Watch Ipswich boss Lambert's pre-Blackpool press conference LIVE from 9am
by Andy WarrenIpswich Town boss Paul Lambert is holding his pre-match press conference ahead of the game with Blackpool.
The Blues are back in League One action following a long lay-off since the 1-0 victory at Rochdale on November 5.
Since then the Blues have progressed in the FA Cup, following last-gasp victory over Lincoln in the two sides' replay on Wednesday night.
They also lost to Colchester in the EFL Trophy.
Lambert has rested many of his frontline players during that spell, but the likes of Luke Chambers, James Norwood and Cole Skuse will all return this weekend.
You can watch Lambert's press conference live, right here.


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import { constructors, particle } from '../core/library.js';
import { mergeOver, pushUnique, λnull } from '../core/utilities.js';
import { requestVector, releaseVector } from './vector.js';
import baseMix from '../mixin/base.js';
The Scrawl-canvas particle physics engine is a simple system designed to allow developers a way to add particle-based effects to their canvas animation scenes. The physics engine is built on top of the following components:
We do not have to handle particle generation and manipulation ourselves. Instead, Scrawl-canvas gives us three dedicated entitys which we use to add particle animation effects to the canvas scene. These entitys are:
The Scrawl-canvas particle physics engine system is based on a fairly classical understanding of particle kinetics (applying forces and constraints to a small, spherical object in 3D space) and kinematics (the movement of the small object in response to the forces and constraints applied to it).
A Scrawl-canvas Spring object connects together two Particle objects, linking them together with a set of constraints which together exert a spring force on the Particles.
The Spring factory uses the Base mixin, thus Spring objects can be cloned and killed like other Scrawl-canvas objects. Spring objects are stored in the scrawl.library.spring
section of the Scrawl-canvas library object.
import { constructors, particle } from '../core/library.js';
import { mergeOver, pushUnique, λnull } from '../core/utilities.js';
import { requestVector, releaseVector } from './vector.js';
import baseMix from '../mixin/base.js';
const Spring = function (items = {}) {
this.makeName(items.name);
this.register();
this.set(this.defs);
this.set(items);
if (!this.action) this.action = λnull;
return this;
};
let P = Spring.prototype = Object.create(Object.prototype);
P.type = 'Spring';
P.lib = 'spring';
P.isArtefact = false;
P.isAsset = false;
P = baseMix(P);
let defaultAttributes = {
particleFrom, particleTo - String name of a Particle, or the Particle object itself. These attributes hold references to the Particle objects involved in this constraint.
particleFrom: null,
particleFromIsStatic: false,
particleTo: null,
particleToIsStatic: false,
springConstant
- float Number. Larger values make the spring stiffer. Suggested values: 5 - 300
springConstant: 50,
damperConstant
- float Number. Larger values forces the spring to take a longer time to come to equilibrium. Suggested values: 5 - 50
damperConstant: 10,
restLength
- The spring’s ideal length - the further away from its ideal, the more force the spring will apply to its connected body objects to get them back to their optimal distance
restLength: 1,
};
P.defs = mergeOver(P.defs, defaultAttributes);
P.packetObjects = pushUnique(P.packetObjects, ['particleFrom', 'particleTo']);
P.kill = function () {
this.deregister();
return true;
};
let S = P.setters;
particleFrom
, particleTo
S.particleFrom = function (item) {
if (item.substring) item = particle[item];
if (item && item.type === 'Particle') this.particleFrom = item;
};
S.particleTo = function (item) {
if (item.substring) item = particle[item];
if (item && item.type === 'Particle') this.particleTo = item;
};
P.applySpring = function () {
let {particleFrom, particleTo, particleFromIsStatic, particleToIsStatic, springConstant, damperConstant, restLength} = this;
if (particleFrom && particleTo) {
let {position: fromPosition, velocity: fromVelocity, load: fromLoad} = particleFrom;
let {position: toPosition, velocity: toVelocity, load: toLoad} = particleTo;
let dVelocity = requestVector(toVelocity).vectorSubtract(fromVelocity),
dPosition = requestVector(toPosition).vectorSubtract(fromPosition);
let firstNorm = requestVector(dPosition).normalize(),
secondNorm = requestVector(firstNorm);
firstNorm.scalarMultiply(springConstant * (dPosition.getMagnitude() - restLength));
dVelocity.vectorMultiply(secondNorm).scalarMultiply(damperConstant).vectorMultiply(secondNorm);
let force = requestVector(firstNorm).vectorAdd(dVelocity);
if (!particleFromIsStatic) fromLoad.vectorAdd(force);
if (!particleToIsStatic) toLoad.vectorSubtract(force);
releaseVector(dVelocity, dPosition, firstNorm, secondNorm, force);
}
};
scrawl.makeNet({
name: 'test-net',
generate: function () {
let { name, particleStore, springs, springConstant, damperConstant } = this;
let leftParticle, rightParticle;
// generate particles
leftParticle = makeParticle({
name: `${name}-left`,
positionX: 0,
positionY: 0,
});
rightParticle = leftParticle.clone({
name: `${name}-right`,
positionX: 100,
});
leftParticle.run(0, 0, false);
rightParticle.run(0, 0, false);
particleStore.push(leftParticle, rightParticle);
// generate spring
let mySpring = makeSpring({
name: `${name}-link-${i}-${i+1}`,
particleFrom: leftParticle,
particleTo: rightParticle,
springConstant,
damperConstant,
restLength: 100,
});
springs.push(mySpring);
},
...
}).run();
const makeSpring = function (items) {
return new Spring(items);
};
constructors.Spring = Spring;
export {
makeSpring,
};


--- layout: default+ title: Verify Game (Steam Launcher) ---
1. Open your Steam Library
2. Right Click on Robocraft or whatever game your want to verify the game files of
3. Select Properties
4. Select Local Files tab
5. Select Verify Integrity of Game Cache...
6. Wait for it to complete and then click OK
7. Congratulations, you have verified the game! Now go test the game out to see if that fixed your problem.


MATERIAL SCEINCE IN QUNTUM COMPUTING
[Article 1]: New material shows high potential for quantum computing
A joint team of scientists at the University of California, Riverside, and the Massachusetts Institute of Technology is getting closer to confirming the existence of an exotic quantum particle called Majorana fermion, crucial for fault-tolerant quantum computing—the kind of quantum computing that addresses errors during its operation.
Quantum computing uses quantumphenomena to perform computations. Majorana fermions exist at the boundary of special superconductors called topological superconductors, which have a superconducting gap in their interiors and harbor Majorana fermions outside, at their boundaries. Majorana fermions are one of the most sought-after objects in quantum physics because they are their own antiparticles, they can split the quantum state of an electron in half, and they follow different statistics compared to electrons. Though many have claimed to have identified them, scientists still cannot confirm their exotic quantum nature.
The UCR-MIT team overcame the challenge by developing a new heterostructure material system, based on gold, that could be potentially used to demonstrate the existence and quantum nature of Majorana fermions. Heterostructure materials are made up of layers of drastically dissimilar materials that, together, show completely different functionalities when compared to their individual layers.
"It is highly nontrivial to find a material system that is naturally a topological superconductor," said Peng Wei, an assistant professor of physics and astronomy and a condensed matter experimentalist, who co-led the study, appearing in Physical Review Letters, with Jagadeesh Moodera and Patrick Lee of MIT. "A material needs to satisfy several stringent conditions to become a topological superconductor."
The Majorana fermion, considered to be half of an electron, is predicted to be found at the ends of a topological superconductor nanowire. Interestingly, two Majorana fermions can combine with each other to make up one electron, allowing the quantum states of the electron to be stored nonlocally—an advantage for fault-tolerant quantum computing.
In 2012, MIT theorists, led by Lee, predicted that heterostructures of gold can become a topological superconductor under strict conditions. Experiments done by the UCR-MIT team have achieved all the needed conditions for heterostructures of gold.
"Achieving such heterostructure is highly demanding because several material physics challenges needed to be addressed first," said Wei, a UCR alum who returned to campus in 2016 from MIT.
Wei explained that the research paper shows superconductivity, magnetism, and electrons' spin-orbit coupling can co-exist in gold—a difficult challenge to meet—and be manually mixed with other materials through heterostructures.
"Superconductivity and magnetism ordinarily do not coexist in the same material," he said.Gold is not a superconductor, he added, and neither are the electron states on its surface."Our paper shows for the first time that superconductivity can be brought to the surface states of gold, requiring new physics," he said. "We show that it is possible to make the surface state of gold a superconductor, which has never been shown before."
The research paper also shows the electron density of superconductivity in the surface states of gold can be tuned."This is important for future manipulation of Majorana fermions, required for better quantum computing," Wei said. "Also, the surface state of gold is a two-dimensional system that is naturally scalable, meaning it allows the building of Majorana fermion circuits."Besides Wei, Moodera, and Lee, the research team also includes Sujit Manna and Marius Eich of MIT.


