| Package | Description |
|---|---|
| org.apache.taverna.facade.impl | |
| org.apache.taverna.monitor |
Defines the API for the monitoring and steering system.
|
| org.apache.taverna.monitor.impl | |
| org.apache.taverna.platform.execution.impl.local | |
| org.apache.taverna.workflowmodel.impl |
Implementation package for workflow entities
|
| org.apache.taverna.workflowmodel.processor.activity |
Provides definitions for a single Activity to be contained within a
Processor.
|
| org.apache.taverna.workflowmodel.processor.dispatch |
Definition and support classes for the Dispatch Stack.
|
| Modifier and Type | Class and Description |
|---|---|
class |
WorkflowInstanceFacadeImpl.StateProperty |
| Modifier and Type | Interface and Description |
|---|---|
interface |
SteerableProperty<T>
Some monitorable properties are mutable and can be written to by steering
agents or other clients.
|
| Modifier and Type | Method and Description |
|---|---|
Set<MonitorableProperty<?>> |
MonitorManager.AddPropertiesMessage.getNewProperties() |
Set<? extends MonitorableProperty<?>> |
MonitorNode.getProperties()
Each monitor node exposes a set of properties, which may or may not be
mutable
|
Set<MonitorableProperty<?>> |
MonitorManager.RegisterNodeMessage.getProperties() |
| Modifier and Type | Method and Description |
|---|---|
void |
MonitorNode.addMonitorableProperty(MonitorableProperty<?> newProperty)
Properties can be added to the monitor node after creation if required,
although this should be used only when necessary to avoid race conditions
|
| Modifier and Type | Method and Description |
|---|---|
void |
MonitorManager.addPropertiesToNode(String[] owningProcess,
Set<MonitorableProperty<?>> newProperties)
Push new property get / set methods into the specified node.
|
void |
MonitorManager.registerNode(Object workflowObject,
String[] owningProcess,
Set<MonitorableProperty<?>> properties)
Register a new node with this monitor.
|
void |
MonitorManager.registerNode(Object workflowObject,
String owningProcessIdentifier,
Set<MonitorableProperty<?>> properties)
Register a new node with this monitor.
|
| Constructor and Description |
|---|
AddPropertiesMessage(String[] owningProcess,
Set<MonitorableProperty<?>> newProperties) |
RegisterNodeMessage(Object workflowObject,
String[] owningProcess,
Set<MonitorableProperty<?>> properties) |
| Modifier and Type | Method and Description |
|---|---|
protected void |
MonitorTreeModel.addPropertiesToNode(String[] owningProcess,
Set<MonitorableProperty<?>> newProperties)
Inject properties into an existing node
|
protected void |
MonitorTreeModel.registerNode(Object workflowObject,
String[] owningProcess,
Set<MonitorableProperty<?>> properties)
Create a new node in the monitor
|
| Modifier and Type | Class and Description |
|---|---|
class |
StaticProperty
A MonitorableProperty with fixed values.
|
| Modifier and Type | Method and Description |
|---|---|
void |
LocalProcessorReport.addProperties(Set<MonitorableProperty<?>> properties) |
void |
LocalExecutionMonitor.addPropertiesToNode(String[] owningProcess,
Set<MonitorableProperty<?>> newProperties) |
void |
LocalExecutionMonitor.registerNode(Object dataflowObject,
String[] owningProcess,
Set<MonitorableProperty<?>> properties) |
| Constructor and Description |
|---|
StaticProperty(MonitorableProperty<?> property)
Records the state of the MonitorableProperty.
|
| Modifier and Type | Field and Description |
|---|---|
protected Map<String,Set<MonitorableProperty<?>>> |
ProcessorImpl.monitorables |
| Modifier and Type | Method and Description |
|---|---|
Set<MonitorableProperty<?>> |
MonitorableAsynchronousActivity.executeAsynchWithMonitoring(Map<String,T2Reference> data,
AsynchronousActivityCallback callback)
This has the same invocation semantics as
AsynchronousActivity .executeAsynch and all
implementations should also implement that method, with the difference
that this one returns immediately with a set of monitorable properties
which represent monitorable or steerable state within the invocation
itself. |
| Modifier and Type | Method and Description |
|---|---|
void |
DispatchStack.receiveMonitorableProperty(MonitorableProperty<?> prop,
String processID)
The dispatch stack acts as an aggregator for monitorable properties
exposed by the dispatch layers.
|
Copyright © 2015–2016 The Apache Software Foundation. All rights reserved.


Oliver Zeigermann / @DJCordhose
Slides: http://bit.ly/ms-typescript
type annotations
Anders Hejlsberg@Build2016: Big JavaScript codebases tend to become "read-only".
let obj: string;
obj = 'yo';
// Error: Type 'number' is not assignable to type 'string'.
obj = 10;
function sayIt(what: string) { // types can be inferred (return type)
return `Saying: ${what}`;
}
const said: string = sayIt(obj);
class Sayer {
what: string; // mandatory
constructor(what: string) {
this.what = what;
}
sayIt(): string { // return type if you want to
return `Saying: ${this.what}`;
}
}
Flow looks the same for those examples
function foo(num: number) {
if (num > 10) {
return 'cool';
}
}
console.log(foo(9).toString());
// error: call of method `toString`.
// Method cannot be called on possibly null value
console.log(foo(9).toString());
// to fix this, we need to check the result
const fooed: string|void = foo(9);
if (fooed) {
fooed.toString();
}
Types are non-nullable by default in flow
function foo(num: number) {
if (num > 10) {
return 'cool';
}
}
// same as flow
const fooed: string|void = foo(9);
if (fooed) {
fooed.toString();
}
// or tell the compiler we know better (in this case we actually do)
fooed!.toString();
Only applies to TypeScript 2.x
Only works when strictNullChecks option is checked
All types nullable by default in TypeScript 1.x
can be anything, not specified
can selectively disable type checking
function func(a: any) {
return a + 5;
}
// cool
let r1: string = func(10);
// cool
let r2: boolean = func('wat');
Types can be parameterized by others
Most common with collection types
let cats: Array<Cat> = []; // can only contain cats
let animals: Array<Animal> = []; // can only contain animals
// nope, no cat
cats.push(10);
// nope, no cat
cats.push(new Animal('Fido'));
// cool, is a cat
cats.push(new Cat('Purry'));
// cool, cat is a sub type of animal
animals.push(new Cat('Purry'));
let cats: Array<Cat> = []; // can only contain cats
let animals: Array<Animal> = []; // can only contain animals
// error TS2322: Type 'Animal[]' is not assignable to type 'Cat[]'.
// Type 'Animal' is not assignable to type 'Cat'.
// Property 'purrFactor' is missing in type 'Animal'.
cats = animals;
// wow, works, but is no longer safe
animals = cats;
// because those are now all cool
animals.push(new Dog('Brutus'));
animals.push(new Animal('Twinky'));
// ouch:
cats.forEach(cat => console.log(`Cat: ${cat.name}`));
// Cat: Purry
// Cat: Brutus
// Cat: Twinky
TypeScript allows for birds and dogs to be cats here :)
let cats: Array<Cat> = []; // can only contain cats
let animals: Array<Animal> = []; // can only contain animals
// ERROR
// property `purrFactor` of Cat. Property not found in Animal
cats = animals;
// same ERROR
animals = cats;
End of story for Flow
aka Disjoint Unions aka Tagged Unions aka Algebraic data types
to describe data with weird shapes
Depending on some data other data might apply or not
type Response = Result | Error; // a disjoint union type with two cases
type Result = { status: 'done', payload: Object };
type Error = { status: 'error', message: string };
function callback(response: Response) {
// given by code completion
console.log(response.status);
// does not work,
// as we do not know if it exists, just yet
console.log(result.payload); // ERROR
switch (response.status) {
case 'done':
// this is the special thing:
// type system now knows, this is a Response
const result: Result = response;
console.log(result.payload);
break;
case 'error':
const error: Error = response;
console.log(error.message);
break;
}
}
class Person {
name: string;
}
class Dog {
name: string;
}
let dog: Dog = new Dog();
// nope, nominal type compatibility violated
// ERROR: Dog: This type is incompatible with Person
let person: Person = dog;
// same problem
// ERROR: object literal: This type is incompatible with Person
let person: Person = {
name: "Olli"
};
class Person {
name: string;
}
class Dog {
name: string;
}
let dog: Dog = new Dog();
// yes, correct, as structurally compatible
let person: Person = dog;
// same thing, also correct
let person: Person = {
name: "Olli"
};
interface NamedObject {
name: string;
}
// this is fine as nominal typing only applies to Flow classes
let namedObject: NamedObject = dog;
// same thing, also fine
let namedObject: NamedObject = {
name: "Olli"
};
// not fine in either, missing name
let namedObject: NamedObject = {
firstName: "Olli"
};
TypeScript has special support for classes
Makes it easier for people coming from Java/C++/C#
Flow does not feature those or any other syntactic sugar, as it is a checker only
Starting from 2016.3
My recommendation


Treebank Statistics: UD_Bengali-BRU: POS Tags: NOUN
There are 35 NOUN
lemmas (30%), 38 NOUN
types (25%) and 62 NOUN
tokens (19%).
Out of 14 observed tags, the rank of NOUN
is: 1 in number of lemmas, 2 in number of types and 3 in number of tokens.
The 10 most frequent NOUN
lemmas: বাবা, নাম, গান, মা, গল্প, পতাকা, হাত, কার্টুন, ক্লাস, দেশ
The 10 most frequent NOUN
types: নাম, গান, বাবা, মা, হাত, কার্টুন, ক্লাসে, গল্প, দেশের, পতাকা
The 10 most frequent ambiguous lemmas: আজ (ADV 3, NOUN 1), পড়া (VERB 4, NOUN 1), মজা (ADJ 1, NOUN 1)
The 10 most frequent ambiguous types: আজ (ADV 3, NOUN 1), মজার (ADJ 1, NOUN 1)
- আজ
- মজার
Morphology
The form / lemma ratio of NOUN
is 1.085714 (the average of all parts of speech is 1.290598).
The 1st highest number of forms (2) was observed with the lemma “গল্প”: গল্প, গল্পটি.
The 2nd highest number of forms (2) was observed with the lemma “পতাকা”: পতাকা, পতাকার.
The 3rd highest number of forms (2) was observed with the lemma “বাবা”: বাবা, বাবার.
NOUN
occurs with 3 features: Case (62; 100% instances), Number (62; 100% instances), VerbForm (2; 3% instances)
NOUN
occurs with 6 feature-value pairs: Case=Gen
, Case=Loc
, Case=Nom
, Number=Plur
, Number=Sing
, VerbForm=Vnoun
NOUN
occurs with 5 feature combinations.
The most frequent feature combination is Case=Nom|Number=Sing
(44 tokens).
Examples: গান, নাম, বাবা, মা, কার্টুন, গল্প, পতাকা, বই, রং, শেষ
Relations
NOUN
nodes are attached to their parents using 11 different relations: obj (23; 37% instances), nsubj (10; 16% instances), root (8; 13% instances), obl (6; 10% instances), compound:lvc (3; 5% instances), nmod (3; 5% instances), compound (2; 3% instances), iobj (2; 3% instances), nmod:poss (2; 3% instances), vocative (2; 3% instances), acl (1; 2% instances)
Parents of NOUN
nodes belong to 6 different parts of speech: VERB (42; 68% instances), (8; 13% instances), NOUN (7; 11% instances), ADJ (3; 5% instances), NUM (1; 2% instances), PROPN (1; 2% instances)
33 (53%) NOUN
nodes are leaves.
16 (26%) NOUN
nodes have one child.
3 (5%) NOUN
nodes have two children.
10 (16%) NOUN
nodes have three or more children.
The highest child degree of a NOUN
node is 4.
Children of NOUN
nodes are attached using 10 different relations: nmod:poss (16; 30% instances), det (10; 19% instances), punct (10; 19% instances), amod (6; 11% instances), nmod (4; 8% instances), advmod (2; 4% instances), nsubj (2; 4% instances), acl (1; 2% instances), case (1; 2% instances), compound (1; 2% instances)
Children of NOUN
nodes belong to 8 different parts of speech: PRON (15; 28% instances), DET (10; 19% instances), PUNCT (10; 19% instances), ADJ (7; 13% instances), NOUN (7; 13% instances), ADV (2; 4% instances), ADP (1; 2% instances), VERB (1; 2% instances)


