When writing a library it is very useful to log information. However there are many logging implementations out there, and a library cannot impose the use of a particular one on the overall application that the library is a part of.
The Logging package is an ultra-thin bridge between different logging implementations. A library that uses the commons-logging API can be used with any logging implementation at runtime. Commons-logging comes with support for a number of popular logging implementations, and writing adapters for others is a reasonably simple task.
Applications (rather than libraries) may also choose to use commons-logging. While logging-implementation independence is not as important for applications as it is for libraries, using commons-logging does allow the application to change to a different logging implementation without recompiling code.
Note that commons-logging does not attempt to initialise or terminate the underlying logging implementation that is used at runtime; that is the responsibility of the application. However many popular logging implementations do automatically initialise themselves; in this case an application may be able to avoid containing any code that is specific to the logging implementation used.
The Release Notes document the new features and bug fixes that have been included in the latest release.
The
JavaDoc API documents for the latest release are available online.
In particular, you should read the package overview of the org.apache.commons.logging
package. In addition, there is a (short)
User Guide.
The Wiki site has the latest updates, an FAQ and much other useful information.
Users needing to become experts or wanting to help develop JCL should (in addition) consult the Tech Guide. This gives short introductions to topics such as advanced class loading.
Binary and source distributions are available here.
This release is a minor update to the 1.1 release that fixes a number of bugs, and resolves packaging issues for maven 1.x and maven 2.x users.
For the full details, see the release notes for this version.
This release makes several changes that are intended to resolve issues that have been encountered when using commons-logging in servlet containers or j2ee containers where complex classpaths are present and multiple copies of commons-logging libraries are present at different levels.
This release also adds support for the TRACE level added to log4j in the 1.2.12 release. In former commons-logging versions, the log.trace method caused log4j to output the message at the DEBUG level (the lowest level supported by log4j at that time).
For the full details, see the release notes for this version.
Note: the 1.0.5 release was abandoned at alpha status.
The next JCL release will be designated 1.1 since we feel this more accurately reflects the improvements made to the codebase.
The 1.0.4 release of commons-logging is a service release containing support for both the 1.2.x and 1.3.x series of Log4J releases.
The 1.0.3 release is primarily a maintenance and code cleanup release with minimal new features.
The 1.0.2 release is a packaging of bug fixes since release 1.0.1.
The 1.0.1 release is a packaging of bug fixes and minor enhancements since release 1.0.
Regular builds of the current SVN HEAD code are made available. See the wiki for details.


For public companies reporting under U.S. Generally Accepted Accounting Principles (GAAP), the new lease accounting standard becomes effective for fiscal years beginning after December 15, 2018. For all other companies reporting under U.S. GAAP, the effective date is for fiscal years beginning after December 15, 2019. Any company, public or non-public, can elect to early adopt the new standard at any time.
For U.S. public companies, the Securities Exchange Commission (SEC) requires 3 years of comparative information on the income statement (including the current reporting year) and two years on the balance sheet (including the current reporting year). As a result, public companies reporting on a calendar year basis will be required to restate their financial information going back to 2017 when publishing their 2019 financial statements.
For all companies reporting under International Financial Reporting Standards (IFRS), the new lease accounting standard will be effective for annual reporting periods beginning on or after January 1, 2019. Early adoption is allowed only after a company has adopted IFRS 15 Revenue from Contracts with Customers.
If the lease term is for a “major part” of the remaining economic life of the underlying asset then the lease will be considered a Finance Lease. While the “bright line” test in existing lease accounting (i.e., 75% of the economic life of the underlying asset) is not present in the new FASB standard, it is referenced in both the Basis for Conclusions and in the Illustrative Examples issued by the FASB that using the 75% test as an indicator of what is considered a “major part” is acceptable.
Exception – If the lease will commence in the last 25% of an asset’s remaining economic life, the lessee will perform this test as if the same term was applied early in the asset’s life.
If the present value of the minimum lease payments, and any residual value guaranteed by the lessee that is not already reflected in the lease payments, equals or exceeds substantially all of the fair value of the underlying asset then the lease will be considered a Finance Lease. While the “bright line” test in existing lease accounting (i.e., 90% of the fair value of the underlying asset) is not present in the new FASB standard, it is referenced in both the Basis for Conclusions and in the Illustrative Examples issued by the FASB that using the 90% test as an indicator of what is considered “substantially all” is acceptable.
For purposes of the present value calculation, the discount rate to be used in the calculation should be the “incremental borrowing rate (IBR)” of the lessee. The IBR is the rate of interest that a “lessee would have to pay to borrow on a collateralized basis over a similar term an amount equal to the lease payments in a similar economic environment”.
The new lease accounting standard defines the lease term as the noncancellable period of the lease, together with all of the following:
The FASB has stated that “reasonably certain” is a high threshold to meet and is consistent with the “reasonably assured” threshold in current lease accounting.
Upon lease commencement, a company shall include the previously referenced periods as part of the lease term having considered all relevant factors that create an economic incentive for the lessee to exercise the option(s). These factors include contract-based, asset-based, entity-based, and market-based factors. These factors shall be considered together, and the existence of any one factor does not necessarily signify that a lessee is reasonably certain to exercise or not to exercise an option.
Examples of economic factors to consider include, but are not limited to, any of the following:
If a lease payment is based on some other method other than a triple-net basis, then it will likely be made up of a “lease component” and a “non-lease component”. The lease component relates to items or activities that transfer a good or service to a lessee and must meet both of the following criteria:
Relative to a real estate related lease, the lease component is that amount that can be identified solely as the amount of rent paid to lease the space.
The non-lease component of a rent payment is associated with reimbursing the landlord for operating expenses, such as common area maintenance, utilities, janitorial services, building security, etc. (excluding real estate taxes and insurance).
The new standard allows a lessee, at their option, to carve out from the gross rent payment any amount reimbursing the landlord for non-lease components for purposes of determining the amount to be used in the calculation of the Lease Liability and Right of Use (RoU) asset recorded on the lessee’s balance sheet.
The FASB believes both real estate taxes and insurance do NOT transfer a good or service to the lessee. Rather, they are considered to be a cost of ownership. Therefore, they may not be excluded from the lease payment on the basis of being a non-lease component. However, the standard does allow for “variable lease payments (VLP)” to be excluded from rent. The most common form of VLP as it relates to a real estate lease is percentage rent, which, as a result of being a VLP, does not have to be taken into account in the calculation of the amount to be capitalized for a lease. If a lease is a “triple-net” lease, then real estate taxes and insurance are considered variable and are therefore VLPs and, as a result, can be excluded from the calculation of the Lease Liability and the RoU Asset.
The following example is provided to demonstrate how non-lease components should be carved-out from the gross rent payment:
The new lease accounting standards require the discount rate used in calculating the amount that goes on the balance sheet to be the interest rate that is implicit in the lease. If that rate cannot be readily determined, which is the case in almost all real estate leases, the lessee is required to use its incremental borrowing rate.
The incremental borrowing rate is defined as the rate of interest a company would have to pay to borrow funds on a collateralized basis over a term similar to the term of the lease in a similar economic environment.


Technology solutions power the constant innovation and disruption that shape the world. At Infinite, we embrace technological disruption to usher in new possibilities and perspectives and bring digital transformation to the world's most innovative brands.Infinite's goal is to enable our customers to become the technology company they want to be to succeed in their respective markets.We are an industry leader in assisting Fortune 500 companies with their business transformation goals We offer impactful solutions allowing companies to accelerate their business successes via automation and analytics Our team consists of the best mind in the industry with deep vertical and domain expertise Our innovation laboratory helps us continually develop breakthrough solutions to solve our clients unique business problems


BIRDMAN.JS IS A JQUERY PLUGIN
THAT CREATES THE ANIMATION OF
TEXT USED IN THE CREDITS OF
THE 2015 MOVIE "BIRDMAN".


In this assignment I used mrJob, built on top of Amazon Elastic Map Reduce (EMR), to compute movie suggestions based on movie rating data from MovieLens 1M and MovieTweetings.
The initial data consisted of lines containing a userid, a movie title and the rating given by that user to that movie.
Through a series of map reduce steps I aggregated this data into key,value pairs of the following format
key: (movie_title1, movie_title2)
value: (rating1, rating2, num_raters1, num_raters2)
I created these key,value pairs for all pairs of movies where a single user had rated both movies.
From each of these individual key,value pairs I was then able to compute different metrics of the similarity of each of the pairs of movies, with the implication that based on how you felt about movie1 one would then be able to use these similarity metrics to predict how well you would like movie2.
Below is an explanation of the four similarity metrics I calculated for each movie pair:
$Correlation(X, Y) = \frac{n \sum xy - \sum x \sum y}{\sqrt{n \sum x^2 - (\sum x)^2} \sqrt{n \sum y^2 - (\sum y)^2}}$
$Weight(X, Y) = \frac{n}{n + VirtualCount}$
$RegularizedCorrelation(X, Y) = Weight(X, Y) * Correlation(X, Y) + (1 - Weight(X, Y)) * PriorCorrelation$
$Cosine(X, Y) = \frac{\sum xy}{\sqrt{\sum x^2} \sqrt{\sum y^2}}$
$Jaccard(X, Y) = \frac{n}{n_1 + n_2 - n}$
After computing similarity metrics for each pair of movies I could then see which movie was most similar to another based on particular metrics.
Below are the 4 movie pairs which were found to have the highest regularized correlation in the MovieLens data set.
You actually have to get all the way down to the 9th highest regularized correlation to find a pair of movies which were not part of the same series.
And all the way down to the 13th spot to find the first pair of 'good' correlated movies ;)
Below are some examples of movies which were found to be most similar by regularized correlation in the MovieTweetings data set.
For this data set you had to get all the way down to the 13th spot to see a pair which were not in the same series.
Clearly there is some real meaning encoded into regularized coefficient, as it makes a lot of sense that people who liked one movie in a series would like another movie in the same series -- suggesting that all unrelated movies the algorithm finds are super interesting insights!
It took a little bit of time to understand the MapReduce paradigm, but then once I got a feel for it it was a delight to use. Anywhere you can systematically perform a computation on a subset of a data set without needing any knowledge of the rest of the data set MapReduce might be able to expedite processing. By stringing together multiple partitioning and calculation steps (map and reduce) there are clearly an amazing number of problems which could be easily deconstructed into a format that would make MapReduce a very beneficial approach.


