%eAS+ z1*Vw($URaa4CSZKVD*?VmA>&lfwRJI_3202%$8;KGI~d)e9Z|OuZoZ@q9+BB#5$FV z!@px}g}>U3Un)v|EG6~!H-}wt;+?_Jm)s3ZPh`935~QiRT~(Drtv|RzC7)##>C+AJq?FJO?#tC)p%$Oxubi>1FJ-7Cb{*k zBSq6OV0$Vye=kAc)@MdQ3|ZY?o612vP!+V&m3(qtYqH|y2qev0Q|}r~R$3g_?*Zgf z#o+9VXB!7V*lg=U*o+G-s?>Gs2MLw++tUVf&l3Qh z+UtKf4xM$S+Gt3)lve+UIgCTgcB`S+W9GR*pqRb3|K5(qMFax#1Wyy3qque^B}F5F6qH=7 zSi5$&fmgvy3OKeiH>&~f9d5%1=Rl9Xy=c>W3B&h4z}i(oP;tO)G!Jv2LBrKv;#~hc zb*>m=aE9cU>o?lB+2X%57egnSf~Zohbu{Kkc*exMw)UCv*we~b)XIN}7rhfR5!Idtr=rFnoC*o~82pKeI=Qch{vpyR) z3yA?`fa^gG5W3X+m8jGNdWY6t$#b0!ZDb91*&axY-bUQvHQVI<`)A939V<@AO_Maw zo^CBe?QI(B4YR3quvO9T@|O{P_Kfv!;vP>8Dii6eqhmw_(MA4pcG5&q1gwe~R0;&a zs>YAw@vpv|@LXZ@rLrItF{8JeAxQa==8VRj(g~<~CvL z5kfyP5s1A&1(_tj7QKU%a<&BAUPF9`BgC=kqK5-co$VzQd~51x7ave$&1dx|m83aq zl^WfsEfP6~{Sx4d?Ac((SPacC8L(V+LRg{U2%+a-B(5i0tw47-;^;H~VV7%rh#+^I0d&tIGB$}?N;`5fkx8=}(Ibp%Sq9Jvj}f1^}dQrUm*SNUsg8SYE(EmqL+EnPFs~)P#1x?RuDl zY<|v?F^Dk_N`($q<_N$zooD|7WS*&u(>!IA=*$?>{KziQ#V`&~^g^kn7s!OQk)M>~ zM)O{*Qji9V*j%TXOIhd;Xr^5-5J%o(irQcdoR(29D&4Zyb3ab#yuM z_UJ9cT0hhP6U*FvgYO_eJB6rymuyPSATs{3DL2qp$H+&M%c82MR=BV*708@-%@C6y$dVB6d01|YI7^EhTKPuE*JY*Ey_$^gF{3VCW zfxA-E-X_i)zyGHS8j*1ni4frCIq`Qk6eUtG(l3(twJsouQu`J0LOqu!ojl8krg0yd zoP{2v=11(l>{vv=y!ZPI0#h-kLDcB#D3n311fC`>K(}85N(u5XcX?8CCf5)9z~=(% zpHdK zuN>BDiF3JO(5~fUFb+z4A?gPkkjkN;jF>`-XM0Gi0rj+M#MDs7B{3P84Vr7G(H+G6 zmr`vaXjlH`{PZ8-9GWJAX7$Udb)(DT-r{JG#5Xu_eG3B}b>mSZM`H=#>?@e0L}q`7 z787)b6$2({G4Rt}r5eXQWlca*-^W%r(AU;3>+u}4Y#roTQ-WU5m5r<*j9$aRPEokB z4%#Mj38JoZu1PWD^mILoZ9ABK)emz#M`;b`27Y_j4{bt#0kOLV^LpOwt2S3R`-|4& zwhOfO3X{hUH3yXnQwrrzL5D+-r__Sf@jWK`X>a(7$I~?^Hym=egvXv(f*DpAMy^y? zHg=cJ>pOHB6POuTf~jse6i8cwFZYxH;xmje#TDd^4}K=K-BOf$6we$o%I0lyl@}VZ zGQO${DJI2vV(LA1^iNSjT!z0u2=An2{|hETSt}jMFN>hm|BjTMkO?&=@a*?uqu5Ft zgG>?7o(2sJL|ey8GE1DP+?^(er3dlA7ZsBmwDBf_w6tq{*M!sTbQ_xN#fnSo?}nN| zATaK+yC4d=0g_By8_m=a!m47(6->K^f5E~76+tUG`pc*H(62<{25GbSm{bGIV^7yL z3L#G8}=Bk2{EhIW|IALm;=E}(X0}2L4C2S2$bEh zhVW^E84XXD-A#6q1Na3=^%~HeQZB^qkuoTYsH!)NW0pNtamu=-pUifDQdT*ZnA7G( z?mYIGt?+4kf$J^xh!@dAijD8-o5XLXjNmPo?*jViCqdQk^ea6|o!_ZPaCeCb<^VDn z_tGb77S=v*PN!ulN>bq<6ZKUIUYXFNS#KQ^so47|4owUPwY*O*G| z?@N7*8Uee(^OBM1!i+4TQSszUigV?=?7Q4PTRV9A0D=MbonT!6qz5xI%t7fQ9HZ;} zHNqZqHq3&^q?K21ulBZ$dgyb6aKP=iTRYiD04^_acOWjZ{#sn9vr@kp#<=7S_pmfw zQC;lW+xSEydP2_NxdUGLXXV9Pq0~3Gjs}QdS&*KVURObS%F1%F2s-^|UoQBb%KKaW zfF?wcA9ZmIwb!^gickIw+Q3%#o_ian@7mKInr#=z4Vluc#9CuiTpZBD)^i158+?AU zK_>k08!@eE#B-XhGzFjBH(IWwr(e*iNTU=C7xsN@<#G~@&Lh7E^GnuwH!3GvwI zUo`zm-lPrFEx4%x=Dv~I&-9g3pU_Xn&!FQ`X4@?yzCPMW6%*aEXYdknd852wPioi|Ez;i=yIsKxcsQeW^@ zY7{OdZ7*Fxbi9_-4MqVfM*{F=KTNiC!(B0V8#qNx-NEz4Spy?PR{y79-L&4P7N7dx z9Ino}2D>}i_i^$rrTGbAr8Jq&Y5mTOM<9Ju6gYKHUv3{r>%)G2>vms8+|8$q37|EE zAe06I7na*vuqGpTK8?T_ole`&SzTcwW+hF819AgdDUA>V!b8hRKA0(2fd5s_%+9TMWA0 zfjHEjD$DZpD>$=TgO3WHGAv@ez@9O_cQrJl%;w5~^R zSD~G3;LDi=FYGsdS0gA>!JvbqnI5|#bq?x4bX_Y2j?6|^tBDhOq+nKT)>?(r?zzEnFUt{ZX9&dXVy|!++F~#Rc`Xj; z(s*dH0+1CyfkpSx#9b~SvYXZzJ<=6ZYs_1nLCns#%|;}jSD7(wI2njybSlZi$1pBg z=cz%2ATXK0735?M`@z(AkfLC<_MHVvQ%`|mX*aFOL!aS%} z@;vY{WDW61g(lP>CS^Y@R#G>w!u!r7B9*#fT!u@?-M;B>K2A{wkhONB(D`C;4#@ST}+Hk3G!VI=f8u1AgFkuM_6KW-cVok_zuY9MTM z{hEF!S*bddiO~FvL=0fAIb4V+?(uyz)}1+2asf(3`>E;9AV8^M#B*C9*wX&PINR*X z7Q*d^Y;5@`;waL^&}-i$aJe0Xx;Z#sQ_*ijgk0WK-k5EOOzeIVlGgji{1E<}9Y9~q ziaPCCxh(aAxT3sbkOm>m2b@ADlr)CPg&7LnNOhMuU*Ou?-GKpwgh&RS&cp_)GLr9ui&faV-GRe-6*U>?9Hm6$of5I8w+g{UE_u=~&J zZ=XB$zP8@Qbi>&`b&MV(()L$yJ3S1@?!@TU3s{{s--(EDM#I56%fKaODpCFwfl~$3 z$RiTY+SdSdTa9-yK5bVvn(pp*$i5X5t_!dEEnZYk*{KmX3Hj zU~z&__vpY!Kg9f)j=odr_u~~1*U##>z21bMGnKu+V#2Tx4}UG|00Pm9&&JOCJ7(dB z4p9Ju`~pZ7CW!03`>gbM-eN1u*rEV_NqB1IXa^`L2kG$Jb>i?l8&dnC+KC)-mM4;+ z#jp&_hU*>;kZ>TQ;kR20Jy(1i?7rnSgL#&R*)v%*1r#M_`n{$FaPs5JX*rU_z%r7R zovKG%^&FLG_0pyCUYK4}wbI)2jhMb`P(ib|o)^AH5HyAn`C;q{AePD_Q9z z#tvKgX5iXHS$P_McbiEt?rPx~Fp!Ts}7>yd|# zmNH3*CGX@NmBfa22+r53UvoZ$@>~>yr)_&CC_Epc;LD;H`d?pn_teWSTle@*P%uB9 zzxx|?qKt{zV(ftd@+gR9fYbpqGZjpk>YjoRo)tC-Ipcw1Vh zBu(-_p4sQ<5eG(_lE5gIsxB~FaW)2AdQkfgpiUGWxC<=kCZp-4vnkls&U7+Hq2-X4 z#UlVX>l;wm2#T!1DQrEkyHTJUmafW7&whCuN*#c$xDM0e@8S0oSL+sM*5;>P69Q*ZYG8 zX)^cJP_;7pQ!($xVn0u=+??lf_qswG%T}3nOqIYe?Zff9VsRk7YK{L?u<#g+0b)_grNWR~8VD zgTjeEq>*yp1&`mb-ZnRPVlS;_d;anrwv8(OLqF1G7NG)T-(EGPcSOX7nN~jJl@Fx{ zwW#rIibKGA|I~5@_lv;46QI+PmI8(l8G-4I_V<0b5jZ0MwGIDJO%rPO2f!3{F#?;GBv2KdMA*~z>|CPXH|uT^z|RAl634} z=pF^!q55~-`QIBt>>6@#(FFkVZnGQqHVOVHd(ZaY_V{16{w?Q)^8YEWxA0I(cd8ev zeQjSZ?yim1V%E}LPQ9(HNTlY%X@xC6bwo2KF8^y52!1?srKe!w+nu7TvI9O0w?cXE z*!nQEFh!*t%!JzB>olR9o{D-BAHJB-)BS?!zL z8RV>6Sp)&E`$C8leO^BP0_wq=ml4X7O#f7IU&?UUq0+eBx@6Ff*EYSbAD>h zx$#z)R^r9=md=PbU*3o0%UlSfRR@V;f<|L)C^ETeJQ0lk_)6hy|RO@8~;=ry5bzTRDUg_)j zop2rFg$l@>WzV89{RwS9-yTN7p#+Vua;5Ng>S`6|&*HrKlPAMsdZq!F1B+2rXsi=h zRaq>NS_Ox$l(2*$Chr^i=ochMI+MgCEXY%5M>Y5Ib%f_)p^Pu?m;CL*3oFz8TPw#a zOGgewP%pxQbBw*8-q?=)0>6hdw%vcq<>EZsmRfFoZL$+kIl|s-`8WrVH{bquX2oH; z_W?iu(yPXI0x=5fFISf@s=sdP$L4dl^j<_(tPt@x!3WBQ*b*P_UF)1XKKboeP$U>P z@+gp=Dun%?e66b~7eGBG9af|wK}61(T-rR7lEB?3V@?s2H^6)G*1vE^3I2cO0-|%L z8+QKa^OGR!9D_S%vm(=?(oyfyb0oB%40qg(c=Nw=^}m(fb6pNk(;A9B4?H=E7y=?!AZK+gOMZ zoQivW4|r}~zZa(VM9s2LGoDy5`0>r_h5>q|s@Y|)w3HVarXJq&d8m%1_Q$Uz&Oemn z+Cof&?Z-+Cq)8NRJE^x{FZ__chK=Q4cH;|MI7xTRedfVHEUdy(y!d=xb#}Rs&rdH; z*9S8(L{h~}VwN7n2U(YVCtZI2a`>L9>}OA_jEvVA_?NLQEW6+T^*rU(E2TDL0{KIl zW$di>M7DQtJ*iNC_Ghz9E83JuM0aMZVfC1{y*HuLMCG5QqGK(ZeJ&+cJ<9l_9qga@ zBK|0MpfK+CpWU4-eEYX@V;uTEr(Z7=X2E_SH8NL1ztnk?`=9 zo`p0D$$dRL-f@&I`KyUJo6i&fXj7>PANQY~>jal9{83MQAyXiD`j7~{?tgX%f$@=D;CrS zF+}JcA*n$}i>lU}YdWeG>pfaIspj1jY$vF{+w!mzujbG88V<+)Rqlmt>`HwKo*TE8 zXLZO{8a=txxqLM#Y%?cGpF`L=EA%BvZsOB-ag0(57gpBn_@`GZx*Ujoj|S$ND}TuA zxUPhl9{->(h_7Jzo824V$t&jnQTF#A*u{Sucj7SXkA@9Uvj6^D!(^#0G#jLX8-?QT zmnzR3ox=pNA}+C?{`~LSo!ndT_EAiGD3!088XK{3(qH{aM&Hl>vrY=9%D?KoJUu2m zsOmC!U(FqgX2~}xiOu-3e-IfT7Sex4q?tOZ}m{r)d9mglP1q=Ky|rDMS@ zU(GM@GV{!IY|hIoWBSVw1I~&@ezZwT zBs2h}@hot@Sek-lyyGdC#L=^P)e3>H*AZs>#ngK;wfyr8_+WD0x5QEXqXP8_9JxO# zxNc1H@{eCNjmX&5^3;Kf4!bO^sD1w57m9y)NX9vJMg~ul75f1U+5sA*37w-~LR8pw zjsIG~0z^df{urUdtN-B3cNV!r8r^;FmntC4v=c==2qwtc&6WPX`e{W7rvLG7kG$E3 zzf6BIzbX>%^iTk8OSZ~jv6~Wh9zF)@_#H8|Iul7L675`z1;Ru zR5U!_?g_>iJh#4ktMNviVcsA1G%CdY)88L#zRSL70MSy1ZV#z@H4QC&sd8Wr-j!Qz zY-xWqrL>7t^Uo=Hx4`GGUwadu8fLGcl!4+}Xy_hB$4FZ|{{TT>(osX`>na#zNJiw|qe-~9L}^Zu{d(LG5a{fEsg z#=8E#jNf7iY748hz9!NkXs~`-vSl*PiarW08v21xZ@l}f1@>m}Y4A@?UPJr^89%KI z+9ecU728uzDMQh{_)^q(^uSQcFw1kl%OZiEFENEZ&h%_AYoAaD9Jb^OykL8;q;LoP zVdVH)7bH}Zb-l1aT`qp;y)J$}qCE$??HlJ+?s;|t$idNiZXEN!+=`qg(;l~2g9ES; zr5#9;eHJtVpsNOdcVUvg%p#Ph%c^e-*1J^6*c-1ts9;CZ(Pr*ogr)tu`?h#%vbIDS zG9pNMQ>5W%*}XE{O6oh8cJJHRZt>*9Xi|A+5+IjN;4dt&<>+X{8>3iS7ruAp+RHmrB;ifMb?q2tFKWB zTyDRIEVnEDlvbmE7_(d3%u|8>JTks2aigQnPlurR6G#~*x82rMAtJ3)*?){$e-h7mnhbxX1_-2<8 z@KQgJm9D!+A6-~GDd6)D><}&jVn;1e_PL_e=dVZ$Bwv)a)QqZ zIl3e(i{&ig;5I+)k1PvPO*K6EiO|N*X=F(SVxeC}#4L-zw$1TMXBiRl73FJX@vuj3 z-z2r#q<>+wi_o%hFMAiOaz9+@qzh2{Y8|ASk<1=`@7YI@rLIR}AT!4g=#>YRr2!>t zm~-{OZcYF!-;SYX6LKzkbIZVcu9WxP-KEM#(A3>H1j!b{JB+ln0cd5G;PUsTY>8~4 z+r$dQ(wtb)Tw&V!uWk_ko+yLQF9w&IpKL!25c`tI&($!jP6qoWHlM?0;M*P*`3)_X zJKTRlc(z(rq0%09I7m<6TKyXOS=mGRhERO>Y6IHx%9ve1H%ns2Q1;<#(U#-dC>A|E z5F}fLB5bMWu(=HNfY^Kc!K%oy;O4{M=z563vNbOb+-ZK$@87R9GCG8me9f+k;UjiB zQX+F2?Yh5o1xHiK_0>n!TbZBB_rcsJR{)?T9L+|dtEdtMA4TB$5Bm|BpeeLlyk<7M zQ2Rb60-91t5g8qR1}++vv&qx1)&Kd#r+9ucgo?dc(V}bsB~`=w*wSupQO9mjI>wgB zH;$4qH_C5hkfu`VhviF_W-I(RSO<>vqtUP5`q7?bd>*krpW+P~f~b^&ii+KLe@sD+ zJRRtJ^3}{XGpMRJs{__ex?gQ@q(**VtJ_xKYuB7stZy%>I-S#^ParWstG?~D{8Qpi zj7n8mi-R7B1Y@emEC+;nT`|dm;1Ug&?VEQ1WK(}&_kJ>83ie2+WXNp|Mr!RAU6aiO=UNvB8Ny8@z8!@l3G2z~Lc+XftgIH@-T?#mEoqNf~rs8(rL zV4RELxATr@3oQW}H(UnKXhrlB$Wp$1Lq~2N?>ul!n}S7>MbhR1Bv!S*r3zplndl~; z8%`vMbn2o}cF8MHYa86W55TN4)?S2xd0+RW4(kO`Tbny{Fxd}Rnt=r%Iq&!z6rw*;&`;6@2VYLa4f>91-h!en5T6=srpvSa0z;`7 z*`y3@UpA}G86Th(b%g4%1$eg%nCYiklKQfKLO*k54W7C%oEW32piVFL(Y1{a-Re$3 z6$&n^LT<`g$U%DR9Ak#BkmHfySX!WL=XrjVS>ib~w+lqk19$In7*Z3QH(cc$ZQwK% z<c%tPnAW3Siv>``44R`3!qTkn@P+%2v(b59gK&*9eao@G)l z`I+W)Qwef-hn>AO`JMkoEub~bwCyyzk8HtDy&(a5aeE=40g(Ydu@9nCB&-6H2(!J)$ZW@sQrF?r$3=(f&j~pU^#Hhp72CRXFfE9& zcW@7-civI~CL%ej0wEs(xpYf;QTmsH$odl++merVzeyTjxXSLp!1k1^l=J%5)>gQ; z(Oo`FWD&PZS|){SP5%F)IaI{Q=>ntl%;<^*ABnmDN_uYbptgju>U6w`QmUi zsX_!g-7IQ*7H6KC3*Vp5`0G7U3HWma?l@z~liXh(}mtOi&+3mo^E)rs1BeEzpr)i3iFZ9!6AX$@&KZMtRU9#Sak>KK4(|>q&K=of% z__X@se)rG!`466iL#NVmeJ{U$T;$GpX*Io2BNE*Be4d;KP;+YXXQ#=NSoqVjegDsm z{LhLHfpR+k`&XG3LLE4=hGe()L-`o9$h_!pmf29yU5vnR(0>+Al_&q{@$hj^(CPM# zZgqCN@!oG^Gaf-r4G0!pR$w6l;(s^DopBFXE-aNN@z0iewV8Rn&<>n0be4x)-{yPo zuC^3U_twO#kzij8ncn|y$o|ty|BH?0Y;+rie3|LVhOR{hT)wcd)n9i1*G-xntmU_v zuKkpe@BK;a)~{sVwV-oh(tf<;A$*T zOK2UJV^Bmy(V>#g)H3flr-}?Am@v5iJYoL5IfCbL3T=$LKCtd%CM__8^bHLWP|K|) zolU5)gc!>pfu;urZUdRbyht*BT8ov=PcaJ>+4!gBynOv+_nJ`*u_mqT$R_l#c#Sx+^litzb{cX*> z*CXuqwl-u$7LToI*BD{+H+??_-b(77FgS1FnJZ&Pd=QcUcyk(t~Xqh4VzQqfm4<}9oJ^HY!V_fybK_A z{$C+`sqBWPjDj-a4cc?;(=7K37JKlN-K2PnoU`HVWaLZ?T0w;666|$%&0L%YvDJs# z$D@1hP>(I~k_4@4a^^?vy_6%dEYM0yGOa?-9YI1Nja^63J$%j$WWUaa8Q8DgiCIh~ z33x9w_3nuMh9~{W+50sagNH(cTe{~6UuZ<9)4VW#PrDHM;lKD($3jj9NG^#fYhB4y z(SwZZ(5X2k^k4y$9?@F;dcsn5G?A!Xi%yvKh*qhFS02lKhYZ9{?FBp&@0ZT_UoVt0 z&={AF;oxEM%9lH*ZA2 zRjw1yWuO33Ag#8lK7)2GBw-3580DVzuHZL)WfhA$;WJo7>55&U6Dw|lA%u6{^cM5` zE$7z6ZL-p~S4k1Std$-n0VN6eA%uZ>E!#|#8GBfyKICQxF%jd%Gr#i;rSn+@B{gB8 z6aOt?ggm@%?N@xW*lx+9`#3And3eY0ajtfbbh)raG@G<)>-l(0>w#$*n}H<#IeXoy zk}2E*2}A$p-kPA(kjO=z@$h2CzjAvX&4!`zcsu)qolj+*ImFr9ufs7Bfh+xk#_d^( zF*t>~9G<(MvFFO-uRPv{D$(Z{#e-D{wa|How_T<^j69sQVUsXYY?TVd zScj|AIsFRXzW!wDZpzu)DD;lY)r|w9u!Fder&rj{ zLTOJxm$keXvuVP-sh0N<3SP6mWUSa5j^J>3V59qrtMm*hol~TWQMZ9JuacLV@1(q8 z^zwmE*P|AS)3@O-&2b}okt_EEg`L5%?Ll$c^}^6r>UmtD(f-*vHz>+wgX8e+U7S0$ z8+|pD`c_}^A~rb`0-T`cBa)p3aaW8Z$Qj^)8%>wnT~m5&TECGOVc_hX`c+IaJA9{T z<6g;=p{CKgZd?0XD7#}^-x3#5#HTT?l#JQBWfkJJV^wBJli8D7HB58iFVFV}>CasD z8IY^dfrKLOe#1CFQ5R#*zhQWF8oT%-y!m9c^2f90H>Cw1H&QUrf5>>iN-QWGKUV+z zo2wL&QV_9uPfehJXDyj_dp8eX=XxKyTfs4gTDnp zHQ27`YnML9Q|t6d&HO@lX!QVXmpO|V?JP{5fyc9FS>)qcd>Vc$ zN+j#lDFK^%t>A*+yT`(;Smk~$d^+@_aS&}+zvoWD)u-%o={)z`#1?@}^Pe_rMg%UwrGLy`~em;!P}3kKGNME@UW?;RJ_(yR-cP!JW6 zoF!)v1<8zxND>f`AQ?ePDp@ikDj-2}kensw9ETto36dm(M#qnIt!W?=@bU?Bz%oyS z7Fj_w@}}MqAlnLZCt|ZAQYiQ{xjA7DYBaC&)SpLsG^k}h3~8@`w!BI~E%j1Q>THz1 zx+cO?{cXK@_w&<$XNFHfe|&Ln3cQt8gxU6{%B;?3KPoX=aozvplB~)pn?Gb7pRH@H zL?$_cX=lw(p|eIcc&;zq26|8e#moVzvCZ52bJKkacxUmsY)x)LOedFl)4RL_q*lx(!*TynBxS^-FgwWYsL1PK#R%< zR1-~eb?|L_LY73Adiuiqq*soviDpHQC~m?-nPfPRc|bF@7b|{&LEk%quXK7m?0oUD zOEujFn?tN8pI@g~uh^&j{6*zKi^e69XD=16kg%Tyo$znz7%}m$Wd=WNsNhsERh=r# zoiIB7nd6ahbA;PimfDHm)=f>rz{-xF*E6=u+c>D8(lt3cKUct6{>32Dt(WMlvgd^F z+oPJp+^hn{?dMGD66dw7_auk3G4$glnN%ZGOrUluvY55Z(p`Gx(v$3_t@|~iy(O+H zE|@sNLJ^i8^h^*Xg+@Tlr>s8RooAt+z7!)f4V(L!0;F5(u``m!X+%AsO|R_|Vc}+3 zM$M;U`%>^rr;LB!cWWMAt7*a%CYQ3%EdV1Clmcg63?+rH%R$C7_BOA0nG_x(VaL9~ zI3ZmVjr(B0MtIVnvEiT`wEEMLdS!Wlw1RiMG_M}3>R5&J+pGS$m9C6hp*xb+#IcH6 zNBm)lA6R&IjJl$`3UO}(b1Pyl6D_S5nBa%A&Tv;!koY6*Ga*F)C+UFKy=2( zviB}Gw^QR3wa=QXFmh@N!Tk-Fg%RaR-OPBwM7f!gbB_fyzjF*1x zx5g+{{T~A{oU-TsoO7YGRjCj9p0aWfO@2EDReaItxMr`2!|1;l+zC~{#TK!)Fum9G zy4@B&vZ{L2x@2~0^tdzlI$LQzB1o6dS^m6C-_pLv2k-~dEX<$^@YEQwmiHyfOQwD-xd>BQ zP*c|a$3Xw#L3_BcM}eDweO7L+(3|o8dZ;&W0_qTQiFZ2y#)%j`8i zalpJ4tb3aLDZDuZCUJpJh}8-tI7%|~3?A}n0ri6lY2YO3!0wv)8P!Ao{@S{Xfs|tZxA{0jLhXxGUTjwkmIXqLNN16yMRA zbrew6|Naf^u;TS^&EUF#HHl$^-qt39V3$5Gv<9F^o1ougSB)GFfcscb|FuYV7h+SH zc$mJ^g35?ce$#A;PNK@bCDy5xvVW~-_zv~4Xi0RYX`qP9AhMQ+CIi^z zNgYS;yj;Vg%g|f5H*dwHeRR&+~o9x&LK|B{mu?j@il-U)?`1^k^y=Ajph*O#U-5qeJ*N=>^^nJ&2$!C^#{G( z@BL;)*g1a5NgK^pcAGtl7SPvO{JlQC#~1#xnSUQiJl30{w|U%C!9g!3D8?nPwtHI;^3IeH{r>kUw+ zCI&R>FsK2^DDksRU4Zd?J71OJbk$|Bv>0mjfdHXkvQN6!0&ed7t*Rw*wG)2lLiT6^ z3n&P;e%)=*@jXxdgCt&>gISu2i*4(SdHZb5<822JpWxgH|^6@_8i#8)Ie6VYZ^U^3~kPB;~0poFne=g3c~9#ibr( zE)lZx%Pz#+wzHf1Typ0U%y_*Q@6WjgI&-5C*7$>G6H0U{NWriXZJBS@qlu0_ycb6; zBv#5jpJ{K2fCyN<5DK1%`(@xNm?bsiK z9_s@%LGKi2zJf!8V?-Y@_4Il^{egsp1)%oDIIk`8!HNrGc47Rc$+F%aweBcY=fD{Q z%CMQ5I*L2@V^*WpH89YNWB7;h`0Yi)LfseVZO!e*cbJ>cGbEv0{bfC7hU=m_Lv+`_ z4kw6gU$_y9+r&h^X%z(6(BR&{Dg2VEeiGJKb(%0c6s702## za_j5As6hXA=3PS%OBz@T?8;%+`aYzuUz^W-K1z)E5Qa_cVMF?s2#M`4@&KZ}45*=? z{!Uov?G23(OZO@*USGGlTaYVk044Hd46uOibUV%x3Z^kcJ=>2R zWVJ-lhO_vp%r9?ylkR%#!RKxwuZOlMlSk@;HaJyZg*AQnN<1$q6X*8rF%`IDK;)2e zdl*@R)&o#m6!q4c&`gAA+ONFjTN5-moDj%Edo2^nkERn8QfOEf#=uIv(fO<&hE1R! z(I#B%HA7M`I|C<699~^awcrc<=K_Fed&L8VBJngi7uByc&*NG}EWE@hy5OX}`_YGV z3VKP?(G3CQeGhdWuEQq+Yre0B#8)y}q`Mxx^Nriq;!MhBhz}>^iA%5*g*=76y|5&> zpLgf0ZAdd-fs3tg*m>d8ura>SC~b%g8Om5P>=rSNaXedy=n6J>z?!3_(6D119F%$Z zQKPyTrCxOr6rLJAL&Kcqlrniwvh5+^c-xRUlsSoOwa}7SxNO+%zNyXx}7WyQO8&5mwt$b;{O&_4g?D2TRX*+Mo)nuK> zK&tvFd&a$lp{Blh4-T)&BiN*83T1D&W?gHysQ>QiM@FeBp5I0&y!KbZb33qcp_Ip$6isv7E0 z#``)Qqi0*_uvR;$3%pK)|GZO0C%{2_a>J(p2YbD!hjQRKnL!~gS;Cuh`&S^?pmvErPJtC+u`5PH)n2x?G=t0mvmFhK2N5+H zkEl-alaigl{(fZpFb;4Of#`_}ND>JMjt403&h{Tfbc^bbK-2HGiKbn*Z-mJlyf(ut zTzpaNzAkgx)vUuUmmeh9XlQQQhuAtzUVJuT4Kh637ia)dLTBb|@0&0l1g)yK)%!Mzpbt=xwC9kYH+ z>X%gi;!*NOB?o(?!$2Vkqgs)|fYJ{ZvmueMT-M$G2@m1b?4RzdxcAt!HC8XU-z2A= zOrt!j;9$9=->afSzFI{v81=Qb`*P7xssItokS0^%yLWF%5)r5>d(-*zlWiZ^T(Q5x z@OrhUtBJu%{1wtUS)B$CL)oMlG;(sIDjhNXgG|?6`Gq@jvI>+x;5%CDjOQpII-H8} z&$zJtfVr~f8j~|%Dw?slKXjy0Rot`(J4fo|_(INW6E>xKpSijJTx8i7NNU9+^j!7p z1eLV+^E6%o3fRl>&g%0yw6Ny%7U52<}oLClnG zZ3^1>aYa^1_J>5z7LiK*b%xpZUy_8zpmGj&)>06^+XQUmu6UZhZ+?d99=vtuo8N2(0`yYaiB>o)}tu z)L9>l{RCzttmv&CM8H~aeo3c<{y;jAhvGjuPqx~>pRIe~<$#@HImNv^MM__=P0{L| zG!WcmFKV6ybxNEuuXD#x0r=BC%HKFR$W)e_cO}*RftX8T&wi3u-XB{+oS~_4V<-`z zE36|w(vuicmHi+7U~4rsZ)rWui-1e-vKAp{1LZttPcUK!!&Ku#54D>|If7UHIEbyw zr8yq_e5j<^cfvXcU)nnS3;apo`h1l5{}xY}Ux5ZRWc z$<=R5obvx>ssG(~xtXQjRStK(bp?U>)a|DGo7M=22T%X9tt?ArbX+0l|M+en?@^Vi zrHEutoWjP}d@4$o5To%ZZ>)Rdhh=+7W?xYuCEj=;cMUFUYaZYN-)_1JTC%qNWwUqg z$L&z;Ra$zv2=I5!HDl!jC(XS7#v@9RMobZL)%oH-s3$^%Fgf|Skpl; z5HaCjnE@AVQ42v$WXO3!$1!YkIk_34EuJ^Y4}WqSRfC9`EgE zZH&(5yDEx6YmJVP?A!6YyA^XMa_mz)Z@4s3E$C2{-0;qSBxeA;i>BMZznijdb9C*# zHKh)gOGV*2VL2pOM89yBdgtYxF_I>NXZ=uiTwZe+WC0i!k43XoLyX61x&&`6^WGB= z?RUBx?J}}m>)`yNo6A4)Gt1%0ck)Qtj2njqBwjJe+A+&{XF>H9QQFf1jGEDuO=$&Y zZ^0x%PfADV|awSK0~1(A2_ALSFKf#^)do#xQq)at)W8?7CEb z7Le)$ZN-MKe3q<& zj19MA$RRAOnYsDR7*JudA^GcTXy#gZy$Pth2*MvBa?y7k>;peby5Pc!&J?81ZQJ6& zMK^tqFHhZcq*72?{)nNu;O&MF_UOnfLDe~tYdJoAT!qs?As&xT(sdr_B0#L&6lkr- zJ7BI2V!Fr>9PG2^7e(AqWhbj+KG1Wq{z#Mfm+U?#@ z*h|b!Ul%BNF@biZZ9CDj>t3g7s3h$!vb_0~MGY)kK6qu|xkOz^y8)iuPUF&elV>|c z5TWcIipDoa&^l`#V(Wmkk4v0FlFcp@Q9iG9ix_>JsfEMJqlIe+=b3;ux!+vTw3Xnh zpcu6l25yC&&&AozPLZ9oH*u)!5ypK9(-=2mF36RVibpv_I}yvkt9O2>Aj+iKB6M*W zSTE!=RkeC?ujz^f7U!pOr*>!l8dZ2c>aRTN*-_r@RFErqZI@H*wtNDk3@ffnUD^YA zgamgWVGHhfjX3ER_-Fvs|SjuQZtDOn5vVPNM&f{%Mn(4-+ zkyc-&-8D~6x?oJJgNS5?QL1}yrYL-t#AF{2Cw%*KtS(Jk{8c=CS$xaC|7B431)Ybw zMXRkGQ<^LiiYf*jG~R!q9{`<{WzQJkpLHb8E~$s|?K10eVm9#KD%QH$oiQ`l3c)Rl zM(`-c1;Rq$&0OqYQ+hmMo`+p|n{=zG zOeSEG{4K4v&>tPKObU&)$8$FwIpqn3s>quCTPsrMXg5(@=o7+yxR^IljSI0Ik%TdI zX|JfRu{d36TV#;s=rJt(7?i_Xc;r|L9eUp*U4r4w?qe(;TRrM#^!K94JMN0zPFuWB z9Y(#uEoiFE*cZ}WkH1omA4B+6xYm4@Hn+keeA+MPZD|)+Nhw;#)7-uB1&5t|vEDbI zh*M2W1>7oUgQ7G>sp1t9rj^glW;245;oVM^oV=+jyeS$Oc-9;oWBiMH&g;+(JpZq< zOvBUWo%{L|ke)YG*`pZrEpw?O!sSoqow^-mB=nt#GGE?D#h)kCPU$`q{%XBw5Wu;t^$WN{+$rYi)6z5rwf zr8q)iW25zW%PV24n7!i(fQb0w%%(&~+8ID+LANgqJ1Y~Hf9ZqM&dyPT00#rF>9kRq!5_ECg2# z4BAf)-k9ZWzYRBWf9&oW+;Z0jB3V9BVJkHzbQLt>J+$C(jiV{r`jhy3p@&(nke+5E z);d1TePelDz|cFIwdCGc@mS5N9b<5i!U;%|7i{=!I>Z zzxYfQt`itX|CaEG@vl$2tV#zXbeTP|2m8$UJvcLy_mPH4?tYmGbi6-da;ki?VuH`! z-*s&Yu<+)C{ErzlxGvEe2IXLRR?b5_0nXQao6QOHMN&`id!&-`oYNjj)nZb#tM|V@ zFMLTmVbJTAH+&mb&^3C-x{VN3~wp#WP4`STv7X9x} z{ypN+9d+E$1geWz&;8mj*_HhBjL?Q&#AE+wEDm4SQy9KSlktTy)UA571r|p+_5iB1 zob4D}+W>7wR)W`RW-9`E{L3k1$2DU@gIHO#f>(VsO+TDUgV4WfL-O(kJhhSn)mTWl3jw>U!-# z%<5fc#XWLXf;5{mr{0SjsuQH^QvX=AWQPj|yhr`CLb;LQWO77=wl0c`4eSsfri6UD zWTo6EQT+jO$4L5=xP@?P(I8PTy^J<`1B3RM`@NUb(VrCNJWHaaW}`m`D+K&KN-IC) zR!r8`rOUaF|J5Y{cjOMJRCojsTCl;$IlL0a?!+T6maO@=WBuz7#GhO6ME_HtN!Tb>|&^F7B8WA1GcAIq_3*Va!lTG&LMz3 z7kJJLsny?R3G>~Ar(_To&aMd#(UeFP8rDU!mUgbcE;bCh5$gRT=BmYK3L(qSueX1} z)PQu<-n=@QUQWQI*kEWgt<=f{)dJlk;!%ibYQuFfr3opWAZ9oBeip8yEVqf8pE!d# zp`QGjoTM%O%q-L9_kQ2vzs@pEE`FkrCgaqSF{AsL@1R#@zV{vW8RC!CKAtX z$z{1o$XW0R*xqVV|IB|bLhHjnrrP<(R6be1Kz47IdLV$KGWV-1@AqQ^p6kQNQ^%^_ zL--E4No4YyQOKhe%k(W+!m|xywaBYrBtS_ZAM}?Exc_mDlR*s8KMOy}X9C2ymTp9@yUCjtB|J6Q1+i_#5Ve1ch(M$#-w&Ox~!zYhiGU+r~A_sQO2 z>Av!Whtm4CEk<8qnIZ4)`S?MfvmChOpH}VIjy0IjFyo>G3gD$c21y9_Q^?PAw~ote znT=V4B=MoM8$lDG&Gd$PBGvmr#@x-7;k`NTqT^gK6`&-yl7zwh0fcNyDIXa)t- z6#YE`XCgr;eyc(?~NLdGRAX&F(kF z55)KK5pUtk@fyGWw6kV>XMbs&Z+%N~Y7PX0Cca3v-;7Vui02si=`Bzk3HT)(%lvcY zKbXfqFGzj(ndd>LOt#um&(T+ng0DiomJ~?@6DVal9#`qwkHdJ;j2m`DN`FB2hq}5j zcwze5nCa_hi%(_X!nM%?EES%yf~A9l2;_-*-R1i6@srrG|?8bJvCY|QG(1p0vz43 zgJgR28~4R{9))u3i+m+pHGMP&Z#Gv5Y0k?bw(P<*VGg`FkJ~_t^wJu{lvl4ol15M zq^glfdu^@J!2A_kE?;z1mfUYbr-hJ^8<;C5J`xNPj$hwx*9!M%5xhFyQ#UWbCt5={ zIfAMsRssz}6-QGsh}R@yTn`+)ci=nG$j~dsJZLlaymfdO!x9P8$L%&trsA*ANM(`~ zBPC8~`fv%hW2bF2@@yJ?JR?7hJ_#o*%*N|H^7!4C3x{5D4W)`_5{BpmludQuQk{ux z&qF2Pc<9Aaz+|ZHAX7HOmW8EH_25lH*gr7zn#Z97`oMlQ$TT!eF~UUYBbbL?_pp{T zv6{48Q^M=7jP31Jnv1xhEg+r)vb$|Zw#7shmV=LXDVy0eHhkV^ukOSZlj*)M^vq5d zsozdbOHM>>&(Rk*Ix5$GVJ+?T&3J`B=j0rNaB$af`=Gg;&Ii$+tvht7&8n*L$f)6+pO%r4*?I5MA7pyNj^wQJ>Rei%3zg~m37u}|Pea3O6uvR55T|N$Bt!I7 zpS&elU<)s8=jARmgJp@UiD9Vnlg7TDjOTTC%c`eh3vHBl_iKf<1i6H3A6*)En~iKr zVz_uY^7e>*0>Skr;~hRa+rTXLcOg^FGKIfdUFW@BPj+1q^v(6wTD6ggN{*B>@lQL` zQtj&aWr%VPf6>m zGE<<;@w_d_gOw+c(L4k*FIoFx34HuPubW*(PeYxZqs&}n;}2OZiId$fLVyKKGSIia zdbv;5Kq*^M@2$*c^!LzVi&I++4h;ighDeFgP;fjS2*=1kLq5X~&$ps)_uO1v2?_r5 z1Y`@~r+SCQiUH7ycrO~mYL;1s9h0#I?OT@V*GkBq{=r^AgNUb(80qq6s*VQQmaLEB zm|X-oTspLy&99l`oG$73K=C3gz2fCd1xr)Sl?TjmYBze7K|96*iHc9OA$bju~lyBoc1e?z;_J z>)YH?ioM-^PG0k-ROf9B0S-KwAaQ3J}L40a+o?0kI(#&{3 zycb~yl%*YZXJ~vy=f>CyaTsJaNLTiGpB^rjjg<7w+hd(#Gd7&x<`5L_IGnd_t?LOU z;>*>;&|ib#v7DNcu0B$)=MTI@`VcUnwR)LMv&q?g5570c8l^-DJ=ISc+RVZK!UUw)D&p_MK zK@L;wT2GLi6k}RRaA_qFQLb9}Ha6V+dO6x_`O*!!uJ`AK-qER5q%AsG7jpcW4I7O2 zTX@G+MdNKEph8R4$t-hb&VB}8>in`eb9(5gG7FYU%O)|UgNaX5L$5Mh8P@P>^z~B1 z@~ow@jJf+UscfaYQsF|TsuQuLt>q^DaT_2JE-&+Ew89@SsWl+ffNpJV(L7P@jqWwn z!GcFtg7Ex~Pn5~GM_1IHLPTBxmXq8Ycx~T&5Xw`~IY2;!I*PTl9(Cu#9`r2eQ&k2; z{{=2_VT-_H;4qYYsjGpY@EKt=VX2|}-cNx5#bOrH%R>JFs{ z5lsjvy}{*xw|F>yWXmbU=T`}T;%y@z0*=3oS&FcoI9wdfE4~eH{cyWS$W&mt&!U&Z zOkVWwufvXp&Rv>sXIJ?ecUSO_tu9YChtT%Su@|Jp7|vLx zS0#gms*I7xzSl80OpDUx=(O49?51EgGCFc$&#w9`*-K?iGW%nyztuUsl3=c~_G|h_(1R(u&Dp(XsTq&0nf*~M`Y02ktskJG_8QW~ zVh5Um{yNXk%Q#E(*O@zfy@yLE{lqHQJv@~6@OW@nHGSMtOWybR^x z`V@V+7s6Pzw$gXahjaI6<*4l(<12`1?ql2)W-&OE=`bdmSJ2@^M6#5W9Oe_M)Sk?a z=(%{%ms-U{kADVgoi+uZ#bbkiF3iENn0zDZkpm4=<-P(+hR*YXEyOQYtqQT%*Q(&b zf6Dx<-V1io@FK?Q6!Z(Re-$A=2@@WBxh%f{eN6WkyogZW-pK%!j= zqj5F~b%UC#-xgx;Y(G!ko3}q+hO30c$$EE39U9JQhfd%y`Qg~y(Lhn$G+)IKM0-TC-y;G8chbB?XHs%S&yu+-IKHoZ86G- z&Jm7S*h}qdomKWX?KYT?<4_@pJ~Q8gi1mJ;LqbR)00=Ur9v&APy2IoxLH*C9#@jb9 z)ne}ll4<%hApQM#iF+CPI9TGI`h9VCi+=13Deq%bFg@<#wuSp;RK3Pj z)X`k!EI%sFc22&&8~uWf_ovPRa0=m-PvJkUHsPAB`5qQRU)<7xgH=gA{*&dA=c2Oi zE9d8SdLqG+H5vkeqWLFoNj|Q_#LGmiMiAG83WX2+^m~^qO)P(qZ5+TEM6F>j&lMU@ z-MLbK1J#Nzo@MYoex~;qZM2%2`B1n5jK6D=VCo8HvS{-52)Mnk#+889=6>Oy9Qzl> zA0NV}LUYwOyG{lHRe5PE{Zk_q<*a_<(4DAw<-v!J@6R1lbs4M>2`5vud+5Z6v&+xU zeTtx)Ap>uVMi+7%m3X78|`g-N>pgW-1$~PSkuO>?`BKz8_2h)kTznsp`R1fVYZ)7q$(r$!nTr2vOrf>D! zFh$7wFFGUrYIiE5=O%- zj!Tl|j}L1!aH&#G_x2y5Rw|o7l7H1v_wFiYKK%&JCksE*#7`J|3NXNYqzzqXT^19p zM}9kL8>o+AOfpdu^GGOe{zT3?)62tZC5+hTip-Vcx&aGl3J%|~wd8#@8I3Bqw%qjL zv4+fyI!liC-P(f}Qs4Lu5^_J4pNoy;j3^Zr=TVh9GS|+OAlXW5yCp5-o%&LYMWi zQ!eFvUh8tq*Wj2MIQ4GRUdsM70yn+zFI1Xa=7GmRL#CJ4GyD%vc(^3dCF^h|LJyM0WL#;`KIThU>Abr0+;) zSi;p=8cXfqZc#9|#+Pqv6F_=rf>uiLrFaUg3b*b{b&PoOxHpuMPPJ=-nl4;K*w#Kz znw6R*Rj>(KneUc8GLcQ6%-87Eo=2GPIuh?UoU#?{-B6((BzD~oSU?WdIb$>lllo=X z3UpaIgB{6`)~_dFCpW$K758Gre(rt0YiZ^?x$cJV?5*4^-h!J>K?HO{jz@S0Y%81h z2|H{du!2u*(^;1?wAC>D!l_90E~1qerv4b|DTiTC2#KctyokYFeBk(Pq?qv-!%WvG zax6TFpD3BXwO3le40I#xy8sB3>a&?=ADXf1@L(4K@QIGB()W}rSwI?E~%MzKQHUkSCLg{Mz2*xrN*9J*m=JTcK=6ZD|1P2gt3)HGM;HR6_dtx@5h@*P{IlifTBV}7HW_=hKS&yLAk#z}sGUc&Zz z76!>D6u^9z&U{sD)|p&Y4gV(f&EZ01oXKFiyq4xpsb>U=%Y-;QROCS=;%b4FvOHPh z@XKF?>9my@fcNFYh3zpvOM7oy%a0R)k`kN4qWmVs@LRXnR=1X`oBiCd`&KJRu}%1y zfe%lk)R*Y9lD<^l9nC3tuY6fOUg0sMTLX={?|R<=Db-X&o4gp0^%3(PAsz3}qw@EMK|*Oz^2gh2=8A zI7vDhB)BLG#&klC4=oS)| zG@sd=n7|KX>!#p%FpP* zQxb!^y72|)#JiiCEJ7_;Bg&IL{GSX)k**NNNclr4DyNoWL;FMg40WG{XmZ5aizS#w zhy?4G@TL%0gW$a`n!|!iw=b+m|Bp=dw+&~XPFIhXt`~2t0xxKXk;NUfc z&RmTq5K>;Rx4``|zDn}HU%G$R^v!HCJ(5qhRssE!jqi^&Z&(noBYXcl196Y44-Ke# zqPG83o>|OZIHC3f(Sf7;zq=+^ODNqE)R1s_ABj7F{!{{wP5tg6FI-AB{m-NSH$Ip8 zbaK{ot7d(v^q`)e>3`suVga3vlGSgCsXYb)vQ=XJ4*-!XbS5N|VJb-@?yCEF$zjXX zGzr}d_eC4KEju?$dfBrh&tR*1^6d*cpQBeO{=+R_asgHqC0l9l1s&97M#_3#tKT6Y z@KOE$f$v`t(MRKm#`~yy3856l6)fl(H4(6NKO&cNBDJ2dFz>BMLS(UJXUqnTW`Ad^ zb@b5pSM<32+>ct#yv^Jxwc9ti)KVyBHz+g|v^I|&l?|nqRx%&zw?;a*xjvM;E^H8} zHH~iOK0_q7J)eKK^@c*!*6UY;Ye|sN2VG+y34W6@=^157IBo^;P1)to1(3OCnEcU0 zw!_83n>&q=m(37RBt`Mo zxcso&O`>0x#Rf9tVcFQ4A8JuO=Ccs!%4VsSn$7Gz=*P$TWHgT1nraFP%|gL6af4!- znQJBmXQ`Oa#UnYnVOE(X!Q9faj8)Kx)cG@&<`{dCL;Oho@!(6F)l=8i8HuT%n@L{3 zUQ9o~{sIHReOAy5_*#E81D@2ifjZg7QYdDh9EL^h7c-y2mWjA}T_CPOI3hm3_S04p z{+Fwlh!!M+6iunNX%IVm3URqJ+_#?Q`MGZYr)EE(9$QMhzT@=li-BD>LE+@0XlB|6 zj+={8>FNG@OlkxzbD=bj-mVj4quIrt zKON{`sz7`rtFp7u^ouiQEf1Eez|56^5$4b^rPG{4d_G`Y;om{|FhM(~?h;r{* zMRAjw&}cv19d6VQgBP5Wcg%@|`>kmQkv*g(v;>s=5rp$Z*G0d-<{0QMfjh-f^v3i* zl`BW?g%Rtm0c8g3#`jf7MQc^V)|>JB$wN=&?qJp*Mvn4}X91_n--){NU1&f87@!BQ zAd*Z(&gCy3OjYke=Y_GgX7%IJ=v^w&Yd*oB;sbVvl_>bCS>g=wqXWncE}!z3oi|^6 z9l2vHANn1cppp4uY!hW732L{2z_nd1OMikWAD?#SZ!2rQEXqP1A(-)3`;GTrvrH3r zFiw7zAEE>jO#h_?z`^tBFLPAi%yHRqI)Z?LXO_~t+71(Gw`+eH>P|*)iM-0hTlpf> zz$YhaR=F$}jeU|sw$ppM`Ffy>V)%AS^cuQGFsQi;flx~ou2_&e0CF&w#UV1`a4smZ^M?<)VxT|Q4LCt>wFgK)%0 zZ@dt>q==our&yVN6$S z@L)snZrFoLfB$h4ZNnF?Joha{*~*VgdG<`?L#2_w){hom#BW->deXjOpOg`}#iT5A z@uNzCveoTnFL%;H>E%S*TqB{2H`b4xW^COU^yA(FjrvQ?Y9`r^kBIpRAMS3BWlTg? zYWG37c?kFHo4MH)#HS}VaUKC^ao(+l`NNcb6!VGi{>hrG<(sxR-bF>qwzKO%0j}OS z#+%W710UcTr5eV8aW}f3Bf1UWsrzBphgxf|dG~W+J-?uRg#uR{_0ZL+FK%V=S@$L; zO!U`9cdM(slmbteUKWOyRGceY*o>2+`ToHCQm4#rMo6kdT#eGO1D zm(_t}#&2rL{=7~@6S-aKKk0T5lSthdLJqBUQRy2+Wx75%$@05T(&PuFStNd@BFs3!>0UYvf0Wa{haK4SC-FIHUxeZN;kQ#OSdVCY&{Ff+UUOt_DoqGX10u@nXC9Z= zt`nTh=U5jmitS3p#qXz+_=pEyvfYM%X_=y8O6%$VUC}u$gyOC{Z*^y4X~^a^%(`;! z#F8AK@=wV0>K^gMmJm)DOA*Hzy#G_JI@Qe&Q@-%|XLS0+zPL!2&MA6lT8K<X!ZJCAr<9!sZkE^6mRMmsSV?d-h-44IQ|7Lb&ucm;Hs z_J~hRk77+!*88>(>aqJ_b`bTt!fvPlFlM#H7c#v?(fevw7)a;%^QUQUV?dlS4i&csODEKqk4So{Mxe^^YR_hVDZXL zlvp@^P}YNj8bgP4+rpRtK2Z26B8Cs}Ax`?XC+p^`5ckwJD56OLvIc6vmT|J2+F?H8Un+`{Tf6O zg>O~BYESIY1)UpodX1^}6X%dI7q2|B?i~WlH$flYWj(xUe)CPt+|-i3Y*Q!}O^yHI zM_tUyb$?mM-?)8gh`|TaJ%%@Sssg0z8aZ%ROq+>}{r%`~*P4JQPA05$jR}9(zIgBV zsR+@;Gk`sm3~{N}|Mbd})W^S?NUe5Bmi!?xB;VObPU>LY8gw|WDqXwm=Xi%e$?Emm z!3Qr&rv%dadNsuj%cqxg7=$es`*;lr^S6WfzwHxsWN>U#|E{3r#z2Y&T+MrnXg_r? zB)Qp2Z%mW%py{u@G1CViQ-Id|o;<*qY&P<(#Gk$xp|PnlJ4b%c+ePan502Ja+-=w+ zLO>XVN$Jqnpydgt ztu**{5upPzzqjhu5OuMiLN92)Ua}b{i zTY<`A8sCe4OG6KeQoOXr6w4eLKOB_tc~<&4^n{Sj9n1T4GG-0`YvS6AtEo@NR;yTBHZLKVqzZfgcK-7N6HE>jY$s$uB%& zxpUb`hvEYS>)lfWZCLHAQsa61`q~friemZ^=81eJn7lG9bco9MRT{dY6{OcT&ij5mzGC zK+PqHLhL?^vrhpbYD)IBg?i})-fjhn&MT!XLjNb%%O$a$=m~ z@6*Edmyx9=Tq>%Hv-lTryi7+v_k=j$^nKwzr;NS8^v!2b|73+(7mD!#aQ?JH&4LHb z-hR{-K-iJO!DaTY%|(){)e3tM-AbC2^uwk13RX9>N_Nzz64muEi1=?p){XQA!_X{sef#(gP_AHHhS;yi2UOw1 z7-cwXK&F$&k#R;f$NPD-;{|U+dvi8{;?BoQ0G{vaU1gtQ@qY{^W2!DR@nfp_^0O~D z=0o($aJCLRym>TaVzDe=f`0MMYm(og>qGe9F7v|02zt_m%{zo6dl3g4U&@y##r9*+ ztQQJm(lVT>EuU{{=tITO|E>Gu0Y)_SeN=r~6zE>M;p1a*{OcweQBTZfLa%=o{ z3hYKEW5wg8LxkSEd_CnBoF2SN;EN!!(G<1$N?K-jhj#zKAudmO4lr+gH3%ahY)7%9*yUJ1YyxSwdwg%!Lzw7jE0X%2CVUW)j z0@5i#&*xv!?VZ3O4y6#}OkVFhUCZ=O@la3dnd_ni-MsXE3uwfKH|ni>)^OW4TomLV z3HLlE8fs~eL8AqHHSC^j(hdTKl89`h2NfagGRPHt$i|2=0ui!`M6aN8>aorv6le3g z#_k+RX#&(G(8R>ZC+0WjL+E4ZnHkx#aTCYzgL#uH`JgI$oSMgR?}SMAlL5D*kn8-# z9f+%We`SBUQ^=Mr>t3FnfHJb;{XC>Avv1elPJ%s2`xWNDg%TRv@jb;sReQ~Jb8d&? zxL9|i+E)qFjJd5C=7|ThP&m0&+FjB^p^Gk%O4AT-V*WJs)i(ObIY7p<`3GnFPEAe+ z_c6u<2`wu{1-Rhl0RM$P8PFx2Ec=)G@=p=3HW3Ike4=MB5El&IorMpXF228LB8D`G!@c!J-{k~uKer~;f{|=n9_u6~yefD1KS^8ngZy3b zS~eo#B??Xav*?p2c`sC0Euw`NCcmHcV#=CA@6KlNwt3+t-X4rJw(SNe>nG)90P7gU zsm@k_bzZ>^;xnr|rPFvsE~cK>DUE60En0m$#bK{LFj4#3Z2tQ#>j#x+WLVp*Pv5JX zJZ$V`cpugi`5q$JIeNue-5Woy39b^;%Cq3C^{hQ3T(Q+LsszIUGRHB8yHE_ZF#}f@ zS$w+u+{HULw~&uuh@e*ho_f3Ll5w`0a{naa4fEbC;XQFatu60|jI^6K7qgfta)zTq zLDo|Z^-IdbW$c}{-D&am7q-Ng@_V(t9U;~Z#K(^QCtsI-j2E;uT%5H1;!4jvyu37* zCseS)AyzPX?7eGs9$MnpFHeNH6TOQ*cGLrL`qmeS{2NwI4;%tbY$t#x=ZlGpDPO5) zqf4z%IKi{K-W(f+o~4EyW5laQTlR%X6!NTQv~_~iVCYw49M*k5J2lpCAj&PvU~^0s z30Yj6Gtv8PSS8d-Cc2PcM~5B`e)x4(U;&0_j2*Uu!9em!50K*g+b6=pLmn1wMrIbA z&n-V)09`b6p8#RJWOS^{85)F>LC*0<@B-+wzH0>1;ZRvUqn!1L?-|7%T>OQp(m_jk z9^UiDYRWN!U`{->@WM5oKmyV!BQ$W704$_IQrmRJuu6T3=z>n`-f$51AA1x~2o^P0 z_P006nWSKTVT`@eJK4yvq9c$jr&Y^Du+ZREUOJ@h{PMAPaCLCz(|f?RLVdUz=AX_JKdgT{@BvEF8XnWEw68REhPc!gu<=h&czJs zSFSA$VlM}~kONE?05SCZ+4+zF7(pKgom1w`slu>~8UuD&0QvUh4g{lMhP}i$ zJ6L$U^f3J*4g{j8DGdNy8(7WrLHOZGv0(?kHO!q8gBXXj>P}dD^}Zc=U(rkU z4cI<7S6gU8I1g_eaVadWw5`*IJj1~WNuD#alg+(_I9O~ynlz1qXod)i31TN%BpwUl z+U75Azl~YNvw#}jJ;t{y#ynQV2_8^?BgSMd?F0djBfI5E>LGBIR>ED}=d6lPMhm*s z2pVhYD*8h1U+`!K;xrGNgCQa&knL`?IGJXB=zwzkMi0p&@1CgRY7I>KcgyCq$KWYr z;=a{&opZ+0Gq~rq{c8-r(ZFu9Yo+FbJ6N^}5+%0s|6!S7?n5%4S@2W=Q@eWF2 zw`YWVjhEfy{=}I<4W)sLGJz?2+l3cW`o&FOyUNg)i&d_ckNi;YlHg9P;M%ZC!ykzN z_S_%V&}$SAvf9CnvNgO2rkX%ToaJiQq3bpi0T@9DN!c&dJ<$~0iy3i z=i_L^ZJi(Y(tQ*G#2#?)49TZSx;pm6)?kSfl`%^2&!;nQ_ZAakwlBxCA{l8)(Z zMJ28VA{;%4TAV$7`phP0`Pd8J{$tTD`5rjXjP00Ihz+0K_?@VMb@bnX-uE8xX+!!g zB9;oiHgT_ARf@fg`;>l@`Mmi?D-7cZ@G)fD6DF!(PwN$^m-fZbLv!v&>V8d!9q0H9 z`yvkDch~3L4bP9#&p$ey?Oq)2RtyFoG#!5{T_09xEy2u`i1IV1(uyX{mHIP&o3(NR zDOa~>caLAlQok71`Hf@HEu(PXTa~T!?3G_3;bc1>t3Vc3KnF|u=}o8oMVZ@RPj#O+ zP+uG|E6z!o*;I)+d94%quIAm5^m|l7!#QQ7g&t_|@NJWj<_dy}%ZwHo1yjEuw$cHR z8e22)c$kto|8cmvZCT6N-TNVTr9pLT78Oll*j01Y|InjtvHmh4sN zYN9vLR^QQ3toj#7ZQ7%97+L@3hlk0jkwonrL%=P1eg<=8M3qoCh8N@j1ZV*L9u`9f*0dDSz#;C&vo=pxSbMlF(FeWF|j|Hsw;Dnsx!1w)(*P@HB%qW_S- z1u_ljGttCgs2hmK)$Zz3-C0GD*#m7^o#wkcu$?~Z%eR*_YOmEAtk@>=3>Hza-AUld zA}q3lY&u(2AyXZLNlpuqmBwy@RHO2qZ%1(_j>Bro*&Ct_-neXu&h6&{H0k^;GFXN_AGp9fo z&g^kP={z{LX6HC0K<~S80nlXzes|5+BLpo6QaN3D2%@Ob6+VUfP@$SxD z`rlTiaO9i>DW|X*E=}oc{%i#B2M)8E-B-gnE|g28wmG_lgYc6@9e(hJ;D5|ho0)bv zr3r1BPGmUHk2$^OUX*z>7<7;k@6zS`17$9xpG?=!qxnry!2oa#YxV|pCY*NoYChy? z<{T%C8|9~HRF#nP4{4c@w8eFN0?1f!d8*)fw>d(iS}rgd8;{sZUE;O#ahX1kM1^Y9 zKK_y?D#0||-R(Q_g+S}r>^XkP9EbCJPL89Dw!T%NTbK|T4#^Lqu6_|6*m_o8~7 z?I<^7!`#;svU@ZsoY3Ea1ML3nQU)_d&y&P(1G~8hp!G^GO4`WGh3-GdKGp_cXmJ0$ zq_T@U&r|c~oOeK-+@N6j{@Ig=^iM7tlv z;1{|&f+Yex_i+olroAF&q1J{)7%RNF<255qAV=_HBO{d7*yZCb{-Qc-nD~1~SEfi@ z(adU${-EtCtfm35GFG-nerWV53!sj>Gil;spY)iXSTD2|yXZVP_*9gM>FDAFfk?0U z(*0ztBwTL`bHae__OT)?khzE{-4v4}bxenZEdHsLX#m!#jWnl4Ir`aof166o(pz!8 zXX<-99L1^O*p{;hhow->AfpPgUQQongsBZRH7sMWvZAy+kIo=#6yF~8a7L4MCw9P2 z6D%Ix;O2~%llh{8%~32=thI6oZ(ITkEtDaCGV71pOXaVdRoDhCG2uO5&!@x+P=dhF6#an}y zh=*o_y#ip;{!XaJqMOJ0+y;bR2Xdx&J_@<0I6SLayeXQSC^H9}c*`uU{CT^|*+5o< zJ~-rrwg}u&%sY3`(+b3|J+yi64&^i7It+n1!yD%};KWpftAgI<5v>wr~>UF~Hnt zLx>xN5`Nqd>XeZIstNim0fe-EBG)D^D?%$5|**rg2*eY%V z0;Wsb)r^(1!tck1FNwRCBNaV5T%U;CU&TzRC(F=cP1le#u}C6m6=?=hj(bGJ8~lF2 z0(k6FV<4-U{{R-~`*?jTGoSJ=UhG@HYYx7V%WR2Z2ig(wSPvQ&rI9Bz(FZ88XNf5n z#Vbc^1mNCI@|5F>c=@>VC8*Kozt*Lq@+9`wx9<%%=zO@IQ2IdH?SzqX9APRfGM3+e zS|3yP$lstTWy9q;)PHFC+}=o#I*rjkK?q9in!#&qeW?=lM6&Ys+Zby6kdVud50|y1 ztO-7sK9zcx2mCHuSsI3&Se+wbXCY2EpWTF<4#|d@pja-|uq^$JONNUmcTWHf7U~)! z6l*sYke>ax&;Wn+pDCHO*eTfd*p}eUVg0F7D+r${o8c)awO-RI=bIp8wk#KY{yJtI z3$s7)Xp`4l^+t^A@^tQsPb&_)@O?fjY5x)(@73<|u{r7Rh3gOJO@FTCc6k2e7|ZNQv4iKyve3lh zkIzN(n=|AV-X?4%3;T5+vQYu7%?pIEJNiQUBODT*ZpL>tX~Lb zHm|n7dgNdl$U?LAiY#1AVzgr0oEf-POkhOG;=#To&Cz2E{7d3EuJ}M zb$B+j+}#18ZzVUK7+_2p-HJnRgoP&_STMF6F&i)Ijl&q!5u2TBw#7}Hm;H;EB)77H zZe?e1f!R@CPG1^kY5(ofbfN>F1HVXi%H6xp(d5E`pa6#bbJRso3trN7?h0t!q5ri3zi-NCo)5@}FB@Ci!C|T1 z#LUtT^Awz_U&xqTZT-?u1ScC(U!x5%W6%$slb06Q%h2mp5O3i88cngxd6P$b#NJ6d zV+%huyqx|iLoN`CzChmX2uB~athh~r;u{q+SjdM3NUnXhPI8T+Lk;#f$(;5V!ZRM2PW7LVm;RI{D8uG$P5{fM2-p_I@(6#FlxLy>uW7s3+$Gy^6YS&4 zrxPa(_8IY=i}{%wR6kOzVL;1JGtwsidzdS`8sEG#!QMrM^(bdwV5;o(iFu{Q2d~;lN-hR+>)t-`j6ouvc zS`!?F+3su&7ibD&)}aYm#GYEV_KWxG@Go}YP9PhBrc#^n{KGV#gSD?WY(?=-Y-z)= z4Z+-B5|UXrV(z&!@0NUt)f7&ki(Q>4Htr?#V^j*QvrIaz&`9M@6el`$JpUj!_53-3>#OC;*Q@T^fUn-#3LOP7+XL-{@ zUIRVeH=h%Q$uZhIF3Mo9S6zayx~&FWwOKCwkRy@3u(jzLrrzV=<|1t6v!LbvXHaA8 ztBU+ne-i35{LRVO3gL%x_cRR5YEYq7nBmEo*(0~r+j3*c@M}CapUBf9`?7B-2@`?M+~0>+vLG_jJ>@F?tb`f1v6BIxmhL@~A9ANt`$LxneKj1a z8-B=ZfH+hTK5E+BxRtSa@s;jX&>JxeMeW*F&Sy)o0a3!U^o%Q=z!8jiIz%;?^%ypi@?8Vsc=Kb^GYU5X*Gq+xuw%QA)(zLk1?)u1A7P~ju14ECEtm`s2LWGl>X9S-h|^{mE3($&80$E6hEgOjFn zXY8d- zD4S2my-R?}sKeNMu1}X9H1BLmfhVbQ!LJ^>VaD07P4|O{>WTLT`C?~p4cDsa-s;QZ z*>!#cILMhket)!V6mh4dR+^uaS>a6c1??aLLXHL_*^%}j|3lQBll|X%>!Y_?d?cz% zGRS@)$i?8+0b^AA(2L^3KYk*~l!- z3ebh4Z61XY7ET(&7(v1c3O%00Nfg{3Rt9`)zoGUOOud3as3QAQ>h`VF$`jebnQSu) zK*kFKNvuS0cbCca%4F{?5q}`lirU?Wu~@o_x8>SQ5xv4+a)&Y zW}5BI(h4E-WN5J7mJQr=%yp6;ZV>Q10*6)QcK}g6GpZ;Wx2vZw`Wd-Z$ov{AYKiV} z4%CBw#~WE^!L**rL$EHBTUtNoU(R3gK-OiJr(BtK70t|NI$!N-m;{<@9XZUH&})l< z@D4Jkg}1!!X1ZRGF@H#a!fxb`G#9>n_*?E)ZfU0%W;Bw@(r1tbcZZUct;;y3!Giit zaRI)S{QzfSuNQ-B`Z4x}W#Mp3Drw0q)$PDFhnqEnFnafz3v2$)Ps|(Gjjxu@!0gBG zeq1j>8GzZ>*Cz}n>4j`Z>0YxDXicp&1C)W(_0q3HJ*wcT0Daea$;RdpmFIltQ=TDf zwis@W`z-m~%Q3ggyq9$ojq+-~QsF?x1!r@=KEG`&9py z;LjCS#oOXIxXnzrFpl56crII*G3w_lkaIlJwo798A@Nch{5(8N5Wy&Cig}`k=*o9G z@F@+bk|t1sy9Qa)zC;UX0g@m~L(q*xExp8XAY^7S599dc`h;JJ`7=rx{V(!ktWlpM z&q@-@NM@Uh{I?4llBzV(8M9q@JO@PK8-v8ecNQXcwKm=<7FS~hF0n{TP7XNGLGdxy zb$ZPmpoVn1`T%tCXm~ZuzCG_==UHLDq^nG{`Z}PQL!o|yLXS%=<+g)i>5zApQMLGc zQ_1I(n4DS6Vi6MF81}P0r8i7m|guYjz_FHahX?*WrfR7O?#GeUW-;fE&BN zNK0bYi^R=p(Y74u-Dkio^Tx`=^P#CGfbl2DAh*+%mlVzL`-qv0U42|@RpK&980UJv z7iV)$WqqfFa`FUKBzp?!JpHJ91+OYy*e+F1OK3EG(#u>pGF?mZsktt20JJcFSOhtG z7F>=zWH8oPx`18GSq+>Tgu2Kq*j(;Ffv98v>UUvbN9>FDX61cGN{>X~W-%NHh0$VH zPtwT}jieu3CR$=`lO$w0lZymbPdu_#T^%UQ_^N|4&D%dEe7QGK8MZ8KvIAah_GfFN zVC8iuFHwIeq}<~N)CB?;s$q*GW9r{#(;vmBK5|EaCtSavj&N~S+#QQVw_TX|u>Th2 zN)7hLYslVmr60%uJM-=)?C`#aB~;@y=a;r#V0Bp>S&z*=#M50m0D0`{$#wq6Px#03 z3l+hq<~hK<`mS(uG*(v1ok8v$uv6T~-}lRf#zx&RQY^mA9zG_j>x#bITe%#pGm$f$ zuhnhRr1m6cs;@_l#cl-?oL~+FJHj)Sx!B!qf1gyex!C8dsg;QW2!sL8 z-TUjb!_}UBk5tZfj3ah$C#X9YK)KUEeur}l!C5F5FzJ8#C<3)dAx?N!0tN1Y{K+pH zH}-v6uGJHIq%S$s5ID6-{l9$vN0p|UASYOK_A=ffgfNQLxB&NN&G8(RSmfA ziD;3E%cM3l^_+R!g46HMAf6>fwhNs&NP2o%KAb!-;R|Am zp46C_5rKMOO2#+s^SWPGm~P-bRX==at{0;hB#T@mYdV;Z$r7tZENTH#ph73t%T3&g zyo_~>tnI)y?Gy1ifYfx76omn0g;h^rcys_bpU&qTzXHBb>4rVmGAQlAaoOYx_FQf8 zytej|Qa}Dp=TU8dTL&-dh?|K!o+1{@kxN&&$MFops*#+RaY^?BhI&A>a}{v6EzE&jyq#ic(eZnaXV3yQF@--e-;VwJgTo<6<{1KSz+XktBs5IY8K;1D^g@~( z4QA`Wj}LNiq13ZQTF%rjx8i4)F-Bg__ouyx)8@%WAaWsOPf199p&c8wj*y}Y0~%v_ z;g+X3*+uG2LCmV09VPyTfI`mapIF%8AJ*b8)|zFFH;P~U>I#Vhx-|A+Hej{iXcU1o zISU)v{k02M+_;$Ev3o2T>53d*;_hRD$}eB18qwZiHA^t0GH;>W2dG3&XO52Q3 zmaRnm!qXOWG8xal&hWJ?k`Szh0$0Ph-|OZnXSLT;%C!Q^1_1kSh@X&@oUW2(V{5>A}Y^k6h777 z<(q-(&12x!mkNU)Kn!V=S!7J4OW$URS?M0q0*UW{xKrcfGDAKOc=Zv6mgqgGmyXSM zKmaHN7(hPb^=I26IjGxU0=Zkm`nHh6MP~&+rV%`4V5{lmk_1y&khiP%Jiz0*Q8Ral zn+#btb|7WD&fFMKzjQcnEjBj03+9@@%F}kCi9Lb7qVMcxU_Nu6=}zea7-`Y>$l&QC z+`D9-RM%0@yG!4t^hY{+J;#*oD}~B+GnuxLtZ;MwrDJ{k@Z-B(AzBYp*0_Qr!AlvL zr_^-BeB+h`{LS$4%>A8YAUd3;Sff%Kcq_Xfq4}W9h}Y<|Ynnb5yrZR`R6;-^d9a9K zaAUDiWv*e?<2wRI$iQ)fKSQFUg#j?bDUdT=>nJgl`SmL%GLSor{e{VRzwi2LtgzGr zajrLDqO7vRu$nC2aBr{NvTAqp`bfL>=^bGbD{gluM0(rgE$DeGoGhx?TZBPDmMcTI z$eUx%$B`+}E%#JB$&fXQ6JtA3wBofh!^b)rqGLz<83AqV@>Uiua7E7^-eTL{?Znl2 zQ@b)?v9w)Ktc)ModX~=rlEuL3l$M6Xe*Qy9VXf#;Q2=S#U2&RA!D*=kJBl;BYOhFs1esEMsPC~|gyz_XJcTC|9H@!xUx=}j*Zt+fO_G@$wl&j@}j|v4A_SxzoN;b2NYqQLL`pSlxe}JO~?P?xi%I8yGrZMZr^+$-|=VV;$H(8W8bMeJCp`4+YUq>E|_BrDl?-LMJX zK1ka8#7rX=fvJHB|GoPW_Z5$tlzL7Wi6(!olP`y{elMW(u+<-ugXJRc5v-E%*^{9e6iGm>*B2!rT zuH^oS(gM^Pb+twVx!Zs+ozn0-Frdwt+d#|!9QDe~-LZ8XO+=daVGF08;~&5*0Tok9emvZUVtIo{XRMe0BLG+@$+L?Gtq4B8WOSj7Tw=5 zgLRyXY&HcEP|TN2tzb3z2MJe)&D^g^K}GN)zy=Kx+kiv|Bi3dM{TB@`J21rLp$zaY z(wTCd_RcZG%Hj58B}0wE$d@2bdsi(kx@*8ZdZ4qyyNLO^EQ^*;T+C^H-$ znmf9Yn=qn2SzEi+3pGodd2fzOyn}ikUvlP~qr=s}7#4kk1p&KJ>5nLA=G^H8Op78R zV+Y?x!Icj~MJG?dK-SdbKVM!%{_JL2%nT$V``vSyUWrW00CCD<{v47m_k*5m$T#S{ z3f}a&iOH8)e-rs_S)Kvnev59fj*nIQ{q<-nr4^EoQheRv{{4B@yibRvKckZMzWN=W z!jScgByj8woT=&PvtzLK-9R^5#Ks2&yZG&m5_ad0JUXV&Tq4E*(~ETWZBU|*L4Bi# z$9%NJzInez%N3tp52!q}>a8|DBBn6%Y4{OMy;WYyV%<{I5Hhz%yfKbEw4hdt48-d~A)fn+lH@jCiStlVQXEi8WX{R(4#O*Fs?Ciip*6B0&l*g|fY;Vz$ zG(tc;7rO|vdUkxxM9$iIR7Gwq4|%KDl>F4OC6t^Qb6wtU?;4>2nWB1>_)t@ZT6mB?Ml1c7tzyf{6Z1BX&Kn-$&$V1 z^%pxEOe_jJ>R%sE1Ybad2h*hJO{PzT53qua_D@kStF9RgiQF7M&u7T5Ubg%x$=Zl| z1~(DTxvx+iwA~ zP!|xIUFNj|#~vCvWe@W~HqnqW%!Pt1w*v0FRy*mojrKqSR!z$NP%I~@ z)S&#`&3&3ZjQD~`1;^Rrp6p<-`Z(LRT^#A9h-GY&X|v4 z{(Lqox;1J`I1As}mPLcqEtX*T>xi-@Ky(0B7|Dza2@ES3v)%m8=7wRUa{6gizyXG5 z91@jYpFM>&5)zp|=hJhu;f4m(w(r(VCV1jbyzdYio+R`uQE2|m=C;cNpR{g?%ysg@+1WwY@{9y$J~!<@c@92c&_YBg zJDtMqQ9HBvmiMjSa$d=Y{@L^>O!}9m6{crM`oe0spG?!2w#N5AU3h zf&tnvCGIaZXT24MnC~)@ZpZJYnp~yWwpCh#SAC;b`fG1r=laVKo0cy`V83W~!z7FG zw8j1x#;r)cvT)V-9iN*=WXOHX!q%XaeY=)aOJB{~?Vw<3C{PyEohl)zC`mOIBkg~$ z;It=y%}lVYGR==kEo`9Z-cVgA5@0^u$nGLbb>gKlljWuIgxm_B^Y_MC}}f z8qB`r-6wK3HPHynOU>@7)}rm1s5Dg=`|k$euZewX89a7#F;8v`r_m1xUvPQ(&h(9e z<{fFG+|>U!Jywp7JP*m+G`DsX3lfQ$ffy51?g$dH?|Xz%qse>59SPa_xwSgUBy`W_ zE}zoJD{nY@_+FObzaIR5=~UWN8fNzmN8dB5ce=3%O%@sUB7ubJ0MV6oMnR)3G}*v;wYiM=L;i2x^*nWvpSAc(P-#%~O{kzvG5{fF?cq)fm$4sodSM@$v_%W&T_b&;5EyVwu z4S)Clzk0~J(jK%F3TBlO&i@QY@}~d)nzMgl5>8s%OXI()^V)-pSDwj$OL2@y=LzVY zT6G2yfBw~0@Lx_Z$5abmQp9hPZy8%}#NE3S_5ln%u!b0^IpR8)!Ks?YozROmsn532 z{O{NO|9)nkD?fF~#ehJTk^DNgFBA;RPxyrY^KySJ15R1aqGX#3c-8zFeqWMaGPTFL zhZ4(ihVx|YOS(?B}Dh~$T@sr2i$i@hQ@vSMGH*!-X0 zMWOjxg@;(r5NPuQRqgvVH4%A2Nq@kd=ij??_Ca&1+j{oQ-mK?dT${aKb4nxUn~N($ zx&O1F|7p|yk29rQ|J-q|Qb=VtIV`G;hO8dDd~AT(#gS{DZ;+=ce>0IPy=M*GZ;ss+(CwoF>&oXbCV>i==Z{tSE@42k24 z3N>_Soc(LGzU{aVWHcD?t4~AKraS#7-qK8G&yG{Auow^`_<6M z4$U9T?1*Th7P>gDO4@$U(|FwE6I1dQr~+=fs4XWgmV)!