Canadian Female athletes are the best female athletes at the Winter Olympics
It can be proven that female athletes representing Canada at the Winter Olympics- past, and present- are the best in the world!
I have prepared the following charts using Python 3 to help prove my theory.
Donut Plot
This chart shows that, although the United States' female athletes have won the most amount of medals overall, Canadian female athletes have won the MOST amount of gold, coming in first place more times than any other country. I've used Germany and the States as main comparisons because they, alongside Canada, are the top three in the world.
Ladies Bronze
This chart takes a close look at the amount of bronze medals won by the top three countries' female athletes. As you can see, the United States has the most amount of bronze medals earned by females. Over 40% of bronze medals handed out to women in the top three countries went to American women.
Ladies Silver
Examining the distribution of silver medals, this chart reveals that American female athletes also take home a LOT of silver medals within the top 3, 45.3% of them to be exact.
Ladies Gold
This is the chart that shows where Canadian female athletes really start to dominate. This chart gives us a better look at just how many medals the Canadian women are bringing home from the Winter Olympics- over HALF of the gold medals handed out to the top three countries to women come back to Canada.
Unknown Chart...
This chart here shows, by mass, the amount of gold, silver, and bronze medals each of the 'top three' countries' female athletes earned.
In Conclusion...
Team Canada's females OWN the Winter Olympics! Our girls have earned more gold medals in the winter games than any other country.
Our dominance has been proven mainly in the sport of Ice Hockey where 101 medals have been earned over the years by Canadian female athletes.
Back to top


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java.lang.Object kdl.prox.qgraph2.QGItem
public abstract class QGItem
Abstract superclass to QGEdge and QGVertex, defines useful IVs and methods. NB: This should probably be named ProxElement or GraphElement, but "element" is too easily confused with XML and collection elements. So we use "item", which could be confused with the data (as opposed to graph) Item, but too bad. The names of this and subclasses start with QG (for "QGraph") to differentiate them from vertices and edges in transformation (or other) graphs. Implements AbsQueryChild because QGItems (QGVertices and QGEdges) can be stored in an AbstractQuery. Implements Comparable so that lists of QGItems can be sorted (used by Query.equalsQuery()).
Regarding processing asterisk support: See my asteriskSource below.
| Field Summary | |
|---|---|
protected static org.apache.log4j.Logger |
log
|
| Method Summary | |
|---|---|
void |
addNames(QGItem qgItem)
Used by Transformations that call absorbEdgeAndVertex() but not replaceQGVertex() after, adds all of qgItem's names to my names, then sorts my names. |
Annotation |
annotation()
Returns my Annotation. |
java.lang.String |
annotationString()
Utility method that returns a pretty string for my annotation. |
java.lang.String |
asteriskSource()
Returns my asteriskSource. |
int |
asteriskSourceAnnotMax()
Returns the upper bound of the annotation on the asterisk |
java.lang.String |
asteriskSourceItemName()
Returns the name of the asterisked item in the asteriskSource vertex. |
java.lang.String |
asteriskSourceToString()
Shows the name of the asterisk source QGVertex, and the name of the asterisked item within that vertex, if any. |
java.lang.String |
catenatedName()
Returns the catenation of my names. |
void |
clearAsteriskSource()
Clears the asterisk source |
int |
compareTo(java.lang.Object o)
Compares this QGItem to another Object. |
org.jdom.Element |
condEleChild()
Returns my condEleChild. |
void |
deleteAnnotation()
Eliminate the annotation on this QGItem |
void |
deleteCondEleChild()
Eliminate the condEleChild on this QGItem |
boolean |
equals(java.lang.Object anObject)
Object method. |
java.lang.String |
firstName()
Utility that returns the first name in my names. |
boolean |
isAnnotated()
Utility that returns true if I'm annotated, and false o/w. |
boolean |
isAsterisked()
Utility that returns true if qgItem has an asterisk, i.e, if it can be asterisked, and its asteriskSource() != null. |
boolean |
isSameAsteriskSource(QGItem qgItem)
Utility that returns true if qgItem and I have the same asteriskSource. |
boolean |
isSupportsAsterisks()
Returns true if my class supports asterisks. |
java.util.List |
names()
Returns a copy of my names. |
AbstractQuery |
parentAQuery()
AbsQueryChild method. |
void |
setAnnotation(Annotation annotation)
|
void |
setAsteriskSource(QGVertex annotQGVertex)
Sets my asteriskSource to a vertex that has a single name, and it therefore can set the asteriskedItemName to the first name of the vertex |
void |
setAsteriskSource(QGVertex annotQGVertex,
java.lang.String itemName)
Sets my asteriskSource to the specified itemName in annotQGVertex. |
void |
setCondition(org.jdom.Element condEle)
Updates the value of the condEleChild by passing in a ConditionElement |
void |
setFirstName(java.lang.String newName)
Used by the QueryEditor to set the first name for a QGItem The first name should be updated on an edit rather than appended NOTE: An editor query is always unconsolidated and will only ever have one name. |
void |
setParentAQuery(AbstractQuery parentAQuery)
AbsQueryChild method. |
| Methods inherited from class java.lang.Object |
|---|
clone, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Field Detail |
|---|
protected static org.apache.log4j.Logger log
| Method Detail |
|---|
public void addNames(QGItem qgItem)
public Annotation annotation()
annotation
in interface AbsQueryChild
public java.lang.String annotationString()
public java.lang.String asteriskSource()
public int asteriskSourceAnnotMax()
public java.lang.String asteriskSourceItemName()
public java.lang.String asteriskSourceToString()
public java.lang.String catenatedName()
public void clearAsteriskSource()
public int compareTo(java.lang.Object o)
compareTo(String)
. Otherwise,
it throws a ClassCastException
(as QGItems are comparable
only to other QGItems).
compareTo
in interface java.lang.Comparable
public org.jdom.Element condEleChild()
public void deleteAnnotation()
deleteAnnotation
in interface AbsQueryChild
public void deleteCondEleChild()
public boolean equals(java.lang.Object anObject)
equals
in class java.lang.Object
public java.lang.String firstName()
public boolean isAnnotated()
public boolean isAsterisked()
public boolean isSameAsteriskSource(QGItem qgItem)
public boolean isSupportsAsterisks()
public java.util.List names()
public AbstractQuery parentAQuery()
parentAQuery
in interface AbsQueryChild
public void setAnnotation(Annotation annotation)
setAnnotation
in interface AbsQueryChild
public void setAsteriskSource(QGVertex annotQGVertex)
annotQGVertex
- public void setAsteriskSource(QGVertex annotQGVertex, java.lang.String itemName)
public void setCondition(org.jdom.Element condEle)
public void setFirstName(java.lang.String newName)
public void setParentAQuery(AbstractQuery parentAQuery)
setParentAQuery
in interface AbsQueryChild
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| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |


--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/Automatically.20parsing.20string.20literals.html ---
I have a type A and a partial function parseA : string -> except string A
, is there an easy way to get Lean to automatically call parseA
parser when I have a literal ("foo" : A)
? If parseA "foo"
returns except.ok r
then I'd like r
to be used, and if it fails I'd like Lean to report the error.
I'm starting down the path of a coercion with a custom tactic, and realized somebody may have done this before. It's for a library for s-expression parsing/generation.
I ended up with writing a coerce
tactic that allowed this:
meta def to_expr : sexpr → tactic expr := sorry -- This tries to prove a property by just running the evaluator. meta def coerce (s:string) : tactic unit := do match parse s with | (except.ok r) := do e ← to_expr r, tactic.exact e | (except.error msg) := do tactic.fail msg end -- This works #eval (by coerce "abc") -- This reports a suitable error message when the tactic runs #eval (by coerce "def))")
I couldn't see a way to introduce a coercion to hide the tactic call, but I suppose I could introduce notation to make the syntax more concise..
@Joe Hendrix Right, there isn't much more you can do there without some kind of user-definable coercions. One alternative is to make it a custom parser with some prefix token, like we already have with format! "{x} {y}"
. This _mostly_ works already in Lean 3.
Thanks for the pointer. Is there any chance that I'd be able to query the environment with that to allow quasi quoting (e.g. sexpr! "(_ Bitvec %%w)"
) ? I'd also be interested in synthesizing patterns, but it's not an immediate need.
I just realized that should be doable given that expressions can reference variables.
You can't access the parser's set of local variables directly, but you can call it recursively to parse arbitrary expressions like format!
does. After that you could even analyze or transform the returned pre-term.
@Joe Hendrix Actually, you can access the environment and even add variables inside the parser. If I remember correctly, it's a bit confusing because there is a lean.parser.set_env
as well as tactic.set_env
. If all you need is reading the environment, tactic.get_env
should do.
@Simon Hudon @Sebastian Ullrich Thanks for the pointers. I have to work on something else for a bit, but will get back to this soon.
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


{% extends "layout.html" %} {% block body %}
You've reached part of app which is not implemented yet. We are (hopefully) working on that, so wait please or join the community @GitHub and help us with this one!
Go to the start


