diff --git a/.flake8 b/.flake8
new file mode 100644
index 0000000..1e4ee66
--- /dev/null
+++ b/.flake8
@@ -0,0 +1,7 @@
+[flake8]
+max-line-length = 130
+ignores = W503
+per-file-ignores =
+    __init__.py: F401
+exclude =
+    .git,__pycache__,.ipynb_checkpoints,models/,dataset/
diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..e7f2efa
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,150 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# Custom
+/datasets/
+/models/
+clearml.conf
+*.parquet
+
+# Intellij
+.idea/
+
+# .DS_Store
+.DS_Store
\ No newline at end of file
diff --git a/Dockerfile b/Dockerfile
new file mode 100644
index 0000000..7d299ac
--- /dev/null
+++ b/Dockerfile
@@ -0,0 +1,8 @@
+FROM tensorflow/tensorflow:2.13.0-gpu-jupyter
+
+WORKDIR /app
+COPY requirements.txt /app
+
+RUN pip install -r requirements.txt
+
+ENTRYPOINT cd src && jupyter notebook --ip=0.0.0.0
diff --git a/LICENSE b/LICENSE
new file mode 100644
index 0000000..179d732
--- /dev/null
+++ b/LICENSE
@@ -0,0 +1,9 @@
+The MIT License (MIT)
+
+Copyright (c) 2023 XMARTLABS
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
\ No newline at end of file
diff --git a/README.md b/README.md
index 5e07f91..b92b5a1 100644
--- a/README.md
+++ b/README.md
@@ -1 +1,30 @@
-# time-series-playground
\ No newline at end of file
+# Time Series Playrground
+
+Welcome to Xmartlabs' time series playground. This repository contains scripts and code to train time series models on weather datasets.
+
+## Instructions
+
+* Download the Jena Climate dataset by running:
+
+```bash
+./download_jena_dataset.sh
+```
+
+* Build the docker container:
+
+```bash
+./build.sh
+```
+
+* Start the docker container with the Jupyter Notebook:
+
+```bash
+./start.sh
+```
+
+* Follow the instructions to access the notebook on your browser
+
+
+## ClearML experiment tracking
+
+If you use the ClearML tracker, make sure to configure correctly your $HOME/clearml.conf file and create a $HOME/.clearml folder that will store the caches and other stuff.
diff --git a/build.sh b/build.sh
new file mode 100755
index 0000000..61bb51b
--- /dev/null
+++ b/build.sh
@@ -0,0 +1,2 @@
+#!/bin/bash
+docker build -t time_series_playground .
diff --git a/download_jena_dataset.sh b/download_jena_dataset.sh
new file mode 100755
index 0000000..67f9e28
--- /dev/null
+++ b/download_jena_dataset.sh
@@ -0,0 +1,17 @@
+#!/bin/bash
+
+# constants
+DIR=datasets/jena_climate/
+DATASET_URL="https://storage.googleapis.com/tensorflow/tf-keras-datasets/jena_climate_2009_2016.csv.zip"
+
+mkdir -p $DIR
+wget -P $DIR $DATASET_URL
+cd $DIR
+unzip jena_climate_2009_2016.csv.zip
+
+# Clean up
+rm jena_climate_2009_2016.csv.zip
+rm -rf __MACOSX/
+
+echo "Goodbye! Here goes a joke:"
+curl -s https://api.chucknorris.io/jokes/random?category=dev | jq -r '.value'
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..d6fde0d
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,6 @@
+clearml
+keras
+matplotlib
+pandas
+scikit-learn
+seaborn
\ No newline at end of file
diff --git a/src/__init__.py b/src/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/src/dataset_loader.py b/src/dataset_loader.py
new file mode 100644
index 0000000..1ba0b70
--- /dev/null
+++ b/src/dataset_loader.py
@@ -0,0 +1,36 @@
+import json
+import os
+import pandas as pd
+from clearml import Dataset
+
+
+class DatasetLoader():
+    """Abstract class that serves to load datasets from different sources (local, ClearML, other tracker)
+    """
+
+    def get_dataset_folder(self, dataset_project, dataset_name):
+        return NotImplementedError()
+
+
+class LocalDatasetLoader(DatasetLoader):
+
+    def get_dataset_folder(self, dataset_project, dataset_name):
+        return f"data/{dataset_name}"
+
+
+class ClearMLDatasetLoader(DatasetLoader):
+
+    def get_dataset_folder(self, dataset_project, dataset_name):
+        return Dataset.get(dataset_project=dataset_project, dataset_name=dataset_name).get_local_copy()
+
+
+class JenaDatasetLoader(ClearMLDatasetLoader):
+    project = 'Time Series PG'
+    dataset = 'jena_climate'
+
+    def load(self):
+        self.data_folder = self.get_dataset_folder(self.project, self.dataset)
+
+    def get_data(self):
+        assert self.data_folder is not None, "You must call `load` before reading files"
+        return pd.read_csv(os.path.join(self.data_folder, "jena_climate_2009_2016.csv"))
diff --git a/src/models/__init__.py b/src/models/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/src/models/single_step_models.py b/src/models/single_step_models.py
new file mode 100644
index 0000000..d82a819
--- /dev/null
+++ b/src/models/single_step_models.py
@@ -0,0 +1,67 @@
+import tensorflow as tf
+from src.models.time_series_model import TimeSeriesModel
+
+
+class Baseline(tf.keras.Model):
+    def __init__(self, label_index=None):
+        super().__init__()
+        self.label_index = label_index
+
+    def call(self, inputs):
+        if self.label_index is None:
+            return inputs
+        result = inputs[:, :, self.label_index]
+        return result[:, :, tf.newaxis]
+
+
+class LinearModel(TimeSeriesModel):
+    def build_model(self, **kwargs):
+        self.model = tf.keras.Sequential([
+            tf.keras.layers.Dense(units=1)
+        ])
+
+
+class DenseModel(TimeSeriesModel):
+    def build_model(self, **kwargs):
+        self.model = tf.keras.Sequential([
+            tf.keras.layers.Dense(units=64, activation='relu'),
+            tf.keras.layers.Dense(units=64, activation='relu'),
+            tf.keras.layers.Dense(units=1)
+        ])
+
+
+class MultiStepDense(TimeSeriesModel):
+    def build_model(self, **kwargs):
+        self.model = tf.keras.Sequential([
+            # Shape: (time, features) => (time*features)
+            tf.keras.layers.Flatten(),
+            tf.keras.layers.Dense(units=32, activation='relu'),
+            tf.keras.layers.Dense(units=32, activation='relu'),
+            tf.keras.layers.Dense(units=1),
+            # Add back the time dimension.
+            # Shape: (outputs) => (1, outputs)
+            tf.keras.layers.Reshape([1, -1]),
+        ])
+
+
+class ConvModel(TimeSeriesModel):
+    def build_model(self, **kwargs):
+        kernel_size = kwargs.get('conv_width', 3)
+        self.model = tf.keras.Sequential([
+            tf.keras.layers.Conv1D(filters=32,
+                                   kernel_size=(kernel_size,),
+                                   activation='relu'),
+            tf.keras.layers.Dense(units=32, activation='relu'),
+            tf.keras.layers.Dense(units=1),
+        ])
+
+
+class RNNModel(TimeSeriesModel):
+    def build_model(self, **kwargs):
+        self.model = tf.keras.models.Sequential([
+            # Shape [batch, time, features] => [batch, time, lstm_units]
+            tf.keras.layers.LSTM(32, return_sequences=True),
+            # Shape => [batch, time, features]
+            tf.keras.layers.Dense(units=1)
+        ])
+
diff --git a/src/models/time_series_model.py b/src/models/time_series_model.py
new file mode 100644
index 0000000..aa99b83
--- /dev/null
+++ b/src/models/time_series_model.py
@@ -0,0 +1,30 @@
+import tensorflow as tf
+
+
+class TimeSeriesModel:
+
+    model = None
+
+    def __init__(self, tracker):
+        self.tracker = tracker
+
+    # hidden1_size=512, hidden2_size=128, l2_param=0.002, dropout_factor=0.2, bias_regularizer='l1'
+    def build_model(self, **kwargs):
+        raise NotImplementedError()
+
+    def compile_and_fit(self, window, patience=2, epochs=20):
+        early_stopping = tf.keras.callbacks.EarlyStopping(monitor='val_loss',
+                                                          patience=patience,
+                                                          mode='min')
+
+        self.model.compile(loss=tf.keras.losses.MeanSquaredError(),
+                           optimizer=tf.keras.optimizers.Adam(),
+                           metrics=[tf.keras.metrics.MeanAbsoluteError()])
+
+        history = self.model.fit(window.train, epochs=epochs,
+                                 validation_data=window.val,
+                                 callbacks=[early_stopping])
+        return history
+
+    def predict(self, batch_generator):
+        pass
diff --git a/src/notebooks/__init__.py b/src/notebooks/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/src/notebooks/example.ipynb b/src/notebooks/example.ipynb
new file mode 100644
index 0000000..1e9eead
--- /dev/null
+++ b/src/notebooks/example.ipynb
@@ -0,0 +1,827 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "papermill": {
+     "duration": 0.019309,
+     "end_time": "2021-01-25T17:44:56.225683",
+     "exception": false,
+     "start_time": "2021-01-25T17:44:56.206374",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "# 1. initial Setup and Imports"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%load_ext autoreload\n",
+    "%autoreload 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-01-25T17:44:56.274544Z",
+     "iopub.status.busy": "2021-01-25T17:44:56.273844Z",
+     "iopub.status.idle": "2021-01-25T17:45:00.930963Z",
+     "shell.execute_reply": "2021-01-25T17:45:00.932314Z"
+    },
+    "papermill": {
+     "duration": 4.688814,
+     "end_time": "2021-01-25T17:45:00.932549",
+     "exception": false,
+     "start_time": "2021-01-25T17:44:56.243735",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "#import numpy for number array handling and represent rgb image pixel values\n",
+    "import numpy as np\n",
+    "from PIL import Image\n",
+    "\n",
+    "#Import and initialize WandB\n",
+    "# import wandb\n",
+    "\n",
+    "#import tensorflow to use any tools needed for deep learning\n",
+    "import tensorflow as tf\n",
+    "\n",
+    "#import keras api needed to implement deep learning techiques\n",
+    "from tensorflow import keras\n",
+    "from tensorflow.keras.models import Sequential\n",
+    "from tensorflow.keras.layers import Activation, Dense, BatchNormalization, Conv2D, MaxPool2D, GlobalAveragePooling2D, Dropout\n",
+    "from tensorflow.keras.optimizers import Adam\n",
+    "from tensorflow.keras.losses import CategoricalCrossentropy\n",
+    "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
+    "\n",
+    "# from focal_loss import SparseCategoricalFocalLoss\n",
+    "\n",
+    "#import libraries for visualization of data\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "#Allow charts and graphics to display right below the page of browser setup\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from conversion import ModelConverter\n",
+    "\n",
+    "from model import MyModel\n",
+    "# from examples.wandb_tracker import WandBTracker, TrainTrackingCallback\n",
+    "from examples.mlflow_tracker import MLFlowTracker, MLFlowTrainTrackingCallback\n",
+    "from metrics import plot_loss, plot_accuracy, print_confusion_matrix\n",
+    "from utils import show_worst_preds, crop_resize_image"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "papermill": {
+     "duration": 0.027768,
+     "end_time": "2021-01-25T17:45:00.990373",
+     "exception": false,
+     "start_time": "2021-01-25T17:45:00.962605",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "# 2. Load and Split images along with applying Data Preprocessing and Data Augmentation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-01-25T17:45:01.056401Z",
+     "iopub.status.busy": "2021-01-25T17:45:01.055577Z",
+     "iopub.status.idle": "2021-01-25T17:45:01.785136Z",
+     "shell.execute_reply": "2021-01-25T17:45:01.784312Z"
+    },
+    "papermill": {
+     "duration": 0.768071,
+     "end_time": "2021-01-25T17:45:01.785335",
+     "exception": false,
+     "start_time": "2021-01-25T17:45:01.017264",
+     "status": "completed"
+    },
+    "scrolled": true,
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "#paths to the train, validation and test image datasets \n",
+    "train_path = '../datasets/kaggle_dataset/images/'\n",
+    "valid_path = '../datasets/kaggle_dataset/images/'\n",
+    "\n",
+    "BATCH_SIZE = 16\n",
+    "CLASSES = ['cardboard', 'glass', 'metal', 'paper', 'plastic', 'trash']\n",
+    "\n",
+    "tracker = MLFlowTracker(\"trash-classification\")\n",
+    "\n",
+    "classifier = MyModel(CLASSES, BATCH_SIZE, tracker)\n",
+    "classifier.load_dataset(train_path, valid_path)\n",
+    "\n",
+    "train_batches = classifier.train_batches\n",
+    "valid_batches = classifier.valid_batches"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "papermill": {
+     "duration": 0.01875,
+     "end_time": "2021-01-25T17:45:01.838639",
+     "exception": false,
+     "start_time": "2021-01-25T17:45:01.819889",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "# 3. Visualization of the images after Preprocessing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-01-25T17:45:01.885615Z",
+     "iopub.status.busy": "2021-01-25T17:45:01.884882Z",
+     "iopub.status.idle": "2021-01-25T17:45:01.888921Z",
+     "shell.execute_reply": "2021-01-25T17:45:01.888396Z"
+    },
+    "papermill": {
+     "duration": 0.03,
+     "end_time": "2021-01-25T17:45:01.889029",
+     "exception": false,
+     "start_time": "2021-01-25T17:45:01.859029",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# plot images after applying VGG16 data preprocessing method\n",
+    "def plotImages(images):\n",
+    "    fig, axes = plt.subplots(1, 6, figsize=(20,20))\n",
+    "    axes = axes.flatten()\n",
+    "    for img, ax in zip(images, axes):\n",
+    "        ax.imshow(img.astype(np.uint8))\n",
+    "        ax.axis('off')\n",
+    "    plt.tight_layout()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-01-25T17:45:01.929599Z",
+     "iopub.status.busy": "2021-01-25T17:45:01.928961Z",
+     "iopub.status.idle": "2021-01-25T17:45:02.763823Z",
+     "shell.execute_reply": "2021-01-25T17:45:02.764347Z"
+    },
+    "papermill": {
+     "duration": 0.857229,
+     "end_time": "2021-01-25T17:45:02.764488",
+     "exception": false,
+     "start_time": "2021-01-25T17:45:01.907259",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "imgs, labels = next(train_batches)\n",
+    "plotImages(imgs)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "papermill": {
+     "duration": 0.025808,
+     "end_time": "2021-01-25T17:45:02.816480",
+     "exception": false,
+     "start_time": "2021-01-25T17:45:02.790672",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "# 4. Building CNN Architecture"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-01-25T17:45:02.877875Z",
+     "iopub.status.busy": "2021-01-25T17:45:02.877237Z",
+     "iopub.status.idle": "2021-01-25T17:45:06.503631Z",
+     "shell.execute_reply": "2021-01-25T17:45:06.503012Z"
+    },
+    "papermill": {
+     "duration": 3.66123,
+     "end_time": "2021-01-25T17:45:06.503741",
+     "exception": false,
+     "start_time": "2021-01-25T17:45:02.842511",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# set the input image size for proposed CNN model\n",
+    "classifier.build_model()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "papermill": {
+     "duration": 0.030793,
+     "end_time": "2021-01-25T17:45:06.952949",
+     "exception": false,
+     "start_time": "2021-01-25T17:45:06.922156",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "# 5. Compile the Built CNN Model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-01-25T17:45:07.027357Z",
+     "iopub.status.busy": "2021-01-25T17:45:07.026725Z",
+     "iopub.status.idle": "2021-01-25T17:45:07.035494Z",
+     "shell.execute_reply": "2021-01-25T17:45:07.034942Z"
+    },
+    "papermill": {
+     "duration": 0.051264,
+     "end_time": "2021-01-25T17:45:07.035597",
+     "exception": false,
+     "start_time": "2021-01-25T17:45:06.984333",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# compile the built CNN model by selecting suitable optimizer and loss function\n",
+    "# myFocalLoss = SparseCategoricalFocalLoss(gamma=2)\n",
+    "# myFocalLoss = focal_loss(alpha=0.25)\n",
+    "\n",
+    "classifier.compile()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "papermill": {
+     "duration": 0.030276,
+     "end_time": "2021-01-25T17:45:07.097660",
+     "exception": false,
+     "start_time": "2021-01-25T17:45:07.067384",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "# 6. Train the CNN model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-01-25T17:45:07.166459Z",
+     "iopub.status.busy": "2021-01-25T17:45:07.165838Z",
+     "iopub.status.idle": "2021-01-25T17:56:09.487184Z",
+     "shell.execute_reply": "2021-01-25T17:56:09.488445Z"
+    },
+    "papermill": {
+     "duration": 662.359554,
+     "end_time": "2021-01-25T17:56:09.488723",
+     "exception": false,
+     "start_time": "2021-01-25T17:45:07.129169",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# train the model with appropriate number of epochs\n",
+    "model_details = classifier.fit(epochs=30)\n",
+    "\n",
+    "# With VGG16: Epoch 18/18\n",
+    "# 143/143 - 35s - loss: 0.3366 - accuracy: 0.8814 - val_loss: 0.3784 - val_accuracy: 0.8645"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-01-25T17:56:09.669548Z",
+     "iopub.status.busy": "2021-01-25T17:56:09.668403Z",
+     "iopub.status.idle": "2021-01-25T17:56:09.679982Z",
+     "shell.execute_reply": "2021-01-25T17:56:09.680599Z"
+    },
+    "papermill": {
+     "duration": 0.105985,
+     "end_time": "2021-01-25T17:56:09.680755",
+     "exception": false,
+     "start_time": "2021-01-25T17:56:09.574770",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# store the losses of training\n",
+    "loss = model_details.history['loss']\n",
+    "validation_loss = model_details.history['val_loss']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-01-25T17:56:09.856889Z",
+     "iopub.status.busy": "2021-01-25T17:56:09.855857Z",
+     "iopub.status.idle": "2021-01-25T17:56:09.857905Z",
+     "shell.execute_reply": "2021-01-25T17:56:09.859525Z"
+    },
+    "papermill": {
+     "duration": 0.094288,
+     "end_time": "2021-01-25T17:56:09.859723",
+     "exception": false,
+     "start_time": "2021-01-25T17:56:09.765435",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# store the accuracy of training\n",
+    "accuracy = model_details.history['accuracy']\n",
+    "validation_accuracy = model_details.history['val_accuracy']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "papermill": {
+     "duration": 0.080179,
+     "end_time": "2021-01-25T17:56:10.016782",
+     "exception": false,
+     "start_time": "2021-01-25T17:56:09.936603",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "# 7. Fine Tune the CNN model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-01-25T17:56:10.141892Z",
+     "iopub.status.busy": "2021-01-25T17:56:10.140312Z",
+     "iopub.status.idle": "2021-01-25T17:56:10.142717Z",
+     "shell.execute_reply": "2021-01-25T17:56:10.143310Z"
+    },
+    "papermill": {
+     "duration": 0.061165,
+     "end_time": "2021-01-25T17:56:10.143447",
+     "exception": false,
+     "start_time": "2021-01-25T17:56:10.082282",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# unfreeze the convolution base of the base model inorder to fine-tune which adapt these pre-trained weights \n",
+    "# to work with the new dataset\n",
+    "classifier.base_model.trainable=True"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-01-25T17:56:10.387406Z",
+     "iopub.status.busy": "2021-01-25T17:56:10.386348Z",
+     "iopub.status.idle": "2021-01-25T17:58:36.150100Z",
+     "shell.execute_reply": "2021-01-25T17:58:36.150833Z"
+    },
+    "papermill": {
+     "duration": 145.836216,
+     "end_time": "2021-01-25T17:58:36.151039",
+     "exception": false,
+     "start_time": "2021-01-25T17:56:10.314823",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# train and fine-tune the model with appropriate number of epochs\n",
+    "model_details = classifier.fit(epochs=10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "papermill": {
+     "duration": 0.045805,
+     "end_time": "2021-01-25T17:58:36.243627",
+     "exception": false,
+     "start_time": "2021-01-25T17:58:36.197822",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "# 8. Visualization of Accuracy and Loss in Training and  Validation sets"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-01-25T17:58:36.342525Z",
+     "iopub.status.busy": "2021-01-25T17:58:36.340772Z",
+     "iopub.status.idle": "2021-01-25T17:58:36.343195Z",
+     "shell.execute_reply": "2021-01-25T17:58:36.343656Z"
+    },
+    "papermill": {
+     "duration": 0.054282,
+     "end_time": "2021-01-25T17:58:36.343781",
+     "exception": false,
+     "start_time": "2021-01-25T17:58:36.289499",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# append the losses to previous stored losses\n",
+    "loss.extend(model_details.history['loss'])\n",
+    "validation_loss.extend(model_details.history['val_loss'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-01-25T17:58:36.444084Z",
+     "iopub.status.busy": "2021-01-25T17:58:36.443528Z",
+     "iopub.status.idle": "2021-01-25T17:58:36.447603Z",
+     "shell.execute_reply": "2021-01-25T17:58:36.446963Z"
+    },
+    "papermill": {
+     "duration": 0.05786,
+     "end_time": "2021-01-25T17:58:36.447709",
+     "exception": false,
+     "start_time": "2021-01-25T17:58:36.389849",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# append the accuracy to previous stored accuracy\n",
+    "accuracy.extend(model_details.history['accuracy'])\n",
+    "validation_accuracy.extend(model_details.history['val_accuracy'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-01-25T17:58:36.554172Z",
+     "iopub.status.busy": "2021-01-25T17:58:36.552802Z",
+     "iopub.status.idle": "2021-01-25T17:58:36.763492Z",
+     "shell.execute_reply": "2021-01-25T17:58:36.763975Z"
+    },
+    "papermill": {
+     "duration": 0.269871,
+     "end_time": "2021-01-25T17:58:36.764093",
+     "exception": false,
+     "start_time": "2021-01-25T17:58:36.494222",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# plot the training and validation losses\n",
+    "plot_loss(loss, validation_loss)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-01-25T17:58:36.872839Z",
+     "iopub.status.busy": "2021-01-25T17:58:36.871372Z",
+     "iopub.status.idle": "2021-01-25T17:58:37.063336Z",
+     "shell.execute_reply": "2021-01-25T17:58:37.063864Z"
+    },
+    "papermill": {
+     "duration": 0.251957,
+     "end_time": "2021-01-25T17:58:37.063995",
+     "exception": false,
+     "start_time": "2021-01-25T17:58:36.812038",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# plot the training and validation accuracy\n",
+    "plot_accuracy(accuracy, validation_accuracy)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Finish tracker run"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "classifier.tracker.finish_run()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Confusion matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "Y_pred = classifier.predict(valid_batches)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print_confusion_matrix(classifier.model, valid_batches, Y_pred, CLASSES)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Print problematic cases"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "show_worst_preds(valid_batches, Y_pred, CLASSES)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Convert Model to TFLite"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "papermill": {
+     "duration": 0.049791,
+     "end_time": "2021-01-25T17:58:37.163896",
+     "exception": false,
+     "start_time": "2021-01-25T17:58:37.114105",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Convert model to TF Lite\n",
+    "converter = ModelConverter(classifier.model)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "converter.to_tflite('../models/model.tflite')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "converter.to_tflite_fp16('../models/model_fp16.tflite')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def representative_dataset():\n",
+    "  for data in tf.data.Dataset.from_generator(lambda: train_batches, (tf.float32, tf.float32)).batch(1).take(100):\n",
+    "    yield [data[0][0]]\n",
+    "\n",
+    "converter.to_tflite_quantized('../models/model_int8.tflite', representative_dataset)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "converter.to_tfjs('../models/js/')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Test model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model.save('../models/saved_model')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# for i in valid_batches[0][0][0]:\n",
+    "#     print(i.shape)\n",
+    "img = valid_batches[0][0][0]\n",
+    "plotImages([img])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from PIL import Image\n",
+    "img1 = Image.open('../datasets/kaggle_dataset/images/cardboard/cardboard10.jpg')\n",
+    "img = crop_resize_image(img1)\n",
+    "img = np.array(img)\n",
+    "img = img.astype(np.float32)\n",
+    "\n",
+    "# img = tf.keras.applications.mobilenet_v3.preprocess_input(img.astype(np.float32))\n",
+    "img = np.expand_dims(img, axis=0)\n",
+    "print(img.shape, img.dtype)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "interpreter = tf.lite.Interpreter('../models/model_fp16.tflite')\n",
+    "interpreter.allocate_tensors()\n",
+    "\n",
+    "# Get input and output tensors.\n",
+    "input_details = interpreter.get_input_details()\n",
+    "output_details = interpreter.get_output_details()\n",
+    "\n",
+    "# Test the model on random input data.\n",
+    "input_shape = input_details[0]['shape']\n",
+    "input_data = img\n",
+    "interpreter.set_tensor(input_details[0]['index'], input_data)\n",
+    "\n",
+    "interpreter.invoke()\n",
+    "\n",
+    "# The function `get_tensor()` returns a copy of the tensor data.\n",
+    "# Use `tensor()` in order to get a pointer to the tensor.\n",
+    "output_data = interpreter.get_tensor(output_details[0]['index'])\n",
+    "print(output_data)\n",
+    "print(CLASSES)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.9"
+  },
+  "papermill": {
+   "duration": 827.092531,
+   "end_time": "2021-01-25T17:58:38.463459",
+   "environment_variables": {},
+   "exception": null,
+   "input_path": "__notebook__.ipynb",
+   "output_path": "__notebook__.ipynb",
+   "parameters": {},
+   "start_time": "2021-01-25T17:44:51.370928",
+   "version": "2.1.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/src/notebooks/time_series.ipynb b/src/notebooks/time_series.ipynb
new file mode 100644
index 0000000..08bc531
--- /dev/null
+++ b/src/notebooks/time_series.ipynb
@@ -0,0 +1,6640 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "2Pmxv2ioyCRw"
+   },
+   "source": [
+    "##### Copyright 2019 The TensorFlow Authors."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "cellView": "form",
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:26:52.778077Z",
+     "iopub.status.busy": "2023-07-27T04:26:52.777713Z",
+     "iopub.status.idle": "2023-07-27T04:26:52.781210Z",
+     "shell.execute_reply": "2023-07-27T04:26:52.780675Z"
+    },
+    "id": "b-2ShX25yNWf"
+   },
+   "outputs": [],
+   "source": [
+    "#@title Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "# you may not use this file except in compliance with the License.\n",
+    "# You may obtain a copy of the License at\n",
+    "#\n",
+    "# https://www.apache.org/licenses/LICENSE-2.0\n",
+    "#\n",
+    "# Unless required by applicable law or agreed to in writing, software\n",
+    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "# See the License for the specific language governing permissions and\n",
+    "# limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "pa49bUnKyRgF"
+   },
+   "source": [
+    "# Time series forecasting"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "11Ilg92myRcw"
+   },
+   "source": [
+    "<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
+    "  <td>\n",
+    "    <a target=\"_blank\" href=\"https://www.tensorflow.org/tutorials/structured_data/time_series\"><img src=\"https://www.tensorflow.org/images/tf_logo_32px.png\" />View on TensorFlow.org</a>\n",
+    "  </td>\n",
+    "  <td>\n",
+    "    <a target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/tutorials/structured_data/time_series.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" />Run in Google Colab</a>\n",
+    "  </td>\n",
+    "  <td>\n",
+    "    <a target=\"_blank\" href=\"https://github.com/tensorflow/docs/blob/master/site/en/tutorials/structured_data/time_series.ipynb\"><img src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" />View source on GitHub</a>\n",
+    "  </td>\n",
+    "  <td>\n",
+    "    <a href=\"https://storage.googleapis.com/tensorflow_docs/docs/site/en/tutorials/structured_data/time_series.ipynb\"><img src=\"https://www.tensorflow.org/images/download_logo_32px.png\" />Download notebook</a>\n",
+    "  </td>\n",
+    "</table>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "GU8C5qm_4vZb"
+   },
+   "source": [
+    "This tutorial is an introduction to time series forecasting using TensorFlow. It builds a few different styles of models including Convolutional and Recurrent Neural Networks (CNNs and RNNs).\n",
+    "\n",
+    "This is covered in two main parts, with subsections: \n",
+    "\n",
+    "* Forecast for a single time step:\n",
+    "  * A single feature.\n",
+    "  * All features.\n",
+    "* Forecast multiple steps:\n",
+    "  * Single-shot: Make the predictions all at once.\n",
+    "  * Autoregressive: Make one prediction at a time and feed the output back to the model."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "XVhK72Pu1cJL"
+   },
+   "source": [
+    "## Setup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:26:52.784670Z",
+     "iopub.status.busy": "2023-07-27T04:26:52.784234Z",
+     "iopub.status.idle": "2023-07-27T04:26:55.568564Z",
+     "shell.execute_reply": "2023-07-27T04:26:55.567878Z"
+    },
+    "id": "7rZnJaGTWQw0"
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Matplotlib created a temporary cache directory at /tmp/matplotlib-bp4j7gib because the default path (/.config/matplotlib) is not a writable directory; it is highly recommended to set the MPLCONFIGDIR environment variable to a writable directory, in particular to speed up the import of Matplotlib and to better support multiprocessing.\n"
+     ]
+    }
+   ],
+   "source": [
+    "import sys\n",
+    "sys.path.append('/app/src')\n",
+    "import os\n",
+    "import datetime\n",
+    "\n",
+    "import IPython\n",
+    "import IPython.display\n",
+    "import matplotlib as mpl\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import seaborn as sns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:26:52.784670Z",
+     "iopub.status.busy": "2023-07-27T04:26:52.784234Z",
+     "iopub.status.idle": "2023-07-27T04:26:55.568564Z",
+     "shell.execute_reply": "2023-07-27T04:26:55.567878Z"
+    },
+    "id": "7rZnJaGTWQw0"
+   },
+   "outputs": [],
+   "source": [
+    "from dataset_loader import JenaDatasetLoader\n",
+    "import tensorflow as tf\n",
+    "\n",
+    "mpl.rcParams['figure.figsize'] = (8, 6)\n",
+    "mpl.rcParams['axes.grid'] = False"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "TokBlnUhWFw9"
+   },
+   "source": [
+    "## The weather dataset\n",
+    "\n",
+    "This tutorial uses a <a href=\"https://www.bgc-jena.mpg.de/wetter/\" class=\"external\">weather time series dataset</a> recorded by the <a href=\"https://www.bgc-jena.mpg.de\" class=\"external\">Max Planck Institute for Biogeochemistry</a>.\n",
+    "\n",
+    "This dataset contains 14 different features such as air temperature, atmospheric pressure, and humidity. These were collected every 10 minutes, beginning in 2003. For efficiency, you will use only the data collected between 2009 and 2016. This section of the dataset was prepared by François Chollet for his book <a href=\"https://www.manning.com/books/deep-learning-with-python\" class=\"external\">Deep Learning with Python</a>."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "R81Wx8WP4c3G"
+   },
+   "source": [
+    "This tutorial will just deal with **hourly predictions**, so start by sub-sampling the data from 10-minute intervals to one-hour intervals:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_loader = JenaDatasetLoader()\n",
+    "data_loader.load()\n",
+    "df = data_loader.get_data()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:26:56.101037Z",
+     "iopub.status.busy": "2023-07-27T04:26:56.100775Z",
+     "iopub.status.idle": "2023-07-27T04:26:56.951664Z",
+     "shell.execute_reply": "2023-07-27T04:26:56.950968Z"
+    },
+    "id": "TX6uGeeeWIkG"
+   },
+   "outputs": [],
+   "source": [
+    "# Slice [start:stop:step], starting from index 5 take every 6th record.\n",
+    "df = df[5::6]\n",
+    "\n",
+    "date_time = pd.to_datetime(df.pop('Date Time'), format='%d.%m.%Y %H:%M:%S')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "VdbOWXiTWM2T"
+   },
+   "source": [
+    "Let's take a glance at the data. Here are the first few rows:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:26:56.955562Z",
+     "iopub.status.busy": "2023-07-27T04:26:56.955283Z",
+     "iopub.status.idle": "2023-07-27T04:26:56.973896Z",
+     "shell.execute_reply": "2023-07-27T04:26:56.973342Z"
+    },
+    "id": "ojHE-iCCWIhz"
+   },
+   "outputs": [
+    {
+     "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>p (mbar)</th>\n",
+       "      <th>T (degC)</th>\n",
+       "      <th>Tpot (K)</th>\n",
+       "      <th>Tdew (degC)</th>\n",
+       "      <th>rh (%)</th>\n",
+       "      <th>VPmax (mbar)</th>\n",
+       "      <th>VPact (mbar)</th>\n",
+       "      <th>VPdef (mbar)</th>\n",
+       "      <th>sh (g/kg)</th>\n",
+       "      <th>H2OC (mmol/mol)</th>\n",
+       "      <th>rho (g/m**3)</th>\n",
+       "      <th>wv (m/s)</th>\n",
+       "      <th>max. wv (m/s)</th>\n",
+       "      <th>wd (deg)</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>996.50</td>\n",
+       "      <td>-8.05</td>\n",
+       "      <td>265.38</td>\n",
+       "      <td>-8.78</td>\n",
+       "      <td>94.4</td>\n",
+       "      <td>3.33</td>\n",
+       "      <td>3.14</td>\n",
+       "      <td>0.19</td>\n",
+       "      <td>1.96</td>\n",
+       "      <td>3.15</td>\n",
+       "      <td>1307.86</td>\n",
+       "      <td>0.21</td>\n",
+       "      <td>0.63</td>\n",
+       "      <td>192.7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>996.62</td>\n",
+       "      <td>-8.88</td>\n",
+       "      <td>264.54</td>\n",
+       "      <td>-9.77</td>\n",
+       "      <td>93.2</td>\n",
+       "      <td>3.12</td>\n",
+       "      <td>2.90</td>\n",
+       "      <td>0.21</td>\n",
+       "      <td>1.81</td>\n",
+       "      <td>2.91</td>\n",
+       "      <td>1312.25</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>0.63</td>\n",
+       "      <td>190.3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>996.84</td>\n",
+       "      <td>-8.81</td>\n",
+       "      <td>264.59</td>\n",
+       "      <td>-9.66</td>\n",
+       "      <td>93.5</td>\n",
+       "      <td>3.13</td>\n",
+       "      <td>2.93</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>1.83</td>\n",
+       "      <td>2.94</td>\n",
+       "      <td>1312.18</td>\n",
+       "      <td>0.18</td>\n",
+       "      <td>0.63</td>\n",
+       "      <td>167.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>996.99</td>\n",
+       "      <td>-9.05</td>\n",
+       "      <td>264.34</td>\n",
+       "      <td>-10.02</td>\n",
+       "      <td>92.6</td>\n",
+       "      <td>3.07</td>\n",
+       "      <td>2.85</td>\n",
+       "      <td>0.23</td>\n",
+       "      <td>1.78</td>\n",
+       "      <td>2.85</td>\n",
+       "      <td>1313.61</td>\n",
+       "      <td>0.10</td>\n",
+       "      <td>0.38</td>\n",
+       "      <td>240.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>997.46</td>\n",
+       "      <td>-9.63</td>\n",
+       "      <td>263.72</td>\n",
+       "      <td>-10.65</td>\n",
+       "      <td>92.2</td>\n",
+       "      <td>2.94</td>\n",
+       "      <td>2.71</td>\n",
+       "      <td>0.23</td>\n",
+       "      <td>1.69</td>\n",
+       "      <td>2.71</td>\n",
+       "      <td>1317.19</td>\n",
+       "      <td>0.40</td>\n",
+       "      <td>0.88</td>\n",
+       "      <td>157.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    p (mbar)  T (degC)  Tpot (K)  Tdew (degC)  rh (%)  VPmax (mbar)  \\\n",
+       "5     996.50     -8.05    265.38        -8.78    94.4          3.33   \n",
+       "11    996.62     -8.88    264.54        -9.77    93.2          3.12   \n",
+       "17    996.84     -8.81    264.59        -9.66    93.5          3.13   \n",
+       "23    996.99     -9.05    264.34       -10.02    92.6          3.07   \n",
+       "29    997.46     -9.63    263.72       -10.65    92.2          2.94   \n",
+       "\n",
+       "    VPact (mbar)  VPdef (mbar)  sh (g/kg)  H2OC (mmol/mol)  rho (g/m**3)  \\\n",
+       "5           3.14          0.19       1.96             3.15       1307.86   \n",
+       "11          2.90          0.21       1.81             2.91       1312.25   \n",
+       "17          2.93          0.20       1.83             2.94       1312.18   \n",
+       "23          2.85          0.23       1.78             2.85       1313.61   \n",
+       "29          2.71          0.23       1.69             2.71       1317.19   \n",
+       "\n",
+       "    wv (m/s)  max. wv (m/s)  wd (deg)  \n",
+       "5       0.21           0.63     192.7  \n",
+       "11      0.25           0.63     190.3  \n",
+       "17      0.18           0.63     167.2  \n",
+       "23      0.10           0.38     240.0  \n",
+       "29      0.40           0.88     157.0  "
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "WRzj1inMfgcO"
+   },
+   "source": [
+    "Here is the evolution of a few features over time:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:26:56.977105Z",
+     "iopub.status.busy": "2023-07-27T04:26:56.976726Z",
+     "iopub.status.idle": "2023-07-27T04:26:59.434254Z",
+     "shell.execute_reply": "2023-07-27T04:26:59.433627Z"
+    },
+    "id": "Vg5XIc5tfNlG"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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hTKRm52HZQesDFJ+l5+LYnWc4cvsZlh+6i+8P3EHM170klFBacvPVGPebfkXFXla+W0/SUMzbwynvCYehYlwE/b08dJNvV4MsrE6ONjJwYdQtbD4bZ5GSIUSn+Qcx9z/5rT/m0Crv9ow+VXquxAK1BlP+uoQtPMnI+SowWUKf749Z/dk3VppeTlYi762PRl6BGmdM3E+WWBW19Fh8xOB9Lku5F5OZwFG8tvw4kjNzzfrySoGQEfLUvecYtOoU2rAyVTgTX/9nmSsNH4NXn8LyQ8rMyqHRaDB83RmMKXT7+evcQ+y+ql/xS7VToYxuiw473T2RnVeA307H4uDNRIcYkuKSMtFgxh6zrjzODCmsCiQjJx/H7z7TJXY3xYZTsVgYdQtL9t3Gp39e0mUIsIX7zzKMKmw4C0kZuXhoImeopaw5dh9ZuQX48eBd3ElMw9X4FCTb6HYhJTsvxeO303G8aYWOOulyolw8z8i1S2qzO4npOHH3ue55zmHlW5QyaNJWzsS8wNL9hql1tMEzV+OlDS4S6tlO35d/KdmWSap2aV9Kei05gt/PSH9ca3j4Igv7byTin8uPkZ1XYJQSz1TqMym4keA8QUrf7b2NKX9dxtC1Z/DPJfsHom6JZgKGueVcXQlSWBXG4VtPUe+L3Ri06hS+3S1utm7pcq8lqNUa5IqMsFcCTWdFod03ByQ73vqTD/Ddvlv4ZtcNRCw8jF5LjqLxl1GSHd9W+KJxswoj06duvewwOZzBH0tMyi17+ZW+ueqk3s/XARZMa/n38mO8ybKOD1zBLOX3WiKtD7jQbyH3pZn733U0n7PXodlSzCl5V+NTMWnLZUWkjMtnKfN8afHsZWHV8iTVdh9yR+FoK3lmnnJWa+yFLArr3Llz0aJFCxQvXhwhISHo27cvbt40zPGXnZ2NMWPGoGTJkihWrBgGDBiAJ08sq17kbOTmqzFkjT5Kf8Whe1i677bdZ62mePn7o2g2O0qwCocjiH2eaWTVZFtBsuwoW06eGudjk422K9FVQKPRYPr2K6gzfRe6f3fYoef+6aj8QVcajQb/2xCNKX85TlG3hD+doIb845Rsg+fJXr7fh2/xW/8d4Y5gihWH7iEpIxfLDvIncZeSu08zcPzuM1Sf9p+o9k1nRWHDKXmLL7ADytzdVDgXa+g+s+54jGDxACnwdFHfTCm48sh5rM/WIovCeujQIYwZMwYnT55EVFQU8vLy0K1bN2Rk6FN6fPjhh9ixYwf++OMPHDp0CPHx8ejfv78c4jqMfLWxYrog6haqT/sP/ZeJ8yf89aR0S0dHbj/F1fhUpGXny1alJD45C+3nHTCyam46E+eQ8wul7Mnj+a3k4Fm6XpGf/c91/FIYRFNUIrLZ3HuWgX8vJ+C307G8Ewq5DVRCGRmKIlvOKVt511oS45KYSoFxSZm4Fp8q6WrTkn23MWjVKdHtX2TmYdrWK5Kd3xrYz5UKwH9XEozaLBDISiIFX+68BgDYfDYOu3jOTbg2smQJ2LVrl8H7devWISQkBNHR0Wjfvj1SUlLw008/YePGjejcuTMAYO3atahTpw5OnjyJ1q1byyG2rJyLTcaZGMf6plyMS9a9/vfKY7SrUcqh5+fKwMaRA96jF8KJ4eXme1Y5PyVYOeWE7fOdnpuPAB9Pg/1y28STeNw3kjJyUTaQIp+1sJeZs3IL4OvlLoscG0/FYtYr9fH2T6cQ8zxTVy2wW90yssjDZu6/13EmJgm/jWoNbw/HXp8C1qxP0Ppux5nhjYQ0PErOwqd/XgIARWRQiEvKxO9n4vBOm8ooXdxbbnFcGkX4sKakMA79wcHBAIDo6Gjk5eUhIiJC16Z27dqoWLEiTpwQnx7F1bAkNYwUzN+jnynHPpcnEXSSQIAT38KQvVwnHiUrV2El9LDviZ0XnaPalpQrIq4A2yOgzvRdwg0l5ExMElrO2Yv/OBXaHr3IQgyn3+OWN5aDFYfv4VxssiwWxoM39cv9kQJuR9esqJJnCUqrojVwxQl8f+AOxm50zoIpzoTseVjVajUmTJiAtm3bon79+gCAhIQEeHl5ISgoyKBtmTJlkJDA/5Dm5OQgJ0e/5Jaa6vr+HI5Erojzb3eJr19+4Kb9fKe4yL28TJhGw2NPVULQSu+lR9CgfBBri/wymePgTdszj4hFDhdFrSHgfSer0CYmi4yU5OarRaXtyiuwr1zm3Jwfp2QhpLgP3B10Mz0uDNBz5eh8pSC7hXXMmDG4cuUKNm3aZNNx5s6di8DAQN1fWFiYRBIScqLNMyuGK48cV9d7/u6bOB8rj18vYZ5LcSn4fv9tA59DJaiGVx6l4rfTequqAnRoswxde8Zh52L7ZNubfy49FixNDPBPepSEo+8dvhgLOVCx1lJ2XjIswX3szjOEz92PYescd88qlQM3E7Ht/CO5xZAUWRXWsWPHYufOnThw4AAqVKig2x4aGorc3FwkJycbtH/y5AlCQ0N5jzVlyhSkpKTo/uLiHBOUQziOjvMO4NUfjyMuKZN3lr3Yjum9uKw+eh/9lh132PkIy/j9bBzm77mFdcfv48qjFMUtIxL8WFNJzFrGbDzn1IFwjs7hq5TJVTzLRYtbyEObR9memQqchWFrz2DC7xcQlySPO589kEVh1Wg0GDt2LLZu3Yr9+/ejSpUqBvubNWsGT09P7Nu3T7ft5s2biI2NRXh4OO8xvb29ERAQYPBHuBYxzzNx9sELTPj9gmKi4IXSff19Md6pkly7KutPPkDvpUcR/vU+PE52XG5NsShFCZCDR8lZWH3knknFS043jvvPMsw3kpEZO6455Dy5+WqHux+Y4jJrJS36gX6VKzU7z8DHWAkuQHLBrqD33IUm67IorGPGjMGvv/6KjRs3onjx4khISEBCQgKyspiZU2BgIEaMGIGJEyfiwIEDiI6OxrBhwxAeHl4kMwQogWB/L7lF0BH94IVRhRW5qP25cWDIsTvPMP638+j+3RGeTxQ9LsQl49YTeSYYcUlMn5Kdp8bBW47zxXQGEgVStjmKtl/vx+x/rqPNXOGSm3LqSY50hVAq2XkFaDY7Cj0WOzavsymEVtImb7lk8H7bBfmWw3dcjDffyI5sZqV9dCXFXZagqx9//BEA0LFjR4Pta9euxdChQwEAixYtgpubGwYMGICcnBxERkZi2bJlDpaU0OLrKU96GWdjxaG72HedFCMA+HzbFdQtF6BL5H91ZiT8ve3X5ZgLxqCU44bkKKSCXVqO8ORTrdHAnX452bj+mMnDnZZtnwISUsLNmvDb6Tj0a1JBoLV9iEvKxD+XH4sKTrMn7AIP/15+jCYVS8gojXTIorCK0fh9fHzwww8/4IcffnCARMpAyRMhb0/HG+MtmRkqYRYZ/eAF5srcUSmJ9ScNq/LU+2I3bs3uAS8PmVzn5a77yYPSA3scxaPkLFx+aBw0qYDHusiRkpmHpftvo2+T8gaVx5T+U3Ct8TfsnF6Lj5e+la4suC2wLbxH7zyXURJpkT2tFaFHyT5TLSsHO/ycg1eLrwLTfLZwtK+jeJbu2AAOOUv2Wsuxu8/QqVaInY5uWiGd+fdVO53XObkarxwf67Zf87sFfP3fDdQtF4BXmznWUuZqpOfkY92x++jZoCyqli5msu2sf67hz+iHWH30PppV0lvmkhyYwUEKUhXiNiYHF1mTPyUYc6RC9rRWhJ4DN5S7lCxU5ep87Au0mbsP/1ySPlH78bviZ4ZyO5Y/Sc3G6PXRdj9Pek4+Bi4/gZ+O3ndo3llXIF9BgSNa7D2WHL71FH2+P4rrPNam9361//1qK2uO3cfHf1yUWwynZ84/1zF/zy10WXjIbNtrrIkMO6hp81nny7yTYcLdpCix60oCluy77fTKKymshCiESgCOWh+N+JRsjCniVT6WOCil1rpj93E6Jgmzdl6TtK65w3Du/lJyLLkcdxLTBbNSCDFkzWlcepiCkb+ctUwwwqU4W1jW2xZ9RcnuK38JlOruvfQo7/aUzDzcfap8v1wpuJGQhvd+jcbCqFsWGYGUCCmsCkK53YEwTqk02QFHpX3JyNUrLM44SdhzzX7lJC/GJdvt2I5k3/UnOgVDy9HbzxCx8JDgAGyO5EzH5uyUGksKiJhCo9Fg7MZzmOEi7iHdFh3ClyLSW1nSOwm5eivVOHfi7nNM3Mxvhedzs/v15AM0+nIPuiw4hHtFRGnVkpimvNR+lkAKKyEKoaWELAstPqbIL1Bj2NrTWLzXcQUApGLTGccsl/109L5DzmMvfjst/XW69DAZR24/xX8y1Fa3Fe5j9Sg5CyN+PotXC8uFatGm6LmTWLQGWC1iJoQ5+QX4/UwsHr4wTpT+JDUbGo0GFx+mYOelx1hXmGDeUQT42Cdc5NaTdKw5dh9fbL+CJIncooQUVqVkleAyb7fpQNecfGaMys4rQGJaNj7bdkW370xM0SqnqlYDyZm52HwmzuLVGiVACquCkFL5swfP0nOwZN9tPE7RVxphW1iv2RjEsff6Exy4+RSL9t6y6TiOxpEPvitZtAvUGuy+moCnNlYb6vP9Mbz902mD+9JZSUjht4CYKot+JiYJlSf/g56LXTfvr1BdeI1Gg38uPcaBm4lYvPc2Jm25jHbfGEZq77wUj1Zf7cMnf16SbZC+NCPSrsf/+cQDTNt6Wff+4YtM/H0xHupCRV8K30VHTJZ/H2V5nnVz8Qu5+WpsPBWL2p/vQss5+wz2ufFo53cS0/DLiRjksYJauddP61Lwvh39wCPrlZH8mBoAHeYdxKdbLvHmEFc6lCVAQfx48K7cIgiy5th9TN16Gc/Sc7Ew6hbuftUTFx8mG7Tp/+Mx3JjVw+pzKHUGb45fTsTY9Pm8AjVO3nuOZpVKwM+r6DySPx+PwZc7r6FUMS+c/ayrzcd7LKDsORNCimlCqrBS/1qhNfaaiTQ+ageu556c0gVf/Xsdf0uYPJ3vumw9/xAf/s6/FFyg1uiU3EVRzAT4z+iHLp1tgF39T6u0Z+Xm4/UWFeUSyWJaVS1p8WfyRIwbU1nKPBvuREij0SBiIVMk4Vl6LiZ2rYlpWy/j0K2n+PeDlxDg4wkAaDY7yu5BnPY4vEajkcy9Rg7IwioDD55noOfiI5J26Pbm5L0kPGOlNTlwIxH9lx03aJOd55wKp63Yusy9KOoW3v7ptNksA1m5yrbAW8re60wZxWecdDmJadmY8881i/3LnDEClhvIohJYj7W1Nnqmg+6dCRE1EBrog89715X0uA9fGFvPhZRVAHjEas++wsrLxCsdfPf/scIcnGxL4rnYF0bt2KgceJV61A+1+RgFZp57U64S3CwCVab8q3utDaTdcCoWD19k4c+z+sAuR2QccVNJX2GST+qElGy8vuIE/rssfaYfqSGFVQam/HUZ1x6nYvxv5+UWxWp2X+X3F7RlyVposFY6tipKvxYm2D9y+5lu2+Yzcag8+R+DZT5XcgcAhH3lpv51BauO3DcbYKTRaPDZNv31cT51FfjrHOObqtFokJNfYKAqOKMCPiGiJgDA10vaynjcKkbmELIo/+4gX3M+fhjU1OHn5LsO5gLOHJkN4OsBDW0+hjkFW8idBIDZQi/pLIXWUYG1Wnw93fH32LbSHpTzFV5k5OKLv6/g1P0kvL9B+UG8pLDKQLoL5Ib7I5o/jcjqo/ccLIn8xDw3DvIQS4Faw5vg+tPCutgbTsXq/O5ULvK0PkrOwoAfj+usP1wuP0oGYN4qeOzOc/x6Mlb33lkj4StP/gdVpvyLWp/twqNkvWVQaHw8eDMRyZnKTuIu9dTTUuVdqPVf5+WrL9+rYVn8OLgpaoSYTtxvLXzfWXvZ2PuaminTeeWR4wpKBPp6Gm2rWzbAomMkpJp2Bfp2103Bfeb6mPasylWO9n8uE+iDCiX8UK+cZdfDFFxrdJNZUXjB6TfVCsxXrcVFhkDngt2Z/3w8BpO3XHJKawofl+KMyyuK5eoj6z8rFdvGSDyjNcOnf14y2uZqS/9cXvpmv0FCci5ilySTHKi0vdyonNk2TSsG2Xye/7GsHEJ9wtC1Z9CP446jBBpWCLTbsa89TjPfSAiZu1a2wtGjQVlETezAG1DTra5tQTZ8t8s/lx/jOacCH999paQE+3UsVFjNIdb1jq/fZbsTLCj0hRYKjJScwp9p7bAWkh3SnC97fHIWms/ZazbzglyQwiozX/x9FZvOxEleJenIp510r1cPaY5+TcpLenwhbFlOWnFYfuus1BMHc7PVLTwJr4WuoaXLokpFqgn8qXuOS4LdsLx5ZczfW9qAuWwTLiC2lnG2R+BFqyr68s1Se/do/Z3FohQDwMaRrbCJJ/KdLzp95ZDmqB1a3OpzCfUbc/+7YZAOjfv8LYy6hXpf7MaeqwmKuG7B/sZWV0cQ81zcM5Wvlt41K6S4t9E2jW6fj2TnMdf3Loy6haSMXPxwQJkB4KSwOgC1WoO0bNMDxJ5rlnXI5ggL9kPM170Q83UvRNQtg0WvN5b0+EIoeDXBiMszuqEYR8mQWvw8Czu3ArXGyFKifc8XeOIIzn3eFW+2tG+kMfsZETvp2XAq1nwjiahSyt9o28KBjVDCTz+4fhpZW9Jzbjptv+8npT/e2E7VUTbQB6M7VNNtc2TgDh/sb5eRK5/1sE21UijuY6yA8SmsAPDjW82sPldBAfOtG3+5x2B7S9ZEAjC2smmDi0atjzYIOpICa4KqmphxWbAXYnT1RVG3cDPBBms/D5VL+qFckC+PPNIPpnwGFPadeJQVR6FESGF1AG+sPIkGM/YgLqnQ19HOwUXleW5+Ngtea2S3c0dde6LoaMO3WusVr+I+noj+PALFWUm9KwX7SXq+/ALLOp307HxdkngtqWYmO7ZwbHJng/cfdKmB6ZwI72B/L8zt3wD+EgfSsKk69V80mLEHu648tjkvqz3oUicEX7xc12C5sn/TCgZW1RpliqFtdcvT8ghx7I79Bg8pB8OPI2vh+OTOKFVMbyXydDfs485Mi8DKt5vh5JQuVp+HvRQbZWaC/8vxGJ0V+YmJlGByMbgV/wSQb2IklvjC68P15eYGa7L9pO1NRB3L3Rx61A/FotcbYe/EDnaQSBgxE+XF+25jxM+2lzle8mYTFPP2QP3yAVg1pDnGda5uLI/IR7RSSfFj1hc8AXen7uuLJ5jzB5YbUlgdwOnCahrbCxWReDt3GCNfqsK7fee4dtjwbisMaFYBO8e1s9v5tdGGqdl5iH7wQhHLTFomda+N8V1q4L8PXgIAeHu449jkzlg2uCn2fdQBJYsZL83YAjdXrTk2n43DDY6/Xquv9uFJarZd/MzKB/nil+Etde/HdKqO4e2qoCRPOhU/iZe8+Xjv13MGVvoVh+46JNjht5GmE5arVCoMa1sFLSobWn+8PPRdqI+nu6SWxQM3bUtl5Ui4GT483A2HltLFvdGtXihCA30wvC1//2QObcUiABj5i2ml4ecTDzBo1UlEP1BmJaOmlRxnRfx8+xWD9wcdeF/1aGBsYeXmwl09pDkAYO1QxldTpVKhX5MKqG6n4DQuKw7dxbe7bjis9OzGd1uhT6NyuDIzEjvHvYQaZYob5N/Wuu+906ay2WN5ubvprltRgBRWO8Ou3etWmF7D3hakdjVK8W6vXz4QbauX0r2WOlcim9x8NRrO2IMBPx5XlO+lv5cHJnataWApC/DxRM8GZVGtNNNBftS1JtpV57+GljJo1SmLll9XHrmHCJ7gi1Zf7bNbpRn28qRWAetYK8So3eohzVHZgtm8FMz97wZvRRZTQVvWINayVaGE6dULvqhnW5n733VJjsNW3mzJy+rj6YbWVYPNtgsL5r9Wg1vb5l4iNsvK1fhUDPjxhPmGduLAxx0F9/l42m+1gouc9gIPN0MV49sBDfF577p4J7wS/vpfGwBARN0yiPm6FzrVNu5zXhIYy6Rk7n83sOzgXTywIduLWK7MjEQbnrGFPd9bOLARbs7ujjARq30bR7ZC1dLSKfalJDbYSA0prHZCa1Wc+pd+drvhpP197ja+2wrVQ8Q57o9oZ2zpGNa2stlBWQwrD+udtnfK6CLADj4DxHljjOtSA7++20oyGSxx0n+almP3qkRlAxknfm1Ud/3yjPLOTlf4YdcaCPLzxNhO+qWqRmFBOPiJ4fWUiz8F0qpZC/ear3i7GU5P64LWVYPxzYAGuu3vtKmMIeGVsK4wcnfeq43g5e6Gz3rVAQDJJ4HP03Ow4hB/MCKf5TnWxKB7PjZZ9/o3K/1jZ/etj7OfdcXaoS3xdutK+HWE8HPSOIzfiijkv2kObSWzF2ZKccpF7dDi2DmuHf4d/xLuzOlh9fI+XwCOs8L+qfd91AEDW4Qh0NcTM1+pbza9FmCbT6+lJGfZ/77ixkxoYT8RKpUK3h6mJzQ/DGqKiV1ropnElvpyQdIFeNmDolMH0oGk5+Sj15IjaF+jtN5vFYzvkL2TD/PN3kxRtbQ/7j1loiM3jw5HyyrBaFWlJN6zsUby/D23dK/F5HVjR7FKSViwHwa3qujQAB1bKbDQ79VSSvh5Yd9HHeBT2CkG+Xnh7GcR8GVZfSqU8MO5z7rqVgXk5pcTMRgSXln3fp+FUePm4F7xyHrMUuamUeEG27093PHlK/V175tVKoFrX0bqlsBDA31Qp2wArpsokyqW2qHFsfuq8PecsOkClr9tOKC3n3cAMV/3AmDsp8p+m2Wlm0VYsJ9u0J3Vt77JtrNeqYcKJXzRn5OhxNpb6o2VJ3FlZiTe+umUdQewIxemd0WQn/VVidpU0/s+t6tRSldQQsuUHrXNJrkHlJdD052lsZbyt1wRF1Lw7MHsndKsZFhDRQtWrsKCfdGrYVm7yPE8XZmTQS1kYbUDW889xIPnmVh/8oFRlLiS/DkBwwAtbTSp1DFhYiyG3b87bPA+UQLnb60Cxp6tWlJNa2afejbLYA32Lvs3rVcd+Hl5GCijpYp5G6VlElJW2cvBQv7SUjN9u2GwQKLEbjW2DPRcf02pKOHnhVtPhCOSdwlUm9Ni6rFbeyzGKplaVTHvCqAlyM8Lk7rXRo0yhis+1lpYAaD+F7sdsnRrKbYoq4ChJZHPD5qdgcEU5sqUcrG3tdrNTYWd49phy/vhCPSzzV1m8+hwyVy1+LB2EicFZQN98fuo1rrYCiH8vNyx5f02dpODHZDn6MpeYiCF1Q6wFQ6t9VKLFLdARJ0yeL+juA7MHPXKGeeXlNqmJjRry8otQMyzDMQlZRopaa+tsN73rGnFIHSuHYLjhRHw1o6PYpzexWDpHMXuVvhqtkWysycAjrTAbr9gvypFJYtJV7P7lcbmiwyIIbfAtnyPOZzo8Dn/Xrc6cO/GrO64+1VPSXwvS7vAkjd7ud9cVhYhfhneEp1rh+DElM4Gvs+2GAws7TsszW9rDfXLB6JZJfETHS57J7bH9jFt0bJKMP4n0binRFpVLWm2aMKrzSqYzMvaXEIXgR0iCy44ElJYJebhi0zM3HFNcL+tCb8BYPU7zfFxt1r4qp/et65Xg7K4P7enxcf6oEsNfNClBv4Zb7+sAWcfvMC5WOMgmYiFh9Bx/kH8y+PjaosVpWeDslgztAVKFEa6a302paJ/0/J4jRPpKiX2SEzNHgQtsTLzwfY9C+DJMWkvPth0wW7H9vPykEyRerddFYNn01ryCtQ2WSOXHbxjtK3eF7utOpanu5vJmuyW4OPpjpNTutg1vZ69aVIxCAsHNkLNMsWwwUp/9/Y1S2PN0BYoG2io8NpylV+3cKIvdf5ve1A9pDgahQUxb5ThoeRwtAUlzE2GAyQM+pQq2FNKSGGVGHZpRT4uxCXbdHxtgIy7mwqDWLn8gvw8rVJEfL3c8WHXmgaW1pplrK+2IsTPx2OMtmmXH8T4ZlnCW60rGbwfEl4Zg1tV1KVPsZUvetezqKqR1sL63+XHZoNdAn09Jbew+nm5Y9RLVSU73nsdq+KzXnWwd2J7DG1T2cDC5IioXings0RIVbPbw93NqoTpXHLz1TZVjjtxV7pKYFIpq1pCA30QEuC8ltahbSqjf9MK2PNhB1S2IXcqH+xuvFFYEG9wrBAXH4orbx3zLAMX45LN5rNVGnIXpJCL7WPb4sinnQQt1d8OaIhXm1VAbwl9W5WYv5gUVom5ZKbD4KsdbwmTu9fh3d6qqnQJyyuX8sfA5vaxIMY+z7R7LWbusqWXhxvm9GvAmy7KGgL9PFHRggIDGmhQoNbg/Q3nMOWvy7htwi+xVmhxyX1Yp/Sso0sZ4ydB8n9vD3e8+1JVVA8pDn9vD4PiA1UlHrztQf+m5fHHe+HmG9pACX8vzOlnOijJHDcS0qz2NQWEfceVYjnxspPvr705+1kEGlYIstvxQ1kW1+1j2uoyT7zePEyyc3ScfxCv/HBMsuM5CrHuF7XsYHSxlSk9rK+E5+3hbjLN1cAWYZj/WiODdIQeCgmYlRLn7DGKANxqQ1q4Fpcjn3bC8rea4mWJowa/fbUR7n3V0ygtlC2kZOWh/bwDaD13n2THtDd9GjFLMHs+bI83W1bUpXmyZCabkVNgkI+366LDmLeb36qcX6CW3MJaPsgHrauWxPYxbXFsUmfzH7CCLe+3wdA2lfFxZC27HF9K6pcL5F2NkDqH6uBWlcw3sgM1p/2HUb+cFbyPuGmyPjHxm418qQouTO8qqXxaWlS23q/RkUTUMcwPau9cle91qIr+TcpjJScDxDevNrTreW1hxst1cWlGN4NtH0bUlPw8YqPp572mnGu15f02GN+lBoZZWTDDEoL9vXB1ZiTuzOmBO1/1xNphLeyWUUAOKK2VQhnergq+3GnsC8sdg8KC/UQlGLYGNzeVpMdm54hUWrYEIZa82QSLXm8MdzcV5vZn+SVaMHldd/y+rnqJlh8O3MXH3YwVhbwCjeQWVu2l1vmB2YFmlUpInhPQXgwSKIs5rWcdPHqRZeRSYgtlArzxJDUHPw9vieuPU/G1xO4vAJPIPztP7/ecW6C2yDexUYUgfPFyXczccQ2vNqtgkON2Wi/7FRdRSso0c9irfxXCz8sDC19v7NBz2kqzSsEGXeLxyZ1RzspgNCmQYiVJKppWDHJo38h2V+tUKwSdaoXgn0v/OOz89oQUVgVTrbQ/7nKzDDiJoscHe4ly+Lozkh9/47ut7DK48PrvWfAz/HDgLrrWNfZp5FMq8grUSMlUdi48c7SsEozT95VZEhMwdhnpWVg+MiTAB39KnDLm8KedkJ6dj5LFvNE4LMguCitbWbWWoW0q46UapVClVDF0q1sGU7dewZI3GtsunBNSs0wxuKlUuJHAuO6w/SaL+9CQyUeDCoFQqzXwdFchr0CjgEwQypkM2RrkSuhRtEvADz/8gMqVK8PHxwetWrXC6dOn5RbJofwyohVaVw3GmqH6YCElqqtTe9YWFZTBVljtUSe9TfVSDreGiIUvndDo9cbFGW4kpBkUXZACR89xfhvZ2m7HvvJIXFCJJZSwMYemKbw93FGycAlZ6nGrhI15LbVooIFKpUL1kOJwd1OhW71QnJnWxeIiJK7C76PCMZwV6BTgq1dSTblPFHXc3FS4PCMS17/sDk87+ie3r1laRCsljpSErShWYf39998xceJEfPHFFzh37hwaNWqEyMhIJCYmyi2awygf5ItNo8LRubY0wUL2YlT7ahjetrLZdvZML9qkYpD9Ds5DSQv92MTWP7cHdSWKfheL1BHlbJ6l50i2yqDNFPB6C+mCWUzh6SZtdyuVr3NxntRkclqF1haWvZWLEv5eBva5d1kZNhxZeckZ8fF0h6+dl+OV5ElS3Mz9YElwLmEexSqsCxcuxMiRIzFs2DDUrVsXy5cvh5+fH9asWSO3aPKisIljl8Loc3OVXp6kZtvNnWF677pYJVHKKrFYqpSlZztWYWUvycnpS6ZFKsf/r/+7IdnEZ9Oo1jg9rYtdI77ZsAfyzwWCKi1BquvQqIJx8RBHUbW0PqvEFy/Xxey+9dFRlAXNvrAVdraSqkSPLF8Jijk4E7bkJpYcM6K81ZrfX97RlJM4F7lcKFJhzc3NRXR0NCIiInTb3NzcEBERgRMn+BMj5+TkIDU11eDPFakZqpx0Hd+93hir32EURXOdyNVHqXar4DS8XRW7R+7aykd/XLTr8T/rVQeda4egfJAvvu7fAJ5KMkMAmP+qNEnibySk2VRYYVJ3fWoZD3c3k1Vj7MGNWd2xbUxbDJOgippUVns5ralsxb1RWBDeal1J0T5/9lw9sBZvT0UO43bj8951jfp7bkYFc1QWmW3AHEq8H/g48ElHuUWQBEXe6c+ePUNBQQHKlDFcCi9TpgwSEvjrZ8+dOxeBgYG6v7AwxyzzaSlQazBkjf18bI9P7ox/x79kdRlAW/h7bFve7X2blBc9uOSrNRj5y1kpxQKgt/AqBSlzJVp03hZhWDO0BY5N7ow3WlZEE4VF7Eu5TGjLxKdTbXmtdz6e7mgcFmRThDzbev48XXnJvS2hQw397yFH3yYE99cZ1b4qGoUFoUcD2wtC2IIPSzl9qUYpbB4dLmjk+2FQU4fIxJ4EOoIqpfxxZloXA6shNw85t3oYl3Gda0giy1DWxPPGrO6I+bqXQRo4pVjkvT3cUcaJC3VoUaTCag1TpkxBSkqK7i8uLs6h5x+9/iwO35I+kEhLuSBfh/siapFiybRckA9SrVwWN6UENpVRMZv1Sj2jbR92rYnjkzvj3Of2yV0pBNfC7a5gK5U5WlYJxq8jWuF9gbrhT9PEKWm2Ju5XKosGNta9fpGZB0935/2t3dxU2DXhJfzxXjjKBChn2ZL7+EztWQfbx7SFt4e8y+9/vtcGL9UohZ3j2mH9iFZoWSVY0Mr3NM2+BVoARkkTek7tiUqlgg9rEszNoezv7SE4AfJwU6GPmRKnYglindfbg1Gn2O5xCtFXATAFdJwdRX6DUqVKwd3dHU+eGKb9efLkCUJD+We43t7eCAgIMPhzJHuvF51gMGvgpueyhBL++g7gk8haCPa3X1S3JbwdXtloW2igD8oF+TpcRm6pWCfWV9GxVmm0q1FK0HKz5uh9UcfhS9yvFIsHAJS1wq/s9LQuKF9CPxBP2nIJeQUK+lJWUDs0wKiIgLV+mXXLStPvK/X5qV8+EOtHtEL98nq/43mv8bvbpDnAb56bIs6RcH8i7mqb0IQ1amIHs1kMxBaGYQff8q02llTIWAW4RllbRSqsXl5eaNasGfbt01dEUqvV2LdvH8LD7VtSkVAeYzrpZ/Al/b1wckoX3Xu589KyfaeUtOSihEArLmJTAr3WzLRbhS2FFZSksFr6G33euy5CivsYDDvRD15IK5RC+Ot/bdCrQVlM7GpZtSRTiqbQ8zmuc3XU5sQG2DPVmdR0qhWCjzjXycvDDe42Wt67CZSyrh5SDP2alMfGka1sOr7UvNzI0GoqFFcRICKX7pI3mog6Z7C/FzaPDseOse0Mtn8/qAnebl3JqGAMYRuKVFgBYOLEiVi1ahV+/vlnXL9+He+//z4yMjIwbNgwuUWzO6PaVzXfSEYuftENd7/qabDNklKllvDfBy8ZpN1xc1MZLG2wrU1y0K1eKA583BGDWlXEplHKmUyN7VQdA5pWMMjh60j4Eqz3qG/e/++TyFpmk47n5psPuhKqdKNUP8m21UsKttMyojA3qBInI1JTp2wAfhjcFGM7VTfw2+SDPaENK8EfTFO1lD/+HtsOjcOCDDITTO5RGx91q2W0XNqhZmkMb1sF8wWsl0pjKCetYCl/LyO3oDoWWJ+PTe6MV5tV4N23/K2mWPR6Y7SpJm+eXq6fKlc/tcVKLtbHvFFYEFpWCUYDTqaN3g3LYVbf+vCwYz5aS1HqqoElKDap3Ouvv46nT59i+vTpSEhIQOPGjbFr1y6jQCxnZsmbTVA20AevLddnPqhQwtdiq4Kj4au5Hhbsh7n9G+CL7VeRW2B75R0t2lnyqPZVcezOM/QpnEX/MrwlTt9PQp9G8s9gq5Tyx1f9Ghht3zw6HANX8Ge1kJIRrCTnWvy9PbBgoHyD7empEWgxZ69BJLu5AL06ZQMwplN1s8f+g1U6FGByHcYmMWV/5/ZvAHc3FdryJL3f91EHBEqUbF9qPoyoiWN3mHvlxqzuqP35LsG2ruCLJhY3NxVuzOoBAHh9xQmc4qmg9mFETYxqXw35BWrM+fc673Ei64eiTIAPto1hAkhP30/CudgXGFWYY/XbVxvinTWnMSGC6XtVKhWmv2y/srRSw5dLl+vbumNsW1Sf9p+o45UP8kUIZ+J4amoXBPt72bUogCV882pDTNt6Wdf/dasbikol/dC0IhPXILQEznetrOH6l93tnnNWSoL9vfCAVR7dGVGswgoAY8eOxdixY+UWwy4sG9wUPRsYWyW/7t9QVr8gIbzc3cwqom+2rIjIeqFoOitKsvNq+9ypPesYbG9fs7TIiify0bJKsPlGNvL7qNZGEbJKwNfLHZH1QrHlnF65FFJX+zUpj8cpWZhnZeqr11uE4dLDZJyJeYHeDcsKDkjVShez6vj2gm3FaV45GOM7V0egn5ekqXK+eLkuZu64Jtnx5IS7xNumWkm0rBIMD3c3BPq68bbRwt3askqwwfNZOzQAJ6d0UXRKLXM0qhCIiw+ZSnAaGF8LtrXP28MNL9UoZTL2gq2Y+nq6KyooDmCU6nXDWure+3q54+DHHXW/YdkgH4O22mw32gnftJ51BCc4AGORFHIher9jNadSVgEmWLPj/INyi2ETypgqFUHYymqVUswSlY+nG9rVUGY5xL/+1wYtqwRji5la61IHGznx+OEQ6siUOUIMH3SpAV9Pd4x8ibGACCliw9tWwaZR4VaV1e1RPxTD21bB8rea4fTULkbKqjZwa7oEifqlhrtkO7FbLYxoV8WqxOhCmQKUOPm1Fu79M6dfA51FVIvQlRNTcciZlVUABn2zRmO6IlT7mqVFpaP6eXhLVC3tj/UjWpptqwTYv2G10sWw4LVGeKt1RWwf2xYli3kbBEn1FfAv7ViLMYQIXb6N77bCx92cr0Rv5VL+KFXMeXyz+VC0hbWo8Puo1vj38mMMEPAZUgL1ywdi82g5fDSdexCxFxend0NOQQECJFresgcVS/rh8oxuOstOBZa/8c5x7dB76VEATC17a/nxLX3QmweP0vZ+x2oY2LyCxaV0HYFQpVZrDKxCmQLOmQjKGtqmMrrVcx4XK64+yefrPK5zDey89BhtqpXEvht666GQP6YrwbagaqDhnSAObVMZ647HYEJEDV4/zU8ia6E7y9e8Q83S2P9RR7vI6wgGNKsgOK4K+cprU1V5ebghO89wVdHX0x1teNyNnAVnn5SRhVUBhAT4YGjbKpL51siNlImkK8gcVOUoPupaE2+2NC7jJ1TaL9DP0+FVmqyBPYiqVCrEfN0LMV/3MkjLY0rpDpfA3UGJyipgYvlawkElKSOXd3uwvxdm9Kkne+CMJbAVsIMfdzQomapFO0la9EZjg+1KCn6xJ1o3h9ebhxkopE0rBgEAZvSphxuzuqNeuUB4cBTW8V1qYEyn6opznbEnptxv1o9ohZDi3vhxcFMsfqMxAn09sXZYCwdKJz1OUphLkKLxFMvM6iHNUbWUv/mGLsK5WOtT7czua5g7z5WWNE0xrksNzO1vGLg1pUdtNAlTVsUqKfnu9cb4vHddVDbxbCjVRUYKIuow1s0gnkCwxRyFy5LjsflQIICznRNaidguFKbuGQ93N3ixFFSx6dRcgTVDW+Dn4S0xrksNg/uBfR9o+1TuhOnDCGmqPzkTd7/qiVuzexhs065VtKgcjNPTItCjQVm80rg8LkzvitYKjBewBFPuRm+2DMOEiBporrAqiWxIYbUjs/vWx9SetRFRtwxGKjxVlZREXdMXfOjFE1hmisGt+C2KRRGVCohPzpJbDLvRt0l53gwHbN59qQomRNTASy6ouL7VuhKWv9UUeya0N9r3SmND/7paZYobteEynJPaaNYr9Qws2WwqSVRL3ZFol/W5OVP5YCus6088sJtMSqOYtwc61CwNT3c3gyh/Lx4LM9sY8PPwlk6/XGwt3KwbQoFWrnB9vnyFMQiN62ycjWVs5xqYEFHTprLR9oZ8WO3IW631lXb4OoyigKXPuCt0ClLhplLhucCSblHB28MdEyJq4kxMEo7cfia3OJLi7qZC9/riJnSiyl+yHp29E9ujegij2P0wqCnGbDxn0PT1FqaLMyiR7vVDsXNcO4M8qkKwB92EVPuXKFUi5vrS0sW9MaJdFXi4q9BB4RlXCGnoWrcMrsyMRDFvDyzdf8dgn7YIT71yATjNkz5OCZDC6iCKqh5mTcQzoYcv56YSI97tTZUi5FLDh1BEMxv2s6ZVVgH+YLQKAgn2lYxKpRK0GBPW8XkR7EvMoaBieHZB6/s965V6+Hz7VaP9H3erBT8vd/QQOZl2JKSwOoiipLfVLRuAa49TATi/k7etLH2zCcb9dt6qz+bkq40CI5wtWbVU0MTHkNebh+H3s3EG24SuEF05wlVXrgoKCpCXl2fzcWqW8kZGYZGTAE81srNd3yr/WpNQLN9/Q/c+LycH2dlucAcwrkNlAJDsOnh6esLd3fZxixRWB1G5ZNGxEE3tWQdv/XQKABRTFUUu+CouiSUs2A93EtMNthVFZZUwhk//EFJKXFVZEQtfmeCiRjURbhTOhEajQUJCApKTkyU53vQOpZGVVwCAKet8//59SY6rdOZFlkVGLvO9s5Ie4/4L+/UVQUFBCA0Ntak/oifZQTSpqNzIO6mpXEq/3NigQqBRKU13NxUK1K6+8MJgi4X55YZl8cOBO+YbFgH40s+UlLhIhVLx55mksPv8uf0boFmlEkjJst3S5IoUZf/MM9MikJmbr9jUbtaiVVZDQkLg5+dn86TM60Wmrox0MW8PlHdClxlrCFOrkZiagwAfDxSzU1pNjUaDzMxMJCYyeZHLlrXe1YAUVgdSs0wx3HqSbr6hk8NWLviWcj1YCuusvvXx+bYrDpPN0VgbcRlS3BsqlarI5I80R6Cva+QotoYgPz7FXH9fafP3nhdIJ1e07atF28LMJMd3LWW1oKBAp6yWLClNmikPrwKoCtwKX3vCx0f5Oa6lopif/ZVzX18mn3piYiJCQkKsdg+g0VAivh3QUG4RFAM7X6KQwqrl7daVdEmtXRFu+U0+1rGSUa98uxmqlPLH6neaAyCXClMUlQwKGp48O2HBxgU1GlUIQnjVknjNTFWnBa81kkw2JdO6KpNEfxBPQQ7CedH6rPpJqGipivy0zv5ofy9bfI7JwioRA1uE4dMtl+QWQxGwrYp8+hpXiXVlC4iYYKGOtUJ0r7vVC0W3evrSiF4CNeKJos3wtlWQkJKNLqzk8G5uKvw2qrXJzx2b3Bnlg4pG9bj1I1ohMS2nyHzfooYrjxuuiBS/F5lv7MTXnKpFANCnUTkAQPUQ1y59Z86qyN3tyt2OUL14sbxceM8QRRc+b28fT3d8+Up9i/0zi5Ly5unuVqS+L2EDCh+Ebt68idDQUKSlpQm2WbduHYKCghwnFItdu3ahcePGUKvVdj0PKax2ojiPA/PoDtWwekhz/PleuAwSOQ53llVQzbOcyfXr5CqwDSswuRZLuUCggK3pmNi+m65Y7YkwD98zRBCEdDhCX1WpVCb/ZsyYIfjZKVOmYNy4cShe3HyVN3tw4MAB9OzZEyVLloSfnx/q1q2Ljz76CI8ePQIAdO/eHZ6entiwYYNd5SCF1U7wDTKe7m6IqFtGIIjCdWBbWPmSARi5BHC6ixVvN8OwtpVdQrHn5lG1FPYySp2yAbaKQzgRb7VmfC8/iawtsyQE4dp4OsD16vHjx7q/7777DgEBAQbbPv74Y97PxcbGYufOnRg6dKjdZeRjxYoViIiIQGhoKLZs2YJr165h+fLlSElJwYIFC3Tthg4diiVLlthVFlJY7URRtooYpCDiuQ5GXQNnQ9lAX3zxcj1UdoHqRlL6WfEF3xCuy6xX6uPklC541UwQFUEQtlG6uD4rgL262dDQUN1fYGAgVCqVwbZixfhdBTdv3oxGjRqhfHnDanfr1q1DxYoV4efnh379+uH58+dGn92+fTuaNm0KHx8fVK1aFTNnzkR+fr5u/40bN9CuXTv4+Pigbt262Lt3L1QqFbZt2wYAePjwIcaPH4/x48djzZo16NixIypXroz27dtj9erVmD59uu5YL7/8Ms6ePYu7d+9KcLX4IYXVToQFF408bny4mbGwcpU4hbsPScrQNpWt/izpq0ULlUqF0EDb0+sE+RXdlGAEIQa+PM9K4ciRI2jevLnBtlOnTmHEiBEYO3YsLly4gE6dOmH27NlGnxsyZAg++OADXLt2DStWrMC6deswZ84cAEx6sL59+8LPzw+nTp3CypUrMW3aNINj/PHHH8jNzcWnn37KKxvbZ7ZixYooU6YMjhw5IsG35oeyBNiJpkWoUAAX9sPPVyCA2ze81boSTt1PQovKrn/NZvSph9qhxTH5r8sWf7aI1FogJKZZpRL4X8dqLrFiQRB8aDQaXaUqawn08cTzjBwE+nogMzff/AcK8fV0t2vGggcPHhgprIsXL0b37t11imTNmjVx/Phx7Nq1S9dm5syZmDx5Mt555x0AQNWqVTFr1ix8+umn+OKLLxAVFYW7d+/i4MGDCA1lMtPMmTMHXbt21R3j9u3bCAgIEJ3sv1y5cnjw4IFN39cUpLASksNWSNUaDcoF+iA+RV+TmPtsv9yoHGqFFkelkkXDKj2gWQWrFNZgf7KUEZajUqnwaXfygyVcl6y8AtSdvluWc1/7MhJ+XvZTpbKysowKGVy/fh39+vUz2BYeHm6gsF68eBHHjh3TWVQBxqqanZ2NzMxM3Lx5E2FhYTplFQBatmxpcEyNRmORMu7r64vMzEzR7S2FFFZCctg3+IvMXGwd0xb/XHqML3deg7+XO2/kfM0y8kQ/yoGlxQCWvtkEu64mYES7qnaSiCAIglAipUqVwosX/FXsTJGeno6ZM2eif//+RvvEVvKqWbMmUlJS8PjxY1FW1qSkJJQubb9SyKSwEnblhwN38UlkbQxvVwWvNa8AT3c3dFlwSG6xZKdsoA8ep2SjVZVgs21fblSO8rESBEEI4OvpjmtfRsp2bnvSpEkTXLt2zWBbnTp1cOrUKYNtJ0+eNHjftGlT3Lx5E9WrV+c9bq1atRAXF4cnT56gTBmmAMmZM2cM2rz66quYPHkyvv32WyxatMjoGMnJyTo/1uzsbNy9exdNmjSx6PtZAimshMPQ5qYtagVKjk7qhG923cT03nV12zaPDsdvp2MxtG1l+QQjCIJwAVQqlV2X5eUkMjIS7777LgoKCuDuzijH48ePR9u2bTF//ny88sor2L17t4E7AABMnz4dvXv3RsWKFfHqq6/Czc0NFy9exJUrVzB79mx07doV1apVwzvvvINvv/0WaWlp+OyzzwDoV0nDwsKwaNEijB07FqmpqRgyZAgqV66Mhw8f4pdffkGxYsV0qa1OnjwJb29vhIfbLx0lZQkgHI6tyfSdjQol/LD0zSYoXVxfCCEs2A+fdq+NkOK2R4EXFUZ3IJcIgiCKFj169ICHhwf27t2r29a6dWusWrUKixcvRqNGjbBnzx6dsqklMjISO3fuxJ49e9CiRQu0bt0aixYtQqVKlQAA7u7u2LZtG9LT09GiRQu8++67uiwBbJeB//3vf9izZw8ePXqEfv36oXbt2nj33XcREBBgkDv2t99+w+DBg+HnZ79YFNeckhCKoVpp48jk2CT7OWUTroutRRgIgiCUwNChQ0UXAvDw8MDUqVOxcOFCREbq3R6GDx+O4cOHG7T96KOPDN5HRkYafIZL7dq1cfToUd37Y8eOAYCRG0FERAQiIiIEj/Ps2TP8+eefOHv2rPkvZAMOt7DGxMRgxIgRqFKlCnx9fVGtWjV88cUXyM3NNWh36dIlvPTSS/Dx8UFYWBi+/fZbR4tqNVRCE6haqKh+zloG19K5doijxSFcAG5FNIIgiKLA6NGj0b59e6SlpUl63K1btyIqKgoxMTHYu3cvRo0ahbZt26JatWoWHScmJgbLli1DlSpVJJWPi8MtrDdu3IBarcaKFStQvXp1XLlyBSNHjkRGRgbmz58PAEhNTUW3bt0QERGB5cuX4/Llyxg+fDiCgoIwatQoR4tMWMGuD9ojPjmLN/fjj281RdS1J2hbjRR7QjxFzJOEIAgCAGNl5Sb1l4K0tDRMmjQJsbGxKFWqFCIiIgzKrYqlefPmRrli7YHDFdbu3buje/fuuvdVq1bFzZs38eOPP+oU1g0bNiA3Nxdr1qyBl5cX6tWrhwsXLmDhwoVOobBSRSLAy8NNMFG5t4c7ejekqHfCNhqFBcktAkEQhNMyZMgQDBkyRG4xRKOIoKuUlBQEB+vT+5w4cQLt27eHl5eXbltkZCRu3rxpVT4yR6MmjZUgJIdrYF01pJkschAEQRCOR3aF9c6dO1i6dClGjx6t25aQkKDLC6ZF+z4hIYH3ODk5OUhNTTX4kwtSWAnCDnB8AijDAkEQRNFBMoV18uTJUKlUJv9u3Lhh8JlHjx6he/fueO211zBy5Eibzj937lwEBgbq/sLCwmw6ni2QvkoQ0hPoS6VpCYJg0NBA61RI8XtJ5sP60UcfmU3TULWqPo9ifHw8OnXqhDZt2mDlypUG7UJDQ/HkyRODbdr37Lq3bKZMmYKJEyfq3qempsqmtNJjRBDSM7hVRczayVR8oUwcBFE08fRkJq6ZmZnw9fWVWRpCLJmZTDpL7e9nDZIprKVLlxZdQ/bRo0fo1KkTmjVrhrVr18LNzdDQGx4ejmnTpiEvL0/35aKiolCrVi2UKFGC95je3t7w9vbm3edoaOZHENLj4+mO6192x/4biWhfkxRWgiiKuLu7IygoCImJiQAAPz8/XWUmQnloNBpkZmYiMTERQUFBumpd1uDwLAGPHj1Cx44dUalSJcyfPx9Pnz7V7dNaTwcNGoSZM2dixIgRmDRpEq5cuYLFixfz1rJVIqSvEoR98PVyR6+GZeUWgyAIGdHqClqllVA+QUFBgivkYnG4whoVFYU7d+7gzp07qFChgsE+rWUyMDAQe/bswZgxY9CsWTOUKlUK06dPV3xKKw83FfLVGrSoEmy+MUEQBEEQFqNSqVC2bFmEhIQgLy9PbnEIM3h6etpkWdWi0rjo+nVqaioCAwORkpKCgIAAh5zzTmI6DtxIxJA2leDtYfuPQxAEQRAE4cqI1dccbmF1ZaqHFEP1kGJyi0EQBEEQBOFSyJ6HlSAIgiAIgiBMQQorQRAEQRAEoWhc1iVA65orZ8UrgiAIgiAIQhitnmYupMplFda0tDQAkLXiFUEQBEEQBGGetLQ0BAYGCu532SwBarUa8fHxKF68uEOSCmsra8XFxTksK4E9aNGiBc6cOSPpMV3l2kiN0HWxx2/gTMh9vyj5+st9bRyFpb9BUbku1mDNtVHyMyAVSr9n5PwNHH1tNBoN0tLSUK5cOaNCUmxc1sLq5uZmlOfVEQQEBCjy5heLu7u73eR39mtjL7jXxZ6/gTMh1/3iDNff1Z8la38DV78utmDJtXGGZ0AqlHrPKOE3cOS1MWVZ1UJBV4QBY8aMkVuEIg/9BvJC119+6DeQF7r+8kO/gTEu6xLgaOQoVOAs0LXhh64LP3RdhKFrww9dF2Ho2vBD10UYpV4bsrBKhLe3N7744gt4e3vLLYrioGvDD10Xfui6CEPXhh+6LsLQteGHroswSr02ZGElCIIgCIIgFA1ZWAmCIAiCIAhFQworQRAEQRAEoWhIYSUIgiAIgiAUDSmsBEEQBEEQhKIhhZUgCIIgCIJQNKSwEgRBEARBEIqGFFaCIAiCIAhC0ZDCShAEQRAEQSgaUlgJgiAIgiAIRUMKK0EQBEEQBKFoSGElCIIgCIIgFA0prARBEARBEISiIYWVIAiCIAiCUDSksBIEQRAEQRCKhhRWgiAIgiAIQtGQwkoQBEEQBEEoGg+5BbAXarUa8fHxKF68OFQqldziEARBEARBEBw0Gg3S0tJQrlw5uLkJ21FdVmGNj49HWFiY3GIQBEEQBEEQZoiLi0OFChUE97uswlq8eHEAzAUICAiQWRqCIAiCIAiCS2pqKsLCwnR6mxAuq7Bq3QACAgJIYSUIgiAIglAw5tw3KeiKIAiCIAiCUDSksBIEQRAEQRBA9Drg60pAQZ7ckhhBCitBEARBFGXUBUBuptxSEEpgxwdAdjKw/CW5JTGCFFaCIAiCKMr81BX4qiyQ9UJuSQil4OUntwRGkMJKOJ7MJODod0DqY7klcW7ysuSWQB72fA4sCwdy0uWWhCBcg0fRzP97B2UVg1AQYa3llsAIUlgJx7N9DLD3C+DX/nJL4rzEnQbmhAJ7Z8gtiWPRaIDjS4DEa8D5X+WWhiBcC41GbgnsR/x54OktuaVwHhRYcIkUVsLx3PyX+Z94TV45nJk9nzH/jy6SVw5H8+dw/ev8ImphJgh7oUAlhRdLFeuMZ8DKjsAPLewijkvw4ARwbbvcUpiEFFaCcBbyc4DrO4GsZOBZEbQU5OcAV//Sv1cX6F/HnQEW1QeubgNSHgHZqQ4XjyAIO6NWAzMCgZlBQG6G+M+lPmIdo0C4HZdTK4F1vV3f/UijAdZ2BzYP0W9TKU89VJ5EBEHw89co4PfBwMaByg+OyE4FEq9b/rmji5gB6foO431cn132wPPnMCAlDvjjHWBRXWB+DcvPTTgHaU+A3dOY+yTjmW3Hys8FCvKlkUuJqNXA3+OBs2tEfkAF7J8NzAxmJohsbvwDrO4KJN2XXEzRPL+tf338e/GfU7nrX+dYMJn97xMg5ghw6kf9tttRTF/MvT7OhkYDJN1j/uekGe+/f8jxMpmBFFaCcAai1wHXtjGv407JKYk4loUDy1ozlk8t6gJGyZgRKLykp/XJ/f0t43352Ybv1SxFgzt45GcDd/ZZLDahcGKOAgtqAicKlZV51aw/Vn4O8E0lZpnYVX03b+wAzv0M7PxQuI1arX+tUgGH5wGaAmDb+4btNg0CHp4G/h5nH1nFwJ6kHvxK/Oc8vPmPweXZHf78o2wL64ZXgUu/A1tGiD+/Uki4AnzXALi4CTgyH1jShHGVuL3HuO3jiw4XzxyksBKEM7DjA7klsIzUh8x/rZINAPcO6F8nx1p+zCdXDN8X5OqtruwBSYszBfXlZgLnfmGshwQ/Gc+Bdb2kO97sECAvk7EyWbJM7Eywl3iFYE/8oBJ4zSIzyRaJbMONVU2+Mc+kVgh2f6MWsKhf/hP4vhmwaTDPTp4JDd8qkNzk5wAbXgOOL+Xfv/U95lpsHc1Y0gHg8QV+5bsy5WF1ffJzrFumctUZvjVkpzKDSFHj7n7hWa2Hj2NlsYbcDCA90XBbQa7+tTtLqTy9Ejj4jfB971WcWapNS9Bv+3WAYZtj3wFfV2R8et29LJf31h7g5n+Wf84enPiesVyt7iK3JMplUT37HVujNt/GVWErcOygq7INzbd3NOxVljIW3A/syavWgppwmZkEaTnxA/P/9m5xx6zXT/z5HcXlPxhrqTYoF2D65INfM779uRb44nr5Sy+fjZDCKjWL6jPLVMlx4to/OK53IpfTN0hJ/NCSWapIvCG3JI7jRQywvh+woj2/EieVwppwGYiaDmSnSHM8Nl+VY3xH2fl12QqrG8uP7MT3zJLeg2P8x3JzA357A1hQC3h4ltnGZ1EpyGV8yvgsrKbIzwE2vsacQwn+wLcKB8kUEf2GWJ/Lh9HAPeX5oVlE2hNmUjIj0L5ZITQiLawajfMG4MSd5t8upIAeW8L/XZ/dlE4mS2ErXNwMKU+uAqs663PKauF+B3Ue41qyvB0wr6p+e/w54fPy9cnFQsXJ7Ej4jGUrOwIH5zJjKp+lWAiuC5YCIIVVSm5HARmFFiZ2NLMp1vbQv977hfQyWYJarYylsbRChYfPr8ZVefFA/5qrQOXnMKXy+HDztOw8y9sBxxYD39sxvcvJZfrX+SyFlc+KJbQa4eYB3IkqPF5hwMPlP/jbZj4XtrAK1cNmK9LpT/nbOBKxFuJz64FZJY2tzVw0GmB1Z+CXPvb9fut6M8qkvYpYnPzB/OQqep3t/RZXaSvIA04sY5QgNsvCgbnlGfcNZ+OnrsbbspKFr2/mM/nHJC4xR/WvfUsY7vuxDaOsrupsqGByLabqAitcS3gUPfYEXCk85ZlMaDMkFORYtpKgBF2Ag8UK6+HDh/Hyyy+jXLlyUKlU2LZtm8F+jUaD6dOno2zZsvD19UVERARu375t0CYpKQmDBw9GQEAAgoKCMGLECKSnG86CLl26hJdeegk+Pj4ICwvDt99+a/m3czRsP8Nnt4XbCSFnLWeNBljTjbHwmbpR058ySyeO8GPiDiKxp5hZ4i0XVGTZnS93Znt4vvDnLEk9EsOyZqZL7CvJtvodX6J/ncuKPs2zYMbO9lW78iejxBcIROVGfS48eGQl829n31ts5dUc+TmMH9iVLeI/IwZ3D/NtAODvscz/O3tNt0tmTYCeWpGtQQzZqUwENQB8a0PwkylS48232fEBcGSBZcflJpDP59wD0euA3VMYJcjgc4XX0hGBR09vMpHw9opGz8tigs6+q6/fxp3gnVnN/1lLr7dUhNTVvy7fTLjd5rf1rw/NM9wnNIkVA7ufO8GTpeDeQWBxY+D+YevPYQslzTyHlngeyun6IYDFCmtGRgYaNWqEH374gXf/t99+iyVLlmD58uU4deoU/P39ERkZiexs/WA1ePBgXL16FVFRUdi5cycOHz6MUaNG6fanpqaiW7duqFSpEqKjozFv3jzMmDEDK1eutOIrOoi4M4a53gLDhNsK+e1Z6keVeN24o7WW3HTg4RkmsCXloXC7nyKA3VOBb6tIc15TcBXnX/szvq0bX7P/uS1Fo7Htt2ArTec3AFve1St4lzcLf05spxJ7EljX03r5zCG0XHt9B3DmJ+Z1Hs+E7I93+D/HVajXdBc+d0EuE/3Kx6VN/NuttR6c+Qm4+JthAQMpEGsp9/AV146dxsecO0nUF8CfIyz3o48/r3+dZyIn5osH1j8bYpWLQxYaNLSKthbuJDHhkmXHk5qEK4xr1J5pwL4vxX8u8QaTYUPoeWCT8sh4m1jl2JxMuZlMEBPbB10K2L8TX3+ihR0Qxe0jr/9t+Xm1z0aGmdWKX14BXtwHfn6ZcWe5tt0wC4O1iJ3smy38YMEz7goKa48ePTB79mz062fscKzRaPDdd9/hs88+wyuvvIKGDRvil19+QXx8vM4Se/36dezatQurV69Gq1at0K5dOyxduhSbNm1CfDwzm96wYQNyc3OxZs0a1KtXD2+88QbGjx+PhQsX2vZt7cl6zvXwCeRv9/d4xl9111TmPXsAssRadu4XJm3Q7NIWiSkIt6P6c7g+ipDNixgbz2PBwMX1b+Q6jKc9YayuWgryGX9HOZYytr0PzK9u/fIr+/ofmM0sf59Zxbw3dc01BaYVjdwMZr+Qr6hUmFoS/mciY40Tcvh/ftd4W1Alw/dPzfgzC1lfvYvzb2d3xmL9FwH7+e+5i1BYn902nBiYGgjZ95O55+HYd4wV+/EF8zKwYSdur9OHv03caWBxQ+P+MT8X+LEtsGUk8/7+YUOrZ24GE4QoVmFV5wE7J4pXur2KGb7nJqE3NzEIqCDuPNayvK3+NduS9/AscIXjbqZWA3cPMM/gzy8zytraHnpXGjbmsnMIPUd8/DWaud4FecD6/oaTht1TmMjzBbVsz5XLhn1fszOQmOI5Z7Xz4FzLz6tVBC0ZoxfUZLI0RH1u+fnYXNwEzCnDTAByM5iS1BnPmGfrv8mW+VRbMil1BYXVFPfv30dCQgIiIiJ02wIDA9GqVSucOHECAHDixAkEBQWhefPmujYRERFwc3PDqVOndG3at28PLy+9X1dkZCRu3ryJFy8UECDBB3vpEwB8g5j/OenMgJGXzfh6nfuZ2X6y0EJdp7f+M5aUxZN6SYqtcNz8l1nyPFy4lKIu4FcqAEZBWx0BRP+s3yb0UDy/y1GwzXzfewf0x+Jzl1hQk3Fj0Ob6vLyZibLePtb0cQFGud36PrP0JwUXf2N8wc6v59+v0TBL+0K5QfkGCrHWCSHLfOwpJhBqeTvj38SaqHpTmPNh/LqicQYBLXwpu6TyDwuuyr+d3Rlf3wms6MDv/8XF3P2iLmCenUPfWuY24ybCJeD75obvL/5m3ObxReD3tw1TgJmyRLGxdOmZXVq5Yjh/m0PfMP8fHGWCSg99y7hp3DvAyHh5M/P8/vyyYdnMP4YySu7Nf8TLc/YnJqhQDNz7i2951xRsxaUgnzEgOCKzyeouTJEMbTaRlIfAlyWA9X2BOaH6GIqcVGDXZOPPJ95gxqLbUcZjFsBvyRN6bi9tYnx8r24D7u4DDswBLm0Gzq4FLmzUt/trpCXfsFAOgf5EaCWHbwleazzwFjAeabGkYhbXfUiMAmjpvcVl62jm/5YRTJ7q7WOYwO6fujIFDfZ9yVyvZeGGlm+tbD5BrG2W+LC6uMKakMAMsGXKlDHYXqZMGd2+hIQEhISEGOz38PBAcHCwQRu+Y7DPwSUnJwepqakGf7Ly6BwTLT23PLOULTQbZN/wQjdTbiZwZKHhgBpU0bDNw7NMJ29JfsuUh8zyc36uYQfB7uiyU5kHZGlTpi2XA3MYV4Id45n3RxYws2o+qyDX0V2MUrK2J2NBeCgQ4QoAjwqjyP/9lPl/caNwWy13oph2Uuc3FfKHvPkfsH+WPr3KpT+YCUzUdOY9N+IVEKdAAYyCtKA2M+tmW7DXdGP+P7liHDwiNWYjSjXCFjy+KitSpRkSstCxO+PD3zKybRpk+fGzkplAD+1zfHoVszpxYI7pxOI6f+zCgBAxFlajY5ww3rY6glnyZLtamJpMaO8/wDK/RLXa0L9ULXCd2b62a3sy1+WfjwwnTHyuKtYGXIpVzrl9z81/Dd9bcv+dXMYYEJY0Ef8ZW9H6tW+xUBksyGH69w2v8k/s+Z7j+TWEldbD8wyv+V8jgZ0TDPvBu/stk/H6Dkb53sNjmWRPqoJZ/po/v2zcdnXnwhdmlMqj3xlvmxnMWJC5cPt3MUqdpdkE0hMNC66wucAztj06y9wP7AkkoF9ZYT//aSJ8wrmfVxAukyVg7ty5CAwM1P2FhZnwIXUEp1cwlSQAxhFbDLEnGasft3P4/S1g30zGp0lLI9bgqtEwM++rW013YGrO8vGK9sD2/zHWXiGFOume3pKjtbiy4UaY7vuS8T9c3Mi4rTb6XyePiIc99jiQdBdG1lj29/ArxfznsxgIwe6YxcyST69iLAnWwk1X9Ne7zP9ji5kJCZ+F4E6UuNn/XyOZazuvGvBVWWbpiAs3a4XUeX/FRIkLfRe++0Aq+YQ6Xb7tz+9YfvyFdZmoZO2gfIE1qTM1UG8aVOiPPZB5z/Zh5UtbxedvyDc54tvGTfOjJfE6c/9pub1HnL+dRsNY9c7+pN8mZJ1tMFD/WjtYxhwBvAP4ZRYTZGUKsYMs16LNvd8sUVhtXfLlOz8f7N9G64cZZOE4d/AbIHot85pbiAMQnnBHCWQLuLYN8Ang38fmQuEYUpAvHAipRVvl7vgSxmJ7O0r/eXY/Y+68ybHMBN5cKdake8auapoCfv937gRYjMtKJYHVByEWN2ZiRWJPGu9T8Rh58nP07mNskgpXRS1x82BTlmcMlxlJFdbQUGYm8eSJYcDEkydPdPtCQ0ORmGiokOXn5yMpKcmgDd8x2OfgMmXKFKSkpOj+4uJE5kG1J2z/SnPL3wDj43dxI7BjAvP+j6GMFe4uzzIyO8UPOw0S119HS142s6S4kTWAZBYmTb57gLF88MH2P1K5GfvmOiLhdvQ6Y4sI2z/Lw4rlbfaSHneQe3aHmbHmpDEd2Z29wL8fM1arc79Y55PFPh87WTVgOvfm0ubC+/hQ5zOWPSEXDi65mYxVbtcUE8dUM/mC+SyhAHOuVZ3597ERsprxDZKmElw3tyDgScjyJ2aylJdtfplcG2yk9ffmKuVPrvFnFOBO9NgW1q/DGGVSy9VtwKK6MEJsKqmjAr7/fG42X5bQ570Vgs+KeWAOMDfM8HolXucPGFS5QdDqZWvux/jzjKXz2nb+/Wo18zxzU8c1eoOR9/yvjPJotl8z4zf+12jgxr/CbdgkxwIL65jOBqINpmKjLgBK1xJ3Di1PzLhMCN1TmSb6PDFjwLb3mNzkq7swmQn4JmB8/DWSsQZvew/YMJDjm134DJuapMwtL+48OyeIa2dkYc1jrpmp3MimJiNHFjJj/H1WEKC2T9GuvrDJ4UlBptEANXsYb/+hpW1uKv2WW/9ZOyGpwlqlShWEhoZi3z69gpWamopTp04hPJyZZYSHhyM5ORnR0fpZ//79+6FWq9GqVStdm8OHDyMvTz/YREVFoVatWihRgpN7rRBvb28EBAQY/MmOQQURoUvNczPf/IfxUbq61XjfkYWMwpTEUkjYVp3M58BjVoSruoB5mJY2Y27e23sY3zr2jZxqovPYwMr3mJZgPNDejhL+rDmrAd9DxseJ72Gk8O9mKVjsCkp85GUBC+sxilnSPaaDOMIaxLmd0A8tmeX7fV8yPrfsnJd/jytMNp/MBNA9vSkuHRnbP5mdrFp7PiEsWcJhI1aZiV7LuHScXCYc3BW9hgniWNyYyV7AVWh2fmhZ4BIXrZWCfb8IBec1fAMo29jyY3Mxp7Dm5wDzqgPzaugHRG5hD7bLhjbpeBJnovBjOOMi8EtfZglW+x3Z1yszyfAZzstkJq1ZycDZNfy+iFoZbcFNoE9a3cVQCUi6B/z6KhB/gXkvlBItJ5WpYKblr1H87dIeC/8utmY92TONkVeoJOnFjczzzI0BCKrEBLFuH8OsRnDv5+UvMf2GGI5+x1jnNr0prv3+2cw12T9LuM2y1sb+vDmpQPGy4s4hFqF7ytREQuxqyHf19W5Bi+oKp2YT8jm9vdvQdUN7j176XficYlLWqVSGz58puPdtThrwbVXDIDkuXIU+N5O5z27uYlZOAeDn3oz7HbvfFp1uTyM8wXekm4oDsFhhTU9Px4ULF3DhwgUATKDVhQsXEBsbC5VKhQkTJmD27Nn4+++/cfnyZQwZMgTlypVD3759AQB16tRB9+7dMXLkSJw+fRrHjh3D2LFj8cYbb6BcuXIAgEGDBsHLywsjRozA1atX8fvvv2Px4sWYOHGiZF/cIbBvOL6Aqvxc4XyOQoFD+2YyS78Gx+F0JqsLg940GqbKxayS+truAJOSin0ji10K5UtdYyqdDZ+PnQEaxiLCDk4RyvvHt3zFPo5Qp3npD8YfKvUho5hpvzfbn9LIkb6wI3xwnP+YD88w9ZrP/cwom1+xBw0BS7qjS++a84nU3o/ZrOUyIcvaucJAssxnjGWfWz7U1py8WuWRPVgKddaxxy2r+iWkmJpaystJB+aUZVxMclL01rhfXjFsx07rBJhWaO4dYALyZocw1afYg9hWHl+5uJNM5omdHxq70mjRBnaKQTup0n7v/BxmwBSCXSJ4SRPGPWVlB+Z9toklVnZJSFOpoYR+FymrWV3dauwbLmT1ZBfmODTPuDCA0XdRMffJQ467xbHFhn6Ge2cw98UDE30h+14Q7Cd4tudmSh88qQ0G5mIqr6glQUtshIpf8FkRtbDHgYI8ZhVE6mtgCu7y+sOzzATTZBYTzm934gfGkv/b64bbvw5jxipdOwuCtW7sFN/WiRGZrVrP2bNn0alTJ917rRL5zjvvYN26dfj000+RkZGBUaNGITk5Ge3atcOuXbvg46MfZDZs2ICxY8eiS5cucHNzw4ABA7BkiT7ZeGBgIPbs2YMxY8agWbNmKFWqFKZPn26Qq1Vx+Jc2ztFmzr9FqHMALKscw83hWJBTuEyRJ28+QXMBELEnGYXaOwCYUrgs/s9H/G1NKUXqfOMZ5t0DTECJmO8v9DuZUpKFgsDkzt+o5ZYJZYQN27/LXyBFGu+SfSZjda3ykvllRnNor//eGaxtApYer+KWuYAIKkYmLEZ3ogwtbPOqAZ7+xpMzk5MoAQpymepTbIRcJbiBQFy4qZlMkZ/NKGXLWgP1BwAB5YBDXwu3v7YNKN/UeHvsSZh1b4o9pQ/4E0LIVSP1sXRWwz+GMv+rdgLKNWZeewpMdtguUdxCC3zLqimx/MvN7CA2QK8wr+0OzBBQxNh9/YLaQBOeEsR85GbYN5L7jY3iAhG1Abe28vCs8WTYFM9vM+mebEaEu562wpZRX8hSRoXcAriTEKmzSTjaGCIjFiusHTt2hMbEBVKpVPjyyy/x5ZfCiYWDg4OxcaPpSO6GDRviyJEjJtsoih7fMulG2LBvbj4/H1MVmyzpiPjyys0JBcaa8UWzN3cPANUjhPdrrRrmnOIB09kP1PnGrgrr+5o/phZLKh2Z48ZOJmL17W2GfreWpCyTAu7AyUX7DJeurd/2Sx/jQVWt1vs6s7m8mbFSW5q7k4+Mp4zSeoonbySXKi+ZdwFhIzQZMZX4n8+/jm8loUpH4PhS8bJITUFhdo/D84BavYAKJir/FOQyy+DZKYybgblCBTUEFM41keblMqesAsKDu9hldEtg9y9i0odxsfeyKntsSE/QB+uaoyDHfgqrf2mggglXJamJOWbfwiamKFXTfJv484w1nRsQzfaVFhpHuGO/0GSNj63viWgkocLaYKDpQjUy4zJZAmSHbwk2nZWCi8+iYyqwxJKbUMhatKy1+GPYg9CGzP+cdMZyYgumUlVFfcEEt1iLlAorwCyfXd2qzw6hLmCUdyWhzmMyH3A7z+8aApvf0Su0C2rx+yxaWlnIFJoC8fdqh0mWLQEKWvJM+G3vmSbu2NpMD3IRf4Gx4B1ZwErhI0BBrqHPoLlAGbEVtazFodXqWJNFrh+yozm1kqnapl0xyssyLJlsCfm5tpUZNUXGU+lyIZvi/AbGIi+XsgqIMrACYJ4xbk5ZdpyJoMJa6LKmDda15Dfjy7XMxVxRFUt4eTHw3jFgugNKr1uBFdNNghdzFgu+wBwpHNlNIXfiX+2yqthITWtJfmDbAJiWwATLVO0sHIhiKdocnMP3MAE5SvQx+vdj423JD5i/zOeAfyl9InIuphQ+axDrR+0TaFnOUr40NKbcbcQG1gDGkeaO5sll8e4YRoOkmf5F6kmcnPzcG2j/CVC+uel8zvbm7n7gv0+Y14e+BbrNMvRZtJT8bPv28Y5QWLf/z/7nEKLBa4xPvlRKvykL6z8fMWngBq6Xf1w2hbsXEFpfbikEIYVVKswtNfEFE5gaOJMf2CYPANTtK758nT3IzRBOOK0k1pqoU28rx5fYnltSDjYNtj6Ywl6o3JhB1BILa246M/nb/Dbz+YTLjqlIJAemvhc3F6s5C+uv/YH3jgIlqwG1eytzwmUJh+cBlV+SVwZ2edqLG21fei3IsW9yd0cGMzmabnP0k26pJmdCx7nNSk+1+W3x2XHkwBGTFBsglwCpcDejsPL5xZnKvykF9uxwPP3MtynIZappFWVu7HS8/6oUxJ20PZiKD/8QoO4r5tvxob2fLbmv933JuD5c38H4m7mqsgqYzqVraXnMvEx9wI0lWRmUjJIG4+wUft9wS8jPtbOF1Yrqa0rgvaPm27QZq1+pkcrCKja37K3/pDmfPVD4WEUKq1TwVaBgw1eJwt7Y1XlaZd4vNT8H8LSzL5wz4IjiCs6Cd3Gg30og0IpKdDqF1cKFIe0yrKsjtqKeWLS+cZYEiSgZuV04pKYgB3hhR59cJSn4lhDaQF/90BTPCt2Qru+Q5rxigg0JmyCFVSoUPjORHHU+sJWTZiydJ62X2Fn6tjHSyKVEuPk6XZWyjYGOJqx8AODlx6QWel8gx60ptBYRroV1sEAu46KGrVWihDBVxUdLv5Xm28gNO7esK7B5iHDeailw5jHNVGUuLc9uMf+lcL8jHAIprAQ/Dd8wvV+db5xMen51w/cFOeKtixd+LVL55FySun3MLx9rS46KqT/ORbuEyp0E1TCROo2wHXMW1sovAY1eN91GCQhVUCKKJjW6yi2BZQRXM9/GxSGF1VFYswQqJ3VeNr1fTCnOglzLSnaaS5QuBR0mAY1EJMOWmz4WVDlRCip388GHUvjcWZIlQA7MWZmdCbXavI+fJUVO5CSoov2O3WwY8Opa+x2fkJ7gqubbKAlLKtuJpXZviM/rJT+ksEqGmR+dm9heqXx6H5h4nVm6tZX8XMuiWP1K2n5OU5SuA7T/1Dl8SsMcmLRbMjTmFdZiElSm4avwVLax7ceVClcJUgKAL0swZWVNoeQ0PWxy0+x7/Pr97Xt8Ldb0kz5BlrXXJtN/dY3l55KDCi0s/wyfj66SrfChDWz4sIB+0nKUU02wSWGVDNZydhmePGZiqjk5ClPVp/yCmbKN+RKk+rDUwsq15ETMtF0GNpXbMQE7UiZatgVTio2HBdWclIJGbT5QozyrGpM1VYcA/ly5w/4FRh1k/tpOAEpWN27jKJxNYbU53VNh3xdSl3+3va6HysLh60WMXcQAAHj5S3Oc8s3NtzF1PUvXkUYOLXxV5ap2lPYctvL+CeDNTUxJ39YmYiHKNAACKwIDf2He8/U/AyQOjq5mpqCHKd7jFJS4us36Y/USqJ7m5gEUC7H+uA6GFFap0CmpKvtZe7zN+P15BwIla4g4kIglACmskNkplh0nh2MBkToCVttB2WNpxRpMKaVCg7GpdGLd5gjvcwgqy5QIqxVWns95+QPlmjB/XWcCTYdYd2xraf+p/rWzZcZgX08x0dVctL7nb/1lvG/oP0yCdoBRjH2DLT++EOYys8iBLSsIZRsDA1abDyLk6zeqdQb6rwb6/mD9+dlof1O+cw3ZbpsiJjVl6jJFTiZeB7p/JdyuQjPgw8v6tHp8/YjUz65vCes/y07gX6KKvpQ5wF+Jrvd3/Mfp/BlQojL/PndPoMlbzF9/OwbwSQQprFLhGwR8fBuYHGu6WlJQJevPMfqQ6f11ejPR1+ZmwLEngcZvmW5T3IYKLFqu/sX4wImFq7DyWaoB84q7EFrrny2/gZSYKn8pFIBWi1PCkO2H1WYsMHw3jCYkLUbyKxP2INNMST92cm1rrciiFF0H+mW5eRgqyJ6+1t+jg/+URiZLYF/PgLJA3x/Ffa5YYR+hVQDYv+c7OxkFonI7oPtc5pivrwcm3QcqtpFGbkstrHxI5ceonZi/9rN1n+/+DdO/B1dhggiH7QI+vMrfls/qWb450PA14awsppLjaycUvOcSOF5rKytU2XP52VxWA64xh2/CI3UhBu/i4ts2elP/Wuv29P4JoN8KYPx5IKCCfv/HN/Wvp8YzekfzYfzHbf+JcJ/p5sH8xq/8wNw/CocUVikpFsJEP5ua+UfOYTpza/AUsezk4QW8/qvpNk2HAK98D7xjIv9c+aaWySYEX43zHgJ16PM45WuFlr4+vAq8vZV/nym0A5xSlrRMKWxcP81eC4EJl407nm6zDd9XbA18wco3WX8AsxxUvYttsool/Ynp/ex69tYuFYuxrEmRkkeskq9yMxzYb/4HDNlm+/ltYWw0MPpIYVCFGdgrGSo38YUZRh1g0lm1/YB5z76fPf0Y1yKAGbQbD9Jbm6Ty9ZQiT6iY62MJ1k7CuMp3pXAgsIK4tgBTwQ0QVjC5fSubMvV5inkUTpj5lGPA+mfXlOuE9j6yF/UHGL7nu3/E9htirft8/vYA/4SWrSznpjP/y9QFGr3ByFWJNdHzCQRG7AVG7meuqQ/H95a7kiGksCo9gJUDKaz2wNTM3780UMVKnzH2zVWjG1CTU1JUa5UTmtW5eTDKYsQXzANQpT0wIwUoXs46eaxhRoqwVSMvC/AqlD20IX+H/dJHzKTAmiWp2JPM/3r9TLdzFNzlfbaVzr+kYSdUsjoT5ZxwyfAzNXswPptavyyA+W1f+oi5RgN+0m/v/rV5y7otqFRA3Cnx7bmdLB98PnlSWNbEUKY+MOYM0GsB0PQd4XbtPjQcwBIuMb66ow8DnT6zv5x8ePoCZRuKUz6f39G/VrmZV7o6f8bcVwHlmHRWuvy4rM+ZUibZMgWUZ6xIYmEvsUphHXVz51/Jsdivt1DRsba6oCUTLL77X1s9SWzea/Z1dPcyVsB0LgEC30dMbIKlSq3YSlHWwpWZV2EV2bcM/kNcOyEXA7Yvv5Y2Y4FO05jXH1wy3t91JhN49fIS5n1YC+Pj9PmeSUn5CifLjKCFlRRWIsvEsqiYB4JrNdPCvumaDQMG/c5pYCaPaYnKQKvRxgNSmoNr3Qtdg7wM6L7DwJ8ZSyh3AGArAJYG1mgVee7gEDHDsuNIRUGO4Xuu/1u7D/Wvtdch8ZphGzc3piPjWki6TGes0Ozv2vp94e865gz/drYiLAZ2tC7f8nYZVqRrrwXmjxfEkw5OzOAuhVLr7gmUrgm0eJdZVuNSvCxj4egwyVD5fnkx879sI8dFjnMRKrJgFpXwZyq1A15ZxlyLBq/ynNMDCGvF+NsJBWABhv1Puw8ZK5JY2K4ynr7AKDNuUuZw8+AfzMs2suw42nvSEZMpvvu/Ulvmv1AVOK4bFFtOd08euc1YWM25dVRqBwzfxRhWhOBO2KUKXAOAiuHm2/D9VmJ/v5C6wJvc8ZcHoevHVmTLNgImxzH/O3zKGHVK8LitBZRjys42MzF5bvo20H8F4zr25u/MqhwgbBEmCyuBqyaWq8UsJTQfwb/duzjj69TwDaBmpPH+MvVMH5dtSRFDaEPzbbp+adkxAeHZXnqifilE5cZ0zL0Wcj7LumUH8ZSeNWV14XOA7/wZY6G0lj5Lrf8sOyDt9Q3G6YHYFgohS4flJzXe5FaomPH534W1Ej7UsF3GrhnsJPM1ujIdZvev9eli+q/Q7xcz4eCz0ogaVCRwCWBbYLj37KiDwJjTjIXDzZ35fdqMB+r1Z/w2+Y7hSLTKgKXnd3MXVlh7zgOaDDb9+WG7gLFnTd+v7OPzySfkuw4YLpuq3K0rQMFG5c6vfIuhVi/9REW72sX3fT65B0x/YTogS+ie7jhVXNvucwvPL6CAcC197GN4eJtYMhb4HU3+vt7AsH+YAMg3NgLjzrFPrH85cr/h5zpM4j/eUJ783M2HM/9r9eL/TADPqmFAecP3fNdR7ATP3ROo1d18OyHYyrqbp+33MReVipFPm3tYqB+wNvBVJkhhdTRirENuHkA5Hh9SlQpo/R4z6PPdgC1H619rK1UJ+YuKYch2Y78fLqVrW35coYfnNKu8o1axNxXRX7Ia0HuR4TZTuerYfpzagKdGg5jrOi0BGL4H+JhHqe+9iHF6Z1/LkjWA8LHWB9cAhoNLYAXjVGJsS5S2I+VbKrIInvtP63pRr6+hBRQw3aFVCjd2zdDmb9QSVJGx7E68xgxc7EmVmM7SnJ/Za+v4P2dLdK7u3Cz52JaIMaeZwZg7yHSbBbzGSR5vqcVNbLW3CZeFJ1odpwLehb5zDywsgevmaUJJEeGf6eYmbOXTwr6W3PzUXsWBap2EP8ue1LmJKFRhjqwkxq2Gi9Z9SIhJMUyswPgLjOKldfPiWwL2CWSuy8e3mDzXbLQTsirt+c/TcRJjcavBMlDwjSHa4whZzEwprO5exvepOZcAU3CttyVZFZrYy/LcvjOwPHNf91up98Ec9AdQua3xOXrMY/proeef28/1XmR83fiezZC6xq52fIi1TD48rX/d/Wv9a/bv8eisuGPZgtBzIqVV2wGQwupoxAxg1lhlPHwMO5f+K4AvkhkXAC1VTQwEfPgFM1YjU/A9uBOvmw4Qs0RRMdeWq+Tx+ePWeZmxxrLLzX5yG/jwGtNJAkwHUrEVUKy0cZWpMg0Yyy07Qr/nPCaAzlKrNRt2B+rmDlTg5GBkWxe1S0t8S0WW4M9JWxTWCnjzN/37tzmBRux7sWIb4KWPhY8dUpdJRN1hMhMQwMa7mOHABUgT7S90DGutZkLHNngmLfE3tPRZFqGwNniNmQgIKZZsH21LU8OZUgKlWj5kryxos0q0ep/53+1L05PkfFZVLT7fSzFUYilAGc/4s7q0GQv0ZOWuHLwFaDeReV1/ADMhcnNj+ki2H2FQRea7sF0i2PeOX7BhFcGPbjIBcqXMpCN8fT3rDc/9p/3NhH67sNaG741cArjH1LoEcO6xyLnCMmoVUG4/xsbTj7l+dfrwW0GDKjJ+0eOigRFRwuVT3T2Y/lpIoea6mfBVN+Qbiz18eFzteOBasrVuQFzYAb7sAD9HK4pCOgV3PFA4zmUPdgX4HpIKLQ1nYtb4QfH64xR2Qv87BVz+A2gzzvLjshl3jrEWzGMpHnxLUAHlCv1RhWTlPDxhrYE4jkVD7DXgpmvpOBk4VZiWZ9BmJrdhsRDjDtm7uHBwGndpXtsBswcD7QzZUl83A1SGr+v1Ywbzck2YTexCCmxl4aWPgCMLGD9Vi0/JuQ4j9hi+51rR2L/VgFXAvYPGxxwRBTw6x/irqVRAJ5Gpa8RMzMytSAjdJ9YoV/1XA3+9q3/PvrcNFAGRVlDA8smnUL5ENtqBT+i7i7GE+gQaWjfbjAeOL2F8nPOz+T8j1fIh1w8VYJa024xlrP3x501/vsc84Nh3jEJpzeT+ASchO1ue944CMceAun2Ze69CC6B0Lf2EtkJzQ2snr3xfA9d3Ar8Xuk9w7+Fus4H7hxnfaN8gcXmhzfWHOp9l1j3b+n/AyWXM6y6fA3eimAl21U7As1usz5qwonLPW7E1fzsAeHcfcHYN0G4C34EAaJjJQsuRJr5IIX7BgB+r2p+Hr+FkxRzhY4F9he5qJaoAniJdi4RWB6YnAV+yIu+518zDl1l1e37bcLt/af7PWBucZy1OtvQvhGt8C2eC7yFpOoSjsBZ2lPHnjNsKHtdExx1Sm+mwhAgMA1Li+KO22cueXAsZYJ1iwLVo1OnNo7CKHIi4CqtvELOEVpBvfmlSiEqcJSjtgMP+rtoOh+2X1uhN4NJm8dW92IOtOo85D9sy+JAVCMX23ev8OdBsKPO7SQ23Y+MOtrV6AuCkWAlraV0pWUnyqdrgq1qpLSPD/cLAnYavARc26EuRsu9Tazt87n08fA+wRiAQpdscRjkyh9bSL1SUg62w+pUCMp8Zy1CiErCAda5us4BOUxnF7KHAEqU9Aoq0kwKVSu+aYs4totUo5g8A0p9afs4a3YDbhRM1Nw9mkhDagPGzLlPf0K2oXGP9a+/iQG0Bn0kjTHyHEpUZ1wBLlG32teebxGmvI3uSVa8f00/5BTMWvbFnmSp/wdWApSyXMz7lSfsbcAOjhO6BrrMYP/geX/Pv/+QukJ5gbPkceQBY1cn8JKBmJHBtG/N66D+m2wKGz4DQpJf7XUxlj+G25f52KjcmGGrPZ8bbtbDHD0dXlyKFlbAKvk6KL/iky+dMzein100HcemOa8Ng8vZW4MBX/JHQwVUZBUnIJ5D7IJiaOWqPz/0Mn9+X2M6cbQ1l+59aq6wCTMfLB1sm7ZJO2YaMohFYgfEB9S5u6ItrCvZ14CuFy87hx7a8qVR6Z3qpYctULNRwwPIPYZbgpj0Wjn619lxs+iwF/ha5GmCtEtVjHhPB/xfH2jNkG7DlXeOAQ7YiINbPlE8+UwNHvb7ijqldBhWjsHaaAvzzkeH+ktX5J6fa51BIRimq3zEH0r8Um87J3ds4qwbA309U6wLc3Sd8LHZgpocXc4xRhxlZpMjfC5h/Pi21DFtjYYWKySCie6sCQuroX3M/ywfXT5tP7r7LgcZvGm9n41+S+eNSvimT+N5cCiz2edlBjaIQUlg527WFMAAmy0DsCeG23Pdu7kwMiYcPcPBr/SSRvUrm6ccEET88w2R14Sq39oTv/ile1nHnlwjyYXU0fDcOn1+id3HG4T7ETOS/7rg2RCOXqsEEiwill2n/MdBCIHOBX0nDXJ9CnYO7NxORD4iTVXedzAwg2g4YYPxPpUIbBMH2RWP/dmwfpDZj9cqG0GDP953TE/Wv+QbjToURwmUb2aaAC8H1awMM5R++i+mIpzxi0q5oFSVPX9smSHznYmNJWVVTCoapwhitRjH+W3y/y4DVQFuO7zZ7wLSkeg2b/50yfd0stYJwA5a0sAd/vvyx7p6m7ychZconSLRoJiklworMZfx5oMnbzJI9Gz5Za3RlVlmEYK+gaJ9pNzfplFWAeWb7/mh9kRguYl1jxCrC3KArI1iTioavsz7HOv6og0wgEXu/NXj5m5fbFuu+WAsru53YYNoWhZPb2r2Y/rHlSEPjAjvGwcObGUf7LXd8/lO+vsXa4g8yQhZWR2P04JnpiKp1Bg4I5GU1eVwHEVyF+dtSqNAKdqysDpD78OTx+Mxpv4+5jrpOH8aXzZSjvzUMWAOcW2eYaN87gOmc1PnCxRaEfofPC4M7ZrAsW+kJzOD5/K5h/lItPgGmB15bqcmzNO3mDry9jXG1CK7CbPMuZtxOCsTcs+zfn88iYOoYVdozAXR/jxVuU7UD49tnzqdMpWImZjlp+kA9S/ELBlJNJEfXfpfqEYYVwbR0/oyxHmo5s4r/OGzrN5/1zNx3ZVuaLPmcWMoITAJ18FiwA8sbJ0MH+Ccc5qyb1SNM75eKxjyBPlLAN1Fh/87VI4CUh4buDFwMXAx4rqHQKgL7c+Wa6P3t7c39I9Ifk3vvsd2ubu8Wdwy+XNL5LONDDGuCxe7LAlh9malANqngnRBYsFKkEEhhtQduHsaBO1p4O2gTSlmFZowzuzl/RWutPnLAfXj4BkJtm+ICg6cWlUqcE7+lFCtt7CKhUjFWBUDYUiaY746nvZsnY4HRFCgrgbOptEJSIsqipWIsFi9imBynfPtNYqZTbjmamYhU7WBeFGsyDxj87mZk1S7Tc5WFbrOBKh0Y9xM29frxuwuZs35z7zWu5VRopcIeOWX57oFAC9xd2DJVaMlEZbOzefDh5Wd6v1KJnAtkJAJHWan8us1m+hF2/z/4T+YeMnUfsMehlDgzJ2b9RlJaoS2h0RtMoJ1ViLSwCo3ZllK1A/DkMjPBbvq2cXyGls6fM8F32pyy9oTt2uUdCOSkWFctUmZIYbUHETOBPdP49/FVFDHnG2bKejjgJyYaciBP0nc5EJqZs7dzB0y+5UntrN+mKHw7YG7QtmRZ97PEwkFFLs8cmQYfS1CpmCChu/v4gyLMDaB89yM72biHl+nKMbbiW4JJQ6VRM4ogOw1Pv5XA1lEsWbSWUY7MQtk9Gg8W59/ORXsPj4hi/Oi6CwTKAECDgcDlwgIddlFWeI5ZrDRTwWqliEkE2zpYqzuTQcPW8yuV8P8x/9kKK9+9IcYXl2spvcepGMY2FBgcS6brFTGDGQuE8tWaQqxLgFQKa6ephWkQezBBuc/v8ueSbf8x8+cIfIOAt7YwcREB5YEb/wBN7Fim206QwmoPLEkTApiugGKOBq9Kk3NSKoQ6B3YFJK7vDN+SFPs6Ve3In05JifB9F74cgIA0fqAuB/f+UQHFyxgvr9bsATy7aT4Ag69MslAks70YsFr/2ieQyf/r4cMEoWgVVnbtevbSpCmqRzCJ1cvUAxaZKG866iCwbQyQeNVwe1hL47RmXIIqAhNviEuVZQ1C/YWp5Ww27AlisjlLoYtQpj7w5Iptx2D3Ux7ejA/+hV+Z92GtGT9L3s/JpLCqVDaUORapsJrL7uJfGsgQkZXCy98w5iPiC/OfcQRsV5jW78knhw3QiGkPTFlMhXK/2VoTWylonclN+YmxO8sOk/iviVwlLW2FK3ePb4GeNlQbK2qI9cV+8zcm4bo5RcqfJ32MvTIsiCWwPH/EtBa+CH4+VCrGD5ntU8tOdq+lXBPzJVWFCCzP+Nv5BZtvaxU2KkDsSV/0WuF2gjifHx+qiLA8m4OteHr4MP31yANMuq0Ru/X+68YftP3cjkase17mC/1rPj9usc8lYTdIYbULJjpBoQG5XGNm6fODi3aRyOGYSpnBVuqKlTFMrqzFICjAiW5TrsLaarRy/YvlspaYwlz6GPZ2MRbqxoOA+gpagRBD97lMdhB3L+DNTZZ9Vuh6WZKKC2AqlpWqybgE2BNrSjtLiTP1LVqqvGS+jTnYVnwPb+a+Kd9UYGKiAB9Wa+hYmGWlF88kDjBWZNl5zyPnGLe3ZSWUkARyCbAHpgYHUx1kxVbSy+Io+iwF/vlYX0JQ7DVQqZhE3kZtFOA3ZQ22pBcjpEelAl79Cbjyp9ySiCewAvC/41Z+WEhhFelmoKXnPCvPL5J39wMJl4RLb0qBpz9TcS+knrE7hA4n6lu01OwOvLqGcQ2wFnbBFXM5lZ1JSWXTcRKTclCoDCo7RypgGCvCV7I08itgXW/7PxuEIKSw2gUTypqzLnWbo+kQxldTF0BlwTUwZymr0ZUJuvGyU3olKWF/t5Jm6oMTPPD4sBK2o61p7uiSkEJUaMb8SUkpTsGPUQcZN4G2E4Bji4GTP+j3acto1h8grQyOQKWyXW62smYv/2QlIKSsAsbfm21k4fMjL9cYmPpQErEI6yCF1R6YsrI54xKUIBxlgh3tz/XjZfvoGlwfEQpJi5FMKbuK4RZL6HCESvEpEgUqg6aSedtCz/nAvx87ZWSsJJRtBIw+wkQIOxuVRS6BD/nb8H3pmox7BWDskzn6EJOrVEwpXFeEHQRryTPmSuNXxXDG0HLuF+Y9+zqIDXwkHAoprPagyWBg1yT+fa70wJuyFrNnq63HGEb9mquLzcXdw4ksIazv4yL1mx2KvZYfm77DVC2ryFPdq6jAzePqKnyWCORmmA4MazwIOP+r3gXBy7/oKquAoUuAOdj9vLO6B/ChUjGubFqFlY2lLjSEQ3Ah7UlBeBcX9gtypQfelIXOVKYEPkVXaflWrYX9+/ItR5WuY7ytKDPyAPDyEv17SyvBicXDi8mF6KouOVpcqn8RiYe3+SwGXv6MVVVbHrqoU2BBztF2E+0nh5KwNDCRcDiksDoaV7KwmhwcNQKvwe8SMPqwawwm7N+Xzzlfu42dvL4oU74pJ3E/N0uAQ6WRj6BK0hzH00mrOBGORZ1nvo0WdsYXcwFazgx7PCPlVZHQmqXdEKrF7OIWHi3sB5778LsJuARINWjLCuv7BFc13l3lJWD8eWX4EirRGudKEzoxDN4CnF8PdJtl23G6fsnULectX0sQHCzx0fT0Yays+TlMTl5Xo2R14Pkd50t/VwQhhdXRuNSSpBQKjwKVJltQifBh5VNkCQYjJdrF7g8uNSKYP1tp+wHz50pEfgUcWcBfDIGwDUt9NJVSrckejNwPPL1lugQ6oQiKmDlDARQVC2vtnqw3InOyarMAOHOwEtua7MzfQzZEFg4gXJ/wMcAnd4EQmYsLuCKmYgyKGj6BQFgLTl9DLgFKhBRWR9CD5cvIXfJ05nJvppQJ9tKk2CICQWHAhMvAp/dsl00u2JYLxVvTFagMkoJKsKH7gSCIQkhhtRdsJa3lSEaBazZMn6u09f+Y/914SsApnYAKzH9TNa3Fzla5A1JQRedW4oXqVhPisFeWAIIgCGsgFy7FQGuWdoOlpKlUwGtrDXdHfgWEjwUCFRB8YynDdwEXNwEtRphu5x0A5KQCNSJNNHIxhYQSTtsGdwJTpb08chAEQQDAe0flloAohBRWe2HOR0ilck5lFWCW7jt8Yr7d+AtM+UNTydpdbcnPmRJOK/LaF8o04TIQfwGo87Ks0hAEUQSp1oWxrJZtbLq8K+FQSGG1F5THDfAvyfyZRIlKkw2QhdU2tEp0UEXmjyAIwtF4+gBjow1TMBKyQ7+G3SCFtUjiKhW7CIIgijKkrCoOu/wiaWlpmDBhAipVqgRfX1+0adMGZ86c0e0fOnQoVCqVwV/37t0NjpGUlITBgwcjICAAQUFBGDFiBNLT0+0hLkFIR83uQP/VwP9OyS0JQRAEQbgMdnEJePfdd3HlyhWsX78e5cqVw6+//oqIiAhcu3YN5cszfpvdu3fH2rX6QCRvb8OSb4MHD8bjx48RFRWFvLw8DBs2DKNGjcLGjRvtITIhFyWryS2BtKhUQMPX5JZCJC7mjkEQBEG4LJIrrFlZWdiyZQu2b9+O9u2ZCN8ZM2Zgx44d+PHHHzF79mwAjIIaGhrKe4zr169j165dOHPmDJo3Z6pPLF26FD179sT8+fNRrlw5qcUmHM3I/cCLB0wteYIgCIIgCBNI7hKQn5+PgoIC+Pj4GGz39fXF0aP69BAHDx5ESEgIatWqhffffx/Pnz/X7Ttx4gSCgoJ0yioAREREwM3NDadO8S+15uTkIDU11eCPUDDlmwH1qe45QRCEfNAqC+E8SK6wFi9eHOHh4Zg1axbi4+NRUFCAX3/9FSdOnMDjx48BMO4Av/zyC/bt24dvvvkGhw4dQo8ePVBQwERYJyQkICQkxOC4Hh4eCA4ORkJCAu95586di8DAQN1fWFiY1F+NIFwLJaa1ouwaBOE4PHzMtyEIhWCXoKv169dDo9GgfPny8Pb2xpIlS/Dmm2/CrTDq7o033kCfPn3QoEED9O3bFzt37sSZM2dw8OBBq885ZcoUpKSk6P7i4uIk+jYEQRAE4YK4UWZLwnmwi8JarVo1HDp0COnp6YiLi8Pp06eRl5eHqlX5S5xVrVoVpUqVwp07dwAAoaGhSExMNGiTn5+PpKQkQb9Xb29vBAQEGPwRBOFkKNHqSxCuCj1vhBNh10Rj/v7+KFu2LF68eIHdu3fjlVde4W338OFDPH/+HGXLlgUAhIeHIzk5GdHR0bo2+/fvh1qtRqtWrewpMkEUIWiwIoiiDfUBhPNgl/WA3bt3Q6PRoFatWrhz5w4++eQT1K5dG8OGDUN6ejpmzpyJAQMGIDQ0FHfv3sWnn36K6tWrIzKSqTlfp04ddO/eHSNHjsTy5cuRl5eHsWPH4o033qAMAQRBEAQhBWRhJZwIu1hYU1JSMGbMGNSuXRtDhgxBu3btsHv3bnh6esLd3R2XLl1Cnz59ULNmTYwYMQLNmjXDkSNHDHKxbtiwAbVr10aXLl3Qs2dPtGvXDitXrrSHuARRRKEAJ4IokrQZz/zvPldeOQjCAlQajWuG5aampiIwMBApKSny+LPeOwT8NRJ4eTFQq4fjz08QQswIZP5HfgWEj5FXFi1amfxLA5/ckVcWgnB1NBog4xlQrLTckhCEaH2NQgTtRdUOwEc3acmFUDB0bxJEkUSlImWVcDrsGnRV5CFllSDEUTGc+d94sLxyEARBEIqELKwEQcjPoM1A7Emgake5JSEIgiAUCCmsBFFUUdIKgE8AULOb3FIQBEEQCoVcAgiCIAiCIAhFU+QtrAUFBcjLy5NbDEIE2rRoBEEQBEEULYqswqrRaJCQkIDk5GS5RSEsICgoCKGhoVApaTnbaaFrSBAEQTgHRVZh1SqrISEh8PPzIwVI4Wg0GmRmZiIxMREAdGV8CYIgCIJwfYqkwlpQUKBTVkuWLCm3OIRIfH19AQCJiYkICQkh9wCCIAiCKCIUyaArrc+qn5+fzJIQlqL9zcjvmCAIgiCKDkVSYdVCbgDOB/1mEkLXkiAIgnASirTCWpRo3749Nm7caNMxZsyYgcaNG0sjEIdr166hQoUKyMjIsMvxCYIgCIJwXkhhLQL8/fffePLkCd544w25RRGkbt26aN26NRYuXCi3KARBEARBKAxSWIsAS5YswbBhw+DmpsyfW+uPOmzYMPz444/Iz8+XWaKiArkEEARBEM6BMjUYgpeOHTti7NixGDt2LAIDA1GqVCl8/vnn0Gg0gp95+vQp9u/fj5dfftlgu0qlwooVK9C7d2/4+fmhTp06OHHiBO7cuYOOHTvC398fbdq0wd27d42OuWLFCoSFhcHPzw8DBw5ESkqKbt+ZM2fQtWtXlCpVCoGBgejQoQPOnTtndO4ff/wRffr0gb+/P+bMmQMA6Nq1K5KSknDo0CFbLhNBEARBEC4GKaxOxs8//wwPDw+cPn0aixcvxsKFC7F69WrB9kePHtUppFxmzZqFIUOG4MKFC6hduzYGDRqE0aNHY8qUKTh79iw0Gg3Gjh1r8Jk7d+5g8+bN2LFjB3bt2oXz58/jf//7n25/Wloa3nnnHRw9ehQnT55EjRo10LNnT6SlpRkcZ8aMGejXrx8uX76M4cOHAwC8vLzQuHFjHDlyxJZLRBAEQRCEi1Ek87AaodEAeZnynNvTz6Jo7bCwMCxatAgqlQq1atXC5cuXsWjRIowcOZK3/YMHD1CmTBled4Bhw4Zh4MCBAIBJkyYhPDwcn3/+OSIjIwEAH3zwAYYNG2bwmezsbPzyyy8oX748AGDp0qXo1asXFixYgNDQUHTu3Nmg/cqVKxEUFIRDhw6hd+/euu2DBg0yOjYAlCtXDg8ePBB9PQgboCwBBEEQhJNACivAKKtflZPn3FPjAS9/0c1bt25tkNopPDwcCxYsQEFBAW8i/aysLPj4+PAeq2HDhrrXZcqUAQA0aNDAYFt2djZSU1MREBAAAKhYsaJOWdWeX61W4+bNmwgNDcWTJ0/w2Wef4eDBg0hMTERBQQEyMzMRGxtrcO7mzZvzyuTr64vMTJkmDwRBEARBKBJSWF2cUqVK4cWLF7z7PD09da+1SjDfNrVaLfp877zzDp4/f47FixejUqVK8Pb2Rnh4OHJzcw3a+fvzK+lJSUmoVq2a6PMRBEEQBOH6kMIKMMvyU+PlO7cFnDp1yuC91k9UqExpkyZNkJCQgBcvXqBEiRJWi6klNjYW8fHxKFeunO78bm5uqFWrFgDg2LFjWLZsGXr27AkAiIuLw7Nnz0Qf/8qVK3j11VdtlpMgCIIgCNeBFFaA8eWzYFleTmJjYzFx4kSMHj0a586dw9KlS7FgwQLB9k2aNEGpUqVw7NgxAx9Sa/Hx8cE777yD+fPnIzU1FePHj8fAgQMRGhoKAKhRowbWr1+P5s2bIzU1FZ988gl8fX1FHTsmJgaPHj1CRESEzXISBEEQBOE6UJYAJ2PIkCHIyspCy5YtMWbMGHzwwQcYNWqUYHt3d3cMGzYMGzZskOT81atXR//+/dGzZ09069YNDRs2xLJly3T7f/rpJ7x48QJNmzbF22+/jfHjxyMkJETUsX/77Td069YNlSpVkkRWgiAIgiBcA5XGVBJPJyY1NRWBgYFISUnRBQxpyc7Oxv3791GlShXBgCQl0rFjRzRu3BjfffedRZ9LSEhAvXr1cO7cOcUqg7m5uahRowY2btyItm3bCrZz1t9OUcwIZP73nA+05M8uQRAEQRCOwJS+xoYsrEWA0NBQ/PTTT0aR+koiNjYWU6dONamsEhJDaa0IgiAIJ4F8WIsIffv2lVsEk1SvXh3Vq1eXWwyCIAiCIBQIKaxOxMGDB+UWgSAIgiAIwuGQSwBBFFnIJYAgCIJwDkhhJQiCIAiCIBRNkVZYXTRBgktDvxlBEARBFD2KpMKqLT9KNeudD+1vxi4hSxAEQRCEa1Mkg67c3d0RFBSExMREAICfnx9UlOJH0Wg0GmRmZiIxMRFBQUGCpWgJC6B7niAIgnASiqTCCkBXSlSrtBLOQVBQkO63IwiCIAiiaFBkFVaVSoWyZcsiJCQEeXl5cotDiMDT05Msq1ISXFVuCQiCIAhCFEVWYdXi7u5OShBRtBi+B0i8BlTtKLckBEEQBCGKIq+wEkSRo2Ir5o8gCIIgnIQimSWAIAiCIAiCcB5IYSUIgiAIgiAUjcu6BGgTzKempsosCUEQBEEQBMGHVk8zVxjIZRXWtLQ0AEBYWJjMkhAEQRAEQRCmSEtLQ2BgoOB+lcZFa12q1WrEx8ejePHiDikKkJqairCwMMTFxSEgIMDu57MXLVq0wJkzZyQ9pqtcG6kRui72+A2cCbnvFyVff7mvjaOw9DcoKtfFGqy5Nkp+BqRC6feMnL+Bo6+NRqNBWloaypUrBzc3YU9Vl7Wwurm5oUKFCg4/b0BAgCJvfrG4u7vbTX5nvzb2gntd7PkbOBNy3S/OcP1d/Vmy9jdw9etiC5ZcG2d4BqRCqfeMEn4DR14bU5ZVLRR0RRgwZswYuUUo8tBvIC90/eWHfgN5oesvP/QbGOOyLgGOJjU1FYGBgUhJSZF9VqQ06NrwQ9eFH7ouwtC14YeuizB0bfih6yKMUq8NWVglwtvbG1988QW8vb3lFkVx0LXhh64LP3RdhKFrww9dF2Ho2vBD10UYpV4bsrASBEEQBEEQioYsrARBEARBEISiIYWVIAiCIAiCUDSksBIEQRAEQRCKhhRWgiAIgiAIQtGQwkoQBEEQBEEoGlJYCYIgCIIgCEVDCitBEARBEAShaEhhJQiCIAiCIBQNKawEQRAEQRCEoiGFlSAIgiAIglA0pLASBEEQBEEQioYUVoIgCIIgCELRkMJKEARBEARBKBpSWAmCIAiCIAhFQworQRAEQRAEoWhIYSUIgiAIgiAUjYelHzh8+DDmzZuH6OhoPH78GFu3bkXfvn1527733ntYsWIFFi1ahAkTJui2JyUlYdy4cdixYwfc3NwwYMAALF68GMWKFdO1uXTpEsaMGYMzZ86gdOnSGDduHD799FPRcqrVasTHx6N48eJQqVSWfk2CIAiCIAjCzmg0GqSlpaFcuXJwcxO2o1qssGZkZKBRo0YYPnw4+vfvL9hu69atOHnyJMqVK2e0b/DgwXj8+DGioqKQl5eHYcOGYdSoUdi4cSMAIDU1Fd26dUNERASWL1+Oy5cvY/jw4QgKCsKoUaNEyRkfH4+wsDBLvx5BEARBEAThYOLi4lChQgXB/RYrrD169ECPHj1Mtnn06BHGjRuH3bt3o1evXgb7rl+/jl27duHMmTNo3rw5AGDp0qXo2bMn5s+fj3LlymHDhg3Izc3FmjVr4OXlhXr16uHChQtYuHChaIW1ePHiAJgLEBAQYOnXJAiCIAiCIOxMamoqwsLCdHqbEBYrrOZQq9V4++238cknn6BevXpG+0+cOIGgoCCdsgoAERERcHNzw6lTp9CvXz+cOHEC7du3h5eXl65NZGQkvvnmG7x48QIlSpQwOm5OTg5ycnJ079PS0gAAAQEBpLASBEEQBEEoGHPum5IHXX3zzTfw8PDA+PHjefcnJCQgJCTEYJuHhweCg4ORkJCga1OmTBmDNtr32jZc5s6di8DAQN0fuQMQBEEQBEG4BpIqrNHR0Vi8eDHWrVvn8ECnKVOmICUlRfcXFxfn0PMTBGF/nmU9w9LzSxGfHi+3KARBEIQDkVRhPXLkCBITE1GxYkV4eHjAw8MDDx48wEcffYTKlSsDAEJDQ5GYmGjwufz8fCQlJSE0NFTX5smTJwZttO+1bbh4e3vrlv/JDYAgXJOPDn6ElZdWYvju4XKLQhAEQTgQSX1Y3377bURERBhsi4yMxNtvv41hw4YBAMLDw5GcnIzo6Gg0a9YMALB//36o1Wq0atVK12batGnIy8uDp6cnACAqKgq1atXi9V8lCML1Sc9Nx7nEcwCAR+mPZJaGIAguBQUFyMvLk1sMQmF4enrC3d3d5uNYrLCmp6fjzp07uvf379/HhQsXEBwcjIoVK6JkyZJGgoaGhqJWrVoAgDp16qB79+4YOXIkli9fjry8PIwdOxZvvPGGLgXWoEGDMHPmTIwYMQKTJk3ClStXsHjxYixatMiW70oQhBOz6eYmuUUgCIIHjUaDhIQEJCcnyy0KoVCCgoIQGhpqk7uoxQrr2bNn0alTJ937iRMnAgDeeecdrFu3TtQxNmzYgLFjx6JLly66wgFLlizR7Q8MDMSePXswZswYNGvWDKVKlcL06dNFp7SSi//u/4ffbvyGee3noYx/GfMfIAhCNDkFOeYbEQThcLTKakhICPz8/KhYD6FDo9EgMzNT5wpatmxZq49lscLasWNHaDQa0e1jYmKMtgUHB+uKBAjRsGFDHDlyxFLxZOXTw0wlrm/OfIOFHRfKLA1BuDYF6gK4u9m+zEQQhPUUFBTolFXuCitBAICvry8AIDExESEhIVa7B0ie1ooAUnNT5RZB0eQU5GDH3R14nvVcblEIJ4I7UZ50ZJJMkhAEoUXrs+rn5yezJISS0d4ftvg4k8JqD8QboIsk30V/h6lHp2LorqFyi0I4ERrOg7U7ZrdMkhAEwYXcAAhTSHF/kMJqB7gDK2HIngd7AAAxqTHyCkI4FZa4IhEEQVjDwYMHoVKp7BJAlpubi+rVq+P48eOSH1tOdu3ahcaNG0OtVtv1PKSw2gG1xr4/mrNDigdBEARR1Fi+fDmqVKmCNm3aWPzZBw8ewNfXF+np6TbJcPDgQcyYMcOifX369EHFihXh4+ODsmXL4u2330Z8vL54S/fu3eHp6YkNGzbYJJs5SGG1A2efnJVbBEVDCj1hDbde3JJbBIIgXJjc3Fy7HVuj0eD777/HiBEjrPr89u3b0alTJxQrVsyqzy9fvtygaFNubi4WLFiAvLw8k/sAoFOnTti8eTNu3ryJLVu24O7du3j11VcNjj906FCDbE/2gBRWwuGQwkpYw6GHh+QWgSAIF6Jjx44YO3YsJkyYgFKlSiEyMlK3Lzo6Gs2bN4efnx/atGmDmzdvGnz2xx9/RLVq1eDl5YVatWph/fr1Js8VHR2Nu3fvolevXgbbjx8/jsaNG8PHxwfNmzfHtm3boFKpcOHCBYN227dvR58+fQAwymHfvn3x1VdfoUyZMggKCsKXX36J/Px8fPLJJwgODkaFChWwdu1a3efDwsLQp08fbN26FVevXkXnzp0BML6lpvYBwIcffojWrVujUqVKaNOmDSZPnoyTJ08aBFC9/PLLOHv2LO7evSvm0luFpJWuCEIMapDCShAEQcjPzz//jPfffx/Hjh0DADx+/BgAMG3aNCxYsAClS5fGe++9h+HDh+vabN26FR988AG+++47REREYOfOnRg2bBgqVKhgkKeezZEjR1CzZk0UL15cty01NRUvv/wyevbsiY0bN+LBgweYMGGC0WeTk5Nx9OhRA6V4//79qFChAg4fPoxjx45hxIgROH78ONq3b49Tp07h999/x+jRo9G1a1dUqFABvXr1Qrt27dC6dWvExsbi6NGjaNKkCQCY3MclKSkJGzZsQJs2bXSVSAGgYsWKKFOmDI4cOYJq1apZ8AuIhyyshMMhCytBEITrotFokJmXKcufpTESNWrUwLfffotatWrpKnICwJw5c9ChQwfUrVsXkydPxvHjx5GdnQ0AmD9/PoYOHYr//e9/qFmzJiZOnIj+/ftj/vz5gud58OCBrpqnlo0bN0KlUmHVqlWoW7cuevTogU8++cTos//++y8aNmxo8Png4GAsWbIEtWrVwvDhw1GrVi1kZmZi6tSpqFGjBqZMmQIvLy8cPXoUABMY1b17d3Tr1g09e/bE+PHjsXjxYhQUFJjcp2XSpEnw9/dHyZIlERsbi+3btxvJWa5cOTx48EDklbccsrASDocUVuBe8j2sv74eoxqMQtli1lf+IAiCUBpZ+VlotbGVLOc+NegU/DzF54Rt1qwZ7/aGDRvqXmurMyUmJqJixYq4fv26UeXNtm3bYvHixYLnycrKgo+Pj8G2mzdvomHDhgbbW7ZsafRZtjuAlnr16sHNTW9zLFOmDOrXr6977+7ujpIlS+p8U+/fv4/t27fj2rVrOHjwIDZs2IAlS5ZArVab3KdN8v/JJ59gxIgRePDgAWbOnIkhQ4Zg586dBumqfH19kZmZKXgNbIUUVsLhkMIKDNk1BCk5Kbj67Co2v7zZZNt8dT5SclJQ0peqyBAEQUiJv78/ACAtNw0vsl+gQM1YFdnL3VqlzJa0TaVKlcLly5ct/lxubi527dqFqVOnGmxny6eVkW+bVub3338fAHDt2jUAgJeXFz7++GOz+9jylypVCjVr1kSdOnUQFhaGkydPIjw8XNcmKSkJpUuXtvg7ioUUVjuRW5ALL3cvucVQJJTWCkjJSQEAXE+6brbt8N3DcT7xPP54+Q/UDq5tb9EIgiBswtfDF6cGnZLt3NYQmxoLAEjKSTLbtk6dOjh27Bjeeecd3bZjx46hbt26gp9p0qQJfvzxR2g0Gp0CXKtWLfz666/IycmBt7c3AODMmTMGnzt48CBKlCiBRo0aWfyd+OjYsSM6duxo8T42WiU4JydHty07Oxt3794V9H2VAlJY7cT+uP3oXrm73GIokgJNgflGhI7ziecBANvubMPklpNlloYgCMI0KpXKomV5JaG1sJrik08+wcCBA9GkSRNERERgx44d+Ouvv7B3717Bz3Tq1Anp6em4evWqbul+0KBBmDZtGkaNGoXJkycjNjZW5werVWr//vtvI3cAR3Lq1CmcOXMG7dq1Q4kSJXD37l18/vnnqFatmoF19eTJk/D29jbYJjUUdGUn7F3xwZkpahbWJxlP8MmhT3SKp9a6aikqUOlDgiAIeyKmn+3bty8WL16M+fPno169elixYgXWrl1r0jpZsmRJ9OvXzyC5fkBAAHbs2IELFy6gcePGmDZtGqZPnw4AOr9WuRVWPz8//PXXX+jSpQtq1aqFESNGoGHDhjh06JDOKgwAv/32GwYPHgw/P/tNVMjCaifcVEV7LvAs6xlOxJ9A76q9jWoIF7W0Vp8f+xwnHp/ArphduPzOZUQ9iLLqOFSrmyAIQjoOHjxotC38pXAjo0rjxo2Ntr3//vs630+xTJs2DV27dsW0adN0BQDatGmDixcv6tps2LABnp6eqFixIs6dO4fU1FR06NDB4Djr1q0T9V1iYmIsko+PBg0aYP/+/SbbPHv2DH/++SfOnrVv0SRSWO1EUVdYO21mctGdTzyP6eHTDfaJCbpi+/k4Oycen5DkOGRhJQiCcF4aNmyIb775Bvfv30eDBg0AAL/88guqVq2K8uXL4+LFi5g0aRIGDhwIX19f5OfnY+nSpUbBVEojJiYGy5YtQ5UqVex6nqKtVdkRV1G2bOWPW39Y/JnTj0+j4+aO2Pdgnx0kkh9rFc+iPgkiCIKwN/Y2DAwdOlSnrAJAQkIC3nrrLdSpUwcffvghXnvtNaxcuRIAk+Lq7bfftqs8UtC8eXO8/vrrdj8PjYB24vJT4/QVmXmZWHtlrS4asSih0Wgw+chkLDlnvtbwiD0jkJSdhAkHJ9hfMCfibrL9St45IyW8S8gtAkEQroaDbU2ffvopYmJikJ2djfv372PRokV29QN1ZkhhtRNrr6412rYoehEWRi9E3+19HS+QjNxMuonXd76Of+79g1WXV8ktjuxYa30/8uiIxJI4N1UC7bv8JDcajQZPM5/KLQZBuDxFLRCYTU5BDnLyc8w3VACksErEvZR7ZtucfcI4JOep8+wtjmLoWqkrXt3xqqh8o4QxOQWGHcmZhDPIzs+WSRrCkcw9PRed/+iMHXd3yC0KQbg0qbmputdFKVZAo9Hgzos7uJN8R1Q6L7khhVUiXtn2itwiKAb2bLVRaWmSHbsSlnSIu2N2G7wfvns4Jh2eJLVIioeruAOu7yf+243fAADfRX9n87Fuv7iNJxlPbD4OQQjhzFbK9Nx0uUVwODn5OYhLi9O9t3d+dCnuD1JY7YSHm2EChpyCHNxJviOTNI6FfeNToJAxphSto4+OosHPDdDg5wbIU+chM8+4LvP+ONMpRlyRtNw0o210b4njcfpj9P+7PyL+jMDlp5fJzYCQFG0Euz1ryNsbDZxX2bYUbZae+6n3efvVvII8xKTEIDUn1WifLWjvD1syHlic1urw4cOYN28eoqOj8fjxY2zduhV9+/bV7Z8xYwY2bdqEuLg4eHl5oVmzZpgzZw5atWqla5OUlIRx48Zhx44dcHNzw4ABA7B48WJdXjIAuHTpEsaMGYMzZ86gdOnSGDduHD799FOrv6jD4dz/rhrxzgcprKYxZWF9f68+r9/fd/5GbkGuI0RSPHzXrMgs3dn4NW++uKl7PejfQQCAy+9YXtNcbrLzs7Hq8ip0DuuMeqXqyS0OUYi7uzuCgoKQmJgIgEk072yrH3m5eVDnMYpcviof2dmu6XaVkZuB+Ix4BPsEIy/H0DUxIzMDOe45eJj6EPmafKRlpqFGiRo2n1Oj0SAzMxOJiYkICgqCu7u71ceyWGHNyMhAo0aNMHz4cPTv399of82aNfH999+jatWqyMrKwqJFi9CtWzfcuXMHpUuXBgAMHjwYjx8/RlRUFPLy8jBs2DCMGjUKGzduBACkpqaiW7duiIiIwPLly3H58mUMHz4cQUFBGDVqlNVf1pFwZ2xFqRwp2xfGXSXu5nye9RzBPsFO19GZI1+db/CeTwGNehCFrpW6Gm1/lvUM7m7WP9yuBJ8FxNqKYc6GrUtprqLYr7q8CisvrcTKSytFKdz56nwUaArg7e5ttq2rkpGXgXNPziG8XLjRqh8A7InZA3eVO7pU6mLTeUJDQwFAp7Q6G/Hp8brX6R7pyPLJklEa+/Ek8wkK1AVIhPHvxLfNI1m6VP1BQUG6+8RaLJamR48e6NGjh+D+QYMGGbxfuHAhfvrpJ1y6dAldunTB9evXsWvXLpw5cwbNmzcHACxduhQ9e/bE/PnzUa5cOWzYsAG5ublYs2YNvLy8UK9ePVy4cAELFy50GoWVq6AWpSWHfI1eSRNjYT366Cje3/s+elftjbkvzbWnaA6Hq7A2+7UZBtQYYLBt4sGJvAOwl7uXywVYZeRlQAXxdcbz1fnYcXcH7qfcN9rHthy6Mk+zhJfws/Kz8MWxL9ClUhdEVo4EwCz5ueLKxo2kGxa1b7K+CQDg6BtHEegdaA+RFE/rja0BAEPrDcVHzT8y2Jeam4qPDjHbzr511ibFXqVSoWzZsggJCUFenvMFFU/dORUZeRkAgIhKERhfZ7zMEtmHmbtmIikrSXT7v/v9Lcl5PT09bbKsarFrpavc3FysXLkSgYGBaNSICb45ceIEgoKCdMoqAERERMDNzQ2nTp1Cv379cOLECbRv3x5eXl66NpGRkfjmm2/w4sULlCjhfPkXndkh3VLYFtaEjASz7VdeYpIk77y30+UVVgDYcnuLqM+qoBLMKJGnzkOBugA+Hj42yedIcgtydQPoxSEXRSlVf976E3NOzbG3aE7J86zn+P3m7/gv5j/8F/MfIitHYt+DfZhydAq+eekbdKrYSW4RJUVMhTw+Vl1ahY9bfCyxNM7FuqvrjBRWtv9igboAkGAxx93dXRLFxNFUDK6oiw3IRCZ8fJynX7WExNxEPM0V78OutOtgl2n4zp07UaxYMfj4+GDRokWIiopCqVKlADBVHUJCQgzae3h4IDg4GAkJCbo2ZcqUMWijfa9twyUnJwepqakGf0qiKFlY2dblxEzTS0Rrr6zF+cTz9hZJNvgUViG47gJqqAUV1qbrm6LFhha8QVlK5UmmPkpdrG+uNhUcYciVZ1fQcXNH/HjxR4PtEw5OQFZ+FsYf0FuIXMXNxto+9E5K0Qh2tRS2YeFE/AlMPzbdqfoTSzkefxzH44/z7mPfW67yvPBh7aRPKdhFYe3UqRMuXLiA48ePo3v37hg4cKDdfVvmzp2LwMBA3V9YWJhdzycGtlX19ovbgu0uJF7AmH1j8CD1gSPEsjtsJc3cA7IweqG9xZEVtnuEOV7b8ZrBe7VGWGHV0uUP23zPHApL3+BLU8WHuYj2JeeW6O43Vx5subz5z5tG2yyZHDkj7P7U3H3Bbnv68Wm7yaQ00nLTsD92v6gJIbtvmnBwArbe2YrVl1fbUzzZyMzLxOio0RgdNZq3n8hV66+XG0stysrPwsO0hw6R0RE4u+HMLgqrv78/qlevjtatW+Onn36Ch4cHfvrpJwCMczZXec3Pz0dSUpLOITc0NBRPnhjmDNS+F3LanTJlClJSUnR/cXFxvO0cybWka7rXJXyE3Rje/u9tHH54GB8e/NARYjkUSxQ2QLwi4yxYokRwi0+cTzxvNmAmPU+Z+QPjUuOw8tJKrL68WjdZU0M/edkdsxupual4lvXM5HHOJZ4zuX/V5VX46/Zf+Pfev2i1sRXmnpqLAX8PcLpk+2qNGptubBL007z+3HzhjSvProg+nzMWL2FPfjv/0dlkW0v96F2F9/e+jw8OfICl55eabcvXN5ly4dpxdwf6bOuDmJQYW0SUhcx8vZKaXWAcF3Ds0THda/b9MnDHQPT4q4fF/tNKhSysIlCr1cjJYRSR8PBwJCcnIzo6Wrd///79UKvVutRX4eHhOHz4sIHzdlRUFGrVqiXov+rt7Y2AgACDP7lh+wiV8TN0ceCrjJWQbt7f0xl4nv1c99pSq8/G6xulFkdWxCoGl58aB10dfngYv17/VWqRHELf7X2x9PxSLD63GP3/ZrKJsK1eMakxaPtbW3Ta3Ik3F6AlPEx/iElHmGIKG29sxK0XtzD16FSbjuko4lLjkKfOw857OzHn1BwjK7uWgTsHmj0WdzDqslnY+u6MfY0lgy17ubsoKawXn14EAFETNr64CpVKBbVGzau4Tj06FfdT7uPLk1/aLqiDsSRTBtslICY1BgCTyYWNs8akFDmFNT09HRcuXMCFCxcA4P/tnXdYFNfXx7+79CJVBQuKDUVFQOwFUewtKhYMCtaoQWPXaGKLJiZ2k5+x9xI1xhZbwN4LKBawYcOG2BGlc98/9t1ldndm2TKzjft5Hp6HKTtz9uydmTPnnoJHjx4hISEBKSkp+Pz5M6ZOnYqLFy/iyZMniI+Px6BBg/D8+XP06iW5Efv6+qJ9+/YYOnQoLl++jHPnzmHkyJEIDw9H2bJlAUgqDVhbW2Pw4MFITEzEjh07sHTpUowbN46/b64HsvKyEH4gHMsTlitVDWDrjGUusTPhB8Jl/2va7o0Z52gOqGuwnnp2SmBJ9Atzik3Ku6zC7NTNSZtl/6ekp6h9XBcbF9Ryl6/Baaplm04+PYmOezpiROwILIrTPTSGqV8ASMtMw7usd5yGianx8vNLueUn6U84DQd1ygjGpcZh0ulJRXr5TRGRSFTkdaWoTwDY/2A/uu7tija72uDAwwOsnzOVvvMAkPg2UaP7C8DuZWaOs74H+qLOpjq48fqGzvLpG1M1tKVobLDGxcUhMDAQgYGSkiHjxo1DYGAgpk+fDgsLC9y5cwdhYWHw8fFBly5d8PbtW5w5cwa1ahU+ZLZu3YoaNWogNDQUHTt2RLNmzbBq1SrZdmdnZ8TExODRo0cICgrC+PHjMX36dJMpaSVl9c3VSHybiD+v/6lW67fcglyjb5+Ym5+LPff34GWG8s2ODU1DAjS9uRg7+5L3qbXfyhsrBZbE8CgmCElheuSL4kP2BwytM1RunbQcjakhnU24lHpJTgfaekGmnJmitG7DrQ2scWv7H/BTrkZo8gryMO/KPKy5uUaujSQAdN7TGXU21QEhBL9d/g1Tz0yVPZCZMztcHtaB/w3E4UeHMTx2OOv2HXd24OLLizx9E/1z4ukJuWXFezbX9L80l2Ll9ZVYnrCc03A1Rt5kvpH99qmfUxF+IByd9nTSKHZTUW+K3HorCb2JOBShvaAG4lOubrNZhkbjslYhISEqrfTdu3cXeQw3NzdZkwAu6tSpgzNnzmgqnlHBfAP77cpvrPswH06ZeZlovas1FrRYIKupaGysvbUWyxKWwd7SHpciLiltV/QoauphPfNc/jd/k/kGJe1Kai6okbDu1jpDi2A0cD38fzj7A86Eq3+tW4nlW/vtuLtDJ7kMBZdhml+Qj30P1XvRYcIWm7c+cT2rwfY847nGx9cnrz6/wt7kvbAUW8p549nIKciRhc4M8x+Gik4V5bymRXng776/ixcZL1DWsaxs3bW0a5hzaQ4A0+kKdull4f2YzWvc9p+2uBl1E0ceH0Fcahwal2ms8niP0x/jz+t/ApA4KmQYqXP+5NOTGHV8FADJb8YMu2u5s7DEGyEEX3K/oOE2SQjixa+Lfim58foGRh0bVezLoxkaQeuwFiealmsqF7itLiefnlRat/rGaqMzWAkheJz+WGZQMoPYmShmYGrqYVVk592dGO4/vFjFoRU3PmR/wPGU42hevrmSMcqGumMhNz8XVhba960WGq5rIz4tHtPPT1daTwjBl7wvcLBy0Og8a2+tVVp34cUFjY6hb4bFDsODjw/U2nfr7a2y/99kvsG3R79FyifVMzWKWfS33tySM1hNKTM89XMqog5H4cXnF0Xu22l3J5lujj45qvY5mOPxxusbePzxMbydvTWWlU/eZr7FkqtL0NOnJ/xL+cuMVRkcfjWRSITDjw7LljclblLaJ+1LGkrbF5bfvJQqeRl4lmE648IcoVYAT7Su0Fqrz7G1lzTG+LIV11eg696uRcbtKGatM9/6tWH59eU49OgQTqScwJ8Jf4IQghcZL4wmUzUnPwdnnp3B7Auz0fSvpgYprWTqgfQAMPrEaLVL6ojVvG2F/h2K/IJ8jb38+oLrdxsaM5R1/Q9nf0CjbY2Q9DaJdbsmvM58jajDUdibvFfnY/GB4qydusYqACyOXyz7f/XN1UrGKrPtcV5BHmacn6FkxBvjPVdd/rj2B6uxyjYTytSNJqE4inTZ24W1+5w+mX1xNvYm70W/Q/1YtzOrkjAhhMjFOKfnKNds73OgD+tnkz/I1/TNL8jH7be38fCDchI1hX+owcoTigkP6sIWW2NsJTTyC/JlU0NFsfrGat7PfyX1Cr478R2WX1+OM8/PoN0/7dBlbxdJfJ6Bg8jnXp6Lb499i533diI9J90gdWXZDJwCUoDDjw4b/dQvkyOPjmD9rfX4M0H1WMvMU6/P9/vs99h5bycabG2AjYkbcfedcbVy1XTs/vtQkvm9/tZ6Xs5/Ne0qpp2bxsuxdGHsibHoc6APL3Vk2Wa5KjhVACDxRAZuDsTu+7uVxtj1tOtyy6ZUr5Kr5iqXwaYNdpZ2Suu67u3K2/E14UvuFyyKX4RjKcdU7sd1ff147keceVYYgsRWiUXdRLyTz06i94He+GqfJIk6vyAfl15e0rnyCYUdarDyhLrJNYoY2uBSh+hj0Wrtt+L6CrXbjmoCMwaN2TlrYfzCIgPkhWbXvV1yy6oaRAjF5dTCwuhP058iryAPe5P3YtLpSWj/T3u9y6MtDz8+xKL4RVh+fTlSP6dyXhvxafGs69n45dIvyCnIwYK4Bej5b098yPrAk7T6xc3WTfa/uTUIOJpyFLff3daojqwmLL26FI8/PsaCuAWc+2xM2ojoY9E4/5y9E1Ly+2ScfnZaEPl0hatW8fNP/L2sqvuSqA9WXF+h1ksb10vH2edncfLZSV5kYSauEUKw/e52DIkZgiZ/NcHYE2PV7uhHUQ9qsPLEgNoDNP7M/CvzMfPCTLX2LSAFBiuqf+5F0bG5H7I+YFnCMkHOz5yum3Vhlty2Bx/UnzrUN++z3uvtXDvu7EDozlB03NMRY0+MxYbEDXo7txBk5mVylgTTJQSCWTbt+zPfY+CRgQYLqdDEi8ecwTEng5WZzCNknHqXvV2KrCZx+tlpDDs6DICyI6H7/u6IPhaNxLeJgsmoLXIJUQx23tsp+Lm77+tepKeTb9YnqmGsEoKsPOUkRL5hOlMKSIFc9Y2jKUeNJuQGMI+mPNRg5Qlna2eNP7MpSTnYm4vwA+FotLWR0Zbw2XV/V9E7acmLDO5kAmlhZ0Nw9vlZpXVMIyR4R7DeZJlzaQ7SMiXe55PPTsqNE1Pw4itSQAoQtCWIdVuPaj20Pi7z5efgw4OIexVnsBAcbaed2WrcmirM+sNC19PVRN9cLzGGfkH+/erv8Nvoh7jUONk6Pqf+NSX5QzLGnBijt/NxvcTGPI6RW075lIJtd3RrQsNVho8J8yWLgCjda42pE+H/rv3P0CLoDDVYeULoh8jtd7eRR/IQ/0r96VBjopxjOa0/e/4F+zQdIKknyeVhEJoRR0cY5LxqwbhvXku7Zjg5/h9Nk9G4Wkv2rdFXbnpcU9iMIn17iKQUFGhnaKi6HkwNvbZQ1eD9gGsq19BNKlbflOQIDPxvoGwdW+IuAIOUA5x2bhomnZ4k2PET0hJY148/NV5uOZ/kq10rnIuiYukB+dkOQghuv5Nvoazv8UIIwYZbG3DqqXwjmrPPz5r8rBtADVbeqO9RX5Djzjw/E/OvzJctG/qGqUgBKcCDDw+KzMS2trAWTIa6W+oaTZkeYzAOAXlv0vtsSWhCQloC3mZqnxmsC3Gv4oreiQGXEdm1SldYiCy0lkN6/TA9IVxxi0IjLUBuaE6knNA6Bl9XmEb7vgf7sCR+iWAhGuqENklhKwVmaui7g9eX3C/Ym7wXhx8dFqwBjrqzRSKI5KpDCAVzyt8YEvXiXsVhYfxCjDw+Um69UTtXNIAarDzh4eCBE735TQAaf3I8/rn/j1zogLGVX1l6dSm67euG/yWonm6wFgtnsALAN7HG1QXN0LFuzIe+CCJcenkJ/Q/3R+td2pVf0xV1E/eKopZ7LV48ccyHC1tZG75Ifp8sV2s5IyeD1/ONChxV9E5F8N2J7/DjuR919khpw+Qzk2X//3XnL6y9tVapb7u+uf32NmvbUkASgnTk8RGjKCW3484Ope5fhiL5fbJ8ApJAxpu6xxVBhIrOFQWRgQkzT4Ft9vPQo0OCy8CErSqMOcSuSqGNA3iE7ymYmCcxSuvUrUGpC4QQhP0bBntLe2zpqFzyg4m6nZwsxaY51O6/v49radfQ06ennKFUVNmS8APhQoumEuaNXQSRzLukj4QdZiF3vhGJRDoZrNIXPqanpqgi87rQfX93AMC2jtsgFokRflAyLs6GK8c/a8MQvyGc4ROa8iH7A8o4luHlWLow4ZRhuwkpdiVkhhytuiFpIZ7XPA+dK3fWq1yKSDtxGQPScW4sXE69rPGsjq6wOU3uvLuDu+/uorpbdb3IwBYeciJFO0fa6LqjdRWHd6iH1cSQPnA/537GuJPjlILN+eBq2lXcf38f119fVxnfp4mnSCwSw8Pegw/xOJl+bjr23N/D6zF77O+B2RdnyxUnBySeMmOGWYYmtyBXo/g9Xfn18q+CHl+nkID/v370nagS8yRGbprux7M/8nJcIeI+H398jDkX5xjE42oMKHrK2Fr/GksIkrEiVOiauh7W2Rdny3WzEgppoqsqbr7RX2tfZmvz2CexSP2cKtckQROG+A3hSyzeoAariSEty7Pm5hrEPolVCjbnA2atSlUZoE3/aqr2McUiMUK8QrQXSg32JO9hbWkJcJd+UZcNiRvwMfujLPt+TzK/hjHfMA3WjUkbBT1Xdn42NiZuxIZbG/SSAKeTh5UlhlUfbEjcIBdTyFcdSC7qlq6LwNKBGn1GasxHHo7Ejrs78N2J74QQTYapVK9g89QxyxcJhanoh43NSZsF6fpnyjrRhfyCfLXKJDKTBcedHIc2u9oYvLIFn1CDlWfsLe0FPb60M42QAfVCeJ9efn6JvjX6AgBcbFx4P74qXmS8QL2t9XTu6tNsezM02tYIgPadzZg0LtNY52Oow43XNzj71utKTn4O6m2phwVxC7AwfiHqbqkryHmY8OFVZItBJITgSuoVzqxrdfmS+wVrbq4xWOvKhp4Nsa7dOtRwq6HR53r92wt/3/tblqQndLmv66+vF72TEcB1rRNCBLkPE0Iw8/xM1NlUR26Gy5SK0G9M2oiG2xrycixCCstF6TuRjA/4CMMaFjsMwTuCOa/Jj9kf8eDDA9Z4VbbQQlOFGqw8Y2VhxctxigrqV3xruvjyolYP2rQvaYg6HCU3fSLEW2zalzRUcamCc33P4X+hwtaDG/Kf/FTGlttbUEAKeCvivO226vp+u+/vVlrHVtZLn/U0NydtFuS4bNOlQsOLh5VlanH/g/0Y9N8gzj7igCQUJ/pYtMqs+sXxi7H06lKDta4sYV0CFmILrRKyfrrwkwASsWNM3ZNUwXU/nHp2KlrubMl7B6xDjw7JOgaOOTFGdny+wkj0TeLbRM5yVOow8vhI9Pq3F/IK8gRrTiMkP1/6GX4b/XDv/T2tj3Ep9RIA5c6KUppvb45u+7oh6W2S0rYn6U+0Pq+xQQ1WnuHLa/bzxZ85t73LeidXnuiPa39gaMxQNNveTOPzzL8yH1fTrmLS6Um48foGCkgBZ3FmPnCydpLLJhWCS6mX5OLv+DbA516eq9JQm3F+htK6Qz2Us0VNeXpLWsbsdeZrvZ9blxhWKWy6P/L4CAD2TFsp62+tx+lnp/HjOXbjISc/B9vvbtdZPl2wt5LM8jhYOeh8LEII4lLj4LfRD79f/V2jz+bk5+Dwo8OsHkpCiCDhTEKQ8DqBdf2BhwcA8FcBQ8qll5fklqOPReNN5hscfix8TCbfFJAChB8IR//D/bWeuTj97DTuvr+Lu+/vChJmoC/C9oep3H7++XkkvlFdXYYrNtgYSmrpA2qw8sy0xqqnnWu711brOKra6rXY0QIvPhd2f5JmrgLchZXZePbpmewhDQARhyLwx7U/dO4QUhT6mNpq+09bmeHBnEYylJHI5hUcVHsQ677zg+ezrueLtrva6lQOJ/l9Mhr/1VjSCcYA6tSltNuGxA0oIAValyUq6qGrTo9zoZGG3vCR+FJnUx1ZkfrVN1fLjZuP2R9VXk//S/gfJp2ehKjDUUrbkt4mFVlpo7jCZnxEHIxQ67OVnCsprdOlM5yuMOtzf8j+oNOxxBDLwlXMjZcZLzHs6DBZFREupM+RI4+PYMX1Fbw/z6o4V+H1eHxDDVaecbJ2Url9dtPZgp5/ypkpau/bYXcHpXVrbq7Bjdc3+BQJAORKwCiGTfi4+ijtv6TlEp3Pue7mOuQV5KkVrK4PRgbIF3NuUrYJ635C1817+fkl5l2ZJ7du592dRZY/yc7PRszjGMy4MAOZeZn4M+FPk4lDlPLP/X9w4OEBpanFN5lvlAyFAlKAfcn78PjjY9k6NmPiTeYb2YND36V02JB6VoWo2ZySLikBlvQ2Cc22N8PoE9ylb6QVTNjaJws5i2MIkt8n4/erv+Nd1jtk5mViwZUFuPrqqsrPXH11FV32dEHozlBcSb0iW8/2MsV0UKiCrVi+0DNaqmBeL8Nih+Hyy8safZ6pCyHL5Rka5qzOrnu78E3MN6xt2KUG68RTE7EsYRlmXpjJa8WaL3nG7cE2zeKYJox0uk4onmU8AyHE6BoMMG9crbxaFbm/fyl/nc+5895OJH9IxtW0wgdHbkEuYp/Eor5nfZS2L836uflX5uNy6mVs7sBv3Ocw/2E49+KcrBsW22/UtUpXzjglPrnw4oJsnOxL3ofZFyUvUjejuEuwLIxbiL/u/CW3jqlbU2HBlQVKnpplCctw7nlhJ6Q99/cgMy8Tcy/PBcCtl5jHMRh/ajzCqoVhZpOZevXg1/dk765XlGe1vXd7nHl+hvWBWBTSY3998GsAwImn6tV4/PfBv+hSpYvG5zMVpHVIk94lobZ7bWxM2oiNSRtVXk9RRwo9z4P+GyTbV5cxxJb0a8hWvsyEo+cZzzE4ZjCO9jyKzUmbMbD2QLjbuav8PNNg3ffAMN3Y9AHz+TjrwiwAwKakTRjhr7pD1e77u3mdqeBqmGEsUA+rntFHAX1mZx1F3mS+0UuyQzXXanLLzBsPs01rSbuSrB4FPuIUAWWDakPiBnx/5nv02N8Df9/7m7U8zaakTbjz7o7aTRGKYkK9wkLoTGOC7TtOrDdRL1UUsvOzMer4KFx4cYEzHlMRfZTy0Qds04qKLwnTz0+XGatMFJMdpUX7pUky+owlW9eOfXyWL1Fe5efmt5iP/jX7a3XOjNwMvMl8o1ZtR6bXaOrZqXLbtK0NCQANy/CTfS4E556f0zm5U5cxxMeLPp+wVQpovas1NiZtRMjOENk6ptFFCMHe5L1Ifp9s0nH+bHB9H7b1n3OUXyhffXmltK+hO8PpE2qw6hm+DDFVsNVPzMrLgt9GP7Tc2RLtdrVjTQziEy9HL7X2+7HRj6wXqxAF0QHg1LNTACTxdz9d+Ak/nP0BuQW5rFOUy68v5+WcEb7s8WdsHlYXWxd0qKQcqjHEbwgm15+stF4XTj07pbIxhJSU9BT0OdBHK4+cuaE45a9oXOjLYJ3fgjvOWZ2XYmZsoSaMPzUebf6Wn3aecX4GYp/EFmlcDPlvCN5mvgUhRKde88tbL8f+bsb78iStla0t0mQubajpXpN1vZutm9bHFJrd93ejyV9NsDFRUi/6v8f/Ydq5aei+vzsefnxoYOn4Rfr8UYSt7KD0GXj2eWFXvNgnsZh5YaYgsgFAZefKgh2bD6jBKgCNyjTi3GaIFqVfcr+g/tbC6cP32e9ZSy/xibq1XEUQsT7khTJY2eJzF8YtRNDmICS/T+b9fH+G/in3m6sTqtHCq4XSum8DvkX3avy3P+RKPkr7koaOuzti7c21mH5+Omu5FH3QpTL7NPJXVb7SsyTsKJaM0ZeeStmV0upzC1osAKCbYa34cN19fzfGnRyHtbfWytaxGa+XUi8hZGcIZl2YhclntHv5WhKyBFZiK9bkIlNCKM+hhZjdISLU/ZQPpM6TBXGSscnsNLb06lKDyCQUo46PwoGHB2S/f+yTWMy6MEsp1AoApJNxI47KhwUI+exuXFY/tcG1xXhHsQnTrBx3eSmxSIyyDmX1KI3+HqJMLEXqGeYERNCQAHXYensrCAjv5WkAoJ5nPblldTK3bS1sldYJ1erw73t/yy2nfZG0Gvwz4U88/fQUS64uket8pm9sLZV1AQBzms3hnBIXCsUKAWtvrpVbjnkcozcvtDZVDsYFjUM773YAtPewqoJpXGTlZ3HuJw2f0JSYsBiEVgyVLRuz17Ao2Eqn/Xb5N52OWd6xPKth6uvmC7EJPeqZZeGYrUbNhSlnpqDV362wMG4hxp0ch133drGG8Ql1z1fFsDrDUMOtBu+zeXyh8Sg+ffo0unTpgrJly0IkEmHv3r2ybbm5uZg8eTL8/Pzg4OCAsmXLIjIyEi9eyGc4vnv3DhEREXBycoKLiwsGDx6MjAz5TLcbN26gefPmsLW1hZeXF+bNk89qNlXEInGRgeZ8kPg2EXkFecjKy9KpYLG2uNi6yC1zXnyEvbyTITwCLz6/4L2TiqLhrs73YvOS6OvmdfXVVbzJfCOXLMF35zNNSqeIRWIsC5Vk9K9ovUJum52lndyykAZMRk6GUp3jJVeXyC0LUVc0qqZySShA/oWOK3lQEeYYalepnW6CFYEQHsQyjmXklnd01n/TCr5gC0HacnuLzsdle9G3EFnAALYPRQVvMt9gQ+IGlfuoe8/X9dnATIJ2tXXF313+Rr+a/XQ6plBobBV8/vwZ/v7+WLZMuePEly9fcPXqVUybNg1Xr17F7t27cffuXXTtKt/xJSIiAomJiYiNjcWBAwdw+vRpfPPNN7Lt6enpaNu2LSpWrIj4+HjMnz8fM2fOxKpVqxRPaZSoGkAiiJRu5kI8aMMPhCNwcyDqb63PmjwiNOo+sGqVrIVaJWsprdenh5WJqqLx2qBooPbzldwImpZrqtFxRCLlcSMEE09PRMudLeUycvluMfpH6B9qVYqQElw+GDejbirprJZ7LYRXL6xbKKR+VNVFFhKu5KiyjoWzNGUcyrDuo4ryjqoTs7RFWhpNH7G8ng6eWnXzMiRbb29Ft73dOLtjhf4dyrpeHcQiMesL8aaOm4w6JEBfsDXSGBs01gCSqIe6Hap0vdamNpyKBp4NsDhksU7H0Qcaj+IOHTpgzpw56N5dOZ7O2dkZsbGx6N27N6pXr45GjRrhf//7H+Lj45GSIqnfd/v2bRw5cgRr1qxBw4YN0axZM/zxxx/Yvn27zBO7detW5OTkYN26dahVqxbCw8Px3XffYdGiRTp+Xf2gKk6RbdsvzX4RUhy9I42TY6IYJnG6z2kc7H4Qng6erHVYDXWD3ZS4idfjKX6PlhVa4kjYEfyvler2tIpjgivW1xTxKuGFpa2Wok6pOkXuq/LlTyTCD41+kC239W7Li3xsaFo/ki88HDxwOUL+3ANrD4Sng6dsmakjVS9C+ih1J0341Fd2d4vyyvHeTEpYl9CLHOry6+Vf8eDjA1m8piLSkBxtYPt923u3h5XYSmVIgCkYKnzQtKzytcEWfmUsZOVnCV7Rp6VXS3g4eGBtu7VoXbG1oOfiA8Gtgo8fP0IkEsHFxQUAcOHCBbi4uKBevcLYvtatW0MsFuPSpUuyfYKDg2FtXVj+qF27drh79y7evzeOIvCqUGVssRkeRZWhMTXaebeT+462FrboVLmT3D6utq6o4FSB8xiGMlhjnsTwejy2h0g5x3JFJt/V9airdBxzMVilsMU5i0ViOY+hOuNgResV+KXZL5zVGPjg3ItzRe/EM32q9wGgHPowpu4YuWXmGFMMmzAEuQW5nB5EbWGrnAGonon5tfmvvNdS1hS/jX44+PAgAAgeC86W7Ct9mWGOEem4ktK6Ymt0rSI/C6ovFMvEaUNYNdUtT6WUtCspCy+SElw+WOfzCwlblzg+cbV1FfT4fCOoVZCVlYXJkyejb9++cHKSdIBKTU1F6dLyMVeWlpZwc3NDamqqbB8PDw+5faTL0n0Uyc7ORnp6utyfobASW3FuY3sAV3SqKKQ4ekVaFoPpYQkuH6yxAWpsjQ9UMbD2QK0/28CzAet6pv6mN54OQP1ENlOBbUwoTmvaWNgUeZym5ZqaTVF65otdPY96rPso6k2bWDchr6+QHSFaVwHggqvcDtd9ZUvHLehUuROquBi+1eT3Z77HpZeX0OtAL8HO0bdGX4wLGqe0Xvo7FzVGhvsPh4OVA6JqRqGGWw1BZGRDsVOaNuXO1K3L279mf9QuWdga/VD3Q3Ivx5s7bFa7w+KSkCXwdvLWREyNOfv8LG6/uy3oOfT5W/OBYAZrbm4uevfuDUIIli/np56lKubOnQtnZ2fZn5eXenVAhUDVw1MEESqUUPYsTmmgfktVQ6HOjcGrhETvmnoD5wdz15U0dsbUHYOqLlW1+uzSlkvR26c3AMhlZpayLyxb1KOqpBe40F3S9A2bsWFvaS/3cP2qqnGUr9IHNd1ropdPoVGjbogDVykjRZhl0YRM4kvP0Z+zwFRiM4fEDBG0RWpkzUjW+4NUP0w9MV+GpSETXiW8cDb8LCbUn4AgjyDB5FREMQTiwssLGh/DWmytcvs3db7BhHoTUM6xHNxs3dCtajeEVQuDl5OXnF68SnghtIJ6McShFUMxui53W2JTgas9uLEiyNUuNVafPHmC2NhYmXcVADw9PZGWJj9I8/Ly8O7dO3h6esr2efVK/k1LuizdR5EpU6bg48ePsr+nT5/y+ZU0ws7SjvOBIBKJ8H3D75XWNy/fXGixdGZe8LwikxzYprrV8eZIy+2YImKRWOv6uo7WjpjWeBri+sXJZWbaWNjgVJ9TOBt+Vm2DxNRgu0bsLO3kxosmHjJTD5n4LvA7uSludY0xdfazs7STi+dka+FpTphbh6SiYIaNrGyzUva/k7Xk2cscI77uvqjlLkl07Vy5s2y99B72XeB3GB80Hge7HxS8EoNijOa0c9M0PkZRz86hfkMRVStKdl+Z3XQ2ZjaZCUDybFrXbh2WhS6TVe9RjBnngulUMGaYNZtnN50tt00fXRX5hHeDVWqs3r9/H0ePHoW7u3wJp8aNG+PDhw+Ijy8sDnz8+HEUFBSgYcOGsn1Onz6N3NzC0h+xsbGoXr06XF3ZYy5sbGzg5OQk92eMiCCSqwog9Vp6lfBCZM1IQ4lVJNEB0XCzdcM3db6RW3+o+yHZTRGQBPkroo43x5RCANjQpi4mE7apbzdbNzjbOHN+xpS90gA4i79LY+xUNeAwR2q619TKY6hORQ3Fa9BcXoKYLV6/b1DoCGDW7zWnkCsumKUSm5RtgpmNZyKgVACG+w9X2rd71e5Y2WYl5gfPZw0jsLeyx4DaA1DBqYJJvARaW1hjbdu1nNuL+g71PevLxbIqxoxLkSaJlraThDQaWxtcLtzt3NHBuwNK25VGm4ryXepUPV+MEY3dQhkZGUhOLuwI9OjRIyQkJMDNzQ1lypRBz549cfXqVRw4cAD5+fmymFM3NzdYW1vD19cX7du3x9ChQ7FixQrk5uZi5MiRCA8PR9myklItX3/9NWbNmoXBgwdj8uTJuHXrFpYuXYrFi00nm5F5kezvth9d90qC2hUNszYVCgfQcP/h2JTEb5Y6X3DFung5eeFYr2M4mnIUbrZuaFxG0ikjyCNI1lO7pF1JfYlpMHQ1WLXBFI185vTd6LqjIRaJ0aFSB/Q/XFi+qZ9vP9R0rynzAqmN8T9bVeJi4wInayfULV1XqeaoKtQxck1xrDBhegKZMOsF21vaY1TgKKR+TkV11+qs+w+oNQDRAdFynf/MkTCfMIT5FCYjMX9/C7EFnG2c0b6SsnPBVGlQpgFuRt2E30Y/pW1cBqgqarjVwJ13d2TLQ/2GYkTACJx+ehoBpQN0EVXvlLAugXkt5iG/IN/kX1Q1Nljj4uLQsmVL2fK4cZI3tKioKMycORP790t6PAcEBMh97sSJEwgJCQEgKVs1cuRIhIaGQiwWIywsDL///rtsX2dnZ8TExCA6OhpBQUEoWbIkpk+fLler1ZSo5FwJu7vuhrWFtezhsrLNSlx8eVHupmKo2qPqoOqhaGtpq/RA6VqlK84/P4+UTyn4NuBbrc75S7NfMPXsVK0+q29aV2yN5A/8t3ZV5OsaX2PbnW0AuBO2jI01bddgSMwQAICNZaEn2dHaEVMaKsduW4gtUN/TvA0KNkQiESxEFtjYYaPStublmnN2/THm+4a6TGs0DX/d+YvzGnK0cmRdz3QMtKrQitVjxPQuj68n39yhp09P7Lq3SxuRTQqtY5ZN/CVQW8o7lpczWL+rKynXxuy0BkhqIL/8/FKvsmnKUL+hAMxjVkVjgzUkJERlfJA6sUNubm7Ytm2byn3q1KmDM2fMpy1bNddqcstNyjYxqYBnpidDHcQiMea10Kw7Wf+a/bE5qbAMTZcqXUzGYB1eZzhWXBe+pBDTW2AqJUmYU7JsU5BMdJmCZH7WxsIG2fnZWh9L3xQV/sBlsAGSKhWnnp1C24rC1aEVmt7Ve6N39d6sHjKAe1x42hfmNGgzvWmI9pcU4SjnWI6X5i/WFoUzQVs7buXc72CPg6i7uS7ndmNAH5019YVppFiaINK3GkPVt+MbffRI93XzLXKfm1E3BZdDE6QGpL7eXk09Hs/D3qPonXigKMPY2CgqmVEs5r5VB3kE4XSf06wNO8wFruQQF1sXbO+8HXu/2qvR8aT3ZWPOGzAGTCGGlcnmDpsRWDpQ5+MwG92oanDCVsJyZMBIg+cXSFs6u9q4oppLNdZ9yjqUZV1vzFCDVSCiA6LxV6e/ZNmIpg7zwpTWhzQmj07bim01fmjxATNWbojfEMEThbpW6YrogGisb7de0PMIhdC1C6WYyjR5WLUwXI64XGTXr6Je5lxtXVnjVKMDogEA0xtN115II0BVDG4t91oqq0mwlXua03QO4vrFwdvZmw/xDEbXKl1ldZqFwNSqLZSyL4VNHTbhj1Z/ANC+BXE773ao7FwZX1XRvKxeaIVQg8cHl7IvhZtRN3E6/LTStSNttBAdGG0I0XTCvCqRGxEWYgu5IsWmCHN65fyL87KLcEnLJTj17JTaNev4ZmbjmZh5YabcuoUhCw0iS1Stwk4k0rp8XNOafGAhtmDN/DVGOlTqgOy8bHjYe2DfV/vwNustvJyEq4/MfLiaUpKROkkhX/t+jdyCXI3DiIb7D0c/335wtOYOKTA0zJeYKs5V8OCjfPejuqV1m3L9pdkvGHtyLIbXKbxuRCKRWk0pjJ2fm/2s1n7TGk3DwP8GYmTASIElMg5alG+B7Z22az0jZW1hjX3d9mn8uX+7/WsUL0GqQl1mNJ6B4f7D5do7mwrUYKVwMrn+ZFlv8HdZ72TrnW2cDRrqEOYThtYVW6PZ9mZF7ywwxmwIGJp5wYUxzJVdKqMy2LsVyaGDQ4eZ0GVKBqs6WImtMMRviFaf5RqjfMX76cLc5nNllUUASdcyRYNV1xi8Ki5VsL/bfo0/V9GpIp6kP9Hp3MZCPc96iO8XLxebqQ6KIQErW6/EsKPD+BRNEEQiEWqV1LDKCA8Yg7EKqL7/iUQikzRWARoSQFFBywqF1SD0kZygiZGhz/pxzPZ9irBl6jPr7OqTsUFjDXJeY0HaZQ0A3G1NI9HAkA1DNnfYXPROArKryy50rtxZziBVLA/XwLOBXH1VIWCrHQ0Avzb/VdDz6htNjVVAvsHErCazUNLe8CUKt3VUnbBNkVQVMUeowUpRC314rMRGOhzLOioHp9+MuombUTdZy30xwwSEpqZ7Tdn/g2oP0tt5jZW5zeein28/hHiFYHGI8ddt1rjWLI8YulNPdTflWqmKRtWqNqtQ2r60oHJwhWRUcFJuoW0MrGy9Es42zlgSskTwc1V1rYqBtQZiYr2J6FGth1HEhjtYOcj+N5XwKH1jLJ5evjFOC6GYUtQb8PwWhss81IeHNbRiKKq5VkNvn96ydfrsa81FUQkxiki7iXB1cuITVaEZJ3ufFPz8fFPVtapOn+9cuTMmN5gMsUiM1hVbY4T/CJ4k4w+mx764llXiiktVrAagjxdlaWw+M0HHSmwl18FPijZF6FUxsNZAjfaPDohGk3JNcKbPGaWaoEIxrt44RNaSVFNQp0lFVRfdruGiqORcCd2rdkePaj1kSYWU4gE1WI0IS7El5/QUwD11pQ+0aRmpKTYWNtjddTemNS7sJ923Rl/Bz1sUI/xHYHTd0WpnuHuV8MKpPqfwT9d/hBWsCAxZf09TQ2xn553o6dMTc5rO4VUOZgzeri6GLxC/vPVydK/aXbZsZaFcFqc40NOnJ+t6xZhJfRj0Tco2wa4uu+SuV2n1j3Xt1gGQJC2NDBjJ+xgaEzRG7VCevV/tlXkUDRWjzfSwchmLQieziUQi/NT0J8xqMkvQ86iL9NmoGApWoYRxeuhNGWqwGhnaJFZUKFEBA2sPxLRG03S+iFe2XgkPew8Mrj1Ybj3b9J0+sBQbPi/QztIOQ/yGoFWFVmp/xs3WjbVGn9BI47t+a/4bAOB0n9N6Oe/84PmycmcANM6w9XX3xYzGM3ifpmZOuRtqDDNpVq6ZXJklQ8U7a0rHSh15PR7Xda0Yw6ovw6y6W3W530XaGre+Z33cjLqJ3tV7Y5j/MN7DBMQiMWcoT2zPWDQt21S2rKp0l75gvgRzPauK26zBzs470d67PTZ1kG+rvq2TfmNtA0oF6PV8hsDw1gBFDk0fqqXsSmFjh40oaScJhn+b+Vbrc09rNA1NyjXB0V5HZetK25dG2pc0dKvaTevj6pM/Wv2Bk09P4p/7/Hs3O1bqiHW3JB4XQohRZqL7lfKTa67gauuK/d32o+teYas6tK/UXja1aky6aVG+BeYFz+PsLV/c6Vy5Mw48PCC37GLjgi23t8jWxfWLg42FDQ49OsTbebmMGkWD1VBom7T3Z+if+PaYdq2oFfF08DQ6D7yDlQN2d90NC7EFLMWW+DbgW/yZ8KfcPpVdKuPW21sGklD/VHerzhqup8/EYEBSRjDhdYJSV01zgnpYjZAdnXfAWiyJZy1q0Hep0kVmrAK6eWzYPIJHwo7gbPhZg5XBYD7Y1rZdK7etYZmGAAoLIQNAiFeIYM0amNNhxtIBRp1av5WcK+HS15f0II0EYzFWAYksHSp1QGWXoktq6Vrv0xywsbBB5yqdldbxDscQYd6/Wnq1ZN9JD2hrbDQv31wuBl8V6sRXc3UpMiTVXKuhsrPkemIbG5PqTzKKUC5jQB95DMxzneh9Ajs679DbOfUNNViNkJruNRHfPx4X+l7A9k7bAUgKagNAnZLyCUCKngq+jQUrsZXe3xSZNPBsABFE8HXzRYMy8iWkloQsweKQxaxlb3pU6yG3HBMWo9b5pDdiNpjtMfNJvlrHExr/Uv5Y0XoFDnQ/oHI/tm4/ReFq46qtWCbJiIAROBt+Fru77ubcRxpqoQ3SF8tuVbuhpF1JuRctQ6F4nQysrX4SUEj5EADAf2H/FbnvoNqD1IoB/6rqVwirFob5wfPxe6vf1ZaFL35u9jOCywdrpAdFBvmpV62DWYZNipXYCiMDRmJ56+UAgKF1hmKo31D81ekvreUREsVOWBPqTYCzjTNsLW2V9g0uH6wvsYyG1hVaq9zO90tZSbuSBglF0xc0JMCIcbR2hKO1I073OS0r/r2k5RLsvLcTK66vMLB0+sHR2hGXIy6zXoSO1o5oXZH9hqCYbSyNSSuKfd32yXWqYtb887Qv9DIbQ3kXKU3LNS16Jy1Y224teuzvUfSOZkJN95pwsnZS+YLWvlJ7TD4zWavjS7OnnW2ccazXMb0kMhZFfc/6ONzjMDzsPUBAYG1hjcS3iWp99vdWvyMrPwt2lnZKoQWKhFYIxZXUK7JlrpAAK7GVQdtZd63SVaOmKB28O+Dw48Ny6xyt1GsmwuZcCKsWhmH+hYX57Szt8F3d79SWR99oMtP0S7NftG72sqPzDrzMeKlRHoEx0Na7LVbfXC23rrR9adQpWQcT6k9A0tsknHh6gpdzGdPMllAY/o5JKRJXW1eZwVbKvpRcdmZxGKS2lrawEGtmIPI1Ze9XqtB4tbeyx+EehxHbM9YojA1dGRc0jnNbcPlgs46FYoOtjBGTX5r9olVCybLQZWjo2VAuIdKYxk/5EuVhZWFVZFk9xb7qIpFIVuZpbvO5Kj9rY2GDYXWMv0OSpugSY8ocS5s7bEbfGn1l7Z1NBU28eWxeV3Wp6V4ToRVDTe55V8OtBv4L+w+tvAoN7WO9jmFxy8Uo51hOrfvJP13/wbRG08yukYU2GM9dk6IVbAOe2Z2Eoh5eJbywsMVCAKrDAsqXKG+ybe3YPD97uu5h3Vc61VfcjFZVdKnShfWBqVi8PKF/gux/WwtbBJcPxpp2a1gbUBg7zBjFHxr9oPHnR9cdjfDq4fBx9TF4owJjJqB0AKY2nGpyrZ57+fSCX8nCl3pVMZvG9JKmT8o6luWMA2feT9hCRADAx9UHvav3RqfKnTA/mLsWO3MG0FwpniPIDAirFgY7SzuE1whX2iadUhvuPxxTG05V2s7WTrQ4oKro96Eeh9DWuy0A8y3LoljvkYCgqmtVfBeoPOUobdigS8ymscOXx0KxLBFzNqBx2ca8nMNQHOx+UPa/NkXzh/gNwQ+NfoBIJIlDl2Iq5bzYYBpoTEIr6KeQvzFhb2WPbZ224a9Of2FG4xmylqBsXQuNKYzKWGA+axTjgdmQPqPYMNfuVkyowWqizGwyE+f7nmdtW9ihUgec63sO0QHR6FujL2LCYjAveB76+faDq40rfmiouafE1GALdpd2oCoKU5t20hbpDXJg7YFyiWuDag+SdbYxV+MdADpV7qTzMep51JNV9GAyqPYgWIutMSZojM7n0DfSBE8XGxd4OHjwdlyRSIR5wfPwTZ1v5Gr2mhrMdsjMKXFNZyPM6dqqXbI2evr0lN07Fb3pDT0bmtX35QumTtjC3phNRhT3L47QpCsTRlVRfWY8XhnHMijjWAYdKnXApPqTioVBxtZONbJmJPY/2F/kZ7tV7YYFcQtQ273oklGmhGLZJmmcr6XYEhG+EXjw4QEsRBZynlhX28JKARvbb0TUkSil42raXtIYqOhUkZfjrGm7hvV6Ghs0FqMCRxlF4wtNsbW0xaWvLwmSbdyhUgfej6lvogOikfwhGd2qdkNN95pa13w253CbSk4KoQGi4uMI0ASmTkYGjMTE0xPltiuWByvuOjS9uylFJ6QDvqVXS6XsxPIlyrN9xGyo7lYdPX16Ytc91e0V+/n2g6+bL2qVrKVyP1OjqmtVbO24FRGHIgAoT/FObzxd6TPudu5YFroMdpZ2qOshb/AuClmExmUam1TcnYe9B159eYWJ9SQPhu8Cv8Pv135HVE15Q9zH1QcPPjyQlS/jmga2EFtwTuWZorEqRZsyaMUFV1tXbGi/AQDwMuOlbH1ZB/VjlFe3XW3WBmvjso0xrdE0XHx5EVdSr2BqA+XQNFU4WDngc+5ngaTTP1xdypgeU8XZ0qkNp8LX3VfxI3Ic73UcXfZ2wc/NftZdSBPAdO+oFJ2Y3ng6Tjw9gQaeDTDcfzgefniI+p71DS0Wr0yqPwnzrszDn6GFnVhmNJ5RpMFqIbZQqvlqLjA9z5Yi9S5/Zv3E0XVHY+nVpQDUD7EwJvZ8tQdP0p/IWrYOrTMUXap0gYe9/NT3zs47kUfyUG+LZOpaVdw30+uheJzixKYOmxB5ONLQYugV5m8vvR6YyUXutu54myXpPljbvTZuvb0FbydvNCrTSL+C6hmRSITe1Xujd/XeWnW+a1SmEY6lHBNIOv0zoPYAZOdnI8QrRG4902nArGwzod4EtZovlLIvhYtfX+RNTmOHGqzFlJJ2JXEl4gpsLGwgEonMzlgFgP41+6N/zf6GFsOsMPUYqhLWJZS6g7FVfbAQW8AChTFlAaUD1Dp+OcdyOslnyjBjOwHlZDRzhJk8Ji3bVMK6BJqWa4oLLy5gXvA8DI4ZDAAYVXcU3me9N/lEPE0p7tPYgKTaBls93XqehbHchBCc63sODz88VPt+U9ygBmsxRpe6eBTThz5IiuZQ90O49/4eWpRvYWhRjAJfN1/cfnebdZviy4y6BfRNGWsLa5zqcwpiiOVCQFa0ljR2YYaLWIuteUn0o5gPTG88AYGTtRM1VlWgcZWA06dPo0uXLihbtixEIhH27t0rt3337t1o27Yt3N3dIRKJkJCQoHSMrKwsREdHw93dHY6OjggLC8OrV6/k9klJSUGnTp1gb2+P0qVLY+LEicjLy9NUXAqFQtEaLycvpYLl0lqIbAlEhmxjrA9UVQ1QNFiLakRgLrjZusHF1oV1G3PcUAcBO780+0WpiQkhRPaSyFeCpLHjYOWg1n77uu1DhRIVZO17ixMae1g/f/4Mf39/DBo0CD16KLdt/Pz5M5o1a4bevXtj6NChrMcYO3YsDh48iL///hvOzs4YOXIkevTogXPnzgEA8vPz0alTJ3h6euL8+fN4+fIlIiMjYWVlhV9++UVTkSkUOU70PoGWO/nt4UwpPrSv1B4BpQNYS8qpKpxuDqisxcqwV51tnNHLp5fwApkA0QHReJ7xXBY3TZHQsVJH1HCrgS5Vuii1Ay5hXQIzGs/AhZcXlKqbmBtTG05F6udUpZAaLio7V8bBHgeL3tEM0dhg7dChAzp04C5N0r+/JGbw8ePHrNs/fvyItWvXYtu2bWjVStKubP369fD19cXFixfRqFEjxMTEICkpCUePHoWHhwcCAgIwe/ZsTJ48GTNnzoS1dfF4c6cIQ0m7knLLbM0VigPqFKpWRNpQoLijGPc6Pmg8Dj46aPZxm+OCxuHBhwdFJoRs7biVVhr4fxQ7oVEkzGg8QzZGfFx9UM6xHJ5nPEc9j3oYEzQGVhZWcgmf5oo6yVUUCXqPYY2Pj0dubi5aty4s7F6jRg1UqFABFy5cQKNGjXDhwgX4+fnBw6Nw+qldu3YYMWIEEhMTERgYqHTc7OxsZGdny5bT09OF/SIUk+ZMnzP4lPMJdlZ2SgYshZuA0gHY2H5jsU4uYmNA7QEYUHuAocUQHE8HT/zTlb3uKLO7EbMONIUi5fsG3+PXy7/Cw95D7oXGSmyFg90PQiwS09h6Cid6N1hTU1NhbW0NFxcXufUeHh5ITU2V7cM0VqXbpdvYmDt3LmbNmsW/wBSzxMXWhTPurLig7YNBsR4rhQJIKiusbrsa2XnZcg0nKBQpEb4R6F29N2tTCrZOTxQKE7NpzTplyhR8/PhR9vf06VNDi0ShUCjFikZlGqGFF62oQOFGiA5qlOKB3j2snp6eyMnJwYcPH+S8rK9evYKnp6dsn8uXL8t9TlpFQLqPIjY2NrCxsRFGaAqFQqFQKBSKwdC7hzUoKAhWVlY4dqywi8Xdu3eRkpKCxo0lBZUbN26MmzdvIi0tTbZPbGwsnJycULOmepl0FAqFQqFQKBTzQGMPa0ZGBpKTk2XLjx49QkJCAtzc3FChQgW8e/cOKSkpePHiBQCJMQpIPKOenp5wdnbG4MGDMW7cOLi5ucHJyQmjRo1C48aN0aiRpF1d27ZtUbNmTfTv3x/z5s1DamoqfvzxR0RHR1MvKoVCoVAoFEoxQ2MPa1xcHAIDA2WZ+uPGjUNgYCCmT58OANi/fz8CAwPRqZOko0d4eDgCAwOxYsUK2TEWL16Mzp07IywsDMHBwfD09MTu3btl2y0sLHDgwAFYWFigcePG6NevHyIjI/HTTz/p9GUpFAqFQqFQKKaHiGhTjNEESE9Ph7OzMz5+/AgnJ1pihUKR4rfRDwAwrdE09K7e28DSUCgUCqU4o669ZjZVAigUCoVCoVAo5gk1WCkUCoVCoVAoRg01WCkUCoVCoVAoRg01WCkUCoVCoVAoRg01WCkUCoVCoVAoRg01WCkUCoVCoVAoRg01WCmUYkoFpwqGFoFCoVAoFLXQuNMVhUIxbTZ32Iz7H+6jUZlGhhaFQqFQKBS1oAYrhVLMCCgdgIDSAYYWg0KhUCgUtaEhARQKhUKhUCgUo4YarBQKhUKhUCgUo8ZsQwIIIQAkPWopFAqFQqFQKMaH1E6T2m1cmK3B+unTJwCAl5eXgSWhUCgUCoVCoaji06dPcHZ25twuIkWZtCZKQUEBXrx4gRIlSkAkEgl+vvT0dHh5eeHp06dwcnIS/HxCUb9+fVy5coXXY5qLbviGSy9C/AamhKHHizHr39C60Rea/gbFRS/aoI1ujPka4AtjHzOG/A30rRtCCD59+oSyZctCLOaOVDVbD6tYLEb58uX1fl4nJyejHPzqYmFhIZj8pq4boVDUi5C/gSlhqPFiCvo392tJ29/A3PWiC5roxhSuAb4w1jFjDL+BPnWjyrMqhSZdUeSIjo42tAjFHvobGBaqf8NDfwPDQvVveOhvoIzZhgTom/T0dDg7O+Pjx48GfysyNqhu2KF6YYfqhRuqG3aoXrihumGH6oUbY9UN9bDyhI2NDWbMmAEbGxtDi2J0UN2wQ/XCDtULN1Q37FC9cEN1ww7VCzfGqhvqYaVQKBQKhUKhGDXUw0qhUCgUCoVCMWqowUqhUCgUCoVCMWqowUqhUCgUCoVCMWqowUqhUCgUCoVCMWqowUqhUChGAs2BpVAoFHaowaoGmZmZcsv0oVLIp0+f5PRBdSNBqoeCggIDS2JcZGVlGVoEo+XDhw/Iy8uTLdNrScKDBw/w4MEDAJDTDwW4desW/vnnH+Tn5xtaFKPi/v37WLBgAe7evWtoUYyO5ORkBAcHY/PmzQBM6z5DDVYV5Obm4ttvv0WvXr0QGRmJU6dOgRACkUhkaNEMTm5uLoYNG4b27dvjq6++wo4dOwCg2OsmNzcXM2fOxPLlywFAZV/k4kROTg7Gjh2LiIgIREZG4syZM4YWyWjIyclBdHQ0OnTogE6dOuG3335DQUFBsb+WAOD48eOoVq0aevbsCQCwtDTbbuIakZOTg8GDB6NOnTq4du0avc/8P/n5+YiOjoafnx9u376N169fG1okoyEnJweRkZGoUaMGzp49i8TERACm9cymo5yDW7duwd/fH0lJSejXrx9SU1Mxfvx4zJw5E0Dx9px9+PABrVq1wq1btzBq1Cjk5uZi2rRpGDdunKFFMygxMTFo2LAhZs+ejR07duD+/fsAivdYAYC9e/eiatWqSEhIQEhICBISEjBlyhT8888/hhbN4Gzbtg1VqlRBYmIiJk2ahHLlymH79u3YuHGjoUUzCu7evYvg4GC8fv0aq1evBkC9rH/88Qfc3d1x584dXLt2DXPmzDEpo0NIFi1ahOvXr+PUqVNYu3YtmjVrBsC0vIhC8Ouvv8LV1RVPnjxBcnIyunTpgtTUVAAwKe88NVg5kD5kjx8/jvDwcOzbtw+hoaGYPXs24uPji/Ub7fXr1/Hq1SusXLkS4eHh2Lt3L6ZOnYolS5bgyJEjhhbPYPz777+oW7cu/vzzTwDA2rVrARRvL+uDBw+wZcsWDBo0CCdOnMCoUaNw7NgxWFtbywz64kpaWhoOHTqE7777DidPnkT37t2xcOFC5Ofnw9ra2tDiGRSpgfHkyRP4+Phg8ODB+Omnn5CTkwNLS8tia4Ckp6dj5syZaNCgAc6dOwd/f3/cuXMHDx48wKdPnwwtnsEghODz58/Ys2cPBgwYgIYNG+LChQtYtWoVzp49i8+fPxtaRIOxdu1a/PXXX9iwYQNOnToFb29vBAUF4ezZswAACwsLA0uoPsX3ScpBQUEBMjMzcfPmTTg6OkIsFiM/Px92dnawt7cHAEyYMMHAUhqWt2/f4tmzZ6hduzYASRu3qKgoREREYOLEicUuTlH68Bw+fDjGjBmDYcOGoUGDBjhz5gxOnToFoPh5WaU6ycnJQZ06dRAVFQVA8jZfqlQpWFhYyOISixtS3bi6umLSpEkYOHCgbFtaWhpcXFzg4uKCt2/fGkpEgyP1GL5+/RqdOnVCr169YGVlhRkzZgAAvnz5Ykjx9I50zDg5OWHBggVISEhAbGwsevfujc6dO6N9+/Zo3bo11q9fb2BJDYNIJMKLFy/w8OFDtG/fHuPHj0dYWBg2btyIsLAwdO/eHenp6YYWU69Inzndu3dHQkICevXqJdvm4OAAOzs7k7sHU4MVwKpVq7Bt2zbcv38fYrEYdnZ2sLKyQk5ODuLi4mRvILdv38b333+P8+fP47///gNg/lMNly9fBiBvcDk5OcHLy0s2pSuN650xYwaSk5Nl683ZSGPqRfpwrVWrlsyI79OnDxwcHLBhwwYUFBRALBab/VgBlMeLr68vpk+fjkqVKgGQvM3n5OTgy5cvaNy4scHkNARS3UjHgZWVFerUqYOSJUsCAKZMmYJatWrhy5cvGDFiBEJDQ3Ho0CEAxedakiLV0YcPH/D582f4+PhgypQpWL58OSIiIjBlypRiYdArjhkAGDBgAKpWrYp27drByckJ69atw9KlS+Hn54cff/wRx48fN5S4eoNtzJQvXx7u7u748ccf8eTJExw7dgz79+/HsWPHEB8fjzlz5hSre7D0u7q5ucmeUdJ1DRs2RFJSEmxtbeXWGz2kGHPkyBFSqlQpEhAQQCpWrEiqVatG5s+fTwgh5PLlyyQoKIhUrlyZDBo0iDg6OpIWLVqQpKQkEhISQkaNGmVg6YVlz549pGzZssTd3Z08evSIEEJIbm4uIYSQhw8fktDQUDJ8+HCSkZFBCCEkPz+f5ObmkoEDB5Lg4GBDiS04bHrJz89n3fe3334jDRs2JFu2bCGEEFJQUKAvMfUOm17y8vJk25nf/dOnT6RatWrk4sWL+hbTIKg7ZsaMGUOOHj1KsrOzyb1798iwYcOIl5eXnqXVH0XpJSsri1SrVo28evWKEELIrFmziK2tLbGxsSHx8fHF+nq6cuUK+f7778mbN29k6x49ekS6detGOnbsqG9x9YYqvbx7944MHjyYlChRgvTo0YPk5+fLxtOaNWuIs7Mz+fLli6FEFxxNnk3JycmkQoUKZP369foTkAeKtYd1zZo16N69O65du4bY2FgMGzYMkyZNwr///ov69etj7dq1GD58OLKysrBx40acPHkSvr6+yMzMROnSpQ0tvmBs3boVv/zyC4KDg+Hr64tff/0VAGSxY5UqVUJISAiuXr2KPXv2AJDEaVpaWsLV1RU2NjbIyMgw5FcQBC69KMaoSt/6+/bti/Lly2PHjh149+4dAODmzZty+5gDXHphxkYxk0LOnTuHjIwM+Pj4yNa9evVKfwLrEXXGjHQsLFq0CKGhobC2tka1atVQr149FBQU4M6dOwaRXUiK0ktBQQEIIahbty62bduGwMBA/O9//0OfPn1gb2+Pjx8/QiQSmWUCljrXU1BQEH744Qe4u7vL1nl7e8PR0VEWz2luFKUXV1dX2fWTn58vN6tVu3ZtWFtb4/bt2waTX0jUfTZJsbW1hY2NjVLJTmOn2Bms0gH86NEjHD16FD169AAAVKtWDePHj0ffvn0xceJEPH78GP7+/pg4cSK2bt2KHj16gBCC5ORkvH//HhUrVjTk1xAEabZg1apVERoait9++w1du3bFyZMncfLkSQCSsk0AMGLECJQrVw6rV6+Wq3WXlpaGsmXLwtHRUe/yC4U6emFmWkpvEl5eXujWrRvev3+PiRMnIiAgAK1bt0ZeXp5ZJGJpqhcpe/bsQUhICFxdXXHt2jW0bNkSI0aMMCsjXhPdSMeCYqb31atXERwcjBo1auhPcIFRVy9isRgZGRnYt28fpkyZgmbNmiEpKQkLFixAmzZt8PXXXwMwrzJXmowZkUikdI/NzMzEixcvULt2bTg4OOhVdiFRRy85OTkAgK5du6J///7Yv38/jh49KjNmz549i4CAAAQEBBjiKwiGNvdgQgjKlSsHDw8PXLx4EYAJOVAM6N3VK/fu3ZObQsrMzCSlS5cmq1atIoQQkp2dTQgh5MOHD8Te3l4WGiD9zMuXL8mLFy9I3759SdOmTcnr16/1/A2EQ1E3hBRO/9+6dYt07dpVbppJuu3MmTOkQ4cOxMXFhUyYMIFEREQQNzc3cuDAAUKI6U+Ba6oX5r7S/+Pj44m7uzsRiURkxIgRJCsrSw+SC4suesnPzydfffUVmT9/Phk5ciQRi8UkMjKS5OTk6Ed4gdFFN4RI7j9PnjwhQ4YMIZUqVSq215J0PPz777/kypUrcp/777//yOzZs0lBQYHJ64UQfsZMSkoKGTRoEPH19SXx8fHCC60HNNWLNDTg4cOHJDIykjg4OJAePXqQvn37Ejc3N7Jy5UpCiOlfS4ToPmYKCgrI6NGjSZMmTWRhfaaA2RusO3bsIN7e3qR69eqkQYMGZO3atYQQQjIyMkhkZCRp166dzFiV3iSnTJlCvL29Zcd48eIF+fHHH4mrqysJDg4mDx8+1P8XEQAu3RAiP8DXrVtHatasSdatW0cIKbwwCJHEmf3www8kMjKS9OjRg9y5c0d/X0AgtNWLYrzQ1q1biYWFBWnZsiV58OCBfoQXED70kpKSQkQiERGJRKRJkyYkKSlJf19AQPjQTUxMDBkzZgzx9PQkISEh5N69e/r7AgLBxz1GcX9zMDgI4WfMHD58mIwYMYK4u7uTkJAQcv/+ff19AYHga8ysWLGCTJw4kQwcONAsnkuE8PdsIoSQ4cOHkxEjRsjsH1PArA3WmJgY4u3tTZYtW0aOHDlCxo0bRywtLWVe1Q0bNpDAwEDZm5d0wF+5coWUKlVK9mafm5tLTpw4QY4dO2aYLyIAbLqxsrIiq1atkgWmS/Xx7NkzMnjwYFK/fn3y6dMnQghRGuTMhABTRle9MD2Ft2/fJv/++6/+v4QA8DVebt26Rfr06UNiY2MN80UEgC/dpKSkkLVr15Ljx48b5ovwDJ/XkrnB15h5/PgxWbZsGTl69KhhvgjP0DHDDV+6kT6rTVFXZmmwSt80Zs2aRYKCguR+mG+//ZYEBgaS//77j6Snp5OIiAjSpEkTWVYdIZK3mLJly5qNJ5VJUbqpV68e2b17t9LnDhw4QOrVq0dmzJhBrl+/Tjp37kxSUlL0JrfQUL2ww5deOnXqZFZ6IYSOGS6oXrih1xM7dMxwQ3VTiOlnfrAgTV5ISkpClSpVYGVlJUsWmjNnDhwcHLBlyxZYWFggOjoaYrEY4eHhOH/+PFJSUnDo0CEEBQXB09PTkF9DEIrSja2tLfbt26fUtq1ly5Zo0KABfvrpJwQFBSE3N9esKiVQvbDDl17y8vLMSi8AHTNcUL1wQ68nduiY4YbqhoGhLWY+iImJIaNGjSKLFy8mly5dkq1ftWoVKVGihJILfNWqVaRq1ark7NmzhBBC7ty5Q4KCgkj16tWJh4cHCQwMNJuYF2104+PjQ06ePCnbNyMjgyxevJhYWFiQkJAQcuPGDf1+CQGgemGH6oUbqht2qF64obphh+qFG6obbkzaYH3x4gXp3LkzKV26NImIiCB+fn7E2dlZ9iPfvXuXlCtXjkybNo0QIh936enpSRYtWiRb/vTpE3n06JHZFDPXVTeLFy+WLScmJpKGDRuSTZs26fU7CAHVCztUL9xQ3bBD9cIN1Q07VC/cUN0UjckarJ8/fyZRUVGkT58+crGmDRo0IAMGDCCEEJKenk7mzJlD7OzsZLEb0niQFi1akCFDhsg+Zy6Zp4TwrxtzgeqFHaoXbqhu2KF64Ybqhh2qF26obtTDZGNY7e3tYWNjgwEDBqBSpUqyjicdO3bE7du3QQhBiRIl8PXXX6Nu3bro3bs3njx5ApFIhJSUFKSlpaFbt26y4ykW7TZl+NaNuUD1wg7VCzdUN+xQvXBDdcMO1Qs3VDfqISLk/1s/mSC5ubmwsrICIOnUIBaLERERAQcHB6xatUq23/PnzxESEoK8vDzUq1cP58+fR40aNbBt2zZ4eHgYSnxBobphh+qFHaoXbqhu2KF64Ybqhh2qF26oborGpA1WNpo1a4ahQ4ciKipK1m5MLBYjOTkZ8fHxuHTpEvz9/REVFWVgSfUP1Q07VC/sUL1wQ3XDDtULN1Q37FC9cEN1o4BBAhEE4sGDB8TDw4PExcXJ1plSFwchobphh+qFHaoXbqhu2KF64Ybqhh2qF26obpQx2RhWJuT/ncRnz56Fo6MjgoKCAACzZs3C6NGjkZaWZkjxDArVDTtUL+xQvXBDdcMO1Qs3VDfsUL1wQ3XDjaWhBeADacLU5cuXERYWhtjYWHzzzTf48uULNm/ebPrFcnWA6oYdqhd2qF64obphh+qFG6obdqheuKG6UYHBfLs8k5mZSapWrUpEIhGxsbEhv/76q6FFMhqobtihemGH6oUbqht2qF64obphh+qFG6obdswq6apNmzaoVq0aFi1aBFtbW0OLY1RQ3bBD9cIO1Qs3VDfsUL1wQ3XDDtULN1Q3ypiVwZqfnw8LCwtDi2GUUN2wQ/XCDtULN1Q37FC9cEN1ww7VCzdUN8qYlcFKoVAoFAqFQjE/zKJKAIVCoVAoFArFfKEGK4VCoVAoFArFqKEGK4VCoVAoFArFqKEGK4VCoVAoFArFqKEGK4VCoVAoFArFqKEGK4VCoVAoFArFqKEGK4VCoZgp3t7eWLJkiaHFoFAoFJ2hBiuFQqEUwYABAyASiSASiWBlZQUPDw+0adMG69atQ0FBgUbH2rBhA1xcXHSS5+TJkzJ5uP5OnjyJK1eu4JtvvtHpXBQKhWIMWBpaAAqFQjEF2rdvj/Xr1yM/Px+vXr3CkSNHMHr0aOzatQv79++HpaX+bqdNmjTBy5cvZcujR49Geno61q9fL1vn5uYGa2trvclEoVAoQkI9rBQKhaIGNjY28PT0RLly5VC3bl1MnToV+/btw+HDh7FhwwbZfosWLYKfnx8cHBzg5eWFb7/9FhkZGQAkntGBAwfi48ePMk/ozJkzAQDZ2dmYMGECypUrBwcHBzRs2BAnT55klcXa2hqenp6yPzs7O5l80j9ra2ulkACRSISVK1eic+fOsLe3h6+vLy5cuIDk5GSEhITAwcEBTZo0wYMHD+TOt2/fPtStWxe2traoXLkyZs2ahby8PD7VS6FQKCqhBiuFQqFoSatWreDv74/du3fL1onFYvz+++9ITEzExo0bcfz4cUyaNAmAxDO6ZMkSODk54eXLl3j58iUmTJgAABg5ciQuXLiA7du348aNG+jVqxfat2+P+/fv8yrz7NmzERkZiYSEBNSoUQNff/01hg0bhilTpiAuLg6EEIwcOVK2/5kzZxAZGYnRo0cjKSkJK1euxIYNG/Dzzz/zKheFQqGoghqsFAqFogM1atTA48ePZctjxoxBy5Yt4e3tjVatWmHOnDnYuXMnAIln1NnZGSKRSOYJdXR0REpKCtavX4+///4bzZs3R5UqVTBhwgQ0a9ZMbpqfDwYOHIjevXvDx8cHkydPxuPHjxEREYF27drB19cXo0ePlvPszpo1C99//z2ioqJQuXJltGnTBrNnz8bKlSt5lYtCoVBUQWNYKRQKRQcIIRCJRLLlo0ePYu7cubhz5w7S09ORl5eHrKwsfPnyBfb29qzHuHnzJvLz8+Hj4yO3Pjs7G+7u7rzKW6dOHdn/Hh4eAAA/Pz+5dVlZWUhPT4eTkxOuX7+Oc+fOyXlU8/Pzi/xOFAqFwifUYKVQKBQduH37NipVqgQAePz4MTp37owRI0bg559/hpubG86ePYvBgwcjJyeH07jLyMiAhYUF4uPjYWFhIbfN0dGRV3mtrKxk/0sNbbZ10uoHGRkZmDVrFnr06KF0LFtbW15lo1AoFC6owUqhUChacvz4cdy8eRNjx44FAMTHx6OgoAALFy6EWCyJuJKGA0ixtrZGfn6+3LrAwEDk5+cjLS0NzZs314/walK3bl3cvXsXVatWNbQoFAqlGEMNVgqFQlGD7OxspKamypW1mjt3Ljp37ozIyEgAQNWqVZGbm4s//vgDXbp0wblz57BixQq543h7eyMjIwPHjh2Dv78/7O3t4ePjg4iICERGRmLhwoUIDAzE69evcezYMdSpUwedOnUyxFcGAEyfPh2dO3dGhQoV0LNnT4jFYly/fh23bt3CnDlzDCYXhUIpXtCkKwqFQlGDI0eOoEyZMvD29kb79u1x4sQJ/P7779i3b59sGt/f3x+LFi3Cb7/9Lu4QuAAAAQdJREFUhtq1a2Pr1q2YO3eu3HGaNGmC4cOHo0+fPihVqhTmzZsHAFi/fj0iIyMxfvx4VK9eHd26dcOVK1dQoUIFvX9XJu3atcOBAwcQExOD+vXro1GjRli8eDEqVqxoULkoFErxQkQIIYYWgkKhUCgUCoVC4YJ6WCkUCoVCoVAoRg01WCkUCoVCoVAoRg01WCkUCoVCoVAoRg01WCkUCoVCoVAoRg01WCkUCoVCoVAoRg01WCkUCoVCoVAoRg01WCkUCoVCoVAoRg01WCkUCoVCoVAoRg01WCkUCoVCoVAoRg01WCkUCoVCoVAoRg01WCkUCoVCoVAoRg01WCkUCoVCoVAoRs3/ARlXpnhrG5iEAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 800x600 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_cols = ['T (degC)', 'p (mbar)', 'rho (g/m**3)']\n",
+    "plot_features = df[plot_cols]\n",
+    "plot_features.index = date_time\n",
+    "_ = plot_features.plot(subplots=True)\n",
+    "\n",
+    "plot_features = df[plot_cols][:480]\n",
+    "plot_features.index = date_time[:480]\n",
+    "_ = plot_features.plot(subplots=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "wXWLG0_WBhZS"
+   },
+   "source": [
+    "### Inspect and cleanup"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "yhmZXJew6GlS"
+   },
+   "source": [
+    "Next, look at the statistics of the dataset:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:26:59.438905Z",
+     "iopub.status.busy": "2023-07-27T04:26:59.438231Z",
+     "iopub.status.idle": "2023-07-27T04:26:59.507537Z",
+     "shell.execute_reply": "2023-07-27T04:26:59.506919Z"
+    },
+    "id": "h510pgKVrrai"
+   },
+   "outputs": [
+    {
+     "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>mean</th>\n",
+       "      <th>std</th>\n",
+       "      <th>min</th>\n",
+       "      <th>25%</th>\n",
+       "      <th>50%</th>\n",
+       "      <th>75%</th>\n",
+       "      <th>max</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>p (mbar)</th>\n",
+       "      <td>70091.0</td>\n",
+       "      <td>989.212842</td>\n",
+       "      <td>8.358886</td>\n",
+       "      <td>913.60</td>\n",
+       "      <td>984.20</td>\n",
+       "      <td>989.57</td>\n",
+       "      <td>994.720</td>\n",
+       "      <td>1015.29</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>T (degC)</th>\n",
+       "      <td>70091.0</td>\n",
+       "      <td>9.450482</td>\n",
+       "      <td>8.423384</td>\n",
+       "      <td>-22.76</td>\n",
+       "      <td>3.35</td>\n",
+       "      <td>9.41</td>\n",
+       "      <td>15.480</td>\n",
+       "      <td>37.28</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Tpot (K)</th>\n",
+       "      <td>70091.0</td>\n",
+       "      <td>283.493086</td>\n",
+       "      <td>8.504424</td>\n",
+       "      <td>250.85</td>\n",
+       "      <td>277.44</td>\n",
+       "      <td>283.46</td>\n",
+       "      <td>289.530</td>\n",
+       "      <td>311.21</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Tdew (degC)</th>\n",
+       "      <td>70091.0</td>\n",
+       "      <td>4.956471</td>\n",
+       "      <td>6.730081</td>\n",
+       "      <td>-24.80</td>\n",
+       "      <td>0.24</td>\n",
+       "      <td>5.21</td>\n",
+       "      <td>10.080</td>\n",
+       "      <td>23.06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>rh (%)</th>\n",
+       "      <td>70091.0</td>\n",
+       "      <td>76.009788</td>\n",
+       "      <td>16.474920</td>\n",
+       "      <td>13.88</td>\n",
+       "      <td>65.21</td>\n",
+       "      <td>79.30</td>\n",
+       "      <td>89.400</td>\n",
+       "      <td>100.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>VPmax (mbar)</th>\n",
+       "      <td>70091.0</td>\n",
+       "      <td>13.576576</td>\n",
+       "      <td>7.739883</td>\n",
+       "      <td>0.97</td>\n",
+       "      <td>7.77</td>\n",
+       "      <td>11.82</td>\n",
+       "      <td>17.610</td>\n",
+       "      <td>63.77</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>VPact (mbar)</th>\n",
+       "      <td>70091.0</td>\n",
+       "      <td>9.533968</td>\n",
+       "      <td>4.183658</td>\n",
+       "      <td>0.81</td>\n",
+       "      <td>6.22</td>\n",
+       "      <td>8.86</td>\n",
+       "      <td>12.360</td>\n",
+       "      <td>28.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>VPdef (mbar)</th>\n",
+       "      <td>70091.0</td>\n",
+       "      <td>4.042536</td>\n",
+       "      <td>4.898549</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.87</td>\n",
+       "      <td>2.19</td>\n",
+       "      <td>5.300</td>\n",
+       "      <td>46.01</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sh (g/kg)</th>\n",
+       "      <td>70091.0</td>\n",
+       "      <td>6.022560</td>\n",
+       "      <td>2.655812</td>\n",
+       "      <td>0.51</td>\n",
+       "      <td>3.92</td>\n",
+       "      <td>5.59</td>\n",
+       "      <td>7.800</td>\n",
+       "      <td>18.07</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>H2OC (mmol/mol)</th>\n",
+       "      <td>70091.0</td>\n",
+       "      <td>9.640437</td>\n",
+       "      <td>4.234862</td>\n",
+       "      <td>0.81</td>\n",
+       "      <td>6.29</td>\n",
+       "      <td>8.96</td>\n",
+       "      <td>12.490</td>\n",
+       "      <td>28.74</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>rho (g/m**3)</th>\n",
+       "      <td>70091.0</td>\n",
+       "      <td>1216.061232</td>\n",
+       "      <td>39.974263</td>\n",
+       "      <td>1059.45</td>\n",
+       "      <td>1187.47</td>\n",
+       "      <td>1213.80</td>\n",
+       "      <td>1242.765</td>\n",
+       "      <td>1393.54</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>wv (m/s)</th>\n",
+       "      <td>70091.0</td>\n",
+       "      <td>1.702567</td>\n",
+       "      <td>65.447512</td>\n",
+       "      <td>-9999.00</td>\n",
+       "      <td>0.99</td>\n",
+       "      <td>1.76</td>\n",
+       "      <td>2.860</td>\n",
+       "      <td>14.01</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max. wv (m/s)</th>\n",
+       "      <td>70091.0</td>\n",
+       "      <td>2.963041</td>\n",
+       "      <td>75.597657</td>\n",
+       "      <td>-9999.00</td>\n",
+       "      <td>1.76</td>\n",
+       "      <td>2.98</td>\n",
+       "      <td>4.740</td>\n",
+       "      <td>23.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>wd (deg)</th>\n",
+       "      <td>70091.0</td>\n",
+       "      <td>174.789095</td>\n",
+       "      <td>86.619431</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>125.30</td>\n",
+       "      <td>198.10</td>\n",
+       "      <td>234.000</td>\n",
+       "      <td>360.00</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                   count         mean        std      min      25%      50%  \\\n",
+       "p (mbar)         70091.0   989.212842   8.358886   913.60   984.20   989.57   \n",
+       "T (degC)         70091.0     9.450482   8.423384   -22.76     3.35     9.41   \n",
+       "Tpot (K)         70091.0   283.493086   8.504424   250.85   277.44   283.46   \n",
+       "Tdew (degC)      70091.0     4.956471   6.730081   -24.80     0.24     5.21   \n",
+       "rh (%)           70091.0    76.009788  16.474920    13.88    65.21    79.30   \n",
+       "VPmax (mbar)     70091.0    13.576576   7.739883     0.97     7.77    11.82   \n",
+       "VPact (mbar)     70091.0     9.533968   4.183658     0.81     6.22     8.86   \n",
+       "VPdef (mbar)     70091.0     4.042536   4.898549     0.00     0.87     2.19   \n",
+       "sh (g/kg)        70091.0     6.022560   2.655812     0.51     3.92     5.59   \n",
+       "H2OC (mmol/mol)  70091.0     9.640437   4.234862     0.81     6.29     8.96   \n",
+       "rho (g/m**3)     70091.0  1216.061232  39.974263  1059.45  1187.47  1213.80   \n",
+       "wv (m/s)         70091.0     1.702567  65.447512 -9999.00     0.99     1.76   \n",
+       "max. wv (m/s)    70091.0     2.963041  75.597657 -9999.00     1.76     2.98   \n",
+       "wd (deg)         70091.0   174.789095  86.619431     0.00   125.30   198.10   \n",
+       "\n",
+       "                      75%      max  \n",
+       "p (mbar)          994.720  1015.29  \n",
+       "T (degC)           15.480    37.28  \n",
+       "Tpot (K)          289.530   311.21  \n",
+       "Tdew (degC)        10.080    23.06  \n",
+       "rh (%)             89.400   100.00  \n",
+       "VPmax (mbar)       17.610    63.77  \n",
+       "VPact (mbar)       12.360    28.25  \n",
+       "VPdef (mbar)        5.300    46.01  \n",
+       "sh (g/kg)           7.800    18.07  \n",
+       "H2OC (mmol/mol)    12.490    28.74  \n",
+       "rho (g/m**3)     1242.765  1393.54  \n",
+       "wv (m/s)            2.860    14.01  \n",
+       "max. wv (m/s)       4.740    23.50  \n",
+       "wd (deg)          234.000   360.00  "
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.describe().transpose()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "TzOTnWOoWMGK"
+   },
+   "source": [
+    "#### Wind velocity"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "i47LiW5DCVsP"
+   },
+   "source": [
+    "One thing that should stand out is the `min` value of the wind velocity (`wv (m/s)`) and the maximum value (`max. wv (m/s)`) columns. This `-9999` is likely erroneous.\n",
+    "\n",
+    "There's a separate wind direction column, so the velocity should be greater than zero (`>=0`). Replace it with zeros:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:26:59.511021Z",
+     "iopub.status.busy": "2023-07-27T04:26:59.510767Z",
+     "iopub.status.idle": "2023-07-27T04:26:59.520268Z",
+     "shell.execute_reply": "2023-07-27T04:26:59.519721Z"
+    },
+    "id": "qFOq0_80vF4d"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.0"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "wv = df['wv (m/s)']\n",
+    "bad_wv = wv == -9999.0\n",
+    "wv[bad_wv] = 0.0\n",
+    "\n",
+    "max_wv = df['max. wv (m/s)']\n",
+    "bad_max_wv = max_wv == -9999.0\n",
+    "max_wv[bad_max_wv] = 0.0\n",
+    "\n",
+    "# The above inplace edits are reflected in the DataFrame.\n",
+    "df['wv (m/s)'].min()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "vtmu2IBPgPG8"
+   },
+   "source": [
+    "### Feature engineering\n",
+    "\n",
+    "Before diving in to build a model, it's important to understand your data and be sure that you're passing the model appropriately formatted data."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "FYyEaqiD6j4s"
+   },
+   "source": [
+    "#### Wind\n",
+    "The last column of the data, `wd (deg)`—gives the wind direction in units of degrees. Angles do not make good model inputs: 360° and 0° should be close to each other and wrap around smoothly. Direction shouldn't matter if the wind is not blowing.\n",
+    "\n",
+    "Right now the distribution of wind data looks like this:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:26:59.523711Z",
+     "iopub.status.busy": "2023-07-27T04:26:59.523155Z",
+     "iopub.status.idle": "2023-07-27T04:26:59.921459Z",
+     "shell.execute_reply": "2023-07-27T04:26:59.920860Z"
+    },
+    "id": "YO7JGTcWQG2z"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Wind Velocity [m/s]')"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist2d(df['wd (deg)'], df['wv (m/s)'], bins=(50, 50), vmax=400)\n",
+    "plt.colorbar()\n",
+    "plt.xlabel('Wind Direction [deg]')\n",
+    "plt.ylabel('Wind Velocity [m/s]')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "yWnf5dwMU1_g"
+   },
+   "source": [
+    "But this will be easier for the model to interpret if you convert the wind direction and velocity columns to a wind **vector**:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:26:59.925284Z",
+     "iopub.status.busy": "2023-07-27T04:26:59.924635Z",
+     "iopub.status.idle": "2023-07-27T04:26:59.939443Z",
+     "shell.execute_reply": "2023-07-27T04:26:59.938895Z"
+    },
+    "id": "6GmSTHXw6lI1"
+   },
+   "outputs": [],
+   "source": [
+    "wv = df.pop('wv (m/s)')\n",
+    "max_wv = df.pop('max. wv (m/s)')\n",
+    "\n",
+    "# Convert to radians.\n",
+    "wd_rad = df.pop('wd (deg)')*np.pi / 180\n",
+    "\n",
+    "# Calculate the wind x and y components.\n",
+    "df['Wx'] = wv*np.cos(wd_rad)\n",
+    "df['Wy'] = wv*np.sin(wd_rad)\n",
+    "\n",
+    "# Calculate the max wind x and y components.\n",
+    "df['max Wx'] = max_wv*np.cos(wd_rad)\n",
+    "df['max Wy'] = max_wv*np.sin(wd_rad)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "7iI0zDoxWDyB"
+   },
+   "source": [
+    "The distribution of wind vectors is much simpler for the model to correctly interpret:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:26:59.942995Z",
+     "iopub.status.busy": "2023-07-27T04:26:59.942516Z",
+     "iopub.status.idle": "2023-07-27T04:27:00.197140Z",
+     "shell.execute_reply": "2023-07-27T04:27:00.196516Z"
+    },