%D=&fv-yaCklTujI6uKxY zw~}Z)86}vPqlsBK+<;!bJ`VzrWUVVOtY^~08v+$axisn;ln&9jDK=)Jd0`^NIuiHp zErGAF{%msZqhf_=0(*Rw?PRl8SZ;;zb5r?1&VqpK{6bFZn71w5Ihh=DEchZt!v!4w zY>j&6@D?Wr+3w0T*205-<-THmiORjGb>6yxoDOaas;h zeHqY5QJjmEFEFfbY=%6VlL5XQHv56WcZUr5BJFQ!BT$TXR3?vzB93ZfD=y97TIPG_ zEn2A1|4%LeExFYOOJthU`DgYe&YF8~s={Jpoq}!;jq&iB{wuZc685_Kys&H&Go0|NQPKRzpwUP^<_2xieyOBX z`;^FPo0_Kd?_>C5G=pt~S8pvoKA1i;0DL$Y3ReG?tlU(RQ?jd7*A2ga)q}t!jqBr4 ze!kQ+@FOnGsSoR4O1Yn#Qd9K5YJ4^5)%h5>jr-9BVsGZn+@upR>A(PvIF0S?zZs-C zs)H~0H-idnKC^+nN@Is&9DeJ<&xbQ3nmforV8d8)0ZTyPzML+$mzj@XLxc}@g z)$gDe*E9t{ly~J!yiZq11aRJ?^fcds)61wQlpM}1svW%}Pv_EE7IW{eQ@iRp#Xl$gJ7KC+_oDrSJtOg z{g)dCxE?jNb^i0fmxcZl?#4z#G|a)RRT)jC@O_o;pX>b}W!i|J6VK+h(k7@&C5*>(1A8q&M!Es~=J6ah;ss-F*`je81ppP-qId#{SZ;!3bTk^(2{o5ijB$D zMGzNxS4-cbUB902`~hP>3WBa13{eBla@r=Fu*|Kq4!<6ByD$wHNmy^0xA<3t6ltl9 ze%iWp=n#cAS+(>BFVjk$#ffguw`>F8 zS?lwG`Lp8=dLdS?kjW?8+?}R7IWsY`FDA6MyljjJZn-{F&WHyi+;!u(mQN1&Zt>UH zxBmev!JOn6o!?2Ssd`tK&Nc33nEuIwSDbcb=0F;pH_=hg@%i7I5TJNsaU%hr$c&HwN5mZ!SJC0uub%G zi4JkQzPmIvrMjpkn1iPDZX!-wCZP<^XAMaM02&6ghi(-vAP$&skTJfY*33~2t=S@Z zj7qJ*S#M#=VmURxv}6`b@qWN4MLXUEfb4=JqP8^hJ2pGexsI22;0n<@tlnXYE>`_E z`KQvN{CFQESiynr?AiilhezP=X-Y{!VPSM3@vbFO{2Z7D>t2y(dn?6tyL;z`!-J~e0t!@k_AFC2H$jcgZKCV$IX z-`R)p4d)o3tPrq+x{5H$DhUVIU)K|54$n6BbUZ6()4jVki(nwou1ID5h>gXjQ}hIO z6$)YmMTorKcSIzer;56AZoI^1jO2qeGLrG!7EnWom!1tibs74kGgZv!MZcMif<}R1 zn9|Y^UzfpoeFB{DxEi|Pu7PUgf0rPf>B_m z_iG>hfc}+323A3^o6fUhbPqwO-Q&vBGSuaRgC3ijY<6on2(@@wOV}buBhXQgAfJHG z7=ph-jC-xdfICoZ!QsgM!3W@S7pCA?kPQ1#&~dWiFK3vgg?sqOaH`uTIXi0uU;N4) z%&y#_83kW0N~<~@UI0Ay=O{ox?T-DgfGP~8JLSEMNfCct3iYT+2|DO}GbZxEUvM`H zcr|9!FW(y6L(I9neM(uXY7)P|pGD8w+EvbYhGa~tdOJl&eAxMTN0maquEH5Y+_~UO zHB9aE2)CfHaxJ3p`K+v~Y-IU^7eCTzw|P~=rD?U|{A1~fFzM(y%Qi=_BBjI(XJ__Z zi}5c4B7}52N?`_z-OdS<9COg&g*u$X%o_ois&oT3W~*Wg^kV4}z1d>ZWS!x>bLY3P z+zetpzTRA00Iv!L271j9DR81$cj+iYLX@I2uodEJ#kzy%z-lW?7V3K0sO+1yaWn+D zgDOm)a$VWkwvC+YQUOJNOQ)yyu$?JBFdOBiSUj8eb~ftOtPU^=ckZDvSnc4INg z8w>BC&_jaTi?>O$^)LANuPQH zKD*rlD_$qs*6W@o)G8UcK#|F_yc86J5@cHN_Cfmc*I~>hJJhkGTGVVg zxb)qThBNt`TN7&VaWZfJ*0zT#v4an=HHz67TEdgYewDO0@J&4zlW!_IfpouP0uUqh z#tc+x8S&xIWX4_yEE&mp15*CH{)dkq%8#0@RiQp+Ad2&pUx3O2s~xt$&iYXfuPKQ% z-Sn%rT&qQ$POutg>X5f1e9;`#cdy4|mNxlDPgZCTxB%8@*e_rh)ETFUxO3EkpiVT$ z;qfR$Ev(UNH3n;lA|z(c#C1@Md788WY$*e8uCN(?YM!YOu<8M@SmNGuVCmE=OE0vx zTKW?)xS>|K6nO?mZ5IS`@)s*ypGXdCR!&>S8?ajhR>BhLb^LZTJk$*YerT!sMea8M zX|ivEKGTbv*D9+2w8AN1Afb5=2H-m;gydGB$q~CxMZV?L0V{e@cX`0nR3tD(TKp24 zqjlm&6Wb@Td+ZrecRb9ll%3&+jesMe$>z7rBtSAOA51Uq#KXDoARw;&j?#6V$yOXx zQ|zPbZuOXjlwlVD;(JaG;#Dc%_9fA+_th~aPNCrY`_id<2lsKa_Pntnf|whn0f_ZV z(hPfm-2;HMKXs`#i*y!NFtvxlvZ~aN!VVN7PCgf5_p_Jh5}nE~JBEBy?gj;xV~}ZW z`vm8YBK)aL%HMsA7YETMs2>%KfRbM^c3HO-i&-Rw0y_ua2ma7L`ZxhUl$0!HMX{V0 zKdGk{=z#iLHQE|Dg>GUX*6NK{-emz+9HT%2-SPlLwV*{$yz@isfUTeziRdky{BeR} zTi6YdVz$yYvUx@j$k|JGB-PWKcg|p z!#EL%Zbq_e)QSamQA@qFl5dBDIc|zGC{bO%CG?$Dm#u(fYt1$)PboKm!iB}0{`C|7 z-O@o2k>?1mVHgPX`s(OSKl?Zph0r)v4xI%TGPH(Z*5|ulAy_)QKeS^R%S!O5+xyi$ zg?bD^S3orl%+C7wF^A82ZInCR6ENKyvNkfCw}J3!c<<(w5PYh({L)Gb1Ac^hXo`@z zJ*}C6nm|@;RDMz9>)H2E#ex}hDsUCMPp`Fk1Ea(vFZS258?)&m&#RP+>|Sb@8}8=Z z>}E`gPK~#}Nw=qIjsnx^iEp=P(7h>RJC?s#3F4QjjqY{+!q5bcgU~b(1b_iK4M3^# zf|XYMnqch&{KCHdIIPDUT5XMyni1n3UuA`zE$x5svvhfAXD}wBr!YHCITC?l4#Sk& zldx?cR*PCc8%fN@GnZ3&Ab^99PT31L&%gw^(e{-r9RphG&jU zz;M);__&(nOd&S&c+C@{LPRHp-qRG(uQa9H+HWMkX_prPTJl<^!|zTtJ}AR0HO5C$BZIM)Y109F$w>7BB9A#Qg<4ck!OSA_D~i1X zfm+w+5WVnm0-{zBBkG4oq34(qezd%H+>&8lKkM+k>gV>g1g*xDltLm})*HgrtOTpA zqDjj6VANR)|L-kpmt=G1<38^SjIa;GsdFO9j?LHAq|(M=UwzUc_B+5ylHU}w1D|JT zI)gT~Cx7H&C0o4!nw6)=zwg1mfhGA~EwMR)px+pOiO7yMI7mr}{*MhJL9I`4V)@n)QcoHMQ(v1p>hk*319sE2T?FT^ZhHOeZvOk=$1YUuOniUl-P)7D6ProIp-fa>0oU|GyZPe7MvW){Hvt)dL9-Krn}(+C6Zp zzo`FTCf}%*z=vu_#l+KJH|fLPN5{Igw?3pvn}0Xk-PY##f1I!QWB#Zl^M>Gc+LdBP zQT^o13s;T|F^m3kPmK8zaWVkQ0o#8P+^=?wnLN9}wBZm91QjJy<-5qRh0U zMmz2!Ah*vNP>`u)6n55{iyr!*2*}F0^%fmRSja^Ys7+Jq4NG*|0Z!2A9(w^9*`|Gp zq3Oh0fDm3-H7v%ZypP3NBKMX_bN=<7?t<*R7l=O_O8m(*nIoT^3f(zVE+GRDPY@9ameU&r0WdgVuG{@O-#E7w# z`jb%TElxPm$>zYHnmuKDjGDZv6OCD;HPToqkXp4F6^&DQPA`vudSJ8-%0pOFw`V|# z`etRS*guQee)a#uNElj_>vPf{3WL_ zJ)L)HX9to9%{MXM#qU|&(V4l1(9|~~-I-*{yQ`71^=UO?!U8pD_CgW0?a>;1(@cnM zI}GTI!jw(aaVpqicFveI%kU>n!Q#7n=`*&zvjTfLHF`g{p03DKrayjB6LdQ=o@FEO z495NOMRT42lDYA1@8lV*7FSd(0-1gVIynG(6GuJEieLwTrJ%`N)Dc^q#dNs^xcg9x zj;FArNEkji+04QZ=IeTY8+Kd%?zd{2!XkPIH2*@Wv7ffA80}7hYEb!UpNe9Hl2Ef7 zFeCyF@$>aNUxr>%(-dwWz!i_~f8Ri2^lE1=@K(kWXI|qzdXvK_b;;pVQw^*0>mH|))|mlXWJ9NDKuqfM;irRm%{F{- zTR2aVJpLM5dzNBrZ=m3enk`*q2v>`}%h9|+Ux0!D3ZRS6V(j^a+%@7wEXBQ$BqQb&6_bV5n zFzQGI0fFozl1@ze`&GNeK>WfuP7qxBtf_EmEd5eY_$=x<=F*{&f;p5mscYn(vv|Y1 zA9<0xd@qxhTQ)nZF)MCg7L3r|V<4p=;lf#2RPVAj&&@UdR0vs%n?tK3x84qA)C3^% zo_67^1}xwy^FNYHf&e;lF=@iPD7QX2Ra4$E2<(*5Fk7`=#e2_P6I=LgWa)GlQEgXSm2*R{fAF7C`vN+y; z$4Q+w_ZF~7vD6xS_eRp1%kn!8s07z^uHm^~_ibqpIE0Zwp74aztM>Ie5fKk{(^)-{ z2NY))p%~lAcKpJrg$%4y^L}Yfk1nlHFCdSn; z)Hw-QGVwWoG@o7N5ex=gjn3EZa6%Sg@u$#%G$< zd!{?zjq`Hg3EuN8%qhb%PoF@AU^)9}x1{i?V<>ZKU#gQjAs`VkV5fQO!i0x0?L zLG2t}>#Oc{6#9d*y!JC9V~z~JL)w|4(=?H3y|Yy*p-04B^^#n`X-6TH+^ zU2NF)CBE2u_S($ykgaI{vl$v2sJ#s5fyt4-lhSzp;j(^e%r&jgAFdbQHTLVvTEoDo zBEr%bKCosB1f0S+5}D8LV+KoDSH8TClF2xfcp(fqe-wAU7Q$3K;T?NpH%t2~+i>&6 zs6O;-2gfjht&oW;bPkx6+rqz>>KspW7V-($F6=a+-P8fKapS0FoyBK;@lqk&RSX<( zu%4?{Q-bVsKnEC+U4dwPpPXlqrh+)k5-n=~G=b^QhAxglA93>Um3Sdh8!Lf7(N!8} zMMe6CR!CBCCby#(0~w~hervG1V%>E$dQA$^K{jXOwZW{8FKe&QE#eD$Es2ig02QJU zaEJKFMF1#Ke5#*#omh*vs_>xC%X6*w%df7VF7)>Au2c6RQN76d1+cf8@W#nkq;zY! zvuQ2V=T%sRX!{M;5Af%c3Mf@oG;XBkM_x6&Riwpx2cdgc!>TD|J%sbik2QflueTZS zmEgp=AM!ww5agO?DG9+`?B3TxFFpl~zEcUV0S1|(uKr*R2J#kQSDY_%iQRa;486}^ zA$UeDCbr%N2U1rx^9qhyKU^}nal{1Qy!^y%z#>mAH$dJW+g?zJKR@`EHg#GasJ*gU zk_Hytlz6G9nzU%VlvU2n|8_k^J#LR0D`|1Av>Sn5p8Z5==*+(xyQuxEFZtc2!%hzO*#1&Fg-7m(yb$jZU0IMkHIl^{}y8LTWF-TEAt+nEvi4aZT zR+FnvG}F9aS+$Cl_O3Cm8!3iLSn8Rb2;e~FN&`BnNzIj-^KBwQmX z^yC@cI4s`Rc=R5{LAqh8>M7KBf4~HmD4$IGr5NiFfavguYaqchIs1fJh;z;6=+Co9 zd14;@&;{ZKM8SGUw3h<9^33XGKCrnw94`ocBhr<NetL)ET3DYWBsxq5DQ2Jw{F-+a%0%*lRJX{Vo-BjdcMx z6M_5CV{1(mkE{R89zyQ_oN)fE7jDj;8r>TqYJKH8PE}bTu2y~P>1zSEa6b)sJlv`> ze2+yL5{LWW$H{hw`OvSJW|rKAV#PXIa)mNL!w0#0{{7*=&fx8{5Z((?vFp}E&q%y( z&_OxK!(VVhtbyr|MgvdaLy#P{oKgxAJ#I2x`dTP{$vP3}ioCF*Wt-K%Dh=!mXu#NZ z{Li8tvoNR*xeCk8$=Mv+WQ>xDIyIj7fc) z3$U-(vHx`{w;EAdTszj2r&}?5^PcXz&K_U=iReA7=BEC%w@wHRSeO!fN{J<+NR^1P?JAw{ z84>-%&u?}3?8cR}`URn^(W%irhK{mldv6D0_SmG2GNj8dOp{Z=j-OYmK}iJ^8XFq1 z2~5xbj|s4@%G2M!eAQ?2MVk*-f$zcazguHL{t14;$g`C@ry_a(21MqD~rf#mR^uJyFZ4tNmJ~NS4*G*fC*vPy{ z^Lo}Y;2=@o{y0cJN=W`*_%V<0o<(%S`glhOcy*p}a@naLYfs_qZQqSX0c z*3Ul;tvR)OeLXx5|yGPDr zT{u%7M#>(b2TjuK{Noq=+;sGt@f0^-`l_*HRx-U!p@#9n$Z zUuh`F5ON-?wBdSa0)?Fa4EdCmQ{3>&%s4|OHFs`z&_Y!CmZUfdxcFHRv1;C6&jh`s{ug=w4SzhL97!<0AV|}FmZC^0zMsJDNWqPJ!lgnHk zgJ^jF$9VATohnh?&9eDTaxb!RAu0LGPJX1*71_f~o~Q8&r0CjB+r?SfIBA{s)$k8B zkDst<9=zgY0^^~t4S_`S_+qbTfWHtcKUaP*b$ExTL#P6UoRK$_Rp%M}9lq|TBkUqe zxOM>@>sZ%}{DJj4hn-=^w)~k~0!oT=p_lCZyQwghi}4m8^&Dw|ld^A=sY-&_;1N8R z(S{HAz2HtMbEq0tzi8aDX7Uq|d)$g0!d2soU**|Q`kfkj?NTCnDX5q1am@oM^`(tN z*cs4mLwd|EG`?@Aa{_|1`y|_Oii&aXVrfMXo;8P=ddlxPwOrzIqh@FdFpD3)H$Yo6 zXi{*~`!{_?pwUi+`n)7sx}57Phn|cR6nDj=a}E1M&@^ zzNmnJ&$#v0fytduD~)?y;IA?sm1U{+EoEC2wGA_uxH5$#{W=+a57^ur`|g#WTchBT z%HkLP0}#>v_`ZrWWO-nqVo5-FxvL9#uib}Wm+I1ket9LAIE4{fvbc9LXJ;#F`S-@9 zNwoQf!De72Q2NZn#xilZN^w5dPEgDcTv;JBzM4)o+F&o=V%xj&ykEfm;^wA5J9(zy zf$hXC-nhH`+>YO++zYf)U&^Pg;xvZWBMA%9hL4F8VTRtfAK79Spy~tJ z7FfNhrFN;a{MUzJ;@Ai6ztiwcm@pJ79i@lsu3RP zaCZs=F4@kAXdg?_fz%GE#MB{#S^L3UIwEyPm2oQg%pD-CjJ9@e7@l|S{-BOa2w`~n zJ)o!va(`DqW%hWU{3$QMht#eVDaqOX5P{j~mVMhpx9eG{2sLT5gesO}iVhGb_(|)# z=c?X{+(u@?KL;rot}XOsT|J#-@Zkz^H5JBau=1&9l(Jq5u#ac%b;p1Z?K#ZzPVBm+_cpIVQ8PK3{YN32>6JAjL={s`58l(L7jcT^TXrd1MI8Wx^CBoSJ?d@}8sG%# zgZG#!j?GSfhqZn2-h%QChSqrLdNFJd-lwDa8p_$W$N1TJjd}{?WXRuZ?SLuSLKjV* zF~IMhGtUIAWzHu-nzIiKAjvrf^bd$)yK#fT5}B3R99fB}YrvQawM}}?)D;ZSg(_-p zz;~?(5xFeZGQdu*(rx39Zh}!@7x4YWSbSofH;RWKDnot$o%t;#&09X-` z<54~P!IMPva!KHL;!z!5_vUlvdn5!F4^hxX7S58Hlu;u8MUc0e;*lt7*ik{Y`Qp6C z4v^myNcXRfYZ-IV@hcrH=D#c_p*ORTYN9AP`&hh`Q7i4jLl;co@)_UO$I3mC_+}~8 zLu(E!veY{p?1Vh4ObLnh{zn+6#+BaJ-6GQKy1DJu1xiu$3!p<8meoT?mPTxrw4& zj|@vhedkkK;dctJ331is6%V+BUXn))CG*_46h*27m_MH7J@F;pMFC9Wv~_CY#~;)!#7I zFD_+A_JxmJbFut%z}?2%5ikgNhEx2Q*4cXm$RocAJ(0gJF)Z;_Eu1`NDA~iGlcgMd zW>EWF?dDHKg(PI0BGrqg+GNEP+zu{qsN4GT&f>wRZ10HDP#~QYpt#=KyCjq2tZ_hel$i(Dr=zL+_0?9D*u**T~b&7qtC)G(8d>k+Nl4c z^%>hml@$SLUh5hztqtZGIo-~sfTMouQ_&qZ3q#pudU*rYr~A*m(`kO{yxV{dm(#`N z#d|n9HgFY634(2JTXj&b!$BU+9k3&@>Nnfk*Gwk8xf6ovIWd|8BvJY|8RJ9vblz}L z6k`G?IC3ZwG`M0iOmZQ*<8$}=Iue%KcpLi8j#F5l4b5Yt>yvJqpF~h>T6!t|=~i#H zx`d(**>Gm*}?-9Qg`&1_DtJvrEcAh7``wqMaesVm82_wN%OCw1Y2AvOk-ZQ zvLG$GuKaTr5-j)~<)7=R!z;P}uLosxMhnn4Zm$4(NP9RA9SuaP_Z*=F)x`*C?M z>=nS0(YVSMTmQ}HSPL55KmeY+EHwin5Z?k@4ehD<5OuZ1sF$s0d2ms2_)tU62$@uU zi!7mE%<<1FBf<~5<*T@RK5L>2m|JzBh`M^pA<4+x7@rI4=IeRW-Atklc69@5gDpJ= z%j7H>;SI}rG*QtSU}X_n<6Co)&sp621|4#68%;OT*$09Q{jsID-1!j4M$IdMHu?f2 zoPtEV%7`};z+`#n9+iCI4U{hszgT=SQVCv?)2MF2dYBcU*-wwH8NLUHmt*{sRt~Fh zzG!i<_b&IugM1wS{XkXV)f-Ur)rsO?lFv&p!VXW4wQJQ&4TyNb?4- zGs}xT%&KZdQi_DKYw=C|;jEXfvg(j=K1~XF#$c9e#F61WD8?WYC5~CZ$`_6OOdT$r z=WN6BP^ObHJ*Q0B%XMNuY&3}M?G=^C0e|&hQXKuOKuH{*~IY zh2ae?G2%t?hJev5k6|bT+JoW7S6SoIKxa*m$cZq57>?~bs%2LTxH}iPDV=>b*(9}*myli2p~IgaEwo}(kaoHf z&FvQ;(!BiXz$nztOSs`AL`lrJh#NqvZV%OXh^Lh_hNP9W742qM5Sl=Uz9ZPJqZo8Z zrH}gp4pT7`-r-V=@nx%ekI#iAcCcBxagMtQ8aqoPm|AcNMaa9f@e^xd`E)_|li%bD zkuA-X$0G#1FFF)}d3CIDU09^$zj>o>g>RxmsKWd{mbr!RtLv;lf1>doCgcIpRn4u{ zS+MHAFHeu}ed_e&*K}VLBnm)x9F(}T zuPUN7r1vWhTRi=<%Q%#Zc^DP9=AqO9LnnxHO_kxDI+zBZp(f7_rD-ZaX>2+JaUCrx@1g<5AWc z=pDe}AX{wOu57;o0GQ{$NlqtL_-cv{&UPNpz)}0>bREY;6LaQBfZv{U-28|uX)zYI{4G2g<+S@5ue5AYrw$W5qf4XiW7VGvFLQ`dy? zo~zveq!RTbWFsi}tMgvEvaTcuT;gRa-{PB}DSMeCWfV0TBy!^x4KZ=sT)B@d>`V-iT3(qov^1OZkYj7^2@w%I=*#bL=!7S3EwfdrjC;nMI1jx zu&Mg!f*93)Bu9492sHG1{KkC1Ski~PGvg4de?e0;y-RZC;y4Dt;;G4ZsNb!fP?0$a z1=MqD$x6Y8_ci#67}G-zkzP2l*(JImjO8Lo&C^HWoz34{PfC6CgteqZ88Jhf^3T1_ zs3uOX>xE*@7@Y6AA6JYv8$w99FV*55>)GQYv$;4c5RvQ1nkPT}1ZeVhe0t$WWpj3z zWxJN)Q6rO%vtYhf{SbYp%bHT6#xFNlIv2ZWzj_)p;oWCs;zK>>Xai`+&M%d zwK7>r(64Q^4ZENi@gq_fe131zi{BJ60&T|t%^8Z~0Uu@_qv1;awhhBAhN3MEH1<{_G5Y*>{&QNZ5{*3AwCy;@4C5Vp2u^-On+SxI9Dp#H zwG_^A%pzy-2PwVBvjuyUs~DB!=ppQ><2|u~hu&Z;Xq6)ogp%m>*{VIJH;l&zA15Y|{B2ZTx;m zeLd#A%g}vn({ou^Aj{can#=?Iq_2@E(`T;DZ+<@vqI?^9LtFX>-qnc_$k`cFs9zPl z;o6F4jm`0Z&=SuE?Pqacl#4{WzhL`EFr8LEc8L3r#wW!NR969?PF?epGK9A z7x=5WC`0IQ5Tr8R(7wu4JQIYIPbq65IH`KQ)J|@o`+iE^X3Q+0N9ee9KR*ZKH-TyK zBl&<_5}OO4y4Ml}Bvp;iL|@#RO=hN3-q*G?)WvS% z763AD$dA~?flK`6^9M)2rH}6s!H2FC$X^>NGwzsg6;;iAH(|z|PND-Hw?o^~*}cbz z72sb$Z61WJt-gN5%6~!S+>Bp=*>uPnxLvCXefRbo!$YlxO~6k1M7#)Jp8H|tv+V^j zPbWNmMRbMMbV%M*9rY$Wo9xylsfQHh`#)IU;;`1-3Xi&bW$pH(L={?(2yC)47e%>L zjo5Cs*iGW#6&huuh1_r9~61wXQws}eu$*gcF%Zj*Fj zw8&g#8$JI$JeQL-Qj7>Trs;OV45|7)n03ErJ@r|xVDEJ~w{nB|2j7L$>oh4fv>%>) zUsGy-I?k6d=wgH#EdY{#jJv-D$SG1^dK(}t`5)gCzT*9HFqW`qr%1#86=ygmp|kIt z)yk_=l@x6zCiVmJTgel84e!%Uh z`5Ic!Ei*)=f*z2Q`Gt876RO6X8de@RT^Z?!X#RLw>m?MGx+TlbK6~l)^!vZw1`S>k z^t%|T9Q+=;((BpvckZ%3OkC?b2XRj}UqN!!)3P_Bv%hibQ4=$7UcoAT>MK1Z!hfvZ z!iVg>HzZ#7Jj9HDiRqrCoavmj`Fy>uRJ--#u`KjjYR}WXM=LbBFxnu?tz~osK2x=M zO~k=F!?1I2<)t^OcZfP=|F6DF9)x^4f)j#UHPcDz!0yvLL#L&8C5|fhSCR4gmpM0a z@bOeE9tlFPiVcfoinKLq)Zzd5Zs+gs;D%cu#yo_{Qi47_p@TZKN$kw4QywZQc?1-O z%YrL%8Lb(bV0u_vjM9SiqaU0^cZJ!CL*)iygE13)HR@DxhU~woZ--NTaN*#Sf91)S zCH*RwB||VO^;CJ}Qk3IgMiqycL>4^}q^pJa3>&9tux_;bq0KWc>or(kq*Vog$Zc3t zsmKnFmcE0Kn=f;l0y=*DI`dhN!m|IR#I;vjl&}-eG+uXH5^Y2;gD7BB>Cz;&+)qWR z9-M5mQU#KgWz_!|J=bCF2NNRI6{7iR`N4~;f`0#)5OAQ>Qz5Ce=afA7_hA8?qqk!; ze762JIJ|!tTyi<9oc%}xl$4Gwbd6rmMa%ip7p-SUhw@4?+bJD#KuSS1BCJ#G>6=G` z{gmjx4L}F~sf(=9#b>FfXouH?%F+YL8dPz!FA4tjd3zmZl=y=KL)zJ_7ZJS$APn9O zI-ot{ObjO)h69sV_(uzNDlGqN0lMf8RXj`1qF!t#3lno?=IjS5%nUydfb z0pDwRS^-0Sj=kMk7wNYn2Ot0t$*=e_LD(G;(6m69lX18 z&=!KZquo?%(F^#q5~-G_?y{lG&&T+9nuI>9J%waT26qbe`F0Op&D6Vik3iiDS0|2U zM**D+N^`8lM)&JYn5!n`>)a%z9N;TPS2ZU{Zrx1y^&Wo&Jz9S2_L9W|sXr!gs{jS0 zS$<4R?}ih&q9r~&xnArd{I|&^t9|LyR8+A1dv>?}Y4m*%F_z9GhPKE%eIw1v{da?t zFE&S$jwp!B)|6Q^GjVffCgLGct(-ViDZ+n^pWpH^mC%26>gjy=iaiMJ%}Z&&**L#T zg>Vy2H<}x(N?z~J7xc>hdr=6kMZucv0~wW`gwoC}=ym_$D)v@L)7O2NMYVfo7+&;5NX92S4F6$e030- zm}!_}gU_?IT!7De&%1klqPVm^)$KG+g8Y#E^}IPlbe`djSKt@jfpPOpmlT0aW36Dr7-HP>4%^HCyH=#wv#{|7_I=%hq&~Y&u@}ZS8 zRflsnmz?moeG+^025kyB7%z=I=Vya^D{tL*s- z?A>pG03WT*WR+h>j8VNDgDA?ekkTY58wqnu8DUTev`iW*H^zCthqmBzYcltPDX&W>wI*bst1vy-!~oDIL5V8ir7O9vlh6ZqYW?XGw0&t>s?N zl;xsvH3zKTva|`R=9)PfqvLglG+FKz{+N1`@!Vb46q=I+yYJ2}l}-V(p!)wx{y6x4oKwF$?%?rej$^Vw$|B{R=?XiD;6{m#bEaC zV|0V2ZRp{6Pu{J5-a#CjI{n6;b)v*sP3Yf?cfPzaUhLd&;{Ht_to2m$;JjZ{o?YU( zf8rbR0L!E?r1toNHgtg{^CI_g5-=zp-lYNSnM4-(g$TJqmYVc7(cv*8SxK9>6i(0-QzMg|5e1;)%R((<2 zh@zF|MUIG;KrVBiQR37qGvYVUM2)X&?`!I1kwn)wgZ7u)^sgbMV{8}J<@NY%CQ>8 zBF%S)pr@#0iE`K{%1;H8$$lO0p)k)UN3)H)6iEp$MB(%$Q~l^85dFFXc4Pik7dPIq zAIvwji{K>_!&xtQA6p?r>vCLxW_4U>7;UzR|^09nI$n2u&(rCMJjKs-mJ42Wg%|oX-kQs*p>1qYS z>KwS7tzR{YwP2@a_;(SUX=*?k6wcd~`$DkiD~WvlwWxR9ImL9T#fArYKA8%~mh&t> z4{*&d%9Q+;Oj&Fz1LPDnqj?R~MUy@mAW+8NHg~S0!4>0mXN@ew^_lq9U`OKx*uF3W zdqBKazAZ=WL#f|racwV{^EJzn%@+yEESgCJwRb3PJpX&b?n-SL7Nrj-&%lP*UU&?j zB&V%~&c3Q&ea&eW@^qdh`=-f7IavwmRZ`)YEsJn@yAgyuq1&(Vsmd#n49 z0iY^gXx-TTen(o4*6!#`yh%tShhFy84#FK8W>*sfn}nMr+QX7@uF0GU&baDHnSX{8 z2~SRjqrNWyE>Fie=+4gmhj_BO2et9r&zjTisiFRz5Pvpei~e)DHF~B=)z0$;eyQ1X ztKV4rdYnsn^m>HJqP-*&s2zK>8xd(j{nr$oSYQIzJ0L-GAI9_kbj0c^iD=N5Wabj^=w-XGAXz^5^GiTqV`RvIlsW|laC=O}&1KKesL;|0Ya-;my zwGSmGaLdtG+0X+J7xvY!Yd%~XY_4}HT`+e^EP$5AV`r1}+~^k14C73Hd?mS{b|ET) zHYVUZ0PJ#S*#xZAsd>;N^n&I2F`z)4L$YuBonUHTVR($6-S^|b005cAUP2Zf8>`Cu z8`@zntmFmdmVUJ!uVPnTn)` zNCXC5-#&<#%O%xU(E8>}T=PS@yfa%}>EUJKTH=e`Y7-zJK1&e)zz+Xx?`k4`t|Yjv z;A-y0M8Ijq4}q#Ouj3c3h zX;rK?l&m63#mrU0A5`9RS@=m~%&RJAU@&+mZBLv^@@R!9;PoKVoJRE5R#wrSs;x1K zOg#aXZo|jA5)`uIpB1Nm`eXc&r4 zy!pW)s+{U(Ee->ts02`|P0uY*=n%lU!e|5Esm4~*Ui;jOhmj!d_3uB&a8N3(#=08i*@C ze|>Uj+6IEV<*FqMNc}){d>S{lLld_X+*jWmn0g(e-Am3#^3H?-c6}-RBnXb?; zp@)}h`wH@`|7p_^d)o+%az;3Ao0A{faY;zVW^C8m8I9aw{Ky|fna3ciGxNv@e~i!k z8J$MP&_g5I$zBl6LXgIXI`y(L_C+uK@;CivO`3V|NG>$$oG0fkD*y zk_j2HvIS?GWzPZpobZXu+QpvY(?{aX_LD(zS1CXo7@%mTvve(W?+sKiR^Y>L4N(K7 z%uJa&M?rdh6F_|~=IzTfl)ck%OfO{tvVk@)-EmX1n}iSFiEX)7<8^__1e$?%6fZ~L zCgGZ2zU}WTC}*wd(}VS;`qH%$(UTn9?g&&WOTeYePf01ooMVH(`n%kfuW7%-(HzZ` z*>Y|AU@`cX(+_-(PS(rikH74HS@ut1ZKL-CqFt8*F5x~MWWE1UP;CrHvj?$wypn8@ zQ+qr=lk1lE>+<@!)iQj)SJXviru$&Uk0BA~1_d{sV$96w34&;1cDHrz&EZ)88*C3R z=vhG1I{Z;ywnvS890rEQ=m#DKBjQA`qCWdbQ=bP^73e%ul>B+K2u_%JG*9$uJAAr}Fm*v~;>m!g1xKVI zMRD*CocwyPiq#)X1uq6_xY_NMgc-jLO~FlP;j+Q+fEbZ63y)FaJvWs-Aud$u=9U0k z&2+KlDm>Pd8GHB2NbM=CL2EVB5)dHV(5|_+u$oG`_R!T;Znav1VkYE4#-%)-;Hpjn z2^y@CvQ8gnj`bt@{O&4RB4^yW4b3KNvCnf`icg%Etf%J$o(}OpB#`^yzTSvdRe_UY zCZXe5cFu9Jn^A$-{oAf=P2$}-9JeCVROC)4OArxh1HtN8c3&plZWcZ-bn072B<_a{ zV`jo|J5;}+?WTy?m``Q44~}LF_7%Tm%sZxIh-k$r3_Q@3bHBf**X|lnQ=f%1off!0 z6s_8#DZjmbd4qm_S|D^wm6aLbKT65FEG0^bKRoMH&X7FCO4LEy!75?1NsA~{H#AzP zm;Qa}No=TIkFLag%Eo3J+HZ67`bOElYQ}Mhzcrv-0E{hh^~JdIIa&oa(sbVAx3Tv9 zUlbr=*sq9B8g_v0*o>){y4lso9r9yGwHcX4cR9Uo{>&=%z^I2;o!&~rrSgP4;wq0% zwyWqz@#9u@lo9a20YWUdV<3-w&t;N2ID1eBZDppGD6|8cpve36YL;1Jh+muG+hg&l zNm$5pXNmAhD52({6a$&J!>yC^LhSBP9pe5%s^T~_lkA$k&BJM-qE$GM9D;JqOrhI0H#>`fj`W-^LRkr?wJeM45?`FkAv#B`w$?oss>}WwQgpauM z;;f<1L*Mf&Lz0F5eAhOa9Ta?&?oOZ%?D}Tm z*7eT44aR$<+;`)}my)-Uv+}2Qea>$oacVvQN3|Lq*jn6XtMQ(~J&u{ua$ga?o_Eox zH3tZpdoD`VQ6XT#t1P2{)a->y(2i~J#BLaq+%JhZH>-690)seIx%CD8ez=o%tf`O4 zwSCLtZRi2Gx7cNo?pes2DYw-4`b@7WVBcS65K{huhB%~+(065w8X!zY3Di=s%qc|^ z--%t0Cg?m{k=AX}`P>w+{_0$HD>U)$TXb?D712N;-C_R%XOd}x(OF4x54wHFq6B?l z+wXR~O?1yv#bz2+UiaZ7K=s?`IVN3M#(m)X4s2)OS6F>l5HkyW9(~LbP+$8=oT88# z+R4hUzVkq)B~Hj{wWT2zrNDzExfl8+=b?N9r=ePV=;8Z!$fA7n^Xbm>KY4ReieQ(C zDikhnab235nm$R6kF)=L|GpJ`nN2|?NGfNFg_agdX&u1tr1$7M&g~PGZ`@hGpJvTa1=L^C=N0Z!BlJZ9 zcC;&qu^C~wxJ{XKUWKk$C}oObOd0Lc|9H+}ohMbadU0tK*p`OJBG&4=ju*l2vNd+_ zr477zV-l9w{T?BIJzbQ3(^~{|6#lqlc%6#`DfUf&NA_=YlHe7A&i{Nx;c$3#HoR4y zd#KUBcjAMXqS{f?QU?t=`}>+j^Z(TbGvq=$Iy%&;mR9F+7-(epe>O5P_2-SgrT_AU z4QRcn5?OfF48VNmS-yD@2Gju~B_{=RG6L%_C8}Kfljv%}zJCQ&%q=TCl;iY?iSKcY z;{W_2<3csY9st@|nLVWFVhVX~%3RW)M}vGugvmE=1cja?1N~3RK=NAN7jEoJtqdad zC+L{6<5|OPOnfuXT;QW}F;nsh(8iqqQVCC|t^_8ImDvIi1lWaz(}Blu?W5Ca*M~$T zL4UhgEQC8#RT}Qybh%us_wMg6Obu3kCB+;Sk!TC$bu0NTz)nj(Z8I;nmWx}@TgBjh zR$WjHYRVOHe5_d;r`PwQCJfKz@<-LX|E;M1sN-veVx{-ut4E-FlZ15SwVbQJ!C>iA zTo{hS`aj2-yk88Uqz^4YaxQiVpyJ|nCpMHV}-*Z4%F{3NA|jv88?pVmibabU>DT?KaKe3c>JSv9F$W2)M2g&hcYA#yvUi%gt7kemH$$?L~kODEzW*rdRzUQ7OwfcOS+;inb-)3&up0n z|6*cc%{9mD4LI8ej+0a1+`9aJ{-2KbUkdwQwLBPd+`7eeg{wS_^7hHKe>W`O7j|tp z`R8XV%WU^Iu8iR6$K;D$7}?PO-D55_>JP}4Vxzf_#gRZ5q5FgNWqpJH`|&?3jr2s# z+E|I{%@4?<-6n6Mk7D9dVC|6ppC0xfu7}$oV;_iZ8T=L~m3md&`f%Ys#O@#eKkK?! ztxD^@HyRGM8{cF3`dPS!srO=}Dqp_mW&xA_{@;85ms?HuQF`vab3X1Rj6@ve>a_;%>y9V%D(Vnc5UmE`FEHF25iDKP{Yg87n^qFrK|=qJ|&l z_BnJ+TzIfz;(xAK3u!BB>9R>syog=WYUc^D%k&SF2IU8#X;y0GXQPAjo$v8E%(ouc zg@x^-eEXlM5O1TJjsDIJ39}LOj*FSylvmbN;e zurtI$e9=d_(R29vLWrfrzEX7vD>J3BM5*l2l44u6R}{L;d|2`W!i1YnzZeoFctq6p zgl(2h6^3+h<#oUJAZqHxcP9x+g0(nkiS<`OduF(GY>CgU|)b_Nfli_xze+T#fKuW{kN_P*sGS^Rx=d_GZ|RFY;t%R8#G&R@=xlUDRF7AFh(sOhVX>~6RDxYO3A z?z`O&qSRViPg_3(wvYqgzjgM=g}L3{Phd$X9gGU;pRQ@!`fFG+Qk(o1x>NV}XX$f` zIUy~=1|W}mOQrIqd~{w;>!$rv#sZ@t3x=IgIlP~1qDhm5VIzM{?1k~RH6HsO!{EEs zPO~$D9fZaGTwkM`&dXJ&77gqEX?Xb|R zc+(?fg@KYc;KpK@|FA1(ow83;fTY~7yt+0Dx zcJ>TnOdPkf4j$&SYJ=AKH|{3(J(cW!K3{GQchYO>bi5BM;pnb6dtNJL6rR&H{#5c& zB@x*b4M!^7dlv>3t9~T>bXXRwaD`Yv_F`>7J1i&v`Pd)RiV-1;91X1h$Jk#OPsNd6 zp1h+#FzH`qx!S^=PriWDXzr>n%uAAEc6 z?WFFE9co7#60?(wXNjdafcsa!rc<1(Hf?{en6P$w)~0oEz>BsH=7+Ch&qjcRuih{W zff=G=XnYp%k4hUgkcBm9G-2x*r5oC1Et7{2BW-8I*RKgL_kq95S$|=E=?hkW ztDTASpc8(3w4tK~D@PbMNa{+cOM&E=`{HdtG+K&oi2C*@?VHC#=2Wf(A(Hm4Cx(rI z!b*IUQ}&&yjn0wHwJ^yWFGdST_>ObMh7jlwYur;R8{8Uq4$!F^QR^vuVeP2`V(W&A zlaa}~rJi&ycc&cVRpgE&A+{Z2P5EJ=ApqweM$Z4@tg7MM`d$O6fa;S%>mTqM4Id+B z>fw8S*wi1QW?_IP>ou5P%3iH{_)I-o3$tCYTP5P0mdrqe!gQ%=zfBpr6iY-)Tx+%} zBud!xJqHd)HeFVWW1^+1AvxNbEYg)I)KxSQg{KNvbS3NH#Z-0bMi^qsz@ecXZvX0y z|52}2p3v~=Nys)cCx7K;%K1zD4n5?xNhACPRfDF^BTBwSto${v(MvC`(B8GA#jn^QPXJ*gp)Z@I0I7}4wfBb&QN#mD<)p*0heWr9ZRqk3Cr8~46!o_3KH^jf>s@Ahw>AmK~v6>m;rSfmDj%4X>D`#5Q9`x)s8Xhd}{8DxQeli-+)(FgvFzK4lgRVaCdfYSsnDnQA z-Mue1Lv!|1=!xCnLSHr?0-PEd5pdfJ>$CV3fao|Zg4A-adBg$}MeVZ@c)UgpHC;~C z{bbOx&}ZF?!2)w@tk+a)y{2AA6sk+*8c*+M?sgPE3mdZAWo|Lnv3R$+>IS+PylVu~ z+XRIZ+l3gGl`}9z847(d;|qPO%BK!7?JaX7leVcL^jfl}WEKn=T^sJMlMHkXPrggt zrSzWOb=80dd!Vtk>r1RfpH`AktRC#=4kqMoHm~?;Gfqpc8b>a7i~#)~s++4=6MYhS zSVNji7EFis+EJZWf=I(*hykD^^O|jLet7oj;o|)vf_l7FvABhcKE%;uR`~Bgn1@c= zbjylJuV};|GD|Xs*Km&ZgkR-U4ToVG20G$ZpP$V^VRGSxZPQPYH|EAZ%<(4mod4w1n(H=H~4B=PA z@TESmqLQ1X;Goy{duO9P_;e+aE&T45#;v*-rhN<&kBBy8)49beT%uJ<C*IOGQFh6E(l}QJ1>uTlZJ#(h4?{h|a$k z4!O`^5UyJ~4-dCfQ%JP6)ZeP-?U`9&C4b%zai9xAYrEMDA-?SfTa{o`J={4H#3UI+ zXPoS`X}z^itmDpRXXX3vUFlXFiWE!Mt&9m89>_C`jtliXgnkBv726>~njSTD77bff zM6OS2f6~<2eW<6XESH6ZW2RgztL>L(ct;lZ!eQ2joSG>?2|;ReW1iC|e8_uyoJ;)a z&eJCcq&5sanP}Q{>LT&>gr)oI<>xvn>*wtY_m9$#f08upf~(=WY&;ouIl>?+uHYy8 z(Dnl-zl~AEH+6j9o>{4D&$*sRueDjcSf@XQ*K^%^f0pd&ngl3eZh~B6;%x+c&AFAQ z1H0jT;BDmzMvGIF-&GA`?0TJ6%$0k}6IU~A*%#FIMFndbnq zP#cLTBv&#&HG5F+an`Jad1$>=nB!MUsrL7#?;b~3p z#9Ri_Rp>Scu$~65o3n~-D|6|Wlz=nGG^q`6jMlSJXG(tdqmZW{s;tH97sbUuXm8%z zL!*)`2DKg3#HdC?y=tMfwxhJnS@8=XEdr!$E>(`0bjCCdl?ty%1u~efohDJI4jYt` zJjl9D*Uut0lJMk?(sIXl1Ey(3Lw82Xo=LZpdOfSpH8Gbh!ZM8Ge_RS-dps=u&Yr^y zZ)ijEQN=aiQvEmD3#YKth~4FQJG{Kw^Zbk>i%^M@b2jmZyh|}fn$l!hBbyeZO7g6= z=hKxJa4L!5pYQxk@uNiru{!O1BhGmEAbLPi8V48!OFl5IbEkfO6x()_556B{(vS-e z-aIA?sC3%>&7Xs1cib=gDooRTZ8ZuVH*nfTT>tE>-V1p}SG=h@znK-|%+8uXyq z5Dk)fPWzcO0{RFMcRci&?|>9hk=x6}`J`gP~>|eZi0~tA(u|T&;Izh{cp@ z0w=oI9sQY#_rFJkb$1L9o92qbduyCImrE)bHDaGcjdH(9z_M&piuqM!uj= z?XT)j$o-qBcWzZ{8MUId8tdveuw*G%U!5nPA|`hjmRCL>c0&8#7gi{n1I)OZ&qX$1 z&YMvlJO&)cCVO2x<(BY;O4#Y@7mA{QgA*;2(_n)gXba}bn4j93mw00M|0w(FxGJ}8 zZAB3U1!-vs1xZm*dMVvVcS|Fk5(`8?r9(hEMY>C35z-*i4bt7sVy*X^?0wF;`<}S> zet&HD4_IrybB;0QeCHVB8P7;x`-K%&^$Y7fPrV?L^+pBCRmq#p?f~7tjU3I10_nj6%8R7>Zx z{G?+4B7#?ZVEVh9-=Yc{ZGc-kC3929{2j?wkPrdRW*syP+Ho&grg$1D$Jqx3HA=gm z?4PI;89wQr4MRXW)i3Zh6g=;3f44H!sND2cpZ;n50@FngLTPyGD8uR@xV=5k#WL!I ziOww;Q0l=4kWilfzC>7g_rj)j3-hPOPc9j#Tg)AAV+oW7?u)aa5Vf=mj>R?5F0%GI z;UxjGDK2OPcl02|Lwo^V@8847y@mI(|Khwz!lF>=-PQ-fc3U_SWIgU+zpIV`9V-*1 za5UD;FJ|MRsG`JnpUPFZz1y7A7+rDUZO7%F2yBb<6cxrTA&6HJmqwtyV`owI0M2Ub zdLe1R9f#TcF~aLu#N@H-7GO9% zY&jocw6J?LY!rH5;m0xKj0tJvZF;U#LcrvIuyLUUD|397Krj8WeP7>Q=p*R1d*<+|(ULH-y6DP6?^Oc3_#>Fw zl!YETPu<*3N?UlwWwM~MzFl+{E(i6UWO9o(pF?M^>qDJ($E;#Q5jXRLzF|+-s%{z) zrRw-7-XyRK-lySle}AFjbeIEf$m~)u79cymZ{>@u zMfW9vIE2NkPS}-6wrT&p*>8oZ5zPzE@Mw{l!RB~c&9V4Vn1q3eAQ^{z#BmCxG^U9C z)ey!06z(OwT9>UzG<<`EoP#7(?+_Y4$nQh-Ewq-I{p@(`-Vy+cA-Ntmt_pqsnk9FmSh@3Wt+oo-XS7)Fy9-q<{fqu&Wv zk&Ei2X~Ag+p0FPVL-+5^^8(WF>uP$y!m-SQmr>b6$>$fS45#{%6)6-ROuZo8YD_Bh zLL9(0L0Bp$A^9ba#s=efTFMu0j57@JtCBBVy|OO8=0H(6ol@Kf9Dqa0vt9dH8P0gp zS(8`G?fDJ)_pDJ>tRqy$7mPcz=X~PEqFovOXA+?e?SZ|V*sbbAn#ia{Ps?=#XuK+@ zQakR}Ntr#+xsSNfNd~y2`*G)6eXmEyUHE#s`0!IBpH+-|jZ^)@ zFFMeMNn?}G-uw%U;~FUM9Q0#7rv)yvRgZ4IHzpi#lRlJ9AyRv;{a}MRYwH`b7JI&Rihld}t(^t2VdLku%C9IN*=x#A=VwP#k zrugK_PJjfU-&rVj^2$QixI<(osFmMyCoMR$?Y8VCp|^JBpVx(o&Ia!ZZvX-}I^?6q z?xTne0%B4ejf4}0eYxIKKS5o~qMq_=xHp0^!hMVnVG_7Bxax&Ex9|qBCc)dfGST;N z0{k@%sQyrT|4e?{;qo>}tuDq}Z>&#MTF+@~z zQUqydjLMz9#H(}w=goBVicAs9J&vmX0V>L>-}ES<=x$X({^$=tG0 zxzMCODti}RcMczDag%r3^IvIkP4QsAt$5Fd5;Q=D?lqv2cHYNU+2R2hidtpg^~&)3 z&1#zpE@!nC@X?=CD*Ln{->#()UHmBA%eR>rRr^75xXK72MDR6WVDEkSCIZg6IQFGc z^8N$SVT9<}0_k1LdpXdc#9*0%7rnqqK|68=B2WwjTw0(7pevvzwBb2iA@}qpk~mRD zj>eCcAx6HUT%ohTTT-Eo-`@_?Yx2*LgLj>K+eM@GvBSC}Sz*I>@kubcDkx{ZL#A4lm=AyCb;++(qiw>4H`e{E~b z-gPF}iKAZQgI8eQ&8`^?U}F$1jZP zI%otOuB)AgrVc$8$lHUvqINdqE;f^>{F8@2LHL+Iwr$0~>AM|I9-_~qx9NT#{NOIP zgu1Op&7bVw-5PrdxZL}1=675xj)wax-hZH(cg%QjGOKpc=l|$)Q6p3MVEP3ObW9|e zae)=4WX;cgq@Zgn*0P(wHi9mFBX3d1Gu_qqTmmr)0)rhKQIx)_?XGWoTh9={!w2bM zTsSyL*0e}KpGprjagxUFqo6bM^OT%XXfyLZZ@ExAW~aS#!M7x2J=zsf!|&<7CByvl zmD{|ORwLh2F@p+W(H|#d&CHLnUn}L@byFLJmUkdhA#e-8Az{BM6U$yf1TFTU`2 zHsfY~Y>^Hw9_-LAjz9LA;<7h>0Ka?6ty&;wsVtyuIz+GhaU$rZ z-^?d4`J7M?Ebh*%__T_7fq$?wu1`KDs`iYV3gsYOG?j1vg^|HxX(PRr6N4pt&hH>s zM|Uevo@nj*H8HZ4g&+CsflszJ7trz8Qj_HfIMe`Yj?QVCu@GlI!h%J&pbhv%*qm>X zLv-6+0JL>&=mq^Aa1)X}-{luW^EEQZEI4`MuX1npmgmLn=%N zRTVMh?7`1uyK_RoY{z7s$wnL75fk3>pE1D^0rf+I2ScM4_#4j`mJZvznOTg*D3XuezGp5lh6eV5*U`QSAdq4Q+zLmV zQxYfeI?E%+1QbV?iTh)vIfBOt`@rxD2V%tnS8?cR6eUnvPT#Txsjbr94WH^K8Ld2W zf|B^ea5OCT=aW5lIzj*3<=>OPdSmqIrRzmC2XIJGaHnBE->R3rq3l%%b$!U=Qx^(n z1FB(z98TaLAF>3i7RMjkaw~Xe-eU!D0dK(3`@yvARDzKAeDy4)B75Lkt9o(!M#7K# zBZ%AVpwyS&m718f9!h2PyhH*lFy$G(-(T?0-+Z!;WAeK5s4v3prsT*z`(tu;T@dlJ zX%Ed8;=vkmk-(H;<6hu!zLSJ?dRF!n`MV^<p7O3w^R1N|llrk>CqbdU7}#N5%26 z9&f@oXq?x&iE%W$g~<<^uT;UKvnq?J%HcC53xhbo4e$Utpy@j<4ljch9rxzPmWWAIwgj zEHpq5@SFL$W-H4m`aF7v^mB(#$1r~Lo{lZM?vVnguWFAQj{t7JulZ=>c_#XqAfUqK z-XO^l;8jfkr z9&~*gPT+gAT4IMK=IZggsYp7ZL~GRnrOo~H$*nEhSDX4Zz+=YikK0ote_HtUJ}=sQ z2FjWJeG)gXX#EOUr>uIDaE1zgk}h)8b)(*>_N}X*Q2_Y8*>OR+aw=Lsb=qb|(2aEi zN|`?9@#4C0W;XRWz(Zc*t|KT60lCe7#HX`I8wTW%*-ukO)#~fA#QozH@B=HHt(}`3 z2KAng@^z%}HCB3Zo{fkg-xkdHv>Qt?YfLl4tF|`c>_51;CrXI$e%}TBsjxOH=ZoiD zo?l3c>AIMw-Ny#^-l?U}h)&k(5S==5@1Toq@e#U#udh1MxExa-CA^ z{$~I9)Y8GPo=kY2CLCl@mE3AM47?>$ygVL41kYE#4JAFGO|lt4S8yP1!%?GfD)a#y zZT0c?!7PM?)1b4VJ@`$;Of83}1SpUpdiKV9fGpHJc2nkAw27Y9@^az;=HW+FQuzZ0 zeM@_pj+Z$AybP)D)EVPzmU35t&bbf7R zJ~t!-Llf4tzqLRpLvXhXKfAfIzH1Ugd)mULUOqZJNj9a>M*IGPYX3B=X1~9Amx7Jt z5j^BZEEe7##>gcj)K`cq_#~{e0g_MVBmS8zNU>cT26{1S4Gf+XT`L!C51NIK&%kJO zkBY5(n@$|jl`VRmy!la7Z>Avq$-_WS{w*kFT%3mU6$6W@d?kd{F9eyF+V1F`ug5-Q zu&R7-eV)>}1wTz*)_u0zF&e=Y5H%?^3H1g;JQUQ>T4S^p2Liqe7xwRSB??+Nb&O-A z|Ck*W!SLIU!s|jdQBf#eRBSJwKv8Wd1qeF+gl31h1$l&Cz@x6&vYr+PE!Yd59~G&# zZKco`gFbc_c|FF5O&RP4ZzkaDRQc{!G|dIsHIN@*sPq+b(*fDgm7u8eBlKuchT|Yq zMktM%WhsILF19GX8(%?w;y$f8mz@#}aCeYwA9qJ0&L4Q~o^H?CZCHnV9Tb2^X;-K@ zgoze0+C`yhhK?bCbnOFifs>gQ8Uc38^V#LIsO?*UXDfILi`y9nv`?z5#yX5Yk8U(;5fxDVEBo=s`|HkA*&#!+!egLC%b~Ke*Y%vMnGh z?>OMPMB_~h=JnFTda={DGU4n>1t z+#xd;yj0pUqI8OEVHD0czd3_?@zTMc|DkWEY!=#}Ds1E)XK&aKl%8qh`0ijJo+ zBM_+f-j42DM^&Xqwtc_kpZ9smkQO;mnY8nu@FZH7R;#T>3c=;z+w}G*q_PJSh~EB` z7Hfmjpwl+l;?Bs~=Ty(dzZ+f3w3SiF&EqDVoDw@RT@ z%35hISqKa(n#f^+=3@EzoC4GW$>RCd6P?+Kxy>ic-kyZkmx{fR$GeNmz40`RYZ0gm z%jhn4Uiz+y2b@o*!bHCvf8XF((O`1u^!Ykg{#87#@yC~aiwG=^q5U?ua3X^yNe znT>=LK=%qU1Kn~rspX-bY_f=)TZ#ngr%)p;$Pl%}vhKx80LEmvY2ksO!*iyaU!CRtRIuSM0me=prai-c{P*CA~rZx2@?88 zX5ihtB>PS`++;fD!yd}#YaabVSC4jK4^A~$-;!E@0n};l9*yl%c0)+GmmJo*e(O-j z0*GRx?)Dy&c4LKQ@?cINh^p;`&kEcI>rfUH_>2tEo|TTVp`>M<9q%|^nhN#aG-uEt z2(sWcIY!o?w%n0PcIT|%K98udo+_qgjiKV7XH#Z2VCFY|uy-W}#-W%dn}xAF@nDaO z8L|iQWnb6L)V+CK*O{!)FXBrp7z+O9@S~j>?4qsA6P54K8SlGU{gkEFJgzTvfr19n zKWe7;0cl4I){&nC83!Fb7End=Be8M@Q}L&0W5(M(2iY2Vnn~jGi?#{@jv(7UgWS%- zqXt@(jeQEdehX+1jc5WswV%X9iLuvINygY1^J>1FiKu1`gUy7#_STMooOr0xi-a22 z9u`6PVg%s|G(iRJmE}+GF@}+iFTWF`WC-+l#V1YN)8iEVLk?A?3Ux-^>IOz2g{2`i zB?j%x^NL$aXjctLgz3J8nw-Nh%bu8s@~TSdD5Ixsx54FNG>aEjV^PLtz_y}czW?Bw z`=`k2Ht!^8e=52Q7+|T3l)#H)z}NdnR3W|CX$_@Toi9sf$Q%&;VTvPHv#?)_jo3O8)aXU>4tt2mf!LQkhWWT3uebEB$5!Af*OhH{j zvaypyr(jQ<(NgUE@%VwnvXObo;;-A&cly|i_Tb%HVXk#&Ii6gyWu#N4Yr4k0^mzV= zV8^JWI{1Dl;dAjKAWCP$ww^Cc}EkCNwev+P;4^-d?l@Mmqn5k3p3gc)L z*ZK*J_9xgJo-`4=ZMo#s8|1}fx24bO=Kbs4M3!!GtatpkINsnTq<{jm)(os;L!;8J*^ek)O2t52 zG9BsedsF8-nHPM+jgO2yoVVb3Vg`b!TXK>Fwjv~ofk((9)Pd?Ar{tC`D`aIM%wu7u(znWEAMg!16*=_u-a76xMTKF>?fQ4&y!ORz#>sQ6|--3Bl4`1m!{&9I( zXfH7x?%{BSNL3Esk0~Vac*KSQQr1NY!ihA44-Krk2%CD6_PVh;=u9z!uicf7P#IbQ z()=~P^1viDQvYI>)+ zv{9?bS_d0;(tye;T=%(8q*#?~@BU8a*8Q`w@6OtT5J_$veQ`1{^^2(9wh(|J2Q4?s z;oE9mSZ7%^(2*1{NZ7*OJT{1{!G*ZLa51a3pNaqAq47haX=7on>yQV`jhB+giAXGC zqMy&hl!8qU<)Tx^JmB`db6>yyEgK~tNVtmQYq(#{L$nT+CMTc+FSe5W_^PEKymeGN zze{4qD*9x`(N?4UHGa*FpC7mU$z=y2h9YxEU)wmN#IUtNC^Q&AcI%PO?V-+qGvBK# z1@Ys^3;DWMbRS%`bLl6@P8sKCVXH8QckI53Q%M$!_Ju6B5PI2$BffQWu0uW#R&k-DBHb z0XAfF(tI>jHH@oI|E+|S?Rg0zb*9C!qW47`(SoPb3hMcd@slvHEF3;cV5b>C+D2$y!>-v3c>=OfSQ&7Qn< zP!^&&IP5&zp!M7HEbeqaZ+d$iCR6KThg{&ykiGdtHSY2{0iu~4{ixf8;*)@K^^jiI#mOAcrdMgFLz0UJ7htZ{5Bc`GI z7>=Br4S*rb08Zef$eUO%SF>?K23f$9roRb}H?)^9U9pz``fw+2?Jt#5au=n0Slt6p zn3qjPm4yI*F{sdM@g+!@3$rXs^8qvp+~jP6!q!6QbqexgXP_M?iF#{-W1@3_ z)SvB_=G%v-ajD0B+8Gz|-dtbE5a$&yo3D?rq|2M0VKt#^99LQ;4weUwsZ}^8L~Xn; z+D%q0zsk`T)O21jCXTr@!4!56k*mJ`sO6#!3#I&*)L?%;4V4e2g2DW%dquNy@O`en`y! zTUs=Vo%Z$qrpw#s-qAA=d7+tN1GpD(f0ANqp+lQE!33Ah)Xol7EMpw`@R8$|MHpw4+ z!im>~Yd=t50tOHZn1kRyGafJGOfH?cSG{|Fj596BUm$@(1e0~nX;-bWhgn;`LLoe!gV(pcpEn)Z9R-^S zQG5+Ed;1BY8xsuuG3rk^8tUg^)MrMgtGnpIA6rR`85d}5WUCMs z;kZJRC{vG_2EzMIooGEDuNi5)^s5$m>;;2MJGobU4(qt;>|HIW4Yk>laG*|Gi%nH) z`uc^}-Rt&uX5lZA4>m^f3xZ3NvrfpWfbC)pK_fa^tYzvOnHQkGfwZ_#>jA<;t{gS7 zaq^C2PrhrX?B{^T%OIZY*!#TK-9sZtx72$tqfWpxA@@~X#^?TO<)W!$e}NJ5MUJ}I z(&W>RwNjtMS6c5t^}y)q#_>zlJe00OrX#Be%T|JuEQ86UHWG2xi)Gk39n^9$`z1xU zPjtL5m@hqLb7!nVCSGzWCVWkJdRW5g$~wZcze}o>ycS$N6X@0xL2@+ucS#6Ev-)-e zzX|W1E?bm1vvc#qoQtAg!e0?t{<5v;Fp;*Z(gH5h)Zug2PdQVKZA^f$N2er_Zhh*@ zi6EgNO{@l%hc240_V@GSy*ham-i_F*z0ruV8G2sqLK(Z@^P@G_AR}63G2#aTSJr}#`}$UM zG$4WM*QB}ADR2JH1<+UT*ATk+)(&d|&bR>k8Bn&6BRRepM?&94r$|yQ^5&P@9)X;= z(mSyrQr<^tawvuFV}u_`@xB59KvGYk_a7=rSRjqpdSOuYo8xX2!VIJU?BfBi8u#b6 zpr2&Q6&HmcjML@LYM>>NN$A$c#&a@|BS>ru+V*Q-{8kD}K)VhgQ?3Qh;&FJVJbd-- zNrli-j#Q9ZJDQD7)oKMbJIqpU+&3ZKH-dyS-%@Kdvz-)O77{ z9PALV>CFq-b7FSp@Y(UYL31jfC6ri$Shiw^b9o+3j!eK+se2E?>OlGuRMXZ7T2H3q zXkd*)Fks5`qeaR`VVCUEftpW2bo_Hc<``U`2Qedmb04LwLpP2x z>U^AUy!+TFbvr6UKz&bW9Vqq8_4jYZ%NO@4(>P7K4_{v(H#g0lmXDnUN0%WPJ%qR4 za=ZCe7B+Tvs=+BJY7gBFUb4Ckl+>CvN+iXV=V;CRTD5ik0fts1lA&$Mv3aB|r+rst z14{0_7dqTM`k}A;Rja+z((q(l!r<@bL2_#w4nue25$f&gpFj3} z-}@buwlJ{!_yLW*wlMSTTbThFDva0o(pj8^$2bF=NNs$&mnQof1tF+gM+i?UsiRV7 z7CA|W`e*3pkc?>!st=Nzh!RYZls%%unK04d4Z7ceV)?C;Px5f{Ca)$%x(d5&X zd~^_g;oCR*SZq2I>q@wvyhH(Dzq6w9!RxxW7`;fi+#Ll2D5!{jMd`X9z|y>~!7%xT zLwe6r)199*$1M+TvycILLMVvK8=SH16t{VgK=ulYctcq$WIu%|hkrhJbSod7wt4?d zzsip?eb4CA*J~jki;Hw^O|Is%Exdg)mbD*d0&NM}20qR1`!Ei!qqmA-(ADA=C_;Vw7`s@i)dgp7&rU`s@GR0g>P4LAR9?I-02t!ei-w=R zwnRmM*5I!uVYQ;v0-JFp-9;Arj>_oxub3wU0?z9TcE?i|6D11`&7oBN9wCtScW6H* zdr0LCyv{h#+EJR&Wn-i$qgl=^2RDc6Sj12c@I_HF{JYQ5V>a}6?tI~J%G!XL$>++t4N!zF>(vg*(z_Bg<11k; z$Niwd$DDTjyYogC*E> z#I*Ele**OR0xF>_g!*;4XSoI9oZt~5zKV2q9SXD{JYHgnZRz@)*PO`fC@o}jp+8tY zu1vh8@NO|&(sk=T=C&JMxIG==4@=j}(AgP5FKe54S3p6%Qf2hyhvn{AF)RhK0n>@< znkQbvzn^APWC;WYBJOXc75hA7VAEFX7~pMA%WsqT`H3jbCwKiPv(LR>L{9?fDY2&$ zi61?_nr8h9^X@g09}!MUfx^$t#IR*wFj1&n{o#XY&yX~f_N!Mj0)y~w*A3MxoWC!j zhC&iY8GJ;95mcFhSH{a$MW-MMs9}?zDH&jBwY^Ze!g)WlCgq=oH+V@Y z#pulBR6pOX3%|HSS6bNKs+yn%2wAE$DkKkY1n7K+7UwYfq%AQSBTmtVYAZ z;Z*ncH@`w*DLm9dEbIm$Hw;LN0roJIie!jx6GM2ScmMfuZyqk$B&1%XgA*7^nf`&V zYT*4Mv$Xor#pve#_aGpcpQQ?zoT)h`wcGQNWD&!*&KruSz7OBKQBcr$hSI=Wi1> z>OPpNIe6E%R778(cX?NL;eGc|$YrSKV>gFF=_J;ifKkXoU#>Y{VxTTT-PMPwI`yy| zFr~qcd!cs!P9Og#%VC|Wu*yC}Oj=*HQt_cqHMuPc>`eHRX=Zs8-+z*^Z`EuX6~EBg zdv7Z;>@3Xu5+6yN4+7c3XIaWj#J3+@nq|2B%05tTitecZE5s~jkkrTT!n4Ce)X?=` zhWei^>EFzpwDxN8hYf55OaR3e|H6IU9!yhxm`?Hi(9C})*Y}~pZJ7CWy^rKp`5vuFfZg4F?*lOG_eA4NTmNUvUS`eunUqDv zZ~p3Gzth0)+fvr(u!>1CXz6HR;#ApX>puTD#z-7~A=NMT$HqL(|LxTHm*xIrTmNUt z5iZ{66@cnYx}RCeKd89W0$umNoHeDpav=A))xDA44r(QO=U1(rT3+J4;<}Imh88d0 zX7~Qz?$UoJG%GG0;7Que|M>Vvk?A2ii*O&E^nJ{YyPD~RPX1qxqW>`Go|`fNAcanu z8m-^cXWZIZAGYE$6}Y!N^^89s1PUMFediiVQ7NUToRCL}Jb&4HbNp(&!2dx~Ji(>rntSCVJ#!_)u`sBJMU2|WvzMV$nL?(2I^$wGt@CgyH=Br3X*0(fJ&@&8vX(} zRKRW74}RXOLrk=Z@$l$Fh1o2%5%Jm5rN!`IZqe}W>s31}DY>oAeKsrv^c_M=5}%h< zr`*rVbooJ3#b0&9E>@QS>$m=;88{18-4Y4=znUsxb{5u;yU9x4Pda67L4&L&EW z47h<0u)+O7By7RLYV&?aM-is??!M^H6UvdUH_}vEWSDq--)H!%e;)JECljfNDDxJd zEAlUqfKMSc7j&?h1eieP3}Vuozlm7k%u37*#e%kj?-$1hpG+bQ7Xs`~rd=72Fuq!Z zm)>V6Wqss8@aEp#Mu*Ba#m{eBOEWv9$_-y!>D40p>yO>0*We!=eHwnuiJbS0L0&64 zMP~X7(Pd13ei<8Skn<^7ff9x#e`?DkCqf8Ao0{~Gvz`>W&b>)^(> zpfitB^p8{A6_x93f14mab!ym+h7-T7@>4mXFX?a02h?(M-(45mn080kpSuzrS+;AN zrWBwYPG+n3k4C&}R6ah%Us4$9(%?Tn%A2h}yzHH*6x=ASnLz4$C8n1=n+h5KEzTnS z&NU44k**K9Lo6{5#N;o3)Ocn^shXqCD)T8(^yx!C8R6v_fOs0TRIaJDHN9XY?YW`E zhSNP54|~)P$;1Mpka7L;IAqMZUzsedFXl*P`|QtgR-;Jm{yq-HjqAk*gHeAGOzLxu z#=l7XMQKgYL;4zM_94GZX3#6*>^RYPpZ`9gj(_>4<`NY!(eoa%iQlG77YQL@<5*$& zT0hhOvR-RoxT;5i|fQ zJla`Cr6gXFxI*H&E%ldGgx}r|EEDh*PU-1d+T$)hC4)GLpW*~|(@6tqfmQxma%Ynl z-**E9Jh{^TMj;i8I802HdMEw&)7f9(f7mG>cRM2J=em}<=L|nK^6}SVsJ?tB%OLvq?=D&YTdV6d|8<|2 z%QRD$U#Ca}g;zkkr1yc)xfJbmI$-ish}=`>4}pNF5! z2LVtZDdKJn#7Cgz(3JQwlhy#s?e;B ze{3fPa<&8ewaRAjcw`7}txtO&gJo8O;+Zvg`<^ycS-__);hxVIwztb6_dk=t7d0DD zId;likwe3goUL!~=TH#-#ZEPu!^}_d0-U;9cFI1quS3`L# zIzxE^+)OWGvqa>WKPVEDvo6q&V=;#_xLdyRiL7>dk^@#R2v%?Jcsy9i%|#0;G9qf} z#B(0;`i)W{*%w$(+JtK88{jGYaC!2b!@|P)~ z`sYm2L+I+>weQR5ofdRhd(ae1U(6nzp+G1gO$B(pY*!C}Sp`~hvAhWQ z6k4HbQO0DC%T@!F^Wf4n%i*(Vm>^)(gw12-<1~B8#PTV4AWHgj@yvmc2MG@0D1FL? zd!bZ<Vn*ziVJQ zVl9dnL#w0Ugd@SQC~yk<7>GE1_pTgQ>bjb)1x1uN@5-y4j&BK(9a*Z587Lh|6S}}SP4FChT7e)vPcYRR=#`4u=C!+m(UO< z^tdDWh~4E*2x_Jr=2$Ew@G*al$}$c2=HmA{co^*uYU*cg7fSh%+iJISnk z_lZAvC?1_X!p}AXUx5kA9C3k=d?M-enpfAG+AfTZU_mrR7F&?pMXPZ$en2E~R>lUo ziB{?TBp!4f*Mez{%5*kN`&f3V6$#W|7nS6B+7;1KREm3z@gzKd;;Z27Aj}M-;C;!ipc;=u34MoxIs=ay5veYu=%)uYypTg#$(#tSEuvTU=KXQF^mIz- zrkoks42av+JVqyTN3M|m$~K?S&pw%DIh;9DcHa@5{W{F0xs#$^G~gDIzSa|puc6GA zF>^KQeTjT`%1XLQ2qro zBS&-!uCk{paK@d?-t-!;blveLXLpEZ(re6>kh>){HU*tK71!dhZ)ie!Q4u0sdWi{0 zSm@E?1`Cj2UkYD8bnfETR}~&1OVgze6w9R%EH&keN5dVEQ0Fes0mYvIK26>Mt6&xF0YO&#Ipi)jxu=Q<4ESB#l2N4oN_k z%ua$G(x2ejaSob8DYe{KVivCo!Ufb3KBR!3v>XDkjw0#sL_e-}9&NhffzKUD%-kZ+ z9S_j3y&Z5YmDgVNqHIHS7HK2oLD}iZ`V8?2ev9QDyQ^NGW)2aUIHE2H2xhnH74PBM zxm2(OA?9&|*T`SlG%^_G52IHaYmuuWpA|vBxB$?g>H5g0j5Z7l7sLhea<(eU@r)NE zkKI6*Y`N#l)2%Lj>ub*^(LeVAo!c5HPmDi<)pTd_BA@lf9HEVE_~O!0XFM2IF7~3k zKj=8lf_3w!>6m}r=B4Kr8I0n3+8Gs<;p8jw-Y%f7%O$QMcuwRYgJ#XLWQ=6fO%Y3_ z2hX_13w1o+f4z!nyeRqbS#!8f&AWG|#&BzBXX53g$1CJm7rw^yRp?gtO_4-XZtUKd z$1sT@UR0;Wqu*^HuSNiFZf$Z4I-JB^whzP%l_Y*kYlYBtijKf4tCvX~XCcAw=U26U zoWDC1ajB?&@sEeR=zPxr0BkE>)&`^b$`>@B5riNq?!N83a>y{t&-s)J5Vu zEH-3Fd-+=e;ih}Mkss;P{s5CSm=$`zZ}4UXU4=Zusa>wBN}K&{n2eXC#SKd{aFNrc zKJ-I{&C)>K7s}-VAyKrKGk!A7jBz>R@2?(Nt%ow;5IBxdHLC{fBI}{&Yx2WdCZ_*n3{U4*5@lWP}2vSTV&>T?zK}a)8x=z zExsAkr0o7ZMW%`^d!1xag9m%*t#v-cI>R&@x8flUum6&1#9QQ+V7cIdMMG_~F$E2d zzNSM}{fYd0FSug068I?9e|_|y#2?9`{_0YP%KrbV!yi1rNr8b16_%Jmw>^2(@BWXv zRSEWNdCb@Uop}F~$VfreB`c`9oLp;=*YQ?EFNNvdw4!!@tZ?rUP)h0}k-y7GCkRKw zcA>LF^{~l!&gW7%$c;;UvoE(Wq4U!pxfQ}?`UqY$_d(9u1`L|)=%ZESk z`PXItpG!n>GJtKsP^(150b1Ugt6R+*K^Rd_p7nmTC(vA8`+N&*F_Xmn%l)MB z%=zZ!&N=-1e){(cjoR9ts_zQt^a=X|F-47>}RKdV-*hu90(i`|5b{(JQCPw|Nm6k zkm~$!henWOx&QbFp5UR6AeOB2UskMW^S_@uCQP*g1C$GI1lm_!w!TSji+^VjGrg4~ z9l00&V{*myCjWn1)TS$74{+wdB>V#E->hJ`B8H%}m2u%D)(d$O7(oGwsD?utg0;j{ z%BvGGd%bPpXR3_Yqa2j(zmybhdFzYpaVO=Ru^QaHMuvCUK0j zM^A&(N0Q=5p@z`c)DIT+Fqc%kK7=l%^O4~dWb(OVsw?q~=upq#4Ffw$)C~)wdGpFa1%_m^oGv7y|kSdRks2AS#=V+fmwSi&%blLjvT`g*@ zY<`KTJfHH|AI`d!Ju|-Y#8BAb410nAkR8N?%}j7ivN(_Aq+XGcQV zUR0fc>pmT@DAi+St8Ybr{b6;U(y#{4-Kg!5bAEI$iSG@ZCgq$bkrxz%?f|Oj^aAGZ zPmxna==YVchHpir?e-``?4BpuvzbBJ7Y~aeXkr;g7d4d;_DkMbWNz(^em0xV8lRRB z9}DdK_OlG$AD$1ZFP>Y$-&ek0Eb=z%iNhaJ5=~l0Ar6oV6QX$QG?N}ZS!~tcdC^g% zv<-SMjrboDpzvl@SzDVH#MJcbZce_;6?Ob|AUX?qVupAXHhnySaJ3q{P*4n;fL@{- z(mWQW0oj6s?sf?2I2&+)fkWoH;DGb^{LWUKUl^5e z2z|s04aB)y%_WAi;nWLF8w?=6}l>nZ*Sbc1t%@D$z49W~s^5RE9A9Y4^Axykaoe4tqy5`Ztt%O{1llva|Q zk=cH#f+)B;fAYJWN*%AMp!4&+w4jxrDX~JD07!y)@G|V7dnFUI!*b_=bof|Ul+ZRb ze;Ss;vULfWY`f1Jv`*5ICvirA>3IA_T|k9D%h0_oVg5v4ZDchucywjyq}FA1Df>H7 zu)I0E#Eq<@i?4GDA_FBB_6ssK{?BaRz5~5pg-I3E$LioF&d;8uad+{(>t8cnhm_Zm zLKh!EEic&hCmd9h<&w2l2tYn(mWI;LG;1t53G?S)y>@{`&FZ~4da6(TQ`ZtIsD$B0 zI<7tj;~%MkSQ6j#t>^Agg(Yk{P7alUUYdT(;YBIlBsx+QR6F-TB8%^nt-#$JtPGm$ z(}NZFiKD&WX(!)SFM^&HEXDcE>R;AUQ2^6lZg)%W@!kj}ew=iX^4Xc78@^bdQSQC> z1T}N?SS%trYW+13BLMdaz0EvNd>#w_=SvfYIt|+z?{7Ng&~EH{jyqfKU@nz8U(6I# z)n-JF`TAdUwWr6!0Inf|}8KiK97(=R@I-w%~waZ~2gMah5hIJo5wJ+iuygeJc+; z6Yin#h61?z8n0xK1`cXghJ^b8hlul}S>fQ*q42K#6rPuakpL_W;;ZiJ!x$sN4Usa_ zo#Ri2!ljWHly^gP3JeTn(*~X229OVoG2*$|mQO;>{p#+*`@2nt&J5RuT%W#{T!7fm zW~X$86N~O}zaBvK;XD6K6qEs63KS$9de(>s9mLDAnoQ$h2?>XKsM?gkQI|TgCrg55 zfXCbJ(0*3f!;&TdFn#Z|SlM1+#NsD=uTzxA{kAW_`Ck4NqNs&v(%vkdY$2VW(XKJq z`FuSOgnIWB2Q6eJQ3_Z{fb6xM5peK0X@hH-B+}d=;?+kh5HmfyH%E^l&VdJ~Efo_W zvmkzRGmqif0)yo?Vl`??Za&Y6Tsdy2&Xw&WZTd=%9x|mpNQdvTx_V+~Wsh`cY>%Vd z7^@1p1l~v(v=(eIbEVH%nOMy82#Van=TbbjW zIr>T@{(OZm8|Iz9*WY_SN~Nopeqp@b|LdtjKbG>voSMK}6a6yR8VWx0*L7~;59wD{ z0V*^a&Wh|@s6T)krwAH+-hS2I&E56}@RBEEQ%*xO9`LZXAeo_7S&2IQJh3A%4ku(!`=oQo`Hfg^r( zrHknT&4x?ZJMssww%&3Wb?05M#0=%Fb4R^Ey~qXmzE>im!^(gXB34=CZi-v`qWl9( zU<59gMi2=-ki@lEu60>-=kdcFS|hWRlsU#B6Mxc|p%qvoANK3d0tkHqIFmI%hXWi{ z-r&8HvxLo4m5UPN(M67Ym1<6Z`N_-4 zXfMTr*2t!dy8P6dQWl(+PRr8Y%1pk|z8UW;`+3k|lI#Fh@nrW{LVRuEv0ft|fNhQz z9btx5v*e`(-1amEyJ$LYM6{f~lmD^90a~5dY>`jo*r}N!#$3-PKvnrnJ)D}? zlR>8e6hWwi26nuT1xZ|J1wnWItsRisk9-A=&9YP@bWzk^3cJCQ8P2Hebpa+rEwwHJ zO1c~RtQ2xC{d!AN{rcLwGhc?ESYby3i=}BYvokk3BJ!HP$N{KU%p*ckI zz1hdiy)K+8f|*L2F^ky}M>k@uOd#0-I?ZxiVRUoMU7m zU5S~yz|wWuEaQzARWMLO|81((iG(%cC2)e@Gt4?tJO@mLGXw+W%De=Z1Fly*&=oW4 z+jr}_6(`+3;%fsTY1G%d7wkI-d%B@!Jbhd&b9}231&;s{0YM3zWQQ#W6umxR%L`}x zHh>3$F^*b|S~R|@%7iA**PI=TKb0UPXqZ%)=!%G+NqD;)9I@xXPCw+j3- z9LB(izudjBCo6UHb7(=75^;rpq2#6}wF2)|<+U-sUt%?pl?ETV#QOHDAKgm_bCh+L zE=PcZPd0%vWZ%5ZJ?)-`6RypCPGLKBL|rAk5f+zn%$F^?A-)kf=?(Hv8@>yfgXY~__yD;s)}~>hC&8Ovu6@a zA`RO2%qT9N(@)%wd3@?8QCY(yK4?hwhV6Yc?&Ts0{&|tZ`{y&l1F8(itYO)SJ~=>A ztGHiL>z$I(7VEL_{O?{KeUrf1AUo3)Zwsmby?6A*Y;WlrHkJwC76HlstKzl|Dxs3@ z5zRA@S)~PeD(wb=saAd$B0deEtj?%LzA`+&$Ukh0QjJgr$oXjEzgvsz#qkLUfHO$% z_k{F`KqV?&w=`V0R%)05BUh~p8>Il~RQ5A;^5rMD`OSq1hq190k6X^s$gi@*^$(mb zP3ZKLH-_7(&Mg4+uIFIQ#G^(HUpkLsS}`i=Z9)~vi@1)T&D^JmZYzSPf2EwX7yx$p zl?ia!ZD6R4m$Wd5i4v;6R#YMS{*CRA0o{0&|E+;gL1)+GQc~J!&D^#(dC9Xwx?+0s zm7ha_TmaXtp>N%`qR+CR5Zc&v@Oi(V{FKdv*IjNe4V6Q$_4e8Vi9(OuMptqe_<< zdU}@$Ajp%v5uU|>it#Aw8BE6r{_0Yvg*B&+oDv)?3zy%x?H1GC-dB=8#~ZKSrC2N) zpZllOERsS&9~IuVN%Pot3GiQfNH_x+}^|wCb8J9 zEK}`dR%Qj1{_QfZ_5bbmM6)4ljm6k3i_dSy&0gze0v3(~yvvY^NC3ncjJ#o|5Q#|5 zKF<$ieFPKslc!R!RZ>yO@1E?bki5N4oen4Sqv{d{8#m#7A^aAfsWNXzKbf5=L|fz# zc6MmghX{Ae%B+dR53tD$$ql)>6<>6{clTkz4IO`V>6F!}>d^(C_wVW*m)JJXB-8J0 z&b*OVzLCUbD3e|EgmHHk%vvYU25n50K%Q_65~aE&oo#n;KwECP)V9q60}CXpqvG(N z+~&io^I886lWeHur>gPGy_c6WO3r_IxDFOmJ_3r%zVoVSW5-Rw9M*7d2dg82vSMpr zI!a^cdl3TNSCT+K8L=}5GQWXQKzY=*p!lQ5Lfj*@P)V=aUh}XzX8FA%5f5m)-~)4e-Ju+7j$T zUzCAD__-eu!5>@;e1jjW#=TE`KvJmV{5w!F+tNhQ&<>>Q6#}F8Jpz3Y?G8o>AsNq{ zk5bPehta_Gd5mEwodeYW+8a6X)UUgzS)51i=4bB(*PHA^e-!;VMas$~r8IgJDTDj1 z-nFzkM|>z_6Ldywi+9;=$I$yg}ZPgLEVr9n?4SQkFOZQr%X zS*bw$0VxfqDlbeIn=&nP?GZt;QJB%P+V^mFkQxn*v4VrQK0$K6>__A1KUYE+jG!(O z<%Z2XzcL5hn6Nvoe)Y*KL{Wa=q2f=$DUwt_1Bo{yLnzQKlsX7wA=NKQ8V382?Eg(A z1v1sCx<9-iD}rWesaj_mT=WUkeuOFTM0ySK<~Tj4p1P+@t*&a)YwANxXQa}0D{M5v zWHN3${;1%l6zfy&nf55Up0wDo-Zq^LOB7@qvLtU35LD&3Kwc*M?lG)0%n@!KHaR?Q zWKp#bUf`S(0ZC&@vYfz%Rs4);OOL%*Tg&A5XEz%<4GO8v^O)l8FBFjw8D81S@u63C zeZC7(A;k@+dF)@hRVbE*u`vxn*OAO%?6cvU9$QPEAQBo@1Y}%bW4MYJ;LdP0$Cr4h zQy!{(ELdt~%#H;~?{q<$heTDo1_Rt4LyaAyd=K=J1F$5O>dnxP!?KgNhT`!m!qVW94( zcdMbcr%XxAIC-VfC2PPIa)^kLPPZgqnw@!Q++C%#Gu3$X4@t{?YTlY{!7;oTapME{ zIlVt#ZE1Q4cAJUV94U46TW+!1;+;`@dJ5CS(sso{u~hq)mFP-C@M4^!VV@?pPJr+0 z60U9WjU~r+c*Mx@3-&=^W-XdFtmxVJrCB9Dd+D`&^H&-)cDT?N$U*7%MIcsuh@U*o zC+7Ypg6KM?2d`wkdD_+TkiDiIq0E$RpSUm8+Lo|IxlX+DMZqaD1WbZyvE(tPkG(Z9 z6R7@Z2Ht0s!oRGx=zH|VD<%7t4&ZKqL`vZs(gMnJ3y&a0F?1AKu30ye$m0c~VGAn^ zSM;7Qbmf{(imqkNQn*cNi3}SYJeCGcVZhOnGuY56x}6$K6&5{p(_J(c7W`C%efv=3 z)juZ>R4kZP(0_4PKP4|BpBkjr9N2^KfWfFmUv!AK=OQWH$KTSeVl^2SPmduhP3uo` z0?NbuVA$`*jnwyO!KS3?77nMFm@lLej!L@L8XMHZ7@=iMU-Q>P47}}RyaYl3{5)@czMEz{= zYuvn$tPsH7=InM&0sgAc{&uFMbJcQx9Ud#Ylue)dMYGXj@li29ql|irxm;E-7(H8N zJ~I(~MjHbqKm)o%5WyczUY-=dDU){4BdL_Y1y7$Q=QeIS( zXlngE3`bdsCGhZ$A}}emT+`_i-naw_WvceqtM52620X8CfsDf-bCqUjeNX`omb`O( z`CLBByi{kOK-M33C@t(;KW@cX&J*_kzmux%9B(&Kq${Xowy`l$lqo}8W^6+cM-cDo znsmjb9==x_`PQ017RsbP2qgFgk3Y6GA0AfW;qH7m06EcDwCPb`V?ifLY`I+Z*0