Method List
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eternity RecurringDate::Enumerator
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infinity RecurringDate::Enumerator
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#initialize RecurringDate::Enumerator
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#inspect RecurringDate::Enumerator
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#matching RecurringDate::Enumerator
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#mday RecurringDate::Enumerator
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#month RecurringDate::Enumerator
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#mweek RecurringDate
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#mweek RecurringDate::Enumerator
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#not_matching RecurringDate::Enumerator
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#not_mday RecurringDate::Enumerator
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#not_month RecurringDate::Enumerator
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#not_mweek RecurringDate::Enumerator
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#not_wday RecurringDate::Enumerator
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#not_yday RecurringDate::Enumerator
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#not_year RecurringDate::Enumerator
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#pattern RecurringDate::Enumerator
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#reject RecurringDate::Enumerator
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#select RecurringDate::Enumerator
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#select_with_index RecurringDate::Enumerator
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#take RecurringDate::Enumerator
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#take_while RecurringDate::Enumerator
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#to_enum RecurringDate
-
#until RecurringDate::Enumerator
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#wday RecurringDate::Enumerator
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#yday RecurringDate::Enumerator
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#year RecurringDate::Enumerator


In as name to here them deny wise this. As rapid woody my he me which. Men but they fail shew just wish next put. Led all visitor musical calling nor her. Within coming figure sex things are. Pretended concluded did repulsive education smallness yet yet described. Had country man his pressed shewing. No gate dare rose he. Eyes year if miss he as upon.
e-mail<EMAIL_ADDRESS>telefone: (11) 9978-6589


THE SOUND OF MUSIC
September 16-28, 1980 at the Arabian Theatre
Director - Wess Hughes
Music Director - Michael Burt
Choreographer - Mary Ann Sumrall
Assistants to the Director - Carolyn Ruth Blake, Barbara Hines
THE CAST
Maria - Juanaree Slade, Brenda Carey
Capt. Von Trapp - Bruce McCraw, Edd Jussely
Liesl - Melanie Butler, Karen Flowers
Louisa - Pam Goodwin, Martie Allen
Frederick - Michael Hess, Jon Howard
Brigitta - Stuart Williams, Rusty Allen
Kurt - Elizabeth McLaughlin, Theresa Lockhart
Marta - Jacqueline Jones, Marty Sumrall
Gretl - Amy Burt, April Harper
Max - Ken Culpepper, Connie Farrell
Elsa - Robin Rogers, Marie Melichar
Mother Abbess - Marge Mayers, Linda Nash
Sister Berthe - Suzanne Mullins, Anita Boyd
Sister Magaretta - Linda Jenkins
Sister Sophia - Lori Barnett, Sonja Myers
Franz - Roger Smith
Frau Schmidt - Betty Whitt, Fedwa Rahaim
Rolf - Jimmy Knight, Ron Boyd
Herr Zeller - Bill Agin
Baron Elberfield - Clyde Allen, John McRae
Baroness Elberfield - Billie Graham, Beverly McRae
Admiral von Schreiber - Jeff Holder
Puppet Trio - Nancy Allen, Cherie Boone, Sharon Loving
The Nun's Chorus
Nancy Allen, Lori Ball, Lori Barnett, Cherie Boone, Adrian Boyd,
Anita Boyd, Jane Bridges, Anne Chesser, Janie Crabtree, Karen Curtis,
Rosemary Farrell, Roseanne Ford, Billie Graham, Kathy Hawkins,
Enid Henderson, Lynn Jefcoat, Linda Jenkins, Terry Keith, Jan Liberto,
Robin Logan, Sharon Loving, Greta Martin, Barbara Mauldin,
Marie Melichar, Suzanne Mullins, Sonja Myers, Mary Ann Peterson,
Jerry Pippin, Faith Poore, Gretchel Rahaim, Betty Slocum, Betty Stone,
Levada Strickland, Connie Taylor, Caroline Thompson, Polly Walker, Lynn Warren
The Von Trapp Neighbors
John Bisnette, Carolyn Blake, Ed Diket, John Jeffries, Billy Lightsey,
David Smith
The Village Childrens' Chorus
Allison Ainsworth, Patricia Anderson, Nathaniel Blackledge,
Christy Buckler, Tammy Chatham, Melissa Diket, Leah Friend,
Donna Lynn Harper, Mike Hedgepeth, Tanya Hedgepeth,
Shannon Henderson, Lyle Hull, Hassen Jones, Malen Jones,
Ragan Jones, Kristy Jussely, Carrie Kuyrkendall, Jennifer Lightsey,
Ruby Lovett, Julie Mayers, Stephan Nash, Forrest Nelson, Lisa Noel,
Jennifer Orman, Todd Orman, Stephanie Powers, Tracy Rahaim,
Robert Ringo, Tiffany Roberts, Ruth Ellen Strickland, Shelly Sumrall,
Jessica Tanner, Laura Tullos, Amy Wallace, Amy Williams,
Robin Williams, Melissa Windham


Altar of Saints:
The altar is depleted of its power. Its former purity is gone. One more altar to go.


I'm Abishek Sriram G,currently pursuing III-year B.Tech in Information and Communication Technology from SASTRA University ,Thanjavur. Basically I'm a Coding lover.Currently working on Web development and APP development.It will never give up.Stay positive!


{% extends "global/Page.html" %} {% load staticfiles otree %} {% load i18n %} {% block title %} Decision {% endblock %} {% block content %}
You have {{ endowment }} in this round.
The lottery has {{ probability }} chance to pay {{ high }} and {{ probability_r }} chance to pay {{ low }}.
Please specify the lowest sure amount that you accept in exchange for the lottery.
{% formfield player.ce label="What is the minimum sure amount that you accept?" %} {% next_button %} {# {% include Constants.instructions_template %}#} {% endblock %}


Register now to get your VIP Customer ID
Enter your age below to get your VIP Customer ID,
that you can use for our Special Offers:
If you are above 18 and register before 11AM you will get the Gold Customer ID, with a value between 0-200
If you are above 18 and register after 11AM you will get the Silver Customer ID, with a value between 201-601
For those of you that are under the age of 18, you will get a ID number between 601-1000, for use in the youth department


--- layout: default title: Wildlife filmmaker and cameraman in India overview: true ---
I am a specialist film editor & cameraman, working in natural history, science, environment & non-fiction documentary films. As an editor & filmmaker, I am passionate about telling stories. My experience in editing and shooting natural history sequences as well as presentor led formats helps me tell impactful stories. You can see my showreel below to see a sample of my work.
I’ve assisted in editing feature films for cinema and giant screen release as well as television documentaties. I've workded in Avid I've worked in both Apple Final Cut Pro X and Premiere Pro for editing 1080p, 4K, 6K & 8K footage. I've also had extensive experience in color correction & grading in DaVince Resolve. My experience also includes working with broadcast quality 4K, 6K & 8K footage, cameras, drones, high-speed cameras and gimbals. I have played various roles in the productions including assistant editor, assistant cameram and sound recordist.


Read Online The Comic Book Story Of Beer The World S Favorite Beverage From 7000 Bc To Today S Craft Brewing Revolution Full Pdf Online Flip Ebook Pages 1 3 Anyflip Anyflip
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Read Comics Online Free Avatar The Last Airbender Comic Book Issue 001 Page 1


Your State Pension
You can get your State Pension on 8 November 2039. Your forecast is
£159.55 a week
£693.76 a month, £8,325.09 a year
Your forecast
- is not a guarantee and is based on the current law
- does not include any increase due to inflation
You need to continue to contribute National Insurance to reach your forecast
- £121.35 a week
- £159.55 a week
£159.55 is the most you can get
You cannot improve your forecast any further, unless you choose to put off claiming.
If you’re working you may still need to pay National Insurance contributions until 8 November 2039 as they fund other state benefits and the NHS.
View your National Insurance record
Changes to your forecast
Your forecast may be different if there are any changes to your National Insurance information. There is more about this in the terms and conditions.
The government has proposed to increase your State Pension age by up to a year. These proposals are not yet law. Check GOV.UK for future announcements.
You’ve been in a contracted-out pension scheme
Like most people, you were contracted out of part of the State Pension.