[Enter personal and organization information through the Preferences > Identity dialog.]
The checker found problems which may prevent the document from being fully accessible.
Document | ||
| Rule Name | Status | Description |
|---|---|---|
| Accessibility permission flag | Passed | Accessibility permission flag must be set |
| Image-only PDF | Passed | Document is not image-only PDF |
| Tagged PDF | Failed | Document is tagged PDF |
| Logical Reading Order | Needs manual check | Document structure provides a logical reading order |
| Primary language | Failed | Text language is specified |
| Title | Failed | Document title is showing in title bar |
| Bookmarks | Passed | Bookmarks are present in large documents |
| Color contrast | Needs manual check | Document has appropriate color contrast |
Page Content | ||
| Rule Name | Status | Description |
| Tagged content | Failed | All page content is tagged |
| Tagged annotations | Passed | All annotations are tagged |
| Tab order | Failed | Tab order is consistent with structure order |
| Character encoding | Passed | Reliable character encoding is provided |
| Tagged multimedia | Passed | All multimedia objects are tagged |
| Screen flicker | Passed | Page will not cause screen flicker |
| Scripts | Passed | No inaccessible scripts |
| Timed responses | Passed | Page does not require timed responses |
| Navigation links | Passed | Navigation links are not repetitive |
Forms | ||
| Rule Name | Status | Description |
| Tagged form fields | Passed | All form fields are tagged |
| Field descriptions | Passed | All form fields have description |
Alternate Text | ||
| Rule Name | Status | Description |
| Figures alternate text | Failed | Figures require alternate text |
| Nested alternate text | Failed | Alternate text that will never be read |
| Associated with content | Failed | Alternate text must be associated with some content |
| Hides annotation | Failed | Alternate text should not hide annotation |
| Other elements alternate text | Failed | Other elements that require alternate text |
Tables | ||
| Rule Name | Status | Description |
| Rows | Failed | TR must be a child of Table, THead, TBody, or TFoot |
| TH and TD | Failed | TH and TD must be children of TR |
| Headers | Failed | Tables should have headers |
| Regularity | Failed | Tables must contain the same number of columns in each row and rows in each column |
| Summary | Skipped | Tables must have a summary |
Lists | ||
| Rule Name | Status | Description |
| List items | Failed | LI must be a child of L |
| Lbl and LBody | Failed | Lbl and LBody must be children of LI |
Headings | ||
| Rule Name | Status | Description |
| Appropriate nesting | Failed | Appropriate nesting |


- Just Java
- Regular house blend, decaffeinated coffee, or flavor of the day.
Endless cup $2.00 - Cafe au Lait
- House blended coffee infused into a smooth steamed milk.
Single $2.00 Double $4.00 - Iced Cappuccino
- Sweetened espresso blended with icy-cold milk, served in a chilled glass. $4.75


{% load static %}
Lakshya CTF - 404
0100 0000 0100

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Hackers are Explorers
But sometimes they get lost too!
Go Back


| Service | Phoenix | Rails |
|---|---|---|
| Web Server | Elixir | Nginx |
| Load Balancer | Elixir | HAProxy |
| KV Server | Elixir | Redis |
| Cache Daemon | Elixir | Memcached |
| Job Queue | Elixir | Sidekiq |
| Process Monitor | Elixir | Monit |
| Performance Graphs | Elixir | RRD/Graphite |
| Search Engine | Elixir Searchex | Elastic Search |
Searchex has a simple CLI, a scalable API, and sharable document Repos. Searchex is ready for testing but not for production.


@Incubating @NotExtensible public interface MockitoSession
MockitoSession
is an optional, highly recommended feature
that helps driving cleaner tests by eliminating boilerplate code and adding extra validation.
If you already use MockitoJUnitRunner
or MockitoRule
*you don't need* MockitoSession
because it is used by the runner/rule.
MockitoSession
is a session of mocking, during which the user creates and uses Mockito mocks.
Typically the session is an execution of a single test method.
MockitoSession
initializes mocks, validates usage and detects incorrect stubbing.
When the session is started it must be concluded with finishMocking()
otherwise UnfinishedMockingSessionException
is triggered when the next session is created.
MockitoSession
is useful when you cannot use MockitoJUnitRunner
or MockitoRule
.
For example, you work with TestNG instead of JUnit.
Another example is when different JUnit runner is in use (Jukito, Springockito)
and it cannot be combined with Mockito's own runner.
Framework integrators are welcome to use MockitoSession
and give us feedback by commenting on
issue 857.
Example:
public class ExampleTest {
@Mock Foo foo;
//Keeping session object in a field so that we can complete session in 'tear down' method.
//It is recommended to hide the session object, along with 'setup' and 'tear down' methods in a base class / runner.
//Keep in mind that you can use Mockito's JUnit runner or rule instead of MockitoSession and get the same behavior.
MockitoSession mockito;
@Before public void setup() {
//initialize session to start mocking
mockito = Mockito.mockitoSession()
.initMocks(this)
.strictness(Strictness.STRICT_STUBS)
.startMocking();
}
@After public void tearDown() {
//It is necessary to finish the session so that Mockito
// can detect incorrect stubbing and validate Mockito usage
//'finishMocking()' is intended to be used in your test framework's 'tear down' method.
mockito.finishMocking();
}
// test methods ...
}
Why to use MockitoSession
?
What's the difference between MockitoSession
, MockitoJUnitRunner
, MockitoRule
and traditional MockitoAnnotations.initMocks(Object)
?
Great questions!
There is no need to use MockitoSession
if you already use MockitoJUnitRunner
or MockitoRule
.
If you are JUnit user who does not leverage Mockito rule or runner we strongly recommend to do so.
Both the runner and the rule support strict stubbing which can really help driving cleaner tests.
See MockitoJUnitRunner.StrictStubs
and MockitoRule.strictness(Strictness)
.
If you cannot use Mockito's JUnit support (for example, you are on TestNG) MockitoSession
exactly is for you!
You can automatically take advantage of strict stubbing (Strictness
),
automatic initialization of annotated mocks (MockitoAnnotations
),
and extra validation (Mockito.validateMockitoUsage()
).
If you use Mockito annotations with MockitoAnnotations.initMocks(Object)
but not Mockito runner/rule please try out Mockito's JUnit support (runner or rule) or
start using MockitoSession
. You'll get cleaner tests and better productivity.
Mockito team would really appreciate feedback about MockitoSession
API.
Help us out by commenting at issue 857.
| Modifier and Type | Method and Description |
|---|---|
void |
finishMocking()
Must be invoked when the user is done with mocking for given session (test method).
|
void |
finishMocking(Throwable failure)
Must be invoked when the user is done with mocking for given session (test method).
|
void |
setStrictness(Strictness strictness)
Changes the strictness of this
MockitoSession . |
@Incubating void setStrictness(Strictness strictness)
MockitoSession
.
The new strictness will be applied to operations on mocks and checks performed by finishMocking()
.
This method is used behind the hood by MockitoRule.strictness(Strictness)
method.
In most healthy tests, this method is not needed.
We keep it for edge cases and when you really need to change strictness in given test method.
For use cases see Javadoc for PotentialStubbingProblem
class.strictness
- new strictness for this session.@Incubating void finishMocking()
UnnecessaryStubbingException
or emit warnings (MockitoHint
) depending on the Strictness
level.
The method also detects incorrect Mockito usage via Mockito.validateMockitoUsage()
.
In order to implement Strictness
Mockito session keeps track of mocking using MockitoListener
.
This method cleans up the listeners and ensures there is no leftover state after the session finishes.
It is necessary to invoke this method to conclude mocking session.
For more information about session lifecycle see MockitoSessionBuilder.startMocking()
.
This method is intended to be used in your test framework's 'tear down' method. In the case of JUnit it is the "@After" method.
For example, see javadoc for MockitoSession
.
finishMocking(Throwable)
@Incubating void finishMocking(Throwable failure)
finishMocking()
.
This method is intended to be used by framework integrations. When using MockitoSession
directly, most users should rather use finishMocking()
.
MockitoRule
uses this method behind the hood.
failure
- the exception that caused the test to fail; passing null
is permittedfinishMocking()


Users
Website Staffs
Welcome to our website STAFFS' page.
This page was purposely created for your convenience if you wanna reach out to any of our staffs for some related issues.
Welcome to our website STAFFS' page.
This page was purposely created for your convenience if you wanna reach out to any of our staffs for some related issues.


/** * Matches the first strong directionality codepoint: * - in group 1 if it is LTR * - in group 2 if it is RTL * Does not match if there is no strong directionality codepoint. * * The form is (?:([strong LTR codepoint])|([strong rtl codepoint])) . * * Generated by UnicodeJS (see tools/strongDir) from the UCD; see * https://gerrit.wikimedia.org/r/unicodejs . */ static private $strongDirRegex = '/(?:()|())/u';


This post is mainly a reiteration of an article, I found online. As of Java 8, we have had the ability to replace looping operations on collections with streams and functional operations. This applies to situations where we don’t have an up-front collection to iterate upon.
What traditionally would have been solved by a for-loop
:
List<String> list = new ArrayList<>();
for (int i = 0; i < 100; i++) {
list.add("Username" + i);
}
// we can now use list
can be replaced by the much more elegant-looking IntStream
:
final List<String> list = IntStream.range(0, 100)
.mapToObj(it -> "Username" + it)
.collect(Collectors.toList());
It is a matter of taste, but I prefer the functional approach from the latter example. A nice advantage of using IntStream
are the reducing helper methods coming from Stream
, such as allMatch
, anyMatch
, noneMatch
, or even reduce
itself. This is helpful when testing multiple conditions and need a single answer at the end:
boolean allMatch = final List<String> list = IntStream.range(0, 100)
.allMatch(it -> booleanTestOn(it))
This is really nothing special that the IntStream
class itself brings on the table, but functionality that it inherits from Stream
.
Analogous to the IntStream
class, alternatives exist for handling Long (https://docs.oracle.com/javase/8/docs/api/java/util/stream/LongStream.html) and Double (DoubleStream
) values.
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Foundations Reflection
Core Learning
Through the core learning, there are 3 things that stood out to me. The first one was properly learning how to use emotional intelligence. I had heard/read about it before but never put It into practise in my everyday life. I found learning about neuroplasticity super useful and how amazing the brain can be, how it can stretch and grow and take on new information. Even with this, I find myself lacking the confidence in myself to learn something when I’m stuck or blocked even though I know the brain is capable of so many wonderful things. I found growth mindset quite interesting and useful. I already seemed to have an understanding of growth mindset without realising what it actually meant. There are a couple of people around me often who use growth mindset daily so I am using that to help me further my daily life not just while studying.
Values, Empathy and Self Awareness in Programming
Being able to be a team player is a huge part of programming but to do that you need an understanding of values, empathy and self awareness. These 3 things impact not just yourself but your coworkers and how they work with you.
Core Learning Surprises
I am quite surprised at how much core material we did but I can see why it is helpful. Understanding how the brain works and how you learn has quite an impact on your growth. In saying that I did feel like it was quite a lot of time to put into learning about it as I got quite behind in the tech side of things.
Core Learning Challenges
Learning about my values and identity was the hardest part, especially talking about my identity and how your upbringing has an effect on your choices.
EDA and Core Learning
I’m not sure I would say studying core was a waste of time but I do think that the amount of time put into it could have been less. The tech part is very time consuming plus you get stuck quite a lot and I did not stick to the time boxes at all really. I would have felt I was making more progress faster if I hadn’t focused on core so much.


