From 0169e95fbfbbb2d28264bd267c7e3d83b05072f8 Mon Sep 17 00:00:00 2001
From: Joseph Omar <j.omar@soton.ac.uk>
Date: Fri, 13 Dec 2024 15:00:11 +0000
Subject: [PATCH] Refactor learning rate parameters and enhance dataset
handling; added new CSV files for results and label mappings.
---
entcl/cl.py | 4 +-
entcl/data/cifar100/cifar100partition.py | 71 +-
entcl/pretrain.py | 3 +-
entcl/run.py | 8 +-
entcl/utils/ncd.py | 43 +-
entcl/utils/ood.py | 11 +-
experiments/experiments3.ipynb | 2497 +++++++++++++++++++---
experiments/labelmaps.csv | 101 +
experiments/raw_logits_results.csv | 21 +
9 files changed, 2436 insertions(+), 323 deletions(-)
create mode 100644 experiments/labelmaps.csv
create mode 100644 experiments/raw_logits_results.csv
diff --git a/entcl/cl.py b/entcl/cl.py
index 4a960e9..e58b11d 100644
--- a/entcl/cl.py
+++ b/entcl/cl.py
@@ -66,7 +66,7 @@ def cl_session(args, session_dataset: torch.utils.data.Dataset, model: torch.nn.
optimiser = torch.optim.SGD(
model.parameters(),
- lr=args.lr,
+ lr=args.cl_lr,
momentum=args.momentum,
weight_decay=args.weight_decay,
)
@@ -135,7 +135,7 @@ def _train(args, model: torch.nn.Module, train_loader: torch.utils.data.DataLoad
"""
model.train()
loss_total = 0
- for x, _, _, _, y in tqdm(train_loader, desc="Training", unit="batch"): # we only want psuedo labels for training
+ for x, y, _, _, _ in tqdm(train_loader, desc="Training", unit="batch"): # we only want psuedo labels for training
x, y = x.to(args.device), y.to(args.device)
logger.debug(f"x shape: {x.shape}, y shape: {y.shape}")
logger.debug(f"Psuedo Labels (Unique): {torch.unique(y, sorted=True)}")
diff --git a/entcl/data/cifar100/cifar100partition.py b/entcl/data/cifar100/cifar100partition.py
index 418384a..e8258a4 100644
--- a/entcl/data/cifar100/cifar100partition.py
+++ b/entcl/data/cifar100/cifar100partition.py
@@ -46,7 +46,7 @@ class PartitionedCIFAR100FeaturesDataset:
+ f"CL sessions: {self.sessions}"
)
- self._verify_splits()
+ self._verify_splits(mutex)
# Train Set --------------------------------------------------------------
@@ -290,7 +290,7 @@ class PartitionedCIFAR100FeaturesDataset:
return all_data
- def _verify_splits(self):
+ def _verify_splits(self, mutex: bool = True):
# verify sessions
if self.sessions <= 0:
raise ValueError(
@@ -298,33 +298,52 @@ class PartitionedCIFAR100FeaturesDataset:
)
# verify known classes
- if not (0 <= self.known <= 100 - self.sessions):
- raise ValueError(
- f'Number of known classes should be between 0 and 100 - sessions ({self.sessions}). Given "known": {self.known}, "sessions": {self.sessions}'
- )
+ if mutex:
+ if not (0 <= self.known <= 100 - self.sessions):
+ raise ValueError(
+ f'Number of known classes should be between 0 and 100 - sessions ({self.sessions}). Given "known": {self.known}, "sessions": {self.sessions}'
+ )
- # verify pretrain_n_known
- if not (0 <= self.pretrain_n_known <= 500 - (self.cl_n_known * self.sessions)):
- raise ValueError(
- f'Number of samples per known class for pretraining should be between 0 and 500 - (cl_n_known * sessions). Given "pretrain_n_known": {self.pretrain_n_known}, "cl_n_known": {self.cl_n_known}, "sessions": {self.sessions}'
- )
- # verify cl_n_known
- if not (0 <= self.cl_n_known <= (500 - self.pretrain_n_known) / self.sessions):
- raise ValueError(
- f'Number of samples per known class for each CL session should be between 0 and (500 - pretrain_n_known) / sessions. Given "cl_n_known": {self.cl_n_known}, "pretrain_n_known": {self.pretrain_n_known}, "sessions": {self.sessions}'
- )
+ # verify pretrain_n_known
+ if not (0 <= self.pretrain_n_known <= 500 - (self.cl_n_known * self.sessions)):
+ raise ValueError(
+ f'Number of samples per known class for pretraining should be between 0 and 500 - (cl_n_known * sessions). Given "pretrain_n_known": {self.pretrain_n_known}, "cl_n_known": {self.cl_n_known}, "sessions": {self.sessions}'
+ )
+ # verify cl_n_known
+ if not (0 <= self.cl_n_known <= (500 - self.pretrain_n_known) / self.sessions):
+ raise ValueError(
+ f'Number of samples per known class for each CL session should be between 0 and (500 - pretrain_n_known) / sessions. Given "cl_n_known": {self.cl_n_known}, "pretrain_n_known": {self.pretrain_n_known}, "sessions": {self.sessions}'
+ )
- # verify cl_n_novel
- if not (0 <= self.cl_n_novel <= 500 - self.sessions):
- raise ValueError(
- f'Number of samples per novel class for each CL session should be between 0 and 500 - sessions. Given "cl_n_novel": {self.cl_n_novel}, "sessions": {self.sessions}'
- )
+ # verify cl_n_novel
+ if not (0 <= self.cl_n_novel <= 500 - self.sessions):
+ raise ValueError(
+ f'Number of samples per novel class for each CL session should be between 0 and 500 - sessions. Given "cl_n_novel": {self.cl_n_novel}, "sessions": {self.sessions}'
+ )
- # verify cl_n_prevnovel
- if not (0 <= self.cl_n_prevnovel <= (500 - self.cl_n_novel) / self.sessions):
- raise ValueError(
- f'Number of samples per previously novel class for each CL session should be between 0 and (500 - cl_n_novel) / sessions. Given "cl_n_prevnovel": {self.cl_n_prevnovel}, "cl_n_novel": {self.cl_n_novel}, "sessions": {self.sessions}'
- )
+ # verify cl_n_prevnovel
+ if not (0 <= self.cl_n_prevnovel <= (500 - self.cl_n_novel) / self.sessions):
+ raise ValueError(
+ f'Number of samples per previously novel class for each CL session should be between 0 and (500 - cl_n_novel) / sessions. Given "cl_n_prevnovel": {self.cl_n_prevnovel}, "cl_n_novel": {self.cl_n_novel}, "sessions": {self.sessions}'
+ )
+ else:
+ # make sure they are all under 500
+ if not (0 <= self.pretrain_n_known <= 500):
+ raise ValueError(
+ f'Number of samples per known class for pretraining should be between 0 and 500. Given "pretrain_n_known": {self.pretrain_n_known}'
+ )
+ if not (0 <= self.cl_n_known <= 500):
+ raise ValueError(
+ f'Number of samples per known class for each CL session should be between 0 and 500. Given "cl_n_known": {self.cl_n_known}'
+ )
+ if not (0 <= self.cl_n_novel <= 500):
+ raise ValueError(
+ f'Number of samples per novel class for each CL session should be between 0 and 500. Given "cl_n_novel": {self.cl_n_novel}'
+ )
+ if not (0 <= self.cl_n_prevnovel <= 500):
+ raise ValueError(
+ f'Number of samples per previously novel class for each CL session should be between 0 and 500. Given "cl_n_prevnovel": {self.cl_n_prevnovel}'
+ )
if __name__ == "__main__":
diff --git a/entcl/pretrain.py b/entcl/pretrain.py
index 328a795..f5ca906 100644
--- a/entcl/pretrain.py
+++ b/entcl/pretrain.py
@@ -1,4 +1,3 @@
-import os
from loguru import logger
import pandas as pd
import torch
@@ -28,7 +27,7 @@ def pretrain(args, model):
optimiser = torch.optim.SGD(
model.parameters(),
- lr=args.lr,
+ lr=args.pretrain_lr,
momentum=args.momentum,
weight_decay=args.weight_decay,
)
diff --git a/entcl/run.py b/entcl/run.py
index dba4b8f..d3a75a0 100644
--- a/entcl/run.py
+++ b/entcl/run.py
@@ -38,7 +38,7 @@ def main(args: argparse.Namespace):
session_dataset = label_ood_for_session(args, session_dataset, model) # returns a new dataset with the OOD samples labelled
# NCD
- session_dataset, mapping = find_novel_classes_for_session(args, session_dataset, model) # returns a new dataset with the novel samples labelled
+ session_dataset, mapping = find_novel_classes_for_session(args, session_dataset) # returns a new dataset with the novel samples labelled
# dataset should now have the form (data, true labels, true types, pred types, pseudo labels)
@@ -85,11 +85,12 @@ if __name__ == "__main__":
# cl args
parser.add_argument('--known', type=int, default=50, help='Number of known classes. The rest are novel classes')
parser.add_argument('--pretrain_n_known', type=int, default=400, help='How many samples per known class to use for pretraining')
-
+ parser.add_argument('--no_mutex', action='store_true', default=False, help='Do not use mutex samples')
parser.add_argument('--cl_n_novel', type=int, default=400, help='How many novel samples per novel class to use in each session of cl') # this val * novel_classes = novel samples per session
parser.add_argument('--cl_n_known', type=int, default=20, help='How many known samples per known class to use in each session of cl') # this val * known_classes = known samples per session
parser.add_argument('--cl_n_prevnovel', type=int, default=20, help='How many known samples per previously-novel class to use in each session of cl (Classes that used to be novel, but are now known)') # this val * knownnovel_classes = knownnovel samples per session
+
parser.add_argument('--sessions', type=int, default=5, help='Number of mixed incremental continual learning sessions')
parser.add_argument('--cl_epochs', type=int, default=100, help='Number of epochs for continual learning sessions')
@@ -104,6 +105,7 @@ if __name__ == "__main__":
# ood args
parser.add_argument('--ood_score', type=str, default='entropy', help='Changes the metric(s) to base OOD detection on', choices=['entropy', 'energy', 'both', 'cheat'])
parser.add_argument('--ood_eps', type=float, default=1e-8, help='Epsilon value for computing entropy in OOD detection')
+ parser.add_argument('--cheat_ood', action='store_true', default=False, help='Cheat OOD. Use the true labels for OOD detection')
# ncd args
parser.add_argument('--cheat_ncd', action='store_true', default=False, help='Cheat NCD. Use the true labels for NCD')
@@ -147,7 +149,7 @@ if __name__ == "__main__":
if args.dataset == 'cifar100':
from entcl.data.cifar100 import PartitionedCIFAR100FeaturesDataset
args.novel_classes_per_session = (100 - args.known) // args.sessions
- args.dataset = PartitionedCIFAR100FeaturesDataset(known=args.known, pretrain_n_known=args.pretrain_n_known, cl_n_known=args.cl_n_known, cl_n_novel=args.cl_n_novel, cl_n_prevnovel=args.cl_n_prevnovel, sessions=5)
+ args.dataset = PartitionedCIFAR100FeaturesDataset(known=args.known, pretrain_n_known=args.pretrain_n_known, cl_n_known=args.cl_n_known, cl_n_novel=args.cl_n_novel, cl_n_prevnovel=args.cl_n_prevnovel, sessions=5, mutex=not args.no_mutex)
if args.head == 'linear':
diff --git a/entcl/utils/ncd.py b/entcl/utils/ncd.py
index 12ad6e6..980510c 100644
--- a/entcl/utils/ncd.py
+++ b/entcl/utils/ncd.py
@@ -189,16 +189,14 @@ def _cluster_features(args, features: torch.Tensor) -> torch.Tensor:
def find_novel_classes_for_session(
args,
session_dataset: torch.utils.data.Dataset,
- model: torch.nn.Module,
) -> Tuple[torch.utils.data.Dataset, Dict[int, int]]:
"""
Finds the novel classes in the given session dataset using KMeans clustering and the given model
:param args: Arguments object with the attributes `device`, `ncd_findk_method`, `novel_classes_per_session`, `seed`.
:param session_dataset: torch.utils.data.Dataset with the session data.
- :param model: torch.nn.Module with the model to use for clustering.
:return: torch.Tensor with the pseudo-labels for the novel classes.
"""
-
+
# first we need to create a torch.utils.data.Dataset with only the predicted novel samples
novel_samples_mask = (
session_dataset.tensors[3] == 1
@@ -210,27 +208,28 @@ def find_novel_classes_for_session(
for tensor in session_dataset.tensors
] # get only the predicted novel samples
- for i, t in enumerate(novel_tensors):
- logger.debug(f"Tensor[{i}] Shape: {t.shape}")
-
novel_dataset = torch.utils.data.TensorDataset(*novel_tensors)
-
- # extract features from the novel samples
- #novel_features = _extract_features(args, novel_dataset, model) # using a feature dataset so this is not needed
-
- novel_features = novel_dataset.tensors[0] # the first tensor in the dataset is the data tensor
-
- # cluster the features
- pseudo_labels = _cluster_features(args, novel_features)
- # pseudo_labels needs to start at the novel class start index, so we add that to the 0-starting pseudo labels
- novel_class_start = args.dataset.known + (args.current_session - 1) * args.dataset.novel_inc
- pseudo_labels += novel_class_start
-
- # calculate the clustering accuracy (not used in the dataset, only for logging and testing)
- mapping = generate_mapping(
- novel_dataset.tensors[1], pseudo_labels, args
- )
+ if args.cheat_ncd:
+ # if we are cheating, we set the psuedo_labels to the true labels
+ pseudo_labels = novel_dataset.tensors[1]
+ mapping = generate_mapping(
+ novel_dataset.tensors[1], pseudo_labels, args
+ ) # we still generate the mapping, but they should map to themselves
+ else:
+ novel_features = novel_dataset.tensors[0] # the first tensor in the dataset is the data tensor (features)
+
+ # cluster the features
+ pseudo_labels = _cluster_features(args, novel_features)
+
+ # pseudo_labels needs to start at the novel class start index, so we add that to the 0-starting pseudo labels
+ novel_class_start = args.dataset.known + (args.current_session - 1) * args.dataset.novel_inc
+ pseudo_labels += novel_class_start
+
+ # calculate the clustering accuracy (not used in the dataset, only for logging and testing)
+ mapping = generate_mapping(
+ novel_dataset.tensors[1], pseudo_labels, args
+ )
# next we need to align the pseudo labels tensor with the original dataset, giving known samples a pseudo label of -1
pseudo_labels_aligned = torch.full(
diff --git a/entcl/utils/ood.py b/entcl/utils/ood.py
index 76c1e93..f171d4a 100644
--- a/entcl/utils/ood.py
+++ b/entcl/utils/ood.py
@@ -168,8 +168,11 @@ def label_ood_for_session(
# next step depends on the selected OOD Score
# placeholder for the final predictions
final_predtypes = None
+ if args.ood_score == "cheat" or args.cheat_ood:
+ logger.debug("Cheating OOD")
+ final_predtypes = session_dataset.tensors[2].clone()
# if we are using entropy only
- if args.ood_score == "entropy":
+ elif args.ood_score == "entropy":
logger.debug("Using Entropy Only")
predtypes_hard, _ = _fit_predict_gmm(
entropies, args
@@ -196,7 +199,9 @@ def label_ood_for_session(
entropy_predtypes_soft, energy_predtypes_soft
)
else:
- raise ValueError(f"Invalid OOD Score: {args.ood_score}")
+ raise ValueError(
+ f"Invalid OOD Score: {args.ood_score}. Must be one of ['entropy', 'energy', 'both', 'cheat']"
+ )
logger.debug("Returning New Dataset")
# return the new dataset with the predicted types
@@ -206,7 +211,7 @@ def label_ood_for_session(
session_dataset.tensors[2], # the real types
final_predtypes.cpu(), # the predicted types (duh)
)
-
+
# compute the OOD Accuracy
_compute_ood_accuracy(session_dataset, entropies, energies, args)
diff --git a/experiments/experiments3.ipynb b/experiments/experiments3.ipynb
index 287d60c..660e703 100644
--- a/experiments/experiments3.ipynb
+++ b/experiments/experiments3.ipynb
@@ -25,158 +25,155 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 174,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
- "\u001b[32m2024-12-03 12:06:35.001\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m59\u001b[0m - \u001b[34m\u001b[1mVerifying incremental learning settings\n",
+ "\u001b[32m2024-12-10 14:47:26.663\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m39\u001b[0m - \u001b[34m\u001b[1mVerifying incremental learning settings\n",
"Known classes: 50\n",
"Pretraining samples per known class: 400\n",
"Samples per known class per CL session: 20\n",
"Samples per novel class per CL session: 400\n",
"Samples per previously novel class per CL session: 20\n",
"CL sessions: 5\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:35.002\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m72\u001b[0m - \u001b[34m\u001b[1mDownload: False\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:35.003\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m75\u001b[0m - \u001b[34m\u001b[1mLoading and Sorting CIFAR100 Train split\u001b[0m\n",
- "/root/miniconda3/envs/entcl/lib/python3.10/site-packages/torchvision/transforms/v2/_deprecated.py:41: UserWarning: The transform `ToTensor()` is deprecated and will be removed in a future release. Instead, please use `transforms.Compose([transforms.ToImageTensor(), transforms.ConvertImageDtype()])`.\n",
- " warnings.warn(\n",
- "\u001b[32m2024-12-03 12:06:41.400\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m80\u001b[0m - \u001b[34m\u001b[1mSplitting Train Data for Sessions\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.401\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m158\u001b[0m - \u001b[34m\u001b[1mSplitting data for 5 sessions\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.401\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m161\u001b[0m - \u001b[34m\u001b[1mSplitting data for session 0 (pretraining)\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.440\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m169\u001b[0m - \u001b[34m\u001b[1mCreating dataset for session 0 (pretraining). There are 20000 samples, and 20000 labels. There are 50 different classes\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.442\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m170\u001b[0m - \u001b[34m\u001b[1mClasses in Pretraining Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+ "\u001b[32m2024-12-10 14:47:26.663\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m54\u001b[0m - \u001b[34m\u001b[1mLoading and Sorting CIFAR100 Train split\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.779\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m57\u001b[0m - \u001b[34m\u001b[1mSplitting Train Data for Sessions\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.781\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m132\u001b[0m - \u001b[34m\u001b[1mSplitting data for 5 sessions\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.782\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m135\u001b[0m - \u001b[34m\u001b[1mSplitting data for session 0 (pretraining)\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.800\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m143\u001b[0m - \u001b[34m\u001b[1mCreating dataset for session 0 (pretraining). There are 20000 samples, and 20000 labels. There are 50 different classes\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.802\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m144\u001b[0m - \u001b[34m\u001b[1mClasses in Pretraining Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
" 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
" 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49])\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.443\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m174\u001b[0m - \u001b[34m\u001b[1mSplitting data for CL sessions\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.443\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m176\u001b[0m - \u001b[34m\u001b[1mSplitting data for session 1\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.443\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m180\u001b[0m - \u001b[34m\u001b[1mThere are 50 known classes. Starting at 0 (inc), ending at 50 (exc)\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.450\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m186\u001b[0m - \u001b[34m\u001b[1mThere are 10 novel classes. Starting at 50 (inc), ending at 60 (exc)\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.460\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m209\u001b[0m - \u001b[34m\u001b[1mCreating dataset for session 1. There are 5000 samples, and 5000 labels. There are 60 different classes\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.462\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m210\u001b[0m - \u001b[34m\u001b[1mClasses in this Session 1's Train Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+ "\u001b[32m2024-12-10 14:47:28.802\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m148\u001b[0m - \u001b[34m\u001b[1mSplitting data for CL sessions\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.803\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m150\u001b[0m - \u001b[34m\u001b[1mSplitting data for session 1\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.804\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m154\u001b[0m - \u001b[34m\u001b[1mThere are 50 known classes. Starting at 0 (inc), ending at 50 (exc)\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.811\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m160\u001b[0m - \u001b[34m\u001b[1mThere are 10 novel classes. Starting at 50 (inc), ending at 60 (exc)\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.817\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m183\u001b[0m - \u001b[34m\u001b[1mCreating dataset for session 1. There are 5000 samples, and 5000 labels. There are 60 different classes\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.819\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m184\u001b[0m - \u001b[34m\u001b[1mClasses in this Session 1's Train Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
" 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
" 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,\n",
" 54, 55, 56, 57, 58, 59])\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.463\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m176\u001b[0m - \u001b[34m\u001b[1mSplitting data for session 2\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.463\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m180\u001b[0m - \u001b[34m\u001b[1mThere are 50 known classes. Starting at 0 (inc), ending at 50 (exc)\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.469\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m186\u001b[0m - \u001b[34m\u001b[1mThere are 10 novel classes. Starting at 60 (inc), ending at 70 (exc)\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.473\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m195\u001b[0m - \u001b[34m\u001b[1mThere are 10 previously novel classes. Starting at 50 (inc), ending at 60 (exc)\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.480\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m209\u001b[0m - \u001b[34m\u001b[1mCreating dataset for session 2. There are 5200 samples, and 5200 labels. There are 70 different classes\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.482\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m210\u001b[0m - \u001b[34m\u001b[1mClasses in this Session 2's Train Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+ "\u001b[32m2024-12-10 14:47:28.820\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m150\u001b[0m - \u001b[34m\u001b[1mSplitting data for session 2\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.821\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m154\u001b[0m - \u001b[34m\u001b[1mThere are 50 known classes. Starting at 0 (inc), ending at 50 (exc)\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.825\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m160\u001b[0m - \u001b[34m\u001b[1mThere are 10 novel classes. Starting at 60 (inc), ending at 70 (exc)\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.828\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m169\u001b[0m - \u001b[34m\u001b[1mThere are 10 previously novel classes. Starting at 50 (inc), ending at 60 (exc)\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.834\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m183\u001b[0m - \u001b[34m\u001b[1mCreating dataset for session 2. There are 5200 samples, and 5200 labels. There are 70 different classes\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.835\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m184\u001b[0m - \u001b[34m\u001b[1mClasses in this Session 2's Train Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
" 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
" 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,\n",
" 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69])\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.483\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m176\u001b[0m - \u001b[34m\u001b[1mSplitting data for session 3\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.484\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m180\u001b[0m - \u001b[34m\u001b[1mThere are 50 known classes. Starting at 0 (inc), ending at 50 (exc)\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.490\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m186\u001b[0m - \u001b[34m\u001b[1mThere are 10 novel classes. Starting at 70 (inc), ending at 80 (exc)\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.495\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m195\u001b[0m - \u001b[34m\u001b[1mThere are 10 previously novel classes. Starting at 50 (inc), ending at 70 (exc)\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.504\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m209\u001b[0m - \u001b[34m\u001b[1mCreating dataset for session 3. There are 5400 samples, and 5400 labels. There are 80 different classes\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.507\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m210\u001b[0m - \u001b[34m\u001b[1mClasses in this Session 3's Train Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+ "\u001b[32m2024-12-10 14:47:28.836\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m150\u001b[0m - \u001b[34m\u001b[1mSplitting data for session 3\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.836\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m154\u001b[0m - \u001b[34m\u001b[1mThere are 50 known classes. Starting at 0 (inc), ending at 50 (exc)\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.840\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m160\u001b[0m - \u001b[34m\u001b[1mThere are 10 novel classes. Starting at 70 (inc), ending at 80 (exc)\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.843\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m169\u001b[0m - \u001b[34m\u001b[1mThere are 10 previously novel classes. Starting at 50 (inc), ending at 70 (exc)\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.849\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m183\u001b[0m - \u001b[34m\u001b[1mCreating dataset for session 3. There are 5400 samples, and 5400 labels. There are 80 different classes\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.851\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m184\u001b[0m - \u001b[34m\u001b[1mClasses in this Session 3's Train Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
" 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
" 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,\n",
" 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,\n",
" 72, 73, 74, 75, 76, 77, 78, 79])\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.508\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m176\u001b[0m - \u001b[34m\u001b[1mSplitting data for session 4\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.508\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m180\u001b[0m - \u001b[34m\u001b[1mThere are 50 known classes. Starting at 0 (inc), ending at 50 (exc)\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.513\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m186\u001b[0m - \u001b[34m\u001b[1mThere are 10 novel classes. Starting at 80 (inc), ending at 90 (exc)\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.517\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m195\u001b[0m - \u001b[34m\u001b[1mThere are 10 previously novel classes. Starting at 50 (inc), ending at 80 (exc)\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.526\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m209\u001b[0m - \u001b[34m\u001b[1mCreating dataset for session 4. There are 5600 samples, and 5600 labels. There are 90 different classes\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.528\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m210\u001b[0m - \u001b[34m\u001b[1mClasses in this Session 4's Train Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+ "\u001b[32m2024-12-10 14:47:28.852\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m150\u001b[0m - \u001b[34m\u001b[1mSplitting data for session 4\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.852\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m154\u001b[0m - \u001b[34m\u001b[1mThere are 50 known classes. Starting at 0 (inc), ending at 50 (exc)\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.857\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m160\u001b[0m - \u001b[34m\u001b[1mThere are 10 novel classes. Starting at 80 (inc), ending at 90 (exc)\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.859\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m169\u001b[0m - \u001b[34m\u001b[1mThere are 10 previously novel classes. Starting at 50 (inc), ending at 80 (exc)\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.867\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m183\u001b[0m - \u001b[34m\u001b[1mCreating dataset for session 4. There are 5600 samples, and 5600 labels. There are 90 different classes\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.869\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m184\u001b[0m - \u001b[34m\u001b[1mClasses in this Session 4's Train Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
" 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
" 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,\n",
" 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,\n",
" 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89])\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.528\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m176\u001b[0m - \u001b[34m\u001b[1mSplitting data for session 5\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.529\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m180\u001b[0m - \u001b[34m\u001b[1mThere are 50 known classes. Starting at 0 (inc), ending at 50 (exc)\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.532\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m186\u001b[0m - \u001b[34m\u001b[1mThere are 10 novel classes. Starting at 90 (inc), ending at 100 (exc)\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.537\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m195\u001b[0m - \u001b[34m\u001b[1mThere are 10 previously novel classes. Starting at 50 (inc), ending at 90 (exc)\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.547\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m209\u001b[0m - \u001b[34m\u001b[1mCreating dataset for session 5. There are 5800 samples, and 5800 labels. There are 100 different classes\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.549\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m210\u001b[0m - \u001b[34m\u001b[1mClasses in this Session 5's Train Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+ "\u001b[32m2024-12-10 14:47:28.870\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m150\u001b[0m - \u001b[34m\u001b[1mSplitting data for session 5\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.870\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m154\u001b[0m - \u001b[34m\u001b[1mThere are 50 known classes. Starting at 0 (inc), ending at 50 (exc)\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.874\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m160\u001b[0m - \u001b[34m\u001b[1mThere are 10 novel classes. Starting at 90 (inc), ending at 100 (exc)\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.876\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m169\u001b[0m - \u001b[34m\u001b[1mThere are 10 previously novel classes. Starting at 50 (inc), ending at 90 (exc)\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.886\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m183\u001b[0m - \u001b[34m\u001b[1mCreating dataset for session 5. There are 5800 samples, and 5800 labels. There are 100 different classes\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:28.888\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_train_data_for_sessions\u001b[0m:\u001b[36m184\u001b[0m - \u001b[34m\u001b[1mClasses in this Session 5's Train Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
" 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
" 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,\n",
" 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,\n",
" 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,\n",
" 90, 91, 92, 93, 94, 95, 96, 97, 98, 99])\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:41.550\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m85\u001b[0m - \u001b[34m\u001b[1mLoading and Sorting CIFAR100 Test split\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:42.969\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m89\u001b[0m - \u001b[34m\u001b[1mSplitting Test Data for Sessions\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:42.970\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m225\u001b[0m - \u001b[34m\u001b[1mSplitting test data for session 0\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:42.976\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m236\u001b[0m - \u001b[34m\u001b[1mCreating dataset for session 0 (pretraining). There are 5000 samples, and 5000 labels. There are 50 different classes\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:42.978\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m237\u001b[0m - \u001b[34m\u001b[1mClasses in Session 0's Test Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+ "\u001b[32m2024-12-10 14:47:28.889\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m62\u001b[0m - \u001b[34m\u001b[1mLoading and Sorting CIFAR100 Test split\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.539\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m65\u001b[0m - \u001b[34m\u001b[1mSplitting Test Data for Sessions\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.540\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m199\u001b[0m - \u001b[34m\u001b[1mSplitting test data for session 0\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.548\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m210\u001b[0m - \u001b[34m\u001b[1mCreating dataset for session 0 (pretraining). There are 5000 samples, and 5000 labels. There are 50 different classes\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.551\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m211\u001b[0m - \u001b[34m\u001b[1mClasses in Session 0's Test Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
" 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
" 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49])\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:42.979\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m242\u001b[0m - \u001b[34m\u001b[1mSplitting test data for 5 sessions\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:42.980\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m245\u001b[0m - \u001b[34m\u001b[1mSplitting test data for session 1\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:42.980\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m250\u001b[0m - \u001b[34m\u001b[1mOld classes end at 50 (exc), New classes start at 50 (inc) and end at 60 (exc)\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:42.986\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m263\u001b[0m - \u001b[34m\u001b[1mCreating OLD dataset for session 1. There are 5000 samples, and 5000 labels. There are 50 different classes\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:42.988\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m264\u001b[0m - \u001b[34m\u001b[1mClasses in Session 1's OLD Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+ "\u001b[32m2024-12-10 14:47:29.552\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m216\u001b[0m - \u001b[34m\u001b[1mSplitting test data for 5 sessions\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.553\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m219\u001b[0m - \u001b[34m\u001b[1mSplitting test data for session 1\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.554\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m224\u001b[0m - \u001b[34m\u001b[1mOld classes end at 50 (exc), New classes start at 50 (inc) and end at 60 (exc)\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.562\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m237\u001b[0m - \u001b[34m\u001b[1mCreating OLD dataset for session 1. There are 5000 samples, and 5000 labels. There are 50 different classes\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.564\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m238\u001b[0m - \u001b[34m\u001b[1mClasses in Session 1's OLD Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
" 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
" 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49])\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:42.990\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m279\u001b[0m - \u001b[34m\u001b[1mCreating NEW dataset for session 1. There are 1000 samples, and 1000 labels. There are 10 different classes\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:42.991\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m280\u001b[0m - \u001b[34m\u001b[1mClasses in Session 1's NEW Dataset: tensor([50, 51, 52, 53, 54, 55, 56, 57, 58, 59])\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:42.996\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m290\u001b[0m - \u001b[34m\u001b[1mCreating ALL dataset for session 1. There are 6000 samples, and 6000 labels. There are 60 different classes\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:42.997\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m291\u001b[0m - \u001b[34m\u001b[1mClasses in Session 1's ALL Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+ "\u001b[32m2024-12-10 14:47:29.566\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m253\u001b[0m - \u001b[34m\u001b[1mCreating NEW dataset for session 1. There are 1000 samples, and 1000 labels. There are 10 different classes\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.567\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m254\u001b[0m - \u001b[34m\u001b[1mClasses in Session 1's NEW Dataset: tensor([50, 51, 52, 53, 54, 55, 56, 57, 58, 59])\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.570\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m264\u001b[0m - \u001b[34m\u001b[1mCreating ALL dataset for session 1. There are 6000 samples, and 6000 labels. There are 60 different classes\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.571\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m265\u001b[0m - \u001b[34m\u001b[1mClasses in Session 1's ALL Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
" 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
" 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,\n",
" 54, 55, 56, 57, 58, 59])\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:42.998\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m245\u001b[0m - \u001b[34m\u001b[1mSplitting test data for session 2\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:42.998\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m250\u001b[0m - \u001b[34m\u001b[1mOld classes end at 60 (exc), New classes start at 60 (inc) and end at 70 (exc)\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.004\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m263\u001b[0m - \u001b[34m\u001b[1mCreating OLD dataset for session 2. There are 6000 samples, and 6000 labels. There are 60 different classes\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.005\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m264\u001b[0m - \u001b[34m\u001b[1mClasses in Session 2's OLD Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+ "\u001b[32m2024-12-10 14:47:29.572\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m219\u001b[0m - \u001b[34m\u001b[1mSplitting test data for session 2\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.573\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m224\u001b[0m - \u001b[34m\u001b[1mOld classes end at 60 (exc), New classes start at 60 (inc) and end at 70 (exc)\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.579\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m237\u001b[0m - \u001b[34m\u001b[1mCreating OLD dataset for session 2. There are 6000 samples, and 6000 labels. There are 60 different classes\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.581\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m238\u001b[0m - \u001b[34m\u001b[1mClasses in Session 2's OLD Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
" 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
" 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,\n",
" 54, 55, 56, 57, 58, 59])\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.007\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m279\u001b[0m - \u001b[34m\u001b[1mCreating NEW dataset for session 2. There are 1000 samples, and 1000 labels. There are 10 different classes\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.008\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m280\u001b[0m - \u001b[34m\u001b[1mClasses in Session 2's NEW Dataset: tensor([60, 61, 62, 63, 64, 65, 66, 67, 68, 69])\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.013\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m290\u001b[0m - \u001b[34m\u001b[1mCreating ALL dataset for session 2. There are 7000 samples, and 7000 labels. There are 70 different classes\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.014\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m291\u001b[0m - \u001b[34m\u001b[1mClasses in Session 2's ALL Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+ "\u001b[32m2024-12-10 14:47:29.582\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m253\u001b[0m - \u001b[34m\u001b[1mCreating NEW dataset for session 2. There are 1000 samples, and 1000 labels. There are 10 different classes\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.583\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m254\u001b[0m - \u001b[34m\u001b[1mClasses in Session 2's NEW Dataset: tensor([60, 61, 62, 63, 64, 65, 66, 67, 68, 69])\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.585\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m264\u001b[0m - \u001b[34m\u001b[1mCreating ALL dataset for session 2. There are 7000 samples, and 7000 labels. There are 70 different classes\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.586\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m265\u001b[0m - \u001b[34m\u001b[1mClasses in Session 2's ALL Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
" 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
" 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,\n",
" 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69])\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.015\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m245\u001b[0m - \u001b[34m\u001b[1mSplitting test data for session 3\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.015\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m250\u001b[0m - \u001b[34m\u001b[1mOld classes end at 70 (exc), New classes start at 70 (inc) and end at 80 (exc)\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.026\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m263\u001b[0m - \u001b[34m\u001b[1mCreating OLD dataset for session 3. There are 7000 samples, and 7000 labels. There are 70 different classes\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.027\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m264\u001b[0m - \u001b[34m\u001b[1mClasses in Session 3's OLD Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+ "\u001b[32m2024-12-10 14:47:29.587\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m219\u001b[0m - \u001b[34m\u001b[1mSplitting test data for session 3\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.587\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m224\u001b[0m - \u001b[34m\u001b[1mOld classes end at 70 (exc), New classes start at 70 (inc) and end at 80 (exc)\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.594\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m237\u001b[0m - \u001b[34m\u001b[1mCreating OLD dataset for session 3. There are 7000 samples, and 7000 labels. There are 70 different classes\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.595\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m238\u001b[0m - \u001b[34m\u001b[1mClasses in Session 3's OLD Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
" 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
" 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,\n",
" 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69])\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.029\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m279\u001b[0m - \u001b[34m\u001b[1mCreating NEW dataset for session 3. There are 1000 samples, and 1000 labels. There are 10 different classes\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.030\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m280\u001b[0m - \u001b[34m\u001b[1mClasses in Session 3's NEW Dataset: tensor([70, 71, 72, 73, 74, 75, 76, 77, 78, 79])\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.037\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m290\u001b[0m - \u001b[34m\u001b[1mCreating ALL dataset for session 3. There are 8000 samples, and 8000 labels. There are 80 different classes\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.038\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m291\u001b[0m - \u001b[34m\u001b[1mClasses in Session 3's ALL Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+ "\u001b[32m2024-12-10 14:47:29.597\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m253\u001b[0m - \u001b[34m\u001b[1mCreating NEW dataset for session 3. There are 1000 samples, and 1000 labels. There are 10 different classes\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.598\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m254\u001b[0m - \u001b[34m\u001b[1mClasses in Session 3's NEW Dataset: tensor([70, 71, 72, 73, 74, 75, 76, 77, 78, 79])\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.600\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m264\u001b[0m - \u001b[34m\u001b[1mCreating ALL dataset for session 3. There are 8000 samples, and 8000 labels. There are 80 different classes\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.601\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m265\u001b[0m - \u001b[34m\u001b[1mClasses in Session 3's ALL Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
" 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
" 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,\n",
" 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,\n",
" 72, 73, 74, 75, 76, 77, 78, 79])\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.039\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m245\u001b[0m - \u001b[34m\u001b[1mSplitting test data for session 4\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.039\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m250\u001b[0m - \u001b[34m\u001b[1mOld classes end at 80 (exc), New classes start at 80 (inc) and end at 90 (exc)\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.052\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m263\u001b[0m - \u001b[34m\u001b[1mCreating OLD dataset for session 4. There are 8000 samples, and 8000 labels. There are 80 different classes\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.054\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m264\u001b[0m - \u001b[34m\u001b[1mClasses in Session 4's OLD Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+ "\u001b[32m2024-12-10 14:47:29.602\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m219\u001b[0m - \u001b[34m\u001b[1mSplitting test data for session 4\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.602\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m224\u001b[0m - \u001b[34m\u001b[1mOld classes end at 80 (exc), New classes start at 80 (inc) and end at 90 (exc)\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.610\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m237\u001b[0m - \u001b[34m\u001b[1mCreating OLD dataset for session 4. There are 8000 samples, and 8000 labels. There are 80 different classes\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.611\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m238\u001b[0m - \u001b[34m\u001b[1mClasses in Session 4's OLD Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
" 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
" 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,\n",
" 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,\n",
" 72, 73, 74, 75, 76, 77, 78, 79])\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.055\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m279\u001b[0m - \u001b[34m\u001b[1mCreating NEW dataset for session 4. There are 1000 samples, and 1000 labels. There are 10 different classes\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.056\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m280\u001b[0m - \u001b[34m\u001b[1mClasses in Session 4's NEW Dataset: tensor([80, 81, 82, 83, 84, 85, 86, 87, 88, 89])\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.064\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m290\u001b[0m - \u001b[34m\u001b[1mCreating ALL dataset for session 4. There are 9000 samples, and 9000 labels. There are 90 different classes\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.065\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m291\u001b[0m - \u001b[34m\u001b[1mClasses in Session 4's ALL Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+ "\u001b[32m2024-12-10 14:47:29.613\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m253\u001b[0m - \u001b[34m\u001b[1mCreating NEW dataset for session 4. There are 1000 samples, and 1000 labels. There are 10 different classes\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.613\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m254\u001b[0m - \u001b[34m\u001b[1mClasses in Session 4's NEW Dataset: tensor([80, 81, 82, 83, 84, 85, 86, 87, 88, 89])\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.616\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m264\u001b[0m - \u001b[34m\u001b[1mCreating ALL dataset for session 4. There are 9000 samples, and 9000 labels. There are 90 different classes\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.617\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m265\u001b[0m - \u001b[34m\u001b[1mClasses in Session 4's ALL Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
" 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
" 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,\n",
" 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,\n",
" 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89])\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.066\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m245\u001b[0m - \u001b[34m\u001b[1mSplitting test data for session 5\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.066\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m250\u001b[0m - \u001b[34m\u001b[1mOld classes end at 90 (exc), New classes start at 90 (inc) and end at 100 (exc)\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.080\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m263\u001b[0m - \u001b[34m\u001b[1mCreating OLD dataset for session 5. There are 9000 samples, and 9000 labels. There are 90 different classes\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.082\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m264\u001b[0m - \u001b[34m\u001b[1mClasses in Session 5's OLD Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+ "\u001b[32m2024-12-10 14:47:29.618\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m219\u001b[0m - \u001b[34m\u001b[1mSplitting test data for session 5\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.618\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m224\u001b[0m - \u001b[34m\u001b[1mOld classes end at 90 (exc), New classes start at 90 (inc) and end at 100 (exc)\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.626\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m237\u001b[0m - \u001b[34m\u001b[1mCreating OLD dataset for session 5. There are 9000 samples, and 9000 labels. There are 90 different classes\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.628\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m238\u001b[0m - \u001b[34m\u001b[1mClasses in Session 5's OLD Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
" 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
" 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,\n",
" 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,\n",
" 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89])\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.084\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m279\u001b[0m - \u001b[34m\u001b[1mCreating NEW dataset for session 5. There are 1000 samples, and 1000 labels. There are 10 different classes\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.084\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m280\u001b[0m - \u001b[34m\u001b[1mClasses in Session 5's NEW Dataset: tensor([90, 91, 92, 93, 94, 95, 96, 97, 98, 99])\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.093\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m290\u001b[0m - \u001b[34m\u001b[1mCreating ALL dataset for session 5. There are 10000 samples, and 10000 labels. There are 100 different classes\u001b[0m\n",
- "\u001b[32m2024-12-03 12:06:43.094\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m291\u001b[0m - \u001b[34m\u001b[1mClasses in Session 5's ALL Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+ "\u001b[32m2024-12-10 14:47:29.629\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m253\u001b[0m - \u001b[34m\u001b[1mCreating NEW dataset for session 5. There are 1000 samples, and 1000 labels. There are 10 different classes\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.630\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m254\u001b[0m - \u001b[34m\u001b[1mClasses in Session 5's NEW Dataset: tensor([90, 91, 92, 93, 94, 95, 96, 97, 98, 99])\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.632\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m264\u001b[0m - \u001b[34m\u001b[1mCreating ALL dataset for session 5. There are 10000 samples, and 10000 labels. There are 100 different classes\u001b[0m\n",
+ "\u001b[32m2024-12-10 14:47:29.634\u001b[0m | \u001b[34m\u001b[1mDEBUG \u001b[0m | \u001b[36mentcl.data.cifar100.cifar100partition\u001b[0m:\u001b[36m_split_test_data_for_sessions\u001b[0m:\u001b[36m265\u001b[0m - \u001b[34m\u001b[1mClasses in Session 5's ALL Dataset: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
" 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
" 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,\n",
" 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,\n",
@@ -187,26 +184,85 @@
],
"source": [
"from entcl.utils.util import seed\n",
+ "\n",
"seed(8008135)\n",
"from entcl.models.model import ENTCLModel\n",
"from entcl.models.linear_head import LinearHead\n",
- "from entcl.data.cifar100feats import CIFAR100FeatureDataset\n",
+ "from entcl.data.cifar100 import PartitionedCIFAR100FeaturesDataset\n",
"import torch\n",
"import pandas as pd\n",
"import numpy as np\n",
"from tqdm.notebook import tqdm\n",
"\n",
- "device = torch.device('cuda:0')\n",
+ "device = torch.device(\"cuda:0\")\n",
"eps = 1e-8\n",
"\n",
"pretrained_model = ENTCLModel(LinearHead(768, 50), backbone_version=1)\n",
- "pretrained_model.head.load_state_dict(torch.load('/cl/entcl_LFS/experiments/dino_nosched_bb/session_0/head_s0_ep99.pt'))\n",
+ "pretrained_model.head.load_state_dict(\n",
+ " torch.load(\n",
+ " \"/cl/entcl_LFS/experiments/dino_cheat_20_cl_eps/session_0/head_s0_ep99.pt\"\n",
+ " )\n",
+ ")\n",
"pretrained_model = pretrained_model.to(device)\n",
"\n",
- "dataset_master = CIFAR100FeatureDataset(backbone=)\n",
+ "dataset_master = PartitionedCIFAR100FeaturesDataset()\n",
"dataset = dataset_master.get_dataset(1)"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": 175,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 1000x500 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Novel Count: 4000\n",
+ "Known Count: 1000\n"
+ ]
+ }
+ ],
+ "source": [
+ "# show a bar chart of the class distribution, colour classes 0-50 blue and 50-100 orange\n",
+ "\n",
+ "from matplotlib import pyplot as plt\n",
+ "\n",
+ "\n",
+ "class_counts = {i.item(): 0 for i in dataset.tensors[1].unique()}\n",
+ "for _, y, _ in dataset:\n",
+ " class_counts[y.item()] += 1\n",
+ "\n",
+ "df = pd.DataFrame(columns=[\"class\", \"count\"])\n",
+ "df[\"class\"] = class_counts.keys()\n",
+ "df[\"count\"] = class_counts.values()\n",
+ "\n",
+ "plt.figure(figsize=(10, 5))\n",
+ "plt.bar(\n",
+ " df[\"class\"],\n",
+ " df[\"count\"],\n",
+ " color=[\"blue\" if c < 50 else \"orange\" for c in df[\"class\"]],\n",
+ ")\n",
+ "plt.xlabel(\"Class\")\n",
+ "plt.ylabel(\"Count\")\n",
+ "plt.title(\"Class distribution\")\n",
+ "plt.show()\n",
+ "\n",
+ "\n",
+ "print(\"Novel Count: \", df[df[\"class\"] >= 50][\"count\"].sum())\n",
+ "print(\"Known Count: \", df[df[\"class\"] < 50][\"count\"].sum())"
+ ]
+ },
{
"cell_type": "markdown",
"metadata": {},
@@ -216,13 +272,13 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 176,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "cba9e1a8a0eb49eb881081a14a2fd8ca",
+ "model_id": "f960e16e502b4d35bae90d4c22df62c4",
"version_major": 2,
"version_minor": 0
},
@@ -232,32 +288,16 @@
},
"metadata": {},
"output_type": "display_data"
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "/root/miniconda3/envs/entcl/lib/python3.10/site-packages/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).\n",
- " warnings.warn(\n",
- "/root/miniconda3/envs/entcl/lib/python3.10/site-packages/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).\n",
- " warnings.warn(\n",
- "/root/miniconda3/envs/entcl/lib/python3.10/site-packages/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).\n",
- " warnings.warn(\n",
- "/root/miniconda3/envs/entcl/lib/python3.10/site-packages/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).\n",
- " warnings.warn(\n"
- ]
}
],
"source": [
- "dataloader = torch.utils.data.DataLoader(dataset,\n",
- " batch_size=512,\n",
- " shuffle=False,\n",
- " num_workers=4,\n",
- " pin_memory=True)\n",
+ "dataloader = torch.utils.data.DataLoader(\n",
+ " dataset, batch_size=512, shuffle=False, num_workers=4, pin_memory=True\n",
+ ")\n",
"\n",
"# DataFrame columns\n",
- "feat_cols = [f'feat_{i}' for i in range(768)]\n",
- "logit_cols = [f'logit_{i}' for i in range(50)]\n",
+ "feat_cols = [f\"feat_{i}\" for i in range(768)]\n",
+ "logit_cols = [f\"logit_{i}\" for i in range(50)]\n",
"\n",
"# List to store batch results\n",
"results = []\n",
@@ -266,36 +306,49 @@
"pretrained_model.eval()\n",
"\n",
"# Iterate over the dataloader\n",
- "for x, label, truetype in tqdm(dataloader, desc='Calculating Entropies', unit='batch'):\n",
+ "for x, label, truetype in tqdm(dataloader, desc=\"Calculating Entropies\", unit=\"batch\"):\n",
" with torch.no_grad():\n",
" # Move inputs to the appropriate device\n",
" x = x.to(device)\n",
- " \n",
+ "\n",
" # Get model outputs\n",
- " logits, feats = pretrained_model(x)\n",
- " \n",
+ " logits = pretrained_model.forward_head(x)\n",
+ "\n",
" # Compute softmax and entropy\n",
" softmax = torch.nn.functional.softmax(logits, dim=1)\n",
" entropy = -torch.sum(softmax * torch.log(softmax + 1e-12), dim=1)\n",
- " \n",
+ "\n",
" # Compute energy\n",
" energy = -torch.logsumexp(logits, dim=1) # Efficient log-sum-exp trick\n",
- " \n",
+ "\n",
" # Move data to CPU and convert to NumPy\n",
- " feats = feats.cpu().numpy()\n",
+ " feats = x.cpu().numpy()\n",
" logits = logits.cpu().numpy()\n",
" entropy = entropy.cpu().numpy()\n",
" energy = energy.cpu().numpy()\n",
" label = label.cpu().numpy()\n",
" truetype = truetype.cpu().numpy()\n",
- " \n",
+ " pred_label = np.argmax(logits, axis=1)\n",
+ "\n",
" # Append batch results to the list\n",
" for i in range(x.size(0)):\n",
- " results.append([entropy[i], energy[i], label[i], truetype[i], *feats[i], *logits[i]])\n",
+ " results.append(\n",
+ " [\n",
+ " entropy[i],\n",
+ " energy[i],\n",
+ " label[i],\n",
+ " pred_label[i],\n",
+ " truetype[i],\n",
+ " *feats[i],\n",
+ " *logits[i],\n",
+ " ]\n",
+ " )\n",
"\n",
"# Create the DataFrame in one step\n",
- "columns = ['entropy', 'energy', 'label', 'true_type'] + feat_cols + logit_cols\n",
- "df = pd.DataFrame(results, columns=columns)\n"
+ "columns = (\n",
+ " [\"entropy\", \"energy\", \"label\", \"pred_label\", \"true_type\"] + feat_cols + logit_cols\n",
+ ")\n",
+ "df = pd.DataFrame(results, columns=columns)"
]
},
{
@@ -307,12 +360,22 @@
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": 177,
"metadata": {},
"outputs": [
{
"data": {
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X9Dqefuz0Yvb+++/nvffe44svvuC7774jODi43N0pz+VMo4re3t6lGoAApYrT0NBQunTpwjPPPFPmdaq6JmzYsGF06tSJ//znPwQEBPDHH3/w/vvvl3numV7PVq1aFWcFePXVV8/YkTA8PLxKeUWk+mhaoIi4rSeffJKpU6eyaNEixo0bV+6uXhs3buTZZ5+lRYsWXHvttdWc8tyGDx9OZmZmqc2BizYfHj58ePExb2/vco/4VOS6VqvI8wJzLyFfX99Sb1APHDjATz/9VOZzO31frg8++AAoXWDfd999HD16lKuvvpq0tLQyp26d7sSJE2RmZpb5taLuhUVv0EeNGsXOnTvPup9aVb93fn5+DB06lA0bNtClSxd69epV6nZ68QNmd8urr76au+++m9TU1LM25iiyYMGCEtNs9+/fz+rVq0u9rj179qR///7MmDGD+fPnM378+GofXWnRogV//vlniWM//fRTqe/VJZdcUrwdQVmvVVWLKzB/rr7++mumTJlCeHg411xzTZnnnf5zunr1avbv31/8eg4YMIDg4GC2bt1aZtZevXqdc7RcRKyjkSsRcWuPP/44drudxx57DMMwWLBgQYkRrPXr1xMUFER+fn7xJsLvvfcejRs3ZvHixaXehDidzuK1KKfr3r17tWwGetNNN/Haa69x8803Ex8fT+fOnVm1ahXPPvsso0ePLrE2p3Pnzvz8888sXryYpk2b0qBBA9q2bVvl61ZUdnb2GV+nyuzv07lzZz788EMWLlxIbGwsPj4+Z22vHxwczGOPPcYjjzzCTTfdxHXXXcexY8eYOnUqPj4+PPHEEyXO9/Ly4oUXXiAzM5PevXuzevVqnn76aUaNGsX5559f4tw2bdpw0UUX8e2333L++eeX2mi6LDt27GDkyJH87W9/Y/DgwTRt2pTjx4/z9ddf8+abbzJkyBD69+8PwKRJk1i4cCGXX345Dz/8MOeddx7Z2dksX76cSy65hKFDh7rke/fyyy9z/vnnM3DgQP7+97/TokULTpw4we7du1m8eHFxcXfppZfSqVMnevXqRVhYGPv372fmzJlER0fTunXrcz5OSkoKY8aM4fbbbyc9PZ0nnngCHx8fpkyZUurc+++/n7Fjx2Kz2Src0a8ybrzxRh577DEef/xxBg8ezNatW/nPf/5DUFBQifOmTZvG0qVL6d+/P/fddx9t27YlJyeH+Ph4vvnmG9544w0iIyOrlOWGG25gypQprFixgn/+859nLIDWrVvHbbfdxjXXXENiYiKPPvooERERxa9XQEAAr776KjfffDOpqalcffXVNG7cmCNHjrBx40aOHDnC66+/XqWsIlKNLGymISJSQlE3rd9//73U14o6v1155ZVGXl5ecbfAopu3t7fRtGlTY8SIEcbLL79sZGRklLrG2boFAsauXbvOmi86Otq4+OKLz/k8Tu8WaBiGcezYMePOO+80mjZtanh4eBjR0dHGlClTjJycnBLnxcXFGQMGDDD8/PwMoMwOe5W5rqu6BQJGfn6+YRhn/n4VdZlbtmxZ8bH4+HhjxIgRRoMGDQzAiI6OLnHuRx99VGaWt99+2+jSpYvh5eVlBAUFGZdffnmpzm5FHeb+/PNPY8iQIYavr6/RsGFD4+9//7uRmZlZ5nXnzp1rAMaHH35Yrtfk+PHjxtNPP20MGzbMiIiIMLy8vAx/f3+jW7duxtNPP21kZWWVOv/+++83mjdvbnh6ehqNGzc2Lr74YmP79u3F55T3e8dp3elOtW/fPuPWW281IiIiDE9PTyMsLMzo379/cec5wzCMF154wejfv78RGhpqeHl5Gc2bNzcmTJhgxMfHn/U5F31v3nvvPeO+++4zwsLCDG9vb2PgwIHGunXryrxPbm6u4e3tbVx00UVnvfaZnKlb4Jl+dnNzc41//OMfRlRUlOHr62sMHjzYiIuLK9Ut0DAM48iRI8Z9991nxMTEGJ6enkbDhg2Nnj17Go8++ugZf07Kcrbvx/jx4w0PDw/jwIEDpb5W9Pvy/fffGzfeeKMRHBxc3BGzrP/3LF++3Lj44ouNhg0bGp6enkZERIRx8cUXn/F3RUTcg80wztBSS0REpBYYP348H3/88Rmn7ZXlqquu4tdffyU+Pv6MTQ6k4hYvXsxll13G119/zejRo62OU6Py8vJo0aIF559/PosWLSr19blz53LLLbfw+++/V6mpjoi4N00LFBGReiE3N5c//viD3377jc8++4wXX3xRhZWLbN26lf379/Pggw/SrVu34hbn9cGRI0fYsWMHc+bM4fDhwzz88MNWRxIRC6m4EhGReiEpKYn+/fsTGBjIxIkTuffee62OVGfcdddd/PLLL/To0YN33333nHuG1SVff/01t9xyC02bNmXWrFlltl8XkfpD0wJFRERERERcQK3YRUREREREXEDFlYiIiIiIiAuouBIREREREXEBNbQog9Pp5NChQzRo0KBeLcoVEREREZGSDMPgxIkTNGvWDLv97GNTKq7KcOjQIaKioqyOISIiIiIibiIxMZHIyMiznqPiqgwNGjQAzBcwMDDQ4jQiIiIiImKVjIwMoqKiimuEs1FxVYaiqYCBgYEqrkREREREpFzLhdTQQkRERERExAVUXImIiIiIiLiAiisREREREREX0JorEREREZEKMgyDgoICCgsLrY4iLuDp6YnD4ajydVRciYiIiIhUQF5eHklJSWRlZVkdRVzEZrMRGRlJQEBAla6j4kpEREREpJycTif79u3D4XDQrFkzvLy8ytVFTtyXYRgcOXKEAwcO0Lp16yqNYFleXM2aNYvnnnuOpKQkOnbsyMyZMxk4cGCZ565atYr/+7//Y/v27WRlZREdHc3EiRN54IEHis+ZO3cut9xyS6n7Zmdn4+PjU23PQ0RERETqvry8PJxOJ1FRUfj5+VkdR1wkLCyM+Ph48vPza29xtXDhQiZNmsSsWbMYMGAAs2fPZtSoUWzdupXmzZuXOt/f35977rmHLl264O/vz6pVq5g4cSL+/v7ccccdxecFBgayY8eOEvdVYSUiIiIirmK3qy9cXeKq0UdLi6sXX3yRCRMmcNtttwEwc+ZMlixZwuuvv8706dNLnd+9e3e6d+9e/HmLFi349NNPWblyZYniymaz0aRJk+p/AiIiIiIiIn+xrOTOy8tj/fr1jBgxosTxESNGsHr16nJdY8OGDaxevZrBgweXOJ6ZmUl0dDSRkZFccsklbNiw4azXyc3NJSMjo8RNRERERESkIiwrro4ePUphYSHh4eEljoeHh5OcnHzW+0ZGRuLt7U2vXr24++67i0e+ANq1a8fcuXP58ssvWbBgAT4+PgwYMIBdu3ad8XrTp08nKCio+BYVFVW1JyciIiIiIqXEx8djs9mIi4sr933Gjx/PFVdcUaXH/fnnn7HZbKSlpVXpOudi+WTR0+c3GoZxzjmPK1euZN26dbzxxhvMnDmTBQsWFH+tb9++3HDDDXTt2pWBAweyaNEi2rRpw6uvvnrG602ZMoX09PTiW2JiYtWelIiIiIjUS0OGDGHSpElWx6ixYkJKsmzNVWhoKA6Ho9QoVUpKSqnRrNPFxMQA0LlzZw4fPsyTTz7JddddV+a5drud3r17n3XkytvbG29v7wo+AxERERGRijEMg8LCQjw8LG/aLdXAspErLy8vevbsydKlS0scX7p0Kf379y/3dQzDIDc396xfj4uLo2nTppXOKiIiIiJyLuPHj2f58uW8/PLL2Gw2bDYbc+fOxWazsWTJEnr16oW3tzcrV64sc6rbpEmTGDJkSPHnhmHw73//m9jYWHx9fenatSsff/zxOXPEx8czdOhQAEJCQrDZbIwfP5558+bRqFGjUu+dr7rqKm666SYAnnzySbp168bs2bOL281fc801pUbA5syZQ/v27fHx8aFdu3bMmjWr4i8YUFhYyIQJE4iJicHX15e2bdvy8ssvl3nu1KlTady4MYGBgUycOJG8vLzir1X2tXI1S0vmyZMnc+ONN9KrVy/69evHm2++SUJCAnfeeSdgTtc7ePAg8+bNA+C1116jefPmtGvXDjD3vXr++ee59957i685depU+vbtS+vWrcnIyOCVV14hLi6O1157reafoIiIiIjUGy+//DI7d+6kU6dOTJs2DYAtW7YA8I9//IPnn3+e2NhYgoODy3W9f/7zn3z66ae8/vrrtG7dmhUrVnDDDTcQFhZWqqHbqaKiovjkk0+46qqr2LFjB4GBgfj6+uLl5cV9993Hl19+yTXXXAOYfRC++uorvvvuu+L77969m0WLFrF48WIyMjKYMGECd999N/Pnzwfgrbfe4oknnuA///kP3bt3Z8OGDdx+++34+/tz8803V+g1czqdREZGsmjRIkJDQ1m9ejV33HEHTZs25dprry0+78cff8THx4dly5YRHx/PLbfcQmhoKM8880yVXitXs7S4Gjt2LMeOHWPatGkkJSXRqVMnvvnmG6KjowFISkoiISGh+Hyn08mUKVPYt28fHh4etGzZkn/9619MnDix+Jy0tDTuuOMOkpOTCQoKonv37qxYsYLzzjuvxp+fiIiIiNQfQUFBeHl54efnV7wt0Pbt2wGYNm0aF154YbmvdfLkSV588UV++ukn+vXrB0BsbCyrVq1i9uzZZy0YHA4HDRs2BKBx48Ylirlx48YxZ86c4uJq/vz5REZGlhgxy8nJ4d133yUyMhKAV199lYsvvpgXXniBJk2a8NRTT/HCCy9w5ZVXAuaSna1btzJ79uwKF1eenp5MnTq1+POYmBhWr17NokWLShRXXl5evPPOO/j5+dGxY0emTZvG//t//4+nnnqK7OzsSr9Wrmb5ZM+77rqLu+66q8yvzZ07t8Tn9957b4lRqrK89NJLvPTSS66KJyIiIiJSZb169arQ+Vu3biUnJ6dUQZaXl1di39eKuv322+nduzcHDx4kIiKCOXPmMH78+BIN5Zo3b15cWAH069cPp9PJjh07cDgcJCYmMmHCBG6//fbicwoKCggKCqpUpjfeeIO3336b/fv3k52dTV5eHt26dStxTteuXfHz8yuRKTMzk8TERFJSUqrltaoMy4srEREREZG6zt/fv8TndrsdwzBKHMvPzy/+b6fTCcDXX39NREREifOq0oite/fudO3alXnz5jFy5Eg2bdrE4sWLz3qfosLLZrMV53rrrbfo06dPifMcDkeF8yxatIgHHniAF154gX79+tGgQQOee+451q5dW677n5rJ1a9VZai4EqlOWamw5yfIOwn52VCYBx2vgODmVicTERGRauDl5UVhYeE5zwsLC2Pz5s0ljsXFxeHp6QlAhw4d8Pb2JiEhoVLT2ry8vADKzHLbbbfx0ksvcfDgQS644IJSe7wmJCRw6NAhmjVrBsCaNWuw2+20adOG8PBwIiIi2Lt3L9dff32Fc51u5cqV9O/fv8RMtj179pQ6b+PGjWRnZ+Pr6wvAr7/+SkBAAJGRkYSEhFTptXIlFVci1eV4PMy73PwI4OENhgErn4crXod2F1uZTkRERKpBixYtWLt2LfHx8QQEBBSPqpxu2LBhPPfcc8ybN49+/frx/vvvs3nz5uJpbA0aNOChhx7igQcewOl0cv7555ORkcHq1asJCAg459qm6OhobDYbX331FaNHj8bX15eAgAAArr/+eh566CHeeuut4sZxp/Lx8eHmm2/m+eefJyMjg/vuu49rr722eB3Zk08+yX333UdgYCCjRo0iNzeXdevWcfz4cSZPnlyh16tVq1bMmzePJUuWEBMTw3vvvcfvv/9evPVSkby8PCZMmMA///lP9u/fzxNPPME999yD3W6v8mvlSpZvIixSJ6Vsg/+OMEeqxrwJN30J138C186Dxh3gw3Gw5FEozD/3tURERKTWeOihh3A4HHTo0IGwsLASzdlONXLkSB577DH+8Y9/0Lt3b06cOFHcDr3IU089xeOPP8706dNp3749I0eOZPHixaUKj7JEREQwdepUHn74YcLDw7nnnnuKvxYYGMhVV11FQEBAqXbwYBY8V155JaNHj2bEiBF06tSpRKv12267jbfffpu5c+fSuXNnBg8ezNy5c8uV63R33nknV155JWPHjqVPnz4cO3aszH4Mw4cPp3Xr1gwaNIhrr72WSy+9lCeffLL461V5rVzJZpw+2VPIyMggKCiI9PR0AgMDrY4jtc2BdfD+VeAbAhdOMz+eyjBg25ew/h2I7AM3fQEeXtZkFRERkQrJyclh3759xMTE4OPjY3WcSrvwwgtp3749r7zySonjTz75JJ9//jlxcXHWBLPI2b6vFakNNHIl4konks2pgIHN4KLppQsrAJsNOlwOI56BA2vh5+k1n1NERETqpdTUVD788EN++ukn7r77bqvj1DkqrkRcacVzZvE0/HHwCjj7ueGdoNv18MtM2L+mRuKJiIhI3XDnnXcSEBBQ5u3OO+884/169OjBxIkTmTFjBm3btnV5rmefffaMuUaNGuXyx3M3mhZYBk0LlEpJ3Qf/6QXdb4BOV5fvPs5C+P4RyMmAv68GH/28iYiIuDN3mRaYkpJCRkZGmV8LDAykcePGNZzIlJqaSmpqaplf8/X1LdUq3V24alqgugWKuMrPz4JPELS7pPz3sTtgwAOw+D747v/MLoIiIiIi59C4cWPLCqizadiwIQ0bNrQ6hmU0LVDEFQ5vgT8/gs5jwaOCf8Vq0ATOuwPiPoDt31RPPhERERGpdiquRFzhx6fMIqn1hZW7f8vh0KwH/PCEOVVQRERERGodFVciVZX4G+z8FrqNA4dn5a5hs5nNLY7uhC2fuTafiIiIiNQIFVciVbXmNQhuDjGDq3adsLYQ2dtsza7RKxEREZFaR8WVSFXknoCd30HLYWBzwa9T13FwbDds+rjq1xIRERGRGqVugSJVseM7KMiBFgNdc73Q1hDV1xy96nQVOPQrKiIiUtccTMvm+Mm8Gnu8EH8vIoJ9a+zx6jO9cxOpis0fQ1h7CAh33TW7Xgdf3Q+bFpnruERERKTOOJiWzfAXfiYn31ljj+njaefHB4dUqMAaP348aWlpfP7558XHPv74Y2644QamTZvGP/7xj2pIWvupuBKprOzjsPtH6HWLa6/bqCU07wc//wu6jDX3whIREZE64fjJPHLyndw9tFWNjCYdTMvmtWW7OX4yr0qP9/bbb3P33Xfz2muvcdttt7kwYd2iNVcilbXtK3AWQPT5rr9252shbb+5nktERETqnIhgX2JC/av95ooC7t///jf33HMPH3zwQXFhNX78eK644gqef/55mjZtSqNGjbj77rvJz88vvt/x48e56aabCAkJwc/Pj1GjRrFr1y4ADMMgLCyMTz75pPj8bt26ldgYec2aNXh6epKZmQmAzWbj7bffZsyYMfj5+dG6dWu+/PLLKj8/V1JxJVJZmz+GJl3Arxp2IQ9tDaFt4be3XH9tERERkXJ6+OGHeeqpp/jqq6+46qqrSnxt2bJl7Nmzh2XLlvHuu+8yd+5c5s6dW/z18ePHs27dOr788kvWrFmDYRiMHj2a/Px8bDYbgwYN4ueffwbMQmzr1q3k5+ezdetWAH7++Wd69uxJQEBA8TWnTp3Ktddey59//sno0aO5/vrrSU1NrfbXobxUXIlURuYR2LcCYlzUyKIs7UbD3mVwdHf1PYaIiIjIGXz77bfMmDGDL774ggsuuKDU10NCQvjPf/5Du3btuOSSS7j44ov58ccfAdi1axdffvklb7/9NgMHDqRr167Mnz+fgwcPFq/jGjJkSHFxtWLFCrp27cqwYcOKj/38888MGTKkxGOOHz+e6667jlatWvHss89y8uRJfvvtt+p6CSpMxZVIZWz93Nz4t3m/6nuMFgPBJwjW/bf6HkNERETkDLp06UKLFi14/PHHOXHiRKmvd+zYEYfjf2vDmzZtSkpKCgDbtm3Dw8ODPn36FH+9UaNGtG3blm3btgFmcbVlyxaOHj3K8uXLGTJkCEOGDGH58uUUFBSwevVqBg8uuY9oly5div/b39+fBg0aFD+mO1BxJVIZmz+Bpt3N4qe6OLyg1YWw4X3IO1l9jyMiIiJShoiICJYvX05SUhIXXXRRqQLL09OzxOc2mw2n0+yCaBhGmdc0DAObzQZAp06daNSoEcuXLy8urgYPHszy5cv5/fffyc7O5vzzS65tP9tjugMVVyIVdeIwJKxx3d5WZ9N2NORlwqaPqv+xRERERE7TvHlzli9fTkpKCiNGjCAjI6Nc9+vQoQMFBQWsXbu2+NixY8fYuXMn7du3Byhed/XFF1+wefNmBg4cSOfOncnPz+eNN96gR48eNGjQoFqeV3VRK3aRitq3wvwY0aP6HyugMUSeB7+9CT1uNqciioiISK13MC271jxOZGQkP//8M0OHDmXEiBEsWbLknPdp3bo1l19+ObfffjuzZ8+mQYMGPPzww0RERHD55ZcXnzdkyBAeeOABunfvTmBgIACDBg1i/vz5TJ48ucrZa5qKK5GKil8BwS3AN6RmHq/taPjhcUhcC8371sxjioiISLUI8ffCx9POa8tqrmGVj6edEH+vKl2jaIrg0KFDufDCC2nWrNk57zNnzhzuv/9+LrnkEvLy8hg0aBDffPNNial9Q4cOpbCwsETjisGDB/P555+XWm9VG9iMM02IrMcyMjIICgoiPT29uIIWKTazCzTpDH3urJnHM5zw+d/NaYhXzq6ZxxQREZEy5eTksG/fPmJiYvDx8anUNQ6mZXP8ZJ6Lk51ZiL9XjWxYXJud7ftakdpAI1ciFZGWaG7u2+36mntMmx1aDofNH0Hu8+Bdu+Yei4iISEkRwb4qduooNbQQqYj4lYANwjvV7OO2HAr5ObDVvXYhFxEREZH/UXElUhH7VkLDGPCp4emi/mHQtCvEza/ZxxURERGRclNxJVJehgH7fjbXW1mh5XDY/wscj7fm8UVERETkrFRciZTX8X2QcQiadDn3udWheT/w9IWNH1rz+CIiIiJyViquRMpr30qzuURNr7cq4ukD0QMg7gNzFE1ERERE3IqKK5Hyil8JjVqBl791GVpeYHYrTFhjXQYRERERKZOKK5HyMAzYt8K69VZFwjtAg6ZqbCEiIiLihlRciZTH0V2Qedi69VZFbHaIHQJbPoe8LGuziIiIiEgJ2kRYpDziV4DdAY07WJ0EYofBxgWw8zvodKXVaURERKSi0hIh61jNPZ5fIwiOqrnHc6H4+HhiYmLYsGED3bp1szrOOam4EimP/auhUWuzW5/VAptCaFvY9JGKKxERkdomLRFe6w352TX3mJ6+cPfvFSqwxo8fz7vvvsv06dN5+OGHi49//vnnjBkzBkPNtcqk4kqkPA6uhyZdrU7xPzGD4I93Ifs4+IZYnUZERETKK+uYWVgNfBCCamA0KT0RVr5gPm4FR698fHyYMWMGEydOJCRE7zfKQ2uuRM4l+7i5cW9oK6uT/E+LgVCYD9sWW51EREREKiMoyuxCXN23KhRwF1xwAU2aNGH69OlnPOeTTz6hY8eOeHt706JFC1544YXir02ZMoW+ffuWuk+XLl144oknij+fM2cO7du3x8fHh3bt2jFr1qxKZ7aaiiuRczkUZ35s1NrSGCX4NYSmXeHPj6xOIiIiInWUw+Hg2Wef5dVXX+XAgQOlvr5+/XquvfZa/va3v7Fp0yaefPJJHnvsMebOnQvA9ddfz9q1a9mzZ0/xfbZs2cKmTZu4/vrrAXjrrbd49NFHeeaZZ9i2bRvPPvssjz32GO+++26NPEdXU3Elci6HNph7WwU2szpJSTGDzL23TiRbnURERETqqDFjxtCtW7cSI01FXnzxRYYPH85jjz1GmzZtGD9+PPfccw/PPfccAJ06daJLly588MEHxfeZP38+vXv3pk2bNgA89dRTvPDCC1x55ZXExMRw5ZVX8sADDzB79uyaeYIupuJK5FwO/QENW5lt0N1J8/5g94DNn1qdREREROqwGTNm8O6777J169YSx7dt28aAAQNKHBswYAC7du2isLAQMEev5s839+c0DIMFCxYUj1odOXKExMREJkyYQEBAQPHt6aefLjHaVZu42btFETd08A9o1NLqFKV5B0BET7NroIiIiEg1GTRoECNHjuSRRx4pcdwwDGw2W6ljpxo3bhw7d+7kjz/+YPXq1SQmJvK3v/0NAKfTCZhTA+Pi4opvmzdv5tdff63GZ1R91C1Q5Gwyj0DGQQh1o/VWp4odDMtnwLE97lkAioiISJ3wr3/9i27duhVP5wPo0KEDq1atKnHe6tWradOmDQ6HA4DIyEgGDRrE/Pnzyc7O5oILLiA8PByA8PBwIiIi2Lt3b/FoVm2n4krkbJLizI/u1MziVJG9zb0rNn8Cg/9hdRoREREpr/TEWvU4nTt35vrrr+fVV18tPvbggw/Su3dvnnrqKcaOHcuaNWv4z3/+U6rb3/XXX8+TTz5JXl4eL730UomvPfnkk9x3330EBgYyatQocnNzWbduHcePH2fy5MkuyV6TVFyJnM2hDeAdCAHhVicpm4cPRPVRcSUiIlJb+DUy/zC68oVzn+sqnr7m41bRU089xaJFi4o/79GjB4sWLeLxxx/nqaeeomnTpkybNo3x48eXuN8111zDvffei8Ph4Iorrijxtdtuuw0/Pz+ee+45/vGPf+Dv70/nzp2ZNGlSlfNawWZoe+VSMjIyCAoKIj09ncDAQKvjiJU+GAuZKXDhNKuTnFnib/DTNPj7GgjvYHUaERGROi0nJ4d9+/YRExODj49P5S6Slmhu6ltT/BpVeAPh+uZs39eK1AYauRI5m0MbIGaw1SnOrll38AowR69UXImIiLi/4CgVO3WUugWKnElGEmQeNnc3d2cOT2jezyyuNBAtIiIiYhkVVyJncmiD+dFdOwWeqsVAOL7vfw04RERERKTGqbgSOZNDG8A3BPxCrU5ybk27gk+QNhQWERERsZCKK5EzOfSHOSXwtM3x3JLdAc37a2qgiIhIDVFPuLrFVd9PFVciZTEMOPiH+6+3OlXMIHPD4wO/W51ERESkzvL09AQgKyvL4iTiSnl5eQDFmx9XluXdAmfNmsVzzz1HUlISHTt2ZObMmQwcOLDMc1etWsX//d//sX37drKysoiOjmbixIk88MADJc775JNPeOyxx9izZw8tW7bkmWeeYcyYMTXxdKSuSE+E7FT33Ty4LI07mK1WN38CUedZnUZERKROcjgcBAcHk5KSAoCfnx+22jDLRc7I6XRy5MgR/Pz88PCoWnlkaXG1cOFCJk2axKxZsxgwYACzZ89m1KhRbN26lebNm5c639/fn3vuuYcuXbrg7+/PqlWrmDhxIv7+/txxxx0ArFmzhrFjx/LUU08xZswYPvvsM6699lpWrVpFnz59avopSm11eKv5sWGstTkqwu6A6P6w5TMY+az5uYiIiLhckyZNAIoLLKn97HY7zZs3r3KhbOkmwn369KFHjx68/vrrxcfat2/PFVdcwfTp08t1jSuvvBJ/f3/ee+89AMaOHUtGRgbffvtt8TkXXXQRISEhLFiwoFzX1CbCwsoXYOWL8LcFtWPNVZGUbfDt/4ObF5vTBEVERKTaFBYWkp+fb3UMcQEvLy/s9rJXTNWKTYTz8vJYv349Dz/8cInjI0aMYPXq1eW6xoYNG1i9ejVPP/108bE1a9aUmiY4cuRIZs6cecbr5ObmkpubW/x5RkZGuR5f6rCUbRDcvHYVVgBh7SAg3OwaqOJKRESkWjkcjiqv0ZG6xbKGFkePHqWwsJDw8PASx8PDw0lOTj7rfSMjI/H29qZXr17cfffd3HbbbcVfS05OrvA1p0+fTlBQUPEtKko7Ztd7h7eYxVVtY7NBi/Nh6+dQqL+kiYiIiNQky7sFnj6v0TCMc851XLlyJevWreONN95g5syZpab7VfSaU6ZMIT09vfiWmJhYwWchdUphPhzbDcHRViepnBaDIPs47F1udRIRERGResWyaYGhoaE4HI5SI0opKSmlRp5OFxMTA0Dnzp05fPgwTz75JNdddx1gLjCs6DW9vb3x9vauzNOQuih1LxTmQUgtLa4axkJQpNk1sPUFVqcRERERqTcsG7ny8vKiZ8+eLF26tMTxpUuX0r9//3JfxzCMEuul+vXrV+qa33//fYWuKfVcyl+dAmvryJXNBi0GwvbFkJ9jdRoRERGResPSVuyTJ0/mxhtvpFevXvTr148333yThIQE7rzzTsCcrnfw4EHmzZsHwGuvvUbz5s1p164dYO579fzzz3PvvfcWX/P+++9n0KBBzJgxg8svv5wvvviCH374gVWrVtX8E5TaKWUb+DYEnyCrk1Rei0GwcQHs/gHaX2J1GhEREZF6wdLiauzYsRw7doxp06aRlJREp06d+Oabb4iONkcMkpKSSEhIKD7f6XQyZcoU9u3bh4eHBy1btuRf//oXEydOLD6nf//+fPjhh/zzn//kscceo2XLlixcuFB7XEn5pWytnc0sThUcZU4P3PyJiisRERGRGmLpPlfuSvtc1XOv9IDwTnDe7VYnqZpNH8GmRfD/9oCXv9VpRERERGqlitQGlncLFHEr+dlwfF/tbWZxqhYDzeez49tznysiIiIiVabiSuRUR3aA4ay9zSxO1aCJuanwpo+sTiIiIiJSL6i4EjlVyjbzY3Ad2Ui6xUDY/SNkpVqdRERERKTOU3ElcqqUrRDQBDz9rE7iGjGDwCiErZ9bnURERESkzlNxJXKqutAp8FS+IdC0G/y5yOokIiIiInWeiiuRU9W14gogdjAkrIG0hHOfKyIiIiKVpuJKpEhOOmQcqhudAk/VvB94eMOmj61OIiIiIlKnqbgSKZKy3fxYFzoFnsrTDyL7qGugiIiISDVTcSVSJGUr2BwQVEc6BZ4qdrD5/A5vsTqJiIiISJ2l4kqkSMpWCIoAh6fVSVyvWQ/wDlRjCxEREZFqpOJKpEjKdgiKtDpF9XB4QvQA2LQInE6r04iIiIjUSSquRIoc2wmBdXBKYJHYIWbDjv2/WJ1EREREpE5ScSUCkJsJJ5LNaYF1VeMO0KApbFxgdRIRERGROknFlQjAsd3mx8A6XFzZbNByGGz5zCwmRURERMSlVFyJwP+Kq7o8cgXQcjjkZ8G2L61OIiIiIlLnqLgSATi6C3xDwCvA6iTVK6AxNO0KG+ZbnURERESkzlFxJQJwbFfdnhJ4qpbDYf8qOB5vdRIRERGROkXFlQiYI1eBzaxOUTOa9wdPX9j4odVJREREROoUD6sDiFjOMCB1D0T0sjpJzfD0gejzIW4+DPoH2PU3FpEal58NaYmQth8yUyD3hHnLPwk2B3j4gIc3+ARCUBQER5v78Hn6WJ1cRETOQsWVyIkkyDtZ95tZnKrVcNi9FBJWQ4vzrU4jUrelJcDB9ZD0JyRthMNbIDO55Dke3uDpZxZVhhMK86Aw3/x/E8b/zgttA1HnQeR55sbgoa1q9KmIiMjZqbgSObrL/Fhf1lwBNO5o7nm14X0VVyKuln4A9vwE8b9A/ErIOGge9w+FkBiIGWxOQw5oDAHh4NcQ7Gf459hZACePmqNbmclwdCfsXw1xH5hFWGgb6HA5tL8MmnQ2t1wQERHLqLgSObYL7A5o0MTqJDXHZoNWF8KmRXDRdLNToohUjrMQEtbAzu9g11I4sh1sdmjUCiJ7Q/gtENYOfIMrfm27h/n/pgZNgC7QeoR5PD/LHAlLWA2/vg4rnoPwTtBnInS6Grz8XPkMRUSknFRciRzdbY7inOkvx3VV6wth43zYuBD63ml1GpHapSAP9v5s7hm3/WvITgXfhhDRAzpcAc26Ve/WDp5+0LyveSvMh6Q42PEtfHkffP8Y9BwP/e8D/0bVl0FEREqpZ+8mRcpwdGf96RR4Kt8QiOoL694x/9qt6UQiZ+csNKf5bf4Etn4BOenmdOKWw6B5PwhtbY5Y1TSHpzlCFtkbTiSbxd5vb8Lvb0G/e6Df3eATVPO5RETqIRVXIsd2Q0RPq1NYo+0o+P6f5pSm6P5WpxFxT8mbzK0LNn0EmYfNke7WI6HFQAhp4V5/mGjQBHpPgM5Xm0Xgqpdg7RswZAr0vh0c+mdfRKQ66f+yUr8V5EJ6orkYvD5q0sX8y/u6OSquRE6VmQJ/LjQbR6RsNUd+WgyC2CFmEwl3KqjK4hMEvW41m11sXADfTTEb2Fz8IjTvY3U6EZE6S8WV1G+pe82OW/WpDfupbHbzL/Bx78NF/9L6DKnfCvNh1/fwx3vmVgXYzLbnwx4311LVxnWZfo3MqYGtR8Da1+GdEdDtBhj5TOUabIiIyFnVwn8pRFyoPrZhP12r4bDhPXNT4QH3WZ1GpOYd3f2/34GTR8wuf70mmC3TfQKtTucaoW1g1POwawmsf9dsFX/Fa+Z6MRERcRkVV1K/HdtldvTyCbY6iXV8gqDFAFg/x/wLt92CBfkiNS0/x+z0t34u7P8FvBtAzBCzi2bDWIvDVRO7A9qOhohesPoVeG8M9L4NLpwGXv5WpxMRqRNUXEn9dnS3OWrl7usnqlubi+C7h2HvMnMkS6SuOrLDLKjiPoCcNHPd4cCHzDWHDi+r09WMgMZmQbXjG/OPKnuXwzVzoUknq5OJiNR6Kq6kfquvbdhP17gjNGwJv85ScSV1T9Eo1bp3zM6YPkHQcri53rA+r7dsdwk07QbLZ8Dbw+CiGeb+WPX9j00iIlWg4krqt2O7of2lVqewns1mdhVb9SKkbIfG7axOJFJ1x/aYIzMb3ofs49CkKwz6h7knlcPT6nTuISgSRj8Pv78NX02CfSvgslfMaZIiIlJhKq6k/jp5zJwWVJ+bWZyqxUD4411z9OqyV6xOI1I5hfnmdLff/wv7loN3oDlK1eai+jtKdS4e3uZGw027wOpX4a1hMHY+hLWxOpmISK2j4krqr2O7zY8qrkwOT2h3sbknzvDHwT/U6kQi5Zd+0PzjwPq55ka/Ye3h/MkQPcAsHuTcijZFXvYsvDUUxryhkX0RkQpSWzCpv1L3mh8bNLU2hztpM8pci/H7f61OInJuhgF7lsGH18PMzmYHvGY94NJXYPRzZptxFVYVExQFF78ATbvCwhvgh6ngLLQ6lYhIraGRK6m/UveaG2x6+lidxH14NzCnUP32Jgy4X6+NuKfsNHOE9be3IHUPBEfDeXdA7FDw8rM6Xe3n6QeDH4Ytn8Cql+DwZrjqbbMRiIiInJWKK6m/ju/TqFVZ2l9mrlnZ9BH0uNHqNCL/k7zJLKg2LYLCPGjeH3rfDuEd1eHO1Ww26HQ1hMTAiufMdVjXfQihra1OJiLi1jQtUOqvY3sgoInVKdxPUARE9TGnWGk6kFitIA82fwL/HQlvnA/bv4aOV8JVc2Dw/5l7M6mwqj4RPc1pgoV55jqsXUutTiQi4tZUXEn9dXwfNFBxVabO15h7gG393OokUl+dSIaf/wUzO8HHt0J+FgyZAlf9F7peB34NrU5YfwRGwKjnzSYhH1wLv7xirncTEZFSNC1Q6qfsNHPfm0BNCyxTWFuI6AU/z4AOV4DdYXUiqQ8MAxJ/M9f8bf0c7J4QO8Tc7DYk2up09ZuXHwx9FOLeh6WPmeuwLn1F6zJFRE6j4krqp+P7zI9ac3VmXa+Dbx403+R2usrqNFKX5efAlk9h7RuQtNEcKel5C7QaDl4BVqeTInYH9LgZglvA6pfh6C7423wIbGZ1MhERt6HiSuqn1KLiSm8KzkijV1LdMpJg3X9h3TuQdcxc3zP8SYjoYW4JIO4pdrBZUC17Bt4cYm44HNXb6lQiIm5B/3pJ/XR8n9l23Ft/FT+rrtfB0R1aeyWulfg7fDzBXE+15j/QvB9cMRsumAqRvVRY1QahreGSl8ztLOaOhg3vW51IRMQtaORK6qfUvZoSWB4avRJXKciDrV/Ar7Pg0B/mqHHPW6DVBeDlb3U6qQzfEBjxDPz2BnxxNxyKg5HPgoeX1clERCyj4krqp9R9asNeXkVrrzZ9DF3HWp1GapuTR2HdHPj9Lcg8DM26w7DHNUJVVzg8oe890LCl2YgkeRNc+646sYpIvaXiSuqn1D3QYrDVKWqHsLYQPQB+eALaX6JRBimf5M2w9nX4c5G5D1XsUGh3qbr+1UU2G7QdbW44vPxfMHsQXDsPmve1OpmISI3Tnw2l/snPNvfQURv28ut5izkC8cvLVicRd+YshG1fwZyL4Y0BsHOJOfJ51Rzod48Kq7qucXu4ZCb4h8Hci2H1f7QflojUOxq5kvrn+H7zo6atlF+DJtDhcvhlJnS/EYKjrE4k7iQ7DeLmm63U0xKgcQcY/H9mowq7/pmpV3xDYMTT8Mc8+P5R2L8arpgFvsFWJxMRqRH6V0/qn9S95kc1tKiYLtfCnp/ghyfh6v9anUbcwZGd8NtsiPsACvOgxfkwYBKEtrE6mVjJ7gG9bjWL7F9mwuyBcM1cs9W+iEgdp2mBUv8c3wce3uDb0OoktYunnzlqtfljSFhrdRqxirMQtn8D714Gr/WGzZ+Yo5pXvQMDH1JhJf/TvK85TdDDB/47Ala+CE6n1alERKqVRq6k/ilqw26zWZ2k9mk1HHZ8A988BLcvA4f+F1JvnDwGG96D39+G9EQIawfnP2iOVjk8rU4n7qpBExj1b3Pa6I/TYM8yuHK2uQmxiEgdpJErqX9S92lKYGXZ7NDnTji82ZzuI3WbYUDib/DpHfBiO1j2jLl57MUvwujnoeVQFVZybnYP6HGzuSdWylaY1Rf+/EjNLkSkTtKfnaX+Sd0LTbtZnaL2CmsLna6Cn/8FbUdBeEerE4mrZaeZLdTXzzHfDDdoAt2uNzf89QmyOp3UVk27wGWvmo1PPr0Ntn5uThsMCLM6mYiIy1g+cjVr1ixiYmLw8fGhZ8+erFy58oznfvrpp1x44YWEhYURGBhIv379WLJkSYlz5s6di81mK3XLycmp7qcitUFhgTmlSSNXVdN1HARFwGcToTDf6jTiCk4n7F0On94OL7SFJQ+bHd4umApj3jQLahVWUlXeDWDQ/4MhUyB+Jbx2nrlBuUaxRKSOsLS4WrhwIZMmTeLRRx9lw4YNDBw4kFGjRpGQkFDm+StWrODCCy/km2++Yf369QwdOpRLL72UDRs2lDgvMDCQpKSkEjcfH5+aeEri7tITwVmgPa6qyuFpdoU7vBVWvmB1GqmKo7th2XR4uQvMuwzifzE7Q141B4Y8YnZ4s1n+dzipa6IHwGWvQXgH+GQCvH8VHI+3OpWISJXZDMO6Pxf16dOHHj168Prrrxcfa9++PVdccQXTp08v1zU6duzI2LFjefzxxwFz5GrSpEmkpaVVOldGRgZBQUGkp6cTGBhY6euIG9r9I7x/JVz5tva5coW4+bDpI5iwFCJ6WJ1GyivjEGz5zJz6lxRndoJscb457S+svZq9SM1KXAtrZ0NuBgx9BPr8HTy8rE4lIlKsIrWBZWuu8vLyWL9+PQ8//HCJ4yNGjGD16tXluobT6eTEiRM0bFiypXZmZibR0dEUFhbSrVs3nnrqKbp3737G6+Tm5pKbm1v8eUZGRgWeidQqx/eB3QH+muPvEp2vhYPrYeENcMfPENDY6kRyJqn7YNti2PoFHFwHdk+I7AWDH4bI3ub2BCJWiOoDTbrAhvfNffT+mAejZpjFvohILWPZXI+jR49SWFhIeHh4iePh4eEkJyeX6xovvPACJ0+e5Nprry0+1q5dO+bOncuXX37JggUL8PHxYcCAAezateuM15k+fTpBQUHFt6ioqMo9KXF/qfsgoIlZYEnVOTzNqWP5WbDwRijIszqRFCnINddQLXkU/tMbXukGPz1ldm47fzKMfQ+GPmqOWKmwEqt5+sJ5t8Olr5gjqe9fBR/8DY7tsTqZiEiFWDYt8NChQ0RERLB69Wr69etXfPyZZ57hvffeY/v27We9/4IFC7jtttv44osvuOCCM/91y+l00qNHDwYNGsQrr7xS5jlljVxFRUVpWmBdtOA6OHEYLpxqdZK6JWUbLHkEul9vdv/StLKal3cSDsXB/l9g30o4sNYssPwameumInpCsx7mm1gRd2YY5s/xuncgOxV6TYDB/wf+jaxOJiL1VK2YFhgaGorD4Sg1SpWSklJqNOt0CxcuZMKECXz00UdnLawA7HY7vXv3PuvIlbe3N97e+sttvXB8H4TEWp2i7mncHvr+HVa/AuGdzL9AS/U5eQyObDOL2uQ/4cA6OLIdDCd4BZhNArrdAE27QkiMil2pXWw2c0Q1sjds+xLi3oeNH8D5D5j77Hn5W51QROSMLCuuvLy86NmzJ0uXLmXMmDHFx5cuXcrll19+xvstWLCAW2+9lQULFnDxxRef83EMwyAuLo7OnTu7JLfUYoYBaQkQ1e/c50rFtR5hFq/f/gO8A6HrWKsT1T4Feeai/px0yEyBkynmx4yD5s/u8XjzlnXMPN/ugOBoaNQKWg6D0Dbm55r2KnWBhzd0vsb8f8vGD2HZs7BmFgx6CHreAp7qAiwi7sfSTYQnT57MjTfeSK9evejXrx9vvvkmCQkJ3HnnnQBMmTKFgwcPMm/ePMAsrG666SZefvll+vbtWzzq5evrS1CQuf/K1KlT6du3L61btyYjI4NXXnmFuLg4XnvtNWuepLiPrGPm1Cl1Caw+vW6Dghxz/ytngTlNsK4pyIWTR+DkUfOWnWoWRLknzFt+jvkaFOSaH5355l5ghflQmHfKx9y/zs02P+Zlmuefzu4wp/YFhIN/Y2g9EoKjIKg5BDYz172J1GU+QdBnInS8wiyyljwCv7xiFlndb9CaQRFxK5YWV2PHjuXYsWNMmzaNpKQkOnXqxDfffEN0dDQASUlJJfa8mj17NgUFBdx9993cfffdxcdvvvlm5s6dC0BaWhp33HEHycnJBAUF0b17d1asWMF5551Xo89N3NDx/ebHgLNPO5UqsDug371gc8AXd5sFVs+brU5VcYX5kLrXnHZ3ZDsc223+/KTth8zDpc+3O8xF+J6+4OEDDi+z6LF7mg0k7I6/PnqYbwS9A8z/dniBw9tsO+3hY07p8/Izpz35BJs37wDtMyUC5v+7B9xvbmi98QP4+kFzn72Bk6H7jSqyRMQtWLrPlbvSPld11OZP4ONb4boPzTexUn0MA9a+ATu+hmH/hPMfBLsbFwjH90Pib2aL8gPrzHVMhX91PvQJgqBI841dQLjZxt+vkXncJxi8G5hFktY1idSstETYtNDsitmgKZw/CXrcpKYtIuJytaKhhUiNOx7/18iACqtqZ7OZC899AuGnZ2D/GhgzGwLcZH+xjEOwZxnErzRv6QfM44ER5vqlHjebjSCCm4NvsKVRReQMgqNg4EPQZay5IfZ3U2DFc9D/Puh1qznqKyJSwzRyVQaNXNVRX95ntve9ZKbVSeqXQxvMqTse3nDVfyFmYM1nKMg1v/e7f4TdP5hT/bBBo5YQ3hHCu5gdD330+y5Sa2UkweaPYM+PZlOdfvfAeXfo91pEqqwitYGKqzKouKqj3r0cnHnmprdSs7KOmQVW8p/Q4XIY9hiEtq7exzwebxZSu5bCvuWQnw3+odC0m7nfU9NuetMlUhdlpsDmj83ffU8/6HeXOZKuUWgRqSQVV1Wk4qqOermr+aa6161WJ6mfnIWwdxnEfWAWW93GmdN3wtq45vrZx83ph3t/Nouq1D1mY43wDtCsJ0T2MtuUa22USP1w8ihs+RR2fgcevtD/nv9NVxYRqQAVV1Wk4qoOchbC042h9x3QbrTVaeq3wjzY8S1sWmTu5xTWHjpdCe0uhtC24CjHUtCCPDi6E5I3QVIcxK+Cw1sAw2w60az7X6NTXbXhqEh9l5VqjmTt/M4cyTp/kllkqfGFiJSTiqsqUnFVB6UlwMzOcMFUiOhpdRoBs8g6+AfsXwWJa81pew4vaBhjFlz+of9rXw7mVJ8TyXAiyZzy58w3jwdGmOc36QThncziSqNTInK6k0dh00ew6ztzz7ihj0DXceX7g46I1GsqrqpIxVUdtG8lvHsJXPGG2VZb3EtBLhzZAekJZnvl9AOQdwKcTjAKzHN8gsE3xLw1aAoNY82Ofl5+lkYXkVomIwni3oN9K8zR8oumQ6vhVqcSETemVuwipzseb34MaGxpDDkDD29o2sW8iYhUp8CmMOgf0PFK+P1teP9KaHsxXPQshLSwOp2I1HJuvKuniAul7TenmTm8rE4iIiLuoFErGDkdBv0/c2rya+fB8n9DYb7VyUSkFlNxJfXD8f3mWhwREZEiNhvEDIYrXod2l8LP/4I3h8ChOKuTiUgtpeJK6ofj8eYCZhERkdN5+kLP8XDxC5B3Et4aBj8+ZXYmFRGpABVXUj8cj4cGTaxOISIi7qxRK7j4Rej6N/jlJXhn5P/W7IqIlIOKK6n78rPhZAoEqLgSEZFzcHhC1+vgon9DxiF4YyBs/dLqVCJSS6i4krovLcH8qDVXIiJSXmFt4dKZ5h56i26E76aYG9KLiJyFiiup+47vNz82UHElIiIV4BUAg6fAeRNh7Wz4YCzknrA6lYi4MRVXUvcdjwe7B/g2rNDdDMPgSJaTtYcKWLg9jz8OF1RPPhERcV82G7S/FIY/Dgmr4b8jzM3ORUTKoE2Epe5L22+ut7I7yn2X3ccLuenrLA6dNIqP2YB7e3hxX09vPOy2aggqIiJuK6KnuQ7rp2nw1lC44VNtfC4ipWjkSuq+4/EQUP427AdOOLn+qyw8HDC5lxfPDfFh7ihfrm7ryX825HHd4iySMp3Vl1dERNxTSDSMfh58guHdS+DgH1YnEhE3o+JK6r7j+8pdXB3JcnLDVycBeLiPD72behDZwI63h40r23jyWD9v9qY7ueSTk6RkqcASEal3fENgxFPQoCnMuwwSf7M6kYi4ERVXUrcZhtktsBxt2DNyDW76Jov0PJjS15sQn9JT/9o1cvD0QB8KnAZPrMqpjsQiIuLuvALgwmkQHA3zLof4X6xOJCJuQsWV1G3Zx83OTuXYQPjl9bnEpzuZ0sebcP8z/2oEe9u4qZMX3+4rYMm+fFemFRGR2sLTD4Y/CaFt4INr4NAGqxOJiBtQcSV1W9pfbdjPscdVSpaT97fmMTrWk6jAc/9a9GvmoEe4nX+uzCE91zjn+SIiUgd5+sDQf0JgJLx/NRzbY3UiEbGYiiup24r2uDrHmqvZcXl42GFUbPkaaNpsNm7t7EVmvsG/ftX0QBGResvTx2zT7ukL742BE4etTiQiFlJxJXVbWoL5D5534BlPSclyMn9rHhfFeODvWf4W64187VzX3pMF2/NZl6w9sERE6i2fILhgKuRlwvyrICfD6kQiYhEVV1K3FTWzsJ25aHpzYx52G1wU41nhyw+P9qB5oI1ZG3KrklJERGq7gMZmgZW6Fz67E5zqKCtSH6m4krotLQECws745SNZTt7fksdFsR4EeFV8Y2C7zcaoGE9+SihkX3phVZKKiEhtF9ICzn8QdnwNK1+wOo2IWEDFldRtafHgf+ZmFm/9NWo1qhKjVkX6RzgI8oY5m/IqfQ0REakjos6DruNg2TOwc4nVaUSkhqm4krrLMCAt8YzNLPILDT7akc/Q5pUbtSri5bBxQbQHi3bkq3OgiIhA17+ZRdYnt6mDoEg9o+JK6q6sY5CfdcY27KsPFXI812BAZPk6BJ7NBS08KXTCgm0avRIRqfdsdjh/MvgEwofXQ3621YlEpIaouJK6K+3sbdgX786nWYCNFoGVH7UqEuxto3+Eg7mb88gv1OiViEi95+UPgx+G1D2w9Amr04hIDVFxJXVXWoL5sYyRq9xCg+/25dO3mQPbWToJVsSoGE+STxp8u09t2UVEBLPBRc/x8Nts2PWD1WlEpAaouJK6Ky0BPP3AK6DUl5YnFpCZD/2aVX1KYJHoIDsdQ+28t0VTA0VE5C/tLoVmPeHzO+HkUavTiEg1U3EldVdagjlqVcbI1OLd+UQH2ohs4NpfgUGRHvyeXMihTO1vIiIimP8GDbgfCvPgi3vMZksiUmepuJK66wx7XGXlGyzdX0BfF45aFenVxIGX3SzeREREAPBrCP3uhZ3fwob3rU4jItVIxZXUXcfjy9zj6sf9BeQUQL9mDpc/pJ+nje7hDr5QcSUiIqdq3hdaDofvH4UTh61OIyLVRMWV1E2GAell73G1eE8+rUPshPtXz49//wgHW4852ZNWWC3XFxGRWqrXrebH7x62NoeIVBsVV1I3ZR0z9xU5rVNgZp7BsoQC+jZ1/ahVkW6NHfh5wJcavRIRkVP5BEHv22DLp7BzidVpRKQaqLiSuql4j6uSxdWvhwrId0LPJtVXXHk5bPRq4uDzXfkYWrgsIiKnihlidg/86gHIzbQ6jYi4mIorqZvOsMfVqoOFhPvZqm1KYJEBER7szzDYfFRdA0VE5BQ2G/T9uznD4qenrU4jIi6m4krqprQE8PI3b6dYeaCAjqHV/2PfMdROkLemBoqISBkaNIGu48zNhZM3W51GRFxIxZXUTWXscZWU6WRPmpPOYdU3JbCIw26jT1MPvtydj1NTA0VE5HTtL4XAZvDdFO19JVKHqLiSuiktAfxL7nH1y8ECbEDH0OovrsBs9X44y2BjiroGiojIaRye0GsCxK+A7V9bnUZEXETFldRNx/eVasO+6kAhsUF2GnjZznAn12odYqeBF/yUUFAjjyciIrVMRC+zucWSR6Ag1+o0IuICKq6k7jEMSEsssYGwYRisPFhAx7Ca+5F32G10CXOwNF7FlYiIlMFmM1uzpx+AX2dZnUZEXEDFldQ9J49CQU6JkasdqU6OZRt0rqEpgUV6hjvYnurk4Al1DRQRkTIER0G70bDiOThx2Oo0IlJFKq6k7imjDfuqgwV42aFNw5r9ke/S2IHDpqmBIiJyFl3Hgc0BP0+3OomIVJGKK6l7ythAeOWBAto1suPlqJn1VkX8PW20a2Tnh/1qyS4iImfg3QA6XQ0b3oNje6xOIyJVoOJK6p7T9rjKKzRYm1RYY10CT9ejsYM1BwvJylerXREROYN2F4NPMCx71uokIlIFKq6k7jltj6sNhwvJKaBG9rcqS48mDvKc5tREERGRMnl4Q9e/weaPIXmT1WlEpJJUXEndc9oeV2sOFRLgCdGBNTslsEgTfzsRATZ+3K/iSkREzqLVBebGwj8+ZXUSEakkFVdS96TFl+gU+MfhAlqH2LHbrCmuALqHO/hhfwFOQ1MDRUTkDOwe0PV62LUEEn61Oo2IVIKKK6lbTtvjymkYbDhcSOsQa6YEFune2MGxbINNR9SSXUREziJmIDSMhR+mmv+miUitouJK6pbT9rjak+bkRD60ruEW7Kdr29COvycsU0t2ERE5G5sdut0ACashfpXVaUSkgiwvrmbNmkVMTAw+Pj707NmTlStXnvHcTz/9lAsvvJCwsDACAwPp168fS5YsKXXeJ598QocOHfD29qZDhw589tln1fkUxJ2kl9zjan1yIXagVbC1P+oOu42OjRysPKDiSkREziGyNzRqBcv/bXUSEakgS99xLly4kEmTJvHoo4+yYcMGBg4cyKhRo0hISCjz/BUrVnDhhRfyzTffsH79eoYOHcqll17Khg0bis9Zs2YNY8eO5cYbb2Tjxo3ceOONXHvttaxdu7amnpZYqXgDYXPk6o/DhTQPtOHjYd16qyKdw+zEpRSSkatpHiIichY2G3S+FuJXQILev4jUJjbDsG5Cb58+fejRowevv/568bH27dtzxRVXMH16+XYp79ixI2PHjuXxxx8HYOzYsWRkZPDtt98Wn3PRRRcREhLCggULynXNjIwMgoKCSE9PJzAwsALPSCz3y8vw87/guoVgszF8YSYxQXYmdPGyOhkpWU7u/zGH2SN8GRnjaXUcERFxZ4YTvrwXQlvDDZ9YnUakXqtIbWDZyFVeXh7r169nxIgRJY6PGDGC1atXl+saTqeTEydO0LBhw+Jja9asKXXNkSNHnvWaubm5ZGRklLhJLXXKHlfpuQZ70py0CbF89isAjf3sNPG3sUpTA0VE5FxsdnP0avcPcPAPq9OISDlZ9q7z6NGjFBYWEh4eXuJ4eHg4ycnJ5brGCy+8wMmTJ7n22muLjyUnJ1f4mtOnTycoKKj4FhUVVYFnIm4lLRECzD2u/jhsFjFWN7M4VadQBytUXImISHm0OB8CI2DF81YnEZFysvxdp+20vYcMwyh1rCwLFizgySefZOHChTRu3LjE1yp6zSlTppCenl58S0xMrMAzELeSFg/+5s/DhsOFBHpBuJ/1662KdAmzsz/DIDFDLdlFROQc7A7ofA3s+BqSN1udRkTKwbLiKjQ0FIfDUWpEKSUlpdTI0+kWLlzIhAkTWLRoERdccEGJrzVp0qTC1/T29iYwMLDETWqhoj2u/mpmsf6v/a3KU6zXlA6hDuw21DVQRETKJ3aIOd39l5lWJxGRcqhUcbVv374qP7CXlxc9e/Zk6dKlJY4vXbqU/v37n/F+CxYsYPz48XzwwQdcfPHFpb7er1+/Utf8/vvvz3pNqSOyj0N+FgSEU+g0iEsppJWbrLcq4u9po1WwXVMDRUSkfOwe0OFy2Pyp+QdEEXFrlXrn2apVK4YOHcr7779PTk5OpR988uTJvP3227zzzjts27aNBx54gISEBO68807AnK530003FZ+/YMECbrrpJl544QX69u1LcnIyycnJpKenF59z//338/333zNjxgy2b9/OjBkz+OGHH5g0aVKlc0otkbbf/OjfmF3HnZzMx22aWZyqc5idXw4WUOhUS3YRESmHVheClx/8+vq5zxURS1XqnefGjRvp3r07Dz74IE2aNGHixIn89ttvFb7O2LFjmTlzJtOmTaNbt26sWLGCb775hujoaACSkpJK7Hk1e/ZsCgoKuPvuu2natGnx7f777y8+p3///nz44YfMmTOHLl26MHfuXBYuXEifPn0q81SlNjllj6v1hwux2yDW4s2Dy9IlzMGJPPjzSKHVUUREpDbw9IU2o+CPuZCdZnUaETmLKu1zVVBQwOLFi5k7dy7ffvstrVu3ZsKECdx4442EhYW5MmeN0j5XtdTqV+GnZ2DcIh78OYcNhwt4ZpCv1alKKXQa3LEkm7939+beHt5WxxERkdog+zh8fCsMexTOf8DqNCL1So3tc+Xh4cGYMWNYtGgRM2bMYM+ePTz00ENERkZy0003kZSUVJXLi1RMWmLxHldxKYXEBjusTlQmh91Gx1AHKxK17kpERMrJNwRaDjWnBhbkWZ1GRM6gSsXVunXruOuuu2jatCkvvvgiDz30EHv27OGnn37i4MGDXH755a7KKXJuafshIJST+QZ705xuOSWwSMdQOxtSCsnO17orEREppw5jIPMwbPrI6iQicgaVevf54osv0rlzZ/r378+hQ4eYN28e+/fv5+mnnyYmJoYBAwYwe/Zs/vhDO4pLDUrbD/7hbDtWiAHEBLlzceWgwAnrDmvdlYiIlFNwFESeB6tfMbcfERG3U6l3n6+//jrjxo0jISGBzz//nEsuuQS7veSlmjdvzn//+1+XhBQ5p1P2uNp0pBAPO0Q2cJ/9rU4XEWAj2NvG6oOaGigiIhXQcQwc2Q57f7Y6iYiUwaMyd1q6dCnNmzcvVVAZhkFiYiLNmzfHy8uLm2++2SUhRc4pJw3yMiEgnM37nEQH2vGwu29xZbPZaN/IbMkuIiJSbuGdICQW1r5hrsESEbdSqZGrli1bcvTo0VLHU1NTiYmJqXIokQorasPuH8amI4W0cOMpgUU6hjrYfNRJRq6mdoiISDnZbND+Eti5BFL3Wp1GRE5TqXegZ+renpmZiY+PT5UCiVTKX8VVjk84e9Kcbr3eqkinUDtOA35L0uiViIhUQMxg8G4Av71tdRIROU2FpgVOnjwZMKc0Pf744/j5+RV/rbCwkLVr19KtWzeXBhQpl7RE8PBmW1YAhUZWrSiuGvvZCPO1sfpQIRe08LQ6joiI1BYe3tB6BGyYB0MfAe8AqxOJyF8qVFxt2LABMEeuNm3ahJeXV/HXvLy86Nq1Kw899JBrE4qUR1oC+Iez+agThw2i3LiZRRGbzUaHUK27EhGRSmg7GrZ8BhsXwHm3W51GRP5SoeJq2bJlANxyyy28/PLL59yhWKTGpO2HgDA2Hy2keaANT4f7F1cAHRs5WJ6Yx7FsJ4183X+0TURE3ERAY2jeF9bOht63mWuxRMRylXo3N2fOHBVW4l7S9oN/Y/6sJc0sinQINbOuTdJ+VyIiUkHtL4Vju2DvMquTiMhfyj1ydeWVVzJ37lwCAwO58sorz3rup59+WuVgIhWSlkhu0/PYleqkb7Pas36pka+dZgHmflejY2tPbhERcQONO0LDWHP0quUwq9OICBUoroKCgrD9NeQcFBRUbYFEKiw7DXIz2EkUBQbE1qKRK4AOjRz8clAjVyIiUkE2G7QZBWtfNxs7BUdZnUik3it3cTVnzpwy/1vEcumJAGzKbYLdBs0Da1lxFWrnh/0FJJ900sS/dmUXERGLxQ6B9XPgj3dh2D+tTiNS71XqnVx2djZZWVnFn+/fv5+ZM2fy/fffuyyYSLn9tcfV5pOBRDaw4VVLmlkU6dDIAcCvhzR6JSIiFeTpC7FDYf27UJhvdRqReq9SxdXll1/OvHnzAEhLS+O8887jhRde4PLLL+f11193aUCRc0pLBIcXf6Z60KKWjVoBBHnbiGpg49dDaskuIiKV0HYUnEyB7V9bnUSk3qvUO9E//viDgQMHAvDxxx/TpEkT9u/fz7x583jllVdcGlDknNISyPdvyo5UJzHBta+4AmjfyMEaFVciIlIZIS2gcQdY947VSUTqvUq9E83KyqJBgwYAfP/991x55ZXY7Xb69u3L/v37XRpQ5JzS4tnt2Y58J7Vy5AqgQyM7+zMMkjKdVkcREZHaqO0o2Lccju62OolIvVapd6KtWrXi888/JzExkSVLljBixAgAUlJStP+V1Lzj+9lujwVqXzOLIu2L111p9EpERCohegB4B2r0SsRilXon+vjjj/PQQw/RokUL+vTpQ79+/QBzFKt79+4uDShyTmkJbC+MpLGfDT/P2tXMokigt43mDWysUVMLERGpDIcXtLoA4t6H/Gyr04jUW5Uqrq6++moSEhJYt24d3333XfHx4cOH89JLL7ksnMg5/bXH1dbcRkQ1qJ2jVkXah2rdlYiIVEGbiyAnHbZ+aXUSkXqr0u9GmzRpQvfu3bHb/3eJ8847j3bt2rkkmEi5/LXH1bZMf6IDa+eoVZEOjewknjA4eELrrkREpBICm0GTruaeVyJiiXJvInyqkydP8q9//Ysff/yRlJQUnM6Sbwb37t3rknAi55SWwFEjkKO5jlq73qpIu4Z/rbtKKuCqBl4WpxERkVqp9YWw8nmzsUVoK6vTiNQ7lSqubrvtNpYvX86NN95I06ZNsdlq94iB1GJpCeywxQC1t5lFkUBvG9GBNn49VMhVbaxOIyIitVJ0f/itAWyYBxdOszqNSL1TqeLq22+/5euvv2bAgAGuziNSMWkJbPPoiLcDwv1rf5HfvpGD1Qe17kpERCrJ4QWxQ2DDfBj6T/DQTAiRmlSpP/WHhITQsGFDV2cRqbi0/WyztSCqgR17HRhB7dDIzsFMg0StuxIRkcpqPRKyjsLO7859roi4VKWKq6eeeorHH3+crKwsV+cRqZjj8WzLb0ZULW9mUaR9Iwc2tN+ViIhUQUgLCGsH6+danUSk3qnUtMAXXniBPXv2EB4eTosWLfD09Czx9T/++MMl4UTOpeD4QXblBtO7lq+3KhLg9b91V9e0tTqNiIjUWq0uhDX/gbRECI6yOo1IvVGp4uqKK65wcQyRSshOY2+OP/mGnea1fI+rUxWtuzIMQ81iRESkcmIGwbq3YcP7MHSK1WlE6o1KFVdPPPGEq3OIVFxaAtuM5kDt7xR4qg6hdr7dV0DiCYPmdWS6o4iI1DBPX2gxEOLeh8H/B/a68++kiDur9G9aWloab7/9NlOmTCE1NRUwpwMePHjQZeFEziotge3O5oT6GAR41Z0iROuuRETEJVpdCOkHIH6F1UlE6o1KFVd//vknbdq0YcaMGTz//POkpaUB8NlnnzFlioaepYakJbCNFkQFOqxO4lL+njZigmysOVRodRQREanNwtpBUJQ5NVBEakSliqvJkyczfvx4du3ahY+PT/HxUaNGsWKF/joiNSQtgW1Gizo1JbDIqeuuREREKsVmg5bDYduXkJ1mdRqReqFS70p///13Jk6cWOp4REQEycnJVQ4lUh7HjyZx2BlUJ4urDqEODmcZxGdovysREamClkOhMB+2fGp1EpF6oVLvSn18fMjIyCh1fMeOHYSFhVU5lEh5bD+aC0B0HSyu2jW0Ywd+1dRAERGpCr9GENET/njP6iQi9UKl3pVefvnlTJs2jfz8fABsNhsJCQk8/PDDXHXVVS4NKHIm29O98LQ5aeJfd5pZFPHztBEbbGeNmlqIiEhVtboADv0BKdutTiJS51WquHr++ec5cuQIjRs3Jjs7m8GDB9OqVSsaNGjAM8884+qMIqVlH2dnfhiRvnk47HWvuAJo38jO6oOFWnclIiJVE3keeAeabdlFpFpVap+rwMBAVq1axbJly1i/fj1Op5MePXpwwQUXuDqfSNnSEtjujCIioG4WVgAdGjlYvKeAPWlOWoXUrY6IIiJSgxyeEDsE4hbA8CfMz0WkWlS4uHI6ncydO5dPP/2U+Ph4bDYbMTExNGnSBMMwsNnq7ptdcR/G8QR2GpFcFuRldZRq07aRHbsNfk0qVHElIiJV0+oCs2vg7h+g7Sir04jUWRWaFmgYBpdddhm33XYbBw8epHPnznTs2JH9+/czfvx4xowZU105RUo4lHSQk/gSGextdZRq4+tho2WwnTUHte5KRESqqGGseYv7wOokInVahUau5s6dy4oVK/jxxx8ZOnRoia/99NNPXHHFFcybN4+bbrrJpSFFTrczKQ2IIqoOdgo8VYdGdlYeKMRpGNg1KiwiIlUROww2zIOsVPBraHUakTqpQu9MFyxYwCOPPFKqsAIYNmwYDz/8MPPnz3dZOJEz2XksD19bPqG+dbvg6BTqIDXHYGeq9rsSEZEqih0MzkLY/InVSUTqrAoVV3/++ScXXXTRGb8+atQoNm7cWOVQIueyI8OTKK+TdX6NX5uGdjzt8IumBoqISFX5hph7XmlqoEi1qVBxlZqaSnh4+Bm/Hh4ezvHjx6scSuSsDIMd2cFE+OVbnaTaeTlstGloV3ElIiKu0XKYuefVkZ1WJxGpkypUXBUWFuLhceZlWg6Hg4ICvQmU6lV4MpXdziZE1uE27Kfq2MjB2qRCCpza70pERKooqg94N4CNGr0SqQ4VamhhGAbjx4/H27vsDm25ubkuCSVyNgn7d5OLF1F1uFPgqTqG2lm0A/48UkiP8EptTSciImJyeEKLgbBxIQx7DOza6kPElSr0Tu3mm28+5znqFCjVbWdCEuBJVKMGVkepES2D7fh6wJqDKq5ERMQFWg6HHd/AvhXQsnSTMhGpvAq9U5szZ0515RApt53J6QTiR1BAI6uj1AiH3Ua7hnZWHSzg7h71Y7RORESqUWgbCIoypwaquBJxqbq9SZDUSTuOFRDpkV7nOwWeqlOog/XJheQUaN2ViIhUkc0GsUNh22LIzbQ6jUidouJKap0dGd5EeGdbHaNGdQxzkOeEPw4XWh1FRETqgtghkJ9tFlgi4jIqrqRWyStwsi8vkCi/+tWVMqqBjUAvWK2W7CIi4goBjaFJZ9i4wOokInWKiiupVeKPZFCAg6jA+vWja7fZ6BDqYJWKKxERcZXYoWZTi4xDVicRqTPq1ztUqfV2xCcCEBniY3GSmtexkZ1NR5ycyNO6KxERcYHoAWZr9j8XWZ1EpM5QcSW1ys7EwzQkg4AGwVZHqXGdwxwUGvDrIY1eiYiIC3j5Q1Rf2PghGPrDnYgrWF5czZo1i5iYGHx8fOjZsycrV64847lJSUmMGzeOtm3bYrfbmTRpUqlz5s6di81mK3XLycmpxmchNWXH4UwibUfAN8TqKDUu3N9OuJ+NlQdUXImIiIu0HApHtkHyJquTiNQJlhZXCxcuZNKkSTz66KNs2LCBgQMHMmrUKBISEso8Pzc3l7CwMB599FG6du16xusGBgaSlJRU4ubjU/+mkdVF21OdRHqkm9MY6qHOYQ6WJ6q4EhERF2nWHXyCzdErEakyS4urF198kQkTJnDbbbfRvn17Zs6cSVRUFK+//nqZ57do0YKXX36Zm266iaCgoDNe12az0aRJkxK3s8nNzSUjI6PETdxPTn4hB7K9iPTJtTqKZbqE2dmfYZB4wml1FBERqQvsHhAzEDYtgkL98U6kqiwrrvLy8li/fj0jRowocXzEiBGsXr26StfOzMwkOjqayMhILrnkEjZs2HDW86dPn05QUFDxLSoqqkqPL9Vjz5FMnNiI8K+/ez11CHVgt8EqTQ0UERFXiR0GJ4/A3p+tTiJS61lWXB09epTCwkLCw8NLHA8PDyc5ObnS123Xrh1z587lyy+/ZMGCBfj4+DBgwAB27dp1xvtMmTKF9PT04ltiYmKlH1+qz67D5i7ykQ0cFiexjr+njVbBdlZoaqCIiLhKo1YQFAV/LrQ6iUit52F1AJvNVuJzwzBKHauIvn370rdv3+LPBwwYQI8ePXj11Vd55ZVXyryPt7c33t7elX5MqRk7k44TSjp+AWeeElofdA6z8318AYVOA4e98r8rIiIiANhsEDsENn8MuZngHWB1IpFay7KRq9DQUBwOR6lRqpSUlFKjWVVht9vp3bv3WUeupHbYdfAoEbYj4NfQ6iiW6hLm4EQe/Hmk/k6PFBERF4sdAvnZsP1rq5OI1GqWFVdeXl707NmTpUuXlji+dOlS+vfv77LHMQyDuLg4mjZt6rJrijV2pJw0iyvf+l1ctQy24+cBKw+ouBIRERcJCIfwTpoaKFJFlnYLnDx5Mm+//TbvvPMO27Zt44EHHiAhIYE777wTMNdC3XTTTSXuExcXR1xcHJmZmRw5coS4uDi2bt1a/PWpU6eyZMkS9u7dS1xcHBMmTCAuLq74mlI75eQXknjCINJ+DLwDrY5jKYfdRsdQh/a7EhER14odAnuXwYnDVicRqbUsXXM1duxYjh07xrRp00hKSqJTp0588803REdHA+amwafvedW9e/fi/16/fj0ffPAB0dHRxMfHA5CWlsYdd9xBcnIyQUFBdO/enRUrVnDeeefV2PMS19udkomBjUjvXLBbvve15TqH2Zm3OZ8TeQYNvLTuSkREXCD6fFg7GzZ/Av3usjqNSK1kMwzDsDqEu8nIyCAoKIj09HQCA+v3KIm7+HzDQSYtjOO/jT/Cr8/NVsex3OGTTib9lMNbI325sEX93FBZRESqwbJnIO8k3LnS6iQibqMitYGGAKRW2Hn4BKH2TPz8G1gdxS2E+9tp4m/jZ7VkFxERV4odCsl/Qsp2q5OI1EoqrqRW2Hn4hDoFnqZrYwc/7S9Ag88iIuIykb3BKwA2LbI6iUitpOJKaoWdyelEGMngG2J1FLfRrbGDpJMGu447rY4iIiJ1hcMTWpxvdg106t8XkYpScSVuLye/kMTjuUSqDXsJHRrZ8XbATwmaGigiIi4UMwTSD0DiWquTiNQ6Kq7E7ZmdAiEKTQs8lZfDRsdQO8tUXImIiCuFd4CAxtrzSqQSVFyJ29uVcgKAZh4nwNPP4jTupVtjB+uSC8nI1borERFxEZsdYgbDlk+hIM/qNCK1ioorcXs7D2cS6pmLX0ADsGlPp1N1b+yg0EAbCouIiGvFDIGcdNi91OokIrWKiitxe7sOnyDSka5mFmUI9bPTvIFNUwNFRMS1QqKhYUv4U10DRSpCxZW4vZ2HM4kgGfwaWR3FLXVt7GBZQgFOtWQXERFXihkMO74xR7BEpFxUXIlby84rJDE1i4j8BHUKPIPu4Q6O5RhsPqqWuSIi4kIxg6AwH7YttjqJSK2h4krc2p4jRZ0CD6tT4Bm0DrHj7wk/7dfUQBERcSH/UGjaFTaqa6BIeam4Ere287DZKTDCdlTTAs/Aw26jc5iDH/fnWx1FRETqmpjBEL8SMg5ZnUSkVlBxJW5tV0omYd6F+DoKwCfY6jhuq2e4g01HnSSf1NRAERFxoegB4PCETR9bnUSkVlBxJW5t5+ETRHhnmeut7PpxPZPu4Q4cNvh+n6YGioiIC3n5QdR52lBYpJz0blXc2s7kE0TYjqmZxTn4e9ro2MjOd/s0NVBERFwsZigc3gwp26xOIuL2VFyJ28rOK+TA8WwinQfVzKIcejV1sDapkPRctWQXEREXiugB3oHa80qkHFRcidvanWJ2CozM26uRq3Lo2cRBoYEaW4iIiGs5PCG6vzk10Km1vSJno+JK3FZRp8DIwoPqFFgODX3stA6xs0TrrkRExNVih0LGQUj81eokIm5NxZW4rV0pmTT2s+Fjy9e0wHLq1cTB8sQCsvM1NVBERFyocXsICFdjC5FzUHElbmvn4RM08/1ripuKq3Lp3cRBTiGsPKjRKxERcSGbHWIGwZbPoCDX6jQibkvFlbitnYdPEOlxAnwCweFldZxaoWmAncgGNk0NFBER14sZAjnpsGup1UlE3JaKK3FLWXkFZqdAW4pGrSqoV7iDH/bnU+DU1EAREXGhkGho2FJTA0XOQsWVuKXdKZkARBYkqFNgBfVu6kF6Lqw5VGh1FBERqWtiBsPO78wRLBEpRcWVuKVdh83iKiJ7l4qrCooJstHE38bi3WrJLiIiLhYzCArzYeuXVicRcUsqrsQt7Uw5QeMAT3zyjqkNewXZbDb6NXPw7b58cgs1NVBERFzIPxSadtHUQJEzUHElbmlX8gkiAmzmJyquKqx/hAcn8mB5ohpbiIiIi8UMgfhVkH7Q6iQibkfFlbilHYczifDOMT9RQ4sKi2xgp3mgpgaKiEg1iO4PDk/Y/LHVSUTcjoorcTsncws4mJZNpMdx8PQBTz+rI9VK/Zp5sHR/AVnaUFhERFzJyx+iztPUQJEyqLgSt7PnyF+dAo1kc0qgzWZxotqpf4SDnAJYul9TA0VExMVihsLhLXB4q9VJRNyKiitxOzuLOgXmxqtTYBU09rPTOsSuqYEiIuJ6ET3AOxA2LbI6iYhbUXElbmfX4RM0buCNT1aiiqsq6tfMwc+JBaTnamqgiIi4kMMTogfAn4vA6bQ6jYjbUHElbmd78gmiQnzgpNqwV1XfZh4UOuG7fRq9EhERF4sdAhkHIWG11UlE3IaKK3E7Ow6fINKvEAynuZ+GVFqIj43OYXY+2q7iSkREXKxxewhoYo5eiQig4krcTEZOPsnpOUR6njAPqLiqssFRHqw7XMjetEKro4iISF1is0PMYNjyGeTnWJ1GxC2ouBK3suuwWVRFkQIePuAVYHGi2q9XEwcBnvDRDo1eiYiIi8UOgdwM2LXE6iQibkHFlbiVHcmZ2G3QNH+/OWqlNuxV5uWw0T/Cg4935FPgVGMLERFxoeAoaNRae16J/EXFlbiVnYdP0DTIF6/Mg2pm4UJDmntwJNtgeaL2vBIREReLHQI7v4esVKuTiFhOxZW4lR3JJ4gM8TW7D2m9lcvEBNmJCbKxUI0tRETE1WIGmU2otn5udRIRy6m4Erey4/AJIgM9IPs4+Km4cqXBUR78uL+AI1naj0RERFzINwSadYONmhooouJK3MbRzFxST+YR5ZNlHtDIlUsNiPDAboPPdmn0SkREXCx2CCT+CsfjrU4iYikVV+I2dhZ1CrT/NWdba65cKsDLRu8mDhZsy8cw1NhCRERcKKofePjCpo+sTiJiKRVX4jZ2Jp/A02EjPP8geDcAT1+rI9U5F7bwYF+6k5UHtOeViIi4kKcPNO8LGz8E/QFP6jEVV+I2dhzOJCLYF8eJg+CvUavq0LahnRZBNuZszrU6ioiI1DWxQ+DYbjj0h9VJRCyj4krcxo7kDCJC/CDjAPhqvVV1sNlsjGzhybKEQvala/RKRERcqGk38G2oxhZSr6m4ErdgGAY7D2cSFeILGYfUzKIa9Y9wEOgF725WYwsREXEhu8Nsy775YyjUvzFSP6m4EreQlJ5DZm4BUf4G5J1UG/Zq5OWwMSzag4925HEiT/PiRUTEhVoOg6xjsPtHq5OIWELFlbiF4k6BHsfNA1pzVa0ujPYgpwA+3pFndRQREalLQmIgpAX8+aHVSUQsoeJK3MLOwyfw9XTQqCAZsKkNezVr6GunT1MHczfn4VRXJxERcRWbzWxssf1ryEm3Oo1IjVNxJW5hR3ImkSG+2DMOgm8wODytjlTnXRTrwf4Mg+/jC6yOIiIidUnMEHPN1dYvrE4iUuNUXIlb2JGcQUSwL2QcVDOLGtI6xEHHRnZeXZ+rTYVFRMR1/EOhaVdzzyuRekbFlViuoNDJrpRMmjfyg/QDmhJYg65o48mWY05+TtTolYiIuFDsUNj/C6QlWJ1EpEapuBLLxR/LIrfASfMQXziRpE6BNahjIzttQ+y8rNErERFxpeh+4OEDfy6yOolIjVJxJZbbnpwBQJRPljlHW9MCa4zNZuOK1p7EpThZfVCbCouIiIt4+kHzfrBxAeiPd1KPWF5czZo1i5iYGHx8fOjZsycrV64847lJSUmMGzeOtm3bYrfbmTRpUpnnffLJJ3To0AFvb286dOjAZ599Vk3pxRW2J52gob8XgbmHzQMauapRXRvbaRls55U/cq2OIiIidUnLYXBsNxz8w+okIjXG0uJq4cKFTJo0iUcffZQNGzYwcOBARo0aRUJC2fNzc3NzCQsL49FHH6Vr165lnrNmzRrGjh3LjTfeyMaNG7nxxhu59tprWbt2bXU+FamCbckZNG/4VzMLuwN8Q6yOVK+Yo1cerE0q5Lckrb0SEREXadLFXEe9cYHVSURqjM2wcKFFnz596NGjB6+//nrxsfbt23PFFVcwffr0s953yJAhdOvWjZkzZ5Y4PnbsWDIyMvj222+Lj1100UWEhISwYEH5frkzMjIICgoiPT2dwMDA8j8hqZT+//qRns1DGMe3kPgbnD/J6kj1jmEYPLIyh1AfOx9d7ofNZrM6koiI1AXr58DuH+GhneDhbXUakUqpSG1g2chVXl4e69evZ8SIESWOjxgxgtWrV1f6umvWrCl1zZEjR571mrm5uWRkZJS4Sc3IyMnnUFoOzRv5mx2FAsKsjlQv2Ww2rmvvxbrDhSzRvlciIuIqscMgJw12fW91EpEaYVlxdfToUQoLCwkPDy9xPDw8nOTk5EpfNzk5ucLXnD59OkFBQcW3qKioSj++VMyO5BMANG/oB2mJ4K/iyipdwhx0C7Mz/dcc8gq1+FhERFwgJBoatdbUQKk3LG9ocfr0I8MwqjwlqaLXnDJlCunp6cW3xMTEKj2+lN/2pAw87Daa+RZAdir4h5/7TlJtxnXwIvGEwQfb8q2OIiIidUXLobDzezh5zOokItXOsuIqNDQUh8NRakQpJSWl1MhTRTRp0qTC1/T29iYwMLDETWrGtuQTRIT44pF5yDwQ0NjaQPVcVKCdwVEOZq7LJT1Xo1ciIuICLQYBTtj8idVJRKqdZcWVl5cXPXv2ZOnSpSWOL126lP79+1f6uv369St1ze+//75K15Tqsy0pg6gQv792cLdpjys3cE1bL7ILDF5Ta3YREXEF32CI6AVx861OIlLtLJ0WOHnyZN5++23eeecdtm3bxgMPPEBCQgJ33nknYE7Xu+mmm0rcJy4ujri4ODIzMzly5AhxcXFs3bq1+Ov3338/33//PTNmzGD79u3MmDGDH3744Yx7Yol1nE6DHckn/lpvlQB+DcHhaXWsei/Ex8alrTx5Z3Meu45rY2EREXGBlsMgKQ5StludRKRaeVj54GPHjuXYsWNMmzaNpKQkOnXqxDfffEN0dDRgbhp8+p5X3bt3L/7v9evX88EHHxAdHU18fDwA/fv358MPP+Sf//wnjz32GC1btmThwoX06dOnxp6XlM+B49lk5RWaxdWOA+CvKYHu4tKWHqw+UMD/Lc/m48v9sas1u4iIVEXkeeAdCBs/gAunWZ1GpNpYus+Vu9I+VzVjyZZkJr63nlnX9yDkm4kQ1g7ajrI6lvxl69FCnlqTy9MDfbihg5fVcUREpLb79XU4uA4e2AoOS/++L1IhtWKfK5HtSScI9PEg2LMAMo+omYWb6RDqYFhzB//6NYfDJ51WxxERkdqu1QWQeRj2/mx1EpFqo+JKLLMtOYPmDf2wZRwCDE0LdEPXtffCw27jiV9yrI4iIiK1XaNWEBytxhZSp6m4EstsS8ogqmjzYNAGwm4owMvGTR09+W5fAYt3a+8rERGpApsNWg6H7V9B9nGr04hUCxVXYomsvAISjmWZzSzSE8w2rZ4+VseSMvRt5qB/MwdTVmSTmKHpgSIiUgWxQ8BZCJs/tTqJSLVQcSWW2JF8AgP+14ZdUwLdls1mY0IXL/w9bdz7Yxb5heqBIyIileTXECJ6QNwHVicRqRYqrsQSWw5l4LDbzGmB6YmaEujm/Dxt3NPDi01HnMxcr82FRUSkCloON7sGHtlpdRIRl1NxJZbYciidyBBfPCmAjCR1CqwFWoU4uKatJ7M25PHLgQKr44iISG0VdR54N1BjC6mTVFyJJTYfzKBFI3/IOASGUyNXtcSlrTzoEmbnrh+y2J+u9VciIlIJDi+IGQwbF0Ch/lgndYuKK6lx+YVOdiSfoEWjv6YEAgSEWxtKysVus3FPD2/8PWzc8m0WGblafyUiIpVQtOfVnh+tTiLiUiqupMbtOZJJXqHTHLlKSzSnBnj5WR1LyinAy8ZD53mTkuXk7h+yKHCqwBIRkQpq2BIaxsKG96xOIuJSKq6kxm0+mAFA80ZqZlFbNQ2wc38vb1YfLGTa6hwMQwWWiIhUgM1mjl7t+A5OHrU6jYjLqLiSGrflUDpNg3zw8/KAtP1qZlFLdQp1cEtnL+ZtyeeldeogKCIiFRQzxPz45yIrU4i4lIorqXFbDmaY+1s5C82GFhq5qrWGR3swrr0nr/yRx6wNKrBERKQCfALNzoEb3gPNgJA6QsWV1Cin02BrUgYxof5w4iAU5kODJlbHkiq4tJUnV7Xx5N+/5TJnkwosERGpgFYXQspWOLTB6iQiLuFhdQCpXxJSs8jMLTCbWaRuNA8GqLiq7a5q40FeocHU1bkUGnBbF2+rI4mISG3QrDv4hcKG9yGih9VpRKpMI1dSo7YcMptZtAj1h9R48A1Wp8A6wGazcV17T65o5cHTa3KZ/msOTk3xEBGRc7E7oOUw2PQR5GdbnUakylRcSY3aciidhv5eBPl6wvF92t+qDrHZbIxt78XNHT2ZvTGPB5dlk1+oAktERM6h1QWQmwFbv7Q6iUiVqbiSGrXlUAbRjf4aqUrdAw2aWhtIXO6iWE/u7eHF4t0F3PxNFqnZTqsjiYiIOwtsBk26wh/vWp1EpMpUXEmNMQyDTQfTiWnkb/6FKitVzSzqqP4RHkzp683mo4Vc8ulJNh8ttDqSiIi4s9YXwv5f4Ohuq5OIVImKK6kxKSdyST2ZZzazOL7PPKiRqzqrQ6iDZwb64OOwcdXnJ/l0Z57VkURExF1F9wfvBrBhntVJRKpExZXUmC2H0gFoEepnNrNweJodgqTOCvWz88QAb/o2czB5WQ73/5hFeq7WYYmIyGkcXhA7BDbMN7dpEamlVFxJjdlyMAN/bwehAd6Q+lczC7t+BOs6L4eNiV29uKu7F0vjCxj1USa/HiqwOpaIiLibViMg6yjs+NbqJCKVpne2UmM2HkgjNjQAm80Gx/dqf6t6xGazMTDSg38N9iHYx8Z1i7N4YlU2J/I0iiUiIn9pGAOhbdXYQmo1FVdSIwzDYENiGi3D/MFZCGkJamZRD4X52Xm0nzc3dPRk4fZ8hi/M5Lu9+RjaE0tERABaj4DdP0L6AauTiFSKiiupEUnpORzLzKNlWABkHDTnUweqmUV9ZLfZGB3ryfNDfWjewM6dS7MZ/20Wu4+ro6CISL0XMxA8fGDD+1YnEakUFVdSI/48kAZAbFjA/zoFalpgvdbI187k3l5M7uXF9mNORn50kid/yeF4jvbFEhGptzz9zAJr/btQqPW5UvuouJIaEZeYTiN/Lxr6e5nNLHyDwcvP6lhiMZvNRu+mHjw3xIex7TxZuD2PQQsymbUhl6x8TRUUEamX2o6GE4dg91Krk4hUmIorqRFxiWnEhvmbnxR1ChT5i6fDxqWtPHlpmC/9mnnw4u+5DFqQybzNeeQVqsgSEalXGrWCRq1h3TtWJxGpMBVXUu2cToNNB9LM9VZgdgrU5sFShiBvG7d09uKFYT50aGTniV9yGLwgk/e35pGrIktEpP5oMxJ2LTUbYInUIiqupNrtPZrJybxCs7jKzYCsVHUKlLNq7Gfn7929eW6ID7HBdh5baRZZ8zbnkVOgIktEpM6LGQyevvDHPKuTiFSIiiupdnGJ6QDmtMCiZhYauZJyiGhg554eZpHVMtjOk6tzOP+DTN7amMtJrckSEam7PH0hdohZXBXmW51GpNxUXEm1+/NAGhHBvvh5eUBqPDg8wS/U6lhSixQVWc8P8aFTqJ1/rc1lwPxMXlmfS3quiiwRkTqpzUWQeRh2fGt1EpFyU3El1S4uIY3Y0KJmFnvMFux2/ehJxTUNsDOxmzcvDfOhd1MHr/6RS//5J5ixNoej2WrhLiJSpzSMhbB2sG6O1UlEyk3vcKVa5RYUsjUpg5aN/2pmcWQnBEVYG0pqvTA/O7d29uKV4b4Ma+7B3M15nD8/k2mrc0g+qSJLRKTOaHMR7P0JUvdanUSkXFRcSbXannSCAqdhNrPIOwnpByAo0upYUkcE+9gY18Essi5u6cHC7XkM/CCTR1dmc/CEiiwRkVqvxUDwDoTf/2t1EpFyUXEl1WrjgTQ87DaiG/lB6m7AgEAVV+JaAV42rm5rFllXtvHky935DP4wk0dWZHNARZaISO3l4Q2tLoAN70FeltVpRM5JxZVUq7jENKIb+eHpsMORXeDwBv8wq2NJHeXnaeOK1p68PNyXa9p68tWefIZ8mMljK7M1XVBEpLZqOxpyMmDzJ1YnETknFVdSreIS0ogJ/Wu91bGdENRMzSyk2vl62LislVlkXd3Gk8925TPog0yeWp3DMTW+EBGpXRo0gche8NubYKhDrLg3vcuVanP8ZB57j56kTXhRM4sdEBRlbSipV3w8bFz+10jWpa08WbDNXJM1c10umXn6B1pEpNZoOxqS/4QD66xOInJWKq6k2qzffxyAdk0aQHYanDyqToFiCT9PG1e39WTmcF+GNvfgtQ25DFqQybub88gvVJElIuL2InqaI1i/v2l1EpGzUnEl1eb3/ak08vciNMDbnBIIamYhlmrgZeOGjl68ONSHLmF2nvwlhwsXZfLdvnwMTTUREXFfNju0GQVbPofMI1anETkjFVdSbX7fl0qb8AbYbDY4uhO8/ME3xOpYIoT6mZsRTx/sQ5C3jTu/z+aaL7L480ih1dFERORMWl1oftwwz9ocImeh4kqqRU5+IZsOptMmvIF54MhOc38rm83aYCKniA6083BfH6b08SYly8lln57kwWVZHFZnQRER9+MTCDGD4be3oTDf6jQiZVJxJdVi08F08gsN2jZpABhwdJc2Dxa31aWxg2cH+XBrZ0+Wxhcw5MNMXvsjl5wCTRUUEXEr7S+DE4dg25dWJxEpk4orqRa/x6fi6+mgeUM/yDwMuRlabyVuzWG3cWELT14cZja9eHFdLhcuymSJ1mOJiLiPhjHQpCv8+rrVSUTKpOJKqsXv+1JpHR6Aw24zpwSCOgVKreDvaePGjl7MGOxDQx8bE7/P5savs/5/e3ceXlV1t338u/cZk5A5ISGQQJgDAZQwGBSEqohUq9anpW+tQx15FKvk1TrbRzvQuThB9dVKbavQPpSKFVGsAjIpIBEERFAgEDIQhoxkOOfs94+dBCODDIGd5Nyf69pXyMo6h1+4DpD7rLV/i20HdD+WiEibkPUt2L0adq91uhKRIyhcSasLhSzW7Dxw+H6rfVvtRha+aGcLEzkJXaNN7h/p497hXrYeCHHpP6r5+cpaKnU+loiIs7oNg+gu8IFWr6TtUbiSVrdtbxWVtQH6NYWrss+0aiXtkmEY5KS6+fVYP9f09fDyxnrGza7in5/Va6ugiIhTTBf0vxw2zoOKPU5XI9KCwpW0utU79mMa0LtzJ7CCULZNzSykXfO6DK7u6+G3Y/30jjPJe6+W/3qtho1l2iooIuKI3peAywurX3C6EpEWFK6k1a3ZcYCeSVH4PS44UACBWohNd7oskdOWFGly9zAfD+farduv+Gc1j7x/iAO1at0uInJWeSOh98Ww5k/QcMjpakSaKVxJq/tw+376NG0JLPnEXr5XuJIOJDvJbt1+7QAP87Y2cOGrVfxlYz2BkLYKioicNVnfgtpyyH/F6UpEmilcSasqLq+l8OChxvOtsMNVbDq4PM4WJtLK3KbBxJ4efjcugpxUF48tq+Wb/1vNisKA06WJiISH6FTIyIUVT0NI27SlbVC4kla16ot9AI3NLCw7XMX3cLQmkTMp1mdw2xAfPx3twwK+/+8abn+rhoIKbRUUETnjBn4bDmyHT99wuhIRoA2EqxkzZpCZmYnf7ycnJ4f333//uPOXLFlCTk4Ofr+fnj178sc//rHF12fNmoVhGEdctbW1Z/LbkEbLtpXRPTGSuEgvlO+BQwchPtPpskTOuF5xLv7nfB9TzvWypiTIRXOq+MXKWsrrtFVQROSMSe4HKdmw/ElQF1dpAxwNV3PmzOGee+7h4YcfZt26dYwePZrLLruMgoKCo87fvn07EydOZPTo0axbt46HHnqIH/3oR8ydO7fFvJiYGIqKilpcfr//bHxLYc2yLJZtLWNgWqw9UPIJGCbEZThbmMhZYhgG53dz87uxfq7sY7duv/DVKmZ9Uk9DUP/pi4icEQO/DYVroGCV05WIOBuufv/733PzzTdzyy23kJWVxfTp00lPT2fmzKMfCvfHP/6RjIwMpk+fTlZWFrfccgs33XQTv/3tb1vMMwyD1NTUFpecedvLqimuqCU7LcYeKPkEYtLAo2Ar4cXnNrimr4fffyOCc1NMHl9ey0Vzqnh9WwMhvbMqItK6ug2z38hd/qTTlYg4F67q6+tZu3Yt48ePbzE+fvx4VqxYcdTHrFy58oj5l156KWvWrKGhoaF5rKqqiu7du9OtWzcuv/xy1q1bd9xa6urqqKioaHHJyVu+rQyXaZDVpSlcbYD47s4WJeKgeL99P9YvL/STFGFw138OccXcat7fHdAhxCIircUwYcBV8NmbsPczp6uRMOdYuCorKyMYDJKSktJiPCUlheLi4qM+pri4+KjzA4EAZWVlAPTv359Zs2Yxf/58Xn31Vfx+P+effz5bt249Zi3Tpk0jNja2+UpPV9vwU7FsWxl9UzrZ51tVlUDVXt1vJQJkxJjcN9LPT0b5aAjBdW/UMGl+DR/sUWdBEZFW0XMcRCbCiqecrkTCnOMNLQzDaPG5ZVlHjH3d/C+Pn3feefzgBz9gyJAhjB49mr///e/07duXp59++pjP+eCDD1JeXt587dq161S/nbAVDFms+HwfA7o03W+1yf6oToEizfon2k0v7hvhY++hEJNer+Haf1fzYZFClojIaXF57HOvPp4N5budrkbCmGPhKikpCZfLdcQqVWlp6RGrU01SU1OPOt/tdpOYmHjUx5imyfDhw4+7cuXz+YiJiWlxycn5pLCcytoAg7o2hqvST6BTCnijnC1MpI0xDIOhKS5+PtrP1GFedlWG+O78GibNr2a5tguKiJy6fpeBJwKWa/VKnONYuPJ6veTk5LBo0aIW44sWLWLUqFFHfUxubu4R899++22GDRuGx3P0Q2otyyI/P58uXbq0TuFyVMu2lRHhcdGrc2OYKtb5ViLHYxgGI7q4mTbGT94wL3trQlz7Rg1X/auahV80EAwpZImInBRPJGRdAR/NgsoSp6uRMOXotsC8vDxeeOEF/vSnP7F582amTp1KQUEBkydPBuztetdff33z/MmTJ7Nz507y8vLYvHkzf/rTn3jxxRe59957m+c8/vjjvPXWW3zxxRfk5+dz8803k5+f3/yccmYs21pGVpdo3KZpn21Vvlv3W4mcANMwGN7Fzc9G+7l/hI+GIExedIiL/l7FK5vqqQ0oZImInLCsK8B0w8pnnK5EwpTbyd980qRJ7Nu3jyeeeIKioiKys7NZsGAB3bvbHeaKiopanHmVmZnJggULmDp1Ks8++yxpaWk89dRTXHPNNc1zDh48yG233UZxcTGxsbGce+65LF26lBEjRpz17y9c1DYEWbvzAJOGNzYCKd1of9TKlcgJMwyDc1JcnJPiYtuBIK9vC/Dw+7X8+sM6rh3g4bqBXlKjHL9NVkSkbfN2gn7fhNUvwAVTITLB6YokzBiWNvgfoaKigtjYWMrLy3X/1QlYtrWMH7z4Ab++ZjDpCZHwwR9h5woYc+/XP1hEjqmkOsRb2wMs3hWgPggTMt1cN9DLyC6u4zb+EREJa7XlMPdmGPUj+MbDTlcjHcDJZAO9DSqn7f1te4mL9NAtPsIeKFwLib2cLUqkA0iJMrk+28szF0fwgwEe1pUG+d7rNYz/RzV//qSe8jq9NyYicgR/LPS91H6zt7bc6WokzChcyWl7Z1MJQ7rF2e+kV+6Bij2Q1NfpskQ6jEiPwYSeHn471s/D5/mI9xk8saKWEX+pZOq79nlZ2oQgIvIlA78NgVpYNdPpSiTMOHrPlbR/28uq+XxvNVee09Ue2L0WTJdWrkTOAMMwyE52kZ3s4mCtxZJd9pbBeVtryIg2+E5/L9/u46FrtN43E5EwF5kI/SbajS1G3KZ7r+Ss0f/Aclr+s7kEj8s4fL7V7tV2Iwu339G6RDq6OL/BlX08/G6cn8dG+ciMM3n2ozoueKWKSfOrmb1Z2wZFJMxl/xcEA7BC517J2aNwJadl0aYSBnWNxe9xQbAOitdDUj+nyxIJG6ZhkJXoYvI5PmaOj+D2c7wcClg89H4tw1+u5Pa3anjj8wYONShoiUiYiYizW7N/8EeoKnW6GgkTCldyyg5U17NmxwGGZsTbA8UbINgAyQpXIk7wuw0uTHfz4Hl+nr7Yz3f6e9h2MMSd7xxi6MuV/OidGhZub9DZWSISPgZ+GwwXLPuD05VImNA9V3LKFn9WStCyOLcpXO1eAxHxEJXsbGEiQoLf5PJeJpf38lBcHWJlYZBVRQHmfx4gwg0XZbi5NNPDuAw3nbxq6y4iHZSvEwy40j73KncKxHZ1uiLp4BSu5JQt2lRC7+QoEqK89sDuNXaXQJ2/I9KmpEaZXN3X5Oq+HvZUhfhgT5DVxQH+/UUAjwnnd3UxvoeHi7q7SdFBxSLS0Qy4Eja/Dkt/DVc86XQ10sEpXMkpqQsEWbJlLxMHdbEHKgqhsgh6X+JsYSJyXGmdDgetvTUh1hQHWVMc5JH3a3nofchOMrm4u4exGW4GJZm4TL1ZIiLtnCcSBn0H1s6C8+7Q7QtyRilcySn54Iv9VNcHyenetCVwLZhuSOzpbGEicsKSI00u62lyWU8PVfUW+aVBPioJ8v/W1zF9bR3xPoMx6S5Gd3NzQTc3qVrVEpH2qv/lsOUNWPQYfH+O09VIB6ZwJafknc0lJEf7yEiItAcKV0NCJrh9zhYmIqekk9fggsYQFQxZbD0Q4uO9QdaXBpm/LYAF9IozuaCri/PS3Izs4iIhQmFLRNoJlweG3gBLfgXbl0LmGKcrkg5K4UpOWihk8fbGEoZmxGMYhn0CevEG6D3e6dJEpBW4TIP+iS76J7qY1B8q6iw27guyYW+Qt3YE+PPGBgD6xpsM7+JiWIqLYaluukUb9r8JIiJtUfcLIPk1eOthuG0JmHqDSFqfwpWctA937Ke4opbJPRPtgd1r7Bbsnfs7W5iInBExPoPcNDe5afZ/GWU1ITbvC7F5f5DFBQH+tskOW4kRBuckm5yb4mZIZxcDE02tbolI22EYMOwmePPHsOEfMGSS0xVJB6RwJSftX+sK6Rzto29KJ3tg+xK7tWlUkrOFichZkRRpMjrSZHS6/V9IZb3FZ/uDbDsY4vMDIWasq6MmYM/tEmWQneQiK9EkK9FF/0STjGg1yhARh3QeAN3Ph/88DgO+BZ4IpyuSDkbhSk5KbUOQN9YXcVFWir39p74adq9Wl0CRMBbtNchJdZOTan8esixKqi22l4fYXh5iR3mID4sDlNfZX/ea0DPOpF+CSa84Fz3jTHrGmWTGmER4FLpE5AwbegO8dgcsfxLGPuB0NdLBKFzJSVm8pZTKugAX9G5cpSpYZW8JTB3kbGEi0maYhkGXTgZdOpmM+tJ5nQfrLAoqQhRWhiistPh0f4j3CgJU1B+ekxJp0D3GpEesSfcYk4zmyyDOp3u6RKQVxKTBwKvh/d/B4O9CgjodS+tRuJKTMm9dIT2To+ga37iMvn0xJPSAiDgHqxKR9iDOZxCX7GJwsqvFeGW9RVFViKJqi5LqEMXVFmuLgyz4ooGqhsPzojzQLdreVpgeY5IebZDe/GuTSK16iciJGjTJvq1hwY/h2n/Y92OJtAKFKzlh5TUNvPtpKd8bnmEP1JbDnnzIusLRukSkfYv2GkQnuOibcOTXquotSmss9taEKK2xGq8QG/cFKa2xCIQOz03wG2TEGPSIcZERY5AeY9KjcRUsKUKrXiLyJR4/DLsFFv8CtiyA/t90uiLpIBSu5IQt+KSIYMgit1djl8Cdy+2P2hIoImdIJ69BJ69Bz7gjuw6GLIuDtU3hy6L0kEVpdYgt+4Ms3W2xv9Zqnhvphh6xJpmxjfd3xR6+3yvaq9AlEpYycqHrMLt7YM9x4I10uiLpABSu5ITN+6iQ7K6xxEd67YEvlkBib/BGOVuYiIQl0zBIiDBIiID+iUd+vT5oN9YobtxqWFxtN9dYuSfYInglRxj0STDpG++id7xJnziTvgkm8X61kRfp0AwDRtwG86fY919d9KjTFUkHoHAlJ2T3gRo+3LGf/76wlz1QvRdKNsKga5wtTETkGLwug/TG7YFfdShgUVRlsacqxJ6qEIVVFu/sbOAvGy2CjbkrKcKgb4JJ/wQX/RNM+ie66BOnjoYiHUpMGmRfA8unw8CrtBtHTpvClZyQVz8sIMLjYniPxpsidiwDlxs6D3S2MBGRUxDhNugZd+R2w0DIDl27K0Psrgyxq9JiwRcNvLTBwgJMAzJiDAYkuuifYJ/f1T/RRbdOuqdLpN0a9F0oWAn/+m+49T1weZyuSNoxhSv5WrUNQV75oIAL+yUT4XUBFmxdBMn97BtCRUQ6CLd59NWu2oDVHLYKKkLsLA/x/u4AlY1t5KM90C/BxYCkxpWuRJN+CS6itMol0va5PDDqblhwLyybDhfe53RF0o4pXMnXev3jPRyoaWD8gBR7oHgDHNwJw292tjARkbPE7zboHe+id/zhMcuym2YUVFjsrAhRUGGf2/XXTQ2ELDCA9BiDrAQX/Rq3FfZLsDsYukyFLpE2JakPZH8blvzK7hyYMsDpiqSdUriS47Isi5eW7+Dc9Di6xDaebbX5deiUAgm9nC1ORMRBhmGQGGGQGAHnphw+u6s+aFFYaVFQaQeuXRUhPigKcLDO/rrXhF7x9gpXn3iTPvF2M41u0YZCl4iThnwfdn0I/5oMt7xr3/4gcpL0qpHjWrvzAJuKKrh/Qn97oKoUClZB1rd04J6IyFF4XQaZcQaZX7mfq7zOYldF071cITaWBXlrewM1AfvrPhdkxtphq3e8i56xJr3iTTJj1ERD5KxweWDUj+DN+2Dpb2Dcg05XJO2QwpUc10vLd5AW62dwt1h7YMsCcHsh7RxH6xIRaW9ifQaxyS6ykw+vclmWxYFai92VFoWNXQu3HQyxdHeA8rrDj+0SZdAr7vAZXZmxLjJjTbpGG7i12iXSepL7weDvwdJfQ+Zo6HGB0xVJO6NwJcdUXF7Lwk+K+cF53TENA4J18NlCSMsBt8/p8kRE2j3jS2d1De7savG1qvqmVvEWRdUhiqss3isI8Gq1RUPInuM2IT3aJDPWsANXnL3S1SPWpEsnw/63W0ROzuBJULIB5t4Ck5dD1FEO0hM5BoUrOaaXV+7A6zYZ0zfJHti+FOoqIeM8ZwsTEQkDnbwGfRNc9E1oOR6yLPYdsiiqtiiuClFUbVFSHWLzvgZKaixCjed0+VyQEW2vdvWI/fKql0lShFrHixyT6YIL/i+8/iO7Pfv35+hWCDlhCldyVPuq6pi1YgcXZ3Um0usGLNg0314uj0pyujwRkbBlGgbJkQbJkTA4ueVqVyBkUXbIorjKorjaDl5F1SHWlQbZW2Of1QV26/jMOJNeca7m7Ya9GkOYz6UfIkWISoILpsJ/HodVMyH3DqcrknZC4UqOaubizwG4YkiaPVC8AfZ/ATk3OleUiIgcl9s0SI0ySI0CaBm86oMWpTUWRY2rXXuqQmwqC/LOzobm87pMA7pFG/SJMxtbz5v0iXfRO86kk1ehS8JMt+Ew4CpY9Ch0Gaz7r+SEKFzJEYrLa3l55U6uGJJGtN8DWLB2FsR2g6S+TpcnIiKnwOsy6BZt0C26ZRdDy7KorIc9jQ019lSF2FMZYkNZA6U1VvO81CiDfgl22Orb2EK+T7xLoUs6tpwb4cB2mPMDuG0xxPdwuCBp6xSu5AhPv7sVn8dk4qBUe6BgFezdYh8arD3HIiIdimEYxPggxuei/1fu268NWOypsiisDLG7KkRhpcW/P2+gpPrwFsOm0NU33j63q2/j+V1Rah8vHYHphgsfgDf+L7zyPbhlEfiina5K2jCFK2mhYF8Ns1fvYtKwdPteKysIa/9sn1ye2Nvp8kRE5Czyuw16xhn0/MqZXXWNoWt3Y+jaXRli/ja7oUaTtE4G/Zq2FTaGrl5xJtFa6ZL2xhcN33gEFtwLc2+F770Cpvn1j5OwpHAlLUx/5zNi/G7GD0yxBz5/D8p3Qe6dzhYmIiJths999IOSawP2eV27KxtXuypDvPaV0JUSaTTfy9UrzqR3vN1MI1kdDKUti8uAMffBf56Atx6CCdO0m0eOSuFKmq3ZsZ956wr54fk98LldEKyHdX+B1EH2/VYiIiLH4XcbjR0IW443by9svJ+rsMpi0Y4GXq4+3Dq+k4fGroWu5pbxmY3t47XFUNqEbsNh5H/DBzMgIh7G3u90RdIGKVwJAHWBIPfPXU/vzp24qH/jqtWWBVCzH8693tniRESkXTvW9sJAyKKksXPhlzsY/mdnAxX1h+clRxjNYatHrEmPGJPusSbdYxS85CzrPxHqq2DxL8AfA+f9t9MVSRujcCUAzHjvc3bsq2Ha1YMwTQOqSmDdX+13aTolO12eiIh0QG7ToGu0QdfoI+9fqapvPKvrS2d2rSkK8vq2BmoCh+clRRjNYatHY+DqHmP/Otan4CVnwKDv2AFr4QPgj4Vzvu90RdKGKFwJn5VU8ux727hySBrpCZFghWDZk+D2Q98JTpcnIiJhqJPXoLfXRe/4luNNreOLq0OU1FiUVIcorrZYvzfIoh0tV7zifAbdYwx6xrnsFa9Yk56NWw7VQl5OmWFAzg+hoRpeuxOCDZBzg9NVSRuhcBXmgiGLH//velJi/Fx1bld78NM3oPhjGHYzePzOFigiIvIlX24d3zfhyK9XN9hbDUsaV7uKq+2thu8WNFBed3hecoTReI9X02V3NUzrZGCqUYF8HcOA8+4Eww2v/whqD8L5dztdlbQBCldh7ul3t5K/6yA/uWIAHpcJFYWw9iXIOA+S1HpdRETalyjP0e/vAjt4NW01LKoOsafKYkVhgP/dYlEfsudEuLFbx8e7ms/v6pdgkhqlbobyFYYJIyeDtxMsegwOHYSLHlMXwTCncBXG3t5YzPR3tvKdnG70T42xz7R6/w/gjdZ2QBER6XCiPEfvZhiyLMoOWRRWNrWSD/FxaZA3Pm+gNmjPifFCVqKr8TIZkGgflux36wfpsGYYMPQ68EXBst9DZRFcPl07f8KYwlWY2lpSyT1z8hnRI+HwdsA1L8HeT2HEbeD2OVugiIjIWWIaBp0jDTpHwrkprubxptBVUBFiV4VFQWWIRTsa+PMnFhbgMqBXnEl2souBiSbZSS4GJLl0UHI4Gvhtuz37iqftn6Um/Q1iuzpdlTjAsCzL+vpp4aWiooLY2FjKy8uJiYlxupxWV36ogSufWUYwZPH4t7KJ8Lpg02vw4fOQdQV0H+V0iSIiIm1WbcBid2WIHeUhdlRY7CwPsbMiREMIDKB7rMGQZBeDkl1kJ9mXGmiEiX3b4L1f2M3BJv0Vuuc6XZG0gpPJBgpXR9GRw1V1XYCbZq3mkz3l/OzKQaTG+mHncnhvGmSOhn6XOV2iiIhIuxMMWRRWWWwvD/HFQTt47awIURe0A1ePWLMxcJkMSnYxMMmlM7o6qkMHYemvoGQTjLkPxtwLLo/TVclpULg6TR01XFXWNnDjS6vZtKeC+yf0p19qNJRugrceguQBMOS79s2ZIiIictqCIYs9VRZflIf4vClwlYeob1zh6hlnB67sZJNBjVsKFbg6iFAA1s+B9X+H1Gy4+nno3N/pquQUKVydpo4YrsprGrj+Tx+wrbSKBy7rT+/O0VC4FhZPg+hU+7wGvasiIiJyRgVCFrsrj1zhatpS2CPWJDvJvn9rYJLdPCMxQm98tltlW+1GF1UlcOGPIfcuNbtohxSuTlNHC1e79tdw21/WsHv/IR6cmEVmUhR8thBWPgtJfWHIJPvAYBERETnrAiG7U+H28hDbG8PWzvJQc6fCzpEGWYkmWYku+sWb9Et00SvOxOfSKle7EKiD/L/B5tcgOg0u/TlkfUst29sRhavT1JHC1cJPirnvHx8T6XMx9eK+dE+IgI/+DBv+1z7Lqv8VYOodMRERkbYkZNmHITcFrZ0VIXZXWuw9ZP/Y5jIgI8akb7xJn3j7IOSecS56xpnqVthWle+GNS/C7tXQ/XwY+yD0uEAhqx1QuDpNHSFc1TYE+dXCT3lp+Q5G9EjgtjE9iaotguVPQelmu3GF/kKLiIi0KzUNdqfCgooQhVUWeypD7K6y2F97+Me5pAiDHjEmmXEmPWJM0mNM0qMNMmJMEvw6DNlxhWvtN7r3fwHdRthNL/pcop/J2jCFq9PUnsOVZVks2FDMLxZspqSilmtHdufSrESMjXPh49ngj4UBV0NiT6dLFRERkVZyKGBRVGWxpypEcXWI4mp75au4OkRVw+F5fjekRZl0izboGm3SJcokNcqgSyeTlEiDlCiTGC8KYGeaZdkrWBv+bp+LldQPcm6AIf8HIhOcrk6+QuHqNLXHcGVZFmt3HuCXb37Kmp0HyMmI5/vDu5J24EO7W03FHugxGnpfpMYVIiIiYaSmwaK0xqK0JkRZjb21sOyQxf5DIfbXWhysaznf77JXv5Ibw1ZShEFShElihEFihEGC//DHOJ+By1QQO2WWBcUb4LMFULDK7trc/3LI/jb0ugi8kU5XKChcnbb2FK5qG4K8/vEeZq3YwcY9FWQkRHBtTgqDD62GjXOhai8k94c+4yGmi9PlioiISBvTELQaQ5bFgVr71+V1FgcbP5bXWVTUw8E6i9BXfmo0gFifQbzfIN4PCX6TuMbP4xrDV3zjx1if/THObxDp1urYEWrL4fP/wOfvwoEd4ImA3pdA3wnQ80KI7eZ0hWGrXYWrGTNm8Jvf/IaioiIGDhzI9OnTGT169DHnL1myhLy8PDZu3EhaWho//vGPmTx5cos5c+fO5dFHH+Xzzz+nV69e/PznP+fqq68+4ZraeriqqQ+w9LMy3t5UzDubSqioDXBO12guTd7P4IrFmHvWQigIXQZDjzEKVSIiInLaQpZFdQNU1FlU1ltU1FtU1kNlvdV8VdXbc6rqLaoaLKrqIXSU53KbNIetWC92EPObxHoPh7JYn0Gsj8aP9liM18ATDl0SywuhYCUUrLDbuWNBfCZkjoFuw6HrUHsrocvtdKVhod2Eqzlz5nDdddcxY8YMzj//fJ577jleeOEFNm3aREZGxhHzt2/fTnZ2Nrfeeiu33347y5cv54477uDVV1/lmmuuAWDlypWMHj2an/70p1x99dXMmzePxx57jGXLljFy5MgTqquthaua+gArP9/H2p0HWLvzAPm7DlIXCJERDUMj9zLGWk2X8o/tA+viMiBlEKQOgohYp0sXERGRMBayLGoaoLrhcNiyA5hFVYMdzKob7EBW3WBR0zinssEicLRUBkS6Dweu5oD2pSvGaxDTGMyivfbn0Y1j7XLFrLYCSj6Boo+hZCMc3AlY9spW5wGQnAXJ/ewrvgfEpms7YStrN+Fq5MiRDB06lJkzZzaPZWVlcdVVVzFt2rQj5t9///3Mnz+fzZs3N49NnjyZjz/+mJUrVwIwadIkKioqePPNN5vnTJgwgfj4eF599dUTqquthaupc/KZt66QOE+Avq5i+oW2MTT0CanGATtAxfaAhB72X6qIeKfLFRERETktlmVRF6Q5eFV9KYRVNbQMZNX1FocCTXPtcBY4xk+3pgFRHjt0RXsNoj0G0V6I8hp08hhEeQyiPBDlMYhs/HWk28DvNoj0QITbwO8Gv9vA77I/+lzgMc9iaGuogX1fwL7P7O2D5bvh4C4IHDo8JyoZYrpCdKp9dUqFyES7WUZEvH35Y8EXDb4YcPvUrfA4TiYbOLaWWF9fz9q1a3nggQdajI8fP54VK1Yc9TErV65k/PjxLcYuvfRSXnzxRRoaGvB4PKxcuZKpU6ceMWf69OnHrKWuro66usN3c5aXlwP2H2RbsP/gQZK8AS6oXgRApeliiedc+y8EfijHvrbvBHY6WKmIiIjI2RHVeDUzAZ991YdMakJuDgVd1ARdHAqZVIfc1AZd1NS72F3Z3rfTJTVeowAwsBqvxl+XW7AHoCll2l+DOgyKgCKMxq9d41rGve6/4zGCZ7hmuzqML52vajSNfTXYNY4NugYu+h/w+M9wbcfXlAlOZE3KsVdWWVkZwWCQlJSUFuMpKSkUFxcf9THFxcVHnR8IBCgrK6NLly7HnHOs5wSYNm0ajz/++BHj6enpJ/rtnBVrnS5ARERERDqUXzZebdPMxqttqKysJDb2+LfdOB7bv7qEalnWcZdVjzb/q+Mn+5wPPvggeXl5zZ+HQiH2799PYmJi+9uXK8dVUVFBeno6u3btahNbPiU86XUoTtNrUNoCvQ6lLTiR16FlWVRWVpKWlva1z+dYuEpKSsLlch2xolRaWnrEylOT1NTUo853u90kJiYed86xnhPA5/Ph8/lajMXFxZ3otyLtUExMjP4hF8fpdShO02tQ2gK9DqUt+LrX4detWDUxv37KmeH1esnJyWHRokUtxhctWsSoUaOO+pjc3Nwj5r/99tsMGzYMj8dz3DnHek4REREREZHW4Oi2wLy8PK677jqGDRtGbm4uzz//PAUFBc3nVj344IMUFhby8ssvA3ZnwGeeeYa8vDxuvfVWVq5cyYsvvtiiC+Ddd9/NmDFj+NWvfsWVV17Ja6+9xjvvvMOyZcsc+R5FRERERCQ8OBquJk2axL59+3jiiScoKioiOzubBQsW0L17dwCKioooKChonp+ZmcmCBQuYOnUqzz77LGlpaTz11FPNZ1wBjBo1itmzZ/PII4/w6KOP0qtXL+bMmXPCZ1xJx+bz+fjJT35yxDZQkbNJr0Nxml6D0hbodShtQWu/Dh0950pERERERKSjcOyeKxERERERkY5E4UpERERERKQVKFyJiIiIiIi0AoUrERERERGRVqBwJWFjxowZZGZm4vf7ycnJ4f3333e6JAkzS5cu5YorriAtLQ3DMPjXv/7ldEkSZqZNm8bw4cOJjo6mc+fOXHXVVWzZssXpsiTMzJw5k8GDBzcf2pqbm8ubb77pdFkS5qZNm4ZhGNxzzz2n9TwKVxIW5syZwz333MPDDz/MunXrGD16NJdddlmLVv8iZ1p1dTVDhgzhmWeecboUCVNLlizhzjvvZNWqVSxatIhAIMD48eOprq52ujQJI926deOXv/wla9asYc2aNXzjG9/gyiuvZOPGjU6XJmFq9erVPP/88wwePPi0n0ut2CUsjBw5kqFDhzJz5szmsaysLK666iqmTZvmYGUSrgzDYN68eVx11VVOlyJhbO/evXTu3JklS5YwZswYp8uRMJaQkMBvfvMbbr75ZqdLkTBTVVXF0KFDmTFjBj/72c8455xzmD59+ik/n1aupMOrr69n7dq1jB8/vsX4+PHjWbFihUNViYg4r7y8HLB/sBVxQjAYZPbs2VRXV5Obm+t0ORKG7rzzTr75zW9y8cUXt8rzuVvlWUTasLKyMoLBICkpKS3GU1JSKC4udqgqERFnWZZFXl4eF1xwAdnZ2U6XI2Fmw4YN5ObmUltbS6dOnZg3bx4DBgxwuiwJM7Nnz+ajjz5i9erVrfacClcSNgzDaPG5ZVlHjImIhIspU6awfv16li1b5nQpEob69etHfn4+Bw8eZO7cudxwww0sWbJEAUvOml27dnH33Xfz9ttv4/f7W+15Fa6kw0tKSsLlch2xSlVaWnrEapaISDi46667mD9/PkuXLqVbt25OlyNhyOv10rt3bwCGDRvG6tWrefLJJ3nuueccrkzCxdq1ayktLSUnJ6d5LBgMsnTpUp555hnq6upwuVwn/by650o6PK/XS05ODosWLWoxvmjRIkaNGuVQVSIiZ59lWUyZMoV//vOfvPvuu2RmZjpdkghgvzbr6uqcLkPCyEUXXcSGDRvIz89vvoYNG8a1115Lfn7+KQUr0MqVhIm8vDyuu+46hg0bRm5uLs8//zwFBQVMnjzZ6dIkjFRVVbFt27bmz7dv305+fj4JCQlkZGQ4WJmEizvvvJNXXnmF1157jejo6OYV/djYWCIiIhyuTsLFQw89xGWXXUZ6ejqVlZXMnj2bxYsXs3DhQqdLkzASHR19xP2mUVFRJCYmntZ9qApXEhYmTZrEvn37eOKJJygqKiI7O5sFCxbQvXt3p0uTMLJmzRrGjRvX/HleXh4AN9xwA7NmzXKoKgknTcdRjB07tsX4Sy+9xI033nj2C5KwVFJSwnXXXUdRURGxsbEMHjyYhQsXcskllzhdmshp0zlXIiIiIiIirUD3XImIiIiIiLQChSsREREREZFWoHAlIiIiIiLSChSuREREREREWoHClYiIiIiISCtQuBIREREREWkFClciIiIiIiKtQOFKRERERESkFShciYiIiIiItAKFKxERaZduvPFGDMM44powYcIJPX7x4sUYhsHBgwfPbKEiIhI23E4XICIicqomTJjASy+91GLM5/O16u9RX1+P1+tt1ecUEZGOSStXIiLSbvl8PlJTU1tc8fHxABiGwQsvvMDVV19NZGQkffr0Yf78+QDs2LGDcePGARAfH49hGNx4440AjB07lilTppCXl0dSUhKXXHIJAEuWLGHEiBH4fD66dOnCAw88QCAQaK6l6XFTpkwhLi6OxMREHnnkESzLAuCJJ55g0KBBR3wPOTk5PPbYY2fsz0hERM4ehSsREemwHn/8cb773e+yfv16Jk6cyLXXXsv+/ftJT09n7ty5AGzZsoWioiKefPLJ5sf9+c9/xu12s3z5cp577jkKCwuZOHEiw4cP5+OPP2bmzJm8+OKL/OxnP2vx+zU97oMPPuCpp57iD3/4Ay+88AIAN910E5s2bWL16tXN89evX8+6deuag52IiLRvhtX0lpqIiEg7cuONN/LXv/4Vv9/fYvz+++/n0UcfxTAMHnnkEX76058CUF1dTXR0NAsWLGDChAksXryYcePGceDAAeLi4pofP3bsWMrLy1m3bl3z2MMPP8zcuXPZvHkzhmEAMGPGDO6//37Ky8sxTZOxY8dSWlrKxo0bm+c88MADzJ8/n02bNgEwceJEevTowYwZMwCYOnUq+fn5vPfee2fsz0lERM4erVyJiEi7NW7cOPLz81tcd955Z/PXBw8e3PzrqKgooqOjKS0t/drnHTZsWIvPN2/eTG5ubnNoAjj//POpqqpi9+7dzWPnnXdeizm5ubls3bqVYDAIwK233sqrr75KbW0tDQ0N/O1vf+Omm246+W9cRETaJDW0EBGRdisqKorevXsf8+sej6fF54ZhEAqFTuh5v8yyrBahqWms6TlP1BVXXIHP52PevHn4fD7q6uq45pprTvjxIiLStilciYhIWGrqANi0qnQ8AwYMYO7cuS1C1ooVK4iOjqZr167N81atWtXicatWraJPnz64XC4A3G43N9xwAy+99BI+n4/vfe97REZGtta3JCIiDlO4EhGRdquuro7i4uIWY263m6SkpK99bPfu3TEMg3//+99MnDiRiIgIOnXqdNS5d9xxB9OnT+euu+5iypQpbNmyhZ/85Cfk5eVhmod32O/atYu8vDxuv/12PvroI55++ml+97vftXiuW265haysLACWL19+st+yiIi0YQpXIiLSbi1cuJAuXbq0GOvXrx+ffvrp1z62a9euPP744zzwwAP88Ic/5Prrr2fWrFnHnLtgwQLuu+8+hgwZQkJCAjfffDOPPPJIi3nXX389hw4dYsSIEbhcLu666y5uu+22FnP69OnDqFGj2LdvHyNHjjy5b1hERNo0dQsUERFpBWPHjuWcc85h+vTpx51nWRb9+/fn9ttvJy8v7+wUJyIiZ4VWrkRERM6S0tJS/vKXv1BYWMgPf/hDp8sREZFWpnAlIiJylqSkpJCUlMTzzz9PfHy80+WIiEgr07ZAERERERGRVqBDhEVERERERFqBwpWIiIiIiEgrULgSERERERFpBQpXIiIiIiIirUDhSkREREREpBUoXImIiIiIiLQChSsREREREZFWoHAlIiIiIiLSCv4/4IDv+Jmq9cIAAAAASUVORK5CYII=",
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",
+ "text/plain": [
+ "<Figure size 1000x600 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
"text/plain": [
"<Figure size 1000x600 with 1 Axes>"
]
@@ -327,14 +390,61 @@
"import matplotlib.pyplot as plt\n",
"\n",
"# Map true_type to labels\n",
- "df['true_type_label'] = df['true_type'].map({0: 'Known', 1: 'Novel'})\n",
+ "df[\"true_type_label\"] = df[\"true_type\"].map({0: \"Known\", 1: \"Novel\"})\n",
"master_df = df.copy()\n",
"\n",
"plt.figure(figsize=(10, 6))\n",
- "sns.kdeplot(data=df, x='entropy', hue='true_type_label', fill=True)\n",
- "plt.title('KDE Plot of Entropy Scores by True Type')\n",
- "plt.xlabel('Entropy')\n",
- "plt.ylabel('Density')\n",
+ "sns.kdeplot(data=df, x=\"entropy\", hue=\"true_type_label\", fill=True)\n",
+ "plt.title(\"KDE Plot of Entropy Scores by True Type\")\n",
+ "plt.xlabel(\"Entropy\")\n",
+ "plt.ylabel(\"Density\")\n",
+ "plt.show()\n",
+ "\n",
+ "# show a histogram of the entropy scores\n",
+ "plt.figure(figsize=(10, 6))\n",
+ "sns.histplot(data=df, x=\"entropy\", hue=\"true_type_label\", bins=50, kde=True)\n",
+ "plt.title(\"Histogram of Entropy Scores by True Type\")\n",
+ "plt.xlabel(\"Entropy\")\n",
+ "plt.ylabel(\"Density\")\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 178,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/tmp/ipykernel_638333/1464431791.py:4: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
+ " data=df[df[\"true_type\"] == 1][df[\"label\"] == 50],\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 1000x600 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# plot kde of entropy for each of the 10 novel classes\n",
+ "plt.figure(figsize=(10, 6))\n",
+ "sns.kdeplot(\n",
+ " data=df[df[\"true_type\"] == 1][df[\"label\"] == 50],\n",
+ " x=\"entropy\",\n",
+ " hue=\"label\",\n",
+ " fill=True,\n",
+ ")\n",
+ "plt.title(\"KDE Plot of Entropy Scores for Novel Classes\")\n",
+ "plt.xlabel(\"Entropy\")\n",
+ "plt.ylabel(\"Density\")\n",
"plt.show()"
]
},
@@ -347,12 +457,22 @@
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": 179,
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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",
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 1000x600 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
"text/plain": [
"<Figure size 1000x600 with 1 Axes>"
]
@@ -367,26 +487,34 @@
"import matplotlib.pyplot as plt\n",
"\n",
"# Map true_type to labels\n",
- "df['true_type_label'] = df['true_type'].map({0: 'Known', 1: 'Novel'})\n",
+ "df[\"true_type_label\"] = df[\"true_type\"].map({0: \"Known\", 1: \"Novel\"})\n",
"master_df = df.copy()\n",
"\n",
"plt.figure(figsize=(10, 6))\n",
- "sns.kdeplot(data=df, x='energy', hue='true_type_label', fill=True)\n",
- "plt.title('KDE Plot of Energy Scores by True Type')\n",
- "plt.xlabel('Energy')\n",
- "plt.ylabel('Density')\n",
+ "sns.kdeplot(data=df, x=\"energy\", hue=\"true_type_label\", fill=True)\n",
+ "plt.title(\"KDE Plot of Energy Scores by True Type\")\n",
+ "plt.xlabel(\"Energy\")\n",
+ "plt.ylabel(\"Density\")\n",
+ "plt.show()\n",
+ "\n",
+ "# show a histogram of the entropy scores\n",
+ "plt.figure(figsize=(10, 6))\n",
+ "sns.histplot(data=df, x=\"energy\", hue=\"true_type_label\", bins=50, kde=True)\n",
+ "plt.title(\"Histogram of Energy Scores by True Type\")\n",
+ "plt.xlabel(\"Energy\")\n",
+ "plt.ylabel(\"Density\")\n",
"plt.show()"
]
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": 180,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "0299d4800a744441ad923b5d9530a21c",
+ "model_id": "7c41517c8a824b0eb2b048858e48b354",
"version_major": 2,
"version_minor": 0
},
@@ -397,25 +525,11 @@
"metadata": {},
"output_type": "display_data"
},
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "/root/miniconda3/envs/entcl/lib/python3.10/site-packages/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).\n",
- " warnings.warn(\n",
- "/root/miniconda3/envs/entcl/lib/python3.10/site-packages/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).\n",
- " warnings.warn(\n",
- "/root/miniconda3/envs/entcl/lib/python3.10/site-packages/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).\n",
- " warnings.warn(\n",
- "/root/miniconda3/envs/entcl/lib/python3.10/site-packages/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).\n",
- " warnings.warn(\n"
- ]
- },
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Accuracy of the model on the testset: 86.96%\n"
+ "Accuracy of the model on the testset: 89.00%\n"
]
}
],
@@ -423,25 +537,90 @@
"testset = dataset_master.get_dataset(session=1, train=False)[\"old\"]\n",
"# get the accuracy of the model on the testset:\n",
"\n",
- "testloader = torch.utils.data.DataLoader(testset,\n",
- " batch_size=512,\n",
- " shuffle=False,\n",
- " num_workers=4,\n",
- " pin_memory=True)\n",
+ "testloader = torch.utils.data.DataLoader(\n",
+ " testset, batch_size=512, shuffle=False, num_workers=4, pin_memory=True\n",
+ ")\n",
"\n",
"correct = 0\n",
"total = 0\n",
"pretrained_model.eval()\n",
- "for x, y, _ in tqdm(testloader, desc='Calculating Accuracy', unit='batch'):\n",
+ "for x, y, _ in tqdm(testloader, desc=\"Calculating Accuracy\", unit=\"batch\"):\n",
" with torch.no_grad():\n",
" x = x.to(device)\n",
" y = y.to(device)\n",
- " logits, _ = pretrained_model(x)\n",
+ " logits = pretrained_model.forward_head(x)\n",
" _, predicted = torch.max(logits, 1)\n",
" total += y.size(0)\n",
" correct += (predicted == y).sum().item()\n",
"\n",
- "print(f'Accuracy of the model on the testset: {100 * correct / total:.2f}%')"
+ "print(f\"Accuracy of the model on the testset: {100 * correct / total:.2f}%\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Confusion Matrix"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 181,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 2000x1600 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "\n",
+ "label_mapping = pd.read_csv(\"/cl/entcl/experiments/labelmaps.csv\")\n",
+ "# label_mapping is a df with two columns id and label. turn it into a dict where an int id maps to the label string\n",
+ "label_mapping = {row[\"id\"]: row[\"label\"] for _, row in label_mapping.iterrows()}\n",
+ "df[\"text_label\"] = df[\"label\"].map(label_mapping)\n",
+ "df[\"text_pred_label\"] = df[\"pred_label\"].map(label_mapping)\n",
+ "\n",
+ "# plot a confusion matrix of the df's true labels and predicted labels\n",
+ "from sklearn.metrics import confusion_matrix\n",
+ "import seaborn as sns\n",
+ "import matplotlib.pyplot as plt\n",
+ "\n",
+ "cm = confusion_matrix(df[\"label\"], df[\"pred_label\"])\n",
+ "\n",
+ "# trim all predicted labels >= 50\n",
+ "cm = cm[:, :50]\n",
+ "\n",
+ "#turn the cm into a dataframe\n",
+ "cm = pd.DataFrame(cm)\n",
+ "\n",
+ "annot_matrix = cm.copy()\n",
+ "annot_matrix = annot_matrix.map(lambda x: f\"{int(x)}\" if x > 0 else \"\")\n",
+ "normed_cm = np.log1p(cm)\n",
+ "\n",
+ "plt.figure(figsize=(20, 16))\n",
+ "sns.heatmap(\n",
+ " cm,\n",
+ " cmap=\"viridis\",\n",
+ " annot=annot_matrix,\n",
+ " fmt=\"\",\n",
+ " annot_kws={\"size\": 8},\n",
+ " yticklabels=[f\"{i}: {label_mapping[i]}\" for i in range(60)],\n",
+ " xticklabels=[f\"{i}: {label_mapping[i]}\" for i in range(50)],\n",
+ " cbar=False,\n",
+ " \n",
+ ")\n",
+ "\n",
+ "plt.xlabel(\"Predicted Label\")\n",
+ "plt.ylabel(\"True Label\")\n",
+ "plt.tight_layout()\n",
+ "plt.show()"
]
},
{
@@ -453,16 +632,23 @@
},
{
"cell_type": "code",
- "execution_count": 18,
+ "execution_count": 182,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.mixture import GaussianMixture\n",
+ "\n",
"# GMM 1: entropy\n",
"df = master_df.copy()\n",
- "entropy_gmm = GaussianMixture(n_components=2, random_state=8008135, max_iter=1000, init_params='k-means++', tol=1e-4)\n",
- "df[\"entropy_cluster\"] = entropy_gmm.fit_predict(df['entropy'].values.reshape(-1, 1))\n",
- "soft_clusters = entropy_gmm.predict_proba(df['entropy'].values.reshape(-1, 1))\n",
+ "entropy_gmm = GaussianMixture(\n",
+ " n_components=2,\n",
+ " random_state=8008135,\n",
+ " max_iter=1000,\n",
+ " init_params=\"k-means++\",\n",
+ " tol=1e-4,\n",
+ ")\n",
+ "df[\"entropy_cluster\"] = entropy_gmm.fit_predict(df[\"entropy\"].values.reshape(-1, 1))\n",
+ "soft_clusters = entropy_gmm.predict_proba(df[\"entropy\"].values.reshape(-1, 1))\n",
"\n",
"mean_0 = df[df[\"entropy_cluster\"] == 0][\"entropy\"].mean()\n",
"mean_1 = df[df[\"entropy_cluster\"] == 1][\"entropy\"].mean()\n",
@@ -471,14 +657,20 @@
" df[\"entropy_cluster\"] = 1 - df[\"entropy_cluster\"]\n",
" soft_clusters = soft_clusters[:, [1, 0]]\n",
" print(\"Swapped Ent Clusters\")\n",
- " \n",
+ "\n",
"df[\"entropy_clusterprob_0\"] = soft_clusters[:, 0]\n",
"df[\"entropy_clusterprob_1\"] = soft_clusters[:, 1]\n",
"\n",
"# GMM 2: energy\n",
- "energy_gmm = GaussianMixture(n_components=2, random_state=8008135, max_iter=1000, init_params='k-means++', tol=1e-4)\n",
- "df[\"energy_cluster\"] = energy_gmm.fit_predict(df['energy'].values.reshape(-1, 1))\n",
- "soft_clusters = energy_gmm.predict_proba(df['energy'].values.reshape(-1, 1))\n",
+ "energy_gmm = GaussianMixture(\n",
+ " n_components=2,\n",
+ " random_state=8008135,\n",
+ " max_iter=1000,\n",
+ " init_params=\"k-means++\",\n",
+ " tol=1e-4,\n",
+ ")\n",
+ "df[\"energy_cluster\"] = energy_gmm.fit_predict(df[\"energy\"].values.reshape(-1, 1))\n",
+ "soft_clusters = energy_gmm.predict_proba(df[\"energy\"].values.reshape(-1, 1))\n",
"\n",
"mean_0 = df[df[\"energy_cluster\"] == 0][\"energy\"].mean()\n",
"mean_1 = df[df[\"energy_cluster\"] == 1][\"energy\"].mean()\n",
@@ -501,23 +693,23 @@
},
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": 183,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Entropy-based Known Correct/Total (Accuracy%) 538/1000 (53.8000%)\n",
- "Entropy-based Novel Correct/Total (Accuracy%) 3278/4000 (81.9500%)\n",
+ "Entropy-based Known Correct/Total (Accuracy%) 537/1000 (53.7000%)\n",
+ "Entropy-based Novel Correct/Total (Accuracy%) 3250/4000 (81.2500%)\n",
"\n",
- "Energy-based Known Correct/Total (Accuracy%) 801/1000 (80.1000%)\n",
- "Energy-based Novel Correct/Total (Accuracy%) 2369/4000 (59.2250%)\n"
+ "Energy-based Known Correct/Total (Accuracy%) 802/1000 (80.2000%)\n",
+ "Energy-based Novel Correct/Total (Accuracy%) 2450/4000 (61.2500%)\n"
]
},
{
"data": {
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",
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",
"text/plain": [
"<Figure size 1000x600 with 1 Axes>"
]
@@ -527,7 +719,7 @@
},
{
"data": {
- "image/png": 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",
+ "image/png": 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",
"text/plain": [
"<Figure size 1000x600 with 1 Axes>"
]
@@ -540,24 +732,34 @@
"novel = df[df[\"true_type\"] == 1]\n",
"known = df[df[\"true_type\"] == 0]\n",
"\n",
- "print(f\"Entropy-based Known Correct/Total (Accuracy%) {known[known['entropy_cluster'] == 0].shape[0]}/{known.shape[0]} ({ 100 * (known[known['entropy_cluster'] == 0].shape[0]/known.shape[0]):.4f}%)\")\n",
- "print(f\"Entropy-based Novel Correct/Total (Accuracy%) {novel[novel['entropy_cluster'] == 1].shape[0]}/{novel.shape[0]} ({ 100 * (novel[novel['entropy_cluster'] == 1].shape[0]/novel.shape[0]):.4f}%)\")\n",
+ "print(\n",
+ " f\"Entropy-based Known Correct/Total (Accuracy%) {known[known['entropy_cluster'] == 0].shape[0]}/{known.shape[0]} ({ 100 * (known[known['entropy_cluster'] == 0].shape[0]/known.shape[0]):.4f}%)\"\n",
+ ")\n",
+ "print(\n",
+ " f\"Entropy-based Novel Correct/Total (Accuracy%) {novel[novel['entropy_cluster'] == 1].shape[0]}/{novel.shape[0]} ({ 100 * (novel[novel['entropy_cluster'] == 1].shape[0]/novel.shape[0]):.4f}%)\"\n",
+ ")\n",
"print(\"\")\n",
- "print(f\"Energy-based Known Correct/Total (Accuracy%) {known[known['energy_cluster'] == 0].shape[0]}/{known.shape[0]} ({ 100 * (known[known['energy_cluster'] == 0].shape[0]/known.shape[0]):.4f}%)\")\n",
- "print(f\"Energy-based Novel Correct/Total (Accuracy%) {novel[novel['energy_cluster'] == 1].shape[0]}/{novel.shape[0]} ({ 100 * (novel[novel['energy_cluster'] == 1].shape[0]/novel.shape[0]):.4f}%)\")\n",
+ "print(\n",
+ " f\"Energy-based Known Correct/Total (Accuracy%) {known[known['energy_cluster'] == 0].shape[0]}/{known.shape[0]} ({ 100 * (known[known['energy_cluster'] == 0].shape[0]/known.shape[0]):.4f}%)\"\n",
+ ")\n",
+ "print(\n",
+ " f\"Energy-based Novel Correct/Total (Accuracy%) {novel[novel['energy_cluster'] == 1].shape[0]}/{novel.shape[0]} ({ 100 * (novel[novel['energy_cluster'] == 1].shape[0]/novel.shape[0]):.4f}%)\"\n",
+ ")\n",
"\n",
"plt.figure(figsize=(10, 6))\n",
- "sns.kdeplot(data=df, x='entropy', hue='entropy_cluster', fill=True)\n",
- "plt.title('KDE Plot of Entropy Scores by Entropy Cluster')\n",
- "plt.xlabel('Entropy')\n",
- "plt.ylabel('Density')\n",
+ "sns.kdeplot(\n",
+ " data=df, x=\"entropy\", hue=\"entropy_cluster\", fill=True, label=\"Entropy Cluster\"\n",
+ ")\n",
+ "plt.title(\"KDE Plot of Entropy Scores by Entropy Cluster\")\n",
+ "plt.xlabel(\"Entropy\")\n",
+ "plt.ylabel(\"Density\")\n",
"plt.show()\n",
"\n",
"plt.figure(figsize=(10, 6))\n",
- "sns.kdeplot(data=df, x='energy', hue='energy_cluster', fill=True)\n",
- "plt.title('KDE Plot of Energy Scores by Energy Cluster')\n",
- "plt.xlabel('Energy')\n",
- "plt.ylabel('Density')\n",
+ "sns.kdeplot(data=df, x=\"energy\", hue=\"energy_cluster\", fill=True)\n",
+ "plt.title(\"KDE Plot of Energy Scores by Energy Cluster\")\n",
+ "plt.xlabel(\"Energy\")\n",
+ "plt.ylabel(\"Density\")\n",
"plt.show()"
]
},
@@ -570,15 +772,15 @@
},
{
"cell_type": "code",
- "execution_count": 20,
+ "execution_count": 184,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Known Correct/Total (Accuracy%) 617/1000 (61.7000%)\n",
- "Novel Correct/Total (Accuracy%) 3093/4000 (77.3250%)\n"
+ "Known Correct/Total (Accuracy%) 594/1000 (59.4000%)\n",
+ "Novel Correct/Total (Accuracy%) 3126/4000 (78.1500%)\n"
]
}
],
@@ -586,25 +788,40 @@
"# if both cluster assignments are the same, then the pred_type is the same as the cluster assignment\n",
"# if they are not the same, the cluster with the best confidence is the pred_type\n",
"vote_df = df.copy()\n",
+ "\n",
+ "\n",
"def vote(row):\n",
" if row[\"entropy_cluster\"] == row[\"energy_cluster\"]:\n",
" return row[\"entropy_cluster\"]\n",
" else:\n",
- " entropy_conf = row[\"entropy_clusterprob_0\"] if row[\"entropy_cluster\"] == 0 else row[\"entropy_clusterprob_1\"]\n",
- " energy_conf = row[\"energy_clusterprob_0\"] if row[\"energy_cluster\"] == 0 else row[\"energy_clusterprob_1\"]\n",
- " \n",
+ " entropy_conf = (\n",
+ " row[\"entropy_clusterprob_0\"]\n",
+ " if row[\"entropy_cluster\"] == 0\n",
+ " else row[\"entropy_clusterprob_1\"]\n",
+ " )\n",
+ " energy_conf = (\n",
+ " row[\"energy_clusterprob_0\"]\n",
+ " if row[\"energy_cluster\"] == 0\n",
+ " else row[\"energy_clusterprob_1\"]\n",
+ " )\n",
+ "\n",
" if entropy_conf >= energy_conf:\n",
" return row[\"entropy_cluster\"]\n",
" else:\n",
" return row[\"energy_cluster\"]\n",
- " \n",
+ "\n",
+ "\n",
"vote_df[\"pred_type\"] = vote_df.apply(vote, axis=1)\n",
"\n",
"novel = vote_df[vote_df[\"true_type\"] == 1]\n",
"known = vote_df[vote_df[\"true_type\"] == 0]\n",
"\n",
- "print(f\"Known Correct/Total (Accuracy%) {known[known['pred_type'] == 0].shape[0]}/{known.shape[0]} ({ 100 * (known[known['pred_type'] == 0].shape[0]/known.shape[0]):.4f}%)\")\n",
- "print(f\"Novel Correct/Total (Accuracy%) {novel[novel['pred_type'] == 1].shape[0]}/{novel.shape[0]} ({ 100 * (novel[novel['pred_type'] == 1].shape[0]/novel.shape[0]):.4f}%)\")"
+ "print(\n",
+ " f\"Known Correct/Total (Accuracy%) {known[known['pred_type'] == 0].shape[0]}/{known.shape[0]} ({ 100 * (known[known['pred_type'] == 0].shape[0]/known.shape[0]):.4f}%)\"\n",
+ ")\n",
+ "print(\n",
+ " f\"Novel Correct/Total (Accuracy%) {novel[novel['pred_type'] == 1].shape[0]}/{novel.shape[0]} ({ 100 * (novel[novel['pred_type'] == 1].shape[0]/novel.shape[0]):.4f}%)\"\n",
+ ")"
]
},
{
@@ -616,15 +833,15 @@
},
{
"cell_type": "code",
- "execution_count": 21,
+ "execution_count": 185,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Known Correct/Total (Accuracy%) 582/1000 (58.2000%)\n",
- "Novel Correct/Total (Accuracy%) 3154/4000 (78.8500%)\n"
+ "Known Correct/Total (Accuracy%) 575/1000 (57.5000%)\n",
+ "Novel Correct/Total (Accuracy%) 3165/4000 (79.1250%)\n"
]
}
],
@@ -634,35 +851,50 @@
"weights = {\"entropy\": {0: 0.574, 1: 0.926}, \"energy\": {0: 0.891, 1: 0.65975}}\n",
"\n",
"wvote_df = df.copy()\n",
+ "\n",
+ "\n",
"def vote(row):\n",
" if row[\"entropy_cluster\"] == row[\"energy_cluster\"]:\n",
" return row[\"entropy_cluster\"]\n",
" else:\n",
- " entropy_conf = row[\"entropy_clusterprob_0\"] if row[\"entropy_cluster\"] == 0 else row[\"entropy_clusterprob_1\"]\n",
- " energy_conf = row[\"energy_clusterprob_0\"] if row[\"energy_cluster\"] == 0 else row[\"energy_clusterprob_1\"]\n",
- " \n",
+ " entropy_conf = (\n",
+ " row[\"entropy_clusterprob_0\"]\n",
+ " if row[\"entropy_cluster\"] == 0\n",
+ " else row[\"entropy_clusterprob_1\"]\n",
+ " )\n",
+ " energy_conf = (\n",
+ " row[\"energy_clusterprob_0\"]\n",
+ " if row[\"energy_cluster\"] == 0\n",
+ " else row[\"energy_clusterprob_1\"]\n",
+ " )\n",
+ "\n",
" if row[\"entropy_cluster\"] == 0:\n",
" entropy_conf *= weights[\"entropy\"][0]\n",
" else:\n",
" entropy_conf *= weights[\"entropy\"][1]\n",
- " \n",
+ "\n",
" if row[\"energy_cluster\"] == 0:\n",
" energy_conf *= weights[\"energy\"][0]\n",
" else:\n",
" energy_conf *= weights[\"energy\"][1]\n",
- " \n",
+ "\n",
" if entropy_conf >= energy_conf:\n",
" return row[\"entropy_cluster\"]\n",
" else:\n",
" return row[\"energy_cluster\"]\n",
- " \n",
+ "\n",
+ "\n",
"wvote_df[\"pred_type\"] = wvote_df.apply(vote, axis=1)\n",
"\n",
"novel = wvote_df[wvote_df[\"true_type\"] == 1]\n",
"known = wvote_df[wvote_df[\"true_type\"] == 0]\n",
"\n",
- "print(f\"Known Correct/Total (Accuracy%) {known[known['pred_type'] == 0].shape[0]}/{known.shape[0]} ({ 100 * (known[known['pred_type'] == 0].shape[0]/known.shape[0]):.4f}%)\")\n",
- "print(f\"Novel Correct/Total (Accuracy%) {novel[novel['pred_type'] == 1].shape[0]}/{novel.shape[0]} ({ 100 * (novel[novel['pred_type'] == 1].shape[0]/novel.shape[0]):.4f}%)\")"
+ "print(\n",
+ " f\"Known Correct/Total (Accuracy%) {known[known['pred_type'] == 0].shape[0]}/{known.shape[0]} ({ 100 * (known[known['pred_type'] == 0].shape[0]/known.shape[0]):.4f}%)\"\n",
+ ")\n",
+ "print(\n",
+ " f\"Novel Correct/Total (Accuracy%) {novel[novel['pred_type'] == 1].shape[0]}/{novel.shape[0]} ({ 100 * (novel[novel['pred_type'] == 1].shape[0]/novel.shape[0]):.4f}%)\"\n",
+ ")"
]
},
{
@@ -681,55 +913,119 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 186,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Means 0, -1, 1: 0.06324542313814163, 0.5723875164985657, 1.943918228149414\n"
+ "Means 0, -1, 1: 0.029665254056453705, 0.295553594827652, 1.5923761129379272\n"
]
},
{
- "ename": "ValueError",
- "evalue": "The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().",
- "output_type": "error",
- "traceback": [
- "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
- "\u001b[0;32m/tmp/ipykernel_1131/4139231074.py\u001b[0m in \u001b[0;36m?\u001b[0;34m()\u001b[0m\n\u001b[1;32m 14\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"cluster\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'cluster'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrename_mapping\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 15\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 16\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"Means 0, -1, 1: {df[df['cluster'] == 0]['entropy'].mean()}, {df[df['cluster'] == -1]['entropy'].mean()}, {df[df['cluster'] == 1]['entropy'].mean()}\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 17\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 18\u001b[0;31m \u001b[0mknown\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"true_type\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"cluster\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 19\u001b[0m \u001b[0mnovel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"true_type\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m1\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"cluster\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 20\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 21\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"Non -1 Known Correct/Total (Accuracy%) {known[known['cluster'] == 0].shape[0]}/{known.shape[0]} ({ 100 * (known[known['cluster'] == 0].shape[0]/known.shape[0]):.4f}%)\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
- "\u001b[0;32m~/miniconda3/envs/entcl/lib/python3.10/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m?\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1575\u001b[0m \u001b[0;34m@\u001b[0m\u001b[0mfinal\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1576\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__nonzero__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0mNoReturn\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1577\u001b[0;31m raise ValueError(\n\u001b[0m\u001b[1;32m 1578\u001b[0m \u001b[0;34mf\"The truth value of a {type(self).__name__} is ambiguous. \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1579\u001b[0m \u001b[0;34m\"Use a.empty, a.bool(), a.item(), a.any() or a.all().\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1580\u001b[0m )\n",
- "\u001b[0;31mValueError\u001b[0m: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all()."