m1!9svrUJu9qo^#-dT7-;lfL%zZ~#m7ql?7sIRu&YMYse~nViV?nke{NDSDaG%Mx>k5IhAc@wq{_iFKY8IP#d9@4X>M>yRlOU5k$@80<*2${i;^~o{DDWRn$iBK|B7L&uom;%yYdXoV(--s-W*4!(-qQN z?jqaJrBE`uA9eeiTv_h5C1`~vf!)}ve=R4xa~1k_yi)fV`4%D&PN6${Ea7vNp3|{A zEHyxAY9ne%53H^XWV4LmQ(N*fHR$GCL z6fSI`Bh#cd7+iF{QREOB2X7h`k8P4rj6Rg*TO{aBIyrQE088dVW@>C%(M_g&D3MEB z$1Xp+EjK4_VAJ+7=Db1Pq3YhNDaCGLs_)M${(leUl3Moqn06MXlHbx*J;aGtjtH`} zf~#LRUws6;`F~aMy|$unmGG)HSL(pxeE`cPXt6&9RL4!+^}sF zAQey<%qBhcL66(fX{_%)lysNR@V(}7mpnU3(`ikg8-^}N9{K3JOgnP?s~eZP*61Pr ziZdA=$)78%A2g?Y){it@Jo)GGk5?jnDVaCkiu^wV+g-@MTHbvA)cU`tBU-PIhCpveQWr*1A&KkrqbPWcga&q4x!~scge}zGOJQlvS3NGB zKlC~4e@7%VZB);gTVi1~3##kaoCh-TUV-xz>(}g*Gx~!kEt4rF5}DCEJXxgoI5P? zb8wS9?{@z-ukd;LODyDlu4E&|mhJ97X_)Qcz|yBRLTTQ)9xyTdO%60qemVspf_^#aVFkiwL{ zP}SBl_|-O=}nUCn7V_QUO1imlpk$M)9;rt@?Dt*NGXs zliV9RLTGe!XP%ccEFQYmgk*(-(SZqw$l@h!7Fy2__G;W*d>Ne6kiR&l4b1U391LmL zS;qEOCo8@|pDJW6Ml@v9J+}FbjDP(l)>5*U291a(&0ohf$&XQd?*mT=K0v20CSfxn zB)wWgK^>-$d#joX;x ztbeugPi^fX@e`i<7cO?xG;m~kJ$2Ag@EB3lv7C<5v)i!zb@Phs(5-W`n z_OKBQ;aQX$Qt2`P&dl(AOIK%~fFC)Z&n(FCo(?I=k1;vudW{i?YNfYN)Io{f(~G{VY?@=5t>l6$KG#R zso-i79K6iC@Rp2v+}1WnF zc)4_gb8ic3)2f;=km0Y&AP+`hpdF)-SS`2;OE(=T1$EHp>48fD;JsPm#tfsnS}-%=NLMPV1S&BDQGmig{k%QU@fC-0X?$OMq&}qayOwc+`oKMt}=e{q(y{H4F-oPw&{V2LBJA7^j` z-E`sfm`27t=Y<$L9IH5{q*t_-h$QJ-BV+rY?_< zUXf;0H(|f;-B)F_1N8N&$oIYOZaO{Hs8{LtpM9~IhRS!O(N86a3gtjXz87n3x*Neo zM|PD;9I!&fn5gWUObC_hEb3)CIabW$MZa;d28f4$C$Bhy9};0rJIK@FcWkD1M6gj$ z7@WXg@>@(^qvsM@X-^)HemCIH1S>GXgt4Ud2H4!YSMNw?uki-yPe)OE%CVIsyD!5Y zAhP^vbA3q;o}wI-Q!)luFjZkc*qYW0CkJNVsi^C^Ku4+#X_`u*pwrBSX6S290V@s2 zp9^Dmie2wlyQnMwNB7X-K-PyW2n{&XzkDZH53l%I1jHgPyH5U^OOdIoBL@>R*YPzd zCLXXTZp;;ENm>tD$JO<$j8n-F0O{+KfzGsloOs1arFrXn=+RdZj~jS)aQoGVd+Hi? zNRY1_WiCP$6me7ZW8WU)+$3n`B5u;`&PNO$Yw-EW-4w?#jG z2JDm8OqWYRtE(=CQBx0V2110=;2_#IrNjIi`4wysvG(hle-0hZW~oz9f6KUM2J6-o zCrDXnbEJ_~`p-TsBqu%btU|?$w6PWf!)!V2jh%3=09`Mz;%FG3O5%y0iZdOBW60&T zaM&A+q9+JR>C?EMuuYlF=m;VL-k9 zAv%U<;C-)C%PdcUrT6AhPEz8 zb7Yj;#YIf%sc8;>0nH#?m2b_a4&s&x;U1EB+HJM|H~ zE_8`MWSakzE40$Ggrb^)O|OA^T_ToJ3Tp?B5>IS0@{o+YC22SxtHdk?i%4B8qZ4wX z^+s#R)orsVTJ@xSyMh7~{aYO`WrV~kk+=8J-&2OSZ%^o5Xrc{kr5j7LK2^z`i}MP)fyym&G`B#VyxM_rkn-U z;~xYnWT?ajnD(NM%Ve2JHR^>J<&m(HbWApC*~n@KNtc!n+I2J`iL#6?jtp$f^E2BoI=OY0G<2lhR~i(S+F zg z1as&`2M^M2N96bP@e=NI83zV5VH=+%5HNejORWwq-W(8uKlGs-%f|WkCERL4@d|u` z-I>*nbiI@E^h!;-=@33FkRpzkMYks^GKujZQJK@tX%g^SGs^S}kDIQ(zlpRAsGp-4 zD(Jk^5y;!#(aVHXKP%nJ8RAR(J-=aFb5)v#V{&G@PoZFW%{^hK?u^Fl6==wlvb_D} ztZ${ZzgUcRCg|QBSzKZfIN^N8w&Xuc$t~eks9im%Q+h6wA+~aI5bEh%`I4mzxAao? zl$pFgiz|e;_gQzKOoP~Sr5T+MSVKD`QZ5cfH-`yyQaCS-52r8-PTk9sDr7aq2vSo} zUQ`as0MXiky z^=gmeR?;Q%eoT=Gq%9Q`aI#QgOUs3&_mRwzwthfeylr4>uCo4vFrd8Pau*ReqE%Nr ztP;a?!Xcd*20XR`VVP2&Sy#-Mj?wkYb5(^Geef~3wVA6mHLkVX(&!l*4e>W6vv2#w zgT5PKMsB7Tx8sBQ4?1+F7o48do3r-+@nsw;)1!2fpYgnhX2n){o4&3cY-+`i;bywM z?p`L~dShlGQQB+8^RN)}T5bnwf2&d(Iv2%FL*j(IksP9jJ7LZwS?M4Dp34|#wy@;d zvl=r<>CHY#_neV%)O@7VE~fpCA^VXe|1rUNOz^Q|d)B|_6ma%AQIdF|nahlFtAi&a zq&H;TOTEAce#*m>sorXudX?&DyKCk*yasN3vCrD4mhh_#(c)YldOdE-uTRzY@aVd6 z|F4c$W2CIeoG9$^KUt3)+WQI$YM(Avyqw<(FIJ!>w;=CLSO2rqg=M|atG0zHcufC^}}KM%8uUmiHx^u2LnD0ZlntOTw%NC)PmX07r%GAc14~M zT?%DEpSv#K|A#m5pKH#a#y)0nJN!#$f8duVJs|{Z4Wb-Na=%v#3y8RJLt5=}ng6sA zBIia42M|_3%j(&nk?0UM7vpf%(zNP9+TCv`uOAg9r{C&o_CHxbes_?&W7qrWn;Gm(~3=+3faWBLf>O`VcV)ed02|MaB%NL>F!&QRz>eZ`7dBDCAzf; zMjBjtv=w0Erh9ab9}T>RZax_rH^a$J<$oXf*%eTS*sIF^7BUi zF}Bm%)Wn%su!GIlLMWdVyo;mdqwiriNCk8WZ^K`JNlf)w9SQS9ZLrB?-^0XdLc>cR zHFAc?Yp%gpgUNxu`OzrGbU+_YCBTx#lF@uslNT`z`BguIYwwP{?(2avA;E&}>7zdv zUi7!jT3BnEN%lz=#{Ep zWfDGW&cYf>OwHn4a~@~}j_u5H*RWm#`BzZ}a;HQQDe+xP@*N4i!sCPQ3oHj6r&GtC zIV@}7+3-Mx<0;%rzey5%XniE&>U>>?mHi%hv;y|Q3cL;afK2d}d=8;fZzyI;KK5gz z_HH~a-51(G8vXV7RiA4*Uzjq!p&oKv_0QtrnfcJ`-8|LgqO6kAWcE!dy*^8Jqx*w))<6;_8$9<_%e6JUGE~{pJJ} z^<1|t;oVC6gMLbVHzf!2hsVp0j}Cf==&5Kn&@JG5tI^Y^HedVpW(n35M=!$cybexO z>)OpRQs;W!d>rLx4N(pX=J`#nb;*`w!^1x>j>I4XI|{g05L4sW?|q1b{c=!trF9L_ z5xy-2y=VBM4BLS}JiHI6T-d&tbrSTu{a#3q@(uP7oA&Oe??O+mJ~`v8#OAPJw0jGUd>ZX?=ZrP(C40EiXrA&y(h4UX-v=uWY z)a^f!j>$!lGImDqo-am?imZJdvEB6iv;K!_lZ8L%IR&>yAZF%Wrfh78)FSF^%dthf zHx|P9?{S{NaOUXl6nLVR_d;c1R?0Fo5zy32`mZF z!~sH9>^753dE_3P84&oduREJ5ka5-RPcbD4X=k7;Oq?WNf z4PPZ?q7dGN!IuTsuGya=7GHCqqaVV-8wPYQqd9)jTe7-{{d53#?<_=@pN9FU3G9Yf3FLsYXV_0ejAz+BE0gJq8Bg z*ZhH0c~tc%)`^)MoS>s^&f+LD-h+%DV$c2WrQ-Ks)ezgdc6}>(RKL-!`?}E1^v)Mc zBKOL~1EZ`k=+R-lQXvEM*6Vil+iV74Yiaf*_AjCT#cuWF2OvnTz+Pz_X$a{%a4vk3 zP-B3W7EvelR5#9BPTZ#rT{d4{tXtC7Xd)D)zKYN>1!#Y;?g8S(&who;z}{au4WIg| z6mpGi5UFOpKj`g{VtCJtI<5H^9&Y0PcC=~K9vktr6Tx5R4?Z+ZAAT#>Lu>Iq>Ab6Y z6p^Vg8|+QNEqJbFEIFxj;`@x<3SA*3(Uw1- zy6Z4$Uhz(xS|67M0;V?T_Fx6D$7=A!8=oyZpS7GSL-(3pFpr^cUI={Ab!-~sLzeh? z$aIgTXCM{8_x)2OBI!jAS)~Ow#WHk>c0#M$t0%GYhDF>8)q1W-ud|?;)!l_2fyO?EG zUv9#*_DuKhr59xrQ5QeE2rngnE`MW_?{wGsxle>RfvWScDg#dSpsMEUm*^eg?X3>f-VyVKqkdC;OR?weuv`VOzyoOEr65GIo@~ zYUWw?Yxb>OqRM~COwtFW-~TMv5Yee_IbCwLVtOhY>R{FebaKoc5xmm%<{92VV+6X; z3eeaz@sQ8e>nrneyd3Q03_LipTl zF;Yzo=kVu@3)d?~>~U;DmopkFK7bVGsjF^vEhbP!trLE5-Osk{y!UZRFwB5jMwzSO z=g=?kktKaw=M=1;zFeiI-B176>H5j+D(b^JLgBaLHd;p-PlECIjnrs3SgF zO|Z2VpvR*5dNN~5eqPXc2T?uq-f}Mc-~tY~?9IZ6xuI5)cLO!S&)_i!W)^S2g^SRb(+Jo6-HsbyZQA<-D}$3of3HZVw-O;+50!Vnbw|14wSEY zP6KbIDm1}c;y?SR3EEGrkMO=9%KMOCLoY|3AD9H1q02YlzgEGM222_9T1Hla|Ds(# zT|!G+E3o-}`%L(@w?_Kr=)j#$ntlKbL*HcADmPHK{4M}R%cIX~mf%%!w(A2fz3^7> z0SY=-%fZ-w0U!(jke0>pg4&vIz!Yt0E2Go-+2+8zT~&kseQRHSX(o1aYiAlIU%P1@ z>2E4^)PF_))0@{fyqo?mL{DVWt-o8*R~;Cah_oVPFJ|kSjlXP%zD$4P)hu{jIqHOK zKCio-FLh7&xma{$j^OqF)bktI@9zff2y9-phbne@dF@`ssJpvNL~&JuaxOPkI&J(% zS1Qkj1IT+RFCHoRu*>k;SFJ{|i39F7@RN~h*I_u6yIr>yRZBUpu&62Y=bM4o?K#1L zY2^Do;MsXYT?^;(PCb>Fi_w>M5reb3XPAp;a1A>mqWzKI9e&qkw$G~qu8kn$EsP-a z2?`Rse?1^Jh*>XGI)$>DlG-r9fkQwdkO*)Q97rsY3p21G+Hd~ zusgAdhR*a03mngEW`Lppy+^3V3klrL><1-lBd@p zhJ_;!e^=MF;8T7fN9u|DwI^=7py%Mo(p-Mg_Jehpg69WyY-nYL$Bjl%x;)**xw}kZ zR0IVneOX0(EZf5;zDQr_?~b%-rB7k_*>}g@w=T*+KC(mL8C6!4kX+Vz2U7KCx#Xka zY7326FUI8I#{vQR*00mX+-*A&uU&j!mqTykMdzI+^G7U}RnVuv{Qj#SzOvH2=iPsF zM1%bYOaod^tZ9L9=q;f_OA}0D57NHz^r|zLLn#*!W#*_f8s^#we8KH&*ZXfhwmFNg z|8GuskI|b?{~iZu*MZP;-|auJ!A&3tS8dp0fWSr3p= zuC$%bUnrOUXpSV(VoT(k`0x_6%$bM8Or+i?+hzSYP}_yRDgaDWQ-i?%4w9E`1;+UI zPF%P1#g-&|S^V(KKn7&U3J7Ka-j@)AQf@LmF!)4;$-H2w!4Jqk1z15Aj~8PR*YY!I z(14I17^|gNWN=KPqtv%oQ8L^bZ`=VmLjKI`2VcrgdKPf`K7&jf*xPzz>*wWdg0w&F zZ&BUhS*tk7(DH|FZzOH2UNQ=flqY8BW+$!IrJhTub{mV*$z{%pk1+s&`k zO)_%_a89tCA0`t)$Ojx(Yf!i6vnj!#o%#YqmZn5?Mo`kc0#9cVtnfeagCQuDNPGp|_Hw6#s8aZ(?Be%}trD`7%R9TWbFS$7+o44?z z)Q)6)u_v7O%MZiqp>vGwJ*Im* zQTNjWrsPXZY8ZK_;;~W7tK|O#Ut71W!FQ4USv0}z;lqB%++%x(xLC4hBEZxO<$wlP zY7d#5X`dn1fwH`3)afK&e!x0S2E7XN#vix!FQWjn3=_iw_LkUPkb`c&SEBFq&cCj)*!wZZMX&-s>RSkUYzBQ}10nhFzO2O5FHIl+h z)^2k+sc|jpJ5^NqE|G`d6SRx~9 zQR$3XhT#oh(D?!9y!^UvvBIIPEOK?RPFFZyzr3je*nBZ;*`edc_$zf&x`#^=3U+&J-JB2LJ zZCU~&QsECQ>o)!RbV1Y3bX7$WZTZgY(K8;q9!Fu!{`oekfTL6FderW7)i%h#uK=X4 z=d2P9%diH!bC|Xi`jOfsJ8*{WF|+hO?SciF1IkN;RWk%@4h{{il3+@wFs-5CFY4W{ z_L9?-R6y=X)#4`*gEge&PqX*;QHka+hV$Fk|8n2`u0e@BjUIeb+H7}R`OPrL>yM^q zXu{`)D;A5%uCH(Re$a!ep}5DVLUQdXqW08(9M-*Z{%OpjZK2TIQ5e|!9t!+nV>Fr@ z=)V8kP zKSTqGX{ofQsmghmQW~*2ea)SK6`-$l(gTrFYB4_HP+;c$ZkW6I2L!Tm7L2g5y#)?x zUV?0LwAptPYx6iEE3!&=?^{P|0w8RCB=mm$Y-J|;Y4PDwUk~0GX4ayVy4R!zgyx1S%mbYIOeFKQg zkRWLm`K{<|zq;iio&lbtUHW-+*vob%yyUs>Jt#6u>oqerOi+H(E5r8X2`LQr)bJeW z8;Iv3C1{?qEgI=}!UC2&m}5m9Pp92V$Li{~5YbnrUEWPfgSWp#8g>Fta2Fi23umXe zD?D?%cqufMWAD%`sd5-Kh|Al}v06ejhXFjd0aY@un~-P~sAKyFRu$sp<3Ja+2egzW zxq9=I|AOgi``&lc(4Pf+sdXbB9#kfDxJ{})n|UhKCmjCL@D<4aC>qD9J;@aQIsRN* zs$487ih?-}x!&^7SkDGF#vhgNUeERg?b4>-hnw%=E1xeIfcGr_8#MrxXb6KaugYoo zIaN+bRMbjbE2N@psh3j%uTOaJL1hNmNEMtlf7Z4+n@!G}7e)~)v zG-$|eA5v4HnFc-j91m`+{mu-hDGkrfkD%g$Z7;kNeIndqGy&`5PWW~;j@jD0cpD;+xkotKF=hnM;TtGX z;@*?vz_e46cj_6S2})+G+y*WUzfGYv;0I*a+C#Zb%OGAYAjjl>#E-Ee1jqy0`9s2{ zN!{u-VP6+?@3JyDqVK$S3jORdb&mBv=U-}*GJ798uouWA;*cxRv4!gr_ZuRF1onK_7 zm~IsZkX~$L-ws{@vO0QOM!3UdE0(mMoS#}-MjrpPb61K!m1#al5@}qvC0#mS#Pjnh zg-&|H`=NcY=_=_0N)r0CbA9!N45SCBKKOHc;eeYJyeRgrGV2v5c(L!%2~(;|lH*8) zA2=iyNzKIaV5!8UOUbRV<@}qf)uBiKlWa^9xfRW)?ghUf(I!BLCh`g+Kk?I#zMg1P zmwxU@K4Il-F`Q43>cpLyKo@bbACYUw15nA6N}SBceNzZmk8X@}iunQ_!sL&7OB%quykW`$Yx&vwEyeML$y zLM=5~>TIS}5)N`0uRjSsy`}Q0E4YoC?+zQt+a~*PrtgDx(;|4{AUlDPhtLB&^bPYJ z0{&9^dm8J3;4!Bo?r^Yjjf{9`oh6*xO^6+cKPAnaNcQZXuUnVfw34$Fh;$Ra4N&kb zZF_RcA$%FHy$QJ>U=Fkb$6toXf8#K}ua@Z8I6vqH-M#uQbmg!fMn7y8N17mPl7pb$w|z-;y$NF`iD>tlePASpQ-2(9N;nKtIz|@f!pR!v(4C z69zmBG8~)k&2Nkl^H;Q=2)8b#z*A#n*9}hwWIc62rzU(MR*D;!fd#-b=%Uv4c;QgS zSQN_Vlh0pWCKx}2z!A0c1uI(~kc(2FA~%TUpGaq-?0;Vz8+WI$MNR=V30@&3tCb0F zwl)zmGUOh0p!3eaZ^S)nvgKj@x$5)yyyi4WdIZUOEYipvG8&DHIw&W~OZ~fR^0uB^ z1QM=-5hWs=yqN?1>r&svfVv*9`6Vt{(>* zBsPDIu~%&Mu_Hl;HeolOe6D#hO^6e{Bv`Nn+c_yJsYCeRn$ z>o!k_+zNx=L3-Z>_`2a0Yy-ar0T*68gxp~r3LdvkJ;AIylbJcxF4L-4*^)k6-4zD~ ze7C5WKW_(Gsy1B`isDQTsz{*=TzmIU*Zlgy2AM`Q_P2SfXIn>xD>#SqqzgQB8W%Y9){nK+_+w*v=a_P1Z zeWh3mL21c;^ctNs!;8Ogz1n`i-rMpNzhUhz1$Q={jZVP|w~^k;Rkj<1tUgITTUl$( zi1T!n;Y39Z%N~nwa8eT})Im4eX-5P~@Qqz_Qd(H8RBSiPfSzQXI8wSD$qKW@xDEQr zG2yE@@0M^Y0;SCr?YW|5u}ywpnKd+;%~39_*9aENG(Q9Tj{i&{l1LF|`&a~%@#1|a z$Xmkucgy9Mc9@^TwD0 z4uY|sz*)Q-=ADS9>_Qc9*3nnJ+ye^W_j zg)Nk76>ylXjVQiGvj9@`9dshQCTRNS8sH~-(?~&1+oQkVz-?!Y=yhJf{or;&2J}RoRBtrqyz!Aa(TenRLnXJ8Nw1mBnOKvPmzPj!FQ1$|2p74 zM_gbdihSLDMN_l@cFFv%9Swa!eQb8>`pUB5!;9B#&wngV9CNP}?IIuK8vOQ7K~f~! zU*a^Hw{JnK&E`#)PL;slFrCGq!`3x)v^N6JN3{yeRO%?EE)7Z8qeSln$0|<%-4yEdrcQ|@B2X% z$>LLBZM&FX(qp-eXy`wsxF^DiO9-4g2i_=w5?|^9S)g^O_{{GQ_yOck&%fTklCLby z5)yZ#C@TEbde{PsBpoG%{um%!zTK|H!+P{fD+Q!G+-gT22#)tYcojC3YLB(ML_%FSptQCl**Pn z+d?~6|K$GoR?uyD3I5;l*c9C4&hUvz zlSxT;;*{=ny9TEmlyc19?fUK_)j7^vbN}7goofnx{5Ks!(VMd8OSyqhPzh~W2q735 zt$M@>PO|?_ z?&dm=FrdE()@OtmzTW%bq-tfH}vJ?K=r}@-s&+(l0OBOKTs3U zt4_4e|7PGff-X@fFVUFs&ucyt`r+|dZeGmWWScaQQZe&U4wwphyfY-WSxVFuHsIHH zP3B*`+7eQE(aY!-^dmcB_356f>Y)Pl{DI0#M6JV%N9J4VBMd+Yb_RPFkKiI)JY76S zOzr{B=efK3HB;$7aibZj#;E2JoF}*&dpSSf%+#mJ#K2wpx@{F4g}4oSKxzan=H5Q`+2<1mrhj?Y!K|9;+iT2tA5pJ3 z^&d{(y>GG>wL9|W@{?%kf^vJvqO7Bkw;jOOod0Mi&oN~hwVM!VtZI=k$}sah;{7me z$|HAV9pMAXYU0AbPVgz0IVEZ7z~i`1^`&*`N_54JtcSq(3#VDz+SzTBQlLp-k5v06 zFZ4m_w{IdKvW60U+PVQIo^f|}8>U(lrt@a-xO0=5X2vDXuuM<(E7&(Uj0 z2*0U*+_6d{G<&kS}uD3wQMwMlvd*lN^TZVn;)J_2k^a@G(Mv!7p;Nb zvuwDNC?j=+1=XqiY|LpO$}IDDIhO+q>?hC8iC z)j51yaU|pusK;Ud1js+~9O{o`4NB@m*ZtvqtZnmA*m8J+R(pjHQ9DIX2vKs^wRN1edmhGNUM_E>a7>jHI@i5q%jh2 zvz6Q|jrbTYVR9~RLSQ3$s+>*6y;xW@fU>J?_EP;8D3W8z+8P6T1d0|5nmr4*p{4!9 z^Jo!4bPoIvv5fb;)F0{;y zxbIbN{A3T0;T-s14%lCsnulQr>D>^IL zQ&_al#hbJ`$Os3ON`0P`SBguq`C5%%i)oUv9AF@OOiCeORC9$r8f3OcJf>|9s?_NO zt`SrsK9tA|*G=~TiWbbI_pdcA7&@1BfWOy!+59*yj~d}(4+d+?PJ)RdtbYn#SIqz~ zY2&bV;A1k+ihmL;d^q5r7Z20|nI#YQgoW}(=Q#+l-AhCM!CB8eSl;cgsjB-6Clv(& zecVSjM>H4fveTXYG`uWzowTs<6+}zzp|{cl|n|xoUmtTpfsgRUc)ADi@)22f&F;l4L)jGT05~Dw};Oo~x$Le`Z z4L)J8eTN9^KX5zxA7903MN2ZaZzjf9jE3c#&Y{nNCmn+0Uzq&9Ut>>?-L^f23HpOn zv-idOZAJN(e0nx_(B|JBmXC`3{dxgd)+BOQAaLU!Y)Cf7*M-E5+1FC3#gEOQerxy2 z-^T@|T?T&<@=^<5H`wd*T@S9J8xN08GY`41R*)6?kn7EydmA_r_K$JCZZ}Wsb$;n| zB6%o6DS`9szHP;FGDL2dLgX)eiU+~GG*iGH(z4ZF)6jmQ?Tg~(Weoglhov!5P zBR+L#01hTNipwuEtHk^7=emQ%;V|P=|8t1)=$nE%t`?*PkL_{-D`7oR`;Dvw6pJtE zT~=`>vcRV8(x(2!Gc6AIMjdGX{yx)v09_>vpdD|zPw*ZH%=_aew~NL*M^VIEpI|Cp zp}530Y)8|2onmHTo(ETAeH@T1UhPAFF_)vtt@#a|>3e2yX6*N7jWn2>BKqQMN9tzO z&(Vz}N3Km*^FmEpjFa4HIl0D zM#1#*{Z{hNXvDvAl^t`ertQ^A_XD#Prh+o9iOau)+FpTqtd-F{N{O`WSt)S_t}GJa zFQNZVr<+903D-vM;<@?!N5qIjhs>|`n4yt6bBEsFu&TOH^IouvUkphhA`g3|Zg%KS z($$ha4Zt?TVDs1^$(%~jxyx2i@H#GJK+1v;S|74xUNQv>#%7SEj6yDj8>iaZI4WNG zeeJ$ArXY+h(}7HhbQn(C;e=MR?sOYJiyglEj|Cr$ZX1A;^uUV$G{K38fGt?#LQ!xs zp$}@<;KZ|1*9?4Wa#nr%a(~o)8pt@X7?Lk$ zC8n0+m z?+uV+nRlTx_a5}(G56P2{XGCDTEr?3xPXI~X8t`r?2q}gKg%sRx(Y)Qm}bVn@e>oU z>7FtfRa2^2>1q%CS~Lq9;^WHjXk{om-2H9iS4&A%IbNjA>N)$qku!K06DnT7V@V%! z>G5=dPSMj5jV}*4+gSUVzrh5E!2xGFVA9iBToI_4NYQ-A`Z)4Bz3D~dND(h+eWpLY zo%*Q)HqWTb`Qin7x9s9P#|HYLh>S^5$#>NgFE*{km6hmI65_~}F8vZS52Ez0W%u#w zn#;y946UKEd$UuKeOTCjK26h{=tHz-~jAstg2@K z=!#+ChLn9yYYNXr{|aNf8Cz7|Q^v%D-@1p~H9EV0e*LuSky4i|=_f?_S2+ zD@R|8x3YN7Y-|ojd(}XN8`QC%Q~IRTXQ~;#mKsU?_}U4on!R{*W>1YRVb(`=`#Fa5 z;QqeR$$8xvzY#EObdGE@0z1iI+xJ{o(x7>q%cj4Vc>v#sd}YBEF50elsts(EwFQ3H zaX?i*{#)I4FqyM}boS3ny~z}jaiQl?K{L!-Pyx1qD7U)02OVwGcA1<`>!1uO48FxS zJ^21PTa!4z$w1JJ7%~^?^tiYWbrr{)#P(MQv_bYt^Q*B~=K#p4UUdd5hUq0U2@ans zGn>>n=V`xOzX=Giu$BlyKCKcA+X&qlK#y2=;DiE>HgB*4r8CeK;PeZjeuvDqWyrnL zzvbZ6)vOS>`sh9^JdVttg@{E7GjS zC#^fFH1E!V-ba^-&>mXBP-(Jcsmc9nP;c3v3yOyBLu!!K1slfA7iN^wG~~;o@2E|+ zDR?jna!r}MBD^4(_j5Nu-($5r2;8XznodOq5J8te2z}Z3M4n!Q`!Mflr9;EVz==>L zOk6p)etPvWOiJaa(VKyvHLq?R~55j*XHs375bbIiH>WH zS`!>P>fUAg7e@Nu=8_wf5`prFbg^{ce`ZX5qMz=_O1hz?NUC++rK3y0P%mQZuXsc%53D=O<#Fy@t7W?{&Bn^5CA;uPxRY$xQRn zH52ANFgJDsTE8Luq&--T-8?MOJ6Vbf&y)crZJ{4w z&|b$yZZ!)%jBk6O-dkiAOf$M!-Ai{GNgi^tk$d#M`p|Q>COeahn5t4R-2wvVZ6tHK z9<(qZCj6H$s6cxy8{ByI&6m)>g+JL>dhhL^9<6EHXug8(t0I~-326Mn*@4EN=+N4! z*L6!GUgGH`k?PUV+AtE0+$IM4nh=(l0^-_E9{#;1F$*ViNnMcBI~9+_#_1n@XrX3)n)~Vnp4lCK++t8RSM&4D#|a!8ku%GV zL<4?sB?7+Jl^_*7MF+v=N88H1Er9{UlqlOVpX_Z1QX~Rmfg9fpAYx zg(tRSTfk?;e5CgZ-Ii?|C6XQ8Nsc6+Eo6Xeu(?!5=^dSiPUh+x_NljxUC8P}9r1kF zoMptPrhnHzGM<4JBZcVA%8QWG3eB3QA`=%bhj*O02`0!NHOSu*+y^j|>354P?*eey z`jh>jX@sPCf0bV5srl%kwzKZ%6*WR^PP-`?6r|c8((!Y?^B;;j`r4Yx1bG$|$J0Cs zO6s=Of&@N-FDrNtf;L+Q5I!jP3!j{)gDe*CXNRc7Ov#llv`Gp)Jdu*kFQT*f{UYSe z{+n_yDDs5hN|->O;yKeWAs^AJ|33@h|6TB&(_ggh{GWV^o?`|Yv8j+K#f&7*k;0AO z?IToFZ$v3Qfh49&nc8h139Bz20z%+H`xPG^&nTYcUZArZBS4{!Xpn2h=~NwUyPQx{y}1XcZue;x}4+cN5$e? z#a%u+qsCUGnaT9q@nZjk5{rWsFOR#R!=t-e4@<-?BF3L0 zqWDka>3hdur|%+?r-q)cFOv`f1RKovC}Fkzraco3TlQ%!cFKFBP8>5Oj@_J?TD+Q{QM zWY)r28&VCxL8SMD8W{9A3C;z6JmjIr@-KNp{yrr4VJsBMlOG{w(W_`F4P7Ce~g0o}rPa`Wq-Lb8&D z9f;4Hs}f|X{|XRc!>=d+r~>N|q85y%D2pl8!IYf0<501WLR`ffC>$pfwDJppH4(G1 zC37%|i4)Y5oqZMrPMNc_iNp5h@cNef^5ztjZwqr2B}l5@xm;j^0adhz55EUxwe?CC zL-q#BW_#ct^*_KPK2C8?Z3s+!P%g1-x)=kD4#u4`8!M4ZiAN^%mQX*T`5&;@iAq0xz=_<-*T%C1C*ci9(ZV3Di@jzS&-*m!Kmgcv{laX#nD+$*sBM2J zwp2~`C)VS;R>s!pW7OZl8+mtU23W!d$jH_wL8+LH<+}<29&CX_tk5ATO-w}WUdCe0 zTSyfB&+ky%$c`rv4<0cse1fWxq>KaNAm9yk>9UXFHukiLFa$6q2L5W<6yLGgeT_>U z@OWQ2fZZ817I?dA7g1Joo$#J1#T5G9H8{G_pH6ORftCP>X9mM0m=%kRUfXhW{ zo{=`Q-8RFNQX*i3`~lHt?YyzdiHot&Xd&jZsA6i75D#iBkabMx!mKiRO#6Tw@^bwV z!lAwLBzBx;TQm#5zND6!6!-|Lsn{5M_Z2j0(8Wbp9#e;qF<*$>*<9FmnmooiMgNKS z&fl<;x>r)KL7n-)uCKy3g_BqWi*v{2oa2yI8if%pG#zQ505Un7ubqwi$2K@o?8bYg zEQAH9-Y+P&!A?dCAda?T8c`&C7$kPGpDe48v4`tLWpuonK0IsLxI&~^`qtNcSbDl| zD+F5v&(1_Y9URu5)DLS;w{3J{X3zW^H~;~P_}Q~i*27;|p5{pUwYUh-T3)4Kv@k4z;QCqLUgErQQ-#obUA2w~@1I!MGF5A8z0O_+wJQ^l5k( zEkU&L1jhF&=RPWC@5@P#?HQ~Lb-EL-5l6G*%TMJV?0Yv`tW(_QAK-3()x}T^DC^gl z`kfRb?KYLX=6y+SV94O&Yi72G#zuGF9=v7g=AO61vTY$(d!!HoB8k;qe~Kf@X^txK z8z9OUz|j=7Cd1B<-=sw-9*rqL!y{cVm(Kqd#CB*U-_T0>_mJxaOYBeZj_^MRo_Hu% z=&iL`1-CH;0X6@=$l2g6*zmh z)xFac_sdI|T4Xxp!aX{!Kyim?v&R7>39|MaoZM`~$0*i-i=>QemkQZ^aaSn|Nj{sB zS4U#-8prD2(bRLgzc-~1ev(UHC=Xk0t4WE`=6U?hI?%r;&6^HLTu&#N#VLn7XpC&CZ3Qe@*(F0&gDtbhG(!yZ?<5mbcqC=USa$kncIx zp9#9z?wGCDrREPGKI2LG(AwnPqw*XfvQNgv!ub7nx8dVTyS%tk-G&@!em{UM-kqRP zUT{?xd;e0LqNq)#0x=~(z{GR64&!v-J*Q0~!}2X+{QYFsZlE;agk`qz0KyATW7vDvfF1@^@?6{WUk1g=1Z{;68g&=~Q0j!BbKw6e;LZ zB|;G?eBvF+N_vQmb{kP4d_J%1YJ=1(U@p16*=96$jmG^JM9kZv$+HlI|5mfvhkszY?iTc;2x)=>NI&W{5Rt9g|{LK z$Bh`HBDsg#6uf>|7M9Y6UE?kcC*hRFJGo9DO{ik*NizLfl#F;X#$=!DOvp;ftPd<< z)Xw_z`TL#TiOV7bC;<>!dAL7;b5+Wg%<}T{Sr%&SI# zp7v`@K<&TVGZD%W%S<0)ZOK^-Wg!XWyMf@$%Fg>;Ksl6e{Igo-&F&MYLFCG zUlw^fXc`K=AhEb(^y9tlOU6f=^jWWbn+~kcE{nVac;0yG%>Qa*WAtf921HTu5c-kI z_N48^m@j8);40$snGv{XQlIeeg(O~2Ao8)?j_rNdfL&zkBC1)hd+0Gl!2~W^07$K= z6{Qbq$)1K7`;@)y>+&(eXYkO7O4#Y)D#IHiOL8?P--0}GW1@YCJe1*lo}nkrwEwY~ zqp$MOe{6}*uo~6B32L=2_8;F%9;f;&o-oar^%-&-MtR(#@y`okY_P-9b$K1~N%WyN zLOzXqjt*?sks@F_0~DO`{m(5jQ~7^8vk$UiLqr^shHvLs`s)7sTQS@(#!lWs$&2vz zr&9hhx)Xt7wW(FJ_@Y`J3E2-s>u*fY5Gza?E}+5FTOzFpUyx0V_U07ko;>*9`;E2f zLU~etg{AehiGlIM))8xtZ33$Y_3z+C__X!t4~7?PA8P*7V`>47nEl1;QTO}%M)>kZ zmsJ19U4uGQ4>Oh6Eyj>x5OxzvU9I#~;rFBrB{E?BCM5~6wy;j&gpK&VMf)kImNkci zK~2er0XEU9M)7Tz47$E@=I^<^Vip`$~eJu=I!v;hp!*4l|H^c#bXv1Lm&Qj&WO=Qp=Gg#hyF{` zc59rL9{Sux2Dy@qbjE_g52N)UQQQM4E^SQVggFNQo5b5Ji+GMNyC%kdD%% z*O3kaf)r6HkuF_&C-g48BZS@&LQO(4bMt-IdhcEL4@fdUoXk0A@6Udo2~^NRjH19A z^4f$ZFpHlZ@A>)PAjPQHw{L&kj$>?Po__f#yCD&Q94$r2sZII|JtPq$2Wb}3XPt(> z7h2SRT_?E=%3U9NSxm)>t2g#&7TP;^!fO`?zomty=^EXu+qvIh;bnh`QUlx4_Gi|~lcBely4b9% zq_a-hfB{6=`b9DuR6Bub1IB%CqLSgn7<$%=up}2G;0)1v z&7Hg_uu#c23wH@!cg!hSSGdeC_fYXj8-9$|I=B^@@m;AMckHS06V^8r9PA30Pbw59GN2gxAacq zg4dwS)^a9n>SFsaMI>V{;sdRUc{$>)>Rh4Qx#7}b-nkzVXJYPz0rUh@{7b9t3q~6 zifc%ax8?hIv6j77?v-t1w4SjbyhOxW5A3W#T4V9`bqc&Vtv66jmZ*lLAGtr8Y5z(6 zgqng~^O+Mp5f!vP?pwui25n>Y=R5;qqS<>k%hBXdPBx<}&pn79-v4mew}yO}`OuNh zR#CG|G(c5y?GLCy3BHN9i@C^TgML)Q;schqk_JOr`#HF({#9O!W1_zl?~`?0%IBW( zDn!sj@LHju&f+gv;IJ z6L@92jNv#v*_xfnVJ^YZ4)Xui$H#ka+a$Rvg-n$jFEGjW{ra|1Yu@t-VI-;Pn?xak zig)`XqsIhnZ`^cUJ5<$|+vj9uFs*!9;TCJ6VvvA7CUVk} zqYHJeK?bpI$MD&U6suA#vSOM8=4OoBbR{RzO9us?tL+J4 z{dj9vhNI;2T2FFbXz_udl!_vj+@Il8_$;-SN0B&Nf4X+`frxGIICLe)<$SUril_2m z1XiK3u;p(tSaJi3jSps05QIUHx2I>z@wdKSfASYP$4pOQ#CNp_NT(XPV^jf#mckLC zifN;asbb?I0r_ct?%M4)khe$Ku&ZB_%*=NZGwi|d^T*YFw1Ha%M9cAs#nEUEb_V62 zOZoP8JCpmj;lwX9NGAOZm-&EasI^WJgFI3?F~B??&98$zMjeW4EhbZg@YW{cN_5vf zQq6FMYzci?26gVj_mjbY=s=&~hrwA4QqqpgG`Rj7WMkU^l>uDIEa*b8?TeE0UFOq_-yD7H#*QnAwMUx-g&|aH3?Hv#NA7E zx*bFtuUiJ0sY^6vYRsUsQHbffW*R+mgXl=P3yo!&{8*DCFG!Gp06gN6+qiEMAz6 zjnRo%{H58J<5+dOFm(_6PBG*Cj4`j_C((kdX$F@03}?~k4jk+uX@o4Qio@xE<#=K$ zo5kfuHnOct@5&`Sv$CNPh2CRw-lT19%%3~?$-5B%4Kbe~n_T^FrSXP|(U%q!s9RV9 z8b`yua+|0$5q7SH_nrqVQ^KKi4b*I4sQ4n+f6N=8bREI{21 z>z=8^e(~;>C1X<$EqBMy7c{WSsb2lPp&p_?Yuk=E$olsCn@jwvERIFj1odydguQw3 zT-k^Alh6Gy^J zOayr>YK2;BL-(>FqN}hLQ2s)>tqh*(M+Uu&K9dEjHnfHjn+Or%@0U}3mqa$NTGf#j zdEF!rEyXdW^w;*3csl^sw{b_*Sj75MPp^@Ms(<-r30bZYb ztRVOEJ$_`tA*CtzBz6D`(D*+tWyz&A!p#&lmXiYulEiOp1CNjb;PA{(gbLd65dJ*$ zU5&0l<0RU-8(jqT@^RpCloTTiGj<}99|)05MI$+>{?;ISC&G5zXw@o*lhc`Z zT0>@5?X%6LhxX49WNY-_L(E>(ht}VL$*Z#fhXtwf8bkR2+G6mG(c(%{_5|v%8`vMy zBk_`ZUkifn2t~`2L`chA|@mopjWtvzm#X$M2mHFYLZE!JDD-P6f?6STzi{f ze+c|}vsu20Hkk<`VU9+nUhm!Y(RWlQatZ&?Z-v`ye1*&k5sIMt?>d_UIV@%k!4BQq z=s1-PQX5(sJcGHm-GV+ND0H{O5AW%o`?pE%Uj3TCe~L6>7GBMeZCeNUKg}Hl4MT$v z{&cjyxPBn5{tM%)Uz0Uzt%P+GImQgq8A-3i*pYXiNP@{2_F;(cv;~X?f24ar?g9so*FJDROX_Q8V@*fCW8>_8Bb_ zYIS|jOyA0js1ZgAGFz6vHdAfq@W5BdtmqJ(hWN!~hz{PF=!I@fEku@j6k`xG5lJ{g z4a8~0ezBAKKnxUyLS!Cr;Njz8&(TGQkLUiGQ8@S*!@`+3+V4_?>Xkw*yskw|_Dy3c zS0BuO3HoYp%EokO-~nPLn}exZ!pZXE_+P!g9GIOn^=s|uq(5psQ4HZt!q^2`%M4ak zrK$U`^sMS4^97B2ee69unJ*_jFW4js++lnCov+G>fH-VNscNKpkRKMg*uZ?sO2T?hJg~~af3UL#`0Qy zmSJd-MyLe3Kj+@XxmmpDrv;xT;Zcy6_dz`Nz_=zGH@JE0quwFVPYyIfi<8h30yKY= zb2OGK$0L7itEIs%>7WKXBjfGJ&MC^x{W}a=CElw7PeX*LZakJa`>vT#I+EQm8LBrr zczl!fDoDZUQ}&WDb~pqa)6*-l4?NE8lWu+P@h;u5U1cn9;0npUq&e3mqPETfeGS2g z_7<%UChALg7Os#xLFBZ`^OgGjr8E}R$>r5%9^}G19Ix;PsTwoqJUw4{M@X|1Pxzhv#s-FDr)7C;J zMT?;iPlDtm7Sio%e)ax%p+^}nl3Q{VXZxDnkD9%iDx6N{cd%4zfZIt}Fc6!1&ClHF z15xMk1)h&rCU$yRv2dkSyG(>TF`1a>ssV*Rnimj_LMV3#DX!A@fW?-?L+Yq{yy{=A zgRrRTUwI=!{!1rRzTcPc?Z2{M5BXL`koApF{&>Z825$}943s~3v9j72 zmSkxlTC_wl0TZ0D25GcWcuD-(?b(WKA0DZH&(eYSb>wCObS9o*E_nG%v)}78SOJHX zY3&)DE%Dd#ZOKJXibQX5x_j5OD1p)stY%r zM_$PQf8XxJ@FXFNoc#5vZU!ul9S$-m*0@8-bPw@iJ7p*5Gi%9R`g!GdaQxu&Q$xtj zTi!k}#jqrO3&H+mxmgwgnYmsf8_{3|#(~z5i0*V&{8dR>;eJ<1I>L9FgSFiOHqvk( z;z}51f6!F02nc0%o4FVr@b$QF62g+@!5WZlSMQkzyDOXFxz8b}huspBPaI!d@ydTL z^Xu2v^TT!{6MPMqv3;v``HLif_X%c!WOZ)I`@es>nDDNizwXD>P4Dwaz|&{YnQa5= zNyemr3vMOqd!Aj1n=ueBrlqs)Xdz5Ns`35y#1T6hJ2K+4??z@yZc-pl%*h2QEkJIx$sxi>vZ2?QM!0An~i8yE<0uEJ(4{@Eps|d#z7e zJqs|$fBV-I8m~-IOz;clL22k~epf%AT--3!fS+@mSsnbthrA}m2ezt(v;6MaVZ&iQ zOt@feQOhH`#7{yS?Ec#$eFK=Z0r};McF}h4A+Vnod}v*1!0&tROm>f`&e$mhs>FP& z4~=Xn3HHtd&YLFST%MOu&+G?9xz5Kr;+O-@SzS6Q$(#&uPKG`zeb;CB1+;%U_(|SC zssCt0rEYeAH=eMUZr0b&_=lBmaI#1*PCS5w8^P1guwQ^z(0J z#!6GIzkZBcGLa(Ch)m7K3QOq*Pga3kmu{wAc<^VR08c~Myb?6+fBmxuSUE`YUsMo$ z`e0+C42me4B9C^`kLdb_t^gDI);VaXop&VFWBxnXF-VL&+L~;TAyK8FuV4sxcE%St za`N6|)2)OQbo6(9rg8LX3-39xcA)g-hKGEbUOm)dF@3rog9i;O?e4$3wDdgo7cUVR zU~-{WBE2B~16@S#KPz(XSL_$yt;$H;X?0=#aO=$R7F+3h=d9Dm_B?-6st?uyfV+<4 zh(+FYyg2?;1+qTG`(SorE?V1bh1mh-sa6tx7AKfw_+bov`46FG<_r3|CW(d@-r+|j zMj1xquz0AruXvaRbMYSU!=gUA0mRnnRibR+67pyIUozW4;!oW{GKnRsZyas50JB$V z_XYRPbNGVgBjo!e$>#Z6%Rb*Z36C%=;C*##=L>8; zUpz=DCnJUQu-`F`zK4dJxt|qe?4>Hmf+3tCoL2sY8)e@<7ilBxxH$8&is)xuMbxff zv)#=jxA!G=bENCEv+UGnZW*Cw1`WK6F*wa zU9cwIx{f!*`SJ~%PuSG_%ZG{6Iu;AwlF0mLw*o7A%6_AIN_=_H-vns0|I8%CVkAYu zgcj{9?nJ?vheA|ZtH(YIDvI_kqK?Q+I@A(R6Q@+b!o7-TJAAvr$U5VYcp8U9lYJH^ z#fKZA=x2oYI=j8F_Z983gs#gx>hj?d*RVH|+Mt(5^n`<)&YDejosb@{T*s6HgIWWK zTc<~giv|MSoHbORIJ`+DO}q&6m9@5pI_K~}ruLem<$ zA%czkw>=@(*k7?Owi4;=K!sZ-^~Y825ZPlG0Kxk1@>tq z$iw^jLN^Cu`i1z=Mi4P|aefO}MDL<0BNevMYa{#>kdIUEJYwP9IXP~wlnK~|(_e^h z8)?Y=e#TSKWJ*@o=iuondiV;lX#k*T`7g$8uFl&}BlZER?#9&q2srL~i4*gSJ9O+u zesfQ}Q}_1-Q6|^n9`&5844{T&27w2HlNFGD$6>A?o0dLNj0Xb1LCBKOM@DWRg>pKo zI8Nig9-a5iw%x8OvZZb6ukdfgBwu(J2J@FH-X1YKZPcp6Q2v9DMF!LE(G}T10yOz? z54*D69~S4E4t!g|Df2Se0R)ivWjRJP%IC=)cF08na**B@FY2jk{2=?g?a{)UM>g;Y z5AtP`yXjW@I@@S5WMKIcjE$jRZ+UFIWG2w?6Kh0IxX&jT-YvL4=&y{Syl`S%th`-v z8#2A+AA{qa^!o}dqPXoS|Awz3KH)tMRlAm@5B_+{)5w{c?ltV(_kDKix@^6`CQ%d( zP<9@n%u;>`1)1sw@CUpuht36E*7?aT=f&`%-Td8mhz?MIxVgP4$+F%WsO1J7ed+SN zmwbO&&X*^*8_W~~)q-OzxqI!L!^L^Zg`a$~!7qfg=}+={OaqKS#QL`1+6y3*^GjX@#XdG_HqFCfOeBRTCpg@pA#3Y)K>$lEBf;4E?_$F#d!2HZk&Wl8hyI z)!$pgz4x*bLVx0~%pCQi0#RPCN!q?E$Q0anBCiJ-IG^S7N<7514YQi{t}X(~yj6Q{ zOJKHv9%Nf~58|$a#J#u6U!VZge}kZuH*}kz^F{BSBHBH1xh)Lslb;|aWsWZ<&Y-}^ zY>B6j_gLnw?c%JPVGPl<<|eSQE!sCp^Wx{3$opWvaIm~_9P!>$~XX71f>j3xS`bx4@i;ddzrG?guQ~mE<6rC_I zy{Tjspg<@*{$sP^s3J~`tO{{RxVD7x1NSa>+@{mr)~bhMwkhV(qcO7@*Q2}rcSBj% zkSPO7Ek4#NkD$sBv3&33D;KmUL4AGyt&u1C&^X<;z{ki>O446-L(h1OHVh+mMYo3G zmYGVK$o+^|ZAFU|oDQ0t4^*4jnEl0?O?Hwx8{dSu+Ob`ur(dHHvefKvbw1u!NcaP8 zd~>;{13ab4-Cwk-yE=no(e-g?c#USg!(j%I!ydI{n4rRFC*5rm4vHMZa6nV{XK@$7 zOvn=FqU;sj{)`)XLYczZ)R5)nal z;mcEtloMd&=pj^d|M&~!yo8zrUhP(aF7*<<*shlT;oZw=q)_O?@!%Sw&GF9}Y&YPe z{E6yg^b`zP`RWix?~+p@JoZ6w5&s?fnJ=FVbU#q$OT9aTL#`3-XmYh&;(yZe@!Hpb z`=pQyZ;20yWEo3N1vV^wWM@!xSF4ntWic$GVbZDh5V($b*>KTk;+^08y)-Le>0hqh z;)j!)xm(I%dyNNL``S259QPgnkKs%7z@sZ%wx*pMccprr(7}Z~BjNv|@fQ|B+_qT2TEKvM90*zgw60y_vN@t!KYn}(eFGn#thK+!Zr>6;6mr>qZYvX12fanY3#x`U0c%KI)FA0*OXU`( zR*LiWXF4ZhV7#$Z$RLLyi*+Kxh+qbZ-F$Jm*y>{wnl)!n{|cfdB=XHAg>b8AbDBXp z$bw#zLn8t51Y^=%=g|)e_3EHSydT(O$a4FZ@N{dGv%2}Hok_Al>mzGJsl<~b(yzWd z!lzz3GPa6Or7Hx&R6gHXufknN?q;n;$PFQZ)|oy^&c z!amQChgx6XK{zD&%Dos?2zil|N0+u+okw`pNoCNRBH4i!4;($fSAA`%c^i=o{e4vE z3_aPAhCZMhKC_DtcS%G#NAhV80^b#S`ynFrEguO;{LEtkTYW@`q-^bsj0DPf#QF2XF(VqWmayLG6Jz=!IPVE@c~o>TZ0)yL*#BMoIqAFF~6` zoiW1|mTSpYIZqdvy~0uK$gNv)f~O#LvOBx(1tlkn?bmiwgRG~EgMB#Of+ghkU$%(h zKI8*xQn&?rnD^T9IHJo)jZD}Ydxhbnwi+zxXxa^+|I{DuRveFIFBc-PB%(A~*P7X&{? zoi{^#dl<95rw@Rdr50WyajDs%MDlDjM(+$A3(Nz>|5~E8A!TVOt*x=5z6=sRk;O5f zdoarMmL-V5+zakEwfL?sD-TtjG3vL;aSeVcjK5Mf)(k%qCUzVTra^E5F|4S>3CiSs zUh7ix_`LL!pRpOY6u1K+u86P08Yj;i%U!n-qtQvnmxi9VyBMB?9T%o3*8TR}o${6% zsgC0r@AWBq#CyLvChoDMufWI#^&`bAEXtyHSaBj|;yCt>p5ehCzi*R9o2jH&b(A{U zZz`2+!hrPlf` zzhNcqx2DNvllj2WQwJvS;w6&|xkG9F$JE%|H#VBaa`{)kP2`0(7$1(lpp@+Xwnxu- z3EC~0{xJ|rH*GMKjb6X#`|>nV_Ntal?7)gqWQSYPk?NH63zS!c{{uNYQ1#KFKtwG& z{J)ed4dI@%F|RPBy6^Z&f&rW*FrH-H8mf@E1)~QoNt~{2gD+wHq<)h%pRXGpYY12J z`(Ee__IBVn#-b>i$sm4jTgBo*3?Te<=dd|qcn~o!={{ymuG~ID@-4j7{vxQ6ajyHV z;B{fO(D^V&Jm21hSIkK*H!>9ZCUNhe7V(EGm7OX`3tlx?_X02rytwL@fS7VP*u&y- z=abi5G^;jUhrF#0Wh#!l9Cn`KGs~>y_9k7C%Xf*F94P!YET^_yu&wjbHIvvT4^UNx zk@4n0P-yP|?^wNW<)%VIj(3h-213jNzAN%6!%1H30=5|#}$i+6t75nb{HpH!2B z6jWUjdX>=mIWoLpi|%IHV?4~IzjV`{+$fZR64!GFfyGGME_U}Qdr&NL{U?P|e7|KHxQ08iUsBMnQO5X-`F9$91jjF6R}C%ZlQ#RiHr2iNaUGVsQgYn_XL)J_ooO2LmC8I(7^KX5)qIXew$uNbi&Cgq&f%Ia`D z-5IFsxFWGMp<8R<)j2L9e4rk1UrENb#!9GQB$gTNZkflbevwY+hRge5Hl5j;Ze-!F z!|@Hu^z=oo>&Y6#ywg{rqb&6jB!NucPK;(sU{~(@0Q&4dqZ9q5#Df*bs?bX9uKZuc zFDe9V_w`;$1wV;6Th5RE6}N~5Ho~yl#h4gS6FH=$M@}xuX+CPF z@l{{Y@{yOC{u~4-tkhgVjm?EWeX}bC?PmoQk&#+;g-z=UBD!v#Gy5f8{ENlJX_DKS z?5G33%rZew+x)ZLPPe|!L1SyTtIF_yfF9dnoWNHPYg?Et{$8}k##>@3$ z2el6NyFShiV7>^4!cKvcr4R)$urUXH0lu3`>XWkF>y=zqr_9Y3vQ8MKkg|(3-?JC} zLgoAgdHGfP<`1CI{57guwbGRBln_)A-Lxp}Kxj9QBT5o307dy4^zU80zOlL)vjdsG z5v`chl(H*z(7SHy7kt0tNP~8#$e+m(?%9qL6QX1aKyg=j6|{{3XOGf6AWQFqLHRr} zD7McEdOi_X+y|ty9XS%M<-`>Vu*x;(!a4&UOF9*;5$G%uLr45lpnGtuyo7pNiedNU{D2rY*ss-=8Uuyjp?akg*xBdSR8d z@XtM!_gPnCSM1jZy!b~X!ftup%ubBr)5Z@wa8GSerkxKnzb?hSHC4N>qc>a8c~OM9)fRdos>)pGc~)8v)0MoRLQa6KE@p2?wFcATm=#qayLbQ>Pi zRJro7akp|CG0QGbnnN}4?9LkkfnRg?Qh$)^Rm=uo@BXc5(K)@?tN&v>{lO=J(#lQf zp8w0!arkK8w_)#YU@&@$b$QZ$a#^WGzXd779woR>y%MAPa*D0_^(LS7`uZu^|5fTp4q7G4Acfzyl8-JFid7@!~&vU7g6 z6(;$n?3Tb3MEAi#$R;eui?xjn(k_L<7Z89{4dtoCPIlw^R+jwN7bsU6etJTADag(1rACDafm*f9 zT&|wL3n|XTXb8gZT81}b+Q7+hX7^3lwRqIl4_4AWhygr4ggqXub?O&(ftXLi6m!U2 zuJhEsAeC{f=EexO(bLvq%WbQwBBjRn2`&V+T?wPN%cE#z`K=e58OE}sKJ(;(iKtw} z+?k95LDT76^kx=n4>6v~&?uTGpqznX!cP_o8bWWhLwYPW+{`@5K+4DL=b>ax8O<<; z{YO--Y=bCIgF~@W_m#t>?7855#{-Wq&o4oRSK_k}jDr}lSgVn1sRQ`jqY4I%mtX}L zv<;tu*NAd@T4$odTixGOMTM`QC1gyIQw-qG*;(2di$$Aii~FxK=KT|N5}$6OBIP~p z0XNv3iYI%d7kPQs7!WQ*Q-JE7w>iIECE)RGmsSw8M7_(17x+UwLgx1ZUMq_EZ3KFC z=l>}}yd5GJN$#wu&r=7_UZgz>uruw-j{mVO(PEUX@u}W!mW$V*)2YFB{ ztWM*)gv@K^*MDq^?&?byw2eK3vA$lo@b-0_bqVMHDndjU30;5s44o5dvbMJ>Y?o=I zj(6XP&N}zSAug91y>BfVSR#1*`<|PbH4Pj86t2{+FqxP1GnMwvcz^?awTi*!x7XR2(F5inH&)VV1 z*H@iqdbO)1Gp}NKCN&XtoJEtwH=Z@b?M^YTyL#74orh7pXXQqCX2VIrO*%{RY4{7+ zK`0rqZ<8&~+5AsDQbJj3t3sz6NH-b5*U{ect_}6k^;k=9SLx% zv;PoAhus?mVDhG`dFct>k=JBmInsw^nFi1F=>_hBpEW(hWj zj`k(x{%ntUew2!T7ctjAK?((v!h(%JVtSBj?jk~$$iry#{x{zPCc@8#c@*M#FqlP_ zk`Mx*z;#5~kBy&H<|FziAa&v!^QUKU`4+aZ^Ay2fKb2o?FqqHZ(Gr(@M#K;%)JF!v zZIn8>358PYk^{dTnJeFt#$zR)fjxz){l!;X0yerxxv`07<@cfMhp=-IX3IZR8<#Pw zx8@(w5=7oGKwE^7jCHij$MoE(H$aMi^O&bNp2pho5#?R3WXi}<-c;K-D2?5rSN@*WI`|=_$yz?T|1&A^bNu3`c$$6m z1?4fvE?zf&of947eQZ~l05R)}>!-q@+WW5>pDn$g0(^t!*PDl|DdpaF%6+GM+#d>R zh=FAokQ_$_nXS5N7vT@ie~#*Vc`_N>_bboWrtqT8af5NRw^bYB0WDy^j95e4-U3G9 zK>yvV)D|Lzq?jX&r8+m3QR!sz1WoR^3idf$3_txj4Y2czn4F8Iwsr=QRiy15#4kqq zWppN#;QIeuC(UfT(17}Khx|PJx7Xx9tm()JKQ4tOHJ_ObP+LXa^H(gwoOpQe#OOX% zkQ_KBV!lH;)WFHz&c(a?l6aSI2S`ii>w0^ILHAjmVPoOKKBSP7{*Hc~VS`Lkg!>;! znc8D6+0`RTXaE!w3-}*lin{c7o&iVfPEmO=X3lQd)w~n}a&e>oZq#mKOcM5iMxqIVYe;duU z{jxGoXLsvHy;6za!!Q4a>WcS$$S;ui^+cCn@6QGKj#)VVy`ysy%9&60TJ+IEzP|+F zoVg-ShmKHo7`&l#U6%(cRMLQMumdULcusGZgaa8rlTa*Os%7yxprS2j;qspj?E2;h z!-0ipH~X*aEwMK7LBl{k|1U)*6Fa(E|`;LGNWKQD;Qbezi5?0AMgJa7mi1gnTM{VI@= z9dgDZ{^3yt=Q(dPev81@Z0cyLe@0k^w$MhimV(h~z?MWTL*+kCNFlDX7ZFi;?D!}x zmw^FZV;PM|b~=|?sALW5<3VbrMlsGaO1ACEFp_dW%jdGVNu95!O~Hw=@Ny|AdL9%E zcGEwQG<(hn>Pv1_D&A;3e+UN{E-oWQcghfB$GPwR9CafOXRPte!S^65D34k}M0CR; z`y>Xj?=x`-`7One9xy8l4090OW&jh~3%cw4TB!t-9tTtK~R>qtWw`_{tl zitrGW&txxy*@iF0LpKPe-~*H0x)f|zTzosqPAYy7L;p5?@Ohs@kRMX}!mX6o#A>9N~8 zw8`mdn8{c`jdbYAKC(l5gh=Qm@ZB!UvO4PEoYqht?UZTn!LQ-8%&@B?yF(1 z((yC&BJ9&sQf5;^jVsONyabhhdEoB6kAOoU@=3XAxGB-)UAO{#{R@x4u@oE2-dDh+Invs4mR^7wjSbC|W0& z^A?~d_)t;ns$ z8uiQ&{Y@%8H0R!<4OV)oj}%K(&wg(iLXg3`J->f`d*h9#b1wgCPj`%u2d1sH-jzUX zC-dtm^)Yh3Lm!)XdX^99Ah!CYy{P~_eB{b_*`(GXSN->|6pR|UTj9X2PtGsABzrJMstwIICobz zw5q`ZWtDlI@5{rulw+)N(KCChLqxDJb}wbS*5_alPbQQfgej24SmaFd*V7C8d4G2g zdj3{`FXg6llqONmb~yI4=l=|*X_}(Y3ZDpG2ZS!!k&V!KTxt4?tM`1N>><55?d9iU zHw+3aYAoMBTWz-s>bNzRv)G-0hc`OIb3nS?d zjMKR;cFYadUfb%z>;VE{ja`IItsjsg=6GQ6&la);<9vEZMMfc80|L1U1Y1z=6el3p z4WIzRq2q?Zfm66@YcR>taAUcN`fiL^;H{gLt8E{*;jcteDw#~*)3~eI-+>SJ^5=@0 zG_oJDG(lA2&wM~7^<~4_gU<+3?mfjYeY@tjip;CmT7NwZ za4ui^#1(h#jgka8*m(528(CCZKw!i#J8FaLmeumU_gN6)f2*DV3(u&szxa|uV7L5< zCG$e3aLq4O({<-lIS!OxN>2-gZ^BCBF-;4eWT$Gbj zQ9BKg+?l=8SD>HD$n&>avZ&HJwO|_Y3Go}hAZmtSPa4n|(w5jl zDlyvjH*<&HRfsq5A67~8<|1${l>OlFt4~@uN%9_J0yRF;@1wE(I&I!wUt&J-_bw8` zV3DTarUG~Vt0x3ydHaum=r=l*srNykBrlY=0H~qR^?#nDAp7qip0@K`nJ^SowK_gAQ=?)tq;+uKC502u4m(5pIFcTq5kZ-5KL`o z&aE!mPkk>KYQy}YJvZ(&@@K37uMiLZ-u=XzCQut=P?m7-PvPqAS6DTkEH0b+@W;7M zbFhlS$wyyUt+NbxCEDbKA~H3MEAfgL(=-k+mS)G0M_l88rC$kn1@(lO+2)5ZC&Wha zdq@q`fs36uVSE<Ky<)*cKq772PrH-+&uYB|=w>#w{Y$OrpfD8d^%5EH;y$VEMyJOlT!fgvxA^ z(UG@*?3}yZOS=I-mlSdCRRC()HT|+J<8SLy{iFJ!@Z96{BhLMBcpaGpD#A zZ~)T<8Eji)`D+F51)?|UWW<;V--R_lHBCj8phffQJjeW}ByW8JbzX~RS(y@r4)%VN zMn}Xz=?&YZw`60i4PvvR+|u6DcuJUz5PGD4eC0z9GD&N-R|apcx7^YAzM4?Tao;O- zfPnlM_J}LI#-#6yp40=aFRi5$_^|%W1{UUYSS{)b6w=g-yjIkWOh~sq+a5;z)zin} zV{jBb>~~S6o=)j#~SziAIe+t=g+a=}5mkLGSWnZeivM~Sti@tYCU zEWL(G>NzY^T|k{-REPHBh;uKwT&mGk`!NbwJhkkr9hm#@LueiOF(4>E5~y#Sn>s_V zx38}q4yM+lpF^_}XFBD{yV#OHU`aIYiSlMpKMU5b{dkb$o|h42&)&;61$#D4*u-ze zV!RgLPr4gwb-Hm>Qk2&!G)*TJ8ZKw#=i_TL$7(C827BK#Qlm#?-fPC=wWD7+3f~w| z6Uo1DC0g3zw#jsPgCdfNTZ%!B6ZR#3CHPzW>#4NtmzyoG1yqCz*tZR(jVO=v640B7 zXP3)Hok_F&^=X^dcCUMzEgFd*{C4w~ZzQ7c)4Qs+s6Sktc{Cos5iWIeEAj@L3M8>K zsr6Fe6k)h*ty{#M!1}Ri`+@hT2MnaiuUqMiUOO{B0^V$RAR7_Og{EGBX&Qe_cceae z$vgh&t6FDSLSmYGrD8t&_Gtq9b%;I#nPlW!ywjO0bE6Bk`DdW9+AwT8Q!A$uAF+?z zpgrH$j#?g6u(7%c1t`WWKa?!wdZ$1eZ38{-GBCXy!*}o1g|oeAYZ7HN6My&5UWwtVD{qF^fxAqHob153vLzu> z*Wdvdm~1l;emXT?hCRI(tuls;-IamLK+`MQf)hf-^5dj|7smRcLT0Zh6vfw$Hf(PK zKUGI1p>&V0#~xo0E4=B-CG{(SZCm7i%$%l)@62BC+|-v_=Cuit%OxL!wU(A#tZT54 zh(CD`Al}JvS5r{Z>BEiIVfEH1Wq86(<~jW1jQcl-Fvirr*p{{j}Tu}PGN~n9APGqpd;xa4M^dVN;t(2`b+o{#83>f9($K(=OO<% zN|Xn1hHPy-oiCWAGGbtkMaT}x5Qfw`?v!7=2@TI~o&vEh1CyTwj9=oGw;{ zz%~bTu)aqIra9*`5c5V%)f@g*3AirbGP%ufxs*S8pa*Uz0vMdme%J(scc?#!<)cNE z<{kj-s0l;)Z~Lja`)aRc3|He!@2pI>2iR!A-!XXMe$W2 z{SH?TCF>5WpP8OVvuG39q8i!s7;m1^{UrCe|x{sw2f;4V*~k^uNGlxw}HA2$L9>8zOYNwpg4Y#R#r% zv^!h$OPo*d^)nWm(0%l$P24){J{R*qML*&L8334L|CFrOTY3v#tT|c`A3sStjO&Ud zMm*v@!o2pOz?&z<+n3GKOh8lQ4Vn+#_UBRp>qxXeQb!n{ts#)J!hBn*3-~P0VbEm&_XSK5#PL zlIKixzWRBzW_52@lM&RuhSa)yX87;SgP=q4^FeO(f#m&I(U5odZod;Czh5plpU0mADP`o<-!P@r>KLdg-S+uPCuvU+3R@-PqV*+UxQ$KijE8)a3V&;|(AQ zb8T^Nt6R9>$EiT#Pgb|Sw?9UZt~1Ab4Ya~MItyAwbZDDNt@XM$^0}xp?j6QvYpyc; zT21kTiOQdQGD&B!hJ{$_iPL9UGZkm3R38Ug+0(y@roOj>kO7uMt2^)w=%XH8@xDqo z+f6DU%uVnB83=xrbiBN6QQ$p^#&b?~2PJQd&e@J-P`jRwP zxRvv30o97DA5vFEjsN?Z@jc*yN8l0pP=ASqpkyj~peGbG@lXrhjbVy4cHUK1PFzP= zq2y}KV|nPGO%JC!gyfNp)LaoygPBmr=MlEe(l$z4`mmJ zP;z5QxfV8ab$Y?cj!is9PK)>k_bRIZKs15oOT%Lzj<5XNjptsmKwa-;yL@Za%Bo%f zPt3fqDjXJA=n)DT9k4lmf*uOQ&?gyH=#yd>8{eH4rDQsEsQX@`-+&3VtqR>uUP21R z8R;^FG|@gDpzlVXZyFN7X?tWa~*#0g< z>&Z!