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diff --git a/appendix/glossary.tex b/appendix/glossary.tex index c16c2a8..b7b53f2 100644 --- a/appendix/glossary.tex +++ b/appendix/glossary.tex @@ -4,3 +4,9 @@ \newacronym{nersc}{NERSC}{National Energy Research Scientific Computing Center} \newacronym{lrz}{LRZ}{Leibniz Supercomputing Centre} \newacronym{sla}{SLA}{Service Level Agreements} +\newacronym{ai}{AI}{Artificial Intelligence} +\newacronym{ml}{ML}{Machine Learning} +\newacronym{dcdt}{DCDT}{Datacenter Digital Twins} +\newacronym{genai}{GenAI}{Generative Artificial Intelligence} +\newacronym{llm}{LLMS}{Large Language Models} +\newacronym{iot}{IoT}{Internet-of-Things} diff --git a/bsc/1.txt b/bsc/1.txt new file mode 100644 index 0000000..89d32ba --- /dev/null +++ b/bsc/1.txt @@ -0,0 +1,53 @@ +==13-05-2026== +Introduction: +Make a compelling story about what the adventure is upon you and what problem you set out to solve. +You can think of it as a classical novel. +Make a protagonist; there is a protagonist, he encounters and issue and overcomes it. +Except it's just more technical. + +Status update template: +Since last meeting, I changed ___ in the thesis text. +I changed ___ in the artifact / experiments. +My next concrete deliverable is ___. +My main blocker is ___. + +Try to find good references in the CompSys manifesto. +This should contain ``good'' references. +Paralysis analysis. +You should write your thesis at the same time as your coding. +DO NOT leave out the thesis as the last part, after all coding is done. +Do both in parallel. + +The `gap` in the presentation slides is `...and this has not yet been done before.` or `we are the first to do...` etc. +`Gap` => nobody did this before (or a knowledge gap). +E.g., a system does not exist. The key is that it is missing worldwide from the scientific community. +Nobody has done yet => part of a `scientific` project. +Why is my project scientific? Because nobody did it yet. + +How to backup that something does not exist? +You cannot cite work that does not exist. +You cannot cite non existing thing, because it's not there. +Typically, you show instead how existing falls short. +1/ State the problem, why it's important. +2/ Refer to recent and impactful work on datacenter simulation or digital twinning. +2a/ Write in a few sentences that this other work did `xyz` and say why `xyz` is NOT ENOUGH to advance the problem you introduce earlier. +You can just say that `this is missing from their work, or I think that this is missing`. +Now YOU need to make a claim, `this is true`, or `nobody did this`. +Making such a claim is bold and YOU could be wrong, but STILL make that claim, but then cite the related work, make the claim `they don't do x`, and then go to your supervisor and tell him `in my mind this is the key issue with my thesis, do you agree with this? Is there any work I Should have cited? Am I misinterpreting anything those other projects did?`Bring this up with a conversation with your supervisor. + +Answer to each research questions is one of your main contributions. +They are the main way the reader can understand what you have done. +System design => contribution to question on ``How to design a ...?'' +Each contribution => a section in your thesis. Core content of the thesis. 3-4 sections. +Each section corresponds directly to a research question. + +Make a skeleton of the thesis first. Very important! +This way you can plan your own work much better => do this. +Map the thesis before writing text. +Put the skeleton in the shared folder. + +Each RQ should be enumerated, you want every question to be not just a nice isolated question,but add a bit of context below: 1) describe why it's important 2) say why it's challenging 3) say what makes it scientific. + +You can take whatever structure you want from any report, no plagiarism nor declarations needed. + + diff --git a/bsc/20260513_133444.png b/bsc/20260513_133444.png Binary files differnew file mode 100644 index 0000000..ed2124d --- /dev/null +++ b/bsc/20260513_133444.png diff --git a/bsc/20260513_135756.png b/bsc/20260513_135756.png Binary files differnew file mode 100644 index 0000000..a0729d8 --- /dev/null +++ b/bsc/20260513_135756.png diff --git a/bsc/20260513_140254.png b/bsc/20260513_140254.png Binary files differnew file mode 100644 index 0000000..3ebc53a --- /dev/null +++ b/bsc/20260513_140254.png diff --git 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commercially, for example in datacenters, predictive modelling is often referred to as predictive analytics~\cite{Wikipedia:PredictiveModelling}. +Almost any statistical model can be used for prediction purposes, but nowadays predictive analysis is synonymous with machine learning. +A primary example of popular analysis type is linear regression. +A major limitation of predictive analytics is that history cannot always predict the future. +Using historical data to predict outcomes works only under the assumption that there are certain long lasting patterns in the system. +Additionally, no matter how extensive is the training data, there is always the possibility of new variables that have not been considered or even defined, yet are critical to the outcome of the prediction~\cite{Wikipedia:PredictiveModelling}. + +%Here you have to cite Deisenroth, 2024, chapter 8.1.4. +An inference function is a machine learning model which uses probabilistic parameter estimation~\cite{}. +A prime example of using probability to find a good machine learning model is Bayesian inference. +% Stanford Encyclopedia of Philosophy, Douven 2017 +The process of inference from data to provide the best explanation is called abduction. + + + +A \gls{dt} is a digital model of an intended or actual real-world system that serves as a digital counterpart of it for purposes such as simulation, integration, testing, monitoring and maintenance %cite the Wikipedia page here!. +The system requires real-time synchronization with the actual system. +A closed loop of continuous feedback exists between the digital twin and physical object. + +The digital twin replicates the physical system to predict failures and opportunities for changing, to prescribe real-time actions for optimizing and/or mitigating unexpected events, observing and evaluating the profile of the system. + +A digital twin is often called a virtual twin. + +The communication between a physical entity and the digital twin is referred to as a digital thread. + +One key application is predictive maintenance, where the digital twin analyzes operational data (e.g., temperature, vibration) to predict when a component is likely to fail. + +This allows maintenance to be scheduled proactively, reducing unplanned downtime and preventing catastrophic failures. + +%Include something about data-preprocessing in the pipeline. +%See the article by Fei Tao + +One of the key arguments that speak for a datacenter digital twin is that datacenters already connect hundreds of monitoring sensors and data coming from them. +Monitoring of server racks, VM's, CPU profiling and all that give us lots of data. + +Data analytics, such as ODA can give actual meaningful insights into what we are doing. +Moreover, advanced technologies have made sensors, IoT give us much information. +ODA can predict failures, help maintain the equipment, save bills, cut costs. +But currently one of the key challenges is to somehow connect the physical and virtual spaces. +The answer to how to do this is a digital twin. + +Since DT's are relatively a new concept, I think they require a short introduction to their history. +It's enough to mention that the first presentation was done by Grieves in 2003, from 2003 to 2018 we have seen a slow incline in numbers of papers (around 50) and now DT's are re-emerging. + +You must include the DT white paper from 2014. + +The concept of a \gls{dt} dates back to 2003, when Dr. Michael Grieves of Dassault Syst\'emes introduced the 3 core components of a \gls{dt}: the virtual entity, physical entity and the two-way connection (see Figure \ref{fig:five_dimensional_dt}). +Due to insufficient technological foundations, little work is available on \gls{dt}s between 2003 and 2018~\cite{DBLP:conf/cirp/TAO2018169}, and it is only with the rapid growth of cloud computing, \gls{iot} and big data analytics that \gls{dt}s have re-emerged. +Today, research is focused on bridging the gap between the long-established foundations of \gls{dt}s and new, novel applications in academia and industry, such as the \gls{dcdt}. +%[citation needed] + +As of 2026, there is a lack of consensus of what is a digital twin. +By proxy, there is neither consensus on what is the definition of a datacenter digital twin. +A generic definition is needed. + + +Most of \gls{dt} usages are related to prognostics and health management. + + +One of the many applications of \gls{dt} is timely system maintenance. +In aerospace engineering, the \gls{dt} can reliably manage the health of the physical entity by detecting \eg fatigue cracks on aircraft wings or damage to the wind turbine blades~\cite{DBLP:conf/cirp/TAO2018169}. +A forecast of future maintenance and virtual health management are the prime purpose of many \gls{dt}s~\cite{DBLP:conf/AIAA/Teugel2012}. + +Optimal datacenter management is characterized by high service availability and low downtime. +However, achieving this in a 21\textsuperscript{st} century datacenter requires revolutionary changes in the way datacenters are operated and maintained. +A concept that creates just such a revolutionary change is the \gls{dcdt}. +% This sentence is stolen from an article. +% Make sure to paraphrase it. + +% This is stolen from the AIAA article. +% Make sure to paraphrase this. + -\todo{ -This section provides the necessary context to help the reader understand the -remainder of the thesis. -} -\lipsum[1-8] diff --git a/content/intro.tex b/content/intro.tex index 58a759a..246d8bf 100644 --- a/content/intro.tex +++ b/content/intro.tex @@ -1,39 +1,81 @@ \chapter{Introduction}\label{s:intro} -Today's transportation systems, education and government largely depend on server-side services, which are hosted in datacentres~\cite{DBLP:journals/corr/IosupKLVG22}. -To facilitate the rising demand managers expand datacenters with new components and more heterogenous architectures (e.g., GPUs and NPUs)~\cite{DBLP:conf/date/MilojicicFDR21}. +Modern society is a technological society. +Presently, computer and network ecosystems play a crucial part not only in the digital industry, but also in everyone's daily lives. +Today, the transport, education and government sectors largely depend on server-side services, which are hosted in datacentres~\cite{DBLP:journals/corr/IosupKLVG22}. +To address the recent rise in demand due to the \gls{ai} revolution managers expand datacenters with new components and more heterogenous architectures (e.g., GPUs and NPUs)~\cite{DBLP:conf/date/MilojicicFDR21}. However, in return datacenter complexity increases significantly. -To make better operational decisions despite the massive scale, new, promising technologies arise, such as datacenter Digital Twins. +To make better operational decisions despite the massive scale, promising technologies arise such as \gls{dcdt}. \section{Context}\label{s:context} -Datacenters are one of the most important components of the digital society. -For example, over 25\% of professionals in the Netherlands depend on cloud services in their everyday work. -Faced with growing demand, this fraction will exceed 35\% by 2025~\cite{DBLP:journals/corr/IosupKLVG22}. -What is more, the surge of AI and Machine Learning workloads opens the need for versatile server architectures, pushing datacenter managers to meet customer expectations by adding more specialized hardware~\cite{DBLP:conf/date/MilojicicFDR21}. -In return, operating a modern datacenter with thousands of diversified servers presents a yet unsolved, non-trivial challenge that requires fast and well-informed decisions from on-site engineers. +% Why is it important? +Datacenters house large volume of computers for processing and storage of data from various organizations and fields of activity. +76\% of large companies worldwide spend more than 5 million USD\$ on hosted services each month, making datacenters one of the most important components of the digital society~\cite{DBLP:report/Flexera2026}. +Additionally, in Netherlands alone over 25\% of professionals depend on cloud services in their everyday work. +Faced with growing demand, this fraction will exceed 35\% by 2025~\cite{DBLP:journals/corr/IosupKLVG22}. +% Why is this a problem now? -To aid in datacenter management, operators turn to \gls{oda}, which is the process of analyzing monitoring data to gain insights into the system behavior. -For example, OMNI at \gls{nersc} and Wintermute at \gls{lrz} employ descriptive analytics to optimize power usage effectivenes~\cite{DBLP:conf/icppw/BourassaJBCJVS19} and prescriptive analysis for energy efficient scheduling~\cite{DBLP:conf/hpdc/NettiMGOTO020}. -Nonetheless, we observe a critical lack of predictive analysis capabilities~\cite{DBLP:conf/wosp/SumanCNTMI24} among the existing \gls{oda} frameworks. -In result, datacenter operators are often confronted with operational decisions with limited time to react, which can lead to missed \gls{sla}. +The increasing popularity of \gls{genai} and monthly releases of powerful \gls{llm} have driven the demand for datacenter services for the past 4 years. +In the \gls{ai} economy datacenters need diverse and scalable server architectures, because inference-based workloads require more heterogenous server components (GPUs, TPUs, NPUs \etc) to perform well. +As such, datacenter operators try to meet customer expectations by adding more specialized hardware~\cite{DBLP:conf/date/MilojicicFDR21}, at a cost of increased system complexity. +In return, operating a modern datacenter warehouse with thousands of diversified servers presents a difficult challenge that requires fast and well-informed decisions from on-site engineers. -``Lab-built, preproduction, or early hardware does \textit{not} work as defined, does \textit{not} work reliably and does \textit{not} stay the same from day to day'', -according to Frederick P. Brooks. -A solution is a dependable simulator of the system~\cite{DBLP:books/daglib/Brooks0080747}. -A novel improvement on simulation is a datacenter \gls{dt}~\cite{DBLP:journals/computer/AthavaleBBMMPS24}. +Quick and correct decision-making in a 21\textsuperscript{st} century datacenter is a hard task. +Oftentimes unexpected events such as \eg service failures or hardware faults result in a downtime that disturbs the users and produces unfulfilled \gls{sla}. +What is more, the rapid expansion of datacenters promotes increased presence of failures across all cloud services~\cite{DBLP:conf/acsos/TalluriOVTI21}. +Currently, preventing service outages in advance could help datacenter operators reduce substantial operational costs, as over 20\% of all reported failure-caused outages amount to more than 1 million US\$~\cite{DBLP:report/AnnualOutageAnalysis2025}. +However, predicting datacenter behaviour quickly and reliably is a non-trivial problem that still remains insufficiently unaddressed~\cite{DBLP:conf/wosp/SumanCNTMI24}. +\begin{figure} + \centering + \includegraphics[width=0.95\linewidth]{images/five_dimensional_dt.pdf} + \caption{A basic framework for the \gls{dt}. Four core elements of a \gls{dt} are defined: The physical entity \one and the simulated virtual twin \two. A service for out-of-band data analytics \three and a persistent storage of historical data \four are crucial to the \gls{dt} because they are necessary to gain meaningful monitoring insights. Adapted from Tao \etal ~\cite{DBLP:conf/cirp/TAO2018169}.} + %Fei Tao is a renowned figure with over 62k citations. He is a figure of authority on digital twins.% + \label{fig:five_dimensional_dt} +\end{figure} +% (3) in the original paper by Fei Tao is referenced to just `Services`. +% Nonetheless I name them here as Data Analysis Services, because what Fei Tao lists (e.g., fault detection, fault determination, fault-tolerant management, maintenance) is inherently reliant on good data analytics. +The expanding \gls{ai} economy and the end of Moore's law have resulted in the rise of more heterogeneous datacenter architectures~\cite{DBLP:conf/date/MilojicicFDR21}. +This means that in modern datacenters there are more server racks and each rack may contain multiple different hardware architectures. +These events have created a need for: +\begin{enumerate} + \item More careful datacenter management to tackle the unprecedented complexity + \item Greater availability of cloud services + \item Lesser downtime and lower electricity cost +\end{enumerate} +Specific goals that can help satisfy these needs are: +\begin{enumerate} + \item Reducing the downtime of failured-caused outages + \item Maximising the monitoring insights that can help make better informed operational decisions + \item Minimizing the downtime caused by server maintenance and hardware inspections +\end{enumerate} + +A \gls{dcdt} mirrors the structure, context and behaviour of a datacenter~\cite{DBLP:journals/computer/AthavaleBBMMPS24}. +Crucial to \gls{dt} operation are predictive capabilities and the continuous interaction with the real-world datacenter. +There already exist digital twin deployments. +For example, ExaDigiT~\cite{DBLP:conf/sc/BrewerMKWBHSGGW24} is a framework for digital twin development of supercomputers. +It has been demonstrated at the Frontier supercomputer and it facilitates virtual prototyping and system optimization, however it lacks core \gls{dt} functions, such as reliable predictive analytics. \section{Problem statement}\label{s:problem-statement} +In this work we argue that the current state-of-the-art ICT Digital Twins lack predictive capabilities that are essential to real-time facility management. +We propose that digital twinning can be enhanced by integrating \gls{oda} through predictive analytics. + \section{Research Questions}\label{s:research-questions} +We divide the problem of enabling predictive analytics using digital twinning into three research questions: +\begin{enumerate}[label=\textbf{RQ\arabic*.}, align=left] + \item \textbf{How to define 5 \gls{dcdt} use-cases and their functional and non-functional requirements?} + \item \textbf{How to design a \gls{dcdt} system model using discrete-event simulation and operational data analysis?} + \item \textbf{How to validate if the \gls{dcdt} system meets the functional and non-functional requirements?} +\end{enumerate} \section{Research Methodology}\label{s:research-methodology} \section{Thesis Contributions}\label{s:thesis-contributions} \section{Plagiarism Declaration}\label{s:plagiarism-declaraion} -I hereby declare that this thesis is my own independent work and writing. +I hereby declare that this thesis is my own independent work and writing. The thesis does not contain any material copied from other sources (person, Internet, or AI), and has not been submitted for assessment elsewhere. \section{Societal Impact}\label{s:societal-impact} diff --git a/datasets/Talluri2021/.gitignore b/datasets/Talluri2021/.gitignore new file mode 100644 index 0000000..b561863 --- /dev/null +++ b/datasets/Talluri2021/.gitignore @@ -0,0 +1,140 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +cover/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +.pybuilder/ +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# pyenv +# For a library or package, you might want to ignore these files since the code is +# intended to run in multiple environments; otherwise, check them in: +# .python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# pytype static type analyzer +.pytype/ + +# Cython debug symbols +cython_debug/ + +.DS_Store
\ No newline at end of file diff --git a/datasets/Talluri2021/1.compare_github_and_outagereport.ipynb b/datasets/Talluri2021/1.compare_github_and_outagereport.ipynb new file mode 100644 index 0000000..1588f8e --- /dev/null +++ b/datasets/Talluri2021/1.compare_github_and_outagereport.ipynb @@ -0,0 +1,749 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "from plotnine import *\n", + "from datetime import datetime\n", + "import numpy as np\n", + "import itertools" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "github_incidents = pd.read_parquet('./github_failures_2019-20').reset_index(drop=True)\n", + "or_events = pd.read_parquet('./outage_report_2019-20')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "github_incidents['start_time'] = pd.to_datetime(github_incidents['event_start_time'], unit='s')\n", + "github_incidents['end_time'] = pd.to_datetime(github_incidents['event_end_time'], unit='s')\n", + "\n", + "github_filter_mask = (github_incidents['event_start_time'] != -1) & (github_incidents['event_end_time'] != -1)\n", + "filtered_github_incidents = github_incidents[github_filter_mask].reset_index(drop=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>status</th>\n", + " <th>event_start_time</th>\n", + " <th>event_end_time</th>\n", + " <th>vendor</th>\n", + " <th>start_time</th>\n", + " <th>end_time</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>0</th>\n", + " <td></td>\n", + " <td>-1</td>\n", + " <td>-1</td>\n", + " <td></td>\n", + " <td>1969-12-31 23:59:59</td>\n", + " <td>1969-12-31 23:59:59</td>\n", + " </tr>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>\\n\\n\\n\\nResolved -\\n \\t2019-05-07 10:35 U...</td>\n", + " <td>-1</td>\n", + " <td>1557225300</td>\n", + " <td>Github</td>\n", + " <td>1969-12-31 23:59:59</td>\n", + " <td>2019-05-07 10:35:00</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2</th>\n", + " <td>\\n\\n\\n\\nResolved -\\n \\tWebhook deliveries...</td>\n", + " <td>-1</td>\n", + " <td>1585641600</td>\n", + " <td>Github</td>\n", + " <td>1969-12-31 23:59:59</td>\n", + " <td>2020-03-31 08:00:00</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3</th>\n", + " <td>\\n\\n\\n\\nResolved -\\n \\tWe have identified...</td>\n", + " <td>-1</td>\n", + " <td>1586352600</td>\n", + " <td>Github</td>\n", + " <td>1969-12-31 23:59:59</td>\n", + " <td>2020-04-08 13:30:00</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " status event_start_time \\\n", + "0 -1 \n", + "1 \\n\\n\\n\\nResolved -\\n \\t2019-05-07 10:35 U... -1 \n", + "2 \\n\\n\\n\\nResolved -\\n \\tWebhook deliveries... -1 \n", + "3 \\n\\n\\n\\nResolved -\\n \\tWe have identified... -1 \n", + "\n", + " event_end_time vendor start_time end_time \n", + "0 -1 1969-12-31 23:59:59 1969-12-31 23:59:59 \n", + "1 1557225300 Github 1969-12-31 23:59:59 2019-05-07 10:35:00 \n", + "2 1585641600 Github 1969-12-31 23:59:59 2020-03-31 08:00:00 \n", + "3 1586352600 Github 1969-12-31 23:59:59 2020-04-08 13:30:00 " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Need to incorporate these later. IMPORTANT\n", + "github_incidents.loc[~github_filter_mask].reset_index(drop=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>status</th>\n", + " <th>event_start_time</th>\n", + " <th>event_end_time</th>\n", + " <th>vendor</th>\n", + " <th>start_time</th>\n", + " <th>end_time</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>minor</td>\n", + " <td>1569502020</td>\n", + " <td>1569506460</td>\n", + " <td>Github</td>\n", + " <td>2019-09-26 12:47:00</td>\n", + " <td>2019-09-26 14:01:00</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3</th>\n", + " <td>minor</td>\n", + " <td>1569324600</td>\n", + " <td>1569334080</td>\n", + " <td>Github</td>\n", + " <td>2019-09-24 11:30:00</td>\n", + " <td>2019-09-24 14:08:00</td>\n", + " </tr>\n", + " <tr>\n", + " <th>4</th>\n", + " <td>critical</td>\n", + " <td>1569255120</td>\n", + " <td>1569256620</td>\n", + " <td>Github</td>\n", + " <td>2019-09-23 16:12:00</td>\n", + " <td>2019-09-23 16:37:00</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " status event_start_time event_end_time vendor start_time \\\n", + "1 minor 1569502020 1569506460 Github 2019-09-26 12:47:00 \n", + "3 minor 1569324600 1569334080 Github 2019-09-24 11:30:00 \n", + "4 critical 1569255120 1569256620 Github 2019-09-23 16:12:00 \n", + "\n", + " end_time \n", + "1 2019-09-26 14:01:00 \n", + "3 2019-09-24 14:08:00 \n", + "4 2019-09-23 16:37:00 " + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Investigating the lack of critical event from September 2019\n", + "filtered_github_incidents[(filtered_github_incidents['start_time'].dt.year == 2019) & (filtered_github_incidents['start_time'].dt.month == 9)]" + ] + }, + { + "cell_type": "code", + "execution_count": 133, + "metadata": {}, + "outputs": [], + "source": [ + "# Check ICPE article as we missed events shorter than an hour" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(39195, 4)" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# I checked outage report code and timestamps are in UTC\n", + "filtered_or_events = or_events[or_events['status_code'] >= 0].reset_index(drop=True)\n", + "filtered_or_events = filtered_or_events.drop_duplicates(subset=['vendor', 'event_time', 'status_code'])\n", + "# Combine events with the same event_time, but different status_code with max\n", + "filtered_or_events = filtered_or_events.groupby(['vendor', 'event_time'])['status_code'].max().reset_index()\n", + "filtered_or_events['evtime'] = pd.to_datetime(filtered_or_events['event_time'], unit='s')\n", + "or_github = filtered_or_events[(filtered_or_events['vendor'] == 'github')].reset_index(drop=True)\n", + "or_github.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[1,\n", + " 32,\n", + " 60,\n", + " 91,\n", + " 121,\n", + " 152,\n", + " 182,\n", + " 213,\n", + " 244,\n", + " 274,\n", + " 305,\n", + " 335,\n", + " 366,\n", + " 397,\n", + " 425,\n", + " 456,\n", + " 486,\n", + " 517,\n", + " 547,\n", + " 578,\n", + " 609,\n", + " 639,\n", + " 670,\n", + " 700,\n", + " 731]" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "days_per_month = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]\n", + "first_day_of_month = list(itertools.accumulate(days_per_month, initial=1))\n", + "first_day_of_month_for_two_years = list(itertools.accumulate(days_per_month + days_per_month, initial=1))\n", + "first_day_of_month_for_two_years" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "4432.0\n", + "2974.0\n" + ] + } + ], + "source": [ + "all_or_github_count = 0\n", + "filtered_or_github_count = 0\n", + "grid_array = np.full((365*2, 24), 0)\n", + "for _, row in or_github.sort_values('evtime').iterrows():\n", + " year_of_event = row['evtime'].year\n", + " day_of_year = row['evtime'].timetuple().tm_yday\n", + " hour_of_day = row['evtime'].hour\n", + " num_reports = row['status_code']\n", + " if num_reports > 2:\n", + " if year_of_event == 2019:\n", + " grid_array[day_of_year-1, hour_of_day-1] = 1\n", + " elif year_of_event == 2020:\n", + " grid_array[365+day_of_year-1, hour_of_day-1] = 1\n", + " else:\n", + " raise Exception('Unknown year: ' + str(year_of_event))\n", + " \n", + " filtered_or_github_count += num_reports\n", + " all_or_github_count += num_reports\n", + "\n", + "or_github_grid_df = pd.DataFrame({\n", + " 'day_of_year': np.repeat(np.tile(np.arange(1, 365+1), 2), 24),\n", + " 'hour_of_day': np.tile(np.arange(1, 24+1), 365*2),\n", + " 'year': np.concatenate([np.repeat(2019, 365*24), np.repeat(2020, 365*24)]),\n", + " 'status': grid_array.flatten()\n", + "})\n", + "\n", + "unified_or_github_grid_df = or_github_grid_df[((or_github_grid_df['year'] == 2019) & (or_github_grid_df['day_of_year'] > 31+28+31+30))\n", + " | ((or_github_grid_df['year'] == 2020) & (or_github_grid_df['day_of_year'] < 365-31-30-31-30))].reset_index(drop=True)\n", + "\n", + "unified_or_github_grid_df['day_of_two_years'] = unified_or_github_grid_df['day_of_year']\n", + "unified_or_github_grid_df.loc[(unified_or_github_grid_df['year'] == 2020), 'day_of_two_years'] = unified_or_github_grid_df.loc[(unified_or_github_grid_df['year'] == 2020), 'day_of_two_years'] + 365\n", + "\n", + "# Reports used for github comparison\n", + "print(all_or_github_count)\n", + "print(filtered_or_github_count)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "def make_grid(df):\n", + " status_to_number_map = {\n", + "# 'maintenance': 1,\n", + " 'minor': 1,\n", + " 'major': 2,\n", + " 'critical': 3,\n", + " }\n", + " \n", + " # First make and populate 2D grid array\n", + " grid_array = np.full((365*2, 24), 0)\n", + " for _, row in df.sort_values('start_time').iterrows():\n", + " year_of_event = row['start_time'].year\n", + " start_day_of_year = row['start_time'].timetuple().tm_yday\n", + " start_hour_of_day = row['start_time'].hour\n", + " end_day_of_year = row['end_time'].timetuple().tm_yday\n", + " end_hour_of_day = row['end_time'].hour\n", + " \n", + " offset = 0\n", + " if year_of_event == 2019:\n", + " offset = 0\n", + " elif year_of_event == 2020:\n", + " offset = 365\n", + " else:\n", + " raise Exception('Unknown year: ' + str(year_of_event))\n", + " \n", + " for day_of_year in range(start_day_of_year, end_day_of_year+1):\n", + " if start_day_of_year == end_day_of_year: # less than a day\n", + " for hour_of_day in range(start_hour_of_day, end_hour_of_day+1):\n", + " grid_array[offset+day_of_year-1, hour_of_day-1] = status_to_number_map[row['status']]\n", + " elif day_of_year == start_day_of_year: # first day\n", + " for hour_of_day in range(start_hour_of_day, 25):\n", + " grid_array[offset+day_of_year-1, hour_of_day-1] = status_to_number_map[row['status']]\n", + " elif day_of_year == end_day_of_year: # last day\n", + " for hour_of_day in range(0, end_hour_of_day):\n", + " grid_array[offset+day_of_year-1, hour_of_day-1] = status_to_number_map[row['status']]\n", + " else: # middle day\n", + " for hour_of_day in range(1, 25):\n", + " grid_array[offset+day_of_year-1, hour_of_day-1] = status_to_number_map[row['status']]\n", + " \n", + " return grid_array" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "github_grid_array = make_grid(filtered_github_incidents)\n", + "github_grid_df = pd.DataFrame({\n", + " 'day_of_year': np.repeat(np.tile(np.arange(1, 365+1), 2), 24),\n", + " 'hour_of_day': np.tile(np.arange(1, 24+1), 365*2),\n", + " 'year': np.concatenate([np.repeat(2019, 365*24), np.repeat(2020, 365*24)]),\n", + " 'status': pd.Categorical(github_grid_array.flatten(), [0,1,2,3], ordered=True)\n", + "})\n", + "\n", + "unified_github_grid_df = github_grid_df[((github_grid_df['year'] == 2019) & (github_grid_df['day_of_year'] > 31+28+31+30))\n", + " | ((github_grid_df['year'] == 2020) & (github_grid_df['day_of_year'] < 365-31-30-31-30))].reset_index(drop=True)\n", + "\n", + "unified_github_grid_df['day_of_two_years'] = unified_github_grid_df['day_of_year']\n", + "unified_github_grid_df.loc[(unified_github_grid_df['year'] == 2020), 'day_of_two_years'] = unified_github_grid_df.loc[(unified_github_grid_df['year'] == 2020), 'day_of_two_years'] + 365" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:727: PlotnineWarning: Saving 25 x 2 in image.\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:730: PlotnineWarning: Filename: plots/github_failures_all.pdf\n" + ] + }, + { + "data": { + "image/png": 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tlZCQoBkzZuiVV17Jcz/m1UyLFi3Sf/7zH/Xr16/Ei2gqVKigc845R5LUokULxcXF6dlnn9UXX3zh12dOIvAKmuc1a9YoKSlJkydP1tGjR73uk5GRodTUVJUtW1ZRUVGaNWuW6tevr/bt2ys1NVWSdPLkSUnSiRMndPToUX5JCjJfr9+cFy6uuuqqPLcxr2arUaOG5x0V2rRpI0l67bXXdPnll3veojvnnTZyS01NlWVZRc5d586dtX79ev38889q3bp1gLtHQQqb19x/1Mt5oatJkyZq27atBg0apNdee02jRo0q9PjMqxl8uX7r1avnWawhZS+yuvDCC/XWW2/p8OHDqlKlimff01/cPOuss1S1alVt27YtGHFQiKKu6ccff1zTp0/XlClTJGW/C0f37t31zTffeL73ni7nD4sNGzb0/HyNkjt+/LhmzZql66+/XlWrVvWMf0ZGhqTs759RUVEqW7as5z7Ffc2K52JnFWeuc8vvdSuej53n67xmZGT4/LoV8xoaKlSooDZt2mj58uU6efJksd9Bge+vZjl9Xr/66iufX6M6/Tbm1VxFXb+FvWa1cuVKbdiwQdOmTfPM7XnnnadmzZrpnnvu0bvvvqvbbrut9EMACBoWbDgkNTVVTz75pPbv368JEyaoYcOGTreEILFtO98/2CclJenpp5/Weeedp5EjR+b5rF84b/fu3UpLS8v3B+BGjRpp8+bNOn78uNfH3TCvZlq0aJEWLVqk2267rUQfhVKQnHNkz549AT82fFfYPO/atUuZmZl67LHH8txvxYoVWrFihRISEnTJJZfol19+0YEDB9SnT588+z7xxBMqX768Fi1aVGo54M3X6zc9PV0ff/yxGjVqpLPOOivP7cxraGncuLGWL1+uffv2qVGjRoqJidHOnTvz7Ldz507FxcXl+dcpp8v5V/4sonRW7nkt6F9hlytXzvN5vUVhXs10+vVb0B8acuYv51/wx8fHF3jMgn6ngrNOv6arVKmiMWPG6PDhwzp06JBq1qypmJgY/e9//8v3o8okaf369frzzz/Vq1evIHcf3o4cOaLDhw9r6dKlWrp0aZ7b+/Tpo4svvlhPPPGEpJK9ZsVzsbP8nev8nP4cy/Ox83yd15tvvtnn162Y19BTkjnh+6u5LMvy6zWq3JjX0HH69VvUa1Y7duyQy+XyetcOSapdu7YqVqyoXbt2lWq/AIKPBRsOyPnFd9++fRo/fnyeJ12Er7Vr1+rkyZM699xzvbZ//fXXevrpp9W0aVM98cQT/FHfUDmfH7h161Z16dLFs922bW3dulUVKlTw+lcqzKuZ3njjDS1atEi33nprqa1E3rRpkyQpLi6uVI6PohU1z126dFHz5s3zbH/iiSd0ySWXqFu3bmrQoIEk6dFHH1V6errXfklJSXr77bd13333eb1FP0qXP9fvl19+qSNHjuS7IENiXkPNpk2b5HK5VLt2bbndbrVt21aff/657rzzTpUrV06S9Pvvv2vTpk0FfuxcbqtXr1ZUVFSJPg4LJZd7Xgty5MgR7dq1S02bNi3yeMyrmU6/fi+++GKtXbtW+/fvV61atSRl/zydlJSk2rVrq1KlSpKy/zVwmTJltGHDBq/retu2bTp06FCe36ngvIKu6SpVqqhKlSqSpGXLlunkyZMFvkPWypUrFRMTo86dO5dyt5HljDPO0FNPPZVn+1tvvaXvvvtOY8aM8Vx7JX3NiudiZ/kz1/nJ73Urno+d5+u85vxc7MvrVsxraEhNTdX69evVsGHDIhelF4bvr2Y5fV79eY0qN+bVbIVdv0W9ZlW1alVlZWXpp59+8no+/u2335SSkqLq1auXau8Ago8FGwG2YcMGnThxQsePH5ck/frrr1qzZo2kv94idMyYMdq+fbvuvvtuZWZm6ocffvDcv3Llyl5/4Pvpp5904MABSdKxY8dk27bneOecc47X28gieIqa5z///FNTp05Vx44dPfO5efNmLVu2TPXr1/d6m6vvv/9eTz31lKpUqaJbbrlF27dv93qs+vXre37hQukqal5r1Kihdu3aacWKFYqOjlabNm2Unp6uxMREbdmyRX379vWslmVezbRkyRItXLhQrVq1Ups2bbyef6Xst16XpD///FObN2+WJM+/4N6wYYMqV66sypUr6/zzz5ckLV++XN99950uvPBCVa9eXSdPntR3332n9957T02aNNHFF18cvHDw8GWea9Wq5fkj0emqVq3q9YtyznmRW8735rPPPpu3nQwSX6/fHDkvXHTq1Cnf4zGvZnrxxRdVrlw5NW7cWFWqVNGRI0e0Zs0affbZZ+rRo4fnXRj69OmjYcOGacKECerZs6fS0tK0cOFCVapUSTfeeKPneO+8845+/fVXtWjRQtWrV9eff/6plStX6uuvv9Ztt91W6B8sEDi+zOvRo0c1evRodezYUXXq1FFMTIz27NmjZcuWKT09Xb179/Ycj3k1k6/Xb9++fbVhwwaNHTtWt912m8qVK6cVK1Zo586dGj58uOd4FSpUUJ8+fTRnzhw9//zz6tixow4dOqQFCxaoRo0a6tq1q1NRI56vc/3hhx9Kyv6XgEePHlVSUpJWrlyp22+/Pd9FAMnJyUpKStLf/vY3VahQIaiZwl1MTEy+fwhatWqVXC6X57aTJ0/6/JoVz8Vm8nWuDxw44PPrVjwfO8/XeZXk8+tWzKt5pk6dqho1aqhRo0aqVKmS9uzZo6VLl+rw4cN66KGHPPv5+ppVDr6/OsuXefXnNaoczKtZfL1+cxT1mlWXLl303//+V5MnT9att96qunXrat++fXrrrbdUtmxZXXPNNaUdCUCQsWAjwGbOnOl5sV+S1qxZ4/mD7+zZsyVlL8LIXed2+eWX6+GHH/bU77//vhITE732eeaZZyRJDz30kNdqaQRPUfNcvnx5ValSxfNNOSsrSzVr1tT111+vW265xetdGDZu3Ki0tDQdOHAg38/lfuqpp/L9oQyBV9S81qpVS8OGDdP777+vjz/+WB999JGioqJUp04dDR061OsHLObVTOvXr5eU/a/ok5KS8tz+7rvvSsr+qISc59ocs2bNkiSdf/75evrppyVJDRo00Pr16/Xaa6/pyJEjcrvdqlOnjm655RbdeOONcrvdpRkHBfB1nhFa/JnX33//XRs3blSnTp1Uvnz5oPWIkmvSpIk++ugjJSYm6ujRoypbtqwaNmyoRx55RJdddplnv3r16umpp57SvHnzNHnyZLndbrVo0UIJCQleH61Rr149ffnll/rqq6+UmpqqmJgYNWzYUI8++qg6duzoRMSI5Mu85szNihUrdPDgQaWlpemMM87Q+eefrxEjRni96w3zaiZfr9+4uDhNnjxZ8+bN00svvaTMzEw1bNhQo0aN0kUXXeR1zB49eqh8+fJatmyZPv30U8XGxqpVq1bq37+/KlasGOyIOMXXubZtW8uWLdOBAwfkcrnUsGFDjRw5Ms/beedYtWqVsrKydOWVVwYrCk5z+PBhn1+z4rk4tJUrV87n160kno9Dia+vW0nMq2ni4+P12Wefafny5Tp+/LgqVqyopk2baujQoV7/oMDX16xy8P3VWb7Oq7+YV7P4M8++vGZVo0YNTZs2TYsXL9bbb7+tQ4cOqUqVKmrSpIl69eqlevXqBSMWgCCy7JwPlwQAAAAAAAAAAAAAAEBQuJxuAAAAAAAAAAAAAAAAINKwYAMAAAAAAAAAAAAAACDIWLABAAAAAAAAAAAAAAAQZCzYAAAAAAAAAAAAAAAACDIWbAAAAAAAAAAAAAAAAAQZCzYAAAAAAAAAAAAAAACCjAUbAAAAAAAAAAAAAAAAQcaCDQAAAAAAAAAAAAAAgCBjwQYAAAAA+Gnu3LmyLMvzVbZsWdWuXVuXXXaZJk2apAMHDjjdYpF27typ6667TlWrVpVlWXr44Yedbilgxo8fr2bNmikrK8uzLfd85f6qXr26JKlz587q3LlzwHpYu3atxo4dq8OHD5foOHfeeafi4+MD0lNp+ec//6lGjRopJiZGlmWVOHMw/e9//9PYsWPzvc2yLA0ZMqRYx925c6csy9LcuXOL39wpOc83O3fu9Pu+Y8eOlWVZOnjwYIn7OP2YgXT6eX7o0CFVqVJFS5cuDejjAAAAAABgmiinGwAAAACAUDVnzhw1adJE6enpOnDggP7v//5PzzzzjKZOnarFixfriiuucLrFAj3yyCP64osv9Oqrr6p27dqKi4tzuqWA2LNnj6ZMmaK5c+fK5fL+Nwo9e/bUsGHDvLZFR0dLkmbMmBHQPtauXatx48bpzjvvVJUqVQJ6bJNs3LhRDz74oO6++271799fUVFRqlixotNt+ex///ufXnrppQIXbRRXXFycPv/8c5199tkBPW6kOOOMM/TII4/oscceU9euXRUTE+N0SwAAAAAAlAoWbAAAAABAMZ1//vlq06aNp7755pv1yCOPqEOHDrrpppv0008/qVatWg52WLDNmzerbdu2uvHGG51uxS/Hjh1TuXLlCrx9+vTpqlKlim666aY8t9WqVUuXXHJJvvdr1qxZkY+dmZmpjIwMlSlTxveGw9x3330nSRo4cKDatm3rcDfmKFOmTIHnGnwzePBgTZw4UW+99Zb69OnjdDsAAAAAAJQKPhIFAAAAAAKofv36mjZtmlJSUvTyyy97tn/11Vfq3bu34uPjFRsbq/j4eN12223atWuXZ5+dO3cqKipKkyZNynPcTz/9VJZl6c033yz08X/55Rf169dPNWvWVJkyZdS0aVNNmzbN8/Egq1evlmVZ+vnnn/XBBx94PhqkoI9b6NKli5o0aSLbtr2227atRo0a6brrrvNsS0tL08SJE9WkSROVKVNGNWrU0F133aXff//d676LFy/WVVddpbi4OMXGxqpp06YaMWKEjh496rXfnXfeqQoVKmjTpk266qqrVLFiRXXp0qXA7Glpafr3v/+tPn365Hl3jaKc/pEoOR9pMWXKFE2cOFENGzZUmTJl9PHHHysrK0sTJ07Uueeeq9jYWFWpUkUtWrTQ9OnTJWV/ZMRjjz0mSWrYsKFnjFevXl1oD3PnztW5557rmbfXXnst3/3GjRuniy++WFWrVlWlSpXUqlUr/fvf//aao7///e+qWrWqjh07luf+l19+uc4777wix+TVV1/VBRdcoLJly6pq1arq0aOHtmzZ4jVm/fr1kyRdfPHFsixLd955Z4HHy/kojW+//Va33HKLKleurKpVq2ro0KHKyMjQ1q1bdc0116hixYqKj4/XlClT8hyjqPNb+mvupk6dqueee04NGzZUhQoV1K5dO61bt86z35133qmXXnpJkvdH5px+Lbz++utq2rSpypUrpwsuuEDvvfdekWOX30ei/P7777rnnnt05plneq6PSy+9VB999FGRxzvdypUr1b17d9WrV09ly5ZVo0aNNGjQoAI/+uTXX3/VTTfdpEqVKqly5crq169fnutSyr4227Vrp/Lly6tChQq6+uqr9fXXX/vUk6/39fU8r1Wrlq688krNmjXLp8cHAAAAACAU8Q4bAAAAABBgXbt2ldvt1qeffurZtnPnTp177rnq3bu3qlatqr1792rmzJm66KKL9P3336t69eqKj4/XDTfcoFmzZmn48OFyu92e+7/44ouqU6eOevToUeDj/v7772rfvr3S0tI0YcIExcfH67333tOjjz6qbdu2acaMGWrVqpU+//xz9ejRQ2effbamTp0qSQV+JMpDDz2k7t27a9WqVV4f8fLBBx9o27ZteuGFFyRJWVlZ6t69uz777DMNHz5c7du3165duzRmzBh17txZX331lWJjYyVJP/30k7p27aqHH35Y5cuX1w8//KBnnnlGX375pRITE70ePy0tTTfccIMGDRqkESNGKCMjo8D8X3zxhZKTk3XZZZfle7tt23nu73a7ZVlWgcd84YUX1LhxY02dOlWVKlXSOeecoylTpmjs2LEaNWqUOnbsqPT0dP3www86fPiwJOnuu+/WH3/8oX/+85965513PGNb2Lt4zJ07V3fddZe6d++uadOm6c8//9TYsWN18uTJPItPdu7cqUGDBql+/fqSpHXr1umBBx7Qb7/9ptGjR0vKnrdXX31VCxcu1N133+257/fff6+PP/7Ys1ChIJMmTVJCQoJuu+02TZo0ScnJyRo7dqzatWun9evX65xzztGMGTO0aNEiTZw40fPxQDVq1Cj0uJJ06623ql+/fho0aJBWrlypKVOmKD09XR999JHuu+8+Pfroo1q4cKEef/xxNWrUyPNuKb6c37m99NJLatKkiZ5//nlJ0pNPPqmuXbtqx44dqly5sp588kkdPXpUb731lj7//HPP/XJfC++//77Wr1+v8ePHq0KFCpoyZYp69OihrVu36qyzzioya2633367kpKS9NRTT6lx48Y6fPiwkpKSlJyc7NdxJGnbtm1q166d7r77blWuXFk7d+7Uc889pw4dOmjTpk2ej/rJ0aNHD916660aPHiwvvvuOz355JP6/vvv9cUXX3j2ffrppzVq1CjdddddGjVqlNLS0vTss8/qb3/7m7788stCz19f7+vPeS5lLwoaOXKkDh8+HNYfLQQAAAAAiGA2AAAAAMAvc+bMsSXZ69evL3CfWrVq2U2bNi3w9oyMDDs1NdUuX768PX36dM/2jz/+2JZkL1myxLPtt99+s6Oiouxx48YV2teIESNsSfYXX3zhtf3ee++1Lcuyt27d6tnWoEED+7rrriv0eLZt25mZmfZZZ51ld+/e3Wv7tddea5999tl2VlaWbdu2vWjRIluS/fbbb3vtt379eluSPWPGjHyPn5WVZaenp9uffPKJLcn+5ptvPLf179/flmS/+uqrRfZp27b9zDPP2JLsffv25blNUr5fs2fPtm3btjt16mR36tTJs/+OHTtsSfbZZ59tp6WleR3r+uuvt1u2bFloL88++6wtyd6xY0eRfWdmZtp16tSxW7Vq5RlP27btnTt32tHR0XaDBg0KvW96ero9fvx4u1q1al7379SpU54+7733XrtSpUp2SkpKgcc8dOiQHRsba3ft2tVr+y+//GKXKVPG7tOnj2ebL9dCjjFjxtiS7GnTpnltb9mypS3Jfueddzzb0tPT7Ro1atg33XSTZ5uv53fO3DVv3tzOyMjw7Pfll1/akuxFixZ5tt1///12QS+NSLJr1aplHzlyxLNt3759tsvlsidNmlRo1pwe5syZ49lWoUIF++GHHy70fvnJGeOCzqWca2jXrl22JPu///2v57acMX/kkUe87rNgwQJbkj1//nzbtrPnNioqyn7ggQe89ktJSbFr165t33rrrXmOmcPX+xbnPF+5cqUtyf7ggw8KGSEAAAAAAEIXH4kCAAAAAKXAPu0jRFJTUz3vGBAVFaWoqChVqFBBR48ezfMxExdccIHXOyDMmjVLlmXpnnvuKfQxExMT1axZM7Vt29Zr+5133inbtvO8e4UvXC6XhgwZovfee0+//PKLpOx/3b98+XLdd999nneneO+991SlShV169ZNGRkZnq+WLVuqdu3aXh8Hsn37dvXp00e1a9eW2+1WdHS0OnXqJEleY5Hj5ptv9qnXPXv2yLIsVa9ePd/bb731Vq1fv97r68Ybbyz0mDfccEOedyto27atvvnmG91333368MMPdeTIEZ/6K8jWrVu1Z88e9enTx+vdPho0aKD27dvn2T8xMVFXXHGFKleu7Bm/0aNHKzk5WQcOHPDs99BDD2njxo1as2aNJOnIkSN6/fXX1b9/f1WoUKHAfj7//HMdP348z8ebnHnmmbr88su1atWqEuW9/vrrveqmTZvKsixde+21nm1RUVFq1KiR10cG+Xt+X3fddV7vUtOiRQtJ8jpmUS677DJVrFjRU9eqVUs1a9b06xg52rZtq7lz52rixIlat26d0tPT/T5GjgMHDmjw4ME688wzFRUVpejoaDVo0EBS/tdQ3759vepbb71VUVFR+vjjjyVJH374oTIyMnTHHXd4Xb9ly5ZVp06dCv04H1/v6+95Lkk1a9aUJP32228+jw0AAAAAAKGEBRsAAAAAEGBHjx5VcnKy6tSp49nWp08fvfjii7r77rv14Ycf6ssvv9T69etVo0YNHT9+3Ov+Dz74oFatWqWtW7cqPT1ds2fPVs+ePVW7du1CHzc5OTnfjzbJ6aM4H70gSQMGDFBsbKxmzZolKfujJmJjYzVgwADPPvv379fhw4cVExOj6Ohor699+/bp4MGDkrIXrvztb3/TF198oYkTJ2r16tVav3693nnnHUnKMxblypVTpUqVfOrz+PHjio6O9vojfW41atRQmzZtvL4KWtyRI7/xHDlypKZOnap169bp2muvVbVq1dSlSxd99dVXPvV5upx5yW9+T9/25Zdf6qqrrpIkzZ49W2vWrNH69ev1xBNPSPIev+7duys+Pt6z+Gfu3Lk6evSo7r//fp/6KehcKu55lKNq1apedUxMjMqVK6eyZcvm2X7ixAmvvvw5v6tVq+ZVlylTRlLec6wwpx8j5zj+HCPH4sWL1b9/f73yyitq166dqlatqjvuuEP79u3z6zhZWVm66qqr9M4772j48OFatWqVvvzyS61bt05S/vlOP4+ioqJUrVo1z5jt379fknTRRRfluX4XL17suX7z4+t9/TnPc+ScE8UZbwAAAAAAQkGU0w0AAAAAQLh5//33lZmZqc6dO0uS/vzzT7333nsaM2aMRowY4dnv5MmT+uOPP/Lcv0+fPnr88cf10ksv6ZJLLtG+ffuK/CO7lP3H5b179+bZvmfPHkkqcnFCQSpXruz5Q/Ojjz6qOXPmqE+fPqpSpYpnn+rVq6tatWpavnx5vsfIeZeCxMRE7dmzR6tXr/a8q4YkHT58ON/75f6X+EWpXr260tLSdPToUZUvX97n+xUmv8ePiorS0KFDNXToUB0+fFgfffSREhISdPXVV+vXX39VuXLl/HqMnEUB+f3h/vRtb7zxhqKjo/Xee+95LXBYunRpnvu6XC7df//9SkhI0LRp0zRjxgx16dJF5557rk/9FHQuFfc8KqnSOr+DpXr16nr++ef1/PPP65dfftG7776rESNG6MCBAwVeN/nZvHmzvvnmG82dO1f9+/f3bP/5558LvM++fftUt25dT52RkaHk5GTPXOeM3VtvveV5pw5/cvlyX3/O8xw5z4+mzy0AAAAAAMXFO2wAAAAAQAD98ssvevTRR1W5cmUNGjRIUvYf/W3b9vwL/xyvvPKKMjMz8xyjbNmyuueeezRv3jw999xzatmypS699NIiH7tLly76/vvvlZSU5LX9tddek2VZuuyyy4qd68EHH9TBgwfVs2dPHT58WEOGDPG6/frrr1dycrIyMzPzvItFmzZtPIsEchZAnD4WL7/8crF7y9GkSRNJ2R/ZEixVqlRRz549df/99+uPP/7Qzp07Jfn3bg7nnnuu4uLitGjRIq+P0tm1a5fWrl3rta9lWYqKivJ6F5Hjx4/r9ddfz/fYd999t2JiYtS3b19t3bo1z7zlp127doqNjdX8+fO9tu/evVuJiYnq0qVLkccoDaVxfhfnXTcCoX79+hoyZIiuvPLKPHmKUpxraMGCBV71f/7zH2VkZHgWlV199dWKiorStm3b8r1+27RpU+Cxfb2vP+d5ju3bt0uSmjVrVuDjAwAAAAAQyniHDQAAAAAops2bNysjI0MZGRk6cOCAPvvsM82ZM0dut1tLlixRjRo1JEmVKlVSx44d9eyzz6p69eqKj4/XJ598on//+99e71KR23333acpU6Zow4YNeuWVV3zq55FHHtFrr72m6667TuPHj1eDBg30/vvva8aMGbr33nvVuHHjYmdt3LixrrnmGn3wwQfq0KGDLrjgAq/be/furQULFqhr16566KGH1LZtW0VHR2v37t36+OOP1b17d/Xo0UPt27fXGWecocGDB2vMmDGKjo7WggU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+ "text/plain": [ + "<Figure size 2500x200 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (326298676)>" + ] + }, + "execution_count": 70, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "plt = ggplot(unified_github_grid_df) +\\\n", + " theme_classic(base_size=12, base_family='sans-serif') +\\\n", + " geom_tile(mapping=aes(x='day_of_two_years', y='hour_of_day', fill='status'), color='gainsboro', size=0.01) +\\\n", + " scale_fill_manual(values=['white', 'green', 'orange', 'red', 'black']) +\\\n", + " scale_x_continuous(limits=(first_day_of_month_for_two_years[4], first_day_of_month_for_two_years[-5]-1), expand=(0.005, 0.005),\n", + " breaks=first_day_of_month_for_two_years[4:-5]) +\\\n", + " scale_y_continuous(breaks=[0, 6, 12, 18, 24],\n", + " labels=['00:00', '06:00', '12:00', '18:00', '24:00']) +\\\n", + " theme(figure_size=(25, 2)) +\\\n", + " guides(fill=guide_legend(title='1 box=1 hour')) +\\\n", + " ylab('Hour of day') +\\\n", + " xlab('Day of year (First day of month is labeled)') +\\\n", + " theme(legend_box_spacing=0.01,\n", + " legend_box_margin=0,\n", + " legend_margin=0,\n", + " legend_key=element_blank(),\n", + " legend_entry_spacing=5,\n", + " legend_background=element_rect(fill=(0,0,0,0), color=(0,0,0,0)),\n", + " text=element_text(size=12))\n", + "\n", + "# scale_x_continuous(limits=(0, 365), expand=(0.005, 0.005),\n", + "# breaks=[31, 59, 90, 120, 151, 180, 211, 242, 272, 303, 333, 364],\n", + "# labels=['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']) +\\\n", + "\n", + "plt.save('plots/github_failures_all.pdf', limitsize=False)\n", + "plt" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:727: PlotnineWarning: Saving 25 x 2 in image.\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:730: PlotnineWarning: Filename: plots/or_github_failures.pdf\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/pandas/core/series.py:726: RuntimeWarning: divide by zero encountered in log\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/pandas/core/series.py:726: RuntimeWarning: divide by zero encountered in log\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "<Figure size 2500x200 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (337549840)>" + ] + }, + "execution_count": 71, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "plt = ggplot(unified_or_github_grid_df) +\\\n", + " theme_classic(base_size=12, base_family='sans-serif') +\\\n", + " geom_tile(mapping=aes(x='day_of_two_years', y='hour_of_day', fill='status'), color='gainsboro', size=0.01) +\\\n", + " scale_fill_continuous('Greys', trans=\"log\") +\\\n", + " scale_x_continuous(limits=(first_day_of_month_for_two_years[4], first_day_of_month_for_two_years[-5]-1), expand=(0.005, 0.005),\n", + " breaks=first_day_of_month_for_two_years[4:-5]) +\\\n", + " scale_y_continuous(breaks=[0, 6, 12, 18, 24],\n", + " labels=['00:00', '06:00', '12:00', '18:00', '24:00']) +\\\n", + " theme(figure_size=(25, 2)) +\\\n", + " guides(fill=guide_legend(title='1 box=1 hour')) +\\\n", + " ylab('Hour of day') +\\\n", + " xlab('Day of year (First day of month is labeled)') +\\\n", + " theme(legend_box_spacing=0.01,\n", + " legend_box_margin=0,\n", + " legend_margin=0,\n", + " legend_key=element_blank(),\n", + " legend_entry_spacing=5,\n", + " legend_background=element_rect(fill=(0,0,0,0), color=(0,0,0,0)),\n", + " text=element_text(size=12))\n", + "\n", + "plt.save('plots/or_github_failures.pdf', limitsize=False)\n", + "plt" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [], + "source": [ + "assert(unified_github_grid_df.shape[0] == unified_or_github_grid_df.shape[0])" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "def merge_dfs(github_df, github_or_df):\n", + " list_of_merged_rows = []\n", + " for i in range(github_df.shape[0]):\n", + " github_status = github_df.loc[i, 'status']\n", + " or_github_status = github_or_df.loc[i, 'status']\n", + "\n", + " final_status = github_status\n", + "\n", + " if or_github_status == 1:\n", + " if github_status == 0:\n", + " final_status = 4\n", + " elif github_status == 1:\n", + " final_status = 5\n", + " elif github_status == 2:\n", + " final_status = 6\n", + " else:\n", + " raise Exception('Unknown github status')\n", + "\n", + " list_of_merged_rows.append({\n", + " 'status': final_status,\n", + " 'hour_of_day': github_df.loc[i, 'hour_of_day'],\n", + " 'year': github_df.loc[i, 'year'],\n", + " 'day_of_year': github_df.loc[i, 'day_of_year'],\n", + " 'day_of_two_years': github_df.loc[i, 'day_of_two_years']\n", + " })\n", + "\n", + " merged_df = pd.DataFrame(list_of_merged_rows)\n", + " merged_df['status'] = pd.Categorical(merged_df['status'], [0,1,2,3,4,5,6], ordered=True)\n", + " return merged_df\n", + "\n", + "merged_df = merge_dfs(unified_github_grid_df, unified_or_github_grid_df)" + ] + }, + { + "cell_type": "code", + "execution_count": 114, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:727: PlotnineWarning: Saving 25 x 2 in image.\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:730: PlotnineWarning: Filename: plots/github_merged_failures.pdf\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 2500x200 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (339631818)>" + ] + }, + "execution_count": 114, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "plt = ggplot(merged_df) +\\\n", + " theme_classic(base_size=12, base_family='sans-serif') +\\\n", + " geom_tile(mapping=aes(x='day_of_two_years', y='hour_of_day', fill='status'), color='white', size=0.02) +\\\n", + " scale_fill_manual(values=['white', 'gold', 'orange', 'black', 'teal', 'magenta', 'red'],\n", + " labels=['None', 'Official Minor', 'Official Major', 'Official Critical', 'Report without Overlap', 'Report overlaps Official Minor', 'Report overlaps Official Major']) +\\\n", + " scale_x_continuous(limits=(first_day_of_month_for_two_years[4], first_day_of_month_for_two_years[-5]-1), expand=(0.005, 0.005),\n", + " breaks=first_day_of_month_for_two_years[4:-5],\n", + " labels=['May\\n\\n2019', 'June', 'July', 'August', 'September', 'October', 'November', 'December', 'January\\n\\n2020', 'February', 'March', 'April', 'May', 'June', 'July', 'August']) +\\\n", + " scale_y_continuous(breaks=[0, 6, 12, 18, 24],\n", + " labels=['00:00', '06:00', '12:00', '18:00', '24:00']) +\\\n", + " theme(figure_size=(25, 2)) +\\\n", + " guides(fill=guide_legend(title='1 box=1 hour', nrow=1)) +\\\n", + " ylab('Hour of day') +\\\n", + " xlab('Day of year (First day of month is labeled)') +\\\n", + " theme(legend_box_spacing=0.01,\n", + " legend_box_margin=0,\n", + " legend_margin=0,\n", + " legend_key=element_blank(),\n", + " legend_entry_spacing=5,\n", + " legend_background=element_rect(fill=(0,0,0,0), color=(0,0,0,0)),\n", + " legend_position='top',\n", + " text=element_text(size=12))\n", + "\n", + "plt.save('plots/github_merged_failures.pdf', limitsize=False)\n", + "plt" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:727: PlotnineWarning: Saving 16 x 3 in image.\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:730: PlotnineWarning: Filename: plots/double_github_merged_failures.pdf\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1600x300 with 2 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (326423902)>" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "plt = ggplot(merged_df) +\\\n", + " theme_classic(base_size=12, base_family='sans-serif') +\\\n", + " geom_tile(mapping=aes(x='day_of_year', y='hour_of_day', fill='status'), color='white', size=0.02) +\\\n", + " scale_fill_manual(values=['white', 'silver', 'orange', 'black', 'teal', 'magenta', 'red'],\n", + " labels=['None', 'Official Minor', 'Official Major', 'Official Critical', 'Report without Overlap', 'Report overlaps Official Minor', 'Report overlaps Official Major']) +\\\n", + " scale_x_continuous(limits=(first_day_of_month[0], first_day_of_month[-1]), expand=(0.005, 0.005),\n", + " breaks=first_day_of_month[:-1],\n", + " labels=['January', 'February', 'March', 'April', 'May', 'June', 'July', 'August', 'September', 'October', 'November', 'December']) +\\\n", + " scale_y_continuous(breaks=[0, 6, 12, 18, 24],\n", + " labels=['00:00', '06:00', '12:00', '18:00', '24:00']) +\\\n", + " theme(figure_size=(16, 3)) +\\\n", + " guides(fill=guide_legend(title='1 box=1 hour', nrow=1)) +\\\n", + " facet_wrap(facets='year', nrow=2) +\\\n", + " ylab('Hour of day') +\\\n", + " xlab('Day of year (First day of month is labeled)') +\\\n", + " theme(legend_box_spacing=0.01,\n", + " legend_box_margin=0,\n", + " legend_margin=0,\n", + " legend_key=element_blank(),\n", + " legend_entry_spacing=5,\n", + " legend_background=element_rect(fill=(0,0,0,0), color=(0,0,0,0)),\n", + " legend_position='top',\n", + " text=element_text(size=12))\n", + "\n", + "plt.save('plots/double_github_merged_failures.pdf', limitsize=False)\n", + "plt" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.1" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/datasets/Talluri2021/2.basic_stats_reports.ipynb b/datasets/Talluri2021/2.basic_stats_reports.ipynb new file mode 100644 index 0000000..d33a3cc --- /dev/null +++ b/datasets/Talluri2021/2.basic_stats_reports.ipynb @@ -0,0 +1,448 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "from plotnine import *\n", + "from datetime import datetime\n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "or_events = pd.read_parquet('./outage_report_2019-20')\n", + "or_reports = pd.read_parquet('./outage_report_individual_reports_2019-20')" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "filtered_or_events = or_events[(or_events['vendor'] != '') & (or_events['vendor'] != 'overview')].copy()\n", + "filtered_or_events = filtered_or_events.drop_duplicates(subset=['vendor', 'event_time', 'status_code'])\n", + "# Combine events with the same event_time, but different status_code with max\n", + "filtered_or_events = filtered_or_events.groupby(['vendor', 'event_time'])['status_code'].max().reset_index()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "filtered_or_reports = or_reports[(or_reports['reason'] != '') & (or_reports['vendor'] != 'overview')].reset_index(drop=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "thresholded_or_events = filtered_or_events[filtered_or_events['status_code'] > 2].copy()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "def proper_vendor_names(series):\n", + " return series.str.capitalize().replace(['Apple-servers', 'Facebook-messenger', 'Youtube'], ['Apple', 'FB Msgr', 'YouTube'])\n", + "\n", + "filtered_or_reports['vendor_proper'] = proper_vendor_names(filtered_or_reports['vendor'])" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "def proper_vendor_names(series):\n", + " return series.str.capitalize().replace(['Apple-servers', 'Facebook-messenger', 'Youtube'], ['Apple', 'FB Msgr', 'YouTube'])\n", + "\n", + "filtered_or_events['vendor_proper'] = proper_vendor_names(filtered_or_events['vendor'])" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['Apple',\n", + " 'Github',\n", + " 'Skype',\n", + " 'FB Msgr',\n", + " 'Gmail',\n", + " 'Whatsapp',\n", + " 'Snapchat',\n", + " 'Netflix',\n", + " 'Facebook',\n", + " 'Twitter',\n", + " 'YouTube',\n", + " 'Instagram']" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vendor_list = list(filtered_or_events.groupby('vendor_proper')['status_code'].sum().reset_index().rename(columns={'status_code':'count'}).sort_values('count')['vendor_proper'])\n", + "vendor_list" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\\begin{tabular}{lrrr}\n", + "\\toprule\n", + "vendor\\_proper & count\\_events & count\\_reports & prop \\\\\n", + "\\midrule\n", + " Apple & 3208 & 2566 & 79.99 \\\\\n", + " Github & 4432 & 1062 & 23.96 \\\\\n", + " Skype & 4799 & 2029 & 42.28 \\\\\n", + " FB Msgr & 13788 & 6836 & 49.58 \\\\\n", + " Gmail & 16471 & 9427 & 57.23 \\\\\n", + " Whatsapp & 34653 & 9426 & 27.20 \\\\\n", + " Snapchat & 68863 & 8118 & 11.79 \\\\\n", + " Netflix & 74631 & 20211 & 27.08 \\\\\n", + " Facebook & 79880 & 25886 & 32.41 \\\\\n", + " Twitter & 136672 & 20252 & 14.82 \\\\\n", + " YouTube & 152169 & 26783 & 17.60 \\\\\n", + " Instagram & 193687 & 41574 & 21.46 \\\\\n", + "\\bottomrule\n", + "\\end{tabular}\n", + "\n" + ] + } + ], + "source": [ + "event_count_df = filtered_or_events.groupby('vendor_proper')['status_code'].sum().reset_index().rename(columns={'status_code':'count'})\n", + "report_count_df = filtered_or_reports.groupby('vendor_proper')['country'].count().reset_index().rename(columns={'country':'count'}).set_index('vendor_proper')\n", + "\n", + "joined_count_df = event_count_df.join(report_count_df, on='vendor_proper', lsuffix='_events', rsuffix='_reports')\n", + "joined_count_df['prop'] = (joined_count_df['count_reports'] / joined_count_df['count_events']) * 100\n", + "joined_count_df['count_events'] = joined_count_df['count_events'].astype(int)\n", + "\n", + "print(joined_count_df.sort_values('count_events').to_latex(index=None, float_format=\"%.2f\"))" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "783253\n", + "174170\n", + "0.22236748534636958\n" + ] + } + ], + "source": [ + "#\n", + "print(joined_count_df['count_events'].sum())\n", + "print(joined_count_df['count_reports'].sum())\n", + "print(joined_count_df['count_reports'].sum() / joined_count_df['count_events'].sum())" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "<ipython-input-34-de7f15117fb8>:3: FutureWarning: Series.dt.weekofyear and Series.dt.week have been deprecated. Please use Series.dt.isocalendar().week instead.\n" + ] + } + ], + "source": [ + "filtered_or_events['evtime'] = pd.to_datetime(filtered_or_events['event_time'], unit='s')\n", + "filtered_or_events['hour_of_week'] = filtered_or_events['evtime'].dt.dayofweek * 24 + (filtered_or_events['evtime'].dt.hour + 1)\n", + "filtered_or_events['week_of_year'] = filtered_or_events['evtime'].dt.weekofyear" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2019-04-14 11:20:00\n", + "2020-10-31 23:00:00\n" + ] + } + ], + "source": [ + "# First and last dates in the dataset\n", + "print(filtered_or_events['evtime'].min())\n", + "print(filtered_or_events['evtime'].max())" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>hour_of_week</th>\n", + " <th>sum</th>\n", + " <th>prop</th>\n", + " <th>vendor_proper</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>0</th>\n", + " <td>1</td>\n", + " <td>19.0</td>\n", + " <td>0.142857</td>\n", + " <td>Apple</td>\n", + " </tr>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>2</td>\n", + " <td>40.0</td>\n", + " <td>0.300752</td>\n", + " <td>Apple</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2</th>\n", + " <td>3</td>\n", + " <td>81.0</td>\n", + " <td>0.609023</td>\n", + " <td>Apple</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3</th>\n", + " <td>4</td>\n", + " <td>124.0</td>\n", + " <td>0.932331</td>\n", + " <td>Apple</td>\n", + " </tr>\n", + " <tr>\n", + " <th>4</th>\n", + " <td>5</td>\n", + " <td>22.0</td>\n", + " <td>0.165414</td>\n", + " <td>Apple</td>\n", + " </tr>\n", + " <tr>\n", + " <th>...</th>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " </tr>\n", + " <tr>\n", + " <th>163</th>\n", + " <td>164</td>\n", + " <td>2431.0</td>\n", + " <td>0.413717</td>\n", + " <td>YouTube</td>\n", + " </tr>\n", + " <tr>\n", + " <th>164</th>\n", + " <td>165</td>\n", + " <td>1151.0</td>\n", + " <td>0.195882</td>\n", + " <td>YouTube</td>\n", + " </tr>\n", + " <tr>\n", + " <th>165</th>\n", + " <td>166</td>\n", + " <td>450.0</td>\n", + " <td>0.076583</td>\n", + " <td>YouTube</td>\n", + " </tr>\n", + " <tr>\n", + " <th>166</th>\n", + " <td>167</td>\n", + " <td>398.0</td>\n", + " <td>0.067733</td>\n", + " <td>YouTube</td>\n", + " </tr>\n", + " <tr>\n", + " <th>167</th>\n", + " <td>168</td>\n", + " <td>398.0</td>\n", + " <td>0.067733</td>\n", + " <td>YouTube</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "<p>2016 rows × 4 columns</p>\n", + "</div>" + ], + "text/plain": [ + " hour_of_week sum prop vendor_proper\n", + "0 1 19.0 0.142857 Apple\n", + "1 2 40.0 0.300752 Apple\n", + "2 3 81.0 0.609023 Apple\n", + "3 4 124.0 0.932331 Apple\n", + "4 5 22.0 0.165414 Apple\n", + ".. ... ... ... ...\n", + "163 164 2431.0 0.413717 YouTube\n", + "164 165 1151.0 0.195882 YouTube\n", + "165 166 450.0 0.076583 YouTube\n", + "166 167 398.0 0.067733 YouTube\n", + "167 168 398.0 0.067733 YouTube\n", + "\n", + "[2016 rows x 4 columns]" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "grouped_df_list = []\n", + "for vendor in filtered_or_events['vendor_proper'].unique():\n", + " vendor_df = filtered_or_events[filtered_or_events['vendor_proper'] == vendor].copy()\n", + " partial_grouped_df = vendor_df.groupby('hour_of_week')['status_code'].sum().reset_index().rename(columns={'status_code': 'sum'})\n", + " partial_grouped_df['prop'] = partial_grouped_df['sum'] / partial_grouped_df['sum'].max()\n", + " partial_grouped_df['vendor_proper'] = vendor\n", + " grouped_df_list.append(partial_grouped_df)\n", + "grouped_df = pd.concat(grouped_df_list)\n", + "grouped_df" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:727: PlotnineWarning: Saving 14 x 3 in image.