- ]
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>Count</th>\n",
+ " <th>In Known</th>\n",
+ " <th>In Unsure</th>\n",
+ " <th>in Novel</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>Known</th>\n",
+ " <td>1000</td>\n",
+ " <td>442</td>\n",
+ " <td>291</td>\n",
+ " <td>267</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Novel</th>\n",
+ " <td>4000</td>\n",
+ " <td>499</td>\n",
+ " <td>874</td>\n",
+ " <td>2627</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " Count In Known In Unsure in Novel\n",
+ "Known 1000 442 291 267\n",
+ "Novel 4000 499 874 2627"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
}
],
"source": [
"df = master_df.copy()\n",
"\n",
"# entropy GMM\n",
- "gmm = GaussianMixture(n_components=3, random_state=8008135, max_iter=1000, init_params='k-means++', tol=1e-4)\n",
+ "gmm = GaussianMixture(\n",
+ " n_components=3,\n",
+ " random_state=8008135,\n",
+ " max_iter=1000,\n",
+ " init_params=\"k-means++\",\n",
+ " tol=1e-4,\n",
+ ")\n",
"\n",
- "df[\"cluster\"] = gmm.fit_predict(df['entropy'].values.reshape(-1, 1))\n",
- "soft_clusters = gmm.predict_proba(df['entropy'].values.reshape(-1, 1))\n",
+ "df[\"cluster\"] = gmm.fit_predict(df[\"entropy\"].values.reshape(-1, 1))\n",
+ "soft_clusters = gmm.predict_proba(df[\"entropy\"].values.reshape(-1, 1))\n",
"\n",
- "cluster_means = df.groupby('cluster')['entropy'].mean()\n",
+ "cluster_means = df.groupby(\"cluster\")[\"entropy\"].mean()\n",
"sorted_clusters = cluster_means.sort_values().index\n",
"\n",
"rename_mapping = {sorted_clusters[0]: 0, sorted_clusters[1]: -1, sorted_clusters[2]: 1}\n",
"\n",
- "df[\"cluster\"] = df['cluster'].map(rename_mapping)\n",
+ "df[\"cluster\"] = df[\"cluster\"].map(rename_mapping)\n",
"\n",
- "print(f\"Means 0, -1, 1: {df[df['cluster'] == 0]['entropy'].mean()}, {df[df['cluster'] == -1]['entropy'].mean()}, {df[df['cluster'] == 1]['entropy'].mean()}\")\n",
+ "print(\n",
+ " f\"Means 0, -1, 1: {df[df['cluster'] == 0]['entropy'].mean()}, {df[df['cluster'] == -1]['entropy'].mean()}, {df[df['cluster'] == 1]['entropy'].mean()}\"\n",
+ ")\n",
"\n",
- "known = df[df[\"true_type\"] == 0]\n",
- "known = known[known[\"cluster\"] != -1]\n",
- "novel = df[df[\"true_type\"] == 1]\n",
- "novel = novel[novel[\"cluster\"] != -1]\n",
+ "trueknowns = df[df[\"true_type\"] == 0]\n",
+ "truenovels = df[df[\"true_type\"] == 1]\n",
+ "\n",
+ "novel_total = df[df[\"true_type\"] == 1].shape[0]\n",
+ "known_total = df[df[\"true_type\"] == 0].shape[0]\n",
+ "\n",
+ "display_df = pd.DataFrame(columns=[\"Count\", \"In Known\", \"In Unsure\", \"in Novel\"])\n",
+ "display_df.loc[\"Known\"] = [\n",
+ " known_total,\n",
+ " trueknowns[trueknowns[\"cluster\"] == 0].shape[0],\n",
+ " trueknowns[trueknowns[\"cluster\"] == -1].shape[0],\n",
+ " trueknowns[trueknowns[\"cluster\"] == 1].shape[0],\n",
+ "]\n",
+ "display_df.loc[\"Novel\"] = [\n",
+ " novel_total,\n",
+ " truenovels[truenovels[\"cluster\"] == 0].shape[0],\n",
+ " truenovels[truenovels[\"cluster\"] == -1].shape[0],\n",
+ " truenovels[truenovels[\"cluster\"] == 1].shape[0],\n",
+ "]\n",
"\n",
- "print(f\"Non -1 Known Correct/Total (Accuracy%) {known[known['cluster'] == 0].shape[0]}/{known.shape[0]} ({ 100 * (known[known['cluster'] == 0].shape[0]/known.shape[0]):.4f}%)\")\n",
- "print(f\"Non -1 Novel Correct/Total (Accuracy%) {novel[novel['cluster'] == 1].shape[0]}/{novel.shape[0]} ({ 100 * (novel[novel['cluster'] == 1].shape[0]/novel.shape[0]):.4f}%)\")\n",
- "print(f\"Known in -1: {df[df['cluster'] == -1 and df['true_type'] == 0].shape[0]} | Novel in -1: {df[df['cluster'] == -1 and df['true_type'] == 1].shape[0]}\")"
+ "display(display_df)"
]
},
{
@@ -748,9 +1044,24 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 187,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "6ba8b1e3f3bf430c9816b63f90b0b6e8",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "Calculating Entropies: 0%| | 0/4 [00:00<?, ?batch/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"# for the feature distance sorting of cluster -1, we need an exemplar set. We will randomly sample 32 images per class from the session 0 training dataset\n",
"session_0_trainset = dataset_master.get_dataset(session=0)\n",
@@ -765,36 +1076,37 @@
"\n",
"for label in unique_labels:\n",
" label_indices = np.where(labels_np == label)[0]\n",
- " sample_indices.extend(np.random.choice(label_indices, samples_per_label, replace=False))\n",
+ " sample_indices.extend(\n",
+ " np.random.choice(label_indices, samples_per_label, replace=False)\n",
+ " )\n",
"\n",
"subset = torch.utils.data.Subset(session_0_trainset, sample_indices)\n",
- "subset_loader = torch.utils.data.DataLoader(subset, batch_size=512, shuffle=False, num_workers=4, pin_memory=True)\n",
+ "subset_loader = torch.utils.data.DataLoader(\n",
+ " subset, batch_size=512, shuffle=False, num_workers=4, pin_memory=True\n",
+ ")\n",
"\n",
"# get the features, logits, entropies and energies of the exemplar set\n",
"results = []\n",
"\n",
"pretrained_model.eval()\n",
- "for x, label, _ in tqdm(subset_loader, desc='Calculating Entropies', unit='batch'):\n",
+ "for x, label, _ in tqdm(subset_loader, desc=\"Calculating Entropies\", unit=\"batch\"):\n",
" with torch.no_grad():\n",
" x = x.to(device)\n",
- " logits, feats = pretrained_model(x)\n",
+ " logits = pretrained_model.forward_head(x)\n",
" softmax = torch.nn.functional.softmax(logits, dim=1)\n",
" entropy = -torch.sum(softmax * torch.log(softmax + 1e-12), dim=1)\n",
" energy = -torch.logsumexp(logits, dim=1)\n",
- " feats = feats.cpu().numpy()\n",
+ " feats = x.cpu().numpy()\n",
" logits = logits.cpu().numpy()\n",
" entropy = entropy.cpu().numpy()\n",
" energy = energy.cpu().numpy()\n",
" label = label.cpu().numpy()\n",
- " results.append([entropy, energy, label, *feats, *logits])\n",
+ " for i in range(x.size(0)):\n",
+ " results.append([entropy[i], energy[i], label[i], *feats[i], *logits[i]])\n",
"\n",
- "columns = ['entropy', 'energy', 'label'] + feat_cols + logit_cols\n",
+ "columns = [\"entropy\", \"energy\", \"label\"] + feat_cols + logit_cols\n",
"exemplar_df = pd.DataFrame(results, columns=columns)\n",
- "\n",
- "# create a df for exemplar means: mean of each column for each label\n",
- "exemplar_means = exemplar_df.groupby('label').mean()\n",
- "\n",
- "print(exemplar_means[\"label\", \"entropy\", \"energy\"])"
+ "exemplar_means = exemplar_df.groupby(\"label\").mean()"
]
},
{
@@ -806,23 +1118,95 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 188,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Index(['entropy', 'energy', 'label', 'pred_label', 'true_type', 'feat_0',\n",
+ " 'feat_1', 'feat_2', 'feat_3', 'feat_4',\n",
+ " ...\n",
+ " 'logit_42', 'logit_43', 'logit_44', 'logit_45', 'logit_46', 'logit_47',\n",
+ " 'logit_48', 'logit_49', 'true_type_label', 'cluster'],\n",
+ " dtype='object', length=825)\n",
+ " entropy energy label pred_label true_type feat_0 feat_1 \\\n",
+ "7 0.192985 -9.655376 0 0 0 0.568121 -4.709133 \n",
+ "9 0.130881 -11.180057 0 0 0 1.489581 -2.478425 \n",
+ "15 0.102368 -10.771288 0 0 0 1.420420 -0.475831 \n",
+ "17 0.140695 -10.907016 0 0 0 0.104761 2.569209 \n",
+ "18 0.475591 -10.290781 0 0 0 0.162173 -1.715846 \n",
+ "... ... ... ... ... ... ... ... \n",
+ "4977 0.470241 -10.575934 59 47 1 0.764202 -3.533105 \n",
+ "4978 0.461605 -9.814182 59 33 1 2.167216 -4.076577 \n",
+ "4982 0.533336 -9.140674 59 49 1 0.964937 -4.056687 \n",
+ "4985 0.518870 -11.476691 59 47 1 0.488649 -4.280091 \n",
+ "4991 0.379548 -10.457094 59 47 1 1.169769 -4.101706 \n",
+ "\n",
+ " feat_2 feat_3 feat_4 ... logit_44 logit_45 logit_46 \\\n",
+ "7 3.552746 -0.882507 -0.314241 ... 0.198901 2.547427 0.513217 \n",
+ "9 2.102047 -2.673830 0.996181 ... -1.823816 3.052798 -1.294632 \n",
+ "15 2.341636 -1.526995 1.079648 ... -1.934299 4.071828 -0.020017 \n",
+ "17 1.471712 -1.004581 1.388844 ... -4.460147 -0.481568 -1.132492 \n",
+ "18 -0.397919 0.221015 -0.025786 ... -1.017803 0.528301 0.338674 \n",
+ "... ... ... ... ... ... ... ... \n",
+ "4977 4.189106 -0.334127 -2.968814 ... 0.732399 -0.661663 1.433711 \n",
+ "4978 5.543993 1.877427 -0.590450 ... 0.320400 1.776519 1.153085 \n",
+ "4982 3.423305 -0.728285 -0.651033 ... 0.653401 -3.948216 1.519995 \n",
+ "4985 2.396956 -2.041231 -0.460762 ... 0.259321 -1.961935 1.364851 \n",
+ "4991 0.928157 -2.391460 -1.872822 ... 1.901749 -1.333985 1.617527 \n",
+ "\n",
+ " logit_47 logit_48 logit_49 true_type_label cluster nearest_dist \\\n",
+ "7 1.335973 0.595306 -1.636142 Known -1 0.300155 \n",
+ "9 -1.462164 3.371264 -1.988588 Known -1 0.310862 \n",
+ "15 0.571535 -1.855251 -2.712907 Known -1 0.230891 \n",
+ "17 -0.542150 -2.385990 -2.606415 Known -1 0.246221 \n",
+ "18 1.076656 -5.591436 -1.155741 Known -1 0.300201 \n",
+ "... ... ... ... ... ... ... \n",
+ "4977 10.416052 -2.374991 3.188021 Novel -1 0.234678 \n",
+ "4978 7.814028 -0.585794 2.456573 Novel -1 0.259376 \n",
+ "4982 6.924827 -1.897368 8.992824 Novel -1 0.285636 \n",
+ "4985 11.249170 -0.396130 2.976443 Novel -1 0.206472 \n",
+ "4991 10.365494 -1.337986 6.212648 Novel -1 0.278078 \n",
+ "\n",
+ " nearest_label \n",
+ "7 0 \n",
+ "9 0 \n",
+ "15 0 \n",
+ "17 0 \n",
+ "18 0 \n",
+ "... ... \n",
+ "4977 47 \n",
+ "4978 33 \n",
+ "4982 49 \n",
+ "4985 47 \n",
+ "4991 47 \n",
+ "\n",
+ "[1165 rows x 827 columns]\n"
+ ]
+ }
+ ],
"source": [
"from sklearn.metrics.pairwise import cosine_distances as dist\n",
+ "\n",
"# filter the df to only include cluster -1\n",
"unassigned_df = df[df[\"cluster\"] == -1].copy()\n",
+ "print(unassigned_df.columns)\n",
"\n",
"# for each sample in unassigned_df, calculate the distance of that sample's features to the nearest exemplar mean's features\n",
"\n",
+ "\n",
"def get_dist_to_nearest(row):\n",
" features = row[feat_cols].values\n",
" distances = dist(features.reshape(1, -1), exemplar_means[feat_cols].values)\n",
" return np.min(distances), np.argmin(distances)\n",
"\n",
- "unassigned_df[\"nearest_dist\"], unassigned_df[\"nearest_label\"] = zip(*unassigned_df.apply(get_dist_to_nearest, axis=1))\n",
- "\n"
+ "\n",
+ "unassigned_df[\"nearest_dist\"], unassigned_df[\"nearest_label\"] = zip(\n",
+ " *unassigned_df.apply(get_dist_to_nearest, axis=1)\n",
+ ")\n",
+ "print(unassigned_df)"
]
},
{
@@ -834,29 +1218,1612 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 189,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "-1 Known Correct/Total (Accuracy%) 261/291 (89.6907%)\n",
+ "-1 Novel Correct/Total (Accuracy%) 96/874 (10.9840%)\n"
+ ]
+ }
+ ],
"source": [
"unassigned_gmm_df = unassigned_df.copy()\n",
- "unassigned_gmm_df = unassigned_gmm_df.drop(\"cluster\") # remove the cluster, because we know they are unassigned\n",
+ "unassigned_gmm_df = unassigned_gmm_df.drop(labels=\"cluster\", axis=1)\n",
"\n",
- "gmm = GaussianMixture(n_components=2, random_state=8008135, max_iter=1000, init_params='k-means++', tol=1e-4)\n",
+ "gmm = GaussianMixture(\n",
+ " n_components=2,\n",
+ " random_state=8008135,\n",
+ " max_iter=1000,\n",
+ " init_params=\"k-means++\",\n",
+ " tol=1e-4,\n",
+ ")\n",
"\n",
- "unassigned_gmm_df[\"cluster\"] = gmm.fit_predict(unassigned_gmm_df['nearest_dist'].values.reshape(-1, 1))\n",
+ "unassigned_gmm_df[\"cluster\"] = gmm.fit_predict(\n",
+ " unassigned_gmm_df[\"nearest_dist\"].values.reshape(-1, 1)\n",
+ ")\n",
"\n",
"# the cluster with the smaller dists are the knowns, so we will swap the clusters if the mean of the knowns is greater than the mean of the novelties\n",
- "cluster_means = unassigned_gmm_df.groupby('cluster')['nearest_dist'].mean()\n",
+ "cluster_means = unassigned_gmm_df.groupby(\"cluster\")[\"nearest_dist\"].mean()\n",
"sorted_clusters = cluster_means.sort_values().index\n",
"rename_mapping = {sorted_clusters[0]: 0, sorted_clusters[1]: 1}\n",
"\n",
- "unassigned_gmm_df['cluster'] = unassigned_gmm_df['cluster'].map(rename_mapping)\n",
+ "unassigned_gmm_df[\"cluster\"] = unassigned_gmm_df[\"cluster\"].map(rename_mapping)\n",
"\n",
- "known = unassigned_gmm_df[unassigned_gmm_df[\"truetype\"] == 0]\n",
- "novel = unassigned_gmm_df[unassigned_gmm_df[\"truetype\"] == 1]\n",
+ "known = unassigned_gmm_df[unassigned_gmm_df[\"true_type\"] == 0]\n",
+ "novel = unassigned_gmm_df[unassigned_gmm_df[\"true_type\"] == 1]\n",
"\n",
- "print(f\"-1 Known Correct/Total (Accuracy%) {known[known['cluster'] == 0].shape[0]}/{known.shape[0]} ({ 100 * (known[known['cluster'] == 0].shape[0]/known.shape[0]):.4f}%)\")\n",
- "print(f\"-1 Novel Correct/Total (Accuracy%) {novel[novel['cluster'] == 1].shape[0]}/{novel.shape[0]} ({ 100 * (novel[novel['cluster'] == 1].shape[0]/novel.shape[0]):.4f}%)\")"
+ "print(\n",
+ " f\"-1 Known Correct/Total (Accuracy%) {known[known['cluster'] == 0].shape[0]}/{known.shape[0]} ({ 100 * (known[known['cluster'] == 0].shape[0]/known.shape[0]):.4f}%)\"\n",
+ ")\n",
+ "print(\n",
+ " f\"-1 Novel Correct/Total (Accuracy%) {novel[novel['cluster'] == 1].shape[0]}/{novel.shape[0]} ({ 100 * (novel[novel['cluster'] == 1].shape[0]/novel.shape[0]):.4f}%)\"\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### GMM uses entropy, feature distance"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 192,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 1000x1000 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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ji21b0ut4ep/OR+/evb1ur127loKCgmJ/N2JiYrj55ptL/LvRt29fr9t9+vQB4K+//gIKp2aPGjWKn376yfN34tChQyxbtowRI0acVzVIIa4XEpiEuMa1bNmS559/nm+++YYTJ04wevRoEhMTPdeTFF3Dc3q1rjO53W66dOnC999/z3PPPccff/zBhg0bPNcKFBQUXFIfU1NT2bFjhyfUFP0EBASgKEqxE8UqVapc0P6LTnY2bdrErl27yMnJ4YsvviAoKKjUx2RmZuLr60t4eLhXu0qlonLlymRmZl5QH8p6v2caP348arW6xBO6on6U9DpGRUV57j/d2V7z0NBQr9tarRY/Pz+vsFHUbrVaPbe///577r//fqKjo/niiy9Yu3YtGzdu5NFHH/Xa7nwtXLiQ/v37M2fOHNq1a0doaCiPPPIIKSkpQOH7DODee+8t9l6bMmUKiqKQlZVFdnY2brebypUrFztGSW0Xo+jkuej1Lkm/fv349NNPOXr0KL179yYiIoI2bdqwYsWKc+7/Yj6zYWFhXreLinoUbZueno5arT7ra1D0Grdq1arYa7xw4cJzhr63336b4cOH06ZNG7777jvWrVvHxo0buf322y+qz0Xv40v9Xer1elq2bFnspyiAXkifzseZn7ei51HaZ/bMz6uvr2+xfhQ939O3ffTRRzEYDMycOROAjz76CIPBwKOPPnrefRXieiAlV4S4jmg0GsaNG8c777zDrl27ADwn7seOHSMmJqbEx+3atYvt27czb948+vfv72kvuhD5UlWqVAmDwcCnn35a6v2nu9BvPotOdi5EWFgYTqeT9PR0r3CjKAopKSm0atXqgvZX1vs9U5UqVXjqqad44403Slx3KywsjJMnTxZrL7o4/VJf8/PxxRdfEBcXx8KFC732X9IaReejUqVKvPvuu7z77rskJSWxZMkSXnjhBdLS0li2bJnnOX3wwQelVjyLjIz0VCUrClqnK6ntYhQVSTjXuksDBw5k4MCBWCwWVq9ezbhx4+jRowf79+8v8WS9SFl8ZsPDw3G5XKSkpJQaoIte42+//fas/SvNF198QadOnZgxY4ZXe15e3oV3mP/CS1n+LsvCmZ+3oudR2mf2zM+r0+kkMzPTKzQVPd/T24KCgjxfMjzzzDPMnTuXPn36FFsSQojrnYwwCXGNKuk/VvhvKk7RN9tdunRBrVYXO0E5XdF/3meWkZ41a1axbc/2bapOpyuxvUePHhw6dIiwsLASv8Utj/VlbrnlFqDwBO503333HRaLxXM/lP68LnW/l+r5558nNDSUF154ocR+JCQksGXLFq/2+fPno1Kp6Ny582XrR2lUKhVardbr5DAlJeW8quSdS7Vq1Rg1ahS33Xab5zl26NCB4OBgEhISSnyftWzZEq1Wi7+/P61bt+b777/3GunKy8tj6dKll9y3FStWMGfOHNq3b88NN9xwXo/x9/enW7duvPzyy9jtdnbv3g2U/nm7kM/s+SqaYnm2vxVdu3bF19eXQ4cOlfoan41KpSrW5x07drB27dqL6nPdunWpUqUKX331ldc0yKNHj7JmzZqL2uflcCF/MwDatWuHwWAo9nfj2LFj/PnnnyX+3Thz3agvv/wSKB7Sn3jiCTIyMrj33nvJycmp0AtcC1FWZIRJiGtU165dqVq1KnfeeSf16tXD7Xazbds2pk2bhtFo5MknnwQKS9y+9NJLTJo0iYKCAk9Z4YSEBDIyMpgwYQL16tWjZs2avPDCCyiKQmhoKEuXLi1xalDjxo0BeO+99+jfvz8ajYa6desSEBBA48aN+frrr1m4cCE1atRAr9fTuHFjnnrqKb777jtuuukmRo8eTZMmTXC73SQlJbF8+XLGjBlDmzZtrujrd9ttt9G1a1eef/55TCYTHTp0YMeOHYwbN45mzZrRr18/r+dc0vO61P1eqsDAQF5++WVGjx5d7L7Ro0czf/58unfvzsSJE6levTo///wz06dPZ/jw4dSpU+ey9aM0PXr04Pvvv2fEiBHce++9JCcnM2nSJKpUqcKBAwcuaF+5ubl07tyZPn36UK9ePQICAti4cSPLli2jV69eABiNRj744AP69+9PVlYW9957LxEREaSnp7N9+3bS09M9YWDSpEncfvvt3HbbbYwZMwaXy8WUKVPw9/cnKyvrvPrkdrs9U+BsNhtJSUn8+uuvLFq0iPr167No0aKzPn7IkCEYDAY6dOhAlSpVSElJYfLkyQQFBXlGIhs1agTAxx9/TEBAAHq9nri4uAv6zJ6vG2+8kX79+vHqq6+SmppKjx490Ol0bN26FT8/Px5//HFiY2OZOHEiL7/8MocPH+b2228nJCSE1NRUNmzYgL+/PxMmTCj1GD169GDSpEmMGzeOjh07sm/fPiZOnEhcXBxOp/OC++zj48OkSZMYPHgwPXv2ZMiQIeTk5DB+/PgLmpJXUFBQYrly4KLWZ7qQvxkAwcHBjB07lpdeeolHHnmEhx56iMzMTCZMmIBer2fcuHFe22u1WqZNm4bZbKZVq1asWbOGV199lW7duhUL6XXq1OH222/n119/5YYbbiA+Pv6Cn48Q17xyKzchhChTCxcuVPr06aPUrl1bMRqNikajUapVq6b069dPSUhIKLb9/PnzlVatWil6vV4xGo1Ks2bNvCqQJSQkKLfddpsSEBCghISEKPfdd5+SlJSkAMq4ceO89vXiiy8qUVFRio+Pj1cFr8TERKVLly5KQECAAnhVqDKbzcr//vc/pW7duopWq1WCgoKUxo0bK6NHj1ZSUlI823FGtbdzKa2s+JnOrJKnKIpSUFCgPP/880r16tUVjUajVKlSRRk+fLiSnZ3ttd3ZnldJzne/F1sl73Q2m02Ji4sr8XU7evSo0qdPHyUsLEzRaDRK3bp1lalTp3qVSi6qRjZ16tRi+y6qrpaenn5efSnpd/HGG28osbGxik6nU+rXr6/Mnj3bs9/TnatKntVqVYYNG6Y0adJECQwMVAwGg1K3bl1l3LhxisVi8drXqlWrlO7duyuhoaGKRqNRoqOjle7duyvffPON13ZLlixRmjRp4inR/MYbb5TYt5IUVSor+jEYDEq1atWUO++8U/n0008Vm81W4utzeuW0zz77TOncubMSGRmpaLVaJSoqSrn//vuVHTt2eD3u3XffVeLi4hS1Wu31mpzvZ7a032NR1bfTK166XC7lnXfeURo1auT5nLZr105ZunSp12MXL16sdO7cWQkMDFR0Op1SvXp15d577/Uq3V4Sm82mPPPMM0p0dLSi1+uV5s2bK4sXLy72+Tzb+7Kkv0lz5sxRateurWi1WqVOnTrKp59+WuJnviRnq5IHKA6Hw+v1OrPaZ1Hlu9MrGZb2N6No2zPfi6c/j6L3ZFBQkHL33XcXK9Ve9PnbsWOH0qlTJ8VgMCihoaHK8OHDFbPZXOJ+582bpwBeJfiFEP9RKcp5lOoRQgghhBBXvQEDBvDtt99iNpvP+zG9e/dm3bp1JCYmlloNU4jrmUzJE0IIIYS4zthsNrZs2cKGDRv44YcfePvttyUsCVEKCUxCCCGEENeZkydP0r59ewIDAxk6dCiPP/54eXdJiKuWTMkTQgghhBBCiFJIWXEhhBBCCCGEKIUEJiGEEEIIIYQohQQmIYQQQgghhCjFdVX0we12c+LECQICArxWlhdCCCGEEEJcXxRFIS8vj6ioKHx8Sh9Huq4C04kTJ4iJiSnvbgghhBBCCCGuEsnJyVStWrXU+6+rwBQQEAAUviiBgYHl3BshhBBCCCFEeTGZTMTExHgyQmmuq8BUNA0vMDBQApMQQgghhBDinJfqSNEHIYQQQgghhCiFBCYhhBBCCCGEKIUEJiGEEEIIIYQoxXV1DZMQQgghhChfiqLgdDpxuVzl3RVxjVOr1fj6+l7yckISmIQQQgghxBVht9s5efIk+fn55d0VcZ3w8/OjSpUqaLXai96HBCYhhBBCCFHm3G43R44cQa1WExUVhVarveRv/oUojaIo2O120tPTOXLkCLVr1z7r4rRnI4FJCCGEEEKUObvdjtvtJiYmBj8/v/LujrgOGAwGNBoNR48exW63o9frL2o/UvRBCCGEEEJcMRf7Lb8QF+NyvN/kHSuEEEIIIYQQpZDAJIQQQgghhBClkMAkhBBCCCHERUpMTESlUrFt27by7oooIxKYhBBCCCGEuErMmzeP4ODg8u6GOI0EJiGEEEIIIa4xLpcLt9td3t24JkhgEkIIIYQQ4hzcbjdTpkyhVq1a6HQ6qlWrxmuvvVZsu5JGiBYvXuy15tT27dvp3LkzAQEBBAYG0qJFCzZt2sTKlSsZOHAgubm5qFQqVCoV48ePBwrLsj/33HNER0fj7+9PmzZtWLlyZbHj/vTTTzRo0ACdTsfRo0fL4qW47sg6TEIIIYQQQpzDiy++yOzZs3nnnXe44YYbOHnyJHv37r2offXt25dmzZoxY8YM1Go127ZtQ6PR0L59e959911eeeUV9u3bB4DRaARg4MCBJCYm8vXXXxMVFcUPP/zA7bffzs6dO6lduzYA+fn5TJ48mTlz5hAWFkZERMTlefLXOQlMQgghhBBCnEVeXh7vvfceH374If379wegZs2a3HDDDSQmJl7w/pKSknj22WepV68egCfwAAQFBaFSqahcubKn7dChQ3z11VccO3aMqKgoAJ555hmWLVvG3Llzef311wFwOBxMnz6d+Pj4i32qogQSmIQQQgghhDiLPXv2YLPZuOWWWy7L/p5++mkGDx7M559/zq233sp9991HzZo1S91+y5YtKIpCnTp1vNptNhthYWGe21qtliZNmlyWPor/SGASQgghhBDiLAwGw3lv6+Pjg6IoXm0Oh8Pr9vjx4+nTpw8///wzv/76K+PGjePrr7+mZ8+eJe7T7XajVqvZvHkzarXa676iKXtF/Tz9WilxeUjRByGEEEIIIc6idu3aGAwG/vjjj3NuGx4eTl5eHhaLxdNW0hpNderUYfTo0SxfvpxevXoxd+5coHCUyOVyeW3brFkzXC4XaWlp1KpVy+vn9Kl7omxIYBJCCCGEEOIs9Ho9zz//PM899xzz58/n0KFDrFu3jk8++aTYtm3atMHPz4+XXnqJgwcP8uWXXzJv3jzP/QUFBYwaNYqVK1dy9OhR/v33XzZu3Ej9+vUBiI2NxWw288cff5CRkUF+fj516tShb9++PPLII3z//fccOXKEjRs3MmXKFH755Zcr9TJctyQwCSGEEEIIcQ5jx45lzJgxvPLKK9SvX58HHniAtLS0YtuFhobyxRdf8Msvv9C4cWO++uorT2lwALVaTWZmJo888gh16tTh/vvvp1u3bkyYMAGA9u3bM2zYMB544AHCw8N58803AZg7dy6PPPIIY8aMoW7dutx1112sX7+emJiYK/L8r2cq5cxJltcwk8lEUFAQubm5BAYGlnd3hBBCCCGuG1arlSNHjhAXF4dery/v7ojrxNned+ebDWSESQghhBBCCCFKIYFJCCGEEEIIIUohgUkIIYQQQgghSiGBSQghhBBCCCFKIYFJCCGEEEIIIUohgUkIIYQQQgghSiGBSQghhBBCCCFKIYFJCCGEEEIIIUohgUkIIYQQQgghSiGBSQghhBBCCCFKIYFJCCGEEEJUKCaLlcSULHYeOUliShYmi/WKHHf69OnExcWh1+tp0aIFf//99xU5rihfvuXdASGEEEIIIc5XSlYek75Yzto9SZ62dvWrM/bh26gcGlBmx124cCFPPfUU06dPp0OHDsyaNYtu3bqRkJBAtWrVyuy4ovzJCJMQQgghhKgQTBZrsbAEsHbPUSZ9saJMR5refvttBg0axODBg6lfvz7vvvsuMTExzJgxo8yOKa4OEpiEEEIIIUSFkJWXXywsFVm75yhZefllcly73c7mzZvp0qWLV3uXLl1Ys2ZNmRxTXD0kMAkhhBBCiAohr8B21vvN57j/YmVkZOByuYiMjPRqj4yMJCUlpUyOKa4eEpiEEEIIIUSFEGDQnfV+4znuv1QqlcrrtqIoxdrEtUcCkxBCCCGEqBBCA/xoV796ife1q1+d0AC/MjlupUqVUKvVxUaT0tLSio06iWuPBCYhhBBCCFEhBPrrGfvwbcVCU7v61Xml320E+uvL5LharZYWLVqwYsUKr/YVK1bQvn37MjmmuHpIWXEhhBBCCFFhVA4NYPKgO8jKy8dcYMNo0BEa4FdmYanI008/Tb9+/WjZsiXt2rXj448/JikpiWHDhpXpcUX5k8AkhBBCCCEqlEB/fZkHpDM98MADZGZmMnHiRE6ePEmjRo345ZdfqF695CmC4tohgUkIIYQQQojzMGLECEaMGFHe3RBXmFzDJIQQQgghhBClkMAkhBBCCCGEEKWQwCSEEEIIIYQQpZDAJIQQQgghhBClkMAkhBBCCCGEEKWQwCSEEEIIIYQQpaiwgWny5MmoVCqeeuqp8u6KEEIIIYQQ4hpVIQPTxo0b+fjjj2nSpEl5d0UIIYQQQghxDatwgclsNtO3b19mz55NSEhIeXdHCCGEEEIIcQ2rcIFp5MiRdO/enVtvvfWc29psNkwmk9ePEEIIIYQQQpyvChWYvv76a7Zs2cLkyZPPa/vJkycTFBTk+YmJiSnjHgohhBBCiLJmsueTaE5nV04yR83pmOz5ZXq81atXc+eddxIVFYVKpWLx4sVlejxxdfEt7w6cr+TkZJ588kmWL1+OXq8/r8e8+OKLPP30057bJpNJQpMQQgghRAWWWpDLa7u+Z13mAU9b27DavNyoF5GGoDI5psViIT4+noEDB9K7d+8yOYa4elWYwLR582bS0tJo0aKFp83lcrF69Wo+/PBDbDYbarXa6zE6nQ6dTneluyqEEEIIIcqAyZ5fLCwBrMs8wGu7vufV+AcI1Ppd9uN269aNbt26Xfb9ioqhwgSmW265hZ07d3q1DRw4kHr16vH8888XC0tCCCGEEOLakmW3FAtLRdZlHiDLbimTwCSubxUmMAUEBNCoUSOvNn9/f8LCwoq1CyGEEEKIa4/Zab2k+4W4GBWq6IMQQgghhLh+GX3Pfh37ue4X4mJUmBGmkqxcubK8uyCEEEIIIa6QUK0/bcNqlzgtr21YbUK1/uXQK3GtkxEmIYQQQghRIQRq/Xi5US/ahtX2ai+qkifXL4myUKFHmIQQQgghxPUl0hDEq/EPkGW3YHZaMfrqCdX6l2lYMpvNHDx40HP7yJEjbNu2jdDQUKpVq1ZmxxVXBwlMQgghhBCiQgnU+l3R0aRNmzbRuXNnz+2idT779+/PvHnzrlg/RPmQwCSEEEIIIcRZdOrUCUVRyrsbopzINUxCCCGEEEIIUQoJTEIIIYQQQghRCglMQgghhBBCCFEKCUxCCCGEEEIIUQoJTEIIIYQQQghRCglMQgghhBBCCFEKCUxCCCGEEEIIUQoJTEIIIYQQQghRCglMQgghhBBCCFEKCUxCCCGEEEKIi5aYmIhKpWLbtm3n/ZgBAwZwzz33XNJxV65ciUqlIicn55L2cy4SmIQQQgghhDiLTp068dRTT5V3N65YQBDeJDAJIYQQQghxCRRFwel0lnc3RBmRwCSEEEIIIUQpBgwYwKpVq3jvvfdQqVSoVCrmzZuHSqXit99+o2XLluh0Ov7+++8Sp5k99dRTdOrUyXNbURTefPNNatSogcFgID4+nm+//fac/UhMTKRz584AhISEoFKpGDBgAPPnzycsLAybzea1fe/evXnkkUcAGD9+PE2bNmXWrFnExMTg5+fHfffdV2ykau7cudSvXx+9Xk+9evWYPn36hb9ggMvlYtCgQcTFxWEwGKhbty7vvfdeidtOmDCBiIgIAgMDGTp0KHa73XPfxb5Wl5vvFT+iEEIIIYQQFcR7773H/v37adSoERMnTgRg9+7dADz33HO89dZb1KhRg+Dg4PPa3//+9z++//57ZsyYQe3atVm9ejUPP/ww4eHhdOzYsdTHxcTE8N1339G7d2/27dtHYGAgBoMBrVbLE088wZIlS7jvvvsAyMjI4KeffmLZsmWexx88eJBFixaxdOlSTCYTgwYNYuTIkSxYsACA2bNnM27cOD788EOaNWvG1q1bGTJkCP7+/vTv3/+CXjO3203VqlVZtGgRlSpVYs2aNTz22GNUqVKF+++/37PdH3/8gV6v56+//iIxMZGBAwdSqVIlXnvttUt6rS43CUxCCCGEEEKUIigoCK1Wi5+fH5UrVwZg7969AEycOJHbbrvtvPdlsVh4++23+fPPP2nXrh0ANWrU4J9//mHWrFlnDQFqtZrQ0FAAIiIivAJanz59mDt3ricwLViwgKpVq3qNbFmtVj777DOqVq0KwAcffED37t2ZNm0alStXZtKkSUybNo1evXoBEBcXR0JCArNmzbrgwKTRaJgwYYLndlxcHGvWrGHRokVegUmr1fLpp5/i5+dHw4YNmThxIs8++yyTJk2ioKDgol+ry00CkxBCCCGEEBehZcuWF7R9QkICVqu1WMiy2+00a9bsovsxZMgQWrVqxfHjx4mOjmbu3LkMGDAAlUrl2aZatWqesATQrl073G43+/btQ61Wk5yczKBBgxgyZIhnG6fTSVBQ0EX1aebMmcyZM4ejR49SUFCA3W6nadOmXtvEx8fj5+fn1Sez2UxycjJpaWll8lpdDAlMQgghhBBCXAR/f3+v2z4+PiiK4tXmcDg8/3a73QD8/PPPREdHe22n0+kuuh/NmjUjPj6e+fPn07VrV3bu3MnSpUvP+piiMKVSqTz9mj17Nm3atPHaTq1WX3B/Fi1axOjRo5k2bRrt2rUjICCAqVOnsn79+vN6/Ol9utyv1cWQwCSEEEIIIcRZaLVaXC7XObcLDw9n165dXm3btm1Do9EA0KBBA3Q6HUlJSRc1pUyr1QKU2JfBgwfzzjvvcPz4cW699VZiYmK87k9KSuLEiRNERUUBsHbtWnx8fKhTpw6RkZFER0dz+PBh+vbte8H9OtPff/9N+/btGTFihKft0KFDxbbbvn07BQUFGAwGANatW4fRaKRq1aqEhIRc0mt1OUlgEkIIIYQQ4ixiY2NZv349iYmJGI1Gz+jHmW6++WamTp3K/PnzadeuHV988QW7du3yTCELCAjgmWeeYfTo0bjdbm644QZMJhNr1qzBaDSe81qh6tWro1Kp+Omnn7jjjjswGAwYjUYA+vbtyzPPPMPs2bOZP39+scfq9Xr69+/PW2+9hclk4oknnuD+++/3XJc1fvx4nnjiCQIDA+nWrRs2m41NmzaRnZ3N008/fUGvV61atZg/fz6//fYbcXFxfP7552zcuJG4uDiv7ex2O4MGDeJ///sfR48eZdy4cYwaNQofH59Lfq0uJykrLoQQQgghxFk888wzqNVqGjRoQHh4OElJSSVu17VrV8aOHctzzz1Hq1atyMvL85T2LjJp0iReeeUVJk+eTP369enatStLly4tFiZKEh0dzYQJE3jhhReIjIxk1KhRnvsCAwPp3bs3RqOxWGlzKAwxvXr14o477qBLly40atTIq2z44MGDmTNnDvPmzaNx48Z07NiRefPmnVe/zjRs2DB69erFAw88QJs2bcjMzPQabSpyyy23ULt2bW666Sbuv/9+7rzzTsaPH++5/1Jeq8tJpZw50fIaZjKZCAoKIjc3l8DAwPLujhBCCCHEdcNqtXLkyBHi4uLQ6/Xl3Z1r0m233Ub9+vV5//33vdrHjx/P4sWL2bZtW/l0rByd7X13vtlApuQJIYQQQghRgWVlZbF8+XL+/PNPPvzww/LuzjVHpuQJIYQQQghxFRg2bBhGo7HEn2HDhpX6uObNmzN06FCmTJlC3bp1L3u/Xn/99VL71a1bt8t+vKuNTMkTQgghhBBlTqbknVtaWhomk6nE+wIDA4mIiLjCPSqUlZVFVlZWifcZDIZiZb+vJjIlTwghhBBCiGtEREREuYWiswkNDSU0NLS8u1FuZEqeEEIIIYQQQpRCApMQQgghhBBClEICkxBCCCGEEEKUQgKTEEIIIYQQQpRCApMQQgghhBBClEICkxBCCCGEEEKUQgKTEEIIIYSoUEwmE4mJiezatYvExMRS1y66XAYMGMA999zj1fbtt9+i1+t58803y/TYovzJOkxCCCGEEKLCSE1NZdKkSaxbt87T1rZtW8aOHUtkZOQV6cOcOXMYOXIkH330EYMHD74ixxTlR0aYhBBCCCFEhWAymYqFJYB169YxadKkMh9pAnjzzTcZNWoUX375pScsFY1AvfXWW1SpUoWwsDBGjhyJw+HwPC47O5tHHnmEkJAQ/Pz86NatGwcOHABAURTCw8P57rvvPNs3bdrUaxHbtWvXotFoMJvNAKhUKubMmUPPnj3x8/Ojdu3aLFmypMyf//VIApMQQgghhKgQsrKyioWlIuvWrSMrK6tMj//CCy8wadIkfvrpJ3r37u11319//cWhQ4f466+/+Oyzz5g3bx7z5s3z3D9gwAA2bdrEkiVLWLt2LYqicMcdd+BwOFCpVNx0002sXLkSKAxXCQkJOBwOEhISAFi5ciUtWrTAaDR69jlhwgTuv/9+duzYwR133EHfvn3L/DW4HklgEkIIIYQQFULR6MrF3n8pfv31V6ZMmcKPP/7IrbfeWuz+kJAQPvzwQ+rVq0ePHj3o3r07f/zxBwAHDhxgyZIlzJkzhxtvvJH4+HgWLFjA8ePHWbx4MQCdOnXyBKbVq1cTHx/PzTff7GlbuXIlnTp18jrmgAEDeOihh6hVqxavv/46FouFDRs2lNVLcN2SwCSEEEIIISqE00dXLub+S9GkSRNiY2N55ZVXyMvLK3Z/w4YNUavVnttVqlQhLS0NgD179uDr60ubNm0894eFhVG3bl327NkDFAam3bt3k5GRwapVq+jUqROdOnVi1apVOJ1O1qxZQ8eOHYv1qYi/vz8BAQGeY4rLRwKTEEIIIYSoEEJDQ2nbtm2J97Vt25bQ0NAyO3Z0dDSrVq3i5MmT3H777cVCk0aj8bqtUqlwu91A4TVKJVEUBZVKBUCjRo0ICwtj1apVnsDUsWNHVq1axcaNGykoKOCGG24472OKy0cCkxBCCCGEqBACAwMZO3ZssdBUVCUvMDCwTI9frVo1Vq1aRVpaGl26dDnvIhMNGjTA6XSyfv16T1tmZib79++nfv36AJ7rmH788Ud27drFjTfeSOPGjXE4HMycOZPmzZsTEBBQJs9LnJ2UFRdCCCGEEBVGZGQkr7/+OllZWZjNZoxGI6GhoWUelopUrVqVlStX0rlzZ7p06cJvv/12zsfUrl2bu+++myFDhjBr1iwCAgJ44YUXiI6O5u677/Zs16lTJ0aPHk2zZs08z+emm25iwYIFPP3002X2nMTZyQiTEEIIIYSoUAIDA4mNjaVRo0bExsZesbBUpGh6Xk5ODrfddhs5OTnnfMzcuXNp0aIFPXr0oF27diiKwi+//OI1ra5z5864XC6v4g4dO3bE5XIVu35JXDkqpbRJldcgk8lEUFAQubm5V/yDJYQQQghxPbNarRw5coS4uDj0en15d0dcJ872vjvfbCAjTEIIIYQQQghRCglMQgghhBBCCFEKCUxCCCGEEEIIUQoJTEIIIYQQQghRCglMQgghhBBCCFEKCUxCCCGEEEIIUQoJTEIIIYQQQghRCglMQgghhBBCCFEKCUxCCCGEEEIIUQoJTEIIIYQQQlQAiYmJqFQqtm3bVt5dua5IYBJCCCGEEBVKVlbWWW9fbgMGDEClUvHGG294tS9evBiVSlWmxxblTwKTEEIIIYSoMJKTk3nmmWdITk723B4zZozndlnR6/VMmTKF7OzsMj2OuPpIYBJCCCGEEBVCVlYWr7zyCjt27GDYsGFs2rSJYcOGsXPnTsaNG1emI0233norlStXZvLkyaVu891339GwYUN0Oh2xsbFMmzbNc9+LL75I27Ztiz2mSZMmjBs3znN77ty51K9fH71eT7169Zg+ffrlfSLigklgEkIIIYQQFUJoaCgTJ04kMjKS1NRUhg0bRmpqKpGRkUyYMIHQ0NAyO7Zareb111/ngw8+4NixY8Xu37x5M/fffz8PPvggO3fuZPz48YwdO5Z58+YB0LdvX9avX8+hQ4c8j9m9ezc7d+6kb9++AMyePZuXX36Z1157jT179vD6668zduxYPvvsszJ7XuLcJDAJIYQQQogKIyYmhgkTJni1TZgwgZiYmDI/ds+ePWnatKnXiFCRt99+m1tuuYWxY8dSp04dBgwYwKhRo5g6dSoAjRo1okmTJnz55ZeexyxYsIBWrVpRp04dACZNmsS0adPo1asXcXFx9OrVi9GjRzNr1qwyf26idBKYhBBCCCFEhZGcnFwssIwbN67Mr2EqMmXKFD777DMSEhK82vfs2UOHDh282jp06MCBAwdwuVxA4SjTggULAFAUha+++sozupSenk5ycjKDBg3CaDR6fl599VWvUSlx5UlgEkIIIYQQFULRNUxF0/BmzpzpmZ5X1tcwFbnpppvo2rUrL730kle7oijFKuYpiuJ1u0+fPuzfv58tW7awZs0akpOTefDBBwFwu91A4bS8bdu2eX527drFunXryvAZiXPxLe8OCCGEEEIIcT6KrmEaN26cZxrezJkzeeWVV8r8GqbTvfHGGzRt2tQzlQ6gQYMG/PPPP17brVmzhjp16qBWqwGoWrUqN910EwsWLKCgoIBbb72VyMhIACIjI4mOjubw4cOeUSdxdZDAJIQQQgghKoyYmBjeeustTziKiYlh2rRpVywsATRu3Ji+ffvywQcfeNrGjBlDq1atmDRpEg888ABr167lww8/LFblrm/fvowfPx673c4777zjdd/48eN54oknCAwMpFu3bthsNjZt2kR2djZPP/30FXluojiZkieEEEIIISqUM8PRlQxLRSZNmuQ15a558+YsWrSIr7/+mkaNGvHKK68wceJEBgwY4PW4++67j8zMTPLz87nnnnu87hs8eDBz5sxh3rx5NG7cmI4dOzJv3jzi4uKuwDMSpVEpZ06uvIaZTCaCgoLIzc0lMDCwvLsjhBBCCHHdsFqtHDlyhLi4OPR6fXl3R1wnzva+O99sICNMQgghhBBCCFEKCUxCCCGEEEIIUQoJTEIIIYQQQghRCglMQgghhBBCCFEKCUxCCCGEEOKKuY7qjYmrwOV4v0lgEkIIIYQQZU6j0QCQn59fzj0R15Oi91vR++9iyMK1QgghhBCizKnVaoKDg0lLSwPAz88PlUpVzr0S1ypFUcjPzyctLY3g4GDUavVF70sCkxBCCCGEuCIqV64M4AlNQpS14OBgz/vuYklgEkIIIYQQV4RKpaJKlSpERETgcDjKuzviGqfRaC5pZKmIBCYhhBBCCHFFqdXqy3IiK8SVIEUfhBBCCCGEEKIUEpiEEEIIIYQQohQSmIQQQgghhBCiFBKYhBBCCCGEEKIUEpiEEEIIIYQQohQSmIQQQgghhBCiFBKYhBBCCCGEEKIUEpiEEEIIIYQQohQSmIQQQgghhBCiFBKYhBBCCCGEEKIUEpiEEEIIIYQQohQSmIQQQgghhBCiFBKYhBBCCCGEEKIUFSYwzZgxgyZNmhAYGEhgYCDt2rXj119/Le9uCSGEEEIIIa5hFSYwVa1alTfeeINNmzaxadMmbr75Zu6++252795d3l0TQgghhBBCXKNUiqIo5d2JixUaGsrUqVMZNGjQeW1vMpkICgoiNzeXwMDAMu6dEEIIIYQQ4mp1vtnA9wr26bJxuVx88803WCwW2rVrV+p2NpsNm83muW0yma5E94QQQgghhBDXiAozJQ9g586dGI1GdDodw4YN44cffqBBgwalbj958mSCgoI8PzExMVewt0IIIYQQQoiKrkJNybPb7SQlJZGTk8N3333HnDlzWLVqVamhqaQRppiYGJmSJ4QQQgghxHXufKfkVajAdKZbb72VmjVrMmvWrPPaXq5hEkIIIYQQQsD5Z4MKNSXvTIqieI0gCSGEEEIIIcTlVGGKPrz00kt069aNmJgY8vLy+Prrr1m5ciXLli0r764JIYQQQgghrlEVJjClpqbSr18/Tp48SVBQEE2aNGHZsmXcdttt5d01IYQQQgghxDWqwgSmTz75pLy7IIQQQgghhLjOVOhrmIQQQgghhBCiLElgEkIIIYQQQohSSGASQgghhBBCiFJIYBJCCCGEEEKIUkhgEkIIIYQQQohSSGASQgghhBBCiFJIYBJCCCGEEEKIUkhgEkIIIYQQQohSSGASQgghhBBCiFJIYBJCCCGEEEKIUkhgEkIIIYQQQohSSGASQgghhBBCiFJIYBJCCCGEEEKIUkhgEkIIIYQQQohSSGASQgghhBBCiFJIYBJCCCGEEEKIUkhgEkIIIYQQQohSSGASQgghhBBCiFJIYBJCCCGEEEKIUkhgEkIIIYQQQohSSGASQgghhBBCiFJIYBJCCCGEEEKIUkhgEkIIIYQQQohSSGASQgghhBBCiFJIYBJCCHHF2V0ODuelkm0zA6AoConmdNKtpnLumRBCCOFNApMQQogryu5ysC37KH3XfMDMg7+Ta8/nkDmVQetmMHb7QglNQgghriq+5d0BIYQQ1xery8HOnCRcipsfkjdwsiCb3TnJ5DmtJFrSsboc5d1FIYQQwkMCkxBCiCsqUOvHvdXa4lLczDn0J+syDgAQqjUyq/UQYvzDyrmHQgghxH9kSp4QQogrLlBj4NbKjb3aGgRFE6z1L6ceCSGEECWTwCSEEOKKUhSFQ+ZUhqyf5dX+T/o+ph9Y7ikEIYQQQlwNJDAJIYS4okyOAr5K/Ic8p5VQrZHvbhzD4Jo3A/Dz8S2YnAXl3EMhhBDiP3INkxBCiCsqSOvHiDpdUat86Bt7IzH+YTxQvT2+Kh9ahtUk2hBS3l0UQgghPFSKoijl3YkrxWQyERQURG5uLoGBgeXdHSGEuK6Z7AUEag3/3XYU4KfW4Osj3+UJIYQoe+ebDeR/JSGEEOXi9LAEhYUghBBCiKuNBCYhxDVHURQybHlk28043G5Cdf6EaQPQquVPnhBCCCEujJw9CCGuKU63iz2m47y49UvSbCYA9GoNI2p3pVtUU4K0fuXcQyGEEEJUJFIlTwhxTUmx5jJiwyeesARgdTl4e+9P7MpJLseeCSGEEKIiksAkhLimrEzdjc3tKPG+GQeWk22XNX6EEEIIcf4kMAkhrhmKopx1FOmoJQO7y3UFeySEEEKIik4CkxDimqFSqWgYVLXU+6v5V0KrVl/BHgkhhBCiopPAJIS4pnSu3BBdKev4DK99GyFa4xXukRBCCCEqMglMQohrSmV9MB+1GkS47r8F6HQ+GkbX607j4Grl2DMhhBBCVERSVlwIcU3x9VHTOLgac9sNJ9tuwel2Eao1EqozolNryrt7QgghhKhgJDAJIa45KpWKCH0QEfqg8u6KEEIIISo4mZInhBBCCCGEEKWQwCSEEEIIIYQQpZDAJIQQQogKw624ybFbvNqy7WYcblljTQhRNiQwCSGEqNCcbhfpVhNmR4GnLaUgh2yb5SyPEhWRW3FzMC+VR9fNINGcBsDx/CyGrp/N7pxkCU1CiDIhgUkIIUSF5XS72J2bTM/Vb7H85A7ynTYSzWn0X/sRsw/+IaHpGmNyFPDc1i84lp/FY+tnsznrMCM3fkKiJZ0xW+ZjcVrLu4tCiGuQBCYhhLjO2F3Os96uSPKcVhYmrsXudvJGwo/MOLCCoRtmk223sDxlO/kuGwA2l4O9ucfJtOWVc4/FpQjS+DGteT8CNQZyHBaGb5jDiYJsdD4a3m05AKOvvry7KIS4BklgEkKI68hhcypbs49gczmAwqlrf6TsJO+06WwVSYjWnzENenBjeH0AFh5dQ7bdQqDGwIQm97M2fT8mRwFbso4wcN0Mpu356YqGJqfbRZbNTL7T7mlLt5rItedf8r4tTpvX7fwzbl+LVCoVNYyRvBb/oFf7mPo9aBBYFV8fdTn1TAhxLZPAJIQQ14lEczpD189mddoe9ptOklqQy5Ob5rEiZScJuce8rgGqSMJ0AYys08Wr7ebIRhzIO8mbe5bw4tYveXrLfFyKmyRLBi7FfUX65XS72Gs6zj2rp7I2Yx9Wl4MkSwaPrP2IhUfXnDU05ZxadLlIls1MwWmh66glne+S1nn2kVqQw5yDf14XI2gnCrKZvHuxV9v0/ctJzs8onw4JIa55EpiEEOI6YfDV0j/uJoK1/hw0pzD74B9U9Qvl1sqN2J17rMJeMJ9oTmP4xjlebYuPbUSr8uW+am3ZmHUIl+KmTkAVprV45KIXNHYpbrLPqM52ZrW20+U5rXx84A+sLgcvbfuaL46sZuiG2WTa8vjq6L9YXfYSH3fEnEa/NR+y13QCl9tFSkEOIzZ+wtqM/RQ47aQU5DBs/Ww+3P8bCxL/JtOWx9Ob5/NF4t+8mbCEbJv5op5fRZBtt/DU5s880/BeaHC3Z3resA1ziv1+hBDicpDAJIQQ14lKWiORhmBmH/yDN3b/SIPgqnSu3JBJu75n5oEV/JO+D7u7Yl3PlGO3FIaEU9PwPm8/yjM978P9v3FP1VYEafwAaBFaA4Nae1HHcSlu9ptO8sLWBaRZcwFItmQyevNnJFlKHtkI0foztnFvmoXEoaDw8cE/yLTl4e+r4+PWjxGuDyz2mGy7hfE7viHVmsvwDXP4N30fT26ax2FzKq/sWES+y4bOx5fOkY0AmHd4FfesmsoBcwpqlQ+9Ylrj76u7qOdYEfirdbzQ4G78fXXMaD2Iu6q2ZFbrIQRp/Hi2wZ3ofDTl3UUhxDVIpSiKUt6duFJMJhNBQUHk5uYSGFj8PyohhLjWncjP4uXtX7M795hXe72AKKa26EfkRY6+lKeUghzG7VjEcw3uooYxkgxbHm8lLOXmKo34+fgWNmYe8kzDG1rrVu6r3pbAUyHqfOXYLfRaPQ2z00q9gCjGNbmPJzfPI82aSzW/MGa3HUaI1r/Exx7KS+Whf9/z3O4XdyODa96Cwbfk8HY8P4sRG+dwsiDH0+arUvNBy4E0Dq6GVu1Ljt3CO3t/5tcT2zzbvNuiPy1Da6BVX9uhwe5yku+yYfTV4+ujRlEUchwWdD5a/Ep5TYUQoiTnmw1khEkIIa4TKQU5vLD1S0bVvZ3K+mBPe5gugNeaPkTwBYaIq0VlQzBTmvWlhjESlUqFWuVDt+im/Hx8C1k2Mz93eoG7olsA8G3yemwXURXQoNbyavwDqFU+7M07wUP/vkeaNReDWsuk+AcI1BhKfNxRSwajNn3q1fbFkX9Yk7HPqxDE6aL9QpnW/BGvtoE1OtHoVFiCwqp/B0wpXttsyz5KwaliHtcyrdqXYK2/p8CDSqUiRGuUsCSEKDMSmIQQ4jrhcDupERBJSkEO6TaTpz3LZmZP7jEKSrmm5kpzKW5SC3I4mJdCkiUD03lUlAvW+qNSqQAI1RlpGBRDlD6Eac37EaozMqJOV/rF3cis1kNKnAp3Ljq1hpahNXiq7h1e7W8260udwCjUquL/nebYLUzc+a1nGt6cNkM90/PGbl9EfilrBqUU5PDytq+92uYfWc2BvJM43S5SC3J5evN8Dp6ahtc4OAaAeYdXsiDxH3IuQwU+IYQQ/5HAJIQQVwGzw0qWzUzRLGm7y0m23XJZ10iqYgjh9irxvLrre1yKm9rGytQPjC48gd+xiN05yeW+JpPJkc8vx7fy8JoP6fPv+/T5932e27qAZEvmBe0nXB/I43VvJ9IQDBSGqIE1OlPNv9JF9y3VauLzxL+92j7a91uplemCtf5MbHI/tQOqMKv1YzQKjuH1pg9yf7V2TGvejwCN4VTJ8f/KgWfbLby07SuOWNLwVakZ26g3VQzB2NwOhm+YQ44jHx+ViiCtH2qVD++06M/bzftzb0xbACL0gahPBUchhBCXhwQmIYQoZ2aHld9TdvLAP+9wxJKGw+1kR85R7l71Jjtzki5biPH1UVPVP4xwXSB1A6J4u2V/pjZ/mMbB1QjTGYnxr+SZ8lUebC4HVpeDX05sJdeRT52AKnzWbiRV/UIZvnEOqQW5F7Q/f433IqZGzcUvapppy2P4xjmeaXgDa3TyTM97dssXZJVSmS7aL5QPWz1KrYBIkvOzGLRuJrdWaUyzkFhy7Pk8sWku/6bv84SmII2BFxreQ7DGnw9aDuT2qHimtxpMlCGEZxvcid5HQ7g+kAlN7md2m6E0D4klSOvHkFo3M6v1EG6v0pSAUqYHCiGEuDhS9EEIIcpZls3Mg/+8R47DQpDGwMAanflw/284FRd1AqL4oNUAQrTGy3a84/lZ+PqoPQUe0q0mrC4HMf5hl+0YF8rmcrAh8yAvbfuacY3vZUv2EdpVqs0rOxbxWK1bOJSXyk0RDbgpsj7pVhO+PmpPkYVMWx6KolDpIqbana88RwE/Hd/CzAMrmNl6CDWMEWzOOswzW77gjWZ9aBVW86wV+HLsFp7Z8jk7cpLQ+fjyWvxDfHxgBftPTatb0vE5z1RBt+LG5CjAT63zBNgsmxmtj+8lhb6rTZ6jwCvcmR3Wa+r5CSGufuebDSQwCSHEVeCIOY2h62eT4/hvHZka/hG823IAlU9NK7uWZdvNDFs/hyOWNDQqNf1rdOSrxH+xuGyE6wKZ1rwfq9P2cHfVljy9eT7NQuMYXOtmXIqbKQk/YnHYmNDkvjIPTVaXg1CdEbXKB5vLgdlpxc9Xd17lyk/kZzFy46ccL8jytBVNq2seEnvNV7c7XZIlg2+OrmVgzc6E6oykWnP5+MDvDK1960WvkyWEEBdKquQJIUQFUtUvlEdrdvJqe6HhPeVa5tvsKPCaamZ3OcpsUdQQrZFpzftRzb8SDsXFnEN/esLS2Ma9eH7bApqHxLE6bQ8HzCksSlrL9P3Lmbx7MStTE9iYdYiE3GOe8uFlIUBjIFwf6CnwoFNrCNMFnPfaTlF+obzTor9XW9/YG2h2nYWlTFsewzbMZmHSWt7e8xNZNjPPbP6cpcc38+K2L0ud3iiEEOVFApMQQpQzu8vJ9uwk3t+3zKv92a2fc8SShrMcCjGYHQUsP7mDaXuWkmUzY3c52JZ9lDFbPvcs3Hq5VTYEM7JOV6+2h2I7sOzEdrJsZqr4hXBblSb0r9ERgMXHNrI6bQ8Az9a/k+ahNUqsVne1SC3I5X/bvavfLTy6hn2mEzjdrover83lINv+X8hwK25y7JazPKJ8aX186Rt7AwDLU3Zwx1+T2Zd3ArXKh0E1b7mmF94t4nS7iv2OcqW6oRBXrav3fxYhhLhO5LtsPLNlPk7FRQ1jBDNaDyZY40+uo4Dnt35Jii33ip9MpVhzeSPhR1ak7GTanqWszzzIk5vnsSs3mY/2LyfPUXBZj2d12knOz2Tijm8BqB1QmdH1uvPxgd+5MaIeH7cZSqQ+iGCtPw/H3kiw5r9FYmP9w+lSJf6qvv4l225h/I5F7M87iVrlw4sN7yHaEIrN7WTkxk/IshcfVcmw5pFoTsN9atQsx27hsDkV22lrLdlcDjZlHmZqwlIybWbcipsDeSk8v2UBqactfHs1CdAYuKtqSwacCr5uCq8MeD3+IVqExqG7ykbbUq25pJ/2JUGWLY+US3htnW4X+/NOMm3PUk+FxWRLBmN3LLyk/V4pWbY8dmQnUXBqHTGTI5+tWUcwOSTwiWuXBCYhhChn/r563mnRn3qBUTxT/042pB/g/ZYDiPOP4KWG9zDn4J/8fHzLFR01iNQHMbpedwBWpOxkzJbPcSluahojGV77trNWYnOdMVpyrtETm8vB1uxElh7bRN+4G2kZWoOXG/UiIfcYLzS8hykJP1LFEIyvj5pMWx6v7f7e61qvREs6Hx/8neyreFQlWOPH0/V7EKTx450W/eke1ZyPWj1KtCGUJ+p2KzatL8Oax6u7vmPg2hkcyEvB5Mjns8Or6PvvB2zOOuwJTZk2M2O2zOf3lJ1MTVjCntzjDFs/m605ibyx+8dLDtpZNjOJ5nTP79Bkz+eoOR1rKYvunq98l5216Qe82v5M2YXltBLrV4NUay7PbP6cF7d9Rbo1lyxbHlP3/MTQDR9zLD/r3DsoQY7dwrANs/nt5A4m715MkiWDYRvmsC7jAP/bvvCqfh9nnnr+Q9bPYk3GfkyOfBYdXcfQDbNZdHSdjJKJa5YUfRBCiKuA49QUnX/T9mFTHMT5R+Dvq2Ppsc00CalOdf9KVPcPv6KjKGZHARN2fsuqU9PeVKj4ufMLVNIFlPoYi9PK5qwj1A2IItIQhMPtIiH3GMEaP6obw0t8zMG8FPqt+RCX4qZPbAe6RTVj+IY5mJ1W7opuSb8aNxJtCMWtuFl4dC0f7C+cuvh0ve6k2/L4/MhqoHCEonPlhlfttDxFUch15GNQaz2jKJk2M1ofdbEAejw/i8fWf0y6zYS/WkfT0Fj+Td8HFF731L9GR4y+elKtufyTvpdpe37yeny4LpCZrQcTcwnrTmXZzLyz52dWpScwo/VgqvlV4ruk9cw4sIIpzfrQNqw2et/zu37rdOlWE2M2z2fvqWl4bcNq829G4XPrWjme0fW7E6q7fFUhL5ZbcbMx8xBPbJqHgkKjoBhCdUbPNNBXGvXm1ipN0F/giFjRdNc3En70avdX65jZZgi1Ayrjc5W+h9OtJl7e/hXbso+iQkV8SHW2ZScCcFd0C0bU6XpV/O6EOF9S9EEIISoQjY8avVqDxWVj2p6fmLbnJ+xuJw2DY5i481tGb55f6gKpZcHucpCQe5x/Tp2kAygovLPnp1L7YXFaWZ26h2e2fM7ozZ+RZs1ld04yIzbMYeiG2Rw1p5f4uDCtkTujWwDwZeK/9FvzIWanlTBdAH3jbiDaEIqvjxqtWsMdUc24MbwezzW4ix7RLegXdyP9a3SkZ0xrWoRdvmuYMm15XtMOs2zmSy54oVKpCNb6e005C9MZSxyti/YLZUbrwYTrArG4bJ6w9FD1Dp6wtMd0nAf/eY9Y/3DujG7u9fjplxiWAOxuJ9tzjmJ1FS6a+9quH5h+YDkKCn+n7aXAfXGjTGqVDzUDKqNW+TCt+SNMjL+fJ+t2A6BRSAwaH/Ul9fty8VH5EB9cnTea9UGFil25yZ6wNKZ+DzpGNrjgsARg1Bi4PaopD5+6jqvIB60evarDEhQuCP1a/EPEB1dHQfEKSyMlLIlr2NX7qRRCiOuMzkdD7YDK+KrUHLGk8eK2r3ht1/e4UajiF4zhIr7Nv1jJ+Zk8uXmeZxregBqdgMLpeZ8c/LPEa5g0KjVhugDUKh8OmlN4dO0MRm78BIfiwuirK3VR3BCdkZF1utImrJanTYWKOW2GEmeMwPe0E+gwfQAvNerJ7VWaYtToCdb60zf2BobWutWzLtOlMDkKSLPm8tzWL1h2YhuZ1jyybGY+2LeMmQd/L7MqgSUJ0vjRLDTWq+2OqGYEagxYnDZWp+4h1hiOw+3iz5TdXttN3/cbmZfY18qGYKa3HkRlfTBWl4M/U3cB0D2qOSPrdL3otcFCdUYer3s7n7UbSYvQOM81TV+0H8UdUc2uqoV39b5amoXEEuv/3+hokMaP2yo3uaR+Ztry+O3kDq+2zw6vvKqn4xXRqX1pFBzj1dYirCb686wWKURFJIFJCCGuEnnOArZnH2Vck3sByLKbcaNQy1iZsY16Y/S9ctPxQrVGukc1o6Yxknda9OeRuBt5ul53QrVGHqjevsSTRa1aQ9OQ6rzXYgAqVKTZTDgUF9GGUD5o9ShVDCElHsutuEm15rIrN9nTpqDw8/EtJV4TEaYL8JqaGKz1vyzfbB82p7Ih4wA/JG9gZ04yU/cs5bvk9by39xd+PrGFH5I3sNd0gisxkz3HbmHe4ZUsP+OketiG2RzISyFAo+fhuBsZ26gXY7cv9JRg7xnTGoC/0nbzwb5fL/m6tyCNHzeE1/Vq6xXTmsBLDDWhOiN1Aqt4RtsCNAbqBEZdVWEJCgscTElYwhFLmqct15HPc1u/8CoEcSFSC3IYtmGOZ7rlPVVbArAqbQ9vJiy5oqH8Qpkc+XxzdB0LEv8BCiseAozf8Q1rM/Z7CkEIca2RwCSEEFcJh9tFhi3PqwoagF1xUuCyYz+j/WLlO21eJ2VOt6vYN9shOiMj6nTlvVML5xo1BrpHN2dBh8dLvRYJQKXyQevji+q0Nl8fNSqvFm9HLRkM3fAxFqeNMF0AN4bXA2DOoT/5Pnk9J/Ozy3xtngyriaHrZzN2xyKahcTROaKhpw+/ntwGwIjaXWgQVBWVqvTncrlYnDa+S14PFE7DW3zTM4TrAgnVGcm152NyFBCk9cPoa2Bq84dpGBTD2Ma9aBYcyzP1e6BXa7ivettLCtkmez7fJa3n21P9KDJy0yfszzt5waXQc+357Ms9gcVpBQrfh/tyT1z2YiZnrsWlKMpFhVy34mZHdhJ/pOwEYHS97rwe/xAqVOzISeK3kzuKfVbPh1bty00R9QuvWWo9hCfrdeeFBnejVvlwd9WW+F3FZdXtLidLjm8CCqfh/dTpeZqGFE7PW3h0DXb3lV8CQYgrQYo+CCHEVcLqcrAh4yDPbf0CNwqV9cFk2PIKy437R/DuqfByKfKdNtak72Nj1mGG1bqVAI2BPabjfHzgD15p3IvwS1go1+F2sTsnmVGbPsXudhKqNZLryPdM63u3xQAiDcX3n2418b/tC0nKz+CDlgM5mHeSjZmHWX5yBx+2epQvjqwmSONXpheUmxz5LDm2mff3/YpGpebzDo8zaO0MLK7Cqm31A6N5v9VAgjR+ZXL8MxWVnv4rdTd9Y28gWOvPifwsLE4bixLXMrjOLTjcTrJtFv5M3UX36Oa8sXsxO3KSeD3+QZqEVCdUa/SaznihUq25PPj3u1hcNrpHNeex2rcydP3HpFhzaB1Wi0nxD5z3NMhcez5fJP7NZ4dX8Uqj3nSMbMC/6ft4ZcciTxGL4MswpdLucrAzN5kq+mCi/EJRFIWD5lRQFGoGRF7w9UEmez7fJq/H31fHHVHN8FWpWZ95gDXp+xhWu8tFvx+z7WbynXaqGILxUflgdhSQ57QSqjVedWXVz3Q8P4slxzbxQPX2hOqMpFtNfH7kb/rGduBkQQ7V/CsRqjNidzk5aE4hXBdIuF7OucTV6XyzQckTyoUQQlw2mbY8XIqbiFNhJNeej93tLHYSUbSYpRuF+oHRvNW8H0mWDB7fNBez04rjEhY3LZJSkMPL2xeiUPit+x1RzXh801xsbgcf7vuNZxrc6ZkWlW23XNB1QTaXgyPmNOxuJ9X8K/Fhy0dJsmTw5OZ5ZNhM5LtKLhkdrg/k1fgHKHDZWJK8mc8T/+bZBndyX7W2fHLoT1al7cGg1tK/RsdLCkyKomBx2rym81kcVvw1egI1ftxdtSXZNjMx/pWYc/APT1gC2GM6zvIT27k9qukVmTbm66OmTkAVqhpCCdQWhjSNjy//pu+gU5WGTNu9lBF1u5CUn0G9oGjmH1rF2Ma9ue/vdxi7YxFfd3gSX/2lFU8I1wUws/UQfjy+icE1byZUZ2R660FM37+cp+rdcUHvDafiYr/pJAATd31Hh5Rdnsp4+0wncJ4xKnQxihZXfnLzPCrrg/mo1aNYXHaGrf8YBZjVegi1Aipf0AhhoNaP3jFtUKlUnt9727DaxAdXJ+QS3oshWiMhp13yY9QYMF5l0xFLE+0XyiM1OnoWGA7XBzKwRkf+Sd/HpF3f0SO6OU/U7cZhcxqPb/yU+kHRTG7aR0KTqNBkhEkIIcpQpi2PqQlLOZafybTm/TCodSw8uobvj21gVushVDujkpnZYWVT1mEaBEUToQ/C7nKyOzeZSrqAS656BoVh7ZuktXx88A+v9ihDCGMb9ybGEEaEIYgj5jSe27qAKc36UMMYWer+zgxVmdY89uWdIM4YQRVDCHaXg+05SYRpjcQZI7xOVl2K26uqnUtxY7Ln89aepfyesotwfSBp1lwMai0zWw+hTmCVi66CpygKh8yprM84wJ3RLQjU+nEiP5tvktbSL+4mQnVGUgpy+PXENvJdNj47vAqAPtVv4ERBFivTEgD4oOVAWofVuiLT8k6X77Txy4mtvJmwhECNgVfjHyTNmsvru37AR+XDR60epaYxknmHV9G6Ui2ah8SivQwjFW7FTZ7DSpD2v5E1kyOfwIsYacuw5jFx17esy/hv/aWWoTWY2OR+Kl2Gk2mn28Ue03FGbPgEm9tBJV0ABS47FqeNUK2RWa2HnHU6qbh4ufZ8fkjewPQDywFoGFSV/aaTOBQX1f3D+aDlwEseHReiLMgIkxBCXAXSrSZWpSXgUtyM2TyfZqFxLExaC8CSY5sYUKOT14iHUaPnxvC6qE9NpdKqfWkcXO2SpladLkjrxwPV27PXdMJTIhngzWYP89Tmefj76vlfo548u2UBOQ4Lz275gk/aDitxutQRcxr/276QN5o+RIx/JVIKcnhh65c81+AuwnWBp/qvoWlILL4qH6+QYXXa2Z5zlOr+4VQ2BGO2W0kqyMBPreWJut2opAtka/YR0qy5dIpsQIxf2CWVDD9RkM3Q9R+T57RiczvpEd2cUZs+4Vh+Fmp8uDOmBUmWDL5O/JfxTe5jjXEfN1duhFrlQ/vwOqhQofXxpXZAlSselgD8fHW0CK1BsMafHIeFZ7Z8jsPtQkGhbkBlqhhCCNT68UiNjvipNZclLEFhae3TwxJwUWEJwM9XS6eIBl6B6aaI+pftmh1fHzX1A6OZ3noQw9bPJuNU+ftgjb+EpTIWpPWjV0xrFGDGgeXszj0GIGFJXDOk6IMQQpShOGME77Toj1rlw35ziics3VO1FX1jb/CEpQKnzXMRvdpHjdPtosBVWHHqcoUlKPwWPtGSzvqMg17tC4+uYXDNm0myZDBk/cfkOCwEagy82axvidft5NgtjN78GQfyTjJswxz2mU7w1KZ5JJiO8fimTzGfurAfCteYOj1kFDjtrMs8wBOb5jF682ecyM9mt+kYwzbMZuiGwhPdMJ2RIbVuoV5gFL+e2MbS45tLLGV+vvzUWjpGNgBg5oEV9Fz1Fsfys4j1D6dLVDzD1s/mq8R/eb7h3UQZQni2wV3o1BrqBFYhx25mTP0ePFXOC6rGGSOY2XowOh8NdrcTBYXq/uE8UbcbPqde32Ct32ULS5dTvtPG32l7PYu1FoXft/f+zJ+puzyFIKDwPXrQlEK61eRpS7JkcCI/C4AMW55XoYhsu8WzNpha5YNBrUXt89/pjdZHfdWs7XQt06u1NAqq6tUWZwxH5yPfzYuKTwKTEEKUIZ1aQ4OgqjQPifO0qVU+DKt9m+caiHxn4cKk+/JO4HS7cLpdJOQeY33GAayXuUxvkiXDM2UpyhBCz6qtAFh6fDOHzWk8VusWz7ZTmvWlhjGyxBGVQI2BKU374qfWkm4z0W/Nhxy2pOGrUvNms4fxU5c+aqBW+eDvq0Ot8uGQOZVhG2bz7NbPsboc6Hw0KMBXif8ydvtCXmrYkzBdAO/t/YVcR/ES4+crRGfk8brd6HQqNDmUwnA6sckD7DedJNNuZlPWYb4++i8vbPuSxzZ8zEf7f0Pj40uH8HpEGIIIK+dFOTOsJvaYjntVIsu2m7G5HUzbvbTMKwleCqvLwZxDfwKF0/B+6fwi7SrVAWDuoZXYXIXPyel2sdd0goHrZjBu+yIybHkkWTIYumE2ozfP50R+Fv/b9jWfHPyTHLuFbLuFmQdWMH7HN2RZ8zhoTmXo+o+xuhz4++rQqNSk2UyM2PgJx08FLnH52V1OduQc5anNnwF4QtLK1ATe3/frVf3eFOJ8SGASQogSuM4osHAhJZRNp53Y59rz+TrxXzZmHfpv34qbJzbNJbUgB4fLycbMQ7y8fSHDN8xhX94JEnKPMXLjJzy/9Uu2ZicW68ulCNL60SG8LlGGEKa3GsSourczpNYtGH31tA+vyx8puzzbTt69mBRrTon78VH5UDuwMu+2GOBZ+wdgbKNe1A6oXOoitVA4zTA+OJb3WvbHBxUp1hysLgcRukBeatST57cuINNupkuVeEK0Rm6oVJdpzR8hTBdwSc+9wGnnYF6KV9s/6XsI1Oh5qt4dAGzLPsohcypqlQ+vxj9ALWMk/pqyWf/K7nJ6va8URcFaSplqq8vBHtNxJu38DgWFWP9wgjR+mBwFvLJjEf1q3oTO5+obWSoSqjPyfssB9KzaiolN7idE68/YRr3pFdOaD1o96hm5c7idpBRkY3c72ZR9mDGb5zN0/cdk2vJoHBzD+oyDbMk+wsKktcw68DvT9//GD8kbWJ95kP15J0m2ZGA+dc3SvHYjmNlmCDofXzJteWTbLVdkDa3rUY7Dwg/JGzzXLH170xgGnlrs+p/0fVicJRd8EaKikMAkhLjuZNvNpJ226KTZUUCmLc9zMpXnKGBV2h7PNnaXg+3ZR0m2ZJ5z32nWXN7Y/aPn2+zk/EzPN+v3RLfirWb9Cqfn5Z1k7uGV2BUnNQMqE6kPwupyMGTdxwzdMBub20mUIYTq/pU81zNdDmG6AJ5tcCczWw8hyi+UAI2Bu6Nb8lGrQXy4bxlptlyertcdjUpNkiWDpzfPJ9tW8jo5GbY8zE4rlfVB9I29gcr6YMJ0Acw7suqc3yj7qFTofbReo1c6tQaX4sbqstMpogEj6nQh0hBE/xodiTOGY1AXlhXLsJpIsmRc0PM+WZDtuWZJ6+NLk+DqAHx88A+OWjJoX6mO19TDaL9QmgRXu6RKaGdjdznZnpNIQu4xnG6XpyjFmvR95JdwcqlWqTD66j3X6XzY8lFmtR5CsMYfvY+GQI0f/prLu35Pps2M2fHfVLksm7nYel0XooohhMfrdvMUeKikD2BUnduJOm1BY4OvjvbhdZkU/wBQWJ0w027GX63j/urt6RTZgH5xNwHwXfJ6fjxWuCbQozU6Uz+oKm0r1eaNZn0Kr1nyDz91TdNgPmo1iHqBUeVy/dn1IFTrz5Bat/Jg9faMrncH/f79EJVKxZBat/BW834EX6Fy/EKUFQlMQojrSrbdzMcH/mDEhjmcLMjG4rCy/OQOHvznXQ6b0zDbC1hxcgcvbPuS57cuIMOWx9bso4za9CnDN8zm2FlCU7bdwvgd3/B7yk5GbJxDSkEOR8ypPFbrVrpWiefRWp1pU6kW7zTvT8vQGgyqeTP+vnqq+oUyo/VggjR+OBUXLsVNmNbIR60GEeUXesnPOcOW57nGAwqnxJ1+TYe/r46j5jTSbbnMav0Yvau15YNWj2JQa3mm/p2e8sGny7VZOFGQzUvbv2LGgRUEa/15Lf5BJuz8liybmTXp+8i1F460Odwuz7/hVDWz3OOM3PQJLsVNoMaAWuVDcn4mH+z7lYnxD5CUn4HZaSWlIIcnN8/jyc2fkVKQQ4bVxCs7FjFo3Uz2m05iOXVCb3M5OJiXQra95KDmq/IhVGtE6+PL9FaDeKv5w/SIbo7RV0+78Dq8tO1rryl/SZYMJu76jpP52ZzIz8LpLvy9pFlzMdkv/loqKBxh3J2bzBOb5jFy4yck5B7j0KmpZC9u+4r1mQeLLYhqchRw1JLOzNZDmNr8YbRqX3bkJDG99SBmlFBtsTSn/x6KbjtLWGw0zZrLc1u/4M/UXZgdVrJsZj7Yt4y5h/66pIVmjWeM1p15GwoLXDQIjPYaMatsCCZMZyREZ+SRuJuI0P1XzSrKEMJDsR0I0vrh56ujfaU6ngIPRQGzQVDVy3otoPDm6+NLVb8Q7qnamnE7viHHYeHTQ39RWR9ETf8IArQVo2S6EKWRK/GEENcVk6OApcc3Y3c7eXzjp9xSuQlzD/8FwILEvxlV53Yi9EH4oGJ37jEeXTuDdJvp1Im9H5qzXMAc4Fs4tSvXUcDk3T9w16o3Mfrq+aDlQNpVqo2fWodOraFZaCx1Aqt4piE53S4ybXmeIg8AZqeNbLuZCH3gJZ3oZdjyeG3n92jUap5vcDdqlQ/zD69mQ8YBprXoT6QhCH+Nnhsj6tO6Um1CtP6oVCoaBcXwY8dn8VPrSpxep/PVYvTV0zqsFqvT9vDR/t9Qq3y4I6oZtQMqY3c78VGpChezzU1mVWoCj9ToSIjWH5vbyWFzKlaXg8r6YKY068tRSzoTdn5LakEuPqhwul0M3zCH91sOxOK0kWU3M2rjJwRrjezIOQrArpwkUgpyaBYax86co4zZ8jn3VG3FY7VvIUTrPTIUrg9ictOHyLSbqWWMxNfHl8fr3E6/2JtYk7Gfg+YU1Cofxje+j0x7Hu/u/YX1GQfZmn2EII0/LkXB4rQybMNsHq3ZmXuqtibwIk8C1SofIvRBVNYHc7wgi2Eb5uDr44PV5SBE60+cf4Rn8VKry0G+08Zru37gn/S93BnVgsfr3c78w6v5IvFvmgbH8nrTh877vfDe3l8YVLMzscYIcuwWPj+ymhsj6tMoqCq+p97bBU473xxdx86cJHbmJBVOB8w9xs8ntgJwQ0Q9WofV8uzX4XZhddk96xTZnHbynFbPSJLT7SLPaT3vdZuSLBkM2zAbm9uBWuWDS3FzyJzKK9sWMrbJvcw7vJI0238FIU4UZDPn4B8MqnUzwVr/Ygu/llVQMjushQs0n/oc211O8l22y7IAb0WU57TybdI6ry8e5h5eSYuwmhiRwCQqNhlhEkJcV6IMoXzY6lG0Pr4k5Wd6wlLHiPqMrNOVUJ2RFmE1mNr8YQBSrDm4FDc1/Aur3UUagkrdt6+PGq2PL+/s+ZnnGtxF/cBoJja5n6l7luJwu/DzLTyR06k1XmGp6Jolu9tJpD6ICF0gNreD4RsLq89dyPVTp3MrbvbmHuffjH2sTE3gjd2L+eTgn3yR+Df7zSn8kbLTM5Lhr9ETqjN6pixp1b4Ea/1LvRZJr9ZQ1S+M5xrcRavQmgA0Dq5Gh/C6vL33Z95I+JE/UnaxKyeZURs/ZUHiP/yYvJECpx1/Xx23VG7M+Mb3MblpH45a0vn1xFZej3+ID1s9SrgugDSbiShDKP6+OiY37VM4RTA/0xOWnm9wNztzk3lm6+dM3PktY7Z8Xjhyk5OM013yIqjh+iDqBUZ7gkGIzkiQ1g+1SsX91doxtdnD/JWyi8N5qfyvYS9G1O7CHtMJxmyZz/fJGxi2YTb5LjuLktZhV4qPylyIaL9QPmo1iHBdIE7F5SlSMKv1Y8SeGh05kZ/F0mObcLpddI5siAoVS09spueqt/gi8W8A6gRWwdfn3P+V59otvL3nJ347uZ2hG2aTZMngk0N/8fmRvxm18VNSTpuiavDV8kBsezpUqgvAW3uWesLSiNpdqBcQ5dnW4XaxOyeZn45vweQowOa0c9iSzieH/iS1IAen28W+vBO8tO0rr2mwpcl32liVlkCGLQ9/Xx3z243k1fgHUaEiwhDEP2l7+T55AwAD4jrSJ/YGABYmreWftL0X/Vm5UGaHlT9TdjFsw2xSCnJwuJ3szEmiz7/vczgvtcyPn2Uzk5B7zFMUxuTIZ1dOEib7xRdGuRiZtjyybWZy7BbmHPyTb5PXAdC+Uh20Pr4cy8/i8Y2fklKQc0X7JcTlJiNMQojrisZHTS1jZW6ObMiyk9s97c80uMtTVEB9as0dr8epfTnX5Q/ZdgvPbV1AoiWd8Tu+5ZXGvflw328cNKfw1OZ5LO74LMFa7/36qFTo1Bp8VWoqGQL5qNWjuIGRG+dgdljRqTUXvf6Qj8qH+JDqPFv/TqbuWcqq09ZderB6e+6Iblbs2/gLoVdrSLM6SLSkA7ArJxlHNRcdKtXh34z9vL77B8+21fzC6BoVj8G38Doko0ZPq7CaTNzxDQFaP/rE3oDFaSPTZqZ5aByfth1OkMaPcH0gapUPUX6hHD11nABfPR3C67IjuzA8rTq1qGy9gCjeatGP8AtYBDVE60/LsJpE6INoEFiV8FqBDFs/Gx+VDz2iWzBtz1LcKCw4FVAi9EHMaDWYSpdYgEJRFPJdNvJd/12vZHc5yXMWnBpxNDNy46ccL8gi226hS+UmPF2vO9P2/oTl1GO6VGnCDRH1ir1XSxKo8WNQzc5syDxItt3CvX+/7bnv/mrtMPp6T42rpAtgfJP7uHPVFE8hikZBMfSq1tprHaZkSwajNn2K3e3Eqbi4IbweT26aR47DgltReDC2A8M3zMHqcvD2np94sWHPYus6nc7PV8dd0S1xuAv3VTMgkmi/UCbFP0CAr55aAZVZk7GPOgFRPBTbAQXl1HTODNqF17li0+4KXHamJPyIQ3Hx+Ka5DKrZmYk7v8OpuJiS8CNvNOt73iNqF6pweuSv/HJiG28060PL0BosObaZ9/f9yrDat9E7ps1ZX+PLJdOWx+TdiwnTBTCk5s00Co7hm6R1PFi9PY/E3cSJgmxGbPyEWP8IKesuKjyVch2VjDnf1XyFENcus6OA5Sd3eNaDKVLNL4wPWj1KmNbI1uyjPLV5nudaomy7BTcKDYOqMqVZXyL0JY8y5dgsHLak8uyWL8g7bV2ZoqlezUJiiShhhMqtuDmYl4rRV+e5ZulYfhZWl52apZT1vhC59nyGbZjNIXPhN99BGgPf3jjmgk6qFEXB7LR6pl1B4dSp4RvmkG4z4a/WUSMgkj25x5nRahBTEpZw0FxYkc5PrWXRjaO9XrfUglye3fI5e/NOoFb50DasNmsy9qOgMKHJfXSMaIifr9ZzzdKmrMPofHyxnbreprp/OJObPsTwDXM8U4CGnrro/EKr2imKQp7DSqDWgMmezys7FrEmYz/NQ+O4N6YtL23/yrPtk3W7cW+1tpcUNIsKPBQtpBuk8UPn40uazYTOx5fprQcTrQ9l+oHfWHJ8MwCj63Un0ZLOD6dGVwDig6sxMf4BqpxWNOFcxz1iTuPBf9/ztN0a2YgXGt1TbDHaomuWfj6xxav9f416cXNkI8+1R1k2M+/t/YVfT24DQIUKBYVAjYEJTe7n/b2/csSSRmV9MNNbD6bqeV6Tl+cowN9Xh8+pLwvynTbUKh90ag2ZtjzUKjXBp96/OXZL4Wf1EkPshci2mdmancjY7Qs9JeoB4vwjGF2vO/WCospsal661cSL275kR04SKlS0DK3hqcJ5e5V4nqpX9uuFudwu/kzdzcvbvwbg7qotaR4SR7g+iJ05Sfj76rgrujnHC7IJ1vpf0d+NEBfifLOBTMkTQlxXsuwWT1i6KaI+H7Qc6Jme9+6eX8hzWjmYl4JLcVPbWJn57UcxtfnDheWvC3JKLfsMhVPt3G6FsY17e7U/WrMzNpej1G+/fVQ+1Ams4lXgoapfKLUCKl9yWMqxW/js8CpPWALIdRTw+u4fvApBnI2iKBw2p/L5kdWeKmkpBdnk2PMJ0xrxV+uY2WYIbzXrx4TG92J1O0jK/6+KXb7Lzj9pe70qrrlxY3EVngRPa96PsY170yq0RmH/7PlYXXaybGaO52ezKeswTYKr8e2NTzO/3Ug0KjVHLen8nbbHM1UNYNbB3/nt5HbMF7jArUqlIlBrIMduYfbBP1iTsZ8mQdXoG3sjr+76zmvbD/YtY33GQa/rzS6GoigoFI5wzW7zGB+3eYxoQygK4FYUArV6Rtbpyu1V4hleuwtJlgxPWKoXGIUKFdtzkpiw41uvBV7PJteRz+JjG73aNmcfKVbRsMBp45uktZ6wNLBGJ9qfWjPp1V3fs890wrNtqM7I6PrdaXlqWmbhs4J3mvf3hCWAWW2GnHdYAgjQGDxhCQpHnopCapguwBOWgHI5IQ/U+lE3sAq9q7Xxan+x0T2eYFdWwvWBTG76EI2Dq6GgeMJS18pXJixB4eLarcNqMajmzQD8eGwT43Z+w9SEJaRbTdxWpTF6Xx01AypLWBLXBAlMQojrSiVdABMa30fHiPq82PAemofW4MOWj1I/MJrR9bsTpgvgzqotGNf4Xt5u0Z9wfSCtwmrxdotHmHmOamQGXy3RfqHMPvCHV/u3SetoFBxzRU5kTudW3GzLTvRc7/JA9Xae9Yb+St3N0uObi1VjK0maNZehG2Zz1JJBli2PDGseozZ+ykf7l/Fa04f4uM1j1A6ojM7HlzB9AGO2fI7d7aSqXygtTi3Y+0bCj/yVuouCU9dcVDGE8GGrR3m/5UBahNYgVGdkfJP7eLNpX7pWiWdr9hHuWT0VH5WK2W0eY3jtLtz3zzscz89iTtth9IntgEqlYm/ucX7t/CIdI+oDMOfQn9gv4jqWlIIc8hxWvkvegJ9ay7gm96FWqXApChG6QD5tO5yGQVVxozBux6KzBmcoHIFItmTiUgqvp8pzFHAiPwury4FKpaJmQCSzWg9hVushxBojiPIrvLZuZushNAwqvM7KqbhJtZpwKi7Up65T6lm1FWMb9WZM/R6oUKHxUZ9XqM6x5zP/8Gq+ProGgM4RDQnUGMi2Wxi6YTbH8v+r/mjw1XF31VbU8I9gRO0u9I27kf817k2HSnXpWjmeOGOE93O1Wzhk9l7f6u/0PdwUWd9ze8b+5dfU4qUut5uUgly+TVrv1f7arh+I9gv1lMAvK3q11nPtYJEOEXXxK+Pjni5I68eD1dtTzS/M02Zy5DO09q3Fiq4IUdHJlDwhxHUn32nD6nKctlimC/MZVbzsbqfXtSF2l/Osi7FC4fSkpzZ/xl7TcdQqH4bVvo35h1d5KoR92eGJK/5ta7bNzMyDv6Pz8eXRmp1Rq3xYdmIbf6fv5ZVGvT2VzM4mx27h7/S9uN1uPj+ymjH178TqshOqNfLq7h94q9nDVNIFYHXZyXHk89K2r3EpLp5veA+59nx+PLaRPabjTG81iDj/CFwo6E99A+90u7xG3lyKG5M9n4HrZnCiIBudj4YhtW5m9sE/sbkdRBtC+aTtMKwuB7MO/l64VpM+iExbHrMO/M7DcTd6Qq1bcXuNUpx5u0iyJZPhG+fQLqwOD8a2w+pyMHXPUrQ+agbVvBmDWkeMfxgOt5MJO79lVJ2u1AmMKnZtWbbdgr9ah8VpZfr+5axI2cH01oOp5l+JX45v5e09P/FW8360DKuJXq1BUZRiYaeoj+lWE69sX8Tm7MOoUPFsgzsJ1PiRaTORbbdQwz8SrdqXCH0gNYyR+JVQ+v10hes+HeXJTfN4sHp7BtToRLqtMAg3Ca7Gy416FXtvZtry0KjUBJ4azcmw5eGDyiv4HzWn89iGj8m2WwjUGKhtrMzm7CMADKl1CzGGMF7ZuQgoDHsj6nS9ItfXlLV0q4l7Vk3FobiI84/g3mpteXfvzzgUF/HB1Zna/OELmpKXc+r1K3p/ZtvMXqNqpzM58j3XLAH4qtQ4FRcqVExp1oe2YbXR+5Z9cMq157Mg8R/mHV7p1d4zpjXDat1aZmuYCXE5nW82kMAkhBCXid3lZFt2ImO2fM5bzfvRLCSWpPwMhq7/mOF1unB7laYlrjtT1rJsZlQqlScQ5jkKsLudFxTeMm159Fz9FlaXg6p+oQytdRuv7/6BApedWsbKTG76EE9unsfMVkOwuKykWU2M3/kNeQ4rr8U/SJwxnGhDKPvzTpJjz6dFWA1PaCrJ8fwsRmycw8nTqmtFGUL4qNUgok9N7cpzFHhdU3X67SybmZ05STQNiSVI60eeo4Dt2UepHxTt9bwLnHZ+PLaJt/f+BBQWUkjOz2RP7nF8UDG99WBqGyt71pEpCgZnhqVj+Vk8tWku/2vUm8qGYAavn0WaNRc/tZbOkQ09VeZuq9yE0fW6U0n/Xx+ybWavk0uTPR+H28ULp65TmdTkfqr6hbEu4wAzD65gYI3ONAmuxpLjG3mi7h2e1+Nc7C4nJ63ZBGn8CNb6oygKKQU5XlUb85129GrfEoNlSdKsuTy/dQHJ+Zm822IAeh9fPjn8F6tS9/BOi0fItpk5ac1h/uHVzGwzhNoBlc9731ezdKuJ31N2sjh5I0/W60aOzYJW7cs7e3/hlca9qR1Q5bxHlNOsuYzf8Q1P1ruD2gGVybHn897eX+gSFU/L0BrFQlOmLY+Ba2eQYs3h9irxPF2/B89s+ZwdOUk0Corhreb9rsg1TH+k7uJ/2xcC0LNqawI1Bj47sgqAMfV70Cum9VmXYRDiaiCBqQQSmIQQZc3ucmJxWvH31aE9NYqQaTej99GUS1i6XFILcthjOs7/ti/EftpCpxH6IKY268uzWxeQZs3l8TpdiQ+J5enN8zE5C68lqhcYxeSmD2GyFzB042zsLifvtRxAy9AaqEu5rsvsKODf9P2M3bHQ0/Za/IPcUKkuBs3ZR1NOL1gwqObNPFi9PT8f38K7+36hU2QDnm9wt1doyrXnsyhpLbMP/jeV0gcVU5s/TMuwmuecXpVrz2eP6TjLTmxjxckdvNW8sFLf+oyDvLfvF892N0c25Mm6d/DriW30jGlFiM7IyfxsPjrwG4/VupVq/pXItln49PBf3BHVjEhdEEfz04kzRuBS3DhcLg6aT9IwKAYflQ92t/OCKgKeKcduYcmxTdxcuTFV/UKxOK38k7aXWGPEBQWbNGsuZoeVt/f8zJasw3zSbhg+Kh8WHP6bZSnbebxON7pUaUy4PvCaCEtQuD7WQdNJ7IoTq9NJ87C4wgWOTy1KfEtk4/NapyvXns/End/yd/pe/NU6Pmo9iC+P/MPylB2oVT58e+PTJQbiY/lZfHd0Hf1q3ESozkiaNZd5h1YyoGanUovSXG6ZtjymJPxImDaAx2rfgg8+fH10DduzE5nQ5P5Lem8KcaVIYCqBBCYhxPXO4rThf9r0LbOjMNyd7TqYlIIcRm38hDaVahOo8eOTQ3967nuvxQBmHFjOXtMJHo69kZsi6nvKTAdqDJgdVtwoNAiqyqM1OvO/HV8TovVneqvBpY6MmOz57Ms7wdObP8fm/u9aIZ2PhvdaDqBuQBT+ZwlNRdMQi4ok1DJW9lTs61o5nqfq34Fa5UOQxs/zvLNtZnqufov8U8Uc6gVG8UHLgQSdx7SqDFseE3Z8Q8fIBthcDpqFxrH02GZ0PhqCtH7MOLDc81rpfHx5fNNcelRtweCaNzNx57eszzxIFUMwM1sP4ZODf7Hk+Cb81Tq+vOEJ3IrCd8nreTj2Rs+J8WeHV9G/RsdLOjE22QtYkPgPcw//5Tn21qxExu/8Bn+1jk/bDS92rdK5nMjPYuSpNXdqBkSyP+8ksf7hvN9yIJUNwRfd1ysl224hwFfvmSKaZTNjUGs9pfDPZHU5MDsK8NfoMai1uBQ3mbY89D7as4alM6cEn15t8nRP1r2Du6q28BpFPZ3ZYfX6Eqbwi5or+6VM5qlpmkUjpLn2fJyKSwo9iApDquQJIYTwkmnLY+aBFZwsyAYKT26+TV7HYXMaLrer2KKfRbc1KjXtK9WlbaXafJn4j9c2b+1ZyvDaXQjTGnkwtj27cpM9BR++aP84k5v2wQcVyZYMdGpfYv3DzxqWAJyKm1e2L8LmdhBlCGFW6yFEGUKwuR28vP1rrxBVVFThdCqViuG1b+Oeqq0AOGhOoZpfGLdVbsxT9e8gy2ZmwNrpHDKnYnHYSLPm8vSW+Z6wBLDXdIKP9i8n+xyFCgqcdr45upb1mQd5M2EJBrWWpcc2813yer48+g8xfmG0OFX978VtX6JSqXioegd+SN7Al0f+ZkCNTujVGk4W5HD3qqksOb4JgLtjWgIwYuMcvjjyN+/t+4Ucu4WXtn3FN0nreHHbV5dURMHPV8tNEfU8x37wn/cYv/MbABqHVCPgIk68w/WBPFG3Gy7c7M87CcDT9XoQXgFOnlMKchizeb5noehMWx5vJCxmXeYBT6GSM+nVGirpAz0jkGqVDxH6oHOGpZWpCfT5932OmtNxul2YHVamNOvrtd0dUU25u2rLUsMSUGzE+kqHJSisWHj6dNIgrZ+EJXFNqjCBafLkybRq1YqAgAAiIiK455572LdvX3l3S4jrlsVhJctmxn3qhNXucpJtM59X1TVx5WXbLEzb8xMLj67h8Y2fkmE18WXiP0zfv5w3dv/AgbwUz8kiFF5DtD6j8GQxTB/AIzU6Mnb7QgpcdiL0QbzUsCdaH1+S8zP5aP9vjGtyH2O3L+LWyo15seE9fNhyEJV0AcT4hfJyo55MjH+Ad/b+wlFLRuGoUwlBp0iw1o+3W/SndkAVnm9wN2/v/Zlxje+ldkAVpjXvh8Gn8JqOw3mp7M5JJteW73lsutXEipM7SLeauDGiHgAdwuvyQsOe3BndgkxbHkM3zOZkQQ4H8lLYnHWY75M2sDv3GD6omNjkfh6t2RmAxcc2sj/vJGebiGHw1XJvtba0CCkMRW8k/Mh3yYWV03rHtMGtuBlRpwsRukDyXXZm7l9B58oNAVhw9F+2ZB3h7eb9vfZ5R1Qz7q3Wln/S9npC368ntnHHX2941t55OO7GS6qI5uujpm5gFDNbDwHwlElvElyNcY3vPa9iIKezu5wcy8/CqNHTLCQWKFwXS6v25bA5rVgYvxLSrLlknFY6P9OWR6o1t9h2ufZ83kxYwq7cZIZvnMPOnCTe2L2YlakJvLD1S7Lsl6+6n9Xl4O29P5FlNzN0w2x+PLaJI5Y05h9e5bXdqtQ9HC/IOuvnpDQ5dgvH8jM9r7nFaeVEfjb5zsIFj7PtZq/fR5bNXGooFEIUqjCBadWqVYwcOZJ169axYsUKnE4nXbp0wWKxlHfXhLjuWBxW/kzdTe/V0ziQl4Ld5WRXbjJ3rZrKpqzDEpquQkaNnvurtfOsOXXXqqnMPbySan5hDK/TlREbP2HYhjnsNZ3gRH42Izd+wtNbPmfdqdDk56vlhYb3EKkP4v0WA9iUdYiJTe4nSOPH6PrdmbF/OVuzj/DJwT+5JbIREfpA9plO8Oj6mYCKrZlHyLVbKHDZ+S55HYnm9FJPBn1UPsT5h/Nq/ANM3PUdWh9f3IrCc/XvxKDWkmrL5XBeKs9s/Ryb20mKLYdcez659nz+TtuLze2k75oP2Gc6yUsNe9K1SjyPb/qUX05sI8tmoU/sDTxdrzs7so/y/LYF1AqozK2RjZgU/wB/pe5G76NhcM2bGVWnK/UDq56zbLeCwv8a9/IKMA2CqnJHdDOqG8N5f++vvNtyADeE1+OVJvcy79TJsQoVYboAlp0qCFFka/YR0qwm5h5eiUtR6B/XEQDnqQVSxze5j3aXoRKaze3giDnNqy3VmkvBRXx+s+1mPtj3K6M3f0af2BtY0vE5ch2FCyZvy04k13Fl/69OLchh9KbPmLxrMZm2PDJtebyZsISnNs0j5bRCIlA4KjKmfg+qGIKxuhwM3TCbVWl7AHi+wV0EnWWU53R2l4MT+VmY7IXX7imKwrH8TK+RwBCtP3PaDKNJUDWy7GbsbgeJ5jSsp0ZN763WlnBdIBaXjWHrZ3M8P/uCnnfRumsP/fMeCbnHyHfa+Ct1Nz1Xv8W/6ftIKcjhmc1feI2kvZnw41lH0oQQFSgwLVu2jAEDBtCwYUPi4+OZO3cuSUlJbN68uby7JsR1x+Z2MvPACs9/6l8f/ZfHN36Kze3gg32/er7JFOUv226hwGlH46OmYXAM77UYAPx38t0itAaVdAEEaPTY3A6Gb5jNo6dKemt9fKmkD0Djo8bPV8eNEfX5rN1IAjUGKukC2Z59lAUdHmdz5mF6RLeghjGC+6u380wVUqlUDK11K/tMJ2geFscnbYfxUPX21DBGcsicQoo1l1x7vucE80R+Flk2M1k2M3tMx+nz7/tk2vKwuuz4++qwuh08vvFTduUeY1HSWp6u14N39vzMhoyD2F0OgrR+tKlUix3ZRwH4+ODv/JO+lwk7v8WluDmYl4JW7UvDoGiahFSne3QzfFVqxu5YSJtKtVmRspO/UndzIO8kd1dtyd1VW53zwv2i61Y+PfSX15S+hNxjJJrTOWbJ5JXGvXlrz1IejruR/bnHWZWWAMC4JveyOzeZJccL/x+7Mfy/KXITdn7DpCYPcHNkQ7acKtNdZF3Gfq9jXQyL08aq1D1M2PktADWNkejVGlKtuYzcOIfj+VkXtD8FSLSkY3c7eXn710xJ+NGz5tOBvJRzFnsw2fNJs+Z6RvOsTjuZtjzsFxHenG4Xu3KSOWBO4e/0PUza+T2v7/6Bv1J3c8icyo7sozjOGPGK9gtlRqvBXm09oprTNSoe43kEJrvLwbbso/T++20WH9uA2WHlkDmV/ms+4r19v3hCk83t5HhBJqPq3k6dgCrsyz3JDRH1ub1KUybHP8SI2l2Y0Xow4bpAOldu6HW94flwuF2sTE3A5nYycuMnvL3nJybu/A4FhZ+ObybRks7O3CSGb5zDrpxk3kxYwp+pu0scScu05XHAdBLnqSIvOXYL+0wn5O+7uC5VmMB0ptzcwmH10NDS58HbbDZMJpPXjxDi0oXqjJ7/1C0uGx/u/w2H4qK6fzjvthgg629cgjxHwVlvX4hsu4WPD/zOv+l7KXDaybXn82+G91TmTVmH0fn4Mr3VYCJ0gdjcTrLsZnxVaqa3HkT9wGjPRfD+vjpCdUbSbXmEaY00CK7KPaveYs6hPzmYl8KzDe7ixW1fkm7Nw9dHTZx/OGqVD4uS1jJmy+ekFuTSM6Y1m7IO46NSc//f7/BD8ga2ZB/mYF4Kj66bybt7f+aIOQ2L00btgMrUD4zmtfiHyLZb+DpxDWk2E6/u/I6qfmFM37+cg+YUph9YjuPUaFW0XyhP1buDjhENAFidtgeX4qa2sTJjG/fC6rLz4raveHn7V1TSBjKj9WBcipvXdv/AytTdtK1Um2ca3EmkIbjYekGO06oDQuFaXXaXk3UZB1h6KvTcEdWM+ODqwP/ZO8/oqMq1DV/TWzLpvZDeSCghCV2wgF0pKorSO4gFey/Yu6LSERULKIgFsaEiPSGUFAIJCaT3ZCaZ3vb3Y8IcothO+c7xnLnWYi2znbJnz0zy3u/z3PcDS0s2o5Eq+PDUXq6NHcqLxz4nzT+aJWmX80jWNQwLTCYvKMndYhc3kiXpV7C03ySUEhlJPuEEK315unQrxT1teDk9g0q3NxzptQg/F01mXa9htO2Wbk4ZWjyeLzEiVFI5IkQMDkrmjdxZLM+djVIiQyaWIv4Dw3DPJlzlz+s5M4lSBWJzOdjT6v6cjYvOZUHymN8cZNplM/Fx7QGu3/0qJw3NWJx29rVXcNWPz3G4s/pPiyapWMLg4GTuzbgagL1tJ9jVchyAu9KvZGhICrKfpTO2W7t5+fi2Xse+ay7mdI/P6PcwOm181XgEp+Di9fKveaHsc+YdWEW3w8KBtpOYnTbsLieHO05xR+G73F74NotSLuaCiExuPfiW57OilMiI1QSzZsg85iVf5NnYAHfIQ7u1+5y+vTOEKLW8ket+H6wuh0eMDw1O4b6+44lSBXoqaXPzV/FDc6n7umRciZ/sb5/3dms3T5ZsYcb+5ZTo6+iym3j31C6m7H2dn1rKMHpFk5f/Mf6SgkkQBJYsWcKIESPIzMz81ds9/fTT+Pn5ef7FxMT8P56lFy//3USo/JmddEGvY0vSLif0fzxK9teCE/4IjeZOXi7bRqvFvbnTZunitRPb//RuP7gX97uay9hce4AHjm6koruRD6p3s+HULgAGBsR5PEgPHPnAPfjyZ4tkMedeNDtcTgYExvF25U4cgpOro3O4ps9g3ju1ixpTOyanezGlkio4P6wvKb4RxKqDMblsPFy0iXlJF7Gn5Tg2l4M3K77h+6ZSbi5YR4fNwJ7WE4hFIl4q+4IHMyfyQvYU4nxCSPAJ5ba0y0jVRuJC4LUT2zlpaEIiEvNy9lSCe0R6p9XATy1ljAhJ7XXOw0PT6Lab6bQauTwymwvC+vJ141GKdNW9Xmu1sRWTw4YgCFjOWqi3WbrYWnuQzp5d+E6bkc/rCjE5rFwcMYBodSATYwaT7BvODXHDGRgQx/CQVIwOKycMDXxRX8hTA25g2t43iFUHMyIkFbNgRy2V8/bQhVwdk8MjRZt4u2onLw+axoXhmZTqaglX+SNCxDMDJ/PMwMncnHIxAH00IUh/pWrTZNZxW+F65uev8bSEPVm6hRn73qSiqxGn4EIllTM0KJkVebN5JGsigQofUrWRrMqby7KcGUSoAv74h60HH5mKvKDEXscuiRyA7+/E6VtdDj6q3ofBYWHegVW8VfkD9x5+H7vgZF3l9xicf35x7iNTckF4JhFnpfOFKv0YE9HvF0EKepuR105s97ThTY0/zyMqFvxsFtivESDXcHPKJVwaOQCALxsO0+2wECh3by790FxKp81AhMqfQIUPRqeVuw+/xwNHPsDktBEk90EqlniEiEoiZ0PVLmbuX0GtsR2Tw8r3TSVM+OlFyrsaflM0+ck1nvM4ww1xw3njxFfUGFt582eVtMsjB3JpZO8ZcXaXk2pjGzaXg5sL1vHAkQ9599RPABzT1WFz9t488OLlv52/ZKz4okWL2LZtG7t37yY6OvpXb2e1WrFa//aLtquri5iYGG+suBcv/yBnPEuLC9ZhP2sHVCNR/FcNp/yzNJo7qehqJCcoEbVUQZuli/1tFYwMTf9FteLndFoNzM1fTbWxlQEBfXh2wI08Wvwx+9rKGR2awX19xxOgcEdcC4KAC8EzPFUQBE4ZWlBLFZ745gZzJ2aHjberdvJV4xGuiMom2Tecl49/yRVRg1iYPIY6UwcPFW3ksX7X8Xjxx542PLVEgc5uRCGWsSJvNqnaSE+VSWczsrbyB7bVH2Jpv+s40d2IXCzljfKveShzIj82l3JrWu9hqm2WLjpsRm4vfJtWaxfRqkBeyZnOyopv+bap2HM7X6mSx/tPYtmJr5ieMIqcgHiCVe7o7BpDK9vqDzM6vC/T9r3huc+VUe54bn+5BpvLwTcNR/GRK3m8eDNOwYUIEQLuP3N3pF/BhWGZHuO/0WHl5oPrmJEwmtFhGdx7+AMaLZ0MCUpmYcpYGsydDA1OweS08vDRTRR0VDIxZjDzk8ew5uQONtbsIycwgcf6XYfBbmF363GWlX+FQizlsX7XEazwxV+u4ZShhUh1AF/VHyW8Z8Gsksh46fg2aoxtfDTidtZX/ci2hsOIEPHsgBv5svEQPzWX8VDWRGI1wST7hKOUyumymak2tdJHHYz2Vz5Tx/X1zMtf7Q7oUGiJVAdwpKdN8aHMCVwQnvWnW71qje0oJFJPlHmLRY/V6SBGEwS4gxM+rN7riZw/c93lYilv5s4iwy8K6W8MMa02tDI/fzXtZ7WFZfnH8vSAG/5wfLrZYUMpkSESidwzgko/5cee9sczjAxJ577McQSfleTmElxUdDcx/8BqFqdewsUR/em0m1hUsIZhwanMTb7wNytkZxAEgYruJm7au8xzbFx0LiNCUrnz8Ab6aEJYkTeLZksXtx58C31P9dhPpubpATcQovAlVhOCSCSi3tTBjXtew9QTsnJZxADW9wyFvSg8i7szrsL/HJH3RoeF75tKWVqyuddxhVjK4/0moZBI2Vpb0Ou6KCUyluf2/p6D+/fZooK11J21YTMpdiizki4453N78fJX5L82Vnzx4sV89tln/PDDD78plgAUCgVarbbXPy9evPzjmJxW7jr0rqcN7+2hizztefccfo+uf6CN7K9Kk1nH4oJ13Hl4Azubj9FhNfBo0Uc8XrKZDad2obO5k9xcggudrbcBvtPmFicLkscgQsSRzmou+eFp9rWVkxeUxMTYwXQ7/mYkP2VoobynUiAIApWGZuYcWOkxtDeYO1lcsI4F+WuYljCKTL8Yvqg/xMnuZl7LmcH85IsIVmo9niaNRIHebkIhlrI8bzZvDV1AhMofm8tBk0XXy+9hdTr4rrEIg8PCQ0WbPFUwp+Dim8ajLE69hICzFlMmh5WC9kqePfYpd6ZfiUIsY2BgPGsrv+faPkN7XYchwSnUmdqZFDsUp+Ci2tSOzenA7LDRau3m/PC+LC3uvRDcVn+I410NmHvmSw0PTeWD03s8bXifnHenp9q0vvJHnIKLd6t+4pXjXxKo8OHhrImIEXHfkQ94JWcqWX6xTE8czcKCtdx35AP2tB7H6nR4ZhJtrj3ADXteZWPNPgAujhhAqb6WG/cuY1n5V4wOy+DiiP48cPRD5h5YxU8tZfzUcoxms54b4oZRqq/lviPvU9RZw4iQVGYmnM++tnKujxtOsm8EK/JmIxaLmBQ7jPNCM2izdBGvCfEEPGjlKrL8Y39VLJkdNo7p63m833WoJHJarF0esbQo5WKSfSN6iSWjw0qnzeDxDjlcDnQ2Y68KQo2xjfn5q7mz8F1aLHpaLHruOrSBefmrqDG2Ae70t009nqXxMXl8PvpuotXu9rw1J7+n+3dauMJUfr/4PNyaeikhij/2d9tgt7CjuZgqQzOOnpbAM6JgSdoV3J1xFQC7WsvY1VzWq/IrFolJ9g3n4/OWMDaiHxqZkmh1IKvy5v0psVRpaGZB/upex7fWFVBpaGZGwmiqja3cfeg92qzdWM9q77S5HPhIlUSrgzxV3vCe2Vhqidw9lLZHLI0ISeOO9Ct+VbBYnQ5Pa2FuYCJvD13oac9bU/k9kaoAz3W5JeUSlqRdjs3p6Kmk9Q6YUEsUDOhJPDzD+eF98fk3xJd78fLv5i9TYRIEgcWLF/PJJ5/w448/kpyc/Kcfwzu41ouXfw4Ol5MTXQ08e+xTnht4E+Eqf2qMbdx7+H2eGDCJBJ+wf/cp/r/TbNbxaPHHFHZUARCu9KfJogPgzvQrOS80jVClHye7m3m4aBMvZN9EtDqIelMHdx56l0ezriVGHcR3zcU8UbIFgIEB8UxNGMldh95z+8ZyZ2N3OZiXvwqby8mKvDkk+IRSqq/j5oJ1OAQnsepgHILTUy16KXsqyyu+oVRfB0C6Noop8SMZHpLmGcjp6glEsLocHs9SvamDSkMzuYGJvxjcedrQyoKfVQOGBidzV8ZV1Brb6KMJIUTpR5fNRIO5k1kHVgAwLf488oKSqTO1keYXze2Fb//CaP5g3wkoJDIeKtqIVCRhWc4MxCIRjWYdXzceZV9bORKRmEeyruH903s43lWPGBFbRt1JpCoAh8tJk0XH6pM7WJg8FrFITJm+nh9bSrksciAAiwrWISAwMCCOTP8Y3u1pU5wWP4qrogehEMt4unQre9pOIELE5LjhRKj8qTS0eIbhAkzuM5zpiaOxu5w8UrQJrUzNXRlXIhGJWVWxgyJdNbemXcbdhzdgdthI1UZS1lUPwKQ+wxjg34c6cwdvlH+Nv0zDisGzqTO2c/fh95CKJazMm0MfTfDvhg7obMZeC+h6Uwf1pg6WlX/Fia4GwF1hWDN4PqFKrcdjaHRY2d1ynBfKPmfl4DnEqoMp1ddxW+F6XsyeSqZfDGKRiMKOKm4rfNsjQkVAuaEJMSJeGTSdQUEJSEViKg3NfFl/iCnx5xGg8KHB1MHqk9+zMGUsIUptj0gRelWaOnuGw+5rr2Bp0WbuzLiSNZU73BHlUiUr8+aQ5Bv+m0mFFoeNHc0lPFb8MVqZinWDFyCIYMOpnwhX+nNheCZiRBR0VFHR3ci8pIv+6T5Lnc3Iw0Wb2N9WQaDch5WD57Cu8ge2NxxBIZbywYhbWVq8hRvjR/Dw0Y2YnDYC5T4ICHTajGgkClYOdr/WM9V5o8PKaye+5JPaAs/zbB65hBhN8K+ehyAInOxu4q2qH5mfPIZFBWt5IHM8H57eyy2pl1LYUUW71UCcJphkbSSf1ObT1z+aI53VzD/ruuhsRt6p+okNp93fDTEiXD0Vw9dzZ5LpF/2bFUMvXv4q/NdVmBYtWsSGDRt4//338fX1pampiaamJszm/72dbC9e/t2cmeHyas50TwtYrCaYN/Jm/U+KJQC1VMltaZeR5R8L4BFLt6ReSqO5E5cg0G03c1vheqoMzSzId6dULSxYQ6WhmVsL12N12fnurBY1k9OKGDEysYQWi545B1Yy+8BK9HYzCrEMpUSGQiIj0y+GZTkzkIok1JjaeomltZU/UKqvY0RIKgP84yjrqueBoxs53HkaZ88uu1gkJqknYOFMS06UOpChwSm/EEsAIQpfLosa6PlZIhJze9rlvHr8S9qs3XTbLTSaOtlce4C9bSe4JfVSzg/ry8TYIdSZ25GIJaw++R0dNgO+UiXLcmZwQZjbj/pGxdekaSOJ04TgEJwsLFjLgvw1rKj4linxIwlX+vPyoGlcEJ7J8wNvIl0bxR3pV3gGrUrFEqLVQdyZfiWBCl+kYglZ/jGk+EbyVuUPBCp8eKr/9YgQcbjztEcsXR6ZzQ1xw1FLFWys3sudGVeSE5jA/OSLUEhkDAyI/4Wjy+y0IyAQotTyeL/ruCvjSoJ62vDmJF3Ay4OmEacJJkYVhAvBI5au6zMUf5maVSd3kOQbjlamQmc3Mm3vGzxz7DNcCKT4RhCi1P6uWGo0d/LGia+pN7oDHtosXbRauviweq9HLIHbJ3Tn4XcxnuUHsrnsvFj2BXq7iXkHVrG1roBFBWsxOqw8W/opRqcVqVjCgIA4XsyegkQkpsLQ5BFLL2ZPZWBgHDKxBJFIRKJPGNMSRnsW3ZHqQG5Pu8wjlo53NVCir/NULKsMzTxStIl2m4E3y7/m8f7X8VXjEZ4beBOZfjEYHBYeKfoIvd3Eb6GUyunrF02AXMMlkQP4rrmYa3e9xJjwfgwKTKDRrGPSnldRSKTMOOv8/pn4yzU8mDmBkSFprMibQx9NCLemXsbV0Tm8njuTIx2nsThtnnbaUIU7cGT14HkEK3xxIeAQXJzZwTbYLexoLO4llgAW5K+h1tj+yxPoQSQSkeQbzuLUS1hS+A7NFj1rKnawJO1ybi5Yx/Nln6ORKkjzi2J+/mo21ezjmK6O2Ynn97ouFqfdM0R5Up9hfD76HmLUQdhcDjac2vW7FUMvXv7b+MsIpuXLl6PX6xk9ejQRERGefxs3bvx3n5oXL/+TSMWSX7SqBPwb+9pdgovOn7e6WY3/bwMzfWVK/GVq5D/bdZWJxFwbO5RIdSA+MhUvZE/xxDfP3L+cRrMOhVjGcwNvYl3lD+xvqwBgVGg65V2NrKj4lmcGTEYhltJhM2BwWNDKVKwcPMfTJiaXSAlX+fcy1/vJ1ESpAzE5LIwOy+CBzAk8OeB6sgPiSfIJI9EnFMlZfgWxSIxULKHT9rdrJhNL6LQZaLN0YbRbAPcMrvLuRrRnJWpdFzuUbQ2H2dlSxhMln1BhaGRz7QHWVH7P2sofiFEHcUfaFdx35H3ClH5sqt7HuJg8hgQl8cqgaSw7sZ1rYgdzRVQ2j2Zdi9Xl4LmBNxKs8EXAvcC0uxwoJXLWDJnnCawIU/nx0qCpPcECvYWFUiKnRFfDjH1v0mTRs7v1ODfGj+T2wrcJVPgwLjrHc1u5WMqtaZciEol4oexz3j29i7sPbeCO9CtotxnQylRsrN7Llp7qUnSPP+uTunxWVeyg3dpNsFJL0Fm+mACFDyFKLVKRlDifkF7nluQTTk5gIkEKH147vp0n+l+PTCRhceqlPD3gBi4MzeTZgTeilshpMHV4hsr+HJ3NyFuVPzAsJJVacwe1hja21OYjILC3J6VuUcrFvJQ91T2/yqLnq4YjGB3u9zKgpxLiJ1Ojt5t57thn2FwOotWBvDxomuf7rJDISPaNIOis73uQwpcUbQQKicxzrM7U0TOXzR2W0WLRc7CjyvOZWZC/hpsL1lGqr6XV0sVtB99mf/tJ7jz0Li9lT2VFxbfsb6vgloNv8Vz2TWT4RfNc9k1/yC8T5xPKyry5pGujKNHVAHDzwXW8d3o3Sw69g1Nw8cGpPf9Sb2Wo0o+Hs67xvN+BCh/mJl1EnbGdx0s2U9ZVz87mYzzR/3oezJrAc8c+QyWRsyJvDivy5pCqjfT4Eg0OC0+VfgK42/DWDJ7nbs+zdvHcsU/R235dROrsJu48tIEaUxsKsYzr40ZwvKuBTH938NWy8q+YtPtV9HYTfjI142PzCPmZTyxM6cfKvDnMTBjNrMTzCVFqeT13JuOjc7m377h/6+96L17+HfxlBJMgCOf8N3369H/3qXnx4uXfjEtwUdnt9g+c2X1tMHWwsGAN5d2Nv5ko9c+izdLFy2XbmJV4AbekXkqo0g+5WEqQQovBYcHosCIRiUnVRvJo1rW97vtQ1kTiNSH49SxCHsm6hkeyruXpATdgdrqHxkrOWuhJRRKkor+JnVpjO7ccfItOmxExIsSIaLV2saTwbZ4eOJl7M64mSOFLiFLL0v6TeGnQVMLOSg87Q4tFz4NHP6S8uxGHy0mH1cBrx79if1sFxboajHYLBod7aHG9qYOl/a5jZd5cdjaXkqGNpp9/LHKxhMeLN/NB9R4ALokYQKfNyPaGw0yOG8FTJZ/w1IAbeKnsCy6NGsh3jcXcnXE1wQotw4JT0UgVLDuxnVpTe69Fod5uxmA3IwgCNqfd8566RYqoV6IduM3vdx9+jwZzJ3ceetctxoo+ptGs46GiTYyLyfPc1uZyuFPZXA7GR+d5KinT973Jpup9BMg1nvbDyXEjWD14HlPjzwOgydxJt918ztSwTquBFSe/5avGo4A7+QzgmdKtGBxmHsu6lgvDMzHYzdyadhnH9HXccvAtLose2OMJK2LCTy9S0FZ5TtHkI1FwSeRAHirayMNHN1FrbicvKIkv6gu5r+847k6/ijClH1/UFfJ4v+u4JnYIF4VnoTnLgxKjDmJ+8phej3t/3/FEqv+Wktdi0XPnoXdpsf5tNEertYs7Ct+hpSdAo87UzoKCNSw+uI7DndW0Wbq45/B73HvkfX5oLsVPpiZMqcXmcrAwfy0vHPuchSljkfS08k3c9RLl3Y1IRGIezJyAr1TJK4OmecTp72FzOmi1dvF06VYuCu/H8B7f2s6WY55WwpcGTSXkX5zi+fNwF7VU7qkaXR45kFvSLiVI7sszJZ9ic7krlLGaYFK1Eb2+4/5yDc9n38TIkHQeyBxPX/8YVuTNoa9fDA9kTvjNEBk/mYpHsq4hSOHL8rzZnB+WQV//GK6IyiY7IB5wD1sWIWLN4Hnn7AoQiUQk+IRxY/xIj2CNUAWwOPXSXoEZXrz8r/CX8TD9M/B6mLx4+e9EZzNy055ltFi7CFVoeXrgZB46upEGcyf+Mg0fjbz9d1Pq/lGazTpqTO08W7qVwcHJXBM7hCazjrdP7USKmPszJxCpDqC+R8idHVUcrvTnzbxZ+MnUNJl1RKoD0EiVmO02asxt3FywFr3djEaiwCG4sLrshCr9WJYzg2C5LztbjvF4yWbkYimv5kzH6LBy7+H3cQhOnht4IyND0npVk85Fl93E06Vb2dFUglIi442cWWyuPcCXPclta4bMo9HUSaWhmbeqfgTgmQGTSdNGobMZWX7yGx7JvIZaUzvl3Y28WPYFyb4R3JxyMa8c38byvDkoJXIsDiuVxmZuObjeI3riNCHckX5Fj9gVCFD48PDRTdgFJ1GqQMQiEbWmdqQiCa/lTOdUdwv9AvqQrA1HZzPxY3MpYUq/XmEILsFFeZe7qnF2G5pWpuKxftfx2vHtpGkjyQlK5ImSLQgIXN9nOHMSz+eIrpo7Dr3ruc8lEQOYEj+So7pqUn0jMTlslHXV4SdXk+Ufy7z9q1mWN4MMv2iMdgtmpw2JSIzV5WDW/hW0WruYmXA+1/UZyu2Fb1PWVc9F4ZksSbuCEn0djxZt4uVB03ioaBMtFj0qiZzRYRlsbzgCwPlhfbkn42oCf9ZKdiYAZF7+KvR2M75SJWKRiKuic7DYbVwZk0O40h+Ly8bGU/uI1ARwXlgGYT3VBIfLQam+nkUFa7GdFULgJ1OxcvBcEnzCcLic7Ggq4aGijUhEYl4YOAVEcOehd3EKLh7vdx0XhmfRbu1mSeE7nqj3EIWWJosOMSKey76J3KBEdDYj8w6s9rSrXhLen6EhKTxS/JHnuR/MnMDFEf17Va5+D5vTwVFdNbceXO+OuY/KJTMghid7vIAAsxLP58a4kb2is/+/MDosVHQ1EasJJlDhg83p4KShiWCF728mAFqcdswOq6dVzim46Lab/1DFzSW46LKb8ZEqPW22J7ubWJC/pleL462pl3JVdM4vKrRevPyv8F/nYfLixYuXX8O3p9XtTMvKrP0raDB3ohDLeHHQlD8dofz3oBBLOaavo8bUzkc1+/nw9F42nNrFoY5T5HdUUmNqo9tmZlHBWk8b3m1pl6GSyGmy6FhUsBaHy0myNsJTAZCIRR5PkJ9MzbqhC1g1eC4qiZxOq4EaYxsmp40BAXHclnYZj/W7jlUVO9hUvY9H+13LfX3Hkekf87tiCUArU7Mo5WL3AttpZ9aBFXzZcBiAGQmj2d1ynAeLNnrE0rjoXPpoQpiydxkFHZXcmXYlzRY9jxV/zHF9PXekX8HJ7ibqzR1kByRgcloRCVBlbGFJ4bs8lDmBq6NziFYHctrYypLCd4jzCSGwZxGpkSqJ1QRzV8aV3JVxFQmaUDRSOVKRhHCVP4sK1lLe3cS3jUU8c+xTThtb2VSzz1NhNDts+MiU3JJ2aa/X+UDf8XRYuknVRjA3+UJGh6bzZP9J9POP5ab4EbiAUl2d5/ZiRPhIFYhFYlJ9I9jdepyNNXtZefI7ThtaaTbrSPePcqdE2i3saC5hQcFayrsbEYtEvJoznblJF3F+WF/arQaeG3gTMxJGc0f6lWhlanylSmwuJxtO7eKNnJmEKv0wO20esTQqNJ27M676hVgCdxXAHUk9GY1UgcFhZU7SRbgEgWvihhKu9EcqlrC/7SRjo/ozOizTI5YADA4rtxWu97ThLc+b7WnPu/PQu3TajEjFEoaFpLAk7QpezJ5CTlACgwLi+eS8O3k46xqGh6QiE0tQSmS8NGgKCZpQnILLI4qeG+gWSyqJHLvL6RFmGomCsZH9ef/0nl6v6YPTe37RWvt7iETu9lGxSMT46DwuCM/gmdKt7v/X4zxbW/kD2xsO/0ODoP9eNFIlAwLjPO+hXCIlwy/6d+PSlRJZL1+RRCT+w3He4p7bnhFL1YZWj1jyk6nJCUwA4NUT29lWf+jfcl3+EQRBOGfa6P9QDcDL/zPeCpMXL17+K3AKLva0nuDOsyoDj/W7lrHh/ZGI/3/2hlrMet49/RMbq/f1Ov5Q5gT6+sUQqvCjsLOKh4s28UbuTFK1UVR0N7Iwfw0PZV3DsHOELJidNg51nCJSFUC8j3sxekxfR7NZz+baA9Qa2xgUmMCU+JE8X/Y5hztPA3BT3AhujBtJkPLPtc80mju5eufznp8vCsvizowrmbT7Zc/cmASfMF7Knsob5V955ijdGDeCH5pLPUJ1Rd5s7jn8HlaXg+V5s3mq5BPuyrgSX4mSckMTn9YVMKnPMOI1odxSuJ4uu4mVeXMIkvmgd1ioM7fhEgQeKfqIAQF9uDXtMprMOp479hnR6iAuCO/L4z0R4zMTzsfstPFB9R5ClX6sypvD8a4GVBI5jxR9hM7+t4VViELLcwNvQiIS8XHNPsZEDCBDG4VdcCIWifjw9F7WVf0AQJZfLONjcnEhYHM5SPAJpbD9FOEqf7QyFVKRmLWVP/Bc9k0EK3xptXQxbufz2AUnsZpgbugzjPdO7WZwcDInu5uYlXg+qX5RKMUyz/tsc9jpclgQBAGNTMHayu89QRQAawbPo69/TK92rTN0WN1hCReGZ/FQ0UYmx42gyaxja10BESp/lufOZm9bOc8d+wyNRMH6YQvpo/mbn8ruclKiq+GZ0k95edA0ItUBVBmauevQBp4deCOJPmGedLpuuxm5WIpULKG8q4F7Dr/Py4OmkugbTq2xnbsPbXBXdos29gqbWJYzg4EBcTRZ9MzLX027tRu1RM4L2VN45fiXnja88dF5fFKXj1NwkegTxuu5M3t5wn4Pu8tJeVcDIUotdx3aQFlXPck+4bySM50Xy77g++YSguQ+bBi++E897n8LZ6LgG8ydrBw8hwC5Dy+XfcGOphKW5c4k0y8GueSvkXp3prL6ZOkWnuh/PRGqABrNnTx49EPu7zuBBJ/Q30xV9OLlbLwVJi9evPxP0WTW8VLZF72OvXHiaxrM7qGLTsGF9Wc+l382comUyXEjelW0UrWRDAyIp83ajRMXOYEJfDxyCT5SFRKRiBTfCD4Zdec5xRK4fS+5gYmegAeJSNyTIhdKmb6OFmsX8b6hbKkr8IglgC21+bRZu3H9Cf9Wh9XAyorveh3b3Xacyu5motVBnmNVhmYOtlcyqc8wj1fkvdO7PWLptZzpILiT9pb2n8SLZZ9Toq9lUcE6upwWPq0rYF9bBXcceheJWMyynJmsyptLnE8o7XYDsw+s4KmSrTxStAm93cTOljLWVf5Am7WbOlMH18YO4aemMs/5NJo7GRvRzz13yKJn0u5XiNEE8Xjxx+jsRvxkKpakXYFGoqDV2sX9R99HK1PxWf0hPji9BwdOAhU+SERignp29CfE5PHUgOvZ21rOEyVbqDW2E6b0x+qys7RkM1trCwhU+FJrakNvM9FucV/rZbkzkYkk1BjbePbYZ9SZOzjYUcXc5IuI8wklQK7xvM+CIFBrbuemvcvotBnY3nCkl1gCWHzwLc/MrbNxCS6MdgsTY4fwaPFHdNnNFLSdZHhIKkqJzJ0Mt/sVnjv2GQC5wYmeJMEzyMQSMv1jWZ432+NZSvAJY/Xgeb3EEriruFKRmG67mXsOv0+TRcf8/DXsay3ntsK3WZA6lkeKNnGiqwExIk9AxG2Fb3NMX4/d5cDucqCRKlg1eB5RqkDGRPRDIhLzzIDJLEwZw6uDpiMRibk6OucX4Sm/h0ws8VRtnht4E5dGDvB4lu7KuJIJMXmsGDznP04s/dz7Znf90gt3Lrp+FvrwWyEQ4A6keD77Jlb3eJYC5BpuS7ucd4Yt+kuJJQC93cTNB9dRrHMPT6/qbmbxwbco1tVy88F1v5uq6MXL34NXMHnx4uUvT6fNwOKD6zwL9tvSLvO05y0oWEunzUBFVyOFHVX/UtFkczp4sngLxrMid090NfD2qZ3UmdoxOixUGpqZtOtlZu5fTpWhxZM2eC6xdIafL2ZkYinBSh+SfCOYGn8eOpuJj2v2A3BBWCYhCi0mp415+as43TNY9LeoMbZRb+pg9ckdnja8y6OyPe15dxx+h8WplzIhOo+8wEQAnijdQrfdzP0Z43s91oXhmUSqAglRanm037Uk+4ZzV/pVBMl9MDgsTN/3Jvt6kgDv6zsOjURBuMqPPj4hdNvNbKzeR4fNgNFh4dWcGUxPGA3A9oYjhCq0vJB9E8f09QwNTUGEiFh1EDtbjqHuSRsDd4T2qorvuCX1UgLkGp4eMJkSfQ2P978OP5mKRSmX0Gbt5sG+43kwczyCALXGNjRSBZdGDmRF3hzmJY9BLpai7fF2fFC9hyWF7/DOqZ8AUEnltFu7mZ88lvn5qzhlbOXx4o+J1QRxQ9zwXtfkocwJ+MvUngj+M+jtJp4u/RSz04ZILOa1E9sBGBqcwltDFhDW0573wrHPzzkM2i44abXo6bZb8JUquSnhPCJUATzV/wbPdQD3ANN7M8YReA6x0Gkz8M6pnbRZ3IEOHVYD75/aTdNZHjtwVyj2tJYjE0l5JWdaT+ueiVsL12NyWj1iVYyIZwfeyNvDFpHkE45TcFGiryVUoWVl3lxW5s0lyTeMCHUAY8P78dHI28n0i8FHpmJAQB+2nHcHF4Zn/V2emjMCL0zlx53pV3qCTYIUvixKubhXde0/gVpjGwXtlVgc7kCPFouerxuO/q74aTB18ljxZs971Gpxh12cNrT85v1ClX69EhsDFT4k+ob/pcQSuFscn+p/A3KxlBpTO9fveZUaYxsykYSn+l/fK9TEi5d/Fl7B5MWLl788KomCJWlXoJLIeTNvFrmBiSztPwmNVMHilEvQWY3Mz1/NHYfe5Ujn6T8dNe4UXDSYOnr1zDeYOmm1/C01zGC38EldAfkdlQAsTr2ESbFDAfi07iAaqZJXj29nYcFaDE4rfj3+lb+HDquBl8q+oEhXTWFHFQMD4lBKZEyPH8XtaZezIm82IQoteUFJv/scNcY25uWv5umST7giKhu1RM685ItI8gnjwcwJhCv9GRqcgtVpJ9Uvknv6Xs2Q4GSyA+KJ9wll0cG1nsdK00aSpo1ib+txGsydPFG8BafLRR9NMK/lzOj1vNfFDnUntp1lwveVqZgSP5LLIgfyRu4sJIgIlGuYGn8ej/e7DhcCPlIlw0NSqOhq5LWc6dyfOYEs/1i+qDtEu7Xb81g7W8rwk6lZM3gezx/7nGCFFoVYxtohC/is7iDvn97NgMB4ZGIpr5d/xdS9b1DR1YRaKic7MJ4AuYYAhQ8zEs/nishsAE4Z3QvSMeH9yA1K5KnST0jyDSNEocUhOPGRqjjaUf0LX87Ski102ozU/ky8+ss1PNF/EuFKf54o3szS/pO4MCyTyyIHIBKJeDN3FueHZvLkgOt/EeMsFomJ8wkhRhPMS4Om8vSAySw78RW7WsqoM/We01Nraj9nyl6H1cBdhzbw/uk9PFa8Gb3NxPb6w2w4vYvFB9fRbu3G6XLSYtFz9+H3uPPwu+xoLiZUoeXevld7Hqfd2k2XzcTyvDk8n30TB9srsbtcvDRoKg9nTuSqqBx85WoSfEJJ8g3zRHtHqAMQA0tLNtNi0SOXyJAg5tHij35z1tAf4YzgOvNdP/Oz8/9pzMBvYXHYqDO1Mz9/DUsOvcP+9graLF3cdWgDj5ds5tO6Arp+pUrSaTVwa+F6drWWcVvh2zSb9Tx0dCPfN5cwP3/Nn/Z//RWRiSX09Y/hkaxreh1/OGsiWf6xyP6AZ9OLlz+LVzB58eLlL49SIiMnKJGto+4iXRuFQiLjo+r9rB2ygANtFUzd9wYmp40ghS+RqkCPEfqP4BRcnOhqYPKe11hzcgd6m4k6Uzvz8lfxePHHHtHUaTOS6BNGblAid2dcRW5gEtGaIK6OzuG62KGEKf34oaUUm8tBmNKPFbmzMTltNJ+1k99g7qTa2Pq759Rs0fNNYxHgrujEqINYnTePkWHpvHJ8G3KxlNVD5nFL2qU8U/opjebOcz6OIAhYnXasTjv5HZW8Wf4N64YsIECmIVIVyFOln/Bov2uZl3wRjeZOMrTRKMUKpsWP4uGsibx6fDunja0oxDJW5c1hUcrFlOhrUEhkaKRKpieO4vmyz2gw63i1p3pyhi8bDrsX8nb3Qt7uctBhNaCRKpmXNAaNRMGLZdt46fg2xPQkCZZ/w5JD7+ASBMbH5OFwuVhTsYPr+wzj0uiB6O0mrojKJtk3ApVEzgvHP6fBrOPiiH5opSo6bAbEiIjXhDA6rC+f1R1kX2s5X9Qfwui0UthRhelnAzlVEtkvItjDlH7EqoNYkTeHQLkPz2dPQStVMTf5Ih4u2oRDcNJHE8KDmROQiSRUG1tZfXIH9ebOXxjVw1X+PD3gBsq66ll78nuyAxM4bWgl0ScMtVTBLWmXeCpTepuJZrPO02YpFomRi6VsrcnHJQhcGtEfkUjES8e3AZCujUIpkdFk0bGwYA3VxjaazXrKuxrptptxCi7u6zsOpUTGgfYKvmo8glIq5/7M8UyMGQwC7G49gVNwESBzC7bVJ3dwvKuBl8u29Xodzxz7FKfLyZGO03zXXMIjRRtRSWSMjeyPVu4WKyKRqNccJJ3NyIz9K9jbVs49h9+j3tTBooPrKGiv7InJN/zqd+CPUGtsp0Rf62l7a7Ho2dtW7pkp9mdpMuvotP7t/Ws26z2VuT/KKUMLP7Yc6wkv8UNA4J7D7zN13xuUddUjEYlJ9AlHIT53SqBGquTujKuQiiRUGZq5cuezHOo8hQgRd6RfgeJPtjL+VWmzdrHyZO/24dUnd9Bq/XPvhxcvfxRv6IMXL17+K6k1tjH3wEraexao/jIN64bO7+XFOYMgCHTZTZ45SOD2CMglMprMnXzVcNQTBHBBWCal+lqae+Kf3xqygATfMPQ2Ex9U7yHeJ5T8tpN8Xl8IwJK0yxkSnMzdh9/jdI8YGhQQz23pl7Ps+Hb6+scwISYPJwKPF39MbmAiF0Vk/Wb7kNlp42B7JUqJjHRtFCqpgg6rgRv3LENnN5IXmMiDWRNZfPAtqo2tJPiEsjx3dq/ErTOcmWE1N38Vw4JTGRuRhUIsJ1jpy/z81ThcTpwuF+NicpnUZxhPlmzhcOdpZsSP5oqYQTxw5AMWpV5MsELLjH1vYnLaOD+sLzenXMLCgjXMSbqQn5rL+KnV7Tm6KW4k2xsO024z4CNV8taQBailCn5sLiXBJ4xiXQ0XhmdRoqshTOXPfUfe556Mq4hWB7P44DrkYikPZk7k4aKNGB1WHut3LTHqYB4p2kSloZl7Mq7mvNA02qzdzM9fw+Q+I4j3CeHBIveQ88f6XYtCLOP+Ix/gQuDW1Esp724kXhPKhJg8Tyz5mc/Altp83qz4xvMZOhMgMTPhfK6PG45/z+31NhOf1OYjE0v4tO4gt6ddTopvBDWmNh48upFHsq4hUhVAtKb356/B3MnignXUnlUVUohlvDN0EStPfscxfZ0ncv7D03t5//RuVuTNIVkbToO5k4X5a2my6LgiMpsRoWnobEaePfYZw0JSWJg8lk6bkTsPv0u0KohHsiZSbWxDK3fH15foahkdlk6I0o9DHVWc7G7m8/pCT9DHrpYyniz9hH7+sSztP4lnSrcyO+lCHj66iXpzB2qJnCXpV7DsxFfo7SYC5BreHXYz1YZWotSBRP7ODCWz00ZBeyV3H9qAi78tRWQiyT8cRFBrbGdB/mo6bUaW5c4kRh3E3Yc3UKqv4+GsiZwf1vdPtW6dNrQyP381F4ZnMifpQixOO0sK3yFAruGxftcS/AfmO9UZ25m5fwU6u5GHMicyKDCBe4681ysk46XsqeQGJf5mrLrN6WBP6wnuOfKe59htaZcxPjrvN1t7/1vosBqYm7/K04Y3NeE83j21C5vLQaw6iFWD550zVdKLl3PhDX3w4sXL/yxOwYXRYcV4VhuS1WXH6LD+IgRBEAROGpp59cR22q3ddFoN1Js6eLP8G5rMnXxZf5jLowZyc/LFAHzfXOIRSyvyZtOnxxPgJ1dzQ5/h/NBU6hFLALlBSdx/5ANOG1sJlPu4d4BFIjqtBibGDsFHquSzukIeLfqIafGj6HaYcbmE32wbVEnkpPtFs6e1nBZrFxKRGIlIxKKUsQDkd1Ry1c7nqDa2IhNJuDvj6l9dHIpFYgLkGl7PmcmQoCReLNuGRqZAbzPiI1XiEFwsTL2YUKUfHTYjMxJHMzluBDE+wZgdNm5Nu4yVFd/xaV0BMxLOB+CH5lIm7nqR5h5PxuT4ESjEMu5Mv5Ip8SNZnjebILkPF4Zn0mEzsKLiW54v+5x1VT+QE5TIntbjPFL8Ec+WbmVF3hy+bjjKqpPf8VL2VJQSGS7BhY9Uic3l4JGij1hS+DaVhmYkIjHR6kD8ZBpStJG8PXQhV8fkMDAwnpzABEaFphOrDual49twIZCujSJGE8yuluNcEjmgl1gCt0dof4/f6vLIbD4aeTsTegbeFnRU4hDc71Gnzcjyim94s+IbThtbubfvOB4u2si8/FVEqgJ4b/hi0rSRvxBLnTYjDx39kFpTO3KxlKcHTCZeE0qgQkOH3cDethPu6lD+Wl47sZ3VlTswOq182XCILrvZ3RZq7eLiiH6MCE3j/iMfUNhxiheyb2JsRD+m7XsTk8PKGzmzWJgylgUFazllbKXK0MxTpZ/wWf1BKg0t7G8tp69fjCfw4rvmYuYcWMmTpZ+4P9syDSJEqCUKVpR/y8KUsfjJVLw8aBoiQcTTA24gUO7DvRlXs/rk9zxWshnnH9iLVUnk5AUlcWfGlb2OPzngerL+wSACmViCSqrALjhZXLCOOQdWUqqvQ4wIf5kGieiPV5mNDgs7W47RYTPwUc1+Xj6+jdsL3+akoYlDnado7hne+3uopHKy/GMAeKnsC04bW3C6ev8+cgqu343G1ttNbPpZEudndYX/M2EHComUmQnnIxdLeT13JtMTRvN6zkzkYikzEy9A8RfzZHn5a+AVTF68ePmvwim4qOhqZH7+aixOO0FyHwLlPpidNuYfWE1Fd1Mv0dRhMzDvwCq21R+mVFfLG+VfM/vASkaHZ3Cksxo/uYbJe5aRFRBLln+s5379/WOJUgV64p4FQaDN2sXBHg/TGTZW72VcTB5RqkDeGrqAN/Nm02E1oJLKebhoE8vKv0ImkbAweSyPl2zm/dN72NZw6BcpWGdaqM7893undvH+6d3MO7Ca04ZWvm0qptLQzIyekIQzPDNw8m8uPlstXZR11fNC2eek+kUxKjQdqUjCS8e/5N6+49gwbDEN5k58ZEr0diNR6mBiNEGeGUu+MhWVhmZ0Nnc73A19egceTEk4j4K2k6wfupBThhY67UbifEJZO2QBAwPi2N5wxGNEL2iv5J7D73layqLVQdQY2xgRms6U+JFYnHbClH48WvwRd6ZfSaQqAJvLQYu1CxEiXh00nYEB8cglUkwOK3tby7nvyPsICDzR73rOD+vL/Uc/4MHM8aRqI1mSfgUPHd2IwWFh7oFVv/D+BCl8Wdp/EremXsri1Evwk6uZlzyG21Iv4+kBNxDcE6JQb+pgS22++z5y9zGz006NqZ33T+9BJpb+QowBBMg1PJg5kVCFltdzZzIqNJ1Xc6ajEsuxOGwsz53taan7tO4g4J5/NT1hNP5yDf0D+vD8wJtYkHwxr5d/hQuBRnMn6dooPq8rxCE4een4NsKUWr5uPIrBYWFt5fe8cvxLwB0GEa0KJM4nlFdPfEmIQsvU+PMAPBWvYcEp3JVxJW+Wf82O5hIKOirZ0VjMysHzeOX4l+gcRgrbq1ieN5u9reUe/02X3YRLcGFyWHu1sf0cnc34ixj+d6p+otP+j3lxwlX+LMuZQYw6CLvgpKGnLfWF7CnkBCWi/BODcTVSJeOic5mWMApwB5CcEeivDJpOsm/4H3qcIIUv92eOZ0RIKkv7T2J5xbeeQb/hSn8A7jn8HgfaT2J2/NJzBm6/2MNHN1HYWYUIEVdGDfK0591W+DZtZ/n4/lvRSJWMCktn63l3kukfi0Iio69/DFvPu5NRYene0Acv/xK8gsmLFy//VQiCgBMXLgRCFVpWDZ7HqsFzCVFocSHgEs5u/nG3Py1MGUuAXIOfXMP3zaW0W7t5rHgz5V2NvHriS6wuOx/V7OfiiP6e++1vP8nqkzs8npQ6Uwfz8lfTZTcTINcwNrwfAFvrCqgxtvFG7iwiVAGka6N4MGsCQXJfBgcnAfBm+TcsLFhLu7UbX5mSq6NzWFf1o8f43mV3t4aVdzXg7KmuXBk9CD+ZCr3dxPW7X2HNyR0MCU7m++bSXtfjw9N7f3XnWRAERIh4+OgmSvV1PFb0EWMi+rHk0DtUdDfyQtnnqCVyLo3oT0F7JXccepdvG48SKPdBLpFy1+ENfFy9n3lJF9FHE4Ld5eD75hLP4w8KTGBT9T5iNEEsyF/DgMA4NlcfoNNmJFIdwLCQVLbVH6LO1MGCZHd17IwHYUhwMnekX4GvTEVOYAIuQWBb/SHy2ytxuJy4EJCe5YcR4d55FvckYevtJl47sZ1SfR13H3qPXa1lLC3ZQqNZx0fV+7kmZjA1xjbeGrLAI0o+qt7fy1PWZunC7LRyTewQAhU+mB02AuQarokdTKjSD0tPBTPeJ4RHs65lVuIF3BA3nCz/WF7PmcmY8CymJpx3zsHJNqeDFoseX6mSDcMX01cbjc5mRCoWszxvNgMD44nVBDMkKKXX/WYkjva0VpqdNo53NfBO1U7uzRjHmPAsFqdewqsntjMveQxjI/rx0qApPFa0mQkxeUSf1SIXrPBlYcpYfKRK3j31EzMSLuCisCyPCATIDoxnfvIYBAROdDUCsDjlEu7NHMdrx7+krKue8q5GgpS+TNr9Cp/WH3QPsM2eRo2xjQ6rkb1t5ayt/P6cYQTt1m5P26hMJOHa2CGIEVGir+Xew+/TYf3HPExikQjlWV4gESLUUgVi/vyMHncFeVivuPMMv2jStJHI/4T4srkc6G0mpGIJOpsRiUjMk/2vZ+2Q+WT5x+JCoMHciV04d4VZIZYxNrIfIkQs7T+JJelX8GrOdKQiCaNDM5D9icrZXxmNVEmwUusJeJCJJQQrtV6x5OVfhtfD5MWLl/86HC4n5d2N+EpVxPS0QdUY2zA5rCRrI34xBNRot7C+aid7206wIHksDxdtwuD4mzF8VGg654f15YWyL3i833XsaT3B5toDiBGxYfhiknzDabd283TpVop1Ne4BrApf3u2pAr2eM5NM/xhP2ITD5aTF0kWVoZn1VT9SpKsB3Au694ffwnundvFFwyFCFVpWD5nHtvrDrDr5HSqJnA3DbiZGEwy4fRqFHVW8UPY5rwyazrPHPvUsPi+O7M8X9YcAPKmB5+rrN9otHOo8zd2HN/Sa9eMjVfJ67gzeOrmTa/sM4YPqPexpPQFAln8sxT3nPCo0g/PD+pLhF021sZWvG4+yp/UET/SfhMVpp8rQQkV3IxOi82ixdtHXL5ok33B0NiOvl3/F5/WHuL7PMHykStZUfu95/sFBSTyYOYFms44E33BarV1M2fs6crGUN3Jn8VjxR1QZWpCIxGhlKjptRk+LTqZfNHbBdU5/TKo2kltTL+WuQxswOq08O/BG+qiDee/0boYEJ7O64jtezZ2BTCR1zxXqbmDt4PkIwNHO01wQnomvTEWzWce2hsOMj84jQKHB6LBgdznx7/HB2V1ODHYLAYre6XbgFku1pjY+qtlPh9XA3RlXY3Za2d16gm31hTyfPQW1RMGm6n2srtzR677hSn9ey5lBnE8IZoeNIl01dpeTD6v3Mio0g9fLvyIvKIlxUTmEqvxYUfEtgQof4n1CPZWlM8xJupBIVQD9/Puwq+U4g4LiWVL4Dq3WLkaHZnBxZH9Wn/zeHYsu13Cwowq9zciwkFT8ZWq+aypmWEgqM/a9SXfP9yVGHcRdGVfSYOpEI1XycNEmBATuSr+ScTG5yM4SHF02M1vr8llZ8R3LcmeSro3iYEcldx3awIOZE9w+I9nftwA+k+x3rKcNTytTo7Mb/5A/ShAEzE476rP8QK0WPbcedLfhnc21sUOYnXThL1IMz0WjuZPbD75NlbGFCGUAD2VNoN1q4NumIkaFZpAblEiRrpohwSmeOPtzYbBb0NmNBMp9UEsV2JwOmi16tDIVfueoZHrx4uXX8XqYvHjx8i/B7nKisxlxnDVgsdNq+EW62L8TqVhCmjbSI5YAYjXBpJxDLIG7GvFdUzEV3U1UG1sZGZrW6//PSx5Dia6WR7KuYU3l90SpApgSP5LnBt5EVM+ufZDCl/v6jmPdkAXE+YTiK1NxY9wINo64rZdYAnfQQkV3IxKRmPqzEuwEBEp0NYyPyfPMkRq/8wVW9aRBjQnPwqdnB7XDauBo52l2tx7nhYE30WbpYkRIKjKRhFWD53J76hU83u86RIi4JLI/VqedelMHTWadJ1rZ7LBhE5zkBMZzS+qlvV7zg5kTaDV3oZTK+LG5lLlJFzIkOBnAI5YuCsvk1tRL6aMJ5rljn3L34ffIDUrkw+G3sqvlOA8c/RCr087kPsP5vL4QQRCIUPljctp4//QePq8/xHV9hhKi0HrEUqTKPUD1QPtJni7dSrvNwFcNhwmS+/J67kxuTrkYuVhCm7UbiUjM8tzZrBuygBh1EDaXg26bGYvTgUoiZ2BAHJdFZfd6Xc8PvAmVRE6KNoJQpR/xmhCC5b5MiR/J0uLNnDa1sahgLfceeY+CjkpEgENwsSB/NU+WfsKXDYdps3SxpPAdVlR8y8qT36KzGdFIlR6xBO4d73OJJQCLy06zpYsttfn82HKMZ0q38l1TMS8f30Z5dxPb6g7RYTN4rsm46FzWDJ7nqYStOvkdzWYdx/R13F74Dg8d3cjkuOFsrNmL2WljSfrlbKrdT4O5E5cgMCAgziOWsgPjPe/j6pM7MDqs7G09gVgk4q5DG3qizbO4L3M8T5Z8QpWhmYeLNtFm7eKYrpbXy7/mrkMbkImlXBCeyeKCdXQ7LJ7vVa2pneXl3xKs1PJU6ScICFwXO5SRoek/E0smtHIV46Lz+Pi8JWT6xaCSyj1pl/+IWAL3Z7ve1IEYES9kT+Hd4Te7q6CCkxNdDVhd557HJggClYZmfmwuxdCTpldnamdr7UGuiM7uacObxtR4d3veRzX7qTb8frIluDdEEImQiiQ8nDWRJJ9wKrqb+KmlDKEnMv+CsMzfFEsAPjIl0eog1D2VS7lESowmyCuWvHj5F+KtMHnx4uUPY3c5KdHVsOTQO7w8aBqZfjHUmtqZd2A1S9Iv57zQdM8f8b8KLRY98w6spt7cwU1xI9DK1J5UtDMEKXx5KXsK6yp/ZGfLMR7JuoYhwcmopQpUkr8vlara0Mr8gjW0W7vRSBX0UYdwrKsOgKf730CkOoBp+9703P680HTuzbgatVSBIAg0WnSsq/yB0aF9EXCR5BtOQXsl2YEJdNvNKCQywpR+WJx22i3dFOtryA6MZ83JHcxPHkOIUkuxrpZ3T/3E/X3Hs6hn7s4Zkn3Cebz/JNqt3dSbOqg3d+AQXLx/erfnNnOSLmRYcCpamZJHiz6iWF+LCBFp2kjKuuoBmBY/ikGB8dxSuB6Aj0cuIVYTTL2pg4UFa7i/73h+bD7G5toDjAhJY37yGEp0NTxz7FOSfMJ5asD1nNA3MDw0DaVEitlhRyyCKkMrUrGYBrOOfv6xdNvNNJn1iEUQ5xNKgFxDYUcVdxx6t1flLF0bxeykC3AKAiEKX/xlGh4r/ojb0i/H6rSz+OBb2M7aDFja7zqyAxN46fg2djQVA6CRKjA6rJ7F88CAuD/VlgVu39M3jUdZXvFtr+ODg5K4t+84VBI5Rbpq9rVWMCVhJGqxHIPTyqqK77gwPIuXyj5nUtxwvm48itVp57a0y3i4aBNddjPZgfHcmX4l3zYWkR0YT7DCl0eKPsJfpmZ8bB6JPmG8WfENpwyt3J52GR1WA/vaKlBL5VwZNYhIdSD+MhUlujpuPriu1/XQylSszJtLpCqA7Y1HeKZ0K0qJjBV5c2izdHP34Q0APDngBjZW78VfpuH6uGHkt5/khj7D8JNrOGVo4Z2qn7g59WKCFL5YnfZeqXDuwBMB6T8YkV1laKbJrCM7MMEtNs06CtpPMiosA63s3OKixtjKjH3L6XZYeDBzAoODkpifv4Z6cwfXxQ7lyqhBxPuEYHba2XB6F+FKfy6O6IfPHxy022TW0WLRk6aNQi6R0m7p5qShib5+Mfj8AwLRixcvfx9/VBt4BZMXL17+MJ02IwvyV1NlaEEulnJbT0Ka3m7CT6Zm08jbCJD/teJcO21GVlR8y/7Wcl7PncV1u1/GKbgYEZLGtIRR3Fa4HqPDypDgZGYmnI9WpiJc5f8PC8Mms47bC992Vwzy5hKs8OXJkk/Y03aC9UMXsrvleK85I6EKLc9l30SLRU+GNto9w8mip97U7hEXt6dfjiAILDn0Dr4yFU/2n0QfdQjvn97Nu6d3EarQsrT/JFaUf8uFEVm8evxL1g6Zz+2H3qHd2o2PVMkNfYazruoHnIKLNG0kzwyYzMnuJo511bOu0h2trhDLPDv0d6ZfQbNFTz//Pqyv+pFSfZ3nnKfEj+SmuJE4BYGnSz9hVFgGF4RlehaGbZZuRLhFa2lXHcOCU2i26JEgosbUTrpfNF02E6EqP3ylKrRyFYIgcNrYSrfNzO6246yv2sl5oencGDeCelMnS0s2k+gTyrMDb2LqvtcxOqyka6O4OjqX5459iguB80LTuSZmCL4yJR9W7+XrxqNoJAreGbaIOw6964l/95Eq+WDErYQp/ei0Gqk0NPHQ0Y202wyoJHLeHrqQCKU/ir8jylkQBOpM7TxVupXCjirAHaf92ei7uWbXS1zfZxjX9hmKwWZhQcFqlva/no2n97IgZQx3H36Pm+JHcrjjFGMi+qGSyLn3yPuMj8nj/dO7sTjtZAfGs7TfJLQyFS5BoMthxulyYXPZCZBpaLZ24RIEHIKTD07vQSoSc1va5fjIFMjEUgx2M41mPUW6ap499qnnvJflzCAvKAmRSITeZmRbw2EG+MeR6hfZ0955CpPDxu7W45Toanm8/3XcXOAWXVPjR3FV9CBm71+Jzm7kssiB3JJ6CcW6WuI0IfTxCcHhcnK8qx6XIJDhF+2pzJ4RVUaHBYvTjkwkRStXYXc56babkYkk+MiUiES9/Uk2p6NX653N5ejlQ/o5bdZunizewp42d/upSiLH7LShEEtZljuTNN8IlD3ffZ3NiFQk/sNi6ez3/uzz/PnPXrz8N+AUXJwytKCVqQhV+gHuaq0gCJ628v8EvILpHHgFkxcv/ziN5k5u/tncGD+ZipWD5xKvCf1L/uHvtBnpspsJkftSpKvh8/qDLEy5mACZhjpzBy+VfcFj/a79xQDTf5Qmsw6jw0q8TwhikZh2azd6m4kfm0tZ0SOWBgbEc6KrHpPTRqjSj4czJ9Js0aOUyPii