#YB}jpE8ldKu+FNX1{o?LmeAdYD6>ffmY%_(bTjb6bt%6cwe%Yqq1?7IR~Ld? zU&gxCu>Vv#6-jn9RC`ghV*RQrBD>wxRV9z=U1T)Zlf4P0ABkoC9??!OAfL1;)qZY0HB^FZ#PHvfV&>1eS zisiQ4e9G;=icqB1y%K%5hJAig6_y$y|LA?VJBD@bka;4lR#C{A%OUr|oR!o@QeC~V>riTT0f+q4W4gHnQ7 zzz>DuV@8%&^EA*RwQBd{PQ&YYD#$3MF66Fb27J;4tqk5Ib0qReUH*ZNRB1GUo0~R- zl4#2={Wa9q+jDga7KLImeMH(Izf+h@Cr|?IS)vY+>aR35QP6|r?^1#*P?>J_rO3Lb z%2r6ldIfQo==K_a@Yx#_JbN)LJka^YOyq$gS-o^(^~nap?$VJf+b%KggeoCT%Hk33 zvQK*k8G;ok?!4-a?Yd?n;PIaDcLt__Opsv9Zk`%a!}yjYSDMFw`kW!Kl+@r7isD^c!rVh$g(l+>9TSw6CT!%H$4G!IzHT~?0v=+0EiL528H3C5{f zTKr@~GxyI%?R{3xKxCX@`|<!to>OcU>J^^nogv^|N6 z=xuUbp?`9HeF63I9`{p9Ob%V9!oGJSdGb8GNlWwZDy-|gRG$jUhyWc4LcKxV>?|}e zN0P-Mg7K$JH~;1W$bS6|p>cLZ`@9$>$M`w*{^bi0D?{WOCVM9-z2&LhO^Iq14BQqj zA;DM*We7)+oPTzPr-*rc<^JVjZsBMFntf`-WA8TNqE)l}`>)fliYFdvesdK#X8C`I zO8h7AtAB3KkQ^k{5Hw`FS;T9PZ8*u}`6K4rZc)3qb3Af%WN5fl0_ix(t0`Z*)~m&} z?yc`>=%fB{w_9)so`=l>g$~i(+AXPgY&`OnE?o3F^!ayQukR=^k4J40QOZIm9}f@t0DMPr&ZyhnK<0JFtKF&b<4O`+2()V8V(;aVA`BJwH{ZyKKb( z&$>$;o21GE^uA7PN-gn!2qVu(sC|`F8t%469T-mJ0wfGxc3WLd-kb2S8}du7M>sd@uh<8jYiBz z^RW$|+k*;mFGTo%`2NKUG*wqE*%TVDqFDf#@95Y3PFt582|nJ|KGgWhHbu|0$H#$l9z$mI6sAF>-~qbB?9z9)4t*J2jSvM zZ-Uymp&Rw4MVB?L1sgz|#&~GFzT7BZas3nNmH`F5E}ZS>*6jEJ&6zcVuN`Te#$JRS zFuKni9#b}WVt(5%+<-TcTRi7S`Skt7_g^lF^#FH5&$HhQZ5+0~l)JGqy1UtD==1N& z8v#Lw-YSeuG*G(ee=3(FH}jtJEKIS`EvFS@HnI`PPh)PR8jws%szn`=kO<&~=_!$$ zY$EF8=+p16crKVe5tbw+0&S4I)UBr~mS9cP1DXTVEx$ zw*3(#s41w&-00RFkQ(7bie&S++&IQ6^oD|quSNG+q)dI} z?%w_MWfg`=6JjAc&=fM*>>U~RlJ?V2cz2%jz5b^pf|Ts5|7zo3+fiO^KX1Dgs=F;E z6tX66CyO#l#Sc7KUirG=NMvQb81nuaa}Bi*xBdB?ST$YAHl8D>BfN zZ(~h;m)?f{cz2t$8rAwlOGD7$@5FwEp~zuUD{4+c%C{>zs{e){A=R8ur9A@}e(42A z2|jrE=+nhUh!sbQba+|yxkcmo-|}fyKKmH5!r^StoH*LoW0UQMku7u(v;$!3dw$Ax z)XaJ6A72eGvzwhs&Wlhfu0I&MsClAQa|e&0c@%J)ULRzvz8!yO+la&(a-)l27@|_l zQUAa1l@rL4b-I-NSA5RW5Np!-#iOW`Dp{CtHokjT&dj+Re?gHwpEA-_COt;6iUkBj z%JJ>jlN0-r5;r2i!sw2KAj2LbW;i$}YhBQwXJX&|FQ*tZ2!ZLL5^aQcBjk(XlG|=4 z?oapWM97*7c|nSHQV*cwB(vj#6SUL#me}sm?)q2ucF$dW4$s()@M4}HTF;>Z2eSo4 zc``2)-Z(#V3flZTLf1F(M;3jq2mps-QqDbD)7LGo*=)OOevWQxXGyPi*=kE$t*YcSL?pRu6I^p{}KOW)6?xkPV|`{I;(@-oz)e7;x_KGU8j zvq@63zy%5aQ=$J4mNWTLX6F4W7JZa-@+^+5QBXl6_vCreyq#=?t%2fWh1gZbLSW#* z*)iZ>)&sqv`6&6 z%LQyveVI8ca{T(q*jJ?|K^i^ssWhO_x$CUCXY zB`ie!bIcf4q_lS!DMSF9(Fz;1@}oNk#GU_99d}0%L|dQ91x}VPvg@Dz>qOO!+&euu z)lqNR7=XR@caFnW5VbtdS%_f{>&HM)H~gHKCffM2vKcd=Ike^G%!nFl(#rfoWXU#P zWMsWY4%1P&u|vS$?k1}}+Gq^DC45(8A31#=3x8(t8z+G1UJ-tAXdTp9+i4^o56>fA zPrKVO6ebqkah^pREI)jWi2GsW2_n46l2wn)8&j`bFrwuu8V##x7nhq6I|VJ~KWst! zbkFmG0=0k6UgY&0+<5n&!aKV@M6=*Z9+AEU7&t$|AeOCvpA< zt8;!IokJ+C4x8a!Tp)1uj|asbike%Ch2~Vth{7e3rz}t#MCsC)JH=xjRl3BGj6JO~ zEX`k^A=*G{ChXeq@Bs@UkLQ={t4r!w1~R(zViQcYdb;v@3NB6vnS1FQZn;+~1%Gw1 zGkJR;-;N%GELRfoNbsr`y9e}VYI~|mElrhPU5R_7x~(Q;D7!6 z=VU$N0mG2T1iIdJAi<#@dmg?_SXegSA#5D%Tq0`t+E5Wkck2xRNHf699KTDm<)6B6@- z=$n=3dO|Ajiuda`#HO!pH|%h-!od`$ivLj|e6=^GzGTK%P4?igq;SPVhZ~=S87Kyj zY2LdBtg^vEpm6{+SMHfls>$3>h^%iVfS9WFl?$C+A&E_B$C083igr1&Rg^wO=gd*% zPi!U}MNZ~`$3q?={ceZb)_*v4ex^W=8Dm}ZA&;UA8(AEtnRK5 zm5TVp!~I4F#)rObI5nvfUuaj7~%qz&;`Bd0kT>OfMfyPAH_43Ek<4L-! zSC|2*eCoT0DQ(CrJu0iI+jCNP11NOB%*bIt!BZLjJumr_6`u7YC-d{4yL3feSF(zy z*fQSgaX<0^>7ccz-NShv;JN?@y`GQ#-D$97Y)F@cv|G4)Cm?_RoZ2!4_E)vlwJ}yt znz?*0&9ywnJ+q~M=LqiFoPq^%{KE{{onw=(|{68~Z-0i3z{7FJ@Ny9b_Q|X33G=4_~l9dAX)+mM3wW1*=ch zCLPWzrU^eoDbp|MT>J-TpgTYQb1GV>=ti<`mV$zZ+!SVDq2l2e*y-k-!qC_1nrL9! z3j>F<_N>ns7*j~+@Sk69J?jfrCv$q#is=hVW1cyDLs<`WSYRtKM4u82o)O^%`x+c! zJAnU)lA4}8SXgfp(NsOyohePia=_3Eav+Rp1gTtteIp{Rxex4P-?>$9mJ?mzvy8!2 z5Z3t;_Am{_Fhg3dYEE))kbZFDi>DX!nWJx6ajxbnGOf8?zwKEPHfs|BFP$R$X|=9$ z-z`R@WXnB&%x$0{2}XoRen#H06UiG8|B*lnb0U%H7B2H|kT(w)tp&dxcOb;}ELv!M z7v!elKZf@__!SdAU$DJMN;*ZovdHK_JoIRSqMq)i;1eRj`$E72_juhTaBw^GQSRKH z_X{iUL9)fh(&(7}qizsctIq!`3~;J-YLhVS*`+u`XIWJ@uy=$gRx zTgTm{jZSMoBH_{%s&jICNd_-XMICGutu3NU-R{_jBf!hPlY!P*D>4qallCJwQly((;2k=M~!)8^9YPCM+kaPS;ncEm5|HSn3`5Grky}$EmKKcIJz|tdv4J311 zH>=a%M&o3C&@j|M9yS)+k6paKS=D>Tk@Nv<*Q-&N!?a^j6)Y{)XwC0Ps{ zy3$PP(+=R5t`pVlS3koo3S3w*{lystV$gyBKpwjtE1w0w8g6MlLg0a`@9Lcf>Yz6# zhYyJlANvWGsSYDwUCM&)ZipSe8eW7oDeHIl52OFBG>`f4xxN+#dPapqUBdPWmSvkT zKGLkCc+B6D^E9>j1)^Sp!>!{_pu;kOU&m=>Q8!s%&ZN2Z2>DaTBp+CUQtxwAF!r;v zjGfuosU1d5hVR%lUcq>scc1Pqu5Oo3Us)R1Il?;pq5JyV2 zr)j?gNz41nhD1P;SE?eC> z0#|Y}ZgJ-ctZ3yWXiDAsuw{I9`ddzSztiM4{`S7XRaNc)^A0XN&(wuK-?p!kf`7_^ zTP%E`b%m<#hha%bMUeuM7|KXysmt@uh+$yz%F_yHZ?I-xLcbUJUOJd%!Hsic7B$r3 zL@PqE02IaQbVbaZVLU(aMn>s4AmY%O3$F6Sg>^DAGyx5pDzjWkJyIJ8!ZYLKdw1sH zcS!aJ(qL9rPMG5{K);6i;(GHK)xTsl3Sgm$&%w$aj2a*%r%!;^jBej{0}}B*iyFBjxwsvqV6~ch)QnOm1pGV zRnbKIuUFUuI#c7S!`oDH4Xwy=Quo^e^Rj4~o?@ki)Ns-X`Co(hRtPIwcE%!7f?yVT z5G`bBHjg+!`;*&z;&(Q?f#1uh?i;`&bY*x(6?%b4Iu-t^y3L-`16$C=vS5zuGLW6W`TKYkbbH3+}bGRStT51f(OK$0*AdW(z?ucrd)wP)fNXut^Y z!$-Qd^8&uQ>E*(joH%gA6({$+Wzuo=2yctWnC?z9E|tnb!UPgcbl#b1ceyi=8p2)6 zXQgiXn&QbAJ`^9YTrpQrSbTv3Xl7}Sl9|5oKNo*+*vPR4??n||$--5kzIfyGBr>7a9skz%ee{+}Cs`rh|<*8RPjqJQe2{ossspy6rd zP49nl9f_i26*f6{ax#!STc2dI7A3w?TTu0n1 z6BmE}m7rmk@CyH9Ovw?fasm5S7(X%xuHS+w_v1xJkkqDJU)L~mj8ol5&i__)+)eo{ z|Fl){RkHhhZG9E@5ZKM;6=6)*Mt-bd8~!5IBL7M=_3*l7-KWwY|2SU0d9T5IeN2fr z&TJVMR2j8V&rnPskU1M|O*oTwapfF`gs!0QeNM2f;cbG}I^kg9&H)#R57_P7C zYdOo7u0+}QB~AHlp^)hlS7Ab6x^SBnP~=(sRP&r+36?<6`|STtQyhP~CctOWOhT~&uTfGGSK+RwZv^&| zcM&YG?F7qGcHAfFN0=gpby$MT&H~4M$M5muYAnIC2WjLFI4sj5-Z%T}E0Zl}W>VEv zsP6c^oI~yIz+JT2$*S%kp$a;TYr(-9iplS;E3%9z!rj}rNqbM64Z&~*M-D?ru2^(=`jI1yfb z{V;1!FbnJ~+O5%oTdbK~sIAK=VM-t02*NytsWji<%gWCbS7%%{5U)xIxKpemtQ;l_ z7mfqSfJ5_%uY6?Wd>#)a7-Nrqj=~maq}9_k@J;W&_+LdUR^sB=NiYpT>;!Y}Y8A4K zRWeM->q*kX2g2X2*Y1?XlQpSCdSmlhpKcaFasqVo$N+6a`-jd|ok=CT%&0F*Zo?=D zq^H(!eB_jzR>&GqZpskgW-b4mPj6K%S^q;m4V)hUi8AD@VuU+hEzCTE_&aCD3pycj znG?C058#aK(G2!c(jZp-Tj5oh=l$<_z|q<)4qU7M{3>oAUE9ha(Bk-mk$$my@&u$K z4>vMaK*?vbCaut(zPYB$K)FQLPfa~7oRZAO1l<)+-j3bz{B~o!pf_u!y%$d=L%!2zYg7)=&GEXEI+1gNx?IQrc>de2_M&vBE z@Q)P}1%|TLrhn5Q#{{!LuTIU^HRO_{DZrzuVtEsNNJFWVVA`>CZRg{B$T2SD*~O@J ztnQEbHz|_TWM5*)^_MPioppjki}uZ)ajS3(GQz2qm|nel=aNv3^?|GuKm5ija&V$oQ`ALmMCE1c3FyzQDJ* z^;vZB*lVTxs*q$BEVbbD6RGbdWiYss1~kBdri@n5Sze(}9Y+pCc=}Z5np5XnKC5Md z;oe7F2oAPOfDOi$5EurN3X+k<9~|l?Y*3<@13*0O3|EB)ME7@8-z*LtjH5e zKA}DooG30J&MgTPQOHrj~yGK^eynA)6HKBlF)$=oL+$ zrx3$6byvqSNX!r#d;|N0qq$PyeM(joBsVojQK?dz*4KzF#vU(VtKe_#D?3u3m)4Mu zN-3+g5I-^X5(SeJ044cmgzlomQjfEVHqj?HcBwI!oj)lKB}CAE>^VT*2zcjRc#o)z z9si5Xl5Bn&!WAK7MUbY1P_9cs2l-*Q(LFK~zF7mkxbc_Ah9fw2=Z=;sJU59z!l78pyW8(TgdEsd#z1yHhV zVNy-;^4h18aMt>(b60*Sty!`(1}qPn!uuj!4Ze2=yx7;N40*Wh=DM0Dj zJM@A8Dc7g~c1kDL1dgh23Hs7iFoT9Hb|4kq%igBGkFw>NOPxPnC)n`l{5Px!olg!Q zz(~PSgDk&tUBPFb9Aj{@d||9iG5o0S6wN86Jrl20E&+ZJNP~?Az(}u9LW+nM~p+9_Wa?mSX-WK1H9=c zgQhPNj#xCZiig!4uL-ih*0=mCZf76S_0R3-5xpX`x;-Cy`uy7V;l zbQxK_X1qDmaC7K`k588a32^tLfT*868OW%02U*Bf;?Z5j(05JJj1bXME0JMoL+1gU zVfTf?73e+SPpxZ_E|65wI{TqTNg24eKk6>`Q4ln?Fj)8iJ+@3qdY+!WbbRHq^i%0~ z71)E4ng3GnVHML{n*W=#6E+Ov_sA#98lj_aQ-v@C(HZ?kV6-N&=3_5CM2?wU>zU241rY zOVZ6+n#DhU+=t{7#XSPb2`$jV;w#c7Ksv++L>NEphx6e3ORAf3+V}4}B;8b=vtLVE zEnIH)8Foac&BF*f+(&h$X8{=}sSw&U{ z!2J8!g?N;nv&TYyv1Qs0DktAwVN1B41uE5cYc_@0=VUlflaFkI@28HqyfDa3bvV+ zO07lbc!ywby|8bSTW{icfc^M12Pn=Rw(7kvmFkTuD$4oWPMRR#BEO#3zb0pN23^sE zz5BK(Zt3~~_VKp`Q@1_qHR~g2@V9VD41Vo3zha!pk;-qEzQy;aSrpl!VcN?(Ko`2U z;DSjcT(*KKmTH6QmS9;pLJ?71<^-u0vL9nh9vtwEf!@F_@w6Ul>p0TdA=%DPieUq5AKZ;VS#%rfMZn$y0t$4WA)PTDz?$ zg;f7WtNH>RkZh2%1unFcdZ()N9S&k6d*h~sX={wxa@&&=cP%FfE8j&GdiF3$`0Mxb z;WI+HIyRx_XnpuH3vnE_-7_^O$EEK0pYt|t^qSI?~5n72pwm==v~F;$51b@|M9({I&FuXSod|w5X6_dusaV z(Pp14bir;@Y2lE^D(Y8=V*A)Z?+iDI|5)sXtNG6qmf`gGZcW8yqR+O7XGm(v6Pv$9 z_MHWx&FdbL6#(i8?MXh%eCsydr*p_Bt+f~IIGj$BL92)81%x^8n;)j1K2df7EwNcV zvy|OohNbb19yo8a?hfE5Z33(X&?b3P8y@}nm1!tfG-^x8D)0K9N*ZCNtbXB^MWc9u83Y49_sgXS1wiQ>yVhu;YPAi(%t_Lh0L~g56^8M&Zf&mF3+%H1L3u>_-5? z01#Iaob>IueD_0P@k^C9S30UcH!zPNdscX#>QSFv1!zBqk94xjaXII6kJ`$r(AzK~L_SXY6@)DOHh@c%KL7 zc)FF3o=M479i`3MS_D?UO*DIrC5u*Jha@hO7@SxAvW~0Hw0CE~7siG@k@($OtN)Z` z&D&76b-z1<70+U6mW8uC1Zv`K1+74nN!<0w%hd|lm2-$%6TQBX+ta}g2Tr= z5Z@L%N-N3o8_oo_j^Vxl%5+9D>*PZROA5q2>h?x|&;%d}mTyeITQqMeJNp@^g+z|A zUvo`l0}?^RHgJ_Fc4wvSxs5vX0?u6+e(nE`w7I{-AsSGO28v&1Dj95Jtuk5vkNLq~ z5TlELH5ayP=rVzpOQ>15JtT^Nn`@2JzDS2~d*ZXMhhghgIGHTZtR5Co^L)fb*%+i_Te?4O`u6~?Dw(~XBLO?$E6a7U~ zfxrQ6NEo}zWHBdltSQ!9^1<}eYOT7N_H{kerr}3_3cJR-8C#JT?njCD<3#;+AHOeG zBT*7M*M}FiwEeTc2&q|SVp49JL!-WoKoe%G!y>Cb`qPYY;F%53KZaTaAVkzx^PoSFzsJc@0SA{)32K^1^eb_=V zwXtN}3g#om#M}86tGLO1hBPZBU_A$_?fS{U7Mq3NDBlLf?Ax^wNX}O%Zp$q;LK)MZ zn)J^C$M$7cK_GuD6aJ6BMMIlb@0`%Q-2y_>dZFYrMs);vIq)a2YcF(!v^9s+EjN{a z2kMbx+5Xe}I8Zh!*=Z?~SY}jiB5W?_`yv$E{y5By#dK4}~$wZ1$=T3Eak0A+b^qGGTY9-mv4`0UoLay_f#7g7wJ zBIs1P^rq}zsf+|Iac4ZhL{@!Sal*?~SX2v#bmXk-z%bwI8u!;FZPsz5g&E;bQ!z1i zfcbl7FpH6*a<%p+(P>43H%DlCC5vGpK&zbPKgnKX^|yLR80y5TqwDpuih*FUU$}dY zphaB59*X>_1gk51MAh-+A>XN{@4^96n|g(&Kb08*h)LhB zK?&1JZoEYrjlfU_4n>rZ5oVPZNyH2wL;P`MBNllS|t81c{W>g%_^xj?1CLuc;8 z57XIuXfXGbFBsCb$zT( z(!HqR>ortw?2+gFKs$E`>~gOwfXLlJsaF`Q#Wrhhk6{OZf$VNn4zS& zIt>cI-> z#hATwj{F@YO?>OyA9SDRiylmnP#Ul|qzSN{w6DwO$i8x)McBA?THi&+x$?On-sm=D zw7YCEV(vS}l)**H+SR#}qXM&4!KTmJH-Y_}h1NI8B$)^>A7eQH8w}9pSV44y|0Q)2 zBBmTO-W33Lps^TZiOjd7*!4{T!vU%zWXYqc=8QH79pDfLxr366LI-Hd*bOO=$T)c=k_D8E0S0?NHc8<*p8~Teso=UEPMAhQClZ+18O4rkiuhuH4^Uw>rB0jlFGstrfe;R&s8FiG~fjNK3 zn)p)P7|#1pow^p(DVaD2tkx`X>7gdLKQ0vkeVh}2x3S6v8o4m>%08+2Y7c;xozHEd zh(ZFaxabDku{>WMNNkRl@jN&f!!zsv@bT_Ak`S~zi{{)E!vx(`1sUZb!yDJruHS^e z58lMW@q`if3pFp9aN?tICL!oy(vfpAxPYtoHy>Jne|H6_I4uVrCk?eePBH zY(Xz#g1Kl&>_U(u-IS%DI(OGc70pMF{Yhz_>xdTs37 zBD8;X%}}!P6Gy{Se6g%xJh$!3$?jOE3<|j7MNz|}rz4JSn2F=^)FD*aLwjo_*sH54 z6xF_iYk4Dat(jDz{a=HaYRx4(u7-jrfNEA@vlKo~*H9p5Q zT7JVMHDj`gSD1dzS#=Y5d>+11X!c+gdfBppNU@ItJ8|cZO8z6I!QpwPUS_SpK}b?p z@jKGK`8)uO2IAYvLnvO06$jc2fU4dv{O$Q#IA3cEczu`b7jcn0Tp z6BEtY>5~$N9?vJK!-Z|T@H`9l#y!XJtLA>=-Ob%PfG;5n>1SC@KAs3sj;r(bIs@-) zpeIGCGvUzaZCW+aSnuu?cd2Eq|?MT(MKMji-+?tf-Aq4&LEMEdE& z4Mct?*X`U7i4vzc3C%Pmd^Fd{(SdV%_b*Y^ungc3k6_uRxa4-{Hjo#;bE{0V#d1=3 zGNHtuCN1jx4YH>22!f$R{&Z;Wef?q5?Z@V6E0kYr{IU8x`Cs+?xEDM@i3{k2{@o+p zc@ub)+il8c-te{#G|O$+8Ei*3vQ^G`B=ZcG<%iLTt(d#y*SGSEWk-w4tFdS;X+b}< zcEJ1Bh4#_9)y02fVfSy}Z|i2*4Z;E(#|`k?TV(wDbtoY8%}UA^5W67eb&SSi-cb9+ z5xTj7Bv>)vDBqfb7^WLG+4Tl#=v8plPz>MKU*~n4rxo903Dy~`dK<@9Hyi94^)WH?e~=@FGkkNfqZ%!aoy7ku=zFWUe<|2GR@P`*P` z=@i^U(*#L1!qolwb~3R_2T zflgVvZ^maiAC$UFpkX%}b!agC&6_05^6vA$hbV!MQbElEBcJbRBe1{MhmcV7!}X|Z zz-}aML!`(Yit72V8~98)cr@Yi0#g^I)Ie_*-Fl&{(Qmz&64SPah;P&@rCpM+m$bG% zq(O;x@~dJ3DDRJu##?<<;85RRY6&vNmDmE$R=C!Abvu1$I=cikd@f;sGt%JNh2Wip z1xM+2k&<6vDzdW}OeFBX`eH-ok!Ui@;Up?=3yI-_iXL8l6pu|=Mvlv}R*5bhN~a$( zrI+u`_=)k;y>lT0s~L1H8_*zdVWnZN-et>kBor|Xx9o<9`745B7_zbK3-jeuB)sBf zZ$7Tw!>&Jcw1R=wCYo7o(wK@HNy>9y0BFUfyQeBxSQN_*wmXB53A1#_t9AK37Xz^! zN;Xn?ey>QrbQu~$(a&jf{?Dl9{We&_GLRY$Q2V@O+lcqQgC7<#Nl$I-u0HRQnxg>g zQKWpMwCHC)YNx{J4n;|G@G6D(xarAq;gm|^4Zuic z-L9WR)_MK#(_5Uc=wU`&+#k%K^o3UvhZ%IL(3M1FWl6`38FO~beSsmJr$d$+{qk-- z9WGE3#l644IXsUCvZtO6BW>>=z?2x$g;+c$`1+V$ZWg zk5<(}Mx6Zu2yu}xum64=+$|sV?e;fLua1`H`_p@0N-d^Bca!n{^8SZBh@+W6t0ks% zQ7G%pgV;{w3Nk2@fYR_6g!%o>4*emYqoo^RazsP8Z@$@-B5^_>)vhS6#6qd-FlhNg zuL98hkfZ~fPT3_FKJU5F2ts=kVF%pgJB$-h?CY(Tr>Q9Vj~PB=~u3 zBsXBY_T~_l@bz_EnHHn>Epv{cS*%cUDz)#}5@=&DLq=agWGbH#dyPrd1da-_#;${d zipHaVQQ<5%LTIlIR$ftM#{2r$9Hvv7Bt@QGgFyzOsx=tC6j8dZ6^HglD;ycP9$!S# zN1Y|kXh8#kG$m;F2$>%2fZ|=Uw6JRNJxE^-Lq))R0#_DUxaksMN;XyB<9Jwwki;qT z7l}jY@qJ^pZJK@!NN9>YaMNKxWXunW3uTQ(cj9QL3FQBlIDl;i_GeoE-TBpl zX&15mw*yp}zrX2yeyj&oPp|&W3`i9K-I+$eJ zOx5Xhv{ec7Fd(^2YnNhoKdFH#K0Bw=?B)ljSRGMj+O8|@ku^0nyUUT&SIyztkw|1q zdSWYTo;}d^D=m~jvvQVv3@xP12lWCAWd8gqRpEv^6bzbyH#?Uo;)HKajHp1nFR=AkIHQH&=?XblV1yeOae3>3J4E;mSV8VOqsGL8 zwp)MMc>iU?^2g(Zvl3Un0)K2`)#L&p(XsQn8~gn5@#`B{n`d!g#!D+O_n0X>|il*qyV{;&)qCh-00 zb@z)Br=?%byH)EGKh<0lF67VMGAyg--z~~FpCN}}=mV4;n+Xe&7T1WK|NBTcnp;}h zAr9;x8J!UvL4q2bnB#@iy1Q2`Hm~Jkd5aS86IvWVhq?dxQ|m_DoVh4e5**lzJHHRY=PC0`F(sl zVy!L@tu@)9u8Bj8wHtj62cNVq;mj%QjC}Y@9fmOvcvVdW$w4Zn3D$owAs5H&|D!A|4vQa2yC+kH)9A@~t-m#VSEzIW8^m>a>%gjGW_!uD4WwB9~L z&OO*#Q95!?+d%ZS(~p0(FKVKWqK+Yo6(4Rbxy=eZ1CH}uk^lC3*jy-ns>!Rq>{G5vZ3Nb`OcpK( zY7&}H(EUuAm7{5V&^UI)X7JgTWpHQ6dm5iQU40HDZVJE9O!4eZk$|x;8-z~N4h0H) z!z{p`@YP?!yM@(DZ|cR9b8K7c+{MVhU#wYpw5*9ng7!}`DNpRhFAN}cH+XtPZQo`% z%YN;6+k!cXb639#W`s@+AV;JHOk&{dMRb@Ry#oAU3tbOUNp|}}`c<$JEM)P3bdq@m z#i2;*M+c8IY zx$}FUF=U?#EEZIKg1CIs4rS)uYuy-QQk=BUi2ZPw*Yqcob`FoAxEFau$Yu|DJ1p@F zl4AF`Desu_+4lPN5#Z{20lag9tcKGR&N7X1e`9t%Nn|&pG zU}OcRSA>;jDCZZu|LHxy{orEoc4RhjS6%K}>_GWfL8-X${Ivp_Cx*Jqywop_PLBH! z{|4PY?*-2LKHT7Zh|JK@a8RU0Xk&~?o|R;1}B&>zqqRQ z^o9mZk?YF(2nuB0TOx&tR9nnM(=0Yx54myyaz&iPvq)v#^M&_p*}go3TiI3NxaU9X zhhEY`B~7AU*(IQJ5*_0;lAHK5C<-z-*7O&@8x0q#JZ7r2+SNJNiL5r5>^E&i4U9Ko z_f!1Z-q#Hu?xI29UQM;dOACyP1su=L-=;(ButTd=nq4?Eq_B?qpN>k7g2`Nx z0E!XTaCJN6VSdx-3#DewR1y*9)JUE7f0Q=ECHMVgf?wrtvK%KdD<8ax0_Z1v)w ztq)`TR{2joYu|sPB_-_X$TPso@Pm00-2-K)HRWvFul9-_9=@}_1j(}2iu(HoajgjOncsw))2IDf~-~E)%NZcx7jLbHvid9$d!H%RpjOB)qC# z1K=H()dhx2_y=?6L}m|vD2w^`hu1TC4)&%NVTU(p2-uC(8E!Q8xDeawUTGP9j=Vm;Mh;PK}MPL40+d_$_;Y{L8>KV(y;I? zc}VDc;wUPIn$xr9w59`b{!{&WA7D4=C_M$}P2KP%^L$iJ<@t#X)=R3xC>Sn}G0zO|@Sotv-+3^%hh-mQQ6{#Nk+Oo_UXSsnZ<8YDw;LXV#wmqZ^J9g3|X zmgWNQ`Vt8xNl65PoLRMDGBBHbb6dt~ii=(MiHqCziAxT@b^HEWg-9w*HOysk|BecB ziG?J3YhHk^O_FPoz}1HP$NNIex$6J(u!#^FA`ZdyJmji;B2P}7i(i4rr zO2wAIdZ*2$Otu=3{g(YZ4VFW7<0JD-zXU(o>(GZR=|!6#XGr4rn27hu0jpuMUyJv3 z8kg=GLq|j;Y1VJWMxd{B12Mt<=$b=_Lq={?XaD>552?3rg@=oKjZfgmxQc&#nl`o( z-7Xh)brin&>^Ya^gxjp#wT{>0qM9o46;i+AjlRbo%Mm@R^e(3)S z*9$pwjp5#g-RCBY5n91FM}-xg;~ur!|H{2{DYmE|`Zw}jW;N~Pt^eU(CU-5~@l6!4 z-Mo?=oX4w~7p6Fo7&P!nrQ-Z=uxvv|=lzZ)_a(DDKHvZv}M><}-X0rcu5Px-I;pH`*9l~I4Tq*0JP^P6 zivusDdnSGf7Xt270DCONL{_i)jZ4636%h7vj^)S2iI||@ zBPPrvFF-lCdr+5KZ*&X=M@)~B=uZ%zbaM&(IJ$qxmq{r%#0xkBO-?sU#?`O|>&WL* z{MU(9n()d}7`>R^njEO|bO*Fa-@NfLU0Le08eAH5=2x`|#CYENUcW2E^)3NRsu)AS z5g^MT&|Bd6ccF9sVG&#V0^mPv0HVJrx6TZwb;82?&#r#HSOKvf5##!zR0;a{V4)eN3kn0qOi8W1lNts_{E= zJw%RvaMoVD4-h@U2>p1O#ndovKq>3pF{bcLqx7&eY`BEo*vAvp^dXm*vTxjP%3q7` z8gQu`1=akcR@w@9WBYNQW`~lQKDYli{gU&29M`Zqc_x5w8@EjK?(*wh4LT7$V0?J{ zFLDoe0IaFO2bj4L?(dqO7A@Wqy98j%r&*G}`r9@#k+f?wL z8Oi&K`NfGSd^vZAGl%LecJucU{_-QV_jB%RyK#Lk_{)qFh%Ii%!|&_Vb-1PbalL1H zu?}BbS?)F^g?8>UdQ@#!n=9R;D6HihxwBm786no!S#c{UPi;TxU@*T$0@@9Yl?ueG z7zQ0&GclafPBNJ6zNCiPRlQgkf7CT0{ZZnH#63aMK>l_g?(YveSbLB0lEW8@hM;g% z+5Pa3BXC13p#D|Byq(Q~-eD=vZzsrxyp|g*!s1v!*nGS@lI)M%&|(#XHQs;=Ky&!_ z|Bt8hj;HdE|9&M2AtO7-9tok$a%@=%Wo1WFBr-FuvSnq2NXH5xd#_{fy+`&qX4b(u z$2r$^pYQK?-}m3=I@jY|<8wam^?E&};Lv;d&;R;hj3#Ifl_G#44Ij=}t6YAW!bc9; zxecu0$Ne?$)4N_ zghxFRV-HwgAu0?pb~DY+zL}DRej_8Xa*(uy)B9Q&Ot_gALq?Wa~s^Vu2l-ZNF3s`V>&ba}mH{%!-ofp>S8%%Vd zU-!rz(%m!LgcWX#Kftdj`}v5Snu!39FC0A9YCp#Rctspr2fr06!+Wi6YJT~B_$+4a z82*oH#Jd&gga05-^b~RB!908AfX(}lyUh;av3i|*O^BdkKxQ~W>yYnQdIYEK{<%1h z78<7`c$t5WYyHJ}@8#$ATD;2zHufBGN6XF*}ES1R`nEi&5XM*j~Ru#u>fjWtW zKE45p)z_`?m|zF8+G^{D7LDt67GJIu2UD8?90;$I>PJC$8Pt z>GY4%Y^1)`&b+|vzE`f++paVtHreUlMQc)xCogs z*UdRF5=F;Vi6&bll$|$F{6~6YDL4F4e(vC?@~SQC>A^$n1QljF0{T+=YNO1i-4qnY zcBIddW1d%j%{DTELr?Wa&edwq>>JV2Jq}bg7D5O-EloWF(K|1Ow5=EAOt0*%;e-M)AZjqGH}V-mTQsy0I@Nr7fnRilU6@}#+t2He!3ES`$bK!cbRe*^>-HI zO(fgukmTv8-ri;XBfhIf)SN8DwU;ajR(6A1(c9l>Urgb`zKFf$BZ7O?#yAvgKHUz! zDU&K8HVA(jLzlp9_C-x(5j-;XO@qys0C2zMfY1JFGFurzGp+|^YrtVE89hYY8DIrY zdnpvzIYUu2@_VI+nS}}r0T<7aw?%6Y+uk1`%o#XvN3rd(usNoH{po;5jcdb8wA865 z(oWyTGS(mqFMsWP>#mGl7f-F!!&B+u5s^h&#eD)C8z)8KK~Lgszje{wF@oBbKzw6=N7_4u}LE z>`I5=)~M_OB#sd||Eb|s-jlEV^!-OgbFtXYp9LkX!*EL;I2!!n<(-yu~r0Bzak zBwvP(tSX?iM8ZmUt3cn-G#2m6Cgp##rdnKKIDwL)v1e(4*i?c?hbm@90rz4yh5&wh zXu{#kQ~OzI@Yj`MoE(&;lCKYrZhY!m?_N6f9s)W~{X}p0tj*%a>rC~HPhoDY7IufR z%vVG2Q+=TrGaSLRoj{Ib!26uWWf@Z}Y8WCA=!$xdZH5P8Pt5pih^IOQ&IzUJ$v-mle?f7UjCB!T`y!i(-j1!Lm&jWSV4xA z0BgG|i@pa`OLYg$hg%v7sjAmFfP6OLwsfz6+f84%nBH=PMV+#WQD_ZFxVA-+xO;#u zjmIcpxtHQNN?TK?(I@ahyfTlzsjVG50Z zW)L*Vh;rt|_rw0TH>`p`GhxR3U}O3~QF+|UPMLMvfnAq#sNV0gxMrMM;*+!xkeDU7 zvqw|afdwPUahXEkE!Vs}V@;0JHLER^HQW)ID4OEIEh{LMIY(t&t#4p5OojB1+Y$MSV*G$*Sc+@l5$0{9}Vy06lNYG6{rt`R4J7#{plhxn762AA> z_eF>PgN8?I!#^I%bbG&=;$PVPN%)M)#dH^aO6$>^$Iw5>R=6-8WUB!)k=zz8jLkZt zwVs#sq+Uz$0bF%Xxa3~u`rAl1HSJ}}^yE+2e{$Gg)9M#?KPq$<@ydOZeQ@6^w)Wue z*VtevWeT24C=lSk^;f&)$*qgvt{;L_1o%5%Io-aSWI}d2U&(Uc`k+J@)wZ97do&F^ z#vA@_P=ObHO+UYy@1MdT$(#}cPcRNvp_ZMAD|6dk#{jr-1bIooXv{SvdVM4(woG_<-SkG8l4E*SolsD zjo|h<#UUE7R}R4Uyq-S;3*(>eS!HDO8~u7enQ{wS+6DgAp{(p2=EK@-!Z`TXj=9vp z+w4&DMbkkj**}1Dc>~l?SQU`_1-bjZTi=An5_KJ3A4dM@9Ti)qn2r~iP94hb`o2pX zpqZ}_o|>xTrZlF;HIix0T`OMkHJMITE4gL{Va$5?CxaA#G3w7IC-@h}Rg@vkj-PkG zw{qvzqg`z9x+E5V*z(|x;J0Q<5~I<(;Qlh=0< zI_^(=42*#ZtJeorYD1YUwFg0voak;(v4(X{{mZ%|iH-AOe!61H3#+_@zQI(2tiyO4 zd_5K=`oqvPFTt-{006)~mJDfOYhB`~r!lP1YK|Va3^X(@M~P8CSvwI}MQJ6chmFI( z!GFSeCb$45+4(cdu|TlS>S>?FFT_uXlD~N~Q}G6Ejb3m2U#hu=i3=}$aB=guFA*HN z7T{KDB>sdCde^*Hfv)S1HYl z*JEOpQryN&g<)r@_B2{MZ+ps$g`HyczxD^iMjP2HNgU zz#jOajZv|FaLZ8v3EfEE9B4e{GKX+2D;!6zTu`S=X~ua=Jr zmCiJD(JmeQwzx^E@vN%kTanUHa(q_U%%EPcy+)p%GV#$l*2Kr?tUo70y_&+-o5%11 zF4}2>F}LJ0xI|u^A?7p|x6ob-m6CsB^=?zXLLUD>1#93tc)mSTLF+!d7DBgCHsbYw zQJ<2zgUBgwfWQmvm8Eu=XX#8EeI(xI4b=|J^LF!Q3H+9EH~NVRUNj_1Ta%S+8a5uVLh%tN4R#2m2 z^G!%co$Hh%10#% z#Qr^4da2@xxK<6>Bb0_UFP~%c% zA7&K8#9z<#V zZpSd0U_*JVi9=BMAH85(6Nu48y;-xWG)J@8#N)-%6c|)Mca~SU1p{bUWU#d~v?wzQ!wg(dLo^HSoUjUuV)=m>O&#lw^6#D68nf8F}gezQUx@ zG|h8ZYimhZCrKRe-1;h@iS?F$M`@Yi4g;n9idaALC3d5E6hYQmjCu00r<)}Z9>A}v-J z>T9~Fw8TgBTt7Cp*%E&~9QTCpctROQF}p`#dYsi`by}uLIDv`DfL||fy#y;Riyi0- z#>d}y>{bZsr6+60&IWv~2z{3R*T?N4&n*!dLhh;9!L2o_T_Cfh;L@N0e!q~JY6l@q ztUYszyAq~RH15|&!q*kI__AsoZ3&alaid(6;4Dt^55z^$a}9NQ3Z7+{U4$%^m)xdg z@t{79g1_dtyr*LcrKJOL4u>L{`}hX1tfCm$5lqP$-Qr3~`l~VYo3UG5&siQy;oFuG zdbEER;%{IdVdQlbrg+D}|wg78*~EUp9|vBT}s=zV-C z^OffN%DuB<(cH#Q%(RXpX#0pGs8Fd?LcL&6eSH|rmhNj$#y+=}0NsmG^G9z?OFnap z4}}{}jWxD?_A#T=*e^>GLf>NgmTxzomz9240|Gu?*)TV;=^9QD0fgMNE-wSIpG%k|gxA z5}y~V0JPh!mFx(`TqIY4v=t1b5n^4DtJb3AJR`Eym1LyW3-!6&x^hiZ@g^3jE-SF5K@CaU*+8X z4&ev_S0>{xVz=^#MkYlEe9I!YGx!?Wy(3-KLy5wfT7qt1!1NK(GTFFK`_8VtAvMwH z7xV2}j0F!G7G%e~mVwsLK0iM}!f4XV zgWth^otftzchD|*e#-7?emFh&TrQ@>B0>-K)Anri2c8&4Nx#e&dsXc*52dbcj2C7x zE0UNvCo@S$Rc=SE@J28es)5P-wLj76fL|(Y<~wkEVi2PDv2mlr3s+Md=cA3``zcQN z)_Eq?uQGR%WRi|FjvhD{|40ghAF9vm2Z*#G)?)qWDteIQgs|o3$r8>fso3epMvOeL z;ejU3@SGk2#7g?skfdgRwAuy}YbZQ4^mNH<@FxR7Y978`wuKjCgSsm~t_Pwit9Z)h zvSH{k_oloQSPlrS z*$E%?sD@=$SZ?8=ZDGjnt#yxS;4|M%Nkk_u*#$u2XA*?%`?g!j0CrDvSJDjfVYwAk zH})~84;Q4=kn75?8A$d&cRDZcZx&9>BT?%OkJO(?0tI9yV;~;*``rKw8NrEQpU+4* zX!V%dM-)n$0>rNCb16<}uso<+3M>BN0FR27cKNx54^t?*48B-{`1gT%bt_!9#g}ZI zrZr;v8D{Hg4sp@_t7nX6h)dmssexb0+X|0#AcJTBV!Kgrej1iiqVeC|1ER*}iY3>_ z&8A%E^T$5jF-SQI z&nx%fa??xH$0reF_Ln@0e!OyYqp=zSQlU&m`Jc#QQ;&xiML1+2g3TBkg#Z-4R9E>& z5a|M%Sd!rSjimtavvL|9AsAj1H+F&;oq~S=mt*I3zMQF%st#D0AFJvH%3Y$8-7)pJ zRb#g1Y$Vp^CUZDw%<Q#_MSh*eT3J3tkO-g7n$(1eOZ@4Q556Ctg&$JQzQ<>C- zwav&ULM-$ep2o8JZ<9tfyju#X4D)ZL*1JJ9qKB8i8RxsLbGBL_Kz|oGBB|De*71I{ zu~P&2;p0BnyW(0_Tkvnmcg z$#|=>e?{**Xf;A@C(zGE;g4N@QXwQRSA|b ztw>(TQ&8 z^!+f*!?=VI&R2=)d{i~DUtz!T%k;8V3}9jb790c{u+NDRJ#@XmY~u(J<4}w4R}6JRep{+c_MZg{u%gZNsJM2~Yf7YcJ*@I^v<{A;O+}*NIJ% z&+n&99YSc#v7ZkGv34#DS)+R7W9G4h3;QQa;jaXK9XMq^((V0Xl4#$!dhOh{}+~`R9R>xF_>hd$TY;23-#GGIx*Emy=& zdVdusKhiTeJj)Q^fx+Z#s`-ukE=rJ!XPAcrWYX22~cmT_QLA{;;pD?9L0F zNLfvu~vFN|b#Xmrt zWPs$+3rT{%pXQ6x!1S+MmAIwJ<4=yTZrCJ~;`9@!WL0F%N^%WuLFS=!D=P}}7zQT7 zF712HS-~Nq{SJ3S#$p$U!+Q<(t+jQH1Cm8?M;}J-g&yTeRFc0|xv+Zv7N4jd__pSh z*@u(JwfL=i1P`dtc5P)mQ2;*>xO$0_*~5F361JZnpJcnApO^xnfZA2iM7NyTA9&YMhbw`UmyFY;x8&)oN!@ee)C>iG}C?{NsIK40JoX!)HW4|G z@(aEB_3xaX*=^Kwosh=>)XtcXTNnYpiKZke5=VVwPH67!DX?}0%WcAEMj|maj`--0 zm%u@WH>=3AQ!($}_IoEKI^gRpYHUp^IY`8X~$h%b6HA6erU2P9Hqzax*0_Wa|IzvY(B3q-lVY`DohlC!JxC z&LHcXF#7UUT8Wg@HblL0UqU7#g(IeU7w$}g3m$PJ%=63F6TP6$F{VawC!vy0L~*ch z0XA5osBq#7L=ws%NwA6?=@x{XllxWZ1qCcQ7+!Ytb2pDG(W8w=l7kd3+Zx}Ux(=|Sv!R@A8>bqUOx0GuK%DW}yAeY(K;MLfdjL~iJb|Tvwe`>9cqg0TDik!*_ zru_hL3lS@J5Es=i#)AtFo9*|_-`elq`tp9Hl`Jd|zh~H%fI##5`-mmINLBcf`N)M1 z{T%ulC!YSl43GTQ{}>+at9W0Zl5%Fq$9O0A;7nR~SB!KqhI%t`b%`1Zf{hZOy(aS7 zSH`CN^~0Kvm9Kth4_^qpLjGCn`LB}v85#GQnqRl*Zu0$Be6Cj7Wc>P|YM$3}!&5b6 z_hs6;=lO|wqn`Zz+ydKcX-3Mguf1TXyyYa8lY8&#YqiiDT37k#HPbJe56=DH{vjZs zXX(%nXsI1}ULfcDrzzLP|3JE^>TD5O3>jnURok_a#^j0K(qZcLIUEiMTcy-iG=|QG(2dXd6SZ1e0%?hV`&?)wWV?bpDuK6b6IQeU~ zC>!G{#|HfJW1l{vm#FE85JcznLm_X@n z&@V7;!-`qn_q$tMoFvJO^{A8Bn{Fv%1(5#KzwGhFuE0t6M0`i}MAe-W z69jcgJna=ASwTFMyzvxlIQ+V}s4c3+oh)=I4AF>_yKJ!2nYE`kL&E@d_=aH)b_wUM z5Iyx>{`-Q@<8(l(StH4v2F5O-RUEFr59JI6c*w_=Ww`J-1%RWG-V~rqOTW*R8lMw{ zoF^tIrt@mH5BMN45KypVT4SYyy4-y+4!BTcTz}`42-!4|$Rp`hG_QFqm=-Ww|!BoMb=MZA$yW^gG;C zX?si9)}?psBjbOcSm%hDU-@xKipwb+m&W_Wtf>v*qOl!`KV@Xe;E?Ji^?t_9|>Kpc#(_z&|Qbw_&x}qfaYUmo7?V3j>vR~+p&~Qzqkvj>x7dn zgtKM3sD>(A`PDy3G*e&zh4z=_R}+~&GL`)fHJhk-<T+`V$r+BeEw}A2}AzqzR9f z6fk(hN(k~k(ZN{7L?WW*k=R7x_Z@B7SXCm?!xE_!4f9#0EU9!4>YOV#3xi+7kZvy=aZ>T>yiQd1w#Cv2yW&BBqKCznh()`zt6p+_w#2ePx@o ze3#FVJ32p1_Z!#H@K4KO~vFsZ3<+H047$ zg?9A^%N%Yg3K`-9t5CE7al`K#l$KJ`8=;Cx0?nD`&9|+y`vZM-{$pa(-O6J-ry=^ex;QVFcmC8G;v0gL`)IgA`EKO z5qARb3Hz@my^CGT*~N872<^qvod26*>&5+oRsg}0>$)?LLZj=aOd*`#pE}a_VUXYZ z4olaezoj$JR7@?V;n7l5kLU(>tbRjhkzZeJJB(JfLywo7_~&n~FO6dbWE|U|$=CLL z24{EC+7}fH4R3*u7aVXK>TB(0RuN(6$ENSCO)XB5RfzekJQ3OdR$*I77c}iM;+c0U zwybRB`JM~{b)}J5#C_Q>rsr_=q!;$pb~N9?f`hRM7X$uzfVA8Ba7hZ}@&8>%{R{tA z?sGzp#Mqs;6$2Mmv*b?Ue)FefYu~$DY`N`dW-drKmDLBr5q!$d$-?dtT>=?~RXxHQ<*o?}A%5}|u!RY?3t_tvHW z#JTF4HNpip*g?IwCih*Yh^l7_DXYS-{5489gaw#iq$Z5BHdj3EM4=e_*$kZ874vGd zZYkzpUAr$gY5j;Ygi`HRVTk4A#4v;D++6Jy&VE7frip9;sVH0XqI+X{J>0a9McE9-L$yvT$?pw>^csb!G=$M+->p18)kR%wR2fgr7a^=JTT z3nexBm#>(ATy2%ClS_(DO_?idV>Qn)B(yh4mhzgcf8GYU5*jFJ^sO*|Pws;g zIhk08UCg-gVM&K_g{a!+tHxQF9l*q_*GnOoXE%eR`J^(k`S1)i&@oOmN!B>D&v=I9 z6u#eiJ3y4-meA@M45I9#Uu^^Da9r*V!v7qOR-@~>9QN_+c@^d+%=!lJg%m_TulQg! z>fElNh&bIL6;C~)r@|}eEl$iYSjIv}uyIWtlS%fm(&jb9*%~c%%qBuwvwbRIKDt|2Sn1j8^uxE)7 zJ7+@4A5C+RY26pUEAgreA${*gMjLd?Oim0(_Rc4bQFlGKzRJ*LN#5!&YuzS(DF<>% zZ5AKQ?l&Es!qkvqF6Hk+aXk3ocOTA@y~&?Hdl;es+q;AqDwCd9fYNgHv{~u=lSz)m z6Un*&gD8FsS@k<$vovoDAVVMY9K{-G97XIm>vA>!KQDkWXq$f1;OieO;%Wt&%AwfH zweMJM+sYCk#vTn3fH7WA2IJu5V$ho^ZT?Ho#lr*Sn)ai7X{Pk&gV(ME?f~M&e4a-N<$N8nw?~5PAFfd9 z9B1Q64X)YAo+3S=RvC^BD~j9O_eeVbT8{jCoU_9GiW zrn!s=?mbR)yZfZEo|*dk_iy$Axv$C3mezTS;mo^otjR6c$+a~y5kh8Hz}~4V1S_x8 zC9EezR2UNQZ&1{WFC@e?kK72rO|d-Y4VrrfCbk6W(MZEJw@OF}3-7ZcR{0UcR$ur0 z{($`(y}Fy$iaAzhrXD{qY1n7MQ#O?ayWeu|<3+;5UZ?G-U(<*ipHd_ErMK287Zlg) zJ&P|-9g9KJOI+R#hk})hr{SB|YcA2a^6D;J8R!wyQjumOa!E`@gIZ=d*B0clQkmcu zpq$wJ3r+l!e$R-L(X6r%o$rR9_B1O&*Zge-w+3UuIG(e!M?1_UFm@J#m9kZe(+d#o zN;QwTHl(t(c^~)8@DYCK%XgGM$U@0o;f#GDu%`(sEpk1MI)RNUT~|!$b4+q#gNo-6 zGnTFM&s_?Skn}DGm1LhxZK(0YgL_c|ydfhcF9!|Blu zzJy*DBbw}?mp;rW@<$PhTA%~khtX#KtUD%m5I%rdN0@5Lnts;pAHAmnJqs%f}~O*(8h}; zE6f$G~b&r{#N2ihHK|m2;H-c1F{&D?rbas+D9a(V-fP(r`lV8mO zYLFD&*{7Q`Go1I;H_jKJ2y*z@1?N(f1}(&1 zXdjPz7M#MDI=q|{%vT2MI1$R##cC}WjoAAhtm9&n^fB~&C6Pd2KihcwlNt|F+Xk<~R zb$hoG>;`_S+W1yxp}If!r!_MTvT@3J63#@GAiCk|-~SEr)m0g1T4 ztDnBw4Cq5SOM5j>(Y%In&K3~X5zXUwVc808BwOwUQCit(jjiM9NxnXol7;Fp%26!V zyS(+4ZqpZ|5c6G4u*Lq}1-3eo$Sz>>2&m)~@!FaUAs#(JyU{*JCYj z)CJ8fmmc~3&bGsj{`8!u1(crsNnCQ~10nVl_4P>X+)68~lr|aH=OoQjBEEyXTz>T| zc31B&5PMv*i@8e-FlM?7go~RQndu(0#O~RlNQZwH6R^VQ_K=^$v?A`mp8AMZ{ z9&i7Vgv!g9)*K%Xay0N468Qb5Y4sf)^+wOHff}rXL3?AvTE6Lb$Lk&1R*q1j z_259Cf{3USAsd^=sXDi@owZ#u4!uc-8g5UkGIl`>IA>y5+bt;bmGRIe4H_Ep!vFUD z1v(SmVGD}KS2B7R25v}KD7SHDN|;%HMN7QefVKKi9*_mycWAvTBE21zUTbKiS0|rn zy79vv-J~DY_rwR?{Qd5H{$my%LW|&<%3q2fyQIOzq4v$>LLP=ba!zzWvt`wjTvMFK z&-c});O~8J~~*Az`pqp@2{yaauS;)izYfD(}?1<0iO>;tN>z7lL0ei=A}2h4_m-P0YZ zA792!(m@6u)93ZYF*tZXZvK6als>{e5&ylQux?V{vgypgQcDSzg3dgT=pNA*jhldv)Sj~cfD|5~u}a2IX^lzu;q^AKly-!BMRdshPW z19t&m*-mY{`3(XYm?9gdES5M6zkqGHNZdU|)|@Y`G@3PmmAvQ*ygy@xm10T_gqmyg z0~M=Z=X`lUdYzbgryP@)Oh6rla8pIdYdt1*FdZ@+uVHmQS>hm6V_gsm&QDGb>M!8; z86=ZT&)|j6+?(w6oUu7{IyVue_xII}`%tZxQ(np&GHS~q&r^#?siR$X6JGRaM5lbq z<`~<~{Zti28bWK|l;7W4MoptGq?IUaP{ls^(v-FH@zU~JDxgO<7GiYU3BvzUeEOa$ zE$rPc46sM+(Y#z5l#Uyv_?QnJ!zI?T@&^ka8$!!2ZR(OAKj-DsD1b0* zG@asQ3=iXVUu~9}5YDkE)febi2QI*MK@b`oJHX*$nToU^Z6EWC4{)wB^eE_Lw0hV+ zGEhAxUM{~1U3Jex!@9_woDh3M$PEBX~ z*)(iXi0o^;&fO^}{!{qZ#E`fE&P?w+Ae}yN2J8B|Ei|5MBO_5}k4?rC(`?UMtvdNh zL0PJ^WAjlwloUXFvXW zsi*7!&t|v?VP!R$fPWIwkIPxLMf zaW^~;gI^Om>0>9`#t{%A2S9ZxR8D$@?33c%)K%DoYJmt|12=wnfIAiVy`6?pDp4J<3>0ou)Yt>y0i};M zbP#I9H&YOv`POE31A&6A0hPcVdurW21QF~)KoAQ9wReUbf2N6lput$@H`5LtsD`zT zv-@=YW10Widu(F0pUHPtW+A2W$F{jz-O15rj8;wWZs(uMkG>Bosvny5;d<-TpE&{iT?F?DPDiu~!=_E>xm(=0FBW3D>q79}8NG0b@fm9!ga+GWlWC%UgOSR@jg zWbj&JJB4>V`7lyF}zI8cBwK|vI`fT+l`RrowmCgq%03Omgt(MAj0)^-$@ z{8oWxAhAjTJHyp+qVg2oE!V|aR4Z_BD<(~=e5wxOzH-FW^6J?YxBl;xU?Nvg z{XpUmWzlkqCvG`n)|;774AOi>5Xx~O3Rs(c4q8O~8m@i1yNPH@Hh*?>x%sJ!=ijhX z8nKV@=Yz-aR!-KE{_sD+7jli{xA(jV31_sJ(Ee z)U6r?8%PMdmuc3yK>T0&E83~o>$4mB#-ptqg8&8KD(qrJ)Q{@sq zQlgbAbaC&1M)1$)`!PU2KK4wkOfLZnFh6L#BzC^MpiC(|NmVOmFZSD7a_)%@eB$=G zs{xP8^Wj^vZ~Fsjfp*SPB0|SNc6Y^w<%5sv$6`$Ok}c$LKQQ%i;41fa(6t7a2`K1i zE6WY)v;dW3y4sR3IjdQH+~M#Qrv>s%hT~&t%oSR^!`ZuNbvRBs0m$C_lb96p2|`+xx%v(?f3(@e)2)!D zunsJ1oLk|zclDab*!la*A?^oxCb1JVG)YZVAhy3zYC9o9c5Ir&FVSLDKxqd7k#DC4 z3ru_pp)jha!d4_-DeU?me@P(z18+m9@z@u86w;MIret&H*0+S6K*ILrH^1fAX&~)K zGu?VA=VqYlRP~T%XRjXFk(cw$e^L*pzepYFoxn=mE>+9!17lJV{`C-f+`8UQJXCs% z=onU@b1;PTh}-zJHww`gZ;U}-34%bMQ~=-h>nPm8b!Lu!XDA!*c!~dTa0|X9;kT7k zllhsS)}n0lVf*mr@u082ITUk7lzVIMiGHjK9K&d7=lLhXPZ9MdV6Hd3M9 z6dA^_q1UQOs0Su4_wd@_@>Iy9K19JtAU*;Kj#udXgNy%cg9a+0?;g;v3xfpoWlbe` zmu3z#ZU>U_9QVq-8->$j=Rbwz-!KD*kdFwddlS!JO#stOS9mVsic{K%R3R_-K7+}W zs4H4x=@W2#DcKkqPfF;*%2> z$Yx0ilp{KjleIWBXE-%7$Z`%ZG%%qElrBF6`1t)fTYyOlxJ3{{0)9NSH&mJBZKm}D zS6eLC2lzP2#!e(lqIa}<{-@+$PfSc1isTREAD1S!4oM4E-r@0Y8D|6&Z*(p&`WLiJ zZGBj0ul29*y(Pl!S=eG$V657Ahx$b}>~?(!YbMn;>`{P&QXFEWGp*<0eI=_LzbInA zL1ApkcU$`&{w~CZmI~tCwjSIl`~1F<5es)8pZCb!jlrB@if^NKsr-7O@@K`RSL3z^ zdza*T4`t-2{O{TF~UB)oD`9n2kCkF9ahtiu=_qC zo7*(b;IEtzpr_FuOLGOl(i$JNAnh;Y1N8<@F7F&76Whg_j_ySDT`SC{USX37$YnwS zs8#5``T4v5L)d%8HSxVszjjcOD5#(ak)jj}DAJ@vsRBYos#1c26agdB>qze%=@JB_ zcSMvHkluUmz4ruCXHI_qbIyDF-sU3nnLT^Y?ES3ueAjZHggfjfbi)@syO=zOn5Ivm z@iFb?Fnmnl?I^OqiZY~L4=ws0q6ZM!$nR}l>*1T2bDJg)15y*m7D&nL42i&^N83TX z?jbea&^$+9$>K!^JHEK2DrKtzqU{y!f;NvbgC|`cN_}SLm}xXGHDyaM(UT?aHYSVV z#tqbEyI%3Fz*EZ$$`4^hvhT+peF>*M0BNVPzP!*w*ysIg>Fs~w59nY^8Gk^j4&W;Z z(J@<_q_A=@weO;p|23w$8(N8papGUI64)o2$5DHAb`e3V-kw1X3j}x?^;)z_w!>S>hMta{a;i8^r+YfUtEmW@k+tpwtLUiz%8k~ z%68SYkaGcZLN;9u17%ZIOR=^#Xa(#nQs4C+>seFRe$6w5+!nKO^PM z;x+TSL~I+Wh$o8$zAHzqfpf}kuP5=JSf$zz>EAF)J-Oc$-ePO_W-j4$&F@B z|F__LB$Zd*W{x?c+Ph~`-z=Stx#ljf?^w+Hw^sbBz6x^o^v}<=FM4^?1VSE6V!W1u zM$1#T<&vO z&<$RY{1^->e(ib*zciM`U^51J)+L^Apuj&=zTSV}9%FK^RpLQ6$<=vjEuiAl;M7U; z%H07LH~e)f{G8I{5`A1dv~zz(Mj4W$6?u5?YjX z-6mxSI|p0*fk8ruzcj>pr*60jewa0&^&}(T)@0p zVH^vkFJU=0EhTK`W}7#WxT%4`yCWz+t6!V2*q1)IiwYKU;8~Yg=>|L;hh*G6Ztp;^D#LFrv+Og3ZXfi5S$;ixy9dapk>?~YgOW7c2S_;; z6S|-?LYX+AC`G`SC04Q-wkJh z{)h>C@sacC3#-R6FC8!&>UY!m7jk;F)Frj$Qw8q5MRR-1&8=Cp0Y`%f3URCA@|Y;3 zmD_v(EYT9m{}=eJt#WGJ0;#KD71VZP zNJwH*D6`$ljB_xyWf{E^*V0EvlI@}Ec%h5|3c76Q&dw`|PC=2tC;%pPP$DWXy7+P} zq)@YoqpkH1e+xq{*&9+$(hD+C?vQ^R;`ojyMCprH{2LIUn!gF7w3LZ+ygUE+KT@?8np&+w_=M`a5 zSA`&#wolUJyJBnmKz1qDTFjxlyxbyKd_(x#psc~ujoh;I<1630d}PQUV`SdkT(9H> z(t52dl*gsK_&zK*Xz1yeKvQpkmD!37M*}ep+I$%a3qLaqeW~2ufEJc#ZNO?;EtCp> z_QE5o$NCFY{tW0ZYOI0f};Psl(Lg@?3Phwntr|F45jQt|ca*Yh8wnfOKs|XlR zm;EZpQ7+d>ax2@(w%@wCma9lQzrv)$dDYwU1W;8-+r-Tl_Mz_K5S7PQxt@vrG%@3P zQUKIAqwOC|)Luki-^c(*DX=T4L*LEzXR)hyl%4+Y$~YeuUYlKN>gw)*=uPcdleyUb z?w9W_vm~eWDTm3KBmLBfh{BD>MWRBtlG8Dl&vi@e1M?53N}@qbWC|mEm5mVGmj-bU zM?d(v$eV5$2}o3ZNt2F)ok)tL!wnr9moNrw ztBp%oAp_M@{;#3G5O(9EJE)Qv=uX9}qHEG8{KRa;KPrf6*vd9`1hXdt;vy~gRs2;z zVUyIiOpq8SJLhdix-M)HFJl6v0VXgnXV0CyTHPJrZvlOYEbY>#)4Y1(-^7KC0_O`* zaolD3aUS{0hrK#Sh%KbY_0ie!;{G=P#BVXOpaEWt2h3Md8}_Y5h{EzHiLu%Cy6l8fRc?enKSby&V!6mJ9^+PoMxqf4p2i}wd? zuVwsZ=3ub~rlSyd#Q7WF?F-r-zVbiWjZRaz03=q|7FW7bXRLAH#9F-siD$kpxcNSWVs&2`%JF~mlrpdIbaDwa zcX+^Y*H{%akh|J;mx<7O{ws9<)yX}n;Mx*A_1!fB!>5br>7r+i7S&!E*skb^9Yc!evZUktSEnKex@gv|G z@~g|(gVKkCwj(^Cn_#V;$(;DwCP8K6%^JL3k&lcKkrMYtitR|n7x4cog4`3ndR5i& zfM}W>vsrcOgiJ@JX50@2NN|7@6nrVifvCF1+R4<85W3{hbF`|`mrfD!zLQ-{q?=;~ z{6+UyySJ^OtQ+Jbcg!V**1m6b8;Dh&2bxSuiP;b5dfyeYy^F_TQ=paKP=CvdQTnbz ze_yFAsIodTFql}WID6*i30=qmK(OE##{M8;0&!*C%b)T%*ReJk z!)xzzAzQrigGb-7vnCln)C^=?e)6K?57=RIJ(SZGrog(4cK()gRy26^Ho&4@I4N$) z_MeKLR)05E!qj4HVmy}u{6>_AIb1JWIza0~PoKl{n2r(ZcYwMeG|O&c8zw1h`fI%Q z-ZHa(KURGYCi;FWdjWN8aA(Yz@o4l87*?p9b>I@J?Jmd(#coF~)4T}Fb;i)_GEui6 z8_zouy^M!`jsi7(ij41m0TXBCXrogEq+#c&@HTn~SphX%e_1iG^sTNp#2qvdw0iBl zAEIf0UctPzhOYVM3$7+*Z{I`?t>>1*=BMujS83dlV9_a=_>1l=%ZvFWF&b8sBA%XN zQt`Q{=>>w5Ip_+Y$u?IH3_S)HfwN8Lw4HFfLNc(nlM|OOem~-D4RrbF@H7viG`woX zp-(0= zJr^+7UseWUFa3}vVxm1Ipp#w1E#UTPqYp^Y%aqBaC>EV^Fp5vH9m`k*Fd#x7Iq%PZ zsgL@$!S`qb^xVs zzw0QZ2d*RPDd#9C7rcliSSesNEJNvVM|e8N$%)6W(bRKyCMe^=*?z9^IBL+tmj3G= z^AZE-Yruoi%oCjm$ge_R=PT9WIdu5NBNoWSL82*1it zf!cSWwAsQfKqzbc7?t+3RIC$W{v&Pd9LP<*0)^pWckVCY&-e-L5XYe$V0r{WoV~Gx zMZdowa^vM|o3A!XH<6W5XoFGe9~f`-{-^CC zVZZapdEz&?Jwdc4{F%e%efo12bJ3ihrL-N7M&RKGEIE~+Bv2^z-B(Off*g~`v@r#)$M+c?Skfp zzglelbM17aym=Akes7sgJ$fh8?@Lu0G6OJ!$!5%#;HVcW;y0F&557l$w4R8qd*Jq{ z-23`J=p&`&udq@}1>Q5~f8Y>ti+??3x1-Ij?Yk3Ji(?4a>$af0je0fFbxa3j04(Z@ z$gCs$D=)&r*9z$k`+=IQZ~lqIxzDP%?5dVfFLUqOn(N&HX&K=MvlWMwOlWD>QF>`( zsv;Qr=#Z{Wx?99aq!o%cqMx`n0W@3JTj=B(t)@mo$viXcK#Bd1R{>4W0U}s6H8dRh zy^MWB8j7e#Pmo-Hw1KC*!p4fvT}C$2{Ua?MxyE~ii3@aG3SM0K~= zAOpAUMx$?TI-NZP`H!MxHazlKIG8O5vLtPF(8T4Ek1gXmYUU>gU-tkl<;9ubhdKA* z13#N4V}KU8Ng$Q?SY~n@`dX2AjM5^f30nMPjMIjyIf3wWHR@!bXBFssp>rK-`|B6B z7k_px(#cTb=i?;nBHx~W5hbW=&MAY7pwHOtGdwEiK80r7UU0-CM={X`$Oq6g;hiwz zrz(`Zi!EH(o*BK7-JsLNz6x(-E1XqKIUClPijIPjQTt`8^6`XwKh4`nc-Kohg#?*@ABR)!j8&hBr75x zddGNnq9|maccj#2?rxy5{MDygt)+L1j=TkXD!KrZc<2Mg#D(!*!+C5zdoT1IYeil8dg2yj%V) zDPFl(ih1y6g-^d=wIPI9Qfu&z#&EKFQ{?|>k`{4Rwn(b-UGy@ zzOW%}!|`-2k92a||%PjtzvD+4ue_SkJF3CDh*)G?wdl?>mQydY-5Py{@@ z(~h#brK4z;9x+(6HLuJ#B8t%$aK()!haNcDXZ2wDP8*y@@?0+k=jci4(Dd@`)ub|& z1FjN&y-%SCoXo-%K&kLIc*eO+-I?nO;rz&w<7?URT+e^0=R3oWyxf`&|6#NyGBFY# z@))}Jkijt&loy+o5?*It3c?;lhva!UJELa^$P6^!lP-vd{?a~ipIL1V?c{Jk$$;N|H(s(#g-OozPIRKF;qHFgWZ*LZ_tt5-Fw#uzPmpb{7wl=O2(OZbR1m?*?%iON!)r z>4kns{A2PjZ1a3C8Qv@`&Z-m5%fyLw>Dz6jRI>>>@fTx(H9pkWCC*$Am7Lr2*YLqp z^@6lf&u~Z94R`(3nbr4mlt101 zA-qQW%qfyiMqX}ehtW|otcQkQgr0X^_8L__hiZ z{R^$=aW@fsb^{AUBD$-fbdEpj@&yf_e;>MsG19U9{C2R`+(Dn(@!v(xZ2_0klyQ$= z(-u}9O?Ni@3!2s((%0M^K}=x07gp9Q`GEuJ0VjCnSz3`)I!|}wqS0QnmH`Fv`Osz< zFE&1!>F+>o=xUQnCD$5}An(&W-QC##Muz*IMI5QoX`|KB%rqYAK^d=w9B7T(he8ypH_tJyZmbY#JW$M)x z^|~65*BC6hKe-UwIMhB2(W-QIeq0}@d5QyNToKaOMy}We+(ft+mihT0DtiadE6Dlu*+wm0i^9=_06G6hlY&ir$F4B1^y=2&dN zVKBYl>_5MHDLU%sJ$jCijeR)9uQ+(0>af)tC4)MTT0mn4&NRpE^UmCJ<{reAND<7z zob9Zxmm(1WK>O^K^quE=!@AW@iKtjEeM7lexh!W9ClmBVeMtYc2x|-i0qYM3MVhe1 z&Fna?kAa>{?$6)0e;O3*I`8R1Cd128()e%@!~^PAAF&$*%pv+lRSozEG2j7dE?8Q6 zTQgmm5`S55^n~BthEqNt-FlZ=d<188)5l#(5M7s}uY;nyUq$;hINE~uV%uY4jS%== zRtrtAWLN_fA!9kn>N_8FEN{xJ?l#SQK^$cdHhx)y&)$A^@8yE1NyxhD1;`hQB_nQf!x$b9E|4x7#2-CN>E8pWpm{#IIPFdzGaX6w zkmaSsdeBqbw*?Lb=Pv|HrG_1`7&{Dr(PIOA0ldJwdY`TG62$vc;-+-xF^@IYTu+s? z$qj2j!mi&@fVBolKCa1}@GJhdM8;SRUlNQK5IbGlBy4~ z*)JHyM*(G1kD-5-RDUbqxSQW&6K)Fbd4le z_OxDRko*2pTm#ub&Mat+=T11K*9r_II0x`QvzwfGj+#F)39Qt3F{(_9B3 za_6v>(c#3#LWp3ICoO{bgTq|C*T?OCCG!Oud0Ix7{i$;fseiO4i{u4&euK9|kjsZ@ z+1+*g6a+BqF^nID=X|Q!&+`4??@~^f)SqV{f^(=*Y?p(&O&lOwX+b?*RDw|FGjJ}3 zg=7g{AB|CyNY22nu&f7putP&p!CM7yD94A}F7z@_#(Lj6?5*g3P#Op-V5NCPr%X$Y zNmyO%$Bj5}(J$=!z?htRn__C1=(W60GFI0C_&TivnvO7(;{(#gWR`Sq%xyh@ft-RN zKE++1?I?1{{a(Jx=NNj10MED32c>>-$kln`Dy)^6V7+69v;4bfasQ(_^rG-2aZ)9< zDa-fV+USzBgs*2`c6OvuBn!pX=g#h+?&3GS=6H zbd-oNB)GFu;<%Dsb*>W_JH_B787#VmZNk<-89#;@e~qi{0IxJ9c^=EpG|lqwAZ+0Z zu1|;PS$I1aAQe%XzF-EelQcO!((l$DaEI7`N>u313An$`5wa2dt@mj-f-bKix_$1R za1D;4Y0u9P3)!>*v#BiA6@R!mt2R(5O+C3*Jfb}{$g2azYQG1vw1|)}C!Wh5$gT0K zzeBGSerU>lEi+j|EkpqiPS9wE^>p7`tb*q9*$#VmF81W30Axm(Etg3+!KsDDW1t=A z0G%#hGxak?(~*eQ;XG)b3NRQ?Q!xqIfp_r8r_Kk|i0PvcI`cji8+LPjhT`!~0>O@P zDPQx}+SP=2#i}fK7Eb-!YLI;8&z_L4;gTr-F;O7sxb03K?e?$`97IpQU-%q&YMR;k+1~N& zVd_Rjv4;)brWf#}t&`*O;Q++HfT(muo=crE{l`Va0~>GHR-A4?td(JZCrM5?f|B3e z=OfN!Yry!cRMXuWE5dH=84TaQv?cd>h;ja;44a8XXfvH{OtasQ(C?DH#SfR*=3^}# zht5)w*t;*l*?{dW`%3_PB#R0?l={>7tVzOzUFPT!V$p?_!OC=3r^D_FW%D2JT7?2a zoSlgpiM4cc+JdP>dWUr=vL=S~Vf{K0D;RIF1Cwm2hu47#LX-*I(Oc0$@S&oJ!mKIF zz%OAA7KK?O-G~`09xL9PP3dd;*hHi%KCG_hN2a{z07=fe>kkx_+5f7Z^(n>IYq#L` z-ReEr;LR13R^@g7^hz4iF+rexAf}i`Hz^aeYE0oI0*hkd{)=t2ouqC1PKG9lSECuc z=V`;_!;S~^ju6(g4j0}6oT_b(#}>lr9WpoI*tB7}!QCLy#L-5ykzz!`8msPGK#gSp z{q%A#{OOpAr2&*+7$4VT&#KZ>>1rn2wf&Q7?)Vwsy@Ozgh8PLhdSIFg-!>L{cD^OE ze4PrrS=#)PEI8eeG~|6}6k=?{mV;tNh--D;%7d3V)Wlr3AyIDNQOfrF&yyutBm1Dya-$7cV(I0UpwVd>NRL8D;!Ij3Z>?!v+LEWk#04= zK)e!~w)g__kD@LnL-lc{Q!&JN@PQ%F+E$#6QgzMC+}t|a7CctEJ=IV(3y2F8;ron zlVLivfO^27me@^~H;6=JxK3{x=~A0fl(VFE!r{9Hv>RBdjiB^GF8Cg&+6>pJMGoHk zBIB0_=~Ja{P$M%e)nUu1HOP@5)^@!Wnm2LsKJ&qXguOWHv|9|asW08dMb{)$*{DH7 z*Y-=*E0+Pnbs3^0!yO7n^ofj7bP3&yy;nbX#2%TS#fZ7~8?3PjZoF=%`IjrkzXI#x zt$Mg7O}`iRbP(&CKk4s>_}=b9PTS7c4I!s$mIfj2|3{i59Ar^M@dUJCbrfX87^8qU;}((qBqcD`K$y7=;|?sbWS z!}GV9w>0Bu`*!Ov!EEubEV@FWU^W>Hcw9z?GmSe# z8OvnArU0=)I~SO9iz?kPcbQ?Jt4i67Fs$L_F>5!UZ};9l(^R$xYjKY8!JxJ2gV-8v z%fGX#EAxw*-EU;$yL{)`@rJL7$hn^~ zduf;+8!MLSvebz@*hZv?ikhZE?>=bf@>j?lEs^PVtK)(Kx3us36pwVsPtfy66@ElN zzq}U=-UvfeuzMxbmJ6%*_JpPd!3DvNb431WX5PJzQw-6pjB$w`OKVXZ+|G70gQ-Wj z4JB|CUZ}IDNo$%Lb@Fh-FG2@EF^7wNq3dAsjMj+?9V!t6DLAwwny+oUVae4{1xXj$ z;C;nN$uLRzHgAeM4TvtQx)U)tH*VlvXaDhYNL<~GH_HeXQeKZ~2iLIcL1BqX{-5S) zHBjK2sTa7@W-IfooyKHmyA_te^?b|^d23%->H83rxp*sAJ$i1aHHp3@VH9{l8SY>>rR6d>NiYAEx(o z;^odJYaGq(K+{P&Yiy{q1Q6D;M$)YYzm!pXZylk299XVzy?PJ>ny*KI=qk_-d*TxP zhZDwfafoen8)eYQzYB6)#=?)Q31@SK_;M6{Uvo>*wSYugf?5x@0S|Nmm6bCY4#K$Xs?cU7uW=a2_2NPjH%_B z6wRWgl5H}U2x4J;{04Ky8YEZ-UuX;h;7u;iW+J9aZ~DG0n#+CQwiMz!Alj8Wx58`~ zXOmZwg>e(txZbRpx(0(J7|w-sW-L$6gbjt(ZDeJ)q*r`fXC2n^jTxi3c>cOHkp8Ik67G5ZFZjJ7Kb zX-HdJwpIEeTAz1Ygm}KFGfun}q=ti(IH;VcbX9%jr{N`R}+fmAZ)S-oiYy(D1IhgY^q!N>kz z>n#^P_EFT0n6MF4-j(4q!s>ArG!fxl8#$stwF}Nj)6l#O2D1qw=TaGDLC)jAuyxLM zOnUgZY2X3E8_r|kfUgLbt!r`Y?nP)op(41pHEcSLh1G7xqz%tyJrbcMw=Gu$lww(_*!y=43L2bo1rt zEOSoxtBh|XeX!