When using Spectacle on a Macbook, hitting fn and WASD of F will move the current window.
Fast window movement with Spectacle even when overriding modifiers in other apps.


---
layout: post
title: New article
date: '2012-12-08T07:20:00.000-05:00'
author: ricleal
tags:
- Research
comments: true
---
My last publication while working at the ESRF is finally
out:
|
J. Synchrotron Rad. (2013). 20 [ doi:10.1107/S0909049512049114 ] A survey of global radiation damage to 15 different protein crystal types at room temperature: a new decay modelR. M. Ferraz Leal, G. Burenkov, S. Russi and A. N. PopovSynopsis: A systematic study of the sensitivity to radiation damage of crystals held at room temperature for a large set of model macromolecular structures is presented.Online 6 December 2012 |


Marika Koroibete credits Michael Cheika after being awarded John Eales Medal
by Online EditorsMichael Cheika may be on the nose with disillusioned Wallabies fans but he’s a hero to newly crowned John Eales medallist Marika Koroibete.
Koroibete paid a heartfelt tribute to Cheika after joining the modern-day greats of Australian rugby as the Wallabies’ 2019 player of the year.
In just his third season in the 15-man code after defecting from the NRL, the electric winger won the battle of the Fijian-born backs to see off Samu Kerevi and claim the Wallabies’ highest individual honour.
Continue reading below…
“It’s such an honour to be named with all the great players who’ve won this medal before. I still can’t believe it. I wasn’t expecting this,” Koroibete said on Australian rugby’s night of nights in Sydney.
The humble star said the gong meant everything to his family, but he singled out the outgoing Cheika for believing in him.
It was Cheika who lured Koroibete from the Melbourne Storm and blooded him on the Wallabies’ 2016 spring tour of Europe. But he made the rookie wait almost another year before handing him his test debut.
“Michael Cheika was the one who spoke to me. He’s the one who moulded me to be here wearing this medal,” Koroibete said.
“He didn’t force me to play early. He took his time and encouraged me, gave me things six months by six months, and this year I’ve been working very hard with the (Melbourne) Rebels coaching staff, they’ve supported me as well.
“(Cheika) is such a great man, he mingled well with the boys.
“I like him as a coach. He’s honest with you. If there’s something you need to work on, he tells you straight. He doesn’t beat around the bush.
“Unfortunately, he’s not here anymore.”
Koroibete’s stunning form at the Rugby World Cup was enough for the 27-year-old to become the first winger bestowed with the country’s premier player prize, awarded since 2002.
He polled 200 votes from his Wallabies teammates, 50 clear of second-placed Kerevi.
The soft-spoken speedster revealed his fierce will to win after joining the likes of multiple winners George Smith, Michael Hooper, David Pocock and fellow code-hopper Israel Folau on the honour roll, as well superstar playmakers Matt Giteau and Kurtley Beale.
“I hate losing,” Koroibete said.
“I just go on the field: ‘Where is the No.14?’ I’m No.11, who is the No.14?  That’s my mentality. We’ll go out there and see who the best player on the field is tonight.
“It’s not about me versing the whole team. I set my goals tiny, me and my winger, compete with him.
“The game plan this year suited me very well, I liked it, and it was simple so I enjoyed it this year.”
RUGBY AUSTRALIA AWARDS WINNERS
John Eales Medal: Marika Koroibete
Wallaroos player of the year: Grace Hamilton
Super Rugby player of the year: Samu Kerevi
Super W player of the year: Tayla Stanford
Rookie of the year: Men – Jordan Petaia, Women – Alysia Lefau-Fakaosilea
Sevens player of the year: Men – Maurice Longbottom, Women – Charlotte Caslick
Junior Wallabies player of the year: Fraser McReight
JOHN EALES MEDALLISTS
2019: Marika Koroibete
2018: David Pocock
2017: Israel Folau
2016: Michael Hooper
2015: Israel Folau
2014: Israel Folau
2013: Michael Hooper
2012: Nathan Sharpe
2011: Kurtley Beale
2010: David Pocock
2009: Matt Giteau
2008: George Smith
2007: Nathan Sharpe
2006: Chris Latham
2005: Jeremy Paul
2004: David Lyons
2003: Phil Waugh
2002: George Smith
AAP
In other news:


Sevilla grind out win at Valladolid to go third
REUTERS: Sevilla climbed above Atletico Madrid into third place in La Liga by earning a nervy 1-0 win away to Real Valladolid on Sunday.
Argentine midfielder Ever Banega struck the only goal of the game when he converted a penalty in the 13th minute after his initial spot-kick was saved but it was ordered to be retaken as Valladolid goalkeeper Jordi Masip had strayed from his line.
Sevilla forward Nolito had earned the penalty after a VAR review ruled he had been fouled and he missed a glorious chance to double his side's lead later in the first half, firing into Masip's hands when unmarked in the box.
The visitors had talisman Lucas Ocampos sent off for a second booking in stoppage time but they still managed to grind out the victory to go third in the standings on 27 points after 14 games, unseating Atletico who drew 1-1 at Granada on Saturday.
Julen Lopetegui's side are one point behind leaders Barcelona and second-placed Real Madrid, who beat Leganes and Real Sociedad respectively the previous day and who have a game in hand each.
(Reporting by Richard Martin; Editing by Christian Radnedge)


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WITNESS LIST
Public Health Committee
April 5, 2016 - 9:00 AM
Chronic Disease, Interim Charge #2
On:
Banning, Tom (Texas Academy of Family Physicians)
Carlo, John (Self; American Heart Association)
Chambers, Laura (The University of Texas System)
Daniel, Katrina (Teacher Retirement System of Texas)
Deshpande, Salil (Self)
Garza, Rene (Self; Texas Pharmacy Association)
Guerra-Cardus, Laura (Children's defense fund - texas)
Guerra-Cardus, Laura (Children's defense fund - texas)
Hellerstedt, John (Department of State Health Services)
Kohler, Adriana (Texans Care for Children)
Kukla, Robert (Employees Retirement System of TX)
Lakey, David (The University of Texas System)
McGinnis, Kevin (Texas A&M System)
Muniz, Michael (Self; Alliance of Independent Pharmacy and Texas Pharmacy Association)
Nussa, Kristen (IT'S TIME TEXAS)
Rodriguez, Olga (Texas Association of Community Health Centers)
Sanchez, Eduardo (Partnership for a Healthy Texas & Texas Public Health Coalition)
Scott, Cam (American Cancer Society Cancer Action Network)
Stewart, Dan (The University of Texas System)
Welch, Ken (Teacher Retirement System of Texas)
Wilson, Porter (Employees Retirement System of Texas)
Zalkovsky, Emily (The Health and Human Services Commission)
Zumbrun, Janna (Department of State Health Services)
1


The angular velocity of the particle in radians / second.
The radius of the particle for collision approximation.
32bit RGBA color of the particle.
The energy of the particle.
Whether the particle is dead.
The lifetime of the particle.
Mass of the particle.
The x coordinate of the particle for the previous update.
The y coordinate of the particle for the previous update.
The rotation of the particle in radians.
scale of the particle.
The x coordinate of the velocity of the particle.
The y coordinate of the velocity of the particle.
The x coordinate of the particle.
The y coordinate of the particle.
A data dictionary that can be utilised by actions and activities.
The inertia of the paricle around its center point.
Gets the transformation matrix for the particle
Creates a new particle with all the same properties as this one.
Optional ParticleFactory to create the new particle.
Sets the default values for the particle.
Generated using TypeDoc
The age of the particle in milliseconds.


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| Scott Aaronson |
|
I'm a PhD student in computer science at UC Berkeley, studying under Umesh Vazirani. This summer I'm at the Perimeter Institute in Waterloo, Canada. I'm finishing my thesis, and in the fall I'm starting a postdoc at the Institute for Advanced Study in Princeton. My research interests are computational complexity, quantum computing, and the foundations of quantum mechanics. Contact
267-337-3284 (cell) Last modified: June 16, 2004 |


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SILTUSSIN SA - guaifenesin liquid
Preferred Pharmaceuticals, Inc
Disclaimer: Most OTC drugs are not reviewed and approved by FDA, however they may be marketed if they comply with applicable regulations and policies. FDA has not evaluated whether this product complies.
Active Ingredient: Guaifenesin 100 mg (in each 5 mL)
Uses Helps loosen phlegm (mucus) and thin bronchial secretions to make coughs more productive
Warnings
Ask a doctor before use if you have
- cough that occurs with too much phlegm (mucus)
- cough that lasts or is chronic such as occurs with smoking, asthma, chronic bronchitis, or emphysema
Stop use and ask a doctor if cough lasts more than 7 days, comes back, or is accompanied by fever, rash, or persistent headache. These could be signs of a serious condition.
If pregnant or breast-feeding, ask a health professional before use.
Keep out of reach of children. In case of overdose, get medical help or contact a Poison Control Center right away.
Directions
- do not take more than 6 doses in any 24-hour period
- repeat dose every 4 hours
adults and children 12 years and over
|
2-4 teaspoonfuls
|
| children under 12 years |
DO NOT USE |
Other informationStore at room temperature 20°-25°C (68°-77°F).
Do not accept if imprinted tamperevident safety seal around cap is broken or missing.
Inactive ingredients
citric acid, D&C yellow no. 10, FD&C blue no. 1, FD&C red no. 40, strawberry flavor, glycerin, propylene glycol, saccharin sodium, sodium benzoate, sodium citrate, sorbitol, purified water.
† This product is not manufactured or distributed by Wyeth Consumer Healthcare, owner of the registered trademark Robitussin®.
Manufactured by:
Silarx Pharmaceuticals, Inc.
19 West Street
Spring Valley, NY 10977
USA
Relabeled by:
Preferred Pharmaceuticals, Inc.
1Anaheim, CA 92807


document^CR Left Hand^2010-07-14T11:34:38.000-07:00^true^ image_slides^CR Left Hand^2010-07-14T11:34:38.000-07:00^false^ --__FF00_SIRF_MULTIPART_BOUNDARY_PART_OOFF__ Content-Type: text/html
X-RAY REPORT
Computed Radiography (CR) Left hand:
Obvious fracture see X-RAY image
LM /RMP--__FF00_SIRF_MULTIPART_BOUNDARY_PART_OOFF__ Content-Type: text/html
Final evaluation and verification performed at Pomerado Hospital, 15615 Pomerado Road, Poway CA. 92064.
Case evaluated, dictated, and diagnosed by: USer Physician, MD 07/14/10 (Electronically signed by) LM /RMP--__FF00_SIRF_MULTIPART_BOUNDARY_PART_OOFF__--


