Are you planning to utilize mermaid for this? There are a number of flow diagrams in lib-jobs if you need examples: https://github.com/pulibrary/lib_jobs/tree/main/docs/alma_people
closed
by Kevin Reiss at 2022-07-08 17:32:37.ready_for_review
by None at 2022-07-08 14:46:54.referenced
by Kevin Reiss at 2022-07-08 17:32:37.merged
by Kevin Reiss at 2022-07-08 17:32:37.closed
by Kevin Reiss at 2022-07-08 17:32:37.head_ref_deleted
by Kevin Reiss at 2022-07-08 17:32:38.I generated this error when I clicked on "Requests to Review" https://approvals-staging.princeton.edu/my_approval_requests/ when I had activated myself as delegate for someone with the admin assistant role.
From Faith/Lynn via Slack:
Affected Collections: MSS: C0140 Component-level record/archival object examples: https://aspace.princeton.edu/staff/resources/3950/edit#tree::archival_object_1461736 https://aspace.princeton.edu/staff/resources/3950/edit#tree::archival_object_1072888 UA: AC214 https://aspace.princeton.edu/staff/resources/2168#tree::archival_object_743892 AC364 https://aspace.princeton.edu/staff/resources/2214#tree::archival_object_770606
ASpace to MARC crosswalk (includes all possible ASpace fields utilized for these records)
ASpace MARC Archival object URI?? 035 Dates/Expression 046 Language 041 RefID (collection code?)/ Archival object URI?? 099 Agent/Creator/Persname or Famname 100 Agent/Creator/Corpname 110 Title 245 Extents 300 Conditions Governing Access (can this be pulled from the collection-level note if there is none at the component level?) 506 Scope and contents 520 Immediate Source of Acquisition 541 Agents/Biographical/Historical note 545 Processing Information 583 Agent/Subject 600 Subjects 610 Subjects 611 Subjects 650 Subjects 651 Subjects 655 Agent/Creator 700 URL ?? + RefID (ex: https://findingaids.princeton.edu/catalog/C0140_c25673-42817) 856 Physical Location (can this be pulled from the collection-level note?) 982
renamed
by None at 2022-07-08 12:49:47.This was resolved yesterday. During the deployment I had to delete a queue I manually created, then cancel the deployment and rerun it.
closed
by Christina Chortaria at 2022-07-08 12:05:50.head_ref_force_pushed
by Christina Chortaria at 2022-07-07 22:09:36.head_ref_force_pushed
by Christina Chortaria at 2022-07-07 22:16:15.head_ref_force_pushed
by Christina Chortaria at 2022-07-08 11:58:41.deployed
by None at 2022-07-08 12:00:52.ready_for_review
by Christina Chortaria at 2022-07-08 12:02:56.referenced
by Christina Chortaria at 2022-07-08 12:14:37.merged
by Christina Chortaria at 2022-07-08 12:14:37.closed
by Christina Chortaria at 2022-07-08 12:14:38.head_ref_deleted
by Christina Chortaria at 2022-07-08 12:14:39.@dependabot rebase
mentioned
by Dependabot at 2022-07-08 12:34:50.head_ref_force_pushed
by None at 2022-07-08 12:35:29.deployed
by None at 2022-07-08 12:40:43.referenced
by Christina Chortaria at 2022-07-08 12:45:55.merged
by Christina Chortaria at 2022-07-08 12:45:55.closed
by Christina Chortaria at 2022-07-08 12:45:55.head_ref_deleted
by Christina Chortaria at 2022-07-08 12:45:56.labeled
by Christina Chortaria at 2022-07-08 12:51:55.referenced
by Christina Chortaria at 2022-07-08 13:01:31.merged
by Christina Chortaria at 2022-07-08 13:01:31.closed
by Christina Chortaria at 2022-07-08 13:01:31.head_ref_deleted
by Christina Chortaria at 2022-07-08 13:01:32.assigned
by Christina Chortaria at 2022-07-08 12:52:36.closed
by Christina Chortaria at 2022-07-08 13:08:50.referenced
by Christina Chortaria at 2022-07-08 13:08:50.merged
by Christina Chortaria at 2022-07-08 13:08:50.closed
by Christina Chortaria at 2022-07-08 13:08:50.head_ref_deleted
by Christina Chortaria at 2022-07-08 13:08:51.closed
by Christina Chortaria at 2022-07-08 12:14:38.reopened
by Christina Chortaria at 2022-07-08 14:31:35.renamed
by Christina Chortaria at 2022-07-08 14:28:44.head_ref_force_pushed
by Christina Chortaria at 2022-07-08 14:45:00.referenced
by Kevin Reiss at 2022-07-08 15:25:23.merged
by Kevin Reiss at 2022-07-08 15:25:23.closed
by Kevin Reiss at 2022-07-08 15:25:23.head_ref_deleted
by Kevin Reiss at 2022-07-08 15:25:23.closed
by Christina Chortaria at 2022-07-08 16:08:44.closed
by Christina Chortaria at 2022-07-08 16:08:56.Not using
closed
by Max Kadel at 2022-07-08 16:09:30.renamed
by Jane Sandberg at 2022-07-07 22:00:22.referenced
by Christina Chortaria at 2022-07-08 14:58:50.merged
by Christina Chortaria at 2022-07-08 14:58:50.closed
by Christina Chortaria at 2022-07-08 14:58:51.head_ref_deleted
by Christina Chortaria at 2022-07-08 14:58:51.deployed
by None at 2022-07-08 15:10:40.referenced
by Kevin Reiss at 2022-07-08 21:54:59.merged
by Kevin Reiss at 2022-07-08 21:54:59.closed
by Kevin Reiss at 2022-07-08 21:54:59.head_ref_deleted
by Kevin Reiss at 2022-07-08 21:55:00.labeled
by Kim Leaman at 2022-07-08 15:10:59.mentioned
by Shaun Ellis at 2022-07-08 15:10:59.subscribed
by Shaun Ellis at 2022-07-08 15:10:59.mentioned
by None at 2022-07-08 15:10:59.subscribed
by None at 2022-07-08 15:10:59.mentioned
by Kim Leaman at 2022-07-08 15:11:00.subscribed
by Kim Leaman at 2022-07-08 15:11:00.The problem is because the titles in the embargo spreadsheet do not match the titles from ThesisCentral.
For example:
title1 = "Breaking the Species Barrier_ Investigating the Host Proteins Involved in Human and Murine Hepatitis - Mansi Totwani.xml"
title2 = "Breaking the Species Barrier: Investigating the Host Proteins Involved in Human and Murine Hepatitis B Infection"
We have to compare titles because a given netid might have more than one thesis, so when applying an embargo we have to match on both netid and thesis title. We are already normalizing the titles for punctuation and capitalization and comparing the Levenshtein distance. I'm now also going to truncate the title at 50 characters. Hopefully that should be enough to solve the problem while still detecting places where it should NOT apply an embargo.
Before this fix, the 2022 molecular biology theses had five embargoed items:
bess@dali ~/projects/senior_theses/2022/output/molecular_biology grep -r "embargo" *
submission_10889/metadata_pu.xml: <dcvalue element="embargo" qualifier="terms">2024-07-01</dcvalue>
submission_10944/metadata_pu.xml: <dcvalue element="embargo" qualifier="terms">2024-07-01</dcvalue>
submission_11267/metadata_pu.xml: <dcvalue element="embargo" qualifier="terms">2024-07-01</dcvalue>
submission_11324/metadata_pu.xml: <dcvalue element="embargo" qualifier="terms">2024-07-01</dcvalue>
submission_11701/metadata_pu.xml: <dcvalue element="embargo" qualifier="terms">2024-07-01</dcvalue>
After the fix there are eight, which is the expected number:
bess@dali ~/projects/senior_theses/2022/output/molecular_biology cd ~/projects/senior_theses/debugging/output/
bess@dali ~/projects/senior_theses/debugging/output grep -r "embargo" *
submission_10889/metadata_pu.xml: <dcvalue element="embargo" qualifier="terms">2024-07-01</dcvalue>
submission_10944/metadata_pu.xml: <dcvalue element="embargo" qualifier="terms">2024-07-01</dcvalue>
submission_11267/metadata_pu.xml: <dcvalue element="embargo" qualifier="terms">2024-07-01</dcvalue>
submission_11324/metadata_pu.xml: <dcvalue element="embargo" qualifier="terms">2024-07-01</dcvalue>
submission_11635/metadata_pu.xml: <dcvalue element="embargo" qualifier="terms">2024-07-01</dcvalue>
submission_11682/metadata_pu.xml: <dcvalue element="embargo" qualifier="terms">2024-07-01</dcvalue>
submission_11701/metadata_pu.xml: <dcvalue element="embargo" qualifier="terms">2024-07-01</dcvalue>
submission_12201/metadata_pu.xml: <dcvalue element="embargo" qualifier="terms">2024-07-01</dcvalue>
referenced
by Hector Correa at 2022-07-08 16:09:45.merged
by Hector Correa at 2022-07-08 16:09:48.closed
by Hector Correa at 2022-07-08 16:09:48.head_ref_deleted
by Hector Correa at 2022-07-08 16:09:48.deployed
by None at 2022-07-08 12:54:01.ready_for_review
by None at 2022-07-08 15:31:27.referenced
by None at 2022-07-08 15:32:03.merged
by None at 2022-07-08 15:32:03.closed
by None at 2022-07-08 15:32:03.head_ref_deleted
by None at 2022-07-08 15:32:04.labeled
by None at 2022-07-08 16:37:32.labeled
by None at 2022-07-08 16:37:37.@kelea99 it's working, it's just that there are two vocabularies called LAE Ephemera in staging and one was empty. Attaching the other one revealed that the functionality is the same as on an edit page.
Fantastic!! thank you.
assigned
by None at 2022-07-08 16:42:53.labeled
by None at 2022-07-08 16:42:58.closed
by None at 2022-07-08 16:45:46.mentioned
by Kim Leaman at 2022-07-08 16:45:46.subscribed
by Kim Leaman at 2022-07-08 16:45:46.assigned
by None at 2022-07-08 16:31:26.labeled
by None at 2022-07-08 16:31:34.referenced
by None at 2022-07-08 16:32:36.unassigned
by None at 2022-07-08 17:19:26.autoloading errors in test run and tests then time out:
DEPRECATION WARNING: Initialization autoloaded the constants ActiveStorage::BaseJob, ActiveStorage::AnalyzeJob, Riiif::AbstractFileSystemResolver, Riiif::FileSystemFileResolver, Riiif::NilAuthorizationService, Riiif::Image, RiiifResolver, Blacklight::ConfigurationHelperBehavior, Blacklight::ComponentHelperBehavior, Blacklight::Facet, Blacklight::FacetsHelperBehavior, Blacklight::RenderConstraintsHelperBehavior, Blacklight::RenderPartialsHelperBehavior, Blacklight::SearchHistoryConstraintsHelperBehavior, Blacklight::SuggestHelperBehavior, Blacklight::CatalogHelperBehavior, Blacklight::UrlHelperBehavior, Blacklight::HashAsHiddenFieldsHelperBehavior, Blacklight::LayoutHelperBehavior, Blacklight::IconHelperBehavior, Blacklight::BlacklightHelperBehavior, Hydra::BlacklightHelperBehavior, and BlacklightHelper.
Being able to do this is deprecated. Autoloading during initialization is going
to be an error condition in future versions of Rails.
Reloading does not reboot the application, and therefore code executed during
initialization does not run again. So, if you reload ActiveStorage::BaseJob, for example,
the expected changes won't be reflected in that stale Class object.
`config.autoloader` is set to `classic`. These autoloaded constants would have been unloaded if `config.autoloader` had been set to `:zeitwerk`.
Please, check the "Autoloading and Reloading Constants" guide for solutions.
I looked at some of those deprecations yesterday - all the Blacklight ones are fixed by updating Blacklight, the Riiif/ActiveStorage ones are fixed by adjusting initializers that reference those to use Rails.application.config.to_prepare do
@hackartisan Can you screen shot what you mean by tight at the top?
Uh, weird, I don't think that's how it looks to me.
@tpendragon It looks like the issue is that it opens up already scrolled to the bottom. can you replicate that on this object? https://figgy-staging.princeton.edu/concern/ephemera_folders/040473cf-c141-4be9-b7f6-58ffd947df59/edit
Yup, weird, doesn't seem to be the case for new items.
deployed
by None at 2022-07-08 18:03:52.mentioned
by None at 2022-07-08 19:04:26.subscribed
by None at 2022-07-08 19:04:26.deployed
by None at 2022-07-08 19:23:36.mentioned
by Trey Pendragon at 2022-07-08 19:56:09.subscribed
by Trey Pendragon at 2022-07-08 19:56:09.labeled
by Eliot Jordan at 2022-07-08 20:48:49.assigned
by Eliot Jordan at 2022-07-08 20:48:49.renamed
by Eliot Jordan at 2022-07-08 20:56:43.head_ref_force_pushed
by Eliot Jordan at 2022-07-08 21:17:26.unassigned
by Nikitas Tampakis at 2022-07-08 15:52:53.unassigned
by Esmé Cowles at 2022-07-08 15:52:59.we can make the changes
Steps to finish this 1. See if any barcode are actually logging into the system. Look at BL users table. 2. If so , is it possible to migrate the old account with the new account. We want to look the account that Joan has set up through a report and compare it with the accounts in the database. If they have used catalog features like bookmarks or searches(if it's still there) then migrate them to the new alma login.
talk to @pmgreen @mzelesky and request an analytics report with the alma user accounts that they've been created since we started the new program.
@christinach since what date?
mentioned
by Peter Green at 2022-07-08 16:16:35.subscribed
by Peter Green at 2022-07-08 16:16:35.mentioned
by None at 2022-07-08 16:16:35.subscribed
by None at 2022-07-08 16:16:35.mentioned
by Christina Chortaria at 2022-07-08 16:25:50.subscribed
by Christina Chortaria at 2022-07-08 16:25:50.We will sunset this system. We dont need to work on this issue.
closed
by Christina Chortaria at 2022-07-08 16:27:14.I am progressing with this, however, I am now finding the following error:
closed
by Hector Correa at 2022-07-08 16:12:41.referenced
by Hector Correa at 2022-07-08 16:12:41.merged
by Hector Correa at 2022-07-08 16:12:41.closed
by Hector Correa at 2022-07-08 16:12:41.head_ref_deleted
by Hector Correa at 2022-07-08 16:12:42.closed
by Hector Correa at 2022-07-08 16:18:29.referenced
by Hector Correa at 2022-07-08 16:18:28.merged
by Hector Correa at 2022-07-08 16:18:28.closed
by Hector Correa at 2022-07-08 16:18:29.head_ref_deleted
by Hector Correa at 2022-07-08 16:18:30.Should we write an upgrade to the gem we are utilizing to include 4.4 schema? https://github.com/sul-dlss/datacite-ruby#validation
There is no JSON schema for 4.4, 4.3 is the latest update: https://github.com/datacite/schema/blob/master/source/json/kernel-4.3/datacite_4.3_schema.json. I wonder if we need to not utilize the ruby Gem.
@hhkitsune do we want to rename the column curator (to moderator) in the dashboard (the text with #2
) as well or only the role at the top? I am thinking just the role at the top since we do want to designate a curator for the dataset, right?
mentioned
by Hannah H at 2022-07-08 19:17:02.subscribed
by Hannah H at 2022-07-08 19:17:02.head_ref_force_pushed
by None at 2022-07-08 12:04:59.deployed
by None at 2022-07-08 12:05:42.head_ref_force_pushed
by None at 2022-07-08 12:14:44.deployed
by None at 2022-07-08 12:14:56.head_ref_force_pushed
by None at 2022-07-08 12:19:23.deployed
by None at 2022-07-08 12:19:39.head_ref_force_pushed
by None at 2022-07-08 12:22:56.deployed
by None at 2022-07-08 12:23:48.deployed
by None at 2022-07-08 12:39:36.Closed in favor of shakapacker
closed
by Bess Sadler at 2022-07-08 13:20:06.head_ref_deleted
by Bess Sadler at 2022-07-08 13:20:12.ready_for_review
by None at 2022-07-08 12:38:35.mentioned
by Trey Pendragon at 2022-07-08 20:19:35.subscribed
by Trey Pendragon at 2022-07-08 20:19:35.labeled
by None at 2022-07-08 20:21:09.Final draft - https://docs.google.com/presentation/d/1ojdbCvc4fkK87ah4xTVp5cVYo_TAneok/edit#slide=id.p1
closed
by Kate Lynch at 2022-07-08 14:30:40.