\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:730: PlotnineWarning: Filename: plots/or_hour_of_week.pdf\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1400x300 with 12 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (306119497)>" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "grouped_df['vendor_cat'] = pd.Categorical(grouped_df['vendor_proper'], categories=vendor_list, ordered=True)\n", + "\n", + "vendor_maxes = grouped_df.groupby('vendor_proper')['sum'].max()\n", + "\n", + "def label_func(vendor):\n", + " if vendor == 'Apple':\n", + " return vendor + ' (max={:,})'.format(int(vendor_maxes.loc[vendor]))\n", + " else:\n", + " return vendor + ' ({:,})'.format(int(vendor_maxes.loc[vendor]))\n", + "\n", + "plt = ggplot(grouped_df) +\\\n", + " theme_classic(base_size=12, base_family='sans-serif') +\\\n", + " theme(figure_size=(14, 3),\n", + " axis_text_y=element_text(margin={'r': 5}),\n", + " panel_grid_minor_x=element_line(size=0.7, color=\"gainsboro\"),\n", + " panel_grid_major_x=element_blank(),\n", + " text=element_text(size=12)) +\\\n", + " geom_step(aes(x=\"hour_of_week\", y=\"prop\")) +\\\n", + " facet_wrap(facets='vendor_cat', nrow=2, labeller=label_func) +\\\n", + " scale_x_continuous(breaks = [12, 36, 60, 84, 108, 132, 156],\n", + " labels = [\"Mo\", \"Tu\", \"We\", \"Th\", \"Fr\", \"Sa\", \"Su\"]) +\\\n", + " xlab(\"Day of Week\") +\\\n", + " ylab(\"Max. Norm. Failures/Hour\")\n", + "\n", + "plt.save('plots/or_hour_of_week.pdf')\n", + "plt" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.1" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/datasets/Talluri2021/3.country and reason.ipynb b/datasets/Talluri2021/3.country and reason.ipynb new file mode 100644 index 0000000..d79ad05 --- /dev/null +++ b/datasets/Talluri2021/3.country and reason.ipynb @@ -0,0 +1,887 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "from plotnine import *" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "or_reports = pd.read_parquet('./outage_report_individual_reports_2019-20')" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "filtered_or_reports = or_reports[(or_reports['reason'] != '') & (or_reports['vendor'] != 'overview')].reset_index(drop=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "instagram_or_reports = filtered_or_reports[filtered_or_reports['vendor'] == 'instagram'].reset_index(drop=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "github_or_reports = filtered_or_reports[filtered_or_reports['vendor'] == 'github'].reset_index(drop=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>country</th>\n", + " <th>count</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>0</th>\n", + " <td>CA</td>\n", + " <td>1828</td>\n", + " </tr>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>GB</td>\n", + " <td>1327</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2</th>\n", + " <td>Other</td>\n", + " <td>15938</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3</th>\n", + " <td>RU</td>\n", + " <td>3272</td>\n", + " </tr>\n", + " <tr>\n", + " <th>4</th>\n", + " <td>UA</td>\n", + " <td>3486</td>\n", + " </tr>\n", + " <tr>\n", + " <th>5</th>\n", + " <td>US</td>\n", + " <td>15723</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " country count\n", + "0 CA 1828\n", + "1 GB 1327\n", + "2 Other 15938\n", + "3 RU 3272\n", + "4 UA 3486\n", + "5 US 15723" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "top4_countries_insta = instagram_or_reports.groupby('country')['vendor'].count().reset_index().sort_values('vendor', ascending=False).reset_index(drop=True).loc[:4, 'country'].values\n", + "\n", + "truncated_insta_reports = instagram_or_reports.copy()\n", + "truncated_insta_reports.loc[~truncated_insta_reports['country'].isin(top4_countries_insta), 'country'] = 'Other'\n", + "\n", + "insta_reports_by_country = truncated_insta_reports.groupby('country')['id'].count().reset_index().rename(columns={'id': 'count'})\n", + "insta_reports_by_country" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 640x480 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (328058811)>" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "plt = ggplot(insta_reports_by_country) +\\\n", + " geom_bar(aes(x='country', y='count'), stat='identity')\n", + "\n", + "plt" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>country</th>\n", + " <th>count</th>\n", + " <th>country_proper</th>\n", + " <th>country_cat</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>0</th>\n", + " <td>CA</td>\n", + " <td>10265</td>\n", + " <td>Canada</td>\n", + " <td>Canada</td>\n", + " </tr>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>GB</td>\n", + " <td>12451</td>\n", + " <td>UK</td>\n", + " <td>UK</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2</th>\n", + " <td>IN</td>\n", + " <td>4478</td>\n", + " <td>India</td>\n", + " <td>India</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3</th>\n", + " <td>Other</td>\n", + " <td>61927</td>\n", + " <td>Other</td>\n", + " <td>Other</td>\n", + " </tr>\n", + " <tr>\n", + " <th>4</th>\n", + " <td>RU</td>\n", + " <td>4200</td>\n", + " <td>Russia</td>\n", + " <td>Russia</td>\n", + " </tr>\n", + " <tr>\n", + " <th>5</th>\n", + " <td>US</td>\n", + " <td>80849</td>\n", + " <td>USA</td>\n", + " <td>USA</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " country count country_proper country_cat\n", + "0 CA 10265 Canada Canada\n", + "1 GB 12451 UK UK\n", + "2 IN 4478 India India\n", + "3 Other 61927 Other Other\n", + "4 RU 4200 Russia Russia\n", + "5 US 80849 USA USA" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "top4_countries_all = filtered_or_reports.groupby('country')['vendor'].count().reset_index().sort_values('vendor', ascending=False).reset_index(drop=True).loc[:4, 'country'].values\n", + "\n", + "truncated_all_reports = filtered_or_reports.copy()\n", + "truncated_all_reports.loc[~truncated_all_reports['country'].isin(top4_countries_all), 'country'] = 'Other'\n", + "\n", + "all_reports_by_country = truncated_all_reports.groupby('country')['id'].count().reset_index().rename(columns={'id': 'count'})\n", + "all_reports_by_country['country_proper'] = all_reports_by_country['country'].replace(['US', 'GB', 'CA', 'IN', 'RU'], ['USA', 'UK', 'Canada', 'India', 'Russia'])\n", + "countries_sorted = all_reports_by_country.sort_values('count')['country_proper'].values\n", + "all_reports_by_country['country_cat'] = pd.Categorical(all_reports_by_country['country_proper'], categories=countries_sorted, ordered=True)\n", + "all_reports_by_country" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:727: PlotnineWarning: Saving 4 x 2 in image.\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:730: PlotnineWarning: Filename: ./plots/reports_by_country.pdf\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 400x200 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (275238765)>" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "plt = ggplot(all_reports_by_country) +\\\n", + " geom_bar(aes(x='country_cat', y='count'), stat='identity', fill='#0280c9') +\\\n", + " coord_flip() +\\\n", + " xlab('Country') + ylab('Number of reports') +\\\n", + " theme_classic(base_size=12, base_family='sans-serif') +\\\n", + " theme(figure_size=(4, 2),\n", + " axis_text_y=element_text(margin={'r': 5}),\n", + " text=element_text(size=12))\n", + "\n", + "plt.save('./plots/reports_by_country.pdf', limitsize=False)\n", + "plt" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "215\n" + ] + }, + { + "data": { + "text/plain": [ + "array(['US', 'CZ', 'CA', 'GB', 'DE', 'RU', 'UA', 'AR', 'FR', 'PK', 'KW',\n", + " 'PT', 'BH', 'MY', 'RS', 'MT', 'AU', 'NL', 'BE', 'HK', 'MX', 'RO',\n", + " 'PL', 'PH', 'SG', 'NG', 'ID', 'SK', 'JM', 'IT', 'KZ', 'SE', 'BR',\n", + " 'IE', 'FI', 'NO', 'HR', 'ES', 'CH', 'ZA', 'EG', 'MM', 'PE', 'UG',\n", + " 'CL', 'OM', 'TR', 'GR', 'IN', 'HU', 'AT', 'BY', 'SZ', 'NZ', 'IS',\n", + " 'BG', 'TW', 'HN', 'EC', 'JP', 'LB', 'BN', 'CN', 'CO', 'LT', 'GH',\n", + " 'AL', 'UZ', 'EE', 'DK', 'GY', 'AE', 'MA', 'HT', 'IM', 'BO', 'BZ',\n", + " 'PA', 'IL', 'TH', 'KR', 'Unknown', 'DO', 'SA', 'BS', 'MK', 'TT',\n", + " 'LV', 'KG', 'PS', 'VE', 'KN', 'NP', 'QA', 'IQ', 'PR', 'PY', 'SI',\n", + " 'ZW', 'TN', 'IR', 'DZ', 'KE', 'LK', 'CD', 'BM', 'MU', 'KH', 'GE',\n", + " 'CR', 'TZ', 'MZ', 'MQ', 'JE', 'CY', 'MD', 'AW', 'DJ', 'VN', 'SV',\n", + " 'SR', 'AZ', 'BB', 'WS', 'SH', 'GG', 'SN', 'BD', 'UY', 'SX', 'JO',\n", + " 'NA', 'NE', 'AD', 'TJ', 'BA', 'LU', 'VU', 'AM', 'AO', 'GT', 'GU',\n", + " 'NI', 'GM', 'KY', 'GA', 'MO', 'CW', 'SY', 'MG', 'AX', 'BJ', 'NC',\n", + " 'RW', 'CM', 'MP', 'RE', 'FO', 'CU', 'BI', 'VC', 'LA', 'ZM', 'SD',\n", + " 'BT', 'CI', 'VG', 'FJ', 'SC', 'DM', 'KM', 'CV', 'BF', 'AG', 'MV',\n", + " 'VI', 'PM', 'YT', 'GI', 'AF', 'XK', 'LY', 'MS', 'ET', 'BW', 'YE',\n", + " 'AI', 'PW', 'MN', 'GP', 'GN', 'GD', 'MC', 'PF', 'ME', 'TC', 'LC',\n", + " 'BQ', 'SO', 'ML', 'LR', 'BL', 'KI', 'TG', 'SL', 'MW', 'CG', 'CF',\n", + " 'PG', 'GL', 'MR', 'MF', 'GF', 'TM', 'WF'], dtype=object)" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "print(len(filtered_or_reports['country'].unique())) # Including unknown\n", + "filtered_or_reports['country'].unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>reason</th>\n", + " <th>count</th>\n", + " <th>reason_cat</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>0</th>\n", + " <td>Can't login</td>\n", + " <td>3654</td>\n", + " <td>Can't login</td>\n", + " </tr>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>Can't upload pics</td>\n", + " <td>4548</td>\n", + " <td>Can't upload pics</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2</th>\n", + " <td>Everything is down</td>\n", + " <td>2613</td>\n", + " <td>Everything is down</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3</th>\n", + " <td>Hashtags not working</td>\n", + " <td>408</td>\n", + " <td>Hashtags not working</td>\n", + " </tr>\n", + " <tr>\n", + " <th>4</th>\n", + " <td>Message read problems</td>\n", + " <td>1127</td>\n", + " <td>Message read problems</td>\n", + " </tr>\n", + " <tr>\n", + " <th>5</th>\n", + " <td>Message send problems</td>\n", + " <td>994</td>\n", + " <td>Message send problems</td>\n", + " </tr>\n", + " <tr>\n", + " <th>6</th>\n", + " <td>Mobile app crashes</td>\n", + " <td>3929</td>\n", + " <td>Mobile app crashes</td>\n", + " </tr>\n", + " <tr>\n", + " <th>7</th>\n", + " <td>Mobile app not working</td>\n", + " <td>15533</td>\n", + " <td>Mobile app not working</td>\n", + " </tr>\n", + " <tr>\n", + " <th>8</th>\n", + " <td>Newsfeed</td>\n", + " <td>4161</td>\n", + " <td>Newsfeed</td>\n", + " </tr>\n", + " <tr>\n", + " <th>9</th>\n", + " <td>Unknown</td>\n", + " <td>1708</td>\n", + " <td>Unknown</td>\n", + " </tr>\n", + " <tr>\n", + " <th>10</th>\n", + " <td>Website down</td>\n", + " <td>2899</td>\n", + " <td>Website down</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " reason count reason_cat\n", + "0 Can't login 3654 Can't login\n", + "1 Can't upload pics 4548 Can't upload pics\n", + "2 Everything is down 2613 Everything is down\n", + "3 Hashtags not working 408 Hashtags not working\n", + "4 Message read problems 1127 Message read problems\n", + "5 Message send problems 994 Message send problems\n", + "6 Mobile app crashes 3929 Mobile app crashes\n", + "7 Mobile app not working 15533 Mobile app not working\n", + "8 Newsfeed 4161 Newsfeed\n", + "9 Unknown 1708 Unknown\n", + "10 Website down 2899 Website down" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "insta_reports_by_reason = instagram_or_reports.groupby('reason')['id'].count().reset_index().rename(columns={'id': 'count'})\n", + "reasons_sorted = insta_reports_by_reason.sort_values('count')['reason'].values\n", + "insta_reports_by_reason['reason_cat'] = pd.Categorical(insta_reports_by_reason['reason'], categories=reasons_sorted, ordered=True)\n", + "insta_reports_by_reason" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:727: PlotnineWarning: Saving 4 x 3 in image.\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:730: PlotnineWarning: Filename: ./plots/insta_reports_by_reason.pdf\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 400x300 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (309548255)>" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "plt = ggplot(insta_reports_by_reason) +\\\n", + " geom_bar(aes(x='reason_cat', y='count'), stat='identity', fill='#0280c9') +\\\n", + " coord_flip() +\\\n", + " xlab('Reason') + ylab('Number of reports') +\\\n", + " theme_classic(base_size=12, base_family='sans-serif') +\\\n", + " theme(figure_size=(4, 3),\n", + " axis_text_y=element_text(margin={'r': 5}),\n", + " text=element_text(size=12))\n", + "\n", + "plt.save('./plots/insta_reports_by_reason.pdf', limitsize=False)\n", + "plt" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>reason</th>\n", + " <th>mean_pdf</th>\n", + " <th>reason_cat</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>0</th>\n", + " <td>Mobile app not working</td>\n", + " <td>0.174832</td>\n", + " <td>Mobile app not working</td>\n", + " </tr>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>Website down</td>\n", + " <td>0.173807</td>\n", + " <td>Website down</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2</th>\n", + " <td>Unknown</td>\n", + " <td>0.130210</td>\n", + " <td>Unknown</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3</th>\n", + " <td>Everything is down</td>\n", + " <td>0.127983</td>\n", + " <td>Everything is down</td>\n", + " </tr>\n", + " <tr>\n", + " <th>4</th>\n", + " <td>Can't login</td>\n", + " <td>0.082374</td>\n", + " <td>Can't login</td>\n", + " </tr>\n", + " <tr>\n", + " <th>5</th>\n", + " <td>Message send problems</td>\n", + " <td>0.075580</td>\n", + " <td>Message send problems</td>\n", + " </tr>\n", + " <tr>\n", + " <th>6</th>\n", + " <td>Message read problems</td>\n", + " <td>0.033245</td>\n", + " <td>Message read problems</td>\n", + " </tr>\n", + " <tr>\n", + " <th>7</th>\n", + " <td>Mobile app crashes</td>\n", + " <td>0.031515</td>\n", + " <td>Mobile app crashes</td>\n", + " </tr>\n", + " <tr>\n", + " <th>8</th>\n", + " <td>Stream not working</td>\n", + " <td>0.029427</td>\n", + " <td>Stream not working</td>\n", + " </tr>\n", + " <tr>\n", + " <th>9</th>\n", + " <td>Videos won't play</td>\n", + " <td>0.023544</td>\n", + " <td>Videos won't play</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " reason mean_pdf reason_cat\n", + "0 Mobile app not working 0.174832 Mobile app not working\n", + "1 Website down 0.173807 Website down\n", + "2 Unknown 0.130210 Unknown\n", + "3 Everything is down 0.127983 Everything is down\n", + "4 Can't login 0.082374 Can't login\n", + "5 Message send problems 0.075580 Message send problems\n", + "6 Message read problems 0.033245 Message read problems\n", + "7 Mobile app crashes 0.031515 Mobile app crashes\n", + "8 Stream not working 0.029427 Stream not working\n", + "9 Videos won't play 0.023544 Videos won't play" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "reason_fraction_df_list = []\n", + "\n", + "for vendor in filtered_or_reports['vendor'].unique():\n", + " partial_df = filtered_or_reports[filtered_or_reports['vendor'] == vendor].reset_index(drop=True)\n", + " count_df = partial_df.groupby('reason')['id'].count().reset_index().rename(columns={'id': 'count'})\n", + " count_df['pdf'] = count_df['count'] / count_df['count'].sum()\n", + " count_df['vendor'] = vendor\n", + " reason_fraction_df_list.append(count_df)\n", + "\n", + "reason_fraction_df = pd.concat(reason_fraction_df_list)\n", + "mean_fractions_reasons = reason_fraction_df.groupby('reason')['pdf'].sum().reset_index().rename(columns={'pdf': 'mean_pdf'})\n", + "mean_fractions_reasons['mean_pdf'] = mean_fractions_reasons['mean_pdf'] / 12\n", + "top10_mean_fractions_reasons = mean_fractions_reasons.sort_values('mean_pdf', ascending=False).reset_index(drop=True)[:10]\n", + "reasons_sorted = top10_mean_fractions_reasons.sort_values('mean_pdf')['reason'].values\n", + "top10_mean_fractions_reasons['reason_cat'] = pd.Categorical(top10_mean_fractions_reasons['reason'], categories=reasons_sorted, ordered=True)\n", + "top10_mean_fractions_reasons" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 400x300 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (309449361)>" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "plt = ggplot(top10_mean_fractions_reasons) +\\\n", + " geom_bar(aes(x='reason_cat', y='mean_pdf'), stat='identity', fill='#0280c9') +\\\n", + " coord_flip() +\\\n", + " xlab('Reason') + ylab('Mean of fraction of reports per service') +\\\n", + " theme_classic(base_size=12, base_family='sans-serif') +\\\n", + " theme(figure_size=(4, 3),\n", + " axis_text_y=element_text(margin={'r': 5}),\n", + " text=element_text(size=12))\n", + "\n", + "plt.save('./plots/all_reports_by_reason.pdf', limitsize=False)\n", + "plt" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1062" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "github_or_reports.groupby('reason')['id'].count().reset_index().rename(columns={'id': 'count'})['count'].sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>vendor</th>\n", + " <th>count</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>3</th>\n", + " <td>github</td>\n", + " <td>1062</td>\n", + " </tr>\n", + " <tr>\n", + " <th>7</th>\n", + " <td>skype</td>\n", + " <td>2029</td>\n", + " </tr>\n", + " <tr>\n", + " <th>0</th>\n", + " <td>apple-servers</td>\n", + " <td>2566</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2</th>\n", + " <td>facebook-messenger</td>\n", + " <td>6836</td>\n", + " </tr>\n", + " <tr>\n", + " <th>8</th>\n", + " <td>snapchat</td>\n", + " <td>8118</td>\n", + " </tr>\n", + " <tr>\n", + " <th>10</th>\n", + " <td>whatsapp</td>\n", + " <td>9426</td>\n", + " </tr>\n", + " <tr>\n", + " <th>4</th>\n", + " <td>gmail</td>\n", + " <td>9427</td>\n", + " </tr>\n", + " <tr>\n", + " <th>6</th>\n", + " <td>netflix</td>\n", + " <td>20211</td>\n", + " </tr>\n", + " <tr>\n", + " <th>9</th>\n", + " <td>twitter</td>\n", + " <td>20252</td>\n", + " </tr>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>facebook</td>\n", + " <td>25886</td>\n", + " </tr>\n", + " <tr>\n", + " <th>11</th>\n", + " <td>youtube</td>\n", + " <td>26783</td>\n", + " </tr>\n", + " <tr>\n", + " <th>5</th>\n", + " <td>instagram</td>\n", + " <td>41574</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " vendor count\n", + "3 github 1062\n", + "7 skype 2029\n", + "0 apple-servers 2566\n", + "2 facebook-messenger 6836\n", + "8 snapchat 8118\n", + "10 whatsapp 9426\n", + "4 gmail 9427\n", + "6 netflix 20211\n", + "9 twitter 20252\n", + "1 facebook 25886\n", + "11 youtube 26783\n", + "5 instagram 41574" + ] + }, + "execution_count": 65, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "filtered_or_reports.groupby('vendor')['country'].count().reset_index().rename(columns={'country':'count'}).sort_values('count')" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/datasets/Talluri2021/4.response time experiment.ipynb b/datasets/Talluri2021/4.response time experiment.ipynb new file mode 100644 index 0000000..3c63e3b --- /dev/null +++ b/datasets/Talluri2021/4.response time experiment.ipynb @@ -0,0 +1,543 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import random\n", + "import gc\n", + "import time\n", + "import pandas as pd\n", + "from plotnine import *\n", + "from numpy.random import weibull" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "31536000\n", + "15768000.0\n", + "{0: 14995272.0, 1: 749658.0, 2: 22542.0, 3: 508.0, 4: 9.0} 10.926686001093943\n" + ] + } + ], + "source": [ + "def runsim(num_reqs, failure_prob_thresh, num_trials=1):\n", + " max_retries = 3\n", + " successful_requests = np.full((num_reqs, num_trials), False)\n", + " current_retries = np.full((num_reqs, num_trials), 0, dtype=np.uint8)\n", + " all_retries = np.full((num_reqs, num_trials), 0, dtype=np.uint8)\n", + " \n", + " # run till all requests succeed or max retries at all levels are exhausted\n", + " while (not np.all(successful_requests)) and np.all(current_retries < max_retries+1):\n", + " random_nums = np.random.random_sample(size=(num_reqs, num_trials))\n", + " successful_this_round = random_nums >= np.repeat(np.transpose([failure_prob_thresh]), num_trials, axis=1)\n", + "# print(successful_this_round)\n", + " \n", + " valid_requests_this_round = ~successful_requests & (current_retries < max_retries+1)\n", + " \n", + " \n", + " success_intermediate = (valid_requests_this_round & successful_this_round) | successful_requests\n", + " (failure_rows, failure_columns) = np.nonzero(~success_intermediate)\n", + " \n", + " # So, if requests fail at level 2 and 3. Only the failure at 2 is counted\n", + " # We can do this because failure_columns is SORTED in column order\n", + " # take care: unique rows does not contain all rows. There are many rows without any failures\n", + " (unique_rows, unique_indices) = np.unique(failure_rows, return_index=True)\n", + " unique_rows_first_column = failure_columns[unique_indices]\n", + " \n", + " # Update retries\n", + " current_retries[unique_rows, unique_rows_first_column] += 1\n", + " all_retries[unique_rows, unique_rows_first_column] += 1\n", + " \n", + " repeated_unique_rows_first_column = np.repeat(np.transpose([unique_rows_first_column]), num_trials, axis=1)\n", + " (row_indices, column_indices) = np.indices((num_reqs, num_trials))\n", + " mask = np.full((num_reqs, num_trials), np.iinfo(np.int32).max, dtype=np.int32)\n", + " mask[unique_rows] = repeated_unique_rows_first_column\n", + "# print(mask)\n", + " \n", + " successful_requests = column_indices < mask\n", + "\n", + " # Rollback to previous level if max retries for this level has been reached\n", + " rollback_mask = current_retries == max_retries\n", + " (exhausted_retries_rows, exhausted_retries_columns) = np.nonzero(rollback_mask)\n", + " exhausted_retries_prev_columns = exhausted_retries_columns - 1\n", + "# print(exhausted_retries_prev_columns)\n", + " valid_prev_col = exhausted_retries_prev_columns >= 0\n", + "# print(valid_prev_col)\n", + " can_be_retried_again_rows = exhausted_retries_rows[valid_prev_col]\n", + " can_be_retried_again_columns = exhausted_retries_columns[valid_prev_col]\n", + " \n", + " exhausted_retries_prev_columns[~valid_prev_col] = 0\n", + " successful_requests[exhausted_retries_rows, exhausted_retries_prev_columns] = False\n", + " current_retries[can_be_retried_again_rows, can_be_retried_again_columns] = 0\n", + " \n", + " # https://lup.lub.lu.se/search/ws/files/5764781/4814056.pdf\n", + " # Magnitude of sin from above paper\n", + " sin_input = np.linspace(-np.pi, np.pi, 24*60*60)\n", + " sin_scaler = np.tile((np.sin(sin_input) + 1) / 2, 365) # Sin min magnitude 0, max 1, for 365 days\n", + " \n", + " results = {}\n", + " overall_successful_requests = np.all(successful_requests, axis=1)\n", + " retries_per_request = np.sum(all_retries, axis=1)\n", + " consolidated_retries = retries_per_request[overall_successful_requests]\n", + " filtered_sin_scaler = sin_scaler[overall_successful_requests]\n", + "# print(consolidated_retries.shape)\n", + "# print(filtered_sin_scaler.shape)\n", + "# return (True, True)\n", + " unique_retries = np.unique(consolidated_retries)\n", + " for entry in unique_retries:\n", + " results[entry] = np.round(np.sum(filtered_sin_scaler[consolidated_retries == entry]))\n", + "# print(np.transpose(successful_requests))\n", + " scaled_unsuccessful_requests = ~overall_successful_requests * sin_scaler\n", + " return (results, np.sum(scaled_unsuccessful_requests))\n", + "\n", + "sin_input = np.linspace(-np.pi, np.pi, 24*60*60)\n", + "per_day_sin_scaler = (np.sin(sin_input) + 1) / 2\n", + "num_reqs = 365*24*60*60\n", + "scaled_num_reqs = np.sum(per_day_sin_scaler) * 365\n", + "print(num_reqs)\n", + "print(np.round(scaled_num_reqs))\n", + "# 20min is outage report granularity\n", + "num_20min_chunks = num_reqs // (20*60)\n", + "failure_probabilities = np.repeat(0.01, num_20min_chunks)\n", + "failure_prob_thresh = np.repeat(failure_probabilities, 20*60)\n", + "\n", + "(results, failed_reqs) = runsim(num_reqs, np.transpose(failure_prob_thresh), num_trials=5)\n", + "# (results, failed_reqs) = runsim(10, np.repeat(0.5, 10), num_trials=5)\n", + "print(results, failed_reqs)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{0: 28523119} 3012881\n" + ] + } + ], + "source": [ + "def runsim_fanout(num_reqs, failure_prob_thresh, fanout=1):\n", + " max_retries = 3\n", + " successful_requests = np.full((num_reqs, fanout), False)\n", + " current_retries = np.full((num_reqs, fanout), 0, dtype=np.uint8)\n", + " \n", + " # run till all requests succeed or max retries at all levels are exhausted\n", + " while (not np.all(successful_requests)) and np.all(current_retries < max_retries+1):\n", + " random_nums = np.random.random_sample(size=(num_reqs, fanout))\n", + " successful_this_round = random_nums >= np.repeat(np.transpose([failure_prob_thresh]), fanout, axis=1)\n", + " \n", + " valid_requests_this_round = ~successful_requests & (current_retries < max_retries+1)\n", + " successful_valid = valid_requests_this_round & successful_this_round\n", + " \n", + " # Update retries\n", + " current_retries[~successful_valid] += 1\n", + " \n", + " successful_requests = successful_requests | successful_valid\n", + " break\n", + " \n", + " results = {}\n", + " overall_successful_requests = np.all(successful_requests, axis=1)\n", + " consolidated_retries = np.sum(current_retries, axis=1)[overall_successful_requests]\n", + " unique_retries = np.unique(consolidated_retries)\n", + " for entry in unique_retries:\n", + " results[entry] = np.sum(consolidated_retries == entry)\n", + " return (results, np.sum(~overall_successful_requests))\n", + "\n", + "\n", + "num_reqs = 365*24*60*60\n", + "# 20min is outage report granularity\n", + "num_20min_chunks = num_reqs // (20*60)\n", + "failure_probabilities = np.repeat(0.01, num_20min_chunks)\n", + "failure_prob_thresh = np.repeat(failure_probabilities, 20*60)\n", + "\n", + "(results, failed_reqs) = runsim_fanout(num_reqs, np.transpose(failure_prob_thresh), fanout=10)\n", + "# (results, failed_reqs) = runsim_fanout(10, np.repeat(0.01, 10), fanout=10)\n", + "print(results, failed_reqs)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "num_reqs = 365*24*60*60\n", + "# 20min is outage report granularity\n", + "num_20min_chunks = num_reqs // (20*60)\n", + "num_iterations = 1\n", + "results = []" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "for iteration in range(num_iterations):\n", + " num_20min_chunks = num_reqs // (20*60)\n", + " failure_probabilities = np.repeat(0.01, num_20min_chunks)\n", + " failure_prob_thresh = np.repeat(failure_probabilities, 20*60)\n", + " \n", + "# (final_counts, failed_reqs) = runsim(num_reqs, failure_prob_thresh)\n", + "# results.append(pd.DataFrame({\n", + "# 'vendor': 'uniform',\n", + "# 'reqs': list(final_counts.values()) + [failed_reqs],\n", + "# 'retries': list(final_counts.keys()) + [100],\n", + "# 'iteration': iteration,\n", + "# 'experiment': 'monolith'\n", + "# }))\n", + " \n", + " (final_counts, failed_reqs) = runsim(num_reqs, failure_prob_thresh, num_trials=5)\n", + " results.append(pd.DataFrame({\n", + " 'vendor': 'uniform',\n", + " 'reqs': list(final_counts.values()) + [failed_reqs],\n", + " 'retries': list(final_counts.keys()) + [100],\n", + " 'iteration': iteration,\n", + " 'experiment': 'deep chain'\n", + " }))\n", + " \n", + "# (final_counts, failed_reqs) = runsim_fanout(num_reqs, failure_prob_thresh, fanout=10)\n", + "# results.append(pd.DataFrame({\n", + "# 'vendor': 'uniform',\n", + "# 'reqs': list(final_counts.values()) + [failed_reqs],\n", + "# 'retries': list(final_counts.keys()) + [100],\n", + "# 'iteration': iteration,\n", + "# 'experiment': 'fanout'\n", + "# }))" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[ vendor reqs retries iteration experiment\n", + " 0 uniform 28382785 0 0 monolith\n", + " 1 uniform 2837362 1 0 monolith\n", + " 2 uniform 284158 2 0 monolith\n", + " 3 uniform 28516 3 0 monolith\n", + " 4 uniform 3179 100 0 monolith,\n", + " vendor reqs retries iteration experiment\n", + " 0 uniform 28387324 0 0 monolith\n", + " 1 uniform 2834446 1 0 monolith\n", + " 2 uniform 282792 2 0 monolith\n", + " 3 uniform 28385 3 0 monolith\n", + " 4 uniform 3053 100 0 monolith,\n", + " vendor reqs retries iteration experiment\n", + " 0 uniform 18618827 0 0 deep chain\n", + " 1 uniform 9311619 1 0 deep chain\n", + " 2 uniform 2795059 2 0 deep chain\n", + " 3 uniform 652424 3 0 deep chain\n", + " 4 uniform 158071 100 0 deep chain,\n", + " vendor reqs retries iteration experiment\n", + " 0 uniform 10993887 0 0 fanout\n", + " 1 uniform 20542113 100 0 fanout]" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "results" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "or_events = pd.read_parquet('./outage_report_2019-20').reset_index(drop=True)\n", + "filtered_or_events = or_events[(or_events['vendor'] != '') & (or_events['vendor'] != 'overview')].copy()\n", + "filtered_or_events = filtered_or_events.drop_duplicates(subset=['vendor', 'event_time', 'status_code'])\n", + "# Combine events with the same event_time, but different status_code with max\n", + "filtered_or_events = filtered_or_events.groupby(['vendor', 'event_time'])['status_code'].max().reset_index()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "sin_input = np.linspace(-np.pi, np.pi, 24*3)\n", + "sin_scaler = np.tile((np.sin(sin_input) + 1) / 2, 365) # Sin min magnitude 0, max 1, for 265 days\n", + "for iteration in range(num_iterations):\n", + " vendor = 'instagram'\n", + " vendor_df = filtered_or_events[filtered_or_events['vendor'] == vendor].sort_values('event_time').reset_index(drop=True).loc[:num_20min_chunks-1]\n", + " scaled_reports = sin_scaler * vendor_df['status_code']\n", + " failure_fraction = scaled_reports / scaled_reports.max()\n", + " failure_prob_thresh = np.repeat(failure_fraction, 20*60)\n", + " \n", + "# (final_counts, failed_reqs) = runsim(num_reqs, failure_prob_thresh)\n", + "# results.append(pd.DataFrame({\n", + "# 'vendor': vendor,\n", + "# 'reqs': list(final_counts.values()) + [failed_reqs],\n", + "# 'retries': list(final_counts.keys()) + [100],\n", + "# 'iteration': iteration,\n", + "# 'experiment': 'monolith'\n", + "# }))\n", + " \n", + " (final_counts, failed_reqs) = runsim(num_reqs, failure_prob_thresh, num_trials=5)\n", + " results.append(pd.DataFrame({\n", + " 'vendor': vendor,\n", + " 'reqs': list(final_counts.values()) + [failed_reqs],\n", + " 'retries': list(final_counts.keys()) + [100],\n", + " 'iteration': iteration,\n", + " 'experiment': 'deep chain'\n", + " }))\n", + " \n", + "# (final_counts, failed_reqs) = runsim_fanout(num_reqs, failure_prob_thresh, fanout=10)\n", + "# results.append(pd.DataFrame({\n", + "# 'vendor': vendor,\n", + "# 'reqs': list(final_counts.values()) + [failed_reqs],\n", + "# 'retries': list(final_counts.keys()) + [100],\n", + "# 'iteration': iteration,\n", + "# 'experiment': 'fanout'\n", + "# }))" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "structures_experiment_results = pd.concat(results)\n", + "structures_experiment_results.to_csv('./experiment_results/long_chain_results_sin1.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "only_const_results = []\n", + "# for iteration in range(num_iterations):\n", + "iteration = 1\n", + "for prob in [0.01, 0.1, 0.25, 0.5, 0.75]:\n", + " num_20min_chunks = num_reqs // (20*60)\n", + " failure_probabilities = np.repeat(prob, num_20min_chunks)\n", + " failure_prob_thresh = np.repeat(failure_probabilities, 20*60)\n", + "\n", + " (final_counts, failed_reqs) = runsim(num_reqs, failure_prob_thresh)\n", + " only_const_results.append(pd.DataFrame({\n", + " 'vendor': 'uniform',\n", + " 'prob': prob,\n", + " 'reqs': list(final_counts.values()) + [failed_reqs],\n", + " 'retries': list(final_counts.keys()) + [100],\n", + " 'iteration': iteration,\n", + " 'experiment': 'monolith'\n", + " }))\n", + "\n", + " (final_counts, failed_reqs) = runsim(num_reqs, failure_prob_thresh, num_trials=5)\n", + " only_const_results.append(pd.DataFrame({\n", + " 'vendor': 'uniform',\n", + " 'prob': prob,\n", + " 'reqs': list(final_counts.values()) + [failed_reqs],\n", + " 'retries': list(final_counts.keys()) + [100],\n", + " 'iteration': iteration,\n", + " 'experiment': 'deep chain'\n", + " }))\n", + "\n", + " (final_counts, failed_reqs) = runsim_fanout(num_reqs, failure_prob_thresh, fanout=10)\n", + " only_const_results.append(pd.DataFrame({\n", + " 'vendor': 'uniform',\n", + " 'prob': prob,\n", + " 'reqs': list(final_counts.values()) + [failed_reqs],\n", + " 'retries': list(final_counts.keys()) + [100],\n", + " 'iteration': iteration,\n", + " 'experiment': 'fanout'\n", + " }))\n", + " \n", + "const_results_df = pd.concat(only_const_results)\n", + "const_results_df.to_csv('./experiment_results/const_experiment_results_1.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# highest failures for instagram are on 13th june 2019. Confirmed that an instagram outage occurred on that date\n", + "vendor_results = []\n", + "vendors = filtered_or_events['vendor'].unique()\n", + "for vendor in vendors:\n", + " vendor_df = filtered_or_events[filtered_or_events['vendor'] == vendor].sort_values('event_time').reset_index(drop=True).loc[:num_20min_chunks-1]\n", + " vendor_df['failure_fraction'] = vendor_df['status_code'] / vendor_df['status_code'].max()\n", + " for iteration in range(1):\n", + " (final_counts, failed_reqs) = runsim(num_reqs, np.repeat(vendor_df['failure_fraction'].values, 20*60))\n", + " vendor_results.append(pd.DataFrame({\n", + " 'vendor': vendor,\n", + " 'reqs': list(final_counts.values()) + [failed_reqs],\n", + " 'retries': list(final_counts.keys()) + [100],\n", + " 'iteration': iteration\n", + " }))\n", + "vendors" + ] + }, + { + "cell_type": "code", + "execution_count": 114, + "metadata": {}, + "outputs": [], + "source": [ + "vendor_results_df = pd.concat(vendor_results).reset_index(drop=True)\n", + "vendor_results_df = vendor_results_df[(vendor_results_df['iteration'] == 0) & (vendor_results_df['retries'] != 0)]" + ] + }, + { + "cell_type": "code", + "execution_count": 115, + "metadata": {}, + "outputs": [], + "source": [ + "vendor_results_df['fraction'] = vendor_results_df['reqs'] / num_reqs\n", + "vendor_results_df['color'] = 'trace'\n", + "vendor_results_df.loc[vendor_results_df['vendor'] == 'uniform', 'color'] = 'uniform'" + ] + }, + { + "cell_type": "code", + "execution_count": 116, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:719: PlotnineWarning: Saving 6.4 x 4.8 in image.\n", + "/home/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:722: PlotnineWarning: Filename: traces_vs_uniform-uniform_workload.png\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 640x480 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (8757981852757)>" + ] + }, + "execution_count": 116, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "plt = ggplot(vendor_results_df) +\\\n", + " geom_line(aes(x='retries', y='fraction', group='vendor', color='color'), size=1) +\\\n", + " scale_y_log10() +\\\n", + " xlab('num_retries')\n", + "\n", + "plt.save('traces_vs_uniform-uniform_workload.png', dpi=300)\n", + "plt" + ] + }, + { + "cell_type": "code", + "execution_count": 140, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 640x480 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (8757963694102)>" + ] + }, + "execution_count": 140, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x = np.linspace(-np.pi, np.pi, 24*3)\n", + "y = np.tile(np.sin(x) + 1, 365) / 2\n", + "\n", + "ggplot()+\\\n", + " geom_line(aes(x=range(len(y))[:10000], y=y[:10000]))" + ] + }, + { + "cell_type": "code", + "execution_count": 128, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.17453292519943295" + ] + }, + "execution_count": 128, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "2*np.pi / (12)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.1" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/datasets/Talluri2021/5.analyze experiment results.ipynb b/datasets/Talluri2021/5.analyze experiment results.ipynb new file mode 100644 index 0000000..e071db7 --- /dev/null +++ b/datasets/Talluri2021/5.analyze experiment results.ipynb @@ -0,0 +1,115 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "from plotnine import *" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# results_df = pd.read_csv('structures_experiment_results_1.csv')\n", + "results_df = pd.read_csv('./experiment_results/long_chain_results_sin1.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "results_df['cat_retries'] = pd.Categorical(results_df['retries']).rename_categories({100: 'Fail'})\n", + "# results_df['fraction'] = results_df['reqs'] / (365*24*60*60)\n", + "results_df['fraction'] = results_df['reqs'] / (365*24*60*60/2) # For sin stuff\n", + "min_max_per_exp = results_df.groupby(['vendor', 'experiment', 'cat_retries'])['fraction'].agg(['min', 'max', 'mean']).reset_index().fillna(0)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:719: PlotnineWarning: Saving 6.4 x 4.8 in image.\n", + "/home/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:722: PlotnineWarning: Filename: deep chain comparison.png\n", + "/home/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/pandas/core/series.py:726: RuntimeWarning: divide by zero encountered in log10\n", + "/home/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:719: PlotnineWarning: Saving 6.4 x 4.8 in image.\n", + "/home/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:722: PlotnineWarning: Filename: deep chain comparison.pdf\n", + "/home/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/pandas/core/series.py:726: RuntimeWarning: divide by zero encountered in log10\n", + "/home/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/pandas/core/series.py:726: RuntimeWarning: divide by zero encountered in log10\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 640x480 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (8762072340285)>" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "experiment = 'deep chain'\n", + "specific_min_max = min_max_per_exp[(min_max_per_exp['experiment'] == experiment)]\n", + "plt = ggplot(specific_min_max) +\\\n", + " theme_light(base_size=12, base_family='sans-serif') +\\\n", + " theme(text=element_text(size=12), legend_position=(0.3, 0.25)) +\\\n", + " geom_point(aes(x='cat_retries', y='mean', color='vendor', group='vendor'), size=3, shape='s') +\\\n", + " scale_y_log10(limits=[1, 1e-8], breaks = [0.1, 0.01, 0.001, 0.0001, 0.00001, 0.000001, 0.0000001, 0.4e-8],\n", + " labels=['10%', '1%', '0.1%', '$10^{-2}$%', '$10^{-3}$%', '$10^{-4}$%', '$10^{-5}$%', '0']) +\\\n", + " guides(color=guide_legend(title='Workload'), fill=guide_legend(title='Workload')) +\\\n", + " scale_color_discrete(labels=['Instagram trace', 'Constant']) +\\\n", + " xlab('Number of retries')+\\\n", + " ylab('Fraction of requests')\n", + "\n", + "plt.save(f'{experiment} comparison.png', dpi=300)\n", + "plt.save(f'{experiment} comparison.pdf')\n", + "plt" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.1" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/datasets/Talluri2021/Dockerfile b/datasets/Talluri2021/Dockerfile new file mode 100644 index 0000000..f13c99a --- /dev/null +++ b/datasets/Talluri2021/Dockerfile @@ -0,0 +1,22 @@ +FROM python:3.8 + +RUN apt-get update && \ + apt-get install -y libjemalloc-dev libboost-dev \ + libboost-filesystem-dev \ + libboost-system-dev \ + libboost-regex-dev \ + python-dev \ + autoconf \ + flex \ + bison \ + cmake + +ADD ./ $HOME/jupyter/ + +WORKDIR $HOME/jupyter + +RUN pip install -r requirements.txt + +EXPOSE 8888 + +ENTRYPOINT ["jupyter","lab","--no-browser","--ip=0.0.0.0","--allow-root","--NotebookApp.token=''","--NotebookApp.password=''"]
\ No newline at end of file diff --git a/datasets/Talluri2021/README.md b/datasets/Talluri2021/README.md new file mode 100644 index 0000000..7f3b862 --- /dev/null +++ b/datasets/Talluri2021/README.md @@ -0,0 +1,27 @@ +## Characterization of OutageReport for years 2019 and 2020 + +This repository contains two datasets extracted from OutageReport webpages in 2019 and 2020. One dataset of total reported failures and another of failure with detailed information. + +The datasets are in the Parquet file format. + +The Jupyter Notebook files read the datasets, clean them, and generate plots and numbers for characterization. + +All the plots used in the paper can be generated by running the jupyter notebooks in order. The plots can also ve viewed in the notebooks themselves. + +The easiest way to run the notebooks is to use the prebuilt docker container using the command `docker run --rm -p 8888:8888 sacheendra/or_char`. + +To reproduce the graphs in the paper: +1. Start the docker container. (If you are using Docker for Mac or Windows, you might need to expose port 8888 between docker vm and host) +2. Navigate to localhost:8888 in your browser. +3. On the webpage, you should see a list of files in a pane on the left. +4. The code to reproduce the graphs in in Jupyter notebooks. Jupyter notebooks have the extension `.ipynb`. +5. The noteboks to produce the plots in the paper are numbered from 1 to 5. +6. To run a notebook, first open it by double clicking it. +7. The code in the notebook can then be run by opening the `Run` dropdown at top-left, and clicking on the `Run all cells` option. + +Figure to notebook reference: +Figure 1 - Notebook 1 +Table 2 - Notebook 2 +Figure 2 - Notebook 3 +Figure 3 - Notebook 2 +Figure 4 - Experiment in Notebook 4, Plot in Notebook 5
\ No newline at end of file diff --git a/datasets/Talluri2021/artifact_documentation.txt b/datasets/Talluri2021/artifact_documentation.txt new file mode 100644 index 0000000..c95f1ff --- /dev/null +++ b/datasets/Talluri2021/artifact_documentation.txt @@ -0,0 +1,23 @@ +System Requirements: +Linux (Port forwarding confirmed to work on Linux) +Docker >= 20.0 + +The artifact is a docker container that can be pulled from Docker Hub using the command `docker pull sacheendra/or_char`. + +The container can then be started using `docker run --rm -p 8888:8888 sacheendra/or_char`. + +To reproduce the graphs in the paper: +1. Start the docker container. (If you are using Docker for Mac or Windows, you might need to expose port 8888 between docker vm and host) +2. Navigate to localhost:8888 in your browser. +3. On the webpage, you should see a list of files in a pane on the left. +4. The code to reproduce the graphs in in Jupyter notebooks. Jupyter notebooks have the extension `.ipynb`. +5. The noteboks to produce the plots in the paper are numbered from 1 to 5. +6. To run a notebook, first open it by double clicking it. +7. The code in the notebook can then be run by opening the `Run` dropdown at top-left, and clicking on the `Run all cells` option. + +Figure to notebook reference: +Figure 1 - Notebook 1 +Table 2 - Notebook 2 +Figure 2 - Notebook 3 +Figure 3 - Notebook 2 +Figure 4 - Experiment in Notebook 4, Plot in Notebook 5
\ No newline at end of file diff --git a/datasets/Talluri2021/deep chain comparison.pdf b/datasets/Talluri2021/deep chain comparison.pdf Binary files differnew file mode 100644 index 0000000..80c73f4 --- /dev/null +++ b/datasets/Talluri2021/deep chain comparison.pdf diff --git a/datasets/Talluri2021/deep chain comparison.png b/datasets/Talluri2021/deep chain comparison.png Binary files differnew file mode 100644 index 0000000..084a34c --- /dev/null +++ b/datasets/Talluri2021/deep chain comparison.png diff --git a/datasets/Talluri2021/experiment_results/long_chain_results_sin1.csv b/datasets/Talluri2021/experiment_results/long_chain_results_sin1.csv new file mode 100644 index 0000000..e3400c9 --- /dev/null +++ b/datasets/Talluri2021/experiment_results/long_chain_results_sin1.csv @@ -0,0 +1,13 @@ +,vendor,reqs,retries,iteration,experiment +0,uniform,14994946.0,0,0,deep chain +1,uniform,750141.0,1,0,deep chain +2,uniform,22399.0,2,0,deep chain +3,uniform,487.0,3,0,deep chain 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.update-title.impact-none a:hover, + .layout-content.status-index .timeframes-container .timeframe.active, + .layout-content.status-full-history .month .incident-container .impact-none, + .layout-content.status.status-index .incidents-list .incident-title.impact-none a, + .incident-history .impact-none, + .layout-content.status .grouped-items-selector.inline .grouped-item.active, + .layout-content.status.status-full-history .history-nav a.current, + .layout-content.status.status-full-history .history-nav a:not(.current):hover, + #uptime-tooltip .tooltip-box .tooltip-content .related-events .related-event a.related-event-link { + color:#24292e; + } + + .layout-content.status.status-index .components-statuses .component-container .name { + color:#24292e; + color:rgba(36,41,46,.8); + } + + + + + /* SECONDARY FONT COLOR */ /* SECONDARY FONT COLOR */ /* SECONDARY FONT COLOR */ /* SECONDARY FONT COLOR */ + small, + .layout-content.status .table-row .date, + .color-secondary, + .layout-content.status .grouped-items-selector.inline .grouped-item, + .layout-content.status.status-full-history .history-footer .pagination a.disabled, + .layout-content.status.status-full-history .history-nav a, + #uptime-tooltip .tooltip-box .tooltip-content .related-events #related-event-header { + color:#6a737d; + } + + + + + /* BORDER COLOR */ /* BORDER COLOR */ /* BORDER COLOR */ /* BORDER COLOR */ /* BORDER COLOR */ /* BORDER COLOR */ + body.status .layout-content.status .border-color, + hr, + .tooltip-base, + .markdown-display table, + #uptime-tooltip .tooltip-box { + border-color:#e1e4e8; + } + + .markdown-display table td { + border-top-color:#e1e4e8; + } + + .markdown-display table td + td, .markdown-display table th + th { + border-left-color:#e1e4e8; + } + + #uptime-tooltip .pointer-container .pointer-larger { + border-bottom-color:#e1e4e8; + } + + #uptime-tooltip .tooltip-box .outage-field { + /* + Generate the background-color for the outage-field from the css_body_background_color and css_border_color. + + For the default background (#ffffff) and default css_border_color (#e0e0e0), use the luminosity of the default background with a magic number to arrive at + the original outage-field background color (#f4f5f7). I used the formula Target Color = Color * alpha + Background * (1 - alpha) to find the magic number of ~0.08. + + For darker css_body_background_color, luminosity values are lower so alpha trends toward becoming transparent (thus outage-field background becomes same as css_body_background_color). + */ + background-color: rgba(225,228,232,0.31); + + /* + outage-field border-color alpha is inverse to the luminosity of css_body_background_color. + That is to say, with a default white background this border is transparent, but on a black background, it's opaque css_border_color. + */ + border-color: rgba(225,228,232,0.0); + } + + + + + /* CSS REDS */ /* CSS REDS */ /* CSS REDS */ /* CSS REDS */ /* CSS REDS */ /* CSS REDS */ /* CSS REDS */ + .layout-content.status.status-index .status-day .update-title.impact-critical a, + .layout-content.status.status-index .status-day .update-title.impact-critical a:hover, + .layout-content.status.status-index .page-status.status-critical, + .layout-content.status.status-index .unresolved-incident.impact-critical .incident-title, + .flat-button.background-red { + background-color:#dc3545; + } + + .layout-content.status-index .components-statuses .component-container.status-red:after, + .layout-content.status-full-history .month .incident-container .impact-critical, + .layout-content.status-incident .incident-name.impact-critical, + .layout-content.status.status-index .incidents-list .incident-title.impact-critical a, + .status-red .icon-indicator, + .incident-history .impact-critical, + .components-container .component-inner-container.status-red .component-status, + .components-container .component-inner-container.status-red .icon-indicator { + color:#dc3545; + } + + .layout-content.status.status-index .unresolved-incident.impact-critical .updates { + border-color:#dc3545; + } + + + + + /* CSS ORANGES */ /* CSS ORANGES */ /* CSS ORANGES */ /* CSS ORANGES */ /* CSS ORANGES */ /* CSS ORANGES */ + .layout-content.status.status-index .status-day .update-title.impact-major a, + .layout-content.status.status-index .status-day .update-title.impact-major a:hover, + .layout-content.status.status-index .page-status.status-major, + .layout-content.status.status-index .unresolved-incident.impact-major .incident-title { + background-color:#e36209; + } + + .layout-content.status-index .components-statuses .component-container.status-orange:after, + .layout-content.status-full-history .month .incident-container .impact-major, + .layout-content.status-incident .incident-name.impact-major, + .layout-content.status.status-index .incidents-list .incident-title.impact-major a, + .status-orange .icon-indicator, + .incident-history .impact-major, + .components-container .component-inner-container.status-orange .component-status, + .components-container .component-inner-container.status-orange .icon-indicator { + color:#e36209; + } + + .layout-content.status.status-index .unresolved-incident.impact-major .updates { + border-color:#e36209; + } + + + + + /* CSS YELLOWS */ /* CSS YELLOWS */ /* CSS YELLOWS */ /* CSS YELLOWS */ /* CSS YELLOWS */ /* CSS YELLOWS */ + .layout-content.status.status-index .status-day .update-title.impact-minor a, + .layout-content.status.status-index .status-day .update-title.impact-minor a:hover, + .layout-content.status.status-index .page-status.status-minor, + .layout-content.status.status-index .unresolved-incident.impact-minor .incident-title, + .layout-content.status.status-index .scheduled-incidents-container .tab { + background-color:#dbab09; + } + + .layout-content.status-index .components-statuses .component-container.status-yellow:after, + .layout-content.status-full-history .month .incident-container .impact-minor, + .layout-content.status-incident .incident-name.impact-minor, + .layout-content.status.status-index .incidents-list .incident-title.impact-minor a, + .status-yellow .icon-indicator, + .incident-history .impact-minor, + .components-container .component-inner-container.status-yellow .component-status, + .components-container .component-inner-container.status-yellow .icon-indicator, + .layout-content.status.manage-subscriptions .confirmation-infobox .fa { + color:#dbab09; + } + + .layout-content.status.status-index .unresolved-incident.impact-minor .updates, + .layout-content.status.status-index .scheduled-incidents-container { + border-color:#dbab09; + } + + + + + /* CSS BLUES */ /* CSS BLUES */ /* CSS BLUES */ /* CSS BLUES */ /* CSS BLUES */ /* CSS BLUES */ + .layout-content.status.status-index .status-day .update-title.impact-maintenance a, + .layout-content.status.status-index .status-day .update-title.impact-maintenance a:hover, + .layout-content.status.status-index .page-status.status-maintenance, + .layout-content.status.status-index .unresolved-incident.impact-maintenance .incident-title, + .layout-content.status.status-index .scheduled-incidents-container .tab { + background-color:#0366d6; + } + + .layout-content.status-index .components-statuses .component-container.status-blue:after, + .layout-content.status-full-history .month .incident-container .impact-maintenance, + .layout-content.status-incident .incident-name.impact-maintenance, + .layout-content.status.status-index .incidents-list .incident-title.impact-maintenance a, + .status-blue .icon-indicator, + .incident-history .impact-maintenance, + .components-container .component-inner-container.status-blue .component-status, + .components-container .component-inner-container.status-blue .icon-indicator { + color:#0366d6; + } + + .layout-content.status.status-index .unresolved-incident.impact-maintenance .updates, + .layout-content.status.status-index .scheduled-incidents-container { + border-color:#0366d6; + } + + + + + /* CSS GREENS */ /* CSS GREENS */ /* CSS GREENS */ /* CSS GREENS */ /* CSS GREENS */ /* CSS GREENS */ /* CSS GREENS */ + .layout-content.status.status-index .page-status.status-none { + background-color:#28a745; + } + .layout-content.status-index .components-statuses .component-container.status-green:after, + .status-green .icon-indicator, + .components-container .component-inner-container.status-green .component-status, + .components-container .component-inner-container.status-green .icon-indicator { + color:#28a745; + } + + + + + /* CSS LINK COLOR */ /* CSS LINK COLOR */ /* CSS LINK COLOR */ /* CSS LINK COLOR */ /* CSS LINK COLOR */ /* CSS LINK COLOR */ + a, + a:hover, + .layout-content.status-index .page-footer span a:hover, + .layout-content.status-index .timeframes-container .timeframe:not(.active):hover, + .layout-content.status-incident .subheader a:hover { + color:#0366d6; + } + + .flat-button, + .masthead .updates-dropdown-container .show-updates-dropdown, + .layout-content.status-full-history .show-filter.open { + background-color:#0366d6; + } + + + + + /* CUSTOM COLOR OVERRIDES FOR UPTIME SHOWCASE */ + .components-section .components-uptime-link { + color: #6a737d; + } + + .layout-content.status .shared-partial.uptime-90-days-wrapper .legend .legend-item { + color: #6a737d; + opacity: 0.8; + } + .layout-content.status .shared-partial.uptime-90-days-wrapper .legend .legend-item.light { + color: #6a737d; + opacity: 0.5; + } + .layout-content.status .shared-partial.uptime-90-days-wrapper .legend .spacer { + background: #6a737d; + opacity: 0.3; + } +</style> + + + <!-- custom css --> + <link rel="stylesheet" type="text/css" href="//dka575ofm4ao0.cloudfront.net/page_display_customizations-custom_css_externals/36313/external20191210-18-vvi5yj.css"> + + <!-- polyfills --> + <script crossorigin="anonymous" src="https://polyfill.io/v3/polyfill.min.js?features=default"></script> + + <!-- Le HTML5 shim --> + <!--[if lt IE 9]> + <script src="//html5shim.googlecode.com/svn/trunk/html5.js"></script> + <![endif]--> + + <!-- injection for static --> + + + + </head> + + + <body class="status index status-none"> + + + + + <div class="layout-content status status-index starter"> + <div class="custom-header-container"> + <div class="header d-md-flex flex-md-justify-between flex-md-items-center px-4 py-3 text-center text-md-left bg-white box-shadow-large">
+ <a href="/" class="text-gray-dark"><svg height="32" class="octicon octicon-mark-github d-block mx-auto" viewBox="0 0 16 16" version="1.1" width="32" aria-hidden="true"><path fill-rule="evenodd" d="M8 0C3.58 0 0 3.58 0 8c0 3.54 2.29 6.53 5.47 7.59.4.07.55-.17.55-.38 0-.19-.01-.82-.01-1.49-2.01.37-2.53-.49-2.69-.94-.09-.23-.48-.94-.82-1.13-.28-.15-.68-.52-.01-.53.63-.01 1.08.58 1.23.82.72 1.21 1.87.87 2.33.66.07-.52.28-.87.51-1.07-1.78-.2-3.64-.89-3.64-3.95 0-.87.31-1.59.82-2.15-.08-.2-.36-1.02.08-2.12 0 0 .67-.21 2.2.82.64-.18 1.32-.27 2-.27.68 0 1.36.09 2 .27 1.53-1.04 2.2-.82 2.2-.82.44 1.1.16 1.92.08 2.12.51.56.82 1.27.82 2.15 0 3.07-1.87 3.75-3.65 3.95.29.25.54.73.54 1.48 0 1.07-.01 1.93-.01 2.2 0 .21.15.46.55.38A8.013 8.013 0 0 0 16 8c0-4.42-3.58-8-8-8z"></path></svg></a>
+
+ <nav class="f4 list-style-none py-2 mt-2 mt-md-0">
+ <a class="mr-3 mr-lg-4 py-2" href="https://help.github.com">Help</a>
+ <a class="mr-3 mr-lg-4 py-2" href="https://github.community">Community</a>
+ <a class="py-2 text-gray" href="/">Status</a>
+ </nav>
+
+ <nav class="f4 list-style-none py-2 text-md-right">
+ <a class="py-2" href="https://github.com">GitHub.com</a>
+ <a class="py-2 ml-3 ml-lg-4" href="https://twitter.com/githubstatus">Twitter</a>
+ <div class="d-inline py-2 ml-3 ml-lg-4">
+ <div id="replace-with-subscribe"></div>
+ </div>
+ </nav>
+</div>
+
+<img src="https://user-images.githubusercontent.com/19292210/60553863-044dd200-9cea-11e9-987e-7db84449f215.png" class="illo-desktop-header" style="display: none;">
+