| Category: containers | Component type: type |
Looking up an element in a hash_map by its key is efficient, so hash_map is useful for "dictionaries" where the order of elements is irrelevant. If it is important for the elements to be in a particular order, however, then map is more appropriate.
struct eqstr { bool operator()(const char* s1, const char* s2) const { return strcmp(s1, s2) == 0; } }; int main() { hash_map<const char*, int, hash<const char*>, eqstr> months; months["january"] = 31; months["february"] = 28; months["march"] = 31; months["april"] = 30; months["may"] = 31; months["june"] = 30; months["july"] = 31; months["august"] = 31; months["september"] = 30; months["october"] = 31; months["november"] = 30; months["december"] = 31; cout << "september -> " << months["september"] << endl; cout << "april -> " << months["april"] << endl; cout << "june -> " << months["june"] << endl; cout << "november -> " << months["november"] << endl; }
| Parameter | Description | Default |
|---|---|---|
| Key | The hash_map's key type. This is also defined as hash_map::key_type. | |
| Data | The hash_map's data type. This is also defined as hash_map::data_type. | |
| HashFcn | The hash function used by the hash_map. This is also defined as hash_map::hasher. | hash<Key> |
| EqualKey | The hash_map key equality function: a binary predicate that determines whether two keys are equal. This is also defined as hash_map::key_equal. | equal_to<Key> |
| Alloc | The hash_map's allocator, used for all internal memory management. | alloc |
| Member | Where defined | Description |
|---|---|---|
| key_type | Associative Container | The hash_map's key type, Key. |
| data_type | Pair Associative Container | The type of object associated with the keys. |
| value_type | Pair Associative Container | The type of object, pair<const key_type, data_type>, stored in the hash_map. |
| hasher | Hashed Associative Container | The hash_map's hash function. |
| key_equal | Hashed Associative Container | Function object that compares keys for equality. |
| pointer | Container | Pointer to T. |
| reference | Container | Reference to T |
| const_reference | Container | Const reference to T |
| size_type | Container | An unsigned integral type. |
| difference_type | Container | A signed integral type. |
| iterator | Container | Iterator used to iterate through a hash_map. [1] |
| const_iterator | Container | Const iterator used to iterate through a hash_map. |
| iterator begin() | Container | Returns an iterator pointing to the beginning of the hash_map. |
| iterator end() | Container | Returns an iterator pointing to the end of the hash_map. |
| const_iterator begin() const | Container | Returns an const_iterator pointing to the beginning of the hash_map. |
| const_iterator end() const | Container | Returns an const_iterator pointing to the end of the hash_map. |
| size_type size() const | Container | Returns the size of the hash_map. |
| size_type max_size() const | Container | Returns the largest possible size of the hash_map. |
| bool empty() const | Container | true if the hash_map's size is 0. |
| size_type bucket_count() const | Hashed Associative Container | Returns the number of buckets used by the hash_map. |
| void resize(size_type n) | Hashed Associative Container | Increases the bucket count to at least n. |
| hasher hash_funct() const | Hashed Associative Container | Returns the hasher object used by the hash_map. |
| key_equal key_eq() const | Hashed Associative Container | Returns the key_equal object used by the hash_map. |
| hash_map() | Container | Creates an empty hash_map. |
| hash_map(size_type n) | Hashed Associative Container | Creates an empty hash_map with at least n buckets. |
hash_map(size_type n, const hasher& h) |
Hashed Associative Container | Creates an empty hash_map with at least n buckets, using h as the hash function. |
hash_map(size_type n, const hasher& h, const key_equal& k) |
Hashed Associative Container | Creates an empty hash_map with at least n buckets, using h as the hash function and k as the key equal function. |
template <class InputIterator> hash_map(InputIterator f, InputIterator l) [2] |
Unique Hashed Associative Container | Creates a hash_map with a copy of a range. |
template <class InputIterator> hash_map(InputIterator f, InputIterator l, size_type n) [2] |
Unique Hashed Associative Container | Creates a hash_map with a copy of a range and a bucket count of at least n. |
template <class InputIterator> hash_map(InputIterator f, InputIterator l, size_type n, const hasher& h) [2] |
Unique Hashed Associative Container | Creates a hash_map with a copy of a range and a bucket count of at least n, using h as the hash function. |
template <class InputIterator> hash_map(InputIterator f, InputIterator l, size_type n, const hasher& h, const key_equal& k) [2] |
Unique Hashed Associative Container | Creates a hash_map with a copy of a range and a bucket count of at least n, using h as the hash function and k as the key equal function. |
| hash_map(const hash_map&) | Container | The copy constructor. |
| hash_map& operator=(const hash_map&) | Container | The assignment operator |
| void swap(hash_map&) | Container | Swaps the contents of two hash_maps. |
pair<iterator, bool> insert(const value_type& x) |
Unique Associative Container | Inserts x into the hash_map. |
template <class InputIterator> void insert(InputIterator f, InputIterator l) [2] |
Unique Associative Container | Inserts a range into the hash_map. |
| void erase(iterator pos) | Associative Container | Erases the element pointed to by pos. |
| size_type erase(const key_type& k) | Associative Container | Erases the element whose key is k. |
| void erase(iterator first, iterator last) | Associative Container | Erases all elements in a range. |
| void clear() | Associative Container | Erases all of the elements. |
| const_iterator find(const key_type& k) const | Associative Container | Finds an element whose key is k. |
| iterator find(const key_type& k) | Associative Container | Finds an element whose key is k. |
| size_type count(const key_type& k) const | Unique Associative Container | Counts the number of elements whose key is k. |
pair<const_iterator, const_iterator> equal_range(const key_type& k) const |
Associative Container | Finds a range containing all elements whose key is k. |
pair<iterator, iterator> equal_range(const key_type& k) |
Associative Container | Finds a range containing all elements whose key is k. |
data_type& operator[](const key_type& k) [3] |
hash_map | See below. |
bool operator==(const hash_map&, const hash_map&) |
Hashed Associative Container | Tests two hash_maps for equality. This is a global function, not a member function. |
| Member | Description |
|---|---|
data_type& operator[](const key_type& k) [3] |
Returns a reference to the object that is associated with a particular key. If the hash_map does not already contain such an object, operator[] inserts the default object data_type(). [3] |
[1] Hash_map::iterator is not a mutable iterator, because hash_map::value_type is not Assignable. That is, if i is of type hash_map::iterator and p is of type hash_map::value_type, then *i = p is not a valid expression. However, hash_map::iterator isn't a constant iterator either, because it can be used to modify the object that it points to. Using the same notation as above, (*i).second = p is a valid expression.
[2] This member function relies on member template functions, which at present (early 1998) are not supported by all compilers. If your compiler supports member templates, you can call this function with any type of input iterator. If your compiler does not yet support member templates, though, then the arguments must either be of type const value_type* or of type hash_map::const_iterator.
[3] Since operator[] might insert a new element into the hash_map, it can't possibly be a const member function. Note that the definition of operator[] is extremely simple: m[k] is equivalent to (*((m.insert(value_type(k, data_type()))).first)).second. Strictly speaking, this member function is unnecessary: it exists only for convenience.


This package fits the partially linear mixed effects model (semiparametric random intercept model) using kernel regression, without distributional assumptions for the random terms. Estimation procedure is an iterative generalized least squares type. A nonparametric heteroskedastic variance function is allowed for the regression error. Bootstrap resampling is provided for inference. The package implements bandwidth selection by an alternative cross validation for correlated data.
| Version: | 0.1-1 |
| Depends: | sm, Formula, nlme |
| Published: | 2012-11-28 |
| Author: | OHINATA Ren |
| Maintainer: | OHINATA Ren <Ren.Ohinata at wiwi.uni-goettingen.de> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | plmm results |
| Reference manual: | plmm.pdf |
| Package source: | plmm_0.1-1.tar.gz |
| Windows binaries: | r-devel: plmm_0.1-1.zip, r-release: plmm_0.1-1.zip, r-oldrel: plmm_0.1-1.zip |
| OS X binaries: | r-release: plmm_0.1-1.tgz, r-oldrel: plmm_0.1-1.tgz |
Please use the canonical form https://CRAN.R-project.org/package=plmm to link to this page.


uni WebAssembly demo; homepage, details. Type help for usage; the README has more examples.
help
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TO WHOM IT MAY CONCERN:
We hereby wish to confirm that {{nombre}}, whose ID number is {{matricula}}, graduated from this Institute having obtained the Title {{carrera}} on {{fecha_graduacion}}.
We also inform you that their grade average was {{promedio}} on a 1(one) to 100(hundred) grading scale, being 100 (hundred) the highest grade and 70 (seventy) the minimum passing grade. This grade average is obtained taking into account all courses taken by the student (when applicable, remedial courses and courses not passed as well).
He/She ranked {{lugar_en_ranking}} in a graduating class of {{total_alumnos_en_la_generacion}} students
We hereby extend this DOCUMENT for whatever legal purposes the student may require, in the city of Monterrey, state of Nuevo Leon on {{fecha_actual}}
Sincerely,
Academic Administration Department
Tecnológico de Monterrey
Campus Monterrey


Functions as First Class Objects
In Scheme, and other functional programming languages, functions are "First Class Objects". But what does that mean?
An object is first class if it can be treated the same way as a value, that is it can be:
- Named.
- Assigned to a variable.
- Passed to a procedure.
- Returned from a procedure.
Having functions as first class objects provides another dimension for program abstraction. A procedure which receives a procedure as an input or generates a procedure as an output, is called a higher order procedure.
Another feature in practice of functional programming is the map-reduce pattern. In map-reduce an algorithm is split into two parts, the "map" where a calculation is done on each element in a list, and the "reduce" where the result of the individual calculations are aggregated.
Scheme has two methods which help implement simple cases of map-reduce:
- Map - Takes a procedure and a list as arguments, and returns a list containing the result of applying the procedure to each item in the list.
- Apply - Takes a procedure and a list as arguments, and returns the result of calling the procedure with all the values in the list.
So say you want to calculate the sum of the squares of a bunch of numbers:
(define square
(lambda (x)
(* x x)))
(define sum-of-squares
(lambda x
(apply + (map square x))))
(sum-of-squares 2 2 2)
=> 12
Now, say you want to calculate the sum of the cubes of a bunch of numbers. Well you could just copy the sum-of-squares function, change the name and change the call to square to a call to cube:
(define cube
(lambda (x)
(* x x x)))
(define sum-of-cube
(lambda x
(apply + (map cube x))))
(sum-of-cube 3 3 3)
=> 27
But you can see most of the sum-of-squares and sum-of-cubes functions are the same, only differing by the function which gets called. You can remove the duplication by exploiting first class functions. Define a sum-of-func procedure, which takes the function you want to apply as an argument, and returns a sum-of function as its result:
(define sum-of-func
(lambda (f)
(lambda x
(apply + (map f x)))))
You use the higher-order procedure sum-of-func like this:
(define sum-of-square (sum-of-func square))
(sum-of-square 2 2 2)
=> 12
(define sum-of-cube (sum-of-func cube))
(sum-of-cube 3 3 3)
=> 27
It's really quite beautiful.