|Utrx#ri3q#X^5_is{oVV%3*ht*_$XE){q;fIZ`&l&rvhjcq+GMm zCpe4KAjCC=jigz2NZjo8jzMMF@Q)USKo)#W{XL|r6jI5(_i%w@_b|G`a$(}=}GE3=i zfs*I)86Qe!UM?$9t8f`wq;n3r{4G`N22Mr1W?Jpi)zUavxTKWh)m8pPy59RT!^L9) zlghTZ_r*T+zQaC@nNd%ly-N@0=^QIai)Sl)#wm8}nSQ$?#BNycHnn=Uj%}<+3w7+U z%9FR8)8n$C*)SMHoBY(2a=(GD6BDeElP3f6Y6fPSWk<(ogMoqo_apLC4`Q>mj%VD^ z_`OD0_6m~F!F&6AZX)GSg4{P=KnXB6r(4?LjdkDMJhg|x?8u6zA9@xwmwk@9{rS3NkjobwHMfJKn&sEU3?A4)1Iuc(d9NC@N zN+xSC_9vlk5;QHj)g55#6$R5x;=ADTwfM7(+J3K+NJrljYLd+FdSDSJ0{!{q)B`4s zVigupB<$T)Ok?Z*9?n)q>N|C}PId3MR#0t8<%bxc3$ZllqBeEp2nyC_lrO(|Z##lF zUq_F&V-De^$-7{yycaifRm0hCt)w@~vI`w6D1Bk^ThiMqQDf7&mBlks)eZL(3=+bsg1LFhj zze6;@47%jt*y_9w%^2fUPw7-&ZG!~o!)9?wW{@akL@f3I23ja`S31K?q1{dEWx@~>anG@96&%uVAdS`r@-3?C`wZ1Z8^d-ucDWP zoW1Qa?_J(^Lo*dmQN80A#+XNgHi=3ddhG!Ldrxi8dG7F0;7Y&XFwz^nP)cPt_O@Dt zja806PqbmntiSm~<Hem+*O@zQ*^k5l%?WfL)e2Z&PeQ%c<# zs{tE7$YyX9osgDyI0YqOlwmD)Cy|BVMDA#O`iVCetF!J+uY`vLs}{MvuV8zu{I)qxH1HB@IR2} zCF-x?!K?#d!ZJIgKY+u1Et9f4Rmw~)&;j=7fHc=T5S&m?&Zhy;7bo0{Q_W&RmL7Y} zU%+`m^aaM|NEK@iU?lUO4DLir{`BwVIeCx5IWTt}-m9$ISmD$2AVa<9u<7Uj&jP^a zFw-#j&4v4U=%eP}*6sA`H`WlOwT$5#;rNb?kNA2Y*hJsJvw}(c6k!j%+XWEry7sQM zb1UMRjIXVLaK-dZDESA*+59~t1w%N<_($lBaR2KX>CVIPGI+q3aSmud#+IaeP7&gq zcqqVv!|2APti7xgCKXk46016^(wl5yuvYWyRFfEmLufgmE_AnWoSjB;rAw#z7OC!_qglH{Yo4n7_I^qRj38Rp#(hZ+_g8a z9%AF`aBepIe5veTN{$R4@_LX zbb~UGe~%#u>IdogfjXB6^u^x8UKPAbjmz#AO8>2MCbU(CoC)Ycu+M!ZuF3`r{5T(V z#pn9V&C!Q3;x;wl<{m{X7g}^ zd%OsmS07{A(1Vl+(x^09)hRD0#ZUIWEL43DNQP~bd=!H!c=r3W&+*tlzVasdRM|dB z4zr4~PH<4`Y(lUQ?Vtv?eK`p`g%p1vmxIQ%hDvM z?^e^}QcF_r)B8>E-D4UWsc;8Suk2k;7p^m7W)gZ7L;sq9Y5Cz>7HM9gm&_)b&&>Z@ z!T1~38u*Q|3nyDHAQ{s9y5E1%woJk)9d$kPQCtP@2HsyLQRBpEO@bJAuCQ1bga%hu zwR_!Hg!j^Bc=N1^tACS9;pEvo=0CY$>MVf7lSZ*du-p6dwb`EA64_0NrfZD{C$lVW zQrksacf{}VCTTq@93CK@C%Wmx%Fh<1Zs>Tj6b7E^%ys#>QpVFUB%yB2Bp3Rm^ZuD@ zDQZ6;Jkl-6^6Jf72uB0PV4LK0(MnZfvyYt+1+zW@xaqXa7 zSFkEI!u#oF2RjoKqiT9ehzF#ZGv%&b0(L$}rhk3i#B}Dv_m7YXo57J~VPsiR*Gi)0 z8@|f7zdJv8F!68}H)ZxDmh^4n(LxQ*-hyU9n^Az0ci`=pb5EWSlW)8hzRwUwbFs#f zDa%->EF{0tX)35!ZGldapfu}7lVI|v3AdJa7Q%GoTCtjxMwalS2>$1{`yRS~S?k0L zGD`ews%hEM?17>YAEN+2;$gAXc>C;Eoyaf2hC^6d|4U{-l!%rAgzy#%9{Klr8~YL* z`o@#;V+|p`6HGH^ja3fqLe@5r&**UM~i4G!439 z_|3%lJa#A9KRd}bGHT7Zd-3qL#*VJpR;;0mp@KN(w{3*2e5JM46E#EOA5S%|e5+Cc z@V^F|MuIAoL}-2%{+lwgM+vPdUSoeQ{Z;|tZb#$8#Z*$UwxCD5YCg(yP*4|p0Qda) zl!_a~uVk}e*P4gjptaiJar4wLsXi0FlMkP1&0Z}ZP7?q06037%m?K22kY_#(E3!5! z@X6@oVRr{l{Z2w8xIZNvReVV~ZxL?*J$dA|dQ^8Ojyo35-R;bb!&3NWP92|^HPhA3 zUQ}~8$56+f-1?AbHwY>8tzLY`)Idw{yl7M((O;amnsOXAoMG_g5g24~)nWx?)A=FO5Dp@+>36yjBf zJt&>U)2*c@gHSA8rXw9HW>&axDaJhIJTSmXPL2n^gRIF5Im*AhkRGI+jRN8Qk?c4M zlJpH*PP+<;$#F5@#1^Vk%Q@|z41KsBgbcf-FGyU*S_zmFuYYVYh3VD0)- zccDKc`Ecodoh$6Zt=`mQ(PIP+ik1dTN6MF(?G-R2J$(<>zp8eHluSfR1#&qT-Eq** zC)_sA{PfhoWmoZy(leX_5C2juL*(!7v$cEe!L6CR>E)skE{2&DS_|gFhQOBQ0*IjQ zYU`r(YiXI(+V)Bmxy>(AdEoOKZ-2sAX+D=z3t6ie|0Vb_%GDC`q*C`vBebiX<_4>J zXuTR@Vf@FAe{;y2y>sRUkh)Z^&IQ&3qgaY6#p)RP?F^kqis{Yq)cAMDpHUUidTZT> zyJ=R(?>+4OC~n>ty&GbE?()9k+>RV>}6&U#GJ}_)5xr*rFH8FYnH}3x91h(v87vqtYHDE&%lLz85 zcH=?Bwj~NB?bOOxQOuqW;8hcX8FWH5o29H%>$DYJCf>Sj-F-HKJ+xo`a|Je1yK8S*_X zQY`Lxp(VIh-C*W&_d2ALXGoLc9ABZDDihAZvsVBeQZ95`!;E!IO9kHQN&*g>1+_4L z4tqBCBLH`Nfw{CQ-fSMrV_tBskth7}|9cl(y#g8CqRY@)&|tn3b%uNiFt%NV2&yrc z1|CWEmo;?rKxL;lt+Sv8^rg$XZN6m0UgqQj}@~FPd8x zs8nfGl~Oc(4(%<@uyt8M8OQ6kHCwk}sh>$)Y#pzXV%6x7#%gn&-Y?-IgR!)ar-;R) zo~(WNx~7;^EP>mGEEqfdEVv_Zm3HziQYG;WmVx^upM-!YV~fqk=tCME@p~F_nPxS+blCr)4zR|~$KmF>q5~K5n{9 zgFATOW#mCsc8e&;zK~5+x%|nXl$R3WmF$g2CilqjouC?O)(%3#HUmKhi|u)DmER8Q ziW|j#*8?kZFf7ct-xOppp{qwD_5O+0$ zVLkTVA*^9<(;_4ZS^z86o>J=pLC@PR^ytfm^PQO`Gu7lI=_Unors7M4suWz~Fh zHzU%&#N&!15r6eI@W{YiRRTFIm6d5%Osy6YUIbe?=H$%XxqZ)%{26^Sqx?M4Fv{i1 zCFRtWddr4bZxP8)a(Go61zgQfUyNJ-eqBTgwP^aZ zN@*hGe*Re!u)A5OZUW_FTUJ-I`mn1-Zd%~5dp-ZTkXx$PZxr|qX3OAnhwm8?FHmzi z8QpUtM4qMYav-c6kwD)nc0y_k~05}P)PaAYi?hc)7M{Mz0Yo1^T zq@AqRb3R+W2=5reqRFr@(pB)dK8)6%S^4Q3v(u=-c9RiE1J;$Mt~YETo;1v=B&>Wt zagpy$S=;R|wt0VY=821xRaQUslPm!(T?JN~Fvf6`u**KpfA54aj09;mD_rV@FYmJA z6~NfsPLxKQSWs1)@wB+MHLt=KPja!m0DZK$Y|3@{5YyuI(fwi+lo{G)UNGzYrGxgG z*g@n%OrNu^oN;V&OwU-2INBY1mC$qsU{n*MBK$2*o1Ef2mmD1z6&IpWG}amHs7m_~ zV|{yR3o-PDzW`+H;YHbPgoUh$GER2|5V|1fZc*!(-Xu@^U(ZOlla`aCpTGL~*I-;n zhsRAC3U2hC_Lel4@%q;pvYz>Z(H}TGeO5N^)>Wtq^1FoNS}qph&<+dtYOsA6M1%g^ zwOA5Uz-SZqW@7QHj}3v&gNWvned#HDk%3W+QT+KJ7WsRE(j^X8NMMiT(jlc>1L?-@wtIicPrZabz`UZ`G+k*H0I|z&jWB5sM zLJXpxxj~dC19Ae6e{N*J$rku)1gRZ~)f5wjo4O3@Y7Y>X#9`kncCZk*!Qwg3l2=~0 zutgIcQrJ9E4DfTDP@V#y~BnxR6WW53w>tN3(VF{+O z;dNXyUqMGAtm;ay3hEqFm`4F=DE#ST^5iwxu0rh@J^zQ-y4#>9q_bN6$sg`;@kc2} z+ljW!j&0I*dM$|Af2}C)ePz!X`|+U4yL&7uH}EMF4A9Br`h^+#5X9;Rqaec_1e7!E%%S)Rf^LYY@EO-#%(@e zP~48|=K){s+rBX8b0h_Ao{&_{|ACnkd8swvNCHz-te%j^>+WA)96 zCi!EwsY+%+%HnW(abQ@&)7<|nZkn~_f4J!naR@}R+un7ln$?!)nsX81MXIpfe!fVy z7GcYKrz3&A;!UB`E2tgYHp+k9c;^^T4?qo_m=n*S?lV)I;Ri78NY_jkF5cH2S2U%6 zHpa_aOXpx+|AT}J?1cuA5jqjy^y-LIWWjC$xo{i%gu-fm^D~F5z(N1d3eyE;>6~9Q z)U$p>oEXC12Vx3Zm}JAnAJyDC{C}7_^JpmF`281^L{XAtnS^BDcNuFE zQrW2{A<34=&Xc8(eG8#UvSwc*+mJ0}&z2bbzMElY%slsZKHu;8o%8$CIsTY)&ph}2 z-0$nUUKgs2rB=u3N{kIP03h?G?f;%Vn*LY~kGKTE_zICurPTi;PJbE>v9PzSE!U!v zzfn5++lG4w z25=g5Jl^|L8YHJ?&ImF-I6z|O&sp+ZpbUW>WXnk#x9?n({k}^)%0o5=3>QzcQ38qY7v<&-{+K2EN=A0MDQS_eap@i=v^TRFaB{hEcce0)7%s zv4H=D?d*%nY{Xq!Mh6fi&Dp=M=QAtySKMa01tQmDLl&TwJvOTUQsvxTphL7z(}RzN zmS58o=H=%d+$I{T>>cyeST^Fmu(|6>NPsQfKWfK(3#_${@U0y`Q zdANan4$SV-3+!|N)w}!e-jpBJ4w#81+v1nx!7V&R+|L5P<<+S7G5R{6YMI*T~42 znn%{_$Q+~tpaSrtaDpuF#7NY`KYbr^qfB_H3k9_{tW0kFt09`9d)fzDt=dV_1J(^P z`-Up~r#=N^iCx(9dR#hBahM>jUhwh9?fP!K;R=FEnks?5*tt<6?FRi{pG+?``LiGw zZoQ}__Puw4zM+drV<3fYB8NWI`LaSjYjm@;mRw!UmBM_@7Mel@Z9k(Y8G@Bg+h^X0 zWHT2RjeY*;pr6})h4LBLAP>X~rTY}JNd;pRkJpPPX2zI3VUR^CAA=*;uwW8G-Q0~Z z%zsQNG*i6vu1ok}qW~WCqRg*txAedgDY`#Z4v2BKRt6;zLp2A zQhNBuj1+1s&?G)5{j*_a6{VeKRqv$R8+C!cxR>uE z^IX;D6oy<+QUes>5G~2DY_;-aorh`x$k;&!b6`7T<~RMOm5X0sbJ*;qs*R&sU(|eo z98@C9pjT~}gnq4;*P!z_J!EchJaVr~9Dr?gT!so~cx%myiBw#DYQ?9(L!CcEgsE-Zol zJEc^8rz+Mi2?>QtC;}?^&TJ;^^g&4WeORj*j~+uTGKbAmf8K0+V`M{=3yJyh&8Mv| z{+1U>lAucNmi$MpU89J1&kmOmcVw_o>h*mo*CgncO&|%q8x~kp4{R>hQ~|*fu!KiE zck%$bXELjlDnCBRCbL}Rngsq=#1m%5J~!=ArSj=LH1$W2hHXTcns+sq`dpXNzszp z{F5p@WccY!#K1!I0eCk%x{S?TC>2NZDH>tNgqke=X(*Gn+s;Shq)%j1WF4T)K`4#S zHumJm9DzxhrQ9jdf@m8VnT?7o;gu)^Sp zBL?!=hd1}x`-=jXYp|A-bQD?Mn|XU`1nE5uj421(D;2gg(cx9&dQ7wqKDZ>!#DUzL5 z-L_X31g)GrNXBr z0GVGa9ar#K^UJnpYL1Eo+*M0Ayr;bv+w|kvRi4gAgPg1T9W}+s;$eoJ)x9aU|7=5-&yG z{enzS=ji{;WeTC*csnewc|W=imy*)f3$r^_uT2M+HhS+*Z)N`bMn!o_WYMHH?f*jY zbo#8Ea4&LkiN9`WhaU&=ipyxh`Ik=)P6w>|;=tbyT^;KvSZaqfy@_TLtdMJma zBV=69r9-6jHl{4)N)qg)1@8}Fux(a{+&&9h_!s|D>UMrYPdXS8pb>i%Fml+qqCFCT z#+26Ki(M=IIpyU+)~Gia{BYKd!ozd<8~u|L8P5FY-%^?15224G=hLHxmT*i4U&`lp z4Bu7a-_h{B>OaY4*LNHYfh!JNZ0Zm~HK*RSKQi--cL;^6Zqa!ph=a(C(j&XeIL~4E zNk4;V&ty8Pf!j`PsH+!u>U-s*kaW#{F;N~FND84YEp)n)=taebE5C9rdQOiJgiX~3#Ir3r zSgOuto1{sNFmZHWFS=rQKQl9#eJ!iVq3X7>hK%m=SL?;a`|S@*<;s*yV-lVZ(URD< z{+cxIXKoj5K{G*X(rDNNf7TH4#b0hn7JoZ)o*i@W4O3{i{^|9og(;_9IE2$d88t4+ zmR6J7kathsvDNQ{wx=6e!8Jb4wDU5l#&5sKbgSIuS1+L>u$+%kE|9%@0kI(OZJV%c z=a3|t1o=q^r7vAPntyY4M`kN#zJFG5peDRr=2eST2LH4*5zPYmF>oG2MP>{4sHj5%o_MDIp;L(0?LzXZS(~A zVtpdf{u6CLpy$?U7k_t`VbaBbEld(y>;=~3)du^0RQZGHD!@NRw!*--wvG|<9;YvC z{@SM&OSo*`XAwQrO2qGpDrgLN{l zEK_D7Y1lOZD)?FnN%X@IKQgh{2=O!=&INHmHmiU|4 z{hJD-hsxsQJWy4~DxOZ52~#zHM6FwVS~~NRg@ktIt9Gxc6$P64>@+slMKyKwJe$Fb z7A*w(LC``RAy?6)bOEEGGVDN_swLEbG zEgK2-MJprb-|l@zuEV6czbt#^%@r4acEni|wH=aPheI)9@2XD|>CXHVI8FU4TKM4- z4Gy{vQ)lV26*8blD`=AX#=Cmo$p5yyZ-pb@y~le$JcBW%Qt8VVLe#rw9M0SRShfm2 zn|*yg!f5@J$rtV;+;8KtzOkpR+{6vWtfKz?%XGt6W)lV=5$nxv*G>htoo=4B3tL_7fx~M?uzTU z?Hk;-H(JG1z9wnTtOef+vR;!_saGVr#x&{uAKmaJX=@4kg3}LCMM~-^}2b?n77~=7F5Z~jVpM>)f1fDUXS1e z;S!`9XcXC7W@7fR(Nl6b=#>4v==WH|lU3i$;I=anUF$t1NIE#9YAy2@y6m1M{h@6T zC&WRnARzag5)g|>EuvA2L5&WPifC){|3ear4nK@}HVvFMVWT3H4dec>E5TfH4=^7+p9JVC>-@iA8jm)uyiJLp4~(zdvB{HOW&$C>fdT7 zc?lmOcbT@x+-HtcM_GFHa2B7aQ$7&-gu_sWGJoYC&W2=D(qOK-iRsVOyZ2{$uRpb5 zwz@-ZRX!Wa_3wKgJ)1QwUV>!vEh{6I+V5|}Jz}GHNV=zbZRfs<)vUXHUI}D-va~oQ zRrIytA`YWMA7+D~721X>J*@W-%h=Zh0XGSrUHxe=@fTk9n7DGzm&PPgJ5Wss-5Gtt z;MW&}9BRUh>FFaK5e;S4o8jMz8)mv6tF%Zit0{dhXz)G0mZZmGb;4Y;(5krNY-{DK z2p*ZC?KALYx{_vlqT0uRc#OElW}O=qsS?gT9n!vLAZF6eaf}@cuS0O{{&V2N(xgV& zZ@;7P=RwMqEcCNe!&BM=*v5VG+UZNrG7|4Lmk>`yQMq6`0v4g|gG^FUx@dKu`=2w~ zhvlU{OQ#Z3iiTpt-IZ~6a8SuXFZ?vI8J|Lq5N*5u+sTpSwUb*jTj^e9ec-f@Rc#C? zm9eSJYAFKx*$n=49hk}2a@!L`dxl{v$NEf4?DuYSi9+PcjYH%^AS7YXm;+h@&${Ra zMz|{GHNAKgmA{bVdSKYYM;B6#QCvZLXwtQcbs>DEo)eXUH3xmlvEMU87GfND*NF|o zBiA*JUpMEtyMaJylPQe$6b*biUbB2{`T0+HR*%jZB$5q<)R-2<)!kw71;iSsyZtlw zB)1Ao#EP_iTyhxb714lf~E9>dN%Hlm%e-*_1}b(x`LaKF-=Gx;D`ga_@< zqI~UIZt26_HeyZScrcWob?3texRNPJOEQtMasV3nhAMX1e6pFXnNV3aPFybCYOMKB z{VwdJnr9XxplIYd zqXonr$v$vV`gKe5nWF*reYPriA-&DDIku=0E;gofZL0q3X94$GE?&P@Bvj#T6<|O145V~&}M{y5S4T1vvVf*Di`+0aLEJyhvv={cF0om}7 zq|?WIi4Q7B74N=7;T?2Bx8@phdH_^^m&27&5=z*&`{ZrvaiEx~wlC`Uts$bV{*HuN zJ+Y0(17G`?lOS9qCa{VqYsk4b^e za4V@%z3T3rIhn?a7ZzNcX;0j_gI(GRBNF0an%%I+v!b4}GADcxJ1I17%La?Hh|SjE z)l08(9-BVnS9E@D-14#iKDcc*?{*~pS4B<}>utpe90{Q%C+}U*>tKszjLbzBFb1iT z<;l>}4=o=b0=3%8-a6>u{6vwcjYj0>r)R0+A$yvf8#R2i@Q)4%3!}qeH~9EiM#weB z_mG6>sN3l#UQd-JsvYJb;KHHYUl1g|n$308aQ{5}L#&HzzcHZWWC|vN@q*7g+9fM2 zF1?C1mkry3-Y{g{mqAk#m0C~GJ2#sx*HPz>3;qg`dy3|qnLgv=-}7Td!1~7ti(g;Q z-FaYJ)cz#EB5nC<#gK<>u!$DdDrQgMs^ITo(0dl@iaugubT8WzCmJFcF5|JXUZ)Sl zM^et?P_P;N8;GKv*;al_qV_w4zdh=|ImZ7nLpFLEKIIIWuM)y497{ZGPmeR>s9R&e zfQ;%(*zL9DE9zdXPst+>`<~uvDGF|Sa3v@tXE>go{oJHaWBACa_Op+{`L3MLu5c>B zkh+_7Q$yT`Xm9twD=Zdglys+uqPx(cgleI=;Pbi$X&va2o07avmwYlB!nyXB{DHGH zPF>}#91aZX7#cI(B;0%5VPUUdO*K_MK_Ei?FTd6(NfM)tw@H-)o%lSk+hthz$%A)m zc3_Ku;7aSO)h8tLck7D2EWdZ+<+0;a;E(X|1%7q6q1j0vEqAM1(2@+roi0ojM#tmp&%z)fLr3rz+u0i zatP@*OzoQ;nxe>aY;?*1InUlNfxP`1Kd?YbsTjO6^0w`{@;VrL6P zIHZeLF6;i~|Henx%wM|3YshA59FnXcWZH%ZnNukLl2rWkg9WXah~mYQ&)A&ZnSLmQ zo3p4(N2_^!eP?(0yUdg~;F=^v4iY|O%22t9qk&X$>X~h2^G920v^H&ho6l8bvmyV) zREJ`!HpsQyh`VFRJGgpp>7#yn8uawU@X9xlQK3Rgq6*=>>~0hqp0@Pt1;~k)f8x1A z#H%{~5>XSYqtcUo(A$F|GbRpkJ4Jv;re3_EG-LbGHwJe$nFbP~fBmIdjQ7UnM_)cn zqKS$iR5;cCI zY;pnHGhHJ_eY>KTGS(v-<<@jT2Im>Wj|rH5ddWhnIZQWXPXP8VbJ&ApJ)ZVZF*{4t z(wAycfbbn*x_|5$Z{n%k1b=h0-;9E?%aCCO>1&ImYskIzO3#X>(yK`ASxH%Yf& zW7)Q{mA*ddYF`BmpK2<7XY`m%0Ukr~a(6VZojRxo#Y)Qsh9#eNahPRI3r>pIEVd40 z?bE`CvsvAzBR_y}jDdnP5fl(?z;C*m%a?ed1NKY3M~BpBY8%=)-q|sVX7XRnT5CE| z-S(k;1bN-q(8p6$MEE!HS#dpvx;oo+bmFdIkkUm5pQ#lRTU)Owm1%4};dF!^F8{r2 z|IOPc)L}~TrCg?o$OB^1HN_j zZqp>sTQlIDf80rET9fDx&a7V#*H{-S%pbgs{9)E=Uh(`il%Hgjpzq5A)!$i|*IuY& z6}r?t@($)w49q)wx-DY8grQHi=Y0#_5@d;RV!W?vGAg)D2W$7lZVbY*^d}W6sg-ec zwCBDKc3mK0A1Uwt_?K?r_-p?D&E~NIauKQiha4MayOhU(orKDg3NRtoEFrrPN;B)(LQuNl_a?a0!Xcd)Mp#Gk zm%V^g?d!8#s=x#ePFy;f&8B)mq?)!fV)w&-smB?Cd=Cydljg^A#*{M5l1CMQuyT-N7KRCADi#VIkoqEr#l<^=yq;E z+*KVO8cNFfWiihAI+x}DO7>jE51YGleACUlaeobcM(HbvkM;jbv}y1;TO{jxR97Qg zN}y?2EE@nNt4zI64p!#B4EgxZW@M@VqHsEL-&aLutdfjbcf_1x+6frfnjOPJxVhn8 z7O)a_@6`J0J@Acu_BiQA6MZ!1^3j!Fn(j%3La^Qt21{lG6;zl}KnbxBxo@&Z_h=lE zd*$^v2mj#xZ8S)vItr2CeE!L(lltUg6k%kk9;Q|VI+jPE+7nYjz(Bce{6kfWGTKFT z-w*BZ_~`GL9BPjrdNBx_IqD0pyR~IGZQ&qL>hV$F*n&Jgw1z-%1KvDXfy+XCv%qJ`4)71(`>Esyh_> zNB&;3&2HA0u0sX#Ck_cHXFr18+oK+d#zXWzeniJ%P4R{v3R4Fk%jfQE#dz_gd%mF| zfsIT7OJqmnyKdZ+WW=}I>kYi-Rdc*TjVTuE81D>T(8uzcMI~kwc!Xmb{&K56(whEq`jm72h0I-FNCRnF}z+zo=^MG@|MvOYMySr z1(V8iDL5pja~{1fgZ*iL;|wR4$o7A0>NG@R;w~gR!}FX^T(Kp4OeZeo0ds}{?rS13 z;K{#vYvSQ+c21E_btH$n)XyO8^bP3gt(mk@fx}xmSg7K47K_+Qr^013fOvj^@fywN zP?OJ_l@jYuvwEM6<|h)v&_#{=J(vb!CWJ5j_@7q(ylKUxbg#IUe)kYUqx~oU!{d~W zXQ&dWo<8OF<4jM5U(F%Xz6zUuv-xJ7QT8fOOx3e+L{yrQYY6;XRvq&{s64opB_4qP zmTnd}$X4C;S|3Gb4QnEb-xmI%MXD;esnYCqF=!?nuPn zsw>Yf=v-VrRdainj6I@Y9aTdh6eAJqL+7vFkF#1(m^M|%9x%;)!2*)}6bQR_t{$-P z&K*;1v$_d|3D6huC@;C6j1nOX2i29^QCqHB1Xi=JEDLU)^iR5d@qVeHPR`>m~%AdnZWA~&$!Y9Y%-u7s4{SPV44)_$LE_2F^kSU8brQc z6RZDq!#=EkWp2q*p|ymJdN;C!c%<(^>UdfMdnGr~*B>)GNe!8b2q#ao!hD1B0Y^8_ zN|x+HD8lwDN+-vRS*dENiB=J^pE!B=HKRtsw)#^6x#gm@H}!nb&s_Em5}HK>uxFBIQJyxJUU5LH{%4*aii7a{-jb1 zAb>3oJ9Hw90QQa(f0-?AUV&?;$LrwQziT_>fxS|kW|6=l#snVTho)A+`M#&^XFYVF zw*%)Vh(iJ}fj8tdwSHkJ)|Gm2yaJ1wWkE%p%aPzrwvKJ*Z?KL!^o{Z@C5~bCl^w?r zNXn{VM0TlnucO>!XmgLmLg$u%$6h6{l?-mgKFsikbBYtu20yQo*=QdsQFy5E6$_{{ z?Z|pIL%<2R?{?*-GkA0OoXah8Zv+xmumKVFTluv>c4g$;9oUm6O~6%h!b@S}nVEm! zZaligP5IRP3_9cop6vDViMY>fDm(Y08JhW77SxUxSbd|w;&ms}7%r$!ZcAFgcJNDA z=n-qSfZiarsoH7-+OZZWloRLan?e zI=LV3noGjYE}}@_&jjNxGT<;h<7O*fO4WJsbo~(j*71Nh;T18vY$j}OSJZQuZah>H zXht|*!)tD*@EinEKT9_PEL^C5C3l2XubvxON~hz$#BF>C>4u`gE% zaR0M849gKPhx%4Yj)!}B_J?X-^U%anA?Pw^=4}1-L?hZv>cL*>5u%|>X`my`oRGt* z`bZ;7SupnXH(f_%-h_w8!)%VT`uU46OQPj$!&OB(X-c0=R(yBL*EaelcW66>7%Df~ zQMOah-7ppX@?~h76Z*J$aTjxc1>(l!G3$o7zZHIbNYbgRaE@i#QERnKEre^xOp1?2 zGG}+$MrpgDWt<*Bt?i3YO4nJSFS;-e^Q7+f-`s#hlE8&smcipI>F~gJ=1W?bi_VWA zj~me1pO{g|?2{iooA2Ye!oRXz9KAmOjx7gka8`vDKJ!dnBb)8H>jSG#3C!lqAYxgn zoF04xgw8I6r)Eymz`Y36gPbPv1e6^y%3Z;*PIw zEkj+amyh~ifq1)h8jY$GfNc!%tJSMBhG$)S@BXS6(5y;>JCzLV zUwctn>ihSZq9vpMN(qI(6XyI7iF@`vBJn=p5HWWH+O*ZISqh$ZcN9m&sG(|n)lmo3WSk6Sv? z3|-2nYMdfMJ_w2Tfqa}cgzxXi6BYcaR~3OYr* z*A|B+AKSky?;|)I&v5~o{ia^bn8eDhk!Q1!-GOFek+?Ue_+(XuLF5FJol7BMzn5(; z40*n#T}Som#fr5^$lxZG^Uw2FKH&bN0kZvz#=<{}s9i4x`OltD0rkE+xx+O{!bHYW z?LI4SDLdP^M%VUIMXbsSS?`EF5%4Nmq$?`DABaN=!W+V*CrYnu=CB*L@uMgQ zgK9@JKbU~GsmFe>k*bnnu zMzqB;UA|NWU#kBzBIVSAS+%Z)e%9K8&M=J+zoBFd6>Ge9u#lwkyI~2_cIm?WF4P9O zV*YXD%*u|v4mp$E{?ge30b}QFHlcw_!1V_RmJXk$Eue1Ai4w80q2E)Xvy-nWM?0l~ zwL~V&EXPMzQm$(-r~U_A9=}?9(9*8mS20E zhceDx7}`cYJCg455(FoF98)eD|enIo75H% zpJ7QJG%X297Vi5O$0+pS+d6VCt4s2YLwk@zv&AN4Qt(Q(%<>(qh^2a&jF+*)c{{lS zZ%&_aTU=vknmfJ!u@3xjA)id#yS8QB<)skyWGwQP=NegAfOb!ONckUl!f>kVzL=Pb zA1{J^@m0oy#di~kv&NF&ji2{KvtmzlTvAFAv`f&ljizH!k$&-$#dPvk;t4ShbH{e= zp^qhZ^?s;(EVi9ryx{n@;X=E4wr0S4a6F<1nP1THN!Xv*Dqud6T%U1fjk6%ZBKL)czzI`J%hlXPWc4E7J0*9%v zpS_330rkgrjG6bBISW?xeZ6kvw8S6l5h5mNb(;Z`7+YO*6-(wSoiK+ zY`XR_>aA*rHHn&xDNDP#{EQP8cqvME`QB39!wPzsTC#E`?BpKmX`L340}LmE9Dz?U zS@rZAvX=F!{PPOO!3XGq-~VF)@V*s}D!Khp_HY~0Vw=DGzA4mVmFYb)&)#bLpcFEJ zmzv*IA-hoARo%#k6}SrXtEv7)e`0>L^{GFO*c`*iV?an?%>?-MJwzCNC^6XR_)a}oaO&q<{IBnz5Cny0$v{UbfGeI%Tykp)${=*& z#RKmgUgMr~ELbrw!94#uk(;!rcHfx76qFCkSA{$$1mAHx_+Hq|lQOQTNkqq4$m61G zo*J-k#J&S@Lxbdf9#w|#@SnUU2ON)6+x6aNsnp+Ri&VSWmoGTJmZ7+mLN>qmN;Ll-Z#Z?B^?_gp~_r)*nfrs@xxx{5mKt{_zm9h^>lj>TT9>*PpO3P5_9zHlQ)LfW7bjiWCu`b0 zmI8l56L($r(OsmrBWme^#I=n?4NwVoO{^rr0+9_T8(QR^bGP3fmUR<#fU^Q0XtMJ? z`snn_lJ$PNrFTyeLr)TP0D2an)jc#f*bdwV{~or-GCg0Jr8c<;d_7m|>GmyGI{#q% zxiO%-S_tyw%zw#21X5TBizuyp$D)rZ;-Hh|OO7Rv(Pr%BL0!pn9t~0PJHJz7?BVM2 zrFAr?aL=B(#m{?-h*wjMusvCw_W=FxD8m+Lrp=Oz{5oqv+mbq>tBB474p;$=httFU z3#|y3z_mP8K3v3qArmk8u}}4*{{4skvE781SaGmcDuW?JV#dh@;_%bc?_SASOa)GE z_F{dv{nC3<#O0BP?#MCnoH*sdz9Z(qu@_6=046*=^C(Dn4E@p*L5^&RCnCZwWv}(Y z2EIRllh+q9^AGPat8HbZymdp~L?l+NuQZ=pzASbVmT3wNr93#3g^Y6dRauXfxfkVf zg;cs8tLnsKNkG}~5T0a5`J|N)QjS^rKKQRO!P7odDwgP#vRCsXMTfx%2l5DS1>Drc zUP6Q`+e`?E67T%X92nA9?Htmz;%-L9EEs;wUc{cVuT#7M+yH_!;tT&QdNxeyS5>Sq zdtArT*~{;)|J#ba-t_SAL&XaZ+`mbFc^>UfjG$Hh-27Q!Gwn^y08wB1YU1AQTB~v; zr2KO$>p|5s7p=tI0{@A})DC$i(RHBF^m==_|KfCg_%s49te#%%FVEe55$9Gm^uL7( zk5;g(1~=NGjGb)*hM4+9rzJtsP5hs)q3ONF*z3bBAzjyH)T_eq$9j zGLio7U7I1v9f4C&KTsWfIgk*M<%2>vYQU%c86|eK+!)x}lX)lD@5x zMtd?Wbnx4Z9HFsdNQItvR$~;<0o8b{N8AlF3X76(nB5B2cmb@?eRBEKNNRWlg4Z4Z z;%a_~-`0zD@ymBeQEh`HbbIFCabGv}@cT3sF_`!d+7s<@T1L(dpP3&3W(|7` z)uZ(P*rBWxhuT_r|D^Z5?eCK=m4i0pa<6QuOGsHOh1ZsZG1pYn)_-~g8u|6-#l(g0 z=lJ~+rNG$)I{!*5P;J{E<)AGHeR#($mPU9Zes-mpXUx&rqlOj5@?+@ZXr|(cW!$O*y9^A2z6Av-_7LFUaad$5xS+dgCb4``{ z5*}e4DmmjSHGH0~r=3tiHkZ0ibbK13`ZHHSic2ROy3AIt)JvD(WIH?tc~kYu3uZy& zUprpE*$r5snDi}~4#USCwh$*%h;E?#9Ut7X%H|Mb_^b7vMqi5q{d?;M&)8SlYwomj1kb4dEpqR)c zkc;p9aD*7bcD7wBs+J6{smZJ?=A8m%s!LPh#GhS1`Z28p=uW%c9KkAriv@Pd))(YL zia#snro@s_QGUlrLFWfgUnETdwaWx#H^uBthyqT4e79}%#EK8?Yd*KwLF`4P5M zLy*UTJ`P2W(uSL5{Hw`Qdkvtq3=h)<+o0=Izpug!9-3R{9VMjqpgDVyJ^7cfJ@&7h zgzIZzTj8Xc?pJP{(V(85TFEZcX}*j}y}FS3QbIiW`0s>UnNm*idc}=s+4D!k&qLVk zwe1uX1nA%Vc0iIbEXWsgmxINy=7BB99A!2#OKo;4q(7%L_vDAl&p28=Az0&hSk#>$ z?qinP;x$pPb=o#`pZl39v4o9qOXaxiAU8;r(Y-OsS+REy4hdiHHNn=6A(KHwY$$wO zHOukPeiLTFo_n$Ps=(kL+yY*AA3rr+1D^~SY`31kML^HT-&0!L27pTi*frDg*71J( zY2r!@EPd{=jHJo4Wy0{-BI&s$SCYeO?Eq-AXop)GW?`(V zQ$Geji~viHw^?oOl5sj{t;8ZWH8kw|x?Ir{hW#rylJfr-=3j0{0~r$gR8o-UnLC$@%*j3n#nAQ+!4&J+fyf4}XGA@)5IZaJ_vK zE2UaYo@(gb%LtA)e%Gg?haH=XTts#`vL3&){hT7ajA`WBfNtMBs~zzZJh>qUB-9_h zh^;Px>UO{h;&WmRzl0cR54v1m5W%Ih4kZlLoR`Hkioy#0ho}aLUu7b2`)=?e6ZM!P zqZ~C#De5=n=fAS&;5+@WM0nN?qZO#xd%W)#yu^LKz$2b2z_eN3-Yq11^lD%O7 zcQ`e|j=_)Lle?V9F{UFW`+5r~bH-no9pnNW+tE%N(oxd|+fN=Ds_Pk>o!j4qY(;RW z)#HmuQ_?y5uw`qXJ+@OSzf>8Hc(1()3FqW~U;UV-;zp~k36S#5MnO@=Fx51p=6-3+ zqh}qJ^2z(kSRj%1#wpHkFg-m@yo7q!(t+6~GD%lq?uoZjLvenyZwyJNqkaz2blpQ* zUBF5A&z(>|Gu)&WLxIaJ(By}GdNm7E3v5w0|E#dY@=5pt@r!5Rh?~GTaNK%{WcYz@ z2}Rh4ksbH@peuhb9imsJ614si=vA$xYa-&>GP^znE8Wl5lByOBfU}50Bat?97AM<$sFL zX`E}zL9VS>Gz63~{+L_?R{NOZ1-<W>!Pfi-q^s)cW`T^9*X}litAdp+b&6TMpP?(!&GAs>DEAQknc*iNt z0+f>2m)!oM>fnoC%o@~)M)xjU;>W1LDPq(jx~D|+yqO94Bp**n&;VcJ$Hze{%FBL9pcr)k5CZN?u>L9qsvEudnZ22S0MjE1B;v0suPqr z5=Jo~P%&!(eVB7i-x3T_!p<$AgXr_$dt2^}HOr3x1Hv)|8t+=$XZyGQ%YU40)sayi z3&x!>-Y-wtuRfI5uwulPrR?r5bKWq^Q&T$aP_DqBM{gUB(Y4{mF zZDe=RUxeq4BmIX7i>(^C59>u-v8HCLv|%(2YDG8p))MFYn}p#%?TM=hw%QGij@Za+ zbcYRtZgyC^(+*1&x-+rruQJN%Yb4PRLHJKTg5mr^xXtgWT?8ievk`S_mqE%x3Av(h zOoT263EdbL@T5kZRJS8I5&ZPHCkhub%-;*Ojhe~n4(ZJy^y>@n&*~2=%_B#lw=Rej zxLx4Wph7D^H;t*P+w-1dpuZHA!Yal0_Fh$WFihA^YYGrMd85kQ#ZKm0YnOzLy8YgE z8kqWpdVZSqfQ?i$0_%J{MV6J|;6hq6!(o-gzhstu@sE@2G=sxay@0=bAoUKmY;Ri%7;(pjUIps0p82QePTW!`i z;$y2Bt*oZXmr$9i8X&}Nb3cOG0xFcUlkkD7E(Mywcmf?>ngGFEhvo7^q(X$fQxzEE z63I?HzVZpILE*&H6xWAPclYNchw$jMlZgk=gKeuB@psXV)P{j)9F@!HjY}q%#oZ+tA7p-c&__y*AL0ByyiRy4QI@*aGbUp5XWIZq|6T> zCpg||I3t^B&nf<7<Z`RVj>Pb_8Jm!B*?86P4@VdnVtgU3C5|%lc(+WzlZSPM}ZFZJ!i$?wHo=OQe5TpGe5XFz$hH@sNFv~vAyu@ zTlWu`&1(_C!J6fqaM$Z(3_Vg)vWkod$Uq1DoIG6c>4j?rkYJ|fVqix0J82Kd+vzBl z<*HXAIbqR|u?13_p-PNYG4yKgyid1|Pv3?y7%A?LW(DwW-q+T1Va?bDL;M_OaTh5A zt0Q+@H<5`7apN8!+nr}BaRVcxz&&800}D{wR`KHW51-rq5{5(8QPz;uDYmC?k6V z4mI_qcEgW{rViAmpNoVlf`E@H?H8 z?Eg(;$7s<|fhM|S6Z0DUSMYLN?GncpbkzV+hn@M(Vb(Bs(P@@mO-8r-qe6S>jQ&BN zs*8u9t5yBVhsKqMcy+Fd#G!(MtdzEw-d|{rlvVgRj9%;GzJ}e4svM%bOgn2Rxx?S2 zIhZHp#1Fn|%?~02w}xG062A?>sp%nb`lq;br~UaB^t@2(0>yC1?bTxV@DumD1tJV4 zIjzRT<#gfQE%Rj?L#7>kJ5a@@Gt5Zkp7Tx;IR?>S*#PdnZ-mNA{@yxRVxhhjT^BvA zSk@>SI$h)WC)Vij-=b@|pz~W|2NT7kJin49RrucOXuJ-tikz{5{BhbP4jdl4m}QIcBp2Lr#0kv4MdP znYQnr`ZL_Pq^i}eA~OWzSz3U!J>@c8OR8u_~FUqM8wk1^A3e5pB*o;qg&^K?^q}Jx=@M_BnQ$FjN%J6dCb=^MBNWoWlCKCL)4pxL-qdg{}oD9L$XB%WeJg` z2$^izNw#c_eF;fYB#wQTeJdHVFOfaM*o7=1MD{)VGMF)Q?(e)m-{0^0{yEomu9h$z!Ksg(&5g)y3<2j9_XV zIR+`QL&r#t_W3>4gOAI9$g0XsZ;`B<1M&|N_P6FRo5HJ84E-sS7xe1sdIQ-cwI8o-bGcEh0$kFFVTiR%G-L&Z|ZHs5IfwBQ{b!^$JE zJP$KYV4VOu_%Ofjn)R%XVf&i`T@!v>uB=a&)DVs#7wN&!%EtlnF%Xl)S(F}dnz)yN zS24;d6m)a3THc=--&ygrDU#+Cr-ZqnA&vmwGnR7){*7r|lojOnT)^oElbcXYBe=5O znknqkvBT}^=9P2%mpb9yK3>JA{EPPNX?gQFDCuE>k`7ft(E;r@_UPuIJKwvYwIgJ> zu*cA54Ci&0<)vReZ(^`GQyiv=>qX2rG;x7&l)40M{iI-d+5|sT_9?+F@W0O>Y^Z2R zXSR>i%8CUw-s#~+b0ck^|9Gu@fX7 zhNN_VD6tjF0+$N#OFe~e=Y304WYV>oV3*QQDmU*;b1PXdIewD~u49H|<>^iFvr@N{ zRpfXYGrWS14L<2sSL_uCH#~5pGek(ohSWYvEC>`@_q381!KA7#4mV=-t-~wy*VG|# zVp}Cc|M@xB{?f#z;^9+!DJHl$F;BP)Mt124v?z(^CF&F zIv?HRy?n4KMs2S>>+=)8GL&$9;o7@L<1?q_-1^Y+%KTpx)=n?aj6Ug9!t{`F=#Hk{ z-`N>}?K)}&rOGTewFIlYy?VTUmRTq;m`>Zv((kS9zUwHIoFwn#0?o3M&2*%lF98q|H5PnQ#|-SeWL2lig`Pf8FqhprV=qdlYU4} z{eD7TQFqUaoAY69`8ATBX2J}5@U0{;7|OFhkQBTdvpztnbS}|`;&E1l!9e{;?0FPl z^&?$5^JoJ@j-JQ4%np!$m(+3X3BmwQq`48#$b!!posr;z<6f78pC{0$yK@wNA(E`Y zvCx~`z&@w+c|>ihGkWbnOLx4r(`;Ecac;q4OwqXLRW+pe=mACC1RV13$^4w_u?Zp8wj;n#(Vtj_U6>Qw_|?t8z< z|K+|9y-5vi!-!=;;^(#0;N}YiYl4U{yN1!Nhx!Vlc7J!rlVC^oOuj}wN8YzNn45v6 z3Db9c2xqzasPglbHFx6wuqQ6adr0&DVT65lbhe@xZV+bCoOzCcizm4v5pF-k^wmO% z$XPw3Gf#-ybDLNjby=hnxYpF17z6E7=-7Y_{kY%SEi%++5j#fOe zrl?fzjcZ!Nj#OxV6s@lMt%GBz*fPYs3IM-5)>4;<=Jrylxjoo%i1G2o-Bc3wN1^XU zfa-BqDnylciM8$2xO%Lf0tern?OqVeMpzCgW|`*P!-na|I5r08Iw0QTQ(UKIVro_C z@DNzFk+foFT)mNZRC-15LiR*g2e1gjpFNyNYi@c=}ndiRuD~WjT_vJj} zKCFd6DeB9Frr7nhkW2HB5Ipm0yz>qfK#nq9&vVsqtnz@JFhwA(f8i(Ylo2p}C0>&Tz`lpdwTU~|2C|y^Gt8^dv zRE4l-6ZKfoYIOUh-u>=*(XaD2SB~}sd=zu28ral32j^za!#OG=d^e#nsMIfH6pLPA zm}OBKpJ|zL6%$p7hA2BksK%!pEozcL z5zOVPOuK~X{Q83ISi_CpxfgOfICvHOSi~66k97@`ke4p+H3v2RfmdvfFb>QIG~MEh zEp88n%|ICeC05azB5H<1kr8059Km;mG~rHY9QoTW{sdbDu9zFz=fyaIU|_&3?fQ2N zi+tNf>Z=n!VvA%EDTB=3%@;23xgX+0_uQOeqZcMcu)AFP2I=S-c#N0$Wjp>?y_p)Gj_IQfGYfff4>gKS5Ad{xNrou2PMiMKLuF4ovj?jz3B! z#GFmd-X~!;4^by>3p!=@LJulVrR|VBP@wsN$Dja=szO8fEHcR0Mq=$pE*1!=-deuRDSdBX5M<1GVlhGt=A8+c}QcjM@7Yp20Dj3Oj{ z?jT6g(5DP+_6>xihLjp-cFGX&!!Z&T%jo^#tP{QQ!tO}IHR|(i?)5ejg zV*s!0GRd9YcYF1|ed_4LpcWP*HW(cwQFXzHF-6)Huh&qR$#nt1kaZZTMl6em)1Fq;$+e*Pky8~oI#3X3X zuJCjiO&t=i&*5G;ymguIP?3tw@9G2AsDehX80p@!le4P60V)E~0_mk%Mt?>P*?H)5 zJ!mGn3OAp+NYn{mshWzoR~;Ubm9@`iD1a6xs00Sh&l6$xE?!896*R4(S%BRKWZ^D{q$DeV1l% zR1T`Og{Y99J-=S@jrH}xV`ZqS)2T8*BL%yUHiNFJ!zsk!x{+_=5EvvkA6+kWic}A0 zF55xmZMfC|tAk3z1j_%%*Pm$c?R5`rjsW24K@nY7TjCEed;ONGq%Ko8k_z_A3Fin6$+kNw5E{hJ?X?>oGQYen@cHKLXSspk40O;-Pt$K zK3j+pxZpj#hpvN9akdkzjzxG}*K&77dM|kCXu|fpyiG4uZ035Bn6GYON84CP0|b6! zu>$yXo;=yy1BTX)ZjgO4pe?20$8%58`Eat{+d)Qi0E8jQU%HN|Nlayn1RBRkH()&oUp9WBC7vca!!?(4{aD0cN&dP;d#7QGRm~!WPl+}{`ri$M;}+)RA8x~pzkirm zq-fr|2%akRdsklJQSjyHf3NqOmrN+m8bYWFz_o*@Q?_Mv!4Inw1su^?t5fSUOHLvz z^wG8m$xG9J1xW$x=^O1Zbwk3};_7>to2Eq!gw?lP2W9JAn>*CAY-&qPT_Ae-UveLEJ%M00x!Ne=(ho~pDb2dn`j`axAZUXYIiK5xo(@=!yPR`JM2MhLF=L*^m_YvMt zXbr&S8v&j-j`_;RGn4rsag7rtHXeQ4jQo>S5}8@ay9oNB6N+e#`C*(0zc}m;Jmx3_ z5ra1r-!LM>fw5b}Z@37shJrbqy-~k#DL@~sKttR@VOsid{O*7)IH zr@yfC3Ipvjti_fz5k@??9v1b!9F(6s9!z`c_Pk!;G~Ef?+Y3+cr#%`k7c5`yzj2Ep z{q8G=&npU^4@U%-TTDH@o~c+};6D;@m)K?TeJSI>;L>>i`dJx~{+f!Bv@kCz8IVIVgK+~KJf(cW ztiBoZ&n1KWUY}d%e3J`p)aE3JhoD@;P$9HpxunK@`FGMrFX!8<=>XeX=*1tCGJ*8q>@x zGi|H+7_O8^ZTe;@mWGpbA)1$#7asDl_!xecB1Etx{R)hDT?N0%QxoMAB$>{;5>(WJ z{U*9^2w8R8*~+JBDPWjjOGt4Wn;Ze8hzMb6J{785Va+W4BVin9P0$(su$ngvpOCh_ zzu7)FA95AFe+pP<#jI7{No-o2;jXtJI#MW(qq)_u7awa}kWL-G8Lxa=<9cywsAC_H z{0QZoZ9!XA^OL3fHX_}UJSPj-Xo#Hd@{(O5ejLSF*$4BDLXKHKwGoq0Az*yaQ*!Yk zf9?(Ut3sFQ^L-omJ26+UxWutvhT_W(f)!2&=X_jxX51B?hCjvztZ}bh;5*U#y?6Yk zCc%d~nW`H}v~WNTAhi? zwlN}f3Dt{YI>+LBJQOC{K5H>Xu)nWk53jw44mPAFNjm&J^hb~ah|lCtPa?(KZ$76M za$Cz!vL}W%!tdWb2B}?%xX(hp=tqM(9%aenc2 zaEglUtDluGjdQrQtA81_mpuA<(Q#3tS<0*WOHcM?`y4Wq_Osc19~nx^(BkzghR-;^ z2Wq&cJa3$olqw*l(VZwoP8hIW)m}J78l_X>9ae8ABU2*`4VkVf%bp=sX8qIv6h~p_ zD~J5O+XLs&?|(iVgt%FN5F!Jkj?60SA`xu8kWuc%|-@J)u0V{(vA zrnWwF@BX$r47Q(v1b?2|8s-Z9#W3bW%aQCsp35RF^1MYOsdWXeMxI{!pFPM#S%Ds& zX(2+ycvxY=Yx*L_048#RRu4EM zH}wklFY*iN2rqtIE+0fSTNW-5_2##s_adqkqCAN3&JlS_v4`~}Ea6rj1qeW#^qt1M z?&QCQ_mz66u*y%GV7D@q%eVgM&jFQ*n&Cm(!fAH_7Y{Sz|NX50QR8(B_NeA1;1gt8 zkHLa)ocWK@=bHEO%VEJyRO-!Dd)d^8v-gt7he1(av;-6SMz|T>q_1xXTW!Z@|9^MC zK~~_G{QtW~&$9<)=IH76&&QH>n;+O&qfsiCB}nd9rG zdJ7bN>nrwlfF}e1dqvJ*XuZl+VtUh#Z z|6Ok$l&-CspP#HZhoQK{^jJDIO3JO;o5-Nm1>xXt5hEGuIM1Brb4o9X${`%JXK?)3Ymd?8GtnJ70 z%N)Ibr)buYCtgIN_c!gv;@m%;lCd1`M7n?_xh2rYEl9~vBK5%= zpJBdp<)C66!5$XO(wmNV-IYECTW6wjh-DUE_E>zKADBn3qwNR&#z@X$dHyK;MmoGmW-2g*$hC~1U`j2vRQT-KyhsXy6!<-~jdKX4;U(AAR? zcY6-HvN<5Kt5<)l`}@l=x}IoCB-e?>a(Vth8t|6tJVCs2j$uvheLcLIpY~;H2&5|a zyTC4JsN%$^-8LTP%ecI*1ee}YE9Wl%iI+4TrzeJ<`7%C}cY-0^mwi_&vha$cp?`eH zjQwx3H+;zH*|b&Gz}4Z-Qq>rLj@n;TJ6n&ort;CZM-t_Rs|NXRwc~O(+0UI)e%LaZ z%W>b$=E{OqpgM{xQi=1=Jy?x$xD~aI(m!W$F&8pI5#pbIVm-_sfa;t09PVQ|l5X+( zL32=4$}AW-0>-X;4k5Q@K*%=-=fHykZ-bP8BS=@|~ z8n&l>W%=AUNCghqW9_wi$y1!an-+AkbGE7KYMLzQd@6VLlF*t0pk@K;(m9M-LfZkp zgZBhDBuPUcA+XVk6gT$YFu6eMjgupjX`81#o>tSP<BoJPd>?g)*1b#8nO&=)+B8(_PFE(SA<|hZ(AQ z_v5~mllOSJv+feg1+Uk{3*Ldb+i5Ab1~6;%)Ed-@+(-{Oz}I6A-r1Y&*veX58*+%-@k+V=kOTsoz1>`TXhjD z2#z+zcSe}D$**+knJECLo1=YwN``K-!xTJ6M*_2x9zw**) zXfq=XM`J!!!y_;L!^z?u9$xZ&or~bS5ZT=69`QN~;yRTbaOOt3m4`w}<@T<; z0nv4Y_3p0e;(brn?=_1iE&T_W12qG?r9)=xe}Qt2w^>4ccD7*^{phFI1C>l@{!{34 zd_G6g%WKi3zBEXVhq~OZo9U(D+{*)z@Oy)+0nkm)!X-wqb$}Ru`S~;ZwKs~>(=WV| z*f?R%_K)d4p;L4^ql3Z3%J{nEJ{_2>)cmGmHipfD^eGCN8HaJM9`Ixz92)fCf$8Vt z;Oyvt124-v2T)Se#jgY)B%Z)xn?kQ7ExEH-9dHM<$(2Y}DRUpCJ3S0U{h`a@Tfi#8Z2}b6?7Nh$Ez3e(ZPC9q<$Gb69F#)|8ngOX3 z$F_k*rs)=RcN(%3v8|84!>iRH5b<`H@hIcN!wS3de)otXlC6Zex}hCD3%Bh+V99-+ z_#j6k8P#!R3|TPEVfL0>2@bOS_0WzS_sC)>+7rD|c7QD`n`OPP6$bV_X_2-(m4~>Q zwi(bCF4)%bULY!G{vXglJ4z!gcy9o@s_@_Us9E(yOcZpedJjRnQu71Ax}S0V`n9;} zaw6GWLL0Us0hq?1RuDTdloz!>i%AMmYMrT!s&7RxP{p;az7YbN2h;=`4$IqcG*N0* zktsbRoC^1&-S!80viyqd?l#qQ-_Vpy9jvUs!E;uLkZZsn>YL{5@@;BvxbbF?s9^uL zRd)oVOLnCuitq#TWdHI|jC!Yhpjr}hwXV?`?WZ8k=1(?^RE%H{DvZCB1)iRvV|Xt_ zbItm(R>VZXWE{MkbuL0^Bc?2QE5Y}x(Tnl(q@3u3TT2(ZPsc(R+Y$cd2D#bKvY)FQ zn_`mSzdIR~s)w;Fe8Z6nGM`H)u^)Pe_i2lz0 z!T|xrQO{1^ld{#BhpilRML^_*R42^*WgQmb?eZ)Al<$2@NNAnqw^sg@YU@F)Vkx%! zo75=TB;EQ4;V)W|-HvIK;7i5v>KC0OMoXOUZ-eW=(4E3&x_zL$@r%;kttv;7{Opo_ z?=`E#BP^S~Ui0mMe7Vk*^9a9AE=ZlPeJB`U)=8nm`CIY6lds-p*S)-mR73M$Bd4ZLJ`zagI1z&Xr=wm;r&|dOF2DV z^1gV>5T2Q%Wx3`$KVZX8R3D9$iNij;ElOb7>OVvUTys)cMUBNW{R9p(s^6Q*X>}>b z+t-m_ieZZC;7Mo#67mG(rc~lrW2#T=UhPh0o`7{TcsNnJ!3%Ij{o5ne70CcsBM#+J>p`-ldS3*FBJWK?lRz5{|AiX&uOV)D=V69hFB_-sZJc z*@lkE#V?jTe{E{e{RL$%GeLu1MO{37te2vGGIaUuk<1QDsVa5?<-N~$IP3YIRj zH{_=B>Fw2v5=)t?c_IXtr%dwL=2X>lgw}?F-X-VY+YF@ZY@)!t^USUNI&YHoOgTUO zCrzQ#A0l7tAeE#}DQjev;rRmVrQn+z@g(6TXoRpml;BB*!@m9pPW%3Og_*t~XmFsI zl_F3`z=q-Z3Y%~5iI7mC@uSFcID7Z@mpiI8Icg zesKf(1Z`qdM^hsL_dDaw?1L+3k$VL&vMKK9(EC4;zXYvC&i!=yet2|L(lkz!9LT|%U63UECSnc_Xc_+0%kU6JqZk$a{8oQ${{rFmic zId9_`j}HYJk<5mU6--Zl)Z&b7rNvr!FMXKE`zY4Ks%Y2}0(YHBFWK_Ct=>~X!*%a` zZv`b3UXd&46I%74)QHF>c^{U!;$sx4h0}RPNj3IWtISjA+p01UMlUhUq{(fHw3^}2 zu!^SP$@Ww5jXpxqt=qUhq7MlI^^V!^ybJ7e_wKWOS1N6a-@@njEk}x-b(bBqcQ;zI zeXTR|lZM1(Iep**w|vxpyy^i{7=*uKJwTX}Js0strL&vfr^pRlbacA+x#^}A%V`2% z&60HhTFNicX8s1Tc5G%ubY13J+LKt=r61L-216<*nDO+q%353*F=h=*#NL{=L3n|r zAm!=@51u}6TNDsA34T8seATnC+B&aiMpreKNosQtHhb{B3w?&&7l@X?NyJH9s6s^J z1~y~~I|2UT^2rkcKhgV5>O}TH01c!gJ$f8{q-&o-+=u4#u9b#rxr31AYuk(0o__*C zXAm4=vApl!*%&tO&RWv!V?s=RAlc&rM{)M$COf%I`^(sl%`^BhoQ@XFAlXig;=r@P zc1aS3G;QS6*hcWj3fR(8UOMH!s(-?F`8*Xbb#LAgYW%!+Tq|qozlTe&S+YsjUXvWv zh#Gd5P$F`Lyza*iz8jtiUW2-^&X#t2&`O%?p%+pdkw@E)V&#nI=wxhjJ6+#HO3_Pvbzqj3a$8^&qN2Gz3v%{nTJF0h3WakV zAqV8_UFX;q2>B15T8}E+?gQ|Kq5U2o*YKBD>Hb9Pr}R;?w_ES-t=v#z2Z8?a47-pX~>eYW^YxOnuuJ~?6pVX5j?u{he%CY`(&_Novi-PgbL>+!RRFGQRs zLnmdxuFuiaH8%FXq?jflS%>R65d3p88XpwQWtD33c7m`Cci|Y|p|k=?`1mG`r3=>Zp|WpaT4dFJX6K>j5$h4C$;KA$434}k|it>Xa8 z&I(I?5^6AGo@l+*d@aLRASPL?dueF!W|_Is?ex?EvogC+^nas)JS6IS@NSK7N3c6H zW{>O_b4P6XREqjr*X}Xc}iCGk0OIhER26gYtDBdv;eLzJv38Cf$ zf++Lp)xIB~_{X-5GpP)`E;uNB`To5>z17PW z+r`mh=8p_s&Qo;E}o5bQNP_Rm>T{RXesp_^{%(rc&{ z8=D>y-!}Lm;k8YDzJE%c-5a>apXlT)W{cZ$y3q<{kol|&ytJJu;})Ze!i+sh;0DBb zU0KM_B%U}0m!90Y*ivx=E+%P!6@JLKy2F>~vX5H9bY*zvd0j#58UR=EfOqIUNHuX^ z#B9FaYe!Z_p5@uF`EkEApuX^VkvjifB1>NA+&16EHOM=jtYq(6LHf4``t|n8XGZbHMVPpV>}fShC%Ze6DuLElQJ`dE0p4C|nOQLaZc`e-`Cg*D~F0UA^ZfHaZd98D-n48B3{fi`>7c|0@ zD63VElsb_j^A}xjoUErbWxh~~dTDgf2EKw=e?Iqib*coFYVZXYgZ-Hpu+BN-(4V*? zdW}yP;p-=%sUADU}|#D*37(7!g6~A!Bz-6b~De@ss{BQ!*#ib9WO8*rnPPG1MB2tO9b2p!5h1vk)eM zdkvdhUVo_;P-jWShaxwHhG0b?!In&0Z1c&3B#y-)a)rY+h*`(4Neq7pRs(-uCPCX| zW-9?2hsDX;mU^->>f`*lVIMd?BJ^YL%YWQ> zb?-kt%+5iz=7&P!z<-9XWD&8O%m0m^`nu0$N%sx|CuVl`T=AHs_3iy5=z1G8i&r80 zfHhK;j`oi5=d2#Fq=Fp=(R3~Rieej?jmhpr2ojd2bdtV2>17VxZ3+SNZ7)+@=4J9uBVuE&@;-Er{$+B{>hhy{$ zo0LPMfcVo)lVlU?YaVp=Mb(!YgPBvRoo(>{;Rw|sDdNpE$N7P{1swwBN*}I|QIPRX z{(o2_HKxmwKHI}9?+DpC7t||XX%C+gnz=?+E5A8jw{q~}s=88jL$mI+3dYBKJI|V8 z5WAh&cwUoMVo>K}^ZVm551poysT1S}P&b@^)(M{T_m^f`qhFm7+D*A8dCZQBJoZ=| z{(?tiGfIv%7~jl;oYAKG*NjK~dN)X+rGok-*FVrkeH+-e0Th|GXQb#nV9q#Fh34?4 z$1!9h1$a-$RJc!EYUSi&QA*@Mw!`e>`=5tQ4e$(VU11j5t>8t&VXZ!1!>);31-{_2 zp858pzIhEtdBX(*kY4~2IVmRsiFMj_?{Hr36I*Qk8TjPogT^D&v^~vi_T3C=2^jknL^9w?X928S;uq*USh6s&O@C^J0 zjwC9L@H@uLW2nAMMz;p`^lDMQ;anNmR06Dbgyg5A>Q}FMqFz78ap&KfsliHqd)l;r zE%}nzw9Mh}i)5d*NKi;_4X5TFuXXW}RO> z#rmzB{E}|T8?7gKxm3yYB*VHe7M|(9R-D7h(uZ-IUnbSjnY0j1Rf)1X=k4@oW;cYBW8@Y0F)~0@^aaz~4isI+EuUuf$wZAG5tp6w zJ!^=8iqkpk3D7OOMQ4iX=OkCAb)^lI#m)JIRis&-)3F#HsX#XSeh<@O%fTb%h$DsH zKe!Wbd@5|v`1TLwKmL|Pby}~}1d{n|D-lG@SNgxmLA`%(dclL=)o(5Vow;vsCdl^j z@z9)NV%rp1f}wH0fQ!}~sK4<6JVGz1H81Jn6eCAMpXKoZ3x~ozKCt)+GVcM{mT1fn z$Y{-&m7TuKZrObtdLgJI^RPB{9hvn?*$g+(0CSf@j4xws$k-uFf?xhAEhh%nM_)Re zU2m-uMK-7((n|Lx?#~E>g|1`XES~uVixZ+*uDSe=FPP+E<*}G2ayMN7O!Yw5*4xxo z$&%a!0z;QLCFydg{A$@B3|ILTJmNhh>Lj*J9`Dl|aJ{gC3m;GJA`c3`pYuG${c4=2 z?fn>qAW3AxRRjI$r~`E_5*1xHfuW5{{dR@oqgmhxm!%>;1xDd&IEh|u+UhH}*BQHM z=h0$srdN2Ol5o0$xk)_w({wqB_2RXC%Ob+LnKs-Et%#3;Yo)}9KkBwDxb*Juf&V3% z({cHK*G$WQmv=e|!e@VS!5BNIypORG*=6sCS;m#80E<|wRo3A)DlYJ;s#6X!gJyu=bM(^b zYx52R`r4JJ&v5G`U2J@R=cx>*Pjsd&Bqtkr3Dr4BZ=aFhjb&k{16gZtZh_F5{kFU% z{VPVvp$A@hkGPY)skn85ZK*S=71K>{B6G@%XTC2Q`603%|42$k8-t>&p$^IY`@^R6 z|J^lAViTe4K*b+rYqB&mbo|6M`q0w@Dn-Amy4+b zRtvIcxdR_9VQ&8zPj`kHOQ}Y=o+XuWgtQ~8m?7|MGe+leJMNr`+9*{D2e-}_wqHF2 zC$YVi2i=LlHY4Q+Xdt8Lc0S!_Kvjv^HU)_^nH`_vm@g)~rSkx#bvOZCUv0ZTa3Zq% zH}*5@xDrn?mLI+oVfi4-s%Cn0`-3 z&BpkJA9a|l0Zq?(z)CfG<0q9-sOK@xHk!YaWOdYYl|=H#$n|5+wq$MNG==YzNI za6~2&3_}Z|-X4}c;3fkE%QFs@=1e{o{0|?#t!SC7()*aB%F@s(S$RO~c5UFL^(8oK+ zu^WyJ5oVTW_93G~tP^bd)@4=U6hGC@>3#B977!4k%&S$SNK>+vEpQx|9W~Yc5ff<2 znB{v_hn)j2;U#Vng(+|zCrKMHJT=ZlMrNHx;qAKuTj&teJh~@^W6h+4r*m>H7 z8jxQeFX2sfm^s6qdcR$P{lin!m?Ohob&xV|tI^tr^rGkisV470eyyT=^a0HAgfa=NLAHn|X-jks7KT)D4W0wZB+rYaG2JG*K<8mE~ z=x2f=90R*w?$Qgu{_WwLnBqXjO>Li$t&-}3V{(HUAERe^hT%Msuc_wD!cC<;sS~93 zjpG>9>y+K2{xyK3Re9J!ocyfw_Fv~^<>!X$h%+4)4~(68q(d&5#w{f`LmQ~%9_->R zch={iLsaN0(A}AdCWG29SrzER*t6ZXJxnNYHoVgy9$D(dh@Th3yQb@Ja+A7N*i?C)9Fw7i7GE7hQi)|%i#ex z*oPWH<9_SvNle!)I`+Oq;-RE4sg3r|BAo)VqAYca$oE}xH>w-H2p0YV|EL{cc!G3p z8R$dq@Z$L%q*%Cx~@q*la8w6rrGqLbV1bf;ev}+l^Q@uxE!)4`3hsT2=VKwoi zuMC7n#n~Pjc~REo4DksxXU`+pY0S?vo+l~(ghs^R1&FGBw91=gnoCyFT^PJhVjA|@ z8R+^;0iAwIcPrj!Zbk;^e{I6^-9J-b1ZZ2q!ObQ&3Klw=S+}Koa#9+>f{CT78LD6q z#b>)t;Dz%A3A5@yBQWZy5#MeCQozzJYt{507=Vc?Cd=+GwoQj8k4lb;!1oGhz8mMc zRvfRbktw?vAAw!q;+zFNc!cfuKOhq=XKQD{d_4Ifj@hu1s5bI(gq+GpJ;=hm#_c%q zmqhS>L}->jxl|Np3wK!-<&EX9+(u@@FLanV0*#%h zD3kant`__TNOzb4Zhmx|=KGKF4=%-Itm^nXK=oE0y(esAvb0Sd^wNlw()9AI-siz2 zztvQN4#vtSI9|Dw%-&QTP(&Tb2M2lHm(Ow~km2s+rTwZ3oZjh&S6Cbn`JUc^XuoJ$ ziPeZX$$v%ePmuNJK9lIdN>8EVuJqvDA5S9c1VTIm@MTq4w>@YN7juYgj#!_u$LH2u ziSm9-&97&mYxSkRWoC6MN^VgEe@PiE9_zVYoEcnt;6-yB2+htkf$a-%H+gAKD%XM3 z^dh-uP7(BzO-Qne&FTZR`vR4 z|A6M%k)H``D4Yy2KgVo$+Zl%7ju=TK0C27n^Lp97ebYU!)CkmwS3aSue@6vfL?;?) z+<&_dr_-%B?rOzgw&b;LLo`K&Ookt!CMZt3Z6url8<6wMNn?p%SS_mghN*GY9Sid zVZKFu`s$FPPXo!;RVcRNvYbx_$xG#L=QQz%twqMO3#bLehBfGJ98fz%&Dt%Hm^(NQ zf*-D)j#MmL$pOMImHrx;6cCVy=xx;H(>GP-aK&(FE;XA?o(!n#)@X0}T~Ask=*=NN zFPY*0bK%bliX0}F41!2cjpV6b;~LmKBlSD64Xk|Y2jy@a5oZxQWt=beY7RJW;qd3+ zo2%FF(2``lmwoj_=0lASd#aiLvJTfTdPI2I5KjUv2^q>Ndy==$gvRY|$6xh@Bgsv8 zH8+yz0a->qAcyOJ>ZQh`)ZE82$#UD(*2W~t+C4eYWo~4m*ULJhEOn8B=EB=yN`@V# zrL>%lP;*c7AiDqM?)H1A57k|&mC6Wpd3O4a$n0<-`^P;wQaD_f@DZv# z;{>^ta`a8!dX|vl)ytoCN81TjrXZHVXwIYu1)TWE0%3J>7NDqaxzaTUzC=@AaQ3Vh zniu4qmnCy7%zH4BuQo$@svG+Ph@hY=?2kGblvytO8zlb!LLIgp+7r;>|6G z$1#VV`E_;eOp^M{(rnEzD{Qio9AB`Pe^pomD2x?28^DU)7)krhQtfikUM)TWkCIhe zfpRrXV5Az%9h+qRL(Z`zfWjjr8Q1WxcpX_ez%vcitn2j719pzDYKPkduyrJR=3Mp0 z3L?)Jd~%O+5=&4n*cWN}h9mZ_4+LL4RTIQ_*{#VBcjt;mZ|p=$@U%vHSv9i%f~y=v!j?w>(FocSB>#fH{qFH@ z3i6xA#;OyTOF1K6fstq^@62kU$!OYLhbr~Y442f^KS|qcZ}id>p#D+(sZdKhdvm0a zN5}AMdJ6rg*4S~*{+Ri&;Xg^fo%B1bogtTE{E@>`vjZ8q=M&+#e=27Fk zm);Go(oFZz@Be3HScqnS!^$hg`$;N`q}Ou1{!PqA3!My8ot@fu_3VwAwUFi*(a>S` zc$RkcNq?_4Ke$&03C}Udh%_AR+9A*In3z3DZzID4{kbUJ3Xb_ybFBG>p_0pHcdVz_ z%5UBlSSJ`gV$Xwaxu4aZ1GQ5i_TebB_`r|Q-|S&Cj@lO*O-;4j!RdT(DjAvd>>c&{ zBEPCb)^inicp1O}3e@vo|3Pxc38+8Bq5sH{dtGv)4TsfbE?bQ&Tgx)o{j$4n{<^8i ziQK3T03yUz5eX!5_8gC9HA()A$azFLtK;_=SlX@!<*^;t48>bOc%ldhwT7%ako#wvFm~;nQV~jfck?M zaeG9H@#acE1-p#zuym8Pv7?`RuneSpL8cuq(0zic>i=?tqD#j;NOKccnwy@78Lm2l z-n>$3vZ<88-*ydZ1P+IMQ*TZ#oLgHa6C(2e#C*(Ry)I^q`8?fMIx!PQMA*8#%x}k8cZ+T4PlkyrM&0|chTf+L0fGp6T%(DbIHQc!O}82u5a#A)AdWlu2$f2>B=ST zmph{35xe5|b$~tldwCFqx+}yL7#4mXXERKS;g}unmc^6}CP=k>^?leO7H@G=n(wrJ zc~q>Kin~B@6w~JJ=WvPJpK>TnCvKZa9Jlr;&8^EB%6|-x6>kzR6K@}=dC1^mEXUq5&cT`2^*is+_w)Jv zf8DP0I8aY0Bfdg9Pu-poSNw{@na4h`#{gV|+*@v7ws->#4S2PE$ts4V zz0~&hlrrejJR90R`Zl8m!jr)(WgIo{DscOT5c9&^S9&m6nF65tQsp|43is@yDAu!& z!ay_LDO4pYkEk>ATu9oUiOfhHV=u13rV!rH2x-3d94DiZexP24*CSH-dU0Xa>$gpN zwd)KB%>DxuK@c@gLc@tQ!+PWuMk)A7Y(SaM3K!}c_AYDUkN^mSaJ`v@SphvK{XQj% zL|WX|{4w0|Yl9Np;eNA&EJi6d{(11)~$H> zT4Igd|pAz+LD3iMdk$R10y7W)(HAr{KzVw85WTu5fx*k}h-`Jl&P6S6eD{ zbk3xATI(={vZP4#&>=N^h<(hCS*jAxoL1Q`*E;jeDi?kB}xROLh zpt`P#Sxc6{DZ~(Sd?!VpL{YReKx?7;^cOMh(3$CQYjO?a9T7y8-ev;AqU6!lnW}?W zG3&bo`mwU^`9Xk0inSrzq>3yi^3cy}THT-j1LSxaJ4D@8I9C74N5w?7@@?Q@?YCut zZu*^)jcW`ct-5hHXH5mYQBzH?Rn)_(t$zIfM@FJLfSh%%P?wfVJorn z(Aj1)6KdVs$Dfy3+8eiEhD>LyZ?NT6gBI--f)5i>XnFH|bR8*G5h<8jxs&&|=fkgz zvw5C_m6TWaf9jmAPj6>8@GfX*;PS9i-OkAEQE00$Ypm1P zYbDwjMH)o?Atgc>=yg_$Uju#zeLS6s#<8KsNT9@vJdA6sN#R=* z_U?FpSz39q-4AML<*%Li;1r4(Is)~=8}l7&djCLOB<;9EuQH309*4EuqUTzb;l7{whd(#`No_`;_;C zfd2*UwE;+JZG`3+r+S;-6TItGl}lF z=Y>(JJk}`BAEBHjtR;88mVdckmQm1gMTocm1#P^MQ}(MJkEvh3tn~94qb?qtt;*>u z)r)}>%W;`gAvat~fWm!$7P-osR_Vg2M-kiK;xR1ku%S5QOfZ)V|1^C0rT^ipjMjUg z>kVSHaGA)Caeg;X**&)C_*QbpR}w7)L+xts_+T3nRlfK~HLDmfEm>`KF4@xJINwSns1wU8Ubo@h48s*?J&0Y z>B$`avH1rm^(qO=BqBvAqLta;J4z8wn2G_-!B34ZGb17;NN9*d-fVB|5_Z#-oN zi{zBk*o9ARyAg_FyLcLBa!;?Oa}>h;q{}cSd#R+_Lj31TF8l%!ey{@<0Q zr(}aSn}{Eud)BqJ{Egh;{Dne4lR;mETEn=W67yA7sCyWCdzO?PG<;Y42>19vFMg`Rx#gE?U9a>^LpKa6vhcG>yZ&?hb6 z6>;$>B^#|XQCbfN= z0IVP{D9R5_Oye14(mq^C`|f$pvcdyB|$V`?*C7f zy1_$|OE6NWg2L|~@0osCLe{=daXEZ8)1SH85eN8C%zHq_Rla)-gs$U#N`qQFs5UY~ ztGAQ8DpDzxL{9RErmAwAoQ1dDw3h$YrPhC8>heAMB4as~VtvWlh(6UOccq*!FK+eD zxB9Wfq+F%+9{CR0{~seSk@y`af<^S`evMe{*FAO#38;q0WHS;p13$fokutN=)GPVY zr3U;*X=)W8+_u+2JX8y%e`3iD{kWZq@h3#3!1LOdQ^>_1Y3TVY;Q{+Zv%nh*s<;>Whuf?2Y62H zH*l}ldKXwaqWEH&Wz;zA@+er0b*gyKA*6h<)FbtYv}mhPriNYVjzAqEfop?y1wCUK z1%}~3Dg%A7Jq zxx`G0UAwzse;swZw4s^SFI`W};7k?(|vu!*9r=g1IrF9glLt<5Ks- z?q91u*P10p3d+qwnKn#zEqttWe&mH+`O9m%MSY3HFYLeaztlV${N5@usmOh3S13&Q zc>l;K0P%H`!