built to share shortcut techniques with others creating shortcuts
Author: @JimSauer
Development Tools
Updated for iOS 13
Note: Versions of Let's Share Shortcut Techniques comments prior to 3.2 will not automatically check for a new version. With these pre-3.2 versions, to check for a new version, select Shortcut Update Initiated by User from the main Choose from Menu.
If you are still running iOS 12, you can download Version 2.4 from this page.
Additional Let's Share Shortcut Techniques comments are available on reddit /shortcuts.
The purpose of this shortcut is to share techniques that I and others have learned as we've developed shortcuts.
I plan to update this shortcut periodically. If you have any snippets that you would like to share, please leave a comment and I'll add them to the next version of this shortcut.
Here's a list of techniques currently included in this shortcut...
Within the shortcut, there is a main Choose from Menu that includes the following items:
- SF Symbol for vCard Menu
- Create Help and Display in Safari (Markdown Source)
- Shortcut Update Initiated by User
- Pick Subset of Shortcuts - all | select | text
- Pick Subset of Shortcuts - all pre | none pre | text
- Backup, Archive, and Restore Shortcuts
- Check Network Status
- Create vCard Menu with SF Symbol Photos
- Various Methods to Access Dictionary Values
- Search For a Shortcut
- Shortcut plist
- Encode a Web Sound & Prepare to Embed
- Run Without Showing Actions
- Force Shortcut Execution in the Shortcuts App
- FileExist? TRUE, return contents; FALSE, create file, set contents
- Dictionary & RepeatWithEach to ReplaceText x N
- Write to a Device-specific iCloud Folder
- Generate a Multiple Line Prompt (e.g., with Ask for Input)
- IF with OR logic
- Write Contents of Dictionary to a New Note
As an example, here are two dialogs, one from Pick Subset of Shortcuts - all | select | text and one from Create vCard Menu with SF Symbol Photos.
In addition, the shortcut includes embedded actions that provide techniques:
- To compare the build number of the current version to the build number of the shortcut when it was previously run. If the difference exceeds a specified build delta, display an alert. See below, top left screenshot.
- To display a "welcome" alert the first time the shortcut is started AND if a specified number of days have elapsed since the shortcut was last run. See below, top-right screenshot.
- To display a daily alert. See below, bottom-left screenshot.
- To automatically check for a shortcut update if a certain number of days have elapsed since the most recent check. See below, botton-right screenshot.
Tests
This shortcut was tested using iOS 13.3.1 (17D5026c) beta 1 on an iPad Pro 10.5" and an iPhone 8 Plus.
Acknowledgments
- Let’s Share Shortcut Techniques is available exclusively on RoutineHub.co. Versions obtained elsewhere might be out-of-date.
- The framed screenshots were created using the shortcut Apple Frames (iOS) from the MacStories Shortcuts Archive.
- Let’s Share Shortcut Techniques can check for updates if a user selects Shortcut Update Initiated by User on the main Choose from Menu. One of two update tools can be selected: 1) Embed-a-Update (Version: 1.1.2, Updated: 10/13/19); or 2) UpdateKit (Version 6.0.2, Updated: 11/13/19)


When you loop with for you execute the code once for each element in the expression. When looping with for a range is defined, in this case the code will execute according to the values between 0 and 5.
for i in 0..5 puts "Value of local variable is #{i}" end
(0..5).each do |i| puts "Value of local variable is #{i}" end
Loops in Ruby are used to execute the same code a certain number of times. The While loop executes code while the conditional is true.
while conditional [do] code end
Looping with Until is similar to looping with While except for the code is executed until the conditional is true. Therefore it executes the code as long as the conditional remains false.
until conditional [do] code end
The for statement creates a loop that consists of three optional expressions, enclosed in parentheses and separated by semicolons, followed by a statement executed in the loop.
for ([initialization]; [condition]; [final-expression]) statement;
The following for statement starts by declaring the variable i and initializing it to 0. It checks that i is less than nine, performs the two succeeding statements, and increments i by 1 after each pass through the loop.
for (var i = 0; i < 9; i++) { console.log(i); // more statements }
The while statement creates a loop that executes a specified statement as long as the test condition evaluates to true. The condition is evaluated before executing the statement.
while (condition) { statement }
The following while loop iterates as long as n is less than three.
var n = 0; var x = 0; while (n < 3) { n++; x += n; }
The for..in statement iterates over the enumerable properties of an object, in arbitrary order. For each distinct property, statements can be executed.
for (variable in object) {... }
The following function takes as its argument an object. It then iterates over all the object's enumerable properties and returns a string of the property names and their values.
var obj = {a:1, b:2, c:3}; for (var prop in obj) { console.log("o." + prop + " = " + obj[prop]); } // Output: // "o.a = 1" // "o.b = 2" // "o.c = 3"


- delete(String) - Method in class edu.umd.cs.datastructures.demos.hashing.LinearProbingHashTable
-
- delete(T) - Method in class edu.umd.cs.datastructures.demos.splaying.SplayTree
-
Removes key from the tree and returns it.
- delete(T) - Method in class edu.umd.cs.datastructures.demos.traversals.BinarySearchTree
-
Deletes key from the tree if it's there, otherwise does nothing.
- delete(KDPoint) - Method in class edu.umd.cs.datastructures.projectskeletons.kdtree.KDTree
-
Deletes p from the KDTree.
- delete(String) - Method in class edu.umd.cs.datastructures.projectskeletons.patricia.BinaryPatriciaTrie
-
Deletes key from the trie.
- delete(T) - Method in class edu.umd.cs.datastructures.projectskeletons.tavl.ThreadedAVLTree
-
Delete the key from the data structure and return it to the caller.
- deleteSimple() - Method in class edu.umd.cs.datastructures.demos.traversals.BinarySearchTreeTest
-
- deleteStress() - Method in class edu.umd.cs.datastructures.demos.traversals.BinarySearchTreeTest
-
- dequeue() - Method in class edu.umd.cs.datastructures.projectskeletons.kdtree.BoundedPriorityQueue
-
Remove and return the minimum priority (top) element from the queue.
- Dimension - Enum in edu.umd.cs.datastructures.demos.matrices.java
-
A simple abstraction of the dimension to sum along a 2D matrix: sums or columns.
- dimension - Variable in class edu.umd.cs.datastructures.examcode.matrix.SquareMatrix
-
- distance(KDPoint) - Method in class edu.umd.cs.datastructures.projectskeletons.kdtree.utils.KDPoint
-
Calculate the squared Euclidean distance between this and p.
- distance(KDPoint, KDPoint) - Static method in class edu.umd.cs.datastructures.projectskeletons.kdtree.utils.KDPoint
-
A static version of distance calculations.
- DynamicallyShuffledBag<Item> - Class in edu.umd.cs.datastructures.demos.bags
-
A DynamicallyShuffledBag is a
Bag
which, very much like a
RandomAccessBag
, shakes its contents
completely (pseudo-) randomly.
- DynamicallyShuffledBag() - Constructor for class edu.umd.cs.datastructures.demos.bags.DynamicallyShuffledBag
-
This constructor is used to initialize the bag with full pseudorandom capabilities for shaking
and the default starting capacity.
- DynamicallyShuffledBag(int, long) - Constructor for class edu.umd.cs.datastructures.demos.bags.DynamicallyShuffledBag
-
This constructor creates a DynamicallyShuffledBag with a provided initial capacity as well
as a client-provided seed.
- DynamicallyShuffledBag(long) - Constructor for class edu.umd.cs.datastructures.demos.bags.DynamicallyShuffledBag
-
This constructor creates a DynamicallyShuffledBag with a provided seed for experiment
reproducibility.
- DynamicallyShuffledBag(int) - Constructor for class edu.umd.cs.datastructures.demos.bags.DynamicallyShuffledBag
-
This constructor creates a DynamicallyShuffledBag with the provided default capacity.


Bryan is the project lead of ELMS Learning Network. Bryan is a graduate of the Pennsylvania State University College of Information, Sciences & Technology with a B.S. (2006) and M.S. (2015). His Master's Thesis of Information Altruism highlights that through donation of information technology we are able to change institutions. He has been contributing to Drupal based systems since 2007 and is a tireless advocate for the transformative nature of open source communities. Bryan is a leading voice in the Drupal in Education community and has helped Penn State adopt and grow a vibrant Drupal community. Presenting at dozens of Education and Drupal conferences alike, Bryan travels with his message that open source can, does, and will transform our institutions and our world.
The world needs more dreamers, bring dreams to life with us!
Michael Potter is affectionately known as the second most famous Michael Potter in Drupal. What he lacks in neutrino particle physics knowledge he makes up for in crafting sustainable, responsive front-end systems and Drupal websites using the latest techniques and tools. Before coming to Penn State, Michael worked for multiple startups where he used and abused Drupal to quickly prototype ideas and solve technological problems for businesses. As an educational technologist, he brings that same passion of solving problems with technology to online learning. Michael is also a core developer for the open-source Drupal platform, ELMS Learning Network.
I came to Penn State with the intention of studying mechanical engineering for four years and leaving. I can’t be more happy that I accomplished none of those things. I’ve been working with online learning technology for about a decade. I started teaching digital media art when I was in graduate school, and during that time discovered that I have a knack for crashing 3D software during in-class demos. Save early, save iteratively, save often.
I prefer to work with people who don’t take “...but this doesn’t exist!” for an answer. Educational Technologist is a vague job title, but essentially it means that I’m passionate about using design and technology to push education forward in a sustainable way. More specifically, I maintain, design, and build online learning infrastructure. Right now we are running on a massive open-source project called ELMS Learning Network. One project that I’m really excited about right now is called HAX, an intuitive drag and drop content authoring interface for Drupal that will one day replace Drupal’s WYSIWYG.
My Spotify playlist is typically hard at work making sure my brain is happy while I’m working through design or code problems. When I’m not working, you can find me... wait, no, you can’t find me because I’m riding on some singletrack with no cell reception. That or I’m traveling to give a talk or volunteer at a nerdy tech conference like SIGGRAPH or DrupalCon.
Brad is a solutions architect, a Drupal site builder and backend developer. With a healthy knowledge of "ground-up" application deployment and system infrastructure, Brad likes to give projects a good home. At Penn State Brad works as a programmer/analyst, specializing in Drupal and Server automation.
Fill in my bio...blah blah blah blah...
What does this team member to? Keep it short! This is also a great spot for social links!


Did you ever stop to think, and forget to start again?
As A.A. Milne said. Some people talk to animals. Not many listen though. That is the problem.
Some people talk to animals. Not many listen though. That is the problem.


In this example, we'll use a mixin, 3 levels of inheritance ( 1, 2, 3 ), and some method override tricks coupled with _super().
_super()
Open your browser's console, then click the button below.


Differential analysis of HiChIP loops
FitHiChIP also supports finding differential HiChIP loops between two categories (such as two different cell types), each with one or multiple replicates.
The script Differential_Analysis_Script.sh contains command to execute differential analysis.
Source code of the differential analysis is provided in Imp_Scripts/DiffAnalysisHiChIP.r
Basics
The objective is to find differential HiChIP loops among two categories (each with one or more replicates).
In addition, if user provides ChIP-seq alignment files for the input categories (details below), the interacting 1D bins in these differential loops are categorized as differential or non-differential 1D (ChIP) bins.
Specifically, the code categorizes 1D bins in three classes, depending on their difference in ChIP-seq coverage among the two input categories:
HD (i.e. high difference) - when the 1D bin is differential (by EdgeR) according to its ChIP-seq coverage in the two input categories.
ND (i.e. no difference) - when the 1D bin is non-differential (by EdgeR) and has < X% difference in ChIP-seq coverage in the two input categories.
Here X is by default 25, and is determined by the parameter --CovThr (mentioned below)
LD (i.e. low difference) - when the 1D bin is non-differential (by EdgeR) but has >= X% difference in ChIP-seq coverage in the two input categories, where X is determined by the parameter --CovThr.
Output differential loops are categorized in the following five classes:
HD-HD - when both interacting bins in the differential loops belong in the class HD
ND-ND - when both interacting bins in the differential loops belong in the class ND
LD-LD - when both interacting bins in the differential loops belong in the class LD
ND-LD - when one interacting bin in the differential loops belong in the class ND, while the other bin belongs within LD
HD-LDorND - when one interacting bin in the differential loops belong in the class HD, while the other bin belongs in either LD or ND.
The category ND-ND (category 2) corresponds to the differential loops involving non-differential 1D bins. That is, differential loops solely due to the changes in 3D (looping).
Options
Parameters associated with this script is:
- --AllLoopList
Comma or colon separated list of loops with FitHiChIP significance (FDR) values, for all categories and all replicates.
User should provide the file *PREFIX*.interactions_FitHiC.bed (please check the page Details of FitHiChIP outputs). Mandatory parameter.
Files can be in gzipped format as well.
- --ChrSizeFile
File having the chromosome sizes for the reference genome.
Mandatory parameter.
- --FDRThr
FDR significance threshold for FitHiChIP loops. Default = 0.01.
- --ChIPAlignFileList
** Optional parameter **
Comma or colon separated list of ChIP-seq alignment files.
Either two files, one for each category, are to be given.
Or, provide ChIP seq alignment files one for each sample.
Note
ChIP-seq alignment files matching with the given HiChIP data (cell type, histone modifications of interest) can be downloaded from ENCODE (https://www.encodeproject.org/).
File can either be in BAM or Bedgraph (4-column) format.
- --CovThr
Applicable if ChIPAlignFileList parameter is not NULL.
Maximum difference of ChIP-seq coverage (in percentage) between two categories to label a non-differential (by EdgeR) 1D bin as ND (i.e. no difference).
Default = 25, means non-differential 1D bins with difference of ChIP coverage < 25% are considered as ND.
In such a case, non-differential 1D bins with difference of ChIP coverage >= 25% are considered as LD (i.e. low difference).
- --OutDir
Output directory to contain differential analysis results.
Mandatory parameter.
- --CategoryList
Comma or colon separated list of strings, representing labels of two categories.
Default: Category1, Category2.
- --ReplicaCount
Comma or colon separated list representing the count of samples (replicates) belonging to individual categories.
Default: 1,1 (means one replicate per sample exists).
- --ReplicaLabels1
Comma or colon separated list of the label of replicates for the first category.
Default: R1,R2, etc.
- --ReplicaLabels2
Comma or colon separated list of the label of replicates for the second category.
Default: R1,R2, etc.
- --FoldChangeThr
EdgeR fold change threshold.
Default = 2 means log2(2) = 1 is employed as the fold change threshold on the EdgeR output.
- --DiffFDRThr
FDR threshold for EdgeR.
Default is 0.05, means that loops with FDR < 0.05, and fold change >= log2(FoldChangeThr) would be considered as differential.
- --bcv
If number of replicates is 1 for either of the input categories, this value is the square-root-dispersion.
Default and recommended value is 0.4. For details, please see the EdgeR manual.
Example 1
Assume the following input conditions:
Two input categories of HiChIP data, denoted as cat1 and cat2.
Each category has two replicates, denoted as repl1 and repl2.
hg19 as the reference genome
One ChIP-seq alignment file for each category.
Then, the command for differential analysis would be:
Rscript Imp_Scripts/DiffAnalysisHiChIP.r \
—AllLoopList cat1_repl1_file,cat1_repl2_file,cat2_repl1_File,cat2_repl2_file \
--ChrSizeFile TestData/chrom_hg19.sizes --FDRThr 0.01 --CovThr 25 \
—ChIPAlignFileList cat1_ChIPAlign.bam,cat2_ChIPAlign.bam \
--OutDir /home/user/diffanalysis/outdir \
—CategoryList CellLine1,CellLine2 \
--ReplicaCount 2,2 --ReplicaLabels1 R1,R2 --ReplicaLabels2 R1,R2 \
—FoldChangeThr 2 --DiffFDRThr 0.05 --bcv 0.4
Here, cat1_repl1_file denotes the loops (containing FitHiChIP significance values) of category 1, replicate 1. Similar notations for the other files.
In the parameter --AllLoopList, all the samples of category 1 should be specified first, followed by the samples in category 2
User can also specify the files using colons (:) as a separator instead of comma.
The file cat1_ChIPAlign.bam represents ChIP-seq alignment file for the category 1. Similar notation for category 2.
Example 2
Assume the following input conditions:
Two input categories denoted as cat1 and cat2.
Each category has two replicates, denoted as repl1 and repl2.
hg19 is the reference genome
One ChIP-seq alignment file for individual samples.
Then, the command for differential analysis would be:
Rscript Imp_Scripts/DiffAnalysisHiChIP.r \
—AllLoopList cat1_repl1_file,cat1_repl2_file,cat2_repl1_File,cat2_repl2_file \
--ChrSizeFile TestData/chrom_hg19.sizes --FDRThr 0.01 --CovThr 25 \
—ChIPAlignFileList cat1_R1_ChIPAlign.bam,cat1_R2_ChIPAlign.bam,cat2_R1_ChIPAlign.bam,cat2_R2_ChIPAlign.bam \
--OutDir /home/user/diffanalysis/outdir \
—CategoryList CellLine1,CellLine2 \
--ReplicaCount 2,2 --ReplicaLabels1 R1,R2 --ReplicaLabels2 R1,R2 \
—FoldChangeThr 2 --DiffFDRThr 0.05 --bcv 0.4
Here, cat1_R1_ChIPAlign.bam denotes the ChIP-seq alignment for replicate 1 of the category 1. Similar notations for the other files.
Details of differential analysis outputs
Within the specified output directory OutDir, following files / folders are generated by the differential analysis:
Input_Parameters*.log : lists the input command line options.
MasterSheet_*Loops.bed :
Union of all FitHiChIP loops of the given categories and samples, with the respective contact counts and interaction significance values.
EdgeR_Loops_Ov_FitHiChIP_Sig_One_Repl :
Folder containing the EdgeR differential loops which are significant (in terms of FitHiChIP FDR threshold) in at least one input sample.
The file DiffLoops.bed contains differential loops.
** If ChIP-seq alignment files are provided **
Underlying folders have name X-Y where X and Y denote the type of 1D bin (LD, ND or HD) according to their ChIP-coverage specific differential analysis.
Within each folder, file DiffLoops.bed contains differential loops of the particular category.
Files DiffLoops_Excl_*.bed contain differential loops exclusive to one category (i.e. significant in only that category).


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Total : 40 SAR
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WATCH: Desert locusts descend upon Karachi
by Our CorrespondentKARACHI: In a rare occurrence, swarms of desert locusts have descended upon Karachi with citizens posting footage of the insects in various parts of the metropolis.
Known as Tiddi Dal in Pakistan, the insects were seen filling the skies. The swarms of the insect have come from Thar, Sanghar and Dadu parts of Sindh.
While Sindh Agriculture Minister Ismail Rahoo has released a video message saying that the locusts are headed to Balochistan after spending the night in Karachi.
Rahoo added that the locusts were in the Malir area and had not harmed any crop so far.
He said the provincial government had already sent teams to the affected areas.
Rahoo urged people to remain calm as the locusts would not harm them in any way.
“We have sprayed pesticides in Nawabshah, Badin and Sanghar,” he added.
On a lighter note, the provincial minister said,”Yes, they [citizens] should make use of the opportunity to cook them.”
Locusts are short horned grass hoppers and desert locusts of Africa and Asia are normally solitary, however, spring rains trigger a behavioural transformation that can results in a swarms of locust. A single swarm ranges from 100,000 to 1 billion locusts.


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accordingTo
- Static variable in class eu.newsreader.eventcoreference.objects.
Sem
According to is used to state which Authority sais that a property constrained by the View Constraint is true.
Actor
- Static variable in class eu.newsreader.eventcoreference.objects.
Sem
Actors are entities that take part in an Event, either actively or passively.
actorType
- Static variable in class eu.newsreader.eventcoreference.objects.
Sem
Has actor type is used to assign a type to an actor.
ActorType
- Static variable in class eu.newsreader.eventcoreference.objects.
Sem
EventType contains all resources that are used to classify Actors, e.g.
addChild(T)
- Method in class eu.newsreader.eventcoreference.ontology.
Tree
addChild(T)
- Method in class eu.newsreader.eventcoreference.ontology.
TreeNode
addCnt(Integer)
- Method in class eu.newsreader.eventcoreference.util.
LabelCount
addComment(String)
- Method in class eu.newsreader.eventcoreference.objects.
Triple
addConcept(KafSense)
- Method in class eu.newsreader.eventcoreference.objects.
SemObject
addConcepts(ArrayList<KafSense>)
- Method in class eu.newsreader.eventcoreference.objects.
SemObject
addCount(Integer)
- Method in class eu.newsreader.eventcoreference.objects.
PhraseCount
addDispersion(Integer)
- Method in class eu.newsreader.eventcoreference.util.
SemUtilObject
addFileList(File, HashMap<String, File>)
- Static method in class eu.newsreader.eventcoreference.util.
SplitTechCrunch
addInstances(Integer)
- Method in class eu.newsreader.eventcoreference.util.
Statistics.TotalStats
addJenaCompositeEvents(Dataset, Model, Model, HashMap<String, ArrayList<CompositeEvent>>, HashMap<String, SourceMeta>)
- Static method in class eu.newsreader.eventcoreference.output.
JenaSerialization
addJenaEntities(Model, ArrayList<SemObject>, ArrayList<SemObject>, ArrayList<SemObject>)
- Static method in class eu.newsreader.eventcoreference.output.
JenaSerialization
addLabelCount(LabelCount)
- Method in class eu.newsreader.eventcoreference.util.
SemUtilObject
addLabels(String)
- Method in class eu.newsreader.eventcoreference.util.
SemUtilObject
addLabels(Integer)
- Method in class eu.newsreader.eventcoreference.util.
Statistics.TotalStats
addLocationTarget(CorefTargetAgata)
- Method in class eu.newsreader.eventcoreference.objects.
AgataMention
addMention(NafMention)
- Method in class eu.newsreader.eventcoreference.objects.
SemRelation
addMentions(ArrayList<NafMention>)
- Method in class eu.newsreader.eventcoreference.objects.
SemRelation
addMentions(String)
- Method in class eu.newsreader.eventcoreference.objects.
Triple
addMentions(Integer)
- Method in class eu.newsreader.eventcoreference.util.
SemUtilObject
addMentions(Integer)
- Method in class eu.newsreader.eventcoreference.util.
Statistics.TotalStats
addMentionToFactRelations(NafMention, ArrayList<SemRelation>, String, String, String)
- Static method in class eu.newsreader.eventcoreference.util.
Util
all mentions are checked against the stored relations if the value and the event are already stored.
addMentionUri(NafMention)
- Method in class eu.newsreader.eventcoreference.objects.
SemObject
addMySemActor(SemActor)
- Method in class eu.newsreader.eventcoreference.objects.
CompositeEvent
addMySemFactRelation(SemRelation)
- Method in class eu.newsreader.eventcoreference.objects.
CompositeEvent
addMySemPlace(SemPlace)
- Method in class eu.newsreader.eventcoreference.objects.
CompositeEvent
addMySemRelation(SemRelation)
- Method in class eu.newsreader.eventcoreference.objects.
CompositeEvent
addMySemTime(SemTime)
- Method in class eu.newsreader.eventcoreference.objects.
CompositeEvent
addObject(ArrayList<SemObject>, SemObject)
- Static method in class eu.newsreader.eventcoreference.util.
Util
addParticipantTarget(CorefTargetAgata)
- Method in class eu.newsreader.eventcoreference.objects.
AgataMention
addPhraseCounts(String)
- Method in class eu.newsreader.eventcoreference.objects.
SemObject
addPhraseCountsForMentions(KafSaxParser)
- Method in class eu.newsreader.eventcoreference.objects.
SemObject
addPredicate(String)
- Method in class eu.newsreader.eventcoreference.objects.
SemRelation
addSingletons(Integer)
- Method in class eu.newsreader.eventcoreference.util.
Statistics.TotalStats
addSources(Integer)
- Method in class eu.newsreader.eventcoreference.util.
Statistics.TotalStats
addTarget(CorefTargetAgata)
- Method in class eu.newsreader.eventcoreference.objects.
CoRefSetAgata
addTermsId(String)
- Method in class eu.newsreader.eventcoreference.objects.
NafMention
addTimeTarget(CorefTargetAgata)
- Method in class eu.newsreader.eventcoreference.objects.
AgataMention
addToJenaDataSet(Dataset, Model)
- Method in class eu.newsreader.eventcoreference.objects.
SemRelation
addToJenaDataSet(Dataset, Model, HashMap<String, SourceMeta>)
- Method in class eu.newsreader.eventcoreference.objects.
SemRelation
addToJenaModel(Model, Resource)
- Method in class eu.newsreader.eventcoreference.objects.
SemObject
addToJenaModelDocTimeInstant(Model)
- Method in class eu.newsreader.eventcoreference.objects.
SemTime
addToJenaModelDocTimeInterval(Model)
- Method in class eu.newsreader.eventcoreference.objects.
SemTime
addToJenaModelOwlTimeDuration(Model)
- Method in class eu.newsreader.eventcoreference.objects.
OwlTime
addToJenaModelOwlTimeInstant(Model)
- Method in class eu.newsreader.eventcoreference.objects.
OwlTime
addToJenaModelTimeInstant(Model, OwlTime)
- Method in class eu.newsreader.eventcoreference.objects.
SemTime
addToJenaModelTimeInterval(Model)
- Method in class eu.newsreader.eventcoreference.objects.
SemTime
addTokensId(String)
- Method in class eu.newsreader.eventcoreference.objects.
NafMention
addTypes(String)
- Method in class eu.newsreader.eventcoreference.util.
SemUtilObject
AgataMention
- Class in
eu.newsreader.eventcoreference.objects
Created by IntelliJ IDEA.
AgataMention()
- Constructor for class eu.newsreader.eventcoreference.objects.
AgataMention
alphaNumericUri(String)
- Static method in class eu.newsreader.eventcoreference.util.
Util
AMOUNT
- Static variable in class eu.newsreader.eventcoreference.util.
EntityTypes
Anaphor
- Class in
eu.newsreader.eventcoreference.util
Created with IntelliJ IDEA.
Anaphor()
- Constructor for class eu.newsreader.eventcoreference.util.
Anaphor
anaphor(String, String)
- Static method in class eu.newsreader.eventcoreference.util.
Anaphor
Authority
- Static variable in class eu.newsreader.eventcoreference.objects.
Sem
Authorities are entities that state SEM properties.
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In this episode we’re going to learn and practice the essentials of writing tests - assertions.
Resources:


Dividing Line
You can control the styling and color.

solid line
double line
dashed line
dotted line
shadow line
gradient line

solid line
double line
dashed line
dotted line
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@@include('./src/components/_global/include-header.html')
@@include('./src/components/_global/include-loader.html') @@include('./src/components/_global/include-toggle-trigger.html')You can control the styling and color.

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EXAMPLE
This is an illustration of the generation of a non-gaussian random process based on a gaussian one. This method applies well for low skewness, and high kurtosis.
- First, the gaussian-distributed sample x is created.
- Then the non-gausian sample y is computed.
- Finally a verification procedure is carried out.
Contents
Input
clear all;close all;clc % Set the input N = 1e6; % number of data point m1 = 10; % mean of x m2 = 4; % variance of x x = m1+sqrt(m2).*randn(1,N); % random gaussian vector of mean m1 and variance m2 % Target: m3 = 0.5; % target skewness. NB: m3 is equal to 0 for a gaussian variable m4 = 4 ; % target kurtosis. NB: m4 is equal to 3 for a gaussian variable
Computation
compute the new random variable y that is non-gaussian.
[y] = MBHTM(x,m3,m4);
applicability condition is verified 4.49 >= m3^2 = 0.25 Equation solved. fsolve completed because the vector of function values is near zero as measured by the default value of the function tolerance, and the problem appears regular as measured by the gradient.
Verification
Let's compare m1, m2, m3, and m4 between x and y. In addition we see how it affects the distributions.
N.B. : The statistical toolbox may be required for the verification step, since I call the function "fitdist" inside "fitDistEtienne"
A good agreement between the computed and target m3 and m4 is observed.
% Gaussianity fit for x Nbin = 500; fitDistEtienne(x,Nbin,'normal'); set(gcf,'units','normalized','outerposition', [0.1 0.1 0.8 0.8]) set(gcf,'color','w') xlabel(' x '); ylabel('normalized pdf'); title(['m_1 = ',num2str(mean(x),2),... ', m_2 = ',num2str(var(x),2),... ', m_3 = ',num2str(skewness(x),2),... ', m_4 = ',num2str(kurtosis(x),2)]); set(findall(gcf,'-property','fontSize'),'fontsize',20) % Gaussianity fit for y Nbin = 500; fitDistEtienne(y,Nbin,'normal'); set(gcf,'units','normalized','outerposition', [0.1 0.1 0.8 0.8]) set(gcf,'color','w') xlabel(' y '); ylabel('normalized pdf'); title(['m_1 = ',num2str(mean(y),2),... ', m_2 = ',num2str(var(y),2),... ', m_3 = ',num2str(skewness(y),2),... ', m_4 = ',num2str(kurtosis(y),2)]); set(findall(gcf,'-property','fontSize'),'fontsize',20)


The self-diffusion coefficient of Ca 2+ in the interlayer of montmorillonite with different charge characteristics (×10 −10 m 2·s −1).


Hello {{ user.username|title }}, Below are all teams of
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We are rethoric question ran over her cheek When she reached the first hills of the Italic Mountains, she had a last view back on the skyline of her hometown Bookmarksgrove, the headline of Alphabet Village and the subline of her own road, the Line Lane.
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Contact Him
Phone Number: +50431729599
Email<EMAIL_ADDRESS>- Colonia Montefresco, 31 Calle, 14 Avenida A, 2da casa color azul, San Pedro Sula, Cortes
Computer Science degree at Universidad Católica de Honduras, 4 years of professional experience looking for showing his passion in everything he can do, combining perfectly these two areas.
Phone Number: +50431729599
Email<EMAIL_ADDRESS>2014
Freelancing El Android HN Blog
Freelance Web Developer
San Pedro Sula
Owning a blog has proven good, this blog on Android Technology has given a lot of opportunity to test new stuff on the front end side, and as well to brand something new on my country, something that has never been done. The blog now has new projections for this year and build a media brand and own two technologies blogs: one for iOS/Mac and continue with the Android Branch.
2012
San Services S de R. L.
Web Developer Front End
San Pedro Sula
San Services S. de R. L. is in charge of all systems and webpages of the company: Unique Vacations Limited from Bahamas to Miami, we asist with web development services and backend services on pages like www.sandals.com, www.beaches.com, www.grandpineapple.com and www.yourjamaicanvillas.com
Has participated on three major reengineering on sandals and beaches websites along with the Travel Agents Portal and worked as front end web developer; by taking the psd design sent and turn them into real web pages with often dynamic content using Coldfusion as midtier.
2012
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Application Developer - Genexus Analyst
San Pedro Sula
Collaborated with other team members on a cost calculating reports project using business logic reporting tools and Genexus 6 as backend platform.
2011
Universidad Católica de Honduras
Computer Science Degree
San Pedro Sula, Honduras
2002
Centro Técnico Hondureño Alemán
Electrician Technical High School Degree
San Pedro Sula, Honduras
2012
Sandals Website Reengineering
Front End Developer
2013
Resort Product Update
Front End Developer/ Coldfusion Developer
2013
Beaches Website Reengineering
Front End Developer/ Coldfusion Developer
2014
Wedding Designer Reengineering
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2014
Travel Agent Portal Reengineering
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Has also knowledge and experience on Agile Methodology, MVC Methodology, Firebase


A simple Comic book collection app designed by James Timberlake
Uses the expansive ComicVine API.
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Contents
Introduction
Corpus analysis is a form of text analysis which allows you to make comparisons between textual objects at a large scale (so-called ‘distant reading’). It allows us to see things that we don’t necessarily see when reading as humans. If you’ve got a collection of documents, you may want to find patterns of grammatical use, or frequently recurring phrases in your corpus. You also may want to find statistically likely and/or unlikely phrases for a particular author or kind of text, particular kinds of grammatical structures or a lot of examples of a particular concept across a large number of documents in context. Corpus analysis is especially useful for testing intuitions about texts and/or triangulating results from other digital methods.
By the end of this tutorial, you will be able to:
- create/download a corpus of texts
- conduct a keyword-in-context search
- identify patterns surrounding a particular word
- use more specific search queries
- look at statistically significant differences between corpora
- make multi-modal comparisons using corpus lingiustic methods
You have done this sort of thing before, if you have ever…
- searched in a PDF or a word doc for all examples a specific term
- Used Voyant Tools for looking at patterns in one text
- Followed Programming Historian’s Introduction to Python tutorials
In many ways Voyant is a gateway into conducting more sophisticated, replicable analysis, as the DIY aesthetic of Python or R scripting may not appeal to everyone. AntConc fills this void by being a standalone software package for linguistic analysis of texts, freely available for Windows, Mac OS, and Linux and is highly maintained by its creator, Laurence Anthony. There are other concordance software packages available, but it is freely available across platforms and very well maintained. See the concordance bibliography for other resources.
This tutorial explores several different ways to approach a corpus of texts. It’s important to note that corpus linguistic approaches are rarely, if ever, a one-size-fits all affair. So, as you go through each step, it’s worth thinking about what you’re doing and how it can help you answer a specific question with your data. Although I present this tutorial in a building-block approach of ‘do this then that to achieve x’, it’s not always necessary to follow the exact order outlined here. This lessons provides an outline of some of the methods available, rather than a recipe for success.
Tutorial downloads
-
Software:AntConc. Unzip the download if necessary, and launch the application. Screen shots below may vary slightly from the version you have (and by operationg system, of course), but the procedures are more or less the same across platforms and recent versions of AntConc. This tutorial is written with a (much older) version of AntConc in mind, as I find it easier to use in an introductory context. You are welcome to use the most recent version, but if you wish to follow along with the screenshots provided, you can download the version used here, version 3.2.4.
-
Sample Corpus: Download the zip file of movie reviews.
A broad outline of this tutorial:
- Working with plain text files
- The AntConc user interface, loading corpora
- Keyword-in-context searching
- Advanced keyword-in-context searching
- Collocates and word lists
- Comparing corpora
- Discussion: Making meaningful comparisons
- Further resources
Working with Plain Text Files
- Antconc works only with plain-text files with the file appendix .txt (eg Hamlet.txt).
- Antconc will not read .doc, .docx, .pdf, files. You will need to convert these into .txt files.
- It will read XML files that are saved as .txt files (it’s OK if you don’t know what an XML file is).
Visit your favorite website for news, and navigate to a news article (doesn’t matter which one, as long as it is primarily text). Highlight all text in the article (header, byline, etc), and right-click “copy”.
Open a text editor such as Notepad (on Windows) or TextEdit (on Mac) and paste in your text.
Other free options for text editors include Notepad++ (Windows) or TextWrangler (Mac), which offer more advanced features, and are especially good for doing a lot of text clean-up. By text clean-up, I mean removing extratextual information such as “boilerplate”, which appears regularly throughout. If you keep this information, it’s going to throw your data off; text analysis software will address these words in word counts, statistical analyses, and lexical relationships. For example, you might want to remove standard headers and footers which will appear on every page. Please see “Cleaning Data with OpenRefine” for more on how to automate this task. On smaller corpora it may be more feasible to do this yourself, plus you’ll get a much better sense of your corpus this way.
Save the article as a .txt file to the desktop. You may want to do some follow-up text cleanup on other information, such as author by-line or title (remove them, then save the file again.) Remember that anything you leave in the text file can and will be addressed by text analysis software.
Go to your desktop and check to see you can find your text file.
Repeating this a lot is how you would build a corpus of plain text files; this process is called corpus construction, which very often involves addressing questions of sampling, representativeness and organization. Remember, each file you want to use in your corpus _must_ be a plain text file for Antconc to use it. It is customary to name files with the .txt suffix so that you know what kind of file it is.
As you might imagine, it can be rather tedious to build up a substantial corpus one file at a time, especially if you intend to process a large set of documents. It is very common, therefore, to use webscraping (using a small program to automatically grab files from the web for you) to construct your corpus. To learn more about the concepts and techniques for webscraping, see the Programming Historian tutorials scraping with Beautiful Soup and automatic downloading with wget. Rather than build a corpus one document at a time, we’re going to use a prepared corpus of positive and negative movie reviews, borrowed from the Natural Language Processing Toolkit. The NLTK movie review corpus has 2000 reviews, organized by positive and negative outcomes; today we will be addressing a small subset of them (200 positive, 200 negative).
Corpus construction is a subfield in its own right. Please see Representativeness in Corpus Design,” Literary and Linguistic Computing, 8 (4): 243-257 and Developing Linguistic Corpora: a Guide to Good Practice for more information.
Getting Started with AntConc: The AntConc user interface, loading corpora
When AntConc launches, it will look like this.
On the left-hand side, there is a window to see all corpus files loaded (which we’ll use momentarily).
There are 7 tabs across the top: Concordance: This will show you what’s known as a Keyword in Context view (abbreviated KWIC, more on this in a minute), using the search bar below it.  File View: This will show you a full file view for larger context of a result. Clusters: This view shows you words which very frequently appear together. Collocates: Clusters show us words which _definitely _appear together in a corpus; collocates show words which are statistically likely to appear together. Word list: All the words in your corpus. Keyword List: This will show comparisons between two corpora.
As an introduction, this tutortial barely scratches the surface of what you can do with AntConc. We will focus on the Concordance, Collocates, Keywords, and Word List functions.
Loading Corpora
Like opening a file elsewhere, we’re going to start with File > Open, but instead of opening just ONE file we want to open the directory of all our files. AntConc allows you to open entire directories, so if you’re comfortable with this concept, you can just open the folder ‘all reviews’ and jump to Basic Analysis, below
Remember we’ve put our files on the desktop, so navigate there in the dropdown menu.
From the Desktop you want to navigate to our folder “movie reviews from nltk”:
First you will select “Negative Reviews” and hit OK. 200 texts should load in the lefthand column Corpus Files – watch the Total No. box!
Then you’re going to repeat the process to load the folder “Positive Reviews”. You should now have 400 texts in the Corpus Files column.
Searching Keywords in Context
Start with a basic search
One of the things corpus tools like Antconc are very good at are finding patterns in language which we have a hard time identifying as readers. Small boring words like the, I, he, she, a, an, is, have, will are especially difficult to keep track of as readers, because they’re so common, but computers happen to be very good at them. These words are called function words, though they commonly known as ‘stopwords’ in digital humanities; they are often very distinct measures of authorial and generic style. As a result, they can be quite powerful search terms on their own or when combined with more content-driven terms, helping the researcher identify patterns they may not have been aware of previously.
In the search box at the bottom, type the and click “start”. The Concordance view will show you every time the word the appears in our corpus of movie reviews, and some context for it. This is called a “Key Words in Context” viewer.
(14618 times, according to the Concordance Hits box in the bottom centre.)
As above, the KWIC list is a good way to start looking for patterns. Even though it’s still a lot of information, what kinds of words appear near “the”?
Try a similar search for “a”. Both “a” and “the” are articles, but one is a definite article and one an indefinite article - and the results you get will be illustrative of that.
Now that you’re comfortable with looking at a KWIC line, try doing it again with “shot”: this will produce examples of both shot the noun (‘line up the shot’) and the verb ‘this scene was shot carefully’)
What do you see? I understand this can be a difficult to read way of identifiying patterns. Try pressing the yellow “sort” button. What happens now?
(This might be easier to read!) You can adjust the way AntConc sorts information by changing the parameters in the red circle: L corresponds with ‘left’ and R corresponds with ‘right’; you can extend these up to ±5 in either direction. The default is 1 left, 2 right, 3 right, but you can change that to search 3 left, 2 left, 1 right (to get phrases and/or trigrams that end in the search term in question, for example) by clicking the arrow buttons up or down. If you don’t want to include a sorting option you can skip it (as in the default: 1L, 2R, 3R) or include it as a 0. Less linear sorting practices are available, such as 4 left, 3 right, 5 right, which includes a lot of other contextual information. These parameters can be slow to respond, but be patient. If you’re not sure what the resulting search is, just press ‘sort’ to see what’s happened and adjust accordingly.
Search Operators
The * operator (wildcard)
The * operator (which finds zero or more characters) can help, for instance, find both the singular and the plural forms of nouns.
Task: Search for qualit*, then sort this search. What tends to precede and follow quality & qualities? (Hint: they’re different words, and have different contexts. Again- look for patterns in usage using the KWIC!)
For a full list of available wildcard operators and what they mean, go to Global Settings > Wildcard Settings.
To find out the difference between * and ?, search for th*n and th?n. These two search queries look very similiar, but show very different results.
The ? operator is more specific than the * operator: wom?n – both women and woman m?n – man and men, but also min contrast to m*n: not helpful, because you’ll get mean, melon, etc.
Task: Compare these two searches: wom?n and m?n
- sort each search in a meaningful way (eg. by search term then 1L then 2L)
- File > Save output to text file (& append with .txt.
HINT: During the course of exploring in your research, you may generate many such files for reference; it’s helpful to use descriptive filenames that describe what’s in them (such as “wom?n-results.text”, not “antconc_results.txt”).
And now you can open the plain text file in your text editor; you might have to widen the application window to make it readable:
Do this for each of the two searches and then look at the two text files side by side. What do you notice?
The | operator (“or”)
Task: Search on she|he.
Now search for these separately: how many instances of she vs he?
There are many fewer instances of she – why? That’s a research question! A good follow-up questions might be to sort the she|he search for patterns, and look to see if particular verbs follow each.
Task: Practice searching a word of your choice, sorting in different ways, using wildcard(s), and finally exporting. Guiding focus question here: what kinds of patterns do you see? Can you explain them?
Collocates and word lists
Having looked at the KWIC lines for patterns, don’t you wish there was a way for the computer to give you a list of words which appear most frequently in company with your keyword?
Good news - there is a way to get this information, and it’s available from the Collocates tab. Click that, and AntConc will tell you it needs to create a word list. Hit OK; it will do it automatically.
NOTE: You will only get this notice when you haven’t created a word list yet.
Try generating collocates for she.
The unsorted results will seem to start with function words (words that build phrases) then go down to content words (words that build meaning)– these small boring words are the most frequent words in English, which are largely phrase builders. Later versions of AntConc often include the search term as the first hit, presumably because the search term you are looking for shows up in the text and we are looking for words which are likely to appear with this word.
Some people might want to remove these small words by using a stopword list; this is a common step in topic modelling. Personally I don’t encourage this practice because addressing highly-frequent words is where computers shine! As readers we tend not to notice them very much. Computers, especially software like Antconc, can show us where these words do and do not appear and that can be quite interesting, especially in very large collections of text - as explored earlier in the tutorial, with the, a, she and he.
Additionally you may have a single letter ‘s’ appear, quite high as well - that represents the possessive ’s (the apostrophe won’t be counted), but AntConc considers that s indicative of another word. Another example of this is ‘t appearing with do, as they contract as don’t. Because these so commonly appear together, this makes them highly likely collocates.
Task: Generate collocates for m?n and wom?n. Now sort them by frequency to 1L. This tells us about what makes a man or woman ‘movie-worthy’: – women have to be ‘beautiful’ or ‘pregnant’ or ‘sophisticated’ – men have to be somehow outside the norm – ‘holy’ or ‘black’ or ‘old’
This is not necessarily telling us about the movies but about the way those movies are written about in reviews, and can lead us to ask more nuanced questions, like “How are women in romantic comedies described in reviews written by men compared to those written by women?”
Comparing corpora
One of the most powerful types of analysis is comparing your corpus to a larger reference corpus.
I’ve pulled out reviews of movies with which Steven Spielberg is associated (as director or producer). We can compare them to a reference corpus of movies by a range of directors.
Be sure to think carefully about what a reference corpus for your own research might look like (eg. a study of Agatha Christie’s language in her later years would work nicely as an analysis corpus for comparison to a reference corpus of all her novels). Remember, again, that corpus construction is a subfield in its own right.
Settings > Tool preferences > Keyword List Under ‘Reference Corpus’ make sure “Use raw files” is checked Add Directory > open the folder containing the files that make up the reference corpus Ensure you have a whole list of files!
Hit Load (& wait …) then once the ‘Loaded’ box is checked, hit Apply. You can also opt to swap reference corpus & main files (SWAP REF/MAIN FILES). It is worth looking at what both results show.
If you’re using a later version of AntConc, the Swap Ref/Main files option may be marked as ‘swap with target files’, and you will need to ensure the target and reference corpora have been loaded (press the load button each time you upload, or swap, a corpus).
In Keyword List, just hit Start (with nothing typed in the search box). If you’ve just swapped the reference corpus and the target files, you may be prompted to create a new word list before AntConc will calculate the keywords. We see a list of Keywords that have words that are much more “unusual” – more statistically unexpected – in the corpus we are looking at when compared to the reference corpus.
> Keyness: this is the frequency of a word in the text when compared with its frequency in a reference corpus, “such that the statistical probability as computed by an appropriate procedure is smaller than or equal to a p value specified by the user.” – taken from here.) For those interested in the statistical details, see the section on keyness on p7 of Laurence Anthony’s readme file.
What are our keywords?
Discussion: Making meaningful comparisons
Keep in mind that the way your organize your text files makes a difference to the kinds of questions you can ask and the kinds of results you will get. Remember that we are comparing ‘negative’ and ‘positive’ reviews quite flatly here. You could, for instance, make other comparisons with different subsets of reviews, which yield very different kinds of questions.
Of course, the files you put in your corpus will shape your results. Again, the question of representativeness and sampling are highly relevant here – it’s not always necessary or even ideal to use all of a dataset at once, even if you do have it. At this juncture, it’s really worth interrogating how these methods help produce research questions.
When thinking about how movie reviews work as a genre, you could consider, for example…
- Movie reviews vs music reviews
- Movie reviews vs book reviews
- Movie reviews vs news articles about sport
- Movie reviews vs news articles in general
Each of these comparisons will tell you something different, and can produce different research questions, such as:
- How are movie reviews different than other kinds of media reviews?
- How are movie reviews different than other kinds of published writing?
- How do movie reviews compare to other specific kinds of writing, such as sport writing?
- How do movie reviews have in common with music reviews?
And of course you could flip those questions to make further research questions:
- How are book reviews different to movie reviews?
- How are music reviews different than movie reviews?
- What do published newspaper articles have in common?
- How are movie reviews similar to other kinds of published writing?
In summary: it’s worth thinking about:
- Why you might want to compare two corpora
- What kinds of queries make meaningful research questions
- Principles of corpora construction: sampling & ensuring you can get something representative
Further resources for this tutorial
A short bibliography on corpus linguistics. A more step-by-step version of this tutorial, assuming no computer knowledge


Lecture 41
Qi Wang, Department of Statistics
Dec 5, 2018
| Monday, Dec 1, 2018 | Tuesday, Dec 2, 2018 |
|---|---|
| 4:00pm - 5:30pm Will | 10:30pm - 12:00pm Ce-Ce |
| 5:30pm - 7:00pm Tim | 12:00pm - 1:30pm Jiapeng |
| 1:30pm - 3:00pm Yan | |
| 3:00pm - 4:30pm Qi | |
| 4:30pm - 6:00pm Will |
Steps to finding the sample score if you are given a probability and know $X \sim N(\mu, \sigma)$
Boxplot is a graphic depiction of the 5 number summary
To draw a modified boxplot, Step 1, 2, 3 are the same, BUT we indicate the outliers with a $o$ or a $\star$. Then draw the line from the ends of the box ot the highest or lowest data point that is NOT an outlier. Most software generate boxplots are modified boxplots.
Test if there is a relationship between two qualitative (categorical) variables via Chi-Square($\chi^2$) Hypothesis test


About Me
Hello, my name is Steven Stefanov and I am learning to become a full-stack web developer at Columbia University Coding Bootcamp. I create simple, clean, and impactful user experiences. I take on projects of all sizes - from portfolio websites to e-commerce shops. Please do say hello - I look forward to hearing about your project!
Projects
NBA Teams
GitHub LinkBikr Marketplace
GitHub LinkWorkday Scheduler
GitHub LinkWeather App
GitHub Link


It's really fun to explore and use the new technologies.
Using a new technology and making something which is merely impossible is an Art. I hope, I have done it appropriately
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AUGMENTED BOT DEVELOPER INTERFACE DESIGNER.
In a mission of exploring the newest technologies and creating something which looks Impossible.


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A Genre Savvy character knows what's going to happen next when the Genre Blind character does something stupid. So they voice that outcome and count down.
"Three... two... one..."
The outcome happens exactly when the countdown ends.
Related to Exact Time to Failure and Improbably Predictable. Not to be confused with the gameshow 321 or the Class 321 Electric Multiple Units. See On Three for characters synchronizing a joint action.
Examples:
open/close all folders
Comic Strips
- Dilbert proposes adding a battery backup to a company product. Hearing no immediate response, he counts in his head until the Pointy-Haired Boss suggests it as his own idea — whereupon Dilbert points out that the product doesn't use batteries.
Fan Works
- The Heart Trilogy: In the 17th chapter of Heart of Ashes, Kathryn goes to explore the abandoned fortress she and Smaug are inhabiting while the control freak of a dragon is away. When she hears him returning, she counts with her fingers the precise moment he discovers her missing from the "den" and roars her name so loud it can be heard in the entire fortress.
Films — Animation
- On the first Ice Age movie, Manny and Diego do this in unison as Sid sits in a geyser, with Manny mentioning how faithful it is.
- The Lion King II: Simba's Pride: Kovu does this. He is counting down the time until Kiara tries to pounce on him.
- Capper in My Little Pony: The Movie (2017) does a silent one before his Bavarian Firedrill scam succeeds on the Storm King's guards.
- On Anastasia, Dimitri counts for the moment Anastasia changes her mind and calls him back.
Films — Live-Action
- The Joker in The Dark Knight, waiting for the bombs to go off at the end. Subverted that time.
- In The Goonies, Mikey passes the framed treasure map to Chunk because he knows Chunk will smash it open by accident which will give them an excuse to scrutinize it. Mikey even counts down to the crash.
Live-Action TV
- Married... with Children:
[Al has gone outside to fix the roof]
Peggy: You know how you are always complaining that your father never does anything with the family? Well, just watch that window and your father has a big surprise for us. Right about now — three, two, one...
[Al screams and falls past the window, family laughs and claps] - Sports Night episode "Quo Vadimus":
[Isaac has told Dana about a new bid from Quo Vadimus]
Dana Whitaker: Isaac doesn't trust that when he tells me something, I can be cool. He thinks it's gonna spread around and the information'll get all twisted and I'm going to show him he's wrong.
Isaac Jaffe: [while in his office] Three, two, one...
Jeremy Goodwin: Isaac, I don't know if you heard. Six this morning there was a bid from an Italian airline called Platypus. - Out Of This World (1987): When the uncle has been wearing some Love Potion in the form of cologne, and is about to take a swim, the daughter and mother count down for when the instant harem will abandon him.
- Double subverted in Cheers episode "Don't Paint Your Chickens". A beautiful woman walks into the bar while Sam is in his office, and Carla does the countdown. It's as if the show is admitting how predictable it is, but Sam is two seconds late. He comes out, asking, "Where is she"?
Carla: He's slowing down, but he's still got it.
Sam: Gimme a break, Carla. There's lead pipes down there. Interferes with the radar. - By Community's second Christmas episode, the glee club have become so predictable that Annie can count down to their "hip-hop remix" of carols.
- Stargate SG-1: In the episode "Window of Opportunity", O'Neill and Teal'c are stuck in a "Groundhog Day" Loop. Since he knows exactly what is going to happen, at one point Jack can be seen counting from three on his fingers, and right on cue Daniel calls him in the hallway to talk to him.
- Nathan Ford does a non-verbal version of this when on Leverage when negotiating with a Russian mobster. The mobster has one of her people highlight Nate with the tell-tale red dot of a Laser Sight. Nate looks at it, uninterested, then counts down with his fingers. The dot suddenly shifts from him to the mobster, because Parker had gotten to the sniper exactly as Nate had intended, and incapacitated them.
- In a first-season episode of Babylon 5, Sinclair and Garibaldi prank Ivanova into thinking that she has slept through breakfast. As she bolts for the command deck, Michael starts counting down: "Three... two... one." "Garibaldi!"
Video Games
- One of the ODSTs in Halo 3: ODST does this with explosive charges that he set, as they fly away.
- Captain Briggs in Limbo of the Lost, in circumstances that are truly indescribable.
- Heard in most Racing Games, where it's used to kick off a race.
Web Animation
- MLP Analysis:
- In "The Fairy Fountain", Dr. Wolf counts down from three after Silver Quill calls Lightning Bliss "cute", knowing it will annoy her. Right on cue, this is followed by an explosion and Silver Quill is on fire.
- TF2 Analysis: In "Mission Unpossible", when Goldenfox rushes in blindly into the teleporter to try saving Keyframe, Voice of Reason lower his head and fatalistically counts down from three... cue explosion, followed by Fox sent flying away screaming and crashing.
Keyframe: [through radio] You know he kind of deserved it for calling me "Schmoopy-Doo". Urk.
Web Comics
- Home On The Strange, with the drinking game.
- Times Like This: Two instances.
- In El Goonish Shive, Sarah does this in her head when Elliot forgets his uniform.
- The Order of the Stick: In "Unfinished Business", Roy Greenhilt counts down from three while the party rests, fully expecting a visit from the ghost of his dead father.
Eugene Greenhilt: What, I'm that predictable now?
Web Original
- Often used in LOLCats captions.
Web Videos
- Derrick Comedy has a sketch with a time-traveling Thomas Jefferson. One of his buddies relates a story from 9/11, where Jefferson showed off by counting down to the exact moment of the terrorist attack.
- Bronies React: At the beginning of the review for the Season 8 Premiere, Dustykatt states "Movie recap in three... two... one..."
- The Nostalgia Critic: In the review for Blade II, it is a running gag for Guillermo del Toro to pitch some (silly) new idea for a movie, only to give up on it a few seconds later. When suggesting a Blade and The Powerpuff Girls crossover, the Critic counts down from three on his fingers, and Del Toro says "Maybe not..."
Western Animation
- Bubbles in The Powerpuff Girls, during an episode in which the girls try to defeat a particularly tough monster in their own ways.
- The Adventures of Jimmy Neutron: Boy Genius had an episode called "Send In The Clones", where Jimmy created clones of himself to try to get everything he had to do finished in one day. One of the clones, of course, is evil, and does this trope under his breath shortly after swapping the signs on a public restroom.
- In Superman: The Animated Series, Gsptlsnz counts down how many seconds it takes Superman to defeat Mxyzptlk. She actually overestimated. She didn't even get to down to one.
- In an episode of Garfield and Friends, Garfield does this when Jon has walked out of the house without pants. Slightly inverted as he counts up instead of down. In another episode he does to see how long it takes for Jon to realize that Garfield accidentally brought a baby home.
- My Little Pony: Friendship Is Magic:
- In "Celestial Advice", during Twilight's third fantasy vision for Starlight's future, Spike realizes it will take the same pattern as the previous two and counts down to the moment Twilight starts to panic again.
- In "To Change a Changeling", Starlight reports to Thorax that Pharynx has left the hive and all other Changelings begin cheering. Trixie just says "wait for it," and Starlight finishes that the maulwurf is on its way to the hive. When the Changelings panic Trixie just says "told you." Justified as the exact same thing happened moments ago outside the hive.
- BoJack Horseman has Todd and BoJack watch the Horsin' Around Christmas special. When Sarah Lynn realizes Santa didn't bring her the gift she wanted, Ethan started the countdown to the waterworks... starting at 50, which BoJack fast-forwards to this.
- Danny Phantom: In "Kindred Spirits", Sam and Tucker repeatedly get in trouble for the collateral damage caused by Danny fighting a ghost. At one point, after the cafeteria gets trashed, they both count down to when Mr. Lancer will angrily burst in.
- DuckTales (2017): In "The House of the Lucky Gander!", Scrooge makes a bet with Liu Hai, a spirit who is feeding off of Gladstone Gander's luck, that Donald can beat Gladstone to get him to set him free. After Donald manages to win, Scrooge reminds him that if Donald bested the luckiest duck in the world, he should be his new prisoner.
Gladstone: The kid's not wrong, Uncle McDunkle? What do we do?Scrooge: Three... two... one... (makes a clear path)(Donald gets tossed out by an emaciated Liu Hai)Liu Hai: His luck! It's awful! So awful!
- In Phineas and Ferb, Major Monogram tries to convince Dr. Doofenshmirtz to team up with him to take down Carl.
Dr. Doofensmirtz: No way! With Perry the Platypus out of the way, that give me an opening to take over the entire entire Tri-State Area!Major Monogram: Not if Carl takes it over first.(Beat)Major Monogram: Let it sink in... Two... Three...


WITNESS LIST
Agriculture, Rural Affairs & Homeland Security
May 19, 2014 9:00 AM
Ammonium Nitrate
ON:
Connealy, Chris Texas State Fire Marshal (also providing written testimony) (Texas
Department of Insurance), Austin, TX
Dippel, Donnie President (Texas Ag Industries Association), La Grange, TX
Henry, Hoyt License Manager (Department of State Health Services), Austin, TX
Herrman, Tim State Chemist and Director (also providing written testimony) (Office of the
Texas State Chemist/Texas A&M Agrilife Research), College Station, TX
Muska, Tommy Mayor (City of West, Texas), West, TX
Perkins, Kathryn Assistant Commissioner, Regulatory Services (also providing written
testimony) (Department of State Health Services), Austin, TX
Rathgeber, Julia Commissioner of Insurance (Texas Department of Insurance), Austin, TX
Sera, Gary Director (also providing written testimony) (TX A&M Engineering Ext Service
(TEEX)), College Station, TX
Providing written testimony:
ON:
Wendell, Ware Director of Legislative Affairs (Texas Watch), Austin, TX
Disaster Recovery
ON:
Fithian, Lisa (also providing written testimony) (Travis Austin Recovery Group), Austin,
TX
Foster, Erin Citizen (Self; Halloween 2013 Flood Survivors), Austin, TX
Hrncir, John Government Relations Officer (City of Austin), Austin, TX
Kidd, Nim Assistant Director, Texas Division of Emergency Management (Texas
Department of Public Safety), Austin, TX
McCraw, Steven C. Director (Texas Department of Public Safety), Austin, TX
Muska, Tommy Mayor (City of West, Texas), West, TX
Vargas, Leonor Social Worker, Director of Mendez Family Resource Center (Halloween
Flood Survivors), Austin, TX


We developed the clues R package to provide functions for automatically estimating the number of clusters and getting the final cluster partition without any input parameter except the stopping rule for convergence. The package also provides functions to evaluate and compare the performances of partitions of a data set both numerically and graphically.
| Version: | 0.5.9 |
| Depends: | R (≥ 3.1.0), stats, utils, graphics |
| Suggests: | cluster |
| Published: | 2016-10-14 |
| Author: | Fang Chang [aut, ctb], Weiliang Qiu [aut, cre], Vincent Carey [aut, ctb], Ruben H. Zamar [aut, ctb], Ross Lazarus [aut, ctb], Xiaogang Wang [aut, ctb] |
| Maintainer: | Weiliang Qiu <stwxq at channing.harvard.edu> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| Citation: | clues citation info |
| Materials: | NEWS |
| CRAN checks: | clues results |
| Reference manual: | clues.pdf |
| Package source: | clues_0.5.9.tar.gz |
| Windows binaries: | r-devel: clues_0.5.9.zip, r-release: clues_0.5.9.zip, r-oldrel: clues_0.5.9.zip |
| OS X binaries: | r-release: clues_0.5.9.tgz, r-oldrel: clues_0.5.9.tgz |
| Old sources: | clues archive |
| Reverse depends: | kpodclustr |
| Reverse imports: | smartR |
Please use the canonical form https://CRAN.R-project.org/package=clues to link to this page.


BELLE DU JOUR A film review by James Berardinelli Copyright 1995 James Berardinelli
RATING (0 TO 10): 7.9
France, 1967 U.S. Availability: re-release begins 6/95 Running Length: 1:40 MPAA Classification: No MPAA Rating (Discrete nudity, mature themes) Theatrical Aspect Ratio: 1.85:1
Cast: Catherine Deneuve, Jean Sorel, Michel Piccoli, Genevieve Page, Pierre Clementi Director: Luis Bunuel Producers: Raymond and Robert Hakim Screenplay: Luis Bunuel and Jean-Claude Carriere Cinematography: Sacha Vierny U.S. Distributor: Miramax Zoe
It's difficult to view BELLE DU JOUR in 1995 and get a balanced historical perspective on the film, which was originally released twenty-eight years ago. Recently, there have been a slew of productions probing issues of identity and double lives. Indeed, this has become a favorite province of independent film makers, probably because it's such a rich field. However, back in 1967, the path was less frequently trodden, and Luis Bunuel's serious-yet-satirical picture helped pave the way for many stories yet to come.
Today, BELLE DU JOUR is as effective as ever. With a ravishing Catherine Deneuve in the title role, this film is a study of contrasts. The main character is at once glacial yet erotic -- a wife by night and prostitute by day. She is two different people in one body, but Bunuel underlines the truth that no person can effectively compartmentalize facets of their life. Crossovers are inevitable, and the harder we try to repress one segment of who we are, the more likely it is to assert itself -- forcefully.
Bunuel also pokes fun at the morals of society by depicting what goes on behind closed doors at the brothel where Deneuve's Severine spends her afternoons. An internationally-known gynecologist begs to be punished. A businessman frolics with three girls at one time. Then there are Severine's erotic fantasies, which easily become entangled with her surreal secondary life. In fact, her misguided relationship with a gangster (Pierre Clementi) arises out of a hidden desire to flirt with danger.
 He loves her, but wishes she would be more sexually attentive. Meanwhile, a friend (Michel Piccoli) pursues Severine tirelessly -- until he learns her secret. At that point, the chase loses its allure. After all, where's the fun if the "forbidden fruit" isn't quite so forbidden?
Much of the film works because of the capable acting of Deneuve. The scenes where she first approaches the brothel, tentative and uncertain yet undeniably intrigued, are perfectly realized. Deneuve's performance allows the viewer to feel -- not merely sense -- the strange mixture of seduction and repulsion that prostitution holds for a woman in her position. And, as Severine's sexual liberation takes place, Deneuve's beauty is transformed from cool and aloof to coy and playful.
Because producers Raymond and Robert Hakim were unwilling to re- release this film in theaters or on video, BELLE DU JOUR has not been seen for over a quarter of a century. Now, with the rights acquired from the Hakims' estate, Miramax has chosen to use this classic to launch their new subsidiary distributor of French fare, Miramax Zoe. Recognizing how greatly admired the film is (directors from Alfred Hitchcock to Martin Scorsese have sung Bunuel's praise), Miramax has therefore given a new generation this opportunity to see a memorable feature from decades past.
- James Berardinelli<EMAIL_ADDRESS>The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
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Related links: index of all rec.arts.movies.reviews reviews


view 1
- Here is some content
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Here I want to add a note
I have so much remarks to do on this slide.
I have so much remarks to do on this slide.
I have so much remarks to do on this slide.
I have so much remarks to do on this slide.
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And I can do it everywhere I want
Remember that: blablabla
- Here is some content
- Go to slide 2


This film is a brilliant dystopia, depicting a nightmare world in which
arena football has become the national pasttime.

OK. Stop. "Starship Troopers" is based -- I use this word loosely -- on Robert Heinlein's novel of the same name. I'm not sure about the history of science fiction, but this novel may have been the first to coin the phrase "bug hunt," which we see most famously in "Aliens." It's combat science fiction, centering on the actions of soldiers from the future, who are recognizably types from today, only with bigger, fancier guns and spiffier uniforms.
The film picks up the plot points and the names: there's a big battle, where the humans get their asses kick. Then there are other battles, and finally, this "brain bug" is captured at the end, giving the humans the key to victory. Woo hoo!
The film, however, is just plain empty. It skips through the novel's plot points, but there's very little behind it beyond a massive special effects budget -- the animated bugs make Jurassic Park's dinos look like something we saw in King Kong (no, wait, they were things we saw in King Kong) -- and the soap opera antics of the gruff foot soldier, the dashing starship pilot (who, apparently, is named "Ace"), the woman that they love, and this other woman who pines for the GFS.
The heart of the novel is its moral vision. You may disagree strongly with what Heinlein thinks, but you can't say that this novel isn't animated by his moral code. The code is expressed in the trooper's actions, his progress through the ranks, the lectures he receives, the conversations he overhears and the implicit comparison between bugs and humans.
The film's fatal flaw is that it is entirely lacking in a moral vision. At most, it makes very nodding, very satirical references to it. No code or vision powers the film; all we have are special effects and soap opera. And when the protagonist finally declares that he understands the morality of this universe, that he knows the difference between "citizens" and "civilians", it's merely a point of melodrama, a tying of plot threads, and a reference to a question he couldn't answer previously. There's no conviction.
But, the one positive thing about Starship Troopers, the movie, in the future, will become fodder for MST3K. To wit:
1) Where else will we "Doogie Howser, Psychic Nazi"? Crow T. Robot will have been saying, "Our minds are linked, your thoughts are my thoughts..." at one point. You'll know when.
2) The continuing mis-casting of Michael Ironside, who, once again, plays the gruff professional soldier. I'm sure he can play a caring, sensitive role, if only they'd let him. Well, maybe not.
3) The insistence of all the troopers to get in real close to the bugs, despite the fact that they have guns, and the bugs have claws. It's sort of like those bad action movies, where the villan, who has a big gun, decides that, yes, getting really close to Steven Segal is _no problem_ -- he can't kick my gun away!
[Actually, this leads to one of the major deviations from the book -- these movie bugs apparently haven't really developed technology. In the novel, there are bugs with ray guns, who pilot space ships, and they're clearly intelligent and scheming. Humanity has an equal opponent, and you can think of bug society as contrast and comparison to human society. I find this scarier, in a way, than the must-invent-wheel-must-discover-fire bugs they have in the movie.]
4) 24th Century Technology, in which they've invented a new form of information storage that looks remarkably like carbon copy.
5) 24th Century Music, which looks remarkably like 1980s music, but with less hair.
6) Tug-o-war with the brain bug. Humanity has apparently lost the ability to manufacture the "bulldozer", and must resort to "Ten Commandments"-like teams of rope-pullers.
7) Arena football. Played with a silver football. 'Nuff said.
I have to credit the film with one good thing, besides the special effects. There was a nice reference to Fritz Lang's "Metropolis" at the beginning.
--
The Internet: an empirical test of the idea that a million monkeys banging on a million keyboards can produce Shakespeare.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Which animal they'd like to learn about.
Choose one of the three animals from the dropdown:
You will have to pay $turtles Turtles are ectotherms—animals commonly called cold-blooded—meaning that their internal temperature varies according to the ambient environment.
You will have to pay $snakes pLiving snakes are found on every continent except Antarctica, and on most smaller land masses.
You will have to pay $ Adult insects typically move about by walking, flying, or sometimes swimming. As it allows for rapid yet stable movement.


The Robotix Club of NIT Raipur is the perfect combination of innovators,
contributors and experts in the field of Robotics. The club has been inspiring minds ever since its
inception in 2014.
The foundation of Robotix Club was laid by a group of enthusiastic and ardent students with a vision
to promote the versatile field of robotics and it’s ever growing application in present time.
We make sure that every student seeking the knowledge gets it .The club is guided by our esteemed
faculty In charge Dr. Rajesh Doriya (Department of Information Technology) who makes sure there is
proper functioning of the club.
Robotix Club NITRR strives to develop technological skills in the diverse field
of mechatronics and robotics by transcending the theoretical knowledge into live application and
providing live simple yet creative solution for real world complex problems.
The club's focus has always been on student specific events and workshops to increase the reach
of robotics in the college. Major part of the club has been involved with students as well as
teachers working together as a cohesive unit.
Kick-starting its journey with a workshop on manual robotics to now providing
insight to most advanced topics like Artificial Intelligence.
The club has been through a remarkable journey and it continues to inspire the students to
explore the discipline of Robotics.
The club conducts regular workshops and competitions to advance robotics in college.
The workshops include free workshops as well as paid workshops where students get to know
everything, from the basics of robotics to advance mechanisms of robotics.


Line Chart
Using the line chart below, compare the progress of various countries throughout the pandemic! Begin by selecting your countries of interest using the checkboxes in the table below. From there, you can select the variable that you are interested in and the window of dates you would like to view.


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Respawn Time: 264 hours.
Respawn Delay: +- 2 hours.
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Respawn Time: 168 hours.
Respawn Delay: +- 2 hours.
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Respawn Time: 20 hours.
Respawn Delay: +- 2 hours.
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Respawn Time: 120 hours.
Respawn Delay: +- 2 hours.
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Respawn Time: 48 hours.
Respawn Delay: +- 4 hours.
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Respawn Time: 60 hours.
Respawn Delay: +- 4 hours.
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Respawn Time: 24 hours.
Respawn Delay: +- 24 hours.
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Respawn Time: 24 hours.


Blacksmith Brunon:
Hello again! Have you brought the new model Calculator? I guess that was too much to hope for. I see that you are still investigating.
Remember, there are two trade guilds you should talk to: the Silver Scale Guild and the Golden Wheel Guild.
Please hurry and get the Calculator for me!


A value object representing a time zone. A time zone is simply a named offset (in seconds) from GMT. Note that two time zone objects are only equivalent if they have both the same offset, and the same name.
A TimeZone instance may be used to convert a Time value to the corresponding time zone.
The class also includes all, which returns a list of all TimeZone objects.
- Comparable
| US_ZONES | = | /US|Arizona|Indiana|Hawaii|Alaska/ |
| A regular expression that matches the names of all time zones in the USA. |
| [R] | name | |
| [R] | utc_offset |
Locate a specific time zone object. If the argument is a string, it is interpreted to mean the name of the timezone to locate. If it is a numeric value it is either the hour offset, or the second offset, of the timezone to find. (The first one with that offset will be returned.) Returns nil if no such time zone is known to the system.
[ show source ]
# File vendor/rails/activesupport/lib/active_support/values/time_zone.rb, line 158 158: def [](arg) 159: case arg 160: when String 161: all.find { |z| z.name == arg } 162: when Numeric 163: arg *= 3600 if arg.abs <= 13 164: all.find { |z| z.utc_offset == arg.to_i } 165: else 166: raise ArgumentError, "invalid argument to TimeZone[]: #{arg.inspect}" 167: end 168: end
Return an array of all TimeZone objects. There are multiple TimeZone objects per time zone, in many cases, to make it easier for users to find their own time zone.
[ show source ]
# File vendor/rails/activesupport/lib/active_support/values/time_zone.rb, line 93 93: def all 94: unless @@zones 95: @@zones = [] 96: [[-43_200, "International Date Line West" ], 97: [-39_600, "Midway Island", "Samoa" ], 98: [-36_000, "Hawaii" ], 99: [-32_400, "Alaska" ], 100: [-28_800, "Pacific Time (US & Canada)", "Tijuana" ], 101: [-25_200, "Mountain Time (US & Canada)", "Chihuahua", "La Paz", 102: "Mazatlan", "Arizona" ], 103: [-21_600, "Central Time (US & Canada)", "Saskatchewan", "Guadalajara", 104: "Mexico City", "Monterrey", "Central America" ], 105: [-18_000, "Eastern Time (US & Canada)", "Indiana (East)", "Bogota", 106: "Lima", "Quito" ], 107: [-14_400, "Atlantic Time (Canada)", "Caracas", "La Paz", "Santiago" ], 108: [-12_600, "Newfoundland" ], 109: [-10_800, "Brasilia", "Buenos Aires", "Georgetown", "Greenland" ], 110: [ -7_200, "Mid-Atlantic" ], 111: [ -3_600, "Azores", "Cape Verde Is." ], 112: [ 0, "Dublin", "Edinburgh", "Lisbon", "London", "Casablanca", 113: "Monrovia" ], 114: [ 3_600, "Belgrade", "Bratislava", "Budapest", "Ljubljana", "Prague", 115: "Sarajevo", "Skopje", "Warsaw", "Zagreb", "Brussels", 116: "Copenhagen", "Madrid", "Paris", "Amsterdam", "Berlin", 117: "Bern", "Rome", "Stockholm", "Vienna", 118: "West Central Africa" ], 119: [ 7_200, "Bucharest", "Cairo", "Helsinki", "Kyev", "Riga", "Sofia", 120: "Tallinn", "Vilnius", "Athens", "Istanbul", "Minsk", 121: "Jerusalem", "Harare", "Pretoria" ], 122: [ 10_800, "Moscow", "St. Petersburg", "Volgograd", "Kuwait", "Riyadh", 123: "Nairobi", "Baghdad" ], 124: [ 12_600, "Tehran" ], 125: [ 14_400, "Abu Dhabi", "Muscat", "Baku", "Tbilisi", "Yerevan" ], 126: [ 16_200, "Kabul" ], 127: [ 18_000, "Ekaterinburg", "Islamabad", "Karachi", "Tashkent" ], 128: [ 19_800, "Chennai", "Kolkata", "Mumbai", "New Delhi" ], 129: [ 20_700, "Kathmandu" ], 130: [ 21_600, "Astana", "Dhaka", "Sri Jayawardenepura", "Almaty", 131: "Novosibirsk" ], 132: [ 23_400, "Rangoon" ], 133: [ 25_200, "Bangkok", "Hanoi", "Jakarta", "Krasnoyarsk" ], 134: [ 28_800, "Beijing", "Chongqing", "Hong Kong", "Urumqi", 135: "Kuala Lumpur", "Singapore", "Taipei", "Perth", "Irkutsk", 136: "Ulaan Bataar" ], 137: [ 32_400, "Seoul", "Osaka", "Sapporo", "Tokyo", "Yakutsk" ], 138: [ 34_200, "Darwin", "Adelaide" ], 139: [ 36_000, "Canberra", "Melbourne", "Sydney", "Brisbane", "Hobart", 140: "Vladivostok", "Guam", "Port Moresby" ], 141: [ 39_600, "Magadan", "Solomon Is.", "New Caledonia" ], 142: [ 43_200, "Fiji", "Kamchatka", "Marshall Is.", "Auckland", 143: "Wellington" ], 144: [ 46_800, "Nuku'alofa" ]]. 145: each do |offset, *places| 146: places.each { |place| @@zones << create(place, offset).freeze } 147: end 148: @@zones.sort! 149: end 150: @@zones 151: end
Create a new TimeZone instance with the given name and offset.
[ show source ]
# File vendor/rails/activesupport/lib/active_support/values/time_zone.rb, line 77 77: def create(name, offset) 78: zone = allocate 79: zone.send :initialize, name, offset 80: zone 81: end
Create a new TimeZone object with the given name and offset. The offset is the number of seconds that this time zone is offset from UTC (GMT). Seconds were chosen as the offset unit because that is the unit that Ruby uses to represent time zone offsets (see Time#utc_offset).
[ show source ]
# File vendor/rails/activesupport/lib/active_support/values/time_zone.rb, line 18 18: def initialize(name, utc_offset) 19: @name = name 20: @utc_offset = utc_offset 21: end
Return a TimeZone instance with the given name, or nil if no such TimeZone instance exists. (This exists to support the use of this class with the composed_of macro.)
[ show source ]
# File vendor/rails/activesupport/lib/active_support/values/time_zone.rb, line 86 86: def new(name) 87: self[name] 88: end
A convenience method for returning a collection of TimeZone objects for time zones in the USA.
[ show source ]
# File vendor/rails/activesupport/lib/active_support/values/time_zone.rb, line 176 176: def us_zones 177: all.find_all { |z| z.name =~ US_ZONES } 178: end
Compare this time zone to the parameter. The two are comapred first on their offsets, and then by name.
[ show source ]
# File vendor/rails/activesupport/lib/active_support/values/time_zone.rb, line 62 62: def <=>(zone) 63: result = (utc_offset <=> zone.utc_offset) 64: result = (name <=> zone.name) if result == 0 65: result 66: end
Adjust the given time to the time zone represented by self.
[ show source ]
# File vendor/rails/activesupport/lib/active_support/values/time_zone.rb, line 47 47: def adjust(time) 48: time = time.to_time 49: time + utc_offset - time.utc_offset 50: end
Returns the offset of this time zone as a formatted string, of the format "+HH:MM". If the offset is zero, this returns the empty string. If colon is false, a colon will not be inserted into the result.
[ show source ]
# File vendor/rails/activesupport/lib/active_support/values/time_zone.rb, line 27 27: def formatted_offset( colon=true ) 28: return "" if utc_offset == 0 29: sign = (utc_offset < 0 ? -1 : 1) 30: hours = utc_offset.abs / 3600 31: minutes = (utc_offset.abs % 3600) / 60 32: "%+03d%s%02d" % [ hours * sign, colon ? ":" : "", minutes ] 33: end
Compute and return the current time, in the time zone represented by self.
[ show source ]
# File vendor/rails/activesupport/lib/active_support/values/time_zone.rb, line 37 37: def now 38: adjust(Time.now) 39: end
Returns a textual representation of this time zone.
[ show source ]
# File vendor/rails/activesupport/lib/active_support/values/time_zone.rb, line 69 69: def to_s 70: "(GMT#{formatted_offset}) #{name}" 71: end
Return the current date in this time zone.
[ show source ]
# File vendor/rails/activesupport/lib/active_support/values/time_zone.rb, line 42 42: def today 43: now.to_date 44: end
Reinterprets the given time value as a time in the current time zone, and then adjusts it to return the corresponding time in the local time zone.
[ show source ]
# File vendor/rails/activesupport/lib/active_support/values/time_zone.rb, line 55 55: def unadjust(time) 56: time = Time.local(*time.to_time.to_a) 57: time - utc_offset + time.utc_offset 58: end