/hAXR/RnaclmnIKLMKUfHVYDdsFJrDqIJelX8HTJVpqt7tjjyyIH0s8/lmePfYbQ4+tZnHIJUrGE1Sd3sCJvDlGqQIp01dx9eAPPZ08h0y8Gs9PKLQfXU2loZkx4FndlXMXjxR+zu/UEqdpIFiaPpc7UQZGumv1tFTw78EY+rtnP+WF9GRmShtFpxeFyopEqe+2iO1wODA4rEsS4cIEA7XYje1qOc0F4JptrDpAXnMiSwneZn3wRE2IG02LVM+/AKuYnj8HmcvJyT6JeH00INcY2BASy/GN5KHMCu1qP811jMUv7T6Ksqx4xIl49sZ0HM8ezvmont6RcisFh4ZXjXzIr6QI2Ve/jcOepXu9RrDqIN3NnY3baeKp0K9MTRvHcsc+4Le0yPq7Zz+LUS0jyDe81kPUMJoe1l7A22i1oZEoEQaDW1Mae1hO8/DNf0ejQDGYlXYDJYWV7/WG+bS7mwcwJbKrez+HOU4Qr/Xl24GTWV+3kh+ZS1BI57w2/hVZrF+naKCq7m5lfsJpbUi/lkogB56xa6G0mNlXv5Z1TuwhW+FJv7iDTL4ZnBk4mVOmHwW5mT+sJtDI1jxZ/1CuwIUYdxCuDphGpDqS8q5Hvmoq4NGIAfTTBVJva+OC020tVpq+jVF/HsJBUyrsbPH66M2hlKk9V6tbC9QTINawcPIduu5kF+WsBgeV5c8jwi6LbbuGbxqMMD0mlVFfHgfYK8oKTSfQJxeq0My9/NQ9nXUOqr7sN1+5y0mrtwkeqxE+uRhAE6k0dqKRygs4Ktfg12q3d3H/kw16fhTWD5/UScF68ePl1zk6r7aMJ4fnsm7C5HCzIX4MgCCzPm/0fI5q8HiYvXrz8S4hQBfBA5oRex+YmXUSsOvgvKZbAHe/cRxOMWqZgYGAcd2ZcRZQ6ELVMQZJvGM8MnPxPF0vgjj5O9A3zLLaDFL5EqANI1kYgRsRlkQO4JnYwS/tPQi2RE6b0w+y08dyxT3ng6IfsayunvKueZwdOBqDZoscuOIlSBfLMgBt5tOhjj1g6LzSduUkXUayr8YglgCEhyehsBtYNmY+fTE23w8yPzcfYMHwxUapAfGRKQpR+vDxoGtMTRnFH+pX4yzXcnXE1k+OGMy/pIhrMnRzT17K/rYLH+13HM6VbyQlKZHfrcerMHTxW/DHbG47gElw0mDpps3bjcDk4pq9n3M7nKeuqxwVUGlv4vO4ggXIfPq7eT4hSy/aGIzgEJ6+Xf81Lx79g3oFV6O1mVlR8R15QIvOSLgKg2tiKgEBfv2imxY9i6r43yNBG88zAydxe+DYPHd1Il93Eqrw5PFf6GYc6TvFw8aaeVLcpuASXZ4H8aNa1rMybg1wspdXajQDccfhdDnee4tljn/JE/0m8VfUjB9pPsrBgLbqzIuD1Pf/dZNaxouJbT5tju7WbVSd30GTWYXBYqDN1eMRSTmAC03o8MT+2HOOL+kJK9LVcEJGJRqLg09qD3JxyscfDNG3fm/zQk4Y4Jf48vm0sIlTuR5NZR7DSl80j7/hVseSO8d7L6srvsbrs7qpMTzLdfUc+oMWix4VApn+sRyxpZSoWJI9FLpZSa2rnzkMb6LQZebz4Y949tYsZ+1fwfXMptxe+w+f1hTxStIlr+gzh/szxFLSfZGhwCiNDevsCVw+eR4ImlCClLxqpgg6bgen73mR+/hqsLjtBCl8C5Bq67RY21ezj+bLPWVL4DhHqAFK0kTx0dCMLC9ZidNrwkalYdXIHnXb3DLUiXTXX7nqZj2v20223UGVoYfr+N3mp7Itebae/htXpoNmi63XstLEVi/PcvicvXrz0xuFy0m4zYHHaKeuq55aD65l/YDXNFj3dDss5ZyL+p+MVTF68ePlTVBmauefwe72OvXpiOyX62l5BEH9VFBJZr8QrsUjcy8z/r0YlkZMblMQ7wxaxIHkshztOs+bk9zw78EYezpzI6+VfYe25ziEKLZdGZuN0uePBzyAXS7ALDs9gVYBmsx6z08rO5mO9nm9p8WbygpI52d3EbYXrebp0K1/UFzJt75s0W/Se9zRc5c/0hNEEKnzosBrYWpvPhWFZPF2ylX7+sRzqPMXMxNF81XCE08ZWni39lBTfCF4u28b+tgrerPiGJouepSWbeazoY9qsBl49/iUmp41bC9ezvf4IBW0n8ZWpUEnl3Bg/giZTB1PjR3FH2hUAfFF/iCh1EPOSLmJZzgw+qzv4C6O7r0yFTCzB7nKyoGAN1/z0ErWmdjQSBXGaUBwuF7ekXYpMJCFc6Y9WqkJnN2F0WLk97TKe6n8D8T4hBMh9WJYzwz2XSBC4NfVSFGIZDeZOZuxf7klfuyPtCs+Q4TpTO0uLN9Ng6uCBIx/yYfVelhZvRm8z8UzpVj6o3sMtB9/C4XKL2ssjB5IXlMSEmME4BRcLk8cSqwlmaHAK71T9xNHOGkaFZeAnVxOpCuDl7Gm9XuuVUYOI8wklWh2EwWlm9oEVPHDkQwCPWOqwGjwiDtwtaWeimMdF57IsZybPDJyMCHcYgagnUU4pkbMw2T2g9rF+19Fg7uDJ/tejkSi4K+NKtFIVL2RPIVIVgNVl56GiTZ6Bzq/nzqTFoueZ0q3clX4lsZpginW1vc79i7pCuuxmknzCWDV4LgqxDKPDis3lIFSh5Y3cWUSpAz3hHVKRhCpjC7cXrufFsi8QEOijCaHbbsZfquL2tMt4u+onpGIJ3zYW4RCcrDz5Hc8d+5R5+avosps52FH1u6KnwdTJzQfX0mDuRCGWkuTjnrH0RMkWvm8u8QRB/KfTbTf/4uf/ht/PXv4aKCQyBgUm8EL2FMSIqDI002Lt6vE7znZvCp6jKv+fzF/rbL148fJvRWczctehDT2eJZW7rN6TTnb7wbcx/Acl5f0RTA5rr1kvdpfznPNi/r9RSmSkaCMRiUSMjexHWVc9u1tOcKTzNDXGv7VCxmiC6LAZePDohwgIBMg1SERiThlbWVq8hcf7XceAgD6IEXGiu4FHiz/msf7X0d+/Dw/0HY8YEce7GthYvRexIMJXqmJy3HAe63cdL2TfSD//2F7G+zPtZUqxlL7+sayu3MErOdOIVgfyyqBpuFwu5iZfSF+/aAQEXj2xnYKeQb5L0i7H4XJSpq+jSFeNwWHhroyrSPAJwym4KNHXEKDwYUXFtzxctIlaUzsXRvSjVF+LSirn6ugcMvyimZEwGoPDio9USbxPKM8f+xwAf5lb1O5vq2Bz7QGeH3gTEpEYu+BEhIg382YRow7m0eKPUEnkrB4yjzvTrmBfewVT972BgMCQ4GTkYimz9q/kvR7P1/iYXIJVWtK10TzZ//pe79PspAso0tXw8vFtNJg6WZi/lp9ay3i06CMeyBwPwN62ci774Wl2tpQBMKnPMGRiCdGaIOanjOHhzInIxVLeP73b/V72ncAjPfOwFBIpH9Xs59vGIqqMzWytK+j1/PntJ9FI5exsLmVRwVr0djPVxjbMPfOhOqwGXj3xJZ/WFaC3meiymfmq4QgRSn9eHjSNBclj8JerGRqUzJu5s3ii/yRClO6WFF+pgmTfcJbnzWHZie18WneQUl0tW867g37+fZBLpESpA3niZ9dkRuJolBIZs/av5ER3I202A4sL3kJnd1eqhga750q9e3oXH1TvRmczYXbaeu0221xO7D0iVC6R0s+/D6/lTAdAbzcj4PY33dBnOI8UbeKG+BHsb6vgvr7jCFf5My95DFdFDQLg68ajntloK/PmeFItfw2xSIRMJEXRE1//eu5MhgenIkKEUiJH/HdU0fU2E62WLs/PZ37v/Kt22DusBpaXf8NpQwvgTiTcWltAqb7eK5q8/L+hlMiI9wlFdZbHM1jhS7BCe8602v90/npn7MWLl38bfjI1zw28kRh1ECsHz2VQYAKv584kwSeUFwdNRS356yTkmRzuast9Rz6g1dKF3eWkVFfLvAOrqDd1/LtPD0EQaLHouevQBgYHJZHuF8VTpVvdi0VtNFl+scSqgzne1eDxLK0ZPI8XB05BIhLTatXjK1OxOOVS7s90iyO5WIpcLOWujCsJVvjyRP/riVQFMC1hFKn+UdydcRX3HH6PT+ryiVQForOfWzyaXHa+bjjC/rYK1pzcQbvNyN7WCpQSOcWdtSztN4nrYod6bn9/3/H09YumSFfD6LC+LM+bja9UxZvlX7M49RIADrZXEaMOIlYTjM3lYNmJr9DbzTxZ8glPlGwh3ieU2YkX8FDRRt47vYuvG4+iFMs8nqW1Q+ZxR7q7ElXe1YhaqkDZk7wmFok42lmDTbBzT8bVCAi8VfkDLgT2t5YD8HTpVtZW/sC9R97HITgp1tUgEUs42lnNya4mXIKLt0/92Os6fFF/iPNC0znSeZpxPz1Pk0WHUiLjtvTLCVP4ec7nzBDSm1Mu5uKI/vjIVEhEYsKU/oSq/Ogf0IdUbSQfVu9lbv4qbC4HE2MGMyQohQnRuawePI+ttQV83XgUgDHh/VBKZDRb9DxZ8gnjYvPcM6Bkbh9QrCYYh8vJrtbjbG84wuvlX7O55gBbag/wevnXPFz8EYLLhW9PWIFSKic7MN4jlmxOO0c6q5l1YCVT9r5OY88w3/WndvLaie2eGWV1pnbuO/J+r2uy9uQP1JraSfeLIkCmIUCuIcE3FG1PpWpMRBZXReUgFUnIDUqmzdrFwvy12AUnwQp3e57ObmR+/mpO98R1OwQn7T8bYmt0WFFIpCgkMl4o+5zcoCRPq2mAXMMNccN73X5YSMof8i+Fq/x5NWc6KwfPJcMvikCFDw9kTeDNvFmMCEn902EvepuJD07vYdb+FdSZ2jE7bOxuPcHEXS9S0fO5+meit5lYVfEdH9ceYF7+amqNbWypzWdZ+VcsKlhL3X/A7zYv/xvUmdqZn7/akyjqPtbBnYfepcWi/zef3Z/HG/rgxYuXP4UgCOjspl5ta51WAxqp8lcHQf6nYHc5Pe1IjeZOxu18AQH3nJqp8edx75H3sbkcDAlO5v6+4/GTq1FJ5FgcNpqtXQTINGjlfy4R6++l3drNc8c+44fmUvpognl2wI3ccehdAuQapiWMIt4nlCdKtpATlEC0KpC+fjHcc/g9Xho0lRpTO34yFY0mHYm+YbxR/jWXR2UTpPBBEKC8uwG1RIHN5SBZG0G33czLx7cRoQpgTLg7de3z+oM0m/W8NGhqL/9WrbGdhQVrWJxyCQfaTzI6LIM1J78nNyiRSKU/Q0JSWFb+Fcm+EXT0pMmBuzo5PjqPlSe/dae3ydVUdjezqGAtHTb3YthfpuGZgZO59/D7GB0W3hl2My+VfeGpUp0hXOnP/Znj6aMO5oeWUi4Kz0ImkmBzOijoqCRU6cdjxR9jclhJ1UYwPfF8aoxtaCQKcoMTOdHVgN3lZE3FDh4fMImXy7b1eo4En1BezJ7KaUMLSw69y0uDprLu5PcU62sRI2J8TB5f1BdidTmIVAXwWL/rmHdgFS4ETziA3u5uwztTWQIYFpzCQ1kTey3cO61G1lTu4KOa/b1eY6ZfDHOSLkQrU3Goo4owlT8PHd3EzSlj6R8Qh8Pl5LZDbzMsOJWhwck8VbqVIcHJPNbvWk8LaYfVwLIT29nWcLjXY18aOYBbUy875yDjM+e0rHw7X9QfItEnjNdzZ7Kt/jCvl39FoNyHdUMWoJLKWZC/hipDMyqJnEeyruHVE1/SaNahkshZP3QhvjIVfjI1J7sbMTisvHDsc04ZW9g04nbAnfxYoq/l1sL1hCn9eDN3FianjXkHViEAK/PmEKkKYE9bOQ8d3YiAQKw6iAazDq1MxdykC4lRB3H3kffwl2t4PWcmcpGULofZ04Z3NvOTxzAxZvAfmlf0z0qyazR3Mmn3K1icdsKV/oyPyWVFxXcICIwMSeOhrIn/1JbfM3Ok5h1YRbfDggiRR0heHpnN4tRLfvV99+Lln4XFYeOrxqM8VfoJKomcFXmzabcauPPQuwC8njuT7MD4/4i2PG9K3jnwCiYvXv53sThsFHaeIlYdTIwmCIPdwp7WEzxctKlXCEKsOoil/a/n9oPruT9zAjlBCeS3n+Sew++zKGUs46Lz/l9Ek8Vhp1hXzUc1+xkXk8v6yp3cmXElVqedVmsXn9UdZHxMHjHqIFosXYSptNQa20n0DcfitKGVqrEJDp4s2cLwkFQGByXxzLFPKdXX8Xi/68gOjEOEmF2tZThdLp7piY4eEpSECBH72isAeHrADYwKzUAqlqC3mXi6dCvfN5cgQsRtaZfxVcMRTwLd1vPu4vvmEl454Q4zWJRyMQa7hbdP7QTgocyJlHc1ADAl4Txu7Une85UqeSBzAgXtlWT6x/BEyRacggutVMXbwxZx9+ENVHQ3Ae42j9V58+iwdROuDEAkEqGSyAlT+dFk0qF3mHi5bBsnuhp4asANhKv8eeDIh/Tzj+Wm+JEoJDKeP/YZBoeFuzOuprC9En+FhvuOfOC59vOTx3B9n2G0Ww0syF/NBeF9yfCL4bHij7kn42ocLifJ2ghuLljL9X2GIxLB+ir3a7wwLJNb0y7jlePb+L4nmCEnMJGDPYLs56Ipv+0kNx9cB8DU+FGk+0XywJEPcSHw1IAbONXdwurKHVwUnsWsxAtoNut49cR27u17NSJEVBtbebp0K66ez/BVUYNYmHIxgQofdD3tpdP2veGpEoUp/dgwbPHvioYOq4GPavZzdXQO4Sp/umxmvm48Qm5QEnE+IbgEFye7m7mtcD0vZE9BJpLQbjPwbOmnTE8Yxb62CvoH9GFESCqz9q1AJpHiL1czIiSNb5uKWJ47hzCVHzannWJ9LeFKf6LUgZ4FvyAIJPqGYXLY+K6pmKdKP2FQQAIPZU2k0tCEVCRhR1MxMxLP57ljn3Jr6uW8f3o30xNGsaLiO75pOtrThjeXDad+4rP6QuRiKZtG3E6kOuDv+k7+PThcTsq73WlhZ/unBgUk8Hj/6zxVvX8mgiBwytDC9Xte9RwbHJTM0v7X/b/6Mb38b9NtN7O94TBZ/rGkaCOxu5wcbK/EJQjkBif+3TMM/9l4BdM58AomL17+u+iwGhCJRJ5qV7fdjM3l+EXrjcVpJ7/9JHcd2kCIwpcVg+fQZTdzqOMUpwwtfF5f6LntJ+fdyavHt/FjSxliRFwc0Z+vGo96Wr+eG3jjH2rt+WdQ2F5FtamND0/voc3azfLc2RzpPM1PrWVUdjfxUvY0niv7jGP6OmYlXsCEmDyqDM28XbWTWlM7T/S/nsruJsq66vm2sYinB0xmRcW3lHc38tGI2/GTqak0NLOjuYQAuYYVPxuiem/G1YyN6N8rba3Foue+Ix9QrKvxHBMj4v7M8ehtJi4I68sLZZ+zp62812NdFJ7FguSxTNr1Mi4E3h12MwD3Hf2A21IvY39bBYODk7j78Hs4BRcJmlBi1EFcGZPDg0c/7LXYvDfjavKCknj71E7GhPdHLZURKPflmdKtHOuq47F+16GSyDjYXoVCIuON8q8BuCSiP0aHlV2txwF4JOsaMrRRPHR0E+WGxl7n+2DmBC4My6TLbqamJwL8+j7D2NFYzPkRmaw9+T0zEs+nqLOa58o+4/ywvmxvONLzWjOZEDOYhQVruTfjasZE9OPH5mMsLdnMxJjBzE26kICeXX69zcQntfkYnVZuihsJCOS3V7Kt/hCXR2UjF0t5u2onJfpaIlT+NJp1LE69hNOGVg60n8ThdLJqyFy+bSpmZcW3yEQSNgxfTIBMw962cpotul8Mxz0j/H9PNJkdtl7+g5/HpLsEF112MzqbkRv3LEMrV/NS9lRKdbXsbTvBReFZGBxWAuU+bK3NZ17yRXzTVEy40o8vGw7zeu4sAuQanIKrl6dBEAQEBM/us8Fu4UjnaVK1kQQpfGi3GpiXv4o6UwfDglN4OOsaHjz6IQc7qojXhPJ67kyeO/YZi1LGEucTSofVwJqTOxgb2Z++fjGeKvPZ/Py1mRxWlBLZP2UH3Oyw8Ub512yq2ec5dmaA87+CLpuJLbX5vQZwn/FwxfmE/kue04uXc2GwW1BJ5Z7vt8VpR0D4jxFL4BVM58QrmLx4+e/B3W70FX5yFdMTRiMRifms7iD57ZU8lDmRYOXfRM3ZMyFMTht+MhVpvpGMi83jkaKPsJ1lhB4YEM8jWdewtORjCjv+Noclyz+Wpwfc4BnA91sY7BYazB2EKf3xk6uxOR1Um1oJlPv8KbHVaTWy6uR3bK49gAgR92RcxTF9PT80l/DswBsJVfqxsuI7vm0qAiBDG83ClLHcdXgDZqeNMKUf6X7R/NhT6ZiRMJoAuQaZWEJfvxi67GbuOPQODsHF6sFzubcnVhogQuXP20MXnXNHusms46qdz3l+vjRiAGl+UZToahkRkkJOUCLT9r1JW0+Ec7Q6kJcHTaOgrRI/mRqFREaqNoJbD67n3r7j2N16nPHRudSZO3jg6IeEK/15MXsqLRY9iw6uxeK0E6r0I0Th6xmMe1/fcQwMiGNP6wn8ZGoy/KIp6KjkxbIvuCv9SnykKtRSOe1WA3Xmdjac2tXrNcxLusjTWqq3mUj0DSMvKJGlJVsoaK8kQK7h/eG3YHXauf/ohxzT1xGu9OfO9Cv54PRuCjtPESz3Zfng2ThcTsKU/mxrOMRLZdt4duBk+vnHUmfqIMEnFB+ZCmNPvHW0JvAXw531NhMCAv5yDcf1Dbxd9SPDQ1P5trGI80Iz6BcQy/wDq+nu8Q6l+ETw4qApvFX1I5P6DCPeJxS9zcTWugL6+ceS7BvOTy3HMTmtPHfsMwAuCMvEJbj4scWdkvho1rWMjej3T5kr1G7t5tljn3LK0MqynBlopArKuxq5+eA6nIKL21IvY1BQgsfPMCV+JFdF5RCtCfrD5u+zRZXRbuH75hKWlmwBQCIS4+zxAi3tN4kRoWk4XA78zvrs6mxGNFLlOcVSp83IR9X7uCIqG6VEjoDA7pYTbg+T3BeRiL+7jc3ksLK79YSnpfAM4Up/3sybRbQ66O963F+jy25ma20+r/dsEuQGJXJcX0+3w0KAXMPqwfP+ZULNyz+Xdms3BoeVGHUgYpEYvc2E3m4iTOmHosef+VfC4XJgdNjwkSk932WdzYhSIvf4Tf8deOcwefHi5b8Wp+CisKOKbQ2HeP/0Ht6q/IHNtfm8emI7+9rK+brxKDbn30SQRCQmWRvBip7ZOlKxlPkpYz1iKVYdxK2plyFCxOHOU7x8fBu3pl7W6zmvjs5BK/v9VjxDz2Lupr2vs6lmH912M8W6GqbtfZMXjn1O21lpWYAnDexcBCg0zE8ew8YRtzE1/jxqTe3cFD+C94bfQoImlFaLnkUpY5kSdx5RqkCOddXxZsU3vJg9BZVETrNF7xFLE2MGMzFmMGMj+jMgIJ6K7kY2Vu/FIbh4qv8NvFX5Yy8jbqNZx1Mln/xibk2LRc+9PzP6f9Xobn/SSpX0C4hjS22BRyyB2+j7U3MZw0NSyQ1OIjc4kSCFLw9kTeDLhsNM6jOUUn0dYQo/Xhg4hWcH3ki33YxTcBGq9CNc6c+DmeOZlzSG3MBE1BI5wQpfDrZX0Wrt4omSLXTYjIwKyeDDEbeSoo1EKZExKDCe/gF9uL7PME+KHkCcJoQBgXEEyjWMCc/igvBMDnec5mR3MxNi8hgT3o83cmehsxu5ueAt5idfRJjSDx+pEqlYzLTEUYQotDze7zoABEAjVXBxRH82n7eEIUHJBCp8SdFG4NPzmdHIlCT5hiE568+u3eVEZzPiJ1d7hGm4yo8IVQBfNxzlwcyJjA7LYFfzcY9YAqgwNFHYUcWMhPOJ76kY+MnVjI/JI9M/Fh+ZikGB8USrgsjwi2ZcdA43xo1gREgaY8P7MTAgjtygxF8VSzqbkdOGVmw9VT2jw0K1sfVXI7WDFL7ck3E1r+fMIFzlj69MRbQ6kMFBSQC8cuJLpu59A6PDSpDCl6ujc1FIZL3izlstXb9pBD9bWGlkSi4Iy+K2nu/oGbF0b8bVjAxNQyNV9BJLAP49GwU/R28z8VblD6yp/J6FBWtpsuj4uvEoT5ZuYV7+ahrMHbxbtbNXmuafodtu4eEesTQoIIHlubM987SeKvnE0zb5z0IplpGmjUIiEnNFVDZP9r+elYPn4itVEq0O+rcuTL38cdqt3Tx/7HOm732Diu4muu1mPqrZx6Tdr1DYUYX1LzYT7MzcvWt3vUxFVyNOwcVpQys37HmNg+2Vf4kZZ94KkxcvXv6S6GxG1lf9yPun9/Q6fnF4f25Pv/wXO8JnvARzD7hTyOYmXUS33cye1uMsy52Jv1zD3tYTPFP6Ka/mTOexoo85ZWzx3F+MiOcG3vSbvdcOl4Nuu4XlFd/yfXMJ/f374BCcFLRX4RCcxGtCeHbgTUSqApBLpDSZdZToahgSnHLOIaPgDtTotJnwk6sIUvjSbu3imK6eeN9QwpV+6G1myrrqkYjEvFD2ObWmdtYOmc/qih3s7/EhiRDx8cjbCe3ZmeywGnjl+DZGhKZjdFhwulw8V+auRNySeikAr53YDrhb0y6LHHiWh+kTvm8u9bThfVKbT6m+DhEitp53J/vbKnj62FbA7eexOO3saTsBwJP9r+eCsL5IehauDpeTLruZwo4qXij7HD+pipcGTaPFomd5xbfMTbyQQKUP3XYL75zaya2pl2Fx2rAJTtZWfM/18cNYWryFBJ9QFqaMxU+m5sWyL3AhMDX+POwuB1ang8/qC9nZ0nv+1OVR2cxMGI1KomBBwRqqja0MDIhnUp+hpPhGEKzwpc7czqz9K+nvH8vtaVdQb+7g4aJN+MnUPDngerQyFTcXrKPLbubN3FnUGNsYEpKCVqaixaLni/pDjIvOJVDhg9Fh4YemUtqt3YyPyUMlVVCsq+GLukJu/pkRX2cz4hRcaCRKvqgv9Lw3o0LT6bAZKNbVIkLEswMnM8A/Hn/FuVvr2ixdVBpa8Jep+ahmH6PCMkj1jcQhuFhb+T1zki4k/GcDmXU2I29X7eTD6r28Mmgaff1i2NN6gidLt3BL6qVcHN4f37M8fL8VhtBhNXBr4XpO9PjWZCIJm0a6Ax8WFqxhQEAct6ZehlNwcf+RD3AKLp4ZOPkPVXFbLV08UrSJgx1VnmPnCtX4PRwuJ2Vd9SzMX4vVZUchlmF1uRdvw4NTGRvZj8eLN7N68Fwy/WP/8OOeweKwsb+9gk3V+3is33UEyDWUdzfyRPEWXsi+icjfiTn/e7A5HdSY2giU+xCo8EEQBKqNrailij90bb38+2k0dzJr/wrarN1oJAqGBCezo7kEcG9+zUu+6C/lR+u0GZm1fzl1pg7UEjn39h3Hy8e30Wkz4idT89HI2/9tr8fbkncOvILJi5ffxu5y0mU3oZLIPf38LRY9CrHsDyVL/X+jt5mYfWAl1UZ3/HCAXMOmEbf/4lx/brwOkGswO21MjR9FblAiwXJfojSBmBw2LE4bDx39kIKOKvr5x/LMgMncc+Q9inW1RKoCeGvowl4JgWc4ZWih02Yk0y8Gk8NCramDSkMzx7vq2VKbT7wmhCXpV/Bw0Sae6D+JWHUItxx8i1PGFh7oO54Lw7N+IZqazDqeP/YZ1/YZwp6WE9wYN5L97RU8VfoJCT6hvJQ9jVPGFu45/B4aqYI3cmfSYOpkV+txPq072OuxwpR+vJE7y9OO02kz8tDRjQwKTCBVG8n3zcWk+EYSofR3V3dwoZYoyA5K8Lxek8NKh83AzQXruDnlYg60VTAiNJ31VT+SF5SESixnVHgG9x/5gCSfMKYljEYkguXl39BqNfDswMm/WKADtJj1NFv0nDQ08WzpZ/jL1Tza7xpCFX6sqviOS6IGIEJEcWcNl0UNpEhXTZxPKA8c+RB/uYYFyWPY0VTCye4mTnQ3uMVj9hRO6OtxAatOfgfAzMTz0dmMbKnNB9xiMNk3nEeKPqLe1MGj/a7lm4ajTE0chb9MjclhQyGWIJVIWXniWy6IyOLhoo1YXQ7CehaezRY9CrGUJ/pfz1tVP3JheCaXR2az5NA7HNPXcUWUO5ms2tDG3PxVACxMHkuWfyy3HHwLu+Bkavx5zEw8v5eHpsmswyUIOAQniw+uI0MbzeiwviglMt6u2okLgYczJxKpDjxn1eCMjyU3KIl7j7xHs0XP0OAUHsycwL09n+cU3whey5nRS6y1Wbu4tWA9FYYmJCIxV0fnMDosA7vLyed1h7g5ZSxSsRQXLiJVAVR0N6GSyH/R5uUSXFR2NzM3fxXGs+azvZEzk1pTuydk5MKwTFqsXRTrahAh4vWcGQwKSvhN71CbpZuHizZ6xNLw4FSPKP9HRNOs/Ss8xwYGxDMxdjCPFG3i0axrGRma9qcjxcEtKGuMbXQ5zMSog/CXa2i26Om0GghWaHu1DnvxcjY1xjbm56/uVa0fF53LguQxHg/kX4laYxsL8tfQYv1bl4WvVMnKwXNJ9An7u1Io/xn8UW3wn50B7MWLl/83zswhWnxwHY9kXcPwkDSaLDrm569mQsxgru8z7D9KNHXbzXxeX+gRS+AWAW9V/cD0hNG9dqscgosOqwGb00G40p/lebPotluYn7+aD07t5s3BsxEEAbVUjloq577M8bxZ/g23p11OsFLL0wMm8/LxbSxKuficYum0oYV5B1ZjcFh4NWc6UapAnizZQpWxhcWpl3B5VDYqsYxGcyedNiO3HFyPv0yNzm7igb4TSNVGIO8ZEHvGzwKwtGQzBe2VHOuq543cmTSaO1BKZEhEYqoMLczNX4XOZsTmchAq1WKwW4lUB/J5nTvE4rrYoVwQ1pfbD71Ds0XPO1U7uTXtMnxlKnQ2Aye7m9ytdDIVg4OSideEcqizij6aELQyFTuby8gOjAfcwvn9U7u5MX4ka4fMZ2P1Xj6tL8QqOHl6wGQK26t4rORj9rWV89zAm6g0NFFtasXqtLMk/UrEItE5xZIgCHQ7zNxWuJ7Bwck8mDWeILkvzx/7HD+ZimkJo3mkaBPnh/blsuiB7Gsr59UT25GLpdhcDgwOCy4EqgzNHrH01IAbKNXVcrK7iSujBzEiJJW+fjHo7CYuDM9ELVXQZunG6nTwbWMxTw24gXpTBw6Xg/GxeTxevJmcwATGReeilCp48OiHFOlqaLF28WL2VJb0XE8AuVjK67mzyG+r4Ji+jmP6Ot6q/BGDw4IYEaND++J0CfTRBHN5ZDbbGg6xq/U4G6v3uudnaYKZGDv4F2JpV0sZKdpIghW+LM+d7RmovK+tnGkJo4hVBxOhDjinWDI6LHzZcIQ3K77hOms318UOZVn5V+xrK+fKH5/FhYAYEXOSLvxFtTRYoeWlQdNYUvg27TYDo0IzeO7YZ6glCp4eMJlKQxMfnN5DnamD13Jm8MjRTXQ5zKzIm9NLNJ35fBodVoLkPkSpAynS1bDo4DpW5c1hUcrFvFH+tWfXXISIZwZMJtM/9neDFqRiMcm+ERzsqOKJfpMYGpLiCdVI0UYi/ZNBDRan3VMFO0OzRYdWpmRUaAZDQ1L+LrEE0GLpYub+5XQ7LEyMGczMxPNZmL+GWlM7Q4KSeaz/def8neLlv49WSxedNiMJPqFIxRI6bQYazTriNb2Hu54hQK5hSHAyX9Qf8hybEPP7YS3/qcRognkoayKLD77lOXZr2mXEa0L/bWLpz+AVTF68eAHA4LCwtvIHrC4HDxzdyMzE0WypzXcbomv2MT4m9999ih6cgovC9ipP29iY8CwC5D5sqtnH+6f3EKkKYFx0nmculFIiIycokVdyphOtDiRKHYRTcLEibw4iRCT7hvf6hR2tDuLevlejlbn/MIUq/biv7zjPzz9HKZETKNegsxu59eB6/ORq2q3dSEUSwpT+7G+roKC9klmJ57Mk7QpeOv6FWyxljmdPywnkYgmxmmDMNhubaw9gcti4MW44t6Zexrz8VUyMGczWHl/QJREDeGXQNG45uL5XQMM9GVdz75H3GROexdMDJnO48zR9/aKQi2WsGjyHNSd/YGbiBSjEMmqMbSzMX4tUJGZy3Aim73sTAYEhwclMTziPcGUA8/PX0GTR0WEzMD95DPcf+YAiXQ3He+K6r40dikIs44qobBYWrGVy3AhmJ17AFVHZPHfsM/a1VRClDmDN4Pm/aZg3OawcaD9Jt8PCd03FmJ02qo2t1Jk6aBZL8ZEquTv9KvoH9OFA+0lePbGd80LT0VmNNFl0tFi7+Kz2IPOTx/Dy8W34yzUESDVEqQMJV/mzveEIMxLPx+FyUqSr4Ziunr7aGOIig/ng9B6Gh6Sx5ODbPDngBiJU/nxRf4hqYyvVxlasLjsyJExNGMVjRR8xPXE04Sp/fKRKz+woH6mSALmGSyIHUKqvY29bOdmB8dQa25mfPAa7y8HxrjoSfcK5Le1SNFIFAwPjUEsUPFO6leW5s5GIxBjsFk+F0eFyUmfq4IWyL7i/7ziyA+KxOO0oJTJCFH49vjeBVosef7kGhVhGg7kDP5maAIUPGqmSwcFJ+Ms0mJxWLo7oj8VpZ3XlDk/8+ENZE8n0iz7nQs1XpuTiyP7saS2n22Gh0azDKbi49/B7KCQySvS1AJToaolUB9L9M7Fx5rqEKLQoJRZW5M3GR6rkieItHOyoQiqWcmXUIN499ZNnVlK8TygDA+POeT4/x1+uYUbiaC6LHEi0JgiNVMEFYX1J9o0gQuX/pxaUBruFrxuPeMIx0rSRnDK00mDu5JnST7m379XsaCrmovAsz6DfP4NSIuPa2KGsq/qBzbUH2FKbj4CAXCxlVtIF+P6dQszLX4tWSxf3HXmfE12NLM+bTYw6kGUnvmJb/WGeGnADw4JTen329TYTm2r29RJLAAvy17Bi8BySfcP/I2YY/RmqDa08UvRRr2MvlX1Bqm8kSdrwPxwA8+/CK5i8ePECuHezHs6ayENHN3Ko8xRrK38AQCtTsTJvLiGK/5w2VolITKZ/LEODU9BKVdyefjlikQiZWMLhztOMDuv7iyG6SomMnMAEj9H9TBCECM75h+eMODLaLdgEp2cX2OZ0YHRae+0Kh6v8eSVnOjcXrKXG1E67tRsRIpb2v44k33ACe1LRNtfk81rOdFQSOZdHZdNg6mRHcwk7mkt4SJhIs0XHqpM7AOjrF815oWm8NWQBtaZ27ugZ+NdHHUx2UAIi8GRuyUQSHIK7hW5kaDpBCl/qzR0c6jiN1d+BS3AxPjqXD07vZlRYXwo7KpmddAFvlH+DQixlSfrllOnrcbicWJ1Ofmop45LI/qyv2snWugK+bDiMzeVAhIhLIgfgEJyEKv08c41ezZnBmorvWJx6KUFKXx7IHM9rJ75ifvKYXxVLJocVi9OOr0xJTmAiMxJG81bVj+xpdbdWycVSXs2ZTo2xjWHBKWikSpJ9I7gz/UqUEhkZ2mgkYjHb6g+R6BNOuMofs8OKj1SJIBL4tLaAIl0N92eOx+K002E10N+/D/PzV+NC4PLIgeQEJXLfkfcRgFPGFop1NVwSMYB2q4GNNXs9i5Wy7no+HH4rJpeNWw6+RYfN4Pnj3mEzcMvBt3ghewpp2ih8ZSqyA+MJjfEDQaDbYUfsEnOsq45Mvxgy/WN48OhGwpR+3Jc5ji/qDyEXS9jbWs6MxNEk+0aglMop1dciIPBU6VYeypxAtamNDad2uaPQ/aIpaD/J06VbWZx6CXlBSUzf9yZXRA9iftJFBCh8iPcJZf3QhUhFYtptBk/L2hm+bSwiRKFFJBL3eo+MDgs/Nh/zpKz5ypTc33c8T5V+QoWhyXO7O9Ov5HDnKcq66ln5s+rSme/Eazkz3KEqPf/vgawJdNmM+MhU3HP4PY9YGhgQR4ulyxO2ciZq/LcS/Pzlml5VZI1MSZpf5K/eHty+ELvL6TmfNks3OruRaFUgIkSMCEllXEwuDpeLh4s2oZYocLhcvHr8S5J8w8n6OzxMfnI1k+NH0Gkz8Eldgad6/FrOdPr6Rf9TUgq9/OdjdzlptXZhddlZkL+GdG0UR3SnAagxtpIbmICKsyL8nVbePfUT4G7Dm5YwijkHVtJm7WZFxbc8knXNX87DdGvhejpsBnylSh7tdy3Pln5Ki7WLRQfX8vHIO/D/D6+c/WfLOS9evPxTabd290qi0ttMtJ6V2hai1LIk/fJe95kQk0ekKuA/rmQerPTlocwJnoAHf7mGaQmjeGHgTb9qbP754kQiEv/mLp3RbuGHllLervrR3frmdFCir+XJki20WXqnx7kXQr2vkVqi4M0T33BheCY3xo3gyf6TeLBoI3aXk72tJ0j0DfO0vC0t2ewRS1dFDaJ/QB/0dhNrKr+nVFfHlPiRDAiII0kbwe2Fb+NCwF+mQSISU2NqZ9mJ7byQfRNamYpiXQ1JmlBGhqbxRMkWni79lDpzB/0C+nDrwbdYW/kDNpeTtUPm0WrpYoB/HH39Yrg6Jofvm0rY1Xqc0WF9uSZmCIAndv3RrGvI9IvB4XLRaunyRNtGqwNZknElQT1+jBClH3dlXEXUrxjaTQ4ru1qOc3PBOtqtBvykSq6KzkEm+tv7k6qNcIcAlH7Kqye2Y3M5CFf5UW1s5YmSLbx7+icEQSBc5c8jxZt4smQLTwy4HrlYglgkZnL8CAYGxrP65Pc4BScmp5XThhaey74JMSK2NRzmseKPEYCHMidQ2FGFVq7CV6ZkVtIF+Ej/5idzCQKttm5OGVppNOtQiGU83f8GXsiegkIspdGso7K7mdygBHICE3im9FMeKdqESqogSOHLw0WbePDoRo7p69hccwCn4EIpkeMUBN6p2onZaSdWE8zCgrVsqc1HJZGztN8kMv1iEBAIUviyv60Cp+DiseKPWX3yO8+w2m8bi2i1dmEXnBzqOIVd+FvqYqQ6ABcCzx37lGP6OsSIGB6SCsDetnI+OL0Hm+tv6VQ2pzsk4/UTXwEwJDiZuzOuoo8mmHClv+d2gXIf0rSR7Gw+ho9U+avJa+Eq/15CKljhS5Q6iG31hzmqq+7xLM1kSvx53J1xFcW6Giq7m6g0NHNMX4fjrLj/38Jgt3C2HdvssHoS/s7QaO5k8cG3mJe/mmpjK+3WbpaWbGbGvuWopUrWD13InRlXsu7kDygl7qrs89k3saO5hGv7DCVW/fdHcRsdFkT/x955B0ZVp237mt4z6b1XQgqQkFBFEQELClItgHQQxd7Fhr13aYKVIiCgqChiAakJkJBGSCC992R6//6YOEt0XfV9d7/X3c31lzlmzpxzcmY49+95nvsG5saMASDLN45KXQs9NuM/fmE//zGEKn14J2sRIQpvLE6bRywtSxjPtIhheP1CLATIvFidtYiZkSO4OWE8YUpf1mQv5rLgNB5KmfJvJZbAPav0zODrCZR5sXbYEkYHDGB19iJCFT48O/h6lH+hXKbfor/C1E8//yX8bFPaYOzgpcw5yIQSPqk+wu66XM/8QZW+hVtz3+vzug8qDpKoCWFkQNL/uI//X4W/vG/V65/9j0i1sY1VhZ8C4HLB6MAk7jjxATaXg0CZF8uTJqIWy2k0dXLniQ+oMbYhFog8LXl3n/qIx9KnE6LwJlzhy7Mlu2kwdvJq5lxEAiGvl37FyrRp3Jq7ge7e1fZYdRC3Jl2OC3jtzFfsa3RnLK3LXoxKJKfB2IHVaSdc6cvK1Gm0mLt5onAHreYe2q16QhU+DPQKo87YjkgoYohPDHmdlbx0Zo/nvKJUAQzxiaa4q44KfQsDvEJ58cznSIViXs2ci85mptXcw5meuj7X41RnJTKRhM2Vh1gQPxab0+5x+fql5bpYIMTmtCPpnc2yO+10Wo3QKyyfKNyB3eXgsYJt3DvwGu7P29TnYb+wq5bdtbk8kDIZb6kKhUiK3mbGS6JEgIBIpT9vnf2GQ23uENoZESMIlfuyNGE8t594j3CFH4sSLkUllvNE4Q5azN2sSpvJQK8wghXeNJg6AfCVqsjyiye5d7vJYeXJok/RX2DjXaZr5PO6E1wamMKq9JnIRRJPrtOq9Fno7SYilX48WrCNJwfNwluqpNNq4I6T7+NwOrG5HIQqfFCIpQTJvZkcFsB10SPZVHWIRE0Iw/3jeaL3Pnv33HdMDEnnQMsZLgpMpqi7lofyt7Bq0EzWn/uO0p4GvmzIAyDZK4wF8ZfyYP4WolQBvDl0/q8WC2QiMYmaUM501/NAyhREAiHp3lGsLt9Huk8kCpH7M22yW8lpP0eCJpg1wxaz8fwPLIwbi9lhZU35t9SbOjz77LDqefHMHj4YeQsbzn3PPSc/4qXMOYgEQiQCMV7S325dk4kkTA4fSpWhhUmhmYCLe/M+xkui4OUM9/fS0uPrsDjtvJO1kIG/U4XpsRn5vO4kw/0TiFMHYXbYONp2DrVYxmCfKKS9Ys5gt9Bu0WGwW1h2fD0hCh9Pa2G1oY2xwSmoxDJezpyLXCTxfNfdmjgRsUD4P54baTJ1ktdexdXhWexvKuCNofMw2W2EK31ZU76fBXFj/+5sXz//eajEMhI0ITSaujzbsvzi/u6/q2KhiCSvUMKVfp57L1Llz/0DJ/9bzjCJhSISNSF8PGoFWokSgUBAhMqf90YsRyWS/aoj5K9If4Wpn37+S2gxd3OgpYRSXQN3n/yId899x7vnv6fNomNP/UnaLTqeKNxBl82Al0TBByOWk+ETgwsXjxVsx+iw/l+fwr+cNnNPn2wYP6matdmLEQmEbKk+zC25G7G5HESpApgbe7GnCmFx2OiwGhALRLycMYcn02cRowrE7nLQau7hs9qT6OxmlsaPZ1X6TNotOo62lbNq0Cx+bC7xiCWACn2zu5rgdHJx0EBEAiFPD7qOVouOtef202zu5on0mdw/cDIP5W/hQHMJLwy5kScHzeLlM19wX94mvKQKniv5nJWnt3Jr4kQiLwjH9JIoWJk6lXfK9uEn0zAuOBUvqYIIpR9Wp507TnyAWCDkg4oDHrvwwT7RAHxWd4Ifm0u4LCSdLquR053VmC5wQPuZnytIxd112JwO7E47tcYO1pbv5+acd3E6nR7ROMQnht11udQa25EKxbydtdCzEr+/qZAolT8j/BKxOe3sbcxDALydtYAWSw9TI7OJUwfxSsZc/OUadHYT/jINFwUMYHnSBIQIeaJgOy3mbrQSJcnaMFae/sQjlgDarXruzfsIqUiMUCBgV10uR9vcduy3JV3BzEh3lW1nbQ4mp40QuTel3Q2c7qrmdFc1H1f9RJQqAIPdwgMpU+ixmnhxyGxUYhlmhw2by4G/TMMDKVP4uv40IwMSyPKLo9tm5KKAAdw24AryO6sZ4Z8AQKjSF5PDilQoZk35twAYHBa+by5mfHB6n+s8MXQQ+xvdc1+XBqWiEf/amt5HqmZJwqVsGL6M423lPFn0Ke0WHe8OW8qksEy0UiUmh5WjbWXcl7eJRcfXIhGIWBA3ljVl+8nvrPa40T2cMpWVqVMRCYSc7WngYMsZJoVlkKQNxeKwcV/eJg62lHBe19zH2avW0E7TBQ+JvjI1dyRdSao2Ah+ZGqVI6m7ZOfE+S46vQ2c3oxLL8JIo/6FYMtrNfFF/ijfO7mXp8XVU6Fs42lbGg/mbuf3k+5TpGj2/6y/V8E7WQlRiGe1WvUcs3THgSuqMbeh6P4O+MnWfB1g/meZXmU5/FLPDSkFnDRFqP247sZFNVYc43HKWMKUv9+dvYnddLi+d2UOn5Z+bxdTPX49Oq543zu7lYMsZAMS91fTlORs429OA/e/k8YmFol+Jo39HsfQzYqEIb6mqT7eKj1T1byGWoF8w9dPPfw2x6iBeznCvAp/VNfBJzVHA3R99Q9Qo/GQanhp0HcleYazNXswArzCeHDSLbL943hg6Hy/xnx94/neixdzN/fmb2Fx1iG6rkQ6LnjXl+9lcdYiXhsz2zKyIBELeGDrPU1FpNnVR3F3H6uyFvDl0Pp9UHeGB/E3cnzKZpwbNotXcw47aY7x59muUYhlbqw/zeOEOsnxjOdpaxobz3wMwITidob6xADxasI0yXSNBci2bRq3AT6ZhZW/4ZZmugQCZhhpDG06Xi4VxlzJAE4qvVE2TqZM7B1yJUCBkQkgak8IyMTutfVY0dTYzZT2NeEtVrD/3HSqxjGOt5axMnYqvVI3d5URvt6CVuis5D6ZM4YboUcyLvRhwt1VFqwLA5WJ4QCKKX6yO2p0OctvP80jBJ9yau5Hi7lrKdc10W418Cr7fuQABAABJREFU3ZhPjbGdW05swO50MCNyOO9X/EiSJpQJIem8MXQeJ9vPIxaImBszhrsGTKLdYsDitOHEhc5uJssvjp9azrCrNodHC7bxSOo02i16bs59l3fPf49YKOLayGHcl7eJ9yt+5N6B16ASyXglcy4FXTWc6qxEgIBV6TN5OWMOQgSU9j78t5p7uCwolaG+sdyWdAUZPtHMjbmY6yJHcl3USOLVwfzYUsKGiu8951vYVcPtJ95HJBRRZ2zn01p3y92FgcQmhxUhAq4IG8yTRTt5rHA7bWYdAXIvbj2xkTfO7iVE4c3lIYNJ0ASjEsv5sPIALlzcGD2azy66h0zfWN7unSv6mTdK95LlF8fFgcm8V/EDXzXk/Spc1uSwUtxVz1NFO/muuQixQMS2mqM8U7ybL+pPulsrhWLClL4oRVLaLDrmHHmLGw+/yf7mQtrMOm5PupLH06YjFYpQimS8MORGbowejc3pYMWJ9xioDefxwh04XE40EgXzj73Ds0W76bDoqe21Rr7z5Ad9RJOPTI1CIiVOHcTaYUtQiqTo7GYMDotnbjJaHfAPP7NKsZxR/kn4StXo7GbmHHmLB/I348JFmncEQb1thD8P0AsQEKb4W5uoVCgm2y+en5pL6bL980WLXCQlySuU0u56Lg1OBeCTmqPcdPRt6owdSIVi5sSMQSP5a1Xu+/nnY7Bb+KE3RHxZwnh2jbmHUIUPFqeNT2uP96lo9/PXpF8w9dPPfwkykYRU70iG+MR4tokEQpZdkOkQpvTl9aHziO3NRAiQe/Fk+kzSvCP/bVaB/idYHDa+ayqksKuW9yp+5MPKA7x+9iu+bDjFgZYztFv1ngqAw+Vk4/kfqNC30Gbu4e5TH/FE4Q6OtpYTqw5iTuwYkr3CiFT6MdQnjlEBSSR7hfFw6rU0m7vwlqqIVQeikSiI0wQRofRjUmgGdyVPYlX6TLJ940j3jiRBE0SMOpBKfSv1xg7GBA7gypDBPJ42gyilP4EyLzYOX4ZIKOTB3tDPXRffi9Vp59oDLzHUN47xIemeFsJIpR8pXuG4cPHSmT1k+MYwISQdEDA9chh2l5MemwkXLp4s+pSJIYNYnb0Ivc3EfXmbUIrkrM5eRJBci1QkYmRg0t+1QxYLRSR6hRDZW7G6OeddFhxbzdpz+3kyfRZSoRg/mQaL087O2hycuHi6aCep2kg+rz1Jmk8UO2qOoZUoKe2p5+HTW9hecwwBAmZGjqDV3MOIgET8pGr0djPfNRdSY3Rby+9vKmTl6U+47cR7WJ12umwGZCIJYqGIdosOh8vJbYmXszJ1KvXGDpI0IbyQMZsbokZhcdqZdfh15h55mykR2RhsFrRSFY8WbGdSeAbzYi9GJBSyo/YYABNC0tk4/GYCZF4YHBber/iReHUw10WP5LYT72N12gmQeaGVKDDYLTyYvxlvqYqRfgk4XG5TgaXH17ttt2UaYtSBXBacRrZfPE6Xk7ezFvJU+izSvaOwuhxsrvwJJy5StRFsHnUbSV6hOHGx4fz3LEuYAMC6c995Qld/xmS38lHlQc7rm0nVRvDJ6DuYFJpBhb6ZnbU5tFl0NJq6PK14MqEYnd3stqqXa5kQms4Q32gMdgttFh2HWks53HKWccFpHGwuYYA2jFCFD/XGDmLUgbRbdJgdNn5qPcOD+ZtZlvMurZYemkxd6H7joVD4i9k/tVjGH52YjFIHsLb3uO29LZ2x6iCeGXQ9AXIvnC4neR1VxKgDefPs15TpGpGLJAz3T8DqtLPixHs8MXgmAuffZvX+mUSpAxjmn8BArzDGBblFk8PlBODNofNJ0YYhFv7nfrf+ErvTToW+mQ6L3rOtxtDWZ7b2P5FQhQ9rs5dwe9IVTI8YRpDCnYt3Q9Qobkmc+G83k/TfSL9g6qef/xK6rUa2Vh3mRMd5zzaHy8kdF9hTA78umcvU/9FiCdxi8vLQwUyLGAbAR5U/sbchH4A5MRfRYOyk1tjBpNAMwN2a9l1TIbtqcyjTNSISCInXBKMUS0nzjmRV+kz85V74ytXEqgN5OWMOWokKP6mGuwZcxR1JV3JO34TFaeP5ITeyJOEyfGVq/OVePJ4+g2cHX0+AXItAIEAsEPJ00U6uDB3CtKjh3H3qI4wOK2neUThx8XD+Vm6Ku5hXznzB1qrD3H3qI2wuB9tqjuItURIg9yJKFcCLGXN4MPVahvhE4yVRkKwNY5R/Ei+WfM5ZXRN3nHgfu8tBuNKXILmWJwp38HbZNwzQhnNRwAAEAijpquPl0i/4tCaHUx2VtP7GQ06Iwoe3shYSofDlqUHXkagJoVLfQqp3BC8Omc2DKdfyWME2zyzW7QOu5PWzX/FVYx4fVBxg/fClfUwgBLgrgE6Xkx9bSni++HNe7m3p+6jyJyRCMTf1tvEVdtV49nv/wMm8WbqXbpuRh/O3EqH0I0UbQaw6kOH+CdQY23E6XFwbmc2myp9wuJxYXHbeLvuay8MG8/jp7ZzqrGDhsTUIEOAv0/B21kKmhGeR4RPDytNbeSRtKpcGpfJw6rVEqPwQIMCFi1CFD4+kTePNoQvwkapw4qLdouOO5KsIVbjNGGwuByqRjFXpMzHZbZzsqOCZ4l2e3COr0879+Zu4N+9jnh58PeOD01kUfym3nXiPe5Kv5uLAgbyVtQBfqYqrwzJZO2wxfjIN7RZdnxazVekzmR4xjHlxlzD3yFuMCkjixujRPJw6lXtPfcTTRTvptpqwOu04LjBPcDgdWBx2VpftI0zpyweVB/iqIY+ddTncc+ojVqXPZH7sJbxeupfH0qYTIvcm2z+eFYmXA5DXWUWrpQeVSMaa7MXEqQP73Cc/h7o6cXFF6BA0YjkDNKGsSp/FiY4KqvWt/BaGXvFlsls5r2vGcoHYaTV302Uz4nK5EAqEDPGNRitVcqqzErlIwtrsJVwbns11USPpsOjR2UxUm9rosf6tNbbNouvTnvs/xeqw027RE6zw4ayur/36gZYS9H+npfU/FbvTTkl3PXOPvM2rZ76k02qgWt/KkuPruPfUx//RokkoEBKvCWJy+FCPwUOY0pdF8eP+VMhyP/93/Gc/BfXTTz8eao1tvNvb/jUlPIuRAYk8mL+FUl0D75//kVuSJqL6OzMQ/y34SNUsSxjPd01FnvacaFUAlwWn82jBNt4YOg+lSIaXRMGXDXlk+8XzSumXALycMYchvtHIRBLqjR3ILlgxdrhcOHESovDB5rSz8NgadHYTdqeTQb5RFHXVku0bx0NpU/GXaTxGFiaHlRPt57k/bxNOXESo/LntxHu0WXSsOPEej6fP4InC7TSauni6aBdvZS3ghsNvABCnDmJZwnjuzfuYR9Om4ytV8UzRLs701PPm0AVoJAp+bCpiRGASRrsFuUiCQiwlVKrm2UHXIxGJuOvkh9QY2pAIRdyTfDVlukYKu2oA+LapgGy/OI61neOy4LRfZefYnXZazT3cmTyJDysPsjD+UuoM7TSbu9lVl8uMiGEsTRjPztrjPJhyLRqxnCfSZvBy6RfcnnQFYoRoJHKWJ07kkqCBqMRybjzyJleHZXJ70hWc0zVzqqPSs1Kf11HJddGj+hxDhNIff5mG+1Ku4cnCT925TuYuvmsqwleqZmb0CLZXH6XTZmQSGX1m9DqtBqr0LdhwIBIIeSljLiqxjG6bkR+bSghT+vJ8yefukNyi3SyMG0u31YiX0o9U73DezlqI3engUEspV4VnsDprER1WPTtqjnNjzOg+D+Jmp41uq5EBXqEeY4UjbWXMP/aOp5XST6ZBAFwWnMaD+VuI1wQTrvBhZepUtFIlNqeDxfHjCJB70WTq4vni3cyOGUOiVwhWh53Xz+5lVtQIemwmjA4rD53eyvzYS3iq8FMkQjEPp06lydzJ8pwN2F0O/GQaTHYL7b2W6W9lLeDh/K302Ez4SFUsSxiPv0yDSwBPFe2k22bkhZLPuWfg1Txyeht3DLgSiUDkMfGIVPkTKPf6lSOl2WGj2dzNnSc/YFnCeDaNWkGPzcQtuRsZE5hMhm8MdqfjV3NMXVYD26qPcmXoEMp1TTyYvwWABHUwbVYdnVYDS4+vY92wJcRpgtFKlcSrg3k8bbp78aBkD4XdNTyYMoXNo1bwUeVBvmrIZ0bkcObHjcVkt7I8912mRQzj2v9FUKjVYaewqwa7y8GLZz73tOEN8o4it+M8m6sOAwLmxV78X1FhMDtslHTXY3Xa+abpNO1WvbvaZNVjc9ox/IeLR6FAiPoX5jg/Z6/189enXzD1089/CVGqAO4acBUV+hZuThiPUizj5Yw5fFz5E/Pjxv7lxJLJbukzH2O0W/6QS1+ruQehQOBZteuw6D25Qf+IDoueN89+3WeWocrQyvdNRbyROY8QhQ8As6JGMjF0MI8WbKPa4F4B77QacLqc1PTOa8Rrgnk0bToOp5N7T32E0Wnl9cx5fN9USJtVh0Ys54MRSynuruNURyVH28tpNXfjf8FKo9Vhp6irDicuZkePxk+i4dnBN7DixEaazF0sy1kPgEwoYdWgmTxbvNvzWrezlwiJUIyfVE1RVy1pPpGU9NRjczpYX/4d37cU0Wk1cs/Aq3mpZE+vUYGc5bnvIhQIeTx9OuC2Ox/ln8TloYOZGTkCRe+AvlwkIdM39u+IJQcl3fVUG9r4obmY/M4qynoaeC1zHu9X/MjBljMcbC5h+0V3MsQnmrtOfchgn2huS7ycDcOXsa5sP8fay9kw/Ga0EgVp3pGeNrg99ScJV/giFol4s9f6ekbEcIb6xfHI6U8APA/qR9vK8JEqWZYwgacGXed2cBOKeLFkDwaHBW+pijmxY6gzdvBA/mYcLieRSj/MDhstlh6P412HWccQn2ikIjE9pk621RzF4rRxb/LVjAxIYvHxtTxdvIvrokYyOmAAseog0rwjaDX3EKL0QSWWEaLwwdeiZm7sGG7J3YDBYcFPqkYlkVNjaOORgk94JWMu6doIbkmcyNtl33jE0mCfaB5KmUJxVx0KsXvmp7S7ngpDK5FKX5ROGQWd1ZzqqOTKsMH82FzCjKgRfN2Y32vecZBDbaU0mjp5atAsro3IYmdtDhsr3DlrH4xYjsvlwmi3Yu9183snaxE6u4llx9djclixOmzckjiBJ4t2siZ7EV4SJa+VfkmrRceDKVN4rGAbTeYu3ijdy53JV/JQ/pY+jodneup5qmgXD6VO6bOabnba2Fmbg83l4M2yr2mz6PiqIY9um5GDLSUsir/0V2Kpx2piU+VPfFB5kLM9DcyOuQiJUESSVwjzY92Oc7fmbkQmEiPvtSo22i2c6DjPN40F3BA92nPPPlu8myhVgOdzrBBJOdfTxNPFO2k2d/NexY9cETaEf/zN8dsIBQKkIjFdJgMhch9azD28MXQ+3VYDYUofdtedINkrDIlQjNVh71PJtzhsHtv+/xTUEgVXhQ3B4XLw+tm9nm4HjVjO2mFL3LOR/fTzF6VfMPXTz38JGomCq8IysDsdnpmlTN9YBniF/Wa46P8VbRYdW6oOMytqBIFyLV1WA7trcxkXnEaEyu83X9dq7uGB/E34StU8kDIFAQLeOLuXsp5GXs28iSCFFoPdguoXQkwsELK3IY8vG9xBpYvjx9Fm0bGrNocPKg8wQBtKoEJLm1nHvXkfU2/qwOKwE6sKoMLQyhOFO/CXedFjM9Jm0dFm0fFI/lZ0drOnZa/R1Mk14VmYHDYuDU4lRh1IoFyLQACBMi1x6qA+56KVKrkhehRZfnG0W3QYnRZKu+t4NHUaD53e6vm9B1Ims6smx1P9AXjw9BbeyVrEW0MXoBRJcbicSIRi1g9bwmulX5HXWUWMKpA5sRdhdtpoMHeit5vZXHmILpuRVG0EiZpQPq05Ro2hDYvDxqyoEWilSqZHDsfqtCP6ReDpz4gEQlRiGVuqDnFn8iTKdI20mLtZkrPO8zsrkq5ALVHQbO4mWO7NsoTxPHT6E5bEX4pMJOHBlCk8W7yLMYEDGeobi8PpYl7sxbxfcYAjbWVcHz0KmVDMqIAk5saOYXX5t542vHeyFvFl/SnWntvPTy2lLI6/DG+JinXn91Pe08TaYUvIbT+HpXd+5fWh84hS+oNAwEtDZtNs7ubxwu3YnA4kAhHbao6R4h3hmTdbnb2Isp4Gxoeko5EoWJO9mD11J0n1jmTFifcY5h/PqvSZ7Kk/xbpz+9lWc5R3shailSgRC0TIRVLkIimrsxYiEgh5IH8zNYZ21GI54QpfSi9wdgOQCkW9Vuc7iVEHcMeAq3iueBd3nHiftcOWoLNbuO3Ee9hcDqxOG1eGZbD0+Hq6bAacLheDfKM40naWlzLmUNxdy5e9Ybw/82LJHhbFX0qyVxivD51HmMLXnd/k0rJm2GKECNzn7ghgy+jbPXNrS+Ivo9LQiq9ExUMp14IAYlSB/NRyhlZLD0qRlLXDllDcVctzJZ9xuLWUJlNXH8HkI1Vxz8CrsTnt/NRaypbqw+57X6JgTfYSzyLFhaglMsaHDGJH7XF+ai3FZLfywpAbsTrt7Kk7yf0pk1mbvRixUESY0heny0lBVw2PnN6GCxcGu5mFcZfidDndbX+9Yml+7CXEa4K57aQ7VkEhkrIme3GfRYw/i1gocgsigZCHU6eit5uJVQdQb+wkQRPCtIjhRKj8sDjt7Gk8yaVBKQTKtehtZg63lpLiHUG48re/7/4d0UgUjAkcyJtnv8bZG+Ibrwl2V1H/Yll//fRzIQLXhWlv/+H09PSg1Wrp7u7Gy8vr91/QTz/9/H+nw6Ln6aKd/NRaSoo2nFcyb+KjioN8XPWT2+hgxM1/t1rkcDo42FrK/XmbALgoYAAKsdSTY7QydSrD/BLYVZfDrMgR+MjUtJp7+LjyJ2bHXATAo6e3Mcw/nqkR2Thwsq78O/Q2sycct9HUyYrcjTSZu/lwxC0oxFJeOfMlJzsqeGHIjUQo/TjZUcnjhds9xyUSCHk5Yw6ZvrF0WQ2AgEC5l+fhwGA3IxGIPHkxF9JjM7K7Npe3yr5hTEAyyxMncOepD/q43gXLvXkodQofVhxkQdylrCrcQZO5izCFL++NuBlvqQqD3czzxZ9zvL2cTqu7gvbVJQ9gdthYlvsuLeZuNGIFK1Ov5WRnJSP8EpAKxYQovPm68TTZfvGsPP0JD6RMIdM35ndXvl0uF5X6FlQSObhcXH3gBc//uyJ0MPcmX4NaIsfssNJtNfFO+TfsbchHIhDxVtYCNpz7npze1edPRt3Ox5U/MTIwydN6NdgnmlsTJxIg8+L75kIuCx7E1urDTI3Ixkui4NvGQjqseob4RBMg88LstDH/2GocLidJmlBGBSR5KiyTw4dyY/RonC4XL5/5gmpDKyvTpqERy3n5zB6KuutQi+Vsu+hO/GUa7E4HFofNfW69dFr0HG4768ns0kqUdPeGkl4TlsktiRMRCoR8XpdLglcIAPsaC8hpP8cDA6e4q1Byb050VLCqyL2PQJkXLRZ3qPRwvwSuix6JTCghSKHl4fythCh8mB93CWKBkHfPfc93zUUAnhkqL4mCJ9Jn8kbpXoIV3tw/8BpmHXoNi9NOmMKXK0IHs+H8D7hwMSogiUdTp6ORyPtUdJy9LY+/bKVrMnVx58kP0EqUrEybSllPI5/VnaDG0MZzQ27gu8ZCrggbQpTKH6PdyrdNBUSrAhmoDfu79845XZOnnRRgVtQIbk6Y8JsVZafLyXl9M7MPv4ULFzGqQPxlGp4cNBPfvyNwWszdPJC3GalQzL0Dr0YiFLO6bJ/nmgHcN/Aazuma2FmbA8CcmDEsjrsUufhfG6jZZTWw8fwPbK0+Qpp3BC8OmcNPLWd4ungXQXIt64b9feH470qVvpVlOevpsOr7bJ8YPMjzPdtPP/8/+aPaoN/0oZ9++vlLoRBLuTYiGyECirvruObHF/i4yh0SemlwKtLfcJQSCUVk+cZy/8DJAPzUWuoRS7cmTmSYXzxLctay8fwPvFO+jy6rgYfyt7Cl+jCPnP4EkUDIk4NnuR+6pUp3fk38OO5MvtLzj3iIwoc3hy7go5G3sv7899x/ahN3DriKj0beSl5nFctzN5DhG4O35G/zCKEKHxI0IZ6cmeeKd/d5WFCJ5X9XLIE7qyNE4YOXWMGKpMu569SHNJq6kAkl3JIwEblIQpO5i2eLd/NY2nReOrOHh1KnMFAbzquZN+EtVWF12CntbmB/U2Gfa/dx5U90WPV0WPQoRVLezlpAlMofX6malac/odXSw2ule9GIFTyUv4UmcxcVuiasjt92Ems191CpbwEgVhOEy+WiydzNSP9Ez+8caC6hztiOw+VELpLiL9ewPGEiSZpQ7h14DWd66rk8bDAigZC3hi6gsLuWG2JG81zRZ4DbCjq/s4rHCrazumwfCrGc9yp+ZE7MRUSo/NFKVWT6xaIQSREgYP6x1WyrOcZzg2/wWOr/LJZGBwxgiE8M3zYW0mrpYUnCZRjsFmQCMYleITyWPgM/qZpbEiciF7r/RmKhqI9YArcxytigFB5OuRbAI5auCBnMLYmX4yNTo5UquTp8KCVddTxVuJMv6k/RYu6hxtBGpb6FBnMXJd31AAz1jeONofO5L/kaABpMHYQqfHkwfzPPFO3mucE3sDh+HHeceJ8H8zZzW9IVZPnGAeDqXbV/fsiNvFG6l0qDO5uo1tjBvNhLCFP4ct/Aa+iyGbk/ZTJeEgXLEyfgLf115pFQIPyVWHI4HZzXN1Ohb+FUZyWPFWzj09rjHG0ro97UQWFnDdl+8dQZO2gx96CWyLksKA2pUOQR6xdSoW/m5px3+2z7pPoo+xoLfmWR/jNGu5WSrjrPuVYaWqgwtPymgUKgXMtzQ27gyUGzUIsVfFBxwCOWfq6YvVDyOWFKX66NyAZgU+VPHG8/h8n+r82fk/W2tgoRUNhVy/WHX+fp4l0AJGhCkAj+cxqBdDYTu2tz6LDq0YjlbB11O7cnXQHgtrC/ILurn37+avRXmPrpp5+/HCaHlWNt5Z5qEcA14UNZkTjxd0Mku6xGFhx7hzqje4DeT6Zhy6jbECDgk+ojHuMLqVCM1WlHgICHUqYw3D+RIMUfm1Y4013Pgt6KRaImlGRtKPsbC1k1aCbryvdz9hdtVUN9Y7khejT3523CBbw34maSvEL/0HsZ7RYaTJ0UdFajlsh5umgXr2bOpc2sJ1DuxR0n32dl6jQG+0Tx8pkvMNjNPJI2jYDeKly1oZXrD73BNeGZTAnPot7YwYOnt5DtF89tSVcgwO2WmOAVghABFfpmGkyd/Nhcwp76k57juDVxIlPCs/GS9h1aNtjMqCRyWs09PJi/mQp9C2uHLUErUfDm2a/Z31TIo2nT0FtNfFB5kJbedq2PRt5KhMrfs59GYyfvlO/jm8bTXByYzM0JE/iptdTt1OcVypL4y1hdvo/nBt/IoZZSXj37JVqJgheHzMFotzLELxpF78yKxW6j3tRBrbGdRwu2YXJYWZU+k32NBRxqLQXclZhdF9/D3CNvMdwvgVuTLsdfpkFvN6MUST0itsOiRyoU9xnOdric6GymPoP6bWYd3zSd5vXSrzzbhvnF81jaDPzl7qqH0+XkvK6ZG4+8CbgF27jgVJ4o3AHAmuzFVOia8ZGpeKxgO88Mug6dzUyKdziFXbU82Vt9GuAVSou5hw6rngFeoTycMpUVJ97rM383N2YM2X7xfF53gn1NBQTKvHgnexHdNiP3nfqYdquey4LTWBp/GSqxzGM28kfvySOtZ3m4NxvsZ+4fOJlMnxhOdlTywpnPGeGfwKNp06k3trM8dwOhCndsQbDCG3BXV+7P20xeZyVaiYJ3shaxuvxbDrWWIhGI2DnmbqRCsaeFuMtqwOKwc7ytnKeKdwKQ7BVGjbENg92Cv0zD2uzFfe6rX9Ji7mZF7ntUGlpYljCeKeFZPFawjePt5zz33dPFOynsqkUkELLn4vv+1LX5n2ByWDnWWs79+X/7vhvmF89j6TP+Vy2Bf0U6LHo2nv+BKRFZxKmD0PeGD8epgxjsE/Wbi0f99POv4o9qg/+cpYt++unnPwaLw0ZhZ02fbed0TX2sg/8eHRY9r5/9yiOWANotOp4u2skDKVO4LDiNVksPn9Wd8GSu3DHgSk50VFChb2FpwmV/yFjCbRU+l7tPfcgw/ziC5N44XS6q9a2c7Z1Zeip9Fh1WPS+e2cOJjgquCB3CcP8EbogeTYzqb/bKNqcdiVCMzmai02rA7nTidDnwlqrxl2swOqw8evoTzumbWRx3KZ+OuZuPKw6yufow44JS+XTM3ShFMhRiKfcMvBqHy+kRS+BuD3skdSqdVgNzj77N42kz+GDEcuqNncw7+g43RI/ixuiLMDtsqMQyYtVBeEvUbK8+1uech/snov5FwGaruYf1575jUdylWJw26owd6O1mlh5fxwCvUE50VABQZ+hgdGASK9VTeapwJ9n+8ah7TUZcLrfddqulxzP0faDlDKU9DTT32gxHKv3wlap5YchsXiv9iplRI3hg4BSCFVosDlsfsdRp1VNn6OCtsm8w9wql/M4qGkydNJg6uDlhAmvLv3XnPxXu5MMRtyAXSfGVqbE57ShFsj7D979sEXK4nJT3NPJW2Tc8mjaNQLmWGkMbqwp3sCj+UgLlWtRiGRX6Fo63n2NV0Q4eTZ2Or0zFOV0zSy+Y5TraVsaEkHRGBSRxuPUsy3LWc0XoYL5rKiJBE4y3VEWcOohXznyJt0zF3cmTePnMF5T2uO2po1UBPJI6jVtyN9JlM6CVKBjQayLwYeVBtBIli+PHkewVxqjAJG7J3UCbRYdUKGZB7Fg+qDzAD83FJGpCeDXzJoQCAV4SBUKB8FcmKyaHFYlAiFgoRimWkekXR7jSl1pjOwB+UneVzeV0MiowiUk9GeypP8lD+VtYljCexfHj2FWb62nzA3eEwRPpM3isYBv3p0wmVh3EwynX8kLJ58yIGs7OmuPUmzq5K3kSIoGATVWHMNutDPdPQCQQMsI/kZWpU2mz6Fiasw4vsQLJ72QaBcq1vD50Hkfbyrg0KBWtVMkDKVP4puE0l4WkEab05dnBN/Bw/lbmxIz5VTXxX4HD6ext1/0bOru5z7X6T8FXpmZJwjg0YgUCgQCNRMGksAxkQnG/WOrnL01/hamffvr5S9FlNfBh78wSQJp3BMW9bnEp2nCeH3Ljb84w7Wss4LHe+aGbE8ajEst56cweAO5OnsS4oFTuz9tMYfffxNiEkHTGBqaS7hNJwJ9YSe6xmfi2sYBmcxf1xk6G+sWS7RvP9tqjDPAKI1UbgVQkZn9TITqbGbPDytmeBp4bfIMnh6PV3MP+pkIuDUphdfm3pGgj0NtNRKsCWX/+O54ffCOdVj0FXTW8cXYvAEqhFKPT3SZ014CrELqEjAtN/YdZHs2mblYV7iC3dy7oqtAhfNNYgN3lIEYVyGtDb2J3bS6zokYC8FrpV3zdmA+4Z7AcLicqkYy1wxYTrwlGKBDSYdHzyOlPyO04T5w6iHeyFlJjbOf+vE19Wg6XxI9jiG8MN+e8y/jgNBbGXYpKLHcbcNjMlHTXIRQIEQmEVOib6bYZWV3+ref1owMGMDEknQRNCG+c3cuRtjK8JSreH3EzBZ01dNmMXBU2BLvTgcPlpN2i462ybzjefo4AmRevZ85DZzfxfMlnrEi6ggPNJUyNGMbdpz5kZepUvqw/xS1JE/GXeVHcVesJh/1l9lin1YDL5QQETPvpZQx2Cyle4axMm8YdJ9+n2dxNlCqAZwZdR6Dci0OtZ3micAeDfaJ4etD1SIQiXirZw76mAvxkGt4dtpRPa46xpfoIbw1dwLMlu6kxtAHuNrGXM+ayrnw/96dcg85m5snCT7l34DXckrvB40CXqo1gZepUVhV9Sr2xnZcz5qIQSSnXNVFtaGWwTzQ9NqPb/MEnisOtZ3mr7BtWZy9CKZJR2lPPk4Wf8uzgG4hW+3Pbifd5cchsAuVefN14mmF+8fhJNZgcVkp7GnrtuYPQ2c28fGYPB1rO9LlGV4UMYXrUcG478R4rkq6g2tBKtl88L5S4q03XR48mTOnzqza/LquhT7Wu06J3V4B6W/UuC04jUObF5l5TiOcGXU+QwpsguTf+cg1Ol5MKfQtqsdxTvfo9fulK1201oJYoEPUeW4dFj6BXQP68rcvqDkL+WZz/M9DbzOxvKuSZ3ja8SKUfdcYOnLhI847g2cE3/K7DZz/99PM/p7/C1E8//fxbIhQI8JG5H56ujxrFwrixFHTVcM+pj9BIFAj5+05KIqGIEQGJTIsYRojCmynh2QgFIBYIOd1ZzcWBA3kofyuF3TUIEDDIJ4r8zir2NRagEEoZ4hv9h4+x22rkh+ZiQhTePF/ymWe7AAFqsZz9TYWc7qwmTh1Eua4JlVjGtuqjALxfcYAbY0bjAlae/oS8zkrO65q5KfZi3jv/I1835jPIO4ol8eP4rqkQi9NGl9XIsoTLWFO+3yOWboq9mCE+MeS0n0MsEP29w/QQpNDyRPoMHi/YTk7HeXLbz+Mv06AQSXk5cy6PFWxDZzNjddq5JnwoP7YUA3BX0lVcFDSAxcfX0WbRsa+xgGC5N15SJWqxjMXx45hlG8nzJZ9x1Y/P83jadBI1IRxrL/e892CfaF4q2UOWbxwTQwdT2FXDuODUPg+KYwNTWBA3lhRtON82Ff7i6F2oJe4cJofLiUwoYXX2Qp4o3EGI3JuB3hFU6lv4sv4U1YY2FseP49rwbGqN7Tw/5EbuzvuQicGDeH7IjSw4uhqd3YzBbmH9sCWsOPEetcZ2Wi09rEydxq0nNuJyuXgnexFp3hGeB/taQxu35G7k1sSJdNuMPJY2nacKd3Kmp57rD78OuCt5D6dcS4BMg1aq4pKggXhLbyJRE+IR4nckX4VUKOamuIsJU/oyN/Zi4jXBdFr11BraPWfcaTVwpruOh1OvJUjhjdPl5IlBM7k1dyM2l8MjYou6a3n97Fc8Peg6LA4bDpeT185+RW77eW5OGI+PVMWPLSXsqs3h8pDB3JI4kUuCUpAKxVx78CUG+0SxadRtGBxmFh5bQ7fNxP6mQrQSJa+d/QofqYpXM2+iXNfIs0W7EQtFrM5eRLO52yOW7k2+Bo1EzmMF2xniF8OHlQfR2c08U7yLuTFjeKHkc+pNHeypP8l10aN+JZaAX2UQ+cjUiIQi7hxwFa+Wfsn+C+6JmZEjGOIX65k9gp9DQYP/4Wfgl/xSEF/Y6mt32qkxtnHvqY95Y+g8EjWh1BrbuDl3Aw8OnEKWf9w/TTQ5XU56emfeRgcM4JHUqRR21XJf3scY7Fac/z1r2v3085emv8LUTz/9/OXosZko1zUSpw7CW6rC7LBR1tNIqML7d+cJOi16RAKhp4qjt5mwOh24cPFCyef82FzCAymT0UqUnO6sZkv1YebFXsK0iGF9Zpi6rAYcLhd+vS1ZBrsZi8OOr0xNcVcd84+9w8K4S3G4HLxfcaDPMSR7hXF38iRuO/EeVqeDVzPncrj1LJ9UH+W+gdfQZOpiSkQWX9SfYkPvTJWvVO2pzMyKGolWomTduf1sHnUbdqeDd89/z8ELVvSH+yVwX8pkNGL5PwzWbDZ1IxYK8RIrONpezstn9vBgyhRcLmgydXJJUApN5m7aLTo+qjwILrghZjQdFh1J2jB8pe5WtSp9K9HqQJwuJ1HqAIx2Cx0WHY8Vbmdx/Di6rEaOtZXxVUM+8De3NrVYzjODr0chlLC8tzpy/8DJZPvFsa+xgLXn9gOwIvFyDHaLx5AhROHtcQMcF5TKddEjWXJ8Peuzl3De0OzJnZoQnI5IIGRvb0XsnuSr6bQauCpkMGX6Jh7K34JUJOajEbfyQ3MR71xQvQL3LNuq9JnsqD7Gic4KIpV+vJm1wONM1mru5oWSPRxoKUGIgFuTLkculJDuE8XZngaeLtqJQiRl44ibUYpknnvI4rAhFoo81Ymf6bGZ8OoNr3S4nOS0neOOkx/g6q2gekkUHG1zC84n0mYwLjgNm8vO9ppjvFO2D7VYzrODr6dS38orpV8gEgh5M3M+8V4hWJ023ijdy74mt9nJhRlD10eN4rqokQgE4C/z4kxPPctzNiAWCDE43GYJWomSDcOXYXXaWZaznh6bCZlQgtVp7z2+CObHXky1oY02i44IpR+Xhw5CKBBS1FmDv1yDUCDixZLPPdVMAJlQzBPpM2kxdzMmaCBqkczz+WwwdiIXSf6uO1q31cjSnPVU6Jt7j0/Bjovu/h8Hyf5ROq0GFh1bQ62xHYVIyv0DJ/P62a/otBrQSpRsv+jOf2rQbLfVyKmOCtK9o/CTuyt6hZ01RKr8/3DFrJ9++vmf8Ue1Qb9g6qeffv5rqDW00WzuRiGS8HHlIWZEjsCBu92sqLuWq8IyUIllnrbAFnM3dyVPQiYSc6D5DJ9UH+HFjNkoRFK+rD/FOV0TN8VewrPFuzzzOmKBiE2jVlClb+XzuhPMjrmINO9IjA4LRV21HG47y6c1x92WwdlL2Fp9xJM/AzA9Yhh+Mg1rz+0nTOHLM4OvZ+P57z0r+kN9Yz3vNcI/kYdSrsVPpv6Vwxm47Z/vPvURYwIHkOEby9NFO3kwZTKrCndidzl4PG0GgXIvnijYQYWhhTeGzudsdx2p3lGIBUKW5KxnoDacJ9JncKK9An+5hvfP/8jK1KkUddciE0rYVnMUm9POAylTmH/0HSxOO3OiL2JyRBZLj6+j3arnqtAhTI8czrpz33G0rQwAIQJmRY1EI1Gw7tx+7k2+hrzOSvY3FTI+OJ0bo0dzqqOCN8q+ZoBXKPcPnIzZYeNoWxlKsYwem5HNVYf7nO/C2LGoJXJeP7sXpUjKCP9ERgcOILRX/IgEQr5pPM32mr/NZz0z6Do+rc3hZEcFQXIt64ctIdgjlnpYVbiDGVEj2HjuB0p66kjxCuehtGu548QHDNSGcUlQCl4SBWvL9yMSCHkxYzZCBBxoOcMlQQN/s1XS4rBhsFvosOhZWfAJCeog7ki+im6LgdfK9lKlb+XVzJuI07jzubqsBrZXH2WgNtxtMx+YTIjCB5lIzDcNp/GTabg1cSIt5h42nP+eH1tKPO81M3IEN8aM5uH8rfTYTbw5dD4BMi8+rz/JcxcEHr+dtZAsvzhcLhcV+hbmHnnL0/4Xqw7k1sTLefj0VuI1QTyVfh0aiRy1RIHd6aDe2METhTvoshp4beg8pv/0ime/V4dlckXoEPR2E4+c3sbCuLFMjxxOu1XHspx3yfSJ4a7kSX1EU5fVwKaqQ3zwi8WI8cFp3J189b/cfrrO2M7NOe965ugA9985ezGx6qA/nBlktFtpMXfjK1XjJXVfqzpjO14SZZ9zcLicfcT1L3/up59+/jX024r3008//VyA0W6hoLOGN89+zf15m1mWOB4XLtaX7+fm3HdJ9Y7wBNpW6Vv5uOon9jUV8PKZPXzTcJrHC7dzpqeeTZWHEAmEXBw4kGmRw6jUN3Oqo9LzPnaXgw8qDhAs13LfwMlEqwIQC4V4S1Uke4VyQ9QovMQKWsw9HGk9+6s8EqPDipdEyTVhmawaNBOlSEqIwheA+5Kv4ZbEiaxMnQq4bc6bzV2U9jRgdzr67MfmdNBm0XFv8tUM80vk5TN7uCRwIDHqIELkWjqtBh4r2M4D+Vso1TV45n+y/BN47eyXiIVilieO55bECTxTtAuFWMKO6mMsjh9HXmcVjxZs45GCT5gbMwa93cwLJZ/zRPpM5sVezGUhaWyrOsJj6dO5NjyLxfGX8cjpT5gcPpQ07wgAnLg4r2/y/PzSmT0M9YvjnuRJLIgbi0wkZpBPNA+nXMui+HHckruBF898zoeVB1lbvp8p4VkEXTDbESz3Zlb0SOS9rVLRqgCuDs8kUunPj83FPFu8Gx+pimNt5X2u03dNRUwMGYQQAUa7BaPjbzbSQgRIhGKeLd7Nw6nXIhIIWZk2leNt5bRaejjQcob9TYWsKd9Pma6RMl0jtYZ2jredI1Thw3vnfqDD0vfvC26xlNdZxdyjbyMUCHgibQYzo0cy+8hb1JjauS5qJE8Pvq5P25m3VMWUiGzKexoRIGBqRDajA5JQiCSc7WlgfuzFnOqsJLfjPJl+McyNGeN5bZQqAKvDTpmukTpDO50WPdWGNlaXfdPnuJ4u2km9sQOzw0adsR37BaYDHRYDIoEQf5mGu5KvJljhjbq3UtZq7qbR3IkAuHfgNdx+4v0++91Tf5ImUyfdViMWp413yvfxeulXLMt5l3aLjsNtZzFcYAnudDnJ66jyiKXpEcO4JXEiAN82FbKn/iQWh+1X1/WfSbjSj0fSpvXZtiLxcqJVgX9KLB1tO8usQ6+xuy4Hnc3EmZ565hx5m9dLv+pzb/xSHP1fiaW/ZzTxn2g+0U8/f5b+ClM//fTzb8Mvnbt++fM/wuFycq6niaU56zA6rGjEckwOG3aXgyhVAG8One9pf+mxmfii7iSvnf2qzz7cNtHTEQgEvFzyBVeHZ3LnyQ9w4iLZK5QkrzB21+UC8GrGTeR3VmFz2bkmbCgKsZTTndXsrc/j9gFXcqqjkoKuGo+5woXtU1eHZXJ1eCZLjq/j9qQriVUHIhdJaDZ382jBNm6IHs3YoIGAgCXH1yEVivlgxHJCFT6eoM1uq5HNVYfY11jAgylT0EqUlPTU8dbZr3kzawEvl+yhsLsWcLe8TQrPJFYVyEOnt1DcXYe3RMVLGXNYU76PEx0VSIViPhxxC0uOr6PHbgIg0zeWuwZcxfxjq7E67QzyjmJ+3CXUGNoIU/pR1tPAVaEZvFb6JdfFjMTpgvvzPqbbZiLLL47J4Vk8XrAdu8uBUiTF5LAxISQdi8PG0oTx1BrakArF/NhS4rmuAgS8lDGbg81n+Kz+RJ+/z+SwoSyKv5SDLWeI0wRTY2ijoLOa4QEJpGgjuK13ZkkqFDPCP5EDvVWYy4LTyPaL55niXWglCtYOW0Ks2l3ZaTfrqDK08sbZvZzpqeem2IsZqA3nbPff8pzA/YD7zKDrkQkl3HHqfcIUvrydtQCZUIJfr614h0WPCxAJBMz46RW6bSb8ZBruHjCJp4t3YrBbCFX4uI1NZF4eO+0LcTspOlCKpfzYXEJRVy3TI4ejEss4p2vyVETqjO34SNUcaClmTswYvm8qYlrEMMA9I/R9UxHvlO9DK1GyPHECr5z5EovTxtSIbIb7J/BA3macuIhWBdBu0aGzm/GRqng8bQZvlX3Nk4NmEaMKpM2iw+5y8GX9KS4LTuOV0i851laOTChmZeo0Pqs7wYmO8wgQ8OmYu9lWfYSt1Uc856MSy1iXvYQ4TVCf+aZOi543y75GKZKxMP5SxAIhe+pOcrj1LE+kz/inW33rbWaMDgs+UjUSoYhKfQvLctb3yY5SiKSsyV5EolfoHxI0nRY9b5zdy5cNeQBcGpTK4dazWJw2QhU+rM1eTNBfqOXO5nRQ0l2Hv0xDmNK9SFOhb8budBL/i79PP/38p9BfYeqnn37+o2g0dbKm/Fvaze5wwzaLjjXl39LUO+fye4gEQuK9glk7bAkSgQiJUIzd5SBU4dNHLIG79WZSeCZDfGI826RCMU8OmoXFacPlcjFAG0q7VcfowAEke4WxKH4cIQpvFsSOZXxQGk6cfFB5gM1Vh9lSfZgfmop5tGAbR9vL+abxNLGaIHS9wuP6qFG8NXQ+1/W61HXZDNT3WqMfai1Fbzezs/Y4IQpvVGIZm6sO8XrpXpYcX4cLF6MCEtHbzeR1VXlWrQ12M5urDlFv6uDZ4t1811zEc8WfobOb2Xj+B66PHgXAjdGjyfSLJUzhwzcNp3kgZQpeEgVdNgOLjq/xtP89mDKFTVU/ecRSkiaEh1Ou5dmi3UwISUcuknC6q5rnSz4jXhPMpzXHECBgxYkNFPfUYXM4uT9vE902E1qJgstDBnO0rcwjWDeNuo3liRP4pvE0eZ1V2F0ODrSeIaI3TPdnJoYMotHU5RFL82IvYXbMRQB8Vn+CI21lZPvFc8fJ93mmeBeDfKL4tqGACn0zcZpgpEIxzw2+gbuTJ3mqMO4A22i0EiUuwOVy252DuxK2tfowZ3rqESJAK1HicDiYGpntsUYHd8talMqfu059gEYs55XMuTyUv5U99SfpsRrdlvelX/HqmS9wuJy8nbUIlVhGu0XHQ6e3YLBb8JNpuH/gZB4t2EajuetXVUNwO+gFyL0QCURoJUp21eYw+8ibLM1ZR4TSj0ilHy+UfM6mqkNYnFYWxY3jkdPb+LrxNPubilCIpcw69BpWp53lCRNYO2wxV4dl8k72QtRiOZPDh6IUyRAIBKR5R3DHgCtZNWgWGrEcqVCMSCCkw2rgycKdNJm7eCh/C/ef2sQ14UNpM+tZEDuWeHUwT6TP5PP6E9ydfBXZfvE8kT4DH4mSGZEj+pzPqIAkQhS/ds7zkam5NfFyFsaPxUeqQiNRcHW4u+r6rxBL3zSe5toDL1HYVUOHRc+dJz+g02pw/y0z5hIk12JyWLk1dyM6m/sz0Gk1YLqgMtZu0dFjNfU5hxVJV3Bl6BAAvm8u8oild7IW/sXEkp2irhqW57zLLbkbaDB2UKFvZunx9SzNWcc5XXN/pamf/2r6K0z99NPPX54Oi57lOe9SYWjhooABPJI2jVWFOzjUepbYXkvrPzLTYHXYKequ5e2z33Bn8lWc6DjPJ9VH2TBsGeBCJpLgJ9NgsJv5sbnEEyj6M+OCUhkVkITebmZccCqf1uQQrvLFW6Ji5emtXB89mosDk7G5HJT1NFDW08iu3srIzwz1jWVa5DBWFX7Kk+kz6bAaaLfo2F2Xy6uZN1HcVYtEKObJok8Z7BPNtIhhPFawDZvLQaZPDHckX8WcI2959pfpG8utSZfzSP5W7ku5ht21J7g7eRI+UhVF3bWsyN3YJ79qiE8M82Iv5r68j7k6fCg+UhXrz31HnDqI54fcSKu5B6vTzu0n3/e8Zm7MGEYHJLEkZ71nm1ai5JnB19Ng7KTbZmCITwx3n/qQLpvR7R44+EbmHX0HJy5UYhlrsxfzWMF22iw6Xs28CalQTKOpg6LuOq4IGczq8n1EqQIJlnuR6BVKYVcNersFAXjChrUSJXq7mUfTprG/sZBYdRBTIrJwuVxsqzlKnbGd8cHpPFO8G4vTRpBcy+Np7pyfNouOh1KvJUYdSJBMS077OeI1wYiFIrzECs7rmxELRGilShI0wQgEAjotej6qPEi2fzzPFO3mjgFXYnc6SPQK5dGCTzx5SD9zWXAak3uv6YHmM6w//x0AC+Mupc7QzjdNpwF4JWMumT6xfNtcwFNFO8nwjWFUQBKhCh++byribE8D82IvIdErlESvkN+8n80OG7nt57j71EcAKEUy3h+xnPcrfuSr3qrGz4QovHkyfRYPn95Ks7mbAZpQXsyY4zGpsDsdGHorti6XizJdAwEyLU2mTnbV5nJjzGgUYikOl5OVpz/hpYw5NJm6WJazniC5F69m3MS7578nt72CpwbN4v3zP3KiswK1WM57I27GV6Kiw2bwtOFdyLKE8UyPGIYLaLfqCJH7oBD/86y7f492i46lOeupMbQhEYi4JXEi4So/Xiz5nJWpUxngFYbObmJF7nvck3w1Kdpw9A4Lx9rKUIpkZPnFAS4ezN/CmMDkPgHPdqeDwq4aluasJ0ETgrdESYw6gKUJE9BI5FgcNmR/gfwhu9NBaU8DN+e8i8Vpw1+mweq009O7wHFh1bWffv6T6K8w9dNPP/8xSIViruutiPzUWspVPzzHodazANwQNQrp74RVwt/E0uqz3zA3dgzLc9+lxdzDgtix1BnbWXR8Lc8U7abdouOcrtkjljJ9Y7k+yv3e3zUXUaprQCwQ4XC5qDQ082ThTu7N+xijw8p5XRMOl5MafRvPl3zOxUEDGeAV6jkGlUjG4+kzeKJgB5m+7upVrDqwN2RUgc3p4HhbOU8WfYrD5WRSWAbfNhV4Bu+TtKF95qUAqgyt9FiNvJQxh1WFn/J9cxEPn95Kh1VPla6FiSGD+vz+AymTefHMHuwuJ6P8E0n2CkMkEHJe38ytJzbSbTPyfsWPfV7zed1JjA4rkUo/EjQheEkUdNuMPJy/lWh1ADtqjvNa6ZesHbYEuUjCrMiRnOqoxIl7Pc5gt1Bv7OTRtOm8lbWAJwt38G75fpK8QrkmbCjfNp7mZEclIwMSsTgdyHqrf1eGDian3e22NiE4nfXDljApLINVhZ9yTfhQJoSmY3ZY2ddwmsnhQ5kYMphVRZ9icdrQShS8k7WQ051VtFh6cOLimaJdtJl7KOmp5ayukUp9C982FrD+/HfUGtt5tngX3zUVYuytGthdTo60lfN00S7eylrAQK8wBmjD2NuQR2lPAyKBkBeG3MiS+HEA7G8qxOqwY3XYuSRoIJcFpwGw4fz3HrF0a+JEIpT+lOkbeLX0SzJ8Y5gROZzzumZMDhvL4sfzQMq1fN9chPp32k1FAiEqsRxBr9W+0WHhyYId3Jo4kcE+0X1+77nBN/JA/maazd0kaUJ5MWN2H1dIsVCEXCRBLBAiFYlJ9Y7ET6Ym0SuU2wdcQYJXCOFKP8IUvryW6a64DPAK5fXMeTyRNpMeu5nj7efoshk42VHBbQOuIFLlj95uZsO5HzA4rLx99hvaLTpUYhkfjLiFiSHpAKw/9x3dNiNf1J/k+kNvcKStDJPdyj+DdouORlOn5+cem5EmU9/qnZ9Mw5tD5xOp8sfmcvDa2a/YcO57XsmYS5wqEK1UiVIk48WM2XxSc4Sddccx2S2c0zXxeOF2XjnzBYVdtRR01fB22T46be42PrvTwZmeem478T5JXqEsS7iMSeEZ1Js6+bohjxpDW29Om+lXx/3/G7FQxACvUFZnL0IqFNNm0dFjM6ERy/vFUj9/mh6riXO6JvQ2M+AOvj6na/pVQPO/E/05TP30089fHrVEzmUhaRjsFl4/+5VHQNw54CrGBaeiksh/Zw/u1iqT3cKwgASOt5VjdtjYUXOMcUGpvFfxA20WHac6KtDbzEQp/ZkUlkGruYfro0eR31nFgrix7G8sYGxgCuFKX947/yNzYi5Gb7e4BYGhnaUJ4znf08QAbSiTwjKQCMV9XNIMDgsfVx7i3eFLOadr4qninUwPH86rmXNRimTcnPtun+H3p4p28mjqNGxOO0FybzRiBa+WfkmAzIvnhtzA62e+oqC7hudLPuetofN5Mm0Wy09sIL+zirfLviFFG8Ge+lN9rsOdJz/gpYw5tFt0bK85hp9UwwtDZnP3qQ95IHkKW2sOk9dZBcAtCRP5rC6HOlMnjxfs4M2s+bT1VgceK9iGRiLHaLdgclhJ1oZjtFvYNvpODjSX8HLpFwgQoJHI6bGZWHl6K69kziVc4UuiVyhTwrNYXfYtUyOGcXFQCmOCUnih5DOKu+uYFJrBLUkT+eD8AWbHjOa8LoFJYRn80FjEteHZhCl8SdCE0G7uweJyUG/qoNNq5OninTh624aMdisNpk6Ot58D/hbA+9DprTySOo1UbQRH28o8lZjH02YwJjCZaRHDsDjtiB02AuRevJZ5E4dbz9Jp0bPixPu8O3wpA7XhTAhJZ5hfAvsaTnN99GhcLneGmLdUxatnv0KIgOeH3MjxtnJ0dvdDQ4ImhIkhgzE6LNxz6iP3vFPSlSw6vhar047VaSdS6cfDp7f0zs4IeDRt2t+1sLb1Vi5W5G7EhQtvicqd5yOE0p4GznTXe37X4XLyTWM+10Zks/7cd0yOGIpW0nefRruF423niFL7E6MKxOFycqanHqvDTpp3JA6XE5vDznl9M5X6Fi4JSkEiFBGtDuBsTwMHm8/wZPoszuubGReUylcNedw9YBI57ecYE5iMWCjinoFXY3HauTVxIlqJihH+SYCAEf6JfN14mvXn3BW53PZzZPhGo+B/V2Vqt+h4+cwX5HdWsSZ7MT5SFdurj/FB5QFWZy0iySvU4y7pJ9MwL+ZiVhV9CsCZnnpqjG1EBw707G9z1SGOtZVzrK2crxryPUHDSrGMRlMnAgQ8N+QGgmTuVWqd3czqsn0Eyb24NfFy7s/7GIvTziOp0whWaLk1dyNN5i4eHDiFi4MG9qmS620mj6nG/y/EQhEqsQyxQMjPclUmkiAX/t9XwPr596HHamR3XS5vlX3DypSpjA1OJa+jkvvyPmZm1AgWxI39p9ry///iT1eY5s2bx8GDB/8Vx9JPP/3085uYHTZOtJ/vsy23/Txm5x9zy5KLJGT6xTHIJ5o5MWOYETkccFeN2iw6VCIZa4YtJkLlh7dMxa2Jl/NI2jQ6LHrerziA1WFnZeo0Oqx6JAIRV4QNcbfhRY3ingGT2DDiZtaf20+QUovN4WB65HB+aC5mfHA6c6JHMyk0A4Ct1Yc51FrKeX0zbw5dgFIiI1Tuw8OnP8FgtzDUN44to24nQROMw+Weg7ox5iKazF3EqAMJlmt5ZvB1PFO0izuSryLbN44HUiazqnAHRqeFJ9Jn4CtVszDuUl4v/QoXLjJ9YtgwbBm+UhUNpk5eK/0KiUDMwZYztFt16GwmRgcMQCwUsiLxchRCKS8MvpEMvxheHTqPcIUPk8IycDjdc0gHmop5Y+h87km+mscLtzM6cAAhvfMYRpuFd89/hwAB9yRfzcsZcz0r90fbyqk3dTEv9hJ21Bxjb2M+y3LXoxLLKe9pYFHcOMYEDCDLP44bDr/BsIAEfmgq5tLgVG46+jZRmkDazDoyfGJYeHQ1LgGcaj/P1eFDufvUh5gdNgJkXgTLvbG5HNx96iNmRY1kcdw4vrzkARI1IThcTj6tPY5cJPGIpemRw7E77cyOuYhaUxuTD7xAfmc1lfoWHE4X8epgFuesw+y08tbZrwmUaxkdkMSBlhL2Nxdx+4n3uTo8E7VIRoulh5KuOq4Oz+TFks89YgmgXNfInvoTNBo7uXPApN6HdYGngrm/qZBFx9fSaTXgJVFwS+IEtJK/nzlkdlg529OAzeUgUuXPR6Nu5e2shSyOH8eD+VuwOG2EKLwZEzAAgM1Vh7E7HcyKGsmLJXs42l6GubeKY3HYON5+jgfyN7P0+Doq9S2enKYVJ97jnL6Jan0rp7tq2Hj+B14+8wUNpk4q9S28U7aP+/I2kekXi1osx+ywcX/eJq4KG0KowodJYZlEKP3wl2kIlLsDlOM0QQQqvBjkE0Wmbyz7mwo8YunaiGyWxl+Gj/R/bxtusFs42lpGm0XHspz1vFG6l7Xn9mN22NjbkOdZnLA6bOR1VPF08a4+r3/09DaKumqwOR349s5U/TyP9LNYuiosg3hNEK+f3cvlIYPI9ov3GK/4SFU8nj6DdO8owpQ+hCl8cbicPFn0Kfee+pgmcxdykYQErxA+q831zGN2Wg28X3GAKn3L//oa/Bkq9S0sOe42xVGKpJ5K0/LcDZ6Zyn76+T1sLgf5vYtuTxXv5MnCHdyX9zFOXBR11f7d2cx/B/60YNLpdEyYMIGEhASeeeYZ6uvrf/9F/fTTTz+/gdlh6zNM7HA5sf7CMrjdrOOlks9p6G2tGeobixABbZYed5vVL2Yifgu5SEKGbwwhSh9ujB7d5/8N9YvrM3yuEEs529PAU0U7Afi46ieW5Kzj0YJt9NjNrCvfT4Opk/vyNiEUCnn33Hd831zMHSc/AAF805DPjppjPFn0KRNCB5PtH8e8mEuIUPoxIXgQMyKG4y1W8XbZN+xtzOf5ITcwMWQQUyOyWZ77LjcnTGBcUCp3DpjEA3mb3WGp3pGsyV7M66V7Oa9vZsWJjcyLG8v6c/vJ76rm/rzNJGvDGBecSo2hjfXDlpLpE8Pj6TMQCASsyV5CijaCJfHjeOj0Fi4JHMjVYZnsbypkXHAqt598nzfO7mXr6NvRSpXcduI97j+1ideGzidGFciSnHVYnXZGBQ5gS9VhHi3YRqfVgNFuYYBXOAdbznD/6c28nbWoN6upht21ubySMZdbEyfiJVHwdtnXNJo6+b65GID5sWM51lZGpCqAzVWHuHfgNbx59ute2/NtDPGNYeGxNXRYDTxdvIsYTSCLc9bRbtOztnw/k8KG4sSJWCAkWO7NG0Pnsyp9JuFKX8QCIV4SBZcFp6IUy3g5Yw6Tw4YyP/YSHin4BPi56jMIrVTFwZZSXE53sKtIIOCH5mJ+ai1BKZYSqvBhmF8810WPRCoU81rpXg62nEEkEHJvytW8VLKHl89+yXdNhbyZtYAGYyffNRcBcEP0KCYEu9vP1p37DjtO7E47Lw6ZzQP5m/CTabgydHCf+/H38n40EgVXhQ3hkdSpvDl0PkFyLSneEQT2tsqFKLx5c+gCJoYOZkJIOiqxjLFBKeisRly4eLlkD6bexQaZSEK0KqC31dLE/GOrWXZ8PRanjSSvEBQiCbee2MgdJ9/nyrAMXsyYwyfVR6g3dfJVQx4Ol5NaQxtGh4UN57+nVNfArtpcguRaolX+fUwavKUqz2dMI1FQ0l3naa8FuCp0CJp/UmUlXOnLmmGLUYlktFl0HqOQa8IyWRB3qScA1+iw8njBNhwuJ/HqYHZcdJdH5D9asA1Dr+gVCgS/ErAasZye3rajbxpPc17XRKu552/nK1GxPHEi4Uo/Xsm8iShVAA6XE53djEggZHXWIvbW57H63LfccfID2i06agyt2F1Oluasp8XcTadF/3ft6f+ZWBw2qg1tvTNLSjYOv5k12YuRCSW0mntotfR4qrf99POP8JNpeDh1KqP8kwD4saUEJy5StRE8N+SGf7ppy/8v/kemD+3t7Xz88ce8//77FBUVcdlll7Fw4UImT56MRPLXLd32mz70089fC5PDysn2CgLlXsRrgnEBZT2NdFkNZPjGeIahO60G6gzt6OwmrA47mX6x1Bja6LIZaTfruCgouU9mze9RY2jj5px3abX09Nl+U+zFzI6+CK1USafVwJwjb9Fi7magNpznB9/Ivac+olTXQKImmOeHzObOkx9QZWglVOHD/QMns6ro018NtM+KHMkVoYMRC4XIRVKMdguFXbWMDUrBiZN9jQW8cXYvqdoIFsVfyr2nPsbmcuArVbFx+HJqDe0EKbzwkarRSpU4XU4q9S2sOPFeH6EoQMDDqddisluxuxy8fnYvYwKTWZF4OVWGVh7K30KMOpAXhsxGKhTzeOE2lsSPp6Crmgp9M/GaYF4rdduoD/AKpdbY7nFueyJtBo8Vbvecm0woZlX6LPY3FvBtcyHgftAdG5yK1WFjpH8S3TYjO2qPE6n0493z3/P84Bv5ujGfoX5x/NhUzA0xo/mqIQ8/qZoT7ed5JG06ZT2N7G8qYFxwGo8Xbu9j6ewnVfNY+nSeL/6celMHKdpw5seOJVjuTYW+mUiVHyqJHDEiCrtrSNCE0GMzUqFv4eWSPWy96A40YgUl3bU8eHoL5gtE+T3Jk2gwdbK56jD3D5xMunckt598nzaLjtnRo7k8dDAGuwWhQIBGomB5zgY6rHrUYjm3JV3OmZ4GdtXmALA47lKG+ydgcFhZW/4tQ/3ikArEXB46yBNuuyThMm7OeZcmcxeRSj/uTr6axwq202X72/lOCstgReLlf9da/EKsTnufGT6rw063zYjNaUclktNjd1+DGHUgapEcq8vOa6VfsjxxIpEq/z77qtS3MP/oO54sqgCZF+uHLcXpcnJP3sdU6JsRCYT4yTS0mLuZHX0R3lIVZoeVWVEjkIuknOyo4Kv6PO5Mvuo3Q3vBbXv/SfURj6HHz8iEEtZk922X+9+gs5l4tmg3+3vvU4BdY+7x2GaD2xGx0tDCiyV7eCxtOsEKbxp721AfSplClDqALquBjyp/4qNKd4eNr1TtyVBbFHcpPlIV5bomIlXu3K9nBl+Pj0RFYXctTxft5M2sBThdTpYdX09L7/eOAAGvD52Hl1jBouNrEQoEPJk+k63VRxjqF0eiJoQETbDb8dBhY3nixH9pYK/RbiWn/RyRKj9i1UEeIwir006qNgKpqH+Ko58/htlh5cfmEh4t2ObZdmviRKZFDkMl/v0W+v+f/EtNH/z8/Lj99tvJy8sjJyeH+Ph45syZQ2hoKHfeeSfl5eW/v5N++unnvxqrw05eRyX3nPqIpTnrOadroqynkWU567nr1Ifkd1bj6C3dWx02Xi79gvvzNuMn02BzOthWfZS7Tn6IQixF9id67HusRt499x2tlh5UIhmrsxZxdVgmAB9X/kSP1Yij13jgpSFzGBs4kMfSpiMXSXghYzbjg9O5J/kaNGI5L2fMAaDB1MnzJZ/xRua8Pu81OmAA0yKzOa9vZn9TEbOPvEmn1UCowpuCrmomH3iRYIU3r2bMZWbUCKoNrdw24ArEAhGPp88kQO7FsIB4otWBntVwoUBIjDqQ1zJv6vNec2Iuwk+qpsbY5lnBP9hyhodPb+Wh/C3YXA7MThsCAVidNh5OmYpvryPcCP9Exgam8FDKtYB7BuZnsfR42nSeLt7JAE0In150N6EKHyxOO+9V/MBtA65gTq+ld7tFT6ImhJEBSSglMuQiKYmaEJ4t3k2bRUe1oZVkrzB+bCom1TuCW3I3kOUbx1C/OG6KvYTjbeXsqD3G5/Un2VWbw62Jl/c5v3sGXs2umhzqTe7WoNsHXInJYWFXXQ5PF+/E5nLgckF+ZxWPFWynQteMl0TJd02F2HFSa2xnT/1J7uxt3ZsWMcyzAvrSmS9I844kyy+O50s+Y8Gx1Z42zREBSdTo27jr1Ifce2oTepsZb6kStVjOk4NmkeEbyxUhgwlV+HDXgKuYFJbJ5/UnuS/vYxbEjcXlcrH+/Hc8XrCdm2IvZkHcWJb3iqVguTePpc/wiCUviYIrQgYD8EX9KdaUf/u7Q9K/NDyRisT4ytTobGamHHyRSn0L6d6RiAVCbjr2Nl/Wn+Ke5GuIUPr1EaR2pwO93YztgnYZs8OK2WElTOnLS0NmE91bHWnpzXqK1QSiEksZ6huLSCBCJpKQ6RvL3clX/0Ox9PO+t1QfBtxteHsuvr/33rKx7tx36Gzmf/h6o91C5wWhz3ang67ejKqf6bEZ2VZ9tI9YAlhyfJ2npQ5AIBAQqw7i2cHXe+IFQhQ+PD/kBqLUAZ79/9xmNCtyBJtH3cb4XlOPwq5aLgpMZmbUCN46+zUFXTU8lL+FI21lrMjdiNFuodnUzfKcDbRYepCLJIQovHHh4s6TH9BjN7E6exGTw4dSpmsir7OK9ee+o1Lfwrpz37G9xv25KOiq/pdaeyvFUkb4J3gMHn42gugXS/38GUwOKzlt53m8YDuAx5TmrbJv+K6pyGME8e/G/8olr7GxkX379rFv3z5EIhFXXnklxcXFDBw4kFdfffWfdYz99NPPfyBSkZhwpR++MjUGu4WFx9ay5PhaTA4rfjINYUofREIRPTYj3TYjXVYDFqeN5bkbuDfvI/Y25uPC5Xa8cv3xnmgvqZIl8ZcxOiCJF4fMRiGWMiksk2vCMnlpyGwQCKgxtGN2WDnWVsaC+Esp6a6jztjO/XmbmBd3Md81FdJtM/LQ6a2e/U6LHMantcf7vFd+ZxVNpi7SvCP5pjHfPd+Rv4ncjgoeyt+Cw+Vkc+UhYjVB7G8q5NXSrziva2b7RXeS4ROD5DdW2NssOp4v+bzPtk9rj+MlVTIzcgQJmhBuT7oSgDJdo3vORenHKxlzwQX7Ggtot+oQCAQkqEMYHZCEC0jWhnn+cQMIlbvnLtK9o1iSMB6BQMCrmTcxOiCJewdeQ5W+BS+JkodSrmVyxFCsTjtKsYxOi4G3y77mkYJPcOLi+cE38FNrKU8U7uCGmNGsKd9Pp9XAowXbONF+nhUn3uNYezkj/BOJUwdxY8xoXi39ss/5PVu8m2sisohVBwKwMn8r8ZoQ4jXBrEqfydtl+1iasw5fmZrH06ejlSpZeXor0yOHk+ETjdAFV4QMIl4dzE2xFzM/7hLuS7mGSwIHMsI/kQRNCGa7u+pkcdoRIuCtrAWY7VaMTivXhmfTZTNw58kPWJF0BU8Puo5mUxdSoZhIlT9rshczxCeawu4aPqs7gdlho6irliC5NwIEFHbXsq+pALPDhpdEiUIk5fkhNxAo0zLYJwoviYLXM+dzS9JElsVfhlggYlxwGkqR2ymvxdzN+T+YhaOzmVh7bj8Gh4V78zaxqy6XpTnraTZ382HlQewuB1WGFhYdW0OlvsXj5rY8511sLgcBMi+8JAp0djNLc9ZRpW9FIOBXYa0yoYQDLWdYlvsu3ze7H4RkIgk+Mne195cNLBcee4Dci7XZS7ghehTL4i8jSKHl7ayFXBEymJWpUz37+HsY7RYOtZ7lhsNvUm1oxd4buDr9p1c401PvEU1dVqOngnVNWCYfjrgFlUhGq6WHd8r20W019tnvLwfRL/zZX+7Fs4Ov557kq1kYfym+MjW3JV3BnQOu4rF0d1XKW6Lk2cE3IEBAQVcN9+a5q8VRqgC0UgU2px25SMKa7MWsH7aUBHUwTpcLk91KaXcdO2tzCFf6MiYwGYB3yvd55uxuirmYIT4x//Lw2F9anIuFon6x1M+fwmS3srp8H05cpGjD2Tv2Qc/i1Lpz32G9IObi34k/3ZJns9n4/PPPee+999i3bx/p6eksWrSIG2+8EY3GvaK0detWbr75Zjo7O39nb/9/6W/J66efvx41hjYWHltNd6+1rrdExcYRywhX+tFjM7Gz9jifVB9lVfpMni7a6ZljAlieMIGpEcM8mSd/BL3NzEslnzMmMBm1RM6D+VsYG5TCNeFD0UgU3HPqIwLlWu5JvhoviYLHCrZxoqOCBbFjQQAHmkt4YchsXij5jOPt5xAi4O2shRxsOeNZMR8blEJBVw3tFh1qsZzV2YuwOx08dHoLjRcE7Q7UhrMgbixvnf2aKkMrAA8MnMyEkHQcvV/NnjkLmwVL78zJyoJPyG0/jwABC+PGsqsu12PX/P6I5bx25iuuDs/kgfzNnvca5hfP3JgxNJu7aDHrWHtuP4+nzUAoAD+pBrPTxiMFbuMJiUDkcSIc6Z/IsoTxLDm+nmUJlxGk8MbY61a4IPZSxgWnsK58P05crEi6Al+Z2mPQcc+pj7g5YTxTI4ZRrm/i9hPv8UTaTKLVASzNWUe3zUSsOpAM31gOt5by9tCFKMRSZh9+k3arHl+pmodSpvB08S46rQb8ZRreH7GcmT+9itFhJc07kmcHX4/eZqbO2M77FQdos+h4LG06m6oOMSdmDAVd1aRow/m6Mb/XgMAXsUCMVqqkx2qkwdRJg6kTlVjK44V9WyofTrkWrVSJwW4mTh3MXac+pK33b5rkFcK9ydfgI1XjI1PRbtYx89CrzIwaicVhQywUkqqN4OvG04zwT+Ro61kWxF/KzpocZsdchMFuRitVYnbYsDsdCBAgF0poterwlihwCaDHZiJAqkEoFHF/3sdUGVpZm72EeE3Q7z44t5p7eOT0J5zq/JsNvUIkdbeKSZWsyH0Pnd1MjCqQNcMW0W7WcdPRdwiQe/FO1kIAFh9fB8Dq7EU8lL+FMl0jIoEQb4mSdqsekUDIU4Nm8XndCWZFjSTDNxa5SEKX1UC7RY/T5SReE0y31YDBYaXF3E2KNhxp70O50+VEbzfjdcFckM5m+t0Zpk6rgekHX0ZnN+MnVXNz4gReLPkci9NOrDqI1dmL8JGqsDhsnOio4GBzCUsTxuMtVVKua2J12T4eTp1KwP9glsLqsPcREDanHckFVT6T3cIbZ7/us3iye8y9hCp9qDa0YrRbSNCEIBaKaDZ1UWlopd7Y7lkAGeYfz+1JV3JzznrPd2KcOog12Ys93wX99PNXp8nUxeryb7klcQKBci3tvUHzN8VeTLjS7//68PrwR7XBnxZM/v7+OJ1Orr/+ehYvXszgwYN/9TudnZ1kZGRQWVn56x38H9IvmPrp56+Fw+WkrKeRJcfXecSAQiRl/bAlxGuCcbhcFHXVcFvuezyYOoWvG09zrO1vLb/rhy0lRRv+p2YdGk2d9NhMFHXVUG/s5OOqnwB36GhpTz11xg6kQjEvZcxhU+VPHlvqR3oDLJ8t3k2P3cQjqVO5P28zD6VeS5ZPLGX6Jm7N3ciksAzGh6RjcdhYVfQpceogpoRnUdBZTYDCizfPfu05lmcHX8/O2hxye93/7k2+hitCB2FzOthTf4o07whi1UFIhCKOtpUBAgZ7R9Fo7uKW3A08njYDhUiCQCDg8cIdXBU6hHClH2qx3BN2qxBJMfXOpFwcmMzShPE8X7yb0101CBAwISSdMIUveoeZbdVH8ZNpeH7wDZzXN/Ns8W5kQglvDJ3Hk0WfUneBU1aaNpLliRNI0IRgcJiRCSV95ivMDhut5m68JEq0UiVdFgNmh41KQwudVj1aiZI3y77mtqQrKOqq5eLAgUQq/SnTNWBx2tlSdZhZ0SOp0reQ7hPF+nPfMSdmDD5iJXXmDt4u+4bnB9+IzWmn22Zibfl+ZseMRiAQsKPmOEfbyvCRqnhr6AI+qjzI142nkQrFbL/oTkIUPoC7zarO2OGx+f65DS9U6UO5rgmAuwZMIlUbzoeVB/mxpaTPvTQpLIMVSZfjI1Xjcrk4r29m6fF1zI8bS6ZvDN81FRGjDiDLNwEHDjZXHuLGmIuQC8VYnHbuOPkBFqeNVzNuQigQ8Grpl5zurObtrEUcaytjw/nveXLQLH5oLKbe3EFRVy0vZcwhyy/uH4ad2p0OxEIR1YZWZvz0t26PqRHZ+Mu8WHduPwBhCh9ezbwJb6mKgs4aIlX+SIQifKQqCrtqCFP6YnPYcQHLczfQbTPywpAbiVUHcvcp90zTXQOuYqhfHBFKP2QiCe0WHdWGNu7P24TD5WR19iKcLhePFWyj1tjOa5k3McQn2iOa/ie4XC7O9V5r/QUuhGEKX97OWkio0sezzeKwYXJYPdUip8tJj830L7E1/jnrbUXuRs+CA0C6dyTPDL6eQLkWp8vZR+zqbWa+bSrg2eLdzI8dy8SQdLZVH2VnXU6ffd814CquCsv4pxli9NPPvxq9zYz6gsiPP7IY8n/Bv0wwffTRR8yYMQO5/K81tPVH6BdM/fTz1+FnsbQsZ727DU+qxomLTqsBlUjG2mGLPaKpztDO2nP7+b7XdeznCohMKGF19iIG/MEBcZ3NxFcNebxW+hWPp83AR6ricOtZT2UI3DMhTw+6js1Vh8nrXZ1/YOBkRAIhL5d+wZPps6g1tqMWy0jxjkBnNTNQG4ZYKKLB1IlMKOa8voWXz+zhgZQpdFuN/NBczIiARJ4q/NQT5gpu174n02fxQcUBirpruTf5Gi4LTmVv42leK/0SjVjOK5lzaTXrePj0VoQCAa9l3kSKVzg2HCiEUvQOMxaHHb3dzA9NxcSqA8nvrHIbLqj8eXrQdeR1VPFK6RdoJQpWZy9GIZTwaOE2CrtqPcfyeNoM6oztjAxIIqe9nBRtBI2mLnykKvylXjxWtM0z9+EjVfFa5jzkQjExmt8PtKwxtKERy6kzdXBrzkYeSZtGsMIbg93Mw6e3siBuLBk+MShFUjRiBQaHhQ6rnh+ai9lUdYg3M+ejELv/31PFO7E57dyedCV1xnYkQjE/NBdxoOUMcpGEFwfPRiwUcX/+Jnp+EQh6c8J4pkUMQyQUegaP7U4HLeZuniv+jMKuGp4cNAuxQMhHlT9xqrOSVekzEQoEPJi/BYAFcWMxO6xsrnLfM0+kzWBCSDoioQiT3cqmqp/I9ovn7lMf0W0zMjt6NDfEXMTNOe9SbWhlbFAK14ZnoRBLuSV3I1annVCFDyEKH052VCAWiNg4fBmdVgNf1J9kmH8CMqEEmUjsdp1TB6IQ/XY+UafFwPH2cpK9wrj1xEaae+eNwD1LcHfyJIq6amm36Hg0bToigZDNVYc42HqG5wffgEai4ER7BY8XbifLN44n0mfgI1NTqW+m2dRNhm8MCrGMOkM7+Z1VjAxI8ghlk93KgZYS4tRB3HbiPdqtelRiGRqxgiZzF2KBiDeHzifNO/J/3eZldzr4tPY4L5/5wrNt/bAlDLogsPf/Nw3GDmb89KqnDW9G5DBePvMlLlxcFDCAR34jU0tvM1NjbEOEkIOtZzwW67MiR1Bv6uRQaykAL2fMZVRA4r+8La+ffv6b+KPa4E9/Y82ZM8fz37W1tQgEAsLDw/9nR9lPP/381+JyuXC6nDhdLgLlWtb0rkQvy1mPwW7B4XLhwv1g5MDJ8XZ3Zemm2IsZF5TKA/mbaTB18lldLuGJE//QirHVaWd3bS4Ol5PHC7dzfdRIrgobwraaox7L3HTvSOQiiUcsgVsgHO0Nu32k4BMu7Q3mBLexw8rUqfiK1R7XMbVEQZp3JA/nb8XssPL+yFtYfGyNu6fbK5yHUq/lnryPaDR18VbZNzyaOo2Fx9fw4pnPUUtkZPvFeVy4bs7Z4JnRGuAVRpjSF3VvC6LOZuKbhgLePfcdTw6ahc1lx+K0E68JZlHcpVwalIpaIidWFch9ydcQqwlid20uATIvlidM4GhbOR/2un712IxcFJiMWixDIZKx4sR7bBq5gpLuWtqtemoN7Z7r0Wk1UNxdy+Uhg373mlfom1l6fD2p2gjuHXgNzw25gY8qD+ItVZHtF8+CuLFU6lv4rrGIZYnjkYokbKz4gS/qT/FQyrW8kTmP8/pmXjv7FXOix/DAwMk8Xridm3PfBdxObq9kzKVM10ijqYsVJ98jVh3Ec4NvYHnuBs9xTAwZxGCfaMxOGx+cO8jsmNGEKHzosOj5vO4kyxMnYLBbeLX0S6oMrazJXozd5SBYpsUpgCt7q3eBUg2DfKPxk2g4r29iiG+0RywdaTvL+nPfoxLLGROYzJ76k3xcdYit1UexuxxIBCKuDB3C1qojTI8azurshdycs4FGUxfTI4ejlSiZE3MRa8u/5UhbOavSZxIs1/J142k+rT3OsoTxhCp8ESLA7nKgEsvR28woxVIMdgt2l5P8zio0YjnPluym2dyNQiTl0bRpbK06wumual4t/ZKto27nnL6JaT+9zIMpU8j0i2GoXyzLct5lQkg6gXIt4LbRBvfsUow6iAilv6eyFa5yZyv9nDkE7nmXAJkXD+dv4bkhN3Jf3sd0Wg0Y7BZEAiGvD533TxNLJd11vHVBtRbggbzNrMlejK9UjUoi8wiLbqsRuUjyD6ty/wy0EiWL4sfxVUMebw6dj7dURaBcy7PFu7kl6be/o9QSOQFSL+YcfZOVqdNI1IQwwj+RAJmGAdowxL2hywO1Yf1iqZ9+/o/40588u93OI488glarJTo6mqioKLRaLStXrsRm+2MBkv30008/YqGIJK9Q1g5bzJrsRYQr/TzD82uzF5PoFYLVYedoWxmPFWzjyfRZLEsYjxABd576kIdTpzI7+iJuTpjwh9tr/GQaXs28iTh1EF4SBVl+8TzYa77wMyc6KtjXWMCdA67Etzc888H8LYzwT2Ry+FDMDptHLA3zi2dqRHafrByj3W0Wsbchny6bAbPTxqOnP+G5ITeQ7RvHwvhL0dlNPJI6ncE+0TyRPgOxUMToAPdQ7PG2cxR31fJO1kJkQolHLMWoAnlm8PV9+r/NDhubqn7C4LDwyOlPcLpcPF20k+dLPkcpkqGVKLE57AQrvTE4zHRY9ATIvMj0i+GbxgIA5sdeAsCrpV9xpruOCn0L2X5xrMtewsn2CuRiGc8Xf4YLFwO14Qz1jQXghZLPOdhSitXx6wFenc1Eu0XnyXYZ5BPF7QOu5FhrGd02I5m+sZT1NHCsrZzynkYkQjFioYgqfQtOl9Mzp/ZM8S4+rDzIa2fdduc1xlZUYhkPp071vJdMJEYgEPD84BsBdxVlVtQIdtfm9jmm423nUInlfFhxgO01R1mRu5FWcw+bqw+zseIHbj2xkUC5lmkRw5gcPpQqfQv+Ug01xnbuPPEBN0SPJss3lmTvcO44+QFpPpFcEToEIUJ6rCYMdguPnt6GCxc/NpdwU+zFjA1KAfD8DV8bOo8BXqHMiBreK9JdjA1M4Z7kqzmvb2akfxLeUhXdNhMuXDxasI03yvZ65mEajJ0Y7GbyOqv4obmYZlMXW6oOU9bTyKbKn7A4bOR1ViIWilgafxnxarchxrbqoyxJuIxM31geTJmC3eVkd20uVqedJwp3cKqjkscKttNtM7Kv8TQZvjGMCUzmsbTpnswUkUD4K8FxoVhy3/sWjrSV0WlzZ3NdWAkTC4RoxPLfNDL5M+jtZm478R4Wp50whS9vDJ2HWiyn3arnnryPabZ0c67XIKPbamRnbQ4nOyqxOP55zyjtFh0FndWe8N9uq5GzukYmhWWwJnsRwQpv5CIJw/0S+GT0HR7nud/CR6bihSGzOdVRycsZc5kdcxHD/BM43HKWO5Ov4qHUa3/XebCffvr51/GnBdOtt97KunXreOGFF8jLyyMvL48XXniBDRs2sGLFin/FMfbTTz//ofxsW3uhCIhU+ZPoFYJIIMSJC5PDSrmuif2NhUwKy2CYfwI9ViNvl33NzKgR/7A96e/hK1UzO+YirosayffNRdQa25EKxbydtdATZrun/iQp2gi2jL6dgdpwnLgo7KpmVK+o+ZlrI7Lxk6pR9TqZAbRZengofysuXAz2iebJ9Fmc1zeztuxb7kuZzAfnD/DSmT2EKrx5MGUKlboWVuRu5JbEidw9YBIDteE0mbup0Lf0cRNqtfTQaOrs4+wlEYh4dvAN+Ms0GBwWNlUdwomLRK8QEr1CQOBCKBSyqzaHt8v2sfL0VoIV3uypO8nuulw+rDxIpm8sUyOyceHivYofCZR78VThLpRiKRvOf49aLCdGHUi6dyQL48YyN2YM0yKGEaLwJkLph8lh7RM0rLOZ2FN3ktlH3qLZ3E2WbxxXhQ5h3tG3CVP6MlAbTrtFx93JV3NO14ifTIOPVMXc2DGMDhiA1eG2PP9ZmJ3oqADcRhp3DLgKvd3Cfac+9rxfg7GTFnM3B5tLWDdsCQ+mTOZURyWlPfVsGL6MeTGX4CVR0GUzcGvuRqZHDidA5kWNsZ1rDrzA5qpDAIwJTKZC38zFQe5ZqqeLd4EA7sv7mEpDCw/mb8bksHFz7rvUmzp4qngnsZogluSsY3ddDiKBkFczbyLLN46HUqYgRMB5fXOf++V4WzkigYivG/M51lbO7SfeZ2LoIIq6a/iy/hTPFO+kw6Ln0bTppGjDceHytE1eHZbJYJ9oms3d3HnyA1YVfsr3zcWk+USyPHcDGyt+ZFet+zgeL9yBXCTlzgFX8V7FjyhEUrzEcq6PHsUQn2giVX7cnTyJDN8YAD6q/IlumxGtRMET6TNZVfgpPlLVn85B0kqVXBc5klcz5/Fq6Zc0mDoRCYSoRDIsTjvLczdQpmv8lXven0UpkvL8kBuJVPnzdtYChvklsHbYEkIU3jyUMoVHTn/C0px1nNc1s6P2OKvL93H3qQ+pNbb//s7/AO0WHc8W72bx8XUcbS+nx2pkU9UhluWsZ0/9SSSCv103uVj6hxZ0xEIRA7Xh3BR7MUEKLVqpkih1APenTCZE4dMvlvrp5/+YPz3DpNVq2bp1K1dccUWf7Xv37uW6666ju7v7N175f0//DFM//fz7YbCbOd1ZTYImBLvTTn5nNSFKHwJkXsiFErbXHGN65LA/lB7uXoGv4s6THyBAwOPpM/i6IZ+rwjIIknkRKNeypfowMepARgUMwE+mpsXczYHmEhI1oSzOWdtnf3KRhHeHLSNWHeh5uOyxGvmqIZ/vm4t4etB1qERS8rtqePnMHl7KmIMAARKhiDClLw3GDo8T1nPFu4lU+aMSScn2T+DB/C24cBGnDqLDqqfTaujNfppLnDoIjVSB1WGnw6rjm8YC3i77xnNcr2fOI1LlT7fVwKrCHbyUeROPnN5KcXddn+O/LmokU8KHUmfs4KuGPJYmjOeukx9Sb+rg6tAMrgrPJKetnPEh6XRajQTJvCjuqSNS5Y/D6UIhkmB12em2Gj1Bw63mHmYdeg293YyfTMPs6NG8VfYNIQpvXhgym0+qj/BZ3Ql8pCqeH3wjR9vKeK/iR6RCMeuHLUUllvFN42lsTgfvV/zoOdYViZczPiSdF4o/51BbKfclX81Qv3gqdM1UGlqIUgWwunwfTw+6zpMn9HzJZzw96DrsLgd3n/qI4X4JLEsYT7Olm5tz3vXse3xwGhm+sTxf8hlhCl9P1tPc6IsZFZjIihPv9RGvPlIVr2TM5a2yrznZUYlMKGb7RXehEcvR2Uz09M5mVRtakQhEpHpHelo8b06YwOjAJO48+aEnz+hnZkaNwFeqdtvQN+Tzef1Jz/97In0GSqGUAdpwni3exZG2MgCECHDiwk+m4dHUaTxf8hlXhg7BiYuN538AYKR/Eg+lTEEsFHnmjWwOOxWGFuYceetv7x85Aj+ZmtXl33p+XhR/KdDXYrvLakAjUfzKZtxkt1Klb8HmcnBL7gYcLhePp88gSK7lgbxNtFv1PJo6jUuD01CK/9xCxy+xOmwYHFZPYLXL5aLV3IPd5WDx8XW0Wnq4KiyD8cFpPJy/lXHBqf+04NdWcw8P5m+moNc4Jc07goKuGgCmRQxjSfy43w0c7qeffv4a/MuCa+VyOdHR0b/aHh0djVT6v/sC7Keffvr5JSqxnGH+CQDccmIjjxVup7izDrVYziMFn7Cx4gdWFX1Kh0X/m/twupy0mnvQ2808WfgpDpeTWHUgKdpwrgwdwrbqozxwegs9dhMBMi8sDhtf1+fRYu4mUK7lsuA03jy7F3DPLO0acw8hCm9iVIG0W3QeS/BGUyf7mgoY6Z/AM4Ouczu21eaQoAnmnayF3HHifRYeW0O31UibRcfTRbtYcGw1VYZmHk2bhtVpp9bYgbdUhUQoIlUbwUsZc1j981yGWI6XVIFCLMXqsHNe18yJjgrW9D7g/sxD+VuoN3bQYzPzSuZNHG09y8rUaX0CflO1EYwNSmHu0XdYWfAJYwIH0m010mnVEyr34ZqIodidDqaEZ+F0uQhX+lJhaOHxgu3ckrsBsVD4/9g77/io6vRtX9Nreu+NNEI6CUXAiihgpSOgghSxIPYOiL0XBGnSVKSDomIvFCGQhIQQ0kN6b5Pp9f1jwmjU3dVd3Xd3f7k+n/ljTiYz3zlnMjn3eZ7nvjE7rNyes4F787ZS2F2L1W7DR6ZmbfZ8Z4uUqZe3Sg9hc9i5Lfpy5EIx14YOxV2ioMusY2HOejb1iaJRfvEoRBLOa1sBXGJJ3He1/q2yQ5zqrOS+wRN5OmUaFdoWnj+7nwSPEK4Py+L54v3U6Tt4MP99LHYbywp30Wjo4tGC7chFUl5Kn8UNYdnU6Ts42lrab3+VahpJ9QrHU6JyiaWLfOOZETWSZM9w7ozvH6L7SNL1vFbyiUssvZp5M24iOd0WHQty1qGzGvGTuSMRiFiRMpWpEcO5NmRo3+dZxmcN+bzxi+Dhi/0TmRw2jDi3QI61lbrE0oVjtrxwN0qxDKlIzGNJNxDvHky40octI+9gpE8cz6ZO54XiA4zyS0AiFPNu5bcEyj0BONZeygvFH+HAQZdJS622nTp9B3eefLffGnbW/kigwpOVKdMAKO6po9di5LHTH7pm2NqNGp47u58yTRM2hx39z1zqFGIpEpGYdyu+5cX0WbyWOYfvms+yvHAXL2fMYUXyVMb4J/7LYglAbzPjJv7JfKrN2Muu2uOsLvuC9cMWcG1IJvFuwbxT/iUvZ852Wd7/nE6TFr3V5LrfYer9h0HB4MyQei5tBsme4Thw9BdLsQNiaYAB/hf5w4LpjjvuYOXKlZhMP33JmEwmnnnmGe68884/dXEDDDDAAOCcn5AIRVzi75wJeaPsU677/kVXu9bE4Azkf2Ogu93Uy46aH7n1x9UsytnAUylTGeYziJczZhGi9GaIZxgSoZDHkm7g/rxtvFPxJf5yD2LcA1hf/jUdpl4sdhv3JI7n7virmBYxkjpdB29n3cbtcVfyyOkPuPvUJhr0Hdx18l1eLP6IffUnseNgReFuVpUd4o2ST7E5HCjFMgIVnnSatdx87G2mRY7k8oAhxLkFc3/ee4zyS0AtkbO58jvWZi9gZeo0QpTeRKv9WZ01j7eG3kq40hexUIRQIMBP7s4rxQexOezOebDsBa72vJfPfYyHVMH7VUcY7hvLgfpTLut2gOKeemp07Yz2S8BX5sYgt0AePv0BQQov3s6ex5sln7EkdzNFPfV4SVV8eP4oMpEYr76g4QUn1rHgxDoMNjO+MjcC5R596xISrvJlTuQYPCVKVmffxu7R99Jq6iGnvYJOYy/P980bOfocA9O9orgsMJnDrSXEu4dwqPE04BRRH1x0t6t1bPv5Y3SYeglR+rCv7iR5XdU8WbiDws4aXs2Yg1wkodnYzZLczXRbdHhIFLyYPovq3hY+PH8MhUjK4bYSl5V8ulcUUqGYWn0HD+d/wFOpU1H2tXhKRWLsdjtV2lY29LmWXeCt0kPMi7kML6mKiSGZVGtbKdc2s7fuJJPDh/Ns0T4eHXI9b2Xdikoi5/Vzn3BrzCVsGn47w3wGEa7yY/v5o/2eM6ejkm6zngiVH183O90gJ4UN4/2L7iLZM5wM7ygMNjM3HX2TDrOWcKUP9yZO5N7crYwPzaDNqCHbZxD5XdXEugUyNiCFLSPv4NGk6wFoNHRislnYUPkN53VtPHN2r6sNb+OwRa4WyKfP7CXDO4oHE6/l+fSbeLRgOyc7K7n95AZqde2sOLOHb1vOcnvOejpNWj5uyHO1ibYYunm38lsClJ50mbXsrzvJjMiLSPYMp8us5WRHBU3G7t8Vvvv3aDf18sLZA66Q2l6LgfO6VrZUf88XzYW8WXqIMJUvr5YcpETTyFdNZ9Bajf1et8nQxYITa/m+pRi91US7UcOygp1sqz78u0STVChhsEdIv21pXpEohAMXjgcY4H+RP9ySd8MNN/D1118jk8lITXU6JBUUFGA2m7n88sv7PXbv3r1/3kr/BAZa8gYY4L+bbrOOdeVfsftnoZBPDpnMZYFJKMWyXz2+y6Tj6aK9HG4759oWqvRmwaArCFJ4keoVQbdZS2FXHa+WHKTD1MvTqdPZUvU9FdpmVqZMI849iDVlX/J5UwErUqZwpLWEL5oLmRicyYzIkSw+uRGNxcBjQ27gRHs5XzafAZyOWT0W54nk8uQpXByQiN5qxmy3crS1lJdLPkYlkvF06nTaTD28WPwxUqGILSPvYM7Rt1kz7DZi3QL7hWL+nF6LAalATElvI6tKD3Fv4kQO1p/ixvDhPHVmN7fHjWV9+Tc8OuR6vmspZm1f9s61IUOp7G3mrKYeIQJeSL+JMk0jN4YNI7+rmiTPMDRmA08V7aa8txmRQEicWxDnNA0EK7x4JnU6S3I3uyy7vaQqNg5bRKdZi7tEQbDCi4KuGgQCAT5SN54o3EGaVyTTIkZisVuxOex811LM+sqfRIinRMXz6TNwOBx4SFWY7VYONZ4m2TOcp4v28kL6TA63ljDSN54nCncwMSSdKHUAz/eZUQBcE5xBvEcIL5/72PW8K1OmkekdRbdZR7OxhzClNz+2l/NqySdMDMngIr8EPCQKp4mDZziTw4fzZsmnNBm7EQmE7Bh1jytU2UuqYv6gy3m95FPMfQGp9ydO5M6T7/JM6nSOtJXwSWM+y4ZMIt07mvvztmLHwcX+g7kqOA2lSEqAwpMes553K791WdlPDMngZEely9Fu84jF9FoM/NB6jsEeIcS7BVOjbydU6cPinA20mjS4SxTcGXcVq8u+oNuiw0eq5s2sWznVUcm5nkaqtM28lDGbIIUXWouRE+3lJHmGIRYIuSd3C20mDcuTp7C+4mtuG3QZ75R9yWPJN/JO2RfMjr6YIR5h2HEgEYr6Wf//nGXJkznX08DO2h9ZMOgKrg/LYumpLSwYdDkRaj9mHXsLo81CoNyT2VFjeK3kE6wOG0keobyWeTMeEiU2h/0Pz0lpLUbeLvucPXUnkAnFrOoLjQbnBYm15V/1e3y6VyRTI0byQvF+3smeT7Q6AJ3FyDlNA0tzt2KyW3g86Qb85B48VeQMLt428k7i3YP/5hp6zHo+OH/EVR2V9eVqCRDwfPpMRvjE/soQ4/fSadIiF0ldVbhusw4BgoHQ2v9xmg3dyIRiV3WyxdDjuig2wF/LX9aS5+npyaRJk5g4cSJhYWGEhYUxceJEbrzxRjw8PPrdBhhggAH+TCx2G9V9LVsXKO1t7Ddf8nNaTD39xBJAvb6TJwt38vzZ/XSatGitJu7P3+bMUBJJkIskdJh7XRbiywt3cajpNA4clGoaCVR4AvBNyxmEAiHPps5ALZbxTNE+hvrEcIn/YACXWLovYSJZ3tFY7XasDhurSz9niGcYr2fezIbhi1CKpeR2VrM8ZQpv9znjvZl1C4PUTrFk/IWzl9ZipNXYw0vFH9Nl1iESCFiWMpkT7WVMCh9Or8XA06nTyO88z/2Dr6HF6MzOCZB7cGNYNtMjR3LroEsZ7BFKpnc0ZruVzVXf8975w2R4RxMg90CIgMWx4xikDsTmsHNO0wDArMjR2B0OTD9zxjPZLPRY9LxU/DELTqx3OtwJBDx7dh+7ap3ubOneUTxTtJdXSz5BKICdtccAyPCKchkyPJy/HU+pmk8b8liauwV/uQcBcg+sdhv3571Hts8gwpQ+LE0Yzxj/wajFcob5DgIgXOnD5UHJbKj4pt++ervscww2CxFqf5I9wxEIhDTou3gj8xbi3IJZXrgTL6matdkLWJrgzHV6NfNmFsWOxeaw83F9LvckTMBbqubtrHn0WoysSJmKWizn3oQJfNl8BjsOHi/cwS0xlzIv+lLiPUIo0TQwKXw44UpfrgpKQwB83lhAo74TtUTOlUGpKERSbo2+hNtjr+S5tJkEyD1I94pEazGyq/Y4VoeNdlMvYqGIku56jrSW8HjyJDwlKjQWA8+e3Ue3RYe7RMHK1GmsKNhNvHsITYYuIlX+rlY+tUTOxQGDCVR44it355WM2fjJ3Fl+Zhe3xFzCayWfEqT0wlfmxpPJkxniEYZUJEYukjjFsnsQb2Te0m+/3hZzGSN841yuc+sqvuKG71+mtLeROn0HnaZenk2d4ar4vXTuI6x92UQrUqbiIVFSrWt1VYj+CGqJnFlRowlWeGGyW5l/Yi3bqn9gW/VhRvsmuKqR8JMpylulh4hQ+uEmVuBwOGgydvPB+aO8mjmHIIUnfnIP3j9/hGXJk3ghbSZhPzOh+S3MdiuHmk4DMDlsOB9f8hApfe15u2uOo/+FuPy9tBudbbo/tpeit5rpNut4r/oIO2t+7Gf2cgGHw0FlbwvNhm7XtkZ9p6utdYD/Dmp17cw7/g5ryr+ky6yjxdDDA3nbeKzgQ9qMmv/fyxugjz8chrBp06a/Yh0DDDDAAH+XNqOGZYU7ye0bnk90D+GcpoEdNccQALfGXIKXtP/swOnO6t94JieV2hZ0ViNioRipUIzZbkVjMbDizG6eTJ7Es0X7aTZ2k991HoCZkaNQiKRsqHSelHtKVfRa9X1X4sVIhFbcJQqXicMFmoxdNBudwu2H1hLujr+K/K5qvKVuPHVmDytSptBs6Kamt40s7xi8ZCr85O6IBEKa9V0cbS/jisBkPKRKGvWdfNKQT6x7IC2Gbmr0bSzN3YpMJObplGm0mnp4vGAHMeoAnkqZyuGWc0jFEiKUvrw7/Ha6TTreLvucvM5qXkibSbjKj121x7E4bHxUf4ppESMRCoTEuAegMsgIVnhRoW0GIN49mBi3AO489S4muwUfmRt2h50us447T73L82kz2VVzHKVYRqemCT+ZO9m+g/CXebC56jtaTT08kHgtZruN64OzaDJ1c3fCeNqMGpbkbiJQ4UGjoZM9dTkYbGZajD2IhUKmR45kW/VhHsp/nw8uupvj7eWEq3zxkqo43l6OAAHPpc/krpObXAJifszlvF3+eV973iY2Dr8drcXgqtCc0zjbEU12K/OOr+GVjDm8cu5zbooaxeqyz4lU+3F/4jUkuAdjtJrZMmIxr5Z8wg1hWXzSkM+u0Usp62liduRoyjSNjA/OoMekY1xwKg/mv0+GdxTDfAaxMHYsb5R+is1h55rQoeyoOcatMZfySUMua7Jvo7rPCVHVN2PlAI60lnBL9CVU9jbjJlFwrL2MUQGD+aQ+l5OdldwVfxUri/a4Pl8PJF5DtDqAFalTCFZ4cf/ga/CTufeb1/l5FedCRtSGym+4P28bAHfEXYm7WIHkN/KRukxaNlb2F6IfNeRydXA6d8Zfhc5m4qvmM652zxi3AEKU3hxvK2d25Jh+lcRlyZORCsRU61pZeGIdRpuF1dm3kege8ocqTSFKb9YNW8B137/ESN84JocPp6q3hUpdC3k/+5u3OGy8eu4gb2fNRSoU4yd3p8us4/ac9fRYDGitBp5NncEThTuo13fSauxhTfZtiAUizDarKy/K4XC6dV6oYvvJ3Xk76zY+a8hncsQwPKUqnkubwQfnjzIzctQ/ZSyht5rYU3ecw23nONJWwoqUKZRrmtjW1z46xDOM4b6xrggDh8NBpbaFhSfW4Sdz5/Wht2B32Lnj5LvorCbWDZtPpNr/D69jgH8vequZo22ltJk07K8/id5mokbbTmlvIyKBkAZD50CV6T+Efzo9rq2tjdLSUgQCAXFxcfj5+f2Z6xpggAEG6IdAIEDa1572dMo0hvnFsqXSWRmRi6QIfqNgrvrZUPgvmR4xEqlQjFosZ27MJZRpmrE5bNTrO7HbHUSp/Wk2drsen+EdxebK71z3LXYbdgc8XbSHHoueZ1Kns6v2uMsNLVrtT5W2lQ/OH8VDokQqEFOlbeHN0kOMD07n5XMf02s1cLjlHMuSJ2PHQZ2uHZVYRpfZaWBR3NPA6a7zaC0Grg5J58H89ynrbWJcYAqPJ99Ih0mLp1RJu6mXRwq2I0RAnHsw0yMv4pYfV/Nc+kykAjEI4NYfV3NH3DhuihyFt1SNu0SBt0zNzdFjkInEjA9OdxksNBu6+bGtjJtjLuZsTx16mxkhAnoseuwOBwFyD1amTMNkt7D8zG4MVhMSoZgHBl+Lv9yD4T6D8JKq+LKpkDEBg5k/6DJajRr21p7g+rBsJoZlIhYK+bzxNBOC03lr6FzaTBqeKNiBwWbm+tAsrgnJQICAsYHJCBEQofbDbLfSoO/k2tCh3HXKefFumO8garXtLIy9gtVlX/BC+k34Sp0hwo8XfMijSTegFEloMnTRazWiEsmYG3MpQoGQp8/sod3US5Oxi2CFFyEKbzylKrZVH2ZCcDrDfAaxKGeDM2AZBxW9zbw19FbeKfuSLN9BvHLuY+bGXMrJjgrG+MfzeVMh53VtnNe1YbJZaDWe4GRnJQDXhA6lrLeZG354GZ3VxJfNhdwdP54Pzx/jUFM+a7MWsKfuBLvqjnOo6TSvZ97C4dZzvF76Ke4SBauGzqPbouPJgp39PscvnfuYtdkLiFYHIBAI/m4rWa/FwKHG0y7RL0CAAwcFXTUoRFIGqQPxkbthslko1TQ6Z+TOHeRERwUAk8OH80lDHq3GHm4/uYH1wxb8yqq7sLuWBPdggpXePF98oN/PHivYzmNJN/LSuY/osRjwkChRi+V/uC2v26xjZ81xRvrGcXngED5rOs0NoVkszFkPONvwMryi2Fj1LV80FxIg92BuzKUAyIUSHkm6gUdOb+d0Vw23Hl8DgFQoZlHsWEp6GvGWqdBajaR6RiIRiqjUtlDS08AlAUmoJc7vlFClNzdFjfqZiPJg/qDLf7M1+B9h7tvf14Rkktd5nvyuap4s/Ok4TwsfQYJHSL+8N6vDRo9Zj8FmoUrXyp0n38XisNLU19rVazVitdv+7r4126xUaVvwlbvj22dbXq1tRS6SEKTw+sPvY4A/jlIsZXxwOlqLkfWVX/NFXz6eSCDk5YzZJLqH/INnGODfxR9uydPpdMydO5egoCDGjBnD6NGjCQ4OZt68eej1vy4ZDzDAAAP8s+gsJlqNPXSatPjK3Hg8eRJrsm5jlH8CHhIlc6LH8ObQW7kpchSev9Hjn+4ViRDBr7bfFnMZarECrcXImZ46Mr1juCo4lauD0nhsyI10mHvxkDif74J18uMFH3Jz33wHQIDcA4PVTKdJi1IkI1Ll5wpxXZownlcy5jAxxGlGkekdzdigFDwlKqq1rajFMl7JmM308BFMj7yItRVf8ejp7fRajTQYOvms8TS3Hl+DUiJltF8CRT11HKg7yQi/OAA+by5kzrG3WXZmJ0/2tWkZbRb0NjP3JIznjZJP6TBruTd3K/X6Du7L3UqrScOrJZ/g3Scm7s9/j7zOKhQiKZPChrGvLofHCz6kUd+FAwdmh40nC3bySuYcdo1aitVhY1v1YV5Kn8VL6bNx4MBdomRlylRWpk7raxlyzhO5SRUuI4n78rayruJr7A47V4Wk89Dp91lWuItWo3MWR2sz8U3zGZ4o2IHeZibLO4YabRtigYj5J9ZxsqOKG8KyiXcL4bWST5gTfTHnehqYFjGS4b6xTAjOoN3US6jCWXVwOBzcl7eNIKUnG4YvIlTpjcFmIa+jiufTZvLm0Fvxk7mzufJ7nkmbzvKUKRxvK+e6sCwMNjMn2ssBONNTx+dNhTw+5EYEAgEeEiX3JkzAXaxAKhLzTtkX3JMwgQ+qjzA5fAS9VhMqsZzJYcMB+KQx3yWWHk26AbPNSm5nFbo+V7Y74q4i1SuCQ02n6bEYWFV+iKE+0UiFYur0Hdx07E1XYG+KZwQeUgVPn9njqqI9mnSDqz3vzpMbXS2gfw+L3eayGr8sYAifXvowiwddiVIs465Tm1hb8RU9Zj25ndUszFnP8sJd3B57JTKBmOXJU7gzbhzvZM9HIZJyZWAKx9vLKdU4r4QneYQC8F71YXQ2M0tyN2Ppa8N7JWM2cpGEJkM3q8oOsTRhAm5iOeuGLSDqD1ZBei0GdteeYGftMe6Kv5pnz+7n88YC2owaxgeluWaWPKRK7o6/mjClD5MihqPqEzoKsZSh3tEsjL2i3/M+mTyJ/fUnWZq3hV6LkTdKPqOg+zxVWmc17KmiPfzQWuwKqgV+JY7+WbGU33WexSc3cn/eNp5Nm94v1y3BPZjbBl3usk+/gEQoJtkznLeG3opYIKJW306ToduVKfePqnZmm5WinjrmHX+HFYW76TD1UqVtYcGJddx18l2a+sKj/0zMNivnehpo72szczgcVPW2/CWv9d+Eh1TJpPBh/TIF49yCGOIR+quw6AH+//GHTR8WLlzIV199xapVq7jooosAOHLkCHfffTdjx45lzZo1f8lC/wwGTB8GGOC/A7PNQo2+nbXlX1HQdR5vqRuzo8cwwjcOb6mq35VWh8PR7/7PMVjNfNtylhVndrvMAa4LHUqIwpujbaVMixjJE4U7EAuEPJUyDblIwmMFH6Kzmng06XqkQjFpXpEsOrmeJkM3YwNTSPEK55VzB3EXK9h20Z2UaZoAeP/8EW6NvgSL3YpCJCVE6Q2AzmriheID6K1mHkq6jvPaVnI6KsnrrGLdsAX0WAzMP7EWm8NOrFsQKZ7h7OkztbgxLJup4SN4rOBDKrUtPDHkRur1na5h8yiVP48kXc+9eVvR9tk7R6n9WZkyjSWnNtFh/slqXS2W82zaDAJkHjx7dh8F3TWIBEIOXvIQHSYts4+twoGDdK8oRvsn8Gafjfo1IZkkuocQrPTidFcN6Z6RPHt2H51mLV5SFUKBELVYxs3RlxCt9se9L58np72CFpOGNeVfADDYI5SK3mbMdithSh/uT7yGRn0npb1N7K8/CcDtsWMJVnojFYjZXnOURbFjMVjNhKl88Jd7cLKjAl+ZO1uqvifGLYBQpTdPndnDjlH38OH5o1waOIRni/bxYsYsNlZ8zRDPcJr0XXSZdVwTmolUKMJit+EtVbv2zeHWc3zUkMuGYQtxkyj4orEAX7kboQofgpVeVGtbyeuqJs0rklpdOyN84/CUOoXK8sKdzI25lDCVLwcbcknzimKQWwDTj7zhOh6xbkG8nDGLp8/sdQkogGkRI5kXcyntxl4WnVyPxmIgwzuKKeHDeeT0dtfjsr1jmBE5ivfPH+bm6ItZcWY3z6RO5/3zR5gdNYZHT29nRcoU/OUe+MrcUIplGK1mGgyd+Mrc8PjFiXaNro3t548yf9Dl+MjcaNR3saf2BNvO/+A6TqWaRqfzolswL2XMQgC4SRQoxTJsDjstxh6ECHiycAdnuut4I/MW4t2DeKv0EB815PJqxhzMditry7/ijaG34Ct1o1hTz+MFO3gk6XpeKTlIj1nHhmGLiFD/se4Uu8NOZW8LC3PWszh2LCFKH+7N24rd4eDhpOtwlyh5o/RTVg2di1efgcgvQ18b9V3ceWoj9fpO17Y0rwjmD7qCUx2VBMg9eb54PyKBELFAiMluxUuqYm32n9/mZrFbOdtdz52n3mX+oMtpNfSwq+646+cCBDybNp0RvvG/acfeZOji5mOr6bY4nf38Ze5sHL6IgL5Zy7+Fzmrih5Zilp3ZBTiFWZOhy1X5eyf7NmLcAv+092m2WTnTXctdpzaR4RXJitSp9Jj1LMxZh7tEyaqsuf9nq1oXZpZKehv7bb8+NIvbY8cO2NT/xfxebfCHBZOvry+7d+/mkksu6bf922+/ZerUqbS1tf1TC/53MCCYBhjgv4Mz3bUsOLEO2y/sh8cHpbM0ccIfcozSW020GHv4vPE0TcZuLg9IJlzlw+MFO7gjbhwvFn9Eg6ETsUCESCB0zudI1bycMZswpS/uUgU1ujZ21vxIqlcEr5z7mDF+g5kbcykaq4HXzn2C3mbiqqA0hvnGsrvmRzrMWm4bdBlvl33O9IiLuDdvKzaHnRh1AMEKLw63lQCwKHYsVwQMoVLbyqMF2/u930sDkrgjbhwbK77hi+ZCHku6gXSvKN4s+4xvW84SrvJlacIElhXuRGMx4C5RIERIt0XHGL9Ergsbyn19MyoADyRey3DfWJ4/u5/7Bk/k+aL9XBeWxaUBTqv2o22lPF6wwyUsAYZ6R3Nj2DCWFe7EXargnaz5WB1OE4YLeUXOAODJdBi1KMVSRvolYLKZef/8YSaFDePrliI2V33ves5QpTdPpUzlgbz3eC5tJsfby51ZWilTsNhtrCzaS4pnOEsSxmOwmrk3byu+MjdWZ81DIZJysCGPt8oO9TvGIQpvHhx8LSvO7OaehPFcGZRCq1HDzppjfNNylocGX8fyM7sQCYSu9r/XSz6l0dDJ06nTOdlewWDPMF4sPuCsQEndqNK18mThTh4cfC2J7iEszdtKra6d22Iu54awociEEg425GK120nyDEOIAB+5Gy8Wf0ROXwvbBSaFDSNY6cVbpYeIdw+mVOM8MZoeMZLpEU6nxUZDF9MiRuIlUfJOxU9Ob2FKH17PvIUWYzcJ7sFY+z4jBV01ZHhFYXHY+LG9jBVndrMiZQqj/RI52VnJw/kfMDtqDLOiRvULnQVnlcZNonDdbzNq2FeX42rVA+cV7lcz5+Av/9sGTm1GDS3GbuLcgpGKxHSZtFTr2ohzC8JstwACvKQqanRt6KwmFGIpKwp3U6NrQ28z4y11ZnaFqnxo0HeiFstd8z8N+k4kQtFvvr7dYafZ0INCLEUpkvFe9Q8uF0gBAraOvONvtia2GzUsyFlHvb4TqVDMNSGZ7K3LwYGDNK8Ink6djsPhYGFOn4EJoBBJ2Trijn8o7tqNGjrMWqLVAUiEIrrNOhoNXUSofP9ue7DFbqNW18Y3LWdZ32dhf2VgCi3GHgq6axAgYHXWPDK8o/pdHPq58BMJhDgcDuw4iFb58/rQW1wGNX8LndXIdy3FrDiz27XNQ6LghfRZHKzPZXHclb8rEPz3oLeaONxawhOFOwCIdwumydiFxmLAU6L6PztzZbCa2Vz1HZuqvkMkEPJC+k2U9DS4/hZXZc0l22fQ/+dV/m/zl7nk6fV6AgICfrXd399/oCVvgAEG+JfpMmt5/uyBX4klgE+b8mkz/THXIKVYRpTan0VxV7IiZSpjAhKJVPvzQvpNvFT8EQ8lXYevzA2rw4bJbkEtlvPOsPlEqvxxlzpPKiNUfiyKHUuGVxTbRt7F/YOvIUjpRZTKj1tiLmF8cAbXhGYSpfbjxvBh+Ms98JAo8ZO5823zWV7JmI1IIKRS2+ISSzMjR2G121hX8Q1JnqH9/imKBEIWxY6ly6xDKZLy2JAb8JKqeaP0U75tOQtAglswVrsNk82Kp0TFm5m38s6w+dwRO44pEcN5pmhfv/2wpvwL6vTtdJl1vFx8kBWpUxnq5XTJczgcpHiGM8ov3vV4IQIeSrqOZmM3oUoftBYjTcZuBAhI94rs99xqsZxLAwYz1Dsam8PGqyUHuTFsOBsqvvnViWuo0ge1WMGdcVcTIPdALBDydtZckjzCEAqECBBQ2F3LisJd3Ju3FbPdilggRCAQoLEYXGLp0oAk3hx6KzKhmAZDJwfqT3HboMt4ofgAFb0tKIUyrgpOY4hHGDaHHbPNSruplztPbuSl4o+o0rZgsduQCERcGzqU9RVfobOauOPkRo60lfB4wQ40FgOvlXyK0WalVteORCAi1SscpUiGu1TJFUEpNBq7MNuteEpVHGoscImlexMnMilsGAB76k7gK3PjrcxbWTV0LrMiR7uO84/tZTQaupgSNhwvqcolluLcglzteUtzNxOi9EYtUeApVeEpVTHaPwE3qQIHDj5ryAdgWeEuVhbt4eH8D3Dg4HRXtUtg/ZyfiyUAd4mCwX0tdReIVPshEYjpMevR/Syc1tDn3gZO84MhnuHYsNNp0uIlU5PhHUW7ScO842tpMfZgsdtwAM8U7eNsdz0rU6eyfvgi3MRyei0G9FYT5Zom5hxbxRuln9Jl1lGv72BRznoezv+AVmPPr9YvFAgJVnrhIVFQo2t15WqBM9trZeFuWgy//j1wtrKND85wta7dFX8Vz6bNQIiASWHDUYnk9FqNLtt8cLritRh7XC23v0W7UcNTRXuY++Mairpr6THr2VT5Hbf8uJrvWor77cNfIhIIECAg2TOcYIUXE0MyyPYZxPKUKaR5RZLtE0OEyrefWDLbrJztqaNe34lMKGZt9nzezpqHWCCiWtdGRW8ztn/gQCgRiolWB7jajgECFV70Wgx80VxIQXfNP3yO34tSLGO0fwJPpUwFnO6mmr5q1tr/o2IJnC2iUyNGMDYwhZczZjPMZxDTIkYyP+ZyliZMGJhh+g/iD1eYLr/8cnx8fNi6dStyufOKicFg4Oabb6azs5OvvvrqHzzD/z8GKkwDDPDnUa1tRSgQEKFyXnVtNnTTadYS5xb0h4e4f06trp3Jh1/9mz9/J+s24t2DXTMJOosRi8P2q6vofw+D1czxjnLWl3/N4rgreaJgBzqbc7ZEKhSz5nc4d3WbdajFcuwOOya7FbvDgVQoRiYSo7UYcZcq6TJp0dlMKEUyluZucdlzy0USdo5aylNn9vD4kBv4oqmQ1X2taxeIcwvi9tgrUYglCBFQo2vnWHsZ37ac5e74q7k8YAgnOsrxkqrxkCjxl3uwtvxLFsReweKTG2gydKMWy1kSfzXvVHxFh8k5l7Vu2AK6zDrCFN7sqz+JxW7jyqAUTnfV8NK5j/qtId0rksVx4zBazawu/4KHk67jWFsZoSofPqnPo6y3iU6zFolAxJtDbyVS5ctL5w6iseiZHTUavc3CssKdmO1WV1YNwLjAFG6JuQSbw4FCKEFvM1PS24jDYcdit/dbR6jSm9cybyZC5Uetto3jHRXkdlaxJP5q3io9xJVBKbx//ggPJ13Pg/nvU6/vwFOi4oOL7mL+iXUsSbianPYKrg5J566T77osn0UCIa9lzkFnMREg90QhlnJv3haafmbR7CNVsyxlMi+c/YhGQxers+aR0PfZ67UYeKf8S3bVHsdDomTLiDuo1rbwQc1RLg9IRiGS0GXRUafrQCQQMjl8GGqxHF+5O91mHVXaVjwlyr5WSNg4bKEz+6toLxf5xbMk/mq6zDruOrWJCKUvr2bO+ZttVu1GDcsLd5Hzs5a/FM9wnkubgd/fqRCB0xY+t7OK+/K2YXPYkYskLiv760KHcnVwOs2Gbi4OSMThgJMdlZztqWNW1Gg8pSqMNjMai4FtVT8wK2oMMpGIBn0XXzQVcqD+JM+lzeTN0s+o1LaQ7BHOyxmzAOixGNBZjQTIPSjrbeae3M0AjPSNp0LbTGtfLtXG4YsY9Ddaw9pNvUw5/Co6qwkfmRs3R13sciV0vtZsvGS//l7QWPRoLSb85W6IhWIMVjM9Fj1uYgVNxi4WnlhHr9WIp0SFSiyjweCs4Lw59BZSPSNd7nk2h90lNpoN3dx56l2XsE7xiiC3L1h7VuQo5kRf/JvfUT9vMZSJJDybOp0yTROvlBxkkDqAlzJmIxOKf7PSo7UY+baliAiVH4M9QrA7nNX5TrOWi/zi/+FMVZW2hYUn1tNj0SMSCF0XqTK9o7kr/irClD6/Etf/Cg6Hg/O6NmYefdP1WgnuIbyWOedXbZP/S9TrO5ALJa5j2GLoxo6jXwtil9k5C3thZqnHrEeIADfpn7f/B/ht/rIK0+uvv86xY8cIDQ3l8ssv54orriAsLIxjx47xxhtv/EuLHmCAAf47qNa2svDEehadWE+Nro1mQzdLTm1m4Yl1/1S2ys8R9l1t/S2WxF/Nty1n+bqlCJ3FiM5i5NuWsxyoO0m3SdfvsZa/sQajzUJORwXvlH3J4rgrebJwJzqbCS+pCn+5B2a7lcU5G/7u++gw9fJaySeU9TYhEoqwOxzsrPmRnI4KDFYz7n0tg14yNUqRlNVln7vE0oU13Je7leXJk+k0a11i6ZKAJJ5NnYFIIKSst4mvW87gLlESpvTFjoNJ4cPYMGwhGouBu3I3obeaCVJ4IhDAD63FfNZ0muWFu3h8yI34yNx4NXMOBpuZZcmT8Jd7cG/iBAxWM5EKXyq0zfjJ3RnlH4/BZnaJlGE+g3gw8VoECMjvOs/+uhzO69pYmjiBUx1VrK34ihWFu1kYO5Y3h95CtDoAi8NGcU89JruVSWHZdJv1Trvc1hLXzNIHF93N4tgrAfixoxyNxUCDvhOzw8aS3M08U7QXpUhGiLL/HIObWOFyR5SLpQz3jWV6xEgsdhsLY6/AV+bOiuSpBMg8eD3zZoIUnjybNp29dTk0GDp5omAno/0Tsdht/Vo55SIJfjIP3iz7jAfyt5HbUcnShAn9XvvWmEs42JBHg6ETD4kSo82MqE9E2x0OrgnJdAUUH6zPRW8zc0NoNtFqf8LVvriJFYQovbgmJJPC7lpaTRpMNgtCBOitTkOTVzJm81LGLL5oKqBG186qoXNZOMj5voZ4hrM2e/7fFUvgrPCNC07rt21sUMrfbQO7QK/FwMf1ua6Zpf1j7mdu9CUAHGkrRYiAl4o/4pvmIn5oPcfDpz9ga/UPfNNchNlupV7fyZxjb5PgEcK+uhN0m/UsP7Mbd4mC60OzWZK7mUptC0nuoSxJuJrJh1/lREcFNocdN4mCW46voUHfwasZswE41l7qEkvvZN/2d00hZEIxi2OvxEfmxtrs+dwYls1rmTejEsm4N3ECbpLffv/uEiXBSi/EfZ8rhVhKoMITlUSGWCBELBThJVWxbtgC3smeT0xfFUYmlCDs+2rSWYwcby935eR4S9W8nD6LcJUvFoftd4klcFaKqrVtzpk3hwMfmRvx7sF91cVOeiz6vykm1BI5lwUmM9gjxBmPIHIaQVzkl/APxZLWYuSb5rP0WPR49M0QLU0YD0Bhl7MN8M8WS9XaVhb0zWtecOQs0TTwZMFOlxHE/xq1unbmn1jHk4XO99hi6Oa+vG3ccXIjjfqfzC68pOp+Bg8eUuWAWPoP4w/biicnJ1NeXs57771HSUkJDoeD6dOnc9NNN6FQDBzcAQb4X8fhcGC127A6bHRbjCw4sQ6FSEqjocuVX2L/Y4XrfnhKVIzwjeVYe1m/7VcGpSASiNhR+yPgPGEVCgRsP3+UO+LGUa5tIkUUgUwsoVHfSYW2haHe0b86cbgwFyEVipH0nTD5yNxYkTwFgUDAs0X7aDf1/s31aS0GNlZ+y2eNp/m25SzvZM/ncGsJGyu/QYiAd4ffTqx7EBKhiC6TlrLeZj5qyAVgwaArSHAP5oH89yjXNrO77gSTw4ZxR9w4KnqbmBtzGQWdNTyXNsN5xT5yNE2GbiJVflwakMQ5TQNnuuvQ20z4SJ3tTwcb8ghX+uEjc2OUXzxH2kpZW/4Vq4bORWPWs7HyW1RiGS+lz2Jt+ZeIhSLmRl9KmMqPzxpPs6PmR5YnT2ZW5GjKepuYFD6MaFUAK1KmsLHyW64KTnO1p12Ybxrjn4jDYSdQ7s1bQ2+loreZ89pWZEIJoUofXki/iSmHX+WF9Jtwkyi4PHAIZ7prGe2XgFwkIUrtzwvFB6jRtSMTitHbzFzkG4+XTM3S3C0AuInlaK0mzmkaWF64m2XJk1lWuBM/uRvTIy6iqKeWH9vLqdW281z6DLRWA+EqX7aMuAOzzZmJVdRdy9meeuw4eLH4I5oM3QgRIBII0VlN3HXqXV7OmM2asi8IVnr3s3IGWFX2OStTpqEQShkblILBZiavo4pMn2hajT20GHt4e+hc7jj1LkO8wmjQd5LtMwi5SMJD+R/gJ3fjzriryOs6z3Nn9xEg9+Cd7Pk0Grp4MP99pEIRL6bP4rPGPD5rPA3AaL9EghReLvvqJM+wfmuy2G1Iflb5NFhMnOmp5emivcBPVuGvnDuIh0TJGP/Ev3vy3GLsYbR/IgEKD8YFpdFi6OGywGTEQjGj/RP6XO9MPF20j7vjr+LSgCQ6TL2M9k9EYzHw+rlP6DLrMNosXBY4hCcKd1Kja0NrMTIjciQ5HRVUaJt5IOlaXj13kF6rkRVndrMw9gp2156g1djDqrLP2TlqqbNNr691Lc4tiCCFV792sV/iJlFwVXAalwUm49M3+5TuFcm+i+//p+zKASLV/qzNng8IiOybWXot8+a+6nkgYqGzgvxd61meOrOHNK9InkubQY2unereFmLVgdTq2l3PN9Iv/u8KV7lYyij/eJ5NnUGseyDhKl+CFF6syprrDA52C/qbpjYAql8cW6lIzK+tIX6NWiJncvgwwEGmdzTPnt1Pimc4SxMm4Ctz43RXNYEKz1+58/2z6Kwmvmstpsc1s7TAKZYKd3K66zwdZu2fNi/1n4LJZqGit5kOUy8dpl4eOb3d2YKqbUYkENJo6CRA4fF3P+MD/Ofwh1ryLBYL8fHxHDx4kMGDB/+V6/pLGGjJG2CAPweHw5lJc1/eVmZFjeGd8i8x2My8PXQu0eoAPH+jDeaPUKtrZ8GJdXT+zOVNLBDx7vBFvFP+pUtMhSl9uC9xIo8X7MBit/J21jz85O4sztlIg6GTZ1KnM8ovAcUv3KVsDjvV2la8JEo6zTqkIglSoQgcYMdBt1lPvPvfbi2s13dwe84GWn4xX3F1UBrJXuEMUgcSovTm/rxtpHhFECT3RG8zc11IJt+3nkMplvFDazF3x4+nvLeRKFUAepsJi8PGpopvuSv+KiRCMd1mHavKPufp1Gk0GLq4PWcDVoeNxXFXMsI3jjtObkRjMTA7agzXhQ7FTaJg5tE3sditvJwxmwfy3uu7gqxgtH8iBxvyAJgSPpwJwenM67vaG60OYOGgK7A57Cwr3MmEkAymR4zAQ6LCYDMz+fCr2PvEUrpnJE+mTEYlltNm7GFhznruSRjPRb7xGO0W7jz5LsN9YwlRerOq9BCzo8fwSUMeTwyZRLJnOAIB6C0m5uescw3Vy4RiNo9YzLctxayr+IpwpQ8vZcymVNPIssJduEvkrMqa57JHv8R/MEKBgG/65rmeHDKJHrOeSwOTEAlELM3dQrOxm7ez5rH9/BEuDkji8YIPAXg+bSYigdDVhvlY0g1keEex+ORGWow9eEvVrEydxtNFe2gydOMhUbBj1FLmHFuFn9ydJ4dMwgEszFlPr8XAU6lT8Zd58MzZfdTo2pgXcynjgtJQiqV82VTIhOBMGo2d3J6zAYPNjJtYjt5m7tvv/twTP57HCj6k12pktF8CK1KmusTSLzHYzOR3VhOm9MVNLMeOgyZDN11mLRsqv0EsEPJi+iyeLNhBTmclQQpPtgxfjL4vdPVClaPR0IVUKMZNLKdO18Hx9lK6LQb21J3AYrPxWuYcynqb2Fd3kkeH3MDKM7uZGTmasz11ZHhHMcInFrlYyldNZ0j0CKFG186RthJqdG3MH3Q5Rd11eEiUfHD+CI8n38gzRftwOBy8OfRWHi/Y4QpDBqehwuqseayv+PpXF0muDk5jSfz4fyoI9q9EbzXzY3spj57+EAcOwpQ+TA4bRpWulQP1pwBcLW4SgYhVWXMZ4hneT+j+EpPN0q/CYLFbESD4l9qb/xEWu5XcjmpeKTlIja6NO+LG4St142BjHrmdVaxMmcoVgcmuquq/So9Zx566HC4NSCJK7Y/eauKH1nMEyj1J8gz7u/vnvxWd1cSRn5ldgPOz8WrGHDK8owZsw/8D+Eta8iQSCSaT6e9e7RhggAH+9xEIBLhLlDw25EZOd53nqRRnS1SAwpNVZYeo0f1rbpnhKl82j1jMw4OvY5RfApPDhrFlxGJClT4sS5lMoNwTAK3ViEQoxlOqxGS3svjkRm79cQ0NBucgdIDc4zf/CYsEQga5BeIjd2eQWyARfVd1g5RehCi9+1pc/vY/71ClD+uHLeyX8TTUO5rLA4fwUvHH3HFyI7edeIdzmgYKu2rI9hnEjWFZeMvdGOIZxvctZ8n2GcTq0s/pNuuZeuQ1jrSV4iVRMXfQZdydu5nV5V9gsJlZmTqNFkM3jYZOsn1iAFhd9gVzjr2NxmLgioAhTAkfDg4HnzTk0WHqpddipKK3meG+sXhIFLyUPptIlR8LBl2BWCAi1SuSbrOOF9NvQiQQUqVt4aHT7/NowXZG+ycyLWIEnWYdFdpmvm8tdoklgEpdC0abGRwONlV9h9Zq5Omiveyrz+HOk+/SYOjkYEMuqV4R3B43lmNtpbSberk3byvtJg2qPsFgsP2UZ2N12KnUtpDoEcJ9CRN5Pv0mdtccZ6h3DM+nzWRN1nyUQinXhg4F4LvWYpdYuiX6YgQISPIMo9dq5Kkzu6nQNmOwmWk0dNJu6uWzxnweG3IDy5In4y6R81XTGZ5Kncp9CRMJVnjx6OntPDT4OsKUPixLnkxRVx1vZN7alyE0hxpdG22mXs721PPs2f20mTSEKr2x4+DJgp08kP8eNbo2JAIRQ71j2FPzIzqriVSvCAw2E9Fqf97Jno9YIKLXasTmsBOm9OGplKn4ytyIVjuNlJzGFnqXqQLgMhow2izkdlRxb+5Wbs9ZT52+g/LeJhaf3MBjBR+yOPZK7o67CqvDzvKUKUwIzuCd7AU0GbuZcfRNtlb9gMaip07XwYLja3m2aC+thm6ajd2EKH1Qi+UYrGYeGHwNjYYuLglIYlxQCue1rQzzjaXHoufTxnyeLdpHXlc1nzbm81zxft4u+5wIlS9fNhVSomlkfcXX2Bx2Xi/9lFaThu9airkpcjStJg0ri/bwZPKkfn9LN0WOos2o4Vh7GQqRlC0j7uDOuHEAfNlYiNZqpKi7DkNf/pHGbOBMVy2dJi11ug521x5nffnXzirF36kM/5koxVJG+MbzTOo0ALrMOoZ4hfNd32fypshRfHzxQ672vO3nj6K1/G3TB+BXJ84SofgvFUsXXiPWLZBwpQ9L4q/mxrBsLvKPZ4hnGBOCM8jyGfSniSUAD6mKqREjXG2WIoGQMf6JJHmGIhGKMPXNzv0voRLLyPSO6lepC1J4Eu8eNCCW/sv4w6YPzz//PCUlJWzYsAGx+A939P1/ZaDCNMAAfw7Nhm6aDd28WPwRFdpmBqkDeTp1Gq+Xfsrx9nJ8pGrev+juP+XKsMVuRSQQIhQIXTNLTxXtcf3cW6rmzaG3cn/eNpqN3YDzH/Ha7PkM9gj9S046esx6tp8/yrtV37q2yUUS3s6ax9bK7/m+7RwA8e7BPJB4LVXaFq4ITEYtkdNk6KLZ0M3CnPU8PPg6jndUuE60rg5KZbhfHAFyT9aUf8GyIZMp7qknwSOEs111hKi8OdxSwpbzTpvukb5xTI0YwbG2MmLdg3imry1rlF88NrudMQGDiXELQG81sav2OOFKX8aHpHOqvZJB7oG0GHv4ruUsR9pKAWc7145RSzjRXo6f3INmQ7crPDXDK4oqbasrOHVt9gIUIikvFB/gx59VBmRCMU+nTkcAJLqHUKVr5c3SzxjqE8PMiIsw2iwsyllPh1mLSizDXaKgydCNWCDi1YzZhCp9qNW1E6X2x2AzY7bbUIgk6KxGvGVuLMxZ5zJm8Jd78EbmzciEEj5rPM3e+hyWJU/ixeKPWRx7JQcbcjnRUcG9iRM5111Pq0lDQVcNG4cvZFvVEWZGXcStP67GjoNrgzKYF3s5d558lzpDBwsHXcH1YVl4SJS0m3op7qnnkdPbceBAIZLySsZs3ij5jNKfZadsHXkHhV21RKh88Ze5s6rsc64KTkMllqEWy1lwYp1LfPrJ3PuqQR/ycNL1NBm6EQmFPF20l2XJkxnjn0inWUuZponhvrHIRBLKNU0sylmP3mbGQ6LEZLdgtFnwl3vwUvosHivYztVB6cyKGo3VYcPhcLCt+jBbqp2fl3FBqeR3VtNq0uAuVrB5xGKeKNzJ2Z46lsRfTYJHCLtqjnOkrYSNw2+nVtfG4wU7kIskvJR+E6vLv6S4p971fj0kSl7OmM3njadJ9AjlmaK9/cT1pQFJLIm/mnp9J6vLv+DBwdfyYP77/ZzvLlxtP69tJdU7knj3YHQWEwfqTzLcN473zv/AocYCnkubQZZPDPvqclhV9jnzYi5FgKCfFXqyZxjPpc38u1bofxZmq4UmYzezf1yF0WYh2T2M+5Ou4XBrCVMjRuApVdFk6GJb1WHmDroU3/9gU4MOU6+z4tg3s9Rt1mF3OP7Syl63WccXTQVcHJBEgNwDndXIj23lxLkHEa7y/cte99/NhZmlst6mftuHekc7L5j8j7Uh/jfyl5k+nDhxgr179xIeHs64ceO48cYb+90GGGCA/23sDrvzRKD6B2ZFjUYkEFKhbWb60Tc43l4OwMLYsa5B/X8ViVCMUCDEareR01HpEkvZPoMY1mfF/VtXlu046DD2cuGaUK/FQLOhG/O/eBWz12Jgb90Jl1i61N/5D99os3DHyY1MixxJqNKbsYHJLIkfz/66HLZWf8/JjgqaDV3ktFeS33UegJfOfcxovwQu9k9EJBCS7RvLV01nXBUPOw6qda3MPPomgUpPfGRuRKj9WDZkMkIELEkYz+MFOzjUdJpAuQdRKn8uCUji0oAhXB+WzdG2EtaVf4W3VE1+ZzXba45y18lN7K8/SYjCmw6T1iWWwGnJ/Ojp7Yz0i+eHlmKClV5IhWIuDxjCzMiLeCZtGp4SFcEKb7rNOpYV7uSBwdf02z/jglJJdA+h26KnWt9GjDqAp1OnM8QjjLM99dgcdmwOh9O+PXs+a7JuI0rlj6NvQkpj1qOWKDDZLVgddqwOG1XaVmr07awq+7yfi12rsYeNFd/QZdbxbtW3dJh6+bq5iElh2cS5B9Fg6OSVjDlcHjCEW2MuoV7fweK4K1GKZdydcBXNhm6uCR3KVYGpLEoYxzlNAyvTphGk8OKq4DQONuTRZuxFazUSofLFV+ZGqNKb9cMWIBGIMfQ5KwKMDUyhTNPEy+c+5pHT2zHaLVwZlMqywl3cl7eNDlMvgz1CCZR7IhdJaDNpeOj0+zyQdC3PFO3lvK6Np4v2YnPY+eD8UXotBm7P2cDDpz+gqLuOLpOOWPcg3smej0wopseix2hzZoY9PuQGHsh/j2TPcCaFD0MhluImUeAuVXJT1CimRYwE4POmAlpNGpQiKauy5iITSXDrm695o/Qznju7nx9az7EiZSrry79CJZYRpvQmRh2AyW7l2dTpeEh+Ms5YljyZNeVfsLvuBEKBgJG/sKV/cPC1PFbwIU8V7eG5tBm8cPaAy9Dh6dTpxKoDsTns3J+3jbHBqcS7ByMSCHGXKrguNAt3iYJGfRcOHDxyejsP5b/PqrLPAajStv5KhJzprmPH+WN/0/DlH/5tmw39qnsmm4VOk/ZXjzNbLVTqWnit5BNWpkwjzi2Q22IvZ3ftCS4LHILN7nSAC1J4sTj+yv9osQTOGc6fGzx4SlV/qVjqMet5r/owL587yP2522g3OiuRjxZsZ1HOehr0HX/Za/87MdusHGkrcZoDCYS8nnkzK/ps1U91VlHUU/en2bYP8Nfzh89oPD09mTRp0j9+4AADDPA/iVAgJMkj1HkVVazi2dQZPHT6fdfPF8WOZWxQ8u9y6PojiIUiEj1CiFL5E6jw5IkhkxAAdfoOVpzZTbOxG6lQjFosp9Os5a6T7/JU6jQMdgt+cne+aCrk5XMf80bmLaR5RSDta4ew2W1/qO1EKZYx0jeeLVXfMy44jdtjx6K1Glmcs5EAuQe9FiPjAlOJcgsgQO5Opk80k8KH0W7qRWc1YbZbeKf8S8BZgfm0IY8ZUaOo1LYQpPDidNd5eq1G7jz5Llk+0XzeVAg4T3aTPcN5qmg3CwddwXNpM1lxxmmG8GThTh4r+JCnU6fTauxhddnnvJo5h3sSJmCwmVl4Yh1Wh51XM+bwWWM+Fb0tdFv0rOlz57ssYAhXBafyyOntVGhb2FDxDdMjL6LD1MvbfYGxc4+vIVDuwXNpM3Dg4JmivTww+FruOrmp3/75qCGXRI9QvKQq3MVKynubONiQz1CfaGLUAXhIlLyTPR+DzcT68q9ZmjCelzNm0WDoIr+zmmh1ADKhiC6zlnUVX7E4bhw2hx2TzcoXTQUAzIkag1AgYHPV93zVUkSGdzTTI0ZSr+8k1TOCZ87u46umM7yWcQtyoYQnCnYwISSdd4ctwuZwUNLrHDZ/LeNmFsdeSbdFxwtFB8jyjcFqt7F1xGK+aCrkWFspg9QBPF98gGXJk4lxC2BW5Gi6zXpeOvcxtfoOJAIRfnJ3FCIpfjJ3fKRqOsxa5vcFL1+YVZKJJAiAVzPnuMS1xW5FiBA7uLKE4t2CWDjochaccOYYjQtMQWs1cvepTbw+9GaXsPwlKpGUexMm/irU2VOqYmbkRaR7RXJO08CWqu/J8I7GW6ZGKHBmbT1TtJdTnVXU6tpRiqQEK7w4r29jeeFuVmfPQyWScbS9lDJNEz2Wn/IWXzl3kOfTZ/JDyzk0FgNH+jLGwHnB4t68rTyVPJUH8t/DbrfzTOp0njm7l5siRxMo9+CVzDncn/ceC2MvRyWW9Rt+d5cqcEfBs2kzeOT0BxR213Kqz3lubGAK2T4xPHd2/6/2w566E0yLHPmHq0y9FgOfNObRYdYyK3I0cpGE3M4q9ted5MHB1/arBGhtJu4+tZkeix6NxcBzaTexNHcztfoOCrprWJN1m+ux6j/5e/B/AblIQqZ3NO+fP0JpbyMzj75Ft8UpVAe5BSIT/m+0qklFYq4ITKHd1EuKZwQZ3lFYHXZWpkyjx6In0zv6T215HOCv5Q+35P03M9CSN8AAfx5mm4Uei4Hnzu7vd6IUqw78hzbI/wothm5EAhG+cudV27K+NqVfmj40Grq4P/EairvrkIkl7K3LAZzi4IHEa/CRu9Fq7KGou5Zsn9hfDdpfCDo12swoRFJ8ZG798lfajRqkIomrN71R30mdroPcrmoUIglryr9kXFAq44PT6TD18nTRXgZ7hPJw0vXcdvwdRvjG8kjSDdTq29lS9T13xI3js8Z80ryjeLJgh8stDJwniCP94njqjLO69uDgaxnhG8umqu+wOxwkeoTwYvFHSIViLHYbz6ROJ1Lth8Vm5WxPPW+UfsYrGbPZUvU9k8KH8XXzGebGXMaxtlIKu2sY4z+YJkMnYSpfdtb8yKLYsQQrvHm95FNmRY3i04Z8Lgscwr15W/GRqtFajdw/+Bq+ajrDsfYyZEIxr2TM4f3zR/ixvQwBAj4ctYQvmwrpNGsZH5LBntrjJHuE831rMStTpnHXyXcp1TYxzGcQ98SP55mz+yjqqWO4byyX+A/mpXMfY3PYGRuYwtyYS5AJnfs0ROlFiMKHBPdgvm8tplrbytXBadgdDoZ4htFq7OHJwp3cP/hafGVu1OucgvqpVOe8kEwo4ZHT26nWtSITinkqZSo2hwObw843zUU8NPhamo09nOmpZZRfAredWEuHqZdghRcPDb6W10o+5d7ECTxTtI9Ok5aXM2YTpfbnVEclSrGMEIU3C3PWufKeghVePJ82E43FgEosY0nuZrK9YrgpejRKsYxSTWM/d77lyZP5vKmQH9vLUIvl7Bh1Dzf88DLRan8Wxo7l0dPbMdjMeEpUGO1mZ0uezJ3Hk2+kpKeBa0OHIhAIkQvFCAQCOk1arA47zxTtJcUrAgHOikJFbzMmm4WZkaPYWvUDX7Wcca3hkaTryfSOplrbSpZPDEKBkC+bClnZV90d5RdPp1lHcU89I3ziWBx/JbOPrXL9fV0WkMSThTux47RevyPuSuQiKcfay4hW+eMrc0MpliEWiug0aVGIpShEv+3tpjEbeO/8YTZXfefa9vDg6zjdVcOhptO/+TsHLn6gX8bN7yG3s4rbczYAMCfqYlI8w3no9PvYHHZuihzF7KgxeMvUdJt1FHXXYrJbXaYPF5AKxbyReQspXhH/kwYGfyYmm4VTnVUuV0xwtv0+nTb9P74i90fpMeuRiySumSWd1YS9z1Z/gP///GUteZdddhnd3d2/+YKXXXbZH326AQYY4L8UrdXYTyxdFjAEkUBIubaZe3O3uvJJ/mwCFJ4usQQQ6xbI2mELWJ19G4M9QglSePF21lxeSJtJlbaFT5ryXWJppG8clwQMplLbTLtRw0P57/Pw6e0cajqN1mJwPWe7qZe3yz5n2pHXmX70DaYdfZ0NFV+7Wv+6TFq21xzD0hfE2mXW8WljPv4KD8YGJiPsu1L+eVOB0+Wub7bD5rCjsxp5KWM2dyeMxyGAb5rPcGVwKrOPrSLGLQAfqZoRvnH93vOUiOFsqvwWBw7uS5yIl1SJAAELYy5nUvgw1pQ5K0VmuxUHDt4o/ZQOk5YghRcRaj82DV/ED63nONlZyaOnt3NxwGB21x4n3j2Ya0OH8kzRXjZUfsuhxgJuj72SYIU3b5R+yuG2czx6ejsTQzOd2TUKL1pNGvQ2M5sqv+O+xInEugXxWubN6KxGHk66jhG+saxImUKPWceGym/YW5fD3toTXOQbz/etxZzoqODL5jM8nHQd1wRncqKjgj31OVwc4HRePd5ezvPFB7A57MS6BTIpPBuFSIbBZmZW1ChClN4kugcjEggY45/I5YHJ+MrdeapoD/fkbkEllvNC+k2sPLOHx09/SLRbAG9nzWNdxdcsObUFo83Mk8mTCFV6E60OQCgQsqxwJyvO7OaG8GzqDV0syd3EK+cOktdZxRuZN+Mvc+fexIn0Wk3OoM1zn/BG5i28mnkzMeoADtSf4qmiPVRqW+i26FwBvQA9Fj0Gm5kfWopZkrsZjcWAXOKs4nSatKw4s7vfsX7u7H6uD80i1TMCg81Mh7mX1zJvxlfqTpdZi6lvZunZtOm8nTUPpUjqFNcOAUM8w6nWtvHi2QM0GrrRmo2Y7Fa+aCokv+s8W6q+x+GA4p56DtSf4lBTAZXaVox2Z5uqt1TtWkNRdx3pXpEoxTLkIgnp3pEEyD24NCCJx4fcyIvpN5HsGUaHSYO7WMnd8Vc7L0YMvpYsnxhWpk4j3j2Yq4JTsTsc/NDq/Cwt7nN2FAtFWO02vGVql1j6Ze6Zxmxgf32OSyxdyO7ZXPU9w3xiuDIoBXBWcUKV3oCzavu3xNffI1oV4DRPAbZWf8/9+c4g3zi3IDK9o1lb/hU9Zj1bq37g3rxt1Os6WRJ/df9jlzZjQCz9TqwOG12/aHfUWgyuQNv/JTykyn4GDyqxbEAs/RfyhwXTd999h9ls/tV2o9HI4cOH/5RFDTDAAP/5SIUSRvjGAvBo0g08PuRGXsu8GZFASIZ31F/u8HQBgUDAIHUAie4/OdsFK70Z6hPzqzXcFDmK96oPsyR3C3OPv8PZnnqECPCXe7haI3QWI6tKP2N7zVFMdotrPmlz9fdsqPiGdqOGFWd288H5Izyc/4FzfqbiG9ZVfM1dpzY5s2GCUl0hreW9TdhxkOAezLxBl/FC8QHCVD7kd1Rjs9uYETmKA3UnsThs1Oo6+KaliC+aC/ut+6H897kv8RpCld4oxTIECHjl3CeIhCKWnNpEr9WIt1TN8uQpKERSWow9vFR8gB6rns1V33GwIY9hvoNIdA/BjoPHC3awp+4E750/jMVucw3q/9hexpG2Ek51VHJDWDbqvlycdlMvb5Z+St3PZgvq9B08fWYPL6bfxNaqHzDYLHSbdFwbMhRPsRIfmRuzo8YA0GnWIhAImBiSwU0RFxGu8sEugASPYKZGjGB37XHcJAouC0jq975Xpk6jXNNEl1mL2W5FJpSQ5B6GxWFj7ol30FqMRKr9aNB3EqrwZmrECL5uLqLLrKPLrKNK18q9eVt5umgvpZpGNBY9zcYejDYzDyddT4OhE7FQRKjSB6vDxtLcLdx5aiM9FgMeEiW+Mne0FiNvDr2VjRXf8ETBDpI9w7k7fjx1unai+3J6lCIpQ72jCVf6sjR3KzaHnVClN95SNTqrifvytjEmYDDeUjWXBiQxL+YyBAIBD/dVMBLcgvlw1BJCFN6Y7FbeLP2MpQkTsDns3HZ8LX4yd4Z4hvJDawnLUibz+JAbUIvlfFh9lKdTp/N21lyUYglLc7dwT+5m5kRfzJdNhTSbunnp7EcM9ghlbKBTXGyp/t6V+TQnagwGm4kjbSXcEXclH45a4hLrx9vLsf7s5DVU6cO6YQt4cPC1eMvc8Jd78FzaTF7JvJkgpSfXhg7lwcHX4iNToxLLCFZ4szj2Sh7Mf58ZR99wVdFi1AHIRRI6TVo+acx3zQj1Wgx83VzUzxDC4rCyp+4E4LQY//TSh7kiIJlHh1xPYF8gsJtYzsrUaTw4+Fpi3QK5N3Hi3wyJ/Xt4yVQsGHQFQzx+yr2SCSW8mH4TTxTsYF99DtOPvsF75w/jKVEx1CeavX1ru8CWqu/pNv965mmA/uisRr5rKXbNo4YrfZxh3dpm7s/d9qu4hgEG+E/gdwumwsJCCgud/8SLi4td9wsLC8nPz2fjxo2EhIT8ZQsdYIAB/rNQS+RcHZzOjlH3uBzgMrwi+eCiu5k76LI/LfDw9yAQ9M8r6bUY+LypgB01x/o97uHTH3Bn/FVEqPxcjnovpN/EUO9oxAhpNnTTatLQZnBWkm6PvZJn02YwvE8YWu02LHYbUyNGIERAUU8d1373gitM96qgVOp0HWyp/v5XTk9Bck9MNgvdJj3tRg0JniGc6qhCLpLyZPJkLg8YwkV+8Wyrdl54GheUwpYRi3ETy+ky69hde5yboy7m6TN7sOPggcHXIBdJWZkyDT+ZO2uz5zMuKJV1wxYQIPPggcHX8WzRPk52VKK1Glld9gXLkie7zDiyfQZxQ2gWjxc480EEfRbpH9Yco9OspdXYw9tZc8nwjsJkM7uMKh4fciPLk6cgEgjJ767hq+YzBMg98JAoWVfxNR/WHMNgM9Nl1jE+OJ350ZexOPZKlhfuZvmZ3WT5DkKIgKW5W3jp3McEK7y4M24c7mIF37ee67fP3io5xBDPcL5qOuMMfbSZUEtklGgamB01hg9rj3Gup4F6XQcPJF3Ldy1nuSQwiS8aC3g1cw5igYhaXTsV2maECFiZOo1THZWY7FYeO/0hGouBZYU7uSdhPMEKL2wOO0abBblIwjOp03ml5CBLcjdzX942zmkaEAAykZgvmgqQiiSc7a7nm5azaCwGxgdnIBWKEQkERKv9eWzIjbwx9BZ8ZG5IhCJsDjtmu5UwhQ9ykRR3iYLVWbdxXUimc62IeCTpelI9I3g5Yxa+cjfClT7EqAPoMevZUv0D37Wc5WB9Hk8X7WN54S4mhmaypep7Xj/3KbfnbMRktzIrajQ5HRW8W/Utd5/azJyYMTTpO7kl5mI8JT/9TUap/BkXlEqWdwyPJt3AdaFZeEpVPDFkEvckjOeehF/nH7lLFPj8rF1KLZYToPBw/ezC46UiCbFuAShEUtzECnr6qrej/RJYmTIVoUDIW6WHeKZoL2+Ufkq3WcfH9bk8UbiDh/Lfd1WnfWRurM66jVlRo1kSPx5PqYrbBl3G8sLdrDyzB5VYxsrUabxVeohHTm/n0aQbiFUHutZnsduo1rb2M26o1bX3E2UXMNksnOmu4Zym4adtdgt763J4OWMW4DSXESLg7ay5LCvcSa2+A6lQzOTw4QgQUNhdyyOnt/+mUcQAP2FzOND2tRwP84ll3bCFvJIxB5FAiMFu/t3B550mLS2Gn46lxqz/zWM7wAB/Br97hkkoFLryl37rVxQKBW+99RZz5879c1f4JzIwwzTAAP83aDNquPGHlzHZrVzsn8jiuHHcnrOBTrOWNK9IpkeM5OHTHwDwcsYsguXemOwW1lV8xdmeel7LvBmAzxpPs7/uJMtSJtNm7EGAgPPaNhbFjuV093keOb3d9ZqTwoZxc/TFvFHyKSP84ni2aB92HKjEMnRWp5vauKDUvvaeL3k2bQYykYRQhTduEgUlmgbWlH/J+OB0jreXMzEkg3pdB34KD3bXHOfexImsLNrD6a7zzIwcxeSwYQQpvajTdaAQSV0nrvX6DkQIMdus3HJiNdPCRzIzahRai4GNld/wcV947Uvps9hW/QOF3bVEqfx5O2seb5V9xmeNp/GUqNg28k7eLvucQ02nmRo+oq9yIGeYzyD21p4gwTOEcz0NeEvVRKn9iVEH8H71YS4OSKJa5zxJLdbUsyR+PJ815JPoEcIThTsRgDNzxW7FS6rimdTpeEpVzD62ytUCle0zyGWCMD44nUFugbxZ+hkLYi7HW6bm+eIDTI8YyTCfWN6vPszDSddz8/G30VlNjA1M5tboS+m1GlhWuMsljL2lap5Lm4FEKOLJwp3U6zvxkCh5JmUaDgE8VuAUUOC0un4lYw6HGvM51Gc0AfBc2kx+aCnms6bT+MncWTdsATf88DJXBaWR6R3NwYZcbo6+GIFAwEf1p7gxLBtPqYpOk5YPzh9FLZZxSZ+NcpjKFw+JnFJNM3KRhCiVX98JuIgAhScigZBmQxcgYPqR19HbzPjLPbg56mJeK/kEq8NGkkcot8VcztI85xyI0178JoQCIffkbqHD1ItIIOSehPGU9DTwSWN+v7+T22PHAqASyUn0DCFU4Y2XTI3ZZnXN65ltVlqNPTiAY22ljA9Op9uiRywQcqD+JFMjRv6mo5reYqJS24zOZuL5swcw2a2sTJmKTCQhQuHD/oZTLse7IIWny/1wXGAqSxMn9HtOncWISiLH5rBzrqeB23M2uKq/MqGYWn0HIoGQN4feQqpnJFKRc5bvbHcdd556l7GBKSxJuJous46FJ9YTpvLhubQZ/YwhCrrOsyhnAzaHnXi3YGLUAXzalN+3n67EYDOxucppz74yZSr1+k42VX3Hqqy5xLkFcaKjgkfyP2BZymQu9h+MUiz7219QA9BrMZDXWU2SRyi+cvc+wVpLiNL7d82fdZq0vHLuY0p7m3hr6K2oxXJ21R5n+/mjrB0235VtNsAA/4g/fYapurqayspKHA4HOTk5VFdXu24NDQ1oNJr/aLE0wAAD/N/BS6rk7ax5jA1M5uGk64lSOwVBlncMc6LG8GzRPnz65jUeyv+AGl0bSrGMEk0jGouBpblb2Fb1A7trj2N12DivbSXNK5I3Sj/jQMMpijX15HZU9XtNZwVCwILYsRxrK8OOg0T3EN7Jns+t0ZcAkN91ngiVL1KhGIVISqjcKZaqtK3cdWoTx9vL+bQxn1i3QO48uQm5WIqbSM4dcePQWow8mTyJ+xImkuIZjloip0zTyM0/vs3bZYfoMumo03Ww6MR6Hi3Yjlws5cOLljAj8iJEAiEHG/JcYmlK2HBajT0sjruScUGpvJh+E0qxjDvixjEtYgRrsm9jR80x11C93mqiy6yjqLuORTnruTwome+ai1GIpKyr+Bp3iYL1FV9zQ3g2D+Rv47WSTxALRSyKHcuSU5t4v+YIhd213JswATsOTHYrbmI5T6dORygQ0GTo4rrQLOLcgliWPIXLApNYHHclPjI3rgnNZHftcSaHDyPdO8olPiNUvnhKlMwddCkNhk6eHDKJEIU314QOpUbfxtG2UpdYAmdb4PNnD4BDwNOp0wlVerMuewFikZjH+8SSh0ThqjTdn7eNMf6DGeodDdDXuunO3JhL8ZKqeHDwtbxQfIBxQakM9Ynm2bP7KOiuYWvVDzxZsINvW86ys+ZHhAhoN2lYkTKFywKHsKxwJ08X7cFgM1He28zikxtYmLOO87o2IlS+LrEEEKjwQiWSck/CBPzlHrw19FZKNPV9AbwKliZMYEPF1673aLZZEQqEvFvxDU+nTkMmFHNNSCY6q8kllq4LHcol/s55sTXlX+Irc6dU04jJZmF9+dd0mbT9xFJRTx3TjrzOhzVHkYjEnNe3Mff4Gp4v3k+UOoDVpZ/T9TMrbgCdxUSFtpm7czez4sweHhtyI8uSJ/N00V4W52ykWt/OdSFZrrbVC2LpioBkliZOwF2i6DfLopLIMduceWwJ7sGszp6HTCimxdjjEktvZP4klgCMNjNnumsx26180pjHEwU7WHhiPd0WHTW6NlcQLjidMt3EClI8I4hzC2JJwtWM9k9gQkgGvjI3RvjG0mnSEqb0AeCJwp2EKX3YMeoekjzCUIplDPeJZf/FDwyIpd+Jm0TBKP8El/ugTCQh3Tvqd5t1dJq1fNdSTK2unbtObWJt+Ve8U/4lPRY9B+pOuS5+DDDAn8XvthWPiIgAwG7/3xvIG2CAAf63EAvFDPYI4YHB17rmGRQiCZPCh7G8cBd3J1xNhMqXF846g3crtS2EKn14OX0W9+e/R5dZx3etxQBMCE7HS6rC5nAwJ2oMHlIl37UU83FDLgApnuEUdddR3FPPw6ff57m0mUwOzyZM5UOyZzgLT6zjvYvuQi2Wk+gRgtVh5/n0mdjsdsQiMd0WPU+d2Y3GYsBLquKOuHG8eu4gdpzOZnvH3E+Nto3BnqEoxTKuCExGKBQiFogo6KrFYDNzqKmAbrOeKm0LrSYNWquRXquBQW4/tSddHZzOR/WnGB+SwZTw4XxUf4oOk5brQ7NQiWX82F5Gp6mXW6IvwU0sJ9snhu01R1kceyXXh2XRaOji9pwNjPCNo0LbwtG2UvK6qglWerEkdzOvZ9yMWCBilF8CX7cUsbHyGzZXfYfNYUctlnNNaCZfNhSgFEnxkqp5Nm0G4Jxn6LHoudg/kZsiL0JvNRMo88BNJGfT8Nup6G0mWhXArMgxHKzPpdOiZePwRZztqqPd3MvjBR9CX5vUytSp3J/nPH6PJF3Pxf6DuTo4DYvDxorC3VTrWinW1JPlHc267AW8Ufop44MzEAqEeEiUrBo6lx6LnlfPHXTNa9kdDtz6ZrkW52xkVdZc3h95F08X7eV4ezn3JkzkXE89fjI3AhWeLE0cz8n2Sj5qzO0zgdATrvTFTSLHV+aGWCiiVt/BwhPr6bUaMNosuEs8kIqcrnaivtZIcBqr2HBwRWAyY/wTESIgUuVPUXct2y9awsP573NWU4+fzB29zUS3RceSU5t5OWO2UwTZrXzeVMDK1Gkkuocw1CeaDK8o2k29CAQCDDYzbmI5VwYn80TBDu5JmOCy2wcw2Mx831KMxWFjV+1xLvEfzJqyL+ix6CnuaWBO1MVcEzoUlai/QHDgPE8QIKDD5DxGYoGINpMGmdBpry4UCPrZiAMIhQLsDgfnNA2IBSLi3IMQCYTU6Npo0HeS4R2NXCTBX+6Bp1TlmnVRi2WEKn1cYgmcJ+TXhQ7F5rCzuvwLTnRUALhCl3/eMisSighUePLA4GtoNnTzQN576Gwm7k2YyJyoMXxcn4tSLOPd4bezry6H1eVfcLAxj0zvGJfBg0IsRSH+42YT/5f55fH/5f2/R7jSl7ey5nLXyXep1bVTq2sH4JqQDG6Jvhj3AVOFAf5k/ilb8bKyMr777jtaW1t/JaCefPLJP21xv+SHH37gpZdeIjc3l6amJvbt28f111//u39/oCVvgAH+b3Ne20advp1DDae5IigZX5k7VbpW4tyCON11nli3QPbV5fBl808Wy2uz55PXWU29roOrQ9Kp03fQbOx2WnSHDePWmEso6Wngwfz3GekXx+K4cdx89G0mRwznQP1J9DYzESo/ViRP4emivZgdVq4OSkMgEBCh8mWEbzzdZi2PF+zgyeRJuEuUVPQ2s7X6B24Iy2Z/XQ5eUhX3JEz4VeuTxqLno/pTvFl6yLVNKZLyTvZ8YvtONn9Om1GDVCjm25azPHt2HyKBkJfSZ2G0WXiswGmR/HzaTIZ6RVOv70QoFPBNy1nGBaWgs5hQS+UUddXx0rmPeTVzDl5SFb0WA7tqj7Ng0OX0WAy0GTXsqv3RNfMEsGXEYl44e4A50ReT6B5Cs7GHR05/wPWhWYzxT+RMVw0x7oHcm7sVqUjsWtNTRbvpMRtYnjKFUx2VTAobxuHWc3zSmI9EKOKJIZN4vPBDmgzODC6pUIzWakQtlvNG5i0YbWbUYjkqiZwOUy/nehrQ20xsqvyOd4bN5+P6U8hFUq4OTqfLrGVv3QlujroYd6mSGl07O84fY3L4cGLcArj71CYaDV0sih2LUiTFQ6okp62Cgu7zvJA+C7PdisFm5kR7OTeGDaPDrEWIgPfPH2Fp4gR8ZW5Y7DaKuutYfHKDq4LiJ3Nn7bD5hPZVLy5Qr+9gV81xMr2jSHAPAQFsrPiWqRHDOdJaQoDCkxVndhOk8OT1zFvotRi4+9QmRvslMNw3jmVnduHAQZxbEDqrkfsHX0u1tpV0r0hWFO5iZpQzayi/s5pAhRf+cncS3UMIVXojFUnoNuuo03cQLPdid91xNlZ+61qbh0TJipQpuInlxLuH9BMqF9BaDJzXtXPXyXfR9QX8SoViVmfNI0rlz0cNubxR+ingbCW8MHsyLiiVbJ8YXjn3CVtGLEYkFDL/+FqnucqIRXhKVNyXt41KbQsCBAgFAmwOO8EKL97OmkdIn1veBWp17Uw5/JrL/jvLJ8bVBvpLOk1aFp5YR42+3XVsNo9YTH5XNdk+g/CUqtCY9eR0VJLmFdEvm+nfhd1hR2MxoBbLXXObXSYtMpEU5f8xwdZrcbbdXnBqFSDgk0se7ueiOsAA/4i/zFZ8/fr1DB48mCeffJLdu3ezb98+123//v3/ypr/ITqdjtTUVFatWvWXvs4AAwzwv0mQ3AOlSMZI/3j2159iSe5mKnqb8ZQqCZR78k3LWb5sPkOcWxDvZM8nUO7JA/nvcbH/YBbGXYEdB6+eOwg4Z4CCFJ6sLf+KWLcg1g1bwH2J13DLsdVYsFHUU8eTyZORCETU6NpYU/4Fi+OupFbXztoKp0VxgnsIJpuZYKU3r2TOwUOqYn9dDvflbWViSAZ5nVWc6KjgUFMBr5V8QodJS7dZ55ojdZcoubTPzv0CsW5BeMvU6Pta136On9wdD6mSEb6xxLkFYXPYuTdvK48WbMeBgzSvCAZ7hCIRifFVuCEA4twCsTnsPFb4IS8Xf4yPTM1L6TfRaexld+1xFuVs4JKAJKRCMW5iOV4yFTV9V3svcLStjHTvKB49vZ0DDad45PQHdJq17Kr9EQ+p0tXOqBBL0VgM3Ju7lccLPsRit3FDXwWsoKuGzxtPM8x3ENeFDmV5yhSKNfW8nD4bP5k7ZrsVrdWIXCTh2dTpKEVSmgzdWBw2FpxYh93hQCoUk+YVSZZvDAFyDxYOuoJJYcMxWM28eu4Tfmgt4YnCnbx49gBuIjkTQtIJV/kiFgh4NnUGSxMmoLeaeK3kUzwlKu5OuIrXht7CIwXbuS9vG15SNZPDR/B88QFuz1mP2W51iSVwVlXkIrHLYANALBT+Sth2mHq5PWcD22uOcrAhD6PdwsP5H7CvPoeVZ/Yy2DOUw63neDp1Og8kXsv+uhyCFV68lTWXm6MvJljphVQoJsMripfSZ/Fq5s08XbSXPbUn6LUa6LEaePbsPp4s3Mm++pOY7BY8JEpOdVRyTtNIo76TXTU/8mTBTlpNGi4PTHbZdgOke0XSbOwht7Mag+3XrrkAaokCL6kK+c9O4qVCMZ5SFTaHnbLeRgCuDEzh/ZF3cWfcOMApcPzlHtwdfzXvnT/MeW0bvnJ35kRfTJO+mwptC1XaVkQCIW8NvZX1wxYgE0poNHRxpruWLtNP7YF1ug5ajT0E/6zN62RHJW+UfPYrY4Y2o4ZlhTtdYgmgzaTh8YIdpHlFugSWu1TJpQGD/7+JpYreFmYcfZMSTSM2u40GfSe3Hl/Dj+1l/doM/9fRmPXsqj3eLwPQgYPbT26gua/Fc4AB/kz+cIUpIiKCxYsX89BDD/1Va/pdCASCgQrTAAMM8LsxWM2c6CjnofwPGOodzaTwYTxRsAOLw0ZAn0Xyopz1RKr8WJIwnheLP+KBxGtYW/ElDyRei85q4u5Tm7A4bISrfJkQnM6a8i8BmBk5iutDs9hec4RwpS8gYIx/AqvKPmdsYApryr/gxfRZeEvVrK34kr11OTyQeC21unauDE4h0T2EWn07i05s4I64K8ntrCbFK5zLAoawu/YEGyq/Zkn8eBLcg3ms4ENWZc0lVOFNo6GLu09totXUP/Pq0oAkZkeNJkLlh5tEgdVuo9dqwEv6U4Wqzajh/j73N3AGrL419FZ6LUYUIgnzTqzl5YzZSIUi3CRKWo09LC/chYdEiUIs5dboS9hY+Q1ne+oRIGBiSDrXh2bzQP57dJq1qMVyotX+FHbXArBo0FjazU6RBeAmlvNW1lx0ZiN35L5LmNKH+xOv4YnCHWgsBtwlClamTKNW306GVxSry75gScLVfNtylgzvKI63laOSyMj0juHuU5vosegBkAhEPJM2nY/qTnGRfwJvlX6G3mYmXOnD48mT+KrpDDdHj8HvZwP/Goue/M7zPJj/vqsSMdQ7httjr+Dh09tZknA1ATJPPmo4xcGGPFakTEHggF11x1mSMJ57Tm12WbsHK7wo6qkDYHnyFEb7JaCx6rHa7ehsJm7P2YDBZsZDokBvNTs/T0of3sqa65rf6LUYOFB/ijdLPwOcrUo2hx0hAh4fciORaj/0VjNV2hZ21R5nacIE3CQKovqOt81hp1Lbgs5qotXQw0i/ONpMvfRY9Dx2ejsykYSXM2azpfI7Pm8uRC12tj82G7u5P28bIUpv7o6/2lnFK9iJAwfLk6fwQvEBGg1dKEVSZkaORiGWkOEVhVQoJkrtj1gootuso8OkRSoUc9epd2k0dCERiBAKhJjsFnxkbqzJmodarKCg8zzpPlF4y9RozAbOdtcR4x6AzW7ng5oj7Kj5EaVIynNpM6nStvJG6adcFZTKKP8EPCUq0rwiEQoEnNM0UNnbwhDPMJ4p2sfzaTNQieVUaVt4ofgAd8c7XRC/bj7D6vIvEAtEbBt5JzFuTmMAm93GF01nWHbGaX3+5JDJSEU/vfdHk25gQkg6EuHvnmL4S+gy67jz5EbKe5uRCSUsS57MqrJDNBq6kIsk7B/zwG8acPwvUt7bzE1H3wRgYkgG44LSuDd3CxaHjQnBGdyXOPFXYeQDDPBb/GUVpq6uLqZMmfIvLe7fhclkQqPR9LsNMMAATpoN3ZRqGl1hkR2mXgq7ajBazXSb9dTq2qnqbfnLAmj/7QhAiBABYLSbSfGI4JXM2QC0GHtYVXaI59Nm8lzaDJYX7qJG18aKM7u5LeZyHjn9AS3Gbob5DiJc5ctDg69DLpIyI+IiPPryg+RCMSfaK4lS+2O0m6nXd5LbWcW3LWdZk30bwXIPvGQqFsaOZV32ArrMWnbUHmNxzgY+ash1DaS/XfYFd8SPQ2s2sL/+JDZsvJQ+i3FBKdTp29FYDCw8sY6K3mZ2152g1aRBKZKyafjtLBh0BQDftxSjt5qxOexY7TZKNI08mPe+a+ajRtvGvXlbuT1uLEEKT9c+KO5pYEvV9zQbe3go6To+achj3vG15HZUcq6nnvmDLqNC28yZ7loeLdjOI0k3kOwZjgMHIoEIhUiKn8wdtVjOUylTmRE5ijH+iYgEQuI9gqn/WY7T9WFZ5HVWo7WbmB012iVUwBlQ+mzqDF4v+ZRXzh3kq+YinkiexGsln7Km/Es2VX5HrHsQKZ4RLM3dQo9Fj0okw0fmhsVh44mCnVwbNpSDDblOdzmZO/cPvoaP63LJ8I5CKBDSoO+kQd+J3mpGKZLhLVUjFPxU+WkzaZCLpMyJGkNeZzUaq56K3maSPEJJ9YzgueL9FHbX8mzRPp5OnY5aLKfTrHWJpQcSryHDK4qy3ib2152irLeJ89o2DDYzAXIPNo+4g7ez5yEVimk39dL7syH1C/M3F8xCLrTvPT7kRuLcg3kg7z2eL97PKP8EZw5T2efcm7vFJZztDjulmkaWnNrEk2d28l1rMXKhBBwOUr0ieSTperrNOi4PSmZiSAYrU6YhFogw2ixYHXaqtK28VPwxj53eQadZi8Vuw4GDp1OmMyPiIlamTnMKev8hvFP2JeW9TZRoGukyaXm34lteKD5Avb6DFmMPMqGEVzPnsDp7HiqxjE6TloreFjQWPQFKD9esicluQSwSohbLseFgtF8i/jJ39DYzS3I3u9r3bA476Z6RpHk5DR7EQhGJ7iGM8otn/vG1nO2pY2nuVmr17TyU/z7lvc28dO4j1BI5N4Zlc2fcON4aeqvLwAGcM0wj/eKYH3M5y/tMR0b5JfBM6jTmRI3hkoDB/9/FEoCXVMWL6bMIVnhhslt4tGA7jYYuZEIJq7Pm/Z+a2wmWe/LkkElcE5LJXXFXke4VyVtZcxnqHc3iuLEDYmmAP50/XGGaN28eWVlZLFq06K9a0+/i91SYli9fzooVK361faDCNMD/dZoN3SzN3UKDoZM12bcRJPfimaJ9HGkr4dnU6RRrGthW/QMAAXIPHhp8HRneUf/17k8Gm5ni7nrCVD5IhWI2V33HB+ePun5+VVAqt0VfhsZm4K6Tm1yzF+BMZ984bBF6q4lOsxaZSIKf3B2r3c5jBR8SpvTh8SE3sqb8Cw7UnyJa7c+Dg68jQO5OiNIHi92GRCjCYDNjsJox22y8UvIRrUYNSxMnsKxwJ3qrmdVZ89BajHRZdJzpruX60Cyqta1EqPzYXP0dl/gP5rGCHdgddh5Jup7T3TXcEJrF+9VHiHULxIozNDXTK5ogpRfdZh03fP8yOpuJeLdgHk++0WU5HaHyY3nyZFYW7aVK24JIIOSplKnsrzvJILdAPqw5hgMHU8KHMzEkk9tz1qP/WQvWzIiL8JG58VbZIV7LuBm1WIbeZkYgELC+/Cssdhuzo8cQrPBi+/mj/QJ5L+QixbsF80ThDhbFjmX5mV10mXWoRDLujr+a093nXSGrHhKlq4q0NGECvRYDgz1CeaJwBwIEPJ82Ex+ZmnvzttJq1LAseTIfN+RysqOSt4beyo6aH1mScDXtxl7EQhG7an9kpG88Ndo2RgUkcMfJjRhtFtzEcvQ2p9iMdQvkocHX0WTo4oumQg73tf/cEnUxQzzDuD//PSQCEc+lz2RDxdeUaJxtZhKBiE0jbqfDpOWB/Pcw263cGTeOSwOSKOttIt49mBCFN3qrmQptEzKhhFj3ICw2G3Kx03Sh1djDQ3lOU4cLXOqfxMLYK7jlx9UY7RaCFc7Wu/O6tl/ZarcbNTxVtIfj7eUAhKt8uT9xIi2GHt4p/9I1Y7U47kpi1YFIRU4zhlaTM5j5gkhTiWW8lD4LX6k7VocNpVjKQ/nvU6/v5O3seXSatOyvP8nRtlJWJE/hUNNpjrSV8mjSDQTIPZAIRawp/9IVFtyk7yJE6cUThTtpM2pcc0ePn95BXlc1T6VMJa+rmh/byng2bTrzT6xzrSXZI4yXM2f3q5RewGyzkN91nntyt/Rz2FOL5azNns8gt0AEAgG9ZgMykQSj3dJPYPRaDFjtNmQiiet7Tm81YbZb/6kg3L+Scz313Pzjatf9O+PGMSPyov8IUffvRGcxYrZb8eqrqpltVnRWo+v+AAP8Hn5vhekP/3UNGjSIJ554guPHj5OcnIxEIun387vvvvuPr/Yv4pFHHuHee+913ddoNISFhf2d3xhggP8bWB12dFYTRpuF23M2EKHyo7TvZK/e0Imm78QUnJWH+/K2sWH4QpI9w//l174gHP7W/b8ShUhKhncU3RY9m6u+d4mlod7RFHTVcKipgGJNA2uz5rMiZQr357/n+t274q5GLpIgFYp5p+Ir6vUdvDn0Fk52VlGja6NG18akH15xiayL/BLoMPWiEEnxspo4012Lv9yDdpOGA3WnuClqNDMiR4HDwdNn9vBI0vW0GjUcaytlTMBg7s7dhKnPSGBaxEhXjpTFbuO+xIm8UHyA587uZ232fEQI6bHqGeWfQIOhEy+JCqlITLOhG6lQxNOp07g//z1KexuZfcw5A6oSy7gvcSLuEiUrU6ay4sxutFYjnlIVGd5RRKr9CVX6UKVtYVrESBaeWIfeZsZP5s7ylCkcbS3BX+HB6yWfIhII8ZWpEQtFvHTuIxwOWBw/DrvDjrtEwbbqw3zTUoSbWM6y5ClsrPyGc5oGVpzZzXsj70LRdwKrs5pwE8t5KnUaCpGUEIU3Wd4xPFW0hx6LnuG+scyNvpQAuTtL87bxfes5VqZMQ9gXFvtt01ley7iZal0rH9c7xRLAijO7eT3zFjZWfMNtgy5j/ol1TmEmljM+KA2VSOacr5GoWJM1D5FQxF2nNtGo7+rLi1KT4R2FWiLns8bTbK7+nvXZC7gqKJXR/onsOH/MJZaECLA4bNx9ajPLkiczxCMMtVjGxQGDCVZ694kIMZXaFmq0bWR6R+MmVdBi6OaH1nNcHpgMOEOWz2rqESJgqE8MOR0VfNt6FoANwxcy9/g7NBq6AGfL3uuZtxDrFuSqkvnK3VmePIXpR96g26KjVtfOntocbo25mA6zc37HjoMus45Y9yCOt5ezsfJbHkm6HplQ7BLGHhIlwQpvgpXOdsE6XQcdZi06m4k7cjYS4xbgarus0bcTqPBidl9VRimS0msxIsDZQvVc0X4GuflzdXAGDgeY7FbuOLmRIIUX53VtgLOCZLFZuSo4jYKu2n7ip1LbQouhB3exAgcOxD8TCFKRhAzvKJbEj+fVkoOu7S9lzHKJJQA3qYIOUy8bKr5heuRIIlR+9Jj17KvPIdM7mkT3ENfvKsUylPxnXSRq0Hf2y38DWF/xDRl95iDif9N36X8CKomcn0tZqUiMVDQglgb4a/jDLXnr1q1DrVbz/fffs2rVKl577TXX7fXXX/8LlvjPI5PJcHd373cbYIABIFTpzerseQTIPTDaLC6xdG/CBFqMPRyoP9Xv8Q4crC79vJ+Q+meo0bVxurMak80CQIuhm2+bi/q1I/3VCAQCpEIRg/qCDW+KHMXzaTN5K2suEoGIwe4h6GwmXvnZSRfAxspvaDJ281bpIXI6Kmg0dFGqaUIhknB7X57MBbF0XehQhnpH023Wc7D+FHmd1dyTu4XbczYgFoi4KjiNxSc3sOTUJnqtRlRiOe+Uf4WP1I1wlR/ntW1MDMkAYG9dDtOOvO6aC5oYkumaA7LjYGneVvR2EzdHXsxtJ9ZisVtpNWmYc+xtanXtnOmqJUDuyW0xl/V7P8+lzUQqEKGzGtldc5xFsWN5Ie0m1CIZFoeNR05/wJnuWq4LzWJr1fc8nHS9c9Zm6K1sq/qBaZEj+fD8McBpAqASyynvbWZ5ylTujL+Kt0oP8cjp7UiEYuYPuoxotT8rU6ezpfp77oq/mmSPMJ5NncGpjkoqtC1EKn15OX02r2XezHtVPxAg96DW0E6Nrp15MZcx3DeWCcEZ7Ko9jtluo1bXTnlvE6vKDvF6yad82pDPZcFDeDD/fT48f4wKbQvPpE5HJZbRburlkdMfsCD2CrZU/cDMyFEEyj25PnQo+V3nebRgO2uybuOd7Ns4p2lk7vE1PJUyhRczbuLN0s/4qvkMgz1CSfOK5IawbJ5Lm0FRTz0zIi8iUO5JXlc1AI8m3cCWkXfg1teel9dZxdKECcyOvhiTzUqLoRupSEKNrp2FJ9bxaMGHHG0vpdXYw52n3uXVkk/YU3sCm8NGhNIXIQIeTrqehwZfx93xVwPOSpFcKMHrZ1UPN7GCMKU3HzfkUtLXZtth7GVv3Qm6LU4TBJlQwoSQdF4792m/z8HBhly6zDrq9Z08lHSts9JpMyMVihEJhDQaurgvb6trkD5M5cM72fPxlbmhs5lcYmlezGXorSZ21x7nkoDBqMVypCIJPnI3Xki/CR+pmgptM4eaCllX/hVvDr2lr7XM6hJLK1OmMcY/kVlRo/GVqV1teEO9o/us080syllPeW8zZb3NWPraiS/QqO9iS9V3/ba9UnzQ5cAH0GPWs6bsS/bUnWDRifVON8La46wu+4LFORto0Hf+1tfGfwRdZh0P5r/vasN7NnWGqz1v8cmNA9lDAwzwF/KHBdPPA2t/eauqqvrHTzDAAAP8R6AUyQhV9LcyjlL7U9LT8JuPP6dpwNgndP4ZanXtLMrZwN25m8nvOk+bUcN9edt4vHAHhxpPo/03/rNXieVcGpjE5hGLmRU5GqVYRrJnOO+OuJ27469myanNNBm6kYsk3Bl3FSqRjDaThmWFu7gl5hIAnhwyCYPVTJp35K9OslqNPUSo/FCKpFweMARfmTtKkZROs5b787bxWMGHzmqKRIFMJEYoEHJH3DieK97PyqI9RKn9iXcPYbRfQr/nfSl9Fm+Vfka7ScOzqdPxlqrRWo08XrCDMLUPdoeDOLdgXig+QJtJw/Izu9BYDU6zhboT/Z7rrdLPUEvkCBHQYdHyWMGH3HlqIy+d+5h3+yykDTYTlb3NXBowhMOt53g8eRISoYg6XQcvnP1/7J13YJPl2sZ/2atJ9560dNDd0paNoCKKigKyRFRARFFxb8WFeysiiAgKgiwFF4pbNpRuSgd0791m7++PlBx6HEc9etbX339Jm+RN3ozneu77vq7dvJ61gEtCMpkRMZLXyvcQJPfkttwNPFf6MVW6ViwOG9cfeYtWYx/PZ1yFTCjG4XQQKPdk8dDz2Vl/BG+ZB++NvhkfmQcSoYiTPQ08kjqTBkMXz5V+zLvVP2C0W7g4JJNHi7fzVUsRuxtyeT7zKlK8wolU+VOjb2dl5ZfU6zu5KW4ybeZeHkqexp6mAp5InY2fTM2jKTPZVnOQiYFJvFf1I89nXoVYIOKtU99QpWvj4aKtHO6o5OGirXSYtaws/xKVSEZ5XxO7Go7hcDqJUPpxUXAarcZeXi3/nLuOv4efTM2LmfO5J3EqsR5B5HVW83r2QhZET2BScBq3Ht/Azcfeocui5cXST2kydCEXSYjxCMSJk8eLdzLvwOs0GLqQCsXEaYIBAbfEX8Q7o25klF8sgXJPLgvLYsOopVwens39BVtoNfW6bLUR0GPVc0vuekb6xrKi+EPq9Z1821rCzjrXOT8/KIUXMq/i44bjFPfUIUDA/KhxeElU9FqNLD32NpeFZdFi7KWzX5ivzlnM8xnzEAmE1OjbaTH24Oiv9rgMJgIGvJ/SvCPJ7a/o3XRsnXs+Um8zcaijwl3VAlelyOq04/N3rXXBCi/kIglhSl+SvSKQiyScG5jMrMhRPJk2B3+ZhnClH10WHbflvktpb/2AGcwbjq51H//S2AsQCYSc0rW4srn6XfHUEjmzo0bjIZbTadEx48eXeOvU14Arq0wjUf72L5J/MZ4SBY+kXOEyzsi5jomBibyRvYgQhTePpMxEIfr/ZSs+yCD/Sv5QDtO/C51Ox6lTrvC5jIwMXnrpJSZOnIiPjw8REf+4VWjQJW+QQVx0mrU8VbKLfe0nAZAJxZgdNuQiCU+kzubdqh/cw+tniFL5szpn8R92YWo19nJn3ntUaJsRCYT4SD1oN/chEgh5efg1ZHpHDQjN/FdgtFnY315GsMKbBE0Idqed09o2avXtPFf6Ma9mXcv+tjLGBQ5jWe56bom/iNzO0xR21/LK8GtRiiVsqPqe3Q2uENsETYi7NWuMXzwXhqTz7IldrBt5AyaHjRuOrsXudPBw8gwOtJczJTSdp0/s4qXMa3A4HTxQ+AE3xU3mu5YSLgxJ57HiHXSdtdCcEzmaCKUfmT5D8JKoqDd28mDhB9w17BKiPQJYVfEVDYZOlsSez/LCbZgcVt4ZeQN35G2k06xFJZYxI3wE79fsx+50MEwTyo1xF9BnMfBVSzE/9If1ApwflMx5gSlIRWJkQgkWuxWTw0qKVwRGuwWxQESYypdei4F6Qwe+MjX35G2iXNtMmNKHJ9Pm8kbFlxztPIVaLOeDsbdxrOMU2X4x+MjUVPY1s6pyLw8nzwCnk0eKtzM3aiyRSj8+bcrj/KAU3qv+gb3NRQPOWbRHIA8mT8NX4oHN6UAqErG5+gCXhA1HKhSjFEnR2U3cmruBVlMvsepgXhl+DXsa8xjlH89H9UfZUX+EK6PGMNQjCIlQzGPFO7A5/1atGOoRyL1Jl1PSU0+TsYswpS+XhGYiRkiHWYfBYWZPYwHTwrNZc+pr9DYTC6InEq7y5cO6o3zbWsItcReS21XFppp9qMVyXhl+DQfby7k0LJsQpTfNhm7uK9jsdikEeDb9SoLkXgzVBCOAn7RX2R12DnZUcmfee4gEQp5Mm4O3VMUtueuxOGzcn3g5wzxDua9gM8+kX4lGoqBW38EQjwAkAiF9NhOlvQ2IBUKqdG2M9o/n7rxNXBSSjkaiYKx/POXaZgJkGl4t38PNcZPdbW8Z3pHo7RZwwgsnP+ZgRwVPps1hZ90R9rWXoRLLWJV9HWsq93Kwo5LzA5O5O/EyjndV8UChq4UsyycGq8PG3KgxfFB7kIL+rC6VWIbeZkYmFPNG9iISPcMAaDB0IRYIWXjkTeRCKQ8lT8fqsPNQ4QdIRWLW5CwmysMl3HRWE182F/JGxZesyVlMpMqf/O5q7srbyAuZ88k46/vF4XRQrWtjbr/L2pnP6yOpM/GS/ucKJvjlHCa5aDA4d5BB/gh/ukteYmIiXV1/20W9/vrraW9vd19ua2tDqfxrv2hyc3PJyMggIyMDgDvuuIOMjIy/NCx3kEH+F9FaTeR1uSrC9yVexrZxtxMk98Jkt3K4o5JR/nE/uc2CmAn/UCy1mXop7annaMcpTvTU02nWAmCyWTDZLTydfiUxHoHYnQ7a+x29Xsq8+t8ilqx2G0c7T/Fg4QfcePRtyvqa0NrM7G8v48e2k7w7+iZ8pWomB6fxdXMR60beSG7nab5uKabd3MezpbvQW83Y+/ec5kaOYUXaHHeejFgoRCgQoLObeaVsD51mLRKhiEdTZvJxYy4j/WJRieQsjJnIB7UHONp5ihczr2ZPYz6Xhg13iyW1WO6uNH1Qe5BmUzcqkYw9Tfl801LMy5lXM0wTitVu56a4C6jQNnOgvZx5Q8Zhdzr4srmQ6eE5qMQynkm/kuE+0TydPhepUMy8qLF4ihVU6dqI+Lvg1HhNKMM8Q9ldn8uhjgpi1EGkeUey7vR3bK095F6seUqVrmBVp4DbEi5mrH88dw+bygc1B5galsW5gck8mzEPIQLGBMTjL/dEJBASqwnmsdRZyIRini/7hNyuKh4q/IBuq57zApPZWnuQxUPPcy+ewdVW9lLmfNQiOdccfoMWcw9SoYTpESO44/i7lPc1obUZWXDoTbcjYKW2mWdO7CJGHUSPRY/FYePa6HOo13dSZ+jAS6pkRviIAc/96fQrkfebgozwHcoY/3hsDjsNxi5s2AlReBOm8qHN3EeNro1DHZXceOxtVpR8yNrT33Ba18quhmOEq3xRiWQ8kTYbu9PJZWE57lkgJ063icUZ+qxGQvqNOj5vyqfXMvDvIqGI4T5DeCxlJstTruDjhlwOd1TyWta13Bw3mdP6Vl4p+5xn0+dhtFuYc+BVSnrqkQhFtJm13HzsHQ60l+En0/Be9Y+8dPJT1o+6kVCFN2tOfc2Cw6s52dvIq+V7qNN3oBLLSfWKIMM7khZTL0uOvEWLqYdus4EnUmezpvIrZkSM4KLgdPQ2M5815nFP4uVMC8vmjsRL8ZapSPAMIUjuxUi/WB5PncXT6XPxlnpwStsCwIrU2WwZcyuhCh/MDtdn0mA3IxaKiPLwJ1Tpw5vZi9FajSwv2saDhVsQCgRuseRwOuix6JGJJEwOTmP7uNvxl2mwOm1keEex+5x7BoglcH3/fddaOuC1LetrpNeq5z8doUCIl1Q1QEx7yzwGxdIgg/zF/OYKk1AopKWlhYAA126ORqOhoKCA6OhoAFpbWwkODsbhcPza3fxbGawwDfJnYrHbBiTcWx22/xqXIofTQWVfC+XaJs4NTMJDoqDB0MmexnzGBSSy+MhqzA6b+/9nRoxkUcy5vyqYqnVtPH9iN/Oix1Orb6fB0MVpbQvLU66gy6JjeeE27kmcymvlezita3Xf7sXMqxnuPQSl5M8bru4ya5EKJW5r2U6zFiGCn7gnNRq6WHrsbZqNPShFMp7LmMfhjkpSvSKo0rUxwm8o+9vLSfWKYEXJh8yNGoNGrODJEx/hxMltCVMIU/hgddqJVgUgE0nZ1XCUOHUI/nI1nhIVW2sPMDtyDPvbT2K0W+k269lRfxiRQMj9SZdT1tfIjv7WqTezr2NV5V5ujJ3Eu1U/UNrbwONps/GRevBp43E+rD/KM+lX4nA6kYnE1Ok7SPWKpNXYQ5DSm6+bixiqCUYmFPNI0Tb3ObwyagwXhw5HKhDybWspxT113DHsYqq0rSjEMop76ljdnymlEEndYaQPJk8nWhVAm7mXkz2NdFp0nBeUTJdFR7DCizTvKKRCMVqrkeKeOr5pKSHdOxIvqQqJQExRdy0+cg8kAhETg5J+sd2pTt/BI0XbECCgpLeeC4PTuTluMgU9NTxStH3A4P/1Q89DLVbwYtmnSIVi7ku8jDcrv6Ld3OdyMhx5A/MPrMRH5sFY/wR29rciXhicxtK4yXRb9HzdXES0OpAEj2BazL3clb9pwGNEewTweOpsJAIhX7eUMCUkgxZTD/cVvI9SJGfdyCXceGwdnWYtT6fPZf3p7+mzGjmlc4mA84NSGOkXy1MlH+EpVbIyaxG76o+yYOhE/GRqmgxd3Jz7jrsNL1jhTa2+HQEClqfMQIiQR4q3sTB6InOjxuDZX/WwOexY+o1AirpreKV8D+cHptBp1iEWCvm29QQr0mbjJVGxo/4wnzbmAa6ZuoPtFbT3W9BvGHUTuZ2neO7kJ4zyjeXuxKncdvxd6vpDW4UIWJ2zmCSvcCT92Uq35K6nvK8JD7GcZ9Ov5NXyz6nQtiAVitk1/m621R5ibtRovGUeaK0m1GfZOjcZuhAKhAT1W9i3G3sxO21U9DYz0j8WpVhGo6GLH9tOMiUkw/18AZxOJ1W6Nq47vNo9I6gWy3l75A1Eqvyo1LZwy7H1PJcxj2SvcFpMPdx0bB1Lhk7inMBhqMQD7aX7LAZ21B9xv99zfIdS2tuAzmbCV+rBWyOWEK4auHkwyCCD/O/yl+UwneHndJbgrAyLQQb5X6bN1MvHDbn0Wlw7kl1mHTvqDrsrKv/pCAVCYjVBnBeUgke/tW6Y0pd5Q8YR7RHA1rG38/Lwa3gqbS7bx93ODbGTflUstZv6eLx4BwuHnsfywq28UvY5/jINN8dfyHMndqOzmrhr2KWsrPiC0/321f4y1xfTPfmbKOypdRtB/LO0GntZXriNr1qK0NlMdJq1vHTyU94+/S3d5oE7yK7d6+vwkqh4KHk666u+Z1PNPrbUuqojO+qPsO70tzxX+jFvZC+i26TDhoPlKTOYET4Cu8PBXfmbqOxtxo6TnXWHuCgkgy6zjmCFNw6nndH+8Vx18HWajT2EKXyYEzWaOHUwdqeDFSUfusXSvKixSIQifKQqOk1abkuYwps5i9nTmEeXWcsYv3jeG3UTZocVmUjMXXmbeKnsM8r6GvGQKrgl9x221B4k3TuSx4p3YHbYCFX4sCJtNrvrc7nu8GruLdhMqncE+9vL2Fy9H7FQTKjCm6+biwE4J2AY745ayoSARHxlasKVPtxT8D4PF24j1jOYi0NdYb0rSj6kwdBFRW8zh9sr0VmNRHsEMsovDn+5J5805rHs+HosThtx6mDG+Cf86mxIhMqP5SlXcNWQcYz3H8bioedxWtfqFkvRHgGM7a+yvXXqG2xOBwuiJ2Bx2Hi8ZKdLLIlcLWHft5zAR+bBQ8kzODcoiWXxF6EUSZkUnIrRbub71hNsrNnHyvIvUErlbrEU4xHI8pQZiAUiqnRtvFL2GXKxlFPaZvqsBswO1/tzrH88LaYenkxzzUZValu4KX4yN8ZNIsXL5cI6yi+Og+3l+Ms1PJk2l+NdpxkXmMBrJ/fQYuzB5nTgdIJUKObJtDk8lzGPdK9InDixOGwkaILxlaoZqg50b8KcydP6se0kcpGEEX5xPJU6l3ODkpkankWDsYun0+didzrotuqZFJTKpKBUAHY35LrF0qqc64hQ+XJBcDqPpFzBgykzEAmFAwSjE5db3ZnfeS+pihVps/GVqdHZTNyU+w4V2hZEAiHPZ1yFWiLn6ujx7g2Js8VSn8XI1y3FvFv1Az0WPUa7hTJtE0+X7CLZK9xt4R2q9GFaePbPiqUlR99Cb3c5KKrEMrQ2E0uOrKXN1MdTJR/RY9Vz07F1fNFUyNKj62g29vBM6a6fnbmUiyQkeYYhEgi5PCybJ9PmsCZnMR5iOeEqP+T/4kr3IIMM8t/Bf8d2+CCD/AfRburjruMbKdM20WLqZf6Qcbx48hO+aikmt7OKB5Kn4StT/7sP8x8iFAhR/V2u0pnFS4jS29069FvoMGsp62ui06wlySucwx2VvFm5F0XVmWqFgGUJFxKq8OGh5Bm0GntQSxVsqT7AoqHn0mzsxuqwIfsDi5Uusw6j3UKIwhuT3UKtvo2b4y9kZcWXWB02+qxGvmpxCYIpIRkoxVL349gcNgw2Mwa7GQdOLgnNJK+rmvzuGqbve8G94JoYlIRMKGZaRA7728vJ76omUuXP5lqXLfk71d9TY+jg5vjJ3Jf3PlPDsqnRtVPW10S9oQOLw8b2usP0BBt469Q3vJA5n6sPrsTaPzeT7h3FCL9Yvmwu5ILgNALlnvSY9YSpfLg4NBNh/8zX1y3FpHtHYbRbyPCO4ljXaZ4p3Y1I4FrwektVmOwWVqTN5tWyz1mecgU+UpdL2RMlO7kl/iJeKP2EqaFZzIochc5mYv7BN1iRNpv87hpi1UHMO/A6DyVPZ4hHAJ4SFZ5ilw3zY0U78JF50Gbq7bcR17C74Ri7G3O5KfYCzglMJN07ilty33FXEBsMnQz1CPqH1cMaXRs3HVtHr8XAjnF3sKv+GIleYQzThGKwW3gwaRrV+jYUIim5XadJ9goDp4D1ZzmiXTf0PIaqg/AQy8j0jeahwq14S1Q8lDyNUSPjeLx4x4B5ofGBiUgEYu4edinb6w5zU9xkPm/K55GUK3i94gtuib8IrdXI4tjzCZF7Y+g180z6PBw4WZa7AblIwivDr8HmdPBAwRY6zTqeSJvFhqofeOrERzyfcRVLYydzZ/5GsnyiSfWK5OKwDJ4q+YgkTTgvDb+aBkMnQXIv1GI5D6fMoELbgo9UxZHOU9w+bApj/BPcrVY1+nZuPPo2ZoeVx1JmkeQZSq/NwJrKrzmta+W5jHmoxXJXgLBYSnlvE9fHnsdXZ2VfjfaLJ1zp6/rsS2RcEJxKh1nLLbnr8ZGpsDvs2HHSbu7jltz1vJ61gBSvCKQiMZEqf14Zfo3blh5gUcxEMn2ikYnEv/jZrda3sbLiS8DVhpjtO5QHC7bgwMnGmn3cGDvJ/b0j/zvTApvTTq9Vj8FmwVuqYk3OYuxOJzccfQuD3UxHf4VvWe566gydPF6yo/9+JLyZcx2ePyPSpSIJGd5RbBp9Mz5SNZ5SJRqJgnUjb8BDLMdfPth9Msggg/yU31xhEggEP6kgDVaUBvn/iFgoItU7EoD3qn9g9v5X3AvyLN8YpP8lbXl/Jr1WA3ang0eLt3Np6HAyvKMA3K1dMyJycAJXRIzk7vxNaKRKPq7P5Ya4Sdydvwkfqccf2tntMut4rXwP1x56g2pdG1qbqd8WejWXhWUR4xFEmNKXqaHDWZE6G7PDxvF+W3Obw85pXRsHOyp4Im0WZb2NJGnCubXfvvmMWJoenoO3RMWdeRuRCMVU9DXxZXMhhd01rB2xhOuHng9Ala6VRkMXtYYOvm0tRiaS8Pbpb0j2jGB6eA4AXzUXMStyFFtq9rvFEkBxTx1Wh50RvrEEK7y5O38T37WVcqTzNA7g5bLPeK18D+neUbxW/gXBci8eSpnONUPGA65qQJZPDBtGLcVosXC8s5o1I64nQK6hVt9GWW8jz2XMY2W5q8IXqPCk26JHKBAS5eHH1tqDXBySzjDPUDRSJY+X7MTmtFOra+P+5GlEqPywOe1ue+ZHU2aiFEo4LyiZexKn0mnWUalt4cmSnZzWtaIQSfGTqfmh7SQFPTW/Wj3ssxjQ2UwoxTKEAiEdZi3DfaPZUXuY+5Mu55n0K9HZjBR01zAtPJu3cq7H4XS6jQTOsLpyLyd7GxAJhDxRtBOrw8YTabPwkqoQInCbccyNHMN10eeyNPYCVGIp5wYm8fLwa1hetI2vW4r5rCmPVdmL8BDLueHo2zxXuhu93UycZzAaiRKrw4YTJx1mLctyN3BP3qb+PCQnXhIV4Qof7E4H75z+DpPDQq2+nZ31R/i08TibqvdxuLOSEQFDeaJ4J2+d+obrj7zF8a5qluVuYHvdIe7K28g5gYluFz1w2e97iGWMDxiGXCRBKZZS3R9Wq7e5wjtfLvsMB9Bp0fJ62R6GaoJYenTdgNfo69ZittYepM3Yy8H2cnosBow2C7GqIOZFjeOV7GtZN+IGolUB7vN95n3aauzhieKdA+7v/Zr91Orb3e55P0eUyp+F0RMBl0X+/QWbceAkyTOM+UPG/WoYtkQoJtkzgpXZC90zS9EeAazOuZ43shcSrwkhROnDk+lzB9xuQfQEYj2CfzGTSCqSEKMOwlvmsmYXCAQM8QgYFEuDDDLIL/K7ZpiSk5MRi12LwaKiIhISEpBKXTtCNpuNEydOYLfbf+1u/q0MzjAN8mfRbdGzuuIrPmo46r7ulrgLuTw8G/VZ6fH/X6jWtTF7/yt4S1U8mjKT50o/ptHoMolRi+W8kb0ImUjC0qNv02nR4S1VsSz+Il4t20OPVY+fTM3mMcvwkqr+wSMNpMnQxbWH3qTHqsdTomC0Xzx7mgsAVzVplF8sDxdt455hU0nzjuTaQ6tw4OTFzPmEKLy5/shaeqx6bkuYQpJnODqrkR/aStl1Vg5VhncUV0aNRS1WEKL04mRvE62mHkIUPtxfsIXVOYso72smWh2In1TN6xVfMCtyFAInyMVSfKQqbE4HV+x7iauixgGwqWYfABcGp1Ola3U7B64dsYRTfc08VboLcM3CnNa2Um/o5LaEKQz3HoJIIMTitHOko5KhHkHUGzr4tu0EMyNGsblmH8uTr+CR4u3cHDeZl8s+5/6ky3mwcAvNxh48JQp6++3bF0RPIE4TzFB1ELX6Dj6pz2Vu1FhXK53DxsTAJEb7xeMr82BlxZdUnTV39kTabBwOB6W9jXRZdAzzDOWUtoXPm/JdrXE512G0mVlx4kNajb1sHXsbFoeNCJWv23XtzAyg3engtLaVLouOir4muix6dtUf5e2RNyBGwPa6w+yoP8rrWQsIUfigFEtYemwdVbo2t6HCS2Wf0mDoQiGSsuucu9FZjdidDjQSJW9W7mVycBorK74k2zcGARCm8CXZKxyj1YxcIuXJko8GuELKhBJWpM1mY/WPNBq6WDNiMVaHnXsLNuMpVnBn4qUsPfo2EwKTmBCYyBPFH/JsxpXsby1jVtRottQcYN6QschEEtad+pZtdYcGvG+XJ88gQuXH/QVb3OYnACqRjJeGX01JTz0/tJXyYNJ0xEIhN+e+Q5ZPNItizqXZ2MOqyi8RC8TMixpDpMqfO/LeI1DuyaOpM5l34HVujJ3E4c5TfN96ApVIxor0OXzemMdXLcUIEbBx9M3cmbeRIIUny+KnoLUauTNvIwFyDY+nzsJot9Jr1ZPpHY2fXE23Wcfd+Zso6qlDJBByS/xFbKz+0e28uH3s7fj9itjosxq4O28T+f2ueBKBiE8n3jcgS+rXsDlsA0JqnU4ndqcDsVBEg6GTpUfX0WLqcf9dKhSzMnshSZ7h/7JQ7EEGGeS/k9+qDX7zVvgjjzwy4PJll132k/+ZMWPG7zjEQQb570NnNeEhkeN0On8S4tpjNfzqTuv/Mj5SDy4ISuXi0EyeP+kSS1Khq41HIZLQaOxm3alveDhlBg8XbqXbouexYlf7jEai4LWsBT/bPvOPCFH6sGbEYpb0C58zYmlCYBJj/ON5uHCrK6tGIEAsFBHjEUiZtok7jr+HRCjG7LCikSjI8onBU6JgfWO+Wywle4ZzoreB/O4aBAh4NHUmTxTvYH70eLosel4r/4IlQ8/DW+ZBomcoHWYdH9YdYVn8hTicTox2C5ur93PlkLHcenwDAN+0FnN/0uV80VzAeUEpnB+UjNZqYk3l1/jJ1QQpvPCRqpgbOYYttQf4uqUYsUDEo6kzqdK2oreb6bHoceDEYLfgK3dZsz+aMpNZ+1/GZLfyUOEH3Jt0GXfmbaTbomdFyYc8nDyDb1pKuG7ouTx7Yjfft5VS1FNHslc4epuZgs5qLgkbzq39YilI7kWtvp2FMRN5ongnVf1zZ14SJZ0WHY8V7eClzPnU6Ns40nmKkt46Hk+dTUlPPU+lz+XJkg/753zmIBGIeLNyLz+0nWRl1kKSPMNot2jJ7TzNxMAkPMRyYtSBeBhlrCr/kmuizyHTewirK7/CbLdyaVgWXjIPjndV8VLrp7yWtYAnUmdzR957vJAxn1hNENEeC1l2fAN3JFyMUiTFW6pCZzXx9qlv2N2Qy97mIp7NmEdBVw3vVH2HEAFv5CwiVOHNEyUfUtJbjxABN8ZdwEf1R2kydvNQ4VbWjVyCQiTFarfTYzPQZOjGLLUiF0m4ODSTSJU/m6r38UjKFQTKvRjuF81txzfwYubVboODxUPP47PGPLdhQYImhNH+8ayv+p47h13CfQWb3e/npXEXECj34oaKt3Hi5EB7GTYcNBt7+KQxD4vdTpOxm+LeegQImBM5GpyuKs6+9jJ21h3mscJWMSQAAQAASURBVNSZPFS4lUdSrsBgMzM7chTvnPqO+5MvRywUMc5/GM2mHlpNvbSYeni4cCutpl5sTjtykQST3cpTJR9yX+LlKPqrvmqJgtsSpnDLsfU8lT6X4T7RjPGP44ajb/N02twB8086q6vidWbm0Wi3UNhdS2F3rft/rE47ayq/4obYSb9pk0T8d1V7gUCAWCCi26LnvvzNtJhcmWkrUmfzWvke6gyd3HLsHXafc88fjkEYZJBBBjmb/6ocpn+WwQrTIP8MXWYdG6q+Z3bkaFZVfOluw4tU+VPbn1R/TfQ5zIsa+7srJf8LdJj6aDb18GTJRzQYOnk8dRZhSl/WVH6FQCBgSkgGflI1NYZ2VpR86L7ds+lXMiEw6Q+3+OqsJl4t/5zdZ1WFVmUv4oWTn1Kla+Wh5Okc7TzFgbZyNoxeyp15G6nTu9zApEIx7466CZ3VSElvPb1WAxuqfuCqqHFk+8bQY9HzaPEOxvoncH/y5eisJqp0rXxUf5Q0r0gUYikrK77kpcyraTH2IBGJeLLkI26Nv4gOs5YQhbd7p18tlrMq5zq+bSlhjH88hd21jAsYRqe5j1ClL2KhCD+ZmlN9LQgEAuYfXInNaeeOhEtoNfWQ4zuU+wo2Y3HYeCJ1Nl5SFY8WbaPN3MfzGfOwOR08VLh1wOJVI1HwatYCTvY0EKTwYnnRNm5LmILRZmFCYBJNhi4eKd7O3QmXMtQziIcLttJp0fF85lVIhWLaTL08UPABWpuRFzPnuyqIRTuo1rdxe8LF1Ok73C5028fejkQoxmi3cP2RNWhtJrylKmI8gsjtcgWa3pFwMWMDEijtacDpdBKtDkQgEKAWy7krbyPl2mZG+A5l/pDx3Jz7DgDZvjEMUfmzre4wANfFnMv8qPGYnS6xKxS4Osu7zTqUYtmAWZp6fQdLj61zW4yfYVJQCotizkXeL+bvL9jMbfFTiNOE0GXR8syJ3ZwflEK40pdzApMQCQQc76xCI1GglihYUfIhDyVPZ/7BlThwkuIVwayIkawo+RCzw0a2bwxPpc3B6nDwRMlODnVUDHj8pbEXMNIvljvzNv6kwvRmznV0mXXcnvceTpwsjbuANlMfO/qfP4AAAfcnXU6gXMOuhly+az0BgI9UxcrsRRzrPM2blXt5IGka79fs59roCRzvPM208By6LXpO9jagEst57uTH7vuMVPnzeOosBECbqY/hPkMQCoX0WgyoxXJkIgk6mwmF6G8zgK3GHjZW7+OUtoUn0majEEv5prmYDVU/8FrWtVgdNvR2C4sPr8GBk0RNGEleYWzvfy4LYyYyf8j4n8xS/lacTifVujaWHd/AsxlXkqAOoc3Ux7LjG7gp7gJG+sYiH7TbHmSQQX6Fv9wlb5BB/j/RazGw9tQ3bK09xGltK939+SiLYs7lwaRpXNGf49Jt1uH4/7MHMQA/uYZYdRAvZFzFquzrSPIMI1Duybwh47g4JJNeiwGxUMTK8i8H3O7Z0o/dAub30mc1sKvh2ACxBHB/wWaWxV9IlMqfUIUPwXJvrogYgc3hGJBtY3PYaTZ2s7P+MK+W78FLouKV4dfgI/Pg1uMbONnXwBvZi7gr8RL8ZGqiPPyJUPlxSdhwpoRm8mljHnangzv6A3mfLPkIu9PBp415ZPlG89apb1gadwETAhJ5Kn0uHcY+rggfwXctJwhR+pDfVU2MOogghRd+/UYhEpGIBwu3uINU9zTnM9ovDicQrvR1OZOVfszd+Rtp63c+EwvFpHpGcv3Q8wa8Di9kzOeH5hJO6Vq4I+89dDYTXzYWkO4TxT35m7A67SjFMiRiMQ8UbOHOxEt5LGUmL5R+Qouxh0CZJyuzF/BS5tWu4Fq7lcdSZ/JIyhXk+MZwor+NbWrocKxOOxaHFW+pimf7DQi6LXq3WFoUM5ERfkN5ofQTYtRBNBhdoaTrT39PvaGLi0MyEQtELI2bTIupl1viLwTgWOdpt1i6MDideE0IervJNZvUL5bsTgfeMo+fGA+oRDJWZi9EJPjbT12aVwSLh57HVQdeZ2XFl0Qq/dgwcikRKj9uOLqWx4p38njqLIQCAU+e+IhVFV9ic9jJ9I1mqEcQnRYtFdpmNtfs57HUmQgQUNxTx8P9Nu5hSh8eTJqOTCRlZ/0Rt1i6L/EyrohwfU9k+AzhwcIP3O5+DyRNw1+mQW83c9OxdQzzDOXcwGQA3jn9HdPCs1GeZYiQoAlhbL/z4PH+PLXb46ewfuRSei0GPqg9gMluZXnRNsr7mlhT+RVzosawovhDbj2+gVhNyE9MXaaH53C4o4JFh1cjFYmw4yS38zSX//A837WdwGy34iVVDXiNuy16ttcdJq+7mocLt/JR/VGePPERjcYuNlXv48e2MuRCCWMC4hmmCWXh0ImcE5DIVVHjCJB7Mjk4dcDz+r2cmT3aNPpm4tUhaG0mgpXerMlZzEjfWIwO6//bqv8ggwzy5zIomAYZ5DeglsiZFp6DUizlgcItXBExgoeTZ2CyW/io4SjXRE/gybQ53BQ3+f91C4hcJCVM5UuqdwSBCi88pUr8ZGo+azrOCP9Y7srfSI9Vj0ai4KHk6ajFcrosOm46to4ey+8PjTTYLLxZsReAC4JSWTtiCZ4SJb1WI5trDrAgZgLLctczyi+WS0OHc+PRt+m1GtBIFEQofXHg5O78TUwKSmNiYBKvlH/u2h0v34Ov1IPR/vF801LMGQncburjxdJPeaxoBw8VfsDT6XOJ7g/i3Vl/BLvTQZw6mBtiJ3F//hauihpHrbadWZGjeLnsM+7I38je5iLiPUPY3XCMp0t3uauTJrsFvc3MjtrDVOnaEAtEPJU2l7uHXYoDJxqRnKWxF/Bs+jxWpM9BLVYgEgh5Jn0eu+uPcUrXwge1Bwe8Pi+d/JQpYcP5sqnQfd29yZdz5/H3ONnXyNMndnHXsEt44eQnnOht4Pbj7xKi9Kaop46Hi7bSZdFR3FPP960nEApFdJi1eIqVmGxWFh1ezc1xF/LR+LuIUQcx/+BKyvuaXIYaTjvRHoHuxxQi4LygFNZWfsvBjgqW5a5nbEACr1d8wVctRdyR9y4TgpJYk3Md37eeYEXJTqJU/iSdFVqrEEm5Jf5CDDYzraZedFYTAN0WHd+2lNBt1g147m3GXr5vLeXr5uIBVbcKbQt1hk7iPENoNnRjclg51FHB9rrD6Gyu+1SJZYgFrtmXPU0FaG0m1GI5rZY+jnac5rHUWYwPSMTisHN5WNaAx30tawEhSm/kIgkzwnPI9olhefIMJgenMT9qPFNDh3O8s4r7k6bhK/XgibTZHGgvY0XabALlnjyWOovTula+bS0hSuXP8+lX8XTJLgx2C2qxnGGaUE72NbK+6jv8ZGpWZi1kRepsLgxJx4GTJ0p20mzsQSaUsDB6ImKBiBp9O/fkb+KhlOlk+USjtRq5K28TAF4SFQIExGtC+LypAKvTzp3HN7K6Yi93523CgZOddUcG5LKdIULlx5NpsxEgIK+7mtfLvwBgnH8C4wMSeevUN1xzaBXTwnK4bui5LC/cyudN+Yzxj+PptLlYHQ4c/HMbTAKBAC+piiZjN3fmbaTR0IWPzINem5EH8jdzStsyKJoGGWSQf5pBwTTIIL8BoUDIUHUgb+Vcj8VhY3nRNr5tLeGUtpXbEy4mUOHJuYFJPwlGHcS1qLo/aRoqkZRHU2biI/XgzezrmBiQxJoR1+Mj9eCx1FkoRb+/LcdXpmZl9kIuCcnkxrgLeK38cx5Lnckov1juT7qc9/vd6Ap76hAIhIiFQjwlCt7KuZ5VOdeRoA5BgAClWMYlIZkAFPQPpj+aOhO1WMG10eegFEnpNrvmgU7pmnkk5QomBafgdAqYFTFywDFNDcvi86Z8EECMOpBgpRdKkYxIpT+PpMwg0sOfVRVfcrijkvuTLifGI4hOk5b3q/djtFu4JvocxgcM4+n0ufjK1DxcuI03KvYiFAkJVnqzoep7Hi3azgPJlxMg88ThdHBD7CQeLd5Ot8UlRhfGTEQkEFKmbeKx4u08njbLfXxPFO/k4ZQZyIRiGo1dLD22jjp9BxKBiEdTZpLfVc3NcZMJU/qiEMtI9Y7go4ZjFHXVEK8JwYqdd6u+x2C3cE/+JjZW/8jLZZ9hdzr4oqkQgUDAJw15FPb8bWbFgZObjq3j2pgJxHoE0W7uY/7BlexvLwdgccx5mOwWOi060r2juC1hCiU99ZzobXDfh9Fu4cmSD4n2CGDxkbfY05TvqvxWfsuDhR+w+tTXdPWLpkZDF7ldp9Hbzaw59TUAI32HEiD3xGi38HDhVm6Om8yKtDlcd3gNL5V9xjkBiUwNzeKRlBncmbeRLN9oboidxKqcRYQovOm1Gnij7AsyfKKQCkQM9QjEU6p0neuzeLx4Bw2GTtpNffjJNTyeNouJgUmoJHKCld5cE30OSrGMVRVf8lr2Atac+hq700GIwof3Rt1MlMqfm469Q6jSm0dTZyIXu6z5NWIFb+Zcx41xFzDCdyjb6w5TrW9nqEcQoUof7ivYjFAgYF7UWOQiCS9kXsWM8BG82N9eOT9qPCa7lWzfoVRom/pFbQBrR17Pg8nTuC9/M3cNu4RIlT9Wp50d9UfcbnbPZsz72Y0gpVjGCL9YRvnFuq8TCYQ8lDKDeE0wiZ6h2Jx27srbyL35mzknMJEkz3BuP74RsVBIjDpwQPXvj9Jt0XPb8Q0U99Sx9NjbVOvauPv4Ro53V7P02Dr6+o1OBhlkkEH+KIMzTIMM8hvpsxjZ1XDUnSkCrgX7mpzFRKj8/o1H9t+DxW7DYDfjKVEiEAhwOp30Wg0oRTKkol/3oLE57ANsgs9ctjrs6G0mPCVKqnVtdJi1DFUH4SPzoNnYzcH2Cs4PSsFTqqRO34HNYWeIRwACgYBWYy+dFi3eEhVXHXwdrc2EWCBiTuRovmst4dWsBQiAF09+yv1J0+i0aOm1GHi/Zh/3J01zLcz6g0/PIBIIeTnzalRiGc+U7iZU4cOdwy4BXO2HIQov5kaN5fuWUi4NH47NYafd3Edu52mKu+u5NeEiyvoaKeqpY5hnGI8UbXNXriRCESd6GxAg4KHk6XzXeoJDHRWsyr6OvK4qttQeYEXaHAJkGhqNXTxQsIWHUmZwoK2M62Mn8dLJT9nfXsakwBQmBCXxYOEH7uNenjwDo91CuncUNrudDquWBwo+4Nroc/CXa0jyDOfm3HdI9YrgxthJLDu2nhbz32aDRvgO5fHUWXSYtVx96A3sTgcLoyeS5RvNvfnvo7WZmBM5motDMpl/6G9ZPrMiRnFFxEieKN7BrMhRqCVKhAJYlrsBcDkFJnmG82r55wBc3W+l/l71j0Sp/Knpr9BdGz2BK6PGIBIIea70Y2r17dwUN5l7899ntH8884eMp9eq58mSj/CRenDXsEuQCaU8XrITnc3IG9mLkArFbKj6ns+b8lmTcz1Bck+UYhlioQhHv5vf4iNrGOMfzw2xk7jywGvugOBLw4azpvJrpoYNJ0LpS5QqgATPUDwlSox2izuQ1WAzs6bya7b0Z3gBbBp9C/4yNXqbGSfQZupBIBDwQMEH2Jx2XstagFQg4uGibdTqO3g6fS59FgPjAxNx4mTajy+gt5lJUIfwZPocAB4t3kGv1cDqrOuwOG2sO/0dEwOTeL38C84PTkEukhDtEYhYIEQjVtBq7iVOHczBjgqeK/3bbNOz6fMY6x+P5Gc+nzqria9binnqxEcDrs/0HsKjqTPZVnuQTTX73dffkXAJJb115HVVs27kDQQr/tYW2GnW0mrqJcYjEJlIQq/FQK2+nSEeAf/QedTmsFPe18SNx94eEFYrEgh5MfNqhvsM+UMZb/8pmO1WxEKRW1w6nA4sDvtgyO4gg/wJ/FZtMCiYBhnkN6C1GNndmMtr5XsAl9V0hbYZvc2Mr0zNWznXE67y/Tcf5V+Hw+mgz2ocYGbRY9H/y8wtmgzdnNa1MNwnGqVYRrupjyMdlYwLGOZeiIJrCNzydwG4Zrv1VxdLTYYudjUcI0juxfrT3/PS8KvZ01RAqncEqyr28kjKFSw4/CaJnmE8mTabO46/R7W+nW1jb2fpsbfpMGuJUwfzZPoc7s3fTJWulRlhI0j2Dnc7AU4Ly2GIKoAYdQAdZi2Pl+zk/qTLGeEbS49Fz43H3ubikAwuCE6j2+py/nLi5PXhCzDaLdxT8L5blAkQ8FjqTCJV/jxZ8iGntC08kDyNQJkX3jIly4u2YbbbeDFzPhqpkq01B7kkLBONWEFRTx3ft5Yyf8g47il4f8DsWKjCh1ezrsVXqkJvs7Du9Ld81HAMgMvCstjfXu62kV4/8kZ+aD3JG5V/2zx4a8T1pHhF0GcxUNhTR0VfE2aHlaMdp7khbhLft57gqqhxrKz4gh/aTrpv5ydT8+rwa9HbzHzfdoIkz3DClL582ngcrdXEvKix/NhWilwk5fu2E9yecAktxm4eOEvsXTPkHK4aMs79Xmg39XF/wWZmRowiysMfu8PBdYdX4yPz4OGUGe75niujxnJpaCZOIFTpA7gW7nqbmTClj3tG6gztpj62VO8nzjMEpUjKyd5Gvmgu5J7EqexvL2NCQCJlfU14SOT0mvVMCk6l2dTDkY5K5g0Zh1gg4puWYp78O4GhkSh4bfgCt2vd0tgLGOkfy9Jj6+i26FGL5aglCpqM3YgEQp5Nv5J4TSiBCk/Mdiu5XVXclbfR/R45Mxe0OmcxsZpg+ixGdDYj9+VvplLXgkgg5IrwkexpzkdvM/Py8GtIUIdQ3FvnbsM7g0Qg4pWsa0nzivzJpsbJ3kauOfQGAGP9E1yV0RO7cOLksrAswpS+vFHxJTKhGLPDhgAB9yZO5XhXNWV9jbyevZAQhTedZi3Plu5mX1sZL2TOJ8UznM01B3in6jtuT7iYS0Iz/6FosjvsHO087XakBLgncSpTQ7P+4WbMfzJmu5W8rmo8pUriNSEIgEptC22mXrJ8Y1D8EzNggwwyyJ9sK/7aa6/95gdetmzZb/7fQQb5b0EqEhPt4WofuSA4ldsTLqbN1MeSo28RLPdC9l/8g/yPcDgdVGpbeKP8Sx5KmU6A3JMGQxdPFO/g4ZQZhCn/WqHYbOzm5tx1NBq6eSJtNlk+0TxStI3crioWRk9kTtRot3ATCAQ/EUe/JpY6zFruyNtIla6VycGpvDv6Jp4s+ZB97WWk9ITzYubVdJj7ECKgtLeBaT++CIBYIEJvNbEyayGvlH/O/KhxeIikvJA5n+dKdzMxKIkAuSc3x01me91hLg5Nx+50oreZ2dtchN3pYEXJh0wLy+GrliJ0NtdO/dSwbMzGHh5JuQKRQEikyh+d3USg3LM/HNXlhJagCcVss/BU+lxOaVuQiyQU9tQQpw6m0dDF1UNcbV8+UhUzIkZwd/4mZkeMYohHAAtiJridAiUCEXOixrCt9iCNxi5uO76Bt3KWoBBLWRgzEZ3NzFctRW5TDZVYxhvZi6jRtQ8QSwC35W5gTc5ivGUefNtcjFrqWuC+NPxqXi37nFmRo1hT+ZVbLF0SMpxDHeV0mLXcenwDT6XNZXd9Lia7lQRNCNH9wa3r+xfNeV1VXD3kHLbXHeLC4PQBj+0r8xjQ2uUv17AibQ5rKr/CS6pkTeXX2HAwNSyLcKUve5uLMNot1OnbEQlE+MhUZ92XGt9+A46/x1+uYUpYJvMPrsTudPBcxlVMDc9iV/1RanTtaH1MvF7hmuN5MGkaTaZubs19F5vTjpfUgwuD03j+5CeAS2AsjbuApUfX0WPVU6VrpaS3HqvTzqsVe2gy9fB46iweKtxKr9WA1mZCiIAn0+YQrwkhUOHpfn9n+0SzLP4iXi77DACD3cIb2YuI1QQjEgjxlqnQ2ox0WfWuCujwa4jxCCS/u5oKbTONhk6X6C/5CAdOhmlCWZE2hzvy3qNW385TJR/x1ojr8RcNXEyEKLxZGD2RCm0zDyZNQyGW4iGWse70d5wflMKDhR9wWWgWc4eM5cmSnRT31PNVSzGzIkbyTUsxtbp2AmUa7E4HrcZe7E4Hd+VtJN07ym1mUatvx+b4x/mOHRade57xDBurf2SUX5xbDP+3YXfYKeyu5Y6895AKxbyZcx0igZAbjqzFaLfwYubVZPvG/FcLwkEG+W/hN1WYhgwZMuBye3s7BoMBLy8vAHp6elAqlQQEBFBVVfWXHOifwWCFaZB/BrPdSq2+Az+ZGh+ZBw6ng2pdO2qJnAC557/78P4yui16Zvz4IjqbiRSvCJYnz2DZ8fU0G3uIUvmzZsT1vzmA8o/QbupjeeE2jndXIUBAoNzTHVK5InU2YwIS3LbEJrsF+Vk7rv+outRrMbC7IZeyvka+bilGKZJislu5MCSdNK9IzgtKRiaS8HljPk/3h8kCPJ0+l/H+w5CIXNbbOCFA4UmrsZc+qwGxQISHRI7d6aDR0ImfTMPqyq84J2AYGqmKLTUHONJZ6b4/X6kHT6bP4fPGAqaGDWdb7SHCVb5MDc3iseId5HVXDzjueE0It8VPQS2SIZfIeKPiS5oM3VwQnEq2bwzftJYg7M/pWV/1vdsM4o6ESxjjH8fRztO8XPYZL2VeTbjSjzpDO3flbeLGuEmkaCIo1zYz2j/WHbh7hklBKdyaMIWZ+17GaLcwwjeW2xOmsCx3PW3mPhI0IbyWtRCdzciXTYVk+URzWtdKgNyTALknIoGARYdXc0PsBZwTMAyLw8btx99luG805welsCx3A06cCBHgwIlcJOG1rAW8VfE1N8RNot7Qib9Mw7Lc9Thw4i1V0d1vFnJP4lQuDE7HQyKn3dTHD62ltJh62F53mJVZC10Lb6cDX5kapcg1FyQVit1tX7Hq4AHVyl+i0dDFmsqv+aI/82uoRyB3DLuUW3PX82jqTHbVH+NYvzPgGaJVAbySdS2+MjVV2laKe+qYEJSEn0xNta6NZ07s5qHk6ZT01nOovYIvmgtQi+WsSJvD8yc/psHgCoGWCcWsH7WUGI/AATb89fpObjy6lrazLMoT1CE8nznfLazAJT7ajL2keUciFUloNfZS1FPLSL9YZEIxVbo2VlXu5YqIkbxfvY8FMRPZWP0j1ww5h2CFF+E/03rcazFgc9rdItNgM2Pqd1T8pDGXGeEjKOypI1YdxId1R7lyyBhajL30WPTk+Ma4bb/bTL3cdXwjZdom931PD89hSeykf/j90mXWcfvxdznZ14hIIOSqqHF8UHsQs8NKsMKLd0be+Isi+D+dBkMnNx59m1ZTL1KhGAECzA4rfjI1qwfbwQcZ5J/mL2vJ27x5M6tWrWLdunXEx8cDUF5ezuLFi1myZAnz5s375478L2RQMA0yyO/HZLNwuLOSe/vbxM4gF0l4M/s64jUhA2aL/graTX08WPABBT017useT53FuIBhbrFUr+8gv7uGiYFJqCUK2ky97Gkq4NLQ4b/qXNhs7OZwRyWtxl42VH3PA8nTMNmtTAhMJEDuSYuxh9tyN1Clb3PfJtEzjOcy5v2sUG439eEEvm0ppt7QydTQLE701OMj9+DD+qPMiRyDVChi6bF17tvMiRzN5OA0Osxamg3dvFT+GeP8E5gYlMTjxTsRIODuYZfiI/PggYItOHCyLP4iRvrG8l71D9To2nl++HxEAiEf1+eyo/4wq3MWEyj3pMui582KL/mi+W9OeVNCMrghdhJfNhUwMSgZuVCC2WHjeFcVEoGIYIWXa4am8AM6zdoBz29hzEQmBaVisJuRIOKxkh08kHw5SpEMpViGr9QDiVBMh1nLD22lrKrYy4q02aws/xIPsZyHUqbTbdGzqXofOJ3cNmwKIkR0mPv4rCmfIR4BvF6+B7PDxqvDr+VgeznDfaORCMX4SdU8XryTSl0z10ZPYF7UWJ468RHftZ5gfMAw7k+6HKlQzAuln7CnuYAF0RPI9BmC0+myoH+oaCsigZCHk6fjJVVxV94mbE479yROxVOiJMd36K+KpgZDJzcdXceNcRfwSeNxOs1abom/iEeKttFnNSIRiHhx+NW8dPJT92yVWizn3dE34S/T4Oi36m4wdA1oM+uxuCo/H9QcINM3mrvzNvFE2mxWln/B6f7QYGl/xpVGomBNzvVE98/hdZq1XHPwDbfF/JyoMbxb9QN2p4NETRgvDb96wPv/l2YBASx2K03GbhYeehNd/6zhfYmXEacJ/lmx9I8w2MwoxTKMNgsSoQiLw4ZSLMPmsGF1Oga0k52JbthWd8h93fMZV7nE3D+Y1THaLBzqqOChwq28mDmfTJ8hnNK2cMPRt7k5fjJTQjL+YUvffzINhk4WHV7t3hzQSBSsH3njHzongwwyyED+shymhx9+mNdff90tlgDi4+N5+eWXeeihh/7Y0Q4yyCD/scjFUkb5xblzcc7wQsZ8Ev4FYgnglyJtz1zfZOzmxqNvs6LkQz5vyqfTrOWe/Pd5o+JL1lR+9YuW5e2mPu7P38LTJ3ZhddpYN/IGDrSX88LJT3i1bA8txm63WBILRMyKGOVuz7sn/323K9vZ+Ms1NBq6eKnsM7bXHWZn/RF85B7cX7CFDpMWuUjMPfnvD7jNB7UHye+u4WB7BbGaYF7ImM++9jIsdhu3xk/hidRZpHiH801zMQ8mT2du5BgsDhvzD61kbtRYnsu8CqVIylfNRYzwG8r6UUsJlHtyrPMUO2oPc93Q8xGe9Sp2W/SIBULOD0qhXt/JE8U7EQsEjPSNJdsvhk6Ljk3V+9wzS29kL+L8oBQA3q36AYC1lV/TadESpfKnzdTH7cffw2K3UdJTT72hk+OdVShFUhI9w9DbzJzWtVLQU8Njxdt5+9Q3tJv7uDQ8iy01B+mx6rE4bZwbmERBdw2Ppc5CJhTzQ1spF4akIxaIeLx4Bzcecy2AXxu+gHlRY/GUKrkncSq3xl/E/UmX4ylR4nTC9bHnE6LwJlYdRKImjBh1AL4yNXHqYOxOB48W7+D24+9hc9qJUvkTovDGU6xA8g/ey0IERKr80UgUlPU2cllYNl80FdBnNeItVbF17G1YHDZ3RQhAazPxQ2spp7QtHOs8zd15m3i57DMOtVe4W82ECPiyqZAkr3Duy3+fYIU3DqeDekMnIoGQp9Pnsn7UjXhLVfRZjZzorcdotwCu8OV5Q8ahFElZnbOYBdETeDFzPhKBiOuGnovy70Jh//7zevZliVCM3enE0p8B1ms18Gbl3n8oWJxO508+Yz0WvfuxFWIpYqHIfVksFP9ELH1Qe9Atls5Yut9XsJnjXVWYzzJy+DkU/d9RH0+4h8x+g4d4TQg7x9/xXy+WHE4H+v6q3RnMdhs6m2mA2cz/B4x2i1s0git/rfsPxFEMMsgf4XcLpubmZqzWn3552e12Wltb/5SDGmSQQf6zaDdr2X7Wzi/AW6e+putf8GPVYepjedE2d3XpTFXnkaLt7G8vx2AzIxOKSfWOBFyOdrP2vUxpbwNCBIwLGDagTe9s7E4HYSrXfMPG6n3cW7CZ71pPABCl8scJXBI2HLFAxOtZC7gpfjIvZLoqOdPDc5AKf352YIiHP3MiRwOwq+EY9+S7TBtuS5jCyvIv0dlM+Eo9WJOzmGyfGADWVH7NnKjRhCq9SfQM4ZXh1zA+MJFLQzPJ9BnCS6WfIRNLKOiqZmpYFoXdNVwYks4TxTsRAEc6T/Fy2WcsPLyaoq4ajnRUcnf++2ys+ZH9bSe5MCQdAB+pBwtiJlDe14TOZubjhlzuSroUk92GVCTmQGs5GrGCy8KyyfEdyhOps3mtfA85vkO5OCSTFzKu4v3qfbSbtayq3Mtwn2ieKtlFoNyT50+63NVO9jawvHgbB9ormD9kHLEeQdzZb1ld3FNPWV8T9yRO5a3Kr9lWd4iddUdQimQ8VryDr1uK+bghl/uSLufD+qN83VKMSCDkqfS5yEUSguSeVOvb3ILBV6ZmZsQoPCVK6g2dlPU1IheIWTtiCQmaUE7rWrE7HMiEYp49qyroxImP1IOHkqcDEKry5URvgytHymGj3dSH9iw76nZTH0qRjFsTLuLhwq1obSY2Ve9jSkgGF4Wk81z6VTQau7kvf7NbiGV4u9rZXy3fQ2lvI3sa83HgJNEzjBTvCHqtBow2CyaHDblIws66I4zyi0culOAv0/BM+pUsT5nBx/W5KEUy1uQsZnnyDM4NTHKLD7VEwSWhmWwfdwexmmBkIgnDfaL5eMI9ZPnG/GYnNafTSZWulSVH38LSfzxCBNQZOrnj+Hu0Gnt+8Xanda08ULDF1Z6Ky6TlnnyXqYjFbuO0tnXA5kKtrt39vwAWh42P++fkpofn8OmEexmmCcXudPB+9X4MNjMtxh46zqp2dpj6BhyTQizFT6Z2izuxUESA3PO/XixValvcM0veUhW+MjVmh5Ubjr5NRV/T/xvRZLRbyO08zWtln9Nl1mF3Oqjoa+ahwg8GvJcGGeSv4ndPCp533nksXryYdevWMXz4cAQCAbm5uSxZsoTzzz//rzjGQQYZ5N9Ih1nLTcfeptnY4wrjDBvB5toDFPXU8UDBll/MaPmzsDrtNPcvjJ5InU22bwwPFnzA8e4qTmtbyPGNwVem5q5hl2C2W9nXXoa2P4D02Yx5DFEFuBeAf49EKOLC4HQsDjvft55w//DOHzKOaI8A5CIJU8OGMykoFZFAiMFmZrhPNB+NvwuhQICpfw7mzND1GYtzL6mKRTHnUtrbQFFPHeCqBPjJ1SyJPZ/1Vd9zR8IlPFnyIVcNGYdMJObysGy0VhMSgYgP6g9isFqIUPnhFEpoNHRxb/JlHGyvYHzAMB4s2ML9SdMo6K5hUcxE7sh7j5vjLmS49xCOd1fzYNFWwNUOFqLwJkLlx7rT3/FM+pX4ydQ8UrSdi0MzCFUYmRySxpMlHxEg1zA1NIsjXae4TJlFj1XPvKixBCu8sDrs9FkN3BQ3CSEiAhVeNBu7WXf6O16v+IIn0mbjcDqIUvm7hcVlYVnsbsil0djFKW0LG0YtJU4TzLbaQ3zdUkyHScv9SZfzY9tJ1ld9z+5G14JZKZKyeOh5tJn6ECAg2iOQTxqPY3HYWJ2zmI/qj/J+zX4+bTjOK1nX4i/XIBWJqdd3cNvxDWitJl7PWoBKLOOJkp2U9jbyUubVBMo8OdnbOGDh3ms10GM1EKn0Y1nuepqM3byYOZ9wpR8vnvyEOVFjiPUIwmi3sK3uEA6nnblR44hRB1Kn7+Sh5On4ydScH5jCyoo93Jt0OSFKb8QIeSFzPlKhmBUlH1KubSJM6cMHtQcIkHuyPHkGtfp2us16mozdXBSSzjDPMOI1oeR3VzNvyFh8JSr0VjN15g7mR4/HV6ZGIhQRKPdCIR64AaCWKAYIA5lI8rtttI12C8U99e5q2Vs519Ns7OH2vHep0bfTadERqPD6ye16rQZ3IPRdxzfyRNpsbs97lwZDF8ty17MmZzFXH1zJpOBUbkuYQpdFx5Ija4lQ+fJ0+pUEyD3xl2t4M+c6PmvMY07UGLylKp7PvIr3qn7g2uiJmBxWbsldT7jClwdTpoPTyeMlO2kz9vJK1rUE/cxx/S/gxCVInTjdM0tCgcD9ejucTpxO5y+X4P+H6DD1uR0cHTiZFTGKm46tw2C38ELpJzyUPB3Nb5hBHGSQP8rvnmFqb2/nmmuu4YsvvkAicX0h22w2Jk+ezIYNGwgICPhLDvTPYHCGaZBBfj9ai5H97WU8XbqLN7OvI9ojkEptM0uOruWp9LmM9I39yQLut9Bj0Q/IX9JZjYAAD4n8J//bZOimUttMlm8Mqn5b8cMdFYwPSHTPnDQbu7kn733KzxoavzluMl0WPQEyDReFpGN0WN0WzXang2ZjNyKEvF6xh69bSty3Wzz0PKaGDidQ4YXD6aDN1MePraXobGbOD05BJZbx4slPkQhELI49D5lQgpdUxYneej5tyOO6oROp1rVzR957A3aAp4XnMC9yLHYcdJj7+KThOKW9jVwdPZ6vmoq4KX4yPRY9y4u281jqTF48+QmRKn+WxV/Ec6Ufc6zrNFNCMrgl/kLerNjLx43HyfAewnVDJ3LH8fd4I3sRjxRtx0+mRms18VDKNHykHjxRspPp4SMY4hGAwWZm6bF1WBw2rooaR3FPHYU9tQgQ8Orwa7A7nZgcFgq6aknzjuSFk67FyJGOSqaF57ht0bVWI4+nzkImErO68mvKeht5IHkaeZ3VXBNzDj5SD5YeW0eVrpW3cq7ny5ZCttce5r6ky3DiMuR4uewzFsZMxOl0sr7qewDWjljCyvI9XBaWTbwmhBp9uzsvylOipNdqAFz5TdcNPdftkFija+eGo2vpsujwEMsJkGuo0rUhQMDzGVchFgrdM0sRSl9EAhHV+jZEAiGPpcxkV8MxinrqeGX4tZisFgr7ahEA3lIPNGIFT574iEdTZ/JlUwFzo8bgI/WguKeO0r5G0rwiidMEs6VqP/NjzkEAnOipZ4g6AKFAiNZq5JkTu6jrb7F7IGkaUSp/vmguYHvdYcKUPryZfR3728t5tnQ3arGc9aOW4iGSIxQKUInlSIQitFYT6p/5fJyh0dCF3elwGwG0m/rotRqIUvn/ptZZrdXIty0nSPOOIMojALPdSn5XDTKRhDh1EKr+x7Y7HRhsZtQSBWa7leNd1dz5d+91qVDMyqyFtJh6WF60DYBs3xgq+prptRrwlCh5e+QSIlX+7tvorKYBn3+9zYxUKObHtlLuL9gCuPK+HDg51uky1nguYx5j/RP+9NZgh9MxwFb+7y//q7A7HZzStqAQSd3ntcHQSZ/VSJw6+F/SEv2fwM/lIAIEyDS8mbP4fzrWY5C/lr88h6miooKysjKcTifDhg0jLi7uDx/sv4pBwTTI/yJ6q4k+mxFviQq5WIrFbqPD3IeHWP5P77idaQlpN/UxVB2En0xNi6mXY52nGO0Xh0ai/ENiqdusY33V95wTkEiKVwQWh5W9zUWIBSLODUr+WdFkddgHzJicPazeZurl7vxNnOxtRIiAKI8AqnSuFuHrYs5FJZYxxj+BOftf4e7EqVwYnEadoZPT2hYOdlTwdUsxAMEKL3c1a3HMecwIz6HdouWGo2uZFpaDVCTGaLPQaurh2/7WvafT5lKrb+fCkHRm7X+FIR4B3Bw3mduOv4vd6SBWHUS0RyBf9psu3DB0EqMD4vms4TghSh9iPAJZVbEXT6mSKSHp+Mk0nOxrxFOi5ImSnYwPGMbC6Il82VzoDjv1landZgzzh4xjclAaFdoWAuRqfmg9SY7fUEKVPmyu3odcJGXekHF0mLU8UbyDQLkXi4ZOZFnuBiwOG+DKdrpz2CW0mnqYGprFUyd2cVvCRdyT/z6tpl7UYjk3xU3mg9qD3DHsYp4s+YhWUy9ykYQAmYY6Q6fL8jp9DpV9LUwNG05FXzP3FmxmfEACS2InsaLkQ0r7Q3cnBCTyXZvr9cv0GcLMiJHuBfFFIekke0awuWYfT6dfSWlvAyaHlVfKPnef+8vDslkQPYFg5d+CTwFqdG0sObqWboueGI9AxgUkECj3QiQQkKAJ5fa899CIFTyQdDmeUiUPFW6lzdTHo6lX8ErZ59ybeBnrTn3LnCFjKO1p4J2q7wB4Jv1KjndWMcJvKHflb0ImFDPWPwGVWM7HjbkIELhMOPyGIhdKWXD4TZI8w5gekcP9+VvwkMjxlalxOp2c6s9BejNrEWanjTvzNmJx2FD0O/cBjPMfxq0JF/F1czEzIkbgKVXSYOhkY9U+ro8972cd3xoNXSw99jZWh53VOYtRiqQ8ULiFsr6m32XOYrRZBnymdRYjZX1N9NqMjPaLQyoSU97XxLHO00wLz0YjUWK2W/msMY9nSne7b/dCxnxG+8eht5nZ3XBswELXU6LkrRHXM8Tjt22w6qwmvm0tYUXJhwOufyTlCiYEJqIS/7KI/CO0GHtoMfaQ6BmKVCShw6yloq+JFK+If0uL38+JtX+XgPt3orOaeLZ0t/u7FOCj8Xf919rGD/KfwV9m+nCGqKgo4uPjufjii/8rxNIgg/wv0m3W8V3bCab98AKHOivpsxgo6a1n5r6X2VF/hD6L4Z+6/ypdGzccWctdeRs51R+WuPTo2zx9YhfftZb+of55o93Cxw25fFB7kFty11PUU8ve5iKeKd3NihMfcqK3np/bx/n7gfyzF39OwOFw2VEvT7mC2xKmMM4/wf33iYFJvH3qGxw4ebZ0Ny+XfcbNx9ahkSpp7s83ujnuQtaPXMoFwakAnNa1up7/0bXobWa+aC5grH8CO+oOu8XSTXGTKemtZ/WprznSeYqrosZRpW1FazWR4R1FrDqIm+ImsyjmXKaH5+ArUzM2IB4REKTw4uWyz3ikaBvLU2YwJSSDR4t3cNvxdxmqDmKMfzzPZ8zjnIBENlb/yLlBScyMGAngFktzI8eQ7h3FVYdW0mHuw0/uSbjKl7vzN/Fu1fdMjxhJgmcoqyu+4oniHdQZOinsqUUhkjHkrJ39LJ8h+MrUbKzexw+tpUwKTmF50Xaey5iHj9QDrc3EM6W7qdG382rZ57w8/BoCZBpMdit1hk4A7k+6nNPaVi4Pz6ZO38G9BZtRiCR0W/TU6tu5M+ESkjzDceL8iVh69sRu9/na01TAyb4Gns2Yx+1572GwmWk2dA849+3mvp+0IbWZehELRfhK1cR4BHJz/IU4nE7XIl8o4f6CLaxInc0LmVchEoq48djbLI2bzMrsBWys/pFmYzcOnMyMGMndeZvcYmliYBJOp5MxAfEke4bzcPJ05CIpk4JTye+3e780NBOBAF4p+xyhQMA5AcM4rWtFIhShkSoIlHuyJPZ8boybRJw6GF+ZGhsOEtShvJG9yP25cJ2LaO4cdgkLDq1i9amveL9mHy3GHm48+jYfNRzl5ZOf/ayJid5mps9ipMOsZcnRtdx2/F0Kumsx2220mvqwOv9xlhEwQCw5nU4qdC3cnPsODxRs4WBHORV9zdxwdC1vVHzJ500FGG0WOs06NtXsG3A/b5/6hi6LDk+pkvEBiQP+FqcJ/l1RBB4SOeP8Ewa4UgYrvBjtF/+XiKXbcjdw47G3ye+upcus46mSD7nt+LvsbS4aMNf2r+LnhNG/QyzprKYBl/+Vr4W93wRl31mh19A/S/sz5juDDPJn87s/cQaDgUWLFqFUKklKSqKuztWfv2zZMp555pk//QAHGWSQn6fZ2E2jsZtd9cdw4OS+/M2srPiSW469g9VpZ09Tgdvt6o+ikSiI9PDHgZO78jYy7+DrtJhcs0wp3uG/eaD8bBQiKZND0olWBWBz2ll6bJ17Z3p8wDCGqoMGZMz8FgLlnrwwfD4rsxfiIZZz+/F3OTcomcdSZ5LjOxRfmZrbh13MDUPPR4CAjxuPo7WZePXk5zyRNpsnUmdxeXg2PjIPbo6bzF3DLmWUXyw3576D3mbGT6ZmVfYiVhTvdC88h2lCGe0XR1j/7ubTJ3ahkSo4LyiFp0o+4s5hl/Jg8nSC5F6oxXIuD8vmzexF3Jv/Phur95HmHYWHWE6nRcfCw2/yaPF27E4HoUofbA47J7rriPYI5KkTH/FNawldZj22vxOo+v5ZLQECVlXuZUXxTl7qDy/ts5poNHSxv72cTN8h1Bk6kQrFvDL8Gj5tzKNc2wy45pzmR4/HW6rihqGTePPUV8SrXaYT7cZe7kmcOuAx5w8Zj0ggGLDTLhII8ZNrmBAwDIvdikai5L6ky1g7YgmPpszE5rAjFYo5Lyh5wH2dG5jM4fYKnsu4ivEBw5gV6XIhHO0XT5/FyOKYc2kwdrG133Akur8icaC9nJdPfkanWUu9voMmQxdmu5VHirbTZu7lgeRpPFuyi3TvKN6v2Y+vzINWUy8PF23lrvxNLD32Np1mHa+WfY7OZqbdpMXssHFP/iYCFJ6kebkMRBI0IcyKGIVCLOXdqh9ot2gZ45/AMxlX8kHtQe4adilx6mAWxExkVcVejnSe4tnS3SyOPY8olT/baw/zatYCFg89j+WFW1leuI0lsefzYuZ8vmkp4dvWYk71n4czNBt7cDgdTA/PAWBD1Q9c/sPz7orelUPG/myVY6g6kNUjFqMSyeg0a6nQNiNAwNPpcxnlFzvAle63IhAICFf6kuodgRMn9xdsYcGhVZjsVgLlnoz1j8dkt3Bz7joaDF3IhGKuGjIOkUBImbaJu/M20WLsZvGRNQPu91h/DthvXeh2mPp4pHj7gOH+ZmMPjxfv+Int/T+LAAFCgdBl0nJ8AzcefZv97eUASAQiBP8jA0NOp/Mn7oO/5kbYZurlhZOf0NJfge8y61hT+TU1urZfvM2fSaOhixuPrsVgtxAg9+SK8BGAa4NldeVX9P6Tm4ODDPKP+N2C6f7776ewsJDvv/8eufxvOzvnn38+W7du/VMPbpBBBvl5Os06bjn2DkuPvc2NsReQ6uVa0OxqOIbVaSdS5c/rWQvw+yfDGgPknjyXMY8Yj0AcONHbzIgEQlZnLybOI5gGQycdpr+FZTYautwVm18jSOHF69kL3RlKADEegTyYPP0PB0xqxAqcTrg7fxN2p8NlMd6Yz43H3uZ4VxU4IULlx13DLkWAAKVIynVDz8VH6sF5QSloJAqsDhsBck+yvKN5+sQuHP25UzMjRlLYXTcgi+lkXyPftJQwxi+BCQFJvDfqJhLUIRR0V7MifTbPl37MgbZyyrVN2JwOdtQdZt3p77g2egJ7m4v4ojGfN3OuQyoUY7BbsDsdhCt9eTJtNqe1rZTrminrbWLx0PO4LWEK+9vL+Kj+KIBbpH3ceJx9bWU8l+HKvyvprQdccx5TQjJ4rHgHATKNe2Ga5BmOVCh2Ox4uT57BS5lX80rZHrbWHmRCYCIvZl7NutPfsrLsC4KUPjxz4m9tVgqRFI1EyeNFOzmta0WAAJVIht3p4IGCLRjsVnQ2M9+3nSBc4cvSY2/TbOphiCqA07pWXivfM+CcvXTyU0b5x3OgvZwnT3yEj9SDNSOu57vWEsRCEWP84t3VxisiRvBS5jXcOewSwFWRMdgsXHtoFe/XHKDPaqSirwmt1YQIIY+nzWZb3SG21R1ie+1hXsqcT5dZR7WuDZPdSoBMw12JlyIAnkybg59Mjd5mpkbfzn1Jl3FhcBqV2hbClD4UdNeS4hXBI0XbaDP18syJ3RR01/BkyYc8mDydZ0/sZu2I65ELJZwflILACUa7mWnhOdydt5EHCregEssJUXrzUOFWlh1bzzkBiRjsVp4tdTkLxqqDkQrFNBq7uPX4Bi4Lz+Hi0AwA9/twdfZi4jUhiH6h4uArUw+owshEYuI0wX+obfYM/nINT6VdSVR/RdKBE6VIypqcxYQpfRELXXb7MqGYN7IXcX3MebyYeTUigZAro8ZwtOOUe2Zp+7jbuTluMgBfNxf/ot3/2dgcdva3l3O4wxX0/FDydO5PuhyAAx3lA+zZ/wwCFZ68PPwaoj0CsTsdVPd/5h9ImvaL7cL/bbgcEds43FGJ0eaqbDYbu/mk8Th91p8Kj26zjgcLPuDzpnxuO/4unWYtr5Z9zra6Qyw5unaAe+FfhYdYzjn92XhvZl/HjXGTuTluMgqRlGnh2f8T52WQ/2x+t0verl272Lp1KyNHjhywC5yYmMjp06d/5ZaDDDLIn4VrJ3c8T534iM01+7k0dLjbjQ1ci0uv39Hy8mtYHDa36xy4WiO6LDoajV0sOPwmyZ7hPJI6E7Pdyk3H1iEWCHk9eyHBCu9fvE+d1ci+tpPobWb3dbX6Dqq0raR4RbiNIH4PJoeVx4q348RJunckDyRN5+GirdidDl44+QkvZM7ngcIPuDA4nbuHXUqgwtNlQ93bRJwmCIvVzjctxYz0i2XxsTUoxTJ8pCrqDJ3sqDvCmznXsShmIma7jRZjD5ND0vihrZR6QweXhmVyX8FmHkiaxpVR4yjvayKvu5q87mquihrLofYKd3DsaL84poYNp97YRZupd8BiT2czIRIISfWOYMnRtQC8OvxahAKBe8h9RvgIFsZMZHvtITZU/0CbqfcnwjjSw58afTvTwrPxlal5s3IvAPnd1XzRXMBjKTNx4EQulLhed12re+bLbLdysKOCd0fdxB1579Fj1eMpUXBr/BR21h9FLBRSrW9zzyx5Sz14pGgbraZeinvq6DBr2VJ7AAECLg7N5NuWEq6MGsPqyq8AVxvePYmX8XjxDkp7G3iz8iseTJrGVy1FpHpFsLpiL8e7q8nrqubd0TdxdfR4RvrFEaHypUbfTqImjGfT56GRKLjuyGq0NhMne+uZGT6CV4ZfS49FT0FXDecHp7Io5lxOaVvosLgqSEKBEEd/hVAqEuMr9eD18i8IUnixMmsh5X1NaCRK3q36gXMCEnE4nRR21+IpUdBt0XNOQCJXH3oDcFUbHkiexsryLzjWdZphraFsGXsrJruV5UXbuCA4DX+5BidONBIlL2RchbdUxcOFWynXNuMlVaLubycb5z+MB5OnUW/o5KZj61x29U4nJ3oaBpzX79tOEKr0+dlw3XZTHw8WbnEv8EUCISa7leuPvMXqnMVuw4DfwtlzTHanA73NhNlu+9vf7VbK+prwlnqglii4ODSTc4OS8ZGqEAvFDPcZwu5z7kYllmO2W5nZ18wVkSOJVPlzeVgOQoGQRM+w3xS8KhaKmBCYSLWujThNMBMCE3E6Xc+vRtfO2IA/3/BBLBTiK/NwfybAtckj/R8xWKjTd7Dk6FtorSaeTp9Lkmc4txx7hzpDJ1qriRkRI9CcVcVUieVcH3sey3I3UKVrZcp3z7hDzK8aMu5f8rr4yDy4NX4KFofN7Yp4eVgOk0PS8ZOpf3YTYZBB/kx+t+mDUqmkpKSE6Oho1Go1hYWFREdHU1hYyPjx4+nt/c/1wx80fRjkfwmdzcSBtjKEAiGPFm0fMKMgQMAzGVcyyjcW+T+xu9zQv4A7YynuJ1PTYOhCiICn0ufyWWMe+9rLSPGKoMPcR7OxB5lQwpoRixmmCf3Z1jqjzcI3rcU8XrwTcFVDWk291OjbEQtErM65jhSviN/dlgdQr+9gVeVelsVfxNpT3zAxMIlPGo4zK3IUDxdto9OsZUZ4DvOHnMP9BZs52dfI7MjRLIyewItln7G3uZBx/gmcH5SCt0yFl0TFZ415jAmI58WTn3F/0uX0mvUM1QTzWPF2poRkMNo/nqsPvkGPVY+fTM2y+IuwOx382HbSnel0hquixnJxaCYGm8XtHmZ3OghReNNrNaC3mfGVevBG9iLyuqrY1ZDLktjzeaxoB3cmXoLBZkEiFNFu7GVCYBIn+hqIUwezve4QnzTmDTAOuCb6HBI1YVT0NZHgGcqhjgo+7K9QvT1iCX5SDcuLt7I45jzK+hp5o19UneHJtDmoxDKeLPmIx1NnYXc6EAoEbKz6kUVDz6XLosNH6sHW2oNc2m/yoLWZeLfqB/xlGh5OmcGRjkrSvCP5tOE4V0SO5IumQmZEjOCO4+/yUPIMvmop4rqYc3mu9GNujZ+Ct9SDZlM3L5z8hLuHXcqzpbsBAc+kX0mbuZdbczegkSh4Km0ujxZvp8nYzTBNCA8mT2dZ7gZiPYJYEns+GqmCDrOWtZXfclvCRbT0t+OZ7FY0EgV6mxm708EQVQDLEi7ikaJtRKsCmBScSo/VwNpT3yBEwKOpM2k39/F6+ReAy2Rgb3MRhzoqWJE2myilP8e6TnOgvZzp4SPwFCuI0QRxqKOCwu4aFEIp0yJGYLZbEQhcrYQXBKdhsJnxkqqo6GtGKhIzROWPSChCLZZRoW1BI1Zwd/4mTutaUYikpHiGc7TLJZgXRE/gyv7Q3rMp7K7lhqNrcTidPJU+l3ClD0uOrEVvN3N7wsVcFpaN8le+C3otepRiOb0WPdvqDjMjPAe1WE67WctnTXlkeA9hZcWXiBBQpm1yfcekX8lI/3/c7tdnNQ5YgPdZjShE0n8YFHw2PRY9EqHIPbOks5qwOe1/2sbQGTrMWp4q+Yj97WWAq2VV27+R8crwa8nwjkT6B1qR/5M4I64Lul3umGqJnD6rEYlAxBvZi0jyCv/JubHYbRztPMUdee+5r7sqahwLYib8V2ddDTLIX2b6kJ2dzWeffea+fGZRs3btWkaNGvUHDnWQQQb5I5hsFqI8AlhT+ZW7De/9Mbe42/OeObELk+OXe9J/C06nE7vDgVwkYXXOYtbkXE+iZxhndllmRrg+88U9dW6xtCpnEXHq4F8UPAqxlCTPcLwkKsYHDOPR1Jm8lrWAaFUAkSo/AuSev1ks6awmWk297kpNuMqP+xIvJ1jhzU1xk/miqZCR/nFusTQ9PIerosajEEmI14QAsLX2IPMOvs7e/gpQqnckMepAXivbw41H32ZO1Bg2Ve+nVt/Ostz1iEQiHi3eRlFPHc+VfozZbuWl4fNRiWR0mLUsL9rGipIPXQv3sxYSQz2CmBU5mudKP2ZT9T73IjPaI5D7ki7j9SzX/JUT1/dqpk80y1OuYHnhNvpsRt6s+AofiQq1WEGQ0pvDHRWM9I3FYDMzxCOQe4ZdyoZRSzk30DUntK/tJGqJArFIRLupjxCFN1dEjOT2hCnsbsjl1QqXK1xRTx2XhA0fUKUKU/rgL9PwbtUPvJa1AKfTyVfNxcSpg3kwZToeYhk9FgNKkZRLQjPZXL2fGn0771b9gFQo5sm0OTxzYhfTwnMIkHlyW8LFtBp6WBA9gTuPv0ev1cjDRVtJ9oxgU/U+Hkqejkos4/WKz9HZjDyQdDkWh50qXRuV2mZuzl3Hrf2ufnKRBKPdgt5m5rKwLCYFpgACnDg50nWKews2027S8mTxR1walsmRzlM0GrvcczfPps/j5cxrEAtEtJp68BDL8JKqKOip5fWKL8j0HkKKZzgOnCwv2uYWS+P9hyEAjnaeAuCd09/RbdXTYurh8vAcHinaxtMnd2GyWwmSe7OrIZctdQc53FGJWCDkjYq9vFn5FTtqD+MpUbKj7gi3573L5w15mOxWnir+kB6LgUTPMIQCIRqJAoVIyps51/Fk+lyuiBiBEAGJnmFIhWK6LfoBMycJmhBezJzPU+lzGe0Xx1B1EKtHLObmuAu5ODTjV8VSt1nPO6e/p8nQxaNF29lQ9T2PFe9AZzeztfYgG6p+6K/SXsWLw68m3TsShUhCiML7F8Obz0bzdwtqjUTxu8QSgJdUNcDgwUMi/9PFEoDJbqW011XZezBpGlvH3sZQjyDsTgeHOyow9G9I/DfjL9fwZNrc/u9yJ3395g0rsxf+rFgC1wbd3rPc6QAOdlQM6BIYZJD/ZX53hengwYNceOGFzJs3jw0bNrBkyRJOnDjBoUOH+OGHHxg+fPhfdaz/NIMVpkH+V+gwa3msaAdVulYeTpnO5poDzIkczdMndvFoykw21+zn5vgLf7Nt769Rr+9AZzMTqw5CLBTRZuqlVtdOilcEPVYDs/e/4q5qRHsE8kb2IhxOBzqbiUiV3y+6OTUYOlGIpO6ZpTPDxL8lhNLqsFGn72BlxZcc7qhEKZIyI2IEV0SMdM9w9Fj0rKn8mp31R9y3uy1+ClPDsvCQyOk261hZ8QWfNOa5/z5/yDhUYjl7mvKp1XcgEgh5MWM+4Spfbjv+LvX9jnDgquLdl3gZfjI1jYYuREIRz5/8GAEC7k2cSnFPHZ815Q847qWxFzDaP45T2lZyO09xYUgGTuDhwg94Nn0eSokMqVBMh6mPO46/x6vZC/io/ih5XdU8k34lTuCmY+uwOe08k34lESo/lh5bR6dZy53DLqFK28oFwWkc6zzNaP847sh7j1SvCM4PSqFK18bFoRmU9zWzvGgbEwKTmBqaidFu5fOmfA70D7afYVJQKpOCU4hVB9Nj0eMn06CWyDHZLbx16humhGTQZuxFJpawvHAbertr4SQWiLg1/iJO61ppMnRxS/xFPFO6m6fS53Dl/tfQ2834yzTMiRzNqsq92J0OMryjuHrIeG7Pe4/hPtFMC8/hy6YCl3FH8Q73MYUovHkp82qWF24ly28onhIlQ9WBdJt1xGqCuTX3XbQ2I4+lzkIkEPBNSwlftxQzI3wECZoQghXePF68gwRNKDMjR6ISyznRU8+LZZ+6H+P8oBRuipvMtYfeoLd/ITlEFcCdwy7hrryNXB6ezY66I9icdqI9ArkncSonextZXbkXs8NGhMqP1TmL2V1/jCpdG1m+0QQrvGg19vJxYy5XDzmHLouOvK5qvmwuZHr4CGLVQTxbupssn2juTpzKbcc3sCx+Ct5SJTEegZgdNoq66whV+hCp9MPksLKqYi/nBiUz3GeIO6TWZLfidDpQ9M8GOpwODDbLr853GG0WttYeZFXlXi4LzSLNO5LHS3aiEsuIUvlzol88XD3kHK6NPgcPiZx2Ux99ViNRHv70WPSY7Fa3tXOvxYDOZiJQ7vmXZCO1m/rQ28zIRBK8pSqUZ81B/lnU6top7W1gXMAwPCRyWo29fNVSxCWhmX+JSPt30Gzs5qZjLrOOMzyTfiWj/OJ+MvPWZdbxStln7rbi8QHDONhe4f4MvJZ17YDZuUEG+W/iL6swjR49mgMHDmAwGIiJiWHv3r0EBgZy6NCh/2ixNMgg/0uIBAIiVX60m/swWC08knIFPRYDraZejnae5r6ky/8UsQQQrvIjXvO3gMQAuSfDfaPptOi44ehat1gCqNK18kjRVk5rW1ly9C1Oa1tx/IL1eJjSd4DBQ5DC6zeJJXD14F9zaBUH2suxOx1obSY2VP3AHcffo93UR49Fzzunv3OLJU+Jq33plfLP2dOUj85q6g9PtQ24X7PdhtPpdIulx1Jnsa3uEBuqvufV4dcO+N9p4dn0WA28Wv45ER5+rD31DQAzIkbQYda6xdLMiJGcH5gCwKrKvZzSttJi7GZu1Di+bz2BAHg2Yx5hKl8+b8xDbzPRZdHxSOpMbj22ntkRo3gt61rsTjtWh40olT92p4N7899nwaFVdJq1qMQykjzD+0WsnomBiQTJvVky9HzuSbwMtUTBCN+hHO08TZDck8dSZzIzYiRyoZROs9Ytlm6Ln8KC6AkAfNVShNbqavtUixWc6K1nf1sZNoeDFM9wtFYTSonMLZb8ZGoeTp7OyuyFrK/6nqHqIO5KvNSVXWW38GlDHgtiJvS3602n3dTHcxnzUIlkXBk1lrdPf4tMKGZR/3yWzmZCIZIiPMuVTCaU0Gbu5cHk6a7Aysq9PFy4lUiPADzEcjwkLgOKR4u24yGS9ZsRuFpJh2lCCZBrsOPEW6YiVOHDyd4Gt1gKkLl+KAPkGvY2F7nFEkCNvp0mYxevZF3DtLBsXhp+NWKBiEtDM9FIFFwUnM7rWQtQiKTckXAxarGcmREjGR8wjGdO7ObuvPcJUnhxY+wFPFy0lWdO7GaE31CWxV3IdTET3eYnuV1VzN7/Cs3GHp49sQsviQon8OLJT3mgcAvPlu6iztDByoov+Lgxlzvz3qPtLNMVuUjiFkvgMoL4R8PwCrGUySFpRKj82N2YS353DbfHT+GJ1NksijmXdO8o5kSOZmbECE7pWjDYzPjLNcSoA+mx6HmqZBeLDq+mVteO1mrk/Zp9zNn/CqW9DX+qGUOvxcAnDceZf/AN5hx4lRk/vshjRTt+k8nM7yXSw5+JQUnu1y5Q4ckVESP/p8TSLbnraTB0IRWKCVe6Ql/vL9jCoY4KtxHEGaRCMRk+QwBYFn8hj6RcwatZ1yIWiEjQhCAW/G/Mdg0yyK/xh4Nr/xsZrDAN8r9Et0VPs7GbKJU/SrEMndVErb6dUKXPX/7DbrRZ2FF/hNfL9yATSliRNpsmYxcvl33unm14v2YfcyLHMCYg/ldnHFqNPZzobeB4VxXhSj/G+scTIPf8ReMHnc3E8sJt7hmDv+fV4dcS7RHAHcffo1LXwlVR47g6ejxPlXzE922ljPGL576ky1hVsZc9zQUAhCp8aDS6dlrnRI5GLVHwQc0B1oy4nnvyNrEs4SI2Vv9IcU+9+3GkQjGPpc5kqCqQG469TadFh0ai4Ka4yfjLNKw99Q3DfYZwaVgWRd21HOk8hdlu5dygZLwkSjZW7yOvuxpvqYqVWQtZe/obvm8tRSoUs37kjayu/JoFMRM40lHJppp9+MrUvJJ5LQIB3Hb8XWr17YDLfGDNiMWU9jRwoq+BPU0FvJ61gGzfGOxOBxKhmE5TH580HOfd6h/J8BnCTbEXsK+9zBXo6hnKrvpcMnyikAklBCu8yOuqpsPcR2x/ZpCnRMlpXStioYihHkF4S5QYHRa6LXpeOPkpBpuZ1TmL2VF3mH3tJ7kncSoBMk8KumtZVfklT6TO5tXyPYz2i+O8oGQeLtzK7cMuxmS3EKsO4bHi7ZzobeD1rAUc6ThNSW8dsyNH80jRNiwOG54SBbr+uaNYdTC3xl/Evfnvo7ebmRycxuKh53Fv/vuc1rUiEgiRCsVYHXYuDE7l+thJ2B129HYzQ9VBtBh7aTR0UW/s5HBHJd+3nuCcgGHcOexSSnsbaDX18HJ/SO5Iv1j6LEZK+1yBu69mXUuAzJON1T+waOi5SAUihIhYXryVAJmGWxKm4CGWYXPaOdBWjlqi4NnS3TQZu92LSpvTTrDCi/uTLuezxnxuiJ2Ej9SDjdU/8vbpb93vr7dHLCHZKxyhQEidvoMbfsaN7MbYC5gRnvNPB1QDtBh6KOypRWc1MVQTxDctxYwLGIbRZsZDomBrzUG+bytlRdpsxvjHoxTLqNN3cO2hVehsJnykHmT7xrhDRa+MGsuC6Ak/a1Dxe3E6nexpyufRs6qNZ5gcnMat8VPwk/9zjqD/Ts4O4f65y382Z0KOO806VmYvJEzpywMFmynoruXRlJmcE5g4wMEUXO3PzaYeAuUaNBIlFruNOkMHPlIPfGQef9mxDjLIX81v1Qa/WzDl5eUhkUhISXHtmO7evZv169eTmJjIo48+ilT6xwfM/2oGBdMgg/x59Fj0fFBzkDEB8ciEYnbWHSHKIwCpUExBdw3j/BMYG5Dwqy0z9fpObjy6ljbz33bJxQIRLw+/mkyfIUh+Zj6i1djLtB9fwPYzGVMCBLw8/GqOdpzisvBsjnRUcl5QCt+1niDVK4KjnaeYEpqJ0+nkocKt5HdXc0v8hUwJyeD1sj183lzAeYHJZPsO5ZnSXQTJvViVvYgXTn7CwY4KBAi4MXYSnzQep74/12j9yBup0bfzwslPeD1rAe9V/ciU0AwECPCRqjjUUcnqyq+4L+lyRAIh71fv457EqZgdNh4u2uqeHzjD7QkX02jsYlvtIfxkavcieVpYNldGjaXTouWBgg/osujcz/mFzPl4S5T80HYStUTORSEZnOitJ8UrAl+Zmi6zjhO9DQiAhwu34ilVkqAJJcs3mhdKP+GexKkEK7xpNHbxXOnHXD1kPKP94vikKY9hmlB3uPDk4FRuT7iEvc2FbKk9wIq0OXhJlHSYtXhKlVx98A0sDhthSh8uCEpzh7+eG5hMjm8Mz5TuRiQQckPsJEb5xXJv/mZaTD3uAOSLgtNJ846kXNtMqMKHlRVfEKb04aXMa2gwdHJ3/iaUIilvZC9iTeXXmBxW7ky4hHZzn9tO/pXh1xIk9+T6o2/RbdHzaPJMJgQlIhdJEAqE6Kwmvmou4tnS3byetYAafTsj/WLpMGvpNusJUXpzT/77xGmCOTfQZSO94fT3WB127ku6DJFAyIOFH9Bj0ZPoGYbFYSO/uwYBAt7IWkiGTxQF3bXceOxtkjzDuC3hYu7Nf999vrylKp5Ov5KHCj9AazUx3n8YS+Mv4Poja2g/SxBl+UTzeOos/OSu36oGQyfTf3zR/fcLglO5L/HyP8VOudPUx66GXEp665kfNQ6ZSEKVro0tNQe4OX4y71X9SF5/SO9dwy7lopB01BIFTqeTU9oWlhxdi+4sJ80rwkeyeOh5eMv+nI2bNlMv1x5a9RPBOD08h1F+cUSq/IjyCMBit1GpbcZfrvmPaxHrNGup03cQrwlBKZbRazFQpWvDX66mWtfGcJ9olGIZHaY+DneeYpx/wp8iNn+JRkMXnWYdwzxDXUYypj5OaVtI9Y7408OABxnkP5nfqg1+t3fvkiVLuO+++0hJSaGqqorZs2czffp0tm/fjsFg4JVXXvlnjnuQQQb5L8FLquLKqLEoxVJ6rQYKumsxO2xYHDYOtVewNO6CXxVLWquRZ0t3DxBL4NqBvzt/E1vH3vaz1uRCgQCVWDqgZeoMcyJHU9RTx+baA3zeVMDK7IV801LCS2WfIhII2Tj6ZnylHggEAlakzaagu4Yc3xjK+ppI8oogySuC4T5DMNmtyEUSWkw9lPY2MH/IeE701nND7AXYHa5F+W3HNzA5OA2JUESKVzibRt+MTCAlVhPE6oqveDJ9Lq3GHiJVruDfp058BMDFIRmU9TUzxj+O17MWck2/TTXArIhRTA5O4/t+d70zC8QRvkNZOHQitboOHineTpdFh0okw1umosHQxT35m3gu4yrOC0rBR6bik8bjrK78iklBKdyVOJWinlruzd9MnDqIJ9Jmc3/BZn5oK2Vq2HDGBiS4g4PPUNJbz9SwLH5oLSVApiGwf/H5ZXMRJ3obaDB0Ee0RSGVfM6EKX1QSGVqzkdeyrmVZ7gYaDF1usZTjG8MloZncm/8+4LKp3lJzgETPMAQCEAuEjPKLZX97OXuaC3DgZHp4DqEKH7ykSgLlniwv3MpT6XN5PuMqxEIRz57YzcKhE9lac5AOSx8f1R/lsdRZKEVSt4vZmpzFFPfUMzYgfsD7UCGWEqMO5IXM+VTp2uizGuk26/CReXBX3kYmBafyQuZ85CIJdx5/j1ZzL68NX4CnVMnCw2+iFitYlbOI6T++yJF+AwgBAt4dtRSZSIITGOIRwANJ00jxikBnM7oDhgEMNjMC4JbYC1FLXcYONfp2Os2uczo1LIsttQfI7ariseIdPJY6C3CZTJzNgbZymoZ0MVQc9Itzgr8Fo81Cq7mPNae+dl83yi+Ol05+igMnXzYXMi4ggbzuau5IuNgtlsBlThKk8CLbJ4bv2v7mCDk3asyfJpbANZv192LpsrAsQhU+3J2/iYuC07l92MWc0rawLHcDiZ6hPJU+Fx+pihp9B95S1R/Od/sz6DRreapkF/vby1iRNpsRvkPZXneIZK8IluWup9HQzYq02Qz3iWZ50TZyu6pYFHMucyJH/2WiKVTpQ7DCy/3e8Zdr8JV5/FPvpUEG+V/md38yKioqSE9PB2D79u2cc845bN68mQ0bNrBz584/+/gGGWSQ/2A0Ulc+zcOFW6nWt/F5Uz5ftxSjt5u58ejbNJ41UPz39Fj0bsexv8dkt1L1CwnyPlIV08NH/uzfPmvK46KQdKJVAfRY9Vx18HVe6p9RmRCQiLdU5Xbg85drODcwCU+pijSvSPzlalK9IghT+hCnCWZV9iJui59CUU8dz5/8mLdH3kB+dzUvlH3C2lPfsCrnOuZEjSbKIwChQMg9ee9T3FvHZaHZPJo6k5Xleyjta+BEfxvfmVmcz5ry0VkNmOxW1p36dsDxf9VSRLdF7664nMHmsNNs6MZTqkQAqMQynkibzT2JU4lTB/f/l5NAhQaFUIpSJCVApuHcoGTuy3ufe/M3IxOJWRI7CalQjMPpxO50sKv+GPclXU6owsf9WH4yNY+mzOSUtpUVabPZWnsQiVDMfYlTWT/yRmwOB9Eegdw17BKcgIdExstln+EUgMPp5ILg1AHHvix+Cs+W7sYJPJg4jbUjrkcmEvNw4Vaez7iKrWNv45b4i7h6yDkIEDDGPx6VWIZCKCVRE8pTJz6iTNvEkqNr2dOYzytln3FK14rd6URrM/FkyUdcN/Q8AmUaEj1DEQoE6Kwm1BIF5wQMo0rXRrux1/06VutakQrF7Ko/xsGOCsYFJFDa18Tq8r282R/GWtnXxJIj/8feeYdHVafv+57e0nvvDUJ6oWMDBUREkaJIBwEVFXtv2AWxIF0FKYpgx4IFQXpIQgoQUkjvPZnef39MHI1lV3d1f+5+c18Xl85kzsmZyZmZ83ze932eTdw5aBKTQzL7zBQcga2PJ09DIZLi2zfzpBBJeSRpKu/XnWT2sbWc66lHJBCiEEmo13WwPPctjDYLfjJH1cNos3Bb7lYClZ581VjIq6Vf4C5R4CV1YVX6bG6IGMnK5OmIBEKujxgFwOaKb9nXZ04yJSTLEbJrNbLk5OZ+Q/s/x2S1cKa7lpY+QxVwzBnWatudtxViKS5iOY8OmQo4rM9XlXxKokcIg9yCuSwgiU1983mD3UP6tdf2mHRsrzrcTywB3HRyIzWatt88rj+KRChC9rNqs7tESbfZEXz7RVMBK/K2cVvuVix2K2qzAYvNyrmeBuYdX8czZz6i4z8Qrvpb2Ox2tBYDdhyV7TvytvHWhYPoLEZ8pG7O++cdX0duZyUAESrfv7QtD/iFOBoQSwMM8Nv84XeH3W7HZnN8mX/zzTdMnDgRgNDQUNrb2//RpgMMMMD/GHa7nVptO3mdjnadlckzeHPYMmRCCY36Lg62nOtnCvFTzP9kIFz9KxUkAJFQxNSwbBJcg37xs1kRo/GUuvBa1gKUP7mwi3UN5N7Eq3+xyizquyCRi6UM9Y4l0sUXqUiCWCgiROGNm0TBe7XHmRo6FE+pC9leMY7HiyRIBCLcJEo0ZgMby7/hbG89d+W/TV5XFW9cOMB3redYW7afob6xjPZNYMfI5YwPTAUgWOXN1sqDfN9WAjjCaN36wlFvPrWFOLcgXMRyQhXeDPOJJa+ris0VB3AXK1iXtYiVyTNYX/4VDxS8w6NJU3k1cx6J7qGOIFGpgknB6byYPps9tSeYH3MxwUpPVqXN5r2aY5jtVlI9wgFwlSg42HLWOb8FjqpWpaaVBl0HG8q/5qWMOUSr/PGUuvBg4Ts8ljyVh4dcy32nd/L8uY8511PP40nTONxWQrm6yXlh/wP3F+zkoSHX8nL6XOLcA3nqzIc8mHgN9w6+CpFAyIq8t2k19HBd6FC2DFvCuZ46luZswYKVEKU3jyVdh0wooc3Yy9ctxTToOnk9awF+MjeqtW0sjRnHx/Wn+LKpEJsdirvrqNG2s7XiO7pMWqRCMWXqJtr0vdTrOjBYzeR2VLEkdhw3RV+GAAGeEiVzoi5GJZIiFoh44sz7dJg07Ko+iotIzh15W9ledZg3hi0jTOHNo4W7aTP2ckfCRF7LnE+Y0pv8ziomBaejFMvYUXWYtyoPIRIIEQmEBCo8WJ0+h4eHXEOQwhOxQIjBaqJc00yZugmN2cBrmfNZc/4zrjv8ErGugXx80T1keEXi1hcMKxNKuDn2cm6Ln8CG7MX4yFy5PX5iv/PcZDXTbdJisVkdYqmnjiUnN3NX/nZaDT1UalpYcnIzS3I29xNNLmI5wUovViQ4vs/nRI5hTuRFPJ0ykyeK9mDr69y/5dQb/cwcesw6tld9Dzja8HaOXI6LWE6HScOmim/pMel+9T38R/GWunLf4KsR/MQApMXQg0IkZXbEaADO9tRjsVuJUPlye8IEXivdz82n3sBks1Ctbf2nnzd/Jb5yN1amzCDNMxI7ds701GG2WzndWcWTKdNJ8QjHjp1mQzcATyRPY5Rfwi/miAYYYID/f/zhlrzMzEyeeuopxo4dy6FDh1i/fj0AVVVV+Pv7/+kHOMAA/+v0mHSoLQYC5G6IhWJ0FiPdJh0eUuVfYpn7ZyIQCBjkHsIzqTOx2myM8ktAKhSzPnshx9vLmRSc/puGDy4Seb8ZnZ/zY+Xkl/jJ3VmdMYdKTQvfNBfjLlEyPijV2Tr2XcvZfnkpVZpWKtUtJHmE/aqZhMVmpaev6qMQSZGKxHjKVIzyS2DbsJvxlbvhJlFwacAQIl18CFH64Nk36OwikXNTzFgq1M2U9DbwQMEu535vj59Ah0HNHQlX8mTRHi4PSsVVIidU6c2lAUM41FrCioSJTAxO47qwoSzJ2cxI33hKexvJ8ormtoQJjnZB91By2ysw262U9jYiEgip1LRitdt49sxH3JEwkXVl+7k57gq8ZC6YbFYeKdpNrbadZn03K1NmsLpkH+d66jnX28B7o1ZQ3F2DzW7HXaoiUuWHt8wVN4mCqaHZeMtcuTNvGzbsvHz+C64LHcqzxR9htdvYWXWEOxMmkeIZwZG287xY8ikhSi+eSbmeucfXAZDtHcPVIZk8WbyXel0nu6uPcm/i1Sw+sZFWYy9PFO/lkSFTuT1vK036bh4pfI/do+4gROFFg66LjdmLEQgE9Fh02O2gFEsxmhyZQwqRIzcpSOHB9hG3Uq1pY0/tCVI9wqnStnBb7lYkAhGvZs3HaLOwIn8bvWY9r2bMw0vmylsXDnJHwpUOi2pjLx/UnWRh9CW4SuSU9zaT2xcQe/egSQQpvDjTXYcNO0qxI2i1rKeRuwdNpsus5dumYrZXHWZl8nReyZjHodYSFpxYz5PJ08nvquRUewWvZy2k16wnt6MCqUjC/YlXY7XbWVu2n2ptG8+m3sCnDXmc7KhwzrM9VryH1zLmO+3CE9yC2DN6BXKhBBeJHBeJnC1Dl3KsrZS5x9exIXsRAQoPTnfV8EDBLtZmLSBC6YvJasGGnTJ1E8tyttBj1tFr1uMuUTpnADuNGl4t/YLPG09zR8JE3hi6lPzOKu45vYPrQoeydfjNyIUybsrZSIO+k6+aCglX+eIuVRIgd+fljLkcaS1lQfTFeEhVbMxezJaKA6xImPintZOpLXqMNgvPpl7PAwXvsDR2HHKRhDjXQCw2K9urDzsfG6r0pt2o5kDLGezYCVF6sTZrwe924PwBm93Wr+Ly89t/FKlQTJxbAKf7ZsEAEt1DEUA/IUjf7T8e2z3AAAP8lfxh04eioiJmzZpFbW0td955J4899hgAy5cvp6Ojg127dv2TPfz/Y8D0YYC/Gz0mHTuqD/NO9VFez1pIrGsA37eW8FjRHp5InsYYv0F/e9EEoLOYALvzWC02K3qr6R8mwNvtdg60nOGBgnd+8bPLA5K5d/Dkf+r+1WnUIBdJnaGcbYZe6rUdLDm1GYARPnE06bup0rYi7nOTG+Ie2i8Yt8Oo5sO6U+ysPkyQwpObYy/nQMtZFsdcRoDCw5H3VPoltyVMJETpRZO+i9LeRqJc/AlT+dBt0lLSU0+cWxBXfvcctr5Y35E+8TyZMh0BAiw2K2qLgesOv8SC6Ev4urmICYGpTAxOw1WswEUix26306TvRiQQkNtZSbJHOBvKv+Lr5mIWRV/KtaHZ7Kk9wVuVBxnjN4gZ4SO4va8FKVLlx72Jk6nRtHNFYDLnehvQWgw8Uvgexp+EFwsR8GzqDQz3jcVis9Fs6ObBgne4d/Bkol380VtN3F+wi0XRl+IqUbAsZ4vz+QDEugRwT+Jk7snfwcsZc3m97CunwLgyKI1Mr2i+bCrgzkGT6DXp6LHo2VD2Nc+lXs+rpV8yJTSLRwp3OzObwFGtW5u5gE6jxjkQb7KZ+aKhgIv8E3nu3IfkdVYhFogQAOY+l7nXMhfQbdJyvqeBKm0bOrORRbGXsTRnE219VutTQ4fyXu1xpEIxu0bcxqKTG2k2dBPvFsTzqbN4oGAXJb0N+MvdeTF9NvOPr+OhIdfgJXXBXaLsc7cTYsPOILdgPKQu5HVeQCqU4C1zYfHJjWgtRrxlrowPTGFn9RHAkVMzyjcBpVjK8fZyTrSVMdwnlmVxV7A0ZzNCgZAabRu3xF5OmmckN+VswoadsQFJ6CxGjrWXsWf0nYSrfGjRd5PXWcWxtlLEQhHXhQ0lVOmD2W7luu9Xo7Oa8JW5MS/qIl4r/RKDzUySexir0mejFEs53VnNHXlbnX9Hd4mCjUNvIsrFscDZblDzZPFeTnSUc2vcFRhtFpI8Qnmy+H1mR47BTaIg2sUfT6mKj+tzuTZ0KO4SBZK+hQeT1YzOanI6c9rtdnrMuj/NqbPDqOa5sx9xqLWEycEZLI27nHeqj7C96jApnuHMjhjDPad3IBWKMNocMQFjA5LI9I7m+bMfMzk4g+Xx4/+Qk2Ctth2dxUisWyAigZBWQw91ug4S3UOR94nYP0KPScfO6iNsrTwIOM55q83Gkykz2Ft7gry+Njw/uTuthh4ECFiZMoNRvvH/FZ//Awzw38xf5pL3WxgMBkQiERLJH/8w+U8xIJgG+LvRZuhlac5mp+PaxKA0Pqo/BUCWVzQrU2b8T1u2aswGzvbU8cr5L6jQNOMldWF25GjGB6X+0yHtFkMP9+bvYE7URYzwiUNnNfJSyT7CVD4oRDJKeuq5Z/BkTDYLd+RuRSIUsypjtrMKBY4B/A3lX/NuzTHiXQN5OGkqS3M2o7UYudQ/kdviJ3LzqS006rtI9Yjg8eRpPHXmA3I7L3BH/ESuCEphe+VhYtz8OdJayoGWM859iwRCVqfPJs41kGZDDxvLv3aaBIDDDfDZ1JnEuAY6Qz9/oNuopdesZ0PF13zTXAxAjEsAFZpmwGGlPD18OD0mHfee3sny+PFEqHyIdwtGgIB1ZftpNnQzOSSThwrfde73ppjLHDMwcje6TVqW5myhUtOCm0TBqvTZvHD2Eyo0zchFEvaMupNtVYfYW3uCALkHC6MvIcs7mjcqDnC6q5rn0mZx3+md/dr5Xky7ES+pCrPNyprzn6MUS1kUcxkhCi96zDpaDb0YrCYeLtrt3ObxpGm4iGXkd1WjFEm5KjiDj+tz8ZO7kddZydLYy7nx6Fpez56P3Q7PnfuICnULL6bN4v26kxxvL2dt5gIEAijoquGKwBSWntzMLfFXUKNtY4hHGB5iJV0mLUa7mUcL3+snAoUIeHDINRxtK+W7lrM8kzITmVDMmpLPeTHjRm48tpZUzwi6TFqmhmYzyD2EW0+9QbDSmzsTruTu09vRWn4UgNneMUwOyeTxoj0IBQKeSJ5OhbqJq4IznQINYEnMWAw2M9neMWjNBr5rOUuSZxhKkZRvmou5I+FKJEIRy3Ic599PmRs5hjlRF9Go62JJziZ0VhN3JkwixjWALRXf8njyNFzEcow2MzqLkRuOvuoUE6FKb9ZnL+rnItes7+Zoaym1unbeqTlKoMKD51NvpFTdyNNnPkAlkvHm8GX4yNyo1bZhs9sJUnjiLXftmwtrxUOqwlf+53+v9ph07Kk9waY+Uwo/mZvTKGZKSBbRrv58WJvD2qyFtBp7WJqzGblQygtps7jn9HZ6zHrmRV3ErIjRv6vi9YOF+w9W+d4yV+7Ke5sydROr0meT6R39h0VTm6GXxSc30qjv4rrQYdwUexmPF+3h+oiRPHf2Yxr0naxMnkGWdzQPFbxLXlcl86Mu5vqIkf8z2U8DDPB35T8umP4bGBBMA/wdadR3sfzUm9TpOpz3/dxS+H+dTqMGk82CUCDAR+b6T1tftBYDa0v3837dSQQIeDRpKkfbSp3iYsvQJYSpfJwXG836bgQCgVMs9Zr1tBl6kYskXHf4Jcb4DWJ6+HBMVguFXTVOh7cfkAklrEyZjlQoZmfVEU71VVViXQO5LGAILYYePqzLAWB+1MWcaC+npLcBkUDIW8OW8U1zMW/3zXosjr6Ub5vPUNlX9do5cvmvhgx3GjV0mjRsqzzkzLYBuDwwhVtir0AkFFLW00iQyhOlUIpUJMGO3ZlB1GLo4cVzn3Cm58fsqCCFJ69nLXQKtAvqFpblbHEOz4ND6K1Jn4tSLGVJzmZ8ZW48OGQK79WcYGb4CMJVPuisJu7Kf9sZfBnp4kdpbyMAy2LH0Wro5f26k4gEQp5LvQEfmSt7a08wJTSbR4t20/QTEwIfmSsvZ8zlntM7aNJ3My/qInxkbqwu2YcdOzfHXsG4wCHY7XC2p45IFz90FhP12g58FG606LtJ9Ajl8aI9lKmbmBScwZzI0awt28/3rSUkeYTyRNJ0Hi3aTajKhzjXQF4p/cL5++9ImEh5b5MzaHhZ7OXEuPrjKVERqvKhoKua+wt2OY04bo27ghZDD3tqT3Bz3OXUazv4pCHPub+3hi3DS6piee5b1Oo6GOwewsOJ13CotYSNFd8gEgjZMnQJOR0XWF/+FSqxjNcyF1CubuK5sx8jFDhs4pM8QllX9hUf9J1XP2fniOWEqXzZXnUIF7GCMnUjhV01rE6fg6/cja+bilhb9mVfBtbnNOi6MNscLXpxroG8kHYjFruVsz31hCq8KOttwlvuyiNFu52tqT/MH6Z7RfJw4rX0mLWU9jbx/LlPuDI4jdviJ1Cv62RZzhYGuQfxdMr1f4lo6jXr2FV9tJ9T4FXBGVzin4hCJCVU6U2ToYv1ZV9zW/wEtBYj0a7+bKk4wN66E7hJFOwccRv+ih9F4q+12NnsNhp0Xc6oA4VIipfUhQZ9p3MBJN0r6l+qMjXqOvm8sYCpodl4ylxoM/TyaX0u4wKTqdS0kukdjUoso83Qy4n2Msb4Df5LbcUHGGAAB79XG/yuhlwvLy+noYOnpydeXl6/+W+AAQb4Y3hKVEwOyex33+zIMf+nVha9ZC4EKDzwk7v/rjkBlVjOguiLSfWMwI6dJ4r3OsXSioQriXTx6/f6BSg8fiKWdHxcf4rrj75CTkcF9w6ezEjfeG7JeYMDLWfI9I7i6p/9PVanz2ZX9VHuyd/BlNAssryjAShXN/FR3SmuCk7HV+bGHfETuTFyNM+kXk+CWzATglLxV7gzPigVD4mKewdPxmAzc+/gybyQNounU2ZisVkxWEx0m7ROJy+91cTZnjryOi4Q+LPZi2CFJyKBAIPVRIdJgwghXnJXLHYrd+a9zZeNBVjtNlaXfMqZnjqECJgZPtJpxHHLqTdoN6pp1HWiFEtZlT673/5vjnMIhiU5mx37SZ/N02c+5EjbedaWfYnOaqLdqEYmlCAVinklcx6PDLmWMb6DAFCKZc6Ky+KYy4h3C2TN+c+4NmwojxftoUnfjVzkMDBQiWW0G9Xcmfc2r2TMA2Br5SFWlXyKHTtJ7mFEufjSZlBzpqeOkt4GZh97nRZDD7HuAXzTVIyn1IXSnkZG+zl+/76GPBac2MD3rQ5DjaHesXzckMtdg67iyqB0vmoq6vd8v2gs4NKAIcS5OWbm1pd/RauhFx+ZKy4SOSme4f2c/9aW7Wdu1EU8MNiRq/VTsQRwz+kd1Ok6eTDxGi7xT2Rx9KUsydlMqNKbq4IzWJ0+mxjXAC72H4y3zBWtxcjikxt59uxH2LEzxD2UUKU3eouZzxpO/+Z74FxPPQVd1exryCfBPYivmoqo03VwV/7bbK/8nmfOfkivWc+nDXlMDxvO2yNu4eXMeYgEQqo0rTToO3iw4B0uqJs53Hae50o+ZlvlIZ5Jud55DoJjzmZG2AjmHn+dgy3nqNV1YMfOvoZ87ju9k2U5WzDazLQYev4yYwW7HafRxA/oLEZaDD3sa8ijTt/BrafeJL+ril3VR4hw8cFL5sLimEuZEzmGjdmL8fuJkLPYrJzvbaTuJ8YXddp2SnsbCVR4sL7PVENvNdGg70SAgNXps8n4F8USQJDSi1kRI52zj75yN66PGEWoyocRfc6QP9w/IShtQCwNMMDfjN9l+rBmzRpcXR3tMQM5SwMM8Oehsxj5vrWE18v297v/ntM7eD1rIYnuwYh/Jbx1APCVu/NC2iwmfPesc/U/2zuGScHp/3B2ymyzktfhmBl49uxHXOQ3iMOt5x3D8b1N3Bg5mtyOC/22+aDuJFcFZ1DUVUO7sRdf6Y/tgs2Gbup1nWwbfjNSkQStxchDBe+yNHYs/nJ37HYo7Kphx8hb2XrhIB/V5zLEPYxPG/KIcwukQtPsbMWs13Zw16CraNR3EqHy5XxPI1srDwHgJlHQa9bzVuVBxEIR/nJ3nj77ASKBkEeTpvJu9TFKehsoUzcx2jeBmeEjONtTz3OpNzDIPZhRvvHclb+dySGZWKwWytXNKERSXj7/Wb/n+nblIYb7xPHg4Cm8W3MMN4mCewc75pbO9zYy48jLuIjlrEyejlIs41hbKTuqj/DmsKVcFz6U/Y2FfNlUAMCemuOkeIRzU+xYdlcf4/aECTxRtJc1GXNxEcuJdwviocJ3WTHoSsw2K1Eufk47eXeJgqdTZ7LoxAZ6zDqyvKM50lYKwKmOC7iIZXzeeJoRvnEM9ghBIZYyO3I026sOO0NUl8WOw2KzsrPqCJOC03nh3KeU9DYgRMCVwel81pBPaW8jWyoOsDptNk+f+YByTQvpXpGU9DSgtRip0DTzRWOB8/Xxk7nRpOsiyTOM2cfWOs+7+VEXc/fp7bQb1WytPMhNMWO5e9BV1PU58+2qPsozqTOx2e2IhSIiXfzYkL2IG4++5myXi3Lx58nk6fjK3Wg3qjH33f9zFCIpmd7RzDjyMiabhU/qclmTMZcVeduo03U4K6SjfROYEzkGqchRBQxSeLImYy4CYOuFQ5Spm7hr0CSe7ssIGxeYTI+5v7Ndu7EXhViKTCRhW9X3rEiYyOKYS9nc15oJEKjwYF3WIoKUv8xN+3f5Yf7nhwptkMKTRn0X37acQSQUkuYZybKcLQCEKL1YGnc5vn2LI54yF+ZGXYSLWO6cW7TYrJSqG1mWswVXsYIN2YsAWJqzBbVFz4bsxfhK3XAVK5yGNEKBAC+py79t86342TySom/2UvKz/f7VduIDDDDAH+d3VZjmzp2LTCZz/v8/+jfAAAP8fow2M6tKPgUcM0sfjbmHUKU3JpuFZ89+hPonsxED9KfDqObFc5/0yyw61XGBnI6KPhOKX8db5sr9iVMY7hMLwKHWEudQ/xPJ0/vmcrqQCSVM7XMJU4nlHG47z/YRtzLEI4xIV8fAvItYDsCjRe9xsr0ckcDhbmWxW3mw4F1uPLaWrZWHGOwewrtVR4l08WdKSCZtxh6OtJ3nzQvfYbJa2Ft7gm2Vh/i25Qwn2stQiWTU6To42VEOwPjAFDYPXcLEPlvyo22lpHpGEOsSgNVu47GiPc4WwNXps/GQqkjzjOSjMXeT6B6CzW5nS8W3bBp6E0qRlJzOC0iEIl4v20+FpgWRQMgd8RPxkKjoMetZlrOZ4b5xvJo1H2+ZK4nuoTw45Brna6ixGGgzqAlT+lCmbsJqt7Hm/GfIhFK+bCpkYfSlTnvphwvfxVfmxp2DJjHEPZQdI5djsVt5vexLXi/bz7ujbsdksVDcXYtMKGFm+AgAesx6vmkuYtPQJVjtdqdYmhycweKYS4lw8SPJI4yHC3fTZdQQqPCgTvtjWytAlaaNK4JSeS71eoxWM5cFJCLEMVc0J3IML6bfiBABw33i0FlM3BJ3Ba9mzOPe0ztRSmTIxBIeKXoPkUBIhlcUL6TO4rHkaTxWvIf1ZV/x8JBrGeETx+SQTF4r+5LV6bMZ4h7CPYMn4y/34PbcrXxQe5L12Yt4JvV6Xi/bz43HXqOitxmN2UB5b5NTLAG0GLrRWAwIBQJcJHJG+sb/6jmst5rQWAw8nzqLONcglsSOZZBbEJf6D+n3uHsGTyZc5eM0eJCJJMS6OipzP7SV3nt6J3cmXMkjQ65FKZLyRPFeAKJd/JGLJLQYenj27Ic8mjQVD4mKY21lZHvH9Ps9ca5BqMQyWgw9lPedD+B4j57rqcdgNfOvYrXbqO9rV54aOpRtw29hScxYANoMarykLk5PuQ3Ziwn52Tygq0TRz+RFKBAgRoQIIW3GXhaf3MTik5toM/Yi6rskWlOyjyptK0IEqMQyrHYbS3M2U9bb9IuMtAEGGOD/Br9rhqm3t/d37/DvPBs0MMM0wN8Nu93OBU0LWyoOcPegSfjI3WjUd/Hc2Y+4P3EKQYo/f8X2vx21WY/GbODdmmO8U3MUgIXRl5DXWUlBVw0CBLw1fBmD3UN+dftabTuf1efjJXdhdck+5/3zoi4i2zuGD+pyONx6no3Zi3GRyLn11JtcHzGSBNcg/BXuPFj4LoPcghnhG8cQj1AeL9rL8fYyRvjE8UDiFGQiCXqrCavdRqteja/chY3l37Ao5jK+bz3H+KBU8jqqONZe2m82CWB62HBmR45mee5bNBu6eSp5JhWaZgLkHqw88z4PJl5Dh1FNtKs/PlJX3KUqpnz/onP7a0OzuTVuPJ0mDWabhRNt5XzakMcrmfOoUDez8swHdJo0AGR4RTEtbBhPFO/lhbQbSfOMoF7XwdKcLdwYOYrLA5PxlblRpm6i16xnXdlXTsMCwCkwrXYbXzUVMi4wmWU5m3l4yFT0VhOhSh/uyNvKvKiLuSxgiNPWucOoxmyzYsfO8ty3uDY4m1AXb7ZUHGBhzKWUdNcTqvJmXfnXPDzkGr5vKeHasKHMPrYWq93GuqyFHGo+R6DSgyuCUrnq4As8OGQKh1vOOwNU492CnDNVk4LTmRUxCrXZgJ/cDZ3VxOaKb+kyangqZQYdJi0HWs7wUd0pVqbM4LmzH9Go78JFLGfP6BUUdFYT5xZIg64Lb5kLcqEEgUDA2rIvWRxzGa4SBXtqTvB21fe8ljmfCJUvxd21BCm9WJKzCYPVzHCfWAR2Acc6ygB4OWMuOouRhwp3Y8dOvGsQ7cZeOkwaVGIZm4cuIcY1gEpNC/OOr/uF4Mj2iuaJlOmoxHJ0FiNSoZivm4t49uxH/R4XqvTmtawF/T5H2gy9zDu+jjbjj9/r7hIlt8dPQCwU8VjRHrK9o3g0aZpjvjL3TfxkbtyXOIW9NceZEJzmdF8UCYRY7TYUIimvZc5n1blPqdW1syF7Mf5yD1aVfMK3zWf+ZbOEH+g0qjnWVsZIv3g8pS50m7QcbStFKZbxaOFup+i8Miid5fHj/6lRjs1uo7y3mcU5G52vrUIkZdPQm5AJJMw98Tomm4XV6bMJV/myJGczrYYe7h08mcv8h4BAgIdEiUAgwGKzoLEYUYpkvxpZMMAAA/y9+VNnmDw8PPD09PyH/354zAADDPD7EQgERLv480Di1U6DhyCFJyuTZwyIpV9BbdazryGfBwp3cWVwOkEKT26Ln4BCJGV53ARSPcO5KjidALnHr27fou9he+X3BKu8WFPiaEX7YXV6a+UharTtLI0Zx9sjbiFY6cXWyoM0G7pZc/4zSnobeKRoN+d66vmwLodAhSeeUhceGTKVm2LGcmPkaNaVfUWNtp1DLeeYc+x1zHYzAgRcGjCEG4+9ho/MjefOfszjxXuYFTEKP9mPH85BCk/mRl1Ek76LOwddiadUxcNF79JhdNg+K0RSPKUqrHYbYoEQT5kL95/e2e/5fVKfR6O+izcqDnBn/ttEuwUwNjCZfQ35lKubGfeTWZy8zkqiXfz5aMzdpHmGIxWJ8ZCqWJu1gFZDL/ed3sWpzkp6zHrWlu13trJdFZyBEAElvQ08WrQboUCAr8yNXrOOt4bdTIxrAOXqJhQiCTuG38rkkAwCFB6YrI6LWm+ZKwEKD7xlrryWOZ9NF77BR+bGPYMn82jhbt6o/I56XSdr0ufw1JkP2Vt3ku2V37M2cwEAK/K2cXFAIuEqP144+wkWuxWlSIawr4qwOOYybom7nFkRo5x/X5vdzor8bbxd+T0iBDToOrh/yDXcV7ALncXIR3Wn6DHruC33LRr7qotrMuZS0FmNyW5h3vF1eMlcEABdZi2zj6/lyuAM/GUe6K0mfGSubBtxMxEuviw4sZ4HCt/hcGsJ67IWIRdJON5e7hRLDyROIck9lACFB1KhmHTPSNZkzGXj0JvwlrniLlE6s8vClD7sGnkbVwVn4CV1IUzpzUOJ1/B48jS8Za7IRRK8ZC50mbROsTTaN4HXMucjFYqp03WwpuQzen8SIKsSyxjiHtrvvNFYDIiEQlr0PbyWOZ9Hk65DLBBS2tPIyxnzWJkykwiVL7clTOSrpiKMNjOBCg8+GnMPN8WMRS6SYLSa6TRp0FlNLM3ZzN352/m6uRgbdhr0nb/ZXvh78JK5Mj4oFU+pQwh1mbQcbyvj0cLd+MjcmB42DIDPGvN588J3/Z7vryEUCFGKpciEPwo4qVCMUiQl1MWbDdmLWJ0+hwyvKIKVXqzPWsTDQ67lUv8hnOq4wLTDL3FB04LFZuVcTwNTDr1IYXe18xwfYIAB/vf4XRWmQ4cO/e4dXnTRRf/WAf2VDFSYBhjg38NssyD5yUyVyWZB2he2KxWKnPNWZpsFs83mzEf6s+gwqjnQfIZB7iF83nCaa8OyKe6qJdrVnypNK9neMchEEpQiKS3GHjwlKtykSiw2Kw26Tsx2Kz0mHS+WfEKlppVBbsE8ljyN1SWfcqrjAn5yd94efotzhbrd4AhZ/akduBABz6fNYqh3DHKxFLVJT4O+kwUnNmDHzq6Rt3FzzhY6TBpcxHJmhA1na9UhrHYbCW5BLI0dR7m6mV6zju1Vh/s9v3lRFzHcJ45jbWUkeYZxd/52589uibuCWm07nzbk8XzaLD6py+VoeylLY8YR5xbIurKv6DXrWJ0+h/1NheyoPkygwoPhPnHUatu5NnQojxW9h9n+4/B8nGsgjyVdR4DCA1eJAoPVTH5HJXfmv+203p4TOQaxUMTWCwd5IW0WHSYNHhIVDxTsYl70xVhtNhI9QthedRhPiYrp4cPxlKrY31TICJ84/BUeCBBwQdNMjEsAFrsVhVhKh1HDK+c/J7ezEpXIUVXZVXOEfQ35AP2qF6vSZxOu9OHl85/zTUsxWd7R3BQzlsUnN+IhUbE+exHl6iYEAgG1mnbMdgtigYgwlQ/+cnfcJUq+aznLxopvGO2bwLK4y2k19KA26/m4PpepYUP75YHdN/hqbHYrIKDV0IsdOyKBkG6TlhjXAF4s+dTpOLjo5EY6jGoGuQWzJmMun9bn8Xr5fkQCIS+kzWJzxbec76t2yYRi3hu9gkCF56/acddq2xEJhAQrvdCYDSjFUhp0nX0CSoCwz+xDLBT1swX/YRby66ZiHhwyBXeJkrM99bxUso/n02b9IrS1vLeJOcdfd7aXLYi+BLVZ7wgA9oxgcfRl5HVW8mbld0S7+PNg4jUkeYYB9AURH2NmxAiClV70mHR8XJ/LKN94pw1660+qV3cmXMmV/2Su8I/SadSwpuQzzvTU8XrWAlwlCt6vPcn2qu/ZMPQmYlz8+7Xh/ZxabTvLcrbQZux1iiajzYyvzI0N2YsIUnphsVmdwcEABqsJvcXM9UdfodOkwVUsZ0nsOF4t/QKTzUK4ypdNQxc7Rd3fCbvd/ovX49fuG2CA/4sM2Ir/CgOCaYC/Iza7jV6zvp+rW49J97dzSeoyaviquYjL/JPwkbuiNus51HKOVK8ISnsa8ZW7EaL0xm63Ua/vpMXQy8ifuD/9GfxQYXr5/OfcNWgSNrsdN4mclWc+YE7kRdwQMRKpUMzJjnLuO72LZbHjmBo2lDpdB0tzNjPSJ56L/AfjJlHwRWMB4wKTWVm8l3sGX82xtlLmRV1ExM8svjuNGsZ/94zz9qX+iTw8ZCouEjndJi3bqw4TrvSh1djDpopvCVJ4ct/gq3myeC8dfe1vALGuASyLvRy1WY/eauK5cx8DMD4wFZFAyGeNDqFw7+DJpHtGIhaKeKBgF+VqR/aSj9SNlzJms7pkH23GXh4Zci0Wm43j7WVkeEcRrfLn04Y8fORu6CxGNBYDb1UexF2iZG3WAhYcX4/ZbiVM5cOsiFG80Df/9fO8L4PVzJaKb9lZfQSVWEavWc/7o+9EIBCiFEqp0rXyVUMhN0SN4pP6XCo1rUwKTufNCwcpVzcxzCeWeJdAhvnF8XDBu30zY1fTbdKxvuwrOs1aXs6Yy/u1J/ioPheA5XHj+aqpkEeTrmND+dccbjvvfN3eHLaMQLkHVdpWbHY7Z3rqyPSKxkuq4va8rcwIH8Gl/onsrDpCi6HHeSF/uPU87YZeYtwCeKDgHWZHjiZY4UWI0ou783eQ4R3F7AiHIcIDBbv6ZR25SxQ8kTydNec/59rQbDqNGt6u+h47du4ZNJkKdROXBCTyVPEHtBp7UYllbMy+iRhXfzQWI29fOESMWwCfN57mRHt5v/MpQO7BuuyFhCi9sdis/Qb8Ow0aLHYbOquRLxpPMzEojeW5b7IyZSZfNhZwY+Ro7sjdilIs48X0G38hmgxWs/PvaLFZUFuMeP6K26bBaqakp55nzn5EjbYNN4mC51Nn8eK5T6jUtvZ77LWh2SyNHdfv80ljMTjn9wCnuOsx6Xi4cLdzPgpg+4hbiXENQPQ73C//CJ1GR9upf58Y7DXpMPSJnn8kBMw2K/mdldyeuxWFSMqGoYvBDktzNmOwmXk5Yy4ZXlG/abxQrWllSc5mukw/WvGHKL1Ym7nwLzG9+Hex2KyU9jbiIVU54wRqNG2Y7FaiXfx+lyvpAAP8L/N7tcG/3HCr0+mora3FZOo/XJ2cnPwbWwwwwAA/54de+l01R7gtfgLeMlfqdR28VPIZDyVeg7f8Rze2/58rgr0mHa+X7eeThjyOt5WxMnk6nzUW8NL5fYSrfLlr0CRW5G1jZcoMLHYbDxa8g8lmYVXabEb4xv1prk8mm4VDLeewY2d1yT7GBSbxbfMZrHYbx9pKmRY+DJvVRqu+Bzt21pV/1be6b8dsc2TOTA0bxsrivcyMGMmjhbvRWU08XrSHOxIm9LsIBGg19PBAwa5+9x1oOctF/oO5yG8wdboOtve5d705bBnftZyjXN3E960lTA0byqaKb53bLYy+lFptO3bsJLqHkuoZTqjSh1jXQCRCERa7lVZDLxEqX8RCEffm72B5/ARkIjFH2s4zwieegq5qVqbM4Pojr+Ijd+dI63miXP25L38nDyVdi7/Cg2f6HM+eSJ7GSN94jraVcqytlJvjruDD+hzuH3w14SpforP8uadgB7OjxmCwmOlEjcVmp9ek44O6HB5Pmoa3zIUni9/n4cLdrE6fjUAgoEnfzTDfOF4r/ZLvW0sIVnjhK3PnzkFXsrb0S0p6GlgSM5Yuk5Zus44Ok4anz3yIzW6nStuKSCCkXtvBlUHpfNdyjlviLifTK5pL/BNpM/ZSqm7q/3o3F3N1aDYvnd9Htaad1emz2VD2FZNDM1mXtQilWIqrRMHc6IvQW00ohVLcZSou8RuMxmrkrQvfYbXb2Fp5iEv9EznZXoHWauRcTz2BSg9uOfWmsw1vSexYtlUeoses4/Givbw5fCnXff+Sw00wYy5aiwGd1US2Tyzv1Rx3VlIeSryGQLkHQoEQg9WExW4jXOXDyXZHZfK2+AmkeUaw7NQWmg3dHGg+w2UBSVRpWsnwikIhltKo6ySno4JUz0iW5mym06Shy6Tl5Yx5VGlaye2spFbXzqKYy+gwalCb9f0Ek1IsQ/mTxQmxUIyn9Ne/4uUiCWlekWzIXkSvWY9IIMRDomRt9kKmHHoRU1/7XJJHGMtiL//F4s3P3ycuEjkdRjUvlexziqUfKoRLTm5iQ/ZiYt0C/1TR9PM5JTepkt+zDCoRikjxjOCljDl4y1yJdQ0AHIYRHSY1qZ4R//DzKkTpzbLYy53vM3BUJH9u//93wNEyWM8tp97AW+bKuqyFmG1WluZsxmizsDF7MdGu/gOiaYABfgd/+F3S1tbGpEmTcHV1JTExkbS0tH7/BhhggN9Pp0nL0pzNfNFY4Bg213Vyc84bgJ2S3gYadY5Vb5vdRoWm5RcuYD+ly6RB9xNXvXajmp5/0sv/e+gx6SjsruHa0KEIcLh3neqsJFDhgVwkIcbF32HEYDFyV/527ju9E5PNQpjSm1i3gD/VItdFLOe+xMmkeIRjx85XTUVY7TZiXQN5NOk6FCIJdsBDpuK51BsAiHTxY7hPHE+nzOS1zPk8d/YjmvrmknR9WTMWuxW91ezMSAFHNWtt6X6Ku+uc4bhD+9zBHuvLE4pU+XFnwpXMjbqIQ60OsTTKN54kjzDeuNA//Pb92pOM8RvE2rL9LM99i1vixjM/+hJeLf2CF859QopnOPOiLiJQ4cnXTcUsT5jAWxe+w0fqyuTgTF46v4+Xzn/G/sYC9o5ZwavnP+eV0s853lbG3YOv4onivc6LuGHesXhKXajRtHNnwkRiXAJI9gjjocRreOX8F1Rr26jTd7Ap+yY2lX2DyW7my8ZC2o292AV2VqbMIKejgseK9vDgkClY7FYONJ/leHsZNruNTxty+b61BH+5BytTZnDf6R2syNvGwuhL2Zi9mGfOfMiHdTk8n3oDIoGQC5oWp1h6Mnk6+xrz0VgMbB1+M1Eu/uypPY7ZbuXRovdoNfSgEElJ84wEYEf1ET5vyGdx9GW4S5VIhCIaDJ08XrQHvdXonPfxkKoIVHjiLnPMeTUZulmRu5UF0ZdydbAjV+tAy1m0ViM+MleeTJ7OzsrD3DPoKlzEclal38gFdTNPpczAQ6JiaexYKnpbmB4+nCdTpvN62X6KumtRm/U8Vfw+14YOJc41kCHuoUiEYg60nqVV38PzZz9mmG8MB1rO8sawJdwWP4GL/AZR0dvMuqxFzI+6mEv9h3Bb7lvclb+dY+2ldBo1PHXmA545+xH1unbGB6YA8GVTAXW6Dj5rzGdFwkRmho9ALpJQo22lUd9Fu/7H1rdabTvNPwkEbtH3UKNp+833ktZsRGcxobMYHee/zczemhNOsQRQ0tNAhbr5d83mqM0Gp5PhioQreX/0XfjJHCYbnzXkozEb/uk+/lPIRRIyvKKIdQ1AKBAiFAiJdQsgwyuqXxte90+qSOCosleom1nd52z6Aw8WvMMFTQt/x4YdxyKbgEZ9Fzf1OQI6K98CgXOGc4ABBvjH/GHBdMcdd9DV1cWJEydQKBR8+eWXbNu2jdjYWD755JO/4hgHGOB/FrlQzPL48YDD3nrK96uIcPFlXEAy95zewYOF79Bm6OWCuoUlJzexLGfzr4qmKk0rMw6/wtG2UvQWE836bpblbOHdmmP9RFOHUU2Locd5u8eko/Unt39Oj0nHntoT3JW/nffrTrJ71O2keUbyQME7vF11iDXpc7nEfwieUpXTkMBqtzkG+rMWEvgnG1forEY+qsvtZ14AcLH/YPY3FaA2G1hV8ikPF+7mTE8dG7MXY7CaePrsh3zSkItEKOKZ1Jl4SPq3KU0KSmdScHq/FXBXiYJlceMIV/nyQtosxvon8VjSdQz1juGW2MudwaZXBqUR6xrItspDiARC7h18NS+c+7hPyAWwKfsmIlW+zIocxbs1x3hj6FIEAsBu59vmYix2h2PcC+c+cbaGfd96jtdKv+SJlOmc7q6muLuWSJWjVfD18q+48dhaZ9talnd0v3MiTOnN4pjL0JoNPJd2PZEuAexrzKdJ34nOYuS2hAk8WvQeTxTv5Xh7OU+kTOfhwt28XPo5nzedpsesI1zpw7SwYYz0jUeEkOdSZ5HtE02MawC7qo4wO3IMm4bexJNJ0wCQCMUYrGYeLHyHFfnbKNc0U9RdS5jKt19LmLfUhTi3QKw2G10mHUIEbKs8xKcN+YgQ4i93RyGS8mTydK4LG8rlgckIERDjGkCNpp016XOw2mx4SFQ8mHgNLmL5rwryDqOapTmbGR+cxuGWEsYGJvX7eZpnJJ5SFxI9QqlQN7Nn9AoC5O4M942j3aBmy7AlnO6q5t6CHchFEjaWf0OZuok9tSdI84rES+bCs2c/4uWMudwSdwWPFO3m6TMfcKy9jMUxl7Gy+AO2VR7iYMs5hnnHcMPR1/BTuBOm9GFiUCoXNC14y1ywY+fBgneZf2IduZ2ObLAGXRfpXpGMD0zl7kFX8XH9KY60lfJY0Xu4S5QcaD7Dh/WnuP/0LrrMWnpNemq07SzJ2cwdedto1nfTou/hrvy3uSlnE9Wa1l+8Pu1GNS+f/4xph19i/on1fFCXw8d1p5z5TVcEpBCp8sNit7I89y0qNM3/+I0JhKq8WZ+9iHsGX8Wk4HSClJ6sz17MnMgxzI++5G/XYiwTSfpVVoQCYT+xVKNp4578HTT1tWq26Ht4oOAdukxagpWO1s6N2YvxlKpQWwzcnb/9FxlW/78RC0UMcgtmXfZCpEIxrcZeus1aRwvp75j1GmCAAX7kD88wBQYG8vHHH5OdnY2bmxu5ubnExcXxySef8MILL3DkyJG/6lj/bQZmmAb4O6I1O2ZNfghmHOWbwOSQDO4/vQsbdsKU3nSYNGgtRrxlrmzIXkS4yte5fY9JxzNnPuS71rMIEHB7/AQ+rD9FjbYNiUDE7tErCFF60WFU89zZjxwOZBlzUYilvFN1lI/qT7EhezERLr6/OLYek473606yofxrwDGHU6FuwY7d2a6D3UavxcAjhbudhgJSoZh1WQsZ/LPgXZ3FSKdJQ69Zj1IkxVPq8ocupIxWM6c6LnDP6R398lAECHgieRqZXlG8eeE79tadBCBc5UuN1rHKPi4gmWtCswhX+WK1W+kx6ekwqQlWeuEmViAXSZ1Bkj+ly6RBIZQiF0ux2Ky0GnoQC0VIhWK0ZiN6m4kGXSefNeQzzCeWdK9I9FYTq859ytK4ywlTemMHbs19k1ptO2N8B3HnoCs50HyWV8u+ABwZXDW6dloNPShFUp5NvYHV5/fRbdLSa9YjRMCL6TfyRWMB3zQXO4/troRJhKl8uD1vq/M+IQIeHHINx1pLGeM/mG+aiznSdh53iZK3hi/jgrqFXdVHOd1VBYCHREW3WYtIIGRz9hK+bi7ik/pcVqbMwE2ioE7XwVNnPuChIddgtFpI9YxAANxfsItb4q4gysUPi93G8lNvOlvUXMUKNg5dzKOF7/3iYjvWNZBnUmcy7/g6bo69nCSPMFbkbUMkELJh6GJaDD28ev4Lzvc2ct/gySS4BZPbcQE/hTsuYjnH2kq5IjAFuVjK+Z4GLgtIwmK30qzv5vvWEgQCAZcHJHOyo5wMr2ia9F08UrgbrbV/ptmsiFFcG5qNyWZBJpQw9/jrDPEI477Bk1GbDbxa+kW/WRyRQMiDidcQqPDgq8ZCrgrNpEnbxWCPEJ4/97HTGEQqFGOyWVCJZKzLXsSbF77jUOs5pEIxi2Iu5a0LB7HZ7Tybej1bKw9S1F3r/B2PDrmOFkMXCe4hrC39kjmRYwh38eX23K2/uBhfEH0Jk4LSCVB4UNhdw/JTb2GxWwlX+SJCQGVfRe+VjHmkeUU6w1FNNgvry75iZ/WP39VhSm/uGnQVjxXt4dKARJbGjsNgNXNH7lY8pS48mTLdaUzxj7DabegtJlwkP7bsac0GVBL5P9jq70e3ScucY6/TbOgmVOnNS+lzeLDgHco1zXhKVWzIXoxMKCZI6UW1ppW7T+/gudQbiP6bCpAabRvzj693Bjr7yFzZMnTp33LmaoAB/tP8qbbiP0Wr1eLn51jp9PLyoq3NcTGSlJREfn7+v3i4Awzw343JaqHXrHfettvt9Jr0/2CLH+kya/mqqch5+0jbeSrVLbyQdiMCBNTqOtBajHhJXZxiSWPWY7Y5xIm7VMmdgyeR7hmJHTsvl37uFEuvZS1wWle3GdQcaSvlgqaFZ89+xObyb3mz8js6TRo+b/z1lhl3qZKpoUO5KeYyAMrVzdixM8Q9lDmRY1iRt423qw5js9uxYSdI4UmgwgOTzcItp96gtLeJDqMancVIu0HNyyWfkd9Rxcn2CqYfeZl78nf0G7b/Z+gsJl4+/xlWu4141yA+u/h+5/N+rfRLRAIhc6MuYlJQOoBTLE0MTGOM3yDuyd+BxW7lq6YiLHYr2d4x+MncKeiu4URHOYZfCbz1lLo4xVJJbwMzjrzCmxcO0mPWsbXyIPOPr8dmt3NT7FhMNgszjrxCWW8TjydPJ0ThRWlvE8faSpkeNhyA79tKeKRgN6EqbxQiKRf7DebW+CtYnT4bP7k7wUovfGRudBjUznMq0yuKCJXvLy6ae8w68vuET6ZnFHGugdiw88yZD7ksMKmvOuEQS+uzF7Ei720eKnyXGeHDSfJwWEt3mx1tRy+mzkIplvJ1cxFaq5FHCnezryGfJ4r3YrXb+KKxAH+5OzKhmDcuHKBa28Z9p3dyrqeBbpMW+U/EZrZ3NGW9TVRomhEJhDyedB2PJV2HSCCkXN1EcVctGV5RNBu6OdFexqr02VwXPow9NSd5+swHlPQ2YMfO8+c+cbgieoTwRPFe7jm9gxG+8RhsZpblbOHpsx9yoOUMXzcVMef462y5cIDNFd8y7cga/GTuqMQy3q876WzDe3PYMsb3hf++X3cSoUBIh1HLY8V7UFsMHG8vY8nJzfSYddwzeHK/1/oiv0HIRRIkQjFL4sZxtquOh4t3c8/pHTw85FqSPRwuciabBQECNg5dTLxbIHcOupKwvjDqdWVfobea8JW7Eunih1ggIlDhwZqMuQQqPDDbLQz1iWNt6ZdMCc3iZEcFjxft4ZXMef2OZVxAEleHZBKi8kYsFJHkHsarmfMQCYTUaNucYmlNxlxSPMOdYgmgw6Bmb+3Jfvur1XWwuuRTXky/kZnhI/CQqghQePBy5rzfLZbAISpdfiaO/tvEEjhaf59Mme60Zp92ZA3lfefyk8nTcZcoCOozUIhw8WPz0CV/X7GkaWPpyc1oLAaWx41nfuTFtBvV3HxqC426TjqNmn+6jwEGGOBfEEzx8fGUljr6lFNTU9m4cSMNDQ1s2LCBwMDAP/0ABxjg747JaqGou4ZP63PpNemx2+1UalrYWPH1P/0yatH3cHPOGzQbupGLJM4L/W9bzqASy/q1iP2Qz6I26/m8sYAz3bWYbVaMVjN12nYeGDKl374nBqeR4BbkmH9SN+Mnd+WVjHkkuYcxK2IUKZ7hRCh9WRR1KTdEjHJe6Nh+lmQvFYoJUXr3uy9I4YmPzBWTzUKXSYtSLCVM6cN9g6/mgcQphCi98JSqcJMouDPvbQ61nuNkezlJnuEcbiuh1dDDLXFXUNBdzd152+kwqn/Xa+0pU/Fq5nwu8UtkVcZsfOVurEyZwbiAZNZnL8JT5oJCLMVf4d5vO6lIRIxrAO+MvI2DLedYW7afZae2UNbbxImOcu4/vYv7T+/iTE/db84h6KxGTraXY7SZ+bzhNFqzkVOdFzDazDxa9B5vVx7ipfOfYcfOodZzCICnz35IUXcNtboOfKSuLIsdB0Bxbx1vXviOjdmLmR4+nAUnNvB542lWp81mZfIM8jsvOCsiQgRMCx/OmvOfc6rDUfEI7ft7bLlwAAGOofMZESN4PHka8W5BRLr4oxLLqOxrx7pv8GQsVgsaiwGlSEq4ygfdz8Rhs7EHuUjC6vQ5+Mhc0VqNfFR/CoB0r0hmhY8izi0QN4mSxTFjGeQWjEIsRSWW8eK5T52W2K5iOd+2nKFS08KKhCt5ImkaJ9rLOdlWzvOpN3Br3HiiXPwZG5DEMO84PKUuHGg+Q5xrIO/UHKFe18k1Idk8OmQqQoGAD+pzUIgkRKr8sNpt3J2/nbvyt6OxGPCWujDIPbhfteQHHix8F5PVzF0Jk7jMfwiPJk3l4cJ3SfIIY3rYcJ5OmcmuqsMIBVDcXYsAAfcMuooAhQcqsYxHCnf329+BlrNoLUa+aixkwnfP8lLpZ7hJFIwPTEFjMfYT/nbslPQ0oLM4MppuT5jo/JlEIOK51Bt45syHNBm6eCBxCpvKv+GBxCm8X3MSd4kCP7kbCpEUk9XMzPAR7Kzq//xyOiroNevpNmr7zm8xYSofvH9iae0hURLp4tevzQxAbzVhtPUPwgWHaFqRt42SPgt0gACFx+8WS/9LiIUihriH8mTy9H733z94Sl9Lpmu/+z2lqr+lWDJazVRpW+k0abkzYRLtxl5kYgkLoy4h2zuGnI4LvHz+8wHRNMAAv4M/7JJ3xx130NTkcDF67LHHuOKKK9i5cydSqZStW7f+2cc3wAB/e2p17dyWuxWL3YrVbmO03yCW5Gx2tFIJBCyOGYvbb2SQSEUiRvrG81ljPuuzFxGh8mW4TxwKsZR7TjuqIQqR1PnFd9/pnTw05FrWle3HbLOyNmsBZpsVi93G3fk7+u37k/o8sryj8ZO5syRnMzdEjGR25BgWxlzC3ae3M9YviceTpyEWinCXONrimvRdtBh6GOwWglQkRm8xcay9jMeK9gCOlVeNxcBXzUVIRWK2Dr8ZkUCACCGrM+bwVVMhrfoeXs2Yj1Ag4N2a45T0NvBY0R5ujrucs911HGotAWB1+mwS3UM421NPm6EX759dhPwWQUovHkq6Bre+Y/aVu3Fv4mTcJUpHC2HtCafhgpfUhU6Tho/qc5EIxVzin0ikiy8Bcg+aDd0sOLHemTeU7BFGuMrnVy982gy9iAVCpoUNBzv4Kzzotei5P3GKw6xD38WXTYWAIzh0efwEmvUOEZzqGcGTxXsZ4h5KfmeVc58lvQ28V3Oca8Oy8Za6MNInHpFASElPPavPO0J1I1S+ZHlFoxTLnKLy5bS5RLj6sqH8a8fvtAsY6RtPWW8jQoQ8njQNsUBIs6Gb6WHDadZ3M9g9hB6zjjeHLsWOnSeL3+eCpgWRQEiKRzjNhm5eOPcJjw6ZiqtEwbqsRTxz9kMKuqpRiWQ8mHgNjboOBECnSU2jrptnU6/ntty3EAmENOm7EAmEvJh2I/5yd+7K387bVd+zKu1G2oxqJgY7DIG+bynhyuB0Hi/ew72DJhOs8mJfYx5fNBZgslu5NW48VZoWMryj8JG5sCptNrtrjqEQSnk+7QaW9wXLmmwWlCIp67MXsan8Wxr1XVwdkklORwVNfcYHsa4BaK0m6nXtZHhH8ezZj2jSd7Oq5FPuGjQJN7ECN6mKQLkHvjI3bosfz1CfWC7yG8wrpV9Qqm5EJBDyRPI0Pq3P52RHOc+c/ZDNQ5dwoqOca0KzGeYTi1QgZtmpLbQb1ahEMkJV3lhsNiJc/DjeXoabREGPSc/67EVsqTjA+d4Guk06GvSdPJ40zWnt/WTx+zyRPJ1DLee4a9BVtBl6WR4/gS0XDvB1s6MCPTYgiVMdF+gx67j11Bu8mrkAoQD0Vgt35W3rl3/UYdJwe+5WXs6Y2y+HSS6SIhOKMf5KkKzGYiB4IDAbcMzBbak40O++t6sOke0T/afPZv5VyEQSsr1j2JS9mGZDDy+d3wfATTGXEe8W6DSJiXcLYlrYMKSif9k4eYAB/uf5wxWmWbNmMW/ePADS0tKorq7m1KlT1NXVMWPGjD/7+AYY4G+Pl9SFcX1D5WvL9jPjyMv0mvV4SlVMDR36m2IJHO1eS2LHsnPEbcS7BqESy8nwjqJe1+lYQZe5sn3EraxKn40QARXqFkw2C6leEZjtVpbmbKHV2MN7NcecbXir0mc729QeKXwPN6kCH5krO6uP8HjRHu4v2IWPzJUrglO4Pe8tluVspkzdRLO+m+W5b7EsZ4sztV5vNfFd8xns2EnxCOf90XeyJGYsAHmdlbhLlPjLPYh2CyBE6cXU0GwWx44lROVNkNKLuZGjyfaKBmBd2VdOsbQg6hIKuqo521MP4LzI/b38IJZ+4AfBZ7FbncPz4wKS2Tx0CVNDhwIOxy+91cTK4g94JvV6VCKZUyyFqXx4LnUWvn02zd0mLUar2TmztK8+j9fKvgS7nYnBabiIZWws/xpvqQuX+if2O5Yrg9N59uyHPFj4LjfFjGVjxdfcM3gyH9blOOdcMr2iANjXmM+bFw46BrBd/R3BpH0XssN8Ynk5Yx5BSk+sdhsrEq7krWHL0NtMlKubWRo7jm3DbmF8UAoPFb5LkNILqVCEzmrkocJ32VNznCzvaBbGXMLL5z9nZfH79PbZfC+MuRRPqYpnU67nnsGTeXjItYSpfPCRueEvd+eOvK3MDB/BSN94VqbM4KHCd+k06ajXdvBZ42n0NiPPnP2QWl0H68q/4smU6TyaNJVoF3+6TFoeGnIN9wyajKfMhVClN08Vf8BzZz9mjP8gXjj3CS+m3YjZbmFz2bdc7JeITChGLpIQ5xrIrMjRrCnZx8m2CqRCEXOiLsJdokRvNfdrSTTaLDTpu/GWubAg6hKCFF48kDiFQIUHca6BLIu7HJFAyMOF7/HCuU8IkHvyTMpMJEIRq0o+5Y3K77iqL1B1XdZCjrSVcqr9AtXaNiYFpxPl4sdTKTMIkntye/x4sryiWRxzGa5iOTPDR1Krbeemk5vQWY0kuAahEsl4Nu16lsdPYMWgiTxRvIdghRc5HRcIU3nzwtlPWBh9CWN8E3iseA8PJE7BZLWwMnk6KpGMdqOao23n0dvM3HD0Vax2K0KBgMsChiARiLghYhSpnhG8lD4bd4mSFM8IFCIpcqGUsz11lPW1jL2aMZ91WQsRC0RUaloo7KrB/BOXOx+ZK9eGZv/q+ypE6fW7xMDPXfNMVsvf0iHuX6XTqOHOvLedLaWzI8c42/NuPfXmf1VFRimWEe8eTJZ3NBODHAsXmyq+5flzDpOu4T5xXBGYMiCWBhjgnzAQXDvAAH8C3SYtDxa847xYFyBgz+gVhKl8/qX99Zp1fN1UTKZ3FOEqXwxWM7kdF3CXKhnkFkyHUc3sY6/TbdbiLXXhyZQZvHjuE+5PnEKSeyjdZh2PFr7HlSFpDPOOZUf1YXZVH3XuP8UjnHsTJ3PrqTfpMmlxEctRiWW0GHqQCESszVrAEA+HXXKHUc1HdaeYHJKJr9yNHpOO/U2FjPSNdwYhAjTruxEJhM4WnnaDGrPdglIk48qDzzntitM8I5kePowHCt5xbrt1+M0Mdg/5l16rn9Os7+brpiJCVT4McQ/Fjp39TYWEKr15pGg3o30HcbH/YB4u3I29TzDJRRLWZy0i3i0ItVnPxopvmBCUhlgg5OZTb7Ag+hIMVjPDfGJ5sOAdhvnEMjYgiWptK2vOf97v98uEEp5KmcH2qu+ZGT6SeNdATndXk9dRyRdNBTwyZCqjfOP5urmIVSX7uD58JHMixzgztzRmPYXdNcS6BPJtyxnWnP8MD4mK9dmLqNG28UDBO0iEIlanz8Zb6sqd+W/TbOgmrG84vVTdxEOF7wIw1DsGqVDM4bbzJHmEcVPMZdyVv51ghSfPpN6A0Wrmzvy3sdptvJo5Hz+5G/ef3kVhdw0yoZiVKTPYUnGAMnUTIoGQD8bchc1uZ+MP1S3g1rgrKOttosukxb/Pae6V81+Q4hlOjbaNTpOGdqPaaWbhJlGgt5hQiGVoLHq+by5hTvQYdBYTaoued6qPclv8BOp0HdyW+xaX+A9mXtQlLDu1BY3FgKdUhYtYTp2uA5FAyEvpc2jUdfJ8ySf4yFxZlT6b10v3My1sGF4yF0p7m/i6uYj5URfzdVMhI/0S2FT+LStTZvBZQx6nu6r7srpgacw4rgxOY0vFt1wRlMa7NUep1rRy7+Cr6TXrONtTz8GWcwx2D+brPvONWRGjuC5sGGqznk/r85gQnMrDhbtp1HfhIVFxX+LVrC39kgZ9Jy5iOe+PvpM78rZxS/wVBMk9CVC4c7qrmltOvckrGfNYV/4Vpb2NzAgbjr/Cg+NtZdwSfwXH28rYWPENYSofnkmZiYtYjp/cHbFQhMZs4NvmM/gr3En3jAAEFHXXUqNt5fLAFFx/tmjTblCzrnw/nzecdi4axLoG8FzqLEJV/dtvf47arOdQ6znSPaMIUnpitJo53VWNt8z1f8Z1TWcx8n1rCU8Wv++cAyvtbeCWU2+yIuFKrghM+cWs1n8D3SYti09ucs52ekpV7B51R79Q4gEG+L/G79UGf1gw2e129u7dy3fffUdrays2W/95hw8++OBfO+L/AAOCaYC/gh9mln5ow/uBW+PGMyU06x9WmP4RjovKHwfpDVYz4r4wyLzOSu7K3+50ivOXubNp2E14SFTObTqNGmRCMTKRhPO9jSw4sd65rysCU7g7YRLNxh5uPfWmc+VeJBCyLmshQzzC+g2KG63mfrMQBosZufjH2036LpbnvoWP1JWVKTMQIGDlmfep1bbzRPI07ju988fsD+DOhEmUq5v4tCGPMJUPG7IX4/M7W/J+D71mHWabFZVIxomOco62lbK/qZAsr2hG+w3i2bMfYcdOvGsQ3WYtFruNLK8oZkaMpLSnkZfOf8ZLGbP5sDaHb1rOADAtbBgHW87RZuzFU6Li7RG3MvPoy2gtRsb4DeL2+Iksz3WEoA5xD+HhpKlsKv+WBLcgsr1jkAnFqC0Gvms5y7jAZEKV3tRo2whT+fzigsVis9Ks73LMHuS/Ta9Zj0woxmRzWJAPdg9hftTFPFK0G4PVjFwkYWXyDLZVHuLW+PFUalp44Vz/mIcHBk/BR+7Kfad3YbFbCVJ4orOY6DZrcRXLWZe1EB+ZGz1mHXflb6dB3+ncViQQ8nzqDfjI3Hi19HPuGnQVK/K2MTfqYi71H4zJbuXBgndI9YzkIr9BTme9HwSpUiRldfocIlW+PFDwLtMjhvFBbQ4qsYxFMZeyumQfy+PH8/zZT1iZMp1nzn7ETTGXsbf2BHcPvgqN2ciynM0ArM9ehB14qOBd6nTtrEyewfbq7ynurmN8YAozwkfwTtURbogYhUIiY19DPkPcQxztZkovDrWUMMZ/EMVdtfSa9eyoPkyCWxA3hI9iuG8c7tK+1s66E2wo/wZwCM8F0ZdwW+5b/VrZrg7JZJhPLMEKL053VOGncOdURwVj/BN5rGg3PT/5PJAJxbyWtYAguScN+i7WnN9Hu0HN69kLebRwN6XqJlQiGU+mTGdTxbfcEnc5r5c5xNP4wFRuT5jAc2c/4lBrCWkeETyddn2/94zGrEcqFCPte5+arBZMNjMuv/H5o7UY6DRq6THrUIikeEpVvwiD/Tkas4Evmk7z4rlPCVZ4sS57EVWaVu7KfxuFSMqWoUuIcvX/h/v4b0FnMaK1GHGXKJCKJFhsVjpNGpQi2X+lWNL2ffY8Wfx+v/tvjbuCKSHZuEn/te+pAQb4b+f3aoM/XIO9/fbb2bRpE5dccgn+/v8bq0kDDPDvUKNtc4olD4mKGNcAcjsvsLbsS8RCIVcFZ/xihff38HOLa7lIgslq4XRXtVMsxbj4Y7CZqdd1ct33L7EueyGJ7qGIhSK8ZC5YbFbKepu4+dQWwFH5+qHiEqL04srgdJRiqVMwiQUi3CQKxD9Lfv/54PhPxZLWbKBC3UydtoNabTsPFbyDWCQit8NRbavUtJLoEUqcayD5nVXkd1U5QljT52CyWVgSO/ZPFUvwY8tep1HDI4XvYbSZSfII45a48TQZulCKpES6+PF06vXY7XbqdR3U6trxkCgZ5ZtAjKs/+V3VzI66CI3FwImOCvbUngAcF/+PJV+HTCjhtcwFvFdznPnRF5PTXsEjQ6bybvVRbom/gmNtZRR21zAlNJNNF77l5tjLEQoE7G8qRCIQMjV8GL4yN9wlSiw2a788oUZ9F3OOrWV91iKeS72B23O3Oi/Uo1z8eDBxCotObsRgdQzvP5R4LXtqT5DpHU2QwpMwlQ87qg7TqO8i2zuG4T6xxLkFIhaKeDp1Jg8WvOM0KVCJZazJmEuHUYNEKGFLxQFeSJvFrGOvOY9nRtgIIlS+fN5UwLneBrrNOjYOvQkB4CVzxWq38VTKTAB2VR1mbGAyMpHYeXwBCg/cJQp0NhOJniF4SFRYbFZuS5jA4dbznO6qZmWxw7r8ntM7qdG28XjRHjYOvQmZUEKvXc/LGfOQicREuPhhtJp5KmUGjfoutlUeori7jkv8BpPpHc2iExt5KnUGepsZk8lClnc0PWYdx9rKONtTz/rsRZzrqcdX5sa68q8Y5BbMwphL0ZqN2Ow22gyOrBqLzcYd8RORCMWsL/8KuUhKmmcEJ/raKoUIWBh9KZ1GNTnt5ayv+IankmfQZdZyrK2Ux5OmsyJ/m/M1vCPhSr5uLOKCpoVHkqaiMRt4KOlaHi/aQ2lfBe+a0GwONp9jYlAaD5x+h5UpM8jtvMCk4AzerDjARf6DCVf5Mi18+C/eMz8XRlKR+B+2WanEclRiOaH844rST5GLJMS7BiETimnQdzLn2GtoLEasdhvBCq//Ske830IplqEUy5y3xUIRfnL3f7DF3xer3cbpzmqnWMr2jsFdouDr5mLWlu3HTaJkYlDaQFveAAP8A/7wDNOOHTv44IMP+OKLL9i6dStvvfVWv38DDPB/DaVYRqjSGw+Jik1DF/NM6kwmBKUiFYoZ7B6C4mdi499BIhThJ3fDRSwjwTWIlzPn8XrWQsJUPrhLlXhKXfpdeKstBrZVHcJgNROo8OCTi+7lhoiRjhkIjwjuyNtGk74bsUCEUiTFaDNz08lNvzu1Xmcx8n1bCQdbzvJE8jQECCjornGKpYeHXEuDrpNkjzCuCxvGE8nTyPJy9NKHq3xYkXAlfrL+FyFm2++fh+gx6Wj/icOezmKi26R13naTKHgtaz4ZXlE8m3o9Ua5+hCt9WJU+m5UpMwhUeGDHzjNnP+SFc59wvL0coVDA2rL9vF62n/drT3DP4Kud+/OTufFI0nVUqlt4pfRzghVe3Bx3OS5iGaP8EghT+fBw0lT85O5cEpDIxuzFbKs8xMzw4dydv52nz37I+qxFBKu8Ke6qZe7xtdTpOviysYA2g2Ng32g1s6PqMDqriWptOz0mHZafOBd2GDV0mbROu3iAHdWHuTFyNLMiRiEWCFl17lMa9V0M9Y5hckgmdboOGvVdCO0Ohz3ZT7KxXMUKhAIh3jJXBAKYGpbNE8V7+73O79edoNOkxV0ix2A106Tr5JP6POYeX0eFupluk5aT7eXckbuVqeHDeKTQUfkS4lhQC1V6U6FpYdrhNQTIPYhy8eP2QROZfXStwzEx9gqqtK0sOrnROYt3R8JEmvXdlKubWXhiA/ee3oHJYsFktWC0mjneXs7BlrNUaloAaNR3E6TwRC6SsKbkM8x2C48Uvccjhbv5tC6Xg63naDZ0syJvG/GuQbxW9iVBCk9ujR/Po4W7eaPyAI36LjaWf02Ntp0P6nJI8Qwnv7OKdVkL+aKxwCmWAGzYWZazBZvdzmeNp3ko8Rq+aCqgqKuWCUGprCr5tN9ruLH8G0b6xaO3GjHbrLyQdiMf1uUwLXwYEoGI51Nv4PKAJC4OGMyrpV84rd1DlN406buYEpqN0WJiXuRF6CxGajRtv+s98mciFooY7B7CuuxFCBHQY9ZjtduIUvnxYrrD8AMchgm9pr9XiOv/ZUQCIfFuQSR5hDLMJ5bHk6Zx16CrmBCUSpjKh6E+MQNiaYAB/gl/uCUvMjKSL774goSEhL/qmP4yBlryBviraDX0oLeaCe+bWeo0aug2awlT+vQTMH8GdrudGm0bSrHMueLZpO/CbLP+6sxUu0HNhoqvmRd1MSFKL7pNWr5uLCTePZibT72B3W7n1cz5eMtcWZKziS6TlieTpnOx/+B+2Tq/RqdRw4IT62kz9PJ61kIeL97jrFz4ytx4a/gymvTdfN96jssCkhjsHkK7UY0QAV4yFzRmR/ZNonsoQUpPTFYLxd21uEuV/zTXpMek472a4xxoOcOajLm4S5UcaytlVck+NmQtIrwviNdis6K26PH8ieVyr0mHm1RJt0lHlaaVbZUHOdZeBvzorCdAwJPJ07DZ7dTrO/m47hQPJ13Ldy3nmBSUzheNBQxyD2ZiUBoi4a+vPRmtZo62lSEAnjnzAStTZ/JezTGOtJUyPjCVGeHD+a7lLG9XfU+6ZyRPpc7Ebrcz//g6lsSOQyIU8VjRHuzYiVT50WFSOyuZT6ZMo7i7jjcqDmDDziC3YFYmz6Cwu4aVZ94nQO7BqvQbmXd8PRa7lTmRY7giMIXluW/RaXK0a1rsNqx2G+EqXx4Zci1KsZSXSj4jt7MSkUDInQlXsqv6KA36TmRCMe+OuoPvW0oY7Z/A/OPr6THrcJcouTIojXdqjnFtaDZBCk9eK/sSpUjK06nX06Tvwk2i5KO6HOeM34zwEeyrz0NrNToqPVkLufHYa84q2gOJUzjZXsGRtvMIcBg83Bo3niCFB0keYRR2VeMjc6fd1IuX1IVNZd+wIPZSdlYe5sao0XxQm8MI3ziePvshCpGUp1JmYLZZeazoPfzl7iyOGcsn9bmOQfjgNJ4u/oAVgyax+ORGesw6RvnGc1v8RO45vYMabRuD3EK4KfYyVuRt44aIkVzkN9jZnjcpOJ25kRdhx84DBe9w7+DJTuc7mVDMopjL2F71vdMIZueI5djtdvY15JPbVYlCJOWWuCs42VbO2MAkFpzYQLOhm3jXIJ5KmUGVtpWHC3cTrvLhudQb0FvN3HrqTURCIeuzFhLh4vcP36N/NkarmbzOKu74SVhyoMKDl9LnEqz0RG028FjRewzzif3NVq96bQdiocjp3tdq6MFgNf/LM58D/IjZZkVrMeIqkTtjKbpNWmQiCRqzAQECfPrmJTuNGsw26y9iGAYY4P8Sf9kM07Zt2/jyyy958803USj+u3peBwTTAP9XUZv1/doCe816LDYrhd01WG02znbXMTNiJDXaNmp17XQY1EyPGN5PZPwWDbpOKtTNvFdznFOdF/r9LMUjnBsiRpHbeYFFMZfh+ZNZHa3FwIHmM6w88wEhSi9ez1pEg66D23K3ohBJ2PxP5iHqtB28VLKPY+1lRLn4MSUki0Otjhmj5XETSPEMx12qdD7fX5slM1rNFHRW023W8klDnjPnCOCJpGnkdVbySUMeN0SMZGroMG455cjMGheQzLK4cahEcjxlvz4wXaNpo07XwVdNhWjMRpYnXEGnUcvRtlJ2VB8GcNqbA1wTms3S2HHY7XY2V3zLCJ94dDYjTxTtZZBbEA8MuQaN2cDdp7ejFMlYnTGbY62lBCm9eLToPe4ZPJncjgvMjhzNx/V5+MpcGeIRyon2cnZWH2FsQBKpnhGsKvkUV7Gc17MW0mXSclf+dkfwb+Z8DrecZ7hvLI8UvcfjSdNI94qg1ajmjtytTAhKxWA1IRGKOdZWxs1xl/No0Xv9nOseGTIVD6mKou4akj3C2Fl1GD+5B6me4SR7hrO6ZB95faIJHKL6lcx5v7g/SuXHHYOu5OHCd+k1653ByZsqvmWM3yDuSJhIfmcVT5/5kGgXP55Nu4EnivZya/x4TDYLd+dvZ1xAEoPdQ4l29edYaykdRjXTI0YgEghRiWQcbj/PhIBUusxaZEIxlZoWanUdrOmzdP8BsUDEqnRHiPTJjgpmR46mRtOOyWZhb+1xVgyaRIu+my8bC7g+chSNuk7swCNFu3kpfQ6fNuRxWUASWy8cZHn8eALkHhxsPYfOYmCkbwJthl6UIintJg0ai4FUz3BeOf8F86Mv5r2a41wRlMK9p3ditdsIVXrTa9bTY9bhJlHwcsZcIlX+qCQy/hMYrGZOd1Y5jUICFR50GjUYbRaCFV68kDaLzRXfcrD1HAIE7B51+y8EXZ22g2U5m3HpO36hQMC9p3fSpO9iY/bi/7gA/F/CbLNypruWe0/v4NXMBcS5BlKja+PmnDd4cMg1ZHlHoxD940WwAQb4v8ZfNsM0bdo03nnnHfz8/IiIiEAi6d9ulJ+f/8ePdoABBvhL+fkMlZtEgc5iRIyId2qPUtBVzc6aI4QovRjsFsL08OGIcbhv/daAc5dJS5dRg0Ikpdesd4ql5XHjcZcqefrMhxR213CJPpElMeOcK81O8WanzwpbTL2uk7nHXkdtcbT4+Mq8+80P/BoqsZRJIemM8R/Ec2c/5nxvAzMjRhKk8OCtCweJdQvAHSVNui5eKf2c5fETkAslWOxWTDYr3jJXjFYzka5+aMwG9D8Lcu216En1jOCThjx2VR9ld81xrHYbCpGUaWHDUAhlvymWarXt3HLqDdqNah4aci1JHqE8VrSHkt4G1qTPxWq38U7NUadYmhySydLYcU5Bme4ZSbDSky+bTvNC2iysdhsLTqwnUO7Jmoy5uIkVfNqQh1QoJsMrik8uupejreex2+34yd1ZEH0xWrOBDpOGNM9IGnVdfNNcjKtEwZ0Jk0j1DEcllmGyWViZMgOFSIIAUFv0yIUSNg29iS8bCxjkFoSbWMGG7EXsbyri/bqTPJh4Dd82F1Pa28jVIVm8XXXI+bxTPMN5qPBd0j0jOdddz72Dr6bLpOVMTx0FndUsiRnLTTmbnI+/KjiDY21l5HVWIhGImBY+jPdqTlCpbeXl85/xXOosbj61hR6TjtC+6sP3rSVUa9uo03Zgx45SLKNW206trp23LnzHjPAReEtdKO9tRiIQsa8hj6lhQ3GTKqjUtPBk8fvcHHc5E4JSqdK2sjz3TS7yH0yWVzQGq4k5kWN4u+p75zE+l3Y9h1pKsNttzIu+BJFAyIr8bcS5BnJT7Fhqte3cX7ALvdWEsO85HGguYveoFTx35kOOtJcisAt4JGkq2yoPMT4ohST3MHosWjZfOMCy2HGc72ng8eK9DuGaMZ/b4sdTr+/iUGsJYwOSWJV2I3flb6dO1+F4P4vlPJk8HaPF/JvVzb8Cm92G2mLAZreT4BrEqozZNOq6WJ77JkabmQ6TmrM99Q7Tl5QZv5j5sdistBl76DBpaDX2clvuW0gFIso0zQgR0KTvJkjhNdAe9i+isRhYeeZ9esx6luZs5t7Bk3n5/Of0mHU8VfwB742+Y0AwDTDAv8gf/lSaN28eeXl53HjjjQOmDwMM8F+MUiwj0zuSck0TBV3VANTrOrl38NVEqvw40OcOd1lAEi4SOd0mrdPNrUHXSb2uk++az5DlE0OHUc2M8BEEyN2p1rZh1dh4NGkqZ7rrAKjUtDDEI5Qes44tFQe4MXI0Zb1NvFtzlOdSb+Ce0zvoNjtmj0KV3qxKn02AwgOLzUq1tg13idJpV16rbUeAgG+ailhf8TVXBKbwWuZ8qrVt+MrcuCPXEeDZbtSwMmU69xbspLS3kQp1M69kzufrpiLWl3/NUykz0FuMRLn682rpF5zpqUOAgBClF3W6DlaX7OPewZO5e9BVrCr51OlI+HrWQqJd/H9hyvED3SYtHUY13jJXWo29PH3mA7xlrrQZexEiwEUiw4btV7f9gUSPUO7Kf5sHEqewvfJ7TnZWYLCa6TZr8ZO7s770a+ZEjaaou4Zvmou5PDCZiwISGe0/CLFAxPG2Mp49+xGD3UNYEjuWvC5H9ebDuhwuD0ym26jBR+HGjqrDBCg8uMQvkTi3QBr0HbhIFcw+upYIlS+X+CeyuuRTboufSJSLH48nTWPLhQM8PGQqXSYN9//EGh5g+ak3eTlzHkdaz+MpVVGr6+DdmqPMiRyDp9SFm3O29Hv8m5Xf8dCQa5kcnMHF/olEu/oz3CeOFXlvMy1sOIdbS/CWubK79jg3hI/izoRJvHR+H7XadgAGu4cwO3IMTxd/wMrk6fgrPDjf3cCGoYvRWUzorEYunPsMf7k7MqGE71rOYsfO62X7Odtdx/H2Mow2C2e765kaOgx/ubszNPgHPq3PZ2xAEmW9jSjFUlzEctZmLeDmnC3ccuoN5+MCFZ5cG5bFurL9zIocxYd1OQz2CKXdpGZO1Bh2VB0mwyuKvTUnuD3hSh4o3EWjvosuo4YbIkY53Q8VYimLTm4kwsWXnSOX4yqW02nSIv2JiYa7VEmgwpPAvpmt/xRKsYxRvvGsyZhLtKs/fnJ3vKQurM1aiN5q5NmzH9Fm7GVcQDIjfeJ+seghFooY4h7Gq5nzuC13K9V99tZCBKxKn02aV+SAWPo38JSqeCVjPstObaHV0OOcRXSXKNgwdJEzr26AAQb44/zhT6bPPvuM/fv3M2rUqL/ieAYYYID/IF0mHfsa8vrdt6PqMMvjx/NiyaeYbBYCFB6Eq3y59/QOnurLf6nXdbKp4hueTb2e2cfW0mXScnv8BLK9Y9hTe4JGfRdykZSZ4SOYdmQNMqGYzUOXsq8hl/frTqISy/CXuyMVitFajNh+0hlssVuxYcdis1La28iyU1tIdAtlZeoMdBYjS3M2IxdJeDrlet6tPcb+pkLK1c1Ualq4OjiL59NmcUfeNk53VXH1oRe5OfZyDFYzcyPH8HVTEevKvwLgq6ZCpocNRywQo+7r7b9v8GQiXHzZVvk9x9vLaDeofyGMTrSXE6r0RsGvCyZXiQKFSMbS2HG8XrafMnUTbcZe3CUKXkybzZHWUnbXHAd+bMn7pD4XkUDorDLprSYiVL5Ualo53HbemZXT1Td/tijmEh4seIfzakd+kMZi4MaI0RhsZr5uKiRY6U2cWyC3JUxgRd4259xTulckXzUVATA1dCg3xVzGzuojrD6/j5nhI0jxjOCjulO8NXwZHlIVs4+tpdOk4ekzH3Bf4tU8deYD6nQdPFz4LqvSZ2PHTqpHOItjLuPBwndpMnTz3JmPuH/IFJQiGdurvie/s4q5kRfxzNkPnTNLT6fMZFPFN+R2VvJSyT72jr6T3PYLHGk9zyjfBHaNvI38zkqmhw9nWvgwluVsodusIcE9qN9rrRLJMNrMPJx0LRvKv6HHrOPZ1Os539PAN83FHGsvY13WIuw2OzKFhEnB6UgEQvY3F3Gw9RwAwQovHku6Dl+5G980n3GaTswIH4Gf3J1XSj/HarexJHYs2B0X/QluwSyJHUedroPPG05jsVt5KX0Ox9pKuSV+PAuOr0NnNXFjxGieTb2BZTlbaDZ0o7EYyPCOZsr3LwKOzK4bIkaxs/owQQpPlsePp9es55GkqeR2VOIhUdJmVLMsZwsGqxmZUIzZZqVe18nDBe+yOmOOcw7oP4VSLGOoT4xzPqbLpOXz+nyOd5Q7K6bfNhczPiiFzF9pAZOKxESo/PCVuTkf7ylVEecW+B8Vf/+rhKq8eXjItdyW+6MJ123xEwhX+g4scA8wwL/BH67lh4aGDsz/DDDA/wBthl5uzX2Dep1joP/KvhT4nI4KXjn/OY8mXcco3wTCVb7ckbeV872NLM3ZTLOhm1dLv6C4u5YH8nfxcsZcBrkFM9wnDnAM7Ce4BXFNaBbguCBNcAumSd/Fx/W5gGM1/hK/RGaEj+CJvlYkP5kbUqGYJn03d+RtpdXQS5O+C6PVQl5XJXflvc2SnM20G9V0GbUIgBsiRgKOCpZKLOOKoGTeqT7Ka5nz8ZSqeGTItVRqW3k86TrKepucYmmUbzyX+A/hUGsJhV3V3Bo/nqdTZjDGbxBmm5VJwemsTJ6Bm0TB62X7kYskZHhGArCp4hv21p2kp88F7KeufABas5EAuTuRLn4kuAUDMNwnjnXZi/CQKp2hkVcHZ7IueyHzoy4BHDNPP1SxJAIhFwck8tzZj7BhJ8EtiLS+3/9q2ZcUdNf0G5DfVnmIdqMag9XEntoTPFG8l1virsBVLGeQWzAeEhWvZs5jRcJEpoUNQyoUc6l/IonuodyZMIkxvoMY7hNHuMqXkb7xyEUSlEIpT6fMRCwQUaltZUnOZup0HUiFYu5PnEKPSUemVxSPJl/H2rL9PJMyk0FuwawYdCX1uk6ePvMBF/kPJtEthMeL93Bz7OWkeUbwSNK1nO2u45a4KxjpE88LaTfyeNF7PHZmD63GXp49+xELT6znuXMf02FUE6L0ZmP2Ykb6JvBY0R4AZ+viqc4LfN5wmkCFFzXadhr1XTxQ8A57607ydXMxWouRwq5qpCIRr5z/nHCVL1eFZPb7e2X7xBCg8OB8bwNai4Gboi9jVfpsRvklUNJbz8NDrmWMXwKuYjlfNJ2m1dBDrbbNERwrc+PJ5Ok8knQtr5d9ydqy/VRrWrk8MBlwuBded/glmg3dKERSpoRk8Xnjaefvfjx5Gu/WHKWouxaN2Yi7RMnGim/YXvU9N0SMxGSzkNt5gW6zFjeJgtXpc3gseRoigZAqbRuN+i5MFgv/aX4QS70mHa+VfsmHDadoNnRz16BJJLqHYMPOPfk7aNZ3/2LbVkMP95ze4RRLAB0mDbfnbv3Vxw/wx6jUtPBI4e5+960q2UeZutH5+TLAAAP8cf6wYFq9ejX33nsv1dXVf8HhDDDAAP8pJEIRF/slIhOKeT1rIbfGj+fOhCtRiWRc7J9IaW8jjwy5Fj+5G08kT0clktFuVDPv+DrK+3JjZkSMwGqzc1/i1QiFQt66cBBXsYLn02bhK3PDW+bCi+k3ckPEKB4t2o3RZmFp7DjGB6YgF0tQmw1Y7FaiVH68nDmPZ1Ovd1ad9FYTI3zjWZkyA4CS3gY6jGpUIhkbhi7GX+6Bq/jHFpPV6XN4rfRLvmou4vHiPazLWsQ3zcV81pDPnflvMzNiJCqRo0XoyuB0Pq7P5YvG01waMAQhkOoZgY/czfFfmSvpXpEcbD2HXCRhQ/ZinkubxdXBmQgREOPij1Qopt3Qy8byb6hQNwMO574P63MoUzfxZNFehvrEsCj6UiYGpTHn2OscbSvjlrgreDDxGpbGjcNdrOSGiJE8OmQqK1NmOLN15CIp7mIF4SpfBruHcEvcFUwNG8pQ7xj85e4kuofQqHfYtd8eP4HNQ2/ijQsHWF/2NavSZuMuUXB3/nZmH3udq0IyeTF9lsNy3ahlVsQodoxYjkwk4dXSL7g1902mhGbhJXWhoreZ2/O2cry9jEZDF4PcgnhoyDX9zpvHkq4jQO7B4dbz3DN4Mg3aDoQIaTequTPhSnxkbggRkOAexJHW8zyZMgON2cDjxXuYHj6cj+tyGe0/iM8bT7Mg5hLcJAoUfa1b2yoPcaKjHLXFwMNDriXKxWH6oRTLON1VhR07yR5hrMmYy7LYcQBUaVvRWAw8mTwdmVBCo77Lad6xNHYcI33jWXpqCxKh2Bmy+lOKu2ppNnTzYMG7bK08iA07QoGAO/K28kVjASW9DWR5x/BI0W7WnP+cXVVHcZUoyOusZGPFN7xbc4wQhTdZ3jEAvHDuY1I9IxnpGw/gvEhdm7WA92qOca6n3vm79zcWMCN8BBFKH2Lc/KnUtFLW20Rxdx0PFb7L8+c+pkHXyfL48axJn4uHREmGVySPJ03jseTrHIYLdvO/8zHwh+kyabH1PSc3qZJlceO4KjiDp5JnMDk4k+fTZpHoHsLcqIvw+plpjNVm5WxPPed66hEi4KX0ObyetQCxQMQFTQu5HZWYbP95Afi/QpdJy4q8bX3ulQpeyZiHn9wdvdXE8ty30JgN/78PcYAB/mv5wy55np6e6HQ6LBYLSqXyF6YPnZ2dv7Hl/38GXPIG+G+my6ilx6wjROmJWChGbdbTZdLiLXNF9U8MEn6LbpMWjcWAu1jJgZYz1Ok6mBKaRYW6mSeL32fb8FsQCYRIhSJqtG1Ua9ux2m2sLtnHTTGXMco3np3VR0jziuTV0i94Ink6+R2VpHlFsrL4fTYOvYltFw7ybcsZzHYrAInuIbyYdiMthh72NeST7R2Dm0TB181FZHnF4C5VIBaK+KA2h9sTJqC3mLj+6KsYbY4LwygXf17LnM/pzioeLnKspI7zT+KasCwsdjt35r2Npe93/cDimMtQiWQEKT259/ROZEIJK1Oms6PqMAqRlAcTr+FQ6zkmBqXjJlVgs9sQCoS0GXrpMeuIdPFDJBDSZdTSauwhTOmD0Wbm9bL9fFyfi5fUhQ3Zi/i2+QwbK75BJhTzSuZ8njnzASN9E3iv1mEYEe3iz9MpM/GVu/Uz4vh5cG27UU2zvgutxYifzJ0es45ekw6T3UqsWwAt+h585W4cayvDZrcT4+rP7X02zy+lz0EqFLM89y3s2BnjN4jZEaMp6q7FR+7K+zUnWZFwJW5SJfef3km5phmRQOjMHAKYEpLJ9eGjEAjg7vzt1PaZDQBEqvxYlX4jzfoehECwyhuL3crrpfuZGJxGqkc4equZD+tzGOYTy2cNp/mo/pRzeyECHku6DpFASGF3DaW9jTybegNTDr3oPEfSvSJ5Ie3Gfs6GLfoe9jcVkOkdzeGW81iwEq70IdLFj3ptBwqJjK0XDnKmxzE3JxGI2DXqNjaVf8MYv8HIhGJ21TgMToIVXjyfNovtlYf4qrmYB4dcQ2FnNfsa+5sWBcg9eCVzHhd6WzjbW4uLWMFQn1h2Vh7m29YzznNrbEAS79eeZEJQKgB6q4knivfSYuhx7uv68JG4ShRsqzzEaL8EvmkuBuDywBTmRV3EgwXvkOkVRZpXJA8X7sbOj1/Nz6fNIlThRYjKB7lIQrO+m4reJpK9wp0hzf8JGnSd3JO/g8eSryPWNYAOo4ZHC9/jhsiRpHhEOI1d2o1qJAKR06Xyp2jMBr5pLsJH5kamdzRCBBR2V1OubmZScPp/9Pn8r2G12yjrbeK+0zt5OXMukSo/6nWd3Jb7Fg8nXUuSe9jAjNgAA/yMv9RW/B8xd+7cP7K7/ygDgmmA/1a6jFrWle3ni6YC1mUtJMrFn88a81ldso+nkmcw0i/hXxZNBouJAy1n2VzxLfclTuaJor2M9hvEtLBh9Jh1vFTyGT4yV5bHj3e6h6V6RvDmhQM8nzYLuVDCivy3aTH0oBRJuXfwZJ4/9wn3Dp7MN01F9Jj1lKubGeoTw5FWxzzOg4lTuKBuodOkZWzAEJ4++yG9Zj2XByYTIPfkQEsxVruN51Nv5M78bc7sph9meTI8I1kccxm3523l2tBshvnEcmf+dp5OnokVGw8Vvut8frMjRiMRihELRVzmP4QV+dto1HeR5B7K3OiLuTt/O/OjLkZnNRHrGsD4vtDhf4bNZqNM3cQtp95AbXHMQP1wkTsxKI1hPrHODCWAaBd/nkyejptE6cw9MdssSIRiuk1alCIZUpGYJn0X++rzGOQeQpjSh/sKdlKn6+C51BuIdvVn1blPOdx2nrsHXcUQj1Aq1M1cULfgKpHjLXXFaDMT5xaIzmyi2diNm0SB3Q6D3IJpM/ZS3ttElk80n9Xnk+4dxbqyr6jQNDuf1+SQTGJcAvqc/d6jtq8Nb0b4cN6pPuaoCLr48WrmfCp6m/GRufJZ42neqTmKSCBkTfoczvTUY7CasNit7Ko+CsC1oVmc72niXK+juvBq5nzWlX3FDZGj+LQ+l5M/CYUFuHvQJC72G4KfwvFZ3W3SkddxgSfO7GV25Bgu8h1EmbqJDeVf80zq9eytdczGfVyfi8VuJUzpzYSgNEb7DeLThjwilL4keYbyduX3TApJR28xIRaKONRawpVBafjL3XmieC+n+wxQRAIh24ffykNF7/JE0jRcxHI+rM/hnepjPJZ8HZ815BOp8iVA4cEYv8GIBULerDzI2IAknuwTS3KRhET3UKdl+g0RI5kYlI7ZZiGvs5LXy77i0aSpxLkGYrSZcZMocZUoWJazmUpNK+AY2H9v1ApUYnm/i12TzfK7ztM/yk/NXcBRtXAVy9FYDNydv52i7lpUIhlrMuayrvwrCrqqEQmEfHLRvU5jln+G2mxAIhQ5Z5ZMVgtGm/kXbp4D/HGsdhtqsx53idI5s9Rl0qLq+3wZYIAB+vOX2IqbzWYOHjzII488QlRU1L99kAMMMMDvw2R3zPGYbBZuPvUGF/kN5utmx/D+wdazZHpH/8uCSS6WMsg9mCsCU8jvrKbDpOGj+lMYrGbK1U1c0LRQpW2l26SlUtNKubqJUb4JRLj4ce/pnazJmMtDQ67hqeIPmBCchlQo4bb4CbQYepgYlI5EJCJQ7kmw0pPTXdXck7+D872NzI++mA/rThHnFsS0sOEUdFVzeWAKjxW+h9Zq5NWMeZzqqKC9rw3v6dSZ1Os6WV2yj4LuGoQCIfcmXk22VzQthh5kQjEGm4nvWs72e35H20t5Pm0WMoGEL5sKeDplJlsrDzI7cgzl6maG+cQS6eLH9srvmRk+AqvN9rualYVCIXGugWzIXsysY685hVGWdzQ3xVxGbkdlvyrB/KiLMVrN2CWO+zqNGg60nGGUbwLbKg8yNiCZONdA1GYDg9xDqNa2Eaz05OqQTOQiKQ8WvEOQ0tN5IW2z2/mw9iSfNuRjw8724bdyvreBl85/RqjSh+fSrqdc04zOYuStCwfZMmwJx9rLuCYkiyClJ9MihtNhdBgp/FQwjfKJ59OGPGq0bUwOyWJTxTe8lD6HcJUPF/slsjRnM4ujL0NnMXK2t5491cdZm72QWm0bR9vLuC1vKzPDR9Bq6OX6iJF803yGi/0Hk+0VwwjfBN6oOIC3zJUQpRfL46/g25azTrG0JGYsRd21HG8vY1XJPqJc/BEJhLhIZMiEYpI8w5geNpxd1UcY7BZMu0nN/YlTsNptDPOJpbEvy8dgNWG128jtrKTdqGZKcAbtJg0f1p1iVuQo7s3fgVIs55nU65kWOgwvqYoqbRslvQ3O18Fqt/FZYz6X+Q/h/7F33tFRlusW/01v6b130kinI01AQRREUZAiRUBQEVSwN7BgVxQVpVeVIlgQOyqdNCAJhIT03tv0fv+YMBLLOXqO59x7zs1ei7XIN5kv73zT3v08z957SfZmBnnH8G13V+h0yyX6e0VRrK4nROnD0uzNRKr8ONVawmDvPgTKPeg063g2ZRpykYRQpTef1WST7B7G4YZ8tFYTMqGYjYMX8VPjBQZ4RSMTibHa7bx+4aDzOQboNOt5+Owunk+djq/o5y/zfwVZqta28mTebp5JmUqYyocmQycr8/ZyT+w44tyCeCr5Fu7K3EizsctpDy9AwHOp01CJfzt+4Lfg+ouoAqlI3LuZ/4sgEgh7EF6gR/5dL3rRi38Mf7rD5OHhQW5u7n8kYertMP13wGa30WToQiGSOkc+6vUdSIUivLs1IP+NqNa2sCxnKzU6x9irn8yNRPcQ7uwzlmCl1z+dr1Gja0UsELG78gS7Ko45j4sEQp5MmsK3DXkcby5iccxYRgckM+/ku8yLvppWo5pGQyc3hw4kq62UbWU/MS4wlfnRV1OpbeHhM7tI8Qzj+dTpuEoUVGlb8JO74SFVobUYUYlldJi05LaVs7P8KPOiR/FJdRZ3x47jXLuDwPV1D+Hd4m+IdvWnr3soKrGMZI8wh120SILFZqFG18ZbRV9yrLkIgJF+CRxvLnZ2RNb2vwOJUIQAASabhfuytxLnHkR/ryjeLv6aNf3m8Grh5/jJPLgtYggRKl9cflHxttlttJt0eMsc2oxOk46Pq0/z3qVvnb/jJXXhzf5zeeLcR1R221+DY0RsZcqtdJn0jA5M4p2ir3CRyJEJJWwp+xGZUML2offwdtFXRLr4IRaIGOGfwI+N56nQNDPML56Xzn9KmmcE44PSONdeyWe1DhONu/tci4tEQV/3EJ7O28NjfW/iiXMf0WTsYkroIKaFD2Fl3j4udNUwwi+BhxInIRNK2FlxlG1ljhwlsUCExW5FJBDycvpMDlRn4i/34LbwodTr23no7C6Wx09kqG8snWYd92ZtZlxQGqP8EjlYm8P0iGE8eW43I/wSEAuF9HENJN4tiBajmuy2MtZf+g6xUMRrGbcTpPDER+pKhbYFGzaeyd/HxJD+1OhaGeYbz8fVp/GRuXFdYCpCgZDzHdV4y1252FXHEO8+WLCytugrLqkbmBY+hNsjR/DKhc8cuUX+ySyOvYaFp9+n3eTQbN0Q3I/Hzn5IubaJ4b7xXO2fxDMF+4hx8ef5tNswWi18WHGcn5ou4CpREOcWhNFqplzbzPVBGWitBvZ0OxuOD0xjsE8Mq/I/xo6d8YFpJHmE8mrh5wAsjB7NuKA0usw6Xi08iFQg4sHESRhtFo42FrKl/Efna2KIdyy3hg9mc+kPvJo+i7zOKh46swuApXHj8Zd7OMfz7o0dz9TwIcj+oJOcwWpGbzHi2f1atdptdJn1v7t5bjdpnZ0tb5kra/vPY3XBAQo6q1GKpBwY+SCeUhXlmiamHVvjvN/MiGHcGTP2d232e9GLXvTi/zL+KDf406YPN910E5988sk/s7Ze9OIfhs1u45K6genH3uTDiuN0mfXU6NpYnLmel7pdtf6d+KVDWrtJy5+sQfwutBYDxu7cFbVZT7G6nkHefQBHJf7F9JncEjaY1wsP0qTvpFbX9k+JekOU3gQoPLg9cgQSwc96miT3UOQiCcebi4hzC2KobxwuIjl7hz/AmIAkLnbWcF33Bt5kdQi2v64/x1N5e3j4zC5s2DHbrNixIxdJiHULdFZAVWIZ7UYNOouJlfl7Keis5v1L3zElbBB3ZW7kxQufIhWIcRUrKFbX82XdWc61V/J9Qz5ZrSXOzaOw27Ur1TMcgDtjxnK1fxJv9JuNWCAixSMccXflVSGSUqVtoVzbzMHaXFbm76PNqKGws5YY10Cmhg8mr6OKb+rzMVjNNOg7aDF0YevWByw6/T4l6ga6TDoOVGc6yVJ/r6juzByH49eDCZPI8Izko2HLCFf5YrZbeavoSxI9Qph1fC2f1ebwRW0uo/wTiVT5MjYgiWPNFznafJHt5Uew2K0cbihga9lPVGpbMFjNvNl/LpNC+5PkHkK1zkHG0jwjCHfx5eULn7I8dzsvps2gRNPAIB/Ha+Xj6tPMPvmOcxRubEAytbp2dFYjB2sclvITg/vx6cgHiXUNxGq3sbvyBOOC0vi4+jQlmka2lx/BYDWz+vwB9lad4t6szbSaNHxWk42bRMH3jQXcnbWRh/pOQi4Sk+EVRYfJoblTm/REufixOm069m67eD+ZO1KxhCClJ/kdVTyWdDOV2mb2Vp0i1jWQBdGjCVF6sTBzPeXaJlwkcp44t5sd5Ue4qK7DZLU4HQh3V55k1vG3+amp0HE9vCIQC0SMDUgGYFfFMW4/8Tbl2ibEAhGTQvrjJ3dFJhQzPWIYZeomXCVykj3DeCFtBq9nzOahhElMCunPk0k3M8SnD+faK53vh1vDBxOp8mNu1EjAoVe6XKyQCERcH5zBDw3n+amxkBkRw7gt4ioezN2Bu0SJq7QnAb8xtD+l6kakQjFW7GR4RvFK+iyWxV3HjSEDGOYbz+q06UwM7sf1wRl/iixlt5Y6nQatdhuXuupZkbuDxt9xonOXKHgmZRoqsYxWo5oZx9+ioLMaIQKe6e6UNRu6ePH8pz3u90l1FlW6FqcRRC960Yte/DfiT3eYnn/+eV599VXGjBlDv379UKl6VquWLl36ly7wr0Rvh+k/H11mPZtLDzt1EZOC+5HZWkqDoQO5SMK2IfcQ6eL3b1lLlbaFZ/M/ZlXKVIKUnjQaOlmVt5f7468nxjXgn8q80JoNHG48j6/MjXSvCPQWE4fqz7Dm4iEWxYylw6zj46rTrEq5lRiXAC6p63kybw+PJ93EaP8kXCR/fDzmSjTqO3ggZzuXrhjRArgxpD8RKl/eLPqSpXHXMdg7hkCFJzKRmA6Tjpkn1nZnMU2g06xja9mPzvsmuAXzSsYs/OQO3Y7BakYsECIWirDYrByszeFYcxGj/BN5vuBAD+tbd4mCl9Jn8dL5TynXNvVY01PJU7ghuB82u41SdSOLMjcwPiiNcYGp/Nhwnl2Vx5gQmM6sqOF4S13wlLlgsVnJ76jinqzNWOxWwlU+SIViLqkbCFf6sCp1KvfnbGO4bzzxbsEM9unDijM78ZO78WjfydybtYUqXQueUhVrMuZQrW/l6by9XO3fl2Vx11GiaeSpc7uJdPFjUZ9rMFstvHPpa1anTmf1+U+4J/ZaVubvpUbXhkggZE7kSGZGXoXBamHq0TdYGn8dWa2lTkMAgPviJ9DXPRQPiZK3i7/CS+bKDcEZKIUytpQd5kRzMffEjedcewWRKj9i3AJ56MxO7o+/nrPtFT3O9UjfyWS3lDA7aiRFXXUkeYRxsDaHMf5J1Bs6SHAPZlf5Mfp7R7O/6jSL+ozl6bw9PJ50M+tLvuPsFcTBRSznnQF3IETIPdmb6DLrCZR78mjSjTybv58MrwimRwxDLpLwdN5eJAIRc6JG8lzBfl7LuJ1IpR95nVU8eGan06TjKt84tGYjTyTfzEvnPyWrrbTHc57sHsrsqJEcbSrkjujRvF/yLV/WnXXe7iDKibQaNYiFIj6tzuLL+p9vX9NvDiKB0EHYRGLeKvqSQIUnSpGUjaWHSXQL4cHEiTQZunj07Af4yFx5JnUaj5z5wBms7CZRsLb/PLwlrmS3O8YunyvY73zdhii9eDX9du7K2kiUiz8FHVXMjhpJknsID+Tu6PH6lgnFvN5vDmEKb8QiMXqrkcMN5xkXmIK4u2Out5gw2Ex4/sJx7m+hTt/OzT+9ig07I/0SmB05knuzN6OzmhjiE8szKVN/05DBZrdxrr2SRZkbnMeWxI5jWvhQZ1HjZEsxAgQs6jOWj6tO02zsQiWS8dGw+5zavF70ohe9+E/Bv6zDtHHjRjw8PMjJyWH9+vW88cYbzn9r1qz5Z9bci178XbhJFMyJGsVNoQMB+Kw2x0mW1g1YQKjS+9+yjnaTlqXZWzjXUck9WZuo0DSzImcH2W1l3J21iU6z7h8+t9VmJautlGcLPub+3G2ca6vEYDOzqeQwAgQM8Y0lq6UEi93K03l72V5+hCfz9mDHzhe1Z/5hW16dxcgHFcedrmmrU6dzY3dmzac12US7+pPoHsJbRV9SpWtFZzEiForxkKp4PWM2US5+DPeLI96tZ7hosMILs82xIdZbTWS1lnCxq87pDDfcLwGhQIC7RMnibqvoy3gpfRbvFH31K7IkQECqRwQARpuFKl0LGouBHxoK8JW5cnWAwy79+8Z87HacHS2xUISv3A0vmQtRKj9ey5jNoj7XkOAWzJiAZI43XaTdpOWz2hxy28tZkbuDsm674w6TlpfTZ+ImUdBu0jLn1LscrM1lbf95LIweTYdJy3vF3/JC2gzmR49BbdbzZN5urglIoULTzDMpU8lsKaFG18Zgnz58eNUyPKUqDFYLPzSeR2s18tL5T7k9cjh+MjfEAhHL4q6jXN3EnafXk9dRxXC/BEKUXsw/9R7fN+azIGYMz6RO452ir7gmIIVYtyAeOrMTmVBMuMqHmivc7cAx1nlH9GgOVGfx/PkD7K08yZTQQRR21eIjc+Wti18yM2IYX9Tmsix+AmuLvuaNfnMw26y/em4mhwzARazAXaLkjX4Os5+BPtEUdtbSbOzi6/o8tpT8wMpzeynqquNCZw0CIErlx9d159BYDdTr23k6+RZG+/dl/cA7udq/L3OiR7Kj/AgrU24lSOHp/HspHmGsTptBra6NhTFjKFE3OLOwLqPF2MXJlkuEKLzxlKoo6qrrcXtmSwn+cg9MNjMGqxmT1UKtrpUAhQdCBFzoquGhM7t49OwH2LDjI3dDbdYzwjeeDYPuxFOqosusZ1PJDxjsZr5ryOe5gv1MDx/Ki2kzkArF1Oja2F+dya1hg8lpK8NoszDGP4mn8vZitdvo4xLA7mH3Eazwwmiz8HzBfrRWI28UHuR8Zw2dZi1f1p3lgZztNBk6UYilf4osAbiK5TyYOAmAn5oKmX/6PXRWE34yN1YkTPxNsuS4fmreKvqyx7EPK0/QaOjEVSLnzpgxKERSVqdNZ0bEMNYNXICvzI0Z3cT4H4XeaurxXFrtNmf33mq3Ua/v4GhTIfuqTpHfUfVvnyT4s2g2dNFs6HL+3G7S9nBM7EUvevGfhz/dYfpPRm+H6b8HDfoOJv30svPnEX4JPJ18y7/NZclis1LYVcvdmRsxXkFQRAIhr2fMJsMr8g+Pz/wWGvUdLM/dQbG6HnBYaT/WdzL7qzMZ6hOLm1TJmsIvKLuCSKR7RvJc6rQ/7FT1W2gxqHnh/AGmhg8hWOFFbls5Reo6wlQ+DPGOZU3RIUQCIXf1uQajzUKcWyBCgRCr3Ua7SUthZw0P5u7Ehh2lSIrOagIcI1+3R46go5torhu4AIVIio/MDTepgkZDB2ablUWnN9Bs/HmjEecaxF2x13C+o4Ykj1AeO/shWquRV9JnkewRhle3PkNnMXKq5RLRrgGEq3yw2KyODbpAQIJbcA/LbvhZr6WzGJl3ah3Ppk5DJhRTp2ujSF3P/upM5++KBSLe6j+PJPcQ7HY7uR0V3J/zs1voquRbHbbVIjH5HVU8nbeXDrMWg9XM1LAhzIwYxrHmi1Tr2pgbNYI9lSeJcvXnYE0uK1Nu5XBDAS8XfgbAyuRbuNhVh0ToGCnTWAysK/4Wb5kL98SO59OabHZVHAVgqE8cD8RfT0lXAwEqD5QiGXqriWVZW3g27TbWFX/jHMNLcA/mfHf+z+zIEQzwjube7C0AJLgF8UzqbewqP8ognxgO1uSwJG48+6pOM9wvnigXfyq1zazM20urSeN83D+L/WXktVexuewHAO6Ivhqz1cKO7nWCw0r8xfQZRKp8aTR00WbSIBYIeezcRwz1ieWhxEkcbbrIaxcPEuXix2vpt6O1GinXNPFk3h76eUVxd+y1qEQyKrUtRLr48m7xN/zYdAFwWJ1fJtVzIkdyY2j/brLrGMNL9gh1ut/NjBhGoMITMUJSvMJZW/QVMpGEq3xief78AeeaE9yCWZUyld2Vx4lyCXDkeSVcz47yI0wIyqDZ0ImrREGZppFrA1Op07UjF0s5WJvNvKirqde3E6L05ou6MxxtKmRJ7Hi2l//EMylT8Vd4UKVt4Zn8fTyYMImHz+6iTt/OSL8EwpQ+zms3P3o0syNH/EP6IK3ZwBsXv+Cz2hznsf3DlxOi+u2iUptRw0NndpLXUYUQAXOiRrKn6iRaixFvmSs7hi7BQ6Kky6xHLpKi7F5Ts6ELqVD8uyTs70FvNZHVUsr5zmpmRAzDRSKnuKuOXeXHuC/+ehoN7SzJ2oLWanTeJ941iFczZiMRiXARy5F0v7/bjBosdhsKkcT5XdBs6EIkEDo/K/7VaDZ08eS53VjtNlanTUcsFLH+0necaCni3QELCFZ6/VvW0Yte9OKP4V/WYboSdrv9L9Nr9KIXfxQ1ujbuPL2+x7EjTYXsKj/2q4rzvwpioYhEt2BWp03vcfzBhIn084r6p8gSgL/Cg9f7zXaOsY3ySyS3rZw+rgE8nb+XBn0HYwNTetxnesRQXESyHroq2xWV2j8CH7krTyRNId0zArPNSrx7MLeEDaZG28p9OVu5J3Ycd/W5hkWn13N31kZK1I3Y7DZEAiEigYAv685iw05f9xD2j1jBHdFXA3C6tYQ2k4Y6XRubh9zFO8Vfs6viGJfU9TQZOtlRdoTnCw7wQML1eMtcuKvPNYgEQorUddTq2hAJhbx76Rve7D+XvcPux46d2SffobrbVEEplnGVbxzhKh+g+/lxD3GSJbPVQqdJh6FbE3ZZr+UqUeApVfHEuY94Jv9j3rn0DVPCBiG+QsOV7BFGjKs/5domag3tvHrh8x7XbE3RIeoN7WgsBvZXZdJg6HD+nWPNFzHZrTQZOrkuKI0TzcVcE5hCZkspd8Vey7Hmiwz0jsFDouT+uAmYbFYkQhESgZgHcrYjEYp5MGEio/2TmHPyHVI8wkj1CGeITyzLE67HW+5Kh0XHM3n7MNss5LaW80b/OQQqPFCJZQgR8ELaDKcbHDi6tDa7nRkRwwBYEncdj5zZxSc1WeytOsV9CdfzVtFXfFx9mtcLDyISCHn/0ne0mjS4iOW8P3AhKR5h2LHzdN5eol38SfJw6Nz6e0XxRW0u44JSnSHBAH3cAolQ+dJh1rOp9DBPdduVTw+/ihMtxdydtYnXLh4EHIQnp72cWSfepkrbysZBi5gdOYLFpzewoeQwUS5+SIViNBaHXu/OmLE81HcSE4P7AdBl1mGz2/GQqhALRDybOpU7Y8Y4bw9UeOIpUZLqFc6Gku+5LiiNWJeAX7nO2bAjFYq5OXQQJ5ou8lTKFPq4BnJ37Dg2lnxPlKs/Se4hDPdLZN6pdRyqP4PNZmNh9FiWZG9mY8lhRAIhMyOGMTogCV+ZKy+kzcBf4QFAmMqHF9JmUKSuY3xgGuDoBl0mS9cEJHNr2OB/iCxZ7Taqda09xjEB3ir+8je7MxabFbBzR/TVSAQiXs6YxW3hQ3lvwEJUYhnTw4ciFTis+b1kLk6yBOArd/uHyRJAjbaVh87sZEvZj+woP0pxVx2LMzfyTUMe60u+41x7VQ+yBFBv6KDB0M49mZso6KjCbLPSYlCzKm8v3zfkc669Ao1ZT5Ohk4fP7OLd4q9pM2p+ZwX/HCw2C+1GDQarGbvdTpW2hTPtFZzrqOSRsx/w1sVDfFx9mnp9B0eaCtF3F5H+U2G322n/De2uxWb9nXv0ohf/HfiHOkzbt2/nlVde4dKlSwDExsby4IMPcvvtt//lC/wr0dth+s+H2qzn1Quf82X9WeQiCe/0n88Xdbnsr85EgIAPhy0lysX/37KWRkMnK3J2UKT+eewnWOHFOwPuIOifrCKarBbyO6q4N3sLFruVBLdgFsSM5slzu1meMBGZSMKTvwi3FAscDmSV2mbGB6XhJlFQqm7k/ZLveDjxxt/sPLUY1FjsVgK6N3EdJkdnJEDhQYdJy/f1BYS7+HB/znaMNjM+Mlf0VhNaixFPqYr3By4k4grNWKtRzb6qU9wUOhA/uTsdJi2Has8Q5xbE0/l7SfcMJ8UjnFe6HcUmBfdDIhTzcfVpAJbH38Awv3h8ZG7ktJXyWuFBXs24nenH3sSGnQS3YG4KHciL5z/Bhp2r/fvyeN+bcPudDZvZZqVO18a+qlPkdVQRpPBkVuRwwlU+Tge83LZylmRtRimWsiplKmuLvuxh6wwwNWwwN4cO4uGzH1CpbUYmFLOozzVsLfuRLrMeL6kL6wfdya1H38COnWsCkjnSdBGjzUywwpN3Bszn+YIDZLWVMj/qasYHpbGz4iif1mRzbWAKi/tcg0IkxdbtZLbw9Ho0FgPeUhemhg/l/UvfYsNOikcYsyKH027UoreaKNM0OZ3y3hu4gPWXvqfVpObawFQyPCPRWAwcabxAkkcYQ33jqNQ2U6JuwEUi51hzET82nmdicD9iXAN44+IXztfRZU3RQ4mTGOITS5tRw4sXPuWRxBtZc/EQS+LG8d6lb7k9cgRf1OZSb+jgvrjr8JO5YcHOj43n2Vh62EkcJwb3QywQkeYVzsq8fQA8n3obcpGYB3J3OK/zAK9oHkqcxKbSw3xVfw6AYb7xnG65hNluJUzlw8vpM/GSqNBaTeR3VHGhs4aPKk/wQPwNKMVS0j0j2F+dybigNNqMaj6sOM7p1hLuj59AH9dA/GRuaK1GvqnPY1fFMcb4JzEmIJknzn2EDTv+cneaDV3O19vDiTfiIpYRrPJGazHyTd05Mrwiye+oItYtiCNNhWwqPQw4jD/KNE20mTS4iuWsH7SIaFd/usw6lCLZrzqd1dpW7srcwCN9J7Oh5HunrblSJOWTkQ/i3t3RUYplaCyGP5ylU6NrZdbxtc4xvGsDU9jZ7Xw5PjCVBxJucI6pWmxWitX13J25kTcy5hCq8sFoNbEocwMLoscwxDcWhUjqDKX9q9Fu1LKx9Hv2Vp3qcdxP7s6afnO4L2cbTb8YZ3u8700caSrkaPNFJAIRr2TM4qPKE5xqcexJtg65m7NtDv3eZeOKrUPuJt49+C9du8VmoaCzhqXZW3g+9TYGesfQZOgku62MF89/2uPz+Y6oq5kecdUfJpcasx6TzersjJmsFnRWI64SBSLBP1Xr/odht9sp1zbx2NmPeCl9JuEqH+r17azI3cmjfScT7xb0q9d4L3rxfx3/sg7T66+/zl133cWECRPYs2cPu3fvZvz48SxevJg33njjn1p0L3rx9+AqUbAkbjxX+cSxbuACEtyDWdTnGqaEDuKl9BkEyT3//kn+ArQZNTzYTZZEAiG3R45AJhRTq2/jnqzNtP4T1UyLzcr5zmonWQpT+mC0mtlYcpi3B9zBEJ8+vFb4OXbsZHhG8unIB4lS+WGxW3n94hfEuwXz3qVvnUYIR5oKWXPx0K/1HgY1zxZ8zJLszdTr22kxqNlUepjbT6zlUlc9YoR4ylSsu/Qtz6ZORSIQ0WJUo7UYcZcoeXfAgh5kCcBb5srsyJHOzphMJCHVMxyL3Yq31IWv6/MwWM1MCR0EODRol8nSrIjhjPJPJKjbTKKfVxQbBy3CT+bGaxmzESKgsKuW1ecPYMNOskcoyxNu+F2yBHCxq5YZx99id9VJCrtq+b6xgHmn1vFtfb6z0pvkHsoHV93LO/3nc6K5yDnG9UzKVCaHDABgT9Upmo1drEi4AZVIxsbBi5gcMoC1/efhLlHwZNLNzuu7LO46Hu17E28PuAOZUEJqd7fu8kZpU9kPPHhmJ5/WOIiOt9QVlUiOt8wVX7k77mIl6wYuwEUsp9WkYd2lb7BhJ84tiDlRI1mVt48XL3yKl8wFk82Cu0TJY4mTiVT58WzqNLykrtTq2thY8j1byn6k3tBBiMobqUiMl8yFNK8IjjcXkd3qMFQoVtdjspp5uFvzcpkszY4cgdVmQ23SY7SZWZlyCxc6a8jvrGJp9lbmR4/mi9pcvm8soEHfgbtUxfHmIlqNanQWE8+mTOPp5Ft4LeN2wlQ+XB2QiEokI8MrkocSJ5LoFvyr94kdKO6qZ3bUSK4NcHRQjzVfdJAlpTdPJU2hWttKp1nPmxcP8WXdWT6qPMH1wRm8d+kbjjQVclfmRm4OHYjObOST6ixnxtPm0h8IU/lQr+/gzYtfMjGkH1Eu/vjK3ShRN2DDTqJ7CK9m3M4LadMRIqDNpKHLouf58wdoMaj5pDqLlws/457szSR7hPF64UGG+8Y7HfOy28qcZOmdAQtwFysw26y4SZS/ORZ6d9ZGrglM4UJnTY8MKJ3VxIvnP6FG18qPjeep1DYz7+S7nOuocDpR/i2oxHLGB6XhJ3Nj3cCFzI8Zw8OJN6IQSZkecVWP0WW1xcC64m/QWU0sztrIt/XnWJS5gSZjF2uKvkAg4F9GlgA8ZSrujBnLIO8Y5zEBAjYMupMyTeOvyBLA28Vfc0vYYMJUPpjtVu7L2eYkSysSJvJJdRZrig45ydLL6bMId/H902trMXRxtq0CvcXxWdFu1JLZUuJ8r1++dgarmQdzd/JBxXEWnn4ff7k7sW6BzvOoRDKmRQz9U2Tpm/o8Zp94m3pdO9XaFmr1bUw/9iYlXfU06Duo646X+Hei06zjgZztlGkaWZy5gfMdju+pS+p6lmVvcXZ9e9GL/0b86Q5TZGQkq1atYvbs2T2Ob9u2jZUrV1JeXv6XLvCvRG+H6b8Hl9PnxUIRdrudZmMXUqEEj39iNOTPQGcxcry5iKfy9vB6xmzSvSIp7qrjnqxNLIkbz4Sg9H9KT1WpbWZx5kbcxAre7D8XAQKW527HaDXzcsYsAN6/9C3TI65CjBAvuSuvXPiMBdFjWJ67vYfWxFvqwnuDFhKu6rlhKOqq446T65yb0Ti3IGcw58yIYYzxT+Jk6yW+b8jngfgbWHFmh7Nj4CtzY93ABYR1j8D9Fi5rEx46s5NFfa6hXt/OJzVZhKl8eGfAfBaeep8GQwcAAXIPXs24HbVZT7JH2K+q6FqLkdcLD/L5FXqMg6MedhKz30KrUc2i0+up+oXxATjsn/cMv9+pJ2gzqtlflcnYwGTWXDzEzaEDCVX6kNlaQpm2iSCFJ11mPbeEDkQoEHG69RKDvPvgJVXRYdJSrK4nWOmFVCjGVaJALBCR2VqCm0RBna6dPm6BSIVi1l36pkew7tSwwYwNSCG/o4pR/om4S1ScbCmmy6yj3aRlY3fnAmDdgAVEufiz4swO8juqiHLx49X02zFYTXzXUMD4oFT85e7ktJVTqW0mUOHJR5UnuMo3jiptC+c7q6nUtvBS+ky6TDpi3QK51FXPML8ENBYDVruNDSXf83V3ZyfDK5JbwwY7bL5Pv4/OYmTT4Lv4tiHPmd0EjtypZ1OncaKpiBtC+rG17Ae+rs8j2T2M1Wm3cbA2l/dLviNQ4cEr6bNYeHo9j/S9EYVQykNnHZlDfjI3PGUuLI27js9qslgSO44aXTs27Ky5eIhL6npuDO7PnOiRrCn8gptCB9Jm0rL6/AHuj7+edM8IGgydPHnuI64LSuf2yOG8WfTlr0KMk9xDeTJ5CvW6dkJVPoiFQqYeXcO08CEEKjwJVXojFYr5oPI44wJTCVV6sSJ3Jw2Gjh6avGsCUlgYM5omQxcHqk5zZ+w1vF30FfOir+aRM7sIVXqzLH4CC0+9z1sD5pHkEebU2VxGna6NdcXfMtI/kcfOfQjASN8EglXefNDdDZodOYIpoYNYnrudEk0jbhIF+4Yv/0Ofc+0mLSarxelcpzY7iK+n1OVXHYomQyePnf2QvI4q5zGlSMp7AxfSxy0QjdnQY7PfadL9avNvtVkRXfEYf/nz78FqtznH8K4cV5sTNZIbgjK49dhvF2JjXAJ4rd/t3PjTK85j1welc2/cdVz/44tON8IhPn14LvW2P/153GLo4qm8PeS2lfNS+kzSPCNYX/Ide6tOsSR2HDeGDMBdqnSO/Z3vrHF8TifcwIXOag5d4d4IkOoRzuq06X9IY9piVHPLkdfwkrnwcOJknsrbTbjKl+nhV+EmUfBq4ecYrOa/ZJrhz8Bmt1GibmRR5nq0lp/HJCUCEW8PuOM3X+e96MX/dfzLOkz19fUMHTr0V8eHDh1KfX39nz1dL3rxD8FTqkIsFNGg7+CjyhM8cuYDHj/7IUebCv+p7s4fxWXNzGcjHyLDKxK5SEKiewgfj1j+T5MlgHCVL+8PXMib/ecSoPBAJhLzQML1LE+cyDP5+xAjZFJIf5ZkbeHOzA0IEfJ08q2EqbxJ9Yzoca71gxb9iiyBw0ji7QF3IBGIqNK1OsnS5JABeMtcueP0e2R4RPB40s08evYDDFYzKrEMqVBMs7GLpdlbqP0bVU4hAiRCEQtiRqM26/mkJguAl9NmsuHS906yBNBg6GB35QlKNQ3ortArNBo6OdtWwdGmQr6oze1x/gdzdzqrz+0mDV0mvfM2vdWE1mz4TbIEYLZbqdQ2A47N3/ayI6wv/Z7ludt5IOEGREIRFdpm1hZ/RYDcHVexgu8a8tBbzXzbkMdzBft5IGcbHWYdheo6lufu4K7MjY68KbsdiVCEu0TJyxc+45mCj1lb9CWGK/J6LkPWHb78WW0OS7O3orMa+a4hD7lIyuZSh4lChlckyxNu4Klzu2kydHBv7HjeGTCfl9NmUdBRxee1uWwu+4HFmRtpMHRSoW3mzaIveTpvD0vjxlOibiDeLZhY1yCsdhuVmmbUFgNvXvySGJdAbHYb5zureTB3B6P9+rIoZgzgGFXcW3UKkUDE40k34yKWIxdKGOYb3+MxxLj402pU4y13odWoZrB3LAIE5HdWMeP4W7xf8h0AKe7hXFI3YLCaWZW3D6PNzCi/RAZ79+HN/vN4IP56Xi88yK1hQ2g1ajHbrbxeeJC7+lxDH9dAPq3N5uu6c0yPGMbxlmL85W7sHX4/vjI3VCIZCqGUjYMXMz96NAWd1U6yNC9qFCsSJiJAQJSLH2fbKqjVt3GmrZyDNbkYbWa2lx8hs7WER85+gNZiwGK1sL/qNB9WHGdxn7EATrI0wi+BBdGjOdZcxHuXvuWuuHF8VHGc0QFJPHHuI55IvplqXStby35iReJEDlRnof1F5b3TpKOgo5o7+4wh1i2Q64PSGeOfxNL4CYwLTOHe2PHEugYyISidlfl7uTfuOgLlHrzd/w5c/2BkgKdUhb/CHZvdhsFqxlWiwEfmhkggxGDpqaPxk7vzWN+behybEjaICJUvdbp2nsrbQ6Pe8V5rMnTyTP4+KjTNPR7PN/X5Tn2U1mLkZMsl6vXtf3edlZpmJ1nyk7szJiAJgG1lP/FN/TmWx9/wq/tIBCKeTr7lV5lQ39TnkddRSYZnpPPYyZZLHKzNRW3W//I0fxN2wGgzY8POw2d2sTR7i3NsUG0xOMft/OTuPJx4I+AYyXSXKp1kaV7UKJ5PvQ0BAs51VHKgOtNZdPpb8JSqeG/gQuJdg6jTt9Fh0nG2vYJt5T/x8oVPKdU00mDooNHQ2cOm/l8NoUBIjKs/L6bN6HF8ReJEknvJUi/+y/GnCVNMTAx79uz51fHdu3fTp0+fv2RRvejFH0G9vp0Fp9/njYtfUNBZTVZbKctzd/DKhU//ZQLfK6EUy/CVuzkNHsRCEX5y97/MqS9M5ePUFrlLlHhKXXjr4iHOd9Yw5djr3JezDaPNzNL461CKpbhK5NTrO8jsHkG6jF0VR38l0gWQCEVEu/g7w17B4fJ3a9hgtpcdAbpH0QxdaLo1S1sG3826gQuQCSW0GNW0mzS/G1gpE0nI8IpkQlA63zTkAfBw4iTyOqqcupsbQ/o7rcs/r81BIhQjFzquZ62ujcfOfoBEKGJl3l7nyNQTSTc7x/NevfA5LYYujjcV8WlNFl1mHQaLicyWEhqNXQzwiv7d63u5tS4TihniG4tcJKFa18Zz+fsxWS08lbcHk83SvXEy8UjiZHaUHyHaxR+RQMglTQOzT7zNQ92ugH5yd+zA4+c+Yl/VKTwkSpbFT0AuFPNw4o18XH2aQ3VnAMeGCGBH+RG+qc/jxdTpLIkbR4O+nQcTJ/HShU+xYefG4AHMj76avPYqFsdey6ayH1CIJOwsP4INO5/VZDPSP8EZmDvz+FqnLXSqZwQuYgXXB6WT31HJ5NABCBAwyKcPhZ01TA4dQKtZzaHaM2wu+YGl8ROwCexMChnAMylTAYhQ+aEQSejrFsKmwYupN7TzQLdDoABHzlhmWyknm4vp4xrI0uwtnGgpZnmCY5Or7iYKw33juS1iKKFKbxLcgrFhp1Lbwk2hA7kn9lpkIjGPnf2QUk0jT+btRm3Rs7rgAKWaRp4/f4AXus1VPqo8TqDCE3exAq3FxLf1ediwUaSuRyEWI7QLqNe3U6FpZmbEMBb3uYZxgalc6Kjm7QF3EOHiR5JHKO0mLa0mNRtKvwccnZ1KrcOafsWZndwUNhC1RY+P3I0K7c/EYFJwP+ZFjUIkFPJ20VcUdFazMm8v0a4BPFewnzp9O3srT3Fnn7H81HSBcBdf7k+43qkXAge5+KjyBE/k7ebNi1/iJlFwR/TV3BM3jqXZm3n1wudkeEXySsYsXrnwGWfaK9hefoTX+s2mj2vgn9KvXA76Pt1yyTlWVqNr4/PaHLquGNGt1rawtNs18TJ2lh+jzaTl3uzNnGwp5r6crdTr23n4zC6ONl/krqyNtBk1dJi0fFBxjDVFX5DVUkq7UcPxpos8kLud+7O30fA7QbmX4SZRkOQeip/cnfcGLuCRxMncGjYYpUjKML8ExgQkcWNIf2eYtrfMlQ2DFrGz4ignW4oBuKvPNc7xvMfPfsSiPmN5NX2WM7z4jYtfUPMnR9h85W68kDaDJPdQbNidI5OzI0cyK2K48zmt0DSxLGcrAFltpVRqmpkRMYzZkSOYFj6UYb7xvDtgPotjxjIlbBBykQSLzUqNrrWH1XijvsNpYiMSCIl08SfaNYCz7RUsT7gBAQIudNZQrm1GJBDyZr+59HUP/bfrmRoNXU4N6mWsL/meuj9AjnvRi/9k/H316C+watUqpk2bxpEjR7jqqqsQCAQcO3aM77///jeJVC968a+AyWrhg4pjvznffrjxPNPCr/q32cj+OyAQCIhQ+fJM6jRmHH/Lefzm0IHcEJSBSiKnStvCoswNTrOAgT4xfFl3lv3VmUiFYuZHj+4xRtNh0rK17Eey28oQdVuDW+02Hj33IatSbuWpvD380HSeu+Ou5eX0GYSpfIlw8cVis7Ju4HysdjvxbkEI/8YXtkwkIVDhyboBC/isJpvR/klY7Xau8o0jTOmDj8zV+Tjq9R0M841HLpbSYujik+os8juqOdxYwNyoUZxqvcR9cRPoMut4POlmNpUeZmHMGM60V/BswX7s3aQlQOHBQ2d2IRdKWNN/Dh2FWi6pHUG8l+2nRQIhEd1dN53VxGfVOTyXehsrcnegt5kQCYUIBQLmRY1CKhTzxsVDBCu8eDFtBnbsPJk0hZX5P9ts93ENYH7MaD6uPsVIv0QiXf1oMHYiBMx2Gy1GNcVdjg789PChzIocwZqLX/BtQz4XOqq5NiCZvVWnyGuvYsPAO3kpbSYfVh5nTvRIbju2BpPNgslm4c6YMSzJ3uxwpSr8jJvDBhMs9+aFtBks7da8AfR1D2FK6CBWnz/AzIhhzIu+mue7r9H7l75lWvhQ7svZhkIk4ZnUadwbfx1P5+1BazHyVv95DPSOYfPguwhWeGK125CJJFix8V19PmqLAS+pC+8NXMD3DQW8X/Id3zcWMDl0AAEKD0KV3r/KnGk3afGQqrDarLycMZNTzZdI84pgZ/lRvqjN5fnUaTyVfAsPndlFvb7DaXkuF0l4LmUa7UYNU8MGM8wvgRJ1PeEuvjx27kOsdhtL467DRSTDZDPjK3fHU6qij2sgdrvdqSOZHTWS060lvFX0Zbf+bj4Wu5XdlSfp7x3F3KhRmG0Wnsn/GKVYitVuY6RfIkabma3d44fzo0fjKpHzfMEBnki+iRfSZ/DomQ8o6KymoLMacNjg3xs3nsMN53k6+RY8JSonOb4Mq91GsMITAQKy20q50FnLe5e+QWMx8GL6TErVDWwrP0JOaynPpE6DMpgTNYInz+3m2dRpRLv4/+FQ7ApNM4tPb3BootJnEOcaxD1ZG6nXO5wcJ4cOwGq3sTJ/H03GLpQiKa/3m8O7xV+T11HFyxc+5dG+k7kvZxulmkbn+JsQAQ8lTuJ0Swn9vaOIdPFjZfKtHG4sQC6WsjLfYezhJfv1+N8v4SN3Y1XKrRhtFueI7ILoMcyIGEaAwgORQMjyhBuYF3U1JpsFpViKt9SFedGjONVyiWXx1zHaP4nxQWncm72F/l5RyIQSBvrEOE0e4t2CnHlwGrMBT5nqby3JCalQTITK1/n8AiS4BzlHhtuMGp7M20O7SYubRMEb/ebweuFBBnrH9HBdbDdpiHELRCWWY7FZKeisJru1DKVIypjAZLDbeSBnO+1mLe8NXEiA3INz7RVsLD2MUiRlSugg3CQKZ75fkMKTaFf/P2QA8lei3ajh/pytVGlbkAhE3BV7LZtKD9NqVLM4cwO7ht6L53/R924venEl/iGXvJycHN544w0KCwux2+0kJiayfPly0tPT/xVr/MvQq2H670GToZOZx9+i83fGLG4IyuCplFv+zav616LVqOa1woM9rILdJUreH7SQqO6xqJcufEp+exXvDVqIp9SFD8qPsaviGO8OnO+02LbYrGgsBlqNaqYff4tAhQdv9ptLh1nHPZmbMNutTA4ZQKDCgw0lh9k4eBE/NV5AbzExJjDZ4TAnlgN2xMI//oWtNRtQdY8T1evaOdlSzIsXHCM198SOI0TpRYTKD2+pC+tLvyfDM5ID1ZlktZUyK2I4GV6RXOisYVxQKvurMrkmMIVHzuyiqTu36bKD3FPn9mKxW3klYxa+3WGsmW2l3Bs3ngS3ED6tyaKveyjjAlOw2e0oRBI+qcnGU+aCn8yNQ7W5lGqbWBQzlmCFF7X6Nh46sxOjzYKbRMG9seORi6Q8mbfb+dgiVX483HcS/jIP1BY9d2dtop9XFGMDkpGLJLQaNUS4+FLUVYdSJCPWLYBmg5pKbTNR3R2r1y4epFLbjFgg4rbwIWR4RdFqVNNh1vFO8dc9rqWbRMGzKdPYXvYTq1Kncry5iBfOf+K83UvqwnOp0xAg4HTLJSJc/Ihw8SW3rZxOs47hvvE8eGYn7SYtSpEUAQK0ViMeEhWvpM9EazWyu/Ik98VPYM3FLxjqG8eEoHQMVjNby37klrDBvHXxSxLcg5GLJES7BrC97CeSu+3Gd5Q7rLFjXAIo1TRix06yexgPJFxPiNIbpViKWCCiRNPIPVkbeThxMm1GDa4SOU/l/Vx4W5V8KxEuvlyvyMg0AAEAAElEQVRSNxCp8iW/o4o1VwSrRrn4c2/ceE42FTHcP4H7c7YT5eLL40k3oxDJWHD6PSRCMW9mzEYgEDpDpWVCMX5yd55MmkKTsROVSEaiewgtRg2Nhg72VZ1iWdwETrVeYt2lb5gVMZxJIf256cirWO02ol38WZUylQ8rjvFFd9cQYM+w+9hRfoTxgensqDhCmbqRDYMXEXhFAG+rQc13DfnYgU9qsrg3bjwPn9mFyWYhWOFFqMqLUy2OLvHiPtcw2r8vz+R/TEFnNe4SJXuH39+jY2XttvX/rZ+bDZ082q1NEiBAKZJisJmRCEWsG7CAuG5XsxpdKytyd7Iq+VZi3AJoNap54txHzI4cSbpnBCdainn83EfOv/Fw4o2UaRrZW3WKWRHDuS1iKHdlbqRa18ow3zhG+ffli9pcnku97Z/KhftbuGxvLROKnZ8rzYYubHY7blIFNruNI42FeEpVRLr44yVz4XxHtdPE5m/pH+HX7n0KkRS91YQQAS+lzyTDK5Kirjq8Za48dvZDnkudRpSLP83GLh4/+xF39hlLikcYZ9srWJq9FQHwasbtuEuV3J25CaPNzH3xE2g3ajjadJGy7kLO2/3vIMLFlxt/egWZUMyL6TN5vfAgpZrGHuvr7xnFqtSp/7Lr+1swWs3ktJXzyNldvNlvLkkeoZRrmlmUuZ4VCRMZ5Z+ISvzHRkZ70Yv/K/ij3KA3uLYX/5FoMnQy/dibzpGfX+K6oHRWJt/yhyux/9fRoO/gneKv+LreMdo2OaQ/PzSep9Osx12iZNuQewhSetJqVGOwmp2V2k6TDq3FgJ/c3UmWirrqWJK1mdVp05GLJEgEIh46u4upYUNI94pka9mPDu1E3l7GBCQjFYp6hF/OihjO3KiRPdzpdBYjSvHPuTtaixHVFT9fiXaThnuztlKsrkMsELGoz1h2lR+jw6zFXaJg8+C7mXZsDQLg/UF38tCZnbQY1cyMGIZCJOXLurO8M2A+80+/59RMBCk8eT71NhZnbsRit/JS+kz2V50mp62ctQPmYbXZ+L4hn4+rM1mVciv9PCPpMOv4qu4cN4Rk0G7UIBdLyGuvItkjjC9rcsnuKEcqFPN86m10mHUsOPU+I/0SGOYXz+oCh1NfgNyDZmMXVruNPi4BPNz3Rh47+yFNxi4S3YJ5JeN2PqnORGc1MTlkICabmR8bL5DiGcZL5z9lQHdQrFIs5bnU23it8KBzBGyAdzRTw4ZQo2ulRN3QY2P+7oD5iBHxbWMeIUpvpyV4glswNbpWZxfolfRZCAUCbNh5ueBTHk6aTIO+HQ+pCrPNypN5u+nqLjq4iOW8O2A+bUYND+Rux4adkX4J3B07jmfzP+aVjFl4y1xRm/UoRFIKu2r5pu4cg31i2Vb+E2fbK3g2ZRoV2iY2lf7A2IBkJoX0p8Ok5em8vSS6BzM3ahTuEgVpXg6NSb2unRajml0VR7klbDDfN+QTpPTi7aKvsWMnUOHBE31vZmX+Pu6Ln0Buaxkf1zhChT0kKjYMvpOjTRfp5xlJk7GLR85+gNVuI1TpTYdJi9piwEOiYlXKreS1VzImMJl5J991hk3HuwWzuM9YHj/7EX09Qnms72S0FiNmu5W1F7/k4cQbsWGny6znYmctvnI3nsjbzVCfWEYHJPFcwf4eGpIEt2BHcK/NipdUhclu5VRzMbdFXEWAwoN2o4a9Vae4LiidvPYKVhV8zCDvGGZHjeT+nG2YrgjBnhs1EpvdzoXOGh5KvJGl2Vt4KHES/b2jkXePAdfr26nTtZPkEYpM5BiTPd9RTYZXZI/g1gdytlOkriNI4cmLaTOQCsWEqXwQC0U0G7oQC4VY7XY8pSon2WoydOEqlqO26Hmku5N2GdEu/jyRdDNLs7egthicHWqpUMyqlFvZW3XKoTNKudXZRf53o1TdyPTjbwIwISidCUHp3J+zDbPdyvjANB5MnPg3x6cbDZ0sOPUejYZO3siYTbRLAI+c+4ALnTU8EH89Q3ximXZsDVEufrzRby5+cjfn9027UYNKLEcqEtNk6OTB3J3OkT4hjvdjkMKThxNv5JmCj2k1qhEJhLzRbw4ZnhHYgOzWUs53VOMlc+GVws8RCYSsSrkVq83REbRj57WM2xnqG/dvHcszWs3orCZnYLAj60+HTCTuJUu9+I/EvyW4the9+N+Ch0TFtYGpv3v7pOB+/zVkqVLTzFsXv2S4XyJigYgF0aOJcQ3knQHzcZcoGOmX4NxAectceyTJu0uVBCm9nJbGaoueNy5+gdZq5IHc7RR11fHQ2V20GNVsK/sJN4mCawNTWJm3lwHe0Vzt35cvf+H2tLPiaI+RqxaDmo0lh53jkR0mLbsrT1Ct/W3DBRexghWJN6AUSVnbfx7XBqTwTOpUPCQqZkeNZFfFUSx2K7eEDeZ0yyVajGpkQgnjg9LYXXmCZI8wTrYU9dCpNegdAujLWiSlSEqFthmjzcy9WVvYXn6EfdWnsXdvfrVWI3urTrGj4gj352zDT+FOdmsZr1/8giXZm7kpfDBhSh9HkKxARIdJix07njIXOk16Z0bPU8m38FTyFEQCIZ0WPTKRxKG1cgvmieQpzDv5Lv7dmVZgZ1X+x0hFYqQCMTX6Ng7W5HSP2uip1rUS5xaEp1SFAAGuYgVCHF2UE91ajcvYXXkCL7kLWrMR324h/0DvGO6IvppVKVNxFctxlyhxkchRiKREu/jzUsZMVhfsJ8o1gHeLv8aGvcdm326302HW4S1zderFJob054Hc7bycPhPv7o2vq0SBWCgiwS2Y2VEjcJMqMHZbxbcY1Qz27sPL6bMYG5DEsuytHG26yOq025gbNYpyTROR3Tlp9bp29lWf4nxnNYv7XMPhhgL6uAVRpm7k3QHzkQul1Os7eP78AV5On4m/3J0LV1hvd5p15LSWke4RwSsXPsdFLHcQRARUd5NGd4mSZ1On8m19HlPCBlGra8N0RcBmvb7NYYYgd6NU3UC7Scvy3B0sydrMPXHjsWLjuYKPuStrI+4yJe5SJfOjRnNH9NVOshTnGsTSuOucurqDNTmOYF8BbCn9gQ8qj/Nc/sd0mHSsu/QtG0sPc1/OVoKUXihFUmZEDEMkENDHNcC5LqlQzHVB6RyszSW7rYx3ir9i4+BFPchSg76D+7O3sSR7MzltZbQZNawu2M+DZ3b2MDkw2ix0mLXODfr9udvJaitFazHQqO/g/pxtrL/0PZe67arBUWg5VJtLm0njJEtCBNwUMhCRQEipppHnCvbzzoD5AM7X0crkW/mmLo/ctnJOt5awumD/bwbl/jvgI3NlSew4AA7VnWFJ9manI+hdsdf8Xa2pv9yddQMX8P7Ahd1umY0si7uOZ1OmIRaIONx4nilhg5CKJAgE9Pi+8ZS5OMfl/OTuvJpxO0HdXUYbdlzFct4ecAdvF3/lvD7eUheiXfyRiiSOEGjvaG4NH8K1gaksiB7NW/3nMsArmpH+iTybOo1H+04m3TPi365hkokkeEpVToMHoUCIl8yllyz14r8ef7jDJBQK/+4GVCAQYLH8/YyI/y30dpj+u1Cra2PBqfd6WGgDDPWJ48nkm50bvP9ktBk13JO1iVJNIwO8o1kadx1f1p3lg4pjDPbuw0OJk1CKZX9Kr9Wo72B57g6K1T+7WqpEMtYNXIBSKKPB2IGXzIVTLcWcbavgSPPFX51jXtTV3BV7DW1GDc/kf8yJliL6uofwer/ZbCv7iQ8qjuMnc2PzkLt+Nfpy2bXLZLOg7A7irNa2YrCa+Lj6tCN0NDCVuVEjmd6t1xIg4I6oUQzxjaVS28Jz3XqcRPcQzDYrl9T1CBHwbOo0vqo7y4WuWlYl38rq8wd6iJGnh1/FzIhhmG1WmoydLM3eitFmRioUO6v7I/0SWBY3Aa3FgJtURam6gRW5O7BhZ7hvPPOjR1OiacBDqmJ/5SlG+ifiIlHgKpFztq0CgUBIikcYe6tOcaz5IkIETre0S+p6RAIhH121DL3VTJdZR6DCA6PVwsfVpznXXslDfSdRpm7kx8bz3B07jmU5W50aieG+CXxR53ALHB+YyqzIEbiK5ZRrm9BYjGwt/ZE7okehEsuxY+ejyuPMihhBqNIHpVjChpLvaTdqmRU1gnuzN9Nl1uMqliMQCJz/fz5tOm8UfsFzqdNYlrOVJ5JuJkThjZ/CvVuwbsFmx1k9X5K1mWXxE7DYrAQrvVhdcIBFMWOJcvXn5iOvYrRZSPeMQCwQ8UL6DNwkCiw2Kz80nneOeS1PuAE3scJZOV8SO45+XlHcnbWJ++MnEOMagN5i4oHcHQQpPJGLJBR21SJAwMqUWwlWeLK19EcWx17LnaffJ0zlw8WuOsKU3rzebw5KkZQz7RU8lbcHq91GmMqHTpPW2aF9o98cvqo7y02hA1mStYlWkwYXsRwfmSsV2mYECHgmZSpBCg8WZ27k1Yzbye+o4khTIatSpiITiinsquXNi4d4NWM2BR1VXOiqIc41iNcuHgQceqzLDmmzI0cgF0kp7Kjh/oTrebv4Kw7/wgI9ROnF6xmzsdnt2LETrvJFLBTRbtIiF0noMul5MHcHF7uz4EKU3k7nx8f73sSYgGTHmG23ZmlZ3ARKNQ0c7HabvCP6ao41XaS4+zX59oA72FRymKdTbuWT6iw2lR5mRsQwQpRevHrhc17JmEU/rygKOqpZlrOVxTFjEQgEvH3FuOiU0EHM7daLPVewnxClF+8OWPCrYGx/uTsCgQCtxYDOYsJdovxdPY7dbv+Hi19qs55n8vfxU1Oh89gXox75w2NsBquZvVUnWVv0FSKBkFfSZ1Gta3V2dFen3kaGV9Tf/Py12KwUdtVyd+ZGZ2dTiIAnk6fwU+MFfmy64PzdONcgXu13O/6/+MzsNOlQiKTOa6SzGLHabX+ZwVAvevH/GX+UG/xhAcKBAwd+97YTJ06wdu1a/h9N9/Xi/wCClV5sHnIXh2rP8F1DPgqRlNsiriLDK/K/giyBQyx/eXY9q7WUe7O20GF2ON5leEci7q7ugeNLVG91bD4E0DMTxW5DgKMa6K/w4MnkKdx+4m3n7TMjh+EuUdJs7CLDK4I2o5ZolwDcJSpcJAqnu9tlmGyOjZ9SLOOWsEGcainmfGcNk3582bkpuCYwpYfw2WS1UG9o52BNDsXqBpLcQxgXlIaLWM7OiqN8VpPtrFSfarnE3KiRbBy0iJfOf+pwLTPru22RRfjKXAlQeDAzYjhRrn48ec4xWhbnFkSCezDzTq6jydBJqkd4D8I0KaQ/+6pPsb3sCHuH38db/eeyKHODkywN9IrmgYSJBHZv8HRmxzW1A4nuITzSdzJai4F2o5Zv6/NYnnADJpuFC5017Kk8wfyY0azM28eHFcdYO+AOWo1qCrtqefnCZ4DD/eql9Bl8UpNFuaaJcUGpLMvZypLYcUS5+DHML54HcrZztX9f7o27Do3FyCDvGE60FPNW/3moRDKiXPxYd8mR3+MmViAROcZitpX9yJK48bQa1QQpvFhVsI8VCRNRiaS0mzX4KYJYGDOGBn0naoseg9WMh0TFG/1mIxGKuTd7M1qLEa3FgItEzqr8fbzd/w7Od9bgLlGC3u7s8phtVmJc/HETyXm93xy+qMlFKZbyVN4enkmZilAg5P1L3zpfC2faKxAgIKu1hFSPcBRiKWmeEYz0S+Snpgu8VnjQ+RyleIQ5LO+Lv2LrkLvZVHIYN4mSOn07S2LHMdQ3jkptM9vKf6Ja24qHRMmu8qPc2Wcs92Zv5qHEG3GXKPmiLpfvGvLJai0lwsWXALk7QgTEugXzdPItji5rznakQjEuYhnzo0fjKVPx7sAF3JW5kTaTxhnE+ULadOLcgph69A1s2FGJZShFUu6NG89dmRsY6huHwWrmlYzb2Vl+hAUxY3i58DMmDMjg0b6TeeH8J06yNCPiKq4NTOVMezlzo0fRYlQ7ydLiPteQ4hHOfTlbcZMoaTaqefLcbl7vNxuBQEC1tpV7sjaxImEiA3yieSXjdpbnbqdYXe8kS4/1ncyYgGRcJHI6zDrujBnLt/V5pHmGMzqgLyke4RR0VDlt60UCIS+nz2RPxUmy28qY/NMrzvehwWpipF8iQ33j8JSqUIikpHmGs3f4/fzQUMDa4q+RCsWkeISR3VbGx9WnUYpl3BY+lNWpt5HoHuI0mukwadlW9hMHa3PYNvgePGQqfmy8wOqCA2watJio3zAxsNgsFKsb8JK6OElXpaYZG3YifxGa/UuYbVZK1Y2c7A60vYx3i7/m3rjr/lCRSS6ScE1ACodqz1CqaeSB3O3O2wb79EEsFGO0/b5NuNVu42JXXbdmyUKA3AMXsYwSTSPP5n/Mk8lTmBU5HI3FyPJcx9hkfnsV3v6JPYKOf5l5pfydcede9KIX/zr8Uxqmixcv8uijj/L5558zc+ZMnn32WcLCwv7K9f2l6O0w/XfCarPSZdYjEgh76Gr+G3Cho4a5p9791fG7Y6+lydDFDw0FvDdoIX4yd35qusDzBQfYPHgxrSYNoUpvgpVe3cGQ9YgFQqJd/anRtbE4cwMtV4zKiARCnkq+hcMN+dweOQJvmStLs7dQrWtlRcJEzrZX9DCb2DhoESndduQGq5lGfQer8vdR0FmNSCDkrX5ziXYNcG5KrHYbuW1lLMve5nRyA1gadx01ujb2V58GYFxgCqdaSug063CXKNky5C6kAgmbSr+n1aRhbEAy7136lsf63oTWYuSpvD34yFx5s/9cANYUfsGdfcbiJlGyt+oku7oDQAUIsGNnRcJEStQNNBo6WdRnDNmtZT0q5A4DjHmEq3xoNWnIailloE80xV31RLv64yd3R28x0qDvBAGUqxv5vC6XCJUvYwKScBUr2FL2I4fqzhCs8OTtAfO56cirzvNPCu5PP+9Ins7byyOJN3KqtYQfuzfLE4P78UPjeafL4QtpMzjZUszEkH4YrGaeOPcRIUpv7oubgMVupbCzBrFQTKpHOGc7KkjzjMRsMSMXS5GLJJjtVrpMehZlrkdnNfHewIV4SJUsz9mBq0TO/OjRiIUi8turcJPICVB4YrZbkQiEvHjhM+JcAxnul8CzBR/jKpbz7sAFqM16p8X7c6m34StzZVf5MSaG9EMoENJu0pDXXoXFbmV7ucOa/ubQgZRrmpykaU2/OVjtNtK9IjBaLSzK3ODc7HtIVLzVfy53Zq53/txg6EAmFPNW/3mEKLzwVbjTYuzCYrOhs5p4Jm8fUa5+RKh88ZG58W1DHiebi3ku9TaEAgFn2ivYXXmCO6KvZoRvPK0mLU+d242P3I2VybegEEtxFcvx7a7q1+naWdEdFAsgFojYOXQJCpGUZmMXz+bv46WMWQgRUq9v4+HujDKAdM9IpoYP5kxbBeMCHUHC6y5900N/1t8riuUJDv2MxWoGgZASdT193AI51XyJ7xryuTlsEGFKbx4/9xEV2mYUIilPJk1hTdEhmgydqMQyDoxYgdVu4+m8vT2iBF7PmM0A72hkIgmtRjVvFH7BpJD+JHuEYbJZ+KjyBCqxjEptM5/WZDPKL5Enk6ZQoWtm/qn3nOcZE5DEw4k39jCYuIxWg5qV+fs4017O2wPuIFLlx8aSw+yuOsHTybcw0i8Bu91hsy0WiBjgE02XScftJ97htoihhCi9cJMoWZq9hfGBaYwNSCLWLchJisBBli501nJ31iaCFV682X8uRquZRZkbsNntvD9o4d8kTWXqRmaffAeTzUKYyoehPrF8VHkCgGlhQ7izz9g/3KFpNnRx27E1Ts1slIsf98ffwP052whSerK2/7wexh5Xolrbwl2ZGxELRbwzYD4SoYgHc3dSrWtlbf95xLj4g0BAbls5dfo2xgWm4fIHs7b+Cvyyg/fPdPR60Yv/RPzlHaYrUVdXx9NPP822bdsYN24cZ8+eJSkp6R9ebC968c9AJBT911qZukuViAWiHiTDVSynv1c0S7O3oLEYWHx6AzeG9Gdz2Y8M842jRNPAqrx9BCg8eHfAAjrNOhZnbkAkEPLewAVsKPmeFqMalVjGK+mzWHPxEMXqep4v2M+OoUu48/R6xAIhrSYNUqEYb5lLD3J1lU8cIUpv58+tRjUr8/cyN2oUO8uPcnPYQD6sPMH1wRlc5RPbbROu5vGzu3s8DoCTzcXcHDqQz2uymRM1kukRV9Fs7GLR6Q3084pCIZKiEEkZ6B1DtGsAs06sxWSzsKX0R2ZEDkMqFFGrb2NV3l6Wxk/gWEsR+Z3VfDRsmTMo97bwocyKHM6dp9fzWuFB3u1/B64SJadaLznJUqJ7CKXqRur1HdyXs5W3+s/jnaKvOdFSzGN9JzPYJxZPmQqj1cyFzlreKvqSNpMGpUjG3bHXcqjuDEKBkE9rskl0D8FFLGNK2GAeOrOzx+M9WJtDimcYo/z78krh5zyRdDNWm5WjzRf5vNtYw1vqwovpM1mZt5dafRtn2yuo0DTTbtbiIpZTpXOMJI4PTGN6xFU8evYD8jqqmBCUzoLo0eyuOsnYgCRClT7Y0SESitCbTCzO3ICnVEWdvh2RQIjFZuXHxgJKNU3EuwWjEisIVXphsll4JX0mW0t/JL5bU9Vu0rLg1Pt4SJQ8kXwzYoEIH5krj539iDuir8Zit9Gs76DLrONq/0Q6zDq+a8h3dDrEMgZ79wEEzryo5wsOsG/4/RSp66nqzp4B6DBryWkrZ0roIK4NTMVdoiC/o4pVefvQWoy4dhdEfGQ/f6k9kzqVW46+zqyIYQz0iaGrWocNO0+c+4hUz3DOtFcAjk1vubaZVy98jtZq5J7QIajEch49uwu6iZzFbuOJcx9RomlEgACpUIxYKKTB0MG7xd8S4+rPmv7zON9RzXcN+bQaNTybMo0n83ZjsJqZGj6YgzW53Bw2kHaThs9qs51kKdkjlPyOapRiGSXqel6/+AVr+89DZzHiJlEy+8Q7PJg4CZFAwJ7KE1wflMELaTO4L2crjYZOHjv3IQBKkZR1AxZgtdt5vmC/kyy5S5R0mnU8eGYnr2bcTrJ7KDvLj/JNQx4/NJ7nzf5zyWktY1OZo7P0esZsirvq+bHpAgMbYvCS9PwMLeysRWsx/iZh8pa78nTyFNpMGiJd/LHYrIwJSOIqvzh+bDhPtIs/dfp2Hj37IQLg3YELSPeMYNPgReytOsV7l77lhuAM1vSbQ5OhiwfP7GKAVxQrU27Fp3tczmZ3dIlsdjvl2iYWZ25AZzHRYdbiKpZjtdv+5ubeQ6pitH9fLnTVsrb/POeI5Y7yI9wUOrDb6dOBJkMnWouRCJUvAoGANqOGVqOacJUvJpuF480XexgMVWpbsNqtDPKO4ZK6HovN+ltLACBU5cO6gQsQCoROfekrGbNQm/WEKLyQiR1h1hlekSTbQv+tZEljNnC+s5oYlwC85a6YrBYudtU64xl60Yte/Iw/1WHq7Oxk9erVrF27lrS0NF566SWGDx/+r1zfX4reDlMv/tNgsJjYUPq906b5MmJcAliReAMrcnc6x4bAoSEYH5TGkqzNGG1mvKUuaK1GDFYzfnJ31g1YgEAA9+VsY3XqbcS4BtBs6OKhM7tYGDOGHxrPOzful3UN5zuq2VN5EheJghkRVzHUN87pfNVi6OL58wc43lzkyMxJvY2Pq05zsqUYAQL2DX+AUJU3hZ21zDn5To/HIBaIGB3QlxuC+xOk8EAhkjir/DW6VhQiqXO0UmcxktdRSadJz4cVx3kqeQpaswGN1cibRYd4JmUaT+ftoVLbwtPJt5DTVsaE4HRONBczI+IqPKQqanVtbCn9gYUxYzBZLZzvquHpvL2M8ItnRcIkSjQNPHLmAyJd/HgwYSIP5G7nsb43YbCZGOTdBy+ZC6XqBix2G4+e+QCVWM5r/W6nxaCmWF3HD43nuT/+eh48s5PXMmaz5uIhjjVfRCQQ8lDiJD6tzuZCVw1CBGwZchcrcncSpvRmTvRIlmZvBRwdlUkh/ZgWNoRNZT+wvzoTiUDE0vjryG0r447o0XxWnc3eaofVsUokQ2s1IkDA/hHLWZ6znTJtE2MDkrk//nreLf6KcUFpPJP/sZP0ChDwcvpMEtyC0VtNlGkaMVrNJHmE0WHS0mjswmA1kegegsasx2SzsiJ3BzKRhJUpt/Di+U+x2m08mTQFvdXE9vIjlKobWJ02nY2XDvNixkykAhF6mwm7HZbmbKFR38mzqVPRWow8V7CfNzJmA7AsZ5vDctwjFFexkhMtRQA8lTSFob6xvFP8NUarhbv6XIusWwx/eUPZYlBjw8aHFcedncTJwf0ZG5jMe5e+6+HqNim4P1f5xvHI2Q+wd0cWTw0dwnD/eO7L2YbVbuMq3zhuCx/KitwdmGxWnk+9jUgXX/ZWniLcxdepWxkTkIRMKOGrurPYsPNY35vIaS3jp+YL2Ox2Xs+YzZnWcqRiMc0GNfuqTzE/ejTXBaWR31FFbHfAb6tJg5tEwdK463ij0GHEEqjwYP2gRdxxcp2jcBAzliSPUGcuFcCDCRO5KXQgjYZO7jy9nmZjF0/0vZmr/OK4P3sbF9V1zIgYxryokeitZu7N3uLs4F3G+MA0ZkYMY1Pp9/zYre95f+BCVp//BB+pCyWaRsYGJHOqpZh3BiwgSOmJ0Wp2hnT/Fup07WwuOcxndTkIEaAUy4h08UOIgNVp0/GVu9Fi6GJ7+RFnpyfOLYjirnrs2MnwjOTZ1Gk99EUmq4X8jiqWZG92jgm6iOWsH3TnH8qjajNqMNutTk1Qp0mHyWbBR+bqvG+ToZNHznxApbaZ9wfdiY/MlTcufsE39XlsHryYCk0zT+fvBRzdwTaThjKNwwJ8bf95BCu8CVR6/M11/F+ExmzgcGMBzxXsZ5hvPE8m3UyZpol7s7cQpvJhTb85vaSpF/8v8Jfbir/88su89NJLBAQEsHr1am688ca/bLH/LvQSpl78b+Gyo9vlEbUGfQd2u51Apafz9jaThjClz6/m+NuMGg7VnWFb2Y90dgvzb48cwY0h/dlW7jBYuIyPrlpGmMqHwq5aFp3e4OzoeMtcWT/wTkJVjs5Qu8lh4S0UCNFZjGjMBkw2M0uytzg1PyKBkE2DFhHh4ofWYkTUrZe6MudFbdZTo2vjkbOOwNErsTRuPNcGpOKncKego5o7Tq1z3uYmUTiDLr+tz8NNosRH5sryhBvo4xaIQiTtcS61Wc939QXEuPqjtxr5uCqT2yKG4i11RW3R8/6l75gaPoRafRuFnbUcqjtDolswL6TNcF7jFkMXpZpG6vTtrLl4iPUD70RnNeIuUbIqby+r02ZQrW/BbLOiNuvxV3jwfvG3nO2o5N648Yz2S+KebIcW4a1+c/GQqvCVu2G127jUVY9MJEGAAJ3VyJe1Zxnp7xhneyhhEn09QjFazTx85gOu8otDazEQrfIn3TuS1y4c5HhLEaP8+7IoZgw6q4ld5UdZ1Oca7srcyPKEG/ix8QJTwwdTpm4k0sWfvVWn+LYhz3l9nk+9jX5eUXxak8W6S98CjtwYkUDIs6nTeOPiF85OjkggZOOgRWgsBg7W5vJ1/Tnui5vAtYEpfFOfx5qiQ4wNSGawdx/OtVcyPjiNZdlbCVP5sCR2HI+f+wi91YSfzA0PqYpidT0CBDzS90b6uoVypr2cWLdAHj/3ES+kTcdP7s6NP72CEAF2YGJwBg8k3IDarOf+nO0oxVKeT51Os7GTjSWHKdc28ULaDL6sPcPuqpPcFDqQsQFJWGw2avVtXBuQSpWuBYPVxPf1+US6+vNa4UGG+caR31HNzMhhVGtbeljhP9J3MtmtpdjtDu3LptIfsGNnRvhVDPCOYcWZHVjtNlI9wpkRcRWWbve7F84fYE70SIQIyW0rZ3PZD8S6BrI84Qaqda006jvwV7iT4hFBg76dR85+QIDCkzX95jD92Js8lzoNiVCMzW5nac4WHkyYSJxbEBKhmGXZW516RHC4ur2WMZvXCz9nfsxoctvKGeOfzPLc7c6sscvP63sDFxDrFkStro1Ok5YoF39UEjmN+k6K1HWkeIQ5O0Mthi5u/OkVzN2fBSkeYTydfAt+cndHWO75T0jzjKDJ0IXBZubuPtfSYdbxTf05olR+pHiGIxII+aI2l/FBab9rmFCpbUZnMfLqhc8p1zbzTMpULHYbfd1C8FW4obUY+LHxAi1GNfX6dvZXZzrvm+YZzvOp03/z3JWaZuacfAed1QQ4xmbfHbAAT6nKqeVpMnQiE4px/41u2N9DlbaFhaffp93k6FzFugWR01YGwGN9byLVI5y7sjaS6B7CY30nY7HbuD9nG3bgjX6zf3cU7/861GYD3zfks/q8Q58e5eJPlbYFi91KlMqPN/rP+Y99bL3oxZ/BX06YhEIhCoWCsWPHIhKJfvf39u/f/+dX+29CL2Hqxf8G2o0a1hZ/hdVuY1ncBEw2CwdrczjadJHnUm/DVSLn1Quf80PjedYOuIMk99BfkSarzUqLUY3RZnEENYplHGsu6hHyCY5xrg2DF6ExG1hw+n2nmYGf3J31AxcSdIXlOECTvpPjLUUEyD14tfBzJgSl02TodLpKrUy5BaFASLJ7CAqxnGZDF4VdtaR7Rjjn/9VmPe0mLbccfd153uuD0lkSex3ecgdBrNe1M/XYGqdA+qnkKewsP0bZL8IYhQjYMHgRyR4/ayHVZj2nWy5xuPE8aZ4RvFr4OTEuAQQqPOgw68jvqHKsNflWTrUUMyE43dlR2TL4Lvp6hGKxWfmmPg+5SMJHlSc4217BYO8+PJ18C7sqjvFpTRbrBy1iQ8l3nG4pQW81EaDwoE7f7iQDdfp2xgWmsiJ3By+nzyLa1RE4a7JaaDdpMVhNyEQSpEIxZpsFsUCEUOCotAuAsx2VuIrlWGw28jocOp/1l75jVcpUGg0dBCu9cBHLebXwIGWaRqJd/Hku9TZeLzxIVlupI9B30CLs2Hkqbw8XOmuc12hmxDBG+SXiK3fjk+pstpb/iEos49mUabxb/A0lmgZEAiEKkRSNxYBCJGVNvzn82HiBDysdhDvJPdTZlRnuG8/kkAEoxTKW5WzFZLPgL3cnTOnD1PAhPJW3B333BlbQ7fglRogVG6vy9xGh8uXRvjfRbtKwu/KEcywOQCIQ8faAO0jyCKPNqEYoEOIrd6PNqHEanDydt4cWo5obQ/oT6xrIK4WfMzYgmXGBqY6O3ZldxLsFMSdqJFKh2OEi6RWFXCTj4+pTzg7GZfdDAQKeSp6Cn8yNLovDGe+erM081vdGBnj3YdHp9TQaHbb4I3ziuT/hBj6oOMbe6lMEK7wY6hPL7VEjeDZ/H9MjhvHkud0M9Ilhaex16GxGVuTuwEOiYln8BMw2C7XadlI9wzjacpEGXQf7u7OjJgSlsyhmLLvKjxLu4scrhZ85r8tL6TNJdg/lvpxtqC161vSby0NndlGpbUYpknJf/PVsKj1M4xUaJrsd9ladZEJwOiFKb0fXoKGAWLdA+rgFojEb2F15go2lh3tc/7cGzCPZPQypSEyrUY0QAQ2GTgIUHtjsNh46s4v8jiomBvdjadx1vFl0iIO1uaR5hvNC2oxfmepUaptZfHoDBpvZYbstFLG26EvKNE28nD6Tfl5R6CxGJh95lTEBSSS5h/JK4efO+48LTOXeuPG/ctSs1DSzKHMDbSYNMqEYi92G1W4jUuXH82m3EazwotnYxeLMDVwfnMGsiGH/EGmq0DSxKHMD7aafCeyS2HFMDhmIm1RBra4NuVCCt9zxuC/br/+nd2A0ZgPfNeSx+orQ6wiVL2/2n9tLlnrx/wZ/eQ7T7NmzmTp1Kl5eXri7u//uv170ohc/w263U9hVx8HaXL6sO8ubRYc4VHeG9SXfU9hVy6c1WXxdd45vGvIw260Ud9X/puuSSCjCX+FBmMoHf4UHequZVfn7AMeYyObBd+EiluMrd6Na28ribuc3d4kCqdBh/3x31ibqdG3Oc7YYunjpwqe4SZTdbneDaTGqiXMP4q3+83g2dSovX/iMZdlbyeuoptWo5um8PazI3cHX9efQdOe8mGwW1hZ92WO93zcW0GBsd872e8tcWBo/vvv/rtjt/IosgSOjZM3FQ3SadM5jRqsZD6mKRPcQxAIhL6XNYEncOMYHpXGx05HL83jfm8htK2OUf186TTpeTp8FgJfUhVajGrFQxDDfeOr17dwWPpQZEVdxU9hAusw6wlU+vNlvLu8Wf82E4AyClF7YsDs7bU8m3YzRamZb2U9UaVt4q/888tor0VmMtBrVbCj5nluPvc6tx97glqOvs6n0MCKBEG+5K54yF2QiCfWGDpZlb2XOyXc5VHeGq/0T+bw2B7PdytN5e6jXt/PImQ/YUX6U+dFXO7Nuph9/k6y2UgBmRg7nQHUmWouB4i5HVyfeLQiAXRXHqNE51lusrgMcOh+hQECtvs1pifxy+iyHcYXVxPnOaiaG9GOkXyKAkyxd7d+XawJTyGwtQdg9thSq9Obl9Fk8kHA97hIlAXIP5/OjEEmIdQ2gTt9OsMKT9QPvZGr4EIQCAVXaFsJVvgAsjB5DmMoHs93KkqzN3d0ZD2dXwUvmQqxrIM/l73OOD4YrfVFbHK+z7xry2Vr2Iw+d2YXFbkVjMRCk8CRM6c24wFSqdG3orSZ+uMJEY/vQJSS6h2DHzsHaXLosBh47+xE27Owf/gDuUhXPn9/PsvgJSAViBAg40nKRFWd2MNw/AVexnAZDB4keIbxa+DkhKh+KuurQWo380HieFy98wvKcHdTrOyjTNCEVithQ8j02bBR0VvFu8TdOsjQuIJU7oq/m1cLPGewby7uXfjYbAVhdsJ8Wo5rxAWnU6ztY2W0MEqTw5OX0WZR1NfJ2/zsIVHjwbMo0bHY728t/YmPpYe7K3Ei9rp1v6s/x3Pn9LM7cQJW2hcMN+U6yNDYg2Xn9l2ZtoVTT4Hw/espcSHAPxlOqQiwQMcQnFoDPa3O45ehrTivyoT5xSAS/UTC1020TbuTJc7t58fwnXFI7zq8xG2jQt+MuUbJ50GLSPSN4tdsVUSVydIi+rj/H9rIjPQiLwWqisKuWNpMGV7GcLUPu5q3+8xALRFTpWqjWtvJl3Rmngc2+qlPOLtSfhbtURR/XwB7HhvnG49o9/hms9HKSJXAQpf90sgSOgsKVelQAX7lbD3fTXvSiFw78Uy55/2no7TD14n8DXSY9n9Rk9nBjAxjhl8Ao/0SeLzjg7D5NCun3h5ybTFYzue0VfFB+jKeSp3Traxr5ovYMfT1CeOLcbnzlbrw3cAHtJi13Z25CKBCwfuCdxLoForOaeLf4a/ZWnUIiELEqdSr57VXObsPa/vMIU/mwImcHl7q7E0EKT6p1jjDa51KmMcwvHpPNwhsXv3CG286OHME39Xk0GDqQiyTsGrrUOQbYZdZzsbOW481FGG3mHiM5v8RnIx8iQOGBxqzn24Z8Xjj/CVPDhjA3ehSl6gbuy9lGhmckk0MHsKHke15Im45EIKJc24zWYsBX7k6XSYdCLMVoNdPXIxQ/uTsdJi13nHqPcQEpJLiHsKn0MNXaVt4ftJAnzu1mcZ9r2FFxhIKOn/Uvz6RMda6/r3sIIoGIQIUHEqGIt4u/5qfGCwigx9jUtQEpPNR3EhabFbPNhtlm4UBNplOL5iFRsSrlVl67eLCH6UGCWzDPpEylRNPAo2c/dB6/M2YsUS6+hCp92Fji0J082ncyAQoPDjcUYMfO1LAhvFP8tTPkNsk9FKvdxvyY0VhsVuLcgviiJoc0r0jq9R3EdrsY7qk62UMjNytiGBKhmLEByXxYcZxRAX0J7CZINuy8XnjQ2TESIsCGw2781YzbOdlSTLxrEOEqX/LaKxGLRNTo2ujrFoKnTIVSJOPenC1c7d+XWRHDe9gltxs1HG48z8mWYo50dzgHeEWzPGEiPzQW8H7Jd87fjVD58nTyrQQpPKjWtRGs9OTmI6/hKpazKnUqp1sucW1gKk+c+4i7+lzL6dYSBnhF81TebuLcglmecD3VulaeOreH64LSSPeKpI9rAFXaVlbm78Vqt/FC2nQO1Z7BQ6oiTOXDO93v31fSZ1GibuixHplQwnsDFxCo8KSoq45Yt0C+qM3t8Z6/N3Y8o/z7YrPbWHh6PR1mLT4yVx6Iv56XL3xOh1mLn9ydDYPu5OHcXSyNuw4bNgIVnpR2NRHvEYREIHJMe4ikGKwmanRt3JO1Cb3V1CNLbLhvAo8lTabTrGPR6Q3cFDKAGZHDMHRrmiJUvjycOMlpsPBLdJl17Co/xpayH53HFkSP5rbwob/pRGq126jQNLEka7MzF0/YnZGV2VrC/OjRBCu9aDWqWV1wgKPNF8nwjOTF9BnsKj/KtvIjBCu8eH/Qwh5dJo3ZwJHmQmJdA4l28cdss3Kuo5JOk47ParM51W0ZrhLLeH/gQmJcAxD+ySDXNqOGN4sOOT/DLjtquorlvP8HtVL/ibisD7s3ewsWuxWVWIbWYgQcHebHkm76r4nn6EUv/hb+8g5TL3rx/wEWm7VHlRP41c9/Fm5SBTeGDHB2A8BRWV0WN4HVBZ90ZyQJGOYb97tkqc2ooaNH9dVMjIu/01VK2G0ZPidqJFf5xvFy+kzWDVhAiNKbBLdg3h04n/cGLiTGLQCBQICqOyslXOWL2W7lsbMfOsnSpOB+lGkaOdpUyGv9ZhPl4o/VbnOSpWdTpjLMLx6lWIabRMGMiGGoRDIeSbyRGRHDeHfgAgLkHlwflIHsikqlm0TBQJ8YFsaM6dGh+CVUYpmzs2G225yC9T1VJ3n87IdOkX6rSYNKLKNe30GToYuPqk7y4JmdlKgbkQrFtJo03JezjUN1Z6jRtdGo7+Dl859Ro2tFIBBwsqWYwq5a+rgFoDUbeTF9Bh9VHqegoxoBAudmYWWeYwM90i+Be7I28Vz+PgxWM50mHcN845gTNZLbo0bwRr85XB+UDsC3DfnU6tqp0rZSq2+lWtdKtIs/I/wSAIcb3OHGAqaGDenx2G8JHQzA/qqeZPL7hnxHtlL+XsYFpfFS+gwKOqqw2W2keoZze+QI6vTtKMUyXMVy1vafyzMpUxnhl8Dm0h9QiqTktJaR4R2FWCikWF3H4cbzfNdQ4CRLl3VjOyuOIRaKUIikFHbVsv7SdyzN3sLZ9grajRrOtVciQMBzqdNYP+hOFCIpjYZOMltKqNd3cH/udvI7qxEJRTx29iPeKf6aVpMGiVBMo6GDdQMW/IosGa1m8jqq0FtNjPBLYGXyLdzV51ru7DOWi101TtJ9GSFKL8QCh67om4ZzHKo9w9r+8+iy6Hn63B5sdjvLsrfwWN+bebHgEzwkSp7K202AwpPlCTfQoO/k46pMbgjOIME9xBFJIFagFElZmXwr98dPIFzpQ52+nUN1Z/CWuTDCL4GFMWO4pK5nfFBaj05LrGsgwUovvGQupHiEcbihwEmW5N1GCWuLv+JUyyVs2Hk+dRpBCk+eSp6CSixn7YB5BMg9eDBhIp9UZfFyxix0ViP352xnZf5eYtwDurVBTVhsVoxWEzvKj7K++FveHTAfwEmWMjwjeShxIgarmSgXf3YOvZdrg1LRWYz4yFx5d8B87okd5zRR+C1YbDYaDZ09jjUZOrH+Tn1VJBDiIpajuiIfSCQQEq7y5c6YsU53OG+ZK48l3cT86NE8mzoND6mKWZHDWRY3gXcG3PGrkTwXiZyr/fo6SYtU5LDRj3UNdJIlcHQTfWVu1Ora0Hab4JisFiq1zT0+N38LnWYd3zcUAI4xvH3DH8BTqkJtMbC/+jRd3Z30/zborSaONhU6NUu7h93P431vAiC/oxq95R/r1vWiF/+t+I8jTO+++y6RkZHI5XL69evH0aNH//6detGLPwCLzUqxup5l2VucM+rV2haWZG36zfGxPwq1Wc+hujNc7KpzHtNajbxd/BUPJ05ChBA7dhacfv83/06bUcPrhQfZXvYTHSYtXSYdH1dn8nzBAWz8vIERCoSOKr5YxhCfWOcmUywUkeAWTKxboNOsAUAukvJC2nTEV2z80j0jGeIbyxsXDxEg93RuhK6Eu1SFuPs8QoGQPq4B7BvxAAO8Y3it8CBKoYQNgxYxO2oEL19wEBSt+WcnPxeJnKsD+iLgt6u2t4QOxkvq0D55SlXMjRrFjIirAEcAqtVuI8rFj+dSp9Fo6MRoM1Orb0PXXR3dWXGUNRe/4NVujYTRasFLquK7hgK+a3RkSUmEIiYGZ5DuGcmTyVN4/eIXtBk11OraECDg0b6TeTFtBgluQdiwc0ldz9n2St7sP5dKbQsNhg4uddWzPHcHrxZ+zmuFB3kodyfeMldmR47Ajh2FSIrZbuW5gv3srTxBuMqX3LZyAEb59yXZI4zXrwhsBZCLJbxa+LlzDG9sQLJzPG9V/j5WJE5iVd5e9laeYkrYYFqMXTyT/zFrL36FXCTh+qB0Ng5ezLn2Ks60VxCs8OKp5CnktJfjLlXy4vlPeercHvZWnaK/dxRfdVfVR/olsm3IPYzqHs/7qbEQiVDEi+kzsdittJo0GKxmKrTNPNJ3Mg8mTqRW18baoi95JmUq86JGMTogibz2Sqzd1tyPnfsQO3aS3EOIdPFlc+kPdJn12O2Oa9Np0tFu0tBiUGO3OTbvbxV9yeqCA7hIFKR4hOIiliMVSliZ5xg/vUzAjzUXsaP8COEqX4b4xPJdQz7n2iu4PXIETUaHE1u6VyQNhnbazFo2lh7GaLPQoO+gydDJhxXHmBo+hChXf14t/JxV+fuoM7TTzysKpVhGikcEXjJXhvrGYrPbeb7gAMN94xEhZKR/IndnbXSaKADkd1bx2oWDtBk1GGxmPqtxGE6M9k/i85EPMyYgGYBPa7JwEclQieU8n3obL5z/hHXF31Da1cDbA+5ge/lPfN9UwLMF+3j07IeY7VY6zXoa9R3ktJWxKn8fHSYt7xR/w47yI4S4+JDXreG7jBp9W7el9wfU6dpoMnQy7+Q6Xi38nHp9BzqrkbuyNrI8dweNvzBqAcfnzdvFXznDqqNc/AH4rDaHd4u/pr3bwOZKNOo7WZ6znSpdKyKBEJVIhtlu5e6sjXSZddiuIGfeMlfmRI10jmK6S1XcHDbwV/rKy1CIpT06PA2GDhZlbejxO2ablW8b8ply9HV+bLyAtttVc/qxt9heduRvkqZQpRfvDpjPsrjrmBwykFCVN+8PXMi08CEsiB7zq9DY/y1YbFY6TNoeFubtJi2Gf5DYuEuVzIkexZLYcbzRfw5+cjfGBCSzMvlW3h+0kJBfFCl60Yv/7/iPIky7d+/mvvvu4/HHH+fMmTMMHz6c6667jqqqqr9/51704u9AazGyNHsLF7vquDd7Cxc7a7krcyOX1A08kLP971Yqfwt2u52CjmqnJfHYgGTmR10NwA+N52kwdHJg5HJnhson1Vk9KppWm5XM1hK+achjZ8UxtpT+wEeVJ1h36RuOtxTxfUM+5u7K8pX4pWmEWCjqQZYcx4R8VpPdIxvJ0bWwMzYgiRhXf57O20NeRyXgyHkBuD9nG2faKzF1h3UKBUKECJh/6j2+bchzWvDel72VI82FrMjdQYW2meNNRc7Nlq/MjaeSp/yKNCV7hHJr+OAeKffK7hymKxHv5tBbXBOQwkOJk2g2dHF3n2uZ0N3hOd9tiDDAO5qHEidxx8n3cJXIudq/L3dEX427RIm/wlHRz2wp4enkKfjIXVk3cAHPpk4jt62cZdlbeLTvTQ5nM9cgol39MVotbB16N9WaFsJcfFgYMwYhAuZFXc36QXfydf05+rgGcn/c9biI5fjJXBHYBcyOHsW93blZPlIXlsSO453ir7FhJ8EtiL3D7ydM6c259kr6e0cDjlDfNM8Ink2ZhkggJMUjHLlQQpJHGNMihvLShU+RC6XcGzuOsYHJeEhUBCu9ePTsB2wsPczJlmLSvSJ5u+grtpX9xLayn1gafx1Nxi5kQgkyoZjHk25iTuRI7o69llpdG1cH9GV25AieTZ3Kpa56RFd02tYWfwUIMFkt5LaVs+7St5zrqOLzmhyuC0wDO7yWcTueV4jugxSerEyZilwo4frgdI43F/FZbTaV2mZ2VRzjh4bzPHluN0XqejylKhLcgrFhZ0XuDu7K2kRhZw0/NV3AYrcSofJlw6BF3B7piLI43VqCDTtCBIiFIkJVPmwvc4TljvBLoJ9XFE+e24MdO7GugfjL3THazDyZt5vbo0awqeQway4eAmCQdwyRKj+UEhnpnhH0cfXHS+bCvKir2Tf8fl5Im46/3IPrg9P5uu4c9XrHyOmWwXexNO46AL5pyKNO3463zJVX+93O3KhRPJg4EXepkhUJNzA3ahRrMubSYOhkwen3mXdqHcN841kSNx67AL6uO8e4gDSWx9/A9PBhSEViwpTePBB/PTvLj/JM6lSWxI7jvUvfkt1WyvYh9xDvFuT8bIl3C0IhktJk6OSpvD2sSJhETlsZ5zoqMdrMHGsu4rmCj1mcuZFWo5pafRua7iLDlbBjd3YX7u5zLe8PXMiimLGAoyvxW32pDrOWym6y9Ea/OWwfugQfmStai5HznTXOYN/LkP/CnvyXrpi/hw6TlucL9tPanSO3adBiBnpFk+EV6QyAXpW/j5fPf8rS7K1Y7FZOtBT/zZwksVBMonswk0L64yZ1dPgjXPxYGDPW6Wr6vw2LzUphVy23Hn2DYnU9Vpuj8z7z+Fucbi35h0mTp1TF1PAhToMHF4mc0f59/2YgcC968f8V/1EapkGDBpGRkcG6dT/bEyckJDB58mReeOGFv3v/Xg1TL8AxqlGubcJb6oqP3BW73U6FthmZUEKzsYu7M3tWj5UiKe8NXEifX3Ro/ijajBrevHgIi93K8oSJCBFwoCaTww0FvJwxi0CFJ2WaRj6pzmJu1KhffUl3mLRsKf3ROTJ3GTcEZ3Bv7Ph/KLRXYzbwUeUJ1nfrMEb7J1GqaaRS24xEIGL9oDvxlroy99S7tJk0PJcyjXSvSJZlb6VE08D8bj3D5eqrzmLkp8YLTrJ0GWKBiJUpt/JZTTaZrSVMDunPPbHjcZcq0VlMtBi7ONFcTLtJyxDfPoQqvXvMzZusZs62V7IsZytWu61HiO+MiKuYGzUKkUCI1W7HaDXzbUMeb11hQHFL2GCS3EOw2u28UHCAFX0nYbPZcJUoWH3+AK9l3E6Y0ocGQwcP5G7nnthxDPHuw5qiQ6R7RjLMNw6hQEhBZzVP5e3h6eRb8JW6IhFJWJq9mYkh/Zkc0p9jzUXsrTzJE8k3o7eYsAPPFnzMC2kzCFF4YbSZebPoSy511bOm31yEgM5mZkPJ99wfPwExIjRWA+8Uf829ceORi6ScbrnE2qKv2Dv8ftpMWs61V/B+yXe8mDaD9y99R2FXLSKBkE9HPshn1VlEuPhTrmlCbzWxs8LReVeKpE4h/D2x42g0dLKv6hTeUhfW9Jvb3QWzMPvEO0S4+PJw4o0oxTLuy97Kaxmz2VDyPUeaHXoilUhGrFsg08KH8sjZD3q8DhdEj2Fn+VHi3ALZW3UKmUhCfkeVM6tGJZJxuq2E4b4J7Cw/wpiAZLaU/UCCWwijA5J4+MxOzDYr6wYu7GFR7yV1YeuQu9lTeYL+3tE8nbeHKWGDcRXLGezTBy+pC+faKkjwCOGtoi/5tiGfIIUnyxMmIgCePLebKFc/nk6+FZPNwvLc7YDDLnpl3l5aTRqiXPx4NmUawUovp031b0Ft1uMqUdBm1LC+5DtuCM4g3jUInc3E5zU5BCm8GOzTB0V3EKneYnL+/8qfG/UdPJCznTTPCAb6xPDwmV0M84tnRsQwxAIh92ZvIUTpzV19ruGL2hyuC8rAYreyq/woKxImsvrCJ9wTey1ri77m6eQpPHzmA6Jc/FjYZwwmq5V7szd3E9VbKVM3orcaaTPpnO91uKz5uZMYV//f1Py0GtUUdFST7hmBm1RJp0nHmfZyUjzCf5NEWGxWirrqUFsMZHhGIBVJqNK2cK69klH+iX9Il/lHUa9v5+Ezu3giaQoxrv60GTWsLjjAkrjxrCk61GNUL8rF/78iT6jdqGFh5nqqtC3IRRIeSZzM2qIvnVle+4Y/8JsBw73oRS/+Pv5yW/H/bZhMJpRKJXv37uWmm25yHl+2bBlnz57lp59++tV9jEYjRuPPFbSuri5CQ0N7CdP/Y1wpdB3gHc3TyVPoMOtYdHo9HlIX3uo3l9z2cqcDHcCb/eYy0CfmHyJLl9Fm1GDH7iQD7d2BilfO7HeZ9bj9zsai06TjjlPrnDoib5krH1217J8aFynTNLLo9AbGB6YyM3IYRquFFWd2EiB35+nkW/CRu1GpaaZU08hgnz4oxTIa9R0caSrk2sDUX/1tvcXI3qpTPYTuTyTdzI+N5znWXOQ8tnPovcS69XSk+j20G7U8V/AxR5svEu3izzsD5rO9O3vKS+rCtqH34C93p9Wg5semC7x04VPAUbG+bHt9e+Rwkj3Cye+o5LOaHFanTef1woOUahqRCEQsiRvPptLDdJn1eEpVfHjVMocexA7nO6sJUHjwdvHX5LSVIUDArWGDOVibg85qIlzpw1sD5jH92JvourOJbg0fzLrib7FhJ90zggUxY3j07AesSJiIv9wdkUCIWCBEJhQjE0l58fynPNz3RtwkcrrMBup0rSjEMjpNemzY2FZ2hFUpt3BP1mYaDB3OayNEwAtp04nr3rTfl7ONySEDGBuQxMHaXLaXH3H+7uI+19Bm1LC/OhM7dqx2G8EKL1al3IrZZuGZgo+5PiiDKWGDKOyoZXfVCe6OHcf9OdtoM2l4IP56BnnHUKVr5YlzH2Hstuq+HAL7SOKNuEmU7Cg/wvyY0djtdg43FJDTXs4TSTfRZdYTKPdkUeYGHul7I8nuYdToW3ni3G7n8zTKL5EpYYO4P2e7kxSP9EvghqAMznfVcKA6k87u7uv08KuYGNIPo8VMp0XHW0VfsTB6NJmtpVwdkEidroME92A0FgN+cjdeu3CQKWGD8JO7IwDuz91Oa7cTn1Qo5q3+80jxCEX8O+5gLYYu3i/5jnlRo3CXKGgxashqLSXVM5xwpQ9l2ibcJIrfHSv7JRr1HVjtdo42F/Ja91hmknsIpd2E10/uzhNJN/Ns/j7WD1rEjONvobeaiHUNZEnsOFbm/w975x0fZZm27WN6Te8J6Y2QEEJC6M2CioKACggICIiAvSs2FHsviFIEUZCOCNixIp1AeiG99zaT6fX7Y8Issey67r7vu+6X4/fjD57MPJlMeeY+7+u6znMvnRYd0apA3hp2M0a7mbnH1pDqFcHdSVejEstYenI9WquRt4ctQiWWccup9e65pcFeEbyacRM+0t/fbHE4HW4xpbUYUIikSHor1zqrCaFAiPIiQWhz2HE4HUgvqh6Z7Bbkf7B69M9wcY4cuK6vcqGErK5KHji31X272xOuZGbEyL8rhP8q1Bs6uO30pj7XALVYzvrhS4n9HeHbTz/9/GP+60wf2tvbsdvtBAUF9TkeFBREc3Pzb97nhRde6GN5Hh4e/r/xUPv5D8bqtNNs6sbmtHOivZR7z25l2akNaKxGui169HYze2tO9rnP6yWf02bS/s4Z/xi+MnWfyomPTP2rAeffE0tai4H9dafdYglcO8AfVv74p9oELxCjDmLr6DtYEncpwQofItUBrBm2yC2WACLVAYwJSHQvOIIU3kwbkPmbQk1jNfJ5Q3afY180ZnNNWHofm9oLDmh/BB+ZipXJM5gdMZo3MhbiK1Nzc8xEbo27jPXDlxIk98Jit9Jh0fFFr/XxSL94Phl/v7s972jreeI9gvGVevBmxkK2VPzInYlXuQ0v3ij53C2W3su8BalQgkQowkuqZKhvFLW6Np5IuY6HB03DiZPdtSfc4ujRlBl811zAc2lzUIqktJq1rC39prfVLoxHkqdjcdiwOey8U/o1dqedJ/N280TebvR2Cw9kb8VDLMdPpsbmdCAAAuRefN9cgEQk5NvmfJ5OvYHsrmpeS5/f57mZFz2WNJ8o9tWdQiaU8Eb6Aow2M5W6Vnee0QVq9G0M9Yli/YilrB++FJlQTKOxq/c9b+G5IXO4NmwYNfp2LE4bMyNGYbHbeD1jAQ8lXUuMOgiRUMT+utOYHTbCFL5sHX07U8LSAfik7jQJniEsi5/EE7m7eCx3J1MGZLA6dRbPFuzn8dxdlGgbmBg0iN01xzHYzbxf/j2rU2ehEEl7WzFHucVShNKPRI9Qbk+4ilX5e9hS+RMhCl8+GLkCP5kHO2qO8VjOTrykSt4s+YJKXQtP5e9hadxlvFB4gI+qfkIAxKoD2V11ghujRpPTVUO9oYO7z26hw9xDqncEA5S+WBw27sr6gCJNA42GLreoaDNpKdM20WnW8WLRAQ7UZ3H7mc10WgxsrTrCy8UHWXZ6I81mDXef3cKKM+/TcJFt/+9hsVuRCMX4ydRcHTqUewdeA0CBpt4dCPz2sJsp7K6jzdzDe6Xf8OwQV1tmaU8Td53d4rbavjPxKk61ldFm0rIi/gp8ZWoaDV1sqviBuwZOZlLwYFdLYPa2PiYP+ZpaXio86BaNv8WFBXi3Rc9HVUc439OIzWF3ZT21FHCi/TyGi1rBxEJRH7EE/I+IJXC1kl0sENRiOUXaeh7J3t7ndmtLv+6daTL98hR/OQYo/ViVekOfY7cnXEm0OrBfLPXTz/8Cf7lP2S/tPZ1O5+9afq5cuRKNRuP+V1dX95u36+f/H1RiGRMDB/FkyvUAFGvr0VhdQZbvDb+FVwoPUqitRymScnvCFUgEImr0bdxzdstvDjv/s7SZtHRedJ5Os+7vijG7w86pjnLeLfsGcAVfzoxwOaltqz76uzNMF9BajVTrWt2GCEa7hSpdqzvnKFjh3aeVI1jh/SurYVnvIkhvNdFp1rnnoyx2G90WPVaHnTaTlruztlClb0UsEHFlyBAAznVWsaf2JE8Nnuk+3z9r0Osv92B5wiR3W423VMWcyDFEql35PlKRBB+piuXxk1gQPZ47Eq/iXEcllwQlsyhmIq+m30R2ZyVNxi5uO7OJ2VGj+aG5kPt6F6oXWBx7Cc3GbppNXSw8vpbjbec52naeFJ9IHs7+mE5zD0tiL3Xf/qrQNDQWg8uEQhXIzF843j2WMoNXig6xvuwwzwyZTZJHKKEKHzQWA3WGDrI6K7kj4Upuib+MKl0rz+Tv41j7eXbXnmB7zTGeLdjPrMhRHG7KI1juzXMF+/ucf0/tSQo19YwKSOD9sm9RimUkeoXyaf0ZjvVW9AZ5DQDgy8YcjradJ0juxUDPMN4etojVqbMo62nmx5ZCpEIxlfpWPqo8wp6ak/hIVbxSdJAqXSthSl+KtQ3U6tq5K3EyU0LTeWjQtdydtYUbI0ezIHo8j6Vch7dYQbDcmwCZBxaHjXuytvBQ9jZaTRoUIilBCm8ETlg1eCaf1p2hWNtAt0VPpl8sLSYtcqEEX6mKKFUAbw9bzDNDZrO18ieeSp3FEO9Ibk+4grzuGtYMW8RAz1DuTbqa285sorq3jfSFtLk4nE6mhqbz1OCZnNc2sqXyJ/bUn+T5gv1EqfwJVfhgc9gZ7hfLk4NvYG3mEsKVfgTLvTDbrRRr6znaWkKTsYun8/dwvK2UZkMXN0WPQyYU02DsZObPr3OwwWXqcEVIKkdai+my6FGJ5H0MVH4LS69xxvzj73C6oxxJ72zaxUSoAjDZrDidLte2RbETCZX7sChmYp/bvTh0HlkdFagkcu49+xFmh4UMvxgez93JV4051OrbuS3hSg435blnfjYMv5UHkqYC8FNrEa3/YCPIYLOwv+40H1UdYcXpTZRoG/m+pYBnCz7h0ZydnNc2/N37g+s7utuix3zRHFOHueff6j6nt5l4tfgzt+PbZxMfZoRfPABvnf8Ci/33r5F/FWr0bTyes7PPsbfOf0FpT9PfndHqp59+/j38ZQSTv78/IpHoV9Wk1tbWX1WdLiCTyfD09Ozzr59+lGIZKd7hfVrsQhW+eEmUXDtgGCqRq79/TuRY1mQuRiYUc0fCVSj+xbaOVpOGR3I+Zs35L+k06+g061hz/iseyfmY1l9Y+F5AJBQx1CeKkf7xTAlL567EySyNu4w5kWNI9Y5gfOAgJL/TRqS1GjhQf4ZZR9/kaGsJequJrI4K5hx9i+3VR/uEw/4j9FYTP7QUMufYW1TpWrE6bBRo6pjx06sUauoQC4WMCxyIWCDirWE3MytilFuQjAlIdLu+AYwLHEiToYtqXRvNxm7sv/Nlb3c60FgM2Bw2t11xl0WH3mZGJenr3Bcg9yTWIxiZUMLKnI/xkXmwKm8PZoeNB7M/5mR7ObtrT2CyWynTNjEjYjhP5O3qc463S74EgYBvm/JpNWt5NHcnHWYdj+Zs53xPE5srf2R0QILbEn1r1c9obUZECMnX1LH1ohY4gPvOfsSCmHEY7VYkQhGZ/nHkdNWydcwd3BJzKVeGDKFG386dWZsx2q0UaOr4oiGbMQGJ7uH9W09tIFzlz5bKHynS1iNEwK1xlxMs98Zkt/Jo7g48JQpuT7yKfbUniVUHuat5K+Kv4JbYS1kYPR4AoUBAh1lHu0lLkMyLSJU/IQofIlUBWBw2Os09XBU6hOsjhiMWCrlj4FXkdFZhddrZU3MCb5mSdrOO6yJG8Ez+XvzlnnRbDFwXPpwgmQcP5Gzj0dwdPDBoKiEKb6xOO1qrEYlAxDNDZrOp/HtGBMTzXtlhJgYnszJ5Bo3GLiwOG60mDY/m7uClofN4PWMhoUofQhU+zI+ZgJ9UzeK4S3gkezsJHqF82ZDN82lzeL7gU3d70vzo8ZRoGxEKBcyNHkuEyp8R/vH81FoEuDKynivczzMF+3hp6DzmRI5BKBAgFUh4K+NmXs9YiEQopsuip8Wk4em8PdydeDVeUiWtZi17a07yRsZCALcz5eXBg4lRB/H2+S+JUQXyRsZCghR/P7y93dzD2tJvaDNr2VT+A8XaRm4/8z6AW2xldVawpfJHrgpL45qw9N7qnvBXuWVvlXzBzMhR5HS5XqON5d/zctFBHDgZ5DWAwd4RGO1WrglL5/rwEbwzbDExqkBG+cdzW/wVvDL0JmIuGu63Ouy0mjToLnK01Fr1XBkyhFCFD2aHlcUn3+PZgk8AGO2fQLjK/+/+vU6nkyp9K7OPvsnZzkrMditNxi6Wnd7IZ/Vn/22iyUem5o2MBUwMHMSbw24mUO7FqsHXc2XIENYPX/qn5jz/LBqLoc+mmNFm6fP/P0OXRc99Zz+iw6JDLZbzevoC9zXg9jOb0P0XVND66ec/nb+MYJJKpWRkZHD48OE+xw8fPszo0aP/jx5VP381LnyBL+3t578gmoq19Txb8AnD/GLZO/5+4jyDkYrEpHiFc3DCQwzzi/2Vs9M/g81h51xnFfnddXzemM0bJZ/zVskXfN54jvzuOrI6Kn93l9Bf7smTKTdwR8JV+MrUeEtVLIqdyItpc93WvBdjdzp67WcdHG8tJVDuhadUyYay73jw3DYcODndUd7H2KLvY7X9KnvK5LDy1vkv6LLoWXZqI/vrznDnmc3o7WZeKTqI2W4jTh3MuuG3sLXyJ3bXniDVO5IPR91Og6GT/b2LvRkDMmk0dDH72JvMOvoGc4+9zdaqn3+1oLA7HZzXNnLDz69TpGnA5rBTp+9g/vG1HGstcQcsXrAr7rEa+b6lgJyuauoMnXzdmMObGQvZX3eaSl0L3zTncUlQMp+Mv5+pYRk8kbvL3Yb3/ohl7va8x3J2cH3ECFK9InDi5L2ybzjf04RIIOSxlBnsrz3Nc2k3MtQnGidO1pUe5orQVJ7K24MDJwM9w3h+yN/a89aXfcsbGQsJV/jRYOjkqfw9rDn/FdPCM9HbzLxT+jXt5h5eLT7ImmGL0NtcrWovD53HJUHJhCl8+KjqCItjL0EtlvNoygw6zD08mjKdYLk3N0aORoCAz+vPUWfoQGMxMCdyDC+kzaHNrOW+cx9x7YBhvDx0HsleA1CL5RgdVs52VbGr5gRP5e/BaLdgddjptOh5Mm833zbn027q4fHcndwYNQYviYJ3MhdTrW/j3rNb0FgMrM28hWVxl/NQ9jaOtZ1HZ7dQqm1GbzPjLVFhvei97MCJ1WFDIZbyctFBrgsfjtApIM4jiOF+cTw8aBozwofTadZhczjwkijoMuswO6yc6ShnZc527s7agt5uZkP5d0wPz+Tesx/1meXYWXOM0QEJiAVC7A47vjI1wQpv1gxbzAtD5hDU2/5ao2+n3dxDh7mHJ3N3c76ngZeLDtJt0bO9+igvFx2koLuOOxMnc6jhLM8X7ufj6qMsjJnAjy1Ffd6jRZp6l0mJVI1cLHVnh/09FCIZS2IvJdEzlAlBg/iiMdvV3in3YvuYu7gt/grA5QDYZtKQ1VFJh7mH5affJ0DuyQtpc7kj4SpEAiFdFj31hg4WxVxCvMffZgJVYhmPp1zHqrw9iAQCFp94Dz+ZBx9W/EiNsZ1bTq2n2dTNTy1F7vkxq8NOfnctM356lcPNeRhsZqp0rcw/vpaPq4/yXuYtfa5/8R7BPDH4evz/QbCpxmrgzeLP6bLouf/cVr5ozObOrA+o1beztvRrd+X730GIwofHU65zV6L95Z48kDSVqP9FxzeNxeV0+kndKZfFvM3C6Y5yd6X1z+IpUfD8kDkEyr1YP3wpowMSeHf4EsIUvryYNhfl/1DrYz/99PM3/jKmD+CyFZ8/fz7r1q1j1KhRbNiwgY0bN1JYWEhkZOQ/vH+/S14/OquRHdXH2FjxPV4SJe+PWEZ+dy2rC/YhEYjYPGoFiRcFzP470VhcFZ+LTRHAZd17XfhwPP8NeR8dJpdd8KvFh3g85Xq8JUr3/29PuJJdNce5Nf5ygmRe7ta7LosOlUiOVCTG5rBRpGng1eLPeHnoPIIV3tTo2njr/Jcsj7+c285s6rMrHKkK4PX0+dx2ZhMtJg1Bci934KW/zIM30hfybOEneEmUzI0ag8luZWXODrdZwAUWRI/nlrjL3IuyLoueO85soqynGalQzMrk6bxX+g2tZi0qkYx94+/HZLfQbu4hVh3ET61FyEVSrA47dqcdT4mSUIUP75R+xdG281wSlMyYgETeOf81L6fPQyQQ8kz+Pu5PmoKHxBVY+ljuTlbEX8GBujPcGn85846vcT++q0OHMso/gUTPEHqsJnpsRvbUnuSmqHE0G7uQi2VsrTzCc2k38lzBfm6MGs2a81+xMnkaJpuNt89/SaXeNVc0Y8BwlsdfztG2EpK8BvBYzk6uCRuKUCBkQuAgqnStOHDQYdYRovDm9eLPCFX48mTqDdTq2lh+5n0CZJ68OHQuZruVU+3lTAsfRrOhm06rjqfy9jLYO5zsrmoA1yIr8xacuGZK7j/3EdeEpZPfXcvXTbkAxHuEUNbTBMBlQSmMDkjkXGclMR5BrC/7lg9H3sax9vP4yTz4rrmAFO9w9FYzcrEEo82M1mrk+ogRCBDwQO/iUC6SoBbLaTf3IBWKeSFtDh5iBa8UH+TR5Bl805THvOhxHKo/Q5pPNN5SJXKhhHxNHdmdVVwTls7SUxvctuCVulZeSb+J9WWHKdE2IhaIuC/pGqp1beyuPYFKJGPH2Ls511lJhm8MQoGAIk0DpzvKmRKWwevFnzF9QCZH2or5oaWQGeHDCZR5sr78W26NuxyDzex2FwyWe7sF2dSwDCYFp3LX2Q8AGOkXR3ZXNWaHjVCFDyuTp/NI9nbiPIJ5Pm3Ob25iXIzWYqTV3M28Y+/w0KBrqdG3MSk4lQZDJwmeIZztqiJC6ce7pd+wKHYiqd6RZHVUoBTL2FF9jCcH30CjsROzw8am8u95OHka9/1CQN4adxlSoYQqXQuTQ4dyz9kP+8QHeIjlbBhxKzG9gbBdFj0vFR7g+xZXgOvsyFF81ZiLxmrAS6Jkw4hbueXkOnp6KxkyoYT3ht/CQM/QPhEAv0WrScOD57ZRfFH7nkQg4p3MxaR4RyD5B/f/T6fVpKHDrCPeI4gSbSPV+jY8xArazFo8xQqezNuNAyfXh4/gjsSrLqqW6/EQy9xGI51mHXKR5HcNKuxOBz29xkAXZpZcraDSX82O9dNPP3+c/zrTB4DZs2fz5ptvsnr1atLS0jhy5AhffPHFHxJL/fQDoJYomBk5iqWxl7JhxK1EqgO4JCiZVYNv4J3Mxe6Qxv8JvKRKpg3IJOQii9sguRcz/k1iqcXYjd5u5v5zH1GibeTR3B3UGTt4Im83ZT3NfFR5hNsTrmRV3h40VgNOp5MmYxd3nvmA/O5aLHYbOpuZu7O2UKJt4J6sLRR017Ls9EaOtpXwfXNBnxkecM3pfNuc7xZJLSYN/jIPBAhoN/eQr6nl3cxbeGnoPCJU/jySs/1XYglgZ81xWk0aLuzf+EhVvDJ0vnso/+n8vbSatShFUt4bfgsWh5Xbz2xmxen3KdE2ku4bw86a4zyRtwubw0GUOpDPGs653fluibuUd0u/oduq54FzW2kydLEyeQYvFx3k0ZwdmO02Xk2fz/fNBUwLz+zjkgiuGSAB0GMxcduZ93k4+2NmRozEQywjSOFDnDqIF4fO5eWig5ztrOT98u94NHk6q/L2cKghi3nRYxAi4PoBI7g17jIkQhFmh40VpzfyVOoNLjez819y/7mPCFf50WTs5qWiAzyVt5dHkqfTZdFRpWtx27Y7cOJwOinRNnJpcApbyn5ggMqPVXl7sDntOJ1OXkib627tW12wD6lQzOHmXFYkTOLjqp9J84liUnAqgFssTQhMYnr4cJQiKRm+MYzxT+T68OHUGTtI8Qqny6LnaFsJ68oOIxGK0FlNbKs+ysGGs5T3NKMUyzDZLShEUtYOW8LzaXMIV/phc9ixOex825zPc0NuZEvlT4wKiOeurA8Y6hvDC4X7yeuu5VxXNU/m7WZ//Rnyu+uYGpbO2ICBrEi4gqdSZ3K8pYR7B16Dh1jOC2lzSPAIIVodyLK4y7ln4NXobCYajF3kd9dhsls51HCWPbUnefDcVp5Pm0OUOoAfevN6Pq07g6dEyVUhaWwo/xa1RM6sSNcc2gXxMSk41TWrZtUjQMDsyNHcEncZq1NnIxOKiVIF4CtVY3bYqDN0YLJb6Lbo3TlGv8TpdNJt1fNk7h6cOHm56CBykYTH83ahlMgIlntzdUgacR4h3J80hZF+8fjK1Azzi+XJvN2c6axgZc52vKUqni/YT253DStzdrA6dRaDPAdweW9A7oby75CJxCyPn8RQ3yjuHji5z+N4JX2+Wyxd+Lw9OGgq4wKSANhVc8Itlt7MWMhD2R/TYzOR5hNFiMIbs8Pqzqj7RwTKvXgu7cY+x66PGEGSV9h/hVh64OxWlp5aT6GmgWC5Dz+3lPBg9jZsDgfH2s/jwMlg73AWxU50i6U6fQe3nFxHYW/1vNWk4YFzW/m5teR3q24igRDvX5hd+EhV/WKpn37+l/hLVZj+VforTP1cQGc1or7IlU5vMyMViv9Hv8A7zTreKf2Kz3rd3C5wTehQ7kyc/C+FJJrtVl4v/oxaQwc3RIygRtfO2a5KznS4ZoeuDx/BTdHjuPfsh1Tr2/CSKHh56E28VHiASn0rCpGUAxMeRCmSkddd4w59vMC4gIHcGDWae7I+7NPK5y1R8cyQ2bxSdIBaQwfJngNYlToTrdXArac2cnnIYFbETUIkFNJk6GLZmY2/euyZvrEUaxt4cvD1yEVShnhHuvNrCrvrWHTyb7lrdyVOZnbkaNrNWu7K2uLOjQpR+lCrb0eAgMdSZpDhE80NP7+BHQdTwzKYHJqG1WFnVd4euq1/azcMlHvxRMp1BMg8eCB7GwuiJ3C0rYQjrcWIBELuGXg13zTmUa5rxmS3snnkclbm7EAllvFU6kzMdiunO8q5ImQI5zqqGKDypVbfToJnCNmd1awp/QohAtaNWMo7JV9xb9I1HGo4y4Lo8aw4vYkmU5dLpAzI5MHsj7E57XiI5e6d/EzfWB4YNBWjzcyjuTtpNHYRpvDlhbQ5PJKznYlBgwiSezMhMIn99WeIVgVysD6LBwddy+vFnzE/ZjxvlXzBs0NuxOawUaZrZmf1ce4eeDUn2koRCgR97MfvSpxMmMKnt43Jid3h+npYcGIt8R7BPDV4JmtKv+JoW0mf1/DKkCFMCUvHYrMhFAmRCyWoRFJ8ZGosDht1hk6+aszmq6ZcYlSBPDDoWp7I3UmHRUe40o8nB9/A0lPr3ecb5hvDXYmTaTJ2Y7CbebbgEzJ8Y1iZPJ23z3/JivgrMNjNrMzZTpOxmzsSrmJi0CCeyd9HbncNk4JTSfOJ5JXiQwDcO/AapoSls6P6GJsrfiBM6Utdb9DqjjF3ceupjdydeBUVuhbCVf50mnWsL/+WScGpTBswDJlIjEwooVzXTKOhiwilH1HqQKRCCXtqj5PpF0e0OhC5SMqK0xu5O/HqPplMF2gydvFC4aecbC9DJBDyQNJU9tedprS37XPfuPsIVfpitluRiSS0mjRIhWJEAiE5XdXultoLyEUSXkyby/fNBdwafzkSoYg157/iTEcF7w2/hQFKP6p1rSw7vbFPm22MKpA3h938q3yi8p5m5h572/3/2ZGjuDFyDDcdX0OadxSPD77OPTcjE0p46zfO8UuajF3uNrwLCBHwWvoChvnFuE1l/oo0Gbu448xm6gwdSIViYtVB7kraLbGXorUZ2Vd7ii8uWekOdO626FmZs4OznZVIhWJeTJvLporvKdTUIxII+XTCg+4W0n766ed/nv+6HKZ/B/2CqZ//K2wOO583ZvNc78D08rhJAKwrd83kPZo8gylh6b/Z3tJt0WOyWxEKBPhJ1Yh+4zZNxi5m/vwGFoeNl9Pmca6rihTvCA7WZxGm9CXRIwShQEiSZyh3Zm3pIxrEAhFrhi1isHcEUpEYq8PGJ3Wn3fkwIoGQQxMf5vojr2G0W4hQ+bMyeToPZ3+M1mokUhXAyuTprCn5kscGX8e7pd/gJVFyQ8QI5CIpnzWcpaC7lqdSZ7Hw+Fq0tr+19F0ZMoSxAQNRiWUIBQI2V/zAnYmT8ZOpcTphxemNtJr/5uQlFYpZm7mEZK8wGo3d3Hf2Q2ovslt/MGkqhZp6VGI5U8LSOVB/hlH+CXxQ+SMPJk2lWNPAy8UH3bd/OnUmXzXkcn/SNbxYdIAGYxevDr2Jh7I/5vaEK/ihpYilsZciFArJ7qyiSt9GYXcdz6XdyHlNI/dnb+XuxMmMC0yiWtfKwznbmRKaznXhw/GQKPiiMZsguRddZh0Tg1NYnb+XAk0dyZ4DeC5tDjefeJduq57hfnFMHeCarbpAqncEc6PGcrztPDdGjqbe0MnTBXvZPHIFXzRk82GVK3tuduQoijUN5HXXcklQMiviJ3G09Tx+MjV+MjUCBKzK30uHuYcrQlJZED2eY23nsThsvF/xPeBq0Ur0DOW68BF0mHuIUPmzt/YEt8ZP4nBTHoO8wlCIpDyeu4u1mUv65BiFK/14J3Mxx9rO80rRIe5NnEy40p/7srcy0DOU54fciEgooqyniYezt/cR4mqxnLWZi9lQ9i3H2ksB8JOq+XjMXbxb+jW1hg7yu2vdltgj/OK4KXocO6qP8eCga1lXepivm11thV4SBRqrEQECHh50LWc7qzjcnMeimEu4dkAGYUpfPqz4EW+pijClH1sqfuDSkMFkdVQQow7CaDMTqQ5wuQnKPPGVeWC0m1123tom7kqcTKtZw1vFXxDrGczM8JG8WHSA0p4mJgQMYlr4MF4uOkizqRulSMon4x/41SZIh7mHGn07T+Xt4ZHkaQzyGkCtvp2Xiw4ydUAGk0OGoLWaONFeypiARO7J+pBHB88gp7Oaa8KGcqj+nPuaAbBm2CLi1cHYcLhjClzzXzaCFd50mnXMOfYWXRY9nhIFi2Imsrb0G2xOOwkeIazJXOTOYrqQy6ax9jWDWZk8nUzfWORiqXtmqcHQiUgg/Idiqdui59GcHWR1ViIRiHg27Ua2VPzoDl3+dPwDBP3FQ2UbjV3ccWYT9RdZyi+OvQSz3crH1UcBmByaxt2JV7vfD42GLu7I6nsfIQJeTr+JTL9YFP/mmaRfugn/PXfhfvr5/43/ypa8fvr5qyIWihgXMJCrQoZwW/wV3BAxgusjRnBHwpVcGTyE8YFJvxJLRpuFnK5q7jn7IQ9mb2PO0bd4v+KH37QhtzsdWBw2FkZPoMbQzs6a4zyVt4epAzIYoPDlxaIDPF+4nw6LjtfTF/S57x0JV5LqE+m2C28ydhOlCiC2tz1RLBBSr+/glaE3EasOYs2wRaT7RLN++FLClX48NfgGXij8lGnhmZT1NHG0rYTPG8+xu+YE++tO83H1UXK7a/mhpZCFMRPcv/eyoBTSfKJ4Mm8375Z+g7/Mk3lR47jjzGbaTFoezN7mbsNbNfgGd3venVmb6bGZkQhFePwiu8pLqqLHauSa0DRwOhnuF8eD2dtwOp30WE2sKf2qz+1fL/6M2VGjeDpvL48Mms4TKdexsfw7Vg+ZhQAB86PHUdLTyLxjb/fOpjiZGzWW64+8jsZqYFrYMN46/yVvlXzBwznbsTsdOHC1Xx5vP0+cRxDne5qw4uD+cx8xJ2oMXhIlc6LH0GMxsCZzEREqf4LkXnT+IhPnQkvUJUEprMrfy+GmPD4YeRsbSg8TrPDmmt6cqV01J8jrrkWAgOF+cXzekE2E2p8zHRWEKFwiod2sxYmThTETONRwlmh1IKc6ygFXYOxHo+5gadzlrMrbzWsln1Fn6GBu9DjuPPMBH1UdoVDTgMFm4caoMXzdlNsnv6fO0MGPLUWEKXxx4kQulmFyWhEAxdoG7jq7hVlH3+BIazHL4i/v8zc+lTqTRkOXWywBdFh0fNecz7yoceR0VWN3OpAKxcR7hHCqo5yn8vdya/zlhCp8uDfpGi4JSu59vlxCfGXyNOoMHYwPSkIpknKyvZQGQydNxm6uCk3jeHspd2d9wLL4SXRb9HzbnE+owhtPiQKT3cqPLYXsqj1Bt0WPxWFnU8UP/NxWws9tJUQo/ZGIxHzZmMNDOR9zR+KVhCi8+amtiPvOueaI5CIJazOX4ClRYHc66DTr3C16fjIPIlX+bB65nGG+MXhLVYQr/Xkl/SauChmCzm7hnrNbeKX4EJ/Wn+HZtNmsKzvMntqTNBi6+LT+TJ/nb13Z4T5iCVyOcReEjFQo5rb4K/CUKFg/fCmzIkexZtgi5CIJ9wy8GpXI5TbZbdHzcuHB3vecgo9H3+luz3u16BBSkbiPwUOY0vcfiiVwRQCsTJ7umifMXMzYgIG8kn4TSZ5hPJ5yHepfuF3+FZELJUQo+7oFxnuEYLRbWNDrUPllYw5bq46g73UgDFX68FbGzX3uMytyFMP/B8RSvaGDcl2L2yCn1aQhr7u2j817P/3084/pF0z99PO/hK9MzT0Dr3HPLF2Yabon6Zo+O9HdFj0F3bXU6ttZdmojseogbou/gmXxk9hU8T1P5O76laucQiQjShXA5SGDSfIMI1oViM1p54ncXW6RMMIvjgiVPy8U9s3z+aDyB6p1rXSZdXSZ9TQZu1lb+jVPpFzHs6k3sjp1NhvKvwVcO9ohCh8EAgEx6iA2jVxOqNKXaHUAzxfux0eiYv6FRUJTDrtrTwAwJSyDq0OHMiYw0R3ga+iddREKBJTrmnkidxdKsZRZkSPZXPEDqwZfz7NDZrNxxDK+a8rnxTTXHNTKQdNdZgdtZVwSlIwAgTv09+m8PcyKHMV3zfl4y1R83DvE/+LQuTyRt9MVDCr34sW0uXhLVGisRl4sPMADyVPZW3sSb6mKYm0Dq/J282rJZ/jK1Lxf/h1mh42Hsj9GIZLxZN4uzA4rmyp+YFHsJQD83FaC3elgatgwrg5L49vmAgZ5DcBHquaqkCF0mnW8NHQe++tO827mEnwkSmRiCW+XfMlTg28g0TOUN0q+AFxGGmKBiJreykOA3JMmYxd5mloMNjM3Ro9lfdm3LIiZ0CcQeIhPJL5SNdeEpfNU7m6SvcP5uPpnbkm4nASPEB5NnsHp9nIyfGP4saWQlcnTuSX2Uu5KnEyHpQd/mQfD/eMAeLX4EHec2Uy3VY+XRMFIvziSvcLxkijdu+ZXhgxhfMBAAN4o+Zwem4l3Mhcz0DOUKGWge26lztBBuNKPScGp7Kw+1ue99+75r5GLpXhKFAz1iWJsQCIArxQfolBTxwtD5iIVink6dRYr4icx0j+eAQpfAmSeCAQCLA4b7b8Qms1GDZOCUzlYn8UzQ2bTYzMiEgh5Km8PjcYuijT1WJ12TnWUMcw3hiHekVT1tDIpJJUkzzBmhGcCsKPmGNt7/9ZJwamMD0ziidzdFGrquWfg1cyMGMV7pYd5aNC0Pr9/fvR4PCQKnECptpHrjrzK8fbzGHoXy34yD/zlnm6HTh+ZyvWZQkCZtomk3uysLZU/cfuZTeR21fDi0Lk8mbfbLchuih6HEAGFmnpW5mz/XdtqtUTOZcGD2T32HmLUQUiEYgZ7R3BgwkOkev9tk8RbquKp1JkM9Ylm/YhbifcM4dGU6VwalMKazMV4S1S/ef4/QrjKny2jbnMbPATKvXgjYyETgwahEv+1BVOHuYfXig9xvFfwy4Su9sJVebu5MmQI86PHc0fClQTJvbg+YoQ7DqHVpOHJvN19zvVJ3WnOa5uw/Z1cvX+WekMHy0+/z62n1lPR00KbScsj2dtZfnqjy7ikXzT1088fpr8lr59+/oPotujZWvUzW6uO9H7RetNp0fFGyedcEzqUgV5hvFb8GZtHriDFO7zPfU+1l3G4KY+BXmEkew7gleJDFGhcYc1x6iDWDFvMvec+okTbgFggYknsJeysOe7eVd44YjkqsZRHcraT312Hh1jOmxk3s7b0a851VSEWiDgw4cHfdAHrMutoMnWT1VHJ5NA07jizmSp9K+Cac9o97h53QG6zsZtCTT01+jaSvcIx2S08nbeX1UNmsa7sMOMCk7gmNI1KXRtfNWYjFAiZFz2OndVHWRx3KTmd1aT7RrO39hQGu5lrQtMRCAQ8W/AJNfo2FkZP4JqwdFqNGoIUXmR1VuIlluMlU/FC4ac8P2QOepsZsVDEqrzd3Jc0hVJNI+ODknip8AC3xF2GEydvlnzBrIhRDPOL4f5zW6m7qPUvVOHD6+kLqDN08GD2NsDVmvZ06kyWn34fi8PG7QlXMj4wiWWnNtJt1XNd+AgCZB581ZTLq+k38WjODsp6mrkxYjQxHkE8X7ifdN9olsZdhs1h596zHxGq8Oa1jAVUaFtQSqS8VvwZb6XfjNlp44XC/eR01fR5HeZGjSHFO4JIZQAHGs6wu+YEKrGMl4feRLGmnndKv0YkEPL+iGWEKHww2MxsLP+OH1uLWJu5GD+ZB4/n7CS/930jRMA7mUvYWnmEG6NG4y1V8WzBPgZ6hnFr3GVYnXbWnP+KLouO1amzAajTt5PiFU6lroUlp9aT5BnGS+nzWHh8rTtHZmHMBNaXfYvNaSdOHczKlOn4SFQu6/HCg5Trmnlo0LUEyDyRiSS8XvwZx9tLeTV9PokeIXhLlTQZNTyVv5v87joECIhSBbjfc0tiLsHosJDTWcN9SdewKm8PDcZOBih9eWrwTLI6KwmSeXG4OY/bEq7EQyznmybXrNqy+Mu5K+sDd7uUv8yDD0fdTouxm4dztrMwZgIVPS1EqfwZ6hvNwzkf02Tsdr8GcpGEtcOWoJLI2FV9nP31Z7gqJI3FsRPdAb5Gm4Xsriqi1YGEKHzc920ydpHXVcP3LYVucwqAtzJuJr+7lm3VP/Ne5i3EqoM43VnBw9kf80LaHEb6xSMX/+uViW6Lvk+QtcuFTeYWVv/tWOzWPiYKF6Iefs8JsF7fwcITa+mxmbhv4DVcGpzCitPvU2fo4Prw4SyLn4QAATan3b1R1N1r33+yvQwhAu5LmsLOmmPUGzqRCsXsHXffH6re/RFq9e0sO73RHVzsJ/OgVt+OEAGvpN/EsP+BilY//fzV6J9h+g36BVM//ynobWasDpt7cWJz2OixmXE4HbxY+Ck/tRYDkOkX6zZuSPeNZmbEKFbmbOf2hCv7tLddOGeRpo4eq4lwpR8tJg0fVR0hv7uWx5KvI0TpjYdYzq2nNrAyZQbnOqu4JnQoD5zbxvzocQgFAmr07UwJS+eh7I/ptPxt11qAgGeGzGK4Xxx2pwOFSIbyFws0o81Cp0XHvtqTfFx9jDlRY/i84Swaq5FrwtJZHjfJHexZ3tPEypydBMo8mRU5ityuagQCAVurXBWhW+Mup0hT7zYXeC19Ph9XH+VcZxUr4q/AaDezpdI1w/N06kyyOiq5Jiyd3K4a6PXhU4mkDPWJYWfNUb5qyuOSoEEsirkElVjOhrLDTAweRJxHCC3GbvxkHrx1/ktmRoxkdcE+bA4bzw+Zg83p4ERbKdEegbxQ+Kn7b3168Cxi1AHcfPI97E4HAgQIBS7DiZ9bSvih1bXYFSLAgRNPiYK3hi3iubx9lPfai4NrPuzV9PmkeA0gv9slUkIUrtepTNdCiNybx3J3ckvspVToWhgfmITBZub7lkJ2155AgIB7Bk6mSNPgtgh/ZehN6K1m4r2CuTtry68qMJcFpXBn4lWEKn2p6GmmzaxlZc4OwhS+3Jc0hYezP+4zx3JP4jV0W/UcbS3mnt4wYq3VwDC/WJQiGVqrEbPDilggRC6SIhOIaDJraDJ20WzoJkjhxcn2MsJVfqwr+5Z3M5fwY0shSV4DeCJvFy+lzSPWIwh/mQdCgZAGQyfNxm4ezd2BzWHn2gHDmBKWwaaK75kYOIgxAYl0Ww1orQaeL/yUUm0TDw26lliPIPbUnORwcx5LYi/B7nS43yMAst5K1c6a4zyWPIMQpQ92hwO5SEKP1USNvo3THeXYnQ73bNcFFsZMIEzuw0CvMCp0LTydv5e1mUt4vfgzKnQtyEUS7hs4hQ8qf2C0fyLBCm/Wln7NfQOnIBOJCVH4cN/Zj7g+fDjzo8dTqKnnkZztDFD68k7m4j6iqdHQxdP5e9y28ACzI0cz3C+WAJknWZ2VTAlLRyaSoLOa8BDL/y1i6Zd0mnU0GruIUQeiFMvosRqp0rUSqQrA69/g6vmfhsFm4UxHOVHqACJVAdgcdreBQ5Jn2G+KJqfTSYWuhbyuGiaFpOIhUdBo7OJgXRazIkf9ppHPhfusOP0+Twy+nuF+cXSaddyRtYnpAzKZPmA4nlLFr+73Z3F1Kmyg46Lr+atD55Pp3y+W+ukH+meY+unnPxa9zcyx1hK2Vv3cGzDryj56sfBTnMAjydMZH+iaH+grlkayqreN47daZFRiGYO9I4hQ+rO6YB8rc7YzP3ocb2Ys5MfWQm47vYnynha2j7mLz+rPsr/uNGc7K9k+5i5GByQQrPDGQyLn+cJPeT2j75zTvOixpHiFszp/H8tObeDpvD0U9861ALSZtHxQ+QN6m4ndtSd5eNC1SIVi3sy4GS+Jgs8bzvFtcx4Wu6vdJETh62prihzF47m72F59jDh1MBMDBwGwofxbt1haFnc5nhKFu4XpvbJv3AvhKWHpmO02LglKRmc1ohRJ2VD+HQkeIZRom/ig8gfmRo/lxaFzOdlexvwT79Bi6uby0FQeydnBdUdeo87QicFu5vb4KxAJhNgdDjRWIytzd3Co/ixDfaN5vdcA4wLPFX5Ck6mbIT6RJHiEsmfcvYzyj+e5gv1MDktjqE8U4LL/FiDgnWGLcdgdzIsZ1+c8Dw+axmCvcLykKkYHJJDsHY6vVM3K7B1oLAYez91Jslc4j+XuxOF08kntaXxlasYEJJLmE8ljKTPothhYFHsJU8MyWBg9gTpDB75yNfX6Tt7NvMX9vAFMDhnCotiJiAUiyrRNPJqzk2pdO6+lz+euxMluseQlUTDYKwIfqYpodQATgwYxISgZX6kKh9NBqNIXuVCCRCiiy6pn4Ym1vF78GTX6NlotPdx39iPeKz1MolcoXhIlBxvOEqrw5aNRt2N12DjUcI6D9VnsH/8AGb7RBMq9EAqE6KwmwpS+7nmZEf7xhKv8uen4GiYGDmKkfwJV+jbmHHuLb5vzeTR5Os8MmU12VxXLT21klH88L6bNZWbEKAJkfb/4HkmezoH6LPK6alhx+n3qDR0oxNLe1j4roQofwpS+brF0ZcgQrg3LAODDyp+w40QmlDDcN44pYem8VfIFtydciZ/Mg2dSZ9Nl1rFm2GJGByRwqr0MgNdLPiO3q4b7zn6EzWnnTGcFDcZOHu3NIvORqhAL/rYQbzJ28UzBXrdYuhBzsKvmOLldNRxvL+Xt819SpGlALpQQIPf802JJYzHQftE8pMFmpsuix9E7d7Xm/JcsObmO423n6bEaOVCfxS2n1rO/7jQai+HvnPmvwYWAbwCT3cqp9jIeyv6Y5ac2UqNvo1jbwG2nN3Hb6fc5r23it/aWBQIBseogrgpNc89Thip8WBAz/nddTy/cZ8+4e8nsDUQPVfqwccSyf7tYAlCIpH2qhuJeV1GZ8P+PqmE//fy76P/E9POnsDns6GxmVGKZ24q706xDJhS7+7T7+W3q9R08nudyQ3M6nYwPTOLOrM2YHTZ8pCqW985qHOmtMgGkeIW7spIcNkQCIRl+0b95brlI6s7HMTtsPJqzg5iLrG47LD3srztNibYRgPfKDpPiFcHXTbkcbMhiaexlvDx0ntvN7wIH6s5wSWAykUp/jraVUGvo4MfWIl5Im0uqdwSP5uwgt7uGUm0TO8fezYay7/iqKYefWgp5b/hSXi48wEj/ePK7awhXBRAo9yTFM5xvmnMx9y5Wh/hEkukXx+mOcgx2lxAb5DWAy4JT2Fj+PXcnTub2M5vd1Y8YdSC3xF5KraGDDyt+ZHLYUDwlCt7MWMhXjblcFzGcJSfXke4bzUDPMDaOWEazqRsh4CtVk+w1gLzuWp4r/MTl+CX3Ys2wxbyTuZjbz7yPxmpkYewE7jv7EWaHjTCFL08Ovp5nCz6hztDBi4UH2DhiGUKg22pg2oBM4tQhhCp8qdK1uZ87J06Ot5cywi+eHb+Y4fm4+iiRKn9CFD4EK7zxkarQWg1MDEnmmYJ9vJa+gDSfSCYGDeKBc1u5Z+DVdFn0+ErVPDJoOu3mHnylaqp1rdwQMQIviRKD3UKbSUORph6hQICjd6EX7xHMlaFpnOusIs0nig8qfuCegVdzsr2Msb1VG1fbkJM3Mm4mQOZBk7Gb1QV7MdqtrB22GLVYzusln5PfXcfazMVEqwPJ66pBazXyQ2sROpuZBmMnjcYuZEIxXRY93zTl8fHoO/mg8ke+bsrFV6rm+bQ5WOw2mgxd2OReBCm86LLo2VV9nMlhaagkcoLk3lwZMoSPqn7C7nTwRN5u5kSO4ZP6U5jsVr5tzueSoBQ+rT9NVkclAM8WfMLDg6ZhslvY/ovnenfNCZ4bciPlPc2IhSIO1Z91u5k9mbebVpOWNzMWku4TjY9UxRUhqcR5BCMUCCntaWKA0helWEqAwpO7Eidzy8l1rCs7zNsZN7P2/Fc8PWQWrSYNflJ1b4XLSXZXFV80Zrvfr3cmTubB7G3YcZDiFc4LaXPdLa4ai4FmYzeW3jawJ1OuJ1odyL7aU3zWeA4nkKAOYXHMJSR7DfiXXM40FgM7a47zecM53h2+BD+pB8fazvN84X7WDV9KgNT12jtx8ljuLjJ8o8nqrCTeI4RR/gmY7FYu2Ew0GrqQCkXuIOy/Anang1JtIw9nb+fNYQuJUgUQovBGJZbRYdGx6MR7WBw2LL3hxN5S5e8+3wKB4Fdhs78XPnvxfS4WMYC7Ze/fSatJw8qc7VToWhAgQCYSY7JbWXZqA+uHLyXWI6hPrlM//fTz+/R/Uvr5p7E57JT2NHHDz6+R312LzWGnTt/OguPv8ENrIfreDJl+fpsghRdzIscAsK36Z249vQGzw8YApS/zo8dztqOSl4tc1tcXqgMfVR3BS6JytYylzsL/F7vnFoeNVpOrDern1hJeS59PqMIHs8PmFkt3JFxJpm8sLSYNe8fdx+wIV0inSixD1/uaDfWN4tWig2R3VSNAwM0xE/GVqumxmbjn7BZmRAxntL9rMN+JkxcKP8HmtDF1gGsn/nh7KfOOreGrphwALg8ejN1hZ0XCFdx84j1WnNnELSfXUadvx0um5KrQNFYNvoF1mbdgdth4sehTt1gCKNLU81VTLotjJ/JlY26fVrFKXSsn28so1TZx98CraTf1EKLw4eOqn7k6NI3zmkauCE4l1TuSDeXf8kTebvxkHoiEIr5uzOHWuMuJUgUArgVUh0WHxWHD7LDiJXG1HK3K281jKTNI8gzj6dSZCAUCHkmeRpJnGG9kLEAulCAUCDlQfwa5SMpVoUPcZgmeEgVDvF2h2uvKDnOqvYzB3hGIBEJmR4zqNXZo4/nCT2k397gH9z0lSqYNGMbecfeR4RuNUixjmF8s+8bfz1UhQwhT+NJt1bPwxLu8W/o1Rd31PJW3F5lQwtnOKr5uzKFY08i4wIG0mbU8nDyNy4KSeWjQtTyeu4vXSz7naGsJdyRO5qWiA+yoOcYHlT8iQMArafN4ZehNrM7fS25XDTKRhG6LgQ5zD7ef2cSD2dvI6qzE7LBSqWvBYLNwRUiqu1XvTGeFWyy9nrGQj6qO8FVTDnOOvc2hhrNYHDZGByTSZtLQaOrE6rTzZJ7LxOT98u/YVv0zNfp2nszdRYm2gSfydrEwZiIpXuE4cbK95igmu5UQhbfb2v6CWHK9J13mF7ef2UyDsROZUMzMiJEIEVCsbeDx3F34yNS8V3aYmRGj8JAo0FgNFGjqqDW081nDOe4aOJkR/vE8eG4bK3N2kOgZwi2xl/JK0UGsDjs6q5HvmwuoNXRQ2tPEvONrON5Rhs5m5p6zH3Hzyff4ojGHWREj+3xGrw4dyon2UrS9bn5SoZiLl+BeUiU+UhU3x0zg1fT5jA0YiK9MzeTQNJ5Nnc3syFGk+IRzY9SYf6klTmc1YbCb+bj6Z5pN3dx2ehO7ao7zeO4u9DYz68u+RSgU8syQ2aT7ROPE6RZL9wy8muVnNrKt6ggai54GQycrzmzk6fy9tJu0OJyOPnlP4JrZ+U/r/O+xGnk4ezvNpm6WndrIqfZy1pR8yerUWciEEnQ2ExaHjQCZJ2szlxCm9P2/fsh/ii6LnlJts2tmaehNbBt9J34yD3Q2E2c7K90dAv30088/pl8w9fNPo7OZeKHwU7RWI3ee2cznDedYcfp9Ws1aXiv6DLP93+fy89+It1TF4thLGO4b6z4mEghZP/xWlCIZmyp+AFyudp9PfIRxvU5knzecZUHMBMYGDER+0WBys7Gb7VVHmX/8HT6tO4NA4KRS10qYou+XfKw6GJFAwJSwDGxOO0viLuXFIXNpMWkYE5DI+MAkdtUcZ0HMBGRCCfcnTcHhdPBU6g1u9zWDzUxOV5X7nBqrkW6LgcuCUnho0LUAGHsFz4Lo8aglCuafWMuy0xsxO1yOTM2mbh7P3UWXRY+HRMGk4FS8pCq+bsx1V9VuihrnbkvcXPEDjcZuirX1TAwcxI2RoxnmGwPAi0UHiFEH8l1THj4yFQqhhCcG38CR1mJazBouCU6h3dJDVmclZT1NrM7fy97aU5zprMDisPWxaBcLRNicDl4qdIXwChHQYOhyBaUmXIHZbmVD2bcEy725LeEKLHYb53saEQmEpHhF4NebZxMk98JTouD19AU8mjKDiYGDEAtEJHqFUG/o4OnBM7kuYgTPp92IWCDiipBUDjfl0XZR3pSnREmY0tcd6ikXSfCTeVCgqed0RznhSj8SPIJZEncpPXYj60cs5cXCT3mmYB8ioYjRAQlorAaUIik5nVXcHHMJ/jIP3sl0VYk2VHzHnGNv9YobCWMDBvJmyWdYnDaEAiFykYTH83bxXP4+nk+bg1osp8Oic4vvB5Omkttdy7MF+7A7HVwWnNKnxSdGHUSw3JurQ9IA3K/91aFDuSF8BK+VfE6XRU9Bdx3ZXdVM+fEl8rtrWRg9AW+JkrzuWgJlnryXeQsJHiHMjRrT5708bUAmP7eW9HnOLiAVirkufDgyoZjNI1dwefBgnkubg0ggZHn8JCp1LZT1NHFe24DdYSdSFcC64UuRiyRsrvyBrxtzaTNrceCkSFPPS0UHeanwU15Nn0+IwpuszkpeLDoAwNiAgVwePNj1nJzbxgtpc5gelsmkkFSe+IUL2julXzNA4cfsSNdGxbmuKrfQuECUOpBkr3AyfWPx7nXPi1YHMioggUC5F95SFd7/glhqN2lZc/5LRAIh7w2/BblIQrOpm3fLvsGJk3SfaFYmT8dbqkIukpDu+7dK9kj/OM52VKC3mdlVe4JXig5x25n3aTJ2k9NVg95mplTbxJ1nNtPYa5hRb+jk9jObqNC1/EeJJm+pijeHLcRLokRjNXD32S2YnDZsDrvbfhvA6rD3yQ37Z9BaDWj/j1sXY9VBvDt8Ca+k30SmfywRKn/WDb+FB5OmcnVo+n+FrXs//fxv0S+Y+vmn8ZaqeHmoy+LZ6rTzXOF+d17OuuFL/6sGgrsthj5f9BqLwT2H82exOWzU6NvI7f6bw5nd6WBH9TEEAng9YwE3hI9g1eAb8JWpeTRlhis/JXMxQXIvFBfNLLQYu6nVtxOtDiRc6cfeupOMDUjicFMeZzpd808XFrKP5HxMh1nHporveb5gP3ang0pdC50WHSKBgHiPEH5qLWZXzXH2jb+P8p5mPqo6wstFB3kjYyFTwzJYfnpjnwoQuNpLzA4bxZr6PsdLe5rwk3n0mdG4QLG2wT0/IBWJUYilXBcxnCTPMG6JvRSBwCW4Lg1KYUpYOnHqIFK8whkflMS0AZnMjxnPSL940rwjcTgdZPrHU6tvp9bYwYwjrzLIewCl2iZW5mznk9pTPJ5yHSKBkLKeZvI1tdyWcCVP5O1CbzfjJ1UTrw4mROFDi6mbKl0rIoGQJwZfz6vpN9Fp1nNX1geUaBu5M3EyXWY9ATJPni7Yy8PZH1OtbyPFJ5xXiw+x5OQ6nhx8PWuGLcJLomTRife4MnQIm0YuZ4DSj3uTruHn1hK6LHp8pGq2jb4DndXEjppjtJt6fvU8XUyZtol3zn+F3ekgt6uGFQlX8FTeHgLlXtiddvfcz+aKHyjtaeKHlkK+acrj+vARdFl0nGgr5bn8T3gtfT5qsRxLr33xs0Nm83H1zwzxieJ0RwV3ZX3A8vhJxKmDqTa0g9NJyEWuXVKhmBiPIIo09dyecCUGm5kVpzdivsgOuVjbwDulXxGq9O0zQ1Wla6XLomPloGmsKz3M2MCBBMu9WRJ7CU8NnolcJMFDrODlofN4PWMBepuZNpOW1QX7+jwX68u+JcEjxC1WwGVM8m7mErZVHyVc5c/usfdysCELrdWIyWZm37j7qdC10GXR886wxWT6xSESihALRYQpfBnsFQFATlc1g3qtvS8QqvRDIZIhEopI9gon1TuCcQFJzIwYSaZfLFeEpOLEiUIk5ebYibxR/Dk2p50YdRAHJzzEsN7NkS2VP3JzzERWp84CoNbQ7m7Bu4CvTI1CLMXpdNJq0tBh0VGr76DR2PUvXXu6LHqeL/yU/fVnuO30+4TIvZnaO6N1gZUp0/GVqdFaDRysz3LPc0kEIrZW/YxCLGNe1FgAvmnOo8nYjUzYmzslVXL32S2U9jRx+5nNFGsauO30+5T1NHN31pZfBeL+FjqrqY9FusVu653z/HOi5e8Row5yvw4pXuHcFDWOJ/J2Y+11tFOJZHRb9e6Zpj9Km0nDZw1nuSfrQ+46u4VPak/RatL82x//H0EsFJHkGUamX5zb4CFSFcA1Yen/9lmpfvr5b6dfMPXzpwhR+PBMr43wBRbHXkK0OrDPAumvTLtJy4uFn1Klb8XpdNJl0bOp4nvXLNG/sHCp0rVx+5lN7rmYyb278Nuqf3bbQN+eeKV7JsBP5sGK+Cv6OGmBa/ezzazlqfw9PJ67i3lR43gl7SZMDitZvWJpcewlrBu+lDCFL2aHje9aChgbOJCf20qY/MMLbKj4jnpDB91WA5t6F0cyoZgzHRUcrM8CXLvEd2V9QLu5hyWxl/Z5DH5SNZ5iBe+Wfs2hhnMAJPcuNk+2l3Gg/gxPpc5EwK/7/02/yAAJkHnyQtpcbA4HEqGYw815jA5IYIRfHGKhyLXAyd/HHVmbCZR58fCgadyZeBUBci9eK/4MkUDIJ3Wn+Gj0HZxqK+OGiBGAKyNJLpIy2Nu1INbbzIgEQjwlCvxkHjw5+AaWJ0xCJhSzu+Ykb2Ys5MW0OUgEIl4pPsTTqTO5M/Eq0nyi8JaoiFIHIhdJECLA6rRz79kPeTh7O+e6qtDbzZT3NGN12NlZc5wHkqaiEEl5uegANx9/l1ajhmvDh/F8wScsP72RCl0LNfo2vCRKBih9qez52058p0lHYXc9Lb2W1QOUvrw4dB5nOirwkal5LGcnDwyaSmVPCzKhhIUxE7k0KJkUr3C8pSo+azjH8fZStlb/TLG2gZeLD1Gma+a75gJm9VY5wCVurglNJ9YjiDdKPkckEOLE1XL5dOosPqj8kbKeZsBVCbU4bDyes5NnUmczQOnLwfos6g2u9reX0uaxLM4VTvtjSxEmh5WBnqEM9o5A0NsWt678MD5SNU+lzkKEgFkRI/GVqXml+BChSh++bsrBT+bB8bZS/GUePFOwz92Gt33MXSR7DcCJk7fOf8k9A6/mzYyF3JlwFfvG3UeXVY+vVEW7ScNXTTnsqjnBIznbEQgEHGkt4q3zX7Cu7DBWh83t8thl1rOh/FvOdFaQ5BnGkrhLeSxnB4Bb7Gd3VfFGyed0mHsIkLvepw8PupZmYzcvFh4g3TeG+5KuYfnpjSw6+S5PDr6eCYFJvJmxkGCFN08Ovp7LgwezNnMJfjIPxgcmsWPM3azLXEqo0vW51lzUumZz2CnQ1LH4xHvMP/4Oi06+y41H3+TT+jN/umqhFstZED0eiUDEIK9wjreVsrf2VJ/b3HnmA2r0bdgdTvfPrgoZwueXPEK6TzS7ao5zdehQhBd9ngd7h2Nz2DndXs7Dg6YhE4ppMHay8MRad27Uy+nzUP+DzCWd1eQKLD6+hhp9G1aHjdzuamYceZVibQM2h512k5ZGQ9ef+vt/SZ2+wz2rqRTLMDks2Jx2QhU+bBqxnA0jbkUtlmNyWLHYbX+oQtZq0vDAuW2szt9HgaaOIk09LxYd4K6sD2j5PxRNF3ckwD+eseqnn35+Tb/pQz9/ijp9Ow+c29rn2Pqyb0nxjiDFK/wvn9uhsRh4vfhzvm8p4GxnBRtGLGNPzUn21p1kb+0pdo29h3CV3586t49URZpPNA3GDt4ZtgSVWIaXVMnnDee4NDgFtVj+qwFj1W98wWmtRgw2C1KhGLPDypN5u5gbNZYQhTerh8ymVNuE3eng/nNbWTX4Bs50lDMrcjRf9Q6hX2DagEy3+96tcZcx0DOMB85txYGTGHUgepuZFpOGh3M+5vX0BdyVMJm3S11tPatSXVWBCwGUy+IuZ2bESH5sLeLZgk9QiKRYHbZeo++/IRWK3WGz4DK/KNe1sPzUBnpsJiYFDWZcUBJP5+/F7nS4W2cAIpT+NBo7CVX4UK1vZ0P5tzyWMoPPG7K5Pnwky06t5/X0hbxz3hXYe2fCVZzpKCen13msw9zDM/n7WJ06C2+pksdzd9Fg7OSZ1Nn4StVU6lqIVgfyVP4e6g2dvFbyGYO9wvmmMY9XM+YjFYpQiWW8PWwRd2Rtpt7Q6d6Bvj9pCqc7ynF2uKygJQIhRruVVpMWvd3Mwznb8RDLaTVrkQrFeEmUSIUSXkibw/3ZW+m26Fk/fCm+EjXFPQ08kr2dWHUQLw2dBzh5Im8X57WNVOhaeG/EUt4u+YLj7aWcbC9j86gViAViCjR1nO4oZ3n8JNaVHeZIa7G71XGkfzyDvSN4sfAAg7wGUKSpZ3PFD9wSeymjPBNI845kYexE1pz/kiTPAahEUvK6awF4IuU6wpX+3HfuIzosOn5qKeK68ExmRY6m22pgTEAiOV01zI4YhVIsQyWW8V1zPgM9wxjpH0+nRceLhQfwFCsQC4X81FLE2c4KotV/s2wf6hPFuMAkNpf/wPyY8azO28vq1Nm8UfIZdyVOZmX2du5IvIrdtSe4I+FKJIj4oiGb+dHjCVX6IBWKKeiqZYDSjyE+URxuyqdc18xT+Xvd77XR/gn4yz3ptujxlXnQbtayr1cc3Bp3GSfayzDYLQTKPHk9YwFZnZW8WfIFJ9pL6bGa8JN5uI0aJoWkumbvCj/tbem0c0P4CAYofXki5Xo8e6vtwQpvHhx0LT69g/7dFgNvnf+ClcnTAZfL5KtFh7g1/jJi1EHu2aILrYzg2mB4tfgQA5S+jO4N+P1nkAhFJHuHszZzMb4yD2YffRMnToZ4R7I07jIeyN5Ks6mbV4oOsWrw9bw3/Bb21JxgXvQ4vKUqnhtyI02mbh7Idl0bLpDVWUmwwpsEj1Dyumu4b+AUXij61P3zp1NnMdAjFNHvZBldwOKw8db5L9HZTCw//T6LYibyZskX2Jx2Xi06yKvpC3g6bw81hnbeG34LA5R/7voLrmrbXVkfuDsjJoemcbSlhGdSZ+MpUaASywhWeLF++FKcQKxH0B8y2TjbWeVuW72YSl0rR1qKuSFixL9k1tFPP/3839Gfw9TPP023Re+yqNY1oxRJeSFtLq+XfE6Nvg2ZUMLBCQ/i8zuWqn8lqnSt7tDRi7k5ZiLzosb+S62H7SYtNqcDqVBMh6UHicDVGuQn8UAh+WM2wZ1mHSuzt3Nz7EReKPyUZlM39w68hiJNPeU9zUwJS2dy6FC+a85nU8UPzI8ex8SgZJ7M2UW+ts59nsuCBnNn4pUcbDjLrIhRtJm1LD+1kXCVH0+nzsLhdHDfuY+wOxw8Pvg6NBYDOquJdL8YQhU+vcYAekq1TSR6huIlVbr/D3D32S3YL5oLAFeuzZLYS907n3angzJtE8tPb0Te29opFYrJ7apmVf4e9/3SvCOZEzWWZwr28f7IZSw+8Z5rcSv3Yl7UGNaWfoPFYSPRM5SXh95Efe8s0ooz7wMuEZPuE82juTvwkii5NiwDiUjMxvLvXDMbPtE8NOhatxCSCcXMihjF9ppj2J0OEj1CeTh5Gq8WHeKegVezpvRLd34SwPND5vBNUy4/thYxxj+B5fGTeL7wU1YkTOLpvL3uLBSRQMhbGTdjtVtpNmkZERDHc/mfUG1oR4SAJwbfgMaq58nc3S7hqgokziOYMYGJrM7f96vn8/0RyzhUf5YDDa6qoL/Mg/uTprK75gTZvTNnUqGYHWPuZtGJ93gsZQZCgYAvGrP5saWIBwdNpai7jikDhrnar6p/5vaEK8DppLSnGY3FQIp3uGunXeDkRFsZMpGEJmMnK+KvRCAAu8MBAldFVGsxoLEaqNC1UqdvZ03pV1wePJhrwtKJUgVwqO4Mm6t+6vM3TAwcxO0JV/JswSfMCB/Ouc5KFsVOZEfVcaYMSOfnthI2ln/HEO8oHk2ZTptJy+HmPA7UZ7nbgb9tLuCjqp8QIuCDUbchAG4/s4meXlOTGHUg9wy8hgZDJ+FKPzJ8Y7A6bJzsKKNY08CNkaMxOWzsqz3JuMAkguReSAQifmotIskrjATP0D4V9G6Lni2VP/Zx5BsfmMTK5Om/63rWZdGz4vRGKnWthCv9WDNsMc8W7HMFLEsU7B57L583nOPt0q9+8/4DPUN5a9git/j6Z+i26NlU/j1SkYREzxD21Z7ixsgxfFJ7ihsiR7Ku7DAPD5pGuNIPP7kHeqvJ7Xqqsxp5p/RrPqk7jUwo4d3hS/ixpYitVUcQIGDjiFuxOe08nb+3T5DvAKUv7wxb4q6k/R4Op4OKnhaWnd7oNqEBiFYF8tCga9lW9TPH2s8D8GLaXMYGJPYJmf1nsNhtFGjqeDh7G2uGLSbeI4QaQxtrSr7ixqjRDPGJQi6SuOeZ/oiTnM5q4r5zH7k3Zn5JgkcI72Qu/pU7Xj/99PN/S39w7W/QL5j+fVTqWrj37Ie8nHYT8Z7BtJq03HN2C3cmTCbDL+ZXLQB/VWp0bcw8+ob7/5cHD2Zl8nR35sa/QpWulQezt1GrbwdclafJoWksiJ7wuxkeF+N0OjlQn4W/zIM157+iSt+KAAEPDpoKTieZfnFEqgPosRo52naegZ6hvFDwKTnd1YgEQsYFDOTH1iLAJZoeHDQFX5kHDqeD8p5mHE4n9537CIAnB18PwK7qEzyUfC3+Ug8kv1FFNNos1Bk62Fp1BD+JmjGBiWR1VrK75gR6uxkviYIFMRO4JjT9V3/jBdEkF0mJUge4A1pXX1QdiFMH8ULaXJacXMfUsHTGBw3inrMfuo0mACKUfryavoBAmRdKiZQeq5EvGrOpN3SyJPYSOsw6Go2d7Ko5wYzwTJ4v2M/08Ex2VB/H5rSzIn4SMpGE90q/4Z3MxSR6hJLdVc195z7i3oHXUKptZFRAYh8x4iGW02MzIRGIeCNjIV815jAtPJNHcrZjdzh4Zsgsni/c715ISoVi1mYuQSWS4cTJpoofuC1hEu0mHUa7hUMNZ7kxajQ9FhM7a44hF0n4ua2Ey4MGMyUsnSNtxXxSdxqAuZFjuC5iBE/k7qJY28CimIlMG5DJjy2FvHn+iz7P8YTAQdyRcCWvFB9koGcolwYPxmS38l1TPnXGDq4OHcq6ssO8mj6fbrOe+89t5dX0mwiUe9Fu7uHhnI8JlHlxd+Jkvm7OZVxAEiP94/vM1YErT2ju0beJ9Qii0djFtAHD2FzxI0leYXhLlKxMns4D2ds432tvrxLL2DP2PtaXH+ZAfRYigZDHkmdwpqOCL3sdF9dmLuHNks9ZFHMJe+tOEqkMYE7UaO44s5nWX5g/TAlLZ0H0eI62neft81+6j4sEQlanziJaFYCf3NMtOow2C2aH1b2Y1VqMOHG6N0X0VhNysbSPWOoy69la9RPbqo8CrgH7Cp0rlHhi0CAeHjTtN0WTzWGnUFPH7Wc2u+fILvBs6mzGBCSyumAfP7QU/uq+4MrV2T3uXoLkXr/589+jy6zng4of2Fl7HIBHBk0j3TeGBcffweSwkuw1gPuSphCm8P3d60+7qYfXiz9jXvRYIpX+lOta+KY5jxSvcDJ8o7n19AaajK42vMUxl7Cp4nvMDhvhSj/eH7kMH+nfv65ZHTZ2VB/jndKv3cfezFjI+rJv3ZWb1amzGB+Y9C+3lVnsNgx2Cx4Suft17bbokYukf+r76x8JpniPENYOW4y3rF8w9dPPfxL9wbX9/I8Sow5iy6jbifd05ZQEK7x5b/gt/1ViqcuiY3ftiT7HznSU02bW/suOT83Gblacft8tlly/T8/26mN82Zj9qwrCbyEQCMj0i2Vd2WGq9C6jAg+JnFeKDlGsaURjNWBz2FGL5QzyCiO3q5oBKtcQ/qrBNzAyIIHbE64EINUnAkmvOYTGauS9ssOYe2eM2s09PJW3l3dLD7MgZjwKkfRXYslit1Gpa6He0MGC42sp0TYyOjARg91Crb6d94YvZc/Ye9k6+k7mRo75zQWZSCAkwTOEKHUAepuZI63FbrEUrvRDJBBSrmvh0ZwdPJ06i+nhw/mppZg5v3BQuz9pKuvKvsHsdD1+D4mCq0OHsjhmIt5SFSqxlFajhhXxk3i+YD+PpVwHwNOpM5EIRAxQ+HJZUAp7x91PstcA5GIp0aoAdo65myJNPSfay/CUKKjUueZ6Hh40jQ9G3eY2QTneXsrsyNHIRWKmhA7lmSGzeKXoIE3GbsQCEdGqAGwOO/dkbcHqtPFBxY8cbz/PE7m78ZGp2Fz5A9+3FPBk7m6SvEKZHp7J+MAkLgtK4doBGUhFYgJkntwcMwGAUx3lOJ1O7kqczH0DpzAtbBhNpi63WBoTkMiC6PEA/NRaxL66UzwyaDoTAgdxy4l17Ks5yQ2RI7l/4BReKjpAq0lLnb6DEKU3ESp/7jq7hUUn3uPus1vQWo20m3vwlCpZGD3hN8USuAwYZoRn0mjs4snB1xOh8uehQddSpWtlXtRYijQNbrEErnYzq8PGxMBk4j1CsDsdrC7Y5xZLC2Mm4C1VUtbTzLMF+1gUM5Fb4y6jydjNS0Pn9ZmRG+4Xx1UhaZztrHKLpXTfaGLUQdidDp7M243GasTrok0PhViKWizH2itgPKUKvKRKLL2fAdVFi+q/4cTY+/O5UWNYN3wpjwyaBoDZbuP3LhFioYgoVSAvps3tc/z2+CsZ4R+PSiL/lenExUSo/JH+idBRqUjEQK8wAOZHj2dC0CDyumsw9bb9FWrqWZm9Hb3N/Lvn8Jd78FDytSR6hFDU08Ctpze4QqNtrmvGkphLUYikvJ6+gHZzDy8NnYdcJOHOxKtQCP9+5dxos5DTWc26sm/7HH+m4BOWx08iVOGDn1RNpl/sv2UGRyoS4y1V9nldL7gD/hnUEjkzwof3OeZx0dzW9AGZ/1WGSP308/8b/YKpnz+Nj1TVp1XBR6r+rxFLGoueLRU/saf2JABXBKfiLVGhsRpZdmoD9YZOeqxGWowa2kzaPyRwLqasp5lOi+43f7al8qd/6Jh2AZPdSoOxE5FAyNOps3h72CJCFN4cajzL+Z5GTHYrAoGAAUo/Ej3DSPIMY23mEr5tzuelwgMM9Ylix5i7mBKW7q6aeYjl3BY/iVpDu9uxqtOio6ynCa3ViMXhEkdGmwWbw47GYiC3u4b5x95ha9XPrB4yk3sHXs1juTv5sPInrgpN476zW5CJJAQrvP/uLMOF95PD6aCnN69mmG8sq1Nn89rQ+YgEQkwOKyKhgO+a8xkVEM+2qp/7nOO5wv0si5/Up2XJQ6Jwt4n6yTxRSmQcbDjLhhHL2FlznK1VP/Np/Rn2jr+PVJ9IXi/+HKPdjEggosuiZ2v1z1ToWmkza2kzu+ZNnk6dxcrk6SR5hvJq4UEeTZ7O8vhJBMu9UIqlqEQyZkeOQn3RzNKaYYt4ceg8nkqdidFuoVbfwZK4S3l2yI3U6NuYffRN8rtrESDg0eTpVOlbWZW3hxcKP+Wy4BSkIgmP5Gxnffm3qMRyZgwYToWuhZU52/GWqBjoGcLMo29ic9iZGpbBaP8E7h84BalQzH0DryFGHcgI/3juztrCjprjrEyZwXWRI6jXtSMWinhn2GLeyFjAEO8IvmrI5uWh8whT+KCzu3JpZEIJ72QupkhTh5dE+ZtiCVyCadqATN7IWMgLhZ/yQuGn5HRV8/GYO5EKxTyeuxORQMhw31hmRYzC7nTwVP4eJEIRzw6Z3WcRO8IvjmlhwzDbbQTKPDHYLbxW/BlOgROrw87njdl9ZuQKumuRCkWk+UThJ1Uz0j+e68JHcEfClcSpg4nsFRwtxr8N4V/IlivorqPNqKFM20R5TzM/tRbTbe7bkmt3OjDYTDiBZfGX83bGzdwcMxEHTq4IGcIbGQt4IuV6/OWu6lKP1UiH+W+f5y6zDq3VyNaqI33Oe7Ahi1aTBoPN/Cub9otZHjfpT7XjqcRyJgQl8dGoO5gTOZrT7eU822t6EO8RjFIkpdWsZcWZ96k3dPzuebylKsQiMXHqYK4ITsVit5HVUckXjdmc66pi6+g7eLf0G3bXnuBcZxX7xz/ASL945GIpGouBEk0DbxR/znMFn3Cmo4J2c48r38pm4r5zW13ugqpA3h62yGVnb+7h7fNf8ljKdXRYdDx4btv/mevcPyLDN4YkT5coHRuQyIYRy7gmdCgx6kAuCRpEi0mD5v/Yaryffvr5c/y1J/P76ed/CKVYzsSgQeytPcm86HHMjx5Hu7mHZac2Mtg7AidOHsn+mLOdVXhJlcyOHM21YRl/OO2+otd17LfQWA2/atX5PaLVAWwYfisdFh2pXhHIxS6L3+yuKiYEDnLnbIgEQgJkHuyqPQFOJ7WGDpQiKX4yj1+FMjqBdrOO5wr248BJvEcwDqcr26nLoufd0m843JTHm8NuxlOsoN3cQ3ZXFVanna+acui09HBe2+QyaTD8TVh3WnQEX2RP/ffwkCi4KjSNQLkXKrGMZac3sCzucl5PXwDAjqpjPD74eq478hoWh40IpR93Jk7mybzdtJo0PJ67k3cyl/zmwlIiFDE+IIlwpR8by7+jzaRlbMBAlsZeilQo5pWiQ/zQWkixtp43h93MnpqT7Ks7xf66M6wfsZQaXRsp3uFsLP+ODN8Yt3B4u+QrEjxDONyUR5LXAOwOB03GLkKVPrydsQiz3YrVaWfxifcYG5DItjF3YLbbuO/ch3hL1KweMpsnc3dhsFt4cNBUrE47ZpuNeI9girUNPJa7C7FAiNVpx1uiYrR/Am0mDQcbsoj3DKHR1MnD2duxOe28Ufw5r2UswOKwobEYmBKWTp2+gweTrkVvNfLO8MWc7ajku5YCGg1dLI+fhEosw2AzE6MKZF3ZYebHjKfe2NkniNTqsFFv6CBKFUihpo5hfrHurKiLEQkEbKs6QrJXBA6nk7eHLaJY08CPzYWMDhjImszF2Bw2wlX+iAUiZCIJPRYDESp/1pZ+3WcDIquzkmp9G8Waet4adjPPF+7n8eTrMNmslGgb2Nu7qXFpUAoF3bW0mrXcc/ZDNo1czvNpc2k1adhedRSJUMRtCVcgFAhoNnUjEgoJdHq5Kpc9zSw/vRG7w8HqIbPxEMt5On8vbWYtjyXPYExAIv5yz97Zl1rUYgXryr7hseTr8Jd70mDo5P3y77h/0FRG+Se4hX+P1cjnDec43VHBY8kzUEvkaKwGXij8lOze1q2pYRl83ZRLnaGDR3K2827mEoLl3qzNXMLKnB3urCmZUMJtCVeQ4h3+dz87Frutj+mO2W51v0YqsZyBXqEY7RbUEjlCBGT6xfF06kxaTBpWnN6IXChG9Af2Un1lau5NmoLNYWNGeCZWp50vGrP5rjkfs8PG+MAk5kSNcbclaiwGPqz8iW3Vf9vgOFCfxTCfGJ5Jm80rRQdZmTydbVU/83zaHNacdwXJvl7yGc8MmUWHWYcQAQWaOn5uLWHqgIw/VWn7s2itBjwlf6sQaSwGPCWKPiYOgXJPXkm/iQptMz02EzcdX8PK5OnckXAVnRYdy05v5IaIkf/yDOx/AnaHvc/m1y//308//230zzD108/vYHXYaTVpUIvl7i+3ekMHdqeDecfWYHHYyPSNJcYjiF01x8nwieH5tBsRCUV9HOB+i59bS7i/dz7ol/hJ1Xw46g4CFX/sPepwOrA57H0GoC9eJIHL7nZlzg7yex3PRAIhdqfDFQ46fOmvHP+qdK3cfmYT/jIPbom7DCECNpV/z90DJ/Nc4afU6NuQCESMCkjgSGsxS2Ivxeaw8+FFg/xeEiVvD7uZKl0bFbpmLg8eTNLfaTX6LexOB/X6Dpaf3kiHRcfS2MuI8whGIhRhsJmRiSSsLf2aV9PnE6b0pVTbxEPZ23g9fQEhcm/UvVkjrSYNEoHoV2YkeqsZk8OCXCjBaLciF0loM2tZlbubR1NmkN1VzRslnwOusFa9zYwTJ0KBkBSvcPQ2Mz+1FDLYJ5IQhQ/vlX5DkbYetVjO6tRZtBi7yfSP452SLxnkHY7N6WBDuavlaKRfHNX6drf18ktp89zmKUmeYTwzZDYn20oZFZDA/ee2Ut3rxCcTitkw4lZW9zr9GewWSrVNvFp8CCdOolWB3DVwMvWGDkb6xdNo7OK5gk94JX2++73xdP5eHkiaQodZR72hg2sHDCO7q5oGQycDvUKxOxz4ytQ8mL0NrdWIl0SJl1RJrb4dkUDIi2lzifcIxuqwE9ibDWa0W2g1alwVCIGQ7K5qXi0+xCPJ03g2/xNG+MeT6BlKum80z+Tvw0Ms5/HB11OiaSBQ5jrH/vrT7KxxzdjMCB9OQXcdZT1NiARC3h+xjO3Vx7g6dChKsRRPiZIOcw8PZG/l2rAMrgsfgd5mZmXOdiJUAaxMns5juTvxk6q5LmI4TmBb5c84cPJI8jQilH7uz0yToYs7szZTa+hALBChEEnosZlQiqQ801vxGuYbS153LXdlfUCA3IOVyTMQIuDR3B3YnQ6eSZ3N980F3D1wMl69Qr2yp4Ubj70FuEJurw4byom2UuI9Qnij5HMeS5mBxmIgVOnLqrzdzIkcw03RY/GSqnA6nbSZtXT15hD5StX4ydR/1+ig26LncFMe44MGEST3wmAzu36fZwgRKv8+tzXaLZRpmwhV+uIv88DudFDR04yHWEHIPzBouIDNYaNI08APLYVIhWI+qPzR/bPb4q/g+ogR7sp1QXcdi0++B8AtsZdS3tPsnqFc32vysqnie26MHMOjuTvQWo2keUfxzJDZeEkUOAVwpr2CAk0d86LGuJ/j/w1aTBreLP6cuwZOJkThQ4e5h/Vl3zI7chQx6l876HWadazK282pjnIA5kaN5WB9Fjqby2Xxw1G3EfhPzqD9J9Fs7Oa8tpFhfjGoequAp9vLGRWQ0G9q0c9fjv4Zpn7+8tTpO2i/qJWlydhN80XuS//TSIQiwpS+eEmV2J0OWozdaCwGzmsaeGnoPO5KmMy08EyUIik3x0ygw9JDq0nLutJv+oQv/hbxHsH4/sYAtEQg4rWMBX3shLsteuoNHdh+p+okFAjR2kzu58rusGO0W2gzuXambQ479YZOCrvrECDg5aHz+GDkCncLzsn2Uoy2v5kmdJp1rC39mlWDb+CWuMso6K7lmfx9LIm7FAECXk+fT6QqAKvT7rar1loMTAoZ3OdxJXqG0GrS8nT+XuQiKd6SC5bKenTWv7lgGWxmun6nPVEkEBKpDmDDiFsB2FjxHXtqT/BdcwGjAhIY7h/HuuFLiVD5u2egNo9cwYcVP3Gs/Tw6q4lmYzdP5Oziy8Ycun7xuqgkMrwkSqr0bcw48irfNecTJPfiqdSZ3HvuI2r0bdw78BoeS55BoNyLob5RaKwG1pZ+zSvFB4lSB5DkNYAXCj/lybxdPD74OuLUQe7z53TV0GDo5Of287xf8T3D/eJYEX8FACc7yt1i6ZnU2Wws/44kzzCEvXlFT+TuYmRAAga7pU/7psVhp1TbRKQqgO+bCzDYzG6xBC6r65PtZUgEIswOG68VH6LVrOW2M+9To2/jybzdNBg7eTxvF6MDEpkUkspLRQd4pmAfdhx4ShSc7CjDU6JEKhTjI1XxesYCXkybS4JHCCKBELVETk5XNbOOvkmhpg6D1UxWRwWzj77J3tqTmBxWXi/5jLGBA8ntclV9DjWcJaermqfz91KsbSCrs5ImYxdNxi4CFJ4IBQJXJUfmwcLo8UwKGsxt8ZOI9whhfGASCpGUgq5aREIhzxXuZ+mp9YgFQj4adTup3pHMO76GDksPazIXc3vCFQiA54fcyIODruVISzFP5u5iRcIVrBp8A55iRR/hEaL04bm0OYQovLE57W4Dj2eGzGZD+Xfsqj5Oj9WIXCRBJBDSZOzm6fy9PJKzHa3ViFQoRioUszxhUp+FfKDci0eTZwBwtK2ER3N2cKjhLBqLnr3j7qOwu441pV+xp/YE20bfyZyLhIBAICBQ7kWiZyjJ3uGEKH3+oVj6uOoorxQf4oGzW2k3afmppYiVuTtYfnrjr9rsFCIpqT6R7sBj1+cn9A+LJYAafTvfNufjKVG6xdKFVsJ3y77hy8YceqxG7E6H27r99oQr0VqNjA0cyMSgZKaEpVPW00x2VzXXh4/kjqzNaHvbce8ceBWeEgVysRSFSEqmfyxz/5fFUpdZx6PZO/iupYA7z2ym1aTh1eLP+LT+DMtOb6TjN671vjI1qwbfwDDfGAC2Vx91i6V1w2/5S4ulFqOG+85+xIPZ2/ixpYgui56Xig6wKn8PH1X+5A4k76ef/zb6K0z9/EdSqWth2akNpHhF8Pjg67A47NyV9QFCBLw17OZ/2NplddjcJgbgyvj4vfYNh9OB1mpEJZYj6W0p6DTrkIskKMUybA4b+d31PJS9zZ0FFKn058nUG1h2aiM2p50F0eMZHZDIw9nb0FiNzIwYybL4y/u0cPzW3/hQ9sdu44cL8yGbK37gvLaR9cOX4iNV8UHlj+ypPcm7mUsY5BWG+Bd/R5tJy+r8vUiEYh5MmorGauCzhnNkdVTwWsYCirrrGeobRbG2AbvTwUi/eCQiMaXaJs51VjI1LMOdFwMuAXO87Tyvl3zO48nXke4bTZmumfvPfsStcZdzaXAKW6uO8HGvO1ikKoCnU2dyd9YW9/NzgUnBqWT6xRIo92SoTzRmh5VtVUcJU/owKTgVoUDAkdZiusx6rgwd4jaDcDqdmOxWFGIpXWYd68q/ZX/daW6IGIm3RMnOmuOs7xVKBrvZ7b6ltRjZWX2MQd4DsDhsdJp1HG7KY1HcRNpMPaR6R+B50TyTxW5DazWyruwbDjacBeCmqLF82ZRLh7kHlVjGlpG38XNrCW+XfsmimImk+URxf++shZdEidbqclRL84liQfR4xAIRdhy8c/4rKnQtLIqZSLxHCACHm/NYHj+JecfWYHPaAVfw5/zo8W7RKhNJeDRnByvir2C4fyx3Zn3grvL4StVU6VsRIuCJwdfjL/Xg3nMfuc91gUeTZ1De08wlQck4cPBk3p4+czRykYRXht7E+rLDaK1GansX0w8PmobJbkEiFKG1GJgQlIzJbsXmtPPAuW1sGrkMjdWIv8yD13vDgicEDSJE7s0rxYeo0LWQ7DWAV9Pm02HtYV3ZYZbFTeLzxnPuyhGAEAEvDZ2H3ekgwTOELxtyGOYXQ72hkziPYATAzprjXBacgkQgwk/mwbvnDzM/dhxeEiW3n9lEp0XnMjTxDON0b1Dz4ynX4S1W8mzBJ2wYuYycrmpeKjrAo8kzaDNrCVf6sSpvD4tjJ3JNaLpbHNgcNqr17dyZ9YH7eRIJhLyQNocjLUVcFpKKWCBiiHcE5b3XJmvvc+4lUbA6dTbR6gCCFb8WG229C+yLXe8OTHiQe7M+pFLf6j4WovDh6dSZJHuFu69D/wxmu5VznVWuCACnA2+Jyh2JMMIvjlWDb/jDLcN/lA5zD03Gbl4o3E9ZTzPjA5J4YNBUXi46wNG288Sqg3gnczFeEiWP5GzHQ6IgRh3ImvNfIUTAI8nTMdjNvFniMih5PPk6fmot4ue2EgCSPMN4pdel8f8Kq8NO0e+4Gt6fNIWrQ4f+pmuqw+mgUFPPkpPr3MeWxF7CgugJvzv791eg3aRldcE+TraXARCm8KXB2Am4rh9XhKT+W1xk++nnf4t+W/HfoF8w/TUw2Sz80FrIqjxX/k6GTzRtZi21hg4kAhHrhi919/FrrcZf9YJ3mnV83ZTLpOBU/OUeaK0GfmopItMv7ldCy+F0UKZt5s6sD3h56DxSvMNpNnVz+5lNLI+bxISgQXRZ9Nx49E3MF31ZChGwMnk6Zzor+KYpr885vSRK1o9YSsxFlYbfo8PcQ5dFj9luxVemxmy3seTke/TYTPhK1Qz1ieLH1iJWJk9HhJCxgQPdOUcCBHhI5JxsL+Oesx8CLocwH6mKr5tyAddubrOxG4FAwKKYiajFcveXtd3pwGgzo/6NLzeDzYzOZsJLokQmkmBz2Okw65AIRXzZmM1bF1k135lwFZX6Vj5vOIeXRMm7mUv4ojGbj6uPIhGI+GDUCsLkfsjFYr5pynPnKj086FpkIilfNeZw7YBhKEVSMnyjkYukVOlaKdY2MMIvni2VP7K79gSzIkYRLPemxazBV6qiRNPI9PBMDjVkcX/SVPesxIU8J7PDxtOps/CUKHihcD/1hk5WDb6BJkM308KHIRWION/TxOsln/Hy0JvYUP5tn9dSJZbxTOpsDtWf5YdW12J3algGS+Muo6KnmXsvaqkc7B3OTVHjeTJvFz5SNeFKX851VWN3OohSBbAwegI/thZxfcRwXij8tE9ODcAVIanMGDAcg93Mt035zI4ajadYgcVh4+6zWzDbbazJXESXRc+60sOU65p5K+NmDtVn8UVTDjFq15D86ry9nO6swEeq4p1hi7k7awvrRyylvKeFh3M+dv++B5KmorUY2FDxnfvYHQlXMdwvlsfzdiEWiLgrcTIH67OYEzWGR3N2cGlQMv4yT75pzsVot/B2xiLyu2t5On8vKrGM59LmsLf2JA8NuhaxQMTSU+tZGDMBgRPS/WL4timfOM9gHsvZQYw6iPuTriFA7sXrRZ/xfWshi2MmEq0OIkYdwEPZ22kwdrJ5xHL85Z4UaupQimS8VnyIJK8wbo65xC2aLnD/wClMCExie/UxMv1jCZJ78WzBJ5RoGxEi4Lrw4Xxan+U2FXhj2EJUYhlKkZQ6Q6eremDWohBJ+4QLv56+gO3VRznVUc6G4beiEEtZcnKd28o+QObJE4OvZ1f1cR5NmeEOtQVoMHSS21XNMwWf9JnLGuEXx5SwDD5rOMujKTO484yrHTBGHch7mbf86Rw7s91KVmcl9/ZeD8AVBvzckBv/7WLpAp3mHox2K5/UnmJu9FjEAle77L66U9wQMdJ9zf2mKY/nCz5h9ZDZvF/+HSUXuSS6Hmc0syJH8lrxIWZGjGJ92bc4cJLqHcErQ2/6P832szrsZHdWcUfWZvexBdHjuTnWdU39Jb+XKQW91vGBA38zjPyvQrtJy6r8PZzpqHAfeyBpKleHDnXPzfbTz1+F/pa8fv4wequJOn07P7UUcaKtlEZDl9tO9/8CuVjKuIAkHu+1ez7bVeUWS6+k3+Set6nSt7K29Os+O+edZh1vn/+SN0o+55mCfXRb9Byoz+KZgk+4M+uDPs5Y4LLQfq7wE7qteu7I2szXTbncdnoTTcZuXiw6gMlu5UR7aR+xBODAyQuFn3J5cCoZvW0X4HIHe3/ksj8klsAV8hnnEexquVH4EKnyZ/2IW/EQy+m06PixtYgnB1/PkdZi5GIJUqEYjcXAzurj7Ks7RY/VRKp3JI8nu56r0x3lbrF0Q/gIxAIhw/3imBqWjlQoRiGW0mbS0mrU0NnrTtVp1v3KdUopliETSmg2dmO0WxD3zmVprAZMve+NS4NS2D7mLj5rOEeGbzRTw9J5e9giPms4x9jAJBZEj+ep1JkYbBZEIiEioYhM/zjGBSQB8FLRQfbUnGBmxEieytvDQ9kfU6Cpp0rfyrLTG3g6fy+nOsqYNmAY6T7RjA0YyNulX7Kr5jgdZh2XhQzmvnMf8W1zAR9XHcXQa4es6p05szhsrMrbzRO5u9whtAqRlFMdZTydt4fj7aXcc/ZDKnWtvH3+S5bFTerzHEwKTqVc1+wWS5ND0rgpehw7q4/+yuFQazURqfZHJpIQIPfk5thLWDX4BkQCIcle4eR0VROrDuJo23l3Ts2mEctZGnsZAIeb8t0L6q+acnk0ZwcP52znmYJ9PJYyg9VDZmJz2PGRqHhw0FReTJtLla6V+TETmBCYxJsZNxMo9+KJwddzefBgnho8k8dyd/JoygzazTr3HNYF3iv7hnS/aOI9gt3HghVe2JwOHkqa6nqPOx0sj5/E1qoj9NiMXDsgg8E+EdTo26k3dLLo5Ls8nb8XB05Clb5YHTbGBwzEU6xAJZLxRMr1fNuUz1DfaM60u+z4N5R9y+ohs0n0DKWsp5klJ9cxPSKTTL84Rgck8nLRAW46vta9Y/1K8SFKe5r4saWI14oPUWvo4GjreSRCEcFyb/djFwmERKkD2Fp1hCkD0pEIxDQYungxbS4DPUNx4GRv3Sm3WHpw0LU8V7CfWn07TUYNXRY9JoeVW+MuZ+OIZTyVOpMIpR9XhQzB6rAhEAhI9hqATCRm+emNGO0WVCIZUqGYNrOWFws/ZXbUKNac/9LdkmS12+ixGt1iKcEjhJtjJgIuK/iT7aU8kXI9IQof1mQuZpR/Am+kL8SBE+1FldpOs67PNQ5c80flPc3u32V3OqjsaaXbYqDHYuxzW53VhJ3/uX1R317jmCVxl+In88BLqiRE6cOS2Ev6bFAN8YnEX+7Jk7m7eCBpap+W5DCFL48kT+O14kO8k7mEuVFjeS19Qa/RxZXuOZnKnhYqelrc7cb/CIvdRmVPi7tF2ul0UqNr+8P3v4DWamB//Zk+x35oKXQ7ef4SjdXIMwX73G14O8bc7W7Pe6bgE3dkw18VgUDwKxdHhUjCL0a5+unnv4r+CtP/53RZ9OyoPsaHlT+5ZyBkQjGrUmcyxj/x/7R1oNWkYfbRN925IDHqIO5OnExRdz2XhQxm6an1aKwGpg/I5PaEK/GSKtFbTfzQUsjqgn0A+ErV7sXtFSFDWBwzke3VR1GIpFwdlk6Ywge93eze4b2AXCThveG3kOgRyktFBzhQn/WrxxelCuCegVezqjfX5QJ3JFzJ9AHD8ZT+ubYErdXA6vx9HGktZm7UWNecRtURBAhYnTqTSl2re17gzYybGeUfj9ZqZMXp9ynvzQbylCjYNvpOSjSN7Kg+isVp4+Wh83A44ZHsj1GIpcyKHI3NYePHliJKehpZM2wRIb0tRRqLgX11p9hQ9i0vDZ3HML8YTrWXszJnB8vjL2eA0g+lWMYz+ft4ZehN7K09yeLYS3gidxdioYhFsRM539vyd66zitfSF7gzurrMOhafXEeDsRNPiYLnhtzIGyWfU6lzZUmJBSJXiKhExbvDl+AnU2O0uUTb5oof3IGtF4hVB/FGxkL34qzVqKHO0MHqgr3uSo5IIOTNjJvxFMtZePLdPvePVgXySvpN3H9uKzW9xgoXv5ZNxm721Z3i7YybqdK3IRIIXbbWOAlX+tFk7HYtxNWBPDfkRhqNXTyas5OhvlFcE5qOn0yNwWbhuYJPeDXjJg7Wn+XKkCHIhRK0NiN5XbUEKbzI7qwi1ScSlUjGswX7kYpE6G1mQhW+PDJoGhvKv+XWuMuw4+DH5iIajd3cl3QNXhIlfjI1AoGALouOUm0TLxcd5PaEKwlX+vFo7k5q9G3IRRLuSpzMpoof6DD34CGWs3nkCpaf2eh2IHs85TqSvcLpsurZVPE95T3NrM1cAk6IUgcATkq1zRRo6nij5HPsTgcZvjE8mDSVu7I+oM3cw8tD5zHQM9TlFOd08nnjOUYHJLLg+FocOEnyDGNs4EA2lruqW1cEp3J7wpXcdHyNu7I6bcAwPqz8CUdvq+ONkaN5JGc7KpGMjSOX8VbJF+6BeolAhNVpx0Ms55khs1GJpOisZqQiCQkeIZzurOCx3B3u1/ShQddSpKnns4ZzJHmGEaTwpkbXxrNDZvNlUw6XBCYDIBYKKdTU4yNVYXM4SPYaQLmumVV5e1gefzkJnqFIBCJuP7MZJ06eHzKHaFUAA1R+bhOANqOWr5ty+Kopl+Xxk6jRtxEk9+aNks9Zm7mYKHWg+3FpLAbMDiuPZG9nTEAiMyNHYnM4eOv8F1gddu5PmoKfzAOj3cKZ9goeyt7GrMhRzI8eT7tZy/LT75PqHcG1A4axKm8PIQpvGo1d2J0OEj1CeTVj/j8ddvt7WOxW9HaL24XS6XSisRpQi+WI/047YbOxm3OdVfRYjbxW8pn7uBABr6TfxECPUAIUrsdotlsx2MzIRVIqdS08nb/XbXwSovDmseTrSPWJ/N0oC4vdRn53LXdmfcDVoWncmTiZdrOWZac39n5W5/SpBv4enWYdrxYf4tvmfMAVXn6ktRhLbyDve78zk9Ro6GJV3m4eH3wdkaoA2kxani/Yz+K4S0jyDPu7z9N/Mh3mHl4qOsCPLS7DDn+Zh3t+9qnBM5kQlITqN6pu/fTzn0p/hamfP0RuVzVbKn/sk2Nidth4LGcnTaau/7PH1WTs4rYzm/qEKFbqWvi4+ijhan/mHnsbjdWAl0TZOyjtastTSeRcEpTsHrS+IJYuDUrh8uAU5h57m4MNZ9lVe4KFJ9ayqeIH1GI5z6XN6fP7F8dcQrw6BLFQxBCfqF89vuVx/4+98wyMsmzT9jG9ZSa9956QHkLoKigoRelFwAKCYhe7IiiCBbtiQRRFVKQoiA0VUEQ6CemB9N57md6+HxNGor5t191vd98c//JkMpnyzDP3eV/XdZ6TWJ+ywCmWXCVKRnhGAvBm6Q983ZD1h11hrcVIdX8r75f/xAtF+znRVvqHnc5uk5ZtFUecZgp7606T5BZComswduysyd/tFEuzgjOJdw2kx6zj/fLDTrEEjlbFZwv3IREKKeipo7ingVZDL6V9jRT11pPVWcln1cf5rjGXH5vzqdW2c7q9HJPVUUmz2K0cb7uADTuP5HzK80X7eSz3M+zYOd5WQqJbMMEKD7aNvoMQhSd3x14DCLg2KIObIi7HRSRnRlAGWosRG3Y6TH1YbFZ0FiOnO8qdFYRes57VeTt5JuV6AhTuWO02jDbzgGC9hc2lP/JO6UEUIik+clduj55M0iW2yjKhmDdHLHOKpT6znq2VP2Gy/TE4tN9iwEUiZ0nY+EHHX8u4ic2lB6nRtqESy9g6ciWjvWIAeKfsILNDRuImUfFQzqeM8owGwI6dFLdQHk+YxQtpix0iz2qh12zgucL9GG1marXtRKn9+KzqOAebctk2+nakAjFT/FPRiJUDw+NfoxEriHHxZ6JfIl/VZZHgGsj6lPk8n7oIT5kasVAIAju6gd3qw02FLA4fz5rE2bhJlbxXfpiq/lYadV24S12I1QRwY8TlpHmEIRdJuCvmalwlSt7MWEayWwjrk+fjLdPw0LDrqNN1sHXkShJdg5EIxQgEArI6K9hcdpCsjkom+iZS3F2PSixDLBSht5ixYiOvq4Ynk+biK3dlWeQE3ir9gQ0pC/GSqZEKxTyc+ykvFn9Fj1nPBN9ETrY5qikXDS0uiqU09zAm+iVysDmfJeHj8ZC68OaIZWgkClYnzkYukrAwdAy7BuafLvONx2q3kTtgyb06cTbbx9yJr0yDWqIgt6sGV6kLZ7sq+L4ph4KeWp7M3z3o/X75/Ddc5h3P5T7xnO9t4EhLEeN94vixKZ9Pqn7l3uxtSIQisjoqeaH4K57I24WXXI1YKCLTM4oPR91OTX87/nJ3hrkG8U7mcsdr6x4ySCwZrGZK+xoZ5hbEo8Nm8FHFL4SovNBajHw46vZBYgkcs2s/NOZR2FPHu+WH+LTqGK9d+JYDjbkcai6gqKcOm92G0Womp6sKG3Z21pxgfeEXrDzzPnqriSptG25SFWO9YngjYynPpl6PSCBEbzVi+xez4v4WJquZ3K4abj75FnXadux2OxX9LSw5vonSviYsNuvf/FsPqQq5SOwUS2nuYc4K4EPnPqFS24p14O9lIgnuMhenGKy+ZDOjSd/NvdnbqPs7eVEGm4n87hosditfNWTzRN5ObjvzHr1mPdX97c6Wyn+EXCRhvE8c4JhZejxhFm+OWIZUKCbNPQyJ4M+FT4DSnRfTlxCq8gbAW65hbfLc/9ViCRwmQpX9jtm7h4ddx6dj72HkwHWxoLv2n47EGGKI/20MVZj+jek2abkn68M/9JJfZGHoGO6LmzoonPa/A4PVxO6ak7xZ+gNhKm8eTZhJva6DDYV7CVC4c1fMNeypPUVOVxV7xt9P6O/scnvNOvbVneWt0h+cxzI8IpkVPIKn8vc4h7XBMX+wKWMp92V/RLOh23lcKhTzZsYyEtyCaTf2csOJN53OTTeEj0chlJLiHsrbpT9Sr+/krYEv0A8rjnCouYDXMm4mUOGOm1SJUixHazFysCmfZ4v2DXqsES6+vD78ZnwHdlWr+9u4/vjrWO02FoaO4TKfeJ7M281rGTdz6+ktaK0OARmrCeDNjGWoJXKOtp7n4RzHfMrC0DH4yF15Y2DGaFnEBPotBuI0AWR6RvFNwznkYolzyPoiN0VczrUBw9FIFU5b2FZDD4/m7qCwu855u0TXYNanzMdP4U5pbyOrsrfzyvAbiRkwNegw9tGs7ybeNQipSEyroYfingYyPCJQiCQcby/lwXMfA47ZNJlIQqO+izWJc7gvext9A/3+IoGQ9ckL+Kohi7MdFXwy5i6ClZ7kdNVwX/a2QfMgyyImDBLNddp27s3eRr2uE6lQjFosp8PUj1Qo5vWMm9lSepic7irn31+skGws3s9t0Vdhs9kx2S3sqjnJ9MB00j3CebP0B8r7mh0OXyYdYqEIiVCEVCimuKeeZLdQzHYLT+V/TqepnwCFO8+lLuKl819hsJp5ZNgMVGI5v7aeZ7hHBGqJnC6TFpvdjkwkYVvFEax2G6vip9Go6yK3q4rvm/J4ZNgMtlb8zEPDrsVdomJV9keU9Tc7bcdfv/Adv7ZdwEfuyktpS1CJ5QSrPOky9jtnPjqMfQiAt0t+5GxXBe+MWI5UKKakt4kabSup7uFoJAr6LQZOtpfhJlXyQvFXPDTQNhWt9mNX9UluiLgMK1YeyvmEkt4mxnnHsiLqKh7N/ZQmfTeJrkE8kTiHiv4WVuftBGCUVzRSoZijred5KP46crqqnDv1AHsve4A7z2ylydDN7dGTuCYgjQ5DLwgECAVCXMQyninc68wsArgndgrDNIE0G7rJ9Iim09yHQiSlx6zHX+6OSCigoLsWX7kre+vOsLfuDBEqH55Omc/6wr2U9DbiKXXh7czlLDj2GgBRLr6sT1nIXWe30mHqR4DAuYk0yiuaaQHp/NxSyEPDruORnE/J764lXhPIq8NvGogQsA8yY7HYrJzrrOKerA8RC0WsS56HVChmzUDO1vrk+WR4RuIpU9Nm6KXbpCXcxYdes563S39wGpBc5PdV6w5DHx8OzPZdxEfuyvOpi2gxdBPh4sPD5z4lROXFlIA0PGQqgpVe/1RF5R/RbdIy99dX6DXr8ZZpeGTYDNYV7KHPYiBA4c6Ho+/4u8G6ddoObj/zntMsxoadh3M+pc+s580Ry5xVbnA4fm4uOzQoruBSrvJLYk3inL/ZCdFj0rGn9pTTyh/ATaJiy8gVfxCsfw+dxUibsRcPqQtqicLpPOp6iYHMvxNN+i7yumoY5x2Hi0ROu6GXI63FXOWXNGQrPsT/OoZMH/6EIcE0mDZDD0tOvDkomPJSxnjFsDFt8Z8GU/5X023ScqqtlCiNP14yNWKBiOyOSnwVrnSZtNyX/RF27KyIvJL5oaOdi+Ves4799VlsKvkegBCVl9OFboRHJDODR7A2f7dzwf1GxlLeLPme0r4m5CIJG5IX8EbJAWp1HciEEvZf/hDuUhWV/S08kbcLvdXE+pQFLD/1LnKRhJfTb8BNqmJf3RlKeptYnTgLi81KYU8t2yp/4eX0GwlXeVOv72Ter6/+6XOdFzKKe+OmIhWKnbu3p9rLnAv1p5Lm8n1TLjuqjzv/RoCA51KvZ7RXDEabma3lPyEViQlTeZPkGsKvbRc401HO9KDhbK/8hTWJc9BIFMw++jJvZd7C80X7ne1n7lIVmzKWYbVZeeXCtzyZNJcglSdthh5+aMznjdJLDB5ir6FV30uyewgbCveit5oIUXnx3sjbnIski806aAf10kDDdkMvd2V9iJfUhbXJc+k3G+gyaXk099OBSp0ClVhOo74LsUDEk0lz8Ve44SNzpc3Uy62nt2C124h08SVK7TfI3GJu8ChUEhnlfc3cdnoLRpuFF9KWIBGKnKYPFxftFX0tXO2fwubygwBc6ZvILVETeTJ/NzXadp5NWYib1AXlwK7/5IAUR6vhybfRWU3cHXMNIzwjeTjnU5oN3SwKHct4n3huP/s+4Ggzy/CMoKirnpkhI7gr6wNkQglPJc9FJpTwbtkhboq4nLX5u7HYrKxPWYBEKOKl899Qr+tgdeIsDjYVMDUgjQClO2vzdvNC2mJqte2sztuJDfugRf3t0ZPRWYzMCh6B0WbhmcK9rEueT6DSg3pdJ88W7mVZ5ATcJS6caS9DKhYDAhQiCd4yDW5SFS+e/4rcrhqu8ktiWeQEyvuaaTf2Ea8JxEemQSCA0r5mvOUa1hV87vxcwW8OjxEqb4w2Cz825fNayW+ifGpAGmnu4TxTtHfQuR+vCeLplHmsPP0eM4IymOSXzPaqo8S6BlKvbXcKh6eT51PQXet0Zvx41F2opQ5r82ClF+9VHCa3q5rXht9MiNKTj6t+ZVfNCZ5JWUh5fzOjvKJZm7+bxxNm8Wn1MZZGXMEzhXsHteFe4TOMO2KuZtHxN5yug8M0gTyWOIulJ9/BYrc688sECHg29XqS3UL+pgip13Zw37mPnNlVQgSY7VZ8ZBrWJs3FQ+qCq1TJmrxdFPXU807mcuI0AWgtRub++rKzzTfSxZfNI1fgeonjptVu40JPA0sHco0ArvBNYJx3LFFqX9YX7KWivwWAVPcwqvvbGOcTy8PxM5CL/3PX84tGObed2YLukiqNh9SFzZkrBlo3/z4NAzOFF40oWg09WO22QWIJHFXh+7O3OyuKvydA4c77o1Y6rdF/j91up1rb5hTGAKO9YliXPG9oYf+f5PcByb93ph1iiP8tDLXkDfEPUYhkxGkC/+bvh3tE/H8RS+Co8NgFsOj4G3zbkIPWYkQsFLL89Lt83ZDNxrTFCBDwXsVh9taddg5JW+1254DvFP9U3h95m9MQod9iQC6SIOS3ydRXz3/Lqrhp+Mhd2Zy5grHesWwasYxQlTfrU+ajFEkRCAREqv14a8QtvJJ+I2qxnA0pCzBYzWwuO0iXScvntafJ767h2cJ9/NJSzHNF+2nSd/NtwzkMVjO/DrTY/Rlf1Wc784GkIgmp7qFcHzaWjyp/IdU9lBPtpU6xNME3gQTXIOzYeSz3M2ebzrKoidwQfhnDPSKxYKPfYmBaYDrr8j+nrK+Zz6qPAwJWJ8xib+2ZQbM6XSYtm0oO0Gbqo7innruyPqBO286JtlI2lX4/6LG+VfIDkWpffmouRG814SN35dX0mwbtKIsvEUdlvU3OZs8uo5Y2Yx+vD7+Jp5LnYbXbeCjnE5RiKUKBcMBhbzmPDJtBhIsPAhyDxH5yV24+9TZ6i4kUt1CiXPx4bfjNPBA/nVlBmXhIXUj3CMdmt6GzGGnSdbExbTFvjlhGrMafA405PDzsOp5JWYhEIKSir4WnU+bjr3BjVdw03KUqboq4nKfyd3NHzNXcGnUlF3obndWxKFd/bjr5NhKBiOuCMgDYVPo9N558y5mjlOYRjlIsJUTpqHYebC6gXtfJrdFXoreaECKg09TPmrzdPJG3i3p9JwKBAIlQhNZq5Im8nWwo3EuNtg0hAmRCCdMCUvGXu3F/9nYa9J08lPMJYSof1ibNBXCKpRvCx2OxWbg2cDhioYgHzm0nv7uWO86+T0VfC4/mfEpWZyWP5u7ARSLn9dIDbCz+ii6TlkPNhdyfvR2ZSEyqezgAh5oLONSUT3lfM2+UHGBj8X4EQgEF3XU8lvsZD2R/zLqkeXjLfvtieTn9Rs62l2Ox29lXd4bhnhGEDrwWQUoP5oSMdIql4e7hrE262J5Xz7ulh3h/1EoClB5orUYu842noLuWFI8wxnjF8EzKQvbUnmKEZxSLQsdyf9w0jHYzj+ft5KXz3yARiqjqb8VgNXNf9jbWF37BZzXHsWHnTEc5Y7xieeDcxzTpu2k39LIqbppTLC0MHcMjw2YgRICXXMPJ9tJBFu21ug4EwL2x1wxcXxwbLWuT5lDcXccLxfv/0Hprt9sp621ibf4uNqQswEemwWq3Oeesnkqex4bCvdyd9QEPZG/nXFcVJpuFZkM3XSYtr174dtBMZEV/C5/XnKLXrKPHpMNktVDa28gdZ7cCjs0TgCMtRRT11CNGRL2u0/n3uV3VdJu1fN+YR6dp8GP9jyAUCIlS+3F//PRBx9clz/unxBJAoNJjkGufj9z1D2IJHN8DQQqPv3k//gr3P5gPXMRut1PZ38KK0+8OOn6yvZQ3S77/QybbEP8al4olYEgsDfF/niHB9G+Mi0TObdFXOb9wL0UlkjHRL/H/w6NyYLCaOd5aAsDrJd/x6oVveCR3ByabhZLeRmI1/swJzkQiEJHqHoZC5LBovbj43ZCygHvjpuImVXGZbzzPpCzklqiJrMnbNaglr0rbit5q4pMxdxGj9sdks+CvcOfdzBWM8ozGdslsl4fMhQi1L2EuPozxjuVq/xTyu2v5qj6LR4ZdhwABed01Tqvma/xTuCH8MlQSOT2mP3dTAjDazIP+j1QkwU2qIkbjz9HW8wxzDcRf4cY1/qlkekZxc8QVJLkGk+Yehkgg5N7sj5yuS981nuPOs1tJdQ9DKZJyW5TDhe1AUy5thh6kIgkHmx3W2TeEj+eumKsBh2tXTX8bM4NG0Kjvos9i4IPKn1GKpUz2S2bfZQ+S6BaMQCDg19bzLAofB8D65PlO10JwVJe6jFraDb2szd/N6rydtBh66DXpeL/iMDeffJv87lqUYhkaiZLboq5ibf4enk5ewBsZS9lcdpA1+bu4O3YKz6Ut4rOaE+xvyOaagBSeKdzLmqQ5vDr8JnwVrrhKlMwJGcnzaYtYm7eb7VVH+am5iAdyPuaF4q+o6mvFRSzn3tipbCjYy7cN5+i16FmTNBsvqZoDTY4g2+2j7+K1899ya/QktpQdoknfjUIkJUDhzsmOUr6pz+bJ5Lk06DuZGTSCSX6DA3qfT11Ena6DvK4a3h6xnNUJs/hkzF2cbC/Fhp2SnkbeGrEclVhGj1lHm9HRgmW323kx7QY8pS7orCZaDD2IBEKeSp7HT82F+Cs9uDPrg4FZPQWPDpuBWCjkx4Gq2kWyOipJdg/FYDVT0F3LPbFTkAklNOm7uf7465T2NSESCFmbOIe9daexYWd6YDpzQkbSZeon2SOUkt4mhAIBC0LHAFDQU0eMJgCxQES1to2lJ9/hqYLPsWMnROVJj1nnbFGdGzIKOzZGe8ew7OTbxLsG0WvWszJmElKhmHpdJ0dbz7M8ciLp7uEsCh9Hq76H59MWEaL0ZEZwBs36bkJV3jyZv4fVuTsZ7x3Huc5KVsVPw1umoaq/FV+5K0vCL2OYaxBV/a34yd3otxh48NzHrB2Yp3K4WjryYRaGjCHCxZdbTm+m16xnmGsQfnI3jFYzE/wSWRY5gXT3cGLU/ryecTOxan+nm2CyWwhRLr7orSZWnnmfCLUfgZcs3H9uLiJc7cPJ9jJafzeH2GzoZuWZ9zDbbbQZep1tpgD6gc9phIsPHaZ+LvQ52qE3pCxgpGcU3zXm8F1jDgArIq/kav9kAN4tP8S5zioONuXRbOjmo8qjzg2LbaNvZ8aAkP+hMRcrdp5PvR6ZcPBml8VuxfR35ov+Wex2O1XaVl7/XVvv0wVfUHdJ1fGvQCoUszBszN/8/S2RE/5m5k+vWc+umpP0mvW4SVR8Pv5+bo26CnA4Uf4+M26IIYYY4u8xtCXwb064yodXh9/Ic0Vf0jJgLR2t9ne2Qv3/wkPm4tzB/LE5n58GQh+DlZ7OPvcVUVcyL3Q0QUrPQUGPblIVV/omOtvA3KQqktxCnO1UlxKi9CRa7Y+bVEW7oY+dNceZHzoaH7kr3SYtX9ad5Sr/JIKUv4kCg9VMbme1c+H6Q1Mel/nEM9wjnKzOSgDEAhF3x07BbHMskMb7xA3qw780VDLJLQSlaHAmh0QoYm7IKPbWneHpgi/YkLKQ8r5mXij+CplIzKdj7gYE3HDiTXRWI/dlf8Qor2h2DLQs/dp6gRVRE0l1D0coEKK1GAlReeEikXN96FgUIilWbHjLNDyROJvT7WVc5ZdEUU89e+pO8fC5T3gyeS5SoRixQITZZuGppLk06ruRCcV8Xe9olXoibxebM5cTrPLCYrNyvreB98t/4pGBLJ5VcdNYm7+bu2Ku5qfmQuzYKetrJtMzClepknE+cWR3VtJh7ONE2wV+bbvgGFK3mMjrqia7s5LszkrezVzBnOCRGK1mDJgQG4V4ytT4yNRsq8yhQd/JR1W/ODNRvGRqxvvE0Wc2sL7wC1qNvbQaeznRXopIIOSB+OmsTZyD1W7nwXMfE+caQEVfC+d7Gzjf28C1gcPJ767hl4HK4GT/FFRyKe3GPgoumelyvNbnmRE0ApVYhh0bgQoP7sn6kHcyl2PDzijvaDqM/ShEUqeJiWRgBspmtw2q4ooEQhQiKXW6Dl678B3rU+azJm83TycvwFWq5I2SA5xoLwVgnHccJ9pKqNG2UaftQOIiJlrtT622nXXJ83g0d4fzfu+NncIIz0jCXXyx2G0sCRuHu1TF+uQFfFz9K35yN+fMD8DZjgpn29mlgc3xmkCWRU7g0dwdCATweMJMus067s76kJlBI9g0YhlV2jbuzdpGinso72auIK+rhtdKvuPG8Mu4N24qe2tPcaK9jBfSFvFc6iLuzvoQndWISizHU+qCRCgiQOFOhkcEPgpXPKVqdo67F1eJErPNSo3WynNFX/JYwkysdiu/tJ6nRttGgmuw8xoGcKV/Etsrf/vMFffU461w5f5z27nCZxhSkRiVRM66gj3cEHY5KR6h3BZ1FcU99axJnEO3WUtJbxMfVR7BZHNYhI/0jOJ0RzlH286DALaPvhOFSEJpbyNKkQwPqZq8rhp85K7cGnUlawbaeD1laqRCkcOsIGsbG1IWorUYyeuuQSaUEK8JRC1RMDUgjWOtFxjnE4ebROUMcgYBCqGUl85/g0os4+Mxd6MUSZkdkskzBft4Lm0RrhIlo71jePPCARZFjCdI6eFsywPwlLqgEP3nXU97zDpuP/O+09FwVdw0ni/6kjZjL/dkbePD0bf/pe1uQUpPnkqax7NF+7guKIMzHeU06Dq5PXoSES4+mG0W+swGFCKpc5ap09iPSCBk5cCG4PVhYwhReTEvZBQigZA0jzACL7mmDzHEEEP8I4ZmmIYAoM3QS69Zj0ggwFWi/B8xyGqxWcnpqubOgdYTgMVh47glcuK/HI5ntduo13awpfwQR1vPIxWKmRGUwfzQMfgp3Og09rOh8AuOtZWQ6BrMy8Nv5OPKX/ik+hi+cle2jlrptI6t0bax4NfXnBbJd8RMJquzko8qBw8mJ7mF8HjCLNylSkw2K7trT/BJ1TEyPCK4J3YKvWYdh5oLmRGUQYJbMP0mAwa72dmPb7SaqdG2cffZD9FZTRhtZlRiGY8Mm8F4nzgkAjF53TXcm7VtUBvRJL9k5oaMxEPmQqjKm16TDht29BYTb5b+QJwmgDSPcIp66ug26Wgz9DA7eCRKsYwn83dzvrcBpUjK82mLeXNgnuvtEcsHzDTOcLT1AhtSFnCs9QIHmnKdM0x2u52ZR1/EYDWT7h7OA/HTuSfrQzpM/cRqArgzZjJZHVXcED4eF4mcTmM/dboOHsvdwVNJ8xAJhLxV+gO3Rl1FoNKdop56DjcXkugWjKtYiUws4emCzwEIVXnzQupi1BI5IoGIu7I+IFTpxdLIKzjQmMuNEZchE4p5u/Qg++rP8GTSXLxkaj6rOc6RlmLujZ3C5d7xBLl4Ua/r4LHcz3gu5Xp21pwYNEgPDkMMiUDEVX5JTnMQuUhCunu4U7w8OmwGSrGMdQWf88iwGbQb+4hW+/FE3k5uirgcmVDCptLvkQhEiIRCZEIxG1IW8tL5b6jRtiEWiJCLJPRbDKhEMtanLOCdsoNMCUilvK+Z3K5q3sxYxsHmfN4pO8jt0ZPxV7gNiDQ421HOtIB0hAhQSeQ8lrtjkJlLgMKdTRlLCVZ5oTUbUA18fk61lVLc24C7VEVeV42zuhHh4kuEiw8ZHhE8X7zfeT8hSk/WJs3l8bzPeDp5ARqxnK8astk54GKX6h5GYXed02Z9ffICDjUV4CZTUdLbSJp7GM8VfYlQIHS0q8k17Kg+zqHmAu6MuZpYjT9eUjVhLj5/cBK71CbaZrexJmkOx9tKiHcNpEHX6RR7F2e7FCIpb2TcTJ22g6NtFzjSUkSI0pMNKQu5J2ubc8NitFcM1wSk8nTB5yyNuILpgcPptxhYeeY9RnlFcVvUJG49s4WHh11HtNqP7xvzeb/iMMsjJzI1II1V5z6iRtuOEAG3Rl9Fl7Gf0+1lPJu2iBNtpeyuOcETSbNxk6ho1HexvvALnkqax9aKnyjra8Zqt+EpU/Nu5gpCVF50GPsQC0Q06x2VqjtirkYiFPF80ZfYsHNr1FXMDx2F0WKmQttKkNKDIKXnwOepHRexnLdKf+BYW8mg1++JxNlMD0z/T5v4GKxmsjsqeaZoL2+PWE6wypPy3mbuyf6QF9OWMMw1cJABxl+B0Wqmw9jPoeZ8RnhGDbjtScnurMRVouRISzHpnuGM8ozGYDWxufwQvnJX5gSPRIBgUMRDr1mPQiQdtMk2xBBD/PsyZPrwJwwJpv89WGwWinoauPPs1j/YlN4XO5Vrg4b/zVaMv4feYqLPogcEuEtVzi/NS7NNbNiRCSUYB6pD14eOZWnkFc5d0xZ9N7tqTpLVWcmr6TdSp+/g1tNbAEclItMzkmcK92HHzryQUcwOymTJyTfZmLoYqVCM1mqgz2wgt6uaNPdwrvAdhkggpFrbSlF3PRP9EvGWa2jSd/FdQw5TA9LoMeuQCEUoRTK85RrEQhFWu40ek44NhXs51nYBcCwWd4y9h5Vn3kMiFPHeyNvoNes5017OBL8E7jy7lRZDDwqRlLHesU7Hsq0jV/LS+a8539uASCBkSfh4rvRN4uGcT5wCIVzlw/neBgAejJ9OgmswD+V8wsvpNxKj8cdoNXO8rYQn8nYNsql3Ect5Onk+b5f+yMMJ1xGq9OJIazGxmgBuPb0FN6mKp5Lmsr7A0XInFYq4L/sj9FYTjyXMpLS3id21J7k2cDhRal9evfAdd8Vcg1Is5ZXz37IxbRFqsQKlWMrW8p+IdQ0k3T0ctUSBXCShUdfJntpTLAobS6DSk/M99ZztqCDZPZQ093C85Gp6TDpcpUp6TDrm/fqqczEdpvLmkYQZ3HX2AzZlLOXT6mNU9LXwTuZymvXdHG8vYU/NKT4bew/FPQ1sKNyL0WZmVvAIvm04h1ggwlWqZF3yfO7N2sZTyXNxk6jYVHKApZETeDzvM6w2Gy+kLcZTpub+c9tpN/axOmEWlgFzi7uzPsRoMxOq8ub14TfTZ9HTbuxFLBA5cpZyd1LcW88Ij0jWJs3hoZxPuNDbiEgg5PrQseypPYXRZnYMyI+8bdDsSHZHJbeffZ8nEmfza+t5fhnI/loYOoZznVWsG2jDC1R40GLowWK3Eqby5qX0G8AO9foO3CUqfmjOG2RKEuHiw8a0xTRoO3k491O2j74TO3YMVgu7a05wpV8iX9Sd5mxHJeuS52HHMWvzee0pHh02g6v8kwfc536jz6znm4ZzvHrhW55JWcix1gucbC/j5eE3cPfZD9BZTVwXOJzF4eO5N2sbzYZuLvOJd8woCQS8UPwVcpGEB+KmU9Hfwm1n3gMc1beq/lanwcRE30TOdJTTP1BBeW/kbWgtBn5pLebnlmLWJM7BYrfQou/hlQvf8nL6DazJd4QjR7j4MDNoBGqJgl9aiglWeXK1fwqn2svQWoxU9Ldwe/Qkni36koWhYwhTeXPrmS1oLUbuiZ3C7OBMlGJHtdlqt1Ha28hNJ3/LDZsRmME9cVMQCoQcbS3myfw9TPRN5JGEGdRq27jz7AeEqbx5aNi1rMre7nwOK6MnMcE3wWmO85/FYDVjsJqc10Sb3UavWY+LWPaXiyVwhKvvqz/LGyUHcJUoeW/kbVT2t/BY7meIBUJeSF/CWyU/cFPE5ZzrqmLfgHh+N3MFaR7hf/njGWKIIf7vMCSY/oQhwfS/hy5TPw+f+5S87hpnOOAbFw7wY3M+GomCnWPvHbTw+yvQW02caCvhsdzfQi5nBGVwZ8zVzoWB1mzgvYqfcBHLSXQLQi6UYrE7LITrdR1c5hPP2Y5K0j3CnS5dTxXsIaerGiEC5oeOxmAxE6By5+3SHwFYlzSPSLUfd539gG6zlntip3C1fwp3n/2ASm0rc0NGckvkRIp76jnUVMC9cVNxlSqp7W/nh+Y8Pqj4edDziHDx4e7YKTyZv5tVcdN4p+wgbhIl61Pm02nU8lTBHqx2G48mzOSV898QpfZjQchoukxanizYw+rEWfjKXMnqrGSkVzRP5u8e1Op0f9w0LDYrPzTn82TSXDQSBRKhGHepCr3FxCdVR3mv4ifn7V9JvwGr3U5Bdy27ak7wQtoSWgw9hKq8uNDTwFcN2Tw87LqBuZsuDjYX8FNLIZ4DmTz767PYWXMCmVDCWyOW8UtLMdcGDeeJvJ2U9jVzX+xU6nQdfFl/ljWJswEBJpuFZ4v2sSpuGi5iGesL96IUSXl1+E0cbi5gd+0phAjYOmolvnI3fm09z2jvGN4p/ZEDTbmDXs85wSMJUXmxu/oE72Qux2Az88C5j5kWmE6SazB+CjeeK/qSIKUnC0PHcOvpd+m1GLg/bjqJbsFoxApaDN2IhSLEAhHeMjW9FgMdhl6UEjkmm4UWXTdV2jYm+iVSrW3FYrUR6+rP0ZbzpHuG83DOpzyWMJPi7joWho3l46pfOdp6nnHescS6BvJMocNQYWpAGkluIbx0/mueTp5PgmsQlf2tPJb7GbdGX+lczF+kSd/F9cdex2A1szpxNgKBw5XtaMt5PGQuvHj+a5JcQ1gZM4kuk5an8vfgLVfz9ojl2O12yvuaqehvIUDhwZMFv+UdTfJLIt09HH+lOwEKD3bVnOCLutPcEzMFjURBrCaAJ/N3U6ltRSwQkeoe6mxnnR6Yzg3hl+Eiljsd6NoNvQgEAsQCIcdaL5DuEU61tp3Pao4zwTeRWI0/h5sLSHMP52hrMfNCRvNZ9XGWRU4gQOmOUCCkw9iHEAEGm3lQULUAAasTZ5HbWc03jeecz8FD6sK7mSvwlWso729lxel3nQ6NY7xj+bjqKAAroyc5q6MA20bdQXl/MxsG3pO5wSNRSxTO/LQH4qcTrwkgSu2PXCShvK+FE20lzArOHCRoOo39f7AY95Zp2Jy5HDepiu8bc3nx/NeAI2agqr8Vk81CiNKT1zOWIkCA0WYe2GRR/6Gy1G3SIRWKnAJNazFitln+R7rHXZybuu30FnrMemdYMUCqeyjLI6/kgXMfOze5AJZHTmRB6Jh/SSR2GPtoM/TSbuzDR+6Kl0x9SVvkEEMM8X+RIcH0JwwJpv9dtBp6eP3Cd9wZew0BCnc6jf1sKTvEvNBRRLj4OgMi/yq6TVq2VR4ZtFOe4BrExrTFg5Lcm/Rd3J31odNWOVjhyRsZSynsqeXJ/D3YsPNEwiwi1f74yNXYgYfOfeKszkgEIp5LXcTntac41VGGSCBkTeJsDjUXOitFSpEUndWEWCBiU8ZSApTuzPrlJWzYmeyXzE0Rl9Nn0bPyzG821qO8o3m28EssdivX+KcS5xpAo74LndnIRL9Etlcd5fGEmfzQlE+KewjvlR9mRdSVCBDwZd0Z7o2ditFmYW/dGa4OSGH5qXd5Knkee2tPc67rt9yiNzOW0WLo4YXi/axLns/OmhMkuAaxPHIiLYYe7hzIsgHHTM6LaUvYX59FpIsvVmxEqHwo72+hWd/F0sgJiAUi7sve5qyq+Mnd+KDyZ6YGpBGo8KCiv5nzvQ0M94jAbLVQrWvneOsFHkucxfr8L7glegKbSn6gbMDcYIJvgrNyNsozmkcSruO20+/Rahw8nD8neCSzgjM52VZKk6ELX7kr75Q5bMYXhY2jz6zn60tsrUOUnnjJNHxa/SufDbSgrYyeRFZHJVmdFQBsyliKTCShvK+Z8r5mxAIR1wSkIhQIcBHLOddRxbbKn3kx7QZqdO2YbWa+bjhHRX8L7428jQZdB35yNxRiGfdmfUiVto1ktxCeSJzD1vLD3BY9CTt2dBYj92Z/hJtUyTMpCzndUe7M1rraP4Vbo65EZzGhlsgp6K4j0S0YpUj6h1Zbi83C6fZyHsz5BLvdzgTfYSyNnMjjuTvI8IxklFcMMWp/Xj7/NUabhSVh4wlQuuMilnPX2a2sSZpLh7GPh3I+wWq3DVrIXhs4nGi1Hz+3FDlzlK4PHUu4iw9BCg9UEhnr8j+nUtvqfDyzgzOJ1wQiFAgp6qnjhvDLEAgE/NRcyAcVP/Nu5go8pC5UaVv5sPII14eOJUzlg9aip0bbTpepnwgXPz6uOsrDw67jgeztbMpc5vz8dhm1DvfA/hakQjH3xk7hvfKf8JaruS9u2qD232sDh3NXzNW4y1xoM/RyoaeRiv5m3i0/5HTLWxQ6lnTPCGe2mFwk4cW0JXSbdJxuLxskwACmBaRxZ8zVKMVyDFYTMpHYOdt2qZDtMvWzufQg++rPAg7b+5PtpeisJrxlGt4bdRtqsZwDjbm8NCCaYPCM59+jx6Tlk+pjhKt8uMJ3GABHW89T3tfMkvDx/2NFU7W2jSXHNznPsUgXXzZlLEUsFHHtkY0YB7oRUtxCeXn4jX+oUv49GnSd3J+9napLzsc4TSAb0xb9w9dziCGG+N/LkK34EP/r8ZG78siwGQQMfFl5yFy4PWbyf4lY6jJp+ajyF6dYSnQNRoiAop56Hs3ZQeslFRZ/hTvvjFiOROBokXtl+I3sbzjrSKaXqng5/QY6TFr6LDpeOf8dIoGQpZFXOP/ebLfSaexjXfI8PGVqrHYb6wv3cm3gcEZ7xQA4zSlez7iZJLcQXMRy7o6dAjhMMBaf2MSh5kLuirmaq/1TGOcTx6GmAp5MmkuSWzBX+SfxceVRIl18uSnyctYV7KGgu5ZNJQcY4RnJc0VfUtBdx8air1CJZSwOvwxvhSsuYhnTAtMJUXry0eg7+L4xxymWpAOtNg/mfIxGouDp5Pl815hDblc1X9Seoceid4olF7GcRWFjmRKQSkV/C7+0FvNB5c8IEVLW18zHVUc52FxATmc1BxpyeHX4TZhsVh7O+ZSHcz7h5ojLebv0B2498y6Raj9Ge8XQpO/CYDOT5BbM9WHj2FC4l4cTZvBu2WE2pCwgWu2P1W5ziqURnpHcEjUBvcXCO5krBr3f47zjmB86mgs99US4+DAlII0IFx/SPcIdM0tCEeN94pkbMoqJvokYrWaWndrM/GOvMT0wgyt8HIvMzWUHnWLp/rjpHGkpZmPRV+R31TLGO5YAhTt6i5FmfTelvU10mbXcEXs1tbp2vqrPwlWqItEtmHdGLMdVokQqlLDkxJt8VZ9FhmckAPndtSw89horoq6iXtfJqnPbsdht3BZ1FXfHTqGir4Xinnrnc/uhKY9XL3xLm7EXg9VMmIsXBrPJORPUou+heyB7TSwUk+EZyc6x97I04nKmB2awp+YkD8Rfy+U+w0h3D+OX5kKmBKRxXdBwYjUBhKi8kAhFTA1IQygQ8EXtaax2GxEuPuwZfz+LwxwOisfaLjDMNYjS3iYAZgVnkuYRRozan28bc8jtqiFWEzDofUlzDyfTM4oLPQ3srTvDnWe3sqvmBG+UHKDfYmB71VFaDD0caMzlbEcFD+V8QmlfIzuqj/NE/i5evvAtNmzY7XZ0VhPPpi0a5GLnIpE7QoRFMt7MWMas4Ey2jlrJXTHX8OhA+PNFvm7IZlfNSdr0PXjLNYSoPGkYCFkWCYRIhWJmh4xkXf4epEIxAQp3AhUeWOw21hd+wczgEYOc9bxlGpZHXYlMKKHT1M/NJ9/mSEsxeqvpD+3FCpGM8T7xCBFwW9RVPJ44i3czb0UpcgRmy4QOoRU9EBh9kUClx9+02b6IxWbl19YLfFT5C08V7OGn5kJ+bilibb7DafJo63ksf4Gb3l+NwWqmqr91kMtpu7GPngE3POMlrdv53bVkd1Sit5j+7K7+QKexn4dzPh0klgAu9DawvuALek1DjnpDDPHvzpBL3hD/o9H8rp3ir+rB/z2igZkmcOyCL4ucQF5XDQ/nfIJaokB4yd5Cj8lhfmC2W3ko7jreKTvITy2FJLkFs33MXeyvz2JL+SH8FW68kbGUdkMfq3N3Dvp/tbp2vmk858xwUYllSEViGvVdg25X2d9CnCYAtUTBjKAM6rQdjPSK4s3S7/m89hRfXvYgV/gm8FzRPrI7q7Bh58bwy3m+6EvWJM3BS6bmk8pfeSBuOnbAW65hc9lBmvTdyIQSVsVN5dUL3yIWiHg+dTGecg2eA21QEmMfOZ3VANwadRUjvaJYnbuTZkM3x9ouEKv255bICdjtNn5tK6HN0MttUZMo7q3nMp94GnSdDnGLgMl+yfzYnM+Hlb+1D14bOBw7drZV/cLPrUU06bsw2iyY7VYECNBZTdwTO4U3Sg5wtPU8i8LGMj9kNEKBkPuyP0JrMfJ04efcGzuVg015jPGOoayvadD9N+m76TY1DsqdAjjXWYnWYiDdI4KDzfl83ZDNw/EzuD50DAXddTTqurjaLxmfgHRajD08lrMDO7AiaiK7a07waMJMjrWVOM02RnhEMtY7hmiNHwluQbhLXdhe+QtLwsejEEuJUvvx8vlv+LE5n7FeMdwdO4UVUVcSrPQiVh3AwaZ8VBI5SrGUeNdA4jSBrM777ZwRCAQIBAIey90xkNu0y9EmZ+zn17YL/DzgIpnmHkZOVzXH2krQWU3cEDYemUhKu7EXCzYkwl5uP/s+1wZmsCR8HG5SFTKRhFAXb26LmUyzvpuXL3zNL63nGe8dh5dMzd6GLBp1nayKnY7VbnMEVgrFpHqEAXBX7DUEqTyYFzIau93G1f6pqMRyRnhGsq7gc7RWhzPgOK9YRAIhSrGU2cGZHGjKdbY/XgyEXVfwOa8Mv5HZwZl81ZBFo75rIEMMRnpGMc47jlXZH/Fk8lyKeuqo7G8d5Aa4NOIK3KUuLI4Yx0M5H3Nf7FRi1L+JMovdSoiLF/sufxCVWI5YKEItkbO79qTT9W3LyFvZVnmEbxrO8Wn1r0wOSMGq6+aurA9oMfSgtRhYFTeNl85/zcM5n/J08gLMNgsqiZw3Sg5wuKmAD0fdzvdNuTTof8tDajP28nntKSb4JvBE3i6aDd1sLN7PKK9oVOLBJjZykYQMz0h2j1+Fm1SJWqIgSiPjozF34iKW4ypRUthTx91ZHzhvb7CaOdVexgvFX/PQsGvx/BthrmKhiJFe0U7Hv6cLv3D+boRHJGO8YpyugBcrkmablX6LYVDe2n8neouRE+2lPD5wHY108aXd2Ot07Hs6ZR7+Cjeu8BlGUU89+d21PJq7g/dG3kqoypsWQzcBCg9cJHL0FhN1unZ85K7OSlqnqX/QteNSsjor6TJr//BdNMS/BxabddBnARzdKP8Tq7BD/NcyVGEaYggcwmxmUCZvj1jO0sgrcJUqGeEVyZaRt7ImcQ5ecsfio99i4Kv6LN4fmNHRWoyM9IpCgCPYc8Gx19hSfgiADI9I5EIpj+Z+itluJUTlxd7LHuDG8MvwVbixqcQRCnu1Xwovpi3hjQsHnI5pF3eOXz7/DQcac+kx6WjUd3GF3zB2VB/jwfhriXDxpUnfzesXvmNJ2GWke4Rzqr2Mpwr2sCZxDm+V/MCumpNMC0jDV+HG4ZZCPij/mRWRE0lxC+XZ1IXEagK4N3YqTyXNo8+sp93QS5exn36zger+Np5Omc+dMVfTa9bxaM4Onkqex80RVzDMNZhus57DzYUsDB1Lukc4WosRiUhEslsIBd21vHzhG7I6KklwDeL2mMlO9z+AQIUHt0VdhVDgcDSr1rZhtFnwV7jxTMpC9FYTDw+7Dg+pC2qxY/d9R/VxjrZe4EJvA08nz0ckEFLS28iPTXkoxfI/uBSuK/gcqVDsqILUnXa81v4p+Mg06Kwm7jrryDjaV3eWel0nx9ovcL6nke1VR50C5a2yH7Db7aS4h/JA/HSq+luZEzKSJ/J2DXImrNN10G8xsjZvNwXddfjJXbkz5mreLTvEGxe+p8XQw/EB17IU9zByu6p5r/wwXeZ+dFYjYWpvDjfn4y9356nkeazO2+k0argvdhp2u52nCz5nQ8oCZEIJDfpO1uTtot3Uh4fU8UV+S+QEVifOZm3iHADcJSq85Roq+ptpN/ZSpW1hXcHnTAlI48v6MxisZn6Pn8KNNzOWMdF3GFcHpPBo7g5WxU3lnthrGOkdxV1ZW6nqb6XPbCDCxZcWfQ9igZClERPwkqqp1XWQ01VJomsQEqGI2QNZaREuPijEUnwVbtjsdlylSg41OSqB0wPT2XvZA0S4+GCxW/mk6leMNjNvjbiFq/1TnI/tjpjJbCr9ni6zlgZdF2+NuAXRJXM5mZ5RJLuHUNbbyDOF+2jSd/Nu2SFs2Gk19GCwmjnbXsGNJ96i16xHZzFitDiMCx5PmMkVPsPYPOBUd1vUJGYEZrAueT7PF33JzKMvOs1SZgVnEqP2RyQQUqdtRyWRsbv2JA+f+4TboydxZ+zVlPc383HVrwBc4ZvA5IE8pU+rj1HYU0eqexhykYR3Mh2VxT9DLpLgKVM7z3+RQIi/3A21WIHWYuBQUz4mm4VgpSefj7+fh+KvBSCrswLdP6iseMs1rEuej5/czXnMR+7K+pQFKMUyfmkpZnP5IbqM/ZhtVop66libt5u2S6p1eouJDmMf+V01PF/0JZ9VHaPD2EeP8a+vxljtNpQiGSKBkFT3UN7IWMqbI27BVaJAIZagEsmZGzyKZZETeS51EcluIVzuG4+v3JU9tadYcuJNfmoupM+s50R7KTeceIut5T85K639l2Rl/Rm6gTiAIf69uBiVsTpvl/Pcr9G2sSr7o0Hh0EP8ezAkmIYYYgCNVEGGZ4Rz50ghkpLsHuoUS+AI9B3jHYtGomBWcCbTAtMY5RXNgwOZURe/eCf7J3NX7NX4Klx5I2MpGR4RbMpYSpDSkwWhY4hVBxCq8maSXxKr4qfhI3dFLBQiFoh4bfhNA4tWR3CwXCShz6yn1dDDlrJD5HXX8FTBHh6Mn87Wip/4te0Cj+Z+ytPJ83lrxDLeyVyOt0xDinso8a6B6G1m9teepd9iYE7oKHRWE5f7xHOgIYd2Yx8vn/+GWl07j+XtoLK/lY3F+6nTdfBw7qdsKT+MCAEhKi/ajX2sydtFhIsPae5hSIQitlcdZdW57cwLGUWPWcfTBV/wdOEXRKh9yfCI4PumXI63lfBl3VnaB6ppAA36Tr6sP0u8JnDQe+AmUaG1GOky9vNjYz553bUkugVz1UBY7K+t5xELRBR313NH9GSECJgdnOnMnxrjFcPucfcRrfbDarfxXvlhxnrHIhdJmBM8klsiJ/Dy8BvxkWlIcguh32Kg3djHFT7DiFcHYhoQEQluQWyvPMrZjgqezN/N/NAxFHbX4a9wZ1/9WWcb3iPDZjDWK5Z0j3CyOyuRicRc4TOMgu46x2yUvoubIy8nq7OSB+Knc2P4ZajFChr0ndwYcTmdAwG2tf0d3BY9CbVEjtZsZHnURAIU7rw14hZmBWfwYvoSmvRdhLn48FzK9QAIETqCYMPG8U7mcqYGpCESCAhVefPG8Ju5J3YK7cY+pAIxrhIVm8sOsTJ6EmKBkA9H3Y6v3JXfj7BarFY0EiU3R05gY/F+gpWebCzaT7jal/uytxHvGkSTvosDjefQWgxkeEagt5r4qaWQLrOWCBcfxnnH02PWc8upzTToOtkz/n5WxU3jkZxPeeX8N0hFYrQmPW+NWMaisLHEqAO4+eTbPDJsBjOCMpgVPIJ99WfpMelIcQ/lGv9UAB7L/YzVCbPwkrogFYrYXHbQOUsEIEKIm0SFq1RFu7GPWHUATyXPo8XQzeaSg/SbDRxrPU+roYdtFT/TbzFQ0d9KbX8bKrGcRxNmorUYaDX04KtwZUX0lZzvaSC3q9oZLP1K+o3EqP0Z5hrIa8NvZrJ/Mu5SFTXadkflL3cnRd31+MhcSXMP4yq/JEZ7RZPsFsq0gDSSXIMJUXpxpLWIm8MvJ9rF/w/26RfpM+s51JRPRX8Ldrsdk9XMua5qcruqUYhk3BI5keWRE3lzhGNG65qAVB5PmMW7mSsIUnr86X1eRGcxcqajnGZDt/NYq6GH0+1ltBl6ebJgD/vqzrC5/BB5XTXcdfYDTneUsbnsIH1mPXqLiVPtZdx04i10ViPdJh0BSg8WHX+Dkr7Gv1w0me02vqnP5oW0xSwJG8+JthI2FHzB08kLeCJxDgEKD64LysBVqsRbruG51EU8MmwGYqGI4h5HbtqGor08mb+Hx3M/w46dkr4mLDbH+fP3KmcigfA/5Mg6xP9++syONvOszgoey91BWW8TK0+/R1FPPY/kfELXgOAe4t+DIdOHIYb4F7Hb7TTpu1GIJLjLXOgx6dhVc8JZdQJHBtPzqYucLl+/L+H3mLQYrGYkQrHThalB10m7sZd4TRBSkZgOYx+V/a3EawIx2Sx8VnWc4V4RPJG3k16zftBjejJpLlf4DnO29jRoOyjsqWNN/m7UYjlPpyzAYDXzZP5urHYbG1IWEq3245ZTm+kx6whRefFQ/LU8U7iPZkM398ZOQWsxUtzTwJqk2WCHc13VbK04zH1x0/ixMZelkRNYlf2R023s0ue+JGw8a/N3M8E3gTjXAKchwWS/ZAw2M0cHAmEfT5jJ8bYSsjor0VlM2LGT5h7OQ8Oupaa/jfO9DfjKXansb+WLutNcGzicVLdQvBUaNhTspdXYS4DCnUcTZnCgIZfboidxoPEcsZpAvmvMYXpgOp5SF1RiOTqLkTfLfmB+yGjcpCqUIim5XTVU9rcwL2QU7aY+KvtaiFL78VjuZzybupANhXsH7SS6iOW8kbGU5wr3sTh8PBa7FTeJkq8bzjEtIA0/hRv3Zm+jy6TlvripJLmF8EzhPuf/SHMPQyGSUdBTywcVP3N3zDWkeYTRauhldd5OrvFPYaJfIsFKT1SXuMT1mHT0Wwyszd/NZL9kyvubmRk0gl01J9BIlFwfNhad2ciZznJOt5ezJHw8AuD+c9sx2izcHzeNGE0Aq3M/o8PUz7LICSwMGU2Vto0AhQe+Cle6jP2caC8l2S2E189/x9KoiVT1t+AqVbI2bzcykYTNmcvJ7aqhzdiLSiwjXh1An8XI0dZixnrHku4RQb/FwJ7aU04Re5lPPDmdVfQNtHS9M2I5WZ0VfFWfzerE2Wwo/IKyvmY0EgWLw8bTpO9igm8C92V/BMBHo+9gfcFeyvqbGOcdy9KIK/ihOZ/dNY68rGkBaQgFQkZ6RfNU/h7G+8RxXdBw1GIF95/bjq/cjedSr+d0exnJbiGc66xilHcM92dvZ7R3DKluocRqAqjTdfDguY9JcAtiY+piDDYzK8+8P2h+cVnEBK4PG4urVInJakZrMeIuc6FO287KM+/jLdewPHIij+Xu4OnkBbhJldixc/fZD7k3birDXIM41VbKlorDSAQi3hyxjES3kD9kAuktJg4257OhcC9qsZx3R95Ku7GPVQOvyebMFSS7hWCwmlCIfwu91lmMKETSvzvjabFZOd5WwkM5nwCQ7h6OUCBwuhRuTFuM3mLkqYHMs4uEKD3ZNGAo0WXSMufoy/RbDHjJ1CyLnMCmku/RW02EqrzZlLEUv784+LxG28bGoq8o6K51uuEluYWwPnk+AX9HILYb+3i2cO+gXKpUtzCeSV3o/Hz1mvSsK9jDrwOmO5dybeBwHoif7nQTHOLfB4PFxKmOMh7J2fGHqIx3M1cQpfb7y+eph/jvZ8j0YYgh/osQCAQEKN2dYunz2lNOsRSt9htoz6vl8dzPnGX83/c7u0pV+CrcBlnWBio9SHYLRSpyjBZ6ytRkeETgIpHjIXPh+vCxRKp82ZSxbNB93RB+GRN8E5xiyWqzcqAhl1CVNx5SF7zlrqwv+IIn8nZislkIULgTovTk7ZIfeDp5PhKBiFptO3dnfejMXApReTHeO47ZwZnY7HY85WpS3ULYkLIQIQKmBaZT2d/Cy+k3or5k/iJE6cmtUVexNn83RpuZo63FRLj4MEwTxOzgTG6PmcxlPvFM8ksizS0MjURJjbadTRnLeDD+WgQIKOtrQmsx8HrJAQKVHrhKlM6WOj+5G+meEU6xpBRJmeibyAvFXxPnGsCavJ3EuQaxJn8Xqe5hPJm/m+Wnt9Bp6mdXzUmi1X6U9DRitJp5JPdTni/+Ei+5GqPNwvtlP/Hi+a853FzIS+lL8JW7sTFtCQJ++0JMdguhWd/Nq8NvIlbtz4bCvTxfvJ97YqfgKlGglsiJcPEF4LUL37Eq+yMq+1sQCYQkuYXwVUM2ZzvKCVN5AbCp9Hu2VvzM6rydWO02yvtbEAqEnO9pGPR/zTYrn9eedrY6jvKMpqq/le+b8thde5Kd1cc50VHK6yUHONVRRlFPnaNC6hYKwCsXvuXusx84DTku94mnsr+NO85u5YFz22nUdbG14ifWFXzOGyUHeDDhOgq6a3i68Au2lB9mfcoCAuRu2Oxgx87W8p/oNxuQiSSIhEJ+bM6nqKceoUCA3mJkin8q80NGAw73tYti6e0Ry1GIJHSbdJT2NVGnbSfN3ZGT02vW807Zj4zyiubLurPYsXND+HiEAiEroiYSrwnkoWHX4SZRMd47DnepiqURExjlFcNNEZfToOvEYrfyc0sRH1Yc4f5z2+k162kz9NJj0vFR5S9sLP6KNI9wHsjeToO+k6/rs4nRBPBzSxEPnvvYmcGmt5q4fUAsKURSRng4DDg+qPyZ3TUn6THpkA5smABoJEqS3EIo7qnnSEsRd8RMpryvmQgXH8JdfHgmdSG5XdXUaNuIcXUYZ5jtVu7J+pC+321+ACjEjvfOQ+pCn8XAzSff5r6sbQ5bc5UPfnI3BALBILEEoBTL/uECTiwUEaPxJ0TpyQiPSNanLGBd8nxGekYRrPQkThPAZT7xjPWOdf6NAAHvZK74zS3ObueZlIWoRDLajX28UPwVeqsJX7krD8RPY0f18UHVv7+CIKUnM4KGD7IOvyn8sn8ozFQiGVf4Jgw6Nt43DqVY6vxZI1XwaMJMpvinOts8xQIRs4Mc16whsfTviVwsZbRXDCujrxp0/LXhNw2JpX9DhgTTEEP8RVwXOJy3RtzCc6nXD1rs/iv8/gJ86c8eMhcEApz5TRf5piHbuQuut5go7Klngn8C++rO8ELaEu6JvYYnEmcjF0nwkWl4MX0JR1svcE/cFGp17dwVe/Wg+3so/jr21p2h0dDNgzkfU9HXDIC3wpUAhQeBSg++bcjhUHMhhT119F/S399s6EEoEHCZTxxBSg8Wh41DiIC1SXO4KfxyHjr3Mc8W7mOkVzT3xk2lTtvBCwPzW4U9tTySMINnU69nY9FXznahixWemUEjuC4ogzMd5cwMzkQpkvJ25nIyPCK4NepKNpX8wMzgTPbXnWW0VwzjvONQimUYbWZeLznA1QEpjPSM5v3Kn2g39jndF98u/ZF7s7eR3eXYYU90C6ayrwWzzRGyeunOYnZnJR4yF9ylKvyUbqxLms8bGUt5NPdTxCIxa/J2MzdkJEluIQDOSuAr6TfSbujjVHsZzYYeQlXejPeOA+B4WwlWu80R5Bt1JSfbSum3GOgcsGYHEABX+MaTMbBwfyzvM/oseq4NHA7ArtqTzhygK30Tudx3GF5yNUvCx5PgGgw43BmFCHg+dRGn2spwkTgWgS2GHn5qLnS2HZ1qL+PJ/N28cuFbAFwlSnRWEzOCR/BR5RGyOyp5NGEmJpuFo60XeK/8MM+nLmJW5VQYmwABAABJREFU8Aia9N0sPbWZfXVnmBqYNui8SnUPw0Pm4jCZUHmxdeRKqrVt7K51VIouLlRX5+3kct94bomYQLiLD2+Wfk+8JpBX0m/ER+6Kq1RJpIsvH42+k3khI0nzCOfn5iIm+ydxz4CTZH53Lb1mPW4SFW+NWMaGQofADlZ5kt9dS72+E5lQwhsZN/Nx5S/IRVKmBKYRrwnkqeR5yEVSAhUeKERSNmcu59nU65kdnImbREmsJsC5qQEOh833yw/zU0shAF83nKOsrxmb3UazvgeNWEGEiw+jvKIJd/FhrFcMmzKWEqby5umUBShFUv6MMBdv3s1cgUIkxWSzYBsIEH4l4yZ8Fa5/+jf/LP4KdzaNWMZTyfPwlmvwlmtYmzSXt0bcgpdMQ3lfC2c7Kpy3t2Pn/Yqf6DL2O8+lE20l3HyJ+yc4nCK3lv9Mg64D218omC6G+D5b9OWg408W7KG8r+Vv/i+9xcSJ9lKeKdwHgHDguryp5HsONRXQb/5tdslbruGRhBnsGb+KT8bczZ7xq7g3buqg2csh/v1oNnQ7q9kXeaPkwKAW8yH+PRgSTEMM8Tdo1nfTafxt0dpm6B3UngMO1755oaN4Jf1G7hgIuB3tFcObI5bxbOr1zpaPfxbTJda4AOZLfu4y9vNM0T5Od5QBjqwgjURBl0nLbWfeo1nfzemOMm49vYUt5Ye5OiAFk83CIzk72Fx2kPXJC7DicDm7NiidLqOWeE0An1U7MoViNQFM9E3ko6pfWBF5JQqhBIBDzQXOoWelWIpCJCVK7ctwjwieLvgCO3biNYEEKT0w2Sysyv6IuSGjuC3yKkZ4RnJX1oc06LtYX/gF5f0tzgDSpws+p0HfyWO5O1iTNIfingZOtZfx+oXvKO9v5sG46WCzE6H2YWX0JBaEjsZX4coYrxgSXYPZNe4+YjUBJLgFoxYp2H/5QyS6BaOWKFgVO41es46NqYu5zCeeJxJnU93fiqtUyazgTI61nue+uGmM8ooGcLoVrk2cg91ux2i3sq/uLPvrswC4xj+VQIUHRpuFe7M+pFbXgUos53LfeFxEMm4Iv4zjrSXUaNtQiKSDFmLg+NJNcAtiTeIcFoePY3vlr4z2jhl0m9FeMXQY+pjkn8yL57/m7dIfnAtUD5kLFX0trE6chWzgfXn1wnfMCRlJqMrbeR/uUhXLo67k5hNv06rvwUfuSvMlzos27JT2NdFl0qGRKHk74xbWp8wnSuOLCBHLIyfydPICbomcSLTajwyPCGYGZSCw25GLpBxoyuXH5nxOt5dhtdv4oPJninvqKe6uRymUoRRLSXYN4Qq/BO4++8Gg5/dzSxHbKo5gsJoxWMx4ydXOnKHpAel8ffkjztmz/fVZpLiHoRTJECNEKBTiKlVQ0ddMSW8jH1Ye4ZFzn2CwminrbUQllrG+4AtGeUUP2qwIU3nTY9ZTq2vnusDhJLgG8/L5bwCYEpBKnbaDrxvP8XrJdywOG0eUiy8SgQhvuYb1KQv4YNTtxGgCcJUquT16Mu+PWkm8ayCKAZHTrO9GZzHwQ1MeADeGX86+yx7kdHs5Wyt/5uOqo/RZDAQrvbjMJ95hFiEU4a9w593MFYz2jEYu/nPBZLKaaTJ0D7om9Jh19Jr1f5g9+4/gr3AfdH3ylmvwU7hRo23jrqwPnCG4c4JHArCv7gwfV/9Kr0mPWqxgnE/cH0KzXzz/FbdETeC6oAwk/8De/F+hz6zn3qyP0FtN+MhdeWfEcjxlarQWI6uyP/pDi/JF9FYT75Ufwo6dVPdQDkx8nHEDGxUfVh75w/VWKZYRpPQkRuNPoNIDxd94b4b496DN0MvK0+85K/NLI65AgID87lqeyNs1aFNriP/7DAmmIYb4E+p1ndx6egsvn/+aTmM/bYZeHsvdwUPnPvmDaNJIlIz1jnW21ynEUjI8IpyLEaPVTIu+G+3AItpmt9Go66Lnd9keLfoevm045zzeYezji9rTl1iPy1kcNh6xQMRTSfO4Leoq3s28FY1EwbSAdEQCIS2GHuzY+bmliNcvHGBV9kfMDs5kdeIsVCIZKW6h9Jr1mG1W9DYTnSYt/go3klyDWRU3jQzPCJJcg3mqYA/hah8UIilX+SfzWfVx6gdmlTxkLkwNSCdE5YlaIifFLZT746fx2vCbiXHxw0umRoCAeNcgpxjbVvkz98dPx1Om5vXhN3OVfzKvZdxMXlcN80NGIxGK8JS6cKSliIr+FgBcZSoOtxaxJm83US5+eMscr6evwo0U91B8FW6IBEKHo6F3JN5yDSqRjHSPcJqN3YgEQp4p2sc47zjuPLuVLpOWm0++jZdMzQTfBGRCMcYBkweFSIpMKKbN2Eu02p9olS+jvWNwEcu5KfxyxvvEsTFtMYEKD0Z7x+A2YDGstRjpNGmJ1wSS5h7GK8Nv4o2S76nStiISCJ1i5rmiL6nqb8NbpsFNomSSfxIvFTsCRy/uem+rPILWaqLfrOe+2KksChuHdkCoCgQCxnjH8k7Zj86WpMVh4/i19cIgy/Quk5bPa09xV+w16Gxm7hrIxVKJZc7MozdKDhCl8UUlluEuc2Fj0Vc8V/Qlo7yjGO8Tz47qYzyS+ym3R08mVOVNqMqb0x0VhKt8uD16EgCHWwr5dGBG6QqfYWR4RvJTaxFqsYInkmfzdX2Wsw1vz7hVLAwdA8AXdafRWoy0GHuo13bwTMpCFoeNY2pgGtXaVu6KuYaZQSNYFTcNm93G9spfuCd2ClqLgfzuWrQWI1KRhH11Zznf18iD5z4mu7OKPbWnuCHiclaeeQ87dudrmttdzY7qYzyROBu9xTRoVujL+rPobSamB6SzOmEWm8sODoinA7QaepGLJESqfZ2Vr3ZjH8tPvcs7ZT/SZdLSrO/mvqxtPJm/h/dHrWRl9FUsCR9HgNKdzZnLmRGUwaq4abhJVQgEAtykqkEGD+4yl78rls51VbMq+yOsdhvBSk/cJCr6LQZuO73FaQTxX4G7VMVY71jnzNLtMZNZHjnReZ1RS+QYbWYezd3hbMN7InG2sz3vpeKvnVXNvwoXsZxXht9AiNKTzZnLGe4ZwebM5QQrPXkp/Ya/acogEYpYlzSfaQFp3BI5EavNyl0xV3Nt4HBWJ8xCb/3ncpqG+PdEJhQzL3S0c2ZpaeQENqYtQiIQsSzyClxEQ62a/04MmT4MMcTvMFrNfN+YxzNFewG43GcYHcY+CnvqECBgU8ZS4jQBWOw2p0gyWc3orCZcJcpBbXRGq5l2o8NMQG8zkeYejsFqpl7XjsFqIc41AH+FO22GXlZlf0RpXxPLIyeyIHQMzxd9yeGWQib6JjostmUumKwWesw6lGIpKrEcu91Oi6EHuUiCm1RFn1nPtw3nnO1U14eORSNR8HVDNq+m34QdO5XaVjYWfcmTSfN4v/wwN0VcjqdMzT1ZH6Kzmng8YRZeMhfyumqZHpjO7tqT7Kk9hZ/cjQ9G3Y6XXE2fWc/Z9nKCVF4OJ7SakyyPvhIfmYZGfRebyw5yb9wUJEIxD+d8Spp7GKsTZmGwmVGKZM6Wps4B2+KNxV86h7JVYhlai9EhDJPnkdtZzcqYq9D8Dfvli/SYtDySu4NznVWoRDJeSl+CUCBkTf7uQSL3Sp9EVsZOYmPRfrI6K9FIFDyXcj06q4k1+btYEXklCW7BCBCgFsuwYefLuiziNAHEaPwdC1+BEKPNwuHmAhp0nYzziePL2jPcGj2J1Xmf0aDv4tmU64nTBPBs0T5Od5TzUPy1xGoC8JW78mDOJ5T0NhKrCeCltBvYWLyfY20X8JZp2DpqJfldNRxtPU+bsY8NKQtQiWVsr/yFDyqPAPBEwmzEQhFPFewBYIJPAi4SGV83nAPg7phrGOEZyZr83XQY+3h1+I0IEbK57CDnuqp4Jf1GghUeVOvaeSz3M4w2M35yN9ykSi70NiJAwCPDruNUexligYgJfgl813CORxNmOh87OBay74+8jSUn3uS+uKlMDUjDRSKn3dDHGyUHWBY5gTAXb9oNveysOUGKeyifVP3KWO9YxnrH0mzoxmi18FjuZ/gpXNk0fBkdpj7uydqGWCDk7czl6Cwm9FYjD+d8iq/cladT5tNn1vPguU+c1u4roq50ikU3iYoX0hZztrOC98oPIxWKeXX4TWws+pIYTQDLIifwYvFX5HRVoxRJ2Tb6DjRiJbtqT/Bx1a+M94rl+vBxFHTXMjUwDU+ZmgZtJweb83m7zNEOO9E3kar+Vqq0rYgFImfej4vkt3m+PrP+X3ZXa9Y7hL67VElRTwN3nt1KmNKLVzJuQmcxcduZLQgRsHnkikGVxb+aDmMfFpsV34H5oB6TDqPNjLdMg0AgwGg1k91ZyQvFX/FU8jw+rjzK7OBMni36khfSlhDnGjDI8v3PsNvt9Jh1g66ZXSYtKpEUqUjyh9tbbFanCL9Il0mLRqL4m//LaDWT11VNaV8z75YdwlWioMesZ3nURLLaK1iTPAcf+X+uvXGI/9v0mnQYbGa8ZGqEAiEGiwmt1YhaLP/T83SI/338s9pgSDANMcSf0GfW83V9Nq+VfOc8JkDA82mLSHML5XBLETuqj/HmiGV4ytTkdFazNn8Xb4+4xRHWOrAAqNd1sir7I6YHptNn1jPSK5rtlUfxkqlJdAvm6/osXkhfgkQg4p2yg3w50KLkKXWhY6Dc/2D8tUwJSP27i69+s4Eesw4BAtqNvSw//a5zV2zZqc0YbWb8FW4sCb+MV85/g9VuI809jAWhY1idtxORQIjJZsFbpuGtEcvYVXOSDmMft0RO5JvGc+yqOcH9sdMZ6xODTCThcHMhr174lofjr8VoNROg9GRt/i4iXHxZGT0JkVDIk3m7EQlFPJE422E0MWB08HvqtR0sO7WZbrOWxxNmkugWwuO5n1GtbWN2cCZeMg1+cleHscUlC1KD1YxUKEIoENJu7MNoNSMUCFl+ajMLQ8eQ6hHG2fYKZCIJrw+8j9FqPx4dNhO5SMKa/F20G/t4J3MFa/J2ohBJuTniCjQSBR9V/kJlfyuvDr+R9QV7Kelr5MmkuRxqLmC0VzS5XTWM8orGTarCZDWzu/YU2Z2VuElUPJd2PT0mHV/WnyXCxZcpAak06roQCQRsKT+Mt1zDXTFX83HVr1zpl8hT+Xt4IH46OV3VLAgdw4GGHDI8I3nw3MeoJQo+GLUST5maNkMv92ZvY4JvAjOCMgBH5cpFLOfWqKuQCEXkddewp+YU98ZN4XR7OZP8k+gYaOvbUX2M64IyHAPsdjs2uyM0+Kbwy1idt8tZuRIg4Onk+UiFIh7J3UG4yoeXh99An9lAVkcFm0q/H/T+TfJLYpRXNDFqf6I0/s7Fa49Jh6tUidVu40JPI2c6yhzGF/XZTA1M5ZnCfdwRPQk/hTv3Zm/DYDU7qn4DbVLjveNYGT2JF4q/4vqwsTyZvxvjwDm6Imoip9vLOTwwNyRAwOfj72dnzXHGecfx8vmvmeibiIfMhWi1P40DLaHp7uHcHjOZDmMf3zflclvUVbQaejHazPSYdAxzDUIoEHLzybcx2szcHj2Jyf4pLD/9LjODRmCz2/hwQLSCwxhgU8ZSktxCnJsAJqtl0IzT73/+WzTpO3njwgF6zQbWJc/DbncEXFvsNkJVXvgp3Kjub0Mg4L9ULP2zGAc2ieRCMb0WAyKEiITCvytgLmK2WqjUtvJwzic8m3I9XjI1ZpuV+859xMPx15HqHvqXLUaNVjNZHZWsOveR81i0ix+vZtz0l4slq82K6JIq4u9/HmKIIf7nMeSSN8QQ/wnUEgXXBKTieolICXfxJt09DJPdyqsXvqVO18FdZz8gr7OahwcyGV4s/poes6OlTmcxsrf2NDXaNt4q/QGr3ca2iiOc7ijj28Zz+MpdidMEIkCAu8yF26MnMT0wHcAplu6Lm8pkv2T6LQaq+ltp0ndhsg7uu6/VtrM6bydP5u+mpLeRR3J2AI75p+eL9zvDTpv03bxY/BVWu40YtT+PJszk7dIfsdptmGwW1GI5b2TcTHF3PeO8YxnnE8dNJ9/CXaritfSbSPEI5YYTb7K1/Cc8pS4IEJDTVc3VAanorSbMAyF/r5d8x5q8XXSY+tFZjLhKlAQM7FT/2XB2kMqTd0eu4KmkuWjESm4/8x73xU1lZfQkhntEsKX8EE8XfsGFgaoGOIa5T7WVUtbXTLuhl2cL97H89Lv0mXVsHbWSRn0Xd5zZSopHKEdaigDwV7hxT+wU7sn+kDvObuXp5Pm8lLaEBl0HVf1tFPXU82HFEbZW/MSJ9lKaDd2c721gkl8SAgSsK/icJeHj+aEpnyn+qWR3VNJr1uEjd0U00AJ2S9QEfKUabHYbp9rLMNksuIjkhCm9eSR3B6V9TRxvK2FP7SlmBo1gbd5u+iwG1hfuZW7wKMxWM1cHpGC120h1D2NL5q30mPVkdVZS0F3LmsQ5uEtVdJm03HTybe6Pn85t0VdhsVv5qOoXTDYLa5Pm8GvrBVwkcnbVnKTN2MtDOZ9wU8TlFPfU83bpjzySu4MYjT/TA4cT7uKD/yVOY0qRlDCVN0FKTx5LmMnzaYvABs36LqdYusoviRvCxgNwsLmAVkMvwSqvQQtl14G2xV6TnheK9/NO2UHuzdpGrMafZwr30WLoYWPxVwQrPXkr4xYAp1hKdQ/jmoBUbjz5FnndNZxuK+W14TcjEYi43HcYPWa9UyyBw5Tg4ZyPmRGUweayg7Qaexk/MDP0XsVhhAhYlzSPO2Imc9fZrWwq+Z7boydz/7ntfN2QTa9ZT5pHOC8Wf02Nto3LfeIBeKfsIHN/fYUOYx/fNmQzOzgT2SWzObEafyLVvk5B1GHsY3ftSWcbbY9Jx1f1WbTou/9w3l9Kj0nL4eYirglIw2Azs7vmJFldFXSZtBxsyuN8bwNmm5UwF+//72LJYDHRaexHJpLgLlUhEYqRCsV4ydW4S1X/WCzZrHSY+lmdt5MmfTd3Z31IblcNd2d9SK22nUdyPkV3Sauc1fYXmEcI/u6Pfwk9Jh2HWwqdZgB6i4nTHeU0/4P3/l+hz6wfFEpstJr/0No9xBBD/NcwVGEaYog/4eLMUn537aDjk/2SuT9+usNd7uwH3B49CYFAgK/cle0VR9mYtoii3nqGaYLwV7rTMdDTf+niDuCe2CmYrRamBw13zjp1GPvYWLSfI63FztstjbiCJLcQHs/7DIPVjFwkYX7IaK4PHYunXE2zvgu91cy+2jN4ydXoLSbG+8ZT0tvISM8ofmk9T6epH5PVwmc1x533u3XkSow2Mw+c+9jZxy8RiHgncznBSi/K+5rYWXPCmUsyNSCNIy1F6KwmvGUa3ht5Kweb8rk2MINqXRuf15xkpFc0zxZ96XSVU4llbMpYRrjKG5VETrdJS05nFanuYU475ksxWEx0m3XcnfUhs4NGMCUwHYvNwobCvbiI5dwfPx0PmQtmq4VTHWU8eO4TQpVePJd2PctPv4vWYsRTpibNPYxDzQUAzAsZhatEyc8tRTw6bCZ9Fj0fVh6hoLsWV4mSVLdQJCIxmZ5RPHfJYwe4I2YynYZ+Jvol4iN35aeWQuzY+ab+HG+MWMqptlJcpUq2VRxhTdJcarRt+MjUWLHTbuzDXaJCKBCglig53V6GQiRlmFsQPSYtVrudjUX7eWDYdEp7m3i3/BAhSk+eS13E3Wc/wGiz8HzaYlzEcu48+z5Gm4WnkubxVX0WZzsrHOePzcK7ZYeZ5J/EMNdAXh3IuloZNQkEsLnsIAD3x02jqKceD6mK+aFj2Fl9gst84thVfYLFEeN5u/RH8rprAEelxo6dAIU7L6YtoVHXyd66Mzw07Dpqte3OCujUgHQu9DVgsVk501HOxtTF+Cvd/+bnqUnf5VwQX0QhkvJ08nzcJErK+1vYWLzf+Ts/uRsvpd9Ag66DN0t/4JW0G9HbTKwr+JzHE2dxy6nNAIz1juUqvySeKdyHxW5lom8iIzwjeeX8N7yYvoQPK47QZOjmnRHL8Ze7UatrY+WZrbw6/CbO99bzQvFXAEzwTaDd0EdBTy0ihHwy9i5ePv+NM5tII1GwddRKHjn3KZXa1kHPbXpgOnfHXIMNeLZwH7+2nWeCbwKPJ8zi0+pjbKs8QrSLH69l3PynJjCOFuBcninah0woYUPKAnrMOp4t3IcdeCn9BjI8Iv5HGBAYBkTA3rozrEmcjZtURWlfE88VfckLaYt/sx3/O9TrOrg/ezur4qaxruDzQYPzMqGYV4bfRIyLP64yJd0mLcdaLzDaOwbP/4Bb3cXWwQfOfYzVbsNbpqHD2IdtwKjmxfQlf0mVqcekY0/tKbaUH2KsVyxrk+Zwrquax3M/I0zlzesZN/+nc6n6zHq+a8zBS6ZmjFcsQoGA7M4qzvfUMzdklHODYoghhvjXGKowDTHEfxCj1cyBxhzyu2sRIODZlOu5N3YqAD8251PQXUusOoDnUxdRrW3jtQvf8XntaV4cvoSznZU8lvsZd2d9QLO+G3epigeHXYf0kl3pNPdw/BVuFPXWOysuHcY+Xiz+2imWQpSegMPJ6UxHOUsGdvMNVjPbq47ybvkhekw6LvQ28lzhPqYGppHsFsoo7xieLvicWHUAVruNMKUXwzRBTuvmizyR78j9UYpleMrU+MndMNut3HF2Kxd6G3i3/BBX+iU5HaW+a8xxiqXNmcsJUHqwMGwM7aZe7j77Aed7GwlReSG7pPXIU6ZGJBDyQ1MePSYd2yqP8EjuDjaXH3K6v12KXCzFT+HG5szlTAtMx02qxEuu4YnE2dwfPx3NQLVPIhITpvLmKt9E+ix61hd8wfpkx5xPh7HPKZbmBI9kRlAGpzvKeDb1enwVbihEUm6NupJ4TSA9Zh2/tJ3nl5bzjgwalafzsbhLVYz0jOb7plwQwNq8XUS4+FCv6+T++GksOf4GNuyoxDJajb2sL/icYZoAhAIR92Zt4/HcnXQOhBXfl72N10q+o9us5WjrebpMOs50lLMqfhofVPyM1mLkjujJ1Oo6WJO/i5eH34jZbuXBc9tZeWYLEqGYUJU3XnI1Nbp21GI5qe5heMnUXOYTh8VuI8kt1On4t7n8oFMsjfVyVArj1AFMD8ygQd/J5b7xeMk0SEUSOk1a53m+LmkemzOXIxNKaNR3caK9lAClB0siLqOkz/H+zgwewTifOB7N/ZQPKn52zGCl3/B3xRKAm0TJ6oRZg44tChtHv9lAbneNUyzFaQKQiyQ0G7p5KOdj3GUuPBh/Lf1WI3dnfUBFfwuHmvK5M+ZqRnlFc11gBqEqL15MW0KM2p8ZQRnsqjmB2W7lkZxPWRQ2ji0jVhCs8kQsEhHu4svu8fcRpfZlsl8yd0RPBhwOfgU9jtdhbdIc+i1Gqi4x05gVnMn+uiwqB2aW3sxYxsoBA4xvGs5RrW1DLpIwyivKeX/zj73KtoH2vVSPMMSCP2/NkokkjPCM5NpAR8bQIzmfcr6ngXmho4nR+BPp4vs/QiwBdJt1PJLzKSfbS1lX8AUF3bWsPPMeJb2NPFO475+qdhxvK6Fa28b7FT/xWMLMQb9bEXUlPzbl8VnNcXpMOrZW/MzThV+wsXi/s2r3r2C0WajRtmO124hTB7Bt9B28nH4jQgS0GXv/4JL3H0UkEOI7ILyOt5dwy+nNPJ77GXbsuEqV/7Dq9o+w2qxkdVTw8vlveDx3J8faLgwIwe28W36In1oK/7LnMsQQQ/w5Q4JpiCF+h0wk4drA4VwXOJzn0xYxzjuWa4OGsypuGiujJ5HiFkp+dy0/txQ5Q0qzOytZdmoz6wu/ABwhixKhiFZDL0/l7x70ZZbTVUVlfytBSg82lXxPq6EHu91Ol0kLOGaWto66nZlBIwDHYPPvdw+/qs9CazFyuq2MReHjWHF6C3tqT2GxWbkvbioP5HzMM4X7iND4OUNRo9V+PJ0839met6X8EGsSZ/NWxjLWJs0hSOmBUCBAIhRhslnoMxtY+ruclav8kvAY2OmViaR4yNRMDUjj8cSZPJ7rqIKJBSIECKjVtvN80Zd4yTXck7WNHdWOCpdCJOHvNcV4ytRoLnm+XnINYoGQQ80FziBgL5mGawJTeSp5nvN/prmHDbqfRWHjECPklsiJHGjI4WBTHq+VfIeXTON8rcUCEWuT5vDC+a8GVT+6TFpeOv8V7426jf11Z8nvqeWhc5/gI9OwOm8nPWY9m8sOEqz0YkPKAmq07bx24QBSkZhItR927KzO28nNJ9+mZSD8dJhrEMfbSlibvxtvuYZtlUco6qmn09TPFT7DiFL7cU/MFNRix9ySAAEuEgXPpCzkudTr6TPrSXYLoc9ioFbbhqdMjUQoYrRXNPvrz/JQ/LX4yd2cz8FP7sayyAl8VnWcsT6x9Fv0PJqzg1XZH9Fp6sdP4cqRliIeHnYdD8RPp17XgUasYEPKAm4IH89or2gUYikbi77ksdzPyO6qolHfxTOF+3gg/lqeS11EnbYDmVBCn1k/yILfYrPQbdI620dbDb2syd896P3ZXvkLAUp3RwgrAkZ7xbAi6kpeSFuCXCRBIZLRbzYgFgip7G+h12zATaJieuBwRnhEMDUgjafy92CyWWk39HJv7BQ8BgRWgMIdi92G0Wbm87rTtBv6sNgstBh6EAqEyEQSNFIl0wOHDwpeTnMPI1rjz6O5O+gw9qESy0h1C+OTql8Jd/Fhsl8yrwy/kUTXIOYGj2Rl9CSeSJhNtNoflVjGNQGpPJ4wCyEC5zl2fehYlkddibtscHj1RbpNWj6tPsYE32FM9ktmbsgofOQaNBIFqxNm8VLx17QPnPcX6TD20T1w/+CocPxHBMW/iloiZ23SXABOd5Rx25n3MFgdhiGPJsz4p6ocFX0teEpdWBE1kdcufDfodx9V/sIVvgn80lrMTSffYleNw2UzSOH5HxIdGomC6YHpjvbb4TfgLdeQ4RnBa8NvZnPmCoKUnv/4Tv4JXCRyJvgmsDpxNuCYXbVjJ9ktlGdSFv7L8RK/RyQUkegWQpp7uPPact+Ag2KM2p8x3rGDNuWGGGKIv56hlrwh/tux2KyYbBZkIsl/euftv5IuYz8KkdRp/dtn0mPDjslmYcYvL2KxW1kacQV+CjeeuyRQMdMzinXJ81CIpLxbdsjZCndr1FVc6GngaNt5AF5Ov4Gv67NZHnUlQUoPtBYj+V01xGkCCVR5UNPfRnZnJXbgheKvBrWLAWwavhR3qYqTHWXO0NIMjwiqtG3Oxd57mbdS3t/Cx1W/cnv0JHbXnmRx2DieL9rPC2mLsdptHG4uYGHoOPQ2I+3GPlr1PQQo3BEJRdxx5n20VuOg//vwsOu4xj/V6QjWZujlSEsRL57/GhexnM2ZK2jUd/Jozg4EAkdQ6gcVP3O+t4HrQ8ewNHICbpc4XfWbDXSbtHSY+rHZbQ7BJFbQbOh2zAcJhHxRd5rNZQdJdw/nmdSFFHTV8kjuDsc8TMr17Kk9xc5LWg7BIbzeGXELVpuN4+0lfFJ1jKdT5vF80X4a9V3IhBKmBqSR4BbEhkKHI+JFG+in8vdgx86quGmM8Ijg0bzPBgmqK30TuSv2Gmw2G3qrGZPNjEaqxGKzIhQIeCJvF6V9TYDDNnzLyFuRCEW8duE7crqqncdfSb+JLrPDtv7qgFSsNguN+m6+bcxhcdg4Ok19PF+0H5FAyOMJszDbLHxee5rF4ePYWLSfRxNnsvL0e8wOGUmQ0uMPC9CH4q8lTOVDp6mfQ035/NJ2Hk+pC8+nLebJ/N006ru4amBG60xHOU8nz2d//VkCFB7sqjmBRqqkw9iHVChmY+oitlf9yiT/JPK7amg19jIvZBQKoZQ6fQd7ak6yacQyvGVqinoauC9rGy+l30CEiw93ZX1IWV8TCpGUdcnzeKv0R2q0bciEYj4ffz+N+i7sdrgzayvxmkBuiZqI3W6n2dBNv9lAp6mPZLcwwl28qdG20WroxVfuhtVuo6S3gdHeMQgFQrykLtyV9SGPJ8zCYreyq+YkJ9tLWRpxOaO8Yrg760NujbqK2cGZdJu0PFmwh4JL2m7lIgmvD1/K6xe+o0bXxvrkBVjsVg41FXCktZgtmbdyrPUC88NG4yZV0WPSIRIInZ+FHpOOJn0XpX1NPFu4Dy+5hmdTFuIlUxOg9PjDNcZgNbOn9iSbSr5HJBDyWMJM2gy9vFt+CIAX0haT3VFJtMafqQFpiIUiOo39vHr+W/yUbiwJG48A2Ft3hoLuOh5PnPkfal37V9BZjLxRcoC9dWecx74Y/8CgCu3f47uGHHzkrrx0/isq+1uRCcXcHjOZ7ZVH6TT1o5Eo2JJ5K4tPbMJqt7EodCw3R14x6Jrxr2K2WQdZyv/+578CvcXEsbYLrM7b6Tw20jOKJ5Pn/WXhtx3GPm45tZnGgWw1D6kLn4y5C6//pCAbYoh/Z/5ZbTC0JTHEfxtas4F6fSe7qk/QaOhiuEc4UwLS8Fe4/48UTr+fs1FLHS1hOouRxxNmsaP6GDOCMjjTUTHodja7HbvdjlIsY1H4OM51VjEvZBQaqZLLfeKdMyIuYjlzQ0YN2Cab0FoM/NxSxKsl3/HOiOXYgdMd5RxpKf6DWAIw2630WvRM9E3AbLOwpfywc+ZCJZaxPnkBGwr3sj5lAavipmK2WRnjFUtZbzObRiyl3djHE7k7aTX20qTvZrRXDB9X/0plfwufjrmbF4r3o7Ua8ZFpeCdzBZtKD3CkpZhNJd9zuc8w5yJRJpJwtX8qNruddI9w/OSuBCs92Ji2GJvdxpf1Zznf2wCAn8J9UGtSr0lHfncted01fFT5C0sjriDMxRsRQtbm7+aagFTujLmaEKUnAgSc66pi6cl3aDH0IBWKeSxhJt0mLXsGWg7nhYxiom8iD+Z8TIexjw8qjjAtMI0IF1/kIgl2OyS5BrMhZQE6iwkbNuq1ndwQPh4fmStKsZwUtxDWJs6hoKcOD6kLarGCh4ddx11nP0AmFDPCM5IpAWmszdvNbdFXIR6oWDyS8ylrE+ciFYnpNv/WmmTDTqO+i+KeOh5JmMnCY68hRMDzaYsRCmBdwefO28Zo/Hk451NMNgtuEiUeMhenuBMJhDQb+rg+fCxqiYJE1yBKe5t4LHEWdrudZ4v2ATDCIxKAs50VvHj+ax5PmMXxthKmBw1HZzVxf/w0Djbl02vWIxaInC2MUqGYF4r381rGzeyoOsYjCTN4ruhLRAIhWzJvxWa3I8BOqMqbvbVnSHAN4rvGHCJcfPmm4RwTfBI40JDDjOARvFT8NVqrkbuzPmRN4mzujr2GZwv38XTyfEJVnryZsZTNpQcZ5xtHjbad7xrOcWfsNajEMgp76thUcgAXkZyXh9+I3mrCYrPiLddgtlr4tfUCb5f9SJJbMCqRjFMd5RxtvcDsoEzsGn8sdhuBSg/cBswx8rqqmRqQzvaqo5hsFt4s/R5vmZoabTsFF9sRk+dRr+1gS8VhVmVvY+uo27HYrZT1NrGhcC9vZCxlYdgY+sx6Mr2icBE78lcuraj0mXSU9TXx4LmPGekVzfNpi5CLJKzO24mH1IXnUq//g2iSiyRM8kvmx8Z8SvoancIdHEHGRquFy32HEa32RywUYbVZOdVexg/NjqBcq92GUiRjy4DA+qk5ipnBI/7S0NhLsdisVGvb+K4xZ9DxF89/xdrEOf/Uwj3NI4yNRfu5Neoqnincy+rE2RxpKebJpLk8XfA5t8dM5qOqX7AOtCtLhOJBYcT/EX4vjv4rxNLJ9lKeyNsFODZrOox9nO4o55mCvaxOmv2fFk1Gq5mS3iZaLolI6DJpye2qZqx33P+Yts0hhvi/ylCFaYj/FgxWMz825Q1aEIBj8HvLyFudoZr/G+g2aTnZXkaCaxDZnVU8N7BQ9Ve40TTgiDTSM4onk+biJdfQaexDJpRgslm4P3s7s0NG0m3SUtnfwqzgkazN34VUKKbLpKXHrHPusHpIXbgzaysmm5UuU78zzd5TpiZG7cckv2QClO68UfI9TybN5bGcHSwIG8Mr578hRhPA0ogrCFJ6kNtVi4dMxQcVPxPu4kOsOoBWQw+p7qFU9LfwzsC8y0VGekbzVPJcLDYrzxXt5764KciEEix2G++XH2ZB2BgC5e4DgahyNpUe4PboybhJlJhtVrZW/MS0wHTqtB183ZjNqfYyZ/4JOKoeUwbyes51VFKja+dke5nTzW6kZxRnOyqwYSfRNZiNaYtRiWUcayvhiUt2b4dpgliTNIdfWovxk7uS21VDrMafvXVnuT16El/VZ3FL5ESyuyr5oTGP++Km8m39Oa4OTOHZwi95KX0JH1T8zJLwywA7MoEEiUjME3k7WZ0wC7vAcX5abFZuO7MFi83GMykLidL4MefoyxhtFmI1AayIvJJ1BXuQCMU8k7KQpwr2ONvwfOWuVGvbECBgQ8oCLvQ2OLJ+vOO4bMCJ7UR7KT8PPPeLBCs9WZc8jwfOfYzOYuL5tEWEqbyo0bbzSM4Owl18WJs0h16TDolQjNVu4/niL/GRuzI9MJ04TSAvn/+aFkMPd8dOYW/taaeQeTFtCRqpnCZdD11mLWvzdiESClmfvAAfuSvuEhV53dV0GPtwl7nwec1p7oubyrmuSkZ5RuMt09Bo6KbbpMVVomBD4V4eGnYdHcY+0jzCEQuEWOw2Hsjezi2RE1GJ5Xxee4qlkVfgKlXiJ3ejxdBDZX8LfWYD6wo+Z+uo26jWttOs7+adgawjgJsjrmBx2DinMOkw9vFwzqcUdNcywTeB26Ku4v2KnzjUXECCaxAbUxdjx7Eg9pC5oLUYMFotCARgt8PrF77jQFMuQgSsTpzNr20XmOSXxFjvWHrNevbVnUEkEBKt9uP1kgNM9k8h2S2E6v5WvmnMIUjpwT2xU/CUqmkxdOMt16CWKDBZLTTpu/i17QJvlBwAYLRXNBX9rbQOnAvvjbyVmD+5ztnsNloNvSw5scn5GY9w8eHhYdexLv9z3shYSqjLb854XSYt75cfZk/tqUH3My0gnbtjr3Fmw/09TDYLVpvtX15kN+o6WXj8dWcb3vTAdN6v+AlwZFM9mjDjn6oEVfa38Enlr9wQcRnPFu6jStvKWyNuQSmS8n7FTxxozMVHpqHV6GhFXBYxgYVhY52B0f/T6DZp2VZ5hB3Vx0l1D+P51EUca7vAhsK9BCjceSdz+T9liPG3sNis5HZVc3fWh472ahc/5CKpc+7uhbTFjPaKHsoFGmKI/wBDFaYh/kfRYXS0Fv0evdXk2MEdvvRv9vhfSpexH7PdhotY5siT+f+AAAF6i5GDTfnOuYFRntHcEjWB4p4GXr3wLS2GHiwDO6QeMjU2u42Gvi6qdW3OOSeAdI8I0jzC+XYgcFQjUfBu5q2Eu/ggEAh4MW0JdboOrHYba/N3IxdKeDJ5HhqxHL3VzLbKI6yMvornCvdxT9wU9tadYV3yfF658C1qiYLXLnzHiqgr2VJ+iOKeei70NDBtRBr53TUIBeGEqLxJcw9ztolJhWI2pCzAVaqkx6TjjpjJNOm72V51lNLeRraMvA1XiYKtlT+T5BbC/rqznO2sJNkthAk+CbxbfoivGrIRCoTMDM6gsLiORWFjWRoxgWeK9nKkpZhjbSVM9EtEaBGyveoop9rLeDxxFtjtHGkt5nRHOQDxmkCeTb0eb7kGg8X0h4FLkVCIRCgiROlJeV8zfgo3Ng64nllsVh6IvxatxcAbFw5gw84bJQdYFDaO+7I+wmy38uqF73ggbjqthh7yu2sx2S1M9ktmgm8C57qqiHcNYlX2R6S6h3F37BS8ZRreLv2R4Z7hPJ28gMdyd1DS28iDOR8DEKbyxl3qcMZTiKS8kbEUV4mS9YVfUNRdh9lmpU7bgQABmZ5RSIQiRzhqQBqthh6Keuqd78Frw2/i1tNb6DJpiXDxQYiAp/I/50JvI0abmV6zDq3FQFFXHYkeIazN283jibPosxgcuThmHbdHT6bLpEVnMXJ37BQ2FHxBs6Gbpws+Z0PqAtYV7iFE6cXbmcux2qy8U3aQLrOWl9NuwF3qQsvAbN3NkZfTZOjCbLOhtRgRCvu5O+sDDFYz65Lm8XzaYtblf87tMZO4/cz7LIucQLpHOM+kXs8zhXtJcw/nxojLqOhrYXJAsqOymbeT/O5aHoy/lm2j7+CTql/5vimX+SGjeSX9Ro61XWBv3Rm2VR4hwTWI8T5xCAVCPGVq1ifP5+uGc/gr3Fh8YhMPD7uOUJUX0wLSUYsVnOgo5ePKozyftgh3qZIqfRdP5u/mzYxlLI2cwIGmXGzYeaZwL68Mv5FhmiCUA9eT2cGZmGwW3is/TKO+i22VR4jXBDorpF4yNSKBgBpdG++U/sg4nziu8kui3djHV3VZJLuHcEf0ZN4u+5GT7WWAQ3S/NeIWItV+f3o90VmMnGgrcYolgBptOzqLibf/H3tnHS11nf//x/TMndvd3X25tCChoqSAlIQBiAIWFjZ2NxgooCiNIgaKiEHH5XZwu7vvne7fH3OZ5a7urrvf3e/u/r73ec6elbkTn5n5zMz7+X49Y+RKgv5sKuUhVbIq+mpOd5TTpOt2HNe98dP+poeox6imRt3BvrozqMw6rvFPZbR3zB9OcHMSy5gXMpqjrYW8N3IFnlJngp28eLXka26NnPiHi3ojnf24K+46ek1aHkyc5ehuejJ/L9k9NSwNH8/NkRN4v+IIBxrOU65qxjJQUvyfCHepklsiJxKs8GKCXyKeMmeu8kt2eBf/J2QJQCwUEaDwwE/uhotYwWuZyxBil/7WazuJcPYdIktDGMK/GEMTpiH8r+BYWwkP5u74i3/fP27doF3UP0e3QU1WVxXbq4/RbVST7hHObdGTCXHy/kOlkP9MmK1matWd/NCSj6tEgUwkJtolgDp1B636XuJdA0lwCx60CKnob2XV+T9FX/vKXB2LsAcTZpLbU8vR1kLClD68N2IFPnJXLDYrFf0t3HH+I/zl7jybthChQMC92dsxWMy8kL4Id4mSrxovcH3IcFaf30KfSUuGRzjr4qfzeMFe6jWdRCh9eShpFmvPb+W5tIXYbJDsEcL5zkq0FoMjjhrsmvgX0hYR4ezL2a4K3in7nvdH3MabpYc401mOk0hKinso57oqSXEPZVX01TRruynua+AKn3h21J4g2S0EH7krfnI3pEIxaR5huEuVdBlUfNuUw/TAYXjLXeg1alibtY0KVQtX+6eQ7hHOaxe/cRzLwrAx3BwxAWexnNOd5TwykDrlI3Ol06DCho0RHlGsT57Fc0VfkjdA+sDeXzUzKBO92UhxfyMP5+7CepmsMUzpw7r4afzcWkSsa6DjcW+PvhqzzUqnod++MzwwfRvnE0+7vp9yVTMigZBPxqzheNtFPqr6iTtjr6Wwt565IaMQAL5yN7QWI9815XBdYAZOYildBjWeEiUP5+9iacR4CnrqmBMyEqVYRoO2m8fz9wwKBrk5cgJgN8GDPVlxQdgYNhTsw0vmzDuZt9Kg7cJP7sZt5zajtRiJcvZnfeIs3in7Ho3ZwBMpc7HYbOytO82Frmo2jbiV54oOEKTwZJJfEo8X2OVDmR4RGG1mCnsbECDg9WHL+LWtmK+bslkYNpaZQcPYVP4DZzsruM4/jdtjr2F97g7KVa2IBEKUYhmroq+moKeOI60FCBFwd/xUjrddJKenBgECPhq1Clexgh6jhiAnT54s2EdOTw1gXzxXq9sAWB41iTiXQGJc/NlVewqT1cya2Gsdmyk9BjVPFuwnzNmbA3XnWBE9mX11Z7gmIJVj7cVsGXUHi069jcZsIM41kJsjJvB04eekuYeyNu5a7s3e7ghjuIQ7Y69ldshIXCUKNCY9/SYdOquRj6t+5YeWfMf1RnhFcVfsdeyrO8Phlnw2pMzDYDXRru/nw8qj3Bl7LSKBkIl+Scw78YZDUpbmHsarw5b+7uRFbzHyU2uRQ5Y5xjuGLoOaclULIoGQTSOWk+ERjvAyyXK/UcuBhvO8d9kk7tI5syR8HO5SJSqTbhB56TfqsGFjc+WPfF5/btDtAhTufDDytj+8qO81ajBazY447ktTvH9GGlyHvp9THWVM9Et0SCp/aS1igl/iv9yb9c+AyWoeJIf8o6XFfxTN2m5EQpEjka9D34/BYiL4D/rHhjCEIfwWQ7HiQ/iPgtn613cHrb/j0bmEPqOWd8t/4ImCvVSqW+k2qvm5rYhlp9+lTNX8F2/3r4LabOC75lwUYikqsw4hQir6WzjfVcn1wSMY75vwmx1bpViGh1SJl8yFzSNv4/XMmxjuGYlMKMFH7kqnvh8BAuo0HTyUu4N2fR+WgR19o9VCtaad9Xk7ufvCJ7Tp+9BbjQgQ0G/ScmP4FRT21LMufpqjTPamM+9Sr+lEIhDxYOJM9tScZrxPPMM8IhjnG4dUICZU6c33zXmAXQZ3V9xUnkqdx0dVP9Ok60FrNvJAwizeKj3EiqhJjPGORWsxOiZAae5hxLj406rv5eumbJ4s2MdNEVfiKXPmnbLveTx/L+5SpWOh6CVzYVHYWLzl9oWPUiRjuGcEk/ySGOUVzRsXvwXsEb03R05AJBByuCWfPpMOrdnA/QkzSHEL4b2RK3g0eTZigYiF4WN4pfhrB1kKGUi9eqv0O75tykEitEeQzwoePuj9eH3YMl4p/ppvm3KQCcVc7Z8CwObKo2yt+pmvGi/gJXPhtqirADjZUeogS29n3oIA2Ft/mgcSZlKr6eBK30TOdpbjIlFQ1NtAtaqVEKU3XjJnTraXUtBdg9qs570RK3ERK8jtqcVf7k6/SecgS8FOno5o8O3Vx3CXKHk78xYA8npqEWCfuoUovNBZjJzuKMNoNZPhGWE30Q9bikAgoLS/mRpNO88WfsGn1cc42lpIr0nD+a4qnky+gQVhY3CVKLgvfjoA2T01DrL0SNL1hCu9HQv0vXWnuTPrY84OTEtSPELRmY08nbqAcKUPFpuV/oHEwJXRk0l2C8GKjbdKv3OQpQcSZtJr1PBTWxH35HyCVCTmyZR53BRxJQAd+j4eSZzNaxlLiXcJ5PH8PVhtNm6Lnszq2CmDJs/OEgXLoybyVUMWL2YsZmnEeD4YdRtHWgqYHzoGm83GQwmzEAmElPU382j+bnzlrjyQOIsPK47SY9TgIpbz2dg7uco/GYAPKo7aC0FNen5qK+Ljql8RISTRLXjQORPt4o9YKKK4rxGzzcLThZ9zrK3E4R+q13RxhU8cd5z/yEGWAPJ763iz9NCgFMFLkA9sQHjLXJjgm8CTKfN4PfMm4l0CiVD6EqzwGkSWLFYLZ7sqHGRpamA6c0NGOs6ZX9qK6TaoePPiIUcwQI9BzSc1v9Ks6yGnu/Y3x9Ci6+Wz6uN/OJbaXaoc1F2kFMvxlDn/U3yoPnJXpgdlOL4zPKRKZgZn/leQJeA33rF/9mZeoJOngyyB/fUaIktDGML/DoYmTEP4X0GDppN5J9783fCCECcvNo9c5VhI/zmqVG3ceOrt3/1bnGsg72Te8rtFqP8KWGxWfm4tciQhLYsYj7tUycaywwDcGXsdM4Myf1de2KztwWyzEKr0Rms2UK/ppNekZWfNCdYlTKdJ282DOTsQCoR8OGoVye4hGC1mCnvrufPCNsciTC6SsGn4cj6vP8fhljz85G68Puwm8nvq0FoMjsQ8gBfTb6RF18PGsh94IGEm0S5+yIRi7rrwMa9kLMVqs9Gm7yXdIxyFWMrdFz6hQtWCr9yNF9IW8W75D+T21KIUyfh07FpuPPUOEqEIjdnA9jFr8Ze70zjQH3RpgXYJV/kl80DiLLz+yntTr+mkQdvFR5U/UdLXSIJrMC+mL+LLhixEAiESkYhZQcMp7K3neHsJS8LHs/LcZib4JjLKK5pUj1AezdtDmaqZR5PmMN433lEUvChsLEvCx1PQW8dTBfsxXSbpSXQN4taoSTxZsA+DxcSHo1axoWA/PUa1vQNK4sR43wQEAgGn28sY7RPD+txdXOWXzMLwsVSqWrnY14hQIGRz5VGECHgkaTY9Ro1jMftqxlLG+9onU236Prr0KnbXnWKCXyJX+SVTrmpBIBCwtfJn1GY9T6cuoE7TwfH2i2R3V/PeiJVIEHG+uxKRUEhxTwOHWuxm+wm+CSyNuJKTbSVEuwbiJXPGarXhJJHSb9LxQM4OzJc931siJ3CVfwq7qk8wJ3QUOd3VTA3KYPnZDxyy0iCFJ0+k3ECzphs/JzcONmTx40AgBMBrGcuIcPZBLpTQYVSxPnenw4AuQMDzaYtI8whj+q8vOW5ztV8y88PGUNhbT7JbCCKBEH+FO4/m7WFe6CgudFezOPwKtlcfI0zpQ7CTJ85iuf2//8JC0GS1oDLpUIilKER2D06XQYUAAV83XrCHRNisGK1mvqg/xydjVvNQ7k4eSJjJvrrTrI29jq8aLxDvFkhOdzXXBaYjsglp1HfzYvFB5oaMJNrZn1cu2uWdTiIp2oFy5xVRk7jGP5VH8nZTc1mB7QTfBFbHTOGbxmx21p1EIZLywcjbuNBVxcbywwgRsG3M6t+QsEto1nYjE0kcxKBN3wc28FP8tlS1U9/PhoL9+MrduCvuOoQCAVsqf+ZifxPPpS3k9ZJvOd5xkWAnTzaPXMWWqp/5suE8LmI57wy/lTsvbENjHpx8qRBJ2T9+3T+lxHUIQxjCEP6b8Ee5wRBhGsL/CjQmPTtqT7J1wCB8CZdkJ5mekX/xtp/Xn+WVAW/K7/59/H2EKr3/acf6t9Cm62NT+WEKe+sHkYRr/FO5LjCNCGc/gn8nQvjP0W/Scaq9lFjXQCKdfdFbTVzoqsJJJCPFPdSxO1mv6WT52fcdHodLZObhvF1ozAZ0FiPRLv68kLaIB3J3DIq/zvAI54GEmbRoezjaVsThljw2pMzDXaqkQdPJG6WHWBo+Hl+5K5P9k+nQ97Mmayu6gQXiJTyRPJec7hryeurYkDqP8v4WhMDF/mZOd5bzasZSVp//CMPALnWCaxCvDlv6Vxdg3QY1UqGYToMKi83K3rrTLI0YT2lfk0Mutjb2WoIUnjyWvwcbNlZGTabXpOXz+rMsCB3LorCxtOl7adP3kt1dg0Qg4ir/ZDqNKrwkzgQpvVhw4k1MNgthSh9mBw9nY9lhrNgY7R3D0gFCZQN21pzghfQbqdd0Eqr0IcjJg1ZtD05iOW+VHeKJ5BuoUbcT6ezPM0Wfsyr6KkKcvHgkb7dDXnkJV/omMDt4OIEKL35qLSC7u5YmXRf3xc9AZzGS4h6KzmJgS+XPLA4fh5fMGblIyp7aUyS6BxPjEoC7xIn3K35EYzbgLJGxKOwKfmkr5t3yH1CKZbw+7CYez99Dj1HD9MAMMj0jiXUJsE9wCvY5PFEyoZi94+5FZdJhBc51ljN8YKJX1Ncw6LiHe0bxSNJsLvY18U3TBcc0cWn4eJwlcnRmAzOCMtlS+RM3hI62x68LbCjFcl5Mv5EXig6SOyC1EyBgfeIsUtzDEAlAKZEjQcyHVUc50HAeIQI2pM7neNtFfmqzE7Oto+7gUFMOZ7rKeSfzVpzFcjxkykFTlt9DvaaTC13VCAUCvGTOCBFS0FuHv8Kd8v4WwpXeBCu9sdqsfFJ1jBXRk9CYDUiFYg42ZDEtKIMvG85zobua90es5MPKo+T21DLWO44nU27g/YojfNV4gQilLy9nLOZgQxa7Loux35Ayjx9bClkRPYlDjTlcHzKcWNdANCYDXzddINTJmxHeUQ6C9z9Fp74foUDoCHjoMWqwWC24S50o7mtibdZWjFYzAgSOTaol4eNwkSgcpcaXQywQ8eWEB/CTu2EdmBpeLiHsM2pw+x/Eeg9hCEMYwn8qhgjT72CIMP170WvUUtLXwLaqX+gw9JPkFsLyqEmEOHkh+yuG1W8aswcFJVwOAQIOXHn/b4zR/0pozQZ7op1Ry5eN5/mq8QJX+SWzMvoqcrurGeYV6Si0Bbuk8C+ZsTVmPU4iGQKBPTZXbzEhRPAnsqTuZO2FrbTp+xALRFhtVqzYiHcJ4qnU+bQb+niyYC8vpi/mxeKDDhne1KB0vmnMwYaNTI8InkyZx1OFnzsWsyO9ohxx6BN8E5gRlInFZmWCXyJ53bWsztriOMZlEePJ9IzkYl8Tw72ieDh3J6O8Y5jsl0yfSUulqhVvuYtjygYgE0p4d8RyEt2CEf9OhG+XQcWLxQe5NiANZ7GcKnUbYUpv8rtrGe+byM7aE/zaXjLoNiluodwUeSVPFOxFbzEBcH/CDMZ4x3Gw4Tw7ak/wfNqNqM06znRWMNE3kUzPSL5rzuG7ZjtR1JsN9Jv1vFzyFa9kLCVK6cfprjKeyN/HG5k38WHFUS72NzE3ZCSLw8dhtdm4M2sr7YZ+Qpy8eCH9Rh7P30udpgMvqTPvj7wNAbDy3AeOFMBwpQ9vDLuJd8q+52J/ExuH30qlqo1wZx8+KP+RuaEjWZ+7i3viphLnFoibRMH92TsY7R3NkohxgMAh6ezQ97G37gyzQ0ZQrWqnoLcOH5krwU5evFfxAxWqVsKVPrw/ciVCBPQaNWyp+oUfWwsGvXYRSl9eSF/EvtozTA8eRlFvA2+VfYcAAY8mzabfrHO8f8+kLqBJ2+3oArrGP4VrA9N5IOczfGWuvDHsZhp0XbxfcYSX0hcjFYiw2GxsqfqZH1sLECBgVfRVhCq9B0I+Stk0fDmBCg9+ai3C38mdrZW/cLG/cdAx3ho5EW+ZC68O+MkeTZpDTnc1M4IyCVP6OKYtGpMeo82Mh9ROFpq1Paw89wGdBhV3x17HcK8onis6QLmqhemBw4hzDUBnMTLCK4p12Z/SZ9LiJnEi2tmP7IHPw/KoSahNen5uK2LXFXdjslr4ov4c88JG4y1zoVHbxVeNF5jom0hhbz1vlB4CcBASsUDEhpR5HGsr4d74aXjJXRwStX6jDolI9D8iS226XqrV7VSqWolw9iXaxf8vBjWYrRYKeuu44/yfPsNzgkdwY/gVLDj51u/e5hr/FB5PvgGZSEyVqo3NFUdZn3Q9PnJXmrXdPF/0JY8lz/ndLqkhDGEIQ/hvxpCHaQj/cXCXOjHWJ443Mm9i66g7eDx5LtEu/n+VLAGke4T9xR6OUd7RuP7BZKZ/FgwWEyc6Srnl7HtEOPvyQMJMJvglsvT0Rhp1PbTq+hwyp3pNJ08V7B/UnXE5lGK5gyyBXW53iSx16PvI6611RFS/MWwZb2bejItYwcroSTxX9AVvXjzEUynzEQtEjPOOQyIQ8WbmzWR6RPJ06nwECJjgl8hnNSd4PHkOwwcmeX8iS4ncEXMNe+pO0WHoo13fx0eVPw06xh9aChAKBBitJh7O3UmXUc3x9ov4yd0Y4RVFqNLbsdge6RlFoMIDg9XE2qxtVKpaf/Oc9RYTX9Sf43j7RQf5aNJ2c3/OZ3xae4JWQy83RV5JpLOv4zZuEnsXkpNYxn3x08nwiEAkEOIilmO0GEn3DOOeuKn4yl34saWAX9uKeapwP1sqf8JgMfNI0mxeLfmaQCcv1EYdu664G1+ZKwhshDh5k+gahMFiIsU9BLAXga469yEvlRxkXcIMpEIxDdoulp3eRJ2mA4lAxAMJMxEi4HRnmYMsXXrPK1QtzA0dydvDb+FwSz6P5u9mZ81JVsdew9eN2RisJl65+DU/tRRy+/kt1Gk7+LY5B7XJwCdVv9JtUKMx68nqqsZX7obZamFDwT6kQjFJbiH80JxHxcBrO8IrirL+ZuQiCd1GjYMsLQkfxzOpCxALRNRo2vmuKY+5oaM41JTLlb4JzA8dzfrEWZzvqkKAnaAsCR9HiJOX4/xYEzuFOSGjsFitzAkZSYdBhUws4YWiA9RrOrk/51OadD08mr+bmcHD8Je781TKfGJdAoh3DSK/tw6dxcidF7axsfwwr5V+w4aCfbyQvmiQ52WEVxSRzn4OsrQufjqFvfWEKn041VHGA7mf0aLroU3Xy4mOUpad2kSDppMuvQq1WU+6RzgA75QfZnXWFkdowlifWCKUviS4BfNF/Tk2DiQX9pm0FPc3clPEldwaORGLzcq++jN0GlQcabG/fvNDR/+pO8cGMwOHIROJ+bj6VwAm+SXx1YQHiXT2HSjJPc3d8VPxVbgNem6uUsX/iCzVqTu49ez73JP9CRvLD3NfzqfccuY9qlVtv3t9lUnHDy2DCXNWdxUigYir/VJ+c/1LoR0KsZQ+k5Y7zn/E8Y6LPJG/l0ZtF2uytpLVXcV9OZ/9JjDjPx3t+j56LvOOder76dD3/xuPaAhDGMJ/K4YI0xD+1+EqccJb7vqHY8E9ZS48kDjjN5d7SJXcnzDjD0fZ/jNgsVnpNWo53maffrxV+h0FPXU8Xfg5FpuVs50VuEudeP3iIRo0Xdxx/iNOdZaxIX/f37XY6ND3sy77Uy72NXFP3FSeSV3AB5VH2Vt7mrcyb0YpkTvM/W+Xfsf26mO4SZ34YNRtdOhV5PXWcaGris/GrqVS1crBxiy0ZgMp7qGDHifNPRSz1Yq7RMlor1ieLvzckV42L2QUCpGUdn0fzxV9yVifeFRmPc5iOZtGLKdc1cIvLYUku4egFMsY5xPH0sjxbBx+K4EKD8KU3o4pwOWQiyTMCRlJhkcENmy8UXqILxrsyV3Tg4YhF0goV7VSo+5w3MZqs2HBylsXDyETSVgbM4VXM5byY2shP7UVYbHaMFotrM3axrzQ0WR6RuIldWZmcCYai4Hni77g3vhpmKxmhnlF8nLxQW4//xHV6nZev/gNT6bOw0vmzMyg4cwKygSg26gmp7sGndnA48lzBz2Hu+OnkuwewrmuCkfK4GjvGGJcArBi45G83QgQ4CxSYLHavWeHmnN4vuhLJvsnOcIddtWdosugQimWsWn4cjYU7udA43nevHiIoy1FPFW4n9cufsOBhvM8mXIDo71jKOlvYFZwJkvDr+SBhBnEuARgtlopV7US6xrAI0mzWRY+HrlIyqGmHF7JWMJ1AWnMDR1JuaqZReFjONtZwTX+qVzorubntiLG+yZQ1teESCDk17YSHkiYwVMp82jX97M2aysdhn4Who4h1T2UZwo/Z0PKfGRCCS26Xu7J/oQqdRtvl37HR6NvJ8ktmPPdVbxUdJC3Mm/GV+6GzmLku+ZchAjs53LFj4OCEbK7qjFYTUzyS8Jb5kKSWzCFvfWM9o5hX/0ZyvqbeTh3F98357GhYD/thn4+qPiRvN46bj7zLovDxzHeJx7A4c95NGkOR1oKUErkfFp9jGsD0zjdWc698dNQiKQ8m7oQs83CjKBh9Bm1TPBNBOC1i99wqqOMPXWnadf3oTHrOd9VyZoL21Cb9DyTupBZQZncEjmR0x1lvJqxlGmB6TycNBupSIz+z+SsfwRGi3nQwt5ms9Fj1NBjUPNw3i46BzZgLqHbqObB3B106gdf3mNUs7nyKF82nAfgCp84pEIxjdpu7sn+mLVx17IhZR5Rzn74y91ZEDqaz8beSciAX0wmlPBw0mxHSfTc4687ipMfS56Di9heVt1tUNN72feZyqRzbBL9p6BF18Oa81vscfkGDZ36fp4u/JzH8vfQ8Rc2sP5RaM0GTJcFG5mt5t/4xIYwhCH8d2Ooh2kI//FQimVMDUgn1T2ML+rP0abv4wqfOMb7xv/d/RbdBjVykcRB1jr1KsRC4R8qW7y0iJGLJSyNGA8IuNBdxZGBHf1IZz9eyVjCvRe206jr4ujA5UqRjHUJ03H7O4hdpaqVclUL5aoWpgamc6SlgCp1G8+nLUIpkuGMjFcylvBQ7k5qNB3UaDo42VHKfSIpGR4RfFB5hDZ9H2c6K+gyqPhkzBrOdlU6dsfFAhFmm4V3yg/zYMJM1sVP56Oqn5kakE5+Tx2PJs1BZdbxTOoCnizYx3UBafSbtBitZh5KmIXObCRM6c07jd+T11fPpuHLMVstdBj6cXd14t0RKxALRL9rWgd7utPLGYuZc+w1NBb7wiLONZA5wSPoNqp5ufgrbNhIcQ/BS+ZKklswB+rPUaFu5amCz3k0aQ4nOi5yqqOMUx1lbBq+nEzPcH5u9eVAw3nmh47GSSxlQ8F+ZgQN4664qYgEQp4rOkCwkycjvGI41l5KaX8z98VP58XigzySNBuLzYrarHccp5tEQZizD88UDpaE7qs7w3DPKJLcQ/CRuRLt4s+MoGHIRRI+rPwJk9VCkMKT3O4a4lwDWB09hVTPUPbWnubDiqM8lTrfkTwHdv9bgMKDKQGpVKhaCHX2Jtk9mGhnf7xkLiwJGwcCqNV0AAK0VhPXBqRQo+5AIhLRa9IQIHfHWSwnwyOcdn0/W6t+ZnXMFNykTtwWfRVVqjasNtBZTAz3imTRybcd6ZQvFh9kXshoDrfksTpmCreeeY90z3C0ZgOPJM3mVEcZrhIFRX0NWGxWfmor5I6Yq3l7oKQV4PaYKRT21vPmxUP4K9x4OX0JKrOesd6xHGzMAuDWqElkd1U74rpvDLuC3J4aSvubeaHoS97MvJlGbRdvlX7HuvjpuInlPJ48l+eKDnCxv8nhFUtxD2VF1GSeKzqAQihFIZLQoe/nkaTZZHVVcbS1kGZdD3OCRyATilkXP537cz6jVd/L3JCRbB19B88VHaCkr5FqdTsPJc5CKZYjLhZSrW7DV+7K++U/kNNdww2ho3ipxN4h93VTNpN8k5gRnMnFvkZCBpImF4ePR2XS4iKR82X9eWYFD8dH/sdk30aLmbyeWr5oOMeDibPwkjpTpW7j1ZKveSx5Lu1/YXHfoO2ix6geFJYjFUrI8IjgQMN5lkdOYknEOKrV7azN2kq0iz9ykYTpQcMY6x2LxWbDVapAelmym5NYxjifeNbEThkUHvPasKUkugYhEoroNqjZWHYYb7kLS8PHIxTYwzZyumt5NHn2f0SincFi4mRHGfXaLuq1XRitJjoMKrIGJqeVqja8ZC5/0xv3R6A1GzjefhFfuRsp7qEIgOK+Rpq03UzwS0Q5QDKHMIQh/HdjyMM0hP8qWKwWzDbr35Tx/R5q1R3ccf4j7o6byiS/RPpMOtZlb2esT5wj7e5yWG1W+ow6PGRKbDYbtZoO6jWdaMx6hntGUdTXwMN5uxzXXxMzhdkhI9ha+TN76884Lv9kzBriXQP/rh/n3bUn+aYxh0q1XXblIVXy7ogVfFL9K1f5JbO79jTPpC1gfe5OxyJSJpSwbfQd9BjVvFzyNQ3aLsAerHHgyvtZm7WVRm03V/jEcW/8NF4o+pLcnlpiXfx5bdhNaMwGdtQcZ3HEOHbVnORQcy7Ppi4k2sWPEx2lWKxWwp19aNb2sLH8MNMDh3Fj+Fh0ZhNW7NO1GJcAUt1DOdpawLWB6X9x8dRn1LKj9oSjZwjsfpAnk28g0T2Ipwo+RywQ8mzaQroMas52lDE5IIUXiw9S2GsPKrhkZn8wYSYCBEQ4+xCo8KJU1UStup02fR8HBnbal4aPp7i3gdzeWgQIeCvzZjr0/SS4BQ3IvXp5Pm0Rx9pKHAQ4TOnDI0mzean4ILWaDsQCEYvDr2BP3WmMVjMhTl68kWl/3eo1nTxd+DkyoZj3Rtqjwx/J28kdMVMo7Wtion8Sj+Xt4abIKwlTevNg7k7HjrwQAY8mzyFc6YOTSEpRXyNuEgUuEgVOIhkBTh5c6KpiQ8F+Xs5YzJcN5xnnE0+KRyj1mk42FOxnXugo5gSPRAjccvZ9VGY998RNo1XXw776szyUOIvhnpFkd1fzcsnXLI+aiJ/cjS8bstiQMo+XS77GTaLg7vipnGwvpc+oJaenhg0p8ykc8E2tHUhqnOCbyJLwcTyYu4M+k9bx/gUqPHgxfTFqs54wpTcKkZRvm3J4c8DvA+And+Px5Lk8W3SAmUGZjPSKQmXWs7XyZ4KcPFkWMZ7lZz7AgpX1CbNI9whDKZHzbvmRQZ1IO6+4i2pVG8fbLnJr9CSeK/iC+eFj+LWtmHE+CZzrqnDEnkuFYqYHDeOzmuPsrz8L2KeceosJAQIeTroed4kT6Z4RWAfS9Zq1vbhI5PQY1WjNRs53VdKu7+e+hGnUa7rQW4woxXLeLD1ElbqNqYHp3BwxgfcqjnC8/SKZHpE8l77wD5GHNl0fc46/htlmYbxPAqtirmLN+S2ozHqGe0YyJ2SkI5XzEkKV3jRoutgy6nZSPAZPjbVmA826HnxkrrhJnTBbzdRpOnEfqDX4W2jSdrM2a+ugQJthHhE8m7YQT6mSo62FPFGwD4BlEVfiKlE4yNV98dO5IXTUb+K1/x3oM2rZV3/mNxLjp1PmM8Ev8Z9SfG62WjjVUcaDuTuQCERsHLEckUDA2qxtGK1mXkpfzHjfBCS/4+McwhCG8J+BIQ/TEP6/hEgo+ofIUr9Ry7aqn+k2qnmqcD+f159jXfZ2qtRt7Ko9OUheAvaAivL+FjYU7KNd34fapEdl0rGr9iQBCk+q1G2/WcS8V3GEE+2lv+kj2VFz4g/L8Vp1PRxpyadO08k1Aam8MewmUtxDeH3YTXzZcJ4jLQU8VbCfBxJnsqns8KB0NoPVxBP5exEIhPSZtIgEQtwkTlhsVlad+4jXhi1jYehYlkdN4ubT73Jz5ARuCBnFi+mLadX24CZRMMkvibXnt3Go2R5fHeLkxSfVx3iv/AibK4+yr+4sG8vtfqUOQz91mk76zVp7f031rzyWv4d6bSdioZijLYX0GNT0GrU0arpo1HTRa9Sgsxj5tinHQZau9k8hxT0UGzaeKfqCek0Xd8dN5anU+chFEqxYmR6cyZqsrTyefAPPpC7gmTS7N2e0dwz+Cg8yvSKRi2QYrEY2Vxzlw8qfGOkV7ZBZ7ag94SBL9yfM4FjbRaJd/Vlx7gNadL3IhVJiXQIc79PyyEm8PmwZTdou5oaMQiIQ8UbmMsZ4x/Bc2kKkQrF9ymiDz6qPOySZWouRg/VZlPc3U6Fq44n8vcS4BvBw3i5qNO28VPwV7lIlapMOpVjGR6Nu59WMpZxsL+X28x/RbuhnpFcUJX2NrMnaytmuCrI6K3k8fy9mm4XdtadYHTOFvJ469tWdwV2iZH7oaFzETrxYfBChUIRUJMZT6sxEv0Qu9jdhw8YrJV/zfsURXi75Ghs28rprCVX6sDJ6Ml82nOfGsLGM8orhXEcFJqsFmUjC7TFX81zRF5ztrMRiszHKK5p4l0AeTrye9Xk7B8ITFKxPvB6Z0E5ANGY9gQoPfOVu6C0mRyLbNf4pHBh/PzbguaIDvDFsGeN94jjfVUVxbwOPJ8/lrtjr0JoNPJQ0i6Xh4xnuFYXBauFUR7nDV3QJzxR8TrjSlwvdNQgRcFVACrWaDo61X+SF4i8Z6RWNxmzg4+pf2Vx5lCpVK7dHX82MwGEAjtCQZ1IX4C5xwkPmzA3HX6dB24WPzBVPmZJ7LnxMg6aLkx2lBCo8eCzZLvG7J/sTTnaUIRAIHNLK75vzWHluM8fbL9rP6YAUZMI/9j0lEgi4K/Y6AE50XGTZ6U2ozHo8pEruS5jBwYasQdcf5xPHw4mzWZ84Cw+ZEqvNSo263eHNcRLLiHbxx0Uip9eoQSwUE+Vin1T2GjX8tT3SzgEJ5iUZ3vzQ0Q553pP5++gz6RjpHcP80NEAfFZz3EGWrvVPY0pA2n8EWQJwkzoxP3T0oMl+pLMfY3xi/ylkCUAsFBHrGkCo0huTzcKa81u4/dxHjg2VBLegIbI0hCH8f4IhwjSE/xNwlTpxd9xURnlFA7Cx/DBV6jZEAiGvD7uJT6uP0zAQx12n6aDPpGF11hbOdlXwaN5uuo1qHs/fS25PLS8VH8RZIsdisxLp7MfXEx5yLJzeLf+BaUEZuIjkTB9YnB1tLeTNi4cGeRR+D9XqNpadfpfH8/dyoOE871cc4dH83ayMuopGbSfjfOIJUngS7RpAs67bMQm5NXIib2XeglggolrTzqmOMuYEj+Sl9MVsHnkbgQoP2vS9XOxrIt0jjCPN+dwbPx2ZUEqgwoMPKn6k36yjSt3GT61FvDtiOaEDBbAby77n3vhp3BIxAcCRsjfGO4Z5oaPZULCf+3M+Y1+dfaJ2bUAaQoGAWk0HCrEUtVnPvrrTnOwoY2ftSY61ldCo6WKiXyKBCg9uCBlFpmckS8PHk+YeRrpHGGablc+qT+AklqIxG3mx+CB76k6zeeQqWnQ9fNuUzbeN2WxInUd2Vw16i5HCnjoatJ3cfv4j7ombygivKNwlSu6Ku+434QKuEgUHGs/xasnXPJ+6iAilDw8nXc/R1kIeSJzJi2k3cqVvAs26HrxkLsS4+HPgygdQimRUqdtxlyjZM+4ehntGsrH8sN1DZbMS7xoIwMGmLE53lvNY8hw0FgMPDkS92wM5bsJisTLGO4bn0xahEEqJcvGjUduNxWbl/pzPeKnkK7bXHAfs0sx+sw4bNtLcw3g6dQFNum4Ot+TxVeMFvm3KwVksZ3Plj+T01HCoKYeto+7gxfQbkQiEPJ26gNQBMvpzW7EjNfGZtIWEOnkRoPDAX+FBqNKb4Z6RjPSOxlXixAivKB7P28N1genEuvrjK3dlScR47oq/Dr3FxIMJs3CXKNk0YgVX+iTw4cjbeDp1AS8Uf8n92Z/SquvFipWX0hdzbUAaq2OmoBBLeTplPjEuAZisZkQCEdXqNiw2K2V9zYiFIrK7a8jqqnKELUhFYl4ZIHkZHuHcFz/DXkqramFr1c/cHns1K89uZpxPHNMDhzme6wvFX7J7IPZ7ZpC9+FRjMVCn/ZMvDqCsv5lEt2BeKf4atVnPnVnb+LrxAqvPb6HLqOb9iiMsDh/H+xU/8kDOZ7w/QAC1ZgNSoYgx3jEsChsL4JBy3hM31Z7+KPljUqx+sw6jzcz1f1au/GL6Yn5ozuOmyCsdl13hE8fV/qncdWEbhb31OIlkVKnaWHH2gwFvjp00WW1WqlRt3HXhY5q13YB9cnTnQBDL5aTJcpn3RiIUMzUwA5lQwnsjV7A29lqeT1uIEAHzwuyeRg+pklXRVzu+IwC8pM48kDjTEXP+n4BOfT9P5O8dFMhSrW7jvfIjf/O7+O9BgMKDTcOX4yVzwYoNKzY8pc5sGrHi75aMD2EIQ/jPxRBhGsL/GXjLXXkyZd6gy6b4p9Km7+Xb5hxWn9/Cha4q7ji/hc0VR7k3bhoCBBT01jP/5Ju06nuRiyTcGXctFquFiX5JPJo0GxexnCeTb+C6gDReyljM0wWf896oldyfOIP74qcjEgiZFpTh2NVs1vVQ1tfsML136PvJ7a7hq4asQRInsO+EH20t4FRHOc8Ufs4L6Tdysa+Jc52V3Bl7LbdETmS8Tzx7a0/zcsYSpvinMiNoGLGuAUQ5+6E1G3kixT6VsdlsPJK/m731ZzjdUcaDuZ+xsfww2d01hDv7crztIiO9o7n7wsc8nbqQ6YHDWBIxnsWn3iHDM2JQV1ayWwjhSp9BRcQZHhHMDRlJhaqVz+vP8lzRAY63l+IskfNG6bd80XAOrcXIlw3nEQtEfDhyFbdFTybRLYheo4aVUZNZEDaW3TUneTJ1LgaLme+b86hWt7On7jS7a0+ys/Yk57oqOddViVggJM0jlMfz9xLtEkCCaxAigZCDDVncGzcVD5mS5woPDAoXON9VSbdBw8KwsQ4fw2PJcznZXsokvyTUJh3BTl6IBELW5+6kWtWOj9yVD8qPsOLcZvJ6ark/51O+arhAr1GLdWDhuSZmCmtip7A4fBwAQoGAZLeQQe/lyuirUAil9Ju1rIq5BneJM88Wf0GfSctLGTcS4+zvCA4BmB6YwbUBabxW8g1Rzn48n76INl0PEUpfx+Mcas5xxH+P94knVOlNt1FNsMKLrO5qCnrqGOsdN+g4JvsnY7PZEAmF7Ks7w9tl3/Fi8UFkYgk/tRbxfPEBHs/fy/ujbiOrq4qvGi/QY1SzLns7917YzsN5uzBYTLw3cgXPFHzOZ7XH8Zd7IBYIadX1Ua1p5+4LH/NI7i4+qPiRRLdgyvqbKetrwmyzsCJqEmarlYLeOq7wiSNE4UmMWwA3nnobN6kT8a6BRDj7cl/Op5T2NbMmZgoZHuHcHDmBor56Hk2aQ4iTF2tipxDvEsi04Ax+bi/GU6rk1WFLUV42PYhxCWB+6Gja9H08lrebwt4GBAgcBbI7ak+wr/4sb2QuI9rZzy6jKvkKg9VEkMKDjSOWs7f2NGabxdFZdV1AOgvCxnCkuYAuo5q6y3rPAMr7WxydaX8EQXJPRnhF8XNr0aDLP60+xtzQ0cS4BHBP3DTcJE5EOftRqWrBYrNyqDmXDQX7uP38R6jNeho0nY7JWb9Jx90XPqasv5m1WdsG/n8r5aoW7sn+xPE906Lr4XRnOdqBgAI3qROLwsayd9y9JLgG4SSWMdYnjoMTHmSsdxwKsRSVScc3TdnUD0h+AbqManbUnvjNpP7fBYPFxLfNOY4esSeS57IyajIABxuzyO+tw3rZ98L/BGarhVZ9L/3GP31395t0tOh6MFrMf/h+egxqzJeR126D2vG+DGEIQ/j3Y8jDNIT/M2jV9TpkeJfjyeQbKO5t4IvG847LlGIZO8bcyS/txbxzWb/Qi+k38nn9OSpVrayOncK7ZYe5I+YaJvol2qUoNtBY9MhFUuQiqaME0lvmgkwkoVnXw11Z2+g0qPhg5Ep85W48mb+P7O5qh7n+1/YSPKXOdBvtu6BjvGMJU3rjLJajsxjZWXsSsPsHrvFPQWPW4yNzY2/daa4PGc6PTYUsiBiN2WrFYDXjIpbTru9DKBCyr/4M3zRlO56Pp9SZZ9IW4C9zRy6SsuzMRnqMGtwlStbFT+OVi1+jMRsIULjzQtqN3H7eLjdJcw9jgm8SbYZe9tadJsYlgG6DmocTr0cqEvNZzXEudFcPep2HeURwb/w0VCY9u2pPsDx6MgFyd3qNWj6s+onrgzJ5v/wIvWYdH45aRaWqFYvVwvmuKkeK3iXcFz+dRLdg3in7nmgXf26PuZqi3gb85e70GDVc7GukUdfNV40X7DK8+Omc66rkREcpAJtHrsJJJOW10m+oVLXybOpCXCRyvGQuPJD9GSujJ9Nj0DDRP4mPKn7iYFMWTiIpDyXOYlvVL8S4BDDaOwax0N6vk+QWTLu+n6zuKkKcvEh0Cya7u5pdtaeoHjjfEl2DeDBxFnde2IZcJOWtzJsxWc18WHGUO2Ov40DjeYfnCuCJ5BtIdQ9lT+1prvCN46Xig7yVeQt6qwlPqZIHc3c4osVdxHI+Gn07JosFJ7EUqVBMeX8zKrOepwo/H/TaCQaS6kZ7x3Cus4InCvZhG9gVv3TOjfOJZ3pQBo/n78Vis7IhZR4uYgXr83Y6CKhwILJ+eeQk/OVuNOt7HV4us+1PC78nk29gnE88CODjql+5wieORLdgbNg40lJAgmsQn9ef5dvmnIHzejy/tpXQoO1CKhTz2dg7UZv0tOp7cRrwRS0Kv4IaVRvdRjVykZQQpRcRSl9+aMl3EMhLz/WplHn4yt34qOoncrtreTjperxlLpxoL+VgYxYPJ17v2AxYenoTMpGYp1MX4Cl1JkDuzp66U2wbCEuxn3szEADpHuG8X3GE053lAMS6BFCuagHsvUd3xFyDxx+YuDRre1h2eqNDhjfRL8mRcne1XwoPJs3CVaKgU9+PwWpGIhTxbWMOH1X9yZvjJXXmg1G3Eab0AewpbSUDBbaXyqTB7nN8JnUBgQp33KRK7rywjXpNJ8+lLWKcTzxO4r8ef26xWvi1vYRH8nYDdqmls1jBlwPfnesTr2dmcOagIIl/F7oMKl4r+YYrfROY4JeIyWphf/0ZdBbT73pW/xGYrRaK+xocnqVAhQcCBDTpupEIRGwasZwU9xDEf+P1aNX18nDuLu5LmE6SWzC9Ji0vl3zFFP9UxvrE/dMkhEMYwhB+iyEP0xCGcBn6TVrevHjIIcN7OX0Jo7zsMrpnir5gXtgYAi4rgnw+7UZsAthXd3bQ/eysOcmNYWN5KX0x5zsrUZn1vHrxGzoMKpp1PThL5EiFEh7J283J9lKEAiFBTp4O39UlU7nOYuSO81u4M2sbWd1VWLFhsVm5PeZqHkqcxevDlpHmHgZAdnc1s4NHYAMHWZoWkM5o7xheKfkak81Kj0nD/LAxvFX6HeP843mx6CBai4FXSr7mdGcZUqGYfpOWawPSBj2fdI9w6jWdnOos40T7Rd4ZfituEgW9Jg0bCvejMRvwkrnwSNJs9tWdYcfYu1gXN40bw68gWOnJJL8kbom4kjWxU3g8ZS4vlXyFUCBgbey1+Mv/9Hr6yt24O34qAuDtsu841VnOE/l76TVpebvsO35tK+aJgn08nbaAHoOaO859RIjCi0S3EBaEjcH5sqSpGJcAMjwiWJu1jWURVzLSKxoQEOXsx67aU9ybvZ3tNce5yi+ZGBd/HkiYSZJ7KGtjr+VKn3iWho+nz6hBKhLTpO1GYzbwbVM27fp+Vpz9gLvipyIWiBjjE8varK1MDkhmVmAm28esxVXsxDNpC6lStxHs5Im/3J0kt2Ba9b382lbCKK9oUtxCqFK1ktNdw91x17EheR6+Mlf0VpNjB77LoOLuCx+zPncX9yfM5MfWAgdZEg50jr1Q/CUX+5uYEpjKkwX7mBaUwZHWAo62FnK0tchBlgBUZj2fVZ/AZDNztLUIq81GvFswHw4Y3jM9Ijk08WGHV+zDyqNYbPYQj/vipwM4yNIor2jWxExhZ81JLDYrS8PHU6vpIFTpPfBa2xGk8OT2mGtYk7WF013lRDv7keAWROBlnyM3icIuj5QpcZcquSVqAoluwThL5LhIFEz2SyJA4cHauGuZ6Gf3m31Wc8JBlp5Onc9bFw8hEAiIdg5gV+0prgtMp9eoYbh3FN8257Cx/DAhTt782l7iIEtTAlJJcQ/Bho2nCj9HbzWxInISr2QsIaurim8as1keNYmPRt1Oukc4t537kGeLvuDZtAU8nbqAd0q/55G8XXQZ1VRr2gEcXUpvlH6LQCDAYrMiHpB73hFzDXfGXcuNA/K8y7vV/hYkQhFX+6fiIVXyVMp8fGWurI6ZglQoZn7YaFzEMkQCIX4Kd0KV3vjJ3ZjknzToPuJdg3CT/IkAiIViEt2CeTz5hkHXuz9hBt8157Di3GZuPfu+QyoaqHD/Q14bkVBEmnsYIzyjuNY/jfsTZrImdgoroyaT6BbMeN/4/wiyBOAlc+HBxFmOgAe7p2nMHyJLJuvgyZBxYHL35xALRbhI7D1bIU5evD9yJe+PXEmY0geFWIqrxAmR4K+/rv1GLa+VfENJfyNrs7Y6ZN+/tpXwWP5ex+dyCEMYwr8XQ4RpCP8n4Cpx4t6EaUQofXk78xau8IllQ8oNjPGO5ZPRa7jY10iLrheAVdFX4y93Y835rQ4Z3pLwcQgQUNTXwI7aE4Q7+/Bg4kwm+SbxcOL17K87w6pzH3K+q5LH8veQ11PLhoJ99Ju0tGp7HdIMd4mSTcOX4ytzRWcxOqZd6xOvJ9k9lHXZnxLt4s/zRQe4K/Y6hntEYrZaUIqkTPJLIsTJi2v8U1kePZnXSr6hqK+B5wq/QCYU81Thfi50V3PvhU94IHEWPzTnc6G7ipeKvyK/tw6ZSDIo1Q/g57YiGjRdjPGO4eWLX7G/7jT3DiygL+HRpNm0aHu4PeZq2vW9uEgUPJy3i68bs1CIpAz3imZ97k42lh3m+fSFeEqcKeptoFXf67iPdn0fVapWWvS93Bs/DZlQTLOuh8Wn3iGvp45pgRncHTcVg8WMWCjiKr9kdBY9FpuFd0q/GxT1XaFq4fvmXN4dcSuP5tmDN8xWCyKBkKK+Bsw2CzeEjsJL6syL6YuRCEXsrTtNXk8dN0dN5NqANMKcfdCZjTyZcgPeMheWR03izdJD9Bg1vFv+AwFOHjxXfIB18dPZUvmz/fW++A3uMiWNmi4eTppNg7YLrUmPyWphS+VPfFZ73B5yILCHAHzXnMsT+XsZ4RXFO8NvQW3S02vSsnH4rTiJpPQYNfQNRLV/22Sfrlzll8zecfc65Hn768/SZ9KiNutJcA3GarWQ6BrEpoHgjXE+ccwJGQnY5XnnOiuJdPZlT90pHsvfw8NJ13NtQBqPJM+mqLeex5LmMDUwnZfSFyNAwI8tBfSbB8vHtBYjLfoeHkqcCYBMJGZqQDoGqwnfgajscT7xPJFyA0U99TyduoC9tafpMPTzfNGBQVKtPpOOey58QuvAZ8tD6uzw9qhNes51VdJv1uElc+G++MFdaxN8E9CajZzpquD+nE8RCODWqIl06PuoUbez8uxmHkyYxXOpi9hRc5xYlwACFO7MCsrk/oQZvJi+mFT3UFLdQ/GSOvNI/m62Vx/jaGshV/unoDUb8Ja5UKvpoM+kpaC3no+rfuWt0kPUaNpp1/dTr+ngnthpzAzK5OsJDzHOxy5v/KElDzepE8ujJvNs2kK6jWruvvAJoUpvXh+27A9Pl8DeGxXt4scrGUv5qbWQUKU3/SYtH49ZTVZXJdrLFuuXvEmrzn0I4Cj0PtVZxnvlP9Ci7eGX1mI+qz5GraaD9yuODHqsT2uOsSBsLM5iOV0GFUIEfDhqFc5ixaBC1zZdH9Wqtt8NiPCWu/J06nzWJUzHU+aM2qznKv8U3hx2E75yNzr0/VzsaxrUS/TvgqfMedB0xk3q9DfJUp9Ry9eN2Y6ycY3ZwKmO8t9ILy8h0tmPD0etYtOI5QOeQHc2Dr+VD0etItLZ92+SZ1epE/clTCdI4YnBamZN1laODYSHrE+chbvE6e95ykMYwhD+RRiS5A3h/wzUJj16ixFXiQKpSILRYqbLoOL1i98wzjeB3O4a5oSM5MfWAtwlSmJc/HmycB8fjLyNCKUv57oqeCRvNy+m3cho7xiMVjNqswGrzcrd2R/TOGCuBvtC5rm0hejMRnJ7apjkl0yQkyeV/S04iWVsq/qF4v5Gx3U3j7qNd8sOk99bT7xrII8lzaW4r4F41yCOthZwU8QECnrrCHP2oc+oJb+njkyvSNac34L2sqJMIQJezFhMr0HNcK9oPqw8yg2hoxDY4NOa45zoKMVL6szLGUv4suE8h5pzkQnFfDr2Tt4v/4GlEVdyT/Yng0oX3SVK3hu5gmgXf1QmPT+2FPBSyUEAYlz8qdN0YrSaCXXy4p3hyynvb+ahvJ0AZHiEY7XZyO+tA+DZ1AVUq9qJcvXn8fw9DolQh6GfMKU3Vap2RntHk9VdxZW+CRxsyHJ0R90dN5UmbbdDnvdS+mLiXAJ4vfRb1sReS7SLPy26Hs53VpLgGoRCLOWVkq+5wieONI8wcntqqdN0YrNZSXILId4tiBZtDwcaz9Os7eb+hJn2othhy3gyfx9Num5CnLx4fdgyNhTs52J/E+4SJdtG34HarOdgQxZX+iVwsPECq2OuYc1AUMDlWB0zhVT3UIxWCzEufjRouvCSu3D7uQ8d1411CeDp1AUcbMgiysWPTeWHeX3YTXzdeIErfRN4omAveouJTcOX4ySWIRdJeK/8CALgmoBUYlz8+bYph6yuKu6IucZuwM/dQYehnwC5O69kLGVb1c8c7yhFIZTxaPL1OIllNGt7sGDl9YvfAhDq5EWDthsbNoZ5RLA8ahL3Zm9nVfRVSIVi3ir7jnviphKq9MZqs/Fw3i5mBQ9njHcMkc5+lPY38/hAcuQjSbNRimU8VWCX592fMIPZwSPQWYwoRFIsNhunOi7yWP5eR3/ZfdnbB5EtgAcSZtBn1BHl4seeutOoTDqGeUY44sGvDx7OtQFprMnaSpJbMM+nLUIukjrCB1p1vfQZtdx2fjN6iwkvmQs3hIyi36RlX90ZXki/kWS3YHJ6atlQsN/hyRvuGcX6pFloTHqq1G2M903Ahj3KfnfNKeaFjuJCdzXPFR1gmEcEbYY+mgaCO+YEjWB59CT8BiZtPQY1eqvJEQCgMunQWYx4SpWIhWKatd30m3TsqDnBvfHTsWFFZdazsfR71ifNxv+yiV2fUcs7Zd/zTVM2XjIXtoy6ne+acvmo6idkQgmbRtzK4/l7eSH9Rp7I3+tIu1sRNYmtVT9jGEhv25Ayj5XnNhPi5MVL6Yu568LHOImlbBq+ApFAyLrs7bTpe9k8ahVRzn5/cdHfpO1mTdYWtGYjH45ahYtYziN5uynpa2TTiOUku4f8x6Tm/RH0GbXsqTvF1qpfiHUJ4K3Mm8npruHxgr14yVz4aNQqgi8Lu/hnokXXw/XHXnX8e1pgBg8mzvy7e5xMVjNigejvmnIOYQj/l/FHucF/zzfZEIbwD8Jms6ExGzjWVsL7lUf4cOQqfOSuNGq7ONScw/GOUk52lPFM6gJOd5Y5FmNvZ97CwSsfxFWiQCwUMdorhq8nPIRSLKNJ180rJV+T21NLgMKdV9KXsuzMJsdjzgrORGXSEeXijw0bD+XuwFPmzLsjVvBS8VcOsqQUy9CYDdxz4ROeSV2AW+MFVkZfxZHWfD6rOUGmZyTPpC4gq7uKx/P3EuTkwbsjVrAs8kqsNiuvDlvK2qxtjse9I/YaCnrqiHT2xX2gsPSuC9u4wieeu+OmIhWKuT5kOE8V7mdh2FikIgnjfOJwEkpZnzSbG0++45DhrY2dwlul39Fr0rAuezsfj16Dt9yFKQGp2LDxcslXDllYsJMn65NmY7FZCHf2IcTJCz+5G/clzEAsEPFSyUE69P24SpxIcLd7VgCeS1vIZzXHKeit58awscwIymRn7Um+acrmXEclq+OuoaC3nsl+SSS6BaMQSZgZZPdICIDbzn/IqxlLCR/wbgQoPJjol0xudzWV6jZHQMSamCk063ocBaojvKLpMqg42VHqCFn4sjGL26OvZlPZD9wZdy0bCvbToO1iwcm3ADsZvTvuOt4p+x6LzcoDiTO568LH1Gs6adX18MGo25h/4k3HezE3ZBQjvaKpVLVwvP0ijyXPxUfhxtosO7GSCEQIBUI6DSrUJh2BCg9eKj5IhLMvWrOBaBd/B1kCeKbwc14ZtoS87lrWxEyhTd8LAgFZXVVMDUznav8UdBYj71UcocNgnxbEuAQgF0lYEDaWSf7JWGxWEtyCeTBnBxP9Eh3E+AqfOJZGjKdK1cbrF7+l36QjQOHOdQGpBDl58lXjBftnoux7rvFP4ee2Yiw2K0W99SwOu4L9dWe50jeedXHT8JO7M8wrArVJzwtpi2jT9zHRN5Fug5pPa44zzieeOJcAkt1DmeyXxEivaDaV/0D9gAzvlYwlHGzI4tf2El67+C37xq3DYDFR2FuPxWZ1TGXH+8QzzDMCN4kTy6Mm4SyW469wH9R3JhWK2Vl7Ar3FxDifOG6LvhoB8Hzxl1ix8Wjebq4PHsGs4ExcJXL6BgjZvNBRPJG/l5czlnCNsz8t+h4eydvFS+mLWRE1CZPNgtZswGKzIhIK+XDkKspVLazL3k52bw23MBGwk6X3yo9woqOUD0beho/che+b89hY9j3vjliBv9yde7O32+V4qfNBAM8XfkmtpoONw28dRJYAXCUKVkZNRiwQMit4OI3aLmYED0MkFBLt7M/GssO06fv4ov4ci8PHsan8MM+lLiTVI4x0j3DuuvAxi8PHcaD+PB5SJc5iOU26HjRmPd1GNauzPkIqlFCn6UAkENJjVGOyeiMV/f5SwWA1oTUb6DPpWHXuQ7xlLlSp2xAgoNeoxWy1Ivkv0rHIRRJS3cMQCYSUq1pYcnqjo2ogQunzh6Pi/17YN+6+HXTZT62FzA0ZSaJbMOK/IZe02Ky06Hr5qbWQ/J5aIpx9mRmUSYDC4x+q4RjCEIbwWwxNmIbw/yU0Zj0Gi90r1GfS4i93p9+kpcuopt+kQ4yQpwo/58mUG/ik+leK+xoH3f6GkFGsjJ78u0WPjdoulp3ahMZiQCaU8GzaAj6rOUFhb73jOlKhmGdSF/BtYw6nO8uwYuNKnwRWRk/mjvMfobUYeX3YMhLdgtlccZSDjVmsir6aGUHDKOtrQms1sqFgP2Av+2zX9zt2/p9NW4iP3JV2fR8P5+5ypHcB+MpceTxlLi8UHeT64OF83XTB3jMkkrB9zFqKehvYVvUL0wLTcZM4oTLrOdtZwWjvGKYGplOjbuflkq95PHkuu2pPMj9sDC8WfckTKTfgIXXm17ZifGSuBCs9BxG1DI9w5oeORioUDyS1aeg1avCWuuAuU6K3GOk2atCaDRxoOE+XQcWjyXNQm/T83FbkWJD7yFwdi/1l4eMZ6RWDv8INq82K3myi26RBKhJhtFhYl7Od4Z6RvJi+GDfpn2Qrbbo+GjSduEoUbKr4wUGILmFOyMgB0iVixdnNGKwmHrrkc8raitqsZ5xPHJP8knm26AvH7e5PmEGowpt7cj4ZdH8SgYi3h99i31Uf6KQBO4l8OHE24Uoflp7eyK4r7qZW08FdFz5GLBDxeuYyFEIpCGBDwT4atd3IhRL2jLuXm89sos+kw1PqzD1x03i55CCjvWO5wieW54u+RCIU82DiTHbWnKRG0876xFkM84jg05oTHBoIT7iE5ZGTmOCXSJu+lxPtpUiEIpZFXMkLRV9yT/xUmrQ9RDr7sjprCyO8ohjrHUu8axACmwCZWEy9phMvqQuf1tqDPBaGjeHrxmziXQJYFXMNd5z/kJHe0dwbOw2VRY/OYsRP5s6rJV9zXWA6ygH/SEV/C48X7EWIgD3j7qFC1YpSJOVCVzXDvCL5qPInVkRNIsE1CKFQyMslXzHZL5krfRMwWEw8X/QlxzvsUiUBAr6a8AAV/a3srjvF0ojxxLoE4i3/7ee126DmaGsBY73jWHDyLVZGT+YK71ieLz5Is66bZ1IX8Hbp99Ro2hEJhOwZdw83n34XrcVIpLMvjyXN5YHcz+gxaghT+vDhqFV4SJWoTXpye2pIcA3GW+6C0WKiqK+BAIUHfnI3jFYzXQY1Nw30KnlKnbnKP9mxITM1IJ1lEVey5PRGR2y8XCRxJLs9n7aICb6Jg8hKlaqVNVlbWRw+ji8bztOs68FDqmTzyFW8W37YIeUC+4TipsgJPF90gCeS5iIUCLFgZXvVMa4PGY6/wp21WVvxkbmyMuoq1uVsxzjg3REJhLyVeQsZHmFI/8qC22azUaNpZ9W5DwclA76Uvpgx3rEo/kaIxD8LGrMBmVDsIBZGixmLzfoPPb7BYiK7u5p7s7c7LktzD+OF9Bvxkf/z1w29Ri1vlR7iu4Huu1sjJ3CkpZAmXTcyoZidV9xNqNL7r97Hxb4m7jj/EbrL1AYigZBXM5Yy2jv6b4ZODGEI/5cxFPowhP8oWGxW2nS9VKpa7T1HRu3fvtE/CI1Zz6mOMspVzdx1YRu3n/uIOk0HrfpetlT+zMO5u2g39DPKO5ptlb/w2rBlOIn+9MOa4Bpklzb9DlkyWy181XgBjcW+M78+aRZfNV6gsLceAQLuiLmGYCdPjFYzTxbsY2XMZNyldnnfrJDhvH7xWzaNWM5bw27CS+bCvBNvMNIrmlcyljLJL5Hbzm2mUtOGQihlw0AEepu+z7Ggeip1Pk4iKd0GNY/m7aaorwEhAhaFjUUpktFu6Oe5wgO8mH4jW6t+cZClVzOW0qztprivkcn+SYzxiSXaxQ8fuSueUmd85K58Uv0rggFPg0QopF3fz8bS79k6ejUeUmfeL/+BnJ4avGQurMv+FPiTET63p5bvm/NwkSi4+8IniBAQ6exHjaadpac30qrrZXv1r/zaVsKMwGGsjb2WJ/P34SlzZnHYOOYO+HAukaWl4eO4PngENmy06nvpMKpwlsoRCGwcbS1iXY59MXOhu5pdNSeoVXc4fDIigQAPmRIE8FDCLFwGBUb4Mz0wAy+pMz4yN94fuZK1sdcy2T+Fddnb0VtMvJK+hHvjpzsWtpewr+4MbjInlkdOGnT5Y8lzyeqqwkNql4FN8ktCKhTTqO3mpRJ7+Iafwg2hQEiwkycbUubxbNoCWrQ9+MrdECJkRdRkZEIJbw2/hXOdFTySNAdvmQtvZt6MVCjimbSF3Bg+ls9qTmDFRrSzH2O9Yx2eIpFAxMfVxzjUnGMv2R12E9f6pwKwrfoXTFYzWZ1V6CxGYl0Deb7oAI8lz2FLxU/IRRIezd/NW5k3k99dxzdNOTyatxuFREqjtptGbTedRhULwsbwXOoCeg0ank6dz/SgTExWMz4yV1ZHT0FvNbE+Zyerzn1Iq76XtXHX8kXDWVZnbaFG3U6fUcvqmCk8kjSbClUr3zfnIhAImRGcyfbqX3kocRaRzn5Ua9pxFst5NHEOI7yiMFstfN+S5yBLYJfGrcv+FKVETll/Mw/k7MCGjY4Br1ytut3RteMpc2ZqYAanO8ow2yx8UPEjxX2NTPJL5ErfBCpVrdRo2hELRLwz/FbadL08kjzH3mumbmfFuQ/oMWpwlSh4KX2xw1PiLJFzhU+cg6RJRRJS3EKxWq18VPkTD+bs4GhLAe+OWImLWE63Ue04p67yS+bu+KkEOnnyQvoiBAjI763jXFcl1wcP59nUBYz1jkVvNdKpV2Gz2eg09LO//iz3xE1jc8VRmnU9APQYNTyUu4PhXlGDzsvvm/P4tbUYvcWI2qInROmFAFgUPpZk91BHf9CS8HGEKL3wuMzb4yJWEKr0/qtkCezhFq5iBd6yPy0ypEIxEc6+/3tkyaTn17ZiyvqbMVstGC1mivoaONdVgc5s/Nt38Gcw26yo/iwWXms2YOVfs7fsJlGwJGI8zmI5Dydez00RE3h3xAqCFJ7MDBqOy9/o8+oyqHiiYO8gsgT239wn8vfSaVD9S457CEP4v4YhwjSEfzn6TTq+b8pl6elNLD71DvNPvMmDOfYyz38FDBYzn1WfAMBqs2Gwmrj7wie8efE7srursWHDbLOHBGxInce+ujODfEBl/c3k99T95gcI7DuZ5zsrHf/eUXOSeaGjcZUoeChxFjabjbczbyXYyZN5oaM41VFGt1GNwWJCLBBSq2nn44pfiXLxZ1PZYTRmA4/n76Fe08m92dtp0/exvfoYMa4Bjt3eSxAgoFnXQ353LSIE3Bw5AbFAxPPpi/CSurBpxHKUIhnzQkfza3uJI9p5akA6oU7eeEtdmB86isl+ybToern7wnb8ZG6sjJ5Mfk8dt0VfhUwk4YGcz7g/ZwdrYqewKuZq3io9xM1n3mVKYBozgzI52VHqaLLfecVdrE+8HoD83jqcxXJGekWhs5p4JG8XKrOeawPSyOmp4QrvOK4NTCPGNYA3Sw/RpOvmrqytdi+YST/ouWotRnQD/7s3ezvbq45Rq+nkh+YC4l0DeW3YMpaGjydA4U6GVwSrs7awLns7rbpeTFYLGwr2c/eFT+g2qnGRKBz3W6Fqpby/hR6jBo1FT7xrIHNDRuIqUfBy+mKeT1uIp8yZJ/L3UNrfhBABC0LHIBWKadB28UT+Xsb7xjvM9mAPAJgeNMxe8hs3jbkhI3k6dQFSoZh093DK+1tYGXUVnjJnJEIx9epOtlcf4/niL1l2ehPPFx2g26Dm8/HraNX28F7FD9So2vls7J0U9dSzoXA/X9Vn4SN15ZGk2VwbkMrjKXPpMKiYGzKK6wLSCXbyZFHYWFLdQ3kqdT553TXcGjWJawNSuSduKt80ZXO0rZBbIyfySvFXXOiu5pnCL5gTOor1eTupULXydun3vDtyOaX9TdwTN5Ueo5qtlT/jKnViXfZ21mVvx2C1kOkVyb0XtvNA7md0GlS8NmwZvgr7RKXbpEFjNnD7+Q95LG8PJzvKsNistOv7qNV00DMQA/5E/l5OdpSR3V3NT61F3Bk7FYPVzFOF+zFaLZT2NdFn1rI+Zyf9Zj2XdBBX+yezfcwaNqTMo1bTwZcN51kZfRUbUubRpu/j1rMfcOOpd1hw8i3uuvAxFapW+/dPcx6vldolTysiJ2MDPqg4yrdNOZisFpaEj2ND6jykQhHxrkEEyT1YHTNl0Dn5asbS35j4L5f/AZSqmll06m22Vv3Cua5K3q04woXuSib5Jw+63u0DGzJOYikZHhEEDvibVkVfTZDCk0S3ECxY+arhAp/WHKNB24XeZCTRLZjDLXk8lTof8WXpa7WaDgLkfypJFSDg/oQZdBj6WRNzLd4yVzRmA9nd1fQYNY4OokAnT2JdA7kv+1Pa9H0IECBEQK9Jw9qsLTRre/hr6ND383DeLkd0vkQgwmg1s+rch47L/pUwWkyc7izn6cLPWZ21hbL+Zor6Grgraxvrc3eR11M7qJj393A5qdKYDdSo2nil5GvAPiUWCYRUqFt5IPszRxDEPxP2BEg/9o9fx5SAVJQSOYFOHmwedRu3xUx2bMT8JfQatX/xt1RjMdCi++cf8xCG8H8RQ4RpCP9y5HbX8EzRF4NKWfN6a1l9fotjKvD3oteooUrVxrG2Egp66mi/7IfMU+bMSxmL2VxxlPWJ1xOgcMdgNVEzEA98f/wMSvuaGOYZwa/txY5QgWmBGSS6BWMd8ByV9TU77rPHoMFisyIVivGW2mO2J/klUa1uY2PZYTaPXEVhb/3AZKGTJ5PnoRTLudBVhVggol7bxdul3/Fs2iL8nNw41lbCwrCxjsfbVG73HshFEj4auYr8njpeKv4KsEdyX3rNNlccxc/JgzZDHwaLid3j7ibCyZfpwcPoNqjZNe5uALZXH3Mc+5eNWWR1VSKXSHmm8Au+qD+HUizjkeTr+aLxPC+VHGR51CR85G64ShR0GVSozXqeLNjHztqT/NRWhMVmpVHbTVFvA1EuftwSOYHHk+fyYM5OrvCJ5f74GTyduoBnCj7nCp843ir9jip1GwcbslgRNZkYlwBiXQM51JiNUCDg0aQ5uEuUrIy+mp21JznSWsAjibNZHHYFAAcaztOg6cBVIsdis9Jr0iIATnaUkeoeSnlfMxP9klgYNhaLzWY/H9Rt3HPhE9Zlb6dc1YJYIMRJLCN6YKo03ieex5LmsLf+DA26LjZX/EiTtttBqLxlrvSZtBxszGJq4DBEAqHdVyZ14unU+UiFYqYEpPFLWzFigZCr/VMAONNZwZulh9g+Zi06i4F2fT+lfY18PHo1N0VciZtYQYJrEGCPOr4hbJRjStFr0lCr6SDdI5xf2orZU3+at4ffygS/RIp7GhjrG8crGUtZETMZV6kTwU5eLA0fzxcN5zjbWUFOTw2p7qEIBQKqVa08njSXbxqzGe0Ty46aE6yIugqN2TBQPqthf/0Zu1cGyOmp4Z7sT9BbTAQo3HkwcSZ7a07z0ajbB8iNhmT3EOQiCQqxPdXvsfzdA3HwGuQiCVabFYvVntzmKlbwTuYteMlc0JgNFPbZJap3RF+DzQbDvCI50HCeJwr2YsVGgmsQo71j2Vt3GnepE/dlb6egt54PK48iE0m4+8LH3BgxjmcLP0dl0vFs6gJuipjAF/XnOdZWwsvpS5gVPJxeo4ZEtyBWnP1g0PdAuaqFVec2ozHpCVN6IxIIGecTz6yQTD6u+gUbNlLdQ5kWlIGPzJVvGrN5pvALbNhwEsv4rOb4oO+cl0u+/qsL5g59P0/k7x3Ue3Rj2BXoLCa+HpCcXsId5z+iVt1Bt0HFs4Vf0KTrZkn4OPQDHrT3K36grL+FjeWH2VN3mp01JyhVtfBC0Zec7aygsLeeZRHjB93n5dK9myOvpFHbxRcN53i8YA8qk47vm3N5ueRr7sv5lGq1/bvQYrVQpW6jUt2KSCB0pLvJBiakhb11fzFSG+wT4ZK+JgQIeDl9CZ+OvRM3iYI+k5aznRV06Pock75/BaQiCYluwQQo3NFbTKw8t5k157dgslkIVXoT4eyL6K/4f9r1fXxS/StdA1MYjVlv97OmLWS8TzwfjbqdN4bdhEggRGPRY7H+c8pu/xwCgQAvmQvOl23u+Mrd/iZZAgYVc/8e/jwifQhDGMI/hiHCNIR/KboMKjaWff+7f+sw9FPa3/R332eHvo8n8/dx46m3eTB3ByvPbeaWM+9R0d/iiMH1k7uxMHQMBqsJd8ngGNkgJ0+WRVyJEAHjfBLwk7sxN2SUgwQku4cwzDOCICdPwC6Jezh3J+X9LUhFYu6Mv47THWWM9Y51kKZbzrzHGJ9YxvrEYh04hhhnf9YnXs97I5bzxrCbyPSMwlfmSo9BTYZnBHk9ddwbN23Qsc0JHoGH1Jk6TYfDs/TpmLU8l7oQsHsGVCYdm8p+wEkso8+opcekYVPZYaJd/Hmt5BveqziCXCTh5fQlDB8o5MzqriKvu46L/U1825zD4eZ8TraX8WtbMYW9DWR1VdGu68VP5saL6YvxlNrjgi/5slZGTUZjNvBFwzlev/gteouJh/N2UaVuBZuAsT5xfFF/lsWR4xAJRUS7+LEobCyvZCyh16ghzT2MJk03K6In4yZxItY1gBfSF+EpdabT0M9zaQvxV7gzMziTx5PmsCJyEj4Ke5nu48lzWR1zDc8VHeDljCWU9DZydUAq++tOk+4eTpDcg9cylhKk8KRG0061ph1fmSsbRyznvfIj3BI5kRT3UO6IuYYT7RdZn3g9SpGcOk0nzboeGjVdaM0GDjXnkOQWghAh/SYtn45dy9HWQj6q/Il+k4694+4lQunD7tpTPJU6n3SPcMcUYpJfErWadkKVPrxffoRZwcMp62+mzdCHl8KFgt46crtraNH2YLJaHFHeYoGIDSnzONpayGjvGJ5JWUBJbyOlfU2IhCJWntuMVChmd81J6rWdLDu9CbXZwC0RE2nWdeMpdSbOLZDvm/IQi8SoLXqeSLmB0+2lzA4ZQWl/k2NxDHCw8QIGi4kbQkYNOu+eS1vEM4VfsKfhDItPvoNUJOHLhiyuC0znTHsZT6cuQCmS0W/SoTLrUYplvJKxFIVIykN5OynorUNl1qO1GAn9sxSxNM8wTnRcxEvq7JBHykUSnkqZh4tYToSzD5vKD/NA4kxEAiFl/c3cdOZdRnhG0ajtJLenlm3Vv1DW38LuulN83XSBX9tL0Jj1OIlk5PXU0qrvJcrZ7zffFRqzgZ/aisjwiODj0au5Png4a85v5anU+Vzjn8JjyXMRC0RcHZCCs1jGO8NvxWKzccf5LfSa7DK8e+KmDsjz2nggZwc9f6EXp8+kdcjkwF4KPS0og21Vv9jPEd9EPht7p0Oe98bFb+k2ajjVWQbYO9FGekcjFYo52lpEjbqd64OHA/ZNj0fzdzuI5kivKPbWnXY8lr1LyYP1ibPwkrlwpKWAK3ziHOR1yemNvHrxGwDG+8b/ScopFJHuEc5zaYt4O/MW0j3CSHQL4t0RK3g0aQ5X+MT9VVletLM/G4ffyksZi0lwC+Ld0sO8kXkz98RN5Sq/ZF4s+YqN5Yf/4mv2z0CQkyfvj1iJm0SBxWbFis3++f+d0IzL0WVQ8Ujebj6u/pUXig7SZ9TyQcWPbKv+hY1l3/NQ4vV4yVwY5hnBxuG3smn4cgKdPP7i/f274CZ1GiSnvByigR7AIQxhCP9zDBGmIfxLYbCafxMVfDnye+r+rvvTW4xsrfyFs12DjfydBhV3XthGu74Pk9VCUW8DUpGEX1qLuThAypQiGUEKT75ryqVa3cbzxV+yPncn741YwcLQ0Sw5tZEVZz/g8aS5PJU6fyBYoZ/vGnPI7a117AoX9dZzrP0iLxYf5ObICQTI3Xk8ZS7fNeVy27kP8ZS50GHoJ7+3jiWnN6K1GLnQVUmGZzgn2kuZGJDMY/m7mRk8jCcK9g56HnvrzlDc18iMoGE8njSXx5LncLG3kXClD+9k3sJDSbPQWYx0GVXsrDmJu1SJyqSj36Rje80x7o6bSoyLP8+mLmRv/WluCB3NMM8IMjwjiXXxZ1X0VQAcbsnjp7YiwB4K0Kjt4rWL34LALtOJcPYddFzpHuGDpIh76k7TY9QQ5xKIUCBAbdKxLn4GPzTn82DODmYGZRLk5MmiU2+T3V1Np6Effyd3lp7exPbqY/QYNTxf9CUbCvZxd9w0JAIx9+V8yjOFX5DsHsponxjuvfAJ6/N2EecSiEQoItMzEq1Zj9Fm4ePqX7g1ahI7ao7Tb9bhJ3fn6dT5ji6f14cto8eoYXpQBs8XHWC4VxQvl3zF8Y5SHs3bTbCTB3fGXMv7FUfYWvULUqGEBWFjEAoE3BR5JWke4ZxqL+PX9hKuDxpOjIs/FpuFPpOGd0es4GxnBVablQ5DP1tH34HGZJ8sHWzIYtuY1eR01/JM0Re8dvFbnERyYlwC2FN7igZtF3trT6MxGxEg4JnUBRxuyWN33Skez9+DQiyjWtNOvHsQzxZ9YQ/HyNtNumcEd2Zto9uo5unCzzHZLFwXkM77FUf4sOIoI72jebrwc9ZmbaNG3c5onzjuzd7OUwX7Ge8bz4MJM3k48XpS3EJwlyp/EwyxqewwSyLGIx0IkzjXWUFRXwMGq5lydStCBIOlaAhwEcvpNWp5OGk2v7QWU9zXyM6aE+T21AL2xRrAAzmfcVfcVHbVnHBEqestJj5vOEdZfxM3RU7gWPtFSvqauDVyouMxvmnKYbxPAtMDhwGwo/YE3zfnAbAwdAxthj4+rz/DOJ941ufu4rHkOYP8apeQ012NQGDvy9FZDDTpunmm8AvGeMdS1t+Eq0SBr9yNR5PnEOTkiVQoZk3sFFwlCjaPvI0FYWN4Z/ityEUS1sVPQyn6fU+J9c92+ruN9oS8DSnzmOibyOrYKcS6BLB51CqGe0byWMpcfGSuPJl8A69lLGO4ZySJrsG8lXkzAK9d/IZxPvGkuIc47lMmlPBkyjyeyN87SEa8JGIcvjJX5oaMYvuYNbw7YgVRLn58NHKV430ASHYL4ZGk2YP8mUqxjHE+caQPBDzYS2+DuNo/ZdDE4/cgFYlJcQ9lmEc4BxrOcbKrjGcLvyBI4clLxV9xsqOUb5tyqFF3AH/yslar2mjUdqExGf7q/f8RGC1mWvV9aC6T1vWZdHQZVJj/ihxPJpQwI8h+bp3ouMj1x15x9KFdG5CGYoAoykQS0j3CCfwPJR4+MhceGpBF/zlWRk3+i2RqCEMYwt+HoeiUIfxLIRYIcZco6TVpfvfvYQNx0H8U3QY13zRl/+byUKU3jZoueowaREIRXzVeYGHoGGaFDCfWNQAnsYx41yA0ZgNqsw4/uRvBTp40aru56cy76MxGrNgIkLkjF0nwlbvRru/jtZJvmBaUwZzgEfgrPDjQcA6FSMotkRPwkDqjMelZET2ZeNdA3hooWF2btZV0jzBOdth3jo+3X8RP7saTBfvYP34dBxuyeC7tRl4sOuiQ4b2YfiNbK3+hqK+BR/N38+WVDxDrGoDOYsCClR6TBleJE3dlbUNvNfFs6kLEQhEP5+6iRtPO48lzOdJSwKrzH/Jm5s00arrI6a6hqLeBp1LmY7VZ6TNpmeyXzMGGLNoHwhUCFR7MCRnB0wX7eSptASabhY2ldq8X2Be9QgQ8nLeLZ9MW8m7ZD1Sq7VHiCpGUZ9IW8Hj+Xu6On0qTrguVWYcNG70mLcfb7Cb9t8u+52r/FH4ZiKLO6qpkol8iXQYVSW7BdA7InGw2Gxf7m3godwddBjUai8FuHBfAuc4KRnlF46dw58HcnbhK5GCDWSEjwGajXtvJE/l7uS4wnSeSb0Bl1vNI3m6iXPxYGT2ZG0++jclmQYCA22OuQm3S4+9k96mcaLtIv0MuKuBYWwkbyw9zc8SVPJe2ELFAxMqzm5nsl8S8sNFsq/qZ+xJmkNtdS7pHGIeacpkXMpKH8nbSqO3m6YL9RLrYpx1Lwq/gdGcZ0c7+TAlMw03iRLSrPxP9kxAjRC6WMC0wgzAnb3zkrsw78ToGq5nsrmpeSL+Rh3J30GvS8HKJXZ7pJXXmzcybadP1sX6g66pG3Y6LRI63zIU2fd9AyavA3jskdbYXoRo1iARinki5gZvOvOuQ4c0MyuTDyp/I7anFSSxjfeL1aC0Gbgwfy81CCW+UHuKWyAlsKNiP2qxHKbKXgKrMeu68sI3Xhy3jyYJ93B03FR+ZC2cGEgnvjL2O8b7xrMnaSpdBxTeNF1gaOYE2Qz+hSm9+aMlnf/1Z1sZeS62mg1iXACb6JrKhcL/jM23DxjOFX/DqsKWc7Sx3kK1QJy9mBGfyafVxVkVfxZrzW5gelMH5ripU5sFeOIAQJ2+sVhs5PTU8XWhPPWzV9/JM0RcIEeA8TMFwryhcLwtzuNo/hfG+8XhKnREIBKS6h/L1hIdwEsn+YsS2m8TpN991ZzrLAfsEUiIUIxAIiHL244X0G3GXKtFZjLhIFLhJnZCJJBisJoc8bKJfEn0mLcW9f0rwNFhNHGzIYnXMFF4v/RZPqTPLoyZxjX8K8oGQhUsSXrVJz69dJYMkWzWadjr0KtwkToP8V5eXuwKIhWKc/2CymlQkRioSsyjsCpq1PRxpLXD0sAE8ljSHWJcAeo0afm4t4v2KH+kzaREiYIJvIvcmTHN0VP29MFnNDs+S2WYhSOGJyWqm3dDP6qwtvD9iJfFuQYNI4yU4S+Rc45+KwWLmjdJvHQT01siJ3DDgS/3T6/HXY73/nRAKhIz2jmbLqNv5oOJHKlQtBCg8WBl9FanuYb95b4cwhCH8YxiaMA3hXwovmctvtPaXIBWKGfFnyU5/CwarGZNt8K7hKK9o1idez8YRt1Lc18hjubu5OWICTfpu1pzfSrOuh9HeMahMOu7L2c4X9efwkrrw7ogVeEqd0QwkIHnJXHg4aTbdRg39Ri37687ya3sJD+fuYoRXFB0DKVWf1hwnyS2E2SEjGOEdzazg4YQpffhg5G14yVxQD+jgwV6sGab0YXPFUV5Iv5GLvU2kuIVS0tfIiuhJhCt9eDvzFnbVnGJ51CRS3EJ5LnUhmyt+ZPnZDwABBouZ10q+RSIUgUCAxmzgify9vFR8cBB5sWFDbdLbF6gDpNJoNfNo/m721J4mWOnF5sqjDrIE0Kzr4d3yIzyZOh9fuRs6i5GrA1KRCSXcFz+dz8fdx/sjVyITSTjVXsas4EwkAhEZ7hG8O2IFCpGU5VGT2Fb1Cw/m7GRZxARS3EJ5puBz++vjaX9/j7YWYrFZiXL24+Gk2ejMJp5NW8iqmKuRiSREKn15OWMJAgTUa7vQWAx4SZ3ZOHw5j+Xt4XBLPhEuvpxoL2XT8OW8kXkz5aoWPq8/i8lmJbenFpPNwjdN2fzSVswjebvpM2mpUrXiKnHCTeqESCDkw1G3McorGoPVzNOF+3nt4rfcEDaKDYX7adP3UtLXSM2AhG17zXG+arjAo3l2KVSTrgcvqQtrYq+lRt1BrGsgHfp+JvklUqvp5P74GUQofbkpcgJRzv7sGHMnvUYtr5R8zesXvyXMydsx3bgvezsI7Lv70c7+eMtdqVS1cmfcdQBEOvtitJq5588km+uTrsdFImdX3Un6TTrcJUqeS1vEuY5KHkuei4dUicFqRm8x4SKW88qwpTRre/CQuvB10wXK+1u4IWQUAQp33sm8FSeRjPsTZqAUy5gfOpq9dad54+IhWrS9CAVCYl0C0JoNqM163CQK3si8iefSF+EqUaAy6WnV9eEuceJwcx5ChLyasYTVMVPoNPTzTun3vJq+hA0p8xjhFY2zWMZ9CdOZE2yPdfeVuZLgGkRuTy2vD7uJDYX76TKoUIplrIq+ireG3cwdsVfzQcWPdBnVuEkUyEUS6rVd/NRayO0xV9Ok7WLbmNVMC8hgS+VPCC8L4xAgQCoQMyt4OFqrkReLD2KxWYlzCeTrCQ85/IMvFR9E/2cBL84SOV4yF8dUTSoSIxQIB5GlPqPWMcHo0PdjAx5KnPWb76wzneVoLQZHma5AIMBdqsRitZDXXcv63J3cmbWVanUbJ9vLeLJgPwmuQcwKyuSFIntfVJxrIDODMgHYW3/a7ku78kE+HbOWeaGj8JAN9rqoBwqmL4UXZHhEOOR5t5//cJBM858FT5kzDybOGtRVlOoeyiT/ZJRiGSfaL/JSyVcOL6sVG7+0F3Nf9qd06v+xJDeRQIhSLEMqFBOm9OH9kSvZPGoVAQp3ZEK79+73yNIlGK1myvqbB11WoWr9r/P9KMVyUj3CeDljCTuvuJt3ht/Klb4JuF9Wt/DvwJ+31vwfarEZwv+HGJowDeFfCpFAyLSgDKrVbRwa6JkAcBbLeX3YMvz+zl4LhUiKi1ju2Eke4RXFjOBM7rnwCZP9Epnsn8JNURM43nGRVl0PNmzsrz9LnaaTgt469BYTdZpOrNho0/UNio+9JG3bVvULYUpvRnvHkugWTElfI4/m73Fcb1pgBp2GfmrV7cS6Bjp+kD2kTgzziODH1gLHda8PHkG9ppP5YWPwlCjpRYuTWEaMawBvXPyGl9IXY7VZKVe18Fj+Hp5PW8TRlgJ+aivm49Gr6TKoOdZewm3Rk+29QsOXszZrK91GNRqdASECXs1Yyo8tBZztrOC1jKXsrTvN+a4qACb7JfFrWwlhzt4cayvhl7ZiAG6OmIBIIGRb9S8cbsljpFcUY7xjea3kG7QWA1tG3Y671Ik9daf5pa2Y1zKWEiD3xIqFq/1TsGJDJhBjE0CYszf3xk+jor8FP7kbCW6BFPbVc6Qln6sDUsjqrnK8Hlf4xPFLWzFjvGPZUX2anO4a3s68BYlIjKfUGaFAgGXgR9VN6oRAYE8O85ApEQmEjPeJ51BzDoeacnhmYOL1S1sxV/knIxII2VV7kpMdpfbbSxS8mL6Yl0u+pseo4YnkuXxafRyxQMSqmKvoMqh5JnUBD+buoFHbzVOFn/NU6nzkIgkGq5kfWwscxx7nGsgjSbMRC4TozEaS3IN5sfgg80NHsy77Uyw2K8+lLeShxFm8U/Y9d8RcQ6Oum4m+SeyrO8Pq2GvI7q6h06jCho1QpTedBpVd9mYxOfqbEtyCudo/BYHNPrF4NG/3oPP/haKDPJu2gHvipiGwwZzQkTxf/CUPxM9AIhRhuMygb7RaMFstBCjceDB3Bx2Gfo62FrI6ZgrPp90IwP76s6R7hLHninvQmo0O4t2i78VoszA7ZARihLyVeTPOEjnOIhkSs46X05fQbVRzsDELT5kzo71jqFC34C93w0Us5/2KI1wXkE6ZqgWz1UKg3B0h9qnXz23FzAoezs2RE2jX9/FY8lzkIjHLwsfzUdVPvDt8Bb4yN7pMKowWM4eacvCRufJyxhIsNgv3XPiET6qPEerkzQivKPwU7khFEj4adTt12g6eGZgiPZE8lxiXAJo0nfjIXHl3xHLeLP2O9UnX4yd345WMJbxS8jV3x03F/W/IljoNKt4v/4GbIycSqvSm16hhd+0pxvnG02vU8HLJ17Tr+5gXMpp3hy/ns9rjVKraCFJ4clv0VcS7Bjoi+C9BJBQRqvQmQOFBk66bHTUnSHYPxYYNuUhCpLMvI7yi6DPZ49jDlT4oxTJ+bi3imoBUAv6Kn0YukhDt6o9MKGGMTwwPJ85GZdZxx/kteEqUvytd/J+iU6/iheIvMVj/dA4W9NbzbWM2k/2Sea/ix9+9XZW6jUZd1+92aP0tCAVCYlz8+XDUKpwlchQiCSKBkPdGrMRoNf9GWnw5ug1qNpUfdshTL33Xn+wo5YWigzyaPPt3qyX+k+EiUQxKBf13Qmc2crG/iVAnL7zlrpitFipUrbhJnP4jvWBDGMLfwlBx7RD+V6Ay6egyqKkd6FgJdvLCW+byd0sdLFYLu+tO885AkMS80NF4SJV8VPkTYC9QrVK30W/S8UDCTBq1Xey5zBztJ3dj88jbaNf3c+eFbRitZgIVHvZFoq4XqVDMs6kL+bTmGNXqdj4ds5abz7zrkGskuAaxJvZa7rqwDYVIyo6xdxIysID6rObEb5K1lGIZr2YsRYCAHqOGx/P3kOkZyYKwMYQqvWnQdKIUyzHZLDyatxu1WY9MKOGNzJv4qPIoYUofwpU+hCt9OdleyjWBqbxQdMDhC5MIRLw2bBmbyg/TrO3h2bSFlKta+KDiR9bFT8NbZv+heq7oAG8Pv4UD9eeIcPYj1SMUtVlPpaqNFm0Pt8deQ426jXXZnzrSw8KU3nwzoOlfHXMNUwLSkQlFGKxmSnobiHUNRCwQ8WLxlzTounhz2M0cbsnjk+pjjPWO5drAdJ4p/Pw3KU73xE0l1T2UVy5+Q5O2mx1j7qTTqOKe7E/QmA0oRFIMFpPD4L4hZR67ak+S3V1DsnswP7TYCeni8HGIBUI+rTnO0ynziXYJYMnpdxyPc4V3LFcFpPBs4QHWxFxDqNLHIWO7xj+FG8PHsbPmBFcHpLChYL8jxn2iXxKjvaJ5aUAGBzA/dDRzQkaiNxvZWvUz/SYdd8Rcg6/CjacLPkchlvJgwiw+KDvCnLCRPJG/j36TlpczlhDp7MuDuTuoVrezPGoScqGEFPdQ1uXYe58uYYJvIjOChvFY/h52XnEXt539kF6TBi+pM3fFXccbpYfoN9nlpO+PWEmLroeXS74i1jmQm6KuZM1A6a67RIlIKKTLoEIhkvJ82iI2Vx6lUdPFmthr2VL1E2qTnmAnL17OWEJZfxON2m4+qf6Vp1MXoDbriXb2R2XWkd1dzZGWAuJdArklciISkYgfWgr4ta0Yd6mSvJ5a3huxArPVgkQoQimWc6qjnNOdpdwUMYGHcndiw8aDCTMJdPLk4dxdGKwmboq4EpFASKZHBF80nrd7ARUemK0WnERSylQt3J/9KWN8YpkWmIG7VMlj+btxkzjxQMJMdtWeZKJfEsfbSlifNBu91cQD2Z/hr3Dn1siJCAQCPq0+Rp2mkzWxU1CKZWR4RtBn1A4qOb707069CpVZh4BLJvo/TWx6jRpeK/mGI60FeMlc2DLqdr6oP8uO2pPIhBLeG7mC9bk7HX039mOcQap7GEqxHFfpX1/ANmt7WHH2fbqMaqYHZnCFTzwJbkEEOXnSoe9DN1BJEOjkSa9Rg9FqdsjuLkefUYN0YKoCoDbpaNP34S5VOhb+9ZpOZEIxfn8lDOEfgc5s4KPKn9lRa69zuC9+OoW99fzYWgjAuyNWsLniRwouK/e+HPcnzGBh2Nh/+PHbdX0caS3g++Y8nERSbomcSKJb0G8mb5ejx6BmS9XP7K8/y5qYKcwNGclPbUW8WHyQKf6p3JcwwzEVHMLfB53ZwNmuSh7O3UWmp71svVXXy+qsLXjLXNg0fMUQaRrCfwz+KDcYmjAN4X8Fl3a+wp3/Ps/Sn0MkFDE9MAOT1cz26mN8Xn+WZRHjWRV9NR9WHnUYzt0lSmJdAghy8hxEmNI9wnEWy9FKjMiEYvwV7mwcfis2G9x5YSsqkw6ZSIzKrOeWyIl805T9m44mtVnH7OARWGxW5CIJPQYNGouBfXVnAPviel7oaId/Y0/daaYGpvN4/h6s2FCb9QgEAlac+YBboybyc2sRK2OucpjGr/JPpry/mbyeOvJ66pgemEGVuo3Jfsm8VvIN9douRAIhMqEYrcXIo/m7eS51IX5yd5zEUpzEMraPWUODppMvGs5xZ8xUvprwIHqLiWlBwwYIIhxuzsNf4cHKmMm8X34EGzbWJ17PyyVfUdBb71jcLAwbQ4p7KPNOvM7TqfNJdw9HJBSx6NTb3BV7HXGugeT01KK1GPmhJR+AO2Ku4akBshTt7M+L6Tfyeum3nO2sYEfNCd4efiuroq9ic8VRTDZ7SIfGbBj4MV1OraaDR/N2U6Npx2A106rrpUnXTZOuG4A5ISMJcfKipK+BUKU3HjIla7K2DDpXTnWW4ylz4aNRq+gyqPGTu3F33FTeKfueo61FjPWJQ2Mx8G1TDusTr+fZoi+Y4JvAeJ94ni86YD/fBEIsNiv768/iJnEi3jWQu+KmktdTS69Rg7fMhefTF3Gxr4lbz77HUynzUYikBCo86DVpWJ+7EzepEz1GDWKBiAhnX061lzLRL5FQhRflA5LKQIUHa2Kn4CyW8ULaIl4v+ZYnUubySsnXPJo0h331Z3g6dQEvFn3JY8lzye6u5vniLwF4K/NmOg1qrDYrXjIXXs1YCth4JG83vUYtCpEUd7ETq9Ku4nBTHu8OX8Fd2R+zJnYKn9edwVXqxPbqY5hsFgp76kh0D2F11ha2j1lLSV8TVpuN2aEjKO5vRG3W88lADD8au5H/kbxdvJi+mIKeepwlcjZX/ohIIMRoNTPKO5qznRWOhLZLz3WUVzQvl3xFhmcEZosFD4mSvO4aop39UZt1lPY3obEYONpaiMqko07TSau+lx6jBqlQzF2xU3np4sGB+H4ZWW1VlKmaKVM1Y7CaECLg9IB/qFXfS7dBTbSL/yCyBPZJTE53Dc8XHaBhYBMixiWAJ5NvIMrFD7FQhKtEwU2RV3Kqs4wug4o5x19z3P7agFQKe+sHlYP2mbRsKNjP/vHr/iZZstis9Jk0jiLsQ825dOj78VdMwU/uho/cDavN6vAb/aVJWK9Rw6fVx0l2D2GMdyxWrPzaVoLWbOTawDTH9UKV3n/1eP5RKMQyFoWPJbu7mjkhI7naP4UpAfbH9ZQ6E6zw/I307XL4y93/4cdu0naz8uwHDo8bwLqc7Uz0TeThpNl/kfR4yJxZGXUVV/omkOAahKvUiWv8Uwl28iTK2X+ILP0PYMUexmHDxoXuatZm2aXxeosJi82K7V9UAjyEIfwrMTRhGsJ/NLoNapRiGbKBxKJugwqJUIxcKKHTqEJtshvR9VYTN556x/FFPCd4BNcFpjt6ZgQIHH9bHH4Ft0ZOotOgwkksJUDhgcasp0nbQ5dB9f/YO+vwKO79+7/WsnF3VyJAAgGCu7u7uxQptKWlStEKRYq7U9xdi3sCJBAn7p5Nsr77+2PTbXPba997v1e+P87z5HmSyezM7Mzs7Od83ud9DmsSLtDE3h97qaWxctXLrTFp1YXE14aZbmg2CWuJGfEVOTwvfctk/05UaGq4WfCaEGt36lm5oQd2p96ig0v92kBODaHWHiyPGMGiF4ewMbGgWFHJnJCefBt3mnxlBdYSM/R6PRMDOpJVXcyp7KeAoadlTnBPPok5hEav5euGQ7GTWvLlq6MGe9z6A+js3IC31YVMe7INbwtHOjqHEWnvj06vZ1ncCb5sOASZWo6VxIxv35xhlG8bzEQS1DotXhYOfPHyKJ81GMiu1Fu8rjA0mpuJTDjZ7gO+eHmYV+VZaPU6+nhEcj4nGq1eRz0rV75pPJpR93/EUmzKlw0H86Q4lTZOwVhLzNmZepMxfm2xM7GgUFHJ8axHjPZtg1qrJbkqn6clqdwrSuBgqzk8Lkkmws6Xz14cJsTanc6uDXCQWuFv7sQnL3/iSa08ToiAA63nYCmSIhAIKFRUciLrMRdzY7CRmLMlaioXcp5zIP0eEoGIva3e44PofXibOfJF+GA+iTlIX8+mPC1J5UFt5srOlJvEV+bwXePRHEi7y6vyTEKtPfg6fCjbUm5wPT8WJ6k125tPo0ar4qf0+5zLec7MwK708mjMnGe7Sa8uQioUG+RTlk5sTLpCsizfeC+viBjJhZzn3C9OwtPcnoVh/WorUXI+rt+fMGsP4sqzaOMUjEyjwEpihlgg4pvXp7lTFI+fhTNLI4ZjIhAx4dEmI5H3NLNnU9QUcuSlWInNWBp7nO7uETSzD6RGq+RZyVu6uoUTW5aBWCSiSq2glVMwEoGIZ6VvqdYosTOx4KtXRznQajYPipJo5xJKTk0pq+LP8X3jsRQoyrE1sWDyoy2o9Vq6uoYz3r8ds5/uplxdTUvHIBaG9WdJ7HFiytJp5xzKnHo9qFTL+fbNGZJkeYCBoBxsNbeWQAqxFJsiEgp5U57NZ68O82FoX5Iq87AzMcdaYs76pMvG82cqkrCp2RRCrN0BPbLa4wYoUVZxIee5Udr4C6YEdEKuVXG78A3bo6bj8Ceyr1RZPmMebPhdFdRMZMLB1nMwFRqMGNzM7EipXfcXdHJpQHPHQFa+Pv2Hz65NzSbT9C/0aGr1OpIqc5nxZAdyrQpHqRUigZACRQVSoZhNUVMItfb4q1V4lU7DueznfPvmDAIELI8YTo1WxbJa0r8sYjidXRr8xTyifxZKlDKkQgmWEtPav6sQCQSYi6SsTbzI8cxHgKG/rJVTPe4XJWIhknKozVxcTG1+FwT816DUqvkh/jyna5+Tf4rtzacTYefzF7eh1+vrOED+6d/v8D9DtUbJvcKEOk6wLqY2bIma+s7q/B3+o/C3coN3pg/v8B+LAkUFC57v43lpGkqtwT3qh/jzXMyNQVE7iAm0ckWuUzHtyTb06BHUNn2H2XhyKO0eCq0aV1Nb9reazSifNgCcyXpGtUZJgJULEoGYnJpSlFoNi14c4ts3Z3AxtWGCf3sa2/niYmpDH/dIxgW0Y1JAR8JsPImw80Gr11GtUbL89Sku571kU8pV1DqtgTS8Osrutz+j1+sZ7dfGSJbAkBmi0mlY1mgEAzybMjOoG45SK76OGEaItTtboqayvNEI9r29zWi/tjjWSmneVhVyNusZ65tOZFnEcEzFJgZb7oaD+SC0D60dg3kjy0Gl09DTrRGZ1cXsTbuDHj1bUwxN8x/FHECt1/LtmzPkystYn3iZZg6BrEm4yMrXp9kSNYV7RYlGsgQg16pYGHOQTxsMZnXkOMQCgwOhVq8jyMqVrxoOJbEyl4Y23hQrZbX9I3pczez4MfESUQ6BPCt5y6o353jv6U4a2HhzrzABGxNzkirzuFkQh7lIikwtJ9jKnTflWUwP6sKtgtfUaFU4S23IV1WQWDvgBkOz+EfRB1Do1OxLu4O1xIyOLvXp6d6IbxuPxlQkwdfCmdG+bfihyVielbxlckAnwu19OJX1lDxFBX6WzjwsTmJZxAgjWRIiILokjXF+7ejv2ZSZ9bohEUpo7hDIMO+WfNt4FG+rCjiZ9QQfCycGezantXMws5/tYn5IbzzM7FHqNOx6ews91AkwBRALhbwX1B2pUIymNgCzuUMg3zYezbOSVNYmXiTCzodqrZLHJSnMfrqTPEUZr8oza8nSMH6IP8eXsUdZ02Q8p9p9SD+PJvTzasqu1FusenOOtQkX+bj+ALQ6PQui97G11nK8WqMg3N6HG3mxfB9/jsPp91Ho1LypzOb7+LOczHrMmibjyVOU08KpHvvf3kGuUfFx2ABUOg0Xc1+g0KpZEj6Mbm7h9PZozM6UW/zYdAItHYMY69eOjYlXGOHTmkkBHXk/uBfbkq8j16rIqC42ngOFVs3j4mQsRCbcLXzD45Jkpj7eymevDD2C9woTmBzYkSb2AbRwrIdY8OsgP9DSFalQjFyrQiwU17FLtpWY0c45FPffuK05S61p5RTM4YwHhFl7/s4tTKFRseftz38Y/KnRaSlTVrEk7gRTHm8jr6bcaGn+C16WZ+BmZotbrbzNWmLGpmZTGOfXDjDIcUsUMkr+THCrAEMOl0ggxMXUhm3NpxkGk2b2iARCJALR3zRwNxGKaeccSoStD3r0fPrysJEstXSsR6Sd/7+ELIHB5EeP3hhW6yC1xFxkQpVGwUT/DjSzD0CAgIVh/ejk0oD3g3uxvtkkLMRS7hcl/t3mDxXqGq7WVrX/CBf+wFH1T/Gn5/gdWfrnQCoU42XhYPxOBnCUWhknP9/hHf7b8K7C9A7/NpRW1lBRo8DL0QaxWERljYLSyhqc7SzRCrWsib/A+dxoRAIhyyNGcj3/FddrNfEHWs2hnrUblWo521NucCTjAbYSCzZFTeZmfhx7397m6/BhPCpJord7JA5SK6wlZhxOv0975/pYqs3Rm+hYlnAcEPBZ/YEodGp2p96ip3tjAmptoSvVciQCEW9LijERirGyNEGhVZNcUkBb1xDulcazKflqnfflZ+HMZw0GUqioNMrwZvv2pFBZwdG8B/T3bEo3h3CsxZYU6Su4mR/Lw5Jk1jWZwInMR4zxa4tQIGRX6q3fWajPCOyKh7k98ZU5iAVCHhensCxiOCq9hi9fHiXYyp1x/u1YFneSuIos7E0sWRw+hO/enCW7ptS4HalQwtKIYTiaWLHi9WnGB7THXGTCB9H7Aejn0YRQG0++e3MWPXpG+bbBw8wOZ1MbPn95BKVOzUehfYlyCGRf2p3fHaebmS1rm0xgSezxOgRssHdzAixcaOlUj/ef7aFQWcmuFjPIqikht6aMjJpisqtLGODVjOjSNIKt3TmYfo/5Ib14WZZOiLUHX746ilKnoZ9HE7wsHHlRls6set1IrMhjb9ptTEUSZgV142VZBm2cgrmQG8NE//Yky/KZH70PgHF+7WjtFEyxUkaVRsF3b86ystEoxAIhFiIpsRWZ6PUGd7RfrIp9LZx4WJJEvryCkT6tKVFVYSUx5f3newiydGOId3M+fXmYpRHD+THhEmnVhYgFIpxMrciTlyNEwMpGI/E2d6RMXc2FnGg6uzbETGTCzFo5YTP7AAKtXPkp4z4Aw3xa4m5qR5iNJ5++/IkPQ/tyOe8lE/zb8+Wro0zy70C1Rom3hSPzn+9Do9diIZIaJV7tnEOZFdSN6U+2MymgIwWKCg6l3wMM0rhfglZn1+tBoJULH0YfwMvcgfmhvZAIxXwScxABQr4OH8qN/FjaO4eRLS9lXcJF5gT3oKtrQ+RaNadznhJfkcNgzyga2nnz/ZtzDPSKYtGLn1Dq1Lib2eFiamOUzH5WfyCN7XwZcm+N8d5o5xTKJ/X7YyUx421VAd+8PmPMUPsFHZzDmBbUBX9L5zrVCMNkyjmu58fVWb+VYz16uDci0MqVQCvXOv8rUcqY/GhLnbDZX+BqasuS8GHMj97LKN82lCmrOZ5lqI60cAwitjyTao0SB6kVS2qlkh+E9eXHhEu0cwnFQiylu2sEq+LPYSkxZV5wrz+UeOn0OlKrCjETSfCsDfzNqSk19JFZuf5Fh7c/RamyitEP1httyT3M7NnVYsZf7OP5Z0OmlnM17xWZ1UWM9++ApVhKTFkGu1NvsbTWol+mkbP77S0u5MQw1q8t4/zacznvBT/En6eNUwif1R/4u0rgn0OhooLhd9ca7/c/xUDPZixqMPCf+Rbf4W+ARqclsTKXmU93oNCqMROZIK+tiDe192dJ+DAc/07Dp3d4h/8tvKswvcN/NEora1h36i6jVhzgdWYBMrmSMw9eM+jrvdx99RaRTsT0el0JsXJHq9fxyYuDRrK0IKR3nVndif4dGOHTim3Np+Jt7sBAz2bMqc2FmV2vB/6WLnhbOGJrYkEf52bsO/GS2etPkSsrR6Y2zHxOe7KNHxMuMS2wCyZCsSFs88kubMRmlMnkXLmSxoXLyQjKTDCTmVOVJOLzzdfo5RpJW6cQ4/sSIGBFo5FIRRIu5kajQ88X9YZQ8lqHc4kLI9xbY643IyddwcHLMagVOi7kxlCilHG/KAEXUxuUWjW3C94YScgIn1YM824BwJaUa1Rp5HR3iyChMoevwofwQcx+Zj7ZwaL6A+jr2YRCZSVJsjzqW3uxNHQk+9/e4auGQ3E1tWVzxDQCLV0Z5duG6NI05j7fw9KIYbwpzyahMpfxfu0Z7NUcfysXXpSl81mDgTSzD6CBjRcbE68gForwtjAM7FYnXCCzppiy2t6BwV7N2Ro1FVORhDx5OT+l32ds7Wz7L4iyD+RK3kuOvH3IxohpfBw8AHOxlEu5L/C3cuFU1hOelqZyOsvgvrbi9Skyqov4ueANfT2aYmNiwZLwYbRzDmWAVxRbk69zvyiR0ffXsyTuODk1pYz1a8dP6fcNNuRFCUwJ7MTprGd4WjgwyCuKXu6NGeQVxfPSNMxFJpQoZZxou4AG1p64mNrwqjydts6hKLRq9qbeRocOX0snilUyLue+pI1TMAhgfeIlKlU1/Nh0IpMDO/HFq6OYCMWIBAKqtUrEAhGrIsewudkUwqwNFtbZNaUodRrczewZ49eOJXHHeVCcyFcNhwDwtDTVSJY6uTSgs0sDGtv7sTbxIsVKGV+9Okobp2C+fHmEzOpiVr4+TQeX+liKpHwdPhTAOHhsZh/A9MAubEi6jE6vo6m9P34WzgzwbAqAuUjKodZzmRbYiU6u9RHXDs7Tqgv55vUZPo45SIXakKslFAjo79mMVQnnWJNwAR16zmU/p0ItZ+rjrbyVFTLSpzX5ygoq1XIyq4sRCgR4mNvhbmbH5w0GMcS7Ba2dgrEUmxJg5UrabypPnV0aMC2oCxq9llJlFS9K01kQ2oePQvuxudkUZgV1A+B2YTxyjYpqza8DZI1Oy/2iRK7nx+FsasMXDQYxJaATAC/K0rESm+Jh9nsJkIlQjMuf6Z3JV5RzryieVY3H8FZWQANbT0QCIf08mjDerz1rIsfXWsK7UK1R0Mm1Ac9KUkmrLmTv29vINWq+jz/H3aIELuW+IK26kGJFJXHlWWRXl1CsqESv1yMUCHGRWuNo8itB8DC3J/g37pt/C6o1Ch7U9lj9glx5GTFl6cg1qr/wyn8claoa8uRlaHQacmpKeV76lj4eTfi54A1PSlJ5//keosvS2JZ8HYlQhJXEDMva8N/9aXeZ/mQ7P8SfBwwhsfwdBR4biXmdHq0/Ra/aYNp3+NdCrlXxsDjJmPd2uM08loYPByC+IucP89Le4R3+0/GuwvQO/xYUlMmYtuYYWUUVSCUi2jb053q0IfSyR7NgPhzaAXsrc0qVVfS6tRJdbf9RW6cQFocP/Z116i+9Ob/921RkYsgu+s0+J35/hPwyw6Ai1NuZ+eNbUiNS8vmrwyi0aiZ7dybA3JUvEn9CgID9UbORqE0Y++1PyGqUtG3gh7OtJSfuxdIizJtRQxqw8NUBNL/JhuroUp9J/h2o0ijJqS6FXDMW7zVUoeYNaYOVqZRlBwy9UXOHtCbTMRMbqTluZnaESb2JlWXQzNmftQkXqW/rRW+PxlSpFVzOf0G+vJz5Ib0xEUgQCqFKriKxPI8vEw8TZu3BzHrdmFdb8Zjo0JX1Rx+wclpPtuZcYZB9S1btvcf7o1qzs+gKEwI6UCqvpoV9INmKUha82MfihkPws3TmRn4cO1Jv0t0tgjbOIayMPcVnDQfxpDiF8QHt+STmIEmyfJxNbdjefBo/pd8nyiGQEqUMJ1NrzudEM9S7Be/VBkoKERisyIVi1jWeSHmemkXbL/Pt1N4IHVV4WzpyryQeS7EZK2rNDH5BlEMAH4f1p0QpQ6nTcK8wgSBrN3JqSlFo1UaCAfBlw8Fcy4tFj54ebo0Q6KG9Syixpdlcy3vFyIBWCBCyPvEi94uT6O/ZlDZOIfyYcIlFYQOxkpgy9elWHEysWOg/AA87OzYkXSKhMpcfIseSKisgpSqfE5mPWdd0AqeznjLKrw0fRR8gR16KjcScZeHDEApFVKpruJzzgrkhvciTl1GorOB1eTYRdj48KkomoTKXeSE9AUPfxN60O8SUpQGGwfyBVnM4nxONi6k1UQ6BzI/eW6dKaCIUsyxiOMczHjEnuAcvyzNZ9RtzBV8LJ1Y1HsvMpzvwNLdnelBXXpZlUKio4GVZBrPqdWNZ3Ek+bzAIN1NbJCIxyZV5fP7qiFGmZiMx4/tGY7E1sWB+9F7yFeWM8m1DfHkOz8pS8bNwZmH9ftzKf42lxJRdqbeoZ+XG4vChxjBgjU6Hi6kNCZU5OEitMBWZUKyQsfDFAQCGe7ck0MqVla9P80FoHxykVob9Pd9LT/dGdHJpwNOSFCzFZnha2BNs7cGyuBN80WBwrZNcJbHlmbypyKaza0OKlTL8LJ15UpxEgJUbWdXFtHMOxfoPMmkeFycz59nuP3xGfd94DDVaJVfzXiFEwBi/tsRX5hBu68OOlBuM9muLXKvCRmJGmaoaG4k5JzIfc/U3sQIAn9YfiJ2JBYtfHeOLhoM5nf2UId4tDKYOUmt2pt6kmUMALRyCjOGzfwlyjQqJUGTsbVJoVLyuyGLm050ANLUPQKlTEVuehQABa5uMJ8oh4H9FllepquF41mN2pd5iQ7NJ+Fo48ag4mcWvjvF+SG+SZLmcz4km0NKVNU3G42JmcPcrV1WzPfkGx2qrdmCYIPgorO/fbeWdW1PKlMdb6xhvGLZXn4Vh/f9l5g2Figr0eozvsVRZZex/+/8RFaoazuc8p4NLfTzM7anWKHlYlIiXhSNBVq5/d7/aO7zD/xbeVZje4T8aLnZWbJo7GC8nG5Rq7a9kqWkwHwxpj72VuVFmo/uNo86D4iRiy7Pq5M0AoBGSU1xBdlE5FdUG8iT5kwFCen6pkSwBJGQVUlqs4n5RIkvDhzPGsz1km3H6YiJf1hvGzqgZ5OXU8PH2C2yeOxgrcyl349I4cS8Wb2dbpo9oZiRLfhbODPSKAuBWwWtOZT/FXCxFIhJh4qKlQ4Sh+Xvd8XtGstQ02BOPAAvuFMXT070Rz4vTeJtTSnpMDav23qWveUtMc6xRV0Jlvpb+LlH09ohErxSS8LYIrULAjcepnL+UzI5GMwm19MQKcwItXfkqZCiLt18jNbeE+RvO0de8BYu33CAtv5QVu2/xcdBAvnh5lNbOwbzNKOfWrUx2R80iUOqORG1Cf89mmAjFXMl7yRcvjxBh74OnmT1DfVqw4Pk+vm08hol+7VkdOY50WSFDvVvgZ+LK9dw43pRnM7teDz6OOYhGr2WYd0t+avG+scdHqBWx93I0ao2WD7ecI+5ZGXO/P4ddmQO2lba0dAwyXiORQMji8GG11UUBl3JfcCTzIesTLxmIR3FynWt8LS+Wnu6NeFqSSqVKjr3cnoyicizU5jTWBaOVCcnPr6ZSZZjhdDCxYl3iRbLkJcyP2YNEIGZzk6l8GjSI/adeUlJVxaOSZPIV5XwQvZ+npSnsS7tDtVbJpdwXRNr78eXLo3wY2hdPc3u+Dh/Krre3sZOYczM/ju7ujfjm9WkWxhzgel4s4XY+RJekcTnvBaP8WmMqMiFJlserikwjWQJDI/83b04TauPO5ZwXiAUivgwZWue9jvVrh5+JK5N9u/Cy7FeyFGjpilggIr26iA+j97MucgLmYhOsRKbUaJScyHrMrHrd2J5yg1JVFZ+8OERsRRbfvT6DhURa53MTbuMLlRKKimqYF9yT5RHD6WQVwSirjrRzCKWPRySPipJ4UJxIhK0P9iaWJMnyWBhzkB8TL/PB8/0cSr+HWqslpaKA95/vRa1TI9cqESBgZehoRvm05V5RAjr0fB9/jvtFicx/vhe51vDZdDWzpVgpo6GtNw1svJj/fC/RpWm893QnmdXFht7D12fo6hbOR9H7+TB6PymyPNo4h7Im4QJL4k5wKvupkcD9FiHWHswI7IL4N1+FYoGIOfV6IBQIiC5N435RIneLElgWd5K1CRdZGHOASQEd2ff2ZxbFHOKrV8doZOtDY3s/Pgrrh+lvejQa2noRae/HRzEHmFbbm/eoOJnPXx6mQF7BtpQbHMt8xMcxh8iWl5JUmcee1J85mfmYrOri31WHajRK7hcnklCZi6Y2Zyu5Kp8yVQ1DvZvT0rEeS8KH8U2j0UTY+uBt4YifpfP/Wg+TSq/lQk40Kp2G2U93sSPlJl+9OoYOPVfzXtLeOQyRQMiGZpOMRAIMn2vXP7E2dza1/ruqar/A3dyenS1mMLted0Ks3Ym092NV47F89C8mS5/EHGLB870UyCsoVVaxLvEikx5uJqOq6F9yDP9psDExZ5BXc6PBg4VYSmunkHdk6R3+a/GuwvQOfxYFZTJevc3j1ssUXO2s6N08FFc7KyzMpH/9xX8DZHIl2y884sCNaOOyre8PoXGgO3Kdii3J1zhW66o00b8DD4qSSJTlIhII2dfyPYKs3dDr9WQUlLHq2G0exqej10OjAHc+HtGRADcHxKJfBwoHb0Tzw/HbAAgE8Mm4DryUJPGoPInVkePQVoqY/M0xAFo19KFfi/p8tvMSWp2enlEhtAzz4cs9BhcuGwtT9n85nK1p10iqzOP9kF7Ym1jysDiJQ+n3WR0xHhuBOSnqPM5lPufDgP7MXHeCrKIKABxtLFizoDfTYgyuY0FWbswM6srV7Fc00YWwdNdNzKQSti8Ywme7LpNVVM7K6T3wdLVh49FH3ItL45MRHUnLL6WepxOpuSX0bhHKJ9svMH90G9zsrKmu1DD7x1Mo1L+aD1iYmrBx3kD2ldygs0tDsuPk3HuVzryBbbGzNONtXgl+/rZ8HHuQjFrbaFuJBV8FDkdXI8DGUcLKhJN8EzyO1NwS/N0cMDEXUFAp45vdt5k7qA06OwU6gR5bsSU38+MY4BbFe6tP88XUjsSp0mlhGYy6Gn44fgexSEBsmsFJblS3RtRrasWy1yfr3CfN7YNYWL8vhYoK3nu6C6FAyO6WM/nq5VHe1vYJtXMO5WaBoX+ltVMwgzyiUJcJ+WzzFazMTNkwdyAVVXI+3XWJarmKFbO6Uy2tJv1NFU0bePBtxkma29VjiFtLDlyKpndUKE8Ss6lRKmnX1psPY/fVyUzq5daY/g7Ncbayolhexd2yONq5hrEk7gTtHEMJVfkRHuTGttTrRmmlqUjC1qipFCtlKLRqzEVSEipyaOzgx4wn2wHo4tKAejbubEoyVCSHebfExdSG+raebEq6yhDXlqx5e95or708dBQ2eguSNTl8n3SWlnb1mOnbg3KBjAUx+/Axd2RF+EgEahEylYKdOdd4UJLEB/X60NExnM/fHORFeQZtnUL5KLA/Xycc4XlZGqYiCd5mjkxz7sGiTVcQCQSsntsXB3MLZq07SXFFNWve64+7uzkzo3dQpqrG09yezxsMZu6z3UaTk0BLV35oPI7VB+8wqH04/h62SIUmmJiIyCuvYP/FGMRCIVMGNuP7hLPcrQ0dBoOj1rKIEXz+4jDTgjoTbuvDrYI4fCyca/vYfr0epkITdrecyYrXp4gtz0SAAEepFUXKSoQIWBU5lqYOAZgIxBRVVGFqIsbGwlCRzi4uR4ma6OoUg0TO1IYHxUl0dW3IrKc70ep1DPFqTjuXMBa9OESYtSfj/NtjY2LGzCc7iLD1ZXZwd0xFEn6IP8f9oqQ69+9E/w7o0HMxJ4YvGg5iRdxp8hXlddYZ79ceXwsnvo47blwmQMAXDQfTyaU+5mIpap2WB0WJLIw5iIlQzOaoKWj1OmY/3YlKp2VV5BjCrL1wMDWQhCJFJVq97nfE5J+NPHkZs5/uMtqyAzSw8WK8f3u+eHUEhVZNP48mzKrXHXupJTK1nIu5MUYZno3EjIraAPFxfu0Y4t0CC7H07w5g1ep1VKkViARCo0vfvwqxZZlMe7INrV5HgKULXhaO/FwbEv5RaF96e0T+znTkHd7hHf4z8K7C9A7/EHKLK5j8w1E+3nGBy08T2XP1GUOX7ufys0RqFP+4Jr6yRsHp+3EcuBGNvaUZP77Xnwa+rszZcIrX6QXoVYbBoqPUivkhvRnr15ZVTcYSbOVOb/fGRtlGbkklE1cd4cEbA1kCeJGay8TvjpBTXGncX41ChZ+rYaZLIID5g9rh62PDk/Jkvg4fxvK4U1yveMHsIS0BeBCbwSfbL6LV6Qn2dGJEh0Z8d/iWcXsV1Qp+OHiXmQHd+D5yDM7YUZytpINjfXY2m0leRjUxSXl44cQoh47cepFqJEsAxRXVPIvLZUOjyYgEQpJleTwvfYuvjSMeLjaYSSWE+TgjMREiFIJGq2PR1st8tvkq9+IMlQiVRsu4Lk158DqDQzdj+GjreZaM78G+8zGUq2rwcbZj7sA2dc77wmEd+enGC8a5dCTvjQIvBzum9mqBs60luy4/wc/TnnN5z8ioLkIsEPFj5ETWhk3i+113+WDDeSoLNaxrOJkVB2/w4dbzXH+eTHGJnGU7bpKcU8xHW8/jJXXi05eHyasqp77On2/3/8z8Qe2QFWtopA/i6NU4rkcn8eWYLkzsHsX03i2o5+lEl7Z+RrLU1N7f2IfyuDSZg+n3kIokfBU+hNE+bRBqRITb+SAWiFjdZBzd3cL5KLQvYAiAVek1OJhbIhGJKK6sZsbaE3y8/QIllTWIxSJcLWwoSVOz8/wzPtt4jVUNx9HWtAE11WpsrU158CYDJxsL2jbwx05gSXP7oDrncWpgZ5JTy8gvqGLtgQf0sW9OfHEumdXFBFi4EOznyBevjhjJkhABCq2aD6MP4CS1xtfcidjyTNq7hqHRahnt04Yurg0Z7tOanJpSFob1J9Tag87WEbSxCeNQ+n0mu3Xl7NkUfgybQn0bTwBOFzzGxsqUIKEHq8LHMs65E1Xlao6diWdl6GgWhw5HqpPywcZzTF5xnHGuHfmm4Shcqp2Z/P1RPvYbTEuHeoywb8fEb48w0r4DTez8+aHxWBaE9kZiIsRCakKVQsX7684yedUxCsqqkErE2JibsiH5MuUqQ+Wmoa03efKyOq5z+YpyShVVmJmYcPBqNBnZlTx+nYlAKyA3r4qzD99w8n4c5+8kMsyzbnBpZ5cGmIlMqNEqWRp3kqH31rAp+Ronsh4b+7V+wfSgLnia27Oy0UhCrT3Qo6dIafj8fxc5xkiWkrKLGLJkH0dvv6SyRkF2UTnT15xgy6lH2Ogt2Zl6kwXR+zie+YgDaXdZGj6Msb7tGOgVxfrEy6yJHMdo3zYseL6XpbEnWR4xgln1uvFzwRuOZTwykqUpAZ3o6toQgN1vfybU2hBEuyz2JN82Hl3n2Ns6hdDeJbQOWQLQo2dp7AkKFYbnRomiEhuJOa5mNih1aqY93saMJ9tre+Ls8Ld0MZIlACdT6/91sgRgZ2LJkNoey18wyDuKh0VJDPBoBsDZnOccSLtDlVqOqlZWCwb58paoqcbXPypOIbO6mGt5r6iqJVF/K0QCITYm5v9ysgQQbO3G2ibjEQmEpFYVGMnS7Hrd6e7W6B1Zeod3+D+Ad4TpHX4HhVLNpnMPyC2p/N3/Vvx0g+LK6n94H0qVhh2XHmNvacaOD4YBAuYPbkeItzOmJmJiUnKpKtawr+Vs+nhEYikxw8XUhtVNxhlnKnU6PVefJVJR/fsGUoVaw/7rz1GqNBSVV7Hp3AN8XOxwd7Rm4bCOFFVUY6Y25avQYai0GtKriziV95jOTQLp2OjX7BSBANbM7MfcjaepUqjo2SyEid0Ng4Dbr95y6V4SYqWEJbuvM3fjaeKTSpBoxVx9nszifVeJTsyltKzGWNmKCvGidUNfANYdu0d2WjU/NpxEN9dwOrk0JFTsw5ebr1GtUPE0MZsrT5NYMqU7fq72aLQ63uYZZnHnDGhDZmE5AxbvQa3VYmoipluTYO7GvWXJ5O7sy7tFgayS3Vfq5pNsu/iIfi3D2Hn2Gd6ODny59woLt5+nqKKaHlGhTP3+GAEKb7q6hLM2cgKnzici0oqQSgxW2As2nWP62hM8TarNaZJKOHE7lrT8MsQiIetmDeBOyWtm+XWnXFVNqJsLrRv4EertzK2XqcxYd4KWYT6M6NiYi4/jWbDlLFUKFe3D/Yl7U8xwr5Y0sw9gjG9bytU1zA3uibeFI0M9WmKttyDQxANhugXDPztEZ7NGHG4xD1+pEyE2HrR1CuFMm4V0cW1IpL0ffq72bF8wFHOphPIqOeXVCsylEr6f3QszqZiDV18A0K9lfc7eSmD26jO8t+40HRsG4WxrycrDN4nNyeWu7A23i97UOY+znu2gSYQrX++/xsvUXNafukczy3q859OD4zmPKVCV86o8AwECljYcxtom4zEXmVCkrORxcSqmOin5NeWcyXgGZRL6ODXjvYAepCZV4GPiTFu7UGa49GLuD+f4Zv/PzPHszYodt3kUn8mXO66yMnQMK0PG0FvcEp1SwKfbLhNg4kZ2XiVmUglKhYZtB58xdcVJRiw5QFq+wQmuuKKGMEtvvtx9lZziCuasO00XYVM+WH+BgrIqfth/j8Uhw7HDmqJ0FVIrIevn9cfW0owapZryKjlSiYjN8wbj7WrNLJ9e7G40m24u4TSw8UZRo2FN/Yk0svXFzsSCKo2CuTG7GN6vARN7NGP2hlMs2nWJp4nZNPRzZWbfltT3caFemC0LXx2oc44PZdznWUkqm6KmGJeZiiRM9O/A4fT7fB08go8DBiJAwLHMh5TIqtFofx+KqdXpQK9HJldw7tFrqhUqNp97yI+n7jF97XHySiu5H5eOt8QZdzM7LERSerlGEmnvR2M7X8b5t8NBakWApQsquR43HHAzsyNZlkdKaSF6uYAXJelEOQZS39qTOfV6UKGuobljEN3dIujn0ZQCRQUvytIZ59+eo78J0gaD0UeZqpoGNl6/e47p0XMjP44yVTXvR+9l0cuf+KrhEGwlFmj0WrR6HQ4mlqxvOvHfkm2j0Bia+9cmXKyz/JvXZ+jmHsHkwE5MD+yCvYkl/T2bYSkxw0FqxVcNhzArqDs93Box5sEGvM0deK9ed2YGdeXjFwfZmXoLpU77Z/b6nwcTkYRga3eCfuPEaCYyobdH5F8NL36Hd3iH/w68I0zv8DuUVsm5+izpD/+n18PD+Ix/eB+ONhbsXDCUbQuG8tnuSyzYfJa80kqWTujBzstPmL/lLI/iM6mp1NSRZjiZWht16TVKFfdep//ZfTxNzKS8Ws7nuy9x6GYMn+66yJ4PR/A6o4D915+zcMtFHLHFUm7JioiRbGsyjaxsGXdeva3zfr89couVk3vRp3koEQFu6PU6pvduQeNAD/o0D0MiFGEiFqPXw+e7LzF7/Wni0vMwlYgplclxd7QhyMORFmE+fD6qC5O6N6NDRAA+LnYEujtSnKekr3ULTl58w9Ktt5jUqxn9WtYHYM/lZ0iR4Ghdt2Hd382e3OIKhrULp324P5vnDcbCVEJydjFJaUV8FTScBRsMRMjC1ISZfVtiKhGTU1zBN4dv8fHwjthbmeFkY4FIKKS8Ss7eq08pq1Kw7sh9Zvp3Q1Ms4NrTZF6l5rJqRl8C3B3Q6HRkFBgG35+P7oKtpamRxG2YPRB3BytaW9Qn+XEVLayDUWt0tK7vy5oTdxjUpgHmUhO+2HOZr/dfY3+tFFNWo8DHxQ5LkSm97JvyedggRJUS8mrKyK4uYW3j8Sgq9aw6dIeKUiW7zz3H1c4KnVLA89g8hBoxUrUUoUrCrSdv0Sj1aBUCUjJLkIhFiEW/PuYkYhEOppa8zS1DKhFjKhHzLDGTnlGhtGvoT5VcycRVR/ju6M94ONrQqpE3W1OuAwYZ3obGk40ugNve3mBMz8Z4ONowqlMkOp0eE5GI1xVZvCjN4JuIUXweOohgqSd2JpasbTKBqf6dUadJmPb9CUY5daC9NIK5688wbtkRMjIr8HWwp6VdMGqllqzsilrinMXAr/aSU1yBqUTMrL6tyMwv58CJlyzceoFnCdlsXzCMHZee8PX+axy9/ZIZfVthJjWhSq6kqrYivGpWH0zsdTyrTGbjnIGYSSXkl8n4asc1quRKHKzN+XpqF1Ymn0AsEhLm50xseQZ6QCT81bpMIBAgEAhQynVcfpjE/gsxzPDuQRPLAJ4/KOKH3ff5InAoGyInY29iibXEnMoKJZ9sv4hGq8PP1Y4gT0dsLc0Z1j6COcNbsSvnBnKtChdTG060XUCL2j62bSnXMReZYCYymCEsixjBluRrDHJpyfmLyUTfL2JR0CCGurakWF7FoheHSKjMRYgAF1NDz8wnLw7xuCQFE6mIyT2bM6CV4bN18l4seaUyTE3EbJwzCB9He75pNIr9kfNooW5AH5emOJhaY2Nijr3Uklk+PThzJZFpP5xgWeBo5vn3oiJFz4TlRxls0wZrkRnvBXcnV17GscxHrIg7RV+PJgzxbs6ahAtMDexMWlUhF3JjAOjqGo6rqS0KrZrPXh5mVr1uxhwpIQK6uIQjQECBogIrsZQVDUdSz9KVCpWcmt/YaFdpFJSra9D8GwiGXKdmRdwp9OgJt/XmVLsP8TJ3QKXTsOL1KXToGeLdgv2tZuNj6WR8naOpNSN9WxFq44GvhROrEy6QKy/j81eHMRdJ2Rw1BYd/oR36P4pSZRVrEi6QUJlrXCbXqpjzdDcF8vJ/34G9wzu8wz8N/zWEafny5bRq1Qpzc3NsbW3/3Yfzfxp6vd4YrPlHqKr548yLvwdVChUB7o6YmojRaLVodDoW773Kwm3njQYQAoEAU5M/H3InEYtwsPqVSIhFQpZP6sknIzohEICdpeF/H4/ohJmJhNi0fPp8vpPzjwzVgj4twrCUSPGzd8BBbou2QsT8zWfQ6vTU83RiQjeD/fLtV2+59jyJYe0bEZ9ZyKC2EfRvVZ9vp/TC3socoVDAl2O6Mql7M/R6sLGQsnZm/9rKmZ6v913h+2l9WDSiEzdfpJCWW0KPpsGsntGPcw/f4GNvi5eNHdU1amb0bYmzjSUz+7TkvX4t2fb+ENaeuGOs6FiZG6QdH209z4TuzbC3MmfpgeusOvozPZqF0LVpPT7ecYE9V57w/qB2WJqasHxiTyxNTVj33gDMpRLmDWrLoZsxaHU6VkzqxTdTerH/+nNGdGxMVLAXa2f056MNFxHqRXw/rQ/ujjYkZhZhbVZX6hLo7kB6fhmTezZn6YQeZBaU8eB1Bm/zSmka5Mmj+AzGrDxEVmE5JbIatpx/yKppfdDrISbFkK/TvWk9RnRoTEM/Nx68SWf0ksPcfpqOq5Ud07270dstEkWljjsvUpnRpxULt1+gQ4Q/yyb24Ov913ickMnzlGz6fL6TuPR8coorScwuov9Xu8kqKufE3VdU1igxk0owNRFTUa1g1rqT2FiYsnhcN7YvGMLKKb058nMMY7pEEhnkYZR22liYYokZi+sPo7dbJI1U9XDS2/Jd/bFE2vrT06Ipa4/cY/X0vlhbSHnwJg1fkRuT/DvSxDQId5wIELtToa/GQWKFA9Z0sGnInvPPKSirYtrqY7z34ylUGi2O1oYQ1k93XSI3X8bifdfILqpgQrdmdc75V+O6cfhWDCWyGiQSQ3/et0duMW/TGc48MMiA7KzMMDMRU1pZ1+QgNa8Yf1NXImx8uP0yhbkD6so1l07ozsnSB4x368STuGzWHbtHa7MGzN9wlpLKGkxNxFibS1GoNMz68STZJZXceZXKlWeJ3I9N51lsDpcfJZGaW8Ldl2ncuPeWHxtP5BPfQXyx+TolshocbSzYOGcQbvbWyGoUXHgcz0cbLjLFpRstHerxqd8QTl2N55OQ/nR3i+CHyHF8/vIIcq2Ktk4h3C2IZ7xfBxSF8DAuk0uPE3l+t5D812pqVCrK1NUIEfB95Bh2t5xFQ1sv9OjJrilBo9Nib2XOtN515WPNQ7xJzy8lOiUHvVLIx9su8OmuS1x6koCs5tfqtVKp5W5cGiWVNcxZd5qExzJ2n3+OUq3lxpMULPRmfBRzgBNZjwFDwPKm5KsoZDo+CO3D46JkWjnVw0IkZZh3S2YEdWFT1GRcTW1pYudPsVJGgaICIQI+CRxIA1kQnwQOpI1TCDVyDUlJZbzv148Vr0+i0mlwMbXB2dQGpU7DzCc7SKw1gvhXwlZizpaoKbR2CmZlo5F4mNuzodkkmjkEsLbJBOxMLLAxMcfpDzJ3pCIJzqbWzA/pDcCprCdUa5RM8G9vjI34b0FqVYEx2Pi9oG6sazIBkUBISlU+p7Of/q9bu7/DO7zD/z7+awiTSqVi6NChzJw58999KP8VKKqoorzqVw14cUU1xRV/m5TO3FRCqLfLn/1/i1Cff+jY8ktlxKbl8TavFHcHG1ZN72esXiRmG4wGfqngWJr+eZtdqUTM6M6GnA2xSMjX47vzOD6DEC8nvhrbjY+Hd+TsgzhKKms4uGgkFlIJU3o1x83emg+Htmd4h0aYm0rQaHXcjE7F1tKMvi3CCPJwZHb/1uiB2f1b42htQY9mIVhbSGkc4MGsdSdQqDTEZxaRklvC0K/3IRCCj4sdn47sxIIh7Zm+9jjfH71F+/AAVk7pzYdbz/Hejydo28CP5qE+RAZ5UlxRRZiPCyqdjtLKGt7r15pqhRI3e2tScotpHx6AjYUprzMLAPhgSHuOfDYGfzfDuXqbW4qXsx0CAbzOKGDamuN8ve8qWp2e6JRcGvi5smfhCLacf0hWUQUSkZBTX0/g8RtDz9Nnuy8jFgnZeOYBL1Jz+XLPZT4Z0YmyKjlzBrZBKBSQVVhGjVLN8TsviUk1kBwbC1MGtw3nUXwmOy8/4bPdl/ByskUHfHPkJot2XsTW0pzLzxJRqDWcehDHoDYNmd2/Dck5xXWuYcswX2JScvhkx0UjUS6urEap1qBXCHETO/AsMZsezUK4FZNMVIgX7SICcLGzIsjDkWHtI9h+4REKtYZPd17EXCph/uYzyJVqtl14RM+oUCzNpGyZN5jtC4ZiaWpCeZWcwvIqDtx4jrmpCfuuPeNmTArvbzrNR0M7YGdlqGhmFpSh1wrwwYnWogY8fZVDfmkVOw5HM9SyLZ9uuoJCpWHrhUcIBQKyiir5bMtVOllFoJXDd4d+xtnSmit3Uui3aA9JGSVUVarZPG8wErGIyholao0WN3sr1s7sz724NArLq5i36Qx6PXSJDOJadN1K7/E7rxjcLoLlB68ztF0Erev7AhirfGM7R9K3ZRgfb79AiLcz/m72BLobcrPWH3/Ao9gsnr3KJSLAg41n60rDluy/zkSXrtx+nI5SqSXIw4nKagUVVQYp49b3h7BmZn8crS2oUajILirH2c6KrpH1kIhEfHvU0OM3vltTqhQqXqTmUZav4ovN1ymVGchbZbWCgvIqNBotr97mserYbWQ1Sq7dTWWiSxe+3nKTPVefceV+KvPq9cJEKCJJlsdw75aM821PN/cIbhe+pkmwJzP7GvoNLzxO4OC1FyzecoPloaNYHTmeZg6BaKv1LG0wgqXhw+jr2QS1Qk96fimTfzhW533ffvWWtPxS4tLyGPftT8RnFiISCvB0tMVE/KtpjFAA303tjaWZlJLKGi48MPThdGoSQLPWLnyVcISl4cOx+E2/SoCZK7eevqW7UyOWNhqOm5kd+1vPZoxfW7wsHPE0d2Br86m8H9qLpbEn0Op1fBjQnwe381j10x0e382nvrk3Zx6+5tNdl1i86yrr60/Fz9yJT+sP5OuGQ/koqD/2JhaYCMUIBX9HiNE/AQKBAH9LF75qOASn2oqem5kdyyNG4PlXJII6vY5kWT4fxxyss3x1wgWiS9NR/akT6n8wQq09WBjWj9n1ujPQqzlN7P1Y22QCfTwiGerdErO/wS7+Hd7hHf6z8V9DmL7++mvmz59Pw4YN/92H8h+P/FIZ7/14kt1XnlJeJae4opqVh2+wZP/Vv4k02Vma8/GIjnVkOL+gVZgPbg51ZwvLquTEZxZQozTMolXJlcRnFlBR9fum3ayicqavPcbPL1N5mphJfqmM3JIKXGzryi88HG3YdfkJOcUVv9vGb+Hras/03i1o08APkUBA1yb1WHXsNr4udjxKyCTM15WNZ+5TXq3gx9kDKSiVsWSCoSfo+J2XnLofR1FFNQNbN+Cz3RcZ1SmS1TP6sfTANZ4nZdO9aTD7PxnJ9ouP0Gp13HqRzKrpfZm36TQ/3YqmuKKK/YtG8fX+a3y17yplMjlKlQaZXMnLt3ksO3CdD7acJSW3hMLyaiqqFWw8c583mQXodHqcbS2Zue4EH247T0W1gshAT2auO8nCHRfILZFhYWrCulkD+GxUZyKDPJi25hjfTe3NrH6taBHmzcP4dJZPNGT55JVWotXpCXJ35LspvXmWmEVafjEN/dwY1TkSJzsLisqr6NMyDEtTE7o3DeaTnRdJyCpEKBDw/fQ+nH4Qx8Lt59Hr9ey/9pz6vq54O9uRWjsgXzy2Kz99OprsonIa+rniZm+FXKlm0qojfHP4Jno9hPu7oVJrSMoqIirEm17NQnB3sCIpu5jVJ+4AGAeiX++/irWFKb2jDOG/M/u2pEN4AE8SMqmqUXLgxnN0ekjMLmJg24a0ru9HXFo+bzLz+WREJw7ejObDoR3wdrZFpdGy8/ITFCqNgYTM6k9VjYKNswdy/XkSGfllbJ0/hLWz+uNsa8nDNxmM/+4IbRr4sXJyL9bPHoROr6d1mC8O1uZM69MCrU6HrbkFIS5uTOvbkg+2nMXW0owARyfmDmgNwM0XKey/9pyh7cNZO7MfS/ZeZ96mM8zs25LMojJMBBIUKg2HbsRQJquhqKIave7XPhu1Rodaq6VDhD/tGvoT5O7I4nHd+Gz3ZaMMb1Abw3PveXI2R2+/4Kux3cgrqTRWHH+Bi70VYqGQbk2DaeDrxrKJPdkwZxDtGvoDoFBpaNPQny/2XDbK8L4a2xVTEzH5ZTIWbDlL+/AA1py4g6WZlMLyKpZN7MHyST0pLKvC09GapRN78PX47tyJfUt6finjuzVl+U/X0evB3sqcER0aEZ2czdgukVyPTsbLyRYvJxvcHaxRabRMX3OcN5kFBHs50zUyiK6RQcwd1AY/B0cGt21IqJczvaJCcDSzwsvUiQMt5xBJMBv2PuFtnIyRPq0xlYoZ3CYcX5dfM240Wh3OJjaEmntSUlbD7I2n+XTTZZpYBSGv0vLybS6bzz0kr7QSUxMxuz8aTv9a6evBm9E0D/VBUuuquWZmf0K9nFFrf620m0ol+Lna06a2B/EXzOjdkgO5d3hbVYAePZ7mBoIqEYjoYh9BeaUcM7EJbmZ2BFq54mnuUMeMwc3MDhdTWzZGTaaelRsFygo8XAzk4+qTZMZ/e5g1tZ8bdwcbKsqVrGowno2JV6iuVpPwqJL1DaYQYOXyb7FrFggE2JpY1Fn2p3//ESrVcha9OES1VomT1Jr9rWYTaOmKVq9j0YtD1Gj/e6oylhJTurtFMMCrGdYmZpiIJDS282FOcM9/mbX5O7zDO/zv4r/OVnzPnj28//77lJeX/9V1lUolSuWv8rHKykq8vLz+T9uKK1Rqjt95ZRyYDm8fQX6ZjNu1fTk/vjeAVmG+CP+ADP0WSrWGtLxS1p++S3RKDjYWZozuHEnPZiE42vz6ZVhWJWfnxcf89HMMKyf1omWYDzdfpPD1/mtM6RnFqE6R2FoaZuzlSjWHbsaw8awhaLRvyzBGdmjE3mvPufIsEQBzqYQapRqxUMg3U3oR4uWMu6Nh8FBcUY2JRIS1uUEaVl5Vg1qjw0wqpqiiBguphNeZBWw4fR+1RsuXY7uy8qeb5JZUsGR8dx6+yeD0g9c42Vqwdd4Qzjx4zd5rzzA1EbPt/SFYmUs5eTeWnJJKZvVrhVBgsLw+eDOa76b25m7sWyKDPBEJBJx9+IYwHxcQwKP4DM4/igdg8dhuNAn24El8FssOXTfKu0zEItbO6k9eSSVLD17HVCJmTOfGtKzvx5wNp6hRqrG3Mken01FercDSTMqmOQMpqqhGLBQS6O7AnE1neJtXgpO1BSsm92TRrkuEejnTtUk9vtx7xXhNQrycmN67JRKxCHcHa7KKyjn74DXT+7RELBJgaSqlskaBHgFlVTV8vf8aCwa3o0quwspcyqEb0QzrEMH5R29IzC6ibQM/OkQEklNSgZO1Bf7uDpTJ5KTmlRDh78b47w5TozTMBvu52vPBkPZ8uPUcCrWGnR8MY8mBawR7OtGpUSCf7b5E1yb1eK9faz7bfYlXb/No5O/O52O6MGTJPtbM7MejN5lITYQMbB2OrEbB8buvOPvwDaM6NaZ1fV/iMwvZdfkJ62YNYPWJ2zhYW9C5cSBf779mPAdfjOmCQADBnk6cfxRPRIAHTxMyGdulCTsuPSa3tJJRHRsjEYvYdPYBk3pEcfV5Eo/iM9gweyC2lmZcfBKPVqfDVCJh77VnbHl/MFmF5ag0WpYdvM6qaX1QqLQsO3Sdbyb3wt3RGolIxMx1J8gurqBLZBDDOzRCIhKy6/JTPhrW3jCZsb5WhmdjQbVChVypxtnWkq/GdqVKrsLZ1oLE7CLe5pVy9sFrNs4dhE6nIzG7mNXHb7NsYg+CPBzZe+25UV5qa2FKea35yaKRnfBwsGH2hlPYWZmx7f0hSE3EJGQW8jghC6VKTYswH9aevMvisd2IzyqgWT1v3t90mtUz+nH1eSKHf35pPJf1fVxo6OfK2C5NuPAkgdP34/BysqWkspqU3BIm94hCo9Ox9+ozANqH+/PR0A7IFEoevM4gws8NF3tLNFo9czeeQlajZMcHw/B3c6Ck1kDGoVaSWFGtQF17buRKFecexbP/+vM6Eye+Lnase28AR35+waGbMXWeWz2aBjOzX0tqFGrGfvMTGp2OIA9HbC3NiE3LY/nEnhy9/ZL3+rUixNuFyhoFG07fI9zfnUfxGVx9bqjorZvVn1svUogIcKdLZBA1CjW3XqZSJqth64VHdfbpYG3O+rkDKDUp52D6PZ6WpOJuZseikIGkvKmgSaAXIV7Of/iMrVGosKuVFet0esqqa1CJ1OjVcOF+IpvP/VoF7BoZRKfGQfx46i4rJvfC2caSxfuvEJdewA/T++LhaIOXk+3v9vOfjIyqIj5/dYQVESPwsnCkQF7Bpy9+4oOwPtSzcjOG877DO7zDO/xv4Z2tOLBy5UpsbGyMP15ev3ch+r8GUxMJfVqEMbpTYwCO3H5pJEufjuxMRID7XyVLYJC7hXg7882U3pz+eiL7Px7J6E6RdcgSgFZrkNHp9bBo10U+23XZOHBNyCpE85sZWjOphEFtGzKiYyMAbr9MRaXR8jQxC4DJPaLYvmAoQR6OaHQ6br9KNdjUAQWlMh68SedebBoV1QrKZDUUllezaOdFyqoU+Lnao9PrOXzrBQuGtEciFjFtzXFySypYPqkXNpZmDO/QGEszEyZ1jyIpuwiT2h6QDuEBmJpIyCmuZP+NaG6+SGHT2fvcfJHCV/uuEOjuwMM3Gfxw/A4z1p1ABzQP9Wbxvqss3nuVDhGBNPB15ZMRnWhSz5PKaiVN63lh9Zu8Ki8nG7ydbQnydMLD0QatTkeIjys3YpJYPqknpiZiSmU1lFcrsDA1Yf17A3C2taRMJsfV3orpP57ggyHtcHewpqiymqlrjhPi5Uy3pvX4er8hs8fB2hyBABKyithx6TFqjZZjd15y9sFr2jT0Y/H+q4AAtVZLqUzOwu3n0Wp1LJ/Yk9ySSr7ad4VFOy/w/uB2hHk7s2BIe5oEeXL8biwrD9/ETCIh0MORgrIqPtt1Eb1OR3xmIXLVr9KZvNJKVBotAbUysI+3X2DhsA7EpuVz62Uqm+YOIjLQk2HL9jOua1OGtY/g01GdmbnuBAAfbTtPhwh/+rdqQFF5FfraexHg0M0Y1p26x46Lj1k+qSerT9xGJBQysHUDvj3yq+U7wLeHb+FqZ41eD6M7R3L8zktO3Ivlw23n6NsyjOjkHHZfecq6U/fILa3E3sqcl29zqVaomL3hFOvP3GP3lad0iAjk2J2XVCtUzFh7gsTsIpbsv4ZGq2PnpSd4Ollz4OOReDrZ8Ca9gNXHb7N+9gCGtA2nf8v6PI3PRKnWMLNvS65HJ1NYXoVGq8PLyZYfpvdl05xBmEslyFVqRCIhcqWKyhqDLNPfzZ5Dn47GydYStVaLn6sdp7+egIVUgkgoJD7DINUc0zmSw5+PpVWYQSp7+9VbowQuzNuFUpkchVKDv5sDd16lkltSSbCnE7s+GMbFpwk0D/bmwqPXbF8wjPOP3jCxe1Sdz7msRsm4rk0prqwh9m0euSWV9IwK4ZMRnRjVqTE7Lz/B18Web6b0Mu7/ekwy1TUqEjILySgs43lyDleeJbBqej+215Ilwz1rYSRLYJB7/rLvksoavjty63dVZh8XO2LT8oxkqW+LMGO/4eVniVyPTiYpu4i9H49ALBSSnFPM08QsFCoN5dVylk7oToi3C2KRELVGS2Rtv92tFymM6tQYkVDAgi1naRzkSamshnMP3/DtkVs08HVl56UnAHRrUo8t8wYb5XmbzzzEXe/IDL9ufBs0jjFmXfhuy32sTE3x/gMSo1RreJaUzYTvD5NdVIFOpyc5p4gxKw9RWaLCUixFIqr79SwSCfF1seXz0V34ZMcFvth7maHtGrFiUk82nX3A7PWnyCgoI7ekEpn8H+szzS2pIK/0V5fUoooqMgvL/qFt/hF8LJ1Y33QiXhaOALiY2bCqydh3ZOkd3uEd/uPwbyVMixcvNjou/bmfZ8+e/Y+3v2jRIioqKow/WVlZ/8Sj/8+FraUZU3o1x/o3cp0gD0e6NgmqM4j/W2BlboqLnRVOtpZ/SLQcbSxYMaknTYI80evB09mGHQuG0r1pPb4c0w0rc2mdXio7SzOm9myOuVRCZY2SL/ZcZsPsgSwY3A6NTsf0tSeYM6ANE7o1Y1zXpmw4c5e3eSUk5xazZP81vth7mbuxb1GqNczffJbolBzmbDhFRkEp8zef5WliFl/uvcw3U3obTCAm9uTgzWhmrTtJbkkFRz8fS2xaHp/svIiJWMTKyT0Z160pMSk5+LjYsWxiDwBuvkhlwxlDJUwPRAZ5Ym9ljqxGyYTvDjN/81k0Oh1+bvaYiEWkF5QZZvmr5JiaSJiz8RSVteYYNhamLBjSgaTsYuwszejRNJi1s/oT5OFIXokME7EYyW96JX75XanWklNcwcl7sQxtG87W84/4cGgH43o+LnbkFFfWmlQ4svvD4Xw7pTcCARSUVWEqlXA3No2Z/Vqx/NAN3mQU8NmeSyRmF/P+5jOk5Zey8ewDKqrlRtvzxkGeWJlLOfsonhWHbjCxezN6RYWQW1JBsLcTSo2WzecesHxyL8xNpXy17wp6PYT6OONiZ4lCpeHTXRf5cGgHGvi4UFxZze4rT5k7sA2dGgViJpWw8vAN5Eo1n++6RN+WYbzJyGfjnEH4uxms088+fMOL1FxUWi0ajZYRHRvRp0UYAKm5xTQJ8jCaDywa2Ynvjt4yyvC2zR9ilOd9uusSFqYmpOaWkJBZCMDQdhEgEBj7vt7mlSBXqKmsVvDd1N7Gqs/NmBQ0Wh1Xnyeyae4gnGqX7736DJ1eT6i3C5N6RjFtzXHOPXqDXKnmi72Xuf3qLWVVcvq3CmP+lrNsu/SYR/GZHLwZzbpT97jxIoXVM/vx3dTeVMuVlMlqWD6pJ6um9cXd3hoXOyu+O/ozh27G0CLUh4yCUnJLKli04xLPk7OpVqiJSy+gVFbDV+O6MWdAGzydbCkur2LewLZM792C3s1DWbL/GpFBHnw0tAMZ+aWMWH6A1NwSFo/rxoiOjRm98hBHb79kdKdInGwsaRsewOn7sfRqHsqV54kUV1TTPtyfz0Z1ZlKPZqw7eZdJq47QMyqELfMGU1AmY8rqYzhaW/D+oDYEeTgS7OnER0M70K6hPw7W5pTKamge4s3yQzdYvO8qQR5O7L36BLO/YOTyW7zJKED3BwKIZ4lZ+Lna06lRIANbNyDYyxkTiZgpPaNoWs8TT0dblh+6QUGZjN4tQn/zLJPSpoEfjjaWRudElVrLj6fucetFCgcXjcbT0YZvp/YBDPJCC1MTPBxteJKQyZbzD/l2am96RoUwpF04VuZSVkzqSVSINxO7N0Or1fPVxht89uM1CvJreH9QWyxMTcgpqajzDARDtX3RjgtkFVUwfe1x7sWlMXW1IePq/ut0Tj94zY+n7wHgXCtXvvw0kadJ2chqlBSUVRGdnMOBG8/ZduFRreFJBW8yC1i87wqf7rhIekHp33Se/xS5JRXMXHeS2RtOkVdaSXFFFV/uucKE748Ye+X+mfhT+Z6dicUfkqUKVQ1Fil9JXLVGSamyCp3+zxsUvcM7vMM7/LPwb5XkFRcXU1xc/BfX8fX1xdT0V3euv0eS96f4W8tu/+0oqaxm+aEb/Pwytc7ysV2aMLF7M6NE7p8BlUZLfkklF58mUFmjwN7KnIuP41k5uRcejjbEpedzPTqJUZ0i8XdzoKBUxsGb0Vx5lkhRRTXTe7dAr9dTUFbFmYevGdSmIW8yCmhSz5MTd16xdlZ/Np69z5LxPfh6/1VepBpsW5sGeTKkfQRf7rmMSvOrM5RIKGDJ+B5cfprAo4RMvp3Sm52XHvM6owChQECwlxPxtYPnkR0b0bt5GFbmUjILy/lw61mWTehJQnahcSZZLBJyeeVU9l99Rp+WYYz77jDyWvmZp6NN7YD9ZzIKyhAI4LupfRAAH247b5Th2VuZs2jnRbycbZndrzVikZBVx28jEgiYM7ANM9edMLqQoTdkSDnbWrJkfHe8XWx5mZJLo0B3Csqq+HDbeYorqo3Sxem9DaGzEQHugMHhMKOgDC8nWx7GZxhmrnOL6NK4Hh9tO19nAPqLDGzpgevkl8mo7+PCN1N6cSMmmQ2nH7B4XDc8nWwQi0SM+eYQrnZWfDu1F+ZSE9QaDRqdnhlrTxDi7cLX47pRrVDx/qYziERC1s8eQLVcxbdHbrFkfHcUKjXH7r6ic6Mglh007A/AVCJm9Yx+nH0Yx7TeLTn36A2B7g4cvf2KCd2b4mpnRVmVHJ1Ox7KD11kxuTeFZTL06AnxcqZUVoO51ITF+64yd2Ab1p26x8fDO7Lq2M9M792SLecfMqZLJGcfvCYyyJPKGgXD2kcw4fsjxkGsp6MNX47tSmW1gtuxbzn38NfMpf2fjMREJOJGTDLbLj42Lv9uah8O34qhvq8r/VqGEZ9ZSH6ZDAdrc+QKNW0b+rPj8uM62wKDRLZrZBA1Kg23X73F1c6Sq8+TaBHiTc/moRy49pyRnRpjbipBq9MjwNCbYyIWU1xRhY2lGaDnu6O3SckpomOjQCZ0a8aZB3HYWJiRV1rJybuxBjLvas/3U/uw9uQd7r1ORyCAAa0acOFxPCqNFi8nG74e3x1LMyn2luacf/yGKoUKoUBAYlYh3ZoEc/NFMtP7tOSL3ZdJzC5CJBTQItSH+7V2/j2bhTC1d3NqFGpMJSLEEhEJGYV8d/QWNpZmpOUZBu2RAe58MKwDUomIhIwierUIpUxWg1KjxdXO6g+fLRcex/PFnsu/Wy4UCPh+Wh9kciWB7g78ePo+TxIymdKzOfU8nfh89yWGtosg3N+Nn27FGJ8ZQoGAQW0aMKln8zr7zCgoQ63RsuPSY64+T6JLZBDzB7Xj/KM3bD7/kHqeTswZ0Jqjt1/yyfBOZBaWEejhiLWZCZVyNfmllciVar7af5UVE3siEgnZfPZBnfiFyEAPlk7sgZu94XtHo9WRkFXItDXHUKg0xvUcrS3Y9eEwNp17wOWnifRoFszHwzty4m4sG87cJ8zHhc9HdSE6JYdVx36uc04+G92Z+6/TuRmTAhhkmgcWjcLdweYPz+8fQafT8yotj2lrjqHR6vB1scPW0sx4Dr+Z0ot2Df3/onvp/wYqVDUcSL/LtbxXbGxmsKu/UxjPt2/OsCVqKoH/pv6t/4soVVZhKpIYw3ZLlVUI/6BP7R3e4f8K/iskeY6OjoSEhPzFn9+SpXf461Cq1Jx58NpIlj4c2p6RtRK4/defE5OSg073z+PIOUXl3HqZypGfXzCgVQO2X3xMekEZi3Ze5MqzRF6k5BDo7khJZTVlVTU8S8qinqcTi8d148sxXTCXSmjb0J9bL1OY0rM5Y7tEsmR8d+68ekvL+j6UVcl5k1HAe+tPsmJST6OU51lyNjeik4wVoV8wd2BbHsZn8DA+gwndmrJk/1Um92xOmI8LOr2+DlmyszJn2ppjnHkQx/zNZ1CqtWy98JBm9X6Vbmq0OpYeuMawDo3IL5WhUv86uCmvVmBuasJ3U3rT0M8VvR7i0vPxc7NnUo9mrJnZH28nWxKzCknLL+XOq7dsPHuflYdv8OB1OiqNluyiCspkcizNpHw7pTcrp/TCXCqhtLIGtUaLQqkh0MORGqWGxfsMph2D2jTg2Bfj6N40mK0XHlEmq8FMKmHr+Yc8TcomyNOR4spqqhUqsorKmdg9Co1WZ5Qt/YIfpvflh+N3jOQlr1RGZlEFYT6urJzSiyvPE5m65jiyGgWt6/uSXybj+J1YzEwkKNVa1Gotuz4czgdD2jFi2QGEQtg0dxBrZvTjy72XScwqNMjtfjzJB1vP8TwpG6lERANfF058NR4PR2uc7SxZfeI27/Vvw8c7LhDh74a3sx3vD26Lg7UFD16nY21uikarZ+OcQVyPTqJKriK7qIKc4gp8XOyJTs7hh+l9ySuVkZRdxAdbzzGrXyu2nH9I/1b1efA6nSeJWbxMzWVY+wg+2XGxzox/dnEFmQVlJOUU/47gHLoRQ1ZROTtqCfQv+Hr/VcZ1bUrzUG/MTCTU93XB29mWx28ycHOwRo+eOf3bYP8b23tfFzu6NqnHnE1n0Ol0xGcWUFxZw+SezfF0tmX/tef0bhHKxFVHOHbnFa/TC1BrdMxYd4LVJ25TIqsht7gCldpgECGTK2ke4oNEJMDV3pp1p+5y9PZLfFztEIuEpOWX8vGOC8wf3J6Wod7o9XDqfpyRLH02qgtxafmIhUKSsotYe/IuOy4+Rq5U0SUyiC/3XuZGTAoXHsezdEJ36nk6odXpjWSpc+MgmgZ7MnzpfvZcfUp5tYL7sWm42VuzbGJP5g9qR6i3C36u9nw5thtF5VUkZRfTPMyHMlk1m889ZNL3R8gqLP/DZ0t93z926tTp9ag0Wraef8TEVUf5cGh7LM2k7Lj0mIXbz+Pnas+wDuFIJWJGdmzMN5N78f3U3nw5tisRAR6k5ZWg+I2M1MfFDkcbC+Okw/XoZMZ/f5jN5x8arpurHfmlMu7GpnEn9i3W5lJ+uhVDan4ZQ5fuo1RWw8Wn8Xw2sjM/HP+Zimo5gR4GiZmJWMTknlG8ySzg812XKKu978QiISGeTswb2LbOe/t2am88nWz5cEgHFo3oxIdDOmBjYcaQtuEsHteNeQPbMmfDKer7uODwm2w2dwdrmgR5ci82zbisvFrBjZgU/tqcqKxGiaZ20kkoFBDk7sDGOYMQi4SkF5QZydKyiT1oXd/vL5KljIKyOlWo/DIZcWn5qDX/mN15tUbB4fQH5MrLeO/pTo5kPOCLV0eo0ijYnnKdSvXvDYbe4e9HkaKCRS9+4nbBG2o0SsqUVWxJvsaBtLuUq/7xwPp3eIf/ZvzXTMlkZmby4sULMjMz0Wq1vHjxghcvXlBVVfXvPrT/KEhNJPRrWZ+WYT58OrIT/VrWZ2qvFozu1Jih7cJp9Df2MP0tqKxWoNJoOXH3FRXVCi48imf9ewOQ1ErUsorKUWq0fHf0ZzacuY9Gq0NqIuGrfVdYeuA6kYGe9GwewpbzD9k4ZxBeTjaAgC3nH7JoZCd6R4XiaG2BAAGfjOhEWn6ZUVdvaWpCnxZh7Lj0uM4xnbj7ih7Ngtk2fwiTe0SxemZ/SmXV+Djb1Vkvwt+dvNJKapRqdl1+ikarI8DNgXmD2rJw+3kigzwY17UJ/VvVZ2yXJiRlFzJ/81kaB3qw/+ORBHk4UiVXMnfjaVQaLfMGtuXDoe3p0zyUtSfu0r9lfZQqNdPXncBELGLBkHaAob/jaaIhU6lT40DMpRK+GteN5RN7sOH0PbZdeGToz5nZDy9nW4RCAdPWHmfRzot8NqoLIzs2olGABwMX72FAq/qsndWPzo2DuPI0kWvRyXx35BYP32QQk5LL9ouPOXU/jtScEgLc7Dn884s652DFTzeYO6ANEf5uWJqaUCqr4cs9l9FodZx7+Ia7sWmoNVoSsouYP7gdnRsFMqVnczacucfduDQyCsuRiITIVWoWjepEWl4ZeWUyapQqRndqwvnH8RSUySgokyESCln/3gDEIhGTekQhFglZO7M/i8d1Y8Wknny07RxlVXJMJGKWHbyOVqvj892XiE3P517cW+yszPho+3myiypIzimioZ8bNhZmDFu6n1AfZ169zaN1fV/srMwor5IzZ8Np5Co1/m4GgwowBC6vOvYzY7pEIhYa9v/JiI7YWZoS4u3CgevPkUpE9G4eyqFFo3G1t2JKzyi+2ncVnV5PmLcLW98fYpTnrTt1FxOxiKScIqRiMUlZxUzoHoWTtQWxaflsu/DI2EsEkF5Qxs8vUxnbpQmLdl1i7oA2VFTLifB3Y+3JuwS4O3D71Vs0Wh2Hb73gbuxbZv54gopqBa8zCnC0scBcKiE1txhfF3suLZ9CkIcDNSoNv3yk2zbwY/X0fiyf2NMgOxMY+mUGtK7rLjqobTheTrYUllcxfPl+nGwtjLLH/dej+WLPFbQ6PcGeTvSOCkUkEtGsnmedbbSu74usRoVaq+N6dDIvU3NpFx6A1ETMN4dv8smOC3w8vCOfjOjIisM3WLDlHCZiMauO3uJFah7ZxeXkl8n4+VUqNYrfO6I5WFkwvmvT3y0XC4VYmkr5YkwXPhjSnoM3oqn6Tc9OekEpNQo1Wy88ZNHOi2h0OlzsrHjwOo0v9lwmPrOQimoFiVmF3IhJ5tXbXFQaLX2ahzJ/sOFz+oubaKfGgYzo0IgbtZb33x65hVanp2NEIGtO3KG8Ss6CLWcJdHdky/kHzOjTisfxmQxu2xBnW0uWTexJtULF8ok9ic8qRFYtp0ahQqfTk5pXwqXH8cZ+U4DPd18mu6gCe2tzBrZugH0tKbK2MKVdeABPEjL4fEwXfjh+m5Lf5GxlF1ew/NANlk3sWccK/X5cWp0K1p+islrB2YevicvIR6PRolCpiU7NxdHGAk/HXytTVuZS6vu4/sXJtoyCMqauPsaUH47yNq+EgjIZC7edZ/Lqo8Sm5aHW/Pnj+GtwNrVhU9RkpEIJufIyNiUb+jab2vvzcVj/d9WPfwLkGhVHMh4SU5bGV7HHuJr3is3J1zid/ZR9aXdIkuX94esqVXJKlLJft6NVUa6q/qtE/R3e4b8N/zUueRMmTGDv3r2/W37r1i06dOjwN23j/xdJHhhkeSYSsbFnqUxWgx7qzHiDYWCgVGvwqP1yLK8yfKE721kZdf6/oLxKjo2FKYJaI4a8kgrWnbpL/1YNDLKiUB+yi8opr1Jw8GY0nRoH0irMlxWHbqDTGyy0iyqqjNbT303tg4VUwrWYZH44dptqhQqxUIhGp8PURMysvq14m19KhJ8r7o62vF+br+Nsa8nKyb345vBNknOKEQkFDGsfwYm7sag0Wrydbdk2fyimJmKq5Ep2XX7CyXtxwK8ufEKBgOWTenIjJtmY/7N6Rj/S8kt4FJ/JrH6tyC2uoEap5vT9OJZO6MH60/fo3SKUdSfvsnpmfz7fdYniymqWjO+ORCTC1tIMPXrWn76PQAD34tJoHuJN7xah1Pd2Zdra48aBmKejDdsXDGX0yoOEeDkTGehBu4gAPt5+AROxiPbh/vSICqGkoppbL1M4dPMF9TydWDerP7N+PElafikSsYjZ/VoT5OFAtVLNsTuveJKQWeea9W0RxrTeLRixfD/VCsO5G905knUn76LT64kM9GDZxB7kl8mYu/EMDtbmfDi0PZ/tukRljZKFwzrQPtyfgrIqxEIhFXIFOq0OuUrD06QsfF3s+eH4bUZ1MoTPCgQCvtxzmSZBHswf3J6Jq46g1epYNaMv2y88Ii2/lA1zBhkc0B6+4fKzRJZO6MHp+3G8zS9h4+xBfLzjAjP6tMDTyRaxSEh2UQUrD99kw+yB6PV6zKUSJCIRx+++wtfVnjBvZ8RiEV/vv0pMSm6d998xIoB5g9pyN/YtPxy/w6hOjWlV3xcB4GJnRXFFNZmFZUjFYur7uSJXqknLL+VNRj6D24Zz+WkCbRr6s/HMfcZ3a8qG0/dZNLITq47dZu7ANnyx5zKB7o5M692C6ORsJGIRjQLceZaUzdqTdwEY3akxxZXVXHlmcGBbMaknlVVyvFzsqFGqOa0kBCkAAGluSURBVHQjmjFdmlBWJcfT0Ybr0UkcvxtrfA+2lmZ8M7kXcqUabxdbUnNKcLG3IiWnGJlcSVFFNSM7NiItrxSFWsO5h6/5YEgH8stkhlweAbz348k60lWBAJZP7MmbjAIO3IhGIhay84PhrPzphrEKay6VsPOD4dx+lYpCpWHP1aeAQf6l0+sRCQWsmdmfKrmCq8+TGdCqPvuuPWfh8I7M3XiawvIqzKUSPBxtjPlbC4d34HVaAa8z8vl8dBcexmcwplNkrdTw9yivkhOblsfOy08oKq+mvq8L/VvV5+CNaCL83ZGIRcZewyFtw8kpqcDL0Za24X5sO/+I2PR8hAIB/m72pOQaKh/zB7cFBEarbgA3eyu2vj+E84/e1JFedogIYHiHRlRUyTn36A3+7g5YmUmxtzIjwt+DL3ZfIiG7CKFAwPYFQ1m87wpZRRX0aBrM1F7NWX7oBtEpOTT0c2XB4PbI5EpqlGoiA935Ys9lpvVuyf3X6bRr6MeM2nw3P1d7diwYanTPq3M+quVcfZbEN4dvIhQI+HZqb6rkSqPRzueju3A39q3R6KdXVAhfje1Wp0fyF6jUGi4+SWDJgWuYiEVsmTcYmUKFUqnmyO2XPE/OrrO+n6s9303tYzR0+VOk5hYzZfUxKqoV2FqasmBUW1wdrPh88xW+HNuNMH8nNAIdDiaWxu+Qvwc1GiXrEy8bg4EBTrb7wGjj/g7/OIoUlSyJPc7jkpQ6y6cEdGK4TytsTOrek5UqOaezn3A2+xnrm03CzsSSJ8UpLIs7yeaoKfhbOv/htdbotMg0Cux+Q3TLVdVYS8zeSSvf4V+O/wpJ3t+DPXv2oNfrf/fzt5Kl/9/gYG1Rx+DBzsr8D8nSsoPXmLTqCJmFZVRUK9h77RlDlu4jMbuuw11ReRVLDlzjbV4Jer2eMlkNu68+o2NEEGceGGyGlWqDE9eR2kqGnaU5OcUVfDa6MwCF5QayFOrtzPsD2yIRC7Ewk9IhPIBpvZsDBvMAgPFdm5JVVE5iViEn78dhZ2WGvZU5LnaWrJ3VHxdbSwa1aYhYKOSH6f3wcbFj+STD7Gr/VvVRqTW8SS9ArdHy4LWhl2BUx8ac+Go8DWrleZeeJNAqzNf4Hj/ffYmm9bz4fHRnEjILCPd3Z+VPN3mdUcAXey/TMyqERTsvkVVUwfdHbvHt1N5smTeYwnIZczeeZuy3h0jLK+XTkZ3pFRXKwmEdKa2soZG/Bz8cv10nAyu7uIIfjt9my/tD6BEVQqfGQRy8Ec2nIzvTvWkwvZuHUVZZQ0ZhOSM6NGZUp8Y42VjwOsNgIezrYodao+Xik3gUai1f77/K+4Pa1ulP83O1Z0qv5ihUakZ0bIyzrSWLx3VDLBSydEJ3LExNmDOgDWVVcr49fItNcwfx2ajOfLH7MpU1SoQCAREB7piIxegBtVaLp4MN5uZSQn1cGNougrR8wyD00M0YTt2LNfaU5ZRUUqNUYS6VYGNpiqlETGZROZU1SmavP8n2i485/zgejVZHYlYRgR6OtGsYgFKt4fMxXXC1t2bexjN8suMiNham7FgwlC/3XmbmjyfJLalEo9MR7OXM1WeJiIRCbr96S0xKLgIBfDS0A/MGtgHg1stUXqbm0rFRIOtnD8DJxhKxUICbvTWLdl5kz9WnNK3nRUN/Nzacuc9X+67S0M+Nbk2CySutZEi7CLQ6LaM7RWJrYcbqmf2wsTBl3sC2WJlJ6dYkmJEdG7Nk/1W6NgkmLi0XjVZHyzBfwv3dmNmnJR0bBTK9d0t6NA2mV/MQIgM9CPZyJiGrkMfxmfRrVR9bSzNep+fx7ZFb9Iz61agAIDLIA1c7KwI9HCmpqMHL2ZZNZ++z9OB1coorsDKTsvr4HU7dj2PRzotEJ+dQUC7DXCrG1ETE8oPXjTK8vQtHEOHvjl5vqJaM6RxJoLsjrcJ8eZtXQlJtcDRAjVLNz69S6Nks2Ghf3rNZCOeXTTLK83Zeeky4nzufjerMJzsvEp2Sw/fHfmbdrP442VhQo1QbydKXY7qSXVjBi7e5fD66C4v3XWVkx8Z/liyBgSy2bejPj+8NYM2Mvgxs3YCUnBLyS2Ucvf2S+r6u+LrYMbRdOBO6N+WL0V1xtrPE0lTKyim9aeBr+Kz/QpbeH9QWSzNpHbIE0Kt5KOcfxxvJ0i/VlZ9fpvLTrRhUGi1zB7alaaAHm84+ID6jkMIyGR+P6AQYZIIP32TQrUkwYHDrG7XyINEphrDnPi3CMDURM3/zGRbtvMDz5GzmDWzHvE1n2HX5CS9ScznwyShsLUxZPK4bVuZ/LEW3tTCjW5N6TO7RjB9m9KVVmC+B7g58OLQDE7s3I6e4wkiWAEbWWuf/EUwkYqJCvPByMpikTF59lIPXn6PW6YxkacGQdqyY1NMo8fz5ZYrRCv5P4e/mwI4FQ7GxkDJjUAue6N+wPO0YGz/uT/0AZ64VvGLY3TWkVBX83dWHao2Su4UJdcgSwOynu8ip+Z+ZW7zD7+Fkas3SiBGYin6VXTaw8WLEH5AlgGqtgm0pN8isKWHO012czX7GwpgDlKurWZ94iQp1ze9eo9FpSZTlMvPJduO1y6wuZvrj7aTICt6ZeLzDfyz+aypM/wz8/1Rh+luQll/K2G8OUaNU42RjQdNgLy49MaTXj+/WlAndmmJjYZA4LT90nRsxKVibS9nxwTAO34rh5L04xCIhOz8YRk5xBfGZhTQP8Wbl4ZsMadsQsUhEmI+zsULwizQk1NuZJeO78zw5mw4RgdQo1az86Qah3s40DvQgo6CMB6/TmdwjCoVag1ylxs3OGitzKVqdjhqlGitTE0wkYgQCAfuvR3P45xjaNPDl4+Gd0Gi0xGcVUiNX4eVsi42lGY/iM2hd35dLTxLo37o+J+7GEuThxL5rz5g/uB2L912lsLwKD0cbNs0dhEqt4UZ0Mk52liw/eKOOWYK3sy3fTulNSWU160/fY+HwTqTkFiOrVtI5Mog9V5/SKsyXR/EZTO4Zxc2YFGMu1pwBrREJhcbqw+a5g8goLOe7I7f4dGRnWjcwDFznbTpjzLe5/TKVH6b3Iy49n6/2XqFHs2Ba1/dj0a6LWJpJ8XO147NRXTj/6A2n78dR9Rt504dD2xMV7I2piYjKGhUfbTuHqYkEXxc7PhrWgcfxGdhbWyAUCrn1IpkbMSlEBnqgUKl5GJ+Jt5Mta2b144Mt53C2s2Rqz+ZYmUlZc/IueaWVfD+tD4dvveDU/TjjPr2cbPl4eEfkKjUBbg7kl1WCXoCZqYQFW84aJXIA0/u0QK/TGweqKyb1pL6vC5kF5czfctZowf3LgE0kFLBsYk8a+Lgwf9tZQj1daNvQnxAvJ3ZefkJ9HxdepOZiZ2WOtbkpshoF/VvVZ9flJ3RuHERcegHdIoPIKCpn0c6LADQP8UYkFPDgjYFYfzmmK0KBgBJZNfuvPWfzvMFUyZXI5Co+3XmR1TP7YWdpxtXnSQxu05Do5BzCfA2SvjFdmnD1WSK9m4eSX1aFVCLi9IPXTOkZhUggRKnRsPzQDT4Z3om3+SX4ONux8ewDZvRpQZmsBq3eQNwrajOVfsGEbk2JDPLAzd6arececv1FCtN6tyDE04mE7EKeJ+Xg7mCNk40Fg9uF8zQhEytzU54nZTGyUyTPk7NxsrEgPb+MBn6ubL3wiGm9muPuYM3jhCzMpRKDzbxOT7CXE56OttyIMVReFwxpR7sG/hy+/YJG/u4cvBHN4vHd2Xv1KZN6RFFYKsPM1ISiimo+3nEBAbBici92X37C61rrc4EA1r83kI1nHzC9TwvQ63l/81ka+rry/bQ+ONtZUVmtwNriV6Lwy99VciWJWUWsP32PlNxi3B2sGdO5CfW8HHmRkkfTYE/0ej2WZlIuP0lg/Zn7uNtbs23+EL47+jN3Yn8lEN9O7c21Z0nciX2Lo40FVXIllTVKVk7qyb3X6Vx4HE+fFqGM6NCYO7Fv2XbhEQ39XJnQrRmLdl5g5eTeKNQaKqsVhl7M2orSL5jRpyVVciUHbkQbl80d2IYujQNRqLR8e+Qmz5NzeH9QW+p5OrFw+wVMJWK2vj8YL2c7quRKLM2kv6vu/ynKq+RIJWLMpBJKK6u58SKFrMLyOvudN6gtA1s3MObW/Tnkl1YycsVB4z03qUcz3OytUao1JGcXk18mY0DrBrx8m4uTjSXdm9b7s0YSBWUyPt11idmjmjM3didKnQYPM3s6uzZgX5rhGdjHI5J5wT2x+TtkdPnycgbc/h4depra+zMhoAMfPN+PUqcmyiGQ5REj/nBA/w5/H8qUVUYZ3m+xuOFQOriEGY0gfoFap+V1eRazn+1CpftVctnAxotvGo/C2fT390mFqoYhd1dToa7B3cyOJeHDWPTiJ4qUlTib2nCg1ex3Est3+Jfib+UG7wjT/8cok9WQVypj2ppjxuBRgBEdGzG1VwvsfjPzm5ZfypTVR+sMdgGm9GpO8xBvLj1J4OS9WByszVk9ox8vUnOJTcujeYg3Gq0hPHLNiTvEZxYytH0EQ9uFU1JRw/WYJHpGhSCrURKbls+OS48Z0jacPs1DyC+rYu3JOwS6O7JoZCdkNUrWnbpLr6gw7KzN+HzXJdzsDblEKrWGyholPi62rJnZH41GR5VChVJlkDHpdYZejufJOchqFLQPD2Dpgau8N6ANh2/F8F7/Nny68yJzBrRh07n7zBvYjm0XHhEV4kVJZQ1Hb/8a5Hngk5EkZBay4qeb6PR6Wob68MWYLuj1MPPHE2QWltMkyJMVk3ryxe7LdGlSj+iUHJoGedAs2AuVRsuDNxlkF5czuE04yw5eJy49H4EA+rWoz4UnhsqLv6s9n4zsxLQ1x3G0saBcJqehv5uhB2bnBXpFhTKyU2PKKqtJKyjnZkwyHw7rwLPELO7EvuVRvEGe993U3qTllRLm40x+aRVezrYcuhXDnP6t+XLPFcZ1bYqPqx3jvztMx4gA2of7Y2NhxpkHcTjZWtIowJ2F2y8A0CTIA6FAyNMkg0X/6hl9AViw5Zzx/PRoFkyEvzuHbkazff4wqhUqxnxzkM9Gd+H8wzc8qpUNejnZsHxiT+yszFmy/xq5pZV8ProzOy4+Zu7AttQo1czZcMpY6RQJDTJKX2c7pFIJphIJd16lcuzOS76d2gexSEhMSg6L9xn6G0Z2bEzv5qEUlFayaNcl2oX7E+HvRpfIelQrVDxNzPpdftMHQ9tT38cVZxsLJq8+SkFZFbYWpozqHMn2C48QCgWEeLkwsUcz3t90hhEdIhjcLoI560+RXyajU6NAWtX3Jb+0khahPny49Rzl1Qr6t6zP5J5RfLTtPInZRbjYWbJ6Rj9+PHXXSFiOfjGOH47f5taLFGwtzfhhel/OPIjj7MM3SMQidiwYyq0XKQxrH4GsRsm5R29oXd8XTycbhAIB9+LSEQgE5JVU4Otqj7OtJU62lnyx5wpRwV44WJvTLNiLDWfv0zWyHml5JXg727Hq+M8sm9CTPVefolJrmdmvFR4O1uy9+oxHCZlsmD2Q43deMqRdBN8f/Zm5A9uw+vhtlk7sQXJ2EfU8DM6T3i52PHidjoejDcfuvORZkqFKYSoRo1BrMJdKWDGpF3FpuQzt0IhlB65zNy6Nr8Z0pW1Df47ffcmAVg1wtrOiqLyKdafuMq13C8pkclb8dMNYqfoFozo1pkqu5MLjePR6WDy+G77Odsz88SQfDe3Az69SjeY3VuZSZLVV0+WTeuJkY+gzc7GzxM/VHrVWh1QiJj6zgIa+rszZeIoujesR7OVEAz83vtxzmZdv8/hwSHuiQrxJLyjj8K0YolNyMBGLWDSyEyfuvGJct2bG5b+gd/NQOjcO5Mz917w3oDVxaXm8Ti/g5dtc5g5si7u9NR6O1kj/Aee58mo5JRXVPEnIQiIW0az2elv+lRgJhUrN08Qs5m8+a5wUMhGL2Dx3ME+TMtly3hDSGxXiTUM/V47fecXhz8bg8gfOhgXlMraef8jp+69pHOTOmMHhfJn4E8rfDKQ7utRnYVg/HKR/7Iz451CjUfGwOJFTmU9YHD4UOxML3lTmsCLuFD80GYe7md1f38g7/EXINUoOpN9je8oNAMb4tiVJlseTWnnelqipRNr7/cHrVGxMusLRzIfGZX9JKqnRaUmozGHmk50odb+OOyxEUrY0n0qQles7Wd47/EvxjjD9Ad4Rpl/xS2J9r6gQdl1+WmcW9sySiRSWV5FTVEGghyO2Fqak5pZgb23O2G9/Mq7XvWk9Ph3ZBaVaQ15pJe+tP0WVXIlIKECr0zOmcyRtG/px9sEbnidn8+PsAVTVKIlOyWHX5SdsnDOI0spq3B1tEQogLj2PjWcfsHPBMPLLq3C0Nkep1lKtUOLmYI1Wo0Ol0SIWCUnJLeHzPZdxtLZg9Yy+aHQ65m08zQdD2vPzy1SeJWezdHwPsorKKZPVsOfqM5ZP6snhWy/o36o+bvbW2FiYIhGLqJIrWX/6PovHdePE3VdEBLiz+dwD5g5ogx6Yt+lMHZenUG8XpvVuzqe7LuFfK3uzNDXB0caCV2/z+Kp2wP5Lr4dAAHs/GoFIKCA1rwSdTk+Tep5ce57MtouPWDuzPxvP3Cc2Pd+4D383ez4d2ZmSymo+3nHRuPzI52OYs+E0rev74udmz/rT91k9vS8+LnYkZhXx6e5LLBrRiWAvZzaevU+NQsWkHs1YuP2C0ZErOjmbrk2DuRmTzKTuUej1cPNlMm3q+1FSWcP8LWcQCYSsntkPM6mEy08T8HO1Z9Wx23XuoeUTe2JpZsJH286j0miN1x0M9tmD24VjIZVQrVBRVFnNmfuvufrc0MdTz9OJeQPboNcbAnedbCzJKirHwtSEFT9dZ3LP5vg42zF1jSGbBgz9dzs/GIZSrWb2+tMsndiDY3de0r9lfZ4nGyos3xy+WecYTcQiNs4dZDAnuf2SHlEhPIzPZGznSEwkIqavPWEMRnW2tWTjnIFodXo2nXvA/EHtmLHuOAVlVYiEAr4Y3RUvJxvsrS248yoVmVxFh4gAPt99ifSCMkxNxGyaM4hjd15y6Wmi8RhsLExZNtHQpzW8QyPmbTpjtKb/BV+O6YK1uSmu9tbsvPSYwW3DDdbofVrwIiWXJvU8OfvwNQuHdaBUJudpYhYbzz5ALBKyZmZ/MgpKjddnxaSenL4fR4tQH67HJPOm1lJ/+4KhpOQUU8/Tic3nHrBgSHtm/XiyNi/Ji89HdyWrqJyPtp3HydaCTXMGo9FqmbPxFBkF5YR6O/PRsA7M33yWitoKy/uD2lImqyHIw4mC8irWn7rL/CHtWbDlLHKlmo+GdaB5iDezfjxJYXkVX4zugplUwvfHfmbz3ME8ScykcYAHszec4pMRnYhOzmZqrxZ8tvsSTxOzcLWzYuPcQdx6kUKQhyPbLz4mrvZzIhIK2DR3EA9eZ7D32jNMTSQc+3Is5TI5cqWaL/deIb9MxrRezRncLpwPt54jNi2fns1CCPd34/LTRN4f1BY9el6k5LL5/AMWj+2Gn5sDJmIRqbnFvM0rxc7SjCBPJ/JKK9HpDE6bQR4OhPm48sHWc3w8vCNn7scyd1A7luy/yvNkA1lqFOBudJjr1qQekUGePHidjo2FKedqJY4z+rSkeYgXQR5OmJua/OGz+n+CEqWMzOpiLuXGIBKI6OXRGE8zB+ykv87cK9UaniVmMW/TGXR6PUEejtQo1eQUV2AiFrFici92XnpCfGaB8TXv9WvNhG5NEf1JBUyr05IrLye+JJdbNzIY3CoCHx8b1iVc5Gr+K+N6Z9svxNXM9n/0nmo0KhRaFfZSQy7VH/XB/E9RrVag0mmwq922SquhWqMw/v3/C/LkZcx5uovubo0Y7tMSpU7DktjjWIhN+Sis7++Irlyr4mlxKgtjDqDjNyoMcwfWN5uE258hslqdjit5L1kce8y47IfIsbR2Cn5Hlt7hX47/cz1M7/A/g0ar/Z1eXKnW8KR2MHL+cXwdsgQw5YejSERCtl54yJhvDvHprou42Fvx062YOus9fJNBQbkhe6a+jyu7PhgGYBw055dW4mhjyc2XKQZTgQ2nuRadzIYz96lRqjl25yX1vJyJS8/jblwaEQEe7PloBD+cuIONuZRbL1MZ/91PlMnkqDU6XmcUMHLFQW68SMHb2ZZvJvfi89GdWXfyLuZSCbs+HE6IlzOPEzIpk8n5Yu9lYtPz2HHpCSYSMXHp+XRsFECwpxNKlZqckgqEQgFf7LnMk8RMRq08SONAD9aevEt+mQxrC1MjWfJ2tmXhsI4IBQLiMws4+vNLPh3ZmUUjO/P90Z85+/ANUokEc1MTPhjSHsA4Yzt/cDtepOYy+puf+HLvVRr4uVFZrcTOypwQL2c8HW0Y3SWyzrnt16I+bzIMttK/xY+n7rF2Zn8GtmnIybuxqDVaFmw9x5HbL/l09yXUGi37rj1DrlQxo08Lvh7XnYtPEmld349wPzfC/d2JCvHCxdaSQHcHsorKKa+S06yeF+amEvxc7Qh0czAQ0E2nmbn2BGcfvqGhn5sxQwbAxc6S+r4uHL390mi08dOnYxjYugEAl54mGPqWCivILq7E2cbSONs/f1BbvhjdhY+3X2Ddqbso1RpkciWf7b7EzB9P8MmIzvi5OPDB1nNGsiQQQKmshgVbzqLXw84PhvLD0Z9pHuLN4n1X6R0Vwsazhub/Ng18Obd0El5ONqg0Wn44dhsvRxt6twzDw9EGc6kEsVjI6hN3jGQJDD12607dI6PQIAlddexnVk7uZSRLt16msOTgdUoqq2kfEYBer+e99Sf5YGh7fF3sWDuzP852lnWc8QA2