@q^+e&X{IZ9?Y^a*HmVD^!7&<$bW~sNO@%cg?rJ+l~(G%<%ft@1|f| zsLM5aqQOLR=Yx~Fk<<0%t};Y=fb17@MC}{Kms|vYA`s)@hyf`6+*!9etN z<`=6Ue>jvvjE0Trkizj6dMfy!ak}M(+gU}guImt-T!><}^Bv}gRr!*ps?yuX=MpH~M7J$T}uFF(iT9>-xsdMh81hfoCCQ28u46uR(!4T(oT z2aPL3Q3qWTFHR2w&C5}Yx-I9O{F`0P+8Gqe{?u?_-jekGp~j_UWq8$>VKNOfSB!`w zChtDc1qa*Oj@tS{gJ5qylu`0^PXM4%(oY78NMDXow-4pRztsbH3XxB}Q}cyS+5Zsv zjKG5HgHymSm#$tLgaZpH|1C&v7$<2LC2I&B~?KsR*22+tck7W@c**+ zJRYh^81b-V!bM^w1pKWHC>H6J_3{~^>4dUvn5$dJGYRb-_U`SA>DPDAtoKE?z660( ztxdv;JykXY+qyY~nbUeS+{fZKbo)>w+C}#-M(qx5$Zjlh%t$T7-u+=#8(5#VxD_be zr0@q)iTv!P48N;h;Z``JD(Ewu#UW!5BW`I)7~Knibl;GjEj9U zU==qjLjlAIBs0!y!Dk~Iv;P(GALyn6Idm<(WCKo1NH{LmKDSm9@ZIjO^> zE?TAb=)LPc>fC@v<6k-Iz)}^6$(U}sF=b8Jfk~~eF)n1|Ia*k!S4>xmxb@i}v=V5r zh>*XtrKwR6lH%Sj90a{t8yUHi4*jGrGiOks*p2cV<{Nal`B4y$dgnTvjEJe_1--k3rIWx;q6nEI!6EIO^EVALN zO(e%HYc8{>D?#$s9@SC{;=y>;1yOV6JSo z!a8F9k(*5CD1YH?JMGh6$YhfRc&+X8#+RbAr3^sNcc(oP3YOk9t=kEpLsk=*_2JGHtGk$gIZp+>q z0{*E_0_ze~7kF-&e_euQeN_ql=AxqM&qpZV^UQ+fTVLNna!7`8Mtlt$r6KDKKU=#? zp&vhUXZ^kiBN^_uC7Ymj!>RQ@IzcrhO9lA7~pFh-p><`wO{rLLrS>QR9C!eVtRj!CdiAmYr z41CKRbmcJ>2XlfUd7oHL@xI<@LVs`Ult%iO{F}vC`nEXD_#)j}-2#>)e&ip;3LcNB z6up&8Dk{<5Y73;+Z78j|Uqh~AlX%QZ(R{mTd{TA~5cCM@2R%H)%N$%grF9XpH3J35vB!@t7sgqHY4|UG>`x`5vBVb2v zA?%nA2v)xS;4kGX7}x54&=#;7EL`f#I+6j7oCTMdUSHxs(1W>Hc+ySi@&HUX3;cn1 z!N%rQEY_U-bIf8D~I3kJ5a=JcW(V_f)xChZ!}+*O*vQ8UlREP zl+7U3y+LOm&rME2T^TuJ3*n3N6b{2w3lvx+{R2AdFJz!;Y0x;#aIJe5BftFCkouH~ zi+;*H*)2e2+q}D7W&_1ak`qdZTo$ zY2M<1323e)gPiU!R01`S(0;KBl&^g%-_JpH1&@poskl&u8}uT8?AfZhb(8`Dg$q1i z_|f%ne?l9!PH`q1X`i0my{+AR`g4Q9MYrj&V8q1f*E*r18ZbCJvKa`K;;*NIEKg?J zs!m~o`;g7kS55I`#v6+(KcX+Yx8IOXzp`y{btcgD?yezxtnGd;L%#5?TN(F#2>0WL zr}%D&KA;D)mT?a2)Ce7&nsk=&rkyp9^*6h`eQ*3t?o~Yj!8e+M)6Q6`D`ROlz@$t2 zi1gqqyq21@`L0(vv;vGWxB8HTw-k@JKDO`UA8n#mMp0yvpYUUP;yiw}M$zCZ^?hwI z?Ml|&hnv6B!NK2g2EsCh!cb1l#2AWhG*wHe$)5H4Gf&1tbOTv4+~sNw-sRq2QwVaj zo99(d?W3@AmCGdC$o$ONIS_969 zN_Q)4{oyY_p@_oAl5E8)3JdhI>MLu`W}PO9aHVq5DLWpiFG$=jlEhC-;#_{K-w z?P9r~zm?ryz_^f6TCsVGQ%0}i-7n(JM`l`^$M1I`DUw?_WBPU(2qkTE5UQv@!ns`33a5WZ$hyFyDOABGNwiH^6SR(Cyx#f5y%^- zGX@jn%6lA8)DBd(2p0syKKU&QA{)pnKU#g z7&OvIzJq#=hgyGG5Gg!@NCq z&=ctSHmvGb*82!B%qh%UOc}j~B8H$N8|>~`g!syJg?R6_T$nCrnhug4I^r0Y4=?f7 zy=qrnUEQB%N)3kHZdkv%<`T3@lB+mHEAs}rs{J-u@wt3Zrx@cv{`nkSp%*p0fDg&Z z?iklCzwP7;`ycihuS#ZOEWdO1#N-6m^xDvJG1{QT;s5p+*@X z3j?)v?um=b@U=-#<|1a@P8e-jIZ#`;G?G%!#0v(;6q*2b*DX51Ug7j?mhad1mL8{z zu_c%+&aCTSb?>&J)6>ot=*#Y!hBK%23@KJx%zTb6mD8-OHKHsp>LNa%>=%G-sg706 z0)kl&6yBec4h&hm0`jDN@72W2c_QeJSt9 z>G8?>{d55gQ?dDlb)At)Ubkav&o}9U^SaYuB*;;SB^ROts$jwq9TAqY>9 zNJ=0qCQdxAd=@sH3)zu-oBGqdF6`RIV@DRE-rQ#%C5Qbp%sIJU(+j^1SHLHtXV+o7 zBf(IoOdj`{s8e4OIHGn6H{0uhJ;WepGt)HBiIGM;i#}JIGdPPch7ND5M7?pX%-wDS zIdP`QhS9RQk{(;rpV?|Mvk7veBJ@Y>J9E^>oaB4UjHW|e;AHVADn^)b^LIUV#C;A6 zaANz7571T(iBG>X&A|vP2UGj2Ta2R9G!S)jw+99_?q#jWdWqP?!6;x+xo2*yagJJ` z<7{cBO;lMC8>r`zoA>~tE2`Ro(QY#My&*4s*wSjIBl~U*TAmkLC)q-{lY#5=zjRL* zd@G8fk6(kq%x#yf*3US{M<;b@*uamrjtkxAp7N=X9ayu{&)O;%YFYZOw)U3+0730mq7)K>Qds{#cc z^ssgt^@x&{`Stla+5^&s?QTCX(Yq}eQ5waA4PT?i+1{vn^sjzp{IJb>M*qXTs`d{8 zruyb~m$F9`a@2x@$WtC#d&xg11628q)N)~JlT`au&354z+7R&-Mj-KWfXwyg-{`F2 zg;9_dg-dWJxiT6wUwMUdcx-PDbzF%BX0%{W^GvK&d#)MuM=T52^x!Mh9`?O>97Ou< zRBWs2nk>dhT47uMLSOrK@7MW|NM^2cn*XyrpG6?~bftq&sn#;+nYon{k@ijI?QhC>g@S7AW;RDFG zyhqtDRRQ)CpJ(@OmgDC08^f6Gi`R_5Mx8qMp>iSiXNf>8#n~G6LhJS@(?g2lZt~7C zV!GN+=+?)8pd=>qyX2;`$c6QJ`8U^n&xusGMOt1`dB-*La7Ch%GGEUuV#EEFH0UQ$ zN(yq4ZQnXV@cg1Oq9|i(p+j}M_NxeFnDWT02rbo%{=F`;X@b-tIY-nClg105teq58 z*+;xfUU)p)S5q4Px%Eu2!j|(T9bZm;#?9+bN`;wzM&u9O`SbR=cCoIZN{t$F=KRg5 z=dM9UZTHx=N+!?zo)t)`Hadts(P!E+?S(In#yuGpY~^cI1NAM)W${3OQe6QG)4%cd zGUPGtRl}Uf`MytN=GPKCj(=rp&wVrTwch4V@qV1$UGrGnzPHo{K&-{wf<6XSXcZ^~ zZ(T6IR*rx=v+Vyu=aFIy`iB((RP!qMLQ>yjQ87n?;s?de{RYBA*Q-15a?lfTBtIf? zXIMOLE$ls8Ftm8@PQ=T|ix2v|Ca-frn`yXt_JYT-OS;LBKBdwQs$YD$AVeM1ybGMU zR*^ijVcJmoKH8Nq&NgCgK2zOt@q*s-sw64A@u)`|vl`V^fv@0kA@#%>HhsjeXS+Li z_Y( zA!`4|FGRTAGn2$OAxg{PlYheY?h8Z1;O%*j0Z1!AAUt9@qH2Z2KO6f_N&l($eIorM zgT#e7^zJ6Ipf?Ud>+l&${^RBoUgY@0L ziaScsDs{4mS(Vq&1G%kc(;C02`9jR=TBVuH_4A4wGsKwYGjuv_=N~;{c*)vP5t<{ zScVkM6*v$6bO#TcYkb7saa{P1h40*?a;)hX5N$I~pi!|80q7heNDd@_us?D5!als) z&F943T2xKov&a_ph{hs3!E>B8t$W~kn|P77cahD8c+mRaz6- zvi0hOt@1T_Sf$q}q>>AKn)(|%a&)|NUuBJlmUo$J7J8-3s#HmCNqipGnjd(q==BDa zG7`qd$DF(&uPmBWE;rK=fv)gajlwK&6MGnoPE10biRD&loe#njD zC_4lVq5`8|pMDEu;<@~^Q1%qC%~i+%9VBmArvjnf;>7=jiZZ<>?BB!=fjc{T!;mJ8 z=hB|3Tk zpqougr+}!EfLM^!F0f0b;9j6Nlx@X+hU2Hpqf-8@$ctp&40nEkrsdblVHqEUgN1U; zdGsthF>a5TR|5S+#J^z-4)v)#N?w&aKf!P?$>m6d$V(A8F6JdM_grB+0b*iP8ratE>WnCa4 z{bY}Z9~;3lqQ=2D+!T9+`+O?Nra5}VdEhg0IfBYF*Qb(WoBffvx5_gfy)Kx)4@lv@ zjnNbA%>A?VjvoxeMxiTC!6oYL4PEMzkPtIPKvaXWT*|#0FpKjub~JF_PPR@dV`hLj zQ{!i052cEz-z7#mJRnJIc48Sra8Y|jC-C>TO(BaLv?`{^!4T)0-YNI-mJyhJQ354Y zanbJJ?E`yQD(XP|HrNXQQg_ovO|Y$}Eh7G#1)1Y4BMNdB-b)5?e8nYW5V#5TxCv#& zEET6FE%>hZP6P(gOq`b!(a>u-=+NoitU3}Umo};=Zzf!ICdX>1qGHwuimdi>q~;g@ z+m0!9V2;2>L^|%F3WkAPy{{p5>*3EdzmRCjYU4TDjw4djgXT#+j&g6OcK-yFPp65H zU5*&3GEv>wS=W$Rl+ls;5AHGfB&%N}L?S?2nc?zCfJa@7`Pz4J6P|>NKCe%Z**7@@ z?Sk(b$_^w+brKO=unXH^(Q<0&e)j^Csa26+?tyMRkc7>H@jQk z?I&S(jUVVG9s;_LE_4q@<~$N2T=<2>xnM1he8_g32^*UCnua==+>^su zwfrp@U+k*ePwu9(j`1j?n*|ncSpA}JWU7ALySxdTrEBFI@@e-9UjD1qWU8UM@|Nmo zkYF~PYx(wR#yYQ|p*$htoig@KvynmUwbx9MqII;5OwYf%|KI;pa*xZEO{me*O$8Kg zikDEF8dD~nMQp1yI1g6j4UXIuYE7LJh#5xi#a<;>sCQ-gA2}z;Wj|QU5Prn zvU9IPoMYBCQdIgKarBXGk2>0}e)gz|yLixeJ_{D|b1t>{v#N&pe;2V_3HVNFnZ=!4 zuQ&4VB?O_8E;lljr-HAhp`O(bl)!rexnH+`YJAT2_AK{s{2idK^iv;U*To)N(F$_6 zD(M(~S$h>Di5H=Gkkag;%|8wrE5>_V^9)}#F&aGTNL68f7&89$+Ox5GGtqdwi~a7% zp>!H|+-siGj^1wFMjn$=zw%LDrQ!{Khh+)L6Q(bIrc#$%7TTr z1!q&2n2XN8=FT^iPlM!F_ipw&6^V5w%U~N{&LlS zJQAgo$i&U5eZZW}TKwMums-t4CrC7MVp!UAC`bG7p2bGUG;{*1A6CdORg26AFaePN zgK2oV#j_Hvn)j0G)muql`sZPey@|5i4L!`Y+}Sl<|Luer?rq?PS@tXJDjxZ@QBUXQ zoASTF=4EA(cLN_;H{Xw?9Za7QkLMoKNE63ro-yLAjvAGDI{e=jTGX{+a-TkFNljp@ zqBT`K+!R!D>HojY4Z}tUw*OBVVNv${XQ?)-k7389a!n-7X9ZarW=|A{w#R~fOZc=8 z>#4VMTNuWEm2p(n7Y*q0y2P~}n`xOE`}AGRkd3t~dGUK>?6V{xuxpZnRDG`-t-yMr z_rn&8^aP-KCkK#5zjwHCZwv8Jnii``L8^W{_M?~qV_dDOE-0?RWX>>m7Id5&(%S&+gK3RAZErlpHY2Aa}Wp~V~ zo>wjMF8w25USYMJde8aC%z+#60UMs`7as7wA#-Vz6#&UE-hO~=$|KF}%DFWg7E!xR zlIuO8(QAKzZuSj*XkgQBRp#(6x2m%gX@|UV3lHDQOC0x@w#dvn9&*TM^joCfO0Mv; zYdrF(&@TM){xzWm4Uw_U8;28_|D4*oa&6woj&m+;+ZGQXy~$r5o$N zJ6*U>DBp+)hT5K_-L#r{r6GF*D^$lTM}wo`FYQN?dcnbRxUH~nJMeDa7@r6o_W>eP z{Ko{F>Dz4iU*~`Ir-(X%y{q$6@X}d89V*?49b!b(_kk6i03#XF0-tQlOXIm7`cDFh zsP8d^K1!vhY#N=Qls<_Fp%gUlSDSogp{2I{zYZ{D8PH^t|Lt# z*2~1Z5Z?#={1&F-Skgph8jus9UZ!`VSDr~Krs-S*&Yy&)B08L=55jSJ*O$OUdwWf!}BKin8J{8@s`W#Z6oq7+`&U)`;&50pJis-az{ zhjO3`BPv*zG;)LY9VH4fO$vQSj}E4yXO^CI68{8Zcod{lgeOVQ zkzIoe%|mCuzXaZ8ytCMaMC&5$g9)nMGo z5~IGgm>snB#>Llc4)T&N^lHUajMpH^&S5oWaHs-?k9R*<48$hF@rlBbpCF%&uc-=z zvDgAH6!EX)V2aQ}N_)>?U1VoS0D2X%kJ=?rA375dPDbA?h7dlJQtKn&9)YDyV;b4_ z_Z@!Ur-fYKwmUopYr>_3JefgS%_4}I_b6ml*{-Fdx~j`^BXuCmmndho zsyQ-$deE%OQca8$o=sAXA9^g+p=2Zad^+u%|9I)K)i}0r7&SH>jj$Nn=Z91;lGorw z^rfC#yCN)@zTIWi&Uoazy}^GJE*%O9id1yfJ3&=vh^YIYDEW)2%Ke3)9b^*xnn7nd z+|5`lV+WOO%llk5u+L%2dK>BbGwEatH0f^4k?24P6+}AhB!Uj{Ls{UP6MU21zm|^p zc)eDg*pYvNvHWxkS6(Jf{o3vPEqCVdGpxF*b3E{wkxGZ0{$hT?uRg`R=X+nC*`Iee z8YCRvDA5&aulz=l!*Kn-tO2S$gbmp*SH3TgL{-|ewtuI;DjL_$JlwFNc59t!#&^PxDYUtEV+ zbY=9ZAEeLC3}2(Ty*Xm_!?h!Ey)fT)hoc@D#H5sagR%XyS?yjDe zR9@8@?QkQLExvLroKMWJO2s;)4y`L8C=yb5VU>J4EFt1Wi%?3C#++_l6h$`PQjt2WQU$Sz$-@=_orI; z>8n?yH*CB%-}#l6-YOwmM?j=G9;KR7eIA5I&c;{0Y$w6iD#99`Y~=Uzt)rU%GIV_q zhb&|2ypI+owLuKEpOwqS!c|DNG6PIogDu3{)?muEN?-aBj6eUP^6&dJA>nYXJoj88 z5qbO%z*;LKkWr3bvgL6)W>ES?aZdlGTil$Wsl-$^Fsbn~vWJ%MMWvCmEg_Zv%z)7Dhz3>( zQkFjw!b%;BQIX_UImw(cmYWFs`dXAIL4ONIoao%od+sj3j%HWRgf2eluua5iM~&H8 zma3?k0o+d@8IirtptWOy%XB{addWjSkgw+rnJTKM3Cyv?RD4I-Efpk=%biswT2g~W z*9arma%Uj+EhWVJXUtWdAD9D^NF$pPtm+s@iu3XLN+V{^SbThnXczL%kEHpe)uEA8g_%%4 zCe_&x8yuzKv6HJJi{fvoX1TXfLi{W09kzmLbS-`6Db;tNka*NCa@uyeQ6~{@>lEe~ zpofJIqHv!q50N1XZ=hZZFx~e*$m{f=*c=!sUM=7Cd=`q6sx=t_1qpTWl{DN-Tv0Dg zrO(;A$w2)OhnMH&8~x?)cb)YeejJLpi;MdwpoG#0gK&oIUV=-R!P4|QGW}2cJ%aiI zq#q;yvTHUb`Laz6sYKFmg>x0f<>H7UEpJ3Zo38s@<=VcMFgPvCan%^5eGv()ps%pk zk;fi(-0wLgJ@F^sW_b}r9yGA(_4Mh@FNcJJ^Tx7xTBnIMYk^9lrM-z!N+cFi_#ozlqNrc4ny3G%U|^N6au1l zS9r;L^T=TD>=)LN#n9Ws2OQ&Ji<>Oa+me5RT+l=U9NlI-549_MX-M)_!9B%kK#?1N z5SNH%)&Egk832r=lLfHXJ%8%mMR4h@<dg0E>9|jMijnrC24U94 z)0mo%fF*!^MRuuWZXEv$%pQjojU}_WWkP~8uL2wHf)sPXddTt#NOEllgX%n1EA%#m zFG7!Mfmx4XRLdv52uq^V@6z8$deR->Ci6}#m5h9oB{1pD>0VP0E~Yu>9eZbzh?0;Z z&9`q)z_(rhPHk&$AXiB+caC+YH?N?YDx#j)VXw@kvlH>JRsL?Z(L4k|5&HTqVC+F) z!kUQcZUf2ZZ?+rRN`Dy?&p)U*HW>mj5$Dy?nWAMY{dsgaJuUAx?+= z%>G7(iRjj+v>Jkbw7MZ~R59nB4S!!}0R5gdXcy#62(iW-K3*Ija z`KD0*^-PLbn!VUOjWX(FyW-%&XZArE2yz9Ef8_ns9_OX8*&AXY&!|!%KUOe`#-lhE zhgd{j`2B^(8Fx~pKMV5^d~kleCdWBv>|mczt-py}M{;ibBtYu`1+@k%$0FTEnHSz- zfr&V(A(S|PY&Y_!>o zgQ0fS@x%-h0}OVO0GntD^P1S!2Fl@<6P`V@9H#4TQRV0Q6YW0I-;6n}-mfWE&a zDHc;fW?KnyixheYy&>zLpiBE8Ey$J1BWS@xZt9=hA@!G#QRoizk5u85l+5z#1lfMK z)isa=T_o3$)$JSm;mTu-_{`Y4kTb#PRk$kN#!F%qj1B(OpNiQhoWQRZ(77KF>ek;6 zLl#7YCi0yL><#F3|BqS(a8o6vxcMy=m(h;%qJ;(5KSMj!ec#IH2ty9mJ31%}fOq{Z zkc0_7Wc)M?{&`&R8TC&>C%)C)N_P_xaIeDAt#S=q$ttb*DhEjqf$Jxr+^U!hW<->< zMfcEcBX|SN3&6V5HZcV4GCW}sqF76sM?9yA|5-|0Kd?^(5T>!3U})EUj0@kFbwcWg z93P)r^njzmck47yWAGr zFO6+H#ohhBgKiD-nvq=Y6P@WJQD9RB)?bHjL7bcy$*!)B3N ziXOi#o(riL0SayGOiIjUzoJ_ee^`>)q7wfCX_H0#*@EoBIr8a+;miZxB!V%`Iun2xKI~KJcItsy=^~=3|hFP6Y6jrPy%^y~)@~iM*U) zjH2<2vn#mVh}vV3#|OFm7)njy7$%Mg0x{}{RK!tB3HK@D)Dp9SOZw-r(BAwHF8a@> z84@<|K(ApMyNdke7%xoAxiBjB7uNY8`+<$j1 z@ANIh4{X_dY5Gqi>HPFYhPE=j!m5PFxo{~G&!u}YgZ7rI6%HAqo|oiWT@*OT^u*j8 zF7oJM|0sVa$xWGWY+yX8EV4Q3_nY}54abp2=O6ZDH?U9**^G&$?&S&f5PxvL?rQWG zsDDhldH8ejj;SAD_*6l2RS-_DHdfrAR0g%?4>)d7a@Q!H$u8Eg&DpBzG`k@W zE@u7Pe;3Q%zz(Ht(mTq`vq9eU3dXwwg%joBlB{rPiImF=Ba%cRI|D%q+p4Y)l7*0 z7NF2t*tr4IUL4vze+U1Fvsh4PUI)d>lRKSGU}w3Spg|n*Z3yx1c5KD( zsV2yDJ%w)1b#$QEA+5po9glr(U!h8JBEuLap6fr9D+S-GkKBGXW8$Q3@b~+STXH3L z`q^Bq9`-o4)dM{ojwKEEAFD>UwoCAkvY%o2q0tu6A7xtC4r?5Lzrwn} z6|&_fL5;!Rb+4)zUM68@SFn2`Bt~`Re~nQh3ee)a1dxJnO_UIg6{R$D(}0rME1;LN zTvIM^C>UMRhWig={?I&0#btb$r2Tc{+?8PU>3oZW^A$ z!hT+QX^7Vm}&P5zNa1Ud#XWa>}`HU;ri)VpaxJLaR~aD zaOa~<)gIdPYK8iCNV3d6Bh*to+E=L1k05D-2ftfqwy#5`N7vFhp)Ld@OU?KXz7*^H z@b}H>pOEQ3ng4GpXC7lUE1BKl@$@=$Jc4@PdS(dp8-}ynRjlokFp5`iye&+* zDH$mYyqj~v2l*eNS6u{9m&vG4$no2rFA(2&oYw|QD;U+K`N7x~=_!w_LE=7l!;;7i z_U@&?+wVV2t-~&r^}vFrJS<_ydE|;I1iRuTM-sOE-4(tOgLR+`OEZNeGXAw{J`Dl3 z+-u+wz82F^KFsrY+}Y0N6q({UB<~&=<;j+)@L>)0qf2l4X3t$Hukv-rGjvh$9p;pM ziw|f0Yb>rNn1_W28!FbXOIRJ}Av&a{Y!rfRzLA<7x!W)5m%{ z@N-Z9Q09lbzWlOs9En!i5uauO$Eug$FUTzG)I0l8&8nQ>q^%KG`0#~i}pqoy&GRaq(&)WvTPQ<|8>ZL`El^Z0%ZpOk=j1kb?JL^Xa0b07J8iLyE<6hdyM^Bh~tAe|f^dHT3Xdw(2 z?`wx)i;*`A3Vexs{4v7#wl-xxyFZubnHoFH^5P2_L4Old*ZI3IKy{Gs56m3>55w(x}Z@TM!7d1F`^ldh8d*~9oUh|8>-U+>n z@f8*S#=S&1G^5(2nC@JaV-%?}?$5A}amv+%YGtMqN`S62D?iPgwA+w?_uZ|Uy@3`^ zbV`rn=&ie_sthj{l2I;eH&<}eI}t8(;al2W?zFdU2fQo0Q`G}2xv5VRN?xETyYYke z;Ii~eJ?OKt3421)NN02(a+1TrZ@PJi9U(JE7E(mXgZsI*;T(+NLX?p z<{@fl4wcpw$ss42Z@{1P8B$v|aEnW)He$mf^#2=BDLzoX-N834pl?0MwDb%b4MR!X z`MLMoh-O=&Y3)EWC?-bUW%9J&M(wQvqeZ}3YLDa6%yoX}^!t2p5yC;o4RO=sIaj_5 zKedpCY&R0QL-t3unfVHjR9~XEeQl9WAqmv^t2JShjMtE^ig&K0LpV})e2ED(Ns0V8 zA@K?l7)71Ce5M#5@QNcM)mPQt*kxqJZ4s}(4)|LJ%Z5S?8nUMdr#Rj)KBpQqt(ISc zIGfUgi5`%2B&|A*XirD4)Vhq0q8pFpc9-CPoV2;?2nwFxr(x4~+NJ0SyFFYS6gxT- zeuCk1%X5-*!*`XtS^kUA;sm5JtxmlDNx1_N?b%_!i>O&dLn@$ZRU51|i$&1nPU@w- zFB)rCR~B^GMaI*30nU#H*k=zIXVUN^^vDUvH&Bc8>}&PYwtS;d!=ThCny0Cze~Z4K z+sXF_ywO6&LMs9jpcqZ=rRREP2Ws228r%z6RUipSkd@X^`vDTmgc8mY8Y{IwOMHWD zo3@2#F4?;SHUGM#V+N`r*^lAU-_UJt`+&@ zwc!}6m8_~@nCF?VAAi}#ehBh?U@&rPzgGI#+{swY^a>Zy@LcLQohN1p`e@Cf^oo%$ zIestzu7=|~{MD9C-GttHZg~-sOMK~TgE(jrle6Tz59(;yV%di^ONuMnz-|r^1ua2Z^6%HTOU<@F>3ZL$Z%5Mfs*WShDAAhP2S!l` zrT^LUG(Go{ahe!_IyqPfP={A$(fcRnIxbbye@?>VJ@e!RB!iWNhi|7rS_U&|;MBJRA%h1IHA zI>IX*oV%=A_xtO=bFLE%|0pRkykY~VW4iR5bDX8F_z4Oftd4xPup9-fS^r3r4GukubRoC7 zo8DeKBefK;cUq=KZljgKTj5#2d9?G3bR_#BkYzSFD(g^QI{=w9paSZY=-m7Jglji4 zQ2*vw{QZ<~sx3idm#Wk%$si(HvJvv!02E1E_3>=`ji;7?-Zk9dXhEKTStCSR&~>6; zKI{931)7Tiwv(EqcOob9)Twi0jj~P8Mm!y+ zJTY>~derM+K=})5%NW!kX?SJ#=g?QKidUxfO`#FKAM;)klCz4KS z;cae;X>oxfM6u~Qqh6r;mPguppuDSEHl7ynOG+gQ<{VTXy@S>k*5P-vitC z4%bV6QdEL}H?L;9K+g>=WOLj_R?}?X zgDv&+5l-QrD4`BLcD?yAhGzRYog=nA1`8X$y0$=7Ih=hIcj?_J*ntWvKR zw|r1|AU;4AtJ)Z+V|kabjv1+zpf>aKiMg-94U#_zI=Xfv&S7xvT+{m_5smoydMfk` zy^C544ynHyZD9Ww?!`$5!<5W!3$yT?xI*eZ`2kx0c5DXw^~SvH+e@$AE1F6!yNbZv z;SQKPJo@57X7)qZOavzH^5E75Q;w9(-W!{;LL+Rio+_?}ZeCp8s$DH`A*C}9BItdH z>{GYK>>emX)oIkfL`A~h)Cv-{C#QJXO_U<@_l*jrk+Uu#jXFh$O*;t7&BO}Wd34?8 zTc!3B*D>@Fm(k~L+4eh&3Vib`@32q`U%eMefG-NZcKJ#;PKDyG&5?u^9+C?22O@bc zS2xDX1Qo6Az3;Gr*k&`TyTStc*_R#^z|D7cGVbRBeq-eiMz*XSb>!*iw=8g#HC#BM z?-*EDdw1NlIw((YF-#kJrCS1V&akH`RGl+>?Lbtq$Z*L0G~fo>C%G#085@JSekkPi znbL1ye34@_IPTOI{ad{3Qbfk@OBiUT^b$SVhuUiD6BHyv>#muCPQFUHV-GQ{S>#^h zeP=ibFi<-S$sTtrFV&Y@nR!snAI=$5aQjF`&L5L`^l@1!9+XLBTL$v>27`}hZbmng z0hWZT5cmhLh|(Zg4jXaS2H>B)%ut%I)|~Ge+5xM>8mPn$)t9ka8fWO@25iPp=6J{_uZxScLQxGUtP*j?Locy ziH&J5RC-lz>cJ~q_f=EFrX)dHijssq35Hmor44!`@z!2!xcWMzP%!sO`lphl6L`u`0`MDQA~g$3%Tx z2bN`M`6r&!=Oz!&@>CgeHQoj%eL4>F_%hxX8A2I#ra^B*)MV(A3e_a;Cr5djgw0jY zXq!P2$!j}RPRhw-1&s*TfbuKJxfuH1GbZCaRlANvIm$jQq+xhXte9FqN;yQ;#~R5U z`x=Jt2;+Qu3cSjaLK+=G)$`x8GHxlnk$%M@D%)De@UG+W0&abKgSoA1BP;8D%x7}| z9;6!YpDXLfVY2fN7aq@cKz+G(0pE_r33z?@d^f&osK9iUhf^j z%Odwd_T}R~1=rN9cl8@}uc^WL~456{rJat83f z?L=qjWK0@mcL{_)RQNyE7Y=7Wu3pcEcJbQaS!(P4R;VTxgI1Aju=8-|P|DWiJ`l}i z&0mCACert>**>NqV{SSS8A6=@VSEmCAzXd(UAZzQi20wUqsd8IRcNNHyspJvYE0v) zMDtJ3HJ|lzbY7$IYdyz4h=H(42VDM~CAYl_f=mxkU9YqJCca0!k~y!~I+=LGed#kJ z5p5=$Sy1`t+p&oWRAJ#3NtmnCaqfxNeh52dH(HuaFzkoFu#hOx#75okOKMD&zS1co z*~2Viue>d##L_ON84;z9eV=3u%?pD3!3y>2vnvPk>l?cAVq>@UOQyPw|8;AxEbotwNfCRq@ui2%C9j73i%wH%MMNTrC1GEiXK7zXN(f_-O-Gt z8EWT#!)$aJXR6KgdMYbdqyQaS$MrkoTv6AQaJw?1BaQeS4XOYrzhn1}>vPKzVcZoA zKUC@rrHB=ul}4*Vdz8q6 zVpo2%VG3?uk5Xi^_KX*6OXn7Yp4fQCpVJCF168bIyMf@zoc|$Fd#y+N`|hBAddT~` zRxGNocco5ejBe2Tl_SQnfe= z&?N7qMfI?ZVbP+iHv2y7TStGeZZW<}MVKeiWgs|1*@_D+o=l=2c7cx9=0xm_SQa_Z zvxy#bZSSJk(F~USyE?)jAO9?(3hmec5d|ubw*?cL5y$^h9c-Wga~Ra{&mD$iU%YMg zzP+LY_2t~%^NCkv^Dk?hw3uo8-n<0A;eEldI^1sj&>LY>^b27#3o>Ww299ReQU%7? z)?SCU-*ETCsFW_RHYmMJ5gzu`6rtpLy0>+cSGRSKH%W-mM$_I1>|))(Yk=a#W<%}> z2{MrEQpLwM<`9m(}Rbityh6)&xd%zo>=L{637`s%AT2qEVvXa`}f#(WNw-T*vCU!IAo%%X0&18oUyr&cX37#c=IEJXT^JjI3s;;rig@3H( z7&-mb^}+b>y2s8x{=Py|D^9?$j9jJt{PLINU&MACW%Xit!cx1g=g^~2fQF>qbT676 zGi0rh-`j~annL)Tz^rwJ>;MC!KB;fvluG#nB)0C*pb^T7zGrm;L{sx{`l^b{Mp;pt z^yXUk=J|(|UWjZvV1V_s^z3<;7X5y6EDGE|^u<)sn-0!dUf=Cg~`#KvMZCha;eT^ea9zzj<=i+l;sno*Xst}9_LBq@%hRK zc^3SNq_MA@_KFBY09-8RMa(@!?m(h*|v zG7Lr232dSx%&o#~M%Z}y**1n9RZ-EUuU!Y`xYIGI`=9C-v0?TQ33&&CSE9YcqvL0G zJE6_0c@LANxAc^zb`5&h8fr%I8B}btiHOR9E`>)x`ROIEpN#)mXyFh!gJ-vFBItAf z0K46<-0p-=n@eB_b>W&*pZgnnSNXN`{ahij_LPSsdyxfHp~%XfKZ>5c4w0E1gg37! zTc+<$)3MJXdlv0mNno;$Td&jMEc1mSuwwyDTL|a9_G|s$5;^kk@@?Lb;|ti^7z*li zpzkt#tFne4`CV~MifkZ5S%97`n$F)L>uQ2EaxdLn3+RF+yn3SC)6kbo#L`)+F04-Z z*G@wVYr6I6I4Wui2)ap(h2GN{eqeTyiQrZ<-B_vF2-8^7Z0mw+R`K4gG(QJt*^0&p zH3UGgb-w`pZEa`-2%H^TgH0$UX$?mmF6lnVsJ#qRvEQu;jN&9!wgetT*Y)7z_xK5+ zkPovHG7;jRw{O9^hER~5=qtm=s);f$$T$t`apw;MspniVj z)8kewiuYmu9@8kB=YLS_`*DeP9-5t3737Ke`(X1+ZJAh?Meiy@N0kOIvrtU_b?&wA zF-!XLwfGy62T{D1PKwtk2wvYCQvl?%LYhN9CDm_-x5fN)8o%OR_ZFfzgvQI^(z=G= z1pfe`4pw^pQ$LAQ1p3r(B>^0M)%6(hS8*`oIQ?IIT~^Iavl}9XCFZGMT(McK59$@O zZ_$2-?#>x+^#S?m9UX=G!y%W|Ox;IY0K_~9GEfIkZJ#4lz@kr&lAw~A6` zIFyL#h{PwV1Y+Pu`FJny!_*%%!&59)XID-TPbJOna*8>$oj^3l>y0FaJt;{l$hfFO zb7k3&X;IIF&gi;ddD6WMY^xx7xapA3s3I3~KZ%F7hXVNAr>>g&D_u&Jf(+o;#qYJv z>TNeS6gk8<7)oXYrE+_L&38X^xdQ*3YM;DeAz)CBf3yuqQ3ZX#N@j(#xi4imW$IQY zh=Gzw`xEI}tfpdxB^}Vcs`?o4OLwFyev1?t2#|*5w`vBhf1ZUTnaF;Wxp7iuA8Q<^xkjYY4bGyb7rWS9O*1R zFJVV}B)LaecH2gn-QjiCUb!LKFG32MR)3ZK%I!QIHz}!Pwi{wIgBpEkBXpVt^=E;V z!tM<}o2^t0cdVA@|F;3{-Gf$-gHJwl$VQ*ZYWIyJYlstq2ar+C7wpYa_?PSa=JEx7 zSh?*6Kcm)?!FRw-vTY<`9eaY<0}X2(MnNS3*a%v>%QF#Y*G6d$W;g{A=Hw1B)D0g)23b^kFwl_A^71dYoNvFl`u6M`uj{wao4_|%|UGR{s1BafcntoG^ zL2c-U+;8t5{CZg@XU?QXzbGsR+AD_6Uzy^4>F5tH&VwLAxbDh8SV=QtY8c68^v|G5 ze)|m)xy}C9$+k=edgZ=2oJ>FLfp&aPA;7CXi%wk|T&_?NoZh{bYkZXXeatyT-cnM1T-9iYc7qS1asCfzxby<;03-63!*$Q zl>dIK#5Md53@erLxi$LRmYUhm?AU*}%F?$43$T@gz2JJ+8%a`*%dnx>AO>v3WK}}A z%Iq!o9=9y&_ICn~wu)Q4VBduQhm=~ej^9>e+r4S)Cw_KNI>)$OQfC15Q(w3XU28*E ziB_fyYzbq1C`dXAx|h=cYZWpne!YB$9{~w5u$n^PB+Gzj{7lLr!TJmNA+vzeZmI68 z@1N&^B(S>#)P4baQLB}19C-oG{-FxQE8=AKFoV#_3Sfb;bOX^*Az}JB$ZAm6v;xGq zKux~Ch(qb^U-kt>KSRu;gn&J?%L`3w`N$*yna>>EhVRF*F8|w-=PO`|Q0hc7ou}f> zcXfXo-EDZX@O|Vblrx>6{*`IgI;pviIWqL=LUU1Fs-QMhpN`0NtD!Q$_d^s~g=D1C zHo=X|43$Dj3!Y^D!SRaVFBBcCP0q{Y-&3Q=Y1c5z-Tt-0{!sz`l(9$K~405@S0Ed zoU;UM`z;{H3%owS_w8Xto^w2*v@QRdhZTjB&961}Q-mphxH#!TlY|~YY_bnS$PcKG zcm6`#=^fp5&hyZZ74e}ikKpaxJLjNPa_()NMH~QS%4`QkIFof2KHHzKY6xUUAGhb! zB#FEd$T!N9L_VVLb}pS%T-W?_H{{U1w(x~kShN=>r$56wm%d@ zp$ig`a*EGCR;oG1fZ8<1yA;n(gYCuqqy$6-{I@~TA5B*J*B(s8W*S!Whp!dgHTMin zh~=x*8A|2zsq=`$BzQNP*k-HybPGsa-pk`U{L(OL;#%{DO+rM`Gc`|M5wv0q$TZ~2 z^$Bs(1;|cbAH){1&q)=tLAtfy=RRj(+0Gukx_0GiBc$yk0F zq4VZxZ_@D2U;T*F2MMQw)&Bc*0`H|7wi&&D4Sx~_re{W;dOn=HTNn|acEu)}rr(kd zN06Izyp1Q`gFkOPV>R6v$b4}vaSc8s1*3M>{|@PyM^NQc`Lw(0MFvqPB`fNxMZSII z>Zjl{P@#0);Z*hULg5PiMD|mEW%%vidf+_p3at}$y>_u85 z@WpP=FGoFhcRp=-+3=#T;;0jdt*fn{H9oE*dfK77UafPxlCn?7vbaPJ*o=OM8jOt% zRNh{(uYv-Zex1?hZtdiMfLAq3qMaPSJ}+ihyaFOxSUn9-2tWOLt1K_~`mN$V*}}(< zo8UNF+So11O~y7=f|{Ir+A;d+n4M=>xvHQgynw&Z4C)jyo1tR<=JY(?nGPdYagC#| zNjX_#z;3bkPr;27wHjIm&^qWLxvw9z~g0oeZe`t)2b z>T*u#olG^LXcv1Mw4X&~-FuLe3!HEJLPcHdQ#(K%#Bd^ct{C0(d;5iT@e5AeHc>IC zRht7N)i3lVtM*oEVo`ufb^b%+xE~xZx0FxvNBchbEZp^ZBip}UXV`F@Qn03uPOVC_ z+b=p(*6cj&&O?lkj~^WM-5AYg=JUSnL)JuJ7{1880)VH`eakvZOR~Tpgtg!n|8$$OZ{s*JboEM z*V~$s?MI?@l}r}e{z3E6_**s4@hc43}&7jY;w{_@` zjoF0yjv?n8SZ%26460xvvecsHV#)7jf#bhI+$<0kOS|lIPLMvmi(Pnd zGRVC(1n^D1w~Wpa+KrBfc=`yyDPNP)lhm?!QG=h7uYh+S@KWzmNo7@DPn(B+&2CZL z7Nkc{@dga(P56BBN$Xkkccs8l!(sMMH)gIz4s6R@{h$&Ql|In1`!912gVj`4?>{QP zbv?!^%iW2@{-p#m)cF121`fqIeD@HQK6mV|UZk!Xx1l*{JHg>NqZMeVG~nxQA8&lk zLe-?|=e|sJSsi@r{hwamPL$5+gm=1zevamK^%RkN8fiP1`5BmhA3U@y9~YdEda5RP z;r^UhoC-u6bz;0nR-C~v?ZRJ@1DEX)M0J}uo#48%mqeo$Ksm>>LB)6!4mGKfUJP9D z1ksM53iyKnEMJ2pVf_>eg?le5tUj=XJ+kelBBfq@cHO|cFx%^$dXe$v*ow8Z`_CUg zp%a%bsrea)XSG<-d8LotZ~9S!QQUbpysuSg>zE*Y2QIsf9t^j5K~#Mc3fn9t9G*!Q zy3tOByoD`W+Mp^)Ut`=KSC~d5wD|20p1XJU|DLm9q^uj}4E4dH>in;Y`2Ay?Scc>;!%fW!x?L(*e-f<~4 zX;fj!>OuX_XMn9*>{lM$;Q(Kzl_eBJCL)j!bItgcl6~eh3mpI(QOPwvA+;B1Ch9#e zG)SM1-^QC$oH_VgBgK(?&rd=2>3C?SI5-M*wc2X(_p3#Q3qA+8l_;sx0qakelT#c{ zNPNivcyc3H=X#YStCZgh)2uE>XNmC&HfTf(KEl?^Hgv^~qDD01n|QNBB5 z=F81?X`^V>^0p*Ex{dr7o<+j#NIzxBy1F3oPBXmQKTXQk@Uo&J$Q5G)smkOrq{g<0 zza7KHmeX}l2;FD6{@BlesVEIN)3{!gOn*6)Wu?0C1e+^t5kf9%*3X670) z(t(bWOR=R&mdy(O*$o<}g!0Z2(ZAm(PHsTJtY{Wq|5UIq6XKJZIDG^=!K z5PaEd5s+aO$I@?N)`s<~TYuJX>$-G70(Vg^O?1KFE1s#oAuQgP9&@L3tdv*R`E$Xs z7M2T9wzCS$DD|rMROacjE70kE_XX^wv|!MdS4Qa5LNMOqMDpbC4W9V0qwHeZFS5hO z2)FTO5yAb?lLhoC1+{XE-KBziVo}WK=9)C1#aA{3mc0~876Dw%1gu2MW|dn_de|); zyo(W~n5?}XDu43}EK@SA<||!%O|0cSH5T0Fzk)R3LP3mhtGu$Xs=ZV@isLniQ@S=*w?chL+sV_*xSX5pWz-TPBDPjw<5LlZOu8t@y6tnthk zn*r7D+Tt~4-uYg?!{T*P_t-?)hpRD_mU_oD?NvVHsW~&sWM6!jKe_fYHuHs{%0MIK z&)xorq0oshb-b*mi9Pz-st*}0dm}GgiKuyKW{eH@mqsG!UFI&AQWhV3cH19jiLFHc zR)Yqylo-B*$saE@DR2Rm@9C^QC>NmQ5+kwTAAPdmQ-GF((m`!A7-fZQf0~A6SSWMs zrNHAEmG`<{6P3&1p0FQFCLcFLLqIc#LHePOTb({HpX zQiMLEimHQN@IihqihgP3S8yZ@Ut>cYWHhGHr)cu|NmVOb3pBC_Yi=O-=@W6I)%FQbq*pHy=ayJhy{A^moI5&jMyI(eo!?AX*i1uGC^_zJR~P80rP z1^fMKy2p`TGe-+*``|4Bg}vU^9R#mX)jV6Q*0t&5hk%Xrzw;&2qv%VF4=$uYGk@<7 zI;TFL;!K3F;JA@rt%X!}8FqW$E_d4Vh}4zp4nqBM10{DHFI3y3I1D_Gy1wP?_-h=% ztfNxup7Ac|!k%&XWL!V}=N!{-I2g~ES?XvFmG#q&ica}gxiB?-E)Uwjq%wbFLD$xi zPT;L@pEZ`YNPCmVvSZ}*q=P2RpgNUCsmD)gz-E&e3D-s(O3&!c&{ssNh3_DsVq38W ziApQb*B9>~4md~g9m>(rWfm=r7WA95c70%}Od6c5_#}e!eK!#hLJD;(6@3%=J&`6)XqXi*jauj6XVK7n(YI3dJ!>6_Ha2As;rx+!SF>kQv=Dl2u# z$M#=iUu)jI+&d8W6{|8-$ldMS>O!33*=fk67ql%5?ot2UPrd!#dOd|VN&e>5L~IK# zS8gNROFd3MWSC|lk5B!$s&Aw6ltZ;p>h_$GYtD;)gOi1u;pbNbS}hBmpXe>WbWma- zig~XFt(f$Bt9g!AgLi!hhXCNY>82#3NSZMkaK+RqO?hqA+KrYxcRw|4_actAC;1cp zY7fF*Mel3${c7lX>idaId-p*ADkf+EWW;9)RbX8RlUmJkeQc5%VqWcct~nQB#N* zXalc}-;>8Dr@`3xTw7qRGJ9jPGW!sK!6T`_euT@h>9NCiFg{!yEeOtzKXQziNA~pi zNf)`Bi$SgBu9EeTlEOoNx;nPTu37*eJY4Yk*{7aVaPotQ7jgzo`wenX4^J;u>j){` zr-cmSj;OnouBdE%$bGZ?##G$c0d!=MPAg>CDD36uGn@f<0bDClysL!$C7v_d$l=dl!q`;WfO8G1Q|3ra(t{ymxOLqR5ttoewxk+aE5|mF}pgVC?vv$7pMJ*b@zn zUsFt*C(Gn-@@4urUWdZwQ>fU!sB>b5_jl6TVUN^i{;C3{8SlKV;FW=(Z8e0S<4cFa zfTcal95Y!gNrRHoB851gFo zMIBhR2@D-`h!g_$jx7Ahy{;h~B9>7g^`p_Zlg>H(C-)8Rk6sNtVf}8wc;)Dq#(PMM zZt{MJ-Uka@2fh%h7W@71O5G~gB#sSRxZT%tR^hMPQP4&WeCG+(u3-7U+fhFwjlTeGEw=+dA83(ze6j@fWaQr zNrn0lNB$$jADH}fm~;CPdGBk^>yMd%GAYKL;YqL46#|9Q-^I7)?)SyHjy=V#Jvn{S zX7#)8rG+H5%$I#~MNZ|H(|L@p-Z0Dj8{S!Tz1L%}^R?uC=n#Mo2RB7Z`UGFWL=&i( z_*&tz8^Px=H=Z`6InWEydbw44HsCqT;HbiG;h+)FEimYe*przuq(M{KGTAW6wrpiZ z*UOah2}}D#9O0f$N~0Iq=0_@nuvQGdtXfR6A21<>ZNX${)$z zC&?B6dd>4iM&uj+>P?MnkfT6&{!zEaWW^Y2tw=!wDXhZLb&_l9j>b;;QHm19k6-kbPdBRWLIRd- z>%F^VJGt*sRrEk;qi$@vF5dO*OSzJd!nUa$+J-QKJYpX!UFyAR*31P4e*c{9_xi+f zouaREp)QlwH0BZ5hlCQy#+8mg^hiTd{x%H4~5cgr_QaG8M zA+HUIWO;Y1s9T;mT5>vN*0|@m%0jw%d14m0Gx)paq(8=|-S%tpk^(({B}FhrKRDFb zMkPSh3TBjI$hN86IRIN#zH&64TNz74uI1_ZU5EHOQ8Xo&x(3@QaaQXXtOJr={>#~kE@O?ORla@XwXq5p!&f#W<-dvt-OxB+ol%AV-1}p=Cjka zk`_rw<%39)gF9_|4fO;01)iQ=yKg=F7vfj84BS;_Y*B~5T^18MK*W>B zM%8lBsC8v_zVlt;Y?3+AN6Q~r8aru0f5zt`R82GJs`wLjz~^s}wcXACrOY#@V`v5) zuX(xTp&HWh2Jv&d(K%acFB>$t;YaMVdeKjxk%MJ4L+rj%F{L3+3_mT$ij|=694Eaj z98|V!;{jxn!@DnHUC-nW8a(YwfuEN`K>HE7FbV&A$Wi2z3NA>*)$gdq;C6gu*2WU* zBqCyN!%LtZ)f@BJ`Gu3ZHi1ZR$ypxJ;7#J7idiv=%@<~7&0`kEnAgIS0WbSIZU5Tp zW!tm?J-6%KQ0vNM8q*dbK(QY6%d`L`>tzQ09!os?jPEuqPt;k?ywH2x1~-41D@%RKR0;1xHSp` zf*nf&o-G`_BDQS!U4FTd>J!`3-NL+Bu+JH!K?J z+PPj=YlOxvA>CyhQNEY)OZ%hQQ)10cKE7embr%|DD&M+|>%P?(s!*Nn-vnaTa4#RT zO8G_=x4zLY!N0zgerh}hg_!%reUXoQ0sjnIjJ^9u{)*+$LuXTp?u5d1RUo%+Ey0&j-AyWVBk@H$c4L6*l-fu)gu@s7r~v&qX(I6_5m!eVo=0!Ji%Ovr_~2x_{< zpojVLWJHKaI4CmS0ang5)E2w5BO6L&*?OD!rp->l4)lM`E(az{GqbgGkBoha z)d(yGcNc~X22E_S;ml|0+8;zO*2kK(Wkud8^GCHMCmJ6IM#R&Yi1^o?uXx(#ksL;I z0OU7$`f(*bb%#mmz0w1ayAirUR1MBGDMk5p9GzVjfLed23O1m&;~w>f(geFv!(md9 zjd+Kzo}WU`J(_UazVoxa&2ybFWOlyaB=#-~UF#z&#&oGTq^@G^lFxU0Og+oCXDccY zHfjN^S(RJ*ta$(lPyM>YYY1uE(s<52O>81YzJH8VChSr^L++#y#(B-FpU!^zqTGah zc!KfD;}vAO)d);o?XPg{OjG@KfGWjg{OJT?fVp_jXZ&xQB4HQxjWG$T;eUtv=YQf?o#+>63#; z(Pkkan&v|ok0pP2_Q@a`c={qgT!%rnyA}+wLu{*>C)1Al%Sn7P&pn#5XbxJlD2&%- zbUlm4Th7H@-a+(4pW+98jC0hwJMO|$b(QnMcmlMe6&70fk12bOD=xtMwWdC$o+`M510BxY*DZ?{e&bZ;CpgZ9f$BiJPLh zgx(E_X9(UmWZ#x=rI0?Mb2|{-HM^2M1^_ zveRE1C`?Z4zshlP6eA7K4{wH?xyRwq=%2AGXRs=Qy%J`t!0_utcJEz&=5D)95B?U7 zoSm@zzgNr|3^VQK&Dxb#fADkG6lYXK>TuCJ{vmgh1!yX~($-}+N3-sZrGOi#S3S=a zM=*xvPO&#BerRpeo$h|zO33y?9tb*ul2;`k&kdozJU-;lo~t#9yFJFq z=SJl$=1bUP=!1|EfyvPfI=lLOc}8L%1Gf;IsjsO%rFsxYM=&+oW;cRQ+Lc=wo7`Ih zTf@sc;)C`rIW$e8f#c85#LRNuOCKoe#m`1iZ^F4bt1FN{VW2_MA_&5xc7Q@ zE0d<(mCvdT4o0JE%f0kHK zV@>L&fMRMmeybV@VteJAi;(E0U*Lxn-yO{I&{ExwSa)7b4u&@R!`AyRZ3`yy@9!a+ z0WrRRpRN89!+V556it1ZVc_!ybZnnZhXXimRX`NH3YkKub}u9gL+s61#NO^Vx&d4w zz?@&!h;Qv*2VR3>b6bb#=LWm<|Ik^xuKGUzgcvo2r9A6m{Y^hYj~}K<9b+nTIR3{* zTgk8IAMG2CE5BYBhLndUm)uYrIQzaMVX#jJr(;(9wkNQL*HqoWkmVSR874A(4TdC$ zhRYQ3Zk2&^5LhB^x@y5wWT zyynKY!hH*tp#OuFe?ZA+J!LOUjAGyL`VHE{dGp7d!a6}A*_|F7P_l^o z-oLQ686YJgimMo|O9a1MI+bC0L#agyihmw*E=d3meW`eJ*Gk2_Xc==u(-c2m_JbNi zHK+ZLkHU&sS2o}7l4>jE)o$;ri;pw+@shcK_18N72>5%|NT2iX!v56&>%8oCu}L(K z{glVw{`HH_fxU}|sO9k6Hs4!eAQID^f~f!|wLsZ>sf+e>`FCKv_()sW1ez~yKH})1 zHfR%fTVouK-ynE5;7SFELNV9_-ZG}M&HVz&p=cW50OqgjVrK0RmUMn~mI!@ELD8I+%0(CodK|Sx@L}G5G-a}lw~B)#_7N8YHNsS&#ZaXS`3JP1OV+<3 zhQK_j(<9%ZQf5+LqPcTKutQhCJ!HTAk)i0_C(E4u&HQdhPC8 zVl*6iy)$(5oONktZ=Ts9_K~Xng@6CSue}4)2+OCk{e|8*zdF6hI*Z{hAUC0i=%2HC z;g6w%tz0YSTk6}38p3l4+cN1rNN}O}Lu|iMe^F8J3#E{}w{j*%8RI~(|Ht-tfwt4- zE68u>l?pDdt%850#LE9dqnif(etH0?k(L=Ys@fY68R5yzLyQ<0M=PAszPnR+l39{ zFe7~a* zoCB=EEz;vDg0ec1`g~DO+Tn|6u>Y$-u}|lMgw+#&+;OKfcW->`x!vC}gC!@i(JfE` za+aV_jn>zIj!zvkC|A(xh)*nV^X-fN`K`-gMv&W!UQhD1UpeOE1at45#fs5qGOUyq zFN0;-XVB6$S2=Y5VgL!;AQsC|HFjMfiRS0U?T0Ey6AMSX8*t;Ds zO{&cr-h_%?LRN@v<*)o&(Hl{lf|}wCd4D$plNGFIznt%K_>J3Rt&wgF&A4B>^mWdo zU86gke$a#Pb+MmLJohLcH)sopg;?V-}gReNJ4>ZS3gfjpGm~gJa>yr>HB#)|B<}i zru@(J$z1VC7gO@lW;@5`SGSF<+3a6hX|E9KyYrWaK)>%bb$DYGT?&4dw(P?-@gV*O zBpp174P{zO`cTX3FFMcDVRFqjY92j8IGbvv|0~=$u;|-=uTg3J|H7pukMCd1W?dYB zxy!>p{||SWjpBXJ`Uw?#OqAKdi~qA~XM%#3l0PRK0(|mUj3#-O=}b>Jq<1EOF~2Vo z20yE(e|vZSKghK8@s|JC;0r~wy{<-MODxY>1vqTwk_0YQeU(Jhy7Zf8m|teoZk%qg zIjNcP{{yST6z^Bb|4Sr?1B$=u;lAFT@0*cXBD>}nJz(7GsKgAuG3RpWtxH+=-Tw#B z9^L_bNVvQ5Rf19qWu(okWC^OErK%Z{Z$P!VXf$y4_^VxJHu?Y{sl4>N1JKw-(7M2~ zkN#{gUT;vb#)Ke;jn?y3Gpu`nBcxMT2U)wi+GKv5H~#;)dh>Xw-uI8cq9oZvg(j7R zyd`VIR6-)6ge+qTSxOSJo>aDM*^_0mlV$9R82iqU?915qZDuU9oH^$=pYQMS`{(!X zc|7JZ=bZaK_kCa2>vcV^F2dj4CGKZZwf_fIXFQ+vqv}PC>-S;}7)15bK`&;71}Jnx zU&Bgt1OfJ4?Q#XV$Dm#Ok^(~~ND7|T=sYGYIEp>?_J25T?R$hDf*IWZKcM&M;d2h0 zr|!pq5PqKFYhnyL;_6PrV&=PZ(E0}6mvDr^;i}P(guStF!|EtZ7yOj!e>62t6&`s~qd@-}UvTN~GuddF?{D-yUKF_0Bo533 zzjQc2l=&Ej|G7&YaTOQ6yCfp{a`|>*fs+yAc>H&jh382N9=*r_6-%6s+W#x|dYtdF z%zt#-4w1`Q+~VwY##98ktbTv6x$cH_)bKFeF@V?M%vDCp*+XEidT z|6ls`5fVD-N!4H zAQM#IA(nvqh*PDCm-b_T=TQ_fpYG7UNeGbrKi+lN?BWv8mV-;8Cu{&ZYY)K>0Z!CW z5)I*B30p(bCCDL(W4sd`FPBkfG3|8pJ!|5D7L=P1Ca|XKp32X>!?w$EhPiely1O??UO|~@ z_2T>kFLk~WgM!wdx@TOr?CM_l444)gt&Y6jI>1^C4XI<~XCEiOvV-dTV9I zxoY6&PjWIxVs*ICkr$>qmeN&cU+ugrBFf&BY(^$qX%Kmj#C737Ehe^Ee6Hos#`}Wg z0hnVUBS>{Y_y!zKwzV&Wqz_Gxz@0bsesyBcL~7I@CAqTDIZ?;)|4zQ}lk2t7y_p+@ z&zlXI@0yRUGNvH*;#4uc6PuChWmesI^b`whc$OnxE>lYdrF zt;wl;t4?S`7s0Dg2Hl3NB}tUt?f-k-XxSKyB%MfpOd_~8Y#`KU0;t^N9_Gdwx_%DV zYogW&YW;`jNT^>I)j6@Uywpjkp7>4OG;0DW5`O>U`0&2iD1u+d;|*uDWlDk0#`FHw zhN3}fTGEDe9eigxnBk6pTfYLBIc&S?p?|YH^Qg0-d+pU4U*Vagi+z4P4g5SnT!$Tj z6PK5WWp_)GsKVrrW+d z(|Pxo>aOcMNFKe<>C;qq={e6)V26dKNprWx+2k15PcNNQ5N?k~+SPxHBl7grsNz&x zqKBd5H%~|(eG3L9c?!3n)1GzIqukD)Kl9M^t(hjgrJrykk$Loyddp?v%i5}8bocN2 zw+6!>BfE7w53n% z`;@Flar4lp-;P}u5@-=UI&|F-A6O(h_nc@?1u2cfqO@Qmd|B;WZ@~UML3#mW_AMl* zE3edO9cx4Bh%%p?+D#ih$-L10d%3mCEM-A)+NQCQ%bv|MJ_WsY!vSVfyDHvklIyqT zpfXh6jgo*Wv6ffa68jJ^xS{v5E(*)OW1DaYF9=LNYln|dA~}6#&r{kTb?`+37Kzv% z5?Xr{Nwq#TH2iqQlJnb*^)VBh_$Q5X4_*v&v4Sa-$LJPz{Pv@ixVDcckZkj2<|*r% zCsO(xN2>Kb+Jbrq;8gCLMc1~BM7kM^mn5W@@?-1*SxfU&%@Nlo2A~>wZc$bE3fyx0 zi`3GoupigY!sh`VYNk~r_SNl9Y>TnQ#Cdo=j*tJ6%g*fD4NuTkz8>tCFx6Z_wSVmF zO##aFLdVoWbdBG7d~f}IN{9YTiCYBKT{)X&(b(E8L+Xh2=-clavK#us8({c@Q!xLO zdnI=BOZx_BcHzHokzSwEQ)m81vIbZ9NG9;N)$2$QcfqAiUrqZvRhM!*{FOaytL{6D zFq-`9?Km!2oddfJD^zW13)?p$MvW<#-!sJ=8@xL&O=n^jy6pI_=e=ow!TG5okmadw zC?H8h2K=&O1EwxP!m7lFX?f%p7K5ob*RDszIRQ*p--r*ex{QRv3TY9XtZ|&fka{^5 zL>;21w}&C?favgzEm$1t_#@|U-FRaj^%q&x@D?IbqOFnJlxTL*iyTLX z@pT&G6NP}fML-*v$NNC8KU&GS3hfc(T4Bkqx?b$vSjWhS;d5Jl+t-mOJB4ViQ@5iX z@0N!VO=4IrLv8Q=91$06%su!M_!37fI~1&0v1uxyUau-H!U?%vO?XE6+#JZ^H~(&p zOcOix>?-g%%69;blyU-*qnloD6NFL{0I&JUx`)sX-d=KJ@hf@f{AAC`VVJKc_yr)I zYGcGgL0?siD7tX}&ybzV<0&J}k~qEO-Oayn&q2{^mVHhp?VuvTis6-~QRUgCcGY@G zC9oRphVDD>HKNw6Ni0|_dq`n=JA~$K$-=ZV5jDE=GUVYWmt<_J4p8h6>&qXd*XYBq zE71eNfo8|F^aLD%{R{`<;PmfeARoCBWm5Bo!_kb4=>L@-h`4!>L_m|U`LA*-DwH9X zmb4bu!8<)S-%6!t_1@W=xSSW@7zSt}*Gu@}O6V+u6l@NNrxj_lVQT0hZ{P(@zh8~u zzjk8R{E_+L43*1?2=0^cOhof?C*Rpd-^UG?_#^LGqD$NG4|9 zkuqIMHKHJ+$yo%kPY;<+Zh3T|k@{Lt8@bMHR|32}&Br#3d~NuTl9c&j*WqV2{xMl> zNoyW0gt28beC~Iq+bX*YGtz||Fv%*5Y5(w6S+HflO!1xFYmRq{tstYfRZ&RNS>R>2 z%ahd21USFOkaBV7;Zhy+9FUPhU-Nutj(?kMcNHKi{}vM1VUS5t!GHZ0ar07+kCjEIWboJ$wkf#w@;{?)I)Zz26~ zU}2|S#E)xuL7D)t1gNRJVr#}v;9r5H0ZycBH&KLFw6={k7&lE8>N}2A?X{-^i4G(s{~c z5dIbzK78Bjs&?M>=ERSm({8c=Mrv~pt`!LZV~;Q}f8xd``tge=OI{0Neo0q;iv%<+ zzn_XscP?pH^IJtBND|@_D1ZNf>X0a<4$OpxtGHe9U&8B=U1yi_ZbMtn z3On;SAneB#Nd?lA+|cX;R>MNA8k}Oz(}F0#@%7inn^w#7FvAHXwfQfEpmp*Hr^n>` zHvf#ak_Apzp49nKPtwvw1h8=Q7O7jx@|yfeqT$sf)Cv&%YC=}z0b5TWH;}?N@LlAZ zcJ-f5J+*e1!j{5ceM8Vlv<=>yQp#3Z=Fy)zf-F<2uyTbMn_Cs%Tu1*3aC>pz_*l)ns6KU(xUGQ^ZNQkiG<0V%blHvJ6AJXd?oCwm9mH&Mu~5T##P7;Y{&1un2~#>1yWm=lJ+!ta+Cs)AfsZjJuu&)WJnqY7$R12{ zV{1X*Ss`QIu>s*o`foVAKfF9Q>E$99@y2VYrVa`qFv^J3c0ka9xX-!$CDz_N;@oX= z(_>nsC0!3AIF;YYGuSesn<=)tMEhvoo;E~$#KmoT6!C#@?=ru;COfy3={by4$*7&D z)M27c-vhI#s8xOo?TnLa!T?GVHy9y~~_ zd{6m0a2%4l3$*;5uQ?Yw>`+c9DR#y%}Lpf~1fWJsTrg_;t&mxhGfN-@>5Dl%d#t2cgW81`N2t!`N4o#dQDG z?4yOmR}+%$#fPr1bWhK!Sgu1!+pvu918R!w`3F;+PZ@uZcZX#YCc(=g#j>-x)3C~< zP=}7+)Im8^<|8w)dh^heL`myF#K#{Z+}1n~tpt1b&z5M^=vn;e;)+P`Q}2&dkaCDP z^7P=Qx$zRq#EE5_EzWZ~<;WFa!VfIt-Aq=!LqoLI>~{T)LSjAQCLdBb=Oh!bPIO}_ z}FembVNy0}#lzX|J>QznDLi9(pRvvtoe z4fyHGs~UT39g{jLie?bX(tBC>oov}hhD1H*>BfOu|Aw!6oOM)z0V@JDvF+U2#hAaf#mbJSvh)o6IfTQS8s< z6Z~V#BW$#5)K@+V>G-xBBIDolumyd5^2hegUZ*^3MH>#VI+<0`)#?bh0}I3E{WNTzefYZ5v)lvVgPgcxLBfzYxUC?;#z3@J_tGACT(neMlK~ zr&Z9JCyIvB2m*gD3hdQveKe!Ff0^p2H2=|-<_-p8$rgY0e{^Yy@5riHk4t3$cR-L_ESzGK~rE?vSha%ch6qW^7a`!tN`aseu(7yI=d$r8~ zOW(fzt{U`?)sQP63B*MAzCg$slzvZaI#&7QwTs~^nK(PCbI(kDx3ZH_|FMpwIwa*3 zy;xB><0EMVt?%a9QNxhFQAh%kyN|Nm`fxmsu@0VTsA4luLRn)2(HuWPmT$u_Z&rkL zdlL`8!*{;Ci8zAvJmz(9qT)TByRoGv6#j%Om5LzJZ#ZYfc#esaf6uoAb*M_2Bt^NN z2fQr_EGMIK7FtL=iRJM|n|=#;s#@4TVr zraFSv!uaMGV9#Vr4q8;~JyF*Tm^nxOeEGlYzn)Q3 zZe~evXaiA4!2{nQ)|#!adwJdJ)!04Ef!Fe+brpy^#Qux^m`XI*{3hQ;b(mPuznAqD z_3>#xlBxnF9Q02lcbB{$#(xlJIk|Xx7|LdXgMVUUtiMr*j{l@b9<`W*Wx!MYgT@P@ zYHDy`;4jF(qpwB|wEr*Y`d0VF*ZkKjdJLT${&zF0OBREuksmiVzgACg17*iHJnZNN z94a%3%QJFr{`ZQ_i~jv2jDnJH%()=8&LYVW% zPhU45WK+1*r0bvE)(rwtDF%Gjknr;a;dr2|Y<<37)Pbfse4Tte7Fn*trECx`M2dk9c5m73dfcb%Nu|5nrN=MUmFy!eZwpYuzcR>fXC{zyYNrwsO>+1R53Q{1 z%ym?(A{m5H`YnBR@KD_B7Lsk}TLQ2IV*DVv7a*niH4!L(Mw4H`j-%r?g{$R9(a$mIa4-;sSv7d)G_lXQXXEQMw1RRfmxpRbQAMe=J1vr@qxHe-%~7i6mzZZ zZB!62nb&DiQJB|*6S0SXi2GRNC+O)Oi@i_djWU!<7qf{XV)%g2-D_SW<}gpbT^q7* z{boryr&mubs@#^3Va`A|{4C?+YLl_%53>MK675>|wJ3Nddd?-P_RjSTwqcJc4Ilw? z5sDw!J_~d|R9!@3{iDr#u^hs+LijiCZJx4HJiy!9et7ZXQFrY^ZxUcOdFjYo>kzxn zB(e)RP3p9Gwa87Z2P*ncTO21X{AZF)8rNy&0B8|Age%=_r#5Q123zzoGT z3^I$xp$v%{Ru*$weFS9sZf>6$&ivq^b0Ue)_cq*3on#L(lv;=$yUbIZ z1?@whj)%JY#9g&nc|*o~&=3vl-ODE+2@V_GDd2XX>s%dS^h*+X`3xY3lF&ub5hshh zL3}^_Ezf%j6%WZ2{aZnvH)ACk_ywNmKnZ?2l!p_fcco6jyCfMB{wrqT)S}ktJE2m) z7UT>($JHoQ(J!}y-$DvV^Omv)n72$C9&_Y40y+rh`I7UVoGC{XoR; zutA(LJq(5`$@I5|F57nELUiy2lnLp3zDgL_4XD4qqI89qIhR{c2Q+eI?|{h%s_S_a zfq10n;`t}Wi-vza*+!6y(F<6Q{C0e)<{OXa@CvAsHi{bbQb}}>hj`h~6tdW)=|#$UVKZ@PWqHQ&~;@d;1M^;;Da@aC7L zkn@Fqfqh~h-}esW(U`V!I`vv!JIoOi7}$^iQ& zc5&XUPkl5*+WB{`A!y6y;>wK%QE`KJon#V|t@;Q$-lQ6e*TQ2U{k_A_3@JY8XvtZ) zUp{4T<;_bWriWE|7X7za{&*J~Nv~@r*i9mpO_v0DRNG)BwI&DkFK$i?jR}2oOlOTN zgWNvl=**%bk_uyYzGHM@(JrxGYU#4&LNv9CnI^3bU%z_Nxb@%DUu=w7$N8w&f&NKt z_doY{;*lp692O&og<$bB!b_+$_(;f+$PV4%p11!W3*eH)6;{5Z;n&l0D_FN&1q2}{ zh389U4+Oe$I$1cLd*uUM4K5TOlao@hI)kW*p+pi2=ol+Ue?gb=m!g&bt&~lr!kAZtf-3}L2dFQ3e z`Bu}Wwa0kOtRre)zx&?N3j1N?^@eHanzhJ|*vkzhBkwpJ@4JYdcdY{QC^*hB=RaA# zM9ykeH&XHVfauy9ZtCDAP$)!OhXX%1oxB}?t-bq0e%1n@eSBkGZUJRpahA?Ld2Hy2 ze?iNX z6+gaH*?t)tdra_x=6K$PuenF)(V}wtppUsT{En|Y8P`|a9G|_*BU<_-AwS9K{Uako zLz`I1%#FGR4Yy^n#t>;-N!%2br=&^qk}$^2L_4i)G4V!fIU$ z7s>i>F9wfsWygK)y118AZ70;T7PN}PeElT7tkli%BH7MIgea~PD3YlTEKc6oq(>1j zcF24MPjE8Y^?`b_)iwsQFDMm^7IkHA<)CJ{FdQKuVSBCg1?8#I*XN(XzM(@oGcteY zH-Cfn!OLXNlrqrlI^+n2=oQ@ySe|>l7}xtE>6?*ING9@WqSqq~HWKip_iiAH0|zb_ z#eIZtLF9acUU+Q(3d-Wze&?Dp^tXTP7?0@XpU)r%tDAS4kW{UUIfkiww$R)mVpSyL znNT5J_4R;wZ67SvtFM5YYKh9k(JG<(yLgV%wqL$A=@n*t$v1vmJAr@9eO>(AFONxx z9*N|3aRS$(;J^(%-xS5ca}scm$=aMqA9Az@?j;w~q=%s!-cd$9r9e9xT7^2QaMw2w zJ~vAgE#6PHki?#`Q6AU}eS2koSK?l9M(clU|7|`MT~8RT_$aY9RzU7}ZBs~)-fYhr zmzW0b_4`bq6Kh_H(b!lwZ*I6hwEIwq1v$4QVXtx|_g{M6nf;&i%ZBeFVZ}e^r3qbn z>&XqL=eHCIqH5`8>EF`hqJ zVau_Wr{{~c`+MSmBlm0VpFn zI)yv#0zr#GD>4P#ZQ7t~YVwBs5e=Y^~Ub0-f?&%UE zPm2Wh@Cj~qyjN4wJDU1&Qe2_5xao3aaqjokv5uwa{Fe+$-J^tdi^xzt{dkFtFDVQ2Bf7 zV3Gu$xWVyR&>iJrgdj(i)@<$JKoJ z=#XNoWtp&=NdErz+n69srGcvddzd4>L)doY?Se(w&<`A8H-!m0ZQ`3bpUa=nUuJbK z?N6PB$)NV3fJY!4|L80FM;pz(k6Fu_g%t>ad+a9 z^6Qf5tfPt5Fu`Kt}suJ zQWO4Oy^a)JBQbe8^=ZJKO4R?|M}h;Bj)do{HT6=gsgt{b5T)o-i4ubeVzM?M|m*HYX6A|smQW5!*z0d^SlgfvROM`#ru&8|NtBNm~& z+>>Q;%c2>z!MX8vg3}pdYng*@kD~k;aIAmi^`fn0cw;iqjTAd+N)=(S&uZTW#7;f& zsHUK*upNZ~6Q~n;(`DLBo94Vdtux^s4Si66@TjgrYLsOfCi)jbi}wT7{VUpMS{6H?Z= zTnYA~;^qY{kK6?i*o)Ch31N^ZmSsWT)r{pKPXAoWo`YJXdp6g#FVr8=&@-<|_2(>6=zMMup&Py7a7>&wZWwyu_&*tG=g@>t9_pG_t0~ zt_$&#J_(9J&*$!YDkl<9`2G$a5WhuNsc#fmo(jPX$l4Mmn)_1h{UREX9RHEyyof?Z zoBg#9y_2R-pkGQw6*7r&~!8^kx3_oC4ggy}4 zxn+H`VItrelvcYDP|2b@AVgnUS2wqq@q(W>*Ws)0zXC2H7^*A2-;%hterq%*N=c)X#gWhkC z6u?fuK>IHr^(Eb4IfM9hFUiiI-bUk`3eLgG^{1|8KppxGDfPLRzW5((`7VL?H5!~r zsL`ji!wHDLW*WNr@;>qJcFfFc;B81c&Xvnbau}B4;3>aqwTef;sCo{VHC>B02~z<9fpt zLof^UI9A@-qOsBf_|~pJkJY*2q z2A=Zp4Bp?5OH$J#hm?Lbdp%Q9RdTFr@U^+>qW5HhyJckgs~%!P5?kgyw<03@`e`z8 zS4^B11za`O>uW~-31nlMWsB3SZe$(jdNIVRy@nW^R}PMpu~#*pKJ`oC)IN^`4#m>0H7 zs8LEynErX!v<9|})&o@InWK_AG`Zl90|4C0E~gD7}xFhIN`nx2Fz{Qe}{I5gkyb+Ad-KKNq!ZZ1d}OP&u;$-BMO_5Jd`Dctlx%UXkdh2Pf9>(##WRmu8C(n{#V(@;YfY=fFl3*d=krLv zA;p9CEW33?Y*_QvkBSzbiIjF9kl&|t^36P7;P?l!wE2&kPu3=iVw*67MzM$k{6@HwYAQ0e(g@xPr4L7cKyTJ!kAmrKrb2Z%3zHXE{n z*{9cx+Fs2+_4(E_3Pr1R?-;6S(v8MU-&G3_zSwN+OWs(~iNj|Kyzsxz4Bmxl^VN7bJ3Rd#I2H~6vYhfA zF$O$H7+_v3WrrNK^Ku&-P0C}WWsiTa@H@E0CAnYrP6QuM>Lv{VCBy~j$=+~uZuow( zsYN-GChG;}lsdkmw$EHCu7{r1j4@1n?H|afF*UiJTByU)y?A>rkHJn`QH5$YL>of6 zI-mY^Nml*y^jH4IFiQu_!;u|Q1l)qZ#Mo~W5b?b29-v2b5A&ib#_bSJi~o7{f*G|U zXGI>iaXtW(kFC509J%WTuJ(s)0r#6+#seTMogOYef?OUrc&xqlKKZgHcj)p;UXkP8 z=jyx3bSCx}lG|V7#zOA*1S=8T>nI=BOAOCs>kN6soa`#ltgWo~uK}np_=p-OSR5>gu6yYI zNQwZUaQKpXP|q=oP)yN2Gx4^cYE~E~A3JCSNf|Oqm+ej)0K~>>(><*#ya}C8QnqsP z9)vDEDF#}Bij%i`-Z*n#Zq~w{J#x5|LgL;pyXtlF=&ma^1!|YfHVDWWw^;o z*W9fBBgVKOw{Rhxi?4dIQ5Sw+E%uj1OU;UIL`4D&uN_9{RPX}a4`1w>okt<*==y3Y zoU?rzaP2mEOi2l1No87Q$WpS(Q22*CR`$uTz@Wz_x#fUy&}v6N;QG>tt%7v9L}b>e zTBA4hdP^b06+@PxbG|+Blzk-9sdYb95iV(cS*`Ad|)u&WpqlZF@trj`BJL zJ~^g)a5=O<^WnA!G}r(OZMC`)h#O@0lJQxAhFKByDHw+@`h6V~3E{l83pQ0d0WH?1 zWR*=7RXFC>KoaXHvNTul?=u^voO@T!A1^TUh>U)to~|GwM( zE-@0!Pk7xhmTiT)>BT%JGa-%KGSi#WH!$Xv(|tJwQm$*KGhC=cW+Yx_A_R}@TnU|-mqyStxFp2 zUs!3aoFqgG%cXf%VCizxs!