--- title: News - Clifford Lab permalink: "/news.html" layout: default ---
November 2016 - Pradyumna Suresha, the newest PhD student in our lab, was awarded the Institutional Gold Medal for securing highest GPA in B.Tech -Electronics and Communication Engineering, batch of 2015-16; as well as 1986 Batch Gold Medal for being the student with best academic record in the department of ECE, NITK Surathkal India. Congratulations!
October 2016 - We have openings for faculty and research positions in machine learning and signal processing applied to biomedical informatics and engineering.
14 Sept 2016 - The winners of this year's PhysioNet/CinC Challenge were announced at the CinC Conference. Congratulations to everyone for a tight run race! We enjoyed running this and hope you all submit to the upcoming Physiological Measurement Special Issue.
28 May 2016 - In support of the Exposome mission, the Clifford Lab will be offering live interactive demos to demonstrate some of the useful capabilities of the Raspberry Pi, sensor technologies and cloud computing. Event takes place June 12 in the plaza level auditorium of the Claudia Nance Rollins building.
More information can be found at the event's website, located here: Emory Hercules, and Human Exposome Project.
April 2016 - Dr. Clifford appointed Interim Chair of Emory's Department of Biomedical Informatics.
7 May 2016 - The Official Phase of the PhysioNet/Computing in Cardiology Challenge 2016 has begun.
February 2016 - The PhysioNet/Computing in Cardiology Challenge 2016, co-organised by the Clifford Lab and the Laboratory for Computational Physiology, is now open.


Day
Week
Month
March
Glasgow
Monday
16.03
2°
Be prepared
Tuesday
17.03
14°
90% Take an
Tuesday
17.03
17°
80% Wear a Hat
12.00 AM
10%
0°
1.00 AM
30%
-1°
2.00 AM
50%
0°
3.00 AM
70%
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4.00 AM
80%
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5.00 AM
90%
0°


Car Reservastion Record
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Search By OrderId:
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Search By UserName:
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Search By UserPhone:
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Search By CreateTime:
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orderAmount |
userName |
userPhone |
userAddress |
carId |
carMaker |
carType |
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We are offering basic knowledge about Computers.
We are offering Professional Trainings also.
We are offering Weekly Internships also.
Most Experianced Development Team
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Status: Released
Documentation:
- Version 1.2 User's Guide
- Manifest Validator
Executable
- Windows: ManifestValidator-1.2.exe
- Mac OS-X: ManifestValidator-1.2.dmg or ManifestValidator-1.2.pkg
- Linux: ManifestValidator-1.2.deb or ManifestValidator-1.2-1.x86_64.rpm
Source code is on GitHub. If you would like more information, please contact us.
Overview
In addition to functional enhancements, the changes for this release include an internal refactoring of code to use the mddf-lib software and a shift to the usage of the MIT License instead of the Creative Commons License.
New Features and Bug Fixes
Schema & Constraint Validation:
- Validation of Media Entertainment Core (MEC) files is now supported.
- non-unique GalleryID will now be treated as WARNING instead of ERROR.
- Ratings metadata is validated against the MovieLabs Content Rating System database.
- language-related metadata is validated in accordance with RFC-5646
Profile Validation:
None.
General Functions and User Interface:
- History of most-recently accessed files are saved and may be recalled
- Banner graphic includes text "Manifest Validation"
- Inclusion of INFO messages in logger output is now optional.
- Non-adherence to Best Practices recommendations is logged as a NOTICE rather than a WARNING.
- Profile selection menu moved to right of the file selection field.
Known Issues
None.
Schema & Constraint Validation:
- Validation of conformance with Common Metadata relating to Digital Assets is incomplete
- SSID syntax is only validated when ID is specified using the EIDR scheme.
Profile Validation:
- None
Other
- Reports that on Mac, clicking on table occasionally corrupts entry.
Other Changes
None.


| Name | Link |
|---|---|
| Branded.Me : | Allan F. Gagnon's Brand |
| GitHub: | Allan F. Gagnon's GitHub |
| FaceBook: | Allan F. Gagnon's Facebook |
| LinkedIn: | Allan F. Gagnon's LinkedIn |
| Twitter: | Allan F. Gagnon's Twitter |
| Professional Blog: | Allan F. Gagnon's Blog |
| Professional Website: | Allan F. Gagnon's Professional Website |
| Professional Resume: | Allan F. Gagnon's Professional Resume |


Toggle navigation
LearnFHIR - Resources
Home
GitHub
Resources
Here we have a compilation of FHIR references and other resources from across the web
Primary Resources
HL7 FHIR Standard:
http://www.hl7.org/implement/standards/fhir/
HL7 List of Resources:
https://www.hl7.org/fhir/resourcelist.html
SMART on FHIR:
http://smarthealthit.org/
HL7 FHIR Wiki:
http://wiki.hl7.org/index.php?title=FHIR
Sandboxes and Test Servers
Aidbox.io:
https://hello.aidbox.io/
Cerner:
http://fhir.cerner.com/millennium/dstu2/#open-sandbox
Epic:
https://open.epic.com/Interface/FHIR
HSPC:
https://www.developers.hspconsortium.org/build
InterSystems:
https://www.intersystems.com/fhir/#try-it-now
Synthetic mass:
https://syntheticmass.mitre.org/api.html
HL7 list of testing servers:
http://wiki.hl7.org...
Other tutorials
Smart Health IT:
http://docs.smarthealthit.org/tutorials/
HL7's FHIR Starter:
http://wiki.hl7.org/index.php?title=FHIR_Starter
Cerner Engineering:
http://engineering.cerner.com/smart-on-fhir-tutorial/
Australian Digital Health Agency:
https://fhir-drills.github.io/
Epic- FHIR basics:
https://open.epic.com/Tutorial
Epic- Oauth2:
https://open.epic.com/Tutorial/OAuth
Technical and Other resources
FHIR.js wrapper:
https://github.com/FHIR/fhir.js
ClinFHIR:
http://clinfhir.com
The SMART FHIR client:
https://github.com/smart-on-fhir/client-js
Value Set Authority Center:
https://vsac.nlm.nih.gov/
HL7 Message examples:
http://www.ringholm.com/docs/04300_en.htm


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The gradient of a scalar function
is readily
calculated from the chain rule,
|
(128) |
Note that the gradient of a scalar function is in the covariant
representation. The inverse form of this expression is obtained by dotting the
above equation by the three contravariant basis vectors, respectively,
|
(129) |
|
(130) |
|
(131) |
Using Eq. (128), the directional derivative in the direction of
is written as
|
(132) |
yj
2018-03-09


--- layout: contact title: Contact shortTitle: Contact permalink: /contact/ ---
Sustainable Computing Research Group,
University of Colombo School of Computing,
No. 35, Reid Avenue,
Colombo 7, Sri Lanka
+94-11-2158919
+94-11-2587239