+    "id": "bMgCG5o2SYKD"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(-11.305513973134667, 8.24469928549079, -8.27438540335515, 7.7338312955467785)"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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XHH7ZglFQDh63bNmi559/Xl27dg10VwAAABqVoBs8Hj9+XCNGjNCf//xnNW3a9LyxFRUVKi0t9doAAABqy22dmTRj3xbos7owQTd4zM7O1tChQzVgwACfsbNmzVJ8fLxny8jIqIMeAgAANFxBNWHm5Zdf1ocffqgtW7YYxefk5GjSpEmer0tLSxlAAgCAWnP7YcKM3e3VlaAZPBYWFur+++/XqlWrFBlpUFNNUkREhCIiDGuXAQAAwKegGTzm5+eruLhYl19+uWefy+XSu+++qz/+8Y+qqKhQiM1FcwEAACTJLYfcNs+Otru9uhI0g8drr71W27dv99o3duxYdejQQVOmTGHgCFwMh+GtE9MVLUzbCxCH0+wXtuW273OxDJ+MdxjeLbEqq8zaM/3dGGr258ARHWXWXpVZ/2SZfS7u42VGcY5Is8/PYbiyjfvECYPG7P1+N71mpt9Txlixpt6bP3++5s+fry+//FKSdNlll2natGkaMmSIJKm8vFwPPfSQXn75ZVVUVGjQoEGaN2+eUlJSPG3s27dPEyZM0Lp16xQTE6PRo0dr1qxZCjX8HSAF0eAxNjZWnTt39toXHR2tZs2anbUfAADATi7LIZfNywnWtr0WLVroySef1KWXXirLsvTiiy9q2LBh+uijj3TZZZfpwQcf1FtvvaVXXnlF8fHxmjhxom6++Wa9//77p47ncmno0KFKTU3Vxo0bdejQIY0aNUphYWF64oknjPsRNINHAACAQKkPE2ZuvPFGr68ff/xxzZ8/X5s2bVKLFi20cOFCLVmyRP3795ckLVq0SB07dtSmTZt01VVX6Z133tEnn3yi1atXKyUlRd27d9djjz2mKVOmaMaMGQoPDzfqR/2+t+RDbm6u5syZE+huAAAAXLDv16SuqKjw+R6Xy6WXX35ZZWVlyszMVH5+vqqqqrxKGXbo0EEtW7ZUXl6eJCkvL09dunTxuo09aNAglZaWaufOncb9DerBIwAAQF1wy+4C4Wcm4GRkZHjVpZ41a1aN/di+fbtiYmIUERGhu+++W0uXLlWnTp1UVFSk8PBwJSQkeMWnpKSoqKhIklRUVOQ1cDz9+unXTHHbGgAAIIAKCwsVFxfn+fp8ZQbbt2+vbdu2qaSkRP/4xz80evRorV+/vi666cHgEQAAwAfLD6V6rP+0FxcX5zV4PJ/w8HBdcsklkqSePXtqy5Yt+sMf/qBbb71VlZWVOnr0qFf28fDhw0pNTZUkpaam6oMPPvBq7/Dhw57XTHHbGgAAIEi53W5VVFSoZ8+eCgsL05o1azyvFRQUaN++fcrMzJQkZWZmavv27SouLvbErFq1SnFxcerUqZPxMck8AgAA+HD6OUW726yNnJwcDRkyRC1bttSxY8e0ZMkS5ebmauXKlYqPj9e4ceM0adIkJSYmKi4uTvfee68yMzN11VVXSZIGDhyoTp06aeTIkXrqqadUVFSkqVOnKjs7u1Yr8jF4BGDO7uLfhkWJnRFmS5K6KysvpjdnMS3W7K6q9hnjNCyBYcoRHmYU54yNMWuwSROzOINZoJIkw2LdKjdrz5nUzKw9w8LZlknxb5kXbTdi+O1p+n1nOuww/bkwLk7uchkeGXYrLi7WqFGjdOjQIcXHx6tr165auXKlrrvuOknSM888I6fTqeHDh3sVCT8tJCREy5Yt04QJE5SZmano6GiNHj1aM2fOrFU/GDwCAAD4UB/qPC5cuPC8r0dGRmru3LmaO3dujTGtWrXS8uXLa3Xc72PwCAAA4EN9uG1dXzBhBgAAAMbIPAIAAPjg9kOpHrvbqytkHgEAAGCMzCMAAIAPPPN4BplHAAAAGCPzCAAA4AOZxzMYPAINWYCKehsf1zDO7qLEjlCzAtumxw2Jib6Y7nhzmn0mDtMi3KFmv+atGLNC7I5Is2LnlsPsj6LDaVaYWmGGf65Kj5kd187i3y7DnwvTOKfhgMKwILopy+b20HAxeAQAAPCBzOMZDB4BAAB8YPB4BhNmAAAAYIzMIwAAgA+W7C/qHaxPmZJ5BAAAgDEyjwAAAD7wzOMZZB4BAABgjMwjAACAD2Qez2DwCDRkhkW9neFmhZ/dVdVGcQ7TIsc2FzEPiY4yijMuOm4YZtKe07CQuHXipNlBDc9VhufqNiz+bcoVbVaIXY4Yo7CQ41VGcc4Isz9rjq++NYozaivc7FwdpgXbKyuN4twnThjFGTNdBACNHoNHAAAAH8g8nsHgEQAAwAcGj2cwYQYAAADGyDwCAAD4YFkOWTZnCu1ur66QeQQAAIAxMo8AAAA+uOWwfXlCu9urK2QeAQAAYIzMIwAAgA/Mtj6DzCMAAACMkXkEGjBHSIhRnOnKMcbHNVyxxjI8rjMy4mK6cxbTz8UZZbhijcnKHJZl1JYjPs4oThVmq5BYzeKN4lwxZqukVMabxbnNPmK5w8wyL+FNzBqM+MbsuM7kRKM4R6XB92iZ4apAJ8uNwtyGcZbb7HvKeOUY0xWfGulKNMy2PoPMIwAAAIyReQQAAPCBZx7PYPAIAADgA7etz+C2NQAAAIyReQQAAPDB8sNtazKPAAAAaPDIPAIAAPhgybjiVq3aDEZkHgEAAGCMzCMQjAyL+ZoWEXY4zZ67MS2aLadZ/xwRZsW/HeFmhanlMDsPq6rKrL1Qs8LUjlCD84gwLJweHWkUJ7dZoeaT6TFmxzUs1u0KN4s7kWT2PdDkG7PzCKk0i3NHmP1ZswyvbUipQQHwEyfMjmlaTDxQRbgbafFvU2455JDNpXpsbq+ukHkEAACAMTKPAAAAPlDn8QwGjwAAAD64LYccrDAjKYhuW8+aNUtXXHGFYmNjlZycrJtuukkFBQWB7hYAAECjEjSDx/Xr1ys7O1ubNm3SqlWrVFVVpYEDB6qsrCzQXQMAAA2cZflnC0ZBc9t6xYoVXl8vXrxYycnJys/PV58+fQLUKwAAgMYlaAaP31dSUiJJSkxMrDGmoqJCFRUVnq9LS0v93i8AANDwMGHmjKC5bf1dbrdbDzzwgH70ox+pc+fONcbNmjVL8fHxni0jI6MOewkAANDwBGXmMTs7Wzt27NCGDRvOG5eTk6NJkyZ5vi4tLWUAifrNsPi3aTFfZ4RZwWlHdBOzw5ZX+A6S5IyLNYpTmGHxb9Oi3obtOUINf/VVV5vFxfgunm6FmRWldsWaXbOqGLNzOJFqFneyuVkGxG1W61xOs28VVcSZfc+fbGZWUD66yGUU1+SrSqM4R4Xv7wGr0vD70/Dn1nKZnYPx7wvYgszjGUE3eJw4caKWLVumd999Vy1atDhvbEREhCIMV7AAAACAb0EzeLQsS/fee6+WLl2q3NxctW7dOtBdAgAAjQR1Hs8Impx3dna2/vrXv2rJkiWKjY1VUVGRioqKdPKk4VqhAAAAF6g+lOoxqXndr18/ORwOr+3uu+/2itm3b5+GDh2qqKgoJScna/Lkyao2fUxHQZR5nD9/vqRTH8p3LVq0SGPGjKn7DgEAANSh0zWvr7jiClVXV+tXv/qVBg4cqE8++UTR0dGeuPHjx2vmzJmer6OizjyX7XK5NHToUKWmpmrjxo06dOiQRo0apbCwMD3xxBNG/QiawaMVrJU0AQBA0DuVKbR7wkzt4k1rXkdFRSk1NfWcbbzzzjv65JNPtHr1aqWkpKh79+567LHHNGXKFM2YMUPh4b5nxQXNbWsAAICGqLS01Gv7bo3q86mp5vVLL72k5s2bq3PnzsrJydGJEyc8r+Xl5alLly5KSUnx7Bs0aJBKS0u1c+dOo+MGTeYRAAAgUPxZquf7ZQSnT5+uGTNmnPe9NdW8/vnPf65WrVopPT1dH3/8saZMmaKCggK9+uqrkqSioiKvgaMkz9dFRUVG/WbwCAAAEECFhYWKi4vzfG1SZrCmmtd33XWX5/+7dOmitLQ0XXvttdqzZ4/atm1rS38ZPAI1sbNgt83FfJ1NzIp6O0LMClMbHzc5ySwwwqxYtzvarA6r5TT7/KxQs7iQ4+VGcaYFu0OO+77FVJ4WY9SW5TTLbBxvYfYZHzdcF6GyqVkBa1POSrPzqIw3i4s5YHZc0+LfYUVmy9W69x80CDJ7cM1dZT6bFfWP9Z/N7jYlKS4uzmvw6Ettal737t1bkrR79261bdtWqamp+uCDD7xiDh8+LEk1Pif5fTzzCAAAEAQsy9LEiRO1dOlSrV271qjm9bZt2yRJaWlpkqTMzExt375dxcXFnphVq1YpLi5OnTp1MuoHmUcAAAAf6sPyhNnZ2VqyZIlef/11T81rSYqPj1eTJk20Z88eLVmyRNdff72aNWumjz/+WA8++KD69Omjrl27SpIGDhyoTp06aeTIkXrqqadUVFSkqVOnKjs723hVPjKPAAAAvlh+2mph/vz5KikpUb9+/ZSWlubZ/v73v0uSwsPDtXr1ag0cOFAdOnTQQw89pOHDh+vNN9/0tBESEqJly5YpJCREmZmZuuOOOzRq1CivupC+kHkEAAAIAr5qXmdkZGj9+vU+22nVqpWWL19+wf1g8AgAAOCLH25bi7WtAQAA0NCReQQAAPDh1PKE9rcZjMg8AgAAwBiZRwAAAB/qQ6me+oLBI3CRHKG+V/qwe6UXh2EtLke42SokCjX7VWDFmK244jKMO5lqFlcZZ3aTxBVu9ovYWR1lFBd9yGxFkIpmvq9HeaK93wPliWZxFS2qzAJPGt6IamK2Eo3ptYj4xux7z/RahB49aRRnFRX7DpIkh+/zcFf6XmHIL0xWtwL8gMEjAACAL5bD/tnRZB4BAAAaJibMnMGEGQAAABgzyjx+/PHHtW64U6dOCjV8jgoAAKBeu4DlBI3aDEJGo7vu3bvL4XD4XBbnNKfTqc8++0xt2rS5qM4BAACgfjFODW7evFlJSUk+4yzLUufOnS+qUwAAAPUJpXrOMBo89u3bV5dccokSEhKMGu3Tp4+aNGlyMf0CAABAPWQ0eFy3bl2tGl2+fPkFdQYAAKDeCtJnFO120TNaXC6Xtm/frlatWqlp06Z29AmNhcNwsn+gCuEaHtdy+Y4xLRLuCDP7kXREhBvFKcysSLjVNNYozhVtVpz8RLpZ8e+qGLPvgePpZrd23L2OGcUNv2SbUdw7BzoYxZVu9f1IjymX4aWNvuyIUVy3hG+N4koqzK7ZtyfN7ipV5JtVMY/Zb/bXOHpvqVGc9h0yCnMdLzOKM/rZpVg3Gplal+p54IEHtHDhQkmnBo59+/bV5ZdfroyMDOXm5trdPwAAgIA7/cyj3VswqvXg8R//+Ie6desmSXrzzTe1d+9e7dq1Sw8++KB+/etf295BAACAgLP8tAWhWg8ev/76a6Wmpko69WzjLbfconbt2unOO+/U9u3bbe8gAAAA6o9aDx5TUlL0ySefyOVyacWKFbruuuskSSdOnFCI4XNdAAAAwcXhpy341HrCzNixY/Wzn/1MaWlpcjgcGjBggKRTdSA7dDB7uBwAAADBqdaDxxkzZqhz584qLCzULbfcooiIU7MvQ0JC9Mgjj9jeQQAAgIBjeUIP48HjqFGjNGzYMA0aNEg//elPz3p99OjRtnYMAAAA9Y/xM4+XXHKJnnjiCSUlJWnIkCGaP3++Dhw44M++AQAA1A/MtvYwzjxOmzZN06ZN0/79+/XGG2/otdde04MPPqjLLrtMw4YN049//GN1797dj11FgxOowrqmxckNOSN9F862qqqN2nIYtCVJCjX70TUu/h1rViC6zLD4d1mq2WfsMmtOJzpUGsU92mWFUdzI2K+N4h5L3mEUpx5mYXaad7SFUdye8mSjuJNNzArKryjsbBSXVmD28x2/86hRnA4cNgqzyivM2jNkVVfZ2h7QENT6r2iLFi10zz33aOXKlfrqq680ZcoUFRQUqH///mrVqpUmTpyonTt3+qOvAAAAgWE5/LMFoYtKwcTGxupnP/uZXnrpJX311Vd64YUXFBISory8PLv6BwAAEHCW5Z8tGF302tanhYSE6Nprr9W1115rV5MAAACoZ2o9ePzmm280bdo0rVu3TsXFxXK7vZ9rOXLkiG2dAwAAqBco1eNR68HjyJEjtXv3bo0bN04pKSlyOILzfj0AAABqr9aDx/fee08bNmxQt27d/NEfAACA+scfE1way4SZDh066OTJk/7oCwAAAOq5Wg8e582bp1//+tdav369vvnmG5WWlnptAAAADY3D8s8WjGp92zohIUGlpaXq37+/137LsuRwOORyuWzrHBo402LdpsXEbS7+7QgJMQt0+/7pd8ZEmx0zItzsmDFRRmHVCU2M4iqamhWIPtrO7DMub2b2GzG0ZZlR3O+6vWEUd0tMiVFcQ3Bd9C6juPxjrYzi1n3awSiu2ftm36Px/zIrxK6DhsW/q8yKdbsrys2Oa/PvC6AxqfXgccSIEQoLC9OSJUuYMAMAABoHZlt71HrwuGPHDn300Udq3769P/oDAABQ/zBhxqPWeftevXqpsLDQH30BAABAPVfrzOO9996r+++/X5MnT1aXLl0UFub9rFTXrl1t6xwAAEC9wG1rj1oPHm+99VZJ0p133unZ53A4mDADAADQCNR68Lh3715/9AMAAKD+IvPoUevBY6tWZmUf/GXu3Ll6+umnVVRUpG7duum5557TlVdeGdA+AQAANBZGE2beeOMNVRnW2JKk5cuX+2UVmr///e+aNGmSpk+frg8//FDdunXToEGDVFxcbPuxAAAAPCw/bUHIKPP4k5/8REVFRUpKSjJq9LbbbtO2bdvUpk2bi+rc9/3+97/X+PHjNXbsWEnSggUL9NZbb+mFF17QI488YuuxUAdMi3/bzLT4t7NJpH0Hra42i4syK+pthZmdg8Nl9pvJafiocqRh3eeyNmbnO7S1WaHrxlT8O7+y0ijuV1/cahT3+b5Uo7iED8yKfzf9zCwx4Cj+xijObXi+lmGcsQD9/gEaAqPBo2VZGjNmjCIiIowaLS83rPBfC5WVlcrPz1dOTo5nn9Pp1IABA5SXl3fO91RUVKiiosLzNcsnAgCAC0KdRw+jwePo0aNr1eiIESMUFxd3QR2qyddffy2Xy6WUlBSv/SkpKdq169zZi1mzZunRRx+1tR8AAACNmdHgcdGiRf7uh1/k5ORo0qRJnq9LS0uVkZERwB4BAIBg5LBObXa3GYxqPds6UJo3b66QkBAdPnzYa//hw4eVmnruZ3oiIiKMb7UDAADUiFI9HrVenjBQwsPD1bNnT61Zs8azz+12a82aNcrMzAxgzwAAABqPoBk8StKkSZP05z//WS+++KI+/fRTTZgwQWVlZZ7Z1wAAAA3VrFmzdMUVVyg2NlbJycm66aabVFBQ4BVTXl6u7OxsNWvWTDExMRo+fPhZd2337dunoUOHKioqSsnJyZo8ebKqTauCKMgGj7feeqtmz56tadOmqXv37tq2bZtWrFhx1iQaAACAhmb9+vXKzs7Wpk2btGrVKlVVVWngwIEqKyvzxDz44IN688039corr2j9+vU6ePCgbr75Zs/rLpdLQ4cOVWVlpTZu3KgXX3xRixcv1rRp04z7YfzM47x583TPPfcYN+wvEydO1MSJEwPdDQAA0Ig45IcJM7WMX7FihdfXixcvVnJysvLz89WnTx+VlJRo4cKFWrJkifr37y/p1KTnjh07atOmTbrqqqv0zjvv6JNPPtHq1auVkpKi7t2767HHHtOUKVM0Y8YMhYf7rvlqnHmcOnWqBg0apIMHD9byVAEAAFCT0tJSr+27NarPp6Tk1AIKiYmJkqT8/HxVVVVpwIABnpgOHTqoZcuWnprYeXl56tKli9dd20GDBqm0tFQ7d+40Oq5x5nHHjh0aP368OnfurGeffVZ33HGH6VuBc3OY/dvF4TT7t5nlNvsnoXF7LrNlVxxhYb6DDNuSZXgO1YarYxh+JpbhPyMrDcu3OqrNPuPt36aZNZhuFlaf7ak+bhR3+8uTjeIizBZwUeoBs++B2C/KfAdJCj1odmDL8I+fu9wsjhVhEHB+LBL+/TKC06dP14wZM877VrfbrQceeEA/+tGP1LlzZ0lSUVGRwsPDlZCQ4BWbkpKioqIiT8y5amaffs2E8eAxPT1db731lhYvXqz77rtPS5cu1a9//WuFhno30bVrV9MmAQAAGr3CwkKvxVVMygxmZ2drx44d2rBhgz+7dk61rvM4ZswYtWjRQoMHD9Zrr70my7LkcDg8/3WZZlgAAACChR/rPMbFxdVqZb6JEydq2bJlevfdd9WiRQvP/tTUVFVWVuro0aNe2cfv1sROTU3VBx984NXe6dnYNdXN/r5az7b+/e9/r2HDhumOO+7QZ599pr179+qLL77w/BcAAKDBsfy01aYLlqWJEydq6dKlWrt2rVq3bu31es+ePRUWFuZVE7ugoED79u3z1MTOzMzU9u3bVVxc7IlZtWqV4uLi1KlTJ6N+GGcev/jiC40ePVqff/65lixZomHDhpm+FQAAABcpOztbS5Ys0euvv67Y2FjPM4rx8fFq0qSJ4uPjNW7cOE2aNEmJiYmKi4vTvffeq8zMTF111VWSpIEDB6pTp04aOXKknnrqKRUVFWnq1KnKzs42XpXPePDYtWtXDR48WEuXLlXz5s0v4JQBAACCU31Y23r+/PmSpH79+nntX7RokcaMGSNJeuaZZ+R0OjV8+HBVVFRo0KBBmjdvnic2JCREy5Yt04QJE5SZmano6GiNHj1aM2fONO6H8eBxwYIFzLAGAAAIEMugIkdkZKTmzp2ruXPn1hjTqlUrLV++/IL7YTx4ZOAIAAAaLT9OmAk2QbU8IQAAAAKr1qV6ANsYFv21DKs/OUINinXLvPi3cWFvA854wxIMTrN/z1khZoVqQ05UmrXnMHtIusnXZv9Mrow3/NXS1iysIRi6eYJRnGnx7+jDhsW/954wijMt/u3++ohRnFxmP9/mRfvNDgv4DZlHDzKPAAAAMEbmEQAAwIf6MNu6vjAaPN58883GDb766qsX3BkAAIB6yY9rWwcbo9vW8fHxni0uLk5r1qzR1q1bPa/n5+drzZo1io+P91tHAQAAEHhGmcdFixZ5/n/KlCn62c9+pgULFigkJESS5HK5dM8999RqXUYAAICgwYQZj1pPmHnhhRf0y1/+0jNwlE5VK580aZJeeOEFWzsHAACA+qXWg8fq6mrt2rXrrP27du2S221WmgEAACCYnJ4wY/cWjGo923rs2LEaN26c9uzZoyuvvFKStHnzZj355JMaO3as7R0EAABA/VHrwePs2bOVmpqq//mf/9GhQ4ckSWlpaZo8ebIeeugh2zuIBsxhc5lRw6Ljpsd1fOfRjPM357s9d0mpUVvO5olmx6yoNoqrTo4yinOHmX0mlbFmMwMdhpei8OumRnG3fDHAKO6VNqvNDhwAltvss4soMWsv+lCVUVzIsXKzBk8axhmsrStJ7kqzAvXGP7dAoPHMo0etB49Op1MPP/ywHn74YZWWnvqDyEQZAACAxuGiioQzaAQAAI2CP55RDNLMY63vGx4+fFgjR45Uenq6QkNDFRIS4rUBAAA0OJaftiBU68zjmDFjtG/fPv3mN79RWlqaHI7grI4OAACA2qv14HHDhg1677331L17dz90BwAAoB5iwoxHrW9bZ2RkyDKcbQcAAICGpdaDxzlz5uiRRx7Rl19+6YfuAAAA1D8UCT+j1retb731Vp04cUJt27ZVVFSUwsLCvF4/cuSIbZ0DAABA/VLrweOcOXP80A00KKbFv20uDmy5zOIchkUBrGqz/jnCfP8YOWOizQ5abXYSVS3NymRZoWbXorypWVz4MbN/JlckGk6kK2xiFJZ/4odGcTPjOhrFTWv+qVGcnaq+jjQLNPzoQsvMCsU7jp0wirNchj9ApnGmAvT7AsCFq/XgcfTo0f7oBwAAAIKA0eCxtLTUUxD89KoyNaFwOAAAaHCYbe1hNHhs2rSpDh06pOTkZCUkJJyztqNlWXI4HHLZfUsDAAAgwPwxwaVBT5hZu3atEhMTPf9PYXAAAIDGyWjw2LdvX+3du1etW7dWv379/NwlAACAeihIM4V2M67z2LZtW7Vu3Vp33nmn/vrXv2r//v3+7BcAAADqIePZ1mvXrlVubq5yc3P1t7/9TZWVlWrTpo369++vrKwsZWVlKSUlxZ99BQAACAwmzHgYDx779evnuWVdXl6ujRs3egaTL774oqqqqtShQwft3LnTX30FAABAgNW6zqMkRUZGqn///rrmmmuUlZWlt99+W88//7x27dpld/8AAAACjtnWZ9Rq8FhZWalNmzZp3bp1ys3N1ebNm5WRkaE+ffroj3/8o/r27euvfiKYmK4EYbqyhM0st9lPa0h0lH0HNaxQYCWa1Ul1R5gtk3OsRbhRnMssTJWxZucRbfhI9IlUs/aqXGG+gyStPFh/V5hxuAy/Bwx/LJxllWaBLrOfR6vspFGcu9LwuAAaLOPBY//+/bV582a1bt1affv21S9+8QstWbJEaWlp/uwfAABA4PHMo4fx4PG9995TWlqa+vfvr379+qlv375q1qyZP/sGAABQL3Db+gzj+4ZHjx7Vn/70J0VFRel3v/ud0tPT1aVLF02cOFH/+Mc/9NVXX/mznwAAAKgHjDOP0dHRGjx4sAYPHixJOnbsmDZs2KB169bpqaee0ogRI3TppZdqx44dfussAABAQHDb2uOCZyxER0crMTFRiYmJatq0qUJDQ/Xpp3X/EDoAAADqjnHm0e12a+vWrcrNzdW6dev0/vvvq6ysTD/4wQ+UlZWluXPnKisry599BQAACAwyjx7Gg8eEhASVlZUpNTVVWVlZeuaZZ9SvXz+1bdvWn/0DAABAPWI8eHz66aeVlZWldu3a+bM/AAAA9Q6zrc8wHjz+4he/8Gc/zuvLL7/UY489prVr16qoqEjp6em644479Otf/1rh4YbVjVF3TIt/21xM3BFiVjjbNM60sLejWaLvoAizItdlbROM4kwLSYcfM/uMq6LNPpOIo2a/6Syn2WcXXmIUJrfhj/nB/QbXQpK7q9nn4jR8LHxLRZXPmLBSs7bi9vpuS5IcldVGcdax42ZxLpdRnO0/3wCCzgUtT1jXdu3aJbfbreeff16XXHKJduzYofHjx6usrEyzZ88OdPcAAEBDxzOPHkExePxuiSBJatOmjQoKCjR//nwGjwAAwP8YPHoExeDxXEpKSpSYeP5bVBUVFaqoqPB8XVpa6u9uAQAANGgXXOcxkHbv3q3nnnvO53OYs2bNUnx8vGfLyMioox4CAICG5PSEGbu3YBTQweMjjzwih8Nx3m3Xrl1e7zlw4IAGDx6sW265RePHjz9v+zk5OSopKfFshYWF/jwdAACABi+gt60feughjRkz5rwxbdq08fz/wYMHlZWVpauvvlp/+tOffLYfERGhiIiIi+0mAABo7Hjm0SOgg8ekpCQlJSUZxR44cEBZWVnq2bOnFi1aJKczKO+4AwAABLWgGIEdOHBA/fr1U8uWLTV79mx99dVXKioqUlFRUaC7BgAAGoH68Mzju+++qxtvvFHp6elyOBx67bXXvF4fM2bMWY//fbdajSQdOXJEI0aMUFxcnBISEjRu3DgdP25WD/a0oJhtvWrVKu3evVu7d+9WixYtvF6zrCDN+TZkNhf/NmVcJDzM8NveNC7SdwXr8ox4o6aqm5gV1z7R3Oyziz5sdi2ii8wKRIdWGP68ucziKuPNrlmTI2afS1GS2efybrnZcftFmp3Hk/uv9xmT8JlZW03+bVY53VF2wijOZfhHwRFqVsjeqjYrYg7AfmVlZerWrZvuvPNO3XzzzeeMGTx4sBYtWuT5+vuP740YMUKHDh3SqlWrVFVVpbFjx+quu+7SkiVLjPsRFIPHMWPG+Hw2EgAAwG/8+Mzj90sJ1jRnY8iQIRoyZMh5m4yIiFBqauo5X/v000+1YsUKbdmyRb169ZIkPffcc7r++us1e/ZspaenG3U7KG5bAwAABJTlp01SRkaGV2nBWbNmXXA3c3NzlZycrPbt22vChAn65ptvPK/l5eUpISHBM3CUpAEDBsjpdGrz5s3GxwiKzCMAAEBDVVhYqLi4OM/XF1opZvDgwbr55pvVunVr7dmzR7/61a80ZMgQ5eXlKSQkREVFRUpOTvZ6T2hoqBITE2s1j4TBIwAAgA+O/2x2tylJcXFxXoPHC3Xbbbd5/r9Lly7q2rWr2rZtq9zcXF177bUX3f5p3LYGAABogNq0aaPmzZtr9+7dkqTU1FQVFxd7xVRXV+vIkSM1Pid5LgweAQAAfPHjM4/+sn//fn3zzTdKS0uTJGVmZuro0aPKz8/3xKxdu1Zut1u9e/c2bpfb1gAAAEHg+PHjniyiJO3du1fbtm1TYmKiEhMT9eijj2r48OFKTU3Vnj179PDDD+uSSy7RoEGDJEkdO3bU4MGDNX78eC1YsEBVVVWaOHGibrvtNuOZ1hKZRwAAAJ/qQ5HwrVu3qkePHurRo4ckadKkSerRo4emTZumkJAQffzxx/rxj3+sdu3aady4cerZs6fee+89rwk4L730kjp06KBrr71W119/va655hqjJZ+/i8wj6j1nuO8i3KcCDR9lDjX7tnc0TTCKq06M9hnjDjHsm+EvkoTdZoWandVmDTorzYqEhx8+ZhTnjok0a6/ErFh3RTOzmYdNt5td24U9+hjFNUtbYRT36TuX+IxJP1Bh1JbDbVhkv+ykWXuGxb/dFeVmxzUt7m+6WAAAY/369Tvv4igrV6702UZiYmKtCoKfC4NHAAAAX/xYJDzYMHgEAAAwEaSDPbvxzCMAAACMkXkEAADw4UImuJi0GYzIPAIAAMAYmUcAAABfmDDjQeYRAAAAxsg8AgAA+MAzj2eQeQQAAIAxMo8IGEeI2eoiCjH7N44zNsasvegoozBXM7P2Kpv6XgEn5ITZCi4R35r9MzSs1GyFmZDjZquGOMrN2tOx40ZhzlLDOMNr4agyW62kKtr3aj+StOn9jkZx/90xySiu6We++xd21GyFGVWbfa+4j5eZtWf3Si+sHIPGimcePcg8AgAAwBiZRwAAAB945vEMBo8AAAC+cNvag9vWAAAAMEbmEQAAwBcyjx5kHgEAAGCMzCMAAIAPTJg5g8wjAAAAjJF5hDmH2b81TIt/O5wOozjj4t9hYUZhVoTvot6S5I4w+/EIPV7tMybs25NGbanKrEC0w7CQtEqPGYVZ5WYFrB3hZp+xTK+ZIWel789Ykpp8bVbsPPaLCKM412dmRcITdx31GeMsMSzqfdLwe8WweL77hFmheNOfb4qEo9HimUcPMo8AAAAwRuYRAADAB4dlyWHZmyq0u726wuARAADAF25be3DbGgAAAMbIPAIAAPhAqZ4zyDwCAADAGJlHAAAAX3jm0YPMIwAAAIyReUTghBp++xkWHZdh8W+FmBUnDyk1K5xt8k8wR5lhoebjZoWkrSqzYtimxb/lMiz87DIsYu40/Hep4feAaVH0iBNm5xsf1sysvSNm1835banPGOvIUaO2rCqzgujuykqjOFOmRfstw/r0QEPDM49nkHkEAACAMTKPAAAAvvDMoweDRwAAAB+4bX0Gt60BAABgjMwjAACAL9y29iDzCAAAAGNkHgEAAAwE6zOKdiPzCAAAAGNkHiE5zP4N4Qw3K8JtGRaSdjZpYhRn7NhxozCHK8os7uTJi+mNF/Ni3WafnWVaINrw2trN9HwdEYb/jA8LM4sz/Fya/LvEKM5xwux7wPrWd3umPxemxb8dhsXzrWqzAvCm/QMaLcs6tdndZhAi8wgAAABjZB4BAAB8oM7jGUGXeayoqFD37t3lcDi0bdu2QHcHAAA0BpaftiAUdIPHhx9+WOnp6YHuBgAAQKMUVLet3377bb3zzjv65z//qbfffttnfEVFhSoqzjy4X1pa6s/uAQCABsrhPrXZ3WYwCprM4+HDhzV+/Hj97//+r6KizGbLzpo1S/Hx8Z4tIyPDz70EAABo2IJi8GhZlsaMGaO7775bvXr1Mn5fTk6OSkpKPFthYaEfewkAABosnnn0COjg8ZFHHpHD4TjvtmvXLj333HM6duyYcnJyatV+RESE4uLivDYAAABcuIA+8/jQQw9pzJgx541p06aN1q5dq7y8PEVERHi91qtXL40YMUIvvviiH3sJAAAaO0r1nBHQwWNSUpKSkpJ8xj377LP67W9/6/n64MGDGjRokP7+97+rd+/e/uxiUHOEGq7KYcrpMAtrEm3vcauqzOJCDb+dDVeOcRuuWCOX7yeeTVcNcYaZnYPpaiCWu9ooznS1EtPzCIk3y/Jb1Wb907dHjcIcEWarIDmchquzfPOtUZwJt40rFknmK8cAgN2C4pnHli1bqnPnzp6tXbt2kqS2bduqRYsWAe4dAABo8E4vT2j3VgvvvvuubrzxRqWnp8vhcOi11177XhctTZs2TWlpaWrSpIkGDBigzz//3CvmyJEjGjFihOLi4pSQkKBx48bp+HHDZMl/BMXgEQAAIJBO37a2e6uNsrIydevWTXPnzj3n60899ZSeffZZLViwQJs3b1Z0dLQGDRqk8vJyT8yIESO0c+dOrVq1SsuWLdO7776ru+66q1b9CKo6j6f98Ic/lBWki4kDAAB81/frUEdERJw1z0OShgwZoiFDhpyzDcuyNGfOHE2dOlXDhg2TJP3lL39RSkqKXnvtNd1222369NNPtWLFCm3ZssVTvea5557T9ddfr9mzZxsvwkLmEQAAwBc/lurJyMjwqks9a9asWndv7969Kioq0oABAzz74uPj1bt3b+Xl5UmS8vLylJCQ4FX2cMCAAXI6ndq8ebPxsYIy8wgAANBQFBYWepUTPFfW0ZeioiJJUkpKitf+lJQUz2tFRUVKTk72ej00NFSJiYmeGBMMHgEAAHzwZ6meYKtFzW1rAACAIJeamirp1HLO33X48GHPa6mpqSouLvZ6vbq6WkeOHPHEmGDwCAAA4Es9KNVzPq1bt1ZqaqrWrFnj2VdaWqrNmzcrMzNTkpSZmamjR48qPz/fE7N27Vq53e5a1c3mtnV94jAby5sWdDZmGRYbdht+kxsWfrYMi47rpGGRcEPGBbarDAtY28i0CLcxw+8pq9rwMzZsz328zKw9Q85Is+d/jIuOf/2NUZhpYW/L9GfDhOFnbPxzC6DBOH78uHbv3u35eu/evdq2bZsSExPVsmVLPfDAA/rtb3+rSy+9VK1bt9ZvfvMbpaen66abbpIkdezYUYMHD9b48eO1YMECVVVVaeLEibrtttuMZ1pLDB4BAAB8qg/LE27dulVZWVmerydNmiRJGj16tBYvXqyHH35YZWVluuuuu3T06FFdc801WrFihSIjIz3veemllzRx4kRde+21cjqdGj58uJ599tla9YPBIwAAgC/fKa1ja5u10K9fv/PWuXY4HJo5c6ZmzpxZY0xiYqKWLFlSuwN/D888AgAAwBiZRwAAAB/qw23r+oLMIwAAAIyReQQAAPDFbZlXHalNm0GIzCMAAACMkXkEAADwpR7Mtq4vGDzWJ4ZFfy2zGtfGnOHhZoEhNieqK80KU7vLK4ziTIt/2y4QxZrtLiRtWqDetLC7IdOC98bFustOmB3X8Dwo/g0AZ2PwCAAA4INDfphtbW9zdYbBIwAAgC82r0XtaTMIMWEGAAAAxsg8AgAA+ECR8DPIPAIAAMAYmUcAAABfKNXjQeYRAAAAxsg8AgAA+OCwLDlsnh1td3t1hcFjMLK7iLBh8W+rwqxYtwwLP5uyqs2KidfrIsx29y1AhaRNi2Y7ww2Lf1dWGsWZFvU2LTpue0F5CnsDaEQYPAIAAPji/s9md5tBiMEjAACAD9y2PoMJMwAAADBG5hEAAMAXSvV4kHkEAACAMTKPAAAAvljWqc3uNoMQmUcAAAAYI/MIAADgg8M6tdndZjAi8wgAAABjZB4vkiM0zCjO9hUtDBivtmG6cowh01VDjJmuzlKfBWoFkgCtumO8KpBpe8Y/P2ZxAVuJBkDw4plHjwbwVxkAAAB1hcwjAACADw73qc3uNoMRg0cAAABfuG3twW1rAAAAGCPzCAAA4AvLE3qQeQQAAIAxMo8AAAA+OCxLDpufUbS7vbpC5hEAAADGyDxeJFuLIdtcDNvuQs0BK9YdqALbDUGAPju7i2vbXdSb4t8Aao3Z1h5kHgEAAGCMzCMAAIAvliS7b+YEZ+KRwSMAAIAvTJg5I6huW7/11lvq3bu3mjRpoqZNm+qmm24KdJcAAAAalaDJPP7zn//U+PHj9cQTT6h///6qrq7Wjh07At0tAADQGFjyw4QZe5urK0ExeKyurtb999+vp59+WuPGjfPs79SpUwB7BQAA0PgExW3rDz/8UAcOHJDT6VSPHj2UlpamIUOG+Mw8VlRUqLS01GsDAACotdOleuzeglBQDB6/+OILSdKMGTM0depULVu2TE2bNlW/fv105MiRGt83a9YsxcfHe7aMjIy66jIAAECDFNDB4yOPPCKHw3HebdeuXXK7T82N//Wvf63hw4erZ8+eWrRokRwOh1555ZUa28/JyVFJSYlnKywsrKtTuzCW294tUP0DbGa5LaMNAPzG7actCAX0mceHHnpIY8aMOW9MmzZtdOjQIUnezzhGRESoTZs22rdvX43vjYiIUEREhC19BQAAQIAHj0lJSUpKSvIZ17NnT0VERKigoEDXXHONJKmqqkpffvmlWrVq5e9uAgCARo46j2cExTOPcXFxuvvuuzV9+nS98847Kigo0IQJEyRJt9xyS4B7BwAAGrx6MGFmxowZZz3e16FDB8/r5eXlys7OVrNmzRQTE6Phw4fr8OHDdn8SwVGqR5KefvpphYaGauTIkTp58qR69+6ttWvXqmnTpoHuGgAAQJ247LLLtHr1as/XoaFnhnIPPvig3nrrLb3yyiuKj4/XxIkTdfPNN+v999+3tQ9BM3gMCwvT7NmzNXv27EB3BQAANDb+KK1zAe2FhoYqNTX1rP0lJSVauHChlixZov79+0uSFi1apI4dO2rTpk266qqrLrq7pwXFbWsAAICG6vs1qSsqKmqM/fzzz5Wenq42bdpoxIgRnonD+fn5qqqq0oABAzyxHTp0UMuWLZWXl2drfxk8AgAA+OLHZx4zMjK86lLPmjXrnF3o3bu3Fi9erBUrVmj+/Pnau3ev/uu//kvHjh1TUVGRwsPDlZCQ4PWelJQUFRUV2fpRBM1tawAAgIaosLBQcXFxnq9rKjM4ZMgQz/937dpVvXv3VqtWrfR///d/atKkid/7eRqZRwD1HwXqAQSaH4uEx8XFeW2mNaoTEhLUrl077d69W6mpqaqsrNTRo0e9Yg4fPnzOZyQvBoNHAACAIHT8+HHt2bNHaWlp6tmzp8LCwrRmzRrP6wUFBdq3b58yMzNtPS63rQEAAHyoD0XCf/nLX+rGG29Uq1atdPDgQU2fPl0hISG6/fbbFR8fr3HjxmnSpElKTExUXFyc7r33XmVmZto601pi8AgAAOBbPSjVs3//ft1+++365ptvlJSUpGuuuUabNm3yrNb3zDPPyOl0avjw4aqoqNCgQYM0b948e/ssBo8AAABB4eWXXz7v65GRkZo7d67mzp3r134weAQAAPDFbUkOmzOPbta2BgAAQANH5hEAAMCXevDMY31B5hEAAADGyDwCAAD45IfMo8g8AgAAoIEj8wgAAOALzzx6MHgEAADwxW3J9tvMlOoBAABAQ0fmEQAAwBfLfWqzu80gROYRAAAAxsg8AgAA+MKEGQ8yjwAAADBG5hEAAMAXZlt7kHkEAACAMTKPAAAAvvDMoweDRwAAAF8s+WHwaG9zdYXb1gAAADBG5hEAAMAXblt7kHkEAACAMTKPAAAAvrjdkmxeTtDN8oQAAABo4Mg8AgAA+MIzjx5kHgEAAGCMzCMAAIAvZB49GDwCAAD4wtrWHty2BgAAgDEyjwAAAD5YlluWZW9pHbvbqytkHgEAAGCMzCMAAIAvlmX/M4pBOmGGzCMAAACMkXkEAADwxfLDbGsyjwAAAGjoyDwCAAD44nZLDptnRwfpbGsGjwAAAL5w29qD29YAAAAwRuYRAADAB8vtlmXzbWuKhAMAAKDBI/MIAADgC888egRN5vGzzz7TsGHD1Lx5c8XFxemaa67RunXrAt0tAACARiVoBo833HCDqqurtXbtWuXn56tbt2664YYbVFRUFOiuAQCAhs5t+WcLQkExePz666/1+eef65FHHlHXrl116aWX6sknn9SJEye0Y8eOQHcPAACg0QiKZx6bNWum9u3b6y9/+Ysuv/xyRURE6Pnnn1dycrJ69uxZ4/sqKipUUVHh+bq0tLQuugsAABoay5Jkd5Hw4Mw8BsXg0eFwaPXq1brpppsUGxsrp9Op5ORkrVixQk2bNq3xfbNmzdKjjz5ahz0FAABo2AJ62/qRRx6Rw+E477Zr1y5ZlqXs7GwlJyfrvffe0wcffKCbbrpJN954ow4dOlRj+zk5OSopKfFshYWFdXh2AACgobDcll+2YOSwrMDlTL/66it98803541p06aN3nvvPQ0cOFDffvut4uLiPK9deumlGjdunB555BGj45WWlio+Pl79NEyhjrCL6jsAAKgb1VaVcvW6SkpKvMYBdeH02CEr5Gbbxw7VVpXWuV4NyHldjIDetk5KSlJSUpLPuBMnTkiSnE7vRKnT6ZTbHZzV2QEAAIJRUMy2zszMVNOmTTV69Gj961//0meffabJkydr7969Gjp0aKC7BwAAGrj6ctt67ty5+uEPf6jIyEj17t1bH3zwgR/O9vyCYvDYvHlzrVixQsePH1f//v3Vq1cvbdiwQa+//rq6desW6O4BAAD43d///ndNmjRJ06dP14cffqhu3bpp0KBBKi4urtN+BPSZx7rGM48AAASf+vDMoz/GDrU9r969e+uKK67QH//4R0mS2+1WRkaG7r33XuP5H3YIilI9djk9Tq5Wle3LUwIAAP+oVpWkM3/HA9YHmw9/+ry+X4c6IiJCERERXvsqKyuVn5+vnJwczz6n06kBAwYoLy/P3o750KgGj8eOHZMkbdDyAPcEAADU1rFjxxQfH1+nxwwPD1dqaqo2FPln7BATE6OMjAyvfdOnT9eMGTO89n399ddyuVxKSUnx2p+SkqJdu3b5pW81aVSDx/T0dBUWFio2NlYOhyMgfSgtLVVGRoYKCwuDalq+HRrzuUuN+/wb87lLjfv8OffGee6SvedvWZaOHTum9PR0m3pnLjIyUnv37lVlZaVf2rcs66wxyfezjvVNoxo8Op1OtWjRItDdkCTFxcU1yl8mUuM+d6lxn39jPnepcZ8/5944z12y7/zrOuP4XZGRkYqMjAzY8aVTk4dDQkJ0+PBhr/2HDx9WampqnfYlKGZbAwAANGbh4eHq2bOn1qxZ49nndru1Zs0aZWZm1mlfGlXmEQAAIFhNmjRJo0ePVq9evXTllVdqzpw5Kisr09ixY+u0Hwwe61hERISmT59e759n8IfGfO5S4z7/xnzuUuM+f869cZ67xPn7w6233qqvvvpK06ZNU1FRkbp3764VK1acNYnG3xpVnUcAAABcHJ55BAAAgDEGjwAAADDG4BEAAADGGDwCAADAGINHmz3++OO6+uqrFRUVpYSEhHPG7Nu3T0OHDlVUVJSSk5M1efJkVVdXn7fdI0eOaMSIEYqLi1NCQoLGjRun48eP++EM7JObmyuHw3HObcuWLTW+r1+/fmfF33333XXYc3v88Ic/POs8nnzyyfO+p7y8XNnZ2WrWrJliYmI0fPjwswrCBoMvv/xS48aNU+vWrdWkSRO1bdtW06dP97lCQzBf+7lz5+qHP/yhIiMj1bt3b33wwQfnjX/llVfUoUMHRUZGqkuXLlq+PPiWTZ01a5auuOIKxcbGKjk5WTfddJMKCgrO+57FixefdY0DXXz5Qs2YMeOsc+nQocN539MQrrt07t9vDodD2dnZ54xvSNcdDB5tV1lZqVtuuUUTJkw45+sul0tDhw5VZWWlNm7cqBdffFGLFy/WtGnTztvuiBEjtHPnTq1atUrLli3Tu+++q7vuussfp2Cbq6++WocOHfLa/vu//1utW7dWr169zvve8ePHe73vqaeeqqNe22vmzJle53HvvfeeN/7BBx/Um2++qVdeeUXr16/XwYMHdfPNN9dRb+2za9cuud1uPf/889q5c6eeeeYZLViwQL/61a98vjcYr/3f//53TZo0SdOnT9eHH36obt26adCgQSouLj5n/MaNG3X77bdr3Lhx+uijj3TTTTfppptu0o4dO+q45xdn/fr1ys7O1qZNm7Rq1SpVVVVp4MCBKisrO+/74uLivK7xv//97zrqsf0uu+wyr3PZsGFDjbEN5bpL0pYtW7zOe9WqVZKkW265pcb3NKTr3uhZ8ItFixZZ8fHxZ+1fvny55XQ6raKiIs+++fPnW3FxcVZFRcU52/rkk08sSdaWLVs8+95++23L4XBYBw4csL3v/lJZWWklJSVZM2fOPG9c3759rfvvv79uOuVHrVq1sp555hnj+KNHj1phYWHWK6+84tn36aefWpKsvLw8P/Swbj311FNW69atzxsTrNf+yiuvtLKzsz1fu1wuKz093Zo1a9Y543/2s59ZQ4cO9drXu3dv6xe/+IVf++lvxcXFliRr/fr1NcbU9LsxGE2fPt3q1q2bcXxDve6WZVn333+/1bZtW8vtdp/z9YZ03WFZZB7rWF5enrp06eJV0HPQoEEqLS3Vzp07a3xPQkKCV7ZuwIABcjqd2rx5s9/7bJc33nhD33zzjVEl/JdeeknNmzdX586dlZOToxMnTtRBD+335JNPqlmzZurRo4eefvrp8z6ekJ+fr6qqKg0YMMCzr0OHDmrZsqXy8vLqort+VVJSosTERJ9xwXbtKysrlZ+f73XdnE6nBgwYUON1y8vL84qXTv0eCPbrXFJSIkk+r/Px48fVqlUrZWRkaNiwYTX+7gsGn3/+udLT09WmTRuNGDFC+/btqzG2oV73yspK/fWvf9Wdd94ph8NRY1xDuu6NHSvM1LGioqKzKsGf/rqoqKjG9yQnJ3vtCw0NVWJiYo3vqY8WLlyoQYMGqUWLFueN+/nPf65WrVopPT1dH3/8saZMmaKCggK9+uqrddRTe9x33326/PLLlZiYqI0bNyonJ0eHDh3S73//+3PGFxUVKTw8/KxnZVNSUoLqOp/L7t279dxzz2n27NnnjQvGa//111/L5XKd8+d6165d53xPTb8Hgvk6u91uPfDAA/rRj36kzp071xjXvn17vfDCC+ratatKSko0e/ZsXX311dq5c6fP3w31Te/evbV48WK1b99ehw4d0qOPPqr/+q//0o4dOxQbG3tWfEO87pL02muv6ejRoxozZkyNMQ3pukPctjYxZcoUS9J5t08//dTrPTWl6MePH28NHDjQa19ZWZklyVq+fPk5j//4449b7dq1O2t/UlKSNW/evAs/sQt0IZ9HYWGh5XQ6rX/84x+1Pt6aNWssSdbu3bvtOoULdiHnftrChQut0NBQq7y8/Jyvv/TSS1Z4ePhZ+6+44grr4YcftvU8LtSFnP/+/futtm3bWuPGjav18erTta/JgQMHLEnWxo0bvfZPnjzZuvLKK8/5nrCwMGvJkiVe++bOnWslJyf7rZ/+dvfdd1utWrWyCgsLa/W+yspKq23bttbUqVP91LO68+2331pxcXHW//t//++crzfE625ZljVw4EDrhhtuqNV7GtJ1b4zIPBp46KGHzvsvKklq06aNUVupqalnzcI8PZs2NTW1xvd8/8H76upqHTlypMb3+NOFfB6LFi1Ss2bN9OMf/7jWx+vdu7ekU9mrtm3b1vr9drqY74XevXururpaX375pdq3b3/W66mpqaqsrNTRo0e9so+HDx8OyHU+l9qe/8GDB5WVlaWrr75af/rTn2p9vPp07WvSvHlzhYSEnDUr/nzXLTU1tVbx9d3EiRM9E/lqm0UKCwtTjx49tHv3bj/1ru4kJCSoXbt2NZ5LQ7vukvTvf/9bq1evrvXdgYZ03RsjBo8GkpKSlJSUZEtbmZmZevzxx1VcXOy5Fb1q1SrFxcWpU6dONb7n6NGjys/PV8+ePSVJa9euldvt9vxxrUu1/Twsy9KiRYs0atQohYWF1fp427ZtkySlpaXV+r12u5jvhW3btsnpdJ71CMJpPXv2VFhYmNasWaPhw4dLkgoKCrRv3z5lZmZecJ/tVJvzP3DggLKystSzZ08tWrRITmftH7GuT9e+JuHh4erZs6fWrFmjm266SdKpW7hr1qzRxIkTz/mezMxMrVmzRg888IBn36pVq+rNdTZlWZbuvfdeLV26VLm5uWrdunWt23C5XNq+fbuuv/56P/Swbh0/flx79uzRyJEjz/l6Q7nu37Vo0SIlJydr6NChtXpfQ7rujVKgU58Nzb///W/ro48+sh599FErJibG+uijj6yPPvrIOnbsmGVZllVdXW117tzZGjhwoLVt2zZrxYoVVlJSkpWTk+NpY/PmzVb79u2t/fv3e/YNHjzY6tGjh7V582Zrw4YN1qWXXmrdfvvtdX5+F2L16tU13s7dv3+/1b59e2vz5s2WZVnW7t27rZkzZ1pbt2619u7da73++utWmzZtrD59+tR1ty/Kxo0brWeeecbatm2btWfPHuuvf/2rlZSUZI0aNcoT8/1zt6xTt/5atmxprV271tq6dauVmZlpZWZmBuIULsr+/futSy65xLr22mut/fv3W4cOHfJs341pKNf+5ZdftiIiIqzFixdbn3zyiXXXXXdZCQkJnqoKI0eOtB555BFP/Pvvv2+FhoZas2fPtj799FNr+vTpVlhYmLV9+/ZAncIFmTBhghUfH2/l5uZ6XeMTJ054Yr5/7o8++qi1cuVKa8+ePVZ+fr512223WZGRkdbOnTsDcQoX5aGHHrJyc3OtvXv3Wu+//741YMAAq3nz5lZxcbFlWQ33up/mcrmsli1bWlOmTDnrtYZ83WFZDB5tNnr06HM+B7Zu3TpPzJdffmkNGTLEatKkidW8eXProYcesqqqqjyvr1u3zpJk7d2717Pvm2++sW6//XYrJibGiouLs8aOHesZkNZ3t99+u3X11Vef87W9e/d6fT779u2z+vTpYyUmJloRERHWJZdcYk2ePNkqKSmpwx5fvPz8fKt3795WfHy8FRkZaXXs2NF64oknvJ53/P65W5ZlnTx50rrnnnuspk2bWlFRUdZPfvITrwFXsFi0aFGNz0Se1tCu/XPPPWe1bNnSCg8Pt6688kpr06ZNntf69u1rjR492iv+//7v/6x27dpZ4eHh1mWXXWa99dZbddzji1fTNV60aJEn5vvn/sADD3g+p5SUFOv666+3Pvzww7rvvA1uvfVWKy0tzQoPD7d+8IMfWLfeeqvX87kN9bqftnLlSkuSVVBQcNZrDfm6w7IclmVZdZjoBAAAQBCjziMAAACMMXgEAACAMQaPAAAAMMbgEQAAAMYYPAIAAMAYg0cAAAAYY/AIAAAAYwweAQAAYIzBIwBb5ebmyuFw6OjRoxfVzpgxYzxrRdtpxowZcjgccjgcmjNnju3tn8+YMWM8x37ttdfq9NgAYBcGjwDOacGCBYqNjVV1dbVn3/HjxxUWFqZ+/fp5xZ4eMO7Zs0dXX321Dh06pPj4eL/2b/78+UpISFBhYaHX/nvvvVft2rXTiRMnanzvZZddpkOHDumuu+6ypS8vvviirrnmGp9xf/jDH3To0CFbjgkAgcLgEcA5ZWVl6fjx49q6datn33vvvafU1FRt3rxZ5eXlnv3r1q1Ty5Yt1bZtW4WHhys1NVUOh8Ov/bv77rt15ZVXaty4cZ59a9as0fz587V48WJFRUXV+N7Q0FClpqaeN6Y2Xn/9df34xz/2GRcfH6/U1FRbjgkAgcLgEcA5tW/fXmlpacrNzfXsy83N1bBhw9S6dWtt2rTJa39WVpbn/79723rx4sVKSEjQypUr1bFjR8XExGjw4MFeGTiXy6VJkyYpISFBzZo108MPPyzLss7bP4fDoYULF2rz5s1asGCBSktLdeedd2rSpEm6+uqra32+DodDzz//vG644QZFRUWpY8eOysvL0+7du9WvXz9FR0fr6quv1p49e7zeV15ernfeecczeJw3b54uvfRSRUZGKiUlRT/96U9r3RcAqM8YPAKoUVZWltatW+f5et26derXr5/69u3r2X/y5Elt3rzZM3g8lxMnTmj27Nn63//9X7377rvat2+ffvnLX3pe/5//+R8tXrxYL7zwgjZs2KAjR45o6dKlPvuXkZGhOXPmaPLkybrjjjsUExOjxx577ILP97HHHtOoUaO0bds2dejQQT//+c/1i1/8Qjk5Odq6dassy9LEiRO93rNmzRr94Ac/UIcOHbR161bdd999mjlzpgoKCrRixQr16dPngvsDAPVRaKA7AKD+ysrK0gMPPKDq6mqdPHlSH330kfr27auqqiotWLBAkpSXl6eKiorzDh5Px7dt21aSNHHiRM2cOdPz+pw5c5STk6Obb75Z0qnnLVeuXGnUx7Fjx+pPf/qT3nzzTW3evFkREREXeroaO3asfvazn0mSpkyZoszMTP3mN7/RoEGDJEn333+/xo4d6/We796y3rdvn6Kjo3XDDTcoNjZWrVq1Uo8ePS64PwBQH5F5BFCjfv36qaysTFu2bNF7772ndu3aKSkpSX379vU895ibm6s2bdqoZcuWNbYTFRXlGThKUlpamoqLiyVJJSUlOnTokHr37u15PTQ0VL169TLq47/+9S99+OGHioqK0nvvvXeBZ3pK165dPf+fkpIiSerSpYvXvvLycpWWlkqSLMvSm2++6Rk8XnfddWrVqpXatGmjkSNH6qWXXjrvxB0ACEYMHgHU6JJLLlGLFi20bt06rVu3Tn379pUkpaenKyMjQxs3btS6devUv3//87YTFhbm9bXD4fD5TKOJyspKjRo1SiNGjNC8efM0depUFRQUXHB73+3n6Qk/59rndrslSR988IGqq6s9z1jGxsbqww8/1N/+9jelpaVp2rRp6tat20WXLQKA+oTBI4DzysrKUm5urnJzc71K9PTp00dvv/22Pvjgg/PesvYlPj5eaWlp2rx5s2dfdXW18vPzfb535syZOnLkiJ555hmNHj1a1113ncaOHesZ3Pnb66+/rqFDhyokJMSzLzQ0VAMGDNBTTz2ljz/+WF9++aXWrl1bJ/0BgLrA4BHAeWVlZWnDhg3atm2bJ/MoSX379tXzzz+vysrKixo8SqeeJXzyySf12muvadeuXbrnnnt8Zuu2bNmi3/3ud1q4cKGnpuTzzz+vgoICPfPMMxfVH1NvvPGGV4meZcuW6dlnn9W2bdv073//W3/5y1/kdrvVvn37OukPANQFJswAOK+srCydPHlSHTp08DwHKJ0aPB47dsxT0udiPPTQQzp06JBGjx4tp9OpO++8Uz/5yU9UUlJyzviKigqNHj1aY8eO1cCBAz3709LS9Nxzz2ncuHG64YYb/Dpo27Nnj3bv3u2ZTCNJCQkJevXVVzVjxgyVl5fr0ksv1d/+9jdddtllfusHANQ1h2XHg0cAECRmzJih1157Tdu2bbuodn7/+99r9erVWr58ea3f63A4tHTpUr8svwgA/sZtawCNzvbt2xUTE6N58+ZdcBstWrRQTk5Ord5z9913KyYm5oKPCQD1AZlHAI3KkSNHdOTIEUlSUlKS39fg/q7i4mJPmZ+0tDRFR0fX2bEBwC4MHgEAAGCM29YAAAAwxuARAAAAxhg8AgAAwBiDRwAAABhj8AgAAABjDB4BAABgjMEjAAAAjDF4BAAAgLH/DyBsfvi/OxvsAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 800x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist2d(df['Wx'], df['Wy'], bins=(50, 50), vmax=400)\n",
+    "plt.colorbar()\n",
+    "plt.xlabel('Wind X [m/s]')\n",
+    "plt.ylabel('Wind Y [m/s]')\n",
+    "ax = plt.gca()\n",
+    "ax.axis('tight')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "_8im1ttOWlRB"
+   },
+   "source": [
+    "#### Time"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "7YE21HKK40zQ"
+   },
+   "source": [
+    "Similarly, the `Date Time` column is very useful, but not in this string form. Start by converting it to seconds:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:00.200710Z",
+     "iopub.status.busy": "2023-07-27T04:27:00.200238Z",
+     "iopub.status.idle": "2023-07-27T04:27:00.312472Z",
+     "shell.execute_reply": "2023-07-27T04:27:00.311903Z"
+    },
+    "id": "LIFf-VjMfnh3"
+   },
+   "outputs": [],
+   "source": [
+    "timestamp_s = date_time.map(pd.Timestamp.timestamp)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "EC_pnM1D5Sgc"
+   },
+   "source": [
+    "Similar to the wind direction, the time in seconds is not a useful model input. Being weather data, it has clear daily and yearly periodicity. There are many ways you could deal with periodicity.\n",
+    "\n",
+    "You can get usable signals by using sine and cosine transforms to clear \"Time of day\" and \"Time of year\" signals:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:00.316130Z",
+     "iopub.status.busy": "2023-07-27T04:27:00.315596Z",
+     "iopub.status.idle": "2023-07-27T04:27:00.326661Z",
+     "shell.execute_reply": "2023-07-27T04:27:00.325967Z"
+    },
+    "id": "MBfX6CDwax73"
+   },
+   "outputs": [],
+   "source": [
+    "day = 24*60*60\n",
+    "year = (365.2425)*day\n",
+    "\n",
+    "df['Day sin'] = np.sin(timestamp_s * (2 * np.pi / day))\n",
+    "df['Day cos'] = np.cos(timestamp_s * (2 * np.pi / day))\n",
+    "df['Year sin'] = np.sin(timestamp_s * (2 * np.pi / year))\n",
+    "df['Year cos'] = np.cos(timestamp_s * (2 * np.pi / year))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:00.329998Z",
+     "iopub.status.busy": "2023-07-27T04:27:00.329549Z",
+     "iopub.status.idle": "2023-07-27T04:27:00.525240Z",
+     "shell.execute_reply": "2023-07-27T04:27:00.524578Z"
+    },
+    "id": "mXBbTJZfuuTC"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'Time of day signal')"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(np.array(df['Day sin'])[:25])\n",
+    "plt.plot(np.array(df['Day cos'])[:25])\n",
+    "plt.xlabel('Time [h]')\n",
+    "plt.title('Time of day signal')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "HiurzTGQgf_D"
+   },
+   "source": [
+    "This gives the model access to the most important frequency features. In this case you knew ahead of time which frequencies were important. \n",
+    "\n",
+    "If you don't have that information, you can determine which frequencies are important by extracting features with <a href=\"https://en.wikipedia.org/wiki/Fast_Fourier_transform\" class=\"external\">Fast Fourier Transform</a>. To check the assumptions, here is the `tf.signal.rfft` of the temperature over time. Note the obvious peaks at frequencies near `1/year` and `1/day`:\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:00.528697Z",
+     "iopub.status.busy": "2023-07-27T04:27:00.528244Z",
+     "iopub.status.idle": "2023-07-27T04:27:04.280344Z",
+     "shell.execute_reply": "2023-07-27T04:27:04.279700Z"
+    },
+    "id": "EN4U1fcMiTYs"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fft = tf.signal.rfft(df['T (degC)'])\n",
+    "f_per_dataset = np.arange(0, len(fft))\n",
+    "\n",
+    "n_samples_h = len(df['T (degC)'])\n",
+    "hours_per_year = 24*365.2524\n",
+    "years_per_dataset = n_samples_h/(hours_per_year)\n",
+    "\n",
+    "f_per_year = f_per_dataset/years_per_dataset\n",
+    "plt.step(f_per_year, np.abs(fft))\n",
+    "plt.xscale('log')\n",
+    "plt.ylim(0, 400000)\n",
+    "plt.xlim([0.1, max(plt.xlim())])\n",
+    "plt.xticks([1, 365.2524], labels=['1/Year', '1/day'])\n",
+    "_ = plt.xlabel('Frequency (log scale)')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "2rbL8bSGDHy3"
+   },
+   "source": [
+    "### Split the data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "qoFJZmXBaxCc"
+   },
+   "source": [
+    "You'll use a `(70%, 20%, 10%)` split for the training, validation, and test sets. Note the data is **not** being randomly shuffled before splitting. This is for two reasons:\n",
+    "\n",
+    "1. It ensures that chopping the data into windows of consecutive samples is still possible.\n",
+    "2. It ensures that the validation/test results are more realistic, being evaluated on the data collected after the model was trained."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:04.284122Z",
+     "iopub.status.busy": "2023-07-27T04:27:04.283883Z",
+     "iopub.status.idle": "2023-07-27T04:27:04.288809Z",
+     "shell.execute_reply": "2023-07-27T04:27:04.288224Z"
+    },
+    "id": "ia-MPAHxbInX"
+   },
+   "outputs": [],
+   "source": [
+    "column_indices = {name: i for i, name in enumerate(df.columns)}\n",
+    "\n",
+    "n = len(df)\n",
+    "train_df = df[0:int(n*0.7)]\n",
+    "val_df = df[int(n*0.7):int(n*0.9)]\n",
+    "test_df = df[int(n*0.9):]\n",
+    "\n",
+    "num_features = df.shape[1]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "-eFckdUUHWmT"
+   },
+   "source": [
+    "### Normalize the data\n",
+    "\n",
+    "It is important to scale features before training a neural network. Normalization is a common way of doing this scaling: subtract the mean and divide by the standard deviation of each feature."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "mxbIic5TMlxx"
+   },
+   "source": [
+    "The mean and standard deviation should only be computed using the training data so that the models have no access to the values in the validation and test sets.\n",
+    "\n",
+    "It's also arguable that the model shouldn't have access to future values in the training set when training, and that this normalization should be done using moving averages. That's not the focus of this tutorial, and the validation and test sets ensure that you get (somewhat) honest metrics. So, in the interest of simplicity this tutorial uses a simple average."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:04.291955Z",
+     "iopub.status.busy": "2023-07-27T04:27:04.291732Z",
+     "iopub.status.idle": "2023-07-27T04:27:04.330937Z",
+     "shell.execute_reply": "2023-07-27T04:27:04.330220Z"
+    },
+    "id": "Eji6njXvHusN"
+   },
+   "outputs": [],
+   "source": [
+    "train_mean = train_df.mean()\n",
+    "train_std = train_df.std()\n",
+    "\n",
+    "train_df = (train_df - train_mean) / train_std\n",
+    "val_df = (val_df - train_mean) / train_std\n",
+    "test_df = (test_df - train_mean) / train_std"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "G6ufs8kk9JQw"
+   },
+   "source": [
+    "Now, peek at the distribution of the features. Some features do have long tails, but there are no obvious errors like the `-9999` wind velocity value."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:04.334797Z",
+     "iopub.status.busy": "2023-07-27T04:27:04.334556Z",
+     "iopub.status.idle": "2023-07-27T04:27:09.417027Z",
+     "shell.execute_reply": "2023-07-27T04:27:09.416293Z"
+    },
+    "id": "T0UYEnkwm8Fe"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df_std = (df - train_mean) / train_std\n",
+    "df_std = df_std.melt(var_name='Column', value_name='Normalized')\n",
+    "plt.figure(figsize=(12, 6))\n",
+    "ax = sns.violinplot(x='Column', y='Normalized', data=df_std)\n",
+    "_ = ax.set_xticklabels(df.keys(), rotation=90)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "ZBBmdxZ2HgfJ"
+   },
+   "source": [
+    "## Data windowing\n",
+    "\n",
+    "The models in this tutorial will make a set of predictions based on a window of consecutive samples from the data. \n",
+    "\n",
+    "The main features of the input windows are:\n",
+    "\n",
+    "- The width (number of time steps) of the input and label windows.\n",
+    "- The time offset between them.\n",
+    "- Which features are used as inputs, labels, or both. \n",
+    "\n",
+    "This tutorial builds a variety of models (including Linear, DNN, CNN and RNN models), and uses them for both:\n",
+    "\n",
+    "- *Single-output*, and *multi-output* predictions.\n",
+    "- *Single-time-step* and *multi-time-step* predictions.\n",
+    "\n",
+    "This section focuses on implementing the data windowing so that it can be reused for all of those models.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "YAhGUVx1jtOy"
+   },
+   "source": [
+    "Depending on the task and type of model you may want to generate a variety of data windows. Here are some examples:\n",
+    "\n",
+    "1. For example, to make a single prediction 24 hours into the future, given 24 hours of history, you might define a window like this:\n",
+    "\n",
+    "  ![One prediction 24 hours into the future.](images/raw_window_24h.png)\n",
+    "\n",
+    "2. A model that makes a prediction one hour into the future, given six hours of history, would need a window like this:\n",
+    "\n",
+    "  ![One prediction one hour into the future.](images/raw_window_1h.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "sa2BbfNZt8wy"
+   },
+   "source": [
+    "The rest of this section defines a `WindowGenerator` class. This class can:\n",
+    "\n",
+    "1. Handle the indexes and offsets as shown in the diagrams above.\n",
+    "1. Split windows of features into `(features, labels)` pairs.\n",
+    "2. Plot the content of the resulting windows.\n",
+    "3. Efficiently generate batches of these windows from the training, evaluation, and test data, using `tf.data.Dataset`s."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "rfx3jGjyziUF"
+   },
+   "source": [
+    "### 1. Indexes and offsets\n",
+    "\n",
+    "Start by creating the `WindowGenerator` class. The `__init__` method includes all the necessary logic for the input and label indices.\n",
+    "\n",
+    "It also takes the training, evaluation, and test DataFrames as input. These will be converted to `tf.data.Dataset`s of windows later."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:09.421376Z",
+     "iopub.status.busy": "2023-07-27T04:27:09.421135Z",
+     "iopub.status.idle": "2023-07-27T04:27:09.427808Z",
+     "shell.execute_reply": "2023-07-27T04:27:09.427182Z"
+    },
+    "id": "Kem30j8QHxyW"
+   },
+   "outputs": [],
+   "source": [
+    "class WindowGenerator():\n",
+    "  def __init__(self, input_width, label_width, shift,\n",
+    "               train_df=train_df, val_df=val_df, test_df=test_df,\n",
+    "               label_columns=None):\n",
+    "    # Store the raw data.\n",
+    "    self.train_df = train_df\n",
+    "    self.val_df = val_df\n",
+    "    self.test_df = test_df\n",
+    "\n",
+    "    # Work out the label column indices.\n",
+    "    self.label_columns = label_columns\n",
+    "    if label_columns is not None:\n",
+    "      self.label_columns_indices = {name: i for i, name in\n",
+    "                                    enumerate(label_columns)}\n",
+    "    self.column_indices = {name: i for i, name in\n",
+    "                           enumerate(train_df.columns)}\n",
+    "\n",
+    "    # Work out the window parameters.\n",
+    "    self.input_width = input_width\n",
+    "    self.label_width = label_width\n",
+    "    self.shift = shift\n",
+    "\n",
+    "    self.total_window_size = input_width + shift\n",
+    "\n",
+    "    self.input_slice = slice(0, input_width)\n",
+    "    self.input_indices = np.arange(self.total_window_size)[self.input_slice]\n",
+    "\n",
+    "    self.label_start = self.total_window_size - self.label_width\n",
+    "    self.labels_slice = slice(self.label_start, None)\n",
+    "    self.label_indices = np.arange(self.total_window_size)[self.labels_slice]\n",
+    "\n",
+    "  def __repr__(self):\n",
+    "    return '\\n'.join([\n",
+    "        f'Total window size: {self.total_window_size}',\n",
+    "        f'Input indices: {self.input_indices}',\n",
+    "        f'Label indices: {self.label_indices}',\n",
+    "        f'Label column name(s): {self.label_columns}'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "yVJgblsYzL1g"
+   },
+   "source": [
+    "Here is code to create the 2 windows shown in the diagrams at the start of this section:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:09.430763Z",
+     "iopub.status.busy": "2023-07-27T04:27:09.430546Z",
+     "iopub.status.idle": "2023-07-27T04:27:09.435057Z",
+     "shell.execute_reply": "2023-07-27T04:27:09.434430Z"
+    },
+    "id": "IsM5kRkz0UwK"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Total window size: 48\n",
+       "Input indices: [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23]\n",
+       "Label indices: [47]\n",
+       "Label column name(s): ['T (degC)']"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "w1 = WindowGenerator(input_width=24, label_width=1, shift=24,\n",
+    "                     label_columns=['T (degC)'])\n",
+    "w1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:09.438109Z",
+     "iopub.status.busy": "2023-07-27T04:27:09.437602Z",
+     "iopub.status.idle": "2023-07-27T04:27:09.441855Z",
+     "shell.execute_reply": "2023-07-27T04:27:09.441298Z"
+    },
+    "id": "viwKsYeAKFUn"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Total window size: 7\n",
+       "Input indices: [0 1 2 3 4 5]\n",
+       "Label indices: [6]\n",
+       "Label column name(s): ['T (degC)']"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "w2 = WindowGenerator(input_width=6, label_width=1, shift=1,\n",
+    "                     label_columns=['T (degC)'])\n",
+    "w2"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "kJaUyTWQJd-L"
+   },
+   "source": [
+    "### 2. Split\n",
+    "\n",
+    "Given a list of consecutive inputs, the `split_window` method will convert them to a window of inputs and a window of labels.\n",
+    "\n",
+    "The example `w2` you define earlier will be split like this:\n",
+    "\n",
+    "![The initial window is all consecutive samples, this splits it into an (inputs, labels) pairs](images/split_window.png)\n",
+    "\n",
+    "This diagram doesn't show the `features` axis of the data, but this `split_window` function also handles the `label_columns` so it can be used for both the single output and multi-output examples."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:09.444742Z",
+     "iopub.status.busy": "2023-07-27T04:27:09.444531Z",
+     "iopub.status.idle": "2023-07-27T04:27:09.449021Z",
+     "shell.execute_reply": "2023-07-27T04:27:09.448472Z"
+    },
+    "id": "W4KbxfzqkXPW"
+   },
+   "outputs": [],
+   "source": [
+    "def split_window(self, features):\n",
+    "  inputs = features[:, self.input_slice, :]\n",
+    "  labels = features[:, self.labels_slice, :]\n",
+    "  if self.label_columns is not None:\n",
+    "    labels = tf.stack(\n",
+    "        [labels[:, :, self.column_indices[name]] for name in self.label_columns],\n",
+    "        axis=-1)\n",
+    "\n",
+    "  # Slicing doesn't preserve static shape information, so set the shapes\n",
+    "  # manually. This way the `tf.data.Datasets` are easier to inspect.\n",
+    "  inputs.set_shape([None, self.input_width, None])\n",
+    "  labels.set_shape([None, self.label_width, None])\n",
+    "\n",
+    "  return inputs, labels\n",
+    "\n",
+    "WindowGenerator.split_window = split_window"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "G6U6VtVuM15s"
+   },
+   "source": [
+    "Try it out:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:09.451969Z",
+     "iopub.status.busy": "2023-07-27T04:27:09.451748Z",
+     "iopub.status.idle": "2023-07-27T04:27:09.468798Z",
+     "shell.execute_reply": "2023-07-27T04:27:09.468238Z"
+    },
+    "id": "YeCWbq6KLmL7"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "All shapes are: (batch, time, features)\n",
+      "Window shape: (3, 7, 19)\n",
+      "Inputs shape: (3, 6, 19)\n",
+      "Labels shape: (3, 1, 1)\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Stack three slices, the length of the total window.\n",
+    "example_window = tf.stack([np.array(train_df[:w2.total_window_size]),\n",
+    "                           np.array(train_df[100:100+w2.total_window_size]),\n",
+    "                           np.array(train_df[200:200+w2.total_window_size])])\n",
+    "\n",
+    "example_inputs, example_labels = w2.split_window(example_window)\n",
+    "\n",
+    "print('All shapes are: (batch, time, features)')\n",
+    "print(f'Window shape: {example_window.shape}')\n",
+    "print(f'Inputs shape: {example_inputs.shape}')\n",
+    "print(f'Labels shape: {example_labels.shape}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "xtMk1ffk2Mmd"
+   },
+   "source": [
+    "Typically, data in TensorFlow is packed into arrays where the outermost index is across examples (the \"batch\" dimension). The middle indices are the \"time\" or \"space\" (width, height) dimension(s). The innermost indices are the features.\n",
+    "\n",
+    "The code above took a batch of three 7-time step windows with 19 features at each time step. It splits them into a batch of 6-time step 19-feature inputs, and a 1-time step 1-feature label. The label only has one feature because the `WindowGenerator` was initialized with `label_columns=['T (degC)']`. Initially, this tutorial will build models that predict single output labels."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "tFZukGXrJoGo"
+   },
+   "source": [
+    "### 3. Plot\n",
+    "\n",
+    "Here is a plot method that allows a simple visualization of the split window:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:09.471813Z",
+     "iopub.status.busy": "2023-07-27T04:27:09.471598Z",
+     "iopub.status.idle": "2023-07-27T04:27:09.474570Z",
+     "shell.execute_reply": "2023-07-27T04:27:09.474016Z"
+    },
+    "id": "fmgd1qkYUWT7"
+   },
+   "outputs": [],
+   "source": [
+    "w2.example = example_inputs, example_labels"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:09.477329Z",
+     "iopub.status.busy": "2023-07-27T04:27:09.477093Z",
+     "iopub.status.idle": "2023-07-27T04:27:09.483378Z",
+     "shell.execute_reply": "2023-07-27T04:27:09.482808Z"
+    },
+    "id": "jIrYccI-Hm3B"
+   },
+   "outputs": [],
+   "source": [
+    "def plot(self, model=None, plot_col='T (degC)', max_subplots=3):\n",
+    "  inputs, labels = self.example\n",
+    "  plt.figure(figsize=(12, 8))\n",
+    "  plot_col_index = self.column_indices[plot_col]\n",
+    "  max_n = min(max_subplots, len(inputs))\n",
+    "  for n in range(max_n):\n",
+    "    plt.subplot(max_n, 1, n+1)\n",
+    "    plt.ylabel(f'{plot_col} [normed]')\n",
+    "    plt.plot(self.input_indices, inputs[n, :, plot_col_index],\n",
+    "             label='Inputs', marker='.', zorder=-10)\n",
+    "\n",
+    "    if self.label_columns:\n",
+    "      label_col_index = self.label_columns_indices.get(plot_col, None)\n",
+    "    else:\n",
+    "      label_col_index = plot_col_index\n",
+    "\n",
+    "    if label_col_index is None:\n",
+    "      continue\n",
+    "\n",
+    "    plt.scatter(self.label_indices, labels[n, :, label_col_index],\n",
+    "                edgecolors='k', label='Labels', c='#2ca02c', s=64)\n",
+    "    if model is not None:\n",
+    "      predictions = model(inputs)\n",
+    "      plt.scatter(self.label_indices, predictions[n, :, label_col_index],\n",
+    "                  marker='X', edgecolors='k', label='Predictions',\n",
+    "                  c='#ff7f0e', s=64)\n",
+    "\n",
+    "    if n == 0:\n",
+    "      plt.legend()\n",
+    "\n",
+    "  plt.xlabel('Time [h]')\n",
+    "\n",
+    "WindowGenerator.plot = plot"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "HXvctEuK68vX"
+   },
+   "source": [
+    "This plot aligns inputs, labels, and (later) predictions based on the time that the item refers to:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:09.486153Z",
+     "iopub.status.busy": "2023-07-27T04:27:09.485942Z",
+     "iopub.status.idle": "2023-07-27T04:27:09.947151Z",
+     "shell.execute_reply": "2023-07-27T04:27:09.946432Z"
+    },