Issue 5430: Show @namespace rules inside CSS panel
Steps to reproduce
Open Firebug
Switch to the CSS panel
Select issue5430.html from the Location Menu
Expected result
There should be two @namespace rules listed inside the CSS panel:
@namespace "http://www.w3.org/1999/xhtml";
@namespace svg "http://www.w3.org/2000/svg";


{% extends 'layouts/base.html' %} {% block content %}
Email {{ business.email }}
No Business in this hood


github.com/shuLhan/share
GoDoc
Changelog
contact
The Go library to manage contacts.
Features
Import Google's contacts v3 with OAuth2
Import Yahoo's contacts with OAuth2
Import Microsoft's Live/Outlook contacts with OAuth2
TODO
VCard 4.0 Encode and Decode


| DOSE: T+ 0:00 |
15 mg |
oral |
2C-I |
(capsule) |
| T+ 2:00 |
|
smoked |
Cannabis |
(plant material) |
| T+ 4:15 |
|
smoked |
Cannabis |
(plant material) |
| T+ 5:45 |
|
smoked |
Cannabis |
(plant material) |
[Prior drug experience – Cannabis, MDMA, Hawaiian Baby Woodrose seeds]
While at university, it was approaching the end of term. My friends and I tried to get hold of some MDMA for a nice night in to celebrate. Unfortunately, all our usual sources were dry, so we decided to try 2C-I instead. Some of us had taken it before, but it was the first time I had tried it. Naturally, I was a bit nervous about the whole thing, but I was definitely looking forward to it, after having done some research on it. I asked my more experienced friends a lot of questions, which helped to calm the nerves a bit.
When we got the 2C-I, it came pre-weighed in gelatin capsules. We went over to my friends room, and at around 19:45, we dropped. I took 15mg, the more experienced among us took 17mg.
Note: These times are the best estimations I can make based on text messages recieved/sent on the night. The passage of time was very strange, and varied from things seeming faster than normal, or much slower than normal.
T = 20:15 (30 mins) - The first effects were felt. I began to feel tingles in my limbs, which seemed to slowly build up over time. I noticed mildly shaking hands, and energy starting to flow from my abdomen. As the body high became stronger, I was unsure as to how I felt about it. I seemed to vary from enjoying it to being slightly scared by it. It was similar to MDMA, but more intense, and lacking the empathogenic aspect. After a while though, I just decided to just roll with it, and try to enjoy it. The shift in my thinking seemed to help, and I started to enjoy it more. I didn't feel any nausea or discomfort.
T = 21:00 (1 hour 15 minutes) - The first visuals were noticed. I was lying on my friends bed, staring at the ceiling, listening to music. It began to look like the ceiling was liquid, and it began to flow and ripple, like looking at water on glass. It was quite beautiful, and for some reason, I found it hilarious. The music seemed to be much slower than normal.
After a while, I began seeing brightly coloured pattens on almost all surfaces in the room. Intricately detailed things seemed to catch my attention specifically. My friend's Monet poster looked incredible. The brush strokes moved into each other, the colours changed and patterns were evident that I hadn't seen before. The body high at this point was such that I felt like moving around a lot, so 3 of us decided to go for a walk. When we left, I was on a +2.
Walking felt very pleasant – it was good to get up and move around, and I felt like I was moving in slow motion. The constant feeling of energy was fun! I wish we had gone out in the Day though. I think that a more colourful environment would have been more fun.
T = 21:45 (2 hours)- We arrive at a bench in a secluded bit of woodland. My friend brought a joint with him. The cannabis seemed to act in a very synergistic manner, and boosted the visuals strongly. Really at a +3 at that point. I was sitting on a bench, looking at the trees. They were moving and waving around. The closest thing I can think of that it looked like, was seaweed moving with the waves. It was stunning. Looking at the floor produced a feeling similar to mild vertigo, but in a very acceptable and pleasurable way – watching the “Persian carpet” type patterns move and adjust was very entertaining. I tried to eat some chocolate, but the food felt foreign and strange in my mouth. Drinking water was fine, but I had to keep reminding myself to swallow.
T = 22:10 (2 hours, 25 minutes) - I had hit the peak of the experience, and plateaued, so I was at a constant +3. The walk back to my friends room was interesting. Walking down a road lined with tall buildings and trees gave me the feeling that I was much taller and thinner than I actually am. I had a couple of moments where my mind felt disconnected to my body, but as soon as I noticed this, I was able to 'get back in'. It wasn't altogether unpleasant, but a little unsettling at first. When my friends were talking, at times I wasn't sure if they were talking or if I was imagining it, so I kept asking them for reassurance that I was still sane. It was all quite funny.
T = 22:30 (2 hours, 45 minutes)– Back at my friends room. I needed the toilet, so I went in and sat down (didn't want to miss!). The floor tiles are patterned, and the effect this gave was mesmerising. It felt like I was in an elevator, gently moving up and down with each inhale and exhale of breath. The floor changed colours constantly. My friends towel was also a point of interest for similar reasons. After I finished, I joined the others back in the room. I remember lying down on the bed, and wishing the visuals would stop for 5 minutes. I had strange mood swings – one moment I was laughing and happy, the next I felt sad. This persisted for around half an hour but after that, I was back into a very good mood. A Kandinsky poster looked amazing, with the geometric shapes moving around and in and out of the paper as well as changing colour. I was also transfixed by some sheet music I found.
T = 00:00 (4 hours 15 minutes) – visuals wearing off a bit, but body high still large. Smoked some more cannabis, which brought back some of the more gentle visual effects. My vision was blurring intermittently, and colours were still boosted. Less movement from inanimate objects than before though. Still had nice trail effects when lights were moved.
T = 00:45 (5 hours) – Open eye visuals pretty much over. Some mild boosting of colours. Closed eye visuals were still active. The body high was waning by this point.
T = 01:30 (5 hours, 45 minutes) – We went back to a different friends room, and smoked more pot. By this point, I just felt stoned, rather than any residual 2C-I effects, but it was hard to tell! Stayed at my friends for around 2 hours, then went home. Sleep came easily enough.
Got a good amount of sleep, and woke up feeling refreshed. The rest of the day I felt energetic, until it got dark at which point I just felt a bit tired. The day after that, as I type this, I feel completely normal.
SUMMARY:
Overall, the experience was positive.
Not as life changing as I was expecting, but this is a chemical that I will be trying again, and I think that as I now know what to expect, I will be able to enjoy and explore the compound more. As a first experience on 2C-I, I had times where I wished I could 'switch off' the visual aspect of the drug. This typically lasted around 5 minutes, then I'd be back to my staring-in-wonderment-at-everything-and-laughing-because-I'm-tripping self. Again, I think that this will be less of a problem the next time I take it.
I didn't have any major epiphanies, but did come out of the experience with a better opinion of myself. I found that touch sensations were amplified and more pleasurable than normal (though not to the extent of MDMA). Like MDMA, my temperature regulation seemed to be thrown a little, and I spent a long time with clammy hands. I tried various types of food, but whilst I was tripping, it felt alien and unpleasant to chew and swallow. The taste was unchanged. Drinking water and coke was fine, but swallowing felt slightly forced.
I am now interested to try 2C-B, and see how that compares.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


|
GenericMatrix
A generic template matrix class.
|
C++ cross platform generic matrix template class, C++11 Required Support.
Two classes:
| Class | Brief |
|---|---|
| GenericMatrix | A generic template matrix class, the matrix elements are managed by a one-dimension pointer. |
| GenericMatrix2 | A generic template matrix class, the matrix elements are managed by a two-dimension pointer. |
More interface information see "doc/html/index.html".
C++跨平台通用模板矩阵类，需编译器支持C++11.
接口详细文档见“doc/html/index.html”。
linux or windows:
(Compiled by gcc 7.4.0) The Result is:
[Apache License 2.0](LICENSE)


|
||||||||||
| PREV NEXT | FRAMES NO FRAMES |
| Packages that use StylesheetComposed | |
|---|---|
| org.apache.xalan.templates | Implements the Templates interface,
and defines a set of classes that represent an XSLT stylesheet. |
| Uses of StylesheetComposed in org.apache.xalan.templates |
|---|
| Subclasses of StylesheetComposed in org.apache.xalan.templates | |
|---|---|
class |
StylesheetRoot
This class represents the root object of the stylesheet tree. |
| Fields in org.apache.xalan.templates declared as StylesheetComposed | |
|---|---|
private StylesheetComposed[] |
StylesheetRoot.m_globalImportList
The combined list of imports. |
| Methods in org.apache.xalan.templates that return StylesheetComposed | |
|---|---|
StylesheetComposed |
StylesheetRoot.getGlobalImport(int i)
Get a stylesheet from the global import list. |
StylesheetComposed |
Stylesheet.getImport(int i)
Get a stylesheet from the "import" list. |
StylesheetComposed |
StylesheetComposed.getImportComposed(int i)
Get a stylesheet from the "import" list. |
StylesheetComposed |
Stylesheet.getStylesheetComposed()
Get the owning aggregated stylesheet, or this stylesheet if it is aggregated. |
StylesheetComposed |
ElemTemplateElement.getStylesheetComposed()
Get the owning "composed" stylesheet. |
StylesheetComposed |
ElemTemplate.getStylesheetComposed()
Get the stylesheet composed (resolves includes and imports and has methods on it that return "composed" properties. |
| Methods in org.apache.xalan.templates with parameters of type StylesheetComposed | |
|---|---|
int |
StylesheetRoot.getImportNumber(StylesheetComposed sheet)
Given a stylesheet, return the number of the stylesheet in the global import list. |
void |
Stylesheet.setImport(StylesheetComposed v)
Add a stylesheet to the "import" list. |
|
||||||||||
| PREV NEXT | FRAMES NO FRAMES |


left.
Clear completed items
This is a technical demo of underscore-observe, a JavaScript utility for underscore.js to make standard arrays observable. Its concept and design are inspired by Jérôme Gravel-Niquet's Todo-list demo.