zxvM/dg0bsSksOnsA5aO717389YziiZBXuSWypj8wxFa1fflxN1X6PR6vJ3s6N+qPr4udnw4pAMikYgFm88S4u2Mn6sh6HfOhlNGstQyzAdrc1NiUnP58fQ9I1n6bmpvDt6MZuXhmxSUyejQKJCF28+zdEJ3OkQE8F7/Npx+EIdeb8gMWj2jHxXVcnQ6Pe/1a1173xcyadVRQ1O/hSkLBrcz5GwduI5AAIt2XiQpp5j9157x46z+fDSsA0lZRaw+fpvN8wYzvXcL2jT0Y9Wx25TJ5ExfexwrMynT1x6nolrBhjP36dMijG6fbONpoqGC+f/au8/wqKr97ePfKZnJpJOEQCAJJUjvVYoU6ShFigoIIkhRihU9YgFBBRVEBcUOKCoiXQQEBem9995DS++ZTHleTJxj/joePY/HoNyf65oXs/eeyZq9J8ncs9b6rf7t6vH5D7uYvmQT//p4OQ+0b0C1MiUYf3976lQoTbDNH7fbzZdj+vL5M33IyM7zfpny/H1teLT7bZhMRrJz7bz64J0Mu7Mxd7esRaWY4jx1dwtOJiQyaMq8gt7Ntvhb/Bg4+SveXLiBAKuFj1ds57V5P3LozGXqxJfmg2+38s3Ww975ja8M7EhmTh73tanPmctJ3kINL/Rry32t6/JAQSn/qLAg0rNzWX/gtDcs3dW0OgFWPwZOmcemQ2fJyftlpcD/RmJuBhMOLGTo9g9ZfHEnCy5sY9DW93j72HKS8/5dVdZiNlGiWDCBNgvVypRg2vC7PEMDi4cRFmTDZvErNF/p9toV6Nqk2i/Cksvt4lJOCk/u/owXDs+lTfsyxMQF8+2l3YXCEsBD2z/6r+ccBZgt3rAEYDaa/rSwtPbqId49voqUvEzsTgcH0y7w7L6vCi2UezOIthXjvYaDubtMY0IsART3D2FszV6/GpYA0u3Z3rBUIyyWyXX6YTGaOZ+dxEsHFpLmoxT5pZxk3jn+XaFtU44s43JO6v/iZYn8KRSY/mLZBWvjrNl7kjV7T3LxemqhkrpOp4sryRmcuZJMQlIaeXYHKRnZhQowJGdke/+55jscvyjJm5WbV7DPycEzVzhVUKgB4GRCIvtOJVAqMoT6lWJZWFCNq2vjakwb0Y2YyFDua1OPr9fvp2/relSOjWJc//as2H6E5QXzmzo0qESxYBvp2Xk8OGUe566mcD0tk61HzxVqx55TCZgM8OZDXbFZ/biSkuENXU2rlaVTwypY/Dzf5E5fsomnP/yW66lZbD18jsxcO2v3nMTpcvPszBXMXrWDF2Z/h8vtZu3ekxgNBo5fvM4rX/zA8K5NSc7I4ZOCYDTnX30oHhqIw+miU4MqvDywI9NHdKN9vUo0rV4Wg8FA8bAgigXZyMzOZcIDHQgJsJKamcOI6Ys4fTmJjOw88vIdDGhXn7ioMCYP6UyFUhE827c1YUE2+rSuwycrtzPmk+VMevAOWtWKp8eLs4grHsaGg4UD6Lp9pylRLNhTXrxHc9Iyc+n36peE2KxMHNSJc9dSeG5m4QU631q8geKhQWwoCLPFQwMxG41sOnSW95ZtJiLYxuQhnp6lfIeTz3/YTb7DSZkSxXiiVwtmrdpBdm4+S7ccpFqZEgzv0oQlmw/x/rItVC8XzZhPltOiZjxJ6dnYHQ6e+Xg56Vl5WMwm3nioK9HhwbjdYDAaeGVgR95btsVb0h3gakomr89by1P3tKJbk2q8MawL6Tm53NuqNoM6NOSVgZ04mZDIyp1HiSkeyszvdjBlaGeG3dmYQJuVi4lp5NodnLiUyLhPV/HQWwtISEonK8dOSkY256+leCsgvj74Tl598A7vPKZjF68z54fdPNazOR8t30ZKZg6T5q7hvUd60KlhZUb3asmmQ2d4Y1gXmtcsz6uD7+D05WSWbzvKhWup3NOyFpt/tsDniK5NebhLE8BT2fByUjrdmlRj6J2NeeWLHygdGUp0RDCbD5/j3NUUJnz+PV+u2cPHK7eTlpXLj3tP0bFhZTYdOkO+w1PE4ufW7z9N//b1CQv0p3erOny5dm+h/d9sPUxadi42i5m8fCdbDp/j6XtaMWVoZx6dsYT+r80lMT0bg9HA4o0HGdixIc9+soKx/doSHPDvIVflSobzYMdGlCgWXKhHtE3dW6hRLhrcnqppOXYHb8z/kUEdG2EyGj1FV974mgYVY4kOD+bZvq1JychhyJvzGTF9EXFRxRjcqVGhNr8yqBN+ZhNGg4G8fAefr9nD4E6NiAwJZEC7BlxKTKdG2ZKs2XeSXs1rMXftHlrUimfaog3MGNWdsEB/0rJyefGz1WQXVL4cf397rqVmckvpCJ7s1YKHOjehRtlo7ry1Kh8/0Yu+t9dh+fYjjB/QgZU7j/JEzxZMXbCeMiWL8dn3u0hMy+RKcjrj53jmI36ycgdnr6Yw45stPPTWQnLz86lfMYbFGw8y5pMVWPzMHD53Fbcb5q/fz3c7jvLszBXk2h2cSkgiwN+Cv8WMy+3mjYUbWLTpAJOH3MmTvVrgdoOf2cj9r81lzCcrGP3hMp54/xuaVSvHe4/0ICcvn9mrd3J7nQq89XBX+rapi9v477/hZUuEMazbraw/cBqr2UxUWJDP4gx/1M7kU2xOPPaL7d8m7OHEz0pDGwwG4ktFMOvJe5g8tDNRxYIoFRHKjEe688FjPSkfHc5zfdswYUB75j3Xj+fva0Nk6C8DSnp+DheyEgkwW3DhZvqJlSTbPXNhAFpEVeHdBoOwGs1cyknmraPLSbf/shhAUbmUk8L4gwtYcmkn7x5fxZ6Us4zc8Qk7k08x48RqMv5Gazy53W5OZ1zlys+CR0JOCmczr/t+0P8R6R9SaD5YpDXY5xDKID9/XqjRkxphsUyq3ZfGxSsyvf5AYgMieKZ6t1+dp5Ziz+Lh7R9xPS+dQJOVxyvf4S0XP2rnTFLsWipGbkwakvdX/vzsXL7Zcpg3F6739sKYjAZGdruNbk2r4XS6WLHjKB8u3+b9FvfNh7syfckmRnZrRpW4EqRl5fDWwg20qBlPoypxnLiUyLXUTG6rUY4Aq4VTCYn8uO80deKjycl38MR73+BvMfPR43fjcrt56O0FZGTn8dKADsRHh3PkwnX2nLxEfKkI9py8yEOdmzJr1Q76t6nPrO92cH/7+ny6ehf929Zj1PTFtK1XiZ7Na5Brd/DQ2wuoXqYk97Wpy75Tl3n3m80A1CofzanLyWTm5BEREsCnT/VmxjebWbbtiPdcfPp0b57+8Fty8uykFkw27takGn1a16XfpC/wM5l4eWBH3l26mWM/q9xVNa4E/+p9O8cvXuOlz39g9N0tCQ8OIMhmwYCBrUfPUbNcKcqWKMa11Eze/3YLj3ZvzsQvf+BycgbvPdKDQH8LbyxYz5bDZ5k8tDPlShTjamomQ99c4P05j/dsjsPhJCPHTscGlQmw+tHlhZm0rB3PiK5NuZKcwaPvLsHucNKwUiz92tQjOy+feT8rx9usejk2HvQsJFnvlhiG3nErJcODuZqSwbaj5wkJ8Pd8uz9tIReup1G+ZDiTBt/Bi5+u4tC5q0SEBPDuyO48N2slz/VtQ0ZOHo++s4TQIH/eHdUds9HoKQRRMAQQ4Ol7WnHk/FUGdWjIPS/NITffQc/mNXE6Xd7CDM/2aU39irEs3nSQ2at3Uj46gmfuvZ08Rz5ul6d61iPvLibX7qBdvYrUji/Fa/N+BGBkt2ZY/UzeHo3RvVoSVyIMm8WPqQvWM7BDQ5IysvhyzV7OXU1heNemfLPlEGevptCgUiz/urcVM5ZuITffQceGlXlh1krv74K/n5m3hnfFz2Ri46EzlCwWTIliwcxfvx+7w0nP22pyJSWDqynpzPlhDy1rxdOsWjle+uJ7XhnYkfoVY0jPzmPZ1sO0r1+JCZ9/z4T72/PFmj20rVeRy8npTJjzPcXDAnl7+F3MX7+fiJAAapQryZWUTFIzczh5KZHaFUpRo1w0L322msMXrlE5NorRd7cgKT2bZ2euLBRG2tWrSPv6lXjyg29wu+HelrUJC7Lx5do9VIwp7u0pGdLpVm6tGsd732xhe8G2HrfVYPn2o+Tk5VOiWBAfP3E3pxKSSM3K5dzVZNrWrciYT1Zw5koyZpOR4qGBXE7O4OHOjSlRLITUrJxC1d5+Gp63bt8p5m/49zf7BgM8dXcrGlWOw2g08Nh7SxnQrgFr95zkakoGj/Vszv7Tl0nPzmX59qPMGNWd62lZPDZjCaUiQnny7paM+Xh5oUIUVeKieGlAR0a9u9jbS9etaXUGd2zERys863/1al6LPrfXYeyn33H84nXee6QH566lEGCxcC0tk9cL3lMALw3owLJth+ndqg4WPzNLNh+kXb1KBNusuHHz5do99L29LkE2K9MWb2RTwdC2t4d3Y/bqnazZcxI/s4mvnr2PIVPnE1M8lNF3tyQ3z8GIdxYRHhzAuH7tWL7jCIsKlhgY3KkRNctF8/3uEyzZcsjblujwYF56oCNr9pzg8zWeL3isfiamPtSVD77dyuM9WzDszfmM7deOuWv3sOfUv0vZj+vXjujwEEa8s4i5Y/py36tfMnFgRwKjTOxOOY39jB+L1x3mxWFt2Jp9hF4xTUi6nkOJ8OBCPbj/rTR7NqN2zuRI+qVf3d8kshKT6vTG3/TnDf9zuBwcSUsgNT+Lj06u4Uj6JTqWqk310Dh2JJ3kySqdibAGcTj9Em8eWc4rtXtTwvbrRSOKQpo9m6/Pb+WDk98X2l4msDjT6j/wXw8h/Ku53W5OZV5l6LYPKG4N4c36A3DhZsSOj8nMz+ODRoMpGxT1p//cLEcuuU4HEQW9f/kuJ5mOHIpZfn0440/z0V46uJD3Gg6mfFAUx9ITGLHjE16u1Zv6EeWxmv77+Xwif5SG5N2AzlxOZsr8dd4PiOAZvvbmwvWcSkhixY5jTP56nfeDybDOTfjs+93sPH6RoVPnc+DMZd5csJ5l247w3rdbOHc1hYfeWsAzHy9nw/7TnL6cxOCp83ln6SYOnb9KkL+VAH8L6dl5DJz8FYOnfk1KRg4BVj8iQwPZcyqBNXtPUjoylMlfr+O+1vV59N0lLNt6hElz1zCq+21M/HIN3247wpPvL2Pm6HsIslm49+U5ZOXaee3BO2lbryJzvt9FbFQYZqORFjXLM65/OyYN6kSQzcq9LWuz/sDpQmEJ4KkPlvFc39ZY/MyA55vvRlXKkJSWxbj+7cnMtbNql6cgxM/1alGT0EB/Xv7iBx656zZOJSTxzMfL+X73CYqHBRIRHMhTHy7j5S89//yup2QR6G8hLSuXrFw7w95awHOzVrLx4BmcLjcXrqfidLl57asfC/2cT1buoFHlMsQWD8VgNJDvdDGmT2uuJWdgtzu4cC2VN4Z1JrZ4GA91bkJM8TCy8+yUjw4HPJXW7m5Riyd7eYbnlY8O59C5Kxw6d5XgQM9clTcWrGfYmwuYMqwLTaqWYfLQzqzZc5JBHRtxW41yzBjVg0tJ6Yzs1oyv1+0nvmQELw/syPj72/PDnhNcT8vipS9+KNTuNxasp0nVshw4e5UxvT0lj+ev3+8NS/e0qEVmjp1BU+Yxe/VOACqUiiA00J853+8mwOrnDUtRYUEcvXCNvHwnPZvXZEzv1kSFBlIpNorn+rbh7ha1MJkMmIxGbFY/Rt7VjHeWbKZ4aJD3m/lpizdy9moKfmYTPW+rSWpGDu3rVyKueCjFQwMJ/Nm8jWLBAZQsFsI3Ww/xycodHDx7BZvFzO11KrD92Hm+Xr+Ps1eSmfPDHirHRtGtSXWmLvQEhte+WktKZg7j56xi1qqdLN50kFcGdmT4tEUs2HiAH/edJC6qGP4WM1dTMhk69Wtii4fidoPN4sf0JRtJSEqnWtmSTJq7xtOj2b8dNcuVZNidjXljvqf4SKPKcd72GgyeCmgul5t7WtTGaDBQ55bS5OU7mDGqB92b1aBDg8qYTUbKRYez5fA5ujatjslo4MleLSlZLJjpI+7CZvWjXb2KHL9wjRJhQbz21Rpmr9rJuavJPNe3DWVKFMPhdHE5OYOKMcVpUSueHHu+NyzVLB9N2YJjHpuxhFurlqF6mRI817cNDSrG4HbDa/PW4nC6yMm180LfNkSHh7Dh4GmOXLjGlPnruJKcwaerd5GYlsWCDQcoERbEpEF38PIDHb1hKSzQn2F3NvYOz3txzioe79GcQH8LscXDWLzpIF3HfkKTqmVpVr0cX6/fR/cXZ3H84nXeGNaFOd/vIiI4kPCQAN4pWDvpJ69//SND72xMfKkIRn+wjJU7jrFw4wFCAv2ZMGc1a/eeYuqC9aRk5tCvTT1vD9X9r8319hTe17ou+89c5sX72/NwlyYMmjyPDQdPM33EXYzpfTvPfLzcG5Y8ZfqD+GD5VlrWji/Uluplo8nMyeNqqueb7sqxUUx9qCsfLt/GvtMJHD53hbb1KhLobyHfWXjIrNPtZvMRz4LP7y/fypShnSkVF8Tog5/y4bnvMZfP48MxPXj9/CLmXtjMx2d+ICLSRoD1zwkwTreLLGeez/1Zjlwcrj+3bLPZaKZKaGlK+IdhM3tex4qEvRxIPc+DFVoT4mfDZDRRJaQ0k+vdd0OFJYBQSwD3lGlM0+KVvNuMGJjR4MG/TVgCcLidpOdnk+PM53TWNUbs+ISHt3/Exexksp15pOfn4HA5//MT/UGBZn9vWALwM5p8hiXwDK1sHFmJhbc9wS3BJfEzmqkcUprFLUYrLMkNTYHpL5KTl8/sVTt97p+1ageXElMLbfto+Ta6N6tOdHgIufkOBk2Zx7cFw+K63FqViJAAasWXAuCZT1bQ+5XPSc3MISTASrmSEXy4fBsvDehAcICVzFw7Gdl5BPpbeH3InaRm5fLKl2s8BRKOX6BN3VtYsPEAfQpWnd998hIdx3zI3lOetW36tq7DzFU7eG/ZFnLtDlbvPs689ft48bNVbDh4loiQAN4e0Y1+beox8cs1zFq1g0+e6EWbuhW93yS3qFmeKUM7e4fnfbFmj3coVFJ6tnfY4NIth2hVK576FWN4e9HGQufkpc+/5+j5a7wz8i5CAjwLSAIs2XyIf320nLcWecp1+/v5kZGTR2pmDmaTkYmDOhEZGkhWrp3DBaWOh3dpQvHQIHaeuMipy0mYTUYe7tLEOzxv+PRFNK1Wjg+XbeVaagY1y0Xz6pA7mb1qJ1aLmdmrdvLi/e15+qNv+XbbYSJDg4gOD2Hm6Huw5zsY9c5iTlxM5JMn7vYsOrtoI8/PWklWjp2Z33nKtsYUD8XPZKJL42q8tWgDTaqVwc9kZEC7Bjz14TIuXE/FZDDQuXEVthw5R7HgAKbMX0erWhV4bpant6NsiWJ8/MTd3uF5k+evIz46HKfbTc/mNb3nLiYylD631+GtRRu882xa1oqnWfVyXE/LYmTXZlj8zARYLUSHBzN95F1MGnQHy7YdplR4CBVLF2ffqQTs+Q4aVozhnpa1KBNVjAlzvuexGUuJDAnE32Lm9Xk/8q+C9Wl+0r1pdeJLRfDp97sIDfKnR/NajPt0FenZniIhBgNcTk7nyQ++oXerujSpVpalWw4z5M0FZBb08m0/doEFGz1DSF8Z2JHpSzbybJ/WhAb6k5qVy6h3FvNi/w4AfLVuH93GzuJKSgY2qx+NqpRh7d6TTB/ZHYvZRGpWLh+v3E7DyrE88cE3pGTksGrXMfafScDthu92HueLNbv5V+/WPDtzBXfcWoWlWw55ewwB3G4YPm0RZUuG07RaGT56ohdV4qLo1LAyESEBHLtwjUaVY5n91L1sP3Yem9WP+OgIlo4fiMvl4sSlRJLSsnj/0Z50aliFWat3kedwMOnBO3C63Lzy5RrCg234FcwZCQ3059k+rRk76ztiIkMJC7LRsHIsfW+vyxO9WlCuZDilI0MJ8rdwb6s65DucPHVPK+pXjOHhzk0wGQ18tW4fJpMJs9HA60M6YzIaOHbhurdHql39itQoF83V1EwC/C1sOHianrfVJCzQn5cHdqJTw8q8NuRO/P3M3Ne6Hos3HWDK0M5MH3EXlWOjcLvB4mfCZDR4z1Fs8TD8LWbWHThDyfBgnnhvKdkFvWovD+zoDT9jPl6OyWj0rsm28eAZ7nnpMy5cT8PqZ2JA+wZ88O1WXv1qLdNHdi/0/urQoJKnF+nTVew/k8Dpy0nk5juYtWonDqeLz3/YTWLBfBx/i5ket9XEZjEXlAv3FFX5aX3N1buPs+PYBR7s1IgFY+9nyrDOfLJyO3tOXsLthqkL1nNPy9p8sHyrt7rlTwt/T5izmsiQIDrfWpVVO4+z+eAZjE4jTcI9H8Y/PruGvlvf4lJOMlajma4xDQi1BBAa+Nulv3+vED8bLaOq+tzfNromgebfrpz337iam8a0YyvYnez5/ShmCWTl5b302zydbUknyXHYC+Yc3XhFFOxOBycyrrA98d+Ltbpw8/6J1aTk/X2Gh/kZzVQPjWNa/QcwG0ycz04kIScFi9HMOw0GUTW0NGbjnzPs8/9XgNlCMWuQt8CD2WgizBKosCQ3NAWmv8hPleR8uZKcQaB/4X9kielZvPjZaiYPvbPQ9jZ1bqFbsxqUDA/h5Qc6Uim2OOCZs2Q2GXl18J1MXbCei/8ngP3E5XITYDFTs3w0TaqWoXPjatSvGIvR4ClP+1OvyE+DNYd3acqxC9f5et2/h/kcu3CdiJAAnC43/hYz11IzmTJ/HelZuWw/doGdxy/yxvz1ZGTn8vLAjrSsFc/ADg1Jy87ljaGdqVGuJHe3qMX89Z7n3Hb0PCu2H8XlcrP1yDke7NSI95ZtweV2Uzk2irnP3kfl2Chvj1z56EgaVo4jyGaldytPyDtzxTOZuEGlWLo1rc7zs1ZSq0IpTEYD4cEBxPyftUPqVCiNzWIm2GbF32LmjWFdSEzN5OWBHQkN9Kd/m3pcS82kf7t6fLl2L6PeWYzRYOCRHs2Z9OUadhy/yGtfreHNh7vQsHIcoz/4hrcXb+STFduJKZg4XSm2OGlZucQWD6N8yXA6NazMkfPXuJSYRuXYKPq1rceU+T8SZLOy/dgFpi/ehMlkZNCUeZy9msLUBes5dO4qCUnpjJ+zmqVbDtGlcTWe+Xg54/q1o1b5Uozp05p5P+7l9cF3UrN8NBMHduKN+espHx3hLbQAnsVy5284wPCCkAqexUnNJiMTPl+N0WjAbDIyaVAnJg66gz0nLjH0rfmM6taMynFRTPpqDfM3HmDBxgMcPHeVTQfPsuvEJZIzsnjq7pZMmPM9CUlpPNP7dl6YXXhC79fr93PuagoDOzRg+bYjbD96noSk9II1aHryysBOmI1GTiYkcjIhkfH92wGeQBccYOW7nYXnZIz7bBVThnXhwOkEz/yLsCDG9GlDQlIaHRsU7pV8bfAdzPxuB7tPXio0sT4jO48ryRk0qBhLcICV6SPu4tG7bmNwp0aYTUba1K3I9EUbaVfvFmqVL8Wsgi882tevxDsj78LPbOLc1RRmfredctERhAXayM61k2N3cOTCNeZ8v5vxc1Yz4bPVtKlTET+TEaPRwJMfLCMk0J+GleMY//lqRr2zmKFvzmdwp0Ycu3Cdo+evEWD1Y/qI7oz5eAUnE5IwGgwYjQZ2n7hE9fLRfLh8Gx893ovn+7YlOSOb8XNWM3loZ8be15aY4mEYjQYaVIply+GzPNylCe3rV+LU5ST6ta2P2WTA3+JHhdIR1K8Y6z0fZqORx7s3p3y0pxzwS5+vZsY3W3C73bwzqjuvzVvLw28vpGKpSBaMvZ+osEB6Nq/FlPnryMt38Gyf1rwzqjvf7z5RaPHUE5cSPcUuBnRgzg+7eXlgR2IiQ3nhvrYs2XyICQ90IDo8hLH92uF0OrHnO+ld8MXNT17s356vftzLvlMJ3NemLrNWFV4nZsvhc1SMiaRsiWK8v2wrB89e5bEezXmyVwuWbz/iXWMLINfu4IVZK6kVX4rFmw+Sa3cQHR7MnH/1oWvjagAs2nQQh8NFaKCVIH8Lrp+NCjCbTCSnZ5OamYPBAC/c144pQztza0HvY2J6FhEhgUSHh9C4WlmGT1lM75K30TTSE5ry3Z5v+afWGcDMeXu4kpxR6Pn/f5iNJu6KbUio3y/XJIryD6V5VBUMPyXDP0lKXiZXc9M4m+UZOv1klc5MqdufqqExuHGzK/l0ofLRN5pz2dcZueMT8t1OygQWp2ecJ7AvubSTT8+s/1vNYbKYzJQKCCfY798BPNQvgJL+oZiN5iJsmcjfnwLTXyTQ30LtCqV97q9VvhTnr6UU2mY0GBh65618vHJ7oe0bD57h7JVkHE4XGdm53kpiAA6ni7NXkmlWvRxP3d2K52atJCM7jyB/C8EBVrJy7Tz90bc43W6G3nErd9xalbGzvuPVr9bQqHIcdzaq5l2w8iebD52lcdWyWH42KblEsSDvmkxmkwl7vpNTCUk4fvaPf+vR87ww+ztCA/15oH0DBk2eR0Z2HvtPX2Zgh4ZsOXyOcf3b8fQ9rQDPmiARoYEYDQYOn7vK5KGdaV6jPA91bszy7Ud49cE7uK1GOd56uBvr9p9k25HzXLieRqmIwmNOf1pzxelysev4RZLTc3hz4Qb2nvbMNfhpcvUj7y4hwGohJSObReMGMHfNHuat38/ctXv44LFeXEnJ4OFpC3G7oWRYEI/1aI7L5Wbxxv28+XBXqpctyRM9WxJs82fS3LUFH7xCeLhLE77ZeogZo7qTkJRObFQY6w+e5tXBd1AxJorJX/8IeAJMeHAAw7s0we5w4nS5aFW7At9uLTx88dvtR4gMDaROfCk6NKjExyu3c/ZqCvPX7+PF/u1wuly0rV+JkdMXcX/b+oQEWnny7hY88f43JKZl0btVbbo18XwQ/Oz7XYQE+nNPi1oAbD96nm+2HObxHs0Lionk88XaPZxMSOTg2StkZOexeNNBwoMDaFnLM3TpzOVkKpSOxGwy8NGKbYQHBxBos3LqchJP3dOKz1bv4lzBMLzn+rahapkSuNxunvpwGaGBNtYdOM35a6k83qM5Mx7pwexVO/h22xFeG3InY/u1IyYylNEfLiM6PJgH2jdgwpzVOF1uqsRF8dTdLTEYYP/py7y9aAP3tqpDRlYu7z3Sg0Ub9gMG9pwsPH9j08GzvNivHYM7NeLJghLoYUE2LH4mnp+1kpa14vnkyXvYe/ISadl5dL61KnP+1Yfk9Czuvb0O3ZrWYO2eEzzZqyV33lqVkV2bkpyexZsPdaVuhdLc364B05ds5rmZKzGbTAT6e0qtO1wu4qMjeKBDQ554fykrdhwjISmdUwmJTPpyDWFBNl598E4MBsjIycNiMpGYns07SzfTsWFlTEYDl1MyMBoMTBjQnmnDu7F0yyFKR4Ty/H1tyMzJ8/zeVonjs6f78NbC9SzcdICeL85m98lLfLBsK/GlIikWFIDJaGTn8QvsPH6Bz1bvIsDfj0UbD7KtYE0sAIfLxah3l+BvMZOWmcPFgvLSleNKcDU5gyvJ6VxMTOPIhWtMW7KRpz/6ljcXbuDEpUSmLd5IvtPJuaspfLP1MP4WM3P+1ZtxBcF314mLBNksPNKtGVeTM3jpgQ5MmPM9t1aOY/uRC7w6+A7eXryRI+evUzu+NBv2Fy6csnLnMbo1rc4TvZqz49gFvt/t+RvVqWFlbw/VUx9+yyuDOhEWZCMqzDPcs3RkKEs2e+Yn3d+2Hq8NvgOjwcChc1dZsvkgT93dis63VmXSg3ew6eBZet9eh76t6/DyAx35fs9xAiwWggP8ub9dA29bsnLtPDdrJaPvbsmE+zsQFxWGxWTkxfvb88rAjvRqXpNTCdeZ9GAnxn66yvN32p7LmaxrhV7T3pSzVCobyYNvfO3zy63/RilbMT659SHuLF0Xf5MfgSYrPeNu5YOGQ/4nQ8wsJj/S7Tk8V707L9boRfvoWrjdbgbFt+LRSnfQv1yLG3oh0nBLEM2jqnjnLA2r0I4hFdoQ6hdA55h6BPvZ/vOT3CASclIYseNjUuxZGDFgxMD1vHQe2TmrUCEIEfnjVPThL3T2ajL3vjQHu6PwOGI/s4kvx/Rl2sKNrPtZhbVR3Zpx9moyS7d4ytDe07IW6/ef4XJyOmWjivHqkDsZ+uZ87zC8EsWCOXEpEYMBJg7qiM1qZfT7nqIPbz3cjaxcO8/P9gSoqcO6sHDTAX7cdwq3GxpWiuXpe1sxYc733mF4LWvGs7agh6JuhdL0vr0Ooz9YBsAbw7ow5pPl5No9ixK+Pbwbj767hBf6tWX64k3e4S8ATaqWoVeLWox+fxlNqpVlWOfGnL+W4p2rVTk2iuSMbMICbeQ7HQT6W1m06SC316pAqYgQ0rJz2XsqgaiwIKqXKUF6dh4nExLZf/oysVFhvLnQMwwvLMhGaqYnxHVuXJW2dSoy6as1vDr4Dga/8TW5dgcjujalfsUYRn+wjOtpWfS5vQ49b6vJqcvJPPvJcuJLRTBhQAdcLjdD35qP2Whk+si7iAzxDOcb/eEyJgzoQEJSOuVLhjPg9bnc0agKHRtUYcr8dTzRswVut5srKRks3HiAe1vVJjk9m4ycPN5csAGHy0W1siVISEonJSOH4AArM0b14IXZK+napDonLl1nWUFgalylDDtPXCTf4aRcyXDef7QnvSZ8SlpWLrfERDK+f3sefONrnE4X4cE26lWM5Zuth7FZzLw7qgfTl2yiSlwUNcqVpGR4CAs2HOBaagYPtG9A6cgw1h84zWtfraVm+WjG3teW0R9+Q5/b67HhwGkqlI6kRc14dh2/SMnwYL7ffZxGleNwud2Uiggl157P97uPs2rXCW6tUoZRdzUjKT2LtKxc4qLCGPPxCp67rw0Z2XYqlApnzCcr6XFbDRxOJ5k5dqYv2UTXJtWIjQyjYeVYHn//Gz58rCfgCWHfbjuCwQDvPdqTrYfPseXwOYbd2ZhyJYtx7OJ1psxfx+QhnRk/ZxXhwYFEhQXRtUk1npu50jsMr26F0mw6dBaA0Xe3JDo8hCff/4aosCBevL8dfmYzI6YtxGgw8PqQO3G53fyw5yQPtG/A5eR0nvrwW57t05oa5aI5fTmJHcfO06RqWaKKBXPswjUWbNhPj9tq8cb8dVxLzcTldlO9bAme7dOG89dS+WjFNp7r24b3vtlCz+Y1eWPBel5+oAOJaVnYrBacLicGDAQHWElMz6ZM8TBOJCTy7MwVdG1cnSF3NOL89VRSM3KICAkgOiKUqykZnLiUyK2VPQsgH7uYSPHQQF6YvYJ/3duGlIxsLlxPY/bqHTzbuw3bj52nRFgQpy4neRapvuNWZn23g0e638bDby8EoEvjqtStEMOEzz3B9KfiDduPnSfIZmXp5oPUii9NrfLRXEnJZN+pS8zfcIDw4ABuq1HOG0ja1L2F/m3rsW7faVrWiqdSbBR5+fn8sOckVj8zVeNKsGrnMdrVr8S4z76jdZ1bcLncNKocxxdr92A0GOhze10em7GEi4meYXgtasZ71+5qXqM83ZpWx+5w8vyslfRvW4/ba1fA7YYR0xbSqEocfW+vS0ZOHiEB/gRY/QgOsLJs6xHSs3Pp37Y+Vj8z246eZ+nmQ4zp05qsXDvbjp5j+7ELJKZmcfjcVQa0b8CmQ2cY1789t5SOBDzr1n28Yjtf/GxphbAgG4/e1Ywm1cp5q8c5nE7MJhPpWbmkZeewetcJqlaJ5NWzC73D8CoGR3MgzVP44/7YlpTOKsltleOJCPlzQ0WuM5/0fM/Q2zBLIJb/YQ9DliMPu9OBv8mMzWzF4XKQnp+LxWgmyO/PGW74v5SUl4HD5fLOr0rPzybXmU+U/4013+q32J0O1l87zJh9c73D8BwuJyN3zsThdjKlbj+aRFbEdIMMyxO5UWjh2l9R1IHJ4XBy5MI1XvxsNacvJwGeUsBj+7WjSlwU19MyGfXOEu++ijHFGdmtKc98tJyBHRrSo3kN0rLyGDp1Ps2qlaVvm3qMmLaQ9OxcPnribgL9LTw/cyX7z1xm/P3tOXjmCrUrlMZm9aN8yWJ8uHwbbepWJDPHs3hs1bgSRIcHE2Sz4nS52H/mCuevpfD1+n08fU8rGlSMY++pS0z4/HvubVWbYkE2PlqxndG9WmK1mBn7s2FX3ZpWJ9hmYd+py3RsWJlXv1pb6LW3qh3PgHYN8DObeHvhBppVL0uN8qXwt/gx5/udJKZnERUaTNPqZcnOyyciJIAAqwWrn5nUzGwuJ2dQOS6KzYfOYrP6UTGmONdTs/h+93HW7T9Ns2plGdu/HZ99v5tPV++kXMlwpj7UhS9+2E2f1nU4dzWN05eTiI4Ipt4tMZy7msKP+05RO74Ut5SO5GpqJlazGT+zETAQGRpAUrqnx8VYMKQPYN/py1xNySAuKoyv1+1jUMdGrNh+lEGdGmLAAG43GTl5vLFgPb1b1SkY3uTm/DXPgqD1bomhT+s6+JlMjPlkBcEBViYPuZNhby3gzkZVKFMinPFzVtO7VW1qli9FWKA/o95dQpOqZRjdqyW7Tlzi7cUbeOvhbljMJt5btoUDZy4zfWR3Aq1+LN58iDk/7OK9R3oUrAnjxuly8/h7S5k6rAs5eQ78LWaS0rMItFm5lJhGSIA/JcICOXctldNXkli//wz/utfT67d613HOXk1meJdmOF0uNhw4zaaDZ/lX79tJz87l09W7eLhzE45fuk6VuCi+2XKY7s1qYLWYScvM5diFa9QoXxI/k5kN+09xW8140rJy2X3iIvM37Pe8Dj8TZpORtMwckjJyKB4WyKjpixnRtSkVY4pjMhpJTM9i54mLtKldAaPRM7Qt3+HkwSnzaFWnAn1a1cXqZ2Lilz+w9/RlZozqToliwcz5fjdfrt3D+PvbU7VsCc5eSaZMVDFCA23k2fNJzMjGnu+kbHQxsnM9w4beXrCeHs1rElUsGD+zkeupWRgMBvzMRsICbRy7eI3zV1OZtmQT5UuG8/rQzuw/fZkJc1YTEujPe4/0wGgAh9PNqcuJjJ29iuFdm9ChQWUuXEvlk5XbiS0eyp23VuW9ZVuIDA2iU0PPgo0lw4NJz84jyGZl/+kE6leMATfYHU6ycu0UC7LhBj5eud1TaMII+Q4XVj8z7yzZxLoDpxnYoQHNa5TnizV72Hn8Ii890IFtR8/TsUFlrqZkkO9wEhLoz+6Tlzh3JYV7WtYi1+4gMyePz3/YzfCuTTEZjaRm5uByu0nNymHzoXOkZGTRr2191u49xcaDZ5jxSA8SktI4dvE6M1duZ+qwrsSXisBq8cyDMxfMvcrKyQMDBPpbSU7PZuWOozSuVpZFG/cz54c9RIYG8PbD3QgJtHHhWgrf7TzGih1HmTbiLix+ZvadSuDNhet56u5WHDxzBT8/E/e3rc/SLYf44oc9zH76HgL8rdgKCo0YDQYsfp6htgBpWbm4XC7vGkk5efnk2PMJDw7A4XRy9Pw1xn66yjukt1RECC/c15Za5aOxWv49pyI9O5fEtCx2Hb+IyWSg7i0xRIYEEmTzPScoLSuHLHcuzx+cy/H0y0yvP4hS/uG8e3IlyxP2Mr7G3dQNKU/x4F8v2yzyR2Tm57L26kHiAotTLbQ0LjccSD1PYl4Gt0VVJuB/MH9N5O9OgelXFHVg+klSehbp2XngdhMS6F/om8XEtEwuJaVz8lIipSJCiY8OB4OniEFIwcTgK8kZ+JmNRIQEcqlgPZvy0eEYDAYuJaaRkJTGZ9/vYsvhc/RrW5/uTapRKjKM5IwsrqZmsvfkJRLTsqlXMYacvHxqlS9FsWAb19Myycqxk+90YTYZsTscOJwu/C1+OJwuriSnE1s8jMwcOxk5efhbzJxKSMLqZ6J8dAROl4uk9GwuXE+lRLFgPl29i9OXkygWbOPelrVpV7ciUxas44H2DSkRFsS+0wks3XIYs8lI71Z18LeYmfD5ahpWiqNSbBRV46LIdzjZcPAMt8QUp1R4CKGB/lxJziA4wIqf2fNB+4c9J2hatRyB/n4YjEY2HDhN46plSM3MwWj0rLnkdLg4fimRiJAAIkMCMRrh5KUkSoaHkJaVQ2RoIAFWC8kZ2QT6+/HNlsPUji9NZFgg9nwHVj8z2Xn5mIwGz3Vwe+aM+ZlN4IZTV5I4duE6KRnZ9Ghegzy7k0B/Cyt2HOWH3SeY9GAn8p0ujAYDpy8nERJoI8DqR2igP35mE9dSMogMDWTn8YuUKVGMkAB/8vIdhBQML/S3mHFjwGz0fBjce/Ii8aWLExJg9VT7u5pM5TIlycrJw2g0sn7/KZpVL8e0xRvp1bwmZUqEk5qVS5DNgj3fic3iR47dTqC/lbx8Bzl5+Ry/dJ2a5aIxGAzsOnGRGuWisfiZMRoMrN9/kmbVy+PGU77Wz2zC7XZjz3fixk2Qzcq5K8nElQjH6XQydeEGAq1+jOx2G263i2MXr1OmRDh2ez42fwv7Tl+mdnwprqVket57qZlEhAZis/px+OwVwkMCuZaSSdUyURgNBhwuNwfPXSYyOIgSxYKwO5zMWb2LLk2rk5iWSdkS4QTbrDhcLrLz7OTnO3G4XESEBJCVm4/B4KmG58aN2WgiJy8PFwbSM3PJzMkjOjKYAKuF97/ZSpt6FQE3lWKj+GLNblbtOs6L97enVHgIAVY/DAYDOXYHW4+co37FWLJycwm2WTlxKYlSESFcT8skyN9KeEgAOfZ8cENCUjphQTZMRiNWPxNJ6VlMnLuWzrdWoWWtCpiNRgL9LUQVC8JgMJCencvRc1eZsWwr2bl5VC8bzX1tPGW1z11NJiwoAKPBU5Vt/vr9HD1/jcd6NGf17uN8u+0IJYoFU7N8NH1a1fEWYsjOy+fD5dvYfuw8oQH+PNP7dqIjQpmxZBMhQf7c17puwTnyrPUWbLOy//RlPl65naspGVQtU4IRXZsSHR6Cw+UiOjwEu8NBcrqnFyM8JACL+T/3YvxUVv/bbUfwt5i5t2UdKsVEEh4SSFpWDnn5DjJz7N51ntIyczAYDazZc5KosCDKlCjGl2t2Ex4SSN/WdSkdGYrV7/+v9+Sn3lF3wd/k4qF/bnGCa7lppNiziA8qgdloIjkvk0s5ycQHldCHWPlTZTlysRrN3jlLdqcDh9up95mIDwpMv+JGCUz/a3n5DlIzc3C7ISTAU1r857Lz7OTm5eNwuQkPtmE2Fe6iz8qxk5mbh9FgIDzEM/8BICUjC4fTjdPlws9sIifPgZ/ZSIDVgp/ZSK7dgZ/RSHquHZfLhcvtxu12Y8SAzepHdp4df4unpLnBYMDlcpOYnoXBAIEWCwE2CwmJaThcLmxWPwIsfuQ7nTidbgxGAz9NVXY4XRgMYDQaCSmYl+VnNnlL8+bk2bH4mb3tzszJJTvP03vgKPg23uV2YTaZyMq1YzQaCAv0x2rxIzUjBzduTEYjOXYHZiP4mc3eb6d/TVpWDlm5dswmE/5+ZkIC/UnLzCE9KxeLnxmHyxNAQwP9MRogMT0bp9OFzeJHWLCNtKwc8h1uzAUlunPt+Z5y1/5migUFkp/vJDM3lxy7EwPugkBrIqwgQKdm5eByuQkNsBIcaMPhdHItNROH03OdIkMCPeHG4SzoMfNUVAoJ8i84n05SMnK8PQLgGSYaZLPidru5XjDczOF0ERJgxernR0Z2LnkOTyh0u93kO1zenri0rBxy8vKxWszeLwOy8+xk5doxYMBkNGAxG7E7XRgwEGSzgBtMJqM3LGTl2DEaDIQF2bBaPP/4c+355Nod2Cx+OJ0ukjKzMeLpuQgL/vc8g8ycPLLzPD/rp/eaw+kkPTvXc/0tZkIDbSSnZ+NwubCaTdj8LRiA62lZmAwGAqxmggNtJKZlkWvPx2bxI+L/LNppdzi8ASEvP5+sHDtOtxu3y+0tl24xm3C63aRkZJPvcBFks+Jyu7DnOwvedzb8rb4rQ6VkZGMvCObhP3sPpmbmkO9w4nC6cDg9575YkOd3OTUrG9wGwoL8MRqN3oALnoWzM3PyMBmNhIcEYDAYcLo8Qd5XMYCk9CwcBe/XkD+pmht43hNGg6cAxX+Slp0LbjehgTbv+yDA6uddlkBEROS/ocD0K26WwCQiIiIiIr9NC9eKiIiIiIj8f1JgEhERERER8UGBSURERERExAcFJhERERERER8UmERERERERHxQYBIREREREfFBgUlERERERMQHBSYREREREREfFJhERERERER8UGASERERERHxQYFJRERERETEBwUmERERERERHxSYREREREREfFBgEhERERER8UGBSURERERExAcFJhERERERER8UmERERERERHxQYBIREREREfFBgUlERERERMQHBSYREREREREfFJhERERERER8UGASERERERHxQYFJRERERETEBwUmERERERERHxSYREREREREfFBgEhERERER8UGBSURERERExAcFJhERERERER8UmERERERERHxQYBIREREREfFBgUlERERERMQHBSYREREREREfFJhERERERER8UGASERERERHxQYFJRERERETEBwUmERERERERHxSYREREREREfFBgEhERERER8UGBSURERERExAcFJhERERERER8UmERERERERHxQYBIREREREfFBgUlERERERMQHBSYREREREREfFJhERERERER8UGASERERERHxQYFJRERERETEBwUmERERERERHxSYREREREREfFBgEhERERER8UGBSURERERExAcFJhERERERER8UmERERERERHxQYBIREREREfFBgUlERERERMQHBSYREREREREfFJhERERERER8UGASERERERHxQYFJRERERETEBwUmERERERERHxSYREREREREfFBgEhERERER8UGBSURERERExAcFJhERERERER8UmERERERERHxQYBIREREREfFBgUlERERERMQHBSYREREREREfFJhERERERER8UGASERERERHxQYFJRERERETEBwUmERERERERHxSYREREREREfFBgEhERERER8UGBSURERERExIe/RWA6e/YsgwYNoly5cthsNuLj4xk7dix2u72omyYiIiIiIv9g5qJuwO9x9OhRXC4X77//PhUqVODgwYMMHjyYrKwsJk+eXNTNExERERGRfyiD2+12F3Uj/huvv/46M2bM4PTp0z6PycvLIy8vz3s/PT2d2NhY0tLSCAkJ+SuaKSIiIiIiN6D09HRCQ0P/Yzb4WwzJ+zVpaWmEh4f/5jETJ04kNDTUe4uNjf2LWiciIiIiIv8Ef8vAdOrUKaZNm8awYcN+87hnnnmGtLQ07+3ChQt/UQtFREREROSfoEgD07hx4zAYDL9527lzZ6HHJCQk0KFDB3r16sWDDz74m89vtVoJCQkpdBMREREREfm9inQOU2JiIomJib95TNmyZfH39wc8YalVq1Y0atSIWbNmYTT+sbz3e8cpioiIiIjIP9vvzQZFWiUvMjKSyMjI33XspUuXaNWqFfXq1WPmzJl/OCyJiIiIiIj8UX+LsuIJCQm0bNmSuLg4Jk+ezPXr1737SpYsWYQtExERERGRf7K/RWBatWoVJ0+e5OTJk8TExBTa9zetii4iIiIiIn8Df4txbQMGDMDtdv/qTURERERE5H/lbxGYREREREREioICk4iIiIiIiA8KTCIiIiIiIj4oMImIiIiIiPigwCQiIiIiIuKDApOIiIiIiIgPCkwiIiIiIiI+KDCJiIiIiIj4oMAkIiIiIiLigwKTiIiIiIiIDwpMIiIiIiIiPigwiYiIiIiI+KDAJCIiIiIi4oMCk4iIiIiIiA8KTCIiIiIiIj4oMImIiIiIiPigwCQiIiIiIuKDApOIiIiIiIgPCkwiIiIiIiI+KDCJiIiIiIj4oMAkIiIiIiLigwKTiIiIiIiIDwpMIiIiIiIiPigwiYiIiIiI+KDAJCIiIiIi4oMCk4iIiIiIiA8KTCIiIiIiIj4oMImIiIiIiPigwCQiIiIiIuKDApOIiIiIiIgPCkwiIiIiIiI+KDCJiIiIiIj4oMAkIiIiIiLigwKTiIiIiIiIDwpMIiIiIiIiPigwiYiIiIiI+KDAJCIiIiIi4oMCk4iIiIiIiA8KTCIiIiIiIj4oMImIiIiIiPigwCQiIiIiIuKDApOIiIiIiIgPCkwiIiIiIiI+KDCJiIiIiIj4oMAkIiIiIiLigwKTiIiIiIiIDwpMIiIiIiIiPigwiYiIiIiI+KDAJCIiIiIi4oMCk4iIiIiIiA8KTCIiIiIiIj4oMImIiIiIiPigwCQiIiIiIuKDApOIiIiIiIgPCkwiIiIiIiI+KDCJiIiIiIj4oMAkIiIiIiLigwKTiIiIiIiIDwpMIiIiIiIiPigwiYiIiIiI+KDAJCIiIiIi4oMCk4iIiIiIiA8KTCIiIiIiIj4oMImIiIiIiPigwCQiIiIiIuKDApOIiIiIiIgPCkwiIiIiIiI+KDCJiIiIiIj4oMAkIiIiIiLigwKTiIiIiIiIDwpMIiIiIiIiPigwiYiIiIiI+KDAJCIiIiIi4oMCk4iIiIiIiA8KTCIiIiIiIj4oMImIiIiIiPigwCQiIiIiIuKDApOIiIiIiIgPCkwiIiIiIiI+KDCJiIiIiIj4oMAkIiIiIiLigwKTiIiIiIiIDwpMIiIiIiIiPigwiYiIiIiI+KDAJCIiIiIi4oMCk4iIiIiIiA8KTCIiIiIiIj4oMImIiIiIiPigwCQiIiIiIuLD3yYwdenShbi4OPz9/YmOjqZfv34kJCQUdbNEREREROQf7G8TmFq1asW8efM4duwYCxYs4NSpU/Ts2bOomyUiIiIiIv9gBrfb7S7qRvw3li5dSrdu3cjLy8PPz+93PSY9PZ3Q0FDS0tIICQn5H7dQRERERERuVL83G5j/wjb9aZKTk/n8889p0qTJb4alvLw88vLyvPfT09P/iuaJiIiIiMg/xN9mSB7A008/TWBgIBEREZw/f54lS5b85vETJ04kNDTUe4uNjf2LWioiIiIiIv8ERRqYxo0bh8Fg+M3bzp07vcePHj2aPXv2sGrVKkwmE/379+e3RhQ+88wzpKWleW8XLlz4K16WiIiIiIj8QxTpHKbExEQSExN/85iyZcvi7+//i+0XL14kNjaWzZs307hx49/18zSHSURERERE4G8yhykyMpLIyMj/6rE/5byfz1ESERERERH5M/0tij5s376d7du306xZM4oVK8bp06d54YUXiI+P/929SyIiIiIiIn/U36Log81mY+HChbRu3ZpKlSoxcOBAqlevzrp167BarUXdPBERERER+Yf6W/Qw1ahRgzVr1hR1M0RERERE5CbztwhMf5af5j1pPSYRERERkZvbT5ngP9XAu6kCU0ZGBoDWYxIREREREcCTEUJDQ33uL9Ky4n81l8tFQkICwcHBGAyGQvvS09OJjY3lwoULKjl+g9A1ufHomtx4dE1uLLoeNx5dkxuPrsmN52a9Jm63m4yMDEqVKoXR6Lu0w03Vw2Q0GomJifnNY0JCQm6qN8rfga7JjUfX5Maja3Jj0fW48eia3Hh0TW48N+M1+a2epZ/8LarkiYiIiIiIFAUFJhERERERER8UmApYrVbGjh2rdZ1uILomNx5dkxuPrsmNRdfjxqNrcuPRNbnx6Jr8tpuq6IOIiIiIiMgfoR4mERERERERHxSYREREREREfFBgEhERERER8UGBSURERERExAcFpl/RpUsX4uLi8Pf3Jzo6mn79+pGQkFDUzbppnT17lkGDBlGuXDlsNhvx8fGMHTsWu91e1E27qb388ss0adKEgIAAwsLCiro5N6V3332XcuXK4e/vT7169diwYUNRN+mmtn79ejp37kypUqUwGAwsXry4qJt0U5s4cSINGjQgODiYqKgounXrxrFjx4q6WTe1GTNmULNmTe/iqI0bN2bFihVF3SwpMHHiRAwGA48++mhRN+WGo8D0K1q1asW8efM4duwYCxYs4NSpU/Ts2bOom3XTOnr0KC6Xi/fff59Dhw4xdepU3nvvPcaMGVPUTbup2e12evXqxUMPPVTUTbkpffXVVzz66KM8++yz7Nmzh9tuu42OHTty/vz5om7aTSsrK4tatWoxffr0om6KAOvWrWP48OFs3bqV1atX43A4aNeuHVlZWUXdtJtWTEwMkyZNYufOnezcuZPbb7+drl27cujQoaJu2k1vx44dfPDBB9SsWbOom3JDUlnx32Hp0qV069aNvLw8/Pz8iro5Arz++uvMmDGD06dPF3VTbnqzZs3i0UcfJTU1taibclNp1KgRdevWZcaMGd5tVapUoVu3bkycOLEIWyYABoOBRYsW0a1bt6JuihS4fv06UVFRrFu3jubNmxd1c6RAeHg4r7/+OoMGDSrqpty0MjMzqVu3Lu+++y4vvfQStWvX5s033yzqZt1Q1MP0HyQnJ/P555/TpEkThaUbSFpaGuHh4UXdDJEiYbfb2bVrF+3atSu0vV27dmzevLmIWiVyY0tLSwPQ/44bhNPpZO7cuWRlZdG4ceOibs5Nbfjw4dxxxx20adOmqJtyw1Jg8uHpp58mMDCQiIgIzp8/z5IlS4q6SVLg1KlTTJs2jWHDhhV1U0SKRGJiIk6nkxIlShTaXqJECa5cuVJErRK5cbndbh5//HGaNWtG9erVi7o5N7UDBw4QFBSE1Wpl2LBhLFq0iKpVqxZ1s25ac+fOZffu3RqZ8B/cNIFp3LhxGAyG37zt3LnTe/zo0aPZs2cPq1atwmQy0b9/fzR68c/1R68JQEJCAh06dKBXr148+OCDRdTyf67/5ppI0TEYDIXuu93uX2wTERgxYgT79+/nyy+/LOqm3PQqVarE3r172bp1Kw899BD3338/hw8fLupm3ZQuXLjAI488wpw5c/D39y/q5tzQbpo5TImJiSQmJv7mMWXLlv3VN8zFixeJjY1l8+bN6jb+E/3Ra5KQkECrVq1o1KgRs2bNwmi8afL+X+a/+T3RHKa/nt1uJyAggK+//pq77rrLu/2RRx5h7969rFu3rghbJ6A5TDeSkSNHsnjxYtavX0+5cuWKujnyf7Rp04b4+Hjef//9om7KTWfx4sXcddddmEwm7zan04nBYMBoNJKXl1do383MXNQN+KtERkYSGRn5Xz32p0yZl5f3ZzbppvdHrsmlS5do1aoV9erVY+bMmQpL/yP/P78n8texWCzUq1eP1atXFwpMq1evpmvXrkXYMpEbh9vtZuTIkSxatIgff/xRYekG5Xa79fmqiLRu3ZoDBw4U2vbAAw9QuXJlnn76aYWln7lpAtPvtX37drZv306zZs0oVqwYp0+f5oUXXiA+Pl69S0UkISGBli1bEhcXx+TJk7l+/bp3X8mSJYuwZTe38+fPk5yczPnz53E6nezduxeAChUqEBQUVLSNuwk8/vjj9OvXj/r169O4cWM++OADzp8/r7l9RSgzM5OTJ0967585c4a9e/cSHh5OXFxcEbbs5jR8+HC++OILlixZQnBwsHd+X2hoKDabrYhbd3MaM2YMHTt2JDY2loyMDObOncuPP/7IypUri7ppN6Xg4OBfzOn7af6+5voVpsD0f9hsNhYuXMjYsWPJysoiOjqaDh06MHfuXKxWa1E376a0atUqTp48ycmTJ4mJiSm07yYZUXpDeuGFF5g9e7b3fp06dQBYu3YtLVu2LKJW3TzuuecekpKSGD9+PJcvX6Z69eosX76cMmXKFHXTblo7d+6kVatW3vuPP/44APfffz+zZs0qolbdvH4quf9//x7NnDmTAQMG/PUNEq5evUq/fv24fPkyoaGh1KxZk5UrV9K2bduibprIb7pp5jCJiIiIiIj8UZoIIiIiIiIi4oMCk4iIiIiIiA8KTCIiIiIiIj4oMImIiIiIiPigwCQiIiIiIuKDApOIiIiIiIgPCkwiIiIiIiI+KDCJiIiIiIj4oMAkIiI3lB9//BGDwUBqaioAs2bNIiws7H/6M8uWLcubb755wz2XiIgUPQUmEZF/qAEDBmAwGJg0aVKh7YsXL8ZgMBRRq/64e+65h+PHjxdpG8aNG4fBYMBgMGA2m4mMjKR58+a8+eab5OXlFTp2x44dDBky5Hc9r8KViMiNT4FJROQfzN/fn1dffZWUlJQ/9Xntdvuf+ny/xWazERUV9Zf9PF+qVavG5cuXOX/+PGvXrqVXr15MnDiRJk2akJGR4T2uePHiBAQEFGFLRUTkz6TAJCLyD9amTRtKlizJxIkTf/O4BQsWUK1aNaxWK2XLlmXKlCmF9pctW5aXXnqJAQMGEBoayuDBg71D5ZYtW0alSpUICAigZ8+eZGVlMXv2bMqWLUuxYsUYOXIkTqfT+1xz5syhfv36BAcHU7JkSfr06cO1a9d8tu3/Dsnbt28frVq1Ijg4mJCQEOrVq8fOnTu9+zdv3kzz5s2x2WzExsYyatQosrKyvPuvXbtG586dsdlslCtXjs8///x3nUuz2UzJkiUpVaoUNWrUYOTIkaxbt46DBw/y6quvFjpXP+81GjduHHFxcVitVkqVKsWoUaMAaNmyJefOneOxxx7z9l4BJCUl0bt3b2JiYggICKBGjRp8+eWXhdrSsmVLRo0axVNPPUV4eDglS5Zk3LhxhY5JTU1lyJAhlChRAn9/f6pXr86yZct+93kSEREPBSYRkX8wk8nEK6+8wrRp07h48eKvHrNr1y7uvvtu7r33Xg4cOMC4ceN4/vnnmTVrVqHjXn/9dapXr86uXbt4/vnnAcjOzubtt99m7ty5rFy5kh9//JHu3buzfPlyli9fzmeffcYHH3zA/Pnzvc9jt9uZMGEC+/btY/HixZw5c4YBAwb87tfUt29fYmJi2LFjB7t27eJf//oXfn5+ABw4cID27dvTvXt39u/fz1dffcXGjRsZMWKE9/EDBgzg7NmzrFmzhvnz5/Puu+/+ZmD7LZUrV6Zjx44sXLjwV/fPnz+fqVOn8v7773PixAkWL15MjRo1AFi4cCExMTGMHz+ey5cvc/nyZQByc3OpV68ey5Yt4+DBgwwZMoR+/fqxbdu2Qs89e/ZsAgMD2bZtG6+99hrjx49n9erVALhcLjp27MjmzZuZM2cOhw8fZtKkSZhMpt99nkREpIBbRET+ke6//353165d3W63233rrbe6Bw4c6Ha73e5Fixa5f/7nv0+fPu62bdsWeuzo0aPdVatW9d4vU6aMu1u3boWOmTlzphtwnzx50rtt6NCh7oCAAHdGRoZ3W/v27d1Dhw712c7t27e7Ae9j1q5d6wbcKSkp3p8TGhrqPT44ONg9a9asX32ufv36uYcMGVJo24YNG9xGo9Gdk5PjPnbsmBtwb9261bv/yJEjbsA9depUn20cO3asu1atWr+67+mnn3bbbDbv/TJlynifa8qUKe6KFSu67Xb7rz7258f+lk6dOrmfeOIJ7/0WLVq4mzVrVuiYBg0auJ9++mm32+12f/fdd26j0eg+duzYrz7ffzpPIiLyb+phEhG5Cbz66qvMnj2bw4cP/2LfkSNHaNq0aaFtTZs25cSJE4WG0tWvX/8Xjw0ICCA+Pt57v0SJEpQtW5agoKBC237eg7Nnzx66du1KmTJlCA4OpmXLlgCcP3/+d72Wxx9/nAcffJA2bdowadIkTp065d23a9cuZs2aRVBQkPfWvn17XC4XZ86c4ciRI5jN5kKvpXLlyv9fVfjcbrfPIhq9evUiJyeH8uXLM3jwYBYtWoTD4fjN53M6nbz88svUrFmTiIgIgoKCWLVq1S/OT82aNQvdj46O9p7nvXv3EhMTQ8WKFX/1Z/yn8yQiIv+mwCQichNo3rw57du3Z8yYMb/Y92sf+N1u9y+OCwwM/MW2n4bC/cRgMPzqNpfLBUBWVhbt2rUjKCiIOXPmsGPHDhYtWgT8/kIS48aN49ChQ9xxxx2sWbOGqlWrep/D5XIxdOhQ9u7d673t27ePEydOEB8f731df2aVwCNHjlCuXLlf3RcbG8uxY8d45513sNlsPPzwwzRv3pz8/HyfzzdlyhSmTp3KU089xZo1a9i7dy/t27f/xfn5rfNss9l+s83/6TyJiMi/mYu6ASIi8teYNGkStWvX/kWvQ9WqVdm4cWOhbZs3b6ZixYreOS9/lqNHj5KYmMikSZOIjY0FKFSw4feqWLEiFStW5LHHHqN3797MnDmTu+66i7p163Lo0CEqVKjwq4+rUqUKDoeDnTt30rBhQwCOHTvmXfPpv3k9K1eu5JlnnvF5jM1mo0uXLnTp0oXhw4dTuXJlDhw4QN26dbFYLIV68QA2bNhA165due+++wBPuDlx4gRVqlT53e2qWbMmFy9e5Pjx47/ay/SfzpOIiPybephERG4SNWrUoG/fvkybNq3Q9ieeeIIffviBCRMmcPz4cWbPns306dN58skn//Q2xMXFYbFYmDZtGqdPn2bp0qVMmDDhdz8+JyeHESNG8OOPP3Lu3Dk2bdrEjh07vGHi6aefZsuWLQwfPpy9e/dy4sQJli5dysiRIwGoVKkSHTp0YPDgwWzbto1du3bx4IMP/sceGQCHw8GVK1dISEjgwIEDTJs2jRYtWlC7dm1Gjx79q4+ZNWsWH3/8MQcPHuT06dN89tln2Gw2ypQpA3gq6q1fv55Lly6RmJgIQIUKFVi9ejWbN2/myJEjDB06lCtXrvzucwTQokULmjdvTo8ePVi9ejVnzpxhxYoVrFy58nedJxER+TcFJhGRm8iECRN+Mdyubt26zJs3j7lz51K9enVeeOEFxo8f/4cq1/1exYsXZ9asWXz99ddUrVqVSZMmMXny5N/9eJPJRFJSEv3796dixYrcfffddOzYkRdffBHw9KysW7eOEydOcNttt1GnTh2ef/55oqOjvc8xc+ZMYmNjadGiBd27d2fIkCG/a52nQ4cOER0dTVxcHC1btmTevHk888wzbNiwodCcrZ8LCwvjww8/pGnTptSsWZMffviBb775hoiICADGjx/P2bNniY+Pp3jx4gA8//zz1K1bl/bt29OyZUtKlixJt27dfvc5+smCBQto0KABvXv3pmrVqjz11FPe3qzfc55ERMTD4P61geoiIiIiIiKiHiYRERERERFfFJhERERERER8UGASERERERHxQYFJRERERETEBwUmERERERERHxSYREREREREfFBgEhERERER8UGBSURERERExAcFJhERERERER8UmERERERERHxQYBIREREREfHh/wHgMblqFII5QwAAAABJRU5ErkJggg==",
+ "text/plain": [
+ "<Figure size 1000x1000 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Known Correct/Total (Accuracy%) 540/1000 (54.0000%)\n",
+ "Novel Correct/Total (Accuracy%) 3250/4000 (81.2500%)\n"
+ ]
+ }
+ ],
+ "source": [
+ "df = master_df.copy()\n",
+ "# compute distances for all samples in df\n",
+ "\n",
+ "\n",
+ "def get_dist_to_nearest(row):\n",
+ " features = row[feat_cols].values\n",
+ " distances = dist(features.reshape(1, -1), exemplar_means[feat_cols].values)\n",
+ " return np.min(distances), np.argmin(distances)\n",
+ "\n",
+ "\n",
+ "df[\"nearest_dist\"], df[\"nearest_label\"] = zip(*df.apply(get_dist_to_nearest, axis=1))\n",
+ "\n",
+ "# normalise the distances using z score\n",
+ "mean = df[\"nearest_dist\"].mean()\n",
+ "std = df[\"nearest_dist\"].std()\n",
+ "df[\"norm_nearest_dist\"] = (df[\"nearest_dist\"] - mean) / std\n",
+ "\n",
+ "# normalise the entropies using z score\n",
+ "mean = df[\"entropy\"].mean()\n",
+ "std = df[\"entropy\"].std()\n",
+ "df[\"norm_entropy\"] = (df[\"entropy\"] - mean) / std\n",
+ "\n",
+ "# normalise the energies using z score\n",
+ "mean = df[\"energy\"].mean()\n",
+ "std = df[\"energy\"].std()\n",
+ "df[\"norm_energy\"] = (df[\"energy\"] - mean) / std\n",
+ "\n",
+ "# 2 Componeent GMM using distnaces and entropyies\n",
+ "gmm = GaussianMixture(\n",
+ " n_components=2,\n",
+ " random_state=8008135,\n",
+ " max_iter=10000,\n",
+ " init_params=\"k-means++\",\n",
+ " tol=1e-4,\n",
+ ")\n",
+ "\n",
+ "df[\"cluster\"] = gmm.fit_predict(df[[\"norm_nearest_dist\", \"norm_entropy\"]].values)\n",
+ "\n",
+ "# plot the clusters, using a differnt marker for novel and known truetypes\n",
+ "\n",
+ "plt.figure(figsize=(10, 10))\n",
+ "sns.scatterplot(\n",
+ " data=df,\n",
+ " x=\"nearest_dist\",\n",
+ " y=\"entropy\",\n",
+ " hue=\"cluster\",\n",
+ " style=\"true_type_label\",\n",
+ " palette=\"viridis\",\n",
+ ")\n",
+ "plt.title(\"Scatter Plot of Distance and Entropy\")\n",
+ "plt.xlabel(\"Distance\")\n",
+ "plt.ylabel(\"Entropy\")\n",
+ "plt.axis(\"equal\")\n",
+ "plt.show()\n",
+ "\n",
+ "plt.figure(figsize=(10, 10))\n",
+ "sns.scatterplot(\n",
+ " data=df,\n",
+ " x=\"norm_nearest_dist\",\n",
+ " y=\"norm_entropy\",\n",
+ " hue=\"cluster\",\n",
+ " style=\"true_type_label\",\n",
+ " palette=\"viridis\",\n",
+ ")\n",
+ "plt.title(\"Scatter Plot of Normalised Distance and Entropy\")\n",
+ "plt.xlabel(\"Normalised Distance\")\n",
+ "plt.ylabel(\"Normalised Entropy\")\n",
+ "plt.axis(\"equal\")\n",
+ "plt.show()\n",
+ "\n",
+ "novel = df[df[\"true_type\"] == 1]\n",
+ "known = df[df[\"true_type\"] == 0]\n",
+ "\n",
+ "print(\n",
+ " f\"Known Correct/Total (Accuracy%) {known[known['cluster'] == 0].shape[0]}/{known.shape[0]} ({ 100 * (known[known['cluster'] == 0].shape[0]/known.shape[0]):.4f}%)\"\n",
+ ")\n",
+ "print(\n",
+ " f\"Novel Correct/Total (Accuracy%) {novel[novel['cluster'] == 1].shape[0]}/{novel.shape[0]} ({ 100 * (novel[novel['cluster'] == 1].shape[0]/novel.shape[0]):.4f}%)\"\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Extracting High Confidence Novel Samples"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# get results of the 2-component gmm for entropy only\n",
+ "df = master_df.copy()\n",
+ "entropy_gmm = GaussianMixture(\n",
+ " n_components=2,\n",
+ " random_state=8008135,\n",
+ " max_iter=1000,\n",
+ " init_params=\"k-means++\",\n",
+ " tol=1e-4,\n",
+ ")\n",
+ "df[\"entropy_cluster\"] = entropy_gmm.fit_predict(df[\"entropy\"].values.reshape(-1, 1))\n",
+ "soft_clusters = entropy_gmm.predict_proba(df[\"entropy\"].values.reshape(-1, 1))\n",
+ "\n",
+ "mean_0 = df[df[\"entropy_cluster\"] == 0][\"entropy\"].mean()\n",
+ "mean_1 = df[df[\"entropy_cluster\"] == 1][\"entropy\"].mean()\n",
+ "\n",
+ "if mean_0 > mean_1:\n",
+ " df[\"entropy_cluster\"] = 1 - df[\"entropy_cluster\"]\n",
+ " soft_clusters = soft_clusters[:, [1, 0]]\n",
+ " print(\"Swapped Ent Clusters\")\n",
+ "\n",
+ "df[\"entropy_clusterprob_0\"] = soft_clusters[:, 0]\n",
+ "df[\"entropy_clusterprob_1\"] = soft_clusters[:, 1]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 1000x600 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# show the kde plot of cluster 0 confidence for entropy by true type\n",
+ "plt.figure(figsize=(10, 6))\n",
+ "sns.kdeplot(\n",
+ " data=df[df[\"true_type\"] == 0][\"entropy_clusterprob_0\"], fill=True, label=\"Known\"\n",
+ ")\n",
+ "sns.kdeplot(\n",
+ " data=df[df[\"true_type\"] == 1][\"entropy_clusterprob_0\"], fill=True, label=\"Novel\"\n",
+ ")\n",
+ "# plot a kde line for each novel label\n",
+ "for i in range(50, 100):\n",
+ " sns.kdeplot(\n",
+ " data=df[df[\"label\"] == i][\"entropy_clusterprob_0\"],\n",
+ " fill=False,\n",
+ " label=f\"Novel {i}: {label_mapping[i]}\",\n",
+ " )\n",
+ "plt.title(\"KDE Plot of Entropy Cluster 0 Confidence by True Type\")\n",
+ "plt.xlim(0, 1)\n",
+ "plt.ylim(0, 10)\n",
+ "# line at 0.5\n",
+ "plt.axvline(x=0.5, color=\"r\", linestyle=\"--\")\n",
+ "\n",
+ "plt.xlabel(\"Entropy Cluster 0 Confidence\")\n",
+ "plt.ylabel(\"Density\")\n",
+ "plt.legend()\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## The Hao Methodâ„¢ï¸\n",
+ "The session dataset is used in its entireity to train a 10-output classifier, after psuedo-labelling with 10-class k-means. This classifier is then used to classify the new data, retrieving entropy. A sample is labelled \"known\" if the old classifier is more confident than the new classifier. Vice-versa for novel sample labelling."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Raw Logits Test Pipeline"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 156,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "a18ca09069df49b1908aa9aca1fdfe7c",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "Num Epochs: 0%| | 0/20 [00:00<?, ?it/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "e2f7cf33550c4015a65c8602698a1e20",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "Repeating Experiment: 0%| | 0/10 [00:00<?, ?it/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
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+ "1 Epochs - Repeat 1/10 - Known Acc: 1.0000 - Novel Acc: 0.0003\n",
+ "1 Epochs - Repeat 2/10 - Known Acc: 0.9990 - Novel Acc: 0.0000\n",
+ "1 Epochs - Repeat 3/10 - Known Acc: 0.9990 - Novel Acc: 0.0008\n",
+ "1 Epochs - Repeat 4/10 - Known Acc: 1.0000 - Novel Acc: 0.0000\n",
+ "1 Epochs - Repeat 5/10 - Known Acc: 0.9990 - Novel Acc: 0.0013\n",
+ "1 Epochs - Repeat 6/10 - Known Acc: 1.0000 - Novel Acc: 0.0000\n",
+ "1 Epochs - Repeat 7/10 - Known Acc: 0.9990 - Novel Acc: 0.0008\n",
+ "1 Epochs - Repeat 8/10 - Known Acc: 1.0000 - Novel Acc: 0.0013\n",
+ "1 Epochs - Repeat 9/10 - Known Acc: 0.9990 - Novel Acc: 0.0005\n",
+ "1 Epochs - Repeat 10/10 - Known Acc: 1.0000 - Novel Acc: 0.0003\n"
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+ "2 Epochs - Repeat 1/10 - Known Acc: 1.0000 - Novel Acc: 0.0000\n",
+ "2 Epochs - Repeat 2/10 - Known Acc: 1.0000 - Novel Acc: 0.0003\n",
+ "2 Epochs - Repeat 3/10 - Known Acc: 0.9990 - Novel Acc: 0.0018\n",
+ "2 Epochs - Repeat 4/10 - Known Acc: 0.9960 - Novel Acc: 0.0030\n",
+ "2 Epochs - Repeat 5/10 - Known Acc: 0.9990 - Novel Acc: 0.0005\n",
+ "2 Epochs - Repeat 6/10 - Known Acc: 1.0000 - Novel Acc: 0.0005\n",
+ "2 Epochs - Repeat 7/10 - Known Acc: 1.0000 - Novel Acc: 0.0000\n",
+ "2 Epochs - Repeat 8/10 - Known Acc: 0.9990 - Novel Acc: 0.0003\n",
+ "2 Epochs - Repeat 9/10 - Known Acc: 1.0000 - Novel Acc: 0.0003\n",
+ "2 Epochs - Repeat 10/10 - Known Acc: 1.0000 - Novel Acc: 0.0000\n"
+ ]
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+ "Repeating Experiment: 0%| | 0/10 [00:00<?, ?it/s]"
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+ "3 Epochs - Repeat 1/10 - Known Acc: 0.9980 - Novel Acc: 0.0020\n",
+ "3 Epochs - Repeat 2/10 - Known Acc: 0.9950 - Novel Acc: 0.0018\n",
+ "3 Epochs - Repeat 3/10 - Known Acc: 0.9970 - Novel Acc: 0.0043\n",
+ "3 Epochs - Repeat 4/10 - Known Acc: 0.9970 - Novel Acc: 0.0027\n",
+ "3 Epochs - Repeat 5/10 - Known Acc: 1.0000 - Novel Acc: 0.0005\n",
+ "3 Epochs - Repeat 6/10 - Known Acc: 0.9980 - Novel Acc: 0.0020\n",
+ "3 Epochs - Repeat 7/10 - Known Acc: 1.0000 - Novel Acc: 0.0013\n",
+ "3 Epochs - Repeat 8/10 - Known Acc: 0.9990 - Novel Acc: 0.0025\n",
+ "3 Epochs - Repeat 9/10 - Known Acc: 1.0000 - Novel Acc: 0.0010\n",
+ "3 Epochs - Repeat 10/10 - Known Acc: 0.9970 - Novel Acc: 0.0055\n"
+ ]
+ },
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+ "text": [
+ "4 Epochs - Repeat 1/10 - Known Acc: 0.9670 - Novel Acc: 0.0343\n",
+ "4 Epochs - Repeat 2/10 - Known Acc: 0.9930 - Novel Acc: 0.0080\n",
+ "4 Epochs - Repeat 3/10 - Known Acc: 0.9890 - Novel Acc: 0.0215\n",
+ "4 Epochs - Repeat 4/10 - Known Acc: 0.9940 - Novel Acc: 0.0030\n",
+ "4 Epochs - Repeat 5/10 - Known Acc: 0.9940 - Novel Acc: 0.0022\n",
+ "4 Epochs - Repeat 6/10 - Known Acc: 0.9910 - Novel Acc: 0.0105\n",
+ "4 Epochs - Repeat 7/10 - Known Acc: 1.0000 - Novel Acc: 0.0003\n",
+ "4 Epochs - Repeat 8/10 - Known Acc: 0.9690 - Novel Acc: 0.0260\n",
+ "4 Epochs - Repeat 9/10 - Known Acc: 0.9850 - Novel Acc: 0.0152\n",
+ "4 Epochs - Repeat 10/10 - Known Acc: 0.9980 - Novel Acc: 0.0045\n"
+ ]
+ },
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+ "Repeating Experiment: 0%| | 0/10 [00:00<?, ?it/s]"
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+ "text": [
+ "5 Epochs - Repeat 1/10 - Known Acc: 0.9830 - Novel Acc: 0.0205\n",
+ "5 Epochs - Repeat 2/10 - Known Acc: 0.9840 - Novel Acc: 0.0127\n",
+ "5 Epochs - Repeat 3/10 - Known Acc: 0.9660 - Novel Acc: 0.0320\n",
+ "5 Epochs - Repeat 4/10 - Known Acc: 0.9570 - Novel Acc: 0.0255\n",
+ "5 Epochs - Repeat 5/10 - Known Acc: 0.9690 - Novel Acc: 0.0420\n",
+ "5 Epochs - Repeat 6/10 - Known Acc: 0.9670 - Novel Acc: 0.0297\n",
+ "5 Epochs - Repeat 7/10 - Known Acc: 0.9880 - Novel Acc: 0.0132\n",
+ "5 Epochs - Repeat 8/10 - Known Acc: 0.9760 - Novel Acc: 0.0190\n",
+ "5 Epochs - Repeat 9/10 - Known Acc: 0.9940 - Novel Acc: 0.0095\n",
+ "5 Epochs - Repeat 10/10 - Known Acc: 0.9720 - Novel Acc: 0.0377\n"
+ ]
+ },
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+ "Repeating Experiment: 0%| | 0/10 [00:00<?, ?it/s]"
+ ]
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+ "text": [
+ "6 Epochs - Repeat 1/10 - Known Acc: 0.9810 - Novel Acc: 0.0307\n",
+ "6 Epochs - Repeat 2/10 - Known Acc: 0.9530 - Novel Acc: 0.0570\n",
+ "6 Epochs - Repeat 3/10 - Known Acc: 0.9760 - Novel Acc: 0.0328\n",
+ "6 Epochs - Repeat 4/10 - Known Acc: 0.9380 - Novel Acc: 0.0685\n",
+ "6 Epochs - Repeat 5/10 - Known Acc: 0.8920 - Novel Acc: 0.1015\n",
+ "6 Epochs - Repeat 6/10 - Known Acc: 0.9610 - Novel Acc: 0.0297\n",
+ "6 Epochs - Repeat 7/10 - Known Acc: 0.9300 - Novel Acc: 0.0730\n",
+ "6 Epochs - Repeat 8/10 - Known Acc: 0.8300 - Novel Acc: 0.1797\n",
+ "6 Epochs - Repeat 9/10 - Known Acc: 0.9560 - Novel Acc: 0.0455\n",
+ "6 Epochs - Repeat 10/10 - Known Acc: 0.9110 - Novel Acc: 0.0975\n"
+ ]
+ },
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+ "Repeating Experiment: 0%| | 0/10 [00:00<?, ?it/s]"
+ ]
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+ "text": [
+ "7 Epochs - Repeat 1/10 - Known Acc: 0.9300 - Novel Acc: 0.0685\n",
+ "7 Epochs - Repeat 2/10 - Known Acc: 0.8100 - Novel Acc: 0.1857\n",
+ "7 Epochs - Repeat 3/10 - Known Acc: 0.7860 - Novel Acc: 0.2162\n",
+ "7 Epochs - Repeat 4/10 - Known Acc: 0.8630 - Novel Acc: 0.1363\n",
+ "7 Epochs - Repeat 5/10 - Known Acc: 0.7960 - Novel Acc: 0.1938\n",
+ "7 Epochs - Repeat 6/10 - Known Acc: 0.9040 - Novel Acc: 0.0950\n",
+ "7 Epochs - Repeat 7/10 - Known Acc: 0.9290 - Novel Acc: 0.0833\n",
+ "7 Epochs - Repeat 8/10 - Known Acc: 0.8310 - Novel Acc: 0.1790\n",
+ "7 Epochs - Repeat 9/10 - Known Acc: 0.8790 - Novel Acc: 0.1035\n",
+ "7 Epochs - Repeat 10/10 - Known Acc: 0.8410 - Novel Acc: 0.1670\n"
+ ]
+ },
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+ "version_minor": 0
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+ "Repeating Experiment: 0%| | 0/10 [00:00<?, ?it/s]"
+ ]
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+ "name": "stdout",
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+ "text": [
+ "8 Epochs - Repeat 1/10 - Known Acc: 0.7210 - Novel Acc: 0.2772\n",
+ "8 Epochs - Repeat 2/10 - Known Acc: 0.7730 - Novel Acc: 0.2268\n",
+ "8 Epochs - Repeat 3/10 - Known Acc: 0.7440 - Novel Acc: 0.2432\n",
+ "8 Epochs - Repeat 4/10 - Known Acc: 0.7800 - Novel Acc: 0.2062\n",
+ "8 Epochs - Repeat 5/10 - Known Acc: 0.7120 - Novel Acc: 0.3043\n",
+ "8 Epochs - Repeat 6/10 - Known Acc: 0.7780 - Novel Acc: 0.2140\n",
+ "8 Epochs - Repeat 7/10 - Known Acc: 0.7440 - Novel Acc: 0.2572\n",
+ "8 Epochs - Repeat 8/10 - Known Acc: 0.7070 - Novel Acc: 0.3033\n",
+ "8 Epochs - Repeat 9/10 - Known Acc: 0.7280 - Novel Acc: 0.2672\n",
+ "8 Epochs - Repeat 10/10 - Known Acc: 0.7490 - Novel Acc: 0.2333\n"
+ ]
+ },
+ {
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+ "Repeating Experiment: 0%| | 0/10 [00:00<?, ?it/s]"
+ ]
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+ "text": [
+ "9 Epochs - Repeat 1/10 - Known Acc: 0.6480 - Novel Acc: 0.3608\n",
+ "9 Epochs - Repeat 2/10 - Known Acc: 0.6700 - Novel Acc: 0.3197\n",
+ "9 Epochs - Repeat 3/10 - Known Acc: 0.6410 - Novel Acc: 0.3820\n",
+ "9 Epochs - Repeat 4/10 - Known Acc: 0.6230 - Novel Acc: 0.3857\n",
+ "9 Epochs - Repeat 5/10 - Known Acc: 0.7450 - Novel Acc: 0.2895\n",
+ "9 Epochs - Repeat 6/10 - Known Acc: 0.6050 - Novel Acc: 0.3955\n",
+ "9 Epochs - Repeat 7/10 - Known Acc: 0.6960 - Novel Acc: 0.2835\n",
+ "9 Epochs - Repeat 8/10 - Known Acc: 0.6370 - Novel Acc: 0.3927\n",
+ "9 Epochs - Repeat 9/10 - Known Acc: 0.6240 - Novel Acc: 0.3485\n",
+ "9 Epochs - Repeat 10/10 - Known Acc: 0.6760 - Novel Acc: 0.3280\n"
+ ]
+ },
+ {
+ "data": {
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+ "version_major": 2,
+ "version_minor": 0
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+ "Repeating Experiment: 0%| | 0/10 [00:00<?, ?it/s]"
+ ]
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+ "text": [
+ "10 Epochs - Repeat 1/10 - Known Acc: 0.5760 - Novel Acc: 0.4203\n",
+ "10 Epochs - Repeat 2/10 - Known Acc: 0.5580 - Novel Acc: 0.4130\n",
+ "10 Epochs - Repeat 3/10 - Known Acc: 0.4980 - Novel Acc: 0.5198\n",
+ "10 Epochs - Repeat 4/10 - Known Acc: 0.5940 - Novel Acc: 0.4178\n",
+ "10 Epochs - Repeat 5/10 - Known Acc: 0.5740 - Novel Acc: 0.4437\n",
+ "10 Epochs - Repeat 6/10 - Known Acc: 0.5770 - Novel Acc: 0.4175\n",
+ "10 Epochs - Repeat 7/10 - Known Acc: 0.5410 - Novel Acc: 0.4537\n",
+ "10 Epochs - Repeat 8/10 - Known Acc: 0.5610 - Novel Acc: 0.4462\n",
+ "10 Epochs - Repeat 9/10 - Known Acc: 0.6050 - Novel Acc: 0.4198\n",
+ "10 Epochs - Repeat 10/10 - Known Acc: 0.5510 - Novel Acc: 0.4500\n"
+ ]
+ },
+ {
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+ "Repeating Experiment: 0%| | 0/10 [00:00<?, ?it/s]"
+ ]
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+ "text": [
+ "11 Epochs - Repeat 1/10 - Known Acc: 0.4270 - Novel Acc: 0.5323\n",
+ "11 Epochs - Repeat 2/10 - Known Acc: 0.5050 - Novel Acc: 0.5010\n",
+ "11 Epochs - Repeat 3/10 - Known Acc: 0.5230 - Novel Acc: 0.4828\n",
+ "11 Epochs - Repeat 4/10 - Known Acc: 0.4690 - Novel Acc: 0.5603\n",
+ "11 Epochs - Repeat 5/10 - Known Acc: 0.3930 - Novel Acc: 0.6080\n",
+ "11 Epochs - Repeat 6/10 - Known Acc: 0.4560 - Novel Acc: 0.5415\n",
+ "11 Epochs - Repeat 7/10 - Known Acc: 0.4820 - Novel Acc: 0.5395\n",
+ "11 Epochs - Repeat 8/10 - Known Acc: 0.4470 - Novel Acc: 0.5733\n",
+ "11 Epochs - Repeat 9/10 - Known Acc: 0.4700 - Novel Acc: 0.5305\n",
+ "11 Epochs - Repeat 10/10 - Known Acc: 0.4000 - Novel Acc: 0.5870\n"
+ ]
+ },
+ {
+ "data": {
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+ "version_major": 2,
+ "version_minor": 0
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+ "Repeating Experiment: 0%| | 0/10 [00:00<?, ?it/s]"
+ ]
+ },
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+ "text": [
+ "12 Epochs - Repeat 1/10 - Known Acc: 0.3950 - Novel Acc: 0.6282\n",
+ "12 Epochs - Repeat 2/10 - Known Acc: 0.2980 - Novel Acc: 0.7143\n",
+ "12 Epochs - Repeat 3/10 - Known Acc: 0.3460 - Novel Acc: 0.6542\n",
+ "12 Epochs - Repeat 4/10 - Known Acc: 0.4190 - Novel Acc: 0.6108\n",
+ "12 Epochs - Repeat 5/10 - Known Acc: 0.3630 - Novel Acc: 0.6418\n",
+ "12 Epochs - Repeat 6/10 - Known Acc: 0.2530 - Novel Acc: 0.7625\n",
+ "12 Epochs - Repeat 7/10 - Known Acc: 0.3620 - Novel Acc: 0.6182\n",
+ "12 Epochs - Repeat 8/10 - Known Acc: 0.3970 - Novel Acc: 0.6070\n",
+ "12 Epochs - Repeat 9/10 - Known Acc: 0.3740 - Novel Acc: 0.6362\n",
+ "12 Epochs - Repeat 10/10 - Known Acc: 0.3580 - Novel Acc: 0.6737\n"
+ ]
+ },
+ {
+ "data": {
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+ "version_major": 2,
+ "version_minor": 0
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+ "text/plain": [
+ "Repeating Experiment: 0%| | 0/10 [00:00<?, ?it/s]"
+ ]
+ },
+ "metadata": {},
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+ "text": [
+ "13 Epochs - Repeat 1/10 - Known Acc: 0.2420 - Novel Acc: 0.7480\n",
+ "13 Epochs - Repeat 2/10 - Known Acc: 0.2510 - Novel Acc: 0.7133\n",
+ "13 Epochs - Repeat 3/10 - Known Acc: 0.2410 - Novel Acc: 0.7495\n",
+ "13 Epochs - Repeat 4/10 - Known Acc: 0.2590 - Novel Acc: 0.7388\n",
+ "13 Epochs - Repeat 5/10 - Known Acc: 0.2670 - Novel Acc: 0.7153\n",
+ "13 Epochs - Repeat 6/10 - Known Acc: 0.2110 - Novel Acc: 0.7815\n",
+ "13 Epochs - Repeat 7/10 - Known Acc: 0.2490 - Novel Acc: 0.7650\n",
+ "13 Epochs - Repeat 8/10 - Known Acc: 0.2280 - Novel Acc: 0.7730\n",
+ "13 Epochs - Repeat 9/10 - Known Acc: 0.2560 - Novel Acc: 0.7160\n",
+ "13 Epochs - Repeat 10/10 - Known Acc: 0.2740 - Novel Acc: 0.7063\n"
+ ]
+ },
+ {
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+ "Repeating Experiment: 0%| | 0/10 [00:00<?, ?it/s]"
+ ]
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+ "text": [
+ "14 Epochs - Repeat 1/10 - Known Acc: 0.2960 - Novel Acc: 0.7145\n",
+ "14 Epochs - Repeat 2/10 - Known Acc: 0.2050 - Novel Acc: 0.7887\n",
+ "14 Epochs - Repeat 3/10 - Known Acc: 0.1750 - Novel Acc: 0.8325\n",
+ "14 Epochs - Repeat 4/10 - Known Acc: 0.1580 - Novel Acc: 0.8143\n",
+ "14 Epochs - Repeat 5/10 - Known Acc: 0.2160 - Novel Acc: 0.7945\n",
+ "14 Epochs - Repeat 6/10 - Known Acc: 0.1990 - Novel Acc: 0.7997\n",
+ "14 Epochs - Repeat 7/10 - Known Acc: 0.2230 - Novel Acc: 0.8133\n",
+ "14 Epochs - Repeat 8/10 - Known Acc: 0.1790 - Novel Acc: 0.7993\n",
+ "14 Epochs - Repeat 9/10 - Known Acc: 0.1760 - Novel Acc: 0.8133\n",
+ "14 Epochs - Repeat 10/10 - Known Acc: 0.1520 - Novel Acc: 0.8233\n"
+ ]
+ },
+ {
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+ "Repeating Experiment: 0%| | 0/10 [00:00<?, ?it/s]"
+ ]
+ },
+ "metadata": {},
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+ "text": [
+ "15 Epochs - Repeat 1/10 - Known Acc: 0.1230 - Novel Acc: 0.8420\n",
+ "15 Epochs - Repeat 2/10 - Known Acc: 0.1630 - Novel Acc: 0.8190\n",
+ "15 Epochs - Repeat 3/10 - Known Acc: 0.1960 - Novel Acc: 0.8340\n",
+ "15 Epochs - Repeat 4/10 - Known Acc: 0.1400 - Novel Acc: 0.8415\n",
+ "15 Epochs - Repeat 5/10 - Known Acc: 0.1590 - Novel Acc: 0.8560\n",
+ "15 Epochs - Repeat 6/10 - Known Acc: 0.1950 - Novel Acc: 0.8345\n",
+ "15 Epochs - Repeat 7/10 - Known Acc: 0.1580 - Novel Acc: 0.8255\n",
+ "15 Epochs - Repeat 8/10 - Known Acc: 0.1540 - Novel Acc: 0.8333\n",
+ "15 Epochs - Repeat 9/10 - Known Acc: 0.1510 - Novel Acc: 0.8225\n",
+ "15 Epochs - Repeat 10/10 - Known Acc: 0.1800 - Novel Acc: 0.8160\n"
+ ]
+ },
+ {
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+ "version_major": 2,
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+ "text/plain": [
+ "Repeating Experiment: 0%| | 0/10 [00:00<?, ?it/s]"
+ ]
+ },
+ "metadata": {},
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+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "16 Epochs - Repeat 1/10 - Known Acc: 0.1150 - Novel Acc: 0.8718\n",
+ "16 Epochs - Repeat 2/10 - Known Acc: 0.0960 - Novel Acc: 0.8902\n",
+ "16 Epochs - Repeat 3/10 - Known Acc: 0.1310 - Novel Acc: 0.8782\n",
+ "16 Epochs - Repeat 4/10 - Known Acc: 0.1350 - Novel Acc: 0.8668\n",
+ "16 Epochs - Repeat 5/10 - Known Acc: 0.1020 - Novel Acc: 0.8875\n",
+ "16 Epochs - Repeat 6/10 - Known Acc: 0.1470 - Novel Acc: 0.8427\n",
+ "16 Epochs - Repeat 7/10 - Known Acc: 0.1610 - Novel Acc: 0.8365\n",
+ "16 Epochs - Repeat 8/10 - Known Acc: 0.0970 - Novel Acc: 0.8782\n",
+ "16 Epochs - Repeat 9/10 - Known Acc: 0.0950 - Novel Acc: 0.9028\n",
+ "16 Epochs - Repeat 10/10 - Known Acc: 0.1180 - Novel Acc: 0.8625\n"
+ ]
+ },
+ {
+ "data": {
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+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "Repeating Experiment: 0%| | 0/10 [00:00<?, ?it/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "17 Epochs - Repeat 1/10 - Known Acc: 0.0890 - Novel Acc: 0.9105\n",
+ "17 Epochs - Repeat 2/10 - Known Acc: 0.1020 - Novel Acc: 0.9070\n",
+ "17 Epochs - Repeat 3/10 - Known Acc: 0.0940 - Novel Acc: 0.8822\n",
+ "17 Epochs - Repeat 4/10 - Known Acc: 0.0930 - Novel Acc: 0.9173\n",
+ "17 Epochs - Repeat 5/10 - Known Acc: 0.0850 - Novel Acc: 0.8982\n",
+ "17 Epochs - Repeat 6/10 - Known Acc: 0.1100 - Novel Acc: 0.8822\n",
+ "17 Epochs - Repeat 7/10 - Known Acc: 0.1210 - Novel Acc: 0.8650\n",
+ "17 Epochs - Repeat 8/10 - Known Acc: 0.1020 - Novel Acc: 0.8878\n",
+ "17 Epochs - Repeat 9/10 - Known Acc: 0.0820 - Novel Acc: 0.9080\n",
+ "17 Epochs - Repeat 10/10 - Known Acc: 0.1140 - Novel Acc: 0.9030\n"
+ ]
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "643410b67a66404f8110c96fe70b2643",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "Repeating Experiment: 0%| | 0/10 [00:00<?, ?it/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "18 Epochs - Repeat 1/10 - Known Acc: 0.0860 - Novel Acc: 0.9237\n",
+ "18 Epochs - Repeat 2/10 - Known Acc: 0.0770 - Novel Acc: 0.9340\n",
+ "18 Epochs - Repeat 3/10 - Known Acc: 0.0790 - Novel Acc: 0.9315\n",
+ "18 Epochs - Repeat 4/10 - Known Acc: 0.0630 - Novel Acc: 0.9217\n",
+ "18 Epochs - Repeat 5/10 - Known Acc: 0.0700 - Novel Acc: 0.9367\n",
+ "18 Epochs - Repeat 6/10 - Known Acc: 0.1020 - Novel Acc: 0.9247\n",
+ "18 Epochs - Repeat 7/10 - Known Acc: 0.0650 - Novel Acc: 0.9180\n",
+ "18 Epochs - Repeat 8/10 - Known Acc: 0.0690 - Novel Acc: 0.9345\n",
+ "18 Epochs - Repeat 9/10 - Known Acc: 0.0930 - Novel Acc: 0.9040\n",
+ "18 Epochs - Repeat 10/10 - Known Acc: 0.0880 - Novel Acc: 0.9197\n"
+ ]
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "052d2a1e6ea341a38143771fb6972b86",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "Repeating Experiment: 0%| | 0/10 [00:00<?, ?it/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "19 Epochs - Repeat 1/10 - Known Acc: 0.0600 - Novel Acc: 0.9380\n",
+ "19 Epochs - Repeat 2/10 - Known Acc: 0.0630 - Novel Acc: 0.9425\n",
+ "19 Epochs - Repeat 3/10 - Known Acc: 0.0590 - Novel Acc: 0.9455\n",
+ "19 Epochs - Repeat 4/10 - Known Acc: 0.0650 - Novel Acc: 0.9280\n",
+ "19 Epochs - Repeat 5/10 - Known Acc: 0.0840 - Novel Acc: 0.9170\n",
+ "19 Epochs - Repeat 6/10 - Known Acc: 0.0870 - Novel Acc: 0.9305\n",
+ "19 Epochs - Repeat 7/10 - Known Acc: 0.0740 - Novel Acc: 0.9320\n",
+ "19 Epochs - Repeat 8/10 - Known Acc: 0.0540 - Novel Acc: 0.9447\n",
+ "19 Epochs - Repeat 9/10 - Known Acc: 0.0900 - Novel Acc: 0.9330\n",
+ "19 Epochs - Repeat 10/10 - Known Acc: 0.0530 - Novel Acc: 0.9370\n"
+ ]
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "99cd5a3ef32f47b190a9736e39107a0a",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "Repeating Experiment: 0%| | 0/10 [00:00<?, ?it/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "20 Epochs - Repeat 1/10 - Known Acc: 0.0610 - Novel Acc: 0.9390\n",
+ "20 Epochs - Repeat 2/10 - Known Acc: 0.0560 - Novel Acc: 0.9470\n",
+ "20 Epochs - Repeat 3/10 - Known Acc: 0.0850 - Novel Acc: 0.9345\n",
+ "20 Epochs - Repeat 4/10 - Known Acc: 0.0440 - Novel Acc: 0.9480\n",
+ "20 Epochs - Repeat 5/10 - Known Acc: 0.0390 - Novel Acc: 0.9515\n",
+ "20 Epochs - Repeat 6/10 - Known Acc: 0.0440 - Novel Acc: 0.9530\n",
+ "20 Epochs - Repeat 7/10 - Known Acc: 0.0450 - Novel Acc: 0.9513\n",
+ "20 Epochs - Repeat 8/10 - Known Acc: 0.0380 - Novel Acc: 0.9575\n",
+ "20 Epochs - Repeat 9/10 - Known Acc: 0.0670 - Novel Acc: 0.9300\n",
+ "20 Epochs - Repeat 10/10 - Known Acc: 0.0550 - Novel Acc: 0.9465\n"
+ ]
+ }
+ ],
+ "source": [
+ "from sklearn.cluster import KMeans\n",
+ "epochs = 20\n",
+ "repeats = 10\n",
+ "\n",
+ "raw_logits_results_df = pd.DataFrame(columns=[\"epochs\", \"repeats\", \"known_acc\", \"novel_acc\"])\n",
+ "\n",
+ "for epoch in tqdm(range(1, epochs+1), desc=\"Num Epochs\"):\n",
+ " for repeat in tqdm(range(repeats), desc=\"Repeating Experiment\", leave=False):\n",
+ " df = (\n",
+ " master_df.copy()\n",
+ " ) # already computed old logits and entropy, just trim off anything else\n",
+ " df = df.rename(\n",
+ " columns={\n",
+ " \"entropy\": \"old_entropy\",\n",
+ " \"energy\": \"old_energy\",\n",
+ " \"pred_label\": \"old_pred_label\",\n",
+ " }\n",
+ " )\n",
+ " df = df.drop(columns=[f\"logit_{i}\" for i in range(50)] + [\"old_entropy\"], axis=1)\n",
+ " \n",
+ " feats = df[feat_cols].values\n",
+ " kmeans = KMeans(n_clusters=10, random_state=8008135, max_iter=300, tol=1e-4)\n",
+ " df[\"cluster\"] = kmeans.fit_predict(feats)\n",
+ " \n",
+ " \n",
+ " new_head = torch.nn.Linear(768, 10).to(device)\n",
+ " criterion = torch.nn.CrossEntropyLoss()\n",
+ " optimiser = torch.optim.SGD(new_head.parameters(), lr=1e-5)\n",
+ "\n",
+ " new_trainset = torch.utils.data.TensorDataset(\n",
+ " torch.tensor(df[feat_cols].values, dtype=torch.float32),\n",
+ " torch.tensor(df[\"cluster\"].values, dtype=torch.long),\n",
+ " )\n",
+ " \n",
+ " loader = torch.utils.data.DataLoader(\n",
+ " new_trainset, batch_size=256, shuffle=True, num_workers=4, pin_memory=True\n",
+ " )\n",
+ " \n",
+ " for i in range(epoch):\n",
+ " new_head.train()\n",
+ " epoch_losses = []\n",
+ " for x, y in loader:\n",
+ " x, y = x.to(device), y.to(device)\n",
+ " logits = new_head(x)\n",
+ " loss = criterion(logits, y)\n",
+ " loss.backward()\n",
+ " optimiser.step()\n",
+ " \n",
+ " feat_set = torch.utils.data.TensorDataset(\n",
+ " torch.tensor(df[feat_cols].values, dtype=torch.float32)\n",
+ " )\n",
+ " featloader = torch.utils.data.DataLoader(\n",
+ " feat_set, batch_size=256, shuffle=True, num_workers=4, pin_memory=True\n",
+ " )\n",
+ "\n",
+ " pretrained_model.eval()\n",
+ " new_head.eval()\n",
+ "\n",
+ " results = []\n",
+ " with torch.no_grad():\n",
+ " for x, y in loader:\n",
+ " x, y = x.to(device), y.to(device)\n",
+ " old_logits = pretrained_model.forward_head(x)\n",
+ " old_softmax = torch.nn.functional.softmax(old_logits, dim=1)\n",
+ " old_predlabel= torch.argmax(old_logits, dim=1)\n",
+ " old_entropy = -torch.sum(old_softmax * torch.log(old_softmax + 1e-12), dim=1)\n",
+ " \n",
+ " new_logits = new_head(x)\n",
+ " new_softmax = torch.nn.functional.softmax(new_logits, dim=1)\n",
+ " new_predlabel = torch.argmax(new_logits, dim=1)\n",
+ " new_entropy = -torch.sum(new_softmax * torch.log(new_softmax + 1e-12), dim=1)\n",
+ " \n",
+ " old_maxsoftmax = np.max(old_softmax.cpu().numpy(), axis=1)\n",
+ " old_predlabel = old_predlabel.cpu().numpy()\n",
+ " old_entropy = old_entropy.cpu().numpy()\n",
+ " \n",
+ " new_maxsoftmax = np.max(new_softmax.cpu().numpy(), axis=1)\n",
+ " new_predlabel = new_predlabel.cpu().numpy()\n",
+ " new_entropy = new_entropy.cpu().numpy()\n",
+ " \n",
+ " combined_logits = torch.cat([old_logits, new_logits], dim=1)\n",
+ " \n",
+ " for i in range(x.size(0)):\n",
+ " results.append([old_predlabel[i], old_maxsoftmax[i], old_entropy[i], new_predlabel[i], new_maxsoftmax[i], new_entropy[i], *combined_logits[i].cpu().numpy()])\n",
+ " \n",
+ " results_df = pd.DataFrame(results, columns=[\"old_predlabel\", \"old_maxsoftmax\", \"old_entropy\", \"new_predlabel\", \"new_maxsoftmax\", \"new_entropy\"] + [f\"logit_{i}\" for i in range(60)])\n",
+ " df = pd.concat([df, results_df], axis=1)\n",
+ " \n",
+ " df[\"old_predlabel\"] = np.argmax(df[[f\"logit_{i}\" for i in range(50)]].values, axis=1)\n",
+ " df[\"new_predlabel\"] = np.argmax(df[[f\"logit_{i}\" for i in range(50, 60)]].values, axis=1)\n",
+ " df[\"new_predlabel\"] += 50 # adjust the new predlabel to be in the range 50-60\n",
+ " df[\"combined_predlabel\"] = np.argmax(df[[f\"logit_{i}\" for i in range(60)]].values, axis=1)\n",
+ "\n",
+ " # compute OOD accuracy\n",
+ " known = df[df[\"true_type\"] == 0]\n",
+ " novel = df[df[\"true_type\"] == 1]\n",
+ " \n",
+ " known_acc = known[known[\"combined_predlabel\"] < 50].shape[0] / known.shape[0]\n",
+ " novel_acc = novel[novel[\"combined_predlabel\"] >= 50].shape[0] / novel.shape[0]\n",
+ " \n",
+ " raw_logits_results_df.loc[len(raw_logits_results_df)] = [epoch, repeat, known_acc, novel_acc]\n",
+ " \n",
+ " tqdm.write(f\"{epoch} Epochs - Repeat {repeat+1}/{repeats} - Known Acc: {known_acc:.4f} - Novel Acc: {novel_acc:.4f}\")\n",
+ " \n",
+ " \n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 158,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " epochs repeats known_acc novel_acc\n",
+ "0 1.0 4.5 0.9995 0.000500\n",
+ "1 2.0 4.5 0.9993 0.000650\n",
+ "2 3.0 4.5 0.9981 0.002350\n",
+ "3 4.0 4.5 0.9880 0.012550\n",
+ "4 5.0 4.5 0.9756 0.024200\n",
+ "5 6.0 4.5 0.9328 0.071600\n",
+ "6 7.0 4.5 0.8569 0.142825\n",
+ "7 8.0 4.5 0.7436 0.253275\n",
+ "8 9.0 4.5 0.6565 0.348600\n",
+ "9 10.0 4.5 0.5635 0.440175\n",
+ "10 11.0 4.5 0.4572 0.545600\n",
+ "11 12.0 4.5 0.3565 0.654700\n",
+ "12 13.0 4.5 0.2478 0.740650\n",
+ "13 14.0 4.5 0.1979 0.799325\n",
+ "14 15.0 4.5 0.1619 0.832425\n",
+ "15 16.0 4.5 0.1197 0.871725\n",
+ "16 17.0 4.5 0.0992 0.896125\n",
+ "17 18.0 4.5 0.0792 0.924875\n",
+ "18 19.0 4.5 0.0689 0.934825\n",
+ "19 20.0 4.5 0.0534 0.945825\n"
+ ]
+ }
+ ],
+ "source": [
+ "out_df = raw_logits_results_df.copy()\n",
+ "out_df = out_df.groupby(\"epochs\").mean().reset_index()\n",
+ "print(out_df)\n",
+ "out_df.drop(columns=\"repeats\", inplace=True)\n",
+ "out_df.to_csv(\"raw_logits_results.csv\", index=False)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Old Head Entropy & Logits"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "\n",
+ "df = (master_df.copy())\n",
+ "df = df.rename(\n",
+ " columns={\n",
+ " \"entropy\": \"old_entropy\",\n",
+ " \"energy\": \"old_energy\",\n",
+ " \"pred_label\": \"old_pred_label\",\n",
+ " }\n",
+ ")\n",
+ "df = df.rename(columns={f\"logit_{i}\": f\"old_logit_{i}\" for i in range(50)})\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### K-Means"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# do kmeans on features\n",
+ "from sklearn.cluster import KMeans\n",
+ "feats = df[feat_cols].values\n",
+ "kmeans = KMeans(n_clusters=10, random_state=8008135, max_iter=300, tol=1e-4)\n",
+ "gmm = GaussianMixture(n_components=10, random_state=8008135, max_iter=1000, tol=1e-4)\n",
+ "df[\"cluster\"] = gmm.fit_predict(feats)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 144,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "do_tsne = False\n",
+ "if do_tsne:\n",
+ " #tsne and visualise\n",
+ " from sklearn.manifold import TSNE\n",
+ "\n",
+ " tsne = TSNE(n_components=2, random_state=8008135, n_jobs=4)\n",
+ " tsne_feats = tsne.fit_transform(feats)\n",
+ "\n",
+ " plt.figure(figsize=(10, 8))\n",
+ " plt.scatter(tsne_feats[:, 0], tsne_feats[:, 1], c=df[\"cluster\"], cmap=\"tab10\")\n",
+ " plt.axis(\"equal\")\n",
+ " plt.title(\"TSNE of Features Cluster Visualisation\")\n",
+ " plt.colorbar()\n",
+ " plt.tight_layout()\n",
+ " plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 145,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 1600x600 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "assignment_matrix = df.groupby([\"cluster\", \"label\"]).size().unstack(fill_value=0)\n",
+ "normed_assignment_matrix = np.log1p(assignment_matrix)\n",
+ "annot_matrix = assignment_matrix.map(lambda x: f\"{int(x)}\" if x > 0 else \"\")\n",
+ "\n",
+ "\n",
+ "plt.figure(figsize=(16, 6))\n",
+ "sns.heatmap(\n",
+ " normed_assignment_matrix,\n",
+ " cmap=\"viridis\",\n",
+ " annot=annot_matrix,\n",
+ " fmt=\"\",\n",
+ " annot_kws={\"size\": 8, \"rotation\":90},\n",
+ " yticklabels=[f\"Cluster {i}\" for i in range(10)],\n",
+ " xticklabels=[f\"{i}: {label_mapping[i]}\" for i in range(0, 60)],\n",
+ " cbar=False\n",
+ ")\n",
+ "plt.xlabel(\"\")\n",
+ "plt.ylabel(\"\")\n",
+ "plt.title(\"Cluster Assignment Matrix\")\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### New Head & Logits"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 146,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "8095306b2c8542f390a966102f1e8a0e",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "Training New Head: 0%| | 0/6 [00:00<?, ?epoch/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Epoch 0 Loss: 2.775409924983978(0)\n",
+ "Epoch 1 Loss: 2.333942914009094(-0.44146701097488394)\n",
+ "Epoch 2 Loss: 1.8984204828739166(-0.4355224311351775)\n",
+ "Epoch 3 Loss: 1.624126774072647(-0.2742937088012696)\n",
+ "Epoch 4 Loss: 1.2895808279514314(-0.3345459461212157)\n",
+ "Epoch 5 Loss: 0.9241639584302902(-0.36541686952114116)\n"
+ ]
+ }
+ ],
+ "source": [
+ "new_head = torch.nn.Linear(768, 10)\n",
+ "new_head = new_head.to(device)\n",
+ "epochs = 6\n",
+ "criterion = torch.nn.CrossEntropyLoss()\n",
+ "optimiser = torch.optim.SGD(new_head.parameters(), lr=1e-5)\n",
+ "\n",
+ "new_trainset = torch.utils.data.TensorDataset(\n",
+ " torch.tensor(df[feat_cols].values, dtype=torch.float32),\n",
+ " torch.tensor(df[\"cluster\"].values, dtype=torch.long),\n",
+ ")\n",
+ "loader = torch.utils.data.DataLoader(\n",
+ " new_trainset, batch_size=256, shuffle=True, num_workers=4, pin_memory=True\n",
+ ")\n",
+ "\n",
+ "losses = []\n",
+ "\n",
+ "for epoch in tqdm(range(epochs), desc=\"Training New Head\", unit=\"epoch\"):\n",
+ " new_head.train()\n",
+ " epoch_losses = []\n",
+ " for x, y in loader:\n",
+ " x, y = x.to(device), y.to(device)\n",
+ " logits = new_head(x)\n",
+ " loss = criterion(logits, y)\n",
+ " epoch_losses.append(loss.item())\n",
+ " loss.backward()\n",
+ " optimiser.step()\n",
+ " losses.append(np.mean(epoch_losses))\n",
+ " tqdm.write(f\"Epoch {epoch} Loss: {losses[-1]}({(losses[-1] - losses[-2]) if len(losses) > 1 else 0})\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 147,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# compute argmax and softmax for the old head:\n",
+ "feat_set = torch.utils.data.TensorDataset(\n",
+ " torch.tensor(df[feat_cols].values, dtype=torch.float32)\n",
+ ")\n",
+ "featloader = torch.utils.data.DataLoader(\n",
+ " feat_set, batch_size=256, shuffle=True, num_workers=4, pin_memory=True\n",
+ ")\n",
+ "\n",
+ "losses = []\n",
+ "\n",
+ "pretrained_model.eval()\n",
+ "new_head.eval()\n",
+ "\n",
+ "results = []\n",
+ "df = df.drop(labels=\"old_entropy\", axis=1)\n",
+ "df = df.drop(labels=[f\"old_logit_{i}\" for i in range(50)], axis=1)\n",
+ "\n",
+ "with torch.no_grad():\n",
+ " for x, y in loader:\n",
+ " x, y = x.to(device), y.to(device)\n",
+ " old_logits = pretrained_model.forward_head(x)\n",
+ " old_softmax = torch.nn.functional.softmax(old_logits, dim=1)\n",
+ " old_predlabel= torch.argmax(old_logits, dim=1)\n",
+ " old_entropy = -torch.sum(old_softmax * torch.log(old_softmax + 1e-12), dim=1)\n",
+ " \n",
+ " new_logits = new_head(x)\n",
+ " new_softmax = torch.nn.functional.softmax(new_logits, dim=1)\n",
+ " new_predlabel = torch.argmax(new_logits, dim=1)\n",
+ " new_entropy = -torch.sum(new_softmax * torch.log(new_softmax + 1e-12), dim=1)\n",
+ " \n",
+ " old_maxsoftmax = np.max(old_softmax.cpu().numpy(), axis=1)\n",
+ " old_predlabel = old_predlabel.cpu().numpy()\n",
+ " old_entropy = old_entropy.cpu().numpy()\n",
+ " \n",
+ " new_maxsoftmax = np.max(new_softmax.cpu().numpy(), axis=1)\n",
+ " new_predlabel = new_predlabel.cpu().numpy()\n",
+ " new_entropy = new_entropy.cpu().numpy()\n",
+ " \n",
+ " combined_logits = torch.cat([old_logits, new_logits], dim=1)\n",
+ " \n",
+ " for i in range(x.size(0)):\n",
+ " results.append([old_predlabel[i], old_maxsoftmax[i], old_entropy[i], new_predlabel[i], new_maxsoftmax[i], new_entropy[i], *combined_logits[i].cpu().numpy()])\n",
+ " \n",
+ "results_df = pd.DataFrame(results, columns=[\"old_predlabel\", \"old_maxsoftmax\", \"old_entropy\", \"new_predlabel\", \"new_maxsoftmax\", \"new_entropy\"] + [f\"logit_{i}\" for i in range(60)])\n",
+ "\n",
+ "# join results_df to the original df\n",
+ "df = pd.concat([df, results_df], axis=1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 148,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 1600x800 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "df = df.select_dtypes(include=['number'])\n",
+ "class_df = df.groupby(\"label\").mean()\n",
+ "class_df[\"label\"] = class_df.index\n",
+ "\n",
+ "fig, ax= plt.subplots(figsize=(16, 8))\n",
+ "\n",
+ "#bar_width = 0.35\n",
+ "classes = range(len(class_df))\n",
+ "#bar_pos_old = [x - bar_width for x in classes]\n",
+ "#bar_pos_new = [x + bar_width for x in classes]\n",
+ "\n",
+ "ax.bar(class_df[\"label\"], class_df[\"old_entropy\"], label=\"Old Head Entropy\")\n",
+ "ax.bar(class_df[\"label\"], class_df[\"new_entropy\"], bottom=class_df[\"old_entropy\"], label=\"New Head Entropy\")\n",
+ "ax.axvline(x=49.5, color=\"r\", linestyle=\"--\")\n",
+ "\n",
+ "ax.set_xticks(classes)\n",
+ "ax.set_xticklabels([f\"{i}: {label_mapping[i]}\" for i in classes], rotation=90)\n",
+ "ax.set_ylabel(\"Entropy\")\n",
+ "ax.set_title(\"Mean Entropy of Classes by Head\")\n",
+ "ax.legend()\n",
+ "\n",
+ "plt.tight_layout()\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 149,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 1600x800 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# plot distribution of entropies in each class using a box plot\n",
+ "df_melt = df.melt(id_vars=[\"label\"], value_vars=[\"old_entropy\", \"new_entropy\"], var_name=\"Head\", value_name=\"Entropy\")\n",
+ "#rename olf_entropy in the head column to Old and new_entropy to NEw\n",
+ "df_melt[\"Head\"] = df_melt[\"Head\"].map({\"old_entropy\": \"Old\", \"new_entropy\": \"New\"})\n",
+ "\n",
+ "fig, ax = plt.subplots(figsize=(16, 8))\n",
+ "sns.boxplot(data=df_melt, x=\"label\", y=\"Entropy\", hue=\"Head\", ax=ax, width=0.6)\n",
+ "ax.set_xticks(list(range(0, 60)))\n",
+ "ax.set_xticklabels([f\"{i}: {label_mapping[i]}\" for i in classes], rotation=90)\n",
+ "ax.set_ylabel(\"Entropy\")\n",
+ "ax.set_title(\"Entropy Distribution of Classes by Head\")\n",
+ "plt.tight_layout()\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Combined Heads NCD/OOD Tests"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "#### Raw Logits"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 150,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Known Correct/Total (Accuracy%) 906/1000 (0.9060)\n",
+ "Novel Correct/Total (Accuracy%) 448/4000 (0.1120)\n"
+ ]
+ },
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th>Label</th>\n",
+ " <th>Head</th>\n",
+ " <th>0: 'apple'</th>\n",
+ " <th>10: 'bowl'</th>\n",
+ " <th>11: 'boy'</th>\n",
+ " <th>12: 'bridge'</th>\n",
+ " <th>13: 'bus'</th>\n",
+ " <th>14: 'butterfly'</th>\n",
+ " <th>15: 'camel'</th>\n",
+ " <th>16: 'can'</th>\n",
+ " <th>17: 'castle'</th>\n",
+ " <th>...</th>\n",
+ " <th>55: 'otter'</th>\n",
+ " <th>56: 'palm_tree'</th>\n",
+ " <th>57: 'pear'</th>\n",
+ " <th>58: 'pickup_truck'</th>\n",
+ " <th>59: 'pine_tree'</th>\n",
+ " <th>5: 'bed'</th>\n",
+ " <th>6: 'bee'</th>\n",
+ " <th>7: 'beetle'</th>\n",
+ " <th>8: 'bicycle'</th>\n",
+ " <th>9: 'bottle'</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>Combined Head Accuracy</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>...</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0075</td>\n",
+ " <td>0.035</td>\n",
+ " <td>0.0175</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>New Head Accuracy</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>...</td>\n",
+ " <td>0.02</td>\n",
+ " <td>0.04</td>\n",
+ " <td>0.2825</td>\n",
+ " <td>0.1225</td>\n",
+ " <td>0.155</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>Old Head Accuracy</td>\n",
+ " <td>0.1</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.05</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.15</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.05</td>\n",
+ " <td>0.05</td>\n",
+ " <td>...</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "<p>3 rows × 61 columns</p>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ "Label Head 0: 'apple' 10: 'bowl' 11: 'boy' 12: 'bridge' \\\n",
+ "0 Combined Head Accuracy 0.0 0.0 0.0 0.0 \n",
+ "1 New Head Accuracy NaN NaN NaN NaN \n",
+ "2 Old Head Accuracy 0.1 0.0 0.05 0.0 \n",
+ "\n",
+ "Label 13: 'bus' 14: 'butterfly' 15: 'camel' 16: 'can' 17: 'castle' ... \\\n",
+ "0 0.0 0.0 0.0 0.0 0.0 ... \n",
+ "1 NaN NaN NaN NaN NaN ... \n",
+ "2 0.15 0.0 0.0 0.05 0.05 ... \n",
+ "\n",
+ "Label 55: 'otter' 56: 'palm_tree' 57: 'pear' 58: 'pickup_truck' \\\n",
+ "0 0.0 0.0075 0.035 0.0175 \n",
+ "1 0.02 0.04 0.2825 0.1225 \n",
+ "2 NaN NaN NaN NaN \n",
+ "\n",
+ "Label 59: 'pine_tree' 5: 'bed' 6: 'bee' 7: 'beetle' 8: 'bicycle' 9: 'bottle' \n",
+ "0 0.0 0.0 0.0 0.0 0.0 0.0 \n",
+ "1 0.155 NaN NaN NaN NaN NaN \n",
+ "2 NaN 0.0 0.0 0.0 0.0 0.0 \n",
+ "\n",
+ "[3 rows x 61 columns]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# using the logits for each sample, apply argmax to the logits to determine class. If the class is 0-50, it is known, if it is 50-60, it is novel\n",
+ "raw_logits_df = df.copy()\n",
+ "\n",
+ "raw_logits_df[\"old_predlabel\"] = np.argmax(raw_logits_df[[f\"logit_{i}\" for i in range(50)]].values, axis=1)\n",
+ "raw_logits_df[\"new_predlabel\"] = np.argmax(raw_logits_df[[f\"logit_{i}\" for i in range(50, 60)]].values, axis=1)\n",
+ "raw_logits_df[\"new_predlabel\"] += 50 # adjust the new predlabel to be in the range 50-60\n",
+ "raw_logits_df[\"combined_predlabel\"] = np.argmax(raw_logits_df[[f\"logit_{i}\" for i in range(60)]].values, axis=1)\n",
+ "\n",
+ "# compute OOD accuracy\n",
+ "known = raw_logits_df[raw_logits_df[\"true_type\"] == 0]\n",
+ "novel = raw_logits_df[raw_logits_df[\"true_type\"] == 1]\n",
+ "\n",
+ "print(\n",
+ " f\"Known Correct/Total (Accuracy%) {known[known['combined_predlabel'] < 50].shape[0]}/{known.shape[0]} ({(known[known['combined_predlabel'] < 50].shape[0]/known.shape[0]):.4f})\"\n",
+ ")\n",
+ "print(\n",
+ " f\"Novel Correct/Total (Accuracy%) {novel[novel['combined_predlabel'] >= 50].shape[0]}/{novel.shape[0]} ({(novel[novel['combined_predlabel'] >= 50].shape[0]/novel.shape[0]):.4f})\"\n",
+ ")\n",
+ "\n",
+ "# region Accuracy\n",
+ "# each sample has been classified by the new head, but the pseudo-labels 50-60 are not necessarily mapped to the correct 50-60. I.E, most of class 50 may be labelled as 51. We need to map the pseudo-labels to the correct labels, using a confusion matrix and the hungarian algorithm\n",
+ "# we cannot map 60 classes to 10, so we need to determine the mapping based on the true classes of 50-60 samples\n",
+ "from scipy.optimize import linear_sum_assignment\n",
+ "from sklearn.metrics import confusion_matrix\n",
+ "\n",
+ "novel_sample_truelabels, novel_sample_predlabels = (\n",
+ " raw_logits_df[raw_logits_df[\"true_type\"] == 1][\"label\"],\n",
+ " raw_logits_df[raw_logits_df[\"true_type\"] == 1][\"new_predlabel\"],\n",
+ ")\n",
+ "\n",
+ "# confmat does not like values not starting at 0, so we will subtract 50 from the both labels\n",
+ "novel_sample_truelabels -= 50\n",
+ "novel_sample_predlabels -= 50\n",
+ "\n",
+ "cm = confusion_matrix(novel_sample_truelabels, novel_sample_predlabels)\n",
+ "row_ind, col_ind = linear_sum_assignment(-cm)\n",
+ "\n",
+ "# we now add the 50 back to the col and row idxs\n",
+ "row_ind += 50\n",
+ "col_ind += 50\n",
+ "\n",
+ "mapping = {true: psuedo for true, psuedo in zip(row_ind, col_ind)}\n",
+ "\n",
+ "# create a new column in the raw_logits_df that maps the new_predlabel to to the correct label\n",
+ "raw_logits_df[\"mapped_new_predlabel\"] = raw_logits_df[\"new_predlabel\"].map(mapping)\n",
+ "raw_logits_df[\"mapped_combined_predlabel\"] = raw_logits_df[\"combined_predlabel\"].map(mapping)\n",
+ "\n",
+ "# compute labelling accuracy\n",
+ "\n",
+ "out_df = pd.DataFrame(columns=[\"raw_label\", \"Label\", \"Old Head Accuracy\", \"New Head Accuracy\", \"Combined Head Accuracy\"])\n",
+ "out_df[\"Label\"] = [f\"{i}: {label_mapping[i]}\" for i in range(60)]\n",
+ "out_df[\"raw_label\"] = list(range(60))\n",
+ "\n",
+ "# for each class in raw_logits_df, calculate the classification accuracy of the old head, new head and combined head\n",
+ "for class_idx in range(60):\n",
+ " just_these_classes = raw_logits_df[raw_logits_df[\"label\"] == class_idx]\n",
+ " if class_idx <50:\n",
+ " old_acc = just_these_classes[just_these_classes[\"old_predlabel\"] == class_idx].shape[0] / just_these_classes.shape[0]\n",
+ " else:\n",
+ " old_acc = np.nan\n",
+ " \n",
+ " if class_idx >= 50:\n",
+ " new_acc = just_these_classes[just_these_classes[\"mapped_new_predlabel\"] == class_idx].shape[0] / just_these_classes.shape[0]\n",
+ " else:\n",
+ " new_acc = np.nan\n",
+ " combined_acc = just_these_classes[just_these_classes[\"mapped_combined_predlabel\"] == class_idx].shape[0] / just_these_classes.shape[0]\n",
+ " out_df.loc[out_df[\"raw_label\"] == class_idx, \"Old Head Accuracy\"] = old_acc\n",
+ " out_df.loc[out_df[\"raw_label\"] == class_idx, \"New Head Accuracy\"] = new_acc\n",
+ " out_df.loc[out_df[\"raw_label\"] == class_idx, \"Combined Head Accuracy\"] = combined_acc\n",
+ " \n",
+ "out_df = out_df.drop(labels=\"raw_label\", axis=1)\n",
+ "# flip the df so the rows are cols and the cols are rows\n",
+ "out_df = out_df.melt(id_vars=[\"Label\"], var_name=\"Head\", value_name=\"Accuracy\")\n",
+ "out_df = out_df.pivot(index=\"Head\", columns=\"Label\", values=\"Accuracy\")\n",
+ "out_df = out_df.reset_index()\n",
+ "#out_df = out_df.applymap(lambda x: f\"{x:.4f}\" if x != np.nan else \"\")\n",
+ "display(out_df)\n",
+ "# endregion\n"
]
}
],
diff --git a/experiments/labelmaps.csv b/experiments/labelmaps.csv
new file mode 100644
index 0000000..2eba264
--- /dev/null
+++ b/experiments/labelmaps.csv
@@ -0,0 +1,101 @@
+id,label
+0,'apple'
+1,'aquarium_fish'
+2,'baby'
+3,'bear'
+4,'beaver'
+5,'bed'
+6,'bee'
+7,'beetle'
+8,'bicycle'
+9,'bottle'
+10,'bowl'
+11,'boy'
+12,'bridge'
+13,'bus'
+14,'butterfly'
+15,'camel'
+16,'can'
+17,'castle'
+18,'caterpillar'
+19,'cattle'
+20,'chair'
+21,'chimpanzee'
+22,'clock'
+23,'cloud'
+24,'cockroach'
+25,'couch'
+26,'crab'
+27,'crocodile'
+28,'cup'
+29,'dinosaur'
+30,'dolphin'
+31,'elephant'
+32,'flatfish'
+33,'forest'
+34,'fox'
+35,'girl'
+36,'hamster'
+37,'house'
+38,'kangaroo'
+39,'computer_keyboard'
+40,'lamp'
+41,'lawn_mower'
+42,'leopard'
+43,'lion'
+44,'lizard'
+45,'lobster'
+46,'man'
+47,'maple_tree'
+48,'motorcycle'
+49,'mountain'
+50,'mouse'
+51,'mushroom'
+52,'oak_tree'
+53,'orange'
+54,'orchid'
+55,'otter'
+56,'palm_tree'
+57,'pear'
+58,'pickup_truck'
+59,'pine_tree'
+60,'plain'
+61,'plate'
+62,'poppy'
+63,'porcupine'
+64,'possum'
+65,'rabbit'
+66,'raccoon'
+67,'ray'
+68,'road'
+69,'rocket'
+70,'rose'
+71,'sea'
+72,'seal'
+73,'shark'
+74,'shrew'
+75,'skunk'
+76,'skyscraper'
+77,'snail'
+78,'snake'
+79,'spider'
+80,'squirrel'
+81,'streetcar'
+82,'sunflower'
+83,'sweet_pepper'
+84,'table'
+85,'tank'
+86,'telephone'
+87,'television'
+88,'tiger'
+89,'tractor'
+90,'train'
+91,'trout'
+92,'tulip'
+93,'turtle'
+94,'wardrobe'
+95,'whale'
+96,'willow_tree'
+97,'wolf'
+98,'woman'
+99,'worm'
\ No newline at end of file
diff --git a/experiments/raw_logits_results.csv b/experiments/raw_logits_results.csv
new file mode 100644
index 0000000..b8dc8cd
--- /dev/null
+++ b/experiments/raw_logits_results.csv
@@ -0,0 +1,21 @@
+epochs,known_acc,novel_acc
+1.0,0.9995,0.0005
+2.0,0.9993000000000001,0.0006500000000000001
+3.0,0.9981,0.00235
+4.0,0.9879999999999999,0.01255
+5.0,0.9756,0.0242
+6.0,0.9328,0.0716
+7.0,0.8569000000000001,0.142825
+8.0,0.7436,0.25327500000000003
+9.0,0.6565000000000001,0.34859999999999997
+10.0,0.5635,0.440175
+11.0,0.4572,0.5456
+12.0,0.3565,0.6547
+13.0,0.24780000000000002,0.74065
+14.0,0.1979,0.799325
+15.0,0.1619,0.832425
+16.0,0.1197,0.871725
+17.0,0.0992,0.896125
+18.0,0.0792,0.9248749999999999
+19.0,0.06889999999999999,0.934825
+20.0,0.0534,0.9458249999999999
--
GitLab