+    "id": "XjTqUnglOOni"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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z9wpuZZdg4Y6L+OFMElY+3hPdPbjkn4iIiIjIkJSXl2PHjh3YvXs38vLz4GDvgPHjx2Py5MncMqBjTVreP2PGDPXr5MmTWLlyJX744QfMnTsXc+fOxQ8//ICVK1fi+PHjuo6XOpB/BTpj32vD8cbYIFiYiHEuMR+PfHECy/degayMS/6JiIiIiAzB3r174eHpgenTp+PA5QP4u+RvHLh8ANOnT4eHpwd++eUXvcS1du1a9OrVC1ZWVvDy8sL//d//obi4uF6/3bt3IzAwEObm5hgzZgySk5M1ru/Zswf9+vWDubk5/P39sWLFClRVVTX4nhUVFZgzZw7c3d1hbm4OHx8frF69Wiefr5bWe/r379+PsWPH1msfO3YsDh061CpBEdUylYjw8ojOOLzwPjzcyx1KFRB2KgGjPjmGn86nQKlkHUoiIiIiovZq7969mDBhAhQ+CgSuCYTvm77w+j8v+L7pi8A1gVD4KDB+/Hjs3bu3zWMTiUT4/PPPceXKFYSHh+PIkSN4/fXXNfqUlpbivffeQ0REBE6ePImCggI89dRT6usnTpzA9OnT8dprr+Hq1avYsGEDwsLC8N577zX4np9//jn27t2L7du3IzY2Flu2bIGvr68uP6b2Sb+joyP27NlTr33Pnj1wdHRslaCI7uRhZ4H/Tu2H758fhM7OVsgprsCiHRcxeUMkrqTJ9B0eERERERHdoby8HDOfmwnrvtbwmuMFMzczjetmbmbwmuMF677WmPncTJSXl7dpfPPmzcPIkSPh6+uL+++/H6tWrcL27ds1+lRWVuLLL79EaGgo+vfvj/DwcJw6dQpnzpwBAKxYsQKLFy/GjBkz4O/vjwceeADvvvsuNmzY0OB7JiUlITAwEMOGDYOPjw+GDRuGp59+Wqefs0l7+utasWIFXnjhBRw7dgyDBg0CAERFRWHfvn345ptvWj1AorqGBTrhj9eG47uT8fj88A2cT8zHo1/8hWmDfbDgwa6QWpjoO0QiIiIiIgKwY8cO5OfmI/A/gRBEDRfkFkQCXCe74saSG/jpp5/w7LPPtll8hw4dwurVqxETE4PCwkJUVVWhvLwcpaWlsLS0BABIJBIMGDBAfU9QUBDs7Oxw7do1DBw4EBcvXsTJkyc1ZvYVCkW959SaOXMmHnjgAXTt2hVjx47FI488ggcffFCnn1Prmf6ZM2fi5MmTsLW1xc6dO7Fz507Y2trir7/+wsyZM3UQIpEmU4kIL91Xs+S/d/WS//DIRNz/8TFsP5fMJf9ERERERO3A7t27Yd3Fut4M/53M3M1g3cUau3btaqPIgISEBDzyyCPo3bs3fv75Z5w/fx7//e9/AVTvu2+q4uJirFixAtHR0erXpUuXcOPGjQYLFPbr1w/x8fF49913UVZWhieffBJPPPFEq32uhmg90w8AgwYNwpYtW1o7FiKtuEst8N9n+uGZgTl4Z+8VxGUV4/Wf/sG2mir/PTtJ9R0iEREREVGHlZefB7GduEl9RXYi5OW33fHv58+fh1KpxCeffAKRqHou/M6l/QBQVVWFc+fOYeDAgQCA2NhYFBQUoFu3bgCqk/jY2FgEBAQ0+b1tbW0xZcoUTJkyBU888QTGjh2LvLw8ODg4tMInq69ZSf/NmzexadMm3Lp1C+vWrYOLiwv++OMPeHt7o0ePHq0dI9FdDQ1wwu9z/4VNJ+Px2eEbuJBUgMe+/AtTB/lg0YNdIbXkkn8iIiIiorbmYO8ARaqiSX2VBUo4eOom6ZXJZIiOjtZoc3JyQmVlJb744gs8+uijOHnyJNavX1/vXhMTE7z66qv4/PPPIZFIMGfOHAwePFg9CLBs2TI88sgj8Pb2xhNPPAGRSISLFy/i8uXLWLVqVb3nrV27Fu7u7ggODoZIJMKOHTvg5uYGOzs7XXx0AM1Y3n/8+HH06tULUVFR+Pnnn9VHGly8eBHvvPNOqwdI1BSmEhFevK8zjiwcgUf7eECpAjafTsTIT45h+1ku+SciIiIiamvjx49H8fViyDPkd+0nT5ej+HoxJkyYoJM4jh07huDgYI3X5s2bsXbtWnzwwQfo2bMntmzZ0uDReZaWlnjjjTfwzDPPYOjQobC2tsaPP/6ovj5mzBj8+uuvOHDgAAYMGIDBgwfj008/hY+PT4Ox2NjY4MMPP0RISAgGDBiAhIQE/P777+rVBrogqFQqrbKh0NBQTJ48GQsWLICNjQ0uXrwIf39/nDlzBhMnTkRKSoquYm23CgsLIZVKIZPJYGtrq+9wCMCpmzl4Z88V3MiqHpQK9rbDu1zyT0RERESktfLycsTHx8PPz6/Bfep3u8/D0wMKHwW85ng1WMxPpVQh+ctkiBPFSEtJ0+r5HcHd/u6bmodqPZxw6dKlBkdgXFxckJOTo+3jiHRiSGcn/P7av/DWQ91gZSrG30kFePTLv/D27ksoKG16YQ4iIiIiImoec3NzhG8KR3F0MZK/TK434y9PlyP5y2QURxcjfFM4E34d0Trpt7OzQ3p6er32v//+G506dWqVoIhag4lYhNnD/XFk0Qg81scDKhXw/ekk3P/JcWw7k8Ql/0REREREOvboo49i165dECeKcWPxDSS8n4Ckr5KQ8H4Cbiy5AXGiGLt378ajjz6q71CNltZJ/1NPPYU33ngDGRkZEAQBSqUSJ0+exKJFizB9+nRdxEjUIq625vj86WD8MHswurhaI6+kAot3XsLEr0/hUopM3+ERERERERm1xx57DGkpadi8eTMe7Pkg+ln1w4M9H8TmzZuRlpLGhF/HtN7TX1FRgVdeeQVhYWFQKBSQSCRQKBR45plnEBYWBrG4aUcyGBPu6TcclQolwk8lYN2hGyiWV0EQgKcHeuM/D3aFvZWpvsMjIiIiImp3mrunn1quNfb0a53010pKSsLly5dRXFyM4OBgBAYGNucxRoFJv+HJKizH+79fw+7oNACAvaUJXh8bhCkhXhA1UGCEiIiIiKijYtKvP3pN+uk2Jv2G6/StXLyz5wpiM4sAAH08pVj5eE/08bLTb2BERERERO1EbeLp6+sLCwsLfYfToZSVlSEhIaFFSb9E2zdVqVT46aefcPToUWRlZUGpVGpc37lzp7aPJNKbwf6O+HXuMEREJuLTg9dxMUWG8V+dxFMDvPH6GC75JyIiIiIyMTEBAJSWljLpb2OlpaUAbv9v0BxaJ/3z5s3Dhg0bMHLkSLi6ukIQuBSaDJuJWITnh/nh0d7uWP1HDHb9nYofziThj8vp+M+YrnhqgDfEXPJPRERERB2UWCyGnZ0dsrKyAACWlpbMA3VMpVKhtLQUWVlZsLOza1HtPK2X9zs4OOD777/HQw891Ow3NTZc3m9czsTnYdmey4jJqF7y37tmyX9fLvknIiIiog5KpVIhIyMDBQUF+g6lQ7Gzs4Obm1uDgyw629Pv5+eHP/74A0FBQdpHbKSY9BufKoVSveS/qKbK/1MDvPCfMUFw4JJ/IiIiIuqgFAoFKisr9R1Gh2BiYnLXGX6dJf3h4eHYt28fvvvuO+7nqMGk33hlFZVjzR8x2HkhFQBgZ2mCRQ92xdMDueSfiIiIiIj0R2dJf1lZGSZMmICTJ0/C19e3XkGBCxcuNC9iA8ak3/idTcjD0t23l/z36iTFysd7INjbXs+RERERERFRR6Sz6v0zZszA+fPn8eyzz7KQH3UYA3wd8Ourw/D96UR8cvA6LqXKMOGrU5gS4oXXx3aFo7WZvkMkIiIiIiKqR+uZfisrK+zfvx/Dhg3TVUwGhzP9HUt2kRxr/ojBzxdSAABSCxMsGtMVz3DJPxERERERtZGm5qEibR/s5eXFxJY6NGcbM3zyZB/89FIourvbQlZWiaW7L+Px//6FC0n5+g6PiIiIiIhITeuk/5NPPsHrr7+OhIQEHYRDZDhCfB2wd85QrHisB2zMJbicWoiJX53C6z9dRG6xXN/hERERERERab+8397eHqWlpaiqqoKlpWW9Qn55eXmtGqAh4PJ+yimW44M/YrDjfPWSf1tzCRaN6Yqpg3y45J+IiIiIiFqdTo/su5sZM2Zo8zijwKSfap1PzMfS3ZdxNb0QANDDwxYrH++J/j6s8k9ERERERK1HJ0l/ZWUlXnzxRSxduhR+fn6tEmhTJCQk4N1338WRI0eQkZEBDw8PPPvss3jrrbdgamra6H3l5eVYuHAhtm3bBrlcjjFjxuCrr76Cq6uruk9Dpw/88MMPeOqpp5ocH5N+qkuhVGFrVCI+2h+LwvIqAMAT/T2xeFwQnFjln4iIiIiIWoFOCvmZmJjg559/bnFw2oqJiYFSqcSGDRtw5coVfPrpp1i/fj3efPPNu943f/58/PLLL9ixYweOHz+OtLQ0TJw4sV6/TZs2IT09Xf0aP368jj4JdQRikYBpob44umgEngzxBAD8dD4FIz8+hvBTCahSKPUcIRERERERdRRaL++fMWMG+vbti/nz5+sqpib56KOP8PXXX+PWrVsNXpfJZHB2dsbWrVvxxBNPAKgePOjWrRsiIyMxePBgANUz/bt27WpRos+ZfrqbC0n5WLbnMi6nVi/57+Zui3cf74EQXwc9R0ZERERERIaqqXmoRNsHBwYGYuXKlTh58iT69+8PKysrjetz587VPtpmkMlkcHBoPGk6f/48KisrMXr0aHVbUFAQvL29NZJ+AHjllVfwwgsvwN/fHy+99BJmzZrV4LL/WnK5HHL57ershYWFLfw0ZMz6edtjzyvDsPVMEj7eH4tr6YV4Yn0kJvWrXvLvbMMl/0REREREpBtaJ/3ffvst7OzscP78eZw/f17jmiAIbZL0x8XF4YsvvsDHH3/caJ+MjAyYmprCzs5Oo93V1RUZGRnq71euXIn7778flpaWOHDgAP7v//4PxcXFd/0cq1evxooVK1r8OajjEIsETBvsg4d6uuGj/bHYdjYZP19IwYGrGVj4QBc8O9gHErHWJ2gSERERERHdldbL+1vT4sWL8cEHH9y1z7Vr1xAUFKT+PjU1Fffddx9GjBiB//3vf43et3XrVsyaNUtjRh4ABg4ciJEjRzb6vsuWLcOmTZuQnJzc6LMbmun38vLi8n5qsr+T8rFszxVcSpUBAILcbPDu+J4YwCX/RERERETUBDpb3l9X7XjB3ZbC383ChQsxc+bMu/bx9/dXf52WloaRI0diyJAh2Lhx413vc3NzQ0VFBQoKCjRm+zMzM+Hm5tbofYMGDcK7774LuVwOM7OGl12bmZk1eo2oKYK97bH7laHYdjYJH+6LRUxGESavj8TEfp2wZFw3LvknIiIiIqJW0az1xBEREejVqxcsLCxgYWGB3r17Y/PmzVo/x9nZGUFBQXd91R7Jl5qaihEjRqB///7YtGkTRKK7h96/f3+YmJjg8OHD6rbY2FgkJSUhNDS00fuio6Nhb2/PpJ50TiwSMHWQD44uGoGnB3pBEICdF1Jx/8fH8N1f8azyT0RERERELab1TP/atWuxdOlSzJkzB0OHDgUA/PXXX3jppZeQk5Ojk6r+tQm/j48PPv74Y2RnZ6uv1c7ap6amYtSoUYiIiMDAgQMhlUrx/PPPY8GCBXBwcICtrS1effVVhIaGqov4/fLLL8jMzMTgwYNhbm6OgwcP4v3338eiRYta/TMQNcbByhSrJ/bGlAHeWLbnMv5JkWHlr1ex/VwyVj7eEwP9uOSfiIiIiIiaR+s9/X5+flixYgWmT5+u0R4eHo7ly5cjPj6+VQMEgLCwMMyaNavBa7XhJyQkwM/PD0ePHsWIESMAAOXl5Vi4cCF++OEHyOVyjBkzBl999ZV6oGDfvn1YsmQJ4uLioFKpEBAQgJdffhmzZ8++50qCunhkH7UWhVKFH88m48P9MSgorQQATAjuhCXjguBia67n6IiIiIiIqL1oah6qddJvbm6Oy5cvIyAgQKP9xo0b6NWrF8rLy5sXsQFj0k+tLb+kAh8diMUPZ5KgUgHWZhLMf6ALZoSyyj8RERERETU9D9U6ewgICMD27dvrtf/4448IDAzU9nFE1AB7K1O8P6EX9rwyFH08pSiWV+HdX6/i4c//QtStXH2HR0REREREBkLrmf6ff/4ZU6ZMwejRo9V7+k+ePInDhw9j+/btmDBhgk4Cbc8400+6pFSqsP1cMj7YF4P8miX/4/t64M2HunHJPxERERFRB6Wz5f0AcP78eXz66ae4du0aAKBbt25YuHAhgoODmx+xAWPST22hoLQCH+2PxdY6S/7njQ7EjCG+MOGSfyIiIiKiDkWnST9pYtJPbemflAIs23MF0ckFAIAurtZY8VhPhHZ21G9gRERERETUZnSa9CuVSsTFxSErKwtKpeZZ4sOHD9c+WgPHpJ/amlKpwo7zyfhgXyzySioAAI/18cBbD3eDK5f8ExEREREZPZ0l/adPn8YzzzyDxMRE3HmrIAhQKBTNi9iAMeknfSkorcDHB2KxJap6yb+VqRjzRnfBzKFc8k9EREREZMx0lvT37dsXXbp0wYoVK+Du7g5BEDSuS6XS5kVswJj0k75dTpVh6Z7L+DupAAAQ6GKNFY/3wJDOTvoNjIiIiIiIdEJnSb+VlRUuXryIgICAFgdpLJj0U3ugVKrw04UUrPkjRr3k/9E+HnjroW5wk3LJPxERERGRMWlqHqr1+t9BgwYhLi6uRcERUesTiQQ8GeKFowtHYHqoD0QC8MvFNIz65Bg2/nkTlQrlvR9C1ELpsjKcupmDdFmZvkMhIiIiIjRjpn/Xrl14++238Z///Ae9evWCiYmJxvXevXu3aoCGgDP91B5dTpVh2Z7LuFCz5D/AxRorH+uBIQFc8k+68ePZJCzZeQlKFSASgNUTe2HKAG99h0VERERklHS2vF8kqr84QBAEqFQqFvJj0k/tjFKpws81S/5za5b8P9zbHW8/3A3uUgs9R0ftkVKpQmmlAqXyKhTLq1AiV9T8WYWSiir118VyRXVbTb/cYjkib+VpPEsQgPCZAzGoswPMJGI9fSIiIiIi46SzpD8xMfGu1318fLR5nFFg0k/tnaysEmsPxGLz6UQoVYClqRhzRwXiuaF+MJWwyr8hU6lUKK9U1knG6ybomsl73aS9pG57nftKKxXQ/iDXuxOLBPg5WaGrqw26uNqgq1v1y9vBEmKRcO8HEBEREVE9Okv6qT4m/WQorqTJ8M6eKziXmA8A6OxshRWP9cSwQC75b0vyKkW9ZLuhBLy4ojZBV2gk8nWT9tIKBRTK1v/PuEgArMwksDaTwMpMAitTcfWf6rbq761Nq9uqFEqs/iMGd0ZibSZGsbzhFWDmJiIEutQOBFijq5sturrawNXWrN7JMERERESkqVWT/r1792LcuHH19u835vfff8fIkSNhYdExlg8z6SdDolKpsPNCKlb/cQ05xTVL/nu5462Hu8HDrmP8f1ZblQqlRpKtOVuumahrLH3XmFmvnmkvkVehUqGbsdbaxFydqJuJ63xd0256O2GvbhPXtN2+z9pMAnMTkdaJ949nk/DmzstQqFQQCwLen9gTT4Z4IbNQjpiMQlzPLEJsRjFiMwtxI7MY8qqGi0tKLUyqVwW4WaOrq416MEBq2bR/g4iIiIg6glZN+sViMTIyMuDs7NykN7e1tUV0dDT8/f2bHrEBY9JPhkhWVolPD15HRGQClCrAwqR6yf/zwwx/yb9CqVIn2I0l5iUVd7YpNGfdK263VTSSnLaUhYlYnZxbmd4xg66RrIvvSNqrv7ask9RbmoghagdL5dNlZUjIKYWvk+Vd60YolCok5ZUiNqMQsRnFuJ5ZhJiMQiTklja6csHV1qxmAMAaXVxtEORmiwAXa1iYsl4AERERdTytmvSLRCKMGzcOZmZmTXrzX3/9FTExMUz6iQzA1bRCvLP3Ms4mVC/593e2worHeuBfgc5Il5UhPqcEfk5WOi38p1KpUKqRhDeteFxjs+5llbopKGoqEd1OzE01Z8atzMSw1Gi7czm8ZpuVqYT72RtQXqnArewSxGbeHgyIzShCakHDRwAKAuDjYFldJ8DVBl3cbBDkZgNfRytIxIY9eEVERER0N62a9M+aNUvrAD766CM4OXWMfcJM+snQqVQq7Po7Fe//HoOcYjkAoFcnW1xJK2zw+LWGiseVVjSyR11PxeMAQCIS6u9B15gtbzwxt6wz8157zYRJpN4UllfiRmYxYjOK1AMBsZlFyKs5leJOpmIR/J2tEORWPRDQtaaAYCc7C9YLICIiIqPAQn5tiEk/GYvC8uol/+Gnqpf838nFxgxllYq2Kx53x57zO4vHNbR3vW4bj4kzbiqVCjnFFTVbA4pwvWYg4HpmEUorGl7tYW0mQaCrdfVggOvtwQBH66atZCMiIiJqL5j0tyEm/WRstp1JwuKdl5rUV5vicXX7tFbxOKI7KZUqpBaUqVcD1K4OuJld3GgRRSdr09vHCdZsE+jiagNrM0kbR09ERETUNE3NQ/nbDBHVc19XZ4gEaMz2iwTg2xkD4ONoqU7ULdpJ8TiiukQiAV4OlvBysMTo7q7q9ooqJRJyS6oHA+qsCkjKK0VOcQVyinNx6mauxrM87S3UqwG61gwEdHa2Nvhil0RERNRxcKa/FXCmn4xRQ8ev1e7pJzImpRVV1fUC6qwKiM0oQlaRvMH+EpEAPyer6qKBrrdrBng7WHIQjIiIiNoMl/e3ISb9ZKyaevwakTHKL6lQrwaouzqgqLyqwf4WJmIEqo8TtFFvF3CxMeO2FSIiImp1TPrbEJN+IqKOQaVSIaOwXKNwYGxGEW5kFaOiStngPXaWJhpFA2u3CUgtTNo4eiIiIjImOkv64+PjceLECSQmJqK0tBTOzs4IDg5GaGgozM3NWxy4IWLST0TUsSmUKiTW1guoWR0Qk1GEhJySBk/CAAB3qblG8cCubjYIcLGGuQlPnSAiIqJ7a/Wkf8uWLfjss89w7tw5uLq6wsPDAxYWFsjLy8PNmzdhbm6OqVOn4o033oCPj0+rfRBDwKSfiIgaUl6pwM3s4tuDATXbBNJk5Q32FwmAr6MVutTUCqjdJuDraAmJmMUDiYiI6LZWTfqDg4NhamqKGTNm4NFHH4WXl5fGdblcjsjISGzbtg0///wzvvrqK0yePLnln8JAMOknIiJtFJZX4kbNaoC62wTySysb7G8qESHA2Vq9NSDIrXpQwENqznoBREREHVSrJv379+/HmDFjmvTGubm5SEhIQP/+/ZserYFj0k9ERC2lUqmQXSzH9YxixGQUVhcQzCzG9YwilFUqGrzHxkyCLrVFA12t0dXNFl3dbOBgZdrG0RMREVFbYyG/NsSkn4iIdEWpVCElv6xmNUCheiDgZnYxqhopGOBkbVbnBIHqwYBAF2tYmUnaOHoiIiLSlVZP+tPS0rB27VosW7as3gNlMhlWrVqFRYsWwdXVtWWRGyAm/URE1NYqqpSIzym5PRiQUYzrmUVIyitt9B4vBwt0dbVFV7faowVt4edkBVMJ6wUQEREZmqbmoU0e8l+7di0KCwsbfJhUKkVRURHWrl2LDz74oHkRExERUZOZSkTqIwDRx0PdXiKvwo2s6tUAMRlFNdsEipBdJEdyXhmS88pw6Fqmur9EJMDf2ap6a4Dr7cEAT3sLiESsF0BERGTomjzT37NnT6xfvx7Dhg1r8PqpU6cwe/ZsXLlypVUDNASc6SciovYur6QCsXUGAWJriggWyasa7G9hIkYX19vFA2sHGJytzVg8kIiIqB1o9Zn++Ph4eHt7N3rd09MTCQkJWgVJREREbcPByhShnR0R2tlR3aZSqZAuK9c4UjAmowhx2cUoq1TgYooMF1NkGs+xtzTROEGga83xgrbmJm39kYiIiKgJmpz0W1hYICEhodHEPyEhARYWFq0WGBEREemWIAjwsLOAh50FRga5qNurFEok5pVWDwbUrg7IKEJCbgnySysRFZ+HqPg8jWd5SM2rBwFqBwJcbRDgYg1zE3FbfywiIiKqo8nL+x9++GF4eHjgm2++afD6Cy+8gLS0NPz++++tGiBQPaDw7rvv4siRI8jIyICHhweeffZZvPXWWzA1bfxYoo0bN2Lr1q24cOECioqKkJ+fDzs7O40+eXl5ePXVV/HLL79AJBJh0qRJ+Oyzz2Btbd3k+Li8n4iIOoLySgXisorrbRNIl5U32F8kAL5OVujqWmcwwM0Gvo5WENfUC0iXlSE+pwR+TlZwl3LygIiIqKlafXn/okWL8MADD0AqleI///mPukp/ZmYmPvzwQ4SFheHAgQMtj7wBMTExUCqV2LBhAwICAnD58mXMnj0bJSUl+Pjjjxu9r7S0FGPHjsXYsWOxZMmSBvtMnToV6enpOHjwICorKzFr1iz8+9//xtatW3XyWYiIiAyVuYkYPTtJ0bOTVKNdVlaJG5l1CgfWbBcoKK3ErewS3MouwR+XM9T9zSQiBLhYw0wiwt9JBVCheoBg9cRemDKg8a2EREREpL0mz/QDwIYNG/Daa6+hsrIStra2EAQBMpkMJiYm+PTTT/Hyyy/rMlYNH330Eb7++mvcunXrnn2PHTuGkSNH1pvpv3btGrp3746zZ88iJCQEALBv3z489NBDSElJgYeHRyNP1MSZfiIiIk0qlQrZRXL1aoDa1QHXM6vrBTREJADH/zMCXg5WbRwtERGR4Wn1mX4AePHFF/HII49g+/btiIuLg0qlQpcuXfDEE0/A09OzxUFrQyaTwcHBoUXPiIyMhJ2dnTrhB4DRo0dDJBIhKioKEyZMaPA+uVwOuVyu/r6wsLBFcRARERkbQRDgYmsOF1tz/CvQWd2uVKqQnF+KPdFpWHvwusY9ShUw4b+nMGuYH54a4AVHa7O2DpuIiMjoaJX0A0CnTp0wf/58XcTSZHFxcfjiiy/uurS/KTIyMuDi4qLRJpFI4ODggIyMjEbuAlavXo0VK1a06L2JiIg6IpFIgI+jFSaHeGLdoetQ3rHeMKekAh/tj8Vnh27g4d7umBbqg2AvOx4TSERE1ExaJ/179+5tsF0QBJibmyMgIAB+fn5NetbixYvxwQcf3LXPtWvXEBQUpP4+NTUVY8eOxeTJkzF79uymB96KlixZggULFqi/LywshJeXl15iISIiMkTuUgusntgLb+68DIVKBbEgYMXjPWBhIkbE6URcTC7Arr9TsevvVPTsZIvpg33xWF8PngZARESkJa2T/vHjx0MQBNxZCqC2TRAEDBs2DLt374a9vf1dn7Vw4ULMnDnzrn38/f3VX6elpWHkyJEYMmQINm7cqG3o9bi5uSErK0ujraqqCnl5eXBzc2v0PjMzM5iZcckhERFRS0wZ4I3hXZyRkFMKXydLdfX+Sf098U9KASIiE7H3Yhoupxbi9Z//wft/XMOTIV54dpAPvB0t9Rw9ERGRYRBpe8PBgwcxYMAAHDx4EDKZDDKZDAcPHsSgQYPw66+/4s8//0Rubi4WLVp0z2c5OzsjKCjorq/aI/lSU1MxYsQI9O/fH5s2bYJIpHXo9YSGhqKgoADnz59Xtx05cgRKpRKDBg1q8fOJiIjo7tylFgjt7FjvuL7ennb4eHIfnF4yCovHBcHT3gIFpZXY+Oct3PfxUczadAZHY7KgvHN/ABEREWnQqno/APTs2RMbN27EkCFDNNpPnjyJf//737hy5QoOHTqE5557DklJSa0SZG3C7+Pjg/DwcIjFt5f21c7Ip6amYtSoUYiIiMDAgQMBVO/Zz8jIwLlz5zB79mz8+eefsLGxgbe3t7oI4Lhx45CZmYn169erj+wLCQnR6sg+Vu8nIiLSLYVShWOxWYiITMTx69nqdm8HSzw72BtPhnjBztJUjxESERG1LZ1U7weAmzdvNvhAW1tb9fF5gYGByMnJ0fbRjTp48CDi4uIQFxdX75SA2jGLyspKxMbGorS0VH1t/fr1GgX3hg8fDgDYtGmTelvBli1bMGfOHIwaNQoikQiTJk3C559/3mqxExERUcuJRQJGdXPFqG6uSMgpwfenE7H9XDKS8krx/u8x+OTAdTzWxwMzhviiZyepvsMlIiIDU15ejh07dmD37t3Iy8+Dg70Dxo8fj8mTJ8Pc3Fzf4bWI1jP9w4YNg42NDSIiIuDsXH0ET3Z2NqZPn46SkhL8+eefOHToEF555RXExsbqJOj2hjP9REREba+sQoE90amIiEzE1fTbx+cGe9theqgPHurlDjMJC/8REdHd7d27FzOfm4n83HxYd7GG2E4MRYECxdeLYe9oj/BN4Xj00Uf1HWY9Tc1DtU76Y2Nj8fjjjyM+Pl5dsT45ORn+/v7Ys2cPunTpgt27d6OoqAjTpk1r2acwEEz6iYiI9EelUuFCUj4iIhPx+6V0VCqqf7VxtDLFlAFemDrYB53sLO7xFCIi6oj27t2LCRMmwLqvNVyfdIWZ2+2C7fIMOTK3Z6I4uhi7du3CY489psdI69NZ0g8ASqUSBw4cwPXr1wEAXbt2xQMPPNAqxfUMEZN+IiKi9iG7SI4fzyZhS1QS0mXlAACRAIzq5orpoT4YFuAEQRD0HCUREbUH5eXl8PD0gMJHAa85XhBE9f99UClVSP4yGeJEMdJS0trVUn+dJv21ysvLYWZm1uH/8WTST0RE1L5UKZQ4dC0TEZGJOHUzV93u72yFaYN9MKm/J2zNTfQYIRER6dvmzZsxffp0BK4J1Jjhv5M8XY4bS25g8+bNePbZZ9swwrtrah6q9dS8UqnEu+++i06dOsHa2hrx8fEAgKVLl+Lbb79tfsRERERErUQiFmFsT3dsnT0YhxYMx4xQH1ibSXAruwQrfrmKwe8fxpu7LiEmo/DeDyMiIqO0e/duWHexvmvCDwBm7maw7mKNXbt2tVFkrUvrpH/VqlUICwvDhx9+CFPT20fj9OzZE//73/9aNTgiIiKilgpwscGKx3vi9Juj8O74nujiao3SCgW2RiVh7LoTeHJ9JH65mIZKhVLfoRIRURvKy8+D2K5pBV9FdiLk5efpOCLd0PrIvoiICGzcuBGjRo3CSy+9pG7v06cPYmJiWjU4IiIiotZibSbBtME+eHaQN6Li87A5MhH7rmTgTEIeziTkwdnGDM8M9MYzg7zhatt+9mwSEZFuONg7QJGqaFJfZYESDp4OOo5IN7Se6U9NTUVAQEC9dqVSicrKylYJioiIiEhXBEHAYH9H/HdqP5x8437MHRUIZxszZBfJ8dnhGxi65ghe2XIBp2/logWlj4iIqJ0bP348iq8XQ54hv2s/ebocxdeLMWHChDaKrHVpnfR3794dJ06cqNf+008/ITg4uFWCIiIiImoLblJzLHigC06+cT++eDoYA30dUKVU4bdL6Xhq42mMXXcCm08nokRepe9QiYiolU2ePBn2jvbI3J4JlbLhQV6VUoXMHZmwd7THE0880cYRtg6tl/cvW7YMM2bMQGpqKpRKJXbu3InY2FhERETg119/1UWMRERERDplKhHh0T4eeLSPB66lF2Lz6UTsupCK2MwiLN19GR/8EYNJ/TphWqgvAlys9R0uERG1AnNzc4RvCsf48eOR/GUyXJ901SjqJ0+XI3NHJoqji7F79+52dVyfNpp1ZN+JEyewcuVKXLx4EcXFxejXrx+WLVuGBx98UBcxtns8so+IiMj4yMoq8fP5FHx/OhG3ckrU7UMDHDFtsC9Gd3OBRKz1okkiImpn9u7di5nPzUR+bj6su1hDZCeCskCJ4uvFsHe0R/imcDz66KP6DrOepuahzUr6SROTfiIiIuOlVKpw8mYOIiITcfhaJmpXgHpIzfHMIG88NdAbTtZ3P+6JiIjat/Lycvz000/YtWsX8vLz4GDvgAkTJuCJJ55otzP8TPrbEJN+IiKijiElvxRbo5Kw7Wwy8koqAAAmYgEP9XLH9FBf9PO2gyAIeo6SiIg6glZN+u3t7Zv8D1henmGeXdgSTPqJiIg6lvJKBX6/lI6IyEREJxeo23t42GJ6qA8e69MJFqZNO/uZiIioOVo16Q8PD1d/nZubi1WrVmHMmDEIDQ0FAERGRmL//v1YunQp5s+f3wrhGxYm/URERB3XpRQZIiITsPdiGuRVSgCA1MIEk/t74tnBPvB1stJzhEREZIx0trx/0qRJGDlyJObMmaPR/uWXX+LQoUPYvXt3swI2ZEz6iYiIKL+kAjvOJ+P700lIyitVt4/o6ozpoT64r4sLxCIu/Sciotahs6Tf2toa0dHRCAgI0GiPi4tD3759UVxc3LyIDRiTfiIiIqqlVKpw/Ho2wiMTcPx6Nmp/0/JysMCzg3zwZIgX7K1M9RskEREZvKbmoVqfM+Po6Ig9e/bUa9+zZw8cHR21fRwRERGRURGJBIwMckHYrIE4tmgEZv/LD1ILEyTnlWH1HzEYvPowFu24iH9SCvQdKhERdQBaz/SHhYXhhRdewLhx4zBo0CAAQFRUFPbt24dvvvkGM2fO1EWc7Rpn+omIiOhuyioU+OViGiJOJ+ByaqG6va+XHaaH+uChXu4wN2HhPyIiajqdHtkXFRWFzz//HNeuXQMAdOvWDXPnzlUPAnQ0TPqJiIioKVQqFf5OLkDEqQT8fikDFYrqwn8OVqaYMsALUwd5w9PeUs9REhGRIdBp0k+amPQTERGRtnKK5fjxbDK2nE5EmqwcACASgPuDXDE91AfDApwgYuE/IiJqRKsm/SUlJbCyavpxM9r2N3RM+omIiKi5qhRKHI7JwubIRPwVl6Nu93OywrTBPpjU3xNSCxM9RkhERO1RqxbyCwgIwJo1a5Cent5oH5VKhYMHD2LcuHH4/PPPtY+YiIiIqAOSiEUY08MN378wCIcW3IeZQ3xhYyZBfE4JVv56FYPfP4wlOy/hWnrhvR9GRER0hybN9MfGxuLNN9/Eb7/9hj59+iAkJAQeHh4wNzdHfn4+rl69isjISEgkEixZsgQvvvgixOKOU4yGM/1ERETUmkrkVdj1dyo2RyYiNrNI3T7A1x7TQn0xtocbTCVaH8JERERGRCd7+pOSkrBjxw6cOHECiYmJKCsrg5OTE4KDgzFmzBiMGzeuQyX7tZj0ExERkS6oVCqcic9DxOlE7L+cgSpl9a9tzjZmeHqgN54Z6A03qbmeoyQiIn1gIb82xKSfiIiIdC2zsBxbo5Lww5kkZBXJAQBikYAxPVwxbbAvBvs7QBBY+I+IqKNg0t+GmPQTERFRW6lUKLH/SgYiIhNxJj5P3d7F1RrTBvtgQj9PWJtJ9BghERG1BSb9bYhJPxEREelDTEYhNkcmYtffqSitUAAArM0kmNivE6aH+iDAxUbPERIRka4w6W9DTPqJiIhInwrLK/Hz+RRsPp2IW9kl6vYhnR0xPdQHo7u5QiJm4T8iImPCpL8NMeknIiKi9kClUuFkXC4iIhNw6Fomaur+wV1qjmcGeuOpgd5wtjHTb5BERNQqWj3pX7lyJRYtWgRLS8tWC9JYMOknIiKi9ia1oAxboxKx7UwycksqAAAmYgHjerpjeqgP+vvYs/AfEZEBa/WkXywWIz09HS4uLq0WpLFg0k9ERETtlbxKgd8vpSMiMhF/JxWo27u722J6qA8e79sJFqYd78hlIiJD1+pJv0gkQkZGBpP+BjDpJyIiIkNwOVWGiMgE7IlOg7xKCQCwNZdgcogXpg32ga+TlZ4jJCKiptJJ0p+ZmQlnZ+dWC9JYMOknIiIiQ1JQWoEd56oL/yXllarbh3dxxvTBPhgZ5AKxiEv/iYjas6bmoVqVce3SpQscHBzu+tKFhIQEPP/88/Dz84OFhQU6d+6Md955BxUVFXe9b+PGjRgxYgRsbW0hCAIKCgrq9fH19YUgCBqvNWvW6ORzEBEREbUHdpammD3cH8cWjcCmmQMwsqszBAH483o2Xog4h/s+Oor1x28ir+Tuv2sREVH7J9Gm84oVKyCVSnUVS6NiYmKgVCqxYcMGBAQE4PLly5g9ezZKSkrw8ccfN3pfaWkpxo4di7Fjx2LJkiWN9lu5ciVmz56t/t7GhmfaEhERkfETiQSMDHLByCAXJOWW4vuoRGw/l4yU/DKs+SMGaw9ex6O9PTA91Ad9vOz0HS4RETWDwe7p/+ijj/D111/j1q1b9+x77NgxjBw5Evn5+bCzs9O45uvri3nz5mHevHnNjoXL+4mIiMhYlFcqsPdiGiIiE3A5tVDd3sdTimmhvniktzvMTVj4j4hI31p9eX97O9JFJpO12naCNWvWwNHREcHBwfjoo49QVVV11/5yuRyFhYUaLyIiIiJjYG4ixpMhXvhlzjDs/L8hmBDcCaZiES6myLBox0WErj6MNX/EILlOLQAiImq/mry8v4kLAtpEXFwcvvjii7su7W+quXPnol+/fnBwcMCpU6ewZMkSpKenY+3atY3es3r1aqxYsaLF701ERETUXgmCgH7e9ujnbY+3Hu6GH88mY2tUElILyrD++E1s+PMmRgW5YFqoL/4V4AQRC/8REbVLTV7erwuLFy/GBx98cNc+165dQ1BQkPr71NRU3HfffRgxYgT+97//Nel97ra8/07fffcdXnzxRRQXF8PMzKzBPnK5HHK5XP19YWEhvLy8uLyfiIiIjJpCqcLha5nYfDoRJ27kqNv9nKwwdZA3Jvf3gtTSRI8REhF1HK1+ZJ8uZGdnIzc39659/P39YWpqCgBIS0vDiBEjMHjwYISFhUEkatruBG2S/itXrqBnz56IiYlB165dm/R87uknIiKijuZmdjE2Rybi5/MpKJJXb400NxFhQnAnTBvsi+4e/J2IiEiXmpqHalW9v7U5OzvD2dm5SX1TU1MxcuRI9O/fH5s2bWpywq+t6OhoiESidlOwkIiIiKg96uxsjeWP9cB/xnTF7uhUbI5MRExGEX44k4wfziQjxMce00J9MK6nO0wluvm9jYiI7k2vSX9TpaamYsSIEfDx8cHHH3+M7Oxs9TU3Nzd1n1GjRiEiIgIDBw4EAGRkZCAjIwNxcXEAgEuXLsHGxgbe3t5wcHBAZGQkoqKiMHLkSNjY2CAyMhLz58/Hs88+C3t7+7b/oEREREQGxspMgqmDfPDMQG+cTchHRGQC9l3OwLnEfJxLzMe71tfw9EAvPDPIG+5SC32HS0TU4eh1eX9ThYWFYdasWQ1eqw0/ISEBfn5+OHr0KEaMGAEAWL58eYMF9zZt2oSZM2fiwoUL+L//+z/ExMRALpfDz88P06ZNw4IFCxrdz98QLu8nIiIiui2rsBxbzyRha1QSsoqq6yCJRQIe7O6KaaE+CPV3bHcnQxERGRqD2NNvLJj0ExEREdVXqVDiwJVMREQmICo+T90e6GKNaaE+mBDcCTbmLPxHRNQcTPrbEJN+IiIioruLzSjC5tMJ2HkhFaUVCgCAlakYE/t5YnqoDwJdbfQcIRGRYWHS34aY9BMRERE1TVF5JXZeSEVEZAJuZpeo2wf7O2BGqC8e6O4KiZiF/4iI7oVJfxti0k9ERESkHZVKhVM3cxERmYCDVzOhrPmN1M3WHM8M8sZTA73gYmOu3yCJiNoxJv1tiEk/ERERUfOlFZRha1QStp1NQk5xBQDARCxgbE93TA/1QYiPPQv/ERHdgUl/G2LST0RERNRy8ioF9l3OQPipBFxIKlC3B7nZYMYQXzze1wOyskrE55TAz8mKRwASUYfGpL8NMeknIiIial2XU2XYHJmIPRdTUV6pBACYSUSoqFJCBUAAMDnEE/d1cYGpRARTiQhmdf40k4hgKhbDzEQEU/HtdtYLICJjwaS/DTHpJyIiItINWWkldpxPxqaT8UgtKG/x80QCYCYRNzBQUN1mJhapBwo0Bwy0uUes0e/Oe6oHJEQQibhlgYiar6l5qKQNYyIiIiIi0orU0gQv/Msf3dxsMfXbqHrXu7nZwMxEjIoqJSoUSsirFNVfVykhr/mzSnl7jkupAsoqFSirVLTlx2iQiVioGSgQa6xG0BwoEN8eMNAYXGjsHs0BB7M6AxF3rnqo7W8iFlgzgciIMeknIiIionbP38UKIgGok79DLAj4btaAe+7tVyhVdQYCFJDXGRCoUCghr1TU/Fn9fW2/2oED+R2DCBUKhbpvY/do3lv9nhUKJequsa1UqFCpUKCkQv8DEJrbIm4PKjQ2UFBvBUOj9zS86uHO7Re1f7b29ot0WRlrQFCHx6SfiIiIiNo9d6kFVk/shTd3XoZCpYJYEPD+xJ5NSuTEIgEWpmJYmIoBmOg+2EaoVCpUKVW3Bw8aHVxQ3DHI0NjAxD3uubPtjut11V4v0tPfTa262y8aXMFwj+0Xde+5mlaI3/5Jr64BIQBrJvbClAHeev6ERG2Pe/pbAff0ExEREbWNdFkZEnJK4etkyZnbFlAqVdWDB3UGEmoHFuoPFNyxOqKBwQaN5zQwkKHu28DAhULZNumIWBDw1+KR/Lkho8E9/URERERkdNylFkzaWoFIJMBcJIa5iRgw128sVYrbgwB1Bwsaqs/Q0AqGhlY8pOSX4vj1HI33UahUSMgp5c8PdThM+omIiIiISG8kNXv5LU1b75npsjIMXXOkXg0IXyfL1nsTIgPBg0qJiIiIiMio1NaAENecSqBNDQgiY8OZfiIiIiIiMjpTBnhjeBdn1oCgDo9JPxERERERGSXWgCDi8n4iIiIiIiIio8Wkn4iIiIiIiMhIcXl/K1CpqsuCFhYW6jkSIiIiIiIi6ghq88/afLQxTPpbQVFREQDAy8tLz5EQERERERFRR1JUVASpVNrodUF1r2EBuielUom0tDTY2NhAqDkWpD0qLCyEl5cXkpOTYWtrq+9wyADwZ4a0xZ8Z0hZ/Zkhb/JkhbfDnhbRlSD8zKpUKRUVF8PDwgEjU+M59zvS3ApFIBE9PT32H0WS2trbt/geY2hf+zJC2+DND2uLPDGmLPzOkDf68kLYM5WfmbjP8tVjIj4iIiIiIiMhIMeknIiIiIiIiMlJM+jsQMzMzvPPOOzAzM9N3KGQg+DND2uLPDGmLPzOkLf7MkDb480LaMsafGRbyIyIiIiIiIjJSnOknIiIiIiIiMlJM+omIiIiIiIiMFJN+IiIiIiIiIiPFpJ+IiIiIiIjISDHp7yD++9//wtfXF+bm5hg0aBDOnDmj75CoHfvzzz/x6KOPwsPDA4IgYPfu3foOidqx1atXY8CAAbCxsYGLiwvGjx+P2NhYfYdF7djXX3+N3r17w9bWFra2tggNDcUff/yh77DIgKxZswaCIGDevHn6DoXaqeXLl0MQBI1XUFCQvsOidi41NRXPPvssHB0dYWFhgV69euHcuXP6DqvFmPR3AD/++CMWLFiAd955BxcuXECfPn0wZswYZGVl6Ts0aqdKSkrQp08f/Pe//9V3KGQAjh8/jldeeQWnT5/GwYMHUVlZiQcffBAlJSX6Do3aKU9PT6xZswbnz5/HuXPncP/99+Pxxx/HlStX9B0aGYCzZ89iw4YN6N27t75DoXauR48eSE9PV7/++usvfYdE7Vh+fj6GDh0KExMT/PHHH7h69So++eQT2Nvb6zu0FuORfR3AoEGDMGDAAHz55ZcAAKVSCS8vL7z66qtYvHixnqOj9k4QBOzatQvjx4/XdyhkILKzs+Hi4oLjx49j+PDh+g6HDISDgwM++ugjPP/88/oOhdqx4uJi9OvXD1999RVWrVqFvn37Yt26dfoOi9qh5cuXY/fu3YiOjtZ3KGQgFi9ejJMnT+LEiRP6DqXVcabfyFVUVOD8+fMYPXq0uk0kEmH06NGIjIzUY2REZKxkMhmA6iSO6F4UCgW2bduGkpIShIaG6jscaudeeeUVPPzwwxq/1xA15saNG/Dw8IC/vz+mTp2KpKQkfYdE7djevXsREhKCyZMnw8XFBcHBwfjmm2/0HVarYNJv5HJycqBQKODq6qrR7urqioyMDD1FRUTGSqlUYt68eRg6dCh69uyp73CoHbt06RKsra1hZmaGl156Cbt27UL37t31HRa1Y9u2bcOFCxewevVqfYdCBmDQoEEICwvDvn378PXXXyM+Ph7/+te/UFRUpO/QqJ26desWvv76awQGBmL//v14+eWXMXfuXISHh+s7tBaT6DsAIiIyHq+88gouX77MfZN0T127dkV0dDRkMhl++uknzJgxA8ePH2fiTw1KTk7Ga6+9hoMHD8Lc3Fzf4ZABGDdunPrr3r17Y9CgQfDx8cH27du5jYgapFQqERISgvfffx8AEBwcjMuXL2P9+vWYMWOGnqNrGc70GzknJyeIxWJkZmZqtGdmZsLNzU1PURGRMZozZw5+/fVXHD16FJ6envoOh9o5U1NTBAQEoH///li9ejX69OmDzz77TN9hUTt1/vx5ZGVloV+/fpBIJJBIJDh+/Dg+//xzSCQSKBQKfYdI7ZydnR26dOmCuLg4fYdC7ZS7u3u9gedu3boZxbYQJv1GztTUFP3798fhw4fVbUqlEocPH+beSSJqFSqVCnPmzMGuXbtw5MgR+Pn56TskMkBKpRJyuVzfYVA7NWrUKFy6dAnR0dHqV0hICKZOnYro6GiIxWJ9h0jtXHFxMW7evAl3d3d9h0Lt1NChQ+sdOXz9+nX4+PjoKaLWw+X9HcCCBQswY8YMhISEYODAgVi3bh1KSkowa9YsfYdG7VRxcbHGSHh8fDyio6Ph4OAAb29vPUZG7dErr7yCrVu3Ys+ePbCxsVHXC5FKpbCwsNBzdNQeLVmyBOPGjYO3tzeKioqwdetWHDt2DPv379d3aNRO2djY1KsTYmVlBUdHR9YPoQYtWrQIjz76KHx8fJCWloZ33nkHYrEYTz/9tL5Do3Zq/vz5GDJkCN5//308+eSTOHPmDDZu3IiNGzfqO7QWY9LfAUyZMgXZ2dlYtmwZMjIy0LdvX+zbt69ecT+iWufOncPIkSPV3y9YsAAAMGPGDISFhekpKmqvvv76awDAiBEjNNo3bdqEmTNntn1A1O5lZWVh+vTpSE9Ph1QqRe/evbF//3488MAD+g6NiIxESkoKnn76aeTm5sLZ2RnDhg3D6dOn4ezsrO/QqJ0aMGAAdu3ahSVLlmDlypXw8/PDunXrMHXqVH2H1mKCSqVS6TsIIiIiIiIiImp93NNPREREREREZKSY9BMREREREREZKSb9REREREREREaKST8RERERERGRkWLST0RERERERGSkmPQTERERERERGSkm/URERERERERGikk/ERERERERkZFi0k9ERERERERkpJj0ExERERERERkpJv1ERERERERERopJPxEREREREZGRYtJPREREREREZKQk+g7AGCiVSqSlpcHGxgaCIOg7HCIiIiIiIjJyKpUKRUVF8PDwgEh0l/l8lYFYtWqVKjQ0VGVhYaGSSqX37F9RUaF6/fXXVT179lRZWlqq3N3dVdOmTVOlpqZq9PPx8VEB0HitXr1aq9iSk5PrPYMvvvjiiy+++OKLL7744osvvnT9Sk5Ovmu+ajAz/RUVFZg8eTJCQ0Px7bff3rN/aWkpLly4gKVLl6JPnz7Iz8/Ha6+9hsceewznzp3T6Lty5UrMnj1b/b2NjY1WsdX2T05Ohq2trVb3EhEREREREWmrsLAQXl5e98xfDSbpX7FiBQAgLCysSf2lUikOHjyo0fbll19i4MCBSEpKgre3t7rdxsYGbm5uzY6tdkm/ra0tk34iIiIiIiJqM/faYt6hCvnJZDIIggA7OzuN9jVr1sDR0RHBwcH46KOPUFVVddfnyOVyFBYWaryIiIiIiIiI2huDmelvqfLycrzxxht4+umnNWbj586di379+sHBwQGnTp3CkiVLkJ6ejrVr1zb6rNWrV6tXHhARERERERG1V4JKpVLp680XL16MDz744K59rl27hqCgIPX3YWFhmDdvHgoKCpr8PpWVlZg0aRJSUlJw7Nixuy7B/+677/Diiy+iuLgYZmZmDfaRy+WQy+Xq72v3UshkMi7vJ6OSLitDfE4J/Jys4C610Hc4RERERERUo7CwEFKp9J55qF5n+hcuXIiZM2fetY+/v3+L3qOyshJPPvkkEhMTceTIkXsm5YMGDUJVVRUSEhLQtWvXBvuYmZk1OiDQnjGBI238eDYJS3ZeglIFiARg9cRemDLA+943EhERERFRu6HXpN/Z2RnOzs46e35twn/jxg0cPXoUjo6O97wnOjoaIpEILi4uOotLHwwhgVOpVFCqAKVKBVWdP1Wo066843vV7fvU7crqxStK1V36Kavb6/ZT3eVP1R39VHfEWf2Wt9+vsX71Po+qiZ9bI57atjs+d/VNdd7/dr/G4q/tV/2s2n5AibwKR2Ky1P/bKFXAkp2X8K9AJ3jYWbb1jwYRERERETWTwezpT0pKQl5eHpKSkqBQKBAdHQ0ACAgIgLW1NQAgKCgIq1evxoQJE1BZWYknnngCFy5cwK+//gqFQoGMjAwAgIODA0xNTREZGYmoqCiMHDkSNjY2iIyMxPz58/Hss8/C3t5eXx+11aXLytQJP1CdwL3x8yVsOZ0EiVion9gqaw58rE0ENRLR2mSxuh/qfF/d785nqWqeVT+pVdbpp79NJtRUShXw4Kd/IsTXAX087dDX2w59PO3gYGWq79CIiIiIiKgRBpP0L1u2DOHh4ervg4ODAQBHjx7FiBEjAACxsbGQyWQAgNTUVOzduxcA0LdvX41n1d5jZmaGbdu2Yfny5ZDL5fDz88P8+fOxYMEC3X+gNhSfU6JO+Ov6J1XW9sG0MkEARIIAATV/CvX/FACIRIK6nyAIEAm371X3q/t93Wer/6x5H9Ed39d9r9pnQ1D3A2qf23g/oc5nENVcvx1P0/rVfk6htn+d+1H3/RvpVzeuovIqfHrwOu78sSmWK3AsNhvHYrPVbd4OlujjZYc+nlL09bJDDw8pLEzFuv6fnoiIiIiImkCvhfyMRVMLKOhLuqwMQ9cc0Uj8RQLw3vhecLQ2rZ8k35EgCnUSzIb+1EhsRbcTyTsTV3U/UZ1EtpEEVxDd8f0dCXjtfaQ7P55Nwps7L0OhUkEsCFjxeA/06iTFxZQCRCcX4GJyAW5ml9S7TywS0NXVBn287NDXS4o+XnYIdLGBWMT/vYiIiIiIWktT81Am/a2gvSf9QP0E7v2JPdvdnn5qf9JlZUjIKYWvk2WDxR8LyytxKUWmHgSITi5AVpG8Xj9LUzF6dapeCdCn5uUhNefADRERERFRMzHpb0OGkPQD907giFpDhqwc0cn5iE6W4WJyAf5JKUBJhaJePydrs+qVAJ41AwGedpBamughYiIiIiIiw8Okvw0ZStJPpA8KpQq3sourVwOkFOBisgzX0gtR1UChCX8nK3V9gD5edujmbgtzE9YHICIiIiK6E5P+NsSkn0g75ZUKXEkrxEX1QEABEnJL6/UzEQvo5m6rXg3Q10sKfydriFgfgIiIiIg6OCb9bYhJP1HL5ZdU4J/U6i0BtfUBcksq6vWzMZOgd51tAX297OBqa66HiImIiIiI9IdJfxti0k/U+lQqFVILytRFAi8my3ApVYayyvr1AdxszdGn5qSAvp526OUphY056wMQERERkfFi0t+GmPQTtY0qhRI3sorV2wKik2WIzSjEneUBBAHo7GyNPp526OtdPRDQ1c0GphKRfgInIiIiImplTPrbEJN+Iv0prajClbRCRCcVILqmPkBKflm9fqYSEXp4VNcHqD060NfRkscGEhEREZFBYtLfhpj0E7UvOcVy/FOzEqB2VUBBaWW9flILE/T2lKJvTW2A3p52cLYx00PERERERETaYdLfhpj0E7VvKpUKSXmliK4pEHgxuQCX0wpRUaWs17eTnUXNSoDqYoE9O0lhZSbRQ9RERERERI1j0t+GmPQTGZ5KhRKxGUW3CwWmFOBGVjHu/C+iSAC6uNponBbQxdUaEjHrAxARERGR/jDpb0NM+omMQ7G8CpdSZNVFApOqBwLSZeX1+pmbiNCrk+axgZ72FqwPQERERERthkl/G2LST2S8MgvL1SsBLiZXDwgUlVfV6+dgZYo+ntXHBtYeHWhvZaqHiImIiIioI2DS34aY9BN1HEqlCvG5JbhYpz7A1fRCVCrq/6fUx9GyzmoAKXp4SGFuItZD1ERERERkbJj0tyEm/UQdm7xKgWvpRdUrApKrjw68lV1Sr59EJKCrm416JUAfLzsEuFhDLOK2ACIiIiLSDpP+NsSkn4juJCurvF0foGZVQHaRvF4/K1MxetVsC6gdCHCXmrM+ABERERHdFZP+NsSkn4juRaVSIV1Wrl4JcDG5AJdSZCipUNTr62xjhj6e1VsC+njZobenHaQWJnqImoiIiIjaq1ZN+hcsWKB1AG+//TYcHBy0vs8QMeknouZQKFW4mV2scWxgTHoRqpT1/7Ps72SFvjVFAvt42aGbuw3MJKwPQERERNRRtWrSLxKJEBoaClPTplWi/uuvvxAbGwt/f/+mR2zAmPQTUWspr1TgSpoM0cky9UBAYm5pvX4mYgHd3W2rBwFqtgX4O1lBxPoARERERB1CU/NQSVMfuGvXLri4uDSpr42NTVMfS0REdZibiNHfxwH9fW6vlMovqdA4MjA6uQB5JRW4mCLDxRQZgEQAgI25pGYAQFqzPcAOLrbmevokRERERNQeNCnp37RpE6RSaZMfumHDBri6ujY7KCIius3eyhQjurpgRNfqgVeVSoWU/DKNbQGXUmUoKq/CX3E5+CsuR32vu9RcvRKgj5cUvTpJYWPO+gBEREREHQUL+bUCLu8nIn2rUihxPbO4ZkVA9WqA65lFuLM8gCAAAc7W1acF1Ly6utnARCzST+BERERE1Cys3t+GmPQTUXtUIq/C5VSZemtAdHIBUgvK6vUzlYjQ08NWPRDQx9MOPo6WPDaQiIiIqB1r1aTf3t6+yb/85eXlNT1KI8Gkn4gMRXaRHP/UrgZIqS4WKCurrNfPztIEvT3t0NdTir7e1ccGOlmb6SFiIiIiImpIqxbyW7dunfrr3NxcrFq1CmPGjEFoaCgAIDIyEvv378fSpUtbFjUREemUs40ZRnVzxahu1XVXVCoVEnJL1VsCLqYU4EpaIQpKK/Hn9Wz8eT1bfa+nvUX1aoCaGgE9O9nC0lTzn5F0WRnic0rg52QFd6lFm342IiIiIqpP6+X9kyZNwsiRIzFnzhyN9i+//BKHDh3C7t27WzM+g8CZfiIyJhVVSsRmFCG6ZkXAxeQCxGUX485/LUQC0MXVpnpLgJcdMmXl+PzIDShV1ddWT+yFKQO89fMhiIiIiIyczvb0W1tbIzo6GgEBARrtcXFx6Nu3L4qLi5sXsQFj0k9Exq6ovBKXUmR1BgJkyCgsv+s9YgH4a/H9nPEnIiIi0oFWXd5fl6OjI/bs2YOFCxdqtO/ZsweOjo7aR0pERO2ejbkJhgQ4YUiAk7otQ1auPi3g+PVsXEkr1LhHoQK+PRGPBQ92qbcNgIiIiIjahtYz/WFhYXjhhRcwbtw4DBo0CAAQFRWFffv24ZtvvsHMmTN1EWe7xpl+Iuro0mVlGLrmSL0jAgHA1lyCJ0O8MC3UBz6OVm0fHBEREZERamoeqvXBzDNnzsTJkydha2uLnTt3YufOnbC1tcVff/2l04T/vffew5AhQ2BpaQk7O7sm3bN8+XIEBQXBysoK9vb2GD16NKKiojT65OXlYerUqbC1tYWdnR2ef/75DrlFgYioJdylFlg9sRfENSe9iATg4V7u8HG0RGF5Ff73VzxGfHwMszadwdHYLCgbGh0gIiIiolan9Uy/vrzzzjuws7NDSkoKvv32WxQUFNzznq1bt8LFxQX+/v4oKyvDp59+ih07diAuLg7Ozs4AgHHjxiE9PR0bNmxAZWUlZs2ahQEDBmDr1q1Njo0z/URE1dJlZUjIKYWvkyXcpRZQKlU4fj0b4ZEJOBZ7+yQAX0dLPDvYB5NDvCC1MNFjxERERESGSWeF/ADg5s2b2LRpE27duoV169bBxcUFf/zxB7y9vdGjR48WBX4vYWFhmDdvXpOS/jvV/qUcOnQIo0aNwrVr19C9e3ecPXsWISEhAIB9+/bhoYceQkpKCjw8PLR6LpN+IqLGJeSUYPPpRGw/l4yi8ioAgIWJGBP6dcL0UB8EufG/n0RERERNpbPl/cePH0evXr0QFRWFn3/+Wb0U/uLFi3jnnXeaH7GOVVRUYOPGjZBKpejTpw8AIDIyEnZ2duqEHwBGjx4NkUhUbxtAXXK5HIWFhRovIiK6O18nKyx9pDui3hyF9yf0QldXG5RVKrA1Kglj153AlA2R+ONSOqoUSn2HSkRERGQ0tE76Fy9ejFWrVuHgwYMwNTVVt99///04ffp0qwbXGn799VdYW1vD3Nwcn376KQ4ePAgnp+rq0xkZGXBxcdHoL5FI4ODggIyMjEafuXr1akilUvXLy8tLp5+BiMiYWJpK8Mwgb+yb9y9s+/dgPNTLDWKRgKj4PLy85QL+9eFRfHnkBnKK5foOlYiIiMjgaZ30X7p0CRMmTKjX7uLigpycHK2etXjxYgiCcNdXTEyMtiFqGDlyJKKjo3Hq1CmMHTsWTz75JLKyslr0zCVLlkAmk6lfycnJLXoeEVFHJAgCBvs74qup/fHXGyPx6v0BcLI2RbqsHB8fuI4hq49g/o/RiE4u0HeoRERERAZL64OT7ezskJ6eDj8/P432v//+G506ddLqWQsXLrxnxX9/f39tQ9RgZWWFgIAABAQEYPDgwQgMDMS3336LJUuWwM3Nrd4AQFVVFfLy8uDm5tboM83MzGBmZtaiuIiI6DZ3qQUWPtgVc+4PwO+X0hF+KhHRyQXY9Xcqdv2dij6eUkwP9cXDvd1hbiLWd7hEREREBkPrpP+pp57CG2+8gR07dkAQBCiVSpw8eRKLFi3C9OnTtXqWs7Ozuop+W1EqlZDLq5eMhoaGoqCgAOfPn0f//v0BAEeOHIFSqcSgQYPaNC4iIgLMJGJMCPbEhGBPXEwuQERkIn65mIaLKTIs3HER7/1+DU8N8MKzg33gYWeh73CJiIiI2j2tq/dXVFTglVdeQVhYGBQKBSQSCRQKBZ555hmEhYVBLNbNDExSUhLy8vKwd+9efPTRRzhx4gQAICAgANbW1gCAoKAgrF69GhMmTEBJSQnee+89PPbYY3B3d0dOTg7++9//YuvWrTh//rz6lIFx48YhMzMT69evVx/ZFxISwiP7iIjaidxiObadTcaW04lIk5UDAEQC8GB3N0wf4oNQf0cIgqDnKImIiIjalk6P7AOqk/DLly+juLgYwcHBCAwMbHawTTFz5kyEh4fXaz969ChGjBgBoHp/6KZNmzBz5kyUl5fjmWeeQVRUFHJycuDo6IgBAwbg7bffxoABA9T35+XlYc6cOfjll18gEokwadIkfP755+qBhKZg0k9EpHtVCiUOXctCRGQCTt3MVbcHulhj+hBfTAzuBCszrRewERERERkknSf9dBuTfiKitnU9swgRkQnYeSEVpRUKAICNmQRPhHhi2mAf+Ds3feCWiIiIyBDpLOlXqVT46aefcPToUWRlZUGp1DxPeefOnc2L2IAx6Sci0o/C8kr8fD4FEZGJiM8pUbcP7+KMGaE+GNHVBWIRl/4TERGR8WlqHqr1Osh58+Zhw4YNGDlyJFxdXbmPkoiI9MbW3ASzhvphRqgvTsTlIOJUAo7EZuHP69n483o2vB0sMW2wDyaHeMLO0lTf4RIRERG1Oa1n+h0cHPD999/joYce0lVMBocz/URE7UdSbim+j0rEj2eTISurBACYm4gwvm8nTA/1RXcP/neaiIiIDJ/Olvf7+fnhjz/+QFBQUIuDNBZM+omI2p+yCgX2RKciPDIR19IL1e0DfR0wfYgPxvRwg4lYpMcIiYiIiJpPZ0l/eHg49u3bh++++w4WFjwjGWDST0TUnqlUKpxLzEf4qQTsu5yBKmX1P3suNmaYOsgHTw/ygouNuZ6jJCIiItKOzpL+srIyTJgwASdPnoSvry9MTEw0rl+4cKF5ERswJv1ERIYhs7AcW6OSsPVMErKL5AAAE7GAcT3dMWOIL/p527FWDRERERkEnSX9Tz75JI4ePYonnniiwUJ+77zzTvMiNmBM+omIDEtFlRJ/XE5HRGQizifmq9t7drLF9FBfPNbHA+YmYj1GSERERHR3Okv6rayssH//fgwbNqzFQRoLJv1ERIbrcqoM4acSsOdiGiqqqo+htbM0wZQBXnh2kA+8HCz1HCERERFRfTpL+oOCgrB9+3b07t27xUEaCyb9RESGL7+kAj+eS8bmyESkFpQBAEQCMKqbK2aE+mJogCOX/hMREVG7obOk/7fffsMXX3yB9evXw9fXt6VxGgUm/URExkOhVOFITBbCTyXgr7gcdXtnZytMD/XFpP6esDaT6DFCIiIiIh0m/fb29igtLUVVVRUsLS3rFfLLy8trXsQGjEk/EZFxissqwubIRPx0PgUlFQoAgLWZBJP6dcK0UF8EuFjrOUIiIiLqqHR6ZN/dzJgxQ5vHGQUm/URExq2ovBK7/k5F+KkE3MwuUbcPC3DC9FAfjOrmCrGIS/+JiIio7egk6a+srMSLL76IpUuXws/Pr1UCNQZM+omIOgaVSoWTcbkIj0zA4WuZUNb8C9rJzgLTQn0wJcQL9lam+g2SiIiIOgSdzfRLpVJER0cz6a+DST8RUceTnFeKLVFJ2HY2CQWllQAAM4kIj/XxwIwhvujZSarnCImIiMiY6SzpnzFjBvr27Yv58+e3OEhjwaSfiKjjKq9UYO/FNISfSsCVtEJ1e38fe0wP9cG4nu4wlYj0GCEREREZI50l/atWrcInn3yCUaNGoX///rCystK4Pnfu3OZFbMCY9BMRkUqlwoWkAkREJuD3S+moVFT/8+pkbYZnBnlj6iBvuNqa6zlKIiIiMhY6S/rvtqxfEATcunVLm8cZBSb9RERUV1ZROX6ISsaWqERkFckBABKRgDE93TBziC9CfOwhCCz8R0RERM2ns6Sf6mPST0REDalUKLH/SgYiTiXiTMLtI227udtiRqgPHu/bCRamYj1GSERERIaqTZL+2ls7+mwFk34iIrqXq2mFiIhMwO7oVJRXKgEAUgsTPBniiWmDfeHtaKnnCImIiMiQNDUPbVZloYiICPTq1QsWFhawsLBA7969sXnz5mYHS0REZOy6e9hizaTeOL1kFN56qBu8HCwgK6vENyficd/HR/F82Fkcv54NpZIL8IiIiKj1SLS9Ye3atVi6dCnmzJmDoUOHAgD++usvvPTSS8jJyWFVfyIioruwszTF7OH+eG6YH45fz0LYqUT8eT0bh2OycDgmC35OVpg22AdPhHjC1txE3+ESERGRgWtWIb8VK1Zg+vTpGu3h4eFYvnw54uPjWzVAQ8Dl/URE1BK3soux+XQifjqXgiJ5FQDA0lSMif06YXqoL7q42ug5QiIiImpvdLan39zcHJcvX0ZAQIBG+40bN9CrVy+Ul5c3L2IDxqSfiIhaQ4m8Crv+TkVEZAKuZxar20P9HTFjiA9Gd3OFRNysnXlERERkZHS2pz8gIADbt2+v1/7jjz8iMDBQ28cRERFRDSszCZ4d7IP984Zj6+xBGNvDDSIBiLyVi5e+v4DhHx7Ff4/GIbdYru9QiYiIyEBoPdP/888/Y8qUKRg9erR6T//Jkydx+PBhbN++HRMmTNBJoO0ZZ/qJiEhXUgvKsDUqET+cSUZeSQUAwFQswiN93DEj1Bd9vOz0GyARERHphU6P7Dt//jw+/fRTXLt2DQDQrVs3LFy4EMHBwc2P2IAx6SciIl0rr1Tgt3/SER6ZgH9SZOr2vl52mDHEBw/1coeZRKzHCImIiKgt6TTpJ01M+omIqC1FJxcg4lQCfv0nHRUKJQDA0coUTw/0xtTB3nCXWug5QiIiItI1nSb9SqUScXFxyMrKglKp1Lg2fPhw7aM1cEz6iYhIH3KK5dh2Jgnfn05CRmF1IV2xSMCD3V0xY4gvBvk5QBAEPUdJREREuqCzpP/06dN45plnkJiYiDtvFQQBCoWieREbMCb9RESkT1UKJQ5ezUR4ZAJO38pTt3d1tcH0IT6YENwJlqYSPUZIRERErU1n1ftfeuklhISE4PLly8jLy0N+fr76lZeXd+8HNNN7772HIUOGwNLSEnZ2dk26Z/ny5QgKCoKVlRXs7e0xevRoREVFafTx9fWFIAgarzVr1ujgExAREemGRCzCuF7u2PbvUOyb9y88M8gbFiZixGYW4a1dlzHo/cNY+ctVJOSU6DtUIiIiamNaz/RbWVnh4sWLCAgI0FVMDXrnnXdgZ2eHlJQUfPvttygoKLjnPVu3boWLiwv8/f1RVlaGTz/9FDt27EBcXBycnZ0BVCf9zz//PGbPnq2+z8bGBlZWVk2OjTP9RETU3sjKKvHT+RRsjkxAQm6pun1EV2fMCPXFfV2cIRJx6T8REZGh0tny/vvvvx+vv/46xo4d2+IgmyMsLAzz5s1rUtJ/p9q/lEOHDmHUqFEAqpP+efPmYd68ec2OiUk/ERG1V0qlCsdvZCPiVAKOXc9G7b/6Po6WmDbYB5P7e0FqaaLfIImIiEhrTc1Dtd7g9+qrr2LhwoXIyMhAr169YGKi+YtC7969tY+2DVRUVGDjxo2QSqXo06ePxrU1a9bg3Xffhbe3N5555hnMnz8fEknjfzVyuRxyuVz9fWFhoc7iJiIiagmRSMDIri4Y2dUFCTkl+P50IrafS0ZibilW/XYNnxy4jvHBnTA91Afd3DlwTUREZGy0nukXieqXARAEASqVqk0K+Wk70//rr7/iqaeeQmlpKdzd3bF7924MGDBAfX3t2rXo168fHBwccOrUKSxZsgSzZs3C2rVrG33m8uXLsWLFinrtnOknIiJDUFpRhd1/pyEiMgExGUXq9oF+DpgR6osHe7jCRKx12R8iIiJqQzpb3p+YmHjX6z4+Pk1+1uLFi/HBBx/ctc+1a9cQFBSk/l7bpL+kpATp6enIycnBN998gyNHjiAqKgouLi4N9v/uu+/w4osvori4GGZmZg32aWim38vLi0k/EREZFJVKhTPxeYiITMS+KxlQKKt/JXCzNcfUQd54aqA3nG0a/reQiIiI9EtnSX9rys7ORm5u7l37+Pv7w9TUVP19S/b0A0BgYCCee+45LFmypMHrV65cQc+ePRETE4OuXbs26Znc009ERIYuXVaGrVFJ+OFMEnKKKwAAJmIBD/dyx/Qhvgj2soMgsPAfERFRe9Gqe/r37t2LcePG1du/35jff/8dI0eOhIWFxV37OTs7q6votxWlUqkxS3+n6OhoiESiRlcCEBERGSN3qQUWPtgVc+4PwB+XMhAemYC/kwqwOzoNu6PT0NtTiumhvniktzvMTcT6DpeIiIiaqEkb9iZMmKDVzPpTTz2F9PT05sbUoKSkJERHRyMpKQkKhQLR0dGIjo5GcXGxuk9QUBB27doFoHpZ/5tvvonTp08jMTER58+fx3PPPYfU1FRMnjwZABAZGYl169bh4sWLuHXrFrZs2YL58+fj2Wefhb29favGT0REZAjMJGKMD+6EXf83FHvnDMWkfp4wlYjwT4oMi3ZcROjqw/hgXwxS8kvv/TAiIiLSuybN9KtUKsycObPRPe53Ki8vb1FQDVm2bBnCw8PV3wcHBwMAjh49ihEjRgAAYmNjIZPJAABisRgxMTEIDw9HTk4OHB0dMWDAAJw4cQI9evQAAJiZmWHbtm1Yvnw55HI5/Pz8MH/+fCxYsKDV4yciIjI0vT3t8MmTdnjzoSD8eC4Z30cmIk1Wjq+P3cSG4zcxupsrZg7xRWhnRy79JyIiaqeatKd/1qxZWj/4o48+gpOTU7OCMjTc009ERB1BlUKJwzFZiIhMwMm42zV5AlysMSPUBxP6ecLaTOvTgImIiKgZDKKQn7Fg0k9ERB3NjcwiREQm4ucLKSitqD6u18ZMgkn9PTEt1Aedna31HCEREZFxY9Lfhpj0ExFRR1VYXomd51MQEZmIWzkl6vZ/BTphRqgvRga5QCzi0n8iIqLWxqS/DTHpJyKijk6pVOGvuBxERCbgcEwWan+78LS3wLTBPpgywAt2lqZ3fwgRERE1GZP+NsSkn4iI6LbkvFJ8fzoR284mQ1ZWCQAwk4gwvm8nTB/igx4eUj1HSEREZPiY9LchJv1ERET1lVUosPdiKsJOJeJaeqG6PcTHHtOH+GJsDzfklsgRn1MCPycruEst9BgtERGRYWHS34aY9BMRETVOpVLhfGI+wiMT8celdFQpq3/1sDGToFheBRUAkQCsntgLUwZ46zdYIiIiA9HUPFTrc3Xi4+Nx4sQJJCYmorS0FM7OzggODkZoaCjMzc1bFDQREREZH0EQEOLrgBBfB2Q93A1bopKw+XQi8koq1H2UKmDxz5dQUFqJh3q5w8vBUo8RExERGY8mz/Rv2bIFn332Gc6dOwdXV1d4eHjAwsICeXl5uHnzJszNzTF16lS88cYb8PHx0XXc7Qpn+omIiLTz5/VsTP/uTKPXPe0tMKSzI4Z0dkJoZ0e42nJigYiIqK5WnekPDg6GqakpZs6ciZ9//hleXl4a1+VyOSIjI7Ft2zaEhITgq6++wuTJk1v2CYiIiMhoBbpaQyRUz/DXEgD06iTF1fRCpOSXYfu5FGw/lwIA6OxshSGdnTCksyMG+zvC3oonARARETVFk2b69+/fjzFjxjTpgbm5uUhISED//v1bHJyh4Ew/ERGR9n48m4Q3d16GQqWCWBDw/sSemDLAGyXyKpxNyEPkzVycupmLy2ky3PnbSjd325qVAI4Y6OcAG3MT/XwIIiIiPWEhvzbEpJ+IiKh50mVlSMgpha+TZaPV+2WllTgdn1szCJCD65nFGtfFIgG9OknV2wH6+9jDwlTcFuETERHpTasn/WlpaVi7di2WLVtW74EymQyrVq3CokWL4Orq2rLIDRCTfiIioraTXSRH5K1cRN7MQeTNXCTklmpcNxWLEOxtV70dIMARfTztYCoR6SlaIiIi3Wj1pH/RokUoLCzExo0bG7z+0ksvQSqV4oMPPmhexAaMST8REZH+pBaUqVcBnIrLRUZhucZ1CxMxBvg5YEhnR4T6O6JnJynEIkFP0RIREbWOVk/6e/bsifXr12PYsGENXj916hRmz56NK1euNC9iA8akn4iIqH1QqVRIyC2tHgC4Wb0loO7RgABgYy7BIL/qegBDAhzRxcUGIg4CEBGRgWn1pN/KygrXrl2Dt7d3g9eTkpLQrVs3lJSUNC9iA8akn4iIqH1SKlW4nlWEU3HVRQGjbuWiSF6l0cfRyhSDa4oCDunsBF9HSwgCBwGIiKh9a9Uj+wDAwsICCQkJjSb9CQkJsLBouAAPERERkT6IRAKC3GwR5GaL54b5oUqhxJW0wupVALdycTY+D7klFfjtn3T89k86AMBdao7QmgGA0M6O6GTH32+IiMhwNXmm/+GHH4aHhwe++eabBq+/8MILSEtLw++//96qARoCzvQTEREZpooqJS6mFNSsBMjB30kFqFAoNfr4OloitLMjQjs7IdTfEc42ZnqKloiI6LZWn+lftGgRHnjgAUilUvznP/9RV+nPzMzEhx9+iLCwMBw4cKDlkRMRERG1EVOJCAN8HTDA1wGvjQ5EWYUC5xPz1TUB/kkpQEJuKRJyS/HDmWQAQBdXa/UqgMF+jpBamuj5UxARETWuyTP9ALBhwwa89tprqKyshK2tLQRBgEwmg4mJCT799FO8/PLLuoy13eJMPxERkXEqLK/E2fg8nLpZXRPgWnqhxnVBAHp6SKtPBujsiAG+DrAya/KcChERUbO1eiG/Wqmpqdi+fTvi4uKgUqnQpUsXPPHEE/D09Gxx0IaKST8REVHHkFdSgahbuTWDADm4ma1ZwFgiEtDXy65mEMAJwd52MDcR6ylaIiIyZjpL+qk+Jv1EREQdU2ZhOSJrBgBOxuUitaBM47qZRIT+PvbqQYDenlKYiEV6ipaIiIyJzpL+vXv3NvwgQYC5uTkCAgLg5+enXbQGjkk/ERERAUByXqm6HsCpm7nILpJrXLcyFWOgn4O6JkB3d1uIRDwekIiItKezpF8kEkEQBNx5W22bIAgYNmwYdu/eDXt7++ZFb2CY9BMREdGdVCoVbmYXVw8AxFUfESgrq9ToY2dpgsF+jhgS4IghnR3R2dkagsBBACIiujedJf2HDx/GW2+9hffeew8DBw4EAJw5cwZLly7F22+/DalUihdffBGDBg3Ct99+27JPYSCY9BMREdG9KJUqXMsorNkOkIuoW7koqVBo9HG2McOQzo41Lyd4OVjqKVoiImrvdJb09+zZExs3bsSQIUM02k+ePIl///vfuHLlCg4dOoTnnnsOSUlJzYvewDDpJyIiIm1VKpS4lCpT1wQ4l5APeZVSo08nO4vqAYAAR4T6O8FNaq6naImIqL3RWdJvYWGBs2fPomfPnhrtly5dwsCBA1FWVobExER069YNpaWlzYvewDDpJyIiopYqr1Tg76QCRNbUBIhOLkCVUvPXNH9nK/UqgMH+jnCwMtVTtEREpG86S/qHDRsGGxsbREREwNnZGQCQnZ2N6dOno6SkBH/++ScOHTqEV155BbGxsS37FAaCST8RERG1thJ5Fc4m5Km3A1xOk+HO39q6uduqtwMM9HOAjbmJfoIlIqI2p7OkPzY2Fo8//jji4+Ph5eUFAEhOToa/vz/27NmDLl26YPfu3SgqKsK0adNa9ikMBJN+IiIi0jVZaSWi4qsHACJv5iI2s0jjulgkoFcnac3xgI4I8XGAhalYT9ESEZGu6SzpBwClUokDBw7g+vXrAICuXbvigQcegEjUMc+dZdJPREREbS27SI7Tt2oHAXKQkKu5rdJULEJfbzv1doC+XnYwlXTM39WIiIyRTpP+WuXl5TAzM2uTo2Xee+89/Pbbb4iOjoapqSkKCgq0uv+ll17Chg0b8Omnn2LevHnq9ry8PLz66qv45ZdfIBKJMGnSJHz22WewtrZu8rOZ9BMREZG+pRaUqYsCRt7MRbqsXOO6hYkYIb72GNLZCUM6O6JnJynEIh4PSERkqJqah0q0fbBSqcR7772H9evXIzMzE9evX4e/vz+WLl0KX19fPP/88y0KvDEVFRWYPHkyQkNDtT4KcNeuXTh9+jQ8PDzqXZs6dSrS09Nx8OBBVFZWYtasWfj3v/+NrVu3tlboRERERDrXyc4CT/T3xBP9PaFSqZCQW6oeAIi8mYvckgqcuJGDEzdyAAA25hIM8nNUnw7QxcUGIg4CEBEZHa2T/lWrViE8PBwffvghZs+erW7v2bMn1q1bp7Okf8WKFQCAsLAwre5LTU3Fq6++iv379+Phhx/WuHbt2jXs27cPZ8+eRUhICADgiy++wEMPPYSPP/64wUECIiIiovZOEAT4OVnBz8kKUwf5QKVS4XpmMU7VnAxw+lYuisqrcOhaJg5dywQAOFqZYnBnR4T6Vw8E+DlZtclqTiIi0i2tk/6IiAhs3LgRo0aNwksvvaRu79OnD2JiYlo1uJZSKpWYNm0a/vOf/6BHjx71rkdGRsLOzk6d8APA6NGjIRKJEBUVhQkTJrRluEREREQ6IQgCurrZoKubDWYN9YNCqcKVNBlO1ZwMcDY+D7klFfjtn3T89k86AMDN1lxdFHBIgBM62Vno+VMQEVFzaJ30p6amIiAgoF67UqlEZWVlqwTVWj744ANIJBLMnTu3wesZGRlwcXHRaJNIJHBwcEBGRkajz5XL5ZDL5ervCwsLWydgIiIiojYgFgno7WmH3p52eOm+zqioUuJiSgFOxVXXBPg7qQAZheXY+Xcqdv6dCgDwcbSsGQRwQqi/I5xtzPT8KYiIqCm0Tvq7d++OEydOwMfHR6P9p59+QnBwsFbPWrx4MT744IO79rl27RqCgoK0DRPnz5/HZ599hgsXLrT60rTVq1ertxsQERERGTpTiQgDfB0wwNcBr40ORFmFAucT8xF5q3o7wD8pMiTmliIxtxQ/nEkGAHRxtcaQzk4I7eyIwX6OkFqa6PlTEBFRQ7RO+pctW4YZM2YgNTUVSqUSO3fuRGxsLCIiIvDrr79q9ayFCxdi5syZd+3j7++vbYgAgBMnTiArKwve3t7qNoVCgYULF2LdunVISEiAm5sbsrKyNO6rqqpCXl4e3NzcGn32kiVLsGDBAvX3hYWF8PLyalacRERERO2NhakYwwKdMCzQCQBQVF6Jswl5NSsBcnE1vRDXM4txPbMYYacSIAhADw9b9SDAQF8HWJlp/WsmERHpQLOO7Dtx4gRWrlyJixcvori4GP369cOyZcvw4IMP6iJGDWFhYZg3b949j+zLzc1Fenq6RtuYMWMwbdo0zJo1C127dsW1a9fQvXt3nDt3Dv379wcAHDhwAGPHjkVKSkqTC/nxyD4iIiLqSPJKKhB1K7emJkAObmaXaFyXiAT08bJT1wTo520PcxOxnqIlIjJOTc1Dm5X060NSUhLy8vKwd+9efPTRRzhx4gQAICAgANbW1gCAoKAgrF69utECfL6+vpg3bx7mzZunbhs3bhwyMzOxfv169ZF9ISEhWh3Zx6SfiIiIOrLMwnJE1gwAnLqZi5T8Mo3rphIRQnzs1TUBentKYSIW6SlaIiLj0NQ81GDWXS1btgzh4eHq72vrBxw9ehQjRowAAMTGxkImk2n13C1btmDOnDkYNWoURCIRJk2ahM8//7zV4iYiIiIydq625hgf3AnjgzsBAJLzSjUGAbKK5OqTAoDrsDIVY6Cfg3o7QHd3W4hEPB6QiEgXmjTTb29v3+RieHl5eS0OytBwpp+IiIioYSqVCjezSxBZMwAQeSsXBaWaJz7ZWZpgsJ8jhgQ4YkhnR3R2tm71QsxERMamVWf6161bp/46NzcXq1atwpgxYxAaGgqg+rz7/fv3Y+nSpS2LmoiIiIiMiiAICHCxRoCLNaaF+kKpVOFaRmHNSoBcRNUMAuy7koF9V6qPTHa2MUOof/UAwJDOTvBysFAPAqTLyhCfUwI/Jyu4Sy30+dGIiAyC1nv6J02ahJEjR2LOnDka7V9++SUOHTqE3bt3t2Z8BoEz/URERETNU6lQ4lKqTL0d4FxCPuRVSo0+newsMKSzI0QiYMe5FChVgEgAVk/shSkDvBt5MhGRcdNZIT9ra2tER0cjICBAoz0uLg59+/ZFcXFx8yI2YEz6iYiIiFpHeaUC0ckF1VsBbubg76QCVCkb/3V1fF8PBLraoJOdBTrZW8DDzgKuNmaQsFAgERk5nRXyc3R0xJ49e7Bw4UKN9j179sDR0VH7SImIiIiIapibiDHY3xGD/R2BB7qgRF6Fc4n52HEuGb/+k16v/+7otHptYpEAN1tzeNiZo5Nd9UBA7YCAZ833VmYGU8+aiKhFtP6v3YoVK/DCCy/g2LFjGDRoEAAgKioK+/btwzfffNPqARIRERFRx2VlJsF9XZzRxdUav19KR91Jf0EAZob6QlZeibSCMqQWlCG9oBxVShVSa74/i/wGnyu1MFEPCHjaW9QMEFiqBwqcrM14ogARGQWtl/cD1Un+559/jmvXrgEAunXrhrlz56oHAToaLu8nIiIi0r0fzybhzZ2XoVCpIBYEvD+xZ709/QqlCtlFcqQWlKkHAtIKypCaX6YeCCgqr7rne5mKRXCvu1Kg9lWzYsBdag5zE7GuPioR0T3pbE8/1cekn4iIiKhtpMvKkJBTCl8ny2ZX7y8sr0R6QTlSC0qRWlCO1HzNAYLMwnLcpYyAmpO1GTrZmVcPBEhvDwjUDhDYWZrw6EEi0plWTfpLSkpgZWXV5DfXtr+hY9JPREREZDwqFUpkyMo1VwoUlCG1oFy9aqCsUnHP51iaiuGhsVLAXP21h50F3KTmMGHBQSJqplYt5BcQEIDXXnsNM2bMgLu7e4N9VCoVDh06hLVr12L48OFYsmRJ8yInIiIiItIjE7EIXg6W8HKwbPC6SqVCQWmlertA7UBAmqx2G0E5corlKK1QIC6rGHFZDZ9uJRIAV9v6xQY71akvYGNuosuPSkQdQJNm+mNjY/Hmm2/it99+Q58+fRASEgIPDw+Ym5sjPz8fV69eRWRkJCQSCZYsWYIXX3wRYnHH2ePEmX4iIiIiqqu8UoF0WXm9egJ1Cw5WKJT3fI6tuaROsUELjZUCnvYWcGbBQaIOSyd7+pOSkrBjxw6cOHECiYmJKCsrg5OTE4KDgzFmzBiMGzeuQyX7tZj0ExEREZE2lEoVckrkNfUEqusLpBWUI6WmvkCarAwFpZX3fI6JWIC7tPr0gbpHEtatL8CCg0TGiYX82hCTfiIiIiJqbcXyKqQXlCGl7haCgtpBgjJkFJZD0YSKg45Wpupig7UDAnW3EDhYmbLgIJEBatU9/URERERE1LaszSQIdLVBoKtNg9erFEpkFsk1thDceUxhSYUCuSUVyC2pwD8psgafY24i0jh14M4tBK625jCVsOAgkaFi0k9EREREZIAkYpE6UR/gW/+6SqVCYVkVUmq2Dtw+heD2qoGsIjnKK5W4lV2CW9klDb6PIACuNubqLQTVKwUsNAoQ2rLgIFG7xaSfiIiIiMgICYIAqaUJpJZS9PCQNthHXqVAhqy8zkDA7foCtQMEFVVKZBSWI6OwHBeSChp8jo2ZpE4tgdtbB2oLELrYmEPMgoNEesGkn4iIiIiogzKTiOHjaAUfR6sGr6tUKuSWVKhXBmisFJBVDxLklVSgSF6F2MwixGYWNfgciUiAm7TxYoMeduawNGVqQqQLTf5/1sqVK7Fo0SJYWjZ8XikRERERERkXQRDgZG0GJ2sz9PGya7BPaUWVemVA3YKDtQMEGbJyVClVSMkvQ0p+Gc408l72libqgoN3biHwsLOAkzULDhI1R5Or94vFYqSnp8PFxUXXMRkcVu8nIiIiImqYQqlCVlFtTYFyjUGB2kGCInnVPZ9jKhHVGQi4vYWgU82qATepOcwkmscTpsvKEJ9TAj8nK7hLLXT1EYn0otWr9/NkPyIiIiIi0pZYJMBdagF3qQX6+zTcp7C8UmOVQErt0YT51fUFMovKUVGlRHxOCeJzGi846Gxtpt46UFRWiRM3cqACIBKA1RN7YcoAb919UKJ2SquNM1xOQ0RERERErc3W3AS2biYIcmt4trKiSonMwnKNkwdS67zSCspQXqlEVpEcWUVyRCcXaNyvVAFv7ryM4V2cOeNPHY5WSX+XLl3umfjn5eW1KCAiIiIiIqK6TCUieDlYwsuh4fpiKpUK+aWVSM2vHgQ4GZeDzacTNfooVCok5JQy6acOR6ukf8WKFZBKGz7ug4iIiIiISB8EQYCDlSkcrEzRy1OKPl5SbIlKhLLODmWxIMDXiUXJqePRKul/6qmnWMiPiIiIiIjaNXepBVZP7IU3d16GQqWCWBDw/sSenOWnDqnJST/38xMRERERkaGYMsAbw7s4IyGnFL5Olkz4qcNi9X4iIiIiIjJKtacGEHVkTU76lUqlLuMgIiIiIiIiolYm0ncARERERERERKQbTPqJiIiIiIiIjBSTfiIiIiIiIiIjxaSfiIiIiIiIyEgZTNL/3nvvYciQIbC0tISdnZ3W97/00ksQBAHr1q3TaPf19YUgCBqvNWvWtE7QRERERERERHrU5Or9+lZRUYHJkycjNDQU3377rVb37tq1C6dPn4aHh0eD11euXInZs2erv7exsWlRrERERERERETtgcEk/StWrAAAhIWFaXVf6v+3d+fhUdb3/v9fM9nXyb4xSQADgsgSEuQg1h+IitQLRSVa6wK2x1YPqAh6BOteK3qsFlsrilcPoN/jUUFAughVVFwOVglEwQUIW1YI2SYbmYSZ+f0RMhACmMBM7snk+biuuUju+cz9eWPval75bKWluuuuu7R+/XpdeeWVJ20TFRWllJSUsy0RAAAAAACf0mum958Jp9OpW265Rffff7+GDRt2ynZPP/204uPjlZ2drWeffVZHjhw57X3tdrvq6uo6vAAAAAAA8DW9ZqT/TDzzzDMKDAzU3Xfffco2d999t0aPHq24uDj93//9nxYsWKDy8nI9//zzp/zMwoUL3TMPAAAAAADwVYaO9M+fP7/TJnonvn744Yczund+fr5eeOEFLVu2TCaT6ZTt5s6dqwkTJmjEiBG644479Nxzz+lPf/qT7Hb7KT+zYMEC2Ww296u4uPiMagQAAAAAwJsMHemfN2+eZs6cedo2AwcOPKN7f/rpp6qoqFBGRob7msPh0Lx587Ro0SLt27fvpJ8bO3asjhw5on379uncc889aZuQkBCFhIScUV0AAAAAAN/S3NysFStWaM2aNaquqVZcbJymTZumvLw8hYaGGl3eWTE09CcmJioxMdEr977lllt06aWXdrg2efJk3XLLLbrttttO+bmCggKZzWYlJSV5pS4AAAAAgO9Yu3atZv5ipmqqahQ5OFIBMQFylDq0atUq3XPvPVq+dLmmTp1qdJlnrNes6S8qKlJ1dbWKiorkcDhUUFAgScrKylJkZKQkaciQIVq4cKGuueYaxcfHKz4+vsM9goKClJKS4h7B37Rpk/71r39p4sSJioqK0qZNm3Tvvffq5ptvVmxsbI/+/QAAAAAAPWvt2rW65pprFDkqUoPuH6SQlGMzuu0H7Dr49kFNmzZNq1ev1lVXXWVgpWeu14T+Rx55RMuXL3d/n52dLUn66KOPNGHCBEnSjh07ZLPZunzPkJAQvfnmm3rsscdkt9s1YMAA3XvvvZo7d65HawcAAAAA+Jbm5mbN/MVMRY6KVPrsdJnMHfeCC0kJUfrsdBW/WKyZv5ipspKyXjnV3+RyuVxGF9Hb1dXVyWKxyGazKTo62uhyAAAAAAA/4vXXX9ett96qQU93HOE/kb3crl0Ldun111/XzTff3IMVnl5Xc6ihu/cDAAAAAGCENWvWKHJw5GkDvySFpIYocnCkVq9e3UOVeRahHwAAAADQ51TXVCsgJqBLbc0xZlXXVHu5Iu8g9AMAAAAA+py42Dg5ah1dauusdSouNs7LFXkHoR8AAAAA0OdMmzZNDTsbZD9gP207e7ldDTsbdM011/RQZZ5F6AcAAAAA9Dl5eXmKjY/VwbcPyuU8+f72LqdLB1ccVGx8rKZPn97DFXoGoR8AAAAA0OeEhoZq+dLlaihoUPGLxZ1G/O3ldhW/WKyGggYtX7q8Vx7XJ0mBRhcAAAAAAIARpk6dqtWrV2vmL2Zq1/xdihwcKXOMWc5apxp2Nig2PlZr1qzR1KlTjS71jBH6AQAAAAB91lVXXaWykjKtXLlSq1evVnVNteKscbrm4Ws0ffr0XjvC387kcrlOvngBXWaz2RQTE6Pi4mJFR0cbXQ4AAAAAwM/V1dUpPT1dtbW1slgsp2zHSL8H1NfXS5LS09MNrgQAAAAA0JfU19efNvQz0u8BTqdTZWVlioqKkslkMrqcU2r/TRAzEtBVPDPoLp4ZdBfPDLqLZwbdwfOC7upNz4zL5VJ9fb3S0tJkNp96j35G+j3AbDbLarUaXUaXRUdH+/wDDN/CM4Pu4plBd/HMoLt4ZtAdPC/ort7yzJxuhL8dR/YBAAAAAOCnCP0AAAAAAPgpQn8fEhISokcffVQhISFGl4JegmcG3cUzg+7imUF38cygO3he0F3++MywkR8AAAAAAH6KkX4AAAAAAPwUoR8AAAAAAD9F6AcAAAAAwE8R+gEAAAAA8FOE/j7iz3/+s/r376/Q0FCNHTtWX375pdElwYd98sknmjp1qtLS0mQymbRmzRqjS4IPW7hwocaMGaOoqCglJSVp2rRp2rFjh9FlwYctXrxYI0aMUHR0tKKjozVu3Di99957RpeFXuTpp5+WyWTSnDlzjC4FPuqxxx6TyWTq8BoyZIjRZcHHlZaW6uabb1Z8fLzCwsI0fPhwbd682eiyzhqhvw946623NHfuXD366KPasmWLRo4cqcmTJ6uiosLo0uCjGhsbNXLkSP35z382uhT0Ahs3btSsWbP0xRdf6P3331dra6suv/xyNTY2Gl0afJTVatXTTz+t/Px8bd68WZdccomuvvpqffvtt0aXhl7gq6++0iuvvKIRI0YYXQp83LBhw1ReXu5+ffbZZ0aXBB9WU1Oj8ePHKygoSO+9956+++47Pffcc4qNjTW6tLPGkX19wNixYzVmzBi9+OKLkiSn06n09HTdddddmj9/vsHVwdeZTCatXr1a06ZNM7oU9BKHDh1SUlKSNm7cqIsvvtjoctBLxMXF6dlnn9Uvf/lLo0uBD2toaNDo0aP10ksv6cknn9SoUaO0aNEio8uCD3rssce0Zs0aFRQUGF0Keon58+fr888/16effmp0KR7HSL+fa2lpUX5+vi699FL3NbPZrEsvvVSbNm0ysDIA/spms0lqC3HAj3E4HHrzzTfV2NiocePGGV0OfNysWbN05ZVXdvi5BjiVXbt2KS0tTQMHDtRNN92koqIio0uCD1u7dq1yc3OVl5enpKQkZWdn69VXXzW6LI8g9Pu5yspKORwOJScnd7ienJysAwcOGFQVAH/ldDo1Z84cjR8/Xueff77R5cCHbdu2TZGRkQoJCdEdd9yh1atX67zzzjO6LPiwN998U1u2bNHChQuNLgW9wNixY7Vs2TKtW7dOixcv1t69e/WTn/xE9fX1RpcGH7Vnzx4tXrxYgwYN0vr163XnnXfq7rvv1vLly40u7awFGl0AAMB/zJo1S9u3b2fdJH7Uueeeq4KCAtlsNq1cuVIzZszQxo0bCf44qeLiYt1zzz16//33FRoaanQ56AWmTJni/nrEiBEaO3asMjMz9fbbb7OMCCfldDqVm5urp556SpKUnZ2t7du36+WXX9aMGTMMru7sMNLv5xISEhQQEKCDBw92uH7w4EGlpKQYVBUAfzR79mz97W9/00cffSSr1Wp0OfBxwcHBysrKUk5OjhYuXKiRI0fqhRdeMLos+Kj8/HxVVFRo9OjRCgwMVGBgoDZu3Kg//vGPCgwMlMPhMLpE+LiYmBgNHjxYhYWFRpcCH5WamtrpF89Dhw71i2UhhH4/FxwcrJycHG3YsMF9zel0asOGDaydBOARLpdLs2fP1urVq/Xhhx9qwIABRpeEXsjpdMputxtdBnzUpEmTtG3bNhUUFLhfubm5uummm1RQUKCAgACjS4SPa2ho0O7du5Wammp0KfBR48eP73Tk8M6dO5WZmWlQRZ7D9P4+YO7cuZoxY4Zyc3N1wQUXaNGiRWpsbNRtt91mdGnwUQ0NDR1+E753714VFBQoLi5OGRkZBlYGXzRr1iy98cYbevfddxUVFeXeL8RisSgsLMzg6uCLFixYoClTpigjI0P19fV644039PHHH2v9+vVGlwYfFRUV1WmfkIiICMXHx7N/CE7qvvvu09SpU5WZmamysjI9+uijCggI0I033mh0afBR9957ry688EI99dRTuv766/Xll19qyZIlWrJkidGlnTVCfx9www036NChQ3rkkUd04MABjRo1SuvWreu0uR/QbvPmzZo4caL7+7lz50qSZsyYoWXLlhlUFXzV4sWLJUkTJkzocH3p0qWaOXNmzxcEn1dRUaFbb71V5eXlslgsGjFihNavX6/LLrvM6NIA+ImSkhLdeOONqqqqUmJioi666CJ98cUXSkxMNLo0+KgxY8Zo9erVWrBggZ544gkNGDBAixYt0k033WR0aWfN5HK5XEYXAQAAAAAAPI81/QAAAAAA+ClCPwAAAAAAforQDwAAAACAnyL0AwAAAADgpwj9AAAAAAD4KUI/AAAAAAB+itAPAAAAAICfIvQDAAAAAOCnCP0AAAAAAPgpQj8AAAAAAH6K0A8AAAAAgJ8i9AMAAAAA4KcI/QAAAAAA+ClCPwAAAAAAfirQ6AL8gdPpVFlZmaKiomQymYwuBwAAAADg51wul+rr65WWliaz+dTj+YR+DygrK1N6errRZQAAAAAA+pji4mJZrdZTvk/o94CoqChJbf+wo6OjDa4GAAAAAODv6urqlJ6e7s6jp0Lo94D2Kf3R0dGEfgAAAADoZZqbm7VixQqtWbNG1TXViouN07Rp05SXl6fQ0FCjyzutH1tizkZ+AAAAAIA+a+3atUqzpunWW2/VP7f/U1sbt+qf2/+pW2+9VWnWNP31r381usSzwkg/AAAAAKBPWrt2ra655hpFjorUoPsHKSQlxP2e/YBdB98+qGnTpmn16tW66qqrDKz0zJlcLpfL6CJ6u7q6OlksFtlsNqb3AwAAAEAv0NzcrDRrmhyZDqXPTpfJ3HmavMvpUvGLxQrYH6CykjKfmurf1RzqV9P7f/e73+nCCy9UeHi4YmJiuvSZmTNnymQydXhdccUV3i0UAAAAAGCoFStWqKaqRsnXJ5808EuSyWxScl6yaqpqtHLlyh6u0DP8KvS3tLQoLy9Pd955Z7c+d8UVV6i8vNz9+t///V8vVQgAAAAA8AVr1qxR5ODIDlP6TyYkNUSRgyO1evXqHqrMs/xqTf/jjz8uSVq2bFm3PhcSEqKUlBQvVAQAAAAA8EXVNdUKiAnoUltzjFnVNdVersg7/Gqk/0x9/PHHSkpK0rnnnqs777xTVVVVp21vt9tVV1fX4QUAAAAA6D3iYuPkqHV0qa2z1qm42DgvV+QdfT70X3HFFXrttde0YcMGPfPMM9q4caOmTJkih+PU/+MvXLhQFovF/UpPT+/BigEAAAAAZ2vatGlq2Nkg+wH7advZy+1q2Nmga665pocq8yyf371//vz5euaZZ07b5vvvv9eQIUPc3y9btkxz5sxRbW1tt/vbs2ePzjnnHH3wwQeaNGnSSdvY7XbZ7ccejLq6OqWnp7N7PwAAAAD0En1l936fX9M/b948zZw587RtBg4c6LH+Bg4cqISEBBUWFp4y9IeEhCgk5PSbPQAAAAAAfFdoaKiWL12uadOmqfjFYiVfn9xhUz97uV0HVxxUQ0GD1qxZ41OBvzt8PvQnJiYqMTGxx/orKSlRVVWVUlNTe6xPAAAAAEDPmzp1qlavXq2Zv5ipXfN3KXJwpMwxZjlrnWrY2aDY+FitWbNGU6dONbrUM+ZXa/qLiopUUFCgoqIiORwOFRQUqKCgQA0NDe42Q4YMcR+10NDQoPvvv19ffPGF9u3bpw0bNujqq69WVlaWJk+ebNRfAwAAAADQQ6666iqVlZTp9ddf1+XnX67REaN1+fmX6/XXX1dZSVmvDvxSL1jT3x0zZ87U8uXLO13/6KOPNGHCBEmSyWTS0qVLNXPmTB0+fFjTpk3T1q1bVVtbq7S0NF1++eX67W9/q+Tk5C7329W1FAAAAAAAeEJXc6hfhX6jEPoBAAAAAD2pqznUr6b3AwAAAACAYwj9AAAAAAD4KUI/AAAAAAB+itAPAAAAAICfIvQDAAAA8EvltsP6v92VKrcdNroUwDCBRhcAAAAAAJ721ldFWrBqm5wuyWySFl47XDeMyTC6LKDHEfoBAAAA9Fr1za3aX9WkfVWN2lfZqH1VTdp1sF5fl9jcbZwu6cFV23Xx4ESlWsIMrBboeYR+AAAAAD6tvrlV+yo7Bvv9VY3aV9WoyoaWLt3D4XJpX2UToR99DqEfAAAAgOHqmlvdgb7tz7aAv7+qSVWNpw/2CZHByoyPUGZ8uAbERyg6PEiPrf1WLtexNgEmk/onhHv5bwH4HkI/AAAAgB5ha2ptC/NVjdpX2TZav7eqLdhX/2iwD1H/+HBlxkdoQEL7nxHKiA9XdGhQp/ahgWY9uGq7HC6XAkwmPXXt+Yzyo08i9AMAAADwmNqmFvf0+71HR+rb/mxUTVPraT+bGNUW7PvHR6h/QtvIff+jI/hRJwn2p3PDmAxdPDhR+yqb1D8hnMCPPstjoX/u3Lnd/sxDDz2kuLg4T5UAAAAAoAfUNLacZMS+7c/aHwn2SVEhR0N922j98V9Hhnh2TDLVEkbYR59ncrmOX+ly5sxms8aNG6fg4OAutf/ss8+0Y8cODRw40BPdG6qurk4Wi0U2m03R0dFGlwMAAACcFZfLpZr2qfjHb5x39Gvb4dMH++TokLbp9/ERykxoW2ffvuY+wsPBHuiruppDPfr/uNWrVyspKalLbaOiojzZNQAAAIBucLlcqm5scW+cd/xo/b7KRtU1Hznt51OiQ9s2zkuI6LDOPjM+XOHBBHvAV3js/41Lly6VxWLpcvtXXnlFycnJnuoeAAAAwAlcLpeqGluOrq/vuM5+X1Wj6n8k2KdaOgZ791T8uAiFBQf00N8CwNnw2PT+vozp/QAAADCKy+VSZUNLx43zqtpG7vdXNqnefvpgn2YJPbppXkTbJnoJEe7N80KDCPaArzJkej8AAAAAz3O5XDrUYNe+yrYR+v1HN9Dbd/S4u4bTBHuTSUqzhB23cd6x3fEz4gj2gL/zWOiPjY2VyWTqUtvq6mpPdQsAAAD4BZfLpUP19g7T74/fHb+xxXHKz7YH+wFHj7kbcNzIfTrBHujTPBb6Fy1a5P66qqpKTz75pCZPnqxx48ZJkjZt2qT169fr4Ycf9lSXAAAAQK/icrlU4Q72x9bZt++O33SaYG82SWkxx4J9/+PW2KfHhSskkGAPoDOvrOm/7rrrNHHiRM2ePbvD9RdffFEffPCB1qxZ4+kuDcWafgAAALRzOk8I9kfX1rdPxT/cevpg3y827LhA3zZanxkfofS4MII9ALeu5lCvhP7IyEgVFBQoKyurw/XCwkKNGjVKDQ0Nnu7SUIR+AACAvsXpdOlgffOxqfiVx03Fr25Uc6vzlJ81myRrbLg70LeP1vePj5A1NlzBgeYe/JsA6K0M3cgvPj5e7777rubNm9fh+rvvvqv4+HhvdAkAAAB4lNPpUnlds/ZXtk2/33f0/Pr2EXv7kVMH+wCzSemxYZ12xO+fEKF+MWEEewA9xiuh//HHH9e///u/6+OPP9bYsWMlSf/617+0bt06vfrqq97oEgAAAOg2p9OlMtvhtmPujk7H33d05H5/dZNaThPsA80mpceFH7e+PlyZCREaEB+hfrFhCgog2AMwnldC/8yZMzV06FD98Y9/1KpVqyRJQ4cO1Weffeb+JQAAAADQExxOl8pqDx87v/64kfuiLgT7jPZgf9z59QMSIpQWQ7AH4Pu8sqa/r2FNPwAAQM8otx3W3spGDUiIUKolzH29Pdgfm4LfdHR3/EYVVx9Wi+PUwT4ooG3E/vjd8DPj20bs02JCFUiwB+CDDF3TL0m7d+/W0qVLtWfPHi1atEhJSUl67733lJGRoWHDhnmrWwAAAPipt74q0oJV2+R0SSZJ47MSFBxo1r6qRhVXN6nVceqxrOAAs9LjwjrtiN/2ywOCPQD/5ZXQv3HjRk2ZMkXjx4/XJ598oieffFJJSUn6+uuv9Ze//EUrV670RrcAAADwQzWNLXpt0z794YNd7msuSZ8VVnZoFxxgVkZ8uHtH/Pb19Znx4UqLCVOA2dTDlQOA8bwS+ufPn68nn3xSc+fOVVRUlPv6JZdcohdffNEbXQIAAMCPHHE49cmuQ1qZX6IPvqs45fT8X4zvr0lDk5UZH65UC8EeAE7kldC/bds2vfHGG52uJyUlqbKy8iSfAAAAAKTCigatyC/W6i2lqqi3u68PSopUYUWDjp/AH2Ay6faLB3ZY2w8A6MgroT8mJkbl5eUaMGBAh+tbt25Vv379vNElAAAAeqm65lb99esyrcwv0daiWvf12PAgTcvup+k5Vg1Ls+itr4r04KrtcrhcCjCZ9NS15xP4AeBHeCX0/+xnP9MDDzygFStWyGQyyel06vPPP9d9992nW2+91RtdAgAAoBdxOl36v91VWpFfrHXbD8h+9Ni8ALNJEwYnKi/XqkuGJCs48NgGezeMydDFgxO1r7JJ/RPCCfwA0AVeObKvpaVFs2bN0rJly+RwOBQYGCiHw6Gf//znWrZsmQICAjzdpaE4sg8AAKBr9lc1amV+id7JL1GZrdl9fVBSpPJyrZqW3U9JUaEGVggAvUNXc6hXQn+7oqIibd++XQ0NDcrOztagQYO81ZWhCP0AAACn1mg/on9sK9eK/BJ9ubfafT06NFBXjUrT9Jx0jbRaZDKxCR8AdFVXc6hXpve3y8jIUEZGhje7AAAAgA9yuVz6cm+1VuSX6B/bytXU4pAkmUzSRVkJystN1+XnJSs0yL9mgAKAr/FK6He5XFq5cqU++ugjVVRUyOnseMTKqlWrvNEtAAAADFZae1jv5JdoZX6Jiqqb3Nf7x4crLzdd12T3U1oMa/EBoKd4JfTPmTNHr7zyiiZOnKjk5GSmagEAAPix5laH1n97QCs2l+jz3ZVqXzwaERygK0ekKi83XbmZsfxMCAAG8Erof/3117Vq1Sr99Kc/9cbtAQAAYDCXy6WtxbVasblEf/u6TPX2I+73/m1gnPJy0jVleIrCg726mhQA8CO88m9hi8WigQMHeuPWAAAAMFBFXbNWbS3VyvwSFVY0uK/3iwnTdTlWTR9tVUZ8uIEVAgCO55XQ/9hjj+nxxx/Xf//3fyssjDVbAAAAvZn9iEMbvq/Qis3F2rjzkJxHp++HBpk15fxU5eVY9W8D42U2M30fAHyNV0L/9ddfr//93/9VUlKS+vfvr6CgoA7vb9myxRvdAgAAwIO2l9q0Mr9EawpKVdvU6r6ekxmr6TlWXTkiVdGhQae5AwDAaF4J/TNmzFB+fr5uvvlmNvIDAADoRaoa7FpTUKaV+SX6vrzOfT05OkTXjrZqeo5V5yRGGlghAKA7vBL6//73v2v9+vW66KKLvHF7AAAAeFCrw6mNOw5pRX6xPvyhQq2Otvn7wQFmXTYsWdNzrLp4UKICmL4PAL2OV0J/enq6oqOjvXFrAAAAeMjOg/VasblYq7eWqbLB7r4+vJ9FeblWXTUyTTHhwQZWCAA4W14J/c8995z+8z//Uy+//LL69+/vjS4AAABwBmxNrVr7ddvu+1+X2NzX4yOCdU12P03PtWpICoM3AOAvvBL6b775ZjU1Nemcc85ReHh4p438qqurvdEtAAAATsLhdOmzwkqt2Fysf353UC1HnJKkQLNJE4ckKS/HqolDkhQUYDa4UgCAp3kl9C9atMgbtwUAAEA37DnUoJX5JVq1pVQH6prd14ekRGl6jlXTsvspITLEwAoBAN7m8dDf2tqqjRs36uGHH9aAAQM8fftT2rdvn37729/qww8/1IEDB5SWlqabb75Zv/nNbxQcfOq1aM3NzZo3b57efPNN2e12TZ48WS+99JKSk5N7rHYAAABPabAf0d+/KdOKzSXavL/Gfd0SFqSrR6UpLydd5/eL5nQlAOgjPB76g4KC9M477+jhhx/29K1P64cffpDT6dQrr7yirKwsbd++XbfffrsaGxv1+9///pSfu/fee/X3v/9dK1askMVi0ezZs3Xttdfq888/78HqAQAAzpzT6dIXe6u0cnOJ3tt+QIdbHZIks0m6eHCi8nLSNWlokkKDAgyuFADQ00wul8vl6ZvOmDFDo0aN0r333uvpW3fLs88+q8WLF2vPnj0nfd9msykxMVFvvPGGpk+fLqntlwdDhw7Vpk2b9G//9m9d6qeurk4Wi0U2m41TCwAAQI8prm7SO1tK9M6WEhVXH3ZfH5gYoek5Vl2bbVWKJdTACgEA3tLVHOqVNf2DBg3SE088oc8//1w5OTmKiIjo8P7dd9/tjW47sdlsiouLO+X7+fn5am1t1aWXXuq+NmTIEGVkZJw29Nvtdtntx461qaur81zRAAAAp3G4xaH3tpdrxeYSbdpT5b4eGRKoqSNTNT0nXaMzYpi+DwCQ5KXQ/5e//EUxMTHKz89Xfn5+h/dMJlOPhP7CwkL96U9/Ou3U/gMHDig4OFgxMTEdricnJ+vAgQOn/NzChQv1+OOPe6pUAACA03K5XMrfX6OV+SX62zflarAfcb83PiteeTnpmjwsRWHBTN8HAHTkldC/d+9ej91r/vz5euaZZ07b5vvvv9eQIUPc35eWluqKK65QXl6ebr/9do/V0m7BggWaO3eu+/u6ujqlp6d7vB8AANC3HbA1t03fzy/RnspG9/X0uDBNH52u63L6yRobbmCFAABf55XQf7z2LQPOdIrZvHnzNHPmzNO2GThwoPvrsrIyTZw4URdeeKGWLFly2s+lpKSopaVFtbW1HUb7Dx48qJSUlFN+LiQkRCEhHG8DAAA8r7nVofe/O6gV+SX6bNchOY/uvhQWFKCfDk9VXq5VF/SPk9nM9H0AwI/zWuh/7bXX9Oyzz2rXrl2SpMGDB+v+++/XLbfc0q37JCYmKjExsUttS0tLNXHiROXk5Gjp0qUym82nbZ+Tk6OgoCBt2LBB1113nSRpx44dKioq0rhx47pVJwAAwJlyuVzaVmrTis0lWvt1mWyHW93vjekfq7ycdP10RKoiQ7w+XgMA8DNe+S/H888/r4cfflizZ8/W+PHjJUmfffaZ7rjjDlVWVnplV//S0lJNmDBBmZmZ+v3vf69Dhw6532sftS8tLdWkSZP02muv6YILLpDFYtEvf/lLzZ07V3FxcYqOjtZdd92lcePGdXnnfgAAgDN1qN6uNVtLtTK/RDsO1ruvp1pCdd1oq6bnWNU/IeI0dwAA4PS8Evr/9Kc/afHixbr11lvd16666ioNGzZMjz32mFdC//vvv6/CwkIVFhbKarV2eK99iUFra6t27NihpqYm93t/+MMfZDabdd1118lut2vy5Ml66aWXPF4fAACAJLUcceqjHRVasblEH++o0JGj8/eDA82aPCxFeTlWjc9KUADT9wEAHmBytSdiDwoNDdX27duVlZXV4fquXbs0fPhwNTc3e7pLQ3X1fEQAANB3fV9epxWbS/RuQamqGlvc10emxygvx6qpI9NkCQsysEIAQG/S1RzqlZH+rKwsvf3223rwwQc7XH/rrbc0aNAgb3QJAADgc2qbWvRuQZlW5Bdre2md+3piVIiuze6n6TlWDUqOMrBCAIC/80rof/zxx3XDDTfok08+ca/p//zzz7Vhwwa9/fbb3ugSAADAJxxxOPXprkqtyC/WB99VqMXhlCQFBZg0aUiy8nKt+v8GJyow4PQbDgMA4AleCf3XXXed/vWvf+kPf/iD1qxZI0kaOnSovvzyS2VnZ3ujSwAAAEMVVjRoZX6JVm0pUUW93X39vNRo5eVadfWofoqLCDawQgBAX+SVNf19DWv6AQDom+qaW/W3r8u1Ir9YW4tq3ddjw4N09ah+ysu1aliaxbgCAQB+y9A1/ZLkdDpVWFioiooKOZ3ODu9dfPHF3uoWAADAq5xOl/5vd5VW5Bdr3fYDsh9p+zknwGzShMGJysu16pIhyQoOZPo+AMB4Xgn9X3zxhX7+859r//79OnEigclkksPh8Ea3AAAAXlNU1aSV+cV6Z0upSmsPu69nJUUqL8eqa7L7KSk61MAKAQDozCuh/4477lBubq7+/ve/KzU1VSYT58wCAIDep9F+RP/YVq4V+SX6cm+1+3pUaKCuGpmmvNx0jbRa+FkHAOCzvBL6d+3apZUrVyorK8sbtwcAAPAal8ulr/bVaMXmYv19W7maWtpmKJpM0kVZCZqeY9XkYSkKDQowuFIAAH6cV0L/2LFjVVhYSOgHAAC9RlntYb2TX6KVW0q0v6rJfb1/fLim51h17Wir0mLCDKwQAIDu80rov+uuuzRv3jwdOHBAw4cPV1BQUIf3R4wY4Y1uAQAAuqW51aH13x7QyvwSfVZYqfatiCKCA3TliFTl5aYrNzOW6fsAgF7LK0f2mc2dd6s1mUxyuVx+uZEfR/YBANB7uFwuFRTXakV+if76dZnqm4+43xs7IE55uemacn6KIkK8dsgRAABnzdAj+/bu3euN2wIAAJyxirpmrd5aqhX5JSqsaHBf7xcTputyrJo+2qqM+HADKwQAwPO8EvozMzO9cVsAAIBuaTni1IbvD2pFfok27jwkh7NtgmNIoFlTzk9RXm66xg2Ml9nM9H0AgH/yWOhfu3atpkyZ0mn9/qn84x//0MSJExUWxoY4AADAs7aX2rQyv0TvFpSqpqnVfX10RozyctN15YhURYd27WcWAAB6M4+t6Q8ICNCBAweUmJjYpfbR0dEqKCjQwIEDPdG9oVjTDwCA8aoa7Hq3oEwr8kv0fXmd+3pSVIiuHW3V9ByrspIiDawQAADP6fE1/S6XSzNnzlRISEiX2jc3N3uqawAA0EcdcTj18Y5DWpFfrA9/qFCro20sIzjArMvOS9b0XKt+kpWgwIDOmwwDANAXeCz0z5gxo1vtb7rpJkbFAQDAGdl1sF4r8ku0akupKhvs7uvD+1mUl2vV1BFpio0INrBCAAB8g8dC/9KlSz11KwAAgE5sTa1a+02ZVm4u1tclNvf1+IhgTcvup7xcq4akMKAAAMDxOIAWAAD4LIfTpc8LK7Uiv0Trvz2gliNOSVKg2aSJQ5KUl2PVxCFJCmL6PgAAJ0XoBwAAPmdvZaNW5hdr1ZZSlduO7QN0bnKU8nKtmpbdTwmRXdtHCACAvozQDwAADFNuO6y9lY0akBChqNAg/eObcq3IL9ZX+2rcbSxhQbp6VJryctJ1fr9omUwmAysGAKB3IfQDAABDvPVVkRas2ibn0cODgwJM7t33zSbpJ4MSlZdr1aVDkxUaFGBgpQAA9F6EfgAA0GOcTpcKDzXow+8r9PS6Hzq81+pwKSM2TD8bm6Frs61KsYQaVCUAAP7DK6F/7969+vTTT7V//341NTUpMTFR2dnZGjdunEJD+Q84AAB9RYP9iL4urlX+/hrl76/RlqIa1TcfOWX7Z6aP0LhzEnqwQgAA/JtHQ////M//6IUXXtDmzZuVnJystLQ0hYWFqbq6Wrt371ZoaKhuuukmPfDAA8rMzPRk1wAAwGAul0slNYfdAT9/f41+OFDnnr7fLiwoQENTo7S1qFbHvxVgMql/QkSP1gwAgL/zWOjPzs5WcHCwZs6cqXfeeUfp6ekd3rfb7dq0aZPefPNN5ebm6qWXXlJeXp6nugcAAD2sudWhb8tsbSP4+2uVX1SjQ/X2Tu2ssWHKyYxVTmasRmfEakhKlAIDzHrrqyI9uGq7HC6XAkwmPXXt+Uq1hBnwNwEAwH+ZXC6X68eb/bj169dr8uTJXWpbVVWlffv2KScnxxNdG66urk4Wi0U2m03R0dFGlwMAgFdU1Ddry3Gj+NtL69TicHZoExRg0vn9LMrJOBryM2OVHH3qpX3ltsPaV9mk/gnhBH4AALqhqznUY6G/LyP0AwD8jcPp0g8H6o6F/KIaFVcf7tQuPiLYPYqfkxmr8/tZ2GkfAIAe0NUc6tE1/WVlZXr++ef1yCOPdOrUZrPpySef1H333afk5GRPdgsAAM6S7XCrthbVtIX8ohoVFNWqscXRoY3JJJ2bHNUh5GfEhctkMhlUNQAA+DEeDf3PP/+86urqTvpbBovFovr6ej3//PN65plnPNktAADoBpfLpb2Vje7d9PP312hXRYNOnPsXFRKoURkx7oA/Kj1GUaFBxhQNAADOiEdD/7p16/Tyyy+f8v1bb71Vt99+O6EfAIAedLjFoW9K2jbaa5+uX9PU2qld//hwjT5uFH9QUpQCzIziAwDQm3k09O/du1cZGRmnfN9qtWrfvn2e7BIAAJyg3Hbs2Lwt+2v0bVmdjpxwbl5woFkjrZa2kJ/RtuFeQmSIQRUDAABv8WjoDwsL0759+04Z/Pft26ewMHbmBQDAU1odTn1fXtch5JfZmju1S4oKUW7/tiPzcjJjNSzNouBAswEVAwCAnuTR0D927Fi9/vrruvjii0/6/muvvaYLLrjAk10CANCn1DS2uNfh5++v0dcltWpu7XhsXoDZpKGpUe4R/JzMWPWLCWPDPQAA+iCPhv777rtPl112mSwWi+6//373Lv0HDx7Uf/3Xf2nZsmX65z//6ckuAQDwW06nS7sPNbgDfn5RjfYcauzUzhIWpNFHN9wbnRmrkdYYRYR49D/xAACglzK5XCfu1Xt2XnnlFd1zzz1qbW1VdHS0TCaTbDabgoKC9Ic//EF33nmnJ7vzCV09HxEAgNNptB/R18W17oC/ZX+N6pqPdGqXlRTpDvk5mbEamBApMxvuAQDQp3Q1h3o89EtSaWmp3n77bRUWFsrlcmnw4MGaPn26rFarp7vyCYR+AEB3uVwuldQc7jBV//vyOp2w357CggI0Kv1YwM/OiFFMeLAxRQMAAJ9haOjvawj9AIAfYz/i0Ldlde4j8/L316ii3t6pXb+YMHfAz8mM1ZCUKAUGsOEeAADoqKs51CsL/tauXXvS6yaTSaGhocrKytKAAQO80TUAAD7hUL1dW45O0c/fX6NvSm1qOdJxw72gAJOGpVncAX90RqxSLKEGVQwAAPyRV0L/tGnTZDKZdOIkgvZrJpNJF110kdasWaPY2FhvlAAAQI9xOF3acaDevQ4/f3+NiqqbOrWLjwh276afkxmr4f0sCg0KMKBiAADQV3gl9L///vv6zW9+o9/97nfuI/q+/PJLPfzww3rooYdksVj061//Wvfdd5/+8pe/eKMEAAC8pq65VVuL2jbc27K/RgXFtWqwd9xwz2SSzk2Oagv5GW0hPzM+nGPzAABAj/JK6L/nnnu0ZMkSXXjhhe5rkyZNUmhoqH71q1/p22+/1aJFi/SLX/zCG90DAOAxLpdL+6qa3Ovwt+yv0c6Kep24I05kSKCyM2I0+mjAH5URo+jQIGOKBgAAOMoroX/37t0n3UggOjpae/bskSQNGjRIlZWV3ugeAIAz1tzq0DcltmMhv6hG1Y0tndplxocrJyPWPV1/cHKUAjg2DwAA+BivhP6cnBzdf//9eu2115SYmChJOnTokP7zP/9TY8aMkSTt2rVL6enp3ugeAIAuO2Brdgf8/KIafVtq05ETzs0LDjRrRL+2DfdGH91wLzEqxKCKAQAAus4rof8vf/mLrr76almtVnewLy4u1sCBA/Xuu+9KkhoaGvTQQw95o3sAAE6q1eHUD+X1yt9frfyiWm3ZX6PS2sOd2iVGhSi3fUf9zFgNS4tWSCAb7gEAgN7H5Dpxi30PcTqd+uc//6mdO3dKks4991xddtllMpv976zhrp6PCADoWTWNLdpaXOMeyf+62KbDrY4ObcwmaWhqdIdj86yxYWy4BwAAfFpXc6jXQn+75uZmhYSEeP2Hp3379um3v/2tPvzwQx04cEBpaWm6+eab9Zvf/EbBwcGn/NyECRO0cePGDtd+/etf6+WXX+5y34R+ADCe0+nSnsqGY1P199do96HGTu2iQwOPBfzMWI20xigixCsT3wAAALymqznUKz/lOJ1O/e53v9PLL7+sgwcPaufOnRo4cKAefvhh9e/fX7/85S893ucPP/wgp9OpV155RVlZWdq+fbtuv/12NTY26ve///1pP3v77bfriSeecH8fHh7u8foAAJ7VaD+ir0vapui3bbhXK9vh1k7tzkmMcIf8nMxYDUyIlJkN9wAAQB/hldD/5JNPavny5fqv//ov3X777e7r559/vhYtWuSV0H/FFVfoiiuucH8/cOBA7dixQ4sXL/7R0B8eHq6UlBSP1wQA8AyXy6XS2sPuI/Pyi2r0fXm9HCdsuBcaZNao9Bh3wM9Oj1VsxKlnewEAAPg7r4T+1157TUuWLNGkSZN0xx13uK+PHDlSP/zwgze6PCmbzaa4uLgfbfc///M/+n//7/8pJSVFU6dO1cMPP3za0X673S673e7+vq6uziP1AgDatBxx6tsym/vIvPz9NTpYZ+/Url9MWNuReRkxysmM05DUKAUF+N/eMQAAAGfKK6G/tLRUWVlZna47nU61tnaeeukNhYWF+tOf/vSjo/w///nPlZmZqbS0NH3zzTd64IEHtGPHDq1ateqUn1m4cKEef/xxT5cMAH3WoXq7thS1Bfwt+2v0dYlNLUecHdoEmk0a1s+inIz29fgxSrWEGVQxAABA7+CV0H/eeefp008/VWZmZofrK1euVHZ2drfuNX/+fD3zzDOnbfP9999ryJAh7u9LS0t1xRVXKC8vr8PygpP51a9+5f56+PDhSk1N1aRJk7R7926dc845J/3MggULNHfuXPf3dXV17qMJAQCn53C6tPNgfYep+vurmjq1i4sI1uiMY2vxR1gtCg3i2DwAAIDu8Erof+SRRzRjxgyVlpbK6XRq1apV2rFjh1577TX97W9/69a95s2bp5kzZ562zcCBA91fl5WVaeLEibrwwgu1ZMmSbtc+duxYSW0zBU4V+kNCQhQSEtLtewOAvyu3HdbeykYNSIhwj8LXNbeqoKjWPVV/a1GtGuxHOnzOZJIGJ0W1TdU/+uofH86xeQAAAGfJK6H/6quv1l//+lc98cQTioiI0COPPKLRo0frr3/9qy677LJu3SsxMVGJiYldaltaWqqJEycqJydHS5culdnc/XWdBQUFkqTU1NRufxYA+rK3virSglXb5HRJJkkXDIiT7XCrdhys14mHw0YEByg7I9Yd8kelx8gSFmRI3QAAAP7M5HKd+KNY71RaWqoJEyYoMzNTy5cvV0DAsSmg7Tvzl5aWatKkSXrttdd0wQUXaPfu3XrjjTf005/+VPHx8frmm2907733ymq1auPGjV3uu6vnIwKAv2mwH9E3xbX6ZNchvbxxzynbZcSFH12HH6ucjFidmxKlAI7NAwAAOGNdzaFeGek3wvvvv6/CwkIVFhbKarV2eK/99xqtra3asWOHmpra1o4GBwfrgw8+0KJFi9TY2Kj09HRdd911euihh3q8fgDwdU6nS3sqG7SlqFZbi2q1tahGOw/Wy3maXx3fe+lg3Tg2XUlRoT1XKAAAANw8NtIfGxvb5bWX1dXVnujSZzDSD8Af1Ta1aGvxsYBfUFyr+uYjndr1iwnTkJQoffhDhY7/D0qAyaTP5k9kh30AAAAv6PGR/kWLFrm/rqqq0pNPPqnJkydr3LhxkqRNmzZp/fr1evjhhz3VJQDAQ444nPrhQP3RkF+jgqJa7als7NQuLChAI6wWZWfEKjsjRtnpMUqKbhvFf+urIj24arscLpcCTCY9de35BH4AAACDeWVN/3XXXaeJEydq9uzZHa6/+OKL+uCDD7RmzRpPd2koRvoB9DYVdc1t0/SL23bT31Zi0+FWR6d2AxMijgX8jBidmxylwIBTb5JabjusfZVN6p8QTuAHAADwoq7mUK+E/sjISBUUFCgrK6vD9cLCQo0aNUoNDQ2e7tJQhH4Avsx+xKFvy+rc0/S3FtWqtPZwp3ZRoYEalR7jDvmjrDGKjQg2oGIAAAD8GEM38ouPj9e7776refPmdbj+7rvvKj4+3htdAgDUtnFpSc1h9zT9rUW1+q6sTi0OZ4d2ZpM0ODnKHfBHZ8RoYEKkzOyoDwAA4Fe8Evoff/xx/fu//7s+/vhjjR07VpL0r3/9S+vWrdOrr77qjS4BoE9qtB/RNyU29zT9rUW1qmywd2oXHxHcYZr+CGuMIkP85gAXAAAAnIJXfuKbOXOmhg4dqj/+8Y9atWqVJGno0KH67LPP3L8EAAB0T9uReY1tI/hHd9XfcaCu05F5gWaThqVFHzeKHytrbFiXT1gBAACA//DKmv6+hjX9ALzB1tSqgpJj0/QLimtlO9zaqV2aJbTDKP6wNItCgwIMqBgAAAA9pcfX9Dc2NioiIsJr7QHAnx1xOLXzYMNx0/RrtPtQ5yPzQoPMGtEvxh3wR6XHKsUSakDFAAAA6A08FvqzsrJ0zz33aMaMGUpNTT1pG5fLpQ8++EDPP/+8Lr74Yi1YsMBT3QNAr3Ko3n7cNP0afVNiU1NL5yPz+seHa7R7FD9W56ZEKeg0R+YBAAAAx/NY6P/444/14IMP6rHHHtPIkSOVm5urtLQ0hYaGqqamRt999502bdqkwMBALViwQL/+9a891TUA+LSWI059V16nrUU12nJ0FL+kpvOReZEh7UfmHRvFj+PIPAAAAJwFj6/pLyoq0ooVK/Tpp59q//79Onz4sBISEpSdna3JkydrypQpCgjwr7WmrOkH0M7lcqnM1uxeh7+1qEbby+rUcqTjkXkmkzQ4Kcod8LMzYnVOYqQCODIPAAAAXdDVHMpGfh5A6Af6rqaWI9pWYnNP099aVKuK+s5H5sVFBCs7/VjAH2G1KCo0yICKAQAA4A96fCM/APB3LpdLeysb20bwj26498OBejlOODMv0GzS0NRo9yj+6IxYZcSFc2QeAAAAehyhHwBOoa65VQVFte6QX1Bcq9qmzkfmJUeHdNhs7/w0i8KC/WsZEwAAAHonQj8ASHI4XdpVUe9eh7+1qFaFhxp04gKo4ECzRvSzuAN+dkaMUi1hxhQNAAAA/AhCP4A+qbLB3jaKf3Sa/tfFtWo8yZF5mfHhR9fitwX8ISnRCg7kyDwAAAD0Dh4N/U888YTuu+8+hYeHe/K2AHBWWo449f3RI/PaNtyrVVF1U6d2EcEBGtm+2V56rEZlxCghMsSAigEAAADP8Oju/QEBASovL1dSUpKnbtkrsHs/4FvKbYfd0/S3FNVqW6mt05F5kjQoKbLDNP1BSVEcmQcAAIBewZDd+zn9D0BPa251aFupzb0Of2tRrQ7UNXdqFxMe1GGa/ghrjCxhHJkHAAAA/+bxNf0cSQXAW1wul/ZXNbnX4W8tqtX35XU6csKReQFmk4akRLmn6WdnxGhAQgT/fgIAAECf4/HQP3jw4B/9wbq6utrT3QLwQ/XNrfq62HbcWvwa1ZzkyLzEqBCNbp+mnx6j4VaLwoPZpxQAAADw+E/Fjz/+uCwWi6dvC8DPOZ0uFR5q0Jb9R0fxi2u0q+IkR+YFmHV+v2j3NP3sjFilWUIZxQcAAABOwuOh/2c/+1mf28gPQPdVN7ao4Lhp+l8X16refqRTO2tsmHsEf3RmrIamRikkMMCAigEAAIDex6Ohn5E2ACfT6nDqh/L649bi12hfVecj88KDAzTCanGH/FEZMUqKCjWgYgAAAMA/sHs/AI87YGvusA7/mxKb7Cc5Mu+cxIhj0/TTYzU4OVKBAWYDKgYAAAD8k0dDv9PZ+Yd6AP6tudWhb8ts7mn6W4pqVG7rfGRedGhgh3X4o6wxsoRzZB4AAADgTWxvDeCUym2HtbeyUQMSIpRqCZPL5VJx9eEO0/S/K69Tq6PjLB+zSTo3JfroCH5byB+YECGzmSVAAAAAQE8i9AM4qTe/LNKDq7fJ6ZJMkoakRqmizq6qxpZObRMigztM0x9htSgihH+9AAAAAEbjp3KgD3E4XappalFVQ4sqG+yqbLDrUH1bkK+stx+91qKKumYdrLe7P+eS9H15vSQpKMCkYWkW9zT97PQYWWPD2MgTAAAA8EGEfqCXa3U43SH+UIP9WKA/GuKrGlt0qL4tzFc32uU8i/02H79qmG4Yk67QII7MAwAAAHoDQj/ggw63ONwj8ZXHhfiqxhYdOi7QVza0yHa4tdv3jw0PUkJkiOIjg5UQGaKEyBAlRoUoPqLte5mkX722ucMvCAJMJl0+LJnADwAAAPQihH6gB7hcLtXbjxwN6y0nDfTto/KV9XY1tji6df8As0lxEe0BPliJkSFKOC7EJ0S1XU+IDFFcRLCCunAs3sJrh+vBVdvlcLkUYDLpqWvPV6ol7Ez/EQAAAAAwAKEfOEPOo+vjTxXiqxqPC/SNLWo5yTn1pxMcaG4L70fD+vGj8glRIUqICD4a5kMUExbk8Z3xbxiToYsHJ2pfZZP6J4QT+AEAAIBeiNAPHOf49fHHh/iq474+m/XxkSGBSogMVvxxYT7h+K+jjn0fGRJo+OZ4qZYwwj4AAADQixH64feaWx1Hg3pbWK86LtAfOmFUvrbpzNbHnzLEHzfNPjEqhPXwAAAAAHoUoR+9zonr49tD/KGTjMp7Yn38iSG+fZp9YlTX18cDAAAAgBEI/fAJ7evj2zeyO3SSUfnKo8fRHWqwn9X6+BNH5eOP2/jOW+vjAQAAAMAIhH54TavDqWr3GfH2k66Vb/+zurFFjm4ukI8MCTxuc7v2ze5ClHjC+vj4yGBF+cD6eAAAAADoaYT+PqTcdlh7Kxs1ICHijDdnO359/MlD/LGvz2R9fMzR8+NPtT7++B3sw4JZHw8AAAAAp0Po7yPe+qpIC1Ztk9MlmU1tZ7DfMCZDLpdLDfYjnc6LPzHEt6+Tb7Af6Va/p1sff/w0e9bHAwAAAIDnmVwuVzcPHcOJ6urqZLFYZLPZFB0dbXQ5nZTbDmv80x92Ol4uJTpUNU0tsnd3fXyAuS2sH3e8XPxxo/KJx+1YHxsezPp4AAAAAPCwruZQRvr7gL2VjSc9T/5AXbP764jggJOG+MQTR+WjQlgfDwAAAAC9BKG/DxiQECGzSR2Cv9kkvXJLjoakRLM+HgAAAAD8FAuo+4BUS5gWXjtcAUdH5wNMJi28drguOy9F6XHhBH4AAAAA8FOM9PcRN4zJ0MWDE7Wvskn9E8LPePd+AAAAAEDvQejvQ1ItYYR9AAAAAOhDmN4PAAAAAICfIvQDAAAAAOCnCP0AAAAAAPgp1vR7gMvVdhZeXV2dwZUAAAAAAPqC9vzZnkdPhdDvAfX19ZKk9PR0gysBAAAAAPQl9fX1slgsp3zf5PqxXwvgRzmdTpWVlSkqKkomk8nock6prq5O6enpKi4uVnR0tNHloBfgmUF38cygu3hm0F08M+gOnhd0V296Zlwul+rr65WWliaz+dQr9xnp9wCz2Syr1Wp0GV0WHR3t8w8wfAvPDLqLZwbdxTOD7uKZQXfwvKC7esszc7oR/nZs5AcAAAAAgJ8i9AMAAAAA4KcI/X1ISEiIHn30UYWEhBhdCnoJnhl0F88MuotnBt3FM4Pu4HlBd/njM8NGfgAAAAAA+ClG+gEAAAAA8FOEfgAAAAAA/BShHwAAAAAAP0XoBwAAAADATxH6+4g///nP6t+/v0JDQzV27Fh9+eWXRpcEH/bJJ59o6tSpSktLk8lk0po1a4wuCT5s4cKFGjNmjKKiopSUlKRp06Zpx44dRpcFH7Z48WKNGDFC0dHRio6O1rhx4/Tee+8ZXRZ6kaefflomk0lz5swxuhT4qMcee0wmk6nDa8iQIUaXBR9XWlqqm2++WfHx8QoLC9Pw4cO1efNmo8s6a4T+PuCtt97S3Llz9eijj2rLli0aOXKkJk+erIqKCqNLg49qbGzUyJEj9ec//9noUtALbNy4UbNmzdIXX3yh999/X62trbr88svV2NhodGnwUVarVU8//bTy8/O1efNmXXLJJbr66qv17bffGl0aeoGvvvpKr7zyikaMGGF0KfBxw4YNU3l5ufv12WefGV0SfFhNTY3Gjx+voKAgvffee/ruu+/03HPPKTY21ujSzhpH9vUBY8eO1ZgxY/Tiiy9KkpxOp9LT03XXXXdp/vz5BlcHX2cymbR69WpNmzbN6FLQSxw6dEhJSUnauHGjLr74YqPLQS8RFxenZ599Vr/85S+NLgU+rKGhQaNHj9ZLL72kJ598UqNGjdKiRYuMLgs+6LHHHtOaNWtUUFBgdCnoJebPn6/PP/9cn376qdGleBwj/X6upaVF+fn5uvTSS93XzGazLr30Um3atMnAygD4K5vNJqktxAE/xuFw6M0331RjY6PGjRtndDnwcbNmzdKVV17Z4eca4FR27dqltLQ0DRw4UDfddJOKioqMLgk+bO3atcrNzVVeXp6SkpKUnZ2tV1991eiyPILQ7+cqKyvlcDiUnJzc4XpycrIOHDhgUFUA/JXT6dScOXM0fvx4nX/++UaXAx+2bds2RUZGKiQkRHfccYdWr16t8847z+iy4MPefPNNbdmyRQsXLjS6FPQCY8eO1bJly7Ru3TotXrxYe/fu1U9+8hPV19cbXRp81J49e7R48WINGjRI69ev15133qm7775by5cvN7q0sxZodAEAAP8xa9Ysbd++nXWT+FHnnnuuCgoKZLPZtHLlSs2YMUMbN24k+OOkiouLdc899+j9999XaGio0eWgF5gyZYr76xEjRmjs2LHKzMzU22+/zTIinJTT6VRubq6eeuopSVJ2dra2b9+ul19+WTNmzDC4urPDSL+fS0hIUEBAgA4ePNjh+sGDB5WSkmJQVQD80ezZs/W3v/1NH330kaxWq9HlwMcFBwcrKytLOTk5WrhwoUaOHKkXXnjB6LLgo/Lz81VRUaHRo0crMDBQgYGB2rhxo/74xz8qMDBQDofD6BLh42JiYjR48GAVFhYaXQp8VGpqaqdfPA8dOtQvloUQ+v1ccHCwcnJytGHDBvc1p9OpDRs2sHYSgEe4XC7Nnj1bq1ev1ocffqgBAwYYXRJ6IafTKbvdbnQZ8FGTJk3Stm3bVFBQ4H7l5ubqpptuUkFBgQICAowuET6uoaFBu3fvVmpqqtGlwEeNHz++05HDO3fuVGZmpkEVeQ7T+/uAuXPnasaMGcrNzdUFF1ygRYsWqbGxUbfddpvRpcFHNTQ0dPhN+N69e1VQUKC4uDhlZGQYWBl80axZs/TGG2/o3XffVVRUlHu/EIvForCwMIOrgy9asGCBpkyZooyMDNXX1+uNN97Qxx9/rPXr1xtdGnxUVFRUp31CIiIiFB8fz/4hOKn77rtPU6dOVWZmpsrKyvToo48qICBAN954o9GlwUfde++9uvDCC/XUU0/p+uuv15dffqklS5ZoyZIlRpd21gj9fcANN9ygQ4cO6ZFHHtGBAwc0atQorVu3rtPmfkC7zZs3a+LEie7v586dK0maMWOGli1bZlBV8FWLFy+WJE2YMKHD9aVLl2rmzJk9XxB8XkVFhW699VaVl5fLYrFoxIgRWr9+vS677DKjSwPgJ0pKSnTjjTeqqqpKiYmJuuiii/TFF18oMTHR6NLgo8aMGaPVq1drwYIFeuKJJzRgwAAtWrRIN910k9GlnTWTy+VyGV0EAAAAAADwPNb0AwAAAADgpwj9AAAAAAD4KUI/AAAAAAB+itAPAAAAAICfIvQDAAAAAOCnCP0AAAAAAPgpQj8AAAAAAH6K0A8AALpl5syZmjZtWo/3u2zZMplMJplMJs2ZM8d9vX///lq0aNFpP9v+uZiYGK/WCACArwk0ugAAAOA7TCbTad9/9NFH9cILL8jlcvVQRR1FR0drx44dioiI6NbnysvL9dZbb+nRRx/1UmUAAPgmQj8AAHArLy93f/3WW2/pkUce0Y4dO9zXIiMjFRkZaURpktp+KZGSktLtz6WkpMhisXihIgAAfBvT+wEAgFtKSor7ZbFY3CG7/RUZGdlpev+ECRN01113ac6cOYqNjVVycrJeffVVNTY26rbbblNUVJSysrL03nvvdehr+/btmjJliiIjI5WcnKxbbrlFlZWVZ1R3U1OTfvGLXygqKkoZGRlasmTJ2fxjAADAbxD6AQDAWVu+fLkSEhL05Zdf6q677tKdd96pvLw8XXjhhdqyZYsuv/xy3XLLLWpqapIk1dbW6pJLLlF2drY2b96sdevW6eDBg7r++uvPqP/nnntOubm52rp1q/7jP/5Dd955Z4cZCgAA9FWEfgAAcNZGjhyphx56SIMGDdKCBQsUGhqqhIQE3X777Ro0aJAeeeQRVVVV6ZtvvpEkvfjii8rOztZTTz2lIUOGKDs7W//93/+tjz76SDt37ux2/z/96U/1H//xH8rKytIDDzyghIQEffTRR57+awIA0Ouwph8AAJy1ESNGuL8OCAhQfHy8hg8f7r6WnJwsSaqoqJAkff311/roo49Ouj/A7t27NXjw4DPuv31JQntfAAD0ZYR+AABw1oKCgjp8bzKZOlxrPxXA6XRKkhoaGjR16lQ988wzne6Vmprqkf7b+wIAoC8j9AMAgB43evRovfPOO+rfv78CA/lxBAAAb2FNPwAA6HGzZs1SdXW1brzxRn311VfavXu31q9fr9tuu00Oh8Po8gAA8BuEfgAA0OPS0tL0+eefy+Fw6PLLL9fw4cM1Z84cxcTEyGzmxxMAADzF5HK5XEYXAQAA8GOWLVumOXPmqLa21pDPAwDQG/GrdAAA0GvYbDZFRkbqgQce6NbnIiMjdccdd3ipKgAAfBcj/QAAoFeor6/XwYMHJUkxMTFKSEjo8mcLCwsltR0nOGDAAK/UBwCALyL0AwAAAADgp5jeDwAAAACAnyL0AwAAAADgpwj9AAAAAAD4KUI/AAAAAAB+itAPAAAAAICfIvQDAAAAAOCnCP0AAAAAAPgpQj8AAAAAAH6K0A8AAAAAgJ/6/wFWCw36lF2gAAAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 1200x800 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "w2.plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "UqiqcPOldPG6"
+   },
+   "source": [
+    "You can plot the other columns, but the example window `w2` configuration only has labels for the `T (degC)` column."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:09.951101Z",
+     "iopub.status.busy": "2023-07-27T04:27:09.950865Z",
+     "iopub.status.idle": "2023-07-27T04:27:10.471389Z",
+     "shell.execute_reply": "2023-07-27T04:27:10.470744Z"
+    },
+    "id": "EBRe4wnlfCH8"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "w2.plot(plot_col='p (mbar)')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "xCvD-UaUzYMw"
+   },
+   "source": [
+    "### 4. Create `tf.data.Dataset`s"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "kLO3SFR9Osdf"
+   },
+   "source": [
+    "Finally, this `make_dataset` method will take a time series DataFrame and convert it to a `tf.data.Dataset` of `(input_window, label_window)` pairs using the `tf.keras.utils.timeseries_dataset_from_array` function:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:10.475584Z",
+     "iopub.status.busy": "2023-07-27T04:27:10.475131Z",
+     "iopub.status.idle": "2023-07-27T04:27:10.479530Z",
+     "shell.execute_reply": "2023-07-27T04:27:10.478964Z"
+    },
+    "id": "35qoSQeRVfJg"
+   },
+   "outputs": [],
+   "source": [
+    "def make_dataset(self, data):\n",
+    "  data = np.array(data, dtype=np.float32)\n",
+    "  ds = tf.keras.utils.timeseries_dataset_from_array(\n",
+    "      data=data,\n",
+    "      targets=None,\n",
+    "      sequence_length=self.total_window_size,\n",
+    "      sequence_stride=1,\n",
+    "      shuffle=True,\n",
+    "      batch_size=32,)\n",
+    "\n",
+    "  ds = ds.map(self.split_window)\n",
+    "\n",
+    "  return ds\n",
+    "\n",
+    "WindowGenerator.make_dataset = make_dataset"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "LvsxQwJaCift"
+   },
+   "source": [
+    "The `WindowGenerator` object holds training, validation, and test data.\n",
+    "\n",
+    "Add properties for accessing them as `tf.data.Dataset`s using the `make_dataset` method you defined earlier. Also, add a standard example batch for easy access and plotting:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:10.482888Z",
+     "iopub.status.busy": "2023-07-27T04:27:10.482340Z",
+     "iopub.status.idle": "2023-07-27T04:27:10.487490Z",
+     "shell.execute_reply": "2023-07-27T04:27:10.486874Z"
+    },
+    "id": "2jZ2KkqGCfzu"
+   },
+   "outputs": [],
+   "source": [
+    "@property\n",
+    "def train(self):\n",
+    "  return self.make_dataset(self.train_df)\n",
+    "\n",
+    "@property\n",
+    "def val(self):\n",
+    "  return self.make_dataset(self.val_df)\n",
+    "\n",
+    "@property\n",
+    "def test(self):\n",
+    "  return self.make_dataset(self.test_df)\n",
+    "\n",
+    "@property\n",
+    "def example(self):\n",
+    "  \"\"\"Get and cache an example batch of `inputs, labels` for plotting.\"\"\"\n",
+    "  result = getattr(self, '_example', None)\n",
+    "  if result is None:\n",
+    "    # No example batch was found, so get one from the `.train` dataset\n",
+    "    result = next(iter(self.train))\n",
+    "    # And cache it for next time\n",
+    "    self._example = result\n",
+    "  return result\n",
+    "\n",
+    "WindowGenerator.train = train\n",
+    "WindowGenerator.val = val\n",
+    "WindowGenerator.test = test\n",
+    "WindowGenerator.example = example"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "fF_Vj6Iw3Y2w"
+   },
+   "source": [
+    "Now, the `WindowGenerator` object gives you access to the `tf.data.Dataset` objects, so you can easily iterate over the data.\n",
+    "\n",
+    "The `Dataset.element_spec` property tells you the structure, data types, and shapes of the dataset elements."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:10.490621Z",
+     "iopub.status.busy": "2023-07-27T04:27:10.490217Z",
+     "iopub.status.idle": "2023-07-27T04:27:10.614889Z",
+     "shell.execute_reply": "2023-07-27T04:27:10.614276Z"
+    },
+    "id": "daJ0-U383YVs"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(TensorSpec(shape=(None, 6, 19), dtype=tf.float32, name=None),\n",
+       " TensorSpec(shape=(None, 1, 1), dtype=tf.float32, name=None))"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Each element is an (inputs, label) pair.\n",
+    "w2.train.element_spec"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "XKTx3_Z7ua-n"
+   },
+   "source": [
+    "Iterating over a `Dataset` yields concrete batches:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:10.617933Z",
+     "iopub.status.busy": "2023-07-27T04:27:10.617702Z",
+     "iopub.status.idle": "2023-07-27T04:27:10.727720Z",
+     "shell.execute_reply": "2023-07-27T04:27:10.726962Z"
+    },
+    "id": "6gtKXEgf4Iml"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Inputs shape (batch, time, features): (32, 6, 19)\n",
+      "Labels shape (batch, time, features): (32, 1, 1)\n"
+     ]
+    }
+   ],
+   "source": [
+    "for example_inputs, example_labels in w2.train.take(1):\n",
+    "  print(f'Inputs shape (batch, time, features): {example_inputs.shape}')\n",
+    "  print(f'Labels shape (batch, time, features): {example_labels.shape}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "LyuGuJUgjUK3"
+   },
+   "source": [
+    "## Single step models\n",
+    "\n",
+    "The simplest model you can build on this sort of data is one that predicts a single feature's value—1 time step (one hour) into the future based only on the current conditions.\n",
+    "\n",
+    "So, start by building models to predict the `T (degC)` value one hour into the future.\n",
+    "\n",
+    "![Predict the next time step](images/narrow_window.png)\n",
+    "\n",
+    "Configure a `WindowGenerator` object to produce these single-step `(input, label)` pairs:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:10.731234Z",
+     "iopub.status.busy": "2023-07-27T04:27:10.730616Z",
+     "iopub.status.idle": "2023-07-27T04:27:10.735370Z",
+     "shell.execute_reply": "2023-07-27T04:27:10.734724Z"
+    },
+    "id": "G5QX1G1JTPCr"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Total window size: 2\n",
+       "Input indices: [0]\n",
+       "Label indices: [1]\n",
+       "Label column name(s): ['T (degC)']"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "single_step_window = WindowGenerator(\n",
+    "    input_width=1, label_width=1, shift=1,\n",
+    "    label_columns=['T (degC)'])\n",
+    "single_step_window"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "RKTm8ajVGw4N"
+   },
+   "source": [
+    "The `window` object creates `tf.data.Dataset`s from the training, validation, and test sets, allowing you to easily iterate over batches of data.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:10.738626Z",
+     "iopub.status.busy": "2023-07-27T04:27:10.738149Z",
+     "iopub.status.idle": "2023-07-27T04:27:10.849969Z",
+     "shell.execute_reply": "2023-07-27T04:27:10.849285Z"
+    },
+    "id": "Do4ILUaBF8oc"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Inputs shape (batch, time, features): (32, 1, 19)\n",
+      "Labels shape (batch, time, features): (32, 1, 1)\n"
+     ]
+    }
+   ],
+   "source": [
+    "for example_inputs, example_labels in single_step_window.train.take(1):\n",
+    "  print(f'Inputs shape (batch, time, features): {example_inputs.shape}')\n",
+    "  print(f'Labels shape (batch, time, features): {example_labels.shape}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "D1bbPiR3VAm_"
+   },
+   "source": [
+    "### Baseline\n",
+    "\n",
+    "Before building a trainable model it would be good to have a performance baseline as a point for comparison with the later more complicated models.\n",
+    "\n",
+    "This first task is to predict temperature one hour into the future, given the current value of all features. The current values include the current temperature. \n",
+    "\n",
+    "So, start with a model that just returns the current temperature as the prediction, predicting \"No change\". This is a reasonable baseline since temperature changes slowly. Of course, this baseline will work less well if you make a prediction further in the future.\n",
+    "\n",
+    "![Send the input to the output](images/baseline.png)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:10.853209Z",
+     "iopub.status.busy": "2023-07-27T04:27:10.852975Z",
+     "iopub.status.idle": "2023-07-27T04:27:10.857398Z",
+     "shell.execute_reply": "2023-07-27T04:27:10.856753Z"
+    },
+    "id": "9TybQaIsi3yg"
+   },
+   "outputs": [],
+   "source": [
+    "class Baseline(tf.keras.Model):\n",
+    "  def __init__(self, label_index=None):\n",
+    "    super().__init__()\n",
+    "    self.label_index = label_index\n",
+    "\n",
+    "  def call(self, inputs):\n",
+    "    if self.label_index is None:\n",
+    "      return inputs\n",
+    "    result = inputs[:, :, self.label_index]\n",
+    "    return result[:, :, tf.newaxis]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "0vb3f948i8p8"
+   },
+   "source": [
+    "Instantiate and evaluate this model:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:10.860747Z",
+     "iopub.status.busy": "2023-07-27T04:27:10.860532Z",
+     "iopub.status.idle": "2023-07-27T04:27:12.250609Z",
+     "shell.execute_reply": "2023-07-27T04:27:12.249842Z"
+    },
+    "id": "IS3-QKc4sX0D"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "  1/439 [..............................] - ETA: 1:14 - loss: 0.0128 - mean_absolute_error: 0.087\n",
+      " 29/439 [>.............................] - ETA: 0s - loss: 0.0131 - mean_absolute_error: 0.0808 \n",
+      " 59/439 [===>..........................] - ETA: 0s - loss: 0.0127 - mean_absolute_error: 0.080\n",
+      " 91/439 [=====>........................] - ETA: 0s - loss: 0.0133 - mean_absolute_error: 0.080\n",
+      "123/439 [=======>......................] - ETA: 0s - loss: 0.0133 - mean_absolute_error: 0.079\n",
+      "153/439 [=========>....................] - ETA: 0s - loss: 0.0130 - mean_absolute_error: 0.079\n",
+      "184/439 [===========>..................] - ETA: 0s - loss: 0.0133 - mean_absolute_error: 0.079\n",
+      "213/439 [=============>................] - ETA: 0s - loss: 0.0129 - mean_absolute_error: 0.078\n",
+      "244/439 [===============>..............] - ETA: 0s - loss: 0.0130 - mean_absolute_error: 0.079\n",
+      "275/439 [=================>............] - ETA: 0s - loss: 0.0128 - mean_absolute_error: 0.078\n",
+      "306/439 [===================>..........] - ETA: 0s - loss: 0.0127 - mean_absolute_error: 0.078\n",
+      "338/439 [======================>.......] - ETA: 0s - loss: 0.0127 - mean_absolute_error: 0.078\n",
+      "370/439 [========================>.....] - ETA: 0s - loss: 0.0128 - mean_absolute_error: 0.078\n",
+      "400/439 [==========================>...] - ETA: 0s - loss: 0.0130 - mean_absolute_error: 0.078\n",
+      "430/439 [============================>.] - ETA: 0s - loss: 0.0129 - mean_absolute_error: 0.078\n",
+      "439/439 [==============================] - 1s 2ms/step - loss: 0.0128 - mean_absolute_error: 0.0785\n"
+     ]
+    }
+   ],
+   "source": [
+    "baseline = Baseline(label_index=column_indices['T (degC)'])\n",
+    "\n",
+    "baseline.compile(loss=tf.keras.losses.MeanSquaredError(),\n",
+    "                 metrics=[tf.keras.metrics.MeanAbsoluteError()])\n",
+    "\n",
+    "val_performance = {}\n",
+    "performance = {}\n",
+    "val_performance['Baseline'] = baseline.evaluate(single_step_window.val)\n",
+    "performance['Baseline'] = baseline.evaluate(single_step_window.test, verbose=0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "nhBxQcCSs7Ec"
+   },
+   "source": [
+    "That printed some performance metrics, but those don't give you a feeling for how well the model is doing.\n",
+    "\n",
+    "The `WindowGenerator` has a plot method, but the plots won't be very interesting with only a single sample.\n",
+    "\n",
+    "So, create a wider `WindowGenerator` that generates windows 24 hours of consecutive inputs and labels at a time. The new `wide_window` variable doesn't change the way the model operates. The model still makes predictions one hour into the future based on a single input time step. Here, the `time` axis acts like the `batch` axis: each prediction is made independently with no interaction between time steps:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:12.254178Z",
+     "iopub.status.busy": "2023-07-27T04:27:12.253926Z",
+     "iopub.status.idle": "2023-07-27T04:27:12.258999Z",
+     "shell.execute_reply": "2023-07-27T04:27:12.258452Z"
+    },
+    "id": "C8jNR5uuJ5Zp"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Total window size: 25\n",
+       "Input indices: [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23]\n",
+       "Label indices: [ 1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24]\n",
+       "Label column name(s): ['T (degC)']"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "wide_window = WindowGenerator(\n",
+    "    input_width=24, label_width=24, shift=1,\n",
+    "    label_columns=['T (degC)'])\n",
+    "\n",
+    "wide_window"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "ZAnj7CFZkuYv"
+   },
+   "source": [
+    "This expanded window can be passed directly to the same `baseline` model without any code changes. This is possible because the inputs and labels have the same number of time steps, and the baseline just forwards the input to the output:\n",
+    "\n",
+    "![One prediction 1h into the future, ever hour.](images/last_window.png)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:12.261636Z",
+     "iopub.status.busy": "2023-07-27T04:27:12.261418Z",
+     "iopub.status.idle": "2023-07-27T04:27:12.363780Z",
+     "shell.execute_reply": "2023-07-27T04:27:12.363047Z"
+    },
+    "id": "sGKdvdg087qs"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Input shape: (32, 24, 19)\n",
+      "Output shape: (32, 24, 1)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('Input shape:', wide_window.example[0].shape)\n",
+    "print('Output shape:', baseline(wide_window.example[0]).shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "SKqQHX1K0JW-"
+   },
+   "source": [
+    "By plotting the baseline model's predictions, notice that it is simply the labels shifted right by one hour:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:12.366870Z",
+     "iopub.status.busy": "2023-07-27T04:27:12.366610Z",
+     "iopub.status.idle": "2023-07-27T04:27:12.907628Z",
+     "shell.execute_reply": "2023-07-27T04:27:12.906930Z"
+    },
+    "id": "jQyAPVLgWTOZ"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "wide_window.plot(baseline)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "e93TLUhfAVg2"
+   },
+   "source": [
+    "In the above plots of three examples the single step model is run over the course of 24 hours. This deserves some explanation:\n",
+    "\n",
+    "- The blue `Inputs` line shows the input temperature at each time step. The model receives all features, this plot only shows the temperature.\n",
+    "- The green `Labels` dots show the target prediction value. These dots are shown at the prediction time, not the input time. That is why the range of labels is shifted 1 step relative to the inputs.\n",
+    "- The orange `Predictions` crosses are the model's prediction's for each output time step. If the model were predicting perfectly the predictions would land directly on the `Labels`."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "E4aOJScj52Yu"
+   },
+   "source": [
+    "### Linear model\n",
+    "\n",
+    "The simplest **trainable** model you can apply to this task is to insert linear transformation between the input and output. In this case the output from a time step only depends on that step:\n",
+    "\n",
+    "![A single step prediction](images/narrow_window.png)\n",
+    "\n",
+    "A `tf.keras.layers.Dense` layer with no `activation` set is a linear model. The layer only transforms the last axis of the data from `(batch, time, inputs)` to `(batch, time, units)`; it is applied independently to every item across the `batch` and `time` axes."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:12.912127Z",
+     "iopub.status.busy": "2023-07-27T04:27:12.911883Z",
+     "iopub.status.idle": "2023-07-27T04:27:12.920328Z",
+     "shell.execute_reply": "2023-07-27T04:27:12.919746Z"
+    },
+    "id": "6341OXuQ5xA9"
+   },
+   "outputs": [],
+   "source": [
+    "linear = tf.keras.Sequential([\n",
+    "    tf.keras.layers.Dense(units=1)\n",
+    "])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:12.923323Z",
+     "iopub.status.busy": "2023-07-27T04:27:12.923109Z",
+     "iopub.status.idle": "2023-07-27T04:27:13.331025Z",
+     "shell.execute_reply": "2023-07-27T04:27:13.330332Z"
+    },
+    "id": "KwaOM8RucUSn"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Input shape: (32, 1, 19)\n",
+      "Output shape: (32, 1, 1)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('Input shape:', single_step_window.example[0].shape)\n",
+    "print('Output shape:', linear(single_step_window.example[0]).shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "OMZTYIj3bYLg"
+   },
+   "source": [
+    "This tutorial trains many models, so package the training procedure into a function:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:13.334544Z",
+     "iopub.status.busy": "2023-07-27T04:27:13.334284Z",
+     "iopub.status.idle": "2023-07-27T04:27:13.339103Z",
+     "shell.execute_reply": "2023-07-27T04:27:13.338513Z"
+    },
+    "id": "CbCL6VIrk-Gt"
+   },
+   "outputs": [],
+   "source": [
+    "MAX_EPOCHS = 20\n",
+    "\n",
+    "def compile_and_fit(model, window, patience=2):\n",
+    "  early_stopping = tf.keras.callbacks.EarlyStopping(monitor='val_loss',\n",
+    "                                                    patience=patience,\n",
+    "                                                    mode='min')\n",
+    "\n",
+    "  model.compile(loss=tf.keras.losses.MeanSquaredError(),\n",
+    "                optimizer=tf.keras.optimizers.Adam(),\n",
+    "                metrics=[tf.keras.metrics.MeanAbsoluteError()])\n",
+    "\n",
+    "  history = model.fit(window.train, epochs=MAX_EPOCHS,\n",
+    "                      validation_data=window.val,\n",
+    "                      callbacks=[early_stopping])\n",
+    "  return history"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "OobVjM-schwj"
+   },
+   "source": [
+    "Train the model and evaluate its performance:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:27:13.342075Z",
+     "iopub.status.busy": "2023-07-27T04:27:13.341855Z",
+     "iopub.status.idle": "2023-07-27T04:28:11.220323Z",
+     "shell.execute_reply": "2023-07-27T04:28:11.219550Z"
+    },
+    "id": "9agbz2qB9bLS"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 1/20\n",
+      "\n",
+      "   1/1534 [..............................] - ETA: 21:37 - loss: 2.5731 - mean_absolute_error: 1.21\n",
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+      "1534/1534 [==============================] - 4s 3ms/step - loss: 0.0090 - mean_absolute_error: 0.0696 - val_loss: 0.0087 - val_mean_absolute_error: 0.0691\n",
+      "Epoch 12/20\n",
+      "\n",
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
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+      "1534/1534 [==============================] - 4s 3ms/step - loss: 0.0090 - mean_absolute_error: 0.0696 - val_loss: 0.0088 - val_mean_absolute_error: 0.0699\n",
+      "Epoch 13/20\n",
+      "\n",
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+      "1534/1534 [==============================] - 4s 3ms/step - loss: 0.0090 - mean_absolute_error: 0.0695 - val_loss: 0.0088 - val_mean_absolute_error: 0.0697\n",
+      "\n",
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
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+      "439/439 [==============================] - 1s 2ms/step - loss: 0.0088 - mean_absolute_error: 0.0697\n"
+     ]
+    }
+   ],
+   "source": [
+    "history = compile_and_fit(linear, single_step_window)\n",
+    "\n",
+    "val_performance['Linear'] = linear.evaluate(single_step_window.val)\n",
+    "performance['Linear'] = linear.evaluate(single_step_window.test, verbose=0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "7U9XukYh8beN"
+   },
+   "source": [
+    "Like the `baseline` model, the linear model can be called on batches of wide windows. Used this way the model makes a set of independent predictions on consecutive time steps. The `time` axis acts like another `batch` axis. There are no interactions between the predictions at each time step.\n",
+    "\n",
+    "![A single step prediction](images/wide_window.png)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:28:11.224571Z",
+     "iopub.status.busy": "2023-07-27T04:28:11.223940Z",
+     "iopub.status.idle": "2023-07-27T04:28:11.245887Z",
+     "shell.execute_reply": "2023-07-27T04:28:11.245217Z"
+    },
+    "id": "K9UVM5Sw9KQN"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Input shape: (32, 24, 19)\n",
+      "Output shape: (32, 24, 1)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('Input shape:', wide_window.example[0].shape)\n",
+    "print('Output shape:', linear(wide_window.example[0]).shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "X-CGj85oKaOG"
+   },
+   "source": [
+    "Here is the plot of its example predictions on the `wide_window`, note how in many cases the prediction is clearly better than just returning the input temperature, but in a few cases it's worse:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:28:11.249222Z",
+     "iopub.status.busy": "2023-07-27T04:28:11.249004Z",
+     "iopub.status.idle": "2023-07-27T04:28:11.728373Z",
+     "shell.execute_reply": "2023-07-27T04:28:11.727741Z"
+    },
+    "id": "bCC8VVo-OvwV"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "wide_window.plot(linear)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Is51vU8EMl6c"
+   },
+   "source": [
+    "One advantage to linear models is that they're relatively simple to  interpret.\n",
+    "You can pull out the layer's weights and visualize the weight assigned to each input:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:28:11.732273Z",
+     "iopub.status.busy": "2023-07-27T04:28:11.732023Z",
+     "iopub.status.idle": "2023-07-27T04:28:11.958362Z",
+     "shell.execute_reply": "2023-07-27T04:28:11.957766Z"
+    },
+    "id": "d4uCTbsmK8VI"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.bar(x = range(len(train_df.columns)),\n",
+    "        height=linear.layers[0].kernel[:,0].numpy())\n",
+    "axis = plt.gca()\n",
+    "axis.set_xticks(range(len(train_df.columns)))\n",
+    "_ = axis.set_xticklabels(train_df.columns, rotation=90)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Ylng7215boIY"
+   },
+   "source": [
+    "Sometimes the model doesn't even place the most weight on the input `T (degC)`. This is one of the risks of random initialization. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "W18e6da1cNbw"
+   },
+   "source": [
+    "### Dense\n",
+    "\n",
+    "Before applying models that actually operate on multiple time-steps, it's worth checking the performance of deeper, more powerful, single input step models.\n",
+    "\n",
+    "Here's a model similar to the `linear` model, except it stacks several a few `Dense` layers between the input and the output: "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:28:11.961635Z",
+     "iopub.status.busy": "2023-07-27T04:28:11.961380Z",
+     "iopub.status.idle": "2023-07-27T04:28:49.496626Z",
+     "shell.execute_reply": "2023-07-27T04:28:49.495872Z"
+    },
+    "id": "Z86WkYp7cNAD"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 1/20\n",
+      "\n",
+      "   1/1534 [..............................] - ETA: 32:00 - loss: 1.6370 - mean_absolute_error: 1.00\n",
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1434/1534 [===========================>..] - ETA: 0s - loss: 0.0183 - mean_absolute_error: 0.080\n",
+      "1451/1534 [===========================>..] - ETA: 0s - loss: 0.0182 - mean_absolute_error: 0.080\n",
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+      "1534/1534 [==============================] - 7s 4ms/step - loss: 0.0177 - mean_absolute_error: 0.0793 - val_loss: 0.0080 - val_mean_absolute_error: 0.0655\n",
+      "Epoch 2/20\n",
+      "\n",
+      "   1/1534 [..............................] - ETA: 38s - loss: 0.0074 - mean_absolute_error: 0.06\n",
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
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+      "1534/1534 [==============================] - 6s 4ms/step - loss: 0.0079 - mean_absolute_error: 0.0648 - val_loss: 0.0072 - val_mean_absolute_error: 0.0608\n",
+      "Epoch 3/20\n",
+      "\n",
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+      "219/439 [=============>................] - ETA: 0s - loss: 0.0076 - mean_absolute_error: 0.064\n",
+      "240/439 [===============>..............] - ETA: 0s - loss: 0.0076 - mean_absolute_error: 0.063\n",
+      "262/439 [================>.............] - ETA: 0s - loss: 0.0076 - mean_absolute_error: 0.064\n",
+      "283/439 [==================>...........] - ETA: 0s - loss: 0.0076 - mean_absolute_error: 0.064\n",
+      "304/439 [===================>..........] - ETA: 0s - loss: 0.0076 - mean_absolute_error: 0.064\n",
+      "326/439 [=====================>........] - ETA: 0s - loss: 0.0076 - mean_absolute_error: 0.063\n",
+      "347/439 [======================>.......] - ETA: 0s - loss: 0.0075 - mean_absolute_error: 0.063\n",
+      "368/439 [========================>.....] - ETA: 0s - loss: 0.0075 - mean_absolute_error: 0.063\n",
+      "389/439 [=========================>....] - ETA: 0s - loss: 0.0074 - mean_absolute_error: 0.063\n",
+      "411/439 [===========================>..] - ETA: 0s - loss: 0.0075 - mean_absolute_error: 0.063\n",
+      "433/439 [============================>.] - ETA: 0s - loss: 0.0075 - mean_absolute_error: 0.063\n",
+      "439/439 [==============================] - 1s 2ms/step - loss: 0.0075 - mean_absolute_error: 0.0636\n"
+     ]
+    }
+   ],
+   "source": [
+    "dense = tf.keras.Sequential([\n",
+    "    tf.keras.layers.Dense(units=64, activation='relu'),\n",
+    "    tf.keras.layers.Dense(units=64, activation='relu'),\n",
+    "    tf.keras.layers.Dense(units=1)\n",
+    "])\n",
+    "\n",
+    "history = compile_and_fit(dense, single_step_window)\n",
+    "\n",
+    "val_performance['Dense'] = dense.evaluate(single_step_window.val)\n",
+    "performance['Dense'] = dense.evaluate(single_step_window.test, verbose=0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "j5dv_whJdswH"
+   },
+   "source": [
+    "### Multi-step dense\n",
+    "\n",
+    "A single-time-step model has no context for the current values of its inputs. It can't see how the input features are changing over time. To address this issue the model needs access to multiple time steps when making predictions:\n",
+    "\n",
+    "![Three time steps are used for each prediction.](images/conv_window.png)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Zac-ti8agbJ7"
+   },
+   "source": [
+    "The `baseline`, `linear` and `dense` models handled each time step independently. Here the model will take multiple time steps as input to produce a single output.\n",
+    "\n",
+    "Create a `WindowGenerator` that will produce batches of three-hour inputs and one-hour labels:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "gtN4BwZ37niR"
+   },
+   "source": [
+    "Note that the `Window`'s `shift` parameter is relative to the end of the two windows.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:28:49.501135Z",
+     "iopub.status.busy": "2023-07-27T04:28:49.500877Z",
+     "iopub.status.idle": "2023-07-27T04:28:49.506291Z",
+     "shell.execute_reply": "2023-07-27T04:28:49.505680Z"
+    },
+    "id": "lBh0j5djUKY2"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Total window size: 4\n",
+       "Input indices: [0 1 2]\n",
+       "Label indices: [3]\n",
+       "Label column name(s): ['T (degC)']"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "CONV_WIDTH = 3\n",
+    "conv_window = WindowGenerator(\n",
+    "    input_width=CONV_WIDTH,\n",
+    "    label_width=1,\n",
+    "    shift=1,\n",
+    "    label_columns=['T (degC)'])\n",
+    "\n",
+    "conv_window"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:28:49.509257Z",
+     "iopub.status.busy": "2023-07-27T04:28:49.509043Z",
+     "iopub.status.idle": "2023-07-27T04:28:50.112373Z",
+     "shell.execute_reply": "2023-07-27T04:28:50.111714Z"
+    },
+    "id": "dCQ5gvs68Xkd"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'Given 3 hours of inputs, predict 1 hour into the future.')"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "conv_window.plot()\n",
+    "plt.title(\"Given 3 hours of inputs, predict 1 hour into the future.\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "We0HdMxKeqB_"
+   },
+   "source": [
+    "You could train a `dense` model on a multiple-input-step window by adding a `tf.keras.layers.Flatten` as the first layer of the model:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:28:50.116292Z",
+     "iopub.status.busy": "2023-07-27T04:28:50.116059Z",
+     "iopub.status.idle": "2023-07-27T04:28:50.128093Z",
+     "shell.execute_reply": "2023-07-27T04:28:50.127515Z"
+    },
+    "id": "oNQnUOkOnC1G"
+   },
+   "outputs": [],
+   "source": [
+    "multi_step_dense = tf.keras.Sequential([\n",
+    "    # Shape: (time, features) => (time*features)\n",
+    "    tf.keras.layers.Flatten(),\n",
+    "    tf.keras.layers.Dense(units=32, activation='relu'),\n",
+    "    tf.keras.layers.Dense(units=32, activation='relu'),\n",
+    "    tf.keras.layers.Dense(units=1),\n",
+    "    # Add back the time dimension.\n",
+    "    # Shape: (outputs) => (1, outputs)\n",
+    "    tf.keras.layers.Reshape([1, -1]),\n",
+    "])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:28:50.131045Z",
+     "iopub.status.busy": "2023-07-27T04:28:50.130593Z",
+     "iopub.status.idle": "2023-07-27T04:28:50.183111Z",
+     "shell.execute_reply": "2023-07-27T04:28:50.182529Z"