|YP^00jkH7k1kCBeAFjB=l0PXRIO?2ynlsf03~=bTBYy{yv-$Q@GV!o%nn^h zK-yZ5wKk|g9T)mKv8C_FP!CBjIuCGE$>5+l`md1#{n~>eNO3*mlXw%^>n!5gq|yid zOLc?g`YLl;6l5k)1suB~8r%lYY8xW4wwR(@9r!D`Xh?u`@@JVI2}%1Abk4y9)c>p- zCbEv&Lib{cWaAll9#llacM+=QvJyLvblH%7;|MOt_07lo;*cuDDj?_D$mUlw<74K& zI-p5HKrIZaXO=O;q5#v77hg%hxDFs{)auUHqr#=~;qxn`wyEhO7@kd!Rb$>%KxN);VFr8KQ(%qR5#iRSn)pGhhH@<%ONLXP>UP`q* z)Ji@Zc*)&PQpc86y6M?=af5}H1qJlm%uvjR)%Mbie97N}8@1{6hB2E+@^Zm@`s1bmy2G;DGNO&Q`2YTMNh=eN1edR1&Ed7V)U>so73CQa^O zS)hu0Mu*4IkOtqxpj5a_c8}d7;n+p%cbJH7VEh$7cz6Mrc$QD*JsOTBnZuu1Z0_G( zpzZz(x|(P_;JCzlv-b3jTFA!U0%i_&llxQ2x%%{TTvaMO_@rR<@qRRo^DXy}*~7E% zl~2+_rWam5bY`fy46EmW0q6kMiTF1*?y(lX&|9mZk&U-pHAiP+FPwi>&gHN)x4L-ooy(zAq#Rn{p$%vB^Wm8^p zaL4YWeJzx~6jeC*^{$lPjuV*&{q~aC&)F*{EODIvIk$=PfBxMjhTho+GD{ia>>+xg zI5qb8Ki_}@&hx?9-AHOK1z{1_*+IfTAp=DnjUHYI`m#Q4Ku^2bli3udkPl`}_{v_2jzL<_7oKEKD@`92`ELWa-# z7Ot#}Rd_fwr>9=PS6GOwAdaidium{8=93Mh2ABCe+-1YFh!}q(V%{QReEUfG%0z3W zIHks8l-`Vv{_=Y*hfPSm^)=Xb#Av1f z!PNnz@Q_E6>s;ihAt=l_ut8eSCiLaoYGFJ$$ z52$h6Q^8Ka5WX_{o7xo`qqA})Jn33{JT)lC2GjtTlwaC+Vk6AKO6Q|E->(d8OJC%<=Sr{l}ifoIX;&8na}L1Zj|}S zjoQJoE+0;dr850Pk0|h8EIUotD3Eh`48C2`vDu_{00B~OZ$Z;*_|oLt9wCGd5V;p+ z3-9gdfP>_P|A(gYj;Hef^Id&UW&>@685 zdpq`wV{dUB;~dVpuKRp{_kI6)*5h2)b*}Rn@AvEVeATSGlDL=#)*y=NpSvZ-a@2mQ z;9+_z;ew)5gU19ebmgv%#RDO{qarDShe(S|3>aQ(75GM4Ft{zpVe2cj(9{!zEv|u-gyX zORmXMANSrnk+ZpodA`Gd3Oh7t!khd4B+<}w9zve;kEwatak~$IYh8VkI8x3u?9Y`k zC__vGkZH7j1^w?$R(akSNCX*PQ%I(H2Nj(vSV zE-l$Zo_vO`=t9ji=r8CokbD5;5V)HRq2bRQ&QP+{lvMdYW=M4j*?tD0)WZAu8ua-e zlndhMggMT!SOciJv14GlTnQ$~UP&JTXQwG;1`l*kD*YBBCJtFOO`7?5i-YAA`3leP zynHKB2Rj7nzoBrLs<;=E6dm9jNH}{^c!g5e;PHMyk5pwvCC z+4bmtZpg!nL0x|g9!K)MG7EAtsX1~lpI#Ci*k+TknL4`5Ffzn3vT35LrBV3DijVcD z!3w+AXXGE+`71AIWERx;`zOT~Fh|TU?^W0wd4g`M%U}B2(3Bm$9DHiJZgo%JVDJH5 zJK}8F7B%E8rt0f*ZQv8&H;j6cQVZ=Az(4)&1T@TQd_DQ(9^o^)4baxY>`>L@r9W<2 zt|#+=Un@3XMbV9is1u0pKvnW@Pz+9@pwr^{p?*EmauDY74Ji}koz6LQO`Cb z*`&l*vz4OM&ENV5;EJb~2=H@cE{~^0@Gp-G_9!Z8Bj}=|K*}ih%;x~VnMDRs87vMr zVexW9WVuMaNL$BosXF8=UTRaZ92}lK?eiDiFiu2UkjlZqx2x4v6_+0J+Fno5zRz{| zkrfI*O#TPI8pznl2hnPJZUY>Yzy-|Bk!Oq)oBK%T$iB`HE5&jMOta1e5QXTk7(!Vy zC??+YYq`1uG!6gS(4&=%na|iMRRukr?mMUOGvCOE#rB_7tI-#0*+84{WDM}`<^c`0 zMnA9$rpMWu19_X>|yEb($C;#m{;z%52M8H(XM-s+f@|bSEt!!7@F??5!CMyRom1jK5T>4 zth0kw*EFovauSZX8Z73_2%bEE8Pn|)Ixnt7=uznbKokGXwGedvD=O{)zYlpFz+()a z+9gR1d$j`wq|y!^zGq(>uDc80IQv_G9PC7N%bR*1h_+DSgueEkXNy>dIap!?LV_QZ za1Lw5F*vsVSLO7_J1(-mwX<6lCUm0m;%~g@K4AP+l6^)2MqHY95r?(K6+&GFNo~(8J@)yMlt2w!A<4SSJ6o7be?pMKke)6a*2ldC^f2d zz`wk92HEFs(SG?QTpPS|ng>s1LVdjsS56%d+sgZ`y~Wqd@pD3ooO|wT*L&ea{!(=x z(Fr3xvR0znc2Bn825^=lL0yX=c(%Gr!ZJgE8{asCDP!4Lj5^$A2tD?4t4(+#j?9t= z{5pDm=y_7>+l;^P2H3nbBUW-RS|rR-_(X3i5Rcu~xxN2t2jZ?7%-V3q-R3_R{pXeobU*fo%`uSMf3Y-$g724n_Ue>|`os?KCq$Vj zg7#jv47*-~B;VCGOA`N@^l2>t+2cn!tPn=;?~7bBlwpMYcuVM%`hL*2exzF@@H@F! z{mGe_>)G1#WjLO@ZPap0ZeeKU>b+CwEzqOWkxGFcdNKXhcs_k)8VXQahuc9E8`|$f zod&*$=H`G2x!-Xwz9`N7_|bpS-1_97qRCrqgWBu8iHz9*GdO)u)LoMj6$7J*o6j%l zzE1w;Z^E{dc-<{k=<-aWtDJ6m4?+-pgTA!@`|vV(!`M<<<%V0Yb^RVPaWDV(ukFD* z{-bLvl}Dlf@d_f$uMcq5FaF(@3oq91v!-AvJ_wWr z>r#biW@JDW6IHdx`ZSrfRbfmclF7yCWQCIJ$1o)~xsrO&={R!|B0Q}P{N15ybfMd; z>)YSke3y9k(RNVa39yR(+&Qmv>FgLptMb`;b`hun*1PKBFR0&=er^#Vn#Zp;Rh+T; zMCE1L1CVmLr|qhGSU6bI+m}k$Oj- zL|h!COR!H@1iDR-E7|E6(~R{zy7hm+ij6DuezIpcli&Pg89pTx`#QOAv}J7Z7wlClndUfC zKiMw|Pc44Rawk#nDC~a4uk~vIc3Lr6HtxNH?geSiT_}c6mfa&` zf{=_d?ae*tZZd{5DYTN{c?s^8CYiXPt@e*H$FHx(5m@#Tym+0X_s0^x?Mi{2xSw)3 z^-DYU(TjzL46rg41)Lavy$G~W_5(D`50CGG0<4_yLXuzL1EZ-ICvbY46(W4#3{Hw_ ztr{E(;)|rpdBDp!=>q1{Pm(Yl2r=CxB>tCw3?5y8-WK}(g+G-+HL(F@PJZ+F7Xn1@ zfXd^4U)YzRX(Hw(p^o_7iopzpX>$t8ULI<*jAD>c4)qstW534doLTrb-G z<_h7s9O$=p{F^xObcdd4(0#-47V!BmmCdsO z-+%m7kuI>?%WZ&e+fZP_`GfG=Yz1Ux$PQ4>p1@%V05zbQ{PEW(H_S45;Fb)Oi6R?sAt^B%YjAT)&7t+yIQ-}=jBP}xZ=t1)vnH!nX)KPA ztAq~Y{-v_Ex)+_3~B^o4;v+!6=eDF>y{a>e9Os^#YCf`R-r86E`%kD-`XY zAFSA8G5Ginnn(M#@=6F$*~&cn%; z<4qZG4%@%!-P;16pvX9Si34ffgp0xSuH2yGJD*o@{OUkW( z9dIB&R=JeJ()}IrLV|f!Vsf!+;$$gHFYUqO{4*O^9ta-od~uaz!0ymCT0Swq2K=Hd zt?i&28#H~uWt6~!Ag3@3Yt@0Tv4F!5sz&vs#Yo}+VAdk=%w`eJ&KG>6d({8h^|Rhr zYNSnBh@+NWCnI_KK(@K?IkbyY_uWs4|2ql^XltJ!#CD;nO!Zr#@AhTa(tuX+Ez~b4 z(#stsd*&(g|Gwccwprkr`?3=oSbR)U z6WV)Yjy|z3b)vr|JINvIRVMQVO-+*f@WXo!pGo)k(qM#D3yZ{MJFFU~++m9?PHl;) zXYKklr6O>mbx^Qe`WoUxPop>txj>krmx>#i(f77s2mD8^`)cN@YEgYu6sJ3KsVCzraX-&-VQ)?{r!ENnw7K-tBE>B9CLZ?en2RdD-)#&eL!nQ5P#G4NcF zzsVew3=Pmi4vp75+0vl$5j@RBH!jQ!`11`5%yrvv$N7~oDWtWTMF$p$Gy?6 z+>trGr+@P-S3r-swbP?P3Q zrOE_t+KnDD{AK%jeukk}9C8JaC>itZ2RM;;ZXoE{PLKi-VZx?1tiAE>VGyu_;wtk5 z9ZlScT?CffZ>zYh)u-f>wAO? zoAI|kU?|&tX=z$JL&vWw-v6EbVEbnFSC*gB6^4|vi2gmGIb$Rp5ixUKzv(^g`?H3v z!t;^C(s{#wM5A3OcB2T0{Nnw*pu0>dPE`qAWxUCf&T%}SO!EuJbREO z-QT5@z8kJfH(4V0(9FKrDOZ_iI?~khj8w%#9 zZnruJ*q}#m2Wp;m41^`{*%_IMGj~2Il7;M)gDR;?P3MWa7pe3_@4t98kSYKgvNT9= zh9^-TuL{D4g2S47Jbh)P+=9iJtFB^>n!qrk>7+;6Axr;)DK8Umug}-Q^T|s;uKoMH z1PS?VXr&{-T!d35F%eTX7j-1@$!SHSJ7K*F^bJIA?S4m9rQCv2fE!OJ&%E#)%@f08 zeB&;Ef%kMr?tP$W<76!*{@-Pyz%+AX{=0r@=eBc-r7IrI931J8`@#~~(tJ1BfnfJ{ zClQ(A#alBkxWemI6OcVj`C)&uk3lmr^ZfG;EZeMrlKoRdYR6M* zXJ@SDF$i*wYY5wapjR5$EH*ZdD;G(>wD{Mq0=B7c(&EFncC@lGu4v+%QKn$8#&_eR z1J}OlO0s6fEvc1-pqSKs!@SR~_H_$gh5OWDi3_{VuBFBkQLOEo-yx8=~N;-*CPM({)FX#jk2xx^>0wjGR@j)?K8UzQAU_ z)x8Q*#(~fTg@y7can`HqX$sYV^%6?pi+|B0f0hH}VR95Ol;aT516W+s=8cc7^@6Z% zy*`v>c#?|+3I1_eUp7BCn`fjAWe2RCP?52;RxY)_pf1vv_Aw|-)ypt7vSEsZEH1Sp z51IT_e6LTnan(kLf?hc**NO`vk4!(p?gvv{_n?R9Q zI+b8{5sAdBT>g$++!?Wqg-+FgQPKj8^ro_|I)uRmv8cbJP`$* zq{H7jqA#`{wKCzoPn9)ZH`RMKFpNVUil~unZl(KFell- zT3SL#q+ty{(>{_V4N)@Q{7oW^X`K;DKOl~PeqKZ;xI@2nOn^dfPOglMLM;Q@{z~f- z)u6^Du5+aesxR0mT=Ol%pJNY3RM5)VfL=rI#GSF0+-HxhQqPsHMSULSw-nbOe~?%9 zj{9{5t{?NEtg8Cu3f<#Jq7q>DIdTge57SOj0T^j-e`_`$U!XR43CaixKo1vn4&isp zCJC*y$?dL|c~Q9L;r8B%AJ@)YSUll|Ha}5<1#c|ZSlm%rugaYdt=xt__^UNU0}(ao z>9rCB!8x<8c1qqY8P~dop!myGBJ}Uqzbtb!7&rV3CUmA;cU|g=7ElHsP;CjKbc2E1 z%=;It{oAn?C6BpBeM#xNC!Kq>DDWI8dZtWh6<~yFi_xRaqgw7Slev2NZLO1{8;0j{ zHhy$dI@7`Y*8;8V!JmCE=~4tdK$Z0Ed#Ej>eoy{^evi-u!UJkPY4t0UjqYPdCrVIo z_LZ?^2LmKAc?8}=dlyvmny?6pXLqaBrX z_%pkK!hJ3Nybjcn!K0!hDQ@veni=&uYx`vX&e zf)Ce;SY2aqw0DLV9$`}YkPs_C$hoC@VZh~_p1T;sT2Ih6#Vi(niuML+SmhLeIJxh- z_Y2cr)WNsa3&MhPZBWoXT}!6;Ubx@MOS~gRW!CRG``!;<>c5YWMDIUzw)a1-1tusA z*fba=9XWl%597I{QX8t^Tx5> zazgH7@SpO}PxT;Xfa&HK$SZoAF}BDV1SI@Fiy_gH1)Oki;|f=~KtjCI^J++T5_NPX zzN6d`zu&imshdb4PLLLXgW%3!*CD;5pZm_A;90%>jxLulgrsYLgJ_1p$Pz(~pjm_S zT@$dYP(3Ep?hrA-TPV8ye7Lr*U+OKzfBrY}YLajAr-IPH$gzs$uvW^#9rC~4))7dlORk)!D-Y*i> zQsJ@L8Q9nDaZ<95w1t?mJ}IO%gNSn0?-ZQVKyU@ zKL3O(SnZMWH_Dyv(<|SEG(k$&7HS1;4%wePxld|o$m!Y(V(moTOpg1?27D30ArT2v zAc^LBo(ZJg0PY{Umj(FYA5CeULOc0j4Y3K>C-+km-u^CasU0?T>zC;NPiGhr!U&sHcFIvLT z{C3375`1$KuNEOhXuDl7M2f9*y#hyqxa;U`43 z$A%pnLXr$oP3x4hwLJu#VtiiVGfGd?`uow|p&V(R{yG_T_1;@i=phc`5il7Izs+TN z9dY!`xEd(k!4O2d3HWxQpgUzmE~I?W)_dI9ZA{&_#4)DsU1Yhpi$|Sutg13x35STbS|cXDxb{DRidQ{{@A92o)}Tpe zfBh^|W}!elK79kECS%gA^on8mbCOqVcU}wx0j{R>m70MB_u?!F>72W@bD_^L&bW> z;`v>?9SR5OceW-ADVl?ij1aTsmG_mxA7{Bpr=s9hV{mHGs86`%oXh(nf}EfwQEiU^ zG;P5YZa-K=J3Ny4U5*q>ELX14Z891jIBkI+jS~_LUlG?lq}X-V04pn(+(&{}2X2;% zfWygho>5sFsDJyv;@x!t%J9p*AF_V|ZZ1qiA*-?2n_t|>2A$HDL*!9~pk0h3y)lsf z>;~+`#b{P>TcKaseaJ8=k+uSn@yN@0(>O_-&J_!(_awP2_%3a`!g^VGD))|c$%Dcp z7D4-V$O_`1(?)-{jzViKQ1*=?ql^lEBnF5A>1!nla*1|g{CxbtVEgfI(AjUxIGqMM zXknifaOpQz(M!#*lg;y1}N{b;f$RO3BkjFrR@d@!>Ou-==x zWuIC@Gtp0KmfA?y9)2H^X!z8*hLT)9hjGajT=jjt;$Sh;(U)|4>-O*J) zaa45=Qih!f4@bAeEo)_6-$bm$8{B5|BCY43?Ef{cW#;aeF76V9gh3O(J^M5r|NZm* z&gf%ug+M1Z9-8n;)A3zo>aT5BhNX~A6)jn0zDZXG6ZCe_UZ*-@pzk@$=IjpC5D^>G ziN)ifhp3~`RdL_p%^iCXg*{zbbveD&T8FV_5r^iP*B<){FE`WN>SGEz-v=Ma2k0XX z;)xi*BOa<2dgNeoNJfq0f&Bo5%zwm@^OrZ#Og{42H$HGlqd($_Bl1&iw>5@Ds5!%nlrWSt1*LhJ%pdzj71MJJHb z66!3qv}uQ4#P#a{k#vht>oQ;QmPyFi+prarIXA(f_=hGnR<8{aX#eCQ`W^WnAG|g_lmqyaqf8<89URWQxbGIBdA;g|t|IjkPh1N z^Y1k`i^KT+ov(a`6Go|HTPHR@w&2C^3l0?iX|{8)R`0`grB#?eo6}d#<4tJgBxfuM zGg|=dZ~!%Xco?qvI)i0D1!GBjv(<1)^~Okrcgpk#DdHIQ-lZCiq@!(#EPj)kr!Sqs z1)7G#Kc1LVy@X)j$k*}x`xG8;72FSNK^Z!wwlOXl>_}fQ2mf;%KB53rc$@h+T#k-x zggORfKlr2p{NAMctrD^R`^oav-m_Z>Oy=~7&d-`?#BormJvfghC9mcHheNA{O(%tC zFO=FU4!e`fA32$wJQZ>@I~h*?h~9a>5W*q>Cy&5q8wic)iH76jxf%JR5Fv3EO5sF+ z)AImebb*;&@V%Czt=U!K>IGp zfV`9}4g-79PKpE@fPRO$Bn?X>A4`>fY}a~0@?O8=kDqH=&5mGX&^qp%`rUyRBw+cL zpdbIuSr3{*4kP;GGe0nPoQ;0*chwnc6Y7IL%Y)I2s4~gbp1@I_ix;q&nHm)ou1a9n<7cyY#xJmRkWRC zOJDPcCa5JGOTVLZPQlsp4LbeKQzOgzmAWL35;nEoCa;BMecM!19`#t0p6An}Dsm}| zGx?>FcYou`$M!6Sm0`@OYlS{%<28kuCc5JC2ZTwM3!tn^!3vRF6NL z1P543s62(!`3Yjf=dHoeX5$A^7+K$WS4Kl`NAtGXuOV9(x`1q}8R0{Q9oF6?3n<7k zGEFOacRYG>)`0lrAHU7NFLiQJ@X?*34x_tK6gfTaZ(Yl#^6Amgdf*Q%`u^6@puw6J6nZZY``R~kVW zv5c%;m8&cQKCE39Vw>bS>1ULNBpPLu%yU)1H_y65X(F{=1498Tzsy*ALB8wxQl;2v;*2+?x@e&fU}*U$%l6a1fBadl2GW4{{Jih^kBv< z;YVa^pqXlg<_G$`BDVA;P-HnQrSZO_Gm0WHO0ysQmiD!rx zzUGrsM@2&Kg>E@nTrPF%B|-a>X? zdSS?T^e_gPaolxMj6e8e$V#XwxMe6lT+LjJ|@ij=WYfVQT>vn9~ufk$BY2v+d zT>xJy2h|5a6@+6l7QeZwHg|wGm#?l_(}6m}X3|lo6V3@NzVl?DU~LzJzJ_?fXnY6+ zB&ziV+_yL;xK+LrRJPN8WhK}Pijq>ECGPLm9Xs{0D9*?q*I`Dqd?WUtIKUUO=~~() zE@Ia9>}xzp1F+N$s=s8fGslbUle<}w#Sr|C!X}8 zXDu2Pv$%hmPHG}X>XlU_vKftuL)pER%ev=SS+2i#dbxqrU9FW``E zRQUDY7Mpu0i$0MxFL#ll9;bq7S`cCjoOheYuHHa58Q!Zp{QCmOb3|@I;M5$7K{x}r z<3yp@=6rJH+K9@RT_JK1(DlB*KL;PY0vA4&KkASU2aG*udG3YS1dVQB~6KuTSYn7?1}Y#b#npRo#&P?;(DKyBAyKZn2Iv?KS}a< zYnvfTmo72X^H^}^!O_p|Y_rZK)I-PDm-T^E7sV}xoR_d2#HRBx?2-T<)E;}|Ztj}# zM@pu$_sQH_yrBQqha}+OHz4mx%sEC?RIx!9u0vV;j))zGtG?_BWQF0XfACUaaOj+J z8%3qBb~y;O6aI$E3qriOknZ7Lr6tp;bx(0Fz<1&rl1biGw({EN zF{BsPo7J@yAo0*gi1q>l#6|aRD|#9mr8q(s(i5x>K1Yk#_LhB4UZJB*8IFLz`M=Lw zC5&s9q?O7~{{;}3QJo&|6YItICnX+}gygY@oo~K@Li`use1w7?nHx_MC^h$%OVrWm zK;H0a9VFnSBXB1 zZ`5df*M00yZ`d@hJ&NTnm0kWHL6o4&8_?f=vpF=7IChm}m8fXCa>3w=Pb2cEOd|ei zq7h34Z?*gG?W1crAY4vJ0T6|ZIERs_H zjBO#C_<2FryEo9GKY+YWhodz*Un`wRz}Pq?k~O0S&p_n2W5IBvl!~5KuHQWK{)Uj2 zyLY1F>^^1gE+Nr~T9ZP0Ogj-I94_=Z$KiQdft2E#w!Irk5H!fQDw{@>4Ii17!{ri;e(DOUR!Qrks`WbE zFtsC}{>K{@S%M)x8i*BG%h?YdjX|7p)FShJkBXZKrMArC6{ncq6eyIt6hwVvB=&7c+b+?K2#=z#tnE%3i;!t zBq^RMc*J-c$F@d+U;l=lO&Sf%_uCZEyp&c-Ok2C>&HXgLzRQOF6%Qh%RJ_Qw?#@gS z>i+_k>k|JzU-_GBldF$N@9G0AdAA5V@;pD87pM>F9Ygo9WE7BRJ2%Yi`yflT633EG zu^=z7%~R^x-w*cqqj=vihJojEz=68uP{*E8J;8ts|I8$|7q^Yr7m7k{H>aJ#^u>FK zH_H+;=ugt(g_ZbXjr|t@N8fQyC%4F;ity_b;&HgISw$EW>*Jo;& zmK4MnO-@%a^$uN&(a6xuHeF6$d)4D$FVu_NDt?ye?BOa-wG)S<$^ARL*)qKHNj$!n z;a^A&>&N(gB=+SWo|-!VHG|Aa7X0waW%*PF{?WHyeIw9au#BkR720>F9p*2pU;awY z#qIe?{9CsP80v>~tIkWpg)gm8sva3Qzoe7K@qr!i!)Goc+ZFvz=g#=Ha_N*4o1YC6 z<(Gu+sr#$j)6J#(I&*yt8|i@}|N4?qUC{&RGYuhbm5b~djxq)eiX zUq&6|?X(z}_ zJ(BkBjXOG4i^easv4e^YmW_wWH6>mw2W$Buwa>5_q_ibW`IcF#S&<0%mOZwkk^of0 zIsfc!2a)M|Ki1yZ1;(IIM zCmXDth-z_J@OesYy&sv@r;MTLX%(1yK#b4SD#n}~%OLPYt2)ImJSE`!X}=WETPqHbI)T3&vLDKbYtRVXv(`iaf}aeb?QXT#uAhgb zCreu3SsrJ_DPIowZim1)98D~NA}iglY{`Q` zojTG`;NKu%TXi#{x6A@F7Pb=XTc1hB$j;vzNEv;bTiA|jwAiHv?x!@focVR-8L+-x zz@QKO2mMV2E|LHNvqd@IKk!GLkElQj;MN{*10xoW<897f!zBkk#%VQK&{y8V>1d|y z)WN(+BP6=pPt;8s$WcHy6?G@T0TKFBt3Js;|NQe9>P~KMgH8EHl6g#^Z5H!L7vC5a zbi`xW^L?2ABhD#xk#4v^N}t3Ojq#74+|T$?I|=OR2W)Y%+(|vvJ=69qQDx^f%2ws; z`J>o0_TFWAQW`UyptuGcXM@4uIEm#@EKB~sF$~Ud93L-AU&>J2itzN%MWx_+eHG1PRivCB*T^D$I7yi0R zYifRuP|qj>anFUzW8Jv}M(JNkorJ4FNY?<2;YLhx-p33SkWZx`x>g#kN0z9p z$v^5!?;du*Gm`@cdcAY4KiS)IR{J5xXoYrTg15BTdI2;7L*`{2n|W)nU&DPkXYh^fM$f>rMz)|$4ANx%XfVzL3B z0o4)5o&CJ=qxlMr#1>1W1cSnXt?$+xN-Ej6J6RmUvtz&PdrBe!($XwGX&tyVY;6e*1Mr4|EX zvYCfBo{WY3`g4$q(+$h_g>1no22$lJym19CQ3{Z^(rX)cAcy~U)&1$v3VI)hJ%>!2 z98f!`b(%asdE5{FT&kdiu5b@x*>Cfa*b6}V*4u~qbT3cYsXwQAH{WCvJ|Qhp{Y96Y`DSmauSbr3yG)m@L<59f5AKcr08ckI(+1(cJW9#+$dA^CDX7;oh4TZCKFTWw&IdStcJsNE8 z4T^DKOfRq8$7bE`Xt}>z08z)Pw816qx2pylmCcI@C>X#_8Ch)ogY{hNH~2+QLic;Ej@Rsou9h`>6y=`^!0E-qp2k`T;a;m{^Y=Z~G#Cgg^Kl&Gv9fL7(a z)$fTK!-OXjE43Z}aXpmY+$vuod?F%5n^-o#O)a!6B0hv(zN7YnrO0OzgN5`))L#+< z_m&BATH+V@tw0`S_X%+E*ULw!nKX9+52ZR1~UHSK>_C~G8TakJ!{1q zA3~q}M;~^^tDd(qcRof3cu);+)ijm>A7&G_O85QKHTqB2>E*`r4>8usrUj_MTy6%% zy+?RmlESGG#;IxhVUsViPwMiGVn~I>G?-;a&`!{Mb42*bO&&q->HGa4`7~Wiu6&Lz@IN&HQonyKxeS4|Ip#t?ju?E3 z;Sll8Z}vUC-<{4)WB+)9s9~foN;eVj1AAw-$Iw(`u!QK|+JxexfcqXdfUD)gpY1ZM z1iXwoiZIw=5<^Qbak5|uVX(4AT`HO|3&Gtl9go&bb@0oufc4~BH*-Y_naUuqJ{hf|}g7H zP99?JFKurW;Cz)cuOy~(@AN%-EbneHyyZo=a$RPpB9$?DzvtKZ$4IeJu?#~IM9Is< z-4v=6s#uLsTMU6cW%8H-@KJG>BmfTB>@?ja0Cy?K&3+XW(zMeDuX@s>nm+X2 zL|OoR7f(9=6Q?BQld0mh%W?-rw!t?Em;ybf*}fKbziuc+EdSoxed`3{9)g#AaJ`_G zZw8eq?8DM6=x-=*M^7Tp&8%TIdT^v~CO3lL-=lDun(sb%Y{4CNMKU3;O0c%8}|6RsFI>0<0g{#k4MUjCfc5DIR* zesM~FnGtu_hT$aNagAlahCt@0qY-SZF%*JmS1 zdMGvVt*>X}{wAoaX0iSS-v8WCGbZmJJ>p_fV+)=&4;ItaDy7qH(~ z*Q_fwJO86MBVKV_f>wh8dcn)=RM#ex2+4zaLD35UX~IeC-FuRZ$8y>Sr<1xHd2=a$ zHXlR|p+j`2Dld|!-ey3KOW5o^XPj(s(J;8Jj9RWNEw5gM>6HLKn($CjZU01!b~wg{ z!1OzEmsBb{M>9wGQrrRD7Wqp=)PWZ@zXve<4v^gtPxdL$0S%(xhddmHQ*hjs#a$2Q zh0l@eyC6M+syBsD+_5z2j7=AV9t=GBJZ}eO;ZVw!k=gfJ2M_WokwBM?fLWcw|3XSz z!Eh=?judC+QyC<@ZbcTnNY@-tC&Nv(q%GWg61roA_b~>nXPAH50d5Re;%rB|sQQT@ zh6zP@(mxhYH4iMPu;k4+RIM%TDP=Y`gvN6&1H=(@L)}3|ZyMd+$e*u}UYI1BbUBo> z6JS0EDQVY7WvtW&KYa-6FFgU(#<5NhE(wWjOB$z^PJ zF8_%7lx&$6uO(GWvQ~VRRtcpt*Lr+#m^(^#-In{FwR1II;^305@FQYN5C*bEfXQUe zJC`T4H;TNVFF%Z;c6PA~EJ|cfzj55hj67MuEea*269^$_)7OL zG^E};SL`kDAIbQo)bt*myZZi2$gA_G@5I85ABR_8$`AV;XS{;p1jM#}=;FN%a1#?r z1?f9FP`0N(5Q`y1RL#4}Jd-doknaJ0Ju0JCbuk zV#nX@5SRw~6Vq}%&45&;EM@O;cL;S6`ttt5s7VLbJqEUgd_02?6rDMV@Yh>Hb#l_( zRiv$s-%D(40~D#|rFKQYt0S%KmQ8*P{i^BBvr~JeM+}wi4)4Fuh?kYRb)A0~|VwniC98ILW*g?dJcYT3f$9 zIH~Itv1ST=69m(Pg~fBD<$<%TIfqo{tS3HeN>*EjE9s3Oa5Q)RZ%LsnLx!xVfBOY3 zQSk;FN=d{z9wS)Yk@3GI!vk=a7FkC*QHkS1yK{qW2>W=2tzBV3D`4l%Er)kOB zH?5^C!H_a*ukA|{wTjOUrj){~$e?8fygEvdj#Ug)fzro-MIq%q*q`e}&%UbygV4?z zYUn;BW%e=k_ri@m2G#U5fO`T;<%~1}9Z>*H9N+=HSx_b088^Lh<&7JA|trm5%QL*#_8`Gb(b!z@zSG-=n{|+a$uJ#Lx6-bG^nN!uA&!beQ ze^<>bPEM42eWUf$@QbuKgzHAwMcOlidO?AQk0WD?N({n!LN2{de{*B3Afq?#WplkI zwYtn}t>H-K6Gm1fGwG?dK9prm$Un*E`}w@M2*B^xoZX5%qbT+AfZ;j+8({J6@bcO3 z%*7T^>jo@lyftcuv41bLF=w)n`BbX!!UVeC0{bZCxhDSEsahw&_pYF3fn74ObF5?? zrmr^sYOwx~&e|f2>__#?w_-2*US$GB<>wf!xAHEK@i^D3R|a+Zq*{Te2WP~9qC{SG zr5T!7*O&YfU04mVujVI263_fEa`WJ?f34p0WF*0TTQuj2G(;iFmlas=LANj6=|NCj zr}Xq}E&Q1(*ZXOYfl(j$#+TR^lK1+%MDghPZzndz(;e_SgVWpe0?XLykcD%5XeJaU z(S>k`>Sxz+J&#O_D(7}QUQEbwILLy;uZ~K}rBH$0R|qy%9b}z0Sl^`)rU1B$5TW)p z^cVVb$@IQ$w1|WqBqnpBqi9?LC7`JS?H{Os1;mdY;+sR1d*PnO7^fK1@3-uB5Z4Y3 z7NAwgcfOE~cZ+`7vv76c@seS2ra@p3?omp6<&ReaCu=eH8m<){zcmyo`NK?#!1K^6gJGB>`T?x4Iu5QC@Kl+KoYDSeIhaB{V%G)LY|Z zr5@c#X2ADN#Fi;@FScdQS^bB^hrEGBqnAEzMzT>aANMN2vewkukA!SrVXUqfe)spS z{v+HwUeG#te9KrHu~#|=v6!EE0AB51E}ei@8v4ljGLqTi`uq`puXrOt5AKV%!f(@D z+(SEO#m2xRA5Cw<#}gcumj)?YET_R>Mw#;Pi3o`z?uR0o>p9W4G(rXy#}4o}r~5omUZ&$R+WC}5dQthq>o+ahM*El1?^dh4CisG9uZNR)eC1UW?md=Y zkti0{zMUD((a9`CU{|82l^AeQ{>AMud$07#DxACZ&@cwqMaG&)KNy=?hE8e#ixny^ zZQR&8R-Ay%Fz{EEXeUwBhLgU?&yXw*bBHEjmtpd%VbP=D5bH;s-%2WRdd*l}3|S~3 z77EsSc5Q;FgEKw^Lw#-^2#GsF@g$_v+>MnMzKxfwh^$@9Y^vBn5tm@zo)=$-8%&o` zmMc^;;MEHIvv0Oz;E8|Oty9+gO5TFJ2chlQ68NK$2(a+8EWN}Gba=XQrFmb{JB?;r z?Ji6Ad3A+wsM{|j@ERE?hu-X96B{Q19Pn1(gUtG~0>tS*O{b*lI6Sn~3zx(>^Gg*$ zv_SLRF>3O(=q_2(7ip(mX2;&<6J1bB7YK&i($InT1}l~|ENC((j$ISE1JF;sRGI#FBYlcpb~@LQ^ag1 zpB?_xS@Iyp<6f?6_-h$WJ;>X%^m#M(*5##R{_jSqP+(ku=0#4mUakPH4wPR|HWo?- z<#r+UjK|0D&;Xi-eNnzoe@$BS0yI{-^5T;FQ=O7x4g|jPv6L378#gS@RYy6end@)B zya<8iHZD8eq5=2mEQ8ONH`VsKHYyz1D?SMhY0A1lT%|h8-l=;x8diCCTO{tzPL%wp zSp)e6VM**w?5#A-yLtB)cc$#`v2*oBAExfduYNquT~~&ME+IAodV~*Hj(Q*Jt~>`< z;+4UUvm5+JJd7~(t0XZxoC4>ZMZsdCr#rGN3{Ua|{+A)~x|L}F5 zQB8bdn71QEB2ADM6#lDpMw(ujNes4ZTT}E?jQF>uJB!n`tRWSsvHaRy^%_>C5=RKQFHu)F&G81 zdl0V=Jp-8ck455ZdM?)41?}<;;Er|2s{4_gKBH(Gm4}TryPDfqL4zwMR?G7zGJ!cq zLF6LV*?1<06J0nlf#wlLYk)XlSpEzBbmBTRg-O6Qj$eHYJ=Q|Zj?|COn1T15SIt*J zn%eV>N8}?Yd6CF|>#Q(GWYsG}*!}~!^T5E31i_SqdmUVNfO5uKPors)Uui zy^JCocsg=fHt-;d@v{Oefh9WLB#4OC6(eV#UFNup3aHg~AQNfCV#tc>BhP~lP#4MH zE{sWm-yVImCwt{)3#$#_-M^8&P-`)cec69-2IDx^fwYhEl%An>`8uuHzng(P&v(P$ za~53nhNQPBf|t()aZgaoZOzXwTv4eF^tD{L=o4bPix#qz^Wx{`%ev6L(1M#TfWmn5 znG(rF;iLS@8B{+`wjuv(KPoseSe??NGlQb4(}qUJYOX59H&p*L?1PD(98atR?F9)a zYmKjV;j^@~Ydn~hL#RIkE%V!_=R0Ov5nbq2|J$l*snD$NH&4g$;m8g8x$hOXgRZM~G9P>e$tK{8?gT(D&;c9089}B%^^H*Lb zv$rqK&Ap?*Rt%V%+9d-B_fgbNB2GTwwS2LQP^!TFR#& zdf7#17tCX2$6u`$+=s0D24DHs1R74`XO0&U-RWycYyBg{-_QEQk6mBF%(#viCTOBA zJ1*5fA=8tTG`pY}Su7X6M!q9y3pr7L%}C|PX_)xee7~o~`lhH%PF2*yUbsxj z`(S%2CZq>P18+O~*&I>}p=<*`5M+c~dKiXv{8#9MiD-crH1qIEHHVk z{l~Pt=qkeUVGN<#8hAXlI7^8l@xTg?%_H*33ElaAnYq*(pWUj%rlX!`% zqvaB|vjvCkAmW%a(70rk$o<#0)Gur)3aOPaE<*#*qarf+FYl`i=gl58MQXDev$! z@fV7sD0>O3kA5OK<0qic6#BT^r1xzr2`S*sCD^SSV8b4a+}!!zn=dE@x<*3X{}BRr z-E$N45q`4d$j!W0Klc}uum;Joqob&X)3 zeF;N_?@)?#_aeoF@VzW~ebY!$=qS4r4h!29{otH}c#^x(BDDOJNYk+F&NNl^RM^mF zDWssP@DFh}IO3v4;IIT!YcwTc7_zM`*4I=XtP#U!=R16;_(-MbJ!a0`KDBWMkx%bx za0uJ)R-ZlWbz&pabfX*X&QG73XvtQEzOlGBw&Pz=x<=OYOUZ1`wgQ@EMC3oj#C@IC zLzyN@Adeu19gBWhk;sX>N- zZpt`TP^T##E55@LL!PgMnn59E?@K0j@4AX?F%+0}Bef_^}bq-xK`XSIv=+|G6 ziQ#(y&r4R*m)qP!u;re5n7>OjS&tE=<&a5p5@&trd z5V(P$Z0zN%DQT$`k__=Ah|q``?PR3U?PsMmy*gm>5nlf9e3qM|cR|FKzCMHSYo(-F z%PsMN`vxpK&{9n|d^BBgP!i?6QX8F1Ig;loA! z2`muKa}fzXqA3`yd(e#yIq2czjX55;B=eBw^PLq)?p;Cg+C<$iP+we7J z&tdTN{@SOdys+1xDd>DjKbfZlvx=6Y)Pf;5o!&M<; z1(;s6CMM|lyR|%es`uEPgJJV9C1ah|eoJ*Jt&?c)Ci=9Ys>Q}&(|qBT$28mto3t)1 z&gK^(aum$ceh;~*?ZNRlKINuXBw8h{vWU5TqXQvi7EOJtqbIdpR}}yoUk2o3UW^LL zb-zQj_%sWIrM!b~yky?+(E1EabOOmN8V>(5Wrp+BE?)A41~{i&Ecx>S2av%M`C2cq zxSLi7kF1_u#}-d+Zg8FEIu~~JBT6s!&Cu>Qq2&QO`{d^pg*$qC233j%VlzKIg2*v> zn%`Z*RBFt#fc2T-aZH z>mtug-vqR&8kCbf9|CroT)rN{K;-UxN-waUJz5+hHV*1pi>^wfjBIhG}zkfNt#Pnu- zl3pos1s!syf=RQ+jw^T!2@6UKOhPE~3m z4-D?(Ug-?Gtim+%YeP(S8#Ty+hVuhJ653fU8;9IQEPFMx=dHO9&0rJE-mH{)5O$O^ zKgsFKWJ*DouW}mwy!ENr5!|)`X6J4^r0HI`y&`@B_w)Z&Zs5I5DZbZj?1?){d0J7e z^ue0gI^%eshlGRtAX|n5lrh;$R6F2yb4Nm%W7?Ng%LvLci1z;b8tU0Tr>+VIm@Re) zir=>#W#h-9-G*wsC0lzl_V-0yl1KDc&y|Gi;PS1EjYVq8?@r(8ti4(!mBpIu!=XKX zq9pn?iswMZ!h+P_vgg1Y;4Y+#b>>>RLJTvykjIy9Z?V6*ueIRT2?V26n$A8k0YguL ztQ!SD*!|)c>Kfzf+ShBBrm*nmAB#N1@WQ-d!a;Yg?Vpcd4(H?*$Cr11Fh0YfX`1n< zIiBlZ@jU~NHo%*Ji4tjZb z9$?m73ilPrs1bng7i2gQ!NvGjE-@~Z1ot@0a=NREkU@xl_c}CS&@-G{fdrw@FtkgqRREHxb;pNHnGqO=9hzo1szD*KRxgGVx^sbQOd1vg*aU|cr{Y@e z4~1+81PGz0l?`&il3sW~$J>I>THxp)RdhQ(6Us_*ZzjJgEDVO0`vr^Uqp2y#Gx&__ zgR>NxT)v>EybiUsB9$d7EEYjj(uhwO8MQA(OI*YI{(-){K7CfXPo-ppk}z3fpN%KB zKtC1Db1fyF8~{_z2ywb*0jkphCG+#qXus(gBF#a-L~|-#k$+^Uq0;=f^<@`jw?gNQ zo32~m9W5R!eZr?C{fz7Oc&r}-2_K-GDN#v|TG=@G6&UE71NivmlJPIgw=lL)6ZozX zi)7%Evrsy&sb%zJLeOoHbWC+D4EQ}NT_ zX!c*A`$s={myTZM_wC;XPJf;DwNO(e=*bCClw%y$sp%FetOS(YpUKvVC3SMoasJsm zF_~+)IaZpwfiODD7k0+REa_RjQQY%;`o`~ZH{YeP@`~@J&K$lu`egs*!Z)pvsevAq zv5)GToXSNXZXL0`&)T12;M&dUoS!Hz=*KX8ugrr^s zh?RT&`R>yt8nI|fxd;pEz$U7*M>ATufQ?cZU-)d=aXXc!GMmb9wK z{t5Z0?x8ccjeGVs3^K%PafgcT&BR87EdE0Y<8j+c#x!6JVpNgiE6P_uD~+|7k!UxH z-U?Rqmy{D^fh6~KH+R`tqiH0dJ-;=>(IK`*Y@IAJli&AQB1T063MKzray7 zS0|`+{EH7$jwHDFodo`68CF@V*c);WHqk_IfNox-6|2dy*I+}&WLbBmzQW|}K6T^e z3G@x7Cf$trX_`CN}-sxBPlHUe56z$>~WiK}iTLm2NFvaUY z`qUEEd;MnQfg0c4H~9AZFs!O;5iBg}+q-P7?hzm#ae*vN%J!y+A5cFa&EsoP-~Mn| zfd{$@^@v zCD!^zPbX1y_n0b-DuLVIv-9fTgXs?i%i^AmaX;(|HP5A-wc36}?0m@hrY$W>*LuUR ztaoAYy=p8Sfb}gUAy`j^BYsf?lZxN#`#wt!SAA7Td(KF};FQkgxT&&2R@B7Q*-X#E z80SBhfsMBut&XoZEOoKFmCDp#@v4A+HPq|Baxb)P?XkTSHUVDige>i+3#%KbK$QSsxZW zxgWbsb&6?ob&Bnq9>M~do>rp1liZV1Z>}H~^Ev~)hS(EZ&7PO8RAjYnRN>BY%2Qe> zz{JrP@{;b#B}khJ7e`^Uov-n`FV0t>EKoL($rMz)y1+=3@L6zTB~|OWhUpPFil0J)t9#RpV2Q_I%WI4%v>}QyK@lIFifcPEaM|}D zXz}kPfG_3{KMcY5`8QZc>>+r5V(&TyBDZCCcC>Llls1(VU*alGdzp)8C#=<0!J(I% z1+Scwlb6P@sBv$|FPcI}Hp@3(av9Zh$b%vl|=3LQN@_YtOW&uw( z+-TzytJL|UaT*(`0J95fUYsikF|sY-_7C1Y=>Sq!|61r=Yq{UO~uWrOJY+|x(mL7HZqeLyRl*W_`}nt=z@-Zq~_ zJPEao=QoizGcn3I=)E~TjU`~M2@EVJ;MIrj?XEL|6vRfll0YX?~IyNO&m3Q)VYNMywK1&MDo9lb`? z##_iAHFh~*LiUyXv(C5v5iDpV^oiHDYKMjRs!$`ZAq4wfRJ6gwhU6bCyaIXzWh^iF zyU{_j`PEqWdt!RcZAKRc))%(+U{6vy!!UUGD%hiSO*;CP>@>i^Ss6wW?Cre}W9wC& zvi>%0<1641a^Ei%ijRyW%(^f|6KCLxzB?3G|AAbkk)jxU}g z8JJN0?#O3ShiWf9w*O2&_@ybdjo;>Y%H~V9G#OsfnSKl7Z_7 z)al~M0;O-%^3|J_rt3fG906*<6(^WKsN)Jx%Ge19lQP}}SJpN>dZQ23 zL>TFM_vJm=pE8T;epaVjWp4)kGu@i%HOE$$5FO^@lA*j|mbB4WS)mQMs*RgLh*PxBU1cJfJwYzuvDX{Iy{YD%-`EvYA%%fvDEZOyLO08XNkVW)9 z?N`V-31Tr&VygPK(^8}VH~nNhqb+>B7}t|UolM)LxLGZp02ExBsgXDt_U;X|6a+BE z2XBsH5a>f5%;&-cW9MdaiiR=hqjPZQv>!Y99vj6>>04PoQgFh!AQWWb_Rn zWONvdTC`jhpFy3!psYR2L58=Syp<6(Ix+}xvWAYp`$>q@+Ut}AMvHYv(nvj&kxw8t zq9_ULlMhR@f65QY^ z*(HObiM{~G3(Ms{(IgQ4tMEvE5Y*yboUmP1oc+bnUhf=kTzf0G;L({%{?%ay$zU)Rl$k1(|^w|05=cZ%}d1LtCu!ITc z3l6KFFVjC(2RWfQKKBUBf)aOQS=v7TLYH1Sr;UkI1Gl8~xgK4eNeP4Y@XKkvlXi7L zYuv;uQ=aPn)qh2OaJIOhm+m@@jQuB7HR`0t}9M$d;m_RCHT2)RohXvu`sr8UM73KH(PKhwCz%s zoi_o-b^9af`@X?rI$;CZzU&?M zVaiW&QC|=fSC4+Ei9STYN%f2FKc1_NUw5GUMgWDgr&`S;emInF>+SEZQ*X2ZNJoVt zqB3xTw$cwWdVnH+-h||EBOC05#!*lahj<%eloL%+ycqthn1ULds5+wo-Z;LpiC7i8 zi(FY~B{#p=`2}o(a97zRqgHUd2XyQu8IW&qRIv|)9_o=0o~0$!eUP)N>mMKrk;O=g za$jTW@|5l&FWqw`L7wri(|4FfZY+H{E?Q2w{*BU*1kjZY9k8DlJ@74eM^V0k z42RSNpVH5$AZ0H(XsKM)EFu@46ooI!E0m1`M?O3o^?}xqA)(w}1TMKNpX&<;X;Kl^ zqI2m4*=-}5X6Wnd<@c$VB#Ih2F9R2u+y;oga%47TgvrI9EKM%q@hRFlA3A71S`7v7 zN5%en`?_N?k%W@hJNW&!?-1}?RaGgzll%|Sr_Q7Fxg?OkFL6vN{(_|LXFZwr!dWSl#F{iSbq^!3*jwz{89%anIHxp3+Jx>igVv}A+;6Hk5Kv}_3`7VC75 z$x<@XYRX-Z#Hc9g(NiOnOCKyj*RKfc*!;E+vsXy6)q;NJgEuZ*PK`0D3~>^%efwdv z67tym2hAGK62;&Dvkvd~m#=K^4brbh=P$wN>pj;NjOsZ-Ps(DgJJYmtWV=7bpmI<@ZnFGL$$+KXNXnjxoS8iex+ z>cf4z+#D>5Bc+O8>48d)y=T@>f>sZ=<5lS-x zo9B7x9pZUSGBmUe8x`F`+y6X-zwmi;5Y?)7Js|Q1#2v?bz#j5EUjGD$oQJpzWWgfo zR)>jT%!94#bc6&sz`5&Uo!%um(FfM~nQ!dCA+`Q9=e7>K`W?a7gUOON&Uh{bI z5r1QHO`BRg;cjni`1EC!q8$BLTt&(~cyHaJ9U9AsD^Opp-zY1IfRn$JRDnso0om=8vPj zWDT(qX*4_NFokD zS+GSy1cQaE@k$519y`rz;p}@?qjxH)kSB)JpQ$4n6o8yeylN8~YAF>31tv8DQCXW-t^ zkI=JmqwZ&bxpE7Kd>CRq^72Y$F>JaFI1hB8X(4!*7}F@iWAD^!49!90e2=}&@c}gj zkb_u2w|2lx?%r3X5=q*db;f#qtcM}^Orv9S+RrmBUfj)?Q9F1KBpUdcHHEi zHvThTvEArVvvZFiZs2~zfk(Ky)F{sc;`Wv3^jYA`r;BMpB`=>%D3$9hT$I&A4jGEl z+PQH-o3P~6xo+S((-L@!`g_mNz^Y+S1icUZ_P?P(-Jbn zz?G;c9zblM5Ri0RbEeJBG}IzW#;`Y2`I*g`@xHjnw;u&ReJ_ z$NRR?%Xkk-fRT3IMSJ1#i-xfa{U6oW);SWRs!94H`Kte$1wi~tms|YyzE6HFHa@HD z^qlH9$DD^ZbJN?K+xCPxIJWi8tmr_oK+yl7%`JaB=q|vwX`_SB|C;a>&#g zrW+=`XlcDRNigqJNb~Q%fqHU3)EMucs1(g66KU?PPcz;vO;K6DZN=UGVq!*C{dS>P z&fR^~evUBy_A1&`CF46*r=97KE|Q+KGQ&DAvrYU-pY`&&@gvC^)A5m}dm~C8*3OSZ z$;VN1b(%`TLQ;W_@8Oojqem`wsgDxi8 z7SmM*1D; ze*4_M&ovz}@BXd9h>S|4@p+jh`8n*qWS8%76DZ3MX@7xofEIb9ZucNv?~nYT_!{*d zQ%pK?6T5Z1U;{;Eod4~+aMF3wcJe*b1`=@uu*d^rtB;qO!6!Hz;4dt8S86Hckc24z z13fjZI!xeb5y3YVuuHWKb`4h3o21?f`paPtp29+=hp6t*JITBeDk~{_9@Ziw^ta|- z{Q>&7^J$3>4`F$ASlETr`PJv4e+1vVDM#2zbl)N>Sn6y+FS5RUpQ9YoelDO1g)gkG zBp7TIbX5H@d%u?W&KjEi2616LwRhzpJ^jXDWs$YMHQOk*T-9A;g(-(T_WDaePmvI4 zmWcS2N-xK9BP#Y-<@l!YduI*t4&3D1GPN|z2Q~3#sSd(VAaDL>DJmNV-#|Bc9BZ@L zo0Jf~$G0+y_xZJc>s}b7EH1#Hc*l0Y8f!3tW2E<>jO_1HH)|;F=#hoKvu^^Pvee&- zzTX~3m#TT!DQ5KM?AC*1e;JWfZN|TU*Jf|^MCt!}R40tX6>!yhhq_rwPdf@uGquF_ zM|06W@B_XSXqa0p>nsGGc+!rgN64`e;|<;L!t3h6WqVPZW4s?B4*vu@T8dQ@=8CDj zH8Sz5)!n?CaWUZOb~YSLPX2EfXd23$pwDJ~4|;azGxwa-)-?L<(##X_SCD<=fJSqrx)w}U7A7BH6WA;m(pR@df^ydHvOjRbO?5HPQm*O!z-OT z(bU=o4~t9ddyKXKyo&OS{~_e9EOFsi#KjNL&C=uQ+GvuvcKkf_)Xyyg%Gq)ah1C4Z z4V2Uc#=vW0OutR?Ja4UD!LBepX2i7Z0;sATH+R75jUQ}kFXXrUS`JIwo1u)(jJ6{U z|BzjTCjAp8pb-6%hxbBiIK0@3Au;YjhF#iDNHdruMZ@gbBQxW&;TLf z!Y^aOTc9-p_ap1<5>4I}Mke6nA*YUm7btwt!+9Q28&Wv2oTLR$lHFI~4W<(~rTE*yGE7QI6fg6Dv_m?FSpgDcv?KBKjpK!nkg7RdiKOEQKNxZ z$`GDU{_?x-0h0O4y*r%3x?jH@PCM~M30`%$BZ691ZyhzOI7k0h^ZHdLuuOPPdPMX2 z_&!pG(sRFZ-{Xl|X%F|yDQFL*Bw zi+Cd+zA|iGAdrEy7qjs7vkrQtLJJOS@>-(mMwP>sh7cM7>IT-DDvgI#HP5 z;ZUo7MHGuTQRJnQW4u~NOaor5Rhs5La~zzm6|vl-={=>*9bUc9%1_!&&Vtbp zbA5J=?*R$!BP4jVjMci?WSg!s3AqMYOVmXxZ)D)i#4g30eL8Y1;b4C?*{rg}UTI+C zssRvS&WDFodFe*`Y_NeaydHeTck2sR(KWs-jqecE6dOHeC;RcG&jZK*W~IxIm`n^G^gA@r1mFFi;qL=P(vK?qRe$&{>h;@;JS}zygOU_?r=BA>P}9 ziR3z?@|t0uynzBYJi^}?%SPQOSFxVl2>5_A9_lx?kom7gI*`DA%1ZlG>-0FN>GR2I z{?P$DgiG0?w-`lKSeVj0bgpZuXv#`CS+$+caKxCrN8mB{F*TixDX)~!y$hjzHJl2Y zLH-|JKl;DAY~TR*;j3Pm2O=YfC}D-CWgkr8Vw>tpg8`)u_N5|O|Fx*+{eOOn?X>P4 zT@%^hr0P=Xym(qMqY;}kLqe4T^TBavE$nQ&krN1y?)OVKbFE!$C-{E zCwetgXd;u=6P`kKStNrFgYGBy#_*FJ6_KmekyLRi$j54N;kI9LzCf+hEbvV%@Ydoj zov(w~6QWl5oJ6r_w;pz~U#fYqf*b*OVxKy^7qL7V!42O(-E-Y;I*~}jwv5TO|L8dO zWeGLWmv(&wWkErmB4?)q`tS^~Cv|mB8Q`|xw#8|2l*Kz_qE+WefLMP-ZOqr)Au-_@ zyp^P?mI4|#`1Xue|Caa z4x9V=pv#1jg}tGg+~^gS)SI=R2PDA%1b9eQizz+W)Zrz1`<)lOg(>U&_MSvfA!*407W6RU77|I|Dv zt=4kSKj>&hBTG$s|+F&qiNKH}b@K&|Yrsvo`jYr+iVVpECkDbg9GoNwu&GlzPC* zMpJD$nnCe5p>mW)bnEMNG>vUOSxVd>e$0eVh(p`+!|xa{zTz_j{|<_gSTPg8X}Z zEG>tUQ)R2J=!sI6^Io5!>{3n^;1rMN$PW}S=tPnb>!@_UW0e5>^@3=z!E0jvUYX0O zHx5cA{Zkh5qc+$6#y*(ehlc}OXfiQ;B=f@Z0t6YIR-}TQXRAO}nB|Sqpyk$5H6$9|3lWIPOA8<2|?}IG2l=e+3C%z1vS( zfbhg&dn^_FwoOlsWk#CTw$e&n^|d-4&DQx}qeYG3I*%6J)|jqx>?i8g zRZ;nAN<`a#*+nhiz?z#ow6hAw|HD{hs#b|Q{F&{@YT8gFWKtQ;P^KWiz}vl40GU3x zx!P|cTJuI+=Er-x{=*MZw;XX?&u^4>xzVN^NR?v;(w z(FLg%m-M36R}D`s!0(Fgo3``oFi(iWZB^aZj95wz zm-4TCp>|rTf)|XFf;giY&BMf2kGkQg+Q+}Az`bjgycEnxOVWc_L+=Nra{vn;6hh{%j=e+(4UG;(ZNH>{WBe&GRO;vYvSgP3h{qT>%Az`}@ zYf8pvehZWFQ|XLGBcHdwkc+F0V3hYri{^HT+ z{)Bm00b8*b{n-)#ZctV~~1bGGKM{KV94X#rD0{HD&R^=EP4v(PGL_AWytDv%+1T(jKkv z;B;`Vr)K$SB1gm=YHt_|Q{c^+|AF?>wQ>CccTM>X{U=o=ghy2vNF;Kuztt-N*$7+$ zmoRYqaT&@M(Ti7qT^K{GVVyWg)>UKDQW0Z5P=taj7s}IcR zUHG6qzacEpfj~or4hTF*qlD?5fq(pXi1ynVgv_?#^+lrz>*mT*I?%GZz-fR-cMMou ztW7s>hHm*S+C_$<>NJ0k31Q(US-6A$_nEJ1a?{-EpI_ag zu|c(He#Us+UuUqFBMn{DqYIGcY?iB!?^fO}eL=^>tjXlgn%Zg1AX8O2cv>gjxF%rw zlS#w#glpB3*+(!X!gD;1D%jbZr{ZyKNAk+4AQNTID#~U9<_`ewcpT5Jg}Vo1vzaR2 zRj70KaYIzN*B=afFlHeV7QFWsbJ`!jOOGVK@gvPc60JV-uAOHW09E4t<2n2Im#{s4 zU6-Fa6A{2TU~e^Ro(K8AYWndmQqZSvb&}n_Mvom**vr}$KSachmiU==yM0VJpF#AT zz^3oR)>27`TyryV08d8|DI}sJD0}T)AYU!>7~XHsY`)84e@6SWKY8EhF|Sl}2mo$I zvc%-Kt1drg;=U{r$#h3_N-6F{W$n)9BK*i3#PZtm94Q)o&W2hx?wjpp9A+k59}&lE z4J2PQsw249li*#56X=NIa3~UYq?zi`zfFQq_WaynWr}Sml88?br;MHGzHueVTzw6ddm%WkGzG zdoX3K<1oK&s1G&%4=4DA+Xi^XX#1-2I5AV%z&~z-8r2eu|CT*PFv7(3E2Jo!rpJN5 zOmLZ*Gaq~?G~zC>;k2mjMY#19O4Q&4CF&D@HGgxY-Z$`VVP7K9f!s>+J;mb)voC7> zAmHpkdra8^YO!c%ilB@fRLIu=JwSQf61crP?8OPY!0f7{zI?|Th`xXOs3!rv`5;_r zIJMUq1_nbym8^4JRFOXnEQI2o)@wn01ELKO9rTKB%K%gyMo3#XZR?G}*DvQm7j11Z zT()akRbh|6xbBX3s#i;=&#Wi3O^oJwx6xQ^myXhi#g|3pelDq>ROPSu9#DZcl*=Na zRG67{SC$_nnXXV5myRUYqb#n`Fv=4&q^aT2K&CyA^LHWxW?cEx?Rlze$Q|Ei?!0rAo+x&nbyjv`~D<9nZ@*(>c@EdxsB&8Aqg1P$YYT)gg9Un3B97J&q zdw6dnLHwHtHGtI&8Eu52R|co{7!e1(d;b;>D9&rXb^J@C9x*xN)a$&DA!#SWgLrTBl(Mr~|eB6`aD)ReKTZ{*Xe&r%+ zsZtBf*zNA}mw)h5>_zwd$z9CQK5jI@`+?XYqBh;bqER18QRQ%zh79RjBl>VZU!ReW zj>${<%0Mp|NNL|cc>r}Zw2|d+Z_brMS5HyqAfIO7HOAj@JmXnqsE;DFNmYcW1>}C* zz-i^f+@|k$Wz)_UGT4J!y>OFQ186_FS}scp(!3>cRbHxhYXnr-K{&ZjC*TramyK01 zWYfffA68KUPp($LA}|tU#~G;BG}=e;CKPE4;1e?2de2Nqcb}ObByf5|d>KFMn>%A! z-6ga~o?l7z2zgo{KpQ9xk11;462-cpHf8p#E-Q*Ciq#YrNz#c=wt(;D-F1kP*OS&I zovxSQhp75hNri z!0(f2a3ds{A{10az6Bz*?i(`wlA;y7>T0CKf>xOUu+uzz2uq^3A7KE=TSb{`z)1P4 zy3eqgh1;QCy}*l8u`+VY3}nu6#_Mh12fLLaaW7j65%=V1MCowLgRq)05R474A@wJO z`%-4Vb;!PKktCBx&amFsC$hNZK~x`6$@5Ew}4kQi1ufAzlg)a3ycl#q1a| z2pS+0Z;wOd5i%pCm9O-LLIO2&HwM@McLi-$P=mQ&((wqi*aynfQao@=_0PeK>|x05 zm%gue5U)2wE0598X?7>cUT}a^jRKH*3ac&uWe~;Xs0MLX*2`mYo|K2IXYY;=Q`5m< zMgT^va0{S~8otZ<#1nG9gLy6mb8q<+QAefjFh`4K8(d%5)W6axM#x`S{dQ6x2Cyr4 z3S}U?WnN}>KZSC!h^~t7pszXAAd?;#b~$y+>ss9t_(Md6DWWq^+E(Y$dyCL>Votf| z%z0N6dO22h3rF*Rsi%xN24@1S#r;%NWY-$J=)x@Y)9guKRL(m|AH&~#0}&>@{ziXq zFG`(Q(LK6gl6{NCIquEQ50A05^MkhNv?BXD1ooPhgM~?D{W_NqHY>MJs5(Ij9+lo0 z1^#c@)c+KqeiHY8UklT|c+F3FS$H*$DP#{jgLFTWd|P?1r~1zE&L6Jns@xPVOGHff z7CoMt2F75hj@XB$3JG)>W;Vs79pq}%O&CwxvYaq5w(lqIn4ScmQ9ibvxMnrS` zt2oT*Hl~`H7YcsSzFfB}S1!s|x+`+#{d#c3-I-Sw#psv&6jDHLosgF1%28yDI3rakNsr#=LMLhK>b5To zP!*JW)Jh5})`EeRBM=T5MIoIW=Km;+S8#a>E`x7_WyVH1K6*=h8@T9w-lJ#I(%>>k zr#2Sq{sO&>9RhdF91VZ0Ys!zS@t-lAlac6YlF&EgmS9qUwts;OnnA` zbK718YPS~Fc*4i{U=7gK9Wce#pgU*_X0@iLjQ%9aBF%ZcAcn01I-5oY_D$}(8#$M zILPfl`&0CPZ~Wlobnx~tdhu|Ft4`%?UTfQ0#dCl<1G?ltYe&_@J%mn6oPVZD-|#_( ztfp9kpqjQ@KR-N2XRkJLlTWtJy5n94>wEfp$%7Ztplj)g=7{k)1$uS!MP-+cmpU~i zlTV6JwW)1)%8on3ZpwW-zAN7&Tt1?LllP09FIB*|4B((Hl$#R-ms zzoDV|hsF!3EGf4o&fT@2x(OJ6nsi83**EwYtv4w&{T@2Q`&VY<0%1ABtptPFd1LJ$ zBIHV38F_uPm`6%7?$AIid7~4>s3lXm=nhsS;9zC3E>z&``8SKZuI($pi}_2Co$E9G zYR~9{1%IwQR{cC;K3uov2tmsQFEFf>`duf zMEAn`&5z)RPOH7ieX)1yexWx9%l^UFf2(gpwr91+hq>e)Hfw;XN~f7b1~r*gj1{^L z;j0VnR!IO0QT$sr?+NhPW9bbBpqYnMjZ7_;sre5`?XNXtx{c0Okx?U2^~W{Tai=lc zm-w6L13j)n(B66p>>Y}xprx(1kcqbrd|$r7*A;cS3i#T{SThb z#2>0R?Ej&X$W(+PV_%c4h+?vnY$3Y|MV7MfamW_gDakU{WJ@9v{fxnR%W2p8G!6b$veXj|=7j^}p~9g#E#kRY&UG0f~)@fV$Q+^H@8 zej;yvb;G2O|1MWhwF%+I`*lUU2KkPnR&{J}GCEg60IZZby^H(?yy^nQLyDytd-LBHH@C^(0(aucM^WhROYCHd`+2O}wfVRL2*lG_jVVu1Bco&1MmiCN znJdU5@(^@K6Z!7~&C5tAU~^eH6B!*gY-ko8d>84H;;o5IDG6Unm-Rrdz^oNr294G%`Tsd7Dz*KZ z#1xZycc3aiL8WF~NtC0ifKqV!SSJDd^l#&KJk_hA{r+_MKr3h%dJfKS!f-=J6vLdR>5tnme(r!uT%RBXSFUOYj_K>=j$<-BdEnD?5h(Hh?W9Dcccke*)l zGc?l6nhm)MbV6R%K#ALZYOv+y?{&2BB2wT{cN2wU!em;l4~b$>7Tv(~G5i42^N6IB z1Qcnc-cizW;M=?>-G99Y)Z4GvLHq*;28k%{6J-6v%L48pUG+HEBB;OmCC@*KtN$w5 zml!72JlB4;64$i27bCBHE=f>?`nR8wBInE11PHXh{e{!zh7)CA_ zS+k_`qp-uSV&Gb!J&oN6fP`KMJ(GL7h6*L=?XFjN6=wNYa*rbepxhZK^vRd}zgWOj zdJjb3<`in9*h==u1Kb;-GLdnYp+1$shRL&!1l)>4<;$WHj}rw~Po7?v_Zd&T$i{K! z(j_;Eqi~iE7nc0T?0eT;Ro%JnJ7)wuEB3Can^NuS`PLA`V2Eu96jPt{8U|K|y3W!1 zJEu1&DWei(pT_R0Fq*x05N}&XfRY}5M@v9l_53e)I~>8AA{`<3-(4K52=;D=a&85G zn`zAOga3F+s8YFNMF->x9G%X)g~`5OGVuOzVrn_*>tO_n&^PMy_80Wt5P5K<6BQ9q z@=nCldZJS5*yWL|v&7|~H=l8n1E5w-dd7XeneXsrWHu=4N~{@Pkp0Hmc8J_dA;q$U zwl)9T+u%EN&B4BNZiS-Z2;mC@5rI4PvNNZ%MB^qlC7q*O*_1rMdjajY5E62qHJAd; zi4NLfI)2RxE!UunID@_}V1r-k;Cg>zqI3im=;drsZ>(Ksj^fT3N2^BMj+eos;E3CY z*=K^fvV0?d`fg6!Wh@})n~N6g5M%)Sqn>Vf^8QwPoz4P@!t9aTTS+xc0*J5uW&({ar%IOl=Az1X#%4 zr?_v%c)s#_;}8qtm~9HrClMSZ!f|VhCrCB$ZXcjb77yZOjdKrK<4Hcm`?j7S z*jS>zM7_a>DP^y=s3PX9J%0}T0C{fA zp3$fdvGA2N=k^UJ2+rPIQP$$&NbN0_A#knm(UTcsKd->|S@E8W+pTQzU_2&U_`s3@ z_h#ot9WvBEV7JLNyw8_{yUql@YC>H2^+KKTqyH{Pgbc(? zq-FD95CSZLY41I!DfW+2zn|Gn|BZKZDjI(kiSYP1iU3|3o*gUCei<=y(>%(h+qi!&c~GUQ+_f|;;DgEm)!^gd_2)5ysB_tc zIM$>mN({`le^`u30|hF%GEQpDl4OfF#dcg;vDBm!K}>GpKJ8r5R3SZxkQbKs4?IHLf8IWWW{<-mlnPsooypZ*|* z#GSSH5BPip|IvAzMiM%3O(1PX3IRh@7Vv9$Sw3K407`sV1Sy%X+fQsgB%+jd5jIv_ zcDW|a`j>5}Q~x#JGt;0KAtH(`PY}(*Z2|<-GchW?3>HzQhYG(9L2Dzjw|mZp7%k zDR594XWG_or}Jq(kO{r^)vt>>MFWl%A0PEuP6EDg)NL#M=tet(82t68!e5jdB7Z|( z@90xxe-y|*Sc%lVD=?wGJHgwJ&zpEH?|A8{3jb7T1*?>m(p}~%q|U-0hR7tvC(-Oi z$trib2gW(Xbnf1&tr{%pmm=56Nr(w8NqE%Z*B3YPgLz1M0JOVTU8JBh3<;1LK_;0i?w}%RSAlO;>F1U|9I=uuStq=$>$aPPY_SYtdG4T85U*yKVj>j z6~PX17u7Fv)z{bI!I(F;XwcUP2UyHCoQAidvm0b(cDay^r(_0>fv^r7FU+x~*`aCT603GU>=#37a9ENGq&;vg1`{m64MZ=TZT+Dkoxnp-ijjdntjz*9BkJMT zZQt&3pT2z9;}ELeLy}P4<}0PHklTL-8(pZ12pfDmzK=3ORodfgz0>cR#?l0j!w4>N z-1HcTI1Axo!#_?H`Mun9C?@J{{TJz=cpmm1^1XBJO4egziFUT@GW1fP!@ll6xG#RL z>2uA@UuC1jd>>Lz{_yMYV4i-{eAw|YwMemwR z71##KL7$7P%OUj3>GXrO#*DVN4MDIJx}yNh2NUU;+c4a*{8TJr@8xG84PiC#i3D3u zw{At90W&%QHUeue`>D_3qN&-!5@DSb925e(w;uIHjI!}X){gw+G^7hgO{S%5z&@&E zzrTe=IH(<+G`XTf=`we3Yqqa(3LJIqiScd)|fWe6m&QPHuU zeJ)BR`+#{%n?pq#C#x3i($)P52aw#!q?4(-I=6P4ym_mp7Ig^$LJ~sN-UvbpvS*7v z52IPH6M|U)*!aNK!))TMA=j4s2>Vp1{i!r4{_eFM*fwpn*p~KW-<|R!*k514(?f42 z6vN+J`>y@zg@l)WSArJ5eZ>4-%t2{APk zVNlWN=DPJgXKshO`V+26b#KTvqxA?ni^z@A!N5gV^Sr=4gMUE1my098P4r%;Bhc3a zCv{y=Q)p zw%Mbdh+zD+icL7x_r;T8H;IWv@iMwJ`8W62Z0aDs!2a81ck(e{n`9O<1iQKEK%OTM z6VhYHK(3xV=v6gD`J8@W=Vlr#BO4%rM4^8Gu|~R;{dCsI=1tMe^3)Ifb3D~T&j-?f zo}OGtihJS4#kB~R*ZNA1olff%L`aJ6;jwAUJU846Jm)d|bmjcyzWL2Oo^Q9W{IK6O zY@c75FQ>^*0$jJGtoNE*mGF8By3+*dxP}bi16)5TEOZXCdGn5(@MeOJ%vXM9;w(oD zFaM*qci%sEmh%}36c!a_ApPp5exk{$}F!?BjWsqyaYPOBK7fy|RlKqg_ z@ZC#h6Va#W7zmN)_1Ka1J9%pIa2fb_zOc|wiF=-A@zk42%!2CAh$VP&*WkLxL?|4hCxWp z_-`d6L{?05-f~g5slkugWG--ELUA714D?a#`VTgRmra?ClPf~jk1cnhl z;`P)NZW9k3rAPSUJ`;s-6|soMGOBC)6r=x(wfhBwm4Y6;_2-sy?2oCL6pm%7>hEf1AGs8LNKcwWa9Vr zP-UWYUsCK3P}7tx;Hqh?r}Mc!x_yYlFp9z-o$eU#%@MQtLF*a4&I5%$?A=HRx)J1KW(E~=1VItKjtpv`>Y1ELWa}4xg7}+SkdQJ7-#H;3 z)0%1xpEJMa-EKRpUY$qIC_ldV_%sIUw|PZP*}MgZIt%mFq%1`S4=<9d!tsh*=!13> z1(r5;X!-t~(g~=&AH9r*gp{LZR$r1y_o>PA+~UDhIpId*=)nC>ZFl>f0S2d~S??_+ zfOIgRJ`@HDkzqoYdLh1%gi|0~oHDoE@r0ynBV|(<7|n2UCw}>~;X4l!p7N`cC z5kBX1ZZ>|6#l)6m)(i1MaMv)kz~8z|3i;ysy96Xj>QeQGCavG< z1ZG)XyreE+kV3`{v(b<)-QZl2pv1}&)FCl*=!tHWn56|hYlj{^?^zwdxH^CwKAIdHz<8h){ZUHZC zQV6mJNAF48@iJKG*A5!Vhw5uwc<|tP>dmD<06Xl`aEo1K>FPpxrld6rM(T}VH zmuG9&ECo($>pc2s&2S^8mkC?NCm2PqTfMKhjEhb-(g_4g!CDIK`>$~ z5IgotKb*rbXa`thA=^+_w|kx|I3vT)14&XXpg8r<;Mb?Z+}ov!ZN?aHJoFdEHrGe1 z7RZ)H+)_2Xf(?L=Cn^;n#YROuP81t|Efwg$&vEpw(5^Rp1ihud%_Y4{F;TBBKGM{b zL!V4hw810-rcH~|hW;<&$RN_41>EQdF9og=|7KNLO)QAU66{U6=j z2y<7V&gT+Q^hEB~GmnGmh`l8>O-LkTe$i7C0tc{+M$6Wto)=`-4mV40dJC+Lk%-TCc9X!`P!Ca4U3zuIEB*Pk6XP$sWVyM#bN64%rvC=b>9 zG=-Pa-=d|zju!_uZfkYRM?vf2WtX2Hx<)kpSWZ10y@N-_-rujV{8JCHYeG3f_lykg zq!#QV%*BAu+Q(wl;W0UyHrF_q_u0;Yb0#0czfjbBYpYTAenigHS3?vC_Tl&2HXp10 ze)p%aUs4|0t3Z+aP_KU=-sGkbX*uQD$PN%SL@~c|eLoMkEhN=_G4j-Z`NK0E@^qye zb(vpei+ctoC}RF>?sWe?KAupT%eh)F#b7lqA4E@_f;6r0=p|4)GxT(4S?By9F!Y3}P|#pF*Hh`c-UKin4)_aJ*(yK$&y08Qbi(c?pIJ#GG; zd->bEukEP5s;7Uu z&Tb!g=Q4>tfUuWSol5YcQ=MeGtw{4;=_(C2jEmRIsv>!)_7RtPw9}Yw?N^2TJl_xM zi5~VzAojLjRzt*Y`l212XgX187l;GqPn+B}3)3PoP%E}=X2uft6G=S1a&ZrsL|L*} z?~5a^%#qf#nVvExEkLDcLg^wB!lLMl8gbQoO=v&Yd-zn=NIhU{#HNjKoT?(a$I7t> zGmivt11hbBIE=^_z#0|DVY#b5d~3jKthCw;+P5^!z(;)>?MG}VoyLGvWb?iCv1}g)tcqnAW^VF8@7lQzx(KXSm*q`w?92l6 z>#u$aq!s#>E95KxkP$!RaBMp!`>j-re$036V~kB~>)-0+7Eo-EX}e`n%GicJo!|;; zK?gucHX0S2%AIMzU?&ljqVNo4cs^h3CP}qFa3M>gp4vsVzkL zd)WrFSmw(PvM&eTWtw(iJ8nEp`M{=kWT272r(CV)-Pj;@gt_VYc;axgw6zZjic>45 z6XW}C)0>cLMO!PoIN8AiaY!oDy>s&#DM8NO%CySol_}arMUR9gt)eeEV>qwsBFKOC zKGrtyzacH7E(`>Lha6r}CYOEd#1ar&{yLAeu2u;^_(s``oskEtN^vPG)KQ)aL{dUK zn8UH8GFmQeQ!n6e#F46TjJ1GrR&LYDpp?kk&3qwGM-l!yq9Iy73@(idtrV7j#+)3V zYS+(;xvYLdgP+N+AEIhF5PngvbHSKDc=RgHbqc%(eKKVmeGWB6dlM{VvI@+fFa=@I z^7{!`1XVp9K?^pm4DYROfQk*lk#}fHHZ#}LMre^!^Kx2HG8R3JSUE#9O{Fg_FiZy` z6r*yM2UTN;q+D;W+r#d>6!FQ?Ur8pTUV_CnwIiAvZ^Jg4Ur6u>viLcc+1#b*f2*0* z_&F&z=5O#!h9jj;mlr)^T`_6Eh`-5S0(@NV&#H;oEXgGdT!dCAXb?nC-h!*hR-(S) ztSk2srSA!$`th*N(s~IH-{oEW2a&Q27~yJ?Ws3B-(XXMjy(onn;Qwd&4|DiI=a{?+ zqvvbQo|k^p{A1ObS`K8TEdhjM#6E#(EHCSzXuMn4F({^zK_EkfO4vL;+my>7TzF0# zERH)e-yU!)hf@?aF&^b8MK=BoV!e#j_ zP6533GY@s zK4_POMmc*`opr>q=zgFlgt8m@bu>EC%6g`<6N*+o*+xl5-;M})tnI1Oeu2Hi1FKBa ze|%ypPPlyKK!