+<img src="https://user-images.githubusercontent.com/19292210/60553865-044dd200-9cea-11e9-859c-d6f266e2f01f.png" class="illo-mobile-header"> + + + + <div class="updates-dropdown-container" data-js-hook="updates-dropdown-container"> + <a href="#" data-js-hook="show-updates-dropdown" id="show-updates-dropdown" class="show-updates-dropdown"> + + </a> + <div class="updates-dropdown" data-js-hook="updates-dropdown" style="display:none"> + <div class="updates-dropdown-nav nav-items-7"> + <a href="#updates-dropdown-email" id="updates-dropdown-email-btn"> + <span class="icon-container email"> + </a> + <a href="#updates-dropdown-sms" id="updates-dropdown-sms-btn"> + <span class="icon-container sms"> + </a> + <a href="#updates-dropdown-webhook" id="updates-dropdown-webhook-btn"> + <span class="icon-container webhook"> + </a> + <a href="#updates-dropdown-twitter" id="updates-dropdown-twitter-btn"> + <span class="icon-container twitter"> + </a> + <a href="#updates-dropdown-support" id="updates-dropdown-support-btn"> + <span class="icon-container support"> + </a> + <a href="#updates-dropdown-atom" id="updates-dropdown-atom-btn"> + <span class="icon-container rss"> + </a> + <a href="#" data-js-hook="updates-dropdown-close" id="updates-dropdown-close-btn"> + x + </a> + </div> + <div class="updates-dropdown-sections-container"> + <div class="updates-dropdown-section email" id="updates-dropdown-email" style="display:none"> + <div class="directions"> + Get email notifications whenever GitHub <strong>creates</strong>, <strong>updates</strong> or <strong>resolves</strong> an incident. + </div> + <form id="subscribe-form-email" action="/subscriptions/new-email" accept-charset="UTF-8" data-remote="true" method="post"><input name="utf8" type="hidden" value="✓" /> + <!-- make sure not to put cookie values in here since this gets cached --> + <input name="email" id="email" type="text" placeholder="Email Address" class="full-width" data-js-hook="email-notification-field"> + <input type="hidden" name="captcha_error" id="captcha_error" value="false" /> + <input type="submit" value="Subscribe via Email" class="flat-button full-width g-recaptcha" id="subscribe-btn-email" data-disabled-text="Subscribing..." data-sitekey=6LdTS8AUAAAAAOIbCKoCAP4LQku1olYGrywPTaZz data-callback="submitNewEmailSubscriber" data-error-callback="emailSubscriberCaptchaError" > + <div class="terms_and_privacy_information bottom small"><div class="privacy_policy_information small">By subscribing you agree to our <a target="_blank" rel="noopener" href="https://help.github.com/articles/github-privacy-statement/">Privacy Policy</a>.</div> This site is protected by reCAPTCHA and the Google <a target="_blank" rel="noopener" href="https://policies.google.com/privacy">Privacy Policy</a> and <a target="_blank" rel="noopener" href="https://policies.google.com/terms">Terms of Service</a> apply.</div> +</form> </div> + + <div class="updates-dropdown-section phone" id="updates-dropdown-sms" style="display:none"> + <div class="directions"> + Get text message notifications whenever GitHub <strong>creates</strong> or <strong>resolves</strong> an incident. + </div> + <form id="subscribe-form-sms" action="/subscriptions/new-sms" accept-charset="UTF-8" data-remote="true" method="post"><input name="utf8" type="hidden" value="✓" /> + <div class="control-group"> + <div class="controls externalities-sms-container"> + <!-- make sure not to put cookie values in here since this gets cached --> + <select name="phone_country" id="phone-country" data-js-hook="phone-country" class="phone-country"><option value="af">Afghanistan (+93)</option> +<option value="al">Albania (+355)</option> +<option value="dz">Algeria (+213)</option> +<option value="as">American Samoa (+1)</option> +<option value="ad">Andorra (+376)</option> +<option value="ao">Angola (+244)</option> +<option value="ai">Anguilla (+1)</option> +<option value="ag">Antigua and Barbuda (+1)</option> +<option value="ar">Argentina (+54)</option> +<option value="am">Armenia (+374)</option> +<option value="aw">Aruba (+297)</option> +<option value="au">Australia/Cocos/Christmas Island (+61)</option> +<option value="at">Austria (+43)</option> +<option value="az">Azerbaijan (+994)</option> +<option value="bs">Bahamas (+1)</option> +<option value="bh">Bahrain (+973)</option> +<option value="bd">Bangladesh (+880)</option> +<option value="bb">Barbados (+1)</option> +<option value="by">Belarus (+375)</option> +<option value="be">Belgium (+32)</option> +<option value="bz">Belize (+501)</option> +<option value="bj">Benin (+229)</option> +<option value="bm">Bermuda (+1)</option> +<option value="bo">Bolivia (+591)</option> +<option value="ba">Bosnia and Herzegovina (+387)</option> +<option value="bw">Botswana (+267)</option> +<option value="br">Brazil (+55)</option> +<option value="bn">Brunei (+673)</option> +<option value="bg">Bulgaria (+359)</option> +<option value="bf">Burkina Faso (+226)</option> +<option value="bi">Burundi (+257)</option> +<option value="kh">Cambodia (+855)</option> +<option value="cm">Cameroon (+237)</option> +<option value="ca">Canada (+1)</option> +<option value="cv">Cape Verde (+238)</option> +<option value="ky">Cayman Islands (+1)</option> +<option value="cf">Central Africa (+236)</option> +<option value="td">Chad (+235)</option> +<option value="cl">Chile (+56)</option> +<option value="cn">China (+86)</option> +<option value="co">Colombia (+57)</option> +<option value="km">Comoros (+269)</option> +<option value="cg">Congo (+242)</option> +<option value="cd">Congo, Dem Rep (+243)</option> +<option value="cr">Costa Rica (+506)</option> +<option value="hr">Croatia (+385)</option> +<option value="cy">Cyprus (+357)</option> +<option value="cz">Czech Republic (+420)</option> +<option value="dk">Denmark (+45)</option> +<option value="dj">Djibouti (+253)</option> +<option value="dm">Dominica (+1)</option> +<option value="do">Dominican Republic (+1)</option> +<option value="eg">Egypt (+20)</option> +<option value="sv">El Salvador (+503)</option> +<option value="gq">Equatorial Guinea (+240)</option> +<option value="ee">Estonia (+372)</option> +<option value="et">Ethiopia (+251)</option> +<option value="fo">Faroe Islands (+298)</option> +<option value="fj">Fiji (+679)</option> +<option value="fi">Finland/Aland Islands (+358)</option> +<option value="fr">France (+33)</option> +<option value="gf">French Guiana (+594)</option> +<option value="pf">French Polynesia (+689)</option> +<option value="ga">Gabon (+241)</option> +<option value="gm">Gambia (+220)</option> +<option value="ge">Georgia (+995)</option> +<option value="de">Germany (+49)</option> +<option value="gh">Ghana (+233)</option> +<option value="gi">Gibraltar (+350)</option> +<option value="gr">Greece (+30)</option> +<option value="gl">Greenland (+299)</option> +<option value="gd">Grenada (+1)</option> +<option value="gp">Guadeloupe (+590)</option> +<option value="gu">Guam (+1)</option> +<option value="gt">Guatemala (+502)</option> +<option value="gn">Guinea (+224)</option> +<option value="gy">Guyana (+592)</option> +<option value="ht">Haiti (+509)</option> +<option value="hn">Honduras (+504)</option> +<option value="hk">Hong Kong (+852)</option> +<option value="hu">Hungary (+36)</option> +<option value="is">Iceland (+354)</option> +<option value="in">India (+91)</option> +<option value="id">Indonesia (+62)</option> +<option value="iq">Iraq (+964)</option> +<option value="ie">Ireland (+353)</option> +<option value="il">Israel (+972)</option> +<option value="it">Italy (+39)</option> +<option value="jm">Jamaica (+1)</option> +<option value="jp">Japan (+81)</option> +<option value="jo">Jordan (+962)</option> +<option value="ke">Kenya (+254)</option> +<option value="kr">Korea, Republic of (+82)</option> +<option value="kw">Kuwait (+965)</option> +<option value="kg">Kyrgyzstan (+996)</option> +<option value="la">Laos (+856)</option> +<option value="lv">Latvia (+371)</option> +<option value="lb">Lebanon (+961)</option> +<option value="ls">Lesotho (+266)</option> +<option value="lr">Liberia (+231)</option> +<option value="ly">Libya (+218)</option> +<option value="li">Liechtenstein (+423)</option> +<option value="lt">Lithuania (+370)</option> +<option value="lu">Luxembourg (+352)</option> +<option value="mo">Macao (+853)</option> +<option value="mk">Macedonia (+389)</option> +<option value="mg">Madagascar (+261)</option> +<option value="mw">Malawi (+265)</option> +<option value="my">Malaysia (+60)</option> +<option value="mv">Maldives (+960)</option> +<option value="ml">Mali (+223)</option> +<option value="mt">Malta (+356)</option> +<option value="mq">Martinique (+596)</option> +<option value="mr">Mauritania (+222)</option> +<option value="mu">Mauritius (+230)</option> +<option value="mx">Mexico (+52)</option> +<option value="mc">Monaco (+377)</option> +<option value="mn">Mongolia (+976)</option> +<option value="me">Montenegro (+382)</option> +<option value="ms">Montserrat (+1)</option> +<option value="ma">Morocco/Western Sahara (+212)</option> +<option value="mz">Mozambique (+258)</option> +<option value="na">Namibia (+264)</option> +<option value="np">Nepal (+977)</option> +<option value="nl">Netherlands (+31)</option> +<option value="nz">New Zealand (+64)</option> +<option value="ni">Nicaragua (+505)</option> +<option value="ne">Niger (+227)</option> +<option value="ng">Nigeria (+234)</option> +<option value="no">Norway (+47)</option> +<option value="om">Oman (+968)</option> +<option value="pk">Pakistan (+92)</option> +<option value="ps">Palestinian Territory (+970)</option> +<option value="pa">Panama (+507)</option> +<option value="py">Paraguay (+595)</option> +<option value="pe">Peru (+51)</option> +<option value="ph">Philippines (+63)</option> +<option value="pl">Poland (+48)</option> +<option value="pt">Portugal (+351)</option> +<option value="pr">Puerto Rico (+1)</option> +<option value="qa">Qatar (+974)</option> 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+</div> + +</div> + +</div> + + </div> + <div class="component-container border-color"> + +<div data-component-id="5l5rlzqm4yzy" + class="component-inner-container status-green " + data-component-status="operational" + data-js-hook=""> + + <span class="name"> + Other + </span> + + <span class="tooltip-base tool" title="Other">?</span> + + <span + class="component-status " + title="" + > + Operational + </span> + + <span class="tool icon-indicator fa fa-check" title="Operational"></span> + +</div> + + </div> + </div> + <div class="component-statuses-legend font-small"> + <div class="legend-item status-green"> + <span class="icon-indicator fa fa-check"></span> + Operational + </div> + <div class="legend-item status-yellow"> + <span class="icon-indicator fa fa-minus-square"></span> + Degraded Performance + </div> + <div class="legend-item status-orange"> + <span class="icon-indicator fa fa-exclamation-triangle"></span> + Partial Outage + </div> + <div class="breaker"></div> + <div class="legend-item status-red"> + <span class="icon-indicator fa fa-times"></span> + Major Outage + </div> + <div class="legend-item status-blue"> + <span class="icon-indicator fa fa-wrench"></span> + Maintenance + </div> +</div> + + </div> + + <script type="text/javascript" charset="utf-8"> + + function calculateViewbox (dayCount, rectWidth, rectPadding) { + var viewBox = []; + if (dayCount === 90) { + viewBox.push(0); + } else { + var offset = 90 - dayCount; + viewBox.push((offset * rectWidth) + (rectPadding * (offset))); // x origin + } + viewBox.push(0); // y origin + viewBox.push((rectWidth * dayCount) + (rectPadding * (dayCount - 1))); // svg width + viewBox.push(34); // svg height + return viewBox.join(' '); + } + + // returns the number of visible columns based on the current screen width + function getVisibleColumns(width, colCount) { + var ONE_COLUMN_BREAKPOINT = 700, + TWO_COLUMN_BREAKPOINT = 900; + var visibleColumns = 1; + if (width > TWO_COLUMN_BREAKPOINT) { + visibleColumns = colCount; + } + else if (width > ONE_COLUMN_BREAKPOINT) { + visibleColumns = Math.min(colCount, 2); + } + return visibleColumns; + } + + document.addEventListener('DOMContentLoaded', function () { + + var MAX_WIDTH_30_DAYS = 600, + MAX_WIDTH_60_DAYS = 1024, + svgs = document.getElementsByClassName('availability-time-line-graphic'), + rects = svgs[0].getElementsByTagName('rect'), + rectWidth = parseInt(rects[0].getAttribute('width')), + rectPadding = parseInt(rects[1].getAttribute('x')) - parseInt(rects[0].getAttribute('x')) - rectWidth, + throttled = false, + delay = 150, + timeoutId, + prevCols, + colCount = 1; + + function getKeyAndCount(width) { + var visibleColumns = getVisibleColumns(width, colCount); + if (width <= MAX_WIDTH_30_DAYS || visibleColumns > 1) { + return { dayCount: 30, uptimeKey: 'thirty', visibleColumns: visibleColumns } + } else if (width <= MAX_WIDTH_60_DAYS) { + return { dayCount: 60, uptimeKey: 'sixty', visibleColumns: visibleColumns } + } else { + return { dayCount: 90, uptimeKey: 'ninety', visibleColumns: visibleColumns } + } + } + + function setUptimeValue(values, uptimeKey, shouldShorten) { + var queryID = '.legend-item-' + values.component; + var currentUptime = document.querySelector(queryID); + if (currentUptime) { + // Faster than setting innerHTML to "" then adding nodes + var clone = currentUptime.cloneNode(false); + var uptimeSpan = document.createElement('span'); + uptimeSpan.id = 'uptime-percent-' + values.component + uptimeSpan.innerText = values[uptimeKey] + clone.appendChild(uptimeSpan); + var appendText = document.createTextNode(shouldShorten ? ' %' : ' % uptime'); + clone.appendChild(appendText); + currentUptime.parentNode.replaceChild(clone, currentUptime); + } + } + + function setDayCount(el, dayCount, shouldShorten) { + // Faster than setting innerHTML to "" then adding nodes + var clone = el.cloneNode(false); + var dateSpan = document.createElement('span') + dateSpan.className = "availability-time-line-legend-day-count" + dateSpan.innerText= dayCount; + clone.appendChild(dateSpan); + var appendText = document.createTextNode(shouldShorten ? ' days' : ' days ago'); + clone.appendChild(appendText); + el.parentNode.replaceChild(clone, el); + } + + function resizeSvgViewBoxes () { + var width = window.innerWidth; + var columnInfo = getKeyAndCount(width); + var dayCount = columnInfo.dayCount, + uptimeKey = columnInfo.uptimeKey; + var newViewboxValue = calculateViewbox(dayCount, rectWidth, rectPadding); + + // If a user quickly resizes from < 450 to > 900 without stopping, + // it will retain the same 30 day info as it wont have changed, but this only + // impacts 30 day display as it is the only one with shortened text + if (newViewboxValue !== svgs[0].getAttribute('viewBox') || prevCols !== columnInfo.visibleColumns) { + prevCols = columnInfo.visibleColumns + for (var i = 0; i < svgs.length; i++) { + var el = svgs[i]; + if (el.getAttribute('viewBox') !== newViewboxValue) { + el.setAttribute('viewBox', newViewboxValue); + } + } + var shouldShorten = columnInfo.visibleColumns === 3; + + var dayCountElements = document.querySelectorAll('.legend-item-date-range:first-of-type'); + + for (var i = 0; i < dayCountElements.length; i++) { + setDayCount(dayCountElements[i], dayCount, shouldShorten); + } + + uptimeValues = [{"component":"8l4ygp009s5s","ninety":99.97,"sixty":99.96,"thirty":99.93},{"component":"brv1bkgrwx7q","ninety":99.97,"sixty":99.95,"thirty":99.91},{"component":"4230lsnqdsld","ninety":99.96,"sixty":99.94,"thirty":99.89},{"component":"kr09ddfgbfsf","ninety":99.97,"sixty":99.95,"thirty":99.91},{"component":"br0l2tvcx85d","ninety":99.89,"sixty":99.84,"thirty":99.91},{"component":"st3j38cctv9l","ninety":100.0,"sixty":100.0,"thirty":100.0},{"component":"vg70hn9s2tyj","ninety":99.97,"sixty":99.96,"thirty":99.92}]; + + for (var i = 0; i < uptimeValues.length; i++) { + setUptimeValue(uptimeValues[i], uptimeKey, shouldShorten) + } + + const uptimeLinkVar = document.querySelector('.components-uptime-link > var') + if (uptimeLinkVar) { + uptimeLinkVar.innerHTML = dayCount; + } + } + } + + window.addEventListener('resize', function () { + clearTimeout(timeoutId); + timeoutId = setTimeout(function () { + resizeSvgViewBoxes(); + }, delay); + }); + + resizeSvgViewBoxes(); + }); +</script> + + <div id="uptime-tooltip"> + <div class="pointer-container"> + <div class="pointer-larger"></div> + <div class="pointer-smaller"></div> + </div> + <div class="tooltip-box"> + <div class="tooltip-content"> + <div class="tooltip-close"> + <i class="fa fa-times"></i> + </div> + <div class="date"></div> + <div class="outages"> + <div class="outage-field major"> + <span class="label"> + <i class="component-status page-colors text-color major_outage"></i> + Major outage + </span> + <span class="value-hrs"></span> + <span class="value-mins"></span> + </div> + <div class="outage-field partial"> + <span class="label"> + <i class="component-status page-colors text-color partial_outage"></i> + Partial outage + </span> + <span class="value-hrs"></span> + <span class="value-mins"></span> + </div> + <div class="no-outages-msg"> + No downtime recorded on this day. + </div> + <div id="major-outage-group-count" class="outage-count"> + <i class="component-status page-colors text-color major_outage"></i> + <span class="count"></span> + had a major outage + </div> + <div id="partial-outage-group-count" class="outage-count"> + <i class="component-status page-colors text-color partial_outage"></i> + <span class="count"></span> + had a partial outage + </div> + </div> + <div class="related-events"> + <h3 id="related-event-header">Related</h3> + <ul id="related-events-list"></ul> + </div> + <div class="no-related-msg"> + <p>No incidents or maintenance related to this downtime.</p> + </div> + </div> + </div> +</div> + +<script src="https://dka575ofm4ao0.cloudfront.net/assets/vendor/bowser-cba5cf944efc2e8d45d5d2a40ed2d6839ecb5ed1a614d19f00e454cd5e8883f4.js"></script> +<script type="text/javascript"> + /** + This file contains the code needed to handle display of the uptime tooltips on status. 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Convert to just number + function dayNumberFromClass(className) { + return parseInt(className.split('-')[1]); + } + + // Class is in format component-<code>. Convert to just code + function componentCodeFromClass(className) { + return className.split('-')[1]; + } + + // Convert number to string pixel measurement + function intToPixels(number) { + return number.toString() + 'px'; + } + + function truncate(str) { + return str.substring(0, EVENT_MAX_LENGTH) + + (str.length > EVENT_MAX_LENGTH ? '...' : ''); + } + + // Tooltip Handling class constructor + function UptimeTooltipHandler(frameWidth) { + this.visible = false; + this.activeDay = { + hovered: false + }; + this.tooltip = document.getElementById('uptime-tooltip'); + this.frameWidth = frameWidth === undefined ? window.innerWidth : frameWidth; + this.scrolling = false; + + window.addEventListener('mousemove', this.tooltipListener.bind(this)); + window.addEventListener('orientationchange', this.orientationListener.bind(this)); + + // on tooltip creation, determine whether to display touch-specific controls + var tooltipCloseButton = document.querySelector('.tooltip-close'); + + if (touchDevice()) { + var componentsContainer = document.querySelector('.components-container'); + componentsContainer.addEventListener('touchstart', this.handleTouch.bind(this)); + + tooltipCloseButton.addEventListener('touchstart', this.unhoverTooltip.bind(this)); + } else { + window.addEventListener('resize', this.resizeListener.bind(this)); + // classList not supported by IE < 9 + tooltipCloseButton.className += ' hidden'; + } + + // Handle toggle of group elements + var groupComponents = document.querySelectorAll('[data-js-hook=component-group-opener]'); + for (var i = 0; i < groupComponents.length; i++) { + groupComponents[i].addEventListener('click', this.hideTooltip.bind(this)); + } + + var tooltipBox = document.querySelector('#uptime-tooltip .tooltip-box'); + tooltipBox.addEventListener('mouseenter', this.mouseEnteredTooltip.bind(this)); + tooltipBox.addEventListener('mouseleave', this.unhoverTooltip.bind(this)); + } + + UptimeTooltipHandler.prototype.tooltipListener = function(event) { + if (!this.tooltipHovered) { + this.updateHoveredDay(event); + this.updateTooltip(event); + } + } + + // this handler will accommodate for mobile orientation change + UptimeTooltipHandler.prototype.orientationListener = function(event) { + // just close the tooltip + this.unhoverTooltip(); + } + + UptimeTooltipHandler.prototype.resizeListener = function(event) { + this.frameWidth = window.innerWidth; + } + + UptimeTooltipHandler.prototype.handleTouch = function (event) { + if (event.target.classList.contains('uptime-day')) { + event.stopPropagation(); + this.bladeTouched(event); + } + } + + UptimeTooltipHandler.prototype.mouseEnteredTooltip = function() { + // Necessary to clear the timeout set for closing the tooltip when the mouse + // moves off the blade or timeline, so the tooltip isnt closed on hover + clearTimeout(timeoutId); + // Sets it to null so the timeout can be set later, as clearTimeout only + // cancels the timer, and we need to allow it to be reset in the mouse + // move handler below + timeoutId = null; + this.tooltipHovered = true; + } + + UptimeTooltipHandler.prototype.unhoverTooltip = function() { + this.tooltipHovered = false; + this.activeDay.hovered = false; + this.hideTooltip(); + } + + UptimeTooltipHandler.prototype.bladeTouched = function (event) { + event.preventDefault(); + var classes = event.target.getAttribute('class').split(' '); + var componentCode = componentCodeFromClass(classes[1]) + var index = dayNumberFromClass(classes[2]); + + // If open and tapped on same component and day, close tooltip + if (this.visible && this.activeDay.component === componentCode && this.activeDay.index === index) { + this.hideTooltip(); + } else { + this.updateHoveredDay(event); + this.updateTooltip(event); + } + } + + UptimeTooltipHandler.prototype.updateHoveredDay = function(event) { + var classes = event.target.getAttribute('class'); // classList doesn't work in IE + var onDay = classes != null && classes.split(' ').indexOf('uptime-day') !== -1; + + if (onDay) { + classes = classes.split(' '); + + var componentCode = componentCodeFromClass(classes[1]); + + this.activeDay = { + index: dayNumberFromClass(classes[2]), + component: componentCode, + bounds: event.target.getBoundingClientRect(), + isGroup: uptimeData[componentCode].component.isGroup, + hovered: true + } + } else { + this.activeDay.hovered = false; + } + } + + UptimeTooltipHandler.prototype.updateTooltip = function(event) { + var classes = event.target.getAttribute('class'); // classList doesn't work in IE + var hoveredOnGraphic = classes != null && classes.split(' ').indexOf('availability-time-line-graphic') !== -1; + + if (this.activeDay.hovered) { + this.updateTooltipData(); + this.positionTooltip(); + } else if (this.visible && !this.activeDay.hovered && !hoveredOnGraphic) { + // Important: since this is on mouse move it will be called multiple times + // which will clear timeoutId and reset it to the new value, meaning + // it is a race condition to cancel it + if (!timeoutId) { + var _this = this; + timeoutId = setTimeout(function() { + _this.hideTooltip(); + timeoutId = null; + }, 250); + } + } + } + + UptimeTooltipHandler.prototype.updateTooltipData = function() { + // Get the data for the day we're hovered on + var day = uptimeData[this.activeDay.component].days[this.activeDay.index]; + + // Update the date for the tooltip + var date = new Date(day.date); + + // UTC necessary since days are passed yyyy-mm-dd, and new Date uses midnight UTC, so local times + // are presented as the day before + var dateString = date.getUTCDate() + " " + monthStrings[date.getUTCMonth()] + " " + date.getUTCFullYear(); + document.querySelector('#uptime-tooltip .date').innerHTML = dateString; + + // Update the outage fields + if (this.activeDay.isGroup) { + this.updateGroupOutageFields() + } else { + this.updateOutageFields(day.outages.p, day.outages.m, day.related_events); + } + } + + UptimeTooltipHandler.prototype.hoursFromSeconds = function(s) { + return Math.floor(s / 3600); + } + + UptimeTooltipHandler.prototype.minutesFromSeconds = function(s) { + // If less than a minute, round up to 1 minute to show that some outage existed + if (s > 0 && s < 60) { + return 1; + } + + // Otherwise use floor + return Math.floor((s % 3600) / 60); + } + + UptimeTooltipHandler.prototype.updateGroupOutageFields = function() { + // Hide time info + document.querySelector('#uptime-tooltip .outage-field.major').style.display = 'none'; + document.querySelector('#uptime-tooltip .outage-field.partial').style.display = 'none'; + document.querySelector(".related-events h3").style.display = 'none'; + document.querySelector('.no-related-msg').style.display = 'none'; + + var eventList = document.getElementById("related-events-list") + var cloneList = eventList.cloneNode(false); + eventList.parentNode.replaceChild(cloneList, eventList); + + var partialCount = 0; + var majorCount = 0; + + var components = uptimeData[this.activeDay.component].component.group + + for (var i = 0; i < components.length; i++) { + if (!uptimeData[components[i]]) continue; + + var outages = uptimeData[components[i]].days[this.activeDay.index].outages; + + if (outages.p) { + partialCount += 1; + } + + if (outages.m) { + majorCount += 1; + } + } + + document.querySelector('#major-outage-group-count').style.display = majorCount ? 'block' : 'none'; + document.querySelector('#partial-outage-group-count').style.display = partialCount ? 'block' : 'none'; + + document.querySelector('#major-outage-group-count .count').innerText = majorCount + (majorCount == 1 ? " component" : " components") + document.querySelector('#partial-outage-group-count .count').innerText = partialCount + (partialCount == 1 ? " component" : " components ") + + document.querySelector('#uptime-tooltip .no-outages-msg').style.display = (majorCount || partialCount) ? 'none' : 'block'; + } + + UptimeTooltipHandler.prototype.updateOutageFields = function(partial, major, relatedEvents) { + // Hide group info + document.querySelector('#major-outage-group-count').style.display = 'none'; + document.querySelector('#partial-outage-group-count').style.display = 'none'; + + // Show the message that no outage present, if none is present + if (partial || major) { + document.querySelector('#uptime-tooltip .no-outages-msg').style.display = 'none'; + } else { + document.querySelector('#uptime-tooltip .no-outages-msg').style.display = 'block'; + } + + // Update partial outage field if an outage exists, otherwise hide it + if (partial) { + var hrs = this.hoursFromSeconds(partial); + var mins = this.minutesFromSeconds(partial); + document.querySelector('#uptime-tooltip .outage-field.partial .value-hrs').innerHTML = hrs.toString() + ' hrs'; + document.querySelector('#uptime-tooltip .outage-field.partial .value-mins').innerHTML = mins.toString() + ' mins'; + document.querySelector('#uptime-tooltip .outage-field.partial').style.display = 'flex'; + } else { + document.querySelector('#uptime-tooltip .outage-field.partial').style.display = 'none'; + } + + // Update major outage field if an outage exists, otherwise hide it + if (major) { + var hrs = this.hoursFromSeconds(major); + var mins = this.minutesFromSeconds(major); + document.querySelector('#uptime-tooltip .outage-field.major .value-hrs').innerHTML = hrs.toString() + ' hrs'; + document.querySelector('#uptime-tooltip .outage-field.major .value-mins').innerHTML = mins.toString() + ' mins'; + document.querySelector('#uptime-tooltip .outage-field.major').style.display = 'flex'; + } else { + document.querySelector('#uptime-tooltip .outage-field.major').style.display = 'none'; + } + + var eventList = document.getElementById("related-events-list") + var cloneList = eventList.cloneNode(false); + document.querySelector(".related-events h3").style.display = (relatedEvents.length ? 'block' : 'none'); + + for (var i = 0; i < relatedEvents.length; i++) { + var listItem = document.createElement("li"); + listItem.className = "related-event"; + var anchor = document.createElement("a"); + anchor.className = "related-event-link"; + anchor.target = "_blank"; + anchor.href = window.Routes.incident_path(relatedEvents[i].code); + + + var text = document.createTextNode(truncate(relatedEvents[i].name)); + anchor.appendChild(text); + listItem.appendChild(anchor); + cloneList.appendChild(listItem); + } + + const displayNoRelatedMsg = ((major || partial) && !relatedEvents.length); + document.querySelector('.no-related-msg').style.display = (displayNoRelatedMsg ? 'block' : 'none'); + + eventList.parentNode.replaceChild(cloneList, eventList); + } + + UptimeTooltipHandler.prototype.positionTooltip = function() { + this.calculatePointerCenter(); + this.calculateBoxPosition(); + + // show tooltip + this.tooltip.style.display = 'block'; + + // position pointer + var pointer = this.tooltip.getElementsByClassName('pointer-container')[0]; + pointer.style.left = intToPixels(this.pointerCenter.x - 8); + pointer.style.top = intToPixels(this.pointerCenter.y - 5); + + // position display box + var box = this.tooltip.getElementsByClassName('tooltip-box')[0]; + box.style.left = intToPixels(this.boxLeft); + box.style.top = intToPixels(this.pointerCenter.y + 5); + + this.visible = true; + } + + UptimeTooltipHandler.prototype.calculatePointerCenter = function() { + var bounds = this.activeDay.bounds; + var rectLeft = bounds.left + window.pageXOffset; + var rectBottom = bounds.bottom + window.pageYOffset; + var rectWidth = bounds.right - bounds.left; + + this.pointerCenter = { + x: rectLeft + Math.floor(rectWidth / 2), + y: rectBottom + 5 + } + } + + UptimeTooltipHandler.prototype.calculateBoxPosition = function() { + var sideWidth = 162.5; + if (this.pointerCenter.x - sideWidth < 0) { + this.boxLeft = 0; + } else if (this.pointerCenter.x + sideWidth > this.frameWidth) { + this.boxLeft = this.frameWidth - sideWidth * 2; + } else { + this.boxLeft = this.pointerCenter.x - sideWidth; + } + } + + UptimeTooltipHandler.prototype.hideTooltip = function() { + this.tooltip.style.display = 'none'; + this.visible = false; + } + + new UptimeTooltipHandler(); + +</script> + + + + + + + + <div class="incidents-list format-expanded"> + <a class="font-largest no-link" id="past-incidents" href="#past-incidents">Past Incidents</a> + + <div class="status-day font-regular no-incidents"> + <div class="date border-color font-large">Dec <var data-var="date">31</var>, <var data-var="year">2019</var></div> + <p class="color-secondary">No incidents reported today.</p> + </div> + + + <div class="status-day font-regular no-incidents"> + <div class="date border-color font-large">Dec <var data-var="date">30</var>, <var data-var="year">2019</var></div> + <p class="color-secondary">No incidents reported.</p> + </div> + + + <div class="status-day font-regular no-incidents"> + <div class="date border-color font-large">Dec <var data-var="date">29</var>, <var data-var="year">2019</var></div> + <p class="color-secondary">No incidents reported.</p> + </div> + + + <div class="status-day font-regular no-incidents"> + <div class="date border-color font-large">Dec <var data-var="date">28</var>, <var data-var="year">2019</var></div> + <p class="color-secondary">No incidents reported.</p> + </div> + + + <div class="status-day font-regular no-incidents"> + <div class="date border-color font-large">Dec <var data-var="date">27</var>, <var data-var="year">2019</var></div> + <p class="color-secondary">No incidents reported.</p> + </div> + + + <div class="status-day font-regular no-incidents"> + <div class="date border-color font-large">Dec <var data-var="date">26</var>, <var data-var="year">2019</var></div> + <p class="color-secondary">No incidents reported.</p> + </div> + + + <div class="status-day font-regular no-incidents"> + <div class="date border-color font-large">Dec <var data-var="date">25</var>, <var data-var="year">2019</var></div> + <p class="color-secondary">No incidents reported.</p> + </div> + + + <div class="status-day font-regular no-incidents"> + <div class="date border-color font-large">Dec <var data-var="date">24</var>, <var data-var="year">2019</var></div> + <p class="color-secondary">No incidents reported.</p> + </div> + + + <div class="status-day font-regular no-incidents"> + <div class="date border-color font-large">Dec <var data-var="date">23</var>, <var data-var="year">2019</var></div> + <p class="color-secondary">No incidents reported.</p> + </div> + + + <div class="status-day font-regular no-incidents"> + <div class="date border-color font-large">Dec <var data-var="date">22</var>, <var data-var="year">2019</var></div> + <p class="color-secondary">No incidents reported.</p> + </div> + + + <div class="status-day font-regular no-incidents"> + <div class="date border-color font-large">Dec <var data-var="date">21</var>, <var data-var="year">2019</var></div> + <p class="color-secondary">No incidents reported.</p> + </div> + + + <div class="status-day font-regular no-incidents"> + <div class="date border-color font-large">Dec <var data-var="date">20</var>, <var data-var="year">2019</var></div> + <p class="color-secondary">No incidents reported.</p> + </div> + + + <div class="status-day font-regular "> + <div class="date border-color font-large">Dec <var data-var="date">19</var>, <var data-var="year">2019</var></div> + <div class="incident-container"> + <div class="incident-title impact-minor font-large"> + <a href="/incidents/krfmmxs3wdry">Incident on 2019-12-19 22:49 UTC</a> + </div> + + <div class="updates-container"> + <!-- postmortem --> + + <!-- incident updates --> + <div class="update font-regular resolved"> + <strong>Resolved</strong> - + This incident has been resolved. + + <br> + + <small> + Dec <var data-var='date'>19</var>, <var data-var='time'>23:12</var> UTC + </small> + </div> + <div class="update font-regular investigating"> + <strong>Investigating</strong> - + Delays in Webhooks and Notifications are currently being investigated. + + <br> + + <small> + Dec <var data-var='date'>19</var>, <var data-var='time'>22:49</var> UTC + </small> + </div> + </div> + +</div> + + </div> + + + <div class="status-day font-regular no-incidents"> + <div class="date border-color font-large">Dec <var data-var="date">18</var>, <var data-var="year">2019</var></div> + <p class="color-secondary">No incidents reported.</p> + </div> + + + <div class="status-day font-regular no-incidents"> + <div class="date border-color font-large">Dec <var data-var="date">17</var>, <var data-var="year">2019</var></div> + <p class="color-secondary">No incidents reported.</p> + </div> + + </div> + + + <div class="page-footer border-color font-small"> + <a href="/history" class="history-footer-link"><span style="font-family:arial">←</span> Incident History</a> + + <span class="color-secondary powered-by"><a class="color-secondary" target="_blank" rel="noopener noreferrer nofollow" href="https://www.statuspage.io/powered-by?utm_campaign=www.githubstatus.com&utm_content=status-pages&utm_medium=powered-by&utm_source=inapp">Powered by Statuspage</a></span> + </div> + </div> + + <div class="custom-footer-container"> + <div class="footer mt-6 border-top" role="contentinfo">
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+ </g>
+ </svg>
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+ <a href="https://github.com/github" data-ga-click="Footer, go to github's org, text:github" style="color: #959da5;"><svg height="20" class="octicon octicon-mark-github d-block" alt="GitHub" viewBox="0 0 16 16" version="1.1" width="20" aria-hidden="true"><path fill-rule="evenodd" d="M8 0C3.58 0 0 3.58 0 8c0 3.54 2.29 6.53 5.47 7.59.4.07.55-.17.55-.38 0-.19-.01-.82-.01-1.49-2.01.37-2.53-.49-2.69-.94-.09-.23-.48-.94-.82-1.13-.28-.15-.68-.52-.01-.53.63-.01 1.08.58 1.23.82.72 1.21 1.87.87 2.33.66.07-.52.28-.87.51-1.07-1.78-.2-3.64-.89-3.64-3.95 0-.87.31-1.59.82-2.15-.08-.2-.36-1.02.08-2.12 0 0 .67-.21 2.2.82.64-.18 1.32-.27 2-.27.68 0 1.36.09 2 .27 1.53-1.04 2.2-.82 2.2-.82.44 1.1.16 1.92.08 2.12.51.56.82 1.27.82 2.15 0 3.07-1.87 3.75-3.65 3.95.29.25.54.73.54 1.48 0 1.07-.01 1.93-.01 2.2 0 .21.15.46.55.38A8.013 8.013 0 0 0 16 8c0-4.42-3.58-8-8-8z"></path></svg></a>
+ </li>
+ </ul>
+ <ul class="list-style-none d-flex text-gray">
+ <li class="mr-3">© 2018 GitHub, Inc.</li>
+ <li class="mr-3"><a href="https://help.github.com/articles/github-terms-of-service/" data-ga-click="Footer, go to terms, text:terms" class="link-gray">Terms</a></li>
+ <li><a href="https://help.github.com/articles/github-privacy-statement/" data-ga-click="Footer, go to privacy, text:privacy" class="link-gray">Privacy</a></li>
+ </ul>
+ </div>
+</div>
+
+<script>
+ $(document).ready(function() {
+ if ($('body').hasClass('status-none')) {
+ $('link[rel="shortcut icon"]').attr("href","https://assets-cdn.github.com/favicon-success.ico");
+ } else {
+ $('link[rel="shortcut icon"]').attr("href","https://assets-cdn.github.com/favicon-pending.ico");
+ }
+ $('span.name:contains("Visit www.githubstatus.com for more information")').parents('div.component-container').hide()
+ $('div.status-green span.component-status').html("Normal")
+ $('div.status-yellow span.component-status').html("Degraded")
+ $('div.status-orange span.component-status').html("Degraded")
+ $('div.status-red span.component-status').html("Incident")
+ $('.outage-field .label .major_outage').parent().html("Degradation")
+
+ var otherParent = $('span.name:contains("Other")').parent()
+ if (otherParent.hasClass('status-green')) {
+ otherParent.parent().hide()
+ }
+ $('.page-status.status-major span.status, .page-status.status-minor span.status').html('Some services are degraded')
+ $('.outage-field .label .partial_outage').parent().html("Degradation")
+ });
+</script> + </div> + + + </div> + + + + + + + + <script src="https://dka575ofm4ao0.cloudfront.net/assets/status_manifest-64c6bc5e1de0835a1c74f402d62e5e4375852ac6274781da0d08eb5c551894d4.js"></script> + <div id="cpt-notification-container"></div> + + + + + + <!-- analytics web client scripts --> + <script> + if (typeof window.awc === 'undefined' || window.awc === null) { + window.awc = new Promise(function(resolve, reject) { + window.awc_resolve = resolve; + }); + } + if (typeof window.analyticsClient === 'undefined' || window.analyticsClient === null) { + window.analyticsClient = new Promise(function(resolve, reject) { + window.analyticsClient_resolve = resolve; + }); + } + awc.then(function(awc) { + var analyticsClient = new awc.default({ + env: awc.envType.PROD, + product: 'statuspage', + version: '8faf6e83cfec3dc827a775e9f1750e38522e2734', + origin: awc.originType.WEB, + }); + + var tenantOrgId = '30gcnw2xxnb0:kctbh9vrtdwd'; + analyticsClient.setTenantInfo(awc.tenantType.ORG_ID, tenantOrgId); + + window.analyticsClient_resolve(analyticsClient); + }); + </script> + + <script> + var eventPayload = {"name":"statusPageScreen","attributes":{"pageIsPrivate":false,"overAllocationsCohort":null,"pageId":"kctbh9vrtdwd","pageType":"public","componentSubscriptionEnabled":false,"pricingPlan":"public-business","subscriptionType":"paid","orgId":"30gcnw2xxnb0","isAaID":false}} + var expectedParams = new Set(); // initializing with iterable not supported in IE11 + expectedParams.add('utm_source').add('utm_campaign').add('utm_medium'); + + location.search.substring(1).split('&').forEach(function(param) { + var arr = param.split('='); + if (arr.length < 2) return; + + var k = arr[0], v = arr[1] + if (expectedParams.has(k)) eventPayload.attributes[k] = v; + }); + + analyticsClient.then(function(analyticsClient) { + analyticsClient.sendScreenEvent(eventPayload) + }) + + if (location.search.indexOf('subscription_confirmed=true') !== -1) { + analyticsClient.then(function(analyticsClient) { analyticsClient.sendScreenEvent({"name":"emailConfirmedBanner","attributes":{"pageIsPrivate":false,"overAllocationsCohort":null,"pageId":"kctbh9vrtdwd","pageType":"public","componentSubscriptionEnabled":false,"pricingPlan":"public-business","subscriptionType":"paid","orgId":"30gcnw2xxnb0","isAaID":false}}); }); + } + </script> + + + <!-- all of the content_for stuff --> + <script src="https://dka575ofm4ao0.cloudfront.net/assets/register_subscription_form-bd6e5b6a473100206b3a7b46580a2bc24972d3c03a6db69641448a1a37fc661c.js"></script> + + <script type="text/javascript"> + $(function() { + SP.currentPage.registerSubscriptionForm('email'); + + SP.currentPage.registerSubscriptionForm('sms'); + + SP.currentPage.registerSubscriptionForm('webhook'); + }); + + + + + + </script> + <script src="https://dka575ofm4ao0.cloudfront.net/assets/status_common-f8b35586d7e6820c2761e822c9860a9ad5f3706467a0f2ea792990ed76958f20.js"></script> + <script> + SP.pollForChanges('/api/v2/status.json'); + </script> + + <script> + $(function() { + $('.tool').tooltipster({ + animationDuration: 100, + contentAsHTML: true, + delay: 100, + theme: 'tooltipster-borderless', + functionInit: function (instance, helper) { + var $origin = $(helper.origin), + dataOptions = $origin.attr('data-tooltip-config'); + if (dataOptions){ + dataOptions = JSON.parse(dataOptions); + $.each(dataOptions, function(name, option){ + instance.option(name, option); + }); + } + } + }); + // clicks on first tab in subscribe popout since we won't know which is first + // upon construction in the ruby code + $('.updates-dropdown-nav > a').eq(0).click(); + + // twitter follow button needs some margin + $('.twitter-follow-button').css('margin-right', '6px'); + }); + + $(function() { + // open/close component groups + HRB.utils.djshook('component-group-opener').on('click', function() { + $(this).find('.group-parent-indicator').toggleClass('fa-plus-square-o').toggleClass('fa-minus-square-o').end().parent().toggleClass('open'); + }); + }); + + $(function() { + $(document).on('ajax:complete', '.modal.in', function(e) { + // Close the active modal. + $('.modal.in').modal('hide'); + }); + }); + + </script> + + + <script> + /** INITIALIZATION **/ + var recaptchaIds = {} + + // Unfortunately there's no unique selectors on the parent divs that recaptcha adds. The first unique selector + // is the iframe rendered 2 levels deep. So this waits until the iframes are added to the page, then finds + // the parent div and sets the z index so that it'll render above our modals & dropdowns from the start. + function setZIndex(captchaCount, startTime) { + // bail after 10s just in case so we don't do this forever if something whaky happens + if (new Date() - startTime > 10000) { + return; + } + + var iframes = document.querySelectorAll('iframe[title="recaptcha challenge"]'); + if (iframes.length != captchaCount) { + setTimeout(function() { + setZIndex(captchaCount, startTime); + }, 500); + } + + for (var i = 0; i < iframes.length; i++) { + // incident subscribe modal is 1050, so this has to be above that + iframes[i].parentElement.parentElement.style.zIndex = "1100"; + } + } + + var onloadCallback = function() { + var captchas = document.getElementsByClassName("g-recaptcha"); + for(var i = 0; i < captchas.length; i++) { + var elId = captchas[i].id; + recaptchaIds[elId] = grecaptcha.render(elId); + } + + setZIndex(captchas.length, new Date()); + } + + + /** SUBSCRIBE DROPDOWN */ + + // callbacks for captcha success + function submitNewSubscriber(type, error) { + if (error) document.querySelector('#subscribe-form-' + type + ' #captcha_error').value = 'true'; + + document.getElementById('subscribe-form-' + type).dispatchEvent(new Event('submit', {bubbles: true, cancelable: true})); + grecaptcha.reset(recaptchaIds['subscribe-btn-' + type]); + } + function submitNewEmailSubscriber(token) { + submitNewSubscriber('email'); + } + function submitNewSmsSubscriber(token) { + submitNewSubscriber('sms'); + } + function submitNewWebhookSubscriber(token) { + submitNewSubscriber('webhook'); + } + + // callbacks if we get captcha network errors + function emailSubscriberCaptchaError(token) { + submitNewSubscriber('email', true); + } + function smsSubscriberCaptchaError(token) { + submitNewSubscriber('sms', true); + } + function webhookSubscriberCaptchaError(token) { + submitNewSubscriber('webhook', true); + } + + // tracking clicks + ['email', 'sms', 'webhook'].forEach(function(type) { + var el = document.getElementById('subscribe-btn-' + type); + el && el.addEventListener("click", function() { + $.ajax({ + type: "POST", + url: "/subscriptions/track_attempt", + data: { + type: type + } + }) + }) + }) + + // form submission success callbacks + $('#subscribe-form-email').on('ajax:success', function(e, data, status, xhr){ + if (data.type === 'success') { + SP.currentPage.updatesDropdown.hide(); + document.getElementById('email').value = ''; + } + }); + $('#subscribe-form-sms').on('ajax:success', function(e, data, status, xhr){ + if (data.type === 'success') { + SP.currentPage.updatesDropdown.hide(); + document.getElementById('phone-number').value = ''; + } + }); + $('#subscribe-form-webhook').on('ajax:success', function(e, data, status, xhr){ + if (data.type === 'success') { + SP.currentPage.updatesDropdown.hide(); + document.getElementById('endpoint-webhooks').value = ''; + document.getElementById('email-webhooks').value = ''; + } + }); + + /** INCIDENT SUBSCRIBE MODALS */ + var modals = document.getElementsByClassName('modal-open-incident-subscribe'); + + // for each modal on the page, we need to add the appropriate callback functions + for(var i = 0; i < modals.length; i++) { + var modal = modals[i]; + var incidentCode = modal.id.split('-')[2]; + + // need these functions to capture the incident code at a specific point in time + function createSubmitFn(incidentCode) { + return function() { + document.getElementById("subscribe-form-" + incidentCode).dispatchEvent(new Event('submit', {bubbles: true, cancelable: true})); + grecaptcha.reset(recaptchaIds["subscribe-btn-" + incidentCode]); + } + } + function createErrorFn(incidentCode) { + return function() { + document.querySelector("#subscribe-form-" + incidentCode + " #captcha_error").value = 'true'; + submitSubForIncident(incidentCode); + } + } + + // create the callback functions and attach them to the window + window["submitSubForIncident" + incidentCode] = createSubmitFn(incidentCode); + window["captchaErrorForIncident" + incidentCode] = createErrorFn(incidentCode); + + // track entrances to the flow + var el = document.getElementById("subscribe-btn-" + incidentCode); + el && el.addEventListener("click", function() { + $.ajax({ + type: "POST", + url: "/subscriptions/track_attempt", + data: { + type: 'incident' + } + }) + }) + } +</script> + +<script src='https://www.google.com/recaptcha/api.js?onload=onloadCallback&render=explicit' async defer></script> + + + + <script src="https://dka575ofm4ao0.cloudfront.net/packs/common-5a02b87391d28401f7a6.chunk.js"></script> + <script src="https://dka575ofm4ao0.cloudfront.net/packs/globals-b223b2cfea95f3cc8185.chunk.js"></script> + + <script src="https://dka575ofm4ao0.cloudfront.net/packs/runtime-40e9e825aee610a66b8b.js"></script> + + + + + +<!-- FOR FLASH NOTICES --> + +<!-- FOR ERROR --> + + + <script> + $(function() { + var $link = $('<span class="color-secondary powered-by"><a class="color-secondary" target="_blank" rel="noopener noreferrer nofollow" href="https://www.statuspage.io/powered-by?utm_campaign=www.githubstatus.com&utm_content=status-pages&utm_medium=powered-by&utm_source=inapp">Powered by Statuspage</a></span>'); + + var setPoweredByStyles = function() { + if (!$('.powered-by').length) { + $link.appendTo($('.page-footer')) + } + $('.powered-by').attr('style', 'display: inline !important; visibility:visible !important; opacity: 1 !important; position:static !important; text-indent:0px !important; transform:scale(1) !important'); + } + + setInterval(setPoweredByStyles, 1000); + }); +</script> + + + + + + </body> +</html> diff --git a/datasets/Talluri2021/github_failures_2019-20/_common_metadata b/datasets/Talluri2021/github_failures_2019-20/_common_metadata Binary files differnew file mode 100644 index 0000000..75756ba --- /dev/null +++ b/datasets/Talluri2021/github_failures_2019-20/_common_metadata diff --git a/datasets/Talluri2021/github_failures_2019-20/_metadata b/datasets/Talluri2021/github_failures_2019-20/_metadata Binary files differnew file mode 100644 index 0000000..4950f58 --- /dev/null +++ b/datasets/Talluri2021/github_failures_2019-20/_metadata diff --git a/datasets/Talluri2021/github_failures_2019-20/part.0.parquet b/datasets/Talluri2021/github_failures_2019-20/part.0.parquet Binary files differnew file mode 100644 index 0000000..9b56db4 --- /dev/null +++ b/datasets/Talluri2021/github_failures_2019-20/part.0.parquet diff --git a/datasets/Talluri2021/github_parser.ipynb b/datasets/Talluri2021/github_parser.ipynb new file mode 100644 index 0000000..ef4ba79 --- /dev/null +++ b/datasets/Talluri2021/github_parser.ipynb @@ -0,0 +1,726 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "from bs4 import BeautifulSoup\n", + "import bs4\n", + "from dateutil.parser import parse as parse_date\n", + "import numpy as np\n", + "from datetime import datetime\n", + "import re\n", + "import json" + ] + }, + { + "cell_type": "code", + "execution_count": 114, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "datetime.datetime(2018, 12, 19, 22, 49, tzinfo=tzutc())" + ] + }, + "execution_count": 114, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pdate = parse_date(\"Incident on 2019-12-19 22:49 UTC\".split(\"on\")[1])\n", + "pdate.replace(year=2018)" + ] + }, + { + "cell_type": "code", + "execution_count": 156, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'event_start_time': 1576795740,\n", + " 'event_end_time': 1576797120,\n", + " 'status': 'minor'}]" + ] + }, + "execution_count": 156, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Parser for github status till september 2, 2020\n", + "# https://github.blog/2020-09-02-github-availability-report-august-2020/\n", + "\n", + "def get_incident_year(incident_title):\n", + " try:\n", + " current_node = incident_title.parent.previous_sibling\n", + " while type(current_node) != bs4.element.Tag or current_node.find(attrs={'data-var':'year'}) == None:\n", + " current_node = current_node.previous_sibling\n", + " return int(current_node.find(attrs={'data-var':'year'}).get_text())\n", + " except:\n", + " print(incident_title.parent.previous_sibling.previous_sibling)\n", + " raise\n", + "\n", + "def get_incident_type(incident_title):\n", + " classes = incident_title.attrs['class']\n", + " if 'impact-minor' in classes:\n", + " return 'minor'\n", + " elif 'impact-none' in classes:\n", + " return 'minor'\n", + " elif 'impact-major' in classes:\n", + " return 'major'\n", + " elif 'impact-critical' in classes:\n", + " return 'critical'\n", + " elif 'impact-maintenance' in classes:\n", + " return 'maintenance'\n", + " else:\n", + " raise Exception('Unknown impact class: ' + str(incident_title))\n", + " \n", + "def get_maintenance_incident_details(incident_update):\n", + " raise Exception('Unimplemented. Implement when we encounter one')\n", + " \n", + "def get_normal_incident_details(incident_updates, year):\n", + " try:\n", + " problem = False\n", + " investigating_divs = incident_updates.select('.investigating')\n", + " if len(investigating_divs) == 1:\n", + " incident_start_time_str = investigating_divs[0].select('small')[0].get_text().strip()\n", + " incident_start_time = parse_date(incident_start_time_str).replace(year=year).timestamp()\n", + " else:\n", + " incident_start_time = -1\n", + " problem = True\n", + "\n", + " incident_end_time_str = incident_updates.select('.resolved')[0].select('small')[0].get_text().strip()\n", + " incident_end_time = parse_date(incident_end_time_str).replace(year=year).timestamp()\n", + "\n", + " ret_data = {\n", + " 'event_start_time': np.int64(incident_start_time),\n", + " 'event_end_time': np.int64(incident_end_time)\n", + " }\n", + " \n", + " if problem:\n", + " ret_data['status'] = incident_updates.get_text()\n", + " \n", + " return ret_data\n", + " \n", + " except:\n", + " print(incident_updates)\n", + " raise\n", + "\n", + "def process_github_page(file_obj, metadata):\n", + " status_data = BeautifulSoup(file_obj.read(), 'lxml')\n", + " \n", + " incident_types = ['impact-minor', 'impact-none', 'impact-major', 'impact-critical', 'impact-maintenance']\n", + "\n", + " incidents_titles = status_data.findAll(attrs={'class': lambda x: x and 'incident-title' in x and any(incident_type in x for incident_type in incident_types)})\n", + " incidents_updates = status_data.select('.updates-container')\n", + " if len(incidents_titles) != len(incidents_updates):\n", + " raise Exception('Number of titles does not match number of updates containers: ' + metadata['date'])\n", + " \n", + " extracted_incident_info = []\n", + " for i in range(len(incidents_titles)):\n", + " incident_type = get_incident_type(incidents_titles[i])\n", + " incident_year = get_incident_year(incidents_titles[i])\n", + "\n", + " incident_details = None\n", + " if incident_type == 'maintenance':\n", + " incident_details = get_maintenance_incident_details(incidents_updates[i])\n", + " else:\n", + " incident_details = get_normal_incident_details(incidents_updates[i], incident_year)\n", + "\n", + " # Using incident field for error if required\n", + " if 'status' not in incident_details:\n", + " incident_details['status'] = incident_type\n", + "\n", + " extracted_incident_info.append(incident_details)\n", + "\n", + " return extracted_incident_info\n", + "\n", + "status_data = None\n", + "with open('github-global-status.html') as f:\n", + " status_data = process_github_page(f, {})\n", + "status_data" + ] + }, + { + "cell_type": "code", + "execution_count": 123, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'event_start_time': 1576795740,\n", + " 'event_end_time': 1576797120,\n", + " 'status': 'minor'}]" + ] + }, + "execution_count": 123, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "status_data = None\n", + "with open('github-global-status.html') as f:\n", + " status_data = process_github_page(f, {})\n", + "status_data" + ] + }, + { + "cell_type": "code", + "execution_count": 125, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['', 'github-status', '2020', '11', '20201107', 'zip']" + ] + }, + "execution_count": 125, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import re\n", + "re.compile('[./]').split(\"/github-status/2020/11/20201107.zip\")" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [], + "source": [ + "def extract_individual_reports(file_obj):\n", + " html = str(file_obj.read())\n", + " if html is None:\n", + " raise ValueError(f'ERROR: HTML IS NONE \\n filename {filename} \\t file_obj {file_obj} ')\n", + " \n", + " # Get list of reasons\n", + " matches = re.search('\"outage_subjects\":(.*?)],\"', html)\n", + " list_of_reasons = json.loads(matches.group(1) + ']')\n", + " map_of_reasons = {}\n", + " for reason in list_of_reasons:\n", + " map_of_reasons[reason['_id']] = reason['name']\n", + "\n", + " matches = re.search('\"recentReports\":(.*?)],\"_', html)\n", + " reports = []\n", + " if matches is not None:\n", + " # The data is in embedded javascript. Remove constructors to make it JSON\n", + " # We used the closing brackets in the regex and don't capture them, adding them back again\n", + " sanitized_match = re.sub(r'new Date\\(\".+?\"\\)', '\"\"', matches.group(1)) + ']'\n", + " reports = json.loads(sanitized_match)\n", + "\n", + " \n", + " report_id = []\n", + " report_country = []\n", + " report_reason = []\n", + " for datapoint in reports:\n", + " try:\n", + " report_id.append(datapoint['_id'])\n", + " \n", + " if 'country_code' in datapoint:\n", + " report_country.append(datapoint['country_code'])\n", + " elif 'countryCode' in datapoint:\n", + " report_country.append(datapoint['countryCode'])\n", + " else:\n", + " raise Exception('Country code not found')\n", + " \n", + " if 'oSubjectId' in datapoint:\n", + " report_reason.append(map_of_reasons[datapoint['oSubjectId']])\n", + " else:\n", + " reason_found = False\n", + " for name, value in datapoint.items():\n", + " if 'subject' in name or 'Subject' in name:\n", + " report_reason.append(map_of_reasons[datapoint[name]])\n", + " reason_found = True\n", + " if not reason_found:\n", + " report_reason.append('Unknown')\n", + " except:\n", + " print(datapoint)\n", + " raise\n", + "\n", + " return pd.DataFrame({\n", + " 'id': report_id,\n", + " 'country':report_country,\n", + " 'reason': report_reason\n", + " })" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>id</th>\n", + " <th>country</th>\n", + " <th>reason</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>0</th>\n", + " <td>5fc3c224dcd8580a7973cd8c</td>\n", + " <td>RU</td>\n", + " <td>Can't login</td>\n", + " </tr>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>5fc3c11dfb995a344b9b68ef</td>\n", + " <td>TR</td>\n", + " <td>Newsfeed</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2</th>\n", + " <td>5fc3bef2fb995a344b9b68ed</td>\n", + " <td>KZ</td>\n", + " <td>Mobile app crashes</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3</th>\n", + " <td>5fc3bb19ae91e3734cd1777b</td>\n", + " <td>US</td>\n", + " <td>Can't upload pics</td>\n", + " </tr>\n", + " <tr>\n", + " <th>4</th>\n", + " <td>5fc3b738dcd8580a7973cd80</td>\n", + " <td>GR</td>\n", + " <td>Website down</td>\n", + " </tr>\n", + " <tr>\n", + " <th>5</th>\n", + " <td>5fc3b66bd4d3565ae19b14b5</td>\n", + " <td>RU</td>\n", + " <td>Mobile app not working</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " id country reason\n", + "0 5fc3c224dcd8580a7973cd8c RU Can't login\n", + "1 5fc3c11dfb995a344b9b68ef TR Newsfeed\n", + "2 5fc3bef2fb995a344b9b68ed KZ Mobile app crashes\n", + "3 5fc3bb19ae91e3734cd1777b US Can't upload pics\n", + "4 5fc3b738dcd8580a7973cd80 GR Website down\n", + "5 5fc3b66bd4d3565ae19b14b5 RU Mobile app not working" + ] + }, + "execution_count": 56, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "status_data = None\n", + "with open('outage_report_instagram.html') as f:\n", + " status_data = extract_individual_reports(f)\n", + "status_data" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': '5a8cb07dee5285d43965f834', 'name': 'Website down'},\n", + " {'_id': '5a8cb06fee5285403b65f834', 'name': 'Mobile app not working'},\n", + " {'_id': '5a8cb06fee5285403b65f835', 'name': 'Mobile app crashes'},\n", + " {'_id': '5a8d3803ee52858b2065f837', 'name': 'Message read problems'},\n", + " {'_id': '5a8d3803ee52858b2065f838', 'name': 'Message send problems'},\n", + " {'_id': '5a8f0b78ee5285e04e16fca8', 'name': \"Can't login\"},\n", + " {'_id': '5a9bdbea1b4314600050c082', 'name': 'Everything is down'},\n", + " {'_id': '5a8f18e4ee5285ad7116fca7', 'name': \"Can't upload pics\"},\n", + " {'_id': '5a912a4eee5285b07a16fcad', 'name': 'Hashtags not working'},\n", + " {'_id': '5a91ab48ee5285e14216fca8', 'name': 'Newsfeed'}]" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "reports_obj" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'_id': '5fc3c224dcd8580a7973cd8c',\n", + " 'serviceId': '5458ac234488de92aa9cda3a',\n", + " 'ip': '178.67.193.121',\n", + " 'oSubjectId': '5a8f0b78ee5285e04e16fca8',\n", + " 'isAmp': True,\n", + " 'uaHash': '38c958b1452dc5eda97de8e89acdfcba',\n", + " 'langCode': 'ru',\n", + " 'latitude': 68.9792,\n", + " 'longitude': 33.0925,\n", + " 'cityGeonameId': 524305,\n", + " 'cityName': 'Murmansk',\n", + " 'divisionCode': '49',\n", + " 'divisionGeonameId': 524304,\n", + " 'countryCode': 'RU',\n", + " 'countryGeonameId': 2017370,\n", + " 'continentCode': 'EU',\n", + " 'continentGeonameId': 6255148,\n", + " 'postalCode': '183006',\n", + " 'time': '',\n", + " '__v': 0,\n", + " 'countryGeoname': {'_id': '5c883341232cdab94da82765',\n", + " 'geoname_id': 2017370,\n", + " 'name': 'Russian Federation',\n", + " 'latitude': 60,\n", + " 'longitude': 100,\n", + " 'feature_code': 'PCLI',\n", + " 'country_code': 'RU',\n", + " 'admin1_code': '00',\n", + " 'center': [60, 100],\n", + " 'alt_names': {'de': {'_id': '5c848dee3e5a333eadaa4547',\n", + " 'alt_geoname_id': 2419059,\n", + " 'geoname_id': 2017370,\n", + " 'lang_code': 'de',\n", + " 'is_preferred_name': True,\n", + " 'is_short_name': False,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'Russland'},\n", + " 'en': {'_id': '5c848dee3e5a333eadaa450c',\n", + " 'alt_geoname_id': 1556487,\n", + " 'geoname_id': 2017370,\n", + " 'lang_code': 'en',\n", + " 'is_preferred_name': True,\n", + " 'is_short_name': True,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'Russia'},\n", + " 'es': {'_id': '5c848dee3e5a333eadaa450e',\n", + " 'alt_geoname_id': 1556489,\n", + " 'geoname_id': 2017370,\n", + " 'lang_code': 'es',\n", + " 'is_preferred_name': True,\n", + " 'is_short_name': True,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'Rusia'},\n", + " 'fr': {'_id': '5c848dee3e5a333eadaa4514',\n", + " 'alt_geoname_id': 1556495,\n", + " 'geoname_id': 2017370,\n", + " 'lang_code': 'fr',\n", + " 'is_preferred_name': False,\n", + " 'is_short_name': False,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'Russie'},\n", + " 'it': {'_id': '5c848dee3e5a333eadaa454c',\n", + " 'alt_geoname_id': 2419064,\n", + " 'geoname_id': 2017370,\n", + " 'lang_code': 'it',\n", + " 'is_preferred_name': True,\n", + " 'is_short_name': False,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'Russia'},\n", + " 'nl': {'_id': '5c848dee3e5a333eadaa454f',\n", + " 'alt_geoname_id': 2419067,\n", + " 'geoname_id': 2017370,\n", + " 'lang_code': 'nl',\n", + " 'is_preferred_name': True,\n", + " 'is_short_name': False,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'Rusland'},\n", + " 'pt': {'_id': '5c848dee3e5a333eadaa452e',\n", + " 'alt_geoname_id': 1556521,\n", + " 'geoname_id': 2017370,\n", + " 'lang_code': 'pt',\n", + " 'is_preferred_name': False,\n", + " 'is_short_name': False,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'Rússia'},\n", + " 'ru': {'_id': '5c848dee3e5a333eadaa4530',\n", + " 'alt_geoname_id': 1556523,\n", + " 'geoname_id': 2017370,\n", + " 'lang_code': 'ru',\n", + " 'is_preferred_name': True,\n", + " 'is_short_name': True,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'РоÑÑиÑ'},\n", + " 'uk': {'_id': '5c848dee3e5a333eadaa4556',\n", + " 'alt_geoname_id': 2419074,\n", + " 'geoname_id': 2017370,\n", + " 'lang_code': 'uk',\n", + " 'is_preferred_name': True,\n", + " 'is_short_name': False,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'РоÑійÑька ФедераціÑ'}},\n", + " 'id': '5c883341232cdab94da82765'},\n", + " 'divisionGeoname': {'_id': '5c88333b232cdab94da5fb00',\n", + " 'geoname_id': 524304,\n", + " 'name': 'Murmanskaya Oblast’',\n", + " 'latitude': 68,\n", + " 'longitude': 34,\n", + " 'feature_code': 'ADM1',\n", + " 'country_code': 'RU',\n", + " 'admin1_code': '49',\n", + " 'center': [68, 34],\n", + " 'alt_names': {'de': {'_id': '5c848bae3e5a333eada3646d',\n", + " 'alt_geoname_id': 13287290,\n", + " 'geoname_id': 524304,\n", + " 'lang_code': 'de',\n", + " 'is_preferred_name': False,\n", + " 'is_short_name': True,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'Murmansk'},\n", + " 'en': {'_id': '5c848bae3e5a333eada36468',\n", + " 'alt_geoname_id': 5463404,\n", + " 'geoname_id': 524304,\n", + " 'lang_code': 'en',\n", + " 'is_preferred_name': False,\n", + " 'is_short_name': True,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'Murmansk'},\n", + " 'fr': {'_id': '5c848bae3e5a333eada3646b',\n", + " 'alt_geoname_id': 11761698,\n", + " 'geoname_id': 524304,\n", + " 'lang_code': 'fr',\n", + " 'is_preferred_name': False,\n", + " 'is_short_name': False,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'Oblast de Mourmansk'},\n", + " 'it': {'_id': '5c848bae3e5a333eada36452',\n", + " 'alt_geoname_id': 1986257,\n", + " 'geoname_id': 524304,\n", + " 'lang_code': 'it',\n", + " 'is_preferred_name': False,\n", + " 'is_short_name': False,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': \"Oblast' di Murmansk\"},\n", + " 'nl': {'_id': '5c848bae3e5a333eada36455',\n", + " 'alt_geoname_id': 1986260,\n", + " 'geoname_id': 524304,\n", + " 'lang_code': 'nl',\n", + " 'is_preferred_name': False,\n", + " 'is_short_name': False,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'Oblast Moermansk'},\n", + " 'pt': {'_id': '5c848bae3e5a333eada36459',\n", + " 'alt_geoname_id': 1986264,\n", + " 'geoname_id': 524304,\n", + " 'lang_code': 'pt',\n", + " 'is_preferred_name': False,\n", + " 'is_short_name': False,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'Oblast de Murmansk'},\n", + " 'ru': {'_id': '5c848bae3e5a333eada3645c',\n", + " 'alt_geoname_id': 1986267,\n", + " 'geoname_id': 524304,\n", + " 'lang_code': 'ru',\n", + " 'is_preferred_name': True,\n", + " 'is_short_name': False,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'МурманÑÐºÐ°Ñ Ð¾Ð±Ð»Ð°ÑÑ‚ÑŒ'}},\n", + " 'id': '5c88333b232cdab94da5fb00'},\n", + " 'cityGeoname': {'_id': '5c88333b232cdab94da5fb01',\n", + " 'geoname_id': 524305,\n", + " 'name': 'Murmansk',\n", + " 'latitude': 68.97917,\n", + " 'longitude': 33.09251,\n", + " 'feature_code': 'PPLA',\n", + " 'country_code': 'RU',\n", + " 'admin1_code': '49',\n", + " 'center': [68.97917, 33.09251],\n", + " 'alt_names': {'de': {'_id': '5c848bae3e5a333eada36470',\n", + " 'alt_geoname_id': 1603034,\n", + " 'geoname_id': 524305,\n", + " 'lang_code': 'de',\n", + " 'is_preferred_name': False,\n", + " 'is_short_name': False,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'Murmansk'},\n", + " 'en': {'_id': '5c848bae3e5a333eada364a6',\n", + " 'alt_geoname_id': 13358809,\n", + " 'geoname_id': 524305,\n", + " 'lang_code': 'en',\n", + " 'is_preferred_name': False,\n", + " 'is_short_name': False,\n", + " 'is_colloquial': False,\n", + " 'is_historic': True,\n", + " '__v': 0,\n", + " 'name': 'Romanov'},\n", + " 'es': {'_id': '5c848bae3e5a333eada36472',\n", + " 'alt_geoname_id': 1603036,\n", + " 'geoname_id': 524305,\n", + " 'lang_code': 'es',\n", + " 'is_preferred_name': False,\n", + " 'is_short_name': False,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'Múrmansk'},\n", + " 'fr': {'_id': '5c848bae3e5a333eada36477',\n", + " 'alt_geoname_id': 1603041,\n", + " 'geoname_id': 524305,\n", + " 'lang_code': 'fr',\n", + " 'is_preferred_name': False,\n", + " 'is_short_name': False,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'Mourmansk'},\n", + " 'it': {'_id': '5c848bae3e5a333eada36479',\n", + " 'alt_geoname_id': 1603043,\n", + " 'geoname_id': 524305,\n", + " 'lang_code': 'it',\n", + " 'is_preferred_name': False,\n", + " 'is_short_name': False,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'Murmansk'},\n", + " 'nl': {'_id': '5c848bae3e5a333eada3647c',\n", + " 'alt_geoname_id': 1603046,\n", + " 'geoname_id': 524305,\n", + " 'lang_code': 'nl',\n", + " 'is_preferred_name': False,\n", + " 'is_short_name': False,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'Moermansk'},\n", + " 'pt': {'_id': '5c848bae3e5a333eada3648b',\n", + " 'alt_geoname_id': 1898338,\n", + " 'geoname_id': 524305,\n", + " 'lang_code': 'pt',\n", + " 'is_preferred_name': False,\n", + " 'is_short_name': False,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'Murmansk'},\n", + " 'ru': {'_id': '5c848bae3e5a333eada36491',\n", + " 'alt_geoname_id': 6004150,\n", + " 'geoname_id': 524305,\n", + " 'lang_code': 'ru',\n", + " 'is_preferred_name': False,\n", + " 'is_short_name': False,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'МурманÑк'},\n", + " 'uk': {'_id': '5c848bae3e5a333eada3649d',\n", + " 'alt_geoname_id': 8191448,\n", + " 'geoname_id': 524305,\n", + " 'lang_code': 'uk',\n", + " 'is_preferred_name': False,\n", + " 'is_short_name': False,\n", + " 'is_colloquial': False,\n", + " 'is_historic': False,\n", + " '__v': 0,\n", + " 'name': 'МурманÑьк'}},\n", + " 'id': '5c88333b232cdab94da5fb01'},\n", + " 'id': '5fc3c224dcd8580a7973cd8c'}" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "reports_obj[0]" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/datasets/Talluri2021/monolith comparison.png b/datasets/Talluri2021/monolith comparison.png Binary files differnew file mode 100644 index 0000000..3b92c7e --- /dev/null +++ b/datasets/Talluri2021/monolith comparison.png diff --git a/datasets/Talluri2021/other notebooks/4.failures from reports.ipynb b/datasets/Talluri2021/other notebooks/4.failures from reports.ipynb new file mode 100644 index 0000000..45248a6 --- /dev/null +++ b/datasets/Talluri2021/other notebooks/4.failures from reports.ipynb @@ -0,0 +1,1920 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "from plotnine import *\n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "or_events = pd.read_parquet('./outage_report_2019-20')" + ] + }, + { + "cell_type": "code", + "execution_count": 104, + "metadata": {}, + "outputs": [], + "source": [ + "filtered_or_events = or_events[(or_events['vendor'] != '') & (or_events['vendor'] != 'overview')].reset_index(drop=True)\n", + "filtered_or_events.loc[filtered_or_events['status_code'] <= 2, 'status_code'] = 0\n", + "filtered_or_events = filtered_or_events.drop_duplicates(subset=['vendor', 'event_time', 'status_code'])\n", + "filtered_or_events = filtered_or_events.groupby(['vendor', 'event_time'])['status_code'].max().reset_index()" + ] + }, + { + "cell_type": "code", + "execution_count": 105, + "metadata": {}, + "outputs": [], + "source": [ + "filtered_or_events['evtime'] = pd.to_datetime(filtered_or_events['event_time'], unit='s')" + ] + }, + { + "cell_type": "code", + "execution_count": 106, + "metadata": {}, + "outputs": [], + "source": [ + "def proper_vendor_names(series):\n", + " return series.str.capitalize().replace(['Apple-servers', 'Facebook-messenger', 'Youtube'], ['Apple', 'FB Msgr', 'YouTube'])\n", + "\n", + "filtered_or_events['vendor_proper'] = proper_vendor_names(filtered_or_events['vendor'])\n", + "\n", + "vendor_list = list(filtered_or_events.groupby('vendor_proper')['status_code'].sum().reset_index().rename(columns={'status_code':'count'}).sort_values('count')['vendor_proper'])\n", + "\n", + "filtered_or_events['vendor_cat'] = pd.Categorical(filtered_or_events['vendor_proper'], ordered=True, categories=vendor_list)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "facebook_reports = filtered_or_events[filtered_or_events['vendor'] == 'facebook'].reset_index(drop=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "sorted_facebook_reports = facebook_reports.sort_values('event_time').reset_index(drop=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>event_time</th>\n", + " <th>status_code</th>\n", + " <th>vendor</th>\n", + " <th>monitor</th>\n", + " <th>evtime</th>\n", + " <th>vendor_proper</th>\n", + " <th>vendor_cat</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>0</th>\n", + " <td>1.555241e+09</td>\n", + " <td>210.