University of Fribourg, March 2020/21
The scope of this compulsory seminar for Psychology students (6 ECTS) is to provide the participants with knowledge in data generation and analysis. The workshops are interactive and are structured on 3 main points:
Language of instruction is German.
Click to get relevant material for the course:


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References
Jangid, D. K., Brodnik, N. R., Khan, A., Echlin, M. P., Pollock, T. M., et al. 2020. 3DMaterialGAN: Learning 3D shape representation from latent space for materials science applications. arXiv Preprint arXiv:2007.13887.
Kao, P.-Y., Shailja, S., Jiang, J., Zhang, A., Khan, A., et al. 2020. Improving patch-based convolutional neural networks for MRI brain tumor segmentation by leveraging location information. Frontiers in Neuroscience, 13: 1449.
Latypov, M. I., Khan, A., Lang, C. A., Kvilekval, K., Polonsky, A. T., et al. 2019. BisQue for 3D materials science in the cloud: Microstructure–property linkages. Integrating Materials and Manufacturing Innovation, 8(1): 52–65.
Zhang, A., Khan, A., Manjunath, B., & others. 2021. Automated segmentation and connectivity analysis for normal pressure hydrocephalus.


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cz-page-router test
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TYPO: International Design Talks is an annual event held in Berlin, London, and San Francisco. This promotional project is developed to market the event for the designindustry. The use of patterns, sophisticated color scheme and typography are applied for the print and mobile application.


--- layout: post title: Cookies and structures tags: [] status: publish type: post published: true meta: {} ---
I was playing around with setting cookies in the Mach-ii framework and kept finding that even tough my cookie was showing up as set in the debug output when I did a StructKeyExists check it returned no. After some head scratching, I realised that, and this is not only specific to Mach-ii, I assumed that by setting a cookie with a value of cookie.searchPref.pref1 I had created a nested structure searchPrefs with a key of pref1. In actual fact I had created a key in the cookie structure called searchPref.pref1. So the check should really have been:
StructKeyExists(cookie,"searchPrefs.pref1")
And bingo I was now reading the values stored in the cookie rather than from my application constants.


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--- layout: post title: When do you lose credibility? Message to InDinero date: 2010-10-02 17:46:00.000000000 -05:00 comments: true categories: [] published: true ---
As a general entity – i.e. a person, for-profit & non-profit organization – credibility comes down to simply doing what you say you are going to do, and the converse – not doing what you say you wouldn’t. Politicians tend to face this crisis all too often. But so do companies. The following example is one such case.
I have been a long time subscriber to mint.com. But, for some reason, I just stopped using it some time ago. Six months after not logging in, in a while, I got this message:
At first, I was a bit shocked – because the subject of this email was “ACTION REQUIRED – Your Weekly Financial Summary from Mint.com”. This was the second time I was getting this email. The first time I got it, six months prior, I quickly logged in. This time, even though I was shocked, I realized that my mint.com account was not worth it enough to cause me to stop doing what I am doing right now to log in. I said I would do it later, and I never got around to it. So I got another one of these messages the following week.
After the 6th week, I started to question the credibility of the threat. Funnily enough, by threatening to cancel my account 6 weeks in, and not canceling it makes me want to cancel it – because it erodes the value proposition. Five months later, and I am still receiving these email threats on a weekly basis. Here is the latest:
Needless to say, I will likely send them a message requesting them to delete my account and take me off of their mailing list.
Word to the wise: InDinero, you say you are the Mint.com for businesses. There are many things Mint has done right. This is not one of them. Please learn from their mistakes. You show much promise.


| Group | Percent | Total |
|---|---|---|
| Results found | 98.35% | 300017 |
| Browser names | 92.95% | 283537 |
| Engine name | Not available with this provider | |
| Operating systems | 94.14% | 287196 |
| Device brands | 44.2% | 134843 |
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| Is mobile | Not available with this provider | |
| Is bot | Not available with this provider | |
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| Bot types | Not available with this provider |


---
sort_order: 198
tei_id: rdx_b5j2m.p.idp128533392
annotation_count: 0
images:
small-thumbnail: http://readux.library.emory.edu/books/emory:b5j2m/pages/emory:p7b4r/mini-thumbnail/
json: http://readux.library.emory.edu/books/emory:b5j2m/pages/emory:p7b4r/info/
full: http://readux.library.emory.edu/books/emory:b5j2m/pages/emory:p7b4r/fs/
page: http://readux.library.emory.edu/books/emory:b5j2m/pages/emory:p7b4r/single-page/
thumbnail: http://readux.library.emory.edu/books/emory:b5j2m/pages/emory:p7b4r/thumbnail/
title: Page 198
number: 198
---
{% raw %}194 MRS. H. BEECHER STOWE's " UNCLE TOM."{% endraw %}
{% raw %}white population, we should surely lose our own{% endraw %}
{% raw %}lives, and make the chains of those in bondage{% endraw %}
{% raw %}heavier and more securely riveted. No, let us{% endraw %}
{% raw %}suffer in God's name, and wait His time for Ethiopia{% endraw %}
{% raw %}to stretch forth her hands and be free." At last I{% endraw %}
{% raw %}prevailed on them to abandon the project. It is{% endraw %}
{% raw %}certain that the slaves had provocation enough to{% endraw %}
{% raw %}rise and take the places of their masters.  He was nearly dead when he was{% endraw %}
{% raw %}given into my care for me to look after his condition.{% endraw %}
{% raw %}After I began to preach, I just escaped receiving{% endraw %}
{% raw %}thirty-nine lashes at the public whipping-post in{% endraw %}
{% raw %}Alexandria, near Washington, simply for asking the{% endraw %}
{% raw %}Mayor to give me permission to comply with a re¬{% endraw %}
{% raw %}quest to preach there. He indignantly ordered me{% endraw %}
{% raw %}to be taken to prison on the Saturday, and to receive{% endraw %}
{% raw %}the whipping on the Monday or to pay a fine of 25{% endraw %}
{% raw %}dollars. I had no money, and I prayed to God to{% endraw %}
{% raw %}show me what to do. At last I found some one to{% endraw %}
{% raw %}send to my master's young brother. He came to see{% endraw %}
{% raw %}me in jail, and by giving him my watch, worth 45{% endraw %}
{% raw %}dollars, he paid the fine and I was released. Before{% endraw %}
{% raw %}we left the city, however, the blacks collected around{% endraw %}
{% raw %}me, and the Lord opened my mouth, and I had the{% endraw %}
{% raw %}moral courage to give them such a sermon as they{% endraw %}
{% raw %}had not heard for a long time. As soon as I had{% endraw %}
{% raw %}finished my sermon, my young master, who was ready{% endraw %}
{% raw %}with his waggon, hurried me into it, and we rode{% endraw %}
{% raw %}out of the city in great haste, for, as he told me, the{% endraw %}


Dynamic Trigger Configuration - check this if you want to specify the URL to a text file containing the Gerrit trigger configuration. This text file will be automatically fetched at regular intervals, and the trigger configuration will be updated accordingly.
The URL must be in a format that can be parsed by java.net.URL.
A Dynamic Trigger Configuration can co-exist peacefully with the regular way of manually specifying the trigger configuration below.
On a set interval, the plugin fetches and parses this file. The file contents should follow this syntax:
p=some/project
b^**/master/*
t~.*
f~\.txt$
p=some/other/project
b^**
Legend:


[§572C-6] Rights and obligations. Upon the issuance of a certificate of reciprocal beneficiary relationship, the parties named in the certificate shall be entitled to those rights and obligations provided by the law to reciprocal beneficiaries. Unless otherwise expressly provided by law, reciprocal beneficiaries shall not have the same rights and obligations under the law that are conferred through marriage under chapter 572. [L 1997, c 383, pt of §1]
Law Journals and Reviews
Tax Justice and Same-Sex Domestic Partner Health Benefits: An Analysis of the Tax Equity For Health Plan Beneficiaries Act. 32 UH L. Rev. 73 (2009).


Gecode::Int::Count::BaseView< VX, VY, VZ, shr > Class Template Reference
#include <count.hh>
Inherits Gecode::Propagator.
Inherited by Gecode::Int::Count::EqView< VX, VY, VZ, shr >, Gecode::Int::Count::GqView< VX, VY, VZ, shr >, Gecode::Int::Count::LqView< VX, VY, VZ, shr >, and Gecode::Int::Count::NqView< VX, VY, VZ, shr >.
Detailed Description
template<class VX, class VY, class VZ, bool shr>
class Gecode::Int::Count::BaseView< VX, VY, VZ, shr >
Base-class for count propagators (view).
Definition at line 232 of file count.hh.
Public Member Functions | |
| virtual size_t | dispose (Space *home) |
| Delete propagator and return its size. | |
| virtual PropCost | cost (void) const |
| Cost function (defined as dynamic PC_LINEAR_LO). | |
Protected Member Functions | |
| BaseView (Space *home, bool shr, BaseView &p) | |
| Constructor for cloning p. | |
| BaseView (Space *home, ViewArray< VX > &x, VY y, VZ z, int c) | |
| Constructor for creation. | |
| void | count (Space *home) |
| Count how many views are equal now. | |
| int | atleast (void) const |
| How many views are at least equal. | |
| int | atmost (void) const |
| How many views are at most equal. | |
Static Protected Member Functions | |
| static bool | sharing (const ViewArray< VX > &x, const VY &y, const VZ &z) |
| Test whether there is sharing of z with x or y. | |
Protected Attributes | |
| ViewArray< VX > | x |
| Views still to count. | |
| VY | y |
| View to compare to. | |
| VZ | z |
| View which yields result of counting. | |
| int | c |
| Number of views which are equal and have been eliminated. |
Constructor & Destructor Documentation
|
|
Constructor for cloning p.
|
|
|
Constructor for creation.
|
Member Function Documentation
|
|
Delete propagator and return its size.
Reimplemented from Gecode::Actor. |
|
|
Cost function (defined as dynamic PC_LINEAR_LO).
Implements Gecode::Propagator. |
|
|
Count how many views are equal now.
|
|
|
How many views are at least equal.
|
|
|
How many views are at most equal.
|
|
|
Test whether there is sharing of z with x or y.
|
Member Data Documentation
|
|
Views still to count.
|
|
|
View to compare to.
|
|
|
View which yields result of counting.
|
|
|
Number of views which are equal and have been eliminated.
|
The documentation for this class was generated from the following files:
- gecode/int/count.hh (Revision: 3684)
- gecode/int/count/view.icc (Revision: 3612)