+    },
+    "id": "cayD74luo4Vq"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Input shape: (32, 3, 19)\n",
+      "Output shape: (32, 1, 1)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('Input shape:', conv_window.example[0].shape)\n",
+    "print('Output shape:', multi_step_dense(conv_window.example[0]).shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:28:50.186247Z",
+     "iopub.status.busy": "2023-07-27T04:28:50.185678Z",
+     "iopub.status.idle": "2023-07-27T04:29:53.501985Z",
+     "shell.execute_reply": "2023-07-27T04:29:53.501229Z"
+    },
+    "id": "fu91yEbRo9-J"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "  1/438 [..............................] - ETA: 24s - loss: 0.0105 - mean_absolute_error: 0.07\n",
+      " 28/438 [>.............................] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.0634\n",
+      " 56/438 [==>...........................] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.062\n",
+      " 83/438 [====>.........................] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.061\n",
+      "111/438 [======>.......................] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.062\n",
+      "140/438 [========>.....................] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.061\n",
+      "170/438 [==========>...................] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.061\n",
+      "200/438 [============>.................] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.061\n",
+      "227/438 [==============>...............] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.061\n",
+      "254/438 [================>.............] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.061\n",
+      "281/438 [==================>...........] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.061\n",
+      "310/438 [====================>.........] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.061\n",
+      "339/438 [======================>.......] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.061\n",
+      "368/438 [========================>.....] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.061\n",
+      "396/438 [==========================>...] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.061\n",
+      "424/438 [============================>.] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.061\n",
+      "438/438 [==============================] - 1s 2ms/step - loss: 0.0072 - mean_absolute_error: 0.0618\n"
+     ]
+    }
+   ],
+   "source": [
+    "history = compile_and_fit(multi_step_dense, conv_window)\n",
+    "\n",
+    "IPython.display.clear_output()\n",
+    "val_performance['Multi step dense'] = multi_step_dense.evaluate(conv_window.val)\n",
+    "performance['Multi step dense'] = multi_step_dense.evaluate(conv_window.test, verbose=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:29:53.505956Z",
+     "iopub.status.busy": "2023-07-27T04:29:53.505386Z",
+     "iopub.status.idle": "2023-07-27T04:29:54.270901Z",
+     "shell.execute_reply": "2023-07-27T04:29:54.270094Z"
+    },
+    "id": "tnqdXYT6pkEh"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "conv_window.plot(multi_step_dense)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "gWfrsP8mq8lV"
+   },
+   "source": [
+    "The main down-side of this approach is that the resulting model can only be executed on input windows of exactly this shape. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:29:54.274703Z",
+     "iopub.status.busy": "2023-07-27T04:29:54.274323Z",
+     "iopub.status.idle": "2023-07-27T04:29:54.304022Z",
+     "shell.execute_reply": "2023-07-27T04:29:54.303424Z"
+    },
+    "id": "j-q6tz5Yq8Jk"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Input shape: (32, 24, 19)\n",
+      "\n",
+      "ValueError:Exception encountered when calling layer 'sequential_2' (type Sequential).\n",
+      "\n",
+      "Input 0 of layer \"dense_4\" is incompatible with the layer: expected axis -1 of input shape to have value 57, but received input with shape (32, 456)\n",
+      "\n",
+      "Call arguments received by layer 'sequential_2' (type Sequential):\n",
+      "  • inputs=tf.Tensor(shape=(32, 24, 19), dtype=float32)\n",
+      "  • training=None\n",
+      "  • mask=None\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('Input shape:', wide_window.example[0].shape)\n",
+    "try:\n",
+    "  print('Output shape:', multi_step_dense(wide_window.example[0]).shape)\n",
+    "except Exception as e:\n",
+    "  print(f'\\n{type(e).__name__}:{e}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "bvvajm3ip_8V"
+   },
+   "source": [
+    "The convolutional models in the next section fix this problem."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "CrpU6gwSJome"
+   },
+   "source": [
+    "### Convolution neural network\n",
+    " \n",
+    "A convolution layer (`tf.keras.layers.Conv1D`) also takes multiple time steps as input to each prediction."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "cdLBwoaHmsWb"
+   },
+   "source": [
+    "Below is the **same** model as `multi_step_dense`, re-written with a convolution. \n",
+    "\n",
+    "Note the changes:\n",
+    "* The `tf.keras.layers.Flatten` and the first `tf.keras.layers.Dense` are replaced by a `tf.keras.layers.Conv1D`.\n",
+    "* The `tf.keras.layers.Reshape` is no longer necessary since the convolution keeps the time axis in its output."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:29:54.307394Z",
+     "iopub.status.busy": "2023-07-27T04:29:54.307173Z",
+     "iopub.status.idle": "2023-07-27T04:29:54.316432Z",
+     "shell.execute_reply": "2023-07-27T04:29:54.315864Z"
+    },
+    "id": "5azaMBj4ac9t"
+   },
+   "outputs": [],
+   "source": [
+    "conv_model = tf.keras.Sequential([\n",
+    "    tf.keras.layers.Conv1D(filters=32,\n",
+    "                           kernel_size=(CONV_WIDTH,),\n",
+    "                           activation='relu'),\n",
+    "    tf.keras.layers.Dense(units=32, activation='relu'),\n",
+    "    tf.keras.layers.Dense(units=1),\n",
+    "])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "ftaH6B5ECRiK"
+   },
+   "source": [
+    "Run it on an example batch to check that the model produces outputs with the expected shape:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:29:54.319462Z",
+     "iopub.status.busy": "2023-07-27T04:29:54.319253Z",
+     "iopub.status.idle": "2023-07-27T04:29:54.360919Z",
+     "shell.execute_reply": "2023-07-27T04:29:54.360227Z"
+    },
+    "id": "5YNgt1-e98lH"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Conv model on `conv_window`\n",
+      "Input shape: (32, 3, 19)\n",
+      "Output shape: (32, 1, 1)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Conv model on `conv_window`\")\n",
+    "print('Input shape:', conv_window.example[0].shape)\n",
+    "print('Output shape:', conv_model(conv_window.example[0]).shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "5m4kC-jGCY3x"
+   },
+   "source": [
+    "Train and evaluate it on the ` conv_window` and it should give performance similar to the `multi_step_dense` model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:29:54.364019Z",
+     "iopub.status.busy": "2023-07-27T04:29:54.363798Z",
+     "iopub.status.idle": "2023-07-27T04:30:56.329899Z",
+     "shell.execute_reply": "2023-07-27T04:30:56.329167Z"
+    },
+    "id": "QDVWdm4paUW7"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "  1/438 [..............................] - ETA: 25s - loss: 0.0058 - mean_absolute_error: 0.06\n",
+      " 22/438 [>.............................] - ETA: 1s - loss: 0.0057 - mean_absolute_error: 0.0551\n",
+      " 43/438 [=>............................] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.056\n",
+      " 66/438 [===>..........................] - ETA: 0s - loss: 0.0063 - mean_absolute_error: 0.056\n",
+      " 88/438 [=====>........................] - ETA: 0s - loss: 0.0063 - mean_absolute_error: 0.056\n",
+      "110/438 [======>.......................] - ETA: 0s - loss: 0.0063 - mean_absolute_error: 0.056\n",
+      "132/438 [========>.....................] - ETA: 0s - loss: 0.0062 - mean_absolute_error: 0.055\n",
+      "156/438 [=========>....................] - ETA: 0s - loss: 0.0062 - mean_absolute_error: 0.055\n",
+      "179/438 [===========>..................] - ETA: 0s - loss: 0.0062 - mean_absolute_error: 0.055\n",
+      "203/438 [============>.................] - ETA: 0s - loss: 0.0061 - mean_absolute_error: 0.055\n",
+      "226/438 [==============>...............] - ETA: 0s - loss: 0.0062 - mean_absolute_error: 0.055\n",
+      "249/438 [================>.............] - ETA: 0s - loss: 0.0061 - mean_absolute_error: 0.054\n",
+      "272/438 [=================>............] - ETA: 0s - loss: 0.0062 - mean_absolute_error: 0.055\n",
+      "295/438 [===================>..........] - ETA: 0s - loss: 0.0063 - mean_absolute_error: 0.055\n",
+      "318/438 [====================>.........] - ETA: 0s - loss: 0.0063 - mean_absolute_error: 0.055\n",
+      "341/438 [======================>.......] - ETA: 0s - loss: 0.0062 - mean_absolute_error: 0.055\n",
+      "364/438 [=======================>......] - ETA: 0s - loss: 0.0062 - mean_absolute_error: 0.055\n",
+      "387/438 [=========================>....] - ETA: 0s - loss: 0.0062 - mean_absolute_error: 0.054\n",
+      "410/438 [===========================>..] - ETA: 0s - loss: 0.0061 - mean_absolute_error: 0.054\n",
+      "434/438 [============================>.] - ETA: 0s - loss: 0.0061 - mean_absolute_error: 0.054\n",
+      "438/438 [==============================] - 1s 2ms/step - loss: 0.0061 - mean_absolute_error: 0.0546\n"
+     ]
+    }
+   ],
+   "source": [
+    "history = compile_and_fit(conv_model, conv_window)\n",
+    "\n",
+    "IPython.display.clear_output()\n",
+    "val_performance['Conv'] = conv_model.evaluate(conv_window.val)\n",
+    "performance['Conv'] = conv_model.evaluate(conv_window.test, verbose=0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "sYRipDeXs0Kr"
+   },
+   "source": [
+    "The difference between this `conv_model` and the `multi_step_dense` model is that the `conv_model` can be run on inputs of any length. The convolutional layer is applied to a sliding window of inputs:\n",
+    "\n",
+    "![Executing a convolutional model on a sequence](images/wide_conv_window.png)\n",
+    "\n",
+    "If you run it on wider input, it produces wider output:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:30:56.334173Z",
+     "iopub.status.busy": "2023-07-27T04:30:56.333523Z",
+     "iopub.status.idle": "2023-07-27T04:30:56.386174Z",
+     "shell.execute_reply": "2023-07-27T04:30:56.385493Z"
+    },
+    "id": "hoqccxx9r5jF"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Wide window\n",
+      "Input shape: (32, 24, 19)\n",
+      "Labels shape: (32, 24, 1)\n",
+      "Output shape: (32, 22, 1)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Wide window\")\n",
+    "print('Input shape:', wide_window.example[0].shape)\n",
+    "print('Labels shape:', wide_window.example[1].shape)\n",
+    "print('Output shape:', conv_model(wide_window.example[0]).shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "h_WGxtLIHhRF"
+   },
+   "source": [
+    "Note that the output is shorter than the input. To make training or plotting work, you need the labels, and prediction to have the same length. So build a `WindowGenerator` to produce wide windows with a few extra input time steps so the label and prediction lengths match: "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:30:56.389181Z",
+     "iopub.status.busy": "2023-07-27T04:30:56.388964Z",
+     "iopub.status.idle": "2023-07-27T04:30:56.394006Z",
+     "shell.execute_reply": "2023-07-27T04:30:56.393460Z"
+    },
+    "id": "_VPvJ_VwTc0f"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Total window size: 27\n",
+       "Input indices: [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23\n",
+       " 24 25]\n",
+       "Label indices: [ 3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26]\n",
+       "Label column name(s): ['T (degC)']"
+      ]
+     },
+     "execution_count": 58,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "LABEL_WIDTH = 24\n",
+    "INPUT_WIDTH = LABEL_WIDTH + (CONV_WIDTH - 1)\n",
+    "wide_conv_window = WindowGenerator(\n",
+    "    input_width=INPUT_WIDTH,\n",
+    "    label_width=LABEL_WIDTH,\n",
+    "    shift=1,\n",
+    "    label_columns=['T (degC)'])\n",
+    "\n",
+    "wide_conv_window"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:30:56.397141Z",
+     "iopub.status.busy": "2023-07-27T04:30:56.396626Z",
+     "iopub.status.idle": "2023-07-27T04:30:56.507243Z",
+     "shell.execute_reply": "2023-07-27T04:30:56.506598Z"
+    },
+    "id": "gtqlWYXeKXej"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Wide conv window\n",
+      "Input shape: (32, 26, 19)\n",
+      "Labels shape: (32, 24, 1)\n",
+      "Output shape: (32, 24, 1)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Wide conv window\")\n",
+    "print('Input shape:', wide_conv_window.example[0].shape)\n",
+    "print('Labels shape:', wide_conv_window.example[1].shape)\n",
+    "print('Output shape:', conv_model(wide_conv_window.example[0]).shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "yzxbbS56cSBV"
+   },
+   "source": [
+    "Now, you can plot the model's predictions on a wider window. Note the 3 input time steps before the first prediction. Every prediction here is based on the 3 preceding time steps:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:30:56.510516Z",
+     "iopub.status.busy": "2023-07-27T04:30:56.510212Z",
+     "iopub.status.idle": "2023-07-27T04:30:57.009411Z",
+     "shell.execute_reply": "2023-07-27T04:30:57.008640Z"
+    },
+    "id": "gR7VyL45UuEe"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "wide_conv_window.plot(conv_model)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "H4crpOcoMlSe"
+   },
+   "source": [
+    "### Recurrent neural network\n",
+    "\n",
+    "A Recurrent Neural Network (RNN) is a type of neural network well-suited to time series data. RNNs process a time series step-by-step, maintaining an internal state from time-step to time-step.\n",
+    "\n",
+    "You can learn more in the [Text generation with an RNN](https://www.tensorflow.org/text/tutorials/text_generation) tutorial and the [Recurrent Neural Networks (RNN) with Keras](https://www.tensorflow.org/guide/keras/rnn) guide.\n",
+    "\n",
+    "In this tutorial, you will use an RNN layer called Long Short-Term Memory (`tf.keras.layers.LSTM`)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "vfQbHSMb1ATa"
+   },
+   "source": [
+    "An important constructor argument for all Keras RNN layers, such as `tf.keras.layers.LSTM`, is the `return_sequences` argument. This setting can configure the layer in one of two ways:\n",
+    "\n",
+    "1. If `False`, the default, the layer only returns the output of the final time step, giving the model time to warm up its internal state before making a single prediction: \n",
+    "\n",
+    "![An LSTM warming up and making a single prediction](images/lstm_1_window.png)\n",
+    "\n",
+    "2. If `True`, the layer returns an output for each input. This is useful for:\n",
+    "  * Stacking RNN layers. \n",
+    "  * Training a model on multiple time steps simultaneously.\n",
+    "\n",
+    "![An LSTM making a prediction after every time step](images/lstm_many_window.png)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:30:57.014136Z",
+     "iopub.status.busy": "2023-07-27T04:30:57.013845Z",
+     "iopub.status.idle": "2023-07-27T04:30:57.027554Z",
+     "shell.execute_reply": "2023-07-27T04:30:57.026854Z"
+    },
+    "id": "DXKLCJy8nWNU"
+   },
+   "outputs": [],
+   "source": [
+    "lstm_model = tf.keras.models.Sequential([\n",
+    "    # Shape [batch, time, features] => [batch, time, lstm_units]\n",
+    "    tf.keras.layers.LSTM(32, return_sequences=True),\n",
+    "    # Shape => [batch, time, features]\n",
+    "    tf.keras.layers.Dense(units=1)\n",
+    "])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "F124B00KZcLC"
+   },
+   "source": [
+    "With `return_sequences=True`, the model can be trained on 24 hours of data at a time.\n",
+    "\n",
+    "Note: This will give a pessimistic view of the model's performance. On the first time step, the model has no access to previous steps and, therefore, can't do any better than the simple `linear` and `dense` models shown earlier."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:30:57.031149Z",
+     "iopub.status.busy": "2023-07-27T04:30:57.030867Z",
+     "iopub.status.idle": "2023-07-27T04:30:57.337848Z",
+     "shell.execute_reply": "2023-07-27T04:30:57.337109Z"
+    },
+    "id": "eZEROCQVYV6q"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Input shape: (32, 24, 19)\n",
+      "Output shape: (32, 24, 1)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('Input shape:', wide_window.example[0].shape)\n",
+    "print('Output shape:', lstm_model(wide_window.example[0]).shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:30:57.341158Z",
+     "iopub.status.busy": "2023-07-27T04:30:57.340894Z",
+     "iopub.status.idle": "2023-07-27T04:32:20.233986Z",
+     "shell.execute_reply": "2023-07-27T04:32:20.233142Z"
+    },
+    "id": "uvdWRl1e9WJl"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "  1/438 [..............................] - ETA: 24s - loss: 0.0045 - mean_absolute_error: 0.04\n",
+      " 18/438 [>.............................] - ETA: 1s - loss: 0.0055 - mean_absolute_error: 0.0516\n",
+      " 36/438 [=>............................] - ETA: 1s - loss: 0.0056 - mean_absolute_error: 0.051\n",
+      " 54/438 [==>...........................] - ETA: 1s - loss: 0.0055 - mean_absolute_error: 0.051\n",
+      " 73/438 [====>.........................] - ETA: 1s - loss: 0.0055 - mean_absolute_error: 0.051\n",
+      " 92/438 [=====>........................] - ETA: 0s - loss: 0.0055 - mean_absolute_error: 0.051\n",
+      "110/438 [======>.......................] - ETA: 0s - loss: 0.0055 - mean_absolute_error: 0.051\n",
+      "130/438 [=======>......................] - ETA: 0s - loss: 0.0055 - mean_absolute_error: 0.051\n",
+      "149/438 [=========>....................] - ETA: 0s - loss: 0.0055 - mean_absolute_error: 0.051\n",
+      "167/438 [==========>...................] - ETA: 0s - loss: 0.0056 - mean_absolute_error: 0.051\n",
+      "185/438 [===========>..................] - ETA: 0s - loss: 0.0056 - mean_absolute_error: 0.051\n",
+      "203/438 [============>.................] - ETA: 0s - loss: 0.0056 - mean_absolute_error: 0.051\n",
+      "222/438 [==============>...............] - ETA: 0s - loss: 0.0056 - mean_absolute_error: 0.051\n",
+      "240/438 [===============>..............] - ETA: 0s - loss: 0.0056 - mean_absolute_error: 0.051\n",
+      "258/438 [================>.............] - ETA: 0s - loss: 0.0056 - mean_absolute_error: 0.051\n",
+      "276/438 [=================>............] - ETA: 0s - loss: 0.0056 - mean_absolute_error: 0.051\n",
+      "295/438 [===================>..........] - ETA: 0s - loss: 0.0055 - mean_absolute_error: 0.051\n",
+      "313/438 [====================>.........] - ETA: 0s - loss: 0.0056 - mean_absolute_error: 0.051\n",
+      "331/438 [=====================>........] - ETA: 0s - loss: 0.0056 - mean_absolute_error: 0.051\n",
+      "349/438 [======================>.......] - ETA: 0s - loss: 0.0056 - mean_absolute_error: 0.051\n",
+      "368/438 [========================>.....] - ETA: 0s - loss: 0.0056 - mean_absolute_error: 0.051\n",
+      "386/438 [=========================>....] - ETA: 0s - loss: 0.0056 - mean_absolute_error: 0.051\n",
+      "404/438 [==========================>...] - ETA: 0s - loss: 0.0056 - mean_absolute_error: 0.051\n",
+      "422/438 [===========================>..] - ETA: 0s - loss: 0.0056 - mean_absolute_error: 0.051\n",
+      "438/438 [==============================] - 1s 3ms/step - loss: 0.0056 - mean_absolute_error: 0.0516\n"
+     ]
+    }
+   ],
+   "source": [
+    "history = compile_and_fit(lstm_model, wide_window)\n",
+    "\n",
+    "IPython.display.clear_output()\n",
+    "val_performance['LSTM'] = lstm_model.evaluate(wide_window.val)\n",
+    "performance['LSTM'] = lstm_model.evaluate(wide_window.test, verbose=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:32:20.238119Z",
+     "iopub.status.busy": "2023-07-27T04:32:20.237543Z",
+     "iopub.status.idle": "2023-07-27T04:32:20.750675Z",
+     "shell.execute_reply": "2023-07-27T04:32:20.750002Z"
+    },
+    "id": "NwAOWCVgB26e"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "wide_window.plot(lstm_model)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "pYglOCKehi8F"
+   },
+   "source": [
+    "### Performance"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "2pCk0_rwhi8H"
+   },
+   "source": [
+    "With this dataset typically each of the models does slightly better than the one before it:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:32:20.754603Z",
+     "iopub.status.busy": "2023-07-27T04:32:20.754334Z",
+     "iopub.status.idle": "2023-07-27T04:32:20.950975Z",
+     "shell.execute_reply": "2023-07-27T04:32:20.950322Z"
+    },
+    "id": "JjEkt488hi8I"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "x = np.arange(len(performance))\n",
+    "width = 0.3\n",
+    "metric_name = 'mean_absolute_error'\n",
+    "metric_index = lstm_model.metrics_names.index('mean_absolute_error')\n",
+    "val_mae = [v[metric_index] for v in val_performance.values()]\n",
+    "test_mae = [v[metric_index] for v in performance.values()]\n",
+    "\n",
+    "plt.ylabel('mean_absolute_error [T (degC), normalized]')\n",
+    "plt.bar(x - 0.17, val_mae, width, label='Validation')\n",
+    "plt.bar(x + 0.17, test_mae, width, label='Test')\n",
+    "plt.xticks(ticks=x, labels=performance.keys(),\n",
+    "           rotation=45)\n",
+    "_ = plt.legend()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:32:20.954254Z",
+     "iopub.status.busy": "2023-07-27T04:32:20.953763Z",
+     "iopub.status.idle": "2023-07-27T04:32:20.957436Z",
+     "shell.execute_reply": "2023-07-27T04:32:20.956868Z"
+    },
+    "id": "cBMCpsdphi8L"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Baseline    : 0.0852\n",
+      "Linear      : 0.0688\n",
+      "Dense       : 0.0616\n",
+      "Multi step dense: 0.0663\n",
+      "Conv        : 0.0549\n",
+      "LSTM        : 0.0529\n"
+     ]
+    }
+   ],
+   "source": [
+    "for name, value in performance.items():\n",
+    "  print(f'{name:12s}: {value[1]:0.4f}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "b5rUJ_2YMWzG"
+   },
+   "source": [
+    "### Multi-output models\n",
+    "\n",
+    "The models so far all predicted a single output feature, `T (degC)`, for a single time step.\n",
+    "\n",
+    "All of these models can be converted to predict multiple features just by changing the number of units in the output layer and adjusting the training windows to include all features in the `labels` (`example_labels`):"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:32:20.960539Z",
+     "iopub.status.busy": "2023-07-27T04:32:20.960045Z",
+     "iopub.status.idle": "2023-07-27T04:32:21.072766Z",
+     "shell.execute_reply": "2023-07-27T04:32:21.072076Z"
+    },
+    "id": "9Gk0Z91xjOwv"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Inputs shape (batch, time, features): (32, 24, 19)\n",
+      "Labels shape (batch, time, features): (32, 24, 19)\n"
+     ]
+    }
+   ],
+   "source": [
+    "single_step_window = WindowGenerator(\n",
+    "    # `WindowGenerator` returns all features as labels if you \n",
+    "    # don't set the `label_columns` argument.\n",
+    "    input_width=1, label_width=1, shift=1)\n",
+    "\n",
+    "wide_window = WindowGenerator(\n",
+    "    input_width=24, label_width=24, shift=1)\n",
+    "\n",
+    "for example_inputs, example_labels in wide_window.train.take(1):\n",
+    "  print(f'Inputs shape (batch, time, features): {example_inputs.shape}')\n",
+    "  print(f'Labels shape (batch, time, features): {example_labels.shape}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "XmcjHfDskX1N"
+   },
+   "source": [
+    "Note above that the `features` axis of the labels now has the same depth as the inputs, instead of `1`."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "9k7S5IHNhSNF"
+   },
+   "source": [
+    "#### Baseline\n",
+    "\n",
+    "The same baseline model (`Baseline`) can be used here, but this time repeating all features instead of selecting a specific `label_index`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:32:21.076400Z",
+     "iopub.status.busy": "2023-07-27T04:32:21.075915Z",
+     "iopub.status.idle": "2023-07-27T04:32:21.089605Z",
+     "shell.execute_reply": "2023-07-27T04:32:21.089045Z"
+    },
+    "id": "sqqB9W-pjr5i"
+   },
+   "outputs": [],
+   "source": [
+    "baseline = Baseline()\n",
+    "baseline.compile(loss=tf.keras.losses.MeanSquaredError(),\n",
+    "                 metrics=[tf.keras.metrics.MeanAbsoluteError()])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:32:21.093093Z",
+     "iopub.status.busy": "2023-07-27T04:32:21.092531Z",
+     "iopub.status.idle": "2023-07-27T04:32:22.352656Z",
+     "shell.execute_reply": "2023-07-27T04:32:22.351893Z"
+    },
+    "id": "ltQdgaqQjQWu"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "  1/438 [..............................] - ETA: 46s - loss: 0.1003 - mean_absolute_error: 0.16\n",
+      " 30/438 [=>............................] - ETA: 0s - loss: 0.0881 - mean_absolute_error: 0.1586\n",
+      " 61/438 [===>..........................] - ETA: 0s - loss: 0.0894 - mean_absolute_error: 0.160\n",
+      " 93/438 [=====>........................] - ETA: 0s - loss: 0.0887 - mean_absolute_error: 0.159\n",
+      "125/438 [=======>......................] - ETA: 0s - loss: 0.0884 - mean_absolute_error: 0.158\n",
+      "156/438 [=========>....................] - ETA: 0s - loss: 0.0889 - mean_absolute_error: 0.159\n",
+      "188/438 [===========>..................] - ETA: 0s - loss: 0.0887 - mean_absolute_error: 0.159\n",
+      "219/438 [==============>...............] - ETA: 0s - loss: 0.0889 - mean_absolute_error: 0.159\n",
+      "250/438 [================>.............] - ETA: 0s - loss: 0.0889 - mean_absolute_error: 0.159\n",
+      "281/438 [==================>...........] - ETA: 0s - loss: 0.0889 - mean_absolute_error: 0.159\n",
+      "312/438 [====================>.........] - ETA: 0s - loss: 0.0889 - mean_absolute_error: 0.159\n",
+      "343/438 [======================>.......] - ETA: 0s - loss: 0.0886 - mean_absolute_error: 0.159\n",
+      "374/438 [========================>.....] - ETA: 0s - loss: 0.0885 - mean_absolute_error: 0.159\n",
+      "403/438 [==========================>...] - ETA: 0s - loss: 0.0884 - mean_absolute_error: 0.158\n",
+      "435/438 [============================>.] - ETA: 0s - loss: 0.0885 - mean_absolute_error: 0.158\n",
+      "438/438 [==============================] - 1s 2ms/step - loss: 0.0886 - mean_absolute_error: 0.1589\n"
+     ]
+    }
+   ],
+   "source": [
+    "val_performance = {}\n",
+    "performance = {}\n",
+    "val_performance['Baseline'] = baseline.evaluate(wide_window.val)\n",
+    "performance['Baseline'] = baseline.evaluate(wide_window.test, verbose=0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "dfbCrf5q3P6n"
+   },
+   "source": [
+    "#### Dense"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:32:22.356873Z",
+     "iopub.status.busy": "2023-07-27T04:32:22.356370Z",
+     "iopub.status.idle": "2023-07-27T04:32:22.365496Z",
+     "shell.execute_reply": "2023-07-27T04:32:22.364823Z"
+    },
+    "id": "NdpzH1dYjdIN"
+   },
+   "outputs": [],
+   "source": [
+    "dense = tf.keras.Sequential([\n",
+    "    tf.keras.layers.Dense(units=64, activation='relu'),\n",
+    "    tf.keras.layers.Dense(units=64, activation='relu'),\n",
+    "    tf.keras.layers.Dense(units=num_features)\n",
+    "])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:32:22.368303Z",
+     "iopub.status.busy": "2023-07-27T04:32:22.368091Z",
+     "iopub.status.idle": "2023-07-27T04:33:17.317459Z",
+     "shell.execute_reply": "2023-07-27T04:33:17.316645Z"
+    },
+    "id": "6uHuU9Cd3PTo"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "  1/439 [..............................] - ETA: 23s - loss: 0.0506 - mean_absolute_error: 0.11\n",
+      " 23/439 [>.............................] - ETA: 0s - loss: 0.0801 - mean_absolute_error: 0.1385\n",
+      " 45/439 [==>...........................] - ETA: 0s - loss: 0.0776 - mean_absolute_error: 0.137\n",
+      " 67/439 [===>..........................] - ETA: 0s - loss: 0.0727 - mean_absolute_error: 0.134\n",
+      " 90/439 [=====>........................] - ETA: 0s - loss: 0.0708 - mean_absolute_error: 0.133\n",
+      "112/439 [======>.......................] - ETA: 0s - loss: 0.0698 - mean_absolute_error: 0.132\n",
+      "135/439 [========>.....................] - ETA: 0s - loss: 0.0690 - mean_absolute_error: 0.132\n",
+      "159/439 [=========>....................] - ETA: 0s - loss: 0.0695 - mean_absolute_error: 0.132\n",
+      "181/439 [===========>..................] - ETA: 0s - loss: 0.0696 - mean_absolute_error: 0.132\n",
+      "202/439 [============>.................] - ETA: 0s - loss: 0.0693 - mean_absolute_error: 0.132\n",
+      "223/439 [==============>...............] - ETA: 0s - loss: 0.0690 - mean_absolute_error: 0.131\n",
+      "244/439 [===============>..............] - ETA: 0s - loss: 0.0689 - mean_absolute_error: 0.131\n",
+      "265/439 [=================>............] - ETA: 0s - loss: 0.0688 - mean_absolute_error: 0.131\n",
+      "286/439 [==================>...........] - ETA: 0s - loss: 0.0686 - mean_absolute_error: 0.131\n",
+      "307/439 [===================>..........] - ETA: 0s - loss: 0.0683 - mean_absolute_error: 0.131\n",
+      "328/439 [=====================>........] - ETA: 0s - loss: 0.0685 - mean_absolute_error: 0.131\n",
+      "350/439 [======================>.......] - ETA: 0s - loss: 0.0687 - mean_absolute_error: 0.131\n",
+      "372/439 [========================>.....] - ETA: 0s - loss: 0.0684 - mean_absolute_error: 0.131\n",
+      "394/439 [=========================>....] - ETA: 0s - loss: 0.0683 - mean_absolute_error: 0.131\n",
+      "415/439 [===========================>..] - ETA: 0s - loss: 0.0686 - mean_absolute_error: 0.131\n",
+      "438/439 [============================>.] - ETA: 0s - loss: 0.0684 - mean_absolute_error: 0.131\n",
+      "439/439 [==============================] - 1s 2ms/step - loss: 0.0684 - mean_absolute_error: 0.1314\n"
+     ]
+    }
+   ],
+   "source": [
+    "history = compile_and_fit(dense, single_step_window)\n",
+    "\n",
+    "IPython.display.clear_output()\n",
+    "val_performance['Dense'] = dense.evaluate(single_step_window.val)\n",
+    "performance['Dense'] = dense.evaluate(single_step_window.test, verbose=0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "dsc9pur_mHsx"
+   },
+   "source": [
+    "#### RNN\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:33:17.321553Z",
+     "iopub.status.busy": "2023-07-27T04:33:17.321315Z",
+     "iopub.status.idle": "2023-07-27T04:34:55.691121Z",
+     "shell.execute_reply": "2023-07-27T04:34:55.690293Z"
+    },
+    "id": "4QbGLMyomXaz"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "  1/438 [..............................] - ETA: 24s - loss: 0.0529 - mean_absolute_error: 0.11\n",
+      " 18/438 [>.............................] - ETA: 1s - loss: 0.0605 - mean_absolute_error: 0.1199\n",
+      " 36/438 [=>............................] - ETA: 1s - loss: 0.0602 - mean_absolute_error: 0.119\n",
+      " 54/438 [==>...........................] - ETA: 1s - loss: 0.0606 - mean_absolute_error: 0.119\n",
+      " 72/438 [===>..........................] - ETA: 1s - loss: 0.0607 - mean_absolute_error: 0.119\n",
+      " 90/438 [=====>........................] - ETA: 0s - loss: 0.0608 - mean_absolute_error: 0.119\n",
+      "108/438 [======>.......................] - ETA: 0s - loss: 0.0607 - mean_absolute_error: 0.119\n",
+      "127/438 [=======>......................] - ETA: 0s - loss: 0.0608 - mean_absolute_error: 0.119\n",
+      "145/438 [========>.....................] - ETA: 0s - loss: 0.0612 - mean_absolute_error: 0.120\n",
+      "164/438 [==========>...................] - ETA: 0s - loss: 0.0610 - mean_absolute_error: 0.120\n",
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+      "218/438 [=============>................] - ETA: 0s - loss: 0.0612 - mean_absolute_error: 0.120\n",
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+      "309/438 [====================>.........] - ETA: 0s - loss: 0.0613 - mean_absolute_error: 0.120\n",
+      "327/438 [=====================>........] - ETA: 0s - loss: 0.0612 - mean_absolute_error: 0.120\n",
+      "345/438 [======================>.......] - ETA: 0s - loss: 0.0613 - mean_absolute_error: 0.120\n",
+      "363/438 [=======================>......] - ETA: 0s - loss: 0.0614 - mean_absolute_error: 0.120\n",
+      "382/438 [=========================>....] - ETA: 0s - loss: 0.0612 - mean_absolute_error: 0.120\n",
+      "401/438 [==========================>...] - ETA: 0s - loss: 0.0614 - mean_absolute_error: 0.120\n",
+      "419/438 [===========================>..] - ETA: 0s - loss: 0.0615 - mean_absolute_error: 0.120\n",
+      "438/438 [==============================] - ETA: 0s - loss: 0.0616 - mean_absolute_error: 0.120\n",
+      "438/438 [==============================] - 1s 3ms/step - loss: 0.0616 - mean_absolute_error: 0.1205\n",
+      "\n",
+      "CPU times: user 3min 40s, sys: 42 s, total: 4min 22s\n",
+      "Wall time: 1min 38s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "wide_window = WindowGenerator(\n",
+    "    input_width=24, label_width=24, shift=1)\n",
+    "\n",
+    "lstm_model = tf.keras.models.Sequential([\n",
+    "    # Shape [batch, time, features] => [batch, time, lstm_units]\n",
+    "    tf.keras.layers.LSTM(32, return_sequences=True),\n",
+    "    # Shape => [batch, time, features]\n",
+    "    tf.keras.layers.Dense(units=num_features)\n",
+    "])\n",
+    "\n",
+    "history = compile_and_fit(lstm_model, wide_window)\n",
+    "\n",
+    "IPython.display.clear_output()\n",
+    "val_performance['LSTM'] = lstm_model.evaluate( wide_window.val)\n",
+    "performance['LSTM'] = lstm_model.evaluate( wide_window.test, verbose=0)\n",
+    "\n",
+    "print()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "UwhY2f_Nn0_K"
+   },
+   "source": [
+    "<a id=\"residual\"></a>\n",
+    "\n",
+    "#### Advanced: Residual connections\n",
+    "\n",
+    "The `Baseline` model from earlier took advantage of the fact that the sequence doesn't change drastically from time step to time step. Every model trained in this tutorial so far was randomly initialized, and then had to learn that the output is a a small change from the previous time step.\n",
+    "\n",
+    "While you can get around this issue with careful initialization, it's  simpler to build this into the model structure.\n",
+    "\n",
+    "It's common in time series analysis to build models that instead of predicting the next value, predict how the value will change in the next time step. Similarly, <a href=\"https://arxiv.org/abs/1512.03385\" class=\"external\">residual networks</a>—or ResNets—in deep learning refer to architectures where each layer adds to the model's accumulating result.\n",
+    "\n",
+    "That is how you take advantage of the knowledge that the change should be small.\n",
+    "\n",
+    "![A model with a residual connection](images/residual.png)\n",
+    "\n",
+    "Essentially, this initializes the model to match the `Baseline`. For this task it helps models converge faster, with slightly better performance."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "yP58A_ORx0kM"
+   },
+   "source": [
+    "This approach can be used in conjunction with any model discussed in this tutorial. \n",
+    "\n",
+    "Here, it is being applied to the LSTM model, note the use of the `tf.initializers.zeros` to ensure that the initial predicted changes are small, and don't overpower the residual connection. There are no symmetry-breaking concerns for the gradients here, since the `zeros` are only used on the last layer."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:34:55.694595Z",
+     "iopub.status.busy": "2023-07-27T04:34:55.694222Z",
+     "iopub.status.idle": "2023-07-27T04:34:55.698733Z",
+     "shell.execute_reply": "2023-07-27T04:34:55.698095Z"
+    },
+    "id": "7YlfnDQC22TQ"
+   },
+   "outputs": [],
+   "source": [
+    "class ResidualWrapper(tf.keras.Model):\n",
+    "  def __init__(self, model):\n",
+    "    super().__init__()\n",
+    "    self.model = model\n",
+    "\n",
+    "  def call(self, inputs, *args, **kwargs):\n",
+    "    delta = self.model(inputs, *args, **kwargs)\n",
+    "\n",
+    "    # The prediction for each time step is the input\n",
+    "    # from the previous time step plus the delta\n",
+    "    # calculated by the model.\n",
+    "    return inputs + delta"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:34:55.701487Z",
+     "iopub.status.busy": "2023-07-27T04:34:55.701277Z",
+     "iopub.status.idle": "2023-07-27T04:35:47.023759Z",
+     "shell.execute_reply": "2023-07-27T04:35:47.022923Z"
+    },
+    "id": "NNeH02pspc9B"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "  1/438 [..............................] - ETA: 24s - loss: 0.0571 - mean_absolute_error: 0.11\n",
+      " 18/438 [>.............................] - ETA: 1s - loss: 0.0617 - mean_absolute_error: 0.1173\n",
+      " 37/438 [=>............................] - ETA: 1s - loss: 0.0621 - mean_absolute_error: 0.118\n",
+      " 56/438 [==>...........................] - ETA: 1s - loss: 0.0628 - mean_absolute_error: 0.119\n",
+      " 76/438 [====>.........................] - ETA: 0s - loss: 0.0623 - mean_absolute_error: 0.118\n",
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+      "339/438 [======================>.......] - ETA: 0s - loss: 0.0622 - mean_absolute_error: 0.118\n",
+      "358/438 [=======================>......] - ETA: 0s - loss: 0.0622 - mean_absolute_error: 0.118\n",
+      "377/438 [========================>.....] - ETA: 0s - loss: 0.0621 - mean_absolute_error: 0.118\n",
+      "396/438 [==========================>...] - ETA: 0s - loss: 0.0621 - mean_absolute_error: 0.118\n",
+      "415/438 [===========================>..] - ETA: 0s - loss: 0.0620 - mean_absolute_error: 0.117\n",
+      "433/438 [============================>.] - ETA: 0s - loss: 0.0620 - mean_absolute_error: 0.117\n",
+      "438/438 [==============================] - 1s 3ms/step - loss: 0.0621 - mean_absolute_error: 0.1180\n",
+      "\n",
+      "CPU times: user 1min 54s, sys: 21.4 s, total: 2min 15s\n",
+      "Wall time: 51.3 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "residual_lstm = ResidualWrapper(\n",
+    "    tf.keras.Sequential([\n",
+    "    tf.keras.layers.LSTM(32, return_sequences=True),\n",
+    "    tf.keras.layers.Dense(\n",
+    "        num_features,\n",
+    "        # The predicted deltas should start small.\n",
+    "        # Therefore, initialize the output layer with zeros.\n",
+    "        kernel_initializer=tf.initializers.zeros())\n",
+    "]))\n",
+    "\n",
+    "history = compile_and_fit(residual_lstm, wide_window)\n",
+    "\n",
+    "IPython.display.clear_output()\n",
+    "val_performance['Residual LSTM'] = residual_lstm.evaluate(wide_window.val)\n",
+    "performance['Residual LSTM'] = residual_lstm.evaluate(wide_window.test, verbose=0)\n",
+    "print()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "I42Er9Du6co1"
+   },
+   "source": [
+    "#### Performance"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "LZxR38P_6pUi"
+   },
+   "source": [
+    "Here is the overall performance for these multi-output models."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:35:47.027299Z",
+     "iopub.status.busy": "2023-07-27T04:35:47.027034Z",
+     "iopub.status.idle": "2023-07-27T04:35:47.207299Z",
+     "shell.execute_reply": "2023-07-27T04:35:47.206598Z"
+    },
+    "id": "6XgTK9tnr7rc"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "x = np.arange(len(performance))\n",
+    "width = 0.3\n",
+    "\n",
+    "metric_name = 'mean_absolute_error'\n",
+    "metric_index = lstm_model.metrics_names.index('mean_absolute_error')\n",
+    "val_mae = [v[metric_index] for v in val_performance.values()]\n",
+    "test_mae = [v[metric_index] for v in performance.values()]\n",
+    "\n",
+    "plt.bar(x - 0.17, val_mae, width, label='Validation')\n",
+    "plt.bar(x + 0.17, test_mae, width, label='Test')\n",
+    "plt.xticks(ticks=x, labels=performance.keys(),\n",
+    "           rotation=45)\n",
+    "plt.ylabel('MAE (average over all outputs)')\n",
+    "_ = plt.legend()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:35:47.210449Z",
+     "iopub.status.busy": "2023-07-27T04:35:47.210181Z",
+     "iopub.status.idle": "2023-07-27T04:35:47.213976Z",
+     "shell.execute_reply": "2023-07-27T04:35:47.213383Z"
+    },
+    "id": "URz3ajCc6kBj"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Baseline       : 0.1638\n",
+      "Dense          : 0.1319\n",
+      "LSTM           : 0.1217\n",
+      "Residual LSTM  : 0.1193\n"
+     ]
+    }
+   ],
+   "source": [
+    "for name, value in performance.items():\n",
+    "  print(f'{name:15s}: {value[1]:0.4f}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "_Vt2MJhNxwPU"
+   },
+   "source": [
+    "The above performances are averaged across all model outputs."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "eYokb7Om2YbK"
+   },
+   "source": [
+    "## Multi-step models\n",
+    "\n",
+    "Both the single-output and multiple-output models in the previous sections made **single time step predictions**, one hour into the future.\n",
+    "\n",
+    "This section looks at how to expand these models to make **multiple time step predictions**.\n",
+    "\n",
+    "In a multi-step prediction, the model needs to learn to predict a range of future values. Thus, unlike a single step model, where only a single future point is predicted, a multi-step model predicts a sequence of the future values.\n",
+    "\n",
+    "There are two rough approaches to this:\n",
+    "\n",
+    "1. Single shot predictions where the entire time series is predicted at once.\n",
+    "2. Autoregressive predictions where the model only makes single step predictions and its output is fed back as its input.\n",
+    "\n",
+    "In this section all the models will predict **all the features across all output time steps**.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "WFsDAwVt4_rq"
+   },
+   "source": [
+    "For the multi-step model, the training data again consists of hourly samples. However, here, the models will learn to predict 24 hours into the future, given 24 hours of the past.\n",
+    "\n",
+    "Here is a `Window` object that generates these slices from the dataset:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:35:47.217020Z",
+     "iopub.status.busy": "2023-07-27T04:35:47.216810Z",
+     "iopub.status.idle": "2023-07-27T04:35:47.758956Z",
+     "shell.execute_reply": "2023-07-27T04:35:47.758231Z"
+    },
+    "id": "1cFYtsz6XiGw"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Total window size: 48\n",
+       "Input indices: [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23]\n",
+       "Label indices: [24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47]\n",
+       "Label column name(s): None"
+      ]
+     },
+     "execution_count": 77,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "OUT_STEPS = 24\n",
+    "multi_window = WindowGenerator(input_width=24,\n",
+    "                               label_width=OUT_STEPS,\n",
+    "                               shift=OUT_STEPS)\n",
+    "\n",
+    "multi_window.plot()\n",
+    "multi_window"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "5lg8SInh9Jzd"
+   },
+   "source": [
+    "### Baselines"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "axwpoWYOApJL"
+   },
+   "source": [
+    "A simple baseline for this task is to repeat the last input time step for the required number of output time steps:\n",
+    "\n",
+    "![Repeat the last input, for each output step](images/multistep_last.png)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:35:47.763031Z",
+     "iopub.status.busy": "2023-07-27T04:35:47.762787Z",
+     "iopub.status.idle": "2023-07-27T04:35:49.617439Z",
+     "shell.execute_reply": "2023-07-27T04:35:49.616773Z"
+    },
+    "id": "_5iaHSaJ9Rxv"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "  1/437 [..............................] - ETA: 57s - loss: 0.5605 - mean_absolute_error: 0.48\n",
+      " 30/437 [=>............................] - ETA: 0s - loss: 0.6357 - mean_absolute_error: 0.5029\n",
+      " 58/437 [==>...........................] - ETA: 0s - loss: 0.6309 - mean_absolute_error: 0.500\n",
+      " 87/437 [====>.........................] - ETA: 0s - loss: 0.6295 - mean_absolute_error: 0.501\n",
+      "117/437 [=======>......................] - ETA: 0s - loss: 0.6284 - mean_absolute_error: 0.500\n",
+      "147/437 [=========>....................] - ETA: 0s - loss: 0.6287 - mean_absolute_error: 0.500\n",
+      "178/437 [===========>..................] - ETA: 0s - loss: 0.6278 - mean_absolute_error: 0.500\n",
+      "210/437 [=============>................] - ETA: 0s - loss: 0.6276 - mean_absolute_error: 0.499\n",