Runs a batch command (or series of commands) of your choice to install the tool.
Jenkins variable substitution, e.g. ${JAVA_HOME}
is performed on the command text before it is run.
Note: If no variable substitution is required then the Jenkins-core functionality can/should be used instead.


... but we can do better than that.
Enhanced static content allows for us to interact with elements on the page without going elsewhere.


SwizDAO
Built an AS3 Project to Work with GenericDAO using Swiz and AS3Signals The project was inspired by Java Spring Framework: IBM Generic Dao The project uses the benefits of DI provided by Swiz 1.0. The Deferred Instantiation of Swiz builds DAO Object only when [Inject] keyword is used. Also, uses the latest Spark SkinnableComponent Framework for the View Part with passive view..
ActionScript
4
1


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Pong
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Staghorn's Sillouette (call name: Shade)
(Ch. Staghorn's Jimmy Hollywood X GCH. Staghorn's Reflection in Black)
Our Miss Shade, proudly co-bred with my dear friend Chantelle Bennett of Benacres Labradors, is a lovely addition to our line up. Best Baby Puppy in Specialty Shows at both the LOC and the Quebec specialties in 2016 and also champion pointed, she has matured into a lovely bitch with a great head and coat, good angels and ample leg under her. I'm very pleased with this girl.
D.O.B. January 17, 2016
PRA and EIC Clear by Parentage
OFA Hips and Elbows pending, Cerf Clear


If you’re building something in backend using Node.js, There’s a good chance that you’re using express.js. Express.js is most popular http framework know for being fast, unopinionated, and feature complete library.
One thing developers need to handle properly when using express with process managers like pm2, forever etc, when these process managers send shutdown signal, we need to do graceful shutdown of out nodejs or express app to avoid side effects. like finishing active requests before closing server, clean up resources, db connections etc.
In this tutorial, we will learn how to properly handle Shutdown in node.js or expres.js based shutdown signals like SIGTERM.
Node.js or Express.js graceful shutdown
const express = require("express"); const expressServerApp = express(); const port = 3000; expressServerApp.get("/", (req, res) => { res.send("Hello World!"); }); expressServerApp.listen(port, () => { console.log(`Awesome app listening at http://localhost:${port}`); }); function handleShutdownGracefully() { console.info("closing server gracefully..."); expressServerApp.close(() => { console.info("server closed."); // close db connections here or // any other clean if required process.exit(0); // if required }); } process.on("SIGINT", handleShutdownGracefully); process.on("SIGTERM", handleShutdownGracefully); process.on("SIGHUP", handleShutdownGracefully); // official link: https://expressjs.com/en/advanced/healthcheck-graceful-shutdown.html
So now we can gracefully shutdown express server, after cleaning up resources, closing all file locks and finishing all active requests, we can also use same for any Node.js app to gracefully shutdown.


q1
transport
or transportation is the movement of people, animals and goods from one location to another. Modes of
q2
tranport inc.
air, rail, road, water, cable, pipeline, and space.