^3~1T~>ckvy^20t=Slc;Lr16M%iS=;zNnZ=eA$m$-iW^970kv;LFo z*8T0hw)9n;8PB%WC)w*q>a)bkM+U*#iwOha#sP0#8knNJhEW`NESKc?J!`nEN`D8A z_4TiaFG?E11fQudDHesmLtA0|=_^3Of1mqJ30p9qN)SIuLm4g=_uTGm-K6HHYQtp6 zXt=0(6w>&{GcDPg_ZCnUdVeGcQQ|`w{n**pHRWb~x)iif1@9?^veuUH$4XaA9M0qw zv>{(&6`Q!=wBZRV`37q`R3f5rI5Uo(&i{k-XOVViD^SK5ysKnpXYH<5+vg40O0b0h zqc`fVq$B*ZfNaR+QmSrJGQ8#P`cUTsxxY{C;Z$Vo4WGBQyRYWF9@&b-D5#r`^FcYYd_iaQHw-Vy z>&Eorwh_61O&?9&bNVvh(&()Aid37Wh^ec)%8aKpUJC&MPvnEzcxZ<1P7(A=?!Lo` z(6ne{4S%5Ece(D&JtCsaNIv>%^kqjAX%IuJi`1uH1P z5A-B(^K^cGe_Xp2Ex(@j{5DHR+woI(C6hNtPQA~%YO3yu+r_VON32B#TKD}g3m~0s z|5&td;kPLp?_9XeaY3VBAnH`%7C4~adF+r99VX{Q8WMN&#q(P2`I1a(!QK}U#BM+C zSWffdG*AVU5T08QI!UwJ!d)5J@Uab_tW-1%zHtVc2z}FON|MTU4{dD5l&|6M&pLGM zZ`f&{72$*`%;I8A)=H77s#S^lP2{HjRlBQmY%cixo5)fce;6ufJZ!sF0BR zlLzCEod_zJwkJ5R_6G=NdD#Z|xzdryiwazm5eVrg-+0hBNL8GCP6}$=0*{__o^>ji zDf?-(;gaQ4Kciqo{bau0R$I>dBvHtCQzc^`j^Vd0E!@ykb*eLewRAk7*z&q{8_K6 zuNzsw(kF*4S+nfm$SwK#j9eigogo(20mE(}@Zz&tgdV zLc%xY()q4&F0j~XeewS`Ui^=&!MNhz%KGNEx|b^phF?UY?nZiA%v7gof2qsZ`n-fu~u3TlB9RjZpu$ z!ey%ixmkZ8iAt(VbDkU@)l1P!RA2{U;<7b(fK5ICoWeZ(DL%V}M35t%HU%5LuS67c}* zM<6|D#M}T9PoWklM0T&C_pv!U9<`3bZyr+Y4nME_= zPI*AA256xd#NBhonKT=`-e~+o@-8Rg_2bc3vE0Mh*grfJXfrCy#QN2DQL#`*}zOk*xdhL4;{ zq!Ez54GEpFh0fJzgGt9cKxkgaK@rcW10{0m+&R|nb+56hneDY!cJano-bIEdBt6eV z@v{=QNgWv66jv|eQDY(K%S<{X6qWUDQ#RP8`R5h)DCtBI+g1{EdnjUvpDYL- zs6U>tIVGc7P7!-MF_JwSYEl7gydnGw*7zdrKnm+VHbUjCZEk$^vY_~@?C)@!T+H_O z;1p+!Y1&|8_MM+i%L`?)gX6qI4%Q-j7tJ=v0&imr3&xHEl5ZX9nE!`%N0M?=)jRGQ}1lDm$P9?ULdnIuU|OsT+8g#e*GnYNNs zgC1A0VIg>yybse;x}=2ML*P=nxriv;-YFVi&8yzzl=%^@YELi@3-?l!nf$-3E&!V zdY(;%>F98XnGp6Dp_u>mNJv?=strSz%pX~^LgGD#GqSfkl3Vf_8Q34#g`T%oe_bf> zeW#iuVxU>G4r)04IG=fIMenAm4a9#*-%5`{@^NeQAbhb9b`)#KJ}K(hRyd)A0DeSV z&QvA7$Ds1sFT2+Xgi3!*emae4>r!o>Jre(5P@p+=B_l90-2B!bsR3ur zw+8=2u{_S{V?Qm+i(VxfZ_uk>_lr0Ecvp%vbb4!9{9CxZ7N;7tuO0r^?jwG8#rq|Z zH8I5S2(kTZ0zLJ`;%i8&P-5QNmBKCIQs;AxM+1N)Rnd-Eb+*i~UkkF*J^U=YI&BC1 zIJD~a16+v7`I^)07wH4Ha1|^-b?t{Z`h;YO5Pot0vZTd<`0CpJ3_ZFccio5Pb?KAG zQ5BE}SA?@pO$Z>A((}pSe%yPY=`#C9Jq>r`qqlO)c@^ZfOdiEoM?oNa3mEnJHi?N% zjTR;01}%dqX{uM}+^z=|XD>UJU+QNtR5z%v$0G#S8d(X0NQH}Fb8gEq?T6t_Vuj8< zKDldTcsnKParPEMe8jMU-G@2C#~?i zn7t^yuf|27umYlX8pO8=wxNmm_uMCll5K)M)$+c5vS_Fxy3~sP#q&N!Z7BN2_Zzy& zOh2`F<}4poBh?Fb9AM%OA+W<>4a7+Zi99j4x~@;7h_-QOt{Z&8f1D8?yjKP zFJ(?`IGj$i=b}lb~D*`d2b6=moMLxuLIPI^Z6hdHXY+- zQU&qcJ3kn^g)qC5nURX{l?~F!yZ2zOODTcYNuce-@la`76vE?YPkT_&#ZJT9MM4ra8Y!l{>V2dX z8=hwVG(o&DcLG+E8fXBQUp*L&$$s>&fd+lR;>=9C6jOiX`g`(9*%{l+`3mIejo7AM z#KK|u1IuhRFr;mWtrnyKj$4!^(NG)JyIbdHpm%p(ZPYVW>F(!*R`H`ll0^*6%H$vI z%ULNT3d0DJ#kfxwttu`a%Dd>%& zZ}5DaR(ZsFaVGTa^Mmup=&$0*KF1#wdr5-NVvV6QK4wsTukn|k!N>m({jQ=b@?is5 zfYw)fOI$2pGG)<3B(pKyvW10Bp~|y37&h}KP)ipdW3vIS*4({>`XPI~O7sW7_JTxJ z{x&2n@o^u55P`cjw|d-PM6VWCyqx@0uc5$mhWe|>hTvMER`t=~*{|ng^bTpLCjuO+ z(=`>79uB}ZB81#NH-F-DP8O5yQJ0#0pe-;S$NK%%W8R+U!+N7b=FYpTJ4xw9y7t)( zYV{gpbZFv9<4MOXFAr~U9Q^%*!2RhS!eQ9yTz{tz^QOC$|7!}L75%}xoj43&9XoQx zLDBj6<8H+1kYWIZ<|@6N1aU(pR7D@5eu_9gQ}S=mahl0L;N&~>!&yjsJ>042*f+Fp z{a9A%6FbB~;WPAdF(x(xTOBSZK)7|+>|PQ15*dE5YYaImD_{|`3&lH#2d(Q~c$Jo4 zARQu74nzhWpZYP)i?6(2or}r;E6T_r5&u~D>9UAOkzoa}ri|`@5)Y9NZpf@5H=Va6 zKX@ZRLHQMMee*q{o5F@h^ft}`umAPY+&p2;*?J=Z^vzSmk2*h|%X;V6 zz6)=QKA`(5SgZEcr7h>|<$I7+qKGBd9Y{TQ7@R8HyJaqKRHz_mTD<>dz;ZaD&Bp7S z=P=z|lEmU4-}g$W2?kO*>`Kl0;CFqvQ=mxVQNpjW>JZf?kIeFKiKat<;q%Gn`Ipt* z_Yx6ALj-GiXkd)CaF^QF8Jwq?n)NqU*xbRor;hZt z$ls_uIN6DTEz8@Z@0eg=n{DPke2k3psy0ju*E zxN`Cv22_-41=CelF`#eOMxv1(BE7k7qO={o7-VS#Xt>Vv=5-qutv7=3gLx}(Jm*D|&YK;y@argvv0o39_4=eFarv z$whAQ-i`2yQLoq%g%Kiq)1fu=jy2wxW{ob&R4$1$@VV)=vu$|$7Y)3j-LoZa%HPFDKxFA+eUh+{Qpzt7%xX?!?(zkm!7!V*|uyJ#xO zQ7kNh(t%!*`#|mC*x`d!5i#R48{8f5Qi8YrY z!pprT&+v9$`l27?)6EvW|NUi8&V^+$We(|#mir5TnL$%yD(A{Gv`WvKM)*IkK3;yt zdNJRF@3SY1!_Bi?Wt?6-al=#>>5r8l%e~sShHs7C9&dhKa_0XxY{ZRu;m3!M0`%JQX>}9#YlY!f< zUd?y+43dfn+dj{4hBdvA6NIpmwdQpxWJj>an(+bjCbVDJglm`|2f^moomV^+xm0Ms z=ut;Z(XGJ;fHj2Wqw7N*hkzGp^TFri)1ghn=CM$%miN_qIl%Pc03O!X$?=O4*3%G& z$6UH?dS03;{zU&B;T>K!C{j8@pW-avFFamv*moT(TCJuYTsvt;+DGrb!8SV!c?K_lHtvWDH0ghL!o_lN{LOz9( zwRLB=01@m0Vy&HN9)ON$AvJFSH-!eMgUI)W37)VBP-lnD0!Of08_X*N*a9>u3wDwM zKOMsWFYV%<3Ok5sI2GTnIrt$XA}SYt!-=3}H>g)Q&j=9EC%^g*ef>hjXU?Nj`up{T z=$3@)I+Y^|FXXZGdVbB7enUzKl&*epvt|q{ukg@*>s|2m)y&UM&6=L7R<&HYS54Ye z^R+hBUl^pUTh`kbb_*(Woexr$?vQFOVH0T-Bu$Ev`$&6Hf0@awtW<{Cf`r-vXt#kJ zFnWW49Gp@Gt97{h&pG5v=RQzw=zjJVaAKWiBvvSz>zcirU4YKo`nxFI6)Oq_j?IYU zh^>th7~={p_@u3I3cZFp>WIpOfVhG6gM@K)IYNu6lwBQXvZ7<=6y#494DKSCq~f0) zAk6{FS|8?D%uCpm%&dd7J{MSBi5PJ%M|x5MX$iUub-ocp<^IT%>Tpn1{ZOU9BdPnO zZ18sWdKB8M*E4Tp3?Zzlr26c1Tc9gK)*1P|+b2}FeDZzc7*;Mtc@)iOwbDy8It19EbT_wvYy^gqi2 z#M5Iz<3q5x4Ub~6A?DXI(9`{Xyz3|=T_(dk5uqsjjfdNMY9<`mCHUSZ)l!NCG?ENM z=)X!2aKA`|_7fBtO{fXgSK=4nR|H36uYy;{_7G=<^e;cS8>|6g#hbsksq~->#iHca z=GPvra$?}HxqwTD{y%4IJBKf2g+q0J5TmOWD1<&gN(9!MgzA>M7Hwzpk#@*2k~9sa z(|OcT&g4ML6-QY3dLFBIzO$W2L^T*njdjas4lI0V;=UL|cQrdS;cdIo^;P59TYVeo zU&V>(%zEBQPkn_2qzc<+C3DNZe9SWl9eVP^NZiG75ccLOMoV9kd9B?8hD+fzK=Fgc z&`~DcSPZDpGJWZ*_c#<4?B}|Ha%<7*5;$1zVB6Fd+O$4$WhXFuB>$Bx8cp&~A>}I> zJ)0g5W;`e|)PpLLPCJ2%ci)P%l}MX$$M9H~sr3r)P1U5{8p{U}A+GN{SeDkDnl73d zo4wU^6dzL6Vwp`>q%$JicuQ#TB76p{lMmYtkQfB%xQ!ZB66m>zf5rs)UOy<3iMU-m zH3NgBgnOV*Bx3nw2hjah+bJ7cp-_e}ydirC>)OBJEjxWIH=%e+*Vr+PVSU`=r>%?7d zD781)`m_N0u^5lvrRWG1n6>kkRy|uwn@Uq}ZE973Xo5#4<8O%nB&rj2fU&?_w2NiH zd)}tZt1Im<2%9jKV$k_#9Uf0i{{wbvAo+996D7&m5xPD2QQJ|`iC#H_f4JI(LjN7W zXAYu;Y7jgUYlu7v2%ixAWeoet4TD2~4H6wS ze#Ahfq=ANH5kuOr?J7BIxF8y=se;bYIuroUc@^mb?oq7Hu>Atn8Hy5kwD{O{=g5Ee zll(Q2=qTj=dF`80pYDQy8njI}@hC!D=^wBBm%q;&g<`e~gIzO$k6ZmWAypnp-jDu5 z=9QxSwFe0l6~r+(@S2DUY}zlvWQGM?KVui{){~wTk)#ocx*Jz{@I+L7rR|l}O-w>o zx{c=DfRr@%Wdona=t{MAEn_M#DCkP~;A8gABaSW$~&rEJ|*q zJQh5HH{i`ToJ7`BSkX)qjeCF;L>qD}lTSlL51?aBT1R+Wyjb8esFI9n5^GHQA?m7s z@{gM9Sh6_YHDL~i*deLR_nRdG{tTqJ@K*NYfe}uG^qD^*E{|`OLp=0kwep`t)Hc@< zVl}j39Qu_t9?SOWb1XT*rrbjsyzB6ju{Yc!#MJoI9kNNe%YUCoG`bQ)?gS#U0az{^)#uFYVYt)2rMv-9P>SH39F^?4|{o zS>yXKXl^L6dcX>c7$tMyfTKB-IC#+Ls`n4}_pm|{&n#Zm-1z;Dc3+t#Aa?zyV}^G; z=$oFFvLueDDGVb(CwTavdGe|jKI+GxtS0NT)Q>kYg}V!zj!lgo(qtH3W19J|DbN#l zA&z$zFzbZA4b0;W%-(!@5MJWorKQ%|U(Ry!^y^pN^Ensw3nsieG8|r3k?LJVG{${% zELn5wI0KxpoiX|RdA~mAG-cGIYiz|VJllBLzs8F)61qC(4>GQRPc<&djlL-fcw{Bc z2^@=V*h{FB(Fsvr<2OqrdBOg$NEf_ZRk%>IO%2=o%qO|3GHd9p+?i9!P0#jAOd9LZ zyQAWY)$gtFq~KCH{}+mpo-H^Fl%JC40#cz%X;lwWdLj^Y)P#ZS9T(SE47py;y-55Q zXymlYnW*TP_{dH^>BIW+Pz9-$<{l^cqf;F6R**#Ju|^K%5Uu!BTUpfwAc^qn&-~Ju zW5$^}pfeYCu9ZT1?{x^RWs>C2l=y+)&9uZFnwtn#t?w#W2?J$Xw*05Rp zm6IaK9ToA0DG9_O;1q}LFaHr|4@iS&G6<^bBMa^ZN0E13DFTMNF_3DZe;z$LG1V#^LWiHhwc*=$Iz3=9g1LJH64c>Ki8qsULCYD}%3oI~1` zgr&67^ibU7Hw?Ot=)qMG!5?GSMbulRV{Eh?X->YlWb#JzoLW4@)0U#%9P%MQWU{P> zmSAehd1TCcZAF;%qo(`Fsx9C0v$RIu1XtGAmCqmd_e_KYqxq7uLjm9XFo` zoDs3+z8Lpe$attp-;3%-P-8d<34-CbORu{`Jh()b=99(3o!EANnOlrpI*MVWBn?uA z!+3OBfadhoq=3j?MiLDs2n*k1tj;A5&LW{TEDu6W|LZ|0G`Gi^de->I9ned-76-&X zqsK$csFHk$RUvcd(9oNEo8j)e-dJgAA3%d~ist)Rjpnx@{3&@HY%% z(d&TqAc&oC%zUh=SGtjYgybGf!SNsB%nSz9U>BjMQZ_K+bIXG;XIh~y5<5@HQIZc) zjFeD+^FVyC-x?~s%{?Y;m@D3by2elb7tsT(5>(m(U?kTn(9{7+fZ`Fi+j3j69TcpD z2D90r84yB4($h|y=yTkLM3`f&c1Ys*E}o)2OYuAAh}&sUuNM@-12uBnn?mv#~U3@%>#1SFqs ztVnHY%K~Br`HW7#K-<0k3?wMGUM%tXmO0dRYnka)F3a$xaVfq-GstekxIbl|;q}t| z&p&0#+49TiMv$+^w-eYsKp2AXMeZgT`fw+24rs7`5O_lD=mN-QIKgS+FYtQyAHRtT zxtVe312Ms?nAixZ89VO+j_({w0FG&H+&W3>%2*SAoyX#=?a_cWDgW7;u;#2X)OdwAsPNRlVVr+|cV@28gYM3i3$ENk=H`pcK+`0_CUmqG$Awwr!p9SYA9 z4ZD$lHiGtuk1`7o*>gT#*!qHnUjC`))vLX0!Wy5(&Ii2>Z~H`@ z7B2APBpjHSB<=5B!JVUuhe~%CKB_R6aJ=Z9 zN&(f1XrOE46mibHe-=H2RGcAsr`QB;aW2Q;S3ww4mrmu#(QkY zA%PQN>|jG#r0++fEo_~|8zU90ALUY$H^LxQbj$#qPT<7wK&pEgI-1qzael52%pYS<( znVbOQ5AI|2i)~MiT%4%nO^nZ`nR$4YQ~$!BMBrc=VauxaK6TlgjeqS!L&hT#{XqW>Bt=lj7 zdDGh?muTpVLtl0Z(KDr0{{01e^p`Pm1RYsOIIz@cXGGOdJg%QPL9bgeQEq)kbkj`G zZL}6lnUHN3Qc`;08ML4%<6cSJ2j_(5r(&FYUW!0OUkhAfY~#{*@uFcdr1CbqA-GUG z1>TU&&t2MhJ`Ed?JuPk-i9C(}v*gl&p)7uB7qfBUi$sZaDM||9?ezmyv&TMPF7R*% z%cMvy6tUw^=KXrnTqFW_%CQ8@e35}eNta)T`gJ0#xyZ8tXt4rurf~2m+(yiX2E39}Xj_p9m2N-ZnrD9ch!Yq>jVS4N85Qdh;L_FU@zrV5mSHMU6h4 zFRqZxeAy(?uqyV&yi2q3&hezN{0~lo2^qqTtak>}T8G+tUhVZ$RyBcRTp+4e@BbQs zPV?t6(DVjdm%ACs!ltHEe#%qf>bweSDU^>lknU-FfPdFP$?4>@c){zF z8>Y-DI0(3e65cQ{vzf#RF7CN#EH!-L)ami;7ShZ4PJGcp%^w7Fuzh0uS8X>VW6j8% zSfFk2>EUqZ=0OZmW^y^+o{>cJB^w_?W%F;lAaj# zpN=IWqGDTW(q;?kvZGw8%Njz8G?f$XoO$^3wMB$t9As9m856}mzrAkc*M%&n3#Ks> zjc^u}Xr*jsEWUP=Pq&q`SRA!PE5L|yZ>|2et@Xox#~I?&v$|0fhzNKEUl_JQ# z%Q5|c5Ffp!P)2#6z?HQ-|Fca0Ejqvce~aEJzSYS0N&}f{(?}U|!n8!u)R#dU2IRGi z&oS|)QZ#WN(gRb6r{9m7mRGF3TBqN14D)z=r+p%${;$<%1bO5ho2fwM?W%>Zx9?{V zF06IrxQQBuKydu}!-JwLN;UaLQ<{L&vL7SX3$c*rt8bFq#UgOy+CetLT7a?hB5o3# z=zGCPq~$o_fx~=cqlp|RfJ`s+PIHCs7uIjBr!ZPzyAaT3Q%ERlnD!GUFLDlJ_iq%y z*mWfM{{Fi~hT<;J0xtWyQM*H><~Y#V`%K?N?=-ACcabcaK=1EAc zdBLX;hwZXSCot)lE0ZzpN(YEo4*ByK8z6Sb^l+8JWlbRUzJwJd2k1m2{+wqIDPBnL z5I5Fa>cJeNJjhg}MSCgfG(cBzw!r&w<2>crgEDx$_1cX$!drKiKU0L?9mq#N^GPKl zsTE`sSoPC-&tZFf`_($-tW=xvi3&*VEtrg? zb=#fL=F0@=xkkb=66h=~JV0=+t+@JjV}!=3lLMr}%*e-w%Px_AoybpeODKb1frYqj zN03iztMTjS^L*g1&$y{}{m4t7xSj0p@z{h^I}N59ezm+lUf>%%fw~%{lr&FRyU-{~ z{jxdYi|yIAxho3q^t~@IebK)nm6uUS?<0O8Oq=g#vCC%;ZN6xaPsPHL;*{q3DTl0_ z8Ffq~O_0CFIaU#GcT(h;rC?|nDr9b|zXbwIel5hGuEFomA@((St`E_S|ZH z%Yl-<-fx5c;tK8~rT}M*`!`$+ynz1nAb+%pT+Vx&Oq+4pt)k{zGZ?h(QMAxD zY!?R~KeUFGSWO^EteO*plK;RCs;X9$unaeH|Hz6SKrhC0z2^|b?fk@9-|2sJv6vn{d0ILas-;d@HrHaj-{bpqh~Se#v?wV>o3uD&!YWFQ0x32PE79* z)>`!P+n~HeFa4Q)`)@Lxm1R3zNthM;46eYn2$*ky-_EZlz|#i6#vWWEsH$9hhKVS1 zQ;2PMdcn<<-%t=OI>FQ4gg&582}5MS@9_!!p{9o~!fo*t_f||O#33A(x=nVY;%wJV z4374MQxnAf%li+gLikmG2d{kV{*IzBxV@CfUd)1)@7I3?1}xW9UCTaZ(ARQsEX6_D zBntITQfTIz6U@!89kt-U!t2B;$7yfN9{LGYblXvY%Tp#uU3rf{bgGP#Xdg7)LvWd} zhy#h?^mnfkmXJRt4-(m1DbHRJ0U07e$LNf z!2}Tk}H4dT$G0k5kf=x!w;t$)U{nW5!0|t)!?R0_Hnl$5s3T8t?}qy6hM= zX7Dl}I0=LOLrhyAFn4f4I7#s%+u$T9TXg5Lzw) zbf)XjWrz3S|6-Bv&PXvDe&(=Fg%v-uS__|yTTr6vNDQ3c2dgZ|=Z$t;#}EdmEHKxC zjDg_v@aaA$xy+%gWE__D zeUK_L#VDYuH+=s3(T3vg3B-O8VA(f6rK1=McU@|jVg^h`2@$Ntu*E~(U-qHOW^BI{O7TXPKO4#03{(T zj~Z^mp-%#x=JVr$pdB^)QSq77GBy@iq`9Yr^&LZ6A8j)Ph8a@k-3{I<^S78$>9MhinbDAw2C9B#39Xc1l`L}TdI@a48A3YQ$h;t<>vRqH5n5u_$O%8-eVXz|q(t=K z^gXcL0f{?h9{Z8Q)j!_mrtJfZhu9|UyKMloAoEI`M1Sqd2&{V!rU~wx^KzuT-6%ea z%f{V-rLQ54d+j9lE31pIwco!xCEf^f_-4#2paN^w4zcqszHs@EHG0Ggwzdr;pNAWN z#h2GpNPe7}Z5jE2!vkd5hicKGDk_}fp>=}~AD3V@n#jZT#;X&&ua2APl_m(cefXkW zMT7ij1XT^AA@wf~FH-|Zc$fY@u-^L9wA`$HWEDNmOQ02f^##);BXhbxbmsgK>RWkR z2(WU3R@csMe1@JQiha(LiGxVI2vbb85>WGlY2%*Zl|{*-pL5Xo<4d->?7~?y+rcf3 zJ2Ab>*%dIqHEc?;sIGImX9U~koU zSMHhbUz58MF-v#9)I^ezegTR*3UDa8mkAw@%gUh0Odt4Ua2hpex5Ufkef(}jJblQ|pdhsY|; z&r!4Az2H!?j19!Iw`~QMJwX=Bu16=u5%K2_Tau)|As36pt&rJfyV=#>SErLZo9~?Z z*8nSyqGM($=%D=jvsqz|-N=E7tWnenPb+c^k;VC@1|w-Z1S2@r4@BXTW9Zc+m>Rs! zF9xqk^e`$`N!iC5b4T8;WG2TYJLLdyraFvAOc!`%k2l4@|qq89WB-B7eQ;@sUfw zC>t*S@*761F!@sb>4P+@BFVcaUnP%x0e)kM3-;RFsISl+>PvS$%2al+iZGyf+|$ie zz{jhRYg($gOr-n}Q&T+lW*Gt1`%KDB*0KH&lMX!zzE5^K$$wwk5Tg&1Os7qJ)l+C2 zmOoCQi(OY6GIKxZ!aYsK)%@f;c(I;jGAD5~=S{teUzte%oeC0fOEa`)QaIFq;KoH# z{_VF3X(N6WkPb^OdD)VUo;SDvQWEFN2-$qDRaN)pMmzXgG9kvswE?|HT5_~BrTuD^ zHGqW*%zKba&;FpU_}(I|*YP_D-MUtgxY@eLLggk2#H?fPZc?2aO`|}OTCVYQujHzL z5cCAs2mQ@U$h&1m{?Hw{1F4K*qRw=lycaNg{$>mCMs&^!Cd)B9{9l(P*O?!3ch)=LP(SQ+OqHfc@Wut*lPj!&EdgA#g`l3 z57r~X9w7Ay=jBLl8=glLU(Kbc(|>sHX4)=7-)kMt8QTA#UxOnnMM6mP&2JgK>2Eb? z*Ol6?T`%u0rpfR6yqHbGDiaX)r^V^%Jr_}oQ$Hv`(EWlq*EPDX$Gyn3CWX*q;6b+k zwb{DQa=P`3QN}o!m!TL3i^=bP(K<37NtHV59`@Vg?|Sdzx{(%~%wwwMkSQ4WEB2YP z+^Q5wKNE@JE(4DSTt*ji zW*u-){gj08O-YkwgE7E_w`yzHg8H66KE@(`kfU2ew;_h8+FrEvWr2B(3x0+vu`}n_ zk-36WbJhN2lSTBueLG4=j%j1)=kN4T%qH3$jP65e2lk^D(mrG|#XLIghB=UtxV=L; z*gWgu*Df$xeSL|Dq%^ng_cI4ohi>o+ok`{D!AINr6)4h_^VDa4IDcBuDk}f#dWqVD zw)R&=dWFMduJR6DN*3~$A6qW$C?+QyJvsNx`-8=SiD%xoiAv|B6ULFcu9244R@igM z^DNdyDV{B;UU~bCyG#%^>%qNm&X$0^;Y9!1Z&UenUSQAM>F%z!h_%q>F4=B}2S8?& zI?jchGR7d_{o#D@+M9)q80g@&C_#2_2WvJ)o`k3s4p7%yT$a##mwgF^4$l39%P0{x zdgKn4!Y>^?*@NuesmZ8^Eu~;KbnzhTU%@%m!M^$d=+Bo*ECS4sZ<5T(^Al>S_0EX! zMyKYxc;$g!a#!{dGBC?WOj{{ha)5wXSbv+IAFMxtZ2f%cMT|U{)chGA-Tz`k);}qd zHtSc^^cnje&XlE&@CON;4SUdxc|`2ljbBg|aE@c{&ck-KBLo9)ZDCFc4T}psa>tW0 zI{&ObBdtd_twOfH3Vd<@&@^}Dz9H*A3PCPvkDv_F{kX>Ea=3j{=SpFAyt>R=$`23z z1EUh?fvz!gQO14Ap9^7ptBr@XXQaDgANN}mM9SZW%?ac=$qbrits!=n!1yhodRL*?)CBk103ja>H7?`~wI6P$5~$<%No zg)1wxe{%HDuJf}7Q&2rZEp-*_*wNlIM%qkO?4O1E;U75&M zQvM;KIDvW3dR2=B&o6w+dX|9WkH&uKD#ap}0`Fx)q5_eHRzw4xaXEnSUA9?;8sLA< zWCk53o67^Yx*WFfW01$)s})aHU1oV)dlZZ;>;KH)ODW_ziL!%d4eHSA7^}}a@2g+z zg{#p1ZcadU;Srdb8z)dt&d4F^{Jna)%!WpW$BK$8U-J1rk&nphy{Y{nTl|sfE#oNN z@gGM6kM*FW#!0;_4YY7!2R}blICN_@=x}qDy#gm$oT@xjyjLWANP4lmQ|6Y)5NVGr zO=>qh7$0%$aAvY73{tQ#y2u`0jpF?6Vs@|z1y(fOkc!}{Iv-Vc5Ran`Z9jlWkFq(e z#k6B?qXRdhU^Kjou+Lshes8<_c6Xt5o9R~*I7?{97f3M|K7WmZc9=@}p4_}rBfb6O z@a^|}2TYvT&)b{9jl^GP-7_;ll~JehMZ>hUcaS^Jmb`_!I2dZ`!+e~ZUdNuprQqE# zM0Dkyxw`|v;=-EP%NC#a<)VJqBZZN_)0SkJgexARGsup1kCR1O$2yB*{BWpa&Y!lz zV4)l0E(;hpGL?ygD$kQll1RzlV_(~27~s}tSK&*P17Q9-8?6}iyQ7&+x4Hc~iv&Ss zCnE1&=xxPVaG@8pz>mhwf^Kqr`~DQjJYHCnnpUYSg8Gyu)JHkc=D?16pwI-p_R)wT+Q+-<(rW`>iLGOh#~Ipc%=kh`AtV z%S)b!eRR_q>?n?s*vBR^qC_I4>>DvVQMgKdeM3KIG1c%=P?;7mnJpwn!{~h2#dnB) z^3U^Q^j3eWcZWu$j1l3+J8;gN2J6)6*nACSvrrp5H{u+0FG~#OQ|1&?pH7TevfDjqMRZtx zt~j^7qkBs;DzH=52=3Ih>q}p}8X5O@YVnu0{f?0+d#1=FLdTsQu0Nk$)%b9V{z2t@ zs%OY|jo)#8TDgSpY5qCFA7|%Paw=YOVf`3w6)H|IPw&X+7R6q7<_t|jN>Ho@6BhVV z?r-UW-4u+2p3AWL*waSVt$V(Aj6R|jVtSBzFT4m;E>yEC2Mmj0*7AO7_x?&>E6K)j zRdnK*Nj{?uqhyvgQTC>AtvMF9x(bKv&yy*u;H&o~IEIC-*tqM|yd(U~-ld;PY4yI` z>$+G@_wGSh>qxB&WqX;@2V^zxG1u+!31hVJ84W#~$PrPdYgaSt)}TGg1U>CsvW+#8 z5cBO?>ShY~vYw4kA!V%h9>wZNCO6+QSL(%Mr=D#A^Qd_?JYvtNNcZd|bOhu@W;1ziM6RE6(Ia@An@9-mN&7Bju(I4=fFzPCl(Ql{IXGl(CD9KJDNvi87F| z5msphr-iByUV_;ZdnrE@b7UT^rNRp^NT=MPlvrUgiEAjfr&H$fQiXgEPBq!v&WcP_ z`lxkgwO)H_`MUTXeQd87?k+-qL9Vb=j@3(48;ai+xXbU@Aua#m!3&?KeTq{B&FFM? zo>x2sN)W?@J{Voan#OJFrzq@6A55E@6Ihzqo>d_?z+IT-#^AO5&ilp;TOYjgp~v-f z$DNpSCg~fu?PiQbnH7Lz=ZjeUvIMqCtZR0KE0TqTpSqdssZfINfgU?pkrC@i5iUSB|*NdjizY+S>P%;610!ACcBLmkxEB5YtW^YFH6&7|gGu0HJ^rj~Ig^#I+7vvKEP zXI4iO%T!j;mMTf4Tj*-MSl#@mzLS%Jsu$t)5V;kfkh&7`tnRM`!u<7W^ZnB>@fTu@ z`u1F1&sQT-D9I=i6fGk2(Fs$R|9m$hXAEG1-Or(<{pNa^?p!G*7wF8L)k#>FDg9fS zafDRa!n`;m8=JqsIEVSY!qh2%--Zc;5oBZKt$O$#*R^Bb>SqcKdSq8)B?T}GDN`=t zKboUUJj9(f+`S5@2M?>Xw$AhWPJdw8orduKrRkC7jo|Z zdI2DJms>inbI2cq*JEIYy`JN$PqaF>IDLS5K8vt%+0=)7K~F!|51f;qmsByZ{`TgN zdg4gOeKE&i|Dx=Jr04$rZg2B#T>7*vQlWC>3Yra~pHDm};+-5^u38?bQXm{J;N8Yu zlyUXg7mVb|9@x1Qm(asZ@q`{wKM`-+JvJ2o@kK&MGGUYe26~$?AAdNJzyTUIZeom* zC>Hb0aEf>{gFdry3(VD?8rs<;gF8p9wXY39_0jJ9 z%I05UE|ZZN2b50Fnt%;-nnOHVRk`bobRhOVrmEM8CG?_9feoq2t}5ZcsQay#?pws?^Y*=#3w|EaN2r(di>4d_Gn*D5 zl&nQ_JsHC&h%b=-S?n>{plCo7PVNo85! zB$z;kvA!1guLe&f7xgk7qe`vYZ_Fu$kQh#LW>A2{99tjt3vkXf`LLiGss43#ouxXy zn8Bs+%+;DF+Pt>Vbrrnljfa=OrCv44(TJ@jJsXh^@m>d7zO!2`$CwKU-82GWoeMSG zyDF^m!5&D$+YzI8!y-RK35r_|->sxKsPx(-$P^EIZk7`96o=>1F9H*AIhPT7za&;^ zq!0On6m)RsV0jDr&Gp{Jn{AFaMgd1Lw|fC-`75FRF?Zl8lYP2-)^65mg5)J0ycM7; zey_gvymmymx$Rx|)^=*vH5a4A?=kl}X-X%PYd9C>FXn$MSn_f4TEP_E&~x>?k4(WtV#M)h|lC1Yd!j+Y$=hn{+Q{IM@af8g0h+ki>4V zT8F`IBEVo7ZIb6?d`XK1cI$wK!Rp(&Sg4lZhVMGL;B{r!?=~Yq>@2*sqxsAH=3POM9PL95fZ)>dDjn{&y+JYyb65#n0G(IOcr-=GSDDL7L8?+$9 zT4!7;NLhj^26J{)nID01zbq);`qZJXIN@_&I0>QPHY2hQQ|q~c?qw3f^_}%5BZ)5Z z>B87LvNNC}tZ^1LiW?50&|*jZvGP`X%REA>VS<0@-hny623&zCz4C{9Av~6wk1pMu zyrk0coSyX{`CDqM^W}Rs$8k)Y9E8DNg@IK>uU+k%r8*~jTVCqC?!&6ULL(8ic4#V? z@H93=jm*i=ZbZ&AY;HSidwEMnt;s%%hrp#<^OekMWcPe(tUg*rVFTSEMb%oWS~GxD zzugp6Z}=sDzdOuv#!dA6X`a{p$U61srQe86*4KAf-m!dw`Zp`@jaEN<#7l+(jfTI$ zXv!Fi<=AC%d<@uxkzL5Nwr>|f>fSOT?@84iiC6@VRzUL1xAoo;@Zyq`op2!dodTX1 zWo$szSB3~(8>2&;SO)N)3b>R7Sn2o%MF7)k+WZ#@S_+rvG)BX zr~`d9Do>6`J2)H?egpF#hPdBr6v*!gGrb-8?((EhOdwVKS!Re>i`HLEGG?ioy^m}8 zqYn?<8?3&IsUO{nzEYXkZZMsr$+l`?=53rbt4l--wF0YS)D_+1?6vkdiS!nYCq->E z<)B-o{^(}n6_jBp>3+clzkG@P2wl)i! z__o~T1>yTV2(cG-cNBp$Of%j=0+b|Tg{YpDUDpGjYtlx1^tXK7IE{pG~3NBpk zYZeaa&FXfjT2E4l_^`t=^!f;6l!ru*Z)o66QmFJ%6=**HCS_FX(q4=LuS}^KQOuYz z9&#j~(z_=8^zh`t|#Rx7tLZy>2LBz}c?1<4b z*#H4`_O8Ny^P5q>Vkx?1g_Apd+GE{GAuG)5=v1o=btXt8uF&&5L8DxTaEvAC_CpTD z1DY+Pb5r~t6u<}1Ok&9eysL`s4XK`N%-Ep-K?*j()4N! z3J?|Rlp*!s`(G(XdU`ld{Nu+xk?1OIDfcm;dh%)JgtFF#9mX9gM>+6Vy z?klK>+gD~q!=l)!6YNaOxjv3;4bhF$q~_F^Y~DX2DOk z92NrW0vjH{a&Q)_7fFlzIu}%nqYmC7A&GnDk?n67(w^FNgI^kZqd^+h-)5C!0Yxp< zFPIj9*%6xwt;FbI$=3o-XWanYw$h7^fsp$7&)b%KH(`y@0mL492CXRs{{WaHm}QN^ z!>H4X{9tbTIbwF{-qY^152_K`4$VuY0$+noHoGypR*iGnCl_)R?_3ESh9={~<8?)+ z>0Q$w@*2M?sz@}7TR%GDVx}c)Z~n&Z%h|Kzg^UNnEd1l2tQqE=5lca~KWNJ+)=S}g zz~uTBULFgDX>M9gB6fpV`b}D!YSof=jp*r1k!{nnBM0MFLRP{bJ>m}NIL_}&#<1U} zVLF@Ag;YKXMi8U& zdywYwtwBd_0x4i;b||{fkRMx+Uev!9FQa$^L@{7Cd`ArJA0y-C5!( z9uJc*l;jzH2mTzo!B^-uU;hJNmK&y^H7~LgzEku>Zj0>*<}z3$u)D9sL1||I`^4?|3q}UC82KimOxGw!S+YO?BEJN%qLx=UFapv7c9i?#52|vQ znrOGTe4~xTt9!K>S?S)m2!muIV%q*v8(mOn=GUX3PcQfB=t#7;B53H}`Q8%S(_%=C zadw6au57qA}m;@9P@?xJ6#D%dDGm^tb` ze-KP<$eGk6X*@{>KGSMfiLnhBOJs4u>8V$g#yCFw0fWmJcGZ!j*9QzI9$pY(9*)|) zic*_NRMV0DyZi@3dw#yhcv}<%zE8!(L5;DDcE9)6IFs`F+pk<6G`p0dk3M6P$+_By ztMx~uKZABt-F|C<8XqW5kV}($U6!=#KT5`6r?FDN)7jq#LdtJHu#`!(e8ZP~041&apmqo+V^7g+~Si8sYU?`FMw?HB$|fuQg& zxN4sYNXjcwPAvFptkO7iWl_1T{E{`&%A5T4^UuS-_NE#Q zqB#QYf3o#iLJJTaMtT@Qp{3(a`;%Ay-VM#A~b8}yN$ zvK4fD)P99>|5MT9+sRNH!*eQ*t2J1#ASwJYRPqOf0n}=VoL|zB`=>jDP-#c}%o`|V zGanHNe)F_Zl_%5~EpZr~pvh&VIWQaG*CK9^c|4Sli!d&?GVwG z#yp;u{4oY^q|{mC0`$vNrki2U%as$7MU;BX!!i_70h^9M>$=V%rwfVYQ7`htDKPIq zXZ2fl1o^rTP}lc+oyl=31{09o#)9Ct+HPcb9f>USKAk8t&glJ|@n{d9l8BN3?YM_g z^4g=Q@}0;7x39*Y-R7Y4y&t8kdlO)Lh;}=h6S$o``cRGm9NbEW=Ykgrie9(ZWBPvbnO$1CMnv0eBaLMPkJj*457EBN zfNLOm#mXvGTm#yZdDEfJOB9iQ7Zg^CT(h>?Eb7z}A);y!1TOJ&KSb)h)N^4byw*9f z->7u=CxjF?K*-#J4&!VKZ*+KGvQYJ-ATa9qlnZ+PEMmd&J$psFFSkzp)FCVNPJlQX z5{+2b54q```pe(}xS*R*p2n3`#8FVFP?Q+1(kC--vvs_;3gO^}I+*$4e{4afGfW_? zjU4*<4I8C`2vp+odvb-!?DaQj7PAB+Tfb1Cq_@Wo#(c$XcceRla83Cpwn}m1HZpJK z(_2Z6GPErO0-xz$c6=q>LXF;$m2tQQRp(0^meq|0M(L8+SA0p0drtx+<#UN;r#MSG zOV{7tWF|mR|5Py&Rg*uC#kHn5VFH&Rl!=cfL^b;=Ze z+Q1D)z2j`(QTN_(rGI*76YbAm5aPRgup5-5L|>R}f*=*VV?T9TZw`^LaPr5usu`57 zyC@+?Q3hC@phuM~d_IbKt5g1ZA2W4!z!cZ67^wOdSp70yGI?6~;ai*3XhXjfl+^v1 zq*s#T`-bp{Y))HjjEGdPvr)U=gf!bLDU~cZ35yYG7+W5b22E}njdQ`T#(|W{=Yl3T z%{&xpS2v=64tQ=nBDWacL}fj)e`Rg5>;ja#^X=qFonAXpOFe7U zOsPJJt?Z-$YqOI8HN`NS##d9~V3TX5koL`n<<<#5W>{=NeZkG+RSD>PQ%mAv_;&GN z1#B>dX~dAaE*DUHbt5lc^e^r@Ml7%wJAMg}&t3j@eOAIO!E*F4RvR)_-TeNU@EJRY z{Rdob^oqMrcma0Fw7W0nWVokZ06NY1+r@Tfp)>v_A4{(+xSf6QeW`+S>6&zz#q1TR zbzCf5O?G`FuPJwc6+Fv?Xrptn<8r>kZ*Zrl39#S`>@JTA98$m?%%u8YzC_&<=q)?e z%5CUR7=^Et(Rz%egj`hY=2KhAOCBr$vr!c740aS<9L~C=`nCqC>3#}M*#V^GUGC|# zHwN6K&mMgOdd(PV#(T??cDG=QPvt*>qnbSmH%SqB)RIXvj1P*Q@z_g+RLno}C4}F9 z6+!T#_d2;-?{%+>%G2D2EiLq2oyUg=2Z^iq@1;v}7KksEy$~p$b?$SizgwoH@KR23 zO^5d}6QQY)sy9r*($e=eY5X{UrZ@OqR7F29{d)0Ay2AQB9G9L$4BzftcfF$?+|Nzi zr)0-9HozY5`?-2$YwSVO{l@gzH-WN-+TFVWkn`=l!H5v)U|Sm7!>OU3+v{j)U;4?@ zkh7STsyBT2JNsi#6SD8=mHS?vBuh2(YhgOb$qA%e;`#|o0-#VkmGQpMIS736nGVkQ zZGG(KP(eL56XXpX6J*YhxX0*Ys7;+wSN(pT&6rRyuDhkF$HNm0(GB0XINbXncl}tQd=XfS!qGMUVe8}~dFnf7s0QCpB<_$VaM3;(?VUYsH2w(NjegNAqv8Tre{oBYiH z?rj3x6po!PPmU%S>-dDEXxzIYD_S*QY0%Xr= z6J+@Z@o1OjiJ;#MopP{`b|PX%8^anCDHGN3!qls{#*_B5^^?TUgI(sQuM=N+#_0$T z1~qzkoo`Zllu2)=vzOmyh6`QlJ_~fg;>JA``UfruR|{j8kK0Y!@3qEKn<)ewFydtx z`37O?f_HyU2qgH2>CdUs0lm*M{9=Ej#S}Kwc4RbYTUs0VQz73V0ndv?HkSpaj(g1J zpt9N`jxmFWD^SPho6aTpP~l|oAz0r5QKvd-obt~t_CM~6(32{@q)m{-eL=^;GWXn9 zQR3!fa=)sZ(2~zQ63=u&DU&3&zWveTUSB*94jV$z-SVASZ+%iRr4#sdyBfs7p=>*H zu@m9}9WUoW(CPK}z-{r&dd$AA8yA&?kWq=bv%)v*8rzZf$>*B#7uCyVFR;)SQT7ii#KMN=hOzGTw+C!hv;$1a&3O_fW%Ap`Q4rxE6d@zD= zuJ*hCZ-xt4kkNY%;~zpizTVxtxQp>6d%h))`>Oo#g?&KWcn-^z9rSlT zUMM0!W><~Vuei-{PexyU81ucq%T^1_N7LROwz{1!QRT6rjZ828Mvz?PsZ%Ahs0oE8 zEla>jK7zKALOwG_R`XxK!gnrROdY=!{AvdE^^C9IKOL~O+Ys*Dp^jLYMHyW7;m0wA zMc}6oVr(^J;%Lh^JV)`{MYhdTi!Z=*Ij%H6oBdW1h$n zJ1Pn9F>}^#9k``IR5u>2{Dzb9wQ8bZPv}oc!Tv6WZ_tCh&0eaPjqIwW?sCBqx*icI z|IFg!4~O|cSvKAKfpwN>>fR7{_NOBC$iwyrK<}~75hx+~fYx{+=;KTt3&mTk_J>gg zP{dNEc7x#g4=~;WcS&QUve=7fK>#Dnp3?OL*3g&)9*w68%uXjBNI@S5hT!uaj`7+Z=J`r&~$rcM#@kZ zx&G)Z&&7wKFcteetG&;;FIwP}A_c?xvp@k6Y5n?^9RlZS?!@lzU|zzH1eUQ%d?B9w z${)w+*!lx}qbD94JjxkU(;myto4Y`Sq#tz33b`uB;2x9O3!>L~mYc1xQAWc>2?3xO z_8{y14v+SDJ*ICjN2*GuJ}NHfrpU^ptRdc%;zaIXGcyg0 zbVlq&lSq5@Qq-!P8xHz^=3|kWVC7$ja|MY=I9V1TzCh~I=Gv>B;y*ojz2LzRdD+1C z+ER2YWk{sETr5jX|B}*+Z(0ry`u_DHt1Vzefw1!e>JzXUnXm^Ob=88VLQD-T_yo_M zGYiu`jzu?-|0C&f!<%zkxgOJmT!M(`F*Q%6(7cKZp)0QEmHMys z)V4IPvP1e8{{{^1kjRH@sDx{KKsv*8~{$^JmHgO zUyA&;poax*C>D!fS5xU`t1}cMB$lw%+>fRB*Ch8jkd8zIp%zKZ)7@FQ4>v>ZZs=~Zp0TjG2rJ3a#a0v z%C(!|qr(jgUY>!^b#G&J<6QrswO%EOI8G=WYlpcG;=tKI8$ zrJLSEw@u1|Jrn+YY%N)472Mv&h;b!YdQaky`(I;ie0R8@rE+<&4^MJ^FPK+Mv>}nU zxt_AB_KZIY7PUV5Me$z1rb0%wuFFLMD6h8GJcLb&RsCNqyHdyA{C;)cvU|8 z#D{I5vMt?0XLb=MFh*S+o6STI@ zbw*Z1F5RPCuI(*84pQIey;o3&tdwHeFDP~?u&O_;DK%_VOCtN!Ps0diQf(7TFuDEQ zspo>>;(zq5S?^0z-;EIa?+LVU?YvRco8KpWS(iyf3Kj3tQU|js%_T$Qn9Voht%FTi z!7~vr2?cnuQR;?LWVRZy?5q>=edY^Z978-Od7ohPM0o^tBD|ey6lJi!{gMFPB~%?F z2~6zCmxz>v3#k>!d*G1aZW|tfp9PjeUO`j}zt<5x-9a&x zQ4BB=cK=mEI@fiuvtQSn z4W!GPKLIGLcAGWWV4lJ<)@&`(BBtakk`&L1|1k+YGP0;&K=58ExsgIL+3`O3gTaOL z9RC5zo#;`m5iAI>(jBKz@A!{VxXWr`hu`2lW=68n+2kdPN>x~Q@*iZE&?j2+Z0--o zTILO60SF5W#dx3z2s6rB&a!HWwKY?CwqhcYW z=#E}CBrwzXiIVtsJQ|5!yOTgBV6JTK&!Ii5eccV`^f$kQx^|uHqZ__F+mF01i-inw z4iISROIxDvZ6w8NI0;_1r#cbnG?OPtbwANHR;rD)o{wB2E2q<;QQcg}_rty7|2GqJ z>-%4f-T6OMZ~Q<0dZna7vTsc&yF|&Fv1LtzNM#uzL{gT>c8ao=C1f|Y$R3giLx^lc z_9*+lk8Nhmoa=L5ulM)!{@!lipT7UV;LPQmb3L!e^ZsPs{0GOdDHakT;6fashja6< zf6(o@fpB7$hg&y!X`EO(21q6ApB#Nz14e!4MR4q2O-zs@@>EMG?N%IJ#H5|SUYW+! z3m#&)Ro~YSzAiLWx-SJ{6zoxHQWe{-ku;CPU(_s&Z+dH4Wl0$yLfi9`?8 z*FQpt8)j1Z1qb<5)=@y~G;HD4VqqQ`!&Ojgv16_&T@Xb@b2F>33Ey;~VIt&%BJN-1 zrr=wt3)K#sZ&z*u6Tho-_$~awD2P$bJ%qi9>j}24ySIgI&&3nS^8ThSGGT54&`rU3 zS`7Z22uX@(dj~%PExs_i{N=m(aTRgPG-@i1GqF(V{j4uCY|RF7E#O_c2zoc@mhaQ2 zM0#+K-ws@xMekr;+V2A+x_iE7Bc|yrFZRK$4?fYK%^#ky6z=hx#GUdk1!-q?hvXPg z`58N)YZhx(UJshpHAF2op!H{<;3V*NATB)VA;2FKGA_;X*(R9`t(Af6GoIgWn0_$t zBX1Gz9|a9?W?CtUzRkdWd7WZ61BFuWv!pMhuVt1>J?lX3h;7Pl4Gl=+E&8Ol)WRV( z8zBsq`fRID1SgfD0)qXu(`7y)ROtE@C6n8?42;ua2u@;m3%&JeLcHd+1%Y45ZWJo> zkh^0G`lz=)HChie?~}OyG~xqqEp8Igjx@9|oH~X+MF;2q1*5LOgCGy@q<9!fAF=6T zzNmP)!ilMcZsBr``LHs^D0`JUdLu}9v0vu4<=JBS&_yK^`a z_eQ_wgSoN_9Md|!$(-Inzi*OAxzK? zt83Wk)|15r7PMKlr*57=%e`z*!yZ?-zkMSUN)s8&k%yZbj=x`|Z1TSmd`FA^Ue92W8 z8ua@Cl{?1jH<8Lx%Zd;DpMDx!C$BcEqM7xJ9zx6$QjTdi?VK^2DV zQtnaDN1Bp^8IA+*DkOMxI(NYiIY=MsIsR=3T67quY94I|n&U19KbgtGs?^EY&~*l> z9l78Qup7N~w0Qn+YKQbJC3Tj0!qW&$sDetR#8b3j4SqIAd{wUD1i4n@016bpcj1@U zN~Lg7FT^G;R|-T<2T9zdzXMuMWKCl?!0H#Ul~dv4bXjQ-soQ6_TK#p_nD~FBu*7pb zZhwUU0);VMTv0YEjqFXES5=q1a6n&!$mgt7TV8gT(MJ5s z$NwZ;k~R9M1q>i7CJB|xDK`g@&zIU|509vNG&!Lr|5Bf8D))4P3b^JY;UBhut+)EH z)UwNd)7Rd162m5bRelj=^Un91Z7_Ol7DjcZS)Q%Rd+BflvUR+}y-ksh zVX06mh?0051}*XK{`tJuKGKM5e3EdMG@c36^yiK}on-FLTIV{gwO<8d^|d!X_|39| zBk#r~wnJ`r;hl{Z?atqJxh|*i#oU?9=ISyU17+8oGM#kHG&Q8K+kyuq(Y>>q=)Jl0MgcjqNnOGGbUH@+i8qJku8l#Qr$eX=*I&Nod+@g)oMv2&3_|T;mUwNvu z0Uiy{aZ4inV#DslcIfWZG;N}L51by>SEV)SL>~C`K6D4Hyj>d*acO!RH}g`28?z(O z{$@hI+PLr2ug)umB2{K>?8ZwUx1-x28w#R|^ml?Li?X)-?1BKX4Z;?;)e7#r-3l($ z-G-)Yao|FdCQUp6j$<^;^B~Q#kqCQsasa`m$AU^xGsb;ryBX!B@*v%v*UAEef+gA2Cceh*jQX9^cP| zg5IeWm95PqO}fkz@7oz|6hlCnkthd@Hd9PzIFY+}MnfxBZU|Lfj1F56rl3B}e=FOU z0s0EL4cxSk$?oYwv_nr?fuP?g+-gs8&?_UY)`Gr}4p@&(0Nm3n> z2*~{t$Vw)h1@y!rhWYt+a(Y4_PXJ6)Ko1+tjupWK7~*&YZ2_ zO5{a6yEcSgSuDchqJq#0-@zo|)n%0v0lg_Ne!scjD{aGf4-BBCb-uJU;xnH* zQBP)Fb$>+tY3~x*mN!A{A!TAuE2hAD@C>Es1v(3U3N*!@*ygP+r91}<>j$VEZSKn> zn{ZrPqjrg(O#{#r3{g(TcA%F?}K!7C#1v$r`X#-Vj$qVoM0n`*~lI&qaW~Ns6qDfJR z2_`BM8Tn28{3ib66Y;Mb=+-0ti#N&?qH9fjuYMgO|i-bXtCvG9iz1IvmPi&DA z1LMSH9y1}b)<7uCPIq-0l~7s)yjW9ehM@;pUEeMC(C*9%1*ikJ^RHAEwE`dQlvYUh z;P-&Ih^y?>UP-_4;ge6lx`$uoc71-@tmMptjsQiiEI+OthF&^GL0?mVY&*3EDr~=m znr9noTa-S^n12Aipb2>U0=d@)3s4C>3QnI4+d+1p^4W96Z&H$dWzl4M@O9CGk3DHw z7Yujc?O>SzCbG9AL_WwM=VMS**4Ho8S9mUXi1pfE8q-6TmkZ6K2gW)(`3o@S6#1w9 zLo9w_lSqq3{)C+G>viybm2Zw*#*Ue9LgP+6=OIcPon|~Z^WXOq?=_9IVNkFn*~_n& zZq8y?nS*BgctMkw**p_jT9TRUUG`rJwFp#`6Mq(SH4gx21KB64`fOO;c-Fsyr>-vQ z;QWu(8*6$lFu3zb(S($pYXhSik>AR2De-y7pPY!)RX>=0&Yh=vks^%wPjn{Np1c{uf1DO( zZ={3cH*@&kD-3>Z$xeRu-kEi9eR) zuTX1yj%;qwboNtHo%-a9uQv5RYw6$aPEMpg*x{-x!{@%cXJ(NnodU^>ms3TCaV2yn z%i5I&pS3P(gKvrG!!O`ahFpJk)4QDahjqi{ssssNW_y)h|G%VIcJTj2!w%dPBq%?- zf6;I@?@yKcZ_@~>d)T0|7nXvY5s-M~NO2v9gG+8p%Dq^}dXFS4lgIzN2;$qvUW%=o zgm(SQs&&2h&O#J1uSU6Nrzl7BdBn2!5}P0Wy!k&Mn@z}0@XNUaG!o?6 zJcMd-d2(pd;F=d-HC9jjeUPq>p?cTyyRpt++<8d-Ev2*YeurtKwfR&rg|E6=1WY zOeykPc+7$Hn|Op>(|Z(&AJbdc-4TX}8)W%CY%zYt2f1IH#au%KDOTFV6hew@%ZLDMSA*8$L~w+9oY;>FEM5`oT#3ei zPbCF*U}AdgVTnhHy2zLhoS3;^8?76ZD{*a?mHaqvPK~aCeHj>r517p(u`n~>AUF)N zr|DFq$s!XU>~wB6LxY=_KVY?3_Mu|APFSQA((p)G!9H4^-!I+V{BzA_Ez-_h+C_$Q zVc3U&I!YL(nZ0hDzBH%#q3##|xsz|QzAb!8Lv5J^>9+J0724~ow~Pi=S@K=0F^m6F zuhT=UDd|f(UHcRhtSV!0g-uH(X8Z_zoo@R(ei@B4o3Xh~#t9!gyD_OeqjJLK@KB0} zg`G8$O!A9?)E^vyd4b0nN@y=|C81>lE`I%<7~0*&hj%m>9GMx=F#KYY=<1lz4e>4t;`)!p;2E>odtqa)Kdk{LW(_$z+QlPaI_ z`NiPB)#_3Pbl@rl&X7bRJ$%3ZaI#V7e|@}-XjR(r8r>_6XHRyRQ49{G%|xrN7|H3} z)>Y^bT(8TlhF4Q0tv(Ry%7MVu@S>ow%ihx47|&PR&q!_E<$*NpHxRMHEWn&mGRTx% z4Li9!3PoDvZ<68?xtNFFP!n7`|6Cw$><-7^y&7%-!b-GzSUQpUOY@N5Jf4C+xE8t+ zfbtmQ@z@8m`Hsl@M7&cyXsk2m*M!;AX-iNmY9$squ~&bZPs4c7s!M^|Ox^)THuO_? zha)d9vCIikMzja-e<_IMuDsdtoDPH1C z6!_t+BaUkLQ};)pWbV`9K9*p%lUtQGr4t$IHYCmCL))q>3oIv*%FwABa3qob@=7VX zUvfZ*R8PY{`7G{_`B@CnR)$Xd;aXSVXx$MbjGuexha(>f!?d1d zpEJ-*Ygf-@cm4lwlCexxaze+eZqo2zp7+DBjdV|kr|A?o5;m$m3O*Q~`(ghn;dn~h zJN&z+^alnYMFUbqH-euZ#H$=-9#K#juVRJXz`1MI> z;O-7rz2O!!zpm2p3{`N%Iz5W8P!WDr)!6Qr=6Tc8eF<-rN%$ixDDES;pHD9>#LI4I zpaMK-ZGm(@lK@Y*Zv1{UFuM!!dWRkX=2LhTu;vJktUfo>vJjlaJ$o^J=_GuvLpZ2{ z3&kibk$IcnV?O6&31>jz_4#3r59Jkz-fhq10KJboZyV&@gmWEiup^&5G7|LU(s#rs z3-e}k{E!lRG%*Wcw!{)eNdAxgXme9zbtC>$)aczrd&{};d^pYpKB4Gf)MDNhaA78U z74J=sgv8aYAzq@0;M1K;AokW)G7(WI_=y|rs}bKUekyzfE?d}oaHMASD;V_!uj@_C zDUdJ`jRhxNx%N?Z$+IiWQ^H<7gE<{S>)&sPaSfvi`!0o3DkV?ET4Y1+*X_NJ6dCwFBrxn5z^kNR4Y+)HpzNe5; zPxFW`q0V$mKAby9gaW?tQqFFddFD={#L}BP*HM7&nWlF+X;Ql3?dLUY$CFFsvK(ZD z0pUF?fxLKr1AUQX(cNdfEh6&dqQa!km6lTMz1L@Lgxlq}v!wF7=?}|xzg^IIEMQ7@Gx4@5s`4dVUh%|WbHx5Gs2m>X43d@5 z?(4;u?3DQ&p}c?gTI)(Ul*!|0$9H|MSR;{<`r4qW`;c2EI06M5b^IN??5QoW@b0#`d7Vs9MM9>d35Aik+!D_{ExpH~}t>wi$P z3YJa<)0{Ms2bbT23OE2BEYlFV6^a^%42y|uU#~23r5a4)$MLBT?yDhyjZ3TsV}2Y4d7z%YkbNEBOI6wFL?@j+je(x;w$_< z@EkST-Yzb^35K47wpPgQ{$N|*pYWPIHrQGauKt&T)Wi20EO2#&N^+qk$hx>ve~zk&PP)R|3uVP$;0FeE`!syYw7j=n+L zkcIVmr-ix^2B?#sv`jgG;A$WdXKCZ2Feor?1@}FD=5jq!Pjo@#m)vO7QrzxO8aULt z*EWD;ONoUj|8}w7>&(A}?7X!VvH01Iq7gCJgzbjkT~qsPmD~1O3F*O?Dk9I1z9d?f z?QxP77G96JxQ&?MK0Hlo=sz23pn3P*X<4)N*-YuA^8~um*2|wx#Owt_aJHQ`X}do= z3k*m49hw!(Xsm`=>%4b{B%6}%3@KDSFMML~GYbk&Mh49=-yzKwm@hvzKqB%H6i|_r2FnTjf5EgU%$8gntIKqk6geE)S#MdMXXc0#6lC zeNgrlwsFn3m$2?is7QM z*w2Q7(j&So%{o_j6wN{({a(jgs0aIE;IhpHD3tMhrJo1 z1i%jW5NnyZrj>&mkf0D;-YO{l0%FZ$E1>znO)`+06V185rDxTgNB-wh;MSZpCzA7a z)4WTR^f!pw?U1U@$4?wU-MfxaGNE3d$e3-6=JCEPh9RZFEmaIB^gu9e(+n*D@zo+$c~^JT*p+xdRV-EZ*mn|3qp z1I)E1yixD}On)qiX-_@Vk;)-C_&T!hP_pZOf%wyohUAZbwB|E0raecX2J5Ph(B>1| z>Gf0()}0M_1L)kj2gusO{F>k&`m`ed4QGh@qS}vl4`Ktuq&p`D7CRTNK9EDVs_vj) zCfWYzN}Wg9E{4j!61h1pIY8cb-lDdm9q^i9KMM&4+?xw%rEb&V3jLzc{7V3}c+1Pc zgG=HRjTtcr>+ERW!{jnsMe4>=D(b>*nlx(O!1d`>3m=S&xH-$j$Vr%zRFb=Bzyis{(Gwo5I_uCVIdOm zn*tR7$DhPcT}+0qRS%X^OIFQ(6zrw9<2TD(;(sa!|0TKIG5@R#Hv@LA+8O+lv$0I% z;Z+fxMXhsq~u zf@k;6l+eTikL@9&zH?M!U=P=Im%nz%{FoP;7)dDbPe}*(JB_E!fmbrEnYoN+Pwnaq zYW?*OgnSaUaZg;Vt!sd0@+-?PqX?C!MW|jaC@GD%qlKm?(?yoX6K>TNZ(Im_^)!gD zu-|^h=14<{^p)&1?)wR*JcCjV6bDK-(&wuIrw?-lvxU8MwnuI(c|f!18<9X0d&CWisd{ zFFfccvTsk=QELmWfQo-4v&+Qmz^fC_V3z2EN$_>2jS_v;znWa;OkN}6O7WVQXgz#X zg6V=T$}Yrp-3!cg-&Huc13EyQmt+VL4oGJdze5#$v3zhS;c~};cyq1e(M)C$bh+i7b7y%zmXp_Oq!}2zkv~9>BCVhclxS|>sQn2-J4~($2FU4l+1%@8%8{?Ov@LTS z^}K39(N+f1tKESPXlb=bigI5`R)c1Z*g5kE{K2WO1Q~L z@9&DMqQTu7xpJ$EiH;X4Jy-F^Tj*GF!|!`sjM2Vk`)r$rTiZu}74LbNky?J5S(S@t zVsX&hS96k&sjX?9`$vWt@eX#a>3Fv}z0N4{gZAB!6Y64x#MKP01&^M4$u;#U*DW%H zexyX{+}uh2P()``^TiV3&rb90yu2=fZsHi(;*-hV@R=QdgVxVgsG5`99KLMGB^E;4 zfTIDkx|3Lq4{6@TViTvvNMm(SslNv=L3hGK2ZTLC7s3k8&&09@I4p@DzEUh@9(k98 z&aVQfou_(7Q$sn7^P@zekE2SoNOIx>O@L8Gf@Dho?Sn(mO@k>#+bl)7VcG6qW{17! zp%~E9we{o*F8Kz<&#F8-H_Ldq)H&)I<2xF#% z%y^RI52E>A<;I_RUo3cbp)(%+HCsso_45O0@y~nP{eXzNp&GE~w`ncovy+bO4|G*~ z5H;+>-^M?>u^5+~rX^0|AI!6d(+y~mT zlW^H2ejO(4A>GW6&cNZfZz|689G+WhMIi~pngMSk#XevwGE%Lzm$fg7$=m> zOkS1#AK~oFi#Ot85q+Ym!`8o77t4NmAAG#Lc#Dp`CTE5@K}js&Q^U1@X?6&}fC6<| zD18JJe`7PL!MF~d>1=$}uf6{j&V+QW-@#)brv5A$X&{B78qu6cxlBpG*Pg<*or(9^ z+)LHU?!v>5?u{He@$rOQn3f*)9Sx-h6hM6I;Xzj#CAdrz`caMQfRB^p`~y^quWd3X z7|7LK2PPqRG#pG7yNSP$Ef3>VK)SsZ zDRjnX^I6@?=%bqO%kOie_z$T(Xhd$yp+~UvY|!*fasNB`C5yCWiLLn36wh%HMVR&IK7SwRYGdT`x3F%A{@ znKW7NeZ4<0VR!;JrPPf@sF$pLKjf+J>keuDlnRezoYU4)yI~><8sR9-~gkwJ4hM62CwX3pOn>r$~kx;gHD@e zQ=0?EKJTMv9EeN)4>mjZ5$&2J`nlIwiY?p0?B2uc15?RXKW=5*us?P(o;Sg3NQ_Od zRn#&4>NlykXP55|=1k41EaI4;4wnp4=(NLf$Pqr_ zzx4nuqitr4is+5Dsfjn}N)(`)$5kL%B-R>DP(1|69rAqM85O+}KbpL1hE+G6(Z5%U8aGY5Y z7Et4A<}!AO6<`(bIZ{<+6zL&#_`*l8NBl)L{Nm3J(aak6!0yIz-0d?`Mn(THm5Bb+ z6QO@5<`p-K?)P(|l}|SIRW?2i{a#4(^H}dr-oN+rk6-tOFV6dp%UV6*Z!0+dURYIG zQB8PI??lPalVyBILl2QN_3eQ)yF$gaz?m1i|5;lpMdnh@nUGuH z=Rdht9^~Os_&VHsco%#v396MFUEc9iVQofA;&?p-4pgw3+)mX1|`GGIL`E;|al=|)1KrED^7K?XQurE;Gea~$a?$dtZC+T!4XgAjHG!oTC>Gvt7J>Ts7yrJM|08I*X+iAjoM@~TW0$1J8`6&0v`8|y z!i=#TBeM!s5tVbfFz4&fhVMB6?@Q;P@;Hh}B*WpcpH~Qwxa+lw+agOvpVGhVTnsl( zKwEx!=)=3sJcK?KMI}B!dZU`4T8jA)lzr7b^P=H0^g+9lmOsRkdImauj`1!ee>I+Z zvENPoGGSQ>D3)_<8TOTRLHxf#QsaXwNVLVcAFS9%UZ!{a`_PoOk+)hTJP1y3GV3iuXD?x>8Q>a(;(IJMutaO~R~rn;k$uOC`dwEs8gdIIDU4B5!u25{V6OF2A>Gz?R2#nFs~ z)4zbiG!cVcO_+RV`6iYo%_2t3zt~3Td@A$V8gd%Vi~3UmsUCU4 zb9P#J-N`?LO#lmuYu#NHwt^{F8y@#fuuWK(?qqG&g=p08qsz{5w~Tby21a}ihI;V5 zP^hA!XM(KTZ~!=A(>gAYTxmuI}u87);C)`DR9PME@Q-!*6G(Z6ReFR zZ9lL%GaG*mk_o0Ut7chvsS0BEn1UU{e;EnV{dM!Xt0#PNU_hAo^COod_DnHzxIvl8 zgzZJ0qR6ee6dqqU8VsvLw@jniSo{RYIi)}l2JuP6vvR*7rU9azC|R=X?g8qb z`~R|P1)%)d;*EBDUWM2CN7X))d4 z;*^`gnQ$luL+Y6h)a~sWMPR^zVq>ZzEa(ST&bu(3Tq9he=WfmiUWw3-yWAJZcroQS z6pMdebBvacDT)M0W!~c+VIUbwKy!}9(WM@IJm0Je7(y8-ggUqryM-ayYN>uqUWXbv z58_nE#-Va|o+Gj9lM1WS35*LA9TK-LxwHKqiV}`?Le^T`C~9NqV3+=$Ud7Q9$B}<= zIbP!$IP(xoepVG;5ae!q4MF#wr;|B_)+2!OSvUFZ>aCi~yJW`;4T~-GWU9+OJx;$3 zsBN;DTH&!n;ok)Xmltq8=QASV3zELlAhB+8bCc?b($-Wnq7)4kdn9xpePDK{?T6y$ zZEVlb0ZCavhk`~Y2;L&Q9dbFQ=O}o9cH$ul5O)Q`slPI z#!s;GAS|Koh1d44x@=Ly4_9_`|5PuIi1yxMryO~S?iS`O(sepMi|)$=wIV5vWBZ$T zTeG1nWj$lqRuH3+vz{c(PE`)Y7cZYFwZ*BhfiZR(Yc5SBdz32TwtIypLM;mPvNB(+ z+)$9Q-;u*c`EtpSQ$r-&q~>w#3zOS5+;Ai(DyX&oCo291?YLSW{52Sw1~q(lb<}DuBxRiH-Zii{QBk6 zYpj;iu-F6lRjBl6*T-OLI#jNsIB*NLPrsEz$i5Em4nj2YURI!g`GdE<(xM>aPraP1ePBUj%0sqv| z+#Ku1+L~hv?DRIE|B}+7M@L#779#QhR$6rSQFy#|8sdByu-j{7mXwuyrh?P&2_Ap_{a4Hx&bYz)d%L9zdkZU9xaIhQ z(v?fVU)LI7N0fgmLKqVvAMn`}@&AQ>P#orJIN!`79|qC+#|)umIht{iUw<5+B@>lg z*C7W(QZwD7R-B8jOB#0*bn_53|K*7n&^s-G-E;4=Ld0_%an2J+%>FV!FImo0$ zRIkYo6spdwh{<0Pg=Vn=KX!;GCHsPGE97>qf37?)FF$_negl*Kk zf4y0d^g*SVZHh3Z=0MYwM|M&H$;Iz4wq#H2;K(keUnBC5u}Y9wPJ5-t=+Wc$A8XaJk4pX>9Sg&>*4Wed76O)C<%-a$%E z{mQF%=)mNF((40_4vNaCVqJw{a%P+~0@=K0r4!Hf<)J3>T0>1-aobG> z?gwu1_~L@19^;}(g?rmr`;)OvTTl!1=yrpAMDxk?QD74wWRRA2tl;V@e)80V|YAPv$%bO(&u+s`U{gsVj5HB9ta> zq{AraO~YI1zo30J8tbjZ!c0ux#Vy#W>7lG{JA9NanTxyYxPZ+Wdq6?@fUNQ^epBDV z6VOz>sTh$}X4>`vGwakg29G7&ZYuPv9O~df} z$^nr8e(~sx4_8zYcDX|*)BU1f2R7k4VwWO{!d6f{)at+)EB7Dj-+yUlsI6TWr7UoW zJW)_nP>xS2yYt*~?1n8wZAzMvrYRmxt8{9@%6RFrSzruVp=m=kE2pE->q-j>y}zP& zp{iqrAk22X2^pJfuwh1>+paO6c6c6wN5X8Q@g1G^_5nTxOe43FZ&V%9k-z9|XGR%H zA3DoUR_0@$cW%M!_ecGSL*JkG9gm$;G`>u{8x`^47-gZjQ&Heo3wrG>GR)vgCAt(O zDbi@n_Kn|G^}CeX7_^dFPZr(Nz8m||Ol$>ZGnKiO)>KmnUk!4vT_2j-YDoC@NG)!0!h7%=Kj=Mo^(JC)ArFO7v85;7+ zACswrlb7=F)5iIZEm`y6J3KgW!yM_b@a*$2I2t z@rA??@!$$L9LCKw+q}ISi*}!dgBh(bw-2)mVaiqJoJywVa0;UGv_Vj?0o0CNM&eM_ zH-INCGG}~K_WspB&_7a#bK57@&OQ9btJWb#!Q6NedMK8BB2=^=zvy{Kv0zwj1oeDV zpk|yVc|me^myV$)tx{&0syq=`iUQM6B-QZnvIsQne~lC7XWmWzvkld`c~a0buKqgs zk#s3t5vuuQiK9ryPI)6Cu|h*~OV@k>g}YqajJHkQn#~ls=-RW)6mY?O@tgQ{k`Qb+ zHF;#eXC3`&^R>s8npm*>av@x!H*g1Tto8+{+nTH7Hm49s`2ctKmu{E-1qFd`0vml3 zOoy9?|ApGf8x~H&n{6zaC9vk1```b{HXSQ&I``*OxYm=Hf27~a73Z10^T{SC@r?67 z6e%c8Y!^=D7-S1ZIu@22yuDPw%KKfkKJWaIKRtOT@z& zj21t-Z}Aw_Jj3HK#neg!jwC00>T%M{KaK63b@RKnyk+P}VrX1oW2Bk_hc)BF?}AZ}=(H)fNR z=${bXJ3L{^g(?`(&{*)u&22OomE90&^}7a`YpJX-T^#AK#CpJ0M-XhCR}Zqo(p0nc z0=u5oaFCVHWcRTp|M!J-Z`mC!IKObe4;diKkW*SjjdQXpy$<*pnvR7V4?@*l=eP zQ4;b)Ssp}C=bFydSKho-I|V$~=Zu3_u;|T&<0k@!eHZc9xb`AAQ7k`r*U`la3o3D3 zn2Ys2OW0Uw9iqbMP1ic0ncfQPJ!ss{!{Jk}KVOoNHXJ!!YRz^3-gceA<6e_qskDJF z{(qCEMVLr0{t2#o7{uZeS$Ba|=51IF`;h0m=UNqZ0eWP0kNWzJVXEaKuXDf;Tv>Q= zJ9BuFcFUZIiQJ!`Y*}SQylb}_s0KF>b%b+yA!$u)n-&wuafj5de1-)f!rE7bMt zAn@lA9@F1I_DjAUgw&ttqpvSg6WV^cq?1INCnt8R<*Ct~R|?-1{ldDpA7-a5Slm%* zp=1a+cJFR|`|s1*RCSDCS)kR>C}b1qBj{d3L$Kn<{Rj5i6y2z7 zAa#JR0CE^nj$Q>op-#%lt-B=SLvLAymQ7hWBMrhhZE%FfW3lhsj|8-Tq_wXp>_{XVZC zI{ER*z>CzxgXrE9HQGrWnghF(xaV(6t)WMTxEXPZJQs<1o94aD z(tN203caW*nif*Ml}^EIFt|L4*2855RRwWd1FQODxWQ{npEuW;r_~!INZP7&sm+yP z_HJiE9h_zrtmRma)*6RAg97V7a8Cq{w?lD{t|pRHdGLM(Ddu{*s7SUoe<0IBD|@~W z7WM7Ua%CfI)pBGmHM6D^eRG&_9WI$I+Xo)h85-)lQa3Gn{C>pumyR#f1e8kQJFn>A z;Pca`SuY6v>hu5k-oHfYB#(yt{e9NhpN$Q+H{O{IhPB?aSgr_>`*n6&#yNjrD0tYj zHgM>d#zYp|_|q7VlhmZ^WEV!A!4(UM>YKMKC*}CP(JnH-3l@xO1F}#$f?c0G@e0D1 zbZGg8F>gPd?B^x@UVt2S>LLEJx4zmWW`=;TX^W8MLz$i5n;7eFwou6&#>7;l8auRn zA%NfP&tj4E)4$K7NZY}Cx=41bIRCRORU-0CoHsuVEqrkrPgkZ+$hF;- z4{eC~709z#dH$D<|HxWdF*rxC%#5%7a6MS*B4m{q6VkuyF;H9jD|(gj0y`qLL7CKp-9#m1Kmgk7 zPrdIiL=tp-8sfW|vc69%{;=379(Hu<+ycj1ve^(e=pUx2!kGsj86$vRbEJ@0%|UWn z`(h-OpW$VW5QX{1pWF6+!B;lGr7jzB;Gu#CM~L@K@y{3}?yW+Q;++N?YWl z`Kwg>-)x<8{E-?oQK81z-1+di1T=O$Rq6eS8@C+at2_Tr?rl}?kt*V(L@-A2H{-;w zrjaJTOx-k=?Sn-3ZB>l1JJNSC`D>T}M#joGO4}AwKFq=pWyLaVC$bw2*FG(0edyH% zkJ>fi-XWLN@06RpGdq)&kJ>xAa~2+RgCB>kk>#TWa^z%*IA8eg)0>oChGDe9(@M+p zaCKc)f`&fTIio!ooF0TLNb-R3T)x_Fuf)Vz(_}fG-%ss z2%VzhB|z)S%hy0KR0FGZu~pqHg)UD@-D|~Ou2j(%^59DU3%(X3 zZ?ra6$Qt}Mv=h|OYm#uGEyN$%^v2y0Av2$WY47p<3%qnKynBuC3Ha0Q;c_Su{Xk