| <=> | -> | compare_without_coercion |
| to_s | -> | to_default_s |
| inspect | -> | default_inspect |
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/date_time/conversions.rb, line 76 76: def self.civil_from_format(utc_or_local, year, month=1, day=1, hour=0, min=0, sec=0) 77: offset = utc_or_local.to_sym == :local ? local_offset : 0 78: civil(year, month, day, hour, min, sec, offset) 79: end
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/date_time/calculations.rb, line 11 11: def current 12: ::Time.zone_default ? ::Time.zone.now.to_datetime : ::Time.now.to_datetime 13: end
DateTimes aren‘t aware of DST rules, so use a consistent non-DST offset when creating a DateTime with an offset in the local zone
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/date_time/calculations.rb, line 7 7: def local_offset 8: ::Time.local(2007).utc_offset.to_r / 86400 9: end
Duck-types as a Date-like class. See Object#acts_like?.
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/date_time/acts_like.rb, line 5 5: def acts_like_date? 6: true 7: end
Uses Date to provide precise Time calculations for years, months, and days. The options parameter takes a hash with any of these keys: :years, :months, :weeks, :days, :hours, :minutes, :seconds.
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/date_time/calculations.rb, line 51 51: def advance(options) 52: d = to_date.advance(options) 53: datetime_advanced_by_date = change(:year => d.year, :month => d.month, :day => d.day) 54: seconds_to_advance = (options[:seconds] || 0) + (options[:minutes] || 0) * 60 + (options[:hours] || 0) * 3600 55: seconds_to_advance == 0 ? datetime_advanced_by_date : datetime_advanced_by_date.since(seconds_to_advance) 56: end
Returns a new DateTime representing the time a number of seconds ago Do not use this method in combination with x.months, use months_ago instead!
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/date_time/calculations.rb, line 60 60: def ago(seconds) 61: since(-seconds) 62: end
Returns a new DateTime where one or more of the elements have been changed according to the options parameter. The time options (hour, minute, sec) reset cascadingly, so if only the hour is passed, then minute and sec is set to 0. If the hour and minute is passed, then sec is set to 0.
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/date_time/calculations.rb, line 34 34: def change(options) 35: ::DateTime.civil( 36: options[:year] || year, 37: options[:month] || month, 38: options[:day] || day, 39: options[:hour] || hour, 40: options[:min] || (options[:hour] ? 0 : min), 41: options[:sec] || ((options[:hour] || options[:min]) ? 0 : sec), 42: options[:offset] || offset, 43: options[:start] || start 44: ) 45: end
Layers additional behavior on DateTime#<=> so that Time and ActiveSupport::TimeWithZone instances can be compared with a DateTime
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/date_time/calculations.rb, line 106 106: def compare_with_coercion(other) 107: other = other.comparable_time if other.respond_to?(:comparable_time) 108: other = other.to_datetime unless other.acts_like?(:date) 109: compare_without_coercion(other) 110: end
Returns the utc_offset as an +HH:MM formatted string. Examples:
datetime = DateTime.civil(2000, 1, 1, 0, 0, 0, Rational(-6, 24)) datetime.formatted_offset # => "-06:00" datetime.formatted_offset(false) # => "-0600"
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/date_time/conversions.rb, line 49 49: def formatted_offset(colon = true, alternate_utc_string = nil) 50: utc? && alternate_utc_string || ActiveSupport::TimeZone.seconds_to_utc_offset(utc_offset, colon) 51: end
Returns the simultaneous time in Time.zone.
Time.zone = 'Hawaii' # => 'Hawaii' DateTime.new(2000).in_time_zone # => Fri, 31 Dec 1999 14:00:00 HST -10:00
This method is similar to Time#localtime, except that it uses Time.zone as the local zone instead of the operating system‘s time zone.
You can also pass in a TimeZone instance or string that identifies a TimeZone as an argument, and the conversion will be based on that zone instead of Time.zone.
DateTime.new(2000).in_time_zone('Alaska') # => Fri, 31 Dec 1999 15:00:00 AKST -09:00
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/date_time/zones.rb, line 14 14: def in_time_zone(zone = ::Time.zone) 15: ActiveSupport::TimeWithZone.new(utc? ? self : getutc, ::Time.__send__(:get_zone, zone)) 16: end
Seconds since midnight: DateTime.now.seconds_since_midnight
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/date_time/calculations.rb, line 27 27: def seconds_since_midnight 28: sec + (min * 60) + (hour * 3600) 29: end
Returns a new DateTime representing the time a number of seconds since the instance time Do not use this method in combination with x.months, use months_since instead!
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/date_time/calculations.rb, line 66 66: def since(seconds) 67: self + Rational(seconds.round, 86400) 68: end
Converts self to a Ruby Date object; time portion is discarded
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/date_time/conversions.rb, line 61 61: def to_date 62: ::Date.new(year, month, day) 63: end
To be able to keep Times, Dates and DateTimes interchangeable on conversions
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/date_time/conversions.rb, line 72 72: def to_datetime 73: self 74: end
Convert to a formatted string. See Time::DATE_FORMATS for predefined formats.
This method is aliased to to_s.
datetime = DateTime.civil(2007, 12, 4, 0, 0, 0, 0) # => Tue, 04 Dec 2007 00:00:00 +0000 datetime.to_formatted_s(:db) # => "2007-12-04 00:00:00" datetime.to_s(:db) # => "2007-12-04 00:00:00" datetime.to_s(:number) # => "20071204000000" datetime.to_formatted_s(:short) # => "04 Dec 00:00" datetime.to_formatted_s(:long) # => "December 04, 2007 00:00" datetime.to_formatted_s(:long_ordinal) # => "December 4th, 2007 00:00" datetime.to_formatted_s(:rfc822) # => "Tue, 04 Dec 2007 00:00:00 +0000"
DateTime formats are shared with Time. You can add your own to the Time::DATE_FORMATS hash. Use the format name as the hash key and either a strftime string or Proc instance that takes a time or datetime argument as the value.
# config/initializers/time_formats.rb Time::DATE_FORMATS[:month_and_year] = "%B %Y" Time::DATE_FORMATS[:short_ordinal] = lambda { |time| time.strftime("%B #{time.day.ordinalize}") }
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/date_time/conversions.rb, line 34 34: def to_formatted_s(format = :default) 35: if formatter = ::Time::DATE_FORMATS[format] 36: formatter.respond_to?(:call) ? formatter.call(self).to_s : strftime(formatter) 37: else 38: to_default_s 39: end 40: end
Attempts to convert self to a Ruby Time object; returns self if out of range of Ruby Time class If self has an offset other than 0, self will just be returned unaltered, since there‘s no clean way to map it to a Time
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/date_time/conversions.rb, line 67 67: def to_time 68: self.offset == 0 ? ::Time.utc_time(year, month, day, hour, min, sec) : self 69: end
Adjusts DateTime to UTC by adding its offset value; offset is set to 0
Example:
DateTime.civil(2005, 2, 21, 10, 11, 12, Rational(-6, 24)) # => Mon, 21 Feb 2005 10:11:12 -0600 DateTime.civil(2005, 2, 21, 10, 11, 12, Rational(-6, 24)).utc # => Mon, 21 Feb 2005 16:11:12 +0000
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/date_time/calculations.rb, line 90 90: def utc 91: new_offset(0) 92: end
Returns true if offset == 0
# File /usr/lib/ruby/gems/1.8/gems/activesupport-3.0.0.beta4/lib/active_support/core_ext/date_time/calculations.rb, line 96 96: def utc? 97: offset == 0 98: end


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{% extends 'accounts/pages/login.html' %} {% load static %} {% load crispy_forms_tags %} {% block content %}
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College GameDay Staff Makes Week 13 Picks For 2019 Season
by Matt LombardiESPN College GameDay is in Columbus, Ohio ahead of Saturday’s huge matchup between Ohio State and Penn State. The game will likely decide the Big Ten East and determine which team gets to move on to the league’s title game.
This week’s celebrity guest picker was former Ohio State running back Eddie George. George took the Buckeyes to roll over the Nittany Lions on Saturday afternoon.
Lee Corso also picked Ohio State to win at home. He donned the famous Brutus Buckeye headgear to make his selection.
Here are the picks for Desmond Howard, Kirk Herbstreit, Corso and George this week.
Lehigh vs. Lafayette
Desmond Howard: Lafayette
Eddie George: Lehigh
Lee Corso: Tie
Kirk Herbstreit: Lehigh
Harvard vs. Yale
Desmond Howard: Yale
Eddie George: Yale
Lee Corso: Yale
Kirk Herbstreit: Yale
Temple vs. Cincinnati
Desmond Howard: Cincinnati
Eddie George: Cincinnati
Lee Corso: Cincinnati
Kirk Herbstreit: Cincinnati
SMU vs. Navy
Desmond Howard: SMU
Eddie George: SMU
Lee Corso: SMU
Kirk Herbstreit: SMU
Pitt vs. Virginia Tech
Desmond Howard: Virginia Tech
Eddie George: Pittsburgh
Lee Corso: Virginia Tech
Kirk Herbstreit: Virginia Tech
Boston College vs. Notre Dame
Desmond Howard: Notre Dame
Eddie George: Notre Dame
Lee Corso: Notre Dame
Kirk Herbstreit: Notre Dame
Georgia vs. Texas A&M
Desmond Howard: Georgia
Eddie George: Georgia
Lee Corso: Georgia
Kirk Herbstreit: Georgia
Texas vs. Baylor
Desmond Howard: Baylor
Eddie George: Baylor
Lee Corso: Texas
Kirk Herbstreit: Baylor
USC vs. UCLA
Desmond Howard: USC
Eddie George: USC
Lee Corso: USC
Kirk Herbstreit: USC
Iowa vs. Illinois
Desmond Howard: Illinois
Eddie George: Iowa
Lee Corso: Iowa
Kirk Herbstreit: Illinois
Michigan vs. Indiana
Desmond Howard: Michigan
Eddie George: Michigan
Lee Corso: Indiana
Kirk Herbstreit: Michigan
Ohio State vs. Penn State
Desmond Howard: Ohio State
Eddie George: Ohio State
Lee Corso: Ohio State
Kirk Herbstreit: Ohio State
Ohio State vs. Penn State is set to kick off at Noon ET on FOX.