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2019-04-14 11:20:00</td>\n", + " <td>Facebook</td>\n", + " <td>Facebook</td>\n", + " </tr>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>1.555242e+09</td>\n", + " <td>299.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2019-04-14 11:40:00</td>\n", + " <td>Facebook</td>\n", + " <td>Facebook</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2</th>\n", + " <td>1.555243e+09</td>\n", + " <td>813.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2019-04-14 12:00:00</td>\n", + " <td>Facebook</td>\n", + " <td>Facebook</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3</th>\n", + " <td>1.555244e+09</td>\n", + " <td>874.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2019-04-14 12:20:00</td>\n", + " <td>Facebook</td>\n", + " <td>Facebook</td>\n", + " </tr>\n", + " <tr>\n", + " <th>4</th>\n", + " <td>1.555246e+09</td>\n", + " <td>891.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2019-04-14 12:40:00</td>\n", + " <td>Facebook</td>\n", + " <td>Facebook</td>\n", + " </tr>\n", + " <tr>\n", + " <th>...</th>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " </tr>\n", + " <tr>\n", + " <th>43674</th>\n", + " <td>1.604180e+09</td>\n", + " <td>0.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2020-10-31 21:40:00</td>\n", + " <td>Facebook</td>\n", + " <td>Facebook</td>\n", + " </tr>\n", + " <tr>\n", + " <th>43675</th>\n", + " <td>1.604182e+09</td>\n", + " <td>0.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2020-10-31 22:00:00</td>\n", + " <td>Facebook</td>\n", + " <td>Facebook</td>\n", + " </tr>\n", + " <tr>\n", + " <th>43676</th>\n", + " <td>1.604183e+09</td>\n", + " <td>0.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2020-10-31 22:20:00</td>\n", + " <td>Facebook</td>\n", + " <td>Facebook</td>\n", + " </tr>\n", + " <tr>\n", + " <th>43677</th>\n", + " <td>1.604184e+09</td>\n", + " <td>0.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2020-10-31 22:40:00</td>\n", + " <td>Facebook</td>\n", + " <td>Facebook</td>\n", + " </tr>\n", + " <tr>\n", + " <th>43678</th>\n", + " <td>1.604185e+09</td>\n", + " <td>0.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2020-10-31 23:00:00</td>\n", + " <td>Facebook</td>\n", + " <td>Facebook</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "<p>43679 rows × 7 columns</p>\n", + "</div>" + ], + "text/plain": [ + " event_time status_code vendor monitor evtime \\\n", + "0 1.555241e+09 210.0 facebook Outage Report 2019-04-14 11:20:00 \n", + "1 1.555242e+09 299.0 facebook Outage Report 2019-04-14 11:40:00 \n", + "2 1.555243e+09 813.0 facebook Outage Report 2019-04-14 12:00:00 \n", + "3 1.555244e+09 874.0 facebook Outage Report 2019-04-14 12:20:00 \n", + "4 1.555246e+09 891.0 facebook Outage Report 2019-04-14 12:40:00 \n", + "... ... ... ... ... ... \n", + "43674 1.604180e+09 0.0 facebook Outage Report 2020-10-31 21:40:00 \n", + "43675 1.604182e+09 0.0 facebook Outage Report 2020-10-31 22:00:00 \n", + "43676 1.604183e+09 0.0 facebook Outage Report 2020-10-31 22:20:00 \n", + "43677 1.604184e+09 0.0 facebook Outage Report 2020-10-31 22:40:00 \n", + "43678 1.604185e+09 0.0 facebook Outage Report 2020-10-31 23:00:00 \n", + "\n", + " vendor_proper vendor_cat \n", + "0 Facebook Facebook \n", + "1 Facebook Facebook \n", + "2 Facebook Facebook \n", + "3 Facebook Facebook \n", + "4 Facebook Facebook \n", + "... ... ... \n", + "43674 Facebook Facebook \n", + "43675 Facebook Facebook \n", + "43676 Facebook Facebook \n", + "43677 Facebook Facebook \n", + "43678 Facebook Facebook \n", + "\n", + "[43679 rows x 7 columns]" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sorted_facebook_reports" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# An event has start, end, peak, median, mean" + ] + }, + { + "cell_type": "code", + "execution_count": 107, + "metadata": {}, + "outputs": [], + "source": [ + "def extract_failures_from_reports(partial_df):\n", + " event_start = None\n", + " prev_event_time = None\n", + " num_reports_list = []\n", + " failure_events = []\n", + " for _, report_event in partial_df.sort_values('event_time').iterrows():\n", + " num_reports = report_event['status_code']\n", + " event_time = report_event['event_time']\n", + "\n", + " if num_reports == 0:\n", + " if event_start is not None:\n", + " failure_events.append({\n", + " 'start_time': event_start,\n", + " 'end_time': prev_event_time,\n", + " 'peak': np.max(num_reports_list),\n", + " 'median': np.median(num_reports_list),\n", + " 'mean': np.mean(num_reports_list)\n", + " })\n", + " event_start = None\n", + " num_reports_list = []\n", + " else:\n", + " if event_start is None:\n", + " event_start = event_time\n", + " \n", + " num_reports_list.append(num_reports)\n", + "\n", + " prev_event_time = event_time\n", + " \n", + " return pd.DataFrame(failure_events)" + ] + }, + { + "cell_type": "code", + "execution_count": 284, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>start_time</th>\n", + " <th>end_time</th>\n", + " <th>peak</th>\n", + " <th>median</th>\n", + " <th>mean</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>2053</th>\n", + " <td>1.564102e+09</td>\n", + " <td>1.564102e+09</td>\n", + " <td>3.0</td>\n", + " <td>3.0</td>\n", + " <td>3.000000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>4601</th>\n", + " <td>1.582679e+09</td>\n", + " <td>1.582679e+09</td>\n", + " <td>3.0</td>\n", + " <td>3.0</td>\n", + " <td>3.000000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>4600</th>\n", + " <td>1.582675e+09</td>\n", + " <td>1.582675e+09</td>\n", + " <td>3.0</td>\n", + " <td>3.0</td>\n", + " <td>3.000000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2433</th>\n", + " <td>1.565659e+09</td>\n", + " <td>1.565659e+09</td>\n", + " <td>3.0</td>\n", + " <td>3.0</td>\n", + " <td>3.000000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2434</th>\n", + " <td>1.565664e+09</td>\n", + " <td>1.565664e+09</td>\n", + " <td>3.0</td>\n", + " <td>3.0</td>\n", + " <td>3.000000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>...</th>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3965</th>\n", + " <td>1.574808e+09</td>\n", + " <td>1.574808e+09</td>\n", + " <td>215.0</td>\n", + " <td>215.0</td>\n", + " <td>215.000000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3994</th>\n", + " <td>1.574950e+09</td>\n", + " <td>1.574952e+09</td>\n", + " <td>415.0</td>\n", + " <td>322.0</td>\n", + " <td>274.571429</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3996</th>\n", + " <td>1.574958e+09</td>\n", + " <td>1.574964e+09</td>\n", + " <td>550.0</td>\n", + " <td>345.0</td>\n", + " <td>253.454545</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3995</th>\n", + " <td>1.574953e+09</td>\n", + " <td>1.574957e+09</td>\n", + " <td>553.0</td>\n", + " <td>453.0</td>\n", + " <td>463.363636</td>\n", + " </tr>\n", + " <tr>\n", + " <th>402</th>\n", + " <td>1.557258e+09</td>\n", + " <td>1.557259e+09</td>\n", + " <td>952.0</td>\n", + " <td>908.0</td>\n", + " <td>622.666667</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "<p>5490 rows × 5 columns</p>\n", + "</div>" + ], + "text/plain": [ + " start_time end_time peak median mean\n", + "2053 1.564102e+09 1.564102e+09 3.0 3.0 3.000000\n", + "4601 1.582679e+09 1.582679e+09 3.0 3.0 3.000000\n", + "4600 1.582675e+09 1.582675e+09 3.0 3.0 3.000000\n", + "2433 1.565659e+09 1.565659e+09 3.0 3.0 3.000000\n", + "2434 1.565664e+09 1.565664e+09 3.0 3.0 3.000000\n", + "... ... ... ... ... ...\n", + "3965 1.574808e+09 1.574808e+09 215.0 215.0 215.000000\n", + "3994 1.574950e+09 1.574952e+09 415.0 322.0 274.571429\n", + "3996 1.574958e+09 1.574964e+09 550.0 345.0 253.454545\n", + "3995 1.574953e+09 1.574957e+09 553.0 453.0 463.363636\n", + "402 1.557258e+09 1.557259e+09 952.0 908.0 622.666667\n", + "\n", + "[5490 rows x 5 columns]" + ] + }, + "execution_count": 284, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Validate this later by plotting both the intervals and direct from reports.\n", + "# To check if the failure creation algorithm is correct\n", + "facebook_failures = extract_failures_from_reports(sorted_facebook_reports)\n", + "facebook_failures.sort_values('median')" + ] + }, + { + "cell_type": "code", + "execution_count": 285, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>start_time</th>\n", + " <th>end_time</th>\n", + " <th>peak</th>\n", + " <th>median</th>\n", + " <th>mean</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>2053</th>\n", + " <td>1564101600</td>\n", + " <td>1564101600</td>\n", + " <td>3.0</td>\n", + " <td>3.0</td>\n", + " <td>3.000000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>4601</th>\n", + " <td>1582678800</td>\n", + " <td>1582678800</td>\n", + " <td>3.0</td>\n", + " <td>3.0</td>\n", + " <td>3.000000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>4600</th>\n", + " <td>1582675200</td>\n", + " <td>1582675200</td>\n", + " <td>3.0</td>\n", + " <td>3.0</td>\n", + " <td>3.000000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2433</th>\n", + " <td>1565659200</td>\n", + " <td>1565659200</td>\n", + " <td>3.0</td>\n", + " <td>3.0</td>\n", + " <td>3.000000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2434</th>\n", + " <td>1565664000</td>\n", + " <td>1565664000</td>\n", + " <td>3.0</td>\n", + " <td>3.0</td>\n", + " <td>3.000000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>...</th>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3965</th>\n", + " <td>1574808000</td>\n", + " <td>1574808000</td>\n", + " <td>215.0</td>\n", + " <td>215.0</td>\n", + " <td>215.000000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3994</th>\n", + " <td>1574949600</td>\n", + " <td>1574952000</td>\n", + " <td>415.0</td>\n", + " <td>322.0</td>\n", + " <td>274.571429</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3996</th>\n", + " <td>1574958000</td>\n", + " <td>1574964000</td>\n", + " <td>550.0</td>\n", + " <td>345.0</td>\n", + " <td>253.454545</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3995</th>\n", + " <td>1574953200</td>\n", + " <td>1574956800</td>\n", + " <td>553.0</td>\n", + " <td>453.0</td>\n", + " <td>463.363636</td>\n", + " </tr>\n", + " <tr>\n", + " <th>402</th>\n", + " <td>1557258000</td>\n", + " <td>1557259200</td>\n", + " <td>952.0</td>\n", + " <td>908.0</td>\n", + " <td>622.666667</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "<p>5490 rows × 5 columns</p>\n", + "</div>" + ], + "text/plain": [ + " start_time end_time peak median mean\n", + "2053 1564101600 1564101600 3.0 3.0 3.000000\n", + "4601 1582678800 1582678800 3.0 3.0 3.000000\n", + "4600 1582675200 1582675200 3.0 3.0 3.000000\n", + "2433 1565659200 1565659200 3.0 3.0 3.000000\n", + "2434 1565664000 1565664000 3.0 3.0 3.000000\n", + "... ... ... ... ... ...\n", + "3965 1574808000 1574808000 215.0 215.0 215.000000\n", + "3994 1574949600 1574952000 415.0 322.0 274.571429\n", + "3996 1574958000 1574964000 550.0 345.0 253.454545\n", + "3995 1574953200 1574956800 553.0 453.0 463.363636\n", + "402 1557258000 1557259200 952.0 908.0 622.666667\n", + "\n", + "[5490 rows x 5 columns]" + ] + }, + "execution_count": 285, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "facebook_failures['start_time'] = facebook_failures['start_time'].astype(np.int64)\n", + "facebook_failures['end_time'] = facebook_failures['end_time'].astype(np.int64)\n", + "facebook_failures.sort_values('median')" + ] + }, + { + "cell_type": "code", + "execution_count": 109, + "metadata": {}, + "outputs": [], + "source": [ + "failure_df_list = []\n", + "\n", + "for vendor in filtered_or_events['vendor_cat'].unique():\n", + " partial_df = filtered_or_events[filtered_or_events['vendor_cat'] == vendor].reset_index(drop=True)\n", + " \n", + " partial_failure_df = extract_failures_from_reports(partial_df)\n", + " partial_failure_df['vendor_cat'] = vendor\n", + " \n", + " failure_df_list.append(partial_failure_df)\n", + " \n", + "failure_df = pd.concat(failure_df_list)\n", + "failure_df['vendor_cat'] = pd.Categorical(failure_df['vendor_cat'], ordered=True, categories=vendor_list)" + ] + }, + { + "cell_type": "code", + "execution_count": 235, + "metadata": {}, + "outputs": [], + "source": [ + "failure_df['duration'] = failure_df['end_time'] - failure_df['start_time']\n", + "filtered_failure_df = failure_df[failure_df['duration'] >= 0].reset_index(drop=True) # filters 5 events for now\n", + "filtered_failure_df.loc[filtered_failure_df['duration'] == 0, 'duration'] = 1200 # 0 means the event lasted less than 20 minutes. round it up to 20\n", + "filtered_failure_df = filtered_failure_df.reset_index(drop=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 282, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\\begin{tabular}{llrr}\n", + "\\toprule\n", + "{} & vendor\\_proper & count\\_events & count\\_failures \\\\\n", + "\\midrule\n", + "0 & Apple & 811 & 38 \\\\\n", + "1 & Skype & 2103 & 89 \\\\\n", + "2 & Github & 2974 & 68 \\\\\n", + "3 & Gmail & 6227 & 426 \\\\\n", + "4 & FB Msgr & 7948 & 210 \\\\\n", + "5 & Whatsapp & 21235 & 884 \\\\\n", + "6 & Snapchat & 52620 & 2549 \\\\\n", + "7 & Netflix & 59595 & 3388 \\\\\n", + "8 & Facebook & 60375 & 4069 \\\\\n", + "9 & Twitter & 123862 & 2908 \\\\\n", + "10 & YouTube & 132760 & 4219 \\\\\n", + "11 & Instagram & 175702 & 3926 \\\\\n", + "\\bottomrule\n", + "\\end{tabular}\n", + "\n" + ] + } + ], + "source": [ + "event_count_df = filtered_or_events.groupby('vendor_proper')['status_code'].sum().reset_index().rename(columns={'status_code':'count'})\n", + "failure_count_df = filtered_failure_df.groupby('vendor_cat')['duration'].count().reset_index().rename(columns={'duration':'count'}).set_index('vendor_cat')\n", + "\n", + "joined_count_df = event_count_df.join(failure_count_df, on='vendor_proper', lsuffix='_events', rsuffix='_failures')\n", + "joined_count_df['count_events'] = joined_count_df['count_events'].astype(int)\n", + "\n", + "print(joined_count_df.sort_values('count_events').reset_index(drop=True).to_latex(float_format=\"%.2f\"))" + ] + }, + { + "cell_type": "code", + "execution_count": 283, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "646212\n", + "22774\n" + ] + }, + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>count</th>\n", + " </tr>\n", + " <tr>\n", + " <th>vendor_cat</th>\n", + " <th></th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>Apple</th>\n", + " <td>38</td>\n", + " </tr>\n", + " <tr>\n", + " <th>Github</th>\n", + " <td>68</td>\n", + " </tr>\n", + " <tr>\n", + " <th>Skype</th>\n", + " <td>89</td>\n", + " </tr>\n", + " <tr>\n", + " <th>FB Msgr</th>\n", + " <td>210</td>\n", + " </tr>\n", + " <tr>\n", + " <th>Gmail</th>\n", + " <td>426</td>\n", + " </tr>\n", + " <tr>\n", + " <th>Whatsapp</th>\n", + " <td>884</td>\n", + " </tr>\n", + " <tr>\n", + " <th>Snapchat</th>\n", + " <td>2549</td>\n", + " </tr>\n", + " <tr>\n", + " <th>Twitter</th>\n", + " <td>2908</td>\n", + " </tr>\n", + " <tr>\n", + " <th>Netflix</th>\n", + " <td>3388</td>\n", + " </tr>\n", + " <tr>\n", + " <th>Instagram</th>\n", + " <td>3926</td>\n", + " </tr>\n", + " <tr>\n", + " <th>Facebook</th>\n", + " <td>4069</td>\n", + " </tr>\n", + " <tr>\n", + " <th>YouTube</th>\n", + " <td>4219</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " count\n", + "vendor_cat \n", + "Apple 38\n", + "Github 68\n", + "Skype 89\n", + "FB Msgr 210\n", + "Gmail 426\n", + "Whatsapp 884\n", + "Snapchat 2549\n", + "Twitter 2908\n", + "Netflix 3388\n", + "Instagram 3926\n", + "Facebook 4069\n", + "YouTube 4219" + ] + }, + "execution_count": 283, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "print(joined_count_df['count_events'].sum())\n", + "print(joined_count_df['count_failures'].sum())\n", + "failure_count_df.sort_values('count')" + ] + }, + { + "cell_type": "code", + "execution_count": 292, + "metadata": {}, + "outputs": [], + "source": [ + "# Compute all CDFs\n", + "\n", + "def compute_cdf(partial_df, variate):\n", + " count_df = partial_df.groupby(variate)['start_time'].count().reset_index().rename(columns={'start_time':'count'}).sort_values(variate).reset_index(drop=True)\n", + " count_df['prop'] = count_df['count'] / count_df['count'].sum()\n", + " count_df['cdf'] = count_df['prop'].cumsum()\n", + " return count_df\n", + "\n", + "duration_cdf_df_list = []\n", + "peak_cdf_df_list = []\n", + "median_cdf_df_list = []\n", + "mean_cdf_df_list = []\n", + "ia_cdf_df_list = []\n", + "ia_count_df_list = []\n", + "\n", + "for vendor in filtered_failure_df['vendor_cat'].unique():\n", + " partial_df = filtered_failure_df[filtered_failure_df['vendor_cat'] == vendor].reset_index(drop=True)\n", + " \n", + " partial_duration_cdf_df = compute_cdf(partial_df, 'duration')\n", + " partial_duration_cdf_df['vendor_cat'] = vendor\n", + " duration_cdf_df_list.append(partial_duration_cdf_df)\n", + " \n", + " partial_peak_cdf_df = compute_cdf(partial_df, 'peak')\n", + " partial_peak_cdf_df['vendor_cat'] = vendor\n", + " peak_cdf_df_list.append(partial_peak_cdf_df)\n", + " \n", + " partial_median_cdf_df = compute_cdf(partial_df, 'median')\n", + " partial_median_cdf_df['vendor_cat'] = vendor\n", + " median_cdf_df_list.append(partial_median_cdf_df)\n", + " \n", + " partial_mean_cdf_df = compute_cdf(partial_df, 'mean')\n", + " partial_mean_cdf_df['vendor_cat'] = vendor\n", + " mean_cdf_df_list.append(partial_mean_cdf_df)\n", + " \n", + " # Compute interarrival time\n", + " sorted_partial_df = partial_df.sort_values('start_time').reset_index(drop=True)\n", + " ia_arr = sorted_partial_df['start_time'].values - np.roll(sorted_partial_df['start_time'].values, 1)\n", + " partial_ia_df = pd.DataFrame({'ia': ia_arr[1:], 'count':1})\n", + " partial_ia_df['vendor_cat'] = vendor\n", + " ia_count_df = partial_ia_df.groupby('ia')['count'].count().reset_index()\n", + " ia_count_df['prop'] = ia_count_df['count'] / ia_count_df['count'].sum()\n", + " ia_count_df['cdf'] = ia_count_df['prop'].cumsum()\n", + " ia_count_df['vendor_cat'] = vendor\n", + " ia_count_df_list.append(partial_ia_df)\n", + " ia_cdf_df_list.append(ia_count_df)\n", + " \n", + "duration_cdf_df = pd.concat(duration_cdf_df_list).reset_index(drop=True)\n", + "duration_cdf_df['vendor_cat'] = pd.Categorical(duration_cdf_df['vendor_cat'], ordered=True, categories=vendor_list)\n", + "\n", + "peak_cdf_df = pd.concat(peak_cdf_df_list).reset_index(drop=True)\n", + "peak_cdf_df['vendor_cat'] = pd.Categorical(peak_cdf_df['vendor_cat'], ordered=True, categories=vendor_list)\n", + "\n", + "median_cdf_df = pd.concat(median_cdf_df_list).reset_index(drop=True)\n", + "median_cdf_df['vendor_cat'] = pd.Categorical(median_cdf_df['vendor_cat'], ordered=True, categories=vendor_list)\n", + "\n", + "mean_cdf_df = pd.concat(mean_cdf_df_list).reset_index(drop=True)\n", + "mean_cdf_df['vendor_cat'] = pd.Categorical(mean_cdf_df['vendor_cat'], ordered=True, categories=vendor_list)\n", + "\n", + "ia_cdf_df = pd.concat(ia_cdf_df_list).reset_index(drop=True)\n", + "ia_cdf_df['vendor_cat'] = pd.Categorical(ia_cdf_df['vendor_cat'], ordered=True, categories=vendor_list)\n", + "\n", + "ia_count_df = pd.concat(ia_count_df_list).reset_index(drop=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 260, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>vendor_cat</th>\n", + " <th>duration</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>2</th>\n", + " <td>Github</td>\n", + " <td>7200.0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>0</th>\n", + " <td>Apple</td>\n", + " <td>10800.0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3</th>\n", + " <td>Gmail</td>\n", + " <td>21600.0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>Skype</td>\n", + " <td>22800.0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>4</th>\n", + " <td>FB Msgr</td>\n", + " <td>30000.0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>5</th>\n", + " <td>Whatsapp</td>\n", + " <td>40800.0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>8</th>\n", + " <td>Facebook</td>\n", + " <td>75600.0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>6</th>\n", + " <td>Snapchat</td>\n", + " <td>108000.0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>7</th>\n", + " <td>Netflix</td>\n", + " <td>117600.0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>10</th>\n", + " <td>YouTube</td>\n", + " <td>146400.0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>11</th>\n", + " <td>Instagram</td>\n", + " <td>171600.0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>9</th>\n", + " <td>Twitter</td>\n", + " <td>238800.0</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " vendor_cat duration\n", + "2 Github 7200.0\n", + "0 Apple 10800.0\n", + 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Do you need to adjust the group aesthetic?\n" + ] + }, + { + "data": { + "image/png": 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99984cOAAHBwcsGTJEsTHx2PNmjVCx27duhUzZ87E8OHDweFw0KFDh0rrGTlyJLS0tLBu3ToMGzYMSkpKaN26Ne7du4c2bdqI9LrIk/379+PHH39Ev379UFxcjHHjxuHQoUNwd3fHy5cv8fPPP2P58uVITU2Fvr4+nJycBPssfctPP/0EDoeD/fv3Y/369XB3d8fff/+N8+fPVzsuRKGnp4eBAwfi2LFjaNu2LZydnYUed3V1xdmzZ7F8+XIMGjQIRkZGGDlyJBYsWCC0IXlNzJ07Fx8+fMCyZcuQk5MDhmEkNuNQSUkJly5dwtatW3H06FGsW7cOysrKsLa2RocOHeDh4SGRegkhhJC6osBI47x9QgghhBBCCCGEECL1aCkcIYQQQgghhBBCCBEJJZYIIYQQQgghhBBCiEgosUQIIYQQQgghhBBCREKJJUIIIYQQQgghhBAiEkosEUIIIYQQQgghhBCRUGKJEEIIIYQQQgghhIiEEkuEEEIIIYQQQgghRCSUWCKEEEIIIYQQQgghIqHEEiGEEEIIIYQQQggRiTLbDZB1sbGxSE9PZ7sZhNSYsbExbGxsKnyM4prIKoprIo8orok8orgm8ojimsijquK6DCWWaiE2NhZubm7gcDhsN4WQGtPU1MSnT5/KvUlQXBNZRnFN5BHFNZFHFNdEHlFcE3lUWVx/iRJLtZCeng4OhwM/Pz+4ubmx3RxCqu3Tp08YPXo00tPTy71BUFwTWUVxTeQRxTWRRxTXRB5RXBN5VFVcf4kSS2Lg5uaGZs2asd0MQsSK4prII4prIo8orok8orgm8ojimsgr2rybEEIIIYQQQgghhIiEEkuEEEIIIYQQQgghRCSUWCJitX//flhZWaFz5851VueQIUMwZMiQOquPyL+XL19i0qRJaNGiBezt7dGkSRP07dsXa9asERzTqlUrjB07lsVWElJ9Hz9+xMKFC9GmTRs4OjrC0dERbdu2xeLFi/HmzRvBcZs2bYKVlZXQcw8dOoSTJ0+WKzMgIABWVla4cuWK2NopiTJJ/VHdOK9LVlZW2LRpk+DnshgPCAhgpT2EfSdPnoSVlVWFt7Vr1wqOa9WqldBjDg4OaNu2LVavXo3MzMxv1lMWa1ZWVhW+hwPA999/DysrK7Rq1Ups/SPy58qVK7CyssLFixfLPda1a1dYWVnh/v375R5r06YNevToAeDze+FPP/0ktjYlJydj06ZNeP/+vdjKJLVDeywRsTpx4gQAICQkBC9fvqQ1xETm3LlzBxMmTICPjw+WL18OU1NTpKam4s2bN7h48SJWrVrFdhMJqZGjR49i+fLlcHR0xKRJk+Ds7AwFBQWEh4fjwoUL6N27Nx4/fgw7OzuMGDECHTt2FHr+kSNHYGhoiGHDhrHTAUKqoSZxXpcuXboECwuLOq2TyIbNmzejYcOGQveZm5sL/dyiRQusWLECAFBUVIS3b99i06ZNePr0Ka5fv16terS1tXHixIly7+GxsbF48uQJdHR0atELUh+0adMGCgoKCAgIQP/+/QX3Z2VlITg4GJqamggICBA6f0hMTERMTAymTp0qkTalpKRg8+bNsLa2RuPGjSVSB6kZSiwRsXnz5g0+fvyILl264O7duzhx4gQllojM2bVrF2xsbHDs2DEoK///LbJ///5Yvnw5iy0jpOaeP3+OZcuWoUuXLtizZw9UVVUFj/n6+mL8+PG4fPky1NXVAQCWlpawtLRkq7mEiKSmcV6XvL2967xOIhtcXV3RpEmTKo/R1dUViqG2bdsiPz8fW7ZsQUREBBwdHb9ZT79+/XDs2DFERkbCwcFBcP+JEydgbm4ONzc3hIaGit4RERQWFkJDQ6NO6ySiMzQ0hKurK548eSJ0f2BgIJSVlTFixIhyszDLfm7Tpk2dtZOwi5bCEbE5fvw4AGDZsmVo3rw5Ll68iMLCQsHjcXFxsLKyws6dO7F161a0aNECDg4O6NWrFx4+fChUVtlyjPfv32Py5MlwcXGBq6srZs+ejYyMjG+2paSkBFu2bEH79u1hb28PDw8PzJ8/v1rPJfVbVlYWDAwMhJJKZRQVq37LPHToEGxsbLBx40b8+eefsLGxQUJCQrnjFixYgEaNGqGoqAjA/5fVXb9+HV27doWDgwN8fHywf//+cs/Ny8vD2rVr0bp1a9jZ2cHb2xsrV64Eh8MRscdEnm3btg1KSkr4448/hD5sf6lv376Cb8m/XgrXqlUrhISE4MmTJ4IlFV8vmeByufj999/RrFkzuLi4YNiwYQgPDxc6plWrVpg3b165uitbylxcXIzVq1fDy8sLjo6OGDx4ME13J5WqaZzPmzcPTk5OCA8Px8iRI9GwYUM0bdoU27dvBwAEBQVhwIABaNiwIXx9fXHq1CmhsjIyMrB06VJ07NgRTk5O8PT0xPfff4+nT5+Wq/frpXCE1FbZDCMVFZVqHd+uXTtYWloKLYfj8/k4ffo0vv/+eygoKJR7zuXLl9GnTx+4urrC0dERPj4+WLBggdAxISEhGDFiBBwdHeHh4YFly5bhzp075ZZ6DhkyBJ07d0ZgYCD69esHR0fHcmUR6demTRtEREQgJSVFcN+TJ0/QpEkTdO7cGW/fvkV+fr7QY0pKSuXOGc6cOYMOHTrA0dERXbt2xe3bt4Uej4qKwvz589G2bVs4OjrC29sb48aNw6dPnwTHBAQEoHfv3gA+n1OXnZ+UvdfGxMRgxowZaNasmWBLi6FDhwqdR1y8eBEjRoxA06ZN4ejoiA4dOuC3334rdz5d9vciJCQEQ4cORcOGDeHh4YGffvpJ6HMu8P/lfkePHoWvry/s7e3RsWPHCpcQyiNKLBGxKCwsxMWLF+Hl5QVXV1cMHz4c+fn5uHz5crljDx48iPv372PNmjXYtm0bFBUVMWbMGLx48aLcsZMmTYKdnR327NmDBQsW4MaNGxg5ciRKS0srbQufz8fEiROxY8cODBw4EIcPH8ayZcvw4MEDDBkypNybACFf8vb2xqtXr7BixQq8fPmyylgrwzAM1q5di9WrV2PDhg1YtGgRxowZA2VlZfj5+Qkdm5WVJfhj9uW35x8+fMCqVaswZcoU7Nu3D82bN8fKlSvx999/C44pLCzE4MGDcfr0aUycOBFHjx7FDz/8gNOnT2P8+PFgGEZ8LwSReTweDwEBAfD09ISZmZlIZezfvx+2trZo3LgxLl26hEuXLpVLeP7+++9ISEjAhg0bsH79ekRFRWH8+PHg8Xgit/33339HbGwsNmzYgA0bNiA5ORlDhgxBTEyMyGUS+SRqnHO5XEyePBldunTBgQMH0KlTJ6xbtw7r1q3DvHnzMHz4cOzfvx+Ojo6YP38+3r59K3huVlYWAGD+/Pk4cuQINm/eDFtbWwwZMoT2TiLVxuPxwOVyhW5fYxhG8FhBQQEeP36Mffv2oUWLFrCxsalWPYqKihg6dCjOnDkjeF/+999/kZSUVOES5xcvXmDGjBmwsbHBzp07ceTIEcybN0+ofSkpKRg8eDAiIiKwbt06bN26Ffn5+ZXO7E5JScHs2bMxcOBAHD16FOPGjatW24n0KJt59OWspYCAALRu3RotWrSAgoKCUHI9ICAAHh4e0NXVFdx39+5dHDp0CIsWLcLevXuhr6+PyZMnC/1tT0lJgYGBAZYtW4Z//vkHv/76K5SVldGnTx/Bl1YeHh7YvHkzAGDu3LmC85MRI0YAAMaMGYO3b9/ip59+wvHjx7Fu3To0btwYubm5gnqioqLQuXNnbNy4EX5+fpg8eTIuX75cYWxyuVyMGTMGvr6+OHDgACZMmAA/Pz9Mnz693LG3bt3CgQMH8OOPP2L37t2wtrbGDz/8UC/2jqSlcEQsrl69itzcXAwfPhzA52m3q1atwokTJzB06FChY/l8Po4fPy74UN2xY0e0atUKGzduFOzRVKZXr16CP1IdOnSAiYkJZs2ahcuXL2PQoEEVtuXy5cu4d+8e9u7dK8hmA4C7uzt69+6NU6dO0R80UqmlS5ciPDwcBw4cwIEDB6CiooImTZqgW7dumDBhArS0tISOLywsxJw5c/Do0SMcPXoU7dq1AwAYGxsLpp/Pnz9f8C368ePHUVJSUi4GU1JScPPmTTRq1AgA0LlzZ6Snp2PLli0YN24cNDQ0sH//fnz69AlXrlwRTJ9v164dzM3NMXXqVNy7d69ON84n0i0zMxNFRUWwtrYu9xiPxxNKRCopKVX4rXXjxo2hrq4OHR2dSpf0ODk54a+//hL8rKioiOnTp+P169ciLwMyMjLC/v37BW1q2bIlfH19sX37dmzYsEGkMol8EjXOS0pKsHjxYsF5Qps2bXDnzh1s374dN2/eFOzZ4enpiSZNmuD8+fPw9PQEADRs2BDr1q0Tqqdjx46Ii4vDgQMHaOkHqZa+ffuWuy8mJkZoxrS/vz9sbW2FjmnatCn27NlTo7qGDRuGrVu34t69e+jatStOnDghmPn8tRcvXoBhGPz+++9CSYEvk1B79+5FdnY2zp07B2dnZwCfz1tGjRqFuLi4cmVmZ2dj9+7d8PX1rVG7ifRo3bo1FBUVERAQgAEDBiAzMxPBwcFYvnw5tLS04OHhgYCAAHTp0gUJCQmIjY1Fnz59hMooKirCiRMnoK2tDeBzgqhZs2a4fPkyZs2aJaindevWgufweDx06dIFnTp1gp+fH1avXg0dHR24uroCAGxtbYXONTIzMxEREYE1a9Zg8ODBgvu//EwIQGgWNcMwaNGiBZycnDB48GB8/PgR7u7ugsdLSkowbdo0TJo0CQDQvn17KCsr448//sDz58/RokULofqvXbsGExMTAECXLl3QuXNnrFu3rtzrIW9oxhIRixMnTkBdXV2woZuWlhb69OmDp0+fIjIyUujYXr16Cc3U0NbWRrdu3fD06dNy33B/nTzq27cvlJWVq/xG8M6dO9DT00O3bt2EvgVq1KgRTE1Ny60PJuRLhoaGOH/+PK5du4Zly5ahe/fuiIyMxLp169ClSxehK7FkZWVh6NCheP36Nc6fPy9IKpWZPHky0tPTBd9S8Pl8HDlyBF26dEGDBg2EjnVxcREklcoMGDAAeXl5ePfuHYDPsV123Jex3bFjRygoKFBsk2rr2bMnbG1tBbfdu3eLXFb37t2FfnZzcwMAxMfHi1zmgAEDhBJd1tbWaN68Oc0GITVSVZwrKCgIJeKVlZVhZ2cHMzMzoY1gDQwMYGxsXC6ejxw5gh49esDBwQE2NjawtbXFo0ePEBYWJvmOEbmwdetWXLt2Tej29TL8li1bCh67cOECNm3ahIyMDAwdOrRaV4YrY2NjAx8fH5w8eRKZmZm4deuW4Mvgr3l5eQEApk+fjkuXLiEpKancMYGBgXB1dRUklcp8ubHzl/T19SmpJOP09fXh7u4uONcMDAyEkpKSIKnSunVrwd/oyvZXatOmjSCpBAAmJibl3l+5XC62bduGjh07ws7ODjY2NrCzs0NUVFS5ZfYVMTAwgJ2dHXbt2oXdu3fj/fv34PP55Y6LiYnBzJkz4eXlhQYNGsDW1laQiKrofXzgwIEV/vz48WOh+319fQVJJeDzFxr9+vVDdHQ0EhMTv9l+WUaJJVJrUVFRCAwMRJcuXcAwDHJycpCTk4PvvvsOAMpd4vTLX7YypqamKCkpQUFBQZXHKisrw8DAQDANvSJpaWnIycmBnZ2d0Amlra0tUlNTa/SHmNRfTZo0wcyZM7Fnzx68fPkSU6ZMQVxcHHbu3Ck4JjIyEq9evUKnTp0E35x8qXHjxmjVqhUOHToE4HNiKC4uDhMmTCh3bGW/F8D/l12kpaXh06dP5eLa2dkZDMNQbBMhhoaGUFdXrzDBs2PHDly7dg0HDx6sdT0GBgZCP6upqQGAYA8xUZTF/pdMTEyqfO8n9ZOoca6hoVFuM29VVVXo6+uXO1ZFRQXFxcWCn3fv3o2lS5cKZo5cvnwZ165dQ6dOnWoV96R+cXJyQpMmTYRuX9PR0RE81qJFCwwfPhzbt29HWFhYjb8QGDFiBG7fvo09e/ZAXV1dcJ7+tdatW+PAgQPgcrmYN28emjdvjs6dO+PChQuCY7KysmBsbFzuuRWdywAVv6cT2dOmTRtERkYiOTlZsNStbCZ/69at8f79e+Tm5iIgIADKyspo2bKl0PO/Pl8APr/vfvm+uWbNGmzYsAE9evTAoUOHcOXKFVy7dg3u7u7Ven9VUFDAyZMn0bFjR+zatQs9evSAh4cHVqxYIdgDqqCgAIMGDcKrV6+wePFinDlzBteuXcO+ffsAlD9/UVZWhqGhodB9ZbH+9XlJZecvFR0rb2gpHKm1EydOgGEYXL16FVevXi33+OnTp7F48WLBz2lpaeWOSU1NhaqqarllRmlpaUKX6eVyuYLNlStjaGgIAwMD/PPPPxU+/nUdhHyLiooKFixYgL179yIkJERwv7e3N/r06YNFixYB+LwvzNcbfE+cOBHTpk3Du3fvcPDgQTg4OKB9+/bl6qjs9wL4/x9iQ0NDaGhoVLoR7Nd/9Ej9pqSkhLZt2+LBgwdISUkR2n+m7FvmipYsSIKamhpKSkrK3Z+ZmVlh3JbF/pfS0tKqfO8n9RMbcX7u3Dn4+Pjg999/F7r/y41rCZGUsiU6Hz9+rNHzevXqhZ9++gk7duzAyJEjq7wqW48ePdCjRw8UFxfj5cuX2L59O2bOnCmYPWpgYID09PRyz6vovRtAhUutiexp06YN9uzZgydPnuDJkydCsz7LkkiBgYGCTb1F+cx17tw5DBkyBEuXLhW6PzMzE3p6etUqw9raWnCuHBERgcuXL2Pz5s0oKSnBH3/8gcePHyM5ORlnzpyBj4+P4Hk5OTkVlsflcsudr5Sdt399XlLZ+UtFx8obmrFEaoXH4+HMmTOws7PD6dOny92mTZuGlJQU+Pv7C55z/fp1oUxwfn4+bt++jZYtW0JJSUmo/HPnzgn9fPnyZXC5XKE3ga917doVWVlZ4PF45b4JatKkCRo2bCim3hN59OXVLr5UNi32681hhw4dip07d+LUqVOYO3duueWcvXr1gpWVFdasWYOHDx9i3LhxFZ5ghYSE4MOHD0L3XbhwAdra2vDw8ADwObajo6NhYGBQYWx/vbyOkNmzZ4PH42HJkiXV2oi+Il9/myiKBg0aCF3RBfh8shcREVHh8RcvXhTaGyc+Ph4vXryo8r2f1F/iiPOaUFBQEMzMK/Px40cEBQVJvG5Cyq5sZWRkVKPnaWhoYN68eejWrRvGjh1breeoqanBx8cHy5YtE6q7devWCA4ORmhoqNDxly5dqlGbiGxp3bo1lJSUcPXqVYSEhAj9TdbV1UWjRo1w+vRpxMXF1Wqvua+v7nnnzh0kJydXeMy3zk8cHR0xb948uLq6lru67Nf1fH3BnS+dP3++wp+/7uejR4+Evizm8Xi4dOkS7OzsYGlpWWVbZR3NWCK14u/vj+TkZPz0008VvoG4urri0KFDOHHiBFavXg3g88auI0aMwNSpU8Hn87Fz507k5+cLZn186fr161BWVkb79u0REhKCDRs2wN3dvcIND8v0798f58+fx5gxYzB58mR4eXlBWVkZSUlJCAgIQI8ePdCrVy+xvQZEvowaNQoWFhbo2rUrGjZsCD6fjw8fPmDPnj3Q0tISbNz3pT59+kBDQwNTp05FUVERduzYIfhjpaSkhPHjx+PXX3+FpqZmuc3sy5iZmWHChAlYuHAhTE1Nce7cOTx48AA//fST4FvFKVOm4Nq1axg0aBCmTJkCNzc3MAyDhIQE/Pvvv5g2bRqaNWsmuReHyJwWLVrg119/xYoVK9CzZ0+MGjUKzs7OUFRURGpqqmCW6Zd7HnzN1dUVly5dwsWLF2Fraws1NTXBPkrVNXjwYMyePRtLly5F7969kZCQgJ07d1b6wSg9PR2TJk3CyJEjkZeXh40bN0JNTU2wuSchXxJHnNdE165dsWXLFmzcuBGtW7dGREQEtmzZAhsbmwqv7EWIqHJzcwUJSy6Xi7CwMPz1119QU1PD+PHja1zetGnTMG3atCqP2bBhA5KSkuDr6wsLCwvk5uZi3759UFFRESQSJk+ejBMnTmD06NFYtGgRTExMcP78ecEeOF/P3ibyQUdHBx4eHrhx4wYUFRWFNq0GPieeypaTiZpY6tq1K06fPo2GDRvCzc0N7969w65du4RWsACAnZ0d1NXVcf78eTg5OUFLSwtmZmbIzMzE8uXL0adPH9jb20NFRQWPHz/Gp0+fMHPmTABA8+bNoa+vjyVLlmDBggVQVlbG+fPnK50FqKqqit27d6OgoABeXl548eIFtm7dis6dO5db7mdoaIihQ4di3rx50NDQwJEjRxAeHi60lYa8osQSqZUTJ05AVVW1wsuVAp9/uXr27ImrV68KfpknTJiA4uJirFixAhkZGXB2dsaRI0fKvTkBwL59+7Bp0yYcOXIECgoK6NatG9asWVMuw/wlJSUlHDx4EPv27cPZs2exfft2KCkpwcLCAq1bt65wLxxCysyZMwe3bt3C3r17kZqaipKSEpiamsLX1xezZ8+Gk5NThc/r0qULjh49ivHjx2PixInYu3evICHUr18//Prrrxg8eLDQFVa+1KhRIwwbNgybNm1CVFQUzMzMsGrVKkydOlVwjKamJs6fP4/t27fjn3/+QVxcHNTV1WFlZQVfX1+asUQqNHbsWHh7e2P//v3Yu3cvUlJSoKCgAHNzczRv3hwnT56sclPVRYsWITU1FYsXL0Z+fj6sra2FLilcHQMHDkRKSgqOHj2KU6dOwcXFBevWrcOff/5Z4fFLlizBmzdvsGDBAuTn58PLywu7du2q8ApGhAC1j/OamDNnDgoLC3H8+HHs2rULTk5O+P3333H9+nW6iAIRq+fPn6Nfv34APp/fmpubw8vLC3PmzBHaZF6cmjZtirdv3+LXX39FZmYmdHV14enpKXjvBgBzc3OcPXsWq1atwtKlS6Guro5evXph0aJFmDdvXqXnOkT2tWnTBq9fv0bjxo2ho6Mj9JiPjw/27t0LVVXVCj/XVcfatWuhoqKC7du3o6CgAB4eHti3bx/Wr18vdJyGhgY2b96MzZs3Y+TIkSgtLcWCBQswbtw42Nra4vDhw0hMTISCggJsbGywcuVKTJw4EcDnz6eHDx/G2rVrMXv2bGhqaqJHjx74+++/0aNHj3JtUlZWxuHDh7FixQps3boV6urqGDlyJFasWFHu2O7du8PZ2Rnr169HQkICbG1tsX379ko3tpcrDBFZUFAQA4AJCgpiuykyITY2lrG0tGR27dr1zWM3btzIWFpaMhkZGXXQsvqnqtiluBa//fv3M5aWlkxwcHCFj7ds2ZIZM2ZMHbdK/lBcE3lEcU3kEcW1fPrxxx8ZJycnpri4mO2msILiWv7MnTuXadiwYbWOtbS0ZJYtWybhFtW96sYuzVgihBAJef/+PWJjY/Hnn3+iR48egm/6CCGEEEJk2Z9//gkzMzPY2NiAw+Hgzp07OHbsGObOnVvlygJCiHyixBIhhEjIpEmTkJaWhpYtW5a7ehAhhBBCiKxSVlbGrl27kJSUBB6PB3t7e6xatQqTJ09mu2mEEBZQYonUmQYNGiAhIaFaxy5cuBALFy6UcIsIkazq7kNT0/1qCCGEEELYNHv2bMyePZvtZhAiUVu2bMGWLVuqdWx1P+fKK9qynxBCCCGEEEIIIYSIpN7NWOJwODh58iSioqIQGRmJ3NxcDB8+HCNHjmS7aYQQQgghhBBCCCEypd7NWMrLy8OtW7dQWlqK1q1bs90cQgghhBBCCCGEEJlV72YsmZqa4tixY1BQUEBubi5u3bolclmFhYUAgNevX4updYTUjU+fPlX6GMU1kVUU10QeUVwTeURxTeQRxTWRR1XF9ZfqXWJJQUFBbGVlZ2cD+HzlJ0JkjaamJoyNjcvdT3FNZBnFNZFHFNdEHlFcE3lEcU3kUWVx/aV6l1gSJwsLCwCAn58f3NzcBPfHx8fD2tparHVlZWVh48aNWLRoEQwMDGpVVkXtE2f5NfV13eJ+/cTdN0mMLxuMjY1hY2NT7n6Ka/GguGYHxbVkUVyzg+Jasiiu2UFxLVkU1+yguJYsimt2VBbXX1JgGIapo/ZIndzcXIwePVrkzbtfvnwJb29vBAUFoVmzZoL7IyMj4eDgIM6mihW1r3akvX21RXEtGdQ+dlFcSwa1j10U15JB7WMXxbVkUPvYRXEtGdQ+6VHvNu+uraSkJLx8+RIvX76s9npDccjPz8f+/fuRn59f67J4PJ5Ey68pSdfNZt/YUljKZ7sJ1cL22Kenp0NSuXW2+yYrirh8JOSWsN0Msarp2JSWlkq0fHGiuP4ss5ArsfcOaVXXY88wDIqKipCWlobIyMga/57Upm5ZK7+6+AyDlHzJvY6ySJrGvqioCCkpKYiNja3zuqWx/G/hMwyyCrms1C3tpGHsGYYBj8dDcXExOBwOcnNzkZmZiZSUFMTHxyMqKgohISEoKioSe921wXZcf41hGJTy+Cji8lFQwkNOEReZhVykFpQiKa8E8bkliM4uRkRmEULSC1n9naClcDW0e/durFmzps7rzczMxOTJk9GtWzdoa2uLVAafz8fRo0excuVK3Lt3Tyh7Ko7yRSXputnsW12KyirGpZAsXArJwruUQsQv9IKqknTnjutq7F1cXJCbm4vg4GB8+vRJ8G9GRgZSU1NhYmIisbrra1xnF3ERnV2M5PxSJOeXIqXs34L//z85vxTZRTyoKSmg4KfmYt0Dj03VHZuIiAhs374dx48fx/v377+5dr2m5UtCfYvr3GIePqRy8D61EB/TCvEhtRAf0gqRnF+K+AVesNBRZbuJdaY6Y1NYWIi0tDRkZWUhMzMTsbGx+PjxI4KDg5GXlwcul4vS0lLk5+dDSUkJpaWlgvsKCwuRnJyMRYsWgc/ng8PhgMv9/wlyeHg4HB0dWeubNJf/JS6fQQmPj7QCLs58zER0djFSC7iIyS7Gu1QOirkMOMubS/35QV2R1NgUFBTg2bNn+PDhA2bPno2QkBDw+XxkZWUhKysL2dnZyMnJEdxyc3NRUvL5SxYnJyeEhobWug3yFNdleHwG+1+lYV9QKj6lF8HHWhu3xrrWSd2ypDpjwzAM8vPzBTGZl5cHDoeDgoICpKenIzk5GZmZmUhISADweaVPWdxyOBzExsZi2bJlAAAulyt04/F4FU5kqMiLFy/g7e0t1r7VRk3LL+XxkVfCR34JD/klfOQV85BfwkNeCR/pnFIEx3HADYlBSkEpUgtKkVbARRGXDx7DgMv/HNOf/8+Ax//8Hs5j/v//mn6FtbWnDWa1Mhet87VEiaUamjZtGvr16wfg8w7po0ePZrlF1XPv3j0sXLgQoaGhmDp1KszN2Qk4Ij4MwyAoqQCXgrM/J5NSC9HQUA39XAywuqM1lBXl40N6ZfLz8xEfH4/k5GQkJSXh/fv3KCkpQVJSkuC+sj+G7dq1g6amJlxcXODm5oYePXpg7ty5cHNzq/O14fKOYRj8/SIVi27FoojLQENZERY6KjDXVoGZtgrMtVTgZqzx+f9f3OoTLpeLKVOm4PDhw2jRogU2b94MXV1dtptFvrDmfjwOvkpHXG4JFAA4GqrB3UQDLa20MKGpCRqZasBEq37FbZmyD8zv3r3Du3fvEBERgbi4OMTFxSEzM1NwnLKyMqysrODu7g5XV1fo6+tDWVkZKioqyM3NhZmZGVRUVKCiogJlZWXk5ORgzpw5WL9+PSwtLaGpqQkdHR3BzdTUlMVeSx7DMCgo5SO3mIfsIh6eJ+QjOb8UOUU85BT/71bERW4xD2m5hShVeIMSHoNiLv/zv7zP//K/+BTibKSOJuaaMNNShreFJtZ0soKjobrcnx+wITMzE//++y8OHjyIBw8eIDAwEAzDCM4x7t+/DwsLCxgaGsLOzg76+vrQ09ODnp4edHV1hf6vr6/PbmekzMOYPNyJzMHHtEI8TyhAGqcUP7axwOpO2vAw1WC7eazi8XjIzs5GRkaG4Jaeno7w8HAAwC+//AIlJSVBwigrKwvp6elIS0tDenp6uZmgmpqagk2azczMYGhoCEVFRVhZWcHZ2VkQp/n5+Vi4cCFWrlwJCwsLKCsrQ1lZGUpKSuX+//W/Ze/7ZTdDQ0M2Xrpvyi7iIv9/XyQl55cIvhRNyv+cHMoq5CI8swhZReUTaKpKCtBWVYSRhjL0lHmwMSqBmZYK3E00YKypDA0VRSgpKEBZUQFKivj8r4Lw/8seq+i48o8pQPl/P+uoKbHwan1GiaUasrCwEGy+Ju0YhsHdu3exZcsWXL9+HZMmTcK1a9fA4XCgqanJdvOICJLzS/BvdB7uR+fiamg2EvJK0cpKC8MbG+GYqwHcjNXlZtZHGR6Ph/DwcLx9+1Zwe/fuHaKiogAASkpKgj9+dnZ2sLCwQNu2bWFubg5lZWVMnToVT548QcuWLaGoSN/QStrKewnYEpiMrb1sMayREbRVFeUuJmuDz+dj4sSJuHnzJh4+fIi2bduy3STyhVIeH0ffZuDXB4nY2ssWray14WqsDk0V9k7U2JKeno6QkBAEBwcjODgYr169AgC4u7sDABwcHNC4cWO4urqiW7dusLa2RoMGDQTvx1paWpX+7le050RsbCzmzJmDHj16fHODUHlQWMrH+1QOjr3LQEBcPt4kc1D6RVbIRFMZTkbq0FVTgp66EvTUlGCtowk9dSWU5jOwsTCFmpIi1JQVoKakCFUlBagpK0BVSRFqSgrQVFGEs5H8nROwjcPhICwsDKGhoQgODsbbt2/x6tUrREREQE1NDS1btkT79u2xYsUKtG3bFmlpabC1tcWZM2fqRVyLC59hcC8qFyffZ2L/qzTY6qmij7M+lrW3xGA3Axhp1q/EPo/HQ1hYGN68eSO4vX37FgkJCULLsnV1dWFkZCSYaRMVFQUTExNoaWnBwMAAjRo1gomJieBmaGgIAwMDGBgYQFtbu8Lz5MrerxcuXIi+ffvKRFwzDIOYnBIk5JaAU8oHp5SPQu7nf0PTixCWWYScIi6yi3hITogDAHjteg8F/XSoKCoIvgQt+1LU20ITRprKMNBQhrGmMhwM1KGtqghtVSVoqyoKzQitT3ss1cvEUlBQEIqKilBYWAgAiIuLw+PHjwEAzZs3h5qaGpvNq7WcnBwcPnwYO3fuREREBAYPHoxXr17B09MTwOcAJ7IhJb8U/8bk4n5UHv6NyUVwehEMNZTQzlYXyztYoa+zvlwvxfjw4QMGDRqE0NBQGBkZwdPTE56enujXrx88PDxgZ2cHY2NjKCoqVvqHDwAsLS0pqSRGDMMgpaAUIelFCMn4vKY7JKMIoelFiMwqxpVRzujZUJ/tZkodhmEwa9YsXL58Gffv30eTJk3YbhIBUMLj405kLs5+zMTF4CwUlPKxrmsDzGhhxnbTJK6goADh4eEICwsT3Mo+MGdkZEBRURH29vZwcXGBvb09AODChQvo0qWLVCxVlFXH3qVj2uVocEr5MNZUxtxW5vilszWMNZWhp64EXTUlGKgrQ6mSmUWRkUVwcBD/Em4iLDExEQEBAQgICMD79+8REhIiOK8wMTGBs7MzPD09sXjxYnh7e0NbWxsuLi4st1p2MQyDf6NzcSkkC2c+ZiElvxS9nPSwr589xjYxrvT3Qd7k5OTg7du3Qkmk9+/fo7CwEMbGxmjSpAmaNGmCYcOGwd7eHkZGRjAyMoKhoSFUVD4n3GJjY2Fra4v9+/fLROJHEnKLeXidXID7UXk49DoNMTmfl5qqK39OvGsoK0JTRRE6akpoYakNL3NN6KsrgW/HxTwAt8a6opmrAwzUlShBX031MrG0a9cupKamCn5+/PixILG0d+9emJlJ38mkubk53r9/X+UStk+fPmHr1q3w8/ODnp4epk+fjilTplRr2Vt1ypcUSdfNZt9qKoNTCv+ozzOS/o3Oxaf0IhioK6G9nS6meZuig50uPMw0oCgnb3BVjc2FCxcwZswY9OrVC/7+/rC0tKzxGzvFtXhlcEqx7WkK/n6RinQOF0oKgKOhOpyN1OFurIEBrgZobqkFL3OtOmuTNKpobBiGwZIlS3DkyBHcuXOnVkklimvxYRgGrfd+REhGIXo21Me23rbo42wAXRankotbUVERIiIiyiWPwsLCkJiYCODzZYSdnJzg5OSEXr16Yf78+XB1dUXDhg0FX7aVlJRg3rx5cHJygqqq+L/QqA9xbWZmhlFnw3HqQyaWtbPEAh9z6KnXy1NxqWFubo63b9+isLAQFy9eFCzxfPbsGaKjo6Gvrw8fHx+0aNECo0aNgouLC5ydnStcvlPRF7f1Ia7FUX5sTjFm/puHewmZaG+rgyW+FhjiblivlhyHhYWhe/fuiI6OhpKSElxdXeHp6YnBgwdj7dq1aNKkCczNzat1LixLYy+uugtL+bgXnYsPqYW4E5mD+9F5YBgGrsYamN3KDANcDWGrr/rNz1AlJYbo+v49nJzsoKpK7881US9frX379rHdhBpTVVVFo0aNKnyMw+Fg7dq12LRpE9q2bYtDhw6hf//+gqx1bcuXNEnXzWbfauLYu3TMvBoDRQWgva0OpniboqOcJZK+VtHY8Pl8rF27Fj///DN++eUXLFmyRORvCiiuxScsowjN97yHhbYKfulsjXa2OnAwUKMNYCvw9djk5ORg5cqV2L17N65fv47WrVuLtfy6JG9x/SGtEG9SOAib4wkHA/U6q7euBAcHw93dXbDXS1nyqFOnTpg6darg5+rs6SJvY1+XdauqqiJB3RrD9oUgLrcEL6Y2RhNz2pKADYWFhXj//j1ev34tuL19+xb5+fnQ0dGBh4cHPDw8sGzZMrRt2xaurq61mvEs73Fd2/IT80pw5kMmfn+UBGM1PoKmNUJj0/r5u2FlZYWVK1eiSZMmcHd3h7q66H+TZGHsxVF3XE4xjoUWIvxtBPwjc5HO4cLDTBNe5pq4OcYSbRpo1/g8VVY+N0oj+kQgIxITE9GwYUPBt4tlbt++DQ8PDxw7dgznzp3D/fv3MWTIkBollaoqvy5Ium42+1YducU8jD0fgYkXorCivSVSf2yG88OdMbe1OZqYa8ptUgkQHpvS0lKcOnUK7dq1w59//olLly5h6dKltZp+SnEtHnnFPGx+kgRNFUV8mOmJKd6mcDXWoKRSJcrGJjo6Gtu2bYOjoyOuXLmCq1evolOnTmIrn+K6doq5fEy9FIVujrpymVQCPu+DFBAQgPT0dGRmZuLp06fw8/PDqlWrMHLkSLRo0aLaGwXL09jXZd0Mw8Dv0Sf0btUYzmr5+DjTk5JKdai4uBgHDx7E6NGj0ahRI2hra6Nly5b4448/kJKSAl9fX2hrayMwMBA5OTl4/Pgx/v77b0yZMgXu7u61XkYvr3EtjvKX342DzebX2Po0GROaGuNoN716m1QCPm+cPWHCBDRr1qxWSSVA+sdeHHVfCwpD8z0fsPdDIRgGWNrOEgkLm+LplEbY3dceHe10RTpPlfbPjdKsXs5YkkVcLhcRERGCS+++e/cOa9euxblz5zBnzhz8/PPPtdrv4Ovy65Kk62azb1VhGAbXw3Mw51oMVJUUEDDZHc0s6tcSorKx2bBhA06ePIm8vDyMGTMGR48eFctGdxTXtVPM5WNvUCp+fZgIdWVF7OpjX2/2OKiN0tJSREREoEOHDuBwOFi1ahWmTZsmtuVDFNe1dz86F7OvxSC3mIcLI5wlWhebVFVVaz1Droy8jH1d1z3vRix23w0HLyMev3eyhJWu/O6LKE0KCgqwb98+bNiwARwOBwMHDsSMGTPg5eUFT09PwZU4Y2NjsX79elhYWEhkHxV5jevaln8zPBvrHiXh4AAHjPE0goKCAu0BK0bSPPa1VVhcgoiICPT75xMmdvTAj+58ODV0FFv50vq5URZQYknGvHv3DnPnzsXFixfRs2dPPHv2DN7e3mw3i9RQQFwelt2Jx5P4fMxobopfu1hDS1V+9vSoSGlpKaKiohAaGiq4vX79GgBw5coV/PTTTxgzZgxddl0KRGcX4+T7DOwJSkV+CR9LfS0xvYUp1JVphtK3MAyDmTNnAgD69u2LX3/9FXp6eiy3inxp6Z04bAxIwpRmpvilizUMNehUiIjf49g8zLgSjeD0Qhwd6IDhmwB1FXoPlbTs7Gzs2LEDW7ZsgbKyMhYtWoSpU6dCR0eH7aaR/2EYBjOuRGN2SzNBUomQb+GU8nA5JBu/XwkHAGzpZYtZ3ewpISlF6GxKRrx//x4A0KdPH/Tv3x/Pnj1D8+bNWW4Vqan3qRws94/HlZBsjPQ0woEBHnK7BKO4uBg3b97EyZMn8fz5c0RGRoLH40FHRwfOzs5wcnJC69at8fTpU9y5cwe2trZsN7neexKXh0W3YhEYXwBXY3VMbmaKmS3N5GojY0nbsWMH7t69CwBYvHgxJZWkzL6XqdgSmIybY1zR2Z6S2EQy3qZw0NMvBP1c9HF+uBNU8lO//SRSK6mpqdiyZQt27NgBQ0ND/Pzzzxg/fnytlxQR8YrPLUG/Y6GIzSnB7FZmlFQi1XL0TTqW+8cjt5iHbsbqeA2gn4sB280iX6HEkpTjcrn47bffsHbtWlhYWODYsWPo2LGj2OvR0NBAv379oKGhIfay2a6bzb59ad/LVPxwJRo9nfTxcnpjeJrJ3zpyLpeL+/fv4/jx4zh37hxKSkrQr18//Pjjj4IrqZiZ/f9EIi0tDVFRUdDUlMxrQXFdPQzD4FJUEX4KDMbwxkbY1cceHqYadMJXQ69fv8bChQuxYcMG3L17VybGXtrqlnT56x8lYU1HK0oqiUDWx74u6i7h8fHnk2SsuZ+Awe6GODLQAQoKCkjjScd5iDyKjY3Fxo0bsXfvXjg4OGDHjh0YPnw4lJWr9xGH4rpuys8t5mHu9Rj4vU2Hk6E6wuc2gZ2+mkTaRaRr7GvrZVIBZlyJxqRmJljTyQqleVkoviwffZM7DBFZUFAQA4AJCgoSuj8iIkIs5YeEhDCtWrVijI2NmXPnzomlTIYRX/skRd7ax+fzmZX+cYzq2mfMgZepEmqV+NQ0rnk8HvP48WNm1qxZjKmpKaOiosL069ePOX78OJOfn18XTa6yfdJCWtuXySllvj8VyqitfcpseZLE8Pl8tpskEZJ+v87Ly2OcnZ2Z0aNHi/U1lNa4KSNL7Tv+Lp1RXP2U+ZDKYbFF4iXpuJYUeWzf2Y8ZjMOWV4zJH0HMX4FJDJcnufdSaX/9aqs6cR0SEsJMmDCBUVZWZpo3b86cP3+e4fF4dd1UIdI+Lmy1j8/nM8NPhzHO214zdyNzGF4lfyOl/fWrLXq/rrn8Yi5jveklM/JMWKXvqfT6SQ9a7C2FGIbBrl270LRpU5iYmODdu3fo3r07Tp06hYKCAonUWVBQINHy2aybzb7x+AwmX4rClsBkXB7pjAlNTeq8DZLAMAxevXqF//znP7C3t0e7du0QHByMdevWISUlBRcvXsTw4cOhpVX1ZuTyPPay0Lf3qRx4736PsIwiXOitj7mtzWmWkohmzpwJhmGwc+dOcDgcqR97aa1bUuWfeJ+BsecisK2XLdxN6FtIUcjq2Euy7iIuHwFxeRh5NhwjzkRglIcxwuc2waxW5kIXOmCzb/Lo2bNncHV1RVRUFK5du4Znz55hwIABIl3BjeJasuUfe5eOxjvf4dynLJwY0hCd7XXl+mrH0kIaxr62EnJLMPhUGBQVFLCvn4PgPVUe+iavKLEkZRITE9G7d2/8+OOP2LJlCy5dugRzc3NkZGRg2LBhyMjIkEi9ki6fzbrZ6hufYTD9SjQuhWTh/ng3dHeUj71WPn36BDc3NzRr1gyPHj3Cjz/+iISEBNy+fRsTJ06EgUH11zzL69jXRd21LZ9hGEy/HA0PM00ETGoEZwNaGS2qI0eO4MSJEzh58iR0dHSkfuyluW5JlX/wVRp+aGGGmS3NxFpufSKrYy+puhPzSuC2/S3aHfiE4LQi3BvvirWdrSvck47Nvsmj5s2b4+nTp7h37x66detWqy9EKK4lV/4/b9Mx4UIUhrgbImyOJ5rWsysfs4ntsa+tmOxiDDwRitR8Li6OcILGFxc+kPW+yTP6JCFFzp8/j8mTJ8PFxQVv3ryBo6P4Lp1I6hbDMJh3PQZnP2bizjhXufpjamdnh4kTJ2LYsGG04bYMC8sswpP4fHya5SH0B5vUTEhICH744Qds3LgRTZs2Zbs5pAKlPD6eJRRgWnNTtptC5EROERff/ROCBrqqeDG1EYw0VdhuUr2iqKiIFi1asN0MUoXj7zIw9nwkfmpniTWdrNluDpEhDMNgyuUoqCkr4sL3DWGpo8p2k0g10acJKcDn87FixQp8//33mD9/Ph48eEBJJRkWk12MfsdDceh1Oq6OckYzOUoqAZ83tVu8eDEllWTci8QCWGirwNmIlgWJqqioCMOGDUPXrl0xa9YstptDKvEgJg+FpXx0dZCPWaOEXcVcPgafDAOPD1wc4UxJJUK+UlDCw9p/EzCpqQnWdqakEqmZgLh83IvKxYH+DpRUkjE0Y4llubm5GD16NB4+fIirV6+iR48ebDeJiIjLZ7D9aQpW3ouHt6UWnk9tBBdj+tBOpM+HVA5W+Mejna0O202RaYsWLUJmZib8/f1pbyopdvpDJro66la4RImQmuAzDMZfiERYZjEeT3KHgQadRhNShs8wuBqajX0v05DB4WJjDxu2m0RkDMMwWP84CT0b6sHJSJ3t5pAakpq/iIWFhfDz88Pjx4+Rl5cHa2trDB48GO3bt6/yecuWLcP79+8rffzw4cOCPV8qO7Zp06ZYs2ZN7ToggrCwMPTv3x/A540InZycKj3WzMwMgYGBMDOTzP4Qki6fzbrrom9pBaX47p8QRGYV48+etpjQ1Jg2J6wGeRh7tuquTflL78bDyUgdB/o7SKBl8q+0tBSHDh3C33//jX///ReGhoZCj0vz2Et73eIun8dncCE4G793ayCW8uozWRt7SdS9+FYcbkXk4MEEN1jrVv+bdDb7RqpGcS2e8tMKSjH9SjSuh2Wjk70uDg5woGQ+i2Q1rk9/zMStiBy8nNa4zuuuq/LlmdQkltatW4ewsDCMGzcOlpaWePDgATZu3AiGYdChQ4dKnzd9+nRwOByh+4qLi7FmzRo4OjqW20jY3NwcCxYsELpPW1tbfB2pphs3bmDEiBFo3749jh49Cl1d3SqPV1NTQ6tWrSTWHkmXz2bdddG3u1G5iMouxoeZnjDTpmnx1SUPY89W3aKUn1XIxbqHibgdkYPtve1ob6Ua4HK5uH//Pk6ePIlz586hoKAAmzZtQtu2bcsdK41jLyt1i7N8hmHw11sOcot56OOsL5Yy6zNZGntx151TxMX0K9G4EJyFm2Nc0MhUU6zlE/bU57gWR/kN3Jtiy/N07H6RCj11JTyd0ggeZjX7/SDiJ4txnc4pxZxrMVje3hJuVVy9VRb7Vl9IxaeKFy9e4PXr15g+fTp69uwJT09PzJo1C15eXjh48CB4PF6lz7WxsYGrq6vQLT09HVwuF926dSt3vKqqarnjra3rbv0vwzDYsGED+vTpg9mzZ+P8+fPfTCoBQFJSEry8vJCUlCSRdkm6fDbrrou+ZRVyYaWjSkmlGpKHsWerblHKn3I5CheCs3BssCMmNjWWSLvkCZ/Px7///osffvgBVlZW6N27N5KTk7F161akpqZi7ty5FT5PGsdeVuoWV/mcUh6mX4nGgY+FOD/cCca0D06tycrYi7PuN8kc/PM2HcPOhONJXD6ujXJBe9tvn7NVt3zCvvoY1+JyLCAY1s6Nsff+R0z1NoX/ODdKKkkJWYvr7CIuuh8JgYWOCn5sa1Gnddd1+fJMKmYsBQYGQkNDA76+vkL3d+nSBZs2bUJoaCjc3NyqXd7t27ehoaGBdu3aibuptVJYWIjJkyfjwoULOHHiBIYMGVLt55aWluLNmzcoLS2VSNskXT6bdddF314lcWBKSaUak4exZ6vumpafVlAK/8hc7Opjh4Fuht9+Qj3FMAwCAwNx8uRJnD59GikpKejSpQvWrVuHgQMHlpsFWxFpG3tZqlsc5b9J5mDk2XAUlvJxuJseejTUF18D6zFZGHtx1V3EZfDzvwlYfT8B1rqqcDBQw7nhTiJfjIPNvpGq1ae4FieGYfDno3gwyWG4O8YJtraWYq+DiE7W4vrnfxNQzOPDf5wbVJWqnvcia32rT6QisRQTEwNra2soKQmvxbW3txc8Xt3EUmJiIj5+/Iju3btDQ6P8NLrk5GSMHDkSHA4HpqamaNeuHYYOHQo1NbXad6QKcXFxGDBgADIzM/HkyRN4enpKtD5Sdx7H5uHg6zTcGuPKdlMIqdTvjxJhb6CGQW7fTozUR0lJSdi8eTNOnTqF+Ph4dOjQAStXrsSgQYNgYmLCdvNINRWW8jHwRCiaW2lhb197ZCTGst0kImOis4vR81IWGEUlHB/iiKGNjNhuEiFS5+SHTLxLLQQAungFqZXYnGLsDUrDnn72tPJDxklFYikvL6/CDbLK9j7Ky8urdlm3b98GAHTt2rXcY+7u7vD19YW1tTVKSkoQFBSEc+fO4ePHj/j111+hqCiZlYGPHj3C4MGD0ahRI9y8eRPGxrQERV6U8viYejkKE5uaoJN9zafHE1JXnsTlY6CrAVS+8U1Qffb06VP8+OOPGDJkCMzNzdluDqkhHp/BrGvRKOUzONDfAdqqSshgu1FE5vzxKBE6qgp4Ot0T2qq0+TAhXyvm8vHzvwkY52WMPWw3hsg0hmEw5VIUWlhpYWgjmk0v66QisQRUne2ubiacx+PB399fsO/S10aPHi30c/PmzWFqaoqDBw/i6dOn8PHx+WYdSUlJgjWXnz59+ubxe/bswaxZszBjxgxs3LgRKiqiZWLV1NTQqVMnic2sknT5bNYtyfKjs0sQnF6EG6NdxF52fSDLY8923TUpPyW/FM8SCvBnT1uJtEUeWFhY4MGDB2IpS5rGXtbqFrX8qKxiLLwVi0cxebg6ypkSAhIgrWMvzrqfJhdj38ssHO2mJ9YYYrNvpGr1Ia7FVfentEL4R+XC72060gq4mN2rAcIorqWSrMT1gVfpeBKXj9czGlf7atqy0rf6SCoSSzo6OhXOSsrPzwdQ/au2vXjxAllZWRg0aFC16+7YsSMOHjyIkJCQaiWWdu/ejTVr1lSr7GvXrmH27NnYvXs3JkyYUO02VcTMzAz+/v61KoPN8tmsW5LlZxVxAQCmWjR1UxSyPPZs112d8kt4fNwMz8GO5ymw0FFBCyvR9gchNSMNYy+rdde0/HcpHPzxOAmn3meguaUW/p3gVuXVZIjopG3sxV334fPX0edYKMY2MUZLMV9lms2+karJe1yLq+7rYdnocywUzkbq6OqgiyMDHeFkpE5xLaVkIa5T8kux+HYsfu5sDQcD9Tqtm83y5ZlUrImwtbVFfHx8uau/RUdHCx6vjtu3b0NZWRmdOnWqcRuqOytq2rRpCAoKQlBQEPz8/Ko8tlevXnj9+nWtk0rA542/r127hsLCwlqXxUb5bNYtyfKfxudDV00JaspS8askc2R57Nmu+1vlP43PR4PNrzHiTASMNJRxbphTtb8NIrXD9thLkjT17WZ4Nlrs+YDMQi5uj3XF40nulFSSIGkae0nU/d3qg9BWKMVvXRpIpHy2+kaqJu9xLY6636VwMOZcBBa3tcCnWZ74q7cdnIzUKa6lmLTHNcMwmHYlCo4GaphVw0y+tPetPpOKT8M+Pj4oLCxEQECA0P3+/v4wNDSEs7PzN8vIyspCUFAQWrduDV3d6u91U5aRdHGp3lImCwsLNGvWDM2aNfvmhuIKCgo1uppdVdLS0vDdd98hLS1NLOXVdfls1i2p8gPj87H4dhw2dBf/SWh9IatjLw11V1R+EZePgLg8bApIwrTLUfC21ELioqb4Z3BDtLCq3sxPUnsU15IvPzKrCENOhWNpOwtcG+WCDna6tIGshEnL2EtCUHgc3m2ZgTWttCWyeSybfSNVk+e4rm3dUVnFmHY5Ch0OfkJXRz382sVarOUTyZH2uP7raQr8I3PhN9gRSoo1+9st7X2rz6RiKZy3tze8vLywa9cucDgcwV4XL1++xIIFCwRXi9u2bRv8/f2xZ88emJqaCpXh7+8PHo+Hbt26VVjHhw8fcOrUKfj4+MDMzAylpaUICgrCzZs34enpiZYtW0q8n0R+pBWUYsjJMEzwMsHkZqbffgIhEvQyqQBzrsUgKKkAXD4DD1NNtLXRwcI25tBVo71miPzxj8qFqZYyVnawYrspRMYxDIMtgSkAACdD2lOD1G9ZhVzsep6K+9G5uBuVC0cDNfzWtQHGNTGmWc9ELD6kcvCfO3HY288ezkY0y1ieSEViCQCWLl0KPz8/HDt2DHl5ebC2tsaiRYvQvn17wTF8Ph98Ph8Mw5R7/p07d2BqagovL68KyzcwMICSkhJOnjyJ3NxcKCgowMLCAiNHjsTAgQMldkU4Ip/OfMyEipICtvSyYbsphOB2RA6S8ktwZaQzWlppQ4eSSUSO5ZfwsDkgGT0c9WmWEqm1Ux8ycSk4GwBdNp2QUeci8C6Fg7FNjDGjhSm6O+pBiy6GQMSkhMfHD1ej0aOhHkZ70lXS5Y3UJJY0NDQwZcoUTJkypdJj5s2bh3nz5lX42K5du6os39LSEitXrqxNEwkReBSbh872ulClS7cTliXmFmPD4zTMbW2OLg56bDeHEIn780kySngMfu9Gy5BJ7STmlWDq5SjMbmWGzWw3hhCWcUp5uBeVi0sjnNHNkc4niHgxDIOpl6MQmVWMgEGObDeHSAB9KpYRpqamuH37drklgLJSPpt1S6L8J3H5aGujI7by6itZHHtpqbus/CuJCrDSVcWydpYSqYfUHMW1ZMsPTi9Ed0c9WuZZx6Rh7MVthX88nAzVseq7xnLXN1I98hjXotb9b3QeFAD4VvP8luJaekljXO94loKzH7NweaQzGuiJvuxYGvtGPpOaGUukaurq6ujatavMls9m3eIun8dnEJ9bAkcD2ouhtmRt7KWpbnV1dag5tcKmo8HY3tuuxpsfEsmhuJZs+THZJejjrCmxNpCKScPYi1N8bgn+eZuBiyOcoKulKVd9I9Unb3Etat25xTwsuBmLIY0MoaFSvXkHFNfSS9riOiixAD/ejsPffezgZa5Vp3VLW/nyjGYsyYiUlBT4+voiJSVFJstns25xl59VzIDHAOYSuHJMfSNrYy9NdaekpGBIr07oZMLFpGYmEqmDiIbiWnLll/L4+JhWCBdjdYnUTyrH9tiL29/PU+BuooHujnpy1zdSffI89tWtm2EYzLoWDT7DYOd3dmIvn9Q9aYrrnCIuhp8Jx/DGRhjnVfvzVWnqGxFGM5ZkRHFxMR4/fozi4mKZLJ/NusVd/vPUUmirKsJWn2Ys1Zasjb001V1cXIzUT0Gw0Ch/MQPCLopryZV/LzoPBaV8dLLXlUj9pHJsj724XQjOwngvEygoKMhd30j1yfPYV6fu3GIeBp0IxZP4fDyc6A7tGmzUTXEtvaQlrhmGwbQr0VBTUsD23rZ1Wre0li/PKLFESA2diyjC9+6GUFemCX+EHZmFXCy4GQMAaGJOS4JI/fHHo0QMb2wIfXU6fSGiW3wrFp/Si9DPVZ/tphDCCk4pDw9i8vDHoyQk55fiw0xP2NEXpkTMDr1Ox+WQLDyd0oiuLlgP0CdjQmogr5iHh4mlGN2ELpFJ2PPnk2Q8T8gHAAxwNWS5NYTUjRIeH/ej8zDFmzbUJKJhGAZXQrPw17MU7OlrD2cjDbabREidC8sogsOWNxh0IgyGGsq4NsqFkkpE7CIyizDvRgz+6NoAjU3pS9D6gL7ykxGqqqpo0aIFVFVVZbJ8NusWZ/lpnFLwGMDZiPb3EAdZGntpqJtTysPGx8nYEpiMaZ5meMBS30jVKK4lU/7LJA4AwEqHYp4N8hDX256mYPHtOExsaowJTf//BZE89I2IRp7H/uu678YVY/id93iZxEFXR12cHepUq1kkFNfSi+245vIZjD0fgbY2OpjZ0qxO65b28uUZJZZkhLm5OZ49eyaz5bNZtzjLzyniAQD06DLXYiFLY8923XyGwdDT4XibzMHffewwwsMIioPY6RupGsW1+MvnMwymXIrCOC9j2NMVOVkhy3HNMAyW+8dj/eMk/N3HvtwFD2S5b6R25Hnsv6x7hX881j3Mww8tTPFnT1u0tNKCilLtFq5QXEsvtuP6tweJCM8sxpsZTlBQEO9Vi9nuG6kcLYWTEUVFRXjw4AGKiopksnw26xZn+YVcPgBU+1KspGqyNPZs1R2SXogV/vFouPUNAuPycW+8G0Z5GqOkuJi1vpGqUVyLv/y3KRx8TCvEb12sJVIv+TZZjuuLIdnYGJCMSyOcK7yKpiz3jdSOPI99UVERjl66jREnPmL94yRs76CDbb3t0NZGp9ZJpbLyKa6lE5txfSsiB788SMCevvYw1xb/rB95/p2VdfTpWEakpqaiQ4cOSE1Nlcny2axbnOXz/3cBLkUxZ9/rK1kaezbq/pDKgcfOd7gZno15rc3xcZYnHA3VxVY+kQyKa/GX/zqZA1s9VYmcpJLqkdW4fpaQj+mXozCnlRl6OenXad11VT4RnTyP/Y57nzC2f3eExyUicLI7utuId7YnxbX0Yiuud79IxXf/hGBxWwv0dzWo07plpXx5JjVL4QoLC+Hn54fHjx8jLy8P1tbWGDx4MNq3b1/l8+7evYutW7dW+Njhw4dhYCAc1K9fv8Y///yDqKgoqKmpoUWLFhg/fjz09fXF1RUix7IKuaDJSqQu8BkGWwJT4GiojmdTG7PdHEJY8zq5AEdep8OS9lYiNXTkTTpmXInC8MZGWNe1AdvNIaROPE/Ix7F3Gdh1Nx4AcHaYM2wstBAZyXLDiFxLzi/Bf27HYlsvW8xoId59lYhskJrE0rp16xAWFoZx48bB0tISDx48wMaNG8EwDDp06PDN58+dOxdWVlZC9+no6Aj9/P79e6xZswbNmzfHTz/9hJycHBw+fBgrVqzA5s2boaKiItY+Efnz94tUdLehDzdEsiKzijDrWgyexufj8khntptDCCteJRVg1f0EXA3NxnfO+vi1My2DI9UXEJeHKZei8EfXBpjb2kzs+3wQIi34DINLIdl4HJuHgLg8PI0vQAc7HWzoboM5m9huHakvlt6Jh5OROqbSlVvrLalILL148QKvX7/GwoULBUkkT09PpKam4uDBg/D19YWSUtWbJdvY2MDJyanKYw4ePAhLS0ssWbJEUJ6ZmRn+85//4Pbt2+jdu7d4OkTkSlYhF2GZRQhKLMCN8Bxc7qPPdpOIHHubwoHPvg9o20AHTya70+WwSb00/0YMLiYlo5+rAV5MbYSmFlpsN4nIkPepHHx/KhxTmplgno85280hRCKKuXwEJRXglweJeBSTh3a2OujqoId9/RzgZqKB2NhYzGG7kaReeBKXh6Nv0vFwohuUFCmJX19JRWIpMDAQGhoa8PX1Fbq/S5cu2LRpE0JDQ+Hm5larOjIyMhAWFoaxY8cKJanc3NxgZWWFwMBAqU4sGRsb4/z58zA2Nv72wVJYPpt1V6f87CIuwjOLEJZR/PnfzCKEZ3z+N7Pw85XgrHRUsNDHHK4GXIm0sz6ShrGXlJrWHZdTjCuh2Tj4Kg3eFlq4Ocalym/Y2ewbqRrFtWjeJHOwPiAXyiPWI4GrgX8nuKCtjc63n0jqhKzE9evkAvQ4GoIuDrrY3NOmTutmq3wiOlkd+30vU/Gf23HILebB20ILz6c2goux8BdRsto3Unt1OfYJuSUYcy4S47yM4dNA8n+zKa6ll1QklmJiYmBtbV1uVpK9vb3g8W8lln7++Wfk5uZCU1MTjRs3xqhRo2BraytUBwDY2dmVe66trS2Cg4Nr2QvJ0tTUxIABA2S2fDbrLis/t5iHoMQChGcWfZE8KkZYZhHSOZ+TRRbaKnAyUkdDQ3UMcDWAo6E6nIzU4WigBi3Vz/EZSYvUxYbiGiji8tHLLwQPYvJgq6eKvi4GmNnS9JvLNtjsG6kaxXXNjTwbjpPvM9HdUQ9Xf56Kbg66tHRJyshCXN+OyEG/46Ho66KPowMdq/3NuSz0jUiGLI79zmcpmH8zFpu6N8BYLxPoqlW8qkMW+0bEo67GvpjLx3eHP8BWXxXbe9tJrL6K6pbV8uWZVGxDnJeXB21t7XL3l92Xl5dX6XP19fUxdOhQzJ49G7/88gtGjRqF8PBw/Pjjj4iKihKq48syv6Sjo4Pc3NzadkOiUlNT0bNnT4nugC/J8tmsOzQmEXqNfKG//DZa7v2A+TdicSsiB0oKCujjrI8d39khaFoj5Cz1RvzCprg33g17+9ljsa8lBrsbwtNMU5BUIuJFcf35ikUPYvIQONkdEXObYGsv22otf2Ozb6RqFNc1E5lVhJPvM3F/vBsOdzfA5pnDkJaWJrbyiXhIe1w/icvDoJNh+LGNBU5971Sj5RjS3jciObI09gzDYGtgMubdiMHhgQ6Y1cq80qSSuOtmo3wiuroa++WX3iKNw8WZoU7QqKOrG1FcSy+pmLEEoMpvJqt6zNvbG97e3oKfGzdujObNm2POnDn4559/sHz58mqVVd1vRpOSkpCUlAQA+PTpU7WeIw5FRUW4efMmioqKZLJ8turm8RlMvxCC3I+PceWQHdp7OkGnij/CpG7V57jOLuLi7McsrL4fjxEeRmhhVT7pXZvyCXvqc1yL4kZYDhwM1OBro424uCyKayklzXH9JpmDPsdCMbGpCdZ0svr2E8RYtzSUT0QnK2P/ND4fP92Nw5P4fBwd5IhhjY3qrG62yieiq6uxv9doJo5PbgsDjbpLKVBcSy+pSCzp6OhUOCspPz8fQMWzjKpiZmYGNzc3hISECNUBVDz7KS8vr9wV5Cqze/durFmzpkbtIexgGAY/3Y3Hq2QOAMDDTJOSSoR1xVw+plyOwpkPmdBTV8IYT2P80oWudkXqp9CMQmx/loLeTvq09I2I5G0KBz39gtHXRR9/9rShOCJy5W5kDpbcicOrJA76uxrg3Q8ecDBQZ7tZpJ7LKiwFAAx0M8AgN0OWW0OkhVQshbO1tUV8fDx4PJ7Q/dHR0YLHa4phGCgq/r97ZWWU7bX0pZiYGNjYVG+Dx2nTpiEoKAhBQUHw8/OrcbtI3cgs5GLIqXDseJ6C7b1rHj+EiBvDMAhJL8SGx0k4/i4DZ4c5IW5BU6zvbgNVJal4KyakTl0MzkKLPR/Q0EgdqzrWfJYJqd8YhsGGx0louecDujl+vhKWIiWViBx5l8LB8DPh8DLXQugcT5wd5kRJJcK6Ii4fM65EAwDWdqIvRsn/ScWMJR8fH9y6dQsBAQFo166d4H5/f38YGhrC2dm5RuUlJycjODgYTZo0EdxnZGQEZ2dn3L9/HwMGDBBsFB4cHIyEhAT069evWmVbWFjAwsKiRu0RB2VlZbi5uUFZWTJDJuny67LuhzF5GHMuAgYaSng2pRH0SrNY6xupWn2I6zvR+bgWGIYHUdnIKMqArZ4qlrWzRC8nfbGUT3EtfepDXNe27lsRORh2OhyrOlphia+FYJYJxbX0kpa4ZhgG96LzsONZCm5F5ODIIAcMbfTtZUHiqFtayyeik9axf5aQj+5HgtHbWR+7+thBWYRLuEtr34jkSWps+AyDsecjEJfPg5OLK7Q1VMVafnVQXEsvqXjFvL294eXlhV27doHD4cDCwgIPHjzAy5cvsWDBAkESaNu2bfD398eePXtgamoKAFixYgUaNWoEOzs7aGhoICYmBufOnQMAjBo1SqiecePGYeXKlfjjjz/Qu3dv5OTk4PDhw7C1tUXXrl3rttM1ZGlpiY8fP8ps+XVRd0x2MX5/lIj9L9MwrbkpNnS3gbqyIgAN1vpGqiavcV3M5SNFQQ9T9t/F9NtxGOdlgmXNtTC4uSMa6KmJpQ42f2dJ1eQ1rsVVdwmPj7HnIrDAxxxL21mKvXwiGdIQ15xSHoacCod/ZC66Oeri8SR3eJpp1knd0lw+EZ20jT3DMDjxPhOzrkVjhIcRdn5nJ/LyTmnrG6k7khqbXx8k4k5ELh7/0A5uq+pur+EvUVxLL6lZf7F06VJ06tQJx44dw+rVqxEaGopFixahY8eOgmP4fD74fD4YhhHcZ2tri4cPH+LPP//E6tWrce7cOXh6emLz5s3lltB5eHhg5cqVyMrKwi+//II9e/bAw8MDP//8M1RUVOqqqyIpKSnBy5cvUVJSIpPlS7LumOxizLgSBZe/3uJNMgdXR7ngr952/0sqsds3UjV5ieucIi42ByRhzLkINNn1DrrrguC98zU2nrmPPzqbY28/e/SzVxdbUgmguJZm8hLXkqr7zMdMFHL5WNbestxjFNfSi+24vh2RA599HxGeUYQPMz1weaSLWJJK1alb2ssnopO2sf/tYSImXYzEj20ssKMWSSVR6pa28onoJDE218KysfbfBBwZ5ABHPSWZPg9hs3x5JhUzlgBAQ0MDU6ZMwZQpUyo9Zt68eZg3b57QfZMnT65RPU2bNkXTpk1FaSKrkpOT4e3tXaP9oKSpfEnUnc4pxQr/eBx8lY5mFpq4MMIJPRz1yv0RZrNvpGryENcMw2DalWgExOahu6MeJjczgaeZJgxL0uHp4ovBc8vv6yYOFNfSSx7iWlJ1J+SWYOmdeMxtZQ5t1fIXU6C4ll5sxTWfYbDCPx7rHydhenNTrOhgBVMt8X4ZKM+/s6Rq0jD26ZxS+Efl4m0yB1ufpmBff3uM9DCuk7qluXwiOnGPTQanFJMuRmKJryX6OBsgNjZWZs9D2C5fnklNYomQmojLKUZPvxCoKilUmlAiRNLSCkrxw9Vo3AjPwcOJbvAy1xI8FhubzV7DCJEyCbkl+ONRIva9TIOXuSaWtKv7vQqJ7Cnh8TH5UhQuh2Tj2igXdHPUY7tJhIhVRGYRuhwOBqeUDy9zTfynrQWGN67dnmGEiNuiW3Ew01LBig7lZxoTUoYSS0TmhGUUofvRYDgZquPccKcKv/UmRFIYhsHNiBzsf5mGyyHZcDFWx9MpjeBuosF20wiROvklPPzxKAmbApLgbqKB40Maop+LPn0RQL4pv4SHIafC8D6lEP9OcBPbsjdCpAHDMHgYm4eRZyLQzFILp79vCDVlqdmhhBCBh4kl8Hubi4BJ7nQVY1IlSiwR1nH5n/fMisgsQrxCHj7Gl+BhbhoyC7nILOQhg8NFRiEXWYWf/w3PLEJne10cH9JQsI8SIXXlr6cpWHw7DoPdDXB1lDM62evSJa4JqcCLxHwMPBEGFUUFHB7oiCHuBpRQItWSXcRFb78QZBXx8GiSO+z0xbc/HSFsuxOZg2V34vAqmYNxTYyxs48dfWAnUonLZ/DL8wLMbGGGFlbabDeHSDlKLMkIIyMjHD16FEZGkpkeK47yGYZBbjEPGYVcZHC4yPxfIiiT878EUdnPgvv+lzDKzYfCwNXocjoJCqrZ0FFRgLFWMYw0lWGooQxDDSWYaSnD3UQdhhrKsNBRRX8XfahU84+wpF87IjpZiOsypTw+Vt1LwIaAJBwd5PjNqeqy1DciXvI89jWp+7eHSWhironT3ztBQ4Xer2VdXcU1NHTR9XAweAyDfye4iX0/parqlsffWVK1uh77v54mY+HNWEz1NsXJ751gbyC5pCnFdf0lrrHZG5SK9CI+Vna0kkj5oqC4ll6UWJIRWlpaGD16dJ2XzzAM4nJL8CG1EDE5JZ9nDXG+SBD971aWSOL9/4J90FRRhKGGMow0lGGkqQwDDSUYaSjDTk/zc8JI8/NjhhrKMNJsCSMNZRhoKCM2OgoODg4S7xthH1txXVORWUUYdTYCMdkluDrKBd2rsc+HrPSNiJ88j311674bmYMrIVm4O86t2kmlmpRP6l5dxHX7vt+j37FQqCkr4tZoVxhq1M1pqjz/zpKq1eXYH3yVhoU3Y3F0kCOG1cE+ShTX9Zc4xia3mIc19xMw00Oz3HuxLJyHSGv58ozmXcqItLQ0DBkyBGlpaRIpPzU1Fb37D8KJp+HYHJCESRcj0WbfBxj8HgT7LW/w/alwbH+ajBvh2YjIKoKSAuBipI4+zvqY19ocO76zw62xrng9vTFi53uh4KfmyFvWHDHzvfByemPcHuuKU987YVcfe/zSpQEWtLHAeC8T9HUxgLNGEZZPHwNwsqGsKP5lEpJ+7YjoJD02tSk/OrsY258mo/vRYLhvfwd9dWW8mt64Wkml2tYtDeUT0cnz2Fen7gcxuRh+JhwL21igna2O2Msn7JD02Fx9HQXndt9Bn5eHW2Nc6iypBMj37yypWl2MfZ8BgzDO7wWmXY7Cju/s6iSpVFY3xXX9JI6x+fnfBOioKWGUi7pEyhcVxbX0osSSjCgsLMTZs2dRWFhYq3IYhkFSAQ83wrOxOSAJk/+XQGq46RmuXzqPiWeCcfx9Brh8Bv1dDXB0kCPC5ngid5k33s/0xL8T3HF+uDP29XfA+u42+I+vJaZ4m2KwuyE62unCw0wTVrqqNdr7SFx9Y6t8IjppGXuGYRCVVYzDr9Mw5VIUXP96A8etb7D1aQoam2jg+mgXXB3lDDPt6i/JkJa+kbonz2NfVd0Mw2Dj4yR0PRyM0Z7G+LmztVjLJ+yS5NhkFnIx+ewnFL+7iwN9rKCnXrcT6uX5d5ZUTZJjE5pRiHmXQ3D14nk8jc7E/QlumOJtKvZ6KkNxXX/Vdmz8o3KxJTAZ23vbQk2p/Jf+0noeIgvlyzNaCleP/PU0GSv845FXwoe6cjbcjDXgbqqB/q4GmOzIx6T1wIeZHrC3s2W7qYTUqQEnwnAlNBsW2ipoZ6uDua3N0cFOF27G6rTZMCHVkFnIxeRLUbgbmQO/wY4Y2oj2JiDVN+taNAzUlZEMSGTmMiF1LTA+Hx0PfkJTzWIAwI0xLrBrULMZnISwIZ1TinHnIzC3lTl6NNRHZGQm200iMoISS/VEThEXK+8lYFEbC7TV56C9R0MofXHyFhvLBQCh+wipD94kc3AlNBuPJrqhtbU2JZIIqQLvf1fxvB6WjeRIRTyJzEXklTeIzCqGm4kGnk5pBFdjDZZbSWTJxeAsnP2YhYu9bNFrOdutIaT2sgq5GHkmHBOaGmOppxlsF4GuHktkAsMwmHIpCmZaKvi1S81nHZP6jRJLMkJJSQkNGjSAkpKSSM/fG5QGPTUl/MfXAnEx0eUSSLUtvzYkXTebfSNVY3vsY3OKsfBmDDra6cBHzN8kst03wh55G/vUglLsC0rD5dAsvA2LAXTNsORuArycVWCrqYjBTczhaaaJphaatb5kNsW19JLE2OQW8zD7WjQWt7WAh4UCnYeQOieJsZl7IwZ66krY3MMWmalJFNekzok6Nn+/SMWdyFy8mNoIalVsa0KfG0lFpCaxVFhYCD8/Pzx+/Bh5eXmwtrbG4MGD0b59+yqfFxAQgMePHyMsLAyZmZnQ19eHm5sbRowYAUtLS6Fjly1bhvfv35cro2nTplizZo1Y+yNuVlZWiI2NFem5xVw+tj5NxkIfC6hUctJfm/JrS9J1s9k3UjU2xp7LZ3A/OhdnPmTi6Nt0eFtoYU8/+zqpW5bKJ6KT5bFnGAbpHC4S8koQl1OCMx8zcepDJmz0VDHG0xgrOljB86dYWOmoQEFBAZGRkXBwEN+eIRTX0ksSY7PsThw0VBSxrJ0lNFQU6TyE1Dlxj01kVhGOv8vAvfGfr4hJ59eEDaKMzYdUDhbdisXWXrZw+cbMY4prUhGpSSytW7cOYWFhGDduHCwtLfHgwQNs3LgRDMOgQ4cOlT7v3Llz0NfXx9ChQ2Fubo60tDScOXMG8+fPx4YNG2BjYyN0vLm5ORYsWCB0n7a2tkT6JE6lpaWIioqCvb09VFSqv4EwABx7l4HCUj4me5tIpPzaknTdbPaNVK2ux373i1SsvBePnCIeujnq4shARwxyM5DI8jeK6/pLWse+mMtHYl4pEvJKkJBbgsS8EiTkfv657P+JeSUo5n1e7qajqghfWx2cG+aEHg31oKigIKibqyFdfSOSJ+6xOf0hE3uCUuH/vw/gdB5C2CDusfnzSTJaWmmhbQNtiZRfExTX9VdNx6aIy8eosxHo7aSPSU0r/7woavniRHEtvaQisfTixQu8fv0aCxcuFCSRPD09kZqaioMHD8LX17fS6WjLly+Hvr6+0H2enp6YMmUKLl68iNmzZws9pqqqCldXV4n0Q5KSkpLg4uKCmJiYcsmyqqQWlGLdw0TMaGEGbdXKp/SJWr44SLpuNvtGqlaXY8/XNcP8GzFY2cEK01uYQl/CVx2iuK6/pG3sGYbB96fDcf5TFgBAAYCZtgqsdFRgqasKax1VeJppwlJHBVa6qrDSUYWVrip01cr/zZC2vpG6I86xicrlYcr1SPzapQF8bXTEXn5NUVzXX+Icm8wiPg6+ysSRQQ6CL6worgkbajo2i27GIruIhz197av1ZSvFNamIVCSWAgMDoaGhAV9fX6H7u3Tpgk2bNiE0NBRubm4VPvfrpBIAGBkZwcjICOnp6ZJorsyIzSlGj6MhMNFSxqI25mw3hxDWpHNKsfxhNFpaaeM/vha0QTepV66EZuNScBaujnKGu4kGLLRVKl0WTYikJeWVYNLdHHSy18VCOjchciKzkIsVT/NhpauC/i4GbDeHkGo79i4de1+mwX+cKww0pCI1QGSUVERPTEwMrK2ty81Ksre3FzxeWWKpIsnJyUhLS0Pr1q0rfGzkyJHgcDgwNTVFu3btMHToUKipqdWuE1ImLKMI3Y4Ew9lIHeeGO1U5W4kQeZXBKQUAtDvwCY52tjg+xJGSSqReuRKaheFnwrHE1xI9G+qz3RxSz2VwStHjaAjMNBXxz2BHulIWkWnZRVw8TyjAy6QCbA1MgZ4KHyeHudIVlonM+JDKwbTL0VjfrQHa2oj3Ijak/pGKxFJeXh7MzMzK3V+291FeXl61y+LxePjrr7+grq6Ofv36CT3m7u4OX19fWFtbo6SkBEFBQTh37hw+fvyIX3/9FYqK8vENbimPj+9PhcHDTAOnhzpBvYpd/QmRRzw+g1X34vHnzU8AgA3dG2B6l8b0IYbUG1FZxVhxLx4n3mVgTScrLGtn+e0nESJBXD6DoafDoaqkgD0ddKGpQl94Edn1Ma0Q7Q98REEpHx6mGpjV0gyDLArhaq7FdtMIqZa8Yh6+PxWO3k76mNOq/OdwQmpKKhJLAKqcRVDdGQYMw2Dbtm348OEDlixZAhMT4c3HRo8eLfRz8+bNYWpqioMHD+Lp06fw8fH5Zh1JSUlISkoCAHz69Kla7RIHAwMD7Nq1CwYG355e++eTZCTll+LOONdqJ5VqUr64SbpuNvtGqiapsVlzPwF/v0jF9sGNUWi3E2NaOdR5Uoniuv5ia+wjs4pwNzIX/lG5uBCchZZWWng40Q0+DcT3LSTFdf1V27FZcz8B71IKETStEUozEsRefm1QXNdfooxNSn4p+h4LQRcHPfgNchAsLY6MjBRL+eJCcV1/fWtseHwGEy5+jte9/aq3r1JNypckimvpJRWJJR0dnQpnJeXn5wOo3lXbGIbBX3/9hX///Rdz586tcBlcRTp27IiDBw8iJCSkWoml3bt3Y82aNdUqW5x0dHQwffr0bx4XkVmENf8m4O8+9jDWrP5O9tUtXxIkXTebfSNVk8TYnP6QiXWPEnF5pPPnpT+tZoi1/OqiuK6/6mrs43KKcfldOu5F5cE/KgfR2SVooKuKzg66ODPUCb2d9MS+9JPiuv6qzdhcD8vG7/97X26gp4bIDPGWX1sU1/VXTceGU8rDgBOhsNBWxaEBDt/cr47imrChqrFhGAbzb8TgflQuHk50r/BCHbUpX9IorqWXVKyRsrW1RXx8PHg8ntD90dHRgserUpZUunv3LmbNmoVOnTrVuA3VPfmeNm0agoKCEBQUBD8/vxrXI6qMjAyMHz8eGRkVnI39D8Mw+OFqNNra6GC0p5HYy5cUSdfNZt9I1cQ5NmHZXPQ7HoqRZ8Pxe9cG6NlQn+KasEISY8NnGHxMK8TuF6kYevgFtFv2g+1vDzD/Rixyirn4sa0lgmd5ImpeExzo74DvnPUlsp8YxXX9JerYBCUWYPS5iG/u80Xv14QNNRmbYi4fw06HI53DxfnhTtBQ+fbHKIprwoaqxmb94yTsf5WGSyOd4WaiIfbyJY3iWnpJRWLJx8cHhYWFCAgIELrf398fhoaGcHZ2rvS5DMNg+/btuHv3Ln744Qd07dq1RnX7+/sDAFxcXKp1vIWFBZo1a4ZmzZrVaEPx2iooKMDhw4dRUFBQ6TF+bzPwKDYPu76zq/EHiuqULymSrpvNvpGqiWNs4nKKMeVSFPpcyQbDMHg1vTEWtrEQW/mioriuvyQxNiPORMBj5ztsDEgCU1KEgueXcXeELZIXNcWp750wvbkpnIzUJb45PcV1/SXK2DyNz0e3I8EY7GaINZ2sxF6+uFBc11/VHZvCUj4GngzD+9RC3BzjAhOt6q0KoLgmbKhsbA69TsMK/3gcH9IQbWqxTJ7imlREKpbCeXt7w8vLC7t27QKHw4GFhQUePHiAly9fYsGCBYKrxW3btg3+/v7Ys2cPTE1NAQB79uzB7du30bVrV9ja2iI4OFhQroqKChwdHQEAHz58wKlTp+Dj4wMzMzOUlpYiKCgIN2/ehKenJ1q2bFn3HRcTTikPa+4n4M8nyfijWwM4Gqqz3SRCJO51cgH+fJKME+8z0dRcE0e66mJEm+oliAmRJZ/SCnHmYyYeTnRDmwY6iI2NxRkAjoaSTyQRIqoHMbnodywUozyN8VdvW7p4ApFZnFIeBp4IQ3hmEe6Nd4OdvnxdSZrUD9fDsjHtcjR29rFDPxfaP4iIn1QklgBg6dKl8PPzw7Fjx5CXlwdra2ssWrQI7du3FxzD5/PB5/PBMIzgvufPnwMA7ty5gzt37giVaWpqin379gH4vBGXkpISTp48idzcXCgoKMDCwgIjR47EwIEDZfaKcPejczHtchSKuQwujnBGLyd9tptEiMQUlPBw/H0G9r9Mw7OEAnR31MPVUc7oYq+LqKgotptHiERsDUxGB1udWn27SEhdYRgGWwKTseROPGa3NMOG7g0oAUpk1ovEfMy6GoPMQi7ujXeDjR4llYjsCU4vxIgz4VjWzgKTm5my3Rwip6QmsaShoYEpU6ZgypQplR4zb948zJs3T+i+ssTRt1haWmLlypW1aSKrFBUVYWBgIEiAMQyDpXfiselJEqY3N8VvXRpAR4TN1yorvy5Jum42+0aqVpOxyeCUotuRECTmlWBsE2McGuAAF+Oq14ZTXBM2iHNsMov4OPo2C8cGN5RI+TVFcV1/VWdssgq5mHgxEv5RuTg80AHDG1d/v0eKa8KGysYmMa8Ey/3jceR1OoY1NsT57k6w0FEVW/l1geK6/vpybHKKuBh4IgxdHfWwokPVS5JFKb+uUVxLL6lJLJGqWVtbIzMzE8DnpNKCm7E48CoNN0a7oIuDnljLr2uSrpvNvpGqVXdsypJKKkoK+DTLEwYa1XvrorgmbBDH2GRwSnE5NBu7nuTCUkcVfZz1xVq+qCiu669vjU1weiH6HQuFpooink1p9M3Ef03LlySK6/rr67Ep5fHx55Nk/PIgEW4mGnjwvyXI4iq/LlFc119lY8NnGPQ/HgpVJQUcGuAgtiXJFNekIpSKkxFcLheJiYkoLS3Fwpux2P8yDVdHiSep9GX5XC5XLOVJU91s9o1UrTpj82VS6cZol2onlapbvqRQXNdfoo5NEZeP3S9S0fXwJ1hsfIWld+LgqKuEs8OcoKT4/5NBimvChqrG5m5kDtru/whPc008nuRe46TSt8qXNIrr+uvLsXkcmwfv3R+w+UkytvW2xZPJ7rVegkxxTdhQNjYr78QgIC4f54Y5QVtV9JUtlZVPcU2+RIklGZGYmAgrKyv8cOI59r1Mw7XRLvC1Ed9+G2XlJyYmiq1Maambzb6RqlU2Nol5JTjyJh1jzkWg0Y53IiWVqiq/LlBc1181HZtSHh97g1Lh8tdbrLoXDy9zLfiPd0P8gqb4xUcHnmaatSpfnCiu66/KxmZPUCp6/xOKad6mOPV9Q2iJ+OGF4pqwoWxsxh4ORMdDn9DaWhsfZ3livJeJWGZ3UFwTNpSNzR/X3+L4kIZiv7ATxTWpCC2FkxFlG5Yff5eJ6zM7iDWpRIi0yC3mYdz5CFwKyYaZlgq6OupifXcbDHIzEOs3LYRIi7SCUgw4EYrg9CL82MYCs1qZUawTmVDK42Px7Tjsep6K3X3tMN7LhO0mEVJjV0OzAQAvkzi4N74JnV8TuRCcVggA+I+vBbo7imd1CyHfQoklGbElMBkAcHCAPdrZ0h89In+is4vR/3goeHwGT6e4w9tCi64kRORaWEYRvvsnBEaayvg40xNm2ipsN4mQaknJL8XwM+EITi/ErbEuaG+ry3aTCKkRPsNgpX88/rgWDQC4MsoZDSmpROTAuxQOxpyPAABM8aYrwJG6Q0vhZMC/0bn462kKAKCVNf3RI/InKDEfPvs+wEJHBY8nuaO5pTYllYjcYhgGd/63J00jUw3cHedKSSUiM4IS89F8z3uU8Ph4PrUxJZWIzMkr5mHQyTDsepGKgwMdAACqSvSRiMi+Zwn56HTok2BvMDqXJnWJZixJuZwiLsZfiMSUtg5wtNwAfX19idSjr6+PDRskVz6bdbPZN1I1fX19jFywGiOvpGCSjz229LKFsqL4/ghSXBM2VDY24ZlFOPY2A8fepSM8sxizW5lhY3cboY25a1N+XaC4rr/09PQwcM5KDL+cgslt7LG5hw3UlMX3YZzimtSFyKwiDDgeBh7DIHByI5iplMjt2FNc1y/3onIx4EQoRnkY47d2DdE2Tz7HnuJaelFiScrNvh4DbVUlbO7nDg2VxhKrR1dXF4sWLZJY+WzWzWbfSOUKSnj4JTAbp/V6YXMPG8xqZS72OiiuCRu+Hpu8Yh4mXozEuU9Z8DTTwKRmphje2BAN9NTEUn5doriun0p4fCy8n4EbJn2wu49k9lOiuCaS5h+Vi2Gnw9DKWhv/DHKEnroyAHW5HXuK6/rjckgWhp0Ox5xW5ljX1RoKCgpyO/YU19KL5n1KsRPvM3DqfSaODHRAYV42Zs2ahczMTInUlZmZKdHy2aybzb6R8hiGwdmPmWi04x1OPo9Cz7B9GOmkKpG6KK4JG74cm+jsYrQ78BEfUgvxfGojvJrugR/bWoicVPq6/LpGcV3/pHNK0f1ICK6/i0WfiH3oZyOZzeUpromkMAyDnc9S0MsvBJOamuLicOf/JZXke+zluW/k/469S8eQU+FY1dEKv3drAAUFBbkee3num6yjxJKUisspxsyr0VjbyQpNLbSQn5+PHTt2ID8/XyL1Sbp8Nutms29EWEh6IXr6hWD0uQiM8zLGreE2uOy3Vy7HnuK6/iobm3shyWi99wPMdVQQMNkdzSy0xFo+xTWRtI9phWi99yMKuXxcGGSN04f2yOXYU1zLt8dx+Vh0Kxb7+9vj924NhJYfy/PYy3PfyGe7X6Ri/PlIbOlpg//4Wgrul+exl+e+ybp6txSusLAQfn5+ePz4MfLy8mBtbY3Bgwejffv2bDdNgM8wmHgxCp5mmljYxoLt5hBSa/klPPz6IBF/PklGV0ddvPvBAw0N1REbG8t20wiRmFFnIzC9iyc29rAR695hhNSFG+HZGHEmAt0d9XBwgD3SkxLYbhIhIvG10UHwbE/Y1GKmKCHSxj8qF3Oux+DAAAeM9jRmuzmE1L/E0rp16xAWFoZx48bB0tISDx48wMaNG8EwDDp06MB28wAAWwOT8SKxAK+nN67xpq6ESJtPaZ9nKSkrAqeGNkRfZ326SgWROxmcUrxM4uBlUgHuvIoEAKzuZIUlvWxZbhkhNcMwDLY/S8HCm7H4qb0lVnSwgiK9ZxMZR0klIm862ekgYJI7vC3FMxuakNqqV4mlFy9e4PXr11i4cKEgieTp6YnU1FQcPHgQvr6+UFKSzN4B1fU2hYNld+Oxt589bPWF/wiqqEj2ctSSLp/NutnsW33nYKCGea3NML25GTRUyq++leexl+e+1XdZhVzsfJ4iSCbF5pRATUkBTcw10VBLBcoqKhjpIblvECmuiSSU8viYez0Wh16n4cggRwxvbCT0uDyPvTz3jVRNnsdenvtW3ykoKFSZVJLnsZfnvsmyepVYCgwMhIaGBnx9fYXu79KlCzZt2oTQ0FC4ubmx1DqgiMvH2HMRGOBqgFEewidzNjY2KCkpkVjdki6fzbrZ7BsB1JQVMd+n4iWd8jz28tw3AqgoKeBGeA6ammuij7MVvC214GasDhWlz8nToxPlc+wpruVbUBIHV8OycW+8G1pZaws9Js9jL899I1WT57GX576Rqsnz2Mtz32Rdvdq8OyYmBtbW1uVmJdnb2wseZ9OF4CxkFfGw8zu7ckuF+Hw+cnNzwefzJVK3pMtns242+0aqJs9jL899I4C2qhIeTnTHtt52mNDUBJ5mmoKkkjyPvTz3jQCtrbURMtuzXFIJkO+xl+e+karJ89jLc99I1eR57OW5b7KuXiWW8vLyoK1d/mSp7L68vLy6bpKQ4Y2NEDStEQw0yk8ki4+Ph56eHuLj4yVSt6TLZ7NuNvtGqibPYy/PfSNVk+exl+e+kc/UlSs+NZTnsZfnvpGqyfPYy3PfSNXkeezluW+yrkaJpcWLF5d7kWUtm1fVpsHV2VA4KSkJL1++xMuXL/Hp0ydxNg0AYKxJazoJIYQQQgghhBAiG2qUWNq0aRMSExMFP/N4PKioqODly5dib5gk6OjoVDgrKT8/HwAqnM30td27d8Pb2xve3t4YPXq02NtICCGEEEIIIYQQIitqtHk3wzDVuk9a2dra4uHDh+DxeEL7LEVHRwse/5Zp06ahX79+AIDXr19j0qRJ5WYuxcfHIzs7W2ztBj7PlAKAd+/eIT09vVZlVdQ+cZZfU1/XLe7XT9x9k8T4ssXV1RWamppC9xUWFgIAxXUtUVyzh+Jaciiu2UNxLTkU1+yhuJYcimv2UFxLDsU1eyqKayFMDSgoKDBPnz4V/MzlchkFBQUmKCioJsWw5sWLF0zfvn2ZBw8eCN2/atUqZty4cQyXy61ReX5+fgwAutFNZm8V/e5SXNNN1m8U13STxxvFNd3k8UZxTTd5vFFc000eb9/K+SgwTPWnHCkqKiIwMBAtW7YE8P+lcC9evECzZs2qWwyrVq5cifDwcIwbNw4WFhZ48OABbt26hQULFqBjx441Kis9PR03b96EnZ0dNDQ0JNNgQiSooswzxTWRdRTXRB5RXBN5RHFN5BHFNZFH35qxVOPE0uHDh9GoUSMAnxNLrVq1gp+fH1xdXcsdL43JpsLCQvj5+eHRo0fIy8uDtbU1hgwZgvbt27PdNEIIIYQQQgghhBCZUuPE0tdXTmMYptL7eDyeeFpJCCGEEEIIIYQQQqROjTbvPnjwoKTaQQghhBBCCCGEEEJkTI1mLBFCCCGEEEIIIYQQUqZGM5ZIebGxsXV+mUVCxMHY2Bg2NjYVPkZxTWQVxTWRRxTXRB5RXBN5RHFN5FFVcS1Q5TXjKvH+/Xtm0qRJjJOTE6OlpcVoaWkxTk5OzNSpU5mPHz+KUqRMiomJYTQ1NVm/9B/d6CbKTVNTk4mJiaG4pptc3Siu6SaPN4prusnjjeKabvJ4o7immzzeKovrL9V4xtKxY8cwYcIElJaWwsLCAh4eHmAYBrGxsdi7dy8OHz6Mo0eP4vvvv69p0TInPT0dHA4Hfn5+cHNzY7s5hFTbp0+fMHr0aKSnp5fLPlNcE1lFcU3kEcU1kUcU10QeUVwTeVRVXH+pRoml2NhYTJkyBY0bN8bu3bvRvHlzocefPXuG6dOnY+LEiWjdujUaNGggWutljJubG5o1a8Z2MwgRK4prIo8orok8orgm8ojimsgjimsirxRrcvCePXugr6+Pu3fvlksqAUDLli1x584d6OjoYO/evWJrJCGEEEIIIYQQQgiRPjVKLN2/fx8TJ06Evr5+pccYGhpi0qRJ8Pf3r23bCCGEEEIIIYQQQogUq1FiKTQ0FK1atfrmca1atUJoaKjIjSKEEEIIIYQQQggh0q9GiaWcnBwYGRl98zgjIyPk5OSI3ChS916+fIlJkyahRYsWsLe3R5MmTdC3b1+sWbOG7aZV28mTJ2FlZYU3b96Ircy7d+9i06ZNYiuPSLeyGHJwcEB8fHy5x4cMGYLOnTvXuNzz589Xujw4Li4OY8aMQaNGjWBlZYWVK1ciLi4OVlZWOHnyZLm2xcXF1bh+Il/KYqGi29q1a1lpU6tWrTB27FhW6rayssJPP/3ESt2kblUW91/fAgICalRuQEBAuedV9fd/27ZtuHHjRq36QuqvsWPHws3NDQkJCeUey8rKQtOmTdG/f3/w+fxa17Vp06Zq/c4MGTKkWuWJeh5EZJ8kPmeVCQ0NxaZNm+gcV8bVaPPu0tJSKCkpffM4RUVFcLlckRtF6tadO3cwYcIE+Pj4YPny5TA1NUVqairevHmDixcvYtWqVWw3kTX+/v44dOgQFi5cyHZTSB0qLi7GH3/8gb/++kss5Z0/fx4hISGYMmVKucdWr16NV69eYdOmTTAxMYGZmRkYhil3XNeuXXHp0iWYmpqKpU1E9m3evBkNGzYUus/c3Jyl1hAieZcuXRL6ecuWLQgICMCpU6eE7nd2dq5RuR4eHrh06ZLQ86r6+//XX3/hu+++Q8+ePWtUDyEAsHHjRnTu3Bk//vgjjh07JvTY8uXLkZ+fjy1btkBRsUbf/1doxIgR6Nixo+Dn1NRUTJ48GRMnTsSAAQME9+vo6NS6LkJEFRoais2bN8PHx6feXPxLHtUosQR83mepom/yv0TL4GTLrl27YGNjg2PHjkFZ+f8h0b9/fyxfvpzFlhHCjk6dOuHChQuYPn06GjVqJNG6goOD0bRpU6EPKBV9Y2NkZFStGaOk/nB1dUWTJk3YbgYhdcbb21voZyMjIygqKpa7v6Z0dHRqXUZt8Xg8cLlcqKmpsdoOInmmpqb47bffMGPGDBw9ehRjxowBAFy/fh0XLlzAb7/9Bnt7e7HUZWlpCUtLS8HPZecXVlZWrMc8IdKCYRgUFRVBQ0OD7abItBqnwpcsWYIhQ4ZUeVu2bJkk2kokJCsrCwYGBkJJpTJffltSttTh3r176NGjBxwdHdG+fXucOHFC6DkZGRlYunQpOnbsCCcnJ3h6euL777/H06dPhY4rW+6zc+dObN26FS1atICDgwN69eqFhw8flmtLeHg4fvjhBzRp0gT29vZo0aIF5syZg+LiYqHj8vPzsWTJEjRu3BiNGjXC5MmTkZycLHTMxYsXMWLECDRt2hSOjo7o0KEDfvvtN3A4HMEx8+bNw6FDhwAIT7+naZryb8aMGTAwMMBvv/1W5XEMw+DQoUPo1q0bHB0d4e7ujilTpiAmJkZwzJAhQ3D37l3Ex8eXW6phZWWF6Oho+Pv7fzO+vl4KFxkZCRcXF0ydOlXouEePHqFBgwZYv359LV8FIouioqIwf/58tG3bFo6OjvD29sa4cePw6dOncsfm5ORgzZo18PHxgb29PTw9PTFmzBiEh4cLjikpKcGWLVvQvn172Nvbw8PDA/Pnz0dGRkaF9V+/fh1du3aFg4MDfHx8sH///nLHJCQkYPbs2fD09IS9vT06dOiAv//+u9yyj6ysLCxduhTe3t6ws7ODj48Pfv/993Lv+V9jGAbr1q2Dra0t/vnnn+q8bEROTJ06FZ06dRK6b9y4cbCyssLly5cF97179w5WVla4desWgPJL4ar6+29lZQUOh4PTp09XuIwoNTUVixcvFsRt69atsXnzZqGZ/F+e/2zZsgWtW7eGvb19jZfwEdnVr18/9O/fHz///DPi4uKQmZmJJUuWoH379hg3bhxu3bqFvn37wtHREc7Ozhg+fDhevHghVMa8efMq3Pu2bPlbdVW21L6iJaJlnj59ij59+gj+zqxfvx48Hk/omJr+/SCyZd68eXByckJUVBTGjBkDJycnNG/eHGvWrCn3d/rw4cPo2rUrnJyc4OzsjPbt22PdunUAPsfftGnTAADff/+94H21bDuIBw8eYMKECfD29oaDgwPatm2LxYsXIzMzs1ybbt68ia5du8Le3h4+Pj7Yt29fhb8PZUvojxw5gg4dOsDe3h6nT58G8Hk2eJ8+fdCoUSO4uLigR48eOH78eLnVBGWfi2/fvo3u3bsLPk/evn1b0K8OHTqgYcOG+O677ySyhFDa1GjG0r179yTVDsIib29vHDt2DCtWrMDAgQPh4eEBFRWVCo/9+PEj1q5di5kzZ8LExATHjh3DwoULBSdPwOcPAwAwf/58mJqaoqCgADdu3MCQIUNw8uRJtGnTRqjMgwcPwtraGmvWrAGfz8euXbswZswYnDlzBs2bNwcAfPjwAQMHDoShoSEWLVoEe3t7pKam4tat/7Z332FNXW8cwL9J2HsvWeICJ+JEcVVbq3XvjXXXarVq66h71Na6fnXgaOvCulq1WvdGEReKe4KyZO8RQsb5/UGJRoZkkRDez/PwKDc3576H9yUk55577lkIhUKZM3zfffcdOnfujE2bNuHt27dYvnw5pk6dKn3BAIo+fH3yyScYN24cTExM8OrVK2zevBn37t2T7jd9+nTk5+fjxIkTMtPv6VIk3WdmZoZp06Zh4cKFuHbtGgICAkrdb/bs2Th48CDGjBmDH374AZmZmVi3bh169+6Nc+fOwd7eHj/++CO+//57REdH47fffpM+t27dujh27BjGjRsHDw8PLFiwAACkl6J+jJeXF1atWoXJkyfj999/x9ixY5GcnIwpU6agVatWdPlmNVA8w+F9SUlJsLa2xrx582Bra4vMzEwcOnQIPXr0wJkzZ6SXzuXm5qJv376IjY3F5MmT4efnh7y8PNy4cQNJSUmoXbs2JBIJxowZg5s3b2Ly5Mlo1qwZ4uPjsXr1agwYMAAnT56UObv3+PFjLFq0CDNnzoS9vT2OHDmChQsXQigUYtKkSQCKTjz06tULQqEQ3333Hdzc3HD+/HksW7YM0dHR0jeaBQUFGDhwIKKjozFz5kzUr18fN2/exMaNG/H48WPs2bOn1J+JQCDAt99+iwsXLmDnzp0lBhmIbmvXrh1OnDiBpKQkODo6QiQS4caNGzAyMsLVq1fRs2dPAMDVq1ehp6dX4v1IsfL+/h87dgyDBg1CmzZtMH36dADvLiNKTk7GF198AS6Xi2+//RYeHh4IDw/Hr7/+itjYWKxbt07mOL///ju8vLywYMECmJubq2yWCqkaVqxYgRs3bmDGjBmwtbWFUCjEmjVrcOTIEUyZMgUdOnTA5s2bIRAIEBQUhIEDB+LAgQNo2bKlRuNOTk7G5MmT8fXXX6NWrVq4cOEC/ve//yErKwsrVqwAALn/fpCqSSQS4csvv8SQIUMwYcIE3Lx5E+vXr4eFhQW+/fZbAEUn8+fNm4cxY8Zg4cKF4HA4ePPmDV6+fAmgaKmHOXPm4KeffsKKFSvQqFEjAICnpycA4M2bN2jWrBmGDh0KCwsLxMbGYtu2bejTpw8uXLgg/cx66dIljBs3Dq1atUJQUBBEIhG2bNmC1NTUUmM/ffo0bt68iW+//Rb29vaws7MDUDTwP2LECOlMv7t372L+/PlITEyU9qnYkydP8NNPP+Gbb76Bubk51q5di/Hjx2PKlCm4du0a5syZAw6HgxUrViAwMBBhYWG6XfeMKCw8PJwBYOHh4ZoORSlpaWmsT58+zMXFhbm4uDAPDw/Wq1cvtmHDBpabmyvdr2XLlszLy4vFxcVJt/H5fFa/fn32/fffl9m+SCRiQqGQDRo0iI0dO1a6PSYmhrm4uDA/Pz/G5/Ol23Nyclj9+vXZ4MGDpdsGDhzIfHx8WGpqapnH2b9/P3NxcWFz586V2b5582bm4uLCkpKSSn2eRCJhQqGQhYWFMRcXF/b48WPpY/PmzWMuLi5lHrOqKq92daWuFVFcQxEREUwgEDB/f3/WrVs3JpFIGGOM9e/fn3Xq1IkxxtidO3eYi4sL27Jli0wb8fHxzMvLiy1fvly6beTIkaxly5alHrNly5Zs5MiRMtuKfzf2799fIraYmBiZfefMmcM8PT3ZnTt32MCBA1njxo1ZYmKi4j+EKqy61HVxLZT2JRQKZfYViUSssLCQtW3bli1atEi6fe3atczFxYVduXKlzOMcPXqUubi4sBMnTshsj4iIYC4uLmznzp3SbS1btmQ1atRgjx49ktl3yJAhrF69eiw/P58xxtiPP/7IXFxc2N27d2X2mzNnDqtRowZ79eoVY4yx3bt3MxcXF3bs2DGZ/TZt2lQibhcXFzZv3jyWnp7O+vTpw/z8/ErEUZVVl7pWxLRp01jt2rWl379+/Zq5uLiwQ4cOMcYYu3XrFnNxcWHLly9nrVu3lu43ZMgQ1qtXL+n3oaGhzMXFhYWGhkq3lff3v3bt2mzatGkltn///fesTp06Mu+TGGMsKCiIubi4sOfPnzPG3r3Gt2nThhUWFsrfcR1AdV3kwoUL0tfvv/76i4nFYubn58c6d+7MxGKxdL/c3FzWuHFjmbqdNm1aqe8tVq9eXWbtFtdeUFCQdFtZ7y9K+73o378/c3FxYWfOnJHZ97vvvmOurq7S2pfn74cu0eW6fv89MmNF9Vfa3+kRI0awdu3aSb//4YcfmI+PT7ltHz9+vEStlab4M1tcXFyJOuzevTtr3rw5EwgE0m25ubmsQYMGJX4fXFxcmLe3N8vIyCj3eGKxmAmFQrZ27VrWoEED6ecBxt59Ln779q1026NHj5iLiwtr2rSp9H0PY4ydPn261N+bqqKitSv3pXAPHz4sd42luLg4PHz4UO4BLqI5NjY2OHLkCE6ePIl58+bhs88+Q1RUFFauXInOnTvLTDWsX7++zHRCIyMjeHl5lbizxe7du9G1a1d4eXnB3d0dHh4euHbtmnR0+n3dunWDkZGR9HszMzN8+umnuHnzJsRiMfh8Pm7cuIEePXpUaI2Zzz77TOZ7Hx8fAJCp2+joaHz99dfw9fWFm5sbPDw80L9/fwAoNUZS/RgYGOD777/H/fv3SywYCxQtes/hcNC/f3+IRCLpl4ODA+rXr4+wsLBKiXPx4sWoW7cuBg0ahLCwMGzYsAGOjo6VcmyiWf/73/9w8uRJmS+g6I5VHTt2hKenJ9zd3eHp6YnXr1/LXOJ26dIleHl5oX379mW2f/78eVhaWuLTTz+VqfEGDRrAwcGhRI3Xq1evxJpkffr0QU5OjvR9QWhoKOrWrYumTZvK7Ddo0CAwxhAaGirdz8TEBD169CixH1B0yef7YmJi0KtXL+Tk5OD48eNqXxuNaCdPT0+4ublJL6cPCQmBj48P+vXrh5iYGLx58wYCgQC3bt1Cu3btVH788+fPo02bNtLZUsVfxXfR+vB35tNPPy1zhjipHj755BP4+fmhZs2a6N+/PyIjI5GYmIj+/fvLLEdhamqK7t274+7du+Dz+RqMuOh9+ofvtfv06QOJRIIbN24AkP/vB6maOBwOPv30U5lt9evXl/lc6Ovri6ysLEyePBlnzpwp9RK28qSmpmL27Nlo3ry59DNl8ay94s9s+fn5uH//Pj7//HMYGBhIn2tqaloivmJt27aFlZVVie3Xrl3D4MGD4e3tLf2MuHr1amRkZJSY/dSgQQM4OztLv69Tpw4AwN/fX2ZmUvFs8dLuBKlL5LoULiQkBF26dEFYWBhcXV1L3ScpKQn+/v44fvw4unbtqpIgSeVo0qSJdCFYoVCIFStWYPv27di8ebN0EW9ra+sSzzM0NERBQYH0+61bt2Lp0qUYOXIkvvvuO9jY2IDH4+GXX34pddDG3t6+xDYHBwcUFhYiLy8PeXl5EIvFMr+45fkwxuIXmOIY8/Ly0K9fPxgaGuL777+Hl5cXjI2N8fbtW4wbN06mL6R66927N7Zs2YJVq1ahe/fuMo+lpqaCMVbm4skeHh6VESIMDQ3Rt29fLFu2DI0aNSp3oIDoljp16pSovwULFmDnzp2YPHky/P39YWlpCS6Xi1mzZsm8tqWlpX10DY6UlBRkZWVJp6N/6MM3h2W9lgPvLpHOyMgo9f1D8WDo+/s5ODiAw+HI7GdnZwc9PT3pfsUiIiKQnp6O2bNnyyxUS6qfgIAA6dINV69eRbt27eDj4wN7e3tcvXoVNWvWREFBgVoGllJTU3Hu3LkyX/8//J2hkwAEKPo7Xvxetfi1rbRlFxwdHSGRSJCZmanRy2mKLxl634ev9fL+/SBVk7GxsczkAKDoc9f77zcGDBgAsViMvXv3Yvz48ZBIJPD19cX333//0fesEokEQ4cORVJSEqZPnw5vb2+YmJhAIpGgZ8+e0uNkZmaCMVZqbZb23gQo/Xfs3r17GDZsGPz9/bFq1So4OzvDwMAAp0+fxq+//lriM+KHA1PFv8dlbf/YGpFVnVwDS5s2bcKAAQPKvYtAs2bNMHjwYPz22280sFSF6evrY8aMGdi+fTueP38u13MPHz4sXWT1fbm5uaXun5KSUmJbcnIyDAwMYGpqCn19ffB4PCQkJMgVR1lCQ0ORmJiIv/76C/7+/tLtWVlZKmmf6A4Oh4N58+Zh6NChJRYBtrGxAYfDwZEjR2TOjhQrbZs6PHv2DL/88gt8fX0RERGBrVu3ShdBJNXP4cOHMWDAAMydO1dme3p6OiwtLaXf29rafvQ11cbGBtbW1mUugG1qairzfVmv5cC7AX9ra+tS1xBLSkqSHrN4v3v37oExJjO4lJqaCpFIJN2vWK9evWBvb4+ff/4ZEolEuvYNqX4CAgKwb98+3Lt3D/fu3cO0adMAFJ2dDgkJQVxcHExNTeHn56fyY9vY2MDHxwezZ88u9fEPB5I+HDglpPi1sqzXSS6XK/3QamhoiMLCwhL7yTtoUzww8OGH3rLaKW3Nmg9f6+X9+0F02+DBgzF48GDk5+fjxo0bWLNmDQIDA3H16tUyJ6sARe9xnzx5gnXr1klnLANFa+W+z8rKChwOp9za/FBpr7///PMP9PX1sWvXLpkBs9OnT3+0j0TOu8KFhoaiT58+H92vV69e0qmQRPsVv6H/UPHsInnPqHE4nBK3y33y5AnCw8NL3f/UqVMyI8C5ubk4d+4cWrZsCR6PB2NjY7Ru3RonTpxQ6RmODz/4BwcHl7mPpqcdE81p37492rdvj3Xr1iEvL0+6vUuXLmCMISEhQTrb7/2v4kswgZKz+lQlPz8fEydOhJubGw4dOoQvv/wSK1euxN27d1V+LFJ1fPjadv78+RJ3xuzUqROioqJKXFL2vi5duiAjIwNisbjUGi+e2l3s+fPnePz4scy2o0ePwszMTLoYZ9u2bfHixYsSl8z/9ddf4HA40sWUAwICpDd++HC/4nY+NH36dCxZsgSrV6+WLgJOqp+AgABwOBz88ssv4HK50huLtGvXDtevX8fVq1fRqlWrj16CVt7f/w/PyBfr0qULnj9/Dg8Pj1J/Z5ycnFTQQ6LLatWqBScnJxw5ckTmLlT5+fk4efIkmjVrJp2t5ObmhtTUVJlB/cLCQly+fFmuYxZ/sP/w7qHFd038UG5ubonHjh49KvP7Ju/fD1I9mJiY4JNPPsE333yDwsJC6eSFD68uKVY8+PPh58oPP7OZmJigSZMmOH36tMxga15eHs6fP1/h+DgcDng8Hng8nnQbn8/H33//XeE2qjO5ZiylpKRU6PaVzs7OFbqrEdEOw4cPh7OzM7p06SK9E9Djx4+xbds2mJqaYuzYsXK116VLF6xfvx6rV69G69atERkZifXr18Pd3b3EHYwAgMvlYujQoZgwYQIkEgk2b96M3NxczJo1S7rPokWL0LdvX/To0QNff/01PD09kZqairNnz+Lnn3+GmZlZheNr3rw5rKysMGfOHMyYMQN6eno4cuQInjx5UmJfb29vAMDmzZvRqVMn8Hg8+Pj4VNpsFKIdfvjhB3z++edITU1FvXr1AAAtWrTA8OHDMWPGDDx48ACtWrWCiYkJkpOTcevWLXh7eyMwMBBAUR2dPHkSu3btQuPGjcHlcsu8hE4es2fPRnx8PE6cOAETExMsXLgQ4eHh0uvY35+hQqqHLl264NChQ6hduzZ8fHzw8OFDBAUFlbiUePz48Th+/DjGjBmDr7/+Gk2bNkVBQQHCwsLQpUsXtG3bFr1798aRI0cwcuRIjBs3Dr6+vtDT00NCQgKuX7+Orl27olu3btI2HR0d8eWXX2LmzJlwcHDA4cOHERISgh9++EH6QWjChAn466+/MGrUKMyaNQuurq64cOECdu3ahVGjRqFWrVoAiqbO79y5E9OnT0dsbCy8vb1x+/ZtbNiwAZ988kmZ0+fHjRsHU1NTfP/998jLy8OyZctoVkg1Y2dnB29vb1y5cgVt2rSR1l67du2QmZmJzMxMLFq06KPtlPf338fHB2FhYTh79iwcHR1hamqK2rVrY9asWQgJCUHv3r0xZswY1KpVCwKBALGxsbh48SJ++uknulSTlIvL5WL+/PmYMmUKRo0ahZEjR0IgEGDLli3Izs7GvHnzpPv26tULq1evxldffYWvvvoKAoEAf/zxByQSiVzH9PX1Ra1atbBs2TKIxWJYWlri1KlTuH37dqn7W1tbY+7cuYiPj4eXlxcuXLiAvXv3YtSoUdLPifL+/SC667vvvoORkRGaN28OR0dHJCcnY+PGjbCwsICvry+Ad6+3e/fuhZmZGQwNDeHm5obatWvD09MTP/74IxhjsLKywrlz5xASElLiOLNmzcKoUaMwbNgwjBs3DmKxGEFBQTA1NUVmZmaFYu3cuTO2bduGr7/+GiNGjEBGRga2bNlCn/sqSK6BJVNT0wrNGMnIyICJiYnCQZHK9c033+Ds2bPYvn07kpOTUVhYCAcHBwQEBGDq1KnShcjkaY/P52Pfvn0ICgpCnTp18NNPP+HUqVOlLtb35ZdfQiAQYMGCBUhLS0PdunWxe/dutGjRQrpPgwYNcOLECemZ6Ly8PNjb26Nt27ZyL3xpY2ODXbt2YenSpZg6dSpMTEzQtWtXbNmypcTlm3379sWdO3ewa9curFu3Dowx3LhxA25ubnIdk1RtDRs2RJ8+fXDkyBGZ7atWrUKzZs2wZ88e7Nq1CxKJBE5OTmjevLnM4sRjx47F8+fP8fPPPyM7OxuMMaUX8Pvzzz9x+PBhrF27VjrYZWBggKCgIHz++eeYMWMGfv/9d6WOQaqepUuXQl9fHxs3bkReXh4aNWqE3377DatWrZLZz8zMDEeOHMGaNWuwd+9erFu3DpaWlmjSpAmGDx8OAODxeNixYwd+++03/P3339i4cSN4PB6cnZ3RunVr6RvBYg0aNMDgwYOxZs0avH79Go6Ojli0aBEmTJgg3cfW1hbHjh3DypUrsXLlSuTm5sLd3R3z58+X2c/IyAiHDh3Czz//jC1btiAtLQ1OTk6YOHEiZsyYUe7PYOjQoTAxMcE333yD/Px8rF69WmYRXKL7AgIC8PTpU5l1lGrUqIGaNWvi9evXFVpfqby//0uWLMEPP/yAyZMng8/nw9/fH3/99RccHR1x6tQprF+/Hlu2bEFCQgJMTU3h7u6Ojh07lrpQLCEf6tu3L0xMTLBhwwZ89dVX4HK58PPzw8GDB2XeG7u7u+OPP/7ATz/9hAkTJsDR0RETJkxAWloa1q5dW+Hj8Xg87Ny5E/Pnz8ecOXNgYGCA3r17Y/ny5Rg1alSJ/R0cHLBixQosW7YMz549g5WVFaZOnSpzQljevx9Ed7Vs2RIHDx7E8ePHkZWVBRsbG7Ro0QL/+9//pDdlcnd3x5IlS/D7779L12Rau3YtBg8ejJ07d2LhwoWYPXs29PT0EBAQgP3790sX8C7WqVMnbN++XTrYam9vj8DAQCQlJVV4xlFAQADWrl2LTZs2YfTo0XBycsKwYcNgZ2eHmTNnqvxno2s47P15lh/Rrl07NG7cGJs2bSp3v8mTJ+PBgwflTrHXBXfv3kWzZs0QHh6ulmv1dV1sbCxat26NBQsWYNKkSZoOp1opr3aprklVRXVNdBHVNdFFVNdEF1FdaxehUIjPPvsMTk5O2Ldvn6bDqbIqWrtyncIbPHgwfv/9d1y5cqXMfS5duoQdO3Zg6NCh8jRNCCGEEEIIIYQQIreZM2fin3/+QVhYGP755x8MHToUL1++xFdffaXp0KoFuS6FmzBhAnbu3InPPvsM48aNQ+/evVGzZk0ARauzHz16FL///juaNGmC8ePHqyVgQgghhBBCCCGEkGK5ublYunQp0tPToaenh0aNGmHPnj1lrstIVEuugSUDAwOcOXMGI0eORFBQELZs2SLzOGMM3bp1w+7du2mRK/JRbm5uSq8zQwghhBBCCCGketu6daumQ6jW5BpYAooW3jx58iTu3r2Ls2fPIiYmBkDRoltdu3aVWbCWEEIIIYQQQgghhOguuQaWQkJC4OfnBzMzM/j5+ZW5eFNqaiqOHTuGMWPGqCRIVcrPz8eBAwfw+vVrREVFITs7G0OGDMGwYcM0HRohhBBCCCGEEEJIlSLXwFKnTp0QFhYmvb2fRCKBkZERbt68KTNTKTIyEuPHj9fKgaWcnBycPXsWnp6eaN26Nc6ePatwW3w+HwAQERGhougIqRxPnz4t8zGqa1JVUV0TXUR1TXQR1TXRRVTXRBeVV9fvk2tgiTFW4nuRSFRiuzZzcHDAn3/+CQ6Hg+zsbKUGljIzMwEAY8eOVVF0hFQeExMT2NnZldhOdU2qMqproouorokuoromuojqmuiisur6fXKvsVTVcTgclbXl7OwMAAgODoaPj490e1xcHFxdXVV2HABISEhAjx498O+//0qPq6jS4lNl+/L68Niq/vmpum/qyK8m2NnZwd3dvcR2qmvVoLrWDKpr9aK61gyqa/WiutYMqmv1orrWDKpr9aK61oyy6vp91W5gSR18fHxk1puysrKCl5eXSo+RmpqKYcOGoVWrVh8dLfyY0uJTZfvy+vDYqv75qbpv6sivNqK6Vg7VtXaiulYO1bV2orpWDtW1dqK6Vg7VtXaiulYO1bX2ooGlKsLOzg579+6tsu1r8tia7Bspny7nXpf7Rsqny7nX5b6R8uly7nW5b6R8upx7Xe4bKZ8u516X+1bVyT2w9Pz5c+jpFT1NLBYDAJ49eyazz4ff65KEhAQkJCQAqPhCVqqQm5uLAwcOYPDgwTAzM1NJm4wx5OXlISMjA3FxcThy5AhatGgBDoeDgoICCAQC8Pl88Pl8FBQUQCgUQiwWQywWQyKRQCwWQyQSQSQSQSKRgDEm/Spu/2PbGGMQCASIjo6Gm5sb9PT0kJOTgx07dsDBwUEl/SzrZydhDAIRQ7ZAjDyhGHmFEuQJJcgWiMEXSpAvlEAglkAkYRCKGfhCCcQMiE3Kg/7LaEgY/vti0n8ZAxjw3r+s6F8AYgnDkIa26FbHSiX90gXqqGtVti8Wi5Gbm4v09HRkZ2cjMzMTmZmZEIvFEAqFKCwshEgkQl5eHgoKCpCZmYm8vDzpthcvXsDDwwNcLhfZ2dkwMTFBx44dMXHixBLHYoxBIGYQiIrqUCRhEEsAMWNIzBUiq0AMoYRBLGEQMwZ+Xi5CTx1F6897w8DYDEJx0fbiumSMQSRh0nYk/7UvlrxXrwDEEkAokSA9MxcmT98g/79jy9Tvf/Vcw1wfa7p6KJsWnVfZdV1YWIiMjAykp6cjPj4eiYmJSEtLQ35+PgQCgfR1u7CwEIWFhdLX3vdft4v3Kd5e/Fjxv6ampvjtt98U7htjDEIJQ6G4qP7E//0/nS/C25xCZBSIIWEM2Tk5uHryCBp36gU9Y1Ow92pVwgCRhEHCimpa9F8bIsn7tf/udVgsYUjLyoHpg0iZ1+te9awxpKGtyvOi67T99fp9jDEUFhZCKBQiLy8PCQkJiI6ORnZ2NvLz88Hn85GVlYXc3FxkZ2ejsLAQkZGR8PT0hJ6eHrKzs2FmZlbme5iy/m9qaoo//vhDGke+UIy0fBFSMrLxz9+HENC9LziGJsgXSsAXSlAgkoAvYsgViJFTKEaOQIx8oeTdewu8/x7jXX0vbKK6ZR2qu8qua4lEgpSUFKSlpaGwsBAFBQXg8/kQCAQQCATIzs5Gbm4uBAIBhEIhBAKB9DVZIpGgoKBA+lX8fry099YAUFhYiJiYGLi5uUFfXx85OTnSugberZ375Zdf4vPPPwcACMUS5BZKpO8fhBKGvEIJhJKi98FF34uRUyhBWmYWrpw4As+2X4AZmEAoZtL3EMWvyQDAUM77Y+k+wNR6DNVjXof6VaXX6/fx+Xzpe+7Xr1/j7du3yM/Ph0gkQm5uLgoKCpCbm4vHjx+jVq1a0NPTQ2ZmJoyNjSGRSCCUAAKuIQTQQwHXCCLwIAQXnw8cCQNzaxSKJRD+9z4kt1AMwX/vIfgiCWpbG2Fhxxpq/9npMrkHlkaPHl1i28iRI2W+Z4ypdC0jbbJ161YsWbKk0o+bnp6OcePG4dNPP61QkWdmZiI6OhpxcXGIjY1FVFQUXr58iZSUFOmH38TERBQUFMg8z8zMDKampjAyMpJ+GRsbw8jICPr6+tDT0wOXywWPxwOXy4Wenh709PTA4/EAFK1hVfz14felfXG5XDDGcOvWLdSrVw8WFhYwMDAAl8sttV8iCUNqvvDdHy4JkPXfQJD4vw/SWQXi9z6YMyTGxWLpuHEI4XoDVk7ILBDjYVI+YrMLpX/03mesx4WxPgcm+jwY8jjQ53Ggz+XAWJ8LHocDYaEQrjaF4HEBLocDLgfgoOj/nP/+X/Tvu++5APT1uDDg6ebvhaLkrWtVtS+RSBATE4PXr18jPj4esbGxSEhIwOvXr5GWlobExESkp6cjKytLpj0ulwtLS0vp74KBgQH09fVhYmICIyMjWFhYwNzcHHp6ehAKhQgNDYW9R23wLJzBN5JAYGGH6yJXpIbEIzFXiJisQkRnChCfU4jcQgkKxaXfCIHLAcwMeNDncsDjAjwOB5LMBCQsn45TkrrQt3aGPo8DLocDHuddLepxOdDjFm3jcTkw4BV9/36t6nE54HE5EORLYKkngqk+D0Z6HJn6Lf7X1lhf5TnSRaqu66ysLERGRuLFixd49eoVIiMjsXPnTmzduhVJSUmIi4uDRCIBABgYGMDJyQm2trYwNTWFgYGB9DXawMAABgYG0tfe91+LeTye9EtfX1/mNZrL5cLMzAxvcwoR+jAa48aNQ4K9L0TmjkhOy4PZqxgUihmS84VIyRMhXyhGgYhJPzhnC8TIKBCX2T89Lgc2xjzocTlAViLils1AQ+OGMLZ1lqlVLue/ev7vtZfHBQx4XPD+q3Xp6zHn3WszjwMY8rjgoOh3gMsBTPVL//tCyqep1+uPEQgEePDgAa5du4bw8HDcunULCQkJyM3NldnPysoKlpaWMDExgYmJifT12tzcHHw+H1evXoWjoyPMzc2l72+Kfw8Yhwsh1xCFXAMUcg1RyDNEIUdfuk3I0UMh1xAF+uYI+P0JEnILkZQrAl9U9HvJMhPB1n8NTpwrjO2c/3ufwYWxHhdGelyYGXBhbsiDuSEPJv+91yiq36L3H9zi13UU/T0Ayv59IvJRR13n5ubi6dOnePToEW7fvo2goCDs27cPz58/x9u3b6Wv18X09PRgaGgIQ0NDmJubw8zMTPq+29DQEDweT/p6/P778+Ltxf++/yXi6oOfW4CbN29Cv+EnEFm7IUvEBc/QFAKOAYRcfRRwDFHANcSVCDPg4V1kFIghKu2N8QeM9biwMORBPzcJMT/ORMBaX1g51oA+jwsTfS70il+jOf99DijxfqLk+wsA4HFEKvn5E+19vQaKJqmEhYXh1atXePPmDZ4+fYqkpCTk5ubKvO82NTWFi4sLTE1Noa+vD1NTU+iZWSGTa4Y7Fy8ivkZbiGw9UeDAg8DEDtn6VhBxZd+n8pgYekyEt0/5cLZA0ftgHgc8Dgcm+lwY6RV9zjPR48LckKt036o7uQaWduzYoa44qoyJEyeiV69eAIpmLI0YMUJjsTDGkJCQgAcPHki/Xrx4gcjISKSnpwMoGihydXWFl5cX6tSpg9atWyMvLw+1atWCs7Mz7O3tYW1tjfz8fDRo0ACPHz/+6MJcFZUjEONNpgAFIgkE4qIzy2LJu5HhvEIJ3uYU4k10NLB3L4QdJiDe1AHp2XnofzwZYkmy9IxHjkAs/fBdGr3/3njpcTmwMuLBVJ8L/f8+cCArEwCQUSCGE4+Lurb66F7HCj72RjDV50nf0Bn/9+ZOn1f+h46oqKhqc62srsjKysLu3bvx9OlThIeH4+bNm8jOzoaenh6cnZ3h6uoKZ2dn1KtXD3Z2dtIP5tbW1rCwsICNjQ0sLS1hZmZW7qC5WMJw+lUWrsXk4NrDl8CRI/jHoR84Vk7gcgB7E3246OkjJiobDqb6qGNjhE+9LOBqaQgzAy6sjHgw4P1Xh/99UOZxARtjPRh8UJcxMbbwWA6Ejm2gkt9ZqmvN4fP5ePr0KSIjIxEVFYW4uDgkJCQgJiYGr169QkZGBgDA0dERderUgYWFBQCgffv2aNKkCby8vODg4ABra2vY2toqfGInq0CExFwhUvJFiMoQ4EFiPu4n5eNVegEy+CL8sjYC3KxEAMDeh2lwczOFuFAEc1EBDHgc2Bnro56tkXRw0kifC0Ne0eurrbEeDPWKPiQXv14b8LiwNOLBzkQP3P9ijomJgcdS4MTweiqs65pKt0O0Q3R0NM6ePYvLly8jKSkJCQkJePHiBUQiERo2bIgWLVpgxowZcHd3h52dHQwMDGBiYgInJyfp701p7jx9hcOHD6P+sNnIMbZHcmIGEiQGiM8uRBpfVOK9h/5/7zUsjXiw/G9AyMmQB1dzA7hZGsDJTB9OZvqwN9WHrbEeMpJs0XQ9EDW9CTw9lJ/1GRUVpXQbRDUkEgnu3LmDixcv4vz583jx4gViY2MBAB4eHtLXMS8vL4waNQoeHh5wcnKCvb09DAwMYGhoCH195U7aZBaI8CSFj3ORWbjyJgeRGQLEZReCGSYC+A0vnAJQz8sTHpxC2FuZF9WsAQ+2JnqwMyl6f2Gox4GVkR5M9LkwN+BKT0zp84o+gBvwuDDWK9rGef/1egmwt39tlb1eE92Sm5uLe/fuYe/evbhz5w6ioqKQkZEBDw8P1K1bF+7u7hg2bJh0AMnFxQW2trYwMzODra0tYrKFOPUyE2FxubgZl4tX6QIgMxFAMMwatkfDujWBgjzUd7VDQ0cTWBvxYG+qD3ODovcWPC6d0K9Mcg0sBQYGqiuOKsPZ2bnSV79/3+3bt3HgwAFcv34dYWFhSEpKgrGxMRo0aIBGjRph4MCBqFWrFmrXrg1PT89S30iV9gEyJiZGqbjEEoZ/X2TicTIfrzIKcDU6B9GZArw/AaN4toUelwMjPS5M9blwMtOHCV8AABBKGGpZG8HVQAAXeyuZs3QmBlzUMDeAjTEPdib6MNHnQp9XdDbE3JBX4kO3bN8s4TEX2PiFp8oGzYh2S0hIQGhoKMLDwwEAfn5+sLGxgZ+fHxo3bozJkyejadOmcHV1lc62U4RIwvAirQC343MRkZiPky8zEZddiLbu5mjkYIJrAM4HeqOZtxdS46NRq1YtFfWQVHUxMTE4duwYTp48iUuXLqGgoAD29vaoVasW3NzcUKNGDbRq1QpmZmbw9/dHrVq1YG5uLn2uh4cHvvnmG4Ve0xhjSMgV4vKbbNyOz8ObTAGepRbgRVrRDFYOAGdzffg6maCZsylGNrGDrbEevKwNYZDrgNrrgDMjveHu7k4DkkTt3r59i927d2Pfvn148OABXF1d0aVLFwQEBMDe3h4NGjSAr68vrKysKtQeYwzxOULcis/F7fg8XI3OwfVHrwAAR55loLaXJeyMuGjnagUXcwPYmejByogHK6N3/xrpceQawOVkFw0ccBUc9CXa5969e/jjjz9w+PBhJCQkwM/PDw0bNsSoUaPg4+MDb29vmJubS1+v58+fr7L3oCIJw+NkPo48Tcc/zzPwMIkPBsDP2QTd61jhy6b2qGdnBEGaFdqvB25PaEiv16TSvHz5EidPnsSZM2dw4cIFFBYWolu3bhgyZAhq1aqFhg0bok6dOiWexxjDnbd5OB6biws3MnA3IQ5vc4RwtzRAB09zTG/thOYuprAUOKDeeuDwkLrv1bVL5XeUlFAtF+8ODw+XXtMMALGxsQgNDQUANG/eHIaGhpoMT4oxhoiICJw6dQpHjx4FAAwcOBBNmjRBmzZtsGbNGjRv3hy1a9dW6sOxMvFdi8nF0WfpCH6QhnyhBH7OJnC1MMCsNs5o6GCMhg7GMNYvmn1R1puwmJgYeHwDrO3qQS8QRGGxsbHYs2cP/vrrLzx69AjW1tbw9PQEAOzevRuDBg1S+veEMYbHKXw8TOLj1KtMHH+eiWyBGDXM9dHEyQRjm9pjjJ897Ez0ERMTgyAAtW2MYGmkhzT6QFHticVinD59Gps3b8apU6dQs2ZNfPHFF5g6dSratm1b4RMB8kr6bxDpRlwuLkRl402mAHlCCWyN9dDW3Qxe1ob4rJYlWtQwhbulIWyM9YouSytFDJ8uIyOVIyUlBYsXL8b27dvh5eWF4cOHY9++ffDx8ZF7Vt6r9AJciMrG5TfZuBqdg4RcISwNeWhewxQdPc0xr3FdfLEe+Pe/mXL0PoSUpqCgAHv37kVQUBDCw8PRqVMnLFmyBD179oSjo6PaBm4KxRK8TCvArfg8nInMwplXWcgWiOHrZIJBDWwR1MMCvk4mMNL7YGaz2EjlsRBSmqioKBw6dAj79u3D/fv3Ua9ePXTp0gXffvstWrduLT0xVpqsAhH23E/FljvJeJZaAG87I3T0tEA/H2v4u5mhjo2RzGt+TEx6ZXSJKKBaDiwFBQUhOTlZ+n1oaKh0YGn79u1wdHTUVGjIyMjA2bNncerUKZw5cwaJiYnw9fXFZ599hgkTJqBv376wtVX9oqNOTk549OgRnJycProvYwynXmVh2ZV4hL/NQ0dPCyzt5Ip+PtawN5V/Oq88x1aEutsnilNFbuLi4rB06VLs2LEDDRo0wLBhw/DFF1+gYcOGEIlEePnyJerUqaPwoFJURgGux+Yi5E0OzkdlITqrEA6memjnYY5tPWuinYcZHE31S3zQobquvj7MTUFBAbZs2YL//e9/SEhIwODBgxEWFoaWLVsqdNlaRXL/ODkfJ15k4sizDNyKz4O1EQ/+bmYI9LVDfXtj1LQ2RF1bI7lnUFBdV1+VlXtDQ0N899132Lx5M7y8vHD06FF069ZN7t+V2CwBDj1Ox5FnGbgem4uaVoYI8DDDyi5uaOVqito27+q/sLCQ6rqaqkhu0tLSEBQUhI0bN0IoFGL8+PHYv38/ateurZL2P8QYw/2kfFyLzsHJV1m4/DobAjGDk5k+PqtliW09a6K9hzkcTPXK/b2g1+vqqzJy//DhQ4SGhqJHjx54+PAh6tati+HDh2P//v3w9vb+aBuXXmdja3gyjj3LgI2xHsY3s8f4Zg5wMTf46LGprrVTtRxY+u233zQdQgkhISH48ccfce7cOVhYWOCzzz7DypUr0bVr10q59M7AwAANGjT46H7XY3Mw93wsbsblYZyfPfYNqA1PK+VmeFX02NraPlGcMrmRSCTYunUrvv/+e/j4+OC3337DqFGjZN5kyds+XyjBjbhc3I7PxYu0AjxO4eNWfB7sTPTQwdMc37V1Rs961nC1KP+PnrJ9qwiqa+1VnBuRSITff/8dixcvhlAoxMyZMzFmzBilTw6UlXuRhOH48wz8ejMJIdE5aOJogi/qWmHTF57wdTJRyWU4VNfVV2Xk/uXLl+jQoQPs7OywY8cO9O/fX66TAlkFIgQ/SMOBR2kIjc1FbRtDDKhvgw3dPeDrZFrusamuq6fycsMYw44dOzBz5kzY2tpi4cKFCAwMhKlp2bUkT/vFnqfycTYyC6/SBYjOEuBxMh9RGQLUtTVC11qWmNrSEc1cTOEg58lbquvqS525Kb7p0pw5cxAeHo4pU6bg0KFDqFu3boVOANxLyMOiy/E4/TITfXys8dfgOvislmWZM6U/RHWtvWhOuwYxxnDu3Dm0b98enTp1gp2dHUJCQpCSkoIDBw5g9OjR0kGlt2/fonbt2nj79q1aYimv/ZQ8IXbcS0H3vc/R/o+n8LAyxNMpjbHxC0+lB5U+dmxVUHf7RHGK5ubatWto3749vv/+e6xatQo3btxAu3btSvxB+1j7EsZwIy4Xiy7F4dPdz2D+4x10C36Ow08zIJQw9KhrhXuTGiJxVlMcHFgHX7VwrNCgkjJ9qyiqa+0VHx8PJycneHt7Y8aMGZg0aRJevXqF7777TiUzTt/PfdGaBLkYf+w1HH+5i5GHo+BtZ4SHkxvh7qSGWPaJK/ycTVW2tgvVdfWlztxkZmZi+PDh6Nu3L7788ks8fPhQrsuXX6UXYOnleDTa/BCrQhPg72aG2xMa4NmUxljR2a3cQSWA6ro6Kys3kZGR6NKlC6ZOnYqFCxfi2bNnmDx5slyDSuW1n1kgwoabiWi1/THqb3qIrXeS8TanEF5WhpjVxhmvpzfB0ymNsb6bB7rVsZJ7UKm8Y6sK1bX2UkduxGIx/v77b7Rp0wbt27fH/fv3ERISgl9++QX16tX76KBSdKYAgUci0WLbY4gkDA8mN8LBgXXQvY5VhQeVAKprbVYtZyxpGmMMJ06cwPLlyxEeHo5Ro0bhjz/+KHdKrUgkQmRkJEQi9dyKs7T2GWNYeCkeq0ITYGeihy/qWOH2hAZo6izfH1VFjl2V2ieKkzc39+7dw5w5c3Du3DkMGzYMf/75Z7mLYZbV/t2EPOyOSMVfT9KRmCtEa1cztHEzww/tXdDUyQSWRsq/NFJdVz8SiQRHjx7FwoULkZSUhL59+2LFihWwsbFR6XGKcx8WnYll/6ThYTIfnb0ssOkLT3xe2xJWKqjfjx2b6rr6UVdubt68ib59+0o/sE+dOrVCd8l6kcbHP88ycfRZOm7E5aGJowmmtXbC5BaOMNaX77wp1XX19WFuGGPYuHEjZs+ejYCAADx69Ag1ayp+Z8kP288WiPHd2RjsjEiFvYkexvrZ4/feNdHQwUQl/Snv2FWtfaI4VeZGJBJh9+7dWLFiBWJjYzFmzBisWrUK7du3r9DyMQk5hfglNAFBd5LRzNkUV8f4wN+t7DWXKhIP1bV2ooGlSiSRSHDkyBEsX74cT548wZgxY7B//37pAsPaJLdQjAnHX+Pki0wcHFgbPetZ0d1MiMbk5+dj0aJFWLduHfr06YNHjx6hfv36crdzMy4Xs8/F4mpMDjp6mmNRxxro7W2t0JlAQoqJxWIcPHgQK1asQGRkJIYOHYrHjx9j7ty5Kh9UAoACUdGtzwcfeoWxnRrh3+H1KjyTjhBtwRhDcHAwJkyYgMDAQMycORN169b96PPS8oWYfjoG+x6moZGjMbrWssKWHjXRyFH1H8xJ9ZKfn48JEybg8OHD2LRpE0aPHq3QOniluZ+Yhx/uROLoswy4Whjg2NA66OxV8ct/CNGE+/fvY9iwYYiLi8PUqVMxffp02NnZVehu4pkFIqy6loBfbyahjq0h/uxfC328rVX2O0W0Dw0sVYIPP3RMnDgR//77L2rUqKHp0Er1Mq0A/Q+8hEAswdUx9enNGtGoCxcuYPz48RCLxTh+/Di6desmfxtRWTh54yWOPM3AkEa2eDalMerY0t1SiHKEQiH27t2LH3/8EW/fvsXXX3+NGTNmQCAQYMeOHWo5ZjpfhGF/Fd0afXc/LwwLUPxMOiGaUvz7cunSJaxatQpTp05FbGzsR5+3+34q5pyLhZOZPi5/6YMAd8XPehPyvtjYWPTu3RtZWVkICwtDkyZNVNJuZHoBAKDPvpfo0dIbwf1q4fPaljDUo9VIiPYSCoX46aefsHTpUnTt2hVXrlyBnZ1dhZ9/NyEPAw68hAGPg99718TABjY0QaEaoIElNSrrQ4cid50zNjZGr169YGxsrIZI37V/+GUeFt96hPaeFtjd10utl1R8eGx1901d7RPFlZcbgUCAefPmYf369ZgyZQpWrFgBMzMzudoX8wxQo3lnfH02Ab38vBA6tj5aucrXhqKornWXSCTCzp07sWLFCmRkZOCbb77BtGnTpOsnpaSkqCU38dmF6Bb8HByuAbp+0QOf1qv8O5hSXVdfqsrN+fPnMXDgQDRp0gQPHjyQzlIqr/1CsQQzTsfgt7spWPaJK6a2cixxa3VlUF1XX8bGxvD390fPnj3RokULXLhwQWUzTbeFJ+Pbv6Ph4PcJDo5rgg4NPFTSbkVRXVdfyuTm0aNHGD16NKKjo7Fv3z74+fmVGFQqq/3cQjHmnIvFljvJGN7YFlt61JT70uSPobrWYowoLDw8nAFg4eHhMtsjIyMZY4zdvn2bWVpasgULFrDU1FRNhFiq4vjeJxRL2MRjUcxk+S224UYCE0skGoisSGnxaRNtj09ZH6vryvDkyRPm6+vLXFxc2Llz5yr0nA/je5nGZ403P2D1fo1gj5Ly1BGmXLS9brQ9PmWpoq4lEgk7ceIEq1+/PrOwsGDLli1jGRkZKo5UVnF8z1Lymee6e+yTnU9YVoFIrceUh7bXjbbHpyxteL2Wx6+//sp4PB776quvmEhUsTpOyi1kHf54wmqsvsuux2SrOcIi2vrzK6bt8SmrsupaIpGwNWvWMB6Px+bMmVPhmizL+/EtvhTLjJfdYlvvJDGJBt9Tv0/b60bb41OWtr9eJyQksK+++orxeDzWr18/lpSUxBireHxZBSLW5rdHrPb/Itil11nqDFWGtvz8yqLt8akSzcNUo+bNmyM+Ph5Lly5V+k5AeXl5OHjwIPLy8lQU3TsCkQR9dt/H/oMHcHKQO6a0cqrU6Yrq7FtltE8U92FuGGPYvn07mjVrBk9PTzx48ABdunSRu93b8blovf0xXAxFmG39BJ6mTNWhfxTVtW65d+8ePv30U/Tu3RtdunRBZGQk5s+fDysrqxL7qjo3T1L46LjzKZq5mOLE8HrgiQo0lnuq6+pLmdwwxrB8+XLMnDkTwcHBmDVrVok7vpXW/qPkfLTe/hhCiQS3JjRQasHX8lBdVz9CoRATJ07EvHnzMHXqVMyfP7/CdyH8mGVX4vHztQQcGVIHw71NcejQIXq9JpVKntyIRCL8+OOPqFWrFsLCwnDixAn89ddfcHBwqHD72QIxugc/R7ZAgtCx9dHR00JlffnYsata+7qMBpbUTN7bkpYlLS0NgwcPRlpamkraKyYQSTDw0Cvci0pAVvBc1DQUqLT9ilBX3yqrfaK493OTl5eHwMBATJ06FevWrcPhw4cVGpC9FZ+Lz/Y8x4D6NgjqbIMxI4dpJPdU17ohNjYWgYGBaNasGaysrPDkyRP873//K3etAVXmJipLhC67nqGDpwX2D6gNIz2uRnNPdV19KZobxhjmzJmDFStW4OjRoxgyZEiF2j8flYV2fzxFazczXAj0gYu5+haop7quXjIzM9GtWzccO3YMBw8exPr161WWm19CE/Dj1bc4PKQOuta2otdrohEVzc3Tp0/Rpk0brF27Flu2bEF4eDi6du360QW2329fIJKg158vkC0Q4/wob7XfEIfqWnvRwFI1JhRLMPTvSNxPzMf+AbU0HQ6pxiIjI9G6dWuEhoYiLCwMEydOVOiuEUm5QvTZ9xKDGthgcw9PWiiQKCw7Oxvz5s1D3bp18fz5c1y9ehV//fUX6tSpU2kxpOQJMfZCNvzdzLCnrxfdPYhUORKJBJMnT8bmzZtx6tQpdO/evULPu/ImG733vcDkFg7Y26+WStdTItVbZGQk/P39kZycjFu3bsHX11dlbe9/UYD5F+Owf0BtfF7bSmXtEqJqYrEYa9euRdOmTeHi4oLHjx9j5MiR4HLle60VSxjG/BOFN5kCnBlZD45mdJfl6oz+UldjU09G42ZcLs6NqgcPK7pDFtGcHj16oFatWggPD0fTpk0VakPCGAKPRsLTygAbu3vQoBJRiFAoxObNm1G7dm0cOHAAu3fvRlhYGNq2bVupcRSIJOh34CVsjLgI7lcL+jz6c02qFqFQiJEjR+LAgQO4cOECOnbsWKHnPUjK+29QyRHLP3GlW1MTlQkNDUXr1q3h5eWFa9euwd3dXWVtX3qdjSW3crGtpyd6e1urrF1CVO3p06cICAjAsmXLsG3bNhw5ckShG0sBwKyzMTgXmY1/h9eFsxpnlZKqQWvuCsfn8xEcHIzQ0FDk5OTA1dUV/fv3R/v27ct93rx58/Do0aMyH9+1axesra3L3bdp06ZYsmSJch2oYm7E5eK3uym4OsYHdW2NEUOXkZJKJhaLsXz5cgDAtGnTsGLFCqU+QGx/zMfNOAHuTmxIH8KJ3BhjOHbsGL7//nukpKRgwYIFmDx5MgwNDTUSz/dnYxCbVYgDn1mo/I4qhKhbYWEhhgwZgrCwMISEhKBhw4YVfm7g4SgM8q+PVZ+60aASUZm9e/dizJgxmDRpEtasWQM9PdV9BIrKKMCgQy8x2scYgb72KmuXEFUSiURYvXo1Fi9ejK5du+Lvv/+Gi4uLYm1JitYuvfImGxenNUNDBxNVhkqqKK0ZWFq5ciVevnyJwMBAuLi4ICQkBKtXrwZjDB06dCjzeZMmTUJ+fr7MNoFAgCVLlqBWrVrSQaViTk5OmDFjhsw2eW9hrgmOjo64ceOGwiPK75Mwhm9PR2N4Y1vpQpiqbF9e6j62JvtGSpebm4vhw4fj6tWr2LRpE8aOHavUB4jLb7KxLiIffw6ojZrW7wYCqK5JRV2/fh2DBg3C1KlT8cMPP5T42yEPZXPzJIWPLXeScWJ4PdhzSl7jT3VNNKGiuSksLMSgQYNw+/ZtXLlyBXXr1q1Q+0aWtvCctQcNfDwQ1MOzUgeVqK51F2MMixcvxooVK7B+/XpMmTJF5nFlcyMQSTDo4Cu0rGGGWU1Lfqyi12uiCR/mJjIyEsOHD8fLly/xxx9/YOjQoUq9xq65XwCbKTtx9qs2aOxYuYNKVNfaSysGlu7cuYOIiAjMnDlTOojUuHFjJCcnY8eOHQgICCjzTg2lTWO9cOECRCIRPv300xKPGRgYwNvbW7UdqASGhoZo1aqVSto6EiXA42Q+/hr0bq0QVbYvL3UfW5N9IyXFxcWhZ8+eyM/Px61bt1C7dm2l2kvIKcSwvyIR6G2EAfVtZB6juiYV1aZNG7x+/Vrhs3fvUzY3s8/F4NNalvi0liWiokoOLFFdE02oSG7eH1S6fPlyhdckE0sYRv8bBwuvJtg32Ae8Sl5PjOpaN/H5fIwePRqnTp3C8ePH0a1btxL7KJubeRdikZwnxJmR9ZCVGKvy9pVBdV19FeeGMYadO3di6tSpaNeuHR4/fgwnJyel2j75MhPb72fh4nf94KemO3WWh+pae2nF/PobN27A2NgYAQEBMts7d+6M9PR0vHjxQq72zp07B2NjY7Rr106VYWpUQkICfH19kZCQoFQ7kekFWHY7D0s7uaKGxbtrYVXVviLUfWxN9o3IunfvHlq1agUrKyuEhYXB1NRUqdwwxvDlP1GobWOIWX4l78BIdU0qisPhqGRQCVAuNxeisnD6VRZWfeqmlvaVRXVdfX0sN4oOKgHA7HOxuPn0DYSbRyA3PVlVIVcY1bXuSUhIQMeOHXHr1i2EhYWVOqhUvJ+iuTn5MhO/3kzC7n61YGtS+qLF9HpNNCEhIQGNGjVC7969MWnSJPz44484ceKE0oNKKXlCjPvnNSb78DClVzuqayJDKwaWoqOj4erqWmJWUs2aNaWPV9Tbt2/x5MkTtGvXDsbGxiUeT0xMxLBhw9CnTx9MmDABe/bsgUAgUK4DlUAoFOL+/fsQCoUKt1EolmD435FoZq+Hb1rLTu9TRfuKUvexNdk38s6xY8cQEBCAzz77DGfOnIGNjY3SuQl+kIar0TnY0ccL+qWc4aa6JpqgaG4kjOH7c7EY52ePBuWsV0B1TTShvNyIRCIMHz4ct27dkntQ6e8n6fj1ZiI2d3PF00cPqK6J0iIiItCyZUvo6+vj1q1baNCgQZn7KpqbvEIxxv3zGnMCXNDR00Ll7asC1XX1FRoaikePHuH58+e4ffs2pk6dqvTlxYwxTPr3DWpY6GNKc1uqa1KCVlwKl5OTU+p1jMVrH+Xk5FS4rXPnzgEAunTpUuKx+vXrIyAgAK6urigsLER4eDgOHz6MJ0+eYMWKFXLfYrGqWXwpHjFZhfinmzndMYtUGsYY1q9fj++++w7Lli3DnDlzVLJ2RnKeEDPORGNJR1fUsjFCVKbysRKiSSdeZOJpCh//DqvYmjSEaAOxWIzAwECEhITIPagUnSnAhOOvsaSTK/zdRGqMklQX//zzD4YPH45+/fph+/btarsBw6ZbSdDjAj+0V81MV0JUQSKR4Oeff8b8+fMBAMePH6/wOncfE/wgDadeZuL2hAYwKEhVSZtEt2jFwBKAcj9oVvRDqFgsxsWLF+Hu7l7qOkojRoyQ+b558+ZwcHDAjh07cPPmTfj7+3/0GAkJCdKpcU+fPq1QXNrgVnwuVl9PwNGhdWHLS9d0OKSaEAqF+Oabb7Bz507s27cPAwcOVFnbM87EwMPSENP9lZvWS4g2YIxh5dW3+LKpPd2yl1QZEokE48ePx5kzZ3Dp0iX4+PhU/LmMIfBIFPycTfF9W2fEx5Vcn4aQimKMYfXq1Zg7d65KT2KVJlsgxi/XE7C0kyuM9HT7pDSpOtLS0jBy5EiEhoZi06ZN+Oqrr2BkZKSStmOzBJh2KhrLPnFFAwcTxMSopFmiY7RiYMnc3LzUWUm5ubkAKn7Xtjt37iAjIwP9+vWr8LE7duyIHTt24Pnz5xUaWNq6dSuWLFlS4fZVxdDQEJ06dVLozItAJMHYf15jRBM7dK9jhaiokgNLyrSvLHUfW5N9q87S0tIwcOBAPHnyBJcvXy51ITxFc3PnbS72P0zDjfH1oVfOIq9U10QTFMnN5Tc5uPM2D3v7f3wxe6progkf5kYikWDSpEk4cuQILly4gEaNGsnVXtDtZEQk5uHh5EbgcTlU10RhhYWFmDRpEvbv348DBw6gf//+FX6uIrn59UYizA14GOtnr5b2VYXquvq4fv06Bg8eDAcHB9y9exdmZmY4ePCgSnLDGMO4Y6/R2NEE01sXncyluial0YqBJQ8PD1y9ehVisVhmnaU3b95IH6+Ic+fOQU9PD506dZI7hoqe1Zg4cSJ69eoFoGjG0oezoNTF0dERFy9eVOi5y67EI4MvwprPSt5BTxXtK0vdx9Zk36qrp0+fomfPnrCwsMDt27fh5lb6QsSK5mbhpXj0q2+N5i7lDzpTXRNNUCQ3K6+9xdBGtqhp/fE3MlTXRBPez41IJMKYMWPw77//4uzZs/Dz85OrrdgcMeaej8Waru5wszQs0X5lo7quulJTU9G/f3+8evUKV69eRbNmzeR6vry5yeCLsDYsEb985g4D3sdnK1FdE3VijGHt2rWYM2cOJkyYgDVr1khnKakqN3++KEBYLB8RXzWU3rGT6pqURivmb/r7+4PP5+P69esy2y9evAgbG5sKXRuakZGB8PBwtG7dGhYWZS+i96HiwqlXr16F9nd2doafnx/8/PzkmvKtLD6fj5MnT4LP58v1vJgsAVZfT8SG7h6wNi57HFHR9lVB3cfWZN+qo9OnT6N169bw9fXF1atXyxxUAhTLzbWYHJx9lYXFHV0/ui/VNdEEeXNzKz4XF6OyMTugYmt1UF0TTSjOTVZWFoYMGYLTp0/j8uXLaNGihdxtLb+Th1auZhj33owPqmsir2fPnqF169bIy8vDrVu35B5UAuTPzfobibAz0cOoJrZqaV+VqK51W0ZGBvr27YvFixcjODgYmzZtkg4qqSo3rzMEWHU3D6s+c4eX9bvL6qiuSWm0YmCpWbNm8PX1RVBQEM6cOYMHDx5g48aNuHv3LkaPHi2dxfTrr7+iT58+SE4ueSvaixcvQiwW49NPPy31GI8fP8aiRYtw+vRp3Lt3D7du3UJQUBD27NmDxo0bo2XLlmrto7JSUlLwxRdfICUlRa7nrbqWgCZOJujjba2W9lVB3cfWZN+qk+JFunv06IHp06fj4MGDMDU1Lfc58uaGMYYFF+MwrLEt6tuXvOujsu2rEtV19SVvbn4JTUAvb+sK1bQi7asS1XX1VZybfv36ISwsDCEhIWjcuLHc7Vx6nY3L8YVY97m7zGxxqmsij3PnzklPYoWEhKBGjRoKtSNPbrIFYmy8lYQ57VygX4HZSvK2r2pU17rr4sWLaNKkCV6/fo3w8HAMHjxY5nFV5IYxhonHX6OJnT4mNpO97JPqmpRGKy6FA4C5c+ciODgYf/75J3JycuDq6opZs2ahffv20n0kEgkkEgkYYyWef/78eTg4OMDX17fU9q2trcHj8XDgwAFkZ2eDw+HA2dkZw4YNQ9++fXXyjnDx2YX4/V4KDgysrbYFDAkBitY3+PrrrxEcHIy9e/eW+AOnKhdeZyM0JgdPp8j/YYYQbRSTJcDRZxm4GFh5M2AJUUR+fj4A4MWLF7h69Sq8vLzkbkPCGL47G4OBtQzR0MFE1SGSauLcuXPo1q0bZs+ejWXLllXae/itd5JhZsDDiMYVm61EiKrx+XzMnTsXGzZswLRp07BixQoYG1fspJS8/riXihtxuTj+hSV9jiQVojUDS8bGxhg/fjzGjx9f5j7Tp0/H9OnTS30sKCio3PZdXFywcOFCZUKsclZfT4CPnTF61rXSdChEh324vkHz5s3VchzGGJZejsdoX3vUslHNXS4I0bTNt5LR2NEEAe4Vu0kFIZqQl5eHUaNGAQAOHTqk0KASAOy5n4qX6QXYFGClwuhIddOuXTscPXoUPXr0qLRjFogkWH8jEbPbOldobSVCVO327dsYNWoU8vPzceHCBXTs2FFtxyoQSbD4chwWdKgBN3O6JIxUDL0y6qjE3EJsC0/GD+1daJSZqM2jR4/QsmVL5Ofn49atW2obVAKAqzE5CIvLxewAZ7Udg5DKlC8U47e7yZjaypFep4nWys/PR48ePZCamgqg6ESdQu0IxVhwMQ7ft3WGvTG9/SSKMzIyqtRBJQDYGZEKkYRV6E5whKiSUCjEokWL4O/vD39/fzx8+FCtg0oAsD08GSIJw+QWDmo9DtEtWjNjiZTPwcEB586dg4NDxX7B115PRC1rI/T1KX9tJUXbVyV1H1uTfdNl//77L4YOHYovvvgCf/zxB0xM5L+sQZ7crLyagMENbeWarUR1TTShornZ+yANPC4HQxrKd1kF1TWpLPn5+ejZsyfi4uJw7tw5vH79WuHcrL2eCAD41t8JibHRJR6nuiaaUJHciCQMq0MT8E0rR5ga8MrcT9H21YXquup78uQJRo4cibi4OBw+fFh6Z/KPUSY3fKEEP11LwHdtnMusd6prUhoaWKoijIyM0KVLlwrtm5wnRNCdZPzWqya4FTwLLk/7qqbuY2uyb7qIMYY1a9Zgzpw5WLRoEebPn6/wbIuK5ib8bR7ORmYhYlJDtbSvDlTX1VdFcsMYw4abSZjQzAFGevLN3qC6JpWhoKAAffr0wZs3b3DlyhW4urqiVq1aCrWVkFOIVaEJ2NDdAyb6pX9QobommlCR3Bx8nIaUfCEmt3BUS/vqQnVddUkkEvzvf//D3Llz0b17d5w+fRr29hWfLadMbraFJ4MxYFI5s5WorklpaC5yFZGUlISAgAAkJSV9dN811xPgaWWIAfVt1NK+qqn72Jrsmy46efIkFi1ahAMHDmDBggVKXcJT0dysvPYWPetZoZGjfLOiqK6JJlQkN5fe5OB5WgEmNZf/jBjVNVE3gUCAvn374uXLl7h06RJcXV2Vys2iS/Goa2uEkU3sytyH6ppoQkVysy4sERObOcDaWP7z8VTXRF5v3rzBJ598gsWLF2Pbtm34+++/5RpUAhTPTb5QjFWhCfi+rXOZJwGUaV8VqK61Fw0sVRECgQChoaEQCATl7pecJ8Tm28mY394FPG7FP/BXtH11UPexNdk3XdS9e3c8fPgQ/fv3V7qtiuTmSQofR59mYE6A/Ot6UF0TTahIbjbcTET/+taoYWGglvbVhepa9wkEAvTv3x9PnjzBpUuX4O7uLt2uSG6epfKxIyIFP3/qVu4saqprogkfy829hDzcTcgvd/aGMu2rE9V11cIYw44dO9C4cWPweDw8fPgQo0aNUugErqK5CbqdDA6AiR856UV1TUpDA0s6RpHZSoTIg8PhKHxHIEX8EpqATjUt0NqV7ppFdMObTAH+fZGJqS3lv6yCEHUqLCzEoEGDcP/+fVy8eBGenp5Kt7n4cjw61bRAZy9L5QMkpJL9cS8FnTzN4WVNd6Ml6nXx4kVMnjwZy5cvx7lz56SD+pUlRyDGz9cSMK+dC4z1aYiAyI/WWNIhKf/NVvqtV025ZisRoq2yBWIcfJyGfQNqazoUQlQm6HYSmjqZ0GAp0SrZ2dkYNmwY7t27h8uXLyu8ntL7IhLz8NfjdFwfV18FERJSufhCCf58mIZfu3loOhRSDXzyySd48eIF3NzcNHL8X28mwtSAS3c+JAqj4cgqwsDAAC1atICBQdmXTay5nqjwbKWKtK8u6j62JvtGyvex3Pz9JB1mBjx0q63YmW6qa6IJ5eUmXyjG73dTMLmlo8Lrk1FdE1V78eIFWrdujaioKFy5cgV16tQpsY8iuVlwMQ4961mhZY2PD6JSXRNNKC83R59lgDGgn4/iVwFQXZOK4nA4KhtUkjc3GXwR1lxPxPz2NWBYgRuKUF2T0tCMpSrCyckJt27dKvNxvlCC7XeTse5zD4VmK32sfXVS97E12TdSvo/lZu+DVAxpaAt9nmJj4FTXRBPKy82+h+ngcTkY0tBWLe2rG9W17jl16hSGDh2KDh06YM+ePbCwsCh1P3lzExabg1Mvs3CvgnfzpLommlBebnbcS8HQRrZKXRZEdU00Qd7crL+RCDsTPYxqUrH3JlTXpDQ0Y6mKKCgoQEhICAoKCkp9/PDTdDAGDFRwbaWPta9O6j62JvtGyldebmKzBLj8JgcjGiv+AZzqmmhCWblhjGHTrSSM87OHUQXOCMrbfmWgutYdjDH8/PPP6NmzJ6ZNm4YjR46UOagEyJ+bRZfjMbihTYXv5kl1TTShrNy8zhDgwutsjGmq3GVBVNdEE+TJTbZAjA03kzC3nUuFT+RSXZPSaM3AEp/Px/bt2zF69Gj0798f06ZNQ0hIyEefd+HCBfTq1avUr4yMjBL7R0RE4LvvvsOAAQMwfPhwrF+/HpmZmWrokWolJyejQ4cOSE5OLvXxHfdSMLyx4mdVPta+Oqn72JrsGylfebn582Ea6toaobmLqVraVzeq6+qrrNxci8nFw+T8j95tRdH2KwPVtW7Iz8/HsGHDsGzZMhw8eBBLliwBl1v++wd5chMWm4OLUdmY375GhWOiuiaaUFZudkakoImjCfycKzYwKm/7lYHquvqSJzdb7yTD3JCH4XKcyKW6JqXRmkvhVq5ciZcvXyIwMBAuLi4ICQnB6tWrwRhDhw4dPvr8adOmoUYN2Tcw5ubmMt8/evQIS5YsQfPmzfHDDz8gKysLu3btwoIFC7B27Vro6+urtE+V5VV6AS69ycHqrpV79wBC1IUxhuAHaRjR2E7hdWgI0TYbbyWht7c13C0NNR0Kqcaio6PRp08fZGdnIywsDI0aNVL5MZaHvMWABjbwsTdWeduEqJtYwrAzIhXftXGi9yBEpxWIJFh/IxFzApxhoOCyE4QU04qBpTt37iAiIgIzZ86UDiI1btwYycnJ2LFjBwICAsDj8cptw93dvdTFJt+3Y8cOuLi4YM6cOdL2HB0dMXv2bJw7dw7du3dXTYcq2Y57KWjmbAJfJ8VndhCiTe4l5uNJCh/DlLgMjhBtEp9diCNP03F2lLemQyHV2OXLlzFw4ED4+vriwoULsLFRfFHistyOz8WZVxVfW4kQbXMuKgvJeUIMa2yn6VAIUaudEakQSRjdCY6ohFYMTd64cQPGxsYICAiQ2d65c2ekp6fjxYsXSh8jLS0NL1++RKdOnWQGqXx8fFCjRg3cuHFD6WNogkjCsCsiFV8qeQ04Idok+H4q2nuYw9OKZnYQ3bAtPBk+9sbo4GH+8Z0JUTHGGDZu3IhPP/0Uo0aNwqlTp9QyqAQAK66+RW9v6wqvrUSIttkVkYo+3tawMdaK8++EqIVIwrA6NAHftHKEiX75EzgIqQiteMWMjo6Gq6triVlJNWvWlD7u4+NTbhvLli1DdnY2TExM0LBhQwwfPhweHh4yxwAAT0/PEs/18PDAs2fPlOyFetnZ2eHIkSOws5M9e3LqZSYyC8QY2ki5mR1ltV8Z1H1sTfaNlK+03IgkDPsfpWPpJxVfm0Oe9isL1XX19WFuJEy1l1VQXRN5CAQCTJ48GXv37sUff/yBkSNHKtRORXJzLyEPx59n4s6EBmppX12orquvD3OTVyjGvy8y8Wf/WmppvzJRXVdfFcnNgUdpSMkXYnILR7W0ry5U19pLKwaWcnJy4OhYsqjNzMykj5fFysoKgwYNQr169WBsbIzo6Gj8/fff+O677/Dzzz9LB6eK2yhu833m5ubIzs5WRVfUxsTEBH369Cmx/fd7KRjQwBpWRsqlsqz2K4O6j63JvpHylZabc5FZyCwQYYCCdzj8WPuVheq6+vowN5ff5CAxV4ghSp4AKKv9ykR1XbUkJCSgX79+iIuLw7Vr19C8eXOF26pIbn68+hY96lqhqbP8l+ZTXRNN+DA3/77IhD6Xg89qWaql/cpEdV19fSw3jDGsuZ6ISc0dYK3AzDyqa1IarbgUDkC5Z3HLe6xZs2YYMWIEWrRogYYNG+KLL77AypUrweFwsHfv3gq3VdGzyAkJCbh79y7u3r2Lp0+fVug5qpCcnIzPP/9cZoX6tzmFOPkiE2ObKneHobLaryzqPrYm+0bKV1pu9jxIRc96yg+WltV+ZaG6rr4+zE3wg1R0r2MJOxPV3CCC6ppUVGJiIszNzXHnzh2lBpWAj+fmVXoBjjzNwJwAZ7W0r05U19XXh7k5+Dgdvb2tYainmo9IVNdEEz6Wm5DoHDxKzseUlvLPVqpI++pEda29tGLGkrm5eamzknJzcwGUPsuoPI6OjvDx8cHz589ljgGUPvspJyenxB3kyrJ161YsWbJErnhUoaCgAGfOnEFBQYF02+6IVNSyMUKAu3w/n4q2X1nUfWxN9o2U78PcZPBFOPo0A38PLn8hfkXbr0xU19XX+7nJKxTj7yfp+KO3l1rar2xU11VL06ZNcfbsWZW09bHcrA9LhL+bGfzdFFtHjOqaaML7uckWiHHqZabK3oN82H5lo7quvj6Wm19vJqGvjw3cFLxLLdU1KY1WzFjy8PBAXFwcxGKxzPY3b95IH5cXYwxc7rvuFbdRvNbS+6Kjo+Hu7l6hdidOnIjw8HCEh4cjODhY7rhUhTGGnREp+NKXbsdOdMf+R2mwNdFT2RR0QjTt6LMM6HE56FHXStOhEKI2qflC7IxIxQx/J02HQojCjj/PgKkBF128LDQdCiFq8yZTgGPPMzC1lWKzlQgpi1YMLPn7+4PP5+P69esy2y9evAgbGxvUrVtXrvYSExPx7Nkz1KtXT7rN1tYWdevWxeXLl2UGsJ49e4b4+Hj4+/tXqG1nZ2f4+fnBz8/vowuKq9P12FxEZggwogktLEZ0x86IVIxsbAcelwZLiW4IfpCGwQ1sVXZZBSHaaMvtZNSw0EevetaaDoUQhR18nI6+3jbQ59HrNdFdm28lwdfJBG3dlL/ihZD3acWlcM2aNYOvry+CgoKQn58PZ2dnhISE4O7du5gxY4b0bnG//vorLl68iG3btsHBoWhdoQULFqBBgwbw9PSULt59+PBhAMDw4cNljhMYGIiFCxfi559/Rvfu3ZGVlYVdu3bBw8MDXbp0qdxOy0lPTw8+Pj7Q0ytK2a6IVHxWyxIu5gZqab8yqfvYmuwbKd/7uXmUnI87b/Owp5/qLhmiuiaaUJyb1AIJzkdl4cqXqj0JQXVNNKGs3BSIJNh4KwmLOtZQ6qQA1TXRhOLc5ImAM6+y8O9w+U5mV7R9qmtSmcrKTV6hGL/fS8Haru5KXfFCdU1KozU/sblz5yI4OBh//vkncnJy4OrqilmzZqF9+/bSfSQSCSQSCRhj0m0eHh64evUqjhw5gsLCQlhaWqJx48YYPHgwatSQvV15o0aNsHDhQvz5559Yvnw5DA0N0bx5c3z55ZfQ11fNoqrq4uLigidPngAoelE4+DgN23up7gP4++1XNnUfW5N9I+V7Pzdrz8SgjZsZ6toaq6X9ykZ1XX0V52bN9QTUtDKEv6tqzwpSXRNNKCs3e+6nQsKAQF/lZlBTXRNNKM7NzogUWBnx0NFTtZfBUV0TTSgrN8EP0qDP5WBwQ+XuUkt1TUqjNQNLxsbGGD9+PMaPH1/mPtOnT8f06dNlto0bN06u4zRt2hRNmzZVJESNKiwsxKNHj9CwYUMceZYNPS4HPetZqaV9AwPVzILSlmNrsm+kfMW5qedTH3sfpmLZJ65qaZ/qmlSm4tzsCgdGNnFU+Tp4VNdEE0rLjYQxrAtLxOQWDjDR56m8/cpCdV19Fedm/0N99K9vAz0VX4pPdU00obTcMMaw8VYSJjZ3gJGSl+dTXZPS0EXEVURiYiKaNWuGxMRE7IpIxdBGtkq/KJTVfmVT97E12TdSvuLc7At7idxCCQY1UO4MSlntU12TylScm0dRcRjeWLU1/X77VNekMpWWm5MvM/EmU4DJCt6y+mPtVxaq6+qrODcXH7zBoAY2amuf6ppUptJyc+F1Nl6kFWBicwe1tF9ZqK61Fw0sVTGxWQJcfJ2t9JRzQrTJwSdp6F/fGhaGyp3xJkSbtKhhAi9rI02HQYjarA9LxMgmdnAw1e7lBAj5GBtjHgLczTUdBiFqs+FmEgbUt1bZ+ryEfIgGlqqYw08z0NDBGM2cTTUdCiEqcykqG6N97TUdBiEqIZIUrQPY10f1Z78J0RaPkvNx6U0OpqhgthIhmta9jhXdkZborKiMApx4kUmv10StaGCpivnrSToCm9ipfM0OQjTJxcIA7T3oTCHRDVejswEAX9Sx0mwghKjRpltJ6OhpjkaOJpoOhRCFpeQJAQA9VLhuKSHaZvOtZDRzMUVrFd9MhJD30cBSFWFra4t5a7fhrcgYwxur/jI4W1tb7NmzB7a2ql8PRNPH1mTfSPlsbGzgGvgjRrWuBa4aBkuprokm/BvL0GrKanjVUM+ZQaprognv5yaDL0LwgzR8rcKz31TXRBOupnBgO2w5Pm3orpb2qa6JJryfm7xCMXZEpODrlqq7mQjVNSmN1twVjpTP1NQUb2t2RncnERzNVL+WgampKUaMGKHydrXh2JrsGynf0ywgoWZnjGutnjd0VNeksiXlCnH8tQDHp4+Dqal6Llmmuiaa8H5utoUlwNZYD73qWaul/cpGdV19HXrJx5jAkTA3U89MDqprognv52brnWToczkYrMLF6amuSWloxlIV8To+EcHzx6Ovej5/IyUlBQMGDEBKSop6DqDBY2uyb6R8my8/h+2/C2AizFZL+1TXpLLtjEiBCy8XW2aP1cncU11XX8W5SUxKxubbyZjU3EGlt2anuiaVLSIxD2HP4/Bg4zSdzD3VdfVVnJvk5GRsupWE8c0cYKjCu4lTXZPS0MBSFfH3/QSIHl9EgIt6VvLn8/n4+++/wefz1dK+Jo+tyb6RsuULxTj8MBHJd87qZO6prqsfCWPYFp6MYd5mOKyjuae6rr6Kc3PyaRLiswsxrplqb7hAdU0q27Y7KWjrrI8zx4/qZO6prquv4txcfJGCZ6l8TGzuoJb2qa7J+2hgqYo48DgNAGDAo5QR3fDXkwzQDViILjkbmYW3OUIMUOF0c0K0za6IFAxpZAs7E9Vflk9IZckRiLH3YSqGNVL9uqWEaItd91PR18cGrhbqmZhAyPtolKIKuJ+Yj/C3+ZoOgxCV+uNuCvp6q259DkI0bcudZAyobwMbY/rATXTX1ehcumU1qfL2PkyDmQEPn9Wy0HQohKjNucgser0mlYYGlqqALXeS0MbDAm5ubuDxeGo5Bo/HU2v7mjy2JvtGSvc8lY+rMTkY2sRBZ3NPdV29xGYJcOJFJiY2d9Dp3Oty30j5eDwezOxd0NzVHH7Oql+YnuqaVBbGGLbdScaYpvYwMtDX2dxTXVdfPB4PFvYu8HYwRYC76hemp7ompdGau8Lx+XwEBwcjNDQUOTk5cHV1Rf/+/dG+fftyn3f9+nWEhobi5cuXSE9Ph5WVFXx8fDB06FC4uLjI7Dtv3jw8evSoRBtNmzbFkiVLVNofVckWiLH3QRr+6NMYA6bHqO04NWrUQEyM+trX5LE12TdSuh33UtGyhik+9a2ts7mnuq5efr+bgvr2xmjrZgYOx1xnc091XX1Z2DmB9+0/mNG1plrap7omleVmfB4eJOXjyJA6qGFlqLO5p7quvmwcnGEw6xi+7eIODkf1605QXZPSaM2MpZUrV+LixYsYMmQIFi1ahDp16mD16tW4cuVKuc87fPgwBAIBBg0ahMWLF2P48OGIiorCt99+W2pRODk5YdWqVTJf48ePV1e3lBZ8PxUWhjx09zLFixcvIBQK1XIcoVCo1vY1eWxN9o2UJBRLsOt+CsY0tdfp3Oty34gsoViC3+6mYGIzB3A4HJ3OvS73jZRvR3gCDLPi0LO2em7LTnVNKsvWO8noVscSHlaGOp17Xe4bKV/wvUSIU6Ix0Fs9l3pSXZPSaMXA0p07dxAREYFJkybh888/R+PGjTFlyhT4+vpix44dEIvFZT53/vz5mD9/Prp06YKGDRuiU6dOWLp0KYRCIf75558S+xsYGMDb21vmy9XVVZ3dUxhjDFvuJGOcnz1Sk5NQr149JCQkqOVYCQkJam1fk8fWZN9ISf++yERuoQSDG9rqdO51uW9E1vEXmcgSiDG8sS0A3c69LveNlK1QLMHqMw+R/HNfpCUnqeUYVNekMqTzRTj4OE16lyxdzr0u942UTcIYVp99hIzV/ZGZSq/X2ta+LtOKgaUbN27A2NgYAQEBMts7d+6M9PR0vHjxosznWllZldhma2sLW1tbpKamqjrUSnU1JgfPUvkY10y1t4gkRJN+v5eCQQ1sYGFI1y4T3bD1TjKGNrSFpZHWXF1OiEr9fjcFuYUSTYdBiNL23E+FvYk+utW20nQohKjFX0/SEZddqOkwSDWkFQNL0dHRcHV1LbFIVs2aNaWPyyMxMREpKSlwd3cv9bFhw4ahT58+mDBhAvbs2QOBQKB48Gq05U4yetazpltEEp0RmyXAmVdZGOtnr+lQCFGJV+kFOB+VLT37TYiuKRBJsPLqW6pxUuUxxrD1TjLGN7MHj6v6dWcI0TQJY1gR8hYj/5tBTUhl0orTqzk5OXB0LHkrRDMzM+njFSUWi7FhwwYYGRmhV69eMo/Vr18fAQEBcHV1RWFhIcLDw3H48GE8efIEK1asAJerFeNsAICkXCEOP8nA8WF1NR0KISqzKyIV9WyN4O+qnjU6CKls2+4ko4WLKZq5qP4uWYRog+3hySgUM4xqYoefNB0MIUq4Ep2DV+kFGNOUTm4R3XTkaQYi0wX4o6MDtmo6GFLtaMXAEoByV6yv6Gr2jDH8+uuvePz4MebMmQN7e9k/HCNGjJD5vnnz5nBwcMCOHTtw8+ZN+Pv7f/QYCQkJ0msunz59WqG4FPHHvRR4Whmgs1fRomvW1tYICgqCtbW1Wo6n7vY1eWxN9o28I2EMOyJSMKWlo/R3Wpdzr8t9I0UKRBLsjEjFT5+6yWzX5dzrct9ISflCMVZeTcDsAGe4OprpbO6prquHLXeS0dvbGs7m764E0OXc63LfSEkSxrA8JB4Tm9ujrquNzuae6lp7acXAkrm5eamzknJzcwG8m7lUHsYYNmzYgCtXrmDatGlo3bp1hY7dsWNH7NixA8+fP6/QwNLWrVuxZMmSCrWtKLGEYVt4Mr5p5Qjufx/Azc3NMWnSJLUdU93ta/LYmuwbeefi62zEZwsxorGddJsu516X+0aK/P0kHSIJw+AGNjLbdTn3utw3UtKW28ngcoBJzR1hrM/V2dxTXeu+pFwhjjzNwInhslcC6HLudblvpKRjzzPxIq0AJ4fXg7m5gc7mnupae2nFtV8eHh6Ii4srcfe3N2/eSB8vT/Gg0oULFzBlyhR06tRJ7hgqOitq4sSJCA8PR3h4OIKDg+U+TkWcfJmJ5DwhAn3fzbhKS0vD6NGjkZaWppZjqrt9TR5bk30j7/x+NwW9vK1gb6ov3abLudflvpEi28KTMaqJHUwNZNcH1OXc63LfiKzcQjF+Dk3A3HYuMNbn6nTudblvpMiO/64E+KSm7O3XdTn3utw3IosxhuVX4jHezwHO5gY6nXtd7ltVpxUDS/7+/uDz+bh+/brM9osXL8LGxgZ165a9zhBjDBs3bsSFCxcwefJkdOnSRa5jX7x4EQBQr169Cu3v7OwMPz8/+Pn5wcfHR65jVVTQnWQMbmgLG+N3E8ry8vKwa9cu5OXlqeWY6m5fk8fWZN9IkdR8IY4+y8DYD9Y10OXc63LfCPAwKR/XYnIxoZQFjXU597rcNyJr480kGOlxpTdb0OXc63LfSNGVANvvJmNCMwfplQDFdDn3utw3Iuv4i0w8SeHj+wBnALqde13uW1WnFZfCNWvWDL6+vggKCkJ+fj6cnZ0REhKCu3fvYsaMGdK7xf3666+4ePEitm3bBgeHojfz27Ztw7lz59ClSxd4eHjg2bNn0nb19fVRq1YtAMDjx49x8OBB+Pv7w9HREUKhEOHh4Thz5gwaN26Mli1bVn7HSxGZXoCzr7IQNq6+pkMhRGX2PkiDk5k+unhZajoUQlTiXGQW2nuYo769saZDIUTlsgVirL6egBWd3WCkpxXnIAlR2NnILCTkCBHoa/fxnQmpYopnK43zs4eLOd1JnGiOVgwsAcDcuXMRHByMP//8Ezk5OXB1dcWsWbPQvn176T4SiQQSiQSMMem227dvAwDOnz+P8+fPy7Tp4OCA3377DUDRQlw8Hg8HDhxAdnY2OBwOnJ2dMWzYMPTt21dr7gi3LTwZfs4maFGD7ppFdANjDL/fTcGXvnR7X6I7ZrRxxqQWdPt1opv+dyMRlkY8fNmUPoiTqi9PKMHUVo6wM9H/+M6EVDEnX2bhYTIfh4fQncSJZmnNwJKxsTHGjx+P8ePHl7nP9OnTMX36dJltxQNHH+Pi4oKFCxcqE6LaFYgk2HEvFSu7uJV4jMvlwtraWm0DYOpuX5PH1mTfCHAzPg9PUvgYXcoHFF3OvS73jRQx0eeVul2Xc6/LfSNFMvgirAtLxJqu7jDgvcuDLudel/tGgAH1bTCgvk2pj+ly7nW5b6QI++9OcGOa2sPV4t1sJV3OvS73rarTmoElAhx6XHSHoaGNSv7xc3V1RXp6utqOre72NXlsTfaNALfjc9GtjiXcLQ1LPKbLudflvpHy6XLudblvpMi6sETYm+phZBPZkwG6nHtd7hspny7nXpf7RoqciczCvYR8HBhYW2a7Ludel/tW1dFQnBapbWOI1V3dSz0LLhKJ8PbtW4hEIrUcW93ta/LYmuwbAaa2csKRMqbn6nLudblvpHy6nHtd7hsputHC/24mYkGHGtD74NJlXc69LveNlE+Xc6/LfSNFs5WWXYnHaF+7EidvdTn3uty3qo4GlrSIv5s5xnxw16xib9++RY0aNfD27Vu1HFvd7Wvy2JrsGyny4QeUYrqce13uGymfLudel/tGgAOP0uFmYYChDW1LPKbLudflvpHy6XLudblvBDgflY07b/Mxp51Licd0Ofe63Leqji6FI4QQQgghmNzCAYMa2NCNFgghRMsZ6nGwtFMNeFqVXGqCEE2ggSVCCCGEEAIOhwN7U7pzFiGEaLv2HhZo72Gh6TAIkaJL4QghhBBCCCGEEEKIQmhgqYqwsrLCL7/8AisrqyrZviaPrcm+kfLpcu51uW+kfLqce13uGymfLudel/tGyqfLudflvpHy6XLudblvVR2HMcY0HURVdffuXTRr1gzh4eHw8/OTbo+KioKXl5cGIysfxaccbY9PWVTX6kHxaRbVtXpQfJpFda0eFJ9mUV2rB8WnWVTX6kHxaQ+asVRFpKenY8qUKUhPT6+S7Wvy2JrsGymfLudel/tGyqfLudflvpHy6XLudblvpHy6nHtd7hspny7nXpf7VtXRwFIVkZubi02bNiE3N7dKtq/JY2uyb6R8upx7Xe4bKZ8u516X+0bKp8u51+W+kfLpcu51uW+kfLqce13uW1VX7e4Kx+fzERwcjNDQUOTk5MDV1RX9+/dH+/btNR0aIYQQQgghhBBCSJVS7QaWVq5ciZcvXyIwMBAuLi4ICQnB6tWrwRhDhw4dNB0eIYQQQgghhBBCSJVRrQaW7ty5g4iICMycOVM6iNS4cWMkJydjx44dCAgIAI/H03CUZdPX16/S7Wvy2JrsGymfLudel/tGyqfLudflvpHy6XLudblvpHy6nHtd7hspny7nXpf7VpVVq4GlGzduwNjYGAEBATLbO3fujDVr1uDFixfw8fHRUHTlc3d3R2FhYZVtX5PH1mTfSPl0Ofe63DdSPl3OvS73jZRPl3Ovy30j5dPl3Oty30j5dDn3uty3qq5aLd4dHR0NV1fXErOSatasKX1cW0kkEmRnZ0MikVTJ9jV5bE32jZRPl3Ovy30j5dPl3Oty30j5dDn3utw3Uj5dzr0u942UT5dzr8t9q+qq1cBSTk4OzMzMSmwv3paTk1PZIVVYXFwcLC0tERcXVyXb1+SxNdk3Uj5dzr0u942UT5dzr8t9I+XT5dzrct9I+XQ597rcN1I+Xc69LvetqqtWl8IBAIfDUeixYgkJCUhISAAAPH36VGVxEUIIIYQQQgghhFQ11WpgydzcvNRZSbm5uQBQ6mymD23duhVLlixReWyEEEIIIYQQQgghVU21Gljy8PDA1atXIRaLZdZZevPmjfTxj5k4cSJ69eoFAIiIiMDYsWNLzFyKi4tDZmamyuIGIJ0l9fDhQ6SmpirVVmnxqbJ9eX14bFX//FTdN3XkV1O8vb1hYmIis43P5wMoOSOP6lo+VNeaQ3WtPlTXmkN1rT5U15pDda0+VNeaQ3WtPlTXmlNaXctg1cidO3dYz549WUhIiMz2RYsWscDAQCYSieRqLzg4mAGgL/qqsl/h4eFU1/Slc19U1/Sli19U1/Sli19U1/Sli19U1/Sli1+l1fX7OIwxhmpk4cKFePXqFQIDA+Hs7IyQkBCcPXsWM2bMQMeOHeVqKzU1FWfOnIGnpyeMjY0BFI1CjxgxAsHBwfDx8VFDD5RD8SlH2+OTV2kjz1TXqkfxVS6q68pB8VUuquvKQfFVLqrrykHxVS6q68pB8VWuj81YqlaXwgHA3LlzERwcjD///BM5OTlwdXXFrFmz0L59e7nbsrOzw/Dhw0t9zMfHB35+fsqGqzYUn3K0PT5lUF2rD8WnOVTX6kPxaQ7VtfpQfJpDda0+FJ/mUF2rD8WnHardwJKxsTHGjx+P8ePHazoUQgghhBBCCCGEkCqNq+kAdI2zszMWLVoEZ2dnTYdSKopPOdoen7poe78pPuVoe3zqou39pviUo+3xqYu295viU462x6cu2t5vik852h6fumh7vyk+5Wh7fKpW7dZYIoQQQgghhBBCCCGqQTOWCCGEEEIIIYQQQohCaGCJEEIIIYQQQgghhCiEBpYIIYQQQgghhBBCiEKq3V3htMEvv/yCBw8eoLCwEA4ODhg1ahRatGih6bBKePbsGWbPno1hw4Zh8ODBmg5Hat68eXj+/Dl4PB4AoE6dOlixYoWGo5J17tw5HDp0CJmZmbCzs8OCBQt0fuE2qmvlUF1rJ6pr5VBdayeqa+VQXWsnqmvlUF1rJ6pr5VBdVx4aWNKAwYMHY/r06dDX18eLFy+wcOFCbNu2DRYWFpoOTUoikeC3335DnTp1NB1KqaZMmYJOnTppOoxS3bp1C8ePH8f8+fPh5uaGhIQEmJubazostaO6Vh7VtfahulYe1bX2obpWHtW19qG6Vh7VtfahulYe1XXloIElDXB3d5f+n8fjQSQSIS0tTateIE6fPg0fHx/k5ORoOpQq58CBAxg7dqw0zy4uLhqOqHJQXes2qmuqa11EdU11rYuorqmudRHVNdW1LtKluqaBpY/Iz8/HgQMH8Pr1a0RFRSE7OxtDhgzBsGHDSuzL5/MRHByM0NBQ5OTkwNXVFf3790f79u1L7LtmzRpcv34dQqEQzZs3h6enp9bEl52djePHj2P16tXYvn27QnGpMz4A+P333/H777/D09MTY8aMgZeXl1bEJxaLERUVhTdv3mD9+vXg8Xjo3LkzhgwZAg6Ho1CM6kB1TXUtT3xU11TXisYHUF0ri+qa6lqe+Kiuqa4VjQ+gulYW1TXVtTzxVZW6rigaWPqInJwcnD17Fp6enmjdujXOnj1b5r4rV67Ey5cvERgYCBcXF4SEhGD16tVgjKFDhw4y+86cORPTp0/HgwcPEBsbq3DxqCO+3bt3o3fv3jA1NVUoJnXHN3r0aLi5uYHL5eLUqVNYvHgxgoKCFIpX1fFlZmZCLBYjIiICGzZsQF5eHhYtWgQHBwd07txZ7vjUhepaOVTXVNfaEh/VteLxUV1TXSsaH9W18qiulUN1TXWtLfFRXSseX1Wp6wpjpFwSiYRJJBLGGGNZWVmsZ8+ebO/evSX2u337NuvZsye7fPmyzPYFCxawwMBAJhKJyjzGkiVL2O3bt7UivpcvX7Jvv/2WicVixhhj69atY/v371coNnXEV5qvv/6a3blzRyviy8nJYT179mQPHz6U7nP48GG2atUqheJTF6prqmt54qO6fofqmuq6slFdU13LEx/V9TtU11TXlY3qmupanviqSl1XFFfTA1vajsPhVGhU+MaNGzA2NkZAQIDM9s6dOyM9PR0vXrwo87kSiQQJCQlaEd/jx48RExODkSNHYvjw4bh69Sr++usvrFu3TiviK+sYjDGtiM/MzAw2NjYKxVKZqK6pruWJj+r6HaprquvKRnVNdS1PfFTX71BdU11XNqprqmt54qsqdV1RNLCkItHR0XB1dZXeyrBYzZo1pY8DQEZGBq5fv46CggKIxWJcu3YNDx8+RMOGDbUivs8++wxbtmzB//73P/zvf/9Dy5Yt0b17d4wdO1Yr4svNzcW9e/cgFAohFApx/PhxZGZmwtvbWyviA4peNA4fPoz8/Hykpqbi7NmzaN68uVrjUxeq68qJj+q6clFdV058VNeVi+q6cuKjuq5cVNeVEx/VdeWiuq6c+KiuKxetsaQiOTk5cHR0LLHdzMxM+nixY8eO4ddffwWHw4GzszO+//57aaFpOj5jY2MYGxtLHzc0NISJiYna7zxQ0fjEYjH27NmDuLg46OnpoWbNmli4cKF0P03HBwBDhgzB1q1bMWbMGBgbG6Nr165ae4vLj6G6rpz4qK4rF9V15cRHdV25qK4rJz6q68pFdV058VFdVy6q68qJj+q6ctHAkgqVNzWu+DFra2v89NNPlRVSqTHI89j06dPVFE3FY3j/MUtLS6xdu7ayQio1ho89pq+vjylTpmDKlCmVEZbaUV0rh+paO1FdK4fqWjtRXSuH6lo7UV0rh+paO1FdK4fqWvvQpXAqYm5uLjP6WCw3NxcA1D4y+jEUn3K0PT510fZ+U3zK0fb41EXb+03xKUfb41MXbe83xaccbY9PXbS93xSfcrQ9PnXR9n5TfMrR9vjUhQaWVMTDwwNxcXEQi8Uy29+8eSN9XJMoPuVoe3zqou39pviUo+3xqYu295viU462x6cu2t5vik852h6fumh7vyk+5Wh7fOqi7f2m+JSj7fGpCw0sqYi/vz/4fD6uX78us/3ixYuwsbFB3bp1NRRZEYpPOdoen7poe78pPuVoe3zqou39pviUo+3xqYu295viU462x6cu2t5vik852h6fumh7vyk+5Wh7fOpCayxVQHh4OAoKCsDn8wEAsbGxCA0NBQA0b94choaGaNasGXx9fREUFIT8/Hw4OzsjJCQEd+/exYwZM0qsCk/xUXyapu39pvh0Oz510fZ+U3y6HZ+6aHu/KT7djk9dtL3fFJ9ux6cu2t5vik+349MkDmOMaToIbTdu3DgkJyeX+tj27dulq77z+XwEBwfj2rVryMnJgaurKwYMGID27dtTfBSf1tH2flN8uh2fumh7vyk+3Y5PXbS93xSfbsenLtreb4pPt+NTF23vN8Wn2/FpEg0sAu2eMgAACxpJREFUEUIIIYQQQgghhBCF0BpLhBBCCCGEEEIIIUQhNLBECCGEEEIIIYQQQhRCA0uEEEIIIYQQQgghRCE0sEQIIYQQQgghhBBCFEIDS4QQQgghhBBCCCFEITSwRAghhBBCCCGEEEIUQgNLhBBCCCGEEEIIIUQhNLBECCGEEEIIIYQQQhRCA0uEEEIIIYQQQgghRCE0sEQIIYQQQgghhBBCFEIDS4QQQghRCofDqdDX5cuXMXr0aHh6emo65BKuXr0KQ0NDREdHS7d17NgRHTt21FxQVYgieb1w4QLMzMwQHx+vnqAIIYQQUik4jDGm6SAIIYQQUnXduHFD5vtly5bh0qVLuHjxosz2+vXrIyUlBdnZ2WjatGllhlguxhiaN28Of39/bNy4Ubr9yZMnAIriJuUbPXo0Ll++jDdv3sj1vE8++QRubm7YtWuXegIjhBBCiNrpaToAQgghhFRtrVu3lvne3t4eXC63xHYAsLCwqKywKuz06dO4e/cu/vzzT5ntNKCkfl9//TUGDx6M5cuXw83NTdPhEEIIIUQBdCkcIYQQQipNaZdMcTgcTJkyBTt27EC9evVgbGyM5s2b48aNG2CM4ZdffkHNmjVhZmaGTz75BK9evSrR7vnz59G5c2dYWFjAxMQEbdu2xYULFyoUU1BQEFq0aIF69erJbP/wUrg3b96Aw+Fg9erVWLt2rTQmf3//ErO2SpOfn49Zs2ahZs2aMDIygo2NDZo3b459+/bJ7Hfnzh306tULNjY2MDIyQtOmTXHw4MES7cXHx2PChAlwc3ODgYEBXFxcMGDAACQlJUn3iYmJwYgRI+Dg4ABDQ0P4+PhgzZo1kEgkCvdr586dqFevnrS93bt3l/lzbdKkCczMzGBubg5vb2/MmzdPZp+ePXvCzMwM27dv/+jPjxBCCCHaiWYsEUIIIUTj/v33X9y7dw8//fQTOBwOZs+ejS+++AKBgYGIiorCxo0bkZWVhRkzZqB///6IiIgAh8MBAAQHB2PUqFHo3bs3du3aBX19fWzduhVdu3bFmTNn0Llz5zKPW1hYiPPnz2Pq1KkVjnXTpk3w9vbG+vXrAQALFixA9+7d8fr1a1haWpb5vBkzZmDPnj1Yvnw5mjZtiry8PDx69AhpaWnSfS5duoTPP/8crVq1wpYtW2BpaYn9+/dj8ODByM/Px+jRowEUDSq1aNECQqEQ8+bNQ+PGjZGWloYzZ84gIyMDjo6OSElJQZs2bVBYWIhly5bB09MT//77L2bNmoXIyEhs3rxZ7n7t3LkTX375JXr37o01a9YgKysLixcvhkAgAJf77nzl/v37MXnyZEydOhWrV68Gl8vFq1evpJcXFjMwMECbNm1w4sQJLF26tMI5IIQQQogWYYQQQgghKhQYGMhMTU3LfMzDw0NmGwDm5OTEcnNzpduOHj3KADBfX18mkUik29evX88AsAcPHjDGGMvLy2M2NjasZ8+eMm2KxWLWpEkT1rJly3JjvXnzJgPA9u/fX+KxDh06sA4dOki/f/36NQPAGjVqxEQikXT7rVu3GAC2b9++co/VsGFD1qdPn3L38fb2Zk2bNmVCoVBme48ePZizszMTi8WMMcbGjBnD9PX12ZMnT8psa86cOQwAu3nzpsz2r776inE4HPb8+XO5+iUWi5mLiwvz8/OTycmbN2+Yvr6+TF6nTJnCrKysyu1rsR9++IFxuVyZ/BNCCCGk6qBL4QghhBCicZ06dYKpqan0ex8fHwBAt27dpDOT3t9efPe269evIz09HYGBgRCJRNIviUSCzz//HLdv30ZeXl6Zx3379i0AwMHBocKxfvHFF+DxeNLvGzduLBNTWVq2bIlTp05hzpw5uHz5Mvh8vszjr169wrNnzzB8+HAAkOlP9+7dkZCQgOfPnwMATp06hU6dOkl/HqW5ePEi6tevj5YtW8psHz16NBhjJRZX/1i/nj9/jrdv32LYsGEyOfHw8ECbNm1K9DUzMxNDhw7FP//8g9TU1DLjdHBwgEQiQWJiYpn7EEIIIUR70cASIYQQQjTOxsZG5nsDA4NytxcUFACAdD2hAQMGQF9fX+br559/BmMM6enpZR63eHDHyMiowrHa2trKfG9oaCjTVll+/fVXzJ49G0ePHkWnTp1gY2ODPn364OXLlzJ9mTVrVom+TJ48GQCkAzQpKSlwdXUt93hpaWlwdnYusd3FxUX6uDz9Kt7fycmpRJsfbhs5ciT++OMPREdHo3///nBwcECrVq1w7ty5Es8t/tl/7OdHCCGEEO1EaywRQgghpMqys7MDAGzYsKHUu9ABgKOj40efX97gk6qYmppiyZIlWLJkCZKSkqSzl3r27Ilnz55JY5k7dy769etXahvFC4zb29sjLi6u3OPZ2toiISGhxPbiWVrFx6uo4oGn0mYWlbbtyy+/xJdffom8vDyEhIRg0aJF6NGjB168eAEPDw/pfsU/e3njIYQQQoh2oIElQgghhFRZbdu2hZWVFZ48eYIpU6bI/fziS8kiIyNVHVq5HB0dMXr0aNy/fx/r169Hfn4+6tWrhzp16uD+/fv48ccfy31+t27dsGfPHjx//rzE3eyKde7cGStXrsTdu3fh5+cn3b57925wOBx06tRJrpjr1asHZ2dn7Nu3DzNmzJBeDhcdHY3r169LZ0J9yNTUFN26dUNhYSH69OmDx48fywwsRUVFwdbWttwBQEIIIYRoLxpYIoQQQkiVZWZmhg0bNiAwMBDp6ekYMGAAHBwckJKSgvv37yMlJQVBQUFlPt/V1RVeXl64ceMGvvnmG7XG2qpVK/To0QONGzeGtbU1nj59ij179sDf3x8mJiYAgK1bt6Jbt27o2rUrRo8ejRo1aiA9PR1Pnz7F3bt3cejQIQDA0qVLcerUKbRv3x7z5s1Do0aNkJmZidOnT2PGjBnw9vbGt99+i927d+OLL77A0qVL4eHhgRMnTmDz5s346quvULduXbni53K5WLZsGcaNG4e+ffti/PjxyMzMxOLFi0tcCjd+/HgYGxujbdu2cHZ2RmJiIlauXAlLS0u0aNFCZt8bN26gQ4cOMus2EUIIIaTqoIElQgghhFRpI0aMgLu7O1atWoWJEyciJycHDg4O8PX1xejRoz/6/OHDh2Pjxo0QCATSdYXU4ZNPPsGxY8ewbt065Ofno0aNGhg1ahR++OEH6T6dOnXCrVu3sGLFCkyfPh0ZGRmwtbVF/fr1MWjQIOl+NWrUwK1bt7Bo0SL89NNPSEtLg729PQICAqTrUtnb2+P69euYO3cu5s6di+zsbHh5eWHVqlWYMWOGQn0YO3YsAODnn39Gv3794OnpiXnz5uHKlSu4fPmydL927dph586dOHjwIDIyMmBnZ4eAgADs3r0b9vb20v0iIyPx8OFDLF68WKF4CCGEEKJ5HMYY03QQhBBCCCGa8vbtW9SsWRO7d+/G4MGDNR1OtbJgwQLs3r0bkZGR0NOj852EEEJIVUQDS4QQQgip9mbPno1Tp04hIiICXC7dNLcyZGZmwsvLCxs2bMDw4cM1HQ4hhBBCFESnhgghhBBS7c2fPx8mJiaIj4+Hm5ubpsOpFl6/fo25c+di2LBhmg6FEEIIIUqgGUuEEEIIIYQQQgghRCE015sQQgghhBBCCCGEKIQGlgghhBBCCCGEEEKIQmhgiRBCCCGEEEIIIYQohAaWCCGEEEIIIYQQQohCaGCJEEIIIYQQQgghhCiEBpYIIYQQQgghhBBCiEJoYIkQQgghhBBCCCGEKIQGlgghhBBCCCGEEEKIQv4PnOGeKQDzrDcAAAAASUVORK5CYII=\n", + "text/plain": [ + "<Figure size 1400x300 with 12 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (311683578)>" + ] + }, + "execution_count": 242, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dummy_df = duration_cdf_df.loc[:1, :].copy()\n", + "dummy_df.loc[0, 'dummy'] = '0'\n", + "dummy_df.loc[1, 'dummy'] = '1'\n", + "\n", + "marker_df = pd.DataFrame({\n", + " 'sec': [60*60, 60*60*4, 60*60*24, 60*60*24*4],\n", + " 'y': [1, 1, 1, 1],\n", + " 'text': ['1 hour', '4 hours', '1 day', '4 days']\n", + "})\n", + "\n", + "plt = ggplot(median_cdf_df) +\\\n", + " geom_line(aes(x='duration', y='cdf'), data=duration_cdf_df, color='black') +\\\n", + " geom_line(aes(x='ia', y='cdf'), data=ia_cdf_df, color='#0280c9') +\\\n", + " geom_line(aes(x='duration', y='cdf', color='dummy'), data=dummy_df) +\\\n", + " scale_x_log10(breaks=[1000, 10000, 100000, 1000000], labels=lambda l: list(map(lambda x: '$10^{}$'.format(int(np.log10(x))), l))) +\\\n", + " geom_vline(aes(xintercept='sec'), data=marker_df, linetype='--') +\\\n", + " facet_wrap(facets='vendor_cat', nrow=2) +\\\n", + " ylab('ECDF') +\\\n", + " xlab('Time (in seconds)') +\\\n", + " scale_color_manual(['black', '#0280c9'], labels=['Duration', 'Interarrival time']) +\\\n", + " guides(color=guide_legend(title='')) +\\\n", + " theme_classic(base_size=12, base_family='sans-serif') +\\\n", + " theme(figure_size=(14, 3),\n", + " axis_text_y=element_text(margin={'r': 5}),\n", + " panel_grid_major_x=element_line(size=0.7, color=\"gainsboro\"),\n", + " text=element_text(size=12),\n", + " legend_box_spacing=0.01,\n", + " legend_box_margin=0,\n", + " legend_margin=0,\n", + " legend_key=element_blank(),\n", + " legend_entry_spacing=5,\n", + " legend_background=element_rect(fill=(0,0,0,0), color=(0,0,0,0)),\n", + " legend_position='top')\n", + "\n", + "plt.save('plots/failure_duration_ia_cdf.pdf', limitsize=None)\n", + "plt" + ] + }, + { + "cell_type": "code", + "execution_count": 243, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:727: PlotnineWarning: Saving 14 x 3 in image.\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:730: PlotnineWarning: Filename: plots/failure_mean_peak_cdf.pdf\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/geoms/geom_path.py:75: PlotnineWarning: geom_path: Removed 1 rows containing missing values.\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/geoms/geom_path.py:81: PlotnineWarning: geom_path: Each group consist of only one observation. Do you need to adjust the group aesthetic?\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/geoms/geom_path.py:75: PlotnineWarning: geom_path: Removed 1 rows containing missing values.\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/geoms/geom_path.py:81: PlotnineWarning: geom_path: Each group consist of only one observation. Do you need to adjust the group aesthetic?\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1400x300 with 12 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (314657497)>" + ] + }, + "execution_count": 243, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dummy_df = mean_cdf_df.loc[:1, :].copy()\n", + "dummy_df.loc[0, 'dummy'] = '0'\n", + "dummy_df.loc[1, 'dummy'] = '1'\n", + "\n", + "plt = ggplot(median_cdf_df) +\\\n", + " geom_line(aes(x='mean', y='cdf'), data=mean_cdf_df, color='black') +\\\n", + " geom_line(aes(x='peak', y='cdf'), data=peak_cdf_df, color='#0280c9') +\\\n", + " geom_line(aes(x='mean', y='cdf', color='dummy'), data=dummy_df) +\\\n", + " scale_x_log10() +\\\n", + " scale_y_continuous(limits=[0, 1]) +\\\n", + " facet_wrap(facets='vendor_cat', nrow=2) +\\\n", + " ylab('ECDF') +\\\n", + " xlab('Number of reports') +\\\n", + " scale_color_manual(['black', '#0280c9'], labels=['Mean number of reports of failure', 'Peak number of reports of failure']) +\\\n", + " guides(color=guide_legend(title='')) +\\\n", + " theme_classic(base_size=12, base_family='sans-serif') +\\\n", + " theme(figure_size=(14, 3),\n", + " axis_text_y=element_text(margin={'r': 5}),\n", + " panel_grid_major_x=element_line(size=0.7, color=\"gainsboro\"),\n", + " text=element_text(size=12),\n", + " legend_box_spacing=0.01,\n", + " legend_box_margin=0,\n", + " legend_margin=0,\n", + " legend_key=element_blank(),\n", + " legend_entry_spacing=5,\n", + " legend_background=element_rect(fill=(0,0,0,0), color=(0,0,0,0)),\n", + " legend_position='top')\n", + "\n", + "plt.save('plots/failure_mean_peak_cdf.pdf', limitsize=None)\n", + "plt" + ] + }, + { + "cell_type": "code", + "execution_count": 246, + "metadata": {}, + "outputs": [], + "source": [ + "filtered_failure_df['parsed_start_time'] = pd.to_datetime(filtered_failure_df['start_time'], unit='s')\n", + "precovid_failure_df = filtered_failure_df[(filtered_failure_df['parsed_start_time'].dt.year == 2019)\n", + " & (filtered_failure_df['parsed_start_time'].dt.month >= 4)\n", + " & (filtered_failure_df['parsed_start_time'].dt.month <= 8)].reset_index(drop=True)\n", + "covid_failure_df = filtered_failure_df[(filtered_failure_df['parsed_start_time'].dt.year == 2020)\n", + " & (filtered_failure_df['parsed_start_time'].dt.month >= 4)\n", + " & (filtered_failure_df['parsed_start_time'].dt.month <= 8)].reset_index(drop=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 247, + "metadata": {}, + "outputs": [], + "source": [ + "def compute_ia(partial_df):\n", + " sorted_partial_df = partial_df.sort_values('start_time').reset_index(drop=True)\n", + " ia_arr = sorted_partial_df['start_time'].values - np.roll(sorted_partial_df['start_time'].values, 1)\n", + " partial_ia_df = pd.DataFrame({'ia': ia_arr[1:], 'count':1, 'vendor_cat': partial_df.loc[0, 'vendor_cat']})\n", + " return partial_ia_df\n", + "\n", + "precovid_ia_partial_df_list = []\n", + "covid_ia_partial_df_list = []\n", + "\n", + "for vendor in precovid_failure_df['vendor_cat'].unique():\n", + " precovid_partial_df = precovid_failure_df[precovid_failure_df['vendor_cat'] == vendor].reset_index(drop=True)\n", + " covid_partial_df = covid_failure_df[covid_failure_df['vendor_cat'] == vendor].reset_index(drop=True)\n", + " \n", + " # Compute interarrival time\n", + " precovid_ia = compute_ia(precovid_partial_df)\n", + " covid_ia = compute_ia(covid_partial_df)\n", + " \n", + " precovid_ia_partial_df_list.append(precovid_ia)\n", + " covid_ia_partial_df_list.append(covid_ia)\n", + "\n", + "precovid_ia_df = pd.concat(precovid_ia_partial_df_list)\n", + "covid_ia_df = pd.concat(covid_ia_partial_df_list)" + ] + }, + { + "cell_type": "code", + "execution_count": 249, + "metadata": {}, + "outputs": [], + "source": [ + "precovid_ia_quantiles = precovid_ia_df.groupby('vendor_cat')['ia'].quantile([0.50, 0.95]).reset_index().sort_values('ia').pivot(index='vendor_cat', columns='level_1')\n", + "covid_ia_quantiles = covid_ia_df.groupby('vendor_cat')['ia'].quantile([0.50, 0.95]).reset_index().sort_values('ia').pivot(index='vendor_cat', columns='level_1')\n", + "# precovid_ia_quantiles" + ] + }, + { + "cell_type": "code", + "execution_count": 250, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead tr th {\n", + " text-align: left;\n", + " }\n", + "\n", + " .dataframe thead tr:last-of-type th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr>\n", + " <th></th>\n", + " <th colspan=\"2\" halign=\"left\">duration</th>\n", + " <th colspan=\"2\" halign=\"left\">ia</th>\n", + " <th colspan=\"2\" halign=\"left\">duration_covid</th>\n", + " <th colspan=\"2\" halign=\"left\">ia_covid</th>\n", + " </tr>\n", + " <tr>\n", + " <th>level_1</th>\n", + " <th>0.50</th>\n", + " <th>0.95</th>\n", + " <th>0.50</th>\n", + " <th>0.95</th>\n", + " <th>0.50</th>\n", + " <th>0.95</th>\n", + " <th>0.50</th>\n", + " <th>0.95</th>\n", + " </tr>\n", + " <tr>\n", + " <th>vendor_cat</th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " <th></th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>Apple</th>\n", + " <td>0.333333</td>\n", + " <td>2.500000</td>\n", + " <td>98.000000</td>\n", + " <td>560.033333</td>\n", + " <td>0.500000</td>\n", + " <td>0.650000</td>\n", + " <td>899.666667</td>\n", + " <td>899.666667</td>\n", + " </tr>\n", + " <tr>\n", + " <th>Skype</th>\n", + " <td>0.333333</td>\n", + " <td>4.633333</td>\n", + " <td>99.333333</td>\n", + " <td>416.800000</td>\n", + " <td>0.333333</td>\n", + " <td>1.483333</td>\n", + " <td>178.666667</td>\n", + " <td>1070.333333</td>\n", + " </tr>\n", + " <tr>\n", + " <th>Github</th>\n", + " <td>0.333333</td>\n", + " <td>1.000000</td>\n", + " <td>60.666667</td>\n", + " <td>308.600000</td>\n", + " <td>1.000000</td>\n", + " <td>1.666667</td>\n", + " <td>158.333333</td>\n", + " <td>646.066667</td>\n", + " </tr>\n", + " <tr>\n", + " <th>Gmail</th>\n", + " <td>0.333333</td>\n", + " <td>0.666667</td>\n", + " <td>5.000000</td>\n", + " <td>62.333333</td>\n", + " <td>0.333333</td>\n", + " <td>2.000000</td>\n", + " <td>26.666667</td>\n", + " <td>583.733333</td>\n", + " </tr>\n", + " <tr>\n", + " <th>FB Msgr</th>\n", + " <td>0.333333</td>\n", + " <td>1.200000</td>\n", + " <td>5.666667</td>\n", + " <td>186.200000</td>\n", + " <td>0.333333</td>\n", + " <td>0.533333</td>\n", + " <td>11.000000</td>\n", + " <td>221.350000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>Whatsapp</th>\n", + " <td>0.333333</td>\n", + " <td>0.666667</td>\n", + " <td>4.333333</td>\n", + " <td>26.200000</td>\n", + " <td>0.333333</td>\n", + " <td>0.666667</td>\n", + " <td>11.166667</td>\n", + " <td>376.150000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>Snapchat</th>\n", + " <td>0.333333</td>\n", + " <td>1.333333</td>\n", + " <td>1.333333</td>\n", + " <td>6.666667</td>\n", + " <td>0.333333</td>\n", + " <td>1.333333</td>\n", + " <td>1.666667</td>\n", + " <td>126.500000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>Netflix</th>\n", + " <td>0.333333</td>\n", + " <td>3.416667</td>\n", + " <td>1.333333</td>\n", + " <td>8.333333</td>\n", + " <td>0.333333</td>\n", + " <td>2.766667</td>\n", + " <td>2.000000</td>\n", + " <td>65.916667</td>\n", + " </tr>\n", + " <tr>\n", + " <th>Facebook</th>\n", + " <td>0.333333</td>\n", + " <td>2.000000</td>\n", + " <td>1.333333</td>\n", + " <td>5.000000</td>\n", + " <td>0.333333</td>\n", + " <td>1.266667</td>\n", + " <td>1.666667</td>\n", + " <td>69.566667</td>\n", + " </tr>\n", + " <tr>\n", + " <th>Twitter</th>\n", + " <td>0.666667</td>\n", + " <td>5.666667</td>\n", + " <td>1.666667</td>\n", + " <td>10.666667</td>\n", + " <td>0.333333</td>\n", + " <td>7.866667</td>\n", + " <td>5.000000</td>\n", + " <td>92.550000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>YouTube</th>\n", + " <td>0.333333</td>\n", + " <td>2.333333</td>\n", + " <td>1.333333</td>\n", + " <td>6.333333</td>\n", + " <td>0.333333</td>\n", + " <td>1.666667</td>\n", + " <td>2.000000</td>\n", + " <td>44.700000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>Instagram</th>\n", + " <td>0.333333</td>\n", + " <td>6.000000</td>\n", + " <td>2.000000</td>\n", + " <td>8.633333</td>\n", + " <td>0.333333</td>\n", + " <td>3.333333</td>\n", + " <td>3.000000</td>\n", + " <td>29.733333</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " duration ia duration_covid \\\n", + "level_1 0.50 0.95 0.50 0.95 0.50 \n", + "vendor_cat \n", + "Apple 0.333333 2.500000 98.000000 560.033333 0.500000 \n", + "Skype 0.333333 4.633333 99.333333 416.800000 0.333333 \n", + "Github 0.333333 1.000000 60.666667 308.600000 1.000000 \n", + "Gmail 0.333333 0.666667 5.000000 62.333333 0.333333 \n", + "FB Msgr 0.333333 1.200000 5.666667 186.200000 0.333333 \n", + "Whatsapp 0.333333 0.666667 4.333333 26.200000 0.333333 \n", + "Snapchat 0.333333 1.333333 1.333333 6.666667 0.333333 \n", + "Netflix 0.333333 3.416667 1.333333 8.333333 0.333333 \n", + "Facebook 0.333333 2.000000 1.333333 5.000000 0.333333 \n", + "Twitter 0.666667 5.666667 1.666667 10.666667 0.333333 \n", + "YouTube 0.333333 2.333333 1.333333 6.333333 0.333333 \n", + "Instagram 0.333333 6.000000 2.000000 8.633333 0.333333 \n", + "\n", + " ia_covid \n", + "level_1 0.95 0.50 0.95 \n", + "vendor_cat \n", + "Apple 0.650000 899.666667 899.666667 \n", + "Skype 1.483333 178.666667 1070.333333 \n", + "Github 1.666667 158.333333 646.066667 \n", + "Gmail 2.000000 26.666667 583.733333 \n", + "FB Msgr 0.533333 11.000000 221.350000 \n", + "Whatsapp 0.666667 11.166667 376.150000 \n", + "Snapchat 1.333333 1.666667 126.500000 \n", + "Netflix 2.766667 2.000000 65.916667 \n", + "Facebook 1.266667 1.666667 69.566667 \n", + "Twitter 7.866667 5.000000 92.550000 \n", + "YouTube 1.666667 2.000000 44.700000 \n", + "Instagram 3.333333 3.000000 29.733333 " + ] + }, + "execution_count": 250, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "precovid_duration_quantiles = precovid_failure_df.groupby('vendor_cat')['duration'].quantile([0.50, 0.95]).reset_index().sort_values('duration').pivot(index='vendor_cat', columns='level_1')\n", + "covid_duration_quantiles = covid_failure_df.groupby('vendor_cat')['duration'].quantile([0.50, 0.95]).reset_index().sort_values('duration').pivot(index='vendor_cat', columns='level_1')\n", + "covid_table = precovid_duration_quantiles.join(precovid_ia_quantiles).join(covid_duration_quantiles, rsuffix='_covid').join(covid_ia_quantiles, rsuffix='_covid') / 3600\n", + "covid_table" + ] + }, + { + "cell_type": "code", + "execution_count": 251, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\\begin{tabular}{lrrrrrrrr}\n", + "\\toprule\n", + "{} & \\multicolumn{2}{l}{duration} & \\multicolumn{2}{l}{ia} & \\multicolumn{2}{l}{duration\\_covid} & \\multicolumn{2}{l}{ia\\_covid} \\\\\n", + "level\\_1 & 0.50 & 0.95 & 0.50 & 0.95 & 0.50 & 0.95 & 0.50 & 0.95 \\\\\n", + "vendor\\_cat & & & & & & & & \\\\\n", + "\\midrule\n", + "Apple & 0.3 & 2.5 & 98.0 & 560.0 & 0.5 & 0.7 & 899.7 & 899.7 \\\\\n", + "Skype & 0.3 & 4.6 & 99.3 & 416.8 & 0.3 & 1.5 & 178.7 & 1070.3 \\\\\n", + "Github & 0.3 & 1.0 & 60.7 & 308.6 & 1.0 & 1.7 & 158.3 & 646.1 \\\\\n", + "Gmail & 0.3 & 0.7 & 5.0 & 62.3 & 0.3 & 2.0 & 26.7 & 583.7 \\\\\n", + "FB Msgr & 0.3 & 1.2 & 5.7 & 186.2 & 0.3 & 0.5 & 11.0 & 221.3 \\\\\n", + "Whatsapp & 0.3 & 0.7 & 4.3 & 26.2 & 0.3 & 0.7 & 11.2 & 376.1 \\\\\n", + "Snapchat & 0.3 & 1.3 & 1.3 & 6.7 & 0.3 & 1.3 & 1.7 & 126.5 \\\\\n", + "Netflix & 0.3 & 3.4 & 1.3 & 8.3 & 0.3 & 2.8 & 2.0 & 65.9 \\\\\n", + "Facebook & 0.3 & 2.0 & 1.3 & 5.0 & 0.3 & 1.3 & 1.7 & 69.6 \\\\\n", + "Twitter & 0.7 & 5.7 & 1.7 & 10.7 & 0.3 & 7.9 & 5.0 & 92.5 \\\\\n", + "YouTube & 0.3 & 2.3 & 1.3 & 6.3 & 0.3 & 1.7 & 2.0 & 44.7 \\\\\n", + "Instagram & 0.3 & 6.0 & 2.0 & 8.6 & 0.3 & 3.3 & 3.0 & 29.7 \\\\\n", + "\\bottomrule\n", + "\\end{tabular}\n", + "\n" + ] + } + ], + "source": [ + "print(covid_table.to_latex(float_format=\"%.1f\"))" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.1" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/datasets/Talluri2021/other notebooks/5.covid period comparison.ipynb b/datasets/Talluri2021/other notebooks/5.covid period comparison.ipynb new file mode 100644 index 0000000..15eaf77 --- /dev/null +++ b/datasets/Talluri2021/other notebooks/5.covid period comparison.ipynb @@ -0,0 +1,229 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "from plotnine import *" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "or_events = pd.read_parquet('./outage_report_2019-20')" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "filtered_or_events = or_events[(or_events['vendor'] != '') & (or_events['vendor'] != 'overview')].reset_index(drop=True)\n", + "filtered_or_events = filtered_or_events.drop_duplicates(subset=['vendor', 'event_time', 'status_code'])\n", + "# Combine events with the same event_time, but different status_code with max\n", + "filtered_or_events = filtered_or_events.groupby(['vendor', 'event_time'])['status_code'].max().reset_index()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "filtered_or_events['evtime'] = pd.to_datetime(filtered_or_events['event_time'], unit='s')" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "def proper_vendor_names(series):\n", + " return series.str.capitalize().replace(['Apple-servers', 'Facebook-messenger', 'Youtube'], ['Apple', 'FB Msgr', 'YouTube'])\n", + "\n", + "filtered_or_events['vendor_proper'] = proper_vendor_names(filtered_or_events['vendor'])" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['Apple',\n", + " 'Github',\n", + " 'Skype',\n", + " 'FB Msgr',\n", + " 'Gmail',\n", + " 'Whatsapp',\n", + " 'Snapchat',\n", + " 'Netflix',\n", + " 'Facebook',\n", + " 'Twitter',\n", + " 'YouTube',\n", + " 'Instagram']" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vendor_list = list(filtered_or_events.groupby('vendor_proper')['status_code'].sum().reset_index().rename(columns={'status_code':'count'}).sort_values('count')['vendor_proper'])\n", + "vendor_list" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "filtered_or_events['year'] = pd.Categorical(filtered_or_events['evtime'].dt.year, ordered=True)\n", + "filtered_or_events['month'] = pd.Categorical(filtered_or_events['evtime'].dt.month, ordered=True)\n", + "filtered_or_events['vendor_cat'] = pd.Categorical(filtered_or_events['vendor_proper'], ordered=True, categories=vendor_list)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "367336.0" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "reports_per_month = filtered_or_events.groupby(['year', 'month', 'vendor_cat'])['status_code'].sum().reset_index().rename(columns={'status_code':'count'})\n", + "subset_reports_per_month = reports_per_month[(reports_per_month['month'] > 3) & (reports_per_month['month'] < 9)]\n", + "subset_reports_per_month['count'].sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "report_count_df_list = []\n", + "\n", + "for vendor in subset_reports_per_month['vendor_cat'].unique():\n", + " partial_df = subset_reports_per_month[subset_reports_per_month['vendor_cat'] == vendor].reset_index(drop=True)\n", + " max_reports = partial_df['count'].max()\n", + " partial_df['prop'] = partial_df['count'] / max_reports\n", + " report_count_df_list.append(partial_df)\n", + " \n", + "reports_per_month_with_prop = pd.concat(report_count_df_list)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:727: PlotnineWarning: Saving 14 x 3 in image.\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:730: PlotnineWarning: Filename: plots/covid_comparison.pdf\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/layer.py:467: PlotnineWarning: geom_bar : Removed 1 rows containing missing values.\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/layer.py:467: PlotnineWarning: geom_bar : Removed 1 rows containing missing values.\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "<Figure size 1400x300 with 12 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (323781768)>" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vendor_maxes = reports_per_month_with_prop.groupby('vendor_cat')['count'].max()\n", + "\n", + "def label_func(vendor):\n", + " if vendor == 'Apple':\n", + " return vendor + ' (max={:,})'.format(int(vendor_maxes.loc[vendor]))\n", + " else:\n", + " return vendor + ' ({:,})'.format(int(vendor_maxes.loc[vendor]))\n", + "\n", + "plt = ggplot(reports_per_month_with_prop) +\\\n", + " theme_classic(base_size=12, base_family='sans-serif') +\\\n", + " theme(figure_size=(14, 3),\n", + " axis_text_y=element_text(margin={'r': 5}),\n", + " panel_grid_minor_x=element_line(size=0.7, color=\"gainsboro\"),\n", + " panel_grid_major_x=element_blank(),\n", + " text=element_text(size=12),\n", + " legend_box_spacing=0.01,\n", + " legend_box_margin=0,\n", + " legend_margin=0,\n", + " legend_key=element_blank(),\n", + " legend_entry_spacing=5,\n", + " legend_background=element_rect(fill=(0,0,0,0), color=(0,0,0,0)),\n", + " legend_position='top',) +\\\n", + " facet_wrap(facets='vendor_cat', nrow=2, labeller=label_func) +\\\n", + " geom_bar(aes(x='month', y='prop', fill='year'), stat='identity', position='dodge') +\\\n", + " scale_fill_manual(['#0280c9', '#78d8da']) +\\\n", + " guides(fill=guide_legend(title='')) +\\\n", + " xlab('Month') +\\\n", + " ylab('Normalized reports/month')\n", + "\n", + "plt.save('plots/covid_comparison.pdf', limitsize=False)\n", + "plt" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/datasets/Talluri2021/other notebooks/8.analyze experiment results.ipynb b/datasets/Talluri2021/other notebooks/8.analyze experiment results.ipynb new file mode 100644 index 0000000..59abcd6 --- /dev/null +++ b/datasets/Talluri2021/other notebooks/8.analyze experiment results.ipynb @@ -0,0 +1,504 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "from plotnine import *" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# results_df = pd.read_csv('structures_experiment_results_1.csv')\n", + "results_df = pd.read_csv('./experiment_results/long_chain_results_sin1.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "results_df['cat_retries'] = pd.Categorical(results_df['retries']).rename_categories({100: 'Fail'})\n", + "# results_df['fraction'] = results_df['reqs'] / (365*24*60*60)\n", + "results_df['fraction'] = results_df['reqs'] / (365*24*60*60/2) # For sin stuff\n", + "min_max_per_exp = results_df.groupby(['vendor', 'experiment', 'cat_retries'])['fraction'].agg(['min', 'max', 'mean']).reset_index().fillna(0)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>Unnamed: 0</th>\n", + " <th>vendor</th>\n", + " <th>reqs</th>\n", + " <th>retries</th>\n", + " <th>iteration</th>\n", + " <th>experiment</th>\n", + " <th>cat_retries</th>\n", + " <th>fraction</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>0</th>\n", + " <td>0</td>\n", + " <td>uniform</td>\n", + " <td>1.499495e+07</td>\n", + " <td>0</td>\n", + " <td>0</td>\n", + " <td>deep chain</td>\n", + " <td>0</td>\n", + " <td>9.509732e-01</td>\n", + " </tr>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>1</td>\n", + " <td>uniform</td>\n", + " <td>7.501410e+05</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>deep chain</td>\n", + " <td>1</td>\n", + " <td>4.757363e-02</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2</th>\n", + " <td>2</td>\n", + " <td>uniform</td>\n", + " <td>2.239900e+04</td>\n", + " <td>2</td>\n", + " <td>0</td>\n", + " <td>deep chain</td>\n", + " <td>2</td>\n", + " <td>1.420535e-03</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3</th>\n", + " <td>3</td>\n", + " <td>uniform</td>\n", + " <td>4.870000e+02</td>\n", + " <td>3</td>\n", + " <td>0</td>\n", + " <td>deep chain</td>\n", + " <td>3</td>\n", + " <td>3.088534e-05</td>\n", + " </tr>\n", + " <tr>\n", + " <th>4</th>\n", + " <td>4</td>\n", + " <td>uniform</td>\n", + " <td>1.100000e+01</td>\n", + " <td>4</td>\n", + " <td>0</td>\n", + " <td>deep chain</td>\n", + " <td>4</td>\n", + " <td>6.976154e-07</td>\n", + " </tr>\n", + " <tr>\n", + " <th>5</th>\n", + " <td>5</td>\n", + " <td>uniform</td>\n", + " <td>1.000000e+00</td>\n", + " <td>5</td>\n", + " <td>0</td>\n", + " <td>deep chain</td>\n", + " <td>5</td>\n", + " <td>6.341958e-08</td>\n", + " </tr>\n", + " <tr>\n", + " <th>6</th>\n", + " <td>6</td>\n", + " <td>uniform</td>\n", + " <td>1.608636e+01</td>\n", + " <td>100</td>\n", + " <td>0</td>\n", + " <td>deep chain</td>\n", + " <td>Fail</td>\n", + " <td>1.020190e-06</td>\n", + " </tr>\n", + " <tr>\n", + " <th>7</th>\n", + " <td>0</td>\n", + " <td>instagram</td>\n", + " <td>1.565882e+07</td>\n", + " <td>0</td>\n", + " <td>0</td>\n", + " <td>deep chain</td>\n", + " <td>0</td>\n", + " <td>9.930757e-01</td>\n", + " </tr>\n", + " <tr>\n", + " <th>8</th>\n", + " <td>1</td>\n", + " <td>instagram</td>\n", + " <td>1.052420e+05</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>deep chain</td>\n", + " <td>1</td>\n", + " <td>6.674404e-03</td>\n", + " </tr>\n", + " <tr>\n", + " <th>9</th>\n", + " <td>2</td>\n", + " <td>instagram</td>\n", + " <td>1.953000e+03</td>\n", + " <td>2</td>\n", + " <td>0</td>\n", + " <td>deep chain</td>\n", + " <td>2</td>\n", + " <td>1.238584e-04</td>\n", + " </tr>\n", + " <tr>\n", + " <th>10</th>\n", + " <td>3</td>\n", + " <td>instagram</td>\n", + " <td>3.320000e+02</td>\n", + " <td>3</td>\n", + " <td>0</td>\n", + " <td>deep chain</td>\n", + " <td>3</td>\n", + " <td>2.105530e-05</td>\n", + " </tr>\n", + " <tr>\n", + " <th>11</th>\n", + " <td>4</td>\n", + " <td>instagram</td>\n", + " <td>1.656685e+03</td>\n", + " <td>100</td>\n", + " <td>0</td>\n", + " <td>deep chain</td>\n", + " <td>Fail</td>\n", + " <td>1.050663e-04</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " Unnamed: 0 vendor reqs retries iteration experiment \\\n", + "0 0 uniform 1.499495e+07 0 0 deep chain \n", + "1 1 uniform 7.501410e+05 1 0 deep chain \n", + "2 2 uniform 2.239900e+04 2 0 deep chain \n", + "3 3 uniform 4.870000e+02 3 0 deep chain \n", + "4 4 uniform 1.100000e+01 4 0 deep chain \n", + "5 5 uniform 1.000000e+00 5 0 deep chain \n", + "6 6 uniform 1.608636e+01 100 0 deep chain \n", + "7 0 instagram 1.565882e+07 0 0 deep chain \n", + "8 1 instagram 1.052420e+05 1 0 deep chain \n", + "9 2 instagram 1.953000e+03 2 0 deep chain \n", + "10 3 instagram 3.320000e+02 3 0 deep chain \n", + "11 4 instagram 1.656685e+03 100 0 deep chain \n", + "\n", + " cat_retries fraction \n", + "0 0 9.509732e-01 \n", + "1 1 4.757363e-02 \n", + "2 2 1.420535e-03 \n", + "3 3 3.088534e-05 \n", + "4 4 6.976154e-07 \n", + "5 5 6.341958e-08 \n", + "6 Fail 1.020190e-06 \n", + "7 0 9.930757e-01 \n", + "8 1 6.674404e-03 \n", + "9 2 1.238584e-04 \n", + "10 3 2.105530e-05 \n", + "11 Fail 1.050663e-04 " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "results_df" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:719: PlotnineWarning: Saving 6.4 x 4.8 in image.\n", + "/home/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:722: PlotnineWarning: Filename: deep chain comparison.png\n", + "/home/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/pandas/core/series.py:726: RuntimeWarning: divide by zero encountered in log10\n", + "/home/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:719: PlotnineWarning: Saving 6.4 x 4.8 in image.\n", + "/home/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:722: PlotnineWarning: Filename: deep chain comparison.pdf\n", + "/home/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/pandas/core/series.py:726: RuntimeWarning: divide by zero encountered in log10\n", + "/home/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/pandas/core/series.py:726: RuntimeWarning: divide by zero encountered in log10\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 640x480 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (8794108912409)>" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "experiment = 'deep chain'\n", + "specific_min_max = min_max_per_exp[(min_max_per_exp['experiment'] == experiment)]\n", + "plt = ggplot(specific_min_max) +\\\n", + " theme_light(base_size=12, base_family='sans-serif') +\\\n", + " theme(text=element_text(size=12), legend_position=(0.3, 0.25)) +\\\n", + " geom_point(aes(x='cat_retries', y='mean', color='vendor', group='vendor'), size=3, shape='s') +\\\n", + " scale_y_log10(limits=[1, 1e-8], breaks = [0.1, 0.01, 0.001, 0.0001, 0.00001, 0.000001, 0.0000001, 0.4e-8],\n", + " labels=['10%', '1%', '0.1%', '$10^{-2}$%', '$10^{-3}$%', '$10^{-4}$%', '$10^{-5}$%', '0']) +\\\n", + " guides(color=guide_legend(title='Workload'), fill=guide_legend(title='Workload')) +\\\n", + " scale_color_discrete(labels=['Instagram trace', 'Constant']) +\\\n", + " xlab('Number of retries')+\\\n", + " ylab('Fraction of requests')\n", + "\n", + "plt.save(f'{experiment} comparison.png', dpi=300)\n", + "plt.save(f'{experiment} comparison.pdf')\n", + "plt" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "# experiment = 'monolith'\n", + "# specific_min_max = min_max_per_exp[(min_max_per_exp['experiment'] == experiment)]\n", + "# plt = ggplot(specific_min_max) +\\\n", + "# theme_light(base_size=12, base_family='sans-serif') +\\\n", + "# theme(text=element_text(size=12)) +\\\n", + "# geom_line(aes(x='cat_retries', y='mean', color='vendor', group='vendor')) +\\\n", + "# scale_y_log10(breaks = [0.01, 0.0001, 0.000001, 1e-8], labels=['1%', '0.01%', '$10^{-4}$%', '$10^{-6}$%']) +\\\n", + "# guides(color=guide_legend(title='Workload'), fill=guide_legend(title='Workload')) +\\\n", + "# scale_color_discrete(labels=['Instagram trace', 'Constant']) +\\\n", + "# scale_fill_discrete(labels=['Instagram trace', 'Constant']) +\\\n", + "# xlab('Number of retries')+\\\n", + "# ylab('Fraction of requests')\n", + "\n", + "# plt.save(f'{experiment} comparison.png', dpi=300)\n", + "# plt" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "# experiment = 'fanout'\n", + "# specific_min_max = min_max_per_exp[(min_max_per_exp['experiment'] == experiment)]\n", + "# plt = ggplot(specific_min_max) +\\\n", + "# theme_light(base_size=12, base_family='sans-serif') +\\\n", + "# theme(text=element_text(size=12)) +\\\n", + "# geom_line(aes(x='cat_retries', y='mean', color='vendor', group='vendor')) +\\\n", + "# geom_ribbon(aes(x='cat_retries', ymin='min', ymax='max', fill='vendor', group='vendor'), alpha=0.5) +\\\n", + "# scale_y_log10(breaks = [0.01, 0.0001, 0.000001], labels=['1%', '0.01%', '0.0001%']) +\\\n", + "# guides(color=guide_legend(title='Workload'), fill=guide_legend(title='Workload')) +\\\n", + "# scale_color_discrete(labels=['Instagram trace', 'Constant']) +\\\n", + "# scale_fill_discrete(labels=['Instagram trace', 'Constant']) +\\\n", + "# xlab('Number of retries')+\\\n", + "# ylab('Fraction of requests')\n", + "\n", + "# plt.save(f'{experiment} comparison.png', dpi=300)\n", + "# plt" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "# const_results_df = pd.read_csv('const_experiment_results_1.csv')\n", + "# const_results_df['cat_retries'] = pd.Categorical(const_results_df['retries']).rename_categories({100: 'Fail'})\n", + "# const_results_df['cat_prob'] = pd.Categorical(const_results_df['prob']).rename_categories({100: 'Fail'})\n", + "# const_results_df['fraction'] = const_results_df['reqs'] / (365*24*60*60)\n", + "# const_results_df.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "# experiment = 'deep chain'\n", + "# specific_const_results = const_results_df[(const_results_df['experiment'] == experiment)]\n", + "# plt = ggplot(specific_const_results) +\\\n", + "# theme_light(base_size=12, base_family='sans-serif') +\\\n", + "# theme(text=element_text(size=12)) +\\\n", + "# geom_line(aes(x='cat_retries', y='fraction', color='cat_prob', group='cat_prob')) +\\\n", + "# scale_y_log10(limits=[1, 1e-6], breaks = [0.01, 0.0001, 0.000001, 1e-8], labels=['1%', '0.01%', '$10^{-4}$%', '$10^{-6}$%']) +\\\n", + "# guides(color=guide_legend(title='Workload'), fill=guide_legend(title='Workload')) +\\\n", + "# xlab('Number of retries')+\\\n", + "# ylab('Fraction of requests')\n", + "\n", + "# plt.save(f'const comparison.png', dpi=300)\n", + "# plt" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "# experiment = 'deep chain'\n", + "# specific_const_results = const_results_df[(const_results_df['experiment'] == experiment) & (const_results_df['cat_prob'] == 0.01)]\n", + "# plt = ggplot(specific_const_results) +\\\n", + "# theme_light(base_size=12, base_family='sans-serif') +\\\n", + "# theme(text=element_text(size=12), axis_text_y=element_text(size=35)) +\\\n", + "# geom_point(aes(x='cat_retries', y='fraction', group='cat_prob'), size=3, shape='s') +\\\n", + "# scale_y_log10(limits=[1, 1e-6], breaks = [0.1, 0.01, 0.001, 0.0001, 0.00001, 0.000001],\n", + "# labels=['10%', '', '0.1%', '', '$10^{-3}$%', '']) +\\\n", + "# xlab('')+\\\n", + "# ylab('')\n", + "\n", + "# plt.save(f'low const.png', dpi=300)\n", + "# plt.save(f'low const.pdf')\n", + "# plt" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "# experiment = 'deep chain'\n", + "# specific_const_results = const_results_df[(const_results_df['experiment'] == experiment) & (const_results_df['cat_prob'] == 0.25)]\n", + "# plt = ggplot(specific_const_results) +\\\n", + "# theme_light(base_size=12, base_family='sans-serif') +\\\n", + "# theme(text=element_text(size=12)) +\\\n", + "# geom_point(aes(x='cat_retries', y='fraction', group='cat_prob'), size=3, shape='s') +\\\n", + "# scale_y_log10(limits=[1, 1e-6], breaks = [0.1, 0.01, 0.001, 0.0001, 0.00001, 0.000001],\n", + "# labels=['', '', '', '', '', '']) +\\\n", + "# xlab('')+\\\n", + "# ylab('')\n", + "\n", + "# plt.save(f'25 const.png', dpi=300)\n", + "# plt.save(f'25 const.pdf')\n", + "# plt" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "# experiment = 'deep chain'\n", + "# specific_const_results = const_results_df[(const_results_df['experiment'] == experiment) & (const_results_df['cat_prob'] == 0.5)]\n", + "# plt = ggplot(specific_const_results) +\\\n", + "# theme_light(base_size=12, base_family='sans-serif') +\\\n", + "# theme(text=element_text(size=12)) +\\\n", + "# geom_point(aes(x='cat_retries', y='fraction', group='cat_prob'), size=3, shape='s') +\\\n", + "# scale_y_log10(limits=[1, 1e-6], breaks = [0.1, 0.01, 0.001, 0.0001, 0.00001, 0.000001],\n", + "# labels=['', '', '', '', '', '']) +\\\n", + "# xlab('')+\\\n", + "# ylab('')\n", + "\n", + "# plt.save(f'50 const.png', dpi=300)\n", + "# plt.save(f'50 const.pdf')\n", + "# plt" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "# experiment = 'deep chain'\n", + "# specific_const_results = const_results_df[(const_results_df['experiment'] == experiment) & (const_results_df['cat_prob'] == 0.75)]\n", + "# plt = ggplot(specific_const_results) +\\\n", + "# theme_light(base_size=12, base_family='sans-serif') +\\\n", + "# theme(text=element_text(size=12)) +\\\n", + "# geom_point(aes(x='cat_retries', y='fraction', group='cat_prob'), size=3, shape='s') +\\\n", + "# scale_y_log10(limits=[1, 1e-6], breaks = [0.1, 0.01, 0.001, 0.0001, 0.00001, 0.000001],\n", + "# labels=['', '', '', '', '', '']) +\\\n", + "# xlab('')+\\\n", + "# ylab('')\n", + "\n", + "# plt.save(f'75 const.png', dpi=300)\n", + "# plt" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "# print(pd.pivot_table(min_max_per_exp[['vendor', 'experiment', 'cat_retries', 'mean']], values='mean', index=['vendor', 'experiment'], columns=['cat_retries']).to_latex(float_format=\"{:0.2e}\".format))" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.1" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/datasets/Talluri2021/outage_report_2019-20/_common_metadata 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d="M39.35294117647058,111.5 L0,111.5 A111.5,111.5 0 0 1 223,111.5 L183.64705882352942,111.5 A72.14705882352942,72.14705882352942 0 0 0 39.35294117647058,111.5 Z " filter="url(#g3-inner-shadow)"></path><path fill="#59922b" stroke="none" d="M39.35294117647058,111.5 L0,111.5 A111.5,111.5 0 0 1 0.00045669881451715355,111.18087051677378 L39.35323668746821,111.29350445203009 A72.14705882352942,72.14705882352942 0 0 0 39.35294117647058,111.5 Z " filter="url(#g3-inner-shadow)"></path><text x="111.5" y="83.625" text-anchor="middle" font-size="41.29629629629629" class="Gauge__Count-s1qahqgd-5 gzhUJh">0</text></svg><div class="Gauge__OuterMessageWrapper-s1qahqgd-4 cCVyAJ"><div class="Gauge__MessageWrapper-s1qahqgd-3 ebnLEW"><span class="Gauge__Message-s1qahqgd-2 cdAMOw">Reports in last 20 minutes</span></div></div></div></div><section class="Box-s12snkgl-0 kdKsXx"><section><section class="report-btn-container"><div style="z-index:3" class="dropdown btn-group btn-group-lg"><button id="dropdown-custom-1" role="button" aria-haspopup="true" aria-expanded="false" type="button" class="dropdown-toggle btn btn-danger"><span class="ReportButton__FingerIcon-s1m3f4hm-1 icon-one-finger-tap kraBGI"></span><span class="ReportButton__BtnMsgWrap-s1m3f4hm-0 jdEbkR">Not Working For Me!</span> <span class="caret"></span></button><ul role="menu" class="dropdown-menu" aria-labelledby="dropdown-custom-1"><li role="heading" class="dropdown-header">What isn't working?</li><li role="presentation" class=""><a role="menuitem" tabindex="-1" href="#">Website down</a></li><li role="presentation" class=""><a role="menuitem" tabindex="-1" href="#">Mobile app not working</a></li><li role="presentation" class=""><a role="menuitem" tabindex="-1" href="#">Mobile app crashes</a></li><li role="presentation" class=""><a role="menuitem" tabindex="-1" href="#">Message read problems</a></li><li role="presentation" class=""><a role="menuitem" tabindex="-1" href="#">Message send problems</a></li><li role="presentation" class=""><a role="menuitem" tabindex="-1" href="#">Can't login</a></li><li role="presentation" class=""><a role="menuitem" tabindex="-1" href="#">Everything is down</a></li><li role="presentation" class=""><a role="menuitem" tabindex="-1" href="#">Can't upload pics</a></li><li role="presentation" class=""><a role="menuitem" tabindex="-1" href="#">Hashtags not working</a></li><li role="presentation" class=""><a role="menuitem" tabindex="-1" href="#">Newsfeed</a></li><li role="separator" class="divider"></li><li role="presentation" class=""><a role="menuitem" tabindex="-1" href="#">Other<!-- -->...</a></li></ul></div></section></section></section><section class="Box-s12snkgl-0 kdKsXx"><ul class="OutageSubjectsList__Ul-s10w08k0-0 jfDAxG"><li>Mobile app not working<!-- --> - <!-- -->18<!-- -->%</li><li>Can't upload pics<!-- --> - <!-- -->18<!-- -->%</li><li>Mobile app crashes<!-- --> - <!-- -->18<!-- -->%</li><li>Can't login<!-- --> - <!-- -->18<!-- -->%</li><li>Hashtags not working<!-- --> - <!-- -->12<!-- -->%</li><li>Website down<!-- --> - <!-- -->12<!-- -->%</li><li>Newsfeed<!-- --> - <!-- -->6<!-- -->%</li></ul></section><section class="Box-s12snkgl-0 eaawzP"><h3 style="margin-bottom:0">Outage History</h3><svg class="react-calendar-heatmap" viewBox="0 0 166 96"><g transform="translate(0, 0)" class="react-calendar-heatmap-month-labels"><text x="0" y="10" class="react-calendar-heatmap-month-label">Sep</text><text x="48" y="10" class="react-calendar-heatmap-month-label">Oct</text><text x="96" y="10" class="react-calendar-heatmap-month-label">Nov</text></g><g transform="translate(0, 14)" class="react-calendar-heatmap-all-weeks"><g transform="translate(0, 0)" class="react-calendar-heatmap-week"><rect width="10" height="10" x="0" y="24" class="ylorrd-scale-2" data-tip="Tue, Sep 1 - 35 reports"><title></title></rect><rect width="10" height="10" x="0" y="36" class="ylorrd-scale-3" data-tip="Wed, Sep 2 - 45 reports"><title></title></rect><rect width="10" height="10" x="0" y="48" class="ylorrd-scale-2" data-tip="Thu, Sep 3 - 35 reports"><title></title></rect><rect width="10" height="10" x="0" y="60" class="ylorrd-scale-1" data-tip="Fri, Sep 4 - 32 reports"><title></title></rect><rect width="10" height="10" x="0" y="72" class="ylorrd-scale-1" data-tip="Sat, Sep 5 - 25 reports"><title></title></rect></g><g transform="translate(12, 0)" class="react-calendar-heatmap-week"><rect width="10" height="10" x="0" y="0" class="ylorrd-scale-1" data-tip="Sun, Sep 6 - 27 reports"><title></title></rect><rect width="10" height="10" x="0" y="12" class="ylorrd-scale-5 with-outage" data-tip="Mon, Sep 7 - 105 reports"><title></title></rect><rect width="10" height="10" x="0" y="24" class="ylorrd-scale-3" data-tip="Tue, Sep 8 - 44 reports"><title></title></rect><rect width="10" height="10" x="0" y="36" class="ylorrd-scale-1" data-tip="Wed, Sep 9 - 23 reports"><title></title></rect><rect width="10" height="10" x="0" y="48" class="ylorrd-scale-2" data-tip="Thu, Sep 10 - 36 reports"><title></title></rect><rect width="10" height="10" x="0" y="60" class="ylorrd-scale-2" data-tip="Fri, Sep 11 - 39 reports"><title></title></rect><rect width="10" height="10" x="0" y="72" class="ylorrd-scale-2" data-tip="Sat, Sep 12 - 36 reports"><title></title></rect></g><g transform="translate(24, 0)" class="react-calendar-heatmap-week"><rect width="10" height="10" x="0" y="0" class="ylorrd-scale-4" data-tip="Sun, Sep 13 - 58 reports"><title></title></rect><rect width="10" height="10" x="0" y="12" class="ylorrd-scale-5" data-tip="Mon, Sep 14 - 86 reports"><title></title></rect><rect width="10" height="10" x="0" y="24" class="ylorrd-scale-3" data-tip="Tue, Sep 15 - 44 reports"><title></title></rect><rect width="10" height="10" x="0" y="36" class="ylorrd-scale-7 with-outage" data-tip="Wed, Sep 16 - 1548 reports"><title></title></rect><rect width="10" height="10" x="0" y="48" class="ylorrd-scale-3" data-tip="Thu, Sep 17 - 47 reports"><title></title></rect><rect width="10" height="10" x="0" y="60" class="ylorrd-scale-1" data-tip="Fri, Sep 18 - 30 reports"><title></title></rect><rect width="10" height="10" x="0" y="72" class="ylorrd-scale-1" data-tip="Sat, Sep 19 - 31 reports"><title></title></rect></g><g transform="translate(36, 0)" class="react-calendar-heatmap-week"><rect width="10" height="10" x="0" y="0" class="ylorrd-scale-2" data-tip="Sun, Sep 20 - 36 reports"><title></title></rect><rect width="10" height="10" x="0" y="12" class="ylorrd-scale-2" data-tip="Mon, Sep 21 - 34 reports"><title></title></rect><rect width="10" height="10" x="0" y="24" class="ylorrd-scale-4 with-outage" data-tip="Tue, Sep 22 - 61 reports"><title></title></rect><rect width="10" height="10" x="0" y="36" class="ylorrd-scale-5" data-tip="Wed, Sep 23 - 85 reports"><title></title></rect><rect width="10" height="10" x="0" y="48" class="ylorrd-scale-3" data-tip="Thu, Sep 24 - 47 reports"><title></title></rect><rect width="10" height="10" x="0" y="60" class="ylorrd-scale-2" data-tip="Fri, Sep 25 - 35 reports"><title></title></rect><rect width="10" height="10" x="0" y="72" class="ylorrd-scale-1" data-tip="Sat, Sep 26 - 27 reports"><title></title></rect></g><g transform="translate(48, 0)" class="react-calendar-heatmap-week"><rect width="10" height="10" x="0" y="0" class="ylorrd-scale-1" data-tip="Sun, Sep 27 - 27 reports"><title></title></rect><rect width="10" height="10" x="0" y="12" class="ylorrd-scale-5 with-outage" data-tip="Mon, Sep 28 - 105 reports"><title></title></rect><rect width="10" height="10" x="0" y="24" class="ylorrd-scale-5" data-tip="Tue, Sep 29 - 77 reports"><title></title></rect><rect width="10" height="10" x="0" y="36" class="ylorrd-scale-1" data-tip="Wed, Sep 30 - 27 reports"><title></title></rect><rect width="10" height="10" x="0" y="48" class="ylorrd-scale-1" data-tip="Thu, Oct 1 - 23 reports"><title></title></rect><rect width="10" height="10" x="0" y="60" class="ylorrd-scale-2" data-tip="Fri, Oct 2 - 33 reports"><title></title></rect><rect width="10" height="10" x="0" y="72" class="ylorrd-scale-1" data-tip="Sat, Oct 3 - 32 reports"><title></title></rect></g><g transform="translate(60, 0)" class="react-calendar-heatmap-week"><rect width="10" height="10" x="0" y="0" class="ylorrd-scale-1" data-tip="Sun, Oct 4 - 31 reports"><title></title></rect><rect width="10" height="10" x="0" y="12" class="ylorrd-scale-1" data-tip="Mon, Oct 5 - 17 reports"><title></title></rect><rect width="10" height="10" x="0" y="24" class="ylorrd-scale-1" data-tip="Tue, Oct 6 - 27 reports"><title></title></rect><rect width="10" height="10" x="0" y="36" class="ylorrd-scale-5 with-outage" data-tip="Wed, Oct 7 - 99 reports"><title></title></rect><rect width="10" height="10" x="0" y="48" class="ylorrd-scale-1" data-tip="Thu, Oct 8 - 32 reports"><title></title></rect><rect width="10" height="10" x="0" y="60" class="ylorrd-scale-1" data-tip="Fri, Oct 9 - 27 reports"><title></title></rect><rect width="10" height="10" x="0" y="72" class="ylorrd-scale-1" data-tip="Sat, Oct 10 - 28 reports"><title></title></rect></g><g transform="translate(72, 0)" class="react-calendar-heatmap-week"><rect width="10" height="10" x="0" y="0" class="ylorrd-scale-6 with-outage" data-tip="Sun, Oct 11 - 119 reports"><title></title></rect><rect width="10" height="10" x="0" y="12" class="ylorrd-scale-7" data-tip="Mon, Oct 12 - 207 reports"><title></title></rect><rect width="10" height="10" x="0" y="24" class="ylorrd-scale-7 with-outage" data-tip="Tue, Oct 13 - 257 reports"><title></title></rect><rect width="10" height="10" x="0" y="36" class="ylorrd-scale-7" data-tip="Wed, Oct 14 - 160 reports"><title></title></rect><rect width="10" height="10" x="0" y="48" class="ylorrd-scale-5" data-tip="Thu, Oct 15 - 102 reports"><title></title></rect><rect width="10" height="10" x="0" y="60" class="ylorrd-scale-5" data-tip="Fri, Oct 16 - 96 reports"><title></title></rect><rect width="10" height="10" x="0" y="72" class="ylorrd-scale-5" data-tip="Sat, Oct 17 - 75 reports"><title></title></rect></g><g transform="translate(84, 0)" class="react-calendar-heatmap-week"><rect width="10" height="10" x="0" y="0" class="ylorrd-scale-7 with-outage" data-tip="Sun, Oct 18 - 170 reports"><title></title></rect><rect width="10" height="10" x="0" y="12" class="ylorrd-scale-4" data-tip="Mon, Oct 19 - 63 reports"><title></title></rect><rect width="10" height="10" x="0" y="24" class="ylorrd-scale-7 with-outage" data-tip="Tue, Oct 20 - 426 reports"><title></title></rect><rect width="10" height="10" x="0" y="36" class="ylorrd-scale-5" data-tip="Wed, Oct 21 - 106 reports"><title></title></rect><rect width="10" height="10" x="0" y="48" class="ylorrd-scale-2" data-tip="Thu, Oct 22 - 38 reports"><title></title></rect><rect width="10" height="10" x="0" y="60" class="ylorrd-scale-1" data-tip="Fri, Oct 23 - 23 reports"><title></title></rect><rect width="10" height="10" x="0" y="72" class="ylorrd-scale-1" data-tip="Sat, Oct 24 - 29 reports"><title></title></rect></g><g transform="translate(96, 0)" class="react-calendar-heatmap-week"><rect width="10" height="10" x="0" y="0" class="ylorrd-scale-2" data-tip="Sun, Oct 25 - 38 reports"><title></title></rect><rect width="10" height="10" x="0" y="12" class="ylorrd-scale-3" data-tip="Mon, Oct 26 - 48 reports"><title></title></rect><rect width="10" height="10" x="0" y="24" class="ylorrd-scale-1" data-tip="Tue, Oct 27 - 31 reports"><title></title></rect><rect width="10" height="10" x="0" y="36" class="ylorrd-scale-1" data-tip="Wed, Oct 28 - 29 reports"><title></title></rect><rect width="10" height="10" x="0" y="48" class="ylorrd-scale-1" data-tip="Thu, Oct 29 - 22 reports"><title></title></rect><rect width="10" height="10" x="0" y="60" class="ylorrd-scale-1" data-tip="Fri, Oct 30 - 23 reports"><title></title></rect><rect width="10" height="10" x="0" y="72" class="ylorrd-scale-1" data-tip="Sat, Oct 31 - 28 reports"><title></title></rect></g><g transform="translate(108, 0)" class="react-calendar-heatmap-week"><rect width="10" height="10" x="0" y="0" class="ylorrd-scale-1" data-tip="Invalid date - null reports"><title></title></rect><rect width="10" height="10" x="0" y="12" class="ylorrd-scale-2" data-tip="Mon, Nov 2 - 36 reports"><title></title></rect><rect width="10" height="10" x="0" y="24" class="ylorrd-scale-1" data-tip="Tue, Nov 3 - 22 reports"><title></title></rect><rect width="10" height="10" x="0" y="36" class="ylorrd-scale-1" data-tip="Wed, Nov 4 - 25 reports"><title></title></rect><rect width="10" height="10" x="0" y="48" class="ylorrd-scale-1" data-tip="Thu, Nov 5 - 18 reports"><title></title></rect><rect width="10" height="10" x="0" y="60" class="ylorrd-scale-1" data-tip="Fri, Nov 6 - 19 reports"><title></title></rect><rect width="10" height="10" x="0" y="72" class="ylorrd-scale-1" data-tip="Sat, Nov 7 - 24 reports"><title></title></rect></g><g transform="translate(120, 0)" class="react-calendar-heatmap-week"><rect width="10" height="10" x="0" y="0" class="ylorrd-scale-1" data-tip="Sun, Nov 8 - 19 reports"><title></title></rect><rect width="10" height="10" x="0" y="12" class="ylorrd-scale-4" data-tip="Mon, Nov 9 - 60 reports"><title></title></rect><rect width="10" height="10" x="0" y="24" class="ylorrd-scale-7 with-outage" data-tip="Tue, Nov 10 - 2685 reports"><title></title></rect><rect width="10" height="10" x="0" y="36" class="ylorrd-scale-7 with-outage" data-tip="Wed, Nov 11 - 1240 reports"><title></title></rect><rect width="10" height="10" x="0" y="48" class="ylorrd-scale-7" data-tip="Thu, Nov 12 - 173 reports"><title></title></rect><rect width="10" height="10" x="0" y="60" class="ylorrd-scale-5" data-tip="Fri, Nov 13 - 92 reports"><title></title></rect><rect width="10" height="10" x="0" y="72" class="ylorrd-scale-4" data-tip="Sat, Nov 14 - 72 reports"><title></title></rect></g><g transform="translate(132, 0)" class="react-calendar-heatmap-week"><rect width="10" height="10" x="0" y="0" class="ylorrd-scale-1" data-tip="Sun, Nov 15 - 27 reports"><title></title></rect><rect width="10" height="10" x="0" y="12" class="ylorrd-scale-1" data-tip="Mon, Nov 16 - 27 reports"><title></title></rect><rect width="10" height="10" x="0" y="24" class="ylorrd-scale-1" data-tip="Tue, Nov 17 - 25 reports"><title></title></rect><rect width="10" height="10" x="0" y="36" class="ylorrd-scale-2" data-tip="Wed, Nov 18 - 35 reports"><title></title></rect><rect width="10" height="10" x="0" y="48" class="ylorrd-scale-4" data-tip="Thu, Nov 19 - 59 reports"><title></title></rect><rect width="10" height="10" x="0" y="60" class="ylorrd-scale-4" data-tip="Fri, Nov 20 - 59 reports"><title></title></rect><rect width="10" height="10" x="0" y="72" class="ylorrd-scale-2" data-tip="Sat, Nov 21 - 35 reports"><title></title></rect></g><g transform="translate(144, 0)" class="react-calendar-heatmap-week"><rect width="10" height="10" x="0" y="0" class="ylorrd-scale-1" data-tip="Sun, Nov 22 - 25 reports"><title></title></rect><rect width="10" height="10" x="0" y="12" class="ylorrd-scale-1" data-tip="Mon, Nov 23 - 23 reports"><title></title></rect><rect width="10" height="10" x="0" y="24" class="ylorrd-scale-1" data-tip="Tue, Nov 24 - 25 reports"><title></title></rect><rect width="10" height="10" x="0" y="36" class="ylorrd-scale-2" data-tip="Wed, Nov 25 - 34 reports"><title></title></rect><rect width="10" height="10" x="0" y="48" class="ylorrd-scale-2" data-tip="Thu, Nov 26 - 36 reports"><title></title></rect><rect width="10" height="10" x="0" y="60" class="ylorrd-scale-1" data-tip="Fri, Nov 27 - 25 reports"><title></title></rect><rect width="10" height="10" x="0" y="72" class="ylorrd-scale-1" data-tip="Sat, Nov 28 - 20 reports"><title></title></rect></g><g transform="translate(156, 0)" class="react-calendar-heatmap-week"><rect width="10" height="10" x="0" y="0" class="ylorrd-scale-1" data-tip="Sun, Nov 29 - 16 reports"><title></title></rect></g></g><g transform="translate(10, 14)" class="react-calendar-heatmap-weekday-labels"></g></svg><div class="__react_component_tooltip place-top type-dark " data-id="tooltip"></div></section><div class="sticky-outer-wrapper"><div class="sticky-inner-wrapper" style="position:relative;top:0px"><section class="Box-s12snkgl-0 eaawzP"><div><ins class="adsbygoogle" style="display:block" data-ad-client="ca-pub-3420388759586523" data-ad-slot="9249234402" data-ad-format="auto"></ins> + </div></section></div></div></div><div class="sc-ifAKCX jwBavN"><div></div><section class="OverlayLoader__Wrap-yneds0-0 hEfbHu"><section class="OverlayLoader__Overlay-yneds0-1 igYRzZ"></section><section class="Box-s12snkgl-0 eaawzP"><div class="BoxHeader-pyfdzt-0 wBQlt">Reports Dynamics<!-- --> <span class="ServicePage__TimeZoneWrap-l00bv6-0 dPxUZH">EST (GMT -05:00)</span></div><section class="D3Chart__Section-s1rg5m6n-2 kpsnLz"><div class="D3Chart__LogoDiv-s1rg5m6n-1 jJVKUf"><img 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class="D3Chart__LinePath-s1rg5m6n-0 fbwPSO"></path></g></svg></section></section><div class="sc-bdVaJa frYeKI"><span data-message="CNS">Received <!-- -->28<!-- --> reports, originating from <ul class="DominantMessage2__CommaList-s109d9sz-0 harauJ"><li><span>Ukraine</span></li><li><span>Russia</span></li><li><span>United States of America</span></li><li><span>Canada</span></li><li><span>Kingdom of Belgium</span></li></ul> <!-- -->and 7 more countries</span></div><div class="sc-bdVaJa frYeKI"><div><ins class="adsbygoogle" style="display:block" data-ad-client="ca-pub-3420388759586523" data-ad-slot="7818110659" data-ad-format="auto"></ins> + </div></div><section class="Box-s12snkgl-0 eaawzP"><div class="BoxHeader-pyfdzt-0 wBQlt">Instagram Outage Map<div class="Label-s858wg0-0 jSuHnk">Live</div></div><section class="map-box"><section style="background-color:#f8f4f0"><div class="OrepMap__Wrap-s1smgq9f-0 gTresv"><img src="outage_report_instagram_files/5458ac234488de92aa9cda3a-470x290-20200826-010136.jpg" class="OrepMap__Img-s1smgq9f-1 gLdFWy" height="290"><div class="sk-fading-circle"><div class="sk-circle1 sk-circle"></div><div class="sk-circle2 sk-circle"></div><div class="sk-circle3 sk-circle"></div><div class="sk-circle4 sk-circle"></div><div class="sk-circle5 sk-circle"></div><div class="sk-circle6 sk-circle"></div><div class="sk-circle7 sk-circle"></div><div class="sk-circle8 sk-circle"></div><div class="sk-circle9 sk-circle"></div><div class="sk-circle10 sk-circle"></div><div class="sk-circle11 sk-circle"></div><div class="sk-circle12 sk-circle"></div></div></div><div id="mapbox" style="height:290px"></div></section></section><section style="font-size:100%"> <ul class="RecentReports__Row-q9gvkj-1 gjMiDF"><li class="RecentReports__Col-q9gvkj-2 gvPnOa"><ul class="RecentReports__InnerGroup-q9gvkj-3 bhSvxn"><li class="RecentReports__InnerCol-q9gvkj-4 kdZniq"><span title="Russian Federation" class="RecentReports__StyledFlagIcon-q9gvkj-5 jTSYEi FlagIcon__Span-s1h5yp3u-0 eAxEIb"></span>Murmansk</li><li class="RecentReports__InnerCol-q9gvkj-4 kdZniq"><span class="RecentReports__Label-q9gvkj-0 ovZit">Can't login</span></li></ul></li><li class="RecentReports__Col-q9gvkj-2 gvPnOa">28m</li></ul><ul class="RecentReports__Row-q9gvkj-1 gjMiDF"><li class="RecentReports__Col-q9gvkj-2 gvPnOa"><ul class="RecentReports__InnerGroup-q9gvkj-3 bhSvxn"><li class="RecentReports__InnerCol-q9gvkj-4 kdZniq"><span title="Republic of Turkey" class="RecentReports__StyledFlagIcon-q9gvkj-5 jTSYEi FlagIcon__Span-s1h5yp3u-0 gpCTmv"></span>Istanbul</li><li class="RecentReports__InnerCol-q9gvkj-4 kdZniq"><span class="RecentReports__Label-q9gvkj-0 ovZit">Newsfeed</span></li></ul></li><li class="RecentReports__Col-q9gvkj-2 gvPnOa">33m</li></ul><ul class="RecentReports__Row-q9gvkj-1 gjMiDF"><li class="RecentReports__Col-q9gvkj-2 gvPnOa"><ul class="RecentReports__InnerGroup-q9gvkj-3 bhSvxn"><li class="RecentReports__InnerCol-q9gvkj-4 kdZniq"><span title="Republic of Kazakhstan" class="RecentReports__StyledFlagIcon-q9gvkj-5 jTSYEi FlagIcon__Span-s1h5yp3u-0 iIyWia"></span>Astana</li><li class="RecentReports__InnerCol-q9gvkj-4 kdZniq"><span class="RecentReports__Label-q9gvkj-0 ovZit">Mobile app crashes</span></li></ul></li><li class="RecentReports__Col-q9gvkj-2 gvPnOa">42m</li></ul><ul class="RecentReports__Row-q9gvkj-1 gjMiDF"><li class="RecentReports__Col-q9gvkj-2 gvPnOa"><ul class="RecentReports__InnerGroup-q9gvkj-3 bhSvxn"><li class="RecentReports__InnerCol-q9gvkj-4 kdZniq"><span title="United States" class="RecentReports__StyledFlagIcon-q9gvkj-5 jTSYEi FlagIcon__Span-s1h5yp3u-0 FnvAx"></span>Lebanon</li><li class="RecentReports__InnerCol-q9gvkj-4 kdZniq"><span class="RecentReports__Label-q9gvkj-0 ovZit">Can't upload pics</span></li></ul></li><li class="RecentReports__Col-q9gvkj-2 gvPnOa">59m</li></ul><ul class="RecentReports__Row-q9gvkj-1 gjMiDF"><li class="RecentReports__Col-q9gvkj-2 gvPnOa"><ul class="RecentReports__InnerGroup-q9gvkj-3 bhSvxn"><li class="RecentReports__InnerCol-q9gvkj-4 kdZniq"><span title="Hellenic Republic" class="RecentReports__StyledFlagIcon-q9gvkj-5 jTSYEi FlagIcon__Span-s1h5yp3u-0 lfHtck"></span></li><li class="RecentReports__InnerCol-q9gvkj-4 kdZniq"><span class="RecentReports__Label-q9gvkj-0 ovZit">Website down</span></li></ul></li><li class="RecentReports__Col-q9gvkj-2 gvPnOa">1h</li></ul><ul class="RecentReports__Row-q9gvkj-1 gjMiDF"><li class="RecentReports__Col-q9gvkj-2 gvPnOa"><ul class="RecentReports__InnerGroup-q9gvkj-3 bhSvxn"><li class="RecentReports__InnerCol-q9gvkj-4 kdZniq"><span title="Russian Federation" class="RecentReports__StyledFlagIcon-q9gvkj-5 jTSYEi FlagIcon__Span-s1h5yp3u-0 eAxEIb"></span>Severomorsk</li><li class="RecentReports__InnerCol-q9gvkj-4 kdZniq"><span class="RecentReports__Label-q9gvkj-0 ovZit">Mobile app not working</span></li></ul></li><li class="RecentReports__Col-q9gvkj-2 gvPnOa">1h</li></ul></section></section></section><div class="sc-bdVaJa frYeKI"><div><ins class="adsbygoogle" style="display:block" data-ad-client="ca-pub-3420388759586523" data-ad-slot="3799736330" data-ad-format="auto"></ins> + </div></div><section class="Box-s12snkgl-0 eaawzP"><section><section><div class="BoxHeader-pyfdzt-0 wBQlt">Discussion</div><p>Please <b>don't call "support numbers"</b> + posted below — most probably it's a scam. Make sure to report and +"downvote" such posts. Also don't post any of your personal information.</p></section><section><div id="disqus_thread"></div></section></section></section></div></div></div><div class="col-lg-4 sidebar"><div><ins class="adsbygoogle" style="display:block" data-ad-client="ca-pub-3420388759586523" data-ad-slot="9363837056" data-ad-format="auto"></ins> + </div><section class="SbBox__SbBoxWrap-s13wx3g3-0 izqjHG"><header class="SbBoxHeader-s1wr1o9x-0 ZVmIm">Having problems? Complain here:</header><section class="SbBoxBody-s1qqdvy0-0 kKdHN"><ul><li class="SupportTargets__Li-qi7gj1-1 jHiDkn"><span class="fa fa-twitter SupportTargets__Span-qi7gj1-0 iXLAql"></span><a href="https://twitter.com/@instagram" target="_blank">https://twitter.com/@instagram</a></li><li class="SupportTargets__Li-qi7gj1-1 jHiDkn"><span class="fa fa-facebook SupportTargets__Span-qi7gj1-0 iXLAql"></span><a href="https://www.facebook.com/instagram/" target="_blank">https://www.facebook.com/instagram/</a></li><li class="SupportTargets__Li-qi7gj1-1 jHiDkn"><span class="fa fa-globe SupportTargets__Span-qi7gj1-0 iXLAql"></span><a href="https://help.instagram.com/" target="_blank">https://help.instagram.com/</a></li></ul></section></section><section class="SbBox__SbBoxWrap-s13wx3g3-0 izqjHG"><section class="TweetsBox__GreyWrap-s12mungy-0 bupUUO"><header class="SbBoxHeader-s1wr1o9x-0 ZVmIm">Twitter Reaction</header><section class="SbBoxBody-s1qqdvy0-0 kKdHN"><section class="Tweets__Wrap-s1ipv0r6-0 eADBGy"><div class="notif-bar"><a>View 0 new Tweets</a></div><section class="Tweets__TweetsListWrap-s1ipv0r6-1 ghHYBw"><ul class="Tweets__TweetsList-s1ipv0r6-2 QQVy"><li data-tweet-id="5eb892187288017b0ac3d4eb"><div class="Tweet__ContainerDiv-eb2fy2-2 iQrcxI"><img class="StyledAvatar-s1akxuvw-0 bPjzgV" src="outage_report_instagram_files/f-iDCSBT_normal.jpg"><div class="tweet-body clearfix Tweet__Div-eb2fy2-0 gHrPMq"><div class="tweet-header"><small><div class="TweetHeader__StyledTweetTime-s1k65s8h-0 jpTejw" id="tweet-time">May 11, 2020 12:45 AM</div></small><a href="https://twitter.com/Tori_LocS" target="_blank" rel="nofollow" id="username" class="TweetUser__A-s11xu2yv-1 igCoAH"><strong class="TweetUser__Strong-s11xu2yv-2 hayQqm">Tori Harvey</strong><span class="TweetUser__Span-s11xu2yv-0 kQndua">@Tori_LocS</span></a></div><p class="Tweet__StyledTweetBody-eb2fy2-1 fnSmlJ TweetBody__P-rrblip-1 ihxmPN">We tryin support black business .. drop IG names please</p></div></div></li><li data-tweet-id="5eb891577288017b0ac3d27d"><div class="Tweet__ContainerDiv-eb2fy2-2 iQrcxI"><img class="StyledAvatar-s1akxuvw-0 bPjzgV" src="outage_report_instagram_files/kobZxKoL_normal.jpg"><div class="tweet-body clearfix Tweet__Div-eb2fy2-0 gHrPMq"><div class="tweet-header"><small><div class="TweetHeader__StyledTweetTime-s1k65s8h-0 jpTejw" id="tweet-time">May 11, 2020 12:42 AM</div></small><a href="https://twitter.com/nopeaceofmind" target="_blank" rel="nofollow" id="username" class="TweetUser__A-s11xu2yv-1 igCoAH"><strong class="TweetUser__Strong-s11xu2yv-2 hayQqm">rosario <img alt="🦋" draggable="false" src="outage_report_instagram_files/1f98b.png" style="height:1em;width:1em;margin:0 .05em 0 .1em;vertical-align:-0.1em"></strong><span class="TweetUser__Span-s11xu2yv-0 kQndua">@nopeaceofmind</span></a></div><p class="Tweet__StyledTweetBody-eb2fy2-1 fnSmlJ TweetBody__P-rrblip-1 ihxmPN">I CANT FUCKING ACCESS MY INSTAGRAM. FIX IT NOW <span class="utils__Span-nq5gy5-0 dHBNZw"><a href="https://twitter.com/INSTAGRAM" target="_blank">@INSTAGRAM</a></span></p></div></div></li><li data-tweet-id="5eb890f37288017b0ac3d140"><div class="Tweet__ContainerDiv-eb2fy2-2 iQrcxI"><img class="StyledAvatar-s1akxuvw-0 bPjzgV" src="outage_report_instagram_files/MYIFvwJK_normal.jpg"><div class="tweet-body clearfix Tweet__Div-eb2fy2-0 gHrPMq"><div class="tweet-header"><small><div class="TweetHeader__StyledTweetTime-s1k65s8h-0 jpTejw" id="tweet-time">May 11, 2020 12:40 AM</div></small><a href="https://twitter.com/hautalaulu" target="_blank" rel="nofollow" id="username" class="TweetUser__A-s11xu2yv-1 igCoAH"><strong class="TweetUser__Strong-s11xu2yv-2 hayQqm">lina</strong><span class="TweetUser__Span-s11xu2yv-0 kQndua">@hautalaulu</span></a></div><p class="Tweet__StyledTweetBody-eb2fy2-1 fnSmlJ TweetBody__P-rrblip-1 ihxmPN">guys my instagram dms aint working so dont try to talk to me there :(</p></div></div></li><li data-tweet-id="5eb890bd7288017b0ac3d082"><div class="Tweet__ContainerDiv-eb2fy2-2 iQrcxI"><img class="StyledAvatar-s1akxuvw-0 bPjzgV" src="outage_report_instagram_files/sUqlZoxo_normal.jpg"><div class="tweet-body clearfix Tweet__Div-eb2fy2-0 gHrPMq"><div class="tweet-header"><small><div class="TweetHeader__StyledTweetTime-s1k65s8h-0 jpTejw" id="tweet-time">May 11, 2020 12:39 AM</div></small><a href="https://twitter.com/KaiEhsan" target="_blank" rel="nofollow" id="username" class="TweetUser__A-s11xu2yv-1 igCoAH"><strong class="TweetUser__Strong-s11xu2yv-2 hayQqm"><img alt="🌚" draggable="false" src="outage_report_instagram_files/1f31a.png" style="height:1em;width:1em;margin:0 .05em 0 .1em;vertical-align:-0.1em"></strong><span class="TweetUser__Span-s11xu2yv-0 kQndua">@KaiEhsan</span></a></div><p class="Tweet__StyledTweetBody-eb2fy2-1 fnSmlJ TweetBody__P-rrblip-1 ihxmPN">Is Instagram trippen ? <img alt="🤨" draggable="false" src="outage_report_instagram_files/1f928.png" style="height:1em;width:1em;margin:0 .05em 0 .1em;vertical-align:-0.1em"> + +Or maybe Some wrong with my account</p></div></div></li><li data-tweet-id="5eb88f967288017b0ac3ccab"><div class="Tweet__ContainerDiv-eb2fy2-2 iQrcxI"><img class="StyledAvatar-s1akxuvw-0 bPjzgV" src="outage_report_instagram_files/v-k0YHFl_normal.jpg"><div class="tweet-body clearfix Tweet__Div-eb2fy2-0 gHrPMq"><div class="tweet-header"><small><div class="TweetHeader__StyledTweetTime-s1k65s8h-0 jpTejw" id="tweet-time">May 11, 2020 12:33 AM</div></small><a href="https://twitter.com/dancergirl403" target="_blank" rel="nofollow" id="username" class="TweetUser__A-s11xu2yv-1 igCoAH"><strong class="TweetUser__Strong-s11xu2yv-2 hayQqm">Elizabeth Underwood</strong><span class="TweetUser__Span-s11xu2yv-0 kQndua">@dancergirl403</span></a></div><p class="Tweet__StyledTweetBody-eb2fy2-1 fnSmlJ TweetBody__P-rrblip-1 ihxmPN">Anyone else’s Instagram tweakin? Mine hasn’t worked in 3 days 🥴 driving me crazy</p></div></div></li><li data-tweet-id="5eb88f197288017b0ac3cb29"><div class="Tweet__ContainerDiv-eb2fy2-2 iQrcxI"><img class="StyledAvatar-s1akxuvw-0 bPjzgV" src="outage_report_instagram_files/ijJfaNbC_normal.jpg"><div class="tweet-body clearfix Tweet__Div-eb2fy2-0 gHrPMq"><div class="tweet-header"><small><div class="TweetHeader__StyledTweetTime-s1k65s8h-0 jpTejw" id="tweet-time">May 11, 2020 12:32 AM</div></small><a href="https://twitter.com/MeganAshleyFit" target="_blank" rel="nofollow" id="username" class="TweetUser__A-s11xu2yv-1 igCoAH"><strong class="TweetUser__Strong-s11xu2yv-2 hayQqm">Megan Ashley</strong><span class="TweetUser__Span-s11xu2yv-0 kQndua">@MeganAshleyFit</span></a></div><p class="Tweet__StyledTweetBody-eb2fy2-1 fnSmlJ TweetBody__P-rrblip-1 ihxmPN">IG is not Tinder, stop confusing the two.</p></div></div></li><li data-tweet-id="5eb88e897288017b0ac3c977"><div class="Tweet__ContainerDiv-eb2fy2-2 iQrcxI"><img class="StyledAvatar-s1akxuvw-0 bPjzgV" src="outage_report_instagram_files/9fqTf-5h_normal.jpg"><div class="tweet-body clearfix Tweet__Div-eb2fy2-0 gHrPMq"><div class="tweet-header"><small><div class="TweetHeader__StyledTweetTime-s1k65s8h-0 jpTejw" id="tweet-time">May 11, 2020 12:30 AM</div></small><a href="https://twitter.com/LuhStalli" target="_blank" rel="nofollow" id="username" class="TweetUser__A-s11xu2yv-1 igCoAH"><strong class="TweetUser__Strong-s11xu2yv-2 hayQqm">TeeWhy <img alt="ðŸŽ" draggable="false" src="outage_report_instagram_files/1f40e.png" style="height:1em;width:1em;margin:0 .05em 0 .1em;vertical-align:-0.1em"></strong><span class="TweetUser__Span-s11xu2yv-0 kQndua">@LuhStalli</span></a></div><p class="Tweet__StyledTweetBody-eb2fy2-1 fnSmlJ TweetBody__P-rrblip-1 ihxmPN">Instagram acting stupid asf ...</p></div></div></li><li data-tweet-id="5eb88cbb7288017b0ac3c35e"><div class="Tweet__ContainerDiv-eb2fy2-2 iQrcxI"><img class="StyledAvatar-s1akxuvw-0 bPjzgV" src="outage_report_instagram_files/QohDHMEI_normal.jpg"><div class="tweet-body clearfix Tweet__Div-eb2fy2-0 gHrPMq"><div class="tweet-header"><small><div class="TweetHeader__StyledTweetTime-s1k65s8h-0 jpTejw" id="tweet-time">May 11, 2020 12:22 AM</div></small><a href="https://twitter.com/lyrrandreantes" target="_blank" rel="nofollow" id="username" class="TweetUser__A-s11xu2yv-1 igCoAH"><strong class="TweetUser__Strong-s11xu2yv-2 hayQqm">ðš–ðšŠðš¡ðš’ðš–ðšžðšœ</strong><span class="TweetUser__Span-s11xu2yv-0 kQndua">@lyrrandreantes</span></a></div><p class="Tweet__StyledTweetBody-eb2fy2-1 fnSmlJ TweetBody__P-rrblip-1 ihxmPN">can't even access my instagram <img alt="ðŸ˜" draggable="false" src="outage_report_instagram_files/1f62d.png" style="height:1em;width:1em;margin:0 .05em 0 .1em;vertical-align:-0.1em"></p></div></div></li><li data-tweet-id="5eb88bcf7288017b0ac3c021"><div class="Tweet__ContainerDiv-eb2fy2-2 iQrcxI"><img class="StyledAvatar-s1akxuvw-0 bPjzgV" src="outage_report_instagram_files/3cWSKcsk_normal.jpg"><div class="tweet-body clearfix Tweet__Div-eb2fy2-0 gHrPMq"><div class="tweet-header"><small><div class="TweetHeader__StyledTweetTime-s1k65s8h-0 jpTejw" id="tweet-time">May 11, 2020 12:18 AM</div></small><a href="https://twitter.com/YTExaktly" target="_blank" rel="nofollow" id="username" class="TweetUser__A-s11xu2yv-1 igCoAH"><strong class="TweetUser__Strong-s11xu2yv-2 hayQqm">ExaktÅ‚y</strong><span class="TweetUser__Span-s11xu2yv-0 kQndua">@YTExaktly</span></a></div><p class="Tweet__StyledTweetBody-eb2fy2-1 fnSmlJ TweetBody__P-rrblip-1 ihxmPN"><span class="utils__Span-nq5gy5-0 dHBNZw"><a href="https://twitter.com/instagram" target="_blank">@instagram</a></span> please fix your log-in system because it’s as bad as the coronavirus death toll</p></div></div></li><li data-tweet-id="5eb88b4d7288017b0ac3be39"><div class="Tweet__ContainerDiv-eb2fy2-2 iQrcxI"><img class="StyledAvatar-s1akxuvw-0 bPjzgV" src="outage_report_instagram_files/2FydZKFL_normal.jpg"><div class="tweet-body clearfix Tweet__Div-eb2fy2-0 gHrPMq"><div class="tweet-header"><small><div class="TweetHeader__StyledTweetTime-s1k65s8h-0 jpTejw" id="tweet-time">May 11, 2020 12:16 AM</div></small><a href="https://twitter.com/fleurvante" target="_blank" rel="nofollow" id="username" class="TweetUser__A-s11xu2yv-1 igCoAH"><strong class="TweetUser__Strong-s11xu2yv-2 hayQqm">ð™›ð™¡ð™¤â· semi ia</strong><span class="TweetUser__Span-s11xu2yv-0 kQndua">@fleurvante</span></a></div><p class="Tweet__StyledTweetBody-eb2fy2-1 fnSmlJ TweetBody__P-rrblip-1 ihxmPN">can bts pls do an in instagram live</p></div></div></li><li data-tweet-id="5eb88aef7288017b0ac3bd05"><div class="Tweet__ContainerDiv-eb2fy2-2 iQrcxI"><img class="StyledAvatar-s1akxuvw-0 bPjzgV" src="outage_report_instagram_files/13krsNSo_normal.jpg"><div class="tweet-body clearfix Tweet__Div-eb2fy2-0 gHrPMq"><div class="tweet-header"><small><div class="TweetHeader__StyledTweetTime-s1k65s8h-0 jpTejw" id="tweet-time">May 11, 2020 12:14 AM</div></small><a href="https://twitter.com/Sephiniixx" target="_blank" rel="nofollow" id="username" class="TweetUser__A-s11xu2yv-1 igCoAH"><strong class="TweetUser__Strong-s11xu2yv-2 hayQqm">$eph</strong><span class="TweetUser__Span-s11xu2yv-0 kQndua">@Sephiniixx</span></a></div><p class="Tweet__StyledTweetBody-eb2fy2-1 fnSmlJ TweetBody__P-rrblip-1 ihxmPN">Man my Instagram keep lagging</p></div></div></li><li data-tweet-id="5eb88a5e7288017b0ac3bb16"><div class="Tweet__ContainerDiv-eb2fy2-2 iQrcxI"><img class="StyledAvatar-s1akxuvw-0 bPjzgV" src="outage_report_instagram_files/Z4Hc2nrF_normal.jpg"><div class="tweet-body clearfix Tweet__Div-eb2fy2-0 gHrPMq"><div class="tweet-header"><small><div class="TweetHeader__StyledTweetTime-s1k65s8h-0 jpTejw" id="tweet-time">May 11, 2020 12:12 AM</div></small><a href="https://twitter.com/WildflowerHBR" target="_blank" rel="nofollow" id="username" class="TweetUser__A-s11xu2yv-1 igCoAH"><strong class="TweetUser__Strong-s11xu2yv-2 hayQqm">Mads <img alt="🔗" draggable="false" src="outage_report_instagram_files/1f517.png" style="height:1em;width:1em;margin:0 .05em 0 .1em;vertical-align:-0.1em"></strong><span class="TweetUser__Span-s11xu2yv-0 kQndua">@WildflowerHBR</span></a></div><p class="Tweet__StyledTweetBody-eb2fy2-1 fnSmlJ TweetBody__P-rrblip-1 ihxmPN">I really wanted for stay up for <span class="utils__Span-nq5gy5-0 dHBNZw"><a href="https://twitter.com/HunterRowland" target="_blank">@HunterRowland</a></span> Instagram live but I’m so fucking tired</p></div></div></li><li data-tweet-id="5eb88a017288017b0ac3b9d1"><div class="Tweet__ContainerDiv-eb2fy2-2 iQrcxI"><img class="StyledAvatar-s1akxuvw-0 bPjzgV" src="outage_report_instagram_files/Nm_SE2A-_normal.jpg"><div class="tweet-body clearfix Tweet__Div-eb2fy2-0 gHrPMq"><div class="tweet-header"><small><div class="TweetHeader__StyledTweetTime-s1k65s8h-0 jpTejw" id="tweet-time">May 11, 2020 12:10 AM</div></small><a href="https://twitter.com/_joyriding" target="_blank" rel="nofollow" id="username" class="TweetUser__A-s11xu2yv-1 igCoAH"><strong class="TweetUser__Strong-s11xu2yv-2 hayQqm">polnareff’s big bazongas(笑)</strong><span class="TweetUser__Span-s11xu2yv-0 kQndua">@_joyriding</span></a></div><p class="Tweet__StyledTweetBody-eb2fy2-1 fnSmlJ TweetBody__P-rrblip-1 ihxmPN">my ig isnt working damn<img alt="😔" draggable="false" src="outage_report_instagram_files/1f614.png" style="height:1em;width:1em;margin:0 .05em 0 .1em;vertical-align:-0.1em"></p></div></div></li><li data-tweet-id="5eb889557288017b0ac3b772"><div class="Tweet__ContainerDiv-eb2fy2-2 iQrcxI"><img class="StyledAvatar-s1akxuvw-0 bPjzgV" src="outage_report_instagram_files/4vdA-UhK_normal.jpg"><div class="tweet-body clearfix Tweet__Div-eb2fy2-0 gHrPMq"><div class="tweet-header"><small><div class="TweetHeader__StyledTweetTime-s1k65s8h-0 jpTejw" id="tweet-time">May 11, 2020 12:07 AM</div></small><a href="https://twitter.com/ChronisterLaken" target="_blank" rel="nofollow" id="username" class="TweetUser__A-s11xu2yv-1 igCoAH"><strong class="TweetUser__Strong-s11xu2yv-2 hayQqm">Laken Chronister</strong><span class="TweetUser__Span-s11xu2yv-0 kQndua">@ChronisterLaken</span></a></div><p class="Tweet__StyledTweetBody-eb2fy2-1 fnSmlJ TweetBody__P-rrblip-1 ihxmPN">if anyone knows how to fix an instagram hack pls lmk :(</p></div></div></li><li data-tweet-id="5eb887eb7288017b0ac3b2aa"><div class="Tweet__ContainerDiv-eb2fy2-2 iQrcxI"><img class="StyledAvatar-s1akxuvw-0 bPjzgV" src="outage_report_instagram_files/3SFysGgy_normal.jpg"><div class="tweet-body clearfix Tweet__Div-eb2fy2-0 gHrPMq"><div class="tweet-header"><small><div class="TweetHeader__StyledTweetTime-s1k65s8h-0 jpTejw" id="tweet-time">May 11, 2020 12:01 AM</div></small><a href="https://twitter.com/princessnxchole" target="_blank" rel="nofollow" id="username" class="TweetUser__A-s11xu2yv-1 igCoAH"><strong class="TweetUser__Strong-s11xu2yv-2 hayQqm">ÑŸĆØÅĘ<img alt="🌻" draggable="false" src="outage_report_instagram_files/1f33b.png" style="height:1em;width:1em;margin:0 .05em 0 .1em;vertical-align:-0.1em"></strong><span class="TweetUser__Span-s11xu2yv-0 kQndua">@princessnxchole</span></a></div><p class="Tweet__StyledTweetBody-eb2fy2-1 fnSmlJ TweetBody__P-rrblip-1 ihxmPN">Ig we going on a adventure</p></div></div></li><li data-tweet-id="5eb886f37288017b0ac3af5c"><div class="Tweet__ContainerDiv-eb2fy2-2 iQrcxI"><img class="StyledAvatar-s1akxuvw-0 bPjzgV" src="outage_report_instagram_files/0JiAf8J3_normal.png"><div class="tweet-body clearfix Tweet__Div-eb2fy2-0 gHrPMq"><div class="tweet-header"><small><div class="TweetHeader__StyledTweetTime-s1k65s8h-0 jpTejw" id="tweet-time">May 10, 2020 11:57 PM</div></small><a href="https://twitter.com/drackiepuff" target="_blank" rel="nofollow" id="username" class="TweetUser__A-s11xu2yv-1 igCoAH"><strong class="TweetUser__Strong-s11xu2yv-2 hayQqm">ð—±ð—¿ð—®ð—°ð—¼ ; semi-ia</strong><span class="TweetUser__Span-s11xu2yv-0 kQndua">@drackiepuff</span></a></div><p class="Tweet__StyledTweetBody-eb2fy2-1 fnSmlJ TweetBody__P-rrblip-1 ihxmPN">idk what i did but jack blocked me big rip ig</p></div></div></li><li data-tweet-id="5eb8844a7288017b0ac3a65d"><div class="Tweet__ContainerDiv-eb2fy2-2 iQrcxI"><img class="StyledAvatar-s1akxuvw-0 bPjzgV" src="outage_report_instagram_files/PwZV52MT_normal.jpg"><div class="tweet-body clearfix Tweet__Div-eb2fy2-0 gHrPMq"><div class="tweet-header"><small><div class="TweetHeader__StyledTweetTime-s1k65s8h-0 jpTejw" id="tweet-time">May 10, 2020 11:46 PM</div></small><a href="https://twitter.com/baysickboyel" target="_blank" rel="nofollow" id="username" class="TweetUser__A-s11xu2yv-1 igCoAH"><strong class="TweetUser__Strong-s11xu2yv-2 hayQqm">Eldrich<img alt="🤱ðŸ½" draggable="false" src="outage_report_instagram_files/1f931-1f3fd.png" style="height:1em;width:1em;margin:0 .05em 0 .1em;vertical-align:-0.1em"><img alt="🤱ðŸ½" draggable="false" src="outage_report_instagram_files/1f931-1f3fd.png" style="height:1em;width:1em;margin:0 .05em 0 .1em;vertical-align:-0.1em"><img alt="🤱ðŸ½" draggable="false" src="outage_report_instagram_files/1f931-1f3fd.png" style="height:1em;width:1em;margin:0 .05em 0 .1em;vertical-align:-0.1em"></strong><span class="TweetUser__Span-s11xu2yv-0 kQndua">@baysickboyel</span></a></div><p class="Tweet__StyledTweetBody-eb2fy2-1 fnSmlJ TweetBody__P-rrblip-1 ihxmPN">Had to stop cooking just to watch <span class="utils__Span-nq5gy5-0 dHBNZw"><a href="https://twitter.com/raveena_aurora" target="_blank">@raveena_aurora</a></span> IG live. Blessed</p></div></div></li><li data-tweet-id="5eb8835c7288017b0ac3a30a"><div class="Tweet__ContainerDiv-eb2fy2-2 iQrcxI"><img class="StyledAvatar-s1akxuvw-0 bPjzgV" src="outage_report_instagram_files/iXRIKwS5_normal.jpg"><div class="tweet-body clearfix Tweet__Div-eb2fy2-0 gHrPMq"><div class="tweet-header"><small><div class="TweetHeader__StyledTweetTime-s1k65s8h-0 jpTejw" id="tweet-time">May 10, 2020 11:42 PM</div></small><a href="https://twitter.com/hoodfavissac" target="_blank" rel="nofollow" id="username" class="TweetUser__A-s11xu2yv-1 igCoAH"><strong class="TweetUser__Strong-s11xu2yv-2 hayQqm"><img alt="👿" draggable="false" src="outage_report_instagram_files/1f47f.png" style="height:1em;width:1em;margin:0 .05em 0 .1em;vertical-align:-0.1em"></strong><span class="TweetUser__Span-s11xu2yv-0 kQndua">@hoodfavissac</span></a></div><p class="Tweet__StyledTweetBody-eb2fy2-1 fnSmlJ TweetBody__P-rrblip-1 ihxmPN">who else insta tweaking cause my shit all fucked up</p></div></div></li><li data-tweet-id="5eb883437288017b0ac3a28f"><div class="Tweet__ContainerDiv-eb2fy2-2 iQrcxI"><img class="StyledAvatar-s1akxuvw-0 bPjzgV" src="outage_report_instagram_files/WHOMMhc4_normal.jpg"><div class="tweet-body clearfix Tweet__Div-eb2fy2-0 gHrPMq"><div class="tweet-header"><small><div class="TweetHeader__StyledTweetTime-s1k65s8h-0 jpTejw" id="tweet-time">May 10, 2020 11:42 PM</div></small><a href="https://twitter.com/annaliselincol2" target="_blank" rel="nofollow" id="username" class="TweetUser__A-s11xu2yv-1 igCoAH"><strong class="TweetUser__Strong-s11xu2yv-2 hayQqm">annalise lincoln</strong><span class="TweetUser__Span-s11xu2yv-0 kQndua">@annaliselincol2</span></a></div><p class="Tweet__StyledTweetBody-eb2fy2-1 fnSmlJ TweetBody__P-rrblip-1 ihxmPN">well ig i was wrong like</p></div></div></li><li data-tweet-id="5eb883447288017b0ac3a293"><div class="Tweet__ContainerDiv-eb2fy2-2 iQrcxI"><img class="StyledAvatar-s1akxuvw-0 bPjzgV" src="outage_report_instagram_files/pF46Bhhz_normal.jpg"><div class="tweet-body clearfix Tweet__Div-eb2fy2-0 gHrPMq"><div class="tweet-header"><small><div class="TweetHeader__StyledTweetTime-s1k65s8h-0 jpTejw" id="tweet-time">May 10, 2020 11:42 PM</div></small><a href="https://twitter.com/spotofbp" target="_blank" rel="nofollow" id="username" class="TweetUser__A-s11xu2yv-1 igCoAH"><strong class="TweetUser__Strong-s11xu2yv-2 hayQqm">Senior Sources</strong><span class="TweetUser__Span-s11xu2yv-0 kQndua">@spotofbp</span></a></div><p class="Tweet__StyledTweetBody-eb2fy2-1 fnSmlJ TweetBody__P-rrblip-1 ihxmPN">Was Mother's Day really as perfect as it looked on Instagram? What am I doing wrong?</p></div></div></li></ul></section></section></section></section></section><section class="SbBox__SbBoxWrap-s13wx3g3-0 izqjHG"><div class="fb-page" data-href="https://www.facebook.com/pages/Outage-Report/954218841304891" data-adapt-container-width="true" data-show-facepile="true" data-show-posts="false"><div class="fb-xfbml-parse-ignore"></div></div></section><section class="SbBox__SbBoxWrap-s13wx3g3-0 izqjHG"><header class="SbBoxHeader-s1wr1o9x-0 ZVmIm">Most Common Report Sources</header><ul><li><span title="United States of America" class="MostCommonReportSources__StyledFlagIcon-j13ztj-0 euXkSR FlagIcon__Span-s1h5yp3u-0 FnvAx"></span>United States of America</li><li><span title="Ukraine" class="MostCommonReportSources__StyledFlagIcon-j13ztj-0 euXkSR FlagIcon__Span-s1h5yp3u-0 fKWNsy"></span>Ukraine</li><li><span title="Russia" class="MostCommonReportSources__StyledFlagIcon-j13ztj-0 euXkSR FlagIcon__Span-s1h5yp3u-0 eAxEIb"></span>Russia</li><li><span title="Republic of Uzbekistan" class="MostCommonReportSources__StyledFlagIcon-j13ztj-0 euXkSR FlagIcon__Span-s1h5yp3u-0 eyJmzF"></span>Republic of Uzbekistan</li><li><span title="Canada" class="MostCommonReportSources__StyledFlagIcon-j13ztj-0 euXkSR FlagIcon__Span-s1h5yp3u-0 eplLcC"></span>Canada</li><li><span title="Republic of Kazakhstan" class="MostCommonReportSources__StyledFlagIcon-j13ztj-0 euXkSR FlagIcon__Span-s1h5yp3u-0 iIyWia"></span>Republic of Kazakhstan</li><li><span title="Netherlands" class="MostCommonReportSources__StyledFlagIcon-j13ztj-0 euXkSR FlagIcon__Span-s1h5yp3u-0 ghYUuh"></span>Netherlands</li><li><span title="United Kingdom" class="MostCommonReportSources__StyledFlagIcon-j13ztj-0 euXkSR FlagIcon__Span-s1h5yp3u-0 hjrbFk"></span>United Kingdom</li><li><span title="Republic of India" class="MostCommonReportSources__StyledFlagIcon-j13ztj-0 euXkSR FlagIcon__Span-s1h5yp3u-0 fVKWPT"></span>Republic of India</li><li><span title="Spain" class="MostCommonReportSources__StyledFlagIcon-j13ztj-0 euXkSR FlagIcon__Span-s1h5yp3u-0 efhEnw"></span>Spain</li></ul></section><section class="SbBox__SbBoxWrap-s13wx3g3-0 izqjHG"><div><ins class="adsbygoogle" style="display:block" data-ad-client="ca-pub-3420388759586523" data-ad-slot="5585800490" data-ad-format="auto"></ins> + </div></section><section class="SbBox__SbBoxWrap-s13wx3g3-0 izqjHG"><a class="twitter-timeline" href="https://twitter.com/instagram" data-height="600" data-show-replies="true" data-chrome="nofooter"></a></section><section class="SbBox__SbBoxWrap-s13wx3g3-0 izqjHG"><div><ins class="adsbygoogle" style="display:block" data-ad-client="ca-pub-3420388759586523" data-ad-slot="2169299665" data-ad-format="auto"></ins> + </div></section></div></div></div><div class="footer"><div class="container" style="color:#9d9d9d"><div class="row"><div class="col-sm-2"><div style="display:block;text-align:center;margin-bottom:10px"><img src="outage_report_instagram_files/logo-small.png" alt="logo" style="display:block;height:70px;margin:auto"><span style="display:inline-block">©<!-- -->Outage.Report<!-- --> <!-- -->2020</span></div></div><div class="col-sm-6"><ul><li><a href="http://outagereport.ca/" target="_blank">Outage Report Canada</a></li><li><a href="http://outagereport.in/" target="_blank">Outage Report India</a></li><li><a href="http://outage.africa/" target="_blank">Outage Report Africa</a></li></ul></div></div></div></div></div></div><span id="lightbox_anchor" class="jslghtbx"></span><script>window.App={"context":{"dispatcher":{"stores":{"CommonStore":{"website":{"_id":"58976bceee5285714568b789","domain_name":"outage.report","title":"Outage.Report","lang":"en","locale_m":"en-us","ga_id":"UA-64830784-1","g_api_key":"AIzaSyAtfemrWHS4GAu3Ezo0UFUTMvoMDFo0ctM","tz":"America\u002FNew_York","fb_page_url":"https:\u002F\u002Fwww.facebook.com\u002Fpages\u002FOutage-Report\u002F954218841304891","fb_locale":"en_US","disqus_short_name":"outage-report","disqus_short_name_dev":"outage-report-dev","disqus_short_name_staging":"outage-report-staging","hostWithPort":"outage.report","https":true},"adsEnabled":1,"lang":{"code":"en","alpha3":"eng","momentLocale":"en","fbLocale":"en_US"},"currentPage":"SERVICE_PAGE","langCatalog":{"languageData":{"plurals":function plurals(n, ord) { + var s = String(n).split("."), + v0 = !s[1], + t0 = Number(s[0]) == n, + n10 = t0 && s[0].slice(-1), + n100 = t0 && s[0].slice(-2); + if (ord) return n10 == 1 && n100 != 11 ? 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+ },"Is {serviceName} down in {divisionName}?":function IsServiceNameDownInDivisionName(a) { + return ["Is ", a("serviceName"), " down in ", a("divisionName"), "?"]; + },"Last incident: {timeStr}":function LastIncidentTimeStr(a) { + return ["Last incident: ", a("timeStr")]; + },"MapPage.backToServicePage":function MapPageBackToServicePage(a) { + return ["Back to ", a("name"), " Outage Page"]; + },"MapPage.header":function MapPageHeader(a) { + return [a("name"), " Outage Map"]; + },"MapPage.subheader":function MapPageSubheader(a) { + return [a("0", "plural", { + one: ["Generated from Reports Received from Affected Users Within Last ", "#", " Hour"], + other: ["Generated from Reports Received from Affected Users Within Last ", "#", " Hours"] + })]; + },"Received {repCount} reports":function ReceivedRepCountReports(a) { + return ["Received ", a("repCount"), " reports"]; + },"Received {repCount} reports, mainly originating from {0}":function ReceivedRepCountReportsMainlyOriginatingFrom0(a) { + return ["Received ", a("repCount"), " reports, mainly originating from ", a("0")]; 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+ },"Received {usrRepCountTotal} reports, mainly originating from {0}":function ReceivedUsrRepCountTotalReportsMainlyOriginatingFrom0(a) { + return ["Received ", a("usrRepCountTotal"), " reports, mainly originating from ", a("0")]; + },"Received {usrRepCountTotal} reports, mainly originating from {0} ({1})":function ReceivedUsrRepCountTotalReportsMainlyOriginatingFrom01(a) { + return ["Received ", a("usrRepCountTotal"), " reports, mainly originating from ", a("0"), " (", a("1"), ")"]; + },"Received {usrRepCountTotal} reports, mainly originating from {0}, mainly {1}":function ReceivedUsrRepCountTotalReportsMainlyOriginatingFrom0Mainly1(a) { + return ["Received ", a("usrRepCountTotal"), " reports, mainly originating from ", a("0"), ", mainly ", a("1")]; + },"Received {usrRepCountTotal} reports, mainly originating from {0}, mainly {1}, mainly {2}":function ReceivedUsrRepCountTotalReportsMainlyOriginatingFrom0Mainly1Mainly2(a) { + return ["Received ", a("usrRepCountTotal"), " reports, mainly originating from ", a("0"), ", mainly ", a("1"), ", mainly ", a("2")]; + },"Received {usrRepCountTotal} reports, mainly originating from {0}, {1}":function ReceivedUsrRepCountTotalReportsMainlyOriginatingFrom01(a) { + return ["Received ", a("usrRepCountTotal"), " reports, mainly originating from ", a("0"), ", ", a("1")]; + },"Recent reports from {cityName} area":function RecentReportsFromCityNameArea(a) { + return ["Recent reports from ", a("cityName"), " area"]; + },"Recent reports from {geonameName}":function RecentReportsFromGeonameName(a) { + return ["Recent reports from ", a("geonameName")]; + },"SearchNotFound":"Nothing found for query","SearchNotFoundJs":"Nothing found for query","ServiceCityPage.RecentReportsHeading":function ServiceCityPageRecentReportsHeading(a) { + return ["Recent reports from ", a("cityName")]; + },"ServiceCityPage.desc.outage":function ServiceCityPageDescOutage(a) { + return ["See if ", a("serviceName"), " is having an outage in ", a("cityName"), " or it's just you. Check current status and outage map. Post yours and see other's reports and complaints."]; + },"ServiceCityPage.h1.default":function ServiceCityPageH1Default(a) { + return ["Is ", a("serviceName"), " down in ", a("cityName"), "?"]; + },"ServiceCityPage.h1.outage":function ServiceCityPageH1Outage(a) { + return ["Is ", a("serviceName"), " Having an Outage in ", a("cityName"), " Right Now?"]; + },"ServiceCityPage.h1.servers":function ServiceCityPageH1Servers(a) { + return ["Is ", a("serviceName"), " down in ", a("cityName"), "?"]; + },"ServiceCityPage.title.default":function ServiceCityPageTitleDefault(a) { + return [a("serviceName"), " Down in ", a("cityName")]; + },"ServiceCityPage.title.outage":function ServiceCityPageTitleOutage(a) { + return [a("serviceName"), " Outage in ", a("cityName")]; + },"ServiceCityPage.title.servers":function ServiceCityPageTitleServers(a) { + return [a("serviceName"), " Servers Down in ", a("cityName")]; + },"ServiceCountryPage.RecentReportsHeading":function ServiceCountryPageRecentReportsHeading(a) { + return ["Recent reports from ", a("countryName")]; + },"ServiceCountryPage.desc":function ServiceCountryPageDesc(a) { + return ["See if ", a("serviceName"), " is down in ", a("countryName"), " or it's just you. Check current status and outage map. Post yours and see other's reports and complaints."]; + },"ServiceCountryPage.h1.default":function ServiceCountryPageH1Default(a) { + return ["Is ", a("serviceName"), " down in ", a("countryName"), "?"]; + },"ServiceCountryPage.h1.outage":function ServiceCountryPageH1Outage(a) { + return ["Is ", a("serviceName"), " Having an Outage in ", a("countryName"), " Right Now?"]; + },"ServiceCountryPage.h1.servers":function ServiceCountryPageH1Servers(a) { + return ["Is ", a("serviceName"), " down in ", a("countryName"), "?"]; + },"ServiceCountryPage.title.default":function ServiceCountryPageTitleDefault(a) { + return [a("serviceName"), " Down in ", a("countryName")]; + },"ServiceCountryPage.title.outage":function ServiceCountryPageTitleOutage(a) { + return [a("serviceName"), " Outage in ", a("countryName")]; + },"ServiceCountryPage.title.servers":function ServiceCountryPageTitleServers(a) { + return [a("serviceName"), " Servers Down in ", a("countryName")]; + },"ServiceDivisionPage.RecentReportsHeading":function ServiceDivisionPageRecentReportsHeading(a) { + return ["Recent reports from ", a("divisionName")]; + },"ServiceDivisionPage.title.default":function ServiceDivisionPageTitleDefault(a) { + return [a("serviceName"), " Down in ", a("divisionName")]; + },"ServiceDivisionPage.title.outage":function ServiceDivisionPageTitleOutage(a) { + return [a("serviceName"), " Outage in ", a("divisionName")]; + },"ServiceDivisionPage.title.servers":function ServiceDivisionPageTitleServers(a) { + return [a("serviceName"), " Servers Down in ", a("divisionName")]; + },"ServiceGeonamePage.desc.default":function ServiceGeonamePageDescDefault(a) { + return ["See if ", a("serviceName"), " is down in ", a("geonameName"), " or it's just you. Check current status and outage map. Post yours and see other's reports and complaints."]; + },"ServiceGeonamePage.desc.outage":function ServiceGeonamePageDescOutage(a) { + return ["See if ", a("serviceName"), " is having an outage in ", a("geonameName"), " or it's just you. Check current status and outage map. Post yours and see other's reports and complaints."]; + },"ServiceGeonamePage.h1.default":function ServiceGeonamePageH1Default(a) { + return ["Is ", a("serviceName"), " down in ", a("geonameName"), "?"]; + },"ServiceGeonamePage.h1.outage":function ServiceGeonamePageH1Outage(a) { + return ["Is ", a("serviceName"), " Having an Outage in ", a("geonameName"), " Right Now?"]; + },"ServiceGeonamePage.h1.servers":function ServiceGeonamePageH1Servers(a) { + return ["Is ", a("serviceName"), " down in ", a("geonameName"), "?"]; + },"ServiceGeonamePage.title.default":function ServiceGeonamePageTitleDefault(a) { + return [a("serviceName"), " Down in ", a("geonameName")]; + },"ServiceGeonamePage.title.outage":function ServiceGeonamePageTitleOutage(a) { + return [a("serviceName"), " Outage in ", a("geonameName")]; + },"ServiceGeonamePage.title.servers":function ServiceGeonamePageTitleServers(a) { + return [a("serviceName"), " Servers Down in ", a("geonameName")]; + },"ServicePage.mapHeader":function ServicePageMapHeader(a) { + return [a("serviceName"), " Outage Map"]; + },"ServicePage.subheader":function ServicePageSubheader(a) { + return ["See if ", a("name"), " is down or having service issues today"]; + },"ServiceSubdivisionPage.RecentReportsHeading":function ServiceSubdivisionPageRecentReportsHeading(a) { + return ["Recent reports from ", a("subdivisionName")]; + },"ServiceSubdivisionPage.desc":function ServiceSubdivisionPageDesc(a) { + return ["See if ", a("serviceName"), " is down in ", a("subdivisionName"), " or it's just you. Check current status and outage map. 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Check current status and outage map. Post yours and see other's reports and complaints","meta.desc.index":"See if your provider or web service is having an outage or it's just you. Post yours and see other's reports and complaints","meta.desc.map":function metaDescMap(a) { + return ["Current outage map for ", a("titleName"), " - ", a("0")]; + },"meta.desc.service":function metaDescService(a) { + return [a("0", "select", { + providers: ["See if ", a("titleName"), " service is down or it's just you. Check current status and outage map. Post yours and see other's reports and complaints"], + games: ["See if ", a("titleName"), " is down or it's just you. Check current status and outage map. Post yours and see other's reports and complaints"], + power: ["See if ", a("titleName"), " is having an outage or it's just you. Check current status and outage map. Post yours and see other's reports and complaints"], + other: ["See if ", a("titleName"), " is down or it's just you. 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Complain here:","thanksForReport":"Thanks for Your Report","tweets.header":"Twitter Reaction","tweets.viewNewTweets":function tweetsViewNewTweets(a) { + return [a("count", "plural", { + one: ["View ", "#", " new Tweet"], + other: ["View ", "#", " new Tweets"] + })]; + },"{0, plural, one {Received {repCount} reports, originating from {cities} and # more cities} =0 {Received {repCount} reports, originating from {cities}} other {Received {repCount} reports, originating from {cities} and # more cities}}":function pluralOneReceivedRepCountReportsOriginatingFromCitiesAndMoreCities0ReceivedRepCountReportsOriginatingFromCitiesOtherReceivedRepCountReportsOriginatingFromCitiesAndMoreCities(a) { + return [a("0", "plural", { + one: ["Received ", a("repCount"), " reports, originating from ", a("cities"), " and ", "#", " more cities"], + 0: ["Received ", a("repCount"), " reports, originating from ", a("cities")], + other: ["Received ", a("repCount"), " reports, originating from ", a("cities"), " and 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Check current status and outage map. Post yours and see other's reports and complaints."]; + },"ServiceCityPage.h1.default":function ServiceCityPageH1Default(a) { + return ["Is ", a("serviceName"), " down in ", a("cityName"), "?"]; + },"ServiceCityPage.h1.outage":function ServiceCityPageH1Outage(a) { + return ["Is ", a("serviceName"), " Having an Outage in ", a("cityName"), " Right Now?"]; + },"ServiceCityPage.h1.servers":function ServiceCityPageH1Servers(a) { + return ["Is ", a("serviceName"), " down in ", a("cityName"), "?"]; + },"ServiceCityPage.title.default":function ServiceCityPageTitleDefault(a) { + return [a("serviceName"), " Down in ", a("cityName")]; + },"ServiceCityPage.title.outage":function ServiceCityPageTitleOutage(a) { + return [a("serviceName"), " Outage in ", a("cityName")]; + },"ServiceCityPage.title.servers":function ServiceCityPageTitleServers(a) { + return [a("serviceName"), " Servers Down in ", a("cityName")]; + },"ServiceCountryPage.RecentReportsHeading":function ServiceCountryPageRecentReportsHeading(a) { + return ["Recent reports from ", a("countryName")]; + },"ServiceCountryPage.desc":function ServiceCountryPageDesc(a) { + return ["See if ", a("serviceName"), " is down in ", a("countryName"), " or it's just you. Check current status and outage map. Post yours and see other's reports and complaints."]; + },"ServiceCountryPage.h1.default":function ServiceCountryPageH1Default(a) { + return ["Is ", a("serviceName"), " down in ", a("countryName"), "?"]; + },"ServiceCountryPage.h1.outage":function ServiceCountryPageH1Outage(a) { + return ["Is ", a("serviceName"), " Having an Outage in ", a("countryName"), " Right Now?"]; + },"ServiceCountryPage.h1.servers":function ServiceCountryPageH1Servers(a) { + return ["Is ", a("serviceName"), " down in ", a("countryName"), "?"]; + },"ServiceCountryPage.title.default":function ServiceCountryPageTitleDefault(a) { + return [a("serviceName"), " Down in ", a("countryName")]; + },"ServiceCountryPage.title.outage":function ServiceCountryPageTitleOutage(a) { + return [a("serviceName"), " Outage in ", a("countryName")]; + },"ServiceCountryPage.title.servers":function ServiceCountryPageTitleServers(a) { + return [a("serviceName"), " Servers Down in ", a("countryName")]; + },"ServiceDivisionPage.RecentReportsHeading":function ServiceDivisionPageRecentReportsHeading(a) { + return ["Recent reports from ", a("divisionName")]; + },"ServiceDivisionPage.title.default":function ServiceDivisionPageTitleDefault(a) { + return [a("serviceName"), " Down in ", a("divisionName")]; + },"ServiceDivisionPage.title.outage":function ServiceDivisionPageTitleOutage(a) { + return [a("serviceName"), " Outage in ", a("divisionName")]; + },"ServiceDivisionPage.title.servers":function ServiceDivisionPageTitleServers(a) { + return [a("serviceName"), " Servers Down in ", a("divisionName")]; + },"ServiceGeonamePage.desc.default":function ServiceGeonamePageDescDefault(a) { + return ["See if ", a("serviceName"), " is down in ", a("geonameName"), " or it's just you. Check current status and outage map. Post yours and see other's reports and complaints."]; + },"ServiceGeonamePage.desc.outage":function ServiceGeonamePageDescOutage(a) { + return ["See if ", a("serviceName"), " is having an outage in ", a("geonameName"), " or it's just you. Check current status and outage map. 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Also don't post any of your personal information.","companies.pageHeader":"Companies that we track","companies.pageSubheader":"Comprehensive list of companies and services that we track","company.outageMap":function companyOutageMap(a) { + return [a("mapName"), " Outage Map"]; + },"country.page.header":function countryPageHeader(a) { + return [a("countryName"), ", Recent Outages"]; + },"countryList.header":"Local Services Outages","gaugeText":function gaugeText(a) { + return [a("0", "plural", { + one: "Report in last 20 minutes", + other: "Reports in last 20 minutes" + })]; + },"historyAlert.buttonText":"Back","historyAlert.text":function historyAlertText(a) { + return ["Showing Details for ", a("0")]; + },"home":"Home","incidentAlert":function incidentAlert(a) { + return [a("context", "select", { + possible: ["Possible Issues at ", a("0")], + other: ["Issues at ", a("1")] + })]; + },"index.page.header":"Recent Outages","intensity":function intensity(a) { + return [a("value", "select", { + LOW: "Low", + MEDIUM: "Medium", + HIGH: "High", + EXTREME: "Extreme", + other: "-" + })]; + },"international.companies.PLURAL":"International","mainly originating from {0}":function mainlyOriginatingFrom0(a) { + return ["mainly originating from ", a("0")]; + },"mainly originating from {0} ({1})":function mainlyOriginatingFrom01(a) { + return ["mainly originating from ", a("0"), " (", a("1"), ")"]; + },"mainly originating from {0}, mainly {1}":function mainlyOriginatingFrom0Mainly1(a) { + return ["mainly originating from ", a("0"), ", mainly ", a("1")]; + },"mainly originating from {0}, mainly {1}, mainly {2}":function mainlyOriginatingFrom0Mainly1Mainly2(a) { + return ["mainly originating from ", a("0"), ", mainly ", a("1"), ", mainly ", a("2")]; + },"mainly originating from {0}, {1}":function mainlyOriginatingFrom01(a) { + return ["mainly originating from ", a("0"), ", ", a("1")]; + },"map.mapLinkText":"Detailed Map","mapLive":"Live","meta.desc.companies":function metaDescCompanies(a) { + return ["Comprehensive list of companies that ", a("wsTitle"), " tracks"]; + },"meta.desc.country.part1":function metaDescCountryPart1(a) { + return [a("countryName"), " - recent outages."]; + },"meta.desc.country.part2":"See if your provider or service is having an outage or it's just you. Check current status and outage map. Post yours and see other's reports and complaints","meta.desc.index":"See if your provider or web service is having an outage or it's just you. Post yours and see other's reports and complaints","meta.desc.map":function metaDescMap(a) { + return ["Current outage map for ", a("titleName"), " - ", a("0")]; + },"meta.desc.service":function metaDescService(a) { + return [a("0", "select", { + providers: ["See if ", a("titleName"), " service is down or it's just you. Check current status and outage map. Post yours and see other's reports and complaints"], + games: ["See if ", a("titleName"), " is down or it's just you. Check current status and outage map. Post yours and see other's reports and complaints"], + power: ["See if ", a("titleName"), " is having an outage or it's just you. Check current status and outage map. Post yours and see other's reports and complaints"], + other: ["See if ", a("titleName"), " is down or it's just you. 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Post yours and see other's reports and complaints"] + })]; + },"meta.desc.service_city":function metaDescService_city(a) { + return ["DESC ", a("serviceName"), " // ", a("cityName")]; + },"meta.desc.service_division":function metaDescService_division(a) { + return [a("serviceName"), ", ", a("divisionName"), " Description"]; + },"meta.h1.service.app":function metaH1ServiceApp(a) { + return ["Is ", a("serviceName"), " Not Working Right Now?"]; + },"meta.h1.service.default":function metaH1ServiceDefault(a) { + return ["Is ", a("serviceName"), " Down Right Now?"]; + },"meta.h1.service.provider":function metaH1ServiceProvider(a) { + return ["Is ", a("serviceName"), " Having an Outage Right Now?"]; + },"meta.title.companies":function metaTitleCompanies(a) { + return ["Companies - ", a("wsTitle")]; + },"meta.title.country":function metaTitleCountry(a) { + return [a("countryName"), " - Recent Outages - Outage.Report"]; + },"meta.title.map":function metaTitleMap(a) { + return [a("titleName"), " Outage Map - ", a("0")]; + },"meta.title.service.default":function metaTitleServiceDefault(a) { + return [a("titleName"), " not working. 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Complain here:","thanksForReport":"Thanks for Your Report","tweets.header":"Twitter Reaction","tweets.viewNewTweets":function tweetsViewNewTweets(a) { + return [a("count", "plural", { + one: ["View ", "#", " new Tweet"], + other: ["View ", "#", " new Tweets"] + })]; + },"{0, plural, one {Received {repCount} reports, originating from {cities} and # more cities} =0 {Received {repCount} reports, originating from {cities}} other {Received {repCount} reports, originating from {cities} and # more cities}}":function pluralOneReceivedRepCountReportsOriginatingFromCitiesAndMoreCities0ReceivedRepCountReportsOriginatingFromCitiesOtherReceivedRepCountReportsOriginatingFromCitiesAndMoreCities(a) { + return [a("0", "plural", { + one: ["Received ", a("repCount"), " reports, originating from ", a("cities"), " and ", "#", " more cities"], + 0: ["Received ", a("repCount"), " reports, originating from ", a("cities")], + other: ["Received ", a("repCount"), " reports, originating from ", a("cities"), " and ", "#", " more cities"] + })]; 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n?"dddd"===e?-1!==(p=Bt.call(this._weekdaysParse,b))?p:null:"ddd"===e?-1!==(p=Bt.call(this._shortWeekdaysParse,b))?p:null:-1!==(p=Bt.call(this._minWeekdaysParse,b))?p:null:"dddd"===e?-1!==(p=Bt.call(this._weekdaysParse,b))?p:-1!==(p=Bt.call(this._shortWeekdaysParse,b))?p:-1!==(p=Bt.call(this._minWeekdaysParse,b))?p:null:"ddd"===e?-1!==(p=Bt.call(this._shortWeekdaysParse,b))?p:-1!==(p=Bt.call(this._weekdaysParse,b))?p:-1!==(p=Bt.call(this._minWeekdaysParse,b))?p:null:-1!==(p=Bt.call(this._minWeekdaysParse,b))?p:-1!==(p=Bt.call(this._weekdaysParse,b))?p:-1!==(p=Bt.call(this._shortWeekdaysParse,b))?p:null}.call(this,t,e,n);for(this._weekdaysParse||(this._weekdaysParse=[],this._minWeekdaysParse=[],this._shortWeekdaysParse=[],this._fullWeekdaysParse=[]),o=0;o<7;o++){if(p=O([2e3,1]).day(o),n&&!this._fullWeekdaysParse[o]&&(this._fullWeekdaysParse[o]=new RegExp("^"+this.weekdays(p,"").replace(".",".?")+"$","i"),this._shortWeekdaysParse[o]=new 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o; +/*! + Copyright (c) 2016 Jed Watson. + Licensed under the MIT License (MIT), see + http://jedwatson.github.io/classnames +*/ +/*! + Copyright (c) 2016 Jed Watson. + Licensed under the MIT License (MIT), see + http://jedwatson.github.io/classnames +*/ +!function(){"use strict";var n={}.hasOwnProperty;function p(){for(var t=[],e=0;e<arguments.length;e++){var o=arguments[e];if(o){var r=typeof o;if("string"===r||"number"===r)t.push(o);else if(Array.isArray(o))t.push(p.apply(null,o));else if("object"===r)for(var b in o)n.call(o,b)&&o[b]&&t.push(b)}}return t.join(" ")}void 0!==t&&t.exports?t.exports=p:void 0===(o=function(){return p}.apply(e,[]))||(t.exports=o)}()},function(t,e,n){"use strict";n.r(e);var o=n(8),p=n.n(o),r=n(7),b=n.n(r),M=n(11),c=n.n(M),z=n(10),i=n.n(z),a=n(9),O=n.n(a),u=n(1),s=n.n(u),A=n(13),l=n.n(A),d=n(4),f=n(25),q=function(t){function e(t){var n;return p()(this,e),(n=c()(this,i()(e).call(this,t))).service=null,n.dominantData=null,n}return 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n=this;p.call(this),this.id=null,this.state=this.CLOSED,this.authState=this.UNAUTHENTICATED,this.signedAuthToken=null,this.authToken=null,this.pendingReconnect=!1,this.pendingReconnectTimeout=null,this.preparingPendingSubscriptions=!1,this.clientId=t.clientId,this.connectTimeout=t.connectTimeout,this.ackTimeout=t.ackTimeout,this.channelPrefix=t.channelPrefix||null,this.disconnectOnUnload=null==t.disconnectOnUnload||t.disconnectOnUnload,this.authTokenName=t.authTokenName,this.pingTimeout=this.ackTimeout,this.pingTimeoutDisabled=!!t.pingTimeoutDisabled,this.active=!0,this._clientMap=t.clientMap||{};var o=Math.pow(2,31)-1,r=function(t){if(n[t]>o)throw new s("The "+t+" value provided exceeded the maximum amount allowed")};if(r("connectTimeout"),r("ackTimeout"),this._localEvents={connect:1,connectAbort:1,close:1,disconnect:1,message:1,error:1,raw:1,kickOut:1,subscribe:1,unsubscribe:1,subscribeStateChange:1,authStateChange:1,authenticate:1,deauthenticate:1,removeAuthToken:1,subscribeRequest:1},this.connectAttempts=0,this._emitBuffer=new i,this.channels={},this.options=t,this._cid=1,this.options.callIdGenerator=function(){return n._cid++},this.options.autoReconnect){null==this.options.autoReconnectOptions&&(this.options.autoReconnectOptions={});var c=this.options.autoReconnectOptions;null==c.initialDelay&&(c.initialDelay=1e4),null==c.randomness&&(c.randomness=1e4),null==c.multiplier&&(c.multiplier=1.5),null==c.maxDelay&&(c.maxDelay=6e4)}null==this.options.subscriptionRetryOptions&&(this.options.subscriptionRetryOptions={}),this.options.authEngine?this.auth=this.options.authEngine:this.auth=new b,this.options.codecEngine?this.codec=this.options.codecEngine:this.codec=M,this.options.path=this.options.path.replace(/\/$/,"")+"/",this.options.query=t.query||{},"string"==typeof this.options.query&&(this.options.query=z.parse(this.options.query)),this._channelEmitter=new p,this._unloadHandler=function(){n.disconnect()},h&&this.disconnectOnUnload&&e.addEventListener&&e.addEventListener("beforeunload",this._unloadHandler,!1),this._clientMap[this.clientId]=this,this.options.autoConnect&&this.connect()};W.prototype=Object.create(p.prototype),W.CONNECTING=W.prototype.CONNECTING=c.prototype.CONNECTING,W.OPEN=W.prototype.OPEN=c.prototype.OPEN,W.CLOSED=W.prototype.CLOSED=c.prototype.CLOSED,W.AUTHENTICATED=W.prototype.AUTHENTICATED="authenticated",W.UNAUTHENTICATED=W.prototype.UNAUTHENTICATED="unauthenticated",W.PENDING=W.prototype.PENDING="pending",W.ignoreStatuses=u.socketProtocolIgnoreStatuses,W.errorStatuses=u.socketProtocolErrorStatuses,W.prototype._privateEventHandlerMap={"#publish":function(t){var e=this._undecorateChannelName(t.channel);this.isSubscribed(e,!0)&&this._channelEmitter.emit(e,t.data)},"#kickOut":function(t){var e=this._undecorateChannelName(t.channel),n=this.channels[e];n&&(p.prototype.emit.call(this,"kickOut",t.message,e),n.emit("kickOut",t.message,e),this._triggerChannelUnsubscribe(n))},"#setAuthToken":function(t,e){var n=this;if(t){this.auth.saveToken(this.authTokenName,t.token,{},function(o){o?(e.error(o),n._onSCError(o)):(n._changeToAuthenticatedState(t.token),e.end())})}else e.error(new A("No token data provided by #setAuthToken event"))},"#removeAuthToken":function(t,e){var n=this;this.auth.removeToken(this.authTokenName,function(t,o){t?(e.error(t),n._onSCError(t)):(p.prototype.emit.call(n,"removeAuthToken",o),n._changeToUnauthenticatedStateAndClearTokens(),e.end())})},"#disconnect":function(t){this.transport.close(t.code,t.data)}},W.prototype.getState=function(){return this.state},W.prototype.getBytesReceived=function(){return this.transport.getBytesReceived()},W.prototype.deauthenticate=function(t){var e=this;this.auth.removeToken(this.authTokenName,function(n,o){n?e._onSCError(n):(p.prototype.emit.call(e,"removeAuthToken",o),e.state!=e.CLOSED&&e.emit("#removeAuthToken"),e._changeToUnauthenticatedStateAndClearTokens()),t&&t(n)})},W.prototype.connect=W.prototype.open=function(){var t=this;if(this.active)this.state==this.CLOSED&&(this.pendingReconnect=!1,this.pendingReconnectTimeout=null,clearTimeout(this._reconnectTimeoutRef),this.state=this.CONNECTING,p.prototype.emit.call(this,"connecting"),this.transport&&this.transport.off(),this.transport=new c(this.auth,this.codec,this.options),this.transport.on("open",function(e){t.state=t.OPEN,t._onSCOpen(e)}),this.transport.on("error",function(e){t._onSCError(e)}),this.transport.on("close",function(e,n){t.state=t.CLOSED,t._onSCClose(e,n)}),this.transport.on("openAbort",function(e,n){t.state=t.CLOSED,t._onSCClose(e,n,!0)}),this.transport.on("event",function(e,n,o){t._onSCEvent(e,n,o)}));else{var e=new l("Cannot connect a destroyed client");this._onSCError(e)}},W.prototype.reconnect=function(t,e){this.disconnect(t,e),this.connect()},W.prototype.disconnect=function(t,e){if("number"!=typeof(t=t||1e3))throw new s("If specified, the code argument must be a number");this.state==this.OPEN||this.state==this.CONNECTING?this.transport.close(t,e):(this.pendingReconnect=!1,this.pendingReconnectTimeout=null,clearTimeout(this._reconnectTimeoutRef))},W.prototype.destroy=function(t,n){h&&e.removeEventListener&&e.removeEventListener("beforeunload",this._unloadHandler,!1),this.active=!1,this.disconnect(t,n),delete this._clientMap[this.clientId]},W.prototype._changeToUnauthenticatedStateAndClearTokens=function(){if(this.authState!=this.UNAUTHENTICATED){var t=this.authState,e=this.signedAuthToken;this.authState=this.UNAUTHENTICATED,this.signedAuthToken=null,this.authToken=null;var n={oldState:t,newState:this.authState};p.prototype.emit.call(this,"authStateChange",n),p.prototype.emit.call(this,"deauthenticate",e)}},W.prototype._changeToAuthenticatedState=function(t){if(this.signedAuthToken=t,this.authToken=this._extractAuthTokenData(t),this.authState!=this.AUTHENTICATED){var e=this.authState;this.authState=this.AUTHENTICATED;var n={oldState:e,newState:this.authState,signedAuthToken:t,authToken:this.authToken};this.preparingPendingSubscriptions||this.processPendingSubscriptions(),p.prototype.emit.call(this,"authStateChange",n)}p.prototype.emit.call(this,"authenticate",t)},W.prototype.decodeBase64=function(t){var n;void 0===o?n=e.atob?e.atob(t):a.decode(t):n=new o(t,"base64").toString("utf8");return n},W.prototype.encodeBase64=function(t){var n;void 0===o?n=e.btoa?e.btoa(t):a.encode(t):n=new o(t,"utf8").toString("base64");return n},W.prototype._extractAuthTokenData=function(t){var e=(t||"").split(".")[1];if(null!=e){var n=e;try{return n=this.decodeBase64(n),JSON.parse(n)}catch(t){return n}}return null},W.prototype.getAuthToken=function(){return this.authToken},W.prototype.getSignedAuthToken=function(){return this.signedAuthToken},W.prototype.authenticate=function(t,e){var n=this;this.emit("#authenticate",t,function(o,p){p&&null!=p.isAuthenticated?p.authError&&(p.authError=u.hydrateError(p.authError)):p={isAuthenticated:n.authState,authError:null},o?("BadConnectionError"!=o.name&&"TimeoutError"!=o.name&&n._changeToUnauthenticatedStateAndClearTokens(),e&&e(o,p)):n.auth.saveToken(n.authTokenName,t,{},function(o){o&&n._onSCError(o),p.isAuthenticated?n._changeToAuthenticatedState(t):n._changeToUnauthenticatedStateAndClearTokens(),e&&e(o,p)})})},W.prototype._tryReconnect=function(t){var e,n=this,o=this.connectAttempts++,p=this.options.autoReconnectOptions;if(null==t||o>0){var r=Math.round(p.initialDelay+(p.randomness||0)*Math.random());e=Math.round(r*Math.pow(p.multiplier,o))}else e=t;e>p.maxDelay&&(e=p.maxDelay),clearTimeout(this._reconnectTimeoutRef),this.pendingReconnect=!0,this.pendingReconnectTimeout=e,this._reconnectTimeoutRef=setTimeout(function(){n.connect()},e)},W.prototype._onSCOpen=function(t){var e=this;this.preparingPendingSubscriptions=!0,t?(this.id=t.id,this.pingTimeout=t.pingTimeout,this.transport.pingTimeout=this.pingTimeout,t.isAuthenticated?this._changeToAuthenticatedState(t.authToken):this._changeToUnauthenticatedStateAndClearTokens()):this._changeToUnauthenticatedStateAndClearTokens(),this.connectAttempts=0,this.options.autoSubscribeOnConnect&&this.processPendingSubscriptions(),p.prototype.emit.call(this,"connect",t,function(){e.processPendingSubscriptions()}),this.state==this.OPEN&&this._flushEmitBuffer()},W.prototype._onSCError=function(t){var e=this;setTimeout(function(){if(e.listeners("error").length<1)throw t;p.prototype.emit.call(e,"error",t)},0)},W.prototype._suspendSubscriptions=function(){var t,e;for(var n in this.channels)this.channels.hasOwnProperty(n)&&(e=(t=this.channels[n]).state==t.SUBSCRIBED||t.state==t.PENDING?t.PENDING:t.UNSUBSCRIBED,this._triggerChannelUnsubscribe(t,e))},W.prototype._abortAllPendingEventsDueToBadConnection=function(t){for(var e,n=this._emitBuffer.head;n;){e=n.next;var o=n.data;clearTimeout(o.timeout),delete o.timeout,n.detach(),n=e;var p=o.callback;if(p){delete o.callback;var r="Event '"+o.event+"' was aborted due to a bad connection",b=new q(r,t);p.call(o,b,o)}o.cid&&this.transport.cancelPendingResponse(o.cid)}},W.prototype._onSCClose=function(t,e,n){if(this.id=null,this.transport&&this.transport.off(),this.pendingReconnect=!1,this.pendingReconnectTimeout=null,clearTimeout(this._reconnectTimeoutRef),this._suspendSubscriptions(),this._abortAllPendingEventsDueToBadConnection(n?"connectAbort":"disconnect"),this.options.autoReconnect&&(4e3==t||4001==t||1005==t?this._tryReconnect(0):1e3!=t&&t<4500&&this._tryReconnect()),n?p.prototype.emit.call(this,"connectAbort",t,e):p.prototype.emit.call(this,"disconnect",t,e),p.prototype.emit.call(this,"close",t,e),!W.ignoreStatuses[t]){var o;o=e?"Socket connection closed with status code "+t+" and reason: "+e:"Socket connection closed with status code "+t;var r=new d(W.errorStatuses[t]||o,t);this._onSCError(r)}},W.prototype._onSCEvent=function(t,e,n){var o=this._privateEventHandlerMap[t];o?o.call(this,e,n):p.prototype.emit.call(this,t,e,function(){n&&n.callback.apply(n,arguments)})},W.prototype.decode=function(t){return this.transport.decode(t)},W.prototype.encode=function(t){return this.transport.encode(t)},W.prototype._flushEmitBuffer=function(){for(var t,e=this._emitBuffer.head;e;){t=e.next;var n=e.data;e.detach(),this.transport.emitObject(n),e=t}},W.prototype._handleEventAckTimeout=function(t,e){e&&e.detach(),delete t.timeout;var n=t.callback;if(n){delete t.callback;var o=new f("Event response for '"+t.event+"' timed out");n.call(t,o,t)}t.cid&&this.transport.cancelPendingResponse(t.cid)},W.prototype._emit=function(t,e,n){var o=this;this.state==this.CLOSED&&this.connect();var p={event:t,callback:n},r=new i.Item;this.options.cloneData?p.data=O(e):p.data=e,r.data=p,p.timeout=setTimeout(function(){o._handleEventAckTimeout(p,r)},this.ackTimeout),this._emitBuffer.append(r),this.state==this.OPEN&&this._flushEmitBuffer()},W.prototype.send=function(t){this.transport.send(t)},W.prototype.emit=function(t,e,n){if(null==this._localEvents[t])this._emit(t,e,n);else if("error"==t)p.prototype.emit.call(this,t,e);else{var o=new l('The "'+t+'" event is reserved and cannot be emitted on a client socket');this._onSCError(o)}},W.prototype.publish=function(t,e,n){var o={channel:this._decorateChannelName(t),data:e};this.emit("#publish",o,n)},W.prototype._triggerChannelSubscribe=function(t,e){var n=t.name;if(t.state!=t.SUBSCRIBED){var o=t.state;t.state=t.SUBSCRIBED;var r={channel:n,oldState:o,newState:t.state,subscriptionOptions:e};t.emit("subscribeStateChange",r),t.emit("subscribe",n,e),p.prototype.emit.call(this,"subscribeStateChange",r),p.prototype.emit.call(this,"subscribe",n,e)}},W.prototype._triggerChannelSubscribeFail=function(t,e,n){var o=e.name,r=!e.waitForAuth||this.authState==this.AUTHENTICATED;e.state!=e.UNSUBSCRIBED&&r&&(e.state=e.UNSUBSCRIBED,e.emit("subscribeFail",t,o,n),p.prototype.emit.call(this,"subscribeFail",t,o,n))},W.prototype._cancelPendingSubscribeCallback=function(t){null!=t._pendingSubscriptionCid&&(this.transport.cancelPendingResponse(t._pendingSubscriptionCid),delete t._pendingSubscriptionCid)},W.prototype._decorateChannelName=function(t){return this.channelPrefix&&(t=this.channelPrefix+t),t},W.prototype._undecorateChannelName=function(t){return this.channelPrefix&&0==t.indexOf(this.channelPrefix)?t.replace(this.channelPrefix,""):t},W.prototype._trySubscribe=function(t){var e=this,n=!t.waitForAuth||this.authState==this.AUTHENTICATED;if(this.state==this.OPEN&&!this.preparingPendingSubscriptions&&null==t._pendingSubscriptionCid&&n){var o={noTimeout:!0},r={channel:this._decorateChannelName(t.name)};t.waitForAuth&&(o.waitForAuth=!0,r.waitForAuth=o.waitForAuth),t.data&&(r.data=t.data),t.batch&&(o.batch=!0,r.batch=!0),t._pendingSubscriptionCid=this.transport.emit("#subscribe",r,o,function(n){delete t._pendingSubscriptionCid,n?e._triggerChannelSubscribeFail(n,t,r):e._triggerChannelSubscribe(t,r)}),p.prototype.emit.call(this,"subscribeRequest",t.name,r)}},W.prototype.subscribe=function(t,e){var n=this.channels[t];return n?e&&n.setOptions(e):(n=new r(t,this,e),this.channels[t]=n),n.state==n.UNSUBSCRIBED&&(n.state=n.PENDING,this._trySubscribe(n)),n},W.prototype._triggerChannelUnsubscribe=function(t,e){var n=t.name,o=t.state;if(t.state=e||t.UNSUBSCRIBED,this._cancelPendingSubscribeCallback(t),o==t.SUBSCRIBED){var 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3166-2:UA"],["AE","ARE","784","ISO 3166-2:AE"],["GB","GBR","826","ISO 3166-2:GB"],["US","USA","840","ISO 3166-2:US"],["UM","UMI","581","ISO 3166-2:UM"],["UY","URY","858","ISO 3166-2:UY"],["UZ","UZB","860","ISO 3166-2:UZ"],["VU","VUT","548","ISO 3166-2:VU"],["VE","VEN","862","ISO 3166-2:VE"],["VN","VNM","704","ISO 3166-2:VN"],["VG","VGB","092","ISO 3166-2:VG"],["VI","VIR","850","ISO 3166-2:VI"],["WF","WLF","876","ISO 3166-2:WF"],["EH","ESH","732","ISO 3166-2:EH"],["YE","YEM","887","ISO 3166-2:YE"],["ZM","ZMB","894","ISO 3166-2:ZM"],["ZW","ZWE","716","ISO 3166-2:ZW"],["XK","XKX","","ISO 3166-2:XK"]]},function(t){t.exports={version:"2018g",zones:["Africa/Abidjan|LMT GMT|g.8 0|01|-2ldXH.Q|48e5","Africa/Accra|LMT GMT +0020|.Q 0 -k|012121212121212121212121212121212121212121212121|-26BbX.8 6tzX.8 MnE 1BAk MnE 1BAk MnE 1BAk MnE 1C0k MnE 1BAk MnE 1BAk MnE 1BAk MnE 1C0k MnE 1BAk MnE 1BAk MnE 1BAk MnE 1C0k MnE 1BAk MnE 1BAk MnE 1BAk MnE 1C0k MnE 1BAk MnE 1BAk MnE 1BAk MnE 1C0k MnE 1BAk MnE 1BAk MnE|41e5","Africa/Nairobi|LMT EAT +0230 +0245|-2r.g -30 -2u -2J|01231|-1F3Cr.g 3Dzr.g okMu MFXJ|47e5","Africa/Algiers|LMT PMT WET WEST CET CEST|-c.c -9.l 0 -10 -10 -20|01232323232323232454542423234542324|-3bQob.c ME01.P cNb9.l HA0 19A0 1iM0 11c0 1oo0 Wo0 1rc0 QM0 1EM0 UM0 DA0 Imo0 rd0 De0 9Xz0 1fb0 1ap0 16K0 2yo0 mEp0 hwL0 jxA0 11A0 dDd0 17b0 11B0 1cN0 2Dy0 1cN0 1fB0 1cL0|26e5","Africa/Lagos|LMT WAT|-d.A -10|01|-22y0d.A|17e6","Africa/Bissau|LMT -01 GMT|12.k 10 0|012|-2ldX0 2xoo0|39e4","Africa/Maputo|LMT CAT|-2a.k -20|01|-2GJea.k|26e5","Africa/Cairo|LMT EET EEST|-25.9 -20 -30|01212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121|-2MBC5.9 1AQM5.9 vb0 1ip0 11z0 1iN0 1nz0 12p0 1pz0 10N0 1pz0 16p0 1jz0 s3d0 Vz0 1oN0 11b0 1oO0 10N0 1pz0 10N0 1pb0 10N0 1pb0 10N0 1pb0 10N0 1pz0 10N0 1pb0 10N0 1pb0 11d0 1oL0 11d0 1pb0 11d0 1oL0 11d0 1oL0 11d0 1oL0 11d0 1pb0 11d0 1oL0 11d0 1oL0 11d0 1oL0 11d0 1pb0 11d0 1oL0 11d0 1oL0 11d0 1oL0 11d0 1pb0 11d0 1oL0 11d0 1WL0 rd0 1Rz0 wp0 1pb0 11d0 1oL0 11d0 1oL0 11d0 1oL0 11d0 1pb0 11d0 1qL0 Xd0 1oL0 11d0 1oL0 11d0 1pb0 11d0 1oL0 11d0 1oL0 11d0 1ny0 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1qN0 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1qN0 11z0 1o10 11z0 1o10 WL0 1qN0 Rb0 1wp0 On0 1zd0 Lz0 1EN0 Fb0 c10 8n0 8Nd0 gL0 e10 mn0|15e6","Africa/Casablanca|LMT +00 +01|u.k 0 -10|0121212121212121212121212121212121212121212121212121212|-2gMnt.E 130Lt.E rb0 Dd0 dVb0 b6p0 TX0 EoB0 LL0 gnd0 rz0 43d0 AL0 1Nd0 XX0 1Cp0 pz0 dEp0 4mn0 SyN0 AL0 1Nd0 wn0 1FB0 Db0 1zd0 Lz0 1Nf0 wM0 co0 go0 1o00 s00 dA0 vc0 11A0 A00 e00 y00 11A0 uM0 e00 Dc0 11A0 s00 e00 IM0 WM0 mo0 gM0 LA0 WM0 jA0 e00|32e5","Africa/Ceuta|LMT WET WEST CET CEST|l.g 0 -10 -10 -20|0121212121212121212121343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343|-2M0M0 GdX0 11z0 drd0 18p0 3HX0 17d0 1fz0 1a10 1io0 1a00 1y7o0 LL0 gnd0 rz0 43d0 AL0 1Nd0 XX0 1Cp0 pz0 dEp0 4VB0 1cM0 1cM0 1cM0 1cM0 1cM0 1cM0 1cM0 1cM0 1fA0 1cM0 1cM0 1cM0 1cM0 1cM0 1cM0 1cM0 1cM0 1cM0 1cM0 1fA0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00|85e3","Africa/El_Aaiun|LMT -01 +00 +01|Q.M 10 0 -10|01232323232323232323232323232323232323232323|-1rDz7.c 1GVA7.c 6L0 AL0 1Nd0 XX0 1Cp0 pz0 1cBB0 AL0 1Nd0 wn0 1FB0 Db0 1zd0 Lz0 1Nf0 wM0 co0 go0 1o00 s00 dA0 vc0 11A0 A00 e00 y00 11A0 uM0 e00 Dc0 11A0 s00 e00 IM0 WM0 mo0 gM0 LA0 WM0 jA0 e00|20e4","Africa/Johannesburg|LMT SAST SAST SAST|-1Q -1u -20 -30|0123232|-39EpQ qTcm 1Ajdu 1cL0 1cN0 1cL0|84e5","Africa/Juba|LMT CAT CAST EAT|-26.s -20 -30 -30|01212121212121212121212121212121213|-1yW26.s 1zK06.s 16L0 1iN0 17b0 1jd0 17b0 1ip0 17z0 1i10 17X0 1hB0 18n0 1hd0 19b0 1gp0 19z0 1iN0 17b0 1ip0 17z0 1i10 18n0 1hd0 18L0 1gN0 19b0 1gp0 19z0 1iN0 17z0 1i10 17X0 yGd0","Africa/Khartoum|LMT CAT CAST EAT|-2a.8 -20 -30 -30|012121212121212121212121212121212131|-1yW2a.8 1zK0a.8 16L0 1iN0 17b0 1jd0 17b0 1ip0 17z0 1i10 17X0 1hB0 18n0 1hd0 19b0 1gp0 19z0 1iN0 17b0 1ip0 17z0 1i10 18n0 1hd0 18L0 1gN0 19b0 1gp0 19z0 1iN0 17z0 1i10 17X0 yGd0 HjL0|51e5","Africa/Monrovia|LMT MMT MMT GMT|H.8 H.8 I.u 0|0123|-3ygng.Q 1usM0 28G01.m|11e5","Africa/Ndjamena|LMT WAT WAST|-10.c -10 -20|0121|-2le10.c 2J3c0.c Wn0|13e5","Africa/Sao_Tome|LMT LMT GMT WAT|-q.U A.J 0 -10|0123|-3tooq.U 18aoq.U 4i6N0","Africa/Tripoli|LMT CET CEST EET|-Q.I -10 -20 -20|012121213121212121212121213123123|-21JcQ.I 1hnBQ.I vx0 4iP0 xx0 4eN0 Bb0 7ip0 U0n0 A10 1db0 1cN0 1db0 1dd0 1db0 1eN0 1bb0 1e10 1cL0 1c10 1db0 1dd0 1db0 1cN0 1db0 1q10 fAn0 1ep0 1db0 AKq0 TA0 1o00|11e5","Africa/Tunis|LMT PMT CET CEST|-E.I -9.l -10 -20|01232323232323232323232323232323232|-3zO0E.I 1cBAv.n 18pa9.l 1qM0 DA0 3Tc0 11B0 1ze0 WM0 7z0 3d0 14L0 1cN0 1f90 1ar0 16J0 1gXB0 WM0 1rA0 11c0 nwo0 Ko0 1cM0 1cM0 1rA0 10M0 zuM0 10N0 1aN0 1qM0 WM0 1qM0 11A0 1o00|20e5","Africa/Windhoek|LMT +0130 SAST SAST CAT WAT|-18.o -1u -20 -30 -20 -10|012324545454545454545454545454545454545454545454545454|-39Ep8.o qTbC.o 1Ajdu 1cL0 1SqL0 9Io0 16P0 1nX0 11B0 1qL0 WN0 1qL0 11B0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1qL0 WN0 1qL0 11B0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1qL0 11B0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1qL0 WN0 1qL0 11B0 1nX0 11B0 1nX0 11B0 1nX0 11B0|32e4","America/Adak|LMT LMT NST NWT NPT BST BDT AHST HST HDT|-cd.m bK.C b0 a0 a0 b0 a0 a0 a0 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1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|326","America/Anchorage|LMT LMT AST AWT APT AHST AHDT YST AKST AKDT|-e0.o 9X.A a0 90 90 a0 90 90 90 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1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|30e4","America/Port_of_Spain|LMT AST|46.4 40|01|-2kNvR.U|43e3","America/Araguaina|LMT -03 -02|3c.M 30 20|0121212121212121212121212121212121212121212121212121|-2glwL.c HdKL.c 1cc0 1e10 1bX0 Ezd0 So0 1vA0 Mn0 1BB0 ML0 1BB0 zX0 qe10 xb0 2ep0 nz0 1C10 zX0 1C10 LX0 1C10 Mn0 H210 Rb0 1tB0 IL0 1Fd0 FX0 1EN0 FX0 1HB0 Lz0 dMN0 Lz0 1zd0 Rb0 1wN0 Wn0 1tB0 Rb0 1tB0 WL0 1tB0 Rb0 1zd0 On0 1HB0 FX0 ny10 Lz0|14e4","America/Argentina/Buenos_Aires|LMT CMT -04 -03 -02|3R.M 4g.M 40 30 20|012323232323232323232323232323232323232323234343434343434343|-331U6.c 125cn pKnH.c Mn0 1iN0 Tb0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 MN0 2jz0 MN0 4lX0 u10 5Lb0 1pB0 Fnz0 u10 uL0 1vd0 SL0 1vd0 SL0 1vd0 17z0 1cN0 1fz0 1cN0 1cL0 1cN0 asn0 Db0 zvd0 Bz0 1tB0 TX0 1wp0 Rb0 1wp0 Rb0 1wp0 TX0 A4p0 uL0 1qN0 WL0","America/Argentina/Catamarca|LMT CMT -04 -03 -02|4n.8 4g.M 40 30 20|012323232323232323232323232323232323232323234343434243432343|-331TA.Q 125bR.E pKnH.c Mn0 1iN0 Tb0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 MN0 2jz0 MN0 4lX0 u10 5Lb0 1pB0 Fnz0 u10 uL0 1vd0 SL0 1vd0 SL0 1vd0 17z0 1cN0 1fz0 1cN0 1cL0 1cN0 asn0 Db0 zvd0 Bz0 1tB0 TX0 1wp0 Rb0 1wq0 Ra0 1wp0 TX0 rlB0 7B0 8zb0 uL0","America/Argentina/Cordoba|LMT CMT -04 -03 -02|4g.M 4g.M 40 30 20|012323232323232323232323232323232323232323234343434243434343|-331TH.c 125c0 pKnH.c Mn0 1iN0 Tb0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 MN0 2jz0 MN0 4lX0 u10 5Lb0 1pB0 Fnz0 u10 uL0 1vd0 SL0 1vd0 SL0 1vd0 17z0 1cN0 1fz0 1cN0 1cL0 1cN0 asn0 Db0 zvd0 Bz0 1tB0 TX0 1wp0 Rb0 1wq0 Ra0 1wp0 TX0 A4p0 uL0 1qN0 WL0","America/Argentina/Jujuy|LMT CMT -04 -03 -02|4l.c 4g.M 40 30 20|0123232323232323232323232323232323232323232343434232434343|-331TC.M 125bT.A pKnH.c Mn0 1iN0 Tb0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 MN0 2jz0 MN0 4lX0 u10 5Lb0 1pB0 Fnz0 u10 uL0 1vd0 SL0 1vd0 SL0 1vd0 17z0 1cN0 1fz0 1cN0 1cL0 1cN0 asn0 Db0 zvd0 Bz0 1tB0 TX0 1ze0 TX0 1ld0 WK0 1wp0 TX0 A4p0 uL0","America/Argentina/La_Rioja|LMT CMT -04 -03 -02|4r.o 4g.M 40 30 20|0123232323232323232323232323232323232323232343434342343432343|-331Tw.A 125bN.o pKnH.c Mn0 1iN0 Tb0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 MN0 2jz0 MN0 4lX0 u10 5Lb0 1pB0 Fnz0 u10 uL0 1vd0 SL0 1vd0 SL0 1vd0 17z0 1cN0 1fz0 1cN0 1cL0 1cN0 asn0 Db0 zvd0 Bz0 1tB0 TX0 1wp0 Qn0 qO0 16n0 Rb0 1wp0 TX0 rlB0 7B0 8zb0 uL0","America/Argentina/Mendoza|LMT CMT -04 -03 -02|4z.g 4g.M 40 30 20|012323232323232323232323232323232323232323234343423232432343|-331To.I 125bF.w pKnH.c Mn0 1iN0 Tb0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 MN0 2jz0 MN0 4lX0 u10 5Lb0 1pB0 Fnz0 u10 uL0 1vd0 SL0 1vd0 SL0 1vd0 17z0 1cN0 1fz0 1cN0 1cL0 1cN0 asn0 Db0 zvd0 Bz0 1tB0 TX0 1u20 SL0 1vd0 Tb0 1wp0 TW0 ri10 Op0 7TX0 uL0","America/Argentina/Rio_Gallegos|LMT CMT -04 -03 -02|4A.Q 4g.M 40 30 20|012323232323232323232323232323232323232323234343434343432343|-331Tn.8 125bD.U pKnH.c Mn0 1iN0 Tb0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 MN0 2jz0 MN0 4lX0 u10 5Lb0 1pB0 Fnz0 u10 uL0 1vd0 SL0 1vd0 SL0 1vd0 17z0 1cN0 1fz0 1cN0 1cL0 1cN0 asn0 Db0 zvd0 Bz0 1tB0 TX0 1wp0 Rb0 1wp0 Rb0 1wp0 TX0 rlB0 7B0 8zb0 uL0","America/Argentina/Salta|LMT CMT -04 -03 -02|4l.E 4g.M 40 30 20|0123232323232323232323232323232323232323232343434342434343|-331TC.k 125bT.8 pKnH.c Mn0 1iN0 Tb0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 MN0 2jz0 MN0 4lX0 u10 5Lb0 1pB0 Fnz0 u10 uL0 1vd0 SL0 1vd0 SL0 1vd0 17z0 1cN0 1fz0 1cN0 1cL0 1cN0 asn0 Db0 zvd0 Bz0 1tB0 TX0 1wp0 Rb0 1wq0 Ra0 1wp0 TX0 A4p0 uL0","America/Argentina/San_Juan|LMT CMT -04 -03 -02|4y.4 4g.M 40 30 20|0123232323232323232323232323232323232323232343434342343432343|-331Tp.U 125bG.I pKnH.c Mn0 1iN0 Tb0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 MN0 2jz0 MN0 4lX0 u10 5Lb0 1pB0 Fnz0 u10 uL0 1vd0 SL0 1vd0 SL0 1vd0 17z0 1cN0 1fz0 1cN0 1cL0 1cN0 asn0 Db0 zvd0 Bz0 1tB0 TX0 1wp0 Qn0 qO0 16n0 Rb0 1wp0 TX0 rld0 m10 8lb0 uL0","America/Argentina/San_Luis|LMT CMT -04 -03 -02|4p.o 4g.M 40 30 20|0123232323232323232323232323232323232323232343434232323432323|-331Ty.A 125bP.o pKnH.c Mn0 1iN0 Tb0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 MN0 2jz0 MN0 4lX0 u10 5Lb0 1pB0 Fnz0 u10 uL0 1vd0 SL0 1vd0 SL0 1vd0 17z0 1cN0 1fz0 1cN0 1cL0 1cN0 asn0 Db0 zvd0 Bz0 1tB0 XX0 1q20 SL0 AN0 vDb0 m10 8lb0 8L0 jd0 1qN0 WL0 1qN0","America/Argentina/Tucuman|LMT CMT -04 -03 -02|4k.Q 4g.M 40 30 20|01232323232323232323232323232323232323232323434343424343234343|-331TD.8 125bT.U pKnH.c Mn0 1iN0 Tb0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 MN0 2jz0 MN0 4lX0 u10 5Lb0 1pB0 Fnz0 u10 uL0 1vd0 SL0 1vd0 SL0 1vd0 17z0 1cN0 1fz0 1cN0 1cL0 1cN0 asn0 Db0 zvd0 Bz0 1tB0 TX0 1wp0 Rb0 1wq0 Ra0 1wp0 TX0 rlB0 4N0 8BX0 uL0 1qN0 WL0","America/Argentina/Ushuaia|LMT CMT -04 -03 -02|4x.c 4g.M 40 30 20|012323232323232323232323232323232323232323234343434343432343|-331Tq.M 125bH.A pKnH.c Mn0 1iN0 Tb0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 1C10 LX0 1C10 LX0 1C10 LX0 1C10 Mn0 MN0 2jz0 MN0 4lX0 u10 5Lb0 1pB0 Fnz0 u10 uL0 1vd0 SL0 1vd0 SL0 1vd0 17z0 1cN0 1fz0 1cN0 1cL0 1cN0 asn0 Db0 zvd0 Bz0 1tB0 TX0 1wp0 Rb0 1wp0 Rb0 1wp0 TX0 rkN0 8p0 8zb0 uL0","America/Curacao|LMT -0430 AST|4z.L 4u 40|012|-2kV7o.d 28KLS.d|15e4","America/Asuncion|LMT AMT -04 -03|3O.E 3O.E 40 30|0123232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323|-3eLw9.k 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1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 19X0 1fB0 19X0 1fB0 19X0 1ip0 17b0 1ip0 17b0 1ip0 17b0 1ip0|28e5","America/Atikokan|LMT CST CDT CWT CPT EST|66.s 60 50 50 50 50|01212345|-32B5R.w UFdR.w 1in0 Rnb0 3je0 8x30 iw0|28e2","America/Bahia_Banderas|LMT MST CST PST MDT CDT|71 70 60 80 60 50|0121212131414141414141414141414141414152525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252|-1UQF0 deL0 8lc0 17c0 10M0 1dd0 otX0 gmN0 P2N0 13Vd0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 1fB0 WL0 1fB0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nW0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0|84e3","America/Bahia|LMT -03 -02|2y.4 30 20|01212121212121212121212121212121212121212121212121212121212121|-2glxp.U HdLp.U 1cc0 1e10 1bX0 Ezd0 So0 1vA0 Mn0 1BB0 ML0 1BB0 zX0 qe10 xb0 2ep0 nz0 1C10 zX0 1C10 LX0 1C10 Mn0 H210 Rb0 1tB0 IL0 1Fd0 FX0 1EN0 FX0 1HB0 Lz0 1EN0 Lz0 1C10 IL0 1HB0 Db0 1HB0 On0 1zd0 On0 1zd0 Lz0 1zd0 Rb0 1wN0 Wn0 1tB0 Rb0 1tB0 WL0 1tB0 Rb0 1zd0 On0 1HB0 FX0 l5B0 Rb0|27e5","America/Barbados|LMT BMT AST ADT|3W.t 3W.t 40 30|01232323232|-1Q0I1.v jsM0 1ODC1.v IL0 1ip0 17b0 1ip0 17b0 1ld0 13b0|28e4","America/Belem|LMT -03 -02|3d.U 30 20|012121212121212121212121212121|-2glwK.4 HdKK.4 1cc0 1e10 1bX0 Ezd0 So0 1vA0 Mn0 1BB0 ML0 1BB0 zX0 qe10 xb0 2ep0 nz0 1C10 zX0 1C10 LX0 1C10 Mn0 H210 Rb0 1tB0 IL0 1Fd0 FX0|20e5","America/Belize|LMT CST -0530 CDT|5Q.M 60 5u 50|01212121212121212121212121212121212121212121212121213131|-2kBu7.c fPA7.c Onu 1zcu Rbu 1wou Rbu 1wou Rbu 1zcu Onu 1zcu Onu 1zcu Rbu 1wou 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60|01212134536363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363|-3tFE0 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1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|21e4","America/Cambridge_Bay|-00 MST MWT MPT MDDT MDT CST CDT EST|0 70 60 60 50 60 60 50 50|0123141515151515151515151515151515151515151515678651515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151515151|-21Jc0 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Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|15e2","America/Campo_Grande|LMT -04 -03|3C.s 40 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FX0 1HB0 FX0 1HB0 FX0 1HB0 IL0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 IL0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1Kp0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 IL0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 IL0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 IL0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 IL0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1Kp0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 IL0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 IL0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 IL0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 IL0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1Kp0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 IL0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0 FX0 1HB0|77e4","America/Cancun|LMT CST EST EDT CDT|5L.4 60 50 40 50|0123232341414141414141414141414141414141412|-1UQG0 2q2o0 yLB0 1lb0 14p0 1lb0 14p0 Lz0 xB0 14p0 1nX0 11B0 1nX0 1fB0 WL0 1fB0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 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50|012121212121212121212121212121212121213121212121214512121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121|-3tFG0 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Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|92e5","America/Chihuahua|LMT MST CST CDT MDT|74.k 70 60 50 60|0121212323241414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141|-1UQF0 deL0 8lc0 17c0 10M0 1dd0 2zQN0 1lb0 14p0 1lb0 14q0 1lb0 14p0 1nX0 11B0 1nX0 1fB0 WL0 1fB0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 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30|0121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212|-2glwf.E 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DC0|8","America/Dawson_Creek|LMT PST PDT PWT PPT MST|80.U 80 70 70 70 70|01213412121212121212121212121212121212121212121212121212125|-3tofX.4 1nspX.4 1in0 UGp0 8x10 iy0 3NB0 11z0 1o10 11z0 1o10 11z0 1qN0 WL0 1qN0 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1qN0 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1qN0 WL0 1qN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1cN0 ML0|12e3","America/Dawson|LMT YST YDT YWT YPT YDDT PST PDT|9h.E 90 80 80 80 70 80 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1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|13e2","America/Denver|LMT MST MDT MWT MPT|6X.U 70 60 60 60|012121212134121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121|-3tFF0 1nEe0 1nX0 11B0 1nX0 11B0 1qL0 WN0 mn0 Ord0 8x20 ix0 LCN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1cN0 1cL0 1cN0 1cL0 s10 1Vz0 LB0 1BX0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|26e5","America/Detroit|LMT CST EST EWT EPT EDT|5w.b 60 50 40 40 40|012342525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252|-2Cgir.N 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Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|37e5","America/Edmonton|LMT MST MDT MWT MPT|7x.Q 70 60 60 60|01212121212121341212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121|-2yd4q.8 shdq.8 1in0 17d0 hz0 2dB0 1fz0 1a10 11z0 1qN0 WL0 1qN0 11z0 IGN0 8x20 ix0 3NB0 11z0 LFB0 1cL0 3Cp0 1cL0 66N0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|10e5","America/Eirunepe|LMT -05 -04|4D.s 50 40|0121212121212121212121212121212121|-2glvk.w HdLk.w 1cc0 1e10 1bX0 Ezd0 So0 1vA0 Mn0 1BB0 ML0 1BB0 zX0 qe10 xb0 2ep0 nz0 1C10 zX0 1C10 LX0 1C10 Mn0 H210 Rb0 1tB0 IL0 1Fd0 FX0 dPB0 On0 yTd0 d5X0|31e3","America/El_Salvador|LMT CST CDT|5U.M 60 50|012121|-1XiG3.c 2Fvc3.c WL0 1qN0 WL0|11e5","America/Tijuana|LMT MST PST PDT PWT PPT|7M.4 70 80 70 70 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1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|76e2","America/Grand_Turk|LMT KMT EST EDT AST|4I.w 57.a 50 40 40|012323232323232323232323232323232323232323232323232323232323232323232323232343232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232|-3eLvf.s 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40|0123232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232|-3eLuu.w 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Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0","America/Indiana/Marengo|LMT CST CDT CWT CPT EST EDT|5J.n 60 50 50 50 50 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Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0","America/Indiana/Petersburg|LMT CST CDT CWT CPT EST EDT|5N.7 60 50 50 50 50 40|012121341212121212121212121215121212121212121212121252125656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565|-3tFG0 1nEe0 1nX0 11B0 1nX0 SgN0 8x30 iw0 njX0 WN0 1qN0 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1qN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 3Fb0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1cN0 1cL0 1cN0 1cL0 s10 1Vz0 LB0 1BX0 1cN0 1fz0 1a10 1fz0 19co0 1o00 Rd0 1zb0 Oo0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0","America/Indiana/Tell_City|LMT CST CDT CWT CPT EST EDT|5L.3 60 50 50 50 50 40|012121341212121212121212121212121565652121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121|-3tFG0 1nEe0 1nX0 11B0 1nX0 SgN0 8x30 iw0 1o10 11z0 g0p0 11z0 1o10 11z0 1qL0 WN0 1qN0 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1o10 1fz0 1cN0 WL0 1qN0 1cL0 1cN0 1cL0 1cN0 caL0 1cL0 1cN0 1cL0 1qhd0 1o00 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0","America/Indiana/Vevay|LMT CST CDT CWT CPT EST EDT|5E.g 60 50 50 50 50 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1nEe0 1nX0 11B0 1nX0 SgN0 8x30 iw0 kPB0 Awn0 1cL0 1cN0 1cL0 1cN0 1fz0 1cN0 1cL0 1lnd0 1nX0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 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Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0","America/Indiana/Vincennes|LMT CST CDT CWT CPT EST EDT|5O.7 60 50 50 50 50 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1nEe0 1nX0 11B0 1nX0 SgN0 8x30 iw0 1o10 11z0 g0p0 11z0 1o10 11z0 1qL0 WN0 1qN0 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1o10 1fz0 1cN0 WL0 1qN0 1cL0 1cN0 1cL0 1cN0 caL0 1cL0 1cN0 1cL0 1qhd0 1o00 Rd0 1zb0 Oo0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 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Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0","America/Indiana/Winamac|LMT CST CDT CWT CPT EST EDT|5K.p 60 50 50 50 50 40|012121341212121212121212121212121212121565652165656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565|-3tFG0 1nEe0 1nX0 11B0 1nX0 SgN0 8x30 iw0 1o10 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1qN0 WL0 1qN0 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1o10 1fz0 1cN0 1cL0 1cN0 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1qN0 jrz0 1cL0 1cN0 1cL0 1qhd0 1o00 Rd0 1za0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0","America/Inuvik|-00 PST PDDT MST MDT|0 80 60 70 60|0121343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343|-FnA0 tWU0 1fA0 wPe0 2pz0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|35e2","America/Iqaluit|-00 EWT EPT EST EDDT EDT CST CDT|0 40 40 50 30 40 60 50|01234353535353535353535353535353535353535353567353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353535353|-16K00 7nX0 iv0 LCL0 1fA0 zgO0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11C0 1nX0 11A0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|67e2","America/Jamaica|LMT KMT EST EDT|57.a 57.a 50 40|01232323232323232323232|-3eLuQ.O RK00 2uM1Q.O 1Vz0 LB0 1BX0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0|94e4","America/Juneau|LMT LMT PST PWT PPT PDT YDT YST AKST AKDT|-f2.j 8V.F 80 70 70 70 80 90 90 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Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|33e3","America/Kentucky/Louisville|LMT CST CDT CWT CPT EST EDT|5H.2 60 50 50 50 50 40|01212121213412121212121212121212121212565656565656525656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565|-3tFG0 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Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 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Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 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Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0","America/La_Paz|LMT CMT BST -04|4w.A 4w.A 3w.A 40|0123|-3eLvr.o 1FIo0 13b0|19e5","America/Lima|LMT LMT -05 -04|58.c 58.A 50 40|01232323232323232|-3eLuP.M JcM0.o 1bDzP.o zX0 1aN0 1cL0 1cN0 1cL0 1PrB0 zX0 1O10 zX0 6Gp0 zX0 98p0 zX0|11e6","America/Los_Angeles|LMT PST PDT PWT PPT|7Q.W 80 70 70 70|0121213412121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121|-3tFE0 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Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|15e6","America/Maceio|LMT -03 -02|2m.Q 30 20|012121212121212121212121212121212121212121|-2glxB.8 HdLB.8 1cc0 1e10 1bX0 Ezd0 So0 1vA0 Mn0 1BB0 ML0 1BB0 zX0 qe10 xb0 2ep0 nz0 1C10 zX0 1C10 LX0 1C10 Mn0 H210 Rb0 1tB0 IL0 1Fd0 FX0 1EN0 FX0 1HB0 Lz0 dMN0 Lz0 8Q10 WL0 1tB0 5z0 2mN0 On0|93e4","America/Managua|LMT MMT CST EST CDT|5J.8 5J.c 60 50 50|01232424232324242|-3eLue.Q 1Mhc0.4 1yAMe.M 4mn0 9Up0 Dz0 1K10 Dz0 s3F0 1KH0 DB0 9In0 k8p0 19X0 1o30 11y0|22e5","America/Manaus|LMT -04 -03|40.4 40 30|01212121212121212121212121212121|-2glvX.U HdKX.U 1cc0 1e10 1bX0 Ezd0 So0 1vA0 Mn0 1BB0 ML0 1BB0 zX0 qe10 xb0 2ep0 nz0 1C10 zX0 1C10 LX0 1C10 Mn0 H210 Rb0 1tB0 IL0 1Fd0 FX0 dPB0 On0|19e5","America/Martinique|LMT FFMT AST ADT|44.k 44.k 40 30|01232|-3eLvT.E PTA0 2LPbT.E 19X0|39e4","America/Matamoros|LMT CST CDT|6E 60 50|0121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121|-1UQG0 2FjC0 1nX0 i6p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 1fB0 WL0 1fB0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 U10 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|45e4","America/Mazatlan|LMT MST CST PST MDT|75.E 70 60 80 60|0121212131414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141|-1UQF0 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14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 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50|012121341212152121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121|-3pdG9.x 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1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|85e2","America/Merida|LMT CST EST CDT|5W.s 60 50 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Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|14e2","America/Mexico_City|LMT MST CST CDT CWT|6A.A 70 60 50 50|012121232324232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232|-1UQF0 deL0 8lc0 17c0 10M0 1dd0 gEn0 TX0 3xd0 Jb0 6zB0 SL0 e5d0 17b0 1Pff0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 1fB0 WL0 1fB0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0|20e6","America/Miquelon|LMT AST -03 -02|3I.E 40 30 20|012323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232|-2mKkf.k 2LTAf.k gQ10 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|61e2","America/Moncton|LMT EST AST ADT AWT APT|4j.8 50 40 30 30 30|0123232323232323232323245232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232|-3txvE.Q J4ME.Q CwN0 1in0 zAo0 An0 1Nd0 An0 1Nd0 An0 1Nd0 An0 1Nd0 An0 1Nd0 An0 1K10 Lz0 1zB0 NX0 1u10 Wn0 S20 8x50 iu0 1o10 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1qN0 WL0 1qN0 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1qN0 11z0 1o10 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1cN0 1cL0 3Cp0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14n1 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 ReX 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|64e3","America/Monterrey|LMT CST CDT|6F.g 60 50|0121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121|-1UQG0 2FjC0 1nX0 i6p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 1fB0 WL0 1fB0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 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1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 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Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|24e4","America/New_York|LMT EST EDT EWT EPT|4U.2 50 40 40 40|012121212121212121212121212121212121212121212121213412121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121|-3tFH0 1nEe0 1nX0 11B0 1nX0 11B0 1qL0 1a10 11z0 1qN0 WL0 1qN0 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1qN0 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1qN0 WL0 1qN0 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1qN0 WL0 1qN0 11z0 1o10 11z0 RB0 8x40 iv0 1o10 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1qN0 WL0 1qN0 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1o10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1cN0 1cL0 1cN0 1cL0 s10 1Vz0 LB0 1BX0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|21e6","America/Nipigon|LMT EST EDT EWT EPT|5R.4 50 40 40 40|0121234121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121|-32B66.U UFd6.U 1in0 Rnb0 3je0 8x40 iv0 19yN0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 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Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0","America/North_Dakota/Center|LMT MST MDT MWT MPT CST CDT|6J.c 70 60 60 60 60 50|0121213412121212121212121212121212121212121212121212121212125656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565|-3tFF0 1nEe0 1nX0 11B0 1nX0 SgN0 8x20 ix0 QwN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1cN0 1cL0 1cN0 1cL0 s10 1Vz0 LB0 1BX0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14o0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0","America/North_Dakota/New_Salem|LMT MST MDT MWT MPT CST CDT|6J.D 70 60 60 60 60 50|0121213412121212121212121212121212121212121212121212121212121212121212121212121212565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565656565|-3tFF0 1nEe0 1nX0 11B0 1nX0 SgN0 8x20 ix0 QwN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1cN0 1cL0 1cN0 1cL0 s10 1Vz0 LB0 1BX0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14o0 1nX0 11B0 1nX0 11B0 1nX0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0","America/Ojinaga|LMT MST CST CDT MDT|6V.E 70 60 50 60|0121212323241414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141|-1UQF0 deL0 8lc0 17c0 10M0 1dd0 2zQN0 1lb0 14p0 1lb0 14q0 1lb0 14p0 1nX0 11B0 1nX0 1fB0 WL0 1fB0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 U10 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|23e3","America/Pangnirtung|-00 AST AWT APT ADDT ADT EDT EST CST CDT|0 40 30 30 20 30 40 50 60 50|012314151515151515151515151515151515167676767689767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767676767|-1XiM0 PnG0 8x50 iu0 LCL0 1fA0 zgO0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1o00 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11C0 1nX0 11A0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|14e2","America/Paramaribo|LMT PMT PMT -0330 -03|3E.E 3E.Q 3E.A 3u 30|01234|-2nDUj.k Wqo0.c qanX.I 1yVXN.o|24e4","America/Phoenix|LMT MST MDT MWT|7s.i 70 60 60|012121313121|-3tFF0 1nEe0 1nX0 11B0 1nX0 SgN0 4Al1 Ap0 1db0 SWqX 1cL0|42e5","America/Port-au-Prince|LMT PPMT EST EDT|4N.k 4N 50 40|012323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232|-3eLva.E 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Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|23e5","America/Rio_Branco|LMT -05 -04|4v.c 50 40|01212121212121212121212121212121|-2glvs.M HdLs.M 1cc0 1e10 1bX0 Ezd0 So0 1vA0 Mn0 1BB0 ML0 1BB0 zX0 qe10 xb0 2ep0 nz0 1C10 zX0 1C10 LX0 1C10 Mn0 H210 Rb0 1tB0 IL0 1Fd0 FX0 NBd0 d5X0|31e4","America/Porto_Velho|LMT -04 -03|4f.A 40 30|012121212121212121212121212121|-2glvI.o HdKI.o 1cc0 1e10 1bX0 Ezd0 So0 1vA0 Mn0 1BB0 ML0 1BB0 zX0 qe10 xb0 2ep0 nz0 1C10 zX0 1C10 LX0 1C10 Mn0 H210 Rb0 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50|0121234121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121|-32B5F.I 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Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|842","America/Rankin_Inlet|-00 CST CDDT CDT EST|0 60 40 50 50|012131313131313131313131313131313131313131313431313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131|-vDc0 keu0 1fA0 zgO0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|26e2","America/Recife|LMT -03 -02|2j.A 30 20|0121212121212121212121212121212121212121|-2glxE.o HdLE.o 1cc0 1e10 1bX0 Ezd0 So0 1vA0 Mn0 1BB0 ML0 1BB0 zX0 qe10 xb0 2ep0 nz0 1C10 zX0 1C10 LX0 1C10 Mn0 H210 Rb0 1tB0 IL0 1Fd0 FX0 1EN0 FX0 1HB0 Lz0 nsp0 WL0 1tB0 2L0 2pB0 On0|33e5","America/Regina|LMT MST MDT MWT MPT CST|6W.A 70 60 60 60 60|012121212121212121212121341212121212121212121212121215|-2AD51.o uHe1.o 1in0 s2L0 11z0 1o10 11z0 1o10 11z0 1qN0 WL0 1qN0 11z0 66N0 1cL0 1cN0 19X0 1fB0 1cL0 1fB0 1cL0 1cN0 1cL0 M30 8x20 ix0 1ip0 1cL0 1ip0 11z0 1o10 11z0 1o10 11z0 1qN0 WL0 1qN0 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1qN0 11z0 1o10 11z0 3NB0 1cL0 1cN0|19e4","America/Resolute|-00 CST CDDT CDT EST|0 60 40 50 50|012131313131313131313131313131313131313131313431313131313431313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131313131|-SnA0 GWS0 1fA0 zgO0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 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Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|90e2","America/St_Johns|LMT NST NDT NST NDT NWT NPT NDDT|3u.Q 3u.Q 2u.Q 3u 2u 2u 2u 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1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|11e4","America/Swift_Current|LMT MST MDT MWT MPT CST|7b.k 70 60 60 60 60|012134121212121212121215|-2AD4M.E uHdM.E 1in0 UGp0 8x20 ix0 1o10 17b0 1ip0 11z0 1o10 11z0 1o10 11z0 isN0 1cL0 3Cp0 1cL0 1cN0 11z0 1qN0 WL0 pMp0|16e3","America/Tegucigalpa|LMT CST CDT|5M.Q 60 50|01212121|-1WGGb.8 2ETcb.8 WL0 1qN0 WL0 GRd0 AL0|11e5","America/Thule|LMT AST ADT|4z.8 40 30|012121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121|-2a5To.Q 31NBo.Q 1cL0 1cN0 1cL0 1fB0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|656","America/Thunder_Bay|LMT CST EST EWT EPT EDT|5V 60 50 40 40 40|01234252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252525252|-32B63 Avc3 1iaN0 8x40 iv0 XNB0 1cL0 1cN0 1fz0 1cN0 1cL0 3Cp0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|11e4","America/Vancouver|LMT PST PDT PWT PPT|8c.s 80 70 70 70|01213412121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121|-3tofL.w 1nspL.w 1in0 UGp0 8x10 iy0 1o10 17b0 1ip0 11z0 1o10 11z0 1o10 11z0 1qN0 WL0 1qN0 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1qN0 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1o10 11z0 1qN0 WL0 1qN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1a10 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 14p0 1lb0 14p0 1lb0 14p0 1nX0 11B0 1nX0 11B0 1nX0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|23e5","America/Whitehorse|LMT YST YDT YWT YPT YDDT PST PDT|90.c 90 80 80 80 70 80 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1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|23e3","America/Winnipeg|LMT CST CDT CWT CPT|6s.A 60 50 50 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Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0|642","America/Yellowknife|-00 MST MWT MPT MDDT MDT|0 70 60 60 50 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EEST|-2p.c -20 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2a3cf.M 1cL0 1qp0 Xz0 19B0 19X0 1fB0 1db0 1cp0 1cL0 1fB0 19X0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1fz0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1cN0 1cL0 1fB0 1cL0 1cN0 1cL0 1cN0 1o30 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 15U0 2Ks0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 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1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 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11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 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11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 WN0 1qL0 11B0 1qL0|25e4","Asia/Ho_Chi_Minh|LMT PLMT +07 +08 +09|-76.E -76.u -70 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11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00|25e4","Atlantic/Bermuda|LMT AST ADT|4j.i 40 30|0121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121212121|-1BnRE.G 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Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 Rd0 1zb0 Op0 1zb0 Op0 1zb0 Op0 1zb0 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1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00|41e5","Europe/Prague|LMT PMT CET CEST GMT|-V.I -V.I -10 -20 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1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00|21e5","Europe/Bucharest|LMT BMT EET EEST|-1I.o -1I.o -20 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11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 WM0 1qM0 11A0 1o00 11A0 1o00 11A0 1qM0 WM0 1qM0 WM0 1qM0 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analysis.ipynb b/datasets/Talluri2021/timeseries analysis.ipynb new file mode 100644 index 0000000..9481dd1 --- /dev/null +++ b/datasets/Talluri2021/timeseries analysis.ipynb @@ -0,0 +1,930 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 139, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "from plotnine import *\n", + "import numpy as np\n", + "from sklearn.linear_model import LinearRegression\n", + "from numpy import polyfit" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "or_events = pd.read_parquet('./outage_report_2019-20')" + ] + }, + { + "cell_type": "code", + "execution_count": 134, + "metadata": {}, + "outputs": [], + "source": [ + "filtered_or_events = or_events[(or_events['vendor'] != '') & (or_events['vendor'] != 'overview')].reset_index(drop=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 135, + "metadata": {}, + "outputs": [], + "source": [ + "filtered_or_events['evtime'] = pd.to_datetime(filtered_or_events['event_time'], unit='s')" + ] + }, + { + "cell_type": "code", + "execution_count": 136, + "metadata": {}, + "outputs": [], + "source": [ + "def proper_vendor_names(series):\n", + " return series.str.capitalize().replace(['Apple-servers', 'Facebook-messenger', 'Youtube'], ['Apple', 'FB Msgr', 'YouTube'])\n", + "\n", + "filtered_or_events['vendor_proper'] = proper_vendor_names(filtered_or_events['vendor'])\n", + "\n", + "vendor_list = list(filtered_or_events.groupby('vendor_proper')['status_code'].sum().reset_index().rename(columns={'status_code':'count'}).sort_values('count')['vendor_proper'])\n", + "\n", + "filtered_or_events['vendor_cat'] = pd.Categorical(filtered_or_events['vendor_proper'], ordered=True, categories=vendor_list)" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [], + "source": [ + "facebook_reports = filtered_or_events[filtered_or_events['vendor'] == 'facebook'].reset_index(drop=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [], + "source": [ + "sorted_facebook_reports = facebook_reports.sort_values('event_time').reset_index(drop=True).set_index('evtime').resample('W')" + ] + }, + { + "cell_type": "code", + "execution_count": 182, + "metadata": {}, + "outputs": [], + "source": [ + "sorted_facebook_reports = facebook_reports.sort_values('event_time').reset_index(drop=True).set_index('evtime').resample('M').sum().reset_index()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1200.0" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# That 20 minutes!\n", + "sorted_facebook_reports.loc[2, 'event_time'] - sorted_facebook_reports.loc[1, 'event_time']" + ] + }, + { + "cell_type": "code", + "execution_count": 183, + "metadata": {}, + "outputs": [], + "source": [ + "model = LinearRegression()\n", + "zeroed_time = (sorted_facebook_reports['event_time'] - sorted_facebook_reports.loc[0, 'event_time']).values.reshape(-1, 1)\n", + "model.fit(zeroed_time, sorted_facebook_reports['status_code'].values)\n", + "# calculate trend\n", + "trend = model.predict(zeroed_time)\n", + "trend[trend < 1] = 0\n", + "sorted_facebook_reports['trend'] = trend" + ] + }, + { + "cell_type": "code", + "execution_count": 184, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:727: PlotnineWarning: Saving 14 x 3 in image.\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:730: PlotnineWarning: Filename: ./plots/week_facebook_fit_trend.pdf\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/pandas/core/series.py:726: RuntimeWarning: divide by zero encountered in log10\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/pandas/core/series.py:726: RuntimeWarning: divide by zero encountered in log10\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1400x300 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (340918032)>" + ] + }, + "execution_count": 184, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Trend\n", + "plt = ggplot(sorted_facebook_reports) +\\\n", + " geom_line(aes(x='evtime', y='status_code')) +\\\n", + " geom_line(aes(x='evtime', y='trend'), color='red') +\\\n", + " scale_y_log10() +\\\n", + " theme(figure_size=(14, 3))\n", + " \n", + "plt.save('./plots/week_facebook_fit_trend.pdf', limitsize=False)\n", + "plt" + ] + }, + { + "cell_type": "code", + "execution_count": 118, + "metadata": {}, + "outputs": [], + "source": [ + "sorted_facebook_reports['detrended'] = sorted_facebook_reports['status_code'] - sorted_facebook_reports['trend']\n", + "sorted_facebook_reports.loc[sorted_facebook_reports['detrended'] < 1, 'detrended'] = 0" + ] + }, + { + "cell_type": "code", + "execution_count": 119, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:727: PlotnineWarning: Saving 14 x 3 in image.\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:730: PlotnineWarning: Filename: ./plots/facebook_detrended_see_season.pdf\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/pandas/core/series.py:726: RuntimeWarning: divide by zero encountered in log10\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/pandas/core/series.py:726: RuntimeWarning: divide by zero encountered in log10\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1400x300 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (378200962)>" + ] + }, + "execution_count": 119, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Seasonal\n", + "plt = ggplot(sorted_facebook_reports) +\\\n", + " geom_line(aes(x='evtime', y='detrended')) +\\\n", + " scale_y_log10() +\\\n", + " theme(figure_size=(14, 3))\n", + "\n", + "plt.save('./plots/facebook_detrended_see_season.pdf', limitsize=False)\n", + "plt" + ] + }, + { + "cell_type": "code", + "execution_count": 120, + "metadata": {}, + "outputs": [], + "source": [ + "pre_covid = sorted_facebook_reports[sorted_facebook_reports['evtime'] < '2020-05-01'].reset_index(drop=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 121, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Coefficients: [ 1.02182988e-36 -5.18993758e-29 2.43161974e-23 3.03903805e-14\n", + " -4.51565610e-07 3.16755426e+00]\n" + ] + } + ], + "source": [ + "degree = 5\n", + "reshaped_zeroed_time = (pre_covid['event_time'] - pre_covid.loc[0, 'event_time']).values\n", + "coef = polyfit(reshaped_zeroed_time, pre_covid['detrended'].values, degree)\n", + "print('Coefficients: %s' % coef)\n", + "# create curve\n", + "curve = list()\n", + "for i in range(len(reshaped_zeroed_time)):\n", + "\tvalue = coef[-1]\n", + "\tfor d in range(degree):\n", + "\t\tvalue += reshaped_zeroed_time[i]**(degree-d) * coef[d]\n", + "\tcurve.append(value)" + ] + }, + { + "cell_type": "code", + "execution_count": 126, + "metadata": {}, + "outputs": [], + "source": [ + "pre_covid['seasonality'] = curve\n", + "pre_covid['deseasoned'] = pre_covid['detrended'] - pre_covid['seasonality']\n", + "pre_covid.loc[pre_covid['deseasoned'] < 1, 'deseasoned'] = 0" + ] + }, + { + "cell_type": "code", + "execution_count": 123, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:727: PlotnineWarning: Saving 14 x 3 in image.\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:730: PlotnineWarning: Filename: ./plots/facebook_fit_seasonality.pdf\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/pandas/core/series.py:726: RuntimeWarning: divide by zero encountered in log10\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/pandas/core/series.py:726: RuntimeWarning: divide by zero encountered in log10\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1400x300 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (340891380)>" + ] + }, + "execution_count": 123, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Fit seasonality\n", + "plt = ggplot(pre_covid) +\\\n", + " geom_line(aes(x='evtime', y='detrended')) +\\\n", + " geom_line(aes(x='evtime', y='seasonality'), color='red') +\\\n", + " scale_y_log10() +\\\n", + " theme(figure_size=(14, 3))\n", + "\n", + "plt.save('./plots/facebook_fit_seasonality.pdf', limitsize=False)\n", + "plt" + ] + }, + { + "cell_type": "code", + "execution_count": 127, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:727: PlotnineWarning: Saving 14 x 3 in image.\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:730: PlotnineWarning: Filename: ./plots/facebook_deseasoned.pdf\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/pandas/core/series.py:726: RuntimeWarning: divide by zero encountered in log10\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/pandas/core/series.py:726: RuntimeWarning: divide by zero encountered in log10\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1400x300 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (347762351)>" + ] + }, + "execution_count": 127, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Deseasoned\n", + "\n", + "plt = ggplot(pre_covid) +\\\n", + " geom_line(aes(x='evtime', y='deseasoned')) +\\\n", + " scale_y_log10() +\\\n", + " theme(figure_size=(14, 3))\n", + "\n", + "plt.save('./plots/facebook_deseasoned.pdf', limitsize=False)\n", + "plt" + ] + }, + { + "cell_type": "code", + "execution_count": 170, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>event_time</th>\n", + " <th>status_code</th>\n", + " <th>vendor</th>\n", + " <th>monitor</th>\n", + " <th>evtime</th>\n", + " <th>trend</th>\n", + " <th>detrended</th>\n", + " <th>status_code_pc</th>\n", + " <th>vendor_pc</th>\n", + " <th>monitor_pc</th>\n", + " <th>evtime_pc</th>\n", + " <th>trend_pc</th>\n", + " <th>detrended_pc</th>\n", + " <th>seasonality</th>\n", + " <th>residual</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>0</th>\n", + " <td>1.555241e+09</td>\n", + " <td>210.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2019-04-14 11:20:00</td>\n", + " <td>3.971304</td>\n", + " <td>206.028696</td>\n", + " <td>210.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2019-04-14 11:20:00</td>\n", + " <td>3.971304</td>\n", + " <td>206.028696</td>\n", + " <td>3.167554</td>\n", + " <td>202.861142</td>\n", + " </tr>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>1.555242e+09</td>\n", + " <td>299.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2019-04-14 11:40:00</td>\n", + " <td>3.971197</td>\n", + " <td>295.028803</td>\n", + " <td>299.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2019-04-14 11:40:00</td>\n", + " <td>3.971197</td>\n", + " <td>295.028803</td>\n", + " <td>3.167012</td>\n", + " <td>291.861790</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2</th>\n", + " <td>1.555243e+09</td>\n", + " <td>813.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2019-04-14 12:00:00</td>\n", + " <td>3.971091</td>\n", + " <td>809.028909</td>\n", + " <td>813.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2019-04-14 12:00:00</td>\n", + " <td>3.971091</td>\n", + " <td>809.028909</td>\n", + " <td>3.166471</td>\n", + " <td>805.862439</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3</th>\n", + " <td>1.555244e+09</td>\n", + " <td>874.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2019-04-14 12:20:00</td>\n", + " <td>3.970984</td>\n", + " <td>870.029016</td>\n", + " <td>874.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2019-04-14 12:20:00</td>\n", + " <td>3.970984</td>\n", + " <td>870.029016</td>\n", + " <td>3.165929</td>\n", + " <td>866.863087</td>\n", + " </tr>\n", + " <tr>\n", + " <th>4</th>\n", + " <td>1.555246e+09</td>\n", + " <td>891.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2019-04-14 12:40:00</td>\n", + " <td>3.970877</td>\n", + " <td>887.029123</td>\n", + " <td>891.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2019-04-14 12:40:00</td>\n", + " <td>3.970877</td>\n", + " <td>887.029123</td>\n", + " <td>3.165387</td>\n", + " <td>883.863736</td>\n", + " </tr>\n", + " <tr>\n", + " <th>...</th>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " <td>...</td>\n", + " </tr>\n", + " <tr>\n", + " <th>48332</th>\n", + " <td>1.604180e+09</td>\n", + " <td>0.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2020-10-31 21:40:00</td>\n", + " <td>0.000000</td>\n", + " <td>0.000000</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " <td>NaT</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " </tr>\n", + " <tr>\n", + " <th>48333</th>\n", + " <td>1.604182e+09</td>\n", + " <td>0.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2020-10-31 22:00:00</td>\n", + " <td>0.000000</td>\n", + " <td>0.000000</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " <td>NaT</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " </tr>\n", + " <tr>\n", + " <th>48334</th>\n", + " <td>1.604183e+09</td>\n", + " <td>0.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2020-10-31 22:20:00</td>\n", + " <td>0.000000</td>\n", + " <td>0.000000</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " <td>NaT</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " </tr>\n", + " <tr>\n", + " <th>48335</th>\n", + " <td>1.604184e+09</td>\n", + " <td>0.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2020-10-31 22:40:00</td>\n", + " <td>0.000000</td>\n", + " <td>0.000000</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " <td>NaT</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " </tr>\n", + " <tr>\n", + " <th>48336</th>\n", + " <td>1.604185e+09</td>\n", + " <td>0.0</td>\n", + " <td>facebook</td>\n", + " <td>Outage Report</td>\n", + " <td>2020-10-31 23:00:00</td>\n", + " <td>0.000000</td>\n", + " <td>0.000000</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " <td>NaT</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " <td>NaN</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "<p>61795 rows × 15 columns</p>\n", + "</div>" + ], + "text/plain": [ + " event_time status_code vendor monitor evtime \\\n", + "0 1.555241e+09 210.0 facebook Outage Report 2019-04-14 11:20:00 \n", + "1 1.555242e+09 299.0 facebook Outage Report 2019-04-14 11:40:00 \n", + "2 1.555243e+09 813.0 facebook Outage Report 2019-04-14 12:00:00 \n", + "3 1.555244e+09 874.0 facebook Outage Report 2019-04-14 12:20:00 \n", + "4 1.555246e+09 891.0 facebook Outage Report 2019-04-14 12:40:00 \n", + "... ... ... ... ... ... \n", + "48332 1.604180e+09 0.0 facebook Outage Report 2020-10-31 21:40:00 \n", + "48333 1.604182e+09 0.0 facebook Outage Report 2020-10-31 22:00:00 \n", + "48334 1.604183e+09 0.0 facebook Outage Report 2020-10-31 22:20:00 \n", + "48335 1.604184e+09 0.0 facebook Outage Report 2020-10-31 22:40:00 \n", + "48336 1.604185e+09 0.0 facebook Outage Report 2020-10-31 23:00:00 \n", + "\n", + " trend detrended status_code_pc vendor_pc monitor_pc \\\n", + "0 3.971304 206.028696 210.0 facebook Outage Report \n", + "1 3.971197 295.028803 299.0 facebook Outage Report \n", + "2 3.971091 809.028909 813.0 facebook Outage Report \n", + "3 3.970984 870.029016 874.0 facebook Outage Report \n", + "4 3.970877 887.029123 891.0 facebook Outage Report \n", + "... ... ... ... ... ... \n", + "48332 0.000000 0.000000 NaN NaN NaN \n", + "48333 0.000000 0.000000 NaN NaN NaN \n", + "48334 0.000000 0.000000 NaN NaN NaN \n", + "48335 0.000000 0.000000 NaN NaN NaN \n", + "48336 0.000000 0.000000 NaN NaN NaN \n", + "\n", + " evtime_pc trend_pc detrended_pc seasonality residual \n", + "0 2019-04-14 11:20:00 3.971304 206.028696 3.167554 202.861142 \n", + "1 2019-04-14 11:40:00 3.971197 295.028803 3.167012 291.861790 \n", + "2 2019-04-14 12:00:00 3.971091 809.028909 3.166471 805.862439 \n", + "3 2019-04-14 12:20:00 3.970984 870.029016 3.165929 866.863087 \n", + "4 2019-04-14 12:40:00 3.970877 887.029123 3.165387 883.863736 \n", + "... ... ... ... ... ... \n", + "48332 NaT NaN NaN NaN NaN \n", + "48333 NaT NaN NaN NaN NaN \n", + "48334 NaT NaN NaN NaN NaN \n", + "48335 NaT NaN NaN NaN NaN \n", + "48336 NaT NaN NaN NaN NaN \n", + "\n", + "[61795 rows x 15 columns]" + ] + }, + "execution_count": 170, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def decompose_timeseries(partial_df):\n", + " sorted_partial_df = partial_df.sort_values('event_time').reset_index(drop=True)\n", + " \n", + " # Compute trend\n", + " model = LinearRegression()\n", + " zeroed_time = (sorted_partial_df['event_time'] - sorted_partial_df.loc[0, 'event_time']).values.reshape(-1, 1)\n", + " model.fit(zeroed_time, sorted_partial_df['status_code'].values)\n", + " # calculate trend\n", + " trend = model.predict(zeroed_time)\n", + " trend[trend < 1] = 0\n", + " sorted_partial_df['trend'] = trend\n", + " sorted_partial_df.loc[sorted_partial_df['trend'] < 1, 'trend'] = 0\n", + " \n", + " sorted_partial_df['detrended'] = sorted_partial_df['status_code'] - sorted_partial_df['trend']\n", + " sorted_partial_df.loc[sorted_partial_df['detrended'] < 1, 'detrended'] = 0\n", + " \n", + " # Compute seasonality\n", + " pre_covid = sorted_partial_df[sorted_partial_df['evtime'] < '2020-05-01'].reset_index(drop=True)\n", + " \n", + " degree = 5\n", + " reshaped_zeroed_time = (pre_covid['event_time'] - pre_covid.loc[0, 'event_time']).values\n", + " coef = polyfit(reshaped_zeroed_time, pre_covid['detrended'].values, degree)\n", + "# print('Coefficients: %s' % coef)\n", + " # create curve\n", + " curve = list()\n", + " for i in range(len(reshaped_zeroed_time)):\n", + " value = coef[-1]\n", + " for d in range(degree):\n", + " value += reshaped_zeroed_time[i]**(degree-d) * coef[d]\n", + " curve.append(value)\n", + " \n", + " pre_covid['seasonality'] = curve\n", + " pre_covid.loc[pre_covid['seasonality'] < 1, 'seasonality'] = 0\n", + " pre_covid['residual'] = pre_covid['detrended'] - pre_covid['seasonality']\n", + " pre_covid.loc[pre_covid['residual'] < 1, 'residual'] = 0\n", + " \n", + " return sorted_partial_df.join(pre_covid.set_index('event_time'), on='event_time', rsuffix='_pc')\n", + "\n", + "decompose_timeseries(facebook_reports)" + ] + }, + { + "cell_type": "code", + "execution_count": 171, + "metadata": {}, + "outputs": [], + "source": [ + "timeseries_analyzed_df_list = []\n", + "\n", + "for vendor in filtered_or_events['vendor_cat'].unique():\n", + " partial_df = filtered_or_events[filtered_or_events['vendor_cat'] == vendor].reset_index(drop=True)\n", + " timeseries_analyzed_df_list.append(decompose_timeseries(partial_df))\n", + " \n", + "timeseries_analyzed_df = pd.concat(timeseries_analyzed_df_list)" + ] + }, + { + "cell_type": "code", + "execution_count": 175, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/pandas/core/series.py:726: RuntimeWarning: divide by zero encountered in log10\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/geoms/geom_path.py:75: PlotnineWarning: geom_path: Removed 15274 rows containing missing values.\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/geoms/geom_path.py:75: PlotnineWarning: geom_path: Removed 15274 rows containing missing values.\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1400x300 with 12 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (421491932)>" + ] + }, + "execution_count": 175, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "plt = ggplot(timeseries_analyzed_df) +\\\n", + " geom_line(aes(x='evtime', y='status_code'), color='black') +\\\n", + " geom_line(aes(x='evtime', y='residual'), color='teal', alpha=0.5) +\\\n", + " geom_line(aes(x='evtime', y='trend'), color='red') +\\\n", + " geom_line(aes(x='evtime', y='seasonality'), color='lime') +\\\n", + " scale_y_log10() +\\\n", + " facet_wrap(facets='vendor_cat', nrow=2) +\\\n", + " theme_classic(base_size=12, base_family='sans-serif') +\\\n", + " theme(figure_size=(14, 3),\n", + " axis_text_y=element_text(margin={'r': 5}),\n", + " panel_grid_minor_x=element_line(size=0.7, color=\"gainsboro\"),\n", + " panel_grid_major_x=element_blank(),\n", + " text=element_text(size=12),\n", + " legend_box_spacing=0.01,\n", + " legend_box_margin=0,\n", + " legend_margin=0,\n", + " legend_key=element_blank(),\n", + " legend_entry_spacing=5,\n", + " legend_background=element_rect(fill=(0,0,0,0), color=(0,0,0,0)),\n", + " legend_position='top',)\n", + "\n", + "plt" + ] + }, + { + "cell_type": "code", + "execution_count": 204, + "metadata": {}, + "outputs": [], + "source": [ + "week_aggregated_df_list = []\n", + "month_aggregated_df_list = []\n", + "\n", + "for vendor in filtered_or_events['vendor_cat'].unique():\n", + " partial_df = filtered_or_events[filtered_or_events['vendor_cat'] == vendor].reset_index(drop=True)\n", + " \n", + " week_df = partial_df.set_index('evtime').resample('W').sum().reset_index()\n", + " week_df['vendor_cat'] = vendor\n", + " week_aggregated_df_list.append(week_df)\n", + " \n", + " month_df = partial_df.set_index('evtime').resample('M').sum().reset_index()\n", + " month_df['vendor_cat'] = vendor\n", + " month_aggregated_df_list.append(month_df)\n", + "\n", + "week_aggregated_df = pd.concat(week_aggregated_df_list)\n", + "week_aggregated_df['vendor_cat'] = pd.Categorical(week_aggregated_df['vendor_cat'], categories=vendor_list, ordered=True)\n", + "month_aggregated_df = pd.concat(month_aggregated_df_list)\n", + "month_aggregated_df['vendor_cat'] = pd.Categorical(month_aggregated_df['vendor_cat'], categories=vendor_list, ordered=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 217, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:727: PlotnineWarning: Saving 14 x 3 in image.\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/plotnine/ggplot.py:730: PlotnineWarning: Filename: ./plots/reports_week_and_month_aggregated.pdf\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/pandas/core/series.py:726: RuntimeWarning: divide by zero encountered in log10\n", + "/Users/sacheendra/miniconda3/envs/thesis/lib/python3.8/site-packages/pandas/core/series.py:726: RuntimeWarning: divide by zero encountered in log10\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1400x300 with 12 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (397037120)>" + ] + }, + "execution_count": 217, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "plt = ggplot() +\\\n", + " geom_line(aes(x='evtime', y='status_code'), data=filtered_or_events, color='black') +\\\n", + " geom_line(aes(x='evtime', y='status_code'), data=week_aggregated_df, color='teal') +\\\n", + " geom_line(aes(x='evtime', y='status_code'), data=month_aggregated_df, color='navy') +\\\n", + " scale_y_log10(labels=lambda l: list(map(lambda x: '$10^{}$'.format(int(np.log10(x))), l))) +\\\n", + " scale_x_datetime(date_breaks='3 months', date_labels='%m-%y') +\\\n", + " facet_wrap(facets='vendor_cat', nrow=2) +\\\n", + " ylab('Number of reports') +\\\n", + " xlab('Time (Start of quarter is labelled)') +\\\n", + " theme_classic(base_size=12, base_family='sans-serif') +\\\n", + " theme(figure_size=(14, 3),\n", + " axis_text_y=element_text(margin={'r': 5}),\n", + " panel_grid_major_x=element_line(size=0.7, color=\"gainsboro\"),\n", + " text=element_text(size=12),\n", + " legend_box_spacing=0.01,\n", + " legend_box_margin=0,\n", + " legend_margin=0,\n", + " legend_key=element_blank(),\n", + " legend_entry_spacing=5,\n", + " legend_background=element_rect(fill=(0,0,0,0), color=(0,0,0,0)),\n", + " legend_position='top',\n", + " axis_text_x=element_text(rotation=40))\n", + "\n", + "plt.save('./plots/reports_week_and_month_aggregated.pdf', limitsize=None)\n", + "plt" + ] + }, + { + "cell_type": "code", + "execution_count": 216, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 640x480 with 12 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<ggplot: (333651035)>" + ] + }, + "execution_count": 216, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "plt = ggplot() +\\\n", + " geom_line(aes(x='evtime', y='status_code'), data=month_aggregated_df) +\\\n", + " scale_y_log10() +\\\n", + " facet_wrap(facets='vendor_cat', ncol=1)\n", + "\n", + "plt" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/images/S0007850618300799.bib b/images/S0007850618300799.bib new file mode 100644 index 0000000..80c465c --- /dev/null +++ b/images/S0007850618300799.bib @@ -0,0 +1,14 @@ +@article{TAO2018169, +title = {Digital twin driven prognostics and health management for complex equipment}, +journal = {CIRP Annals}, +volume = {67}, +number = {1}, +pages = {169-172}, +year = {2018}, +issn = {0007-8506}, +doi = {https://doi.org/10.1016/j.cirp.2018.04.055}, +url = {https://www.sciencedirect.com/science/article/pii/S0007850618300799}, +author = {Fei Tao and Meng Zhang and Yushan Liu and A.Y.C. Nee}, +keywords = {Maintenance, Condition monitoring, Digital twin}, +abstract = {Prognostics and health management (PHM) is crucial in the lifecycle monitoring of a product, especially for complex equipment working in a harsh environment. In order to improve the accuracy and efficiency of PHM, digital twin (DT), an emerging technology to achieve physical–virtual convergence, is proposed for complex equipment. A general DT for complex equipment is first constructed, then a new method using DT driven PHM is proposed, making effective use of the interaction mechanism and fused data of DT. A case study of a wind turbine is used to illustrate the effectiveness of the proposed method.} +}
\ No newline at end of file diff --git a/images/five_dimensional_dt.pdf b/images/five_dimensional_dt.pdf Binary files differnew file mode 100644 index 0000000..b151bce --- /dev/null +++ b/images/five_dimensional_dt.pdf diff --git a/images/introduction-digital-twin.png b/images/introduction-digital-twin.png Binary files differnew file mode 100644 index 0000000..b7a26f2 --- /dev/null +++ b/images/introduction-digital-twin.png @@ -1,147 +1,226 @@ @article{DBLP:journals/corr/IosupKLVG22, - author = {Alexandru Iosup and - Fernando Kuipers and - Ana Lucia Varbanescu and - Paola Grosso and - Animesh Trivedi and - Jan S. Rellermeyer and - Lin Wang and - Alexandru Uta and - Francesco Regazzoni}, - title = {Future Computer Systems and Networking Research in the Netherlands: - {A} Manifesto}, - journal = {CoRR}, - volume = {abs/2206.03259}, - year = {2022}, - url = {https://doi.org/10.48550/arXiv.2206.03259}, - doi = {10.48550/ARXIV.2206.03259}, - eprinttype = {arXiv}, - eprint = {2206.03259}, - timestamp = {Mon, 05 Feb 2024 20:18:06 +0100}, - biburl = {https://dblp.org/rec/journals/corr/abs-2206-03259.bib}, - bibsource = {dblp computer science bibliography, https://dblp.org} + author = {Alexandru Iosup and Fernando Kuipers and Ana Lucia Varbanescu + and Paola Grosso and Animesh Trivedi and Jan S. Rellermeyer and + Lin Wang and Alexandru Uta and Francesco Regazzoni}, + title = {Future Computer Systems and Networking Research in the + Netherlands: {A} Manifesto}, + journal = {CoRR}, + volume = {abs/2206.03259}, + year = {2022}, + url = {https://doi.org/10.48550/arXiv.2206.03259}, + doi = {10.48550/ARXIV.2206.03259}, + eprinttype = {arXiv}, + eprint = {2206.03259}, + timestamp = {Mon, 05 Feb 2024 20:18:06 +0100}, + biburl = {https://dblp.org/rec/journals/corr/abs-2206-03259.bib}, + bibsource = {dblp computer science bibliography, https://dblp.org}, } @inproceedings{DBLP:conf/date/MilojicicFDR21, - author = {Dejan S. Milojicic and - Paolo Faraboschi and - Nicolas Dub{\'{e}} and - Duncan Roweth}, - title = {Future of {HPC:} Diversifying Heterogeneity}, - booktitle = {Design, Automation {\&} Test in Europe Conference {\&} Exhibition, - {DATE} 2021, Grenoble, France, February 1-5, 2021}, - pages = {276--281}, - publisher = {{IEEE}}, - year = {2021}, - url = {https://doi.org/10.23919/DATE51398.2021.9474063}, - doi = {10.23919/DATE51398.2021.9474063}, - timestamp = {Wed, 21 Jul 2021 10:05:23 +0200}, - biburl = {https://dblp.org/rec/conf/date/MilojicicFDR21.bib}, - bibsource = {dblp computer science bibliography, https://dblp.org} + author = {Dejan S. Milojicic and Paolo Faraboschi and Nicolas Dub{\'{e}} + and Duncan Roweth}, + title = {Future of {HPC:} Diversifying Heterogeneity}, + booktitle = {Design, Automation {\&} Test in Europe Conference {\&} + Exhibition, {DATE} 2021, Grenoble, France, February 1-5, + 2021}, + pages = {276--281}, + publisher = {{IEEE}}, + year = {2021}, + url = {https://doi.org/10.23919/DATE51398.2021.9474063}, + doi = {10.23919/DATE51398.2021.9474063}, + timestamp = {Wed, 21 Jul 2021 10:05:23 +0200}, + biburl = {https://dblp.org/rec/conf/date/MilojicicFDR21.bib}, + bibsource = {dblp computer science bibliography, https://dblp.org}, } @article{DBLP:journals/computer/AthavaleBBMMPS24, - author = {Jyotika Athavale and - Cullen E. Bash and - Wesley Brewer and - Matthias Maiterth and - Dejan S. Milojicic and - Harry Petty and + author = {Jyotika Athavale and Cullen E. Bash and Wesley Brewer and + Matthias Maiterth and Dejan S. Milojicic and Harry Petty and Soumyendu Sarkar}, - title = {Digital Twins for Data Centers}, - journal = {Computer}, - volume = {57}, - number = {10}, - pages = {151--158}, - year = {2024}, - url = {https://doi.org/10.1109/MC.2024.3436945}, - doi = {10.1109/MC.2024.3436945}, - timestamp = {Tue, 22 Oct 2024 21:09:19 +0200}, - biburl = {https://dblp.org/rec/journals/computer/AthavaleBBMMPS24.bib}, - bibsource = {dblp computer science bibliography, https://dblp.org} + title = {Digital Twins for Data Centers}, + journal = {Computer}, + volume = {57}, + number = {10}, + pages = {151--158}, + year = {2024}, + url = {https://doi.org/10.1109/MC.2024.3436945}, + doi = {10.1109/MC.2024.3436945}, + timestamp = {Tue, 22 Oct 2024 21:09:19 +0200}, + biburl = {https://dblp.org/rec/journals/computer/AthavaleBBMMPS24.bib}, + bibsource = {dblp computer science bibliography, https://dblp.org}, } @inproceedings{DBLP:conf/icppw/BourassaJBCJVS19, - author = {Norman Bourassa and - Walker Johnson and - Jeff Broughton and - Deirdre McShane Carter and - Sadie Joy and - Raphael Vitti and + author = {Norman Bourassa and Walker Johnson and Jeff Broughton and + Deirdre McShane Carter and Sadie Joy and Raphael Vitti and Peter Seto}, - title = {Operational Data Analytics: Optimizing the National Energy Research - Scientific Computing Center Cooling Systems}, - booktitle = {48th International Conference on Parallel Processing, {ICPP} 2019 - Workshop Proceedings, Kyoto, Japan, August 05-08, 2019}, - pages = {5:1--5:7}, - publisher = {{ACM}}, - year = {2019}, - url = {https://doi.org/10.1145/3339186.3339210}, - doi = {10.1145/3339186.3339210}, - timestamp = {Mon, 29 Jul 2019 12:39:30 +0200}, - biburl = {https://dblp.org/rec/conf/icppw/BourassaJBCJVS19.bib}, - bibsource = {dblp computer science bibliography, https://dblp.org} + title = {Operational Data Analytics: Optimizing the National Energy + Research Scientific Computing Center Cooling Systems}, + booktitle = {48th International Conference on Parallel Processing, {ICPP + } 2019 Workshop Proceedings, Kyoto, Japan, August 05-08, + 2019}, + pages = {5:1--5:7}, + publisher = {{ACM}}, + year = {2019}, + url = {https://doi.org/10.1145/3339186.3339210}, + doi = {10.1145/3339186.3339210}, + timestamp = {Mon, 29 Jul 2019 12:39:30 +0200}, + biburl = {https://dblp.org/rec/conf/icppw/BourassaJBCJVS19.bib}, + bibsource = {dblp computer science bibliography, https://dblp.org}, } @inproceedings{DBLP:conf/hpdc/NettiMGOTO020, - author = {Alessio Netti and - Micha M{\"{u}}ller and - Carla Guill{\'{e}}n and - Michael Ott and - Daniele Tafani and - Gence Ozer and - Martin Schulz}, - editor = {Manish Parashar and - Vladimir Vlassov and - David E. Irwin and + author = {Alessio Netti and Micha M{\"{u}}ller and Carla Guill{\'{e}}n + and Michael Ott and Daniele Tafani and Gence Ozer and Martin + Schulz}, + editor = {Manish Parashar and Vladimir Vlassov and David E. Irwin and Kathryn M. Mohror}, - title = {{DCDB} Wintermute: Enabling Online and Holistic Operational Data Analytics - on {HPC} Systems}, - booktitle = {{HPDC} '20: The 29th International Symposium on High-Performance Parallel - and Distributed Computing, Stockholm, Sweden, June 23-26, 2020}, - pages = {101--112}, - publisher = {{ACM}}, - year = {2020}, - url = {https://doi.org/10.1145/3369583.3392674}, - doi = {10.1145/3369583.3392674}, - timestamp = {Sun, 04 Aug 2024 19:37:21 +0200}, - biburl = {https://dblp.org/rec/conf/hpdc/NettiMGOTO020.bib}, - bibsource = {dblp computer science bibliography, https://dblp.org} + title = {{DCDB} Wintermute: Enabling Online and Holistic Operational + Data Analytics on {HPC} Systems}, + booktitle = {{HPDC} '20: The 29th International Symposium on + High-Performance Parallel and Distributed Computing, + Stockholm, Sweden, June 23-26, 2020}, + pages = {101--112}, + publisher = {{ACM}}, + year = {2020}, + url = {https://doi.org/10.1145/3369583.3392674}, + doi = {10.1145/3369583.3392674}, + timestamp = {Sun, 04 Aug 2024 19:37:21 +0200}, + biburl = {https://dblp.org/rec/conf/hpdc/NettiMGOTO020.bib}, + bibsource = {dblp computer science bibliography, https://dblp.org}, } @inproceedings{DBLP:conf/wosp/SumanCNTMI24, - author = {Shekhar Suman and - Xiaoyu Chu and - Dante Niewenhuis and - Sacheendra Talluri and - Tiziano De Matteis and - Alexandru Iosup}, - editor = {Simonetta Balsamo and - William J. Knottenbelt and - Cristina L. Abad and - Weiyi Shang}, - title = {Enabling Operational Data Analytics for Datacenters through Ontologies, - Monitoring, and Simulation-based Prediction}, - booktitle = {Companion of the 15th {ACM/SPEC} International Conference on Performance - Engineering, {ICPE} 2024, London, United Kingdom, May 7-11, 2024}, - pages = {120--126}, - publisher = {{ACM}}, - year = {2024}, - url = {https://doi.org/10.1145/3629527.3652897}, - doi = {10.1145/3629527.3652897}, - timestamp = {Fri, 17 May 2024 21:42:59 +0200}, - biburl = {https://dblp.org/rec/conf/wosp/SumanCNTMI24.bib}, - bibsource = {dblp computer science bibliography, https://dblp.org} + author = {Shekhar Suman and Xiaoyu Chu and Dante Niewenhuis and + Sacheendra Talluri and Tiziano De Matteis and Alexandru Iosup}, + editor = {Simonetta Balsamo and William J. Knottenbelt and Cristina L. + Abad and Weiyi Shang}, + title = {Enabling Operational Data Analytics for Datacenters through + Ontologies, Monitoring, and Simulation-based Prediction}, + booktitle = {Companion of the 15th {ACM/SPEC} International Conference + on Performance Engineering, {ICPE} 2024, London, United + Kingdom, May 7-11, 2024}, + pages = {120--126}, + publisher = {{ACM}}, + year = {2024}, + url = {https://doi.org/10.1145/3629527.3652897}, + doi = {10.1145/3629527.3652897}, + timestamp = {Fri, 17 May 2024 21:42:59 +0200}, + biburl = {https://dblp.org/rec/conf/wosp/SumanCNTMI24.bib}, + bibsource = {dblp computer science bibliography, https://dblp.org}, } -@book{DBLP:books/daglib/Brooks0080747, - author = {Frederick P. Brooks Jr.}, - title = {The mythical man-month - essays on software engineering {(2.} ed.)}, - publisher = {Addison-Wesley}, - year = {1995}, - isbn = {978-0-201-83595-3}, - timestamp = {Wed, 27 Apr 2011 17:30:30 +0200}, - biburl = {https://dblp.org/rec/books/daglib/0080747.bib}, - bibsource = {dblp computer science bibliography, https://dblp.org} +@book{DBLP:books/worldcat/Kafka2021, + edition = {2nd edition.}, + title = {Kafka: {The} {Definitive} {Guide}, 2nd {Edition}}, + isbn = {9781492043065}, + shorttitle = {Kafka}, + language = {eng}, + publisher = {O'Reilly Media, Inc.}, + author = {Shapira, Gwen and Palino, Todd and Sivaram, Rajini and + Narkhede, Neha and {Safari, an O'Reilly Media Company.}}, + year = {2021}, + note = {OCLC: 1355686050}, +} + +@inproceedings{DBLP:conf/sc/BrewerMKWBHSGGW24, + author = {Wesley Brewer and Matthias Maiterth and Vineet Kumar and Rafal + P. Wojda and Sedrick Bouknight and Jesse Hines and Woong Shin + and Scott Greenwood and David Grant and Wesley Williams and + Feiyi Wang}, + title = {A Digital Twin Framework for Liquid-cooled Supercomputers as + Demonstrated at Exascale}, + booktitle = {Proceedings of the International Conference for High + Performance Computing, Networking, Storage, and Analysis, { + SC} 2024, Atlanta, GA, USA, November 17-22, 2024}, + pages = {23}, + publisher = {{IEEE}}, + year = {2024}, + url = {https://dl.acm.org/doi/10.1109/SC41406.2024.00029}, + doi = {10.1109/SC41406.2024.00029}, + timestamp = {Thu, 19 Dec 2024 09:58:08 +0100}, + biburl = {https://dblp.org/rec/conf/sc/BrewerMKWBHSGGW24.bib}, + bibsource = {dblp computer science bibliography, https://dblp.org}, +} + +@misc{Wikipedia:PredictiveModelling, + author = "{Wikipedia contributors}", + title = "Predictive modelling --- {Wikipedia}{,} The Free Encyclopedia", + year = "2026", + url = "https://en.wikipedia.org/w/index.php?title=Predictive_modelling\& + oldid=1334478640", + note = "[Online; accessed 27-February-2026]", +} + +@misc{DBLP:report/Flexera2026, + title = "State of the Cloud, Insights from cloud leaders", + url = "https://info.flexera.com/CM-REPORT-State-of-the-Cloud", + journal = {2026 State of the Cloud | Insights from cloud leaders \& + practitioners}, + publisher = {Flexera, formerly Acresso Software (2008-2009)}, + year = {2026}, + month = {Mar}, +} + +@inproceedings{DBLP:conf/acsos/TalluriOVTI21, + author = {Sacheendra Talluri and Leon Overweel and Laurens Versluis and + Animesh Trivedi and Alexandru Iosup}, + editor = {Esam El{-}Araby and Vana Kalogeraki and Danilo Pianini and Fr{ + \'{e}}d{\'{e}}ric Lassabe and Barry Porter and Sona Ghahremani + and Ingrid Nunes and Mohamed Bakhouya and Sven Tomforde}, + title = {Empirical Characterization of User Reports about Cloud Failures + }, + booktitle = {{IEEE} International Conference on Autonomic Computing and + Self-Organizing Systems, {ACSOS} 2021, Washington, DC, USA, + September 27 - Oct. 1, 2021}, + pages = {158--163}, + publisher = {{IEEE}}, + year = {2021}, + url = {https://doi.org/10.1109/ACSOS52086.2021.00039}, + doi = {10.1109/ACSOS52086.2021.00039}, + timestamp = {Sun, 04 Aug 2024 19:43:01 +0200}, + biburl = {https://dblp.org/rec/conf/acsos/TalluriOVTI21.bib}, + bibsource = {dblp computer science bibliography, https://dblp.org}, +} + +@misc{DBLP:report/AnnualOutageAnalysis2025, + title = {Executive summary: Annual outage analysis 2025}, + url = { + https://uptimeinstitute.com/resources/research-and-reports/annual-outage-analysis-2025 + }, + journal = {Uptime Institute}, + publisher = {https://uptimeinstitute.com/}, + author = {Donnellan, Douglas and Lawrence, Andy and Weinshenk, Rose}, + year = {2025}, + month = {May}, +} + +@article{DBLP:conf/cirp/TAO2018169, + title = {Digital twin driven prognostics and health management for + complex equipment}, + journal = {CIRP Annals}, + volume = {67}, + number = {1}, + pages = {169-172}, + year = {2018}, + issn = {0007-8506}, + doi = {https://doi.org/10.1016/j.cirp.2018.04.055}, + url = { + https://www.sciencedirect.com/science/article/pii/S0007850618300799 + }, + author = {Fei Tao and Meng Zhang and Yushan Liu and A.Y.C. Nee}, + keywords = {Maintenance, Condition monitoring, Digital twin}, +} + +@inproceedings{DBLP:conf/AIAA/Teugel2012, + author = {Tuegel, Eric}, + year = {2012}, + month = {04}, + pages = {}, + title = {The Airframe Digital Twin: Some Challenges to Realization}, + isbn = {978-1-60086-937-2}, + journal = {Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC + Structures, Structural Dynamics and Materials Conference}, + doi = {10.2514/6.2012-1812}, } @@ -1,5 +1,4 @@ \documentclass[twoside,11pt]{style/class/PhDthesisPSnPDF} - \input{style/style.tex} \input{appendix/glossary.tex} @@ -15,10 +14,7 @@ \listoffigures \listoftables \mainmatter -% Uncomment to print `Chapter 1` instead of just `1` -\renewcommand{\chaptername}{} -% test comment \input{content/intro} \input{content/background} \input{content/overview} diff --git a/sources/figure1.svg b/sources/figure1.svg new file mode 100644 index 0000000..d49b96d --- /dev/null +++ b/sources/figure1.svg @@ -0,0 +1,306 @@ +<?xml version="1.0" 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subfigure,tocbibind, vmargin, watermark, graphicx} +\usepackage{xspace, xcolor, lipsum, booktabs, caption, fancyhdr, footmisc, natbib, nomencl, rotating, setspace, subfigure,tocbibind, vmargin, watermark, graphicx, enumitem, pifont} -\hypersetup { - hidelinks=true, +\hypersetup { + hidelinks=true, } - \usepackage[acronym, toc]{glossaries} \textwidth 15cm \textheight 22cm -\parindent 10pt +\parindent 10pt \parskip 0pt \oddsidemargin 2.5cm \evensidemargin 2.5cm @@ -18,3 +17,7 @@ \newcommand{\etc}{etc.\xspace} \newcommand{\etal}{\emph{et~al.}\xspace} \newcommand{\todo}[1]{\textcolor{blue}{#1}} +\newcommand{\one}{(\ding{182})\xspace} +\newcommand{\two}{(\ding{183})\xspace} +\newcommand{\three}{(\ding{184})\xspace} +\newcommand{\four}{(\ding{185})\xspace} |