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Let's expand on the notion of argument passing in Python. Earlier, we noted that arguments are passed by assignment ; this has a few ramifications that aren't always obvious to beginners:
Function arguments should be familiar territory by now: they're just another instance of Python assignment at work. Function arguments are references to (possibly) shared objects referenced by the caller.
Argument names in the function header become new, local names when the function runs, in the scope of the function. There is no aliasing between function argument names and names in the caller.
On the other hand, since arguments are simply assigned to objects, functions can change passed-in mutable objects, and the result may affect the caller.
Here's an example that illustrates some of these properties at work:
>>> def changer(x, y): ... x = 2 # changes local name's value only ... y[0] = 'spam' # changes shared object in place ... >>> X = 1 >>> L = [1, 2] >>> changer(X, L) # pass immutable and mutable >>> X, L # X unchanged, L is different (1, ['spam', 2])
In this code, the changer function assigns to argument name x and a component in the object referenced by argument y. Since x is a local name in the function's scope, the first assignment has no effect on the caller; it doesn't change the binding of name X in the caller. Argument y is a local name too, but it's passed a mutable object (the list called L in the caller); the result of the assignment to y[0] in the function impacts the value of L after the function returns. Figure 4.2 illustrates the name/object bindings that exist immediately after the function is called.
If you recall some of the discussion about shared mutable objects in Chapter 2, you'll recognize that this is the exact same phenomenon at work: changing a mutable object in place can impact other references to the object. Here, its effect is to make one of the arguments an output of the function. (To avoid this, type y = y[:] to make a copy.)
Python's pass-by-assignment scheme isn't the same as C++'s reference parameters, but it turns out to be very similar to C's in practice:
Objects such as integers and strings are passed by object reference (assignment), but since you can't change immutable objects in place anyhow, the effect is much like making a copy.
Objects such as lists and dictionaries are passed by object reference too, which is similar to the way C passes arrays as pointers—mutable objects can be changed in place in the function, much like C arrays.
Of course, if you've never used C, Python's argument-passing mode will be simpler still; it's just an assignment of objects to names, which works the same whether the objects are mutable or not.
We've already discussed the return statement, and used it in a few examples. But here's a trick we haven't shown yet: because return sends back any sort of object, it can return multiple values, by packaging them in a tuple. In fact, although Python doesn't have call by reference, we can simulate it by returning tuples and assigning back to the original argument names in the caller:
>>> def multiple(x, y): ... x = 2 # changes local names only ... y = [3, 4] ... return x, y # return new values in a tuple ... >>> X = 1 >>> L = [1, 2] >>> X, L = multiple(X, L) # assign results to caller's names >>> X, L (2, [3, 4])
It looks like we're returning two values here, but it's just one—a two-item tuple, with the surrounding parentheses omitted. If you've forgotten why, flip back to the discussion of tuples in Chapter 2.
Although arguments are always passed by assignment, Python provides additional tools that alter the way the argument objects in the call are paired with argument names in the header. By default, they are matched by position, from left to right, and you must pass exactly as many arguments as there are argument names in the function header. But you can also specify a match by name, default values, and collectors for extra arguments.
Some of this section gets complicated, and before we get into syntactic details, we'd like to stress that these special modes are optional and only have to do with matching objects to names; the underlying passing mechanism is still assignment, after the matching takes place. But as an introduction, here's a synopsis of the available matching modes:
The normal case which we've used so far is to match arguments by position.
Callers can specify which argument in the function is to receive a value by using the argument's name in the call.
Functions can use special arguments to collect arbitrarily many extra arguments (much as the varargs feature in C, which supports variable-length argument lists).
Functions may also specify default values for arguments to receive if the call passes too few values
Table 4.2 summarizes the syntax that specify the special matching modes.
|
Syntax |
Location |
Interpretation |
|---|---|---|
|
func(value) |
Caller |
Normal argument: matched by position |
|
func(name=value) |
Caller |
Keyword argument: matched by name |
|
def func(name) |
Function |
Normal argument: matches any by position or name |
|
def func(name=value) |
Function |
Default argument value, if not passed in the call |
|
def func(*name) |
Function |
Matches remaining positional args (in a tuple) |
|
def func(**name) |
Function |
dictionary) |
In the caller (the first two rows of the table), simple names are matched by position, but using the name=value form tells Python to match by name instead; these are called keyword arguments.
In the function header, a simple name is matched by position or name (depending on how the caller passes it), but the name=value form specifies a default value, the *name collects any extra positional arguments in a tuple, and the **name form collects extra keyword arguments in a dictionary.
As a result, special matching modes let you be fairly liberal about how many arguments must be passed to a function. If a function specifies defaults, they are used if you pass too few arguments. If a function uses the varargs forms, you can pass too many arguments; the varargs names collect the extra arguments in a data structure.
Let's look at an example that demonstrates keywords and defaults in action. In the following, the caller must always pass at least two arguments (to match spam and eggs), but the other two are optional; if omitted, Python assigns toast and ham to the defaults specified in the header:
def func(spam, eggs, toast=0, ham=0): # first 2 required print (spam, eggs, toast, ham) func(1, 2) # output: (1, 2, 0, 0) func(1, ham=1, eggs=0) # output: (1, 0, 0, 1) func(spam=1, eggs=0) # output: (1, 0, 0, 0) func(toast=1, eggs=2, spam=3) # output: (3, 2, 1, 0) func(1, 2, 3, 4) # output: (1, 2, 3, 4)
Notice that when keyword arguments are used in the call, the order in which arguments are listed doesn't matter; Python matches by name, not position. The caller must supply values for spam and eggs, but they can be matched by position or name. Also notice that the form name=value means different things in the call and def: a keyword in the call, and a default in the header.
Here's a more useful example of special argument-matching modes at work. Earlier in the chapter, we wrote a function that returned the intersection of two sequences (it picked out items that appeared in both). Here is a version that intersects an arbitrary number of sequences (1 or more), by using the varargs matching form *args to collect all arguments passed. Because the arguments come in as a tuple, we can process them in a simple for loop. Just for fun, we've also coded an arbitrary-number-arguments union function too; it collects items which appear in any of the operands:
def intersect(*args): res = [] for x in args[0]: # scan first sequence for other in args[1:]: # for all other args if x not in other: break # item in each one? else: # no: break out of loop res.append(x) # yes: add items to end return res def union(*args): res = [] for seq in args: # for all args for x in seq: # for all nodes if not x in res: res.append(x) # add new items to result return res
Since these are tools worth reusing (and are way too big to retype interactively), we've stored our functions in a module file called inter2.py here (more on modules in Chapter 5). In both functions, the arguments passed in at the call come in as the args tuple. As in the original intersect, both work on any kind of sequence. Here they are processing strings, mixed types, and more than two sequences:
% python >>> from inter2 import intersect, union >>> s1, s2, s3 = "SPAM", "SCAM", "SLAM" >>> intersect(s1, s2), union(s1, s2) # 2 operands (['S', 'A', 'M'], ['S', 'P', 'A', 'M', 'C']) >>> intersect([1,2,3], (1,4)) # mixed types [1] >>> intersect(s1, s2, s3) # 3 operands ['S', 'A', 'M'] >>> union(s1, s2, s3) ['S', 'P', 'A', 'M', 'C', 'L']
If you choose to use and combine the special matching modes, Python has two ordering rules:
In the call, keyword arguments must appear after all nonkeyword arguments.
In a function header, the *name must be after normal arguments and defaults, and **name must be last.
Moreover, Python internally carries out the following steps to match arguments before assignment:
Assign nonkeyword arguments by position
Assign keyword arguments by matching names
Assign extra nonkeyword arguments to *name tuple
Assign extra keyword arguments to **name dictionary
Assign default values to unassigned arguments in header
This is as complicated as it looks, but tracing Python's matching algorithm helps to understand some cases, especially when modes are mixed. We'll postpone additional examples of these special matching modes until we do the exercises at the end of this chapter.
As you can see, advanced argument matching modes can be complex. They are also entirely optional; you can get by with just simple positional matching, and it's probably a good idea to do so if you're just starting out. However, some Python tools make us e of them, so they're important to know.
Why You Will Care: Keyword ArgumentsKeyword arguments play an important role in Tkinter, the de facto standard GUI API for Python. We meet Tkinter in Chapter 10, but as a preview, keyword arguments set configuration options when GUI components are built. For instance, a call of the form: from Tkinter import * widget = Button(text="Press me", command=someFunction) creates a new button and specifies its text and callback function, using the text and command keyword arguments. Since the number of configuration options for a widget can be large, keyword arguments let you pick and choose. Without them, you might have to either list all possible options by position or hope for a judicious positional argument defaults protocol that handles every possible option arrangement. |
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# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Sensitivity analysis implementations for kernel sparsity on Modules against loss funcs.
"""
from typing import Any, Callable, List, Tuple, Union
import torch
from torch import Tensor
from torch.nn import Module
from torch.utils.data import DataLoader
from sparseml.optim import (
PruningLossSensitivityAnalysis,
default_pruning_sparsities_loss,
)
from sparseml.pytorch.optim.mask_creator_pruning import UnstructuredPruningMaskCreator
from sparseml.pytorch.optim.mask_pruning import ModuleParamPruningMask
from sparseml.pytorch.utils import (
DEFAULT_LOSS_KEY,
LossWrapper,
ModuleRunFuncs,
ModuleTester,
PyTorchLogger,
get_prunable_layers,
infinite_data_loader,
)
__all__ = [
"model_prunability_magnitude",
"pruning_loss_sens_magnitude",
"pruning_loss_sens_one_shot",
]
[docs]def model_prunability_magnitude(module: Module):
"""
Calculate the approximate sensitivity for an overall model.
Range of the values are not scaled to anything, so must be taken in context
with other known models.
:param module: the model to calculate the sensitivity for
:return: the approximated sensitivity
"""
prunable = get_prunable_layers(module)
tensors = []
for (name, layer) in prunable:
weight = getattr(layer, "weight")
values = weight.view(-1).abs()
tensors.append(values)
all_weights = torch.cat(tensors)
avg = all_weights.mean().item()
return avg
[docs]def pruning_loss_sens_magnitude(
module: Module,
sparsity_levels: Union[
List[float], Tuple[float, ...]
] = default_pruning_sparsities_loss(True),
) -> PruningLossSensitivityAnalysis:
"""
Approximated kernel sparsity (pruning) loss analysis for a given model.
Returns the results for each prunable param (conv, linear) in the model.
:param module: the model to calculate the sparse sensitivity analysis for
:param sparsity_levels: the sparsity levels to calculate the loss for for each param
:return: the analysis results for the model
"""
prunable = get_prunable_layers(module)
analysis = PruningLossSensitivityAnalysis()
for index, (name, layer) in enumerate(prunable):
weight = getattr(layer, "weight")
name = "{}.weight".format(name)
values, _ = weight.view(-1).abs().sort()
prev_index = 0
for sparsity in sparsity_levels:
val_index = round(sparsity * len(values))
if val_index >= len(values):
val_index = len(values) - 1
if sparsity <= 1e-9:
baseline = True
sparsity = 0.0
sparse_avg = 0.0
else:
baseline = False
if val_index > prev_index:
sparse_avg = values[prev_index:val_index].mean().item()
prev_index = val_index
else:
sparse_avg = values[val_index].item()
prev_index = val_index + 1
analysis.add_result(None, name, index, sparsity, sparse_avg, baseline)
return analysis
def _sensitivity_callback(
prunable_layers: List[Tuple[str, Module]],
sparsity_levels: List[int],
steps_per_measurement: int,
analysis: PruningLossSensitivityAnalysis,
loss_key: str,
) -> Callable:
measurement_steps = 0
layer_index = -1
sparsity_index = -1
current_mask = None
def complete_measurement():
"""
Uses complete_measurement to handle when all of the required steps have been
taken for a given layer and sparsity level.
This handles incrementing to the next sparsity level.
If all sparsity levels are complete,
increments to the next layer and starts from the initial sparsity level.
Should only be invoked when all measurements have been taken.
"""
nonlocal measurement_steps
nonlocal layer_index
nonlocal sparsity_index
nonlocal current_mask
measurement_steps = 0
sparsity_index += 1
if 0 <= sparsity_index < len(sparsity_levels) and 0 <= layer_index < len(
prunable_layers
):
# increment sparsity level for current layer
current_mask.set_param_mask_from_sparsity(sparsity_levels[sparsity_index])
else:
# go to next layer
sparsity_index = 0
layer_index += 1
if current_mask:
current_mask.enabled = False
current_mask.reset()
del current_mask
current_mask = None
if layer_index < len(prunable_layers):
current_mask = ModuleParamPruningMask(
prunable_layers[layer_index][1],
store_init=True,
mask_creator=UnstructuredPruningMaskCreator(),
)
current_mask.enabled = True
if sparsity_levels[sparsity_index] > 0.0:
current_mask.set_param_mask_from_sparsity(
sparsity_levels[sparsity_index]
)
complete_measurement()
def batch_end(
epoch: int,
step: int,
batch_size: int,
data: Any,
pred: Any,
losses: Any,
):
nonlocal measurement_steps
measurement_steps += 1
if layer_index < len(prunable_layers):
analysis.add_result(
None,
"{}.weight".format(prunable_layers[layer_index][0]),
sparsity_index,
sparsity_levels[sparsity_index],
losses[loss_key].item(),
baseline=sparsity_levels[sparsity_index] < 1e-9,
)
if measurement_steps >= steps_per_measurement:
complete_measurement()
return batch_end
[docs]def pruning_loss_sens_one_shot(
module: Module,
data: DataLoader,
loss: Union[LossWrapper, Callable[[Any, Any], Tensor]],
device: str,
steps_per_measurement: int,
sparsity_levels: List[int] = default_pruning_sparsities_loss(False),
loss_key: str = DEFAULT_LOSS_KEY,
tester_run_funcs: ModuleRunFuncs = None,
tester_loggers: List[PyTorchLogger] = None,
show_progress: bool = True,
) -> PruningLossSensitivityAnalysis:
"""
Run a one shot sensitivity analysis for kernel sparsity.
It does not retrain, and instead puts the model to eval mode.
Moves layer by layer to calculate the sensitivity analysis for each and
resets the previously run layers.
Note, by default it caches the data.
This means it is not parallel for data loading and the first run can take longer.
Subsequent sparsity checks for layers and levels will be much faster.
:param module: the module to run the kernel sparsity sensitivity analysis over
will extract all prunable layers out
:param data: the data to run through the module for calculating the sensitivity
analysis
:param loss: the loss function to use for the sensitivity analysis
:param device: the device to run the analysis on; ex: cpu, cuda
:param steps_per_measurement: the number of samples or items to take for each
measurement at each sparsity lev
:param sparsity_levels: the sparsity levels to check for each layer to calculate
sensitivity
:param loss_key: the key for the loss function to track in the returned dict
:param tester_run_funcs: override functions to use in the ModuleTester that runs
:param tester_loggers: loggers to log data to while running the analysis
:param show_progress: track progress of the runs if True
:return: the sensitivity results for every layer that is prunable
"""
analysis = PruningLossSensitivityAnalysis()
tester = ModuleTester(
module,
device,
loss,
loggers=tester_loggers,
log_summary=False,
log_steps=max(1, round(steps_per_measurement / 10)),
)
layers = get_prunable_layers(module)
batch_end = _sensitivity_callback(
layers, sparsity_levels, steps_per_measurement, analysis, loss_key
)
batch_end_hook = tester.run_hooks.register_batch_end_hook(batch_end)
if tester_run_funcs is not None:
tester.run_funcs.copy(tester_run_funcs)
data_loader = infinite_data_loader(
data, early_stop_steps=steps_per_measurement, cache=True
)
tester.run(
data_loader,
desc="KS Analysis",
show_progress=show_progress,
track_results=False,
max_steps=steps_per_measurement * len(sparsity_levels) * len(layers),
)
batch_end_hook.remove()
return analysis