| Modifier and Type | Method and Description |
|---|---|
Filter |
FilteredAssociator.getFilter()
Gets the filter used.
|
| Modifier and Type | Method and Description |
|---|---|
void |
FilteredAssociator.setFilter(Filter value)
Sets the filter
|
| Constructor and Description |
|---|
FilteredAssociationRules(Filter filter,
AssociationRules rules)
Constructs a new FilteredAssociationRules.
|
FilteredAssociationRules(Object producer,
Filter filter,
AssociationRules rules)
Constructs a new FilteredAssociationRules.
|
FilteredAssociationRules(String producer,
Filter filter,
AssociationRules rules)
Constructs a new FilteredAssociationRules.
|
| Modifier and Type | Method and Description |
|---|---|
Filter |
FilteredClassifier.getFilter()
Gets the filter used.
|
| Modifier and Type | Method and Description |
|---|---|
void |
FilteredClassifier.setFilter(Filter filter)
Sets the filter
|
| Modifier and Type | Method and Description |
|---|---|
Filter |
FilteredClusterer.getFilter()
Gets the filter used.
|
| Modifier and Type | Method and Description |
|---|---|
static Canopy |
Canopy.aggregateCanopies(List<Canopy> canopies,
double aggregationT1,
double aggregationT2,
NormalizableDistance finalDistanceFunction,
Filter missingValuesReplacer,
int finalNumCanopies)
Aggregate the canopies from a list of Canopy clusterers together into one
final model.
|
void |
FilteredClusterer.setFilter(Filter filter)
Sets the filter.
|
void |
Canopy.setMissingValuesReplacer(Filter missingReplacer)
Set a ready-to-use missing values replacement filter
|
| Modifier and Type | Method and Description |
|---|---|
Filter |
FilteredDistance.getFilter()
Gets the filter used.
|
| Modifier and Type | Method and Description |
|---|---|
void |
FilteredDistance.setFilter(Filter filter)
Sets the filter
|
| Modifier and Type | Method and Description |
|---|---|
Filter |
FilteredNeighbourSearch.getFilter()
Gets the filter used.
|
| Modifier and Type | Method and Description |
|---|---|
void |
FilteredNeighbourSearch.setFilter(Filter filter)
Sets the filter
|
| Modifier and Type | Class and Description |
|---|---|
class |
AllFilter
A simple instance filter that passes all instances directly
through.
|
class |
MultiFilter
Applies several filters successively.
|
class |
RenameRelation
A simple filter that allows the relation name of a set of instances to be
altered in various ways.
|
class |
SimpleBatchFilter
This filter is a superclass for simple batch filters.
|
class |
SimpleFilter
This filter contains common behavior of the SimpleBatchFilter and the
SimpleStreamFilter.
|
class |
SimpleStreamFilter
This filter is a superclass for simple stream filters.
|
| Modifier and Type | Method and Description |
|---|---|
Filter |
CheckSource.getFilter()
Gets the filter being used for the tests, can be null.
|
Filter |
MultiFilter.getFilter(int index)
Gets a single filter from the set of available filters.
|
Filter[] |
MultiFilter.getFilters()
Gets the list of possible filters to choose from.
|
Filter |
CheckSource.getSourceCode()
Gets the class to test.
|
static Filter[] |
Filter.makeCopies(Filter model,
int num)
Creates a given number of deep copies of the given filter using
serialization.
|
static Filter |
Filter.makeCopy(Filter model)
Creates a deep copy of the given filter using serialization.
|
| Modifier and Type | Method and Description |
|---|---|
static void |
Filter.batchFilterFile(Filter filter,
String[] options)
Method for testing filters ability to process multiple batches.
|
static void |
Filter.filterFile(Filter filter,
String[] options)
Method for testing filters.
|
static Filter[] |
Filter.makeCopies(Filter model,
int num)
Creates a given number of deep copies of the given filter using
serialization.
|
static Filter |
Filter.makeCopy(Filter model)
Creates a deep copy of the given filter using serialization.
|
static void |
Filter.runFilter(Filter filter,
String[] options)
runs the filter instance with the given options.
|
void |
CheckSource.setFilter(Filter value)
Sets the filter to use for the comparison.
|
void |
MultiFilter.setFilters(Filter[] filters)
Sets the list of possible filters to choose from.
|
void |
CheckSource.setSourceCode(Filter value)
Sets the class to test.
|
static Instances |
Filter.useFilter(Instances data,
Filter filter)
Filters an entire set of instances through a filter and returns the new
set.
|
| Modifier and Type | Class and Description |
|---|---|
class |
AddClassification
A filter for adding the classification, the class
distribution and an error flag to a dataset with a classifier.
|
class |
AttributeSelection
A supervised attribute filter that can be used to
select attributes.
|
class |
ClassConditionalProbabilities
Converts the values of nominal and/or numeric attributes into class conditional probabilities.
|
class |
ClassOrder
Changes the order of the classes so that the class
values are no longer of in the order specified in the header.
|
class |
Discretize
An instance filter that discretizes a range of numeric attributes in the dataset into nominal attributes.
|
class |
MergeNominalValues
Merges values of all nominal attributes among the
specified attributes, excluding the class attribute, using the CHAID method,
but without considering re-splitting of merged subsets.
|
class |
PartitionMembership
* A filter that uses a PartitionGenerator to generate partition membership values; filtered instances are composed of these values plus the class attribute (if set in the input data) and rendered as sparse instances.
|
| Modifier and Type | Class and Description |
|---|---|
class |
ClassBalancer
Reweights the instances in the data so that each class has the same total weight.
|
class |
SpreadSubsample
Produces a random subsample of a dataset.
|
class |
StratifiedRemoveFolds
This filter takes a dataset and outputs a specified
fold for cross validation.
|
| Modifier and Type | Class and Description |
|---|---|
class |
AbstractTimeSeries
An abstract instance filter that assumes instances form time-series data and
performs some merging of attribute values in the current instance with
attribute attribute values of some previous (or future) instance.
|
class |
Add
An instance filter that adds a new attribute to the
dataset.
|
class |
AddCluster
A filter that adds a new nominal attribute
representing the cluster assigned to each instance by the specified
clustering algorithm.
|
class |
AddExpression
An instance filter that creates a new attribute by
applying a mathematical expression to existing attributes.
|
class |
AddID
An instance filter that adds an ID attribute to the
dataset.
|
class |
AddNoise
An instance filter that changes a percentage of a
given attribute's values.
|
class |
AddUserFields
A filter that adds new attributes with user
specified type and constant value.
|
class |
AddValues
Adds the labels from the given list to an attribute
if they are missing.
|
class |
CartesianProduct
A filter for performing the Cartesian product of a set of nominal attributes.
|
class |
Center
Centers all numeric attributes in the given dataset to have zero mean (apart from the class attribute, if set).
|
class |
ChangeDateFormat
Changes the date format used by a date attribute.
|
class |
ClassAssigner
Filter that can set and unset the class index.
|
class |
ClusterMembership
A filter that uses a density-based clusterer to
generate cluster membership values; filtered instances are composed of these
values plus the class attribute (if set in the input data).
|
class |
Copy
An instance filter that copies a range of
attributes in the dataset.
|
class |
DateToNumeric
A filter for turning date attributes into numeric ones.
|
class |
FirstOrder
This instance filter takes a range of N numeric
attributes and replaces them with N-1 numeric attributes, the values of which
are the difference between consecutive attribute values from the original
instance. eg:
Original attribute values 0.1, 0.2, 0.3, 0.1, 0.3 New attribute values 0.1, 0.1, -0.2, 0.2 The range of attributes used is taken in numeric order. |
class |
FixedDictionaryStringToWordVector
Converts String attributes into a set of attributes
representing word occurrence (depending on the tokenizer) information from
the text contained in the strings.
|
class |
InterquartileRange
A filter for detecting outliers and extreme values
based on interquartile ranges.
|
class |
KernelFilter
Converts the given set of data into
a kernel matrix.
|
class |
MakeIndicator
A filter that creates a new dataset with a Boolean
attribute replacing a nominal attribute.
|
class |
MathExpression
Modify numeric attributes according to a given
mathematical expression.
|
class |
MergeInfrequentNominalValues
Merges all values of the specified nominal attributes that are insufficiently frequent.
|
class |
MergeManyValues
Merges many values of a nominal attribute into one
value.
|
class |
MergeTwoValues
Merges two values of a nominal attribute into one
value.
|
class |
NominalToBinary
Converts all nominal attributes into binary numeric
attributes.
|
class |
NominalToString
Converts a nominal attribute (i.e. set number of
values) to string (i.e. unspecified number of values).
|
class |
Normalize
Normalizes all numeric values in the given dataset
(apart from the class attribute, if set).
|
class |
NumericCleaner
A filter that 'cleanses' the numeric data from
values that are too small, too big or very close to a certain value,
and sets these values to a pre-defined default.
|
class |
NumericToBinary
Converts all numeric attributes into binary
attributes (apart from the class attribute, if set): if the value of the
numeric attribute is exactly zero, the value of the new attribute will be
zero.
|
class |
NumericToDate
A filter for turning numeric attributes into date attributes.
|
class |
NumericToNominal
A filter for turning numeric attributes into
nominal ones.
|
class |
NumericTransform
Transforms numeric attributes using a given
transformation method.
|
class |
Obfuscate
A simple instance filter that renames the relation,
all attribute names and all nominal attribute values.
|
class |
OrdinalToNumeric
An attribute filter that converts ordinal nominal attributes into numeric ones
|
class |
PartitionedMultiFilter
A filter that applies filters on subsets of
attributes and assembles the output into a new dataset.
|
class |
PKIDiscretize
Discretizes numeric attributes using equal
frequency binning and forces the number of bins to be equal to the square root of
the number of values of the numeric attribute.
|
class |
PotentialClassIgnorer
This filter should be extended by other unsupervised attribute filters to
allow processing of the class attribute if that's required.
|
class |
PrincipalComponents
Performs a principal components analysis and
transformation of the data.
|
class |
RandomProjection
Reduces the dimensionality of the data by projecting it onto a lower dimensional subspace using a random matrix with columns of unit length.
|
class |
RandomSubset
Chooses a random subset of attributes, either an absolute number or a percentage.
|
class |
Remove
An filter that removes a range of attributes from
the dataset.
|
class |
RemoveByName
Removes attributes based on a regular expression
matched against their names.
|
class |
RemoveType
Removes attributes of a given type.
|
class |
RemoveUseless
This filter removes attributes that do not vary at
all or that vary too much.
|
class |
RenameAttribute
This filter is used for renaming attributes.
|
class |
RenameNominalValues
Renames the values of nominal attributes.
|
class |
Reorder
A filter that generates output with a new order of
the attributes.
|
class |
ReplaceMissingValues
Replaces all missing values for nominal and numeric attributes in a dataset with the modes and means
from the training data.
|
class |
ReplaceMissingWithUserConstant
Replaces all missing values for nominal, string,
numeric and date attributes in the dataset with user-supplied constant
values.
|
class |
ReplaceWithMissingValue
A filter that can be used to introduce missing values in a dataset.
|
class |
SortLabels
A simple filter for sorting the labels of nominal
attributes.
|
class |
Standardize
Standardizes all numeric attributes in the given dataset to have zero mean and unit variance (apart from the class attribute, if set).
|
class |
StringToNominal
Converts a range of string attributes (unspecified
number of values) to nominal (set number of values).
|
class |
StringToWordVector
Converts string attributes into a set of numeric attributes representing word occurrence
information from the text contained in the strings.
|
class |
SwapValues
Swaps two values of a nominal attribute.
|
class |
TimeSeriesDelta
An instance filter that assumes instances form time-series data and replaces attribute values in the current instance with the difference between the current value and the equivalent attribute attribute value of some previous (or future) instance.
|
class |
TimeSeriesTranslate
An instance filter that assumes instances form time-series data and replaces attribute values in the current instance with the equivalent attribute values of some previous (or future) instance.
|
class |
Transpose
Transposes the data: instances become attributes and attributes become instances.
|
| Modifier and Type | Method and Description |
|---|---|
Filter |
PartitionedMultiFilter.getFilter(int index)
Gets a single filter from the set of available filters.
|
Filter[] |
PartitionedMultiFilter.getFilters()
Gets the list of possible filters to choose from.
|
Filter |
KernelFilter.getPreprocessing()
Gets the filter used for preprocessing
|
| Modifier and Type | Method and Description |
|---|---|
void |
PartitionedMultiFilter.setFilters(Filter[] filters)
Sets the list of possible filters to choose from.
|
void |
KernelFilter.setPreprocessing(Filter value)
Sets the filter to use for preprocessing (use the AllFilter for no
preprocessing)
|
| Modifier and Type | Class and Description |
|---|---|
class |
NonSparseToSparse
An instance filter that converts all incoming
instances into sparse format.
|
class |
Randomize
Randomly shuffles the order of instances passed
through it.
|
class |
RemoveDuplicates
Removes all duplicate instances from the first batch of data it receives.
|
class |
RemoveFolds
This filter takes a dataset and outputs a specified
fold for cross validation.
|
class |
RemoveFrequentValues
Determines which values (frequent or infrequent
ones) of an (nominal) attribute are retained and filters the instances
accordingly.
|
class |
RemoveMisclassified
A filter that removes instances which are
incorrectly classified.
|
class |
RemovePercentage
A filter that removes a given percentage of a
dataset.
|
class |
RemoveRange
A filter that removes a given range of instances of
a dataset.
|
class |
RemoveWithValues
Filters instances according to the value of an
attribute.
|
class |
Resample
Produces a random subsample of a dataset using
either sampling with replacement or without replacement.
|
class |
ReservoirSample
Produces a random subsample of a dataset using the
reservoir sampling Algorithm "R" by Vitter.
|
class |
SparseToNonSparse
An instance filter that converts all incoming sparse instances into non-sparse format.
|
class |
SubsetByExpression
Filters instances according to a user-specified expression.
|
| Modifier and Type | Method and Description |
|---|---|
Filter |
Filter.getFilter() |
| Modifier and Type | Method and Description |
|---|---|
void |
Filter.setFilter(Filter c)
Set the filter to be wrapped by this bean
|
| Modifier and Type | Field and Description |
|---|---|
static Filter |
PreprocessPanel.PreprocessDefaults.FILTER |
| Modifier and Type | Method and Description |
|---|---|
Filter |
Filter.getFilter()
Get the filter.
|
| Modifier and Type | Method and Description |
|---|---|
void |
Filter.setFilter(Filter filter)
Set the filter.
|
Copyright © 2018 University of Waikato, Hamilton, NZ. All Rights Reserved.


For the convolution problems I actually wrote a convolution algorithm that I used to get
the convoluted signals requested in A-E. I used the convolute function along with multiplication and
subtraction ( 2f(t) - (f(t) * Gaussian)) .
Part A - Rect Function * Rect Function As we move one rectangle over another the value of the convoluted signal at each point is dependent upon the values around that point. As a result when the rectangle signals are superimposed the signal doubles. As an example at time point m + n - 1 where m is the length of the input and n the length of the impulse, the kernel barely overlaps the input signal and so the output value at that point is small which also happens to be the same value as the point where the kernel and the input signal overlap for the first time (the signal is symmetrical). This operation has a smoothing effect of the signal (we go from two hard edges to only one hard edge). Part B - Rect Function * Gaussian Function The Gaussian function has a smoothing effect on the input function just like the Rect Function did in part A. The difference is in the localization of the smoothing effect. The Rect function averages over a wider range and thus the smoothing can be quite dramatic and in fact changes the shape of the input signal from a square to a triangle. The Gaussian tends to have a smaller span and so the averaging occurs more locally and the smoothing effect is redendered as the softening of edges while retaining the shape of the original signal. Part C - Gaussian Function * Gaussian Function On the homework assignment that I turned in I included the derivation sequence for why a gaussian convolved with a gaussian produces another gaussian. It is at the end of the assignment. The mathematical explanation without the derivation sequence is based on the fact that a gaussian function is closed under convolution. This is due to the fact that the derivative of e^x is e^x. Thus the integral of e^x is e^x. So anytime we want to get the derivative or integral we get back an equation of the same form that varies only according to whatever the true value for x is. When we convolute two gaussians we simply multiply them together to get the equation in terms of only one function (which is a gaussian) and a constant (the derivation sequence show this really well) and then solve for the integral which returns to us another gaussian as the output. Part E - Gaussian Function * Noise Function D had a greater effect on the Noise function than E in the sense that the convolution of the Rect Function with the noise function produced a smoother more symmetrical output function. This also is the biggest difference between the two convoluted outputs. While the Gaussian also smoothed the noise function to an extent because of the way the averaging is done when using the Gaussian as the impulse we see the inconsistencies as waviness in the curve (not symmetrical). |


Keep going forward because success will come
The dataset used for the training of this website contains 14999 rows and 9 question variable to predict the target wheather the employee will stay or quit. The 9 variables used for the prediction are satisfaction level (in %), last evaluation i.e., the satisfaction level last time this observation was made (in %), number of projects the employee is currently working on, Average monthly hours employee works in the company, number of years the employee has already worked in the company, wheather the employee has been involved in a work accident before, wheather the employee has received any promotion in last five years, the department in which the employee works in and the salary range i.e., low, medium or high.
Given below is certain stats to visualize Data Imbalance.
We used several different different machine learning algorithms, for the prediction of the employee will wheather stay or quit the company.In total we used 7 different machine learning algorithms for the purpose of prediction.The name of these machine learning algorithms is as follows, Decision Tree Classifier, K Nearest Neighbors, Logistic Regression, Multi Layer Perceptron, Gaussian Naive Bayes, Random Forest Classifier and Support Vector Machine.The different accuracy score which we observed from all these machine learning algorithms is as follows:-
| Method | Score |
|---|---|
| Decision Tree Classifier | 98.3 |
| K Nearest Neighbors | 99.2 |
| Logistic Regression | 79.3 |
| Multi Layer Perceptron | 89.9 |
| Gaussian Naive Bayes | 93.8 |
| Random Forest Classifier | 64.8 |
| Support Vector Machine | 90.4 |


The U.S. Federal Reserve is planning to release a real-time payment and settlement service in order to boost the payments infrastructure in the country.