pheonix yellow metallic
imola red
interlago blue metallic
alpine white
4.4.18.a xforms-scroll-first and xforms-scroll-last events
You must see an xforms-scroll-first message when you activate the Scroll First trigger.
You must see an xforms-scroll-last message when you activate the Scroll Last trigger.
Scroll First
Scroll Last
xforms-scroll-first
xforms-scroll-last


error.Rd
Compute the root-mean-squared forecast error (RMSE) or mean absolute forecast error (MAE) of direct forecast OLS method for forecasting.
error(df, lags, .H, .K, ic = BIC, .var = "all", .diff = FALSE, dev = "RMSE", wav = FALSE, xreg = NULL, ...)
| df | A data frame. The first column of the data frame
must be the base variable for constructing the
dependent variable, the multiperiod ahead
value to be forecasted, \(x_{t + h}\). If |
|---|---|
| lags | An integer vector defining the lags of the
regressors. If |
| .H | An integer representing the maximum horizon step. |
| .K | An integer, the number of pseudo-out-of-sample forecasts. |
| ic | Information criterion, |
| .var | A string to determine how the model will be
specificated: |
| .diff | Logical |
| dev | A string, |
| wav | Logical. If |
| xreg | Data frame. Exogeunous variable not subjected
to be lagged. The number of rows must be the same as in |
| ... | Further arguments passed to |
A double vector with forecasts error (RMSE or MAE) from
1 to .H
step-ahead.
See wavdrcast-package
and
model
.
#>#> #>#>#> #>#>#> #> #>#> [1] 0.1896285 0.2192279lgdp <- gdp[1] error(df = lgdp, lags = c(1, 1), .H = 2, .K = 8, wav = TRUE, .diff = TRUE, wt = "modwt", a = 1)#> [1] 0.005388602 0.011127183


Temperature/Length Converter
Enter Temperature/Length (examples: 32F, 45C, -2.5f):
Converted Temperature/Length:


The following is a list of compile dependencies for this project. These dependencies are required to compile and run the application:
| GroupId | ArtifactId | Version | Type | License |
|---|---|---|---|---|
| com.github.davidmoten | grumpy-ogc | 0.3-SNAPSHOT | jar | The Apache Software License, Version 2.0 |
| com.github.davidmoten | grumpy-ogc-layers | 0.3-SNAPSHOT | jar | The Apache Software License, Version 2.0 |
| log4j | log4j | 1.2.17 | jar | The Apache Software License, Version 2.0 |
| org.slf4j | slf4j-log4j12 | 1.7.7 | jar | MIT License |
The following is a list of transitive dependencies for this project. Transitive dependencies are the dependencies of the project dependencies.
The following is a list of compile dependencies for this project. These dependencies are required to compile and run the application:
Simplified BSD: Support and utility classes, ZonalStats operator
Unknown: jai_codec, jai_imageio, jgridshift, servlet-api, vecmath
BSD License: jsr-275
Apache License, Version 2.0: java-xmlbuilder
Public domain: base64
OGC copyright: Open GIS Interfaces
MIT License: SLF4J API Module, SLF4J LOG4J-12 Binding
The Apache Software License, Version 2.0: Apache Commons Lang, Apache Log4j, Commons IO, Commons Math, Commons Pool, Guava (Google Common Libraries) Annotations, Guava (Google Common Libraries) Base, grumpy-core, grumpy-ogc, grumpy-ogc-layers, grumpy-projection, wms-demo
JDL (Java Distribution License): Java Advanced Imaging
Similar to Apache License but with the acknowledgment clause removed: JDOM
Lesser General Public License (LGPL): API interfaces, EPSG Authority Service using WKT file, Grid Coverage module, Image I/O-Extensions - utilities classes and methods, Improved TIFF Plugin, JTS Topology Suite, Main module, Metadata, OGC CQL to Filter parser, Open GIS Interfaces, Referencing services, Render


{% extends 'base.html'%} {% import "bootstrap/wtf.html" as wtf %} {% block content%}
{{blog.blog}}
Posted: {{blog.date.strftime("%c")}}
{{comment.comment}}
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Screen shot of wfccd_chkarc
- The red lines indicate the position of standard He,Ne arc lines.
If your lines don't line up with these, there is a problem.
- Also, the RMS should be less than 0.3 for most of the slits. The
ones that extend to 1micron do show larger values, however.
2004-06-10


Oh, one of those memorable moments in my life.
We got up early in the morning to prep water for hydrating the saplings we're going to plant. I remember having a relay line from the second floor of the new boy's dorm to the jeeps on the parking lot near the ASTB. Me, being a lazy, impatient and relatively strong, proceeded to grab a backpack and stuffed litres of water in there (of course, the water was stored in bottles).
It was a relatively long journey there, me sitting in the center of the jeep keeping the water bottles from falling out. It may sound arduous in my part but I was actually pretty comfy back then. No aching ass, no awkward seatmates, and the motion of the jeep is just right for my body.
When we arrived there I began packing as many litres of water in my backpack as I could. We were all supposed to carry water, and since I was really in the mood that time (the beautiful scenery hyped me up) I decided to hoard many bottles and even carry a gallon with them.
The journey to the planting site was traversed by foot; that meant that I carried around 15 kilograms of water with me. It was pretty hard on my back and needless to say, halfway through I needed a bit of help from Sir Cy since I was already lagging behind.
We arrived at the planting site, and it was really windy and cool up there, featuring a nice view of the landscape. It was refreshing, getting my hands dirty, learning how to plant trees, basically helping out momma nature.
TL;DR: I enjoyed this activity, it was very productive, I had a great time and a good feeling knowing that those trees of ours will grow into oxygen-producing factories that can help the earth in the long run.


PharmaNet Site Registration
Directly sets up individual PharmaNet access accounts at a site or has the authority to request accounts from the
site's PharmaNet software vendor. May be the Signing Authority.
The PharmaNet Administrator could be the site's administrator, manager, HR lead, medical office assistant (MOA), a
practitioner, software vendor, etc.


|
Standard Reference Data Program |
Data Gateway |
Chemistry WebBook |
NIST subscription sites provide data under the NIST Standard Reference Data Program, but require an annual fee to access. The purpose of the fee is to recover costs associated with the development of data collections included in such sites. Your institution may already be a subscriber. Follow the links above to find out more about the data in these sites and their terms of usage.
Go To: Top, Constants of diatomic molecules, References, Notes / Error Report
Data compilation copyright by the U.S. Secretary of Commerce on behalf of the U.S.A. All rights reserved.
Data compiled as indicated in comments:
LL - S.G. Lias and J.F. Liebman
LLK - S.G. Lias, R.D. Levin, and S.A. Kafafi
B - J.E. Bartmess
View reactions leading to BrO+ (ion structure unspecified)
| EA (eV) | Method | Reference | Comment |
|---|---|---|---|
| 2.3530 ± 0.0060 | LPES | Gilles, Polak, et al., 1992 | B |
| >1.45 ± 0.23 | R-A | Vogt, Dreves, et al., 1977 | Br- + O2 ->; B |
| IE (eV) | Method | Reference | Comment |
|---|---|---|---|
| 10.46 ± 0.02 | PI | Monks, Stief, et al., 1993 | LL |
| 10.29 ± 0.01 | PE | Dunlavey, Dyke, et al., 1978 | Vertical value; LLK |
Go To: Top, Gas phase ion energetics data, References, Notes / Error Report
Data compilation copyright by the U.S. Secretary of Commerce on behalf of the U.S.A. All rights reserved.
Data compiled by: K.P. Huber and G. Herzberg
| State | Te | ωe | ωexe | ωeye | Be | αe | γe | De | βe | re | Trans. | ν00 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| A (2Π3/2) | 27871 | 485.9 1 H | 5.40 | -0.074 | 2 | A ↔ X1 R | 27725 1 H | |||||
| Coleman and Gaydon, 1947; missing citation | ||||||||||||
| X2 2Π1/2 | (900) 3 | |||||||||||
| X1 2Π3/2 | 0 | 778.7 1 H | 6.82 | 0.429598 4 | 0.003639 | (0.523E-6) | 1.7172 5 6 | |||||
| Powell and Johnson, 1969; Amano, Yoshinaga, et al., 1972; Carrington, Dyer, et al., 1970; Brown, Byfleet, et al., 1972 | ||||||||||||
| EPR sp. | ||||||||||||
| Carrington, Dyer, et al., 1970; Brown, Byfleet, et al., 1972 |
| 1 | Normal isotopic mixture. The vibrational numbering in neither A nor X1 is quite certain. In order to fit the absorption and the emission bands into the same vibrational scheme it was assumed Durie and Ramsay, 1958 that the longest-wavelength absorption band was 1-0 and that the v" numbering of the emission bands Coleman and Gaydon, 1947 had to be raised by four units. |
| 2 | All A ← X1 bands are diffuse on account of predissociation, though a few bands show evidence of rotational fine structure. |
| 3 | A0= -815 from EPR sp. Carrington, Dyer, et al., 1970; estimate A0 = -980 Brown, Byfleet, et al., 1972. |
| 4 | Effective constants. |
| 5 | From the "true" Be = 0.4299 Amano, Yoshinaga, et al., 1972. |
| 6 | Microwave sp. 8 |
| 7 | From the near-convergence of the absorption bands A ←X1 assuming dissociation of A into Cl(2P3/2) + O(1D2); see Durie and Ramsay, 1958. |
| 8 | μel(v=0)= 1.765 D Amano, Yoshinaga, et al., 1972; 1.61 D Carrington, Levy, et al., 1967, Byfleet, Carrington, et al., 1971 from Stark effect in the gas-phase EPR sp. Carrington, Levy, et al., 1967, Byfleet, Carrington, et al., 1971. For eqQ(79,81Br) and magnetic hyperfine parameters for both isotopes see Powell and Johnson, 1969, Carrington, Dyer, et al., 1970, Amano, Yoshinaga, et al., 1972, Brown, Byfleet, et al., 1972. |
Go To: Top, Gas phase ion energetics data, Constants of diatomic molecules, Notes / Error Report
Data compilation copyright by the U.S. Secretary of Commerce on behalf of the U.S.A. All rights reserved.
Gilles, Polak, et al., 1992
Gilles, M.K.; Polak, M.L.; Lineberger, W.C.,
Photoelectron Spectroscopy of the Halogen Oxide Anions FO-, ClO-, BrO-, IO-, OClO-, and OIO-,
J. Chem. Phys., 1992, 96, 8012. [all data]
Vogt, Dreves, et al., 1977
Vogt, D.; Dreves, W.; Mischke, J.,
Energy dependence of differential cross sections in endoergic ion-molecule collision processes of negative ions,
Int. J. Mass Spectrom. Ion Phys., 1977, 24, 285. [all data]
Monks, Stief, et al., 1993
Monks, P.S.; Stief, L.J.; Krauss, M.; Kuo, S.C.; Klemm, R.B.,
A discharge-flow photoionization mass-spectrometric study of the BrO(X 2) radical. Photoionization spectrum and ionization energy,
Chem. Phys. Lett., 1993, 211, 416. [all data]
Dunlavey, Dyke, et al., 1978
Dunlavey, S.J.; Dyke, J.M.; Morris, A.,
The first ionization potential of the BrO(X2π3/2) radical obtained using photoelectron spectroscopy,
Chem. Phys. Lett., 1978, 53, 382. [all data]
Coleman and Gaydon, 1947
Coleman, E.H.; Gaydon, A.G.,
The radicals BrO and CBr in flames,
Discuss. Faraday Soc., 1947, 2, 166. [all data]
Powell and Johnson, 1969
Powell, F.X.; Johnson, D.R.,
Microwave spectrum of the BrO free radical,
J. Chem. Phys., 1969, 50, 4596. [all data]
Amano, Yoshinaga, et al., 1972
Amano, T.; Yoshinaga, A.; Hirota, E.,
Microwave spectrum of the BrO radical equilibrium structure and dipole moment,
J. Mol. Spectrosc., 1972, 44, 594. [all data]
Carrington, Dyer, et al., 1970
Carrington, A.; Dyer, P.N.; Levy, D.H.,
Gas-phase electron resonance spectra of BrO and IO,
J. Chem. Phys., 1970, 52, 309. [all data]
Brown, Byfleet, et al., 1972
Brown, J.M.; Byfleet, C.R.; Howard, B.J.; Russell, D.K.,
The electron resonance spectra of BrO, IO and SeF in J=5/2 rotational levels,
Mol. Phys., 1972, 23, 457. [all data]
Durie and Ramsay, 1958
Durie, R.A.; Ramsay, D.A.,
Absorption spectra of the halogen monoxides,
Can. J. Phys., 1958, 36, 35. [all data]
Carrington, Levy, et al., 1967
Carrington, A.; Levy, D.H.; Miller, T.A.,
Stark effect in gas-phase electron resonance. The dipole moments of ClO, BrO, SH, and 1ΔSO,
J. Chem. Phys., 1967, 47, 3801. [all data]
Byfleet, Carrington, et al., 1971
Byfleet, C.R.; Carrington, A.; Russell, D.K.,
Electric dipole moments of open-shell diatomic molecules,
Mol. Phys., 1971, 20, 271. [all data]
Go To: Top, Gas phase ion energetics data, Constants of diatomic molecules, References
| EA | Electron affinity |
Copyright for NIST Standard Reference Data is governed by the Standard Reference Data Act.
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Standard Reference Data Program |
Data Gateway |
Chemistry WebBook |
If you have comments or questions about this site, please contact us.