+      "240/437 [===============>..............] - ETA: 0s - loss: 0.6285 - mean_absolute_error: 0.500\n",
+      "269/437 [=================>............] - ETA: 0s - loss: 0.6281 - mean_absolute_error: 0.500\n",
+      "298/437 [===================>..........] - ETA: 0s - loss: 0.6290 - mean_absolute_error: 0.500\n",
+      "328/437 [=====================>........] - ETA: 0s - loss: 0.6282 - mean_absolute_error: 0.500\n",
+      "358/437 [=======================>......] - ETA: 0s - loss: 0.6266 - mean_absolute_error: 0.500\n",
+      "387/437 [=========================>....] - ETA: 0s - loss: 0.6284 - mean_absolute_error: 0.500\n",
+      "416/437 [===========================>..] - ETA: 0s - loss: 0.6279 - mean_absolute_error: 0.500\n",
+      "437/437 [==============================] - 1s 2ms/step - loss: 0.6285 - mean_absolute_error: 0.5007\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "class MultiStepLastBaseline(tf.keras.Model):\n",
+    "  def call(self, inputs):\n",
+    "    return tf.tile(inputs[:, -1:, :], [1, OUT_STEPS, 1])\n",
+    "\n",
+    "last_baseline = MultiStepLastBaseline()\n",
+    "last_baseline.compile(loss=tf.keras.losses.MeanSquaredError(),\n",
+    "                      metrics=[tf.keras.metrics.MeanAbsoluteError()])\n",
+    "\n",
+    "multi_val_performance = {}\n",
+    "multi_performance = {}\n",
+    "\n",
+    "multi_val_performance['Last'] = last_baseline.evaluate(multi_window.val)\n",
+    "multi_performance['Last'] = last_baseline.evaluate(multi_window.test, verbose=0)\n",
+    "multi_window.plot(last_baseline)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "AvHZ93ObAfMA"
+   },
+   "source": [
+    "Since this task is to predict 24 hours into the future, given 24 hours of the past, another simple approach is to repeat the previous day, assuming tomorrow will be similar:\n",
+    "\n",
+    "![Repeat the previous day](images/multistep_repeat.png)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:35:49.621545Z",
+     "iopub.status.busy": "2023-07-27T04:35:49.621292Z",
+     "iopub.status.idle": "2023-07-27T04:35:51.440246Z",
+     "shell.execute_reply": "2023-07-27T04:35:51.439254Z"
+    },
+    "id": "L8Y1uMhGwIRs"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "  1/437 [..............................] - ETA: 52s - loss: 0.3771 - mean_absolute_error: 0.37\n",
+      " 29/437 [>.............................] - ETA: 0s - loss: 0.4291 - mean_absolute_error: 0.3949\n",
+      " 56/437 [==>...........................] - ETA: 0s - loss: 0.4270 - mean_absolute_error: 0.395\n",
+      " 85/437 [====>.........................] - ETA: 0s - loss: 0.4233 - mean_absolute_error: 0.395\n",
+      "114/437 [======>.......................] - ETA: 0s - loss: 0.4267 - mean_absolute_error: 0.395\n",
+      "143/437 [========>.....................] - ETA: 0s - loss: 0.4286 - mean_absolute_error: 0.396\n",
+      "173/437 [==========>...................] - ETA: 0s - loss: 0.4299 - mean_absolute_error: 0.397\n",
+      "204/437 [=============>................] - ETA: 0s - loss: 0.4309 - mean_absolute_error: 0.397\n",
+      "234/437 [===============>..............] - ETA: 0s - loss: 0.4304 - mean_absolute_error: 0.397\n",
+      "265/437 [=================>............] - ETA: 0s - loss: 0.4294 - mean_absolute_error: 0.397\n",
+      "295/437 [===================>..........] - ETA: 0s - loss: 0.4302 - mean_absolute_error: 0.397\n",
+      "325/437 [=====================>........] - ETA: 0s - loss: 0.4302 - mean_absolute_error: 0.397\n",
+      "355/437 [=======================>......] - ETA: 0s - loss: 0.4284 - mean_absolute_error: 0.396\n",
+      "384/437 [=========================>....] - ETA: 0s - loss: 0.4281 - mean_absolute_error: 0.396\n",
+      "412/437 [===========================>..] - ETA: 0s - loss: 0.4277 - mean_absolute_error: 0.396\n",
+      "437/437 [==============================] - 1s 2ms/step - loss: 0.4270 - mean_absolute_error: 0.3959\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "class RepeatBaseline(tf.keras.Model):\n",
+    "  def call(self, inputs):\n",
+    "    return inputs\n",
+    "\n",
+    "repeat_baseline = RepeatBaseline()\n",
+    "repeat_baseline.compile(loss=tf.keras.losses.MeanSquaredError(),\n",
+    "                        metrics=[tf.keras.metrics.MeanAbsoluteError()])\n",
+    "\n",
+    "multi_val_performance['Repeat'] = repeat_baseline.evaluate(multi_window.val)\n",
+    "multi_performance['Repeat'] = repeat_baseline.evaluate(multi_window.test, verbose=0)\n",
+    "multi_window.plot(repeat_baseline)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "tbndS-ct9C2Q"
+   },
+   "source": [
+    "### Single-shot models\n",
+    "\n",
+    "One high-level approach to this problem is to use a \"single-shot\" model, where the model makes the entire sequence prediction in a single step.\n",
+    "\n",
+    "This can be implemented efficiently as a `tf.keras.layers.Dense` with `OUT_STEPS*features` output units. The model just needs to reshape that output to the required `(OUTPUT_STEPS, features)`."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "NCKS4m1VKrDQ"
+   },
+   "source": [
+    "#### Linear\n",
+    "\n",
+    "A simple linear model based on the last input time step does better than either baseline, but is underpowered. The model needs to predict `OUTPUT_STEPS` time steps, from a single input time step with a linear projection. It can only capture a low-dimensional slice of the behavior, likely based mainly on the time of day and time of year.\n",
+    "\n",
+    "![Predict all timesteps from the last time-step](images/multistep_dense.png)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:35:51.444440Z",
+     "iopub.status.busy": "2023-07-27T04:35:51.443724Z",
+     "iopub.status.idle": "2023-07-27T04:36:25.734841Z",
+     "shell.execute_reply": "2023-07-27T04:36:25.734144Z"
+    },
+    "id": "kfRz_WVhIQcd"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "  1/437 [..............................] - ETA: 23s - loss: 0.2299 - mean_absolute_error: 0.29\n",
+      " 26/437 [>.............................] - ETA: 0s - loss: 0.2520 - mean_absolute_error: 0.3041\n",
+      " 52/437 [==>...........................] - ETA: 0s - loss: 0.2541 - mean_absolute_error: 0.303\n",
+      " 78/437 [====>.........................] - ETA: 0s - loss: 0.2548 - mean_absolute_error: 0.304\n",
+      "104/437 [======>.......................] - ETA: 0s - loss: 0.2562 - mean_absolute_error: 0.305\n",
+      "130/437 [=======>......................] - ETA: 0s - loss: 0.2539 - mean_absolute_error: 0.304\n",
+      "157/437 [=========>....................] - ETA: 0s - loss: 0.2533 - mean_absolute_error: 0.303\n",
+      "185/437 [===========>..................] - ETA: 0s - loss: 0.2534 - mean_absolute_error: 0.303\n",
+      "211/437 [=============>................] - ETA: 0s - loss: 0.2537 - mean_absolute_error: 0.304\n",
+      "237/437 [===============>..............] - ETA: 0s - loss: 0.2535 - mean_absolute_error: 0.303\n",
+      "263/437 [=================>............] - ETA: 0s - loss: 0.2540 - mean_absolute_error: 0.304\n",
+      "289/437 [==================>...........] - ETA: 0s - loss: 0.2549 - mean_absolute_error: 0.304\n",
+      "316/437 [====================>.........] - ETA: 0s - loss: 0.2549 - mean_absolute_error: 0.304\n",
+      "342/437 [======================>.......] - ETA: 0s - loss: 0.2554 - mean_absolute_error: 0.304\n",
+      "368/437 [========================>.....] - ETA: 0s - loss: 0.2550 - mean_absolute_error: 0.304\n",
+      "395/437 [==========================>...] - ETA: 0s - loss: 0.2552 - mean_absolute_error: 0.304\n",
+      "422/437 [===========================>..] - ETA: 0s - loss: 0.2551 - mean_absolute_error: 0.304\n",
+      "437/437 [==============================] - 1s 2ms/step - loss: 0.2550 - mean_absolute_error: 0.3046\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "multi_linear_model = tf.keras.Sequential([\n",
+    "    # Take the last time-step.\n",
+    "    # Shape [batch, time, features] => [batch, 1, features]\n",
+    "    tf.keras.layers.Lambda(lambda x: x[:, -1:, :]),\n",
+    "    # Shape => [batch, 1, out_steps*features]\n",
+    "    tf.keras.layers.Dense(OUT_STEPS*num_features,\n",
+    "                          kernel_initializer=tf.initializers.zeros()),\n",
+    "    # Shape => [batch, out_steps, features]\n",
+    "    tf.keras.layers.Reshape([OUT_STEPS, num_features])\n",
+    "])\n",
+    "\n",
+    "history = compile_and_fit(multi_linear_model, multi_window)\n",
+    "\n",
+    "IPython.display.clear_output()\n",
+    "multi_val_performance['Linear'] = multi_linear_model.evaluate(multi_window.val)\n",
+    "multi_performance['Linear'] = multi_linear_model.evaluate(multi_window.test, verbose=0)\n",
+    "multi_window.plot(multi_linear_model)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "zi2TMHk2IRrh"
+   },
+   "source": [
+    "#### Dense\n",
+    "\n",
+    "Adding a `tf.keras.layers.Dense` between the input and output gives the linear model more power, but is still only based on a single input time step."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:36:25.738763Z",
+     "iopub.status.busy": "2023-07-27T04:36:25.738489Z",
+     "iopub.status.idle": "2023-07-27T04:37:32.378648Z",
+     "shell.execute_reply": "2023-07-27T04:37:32.377875Z"
+    },
+    "id": "jezm-BKaGj91"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "  1/437 [..............................] - ETA: 24s - loss: 0.2633 - mean_absolute_error: 0.30\n",
+      " 22/437 [>.............................] - ETA: 1s - loss: 0.2175 - mean_absolute_error: 0.2790\n",
+      " 45/437 [==>...........................] - ETA: 0s - loss: 0.2168 - mean_absolute_error: 0.278\n",
+      " 69/437 [===>..........................] - ETA: 0s - loss: 0.2171 - mean_absolute_error: 0.279\n",
+      " 92/437 [=====>........................] - ETA: 0s - loss: 0.2160 - mean_absolute_error: 0.278\n",
+      "114/437 [======>.......................] - ETA: 0s - loss: 0.2170 - mean_absolute_error: 0.279\n",
+      "137/437 [========>.....................] - ETA: 0s - loss: 0.2168 - mean_absolute_error: 0.279\n",
+      "160/437 [=========>....................] - ETA: 0s - loss: 0.2169 - mean_absolute_error: 0.279\n",
+      "182/437 [===========>..................] - ETA: 0s - loss: 0.2171 - mean_absolute_error: 0.279\n",
+      "204/437 [=============>................] - ETA: 0s - loss: 0.2174 - mean_absolute_error: 0.279\n",
+      "227/437 [==============>...............] - ETA: 0s - loss: 0.2181 - mean_absolute_error: 0.280\n",
+      "250/437 [================>.............] - ETA: 0s - loss: 0.2188 - mean_absolute_error: 0.280\n",
+      "272/437 [=================>............] - ETA: 0s - loss: 0.2189 - mean_absolute_error: 0.280\n",
+      "295/437 [===================>..........] - ETA: 0s - loss: 0.2195 - mean_absolute_error: 0.280\n",
+      "318/437 [====================>.........] - ETA: 0s - loss: 0.2193 - mean_absolute_error: 0.280\n",
+      "341/437 [======================>.......] - ETA: 0s - loss: 0.2193 - mean_absolute_error: 0.280\n",
+      "364/437 [=======================>......] - ETA: 0s - loss: 0.2190 - mean_absolute_error: 0.280\n",
+      "387/437 [=========================>....] - ETA: 0s - loss: 0.2188 - mean_absolute_error: 0.280\n",
+      "411/437 [===========================>..] - ETA: 0s - loss: 0.2186 - mean_absolute_error: 0.280\n",
+      "434/437 [============================>.] - ETA: 0s - loss: 0.2183 - mean_absolute_error: 0.280\n",
+      "437/437 [==============================] - 1s 2ms/step - loss: 0.2183 - mean_absolute_error: 0.2804\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "multi_dense_model = tf.keras.Sequential([\n",
+    "    # Take the last time step.\n",
+    "    # Shape [batch, time, features] => [batch, 1, features]\n",
+    "    tf.keras.layers.Lambda(lambda x: x[:, -1:, :]),\n",
+    "    # Shape => [batch, 1, dense_units]\n",
+    "    tf.keras.layers.Dense(512, activation='relu'),\n",
+    "    # Shape => [batch, out_steps*features]\n",
+    "    tf.keras.layers.Dense(OUT_STEPS*num_features,\n",
+    "                          kernel_initializer=tf.initializers.zeros()),\n",
+    "    # Shape => [batch, out_steps, features]\n",
+    "    tf.keras.layers.Reshape([OUT_STEPS, num_features])\n",
+    "])\n",
+    "\n",
+    "history = compile_and_fit(multi_dense_model, multi_window)\n",
+    "\n",
+    "IPython.display.clear_output()\n",
+    "multi_val_performance['Dense'] = multi_dense_model.evaluate(multi_window.val)\n",
+    "multi_performance['Dense'] = multi_dense_model.evaluate(multi_window.test, verbose=0)\n",
+    "multi_window.plot(multi_dense_model)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "icsBAjCzMaMl"
+   },
+   "source": [
+    "#### CNN"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "34lCZrWYNBwd"
+   },
+   "source": [
+    "A convolutional model makes predictions based on a fixed-width history, which may lead to better performance than the dense model since it can see how things are changing over time:\n",
+    "\n",
+    "![A convolutional model sees how things change over time](images/multistep_conv.png)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:37:32.382928Z",
+     "iopub.status.busy": "2023-07-27T04:37:32.382678Z",
+     "iopub.status.idle": "2023-07-27T04:38:21.758312Z",
+     "shell.execute_reply": "2023-07-27T04:38:21.757664Z"
+    },
+    "id": "0xJoIP6PMWMI"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "  1/437 [..............................] - ETA: 23s - loss: 0.2645 - mean_absolute_error: 0.32\n",
+      " 24/437 [>.............................] - ETA: 0s - loss: 0.2179 - mean_absolute_error: 0.2855\n",
+      " 47/437 [==>...........................] - ETA: 0s - loss: 0.2162 - mean_absolute_error: 0.284\n",
+      " 71/437 [===>..........................] - ETA: 0s - loss: 0.2158 - mean_absolute_error: 0.283\n",
+      " 95/437 [=====>........................] - ETA: 0s - loss: 0.2124 - mean_absolute_error: 0.281\n",
+      "119/437 [=======>......................] - ETA: 0s - loss: 0.2136 - mean_absolute_error: 0.282\n",
+      "143/437 [========>.....................] - ETA: 0s - loss: 0.2157 - mean_absolute_error: 0.283\n",
+      "169/437 [==========>...................] - ETA: 0s - loss: 0.2165 - mean_absolute_error: 0.283\n",
+      "192/437 [============>.................] - ETA: 0s - loss: 0.2161 - mean_absolute_error: 0.283\n",
+      "216/437 [=============>................] - ETA: 0s - loss: 0.2158 - mean_absolute_error: 0.282\n",
+      "240/437 [===============>..............] - ETA: 0s - loss: 0.2152 - mean_absolute_error: 0.282\n",
+      "264/437 [=================>............] - ETA: 0s - loss: 0.2160 - mean_absolute_error: 0.282\n",
+      "287/437 [==================>...........] - ETA: 0s - loss: 0.2153 - mean_absolute_error: 0.282\n",
+      "311/437 [====================>.........] - ETA: 0s - loss: 0.2154 - mean_absolute_error: 0.282\n",
+      "335/437 [=====================>........] - ETA: 0s - loss: 0.2158 - mean_absolute_error: 0.282\n",
+      "359/437 [=======================>......] - ETA: 0s - loss: 0.2160 - mean_absolute_error: 0.282\n",
+      "383/437 [=========================>....] - ETA: 0s - loss: 0.2155 - mean_absolute_error: 0.282\n",
+      "407/437 [==========================>...] - ETA: 0s - loss: 0.2155 - mean_absolute_error: 0.282\n",
+      "432/437 [============================>.] - ETA: 0s - loss: 0.2156 - mean_absolute_error: 0.282\n",
+      "437/437 [==============================] - 1s 2ms/step - loss: 0.2156 - mean_absolute_error: 0.2824\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "CONV_WIDTH = 3\n",
+    "multi_conv_model = tf.keras.Sequential([\n",
+    "    # Shape [batch, time, features] => [batch, CONV_WIDTH, features]\n",
+    "    tf.keras.layers.Lambda(lambda x: x[:, -CONV_WIDTH:, :]),\n",
+    "    # Shape => [batch, 1, conv_units]\n",
+    "    tf.keras.layers.Conv1D(256, activation='relu', kernel_size=(CONV_WIDTH)),\n",
+    "    # Shape => [batch, 1,  out_steps*features]\n",
+    "    tf.keras.layers.Dense(OUT_STEPS*num_features,\n",
+    "                          kernel_initializer=tf.initializers.zeros()),\n",
+    "    # Shape => [batch, out_steps, features]\n",
+    "    tf.keras.layers.Reshape([OUT_STEPS, num_features])\n",
+    "])\n",
+    "\n",
+    "history = compile_and_fit(multi_conv_model, multi_window)\n",
+    "\n",
+    "IPython.display.clear_output()\n",
+    "\n",
+    "multi_val_performance['Conv'] = multi_conv_model.evaluate(multi_window.val)\n",
+    "multi_performance['Conv'] = multi_conv_model.evaluate(multi_window.test, verbose=0)\n",
+    "multi_window.plot(multi_conv_model)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "weBjeZAFJOP4"
+   },
+   "source": [
+    "#### RNN"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "8022xOKxOO92"
+   },
+   "source": [
+    "A recurrent model can learn to use a long history of inputs, if it's relevant to the predictions the model is making. Here the model will accumulate internal state for 24 hours, before making a single prediction for the next 24 hours.\n",
+    "\n",
+    "In this single-shot format, the LSTM only needs to produce an output at the last time step, so set `return_sequences=False` in `tf.keras.layers.LSTM`.\n",
+    "\n",
+    "![The LSTM accumulates state over the input window, and makes a single prediction for the next 24 hours](images/multistep_lstm.png)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:38:21.762666Z",
+     "iopub.status.busy": "2023-07-27T04:38:21.762334Z",
+     "iopub.status.idle": "2023-07-27T04:39:31.155232Z",
+     "shell.execute_reply": "2023-07-27T04:39:31.154519Z"
+    },
+    "id": "Bf1ks6RTzF64"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "  1/437 [..............................] - ETA: 24s - loss: 0.2208 - mean_absolute_error: 0.28\n",
+      " 19/437 [>.............................] - ETA: 1s - loss: 0.2106 - mean_absolute_error: 0.2811\n",
+      " 38/437 [=>............................] - ETA: 1s - loss: 0.2134 - mean_absolute_error: 0.282\n",
+      " 58/437 [==>...........................] - ETA: 1s - loss: 0.2149 - mean_absolute_error: 0.284\n",
+      " 79/437 [====>.........................] - ETA: 0s - loss: 0.2165 - mean_absolute_error: 0.285\n",
+      " 98/437 [=====>........................] - ETA: 0s - loss: 0.2158 - mean_absolute_error: 0.284\n",
+      "118/437 [=======>......................] - ETA: 0s - loss: 0.2153 - mean_absolute_error: 0.284\n",
+      "138/437 [========>.....................] - ETA: 0s - loss: 0.2154 - mean_absolute_error: 0.284\n",
+      "158/437 [=========>....................] - ETA: 0s - loss: 0.2156 - mean_absolute_error: 0.284\n",
+      "178/437 [===========>..................] - ETA: 0s - loss: 0.2163 - mean_absolute_error: 0.284\n",
+      "198/437 [============>.................] - ETA: 0s - loss: 0.2161 - mean_absolute_error: 0.284\n",
+      "218/437 [=============>................] - ETA: 0s - loss: 0.2166 - mean_absolute_error: 0.285\n",
+      "239/437 [===============>..............] - ETA: 0s - loss: 0.2166 - mean_absolute_error: 0.285\n",
+      "258/437 [================>.............] - ETA: 0s - loss: 0.2163 - mean_absolute_error: 0.285\n",
+      "278/437 [==================>...........] - ETA: 0s - loss: 0.2158 - mean_absolute_error: 0.284\n",
+      "298/437 [===================>..........] - ETA: 0s - loss: 0.2156 - mean_absolute_error: 0.284\n",
+      "318/437 [====================>.........] - ETA: 0s - loss: 0.2159 - mean_absolute_error: 0.285\n",
+      "338/437 [======================>.......] - ETA: 0s - loss: 0.2158 - mean_absolute_error: 0.284\n",
+      "358/437 [=======================>......] - ETA: 0s - loss: 0.2155 - mean_absolute_error: 0.284\n",
+      "378/437 [========================>.....] - ETA: 0s - loss: 0.2152 - mean_absolute_error: 0.284\n",
+      "398/437 [==========================>...] - ETA: 0s - loss: 0.2155 - mean_absolute_error: 0.284\n",
+      "418/437 [===========================>..] - ETA: 0s - loss: 0.2150 - mean_absolute_error: 0.284\n",
+      "437/437 [==============================] - 1s 3ms/step - loss: 0.2145 - mean_absolute_error: 0.2844\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "multi_lstm_model = tf.keras.Sequential([\n",
+    "    # Shape [batch, time, features] => [batch, lstm_units].\n",
+    "    # Adding more `lstm_units` just overfits more quickly.\n",
+    "    tf.keras.layers.LSTM(32, return_sequences=False),\n",
+    "    # Shape => [batch, out_steps*features].\n",
+    "    tf.keras.layers.Dense(OUT_STEPS*num_features,\n",
+    "                          kernel_initializer=tf.initializers.zeros()),\n",
+    "    # Shape => [batch, out_steps, features].\n",
+    "    tf.keras.layers.Reshape([OUT_STEPS, num_features])\n",
+    "])\n",
+    "\n",
+    "history = compile_and_fit(multi_lstm_model, multi_window)\n",
+    "\n",
+    "IPython.display.clear_output()\n",
+    "\n",
+    "multi_val_performance['LSTM'] = multi_lstm_model.evaluate(multi_window.val)\n",
+    "multi_performance['LSTM'] = multi_lstm_model.evaluate(multi_window.test, verbose=0)\n",
+    "multi_window.plot(multi_lstm_model)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "d5n-1cDW12Vo"
+   },
+   "source": [
+    "### Advanced: Autoregressive model\n",
+    "\n",
+    "The above models all predict the entire output sequence in a single step.\n",
+    "\n",
+    "In some cases it may be helpful for the model to decompose this prediction into individual time steps. Then, each model's output can be fed back into itself at each step and predictions can be made conditioned on the previous one, like in the classic <a href=\"https://arxiv.org/abs/1308.0850\" class=\"external\">Generating Sequences With Recurrent Neural Networks</a>.\n",
+    "\n",
+    "One clear advantage to this style of model is that it can be set up to produce output with a varying length.\n",
+    "\n",
+    "You could take any of the single-step multi-output models trained in the first half of this tutorial and run in an autoregressive feedback loop, but here you'll focus on building a model that's been explicitly trained to do that.\n",
+    "\n",
+    "![Feedback a model's output to its input](images/multistep_autoregressive.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "PKRreBbULRXY"
+   },
+   "source": [
+    "#### RNN\n",
+    "\n",
+    "This tutorial only builds an autoregressive RNN model, but this pattern could be applied to any model that was designed to output a single time step.\n",
+    "\n",
+    "The model will have the same basic form as the single-step LSTM models from earlier: a `tf.keras.layers.LSTM` layer followed by a `tf.keras.layers.Dense` layer that converts the `LSTM` layer's outputs to model predictions.\n",
+    "\n",
+    "A `tf.keras.layers.LSTM` is a `tf.keras.layers.LSTMCell` wrapped in the higher level `tf.keras.layers.RNN` that manages the state and sequence results for you (Check out the [Recurrent Neural Networks (RNN) with Keras](https://www.tensorflow.org/guide/keras/rnn) guide for details).\n",
+    "\n",
+    "In this case, the model has to manually manage the inputs for each step, so it uses `tf.keras.layers.LSTMCell` directly for the lower level, single time step interface."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:39:31.159936Z",
+     "iopub.status.busy": "2023-07-27T04:39:31.159671Z",
+     "iopub.status.idle": "2023-07-27T04:39:31.164575Z",
+     "shell.execute_reply": "2023-07-27T04:39:31.163930Z"
+    },
+    "id": "s5tz3Nu0R5JG"
+   },
+   "outputs": [],
+   "source": [
+    "class FeedBack(tf.keras.Model):\n",
+    "  def __init__(self, units, out_steps):\n",
+    "    super().__init__()\n",
+    "    self.out_steps = out_steps\n",
+    "    self.units = units\n",
+    "    self.lstm_cell = tf.keras.layers.LSTMCell(units)\n",
+    "    # Also wrap the LSTMCell in an RNN to simplify the `warmup` method.\n",
+    "    self.lstm_rnn = tf.keras.layers.RNN(self.lstm_cell, return_state=True)\n",
+    "    self.dense = tf.keras.layers.Dense(num_features)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:39:31.167728Z",
+     "iopub.status.busy": "2023-07-27T04:39:31.167255Z",
+     "iopub.status.idle": "2023-07-27T04:39:31.178162Z",
+     "shell.execute_reply": "2023-07-27T04:39:31.177546Z"
+    },
+    "id": "2OXVM9G1U7xR"
+   },
+   "outputs": [],
+   "source": [
+    "feedback_model = FeedBack(units=32, out_steps=OUT_STEPS)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "ph5uFSfTUNho"
+   },
+   "source": [
+    "The first method this model needs is a `warmup` method to initialize its internal state based on the inputs. Once trained, this state will capture the relevant parts of the input history. This is equivalent to the single-step `LSTM` model from earlier:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:39:31.181484Z",
+     "iopub.status.busy": "2023-07-27T04:39:31.181106Z",
+     "iopub.status.idle": "2023-07-27T04:39:31.184688Z",
+     "shell.execute_reply": "2023-07-27T04:39:31.184105Z"
+    },
+    "id": "vM2K_LLdRjDZ"
+   },
+   "outputs": [],
+   "source": [
+    "def warmup(self, inputs):\n",
+    "  # inputs.shape => (batch, time, features)\n",
+    "  # x.shape => (batch, lstm_units)\n",
+    "  x, *state = self.lstm_rnn(inputs)\n",
+    "\n",
+    "  # predictions.shape => (batch, features)\n",
+    "  prediction = self.dense(x)\n",
+    "  return prediction, state\n",
+    "\n",
+    "FeedBack.warmup = warmup"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "6JkaSYaZ9eB7"
+   },
+   "source": [
+    "This method returns a single time-step prediction and the internal state of the `LSTM`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:39:31.188078Z",
+     "iopub.status.busy": "2023-07-27T04:39:31.187633Z",
+     "iopub.status.idle": "2023-07-27T04:39:31.271514Z",
+     "shell.execute_reply": "2023-07-27T04:39:31.270956Z"
+    },
+    "id": "w9Fz6NTKXXwU"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "TensorShape([32, 19])"
+      ]
+     },
+     "execution_count": 87,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "prediction, state = feedback_model.warmup(multi_window.example[0])\n",
+    "prediction.shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "S_ZdvPjdX3y3"
+   },
+   "source": [
+    "With the `RNN`'s state, and an initial prediction you can now continue iterating the model feeding the predictions at each step back as the input.\n",
+    "\n",
+    "The simplest approach for collecting the output predictions is to use a Python list and a `tf.stack` after the loop."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "yotTad3nZXQU"
+   },
+   "source": [
+    "Note: Stacking a Python list like this only works with eager-execution, using `Model.compile(..., run_eagerly=True)` for training, or with a fixed length output. For a dynamic output length, you would need to use a `tf.TensorArray` instead of a Python list, and `tf.range` instead of the Python `range`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:39:31.274952Z",
+     "iopub.status.busy": "2023-07-27T04:39:31.274446Z",
+     "iopub.status.idle": "2023-07-27T04:39:31.279211Z",
+     "shell.execute_reply": "2023-07-27T04:39:31.278557Z"
+    },
+    "id": "g1GRDu3mZtr9"
+   },
+   "outputs": [],
+   "source": [
+    "def call(self, inputs, training=None):\n",
+    "  # Use a TensorArray to capture dynamically unrolled outputs.\n",
+    "  predictions = []\n",
+    "  # Initialize the LSTM state.\n",
+    "  prediction, state = self.warmup(inputs)\n",
+    "\n",
+    "  # Insert the first prediction.\n",
+    "  predictions.append(prediction)\n",
+    "\n",
+    "  # Run the rest of the prediction steps.\n",
+    "  for n in range(1, self.out_steps):\n",
+    "    # Use the last prediction as input.\n",
+    "    x = prediction\n",
+    "    # Execute one lstm step.\n",
+    "    x, state = self.lstm_cell(x, states=state,\n",
+    "                              training=training)\n",
+    "    # Convert the lstm output to a prediction.\n",
+    "    prediction = self.dense(x)\n",
+    "    # Add the prediction to the output.\n",
+    "    predictions.append(prediction)\n",
+    "\n",
+    "  # predictions.shape => (time, batch, features)\n",
+    "  predictions = tf.stack(predictions)\n",
+    "  # predictions.shape => (batch, time, features)\n",
+    "  predictions = tf.transpose(predictions, [1, 0, 2])\n",
+    "  return predictions\n",
+    "\n",
+    "FeedBack.call = call"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Ubop-YWp15XW"
+   },
+   "source": [
+    "Test run this model on the example inputs:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:39:31.282503Z",
+     "iopub.status.busy": "2023-07-27T04:39:31.281948Z",
+     "iopub.status.idle": "2023-07-27T04:39:31.387355Z",
+     "shell.execute_reply": "2023-07-27T04:39:31.386742Z"
+    },
+    "id": "Xja83zEYaM2D"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Output shape (batch, time, features):  (32, 24, 19)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('Output shape (batch, time, features): ', feedback_model(multi_window.example[0]).shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "qMs0rYB8be9M"
+   },
+   "source": [
+    "Now, train the model:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:39:31.390842Z",
+     "iopub.status.busy": "2023-07-27T04:39:31.390286Z",
+     "iopub.status.idle": "2023-07-27T04:46:35.212115Z",
+     "shell.execute_reply": "2023-07-27T04:46:35.211442Z"
+    },
+    "id": "VBRVG2hnNyrO"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "  1/437 [..............................] - ETA: 25s - loss: 0.2621 - mean_absolute_error: 0.31\n",
+      "  9/437 [..............................] - ETA: 2s - loss: 0.2519 - mean_absolute_error: 0.3179\n",
+      " 17/437 [>.............................] - ETA: 2s - loss: 0.2488 - mean_absolute_error: 0.315\n",
+      " 25/437 [>.............................] - ETA: 2s - loss: 0.2440 - mean_absolute_error: 0.312\n",
+      " 34/437 [=>............................] - ETA: 2s - loss: 0.2393 - mean_absolute_error: 0.309\n",
+      " 42/437 [=>............................] - ETA: 2s - loss: 0.2373 - mean_absolute_error: 0.308\n",
+      " 50/437 [==>...........................] - ETA: 2s - loss: 0.2331 - mean_absolute_error: 0.306\n",
+      " 58/437 [==>...........................] - ETA: 2s - loss: 0.2325 - mean_absolute_error: 0.305\n",
+      " 66/437 [===>..........................] - ETA: 2s - loss: 0.2318 - mean_absolute_error: 0.305\n",
+      " 74/437 [====>.........................] - ETA: 2s - loss: 0.2320 - mean_absolute_error: 0.306\n",
+      " 82/437 [====>.........................] - ETA: 2s - loss: 0.2327 - mean_absolute_error: 0.307\n",
+      " 90/437 [=====>........................] - ETA: 2s - loss: 0.2329 - mean_absolute_error: 0.307\n",
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+      "401/437 [==========================>...] - ETA: 0s - loss: 0.2306 - mean_absolute_error: 0.305\n",
+      "410/437 [===========================>..] - ETA: 0s - loss: 0.2306 - mean_absolute_error: 0.305\n",
+      "418/437 [===========================>..] - ETA: 0s - loss: 0.2305 - mean_absolute_error: 0.305\n",
+      "426/437 [============================>.] - ETA: 0s - loss: 0.2303 - mean_absolute_error: 0.305\n",
+      "435/437 [============================>.] - ETA: 0s - loss: 0.2303 - mean_absolute_error: 0.305\n",
+      "437/437 [==============================] - 3s 6ms/step - loss: 0.2303 - mean_absolute_error: 0.3055\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "history = compile_and_fit(feedback_model, multi_window)\n",
+    "\n",
+    "IPython.display.clear_output()\n",
+    "\n",
+    "multi_val_performance['AR LSTM'] = feedback_model.evaluate(multi_window.val)\n",
+    "multi_performance['AR LSTM'] = feedback_model.evaluate(multi_window.test, verbose=0)\n",
+    "multi_window.plot(feedback_model)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "hGjcJsAQJUkI"
+   },
+   "source": [
+    "### Performance"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "sODAwr2ndtDB"
+   },
+   "source": [
+    "There are clearly diminishing returns as a function of model complexity on this problem:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:46:35.216799Z",
+     "iopub.status.busy": "2023-07-27T04:46:35.216560Z",
+     "iopub.status.idle": "2023-07-27T04:46:35.396880Z",
+     "shell.execute_reply": "2023-07-27T04:46:35.396080Z"
+    },
+    "id": "WZwWBA8S6B3L"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "x = np.arange(len(multi_performance))\n",
+    "width = 0.3\n",
+    "\n",
+    "metric_name = 'mean_absolute_error'\n",
+    "metric_index = lstm_model.metrics_names.index('mean_absolute_error')\n",
+    "val_mae = [v[metric_index] for v in multi_val_performance.values()]\n",
+    "test_mae = [v[metric_index] for v in multi_performance.values()]\n",
+    "\n",
+    "plt.bar(x - 0.17, val_mae, width, label='Validation')\n",
+    "plt.bar(x + 0.17, test_mae, width, label='Test')\n",
+    "plt.xticks(ticks=x, labels=multi_performance.keys(),\n",
+    "           rotation=45)\n",
+    "plt.ylabel(f'MAE (average over all times and outputs)')\n",
+    "_ = plt.legend()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Zq3hUsedCEmJ"
+   },
+   "source": [
+    "The metrics for the multi-output models in the first half of this tutorial show the performance averaged across all output features. These performances are similar but also averaged across output time steps. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 92,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-07-27T04:46:35.400116Z",
+     "iopub.status.busy": "2023-07-27T04:46:35.399724Z",
+     "iopub.status.idle": "2023-07-27T04:46:35.403396Z",
+     "shell.execute_reply": "2023-07-27T04:46:35.402806Z"
+    },
+    "id": "jKq3eAIvH4Db"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Last    : 0.5157\n",
+      "Repeat  : 0.3774\n",
+      "Linear  : 0.2979\n",
+      "Dense   : 0.2762\n",
+      "Conv    : 0.2765\n",
+      "LSTM    : 0.2772\n",
+      "AR LSTM : 0.2969\n"
+     ]
+    }
+   ],
+   "source": [
+    "for name, value in multi_performance.items():\n",
+    "  print(f'{name:8s}: {value[1]:0.4f}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "MpBFwfnaHP23"
+   },
+   "source": [
+    "The gains achieved going from a dense model to convolutional and recurrent models are only a few percent (if any), and the autoregressive model performed clearly worse. So these more complex approaches may not be worth while on **this** problem, but there was no way to know without trying, and these models could be helpful for **your** problem."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "pOzaIRYBhqwg"
+   },
+   "source": [
+    "## Next steps\n",
+    "\n",
+    "This tutorial was a quick introduction to time series forecasting using TensorFlow.\n",
+    "\n",
+    "To learn more, refer to:\n",
+    "\n",
+    "- Chapter 15 of <a href=\"https://www.oreilly.com/library/view/hands-on-machine-learning/9781492032632/\" class=\"external\">Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow</a>, 2nd Edition.\n",
+    "- Chapter 6 of <a href=\"https://www.manning.com/books/deep-learning-with-python\" class=\"external\">Deep Learning with Python</a>.\n",
+    "- Lesson 8 of <a href=\"https://www.udacity.com/course/intro-to-tensorflow-for-deep-learning--ud187\" class=\"external\">Udacity's intro to TensorFlow for deep learning</a>, including the <a href=\"https://github.com/tensorflow/examples/tree/master/courses/udacity_intro_to_tensorflow_for_deep_learning\" class=\"external\">exercise notebooks</a>.\n",
+    "\n",
+    "Also, remember that you can implement any <a href=\"https://otexts.com/fpp2/index.html\" class=\"external\">classical time series model</a> in TensorFlow—this tutorial just focuses on TensorFlow's built-in functionality.\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "accelerator": "GPU",
+  "colab": {
+   "collapsed_sections": [],
+   "name": "time_series.ipynb",
+   "toc_visible": true
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/src/scripts/upload_dataset.py b/src/scripts/upload_dataset.py
new file mode 100644
index 0000000..fb8db9d
--- /dev/null
+++ b/src/scripts/upload_dataset.py
@@ -0,0 +1,30 @@
+
+from argparse import ArgumentParser
+from clearml import Dataset
+
+
+def main(args):
+
+    # Create a dataset with ClearML`s Dataset class
+    print(f"Creating dataset {args.dataset_name} in project {args.project}")
+    dataset = Dataset.create(dataset_project=args.project, dataset_name=args.dataset_name)
+
+    for f in args.files:
+        # This works for both files and folders
+        dataset.add_files(path=f)
+
+    # Upload dataset to ClearML server (customizable)
+    dataset.upload()
+
+    # commit dataset changes
+    dataset.finalize()
+
+
+if __name__ == '__main__':
+    # Example: python3 upload_dataset.py -p asd -n fds -f $BASE_PATH/*.csv $BASE_PATH/*/*.parquet
+    parser = ArgumentParser()
+    parser.add_argument('--project', '-p', type=str, default='Time Series PG')
+    parser.add_argument('--dataset_name', '-n', type=str)
+    parser.add_argument('--files', '-f', type=str, required=True, nargs='+')
+    args = parser.parse_args()
+    main(args)
diff --git a/src/tracking/__init__.py b/src/tracking/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/src/tracking/clearml_tracker.py b/src/tracking/clearml_tracker.py
new file mode 100644
index 0000000..a30b91e
--- /dev/null
+++ b/src/tracking/clearml_tracker.py
@@ -0,0 +1,45 @@
+from clearml import Task, Logger, OutputModel
+from .tracker import Tracker
+
+
+class ClearMLTracker(Tracker):
+
+    def __init__(self, project_name=None, experiment_name=None):
+        self.task = Task.current_task() or Task.init(project_name=project_name, task_name=experiment_name,
+                                                     #  auto_connect_frameworks={'tensorflow': False, 'tensorboard': True}
+                                                     )
+        self.logger = Logger.current_logger()
+        self._callback = None
+
+    def execute_remotely(self, queue_name):
+        self.task.execute_remotely(queue_name=queue_name)
+
+    def track_config(self, config):
+        self.task.set_parameters_as_dict(config)
+
+    def track_artifacts(self, filepath, name=None):
+        self.task.upload_artifact(name, artifact_object=filepath)
+
+    def track_model(self, filepath, name=None):
+        output_model = OutputModel(task=self.task, framework="TensorFlow")
+        output_model.tags = [name]
+        output_model.update_weights_package(weights_path=filepath, auto_delete_file=False)
+
+    def log_scalar_metric(self, metric, series, iteration, value):
+        if iteration is None:
+            self.logger.report_single_value(metric, value)
+        else:
+            self.logger.report_scalar(metric, series, iteration=iteration, value=value)
+
+    def log_chart(self, title, series, iteration, figure):
+        self.logger.report_plotly(title=title, series=series, iteration=iteration, figure=figure)
+
+    def finish_run(self):
+        self.task.mark_completed()
+        self.task.close()
+
+    # def get_callback(self):
+    #     if self._callback is None:
+    #         from src.tracking.keras_tracking_callback import ClearMLTrainTrackingCallback
+    #         self._callback = ClearMLTrainTrackingCallback(self.logger)
+    #     return self._callback
diff --git a/src/tracking/tracker.py b/src/tracking/tracker.py
new file mode 100644
index 0000000..ec8c754
--- /dev/null
+++ b/src/tracking/tracker.py
@@ -0,0 +1,32 @@
+
+class Tracker:
+
+    def __init__(self, project_name, experiment_name):
+        super().__init__()
+
+    def execute_remotely(self, queue_name):
+        pass
+
+    def track_config(self, configs):
+        # Used to track configuration parameters of an experiment run
+        pass
+
+    def track_artifacts(self, filepath, name=None):
+        # Used to track artifacts like model weights
+        pass
+
+    def track_model(self, filepath, name=None):
+        # USed to track model weights
+        pass
+
+    def log_scalar_metric(self, metric, series, iteration, value):
+        pass
+
+    def log_chart(self, title, series, iteration, figure):
+        pass
+
+    def finish_run(self):
+        pass
+
+    def get_callback(self):
+        pass
diff --git a/src/training/__init__.py b/src/training/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/src/training/window_generator.py b/src/training/window_generator.py
new file mode 100644
index 0000000..4bfa14f
--- /dev/null
+++ b/src/training/window_generator.py
@@ -0,0 +1,124 @@
+import numpy as np
+import tensorflow as tf
+import matplotlib.pyplot as plt
+
+
+class WindowGenerator():
+    def __init__(self, input_width, label_width, shift,
+                 train_df, val_df, test_df,
+                 label_columns=None):
+        # Store the raw data.
+        self.train_df = train_df
+        self.val_df = val_df
+        self.test_df = test_df
+
+        # Work out the label column indices.
+        self.label_columns = label_columns
+        if label_columns is not None:
+            self.label_columns_indices = {name: i for i, name in
+                                          enumerate(label_columns)}
+        self.column_indices = {name: i for i, name in
+                               enumerate(train_df.columns)}
+
+        # Work out the window parameters.
+        self.input_width = input_width
+        self.label_width = label_width
+        self.shift = shift
+
+        self.total_window_size = input_width + shift
+
+        self.input_slice = slice(0, input_width)
+        self.input_indices = np.arange(self.total_window_size)[self.input_slice]
+
+        self.label_start = self.total_window_size - self.label_width
+        self.labels_slice = slice(self.label_start, None)
+        self.label_indices = np.arange(self.total_window_size)[self.labels_slice]
+
+    def __repr__(self):
+        return '\n'.join([
+            f'Total window size: {self.total_window_size}',
+            f'Input indices: {self.input_indices}',
+            f'Label indices: {self.label_indices}',
+            f'Label column name(s): {self.label_columns}'])
+
+    def split_window(self, features):
+        inputs = features[:, self.input_slice, :]
+        labels = features[:, self.labels_slice, :]
+        if self.label_columns is not None:
+            labels = tf.stack([labels[:, :, self.column_indices[name]] for name in self.label_columns], axis=-1)
+
+        # Slicing doesn't preserve static shape information, so set the shapes
+        # manually. This way the `tf.data.Datasets` are easier to inspect.
+        inputs.set_shape([None, self.input_width, None])
+        labels.set_shape([None, self.label_width, None])
+
+        return inputs, labels
+
+    def plot(self, model=None, plot_col='T (degC)', max_subplots=3):
+        inputs, labels = self.example
+        plt.figure(figsize=(12, 8))
+        plot_col_index = self.column_indices[plot_col]
+        max_n = min(max_subplots, len(inputs))
+        for n in range(max_n):
+            plt.subplot(max_n, 1, n + 1)
+            plt.ylabel(f'{plot_col} [normed]')
+            plt.plot(self.input_indices, inputs[n, :, plot_col_index],
+                     label='Inputs', marker='.', zorder=-10)
+
+            if self.label_columns:
+                label_col_index = self.label_columns_indices.get(plot_col, None)
+            else:
+                label_col_index = plot_col_index
+
+            if label_col_index is None:
+                continue
+
+            plt.scatter(self.label_indices, labels[n, :, label_col_index],
+                        edgecolors='k', label='Labels', c='#2ca02c', s=64)
+            if model is not None:
+                predictions = model(inputs)
+                plt.scatter(self.label_indices, predictions[n, :, label_col_index],
+                            marker='X', edgecolors='k', label='Predictions',
+                            c='#ff7f0e', s=64)
+
+            if n == 0:
+                plt.legend()
+
+        plt.xlabel('Time [h]')
+
+    def make_dataset(self, data):
+        data = np.array(data, dtype=np.float32)
+        ds = tf.keras.utils.timeseries_dataset_from_array(
+            data=data,
+            targets=None,
+            sequence_length=self.total_window_size,
+            sequence_stride=1,
+            shuffle=True,
+            batch_size=32,)
+
+        ds = ds.map(self.split_window)
+
+        return ds
+
+    @property
+    def train(self):
+        return self.make_dataset(self.train_df)
+
+    @property
+    def val(self):
+        return self.make_dataset(self.val_df)
+
+    @property
+    def test(self):
+        return self.make_dataset(self.test_df)
+
+    @property
+    def example(self):
+        """Get and cache an example batch of `inputs, labels` for plotting."""
+        result = getattr(self, '_example', None)
+        if result is None:
+            # No example batch was found, so get one from the `.train` dataset
+            result = next(iter(self.train))
+            # And cache it for next time
+            self._example = result
+        return result
diff --git a/start.sh b/start.sh
new file mode 100755
index 0000000..c24ff0e
--- /dev/null
+++ b/start.sh
@@ -0,0 +1,2 @@
+#!/bin/bash
+docker run --rm -it -u $(id -u):$(id -g) --gpus all -p 8888:8888 -v $PWD/:/app/ time_series_playground