Sanyadurnov06-Aug-19 04:18 AM
@jl777c do u have some interest from the companies in using antara after launch?
Maybe some big companies?
Caglio06-Aug-19 04:18 AM
@Sanyadurnov well I am thinking 10 Grand is a decent chip in already
maybe i need to put a bit more
p.06-Aug-19 04:18 AM
@Caglio fam chill lol
maybe a stop loss
Caglio06-Aug-19 04:18 AM
so selfish of me
actionslacks06-Aug-19 04:19 AM
you paid that to whoever sold you that order
p.06-Aug-19 04:19 AM
^^^^^
Caglio06-Aug-19 04:19 AM
exactly
seems right now everyone just sells kmd tho
actionslacks06-Aug-19 04:21 AM
nope no one is buying or selling. it's just exchange bots trying to move to random real bids and asks
i could move the price right now using coinbene
likely most are staking on binance or have iron hands and are waiting
p.06-Aug-19 04:23 AM
few not most
most capitulated
pretty sure hollowman was trolling earlier as well
actionslacks06-Aug-19 04:25 AM
thats just hollow. and at least he's funny about it.
volume is anemic, traders are chasing other butterflies rn.
kmd didn't kidnap your sister.
Alexfrog06-Aug-19 04:30 AM
actually it did, theyre demanding a ransom for her of 1M KMD
i need you all to sell to me at 1 sat each so i can afford it
Do you think all of those US customers will migrate to atomic dex ?
polycryptoblog06-Aug-19 04:41 AM
Binance USA will probably be up shortly after that
Caglio06-Aug-19 04:42 AM
So ? nothing happens then rofl ?
actionslacks06-Aug-19 04:43 AM
the people who know are likely trading on the info and not telling anyone since insider trading in crypto is what the cool kids do now.
Caglio06-Aug-19 04:44 AM
Wish I could get some inside information
Except falling for the best tech memery
actionslacks06-Aug-19 04:45 AM
we are afloat on a ship of fools. the whole space is mostly bullshit(edited)
polycryptoblog06-Aug-19 04:48 AM
Komodo has a bright future ahead from what I see.  But it’s the market and Komodo has the funds to outlast the market fluctuations.


fun setNegativeButtonText(visibility: String): Unit
Sets the negative button text
visibility - String The negative text to be shown in the button
visibility


--- layout: post date: 2012-01-26 time: "10:00:00" authors: ["Greg Wilson"] title: Our Long Tail tags: ["Noticed"] ---
Frequency a page is viewed (as a percentage of total views) vs. pages (ordered by frequency); data taken over the last 90 days. I guess there's something to this "long tail" stuff after all.


In example 3 you don't modify the array. In all other examples you modify either the contents or the internal array pointer. This is important when it comes to PHP arrays because of the semantics of the assignment operator.
The assignment operator for the arrays in PHP works more like a lazy clone. Assigning one variable to another that contains an array will clone the array, unlike most languages. However, the actual cloning will not be done unless it is needed. This means that the clone will take place only when either of the variables is modified (copy-on-write).
Here is an example:
$a = array(1,2,3);
$b = $a; // This is lazy cloning of $a. For the time
// being $a and $b point to the same internal
// data structure.
$a[] = 3; // Here $a changes, which triggers the actual
// cloning. From now on, $a and $b are two
// different data structures. The same would
// happen if there were a change in $b.
Coming back to your test cases, you can easily imagine that foreach
creates some kind of iterator with a reference to the array. This reference works exactly like the variable $b
in my example. However, the iterator along with the reference live only during the loop and then, they are both discarded. Now you can see that, in all cases but 3, the array is modified during the loop, while this extra reference is alive. This triggers a clone, and that explains what's going on here!
Here is an excellent article for another side effect of this copy-on-write behaviour: The PHP Ternary Operator: Fast or not?
each()
at the end of the first test case, where we see that the array pointer of the original array points to the second element, since the array was modified during the first iteration. This also seems to demonstrate thatforeach
moves the array pointer on before executing the code block of the loop, which I was not expecting - I would have thought it would do this at the end. Many thanks, this clears it up for me nicely. – DaveRandom Apr 8 '12 at 15:59


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| Week | Date | Lecture | Presentations | Labs | Assignments | DUE | Readings (For class) |
|---|---|---|---|---|---|---|---|
| 01/16 | HOLIDAY | ||||||
| 1 | 01/23 |
Introduction
Privacy, Security, and HIPAA (Find on E-Campus/Other Info) |
Guest (Privacy Officer) | L1 | A1 | None | None |
| 2 | 01/30 | Fundamentals of Computing | L2 | A2 | A1 & P. Email |
R1 | |
| 3 | 02/06 | Computer Programming | Grp 1 | L3 Week 1 | A3 Week 1 | A2 | R2 |
| 4 | 02/13 | Networks | Grp 2 | L3 Week 2 | A3 Week 2 | A3 Week 1 | R3 |
| 5 | 02/20 | Web | Grp 3 | L4 | A4 | A3 | R4 |
| 6 | 02/27 | SQL I | Grp 4 | L5 Week 1 | A5 Week 1 | A4 | R5 |
| 7 | 03/06 | SQL II | Grp 5 | L5 Week 2 | A5 Week2, Mid Review | R6 | |
| 03/13 | Spring Break | A5(3/12) | |||||
| 8 | 03/20 | Data to Decisions, Review Assignment 5 | Midterm | L6 | A6 | Mid Review | None |
| 9 | 03/27 | Data to Decision & Coding | Guest (Coder) | L6 & A6 Progress Report | R7 | ||
| 10 | 04/03 | IT Management | Grp 6 | A7 | A6 | R8 | |
| 11 | 04/10 | Standards & HIE | Guest (HIE Use Case) | A7 Progress Report | R9 | ||
| 12 | 04/17 | Security | Grp 7 | A8 | A7 | R10 | |
| 13 | 04/24 | Wrap Up & Review | Grp 8 | Guest (HIPAA Compliance Officer, RCHI) | Review | A8 | |
| 14 | 05/1 | Final |
[I] Internet: search online, find, and read
[L] Link: click on the link
[A] Article: get from the library, usually available on ejournal format


|
< Earlier Kibitzing · PAGE 2 OF 2 ·
Later Kibitzing> |
| Jan-21-13 | | Whitehat1963: I can't see the site now, but I'm sure you can find the instructions on the Guess-the-Move page. You probably just copy and paste this game's URL in a box somewhere on the Guess-the-Move page. |
|
Jan-21-13
| | perfidious: <Whitehat> Never went to the GTM page till your prompt, but have submitted this game. Thank you sir! |
|
| Jan-21-13 | | Whitehat1963: You're very welcome. I think you'll find that you'll enjoy playing Guess the Move. Over the years I think I've placed about 2,000 games in the database, mostly famous games, those of the highest-level players, or games with somewhat baffling move orders (in my opinion), but my skills aren't such that I'm good at finding really tough ones. In any event, enjoy yourself! |
|
| Jul-27-13 | | Xeroxx: Cool game. |
|
| Aug-08-13 | | EvanTheTerrible: Cool. |
|
| Aug-09-13 | | hedgeh0g: Quite possibly the quickest rout of a GM who didn't hang a piece in the opening. Although, admittedly, Black played like a complete amateur here, Kurnosov prosecuted his attack brilliantly and some of the variations after 13.Rxe6! are particularly aesthetic. I think making this tomorrow's GotD would serve as a fitting tribute to this inspiring player. |
|
Aug-09-13
| | keypusher: Lovely. f6-f7 mate after 14....Bxc6 is the same as could have occurred at the end of this game Carlsen vs Nakamura, 2013
which I never thought I'd see once, let alone twice. |
|
| Dec-28-13 | | hudapri: Was there a chance this was preparation? I don't know the Sicilian but it seems like a forcing line. |
|
| May-31-15 | | Poisonpawns: <hudapri Was there a chance this was prepration?> Yes; a lack of preparation. |
|
| May-31-15 | | Conrad93: The premium membership is worth it just for Guess The Move and the Opening Explorer alone. |
|
| May-31-15 | | I Like Fish: cool...
hello xeroxx...
hola evan... |
|
Oct-30-15
| | Mating Net: 11.d5 is one of the best examples of forcing open lines against the enemy King. |
|
Mar-28-16
| | An Englishman: Good Evening: Never understood why the Byrne Variation (4.Bg5) never became the primary weapon for White vs. the Pirc. In fact, I gave up the Pirc because I trusted of Black's responses to the Byrne--even though no one ever played it in a game against me! |
|
| Mar-28-16 | | Razgriz: 15. ... Qxd7
16. f7+ Kxf7 or Kf8
17. Qxd7+
and Good luck trying to defend against that attack |
|
| Mar-28-16 | | Razgriz: Whoops. I pasted the wrong line. Sorry
15. ... Qxd7
16. f7+ Kxf7
17. Qxd7+ Kf8 (if Kg8, then Bc4#)
18. Qe7+ Kg8
19. Bc4#
Other option is..
15. ... Qxd7
16. f7+ Kg8
17. Qxd7 Rd8
18. Qxd8#
I like the pun, goes well with how he broke down the door and he didn't even have to use the king side pieces. |
|
| Mar-28-16 | | not not: 11... Na4?? I don't get it. Can you violate someone's half like that? Can you kick the door to someone's house and walk in just like that? what was wrong with grabing white pawn on d5 instead? the white pawn is a criminal being in black half, why is black commiting the same crime with Na4? what does computer say about this move? it defies logic |
|
| Mar-28-16 | | not not: oh I see it now Qc6 check and capture knight via pin |
|
| Mar-28-16 | | not not: perhaps it was better to kill that little criminal on f6 on the spot with 9...Nf6 why to spare him and let him terrorise local population from f6? |
|
Mar-28-16
| | morfishine: Impressive demolition <13.Rxe6+> exploding Black's position. Surreal and unique position after <14.dxe6> with two-connected pawns on the 6th rank Great way to start the week!
***** |
|
Mar-28-16
| | mjmorri: If 11...Nxd5, then 12.Qc6+ and the Knight is gone because the e6 pawn defending it is pinned. |
|
Mar-28-16
| | kevin86: Black can take the queen, but is then mated by two pawns! |
|
| Mar-28-16 | | SamAtoms1980: Hard to believe this was a game between two 2500+ players. |
|
| Mar-28-16 | | scormus: guys can we get this straight, the one playing Black was a GM? do they do match fixing in chess as well? |
|
| Mar-28-16 | | catlover: The pun is "I'll huff and I'll puff"...I guess CG is referring to the demolition move 13. Rxe6, blowing down the "house" around the king.


Welcome to Motivate Me!
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--- layout: post title: OData.org Weekly News Letter (3rd week 2015) date: 2015-01-20 01:31:25.000000000 +08:00 categories: - News letter tags: [] status: publish type: post published: true author: Qian Li ---
I am super proud to announce the first version of the JayData library to support the OData V4 format – and a growing number of V4 features. You can check it out at http://odata-v4.azurewebsites.net/ to see it in action.
Check out more from this blog post
Apache Olingo is a Java library that implements the Open Data Protocol (OData). Apache Olingo serves client and server aspects of OData. It currently supports OData 2.0 and OData 4.0. The latter is the OASIS version of the protocol: OASIS Open Data Protocol (OData) TC. The extensions part of Olingo contains additional features like the support of JPA persistency or annotated bean classes. Read more tutorials of Olingo JAVA at this blog site.
here I'd like to share what I have learned while trying to access a HANA XS OData service in our SAP Web IDE (cloud) trial edition. I've have been asked by several people if it is possible - and the answer is: it depends.
Check out detail information of HANA XS OData in Web IDE and more at this blog post.
Simple.OData.V4.Client is a multiplatform OData client library supporting .NET 4.x, Windows Store, Windows Phone 8, Silverlight 5, iOS and Android. The adapter provides a great alternative to WCF Data Services client. It does not require generation of context or entity classes and fits RESTful nature of OData services
Get this new release from nuget and know more about Simple.OData at GitHub
I’ve been working on a project to bring the major elements of SAP mobility together in a single example. This example will explore the details of creating a delta-enabled OData web service, something that I mentioned in my last blog post.
At the end of the project we'll have this:
- A web service that supports OData Delta Token processingc
- A Hybrid Kapsel application created using Web IDE that uses that service
- Support for disconnected operation in the mobile app using the SMP SDK’s Offline capabilities
- Support for adding and editing records in the mobile app
- Run both the web service and mobile application atop the HANA Cloud Platform
Read more from this blog post
This guide will give a clear understanding on how to create an OData service for a given SAP Gateway data source.
Read more from this blog post
The members of the OASIS Open Data Protocol (OData) TC have requested that OASIS submit the following OASIS Standards:
- OData Version 4.0 (OASIS Standard incorporating Approved Errata 02, 30 October 2014)
- OData JSON Format Version 4.0 Plus Errata 02 (OASIS Standard incorporating Approved Errata 02, 30 October 2014)
to ISO/IEC Joint Technical Committee 1 as a P.A.S. submission for approval as proposed International Standards.
Read more at the announcement.


Every week you get your % of the share of the total $WeeklyBNB token. This is calculated by (Total Suplly - Burn Adress) / (Your share)
2% of every transaction is rewarded to all holders.
There is an active community set up to help everyone on earth with the project.
There are no hidden things under the table.
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To start up a crypto token its important to have a clear idea. In the second quarter of 2021 we spend time thinking what is the best oppertunity and plan for the forture.
Officialy launching the website and social media platforms. Launching the $WeeklyBNB token on DxSale and list it on Pancakeswap, Also list on PooCoin
Make big news of the new token. Put it on listing sites like CoinMarketCap,CoinGecko and others.
Update Dapp and website. New Logo, New banner & more.
Creation of own Decentrelized exchange.
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Lorem ipsum dolor sit amet, consectetur adipiscing elit. Fusce eleifend euismod nibh
Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam.


MonoidState uses Algebird Monoid to aggregate state
PersistentState is part of the transaction API
PersistentState is part of the transaction API
Users could get transaction support from the framework by conforming to PersistentState APIs and extending PersistentTask to manage the state
PersistentTask is part of the transaction API
PersistentTask is part of the transaction API
Users should extend this task if they want to get transaction support from the framework
MonoidState uses Algebird Monoid to aggregate state
on start, state value is initialized to monoid.zero on each new message, existing state value is aggregated with the incoming value using monoid.plus to get a new state value


To volunteer to speak, or if you have any questions about speaking, please email us.
Bleeding Edge Web events follow a consistent format:
What to Talk About
If you'd like to talk but don't think you can fill 30-40 minutes, try a lightning talk (see below)!
We like to discuss all things web + mobile. We've had a number of talks about Node.js, HTML/JS/CSS, web servers, libraries & frameworks, etc. We've also had talks about Google Glass, "Internet of things", etc. Bottom line: if you think it would interest other web app developer types, it's likely a good fit.
Our members are generally interested in web technology, but fall into a wide spectrum. Many are entrepreneurs, job seekers, employers, developers, students, and tinkerers. Lots of people means lots of interesting subjects.
If you run a tech meetup organized around a specific technology you might be a good candidate for speaking to our group. Overview talks about languages and franeworks generally make for perfect topics for our members who might not otherwise attend a meetup specific to them.
Lightning Talks
There aren't any formal guidelines for these, other than trying to keep it to 5-10 minutes. Some people use 3-5 slides, some just talk. Topics can be anything of interest to the group. You know what the group is interested in because you're a part of it (what interests you?).
Lightning talks in the past have covered things like Vue.js, RiotJS, functional programming, mobile apps, CSS Pointer Events, Node.js utilities, developer services, personal project, hackathons, etc.
Speaker Guide
If you are ready to present at the meetup we have a handy speaker guide that includes what we'll need from you and some tips that might help with your talk.