Hack Cambridge is going to be an amazing event, and you as a sponsor are going to allow that to happen. These are tips accumulated from the Hack Cambridge team's experiences in previous years, which we hope will help you get the most out of your sponsorship.
Students attend Hack Cambridge from all over the world. They come to learn new tech, meet like-minded people and produce amazing new things.  We encourage friendly competition, not fierce rivalry. As sponsors, you make this all happen—so thank you!
You can really influence hackers' experiences and form a lasting impression amongst the next generation of engineers. We are selective about who comes, and so are confident that you will find some of the brightest and keenest engineers here and cannot wait for you to meet them. That said, whilst most hackers will be looking for jobs this year or next, they won't be treating the event like a recruitment fair. They will of course speak to recruiters, take business cards and leaflets; they will be looking out for companies they may want to work for in the future; but they also will be spending 24 hours intensely building cool software and learning new tech. People who attend hackathons are amongst the the keenest techies out there, so tech is the content that will most resonate with them.
The quality of mentors and engineers really does influence attendees' perception of companies. In the past we have had feedback from hackers who have been extremely impressed by mentors from particular companies, and have then indicated their interest in working in a similar team; they can also be impressed by good workshops which show off what you do. By being at a hackathon, you already send out a message that you are proactive, have a strong engineering culture, and are interested in graduates. You are gaining mindshare ahead of many other companies, and can really get hackers enthused about the tech you produce. By providing you with attendess' CVs, we hope you are also able to continue the relationship with hackers after the event, following on from interaction at the hackathon. We hope these tips help you get the most out of the event!
Mentors are incredibly valuable to us as they can dramatically speed up hacker's development time by short-circuiting the process of finding the right technology, squashing time-consuming bugs much faster and by speeding up the ideation process. As a sponsor, mentorship is valuable for you because a good mentor experience will provide a long-lasting impression about your company, often stronger than any ad or recruitment speech can.
Mentors should be technically focused people — software engineers, developers and the like. Their primary concern is to help hackers with technical issues, though they may also discuss the your company and your products. We recommend sending developers whose expertise covers a wide range of technical areas, and certainly ones who are knowledgeable about any software or hardware you have listed with us. The most important thing a mentor should remember is to be proactive. Hackers will often be shy and reluctant to ask for help when they're having problems.
Mentors can also opt-in to the judging period of the hackathon, where they get to interview teams on what they have created and score them to allow us to decide on a winner.
To aid with hacker-mentor discovery, we will set up a Slack service and provision one channel for each sponsor. We will also deploy a hackathon-specific ticketing system called HELPq, where hackers request help and are paired with mentors.
Workshops and product demos are especially useful to hackers who aren't sure what they're creating or are new to hackathons and developing in general. As short-sighted as this may seem, hackers often look for workshops that will aid them in their hackathon project rather than something that will help them after the event. We will be promoting the talks heavily, but ultimately it is you who must ensure that your presentation sounds compelling enough to persuade hackers to put down their projects and come listen! If you want to run ideas past us we are more than happy to discuss them with you. Talks discussing currently 'hot' topics always do well, which for HackCambridge 4D would likely include machine learning, AI, and blockchain.
Workshops and demos will occur in a dedicated room outside of the main hall, where we will provide a projector for you to present on via HDMI. Product demos and workshops are 10 minutes and 30 minutes respectively, occuring on the Saturday afternoon. We will release an exact schedule once we have received workshop details from all sponsors.
Swag can draw hackers to your recruitment stand, and in the longer term be an effective long-term reminder to a hacker about a company after the event. Our experience indicates the swag which gets the best response are things useful in day-to-day life, rather than novelty items or trinkets. For example, one previously sponsor distributed umbrellas and people still used them on a daily basis a year later whilst commenting on their usefulness and durability.
We recommend you send 400 of each item of swag. This ensures we definitely have enough and leftover can be taken back with you. This is especially important for clothing where it is hard to predict sizes!
T-shirts and hoodies are always popular, and we will welcome as many as you want to send! However, the reason we do ask you to run swag past us is to ensure we have a good spread.
We will pack all swag except clothing into hackers' swag bags if they are sent to us in time. Clothing will be distributed by hand so people get their size.
Competitions can really make your company stand out, giving incentive for hackers to use your products and interact with your team. We recommend that competitions be open-ended enough to fit into a variety of projects, rather than a very specfic task. For example, a competition for the best use of a particular API; or a challenge to analyse a piece of data the best.
We discourage expensive prizes such as laptop—the atmosphere of the event is intended to be a friendly and collaborative get-together rather than an opportunity to grab expensive new toys. Suitable prizes include Amazon vouchers; free subscriptions to commercial software; or relatively low-value devices like Raspberry Pis and GoPros. We believe that hackers participating out of raw enthusiasm will produce more interesting hacks, rather than simply aiming to fill judging criteria.
This is a great opportunity to form relationships with talented developers who have shown an interest in what you do. Extending further training schemes or getting in touch about internship opportunities to prize winners and runner-ups has worked for companies in past hackathons.
 Make sure you have set criteria and set aside time at the end of the event for mentors to not only check out the submissions for the prize but also to interview the hackers. Interviewing them allows you to not only see more about their submission but to also see what they are like as developers, and gain insightful feedback about how they as users found using your API. Hackers will also get a very positive impression of companies who take an active role in seeking out hackers working on their APIs and offering advice, so do take time to talk to them throughout the event.


1. Introduction
1.4 Cayenne User Directory
Cayenne has a notion of Cayenne User Directory - a file system directory, one per each user
account on a given machine, where Cayenne-related information is stored. While Cayenne runtime
knows how to locate and access this directory, it never uses it or relies on its presence. The reason is that Cayenne
is often deployed in J2EE containers and should avoid any assumptions about the underlying filesystem layout.
CayenneModeler on the other hand uses it to store a number of things, like log files, preferences, etc.
While users shouldn't normally care about Cayenne User Directory, as its creation and use are transparent,
sometimes it is helpful to know where it is located and what information is stored there.
1.4.1 Cayenne User Directory Location
Cayenne User Directory is a filesystem directory called ".cayenne" (notice the dot in front of the name, it makes it "hidden" on
UNIX operating systems) that is a subdirectory of a user HOME directory. HOME directory is OS and
machine dependent. For example on Windows this is something like "C:\Documents and Settings\username\".
Cayenne User Directory is created automatically when CayenneModeler is started on a user
machine for the first time.
1.4.2 Accessing Cayenne User Directory Programmatically
For those rare cases when you application needs to access Cayenne User Directory, you can take advantage of
CayenneUserDir class API, via
a shared instance of CayenneUserDir.
1.4.3 Information Stored in Cayenne User Directory
prefs : preferences database subdirectory.
modeler.preferences : this is an old modeler preferences file. It is still used by CayenneModeler, but will be
completely replaced by the preferences database in the future releases.
cayenne-log.properties : Log4J configuration file for the Modeler.
modeler.log : CayenneModeler log file.
modeler.classpath : (unused) an old CLASSPATH configuration file that is now migrated to the preferences database.
|


CryptoCoreComponent |
Encapsulates logic, associated with keys generation and encryption/decryption processes interface CryptoCoreComponent |
EdDSAKeyProvider |
Describes functionality of echorand key generation for account registration interface EdDSAKeyProvider |
WifProcessor |
Provides methods for working with private key WIF format interface WifProcessor |


--- layout: default title: Style Guide ---
I'm a big fan of design systems and wanted to take a small shot at something similar on a very small scale and tbh I know this is not a design system, it's a style guide w some components. Every font, color and design pattern has an intention and purpose
"Nothing without intention. Do nothing without intention". - Goddess Lula Belle
hex: #323667
class name: color400
hex: #404585
class name: color800
hex: #4F55A3
class name: color200
hex: #F4F4F5
class name: color100
hex: #333547
class name: grey800
hex: #70728F
class name: grey200
hex: #E2E3E9
class name: grey100
hex: #FCFCFC
class name: white100
Font-family: DM Serif Display - Font-size: 64px - Font-weight: Regular - Line-height: 88px - Color: #323667 - color400
Font-family: DM Serif Display - Font-size: 48px - Font-weight: Regular Line-height: 66px - Color: #404585 - color800
Font-family: DM Serif Display - Font-size: 36px - Font-weight: Regular - Line-height: 48px - Color: #4F55A3 - color200
Font-family: DM Serif Display - Font-size: 27px - Font-weight: Regular - Line-height: 37px - Color: #5D64C1 - color100
Subtitle text with description elements
Font-family: Lato - Font-size: 16px - Font-weight: Regular - Line-height: 20px - Color: #70728F - grey200
"A nice lil block quote from user or my face quote". - Silvia F.
Font-family: Lato - Font-size: 1.8rem - Font-weight: Regular - Line-height: 20px - BG-Color: #F4F4F6 - grey50 - Border-Color: #E2E3E9 - grey100
Regular paragraph text — "The quick brown fox jumps over the lazy dog" is an English-language pangram—a sentence that contains all of the letters of the alphabet. It is commonly used for touch-typing practice, testing typewriters and computer keyboards, displaying examples of fonts, and other applications involving text where the use of all letters in the alphabet is desired.
Font-family: Lato - Font-size: 16px - Font-weight: Regular Line-height: 24px - Color: #333547 - grey800
Bolded text that is like important standout information of a case studyFont-family: Lato - Font-size: 16px - Font-weight: Bold 700 - Line-height: 125% - Color: #404585 - color800
Link Text — The quick brown fox jumps over the lazy dogFont-family: Lato - Font-size: 16px - Font-weight: Regular Underline Line-height: 24px - Color: #5D64C1 - color100
Product Design, User Research, User Testing / Fall 2018
Helping international music fans learn a new language with a built in lyric translating feature
View Case StudyProduct Design, User Research, User Testing / Fall 2018
Helping international music fans learn a new language with a built in lyric translating feature
View Case Study