Copyright 2017 Google Inc.
Copyright 2018-2019 the OpenGEE Contributors.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.


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Full name:
org.dellroad:dellroad-stuff-maven-plugin:2.1.0:git-describe
Description:
Attributes:
| Name | Type | Since | Description |
|---|---|---|---|
| abbrev | int | - | Instead of using the default 7 hexadecimal digits as the
abbreviated object name, use this many digits, or as many digits as
needed to form a unique object name. A value of 0 will suppress
long format, only showing the closest tag. Default value is: -1. User property is: abbrev. |
| all | boolean | - | Instead of using only the annotated tags, use any ref found in
refs/ namespace. This option enables matching any
known branch, remote-tracking branch, or lightweight tag. Default value is: false. User property is: all. |
| always | boolean | - | Show uniquely abbreviated commit object as fallback. Default value is: false. User property is: always. |
| candidates | int | - | Instead of considering only the 10 most recent tags as candidates
to describe the input consider up to this many candidates.
Increasing this value above 10 will take slightly longer but may
produce a more accurate result. A value of 0 will cause only exact
matches to be output. Default value is: -1. User property is: candidates. |
| committish | String | - | Commit-ish object name to describe. Defaults to HEAD
if not set. Note: this property is incompatible with
dirty. User property is: committish. |
| contains | boolean | - | Instead of finding the tag that predates the commit, find the tag
that comes after the commit, and thus contains it. Automatically
implies tags. Default value is: false. User property is: contains. |
| dirty | String | - | Describe the working tree. It means describe HEAD and
appends the configured value if the working tree is dirty. Note:
this property is incompatible with committish. User property is: dirty. |
| exactMatch | boolean | - | Only output exact matches (a tag directly references the supplied
commit). This is the same as setting candidates to
zero. Default value is: false. User property is: exactMatch. |
| firstParent | boolean | - | Follow only the first parent commit upon seeing a merge commit.
This is useful when you wish to not match tags on branches merged
in the history of the target commit. Default value is: false. User property is: firstParent. |
| longFormat | boolean | - | Always output the long format (the tag, the number of commits and
the abbreviated commit name) even when it matches a tag. This is
useful when you want to see parts of the commit object name in
"describe" output, even when the commit in question happens to be a
tagged version. Instead of just emitting the tag name, it will
describe such a commit as v1.2-0-gdeadbee (0th commit
since tag v1.2 that points at object
deadbee....). Default value is: false. User property is: long. |
| match | String | - | Only consider tags matching the given glob(7) pattern,
excluding the refs/tags/ prefix. This can be used to
avoid leaking private tags from the repository. User property is: match. |
| propertyName | String | - | The name of the Maven property to set. Default value is: git.describe. User property is: propertyName. |
| tags | boolean | - | Instead of using only the annotated tags, use any tag found in
refs/tags namespace. This option enables matching a
lightweight (non-annotated) tag. Default value is: false. User property is: tags. |
| workingDirectory | File | - | The git(1) working directory where the code is checked
out. Default value is: ${project.directory}. User property is: workingDirectory. |
all:
tags:


{% extends "base.html" %} {% load static %} {% block content %}
Version 1 - July 2018
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The information being hosted by the University of Cambridge for this Initiative is provided by Cambridgeshire County Council (the "AUTHORITY"). The information will be hosted on a restricted access webpage (the "WEBSITE").
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The Authority accepts no liability for the loss, theft, damage or destruction of computer or other related equipment used for the purposes of the Initiative.
{% if not accepted_tcs %} {% endif %} {% endblock %} {% block lazy_script %} {% if not accepted_tcs %} {% endif %} {% endblock %}


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Copyrigh 2015


We analyzed all 37 models for which surface air temperature was available from the historical and RCP8.5 simulations: ACCESS1-0, ACCESS1-3, bcc-csm1-1, bcc-csm1-1-m, BNU-ESM, CanESM2, CCSM4, CESM1-BGC, CESM1-CAM5, CMCC-CESM, CMCC-CM, CMCC-CMS, CNRM-CM5, CSIRO-Mk3-6-0, FGOALS-g2, GFDL-CM3, GFDL-ESM2G, GFDL-ESM2M, FIO-ESM, EC-EARTH, GISS-E2-H, GISS-E2-R, HadGEM2-AO, HadGEM2-CC, HadGEM2-ES, inmcm4, IPSL-CM5A-LR, IPSL-CM5A-MR, IPSL-CM5B-LR, MIROC5, MIROC-ESM, MIROC-ESM-CHEM, MPI-ESM-LR, MPI-ESM-MR, MRI-CGCM3, NorESM1-M, and NorESM1-ME. The historical simulation starts in the year 1850, with the exception of the three versions of HadGEM2, where it starts in 1860. The RCP8.5 simulation ends in 2100 and has been extended to 2300 in the models bcc-csm1-1, CCSM4, CNRM-CM5, CSIRO-Mk3-6-0, GISS-E2-G, GISS-E2-H, IPSL-CM5A-LR, and MPI-ESM-LR, and to 2299 in HadGEM2-ES. For GFDL-ESM2M, years 2101 to 2200 were also available but were not used for our analysis.
In the RCP8.5 scenario, atmospheric CO 2 shows an accelerated increase until the year 2100, when a radiative forcing of approximately 8.5 Wm −2 is reached. Thereafter, the CO 2 concentration stabilizes at almost 2000 parts per million ( 20), yielding the largest warming of all CMIP5 simulations. For each model, we combined the historical simulation, the RCP8.5 simulation, and (if available) the extended RCP8.5 simulation, obtaining one long time series per grid cell and model.
Although temperature output was available from all selected models, this is not true for all variables that we analyzed. Specifically, LH was not available for EC-EARTH, downwelling net radiation was not available for FIO-ESM and EC-EARTH, and surface soil moisture (shown in Fig. 2, A and D) was not available for the CMCC models, FIO-ESM, EC-EARTH, GISS-E2-R, HadGEM2-AO, HadGEM2-ES, inmcm4, the IPSL models, MIROC-ESM, and the MPI-ESM models.
We used two observational temperature data sets, based on in situ measurements from meteorological stations: HadCRUT4 ( 45) and the GISTEMP ( 46). The latter data set has been interpolated over a scale of 1200 km to fill spatial gaps between stations, which is the reason for the very uniform changes in the Arctic in fig. S8 ( 46). Because these data sets report temperature as standardized anomalies, we did not calculate absolute changes in variability, but only the direction of change as Kendall τ values. The GISTEMP data set has been obtained as version 5 from the GISS, https://data.giss.nasa.gov/gistemp/. The HadCRUT data set (version <IP_ADDRESS>) has been obtained from https://crudata.uea.ac.uk/cru/data/temperature/. Both data sets have been downloaded on 31 January 2018. The four reanalysis data sets and their sources are the following:
(1) NOAA-CIRES (National Oceanic and Atmospheric Administration–Cooperative Institute for Research in Environmental Sciences) 20th Century Reanalysis V2c ( 42), https://esrl.noaa.gov/psd/data/gridded/data.20thC_ReanV2c.monolevel.mm.html
(2) NCEP/DOE (National Centers for Environmental Prediction/Department of Energy) 2 Reanalysis data provided by the NOAA/OAR/ESRL PSD, Boulder, CO, USA ( 43), https://esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis2.gaussian.html
(3) MERRA2 (Modern-Era Retrospective Analysis for Research and Applications, version 2) ( 44), https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/
(4) ERA (European reanalysis)–Interim ( 41), http://apps.ecmwf.int/datasets/data/interim-full-daily/levtype=sfc/
All reanalysis data sets have been downloaded on 19 January 2018.
We used the monthly mean surface air temperature and removed the annual cycle at each grid cell within a running window of 30 years length, centered at the time point under consideration (fig. S8A). Choosing a baseline in such a local time window and considering each month separately are crucial to our analysis because it circumvents two problems: (i) the typical annual cycle changes over time ( 53, 54), for example, because the minimum and maximum sea-ice area occurs later in the year in a warmer world ( 54), and (ii) the choice of any specific reference period would lead to biases due to the limited sample size ( 47). Within the window and for each month, we subtracted the mean value of all 30 temperature values to obtain a temperature anomaly. Because of the necessity of 15 years of data to both sides of a data point, the procedure shortens each time series by 30 years.
Thereafter, we calculated the SD within a sliding window of 100 years that we moved along each anomaly time series at each grid cell in each model (fig. S8B). Hence, the window covers almost half the length of the whole time series like in previous studies ( 55). We calculated the trend in the obtained SD values based on the Kendal τ rank correlation coefficient (fig. S8C). A positive Kendal τ signals increasing SD, whereas a negative τ indicates decreasing SD. For example, a monotonous increase over time would yield τ = 1, whereas a monotonous decrease would yield τ = −1, and no trend would yield τ = 0. The Kendall τ values were used to assess the model agreement in fig. S1 and the hatching in Fig. 1. These sign agreements hence reflect the changes over the whole time series from 1850 to 2100.
For comparing trends in models and observations in the period 1958–2017, we used the same procedure but with a sliding window size of 15 years to remove the annual cycle, and 20 years to calculate the SD of the residuals. We took 1958 as the start year because we expected the anthropogenic fingerprint to be small before the mid–20th century and because only few observations are available from earlier years.
For comparing models and reanalysis data sets in the time period 1980–2010, we used a slightly different procedure: Instead of using a running window, we removed a linear trend from each month’s yearly time series. This linear trend removal is adequate because of the short time period and has the advantage that no data points are lost in the beginning and end of the time series. As we removed trends for each month separately, we still took into account that the typical annual cycle can change within the time period.
To calculate geographic maps ( Fig. 1 and figs. S2 and S3) and scatter plots ( Fig. 2) with changes in variability, we selected two time periods (1875–1904 and 2055–2084 to assess changes until 2100) from the anomaly time series mentioned above in each model.
When calculating seasonal changes, we only selected the anomalies from the specific months belonging to a season (hence removing all other months from the time series). For each model, season, and time period, we then calculated the SD of the anomaly time series for the variable under consideration and took the absolute and relative difference between the two periods for each season and model. Because the historical simulation from 1850–2005 includes the radiative forcing from volcanic eruptions (in particular the strong eruption of Mt. Krakatoa in 1883), whereas the future scenario does not, we verified the robustness of our results. For example, when using a base period from 1888 to 1917 (that is, excluding the Krakatoa eruption) or the preindustrial control simulations (which do not contain volcanic eruptions), our results remain essentially the same.
Thereafter, we averaged the resulting maps over all models. To do so, we brought the data on the same grid by interpolating each map to the grid of the model with the highest resolution (CCSM4), using a bilinear interpolation (CMCC-CM has even higher resolution but not all variables that we analyzed were available in that model, see above). The same method and grid were also used for interpolating the four reanalysis data sets. All multimodel averages are based on the same time period in each model.
The GDP per person (based on purchasing power parity) for Fig. 5 has been obtained from http://data.worldbank.org/indicator/NY.GDP.PCAP.PP.CD?view=chart for the year 2015. Countries smaller than 60,000 km 2 were omitted. For four countries, data from the year 2015 were not available, in which case we chose the most recent year for which data were available: Eritrea (2011), Libya (2011), Papua New Guinea (2014), and Venezuela (2013). To calculate changes in SD in individual countries ( Fig. 5), we interpolated the multimodel average of the relative annual SD changes ( Fig. 1C) to a global grid of 0.1 × 0.1 degrees using a bilinear interpolation. We then picked all grid cells in a particular country and calculated the area average. The country boundaries for creating the selection mask have been obtained from http://gadm.org/. Population estimates and projections have been obtained from https://esa.un.org/unpd/wpp/Download/Standard/Population/. Estimates for the year 2015 have been used for Fig. 5. Greenhouse gas emissions have been obtained from the World Resources Institute ( http://cait.wri.org). For Sudan, emissions from 2011 were used, whereas South Sudan was omitted. Country acronyms in Fig. 5 and fig. S7 are International Organization for Standardization alpha-3 codes.


{{ define "main" }} {{ $years := slice }} {{ range sort .Params.publications "year" "desc"}} {{ $years = $years | append .year}} {{ end }} {{ $years = $years | uniq }} {{ range $elem_val := $years }}


{% extends "base.html" %} {% block body %} {% if is_ipython %}
Full path: {{ full_path }}
{% endif %} {% from 'info_panel.html' import info_panel %} {% call info_panel() %}Click on a function name to view calls to that function.
Click on the icon to view the most recent call to that function.
{% endcall %}


{% include evaluation/challenges.html %} {% include evaluation/completion.html %} {% include evaluation/packages.html %} {% include evaluation/incomplete.html %} {% include evaluation/evaluation.html %} {% include evaluation/future.html %}


AP NewsAlert
by EndPlayNEW ROADS, La. - NEW ROADS, La. (AP) - Louisiana governor's office says novelist Ernest J. Gaines, who wrote about black struggles, has died at age 86.
NEW ROADS, La. - NEW ROADS, La. (AP) - Louisiana governor's office says novelist Ernest J. Gaines, who wrote about black struggles, has died at age 86.


ABAP Quick Fixes - Changelog version 1.1.1
Translate comment to English
quick fix works now again
Help content added to plugin


2019-06 - Todo.002 - to creating Todo applications in various technologies and techniques (whether good or bad).


WCPR Graphics and Logo Files
Right-click on the text below each image and choose "Save Target As" to download the file.
(Do not click on the image and choose "Save Picture As", they are lower quality thumbnails)
| Download Original Files: Must have appropriate editor | |
| WCPR Header.png(Fireworks) | |
| WCPR Header.psd (Photoshop) | |
| Seeper Logo.png(Fireworks) | |


White to play 22
pips White=114 Black=200
(CorrectAnswer= 0/0, ErrorScore= 0)
1. Bar/23 15/11 10/8 eq: +1.475 86.65% (G:66.89% B:12.79%) 13.35% (G: 0.25% B:0.01%) 2. Bar/23 15/13 10/8 6/4 eq: +1.473 (-0.001) 86.89% (G:66.52% B:12.46%) 13.11% (G: 0.22% B:0.00%) 3. Bar/23 15/13 10/8 3/1* eq: +1.413 (-0.061) 87.59% (G:63.25% B:8.58%) 12.41% (G: 0.94% B:0.03%) 4. Bar/23 15/11 6/4 eq: +1.361 (-0.114) 84.33% (G:62.44% B:11.92%) 15.67% (G: 0.92% B:0.03%) 5. Bar/23 10/8 3/1*(2) eq: +1.329 (-0.145) 83.55% (G:65.35% B:7.01%) 16.45% (G: 0.68% B:0.01%)


Custom builds make it easy to create lightweight versions of Lodash containing only the features you need. To top it off, we handle all function dependency & alias mapping for you. Review the build differences & pick the one that’s right for you.
The Lodash command-line interface is available when lodash-cli
is installed as a global package:
$ npm i -g npm$ npm i -g lodash-cli$ lodash -h
core
modifier.
lodash core
strict
modifier.
lodash strict
modularize
modifier.
lodash modularize
category
command to pass comma separated categories of functions to include in the build. Valid categories are “array”, “collection”, “date”, “function”, “lang”, “object”, “number”, “seq”, “string”, & “util”.
lodash category=collection,function
exports
command to pass comma separated names of ways to export the lodash
function. Valid exports are “amd”, “commonjs”, “es”, “global”, “node”, “npm”, “none”, & “umd”.
lodash exports=amd,node
iife
command to specify code to replace the IIFE that wraps Lodash.
lodash iife="\!function(window,undefined){%output%}(this)"
include
command to pass comma separated names of functions to include in the build.
lodash include=each,filter,map
minus
command to pass comma separated function/category names to remove from the build.
lodash minus=result,shuffle
plus
command to pass comma separated function/category names to add to the build.
lodash category=array plus=random,template
template
command to pass the file path pattern used to match template files to precompile. Note: Precompiled templates are assigned to the _.templates
object.
lodash template="./*.jst"
settings
command to pass template settings used when precompiling templates.
lodash settings="{interpolate:/\{\{([sS]+?)\}\}/g}"
moduleId
command to specify the AMD module ID for Lodash or the module ID used to include Lodash in compiled templates. Use “none” as the module ID to create compiled templates without a dependency on Lodash.
lodash moduleId=underscore
exports
values “es” & “npm” may only be used in conjunction with the modularize
commandmodularize
command uses the first exports
values as its module format, ignoring subsequent values-o
or --output
all files created are saved to the current working directoryThe following options are also supported:
-c
, --stdout
................ Write output to standard output-d
, --development
..... Write only the non-minified development output-h
, --help
.................... Display help information-m
, --source-map
....... Generate a source map using an optional source map URL-o
, --output
................ Write output to a given path/filename-p
, --production
....... Write only the minified production output-s
, --silent
............... Skip status updates normally logged to the console-V
, --version
............. Output current version of Lodash


| Package | Description |
|---|---|
| org.drip.execution.bayesian |
Bayesian Price Based Optimal Execution
|
| org.drip.execution.capture |
Execution Trajectory Transaction Cost Capture
|
| org.drip.execution.discrete |
Trajectory Slice Execution Cost Distribution
|
| org.drip.execution.principal |
Information Ratio Based Principal Trades
|
| org.drip.measure.gaussian |
R^1 R^d Covariant Gaussian Quadrature
|
| Modifier and Type | Class and Description |
|---|---|
class |
ConditionalPriceDistribution
ConditionalPriceDistribution holds the Price Distribution Conditional on a given Drift.
|
class |
PriorDriftDistribution
PriorDriftDistribution holds the Prior Belief Distribution associated with the Directional Drift.
|
| Modifier and Type | Method and Description |
|---|---|
R1UnivariateNormal |
PriorConditionalCombiner.jointPriceDistribution()
Generate the Joint Price Distribution
|
R1UnivariateNormal |
PriorConditionalCombiner.posteriorDriftDistribution(double dblDeltaS)
Generate the Posterior Drift Distribution
|
| Modifier and Type | Method and Description |
|---|---|
R1UnivariateNormal |
TrajectoryShortfallAggregate.totalCostDistribution()
Generate the Total Cost R^1 Normal Distribution
|
R1UnivariateNormal |
TrajectoryShortfallEstimator.totalCostDistributionSynopsis(ArithmeticPriceEvolutionParameters apep)
Generate the Total Cost Distribution Synopsis Distribution for the Trading Trajectory
|
R1UnivariateNormal |
LinearImpactUniformTrajectoryEstimator.totalCostDistributionSynopsis(ArithmeticPriceEvolutionParameters apep) |
R1UnivariateNormal |
LinearImpactTrajectoryEstimator.totalCostDistributionSynopsis(ArithmeticPriceEvolutionParameters apep) |
R1UnivariateNormal |
LinearImpactBlockTrajectoryEstimator.totalCostDistributionSynopsis(ArithmeticPriceEvolutionParameters apep) |
| Modifier and Type | Class and Description |
|---|---|
class |
ShortfallIncrementDistribution
ShortfallIncrementDistribution holds the Parameters of the R^1 Normal Short fall Increment Distribution.
|
| Modifier and Type | Method and Description |
|---|---|
R1UnivariateNormal |
GrossProfitEstimator.horizonPrincipalMeasure(double dblPrincipalDiscount)
Generate R^1 Univariate Normal Gross Profit Distribution from the specified Principal Discount
|
R1UnivariateNormal |
GrossProfitEstimator.principalMeasure(double dblPrincipalDiscount)
Generate R^1 Univariate Normal Gross Profit Distribution from the specified Principal Discount
|
| Modifier and Type | Method and Description |
|---|---|
static R1UnivariateNormal |
R1UnivariateNormal.Standard()
Generate a N (0, 1) distribution
|


Text goes here.
Name
HP
MP
$
XP
ASC RPG Demo v.<IP_ADDRESS>.9.8
Created by
Scott Geyer
for the
ASC
.
Contribute to the project at
Github
.


--- title: "BizTalk 2006 R2 Developer Edition on MSDN" layout: post ---
Thanks to Tomas Restrepo for pointing out that the Developer Edition of BizTalk 2006 R2 is now up on MSDN. If you're working with EDI and BizTalk server you seriously need to check this out and realize what is coming your way.


Gylfi Sigurdsson issues rallying cry to Everton teammates after win against Southampton
The Toffees have climbed up to 15th in the table after two positive results and next face bottom club Norwich ahead of a tricky run of fixtures in December
by David Anderson, https://www.mirror.co.uk/authors/david-anderson/Gylfi Sigurdsson claims it is time for Everton to climb the Premier League table.
Everton have risen out of the drop zone to 15th on the back of their mini-revival and Sigurdsson claims they must build on this momentum ahead of their next game against Norwich.
Norwich visit Goodison Park on Saturday week and Daniel Farke’s Canaries have the worst away record in the Premier League with just one point from six games.
Sigurdsson, 30, was heartened by Everton’s positive results in their last two games before the international break and says they must keep going.
“It’s extremely important to build from the Southampton game going forward,” said the Icelandic star.
“It was a strong showing to get the equaliser against Tottenham, followed by three points against Southampton.
“There are some tough games ahead of us. We have Norwich at home next and then four very tough games on the way.
“There’s not much to choose between many of the clubs.
“It’s time for us to start climbing up the table.”
Everton are only three points behind fifth-placed Sheffield United and Sigurdsson claims they could shoot up the table on the back of a run of wins.
“There are only three points between ourselves and fifth place, which is really amazing considering how things have been with us,” said the playmaker.
“The league is such that if you put together three results in a row you will jump up four or five places.
“There are lots of games ahead and it's a fun time when there is little time for training but plenty of games.”
Pressure had mounted on manager Marco Silva after they lost four Premier League games in a row, but the Toffees are now unbeaten in their last three in all competitions.


The layer "{{layerName}}" uses an outdated version of ATT&CK (v{{vmVersion}}). Do you want to open the workflow to upgrade this layer to ATT&CK v{{currVersion}}? This version is not supported by Navigator v{{nav_version}} and must be upgraded for use.


--- layout: page title: Lean Prover Zulip Chat Archive permalink: archive/113488general/09916outdatedwebsitelink.html ---
@Sebastian Ullrich The link at https://leanprover.github.io/documentation/ is outdated; it links to the Gitter chat room.
thought i would mention it since you recently updated README.md
{% endraw %}


From: JPMorgan Chase Bank
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To: < >
Subject: Frault Alert
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Dear ,
This is a fraud alert. Let us know immediately if you, or anyone you authorized, changed your Executive Card that was recently used for veterinary care. Please confirm you used your Citi® / Capitol One Executive Card ending for the transaction(s) noted below by confirming your age. You may not be able to make purchases on your Executive Card until we hear back from you!
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Bangladesh evacuates 100,000 as Cyclone Bulbul approaches
by AFPDHAKA: Bangladesh authorities have evacuated around 100,000 people from the country’s low-lying coastal villages and islands with Cyclone Bulbul set to slam into the country later on Saturday, officials said.
The Meteorological Department has asked local authorities and two ports to raise their highest alert, as the cyclone is expected to unleash a storm surge as high as seven feet (two metres) in coastal districts.
Bulbul, packing a maximum wind speed of 120 kilometres per hour (75 miles), is on course to make landfall near the Sundarbans, the world’s largest mangrove forest, which straddles Bangladesh and part of eastern India and is home to the endangered Bengal tigers.
The cyclone is expected to hit the Bangladesh coast at around 8 pm (1400 GMT), disaster management secretary Shah Kamal told AFP, adding there are plans to evacuate some 1.5 million people before that.
Authorities have suspended a nationwide school test, cancelled the holidays of officials posted in coastal districts and called off a traditional fair that draws tens of thousands of people in the Sundarbans.
Operations at the country’s two major ports – Mongla and Chittagong – have been suspended, Kamal said.
Some 55,000 volunteers have been mobilised to go door to door and alert people about the storm.
Bangladesh’s low-lying coast, home to 30 million people, is regularly battered by powerful cyclones that leave a trail of devastation in their wake.
Hundreds of thousands of people have been killed over the last few decades in cyclones, whose frequency and intensity have increased.
Bangladesh has, however, improved its preparedness in recent years, cutting the number casualties since Cyclone Sidr killed more than 3,000 people in 2007.
In May this year, Fani became the most powerful storm to hit the country in five years, but just over a dozen people were killed.


About
Rest API. They are all static assets in the API, such as cards, decks, avatars, game types, etc.
Links
Github repository: https://github.com/thefirstspine/rest/
Service URL: https://rest.thefirstspine.fr/
Rest API. They are all static assets in the API, such as cards, decks, avatars, game types, etc.
Github repository: https://github.com/thefirstspine/rest/
Service URL: https://rest.thefirstspine.fr/


This means that you have a simple loop that calls Sprite.SetPosition 200 times a second, the image of the sprite on the screen is still only being moved (by default) 33 times a second.
You can specify how many times a second Turing checks to see if a sprite has moved by using the Sprite.SetFrameRate procedure. Rates of 5-10 will make the movement of the sprites seem very choppy. Rates of 100 are more or less completely smooth (the maximum is 120) and most CRT's will not notice any difference after 60. The default rate is 33 frames per second. You should note that if you set the rate higher than your computer can handle, every other part of your program will slow down as Turing will be checking for sprite movement rather than executing your program.
A modern PC (2+ GHz with a decent graphics card) can probably handle a frame rate of 60+, depending on the number of sprites. A Pentium III should probably use the default rate. Slower machines should probably use a lower rate (around 20). Experimentation is the best way to determine the ideal frame rate.
This means that you can only call the function by calling Sprite.SetFrameRate, not by calling SetFrameRate.


|
PX4 Firmware
PX4 Autopilot Software http://px4.io
|
Directories | |
| directory | commander_tests |
Files | |
| file | accelerometer_calibration.cpp [code] |
| Implementation of accelerometer calibration. | |
| file | accelerometer_calibration.h [code] |
| Definition of accelerometer calibration. | |
| file | airspeed_calibration.cpp [code] |
| Airspeed sensor calibration routine. | |
| file | airspeed_calibration.h [code] |
| file | arm_auth.cpp [code] |
| file | arm_auth.h [code] |
| file | baro_calibration.cpp [code] |
| Barometer calibration routine. | |
| file | baro_calibration.h [code] |
| file | calibration_routines.cpp [code] |
| Calibration routines implementations. | |
| file | calibration_routines.h [code] |
| Don Gagne don@t hega gnes. com | |
| file | Commander.cpp [code] |
| file | Commander.hpp [code] |
| file | commander_helper.cpp [code] |
| Commander helper functions implementations. | |
| file | commander_helper.h [code] |
| Commander helper functions definitions. | |
| file | esc_calibration.cpp [code] |
| Definition of esc calibration. | |
| file | esc_calibration.h [code] |
| Definition of esc calibration. | |
| file | gyro_calibration.cpp [code] |
| Gyroscope calibration routine. | |
| file | gyro_calibration.h [code] |
| Airspeed sensor calibration routine. | |
| file | health_flag_helper.cpp [code] |
| Contains helper functions to efficiently set the system health flags from commander and preflight check. | |
| file | health_flag_helper.h [code] |
| Contains helper functions to efficiently set the system health flags from commander and preflight check. | |
| file | mag_calibration.cpp [code] |
| Magnetometer calibration routine. | |
| file | mag_calibration.h [code] |
| Barometer calibration routine. | |
| file | PreflightCheck.cpp [code] |
| Preflight check for main system components. | |
| file | PreflightCheck.h [code] |
| Preflight check for main system components. | |
| file | px4_custom_mode.h [code] |
| PX4 custom flight modes. | |
| file | rc_calibration.cpp [code] |
| Remote Control calibration routine. | |
| file | rc_calibration.h [code] |
| Remote Control calibration routine. | |
| file | rc_check.cpp [code] |
| file | rc_check.h [code] |
| RC calibration check. | |
| file | state_machine_helper.cpp [code] |
| State machine helper functions implementations. | |
| file | state_machine_helper.h [code] |
| State machine helper functions definitions. | |


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PACK THIS!
Basics
Travel Aids
Pleasure reading
Chewing gum
Snacks
Water bottle
Earplugs
Sleeping mask
Travel pillow
Motion sickness remedy
Sleeping pills
Anxiety medication
Funds
Wallet
Cash
Credit cards
Debit cards
Traveler's checks
Travel Info
Passport and visas
Driver's license
Itinerary
Tickets
Travel confirmation
Travel guides
Miscellaneous
Documents
Copies of travel documents
Copies of credit cards
Copies of passport
Credit-card contact info
Emergency contact info
Medical insurance card
Medical history
List of medications
Prescriptions
Travel insurance
Car insurance card
Bags
Backpack/daybag
Purses
Collapsible tote
Money belt
Shoulder straps
Plastic bags
Laundry
Laundry bag
Laundry kit
Stain remover
Sewing kit
Travel iron
Miscellaneous
Umbrella
House keys
Travel locks and keys
Luggage tags
Hospitality gifts
Journal
Sports gear
Contacts
Address book
Important numbers
Datebook
Business cards
Calling card
Technology
Cell phone & charger
Laptop & charger
Camera & charger
Headphones
Voltage adapters
Batteries
Flashlight
Binoculars
Alarm clock
Work
Work documents
Work reading
Office supplies
Notebook
Clothes
Basics
Underwear
Socks
Undershirts
Bras
Pantyhose
Sleepwear
Robe
Dressy
Dress shirts
Sweaters
Blazers
Slacks
Skirts
Dresses
Suits
Tuxedo
Outerwear
Jackets
Coats
Raincoats
Hats
Gloves
Scarves
Casual
T-shirts
Tank tops
Sweatshirts
Jeans
Shorts
Exercise clothing
Swimsuits
Footwear
Athletic shoes
Leisure shoes
Dress shoes
Sandals/flip-flops
Slippers
Accessories
Belts
Ties
Wristwatches
Robe
Jewelry
Glasses
Sunglasses
Reading glasses
Glasses cases
Hygeine
Toothbrush
Toothpaste
Dental floss
Mouthwash
Soap
Washcloth
Deodorant
Shampoo
Conditioner
Brush
Comb
Hair dryer
Curling/flat iron
Styling products
Hair accessories
Mirror
Cleanser
Sunscreen
Moisturizer
Lip balm
Contact lenses & case
Saline solution
Shaving cream
Razor
Perfume/cologne
Makeup
Makeup remover
Birth control
Feminine hygeine
Nail clippers
Nail file
Nail polish remover
Hand wipes
Tissues
Cotton balls
Cotton swabs
Tweezers
Lint roller
Insect repellent
Medications
Pain reliever
Vitamins
First-aid kit
Band-Aids
Bring half of what you think you need, and twice as much money.


| fastmap {fastmap} | R Documentation |
A fastmap object provides a key-value store where the keys are strings and the values are any R objects.
fastmap(missing_default = NULL)
missing_default |
The value to return when |
In R, it is common to use environments as key-value stores, but they can leak memory: every time a new key is used, R registers it in its global symbol table, which only grows and is never garbage collected. If many different keys are used, this can cause a non-trivial amount of memory leakage.
Fastmap objects do not use the symbol table and do not leak memory.
Unlike with environments, the keys in a fastmap are always encoded as UTF-8,
so if you call $set()
with two different strings that have the same
Unicode values but have different encodings, the second call will overwrite
the first value. If you call $keys()
, it will return UTF-8 encoded
strings, and similarly, $as_list()
will return a list with names that
have UTF-8 encoding.
Note that if you call $mset()
with a named argument, where the name is
non-ASCII, R will convert the name to the native encoding before fastmap has
the chance to convert them to UTF-8, and the keys may get mangled in the
process. However, if you use $mset(.list = x)
, then R will not convert
the keys to the native encoding, and the keys will be correctly converted to
UTF-8. With $mget()
, the keys will be converted to UTF-8 before they
are fetched.
fastmap
objects have the following methods:
set(key, value)
Set a key-value pair. key
must be a string. Returns value
.
mset(..., .list = NULL)
Set multiple key-value pairs. The key-value pairs are named arguments,
and/or a list passed in as .list
. Returns a named list where the
names are the keys, and the values are the values.
get(key, missing = missing_default)
Get a value corresponding to key
. If the key is not in the map,
return missing
.
mget(keys, missing = missing_default)
Get values corresponding to keys
, which is a character vector. The
values will be returned in a named list where the names are the same as
the keys
passed in, in the same order. For keys not in the map,
they will have missing
for their value.
has(keys)
Given a vector of keys, returns a logical vector reporting whether each key is contained in the map.
remove(keys)
Given a vector of keys, remove the key-value pairs from the map. Returns a logical vector reporting whether each item existed in (and was removed from) the map.
keys(sort = FALSE)
Returns a character vector of all the keys. By default, the keys will be
in arbitrary order. Note that the order can vary across platforms and is
not guaranteed to be consistent. With sort=TRUE
, the keys will be
sorted according to their Unicode code point values.
size()
Returns the number of items in the map.
as_list(sort = FALSE)
Return a named list where the names are the keys from the map, and the
values are the values. By default, the keys will be in arbitrary order.
Note that the order can vary across platforms and is not guaranteed to
be consistent. With sort=TRUE
, the keys will be sorted according
to their Unicode code point values.
reset()
Reset the fastmap object, clearing all items.
# Create the fastmap object m <- fastmap() # Set some key-value pairs m$set("x", 100) m$set("letters", c("a", "b", "c")) m$mset(numbers = c(10, 20, 30), nothing = NULL) # Get values using keys m$get("x") m$get("numbers") m$mget(c("letters", "numbers")) # Missing keys return NULL by default, but this can be customized m$get("xyz") # Check for existence of keys m$has("x") m$has("nothing") m$has("xyz") # Remove one or more items m$remove(c("letters", "x")) # Return number of items m$size() # Get all keys m$keys() # Return named list that represents all key-value pairs str(m$as_list()) # Clear the map m$reset() # Specify missing value when get() is called m <- fastmap() m$get("x", missing = key_missing()) #> <Key Missing> # Specify the default missing value m <- fastmap(missing_default = key_missing()) m$get("x") #> <Key Missing>


Reflection is a method by which we can use metadata at runtime to dynamically create an instance of a type, bind the type to an existing object, or get the type from an existing object and invoke its methods or access its fields and properties. It has many uses, ranging from allowing usage of attributes to creating instances of dynamically generated classes and using them. You can even use reflection to read and modify private member variables of an object. Today, we're going to look at a very simple example which will allow us to read the value of a public property given an instance.
The Class
Let's take a very simple class:
namespace MyNamespace { public class MyClass { public int MyProperty { get; set; } } }
Note, that I've put it in a separate namespace to show that it's easy to deal with this when using reflection.
The Runner
We'll run everything in a very simple console application:
public class Program { static void Main(string[] args) { new Program().Run(); } private void Run() { MyClass o = new MyClass { MyProperty = 25 }; object value = GetPropertyValue(o, "MyProperty"); Console.WriteLine(value); } }
We're basically creating an instance of MyClass and passing the instance and the string "MyProperty" to a method called GetProperty. The method is returning an object (which we could have cast to anything we needed). We're passing the returned object to Console.WriteLine.
The Method
This is where we use reflection to find the value of the "MyProperty" property given an instance. Add the following method to the class:
private object GetPropertyValue(object o, string propertyName) { Type type = o.GetType(); PropertyInfo info = type.GetProperty(propertyName); object value = info.GetValue(o, null); return value; }
We're getting the type information by calling GetType() on the object. Next, we call GetProperty() on the type information. Note, this only gives us information about the property and not the property itself. We then have to call GetValue() on the property information passing in the instance from which to get the actual value.
And that's all it takes :)
PS: You'll need a reference to System.Reflection to use Reflection.
PPS: Yes, this is a very very simple example of using reflection, but I found quite a few questions over at the forums today that would be answered by this. We all have to start somewhere, right?


{{bookData.title}}
by {{bookData.author}}
Please take the book from Counter {{bookLocation.shelf}} under Rack {{bookLocation.block}}
Issuing Date: {{todaysDate | date}}


{% extends 'base.html' %} {% load static %} {% block link %} {% endblock link %} {% block content %}
Are you sure you want to delete this?


Vote for Jayson Fong
National Honor Society
Technology Student Association
National Technical Honor Society
Technology Association of Georgia
Beta Rho Rho, Phi Theta Kappa Honor Society
Hello! Thanks for visiting my campaign website. My name is Jayson Fong and I am running for Discovery's National Honor Society secretary role. School clubs rarely change, but that does not mean they are perfect. Why not choose change instead of the regular?
Imagine automation and getting news right when it comes out, not when your friend tells you when it is too late. Imagine a system where you can effectively transform your work at NHS into a marvelous portfolio piece with increased logging. Know your hours at your own time – not an officer's.
I know business, and I know how to organize NHS. And I don't just say it, take a look at my previous work:
- Chief Operating Officer, Interbix Holdings LLC
- Systems Administrator, Mick Capital Pty. Ltd.
- Software Engineer, Mick Capital Pty. Ltd.
- Software Engineer, Marchet Ltd.
- Bronze, President's Volunteer Service Award
Still not convinced? Don't worry, I am a skeptic myself. Well...see, this website is not big enough for everything. Visit and connect with me on LinkedIn perhaps?
This is a far cry from all of what you need to know. Feel free to shoot me an e-mail if you have any questions using your school Gmail account.
Your vote matters and it is not just a cliche. Change Discovery for the better. Cast your vote today.
Your vote can mean all the difference. Thank you for your time here.


All Files
(88.24%
covered at
2.44
hits/line)
4 files in total.
102 relevant lines.
90 lines covered and
12 lines missed
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# As far as I can tell, Cassandra uses an x.x.x versioning scheme. This allows us
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# to quickly and easily sort cassandra versions.
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1
class CassandraVersion < Array
-
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1
def initialize version_string
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92
super(version_string.split('.').map { |sub_version| sub_version.to_i })
-
end
-
-
1
def < x
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3
(self <=> x) < 0
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end
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1
def > x
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3
(self <=> x) > 0
-
end
-
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1
def == x
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2
(self <=> x) == 0
-
end
-
end
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1
module Cli
-
-
1
LINE_WIDTH = 80
-
-
# Constrains text to a given width
-
1
def self.wrap(text, width)
-
# match the first width characters which are followed by some spaces or a newline
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# over and over, then tack on whatever is left.
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5
text.gsub(/(.{1,#{width}})( +|$\n?)|(.{1,#{width}})/, "\\1\\3\n").rstrip
-
end
-
-
# simply adds the given statement to the interface
-
1
def say statement
-
1
puts Cli.wrap(statement, LINE_WIDTH)
-
end
-
-
# returns value provided by the user
-
1
def ask property_name, default_answer, description
-
2
puts "\n#{Cli.wrap(description, LINE_WIDTH)}\n"
-
2
print "#{property_name} #{default_answer.nil? ? '' : "|#{default_answer}|"}: "
-
2
answer = gets.chomp
-
2
if answer.length == 0 and !default_answer.nil?
-
1
answer = default_answer
-
end
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2
return answer
-
end
-
-
end
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1
$: << File.dirname(__FILE__)
-
1
require "trollop"
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1
require "migrator"
-
1
require "prompter"
-
1
require "yaml"
-
-
# Contains the central control logic for the migration. Parses user input from the command line
-
# and delegates tasks to other helpers.
-
1
class Main
-
-
1
MISSING_OPTION = "Some options are missing"
-
1
MISSING_FILE = "could not be found. Please make sure the file exists"
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1
MISSING_MIGRATION = "No migration data for version"
-
1
MIGRATIONS_DIR = "#{File.dirname(__FILE__)}/migrations"
-
-
# verifies that migrations can be found for the to and from versions
-
1
def identify_migrations
-
1
orig = "cassandra_#{@opts[:original_version]}"
-
1
Trollop::die "#{MISSING_MIGRATION} #{orig}" unless File.exists? "#{MIGRATIONS_DIR}/#{orig}"
-
-
1
final = "cassandra_#{@opts[:final_version]}"
-
1
Trollop::die "#{MISSING_MIGRATION} #{final}" unless File.exists? "#{MIGRATIONS_DIR}/#{final}"
-
end
-
-
# parses command line options and stores them in @opts
-
1
def process_params
-
3
@opts = Trollop::options do
-
version "cassandra_migrate version 1 (c) 2013 Steven Mark McCraw"
-
banner <<-EOS
-
cassandra_migrate is a tool for migrating cassandra config files from one version to the next.
-
Usage:
-
cassandra_migrate [options]
-
[options] (all are required):
-
EOS
-
opt :original_config, "The location of the current cassandra.yaml that needs to be updated", :type => String
-
opt :final_config, "The location to write the updated cassandra.yaml file", :type => String
-
opt :original_version, "The version of Cassandra to migrate from", :type => String
-
opt :final_version, "The version of Cassandra to migrate to", :type => String
-
end
-
if @opts[:original_config].nil? or
-
3
@opts[:final_config].nil? or
-
@opts[:original_version].nil? or
-
@opts[:final_version].nil?
-
1
Trollop::die MISSING_OPTION
-
end
-
3
Trollop::die "#{@opts[:original_config]} #{MISSING_FILE}" unless File.exist?(@opts[:original_config])
-
end
-
-
# Highest level orchestration of program flow
-
1
def run
-
process_params
-
identify_migrations
-
-
# For the moment, we're only prompting for the migrations for a single machine,
-
# but we could have multiple migrators for multiple machines, and those could
-
# be aggregated here prior to prompting in order to bring multiple machines
-
# of varying versions up to a common configuration for a single version.
-
migrator = Migrator.new(@opts[:original_version], @opts[:final_version])
-
answers = Prompter.new.human_answers migrator.added_properties
-
final_config = Main.modify_config YAML.load_file(@opts[:original_config]), answers, migrator.removed_properties
-
File.open(@opts[:final_config], "w") {|file| file.write(final_config.to_yaml indentation:4)}
-
end
-
-
# Applies the diffs determined from our migrations,
-
# and returns the modified config object
-
1
def self.modify_config original_config, answers, removed_properties
-
2
removed_properties.each do |property|
-
1
original_config.delete property
-
end
-
-
2
answers.each do |property, answer|
-
1
original_config[property] = answer
-
end
-
2
return original_config
-
end
-
-
end
-
1
$: << File.dirname(__FILE__)
-
1
require "cassandra_version"
-
-
# Determines the full set of migrations between a start and end point, and calculates the
-
# set of additional properties needed between those points
-
1
class Migrator
-
-
1
STRING = "string"
-
1
ARRAY = "array"
-
1
NUMBER = "number"
-
1
HASH = "hash"
-
1
MIGRATIONS_DIR = "#{File.dirname(__FILE__)}/migrations"
-
-
1
def initialize start_version, end_version
-
4
@start_version = start_version
-
4
@end_version = end_version
-
4
@answers = {}
-
end
-
-
# Returns the full set of migrations. Assumes all migrations live in the migrations folder
-
1
def find_all_migrations
-
2
sorted_list = Dir.glob("#{MIGRATIONS_DIR}/**").sort do |file1, file2|
-
6
CassandraVersion.new(File.basename(file1).split("_")[1]) <=> CassandraVersion.new(File.basename(file2).split("_")[1])
-
end
-
2
in_range = false
-
2
applicable_migrations = []
-
2
sorted_list.each do |migration|
-
5
applicable_migrations << migration if in_range
-
5
if !in_range and (File::basename(migration) == "cassandra_#{@start_version}")
-
2
in_range = true
-
end
-
5
if in_range and (File::basename(migration) == "cassandra_#{@end_version}")
-
2
return applicable_migrations
-
end
-
end
-
end
-
-
1
def add_property name, type, default_value, description
-
8
@added_properties << {name: name, type: type, default_value: default_value, description: description}
-
end
-
-
1
def remove_property name
-
2
@removed_properties << name
-
end
-
-
# Determines what prompts must be removed and what prompts must be added to be able to migrate from start to finish
-
1
def calculate_changes
-
2
@added_properties = []
-
2
@removed_properties = []
-
2
all_migrations = find_all_migrations
-
2
all_migrations.each do |migration_name|
-
2
eval File.read(migration_name)
-
end
-
end
-
-
# The list of properties that must be added to migrate from start to finish
-
1
def added_properties
-
2
return @added_properties unless @added_properties.nil?
-
1
calculate_changes
-
1
return @added_properties
-
end
-
-
# The list of properties that must be removed to migrate from start to finish
-
1
def removed_properties
-
2
return @removed_properties unless @removed_properties.nil?
-
1
calculate_changes
-
1
return @removed_properties
-
end
-
-
end


Kronos
Beta v0.5
Welcome to Kronos FAST, quick
access to a simplified of
Kronos for on the go.
Enter Bell Times


This is a page of sticks and music that go well together!
You can make certain music trigger certain sticks automatically --
there are instructions at the bottom of this page.
Instructions | |||
You can make it so that certain music triggers certain visualizations --
set it to Randomize, then open the Stick Figures folder and
double-click on "Associate Sticks with Music". Here's how:
| |||
| If you have special favourites that you want to be listed here, please email them to me<EMAIL_ADDRESS>and I'll add them to this web page. |


Crossword Puzzle Maker
Title
Subtitle
Grid Height
Grid Width
*Height and Width will adjust based on input
Puzzle Mode
Crossword
Fill-In
Input (Enter the Word and Clue separated by a comma, each pair on a separate line)


Welcome to Skycon.Pdf documentation Wiki pages. Here you will find all information you need to know better Skycon.Pdf and how you can work.
Skycon.Pdf has no dependencies. You can DOWNLOAD from releases, into your Bin folder and add it as Reference.
What is it?
Skycon.Pdf is a core wrapper for wkhtmltopdf and ghostscript libraries that uses Webkit engine to convert HTML pages to PDF, Image and to print.
Where to use?
- All desktop/web applications need to communicate with a database
- Multi database operation
- Multi client application
- .Net / Asp.Net / .Net Core / Asp.Net Core
License
MIT


@string/excerpt
@string/excerpt
@string/excerpt
@string/excerpt
Believe it or not these are permissions requested by an application from Google Play supposed to be a celebrity face recognition game. And it has 1 to 5 millions installs. Amazing!
I tried to find out why developer may need those permission since beside in-app purchases all other have no reason. Of course, I got no answer.
Now, I cannot prove this application is actually doing but it is granted by Android operating system the rights to record sounds from microphone and send to another device. And because it prevent device from sleeping it can run while device seems to be on standby.
And at least one million users are exposed to this kind of attack.
Google Play SupportAnyway, applications that abuse user private data are not the norm. Vast majority requires, beside in-app purchasing, only networking access, perhaps to load content, or even no special privileges.
Computing Technologies are New Mediums - Paper and pencils have been around for centuries and we understand their best uses; computers, however, are still relatively new
Corollary - You can't simply digitize existing technologies and expect to revolutionize anything, e.g. online textbooks are just a convenience
Lau explained his take on the concept of "spaced repetition," wherein the absolute best time to review material is right before you forget it. Fortunately, this pattern of forgetting is extremely predictable, although it varies slightly from student to student. Rosetta Stone, the most famous language learning software, and the open source flashcard software Anki both use this same technique.
Finally, Lau closed with an example of his "perfect" tutor: a personalized teaching computer from the recent Star Trek movie. "I'm a huge geek, I've always wanted to show something like this," said Lau. "We're getting to the point where these science fiction ideas are almost here."
In my own experience, "individual learning" in high school was an excuse for teachers to not teach and to expect students to learn the material on their own time at home. Is our current paradigm of the teacher-classroom model not the most effective one? I don't believe simply handing a student a textbook is effective either, but is there a happy medium that will replace schools entirely and that leverages the analytical abilities of computers to learn how students learn?
reference@string/p1
@string/p2
@string/p3
Did you ever wonder what device ID and call information means? It is a permission requested by some apps and if you accept, that app is able to retrieve your phone number and all phone numbers you are talking with. Now, is obvious a kids learning app has no need for such permission; the only reason that permission is requested is to spy on you.


Rabbits are little creatures with long ears and puffy tails, and they move their nose up and down in an adorable way. They eat the most orange vegetables in our world, and they reproduce more than any human ever has.
Little Bunny Foo Foo,
I don't want to see you
scooping up the field mice
and bopping them on the head!
And down came the Good Fairy
And she said
"Little bunny Foo Foo
I don't like you're attitude
Scooping up the field mice
And bopping 'em on the head"
I'll give you 3 chances.
Then I'll turn you into a goon!
The next day…


[pre-Alpha]Mapillary Sequence Straightener
Mapillary sequence ID:
Edit. Left click to move and show image. Right click to set "Corner" image.
Attributions
Images from
Mapillary
Map:
(C)OpenStreetMap contributors
Display map:
Leaflet
Bug report at
Github


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Today we will be making a site from scratch using divs and spans to create a header, footer, sidebar and a content area.
So far, we have mostly seen "block" elements
They appear on the next line, like paragraphs
There are also "inline" elements
They appear on the same line that they are written on.

Content

Content

Main Heading

Some more content

.align-right {
text-align:right;
color: green;
font-weight: bold;
}

Lorem ipsum dolor sit amet, consectetur adipisicing elit

Sed do eiusmod tempor incididunt ut labore et dolore.

Magna aliqua. Ut enim ad minim veniam.

Quis nostrud exercitation ullamco.
Lorem ipsum dolor sit amet, consectetur adipisicing elit
Sed do eiusmod tempor incididunt ut labore et dolore.
Magna aliqua. Ut enim ad minim veniam.
Quis nostrud exercitation ullamco.
Let's create a site using divs to separate content into different sections on our page.
Create a header, content area, sidebar, and a footer.
Span is used to apply a specific style inline
.yellow {
color: yellow;
}

Paragraph with yellow text.

Paragraph with yellow text.
Let's add some spans to our content to help highlight some text.
Changing the format of a link when you hover over it is accomplished by using pseudo-classes.
CSS pseudo-classes are used to add special effects to some selectors.
selector:pseudo-class {
property: value;
}
Example:
a:link {
text-decoration: none;
}
a:link { color: #FF0000; } /* unvisited link */
a:visited { color: #00FF00; } /* visited link */
a:hover { color: #FF00FF; } /* mouse over link */
a:active { color: #0000FF; } /* selected link */
Note: a:hover MUST come after a:link and a:visited in the CSS definition in order to be effective!
Note: a:active MUST come after a:hover in the CSS definition in order to be effective!
Add pseudo classes to your links
Space between the border and the content
Space between the border and the content
Adds to the total width of the box.
padding: 15px;
10 pixels on top only
padding-top: 10px;
10 on top, 5 on right, 3 on bottom, 5 on left
padding: 10px 5px 3px 5px;
Four values
padding: top right bottom left;
Two values
padding: top/bottom right/left;
One value
padding: all;
padding: 10px 20px 30px 40px;
The edge around the box, specified as "thickness, style, color."
A solid red border
border: 1px solid #ff0000;
A thick dotted black top border
border-top: 4px dotted #000000;
Two diﬀerent border styles
border-top: 1px solid #ff0000;
border-bottom: 4px dotted #000000;
border-width: 10px;
border-style: dashed;
border-color: #666666;
You can specify each property separately, or all three together.
The transparent area around the box that separates it from other elements.
15 pixels on all sides
margin: 15px;
10 on top, 5 on right, 3 on bottom, 5 on left
margin: 10px 5px 3px 5px;
10 pixels on top
margin-top: 10px;
If a margin is set to auto on a box that has width, it will take up as much space as possible.
CENTERED
margin: auto;
width: 300px;
FLUSH-RIGHT
margin-left: auto;
margin-right: 5px;
width: 300px;
Let's add some padding, borders, and margins to our divs.
Let's center our entire document in the browser.
Sets the width of an element.
Does not include padding or borders, remember these add to the width.
Sets the height of an element.
Does not include padding or borders, remember these add to the width.
Add a width & height to our divs.
Use IDs to target each div with CSS


to: -4 && goal.status === 0), 'goal-date-over': (goal.goalLeftDays > 0 && goal.status === 0)}"> 0{{goal.until_date.day}}/ 0{{goal.until_date.month}}/{{goal.until_date.year}}
{{goal.description}}


Ant Conquest
Foragers
:
0
Cost:
10
Buy
Seeds
to
food
Fruit
to
food
Honeydew
to
food
Insects
to
food
Honey
to
food
Animals
to
food
Fungi
to
food
Nectar
to
food
Food Supply
:
0
Seeds
:
0
(
0
/s)
Fruit
:
0
(
0
/s)
Honeydew
:
0
(
0
/s)
Insects
:
0
(
0
/s)
Honey
:
0
(
0
/s)
Animals
:
0
(
0
/s)
Fungi
:
0
(
0
/s)
Nectar
:
0
(
0
/s)
Save Game
Delete Save
Copy
Import Game
Export Game
Meadow Ant Colonies
:
0
Display Colony Information
New Colony Cost:
5
Qu,
50
Wk
Queens:
0
Cost:
20
workers
Workers:
0
Cost:
10
food
To Queen
Auto Queen
Garden Ant Colonies
:
0
Display Colony Information
Create New Colony
Queens:
0
Workers:
0
Harvester Ant Colonies
:
0
Display Colony Information
Carpenter Ant Colonies
:
0
Display Colony Information
Weaver Ant Colonies
:
0
Display Colony Information
Red Stinging Ant Colonies
:
0
Display Colony Information
Honey Pot Ant Colonies
:
0
Display Colony Information
Fire Ant Colonies
:
0
Display Colony Information
Leaf Cutter Ant Colonies
:
0
Display Colony Information
Trap Jaw Ant Colonies
:
0
Display Colony Information
Argentine Ant Colonies
:
0
Display Colony Information
Army Ant Colonies
:
0
Display Colony Information
Bullet Ant Colonies
:
0
Display Colony Information
Food
Forager
Forage For Ants
Add to Food
Easy Queens
Meadow Worker
Meadow Queen
Meadow Colony
Log:
Expand
Home
Settings
Pause
Quick Save
Buy 1


Total Payoff: 0
This is the first block of trials. Each block consists of 35 trials.
You've only received sales data for 20 random stores (out of 200) in each region.
To help you evaluate the regional profits with incomplete data, your business analyst used statistics and created plots. Each plot shows the estimated average profit (in thousands of dollars) for a region based on the 20-store sample, and some uncertainty around the estimate (95% confidence interval).
This is the first block of trials. Each block consists of 35 trials.
You've only received sales data for 20 random stores (out of 200) in each region.
To help you evaluate the regional profits with incomplete data, your business analyst created plots like the one to the right. The points show the profits made by the twenty-store sample in a given region. Keep in mind that there are 200 stores in total in each region, so your data are incomplete.
This is the first block of trials. Each block consists of 35 trials.
You've only received sales data for 20 random stores (out of 200) in each region.
To help you evaluate the regional profits with incomplete data, your business analyst used statistics and created plots. Each plot shows the estimated average profit (in thousands of dollars) for a region based on the 20-store sample, and some uncertainty around the estimate (95% confidence interval). In addition, the grey blob shows the density of the average estimate: the blob is wider around estimates of profits that are more likely.
This is the first block of trials. Each block consists of 35 trials.
You've only received sales data for 20 random stores (out of 200) in each region.
To help you evaluate the regional profits with incomplete data,
your business analyst used statistics and created dot plots, see
the example on the right. Each big blue dot shows a possible
average profit for a region (an educated guess) based on your
partial data. Since there is uncertainty around the profit
values, your analyst plotted twenty dots/guesses.
This is the first block of trials. Each block consists of 35 trials.
You've only received sales data for 20 random stores (out of 200) in each region.
To help you evaluate with incomplete data,
your business analyst used statistics and created animations like the ones on the
right. Each frame shows an educated guess of the average
profit, and the animation shows 20 guesses in total.
This is the first block of trials. Each block consists of 35 trials.
Since you've only received incomplete sales data, i.e., 20 random stores
out of 200 in each region, your analyst made some educated
guesses about the real profits using statistics. On the right, the animation shows
one guess in each frame --- what the profits could be for
any 20 stores in the region.