From 4f51b198f6306151305536f1b180614ee6e6a3d4 Mon Sep 17 00:00:00 2001
From: Michael Weinold <23102087+michaelweinold@users.noreply.github.com>
Date: Tue, 22 Oct 2024 13:05:58 +0200
Subject: [PATCH] updated content
---
.../1_brightway_browser_introduction.ipynb | 196 ----
content/1_bw_useeio_example.ipynb | 154 ++++
content/2_brightway_browser_matrices.ipynb | 847 ------------------
.../brightway2-project-USEEIO-1.1-backup.gz | Bin 0 -> 15292046 bytes
content/tests_brightway/tests_brightway.ipynb | 11 +-
dev/test_project_upload.py | 27 +
6 files changed, 187 insertions(+), 1048 deletions(-)
delete mode 100644 content/1_brightway_browser_introduction.ipynb
create mode 100644 content/1_bw_useeio_example.ipynb
delete mode 100644 content/2_brightway_browser_matrices.ipynb
create mode 100644 content/tests_brightway/brightway2-project-USEEIO-1.1-backup.gz
create mode 100644 dev/test_project_upload.py
diff --git a/content/1_brightway_browser_introduction.ipynb b/content/1_brightway_browser_introduction.ipynb
deleted file mode 100644
index 495956f..0000000
--- a/content/1_brightway_browser_introduction.ipynb
+++ /dev/null
@@ -1,196 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Imports\n",
- "\n",
- "Due to a limitation of Pyodide (see also [the Limitations page of the documentation](https://docs.brightway.dev/projects/live/content/limitations.html#)), a patch is required to use Brightway in the JupyterLite environment:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "trusted": true,
- "vscode": {
- "languageId": "plaintext"
- }
- },
- "outputs": [],
- "source": [
- "import micropip\n",
- "await micropip.install(\n",
- " 'https://files.brightway.dev/fs-2.5.1-py2.py3-none-any.whl'\n",
- ")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Due to a limitation of Web Assembly, SQL databases cannot be stored in every directory of the file system. The `BRIGHTWAY_DIR` environment variable must be set to make sure the `/tmp/` directory is used for databases."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "trusted": true
- },
- "outputs": [],
- "source": [
- "import os\n",
- "os.environ[\"BRIGHTWAY_DIR\"] = \"/tmp/\""
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Now we can import the Brightway packages. The Pyodide kernel of the JupyterLite environment uses a [the `micropip` package](https://micropip.pyodide.org/en/stable/) to install other packages. Make sure not to change the exact versions of the Brightway packages. Only the versions listed below have been optimized for use in the JupyterLite environment."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "trusted": true
- },
- "outputs": [],
- "source": [
- "await micropip.install('bw2data==4.0.dev29', keep_going = True)\n",
- "await micropip.install('bw2io==0.9.dev23', keep_going = True)\n",
- "await micropip.install('bw2calc==2.0.dev14', keep_going = True)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "trusted": true
- },
- "outputs": [],
- "source": [
- "import bw2data\n",
- "import bw2calc\n",
- "import bw2io"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Brightway Functionality\n",
- "\n",
- "Due to a limitation of Pyodide (see also [the Limitations page of the documentation](https://docs.brightway.dev/projects/live/content/limitations.html#)), Brightway project backup files cannot be loaded at the moment. But we can create a sample database:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "trusted": true
- },
- "outputs": [],
- "source": [
- "bw2io.add_example_database(searchable=False)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "We can now do normal Brightway operations in the Browser:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "trusted": true
- },
- "outputs": [],
- "source": [
- "bw2data.databases"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "trusted": true
- },
- "outputs": [],
- "source": [
- "for obj in bw2data.Database(\"Mobility example\"):\n",
- " print(obj)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "trusted": true
- },
- "outputs": [],
- "source": [
- "co2 = bw2data.get_node(name=\"CO2\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "trusted": true
- },
- "outputs": [],
- "source": [
- "gwp = bw2data.Method((\"GWP\", \"simple\"))\n",
- "gwp.write([(co2.key, 1)])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "lca = bw2calc.LCA({bw2data.get_node(name=\"Electric car\"):1}, method=(\"GWP\", \"simple\"))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "lca.lci()\n",
- "lca.lcia()\n",
- "lca.score"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python (Pyodide)",
- "language": "python",
- "name": "python"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "python",
- "version": 3
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython3",
- "version": "3.8"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/content/1_bw_useeio_example.ipynb b/content/1_bw_useeio_example.ipynb
new file mode 100644
index 0000000..9235660
--- /dev/null
+++ b/content/1_bw_useeio_example.ipynb
@@ -0,0 +1,154 @@
+{
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python (Pyodide)",
+ "language": "python",
+ "name": "python"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "python",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.8"
+ }
+ },
+ "nbformat_minor": 4,
+ "nbformat": 4,
+ "cells": [
+ {
+ "cell_type": "code",
+ "source": "import micropip # required by Pyodide\nimport lzma # required by Pyodide",
+ "metadata": {
+ "trusted": true
+ },
+ "outputs": [],
+ "execution_count": 1
+ },
+ {
+ "cell_type": "code",
+ "source": "await micropip.install('bw2io==0.9.dev41', keep_going = True)\nawait micropip.install('bw2calc==2.0.dev23', keep_going = True)\nawait micropip.install('bw2data==4.0.dev59', keep_going = True)",
+ "metadata": {
+ "trusted": true
+ },
+ "outputs": [],
+ "execution_count": 2
+ },
+ {
+ "cell_type": "code",
+ "source": "import os\nos.environ[\"BRIGHTWAY_DIR\"] = \"/tmp/\"",
+ "metadata": {
+ "trusted": true
+ },
+ "outputs": [],
+ "execution_count": 3
+ },
+ {
+ "cell_type": "code",
+ "source": "import bw2data as bd\nimport bw2io as bi\nimport bw2calc as bc",
+ "metadata": {
+ "trusted": true
+ },
+ "outputs": [],
+ "execution_count": 7
+ },
+ {
+ "cell_type": "code",
+ "source": "bi.install_project(project_key=\"USEEIO-1.1\", overwrite_existing=True)",
+ "metadata": {
+ "trusted": true
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "text": "Downloading USEEIO-1.1.tar.gz to /home/pyodide/.local/share/Brightway3/bw2io_cache_dir/USEEIO-1.1.tar.gz\n",
+ "output_type": "stream"
+ },
+ {
+ "name": "stderr",
+ "text": "/lib/python3.12/site-packages/bw2io/download_utils.py:73: TqdmMonitorWarning: tqdm:disabling monitor support (monitor_interval = 0) due to:\ncan't start new thread\n with tqdm(total=total_length) as pbar:\n15925248it [00:00, 455005969.90it/s] \n",
+ "output_type": "stream"
+ },
+ {
+ "name": "stdout",
+ "text": "Restoring project backup archive - this could take a few minutes...\nRestored project: USEEIO-1.1\n",
+ "output_type": "stream"
+ },
+ {
+ "execution_count": 9,
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": "'USEEIO-1.1'"
+ },
+ "metadata": {}
+ }
+ ],
+ "execution_count": 9
+ },
+ {
+ "cell_type": "code",
+ "source": "bd.projects.set_current('USEEIO-1.1')",
+ "metadata": {
+ "trusted": true
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "text": "\u001b[2m13:00:58\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mApplying automatic update: 4.0 database search directories FTS5\u001b[0m\n\u001b[2m13:00:58\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mReindexing database USEEIO-1.1\u001b[0m\n",
+ "output_type": "stream"
+ }
+ ],
+ "execution_count": 13
+ },
+ {
+ "cell_type": "code",
+ "source": "activity_cars = bd.utils.get_node(\n database = 'USEEIO-1.1',\n name = 'Automobiles; at manufacturer',\n type = 'product',\n location = 'United States'\n)",
+ "metadata": {
+ "trusted": true
+ },
+ "outputs": [],
+ "execution_count": 15
+ },
+ {
+ "cell_type": "code",
+ "source": "method_gcc = bd.Method(('Impact Potential', 'GCC'))",
+ "metadata": {
+ "trusted": true
+ },
+ "outputs": [],
+ "execution_count": 16
+ },
+ {
+ "cell_type": "code",
+ "source": "lca = bc.LCA( \n demand={activity_cars: 1}, \n method = method_gcc.name\n) \nlca.lci() \nlca.lcia()",
+ "metadata": {
+ "trusted": true
+ },
+ "outputs": [],
+ "execution_count": 17
+ },
+ {
+ "cell_type": "code",
+ "source": "lca.score",
+ "metadata": {
+ "trusted": true
+ },
+ "outputs": [
+ {
+ "execution_count": 18,
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": "0.3768834121437975"
+ },
+ "metadata": {}
+ }
+ ],
+ "execution_count": 18
+ }
+ ]
+}
\ No newline at end of file
diff --git a/content/2_brightway_browser_matrices.ipynb b/content/2_brightway_browser_matrices.ipynb
deleted file mode 100644
index d5d299a..0000000
--- a/content/2_brightway_browser_matrices.ipynb
+++ /dev/null
@@ -1,847 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "id": "1c6c844b-622e-4e74-83b1-c8a1071aaaea",
- "metadata": {},
- "source": [
- "This notebook is based on the [`2 - Building and using matrices in bw2calc.ipynb`](https://github.com/brightway-lca/from-the-ground-up/blob/main/2%20-%20Building%20and%20using%20matrices%20in%20bw2calc.ipynb) notebook by [Chris Mutel](https://github.com/cmutel/)."
- ]
- },
- {
- "cell_type": "markdown",
- "id": "3beee94f",
- "metadata": {},
- "source": [
- "# Imports"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "599ed81f",
- "metadata": {},
- "outputs": [],
- "source": [
- "await micropip.install('bw_processing')\n",
- "await micropip.install('bw2calc==2.0.dev14', keep_going = True)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "80d2e946",
- "metadata": {},
- "outputs": [],
- "source": [
- "import bw_processing as bwp\n",
- "import matrix_utils as mu\n",
- "import bw2calc as bc\n",
- "import numpy as np\n",
- "import pandas as pd"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "4a8c9830-d0ca-479a-9f6a-020b5dd8bc15",
- "metadata": {},
- "source": [
- "Before we dive into it, let's think about what we need to actually build a matrix. What specific data would you need? What don't you need?\n",
- "\n",
- "## Exercise\n",
- "\n",
- "Please think about the minimal set of information you would need to build a *sparse matrix* using [scipy.sparse.coo_matrix](https://docs.scipy.org/doc/scipy/reference/generated/scipy.sparse.coo_matrix.html) (sparse matrices store only non-zero values). Then, create this information as Numpy arrays and actually build a sparse matrix.\n",
- "\n",
- "Here is the matrix you should build:\n",
- "\n",
- "$$\\begin{bmatrix} 0 & 1 \\\\ 2 & 3 \\end{bmatrix}$$"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "1635ef16-d33c-4663-9237-747b45a2ccde",
- "metadata": {
- "tags": []
- },
- "source": [
- "## Hint"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "9b41ae23-bc12-4ddc-9292-49da20f33c32",
- "metadata": {
- "tags": []
- },
- "source": [
- "You will need three Numpy arrays: one for the data, one for the row indices, and one for the column indices."
- ]
- },
- {
- "cell_type": "markdown",
- "id": "41a9de30-1ac1-40af-9ba8-092564e31278",
- "metadata": {},
- "source": [
- "## Solution"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "47d29ce0-79a9-4afd-b1db-7c76faa40bf6",
- "metadata": {
- "tags": []
- },
- "outputs": [],
- "source": [
- "from scipy import sparse\n",
- "\n",
- "data = np.array([1, 2, 3])\n",
- "rows = np.array([0, 1, 1])\n",
- "cols = np.array([1, 0, 1])\n",
- "\n",
- "matrix = sparse.coo_matrix((data, (rows, cols)), (2, 2))\n",
- "matrix.toarray()"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "20404d5e-261f-4922-93e0-bd35ad0d0a15",
- "metadata": {},
- "source": [
- "## `bw_processing`\n",
- "\n",
- "We can run into difficulties when we want to store this data. The library `bw_processing` helps us create data packages, which can store this matrix-building data on variety of file systems. You can read the [`bw_processing` README](github.com/brightway-lca/bw_processing) for more information, and can see the [PyFilesystem2 Docs](https://docs.pyfilesystem.org/en/latest/) for more on the filesystems that can be used.\n",
- "\n",
- "Let's define this same matrix in `bw_processing`.\n",
- "\n",
- "Matrices by definition are two-dimensional, so we know that to build matrices we will always need to specify the row and column indices of the data. We combine these two arrays into a single Numpy [structured array](https://numpy.org/doc/stable/user/basics.rec.html), which uses the labels `row` and `col`."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "04ba1424-c124-4391-805e-68588143ef72",
- "metadata": {},
- "outputs": [],
- "source": [
- "import bw_processing as bwp\n",
- "import numpy as np\n",
- "\n",
- "indices_array = np.array([(0, 1), (1, 0), (1, 1)], dtype=bwp.INDICES_DTYPE)\n",
- "indices_array"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "6396041c-17bf-4a0b-b72a-7f7d73a180f0",
- "metadata": {},
- "outputs": [],
- "source": [
- "indices_array['row']"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "3dcba032-da1a-4818-8126-f4ab1e418c4d",
- "metadata": {},
- "outputs": [],
- "source": [
- "bwp.INDICES_DTYPE"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "1afb5959-335f-4ba0-a40b-91324cc408e0",
- "metadata": {},
- "source": [
- "The data array is the same as before:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "b43f5478-c4aa-4b00-96c2-7d06f115f9b5",
- "metadata": {},
- "outputs": [],
- "source": [
- "data_array = np.array([1, 2, 3])\n",
- "data_array"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "8d887832-21d2-4ca6-aba2-d4f9e27c2c07",
- "metadata": {},
- "source": [
- "This is all we need to create a data package:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "9174a0c1-555f-4857-949f-6276d7d39bf9",
- "metadata": {},
- "outputs": [],
- "source": [
- "dp = bwp.create_datapackage()\n",
- "\n",
- "dp.add_persistent_vector(\n",
- " matrix=\"some name\",\n",
- " data_array=data_array,\n",
- " name=\"some name\",\n",
- " indices_array=indices_array,\n",
- ")"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "c67db730-388f-4b92-9448-44b5b8058880",
- "metadata": {},
- "source": [
- "For such simple matrices, we can also use a shortcut:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "7e993ae8-8c3a-495e-9f74-a4efc1661475",
- "metadata": {},
- "outputs": [],
- "source": [
- "bwp.simple_graph({\n",
- " \"some name\": [\n",
- " (0, 1, 1),\n",
- " (1, 1, 2),\n",
- " (1, 1, 3),\n",
- " ]\n",
- "})"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "92f8c609-333e-4d9c-9829-1b5d6b9ed146",
- "metadata": {},
- "source": [
- "In our technosphere matrix, we will have three production exchanges (each of amount 1), and two consumption exchanges. Our biosphere matrix will only have one number, the emission of $CO_{2}$ from carbon fibre production.\n",
- "\n",
- "Our matrices should look like this:\n",
- "\n",
- "## Technosphere matrix\n",
- "\n",
- "Dimensions are products (rows) by activities (columns).\n",
- "\n",
- "$$\n",
- "\\left[\\begin{array}{ccc} \n",
- "1 & 0 & 0\\\\\n",
- "-237 & 1 & 0\\\\\n",
- "0 & -2.5 & 1\\\\\n",
- "\\end{array}\\right]\n",
- "$$\n",
- "\n",
- "## Biosphere matrix\n",
- "\n",
- "Dimensions are flows (rows) by activities (columns).\n",
- "\n",
- "$$\n",
- "\\left[\\begin{array}{ccc} \n",
- "0 & 26.6 & 0\\\\ \n",
- "\\end{array}\\right]\n",
- "$$ \n",
- "\n",
- "## Characterization matrix\n",
- "\n",
- "Dimensions are flows (rows) by flows (columns).\n",
- "\n",
- "$$\n",
- "\\left[\\begin{array}{c} \n",
- "1\\\\ \n",
- "\\end{array}\\right]\n",
- "$$"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "8081b317-4d2e-447e-a5dc-2e2485920030",
- "metadata": {},
- "source": [
- "But before this gets too abstract, let's do the same for our example system:\n",
- "\n",
- "
"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "c52f1897-f6c7-410c-9cfa-8fc0b0be51d6",
- "metadata": {},
- "source": [
- "We need integer indices for each concept. The numbers themselves are arbitrary, the point is that we will use them consistently in the datapackages, and maintain a mapping from our concepts to these numbers. This might be similar to other fundamental concepts such as a [basis](https://en.wikipedia.org/wiki/Basis_(linear_algebra))."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "7a30f9eb-8914-4273-925f-3d78893cd7bc",
- "metadata": {},
- "outputs": [],
- "source": [
- "natural_gas = 101\n",
- "carbon_fibre = 102\n",
- "bike = 103\n",
- "co2 = 201"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "5a2d45da-125b-40a8-a0de-a10f05af12d1",
- "metadata": {},
- "source": [
- "# A first LCA calculation\n",
- "\n",
- "To use datapackages, we need to know four thing for each point: the row and column ids, the data value, and the sign. We only need to store the non-zero points. Here is an example for the technosphere matrix:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "23951444-84a2-40b5-9687-e3cbd3053dc2",
- "metadata": {},
- "outputs": [],
- "source": [
- "t_data = np.array([\n",
- " 1, # production of natural gas\n",
- " 1, # production of carbon fibre\n",
- " 1, # production of bike\n",
- " 237, # input of natural gas\n",
- " 2.5, # input of carbon fibre\n",
- "])\n",
- "t_indices = np.array([\n",
- " (101, 101), # production of natural gas\n",
- " (102, 102), # production of carbon fibre\n",
- " (103, 103), # production of bike\n",
- " (101, 102), # input of natural gas\n",
- " (102, 103), # input of carbon fibre\n",
- " ], \n",
- " dtype=bwp.INDICES_DTYPE\n",
- ")\n",
- "t_flip = np.array([False, False, False, True, True]) # Numerical sign of the inputs needs to be flipped negative"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "b29dcb59-79eb-4ce4-8881-024b7b0892ab",
- "metadata": {},
- "source": [
- "And similarly for the other matrices (no need to flip signs, so we skip that part):"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "15eaabd8-0b91-4973-a7d6-cb6b5ed9f54e",
- "metadata": {},
- "outputs": [],
- "source": [
- "b_data = np.array([26.6])\n",
- "b_indices = np.array([\n",
- " (201, 102), # emission of CO2\n",
- " ], \n",
- " dtype=bwp.INDICES_DTYPE\n",
- ")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "4e6efb7c-cac3-4536-b93e-da76fa2a49a3",
- "metadata": {},
- "outputs": [],
- "source": [
- "c_data = np.array([1])\n",
- "c_indices = np.array([\n",
- " (201, 201), # CF of CO2\n",
- " ], \n",
- " dtype=bwp.INDICES_DTYPE\n",
- ")"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "53f00163-c997-4555-a563-8a767e75f2fa",
- "metadata": {},
- "source": [
- "We can now create our datapackage, and add the data for all three matrices to it:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "a7fc1602-4fad-45c8-a84f-f47943bfe739",
- "metadata": {},
- "outputs": [],
- "source": [
- "dp_static = bwp.create_datapackage()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "46e9a1b2-6ec3-4627-924a-646a4e8e64a1",
- "metadata": {},
- "outputs": [],
- "source": [
- "dp_static.add_persistent_vector(\n",
- " matrix='technosphere_matrix',\n",
- " indices_array=t_indices,\n",
- " data_array=t_data,\n",
- " flip_array=t_flip,\n",
- ")\n",
- "dp_static.add_persistent_vector(\n",
- " matrix='biosphere_matrix',\n",
- " indices_array=b_indices,\n",
- " data_array=b_data,\n",
- ")\n",
- "dp_static.add_persistent_vector(\n",
- " matrix='characterization_matrix',\n",
- " indices_array=c_indices,\n",
- " data_array=c_data,\n",
- ")"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "58cc32ba-d495-4a27-a7e6-a9c9ceaa7b85",
- "metadata": {},
- "source": [
- "This is already enough to calculate an LCA score:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "4de9b4ab-ce03-4ab3-9e56-42420875356c",
- "metadata": {},
- "outputs": [],
- "source": [
- "lca = bc.LCA(\n",
- " demand={bike: 1},\n",
- " data_objs=[dp_static],\n",
- ")\n",
- "lca.lci()\n",
- "lca.lcia()\n",
- "lca.score"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "c624a683-9374-47f3-b496-7af3b99be0ff",
- "metadata": {},
- "source": [
- "## Exercise\n",
- "\n",
- "Do the same for your steel bike. Make sure you get the same LCIA results as before."
- ]
- },
- {
- "cell_type": "markdown",
- "id": "6f964f4d-28ca-4bbc-8ed2-18068c37cbe5",
- "metadata": {},
- "source": [
- "# A stochastic LCA\n",
- "\n",
- "This is pretty boring so far. The only marginally interesting thing is that we could put our datapackage on another computer, and do calculations on that computer - i.e. we are ready for cloud calculations. Indeed, the library `matrix_utils` allows us to specify datapackages on FTP sites and cloud storage such as Amazon S3.\n",
- "\n",
- "But we can make our example more interesting by adding uncertainty. To do this, we will use the standards in the [stats_arrays](https://stats-arrays.readthedocs.io/en/latest/) library.\n",
- "\n",
- "We will only add uncertainty to the inputs, and the CO2 emission. The other edges will have uncertainty type zero - no uncertainty."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "1c82ee36-07d3-4a3e-aaa3-164682d68344",
- "metadata": {},
- "outputs": [],
- "source": [
- "t_uncertainty = np.array([\n",
- " (0, 1, np.NaN, np.NaN, np.NaN, np.NaN, False),\n",
- " (0, 1, np.NaN, np.NaN, np.NaN, np.NaN, False), \n",
- " (0, 1, np.NaN, np.NaN, np.NaN, np.NaN, False), \n",
- " (5, 237, np.NaN, np.NaN, 200, 300, False), # triangular uncertainty from 200 to 300 \n",
- " (5, 2.5, np.NaN, np.NaN, 2, 3, False), # triangular uncertainty from 2 to 3\n",
- " ], \n",
- " dtype=bwp.UNCERTAINTY_DTYPE\n",
- ")\n",
- "b_uncertainty = np.array([\n",
- " (3, 26.6, 1.5, np.NaN, np.NaN, np.NaN, False), # normal uncertainty with std. dev. of 1.5\n",
- " ], \n",
- " dtype=bwp.UNCERTAINTY_DTYPE\n",
- ")"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "efc258ba-5ff1-4f87-bb7d-7b4d99e51e73",
- "metadata": {},
- "source": [
- "We then will create another data package, and use it to do Monte Carlo:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "bde2e4dd-cf2e-4ad7-8f22-b23c7f7cc847",
- "metadata": {},
- "outputs": [],
- "source": [
- "dp_stochastic = bwp.create_datapackage()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "b1613950-5464-4774-b09c-e06dabe6c57e",
- "metadata": {},
- "outputs": [],
- "source": [
- "dp_stochastic.add_persistent_vector(\n",
- " matrix='technosphere_matrix',\n",
- " indices_array=t_indices,\n",
- " data_array=t_data,\n",
- " flip_array=t_flip,\n",
- " distributions_array=t_uncertainty,\n",
- ")\n",
- "dp_stochastic.add_persistent_vector(\n",
- " matrix='biosphere_matrix',\n",
- " indices_array=b_indices,\n",
- " data_array=b_data,\n",
- " distributions_array=b_uncertainty,\n",
- ")\n",
- "dp_stochastic.add_persistent_vector(\n",
- " matrix='characterization_matrix',\n",
- " indices_array=c_indices,\n",
- " data_array=c_data,\n",
- ")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "984c71e8-dfcc-445e-9acd-9ba0bc8c9fc9",
- "metadata": {},
- "outputs": [],
- "source": [
- "lca = bc.LCA(\n",
- " demand={bike: 1},\n",
- " data_objs=[dp_stochastic],\n",
- " use_distributions=True,\n",
- ")\n",
- "lca.lci()\n",
- "lca.lcia()\n",
- " \n",
- "mc_results = [lca.score for _ in zip(range(50), lca)]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "666b3486-280f-4503-85e4-9e25ea5f3f4e",
- "metadata": {},
- "outputs": [],
- "source": [
- "sb.displot(np.array(mc_results))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "bce3c9f5-cfd6-40f0-94af-5e36b8bcc3a3",
- "metadata": {},
- "outputs": [],
- "source": [
- "import numpy as np"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "a0e37bd1-bf63-4037-9916-06b9db6f9895",
- "metadata": {},
- "source": [
- "## Class Exercise\n",
- "\n",
- "The numpy function for correlation coefficients is `corrcoef`. Can we do a basic sensitivity analysis on the Monte Carlo parameters? See if you can capture the matrix values during each iteration, and then calculate the correlation coefficients between this matrix values and the LCIA scores."
- ]
- },
- {
- "cell_type": "markdown",
- "id": "688ed0a3-f5ff-476a-b1d6-cc1bc63abc6d",
- "metadata": {},
- "source": [
- "# Correlating exchanges\n",
- "\n",
- "If we sample each exchange independently, we lose some of the logic of our product system. In our example system, the $CO_{2}$ should be tied directly to the natural gas consumption, but it isn't:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "1b926b98-7cee-4c69-a846-35f6cbb97aa3",
- "metadata": {},
- "outputs": [],
- "source": [
- "params = []\n",
- "\n",
- "for _ in range(100):\n",
- " next(lca)\n",
- " params.append({\n",
- " 'co2': lca.biosphere_matrix[lca.dicts.biosphere[co2], lca.dicts.activity[carbon_fibre]],\n",
- " 'ng': -1 * lca.technosphere_matrix[lca.dicts.product[natural_gas], lca.dicts.activity[carbon_fibre]],\n",
- " })"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "1c60872b-2309-4e15-b551-741266146c30",
- "metadata": {},
- "outputs": [],
- "source": [
- "sb.scatterplot(data=pd.DataFrame(params), x='ng', y='co2')"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "7347e5e4-776f-4a1b-8ac7-dab734c74801",
- "metadata": {},
- "source": [
- "We fix this by drawing correlated samples ahead of time - this is the idea behind the `presamples` package, whose functionality is now integrated directly into Brightway. We will make up a model to illustrate how this would work; we can assume that (again, totally made up) 80% of the natural gas goes to energy, the ratio stays the same, but with a little bit of noise."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "6412f750-65bd-42f7-b290-0cef96ddd4be",
- "metadata": {},
- "outputs": [],
- "source": [
- "ng_samples = np.random.triangular(200, 237, 300, size=100)\n",
- "co2_samples = 26.6 / 237 * ng_samples * np.random.normal(loc=1, scale=0.025, size=100)"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "2cf9ceb1-b7f3-4b8f-b13f-3d4c05f46553",
- "metadata": {},
- "source": [
- "We can now add another datapackage which will overwrite our previous values (but only where we tell it to). Note that we are now creating `arrays`, not `vectors`.\n",
- "\n",
- "We need to tell the datapackage that these two resources are correlated - otherwise there would be two RNGs used to samples them independently again. We can do this by either setting `sequential=True` (in which case they would start with column 0, then column 1, etc.), or by using the same RNG seed for both resources."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "18c956d5-a89c-423f-aad2-906012590a52",
- "metadata": {},
- "outputs": [],
- "source": [
- "dp_correlated = bwp.create_datapackage(seed=42)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "b13c9c8a-cecc-4909-80c9-d8d5b451861f",
- "metadata": {},
- "outputs": [],
- "source": [
- "dp_correlated.add_persistent_array(\n",
- " matrix='technosphere_matrix',\n",
- " indices_array=np.array([(101, 102)], dtype=bwp.INDICES_DTYPE),\n",
- " data_array=ng_samples.reshape((1, -1)),\n",
- " flip_array=np.array([True]) ,\n",
- ")\n",
- "dp_correlated.add_persistent_array(\n",
- " matrix='biosphere_matrix',\n",
- " indices_array=np.array([(201, 102)], dtype=bwp.INDICES_DTYPE),\n",
- " data_array=co2_samples.reshape((1, -1)),\n",
- ")"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "192177b8-45e6-4f64-a201-c0fb0555f630",
- "metadata": {},
- "source": [
- "And now the use of our correlated samples reflects reality a lot better. Note that we justs add the new datapackage after the original one, and set `use_arrays=True`:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "7ac9c5fb-a726-40c4-9e51-d1e422fe93a2",
- "metadata": {},
- "outputs": [],
- "source": [
- "lca = bc.LCA(\n",
- " demand={bike: 1},\n",
- " data_objs=[dp_stochastic, dp_correlated],\n",
- " use_distributions=True,\n",
- " use_arrays=True,\n",
- ")\n",
- "lca.lci()\n",
- "lca.lcia()\n",
- "\n",
- "corr_params = []\n",
- "\n",
- "for _ in range(100):\n",
- " next(lca)\n",
- " corr_params.append({\n",
- " 'co2': lca.biosphere_matrix[lca.dicts.biosphere[co2], lca.dicts.activity[carbon_fibre]],\n",
- " 'ng': -1 * lca.technosphere_matrix[lca.dicts.product[natural_gas], lca.dicts.activity[carbon_fibre]],\n",
- " })"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "d71fa519-7b1b-4122-be55-11cae2164437",
- "metadata": {},
- "outputs": [],
- "source": [
- "sb.scatterplot(data=pd.DataFrame(corr_params), x='ng', y='co2')"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "da36cc00-a224-4334-8da1-a55a24f05cf3",
- "metadata": {},
- "source": [
- "## Exercise\n",
- "\n",
- "Do the same for your steel bike - correlate iron ore resource consumption to mining."
- ]
- },
- {
- "cell_type": "markdown",
- "id": "8216209b-1a34-4e4c-86e6-a69862e463fe",
- "metadata": {},
- "source": [
- "# Using arrays for scenarios\n",
- "\n",
- "In addition to correlated samples, we can use arrays for scenarios. Let's imagine two different possibilities: a lightweight bike with 1.5 kilograms of carbon fibre, and a technology platform that allows for efficient bike sharing making each bike functionally equivalent to two bikes (I know, I find this silly as well). If we treat these as separate possibilities, we have four scenarios in total.\n",
- "\n",
- "For this to work, we will need to create **two** new arrays, one for each choice, and then tell the software to do combinatorial sampling:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "1c5af1e7-4063-46da-b3cc-3a25769e51c7",
- "metadata": {},
- "outputs": [],
- "source": [
- "dp_scenarios = bwp.create_datapackage(combinatorial=True)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "c4ad459f-29bd-4454-b51f-72dbc16a5356",
- "metadata": {},
- "outputs": [],
- "source": [
- "dp_scenarios.add_persistent_array(\n",
- " matrix='technosphere_matrix',\n",
- " indices_array=np.array([(102, 103)], dtype=bwp.INDICES_DTYPE),\n",
- " data_array=np.array([(2.5, 1.5)]),\n",
- " flip_array=np.array([True]),\n",
- " name='cf scenario'\n",
- ")\n",
- "dp_scenarios.add_persistent_array(\n",
- " matrix='technosphere_matrix',\n",
- " indices_array=np.array([(103, 103)], dtype=bwp.INDICES_DTYPE),\n",
- " data_array=np.array([(1, 2)]),\n",
- " name='double bike'\n",
- ")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "f75e957c-077a-481f-82e6-09dfd1007bbe",
- "metadata": {},
- "outputs": [],
- "source": [
- "scenario_mapping = {\n",
- " (0, 0): \"Original\",\n",
- " (0, 1): \"Each bike counts double\",\n",
- " (1, 0): \"Lightweight\",\n",
- " (1, 1): \"Lightweight & each bike counts double\",\n",
- "}"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "13c7d614-db27-47bf-844f-090f5a5306db",
- "metadata": {},
- "outputs": [],
- "source": [
- "lca = bc.LCA(\n",
- " demand={bike: 1},\n",
- " data_objs=[dp_static, dp_scenarios],\n",
- " use_arrays=True,\n",
- ")\n",
- "lca.lci()\n",
- "lca.lcia()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "cf559abe-39d1-410c-9410-9ea46c0c3ef2",
- "metadata": {},
- "outputs": [],
- "source": [
- "resource_group = next(grp for grp in lca.technosphere_mm.groups if grp.label == 'double bike').indexer.indexer"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "f85dcaef-f510-45c1-9a99-56436aa9c93b",
- "metadata": {},
- "outputs": [],
- "source": [
- "print(lca.score, scenario_mapping[resource_group.index])\n",
- "\n",
- "for scenario_result in lca:\n",
- " print(lca.score, scenario_mapping[resource_group.index])"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python [conda env:bw25]",
- "language": "python",
- "name": "conda-env-bw25-py"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 3
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython3",
- "version": "3.10.10"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/content/tests_brightway/brightway2-project-USEEIO-1.1-backup.gz b/content/tests_brightway/brightway2-project-USEEIO-1.1-backup.gz
new file mode 100644
index 0000000000000000000000000000000000000000..5ca407519ffc9171a0dfe24255462f25e8c2f161
GIT binary patch
literal 15292046
zcmV)7K*zryiwFoRRTpOh|6+1!XJ~YHVRIWn*+LRZ~SpNlz^?E-@`)VPk7`
za56G2Ph)g%Vr6nIGB7eUEigGPGcrLi9k+}V!|IA;qoO_$m!?y`bh(a1|M6U9|rjSKp#FT?3{`!CZ*Sc#jyX=aqXF?3t
zwveT){9^wj=f5zf`={;xnalCdywKL#TpKM5oPRB)8Z@{0cb@-khBsTdu=P%1__o_^
z?f?1b@MAIlzqkK`C*uD^{7?8_nNq5v99#hjDp5|v|Nl(ztiq4>Ysyxiq^hs-^1ZwZ6Nyn9SM
z7yl{0{{P|sc2MrCyT)f>>K}^=mGvS@!z}Au6CossQ(V_H%|Yh
z^ZviWe;C_8#Q$3TM@X2c|Nbrd?;mvEkhyo8H*Pm_8#kJQaP?J|9ya$%Yp=dqw#qW|
zE;{$TK8y(4`ce3!jW)r*k|yBa`IDoz-+K7yz@OQ6hi&RG68}wFUE$xi+0GA-!$bR1
zGM6gLbtcMngc+i$AyN%4h16E^%FV-e&30RF9h%X@x7&8yO-2Pb68lnbO^G^sPO
z{}1*5yKL*=4M&C1P=SL-3~#pDI{c6N|2#M2>py_HDJJ^=f5)%AC*5Pr;EBgzqW_=h
z|0nu?`v1ZV*2-48G86s(f2RM365Ga&7%_a?&Hp=`|Nn{qH}dcPzpei%jIm49;hH0y2)MepZcd$b!JMvYndr#nm}2^0PQMF0OE;{OX)
z;7s)Y|C#=O__m|N$Zdij4(MO(zw7+}ALoBt|8H%fC+2@A;{Qba|M%g4A&o4F`-AgR
zT2)TW|4zjJu-N81jTkl9s#=@e6~4~BjL}y3trH?DV*uE;o`6oAu>P}c{?{la3#A6-
z(&&7m{`+_7zu%3vYd%
zIb-pJ0smJSA2QeABCCuPrEjl#f5Ff1I%?yE(p93agj71i1L+KgS7)Wlt4v!VgwLx+
zo1(qyt=RtRuJTP@YNhhbh`h|SubRvi!DpdXN*j|GQKZ%kC=ERK8UFu_9nKLRDsEC{$L2(1cto
zV+;Gwt5FtZshkd(2r6V6e@9m34gL~Q2d8W-bD_t-SC~lYCi1_D{BI)v`#b;BgLNUQ
zDxb*zCi1_3=6_*up{u6O%gQ-d*0Kq{&Mmy63-FB=&ien7|H0t&Ki2ji@Y#R87lILf#HjsF!rI-mwDb)&bI7o;QF&>{nL`?9iBK@G*ytL$Vv?&tUMmm
zHFcSVQr6T&b!b}tH&Cvy>GO;I{G!DF8eN;H@JfL%=QSQqx-yF(g`lWKS-aTX>w>dB
znfi!x(`wiNO$F*!D7=!gvc|n|YwJsI3S(*O$jpSV$7_&}c97s$0X|
z4_^4G6JK4vy9$p1ys2=3ge=fbP#b_8*Nu0ztyHOP(_XdADqH{ln&G0mstCD(L*wd}t`cQ!Lj?{UglRIBM?ntlGtpEbR*kBq
z>1=+)rRQxt(<*!Swh={D!pLJNEbOqtYUBdDEQ5?bH+dertH$J)@ABf}_oe+Z5D^Vd
zO4NCT4k;~kOs+uR^JoK3m=moI85lMD#lQRcN>3!4uSIBL36}3AG!GR?DLj^>s3Hza
zSrxWBUxzMaKiuGU-Cd=f_fiC%;g(P@3dZEP-zGLi*%Y}`y1Un73qSwX#wQ(}R-=M`
zvodB@Rk
zbtzPLmWRGQ|B21UU%rsu%T+2CwaJ2W2DYJa((q)NRSq5jnkSasF0VZA(5UJ
zprgXM3q@83Qv%+gHY*|{9A=4i(q5GvMjiKVRN{}bCAC@FMq7x|!c%+a5Ok2hGJ}K*
zb)`h(>TWeQJnh6Q7kTyjWb9ZyjIS@c=Y%n(61L<5{M?6S(QpRq4)bho&HzeF>6x4DJ>nl`EcxzyXHfD7J
z#jERx*Xl58yTj&varB#8r+ewL@Pc~Q1)OEr0+cPDFv4!jJV2u+i(2rxWB#__G06@K
zm{g3wGpq2JI@dTU7RM!4Fv1FtS9LyRV3C(+TkDq#%#m;-t$ca3{Dg6FcpF$J9^!<B9T6?%wNzcTYQdo~fov)>}9yOS~710d^>=B6B5BI5$>RLST(Loj>sSR407-
z@cfIVd)Y?i-ojz!aOuD(cyn(wz{ddd>QFaji}M42oP3gRk9qXk-Y-KKXjf-N8Gwg%
z2|LcY5qV>!a6uNbL+nw0f#uGgV{CU7Z~=d9@K!D0IW>?j+
zY-$xcPjuw4XLeiRj#-jzI0tWDHJOL#$+YJN%L4vSN(tzdP42o~e)YVWRz2#^$EVc*
zWE-jAPDtF~8?o}rNE{rXaxTEIM8`MQ`F_8rw)ekFPiTd*9@giZoZg{=CsMG(1}|GW
z*ECq9_NsY5KWW5gTTYku3%oH@7St|RKsJq)hwl+2esIaofN^%aeAP-XyftF}U3#BV
z(X1P=F9Vwo0zRb?WQq#JS9w?YZkMn9)tbLu`90Zt2Z?QV05ylBrK7aOUht>_3>Bi2
zF0{SZ^0z*-_->OdRdBYYcKK|%a@bZ;8@Fy#+T(%HkE7)EUP=q
z7tdQBI^yKNrCrXAv3Mp>aSsll>Gc$dwg*ehp>1klPJ7iK&X{D$#okFL#o0<@(M9G7
z_PPLls2%)Yg*^a!g=8|_6Q23Z%^N*@>j^!I=BlW1w1k5RYbl{qDv&WI48ZisrMr6-
z2S2y3zxRTk_iAnph?5|<(G7j2#-&ZEYamuFI*S?@@$9UZPCCU-X_tKfZ^t32B$h6B%-Z(In%txv=1+*$1ZXLYOYoWmbW0(0je!1E2x@elm
z(y0Vh=AXmJfdJSapr}Jnev+=a_WK71Aza
zi#&xSI0EAvaFebSIBv$t91vHQvb$>Z#Z!NL?^3TO>$P4;5@j$Tjg=?W09}UO*3sqU
zn|X_(LqDGW$DN+oAz@Ti#7ee{<{)~tRT0$C7qk*1YwKLCJBwOQO*Zhrrt9_`y8s(+
z;I)E+^+MkRqdWi{c7+Rb0k_v_*hl3w1I0B7H%tt5U1D2(Q!#Ic>nla_Y=BS(%+GXJ
zH5+d;WPuBkLd2g1<3Qjc_#KrLcbR%XS_c3Cgo}=|9X@*S=~I34_CLlPa6Tp!bGU7%
zOP|_x$LV@Ite^p4OwnWI6^IU213m?Wp{{ED8R$;uiEb}$8T8#@J;!e9$P5}t3K7@f
zUW7LRNUdR4)HhuB$p6#Eo@&H`m2H*(qg`-(Y*n9~+
zC5#c?ijJjRvDq=#JoA0R4bVfaWiGNh(x*VcLD9qE7B~Z(76e+{?bm&O9l7q^ci)p%
zzJUrTVR)6m25To}Rs*!aH#Fb?Pn@T?&2!T{aPt~h9@*o(FAI8ehZg{1)9b-)g47o!
zJb)@=(OK`Y_e`6;JXwk?LG#qGg&OiRCmsUSoWuEyN;!um1oCw#`re~MR~Yp1e7$#o
ztAS_E8c#+9{LbobcJ~rDZaj9MENOE{a$%(v85l%GWCItK5gxiR0+^_+
zNp`r?$QgFFH>RkgcQ_7Ud0^In0UhClz=0sF>I(b|NF`;Lo&Dh9A+PMW)ZKmT%hn|=
zJ$MTgHSk|}AD3Aj@_>zSHbouJ+H>lw=RIVXp0kl-1)1UJVTa_+Wes5^f`A1A!OQf7
z3#@qCBpY3^WFI54a1Wrz70q1>II)^BCK(L=J`XjT&hnKcc`6&lMF%oES_ptQ*c4~mb)Q=f
zIBk|sk|t6hY(N%9p)?s0R9gd#Y62rL62P4B@X!rDJ>hb-dmpQ;fq^(AKqPutY*p>C
zkXjXm(H;~!@9uTzT|fWRMw{N6R)Z;t95fO#k&z|PqPnPk79qMN03Q;!W9FyL?w|eL
zBreo&IKef+X?>;z5@4u`p2<(cUL>C~xwWimrAPvANiZX9^dFZ*~+N0i^
z!KJH=Rp6s8gPa1#CZVhhPFigMc{MmOm~4Bm8!o%yPiJ0yOMg;eHBy7^%JyE=L=gs(
z`xpud*cS;!Z~EQ2FP{A76v?MJ-xPRCl21tu3pHCaMr10NSFtQ)-C1w-n>SbgVAmAk
zWUL458+JsOti3D10kDw9tX=wUpgSS%0q+f3^LdgL@BKKw98}y5<_@!0ysFFh
z&Z35%{>$6zv*OXcMdeK_48zKhugbLA0bH~&zVzA%U8E-*w(mT&I{}dG|XloYm0{o+GKzjhe1*8DT0X3}9-Mwa=
z|MlXXA8$__z*ukbIvE%#P6}0e9dNG*M?sfV6|TG2O=CB{>d5ET=%e}t;84I^3y?(B
z-iA5{i~wRl#2SRI(+<;YfA`q)W=?BpBj|#|S@vYhwFEpVEJ+D3?*qIPtg(xV9Q);x
zOU|7lWXu_{OR335VUW=3g${Jb9v0JIcU@u|`-FnWAH23OER58sVBnXHnBXy4IJoo;g`s
z`C6;8B0p3bt0Bo8pyVhDw1#$pqUctBclGS(NoGoMHc$$mtGd9-M;y&sF+SqU%;v%3
zzZ8W{(bQ$1zH09MF220idZDU3mahQ>fZG(XouSIy(&io!>R}v
zL5fr?_t&ew|NLkBB@bH`VACLk06=EVaz>UadOZ&u2PPJ}yVuc+&HZV;+E2&jMsr)h
zm?UYe0$#Bqug)MfJRAh%tnPAB2j*uz9k}HGo>XY#@#bScUw*QH5+<(ChPp0?sK%&~<4($^f
zsO%cXg_pxohG~MfcWc;eIp4l-Pns$qA;h69AT|nI&3p=M0|pCf3Kv>JvYDo}`C(K1
zWi~ziLP_0Jjj057GAne;MQsU-f*tzGyAs~U!&2IN?YsUf3yJ4n{m1u$U!Krep7r(<
zmzr|_
zOjg9H6wI`c>~*_**-_7(yw<9B^|(>Qri8glf+AFe0wa=O4h(HToQ6~nIxx@OW8b|`
zCa*_!8<>P@ld8U!Q&En^Mb8_+BbmOi3
zgni{5n=NtD#;+%ZSh%tQp@Bk#17gk>bS+j~7Y}FNz{I+U^w2L?v@c!#=ajEBAQg=S
zQ>*YAuz5&Z+_F6Nq<$L5sGELF~FUurf%bG5@wkP0B8fV?|9Vy
z=N)$XrbiXMH@AfhxrRlR++|$qq+?x*&kcRE=_+vt4mse0HC}u3_`Zq&L{&s`WH=%1
zfCV6G0L743M(UjC0$x;wUf%ru)`_1&)$$Icr8_vYy9O4d}=
zIA4vf!J}MZLVZ*)we2l5Mhb4UAo{WE6(`J<$dK$Wg!x=OF8_P2BFQIz+VDM3D#pJ!`$svXS_D>
z^%M^c?V~*bh{srnY-2>!unfDEP_nAFjg2Ye^W+8>OtH}yucg(H!K(_^3oj7bSboMe
zz+(#Ns7Amcb(-jk*N>m{md(?9`3m;HYLvRcLQrC0mp!4lfZ15nxD<8#>FB#QUipUy
z|Be7<1@bx}1eo*rci(w%s^raKZlz#AzGNI)Yg|xP5IY_?lLzICBB{~y-kC-{w)$h^
zqK+VeZE84Y#R4NZ9(&*laBMufFz03O&#n8adJFef
zs!Y_Z9UxP5APkJa;53xrfU0}KJx_dj#koiPv{!Amfk+1S*5ufsF|3AZ^Lk*}m4Kag
zXL;o>*7?Jr^HK#Diz!QHrJ4K(gT=Elzz!Z(l?onA8sEhMKA!7~H%}Xq6upNeFC;yY
zD!?~%1^)$Rm_ZK%jJ?TY%2$rKAEu=02ptOmpi2p~V#0~gV8
zwt;=FbuVl@^^<)j%b41;9zeqzGw+&lYZ-HJ0TM=*b$3$U7(L5k(_WXVbSmj3PArb0
z!{KM&5CD_`PX&i<0kO5}y!rfN_9?&k@UU?wrIf}N6J#j^e|cy&MD;6xX?Kzlm0R8Pe(b+S9JoKpVzvz`zU4Scr8b-#}vt(r%fr#%G8~04E^Nm&)>diwYz$bEpV72t7BWu
z0@se6gOF9uX>9}iY|0e>deX0MI&JlflTKl_%fZq^)i6iznem~+tU?e5oI|Es$76px
z<(xZCmN*-ZkO9^j#*-SxmZ=bN-0;H;27+Oy_gcDqv>3Dhq2pB&nh9dm*^k@vAG&Pq
z@wiPjVOF{3{c~;dMT&}m@#_+>f)i}$Qv&w82GCWat_ovgBRe%Zbe^l+&M*G>P2x7D
z5fVs|VI2w%i$rN6wNqBRc10bu)`ce)&jYlcQ}mZ91TU_l|Zv$@DYF*^@C$5xZxHTy0X^|58P
z=;J`y_COm?_YWa!80&3v{8?WidHIc>OmWvU{Ye2pw@1U*mh~I3c}6NcmOhryL}l!*
znsKVV=ehn@aXd}rCTJUvUcAfV<&8)6F$WiMD1aNhN(bl^S3($pxv-=F)~h<3KW2y+
zm}KB*=~UtrnH&TKur63h2o4crorw~!RD*Q{)t%)vMjkuKbg#bIXZB+SzCcgHBp5^&
zZ3}eKI;&)(wC}pY2I68j-Sg67N2L8yu6AY4`a{Nsy*Ff3*gk22i+EOWxAv-Yf4Rh0
zGryC%-GDW|h5!QXXZ)~Y)dwrnnnLEaBYCJ&FWHbGU+n(jOvyXcfC{2}v|J6K2-Bj1
zg)mmYw_~F_pK{U>^|`-!ppPvVqKRy!3kAfb23-Ws!<*M0PEWvp=3QKL*gPk^k$-*g
zC4Fq!8^g2>WV{3(LQ-Peq0K?>m8%
z>pOk^3j&c9T;K`JNmU?T4XgV~Uw8p*E2?gn{Q|cie#;ztCH+Nw27AEKV1;B&Rw
z342+T0+O5+3a$%xfJHU%%eiIH0fInx@u;CUJbuNQ``!8LJ}Q!1+kjv|$zu6S4K`pw
z&z)CA>0CiA+}`V=9n@XZe|lA415@N}q+J#Q?kJax+c559VWBouqG`JG_0FzGj{4-e
zd&bp^`YLDbcERke6cUPs#VIfj$nBcBxGtByz~E_DxNN=ga6X?PV*g~(HLo8u=cIki
zfysIJW#C?0Z&NX#Z=h445N!c#OKW(aS}KfP!}NUtMFpIZnK1OQw#}MphGc6~)OExm
z>)z`p$G>;^QJ4I&w~fH6If5;#bQ)l9Rb$h0uyPh$!o_yhd*M&S&(?lo8^*(1
z@eYb9*iuO`%i}XY=N~)WhB{9)?*nmmZM6>&qy`g)j>VyEuUc>NNB{i5av$_-C}UY$odGbRDR+W}a)Y4SVaw5ejw0%G3-EHhlgW#24G-Sp$u&PZ_km=+5eymnGs`tszAgmo
zmhps8asmfT*{+s&=vzxpf8HEREZgVW3Y#m4USBceqZ{m(f`@H{bKs}~9*Q1r1iPaCwss=ALy;f2V9u*>p)w;H=#
z^?bN~rnh>g=aqu%z>$Y0QnrF}1|+bADPr;QZixeIbIn&fRBfYjwX017MQBL?b1Jzar5S&JW
zqTpGrP5X87<4b>exnHiYBrJ=@KmbIobf!QefEyqk1h7^
zRjkYf;0pf+sT
zxK!=D^Y7QW-TZWTzw(W(B92xNu~ohryWBL)h1byw77TYj<>F^={p#3jm+GGoU>F)0
zo`q_|RjkHruLn1bc;J|7Q?J>%y!N8CcTP{(fMBsgvM%8rbj2qmCEyt@f>g$Y4(HeZ
z^~jB0eCn;fPLH~`?GzEX7fhXgnPE;G600CQ{tF{g-3Orc@7dWHO^6r1TOTz
znYSFed5YVFB7j`y^gpx>*dC5CXG7#Ng3h!0q~iep^}Efd+y3V%ZX<*Z!72FgwmQ9T
zLPjai)-!NyVc@1Zi~8ks3!Z!9=~MQ#b66<+kM#hOc_OTf5jq2%hz()GdVQpw=o{Fv6v1GnZzCPdwSiTZ6%euPt~&Ffcc-4|taO$QfI+a`k^GUB@Bumn
zo~+4zB|&>Vp0ulx-u%_GZo2lozT?Tm1x40vk(oDu495hJgxK*cs%g3`%s_bIwDniL
zYudhIoZ;`bSFCJRwq|t%i!)0W1jPVm)?Rhz`WIfl>*QPY^@okMEVwt&4WQ@nDNXA!+$>F{G0j;$=XAT)TGC(`(lEVY48%%+g8HmePrpjbuQU+qc_GR
z?@)o41)O`xH0)PyxK%~lgNJ|M-CXLEy6DQKE<0w|xyP$Lm|#|V;Iwb2dSy&=d>^+F
z1+343V6a|PIoKhvE;CY=wE{CMQY_`*p|@V}?Ljm3RUfQP$k}bRh;@w(HFK_I2r0#yaN@WU`j5Jz(P^kTnya6ScPrd)8U+!7qF{$2OOwIz6V99SDC`
zXjT$7kPUU4lrf}D!vl)iSTfWT@-8bq
z^t~|EfCe7F_%7}Dc
zW9OLvVx6wH21eS|9t;e+{GH4$xno*+kok%%-dfg}!GW<>1P=^45Ukd~*zR5jTtCUr
zuia{{zMf5of^~M4RBT^p*vElGhI>_TnuhYMtJJ-Hl`B?%XQ%$XJbWAQ5YCx7Def2Z
zoq}OyX_?pVFzU0BKf83PY41o+*c6Z@5L}ktn0lA}4iwE^;uO_PXSG+|HRmL+?lG|7
zc+u2mf+uB*Uw^yp^p_^4r}6;UfKSPp+f-Fe#KwV!{57Q#Q2@`oI-<`We(fj!bx^OQ
zqEPH##u8)Y1tV?||EeH1ZJy`8Np&fAZgA)3C$4o|hT;xeTG@l|B;a^sn~
zg$~HO)%g9M%fI>b*i;Emj#UtGn>weuiHrnNNdY}z^Ne+Le%ao1#r2opd2HXgPznf6
zI(+ZGBMHfH$+O+c~++aEw&Ms4q%t1I1%98!&La{uy$VI~5
zdoDcs{?ne{qmLh!1s)N{P*Jsk&)}r6`WEC{2^`o$Rb5PPnO*PP_Z8oJbCBb_Dd-bm
zQIeiavQ7^i1p)!@+40_ClT9+&rkl>w*91cBRoGnMMon+-Jp-w2@*Tq02U(^p%z7hV
zUF-58XZ5*kV61~)*6a&VaNq2_W49?-i`BmIY31vD)c#|ZTzp(@s!~jo3AUzaDao4)
z5;st!rdBFF;lQOUPqOo+W3Eq%BQFf_fnuJXD0j?C;|Uwb{t@UFlh9`W-PFw=EVf&p
zcVJ(swBUCo^RNNGgG7WjH?nEGhaT;0{*_Iins3SN=kH^B%p^OqFY*n?tQqryIR6ra
zvyn}*-kWFr@!7`~UL-xC0&SFF8D6uRg>{)V^;=-QJxd8(>UbLR`LjD*IQY!Ie#4PP
zLONOYa#Csor(n!^)HOVx?>h>=d1fm==VS|x+vNbw57Ek4zGi3x3OcaZ0kYe{=&R16
zHb3KrUDsQA)%0GX(vhKF-&9!0$V!d^Oi>6|1gIzpuxzh-ajC_wU;gD(r`IrWN6IP%
z<4FM+S3yB!jb^SIcwHt&wB_K#uNwNArKXHMUnbFer}K@%%gwLZg=8j1AXNT7$T$BaEyVT2uG`6
zdn+ED4T+G;-7bH0$q7Rq9rHxb%!``kNie~h{-=mtUXR5pPRq6|ti9^1%j_?Ha??sZ
z+CN2y3JxcV+)H-okBGl@SslR
zCavKMt6X*d31?h4uFu!OP)k@ZyBF)goRlHaR+zJZ=f0^aGDte#i%0-k24m1;Nc6C`VfbHIoF}t
zNBdsWR}sJp9o`0-x?!CIt68+qf(>90SR9`a`?8PM9=*Y;ul1QMfT3hJH=B@k2@|X(
zHo_^98!~9sRaFi9&4SasucrG+uQ+TKn3)H|rOJl;uS+H$l+FYDTJvs~hfQ+)nSa}T
z+Z0U=0e0BHF+k1;)+~Y91I{w`wF^$eD^hj(WZArDOuIy4L`JZ23!DvZ*+b#sXaW?9
zEL5zi^)>#eTls4ap6sR(I_(#TgEfIliuJv^k!-tV2@@EZWyP~ibq;S_yZjTA&%bg%
z!>);qW-q7VRW7nGo4QmA@WzO>P+b)3`|0nWeae?s?_-s0*J5#qXH7eC-r1TMCxNcH
zz|wYp`HXunTXDTX*Y*(@cp_3L!(24ZKIja~ve8f`h27(P`%3
z`Bxrs+MQdCcdrTOM&J5=_e1AfKSdoKXqk5w#!wgJ00AcjzB6N)7$iX3O4r_N&C|bK
za^EX9?om_~-m$Gu6-?k%vg`A$1a*q=z>dxiPrB}|t?!!rvA&9cwcpT0P1A7j3_H03
zC^KY82_6chOg?3)9XI^RB1a$CM|*TpvBE^R(eILa+krAeH8d{3pEoJ0zyE4m&9mx2
zAGZmWsew`%+?QkLIPj2-t}HwQS*nap6DJng@3ET?zHafps>)bTVFL2rM$BOD5q^T*
zI7a0~09EPs>)I(Fd2q%3dOXzF9%ju1mJePI(u+;Z(P{?9b5*9glh@jKP4$vs1FoPg|yCvCF=!
zqG+FRSbX}aQ!ZI?-((v(K$-g`JR`Tpat;j6axQSQqOzPJ*;TYya6>VRaeeheNZb%b%h;(=j$t4
z7khBirB7e@_Wo4rHn5+u^%dtH#smV)Ih(;qFTi+Q_~#iWRe`!B~KJ4n3J0Q
z^PS%ihwR;F9&;UPLFq)Df?L3wLwn>-IBXV3K$`XO^(&{m_48l7I9|oVgey$u`S7TB
z{`^2+Bh6@P6gD%hx&i$Fx4}Ys3ponumIv3J%D)}9;x8{;e6w*}6ds^%E9QV~f{0xK
z_Dx+C;LCMgq)gVSgYWz5v2)+<`?4jxB9$*EmuSQKLza(fFMY`g5w^39pWV`GQ1WbU20`>z0fsLwd
z+wXd^7JKcvJ@1{p&zl=7DmM8$_Ruw0lDcA1K?G*hs%}Ec>wR+af{U#6-5Gz+r__-R
zuoK9qxL=HTYn@A8A2)SMRSk58FZqNyqhQd#8OI(4$-YG2q3FqX&G5x#&2xR64cZ4f
zCWAksPibR%csVOUPe8IjA3FxS!C9MzP4`Xg3$(;}HaHZ_`6>pZ9ZMfAxeA0^le!lN
z?p*ef(;r^#z8-B%A(^N!tZq}0L#{;NUJes`oUA*d&!RDBAj)IZLt9(W+XU{u`}4cj4rRR9NqMox1O4P
z?V}exwXY)rfmIyt;n~OGa9m2J&P34kQMJ*jYi#qS_g`j{`G@pTeKybl%Dnef0YCtp
zn=%v7q=o0GrLyytN1S-&sNeQ=4nT@ZHkIzYu_BLRi9VeLtVP$#b(xWY8{S#z#I+Xx
zqR)UEycpbEX<5SwW6f#^X3%>RoKl4i2{)eJ|CX5^{2_HO;&C*HF*sXjC)EThsj`bc
zfFFV?cKu(&=KtW}*WZeF_WfU)4-c(JoChIfM@B^`g^mK{$U~}IzGCxr7p(d|dJdJa
zGQclK9!=Y#4H+CFg^ta1R@0X#r*g~iQQnbUssUJ3rrmCT_Wvx=}_k)YS{rpP@{;gN^;Q1xipsN+}
zfk`ZtGyGd~z*XIAqVYOFYtLYCpcAQ?hh>hw%vt=*Sve3EP3odO;pC^+ID4zZ#>>ay*IZP?(0HAWsQE9i^fLpGu)2>W^6SOQZks(R5)Ft?x$O9y2VUyez;X%
zKi_DUpl84pMwWm8E&_6JAcJ5py$PK~9dzH02X5EAGcGz;h`?zHwPTk$4s^vdod=T>
zfm4OM9)zJg?>Ns@W6!&#&!^;0m6olQ%q}^{cyZM1{*Yk7rEgM&2s(Xiq!w5`ihWw5231%9m4X|G!I(Wke6;LW4^p8di#n$^yf%JAmQ!?rHQ0J#gC
zwNw#w#Xhrac=wv`_Z>8qHe|3lYxT7Ytc2&tI-sEuh4muk5MSQ%x*0#*tM7R71%SzN
zK)GzECI)sQb4(VKzHp=Pvt2#gV>fI)-FK(-6O)83n3Dp6amqQTx^Z5Z^C7}x8;H(s
zmj}dj!!KR!g>i^o$hxvT8t_DvC^bhk399AFa_~v#_4aGl`}h{WMgN3(ENaq{NZG-`
zX{BP?$Pnl)3vRk6Tw8AUuG;p=zP}Qv&S`U+eHfa91%do7YlGX^Ze>#i@(zp6xX`zk
zJ=V{v;(^C5Rd@w>bDU-88=u8OgS-|I`nS8+F(d!H|2$`>HOxy83(oprj~z~B8%+gY
z0ruwbh*h4a9@Xia7e_zd_kXca$d+{g(XH4`z!Z^fbxve1MX}qzv)-ll{P;KPY(B2a
zG&Jmw%sE=Vv)E*4d9Srt6tl&Yj`Rf$SDpobQUO|
zDolnxcf|?YOn1&Y>0VU?Y+zdpwpp_@fMMkZ3mFRo&W;o2|2b0(6(~7;lCNKK<_xPb
z@p6XsWsvkLPrP@!u}j=>+D~TccNq$bZ7`BkAQZE1@Ol7Mg+&drgrRlVd-MFeRQn%w
zUte)Y5T)TV!3l;*TEm@#dxawl*w2ootb2I%_WM8deQlsGrG`#X?W7tC0LSfvvu=PL
ztS{`)=FHcR`e@c`Q&hj?B+atKk*^r-fnUvB*|0bh)JD6qC_-oR$BNU}dg`p-^k*4=
zWZ?8+S$IMlTULqH04U;YMG)`~H|F&lK6vl?2lTZfdBblRWH_F!{(?8>kQ{h5Fns_A
zoItx@CyyNT(012f*K->u@dBKi%5J!Z9cm2==zv@@2l{&3F^4DL|N8!?H+na5fY?Oq
z3RbZZMN0`?S%bYnnZrlrP;_Z_#8Fe9xau6=zuarsQiQU^Be7Z;OO`Vli=$mMx~`R$
zK2@{i)rR}5I?YLaAH7i6t~xUu5T;|-=L;3Uu1g=KiD@3u@9y|u!LeKP6DMGYRTX1~
z{b3axrwTv`<5a@;aul3OS+n^Md1IS{-g&5BdB7(pCI!jqF@XT8uxXqCp`{7Nr@qlW
z?kwl~!mZwCZ$bRo8{rdp5DR>r6@`)wmIc7kMJoJ<*WLZ=SyH4u0{#O>vqdI*KsriJ
zB`{e7WnOEhc14G5**wig_MWBwF)M8*9FLlJ@wX2D@U>L;#fFiJ<31VbV&oQ{$a8L;
zb`hwb2S7lVZQtau!!A4P#Xf!r9^YWSv1qdE$#RZ`(s@-viwY^z6r-g+-s72zr@p^e
zhz%eL%V$_MuX5@X2D4du>T)=nex~lw6?VIE^3k`C7yFuE-{`<6=bU-oMW2rCPh}Oz