| [
20]
|
Climate Change Vulnerability Index (CCVI) |
To provide insights into the vulnerability of countries by quantifying potential impacts of climate change and climate-related extremes |
1. Exposure; 2. Sensitivity; 3. Adaptive capacity |
Indicator 1–50%
Indicator 2–25%
Indicator 3–25%
|
| [
21]
|
Risk Management Index (RMI) |
To provide a way to identify risk management capacities, as well as comparative data for evaluating the effects of policies and investments on risk management |
1. Risk identification; 2. Risk reduction; 3. Disaster management; 4. Governability and financial protection |
Equal |
| [
21]
|
Disaster Deficit Index (DDI) |
To provide a measure of country risk from a macro-economic and financial perspective when faced with possible catastrophic events |
1. Volume and cost of exposed elements to disasters (Maximum Considered Event); 2. Stock of available funds for recovery (Economic Resilience) |
Equal |
| [
22]
|
Economic Vulnerability Index (EVI-G) |
To provide an assessment of the vulnerability of the SIDs or to identify the least developed countries (LDCs) |
3 shock sub-indices e.g. instability of goods and services and instability of agriculture production due to natural disaster; 4 exposure sub-indices e.g. smallness of population size, remoteness |
Shock indicators– 50%
Exposure indicators– 50%
|
| [
18]
|
Environmental Vulnerability Index |
To reflect the extent to which the natural environment of a country is prone to damage and degradation |
50 sub-indices e.g. wind, dry, wet, slides, relief, low lands, air, waste, fisheries |
Equal |
| [
23]
|
Commonwealth Vulnerability Index (CVI) |
To provide a tool to complement additional criterion (e.g. per capita income) for determining whether small states should be accorded differential treatment by the international community. |
1. Lack of diversification; 2. Export dependence; 3. Impact of natural disasters; 4. Resilience
|
Two elements comprise index: vulnerability index and resilience index. Indicators1-3 are weighted using principal component analysis (PC) and combined with the resilience PCA. |
| [
17]
|
Economic Vulnerability Index EcVI |
To examine the exposure of an economy to exogenous shocks arising out of its inherent characteristics e.g. smallness |
1. Exposure to foreign economic conditions; 2. Remoteness and insularity; 3. Disaster proneness |
Two sets: 1. Equal
2. Indicator 1–50%
Indicator 2–40%
Indicator 3–10%
|


glow.net.get
Memory Leak Test
Start test
A file will be fetched every 500ms. Memory usage should not creep up. Logging has been commented out to avoid memory creep caused by adding elements to the logger.


2-6 December 2018
Perth Western Australia
Aesthetics relates to the subjective notion of art, beauty and taste. The advancement of digital technologies, particularly the explosive growth in mobile devices, the expansion of social media and further digitization of artworks, have spurred on a rapidly growing interest in the field of "computational aesthetics". With the large amount of artistic media content (artworks, photographs, video) readily available, there arises a need for intelligent analysis and prediction of aesthetics, and other associated concepts such as interestingness, popularity, and viralness of media content. In addition, recent advances in machine learning, artificial intelligence and multimedia technologies are transforming the way artistic media content are generated and manipulated. Automatic generation of photo-realistic art, enhancement and manipulation of media content, and transfer of artistic styles from artworks to images/videos, are now real possibilities.
This workshop aims to bring together individuals with technical experience of using computer-based techniques such as machine learning, artificial intelligence and multimedia technologies to solve a variety of problems, ranging from automatic analysis and understanding of aesthetics in media content (artworks, photographs, videos) to aesthetics-driven content generation and synthesis. The scope of this workshop includes, but is not limited to:
|
Paper Submission due
|
|
|
Notification
|
|
|
Camera-ready paper deadline
|
Nov. 1, 2018
|
|
Workshop Dates
|
Dec. 2-3, 2018
|
|
Main Conference Dates
|
Dec. 4-6, 2018
|
The workshop paper format should follow the guideline for paper submission in ACCV2018 (see http://accv2018.net/call-for-papers/#guidelines)
University of New South Wales
This talk will briefly summarize both historical and recent developments in adversarial and convolutionary machine learning - including virtual creatures, sorting networks and game playing, as well as computational creativity. Recent work in artist-critic convolution will be described, in which a genetic program artist trained by hierarchical evolution contends with a deep convolutional neural network critic trained by gradient descent. Driven by selective pressure for low algorithmic complexity, combined with the need to fool the critic, the artist evolves to produce geometric shapes and patterns which remind us of everyday objects, landscapes and designs in a manner comparable to abstract art of the early 20th Century. The talk will conclude with a discussion of recent developments in the field, and possible future directions.
Alan Blair completed his PhD at MIT and worked at Brandeis, University of Queensland and University of Melbourne, before taking up his current position at UNSW. His research interests include self learning for strategic games, robot navigation, language processing, convolutional network architectures and training, adversarial and coevolutionary dynamics, multi-task learning, hierarchical evolution and computational creativity.
|
02:00 pm - 02:10 pm
|
Opening Address
|
|
02.10 pm - 03:30 pm
|
Invited Talk
|
|
03:30 pm - 04:00 pm
|
Coffee break
|
|
04:00 pm - 05:20 pm
|
Oral presentations
|
|
05:20 pm - 05:30 pm
|
Closing Remarks
|
|
04:00 pm - 04:20 pm
|
Let AI Clothe You: Diversified Fashion Generation
|
|
04:20 pm - 04:40 pm
|
Word-Conditioned Image Style Transfer
|
|
04:40 pm - 05:00 pm
|
Paying Attention to Style: Recognizing Photo Styles with Convolutional Attentional Units
|
|
05:00 pm - 05:20 pm
|
Font Style Transfer Using Neural Style Transfer
|
National Chiao Tung University, Taiwan
National Chung Cheng University, Taiwan
Multimedia University, Malaysia
Multimedia University, Malaysia


--- layout: foundations title: Foundations for the DOS AND DON'TS permalink: /foundations/ ---
The information below provides foundations to help understand the DOS AND DON'TS. This includes a synthesis of earlier guiding documents, a short description of key uncertainities studies are designed to consider, and the full citation of references used. These foundations are referred to throughout the DOS and DON'TS and provide important additional information for those interested in diving deeper.


Return the first four moments of the SMN distributions (Normal, Student-t, Pearson VII, Slash or Contaminated Normal).
| Version: | 1.0.0 |
| Published: | 2017-04-04 |
| Author: | Eraldo B. dos Anjos Filho and Aldo William Medina Garay |
| Maintainer: | Eraldo B. dos Anjos Filho <ebdaf1 at de.ufpe.br> |
| License: | GPL (≥ 3.0) |
| NeedsCompilation: | no |
| CRAN checks: | TSMN results |
| Reference manual: | TSMN.pdf |
| Package source: | TSMN_1.0.0.tar.gz |
| Windows binaries: | r-devel: TSMN_1.0.0.zip, r-release: TSMN_1.0.0.zip, r-oldrel: TSMN_1.0.0.zip |
| OS X binaries: | r-release: TSMN_1.0.0.tgz, r-oldrel: TSMN_1.0.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=TSMN to link to this page.


{#
Based on code by @yeyezizhi:
https://gist.github.com/yeyezizhi/046fa6e86c1cb3452e90c2dafcdb4915
The editor.md tool is a bit overkill; we want to support extremely basic markdown, so we use SimpleMDE.
#}
{% extends 'admin/model/edit.html' %}
{% block body %}
{% block navlinks %}{% endblock %}
{% block edit_form %}
{{ lib.render_form(form, return_url, extra=None, form_opts=None) }}
{% endblock %}
{% endblock %}
{% block tail %}
{{ super() }}
{% endblock %}


'b00t2root' is a virtual gathering of all the cyber security enthusiasts to enrich their skills in the field of Information Security and would serve as a great platform to find better solutions to real life security threats solving the challenges of this competitive jeopardy style CTF.
(There might be a change in the timeline as it is tentative as of now)
Registration portal opens! The registration process will begin on the 10th of March.
This is a 12hr long CTF and will begin on the 27th of march at 11:00 P.M IST
CTF ends on the 28th of March at 11:00 A.M IST
Behold the winners! Winners will be announced and the goodies/prizes will be distributed among the teams.
A good introduction to CTFs is available here.Below are the links to similar challenges:
1.pwnable
2.Cryptopals
3.XSS Game
You will be presented with challenges. The ultimate goal of every challenge is to find a "flag". A flag looks like this: b00t2root{7hi5_1s_4_fl4g}, and the method in which you find the flag depends on the challenge.
You can always contact us if you feel that a challenge is broken.
Yes, there is size limit of 4 participants, lone wolves are also welcome :)
Of course not.


--- title: Template Builder keywords: fastai sidebar: home_sidebar nb_path: "competition_notebook/Atom/generate_template.ipynb" ---
rm -rf 'abc175'
!atcoder-tools gen abc200 --workspace='.' --lang='python' --save-no-session-cache --config='../configs/atcodertools.toml'
The latest version 2.2.0 is available! (The current version: <IP_ADDRESS>) To upgrade, run the following command: pip3 install atcoder-tools --upgrade 2021-05-08 21:00:14,517 INFO: Going to load ../configs/atcodertools.toml as config 2021-05-08 21:00:14,519 INFO: Loaded session from /home/me/.local/share/atcoder-tools/cookie.txt 2021-05-08 21:00:14,940 INFO: Successfully Logged in using the previous session cache. 2021-05-08 21:00:14,940 INFO: If you'd like to invalidate the cache, delete /home/me/.local/share/atcoder-tools/cookie.txt. 2021-05-08 21:00:14,940 INFO: Login successful. ================================================= 2021-05-08 21:00:15,132 INFO: Problem A: ../configs/ipynb_template.md is used for template 2021-05-08 21:00:15,290 INFO: Problem A: Created examples. 2021-05-08 21:00:15,291 INFO: Problem A: Format prediction succeeded 2021-05-08 21:00:15,379 INFO: Problem A: Saved code to ./abc200/A/main.py 2021-05-08 21:00:15,380 INFO: Problem A: Saved metadata to ./abc200/A/metadata.json 2021-05-08 21:00:15,380 INFO: Problem A: Executing the following command in `./abc200/A`: bash ../../../configs/post_problem.sh ================================================= 2021-05-08 21:00:16,832 INFO: Problem B: ../configs/ipynb_template.md is used for template 2021-05-08 21:00:16,989 INFO: Problem B: Created examples. 2021-05-08 21:00:16,989 INFO: Problem B: Format prediction succeeded 2021-05-08 21:00:17,074 INFO: Problem B: Saved code to ./abc200/B/main.py 2021-05-08 21:00:17,075 INFO: Problem B: Saved metadata to ./abc200/B/metadata.json 2021-05-08 21:00:17,075 INFO: Problem B: Executing the following command in `./abc200/B`: bash ../../../configs/post_problem.sh ================================================= 2021-05-08 21:00:18,421 INFO: Problem C: ../configs/ipynb_template.md is used for template 2021-05-08 21:00:18,568 INFO: Problem C: Created examples. 2021-05-08 21:00:18,569 INFO: Problem C: Format prediction succeeded 2021-05-08 21:00:18,652 INFO: Problem C: Saved code to ./abc200/C/main.py 2021-05-08 21:00:18,652 INFO: Problem C: Saved metadata to ./abc200/C/metadata.json 2021-05-08 21:00:18,652 INFO: Problem C: Executing the following command in `./abc200/C`: bash ../../../configs/post_problem.sh ================================================= 2021-05-08 21:00:20,133 INFO: Problem D: ../configs/ipynb_template.md is used for template 2021-05-08 21:00:20,288 INFO: Problem D: Created examples. 2021-05-08 21:00:20,289 INFO: Problem D: Format prediction succeeded 2021-05-08 21:00:20,367 INFO: Problem D: Saved code to ./abc200/D/main.py 2021-05-08 21:00:20,367 INFO: Problem D: Saved metadata to ./abc200/D/metadata.json 2021-05-08 21:00:20,367 INFO: Problem D: Executing the following command in `./abc200/D`: bash ../../../configs/post_problem.sh ================================================= 2021-05-08 21:00:21,859 INFO: Problem E: ../configs/ipynb_template.md is used for template 2021-05-08 21:00:22,049 INFO: Problem E: Created examples. 2021-05-08 21:00:22,050 INFO: Problem E: Format prediction succeeded 2021-05-08 21:00:22,122 INFO: Problem E: Saved code to ./abc200/E/main.py 2021-05-08 21:00:22,122 INFO: Problem E: Saved metadata to ./abc200/E/metadata.json 2021-05-08 21:00:22,122 INFO: Problem E: Executing the following command in `./abc200/E`: bash ../../../configs/post_problem.sh ================================================= 2021-05-08 21:00:23,473 INFO: Problem F: ../configs/ipynb_template.md is used for template 2021-05-08 21:00:23,624 INFO: Problem F: Created examples. 2021-05-08 21:00:23,625 INFO: Problem F: Format prediction succeeded 2021-05-08 21:00:23,706 INFO: Problem F: Saved code to ./abc200/F/main.py 2021-05-08 21:00:23,706 INFO: Problem F: Saved metadata to ./abc200/F/metadata.json 2021-05-08 21:00:23,706 INFO: Problem F: Executing the following command in `./abc200/F`: bash ../../../configs/post_problem.sh ================================================= 2021-05-08 21:00:25,043 INFO: Executing the following command in `./abc200`: bash ../../configs/post_contest.sh


class: center, middle, inverse, title-slide # 4.3 — The Standard of Care ## ECON 315 • Economics of the Law • Spring 2021 ### Ryan Safner
Assistant Professor of Economics
<EMAIL_ADDRESS>ryansafner/lawS21
lawS21.classes.ryansafner.com
--- class: inverse # Outline ### [Standard of Care](#3) ### [The Effect of Court Errors](#) --- class: inverse, center, middle # Standard of Care --- # Standard of Care .pull-left[ - So far, we have been assuming that the legal standard of care is set to the efficient level `$$x^l=x^\star$$` - In some cases, this is what courts actually try to do ] .pull-right[ .center[ ![](../images/caution.jpg) ] ] --- # U.S. v. Caroll Towing Co. .pull-left[ .quitesmall[ - *U.S. v. Caroll Towing Co.* 159 F.2d 169 (2d. Cir. 1947) - Several barges tied together to piers in NY Harbor - Defendant’s tugboat was hired to tow one out to harbor - Crew readjusted the lines to free the barge - Done incorrectly, one broke loose, collided with another ship, sank - Barge owner sued tugboat owner, claiming employees were negligent - Tug owner claimed barge owner was also negligent (did not have an agent on board the barge) - Question for court: .hi-turquoise[was it negligent to not have a “bargee” on board?] ] ] .pull-right[ .center[ ![](../images/barges.png) ] ] --- # U.S. v. Caroll Towing Co. .left-column[ .center[ ![:scale 80%](../images/learnedhand.jpg) .smallest[ Learned Hand 1872—1961 U.S. 2nd Circuit Court of Appeals ] ] ] .right-column[ .smallest[ > “It appears...that there is no general rule...Since there are occasions when every vessel will break away from her moorings, and since, if she does, she becomes a menace to those around her; the owner’s duty...to provide against resulting injuries is a function of three variables: > “(1) the probability that she will break away; (2) the gravity of the resulting injury, if she does; (3) the burden of adequate precautions. > “Perhaps it serves to bring this notion into relief to state it in algebraic terms: > “if the probability be called P; the injury, L; and the burden, B; > “.hi[liability depends upon whether B is less than L multiplied by P.]” ] ] --- # The Hand Rule .left-column[ .center[ ![:scale 80%](../images/learnedhand.jpg) .smallest[ Learned Hand 1872—1961 U.S. 2nd Circuit Court of Appeals ] ] ] .right-column[ - .hi[The “Hand Rule”]: failure to take a precaution constitutes **negligence** if: `$$\color{green}{B} < \color{red}{L \times P}$$` - `\(\color{green}{B}\)`: cost of precaution (“burden”) - `\(\color{red}{L}\)`: cost of accident (“liability”) - `\(\color{red}{p}\)`: probability of accident - A particular precaution activity is required to avoid liability if it is .hi-purple[cost-justified]: costs less than the benefit it provides - “If a precaution is efficient, you are negligent if you failed to take it” ] --- # The Hand Rule .left-column[ .center[ ![:scale 80%](../images/learnedhand.jpg) .smallest[ Learned Hand 1872—1961 U.S. 2nd Circuit Court of Appeals ] ] ] .right-column[ - .hi[The “Hand Rule”]: failure to take a precaution constitutes **negligence** if: `$$\color{green}{B} < \color{red}{L \times P}$$` - `\(\color{green}{B}\)`: cost of precaution (“burden”) - `\(\color{red}{L}\)`: cost of accident (“liability”) - `\(\color{red}{p}\)`: probability of accident - Ruled in this particular case (*Caroll Towing*) that barge owner was negligent for not having a bargee aboard the barge during the day ] --- # The Hand Rule .pull-left[ - Having a bargee or not is a discrete choice - If precaution is continuous variable `\((x)\)`, we can think of these as `\(\color{green}{MC}\)` and `\(\color{red}{MB}\)` of precaution in our model - Burden (B): `\(w\)` - Probability (P) of accidents: `\(-p'(x)\)` - Liability (L) or size of accident: `\(A\)` ] -- .pull-right[  ] --- # The Hand Rule .pull-left[ .smallest[ - .hi[The “Hand Rule”]: failure to take a precaution constitutes **negligence** if: `$$\color{green}{B} < \color{red}{L \times P}$$` - In our model: negligence if `\(\color{green}{w}<\color{red}{-p'(x)A}\)`, i.e. if `\(x<x^\star\)` ] ] .pull-right[  ] --- # The Hand Rule .pull-left[ .smallest[ - .hi[The “Hand Rule”]: failure to take a precaution constitutes **negligence** if: `$$\color{green}{B} < \color{red}{L \times P}$$` - In our model: negligence if `\(\underbrace{\color{green}{w}}_{\color{green}{MC}}<\underbrace{\color{red}{-p'(x)A}}_{\color{red}{MB}}\)`, i.e. if `\(x<x^\star\)` - In marginal magnitudes: - `\(\color{green}{MC}\)` of precaution: cost of precaution `\(w\)` - `\(\color{red}{MB}\)` of precaution: reduced probability of accident `\(-p'(x)A\)` ] ] .pull-right[  ] --- # The Standard of Care .pull-left[ - The hand test is one (efficient!) way courts have tried to set standards of care - Laws & regulations are another - Finally: enforce social norms or industry best-practices ] .pull-right[ .center[ ![](../images/caution.jpg) ] ] --- # The Standard of Care .pull-left[ .smallest[ - U.S. courts have consistently *misapplied* the Hand Rule (if their goal is efficiency) - Efficient level of precaution `\(x^\star\)` should be based on minimizing **total social cost** of accident - This includes **both** harm to victim (.hi-purple[“risk to others”]) and to injurer (.hi-purple[“risk to self”]) - Social benefit of me driving carefully is reduced risk of harm to pedestrians/bikers *and* to me! - Courts have tended to only count risk to *others* when calculating benefit of precaution `\((PL)\)` ] ] .pull-right[ .center[ ![](../images/caution.jpg) ] ] --- # The Standard of Care .pull-left[ - Hindsight bias - After an accident, we assume it was likely to occur - Hard to get unbiased probability estimate `\((p)\)` of something after it happens (likely to *over*estimate the likelihood) ] .pull-right[ .center[ ![](../images/caution.jpg) ] ] --- class: inverse, center, middle # The Effect of Court Errors --- # The Effect of Court Errors .pull-left[ .smallest[ - We’ve seen .hi[negligence rules] lead to efficient precaution `\((x^\star, y^\star)\)` by both parties - But .hi[strict liability] leads to efficient activity levels by injurers - Over the 20th century, strict liability rules became more common (especially for manufacturers)...why? - We will examine products liability next class - The role of information ] ] .pull-right[ .center[ ![](../images/information.png) ] ] --- # The Effect of Court Errors .pull-left[ - It’s relatively easy (for .blue[Plaintiff]) to demonstrate (1) harm and (2) causation - .hi-green[Example]: A Coca-cola bottle explodes and takes out my eye - Much harder to prove (.red[Defendent’s]) negligence - .hi-green[Example]: How can I show Coca-cola was negligent in their bottling process? .source[*Escola v. Coca-Cola Bottling Co.*, 24 Cal.2d 453 (1944)] ] .pull-right[ .center[ ![](../images/coke-explode.png) ] ] --- # The Effect of Court Errors .pull-left[ .smallest[ - If this is the case, .red[Injurers] might avoid liability altogether...in which case they would have no incentive to take precaution! - .hi-green[Example]: Negligence requires **me** to figure out the efficient level of care for Coca-Cola; strict liability only requires **Coca-Cola** to figure out its efficient level of care - Coca-cola likely has better information about their bottling process than I do - May explain why .hi-turquoise[strict liability rules have become more common] ] .source[*Escola v. Coca-Cola Bottling Co.*, 24 Cal.2d 453 (1944)] ] .pull-right[ .center[ ![](../images/coke-explode.png) ] ] --- # Errors & Uncertainty in Assessing Damages .pull-left[ - .hi[Random mistakes]: damages could be set too high or too low, but on average (cancel out and) are correct - Your textbook calls this “uncertainty” - .hi[Systematic mistakes]: damages are consistently set *incorrectly* on average, consistently too high or too low - Your textbook calls this “errors” ] .pull-right[ .center[ ![:scale 100%](../images/court1.jpg) ] ] --- # Effects Errors & Uncertainty Under Strict Liability .pull-left[ .smallest[ - Under .hi[strict liability] - .red[Injurer] minimizes `\(wx+p(x)D\)` - With perfect compensation, `\(D=A\)` - Leads .red[Injurer] to efficiently minimize total social cost `\(wx+p(x)A\)` at `\(x^\star\)` - .hi-purple[Random errors in damages have no affect on incentives] - .red[Injurer] only cares about **expected** level of damages - As long as damages correct on average, .red[Injurers] still internalize cost of accidents, and .hi-purple[take efficient precaution and activity level] ] ] .pull-right[ .center[ ![:scale 100%](../images/court1.jpg) ] ] --- # Effects Errors & Uncertainty Under Strict Liability .pull-left[ .smallest[ - On the other hand, **systematic errors** will skew .red[Injurer]’s incentives - .hi-green[Example]: suppose damages are set too low, `\(D<A\)` - New expected level of damages, `\(\color{red}{p(x)D}\)`, below true `\(\color{red}{p(x)A}\)` - New private cost for .red[Injurer] to minimize: `\(\color{blue}{wx+p(x)D}\)` at `\(x_2\)` - .red[Injurer] would internalize less than full social cost of accidents, **underinvest** in precaution `\(x_2<x^\star\)` - Note if damages were set too high `\(D>A\)`, opposite would happen (too much precaution)! ] ] .pull-right[  ] --- # Effects Errors & Uncertainty Under Strict Liability .pull-left[ .smallest[ - So under .hi[strict liability] - Random errors in setting damages have no effect - Systematic errors in setting damages skew .red[Injurer’s] incentives in direction of the error - If damages set too low, `\(D<A\)`, precaution will be inefficiently low `\(x<x^\star\)` - If damages set too high, `\(D>A\)`, precaution will be inefficiently high `\(x>x^\star\)` ] ] .pull-right[ .center[ ![:scale 100%](../images/court1.jpg) ] ] --- # Effects Errors & Uncertainty Under Negligence .pull-left[ .smallest[ - Under a .hi[negligence rule] - Random errors in setting damages have no effect - .hi-green[Example]: assume court had again accidentally set too high damages, `\(D>A\)` ] ] .pull-right[  ] --- # Effects Errors & Uncertainty Under Negligence .pull-left[ .smallest[ - Under a .hi[negligence rule] - Random errors in setting damages have no effect - .hi-green[Example]: assume court had again accidentally set too high damages, `\(D>A\)` - Recall negligence is a threshold rule, private cost to .red[injurer] is: `$$\begin{cases} p(x)A+wx && \text{if } x<x^l\\ \end{cases}$$` ] ] .pull-right[  ] --- # Effects Errors & Uncertainty Under Negligence .pull-left[ .smallest[ - Under a .hi[negligence rule] - Random errors in setting damages have no effect - .hi-green[Example]: assume court had again accidentally set too high damages, `\(D>A\)` - Recall negligence is a threshold rule, private cost to .red[injurer] is: `$$\begin{cases} p(x)A+wx && \text{if } x<x^l\\ wx && \text{if } x \geq x^l\\ \end{cases}$$` - So assuming the standard is set correctly, small errors in actual damages have no affect on .red[Injurer] precaution! ] ] .pull-right[  ] --- # Effects Errors & Uncertainty Under Negligence .pull-left[ - Under a .hi[negligence rule] - If the court makes a mistake in setting the standard of care, `\(x^l\)`... ] .pull-right[  ] --- # Effects Errors & Uncertainty Under Negligence .pull-left[ - Under a .hi[negligence rule] - If the court makes a mistake in setting the standard of care, `\(x^l\)`... - Setting lower standard reduces precaution ] .pull-right[  ] --- # Effects Errors & Uncertainty Under Negligence .pull-left[ - Under a .hi[negligence rule] - If the court makes a mistake in setting the standard of care, `\(x^l\)`... - Setting lower standard reduces precaution - Setting higher standard increases precaution - ....red[Injurer] adjusts precaution **exactly** to whatever the standard is set to ] .pull-right[  ] --- # Effects Errors & Uncertainty Under Negligence .pull-left[ .smallest[ - Under a .hi[negligence rule] - If the court makes **random errors** in choosing a standard `\(x^l\)`, creates .hi[uncertainty] for the .red[Injurer] - or, equivalently, uncertain how court will compare chosen `\(x\)` with `\(x^l\)` - In general, .red[Injurer] being uncertain about whether they might be found liable or not causes them to **undertake excessive precaution** - Increased precaution `\(wx\)` often costs little, whereas increased liability often costs a lot ] ] .pull-right[  ] --- # Summing Up Errors Under Different Rules .pull-left[ .smallest[ - Under strict liability - failure to consistently hold injurers liable leads to less precaution - **random** errors in setting damages have **no effect** - **systematic** errors in setting damages skew .red[Injurer] incentives in same direction - Under negligence - **small** errors (random or systematic) in setting damages have **no effect** - **systematic** errors in setting the **standard of care** have a 1:1 effect on precaution ] ] .pull-right[ .center[ ![:scale 100%](../images/court1.jpg) ] ] --- # Summing Up Errors Under Different Rules .pull-left[ - So this has the following normative implications: 1. When a court can assess damages more accurately than standard of care, strict liability is better 2. When a court can better assess standards, negligence is better 3. When standard of care is vague, court should err on side of leniency (not encourage excessive precaution) ] .pull-right[ .center[ ![:scale 100%](../images/court1.jpg) ] ] --- # Bright-Line Rules vs. Standards .pull-left[ .smallest[ - In our simple model, the economic goal of tort liability is to minimize total social costs (sum of costs of precaution and expected cost of accidents) - In reality, we also have to consider any given rule’s .hi[administrative costs] - Tradeoff between rules (like legal standard of care) tailored to individual situations, vs. broad, simple rules that apply to many situations - Broad, simple rules are cheaper to create and enforce, but will not create perfect incentives in every situation - More specific, detailed, “tailored” rules will be more costly to create and enforce, but will create more efficient incentives ]] .pull-right[ .center[ ![:scale 100%](../images/court1.jpg) ] ] --- # Administrative Costs: Negligence vs. Strict Liability .pull-left[ .smallest[ - Under negligence: - Longer, more expensive trials (.blue[Plaintiff] needs to demonstrate .red[Defendant] was negligent) - But fewer trials! Not every .blue[Victim] has a case, since .red[Injurers] tend to take precautions to avoid liability! - Under strict liability: - Fewer, speedier trials (no need to demonstrate negligence, only harm & causation) - But more trials! .blue[Victims] are much more likely to win, and have a stronger incentive to bring lawsuits ] ] .pull-right[ .center[ ![:scale 100%](../images/court1.jpg) ] ] --- # Another Point About Information and Errors .pull-left[ - .hi[Negligence with a defense of contributory negligence] was dominant liability rule in common law countries - Negligent .red[Injurer] is liable, unless .blue[Victim] was also negligent - .hi-green[Example]: car going 60 MPH hits a car going 40 MPH in 25 MPH zone ] .pull-right[ .center[ ![:scale 100%](../images/spidermannegligence.jpg) ] ] --- # Another Point About Information and Errors .pull-left[ .smaller[ - Over the last half century, most U.S. States have adopted .hi[comparative negligence] rules - Often via legislation, sometimes through court decisions - Appealing from a fairness point of view - But we saw *any* negligence rule leads to efficient precaution - So why this consistent change? ] ] .pull-right[ .center[ ![:scale 100%](../images/spidermannegligence.jpg) ] ] --- # Comparative Negligence and Evidentiary Uncertainty .pull-left[ .smallest[ - .hi[Evidentiary uncertainty]: uncertainty in how court/jury will interpret evidence - Given a legal standard for negligence, `\(x^l\)`... - ...and an actual level of precaution chosen, `\(x\)`... - still uncertain whether court will find .red[Injurer] was negligent - Evidentiary uncertainty leads to over-precaution - But comparative negligence mitigates this effect! - Injurer might only be found *partly* liable (liability shared with victim), so less over-cautious ] ] .pull-right[ .center[ ![:scale 70%](../images/evidence.png) ] ]


Hi, my name is Lukas, i am 33 years old, live in Germany and try to learn more about Web-Development and Design. Unfortunately it's not so easy to find time to do this.
When i am programming, i mostly use these technologies
Either through eMail or facebook.


---
layout: post
title: Ferdinand I of Portugal death
date: '2013-03-22T19:18:00+01:00'
categories:
- Atoleiros Battle
picture_url: https://film-Storyboards.tumblr.com/post/46029797246/death-of-ferdinand-i-of-portugal-rough
---
Death of Ferdinand I of Portugal.
Rough Storyboards VS animatic drawing of the same shot.
- death - monks - procession - Illustration - black and white drawing - Ferdinand I of Portugal - succession


So far in this class we have looked at the population as the fundamental unit that we are interested in modeling. This makes sense for a population ecology class! But we are all aware that populations consist of individuals that are semi-autonomous. Sometimes the questions we want to ask in ecology and conservation biology require us to zoom in on the processes that are occurring at the individual level.
In some ways a population is hard to define- it can be a bit of an artificial concept. The individual is (mostly) a straightforward, biologically meaningful concept.
Before we define how individual-based models differ from the population-level stock-flow models we have already been using, let’s first point out the similarities.
First of all, the basic modeling workflow is ALWAYS the same, no matter what kind of model we want to use!
All models are a way to formalize our understanding about our study system.
Population-based models (PBM; i.e., models of \(N\)) are the main type of model we consider in this class- because it is the most direct way to think about population dynamics: \(N\) is our main variable of interest, and it is controlled by intrinsic (e.g., density-dependence, demographic stochasticity) and extrinsic (e.g., environmental stochasticity, harvest) factors.

Individual-based models (IBM; also known as “agent-based” models) is a way of modeling populations such that all individuals are considered explicitly! We no longer need to put individuals into groups- each individual can potentially have a different survival probability, or chance of breeding, or movement propensity! In this case, we don’t model \(N\) directly at all – in fact, \(N\) is an emergent property of individual organisms interacting with each other, with predators and competitors, and with their abiotic environment.
In general, models are tools- you should use the model structure that best fits with the questions you are asking and your understanding of the study system!
And also, if two different model structures are equally appropriate, you should usually use the simplest approach! This idea is often called the Principle of Parsimony (or, Occam’s Razor).
Both IBM and PBM can be used to address questions at the population or metapopulation level
In general, you should use IBM if your primary information at the individual level (e.g., telemetry data)– allowing you to build informed models of how individuals interact with members of their own species, possibly other species, and their local environment – in which case the principle of parsimony dictates that you should build models at the individual level!
You should use PBM if your primary information is at the population level (e.g., the results of most mark-recapture analyses) – in which case the principle of parsimony dictates that you should build models at the population level!
Q: All populations are composed of individuals. Why then don’t we always model populations using individual-based models? (this could be a good exam question…)
Q: What are some questions that might be best addressed using individual-based models (IBM)?
Q: What are some questions that might be best addressed using population-based models (PBM)?
Individual-based models are powerful- but with power comes great responsibility!
The goal of this activity is to build a mechanistic, individual-based model (IBM) of a (real, not made-up by my postdoc I swear!) ecological system.
The laphlag island archipelago is famous for its dramatic slopes, lush green grass, and its native sheep, the laphlag island bighorn. About 50 years ago, the native island wolf population was hunted to extinction by ranchers, to prevent any wolf predation on their precious livestock.
However, without wolves, populations of the native sheep skyrocketed, and the famous laphlagian lush green grass is quickly being lost to overgrazing by the native sheep.
The locals now realize: They need to reintroduce wolves to the islands!
You have been hired as a research ecologist to help the locals and biologists address the following questions:
How are reintroduced wolves likely to affect grass biomass and distribution?
How many wolves are needed to effectively restore that characteristic lush green grass to the islands?
The local management agency is about to start an experimental wolf reintroduction, but they want to know what to expect before making the final decision to go ahead with it.
They give you some information to get a first guess but they promise that you’ll be able to come study the experimental setup once it’s underway.
The hypothesis is that presence of wolves affects sheep populations in such a way that grass growth is promoted.
The enclosure is deployed after the breeding season and the experiment is run for 365 days.
 Here is the link!.
Make sure you can run the model and interpret the resulting figures.
Does the model behave realistically? Test it! What happens if you start with lots of sheep and no wolves?
Is it possible for the experimental plot to support sheep, wolves, and grass indefinitely?
What if wolves were more efficient at killing sheep? Try doubling the “Prob of kill” variable and see how your answer changes.
What if grass were more productive? Try doubling the “Grass Growth Rate” and see if more sheep can be supported sustainably.
What if the wolves don’t actually kill the sheep, but just scare them (make them move)?? Does the presence of wolves affect grass growth in this case? (hint- you might need to set sheep birth rate to 0 to see an effect)
Q: is there any stochasticity in this model? If so, what kind of stochasticity is there? Take an educated guess!


Contributing to the AWS SDK for Ruby
We work hard to provide a high-quality and useful SDK, and we greatly value feedback and contributions from our community. Whether it's a new feature, correction, or additional documentation, we welcome your pull requests. Please submit any issues or pull requests through GitHub.
What you should keep in mind
- The SDK is released under the Apache license. Any code you submit will be released under that license. For substantial contributions, we may ask you to sign a Contributor License Agreement (CLA).
- We maintain a high percentage of code coverage in our unit tests. If you make changes to the code, please add, update, and/or remove unit (and integration) tests as appropriate.
- We may choose not to accept pull requests that change service descriptions, such as
aws-sdk-core/apis/S3.api.json
. We generate these files based on our internal knowledge of the AWS services. If there is something incorrect with or missing from a service description, it may be more appropriate to submit an issue. We will, however, consider pull requests affecting service descriptions, if the changes are related to paginators, waiters, or resources configurations. - If your code does not include adequate tests, we may ask you to update your pull requests before we accept them. We also reserve the right to deny any pull requests that do not align with our standards or goals.
- If you would like to implement support for a significant feature that is not yet available in the SDK, please talk to us beforehand to avoid any duplication of effort.
What we are looking for
We are open to anything that improves the SDK and doesn't unnecessarily cause backwards-incompatible changes. If you are unsure if your idea is something we would be open to, please ask us; Open an issue, send us an email, or ask in the Gitter channel. Specifically, here are a few things that we would appreciate help on:
- Waiters – Waiter configurations are located in the apis directory.
- Docs – We greatly appreciate contributions to our documentation. The docs are written as code comments and via a pair of YARD plugins.
- Tests – We maintain high code coverage, but if there are any tests you feel are missing, please add them.
- Convenience features – Are there any features you feel would add value to the SDK? Contributions in this area would be greatly appreciated. See the feature requests document for a list of ideas.
- If you have some other ideas, please let us know!
Running the unit tests
The AWS SDK for Ruby is unit tested using RSpec. You can run the unit tests of the SDK after cloning the repo:
bundle install
bundle exec rake test
To run integration tests, create a integration-test-config.json
file at the root of this repository. It should
contain a "region"
and credentials. Running rake test when this file is present will enable integration tests.


| Criteria | Evaluation Item | Points Earned |
Possible points |
|---|---|---|---|
| Program Setup & Runs | Project successfully runs. Netbeans project zipped and submitted to D2L dropbox. Student's Name appears in the Window Frame when program is run and in screen capture image and in screen capture. | |
5 |
| House Output | Output shows a house with windows and a door; it looks like a normal house (windows and doors are contained within the house rectangle) | |
5 |
| Roof Output | Roof of house drawn with diagonal lines | |
5 |
| Tree Output | Tree drawn with green oval overlapping brown trunk | |
5 |
| Sun Output | Sun drawn with eyes and smile inside the circle | |
5 |
| Total Points ====> | |
25 |


Refund Dashboard
Card:
Phone:
Name:{{name1}}
Status:
{{status}}
Card:{{card}}
Balance:{{bal}}
Phone:{{(phone).substring(3)}}
Valid:{{valid}}
UserID:{{userID}}
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Payment Gateway
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Debit Amount
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GatewayTransactionId
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Submit


Visualization of Air Pollution
Loading...
Try clicking a dot on the map, a layer in the stacked area chart, or a pollutant name on the bottom.


CliFlo is a web portal to the New Zealand National Climate Database and provides public access (via subscription) to around 6,500 various climate stations (see <https://cliflo.niwa.co.nz/> for more information). Collating and manipulating data from CliFlo (hence clifro) and importing into R for further analysis, exploration and visualisation is now straightforward and coherent. The user is required to have an internet connection, and a current CliFlo subscription (free) if data from stations, other than the public Reefton electronic weather station, is sought.
| Version: | 3.2-0 |
| Imports: | methods, lubridate, xml2, magrittr, RCurl, utils, ggplot2 (≥ 2.0.0), scales, RColorBrewer, reshape2 |
| Suggests: | knitr, rmarkdown, ggmap (≥ 2.6), pander, testthat |
| Published: | 2018-07-25 |
| Author: | Blake Seers [aut, cre] |
| Maintainer: | Blake Seers <blake.seers at gmail.com> |
| BugReports: | https://github.com/ropensci/clifro/issues |
| License: | GPL-2 |
| URL: | https://github.com/ropensci/clifro |
| NeedsCompilation: | no |
| Citation: | clifro citation info |
| Materials: | README NEWS |
| CRAN checks: | clifro results |
| Reference manual: | clifro.pdf |
| Vignettes: |
Working with clifro stations Choosing a clifro datatype Choosing a clifro station An introduction to clifro |
| Package source: | clifro_3.2-0.tar.gz |
| Windows binaries: | r-devel: clifro_3.2-0.zip, r-release: clifro_3.2-0.zip, r-oldrel: clifro_3.2-0.zip |
| OS X binaries: | r-release: clifro_3.2-0.tgz, r-oldrel: clifro_3.2-0.tgz |
| Old sources: | clifro archive |
| Reverse suggests: | macleish |
Please use the canonical form https://CRAN.R-project.org/package=clifro to link to this page.