Git Gud v0.1.0 GitGud.GraphQL.Resolvers View Source
Module providing resolution functions for GraphQL related queries.
Link to this section Summary
Functions
Resolves the type for a given Git actor
Resolves the content length for a given Git blob
object
Resolves the author for a given Git commit
object
Resolves the message for a given Git commit
object
Resolves the timestamp for a given Git commit
object
Resolves the commit history starting from the given Git revision
object
Resolves the type for a given Git object
Resolves the Git target for the given Git reference
object
Resolves the type for the given Git reference
object
Resolves the author for a given Git tag
object
Resolves the message for a given Git tag
object
Resolves the Git target for the given Git tag
object
Resolves the type for a given Git tag
Resolves the tree for a given Git commit
object
Resolves the tree entries for a given Git tree
object
Returns the underlying Git object for a given Git tree_entry
object
Resolves a node object
Resolves a node object type
Resolves the default branch object for a given repo
Resolves the owner for a given repo
Resolves a Git reference object by name for a given repo
Resolves all Git reference objects for a given repo
Resolves a Git tag object by name for a given repo
Resolves all Git tag objects for a given repo
Resolves a list of users for a given search term
Resolves the URL of the given resource
Resolves an user object by login
Resolves the public email for a given user
Resolves a repository object by name for a given user
Resolves all repositories for a given user
Link to this section Functions
git_actor_type(GitGud.User.t() | map(), Absinthe.Resolution.t()) :: atom()
Resolves the type for a given Git actor
.
git_blob_size(GitGud.GitBlob.t(), %{}, Absinthe.Resolution.t()) :: {:ok, integer()} | {:error, term()}
Resolves the content length for a given Git blob
object.
git_commit_author(GitGud.GitCommit.t(), %{}, Absinthe.Resolution.t()) :: {:ok, GitGud.User.t() | map()} | {:error, term()}
Resolves the author for a given Git commit
object.
git_commit_message(GitGud.GitCommit.t(), %{}, Absinthe.Resolution.t()) :: {:ok, binary()} | {:error, term()}
Resolves the message for a given Git commit
object.
git_commit_timestamp(GitGud.GitCommit.t(), %{}, Absinthe.Resolution.t()) :: {:ok, DateTime.t()} | {:error, term()}
Resolves the timestamp for a given Git commit
object.
git_history(map(), Absinthe.Resolution.t()) :: {:ok, Absinthe.Relay.Connection.t()} | {:error, term()}
Resolves the commit history starting from the given Git revision
object.
git_object_type(GitGud.Repo.git_object(), Absinthe.Resolution.t()) :: atom()
Resolves the type for a given Git object
.
git_reference_target(GitGud.GitReference.t(), %{}, Absinthe.Resolution.t()) :: {:ok, GitGud.Repo.git_object()} | {:error, term()}
Resolves the Git target for the given Git reference
object.
git_reference_type(GitGud.GitReference.t(), %{}, Absinthe.Resolution.t()) :: {:ok, GitGud.GitReference.type()} | {:error, term()}
Resolves the type for the given Git reference
object.
git_tag_author(GitGud.GitTag.t(), %{}, Absinthe.Resolution.t()) :: {:ok, GitGud.User.t() | map()} | {:error, term()}
Resolves the author for a given Git tag
object.
git_tag_message(GitGud.GitTag.t(), %{}, Absinthe.Resolution.t()) :: {:ok, binary()} | {:error, term()}
Resolves the message for a given Git tag
object.
git_tag_target(GitGud.GitTag.t(), %{}, Absinthe.Resolution.t()) :: {:ok, GitGud.Repo.git_object()} | {:error, term()}
Resolves the Git target for the given Git tag
object.
git_tag_type( GitGud.GitReference.t() | GitGud.GitTag.t(), Absinthe.Resolution.t() ) :: {:ok, atom()} | {:error, term()}
Resolves the type for a given Git tag
.
git_tree(GitGud.Repo.git_revision(), %{}, Absinthe.Resolution.t()) :: {:ok, GitGud.GitTree.t()} | {:error, term()}
Resolves the tree for a given Git commit
object.
git_tree_entries(map(), Absinthe.Resolution.t()) :: {:ok, Absinthe.Relay.Connection.t()} | {:error, term()}
Resolves the tree entries for a given Git tree
object.
git_tree_entry_target(GitGud.Repo.t(), %{}, Absinthe.Resolution.t()) :: {:ok, GitGud.GitTree.t() | GitGud.GitBlob.t()} | {:error, term()}
Returns the underlying Git object for a given Git tree_entry
object.
node(map(), Absinthe.Resolution.t()) :: {:ok, map()} | {:error, term()}
Resolves a node object.
node_type(map(), Absinthe.Resolution.t()) :: atom() | nil
Resolves a node object type.
repo_head(GitGud.Repo.t(), %{}, Absinthe.Resolution.t()) :: {:ok, GitGud.GitReference.t()} | {:error, term()}
Resolves the default branch object for a given repo
.
repo_owner(GitGud.Repo.t(), %{}, Absinthe.Resolution.t()) :: {:ok, GitGud.User.t()} | {:error, term()}
Resolves the owner for a given repo
.
repo_ref(GitGud.Repo.t(), %{name: binary()}, Absinthe.Resolution.t()) :: {:ok, GitGud.GitReference.t()} | {:error, term()}
Resolves a Git reference object by name for a given repo
.
repo_refs(map(), Absinthe.Resolution.t()) :: {:ok, Absinthe.Relay.Connection.t()} | {:error, term()}
Resolves all Git reference objects for a given repo
.
repo_tag(GitGud.Repo.t(), %{name: binary()}, Absinthe.Resolution.t()) :: {:ok, GitGud.GitReference.t() | GitGud.GitTag.t()} | {:error, term()}
Resolves a Git tag object by name for a given repo
.
repo_tags(map(), Absinthe.Resolution.t()) :: {:ok, Absinthe.Relay.Connection.t()} | {:error, term()}
Resolves all Git tag objects for a given repo
.
search(map(), Absinthe.Resolution.t()) :: {:ok, Absinthe.Relay.Connection.t()} | {:error, term()}
Resolves a list of users for a given search term.
search_result_type(GitGud.User.t() | GitGud.Repo.t(), Absinthe.Resolution.t()) :: atom()
url(map(), %{}, Absinthe.Resolution.t()) :: {:ok, binary()} | {:error, term()}
Resolves the URL of the given resource
.
user(%{}, %{login: binary()}, Absinthe.Resolution.t()) :: {:ok, GitGud.User.t()} | {:error, term()}
Resolves an user object by login.
user_public_email(GitGud.User.t(), %{}, Absinthe.Resolution.t()) :: {:ok, GitGud.GitReference.t()} | {:error, term()}
Resolves the public email for a given user
.
user_repo(GitGud.User.t(), %{name: binary()}, Absinthe.Resolution.t()) :: {:ok, GitGud.Repo.t()} | {:error, term()}
Resolves a repository object by name for a given user
.
user_repos(map(), Absinthe.Resolution.t()) :: {:ok, Absinthe.Relay.Connection.t()} | {:error, term()}
Resolves all repositories for a given user
.


Abyssal Saintess Elcadia:
Yes! This is the book I was looking for! Now that we're finished here, let's hurry to my house. There is much about the future we need to discuss.


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Below are some hints to use Azure pipeline
1. If a variable is dependent on another, then the latter should be a constant. If both are evaludated from a non-constant expression then the value may not be correct. E.g.
2. Quote the parameters otherwise the value may not be considered as string.
E.g. stage S1 is fine whereas S2 will throw an error.
3. Use |
for convenience. E.g.
4. Use single quotes to escape :
in script.
E.g. Script S1 is fine whereas S2 throws errors
5. Use dependsOn
to ensure job dependency. succeeded()
does not ensure that. E.g.


Spencer's Notes On Electronics
Introduction & Motivation
As I struggle through the subject of electronics, here I'm keeping a formalized set of notes to
help me remember what I've learned, or what I think I've learned. It could all be fallacy.
Table of Contents
My notes are organized as follows.
- The Physics & Analogous Models
- Ohm's Law
- Kirchhoff's Laws
- Resistors in Series
- Resistors in Parallel
- Analyzing Circuits of Resistors & Batteries
- A Case of Zero Current
- Power
- Light Emitting Diodes
- The RC Circuit
- The RL Circuit
- Capacistors in Series and Parallel
- Inductors in Series and Parallel


Conflict and how we all deal with it
August 10th, 2015
In every point in someones life, we all deal with conflict. Whether its internal conflict, or conflict with family or friends, it all pretty much puts a strain on your emotional health and your overall well-being. Bottom line is, we all deal with conflicts on a daily basis, whether it's a minor or major one. I think as we mature and grow wiser, it's important to really evaluate where your emotions comes from and figure out what the actual cause of the problems are.
If you've ever had a long term intimate relationship with another person, you probably know as well as I do that conflict is something that sometimes is unavoidable. When you spend so much time with a particular person and have that comfort level, it really is easy to let your emotions, in a sense, run wild.  I'm gonna be talking about a recent conflict I've had with my girlfriend, and how I eventually broke it down to the root of the problem.
The times when my girlfriend and I fight the most is when one of us, or both, are in a somewhat bad/negative mood. We tend to lose our patience and tend to become more argumentative. We recently adopted a puppy together, and while it brings us a lot of joy and happyness, it also sometimes puts a strain on my relationship with my GF.
We sometimes fight about the stupidest things. What kind of food we should feed the dog, how we should train him, and all sorts of topics that don't necessarily need to be conversated in a hostile way.  But both of us are big dog lovers and on that particular day, both of us were not in the right state of mind. So the argument proceeded, and we were pretty upset with each other.
Initially, my thought was, who cares who walks the dog? Why is she being like this? Why is she making such a big deal about who gets to hold the friggin leash? I didn't understand why she was so upset. So like most of our fights, we didn't really talk to each other for awhile, all while putting on a angry face that let each of us know that we weren't happy with one another.
After taking some time to cool off, we talked about our fight and why it escalated to the point it did. It was something very silly to be honest, and I didn't really take in consideration of the fact that she wanted to be more involved with taking care of OUR dog. Also, we weren't in the best of moods that day, which resulted us being very snappy with each other. I think it's very important to be able to analyze why the actual fight happened. Sometimes, you fight about topics that your not really even angry about, but there's topics that lie beneath the argument, that can make things a lot worse.
What did I learn from this? I learned that it's important to be able to understand the deeper issues at hand, and to be able to be more empathetic about people's current state of emotions. var happy_girlfriend == happy life. =] Till next week!


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