| APPETIZERS |
| A1 |
French Fries |
| *A2 |
Chilli Wings |
| *A3 |
Spicy Poutine |
| A4 |
Chicken Nuggets |
| A5 |
Onion Rings |
| A6 |
Chicken/Shrimp/Vegetable Spring Roll |
| A7 |
Lollipop Chicken |
| A8 |
Mixed Platter |
| CHICKEN |
| **C1 |
Chilli Chicken |
| C2 |
Honey Chicken |
| *C3 |
Manchurian Chicken |
| **C4 |
Szechuan Chicken |
| C5 |
Sweet&Sour Chicken |
| C6 |
Orange Chicken |
| C7 |
Sesame Chicken |
| C8 |
Chicken with Green Beans |
| *C9 |
Chicken Ma Po Tofu |
| C10 |
Chicken in Black Bean Sauce |
| BEEF |
| **B1 |
Chilli Beef |
| *B2 |
Beef Orange Delight |
| *B3 |
Manchurian Beef |
| **B4 |
Szechuan Beef |
| **B5 |
Beef in Yellow Curry Sauce |
| B6 |
Ginger Beef |
| B7 |
Sesame Beef |
| B8 |
Beef with Green Beans |
| *B9 |
Beef Ma Po Tofu |
| B10 |
Beef in Black Bean Sauce |
| SEAFOOD |
| **S1 |
Chilli Fish/Calamari |
| *S2 |
Deep Fried Tiger Prawns |
| *S3 |
Manchurian Fish/Tiger Prawns |
| **S4 |
Szechuan Fish/Tiger Prawns |
| *S5 |
Tiger Prawns in Lobster Sauce |
| S6 |
Sweet&Sour Tiger Prawns |
| S7 |
Tiger Prawns with Snow Peas |
| **S8 |
Tiger Prawns in Yellow Curry Sauce |
| *S9 |
Tiger Prawns in Mango Sauce |
| S10 |
Steamed Fish |
| VEGETARIAN |
| **V1 |
Chilli Vegetable Balls |
| *V2 |
Manchurian Balls |
| **V3 |
Spicy Garlic Tofu |
| V4 |
Sweet&Sour Mixed Vegetables |
| **V5 |
Vegetables in Yellow Curry Sauce |
| V6 |
Gai Lan/Baby Bakchoy/ On Choi |
| *V7 |
Spicy Deep Fried Tofu |
| **V8 |
Szechuan Mixed Vegetables |
| **V9 |
Chilli Paneer |
| V10 |
Mixed Vegetables in Black Bean Sauce |
| NOODLES |
| N1 |
Hakka Noodles(Chicken/Shrimp/Vegetarian) |
| N2 |
Sweet Hakka Noodles(Chicken/Shrimp/Vegetarian) |
| *N3 |
Manchurian Hakka Noodles(Chicken/Shrimp/Vegetarian) |
| **N4 |
Szechuan Hakka Noodles(Chicken/Shrimp/Vegetarian) |
| *N5 |
Singapore Noodles(Chicken/Vegetarian) |
| N6 |
Beef Ho Fun |
| **N7 |
Chilli Chicken on Fried Noodles |
| *N8 |
Manchurian Chicken on Fried Noodle |
| N9 |
Chicken or Beef Shanghai Noodles |
| N10 |
American Chop Suey(Chicken) |
| RICE |
| R1 |
Chicken Fried Rice |
| R2 |
Sweet Fried Rice(Chicken/Shrimp/Vegetarian) |
| *R3 |
Manchurian Fried Rice(Chicken/Shrimp/Vegetarian) |
| **R4 |
Szechuan Fried Rice(Chicken/Shrimp/Vegetarian) |
| *R5 |
Singapore Fried Rice(Chicken/Vegetarian) |
| R6 |
Beef Fried Rice |
| R7 |
Vegetable Fried Rice |
| R8 |
Mushroom Fried Rice |
| R9 |
Paneer Fried Rice |
| R10 |
Steamed Rice |
| *Spicy **Extra Spicy |


|
|
.NET Framework |
| PREV TYPE NEXT TYPE |
FRAMES NO FRAMES |
| SUMMARY: INNER | FIELD | CONST | PROP | METHOD | OP | EVENT |
DETAIL: FIELD | CONST | PROP | METHOD | OP | EVENT |
NVelocity.App.Events
Interface NullSetEventHandler
Event handler : lets an app approve / veto
writing a log message when RHS of #set() is null.
*
| Method Summary |
| bool |
shouldLogOnNullSet(string lhs, string rhs) Called when the RHS of a #set() is null, which will result
in a null LHS.
*
|
shouldLogOnNullSet
public bool shouldLogOnNullSet(string lhs,
string rhs)
-
Called when the RHS of a #set() is null, which will result
in a null LHS.
*
Parameters:
-
lhs
- reference literal of left-hand-side of set statement
-
rhs
- reference literal of right-hand-side of set statement
Returns:
- true if log message should be written, false otherwise
|
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|
Interface Summary |
| Context |
Defines an interface to provide client context information . |
| Cookie |
Creates a cookie, a small amount of information sent by a servlet to
a Web browser, saved by the browser, and later sent back to the server.
|
| Environment |
Base interface for an environment abstraction |
| ModifiableSource |
Describes a Source object whose data content can change. |
| Redirector |
Interface for an redirector abstraction |
| Request |
Defines an interface to provide client request information . |
| Response |
Defines an interface to provide client response information . |
| Session |
Provides a way to identify a user across more than one page
request or visit to a Web site and to store information about that user.
|
| Source |
Description of a source. |
| SourceResolver |
Base interface for resolving a source by system identifiers. |


{% extends "base.html" %} {% load base_paths %} {% block body %}
Thank you for your participation! Your participant number is {{ participant.participant_number}}.
Please take a few minutes to complete this survey, using the participant number above.
{% endblock %}


Who are we looking for
Cerebtech is looking to hire a Mobile Strategist / Solutions Architect to help in the delivery of Cerebtech's Mobile Strategy and app development engagements.
Typical travel is 30-50% for this position.
The Mobile Strategist / Solutions Architect will work on a variety of exciting project engagements with an exceptional team of professionals. This individual must have assisted organizations in the formulation, planning, and execution of a mobility strategy and delivery of a mobile app. The candidate must be familiar with the current state of mobile technology and mobile best practices throughout a variety of industries. Must be knowledgeable about mobile development standards, have the ability to identify a landscape of mobile vendors (MDM, MADPs, etc.), be familiar with the deployment of mobile apps across platforms, and have created a center of excellence design and execution for mobility. Must have led project teams through a mobile app SDLC.
What will you be doing?
Requirement
Copyright (C) Cerebtech. All Rights Reserved.