z0&!9x6E%CEDh^RBA|+o{L1lIK+F^s6pF983I_)yQ-T`XK2_cMY;-r*p=TbuE&Op?M
zPNxk0@#W=yz3T3%;;vyKhQ*73Pbx;rfi{rIpaeLk0Bu{QKB=vLz4;%+Bm4E(TLfDM
zn@I{b)pB&mbjGtHoLS(U&TjI_ebp&feZ6VVD)Dz(4R~QWMHhi#TSmjgK2DcvQeDdW
zKYRMvRW8}M&mbt!`G#NVVCO>nRh62#gpz%}4mV6HVBfX(9{KtK^|)SXW=>-!gXVnf
ziZz^&0#z+5#S#sjH0)J>UT~i8J~^jH?6S$*A_@b3s6juVMgic#R8By;NgF$4%Wevb
z9KFR~`q^R<-hq>xg7R*t!bBWo}
zQL?zQ3^Bw?`yzEcU%$|?Oa6G$AN$Ed1!Op@0DwqcpD#QDvjQNFHO#|wS+jv_7GCW5
zksFK|S0M=tbu1RwoGReRQn25kF1CTQkvi2#ud~3kPv3vSrF|AA(uEgzLTDN=BF%hE
zLpKe{&Z3%>g*o5XbDd@;>pLYS%dvq`s@>(lYyUn~qMdwO9<(Vvl2hB+}FhAYsruQ}+m6TM>i>N$Ed0Qf(IL)|b!y3c6%-pet
zy1nYn-L}1Y@%8fF<}0N*wU>p%-~e4`E5G}~iDS@axl0!H)aOqeF<+`@gC;JaYh(ro
z!pcvNopZ7cPYDkC-~_xbMr8Kb^KYBgeV;D~UEqL9Zv>fMV8fVULkwYqosbao*wwtuohkeV3nSPmaihVc!j_Ibo5|db0E-kdf^)-Q?se*M4F5
zu^ac*EWv}caaOS7lx9K(lNZ3;U^r#mr~3K1cbIRHJ4e0I&#YE>8K$nvGO|;Wd05;~
zfc-L}!wu{DD-Yac^LckzviGpH$Cg=U_BquJ?5nciQ9eSu;i!Onbf+@Ta_F=3gz0+y
zr687A`d;&V2-f#9$Wg%|H|+3^u6wT!#almF>Z}wO1ql&N1Z8EKjGT?lx}lxLZ4B|c
zOmpXkJaX$rU(LAZIMo)c1v7VSiq$&jm_;gI%gF||QZY>x*lpXjmsw@yfqs4z08Fv}
zSg;>fF!NZqvE^99s}~HYw^w}`fBwWYfBStuExdx#f=_{`Dw)gXWW3TtX8M{VYju^T
zPcJuTzG{AbUmumjDVm%BML@d0?Kz%(Z9x2*_4j!M3^h$&^giXpZ>~LQ#=iwoT=fifT4HiYw0WQz4Pt&f77c`lN-U>
zZ*V%IO=MiO0cio;z^ULUbO^A_32z?q+ARHK1`(nL31qeE*IT=a
z@lWqt?~)ZhxM5svY6brbi1wnLsHy2ruo}{})2(uwBAg4Xxb*k;tXuVY2UT(IR8~Mm
z07WgweFCFc*9kUnL!KgLtN(n&AC|l!MN@;Uz^ii(&tbfmt+Zuck$!NVZd1cYcl-7H
zl7BpW*Fk5FH*-c$kZ;^|`W|=OyLhrgSU?O#3xMo+V#Qt!k-UEdvSqT>h8GQ2u_+sP_%a@brDakyg8MQ0laOm_IwGfz2X
zj~h*a*9P0onNej$k>dcr27){bNJDrnhyGX?k8xK9_q$m5@
zIT&FD#5E;@ZLX$Hp(m<1LXtIzX}`{V|IqoLpZkt+GsfXbL&YY?$Z`xghC;b4MjJ$}
zZLrCD-&=4@e&LKM4=bdFIH{qnZNnTQR0KyXWuoH9v=Zkfsq9nky=}dPia+-e>6i-}
zedcSfJi8wqhe-#JUMo~-Y!|5*_VdSHpZS=pXX>YFixSKlK*4DwiW9P`ob$Euz6Dd(
zdDD5KO^=v$$~j*eG>)au=1>jbSE0Kc$G{=qeX_tEYV&>yderOf##u-*A;xmj7zuUeOmg^*B|5z0#bIfb)grmn;dUUJgl{
zf4f0^z_V*uiD+)
zGg#0H1F<37>{8{bZVI0U_+#PoP^P^3qQ{)`!*6$9wvS^6&Eawo$RGkx)~Z8B23WB9
zwU)Mfud(I6a~`tsNI6216Eh`vS>dU58~Vi3wK~RbDC`#b>rBID_BrfIG-Yc
z10Q{L%eO}y)c3Zl25Ji4p$u(w4m(%EqAJ0`bGC#)@1Ahd`*)oD!c`CMtEzl(q%{Rg
zh!iV*OJ?01%PozNp-T1G)4i0h^s$KJx=lGB!ooXnm)X!+GRSWVWkK`2C|!3i^Wd+(
zzUB3OdVUB$#1R$n$fldqj-O>am?*Ri&>eZV^4ET}^lEcYeR+Sr3VuT?I~2bI1&oK--hW8W_)5rDpRuTt*jx85nui*;Bo{
zUCOAIaQKp+TL7cxWLHa~4E@#^IAvR~X|JmXnDme>=6mAQR4gWdJZpby9CWgL>NSp;8VO)`;VCt$i(
z72O(6{@V-774BMeysG;N_kb__#IzsZfAI9<=9mF*fY@*b{9ZswrU=r39kzKRqR=Vc
z8y`})t-bPWeP5ds?T416Wc>wDg8Gdg9e|gQkuwmx8nY8O`O9&yO>utTg8)5UVbN3@
zonx~u&ONJV^CA}|C_wu9&lUF$y>`DWsQ>|&#Ycn_VkV2+sDcW?l1Pv??_8eda4!1N
zSC>D0=h6K%5(9OP3t~g27Yi2lu_Olk16(^s)vf%npY3}7fxoG@60}~>Z71!2GM0yr0RN#
z4M+=Q1HbZGcUiLmHRUT8?K4k5G0By+S2;V>s76ap(qLafPS5!>EL=Z(zOk#=%FIShGQ4Ch>Qq^L8_vkCvc;~(GaDKv(rB8n`_s{;i!J*^X
z;RN~Nuqi&AbE-F{?K@~9yl(;05DL!UV9J~=t)Pn$FejlPIuspxO}W|pqmKA(Ki>vU
z*>Sw8VQ$m6Cxxjqwj}0&@|c*z&>8OBV6RVS?lTCv!ck}YK+Y&JfTr!{uK0nYhV$-a
z7Zn*f^>W95{^G)YABPtz=55I_pO8&=Ij*-hKw1Yz)BgyZO54uVfV03c
zD6#K(EfcHUa1%dx&OyiYb;}Sjd07Hp8rA|c(@cjOi+0{$U7N0waA51HPoC@ey=Lq4
zdWOMPmxYECllajaxPN|!IOkjkH7>7b=6USL=VyIl+!Waei5oHwwFWn7_)RauTfs68
zeoQ9yjSe|uvZ;S|(39gSsR?$P4Exyy4;+8is2Te{DI606i-10B`coMtODqb`*@eirbuW?U}c2{6s(V6IN4Nj#pr{avR^MINB`~wvr||HfOhMxYSO|
z=9hk+rS~cWC{x8xG%8l=a_SW1X$JS#0NWby%I>NK@80C_r+$B5-?>mk2f)b$qlVh?
zD+3j{4J(B;d@mNMv%@i4F7@&fZ}+n?8ysI-vay%nXdo23jOujz
z`4hI9y#KxfbZW&QdBGwnjW+}{$I8Q-NDhJtsmk=mg|7Z^j}7~8A%WW#9B~V)U_G|w
zj6B9HAVf8ID*SF2k$&Zb^&i{kx|jMKqBp(`IF_7?RkdaMw#Y=2+UNGDavvQ0C
zO3pB;@=!F%JA_MKetzozI=e?~DLL3H13fI+Z_dfCo{c_|^W8&JcHej!Ht81wTfQ>G
z=RNjD*)}{I#x>ioC)AqEK|`>yb~k=I)O$N@n<67t7)T+u5;{fa^uZn0P6FXMv&b(EwaoJ{lCo)Xlg(KO1
zpr%{-oyUlsUz==nA4_37k#6ZVs|bi}lCu^$#6QX+R_S{jui0bnJ9N=``Ys70_zfal
zkmu=MtdISJM255ixE4Ek}$6ZRSxkJ1i4D)Wwt!?yi;{2m9M0I1Kh)9zmK
z)GrR$>-T-FzSLk!?P$=36L?_wV9X^ag<`Kfzq8ZbYmZI;Yx4)(y5o8t0X71EdFhG0
z?W`(}(*P^OyBT)owdZTPuXj*KUAS9cWomP1dKLjzt!-#>QI2^8LsD!~POGu?V}60l
z#~jjsBZFU^bqza~sInRT&MjMMt%cZQ$6j~UebWy*c+oNAdg!7dY0nyA+MX;%i8*7a
za8S0n$g7lX-~HVujyq=hz7Nq$uo4L(^=-2
zrHXAZoZv>j!8%xay_&IQ!NF#o*UR^RZuzOMTxJ{surq{wLvd~ot0UO24t?L`l?hc$
z-;+A(oFA51agKfZnu_29r{kt9XJF5M!?}(!K*K~?rh1!ex83f;m6xyk_y&8P%b39j
zryjcYiyI?$E;wgFAhDUCDR;o($Ik9pt)
z_i`Txa8b8YV0}AMi*;Wd%nRXcOAh^3>7<*8a;-zR|S9rkj4o*?o?^8Kv+vC+LE1mtWfDi6=kYa_{kG
z1lbAB2wHXXRUSY6g1!2RaWLDq-LYV`SQ``Mhb7^8;m2HnId@O^)Pu8cddlgi_YAfy
ztM*%$jy6lP;Kv!Vyl85+lq;FOvAf=EyPC-!I-}QL8mzNn3q7;9k=1<>dLYIK+1w}|
z){a$vJg~$M!?Ql72Ow-j#pxF8%jTRV4RzDvq0s#HM~47YF8b)vqx1QDerN&?62A(;
z@8dCDTrpVZ1N2xy3rh-7j$Pn}Th8vkh?;YfysS78nqTGP)F~hMp+X-xD;~tGv)*++
z`*G2GFB=$7NllpdUR6#r_UC6j-}iu*ptt}v5D$J2it_>5Ptuqo`l9By5j#cy+Tf+;
zzhH^bS1n2)Ja$<+u3;Ye?GO%=X^O`BhQ*HEz2VlH`?cH}
zz%87JNgi7s_l|iw+h_8HQmu%9L9IF%?>}>p9PaiFK@W4jG+h
z-QR!IZFhfmVE^^i0w=K`Ul9B*48ITSIWhsaRo*!zJH9dWxzTs+_tD&c>@&r9Uw(mt
zqK~tWSU+F!t79Mr{H$!{yRSk_cjl#^?X_~>Yvv5l7Xl#gqcxh-Bx}KDtB&+Ui1Tg@
zZ`pO|ok#9*(zx$0Lw@t)5rPxb`3Z$e8wDkW`zp{qk@A)2{OP~WJmB)H`{`#bJA?O3F#a&t#S?gi)-?sQJnG5|{?o0~1NuyTJ*wKCLg9xzA(;EBIk7!2)hw
zvLi8fl4V7zRGh$`I-U+#Y~}kmxoXz_YwuCOH48Rx8tN3Rd~H|{K--N1hoyVMQD<-S
z^*7Ic)K8x-N{;8@5DYSNew|COkds6908mB$MLBh(+V#o3n*O^>{MIL1&Ao5G$`{~W
z0_(Bi*Z={hO7nNeyWiMPB;#iYS@hyKoe3*K#R2RUL6jax8JN@U*J1DebdES<
zk8B0MAkCx*XUA%*$%uqz7)Cc$rHYtp^_QRH)JOLD!!Et9jCsZJthQ#Hjk2MxflCO@vu_^q!f)Og)%Rps!=QQwo!frJgEcTXl?8-|kDz2S&1N}u^lWo(WFGD3nH#uD
zTS4p5dikl+GC)2zuqHftjMjH+xbJFL?@%ss&$v0axoRh%%3OE(N|-uRf)?;$n$pGY
zq@4QUOmXA2_UhR(p0SG1G?LTLG|4M&k$HY;E=pb4#9+Uk>Z475^HQqEjvOwj+EN*^
zFZS+MERqrpY`QIKue$x(X6Q_BJh|bUET;*U6c`1yo
z1jIqdH*U=Sc*y6Mp3_Giwd2>OIC`EvK0uI?C1VEc7jA|zu1+sMZrqVmt^E6cU7ap#
z@z2%i!`A-&o~!wfdPUD(Sx<{%q(ZTlxZrm=CB%WQgg4z3qk%);AC|o}^VNNg8ApK#
zW&_)5G0x!ft>6PWz-Cpp=zQgOZ~g9(4L0p_912uga}K8>ZUhfM5d*(q%g=7Jr>u+V
z4P0>TX>(2e<|5;D(3lB!&>Z*8lrQbPf8z5h5IFgS-SbVwd9W~HuQ?^y=kT^2kGgh--~aX58?Wm-kt+kb4?7Z^
z1jUbevveN3*GFsX=*koaIA#0Y%=Hg{Jzmst!ZQ{Qz5lasANa5TkG=N{yP`<9hB4k$#Fy4?5MUsC;H&{o+O4QPDyNKNQ
zh6THGlq*N3sd1Rd1L{u2C({RRaoK!_G7V5IX-a>=weT(@mo*YTPMQ!OMlN1wy*&<_
z`ufeQT;}l`p+%*wYZWORC#*zJau5lsNs0S$dpA2wxPIN6$WmY;me(a^U$jCY
zNcfX7Or0+0?+1Rd>+s`u@C>N9NL=lgjQp{oo)p1I(vDf|HlX>yZs)P6zy=
z-Iu!h%_9c4GP>w2W}DHZG3~G$+S|2gKFE(r%nsC5Y5BBl>DB38w+ycc~4=Hb!ahC?EQZB+!d!?brcTtyZaFoXq
z$AQkR&;(MlBh8IM4oFjrl-+Q#rB-=s`D)!6Z|EVD{rxJ!h@yr?64C<@5k!W^3a(&{
z)!I!)b~>{BdEVR0wTYGOV=BULKY#R%Gj8-aa~Mtv!-IEGsM;z99ug_b0_Q2XMpNG}
zx!Y|6mU^tS-)xOgx>v;l$63^DH6?S=s3d_WHOK3x#yolE7fW{X++v7Z2}_hRC8k1g
zlPkc_gl*(0_Y!pN54&!3|ESIHoH@769JXvXR*v6$;*niUw^+=SI6B~5aq&>vb5}PR9evmsehwf#N4WJ(Y(uA{T5$k$pdcp
zJe;^dGNT?8y(s(y(MPsHF1@l4hRQ3|TmJmfJMMaP?w>u5h)Rh_P>8Rm=0ZtD)ufRL
zviI47s-QKu*j_)WS8i`*??j$P6aa1+74JiK^n
zY`0hW>88)0)qlc%t(tfI>r^FkS*PbFL~2>GrpS2LN#$h>>&Xn=pe;l~<&Yo{M7KrnzAxp;P
zFe9`V(VVnxd5l*tozCMm_jcd;vm-8T-G)mL>d3W-L_mbqzB*o-L}JK&5w3F7^UC|X
zcYAW?_N}`xmP)FPh#-303(Z&?SLBdU9wWPQ@9T!$=d5<)NjrO1QkzB`{Uf88th^NfF1T9PJH1)X+?Uq~vyGEtl$M>@#r(+GRsc*DNS4)Bv=
zBs~^y8ArzcA-g@?N77W3OEZ*>ZeQ=b?z^nLRmW@E^n2UI>2=+3z}q8V_Pa|0$vlEh
z%!z2l+L4j-Q#Rm&;)vy~EuE_D0ax5M=aQxU{uitc2?OpT&OnfGF*9UB4B(~ko|B-)
z5w&F|Pn8ITL6}p5`wm4?VcH9hjgZ?KgRfhk;WujPQy=Z=6tBokpOQLW7-pbCQB(u3
z&mhB#kz@rPj~$g8s?Ogzu3#GkX~g3TBI1@M+3IplS)WptF%@GRetxlQ`kgrYw9Q*}
ziZg9Oj)=&Zglw^qQ6f1klnP_35Hf4km8Gt}_S&CLS>MlLRf#fOHSluC-dWAE$+uFZ
zc+qLfZKOJ93#Tme;LJCCmpBek`NAm)PGJakFkGq)wJ~`Rgk*-UvEP0A{ps7ocJ!0t
zC|8nGWwP5+r<+)lyb(qP4hp|a=XH*K`4Th3U4DApcY8FFeIzKznuzVm5L}rbrXof~
zkIej_afMLGSdr;i+D&N<&g{w@+}(
zJT|Bm;cbvsDI?-EqZ&nB(XYSJ`0LM!y}B{}Kw2UJ$@(iocFb%+!~)(|MDq30={$x@
z9dXp9>-mfbS)i2E)+Vn$+!b|75G=x6*c9beoI8&3NmsUvxbTmjK~72PKj5iQxs8lU
zT3w>p%Tlgf*B15pz1u!>+jeLByIdqC5qB)Okh8HuL^es$Qme?)?(w~A9sJ>o!yojV
z@JIn7#XdmF^gLn3kx(-zM$)Gf*rMy{t+vGLYjuBQRnMKC=3Gc`6qa2_t~w;_P1`Ji
z)kul~*U@3UO^&$otZSF>z2yiQ0vp$o9y_F}1jS*vB*7gNS=PR{<;Pyh$)oPhJqK3;
zlMPGCpWz#pu;WUXGf3E6&R9Ftc6i{xM<=h`YfryO3r*sQg2iPppaXtA(u02-+T38
zZ|`yFl0_R-aQjoUi}u*$_Y;B6vf#O$5ZHLou_;SMRdmO^V3YC%fxk2)JM50O?6@f{^(?z0G
zsdAbo$Gy1Dj;H_KZ-1b`%_&Tbzmz`8R6?E{QWwa(kSfKlV>Wuss5k$9-EN)Z7ASX>;=J@0#7#?X!<}^DO8RfzhUd`~VDn8M_A=oBWYN0)~na|I}x=;e}$;
zF)rW8N>m(Nn-zK80At&W1)~i}Vi==*sIB+z#s};DLHx1R4r2wwZ)BRY07bo0RSAxf
z@>6kJqmC)(UANe%!9QNzs)!nJ^|B$^)rg~zlSeHZx>N>UFSdc3j9l^2Ss%`78S3|L
z!c2$kyO0$?C~`++$f&F^r6I^vx!-lqQA?k`#OSwtHCkq5XCTN4o-JlzAf_D$OM2Xr
z($uw*@*^w0_rvJcJr0fh6YeRCK1=Na28v>i>6hx}uR|k9M*p8q0sTnzDH7gF{fJo?!