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Preparation time
less than 30 mins
Cooking time
10 to 30 mins
Serves
Serves 4
Dietary
Soak four to eight wooden skewers in a bowl of water for 10 minutes, then shake off any excess moisture and set aside.
Thickly slice each aubergine half into half moons. Meanwhile, place the aubergine slices into a large bowl, sprinkle over the salt and drizzle over the oil. Mix well until all of the slices are coated evenly in the oil and salt. Set aside for 20 minutes.
When the aubergines have stood for 20 minutes, heat a chargrill pan over a high heat.
When the pan is hot, add the aubergine slices, in batches, and griddle for two minutes on each side, or until golden-brown griddle marks appear on both sides. Remove the aubergine slices from the pan and set aside until cool enough to handle.
Repeat the process with the remaining slices of aubergine.
Thread the chargrilled aubergine slices onto the soaked wooden skewers, arranging each half moon at a different angle to the one below it to create a spiral. Set aside.
For the satay sauce, heat 80ml/2¾fl oz of the oil in a wok over a high heat. Add the peanuts and stir-fry for 2-3 minutes, or until golden-brown.
Transfer the fried peanuts to a food processor and blend to a smooth paste.
Heat the remaining oil in a frying pan over a medium heat. Add the shallots and garlic and fry for 1-2 minutes, or until softened.
Add the chilli powder, brown sugar, soy sauce and water, stir well and bring the mixture to the boil.
Add the peanut paste and chopped red chilli and stir well to combine. Bring the mixture to a simmer, then continue to simmer for 8-10 minutes, or until thickened. Stir in the lemon juice and salt.
To serve, arrange the aubergine skewers in four tall glasses or onto four serving plates. Serve the satay sauce in dipping bowls alongside.


| Package | Description |
|---|---|
| org.apache.log4j |
The main log4j package.
|
| org.apache.log4j.helpers |
This package is used internally.
|
| org.apache.log4j.jdbc |
The JDBCAppender provides for sending log events to a database.
|
| org.apache.log4j.jmx |
This package lets you manage log4j settings using JMX.
|
| org.apache.log4j.lf5 | |
| org.apache.log4j.net |
Package for remote logging.
|
| org.apache.log4j.nt |
Package for NT event logging.
|
| org.apache.log4j.or |
ObjectRenders are resposible for rendering messages depending on
their class type.
|
| org.apache.log4j.pattern |
Provides classes implementing format specifiers in conversion patterns.
|
| org.apache.log4j.rewrite | |
| org.apache.log4j.spi |
Contains part of the System Programming Interface (SPI) needed to
extend log4j.
|
| org.apache.log4j.varia |
Contains various appenders, filters and other odds and ends.
|
| org.apache.log4j.xml |
XML based components.
|
| Class and Description |
|---|
| AppenderAttachable
Interface for attaching appenders to objects.
|
| Configurator
Implemented by classes capable of configuring log4j using a URL.
|
| ErrorHandler
Appenders may delegate their error handling to
ErrorHandlers . |
| Filter
Users should extend this class to implement customized logging
event filtering.
|
| HierarchyEventListener
Listen to events occuring within a
Hierarchy . |
| LoggerFactory
Implement this interface to create new instances of Logger or
a sub-class of Logger.
|
| LoggerRepository
A
LoggerRepository is used to create and retrieve
Loggers . |
| LoggingEvent
The internal representation of logging events.
|
| OptionHandler
A string based interface to configure package components.
|
| RendererSupport |
| RepositorySelector
The
LogManager uses one (and only one)
RepositorySelector implementation to select the
LoggerRepository for a particular application context. |
| ThrowableRenderer
Implemented by classes that render instances of
java.lang.Throwable (exceptions and errors)
into a string representation.
|
| ThrowableRendererSupport
Implemented by logger repositories that support configurable
rendering of Throwables.
|
| Class and Description |
|---|
| AppenderAttachable
Interface for attaching appenders to objects.
|
| ErrorHandler
Appenders may delegate their error handling to
ErrorHandlers . |
| LoggerRepository
A
LoggerRepository is used to create and retrieve
Loggers . |
| LoggingEvent
The internal representation of logging events.
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| OptionHandler
A string based interface to configure package components.
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| Class and Description |
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| LoggingEvent
The internal representation of logging events.
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| OptionHandler
A string based interface to configure package components.
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| Class and Description |
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| HierarchyEventListener
Listen to events occuring within a
Hierarchy . |
| Class and Description |
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| Configurator
Implemented by classes capable of configuring log4j using a URL.
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| LoggerRepository
A
LoggerRepository is used to create and retrieve
Loggers . |
| LoggingEvent
The internal representation of logging events.
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| OptionHandler
A string based interface to configure package components.
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| ThrowableInformation
ThrowableInformation is log4j's internal representation of
throwables.
|
| Class and Description |
|---|
| LoggerRepository
A
LoggerRepository is used to create and retrieve
Loggers . |
| LoggingEvent
The internal representation of logging events.
|
| OptionHandler
A string based interface to configure package components.
|
| TriggeringEventEvaluator
Implementions of this interface allow certain appenders to decide
when to perform an appender specific action.
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| Class and Description |
|---|
| LoggingEvent
The internal representation of logging events.
|
| OptionHandler
A string based interface to configure package components.
|
| Class and Description |
|---|
| RendererSupport |
| Class and Description |
|---|
| LocationInfo
The internal representation of caller location information.
|
| LoggingEvent
The internal representation of logging events.
|
| ThrowableInformation
ThrowableInformation is log4j's internal representation of
throwables.
|
| Class and Description |
|---|
| AppenderAttachable
Interface for attaching appenders to objects.
|
| LoggingEvent
The internal representation of logging events.
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| OptionHandler
A string based interface to configure package components.
|
| Class and Description |
|---|
| AppenderAttachable
Interface for attaching appenders to objects.
|
| Filter
Users should extend this class to implement customized logging
event filtering.
|
| HierarchyEventListener
Listen to events occuring within a
Hierarchy . |
| LocationInfo
The internal representation of caller location information.
|
| LoggerFactory
Implement this interface to create new instances of Logger or
a sub-class of Logger.
|
| LoggerRepository
A
LoggerRepository is used to create and retrieve
Loggers . |
| LoggingEvent
The internal representation of logging events.
|
| NOPLoggerRepository
No-operation implementation of LoggerRepository which is used when
LogManager.repositorySelector is erroneously nulled during class reloading.
|
| OptionHandler
A string based interface to configure package components.
|
| RepositorySelector
The
LogManager uses one (and only one)
RepositorySelector implementation to select the
LoggerRepository for a particular application context. |
| ThrowableInformation
ThrowableInformation is log4j's internal representation of
throwables.
|
| ThrowableRenderer
Implemented by classes that render instances of
java.lang.Throwable (exceptions and errors)
into a string representation.
|
| Class and Description |
|---|
| Configurator
Implemented by classes capable of configuring log4j using a URL.
|
| ErrorHandler
Appenders may delegate their error handling to
ErrorHandlers . |
| Filter
Users should extend this class to implement customized logging
event filtering.
|
| LoggerRepository
A
LoggerRepository is used to create and retrieve
Loggers . |
| LoggingEvent
The internal representation of logging events.
|
| OptionHandler
A string based interface to configure package components.
|
| Class and Description |
|---|
| Configurator
Implemented by classes capable of configuring log4j using a URL.
|
| LoggerFactory
Implement this interface to create new instances of Logger or
a sub-class of Logger.
|
| LoggerRepository
A
LoggerRepository is used to create and retrieve
Loggers . |
| LoggingEvent
The internal representation of logging events.
|
| OptionHandler
A string based interface to configure package components.
|
| ThrowableRenderer
Implemented by classes that render instances of
java.lang.Throwable (exceptions and errors)
into a string representation.
|
Copyright © 1999-2016 Apache Software Foundation. All Rights Reserved.


WILD MAN BLUES (director: Barbara Kopple; cinematographer: Tom Hurwitz; cast: Woody Allen, Soon-Yi Previn, Dan Barrett, Simon Wettenhall, John Gill, Cynthia Sayer, Greg Cohen, Eddy Davis, Letty Aronson, 1998)
Barbara Kopple was asked by Woody to do a cinema verite documentary on his 18 city European New Orleans Jazz tour he will be on with his demonized girlfriend and soon to be wife, Soon-Yi Previn, promising to let her do her thing without any interference from him. It is a most relaxed and enjoyable look at the neurotic comic, who appears to be no different than he is in his films. But what is vividly shown, is how exhilerated he gets from playing the clarinet and how wonderfully morbid he is about everything he does, from eating a vulcanized Spanish omelet in Spain to getting seasick on a gondola in Venice. Woody's trek from one luxury hotel to another let's us hear the comedian's constant wisecracks and tune into his idiosyncrasies: when sending out his laundry in Milan, he says, "I hope it doesn't come back breaded." He looks into the unintrusive camera and tells us that he always must have his own bathroom when travelling, this way he can have room for all his ointments to help him look good.
He seems to be acting natural as he interacts with his sister Letty Aronson and the ever motherly Soon-Yi, as she relates to the aging comic's foibles and crankiness and need to be treated with kid gloves, by voicing her opinion on what he should do, which he either ignores or childishly follows or comes up with a good one liner for. You can't help but realize that this is really Woody, it is not a put on, and you either love him or shy away from him. The relationship between the couple is what the film turns out to be mainly about, and since he lays it out there for everyone to see what they are all about, there is no need to look for gossip columns to know more about the star and the tabloid headline relationship he has with his step-daughter and now lover. There seems to be nothing seedy going on between them, except a relationship based on need and affection, though there relationship does not appear to be fraught with overt sexuality.
Where he is at his height of ecstasy, we see him playing the clarinet with the band, as his head bobs up and down and he keeps time with the music by tapping his feet. Some of the snippets from the numbers he played included the joyous songs like "Down by the Riverside" and "Home Sweet Home." If there is any criticism for the film, it could be noted that we didn't hear enough of the band playing.
Woody seemed to be comfortably aloof from the band, relating mostly to the smiling banjo player, Eddie Davis, the one who put the group together. There are good vibes there, as they all seem to be on the same page. What might be surprising to a lot of people, is how good the band actually is and how much fun they seem to have playing together. After the concert Woody and the band go their separate ways, so this documentary covers Woody fully, giving us a fly-in-the wall look at the claustrophobic star, as he is mobbed by admiring fans and wends his way through autograph seekers and those who want to take photos of him, and his ardent wealthy admirers who flatter the star, but as Woody duly notes, they won't pay a dime to see my films.
Woody and the band show their mettle in one Italian city, as there is a power failure and they continue playing. That he receives an engraved plaque for this, encourages Woody to joke about how it comes easy for him to be a hero. After a while, seeing one luxurious hotel after another becomes a déja vu experience-- the trip took him to Paris, where he was excited about going into a music store that had a historic clarinet that suited him, and to Geneva and Vienna, and finally to London, where he quipped that he can fail at last in a country that speaks his language. Woody comments that he is always wants to be somewhere he isn't, if he is in Milan, he wants to be in New York, if he is in New York, he might want to be in Paris.
The travelogue ends on his arrival in New York and the high-rise apartment of his 96-year-old father and 90+ mother, who treat him to a neurotic scene that could be right out of a shrink's office or one of his films. The father would have preferred that Woody had been a pharmacist. The mother would have preferred if he married a nice Jewish girl.Woody and Soon-Yi sit there in the kitchen and take in all the put downs without fighting back.
REVIEWED ON 7/9/99 GRADE: B
Dennis Schwartz: "Ozus' World Movie Reviews"
http://www.sover.net/~ozus
© ALL RIGHTS RESERVED DENNIS SCHWARTZ
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
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Class Mapper
Provides mapping between repository and storage.
- Orm\Object
- Orm\Mapper implements Orm\IMapper
Indirect known subclasses
Orm\FileMapper
Abstract
Namespace: Orm
Package: Orm
Subpackage: Mappers
Author: Petr Procházka
Located at Mappers/Mapper.php
Namespace: Orm
Package: Orm
Subpackage: Mappers
Author: Petr Procházka
Located at Mappers/Mapper.php
public
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getCollectionClass( boolean $info = false )
Vraci informace o collection kterou pouziva tento mapper.
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__callStatic(),
__get(),
__isset(),
__set(),
__unset()
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createManyToManyMapper(),
findAll(),
flush(),
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Sturgeon's Law
`Prev `__
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`Next `__
--------------
**Sturgeon's Law**: prov.
“Ninety percent of everything is crud”. Derived from a quote by science
fiction author Theodore Sturgeon, who once said, “Sure, 90% of science
fiction is crud. That's because 90% of everything is crud.” Sturgeon
himself called this “Sturgeon's Revelation”, and it first appeared in
the March 1958 issue of *Venture Science Fiction*; he gave Sturgeon's
Law as “Nothing is always absolutely so.” Oddly, when Sturgeon's
Revelation is cited, the final word is almost invariably changed to
‘crap’. Compare `*Hanlon's Razor* <../H/Hanlons-Razor.html>`__,
`*Ninety-Ninety Rule* <../N/Ninety-Ninety-Rule.html>`__. Though this
maxim originated in SF fandom, most hackers recognize it and are all too
aware of its truth.
--------------
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| `Prev `__ | `Up <../S.html>`__ | `Next `__ |
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| Stupids | `Home <../index.html>`__ | sucking mud |
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{% extends "site_base.html" %} {% block page-subtitle %}: Request Materials{% endblock %} {% block content-header %}
If you plan to visit MARBL, you may use this form to request that materials be placed on hold for you prior to your arrival.
{% else %} {# if form not included, display email success/error #} {% with 'request for materials' as message_type %} {% include 'content/snippets/email_sent.html' %} {% endwith %} {% endif %} {% endcomment %}The Stuart A. Rose Manuscript, Archives, and Rare Book Library, which includes the Emory University Archives, is located in the Robert W. Woodruff Library on Emory University's main Atlanta campus. It is a closed-stacks library which means that all of its holdings are located in secure areas and are accessible in our on-site reading room. Please visit the Rose Library website to register and request materials. If you have any questions, please feel free to contact the Rose Library reference staff.
For access to collections at other campus repositories, please contact the archivist for that library directly:


Get to Mars
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K Nagendra Gopal
FIDE Title: Candidate Master
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You can use the mail from below to send results to assessmemnt participants. The words with a '$'-prefix will be mapped to the actual participants data. You may change the mail text to your liking, which will then be used for the mail(s) you send.
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The Long Bombers - 2019 RHFL Champion December 26, 2019 11:12 pm Congratulations to Sam on deafeating Skully 141.9-120.1 and winning the 2019 RHFL Championship. Categorized in: News, Playoffs


steven hofman
Republican
self employed corporate consultant
b.a., political science and history, queens college, n.y. ph.d. candidate, attended three years, university of chicago
80487
during most recent election cycle, advocate in public forums in opposition to proposition 113; advocated in public forums in local elections in 2018 against increases in taxation to fund a new public school.
active in routt county republican party; elected delegate to state party convention, 2016, elected alternate delegate to national convention; wrote nomination speech of george h.w. bush at 1992 convention; assisted vice president nominee dick cheney during 2000 campaign.
chairman of the board, citizens against government waste; member of the board, partners in routt county; member of the board, seminars at steamboat; member of advisory board, steamboat institute
i have been active in redistricting reform issues since i authored congressional legislation in the mid-1980s to create national standards when i was the director of the house wednesday group. as a political scientist by training, i have followed this issue closely at the state level for almost 40 years.
i start with the idea that partisan redistricting is not in the interest of fair and effective governance. districts should be drawn around notions that do not guarantee a political outcome, but follow standards such as geographic compactness and contiguous districts, among others. Throughout my career, first in government, and then in the private sector, i have worked to build consensus decisions and policies because i believe they are usually the most equitable but they are also the most sustainable. I have followed the belief found in the words of senator henry clay, who reminds us, "do not despise compromise, it is the cement that holds the union together." although spoken about 180 years in the past, they remain worthy guideposts today in our nation of competing interests. My professional and personal long track record of working with people of many political and philosophical viewpoints speaks directly about my ability to be fair and impartial.
I have over a 40 career in public policy, and business leadership. i have published scholarly papers, written in virtually every major national publication, advised personally the ceo's in major companies, including the washington post, priceline, barclays global investors, texas instruments, deloitte, mitsubishi motors, among others. As a graduate student at the university of chicago, i did several quantitative projects in conjunction with the national opinion research center. i am also a former guest scholar at the brookings institution, a member of the council on foreign relations, and an advisor to the president of committee for economic development (the think tank for fortune 500 ceos and university presidents).
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Cats rescued from B.C. property had been shot with pellet guns
The feral cats had each been shot and had pellets embedded in them
by Matthew ClaxtonMysterious lumps on two rescued feral cats from Brookswood turned out to be pellet ammunition when the animals were taken to the vet.
Shelley Roche, founder of the TinyKittens rescue group, said two cats dubbed Angela and Shirley were trapped late last summer on a property that has a sizable cat colony.
TinyKittens does trap-neuter-release, adopting out kittens and trying to slowly reduce the population of feral cats in Langley.
Angela, already pregnant, was trapped first on Aug. 23, followed by her tabby sister Shirley, who already had three kittens by the time the team managed to catch her on Sept. 23, said Roche.
“On intake, I noticed peculiar lumps under the skin on both Shirley and Angela,” said Roche. “Our vet came out to do exams and wasn’t sure what they were, so we decided to have them removed and biopsied during their spay surgeries.”
The lumps turned out to be .177 calibre lead pellets, used in pellet guns.
“We are very concerned for any other outdoor cats that might still be in the area, and have filed a report with the SPCA animal cruelty team,” said Roche.
This also means they now consider the area too dangerous to re-release Angela and Shirley back in their former home.
Instead, TinyKittens is looking for a new home for both cats together.
“We would love to find them an indoor-only home with people who will appreciate them for who they are and what they’ve survived, and will love them on their terms,” Roche said.
As former feral cats, they may take quite a while to learn to trust humans, but both cats have been living quite happily indoors in recent weeks.
A home, or possibly a barn, where they will be fed and cared for and receive vet care would be ideal, said Roche. Both Angela and Shirley will need to stay in a confined area for at least four weeks to ensure they can acclimate.
Both cats survived being shot, their health is good, and they are playful and loving with each other, said Roche.
“They are understandably still fearful of humans, but do not express their fear with aggression or physical defensiveness,” she said.
READ MORE: TinyKittens YouTube success fuels more cat rescue efforts
Angela found herself at the center of another drama even before she had come to Tiny Kittens.
She is named after a viewer of the TinyKittens YouTube channel, a 46-year-old woman with MS who had been transferred to hospice in August.
Her caregiver contacted Roche and asked if it was possible to name a kitten after Angela, who said watching “took her mind off the constant pain and loss of independence.”
The pregnant cat Angela was given the name so the human Angela could watch for the kittens to be born.
The human Angela watched for four days until she became unresponsive, passing away shortly after.
The cat colony where Angela and Shirley came from has numerous cats, with 74 from that one site trapped, spayed and neutered, and for the most part adopted into new homes.


The bars included in the project have become staples to thousands of Ohio University students, and now, with this cheat sheet, incoming freshmen can gain four years’ worth of Court Street bar-food expertise in just one quick read.
Published May 26, 2023
F or the following project, data visualizations were created and compiled from an overarching data set highlighting different aspects of all Court Street bar food. The data includes the menu items of every bar on Court Street with an active kitchen: Broney’s Bar & Grill, Courtside Pizza, North End Kitchen + Bar, Stephen’s Restaurant & Bar, The Over Hang, The Pigskin Bar and Grille and The Pub. Information on each of the establishments was recorded over many months, utilizing menu information found online and in-store. For the purpose of the project, and to ensure proper context throughout, outlier menu items were removed from consideration; that includes disproportionately inexpensive menu items or additions, such as additional sauces or small sides, as well as excessively expensive menu items, such as catered portions or meals designed to feed multiple patrons. Similarly, the data does not include custom items that may warrant additional cost. All of those omissions were made with the intent to preserve the application of the project's findings.
The bars included in the project have become staples to thousands of Ohio University students, and now, with this cheat sheet, incoming freshmen can gain four years’ worth of Court Street bar-food expertise in just one quick read.
© Copyright 2023, The Post, Athens, OH


Payday 2 is getting a free update and more DLC tomorrow
by Fraser BrownAfter announcing that development on Payday 2 would be starting up again, Starbreeze and Overkill have unveiled their new plans for the co-op FPS, which includes a free update, Silk Road, and three DLCs.
With the Silk Road update, all players will get access to a new cosmetic system that lets you choose both the mask and outfit for their bank robber, and to start you off you'll get access to six outfits for free.
The tactical BDU, raincoat, scrubs, winter camo parka outfits and more will all be free, while a further 20 will be available via the Tailor Pack 1 DLC. Technically, you actually get fewer unique outfits than with the free update, numbering at only four, but each comes in five different colours.
Free
- Tactical BDU
- Raincoat
- Scrubs
- Winter Camo Parka
- Tuxedo
- Murkywater Uniform
DLC
- The Showman
- The Casual Formal
- The Sunny Rico
- The Classic
For more practical criminals, there's also the Cartel Optics Mod Pack DLC, which nets players ten new weapon mods themed around optics and sights. You'll get three sights, two pistol sights, two optics gadgets, a grip, a muzzle brake and a compensator.
The third piece of DLC is a new heist. The gang will have to head to the border with Mexico to mess up the plans of their enemies, Murkywater and the Dentist, who are moving cash and illegal goods through a tunnel under the border. Some of the gang will need to tackle Murkywater and the Dentist, while the rest rescue their old handler, Bain, who is apparently in trouble yet again.
Development on the game ceased last year amid troubles at publisher Starbreeze, not made any better by the commercial failure of Overkill's The Walking Dead, which was eventually removed from Steam and ended with Skybound Entertainment, the owner of The Walking Dead, terminating its contract with Starbreeze.
Payday 2's Silk Road update and the accompanying DLC are due out on November 7.


This is a basic React application, designed to assist people to learn how to use the Toolkit's React
integration, written using React Hooks. The demo shows:
- The basic structure of a Toolkit/React application
- How to include a Surface component in your UI
- How to map node types to components
- How to bind click listeners in nodes and access the underlying data
- How to render edges
- How to pass props down into your node components


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USWNT: Pride of a Country
Paola Perdomo
July 22, 2015
Sports in the World
- First popular sports
- Second viewer stats
Sports in the USA
- First Stats of big sports
- Second compare to men's soccer
- Third compare to women's soccer
Why no love?
- First stats of uswnt success
- Alpha UNC women's success
- Second stats of unfairness
- Alpha discrepancy in pay
Minimal Change
- First Sports Illustrated covers
- Second Alex Morgan FIFA cover
- Third Tape parade
- Fourth show appearances
Short or Long term?
- First stats on young athletes
- Second not a phase
Solutions?
- First deserved support


Donkeycar
Donkey is a Self Driving Car Platform for hobby remote control cars. Donkey Car is made up of several components: * It is a high level self driving library written in Python. In this project we have automatised a lot of things. We have made two major improvements : The first, is that we have reduce the installation time of 4 hours to less than 5 minutes ( time for download the raspian image). The second improvement is the infrastructure between car and server, now we can see the laps time, and we don't need to touch of any line of code, the driving + training of AI model is fully automatised !!


class: center, middle, inverse, title-slide # Geography 176A ## Lecture 14: Writing functions ### Mike Johnson ---  # Over the last few days: We have learned a lot! -- ### tools for reading and writing data: - read_sf / write_sf - read_csv / write_csv - read_excel -- ### tools for data maniputation - filter - select - mutate - group_by - summarize - rollmean, lag --- ### tools to manage/manipulate data type/structure - as.numeric - as.factor - st_as_sf - data.frame -- ### tools for merging and shaping data - inner_join - left_join - right_join - full_join - pivot_longer - pivot_wider -- ### tools for measuring geometries: - st_distance - st_area - st_length - set_units / drop_units --- ### tools to manage the level and type of geometry - st_combine - st_cast -- ### tools to define topological realtions: - st_intersects - st_touches - st_covers - ... -- ### tools to modify geometeries - st_buffer - st_centroid - st_coordinates - st_bbox -- ### tools to modify geometries based on others - st_intersection - st_difference - st_union - ... --- ### tools to join and filter data spatially - st_filter - st_join --- ### tools to simplify complex geometries - st_simplify (feature-based) - ms_simplify (topology-preserving) - mapview::npts -- ### tools to ask about, set, and change CRS - st_crs - st_set_crs - st_transform --- ### tools to visualize data - ggplot - geom_* - labs - ggrepel - gghighlight - scale_* --- # These tools are all functions - R is a statistical computing language that provides _features_ as _functions_ -- - Even with just its base installation, R provides hundreds of functions: ```r length(lsf.str("package:base")) + length(lsf.str("package:stats")) + length(lsf.str("package:utils")) ``` ``` [1] 1893 ``` -- - sf provides over 100 more ```r length(lsf.str("package:sf")) ``` ``` [1] 129 ``` -- - and the core tidyverse packages (that we use) an additional ~750 ```r length(lsf.str("package:dplyr")) + length(lsf.str("package:ggplot2")) + length(lsf.str("package:tidyr")) + length(lsf.str("package:forcats")) ``` ``` [1] 785 ``` --- # To date, - We have been using functions written for us - mostly by `sf` and the `tidyverse` -- - This how any commercial GIS suite operates as well - Analysis and workflows are limited to the tools kits and options exposed to the user - In R, a lot more is actually exposed! -- - Everytime we install a new package, we download code that provides new specific features (as functions) -- - Everytime we *attach* a package to a working session (`library()`) we are making those functions available/visible --- ## Functions are objects - Just like `x = 10` binds the value of 10 to the name x creating an object visible in the environment, -- - functions are objects that can be called by name to execute a set of directions over defined arguments. -- ```r class(sf::st_intersects) ``` ``` [1] "function" ``` ```r class(sf::st_as_sf) ``` ``` [1] "function" ``` --- # Our own functions are visable as objects in the environemnt ```r x = 10 y = data.frame(x = 1:10, y = 10:1) f = function(x,y){ x + y } ```  --- # Advancing your programming skills - One of the best ways to improve your skills as a data scientist is to write functions. -- - Functions allow you to automate common tasks in a more general way than copy-and-pasting. -- - The more times you apply a function, the more incentive you have to optimize it for speed/accuracy -- - The more creative/unique your analyses and questions can be --- # So why write functions opposed to scripts? - The process can be named -- - As requirements change, you only need to update code in one place -- - You eliminate the chance of making incidental mistakes when you copy and paste (forgetting to change `dist_to_state` to `dist_to_border`). -- - functions can be 'sourced' into Rmd files and R Scripts -- - You save youself time --- # Rule of thumb
- Data is the first argument (better for pipes!) -- - Whenever you have copy-and pasted code more than twice you should write a function -- For example how many times have we coded: ```r states = USAboundaries::us_states() %>% filter(!name %in% c("Hawaii", "Puerto Rico", "Alaska")) ``` -- - Or made the same table with `knitr`/`kableExtra` only changing the `col.names` and `data.frame` -- - Or calculated a distance, changed the units, and dropped them? -- - All of these task are repetitive and prone to making errors that could impact our analysis but not break our code... --- # The form of a function: Creating a function follows the form: ```r name = function(arg1, arg2, *){ code .. .. .. return(...) } ``` Where: -- - `name` is the function name (e.g. `st_as_sf`) - This is the name on which R is able to call the object -- - `arg1` is the first input -- - `arg2` is the second input -- - `*` is any other argument you want to define -- - `code ...` defines the instructions to carry out on `arg1` and `arg2` -- - `return(...)` is what the function returns --- # Defining a function - To define a function we need to identify the code we have, and what can/should generalized for future uses? -- ```r states = USAboundaries::us_states() %>% filter(!name %in% c("Hawaii", "Puerto Rico", "Alaska")) ``` -- - Here the input data (us_states) could change -- - So could the variable name we filter by (name) --- # Function Signiture So, lets start with a function that takes general input data and a variable name -- ```r get_conus = function(data, var){ } ``` --- # Function arguments Function arguments typically include two two broad sets: - the data to compute on, - arguments that control the details of the calculation -- - In `st_transform` `x` is the data, `crs` is the proj4string/EPSG code -- - In `ms_simplify` `input` is the data, `keep` defines the directions -- - In `get_conus`: `data` provides the data, `var` defines the column to filter -- - Generally, data arguments should come first. - Detail arguments should go on the end - It can be useful - and good practice - to define default values. - should almost always be the most common value. - The exceptions to this rule are to do with safety of the process. - e.g. `na.rm = FALSE` --- # Code body We then have to carry these generalizations into the function directions using the arguments as our operators: ```r get_conus = function(data, var){ conus = filter(data, !get(var) %in% c("Hawaii", "Puerto Rico", "Alaska")) return(conus) } ``` -- - here, we replace `us_states()` with `data` -- - we use `get()` to return the *value* of a *named* object -- - We assign our filtered object to the name `conus` -- - And explicitly return the `conus` object from the function -- *** - The value returned by the function is *usually* the last evaluated statement, if we don't specify return we can take advantage of this default: ```r get_conus = function(data, var){ filter(data, !get(var) %in% c("Hawaii", "Puerto Rico", "Alaska")) } ``` --- # Using our function: - Like any object, we have to run the lines of code to save it as an object before we can use it directly in our code: - But then ... -- .pull-left[ ### States ```r x = get_conus(us_states(), "name") plot(x$geometry) ```  ] .pull-right[ ### Counties ```r x2 = get_conus(us_counties(), "state_name") plot(x2$geometry) ```  ] --- ## Cities ```r cities = read_csv("../labs/lab-01/data/uscities.csv") %>% st_as_sf(coords = c("lng", "lat"), crs = 4326) %>% get_conus("state_name") plot(cities$geometry, pch = 16, cex = .1) ```  --- # It's ok to be more detailed - Another advantage of functions is that if our requirements change, we only need to make the change our code in one place. -- - This also means we can spend more time fine-tuning our code since we know it will be recycled. -- - Here we can be more focused and make sure to remove other potential "non-conus" states from any input object: ```r get_conus = function(data, var){ filter(data, !get(var) %in% c("Hawaii", "Puerto Rico", "Alaska", "Guam", "District of Columbia")) } ``` -- ```r conus = get_conus(us_states(), "name") nrow(conus) ``` ``` [1] 48 ``` --- # Point-in-Polygon Case Study - The power of GIS lies in analyzing multiple data sources together. - Often the answer you want lies in many different layers and you need to do some analysis to extract and compile information. - One common analysis is Points-in-Polygon (PIP). - PIP is useful when you want to know how many - or what kind of - points fall within the bounds of each polygon --  -- - In 176B you will learn about other useful ways of analysis point/polygon relationships such as point pattern analysis, interpolation, and others --- # Data ### CONUS counties ```r counties = st_transform(us_counties(), 5070) %>% select(name, geoid, state_name) %>% get_conus("state_name") ``` -- ### CONUS Starbucks ```r starbucks = read_csv('/Users/mikejohnson/Desktop/directory.csv') %>% filter(!is.na(Latitude), Country == "US") %>% st_as_sf(coords = c("Longitude", "Latitude"), crs = 4326) %>% st_transform(5070) %>% st_filter(counties) %>% select(store_name = `Store Name`) ``` -- ### California Counties ```r ca = filter(counties, state_name == "California") ``` ---  --- # Step 1: Spatial Join To count the Starbucks locations in CA counties, we start by joining the CA counties to the locations: -- - Here we uses the `counties` as the x table and the locations as the y table - This is because we want to **add** the starbucks information to the `county` sf object. -- - Remember the default of `st_join` is a `left_join` on the `st_intersects` predicate -- ```r (starbucks1 = st_join(ca, starbucks)) ``` ``` Simple feature collection with 2816 features and 4 fields geometry type: MULTIPOLYGON dimension: XY bbox: xmin: -2356114 ymin: 1243190 xmax: -1646840 ymax: 2452711 projected CRS: NAD83 / Conus Albers First 10 features: name geoid state_name store_name 1 San Francisco 06075 California Teavana - San Francisco Centre 1.1 San Francisco 06075 California Church & Market - S.F. 1.2 San Francisco 06075 California 120 4th Street 1.3 San Francisco 06075 California Safeway - San Francisco #995 1.4 San Francisco 06075 California Teavana - Stonestown Galleria 1.5 San Francisco 06075 California Safeway - Noriega #985 1.6 San Francisco 06075 California Safeway - San Francisco #667 1.7 San Francisco 06075 California 5455 Geary Blvd. - WFB 1.8 San Francisco 06075 California Safeway-San Francisco #2606 1.9 San Francisco 06075 California California & Battery geometry 1 MULTIPOLYGON (((-2283315 19... 1.1 MULTIPOLYGON (((-2283315 19... 1.2 MULTIPOLYGON (((-2283315 19... 1.3 MULTIPOLYGON (((-2283315 19... 1.4 MULTIPOLYGON (((-2283315 19... 1.5 MULTIPOLYGON (((-2283315 19... 1.6 MULTIPOLYGON (((-2283315 19... 1.7 MULTIPOLYGON (((-2283315 19... 1.8 MULTIPOLYGON (((-2283315 19... 1.9 MULTIPOLYGON (((-2283315 19... ``` --- # Step 2: Point counts by Polygon `count()` is a dplyr function that "*lets you quickly count the unique values of one or more variables: df %>% count(a, b) is roughly equivalent to df %>% group_by(a, b) %>% summarise(n = n())*" -- ```r (count(starbucks1, geoid)) ``` ``` Simple feature collection with 58 features and 2 fields geometry type: MULTIPOLYGON dimension: XY bbox: xmin: -2356114 ymin: 1243190 xmax: -1646840 ymax: 2452711 projected CRS: NAD83 / Conus Albers First 10 features: geoid n geometry 1 06001 116 MULTIPOLYGON (((-2267172 19... 2 06003 1 MULTIPOLYGON (((-2057214 19... 3 06005 2 MULTIPOLYGON (((-2137018 20... 4 06007 10 MULTIPOLYGON (((-2180023 21... 5 06009 2 MULTIPOLYGON (((-2142592 19... 6 06011 1 MULTIPOLYGON (((-2255965 21... 7 06013 97 MULTIPOLYGON (((-2270362 19... 8 06015 1 MULTIPOLYGON (((-2292580 24... 9 06017 14 MULTIPOLYGON (((-2140513 20... 10 06019 53 MULTIPOLYGON (((-2150735 18... ``` --- # Step 3: Combine the processes ... ```r starbucks1 = st_join(ca, starbucks) %>% count(geoid) plot(starbucks1['n']) ```  --- # Now for Colorado? We can anticipate that PIP is a useful process we want to implement over variable points and polygons pairs -- So, lets make a function named `point_in_polygon`, that takes a `point` dataset and a `polygon` dataset -- ```r point_in_polygon = function(points, polygon){ st_join(polygon, points) %>% count(geoid) } ``` --- # Test .pull-left[ ```r ca_sb = point_in_polygon(starbucks, ca) plot(ca_sb['n']) ```  ] .pull-right[ ```r co_sb = point_in_polygon(starbucks, filter(counties, state_name == "Colorado")) plot(co_sb['n']) ```  ] --- .pull-left[ ```r or_sb = point_in_polygon(starbucks, filter(counties, state_name == "Oregon")) plot(or_sb['n']) ```  ] .pull-right[ ```r ny_sb = point_in_polygon(starbucks, filter(counties, state_name == "New York")) plot(ny_sb['n']) ```  ] --- # Generalizing the `count` variable - In its current form, `point_in_polygon` only counts on `geoid` -- - Lets modify that by making the variable name an input - again, we use `get()` to return the *value* of a *named* object - we call this, variable `id` -- ```r point_in_polygon2 = function(points, polygon, id){ st_join(polygon, points) %>% count(get(id)) } ``` --- # Applying the new function - Here, we can apply the PIP function over **states** and _count_ by `name` -- ```r states = get_conus(us_states(), "name") %>% st_transform(5070) state_sb = point_in_polygon2(starbucks, states, 'name') plot(state_sb['n']) ```  --- # Optimizing functions - Lets apply our function over the counties and see how long it takes -- - We can check the time it takes by wrapping our function in `system.time` -- ```r system.time({ us = point_in_polygon(starbucks, counties) }) # user system elapsed # 3.719 0.354 4.309 ``` --- # Thats not bad... ```r # How many seconds per point? (point_per_sec = 4.3 / (nrow(counties) * nrow(starbucks))) ``` ``` [1] 1.036916e-07 ``` -- ```r # How will this scale to our dams data # (assuming the process is linear) point_per_sec * (nrow(counties) * 91000) ``` ``` [1] 29.31745 ``` -- - ~ 30 seconds to test ~282,100,000 point/polygon relations is not bad, but could be a bottle neck in analysis -- - Lets look at a common means for improvement... --- # To keep geometery or not? - Remember our geometries are **sticky**, that means they carry through all calculations - whether they are needed or not -- - We can ease _alot_ of computational overhead by being mindfull of when we retain our geometry data with our attribute data. -- .pull-left[ ```r system.time({ st_join(counties, starbucks) %>% count(geoid) }) #user system elapsed #3.970 0.421 5.521 ``` ] .pull-right[ ```r system.time({ st_join(counties, starbucks) %>% st_drop_geometry() %>% count(geoid) %>% left_join(counties, by = 'geoid') %>% st_as_sf() }) # user system elapsed # 0.396 0.017 0.598 ``` ] --- ```r # How many seconds per point? # How many seconds per point? (point_per_sec = .598 / (nrow(counties) * nrow(starbucks))) ``` ``` [1] 1.442037e-08 ``` ```r # How will this scale to our dams data # (assuming the process is linear) point_per_sec * (nrow(counties) * 91000) ``` ``` [1] 4.077171 ``` ### Awesome! Effectivly a 86% decrease in time needed ((29-4) / 29) --- ### "Function-izing" our improvements ```r point_in_polygon3 = function(points, polygon, id){ st_join(polygon, points) %>% st_drop_geometry() %>% count(get(id)) %>% * setNames(c(id, "n")) %>% left_join(polygon, by = id) %>% st_as_sf() } ``` --- # What else can we wrap? - What about a really nice, clean, informative plot? -- - ggplots look great but can be time consuming to program... -- - A function would allow us to take care of the groundwork -- ```r plot_pip = function(data){ ggplot() + geom_sf(data = data, aes(fill = log(n)), alpha = .9, size = .2) + scale_fill_gradient(low = "white", high = "darkgreen") + theme_void() + theme(legend.position = 'none', plot.title = element_text(face = "bold", color = "darkgreen", hjust = .5, size = 24)) + labs(title = "Starbucks Locations", caption = paste0(sum(data$n), " locations represented")) } ``` - This is great because we can devote the time to making a nice plot and we will be able to recycle the work over other cases... --- # Test .pull-left[ ```r point_in_polygon3(starbucks, filter(counties, state_name == "California"), "geoid") %>% plot_pip() ```  ] .pull-right[ ```r point_in_polygon3(starbucks, filter(counties, state_name == "New York"), "geoid") %>% plot_pip() ```  ] --- .pull-left[ ```r point_in_polygon3(starbucks, counties, "geoid") %>% plot_pip() ```  ] .pull-right[ ```r point_in_polygon3(starbucks, states, id = "name") %>% plot_pip() ```  ] --- # Moving beyond Starbucks? - [Here](https://www.qgistutorials.com/en/docs/points_in_polygon.html#:~:text=One%20such%20type%20of%20analysis,use%20this%20method%20of%20analysis.) is a nice tutorial of point-in-polygon in QGIS. It is looking at earthquakes by country. - Just like us they use `naturalearth` data for the polygon areas - And they are looking at earthquake data maintained by NOAA. - In R, we can read the NOAA data directly from a URL. - The data is a tab delimited txt file so we use `readr::read_delim()` --- ```r countries = st_as_sf(rnaturalearth::countries110) url = 'http://www.ngdc.noaa.gov/nndc/struts/results?type_0=Exact&query_0=$ID&t=101650&s=13&d=189&dfn=signif.txt' quakes = read_delim(url, delim = "\t") %>% filter(!is.na(LATITUDE), !is.na(LONGITUDE)) %>% st_as_sf(coords = c("LONGITUDE", "LATITUDE"), crs = 4326) %>% st_transform(st_crs(countries)) nrow(countries) ``` ``` [1] 177 ``` ```r nrow(quakes) ``` ``` [1] 6152 ``` ```r nrow(st_intersection(quakes, countries)) ``` ``` [1] 4148 ``` --- # PIP --> Plotting Method - We can use our functions right out of the box for this data -- - But... somethings are not quite right.. ```r point_in_polygon3(quakes, countries, id = "admin") %>% plot_pip() ```  --- # Modify for our analysis ... ```r point_in_polygon3(quakes, countries, id = "admin") %>% * plot_pip() + labs(title = "Earthquake Locations") + scale_fill_viridis_c() + geom_sf(data = quakes, size = .25, alpha = .05, col = 'red') ``` ---  --- # Improve the anaylsis... ```r point_in_polygon3(quakes, countries, id = "admin") %>% plot_pip() + labs(title = "Earthquake Locations", subtitle = "Most impacted countries") + theme(plot.subtitle = element_text(hjust = .5), plot.title = element_text(color = "navy")) + scale_fill_viridis_c() + geom_sf(data = quakes, size = .3, alpha = .05, col = 'red') + gghighlight::gghighlight(n > (mean(n) + sd(n))) ``` ---  --- # Revisit Lab 3: Set up ### Data ```r states_u = get_conus(us_states(), "name") %>% st_union() %>% st_cast("MULTILINESTRING") states_c = get_conus(us_states(), "name") %>% st_combine() %>% st_cast("MULTILINESTRING") countries = st_as_sf(rnaturalearth::countries110) ``` ### Function ```r dist_5070_km = function(g1, g2){ g2 = st_transform(g2, crs = st_crs(g1)) drop_units(set_units(st_distance(g1,g2),"km")) %>% as.vector() } ``` --- # Revisit Lab 3: Distance Calculations ```r cities = st_transform(cities, 5070) %>% select(city, state_name, population) cities = cities %>% mutate(dist_border = dist_5070_km(., states_u), dist_states = dist_5070_km(., states_c), dist_mex = dist_5070_km(., filter(countries, admin == "Mexico")), dist_can = dist_5070_km(., filter(countries, admin == "Canada"))) ``` -- ```r head(cities) ``` ``` Simple feature collection with 6 features and 7 fields geometry type: POINT dimension: XY bbox: xmin: -2029657 ymin: 2893706 xmax: -1656131 ymax: 3052773 projected CRS: NAD83 / Conus Albers # A tibble: 6 x 8 city state_name population geometry dist_border dist_states <chr> <chr> <dbl> <POINT [m]> <dbl> <dbl> 1 Sout… Washington 2500 (-1990750 2945845) 104. 104. 2 Rosl… Washington 947 (-1888287 2946236) 135. 135. 3 Spra… Washington 441 (-1656131 2893706) 187. 70.8 4 Gig … Washington 9507 (-1995528 2985843) 64.8 64.8 5 Lake… Washington 3591 (-1936810 3052773) 34.7 34.7 6 Teni… Washington 1830 (-2029657 2940259) 83.9 76.6 # … with 2 more variables: dist_mex <dbl>, dist_can <dbl> ``` --- # Revisit Lab 3: Plotting ```r plot_dist = function(data, var){ ggplot() + geom_sf(data = data, aes(color = get(var)), size = .1) + scale_color_gradient(low = "pink", high = "darkred", name = "Distance (km)") + theme_void() + theme(legend.position = "bottom") } ``` --- .pull-left[ ```r plot_dist(cities, "dist_border") + geom_sf(data = states_u) ```  ] .pull-right[ ```r plot_dist(cities, "dist_states") + geom_sf(data = states_c) ```  ] --- # Revisit Lab 3: Plotting ```r mutate(cities, equidist = abs(dist_mex - dist_can)) %>% plot_dist("equidist") + gghighlight::gghighlight(equidist <= 100) + geom_sf(data = states_u) ```  --- # Assignment - Compute and plot the number of cities in each US (CONUS) county as a PIP plot - Use the `uscities.csv` to create your points - Use `USAboundaries::us_states()` to define your polygons - Use the PIP function developed here to compute PIP counts - *MODIFY* the `plot_pip` function to plot your data - save your plot with `ggsave()` --- class: center, middle # Submission Submit your image to gauchospace


For #RoeAt40, all of my favorite pro-choice resources
As my long-time readers know, abortion is an issue I’m very passionate about. So passionate that I have a bookmarks folder simply labeled “Abortion” that has about 75 links in it. For your edification, some of my favorite response to pro-life ignorance:
“Banning…


Jack P. Silva
Jack P. Silva, age 64, passed away after his long struggle with cancer at Meriter Hospital in Madison, WI on November 15, 2019.
He was born on June 15, 1955, a birthday which he shared with his daughter, Autumn. Jack was a jack of all trades (as he would say); he was a mechanic at Blain's Farm and Fleet, enjoyed woodworking, and seemed to be able to fix anything he put his mind to. He loved to hunt and fish whenever he could find time, especially with his good friends and children, whom he brought since they were three and four years old.
Jack was an amazing cook and baker; he always cooked the big holiday dinners, Christmas cookies, and his children's birthday cakes which they asked for every year. Anyone who knew him knew he was a great storyteller and had many stories to tell from throughout his life.
Jack is survived by his partner Kathy Sveum; his three children: Melanie Haase, Autumn-Breeze Silva, and Mitchell Silva; his three sisters: Debbie Mckinley, Vickie Weriberg, and Shari Bender; and several nieces and nephews. He was preceded in death by his son: Hunter Silva; his parents: Jack Silva, and Delores Silva; his two brothers: Douglas Silva, and Kevin Silva; and his dogs: Danny and Maggie.
Jack will be deeply missed. He was greatly loved and will continue to be forever in our hearts and memories.


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Version 1.0.0
T3A06-CSS-Liam.html
CSS stands for Cascading Style Sheets. Typically a file is made with a .css stylesheet file that formats your CSS for your entire website of numerous pages.
Examples: Make the colours Red and Green on Christmas, Pink on Valentines Day, and Green on St. Patrick's Day.
CSS can also be used in the Style part of any webpage that defines colours and such for the whole page.
Mr. Ellis teaches "inline CSS" the most powerful type. All web pages have a CSS style to control it.
This isn't cool.


Progression Stars/Chat - Better Battlelog Forums #2064
Sitemap
26. September 2012 14:03
Topicstarter
darksyderydaz
BB Version: 2.5.0
FF Version: 15.0.1
The newly added stars on the weapon progression show through the chat/party boxes.
http://www.servimg.com/image_preview.php?i=568&u=13144791
26. September 2012 14:10
BrainFooLong
Administrator
Confirmed. On Todo.
05. October 2012 14:08
Pun1a
Helping Hand
http://img.pun1a.net/2012-10-05_1407.png
Wrote a little fix until brain will fix it.
http://pun1a.net/bblog_plugins/BBLog_ServiceStarFix.js


vmserver controls the voicemail system by controlling a voice mail user agent (UA) which actually handles the SIP calls. vmserver knows about things like answering the call, which greeting to play, and where to send the .wav file which contains the caller's voice mail message.
fork into background as a daemon(NOTE: this is opposite all other commands)
run from inetd
specify voicemail configuration file
specify number of VMCP handles
specify the debugging level
run in IVR mode. In this mode, vmserver listens on port 9024 instead of 8024. the corresponding option to ua is -a.


We are looking for motivated UB students that want to get involved!
Fill out the application form, attach your resume, and bring it to the SBI office at 341 Student Union. Applications are being considered now. Forms submitted by e-mail will not be accepted.
Assistant Director of SBI Gaming.
The Assistant Director of SBI Gaming is a student held volunteer (or work study) part-time position. Duties of this position will involve:
(1) attending bi-weekly SBI Gaming meetings.
(2) help plan, promote, and run the annual Esport Olympics gaming tournament at UBCon.
(3) aid the Director of SBI gaming with anything he/she may need. The applicant is expected to be knowledgeable about Esports and popular competitive games (League of Legends, Hearthstone, etc.).
Compensation: Volunteer
Marketing Designer(s): (3)
Position:
Designs the layout of Advertising for flyers, magazine and digital ads. Position utilizes current computer layout programs such as Illustrator, Photoshop and InDesign.
Qualifications:
Experience with layout or design is beneficial with special emphasis on the aforementioned programs. Candidate must have the ability to creatively and coherently depict information in an aesthetic manner. Must have good time management skills and be able to produce within deadlines. Candidate should have the ability to receive constructive criticism on proofs of advertisements and work promptly to address design issues and adhere to tight deadlines.
Compensation: Volunteer
SBI Safety Service
Safety Shuttle Drivers
Responsible for the safe and professional operation of SBIâ€™s Safety Shuttle. Additional duties include: recording statistics related to services, attending staff trainings and maintain a clean vehicle.
Qualifications:
Must have valid U.S driver's license and be eligible for shuttle testing. Must complete a comprehensive training on Safety Services topic areas.
Compensation: An hourly rate of $9.75 is paid to drivers


--- layout: press title: Pinter Double Bill - Press Archive - Fail Better Productions menu-item: press submenu-item: pinter description: View details and photographs from the production. For details about the company and our previous productions visit www.failbetter.co.uk. popup-script: true styles: - /css/colours.css - ../press.css styles-ie6: ../press-ie6.css show: id: pinter class: two-lines title: A Kind of Alaska and Silence author: by Harold Pinter [Double Bill] ---


Copyright (c) 1998 Sean Bridges
This game is played on an empty 3x3x3x3 cell board (or one 9x9 square board):
|
| N rows 4
dimensions... The green dots show all the 3 in-a-rows that include the black stone. |
|
| A sample
endgame
This game was a victory for White, which won 73-42. |
There is a Java program to play 4D Tic-Tac-Toe.


SPARQL has 4 result forms:
The SELECT form directly returns a table of solutions as a result set, while DESCRIBE and CONSTRUCT use the outcome of matching to build RDF graphs.
Pattern matching produces a set of solutions. This set can be modified in various ways:
The solution modifiers OFFSET/LIMIT and ORDER BY always apply to all result forms.
A set of solutions can be abbreviated by specifying the offset (the start index) and the limit (the number of solutions) to be returned. Using LIMIT alone can be useful to ensure not too many solutions are returned, to restrict the effect of some unexpected situation. LIMIT and OFFSET can be used in conjunction with sorting to take a defined slice through the solutions found.
SPARQL solutions are sorted by expression, including custom functions.
ORDER BY ?x ?y
ORDER BY DESC(?x)
ORDER BY x:func(?x) # Custom sorting condition
The SELECT result form can take the DISTINCT modifier which ensures that no two solutions returned are the same - this takes place after projection to the requested variables.
The SELECT
result form is a projection, with DISTINCT applied,
of the solution set. SELECT
identifies which named variables are
in the result set. This may be "*
" meaning "all named
variables" (blank nodes in the query act like variables for matching but are
never returned).
CONSTRUCT builds an RDF based on a graph template. The graph template can have variables which are bound by a WHERE clause. The effect is to calculate the graph fragment, given the template, for each solution from the WHERE clause, after taking into account any solution modifiers. The graph fragments, one per solution, are merged into a single RDF graph which is the result.
Any blank nodes explicitly mentioned in the graph template are created afresh for each time the template is used for a solution.
The CONSTRUCT form, takes an application template for the graph results. The DESCRIBE form also creates a graph but the form of that graph is provided the query processor, not the application. For each URI found, or explicitly mentioned in the DESCRIBE clause, the query processor should provide a useful fragment of RDF, such as all the known details of a book. ARQ allows domain-specific description handlers to be written.
The ASK result form returns a boolean, true of the pattern matched otherwise false.


public class TextFormatter
extends java.lang.Object
| Constructor and Description |
|---|
TextFormatter() |
| Modifier and Type | Method and Description |
|---|---|
private static java.lang.String |
addFormat(java.lang.String input,
java.lang.String formatClass,
char trigger)
Replace a backtick format marker, such as
`b` , with its
respective span class |
private static java.lang.String |
addLinks(java.lang.String input)
Makes text surrounded with tildes (~) clickable.
|
private static java.lang.String |
addNewlines(java.lang.String input)
Deprecated.
|
private static java.lang.String |
clean(java.lang.String input)
Strip potentially dangerous characters to prevent HTML injection.
|
static java.lang.String |
full(java.lang.String input)
Prepares raw
Strings from the user for displaying on a web page |
static java.lang.String |
removeRepeats(java.lang.String input,
java.lang.String target,
int limit)
Removes consecutive repeats of a
String after the amount of
repeats surpasses a limit. |
static boolean |
shouldCensor(java.lang.String input)
Informs a Servlet if it should accept a user's post.
|
static java.lang.String |
swapEscapeForHTML(java.lang.String input,
char target,
java.lang.String replacement,
int consecutiveLimit)
Allows special characters from forms to be rendered as HTML.
|
public static boolean shouldCensor(java.lang.String input)
input
- A String
from the user.public static java.lang.String full(java.lang.String input)
Strings
from the user for displaying on a web pageinput
- Main String
from userString
that is ready to appear as a
post.public static java.lang.String swapEscapeForHTML(java.lang.String input, char target, java.lang.String replacement, int consecutiveLimit)
input
- Main String
from usertarget
- Escape character to replace with HTML codereplacement
- HTML code that will replace target
consecutiveLimit
- Maximum times the target may appear consecutively and
be replaced. Excess appearances are removed.String
which contains ready-made HTML instead of
inconsequential Java escape characters.public static java.lang.String removeRepeats(java.lang.String input, java.lang.String target, int limit)
String
after the amount of
repeats surpasses a limit.input
- A String from the user, which may have repeats.target
- The String
whose repetitions should be limited.limit
- Amount of times the target
is allowed to repeatString
with a limited amount of a repeated target.@Deprecated private static java.lang.String addNewlines(java.lang.String input)
`n`
input
- A String
from the user with formatting.
instead of `n`
private static java.lang.String addFormat(java.lang.String input, java.lang.String formatClass, char trigger)
`b`
, with its
respective span classinput
- A String
from the user with formatting markers.formatClass
- The CSS class of the formatting type.trigger
- The character that will be used inside of the backticks to
form the marker.String
whose markers have been replaced with spans.private static java.lang.String addLinks(java.lang.String input)
input
- A String
fro the user.String
with clickable links; determined by user.private static java.lang.String clean(java.lang.String input)
input
- A String
from the user.String
without angle brackets representations.


#Just Little Splatoon Things: JLST
What's your excuse?
Salt Simulator
Make your randomized battles even more interesting!
Gear Randomizer


European officials have often pointed out that English spelling is unnecessarily difficult; for example: cough, plough, rough, through and thorough. What is clearly needed is a phased programme of changes to iron out these anomalies. The programme would, of course, be administered by a committee staff at top level by participating nations.
In the first year, for example, the committee would suggest using 's' instead of the soft 'c'. Sertainly, sivil servants in all sities would resieve this news with joy. Then the hard 'c' could be replaced by 'k' sinse both letters are pronounsed alike. Not only would this klear up konfusion in the minds of klerikal workers, but typewriters kould be made with one less letter.
There would be growing enthusiasm when in the sekond year, it was announsed that the troublesome 'ph' would henseforth be written 'f'. This would make words like 'fotograf' twenty persent shorter in print.
In the third year, publik akseptanse of the new spelling kan be expekted to reash the stage where more komplikated shanges are possible. Governments would enkourage the removal of double leters whish have always been a deterent to akurate speling.
We would al agre that the horible mes of silent 'e's in the languag is disgrasful. Therefor we kould drop them and kontinu to read and writ as though nothing had hapend. By this tim it would be four years sins the skem began and peopl would be reseptive to steps sutsh as replasing 'th' by 'z'. Perhaps zen ze funktion of 'w' kould be taken on by 'v', vitsh is, after al, half a 'w'. Shortly after zis, ze unesesary 'o kould be dropd from vords kontaining 'ou'. Similar arguments vud of kors be aplid to ozer kombinations of leters.
Kontinuing zis proses yer after yer, ve vud eventuli hav a reli sensibl riten styl. After tventi yers zer vud be no mor trubls, difikultis and evrivun vud find it ezi tu understand ech ozer. Ze drems of the Guvermnt vud finali hav kum tru.


The impact of temperature on the incidence of LD. Note: this figure presents the estimated impacts of temperature on the incidence of LD—cases per 100,000 population—reported in the last column of Table 2 and represented here by blue squares. The vertical dashed lines around each blue square represent the 95 percent confidence interval.


This is an example of my custom designs.
This design was created exclusively for "Diversity One Staffing" using Adobe Illustrator.


--- layout: gallery title: Do Savannah HTML5 site and mobile app date: 2013-07-10 03:58:15.000000000 +05:30 categories: [] tags: [] status: publish type: gallery published: true meta: _edit_last: '1' _thumbnail_id: '3400' _wpas_done_all: '1' _jetpack_related_posts_cache: a:0:{} author: login: cvlewis email<EMAIL_ADDRESS>display_name: Carl V. Lewis first_name: Carl V. last_name: Lewis excerpt: !ruby/object:Hpricot::Doc options: {} ---
[gallery ids="3462,3463,3464,3465"]


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This page explains the use of Flink’s API for asynchronous I/O with external data stores. For users not familiar with asynchronous or event-driven programming, an article about Futures and event-driven programming may be useful preparation.
Note: Details about the design and implementation of the asynchronous I/O utility can be found in the proposal and design document FLIP-12: Asynchronous I/O Design and Implementation.
When interacting with external systems (for example when enriching stream events with data stored in a database), one needs to take care that communication delay with the external system does not dominate the streaming application’s total work.
Naively accessing data in the external database, for example in a MapFunction
, typically means synchronous interaction:
A request is sent to the database and the MapFunction
waits until the response has been received. In many cases, this waiting
makes up the vast majority of the function’s time.
Asynchronous interaction with the database means that a single parallel function instance can handle many requests concurrently and receive the responses concurrently. That way, the waiting time can be overlayed with sending other requests and receiving responses. At the very least, the waiting time is amortized over multiple requests. This leads in most cased to much higher streaming throughput.
Note: Improving throughput by just scaling the MapFunction
to a very high parallelism is in some cases possible as well, but usually
comes at a very high resource cost: Having many more parallel MapFunction instances means more tasks, threads, Flink-internal network
connections, network connections to the database, buffers, and general internal bookkeeping overhead.
As illustrated in the section above, implementing proper asynchronous I/O to a database (or key/value store) requires a client to that database that supports asynchronous requests. Many popular databases offer such a client.
In the absence of such a client, one can try and turn a synchronous client into a limited concurrent client by creating multiple clients and handling the synchronous calls with a thread pool. However, this approach is usually less efficient than a proper asynchronous client.
Flink’s Async I/O API allows users to use asynchronous request clients with data streams. The API handles the integration with data streams, well as handling order, event time, fault tolerance, etc.
Assuming one has an asynchronous client for the target database, three parts are needed to implement a stream transformation with asynchronous I/O against the database:
AsyncFunction
that dispatches the requestsResultFuture
The following code example illustrates the basic pattern:
Important note: The ResultFuture
is completed with the first call of ResultFuture.complete
.
All subsequent complete
calls will be ignored.
The following two parameters control the asynchronous operations:
Timeout: The timeout defines how long an asynchronous request may take before it is considered failed. This parameter guards against dead/failed requests.
Capacity: This parameter defines how many asynchronous requests may be in progress at the same time. Even though the async I/O approach leads typically to much better throughput, the operator can still be the bottleneck in the streaming application. Limiting the number of concurrent requests ensures that the operator will not accumulate an ever-growing backlog of pending requests, but that it will trigger backpressure once the capacity is exhausted.
When an async I/O request times out, by default an exception is thrown and job is restarted.
If you want to handle timeouts, you can override the AsyncFunction#timeout
method.
The concurrent requests issued by the AsyncFunction
frequently complete in some undefined order, based on which request finished first.
To control in which order the resulting records are emitted, Flink offers two modes:
Unordered: Result records are emitted as soon as the asynchronous request finishes.
The order of the records in the stream is different after the async I/O operator than before.
This mode has the lowest latency and lowest overhead, when used with processing time as the basic time characteristic.
Use AsyncDataStream.unorderedWait(...)
for this mode.
Ordered: In that case, the stream order is preserved. Result records are emitted in the same order as the asynchronous
requests are triggered (the order of the operators input records). To achieve that, the operator buffers a result record
until all its preceding records are emitted (or timed out).
This usually introduces some amount of extra latency and some overhead in checkpointing, because records or results are maintained
in the checkpointed state for a longer time, compared to the unordered mode.
Use AsyncDataStream.orderedWait(...)
for this mode.
When the streaming application works with event time, watermarks will be handled correctly by the asynchronous I/O operator. That means concretely the following for the two order modes:
Unordered: Watermarks do not overtake records and vice versa, meaning watermarks establish an order boundary. Records are emitted unordered only between watermarks. A record occurring after a certain watermark will be emitted only after that watermark was emitted. The watermark in turn will be emitted only after all result records from inputs before that watermark were emitted.
That means that in the presence of watermarks, the unordered mode introduces some of the same latency and management overhead as the ordered mode does. The amount of that overhead depends on the watermark frequency.
Ordered: Order of watermarks an records is preserved, just like order between records is preserved. There is no significant change in overhead, compared to working with processing time.
Please recall that Ingestion Time is a special case of event time with automatically generated watermarks that are based on the sources processing time.
The asynchronous I/O operator offers full exactly-once fault tolerance guarantees. It stores the records for in-flight asynchronous requests in checkpoints and restores/re-triggers the requests when recovering from a failure.
For implementations with Futures that have an Executor (or ExecutionContext in Scala) for callbacks, we suggests to use a DirectExecutor
, because the
callback typically does minimal work, and a DirectExecutor
avoids an additional thread-to-thread handover overhead. The callback typically only hands
the result to the ResultFuture
, which adds it to the output buffer. From there, the heavy logic that includes record emission and interaction
with the checkpoint bookkeeping happens in a dedicated thread-pool anyways.
A DirectExecutor
can be obtained via org.apache.flink.runtime.concurrent.Executors.directExecutor()
or
com.google.common.util.concurrent.MoreExecutors.directExecutor()
.
The AsyncFunction is not called Multi-Threaded
A common confusion that we want to explicitly point out here is that the AsyncFunction
is not called in a multi-threaded fashion.
There exists only one instance of the AsyncFunction
and it is called sequentially for each record in the respective partition
of the stream. Unless the asyncInvoke(...)
method returns fast and relies on a callback (by the client), it will not result in
proper asynchronous I/O.
For example, the following patterns result in a blocking asyncInvoke(...)
functions and thus void the asynchronous behavior:
Using a database client whose lookup/query method call blocks until the result has been received back
Blocking/waiting on the future-type objects returned by an asynchronous client inside the asyncInvoke(...)
method


Basic Javascript Events by Dakaro
Remember 9/9 for window.getSelection();
Note: Tap one of the WASD keys to see the object move!
W3Schools Js Events |
W3Schools Js Events Examples |
W3Schools HTML DOM Events
W3Schools HTML DOM Events Examples |
Mozilla Js Events |
Mozilla Js Touch Events
Cant touch this ;)
Double click me
I Like to
Copy me!
Events in order on page
- onKeyDown
- onContextMenu
- onBlur
- onChange
- onFocus
- onSelect
- onMouseOver
- onMouseDown
- onMouseUp
- onDblClick
- onMouseMove
- onClick