Mymap Route to Locations
Please insert a Google maps browser API key with the constant editor first!
{Lvar} sys_language_uid for use with language


yconic is a platform for high school and post secondary students interested in scholarship and bursary matching.
Goals: Assist in updating the user interface and user experience. Establish a style guide and user experience best practices with the design team.
My Roles: UI/UX
Next project
Star Touch Interactive Ads
©2022 Designed and Developed by Sonia Tam


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{{itm.address.firstname}} {{itm.address.lastname}} tel: {{itm.address.tel}}
0" class="categories-title">{{'สินค้า'}}see all
0" [populars]="shopDetailData.shop.products">


Episode VIII
A lead UI developer for React/Redux, Vue.js & AngularJS builds, creating self-aware modular components and a frontend engineer providing a seamless bridge between design and back-end.
Specialties include UI development for large scale client-side web apps or CMS websites, full-stack JavaScript development, responsive web design, mobile optimization, and scalable, efficient CSS.
Technical expert able to architect projects from scratch or smoke jump when one goes off the rails :).
Check my stuff:
GitHub
Bitbucket
CodePen
Resume
LinkedIn


# new ERC20TokenLock(params)
ERC20 Token Lock Contract Object
Parameters:
| Name | Type | Description |
|---|---|---|
params |
Object | |
tokenAddress |
Address | |
contractAddress |
Address | ? (opt) |
Methods
# approveERC20Transfer() → {Boolean}
Approve this contract to transfer tokens of the ERC20 token contract on behalf of user
Success True if operation was successful
# canRelease(params) → {Boolean}
Check if locked tokens release date has come and user can withdraw them
Parameters:
| Name | Type | Description |
|---|---|---|
params |
Object | |
address |
Address |
canRelease
# deploy()
Deploy the ERC20 Token Lock Contract
# getLockedTokens(params) → {Integer}
Get locked tokens amount for a given address
Parameters:
| Name | Type | Description |
|---|---|---|
params |
Object | |
address |
Address |
amount Locked token amount
# getLockedTokensInfo(params) → {Date|Date|Integer}
Get locked tokens info for a given address
Parameters:
| Name | Type | Description |
|---|---|---|
params |
Object | |
address |
Address |
startDate
endDate
amount Token amount
# getTokenAmount(params) → {Integer}
Get Token Amount of ERC20 Address
Parameters:
| Name | Type | Description |
|---|---|---|
params |
Object | |
address |
Address |
Token Amount
# lock(params) → {Boolean}
User locks his tokens until specified end date.
Parameters:
| Name | Type | Description |
|---|---|---|
params |
Object | |
address |
Address | User Address |
amount |
Integer | Tokens amount to be locked |
endDate |
Date | Lock tokens until this end date |
Success True if operation was successful REQUIREMENTS: user must have approved this contract to spend the tokens "amount" he wants to lock before calling this function.
# async maxAmountToLock() → {Integer}
Get maximum amount of tokens to lock per user
Maximum Amount
# async minAmountToLock() → {Integer}
Get minimum amount of tokens to lock per user
Minimum Amount
# release(params) → {Boolean}
User withdraws his locked tokens after specified end date
Parameters:
| Name | Type | Description |
|---|---|---|
params |
Object | |
address |
Address | User Address |
Success True if operation was successful
# setMaxAmountToLock(params) → {Boolean}
Admin sets maximum amount of tokens to lock per user
Parameters:
| Name | Type | Description |
|---|---|---|
params |
Object | |
tokenAmount |
Address | Amount of Tokens |
Success True if operation was successful
# setMinAmountToLock(params) → {Boolean}
Admin sets minimum amount of tokens to lock per user
Parameters:
| Name | Type | Description |
|---|---|---|
params |
Object | |
tokenAmount |
Integer | Minimum tokens amount |
Success True if operation was successful
# async totalAmountStaked() → {Integer}
Get All Tokens staked/locked at that specific moment
Token Amount


50+ budding apprentices
8 other employers
We’ll let you know when new standards are developed for sectors you’re interested in.


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Try out our Premium Member services: Virtual Legal Assistant, Query Alert Service and an ad-free experience. Free for one month and pay only if you like it.
Page No.# 1/2 GAHC010264402019 THE GAUHATI HIGH COURT (HIGH COURT OF ASSAM, NAGALAND, MIZORAM AND ARUNACHAL PRADESH) Case No. : WA 6/2020 1:M/S T. G. ENTERPRISE, REP. BY ITS DIRECTOR P. TOHEVI AWOMI, AIKO BUILDING 5TH FLOOR, OPPOSITE- TOWN HALL, BANK COLONY, DIMAPUR, NAGALAND. VERSUS 1:NEW SOCUNOMA VILLAGE AND 6 ORS. REP. BY SHRI SALEW SEYIE, CHAIRMAN, NEW SOCUNOMA VILLAGE COUNCIL, P.O. MEDZIPHEMA, DIMAPUR, NAGALAND. 2:THE STATE OF NAGALAND REP. THROUGH THE CHIEF SECRETARY TO THE GOVT. OF NAGALAND KOHIMA. 3:THE PRINCIPAL SECRETARY DEPARTMENT OF ENVIRONMENT FORESTS AND CLIMATE CHANGE NAGALAND KOHIMA. 4:THE DEPUTY COMMISSIONER DIMAPUR NAGALAND. 5:THE ADDITIONAL DEPUTY COMMISSIONER MEDZIPHEMA DIMAPUR NAGALAND. 6:THE NAGALAND POLLUTION CONTROL BOARD REP. BY ITS MEMBER SECRETARY SIGNAL POINT DIMAPUR NAGALAND. Page No.# 2/2 7:SHRI MHIESISATO VUPRU NEW SOCUNOMA VILLAGE P.O. MEDZIPHEMA DIMAPUR NAGALAND Counsel for appellant : Mr. A Dasgupta, Senior Advocate Counsel for respondent No.1 : Ms. M Dev
Counsel for respondent Nos.2, 3, 4 & 5: Ms. T Khro Counsel for respondent No.6 : Mr. T Islam BEFORE HON'BLE THE CHIEF JUSTICE MR. AJAI LAMBA HON'BLE MR. JUSTICE SOUMITRA SAIKIA 27.05.2020 (Ajai Lamba, C.J.) The Court proceedings have been conducted through Video-Conferencing in view of the present scenario so as to maintain social distancing.
2. It appears that the consent to operate stone crusher unit under the name and style of M/s T.G. Enterprise Stone Crusher Unit, New Socunoma village granted under Sections 25/26 of the Water (Prevention & control of Pollution) Act, 1974, as amended and under Section 21 of the Air (Prevention & Control of Pollution) Act, 1981 was in vogue till 2.8.2019. It has been contended on behalf of the respondents that the licence itself having expired, the issue raised by the petitioner is rendered academic. There is no cause of action as on date because in the absence of licence in any case the unit cannot be operated.
3. We hereby give time to learned counsel for the petitioner to take instructions in view of the changed circumstances.
4. List on 10.6.2020.
5. Let copy of this order be provided under the signature of the Court Master.
JUDGE CHIEF JUSTICE Comparing Assistant


---
title: The DeBary Institute
date: 2013-01-25
comments: true
layout: post
categories:
- friends
- travel
ref_url:
---
Its been a great J-Term. A trip to Vail for some Skiing, **and** a trip to Florida to solve the worlds problems with great friends at the DeBary Institute. For those who do not know, the DeBary institute is a newly renowned think tank with roots in the Bone Lake Global Institute.
We arrived on Friday and spent a wonderful late afternoon enjoying the hospitality and home of our host, Tim Peter.
On Saturday we toured Stetson University in the morning.
Later we repaired to Smyrna Beach, it was a bit windy but we enjoyed it all the same.
The culinary highlight of our trip was dinner at the Swamp House Grill and Tiki Bar. We enjoyed some lovely alligator bites as appetizers:
(Yes, as the famous frog said, they do taste like chicken)
After dinner we sat around enjoying the music of Mark Moore.
Sunday was Football (European and American) and then Golf day.
Dinner was provided by Gregory and Brad who made a charming seafood alfredo.
Monday morning we left the house at 5:50AM. The temperature was 62 degrees. Five hours later we arrived in Cedar Rapids where the temperature was -2. Thats a big swing for a monday morning.
Already looking forward to next year!


Alex Childers
CS 328
Homework 6, Problem 2
The Basics
Name:
Age:
Which college of HSU are you primarily involved in?
College of Arts, Humanities, and Social Sciences
College of Natural Resources and Sciences
College of Professional Studies
General Studies
Preferences
Choose some colors.
What is your favorite color?
What is your second favorite color?
What is your least favorite color?
Which flavors have you tried?
Chocolate
Vanilla
Strawberry
Asphalt
Chalk
Which flavor is your favorite?
Chocolate
Vanilla
Strawberry
Asphalt
Chalk
Express yourself
Write a poem about your favorite flavor.
I savor The flavor My favored Lifesaver
Validate by pasting .xhtml copy's URL into
https://html5.validator.nu/


Installation
The following section outlines the installation guide of the DCActivity module.
Python 3.6 or higher is required
discord.py V1.5.0 or higher is required
Install using pip:
Git clone from Github:
# Windows
python -m pip install dcactivity
# macOS/Linux
python3 -m pip install dcactivity
$ git clone https://github.com/AkshuAgarwal/dcactivity.git
$ cd dcactivity
$ python setup.py install


Thanks Everyone For A Terrific Halloween 2016! Check Back Soon For DIY Instructions!
You can control this Halloween decoration on my front porch! There is about a 15 second video delay. Taking it down Saturday!
Speak From The Upside Down
Your message will go through, but you will be able to see it better at night.


Simple SpriteSheet Example
A simple example of defining a
SpriteSheet
and playing it back using
Sprite
.


Marker-based
A marker-based AR experience uses an image to anchor the AR content. Follow the steps below to get started now.
Once you have created it, you will obtain a marker image that you have to give to the users, either on print paper (better) or shown on screen.
1. Use a premade marker or upload your own
Here is a sample marker for you. Feel free to use it as the marker for your project. Alternatively, click “Upload image” to use a custom one. Not sure what makes a good marker? Check out this guide.
2. Choose the content
Select supported content with the type listed below: