{ "cells": [ { "attachments": {}, "cell_type": "markdown", "id": "55822295", "metadata": {}, "source": [ "![Finance Toolkit](https://github.com/JerBouma/FinanceToolkit/assets/46355364/198d47bd-e1b3-492d-acc4-5d9f02d1d009)\n", "\n", "**The FinanceToolkit** is an open-source toolkit in which all relevant financial ratios (100+), indicators and performance measurements are written down in the most simplistic way allowing for complete transparency of the calculation method. This allows you to not have to rely on metrics from other providers and, given a financial statement, allow for efficient manual calculations. This leads to one uniform method of calculation being applied that is available and understood by everyone." ] }, { "cell_type": "markdown", "id": "2937a8f2", "metadata": {}, "source": [ "# Installation\n", "To install the FinanceToolkit it simply requires the following:\n", "\n", "```\n", "pip install financetoolkit -U\n", "```\n", "\n", "From within Python use:\n", "\n", "```python\n", "from financetoolkit import Toolkit\n", "```\n", " \n", "To be able to get started, you need to obtain an API Key from FinancialModelingPrep. This is used to gain access to 30+ years of financial statement both annually and quarterly. Note that the Free plan is limited to 250 requests each day, 5 years of data and only features companies listed on US exchanges.\n", "\n", "___ \n", "\n", "
Obtain an API Key from FinancialModelingPrep here.
\n", "___\n", "\n", "Through the link you are able to subscribe for the free plan and also premium plans at a **15% discount**. This is an affiliate link and thus supports the project at the same time. I have chosen FinancialModelingPrep as a source as I find it to be the most transparent, reliable and at an affordable price. When you notice that data is inaccurate or have any other issue related to the data, note that I simply provide the means to access this data and I am not responsible for the accuracy of the data itself. For this, use their contact form or provide the data yourself. \n", "\n", "The current Notebook is revolved around the Ratios class. If you are interested in the other modules, you can find the related Notebooks below. **Please view the documentation here to find all the available functionality.**\n", "\n", "\n", "\n", "
\n", " Toolkit\n", " Discovery\n", " Ratios\n", " Models\n", " Options\n", " Technicals\n", " Fixed income\n", " Risk\n", " Performance\n", " Economics\n", "
" ] }, { "cell_type": "code", "execution_count": 1, "id": "11269a00", "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "\n", "from financetoolkit import Toolkit\n", "\n", "API_KEY = \"FINANCIAL_MODELING_PREP_API_KEY\"" ] }, { "attachments": {}, "cell_type": "markdown", "id": "a3f7fc24", "metadata": {}, "source": [ "**Initializing only is required once.** This is the case for any function so once you have obtained a balance sheet statement, it will be stored accordingly which means that requests to FinancialModelingPrep, the source used in these examples, are kept to a minimum. Note that in this example annual data is used but by adding `quarterly=True` to the Toolkit initialization, quarterly data can also be collected. Note that this requires a Premium subscription from FMP." ] }, { "cell_type": "code", "execution_count": 2, "id": "b3507cb1", "metadata": {}, "outputs": [], "source": [ "# Initialize the Toolkit with company tickers\n", "companies = Toolkit(\n", " [\"AAPL\", \"AMZN\", \"META\", \"WMT\"], api_key=API_KEY, start_date=\"2005-01-01\"\n", ")" ] }, { "attachments": {}, "cell_type": "markdown", "id": "af12299f", "metadata": {}, "source": [ "After initialization of `Toolkit`, you can get access to the Ratios module which includes over 50 different ratios. This can be done by calling the `ratios` property. Please view the documentation here to find all the available ratios. \n", "\n", "Within this ratios module, the distinction is made between `collect_` and `get_`. The former obtains a collection of ratios (e.g. all solvency ratios) whereas the latter obtains a specific ratio. You will note that it will collect data first, this is done only once so that the ratios can be calculated efficiently. For example, let's start with getting all ratios." ] }, { "cell_type": "code", "execution_count": 3, "id": "3c79b76d", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Obtaining financial statements: 100%|██████████| 3/3 [00:04<00:00, 1.35s/it]\n", "Obtaining historical data: 100%|██████████| 5/5 [00:00<00:00, 9.30it/s]\n" ] }, { "data": { "text/html": [ "
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2005200620072008200920102011201220132014201520162017201820192020202120222023
AAPLDays of Inventory Outstanding (DIO)NaN5.78757.09187.3147.51936.95095.1753.25544.37396.29975.81026.22479.04049.81959.09448.79039.11819.40979.6109
Days of Sales Outstanding (DSO)NaN39.277952.25836.248328.885737.171536.485235.459242.000347.782844.948250.476351.726158.178566.497155.344744.376252.037758.0504
Operating Cycle (CC)NaN45.065459.349843.562336.405144.122441.660138.714646.374254.082450.758456.701160.766567.99875.591564.13553.494361.447467.6613
Days of Accounts Payable Outstanding (DPO)NaN68.771896.246589.735986.745481.30675.477374.38974.5485.452785.572101.1074111.718116.9484115.202195.288983.168397.0504108.0033
Cash Conversion Cycle (CCC)NaN-23.7064-36.8967-46.1736-50.3404-37.1836-33.8172-35.6744-28.1658-31.3703-34.8136-44.4063-50.9515-48.9504-39.6106-31.1539-29.674-35.603-40.3419
...............................................................
WMTEV-to-EBIT9.58339.08188.91119.41478.43928.18098.19319.19319.834710.9418.022410.052414.31817.907429.03320.740719.891621.688725.0026
EV-to-EBITDA7.59817.20936.68027.22976.49416.19066.46236.88137.37738.10035.92167.12929.6849.710711.829413.782213.258513.121316.2302
EV-to-Operating-Cash-Flow10.85679.50468.599110.05678.28687.33639.06999.841210.46512.44877.52958.735210.087510.611613.910318.391912.507618.31816.7812
Tangible Asset Value38593000000.040983000000.047814000000.048537000000.050025000000.057110000000.054892000000.055514000000.061760000000.063320000000.067835000000.066916000000.063498000000.062580000000.048453000000.050479000000.058548000000.062877000000.055817000000.0
Net Current Asset Value-4397000000.0-5002000000.0-5166000000.0-10869000000.0-6441000000.0-7230000000.0-6591000000.0-7325000000.0-11878000000.0-8160000000.0-1994000000.0-4380000000.0-9239000000.0-18857000000.0-15580000000.0-15984000000.0-2578000000.0-6309000000.0-16543000000.0
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268 rows × 19 columns

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" ], "text/plain": [ " 2005 2006 \\\n", "AAPL Days of Inventory Outstanding (DIO) NaN 5.7875 \n", " Days of Sales Outstanding (DSO) NaN 39.2779 \n", " Operating Cycle (CC) NaN 45.0654 \n", " Days of Accounts Payable Outstanding (DPO) NaN 68.7718 \n", " Cash Conversion Cycle (CCC) NaN -23.7064 \n", "... ... ... \n", "WMT EV-to-EBIT 9.5833 9.0818 \n", " EV-to-EBITDA 7.5981 7.2093 \n", " EV-to-Operating-Cash-Flow 10.8567 9.5046 \n", " Tangible Asset Value 38593000000.0 40983000000.0 \n", " Net Current Asset Value -4397000000.0 -5002000000.0 \n", "\n", " 2007 2008 \\\n", "AAPL Days of Inventory Outstanding (DIO) 7.0918 7.314 \n", " Days of Sales Outstanding (DSO) 52.258 36.2483 \n", " Operating Cycle (CC) 59.3498 43.5623 \n", " Days of Accounts Payable Outstanding (DPO) 96.2465 89.7359 \n", " Cash Conversion Cycle (CCC) -36.8967 -46.1736 \n", "... ... ... \n", "WMT EV-to-EBIT 8.9111 9.4147 \n", " EV-to-EBITDA 6.6802 7.2297 \n", " EV-to-Operating-Cash-Flow 8.5991 10.0567 \n", " Tangible Asset Value 47814000000.0 48537000000.0 \n", " Net Current Asset Value -5166000000.0 -10869000000.0 \n", "\n", " 2009 2010 \\\n", "AAPL Days of Inventory Outstanding (DIO) 7.5193 6.9509 \n", " Days of Sales Outstanding (DSO) 28.8857 37.1715 \n", " Operating Cycle (CC) 36.4051 44.1224 \n", " Days of Accounts Payable Outstanding (DPO) 86.7454 81.306 \n", " Cash Conversion Cycle (CCC) -50.3404 -37.1836 \n", "... ... ... \n", "WMT EV-to-EBIT 8.4392 8.1809 \n", " EV-to-EBITDA 6.4941 6.1906 \n", " EV-to-Operating-Cash-Flow 8.2868 7.3363 \n", " Tangible Asset Value 50025000000.0 57110000000.0 \n", " Net Current Asset Value -6441000000.0 -7230000000.0 \n", "\n", " 2011 2012 \\\n", "AAPL Days of Inventory Outstanding (DIO) 5.175 3.2554 \n", " Days of Sales Outstanding (DSO) 36.4852 35.4592 \n", " Operating Cycle (CC) 41.6601 38.7146 \n", " Days of Accounts Payable Outstanding (DPO) 75.4773 74.389 \n", " Cash Conversion Cycle (CCC) -33.8172 -35.6744 \n", "... ... ... \n", "WMT EV-to-EBIT 8.1931 9.1931 \n", " EV-to-EBITDA 6.4623 6.8813 \n", " EV-to-Operating-Cash-Flow 9.0699 9.8412 \n", " Tangible Asset Value 54892000000.0 55514000000.0 \n", " Net Current Asset Value -6591000000.0 -7325000000.0 \n", "\n", " 2013 2014 \\\n", "AAPL Days of Inventory Outstanding (DIO) 4.3739 6.2997 \n", " Days of Sales Outstanding (DSO) 42.0003 47.7828 \n", " Operating Cycle (CC) 46.3742 54.0824 \n", " Days of Accounts Payable Outstanding (DPO) 74.54 85.4527 \n", " Cash Conversion Cycle (CCC) -28.1658 -31.3703 \n", "... ... ... \n", "WMT EV-to-EBIT 9.8347 10.941 \n", " EV-to-EBITDA 7.3773 8.1003 \n", " EV-to-Operating-Cash-Flow 10.465 12.4487 \n", " Tangible Asset Value 61760000000.0 63320000000.0 \n", " Net Current Asset Value -11878000000.0 -8160000000.0 \n", "\n", " 2015 2016 \\\n", "AAPL Days of Inventory Outstanding (DIO) 5.8102 6.2247 \n", " Days of Sales Outstanding (DSO) 44.9482 50.4763 \n", " Operating Cycle (CC) 50.7584 56.7011 \n", " Days of Accounts Payable Outstanding (DPO) 85.572 101.1074 \n", " Cash Conversion Cycle (CCC) -34.8136 -44.4063 \n", "... ... ... \n", "WMT EV-to-EBIT 8.0224 10.0524 \n", " EV-to-EBITDA 5.9216 7.1292 \n", " EV-to-Operating-Cash-Flow 7.5295 8.7352 \n", " Tangible Asset Value 67835000000.0 66916000000.0 \n", " Net Current Asset Value -1994000000.0 -4380000000.0 \n", "\n", " 2017 2018 \\\n", "AAPL Days of Inventory Outstanding (DIO) 9.0404 9.8195 \n", " Days of Sales Outstanding (DSO) 51.7261 58.1785 \n", " Operating Cycle (CC) 60.7665 67.998 \n", " Days of Accounts Payable Outstanding (DPO) 111.718 116.9484 \n", " Cash Conversion Cycle (CCC) -50.9515 -48.9504 \n", "... ... ... \n", "WMT EV-to-EBIT 14.318 17.9074 \n", " EV-to-EBITDA 9.684 9.7107 \n", " EV-to-Operating-Cash-Flow 10.0875 10.6116 \n", " Tangible Asset Value 63498000000.0 62580000000.0 \n", " Net Current Asset Value -9239000000.0 -18857000000.0 \n", "\n", " 2019 2020 \\\n", "AAPL Days of Inventory Outstanding (DIO) 9.0944 8.7903 \n", " Days of Sales Outstanding (DSO) 66.4971 55.3447 \n", " Operating Cycle (CC) 75.5915 64.135 \n", " Days of Accounts Payable Outstanding (DPO) 115.2021 95.2889 \n", " Cash Conversion Cycle (CCC) -39.6106 -31.1539 \n", "... ... ... \n", "WMT EV-to-EBIT 29.033 20.7407 \n", " EV-to-EBITDA 11.8294 13.7822 \n", " EV-to-Operating-Cash-Flow 13.9103 18.3919 \n", " Tangible Asset Value 48453000000.0 50479000000.0 \n", " Net Current Asset Value -15580000000.0 -15984000000.0 \n", "\n", " 2021 2022 \\\n", "AAPL Days of Inventory Outstanding (DIO) 9.1181 9.4097 \n", " Days of Sales Outstanding (DSO) 44.3762 52.0377 \n", " Operating Cycle (CC) 53.4943 61.4474 \n", " Days of Accounts Payable Outstanding (DPO) 83.1683 97.0504 \n", " Cash Conversion Cycle (CCC) -29.674 -35.603 \n", "... ... ... \n", "WMT EV-to-EBIT 19.8916 21.6887 \n", " EV-to-EBITDA 13.2585 13.1213 \n", " EV-to-Operating-Cash-Flow 12.5076 18.318 \n", " Tangible Asset Value 58548000000.0 62877000000.0 \n", " Net Current Asset Value -2578000000.0 -6309000000.0 \n", "\n", " 2023 \n", "AAPL Days of Inventory Outstanding (DIO) 9.6109 \n", " Days of Sales Outstanding (DSO) 58.0504 \n", " Operating Cycle (CC) 67.6613 \n", " Days of Accounts Payable Outstanding (DPO) 108.0033 \n", " Cash Conversion Cycle (CCC) -40.3419 \n", "... ... \n", "WMT EV-to-EBIT 25.0026 \n", " EV-to-EBITDA 16.2302 \n", " EV-to-Operating-Cash-Flow 16.7812 \n", " Tangible Asset Value 55817000000.0 \n", " Net Current Asset Value -16543000000.0 \n", "\n", "[268 rows x 19 columns]" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "companies.ratios.collect_all_ratios()" ] }, { "cell_type": "markdown", "id": "3fcf7e9a", "metadata": {}, "source": [ "Given that you might not be interested in all of them, it is possible to also call each and every single one seperately." ] }, { "cell_type": "code", "execution_count": 4, "id": "8b9fa8b4", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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date2005200620072008200920102011201220132014201520162017201820192020202120222023
AAPL0.26450.29420.30190.29890.28560.24420.24220.25160.26150.26130.26370.25560.24560.18340.15940.14430.1330.1620.1472
AMZN0.2220.4960.27880.27410.21790.23510.31161.10030.3701-2.25680.61450.37540.20230.10620.170.11830.1256-0.5417NaN
METANaNNaNNaNNaNNaN0.39880.410.89270.45530.40120.40460.18380.22630.12810.2550.12160.16740.195NaN
WMT0.3470.33430.33560.3420.34190.32350.3220.32560.31010.32870.3220.30310.30270.30420.37360.24430.33350.25440.3364
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date2005200620072008200920102011201220132014201520162017201820192020202120222023
AAPLDebt-to-Assets RatioNaNNaNNaNNaNNaNNaNNaNNaNinf0.85840.4580.2190.13940.01560.01980.08740.0236-0.0419-0.0743
Debt-to-Equity RatioNaNNaNNaNNaNNaNNaNNaNNaNinf1.30440.7070.25640.27170.23810.11750.44120.14880.1987-0.2456
Debt Service Coverage RatioNaN-0.19950.2506-0.0607-0.1081.23360.36170.1864-0.1933-0.28430.0678-0.1038-0.2316-0.003-0.00330.04020.3804-0.10660.0141
Equity MultiplierNaN2.47950.05330.05170.0474-0.1076-0.0976-0.02510.05560.1780.21190.0930.07480.15620.15980.1930.23620.17720.0106
Free Cash Flow YieldNaN-0.44250.20233.2654-0.57440.180.4320.02850.0051-0.15310.5241-0.2996-0.31380.4062-0.4784-0.2735-0.02160.6782-0.3816
Net-Debt to EBITDA RatioNaN0.2505-0.171-0.1107-0.6423-0.0785-0.5247-0.3341-1.25716.51910.48040.73330.4649-0.1884-0.2850.243-0.224-0.0108-0.127
Cash Flow Coverage RatioNaN-0.44250.20233.2654-0.57440.180.4320.02850.0051-0.15310.5241-0.2996-0.31380.4062-0.4784-0.2735-0.02160.6782-0.3816
CAPEX Coverage RatioNaN-0.65340.64180.44260.04650.0468-0.42560.07410.09320.02910.1625-0.31320.0230.17020.13680.6694-0.14970.2154-0.1158
Dividend CAPEX Coverage RatioNaN-0.65340.64180.44260.04650.0468-0.4256-0.1507-0.36110.04370.2363-0.2735-0.02870.1517-0.01610.33780.07950.1742-0.1102
AMZNDebt-to-Assets RatioNaN-0.2943-0.2865-0.7283-0.85973.31650.64221.10.09690.776-0.0541-0.15830.5833-0.1530.1472-0.06380.05370.0939-15.0499
Debt-to-Equity RatioNaN-0.5245-0.6181-0.8441-0.88183.51210.95291.5630.13711.1872-0.0886-0.25550.7349-0.33250.1147-0.1128-0.06820.1396-5.4343
Debt Service Coverage RatioNaN-0.31430.14840.0057-0.1359-0.1155-0.573-0.3851-0.0899-0.80569.46030.4492-0.25761.5614-0.08810.0942-0.0348-0.5495-54.9886
Equity MultiplierNaN52.1429-0.4402-0.426-0.2704-0.03590.12050.20290.11790.13990.076-0.08360.0028-0.0971-0.1097-0.043-0.089-0.0297-2.3694
Free Cash Flow YieldNaN0.09190.04041.0388-0.2048-0.3752-0.147-0.86522.05560.23640.67650.1754-0.58211.05360.013-0.3305-1.55131.314212.7839
Net-Debt to EBITDA RatioNaN-0.5509-4.21530.53670.0858-0.28210.2472-0.144-0.4221-0.5167-0.54260.5459-4.3337-0.74081.57790.17790.53770.1776-3.6725
Cash Flow Coverage RatioNaN0.09190.04041.0388-0.2048-0.3752-0.147-0.86522.05560.23640.67650.1754-0.58211.05360.013-0.3305-1.55131.314212.7839
CAPEX Coverage RatioNaN-0.09550.9299-0.18750.7324-0.5956-0.3963-0.48760.4394-0.12040.8576-0.0604-0.36830.484-0.0017-0.2795-0.5389-0.03194.7913
Dividend CAPEX Coverage RatioNaN-0.09550.9299-0.18750.7324-0.5956-0.3963-0.48760.4394-0.12040.8576-0.0604-0.36830.484-0.0017-0.2795-0.5389-0.03194.7913
METADebt-to-Assets RatioNaN-0.09550.9299-0.18750.7324-1.0179-0.32430.4593-0.8295-0.782-0.6034-1.0NaNinf14.1765-0.13570.24960.7129-30.7088
Debt-to-Equity RatioNaN-0.09550.9299-0.18750.7324-1.0248-0.36840.4501-0.8463-0.789-0.6-1.0NaNinf16.322-0.18790.33860.9037-21.1149
Debt Service Coverage RatioNaN-0.09550.9299-0.18750.7324-1.3005-0.2637-0.73823.98460.3758-0.07790.33660.2431-0.3392-0.55120.36860.0144-0.5158-4.9723
Equity MultiplierNaN-0.09550.9299-0.18750.7324-1.3005-0.5024-0.0251-0.0583-0.0707-0.0096-0.00860.01220.02520.08570.02430.00680.0923-4.0312
Free Cash Flow YieldNaN-0.09550.9299-0.18750.7324-infNaN-1.03.75-0.16270.17140.6878-0.03180.197-0.1047-0.16710.36120.4398-73.599
Net-Debt to EBITDA RatioNaN-0.09550.9299-0.18750.7324-0.8731-0.6416-0.941230.6229-0.123-0.10360.0274-0.423-0.0635-0.0958-0.4054-0.715-7.3427-14.4417
Cash Flow Coverage RatioNaN-0.09550.9299-0.18750.7324-infNaN-1.03.75-0.16270.17140.6878-0.03180.197-0.1047-0.16710.36120.4398-73.599
CAPEX Coverage RatioNaN-0.09550.9299-0.18750.7324-0.73020.073-0.48931.3749-0.03860.14360.05240.0028-0.41510.1430.06610.2119-0.48311.6492
Dividend CAPEX Coverage RatioNaN-0.09550.9299-0.18750.7324-0.73020.073-0.48931.3749-0.03860.14360.05240.0028-0.41510.1430.06610.2119-0.48311.6492
WMTDebt-to-Assets RatioNaN0.0738-0.08120.0585-0.0545-0.06270.140.0007-0.03510.0379-0.10590.0137-0.0786-0.0160.16410.1576-0.1822-0.06550.0337
Debt-to-Equity RatioNaN0.1467-0.1320.0911-0.0647-0.0970.24570.0298-0.05350.0475-0.16670.0036-0.04940.0110.22060.2189-0.1864-0.13670.1246
Debt Service Coverage RatioNaN-0.04770.0435-0.04970.09380.04740.013-0.0238-0.0920.0010.0733-0.1031-0.0882-0.23460.0887-0.067-0.07940.2198-0.256
Equity MultiplierNaN5.32220.001-0.01110.0092-0.02410.0270.06030.004-0.0047-0.0306-0.03880.01040.02980.03850.05080.0227-0.04150.0016
Free Cash Flow YieldNaN0.45570.40430.02481.2810.1921-0.2767-0.11370.026-0.26351.2294-0.1574-0.072-0.0632-0.2514-0.30390.752-0.56310.0035
Net-Debt to EBITDA RatioNaN0.1541-0.12530.1328-0.1434-0.09210.19150.0559-0.05510.0815-0.17770.0844-0.0340.07860.20150.212-0.2843-0.05710.319
Cash Flow Coverage RatioNaN0.45570.40430.02481.2810.1921-0.2767-0.11370.026-0.26351.2294-0.1574-0.072-0.0632-0.2514-0.30390.752-0.56310.0035
CAPEX Coverage RatioNaN0.03770.0630.05870.47720.0702-0.1358-0.03570.1052-0.10620.32310.01710.2442-0.0505-0.0483-0.12070.4897-0.475-0.0643
Dividend CAPEX Coverage RatioNaN0.03710.05720.00650.38170.0541-0.138-0.05270.0724-0.13820.2881-0.00940.2152-0.0646-0.0368-0.10670.4609-0.42990.009
\n", "
" ], "text/plain": [ "date 2005 2006 2007 2008 2009 \\\n", "AAPL Debt-to-Assets Ratio NaN NaN NaN NaN NaN \n", " Debt-to-Equity Ratio NaN NaN NaN NaN NaN \n", " Debt Service Coverage Ratio NaN -0.1995 0.2506 -0.0607 -0.108 \n", " Equity Multiplier NaN 2.4795 0.0533 0.0517 0.0474 \n", " Free Cash Flow Yield NaN -0.4425 0.2023 3.2654 -0.5744 \n", " Net-Debt to EBITDA Ratio NaN 0.2505 -0.171 -0.1107 -0.6423 \n", " Cash Flow Coverage Ratio NaN -0.4425 0.2023 3.2654 -0.5744 \n", " CAPEX Coverage Ratio NaN -0.6534 0.6418 0.4426 0.0465 \n", " Dividend CAPEX Coverage Ratio NaN -0.6534 0.6418 0.4426 0.0465 \n", "AMZN Debt-to-Assets Ratio NaN -0.2943 -0.2865 -0.7283 -0.8597 \n", " Debt-to-Equity Ratio NaN -0.5245 -0.6181 -0.8441 -0.8818 \n", " Debt Service Coverage Ratio NaN -0.3143 0.1484 0.0057 -0.1359 \n", " Equity Multiplier NaN 52.1429 -0.4402 -0.426 -0.2704 \n", " Free Cash Flow Yield NaN 0.0919 0.0404 1.0388 -0.2048 \n", " Net-Debt to EBITDA Ratio NaN -0.5509 -4.2153 0.5367 0.0858 \n", " Cash Flow Coverage Ratio NaN 0.0919 0.0404 1.0388 -0.2048 \n", " CAPEX Coverage Ratio NaN -0.0955 0.9299 -0.1875 0.7324 \n", " Dividend CAPEX Coverage Ratio NaN -0.0955 0.9299 -0.1875 0.7324 \n", "META Debt-to-Assets Ratio NaN -0.0955 0.9299 -0.1875 0.7324 \n", " Debt-to-Equity Ratio NaN -0.0955 0.9299 -0.1875 0.7324 \n", " Debt Service Coverage Ratio NaN -0.0955 0.9299 -0.1875 0.7324 \n", " Equity Multiplier NaN -0.0955 0.9299 -0.1875 0.7324 \n", " Free Cash Flow Yield NaN -0.0955 0.9299 -0.1875 0.7324 \n", " Net-Debt to EBITDA Ratio NaN -0.0955 0.9299 -0.1875 0.7324 \n", " Cash Flow Coverage Ratio NaN -0.0955 0.9299 -0.1875 0.7324 \n", " CAPEX Coverage Ratio NaN -0.0955 0.9299 -0.1875 0.7324 \n", " Dividend CAPEX Coverage Ratio NaN -0.0955 0.9299 -0.1875 0.7324 \n", "WMT Debt-to-Assets Ratio NaN 0.0738 -0.0812 0.0585 -0.0545 \n", " Debt-to-Equity Ratio NaN 0.1467 -0.132 0.0911 -0.0647 \n", " Debt Service Coverage Ratio NaN -0.0477 0.0435 -0.0497 0.0938 \n", " Equity Multiplier NaN 5.3222 0.001 -0.0111 0.0092 \n", " Free Cash Flow Yield NaN 0.4557 0.4043 0.0248 1.281 \n", " Net-Debt to EBITDA Ratio NaN 0.1541 -0.1253 0.1328 -0.1434 \n", " Cash Flow Coverage Ratio NaN 0.4557 0.4043 0.0248 1.281 \n", " CAPEX Coverage Ratio NaN 0.0377 0.063 0.0587 0.4772 \n", " Dividend CAPEX Coverage Ratio NaN 0.0371 0.0572 0.0065 0.3817 \n", "\n", "date 2010 2011 2012 2013 2014 \\\n", "AAPL Debt-to-Assets Ratio NaN NaN NaN inf 0.8584 \n", " Debt-to-Equity Ratio NaN NaN NaN inf 1.3044 \n", " Debt Service Coverage Ratio 1.2336 0.3617 0.1864 -0.1933 -0.2843 \n", " Equity Multiplier -0.1076 -0.0976 -0.0251 0.0556 0.178 \n", " Free Cash Flow Yield 0.18 0.432 0.0285 0.0051 -0.1531 \n", " Net-Debt to EBITDA Ratio -0.0785 -0.5247 -0.3341 -1.2571 6.5191 \n", " Cash Flow Coverage Ratio 0.18 0.432 0.0285 0.0051 -0.1531 \n", " CAPEX Coverage Ratio 0.0468 -0.4256 0.0741 0.0932 0.0291 \n", " Dividend CAPEX Coverage Ratio 0.0468 -0.4256 -0.1507 -0.3611 0.0437 \n", "AMZN Debt-to-Assets Ratio 3.3165 0.6422 1.1 0.0969 0.776 \n", " Debt-to-Equity Ratio 3.5121 0.9529 1.563 0.1371 1.1872 \n", " Debt Service Coverage Ratio -0.1155 -0.573 -0.3851 -0.0899 -0.8056 \n", " Equity Multiplier -0.0359 0.1205 0.2029 0.1179 0.1399 \n", " Free Cash Flow Yield -0.3752 -0.147 -0.8652 2.0556 0.2364 \n", " Net-Debt to EBITDA Ratio -0.2821 0.2472 -0.144 -0.4221 -0.5167 \n", " Cash Flow Coverage Ratio -0.3752 -0.147 -0.8652 2.0556 0.2364 \n", " CAPEX Coverage Ratio -0.5956 -0.3963 -0.4876 0.4394 -0.1204 \n", " Dividend CAPEX Coverage Ratio -0.5956 -0.3963 -0.4876 0.4394 -0.1204 \n", "META Debt-to-Assets Ratio -1.0179 -0.3243 0.4593 -0.8295 -0.782 \n", " Debt-to-Equity Ratio -1.0248 -0.3684 0.4501 -0.8463 -0.789 \n", " Debt Service Coverage Ratio -1.3005 -0.2637 -0.7382 3.9846 0.3758 \n", " Equity Multiplier -1.3005 -0.5024 -0.0251 -0.0583 -0.0707 \n", " Free Cash Flow Yield -inf NaN -1.0 3.75 -0.1627 \n", " Net-Debt to EBITDA Ratio -0.8731 -0.6416 -0.9412 30.6229 -0.123 \n", " Cash Flow Coverage Ratio -inf NaN -1.0 3.75 -0.1627 \n", " CAPEX Coverage Ratio -0.7302 0.073 -0.4893 1.3749 -0.0386 \n", " Dividend CAPEX Coverage Ratio -0.7302 0.073 -0.4893 1.3749 -0.0386 \n", "WMT Debt-to-Assets Ratio -0.0627 0.14 0.0007 -0.0351 0.0379 \n", " Debt-to-Equity Ratio -0.097 0.2457 0.0298 -0.0535 0.0475 \n", " Debt Service Coverage Ratio 0.0474 0.013 -0.0238 -0.092 0.001 \n", " Equity Multiplier -0.0241 0.027 0.0603 0.004 -0.0047 \n", " Free Cash Flow Yield 0.1921 -0.2767 -0.1137 0.026 -0.2635 \n", " Net-Debt to EBITDA Ratio -0.0921 0.1915 0.0559 -0.0551 0.0815 \n", " Cash Flow Coverage Ratio 0.1921 -0.2767 -0.1137 0.026 -0.2635 \n", " CAPEX Coverage Ratio 0.0702 -0.1358 -0.0357 0.1052 -0.1062 \n", " Dividend CAPEX Coverage Ratio 0.0541 -0.138 -0.0527 0.0724 -0.1382 \n", "\n", "date 2015 2016 2017 2018 2019 \\\n", "AAPL Debt-to-Assets Ratio 0.458 0.219 0.1394 0.0156 0.0198 \n", " Debt-to-Equity Ratio 0.707 0.2564 0.2717 0.2381 0.1175 \n", " Debt Service Coverage Ratio 0.0678 -0.1038 -0.2316 -0.003 -0.0033 \n", " Equity Multiplier 0.2119 0.093 0.0748 0.1562 0.1598 \n", " Free Cash Flow Yield 0.5241 -0.2996 -0.3138 0.4062 -0.4784 \n", " Net-Debt to EBITDA Ratio 0.4804 0.7333 0.4649 -0.1884 -0.285 \n", " Cash Flow Coverage Ratio 0.5241 -0.2996 -0.3138 0.4062 -0.4784 \n", " CAPEX Coverage Ratio 0.1625 -0.3132 0.023 0.1702 0.1368 \n", " Dividend CAPEX Coverage Ratio 0.2363 -0.2735 -0.0287 0.1517 -0.0161 \n", "AMZN Debt-to-Assets Ratio -0.0541 -0.1583 0.5833 -0.153 0.1472 \n", " Debt-to-Equity Ratio -0.0886 -0.2555 0.7349 -0.3325 0.1147 \n", " Debt Service Coverage Ratio 9.4603 0.4492 -0.2576 1.5614 -0.0881 \n", " Equity Multiplier 0.076 -0.0836 0.0028 -0.0971 -0.1097 \n", " Free Cash Flow Yield 0.6765 0.1754 -0.5821 1.0536 0.013 \n", " Net-Debt to EBITDA Ratio -0.5426 0.5459 -4.3337 -0.7408 1.5779 \n", " Cash Flow Coverage Ratio 0.6765 0.1754 -0.5821 1.0536 0.013 \n", " CAPEX Coverage Ratio 0.8576 -0.0604 -0.3683 0.484 -0.0017 \n", " Dividend CAPEX Coverage Ratio 0.8576 -0.0604 -0.3683 0.484 -0.0017 \n", "META Debt-to-Assets Ratio -0.6034 -1.0 NaN inf 14.1765 \n", " Debt-to-Equity Ratio -0.6 -1.0 NaN inf 16.322 \n", " Debt Service Coverage Ratio -0.0779 0.3366 0.2431 -0.3392 -0.5512 \n", " Equity Multiplier -0.0096 -0.0086 0.0122 0.0252 0.0857 \n", " Free Cash Flow Yield 0.1714 0.6878 -0.0318 0.197 -0.1047 \n", " Net-Debt to EBITDA Ratio -0.1036 0.0274 -0.423 -0.0635 -0.0958 \n", " Cash Flow Coverage Ratio 0.1714 0.6878 -0.0318 0.197 -0.1047 \n", " CAPEX Coverage Ratio 0.1436 0.0524 0.0028 -0.4151 0.143 \n", " Dividend CAPEX Coverage Ratio 0.1436 0.0524 0.0028 -0.4151 0.143 \n", "WMT Debt-to-Assets Ratio -0.1059 0.0137 -0.0786 -0.016 0.1641 \n", " Debt-to-Equity Ratio -0.1667 0.0036 -0.0494 0.011 0.2206 \n", " Debt Service Coverage Ratio 0.0733 -0.1031 -0.0882 -0.2346 0.0887 \n", " Equity Multiplier -0.0306 -0.0388 0.0104 0.0298 0.0385 \n", " Free Cash Flow Yield 1.2294 -0.1574 -0.072 -0.0632 -0.2514 \n", " Net-Debt to EBITDA Ratio -0.1777 0.0844 -0.034 0.0786 0.2015 \n", " Cash Flow Coverage Ratio 1.2294 -0.1574 -0.072 -0.0632 -0.2514 \n", " CAPEX Coverage Ratio 0.3231 0.0171 0.2442 -0.0505 -0.0483 \n", " Dividend CAPEX Coverage Ratio 0.2881 -0.0094 0.2152 -0.0646 -0.0368 \n", "\n", "date 2020 2021 2022 2023 \n", "AAPL Debt-to-Assets Ratio 0.0874 0.0236 -0.0419 -0.0743 \n", " Debt-to-Equity Ratio 0.4412 0.1488 0.1987 -0.2456 \n", " Debt Service Coverage Ratio 0.0402 0.3804 -0.1066 0.0141 \n", " Equity Multiplier 0.193 0.2362 0.1772 0.0106 \n", " Free Cash Flow Yield -0.2735 -0.0216 0.6782 -0.3816 \n", " Net-Debt to EBITDA Ratio 0.243 -0.224 -0.0108 -0.127 \n", " Cash Flow Coverage Ratio -0.2735 -0.0216 0.6782 -0.3816 \n", " CAPEX Coverage Ratio 0.6694 -0.1497 0.2154 -0.1158 \n", " Dividend CAPEX Coverage Ratio 0.3378 0.0795 0.1742 -0.1102 \n", "AMZN Debt-to-Assets Ratio -0.0638 0.0537 0.0939 -15.0499 \n", " Debt-to-Equity Ratio -0.1128 -0.0682 0.1396 -5.4343 \n", " Debt Service Coverage Ratio 0.0942 -0.0348 -0.5495 -54.9886 \n", " Equity Multiplier -0.043 -0.089 -0.0297 -2.3694 \n", " Free Cash Flow Yield -0.3305 -1.5513 1.314 212.7839 \n", " Net-Debt to EBITDA Ratio 0.1779 0.5377 0.1776 -3.6725 \n", " Cash Flow Coverage Ratio -0.3305 -1.5513 1.314 212.7839 \n", " CAPEX Coverage Ratio -0.2795 -0.5389 -0.0319 4.7913 \n", " Dividend CAPEX Coverage Ratio -0.2795 -0.5389 -0.0319 4.7913 \n", "META Debt-to-Assets Ratio -0.1357 0.2496 0.7129 -30.7088 \n", " Debt-to-Equity Ratio -0.1879 0.3386 0.9037 -21.1149 \n", " Debt Service Coverage Ratio 0.3686 0.0144 -0.5158 -4.9723 \n", " Equity Multiplier 0.0243 0.0068 0.0923 -4.0312 \n", " Free Cash Flow Yield -0.1671 0.3612 0.4398 -73.599 \n", " Net-Debt to EBITDA Ratio -0.4054 -0.715 -7.3427 -14.4417 \n", " Cash Flow Coverage Ratio -0.1671 0.3612 0.4398 -73.599 \n", " CAPEX Coverage Ratio 0.0661 0.2119 -0.4831 1.6492 \n", " Dividend CAPEX Coverage Ratio 0.0661 0.2119 -0.4831 1.6492 \n", "WMT Debt-to-Assets Ratio 0.1576 -0.1822 -0.0655 0.0337 \n", " Debt-to-Equity Ratio 0.2189 -0.1864 -0.1367 0.1246 \n", " Debt Service Coverage Ratio -0.067 -0.0794 0.2198 -0.256 \n", " Equity Multiplier 0.0508 0.0227 -0.0415 0.0016 \n", " Free Cash Flow Yield -0.3039 0.752 -0.5631 0.0035 \n", " Net-Debt to EBITDA Ratio 0.212 -0.2843 -0.0571 0.319 \n", " Cash Flow Coverage Ratio -0.3039 0.752 -0.5631 0.0035 \n", " CAPEX Coverage Ratio -0.1207 0.4897 -0.475 -0.0643 \n", " Dividend CAPEX Coverage Ratio -0.1067 0.4609 -0.4299 0.009 " ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "companies.ratios.collect_solvency_ratios(diluted=False, growth=True)" ] }, { "cell_type": "markdown", "id": "e7ec2674", "metadata": {}, "source": [ "For all ratios, it is also possible to show the growth instead. E.g. if you are interested in the growth of the Price-to-Book ratio you can use the following:" ] }, { "cell_type": "code", "execution_count": 6, "id": "48b75204", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Date2005200620072008200920102011201220132014201520162017201820192020202120222023
AAPLNaN-0.0970.6254-0.69860.8785-0.0908-0.2071-0.1330.01950.4618-0.1422-0.00610.35620.12681.08031.380.3416-0.11290.1767
AMZNNaN-0.5251-0.1544-0.74760.36730.0567-0.14020.34890.3719-0.29830.804-0.21870.1057-0.1712-0.12980.1848-0.3017-0.5287.359
METANaN-0.5251-0.1544-0.74760.3673-1.0NaNinf0.8128-0.35240.1727-0.15810.2341-0.35120.28340.05270.2523-0.664117.9395
WMTNaN-0.0868-0.09860.1173-0.0646-0.06540.11250.06420.07690.085-0.3210.16320.4678-0.06690.3680.166-0.0703-0.04230.1943
\n", "
" ], "text/plain": [ "Date 2005 2006 2007 2008 2009 2010 2011 2012 2013 \\\n", "AAPL NaN -0.097 0.6254 -0.6986 0.8785 -0.0908 -0.2071 -0.133 0.0195 \n", "AMZN NaN -0.5251 -0.1544 -0.7476 0.3673 0.0567 -0.1402 0.3489 0.3719 \n", "META NaN -0.5251 -0.1544 -0.7476 0.3673 -1.0 NaN inf 0.8128 \n", "WMT NaN -0.0868 -0.0986 0.1173 -0.0646 -0.0654 0.1125 0.0642 0.0769 \n", "\n", "Date 2014 2015 2016 2017 2018 2019 2020 2021 2022 \\\n", "AAPL 0.4618 -0.1422 -0.0061 0.3562 0.1268 1.0803 1.38 0.3416 -0.1129 \n", "AMZN -0.2983 0.804 -0.2187 0.1057 -0.1712 -0.1298 0.1848 -0.3017 -0.528 \n", "META -0.3524 0.1727 -0.1581 0.2341 -0.3512 0.2834 0.0527 0.2523 -0.6641 \n", "WMT 0.085 -0.321 0.1632 0.4678 -0.0669 0.368 0.166 -0.0703 -0.0423 \n", "\n", "Date 2023 \n", "AAPL 0.1767 \n", "AMZN 7.359 \n", "META 17.9395 \n", "WMT 0.1943 " ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "companies.ratios.get_price_to_book_ratio(growth=True)" ] }, { "cell_type": "markdown", "id": "bfedee0b", "metadata": {}, "source": [ "By default, the lag is set to 1 (one period) but it is possible to change this and add multiple lags as well." ] }, { "cell_type": "code", "execution_count": 7, "id": "8dae792f", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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date2005200620072008200920102011201220132014201520162017201820192020202120222023
AAPLLag 1NaN-0.24160.05310.0426-0.2360.0694-0.2003-0.070.1222-0.35660.02650.22-0.0566-0.11930.3704-0.1146-0.212-0.18170.1236
Lag 2NaNNaN-0.20130.0979-0.2034-0.183-0.1448-0.25630.0436-0.2779-0.33950.25230.1509-0.16920.20690.2133-0.3023-0.3551-0.0805
Lag 3NaNNaNNaN-0.1673-0.1612-0.1482-0.3466-0.2047-0.1654-0.3285-0.2588-0.19420.18140.01360.13860.0686-0.0439-0.429-0.2754
AMZNLag 1NaN-0.12270.0437-0.0670.0255-0.0038-0.1141-0.0455-0.04380.0408-0.0353-0.0289-0.00470.0559-0.001-0.04270.0814-0.16830.0
Lag 2NaNNaN-0.0843-0.0262-0.04320.0217-0.1174-0.1544-0.0873-0.00490.0041-0.0632-0.03340.0510.0549-0.04360.0353-0.1005-0.1683
Lag 3NaNNaNNaN-0.1456-0.0013-0.0468-0.0949-0.1576-0.1915-0.0501-0.0399-0.025-0.06750.02060.050.00990.0343-0.1389-0.1005
METALag 1NaNNaNNaNNaNNaNNaN-0.1131.09130.1094-0.19210.17170.06380.0794-0.443-0.38850.1481-0.3755-0.30150.0
Lag 2NaNNaNNaNNaNNaNNaNNaN0.8551.3201-0.1037-0.05340.24640.1483-0.3988-0.6594-0.2979-0.283-0.5638-0.3015
Lag 3NaNNaNNaNNaNNaNNaNNaNNaN1.05790.87450.05020.0070.3454-0.3604-0.6323-0.6089-0.5615-0.4992-0.5638
WMTLag 1NaN0.00010.0029-0.09570.0856-0.01570.02-0.0055-0.05420.05720.0987-0.0384-0.0754-0.11850.0514-0.00550.2236-0.0456-0.115
Lag 2NaNNaN0.003-0.093-0.01830.06860.00410.0144-0.0594-0.00010.16160.0565-0.1109-0.1849-0.07310.04560.21690.1677-0.1554
Lag 3NaNNaNNaN-0.0929-0.0154-0.03370.09-0.0015-0.0405-0.00560.09860.117-0.0231-0.2162-0.143-0.07820.27940.16130.0334
\n", "
" ], "text/plain": [ "date 2005 2006 2007 2008 2009 2010 2011 2012 \\\n", "AAPL Lag 1 NaN -0.2416 0.0531 0.0426 -0.236 0.0694 -0.2003 -0.07 \n", " Lag 2 NaN NaN -0.2013 0.0979 -0.2034 -0.183 -0.1448 -0.2563 \n", " Lag 3 NaN NaN NaN -0.1673 -0.1612 -0.1482 -0.3466 -0.2047 \n", "AMZN Lag 1 NaN -0.1227 0.0437 -0.067 0.0255 -0.0038 -0.1141 -0.0455 \n", " Lag 2 NaN NaN -0.0843 -0.0262 -0.0432 0.0217 -0.1174 -0.1544 \n", " Lag 3 NaN NaN NaN -0.1456 -0.0013 -0.0468 -0.0949 -0.1576 \n", "META Lag 1 NaN NaN NaN NaN NaN NaN -0.113 1.0913 \n", " Lag 2 NaN NaN NaN NaN NaN NaN NaN 0.855 \n", " Lag 3 NaN NaN NaN NaN NaN NaN NaN NaN \n", "WMT Lag 1 NaN 0.0001 0.0029 -0.0957 0.0856 -0.0157 0.02 -0.0055 \n", " Lag 2 NaN NaN 0.003 -0.093 -0.0183 0.0686 0.0041 0.0144 \n", " Lag 3 NaN NaN NaN -0.0929 -0.0154 -0.0337 0.09 -0.0015 \n", "\n", "date 2013 2014 2015 2016 2017 2018 2019 2020 \\\n", "AAPL Lag 1 0.1222 -0.3566 0.0265 0.22 -0.0566 -0.1193 0.3704 -0.1146 \n", " Lag 2 0.0436 -0.2779 -0.3395 0.2523 0.1509 -0.1692 0.2069 0.2133 \n", " Lag 3 -0.1654 -0.3285 -0.2588 -0.1942 0.1814 0.0136 0.1386 0.0686 \n", "AMZN Lag 1 -0.0438 0.0408 -0.0353 -0.0289 -0.0047 0.0559 -0.001 -0.0427 \n", " Lag 2 -0.0873 -0.0049 0.0041 -0.0632 -0.0334 0.051 0.0549 -0.0436 \n", " Lag 3 -0.1915 -0.0501 -0.0399 -0.025 -0.0675 0.0206 0.05 0.0099 \n", "META Lag 1 0.1094 -0.1921 0.1717 0.0638 0.0794 -0.443 -0.3885 0.1481 \n", " Lag 2 1.3201 -0.1037 -0.0534 0.2464 0.1483 -0.3988 -0.6594 -0.2979 \n", " Lag 3 1.0579 0.8745 0.0502 0.007 0.3454 -0.3604 -0.6323 -0.6089 \n", "WMT Lag 1 -0.0542 0.0572 0.0987 -0.0384 -0.0754 -0.1185 0.0514 -0.0055 \n", " Lag 2 -0.0594 -0.0001 0.1616 0.0565 -0.1109 -0.1849 -0.0731 0.0456 \n", " Lag 3 -0.0405 -0.0056 0.0986 0.117 -0.0231 -0.2162 -0.143 -0.0782 \n", "\n", "date 2021 2022 2023 \n", "AAPL Lag 1 -0.212 -0.1817 0.1236 \n", " Lag 2 -0.3023 -0.3551 -0.0805 \n", " Lag 3 -0.0439 -0.429 -0.2754 \n", "AMZN Lag 1 0.0814 -0.1683 0.0 \n", " Lag 2 0.0353 -0.1005 -0.1683 \n", " Lag 3 0.0343 -0.1389 -0.1005 \n", "META Lag 1 -0.3755 -0.3015 0.0 \n", " Lag 2 -0.283 -0.5638 -0.3015 \n", " Lag 3 -0.5615 -0.4992 -0.5638 \n", "WMT Lag 1 0.2236 -0.0456 -0.115 \n", " Lag 2 0.2169 0.1677 -0.1554 \n", " Lag 3 0.2794 0.1613 0.0334 " ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "companies.ratios.get_current_ratio(growth=True, lag=[1, 2, 3])" ] }, { "cell_type": "markdown", "id": "4408750c", "metadata": {}, "source": [ "It is also possible to get trailing results. E.g. the TTM Earnings per Share ratio can be acquired by setting trailing to 4 (quarters). Note that this does not lead to meaningful results when using yearly data and therefore this image now shows the 4 year trailing result. Set `quarterly=True` in the Toolkit initialization to use quarterly data." ] }, { "cell_type": "code", "execution_count": 8, "id": "f28ffcb0", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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vOX+zE/L6VRSF1q1bc+jQIfr160fx4sVZv349PXr0SNC1xCS2Dh06ZCxNcPjwYapWrUqVKlWwsrLiyJEjtGrVyrguY8aMlClTBlCT0w4ODnz99dc4ODiwZ88exowZQ2BgID///HOCnsuIiAgGDhyIn58fU6dOpVOnTtSrV499+/YxbNgwvL29mTVrFt9++y0LFiww7mvOuZ89e0bTpk3p0qUL3bt3J0eOHNSpU4eBAwfi4ODAyJEjAYy9CIQQ6ZQihBAp1OzZsxUnJyfl8ePHiqIoSu3atZWSJUsmeP/IyEilbNmyirOzswIo8+bNUxRFUV68eKFkypRJ+eyzz0y2f/jwoeLk5GSyPCQkJM5xV6xYoQDKgQMHjMvGjh2rAErXrl3NukZFUZSff/5ZARQfHx/jsh49eiiA8v3338fZPr6YfvrpJ0Wn0ym3bt2KE9Or8uXLp/To0cM4v3fvXgVQ9u7da1xWu3ZtBVCWLFliXBYeHq64uLgo7du3Ny6bPn26AigbNmwwLgsNDVWKFSsW55jxWbhwoQLE+7CxsXnrNUdERCju7u5KvXr1TJYDioWFhXLp0qV4z9WgQQPFYDAYlw8ZMkTR6/XK8+fPTa6/du3acZ6j4sWLK+Hh4cblv/76qwIo//33n/E5ypIli1KpUiUlMjLSuN2iRYsUwOSYrVu3Nutefj0WV1dXJTAw0Lj877//VgDl119/VRRFUQwGg1K4cGGlcePGJtcbEhKi5M+fX2nYsKFxmbn37sWLFxU7OzsFUMqWLasMHjxY2bBhgxIcHBxn23z58sV5rTx+/FixsbFRvvnmG+OysLAwJTo62mRfHx8fxcbGRvnhhx/iXH+BAgVM7glzrjc+5cqVUzJlyhRneVBQkPLkyRPjIyAgwLgu5p6qUaOGEhUVZXJ91tbWSqNGjUyuafbs2QqgLFiwQFEURYmOjlYcHR2V7777zngNWbJkUTp27Kjo9XrlxYsXiqIoyv/+9z/FwsJC8ff3VxRFUZ48eaIAytixY+PEG/O+8epzFnN9FSpUeOtzELN/hgwZTJadO3dOAZRPP/3UZPm3336rAMqePXuMy2L+v7dt2/bOc8WYNm2aYmdnZ7yfr127pgDK+vXrTbaLeb4rVKigREREGJdPnTpVAZR//vknThxr1641LgsICFBy5syplCtXzrjs9fe/D72P3mbAgAFKnjx5jMfdsWOHAihnz5412S7m9di3b1/jsqioKCV37tyKTqdTJk+ebFzu7++v2NnZmbynR0VFmbxPxWyXI0cOpXfv3m+M7/Dhw4qVlZXJNl999ZUCKAcPHjQue/HihZI/f37Fzc3NeH8n9D3SXIDy5ZdfKn5+foq1tbXy119/KYqiKJs3b1Z0Op3i6+trfL6ePHli3C/mdRDfo3HjxvGeK76/wzEePXqkWFpaKvPnzzcu8/DwUFq3bp2g60jo3+yEvn43bNigAMrUqVONy6KiopSaNWsqgLJw4cK3xhMYGKjo9XqlT58+xmVFixZVxo8fryiKolSuXFkZOnSocV22bNlM7v34rufzzz9X7O3tlbCwMJPryZcvn3Hex8dHAZRs2bKZ/M0dPny4AihlypQx+dvZtWtXxdra2uSYCT13zOeY33//Pc72JUuWNPl7LIRI36TLpBAiRXr27Bljxoxh9OjRxi5C5rK0tOSPP/7Az8+PqlWr8tlnnwFqq6/nz5/TtWtXnj59anzo9XqqVKli0sLp1do3YWFhPH36lKpVqwJw5syZOOfs16/fe8X6JvG16Hg1puDgYJ4+fYqHhweKonD27NlEOa+Dg4NJaxlra2sqV67MzZs3jcu2bduGq6ur8VdkUAsgxzzPCfXbb7+xc+dOk8fWrVtNtnn1mv39/QkICKBmzZrx/h/Url2bEiVKxHuuvn37mrQiqVmzJtHR0dy6deudcfbq1cukxUrNmjUBjM/JqVOnePbsGZ999plJ7baPPvqIzJkzmxwrU6ZM3L17l5MnT77zvPH55JNPyJgxo3G+Q4cO5MyZky1btgBw7tw5rl+/Trdu3Xj27JnxHg8ODqZ+/focOHAgzihpCb13S5Ysyblz5+jevTu+vr78+uuvtGnThhw5cjB//vw425coUcL4XAFky5aNokWLmtxLNjY2xhpg0dHRPHv2DAcHB4oWLRrv/3GPHj1M7on3ud5XBQYG4uDgEGf5yJEjyZYtm/ERX+u9zz77zFioG2DXrl1ERETw1VdfmdQ1++yzz3B0dDR2N7OwsMDDw4MDBw4AcOXKFZ49e8b333+PoigcPXoUUFuNubu7kylTpjfG/7rX/y9r1qxp8nybI+aeerUbJ8A333wDEKf7XP78+WncuHGCj79s2TKaN29uvJ8LFy5MhQoV4u02Cepr2MrKyjjfv39/LC0tjXHGyJUrl0kLppjulWfPnuXhw4fxHvtD76M3iYqKYtWqVXTu3Nn4/lOvXj2yZ8/+xut8tfWWXq+nYsWKKIpCnz59jMszZcoU57Wk1+uN71MGgwE/Pz+ioqKoWLFivK8lUOtndejQgbJlyzJnzhzj8i1btlC5cmWTLtQODg707dsXX19fLl++bHKcd71Hvq/MmTPTpEkTVqxYAahdTz08POLtth3D1tY2zt+VnTt3MnnyZLPPv3LlSiwsLGjfvr1xWdeuXdm6dWuc7rrxMfdv9rtev1u2bMHS0tLk84Fer2fgwIEJup6MGTNSunRpY62wp0+f4uXlZWwRWr16dWM3yWvXrvHkyROTe+DV63nx4gVPnz6lZs2ahISEcPXq1Xeev2PHjjg5ORnnq1SpAqgtdF/921mlShUiIiK4d+/ee53bxsbGZHAAIYSIj3SZFEKkSKNGjcLZ2TnBH/DepFKlSgBUqFDB+EXk+vXrAG/s7vVqdwo/Pz/Gjx/PypUr4xQMDwgIiLNvfKMlvi9LS0uTbnYxbt++zZgxY/j333/jfBiPL6b3kTt37jjdQTNnzsyFCxeM87du3aJgwYJxtjN3dMjKlSu/s6j+pk2bmDhxIufOnTOpWxRfjbS3/R/kzZvXZD4mUZWQLzXv2jcmqfb69VtaWsYp0jxs2DB27dpF5cqVKVSoEI0aNaJbt25vrF/1usKFC5vM63Q6ChUqhK+vLxB7j7+tC01AQIBJos6ce7dIkSL89ddfREdHc/nyZTZt2sTUqVPp27cv+fPnNyk2/frzBupz9+pzbjAY+PXXX5kzZw4+Pj4m9WBe7Tr7pljf53pflTFjxjh1AUHtDhnTnfFN3SlfjyXmPni9q6C1tTUFChQwSb7WrFmTcePGERoaysGDB8mZMyfly5enTJkyHDx4kIYNG3Lo0CE6der0xut6na2tbZwfEV5/vs1x69YtLCws4tzXLi4uZMqUKU4y2Zz76MqVK5w9e5ZPPvnEpJ5RnTp1+O233wgMDIzTve31e9/BwYGcOXMa7/0YhQoVivP+UKRIEUCtZeTi4hInng+9j95kx44dPHnyhMqVK5tcZ926dVmxYgVTpkyJMyjE668bJycnbG1tTUZAjFn++r27ePFipk+fztWrV4mMjDQuj+//Jioqik6dOhEdHc26deuwsbExrrt165YxWfGq4sWLG9e/WsPrQ95f36Vbt258/PHH3L59mw0bNsRb0/JVer0+0YreL126lMqVK/Ps2TPjc12uXDkiIiJYvXq1yWjW8THnb3ZCXr+3bt0iZ86ccZL47+qe/KoaNWowa9Ysnj59ypEjR9Dr9cYf+zw8PIx1WF+vHwZw6dIlRo0axZ49e4z1G990PfGJ794GyJMnT7zLX712c87t6uoqg+QIId5JEmJCiBTn+vXr/PHHH8yYMYP79+8bl4eFhREZGYmvry+Ojo44Ozu/1/FjfuH/66+/4v1S9OovlJ06deLIkSMMHTqUsmXL4uDggMFgoEmTJvG2FHjXaGrmeLXVTIzo6GgaNmyIn58fw4YNo1ixYmTIkIF79+7Rs2fP92q9EJ9XW7y8SvnAumjv4+DBg7Rq1YpatWoxZ84ccubMiZWVFQsXLoy3KPXb/g8+5LoS8zkpXrw4Xl5ebNq0iW3btrF27VrmzJnDmDFjGD9+vNnHe13MffDzzz8bawa97vUvU+9z7+r1ekqVKkWpUqWoVq0adevWjTP6WkKetx9//JHRo0fTu3dvJkyYgLOzMxYWFnz11VcJep29z/W+qlixYpw7d4579+7h6upqXF6kSBFjEuVNI5V+yGu+Ro0aREZGcvToUQ4ePGhsUVOzZk0OHjzI1atXefLkiUkLu3d50/P9od41QEcMc56PpUuXAjBkyBCGDBkSZ/3atWuTtYXHh95HbxLTCuxNic39+/dTt25dk2Xx/T8m5LW0dOlSevbsSZs2bRg6dCjZs2dHr9fz008/cePGjTj7Dh06lKNHj7Jr1654f4AxR1L+3WjVqhU2Njb06NGD8PBws5LEH+L69evGlryvJ2NB/b99W0LM3L/ZSfX6fV1MQuzw4cMcOXLEOKAJqAmx8PBwTp48yaFDh7C0tDQmy54/f07t2rVxdHTkhx9+oGDBgtja2nLmzBmGDRuWoM8gb7rGd90/5p47MT+PCSHSLkmICSFSnHv37mEwGBg0aBCDBg2Ksz5//vwMHjzY7JEnYxQsWBBQR8R72y/I/v7+7N69m/HjxzNmzBjj8phWBFr477//uHbtGosXL+aTTz4xLt+5c2eyx5IvXz4uX76MoigmX5Y/dFSx161duxZbW1u2b99u0nph4cKFiXqeDxXTfcfb29vky21UVBS+vr4mhc8BMmTIQOfOnencuTMRERG0a9eOSZMmMXz48DcmX2K8fg8qioK3t7fxHDH3uKOjY6K1kniXmFZ+Dx48MHvfNWvWULduXTw9PU2WP3/+PE6LmPh86PW2aNGClStXsmzZMr777juz939VzH3g5eVFgQIFjMsjIiLw8fExia9y5cpYW1tz8OBBDh48yNChQwGoVasW8+fPZ/fu3cb5GAlNTCWWfPnyYTAYuH79urFlEKgF158/f/7WbmtvoygKy5cvp27dunzxxRdx1k+YMIFly5bFSYhdv37d5PUVFBTEgwcPaNasmcl23t7ecd6brl27BhCnxWaMpHjdBAcH888//9C5c2c6dOgQZ/2gQYOMBdsTw5o1ayhQoADr1q0zufaxY8fG2XblypXMmDGDGTNmULt27Tjr8+XLh5eXV5zlMV3T3vf//n3Y2dnRpk0bli5dStOmTRP0vpAYli1bhpWVFX/99VechM2hQ4eYOXMmt2/fjrclLCTN3+x8+fKxe/du4yADMeL7v3qTVwvrHz161KR1cq5cuciXLx+HDx/m8OHDlCtXzjioz759+3j27Bnr1q0zeV/y8fF57+tJqMQ6d3K/hwohUjapISaESHHc3d1Zv359nEfJkiXJmzcv69evN6mjYq7GjRvj6OjIjz/+aNKdJMaTJ0+A2F8rX/91+30TcYkhvpgUReHXX39N9lgaN27MvXv3+Pfff43LwsLC4q0j9SH0ej06nc6kG52vry8bNmxI1PN8qIoVK5IlSxbmz59PVFSUcfmyZcvidJN5vYuTtbU1JUqUQFGUeO/J1y1ZsoQXL14Y59esWcODBw+MI4BWqFCBggULMm3aNIKCguLsH3OPv4+DBw/GG2NMDSdzuu3E0Ov1cV5nq1evNqkd8zYfer2dOnWiRIkSTJgwgWPHjsW7TUJbuTRo0ABra2tmzpxpso+npycBAQEmo6La2tpSqVIlVqxYwe3bt01aiIWGhjJz5kwKFixIzpw5jfvEfDF9/vx5guL5UDGJptff9/73v/8BxBnlNaEOHz6Mr68vvXr1okOHDnEenTt3Zu/evSathAH++OMPk/tv7ty5REVFGe/9GPfv3zcZATMwMJAlS5ZQtmzZeFsGQ9K8btavX09wcDBffvllvNfZokUL1q5da9IV/EPE9zfi+PHjxpp0MS5evMinn35K9+7dGTx4cLzHatasGSdOnDDZNzg4mD/++AM3N7c31mpMKt9++y1jx45l9OjRyXbOZcuWUbNmTWNC89VHTAI7prZZfJLib3azZs2Iiopi7ty5xmXR0dHMmjUrwcfIlSsX+fPnZ/fu3Zw6dcpYPyyGh4cHGzZswMvLy6S7ZHzXExERYVJ7Lqkk1rkzZMiQbO+fQoiUT1qICSFSnKxZs9KmTZs4y2O+kMW3zhyOjo7MnTuXjz/+mPLly9OlSxeyZcvG7du32bx5M9WrV2f27Nk4OjpSq1Ytpk6dSmRkJK6uruzYsSNZfgl9k2LFilGwYEG+/fZb7t27h6OjI2vXrk2UGi3m+vzzz5k9ezZdu3Zl8ODB5MyZk2XLlhlbNyX0V9itW7fGW4jXw8ODAgUK0Lx5c/73v//RpEkTunXrxuPHj/ntt98oVKiQSU0zrVlbWzNu3DgGDhxIvXr16NSpE76+vixatChOrbVGjRrh4uJC9erVyZEjB1euXGH27NkmxcXfxtnZmRo1atCrVy8ePXrEjBkzKFSokHFAAwsLC/7880+aNm1KyZIl6dWrF66urty7d4+9e/fi6OjIxo0b3+s6p0yZwunTp2nXrp2xRdqZM2dYsmQJzs7OfPXVV2Yfs0WLFvzwww/06tULDw8P/vvvP5YtW2bSwuptPvR6raysWL9+PY0bN6ZGjRq0a9eOmjVrGrs2/fvvv9y+fTtByZ9s2bIxfPhwxo8fT5MmTWjVqhVeXl7MmTOHSpUqxalFVrNmTSZPnoyTkxOlSpUC1NarRYsWxcvLi549e5psb2dnR4kSJVi1ahVFihTB2dkZd3d3k1pOialMmTL06NGDP/74w9hl6cSJEyxevJg2bdq8d8umZcuWodfr3/ictmrVipEjR7Jy5UqTgv4RERHUr1+fTp06GZ/XGjVqmAzuAWp31z59+nDy5Ely5MjBggULePTo0Vtblpp7H+l0OmrXrs2+ffveep1ZsmSJk3B49Trnz5/P5s2badeu3RuPk1AtWrRg3bp1tG3blubNm+Pj48Pvv/9OiRIlTJJ8MS3vatWqZey6GiPmvff7779nxYoVNG3alEGDBuHs7MzixYvx8fFh7dq1cbr0J8S+ffuoW7cuY8eOZdy4cWbtW6ZMGcqUKZOgbaOiouJcV4y2bduSIUOGdx7j+PHjeHt7M2DAgHjXu7q6Ur58eZYtW8awYcPi3SYp/ma3bNmS6tWr8/333+Pr60uJEiVYt26d2TVEa9SowV9//QUQp36lh4eHMdH3akLMw8ODzJkz06NHDwYNGoROp+Ovv/5KlnIKiXXuChUqMHfuXCZOnEihQoXInj37G2vKCiHSPkmICSHSpW7dupErVy4mT57Mzz//THh4OK6urtSsWdOki87y5csZOHAgv/32G4qi0KhRI7Zu3UquXLk0idvKyoqNGzcyaNAgfvrpJ2xtbWnbti0DBgxI8BeFxOLg4MCePXsYOHAgv/76Kw4ODnzyySd4eHjQvn37d3b7i/Fqd9RXLVy4kAIFClCvXj08PT2ZPHkyX331Ffnz52fKlCn4+vqmqIQYwIABA1AUhenTp/Ptt99SpkwZ/v33XwYNGmTyfHz++ecsW7aM//3vfwQFBZE7d24GDRrEqFGjEnSeESNGcOHCBX766SdevHhB/fr1mTNnjrH1EKiFyY8ePcqECROYPXs2QUFBuLi4UKVKFT7//PP3vsYRI0awfPly9u/fz7JlywgJCSFnzpx06dKF0aNHv9fAEiNGjCA4OJjly5ezatUqypcvz+bNm/n+++8TfIwPvd4iRYpw7tw5Zs6cyfr169m6dSsRERHkyJGDKlWqMHbsWGOB/XcZN24c2bJlY/bs2QwZMgRnZ2f69u3Ljz/+aDJCIsQmxDw8PEwSDDVr1sTLyyve+mF//vknAwcOZMiQIURERDB27NgkS4jFnK9AgQIsWrSI9evX4+LiwvDhw+PthpcQkZGRrF69Gg8PjzfWgnR3dyd//vwsXbrUJCE2e/Zsli1bxpgxY4iMjKRr167MnDkzTgK+cOHCzJo1i6FDh+Ll5UX+/PlZtWrVO0fATOh9FJNcerX13useP37Mrl276Nq16xvrI9WvXx97e3uWLl2aKAmxnj178vDhQ+bNm8f27dspUaIES5cuZfXq1SaJuydPnhAcHBxv/auY994cOXJw5MgRhg0bxqxZswgLC6N06dJs3LjxvVsGJuR5Swzh4eF8/PHH8a7z8fFJUEIspvZby5Yt37hNy5YtGTduHBcuXIjTLR6S5m+2hYUF//77L1999RVLly5Fp9PRqlUrpk+fTrly5RJ8nJiEmKura5zur68myF5NiGXJkoVNmzbxzTffMGrUKDJnzkz37t2pX7++WaPLvo/EOveYMWO4desWU6dO5cWLF9SuXVsSYkKkYzpFiwrJQggh0qwZM2YwZMgQ7t69a1KgPL0yGAxky5aNdu3afXB30pjWFatXr463HpEQadWiRYvo1asXJ0+efOeotG5ubri7u7Np06Yki2fLli20aNGC8+fPG1v2iXf77rvvWLFiBd7e3iY1IYUQQggtSA0xIYQQ7y00NNRkPiwsjHnz5lG4cOF0mQwLCwuL031jyZIl+Pn5UadOHW2CEkIkur1799KlSxdJhplp7969jB49WpJhQgghUgTpMimEEOK9tWvXjrx581K2bFkCAgJYunQpV69eNXY1SW+OHTvGkCFD6NixI1myZOHMmTN4enri7u5Ox44dtQ5PCJFIfv75Z61DSJVOnjypdQhCCCGEkSTEhBBCvLfGjRvz559/smzZMqKjoylRogQrV66kc+fOWoemCTc3N/LkycPMmTPx8/PD2dmZTz75hMmTJ2Ntba11eEIIIYQQQoiXpIaYEEIIIYQQQgghhEhXpIaYEEIIIYQQQgghhEhXJCEmhBBCCCGEEEIIIdKVVF1DzGAwcP/+fTJmzIhOp9M6HCGEEEIIIYQQQgihIUVRePHiBbly5cLC4s3twFJ1Quz+/fvkyZNH6zCEEEIIIYQQQgghRApy584dcufO/cb1qTohljFjRkC9SEdHR42jSd0iIyPZsWMHjRo1wsrKSutwhADkvhQpk9yXIiWS+1KkRHJfipRK7k2REsl9mXgCAwPJkyePMWf0Jqk6IRbTTdLR0VESYh8oMjISe3t7HB0d5cUnUgy5L0VKJPelSInkvhQpkdyXIqWSe1OkRHJfJr53ldaSovpCCCGEEEIIIYQQIl2RhJgQQgghhBBCCCGESFckISaEEEIIIYQQQggh0pUUU0Ns8uTJDB8+nMGDBzNjxoxEO66iKERFRREdHZ1ox0yLIiMjsbS0JCwszOznysrKCr1en0SRCSGEEEIIIYQQQiSuFJEQO3nyJPPmzaN06dKJetyIiAgePHhASEhIoh43LVIUBRcXF+7cufPOwnOv0+l05M6dGwcHhySKTgghhBBCCCGEECLxaJ4QCwoK4qOPPmL+/PlMnDgx0Y5rMBjw8fFBr9eTK1curK2tzU70pCcGg4GgoCAcHBywsEh4T1pFUXjy5Al3796lcOHC0lJMCCGE0IIhGquoF1pHIYQQQgiRamieEPvyyy9p3rw5DRo0eGdCLDw8nPDwcON8YGAgoHb3i4yMjLNtdHQ0rq6u2NvbJ37gaYyiKERERGBjY2N24jBLliwEBQURGhqKjY1NEkUo0qOY1/Xrr28htCT3pUhxFAXdmp40u76VyIw3iKw7QuuIhADk/VKkXHJvipRI7svEk9DnUNOE2MqVKzlz5gwnT55M0PY//fQT48ePj7N8x44dcZJelpaWuLi4EBISQlRUVKLEmx68eGH+r8sRERGEhoayf/9+ea5Fkti5c6fWIQgRh9yXIqXI+uIy1b23AmB55Bf2P8tEgL2btkEJ8Qp5vxQpldybIiWS+/LDJbRslmYJsTt37jB48GB27tyJra1tgvYZPnw4X3/9tXE+MDCQPHny0KhRIxwdHU22DQsL486dOzg4OCT4+OmZoii8ePGCjBkzmt1CLCwsDDs7O2rVqiXPtUhUkZGR7Ny5k4YNG2JlZaV1OEIAcl+KlEe/colxWodCraB/iW6/BXQymLjQlrxfipRK7k2REsl9mXhiehO+i2YJsdOnT/P48WPKly9vXBYdHc2BAweYPXs24eHhcepR2djYxNslz8rKKs4NEx0djU6nw8LCwqyaWOmVwWAAMD5n5rCwsECn08X7/yBEYpB7S6REcl+KFOHRZbixy2SRxb1TWFxaA+U+0igoIUzJ+6VIqeTeFCmR3JcfLqHPn2YJsfr16/Pff/+ZLOvVqxfFihVj2LBhUpxdCCGEEOJdjs42Tt7PVIlcz1+Wodg5Boo1B7tM2sQlhBBCCJHCadZ0KmPGjLi7u5s8MmTIQJYsWXB3d9cqrBTl6NGj6PV6mjdv/sZtVqxYgV6v58svv4yzbt++feh0OuMjR44ctG/fnps3bxq3cXNzY8aMGUkRvhBCCCGSUuB9uPA3AIptJs7k/QxD8dbqupCnsPdHDYMTQgghhEjZpC9hCubp6cnAgQM5cOAA9+/ff+M23333HStWrCAsLCzebby8vLh//z6rV6/m0qVLtGzZkujo6KQMXQghhBBJ7fjvYFBHUTKU70W03pboBj+A1cuBhk7Oh4f/veUAQgghhBDpV4pKiO3bt09aK70UFBTEqlWr6N+/P82bN2fRokVxtvHx8eHIkSN8//33FClShHXr1sV7rOzZs5MzZ05q1arFmDFjuHz5Mt7e3kl8BUIIIYRIMmGBcGqhOq23xlDpU3Xa0RVqfatOKwbYMhQURZsYhRBCCCFSMM1qiGml5axDPHkRnqznzJbRho0Da5i1z99//02xYsUoWrQo3bt356uvvmL48OEmI0AuXLiQ5s2b4+TkRPfu3fH09KRbt25vPa6dnR0AERER5l+IEEIIIVKGM4sh/OUISmW6gEOO2HXVBsDZZeB3A24fVbtVlumsTZxCCCGEEClUukuIPXkRzsPA+LsWpiSenp50794dgCZNmhAQEMD+/fupU6cOoI4KuWjRImbNmgVAly5d+Oabb/Dx8SF//vzxHvPBgwdMmzYNV1dXihYtmizXIYQQQohEFh0Jx+bGzlcbaLre0gaaTYWl7dX5naOhaFOwdUy+GIUQQgghUrh0lxDLltEmxZ/Ty8uLEydOsH79egAsLS3p3Lkznp6exoTYzp07CQ4OplmzZgBkzZqVhg0bsmDBAiZMmGByvNy5c6MoCiEhIZQpU4a1a9dibW394RcmhBBCiOR3cR0E3lOnizSFbEUgMtJ0m0INoFgLuLoJgh7BvsnQRIrsCyGEEELESHcJMXO7LmrB09OTqKgocuXKZVymKAo2NjbMnj0bJycnPD098fPzM3aBBLXV2IULFxg/fjwWFrHl4Q4ePIijoyPZs2cnY8aMyXotQgghhEhEigJHZsbOVx/05m0b/wjeuyAqTC3AX/5jyF486WMUQgghhEgFUlRRfQFRUVEsWbKE6dOnc+7cOePj/Pnz5MqVixUrVvDs2TP++ecfVq5cabLN2bNn8ff3Z8eOHSbHzJ8/PwULFpRkmBBCCJHa3dgDjy6q064VIW+1N2+bOR/U/EadVqKlwL4QQgghxCvSXQuxlG7Tpk34+/vTp08fnJycTNa1b98eT09PwsLCyJIlC506dTIpsg/QrFkzPD09adKkSYLPee/ePc6dO0dwcDAZMmTAwsKCfPnykTlz5kS5JiGEEEIkktdbh732OSAOj0Fwbhn4+4LvQbi4Fkp1SNIQhRBCCCFSA2khlsJ4enrSoEGDOMkwUBNip06d4uuvv6Zt27ZxkmEx2/z77788ffo0weecNm0aFSpUoFatWlSoUIFy5cqxefPmD7oOIYQQQiSyB+fh5j512rmAWiPsXaxsocmU2PkdoyD8RZKEJ4QQQgiRmpjdQiw4OJjJkyeze/duHj9+jMFgMFl/8+bNRAsuPdq4ceMb11WuXBnlHV0dOnXqRKdOnQCoU6fOO7f39fUF1PpjgYGBODo6mtQfE0IIIUQKcWRW7HS1L8FCn7D9ijaBIk3g2jZ48QAO/AwNf0iaGIUQQgghUgmzE2Kffvop+/fv5+OPPyZnzpzxtlISQgghhBCJ6PltdXRJAPssUKabefs3mQw39kJ0OBz9Dcp2V0enFEIIIYRIp8xOiG3dupXNmzdTvXr1pIhHCCGEEEK87tjvamF8gEqfgbW9efs754caX8H+KWCIgq1D4eMN765BJoQQQgiRRpndNy5z5sw4OzsnRSxCCCGEEOJ1oc/hzGJ12tIWKn/2fsep/hU45VWnb+6Dy/8kQnBCCCGEEKmT2QmxCRMmMGbMGEJCQpIiHiGEEEII8apTCyAiSJ0u+xFkyPp+x7G2hyY/xc5vHwkRwR8enxBCCCFEKpSgLpPlypUzqRXm7e1Njhw5cHNzw8rKymTbM2fOJG6EQgghhBDpVVQ4HP/95YxOLab/IYo1h0INwHsXBN6Fg9Oh/pgPDlMIIYQQIrVJUEKsTZs2SRyGEEIIIYSI48LfEPRInS7eErIU/LDj6XTQdCrMqQrREerIlWU/+vDjCiGEEEKkMglKiI0dOzap4xBCCCGEEK8yGNSEVQyPQYlz3CwFodoAOPQ/NSm29Tv4aI0U2BdCCCFEumJ2DbECBQrw7NmzOMufP39OgQIFEiUoIYQQQoh0z3snPPVSp/NWgzyVEu/Ytb4Fx9wvz7MLrm5OvGMLIYQQQqQCZifEfH19iY6OjrM8PDycu3fvJkpQQgghEtfR+0eZfXY2z8Oeax2KECKhDs+MnU6s1mExrDNA40mx89uGQ2Ro4p5DCCGEECIFS1CXSYB///3XOL19+3acnJyM89HR0ezevZv8+fMnbnRCCCE+2K3AW3yx6wuilCiOPTjG4iaL0VvotQ5LCPE2907DrUPqdNYiUKRJ4p+jRGsoUAdu7oOA23DoF6g7IvHPI4QQQgiRAiW4hVibNm1o06YNOp2OHj16GOfbtGlDly5d2LlzJ9OnT0/KWNOdo0ePotfrad68uclyX19fdDoder2ee/fumax78OABlpaW6HQ6fH19AahTpw46ne6Nj/379wPwxRdfoNfrmTx5sskxN2zYYDLKqBAidZl3fh5RShQA55+cZ/HlxRpHJIR4p1dbh1UbABZmN+p/t5gC+xYvfx89NAP8bib+eYQQQgghUqAEf7oyGAwYDAby5s3L48ePjfMGg4Hw8HC8vLxo0aJFUsaa7nh6ejJw4EAOHDjA/fv346x3dXVlyZIlJssWL16Mq6urybJ169bx4MEDk8etW7dwd3enYsWKVKlSxbitra0tU6ZMwd/fP2kuSgiRrHwCfNjsY1obaPbZ2Xj7e2sUkRDinfx84MrLlvkZskPpzkl3rmxFoeoX6nR0uNp1UgghhBAiHTD758YrV66QNWvWpIhFvCIoKIhVq1bRv39/mjdvzqJFi+Js06NHDxYuXGiybOHChfTo0cNkmbOzMy4uLiaPCRMm8PTpU9avX4+tra1x2/r16+Pi4sJPP/2UJNclhEhev5//HYNiACBPxjwARBoiGXFoBJGGSC1DE0K8ydHf4OXrliqfg5Xt27f/ULW/g4w51elr28BrW9KeTwghhBAiBUhwDbEYmTJlonLlytSuXZs6derg4eGBnZ1dUsSWNObVhqDHyXtOh+zw+X6zdvn7778pVqwYRYsWpXv37nz11VcMHz7cpOtiq1at+P333zl06BA1atTg0KFD+Pv707JlSyZMmPDGY8+ZM4clS5awd+9ecufObbJOr9fz448/0q1bNwYNGhRnvRAi9bj5/CZbfbYCkMkmE8uaLaPntp7cDLjJFb8r/Pnfn/Qv01/jKIUQJoKfwdml6rRVBqjYO+nPaZMRGk2EtX3U+W3D1NpiSZ2IE0IIIYTQkNktxHbt2kWTJk04fvw4rVu3JnPmzNSoUYORI0eyc+fOpIgxcQU9hhf3k/fxHgk4T09PunfvDkCTJk0ICAgw1vqKYWVlRffu3VmwYAEACxYsoHv37lhZWb3xuAcOHOCrr77it99+w8PDI95t2rZtS9myZRk7dqzZcQshUo655+eioADQy70XmW0z82ONH9Hr1IL6f5z/gyvPrmgZohDidac8IerlaI/lPwZ75+Q5r3t7yFdDnfb3hSMz37q5EEIIIURqZ3ZCrEaNGowYMYIdO3bw/Plz9u7dS6FChZg6dSpNmiTBCEiJzSE7ZMyVvA+H7GaF6OXlxYkTJ+jatSsAlpaWdO7cGU9Pzzjb9u7dm9WrV/Pw4UNWr15N795v/iX59u3bdOjQgb59+/Lpp5++NYYpU6awePFirlyRL8tCpEbX/a+z3Xc7AM62znQp2gWAkllL0qeU2gokSolixKERRERHaBanEOIVkaFwfJ46rdPH1vZKDjodNPtZPS/Awengfyv5zi+EEEIIkczM7jIJcO3aNfbt22d8hIeH06JFC+rUqZPI4SUBM7suasHT05OoqChy5cplXKYoCjY2NsyePdtk21KlSlGsWDG6du1K8eLFcXd359y5c3GOGRoaStu2bSlZsiQzZsx4Zwy1atWicePGDB8+nJ49e37gFQkhkturrcN6u/fG3sreuK5f6X7sv7MfL38vvJ97M/f8XAaXH6xVqEKIGOdXQMhTdbpkG8icL3nPn6MEVOkHx36DqDDYPgK6LEveGIQQQgghkonZLcRcXV2pWrUq27Zto2rVqmzdutVYnH3wYPlC9aGioqJYsmQJ06dP59y5c8bH+fPnyZUrFytWrIizT+/evdm3b99bW4d9+umn+Pn5sXr1aiwtE5YHnTx5Mhs3buTo0aPvfT1CiOTn5efFzltqF/YstlnoVLSTyXorvRWTakzC0kJ9L1hwcQHnn5xP9jiFEK8wRMORV3708hikTRx1vldHtgS4ugm8d2kThxBCCCFEEjM7IZYtWzZCQkJ4+PAhDx8+5NGjR4SGhiZFbOnSpk2b8Pf3p0+fPri7u5s82rdvH2+3yc8++4wnT568sRvkzz//zOrVq/n999+Jiooy/t/FPN70/1eqVCk++ugjZs6UOiJCpCZzz881Tvcp1Qc7y7gDnxR1LmosqG9QDIw6NIqwqLBki1EI8RqvLeB3Q53OXwtyldUmDltHaPTKwDxbvoOocG1iEUIIIYRIQmYnxM6dO8fDhw/5/vvvCQ8PZ8SIEWTNmhUPDw9GjhyZFDGmK56enjRo0AAnJ6c469q3b8+pU6cIDAw0WW5paUnWrFnf2PJrzpw5REZG0qRJE3LmzBnnsWrVqjfG88MPP2AwGD7sooQQyebKsyvsvr0bgGx22ehYpOMbt+3t3hv3LO4A+Ab6MvOsJL+F0MzhV15/WrUOi1G6M+Stpk773YCjs9++vRBCCCFEKvReNcQyZcpEq1atqF69Oh4eHvzzzz+sWLGC48ePM2nSpMSOMV3ZuHHjG9dVrlwZRVFrAsX8G5+yZcuarPfx8XnneQ0GA3PmzMHR0dFkuZubG+Hh8suwEKnFnPNzjNN9SvXB1tL2jdtaWlgyqcYkOm7sSIQhgqWXl1IvTz0qulRMjlCFEDFuH4e7J9Tp7CWgUANt44kpsD+vFigGODBNTZI55dY2LiGEEEKIRGR2C7F169YxaNAgSpcuTY4cOejfvz9BQUFMnz6dM2fOJEWMQgghEuDS00vsu7MPgOz22elQpMM79ymQqQCDyqutURQURh0eRUhkSBJGKYSI48irrcMGqgkprbmUgkqfqdORIbBdegEIIYQQIm0xOyHWr18/7t+/T9++fTl79iyPHz82JsnKlCmTFDEKIYRIgFdbh31W6jNs9DYJ2q978e6Uz14egHtB9/jf6f8lSXxCiHg89Yarm9XpjLnA/d2J7GRTdwTYZ1WnL2+AG3s1DUcIIYQQIjGZnRB7/Pgxa9asYcCAAZQqVSopYhJCCGGmC08ucODuAQBcMrjQrnC7BO+rt9AzsfpEY/H9VV6rOHL/SJLEKYR4zdFZwMsyB1X7gaW1puGYsMsEDcfHzm/9DqIiNAtHCCGEECIxmZ0QA4iOjmbt2rVMnDiRiRMnsm7dOqKjoxM7NiGEEAn0euswa715X6rzOObh6wpfG+fHHB7Di4gXiRafECIeQY/h3Ap12jojVOipaTjxKtMNcldSp59eg+O/axuPEEIIIUQiMTsh5u3tTfHixfnkk09Yt24d69at4+OPP6ZkyZLcuHEjKWIUQgjxFucen+PwvcMA5MqQi7aF2r7XcToV7USVnFUAeBTyiCknpiRajEKIeJz4A6JfDlxToQfYxh1hWnMWFtBsGvCyrtn+KRD4QNOQhBBCCCESg9kJsUGDBlGwYEHu3LnDmTNnOHPmDLdv3yZ//vwMGmTeMOFz586ldOnSODo64ujoSLVq1di6dau5IQkhRLo251xs67C+pftipbd6r+NY6CyY4DGBDFYZAPjnxj/sv7M/UWIUQrwmIhhO/qlOW1hC1f7axvM2ucpCxV7qdEQQ7BilaThCCCGEEInB7ITY/v37mTp1Ks7OzsZlWbJkYfLkyezfb94Xp9y5czN58mROnz7NqVOnqFevHq1bt+bSpUvmhiWEEOnSmUdnOPrgKACuDq60KtTqg46X0yEnwyoNM86POzqO52HPP+iYQoh4nF0Gof7qtHsHcMqtbTzvUm802L387HdxDfgc1DYeIYQQQogPZHZCzMbGhhcv4taVCQoKwtravJo1LVu2pFmzZhQuXJgiRYowadIkHBwcOHbsmLlhCSFEuvRq67DPS3+OlcX7tQ57VZtCbajpWhOAp6FP+fH4jx98TCHEK6Kj4Ojs2HmPgdrFklD2ztBgbOz81u8gOlK7eIQQQgghPpCluTu0aNGCvn374unpSeXKlQE4fvw4/fr1o1Wr92+ZEB0dzerVqwkODqZatWrxbhMeHk54eLhxPjAwEIDIyEgiI00/lEVGRqIoCgaDAYPB8N5xpReKohj/Nff5MhgMKIpCZGQker0+KcIT6VTM6/r117dQnX50muMPjwOQ2yE3TfI2SbTnalSlUXR80pHAiEC2+m6lbu66NMjbIFGOndrJfSk+lO7yBiyf3wLAUKAe0VmKwgfeT8lyX5bqiv7UIiwenIXHl4k+9juGyv2S7nwi1ZP3S5FSyb0pUiK5LxNPQp9DnRKTCUmg58+f06NHDzZu3IiVldoSISoqilatWrFo0SKcnMwrCPvff/9RrVo1wsLCcHBwYPny5TRr1izebceNG8f48ePjLF++fDn29vYmyywtLXFxcSFPnjxmt1wT5omIiODOnTs8fPiQqKgorcMRIl1QFAXPIE98o30BaG/fnnLW5RL1HOcjzrM6ZDUA9jp7BmUchIOFQ6KeQ4h0R1GodW0cmUN8ADhcaBhPM5bUOKiEyxR8g1rXfkCHQqSFHbtLTCHcKpPWYQkhhBBCGIWEhNCtWzcCAgJwdHR843ZmJcQUReHOnTtky5aNe/fuceXKFQCKFy9OoUKF3ivQiIgIbt++TUBAAGvWrOHPP/9k//79lChRIs628bUQy5MnD0+fPo1zkWFhYdy5cwc3NzdsbW3fKzat9OrViyVLltC3b1/mzp1rsm7AgAHMnTuXTz75hIULFxq3fV2jRo0YNmwY9evXf+u5du/eTZ06dbhz546x6+qFCxfMijcsLAxfX1/y5MmT6p5rkbJFRkayc+dOGjZsaEzAC9WJhyfot0dtmZEvYz5WN1+NpYXZjX7fSlEUhh4ayp47ewCom7su02pOQ6fTJep5Uhu5L8WH0N06hOXSNgAoOUoR1WcPJMJrKjnvS/3mr7A4txQAQ6lORLea8449RHol75cipZJ7U6REcl8mnsDAQLJmzfrOhJhZ354URaFQoUJcunSJwoULv3cS7FXW1tbG41SoUIGTJ0/y66+/Mm/evDjb2tjYYGNjE2e5lZVVnBsmOjoanU6HhYUFFhZml0rTlE6nI0+ePKxatYoZM2ZgZ2cHqImnFStWkDdvXuO16XQ6mjRpwsKFC02OYWNjQ4YMGXjwIHZo9MGDBxMYGGiyrbOzMxYWFixZsoQ2bdpw7NgxTp48SZUqVRIcb0wc8f0/CJEY5N4ypSgKf1z8wzjfr2w/7GzskuRcY6qN4dyTc/iF+bH37l6239lOy4Itk+RcqY3cl+K9HI9NHumqD8YqkVuxJ8t92fAHuLoJwp5j8d/fWFTsDfniL3chBMj7pUi55N4UKZHclx8uoc+fWZkiCwsLChcuzLNnz94rqIQwGAwmrcDSq/Lly5MnTx7WrVtnXLZu3Try5s1LuXKm3aJsbGxwcXExeWTOnBlra2uTZXZ2dnG2tba2RlEUFi1aROfOnenatSuenp7JfblCCDMcfXCUM4/PAJDfKT9N3Zom2bmy2GVhdNXRxvmfjv/Eo+BHSXY+IdK0x1fg+g512ikPlGyjaTjvLUMWqB/7vsCWoepAAUIIIYQQqYjZ/WsmT57M0KFDmTt3Lu7u7h908uHDh9O0aVPy5s3LixcvWL58Ofv27WP79u0fdNy36bypM09DnybZ8eOT1S4rq1qsMnu/3r17s3DhQj766CMAFixYQK9evdi3b1+ixrd3715CQkKoU6cOhQsXpkaNGvzyyy9kyJAhUc8jhPhwiqKYjCzZv0x/9BZJO5hFg3wNaF6gOZtvbuZF5AvGHh3L3Ppz033XSSHMduSVkSWrfgH6VPzrb4VecHoxPLwAj/6DUwugSl+toxJCCCGESDCzE2KffPIJISEhlClTBmtra2N3vhh+fn4JPtbjx4/55JNPePDgAU5OTpQuXZrt27fTsGFDc8NKsKehT3kc8jjJjp+YunfvzvDhw7l1Sx2J6vDhw6xcuTJOQmzTpk04OJgWuh4xYgQjRoxI0Hk8PT3p3Lkzer0ed3d3ChQowOrVq+nZs2diXIYQIhEdvn+Y80/OA1AoUyEa5WuULOcdXnk4Jx6c4EnoEw7fO8y66+toX6R9spxbiDQh8AFcePnjmK0TlP9E23g+lIUemk8Hz5ef2fZMhJJtwSGbtnEJIYQQQiSQ2QmxGTNmJNrJteial9Uua6o5Z7Zs2WjevDmLFi1CURSaN29O1qxxj1W3bt04xfednZ0TdI7nz5+zbt06Dhw4YFzWvXt3PD09JSEmRArzeuuwfmX6JXnrsBhONk6M8xjHl7u/BGDqyalUzVUVVwfXZDm/EKne8d/B8HII8Ip9wCYNjNiapzKU/QjOLYPwANg1Dtr8pnVUQgghhBAJYnZCrEePHkkRR7J5n66LWurduzcDBgwA4Lff4v+QmSFDhvce4GD58uWEhYVRrVpsMVxFUTAYDFy7do0iRYq813GFEInv4L2D/Pf0PwAKZy5Mw3xJ15o2PrVy16Jd4Xasu76OkKgQxhwew/xG87HQpa6BS4RIduEv4NTLAW301lDlc23jSUwNxsGVTWpC7NxSqNAT8lTSOiohhBBCiHd6728xly5d4sKFC8bHpUuXEjMu8VKTJk2IiIggMjKSxo0bJ/rxPT09+eabbzhz5gwHDhzgzJkznD9/npo1a7JgwYJEP58Q4v0oisJv52KT4l+U+UKTRNTQikPJmSEnACcenmDl1ZXJHoMQqc7pxWrCCKB0J8joom08ickhO9R9pUTDlm/AEK1dPEIIIYQQCZTgb1MHDx6kUqXYX/yqVq1KuXLlKFu2LGXLlqV06dLs2rUrSYJMz/R6PVeuXOHy5cvo9fF3jQoPD+fhw4cmj6dP3z1wwLlz5zhz5gyffvop7u7ulChRAnd3d9zd3enatSuLFy8mKkpGjRIiJdh3Zx+Xn10GoJhzMerlradJHA7WDvxQ/Qfj/C+nf+FW4C1NYhEiVYiOhGOvlDXwGKRdLEml0qeQ4+VASw/Ow+lFmoYjhBBCCJEQCU6IzZkzh48//thk2d69e/Hx8eHmzZsMHjw4Th0rkTgcHR1xdHR84/pt27aRM2dOk0eNGjXeeVxPT09KlChBsWLF4qxr27Ytjx8/ZsuWLR8UuxDiwymKwpzzsbXDtGodFqNqzqp0KdoFgLDoMEYdGkW0tAgRIn6X1kPgXXW6SBPIVlTbeJKC3hKa/Rw7v/sHCH6mXTxCCCGEEAmQ4Bpip06dYuTIkSbLcufOTb58+QD4+OOPad68eeJGl04tWrTores3bNhgsu27tn/TcWfNmvXGbV1cXIiOli+4QqQEe27v4arfVQBKZClBnTx1tA0IGFJhCIfvH+bOizuce3KOJZeX0Mu9l9ZhCZGyKAocnhk7nxZbh8XI5wGlO6sjaYY9hz0/QMtftY5KCCGEEOKNEtzE4O7duzg5ORnnFy9ejItLbA0MZ2dnnj2TXwOFECIxGRQDv52PrR32Zdkv0el0GkaksreyZ2L1iehQY5l9djY3nt/QOCohUpibe+GROhAGrhXUpFFa1vAHsM6oTp9eDPfOaBuPEEIIIcRbJDghljFjRm7ciP2y065dO+zt7Y3zPj4+b+3WJ4QQwny7bu3iuv91AEplLUVN15oaRxSrfI7yfFLiEwAiDBGMPDSSSEOkxlEJkYK83josBSSzk1RGF6jz/csZBbZ8CwaDpiEJIYQQQrxJghNiVapUYcmSJW9cv2jRIqpUqZIoQQkhhFBbh809H1ub8YuyX6SI1mGvGlBuAPmd8gNw6dklPP/z1DgiIVKIBxfUFmIAmd2geEtNw0k2VT6HbMXV6Xun4exf2sYjhBBCCPEGCU6Iff311yxevJihQ4fy+PFj4/LHjx/zzTffsHTpUr7++uskCVIIIdKjHb478H7uDUDpbKWpnqu6xhHFZWtpy6Tqk9Dr1FFw552fZ6x3JkS6duSVOp3VBoBF/CNFpzl6K2g2NXZ+1zgI8dMsHCGEEEKIN0lwQqxu3brMmjWLmTNnkjNnTjJnzoyzszM5c+Zk9uzZzJgxg3r16iVlrEIIkW5EG6JNRpZMKbXD4lMqWyl6u/cGIEqJYuShkURER2gclRAaCrgLF9eq03bOUPYjbeNJbvlrQcl26nSoH+ydpG08QgghhBDxSPAokwBffPEFLVu2ZM2aNVy/rta0KVy4MB06dCBPnjxJEqAQQqRH23y34RPgA0C57OWolrOaxhG9Xf8y/dl/dz/X/K9xzf8av5//nUHl0/CIekK8zbG5oLwcqbnyZ2Bt//bt06JGE+HadogMhlMLoPwnkLOM1lEJIYQQQhiZlRADyJMnD0OGDEmKWIQQQgBRhih+P/+7cT4ltw6LYaW34scaP9JlcxeiDFF4XvSkTp46lM5WWuvQhEheoc/h9CJ12tIWKvfVMhrtOLlC7e9g11hQDLD5W+i9HSwS3DlBCCGEECJJyacSIYRIYbb6bMU30BeACjkqUNmlsrYBJVBR56L0K90PUAcEGHloJGFRYRpHJUQyO70QIoLU6bLdIENWbePRUtUvIEthdfruCbiwUtt4hBBCCCFeIQkxIYRIQVJj67BX9SnVB/cs7gD4Bvoy6+ysd+whRBoSFQ7HYl6/OrWYfnpmaW1aYH/nGLUFnRBCCCFECiAJMSGESEE23dzE7Re3AajsUplKLpU0jsg8lhaWTKoxCWsLawD+uvwXpx+d1jgqIZLJf6sh6KE6Xaw5ZCmobTwpQcF6ULyVOh38BPb9pG08QgghhBAvSUIshfn999/JmDEjUVFRxmVBQUFYWVlRp04dk2337duHTqfjxo0buLm5odPpWLkybneEkiVLotPpWLRokXGf1x96vZ7MmTOj1+vZt29fEl+lECI+kYZIk9ZhX5T9QsNo3l+BTAUYWG4gAAoKow6NIiQyROOohEhiigJHXmkRWX2wdrGkNI1/BKuXAwuc+AMeXtQ2HiGEEEII3jMh9vz5c/7880+GDx+On58fAGfOnOHevXuJGlx6VLduXYKCgjh16pRx2cGDB3FxceH48eOEhcXW49m7dy958+alYEH1F+g8efKwcOFCk+MdO3aMhw8fkiFDBgA8PDx48OCB8dGpUyeaNGnCvXv3uHr1Kvfu3cPDwyMZrlQI8bqNNzZyL0h9H62asyoVclTQOKL393GJjymXvRwAd4Pu8r/T/9M4IiGS2PWd8OSqOp2nKuRJHbX/kkWmPFDzG3VaMcCWoWoCUQghhBBCQ2YnxC5cuECRIkWYMmUK06ZN4/nz5wCsW7eO4cOHJ3Z86U7RokXJmTOnSSutffv20bp1a/Lnz8+xY8dMltetW9c4/9FHH7F//37u3LljXLZgwQI++ugjLC3VAUWtra1xcXExPuzs7LCxscHFxYUcOXLg4uKCtbV10l+oEMJEZHQk887PM85/WfZLDaP5cHoLPROrT8TO0g6AVV6rOHr/qMZRCZGEjsyMna4+SLs4UiqPgeBcQJ2+fUTtXiqEEEIIoSFLc3f4+uuv6dmzJ1OnTiVjxozG5c2aNaNbt26JGlxS8GnfgainT5P1nJZZs5J/7ZoEb1+3bl327t3L999/D6gtwb777juio6PZu3cvderUITQ0lOPHj9O7d2/jfjly5KBx48YsXryYUaNGERISwqpVq9i/fz9LlixJ9OsSQiSeDTc2cD/4PgDVc1WnbPay2gaUCPI65uWr8l/x0wm1ZtCYI2NY12odGa0zvmNPIVKZe2fA96A6naUwFGmqbTwpkaUNNJ0Kyzqo8ztGQZEmYOuobVxCCCGESLfMToidPHmSefPmxVnu6urKw4cPEyWopBT19ClRjx5pHcZb1a1bl6+++oqoqChCQ0M5e/YstWvXJjIykt9/V+sLHT16lPDwcJMWYgC9e/fmm2++YeTIkaxZs4aCBQtStmxZDa5CCJFQEdER/HHhD+N8aq0dFp8uxbqw5/Yejj88zsPgh/x88md+qP6D1mEJkbhebR3mMQAspERrvAo3hKLNwWszBD2C/VOg8SStoxJCCCFEWvP4SoI2MzshZmNjQ2BgYJzl165dI1u2bOYeLtlZZs2a4s9Zp04dgoODOXnyJP7+/hQpUoRs2bJRu3ZtevXqRVhYGPv27aNAgQLkzZvXZN/mzZvz+eefc+DAARYsWGDSgkwIkTKtv76eh8HqDwo1XWtSOltpjSNKPBY6C36o/gPt/m1HcGQw673XUz9vfWrnqa11aEIkDj8fuPyPOp0hG5Tuom08KV2TH+HGbogKg2NzoVx3yF5c66iEEEIIkVZc/hf+6p6gTc1OiLVq1YoffviBv//+GwCdTsft27cZNmwY7du3N/dwyc6crotaKVSoELlz52bv3r34+/tTu7b6xTFXrlzkyZOHI0eOsHfvXurVqxdnX0tLSz7++GPGjh3L8ePHWb9+fXKHL4QwQ3h0OH/8F9s6LLXXDotPLodcfFfpO8YeGQvAuKPj2JB9A042ThpHJkQiODZHLRQPUPlzsLLVNp6ULrMb1BgC+34CJVotsN9jI+h0WkcmhBBCiNTu+R34d0CCNze7Tf/06dMJCgoie/bshIaGUrt2bQoVKkTGjBmZNEmavSeWunXrsm/fPvbt20edOnWMy2vVqsXWrVs5ceJEnO6SMXr37s3+/ftp3bo1mTNnTqaIhRDvY+21tTwOeQxAnTx1KJm1pMYRJY22hdpS07UmAE9Dn/Lj8R81jkiIRBDiB2eXqtNW9lCpj7bxpBbVB0OmfOq070G4tE7beIQQQgiR+kVHwdpPISwgwbuY3ULMycmJnTt3cvjwYc6fP09QUBDly5enQYMG5h5KvEXdunX58ssviYyMNLYQA6hduzYDBgwgIiLijQmx4sWL8/TpU+zt7ZMrXCHEewiLCuPP//40zn9RJu3UDnudTqdjnMc42vzThhcRL9jis4UG+RrQMF9DrUMT4v2d9ITIEHW63Mdg76xtPKmFlR00nQIrXnYv3T4KCjcGGwdt4xJCCCFE6rV/Mtw5pk475gbeXUfMrBZikZGRWFpacvHiRapXr84XX3zBd999J8mwJFC3bl1CQ0MpVKgQOXLkMC6vXbs2L168oGjRouTMmfON+2fJkgU7O7vkCFUI8Z7WXFvDk9AnANTPW5/iWdJ2HZ3s9tkZUWWEcX7C0Qk8C32mYURCfIDIMDjxcpAhnQVUS7sJ7SRRtKmaBAN4cR8O/KxtPEIIIYRIvXwOwIFp6rROD61nJ2g3s1qIWVlZkTdvXqKjo82OT5jHzc0NRVHiLM+XL1+8y319fd96vOfPn8e7fNGiRQAYDAZzQxRCfIDQqFCT1mH9y/TXMJrk0zx/c3bd2sXu27vxD/dnwrEJ/FLnF3RSP0ikNudXQLCa0KZEG7U2ljBPk5/g5l6IjoCjv6kF9rMW1joqIYQQQqQmwU9h7WfAyzxJvVGQu2KCdjW7htjIkSMZMWIEfn5+5u4qhBDipb+9/uZZmNo6qmG+hhR1LqpxRMlDp9MxuupoMtuo9Q13397NZp/NGkclhJkMBjj6yi+PHgO1iyU1y1JQrScGYIhUC+zH86OfEEIIIUS8FAU29Iegh+p8gTpQ/asE7252Qmz27NkcOHCAXLlyUbRoUcqXL2/yEEII8XYhkSEsuLgAAB26dNM6LEYWuyyMrjbaOP/j8R+NAwsIkSp4bYFn3uq0W01wlc8/763G1+CUV52+uReu/KttPEIIIYRIPY7Nges71OkM2aDtH2CR8DSX2UX127RpY+4uQgghXrHSayV+YWor28ZujSmcOf11EWqYryFN8zdlq89WXkS8YOyRscypP0e6TorU4cis2GmPQdrFkRZY20OTH2FVd3V+2wgo1ACsM2gblxBCCCFStvtnYefY2Pm2v0PGHG/ePh5mJ8TGjh377o2EEELEKzgymIUXFwJq67B+ZfppHJF2RlYZycmHJ3ka+pRD9w6x3ns97Qq30zosId7uzonYEYyyFYfCMlLqByvWAgrWgxt7IPAuHPwf1B/97v2EEEIIkT6Fv4A1vdWSC6D+QFnI/MEeze4ymdrEV4BeJC55joVIuBVXV/A8/DkATfM3pWCmgtoGpCEnGyfGe4w3zk89OZX7Qfc1jEiIBDj8a+y0x0CQVo0fTqeDpj+DhZU6f2QmPLuhbUxCCCGESLk2fwN+N9XpXOWh3vv9kGZ2Qiw6Oppp06ZRuXJlXFxccHZ2NnmkFFZW6oeqkJAQjSNJ+yIiIgDQ6/UaRyJEyhYUEcSiS4sAsNBZpOvWYTFq5a5Fm0JtALX13JjDYzAoMuqtSKGeesPVl4NAZMwJpTpqG09akrUQeAxQp6MjYOswKbAvhBBCiLjOrYALq9Rp64zQYQFYWr/XoczuMjl+/Hj+/PNPvvnmG0aNGsXIkSPx9fVlw4YNjBkz5r2CSAp6vZ5MmTLx+LFaqNne3l5q07yFwWAgIiKCsLAwLMwoQmcwGHjy5An29vZYWpp9OwmRriy7soyA8AAAmudvTn6n/BpHlDJ8V+k7jj04xsPghxx/eJxVXqvoWqyr1mEJEdfR2RiH9K7S770/fIk3qDUULvwNgffAe6c6eEGx5lpHJYQQQoiU4qm32josRssZ4Pz+36nMzmAsW7aM+fPn07x5c8aNG0fXrl0pWLAgpUuX5tixYwwalHKKy7q4uAAYk2LizRRFITQ0FDs7O7MThxYWFuTNm1cSjkK8xYuIFyy+vBgAvU7P52U+1ziilCOjdUZ+8PiBvjv7AvDL6V+onqs6eR3zahyZEK8IegLnlqvT1g5Qoaem4aRJ1hmg0URY00ud3/a9WlvMyk7buIQQQgihvahw9TNCZLA6X647lOrwQYc0OyH28OFDSpUqBYCDgwMBAWprhxYtWjB6tHn9Nn/66SfWrVvH1atXsbOzw8PDgylTplC0aFFzw4qXTqcjZ86cZM+encjIyEQ5ZloVGRnJgQMHqFWrlrG7aUJZW1ub1apMiPRo6eWlvIh4AUCLAi3I55hP44hSlmq5qtG5aGdWea0iNCqUUYdHsbDxQvQW0hVbpBAn50N0uDpdoSfYZdIymrSrZFs4vRB8DsDz23BoBtQdrnVUQgghhNDazrHw8II6nbUINJ36wYc0OyGWO3duHjx4QN68eSlYsCA7duygfPnynDx5EhsbG7OOtX//fr788ksqVapEVFQUI0aMoFGjRly+fJkMGRJvuG29Xi/1rd5Br9cTFRWFra2t2QkxIcTbBYQH8Nflv4CXrcNKS+uw+Hxd4WsO3zvM3aC7nH18lqVXltKjZA+twxICIkLgxHx12sISqvbXNp60TKeDZtNgrgcYouDQL1Cmywd1hxBCCCFEKue1FY7PVaf1NtBhodqy/AOZ3aynbdu27N69G4CBAwcyevRoChcuzCeffELv3r3NOta2bdvo2bMnJUuWpEyZMixatIjbt29z+vRpc8MSQogU66/Lf/EiUm0d1rpQa/I45tE4opTJ3sqeiTUmokPtfj3zzExuPJeR5kQKcG4ZhPqp0+7twSm3tvGkddmKxiYdo8Nhm7QQE0IIIdKtgHuw4YvY+caTwMU9UQ5tdguxyZMnG6c7d+5M3rx5OXr0KIULF6Zly5YfFExM98s3jVYZHh5OeHi4cT4wMBBQu/tJl8gPE/P8yfMoUpK0cF8GhAew9PJSACx1lvQu3jtVX09SK+1cmo+KfcTSq0uJMEQw8uBIFjZaiKVFyhm0Iy3cl8IMhmgsj8wmpkpmZOX+kAL/79PcfenxNZYX/kYX9AiubSXq8maUwo20jkqYKc3dlyLNkHtTpERyX8bDEI1+7adYvPxh0lCkGdFle7zzs1hCn0OdoqSMMa0NBgOtWrXi+fPnHDp0KN5txo0bx/jx4+MsX758Ofb29kkdohBCmG1n6E72h+8HoKJ1RdrYt9E2oFQgUolkzos5PDE8AaCBbQPq2NbRNiiRbuXyP0El39kAPM7oztFC32kcUfrh6neEird+ByDIOjt7i/+IwUJG9hRCCCHSiyIPNlD84ToAQqyc2VdsIpGWDu/cLyQkhG7duhEQEICjo+Mbt3uvhNj169fZu3cvjx8/xmAwmKwbM2aMuYcDoH///mzdupVDhw6RO3f8XRHiayGWJ08enj59+taLFO8WGRnJzp07adiwodQQEylGar8v/cP8aflvS0KiQrC0sOSflv+QM0NOrcNKFf57+h+9dvbCoBiwtLBkaeOlFMlcROuwgNR/XwozKAr6hY2weHAWgKiua1AK1NE2pjdIk/eloqBf2hqL20cAiK49HEONb96xk0hJ0uR9KdIEuTdFSiT3pSnd7SPol7ZBpxhQdBZEf/wvSp6qCdo3MDCQrFmzvjMhZnYflPnz59O/f3+yZs2Ki4sLOp3OuE6n071XQmzAgAFs2rSJAwcOvDEZBmBjYxNv4X4rKyu5YRKJPJciJUqt9+WyC8sIiQoBoH3h9uTNlFfjiFKP8jnL08e9D/P/m0+UIYoxx8awsvlKrPQp5z5IrfelMIPvIXiZDMOlFJZFGqhF31OwNHdfNp8Gv9cEJRr94Rnoy3UDeS9NddLcfSnSDLk3RUok9yUQ4gf/9AdFbYClqzMcywI1E7x7Qp8/s4vqT5w4kUmTJvHw4UPOnTvH2bNnjY8zZ86YdSxFURgwYADr169nz5495M8vIwgJIdKGZ6HPWHF1BQBWFlZ8WupTjSNKffqV6UfhzIUBuOZ/jbnn52ockUh3jsyKnfYYlOKTYWlSjpJQua86HRUK20doG48QQgghkpaiwD8DIPCeOu9WE2omTQtxsxNi/v7+dOzYMVFO/uWXX7J06VKWL19OxowZefjwIQ8fPiQ0NDRRji+EEFpZdGkRoVHqe1mHIh1wyeCicUSpj7Xemh9r/IilTm3MvODiAi4+vahxVCLdeHwVrm1Tpx1zQ8m22saTntUdDhmyq9NXNoL3bm3jEUIIIUTSOTEfvDar03bO0O4PsNAnyanMToh17NiRHTt2JMrJ586dS0BAAHXq1CFnzpzGx6pVqxLl+EIIoYWnoU9ZeXUlANYW1tI67AMUcy7G52U+ByBaiWbkoZGERYVpHJVIF46+0jqs2heQgrrrpju2TtDwh9j5rd9BVPibtxdCCCFE6vTgAuwYGTvfZi445kqy0yWohtjMmTON04UKFWL06NEcO3aMUqVKxembOWjQoASfPIUMcCmEEIlqwcUFhEWrSZtORTuR3T67xhGlbn1K9WHvnb1cfnaZmwE3mX12Nt9W+lbrsERa9uIhXPhbnbZxgvKfaBuPgDJd4PQiuHMMnnnD0d+g5tdaRyWEEEKIxBIRDGt6Q3SEOl/1CyjaJElPmaCE2C+//GIy7+DgwP79+9m/f7/Jcp1OZ1ZCTAgh0ponIU/420v9Im2rt6VPqT4aR5T6WVlYMan6JDpv6kyEIYIll5dQL289yucor3VoIq06/nvsh7FKvcEmo7bxCLV+W7Of4Y/aaoHdAz9D6c7g5Kp1ZEIIIYRIDFu+g2fX1WmX0tBgXJKfMkEJMR8fn6SOQwgh0gTPi56ER6tdeToV7URWu6waR5Q2FMpciAHlBvC/0/9DQWHU4VGsabkGeyt7rUMTaU34Czi5QJ22sILKn2sbj4iVszRU7AMn50NkiNqlouMiraMSQgghxIe6sBrOLVWnrR3Uv++WNkl+WrNriL0uKiqKoKCgxIhFCCFStUfBj1jttRoAO0s7ern30jiitOWTEp9QNltZAO68uMMvp395+w5CvI8zf0F4gDpdujM45tQ2HmGq3kiwf/lDw6X1cHOfpuEIIYQQ4gP53YRNQ2Lnm0+HLAWT5dQJToht3LiRRYsWmSybNGkSDg4OZMqUiUaNGuHv75/Y8QkhRKrx539/EmFQu1l1KdpFWoclMr2Fnok1JmKrtwVgpddKjj04pnFUIk2JjoRjc2LnPQZqF4uIn11m0y4UW76DqAjNwhFv8eIRFnsnUePaBCyOz5H/JyGEEHFFRah1wyJeqPOlu6h1Q5NJghNi//vf/wgODjbOHzlyhDFjxjB69Gj+/vtv7ty5w4QJE5IkSCGESOkeBj9k7fW1gNo6rKd7T20DSqPyOebjqwpfGefHHB5DUIS0UhaJ5NIGCLijThduDNmLaRqOeIOyH4FrRXX6qRecmKdtPMLUEy/4ZwDMcEd/5BeyBF9Hv2sMzK0G1xJnpHohhBBpxO7xcP+sOu1cEJpPS9bTJzghdunSJTw8PIzza9asoWHDhowcOZJ27doxffp0Nm7cmCRBCiFESjf/wnwiDZEAdCvWDWdbZ40jSru6FutKZZfKADwIfsDPp37WOCKRJigKHPk1dr66DBKUYllYqAX20anz+yZD4ANNQ0r3FAV8D8HyzvBbZTj7V+zAFDGeecPyjrCsIzy9rk2cQgghUo7rO+HobHXawgo6LEj2gYwSnBB78eIFWbJkMc4fOnSI+vXrG+dLlizJ/fv3Ezc6IYRIBe4H3Wed9zoA7C3t6Vmyp7YBpXEWOgt+qP4D9pZqQf1119dx4O4BjaMSqd7NffDwP3U6V3nIV13TcMQ7uJaHCj3V6Ygg2Dla03DSregouLgO5teDRc3h2rbYdTaORFcbyJGC32HIXSV2+fUdMKcqbB8JYQHJH7MQQgjtvXgI6/vFzjeaALnKJnsYCU6Iubq6cuXKFQCCgoI4f/68SYuxZ8+eYW8vo30JIdKfPy78QZQhCoCPin9EJttM2gaUDrg6uDK00lDj/Lgj4wgIly9W4gMcmRk77TEQdDrtYhEJU3+MWlMM4L/VagslkTwiguH4HzCrPKzpBffPxK5zdIVGE2HIJQz1xvLE0Z3oTzZBe091HYAhSm0VMLM8nF4MhmhtrkMIIUTyMxhgXV8IearOF2kCVfq9fZ8kkuCEWMeOHfnqq6/466+/+Oyzz3BxcaFq1arG9adOnaJo0aJJEqQQQqRUd1/c5R/vfwBwsHKgR8keGkeUfrQv3J7qrmorniehT/jpxE8aRyRSrYf/wY096nSmfFC8lbbxiISxd1aTYjG2DFVbLImkE/QY9kyEX0rC1qHw/FbsuhyloO0fMPi8mlS2dYxdp9NBqQ4w4CTU+g4s1cFRCHkKGwfB/Lpw62jyXosQQghtHP4FfPar0xlzQus5mv0QmeCE2JgxY6hUqRKDBg3i3LlzLF26FL1eb1y/YsUKWrZsmSRBCiFESvXHhT+IUtQvYN1LdMfJxknjiNIPnU7H+GrjyWit1hrYfHMzu27t0jgqkSodmR07XW0A6C21i0WYp3wPyFlWnX58GU7O1zScNOvpdfh3EPziDgd+htBXRpYvUBc+Xg/9DkKZzqC3evNxrDNAvZHw5Qko0SZ2+YPzsLAJrOkDAXeT7DKEEEJo7PZx2DPp5YwO2s2HDFneuktSSvAnPjs7O5YsWfLG9Xv37k2UgIQQIrW4HXibf2/8C0BGq4x8XOJjjSNKf3JkyMHwysMZcWgEABOOTaB8jvIyqIFIuIC7cHGNOm2XGcp9pG08wjwWemg+Hf58Wdd2749Qsh1kzKFtXGmBosDtY2p3Yq8tpussLMG9A3gMAJdS5h87cz7otBh8DsK27+HRRXX5xTVwdTPUGKIObGFl9+HXIYQQImUI9Ye1n4Lyspt8raGQv6amISW4hZgQQghT8y7MI/rlG/rHJT/G0drxHXuIpNCiQAvq5akHgF+YHxOOTkBRFI2jEqnGsblqPSOASp+pLVhE6pK7IpR7+YNEeCDsGqttPKmdIRou/wOeDdVWW68mw6wzqq0oB5+HdvPeLxn2qvw1oe9+aP4/sHv5Q0ZUKOz7EWZXhkvr1cScEEKI1E1R1JbGAbfV+bzVoPYwbWNCEmJCCPFefAN82XRzEwCO1o50L95d44jSL51Ox+hqo8lkkwmAXbd3scVny9t3EgLUEe5OL1an9TZQua+28Yj312Ac2L7ssn5+hdqySZgnIgROzIdZFeDvT+Duydh1GXNBwx/g60vQeBI45U688+otoVIfGHRGLaqse1mSJeA2rO4Ji1rEjgArhBAidTq9EK6oPWuwzQTt/0wRJSokISaEEO9h3oV5GBQDAD1L9jTWsRLayGqXldFVRxvnfzz+I49DHmsYkUgVTi2EiBfqdNmu4JBN23jE+8uQFerFvgew+VsZuTChgp/C3p9ghjts+Rb8fWLXZS8JbX5XW4RVHxybdEwKdpmh6RTof0StSxbj1iGYVws2DYHgZ0l3fiGEEEnj0WXYNjx2vvVvifvDygeQhJgQQpjpZsBNYwukTDaZ6Fa8m8YRCYBGbo1o6tYUgMCIQMYfHS9dJ8WbRUXA8d9fzuig2kBNwxGJoGLv2C58j/6DUwu0jSele3ZDTTL9UhL2T4aQV5JN+WtD97XQ/7CaLLa0Tr64shdTi/R3WQGZ86vLFIP6/zmrnNrNOToy+eIRQgjx/iJCYE0viApT5yt9BsVbaBvTK8xKiEVGRlK/fn2uX7+eVPEIIUSK9/v5301ah2WwkppDKcWIKiPIapcVgAN3D7DBe4O2AYmU6+IaePFAnS7WHLIW0jYe8eEs9NBsWuz8nglq6ydh6s4JWPmR2jXy1ILYLyk6PZTqqNb06vEvFGoAOp02Mep0UKwZfHlc7Q5r7aAuDwtQi/DPrQ7eu7WJTQghRMJtHw5PrqrTOdyh0URt43mNWQkxKysrLly4kFSxCCFEiuft7802n20AZLbJTNdiXTWOSLwqk20mxlaLLag95eQUHgQ90DAikSIpChyZFTvvMUi7WETiylsVyrx8Xw4LkAL7MQwGuLIJPBupxfKvbgJetqC1doCqX8Lgc2pNl1xlNQz0NZY26oiTA09D2VdGgH3qBUvbwYquaks3IYQQKc+l9XB6kTptZQ8dFoCVraYhvc7sLpPdu3fH09MzKWIRQogU7/cLv6O8/BLR27039lb2GkckXlcnTx1aF2wNQHBkMGOOjDG26BMCAO9d8PiyOp2nCuStom08InE1/AFsXo76e3Yp3D2lbTxaigxVW4HNrgirPoI7x2PXObhA/bEw5CI0+REy5dUuznfJ6AJt5sCne8C1Yuxyry3wWxXYOQbCX2gXnxBCCFP+vvDv4Nj5plMhW1HNwnkTs8v6R0VFsWDBAnbt2kWFChXIkMG0q9D//ve/RAtOCCFSkmv+19juux0AZ1tnOhXtpHFE4k2GVR7G8YfHeRj8kGMPjvG31990KdZF67BESnH419hpaR2W9jhkh7oj1K51AJu/gc/2qF0q04vgZ3DyTzjxB4S81m00WzHwGKh2j7S00Sa+95W7AvTZCf/9DTvHQtBDMESqr+nzK9UEX5muYCFlkoUQQjPRkbCmD4QHqPPuHaBcd21jegOzE2IXL16kfPnyAFy7ds1knU6rOgNCCJEMfj//u3G6j3sfaR2WgmW0zsh4j/F8vvNzAP53+n9Uz1WdPI55NI5MaO7+WfA9qE47F4SizbSNRySNSp/BmSVqS8AH5+DMYrXoflrndxOOzlFbxkWFmq5zq6kmgAs1SN0JIwsLKNMFirWAg9Ph6GyIjoCgR/DPF2oisOlUyFNJ60iFECJ92jsJ7r1snZ3ZDVr8ol1NyncwOyG2d+/epIhDCCFStKt+V9l5aycAWe2ySuuwVMAjlwedinTi72t/ExoVyqjDo1jQeAH69NRKRMR1eGbstMeA1J0YEG+mt1QL7C96mfDc/QOUaAP2zpqGlWTunoIjM+HKRnVExhg6CyjZFqoNANfy2sWXFGwcoMFYKP8J7Bj1si4acP8MeDaA0l3UgvyOOTUNUwgh0pUbe+DQDHXawhLaLwBbR01Depv3/hTo7e3N9u3bCQ1Vf32Soe2FEGnZ3HNzjdOflvoUW8uUVRBSxO+bit/g6uAKwJnHZ1h6ZanGEQlN+fvC5Q3qtH3W2OLrIm1yq652CwQI9VeTYmmJwQBeW2FBU/izPlz+JzYZZpUBqvSDQefUIsZpLRn2Kuf80GUZfLwBshWPXX5hpTqS5oFpEBmmWXhCCJFuBD2GdZ9jHLSl/li1q3sKZnZC7NmzZ9SvX58iRYrQrFkzHjxQR+/q06cP33zzTaIHKIQQWrv87DJ77uwBILtddjoU6aBxRCKh7K3smVh9IjrUZtozz8zk5vObGkclNHNsbmzCoMrnYGWnbTwi6TWcoI6iCOpIV/fOaBpOoogMg9OLYU4VWNEFbh+JXZchO9QbrRbKbzoFMufTLs7kVrAu9DsETX8G20zqsshg2DMBfqv8svWc/IAvhBBJwmCA9f0g+LE6X7C+2jo5hTM7ITZkyBCsrKy4ffs29vax9XM6d+7Mtm3bEjU4IYRICUxah5X+FBt9KitCnM5VdKnIR8U/AiDCEMHIQyOJMkRpHJVIdiF+ak0pUIf+rvSptvGI5OGYE+q8LK6PAluGqh/aU6MQPzjwM8woBRsHwdNXavlmLQKtZsFX/0Gtb9Nu19B30VtClb4w6KxaR0738qvO81uwqjssaQ2PLmsboxBCpEVHZ8GN3eq0Qw5oOy9VlKUwO8IdO3YwZcoUcufObbK8cOHC3Lp1K9ECE0KIlODi04vsu7sPgBz2OWhfuL22AYn3Mrj8YNwc3QC4+OwiCy8u1DYgkfxOeUJkiDpdrnv6TRikR1X6QdaXQ73fOwXnUlnXaX9f2PId/FIS9kyM/fUdIF916LoKvjiu1tKyku78gPr6bj5NbTHmVjN2uc9++L2GmhgN8dMuPiGESEvunn6lLIFOTYY5ZNM0pIQyOyEWHBxs0jIshp+fHzY20mpCCJG2zDk3xzjdt3RfrPXWGkYj3petpS2TakzC4mVrgTnn5+Dl56VxVCLZRIbB8T/UaZ0FVP1C23hE8tJbQbOfY+d3jVNriqV0987A6l4wsxycmBeb0NVZqAMEfLoHem2Bok1Sxa/wmshREnpshE5/Qaa86jIlGk78AbPKw4n5EC0thoUQ4r2FBcCaXhDT+6LGV2oX9lTC7L+eNWvWZMmSJcZ5nU6HwWBg6tSp1K2bei5cCCHe5fyT8xy8dxCAnBly0rZQW40jEh+idLbS9HbvDUCUIYqRh0YSGR2pcVQiWVxYGduqpngrtQi3SF8K1FZHWwQIeQZ7Jmkbz5sYDHBtOyxsDvPrwqV1sXXvLO2gcl8YeBo6LU7xhYpTDJ0OSrSCL09CvVFql2lQk6JbvoV5NeHmfm1jFEKI1EhRYNMQtVs6QO5KUHektjGZyeyE2NSpU/njjz9o2rQpERERfPfdd7i7u3PgwAGmTJmSFDEKIYQmXm8dZqW30jAakRj6l+lP4cyFAfDy92LehXkaRySSnMEAR2bHzlcfpF0sQluNJsUmQ055woML2sbzqqhwOPMXzK0GyzvBrUOx6+yzql8wvr6stnRzLqBdnKmZlS3UGqomFEt1il3++DIsaaXWGPP31Sw8IYRIdc4uhYtr1WkbJ2jvqbbKTkXMToi5u7tz7do1atSoQevWrQkODqZdu3acPXuWggULJkWMQgiR7M4+PsuR++rIXa4OrrQu1FrjiERisNZbM6n6JCx1lgD8+d+fXHx6UeOoRJK6tg2eXVen89UAV2lVk245uaoJEVBbXW35VvsC+6H+cHC6Wij/3wHw5GrsuiyFoMUMdcTI2t9J3bvE4pgL2s+H3jsgV7nY5Vc2wuzKsHsChAdpF58QQqQGT7zUeowxWv2aKkc2tnyfnZycnBg5MnU1hRNCCHP8du434/TnpT/HyiJ1/doh3qx4luL0LdOXOefmEK1EM/LQSP5u+beMHppWHZkZOy2tw0S1AXBuGTzzhjvH4cIqKNs1+eN4fhuOzYXTiyEy2HRd3mrgMRCKNJXaYEkpbxW1Dtv55bBrvNqtOjocDk5T75EG46F0J7XLpRBCiFiRobCmN0SFqvMVesaWJUhl3uuvrL+/P9OmTaNPnz706dOH6dOn4+cnI7UIIdKGUw9PcfzBcQDyZMxDi4ItNI5IJLZPS31KiSwlALgZcJPfzv72jj1EqnTnJNw+qk5nKwaFGmobj9CepTU0nRo7v3OMWhA4udw/B2v6wK9l4dicV5JhOrW+XZ9d0HsbFGsuybDkYGGhjjo78DR4DIKYH79ePID1fcGzEdw7rW2MQgiR0uwYBY9e9rDIVhwa/6RtPB/A7L+0Bw4cwM3NjZkzZ+Lv74+/vz8zZ84kf/78HDhwICliFEKIZDXnfGztMGkdljZZWVgxqfok4//tokuLOPv4rMZRiUR35NfYaY+BkmAQqkL1oXhLdTr4MexN4g/yigLXd8HilvBHbbi4Rh3pEMDSFir2URMynf+CPJWSNhYRP1tHaDQBvjwORZrELr97AubXgw1fwotH2sUnhBApxZWNcPJPddrSFjosAGt7bWP6AGZ/Mvzyyy/p3LkzPj4+rFu3jnXr1nHz5k26dOnCl19+mRQxCiFEsjnx4AQnH54EIJ9jPpoXaK5xRCKpFMpciAHlBgCgoDDq0ChCIkM0jkokmmc34MomddrBBUp11DaeJHTN/xqzzs3ir6C/+PnUz/x741+8/b2JNkRrHVrK1fhHddRGgBN/wKNLiX+OqAg4txzmesCy9uDzyg/H9lmgznAYcgla/A+ySB3eFCFLQei2Cj5aC1mLxC4/txRmVYDDv6oDIAghRHr0/A78MyB2vslPkKOEdvEkArNriHl7e7NmzRr0er1xmV6v5+uvv2bJkiWJGpwQQiQnRVHi1A6ztHivUosilehRogd7bu/h/JPz3H5xmxlnZjCiygitwxKJ4ehsQFGnq3wOlmmrRtydF3fY6rOVrT5b8X7ubVzudc0LrqnTdpZ2FM1clBJZShgf+Z3yy/saQKa8UPMb2DtRba21ZSj03Jw49aLCAuDUQjj+u9r17lXOBdQ6ZmW6pupf1NO8wg2gQG04MR/2TYbwAIh4oXaxPb1ITagWaSL1xYQQ6Ud0FKz9FMKeq/MlWkOFXpqGlBjM/kRUvnx5rly5QtGiRU2WX7lyhTJlyph1rAMHDvDzzz9z+vRpHjx4wPr162nTpo25IQkhRKI4/vA4Zx6fAcDN0Y1m+ZtpHJFIanoLPROrT6Tjxo6ERYex4uoK6uetT5WcVbQOTXyI4KdqyxwAaweo2FvbeBLJk5AnbPfdzlafrVx4euGd24dGhXLuyTnOPTlnXGart6Woc2ySrLhzcQpmKpg+k2QeA9Xi6f4+cOsw/LcGSn9AS8KAu7GF8iNemK7LXVkd1KFoM7DQx7+/SFn0VlDtC7Ww/p4J6v8rCvjdhBVdoGB9tXVEtqLvPJQQQqR6+6fAnWPqtFNeaDkzTfwoYPann0GDBjF48GC8vb2pWrUqAMeOHeO3335j8uTJXLgQ+wGtdOnSbz1WcHAwZcqUoXfv3rRr187cUIQQItEoimJSWL1/mf7o5UtLuuDm5MZXFb5i8onJAIw5PIa1rdbiYO2gcWTivZ2YD1Fh6nT5HmCXSdNwPkRAeAC7b+9mi88WTj48iUExxNmmTLYyNM7bmIhrERSuWJhrAde4/Owyl59d5l7QPZNtw6LDOP/kPOefnDcus9HbUDRzUYpnKU7JLCUpkaUEBTIVSPv1E61s1QL7y18mwXaMgiKN1XpS5nj4HxyZBRfXgiHqlRU6tTi+x0DIWzXRwhbJLENWaPmrWutt6zC4fURdfmO32h22cl+oPSxVv88IIcRb+RyAAz+r0zo9dPBMM+95ZifEunZVh6b+7rvv4l2n0+lQFAWdTkd09NtrVzRt2pSmTZuaG4IQQiS6o/ePGltRFHQqSGO3xtoGJJJV12Jd2X17NycfnuR+8H2mnZrGOI9xWocl3kdEiFoTCtQPbVX7axvPewiJDGH/3f1s8dnCoXuHiDJJsqiKZC5C0/xNaZq/Ka4OrkRGRrLlxhaq5axGrby1jNsFhAcYk2Mxj7tBd02OFR4dzoWnF0xanVlbWJu0JCuRpQQFMxVMe0myIo2gSFO4thWCHqq/gDee9O79FAVu7FETYTf3mq7T20DZblDtS8haOGniFskvZ2notQUurYcdoyHwrpoAPTYHLqyCeqOh/CfSAlAIkbYEP4V1fTGWoag3EvJU1jSkxGR2QszHxycp4kiQ8PBwwsNjC1kGBgYCEBkZSWRkpFZhpQkxz588jyIlSa77UlEUZp2dZZz/zP0zDNEGDNFxW2KItGtM5TF03tKZkKgQ1l5fSx3XOlTPVT3OdvJ+mbJZnP4LfagfAIaSbYnO4AKp4P8qMjqSow+Pst13O/vu7SM0KjTONrkdctM4X2Oa5GtCwUyxRdhf/Rz0+n1pb2FPxWwVqZitonFZYEQgV/yumDxeT5JFGCL47+l//Pf0P+MyawtrCmcqTDHnYhR3Lk5x5+IUciqElT6VJ8kaTMDyxh500eEox38nqlTXN3eDi45Ed3k9+mNz0D2+aLJKscuMoUJvDBU/hQzZ1IWp4N5LSmny/bJoSyhQH4ujs7E4OgtdVCiEPINNX6Gc9CS60SSUvB5aRyneIU3emyLVS3H3paKgX98Pi5f1MA1utYiuMiBV/G1L6HOoUxRFSeJYEkSn072zhti4ceMYP358nOXLly/H3l4Kkwoh3s+1yGssCVYHBclhkYMvM36Jhc7sQXhFGnAy/CT/hP4DQEZdRgZlHISdhZ3GUYkEUwzUv/wdDhGPAdhbdAKB9vk0DurNDIoB3yhfLkRe4FLkJUKVuEkwB50Dpa1LU9qqNK56V3RJVK8j1BDK/ej7Jo9nhmfv3E+Pnhz6HOTS58JV70oufS5y6HNgqUtdNcmKPlhHsYcbAHjiUIIjhYaZ1EaxjA4l39N9FHyyHbtIP5N9g62zcyN7E2471yRan7YGbxBvZxfxlBL3VpH7+XGT5fcyVeaSaxdCrbNqFJkQQny4Ao+3UeqeWpM13DIje4tNItwqk7ZBJVBISAjdunUjICAAR8c3l0JIVQmx+FqI5cmTh6dPn771IsW7RUZGsnPnTho2bIiVVSr/pVekGclxXyqKwsfbP+ay32UAfq7xM/Xz1k+Sc4mUT1EUBuwbwNEHRwFo5taMiR4TTbaR98uUS3flXyzXqQX0DflrE91trcYRxaUoClf8rrDVdys7bu/gSeiTONtktMpIg7wNaJyvMRWyV0hQPcOkuC9fRLzAy9/LpCXZrRe33rmfpYUlhZwKGVuRlXAuQaFMhbDWWydKXEkiMhTLedXRBdwGIKrtnygl2kDgAyxOzsPi7GJ04aaF8g25ymOoOgClaHPpJvcG6eX9Unf7KPodI9A9im1RqVjaYqg2EEO1gWAlP9ynNOnl3hSpS4q6Lx+cw3JRU3QGtaVVVJdVKAVTz3ekwMBAsmbN+s6EWKr6+c7GxgYbm7i/vFlZWWl/w6QR8lyKlCgp78v9d/Ybk2FFMxelUYFG0josnfuh+g+0+6cdLyJfsMV3C43cGlE/X9wPAPJ+mcIoChyPHRjDovpgLFLQ/8/N5zfZ4rOFrT5buf3idpz1dpZ21Mldh6b5m1Ldtfp7J48S8750tnKmWoZqVMtdzbgsKCKIK35XuPzssvFf3wBfFGJ/X40yRHHV/ypX/a+y/sZ6ACx1lhTKXEitR+as1iQr4lwEm5TSosrKCppOhpXdALDcNQZu7ob/Vr9WKB91pEiPgVjkrYZFGhhhKzmk+ffLgrXg8/1w9i/Y/QOEPEMXFYb+4M/oz6+ARj9AyXZpYkS2tCbN35siVdL8vgx/ARv6wstkGB4DsSzWRLt43kNCn79UlRATQojEpCgKv517ZWTJsv0lGSZwyeDC91W+Z+ShkQD8cOwHyuUoh7Ots8aRibe6fRTunVanc5SCgvW0jQd4EPSArb5b2eqzlat+V+Ost7SwpHqu6jTL34w6eepgnwpakThYO1DJpRKVXCoZlwVHBnPV76pJ4X6fAB/TJJkSxVW/q1z1u8o61gFqkqxgpoImhfuLZC6CraVtsl8XoCa6CjUE753w4j6cXxG7Tm8NZbpAtYGQrYg28YmUzUIPFXpCiTawfyqcmKcmUwPvwprecOJPNemas4zWkQohxNtt/hb8bqrTucpDvTHaxpOENE2IBQUF4e3tbZz38fHh3LlzODs7kzdvXg0jE0KkB3vv7OWK3xUAijsXp14e7b9Ai5ShZYGW7Lq1i7139uIX5sfEYxOZXnt6ktVvEong8MzYaY+BmrXEeBb6jB23drDVZytnH5+Ns16HjkoulWiavykN8zXEycZJgygTVwarDFTIUYEKOSoYl4VEhsRNkgX6YFBiByuJUqLw8vfCy9+L9d5qSzK9Tm9MkhV3Lk6JLCUo6lwUO8tkqOWn00HTKTBnP0RHqMtsM0GlT6FyX8iYI+ljEKmfXSZo8qOaHNs+HLx3qctvH4F5tdWRKOuNBodsWkYphBDxO7cCLqxUp60zQgdPsEzBJQ8+kNkJsTt37qDT6cidOzcAJ06cYPny5ZQoUYK+ffuadaxTp05Rt25d4/zXX38NQI8ePVi0aJG5oQkhRIIZFANzzs0xzn9R9gtJdggjnU7HmGpjOPv4LM/Dn7Pz1k62+W6jaf6mWocm4vPEC65tVacdc4N7u2Q9fVBEELtv72arz1aOPThGtBIdZxv3LO40zd+Uxm6NyZEh7SdW7K3sKZ+jPOVzlDcuC4kM4Zr/NS49u2RMkt0MuGmSJItWornmf41r/tfYwAZATZLld8pvbEVWMkvJpEuSZSkInZbA2aXgVhPKdQcbh8Q/j0j7shWBj9bA9R2wbTj43QAUOLMYLm2AOsOg0mdp+oumECKVeeoNm7+JnW85A5wLaBZOcjA7IdatWzf69u3Lxx9/zMOHD2nYsCElS5Zk2bJlPHz4kDFjEt6crk6dOqSQmv5CiHRmz+09ePl7AVAyS0lq566tcUQipclql5WRVUcydP9QACYem0jFHBXJlEpG10lXjsyKna7aH/RJX3cjLCqMg/cOstVnK/vv7CfCEBFnmwJOBWiWvxlN8zclr6O0fLe3sqds9rKUzV7WuCw0KhQvP6/YlmR+l7n5/KZJUjFaicb7uTfez73598a/AFjoLCjgVMCku2XRzEUTp9tp0abqQ4gPpdNBkcZQoC4c/13tShnxAsIDYPsIOLUQmkyGwg20jlQIkd5FhcOaXhAZrM6X7Q6lOmgbUzIwOyF28eJFKleuDMDff/+Nu7s7hw8fZseOHfTr18+shJgQQmjBoBhMaodJ6zDxJk3cmrD71m62+W4jMCKQ8UfH87+a/9M6LPGqFw/hwip12sZR7Y6URKIMURx/cJwtPlvYfXs3wTEfGl+RK0MumuRvQrP8zSiSuYi8t7yDnaVdnCRZWFQYXv5qkuzKM7Vwv/dzb5MkmUExxJsky++otiQrnqW4sdtlaqjNJtI4S2uoPkitQ7d7PJxdBijw7Dosaw+FG0PjHyFrIa0jFUKkVzvHwsML6nSWwtBsqrbxJBOzE2KRkZHGkR537dpFq1atAChWrBgPHjxI3OiEeA+KohBtUIiINhAR9fIRHftvZJRCRHQ04S/XRUYrL9dFv/xXMe4XGR13f+MxY9ZHGwh/ddsoAwZFwcZSj521HlsrC2wt9dha6bGxssDWSv9y/uX0K8uM66302Fq+Mv3aNjaWFvIl6wPsvLUT7+dq/cLSWUtT07WmxhGJlGxklZGcfHiSZ2HP2H93Pxt9NmIpY9KkHMfnxdZ7qtgLbN88tPb7MCgGzj0+xxafLey8tRO/ML842zjbOtMoXyOaF2hO6WylZXCOD2RraUuZbGUoky22+Hh4dDjX/K4ZW5FdfnYZb39vopTYESANioEbATe4EXCDjTc3AmrNNjcnN5PRLYtnKU4GqwzJfl1C4JAdWv8GFfvAtu/hznF1+fXtcGMPVO0HtYaCbeqvLSiESEW8tsLxueq03gY6LgTr9PF30uxP9CVLluT333+nefPm7Ny5kwkTJgBw//59smTJkugBipRLURSiDIpJIij8lSRRnGRUTPIpJvH0WvIpIjramJx6PcEUEa3Oh8eTjIqZDn9l27TeE1enAxvLuMk1G5NEWnzJt9cSbO9M1sVuY2GRNhJw0YZo5p6ba5yX1mHiXTLZZmJstbEM2jsIgGmnp9HPrp/GUQkAwoPglKc6bWEFVfonymEVRcHL34stPlvY5rONB8Fxf/BzsHKgXt56NM/fnMo5K2NpIUnSpGSjt6FUtlKUylbKuCw8Opzr/tdNCvdff36dKENskkxBwSfAB58AHzbf3AyoSbJ8jvlMulsWdy6Og7XUChPJxLU89N4O/62BnWPUUU0NkWr37/Mrof5YKPsRWEhyXQiRxALvw4YvYucbTQSXUm/ePo0x+9PblClTaNu2LT///DM9evSgTBn117v/t3ff8XFU9/7/XzOzVb0Xq1nGXcYVV1ogVNMCqaRQEkIgIe178yPl5qbcmx4uNwXSSAKXJJcEEkiAUEMxxcYYY7AtV1wkq1m9b52Z3x+zu9rVrmTJXvXPk8c8dvbM2dmzZiTtvveURx99NDKUUkwNhmFyuLWP3fVdvFXbzpv7VR5pe5OgQVygNTicminB02g5NBW7pqAqCt6gFfCNBdMEb8DAGzCAwJg8x2AOTY3qwTYQpEXCuMG93gYfT9DrzR217xxU366NzZvAZ2qe4VDXIQCW5y9nw6wNY/I8Yno5r/w8rjztSh499Ci9gV4eMR/hWvPaiW6W2PEH8HZZ+0s/ABnFp3S6mu4anjjyBE8eeZIjXUfijjs1J+eUnsPGyo2cXXo2Ts15Ss8nTo1Tc7IkbwlL8pZEyvy6n4Odg0KyjoMEjIG/lSYmR7uPcrT7KE8ceSJSXpFREelFtjB3IUUpReS6c0mzp8kXJyL5FAWWvh8WboRX/sdaKVf3QV8LPHobbPstXPojKF870S0VQkxXhg5/+yR4Qr3fF1wGaz45sW0aZ6MOxN71rnfR2tpKd3c32dnZkfKbb76ZlBSZo2Gyig6/doW26vou+vzRK2Gp0N46YW0cjXDw5LCpkc2uqVZoE33fZpXF3J7gmENTsduGO5eCQ9OizqVEjg1+w6wbJt6Abm1BY2A/YOAL6HiDeijYiroNRh0Plwf1QXWs455AbLkvaAzxL3bq/KEeeT3e4IkrJ4GmKrhsKnY0Hml7k6WlWVSVZLKkJJNZma6T+nCiG3rMypKfWfEZ+ZAjRuzLa77Ma42v0dzfzKHgIa567CrmZM2hPL2c2RmzKc+wbgtTC2XI3HjQg7Bl4OeZDZ89qdMc7zvOU0ef4skjT1LdVh13XFM01s1ax8bKjZxfdr70IprkHJqDqtwqqnKrImUBPRAXkh3oOBATkoEViNZ01/Dk0Sdjyp2ak1xXLrnu3IHb6P3QbZ47T8IzMXqOVDj/69aKps/8B+y15sSj8S34/UVw+vvhgm9DZsmENlMIMQ29dAfUvGLtZ5TAVXdZYf0MclL9+zVNiwnDAGbPnp2M9ogkMAyTI21W+LWzzgq/9jR00+sbfZARDopiwifNCohGEjxFh0sOm/WY6PrDB0+DzhVuR4LgabLSVIVUp41U5/gMpTFNE18wccAWE8YNDtgGhW7xYd2g/ahwzxijXoK6YYYCW4UXD7Ty4oGBsDYrxc6SWZlUlWSwZJYVklXkpJxwWOcTR57gaPdRAFYWrGRtkXzrKkYuw5HBf234Lz71r08BUNdbR11vXVw9p+akLL0sJiSryKigPKOcXFfulPn9Nent+Tt01Vr78y6CgkUjfmint5Nna5/lySNP8kbTG5jE/yJbWbCSjZUbuXD2heS4cpLUaDER7Jo9MjQyLKAHONR1KCYk29++P+FqoT7dR0NfAw19DSd8LofqGDo4GxSepdvT5feBGJA9Gz74BzjyEjz5FWgOBfS7HoJ9/4Sz/h9suA3s7gltJgCGAaYBpm7dGnrUfTNBWfT9qC2uzqDzJnpczP0hHjeC51KDQeYeP4j6ei3YXaDaQHNYqxSrttCtHbRQuWpPcMweux8+pjlA1Sb6/5IQw6vZDJt+YO0rKrz3t5Ay897vjPpT+ooVKxL+8VYUBZfLxdy5c7nhhhs477zzktJAMTzDMDna1mf1+gqFX9UjDL9KstwsKclgaWkWiwpTqdn9OhsvuoBUt3PKBU/CoihKZEjieDBNk4BuRsI03xABW3SQ5hscsA3qJRcO6zwBHY9fp6G9F48eex129gd45Z1WXnlnICRLc9pYXJwRE5Kdlp+KLTT0MmgE+fXOX0fq37biNrm+xahtKNnAl8/4Mv/75v/SqXTi1b1xdXy6L7L63WBp9jTKM8qpyKiICczKM8rJcCR3MvhpzTTh1Z8O3B9B77D+QD8vHHuBJ448web6zTGTsYctylnEpZWXcsnsSyhOO7Xhl2Jys2t2FuYsZGHOQq6Zdw0AASPA4c7DkVUtWz2ttHnaaPO20eZpo8PXccLz+g0/jX2NCeedi2uDao8LyYbqiZbhyJC/WTNF5TnwqZfgzfvg+e+ApwMC/fDCd+DN/7Xm9hkcJA0bCg0XUo0mgIoqnwY0oAqg4S9j9AxKbKimhoKyyH6iwM02KFxLFNANEcKdMKCzDdGeEwSA8ntneupvh7/dNPDzfO5XoGJmTiMz6kDskksu4Ze//CWnn356ZM6wbdu2sXPnTm644Qb27NnDBRdcwMMPP8xVV12V9AbPZNHhV7j3156GbnpGEH7NynRxemkmp4eGnJ1ekklu2sDcJ4FAgJ6DkJPqwG6XiYHFyCiKYg0htalkuOxJP38gEOCf/3yCZRvOY39zH7vru9nd0MXu+m5ae30xdXt9QV4/2s7rRwdWgHPaVBYWZ7BkVgZG6jZqumsAWF20mtVFq5PeXjEzfHD+B0l/J51LL72UjkAHtT21HO0+Sk1XDTU91pCrYz3HYib2DusN9EZ6owyW48qxepKllzM7czbl6eWRnmVu2yToETCZHNk0sDR48XKYnXilWL/u55X6V3jyyJO8eOzFhAFmRUYFl1ZeyqWVlzInc87YtVlMenbVzoKcBSzIWZDweNAI0uHtsIKyUEgWvo0ua/e20+HtSNjzMFrACNDU10RTX9OI2pbjyokEZHnuvLhhm+EyCc+mAc0Gq2+CqmvgxR9Y84mZOnQdszYxBZjWCsi6f7ym+x0bijZE4BYV3tndUHmuNfdUxqyJbrE4EdOEf9wG3fXW/Yqz4JwvTWybJtCok4/W1lb+7d/+jf/4j/+IKf/Od75DTU0NzzzzDN/85jf5r//6LwnEToFhmNS094d6fnWG5vwaefgVDr1OL7UCsLw0mfhXTE2KAqXZbioLMrhkyUCPjeZubyQc2x3qGVnf6Yl5rC9o8PaxTt4+1kbqafejOqzyowfP4vaet6malcmSkgwWFWeQ4pAgWIyOoigUphZSmFoYF7AGjSCNfY2ROYmit4behoQflNu97bR729nRvCPuWGFKYczQy3CvstK0Uuxa8sPoSe/Vnw3sn/m5mG+wdUNn2/FtPHnkSZ6teZYef0/cwwtSCrhk9iVsnLORxTmLJTwQI2JTbeSn5JOfkn/CuuHwbLjgLNLzbITh2fH+4xzvPz6idua4ck4YnOW6csl0Zsr1P5ml5MDGH8EZN8LTX4NDz4/iwYo1bE9RQ1toXx18P7qOOqhs8GOGeVzSnkuzfqcnfFzo2ODHxDwu0WPUuMcFdZ03t29j5bLTsSkm6AErvDKC1r4RsOaqNAInOOaPrReuo/vjz2EEQ/UDseeazL3uTB2COhD/hVKM+u2w+WdQdTWsuxVKVo1L88RJ2PZb2G+tuow7B957z4we4jvqT4APPvgg27dvjyv/0Ic+xKpVq7jnnnu49tprufPOO5PSwJkgOvzaHRr6uLu+a0ThV3Eo/FpaksmSUA8wCb/ETFCQ4eL8DBfnLyyMlHX0+aluCPcis0KyI6192DLfRHW0ARDsm8vhukIO19UB1vxPigKn5aexZFYGS0oyWTwrg6pZmWS6Z2DQIJLCptooSy+jLL2Ms0rOijnm033U9dQlDMtaPC0Jzxf+ILy1aWtMuaZolKSVxIRk4eGYRalF03Ny/6bdcOg5az+rHBZdhWma7GrdxRNHnuDpo0/T6olfICbTmclFFRdxaeWlrCpcNT3/bcSkMdrwrNPXaYVkJwrPfB0YJ/jwHDSCNPc309zffOJ2KraBnmfDBGe5bis8k5+bCVKwCD72iDV8Ug+OMKSSoHM4ZiBA4yEwqzaCfYLf7xl6VNAWiA/eEoZr4aDuVMK7kQZ7JzhXwAOYVr1dD1lb2VorGFt4hdWbTEwOTbvg6X8fuP+eX8z4Xn2jvjpdLhebN29m7ty5MeWbN2/G5XIBYBhGZF/EMk2Tmrb+yEqPu+q62N3QNaKV+4oyBoY9hoc+5qdL+CVEWHaqg7Pm5XHWvLxIWUd/P9c8+hNaQyMsC/UrqVWIWQzANOGd5l7eae7l728NTJpcnpPCkhIrHKsKhWUSOItT5dScnJZ1GqdlnRZ3rC/QR213rTX0sisUlIWGYXb5uuLq66ZObU8ttT21vFL/Sswxh+qgPKPcGnqZGZqzLDQcc0pP7r/lrsjuwZXX8uTbv+DJI08mXODAbXNzfvn5bKzcyPri9TOzN52Y9GyqjTx3HnnuvBPW1Q2dDl9HTEgWsx8Vpo0oPDODNHuaafaMLDzLdmWT584jx50zbHiW5cyS8GwsuLNPXEdMPaoW6qEzRT8/9zTBtt/BG7+DfusLaI5ttbaMUlh7M6y8Tq7fiebvg4duBD30oWjtrbDg0olt0yQw6kDss5/9LLfccgvbt29n9WpriMi2bdv47W9/y9e+9jUAnn76aZYvX57Uhk5FpmlS297PzlCPr3AINtLwKzzscWmphF9CnKzn6p6g1WfNz7Jh1gZ+ff2NePw6+5q62d3QTXWoJ9n+ph78euwHh9r2fmrb+3li18D8LtbPZkZouKUVlBVnuqZuuCAmlVR7KotyF7EoN37FxE5vZyQcC2+13db8ZZ6gJ66+3/APTO4/aMqZVHuqFY5F9SoLb5nOzLF6eaeuq566vQ/zVGYGT6Snc/DIA3FV7Kqds0rOYuOcjZxbeq7MvyamFU3VRhWedfo648KywQFaq6eVDm8HuqkPe76gGaTF0zJkT9aYdioaOa4cclw5GL0Gb297m8qsysg8iSXpJdhVCaiFmBbSi+D8f4ez/83qHfbaLwdWSe2ug2e/AS/+EJZ/GNbeAnlzhz+fGBtP3g5tB639oqVw4bcntj2TxKgDsa9//etUVlZy11138Yc//AGABQsWcM899/DhD38YgFtuuYVbb701uS2d5MLhV0zPr/ouukcQfhVmOEO9vrI4vdTqhVKQPkW/IRBiEgnoAX6z8zeR+59e/mkA3A6NFeXZrCgf+KbKHzQ42NxDdf3AkMu9jT14ArEfEJq6vTR1e/nX3oFv03NSHZEeZEtC85KV56RISCaSKsuVRZYri2X5y2LKTdOkxdOScAjmsZ5jBIz42Xz7An3sbd/L3va9cceyndlxIdnsjNmUpZeRYk8Zs9c3nFZPK08ffZondvyanSWFccdVRWVN0Ro2Vm7k3RXvlhU7hcAKz8JDITlBxwzDNAaGbYZCskQ9z8KLBpwoPNNNPSY8O3jwYGzbFI1ZabMoTy+P/L4JLyQyK20WNlWGWAkx5dhdsPJjsOKjcOQlKxg78BRgQqAPtt1jbfMutoZTznmXDO0dL7v+Cjv+aO3bU+F994JNOtvASQRiAB/5yEf4yEc+MuRxt3t6fxtrmibH2j3squ9iZ30nu+utib27PCdeQqQg3Rnp8RUe+liQIeGXEGPhkXceobGvEYCzSs6KCxKiOWxqaGhkJh+gDADdMDnS2huZuH93g9WbbHAvz/Y+Py8fbOXlgwPzFqU7bSwOh2QlGSyZlcmc/DQ0Vf7wi+RSFIWClAIKUgriJvfXDT1+cv/QcMyGvoaEw6k6fB10tHTwdsvbcccKUgpiQrLwcMyytLKkD0fs9nfzXM1zPHHkCV5vej1hW5fmL2Vj5UYunn3xiHrMCCESUxU10qNrHvOGrWuYBl2+Lmtoprc1fu4zbyvtnvZIeBY0478c1k2dYz3HONZzjFcbXo05ZlNslKSXxKy0W5Fu3RanFqPN4MmfhZgSFAXmnGttbYdg669gx5+sUAzg4NPWlr/ICsaWfsBaqVKMjfbD8NgXBu5f9t/SSy/KSX/94vf7aW5uxjBi36CWl5efcqMmk+jwKzLpfX3XiMOv8FxfS0sl/BJiPPl1f0zvsM8s/8yoz6GpCnML0plbkM57VpQAA78Twr3IwsMu2/r8MY/t8QXZeqSdrUfaI2Uuu8qi4oxIL7KqWZnML0zHYZN5VsTY0FSN0vRSStNLObPkzJhjft1PXW8dNV011PZYQy/DodlQk3GHJ+re1rQtplxVVGalzqIis4KK9KjAbJQfYD1BD5vqNvHk4Sd5uf7lhL3b5vr9bMxYwCUb76YsvWyE/xJCiGRRFZVsVzbZrmzmMvyHKp/fx1//+Vfmr51PfX+9NUdiqPdqTXcN/cH+uMcEzWDkd9HL9S/HHLOpNkrTSuOCsoqMium7kIgQU1nuabDxx3Dev8OOP8DW30BXrXWsZS889jn417fgjI/D6psgo3jY04lRCvrhrx+H8IrbSz8Iy6+d2DZNMqMOxA4ePMjHP/5xNm/eHFNumiaKoqDrw3ehnsxM06SuI9Tzq2504Vd+utNa6THc86s0k0IJv4SYMH87+LfI8vTnlp7LkrwlSTmvoiiU56ZQnpvCxtOtP9qmadLU7Y0abtlNdUMXjV2xS1R7AwY7ajvZUdsZKbNrCvML0wdCspJMFhVl4HbIN+BibDk0B3My5zAnc07csf5AP7U9tQmHYXb6OuPqG6ZBXW8ddb11vEpsbw+7aqcsvSwmJAv3Mst35xM0g2xp2MITR57ghdoXEn5ALkkrYWPzMS5tP868QBCufhwkDBNi0lMVlTQ1jeX5y1ltj+3Bapombd62yHyINd01kd87x3qOJZwbMWgEOdp9lKPdR+OOOVQHZellA0Mww4uKZFRQkFIgYZkQE8mdBRs+a03kvv+f1nDK2i3WMU87vHwHvPoTqLoG1n8aZq2YyNZOH8//JzTssPZz5li9w0SMUQdiN9xwAzabjccff5zi4uIpO0dOdPgV3fOrs//E4Vde2sCwx6USfgkx6fh0H7/d+dvI/fDcYWNFURSKM90UZ7q5YPHA/EatvT6qG6xwLByW1bTFftgP6GaoTjd/ecMqUxWYW5AWs7rl4lkZZLhkAmIxPlLsKSzMWcjCnIVxx7p8XQmDsqF6ewSMAIe7DnO463DcMbfNjU210RP+5jJKriuXSyov4dLKS1laV42yKzQ36YLLIG/4IV1CiMlPUZTIAgGrClfFHDNNk+b+5khAVttdGxOW+cKrpEXxG34OdR3iUNehuGMuzUVpeuKeZfnu/Cn7eUaIKUezweKrrK3+TSsYq34YjKC17XrQ2srXW8MpF1xmPUaM3sFnYfPPrX3VDu/7PTjTJ7ZNk9Cor6633nqL7du3s3Bh/JvkySocfkWv9Dia8Ov0koxQr68sTi/JpDDDOaX+cJqGgc/XhcfTjtfbicfXhcfXidfXg9ffg8fXQ5+vm7qORmqPZVBZcTaq/OIRU9hfD/w1soT8eWXnsTh38YS0Iy/Nybnz8zl3fn6krMsTYE84JGuw5iY71NKLYQ48zjDhwPFeDhzv5ZEd9ZHy2bkpVkgWmpOsalYGuWkyIaYYX5nOTJbmL2Vp/tKYctM0afW0xs1VFv4A6zf8ceca3AMk3Z7OBRUXsHHORlYXrraGWpomPBS1UM+ZnxuT1yWEmDwURaEwtZDC1MK4uREN06C5vzlmtd2aHut2qIVEvLp3YNXdQdw2d2Ry/5h5yzIqyHXlTqn3/EJMKSUr4b33wIX/Cdt+C2/83uotBlbvsdotkFkOa2+GFR+zepmJkelpgkduGbh/4X9Kr7shjDr1WLx4Ma2trSeuOEFM06S+0wq/dtYN9P7qGFH45YhMdL8k1POrKMM1pn8ITcMgEOjD4+0IBVZdeH1deHzdePzdeP29ePy9eAN9eIP9eAL9eHQv3qAXj+7Dq/vxGn76jQBeU8drBvGYBl5MvIqJB/CMdBJvBX718nbSN5ksVt1UpZWzpHAVS+ZcTFHRChRVupqLyc8b9PLbXePXO2y0Mt121p+Wy/rTciNl/f4gext7qA7PS1bfzcHmHgK6GfPYo239HG3r55+7GiNlszJdVJWEepLNsn53TbXQXkwPiqKQn5JPfko+ZxSdEXNMN3Sa+psS9irr9feytngtl1ZeylklZ+HQHLEnfue5geXbS9dA+bpxekVCiMlIVVSKUosoSi1ibfHamGPh3zW13bUxQVlNdw11vXUEjfgJ/j1BD/s79rO/Y3/csVR7alxYFg7Msp3Z8rdWiGTIKIZ3/wec8yXY+aDVa6wltAp2Vy0883V44fuw4iOw9hZrXjIxNMOAh2+G/lBmE17VUyQ06kDshz/8Ibfffjvf+973OP3007HbY4fwZGSM/1Lnz+5p4nBXA7vqu9lV1zmi8Cs31cHppQMrPQ4VfgUC/Xg9HVbPKm8HHl8XXl+PdRvojQRWnmA/3oAHT9CDV7fCKo/uw2v48RpBPKHAyoMRFViBRwEjWX9MldAWUzB6ParCVrxs7T0AvQfg0APkGCZVWhpV6ZUsKV5N1dyN5OVNnV6CYuZ4cP+DtHqsPwAXlF+QcMjXZJPisLGqIptVFdmRMl9Q5+Dx3sjqlrvru9nb2I0vGLuQSUOXl4YuL8/uOR4py0tzUBU1cf+SWZmU5bjljbuYMJqqUZJWQklaCRtmbRjdgzf/dGB/w2eT2zAhxLQS/btm/az1MceCRpDGvsa4+cpqu2up761HN+PnQe4L9LG3fS972/fGHUu3p1OWURYz/DI8HDPLlTVWL1GI6cvuhlXXw8rr4PCLVjB28GnrWKAPXv8NvH4PzL8Y1n0aKs+xVrQUsV79HziyydpPL4b3/EL+nYYx6kDsggsuAODd7353TPlETqr/X399ipQUA6fSR4HaT2mqF5vqwaZ40VQfKQ4/GW6TFKeO3R5E1YLoBPAYfo42BdnbGOB/X9fxouM1DTxRYVVwkoVVJ6KaJm4TXCa4UXApKm5U3IqGS7XjUm24VScuzYFbc+LWXLhsbpyai8MNh2h2dFMd7KFFi21fu6rwstnHy927oXs37L+XQt1kiT2TqszTqJq1jqp5l5OZOb1WGRVTS3+gn9/t/l3k/q3Lp+63IU6bxpJQb9WwoG5wuLUv0otsd0MXexq66fXFfuPd2utn04EWNh1oiZRluGwsKEonO8VBhttOpttOhstOpttGRng/xbrNcNvIdNtx2zUJ0cTEangLjrxk7efMgYWXTWhzhBBTl021UZZeRll6WdyquwEjQGNvY1xQVtNdQ0NfA4ZpxJ2vJ9DDnrY97GnbE3csw5GRcL6ysvQyMp2ZcfWFEFEUBU47z9paD8LWX8Fb/weBfsCEA09ZW0GV1fPp9PeDXebzBuDY6/D8d0N3FLjmN5CaN6FNmuxGHYi98MILY9GOU+Kf+yt0t0b8lLwJGKFtsJjRgGP3AdBtmLgBl6ngQsGtqLgUG27Fhlu14VIduDUHLs2Jy+bCbXPjtrlx2VJwO9Jw2VNxOdJIcWbicqTjcmbidmfjcmXhdmVjt6ee1NDGQCDAE088wcaNG7Hb7TQf383uQ09QfXw71d1H2W300TVo6OVxTeG40c1zHTugYwdU/5IyHZY4cqjKXkBVyQYWz91ISlpBkv71hBjeg/sfpN1rzT1w8eyLmZ89f4JblFw2TWV+YTrzC9O5ZqVVZhgmNe39oeGW3ZFhl4N7ynZ7g2w72jG651OVqPAsFJy5Y0Mzaz+2TrjcYZNh1uIUhSeDBVh/G6iy+qoQIvnsqt0aFpkR/8VuQA9Q11sX07MsPMl/Q28DJmbcY7r93exq3cWu1l1xx7KcWXFBWfh+miNtTF6fEFNW3jxrZcTzvw5v3g9bfwPdddax5mp49Db417fgjI/D6k9AetGENndCeTrhr5+AcG/Xc75k9aITwxp1IHbuueeORTsmBadh4gKrhxUqbiXUsyrUu8qtOqxbzYnb5sJls3pXuW2puOypuO2puJ3poaAqHbczC7cz0wqr3Dk4nZlTZh6ugsIlnF+4hPND903DoL7hdXYffoY9zTvY3XuMPaaXvkEh2TENjuntPNm6BVq3oLx1B3MMlSpXPktyFlFVdjYLTrsEp0u+HRPJ1R/o597qewFQULh12dTtHTYaqqpQmZdKZV4qly+dBVg9dhu6vOyutyburw4NuzzeHb8q13CChkl7n5/2vvjJ0EfCZVdPGJpluq1wLbaOnXSXDXWk8x+K6amzFqofsfZT8mD5hye2PUKIGcmu2anMrKQyszLumF/3U9dTF9+zrKeGpr6mhOfr9HXS2dLJzpadccdyXDlWQBaetywUlFVkVJBiT0n6axNiynBnw5mfh3WfgX2PWcMpj221jvW3wks/glf+B5a81+o1Nmv5hDZ33JkmPPY5a841gLJ1cO5XJrZNU8SIArGdO3eyZMkSVFVl5874X97Rli5dOuzxsXC2kkam5h7oWaU5o3pWuXHb03DZU3A50nE703GHe1a5snA5s6xbd46srDgMRVUpLV1Haek6LgmVGXqQo7UvUX30OapbdrK7r559+PFFfYg1FYVDmsmhQDOPHm+G45uwbfsv5pk2qtyFLMldQlX5uZw25wLs8odenIIH9j0Q6R12SeUlnJY1cyfcVBSFkiw3JVluLq4a+Kas3x+k2xOk2xug2xOgyxMI7Qet/dB9az8YtR+gxxfEjP8SfFjegIE34Bt1EGe9Bkhz2uJCs8yoXmoy3HOa2/KLgW8519xszS0ihBCTiENzMCdrDnOy5sQd8wa9HOs5FjO5fzg0a+5vTni+dm877d52djTviDuW586jNK0Uu2bN32yaZqR3mhn6Ax19P/xf6IB1L6reSB8bOT7osWbUm4K4xyY4Z6LHmlbDBuqN5WOj/73Ct4bJt/78LZTQ6KDIrZL4frQh64ZHGikjqzf43InKx+rcwz1X5H5UXcM00Q3QjfCtgW5Yq6OnqDlk2ovJcRST55pFgXsWhe4S0p1u3A4Vl03Daddw2VVcdg23XcMVvm/TRv4lqGaDqqutrW47bP2l9eWZEQQjADv/bG0VZ1rB2IKNM6N3+fb7YM8/rH1XFrz3t9a/lTihEf0rLV++nKamJgoKCli+fDmKosT8EgybqDnEfnztvyZkMv+ZTtVszKk8nzmV53NFqCwQ6OfwkefZXfMC1W3V7PY0cVAJxszFFlQU9io6e30N/LWhARqewbn5ayzEQVXqLJbkL6Nq9vnMLj9XQkoxIn2BPu6rvg+wVp+6Zdktwz9ghkpx2Ehx2CjKHP08C4Zh0uMLJgzNuiNhWuJgrcsTwBMY3d8G04Qeb5Aeb5D6Ts+o2zvS4Z4DAZstJmyT4Z4TzNNhDY0AsLlh9U0T2x4hhBgll83FvOx5zMueF3esP9BvhWWD5iur7amNLAw0WKundchj4hQkmkpHjFqXXktj4C3oHygzTQUzmIHhz8EI5GL6cyP7hj8HjIHOEA6bisumhkIyKyhz28MhmhY55o4K1Zz2dNy5XyXnzJtY0vBX5tU+iCPQZZ2w5lWoeRV/ehk9yz5BcOlHcKZlWY+zqdPrS9Pje+CpqN5gV90FWWUT154pZkRpw5EjR8jPz4/sCzEUuz2FBfMvZ8H8y3lvqMzn7eLAoWfYfWwT1e37qPY2c0g1MKN+EflUhbcJ8LanBmproPZRUg2TxYqLqrQyqgpWUFV5IaUla6fMsFMxfv5v7//R6esEYGPlRuZkxn9TK06NqipkhgKmk+EPGvSEQzJvMHEPtZiea0F6QvtdngBBY3Td0051uKfbriXolWaFZqkOjbp6hYZXjqJpKgpKzOI9A9+mhu9H7ytxZShKTF3rsUrUfvR5Bgrjzhn9+ATnGbptyqDHRC9GFN9eJVF7B7Vt4DwJ2jbonJqqkJ3qIDfVQVaKA01VYNvvrBWlAFZ8FFJzEUKI6SLFnsKCnAUsyFkQd6w/0J8wKKvpron0hD8V1t+FgV4/StQflPD9mOODeg9ZfwOiehgpQx8byWOjeylF2kPiXkyD2za4XtxzJmhP+L5pmnR3d5ORkWF19hiqx9yg8mgjrTtcb7zo+4PPO9y5o3v/Rd83TDPUk8uM7JumiR66tcrANA0MM/q9SHQbBr/WIe5HHqyjqPFffCqKiWLvQrV3AfEZghlMwQjkYPhzMQI59Ptz6fPnYHjyMIPp0U8wAufhYgNXa6/wce0p5qn1ADh6jpH7yrfoffkHPKSfy336xdSYRZFQzWUbCNhcUWFbuNzt0HDaYkO66HpOm4bboQ0T5qk4tDEM4Pz98NePQ9Br3V99Eyy6YvjHiBgjCsQqKioS7gsxEk5XJqdXvZ/Tq94fKevvbWbvoSfZXfcq1R37qfa3UzuoN2ufqrANH9v63oEj78CRh8gyTKrUVBanV7Ck6AyWnLaRgsIl4/yKxGTS6++N6R32qaWfmtgGiYQcNpXcNCe5ac5RP9Y0TbwBI0FoNnbDPT0BHU9AH2a4p8ajtQdG/VrE8FQFCt3wT/Pn5AAGKj/tuwD1XwfJSXOQl+ogJ9VhXUupDjLddplrTggxraTYU1iYs5CFOQvjjvl0H4ZpDBkihQOmoUIkMSCyoNil1oJik1VAN+jo89PS66Ot109bn3Ubc7/PT2uPj9Y+P/5gcru8qQrkpDrJS3OQm+YgL81JbqoztG/dz3Tb6fC1Udd7jMa+epr662jxNtDma6TD34jX6E54bsXWj2brR3PXxR0zDXsoLMuxepaFepUZ/lzMQDYQPwzSi5MH9HfzgH4+Z6u7+Lj2JOdpbwOQpni50fY012vP8Jyxkt/rl7AlsJixXEwvTFEYCNJs4d5tGu7BQZxNw64pNNSp7HhiHw67DU1VsKkKqmLdalroVlWxqQob9vwX81r2AtCVMZ+Xiz+Duqsx8jjrVkVVwaaqseWDzjX4MeHnCj/3dH2/dVLj0Q4ePMgLL7xAc3MzhhH7Q/eNb3wjKQ0T01tKWgGrll3PqmXXR8q6umrZ884TVNdvobrrELsDnTRpsT94narCq/Tzas9e6NkLB/9Avm5SZcugKnMOS4rXUjV3I9k5M3f+qJnmj3v/SLff+kN7+ZzLmZ05e2IbJJJOURTcDusbuPEe7tntDdDvH/+pAGYqw4RzfC+QY+8E4En9DH76pg4kDh81VSE7xXpTHh2U5aY6yElzRN6054aOZbhs8sFQCDFlObXRf6kkJhfTNOn1BWnt9dPW67Nu+3y09gyEXa29Plp7raCrc9Cq4cmQ6tBCX1Jafyfz06P+XqY5I0FXTM/tE8oB4ocHA/T4ezjWcyyy1fXURfab+poSrtSqqAE053E05/G4Y6qikeMsINc5i2x7EZn2ItK1QlLUIpzkY+gOvIG5bApcyY7ew6xpfog1XU/hMH2oismF2nYu1LbzjjqbB5TLecxYT1dAw5fkMDHMNKHfr4/i/aTKy021J6y1UX2N6x1/BaDfdHJNyyc59ODeU2jp8BSF2MAsJkALh3Xx5ergoG1QKJc4kLPKNZX448MFeVHn8/b3juh1jToQu+eee7j11lvJy8ujqKgorluqBGLiZGVmlrN+1S2sXzUw/1Nr6z72HHqS3Q2vU91zlN16D+2Dfim3aAovmj282Pk2dL4Ne39DiQ5VjiyqMuexpHQDi+deRlp68Xi/JDHGuv3d3F9tzTOkKRq3LJW5w0S8ZA33DIdm7b0eXt6yjRUrVmCz2SK9z6xJe8P7odvoYQ/Rk/+a0WWxdc2oEyQ+Z4LzRN0xY86foGyItiV6vujy6Hox5zZH17bB9QK6Nby1rddHR6+XW9ufiFT8TfByhqMbZuSDw0jYNYWcVEfk2+6c1NjQLCZUS3OQ5pQATcwcpmkS0E2ChkEgaOLXjch+wDAI6FH7QYOAPrAfNEwCuoE/aj+gm3j9AfbWK7RsqSEzxUma00aay0aa00a6y0aq09pPdcjKwmLqCugG7X1WkNUWFXC1hgKuSPDVO3G9uMJ/2/LSnLgd4zvJfLojncW5i1mcuzjumF/3U9dbFxOSRQdnASM+EDRMnVZvI63exoTPl+vKpSy9jLLsMtzlZXSsfT97HDdRfvgVsrf/EaXbGk451zjKf3AX/5H6FzjjE5hnfByfKw9vaJSAtTiUHtqi9oPWfY9/YN8XOhbzuKCBN1JnoNwT0PEFDPz6yV8HpUoLP7D/NnL/W8HrOGSWnPT5RsI0rfdsAd1kKky+Z/j6T1yJkwjEvvOd7/Dd736XL3/5y6NulBCjlZe3kHPyFnJO6L5pGDQ17aD68DPsPr6d6t5aqo1+ega9iarXoF7v5Jn2bdC+DXb+lNm6whJnLlU5C1hSejYLTrsUd0pOUtppmiYEg5h+P4bfD4aBYrOh2O0oNhvY7fKhagz8cc8f6Qn0AHDlaVdSliETSIrkGzzcMxBIpeeAyaVLiib1MIspaf+T8ID1RlUv28BdV3+StlBYZt36aQ9/wOizPnS09/pH/AEjoJsc7x75yqcOTSU3qvfZ4CGb4WN5aU5yUh2kOGR1U2HRI6FQKDgaYj+oWx+Kwvsnqh/QDYKhW/8Q+9GPCeqDgi3dCIVYg9phGKEPOWNB4/Ha/SeslerQImFZdHCW5rST5gwfi91PdWqkO+2kuWyRfZd9mk2YLcbdSHpxWUMWx6cXV16o19ZAyBV1m+ogO8UxZQNlh+ZgTuachPP/6oZOc39zXFAWDsvCnwEGa/O20eZt462Wt+KOpRZlUFZaQllfB6XdLZQFA5QFuil/9ccUvnInriXvw7XuVrKKlyb7pcbRDRNfOFwLBWq9Hh8vvfwKa9dvQFE1gro1H1zQMEK3JkbQz9oXP0pGhxX41My6lGVLb2OJSVR9E90wQrfmwK1uletm9P2o41HPE3vcKtfNgbIhH6fHlo9yGuBxN+pArKOjg/e///0nrijEGFBUlaKiFRTmVHGe328FUF4v9bVbeafmZQ437+Vo73HqgwEMA2y6tdmDYNfBpzezU29mr/4yjuB3KQgqFJJCvj2HXHchGc4iFN3ADJ3bDASs5wj4Mf2BmLKYLRDghJMU2WwxIVn0LXYbit0RWx5zzI5is8c/1mGPOm/U4+2Dzm+LPscQx+wJzj+Jw7wuXxd/2PMHAGyKjZuX3jzBLRJCnLJXfxbZ1c76PGU5KZTlpAzzAItpmvT59bjgrLXXH+l9Fi5v6/PR3ucf0Yd/v27Q2OWlscs7oua77GrkA0ui3mfh4Cw8TGW8v6WfbkzTxBe0wqDwt+3+oIEvqOMPhvcHbiPlI6mvD93zKXo/HDgN3h/tvIUC+vw6fX6d44wssB6KpioDoVooWEt12kgP90YLlaUP2k9zWT3V0l0D9WTF4akh3Lsx+mc85md60M+8P2jQ5/XzaoPC7qcP0OEJjmsvrryo4Yq5aQ7y0waGK05UL67JSFM1itOKKU4rZk3xmphjpmnS6etMGJQd6zlGi6cl4Tn7An3sC/SxTwWyMmKO2UyT0tYXKP37s5S58ymrOJeyORdRnjmbkvSSpA9Z1lQltAL8QFkg4ORoGqwoyxr6S9d/fRs6rLnRyKqg4rpfU+HKPOHzmYYBhmHd6nrMvmma1q1ugBkqC9fXDTCi7+vWHBfGQH0zdL5E9Y2gjqHr6LqOEdTRdSN0G8QI7YfLTd0qN3UDQ9dDm3VOU9cxDB0zGN63bk3dwDRibzEMer1eRrK8wKgDsfe///0888wz3HLL5BmaFGhuJuDxDqxyoiiDlr6KXXZLGepY5EN/aFWuE9RThjuHMvUnsDRNEwIBDH8AM+AfOgwKlRuR+0MER4FR1I0+b3QY5fdbP8AJlIa2cxIeHfJVAr2hrZbE3zMkSTCIGQxiekf2wWpSGSLIGwjlhjuWINAb7lhUoKcrCmm7dtFrs6FpWmiclbVKztNHnmZZbTeKCWuKlpH+/HY6zTcGxnmZJjBQPzKua7jyuGOjLY8/NqrniHnMUOUjfI5E5wIUTbNCVs1m7ds0698/vK+F/v/YNAjVUew20MLHNOv/W3hfCz0+sh8KUsP7oVtC+2ia9f9Y00LPGaqvyjf6M17dG1C72drPWwDzLhrxQxVl4ANwRW7qCeubpkm3NxgXlsWEaFE90dr7/Ogj+IrTGzCo7/RQ3+kZUbtTHFooPDtx77OcVAcu+8R/QBr8wTMcIA184NRD4ZMRFzL5g3ps/eBAIOWLqxsKqvRE5QPnECNjUxXsmopdC9+q2G0KdtXat4XKHVH70XVtmoJj0L4t+lyhfZum4ojaV02DHTveZNHpy/EETfp8QXq9QXp9oS16P3S/zxek1z/6xVDCdMOMrFB8qhw2dSA4i+m1NihUS3AsJpBz2EY4D9PUYJpWDxD/ED//8eVRP7/6oJ/xqLrRdQYeN0TINeh8J0eDmqMn/e8w0l5ceWlOsmQRmKRSFIVsVzbZrmyW5sf35uoP9FPXWxc3Z9mxnmM09Dagm/GfJ4OKwlGHnaMOO9ALtf+0NqzFKgpSCqyhmNFbhnWb4cjANE1Mnw+jvz+ymeF9jydUFr7twwyX9Q0c1/v7KGtt49gf/ohiGANBlREKoby9mF0NQAGmqYA7DfNvl4M+KNhKEH5NFeGvIU71HU/qEJnBYIqZaA3ZYXz/+9/nzjvv5LLLLuP000+PSy4/97nPjeZ0p6S7u5vMzExenzuPNG3i3yQOa3BoFh2cRdcZop6S6BxR+8OeI7If2iW+DQCe/n6cmgbRvZ5EhK4pKHYN1enC5kxBcTgGbaFQx+FAUTUr/AoGrH/HQNAK/YJRt6F9AoGYY/K1spixEgRoJx/ghc81OMCLrh96/GgCP82GrsC27dtZu+FMbG6XddwxqGdndM/L8P5k/zs10f7yMdj7qLV/5c9h5XUT254ohmHS7Q3EBWeR/T4/7VG9z9r7/GMyRCDNaYvtfRYVnGW5bRzY/RYrVq5CR0kcLsV90AzX0YcMnHwBPRJehctnMlUhLgQK79tC+47Ifvxxx6B9m6pgt4XqRO+HQyVVwREqi9RVQ8fD+7bQ84T2bWroeUL7dm3ivqSNrOS3cXQr+RmGSX9AHzo88wbo8+v0eIP0+gL0+WL3e31BekLhmicwORZGSXFo8WHZoAAt1TnQQy1RuOZ2aOihIMoXHPxzHP65HQirB4dT/iF+tgfXGaosugfWdHy7Kr24Zga/7qeprZb61kM0thyhua2Wto56Ojoa6Ok8juLXcfnBFSB0a+LygzN83w/OgBk57gyA26/gDJio0/DnYqrq1XXWvHOQrq4uMjIyhqw36kCssrJy6JMpCocPHx7N6QC4++67+fGPf0xTUxPLli3j5z//OWvWrDnh46ZUICZGTtMGQia79UFTtTsGlQ0dRqmReuHyoesGTB/HWt7kcPtuDvbVsN/o4qjdJGCDoAYBzboNakT1IIR0w2Sx6mZJWgVLCldRNeciiopWoKin3rXe1PXY8CwcmgUHhWqBqMAt0bFAIP54YHAg58cMBkOhXILQLvocIwj1hBDDUJTYeQWH6HWZcJh0VO9JImXxPSsT97pMNHQ61BNz8PDtBMOqIwHlWH6gbjsEP18FmJBWCF/YBbapu5pauIfKSHufdfT7p+WHy2QIB0JOm4ojtDltGg5NjSl3hsttVhjktEffagnOEf3Y+MeF79sH9YSaTr18xsPJBmLJFNQNKyTzh0O1AL0+PbJvBWd6qDwYOha17wtEwrixm2dNnEii3wXWz2ro53vwz68tdj/8c+60hcNok6P7q7ngrLUUZqVIL65JyDRNa+qaUC8q0zPQ88rweKyeVf39GKFyM6bME1W3H3NQ+aTvMaUo1mfi8K2qgu4FM4iimGBzoKTkgKaBqqCoGmgqiqIO1FdVq0zVrJEYqhp7Tk0FZVAdTQV1iHMmqh8+p6pYj4vUV60vgpUhzqlaZTHnTFRfi3qeqPqKZj0vSrhOqA1Rr727r4+CZcuSG4iZpkltbS0FBQW43e6k/L/+y1/+wnXXXcevfvUr1q5dy09+8hMeeugh9u/fT0FBwbCPDQdie27+FOkOe6SNsctYmTH7kWVdh6sXHmYEg5fritk3Gf65rIcnqDP4HEM9T+R/zQnaM9xzDdWeuH8X8Hq9uDMyUJ3O2DAqEi6NIowaXNceXdcxcN5EdSc43OztaWTPO/+kun4LuzsPUO3vpH4ETcoxTKq0NJakV7KoaBVlBUspKT4jaRP3T3aRLroJgjmCgQRh24lDu6DXy77qahYuWoim2UBR6Nc9/Gbnb/AbAVRV41PLPkWGM3OgF2R4uLI17jlxuaJGygfKYusPVR57nvCxocpH8RxR50pcfjKPGVRumta4ej0YCl6DA/tBHTMYsP4fBnVMPRga5hvaD9WP7Ad1K0zVgwnq61Z5IDiwH6pv1dNDzxkY2NeDVuga3o/U163z6qHnC++HysU4SjDHYNzQ6SGPJQjwQmEddjvKoedQGrdb1+z8C1DmnR/qzRd+gxbdwy9UFhmGa5VFhuSOpMxmC72JG1QvCV9qnIygbtDRHxg0hNPqbRbd+ywcriVjKNhwNFWJC4esD6FabJgUV0eLCZwGQiYNZ1yANVRdFac2cEwCqKltMgRiyeQL6qFhnTo9oaCszx8M9U4LRoaE9oSHfw5xrM8XnPQTTYd/DyT8OR0ioHYMqjNUeBXzuyDRY+2DQm9NPemgyjQM9PZ2AsePE2xuJni8mWBzM/6WFmpraiifXYFms1nvDVXV+lAd2kfB+rugqKEP84n2w49RTlAvvJ/keqoKKKFAIsExZYh64akqEtULv6dNUC/uMYoSE1zFDxEMDxPsGwitBg0TjAm1BpVP5uDK0CDg0PA5NfrtBn2ajscBPgd47eAN3Vr3FbwO8EWVex0KAYdKWmY+edklFOSVU5hdTvfhPm6+/FOkuKLmUH31Z/Dsf1j7qQVw66uQNnxWMtOFs6KkBmKGYeByuaiurmbevHlJaejatWtZvXo1d911V+Q5ysrK+OxnP8tXvvKVYR870hcpTmy6vWFJto72Q1S/8wTVja+zu+sQ1cFuWrSR/WHO1U1KFAeljgxK3AWUZpRTmruQkoKlFBYsxWZ3jXHrp65E1+Wd2+/k3t33AvChBR/i39f9+0Q2UUyggQlA9YE5+sLBWeg2sh8XAAZjg7ZI/RMEeLqO7vdzcN8+TquYjWqEgsLhelYmODZsj0sJ+iaOosQO142EbmrssF3NFvp2cnBZVACXoCx6aC82DUU9cdnAfvgbWhu6qtIfNOkNmPQETLoDBp0+nQM1dZRXVOBwObE57dgcDmwOO3bnwK3D6cDutONwOXA4nThdDhwua36y8IdRmyYTiYvkkPeXiZmmiWe4IaEJh4kG6ffrkTnc4kKjqB5R8UFU4h6R8QHW1AmjTdPE6OmxQq7mZgKhoCt4/DjBlmYC4fCrtVX+ro610Jeuk5bdjpqSYm1ud+x+agpKSgqqOyWuXE1JQQnXVwOoh59G3fsQqq8RVTNRwh0mUgtg9U34V3yUevxDrooZMEb+ZZZLc3FG0RmsK17HOjWDeQ/dhGqEruOPPQKnnZ/8f6dpZqRZ0agm1VdVlXnz5tHW1paUQMzv97N9+3a++tWvxjzHBRdcwJYtW+Lq+3w+fL6BlWe6u7sB649tQIZrnZLwv5/8OyaWll7O2hW3sHbFwGISLS27qT78NHuPv0l1bw3VRh9dCd48tGkKbQTYGWyDnjbo2Qv1TwPWaiZFhkKJ6qLUkcWs1GJmZcymNHcRswqXk5U1Z8J6LEwGg6/Ldm87D+x9AACH6uCGRTfINSusbykdDmuLEuonl3SBQIC2Z59l5YUXjskHPNM044ZBMyg4SzSMmuhQLTKkOjjicxCpH4g7X8zQ6lC9uKHaoTpTWmgxGTMQYBK/tY+RHtpKgKpRPjYY2vog0ususnJxeN8e6t2X6FhkNeLwvHux5ZFjMY8ZdC77oIU4bPao5x3qOaOGCA9eyCM8PFgW6ZgU5P3l0OwKZLs1st0aMJmGiBvWym8TOPWa4fWit7QSbD5OsKUFvbnF2m9uIdjcjN7SQrClGdMzBReqmo6SFYbZbJFASkkZFEhFytwxxxPXTUFJcYdCLrf1dyEZlq2BK7+Cue9RzK2/QmncYZX3NcOL38P+8h1UVL2P0jU3s37uB2IeapgGzf3NAxP999bF7PcGemPqe3Uvr9S/wiv1rwCQU1rIGo+XNSVnsSbnNGbJ79QTGunfnVHPIfbYY4/xox/9iF/+8pcsWbLkpBoX1tDQQElJCZs3b2b9+vWR8ttvv51NmzaxdevWmPrf+ta3+Pa3vx13nv/7v/8jJeXEy7ILMZZMw8DrO0ybdxetwXrazW5a8NCk6bSc5LftbsNglq5QYDrIJY0cNZsMWyGp9jJSnJVotvQkv4rJ7UnPk7zqexWA9Y71XJZy2QS3SAgRwzTBMFAMAyWog6Gj6LEbuh45rgW9rDp8N/agB8NQebv0Bvxa2sA5DAP00K0Ze18JraAUexs6txFuhx51zAwdC5WFluVWTCNyP3IuM+p5jeGeL+qYmFRMVbW2UA+98L4Zmo/E2rfmJDGjjhNVz7RpmJoN02az9m02676mxZfF3dcGbm222PLIfS1mflIhpj1dx9bbi9bdjS166wrd9lj7mmdkK/UOx1QU9NRUghkZBDMzCKZnRPb1jAyC6emYqooSNQWNYprWSn7h+0RNT2Oa1t+W6LqmMbAPkcdGnxPTGPQcxJ4zdI74xxH/HIPbGm4vZvzrCB2LedygeoOPK1H1Er/exPcV08Rw2DEcDkyHE8PhsDZn+L4dw+EM3Q8fc2LarTrh+thG1VdnYpkm2f3vcFrz0xR3voFK7PuAlrRFHC64mKaM5dYw1mFPZeIxPbQb7RzXj3MkeIRDwUP0mD1DPiZbzeY022nMtc2l0lZJqnriFbZnmv7+fj784Q8nf1L97Oxs+vv7CQaDOByOuLnE2tvbR3yu0QZiiXqIlZWV0draKkMmT1EgEODZZ5/lwjHq8TDT+XxdNDTtoKFlNw2dh6jvOUa9t5V6vZd6dHpOslt6jmFSip0SewazXPmUZJRTkjOPWfmh4Zi2qT0cM/q67Ap2ceWjV+LVvTg1J49e+Sj57vyJbqKYgeT3ZfKo23+P9tTtABhV16C/5zcT3KKTY4aCwMjQ29AS59FDdgmGlk2PHqYbmo8PI6pOeJ6+qPn+hiqPDPE1DHS/n8MHDlBZXo5qmqEee8GB4bjhYcKhFZAHegAOPhYeQhzVE3DQ4yfznC5Tjs0WOy9rzFyt4QUwBs/bmmAe1+i5WgcvLuRwWHP1DSqLe87IStnJ65kuvy9nBtM0Mbq6IsMX9ZYWa7hiS3Ood1ez1dOrrS0pvz/U9HS0/HxsBQXYCqxbLT9qv6AAW27usD2D5NoUSdNVh7r9d6g77kfxdsUcMrMrMVbfjLH0Q+A8cUeG8HV5wQUXUL/jV2x7/U5ec7nY5nbTN8TnRQWFBdkLWFO0hrVFa1mevxy3LTnzvU9l3d3d5OXlJXfIJMBPfvKTU2lXjLy8PDRN4/jx4zHlx48fp6ioKK6+0+nE6YzvUmy32+UXWZLIv+XYsNvzmD/3QubPvTDh8a6uWuob36SuZTf1XUeo722gztdOvd5PvWoSGOIb5HZVoZ0gO/V26GuHvv3Q+CwAWmg4ZqlmDccsSS2mJLOS0txFlBStJCdn7pQZjmm327l/9/14datr/AcWfIBZGbMmuFVippPflyfJ1wsHnoLqR+Dgs5Fi9awvoMq/50kLBAJse+IJ1o7DXE1mOOyLnv8uFK4RDETm5ovcjwnfArEB3OCy8OIa4dAuJtQbomzI4G/oOtHtn9C5b8Lt6e+fuDYMFgrp1EQLKQ0O7MILKg2x+JKpaWQdOkR/Xz/2tFQUl8saxuR2WcObQpvicllDnhwOGe46yRj9/aEJ6UPBVvPx2Dm7Qpvp95/ycykOB7bCwkjQZS8I7xdgKyzAHtpXkzgySP6Wi1OWVwkXfwfO+yq8/QC89ktoewcApeMI2jNfRdv0fVh5Haz5JGTPPuEpHd1Hmb/pDuYH+vlIdy/B9/2O6sJ5vNbwGq81vsZbLW8RDM0pZmKyr2Mf+zr2cf/e+7GrdpYXLGdd8TrWFq+lKrcKmzqFet8lyUh/rkf9L3P99dePujFDcTgcrFq1iueee473vOc9gDWp/nPPPcdtt92WtOcRYrLLzCwnM7OcxQvfE3fM0IM0t+ym/vjb1LXtpb6rhnrPcer8XdQZPpqHmNxfVxTqNajHy1Z/E/iboGMHHLWOuw2TEjRKtVRKXbmUpJdQkjWX0vwllBSvIiV18vS+aulv4cH9DwLWJJMfX/LxCW6REGJU/H1w8BnY/bB1Gxw078vcC6F42cS0TYyaoqpWr6NB8/ZNVXEBXnjF5EAA0++P2YzIfuhYdJ3AEHUG1wufK3DiOhMiFNIlawqpAqDl8cdHVllVUV2hsMzlsub/cYVCM3coTIsuH1QnPmhzW3MOuQbKJ3o188nC9PsJtrYmCLeOD0xI39yM0dt74pOdiKpiy8sLBVuFobCrAFs48AqFXWpmpgSiYupypMLqm2DVx+Gdf8Frv4DDL1jHfN2w5S6rbOFlsO7TUL4+4bB51fBje+STEAh9UbLyemxL3scyYFn+Mj617FP0B/rZ0byD1xpfY2vjVva27408PmAE2Na0jW1N2/j5jp+TZk9jddFq1havZX3xeiozK+XnLMopRYVerxf/oD/Wox26+P/+3//j+uuv54wzzmDNmjX85Cc/oa+vjxtvvPFUmibEtKFqNoqKllNUtJxVCY77vNZwzPrmXdS1H6C+t456Twt1wV7qCA45HNOjKryDwTtmD3h6wHMUml+FA9bxHN2kVLGGY5a6CyjJKKMkZwGlhUspKlyOzT5+XXHv3XMvfsP6XfOhhR8iz503bs8thDhJAY/VA6z6EatHWCBBD5i0Qqi6Gs7/+vi3T4iQyKqiCUYhTCQztMiD4Q9EwrZEoVlcCDe4TiBBvUAgNoyLC+qGrjOmPeoMA6O/H/r7kxbIDabY7dYk3C5XKGgLBWgulzURtysqWAsFanE921yJwrfJ0cvNNAz0jg6Cx0PBVlS4FWxujpTpbW1JeT4tMzOqV1dsT65I4JWXK0GkmDlUFeZfZG3H98DWX8HOv1hfBpoG7H3M2oqXWcFY1TVgG/iCqar+zyit1dad/IVwyQ/iniLFnsKZJWdyZsmZgLXw2OtNr/NagxWQ1fXWRer2Bnp54dgLvHDMCucK3AWsLV7LulnrWFu0lsLUwjH8x5j8Rh2I9fX18eUvf5kHH3yQtgS/SHV9dH++PvjBD9LS0sI3vvENmpqaWL58OU899RSFhTP7f4wQI+V0ZVI5+11Uzn5XwuPh4Zj1rXuo7zxMXW/9yIZjalHDMXvboXcfNDwLu6OGY6ouSpxZlKQWUZoxh5K8hZQWrSQnZ17ShmN2GV387Z2/AeC2ublxiYTlQkxaQR+885wVgu1/AvwJehak5MHiq6wgrGIDqPIhSYhEFEUBhwPN4QAmx4TJkVVww+FadGgWiA/XAh4PO7ZuZdmiRSj+AIanH9PjxfB4MLwezH4PhtcbXx7Z92J6PEkN4cxAALOrC6Or68SVT0Z0L7dwr7Xherm53ScI2gZ6uWGzobe3h3p1RQ1jPB4axtjSTLClNSkr/ipu90CwFT2MMTr8KihAnWRBshCTSuFiuPJn8O5vwvZ74fV7oLfJOtb4NjzyKXj2G1bPsjM+jnLkVea0/ss6bnPB++4Fx4mHCOe4crhk9iVcMvsSAI71HGNr49bI1uHriNRt9jTz2OHHeOzwYwBUZlayrngd64rXsbpoNemOmbVo26gDsdtvv50XXniBX/7yl3zsYx/j7rvvpr6+nl//+tf84Afx6eVI3HbbbTJEUogxEhmOyXvijhl6kJbWPdQ17aC+bT/13Uep62+KDMdsUa1VegaLHo5JZDjmW1BjHXcbJiWmSqktlRJXLiVpJZRmz6Ukr4rS4lWkpI088H7J+xIBw3pjd+3Ca8lx5ZzMP4MQYqwE/XD4Rah+GPb90xoWMJg7GxZdCUuugYqzQJt5c1kIMR0oimJN0G+3o6aeOKQLBAL0+HxknMLcdqZpYvp8GB4PpsdjBWUeL6anPxSmhctD+14PRoKgzfRG1QmfJ/T4ZARIEePQy+2U2GzY8vNj5+iKHsYYCrzUtDQZViVEsqTmwjlfgg2fgz1/t4ZONuywjvUehxe+Cy/dgRb9/uji71mB2kkoSy+jLL2M981/H4ZpcKDjAFsbt7KlcQtvHn8TT3BgJdcjXUc40nWEB/Y9gKqoLMldYg2vnLWeZfnLcGjTY3qEoYz6Heljjz3G/fffz7ve9S5uvPFGzj77bObOnUtFRQV/+tOf+MhHPjIW7RRCjAFVs1FYuJTCwqUJh2P6fT00NL5JXfNO6jsOUt9zjLrQcMx6gnQPOxzT5B2zFzy94KmBls0DwzENkxLslNozKHHnU5JeRmnuAkoKllJUtBy73fompLGvkTf8bwCQYkvhhqobxuBfQQgxanoAjmyyeoLtfRy8nfF1XJmw6AqrJ1jluaDJpMVCiNFTFMUajuhyQXb2mDyHGQjEhmuhnmlGJGjrx/R6Q0FbdAAXCtwS9XLr98ScczxoOTnDztFlKyhAy8mZMosqCTHt2Byw9ANw+vvh2FYrGNv7mDWUUveh6D4AjIVXoJ6RnDmTVUVlYc5CFuYs5Pqq6wnoAd5ueZvXGq0J+ne37kY3rfjeMA12tu5kZ+tO7tl1Dy7NxcrClZEJ+hfmLERVptfvj1EHYu3t7cyZMwew5gtrb28H4KyzzuLWW29NbuuEEBPK4Uxn9uxzmT373ITHu7uOUd/0JvUte6jrPERdXwN13jbqdQ8NqoH/BKtj7ooMx9wPjVb34PBwzBLVSY9mQw99v/qRtLlkv/lHUO3WECvNDqpt4L5qiyqzjex+pEwLnSd0X1ETTnIpxIymB6HmFWti/L2Pgac9vo4zw5ostupqmHNezJwYQggxWSl2O5rdjpY+NkOFTNO0ArVBQVukl1t/uAfb8EGb6fdjy82xQq78qJ5dhYXY8vKsxS6EEJOfokD5OmvrrIXXfwPb7wdfF72OApwb/wd1jD6L2DU7ZxSdwRlFZ3Dbitvo9ffyxvE3rICs4TUOdR2K1PXqXjY3bGZzw2YAspxZrClaE5mgvzS9dMr3JB11IDZnzhyOHDlCeXk5Cxcu5MEHH2TNmjU89thjZGVljUEThRCTVUZmGRmZZSxacFXcsfBwzPqmt6hv309d1xHq+o9T5++k3vDRfMLhmD4wrG9JUg2D699+AowRrlKVDNEBWXRgptqs4V7RYdzgcG6kwVvC+7aoMtsI7w/z3NH37Slgd43fv6GY+gwdajaHeoI9Cn0t8XUcabDgUmtS2NPOl2tMCCEGURQlMi/YWPVyE0JMUVnlcNF34NyvEKzZyqbdzVzkzhq3p09zpPGusnfxrrJ3AdDc38zWxq2RHmTN/c2Rup2+Tp6peYZnap4BoCStxJqgv3gda4rWkOvOHbd2J8uoA7Ebb7yRt99+m3PPPZevfOUrXHHFFdx1110EAgHuvPPOsWijEGIKih6OuTLB8fBwzPqWXdS3H6Sup5Y6Tyv1wR7qBg3HvKWji0zDGL/GAxgBawuOzzCHcaGoUFgFFWdaSz1XbIC0golulZhsDMPqxl/9MOz5hzW3xWD2FJh/sRWCzbsQxnHVWSGEEEKIaceZhll5DsG9T0xoMwpSCrjitCu44rQrME2To91Hea3RWr3y9cbX6Qn0ROrW99bz8MGHefjgwwDMz54fmaB/VeEqUuwnXhBgoo06EPviF78Y2b/gggvYt28f27dvZ+7cuSxdujSpjRNCTF8nGo7Z011PTd3r7HnjZa6++DxQASNoDdsygqHAKsF9Q7fmN4qUDXc/tOlRj42cNzDo/lDPGyqbCkwDmnZZ29ZfWWW5cwfCsYoNkFUhw0VnItOEujesEKz679DTEF/H5oJ5F1nDIedfDI7JseqdEEIIIYRIPkVRqMyspDKzkmsXXkvQCLK3bW8kIHuz+c3I4mcABzoOcKDjAPfvuR+bamNp3lLWzVrH+uL1VOVVYVcn33yyp7zMU0VFBRUVFcloixBCRKRnlLBg3uUcOqjC/EvgJFenGhemGZoMc6RBXDhsCw4Tzg1xfySh4FAhYU8jHK8Gopavb3vH2nb8wbqfPgsqQgFZ+QbIXwgy+e70ZJrQ8KY1HLL679B1LL6O5oC5F1qrQ86/BJxp495MIYQQQggx8WyqjdPzT+f0/NP55NJP4gl62NG8IzLEcm/bXszQ54ygEeTN5jd5s/lNfvHWL0ixpbC6aHWkB9lpWadNivnHRhyIbdy4kQceeIDMzEwAfvCDH3DLLbdE5g1ra2vj7LPPZs+ePWPSUCGEmLQUBRTNmsNrsvN0WsPhajZD7RaofzO2h1tPA+z+m7UBuLOhbN1AD7LiZbJa4FRmmtC005oYv/oR6KyJr6PaYe67rZ5gCy61VosUQgghhBAiitvmZsOsDWyYtQGATm8n245v47UGa/6x2p7aSN3+YD+b6jaxqW4TAHnuPNYWr2Vt0VrWz1pPUWrRhLyGEQdiTz/9ND6fL3L/e9/7Hh/4wAcigVgwGGT//v1Jb6AQQogkcmdZw93mX2zd9/dD/XYrHKt5FY5tg0DfQH1PBxx40trAmjuqdHWoB9l6a98x+ecHmNFM0+oZWP2ItbUfiq+j2mDOu6w5wRZutIJQIYQQQgghRijLlcWFFRdyYcWFADT0NrC1cStbGrewtXEr7d6BFcpbPa388/A/+efhfwIwO2N2ZIL+1UWryXSOzxeyIw7ETNMc9r4QQogpyJEClWdbG1hDK5t2Wj3IarZYQZln4I8XgX44ssnawApSZq0YmIesfJ2EKZNF877QnGCPQOuB+OOKBpXnWD3BFl0BKTnj30YhhBBCCDEtzUqbxdXzrubqeVdjmiYHOw9Geo+9cfwNPFGLlx3tPsrR7qP8Zf9fUBWVxTmLrYBs1jpWFKzAqTnHpI2nPIeYEEKIaUSzQ8kqa9vwWWvFwdYDVu+x2i1WUNZdP1DfCELdNmvb/DNAgYLFsfOQZRRP2MuZcVrfGQjBmhNNYaDA7LOsEGzxVZCaN+5NFEIIIYQQM4uiKMzPns/87PlcV3UdAT3ArtZdkQn6d7bsJGgGATBMg91tu9ndtpvf7f4dTs3J8oLlrCu2JuhfmLMQLUlT1Yw4EFMUJW7Ss8kwCZoQQogxpKpQsNDaVn/CGn7XWTswxLJmC7QdjHqACc3V1rbtt1ZR9myoOHOgF1nOHFnJMpnaD1sB2O5H4PiuBBUU699+yTWw6EpILxz3JgohhBBCCBFm1+ysLFzJysKVfHr5p+kL9LH9+HZea7R6kB3sGPh84dN9bG3cytbGrfyUn5LhyGBN0Rprgv5Z6yhPLz/pbGpUQyZvuOEGnE6rq5rX6+WWW24hNdVadj16fjEhhBDTlKJAdoW1LfuQVdbbMtB7rHYzNO2yVt0M6zhqbW/9ybqfVhg1xHI9FFZNjQUJJpOOmoE5wRrfSlynbO1AT7CMWePaPCGEEEIIIUYq1Z7KOaXncE7pOYA1x1g4BNvSuIWmvqZI3W5/N/+q/Rf/qv0XAEWpRawrXheZgyzPPfIRECMOxK6//vqY+x/96Efj6lx33XUjfmIhhBDTRFo+LL7S2gC83XDsdSscq9kC9W+A7h+o33sc9vzd2gCcmVC+NhSSnWnNSWZzjPermPy66qD679aQyPrtieuUrLImxl98FWSVjWvzhBBCCCGESIY8dx6XzbmMy+Zchmma1PbUsrVxa2SIZbe/O1K3qa+Jv7/zd/7+zt8BmJs1l+Xpy0f0PCMOxO69995RvQAhhBAzlCsD5l1gbQABLzS8GZqof7MVlvl7Bur7uuDgM9YGYHNByRlWD7KK9VC6Bpxp4/86JoPuRtjzDysEO7Y1cZ3iZVYIVvUea3iqEEIIIYQQ04SiKFRkVFCRUcEHFnwA3dDZ17EvMkH/juYd+PSBEYvvdL7D/sb9Izq3TKovhBBibNldoXBrg3VfD8Lx3bHzkPW3DtQPeqHmFWsDazXE4mUDQyzL10Nq7vi/jvHS22yFYLsftv6NSLCqc+HpVgBWdTXknjbeLRRCCCGEEGJCaKpGVW4VVblVfOL0T+DTfbzV/JY1/1jDa+xp34OOPqJzSSAmhBBifGk2mLXc2tbdak3U3/bOQDhWu9mauD/M1K0eZg1vwpa7rLL8hQPzkFVsgMzSiXglydPXCnsftUKwmldj52ALy19kTYxfdTXkzRv/NgohhBBCCDHJODUna4vXsrZ4LZ9f+Xm6fF1sOriJq7jqhI+VQEwIIcTEUhQr4MmbB6tusMq66gbCsZrN0LIv9jEt+6xte2g4f2a5NbyyYgOUb7DONdlXsuxvh72PWRPjH3nJCv4Gy503EIIVLBr/NgohhBBCCDGFZDozeVf5u0ZUVwIxIYQQk09mKSx9v7UB9LXBsdcG5iFrfDs2QOqqhZ21sPMv1v2UPChfZ03SX7HeGmKoTYI/eZ5O2PdPa06wwy+CEYyvk10ZCsGusVbgnOzBnhBCCCGEEFPQJPh0IIQQQpxAai4svMzaAHy9ULfNCsdqt1j7Qe9A/f5W2Pe4tQE40qFsjRWOlW+wVmO0u8an7d5u2P+E1RPsnefACMTXySoPTYx/tTVfmoRgQgghhBBCjCkJxIQQQkw9zjQ47TxrAwj6oOGt0BDLLVD7mrV6ZZi/Bw49Z20AmsMKxcrXW73IytZYq2Mmi68XDjxlzQn2zr8gauWbiIxSa2L8JdfArJUSggkhhBBCCDGOJBATQggx9dmcUL7W2s76Ihg6NO+xwrGaV61eZL3HB+rrfqusdgu8cicoKhQuGZikv3wDpOWPrg3+Pjj4jBWCHXwmtsdaWHoxLH6PFYKVnAGqekovWwghhBBCCHFyJBATQggx/agaFJ1ubWtvtlaybD88MMSyZjN0HBmobxrQtNPatv7KKsudOxCOVayHrIr4XlwBDxx81hoOeeApCPTHtyW1wOoJVnU1lK2TEEwIIYQQQohJQAIxIYQQ05+iQO5p1rbyY1ZZd2PUEMstcLwaMAce0/aOtb15v3U/owTK16OWrqG48xja3/8BB58Gf2/886XkweIrrXnBKjZYAZ0QQgghhBBi0pBATAghxMyUUQxL3mttAJ4OqN0aCsk2Q8OO2FUgu+th91/Rdv+VNYnO586GRVdaPcFmnz05VrUUQgghhBBCJCTv1oUQQgiwAq0Fl1gbgL8f6t+wwrGazdZKloOHRLoyYeEVsORqqDwXNPv4t1sIIYQQQggxahKICSGEEIk4UqDyHGsD0APQuBP9yEsc2bWV2e/6GLb5F4LNMbHtFEIIIYQQQoyaBGJCCCHESGh2KF2FUbiU6vY5VMy7CGzSI0wIIYQQQoipSJa6EkIIIYQQQgghhBAzigRiQgghhBBCCCGEEGJGkUBMCCGEEEIIIYQQQswoEogJIYQQQgghhBBCiBlFAjEhhBBCCCGEEEIIMaNIICaEEEIIIYQQQgghZhQJxIQQQgghhBBCCCHEjGKb6AacCtM0Aeju7p7glkx9gUCA/v5+uru7sdvtE90cIQC5LsXkJNelmIzkuhSTkVyXYrKSa1NMRnJdJk84IwpnRkOZ0oFYT08PAGVlZRPcEiGEEEIIIYQQQggxWfT09JCZmTnkccU8UWQ2iRmGwfz589m+fTuKokx0c6a07u5uysrKOHbsGBkZGRPdnClv9erVbNu2baKbMeXJdZlccl0mh1yXySXXZXLIdZlccl0mh1yXySfXZnLItZlccl0mh1yXyWOaJqtWreLAgQOo6tAzhU3pHmKqquJwOIZN/MToZGRkyA9fEmiaJv+OSSTXZXLIdZlccl0mh1yXySXXZXLIdZlccl0mj1ybySXXZnLIdZlccl0mh8PhGDYMg2kwqf5nPvOZiW6CEHHkuhSTkVyXYjKS61JMRnJdislKrk0xGcl1KSajkVyXU3rIpEie7u5uMjMz6erqkjRaTBpyXYrJSK5LMRnJdSkmI7kuxWQl16aYjOS6HH9TvoeYSA6n08k3v/lNnE7nRDdFiAi5LsVkJNelmIzkuhSTkVyXYrKSa1NMRnJdjj/pISaEEEIIIYQQQgghZhTpISaEEEIIIYQQQgghZhQJxIQQQgghhBBCCCHEjCKBmBBCCCGEEEIIIYSYUSQQE0IIIYQQQgghhBAzigRi08j3v/99Vq9eTXp6OgUFBbznPe9h//79MXW8Xi+f+cxnyM3NJS0tjfe+970cP348ps7nPvc5Vq1ahdPpZPny5Qmfa+fOnZx99tm4XC7Kysr40Y9+NFYvS0xx43Vdvvjii1x11VUUFxeTmprK8uXL+dOf/jSWL01MYeP5+zLsnXfeIT09naysrCS/GjFdjOd1aZomd9xxB/Pnz8fpdFJSUsJ3v/vdsXppYgobz+vy6aefZt26daSnp5Ofn8973/tejh49OkavTExlybgu3377ba699lrKyspwu90sWrSIn/70p3HP9eKLL7Jy5UqcTidz587lvvvuG+uXJ6ao8bouH374YS688ELy8/PJyMhg/fr1PP300+PyGqcbCcSmkU2bNvGZz3yG1157jWeffZZAIMBFF11EX19fpM4Xv/hFHnvsMR566CE2bdpEQ0MD11xzTdy5Pv7xj/PBD34w4fN0d3dz0UUXUVFRwfbt2/nxj3/Mt771LX7zm9+M2WsTU9d4XZebN29m6dKl/O1vf2Pnzp3ceOONXHfddTz++ONj9trE1DVe12VYIBDg2muv5eyzz076axHTx3hel5///Of57W9/yx133MG+fft49NFHWbNmzZi8LjG1jdd1eeTIEa666irOP/983nrrLZ5++mlaW1sTnkeIZFyX27dvp6CggD/+8Y9UV1fz7//+73z1q1/lrrvuitQ5cuQIl112Geeddx5vvfUWX/jCF7jpppskfBAJjdd1+dJLL3HhhRfyxBNPsH37ds477zyuuOIKduzYMa6vd1owxbTV3NxsAuamTZtM0zTNzs5O0263mw899FCkzt69e03A3LJlS9zjv/nNb5rLli2LK//FL35hZmdnmz6fL1L25S9/2VywYEHyX4SYdsbqukxk48aN5o033piUdovpbayvy9tvv9386Ec/at57771mZmZmspsvpqmxui737Nlj2mw2c9++fWPWdjF9jdV1+dBDD5k2m83UdT1S9uijj5qKoph+vz/5L0RMK6d6XYZ9+tOfNs8777zI/dtvv92sqqqKqfPBD37QvPjii5P8CsR0NFbXZSKLFy82v/3tbyen4TOI9BCbxrq6ugDIyckBrLQ5EAhwwQUXROosXLiQ8vJytmzZMuLzbtmyhXPOOQeHwxEpu/jii9m/fz8dHR1Jar2YrsbquhzqucLPI8RwxvK6fP7553nooYe4++67k9dgMSOM1XX52GOPMWfOHB5//HEqKyuZPXs2N910E+3t7cl9AWJaGqvrctWqVaiqyr333ouu63R1dfGHP/yBCy64ALvdntwXIaadZF2Xg987btmyJeYcYH3uOdX3qGJmGKvrcjDDMOjp6ZHPPSdBArFpyjAMvvCFL3DmmWeyZMkSAJqamnA4HHHz1xQWFtLU1DTiczc1NVFYWBh3jvAxIYYyltflYA8++CDbtm3jxhtvPJUmixlgLK/LtrY2brjhBu677z4yMjKS2WwxzY3ldXn48GFqamp46KGHuP/++7nvvvvYvn0773vf+5L5EsQ0NJbXZWVlJc888wxf+9rXcDqdZGVlUVdXx4MPPpjMlyCmoWRdl5s3b+Yvf/kLN998c6RsqM893d3deDye5L4QMa2M5XU52B133EFvby8f+MAHktb+mcI20Q0QY+Mzn/kMu3fv5pVXXpnopggRMV7X5QsvvMCNN97IPffcQ1VV1Zg+l5j6xvK6/OQnP8mHP/xhzjnnnKSfW0xvY3ldGoaBz+fj/vvvZ/78+QD87ne/Y9WqVezfv58FCxYk/TnF9DCW12VTUxOf/OQnuf7667n22mvp6enhG9/4Bu973/t49tlnURQl6c8ppodkXJe7d+/mqquu4pvf/CYXXXRRElsnZqrxui7/7//+j29/+9v84x//oKCg4KSfa6aSHmLT0G233cbjjz/OCy+8QGlpaaS8qKgIv99PZ2dnTP3jx49TVFQ04vMXFRXFrRwUvj+a84iZZayvy7BNmzZxxRVX8D//8z9cd911p9psMc2N9XX5/PPPc8cdd2Cz2bDZbHziE5+gq6sLm83G73//+2S9DDHNjPV1WVxcjM1mi4RhAIsWLQKgtrb21Bovpq2xvi7vvvtuMjMz+dGPfsSKFSs455xz+OMf/8hzzz3H1q1bk/UyxDSTjOtyz549vPvd7+bmm2/m61//esyxoT73ZGRk4Ha7k/tixLQx1tdl2J///GduuukmHnzwwbihvWJkJBCbRkzT5LbbbuORRx7h+eefp7KyMub4qlWrsNvtPPfcc5Gy/fv3U1tby/r160f8POvXr+ell14iEAhEyp599lkWLFhAdnb2qb8QMa2M13UJ1rLYl112GT/84Q+H7VYsxHhdl1u2bOGtt96KbP/5n/9Jeno6b731FldffXXSXo+YHsbrujzzzDMJBoMcOnQoUnbgwAEAKioqTvFViOlmvK7L/v5+VDX2o4mmaYDVq1GIaMm6LqurqznvvPO4/vrr+e53vxv3POvXr485B1ife0b7HlXMDON1XQI88MAD3HjjjTzwwANcdtllY/OCZoIJnNBfJNmtt95qZmZmmi+++KLZ2NgY2fr7+yN1brnlFrO8vNx8/vnnzTfeeMNcv369uX79+pjzHDx40NyxY4f5qU99ypw/f765Y8cOc8eOHZFVJTs7O83CwkLzYx/7mLl7927zz3/+s5mSkmL++te/HtfXK6aG8boun3/+eTMlJcX86le/GvM8bW1t4/p6xdQwXtflYLLKpBjOeF2Xuq6bK1euNM855xzzzTffNN944w1z7dq15oUXXjiur1dMDeN1XT733HOmoijmt7/9bfPAgQPm9u3bzYsvvtisqKiIeS4hTDM51+WuXbvM/Px886Mf/WjMOZqbmyN1Dh8+bKakpJj/3//3/5l79+417777blPTNPOpp54a19crpobxui7/9Kc/mTabzbz77rtj6nR2do7r650OJBCbRoCE27333hup4/F4zE9/+tNmdna2mZKSYl599dVmY2NjzHnOPffchOc5cuRIpM7bb79tnnXWWabT6TRLSkrMH/zgB+P0KsVUM17X5fXXX5/w+Lnnnjt+L1ZMGeP5+zKaBGJiOON5XdbX15vXXHONmZaWZhYWFpo33HCDfIEgEhrP6/KBBx4wV6xYYaamppr5+fnmlVdeae7du3ecXqmYSpJxXX7zm99MeI6KioqY53rhhRfM5cuXmw6Hw5wzZ07McwgRbbyuy6F+n15//fXj92KnCcU0TXMUHcqEEEIIIYQQQgghhJjSZA4xIYQQQgghhBBCCDGjSCAmhBBCCCGEEEIIIWYUCcSEEEIIIYQQQgghxIwigZgQQgghhBBCCCGEmFEkEBNCCCGEEEIIIYQQM4oEYkIIIYQQQgghhBBiRpFATAghhBBCCCGEEELMKBKICSGEEEIIIYQQQogZRQIxIYQQQgghhBBCCDGjSCAmhBBCCDFJ3HDDDSiKgqIo2O12CgsLufDCC/n973+PYRgjPs99991HVlbW2DVUCCGEEGKKk0BMCCGEEGISueSSS2hsbOTo0aM8+eSTnHfeeXz+85/n8ssvJxgMTnTzhBBCCCGmBQnEhBBCCCEmEafTSVFRESUlJaxcuZKvfe1r/OMf/+DJJ5/kvvvuA+DOO+/k9NNPJzU1lbKyMj796U/T29sLwIsvvsiNN95IV1dXpLfZt771LQB8Ph9f+tKXKCkpITU1lbVr1/Liiy9OzAsVQgghhJhAEogJIYQQQkxy559/PsuWLePhhx8GQFVVfvazn1FdXc3//u//8vzzz3P77bcDsGHDBn7yk5+QkZFBY2MjjY2NfOlLXwLgtttuY8uWLfz5z39m586dvP/97+eSSy7h4MGDE/bahBBCCCEmgmKapjnRjRBCCCGEENYcYp2dnfz973+PO/ahD32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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "companies.ratios.get_earnings_per_share(trailing=4).T.dropna().plot(\n", " figsize=(15, 3),\n", " title=\"4 Year Trailing Earnings per Share for Apple, Amazon, META and Walmart\",\n", " grid=True,\n", " linestyle=\"-\",\n", " linewidth=2,\n", " xlabel=\"Date\",\n", " ylabel=\"Earnings per Share\",\n", ")\n", "\n", "companies.ratios.get_earnings_per_share(trailing=4, growth=True).T.dropna().plot(\n", " figsize=(15, 3),\n", " title=\"4 Year Trailing Earnings per Share Growth for Apple, Amazon, META and Walmart\",\n", " grid=True,\n", " linestyle=\"-\",\n", " linewidth=2,\n", " xlabel=\"Date\",\n", " ylabel=\"Earnings per Share Growth\",\n", ")" ] }, { "cell_type": "markdown", "id": "658d7f7b", "metadata": {}, "source": [ "It is possible to define custom ratios if the current ratio calculations are not sufficient. Define how each custom ratio needs to be calculated. This can be any of the following structures:\n", "\n", "- **Simple operations such as:** `'Quick Assets': 'Cash and Short Term Investments + Accounts Receivable'`\n", "- **Working with multiple operations:** `'Cash Op Expenses':'Cost of Goods Sold + Selling, General and Administrative Expenses - Depreciation and Amortization'`,\n", "- **Using curly brackets:** `'WC / Net Income as %': '(Working Capital / Net Income) * 100'`,\n", "- **Defining a criteria:** `'Large Revenues': 'Revenue > 1000000000'`,\n", "- **Using actual numbers:** `'Daily Cash Op Expenses': 'Cash Op Expenses / 365'`,\n", "- **Combining earlier defined formulas:** `'Defensive Interval':'Quick Assets / Daily Cash Op Expenses'`\n", "\n", "Not that it is important you follow the NAME - FORMULA format and that you adhere to the financial statement naming. See some of the available fields you can use below, shrunken down for readability." ] }, { "cell_type": "code", "execution_count": 9, "id": "ee2da2f7", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The following names are available to be used in the Custom Ratios calculations.\n", "\n" ] }, { "data": { "text/plain": [ "['CAPEX per Share',\n", " 'Capital Expenditure',\n", " 'Capital Lease Obligations',\n", " 'Cash Beginning of Period',\n", " 'Cash Conversion Cycle (CCC)']" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "companies.ratios.collect_custom_ratios(options=True)[10:15]" ] }, { "cell_type": "markdown", "id": "19853ba6", "metadata": {}, "source": [ "Then create your custom ratios and add them to custom ratios function." ] }, { "cell_type": "code", "execution_count": 10, "id": "1fe66edb", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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2005200620072008200920102011201220132014201520162017201820192020202120222023
AAPLWC / Net Income as %510.5618404.1227362.0423426.1067297.7384149.546865.650845.793579.995712.865116.421360.986757.560324.3117103.33966.74859.8807-18.6137-1.796
Large Revenues1.01.01.01.01.01.01.01.01.01.01.01.01.01.01.01.01.01.01.0
Quick Assets9573000000.012955000000.019415000000.026912000000.026825000000.035544000000.037669000000.047821000000.061187000000.052296000000.071944000000.096454000000.0109854000000.0115296000000.0146361000000.0128388000000.0114145000000.0109236000000.0122540000000.0
Cash Op Expenses11568000000.015925000000.018498000000.024622000000.026843000000.044031000000.070216000000.094609000000.0110679000000.0116305000000.0143161000000.0135065000000.0146152000000.0169558000000.0167480000000.0178419000000.0223670000000.0237536000000.0227550000000.0
Daily Cash Op Expenses31693150.684943630136.986350679452.054867457534.246673542465.7534120632876.7123192372602.7397259202739.726303230136.9863318643835.6164392221917.8082370041095.8904400416438.3562464542465.7534458849315.0685488819178.0822612794520.5479650783561.6438623424657.5342
Defensive Interval302.0526296.9278383.0941398.9473364.7552294.646195.8127184.4926201.784164.1205183.4268260.6575274.3494248.1926318.974262.6493186.2696167.853196.5594
AMZNWC / Net Income as %300.3003442.6316304.6218218.7597269.7339292.9688411.0935-5882.0513600.365-1343.5685432.04782.876476.294166.613773.541629.759557.8887316.0176NaN
Large Revenues1.01.01.01.01.01.01.01.01.01.01.01.01.01.01.01.01.01.00.0
Quick Assets2274000000.02418000000.03817000000.04554000000.07354000000.010349000000.012147000000.014812000000.017214000000.023028000000.026231000000.034320000000.044150000000.057927000000.075837000000.0108938000000.0128940000000.0112386000000.0NaN
Cash Op Expenses7890000000.010107000000.013925000000.018061000000.022900000000.032124000000.045978000000.053862000000.064226000000.075215000000.086416000000.0107433000000.0139448000000.0175992000000.0208060000000.0295320000000.0354396000000.0385338000000.0NaN
Daily Cash Op Expenses21616438.356227690410.958938150684.931549482191.780862739726.027488010958.9041125967123.2877147567123.2877175961643.8356206068493.1507236756164.3836294336986.3014382049315.0685482169863.0137570027397.2603809095890.411970947945.20551055720547.9452NaN
Defensive Interval105.197787.3226100.050692.0331117.2144117.587696.4299100.374797.8281111.7493110.7933116.601115.561120.1382133.041134.6416132.7981106.4543NaN
METAWC / Net Income as %NaNNaNNaNNaNNaN306.4356370.519273.5849798.0416.5306534.897308.5642281.1786196.5584276.8299208.2241115.649140.1853NaN
Large Revenues0.00.00.00.00.01.01.01.01.01.01.01.01.01.01.01.01.01.00.0
Quick AssetsNaNNaNNaNNaNNaN2158000000.04455000000.010796000000.012609000000.012877000000.020993000000.033442000000.047543000000.048701000000.064373000000.073289000000.062037000000.054204000000.0NaN
Cash Op ExpensesNaNNaNNaNNaNNaN659000000.01244000000.02503000000.02642000000.03563000000.04942000000.06950000000.09671000000.016337000000.027370000000.027985000000.038554000000.043641000000.0NaN
Daily Cash Op ExpensesNaNNaNNaNNaNNaN1805479.45213408219.17816857534.24667238356.16449761643.835613539726.027419041095.890426495890.41144758904.109674986301.369976671232.8767105627397.2603119564383.5616NaN
Defensive IntervalNaNNaNNaNNaNNaN1195.25041307.13421574.32681741.97011319.14261550.47451756.30651794.35371088.074858.4635955.8865587.3192453.3457NaN
WMTWC / Net Income as %-42.8265-44.5374-45.7816-85.3743-48.0672-50.436-40.216-46.659-69.8747-50.93-12.186-29.8081-67.7197-191.2087-233.5832-107.4121-19.0822-46.142-141.6353
Large Revenues1.01.01.01.01.01.01.01.01.01.01.01.01.01.01.01.01.01.01.0
Quick Assets7203000000.09076000000.010213000000.09223000000.011180000000.012051000000.012484000000.012487000000.014549000000.013958000000.015913000000.014329000000.012702000000.012370000000.014005000000.015749000000.024257000000.023040000000.016818000000.0
Cash Op Expenses266493000000.0292407000000.0322694000000.0350486000000.0376070000000.0377107000000.0388666000000.0412262000000.0432860000000.0440552000000.0449331000000.0448571000000.0453029000000.0469377000000.0481770000000.0490262000000.0525120000000.0538996000000.0581200000000.0
Daily Cash Op Expenses730117808.2192801115068.4932884093150.6849960235616.43841030328767.12331033169863.01371064838356.16441129484931.50681185917808.21921206991780.82191231043835.61641228961643.83561241175342.46581285964383.56161319917808.21921343183561.64381438684931.50681476701369.8631592328767.1233
Defensive Interval9.865511.329211.5529.604910.850911.664111.723811.055512.268111.564312.926411.659410.23389.619210.610511.725116.860515.602310.5619
\n", "
" ], "text/plain": [ " 2005 2006 2007 \\\n", "AAPL WC / Net Income as % 510.5618 404.1227 362.0423 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 9573000000.0 12955000000.0 19415000000.0 \n", " Cash Op Expenses 11568000000.0 15925000000.0 18498000000.0 \n", " Daily Cash Op Expenses 31693150.6849 43630136.9863 50679452.0548 \n", " Defensive Interval 302.0526 296.9278 383.0941 \n", "AMZN WC / Net Income as % 300.3003 442.6316 304.6218 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 2274000000.0 2418000000.0 3817000000.0 \n", " Cash Op Expenses 7890000000.0 10107000000.0 13925000000.0 \n", " Daily Cash Op Expenses 21616438.3562 27690410.9589 38150684.9315 \n", " Defensive Interval 105.1977 87.3226 100.0506 \n", "META WC / Net Income as % NaN NaN NaN \n", " Large Revenues 0.0 0.0 0.0 \n", " Quick Assets NaN NaN NaN \n", " Cash Op Expenses NaN NaN NaN \n", " Daily Cash Op Expenses NaN NaN NaN \n", " Defensive Interval NaN NaN NaN \n", "WMT WC / Net Income as % -42.8265 -44.5374 -45.7816 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 7203000000.0 9076000000.0 10213000000.0 \n", " Cash Op Expenses 266493000000.0 292407000000.0 322694000000.0 \n", " Daily Cash Op Expenses 730117808.2192 801115068.4932 884093150.6849 \n", " Defensive Interval 9.8655 11.3292 11.552 \n", "\n", " 2008 2009 2010 \\\n", "AAPL WC / Net Income as % 426.1067 297.7384 149.5468 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 26912000000.0 26825000000.0 35544000000.0 \n", " Cash Op Expenses 24622000000.0 26843000000.0 44031000000.0 \n", " Daily Cash Op Expenses 67457534.2466 73542465.7534 120632876.7123 \n", " Defensive Interval 398.9473 364.7552 294.646 \n", "AMZN WC / Net Income as % 218.7597 269.7339 292.9688 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 4554000000.0 7354000000.0 10349000000.0 \n", " Cash Op Expenses 18061000000.0 22900000000.0 32124000000.0 \n", " Daily Cash Op Expenses 49482191.7808 62739726.0274 88010958.9041 \n", " Defensive Interval 92.0331 117.2144 117.5876 \n", "META WC / Net Income as % NaN NaN 306.4356 \n", " Large Revenues 0.0 0.0 1.0 \n", " Quick Assets NaN NaN 2158000000.0 \n", " Cash Op Expenses NaN NaN 659000000.0 \n", " Daily Cash Op Expenses NaN NaN 1805479.4521 \n", " Defensive Interval NaN NaN 1195.2504 \n", "WMT WC / Net Income as % -85.3743 -48.0672 -50.436 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 9223000000.0 11180000000.0 12051000000.0 \n", " Cash Op Expenses 350486000000.0 376070000000.0 377107000000.0 \n", " Daily Cash Op Expenses 960235616.4384 1030328767.1233 1033169863.0137 \n", " Defensive Interval 9.6049 10.8509 11.6641 \n", "\n", " 2011 2012 2013 \\\n", "AAPL WC / Net Income as % 65.6508 45.7935 79.9957 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 37669000000.0 47821000000.0 61187000000.0 \n", " Cash Op Expenses 70216000000.0 94609000000.0 110679000000.0 \n", " Daily Cash Op Expenses 192372602.7397 259202739.726 303230136.9863 \n", " Defensive Interval 195.8127 184.4926 201.784 \n", "AMZN WC / Net Income as % 411.0935 -5882.0513 600.365 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 12147000000.0 14812000000.0 17214000000.0 \n", " Cash Op Expenses 45978000000.0 53862000000.0 64226000000.0 \n", " Daily Cash Op Expenses 125967123.2877 147567123.2877 175961643.8356 \n", " Defensive Interval 96.4299 100.3747 97.8281 \n", "META WC / Net Income as % 370.5 19273.5849 798.0 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 4455000000.0 10796000000.0 12609000000.0 \n", " Cash Op Expenses 1244000000.0 2503000000.0 2642000000.0 \n", " Daily Cash Op Expenses 3408219.1781 6857534.2466 7238356.1644 \n", " Defensive Interval 1307.1342 1574.3268 1741.9701 \n", "WMT WC / Net Income as % -40.216 -46.659 -69.8747 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 12484000000.0 12487000000.0 14549000000.0 \n", " Cash Op Expenses 388666000000.0 412262000000.0 432860000000.0 \n", " Daily Cash Op Expenses 1064838356.1644 1129484931.5068 1185917808.2192 \n", " Defensive Interval 11.7238 11.0555 12.2681 \n", "\n", " 2014 2015 2016 \\\n", "AAPL WC / Net Income as % 12.8651 16.4213 60.9867 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 52296000000.0 71944000000.0 96454000000.0 \n", " Cash Op Expenses 116305000000.0 143161000000.0 135065000000.0 \n", " Daily Cash Op Expenses 318643835.6164 392221917.8082 370041095.8904 \n", " Defensive Interval 164.1205 183.4268 260.6575 \n", "AMZN WC / Net Income as % -1343.5685 432.047 82.8764 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 23028000000.0 26231000000.0 34320000000.0 \n", " Cash Op Expenses 75215000000.0 86416000000.0 107433000000.0 \n", " Daily Cash Op Expenses 206068493.1507 236756164.3836 294336986.3014 \n", " Defensive Interval 111.7493 110.7933 116.601 \n", "META WC / Net Income as % 416.5306 534.897 308.5642 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 12877000000.0 20993000000.0 33442000000.0 \n", " Cash Op Expenses 3563000000.0 4942000000.0 6950000000.0 \n", " Daily Cash Op Expenses 9761643.8356 13539726.0274 19041095.8904 \n", " Defensive Interval 1319.1426 1550.4745 1756.3065 \n", "WMT WC / Net Income as % -50.93 -12.186 -29.8081 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 13958000000.0 15913000000.0 14329000000.0 \n", " Cash Op Expenses 440552000000.0 449331000000.0 448571000000.0 \n", " Daily Cash Op Expenses 1206991780.8219 1231043835.6164 1228961643.8356 \n", " Defensive Interval 11.5643 12.9264 11.6594 \n", "\n", " 2017 2018 2019 \\\n", "AAPL WC / Net Income as % 57.5603 24.3117 103.339 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 109854000000.0 115296000000.0 146361000000.0 \n", " Cash Op Expenses 146152000000.0 169558000000.0 167480000000.0 \n", " Daily Cash Op Expenses 400416438.3562 464542465.7534 458849315.0685 \n", " Defensive Interval 274.3494 248.1926 318.974 \n", "AMZN WC / Net Income as % 76.2941 66.6137 73.5416 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 44150000000.0 57927000000.0 75837000000.0 \n", " Cash Op Expenses 139448000000.0 175992000000.0 208060000000.0 \n", " Daily Cash Op Expenses 382049315.0685 482169863.0137 570027397.2603 \n", " Defensive Interval 115.561 120.1382 133.041 \n", "META WC / Net Income as % 281.1786 196.5584 276.8299 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 47543000000.0 48701000000.0 64373000000.0 \n", " Cash Op Expenses 9671000000.0 16337000000.0 27370000000.0 \n", " Daily Cash Op Expenses 26495890.411 44758904.1096 74986301.3699 \n", " Defensive Interval 1794.3537 1088.074 858.4635 \n", "WMT WC / Net Income as % -67.7197 -191.2087 -233.5832 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 12702000000.0 12370000000.0 14005000000.0 \n", " Cash Op Expenses 453029000000.0 469377000000.0 481770000000.0 \n", " Daily Cash Op Expenses 1241175342.4658 1285964383.5616 1319917808.2192 \n", " Defensive Interval 10.2338 9.6192 10.6105 \n", "\n", " 2020 2021 2022 \\\n", "AAPL WC / Net Income as % 66.7485 9.8807 -18.6137 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 128388000000.0 114145000000.0 109236000000.0 \n", " Cash Op Expenses 178419000000.0 223670000000.0 237536000000.0 \n", " Daily Cash Op Expenses 488819178.0822 612794520.5479 650783561.6438 \n", " Defensive Interval 262.6493 186.2696 167.853 \n", "AMZN WC / Net Income as % 29.7595 57.8887 316.0176 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 108938000000.0 128940000000.0 112386000000.0 \n", " Cash Op Expenses 295320000000.0 354396000000.0 385338000000.0 \n", " Daily Cash Op Expenses 809095890.411 970947945.2055 1055720547.9452 \n", " Defensive Interval 134.6416 132.7981 106.4543 \n", "META WC / Net Income as % 208.2241 115.649 140.1853 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 73289000000.0 62037000000.0 54204000000.0 \n", " Cash Op Expenses 27985000000.0 38554000000.0 43641000000.0 \n", " Daily Cash Op Expenses 76671232.8767 105627397.2603 119564383.5616 \n", " Defensive Interval 955.8865 587.3192 453.3457 \n", "WMT WC / Net Income as % -107.4121 -19.0822 -46.142 \n", " Large Revenues 1.0 1.0 1.0 \n", " Quick Assets 15749000000.0 24257000000.0 23040000000.0 \n", " Cash Op Expenses 490262000000.0 525120000000.0 538996000000.0 \n", " Daily Cash Op Expenses 1343183561.6438 1438684931.5068 1476701369.863 \n", " Defensive Interval 11.7251 16.8605 15.6023 \n", "\n", " 2023 \n", "AAPL WC / Net Income as % -1.796 \n", " Large Revenues 1.0 \n", " Quick Assets 122540000000.0 \n", " Cash Op Expenses 227550000000.0 \n", " Daily Cash Op Expenses 623424657.5342 \n", " Defensive Interval 196.5594 \n", "AMZN WC / Net Income as % NaN \n", " Large Revenues 0.0 \n", " Quick Assets NaN \n", " Cash Op Expenses NaN \n", " Daily Cash Op Expenses NaN \n", " Defensive Interval NaN \n", "META WC / Net Income as % NaN \n", " Large Revenues 0.0 \n", " Quick Assets NaN \n", " Cash Op Expenses NaN \n", " Daily Cash Op Expenses NaN \n", " Defensive Interval NaN \n", "WMT WC / Net Income as % -141.6353 \n", " Large Revenues 1.0 \n", " Quick Assets 16818000000.0 \n", " Cash Op Expenses 581200000000.0 \n", " Daily Cash Op Expenses 1592328767.1233 \n", " Defensive Interval 10.5619 " ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "custom_ratios = {\n", " \"WC / Net Income as %\": \"(Working Capital / Net Income) * 100\",\n", " \"Large Revenues\": \"Revenue > 1000000000\",\n", " \"Quick Assets\": \"Cash and Short Term Investments + Accounts Receivable\",\n", " \"Cash Op Expenses\": \"Cost of Goods Sold + Selling, General and Administrative Expenses \"\n", " \"- Depreciation and Amortization\",\n", " \"Daily Cash Op Expenses\": \"Cash Op Expenses / 365\",\n", " \"Defensive Interval\": \"Quick Assets / Daily Cash Op Expenses\",\n", "}\n", "\n", "companies.ratios.collect_custom_ratios(custom_ratios_dict=custom_ratios)" ] }, { "cell_type": "markdown", "id": "4306cd49", "metadata": {}, "source": [ "It is also relatively straight forward to use the actual models provided you have the data available to flow through these functions. While the `Toolkit` class itself parses data from Financial Modeling Prep, if you utilize the individual models you can provide your own data as well while reaching the same results." ] }, { "cell_type": "code", "execution_count": 11, "id": "c38bb4b6", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Asset TurnoverQuick RatioReturn on AssetsDebt to AssetsPrice to Earnings
00.21.23076923076923080.457142857142857130.560.0
10.265060240963855441.16666666666666670.160.785714285714285727.5
20.38709677419354841.63636363636363650.114285714285714280.75120.0
30.651.13333333333333330.066666666666666670.81259.09090909090909
40.81.60.0421052631578947360.2666666666666666625.0
\n", "
" ], "text/plain": [ " Asset Turnover Quick Ratio Return on Assets \\\n", "0 0.2 1.2307692307692308 0.45714285714285713 \n", "1 0.26506024096385544 1.1666666666666667 0.16 \n", "2 0.3870967741935484 1.6363636363636365 0.11428571428571428 \n", "3 0.65 1.1333333333333333 0.06666666666666667 \n", "4 0.8 1.6 0.042105263157894736 \n", "\n", " Debt to Assets Price to Earnings \n", "0 0.5 60.0 \n", "1 0.7857142857142857 27.5 \n", "2 0.75 120.0 \n", "3 0.8125 9.09090909090909 \n", "4 0.26666666666666666 25.0 " ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from financetoolkit.ratios import (\n", " efficiency_model,\n", " liquidity_model,\n", " profitability_model,\n", " solvency_model,\n", " valuation_model,\n", ")\n", "\n", "# Note: this is dummy data, not actual data\n", "\n", "asset_turnover = efficiency_model.get_asset_turnover_ratio(\n", " sales=pd.Series([100, 110, 120, 130, 80]),\n", " total_assets_begin=pd.Series([500, 400, 300, 200, 100]),\n", " total_assets_end=pd.Series([500, 430, 320, 200, 100]),\n", ")\n", "\n", "quick_ratio = liquidity_model.get_quick_ratio(\n", " cash_and_equivalents=pd.Series([100, 110, 120, 130, 80]),\n", " accounts_receivable=pd.Series([30, 20, 30, 20, 40]),\n", " marketable_securities=pd.Series([30, 10, 30, 20, 40]),\n", " current_liabilities=pd.Series([130, 120, 110, 150, 100]),\n", ")\n", "\n", "return_on_assets = profitability_model.get_return_on_assets(\n", " net_income=pd.Series([80, 40, 40, 30, 20]),\n", " total_assets_begin=pd.Series([150, 200, 300, 400, 500]),\n", " total_assets_end=pd.Series([200, 300, 400, 500, 450]),\n", ")\n", "\n", "debt_to_assets = solvency_model.get_debt_to_assets_ratio(\n", " total_debt=pd.Series([100, 110, 120, 130, 80]),\n", " total_assets=pd.Series([200, 140, 160, 160, 300]),\n", ")\n", "\n", "price_to_earnings = valuation_model.get_price_earnings_ratio(\n", " stock_price=pd.Series([30, 11, 12, 10, 30]),\n", " earnings_per_share=pd.Series([0.5, 0.4, 0.1, 1.1, 1.2]),\n", ")\n", "\n", "components = {\n", " \"Asset Turnover\": asset_turnover,\n", " \"Quick Ratio\": quick_ratio,\n", " \"Return on Assets\": return_on_assets,\n", " \"Debt to Assets\": debt_to_assets,\n", " \"Price to Earnings\": price_to_earnings,\n", "}\n", "\n", "\n", "pd.DataFrame(components)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.9" } }, "nbformat": 4, "nbformat_minor": 5 }