z3Nay6M+e5JK;}+K`KS{I9n&lh3x$*ETwk^G`8BU`jN~m}b$d{6aSw+-}x=c~rtju;P^VUE5
z-dBOgi2be%q-F`r@`fePY8(bpR%@xZOxo(e7584z*UJjeusX3RpDGn^3PJ??p-9m~
zc9`n^#;HA)d-dV3d`(m!uO#ycN(D0UlAWo#ZhCJ=n!kFfd%gJ95iOgXgTYmaW
zK5gQ3hZjvqX^*0)5foIQFx)AoGz3Cu5=S^4?G`ZB9*=zHcdGKbjU(8$qBmAI+^
z!Iv{6Z?u`~eVsgahspE);-~GLs8e4^Q~jI5j_^?_HMwvXQ0^I@i(b0*&&y1Id7|G?
z<6TSGf8>0d!3dfIq@dLYE+^b{uj~Pcw(h@7V0h;QNzY9fJ33o$!
z(bQ?0-1x-dr!M`W=L*h|&zpkyCT=chMQ&$~AInOu(I7W-JknQgJhgGuvtE%WFiA<7
zFv*R0D)Qhdg#ur5UL?xI?Js{dY4Mj{o$CAsyZsd%6B4GFx|{`b0P+$Ou2*JAmTPU(
zO()*hGPlE>t!nSWN|>OcfW1h$)nf3`MDJ--H@Vkcy7S|4_nkcBeBTu*GSq>hkyku0
z#DL;D<_!g-;B+yK!x|O*_2D<}`_}l89{FiIA<5DuM#pSwmC3C(e=cW!$nTNZFL(O~!6|d(iH4_vrR}uNr0vBIf=vYCi5t
zXC!o^NFRAU;pQ`^PI7Von_hV3hmAc)P#)zt`$ieD=RhD!g?3IU8K%pWgQ8k5`^>}7
z>gm~5$zsEPDgstQrkP61FT)we_}3xws-WI%ZF%s#!#1}wmh{`fNSKIyBdsF0#yF8>
zIHIGELR*OXeYL#OjGH|NHCy#=LVQX@-%FlavY&C85wX>jNvx39*0%BO^Q%2^@=Evk
z8KO?fcaIVtK?nwfx-x^yLWB>3B9CI>b~z6`XZ_o*9kE_3#*Cz(Fdg>y&YhS*+?=e1p;VWjA1n5N-zqrSNVkIo1BqE2PbUE8DkMtPW^}O$WMr0B=
zTpXVv|AwY&7$u)LQp{i&R6D3n{Mu(z^Iq(D#TggvR_@e^nB01p<(0X)J3UCW^xU0L+MPFB9~*%>6nv0KlRHVA8OZI
z=JHX@CSYX9rmsRWPgbp!NTUvxLGE~94)3`B*l}xl<`X!WBFM=-%kDu+U_?nOK8asv
zkc|n~#d>wuyWT%{<$kT4PC~G;R(ZjgL<`lV*yb6^W|@SlW^`$pxx@HNM~@!oxo1-@
zS>rD2diFxSH$)e!vIO}79I)F$8u8TWTOBy}SieJ;$AbFi@Gb{OTo4x%vM5PxX7bVi46(Y3>GGeUp;gXqyLzzx|a^rQEy#IF|
zw;U$|rB6dvs+SS-un4{&fR~9%o!O$^PwDd6hV$ZXS1;ctXKTMgylD6dpFX&S+w+as
zP0J8cC28PdcK1?6GBe8CbEKL%EODp#-EMgNDZi~#L_Fh+Q)zCS!Xiyhc@BfBEic2e
zbf4AX*%NBEPj0IpAd>F(oCJAL9$ULDdPuHol%
zNuM)BO<7aYJcc5QBtNb80MqxMvhn<#rSE+OCMaMGn&*w`2ENxOT&mRp_Y88sB{Ao>
z+kSarkxzYoD9eIsW@RV}eikRiFsl&X&g7`3ye^F0aMeZD9PzT>u2O8tQ51?y@@&#)
zl&^s&mM{y-!`AOBe|f}@C&d0%hIynlDk*J<7R$(sWlTyciIh7CrNa@moORZqXP4aH
zD|*W$B2hbznz^V!E=#pA;!VpOc1`)RT0`yXw{F;Qn~tsCCWsVr|CHd!SY}j{f%WHz
zWVj^!w)M%6+;7Al&ka4vBR@%EMBEk)Ur-ClR9k0=B}G8_O+P7qs9STuNzFFho_~Sy
zZ`^DBzaKx>vouqT7WJ}*5fjfQ>JBMy7JeCXvf2)}JL1msH@kXU&*>y{%U!W7;w}s)
zeC!!CSmfbV1}ORJ?CZ=ipR6%dI=>NUk+Nt)3D1sMHCrt-X8~y*8p6}-9l9<%zuA4K
zt>65+$Mzt%CJh|>pxmuc%u+1(D&@f$_IFvqv=Pm9#f`~bGgE{GQ#caPM``Xh$HP&xKKpXzz5VQ_L?)GR
zHByqppIihfh1ddQeL7E+bR2j2C8OW__MI(!TrPrG5Rr=i&U2^ZG~gCei7b{HyfqiW
zyN_M<)mbZgd~b$o4>tuq$CB%Vor)CS5Cvs{zpjYg+R%*q=De{J1r
zAu;xTH~fCjKX1Z_?Ndt{0>Poa
z3Asb3$+eirg>aZ9IcW6DBhFaetI2TBh=ihwoxqebnVdnUl#NAtV{^yBHGA`xgExHq
zQQv_nErG#}C?WE*vM8cqkb@#Bq2dgj+WSSbhF-JAyYG6`qR5&0Qo1WA-V+g;>7LAC
z7^SgMn%19n(@lHMyW*`2d?zqVLQzJIvgF*Mr0NPnHL_*W;-zp4?spx3;IhxZ@;8T0
z&um1fkZF{HahdpFq%#5Aw)dQ0JN%5#bcEZj{VpvoJ2S>*=jH^|%|~{%h!aL`b$$
z90ZPxJb{+eTS^Tmi%OGhA8!8Dec&g@O*_D=CuGzGqiSWz`Le8#7(ACKRyZWfO@ZpE
z*MGh7y?HPF?Dc#LWH31I+)%SM6x9Dx1$nWk<{VPSp?d1U`_uK-_{1?7L?Okf;YDRa
z)i8;3$;dNUB0%z^xWRu3;mn
z8>q`TrS6t-3hb9260LGTk5*3I60Zj*7m+yl?W;+dREz-PUSEw#CV1Jw#@t_
zYcsXTxi`-|-e)OF2QgkyE>nj+$V${6h@Tm*GJ=|m%fp9mF!X?1BHtxW4C!U4R89s|
z!HFypcc_Uhac83L1GIdx#p}ac)^PmTCB?4EI+YQ;43Et-ERd)x6{dx@EFtP%gb=cR9NrbjQIn%PVg6Je;Y8=g1mi5)0yc@s=$+oG}Sd;Fe>z$MM2fhu`zt
zzIXZklst-X{kRrEm}Ej_!$MXVPE-{zD^dIT(>5AAxnSaLvn(kCHx_N
zTuFVDP|46UpLCy|f7gHYMLlO47mkq{<^|OTxxJr>3ILwUROyhUkM*>DnNLpaw$3iT
ze;AYj%krS8*qL%BUgXs;OUnBcT$8BxvQL=%c(#n2N|$LaR0WmED*cp-84qU3e`|`!
z>d+~Mthx4XGnXw+YURcxds|HR!k#(Nm>I51WFu12q0D#NI%^N>b=?=6Mt%nzxfu+R
zmzUeUK{aicxHt(J4v`f*1&U2pUhMRBTXymND47~YJ=Eq@8j@5`K+0Vz#8e%}Fq7NLaCLt?*k9G}r9Mh%|C0xt}9!f8urpb8y_;IwX2Urp1SQ>
zzztCDN*h+QC}iPMOVpNb*0%JK^9CR6CnM6@3{k&92^)4eVNr#ln2$;LXUrh#+349b
z^0ogw$>Y94T}DXCQ9*ljl}ag!Ts^gCIOnK!fA0}NWg2F1xp>R$t`+RL
zbMrhjDj{PQN!se2$L0G!z5D^2w(6&7xF}=}hH|fp9F&MZ4NYc4dNo_&x}GbomR3+eD>=Jj6s`dj?_Led74YlQes@b2U>qb3SIG(#Sd
z#Cgr6(ei5Z>156p9ubu21a%5msu5V=yNNv@Lvf}l*i_ocA-ERpc*N+N`g>kSnQ2mV
zH7v7uF0VoXJmfjpK{Bc*k@
z&6oopIs2QZT3WdyL`95iSYQj4aub=<+A3f#idkhHD{qp&tTpnTacyEs`|oSqVpC6D
z?4*x9(uo*P!Ay^+#Wd&sG78y3;+7S>YO2PHT(!!!zmJ~yq!klLp&7;mq6o+ygMv4w
z+s-up!cf)Q1YNh9dCM~o_x0+lL1<$|y-@PAA&Eo=%pOyb;2sw_N7}XZzOeRbM|?Kr
zAiw2@j3Q@)IAs+;RvmaNRBb_Aus07+TI-D-BC_$rvUmNAUPq-s#Xyxt_jx1&2vxU$=YeSF0c
z=~Te8p?amasg%muwJhM)5^6UGwM89u`33QM{rmZCQ<;d0=00HmP(>v%W@Q7loJDdU
zOX=|dW4`YrDIFxjZQs99T)MfRauV_ZGo{!S@7fHlxZs+Cy`q5suIAj_EFJb_tPZBbGWCis&I8ead&dLZ@UvtlPUG~d&_kC^U
zi+x;Hh;N*tu=R)-SMjC_Hrv?ehxxl%_KVLKdyhVR?KX8~`&s2Lzg>G>kH2^M2QM)`
z28I_>1(*WcSx}@6Sc=UI6+mh}hn81Q8udid)y2v@)Eq={Eu9K430)zZ2?FJiVysS_
z8ue;deA(@camp+67Lh_l*U*+*Eio~>0eR4rDRh)c>AAQ!dQuGdspAHIlMBgaNf}zM
zs>hM8@V)dqqD&HelgzP^bl!g0O<&G%om)7S0)aSgsFHaU1&s`o-@qV928mSCG2|ci
z^Q&EZPZ{iau@r9@GChLYVnJ1-kOb_cYLi*6(!9>2Mt;$I%aIe^yfV_b6O@sym0ly*
zVN$)hJc3NL2jga3u&#rrk+3Jy*4>O`hllHUH`ySF7uN|9UwEK0~D-o4Dq6*YR1)$LMq<4
zP2^kq-TJp1pV`~b^%P+W@bk7(4&@#_P7l8;3Ddx4X;R}Hx;$~t30IH!YOvo=F{muz
zqa>Nd1xv3)hZYWj$|*&NlBvEaI}hl);>-v9G!R!jtv1v&`5dBz`5^)1IwLJd5_#q8
zoE;^8-bxy!p7x2mob$mf}}$%^r)
z>dzy+&$(j_2W1>0XtA+D(rxz+o|z#@BoV}lIw3JDF?jcwYHFm#kXc&$sIJX>=e)A*
z5uH5lD~A6f^CU@pMTF~;QshBqC8_1$bR5&#svC3~zhut=zW1e3J0OO`PjQ=oTm>bQL8q>Fp(a_V!wmx3r2QL;AYTrVJ#JeOQ3keb*MS(J-kH;*3M>GbEn
z_L~bOE(&4_Dm&&I+}Y={FF}M7AIep^>ZvnV8g%=<53bAtK=l$-1idSv5U1|NJ=oBm<@j7i5obonkPPd?DIGf5Z^zMQm#e^SWPNCYMwo0vNi
zq)e%;_r0@s+~tbpyq}MhVj5aV&S7=M7DOyDmGDr5Q6sLNaV$6C%lT8sd!_Os$ZCKo
zu_7ULbIHAq5TBy74|2~qG5CW+(j7;S^}KTdZX!oKoHoQHw?b+y32K9DP^9UsPkzXc
z$E^A6^xu58oWK;UZbSt?i!7H(npT2<4+(Ld`2q-nJgji476>Kx$9r1ABH{(tcd!%>hb
zszL-AIX~IekK?GyS283IL0EGvw5;&TmYb~c_jUaqy(x1-98^`q@*8HPH>WIJh}=1k
zYD7?%3*^Av*9bQM2PZ~cz{RVWNcaeMIaP!pMPY8ZJD$6fZ!?w73W}t_1f{9~BQUFs
zxMgl5AQQETtZ!w@RX^M?{ps%3M{_Eem#RUHZfaO7vd3sL_)rrB38LGSyzjCbCQm;5
zPo5)4k^YJLLIHPFGfo_Rb$34}ili=3zN%^}O$e>YcrKbHai-JI
z%@Buub7mS$P4z*9hwv+RJoFr*eJ6&ZtKS=3MU?zmpJEq{B+R~$AZy9t7b
z;_L?BmAPr7Ft~7Kl!a+oeZ#K9mMPwPdCB=ctBe9V70O(aGmZUT67rPDA
zJ$WkFB}VBQsEi_jw*Fmzxa*+h`d|KLn~lQuSs;d9F}kA|x1R6Za=1>iBomYO8{ah}
zOG}mo3_~`_RqaLlKDk-g`N#qOF2kKue>pc~7Yq=RalfdSjTcxbUb8w&nf1WU&rF)Q
ziboN^s|1=FgB-aV{5UpB8kE+tT*xULGVL#OX5De}rdPGrUsAz&Hee)?V@x6tCXg0U
zUKf-Gsr6H?*`U|F(_8tYR1!z5E7?oIT~6v5qAGP_kcV+eyY7ly-~G2kFLbpYb<*I`
zMMI}?Ui0Z8aS>d^3yIr}l{@(vHyqh-*&nQDY3AND%mQ|m5f8xAPzAYXgP5>I$7bAh
z@fF7oIAX`eyazz;m6mig>=99JDAV*CDhpAX!VS3lwZu|WroJ+1V4Jrr+I`E1_P_qL
z3m1(%E`{HZsa=H!Kt;&uEm;XnCdoJ;T{rdOBX1vIS5De=d;SG1@yJUa{Ne8BeSgEU
zqn=Rqp4k^tl{BX`k~A9mFm9RK4jyvW>Wl9-yk{#rQxTKvLsCpm6cOVx@_7_rDZApO
zaj|l(-h-zfwEcNriBch(BZ!c4uOejwi{kA?gv2Nb^34CPGY6l2_g@=p`)ag;pWr7E
z)eE;lT&2NNaJ*70ftOZW@8B~p>vrl(em9U}Cj#+@;v1|+4K8Fx&d)4Qi_maawR&pi
z$%hT-bWY;+D^uih1RL0-s@fu|%4Uq_xM3P8Y0Z$|_26xu_-d28-u5$kq#_X+HFKgd
zi8V<=;t5O)ACBJ^yBWtrU;a70x#z)cDyjB&+gIBCw^b${>agEPZjqS;xKNtRC!{^%
zqILthl*p8Ur+1i&+nSvx&3ZHTy0;-riV0;1mji!Auy_$RLej{i4hXeF1g)Wmz5nxT
zdwO(47+VSxBN~y!mnc)xAe5PrFpfNwbvL!kf!%ic;Ip4wHwwuviKr!uip#X(x?=hv
z@t%u34D(u{tYzNHe?R%96IW@o>EAvB&j*XQeEaj05Bb_W%~XUJtXPr9G3u{`=ynrw
z%|)VicK!JcI{xv9r?z^;?^a}4PIF})Lxd#avMvZTD@#OPB-w6mexO|awjDRw-|tG}
zHPhKz)`c-aZ7DoWL*qk`o8yn&9!J*mhF`kq)%@liN)d8ZhkG^u|CQrB>pCl3piO8d3!TFcr7Oh}O3ZqZSac&&~`HcA&od8iluD`d$cT+sW
zmClQp>mEU++ALrj8V)?P%A(SgCUrY>*B$lZD_?IhuoZnIQbAS$p1dFvB3oB4NgUI+E*9N-E8|#9{WvEVL0nbfH5wp^vWT1PU2)*ymp*U
z2M_4b$ObOiItvJy?UUhyxeZkcszxm0kRSk0yVKZzW{1NLI_U5IeU-Q(0q2#9@-;{(
zQx3FE!oC+0Fca0EWj>XEUFp47TQ|p%n&5t@fKQRktm;UMLRpKtC(Rr?lR2<>^PbZu
zx9;5__rzU{N=tS@`gyjsBfMryCCtnzp}c;>L)TqD{9Dh>f*(LSc=8w!o65M1Bont7
z_K9jlx>@$wH(xUB(zjOjcNyPYi%CD3l1EyK3~n;B
zW#~}c=dQlOPj{?8->b?hU0O2SSKT>AbMdi05@m?=+*m?bCmNIL#-vcon4H?I^m}b{zJBMlyU+W;Zy~{V72Gkcl%Y`U
z)E31tkRef|ayRAL71sXtg01iL*tw7t*f>5*lnzo*+!<{t2#D+}mnv{I>?U_?uy~`>
zrLF4WIg3?X-YQ#G)RaUaD^c?1LX?ygs(UGWJv3;!ulH-^`iPSd*DxUBTX3%};a~~{
zVup{hB6h6W-^_aDgkjCCJZD!qSFGM?Dmlk*ME1#`Im2TZ!0pT
zG?bsfd*V!$3MwQ*O=U>hr6`Hr*5hgNjp<)sJj8d2f+VCzL?~(kkSEZbuE_
zXU6EBpSJ$4RC5=rU`t=HIf5XW!u>GMFY&t^zr_iM_do8$56@}kCQk$QYqE$gn3#u*
z8fT@IWhzUKnCocy+*?;}y4B3-erq4U8%1IxQbchk)OjNsE0=K)r8+8&n@dl;r`uut{etM&*qMQ)gpo!t)`?ADVBXgtzNa8SDdvDY|I_aFyvn`S^
z1Fqdxth!uy%xqLi=jAEYrE{k#cjeoEJM+t??-S#dknFU9Vw=5&gnh@Hi*5-b1fp-~
zm>u{0aPebMR`@N10EG#zi48(xOpp&4X3j9$fStucJ2k)IkAM52U1=$gKtysbIK3&U
z>5X)eIMa+gMrD!fOs1~iv&xSb&iU%Y0e)|+&>`J*QEm6xYQik39Z)7j;NctAotqav
zUh(`do_D+g@XIPKP&h;g!DQn`o>Fnur0^%PAy;?pM_VTBymRB}q5gLn9Z=7V+i1+_
zExm8juqsEvXQCi?Oq`E@uzImy&wISaW??0B8l*rR{l*fph=P86o}I0dl#&OT+GAsQ#t1=R_pVP#knM~4_~$^M&jLpZD>^N5Ybl>I+>
z-6QBT%XOnhs1aTTwPGvBuhJwfEtyu_l;e%R{&@TE);QO5GX$~ZW&qMxvhbG?of>y&
z1fnnL9bLw8`KoKKch~HX{l;FV;W6??P;mBGaguRkJ*FyJnP}oC>c~8Lz20Mgf2-f4
z%@G7(3_KL3q?|#(9|k$6%_Svz>yuyl$%*HWn6|q|!BCfr{J05Gw*_xySP*{{*dQg1
zjbm9jVoK+IR(P$Se+t)*yf}zmg~REjY)s=QqD))iI9o?sU+@NBAv-(Bf5+l9ZZqBBW|V#9oEbLKdYg9D78^
zo$tMJlUFm37mFjf#DYqV#Bhmfn=>GV5_RR_Ngb{#{&>5w=J^{udtVur8HIJM<;rx*
zN+%sDKok}a`@>7wKDe<6~;ud!4#(~QZ(PUL{b^239fYgme1aC=2tI@$-Yv7
zS;JHtQB-Z;##yag0Y?`|I7L*r_3t`#_^VItwazboh7h7GCt{Qtxd@rfG6<@aNi6Bb
z!uoyPTbwiX!fzZS5u$RO=9I0W$X1*qhe!o=cJKv-D!-;O#XI>{wH=0+SI=7=di~dHtM4*
zvNwIVGDZy<6ZXR1t>&(O990@h$T8CpmQ~~6CSN{ciytrf+_S>NeJRqpc_m=
zbIN^h6;T<6Z<#YAqAHNTMwu}Z@6%03H~DDFBgaa=If_J~Kmn^cwiH$WoD*tF!sKOQ
zBjGCMb-!8XSZ93Be^QOyrp^NY^d3h0?0x-&ZLXS?%$`e%?@7e
zIpLC}By(J)$y0IU3j_-*B+>xoS^P&nd|daV|Fo>f&kBiH$B{C3TT^!EBQ7(cWQJj9
zapAnpOEYeqzx8?>dnQh}Yei+vFk-b=5=A2u$^s*wq^7&WA6<7-#~J08J9t!kNS=8gq3Mbvx@M|1$=AjbaHn4>Fe1~c%?^Nlbk*(A@xjI
zZDwaAl@t~ym1?iRJa7H)-ygTF@l^nO&q)PZhcl7I%nz}-|;QVh?dR)FK-HKy;3#89MwaZ)9KXrYwDXnuk_GUy?v)G
zPZX+=2K5yhf*)u|LM`)<^Lqi4lK;F_9EF7~4SDM$au{g3j7%%Obd>W^Y^BRZuY2vR
zUN?1e45K+NZb1*ANw*ZI2$%`=x$>xh=aq0CZYnip{~4c+ow9}Z*rhF^oXp>3?jiH4
z(OM9}XrfZnIGnO{H2b*?K7Pk@LZ`}VLX{~39!orsXdDR)EGxALRphYM;>yMrgX6V)
zkCSTcID@JhC3k6qT89mMK7Lk|M`dmEEgwGI_x9aaxV}}zIz`n+-AnQ`lR1?OTNO2c7#anTF
zb+3*bVK%(e)p{_qm@*V32Ot}qCEAfRzHoG?O%*cd+KZld)EkX$^tr9`3eLJos$cW{
zP=m>k*EA($4RuG|@ojnWg)@%qcK;u}5<;FAX+Y6hGGkeG1PCBiNN_?`M3L8P+TtAX
z-g(;$_5Kh=2D}4OR?crLGCh{h_?9L?eXa_J3*LFp4)V8OhWSn#>Kk3PqnW{G+#y9?
z*no>tR6N70tUqhQ20f;2dftIPbFeUa6QL$5sG-D-B9bq{8FD^KF2;HzcG^q3Uif<7
zi5??q;j@{%W+trn7m2@spSK1@ND*om9rl<#Ke}Mt9j$Yi*cgjS$P`tq6Wq#@RV&vT
zSWcKZe|YlPWjl&n{pJm6!9wzdmm~`lsEIUe1LbvuvJ~Z%<5~G;mlY=U>3w0FUSRvv
zw&RD6`f&Z;8+sL*2>C0jf5p}wneqr{C8b<0@R{1=PMzSAx!XVg_!_5s9wWq#l+AT&
z-66^nnFxW
z7_-99k6!VH?>p)!B~}*~ng~Sp9H@I4lM*~;*mazL$6xyJrJ
zFj*wI+zBTsk$M?7v24?~v0U7i0;vL>H8Wj~%qZp|l*HRpp;P4=u*>^voWIjH-ZoHI
zlA|#;f;k&vZD#Q1a7~mDd5pZhe(L%^?0n#=A6(-*qdFo00ZAGTJx(ZJOWeKYzHX=j
zBwzKdJoMDVyN{VR)nnl)1+Q^vm2D_uOxSiSQ-ibyMKHozb%ta5|In>-{!S}HK$PaB
za-=M;$a7A>IM9j$((S^JM-K1&)B4$>&m8LOuN3|k$qcf@)M0hGhh($B;C91Xmi0}!
zVv(WqzrWCPcj1&I7t>>6m8wo4%sIua48s%w#|YP1kzqh{ezE>roASBo%v{`Pck~~-vj*a?T7^iT)&O?(n+@{yJ
z|4>9kZW2*(l)N}p5|65d|ENfieNa%O-W(nK-L<#eJIz=#-_T%M}^kSfJ>1+#b?8
zcMTtNnn#P^qL2YGk1g3*kRK*g*+}yePek~|HO8dtB3D1W-26Q!d8{rfnj|4#IN2lc
z%IU02!X=~)Q8JgVy4mcG_}8ya^`0$NsBValAbJjQHQ_E-K!|I=S62A>?YNf@9CFBc
z7khk!Br=Q`5u#v_eKrz-k4APCQLs(>o^1QW9Pf*hcrYAbhROOo8+LO9NeOE$WG*W*Tw^0}x~8Mg?K
z;t(&Ea<`Q*kV0l$WWCL66%`ZGGbHep2QUTo24w>WuT_*5s+9WwfKSJ@3<=T`3DI+rCJ(x*7I8{#
zjilB{&BJ%+_kVup+LOILB=W+7qJberFF5h3T1MPsBKsBj*6J;v!v;Q_p18GV)=$%j
zvqz}
z4!q@^&wu#o6psolLYcx2D@~mW(UydG%Nh~Gz&uP*Ge|Xmx$4``-#=oq@4?1e+K3W2
zqNrI3Gq{Qd3XRgR-LGr@v#v*+e82<8bU45>1SF_85w)Zsz`EdOH|OmZsXQDCZjsya
z>9Nf4`P=zUU=HKP3qoz4Q(3wouXb4NtHLiB!}_ScUsE6aq|-X7=dU>DrDqTCJlCVlV5TZ?8KyOosO9coiy2=({e?e6BPhv09bk6asR^D{1j;rj
zq_rZb8QT5}+7Yq0FsQOEOag{a{qQ0uD5?#ygM5)e|wL2PJ;>*8R<$(
znYiEx;j9Sp>tZ(eUFI<7kX5(1e%#~!sW_1+vk@yfIVXKLd^mogB@?Ykv((MN_x`QZ
z1CMoH(nnY=D|mELF62$D{UZA1fou@5%euH`ix!v#karmoeJ)?6>%es$-u#(
zN)m;61J!kmq?C&Tj)CLt)vkSJ?mAv~C5>%{&{LM2WN`&IO9k@zjP9p2Lb_ea3yK~$
zzIm*xiE?^16D7+zAGLj)(Pb>M8i<0e1ubmhs@{3b`CGhWDuJ-t{IT*u(8
z4oc15VUanOg*|`VXMVpvC$;)sl*feG7I;7qDwc6)3g53JJwTYbJ)}E7eQ4KrhxYZe
zn=od1hB`%6EUhv3TF54c3R~)cVBG4d`=@`>9J=q79toQVDdCY?Gc&KYx2q`P2O`82O81ccwBywH?U5DLMPtBQiOQ6&<25=SE^(
z1&sLVn?Fwe)vFUw7M+tv61>KwkWH!S6TxaTe2z3}9bq3l@}$@A==``xJ4WzDjF2gN
zl_~eRpi$yX;R|BlP8DC=3j<VJpUE(u4|1Mxz$x#*-{v
zzH!oS$6mVD!AH5z(m`AjrxRAn?Ik;;>}P3|S0=T@!nxBpe{4Lb_m{0o;5G@#eUfq~
z1DUmpUocDDB4w=W=`C~4edAv5HPWL9$SedCQi3Q>4jt*y8WFOI0-u_Aev7?MduyMs
zeMKL{s1Z_29wP1`1sv%WWr@F}Ov)@1)@zjA{^`8Oum9wdR^G%S;$%N3b!V(lgdtYO
z-02WpaLKe|X>IBK(BMg{{^pU(QIHYD8kH4~Y^C;$0-~TqiiFpWT%EGp7lQ|#G^~|@
zKH?yr^d8j?4V8Q{fxko|yyr2`s6LI0XU{wJu*+ShmuSRtmXrt*0k?0dI*#Z7V}|Vu
zWU5XHVeeU|4Eb!}SkDG$4g8U8AcBzWlIb;fix5sqL4}C0-VbhhW~$wG@AuaAC^KBg
z1a?@)Y(0vC8|P%>PIC&QYlFvX{Lv;WZnE!Q(_1$ztqDnP&2CK`GLK3kl=T58dTA7z
zr2bulEhk{l@)x<)*1k4JlEU#{
zNLJjK#Iwj~@PA4P+h8xCW)|ss?dUs#Uypp=v(B(%kg|Kt?l)PlIkRgZC&zbylMI}y
z$w4RI+wJSWFV|*=Mz^~|v-WjIel~3WPyXaHiHZ(YKvr?P#$+U7i6oO4@g^;`>k=P%
z(3$sa^@pE*ei)V#)i^>b`OlJSFO%~x#7SHtqa2@cmt~fF@`PSv?(=h^vakg&R3;f=
z6Ygau)UOL<#W7ntX5t+dIjGnB-;HaHdJ0J_F?a0gCCu3<(Jc|mjLO5*Ybke}QqCE^
z>GB@G!6suhT`DRMKwL4N&q=s%;t=1qe(LtGAKG)Bi)OZ}JV}`g?xvEz(~wu2plO>Y
zsYc-wI1Ym@XWshdOY01r&<1JVK34a;(hj_#yX)Ja#tN+#CGN7QxD2VX3um7RVpBc+7yl#}qpt+X|^osN>FL`iYfVw!?q^`5*t!
z0X=rwX}5jgT|37LF$u-$HhudID2_j-$orZB#WsD9Io8+#jbr-{DEbZPYmP2D+W^La
zAb{i?VIB2>Mowr{VJ!Xy(v;4}_O(YHUHq5(uiSmtO4fHh`p2Euq394&t`aFfVtI!E
z^=BA%*f98a-v49z+CHW@`sAW-zy3$(|NP(KKP$`sdGCMl;$x;QQvc7xFX?ptvfds#
zhnH|Jkx5I=F#%_mD|p}@Y07apZ#8&xZN)EW6MWhEjjZ32WNZM
z3}n+8dlEV$8ag5yNUj@EY=a~$LgaRJ?LP0*v)8|W-_KmM#~;RIz>yqk#(8Qv&&-i_
z2@y*f=(5IYwOlv;0kigLe)13FMg3DCFJ_mEW1%##9HnN35vojrdQRK&NYBwP?!Dc!
ztxpvZN8+eJ*h8Ya6=C+c1}M%WqB!ba%d;IWx#si%`}iqnN`k2r8IMAxMLDbrL!F_z
zjgd?hxvOK=>-6393wpX~yhT1AMuHq7l_r+XP?|B5IG@f3q`1t=h
zi}_Fd|4;mH8~`!>h~gaO{mJck)cIPB=
zPV&TNp(PhztzFVmeOr%@Ayq|5tQ%PoLSo&>xgF(M!W{$|yS?(UyDsoloKfBo4$B#54qnDbfUXkVzA1a-2pKmRNA;|SeghCQCLs5Zc4pNj(i}0bj3p`aMDk}>cH4q9VkHS97D+CJ!u4k-
zpR~YJf&+1`;+lZEG?w}n!U{J1%3L8CGH%Q3;kOt3tegzg)SXvV-??I@O_B6TEAmj<
zAdBjr&eg*fcnWD(nTN4#sL-$rZ*;@(rP+d-UwM-F{?R!T7I;eHi>HPtCR=UU<5Sa^
z(oT6nlIf@joW}iKqZa&zsm_#2$sdB>RqcnGN(K?-2d6Eu3F`ONYw!Y3*`hEqBa|s2
z=Cam+gE5yf%}PZ{BZmmdx-9Tii9h3rw4q~SE-MvCMLU$lm}WVCU)^=8&9K8l?s%-W
z;8UT5B~?-&n)3_6x2y;mQUyDeA-VYKt%fz**oH0xft(fDZo%Fn5q8{bsx&HX5|r+y
zT-wGCWssY|a*{#KSxI*KLK}kfgpPs)$5Wq1j|ER7v7GA{#K-Wa1eTLRSF`WLJK0i4Tn;(HBN*3_-hwD`MN)A
z+THa0YQfJ+R8DbZGO8&~tcjE{lF!4E11s~`vC@s1v%pjEU&@-uG-MtG4Q?j0KO3-J
ztHX@y6>cB$g=ZFg>R)6kX!}|4Yk9Y;?Y`J`iH8(6~%-Ms4IrxyIIAW})m
z#-}1IKjEgFrS?`#Hl2V}eYG79U3!71Oh##_g5pm&2*IzJaf1S9E@Y+)m4>x#JhS0~
z-bTVdm&D*n!Kn#%dMa%^D#H~)VnU~*_sWh7e#1}|)$TBNGa4d^aJ3ZIBTb5rDFf=j
z)EK_y7rZH{5=L+dC)c!I9X2wqH&PQOF)&i&@Y6H4XcHa&H5JG%TP|oD7AH|yMU7um
zVIVl3rS=wwt+hgAJ^z@s`+{c}s$4~=T6K^|oPg>EwTt0YrOKk%P?NUCtX#g}U6v>v
zk#y6ak+*@LWeZZJAyq1EsjPd;&wRAtQ<}0~mP5WUB?6}+5UhZ*Aq-k6k^dj;&>CCj
zahx=irAP&VLMh4W%UlLjl}yX1KEwOIZgVS5f$(9;RKTqUsst6Jo6}aSJVQZj>)(|v
zXuT!P0W~?ClHh6J__B(a(P(&V5+k^c%^3^E6x7AINfB+{xQSZAwP>q2Y)7#5D5%*l
zyQltF_wN7a^#8>_*Z<*v>i>UB{jdLP{VzJFG1-p(Q~v*_{{QFtzfWh85+z)e)Me(D
zRV3q(%~V;qw)i@jJ4*%ycE0S+O-B*Q2HrQj|DBt|4?9RF!=5z2gQ98+4Xu+fNBR
zAgrh+Vx@u$!E06&MU3JP1$LF4G_O5*qci#}v-!g5d^h{{FSh@~gKv7}U5%<#Wo!zr8P`t@TJfyTUmpDF!tI1L?JC<%yy);>Jc}jVacr^%`Mt^H!E6!-
zsYnqUnj+Hm?o{)X?^oG$_REWVOovHLAq9mEh=8sXlJJF#ERr%#2+*r4!{+$p_&t-K
z&h@MYX>O2+HwsIRhlFztjwx)GWL8s_J+CVH=4`#((u-cu+bde7B26uIkxHUm4YEl%
zkVX-dMVJRgme=!|=8IRZ@#JaZxrO7}Za(tF2B%!}@)n-?j(W|83eMyK3=39ktbKzL
z))nPRQ1AUTXP&#q957|K9d7FKSI^L$M>fF=l9Wh|11?+fNJ^zjYW0v@
zvU+O7NB69H^Ug~y94fh)cY1Q)a7k1h_`
z)T^uJfl?uA@>GT7IJV@ZCT`7e*E0x8QSWy)&+50~CWmaWl1D(pb5Px&prRF7S7Gke
z;7mqb7K&YOsQK_Oi>US4y;mdif0%4$yaJhC#}bq9a#(gW5a|
zZvN-Q`z1B!U~|Ihr!RKE_J8wyXDS73%97ot=BMf4yKW0kks{U{GT6NBguY56a;n*IVy?*J~zuRw1`TC#U
zE5XT=XbUfvmAq1oLUSWm#5n#6h1WcE9-~B}+@eR~reU3*iAmf?g}SAw#P8`ZPY7b;5y{t@NnxHYTW$
zi)t%|78O>S3Mt&aqR?V!B8LZGWs^&P_w-WN`Z=#P5v6Rj(p;3~UU*9Rc_b7%lm-5p
znooJ1>!z)6;>pkY&50t33>P%WDIMcKBa&ai&xbNnm5@jkznW(+D?5%~;b9*gBtDFK
zY9+TBa!HFyxm=!;14zJ^)=%BF)s~xGzu`K5TL@(`6=vg#(J#dZrc_ml;)vo62?5^K
zQx9D>-y!v^ckljpU;8)WU~
z8|NM~Y3?6?>$`A#W6i-EZ~JiHZd2OiHti~%v~1S({24F5>a}LGw2X1S4a)~az?+iG
z1gAme7YTn}?~*o;9XjFR#h>>WQnECZq9VS<$>%Y34h)qGlPHno-Kcr*q((j~XAST+{P`W6q@v6;p9{HkA-%%a>hMWy?$0DkAa{5AYQ-sw<
zp^%oztjP0vbG>=tCqMjc+fST+17#2k!m~O2Xi!Fny0~~$s=`JH?xNl>XokbjeCdOJ
zuP&ToT=T81u3vrsmi4@zXdwgYh-f524Z$QaO#~Uflc=B^gRM7EcbIwWjekA;fhk_4
zp6ZkoEJp%?_(dj0%1nege2!*Eux90HUUA(gPe1vDZL_!9u2y<;?9eG|-oO9K3&&vB
zJg&KPa>CBL`I$|OjF?SHsvO1zHJl0;(q@O2PR93Z3jelbBJn89Ff5;L&_19S-sKNy!q_cTKYY5
zuHS;P97QQg(QrEpF2^J!NGr)nPr;p<9jf_!$3LIG^&iH2MUXNK6LPjyYZyvW&(
z$Q+kXbGt9U81=zjmoFS&d2?J}JLcjE2P_A3SvCU7ws4
z`1b{qB2fcg758Z)JkMy(=^&x_VPb2W|GCG@d~vY*yh7
zqW~*{dbgwbhYr_&KVe&e7y%oMArnY7l`6^831?u++5_zS-lp=omGAVL3Z!X84Js{Tr7bEg
zXA}iF?l=-RA!V@b>+*AA%6-z
z%lW^mmEOF0pC`7Ow)|nO>Z(*3LFNFLi_an_2T3zYGgF`lNv)`V*WLH-_>KMkF8{j(
z(h+{8oGKmMxike5?L0OnCFiW0do|BKZ`fa#pV+Fphq!~kxS_c7k8Bw}P6k{%4ueWZ
zCaw2zo86z=cip~kEz!mUw9CBG{HEvi53Y9q8=lQe<1Qe4r_>OP6M^U9!7E-bi{Ql-
z?CPn%U-qUwe7xJZvN+<1L|&vt!FeONCRA`isz#n3m8zmX!}H&nbLPQcd*(|eLR>Lq
zDS~HMBn*?N+N3HCIX3Zi>*{8yv0Fa;cF)z@=;yV|%-6hrhXckht1j|cCH_W2Nn*h*
z-U62d#Z5$|WFoZSxm+uPfrvsmf>!4ibu%dR6X_Q<1XsH%CI*VPK%|v!-PlIJ^T98
z7tFEacK3c-I=nf0*K6jT^R!5aj63Dm|R6LH^}fP<`E5)RYNtefP-0C?I<3dypG-TDrLpLg;0Jl^&#(hxE+q{3&GY{TA=`&yXmN6?5R`fJR7)Z+X
zTolTvQp=E-kLsz5COvh=c;)pQvWSb}DdH-vm+HqbOGEW6b`VP&)x5~fAse6Y>D7N)
zNS@v1D?<)n`RYp+@f<}tk_Y%R?a%QV)oF-~j@YnD=OC|?3kkQ6Oss4a8+TLQI`PZz
zN8T#@{X#k%MG=xT!kkLQ&GjU2NS!m;OXF147IoX;JC@&RkssT5?5N#u_?Ky2x83h5
z_Y|_FtRT24EE1}!upgBXsgJx{Bu12uo3r`mrf8_^qWsKk@Cm7EW8SIc|$Bew=>q;vVf0B|6M`D@l$_3eiekm8`=^{)9~G
zn6krbACF&q(OxevoPK$;>$;bXd#mNfh2t98;oZsWt@G)rpDdh;Ky%ojH&!_5WzUBc
zA#X2{Jr!h!NAd|jPabQ9YhA>7Xz<1B8ur3TAHDu%zXjR$si^pW$6z%tAAa2re>?uT
z*4}ag?^PhtCI1IIw^^K$coZHRi3^oitEWzwa_9?P&Y#ta6U|b5d-mk`zF58@0yU`5
zf!ra>biE1Pyrj$Px8Aec=3b>ko0JGAu2&QL!i{5vQXtGM@{SVeaDBgSGmEZy)=0;$
zq01yuCZN&@*+V()NXooq&jCLwkW$sG2F;U?UhSZVPjC#Zh@-^(A*nWGdo9AMxf!6a
zLIgzGrcwJ;Pdzj4k6&Na&Gm>xn3*&ch_Dn9iet;np`gB(je;Z$|ZU!YL{=$933ac6n*1g+rG%A6a_Rw6UE=_;1J;$qr|klWj<&IAp&#
zN792YUu0!gpT@}3hIiOxv-P}MCtNw%f^@4IR5HeR&-{P3l2a_bQ{U%GHA+Rc||
zY<0tG6EE?oKKM(j?nQJNobXrBSA?S?N9Ks)rdDNc4!nHr>9>A7qgCA}2vhPxR$5|4
zQy`H!1ZvkJPOSN}fehE1fjY`R?^4=k7VsGi>3bPzT@>7?h1e%h+ZW}!=gg<@pmcCI8b*nbAZ>XZT^@g
z){IZs`xM`SiQ#LjnntldPyIZ21=K0zW6t5uRqf~RF+(@JEZxG#6r@C)y(mfo#uiQy
znHqmrE`rdI=e+jVL*JkB$PSn9+NM9>E(2@xjBt}-_dR{7SBpuMwIqY#fD?6PM4k*)
zX_4Vaks`J}!%Os#?e3Z6xQcC#YA=g*Lzk5{RV2vSmQfdwT#p>y)IKVCuq^sN=QYI>
z5>B>zm_l+yhA`HQYX=q7t_5hz&
ziqg&6X59M2&bu7{qwn?<{~vpA9=FxFzYU}8Ogl2{GFLJrSFN?qb*=$jcZL)h8nz0N
zHJyZ%6p1KONk~%4TuRDNNg_ii2|F1hb7GT1gle-r$FbIV-oM}d?)QCe_kF+b^T+c(
zKEKc2`?q&j*R{^|J-^@MI~_-yv-qVR=gS?%t~Tx`2U{6Mk+&7M@}ZuMU)}p+yJniK
zRq^4U}E$2T^gIKJn>Gg%h#hU1fu7J!r^-|+W-;uKTP<-u073tKk4y9&E}
zwK{XJ||jw(EQQ+I9?UpTYbIv{>>}TxU1t|4d1ivCzfO@pIvDy
zOiHAzpkxPi-2%%lxc19aE+~C*<~I5lvXz+SyfPQ|ApW9?JpC1f4qD{<@^S4F>a;G
zy$zCQPNlP78Nr!n$PaWze?YSt4^GaqtTfSmqT7~yJpSGp`hCSwlqJZD@u_@E2VOXIeB`kBZE*}gZ)py&9lsy7
zdhpO^%#(g66(D2bbM?1eU^nF0&`5Q%hBD3F!k?yc-q2icW6Lbelzr~16|rZFGA|42BfO5LXVNc437J$}C6
z#hGSCAHY`N$~)}m3rcq8I>e6T=t-PeLeFA7cFLKP2e#3QTS(ec#{v{r2|1MERH@Zx
zn*Po7+DH>Dy^>Vi;3BDCkSiTYpX2Xdpml`G{_uL&z0p$l
z=xrn!4wW9Vz^3&wYeOzsvg{P-fLzf9cVNXfEl>I6-sA4Bf+|(Dr?Fw@rHR}AP!siJ
z=J{+xCuD_7sW%@JxVcCWkxT(A7M~jVw_bnyZH=Cf!b96YM3PceWTR9p+2Ax%<;yHc
z0_hhjJ>~Zn$POZi&aU#19N$hwbo6c_GryNWX`zjW?i!^gKBQ8P`I@-+V`xT8MZweb;^b?j7<-AN?yF~W*n;9l5a
z%mRN*kwl&Aoz;8QP2>7(HghR4;A7qf$Y)^qTRDJ$d^xg{D2rl^=Qqx{a_&`kx2;lx
ztv8a_G!i&D^C_OIVDlywkQa!w#Z9^Vq`s=b&oiskqpWHX(c6!C6|eV-D%lOGutkz=vU+p=
z5V=#zo|NxWxYV(VlV8|!`E%!7^JC?_jqlqwH4+)pJ=SoM$Cuz|WS|`73+TyfJ7w}z2uY*YkJgwl}foz6h)$#{4CF&zkSE%AL%M_oMb+ino9|l6Z&mZr7a|mZWilL?Q!w6H{L&EYn79)zDj)E_Q$m;z41xqjF}J|vW+5uJeT6?G1JTh
zIZ^BZG^av&m=rD;(yYrCw;Ja_2}ttwRkm8BAnHc`Sjr`JpKVgNu*
z;z=7ZGykqtd)nbnjT5s;=;DDLRq|Ns1r}%gixQl?B=Ut@Eo{ExkbBm3-f?XMQ}1;X
zpCT$2DQW~Pq7(