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Macros | |
| #define | CSL_INTC_VECTID_NMI (1) |
| #define | CSL_INTC_VECTID_4 (4) |
| #define | CSL_INTC_VECTID_5 (5) |
| #define | CSL_INTC_VECTID_6 (6) |
| #define | CSL_INTC_VECTID_7 (7) |
| #define | CSL_INTC_VECTID_8 (8) |
| #define | CSL_INTC_VECTID_9 (9) |
| #define | CSL_INTC_VECTID_10 (10) |
| #define | CSL_INTC_VECTID_11 (11) |
| #define | CSL_INTC_VECTID_12 (12) |
| #define | CSL_INTC_VECTID_13 (13) |
| #define | CSL_INTC_VECTID_14 (14) |
| #define | CSL_INTC_VECTID_15 (15) |
| #define | CSL_INTC_VECTID_COMBINE (16) |
| #define | CSL_INTC_VECTID_EXCEP (17) |
Typedefs | |
| typedef Int | CSL_IntcEventId |
Enumerations | |
| enum | CSL_IntcHwControlCmd { CSL_INTC_CMD_EVTENABLE = 0, CSL_INTC_CMD_EVTDISABLE = 1, CSL_INTC_CMD_EVTSET =2, CSL_INTC_CMD_EVTCLEAR =3, CSL_INTC_CMD_EVTDROPENABLE =4, CSL_INTC_CMD_EVTDROPDISABLE =5, CSL_INTC_CMD_EVTINVOKEFUNCTION = 6 } |
| enum | CSL_IntcHwStatusQuery { CSL_INTC_QUERY_PENDSTATUS } |
| enum | CSL_IntcExcepEn { CSL_INTC_EXCEP_0TO31 = 0, CSL_INTC_EXCEP_32TO63 = 1, CSL_INTC_EXCEP_64TO95 = 2, CSL_INTC_EXCEP_96TO127 = 3 } |
| enum | CSL_IntcExcep { CSL_INTC_EXCEPTION_NMI = 31, CSL_INTC_EXCEPTION_EXT = 30, CSL_INTC_EXCEPTION_INT = 1, CSL_INTC_EXCEPTION_SW = 0 } |
| #define CSL_INTC_VECTID_10 (10) |
CPU Vector 10
| #define CSL_INTC_VECTID_11 (11) |
CPU Vector 11
| #define CSL_INTC_VECTID_12 (12) |
CPU Vector 12
| #define CSL_INTC_VECTID_13 (13) |
CPU Vector 13
| #define CSL_INTC_VECTID_14 (14) |
CPU Vector 14
| #define CSL_INTC_VECTID_15 (15) |
CPU Vector 15
| #define CSL_INTC_VECTID_4 (4) |
CPU Vector 4
| #define CSL_INTC_VECTID_5 (5) |
CPU Vector 5
| #define CSL_INTC_VECTID_6 (6) |
CPU Vector 6
| #define CSL_INTC_VECTID_7 (7) |
CPU Vector 7
| #define CSL_INTC_VECTID_8 (8) |
CPU Vector 8
| #define CSL_INTC_VECTID_9 (9) |
CPU Vector 9
| #define CSL_INTC_VECTID_COMBINE (16) |
Should be used at the time of opening an Event handle to specify that the event needs to go to the combiner
| #define CSL_INTC_VECTID_EXCEP (17) |
Should be used at the time of opening an Event handle to specify that the event needs to go to the exception combiner.
| #define CSL_INTC_VECTID_NMI (1) |
Interrupt Vector IDsShould be used only along with CSL_intcHookIsr()
| typedef Int CSL_IntcEventId |
Interrupt Event IDs
| enum CSL_IntcExcep |
Enumeration of the exception These are the symbols used along with the Exception Clear API
| enum CSL_IntcExcepEn |
Enumeration of the exception mask registers
These are the symbols used along with the value to be programmed into the Exception mask register.
| Enumerator | |||
|---|---|---|---|
| CSL_INTC_EXCEP_0TO31 |
Symbol for EXPMASK[0].
| ||
| CSL_INTC_EXCEP_32TO63 |
Symbol for EXPMASK[1].
| ||
| CSL_INTC_EXCEP_64TO95 |
Symbol for EXPMASK[2].
| ||
| CSL_INTC_EXCEP_96TO127 |
Symbol for EXPMASK[3].
|
| enum CSL_IntcHwControlCmd |
Enumeration of the control commands
These are the control commands that could be used with CSL_intcHwControl(..). Some of the commands expect an argument as documented along-side the description of the command.
| Enumerator | |||
|---|---|---|---|
| CSL_INTC_CMD_EVTENABLE |
Enables the event.
| ||
| CSL_INTC_CMD_EVTDISABLE |
Disables the event.
| ||
| CSL_INTC_CMD_EVTSET |
Sets the event manually.
| ||
| CSL_INTC_CMD_EVTCLEAR |
Clears the event (if pending)
| ||
| CSL_INTC_CMD_EVTDROPENABLE |
Enables the Drop Event detection feature for this event.
| ||
| CSL_INTC_CMD_EVTDROPDISABLE |
Disables the Drop Event detection feature for this event.
| ||
| CSL_INTC_CMD_EVTINVOKEFUNCTION |
To be used ONLY to invoke the associated Function handle with Event when the user is writing an exception handling routine.
|
Enumeration of the queries
These are the queries that could be used with CSL_intcGetHwStatus(..). The queries return a value through the object pointed to by the pointer that it takes as an argument. The argument supported by the query is documented along-side the description of the query.
| Enumerator | |||
|---|---|---|---|
| CSL_INTC_QUERY_PENDSTATUS |
The Pend Status of the Event is queried.
|


Shell and Utility Commands
Shell Commands
fs
Invokes any FsShell command from within a Pig script or the Grunt shell.
Syntax
|
fs subcommand subcommand_parameters |
Terms
|
subcommand |
The FsShell command. |
|
subcommand_parameters |
The FsShell command parameters. |
Usage
Use the fs command to invoke any FsShell command from within a Pig script or Grunt shell. The fs command greatly extends the set of supported file system commands and the capabilities supported for existing commands such as ls that will now support globing. For a complete list of FsShell commands, see File System Shell Guide
Examples
In these examples a directory is created, a file is copied, a file is listed.
fs -mkdir /tmp fs -copyFromLocal file-x file-y fs -ls file-y
sh
Invokes any sh shell command from within a Pig script or the Grunt shell.
Syntax
|
sh subcommand subcommand_parameters |
Terms
|
subcommand |
The sh shell command. |
|
subcommand_parameters |
The sh shell command parameters. |
Usage
Use the sh command to invoke any sh shell command from within a Pig script or Grunt shell.
Note that only real programs can be run form the sh command. Commands such as cd are not programs but part of the shell environment and as such cannot be executed unless the user invokes the shell explicitly, like "bash cd".
Example
In this example the ls command is invoked.
grunt> sh ls bigdata.conf nightly.conf ..... grunt>
Utility Commands
clear
Clear the screen of Pig grunt shell and position the cursor at top of the screen.
Syntax
|
clear |
Terms
|
key |
Description. |
|
none |
no parameters |
Example
In this example the clear command clean up Pig grunt shell.
grunt> clear
exec
Run a Pig script.
Syntax
|
exec [–param param_name = param_value] [–param_file file_name] [script] |
Terms
|
–param param_name = param_value |
|
|
–param_file file_name |
|
|
script |
The name of a Pig script. |
Usage
Use the exec command to run a Pig script with no interaction between the script and the Grunt shell (batch mode). Aliases defined in the script are not available to the shell; however, the files produced as the output of the script and stored on the system are visible after the script is run. Aliases defined via the shell are not available to the script.
With the exec command, store statements will not trigger execution; rather, the entire script is parsed before execution starts. Unlike the run command, exec does not change the command history or remembers the handles used inside the script. Exec without any parameters can be used in scripts to force execution up to the point in the script where the exec occurs.
For comparison, see the run command. Both the exec and run commands are useful for debugging because you can modify a Pig script in an editor and then rerun the script in the Grunt shell without leaving the shell. Also, both commands promote Pig script modularity as they allow you to reuse existing components.
Examples
In this example the script is displayed and run.
grunt> cat myscript.pig a = LOAD 'student' AS (name, age, gpa); b = LIMIT a 3; DUMP b; grunt> exec myscript.pig (alice,20,2.47) (luke,18,4.00) (holly,24,3.27)
In this example parameter substitution is used with the exec command.
grunt> cat myscript.pig a = LOAD 'student' AS (name, age, gpa); b = ORDER a BY name; STORE b into '$out'; grunt> exec –param out=myoutput myscript.pig
In this example multiple parameters are specified.
grunt> exec –param p1=myparam1 –param p2=myparam2 myscript.pig
help
Prints a list of Pig commands or properties.
Syntax
|
-help [properties] |
Terms
|
properties |
List Pig properties. |
Usage
The help command prints a list of Pig commands or properties.
Example
Use "-help" to get a list of commands.
$ pig -help Apache Pig version 0.8.0-dev (r987348) compiled Aug 19 2010, 16:38:44 USAGE: Pig [options] [-] : Run interactively in grunt shell. Pig [options] -e[xecute] cmd [cmd ...] : Run cmd(s). Pig [options] [-f[ile]] file : Run cmds found in file. options include: -4, -log4jconf - Log4j configuration file, overrides log conf -b, -brief - Brief logging (no timestamps) -c, -check - Syntax check etc …
Use "-help properties" to get a list of properties.
$ pig -help properties The following properties are supported: Logging: verbose=true|false; default is false. This property is the same as -v switch brief=true|false; default is false. This property is the same as -b switch debug=OFF|ERROR|WARN|INFO|DEBUG; default is INFO. This property is the same as -d switch aggregate.warning=true|false; default is true. If true, prints count of warnings of each type rather than logging each warning. etc …
history
Display the list of statements used so far.
Syntax
|
history [-n] |
Terms
|
key |
Description. |
|
-n |
Omit line numbers in the list. |
Usage
The history command shows the statements used so far.
Example
In this example the history command shows all the statements with line numbers and without them.
grunt> a = LOAD 'student' AS (name, age, gpa); grunt> b = order a by name; grunt> history 1 a = LOAD 'student' AS (name, age, gpa); 2 b = order a by name; grunt> c = order a by name; grunt> history -n a = LOAD 'student' AS (name, age, gpa); b = order a by name; c = order a by name;
kill
Kills a job.

 Under certain conditions, however, this may fail; for example, when a Pig job is killed and does not have a chance to call its shutdown procedures.
Example
In this example the job with id job_0001 is killed.
grunt> kill job_0001
quit
Quits from the Pig grunt shell.
Syntax
|
exit |
Terms
|
none |
no parameters |
Usage
The quit command enables you to quit or exit the Pig grunt shell.
Example
In this example the quit command exits the Pig grunt shall.
grunt> quit
run
Run a Pig script.
Syntax
|
run [–param param_name = param_value] [–param_file file_name] script |
Terms
|
–param param_name = param_value |
|
|
–param_file file_name |
|
|
script |
The name of a Pig script. |
Usage
Use the run command to run a Pig script that can interact with the Grunt shell (interactive mode). The script has access to aliases defined externally via the Grunt shell. The Grunt shell has access to aliases defined within the script. All commands from the script are visible in the command history.
With the run command, every store triggers execution. The statements from the script are put into the command history and all the aliases defined in the script can be referenced in subsequent statements after the run command has completed. Issuing a run command on the grunt command line has basically the same effect as typing the statements manually.
For comparison, see the exec command. Both the run and exec commands are useful for debugging because you can modify a Pig script in an editor and then rerun the script in the Grunt shell without leaving the shell. Also, both commands promote Pig script modularity as they allow you to reuse existing components.
Example
In this example the script interacts with the results of commands issued via the Grunt shell.
grunt> cat myscript.pig b = ORDER a BY name; c = LIMIT b 10; grunt> a = LOAD 'student' AS (name, age, gpa); grunt> run myscript.pig grunt> d = LIMIT c 3; grunt> DUMP d; (alice,20,2.47) (alice,27,1.95) (alice,36,2.27)
In this example parameter substitution is used with the run command.
grunt> a = LOAD 'student' AS (name, age, gpa); grunt> cat myscript.pig b = ORDER a BY name; STORE b into '$out'; grunt> run –param out=myoutput myscript.pig
set
Shows/Assigns values to keys used in Pig.
Syntax
|
set [key 'value'] |
Terms
|
key |
Key (see table). Case sensitive. |
|
value |
Value for key (see table). Case sensitive. |
Usage
Use the set command to assign values to keys, as shown in the table. All keys and their corresponding values (for Pig and Hadoop) are case sensitive. If set command is used without key/value pair argument, Pig prints all the configurations and system properties.
|
Key |
Value |
Description |
|
default_parallel |
a whole number |
Sets the number of reducers for all MapReduce jobs generated by Pig (see Use the Parallel Features). |
|
debug |
on/off |
Turns debug-level logging on or off. |
|
job.name |
Single-quoted string that contains the job name. |
Sets user-specified name for the job |
|
job.priority |
Acceptable values (case insensitive): very_low, low, normal, high, very_high |
Sets the priority of a Pig job. |
|
stream.skippath |
String that contains the path. |
For streaming, sets the path from which not to ship data (see DEFINE (UDFs, streaming) and About Auto-Ship). |
All Pig and Hadoop properties can be set, either in the Pig script or via the Grunt command line.
Examples
In this example key value pairs are set at the command line.
grunt> SET debug 'on' grunt> SET job.name 'my job' grunt> SET default_parallel 100
In this example default_parallel is set in the Pig script; all MapReduce jobs that get launched will use 20 reducers.
SET default_parallel 20; A = LOAD 'myfile.txt' USING PigStorage() AS (t, u, v); B = GROUP A BY t; C = FOREACH B GENERATE group, COUNT(A.t) as mycount; D = ORDER C BY mycount; STORE D INTO 'mysortedcount' USING PigStorage();
In this example multiple key value pairs are set in the Pig script. These key value pairs are put in job-conf by Pig (making the pairs available to Pig and Hadoop). This is a script-wide setting; if a key value is defined multiple times in the script the last value will take effect and will be set for all jobs generated by the script.
... SET mapred.map.tasks.speculative.execution false; SET pig.logfile mylogfile.log; SET my.arbitrary.key my.arbitary.value; ...


This app does not transmit or save data. Generated phrases should be written down
and kept in a safe place.
Recommended: 16 byte (128 bit) key length for file encryption,
32 byte (256 bit) key length for bitcoin brainwallets.
For added security, app can be
downloaded
to a thumb drive/SD card and
run on an air-gapped (quarantined) device.
Source code,
other passphrase tools
Dictionary extracted from Alan Beale's
2 of 12 public domain dictionary


My name is Eugenia. I am a computer science major at Boston University. I specialize in front-end development, and clean, focused information architecture.
Click to see MoreI have experience in software, visual arts, and graphics. This allows me to both design and implement user interfaces with the creative process of an artist, and the technical skills of a software developer.
My background in computer science allows me to directly implement my designs through code. I have expertise in JavaScript, HTML, and CSS, including other languages and prototyping software.
Trends in UX and UI are constantly evolving. I keep up with these trends and use them in my work to ensure my designs reflect the current state of web/app development.
Good interaction design thrives upon user feedback. My experience with user testing allows me to continually innovate my designs.


--- layout: paper headline: Publications title: 'View-based Propagator Derivation' authors: 'Christian Schulte, Guido Tack' howpublished: > In: Constraints 18(1), pages 75-107. Springer-Verlag, 2013. copyright: Copyright Springer-Verlag, the original publication is available at www.springerlink.com link: pdf bibtex: > @Article{SchulteTack:Constraints:2013, Author = "Christian Schulte and Guido Tack", Title = "View-based Propagator Derivation", Journal = "Constraints", Year = 2013, Publisher = "Springer-Verlag", Volume = "18", Number = "1", Pages = "75--107", } relation: > Design and evaluation of generic propagators as used in Gecode shorthowpub: > Constraints, 2013. ---
When implementing a propagator for a constraint, one must decide about variants: When implementing min, should one also implement max? Should one implement linear constraints both with unit and non-unit coefficients? Constraint variants are ubiquitous: implementing them requires considerable (if not prohibitive) effort and decreases maintainability, but will deliver better performance than resorting to constraint decomposition.
This paper shows how to use views to derive propagator variants, combining the efficiency of dedicated propagator implementations with the simplicity and effortlessness of decomposition.
A model for views and derived propagators is introduced. Derived propagators are proved to be perfect in that they inherit essential properties such as correctness and domain and bounds consistency. Techniques for systematically deriving propagators such as transformation, generalization, specialization, and type conversion are developed. The paper introduces an implementation architecture for views that is independent of the underlying constraint programming system. A detailed evaluation of views implemented in Gecode shows that derived propagators are efficient and that views often incur no overhead. Views have proven essential for implementing Gecode, substantially reducing the amount of code that needs to be written and maintained.


Jakob the Liar (1999) 2 stars out of 4. Starring Robin Williams, Alan Arkin, Bob Balaban, Michael Jeter, Armin Mueller-Stahl and Liev Schreiber
"Jakob the Liar" unfolds like a Sholemcq Aleichem story: Through a misunderstanding, an unimportant little man suddenly gains stature and influence that he neither wants nor deserves.
However, instead of some turn-of-the-century shtetl in Russia, this story is set in an unnamed Polish city's Jewish ghetto during World War II.
 People are shot at random, put into cattle cars or commit suicide.
Jakob only wants to stay alive and away from the Nazis.
One night, though, near curfew he is accused of trying to escape from the ghetto and is sent to the office of a Gestapo official.
There he hears a radio broadcast and sees a map that pinpoints Russian troop deployments, indicating they are only 400 miles away and closing fast.
This information bolsters his spirits, and when he is allowed to return to the ghetto, he determines to spread the information among his friends, thus giving them hope.
But, like the story that is passed around the campfire, changing from person to person until it is barely unrecognizable, the other ghetto residents come to believe that Jakob has a hidden radio and begin pestering him for more news on the war's progress.
Despite his various protestations, no one believes Jakob when he insists he has no radio. Situations begin to escalate in comic and tragic turns. People begin treating him with respect and he becomes a reluctant leader in the community.
Jakob seems like a role created for Williams. He is funny, yet subdued as the circumstances demand. His asides and mutterings to himself are pure Williams, and that is the flaw in his performance. He doesn't come across as a poor, simple, scared former potato vendor, but as a big-time actor doing a star turn with an affected Eastern European accent.
The movie, directed by Peter Kassovitz with a screenplay by Kassovitz and Didier Decoin, struggles to blend comedy with the horror of the Holocaust, while also trying to keep an reverent tone concerning that nightmare.
They succeed partially. Kassovitz is able to convey the casualness of the brutality and death the Jews were forced to endure. It seems so impersonal that it lacks any emotional resonance or shock.
Despite a strong cast, including Alan Arkin, Bob Balaban, Michael Jeter, Armin Mueller-Stahl and Liev Schreiber, Jakob the Liar feels cold and impersonal. The performances by all concerned are good, but a spark, something to ignite the audience's emotions, is lacking.
"Jakob the Liar," unlike "Life Is Beautiful" - to which it will be compared mostly - and "Schindler's List," fails to touch our hearts and souls concerning the plight of these unfortunate people persecuted simply because they are Jewish.
Like the film's setting, "Jakob the Liar" is cold and gray. It neither inspires nor shocks. It just sits like a cold, day-old potato pancake.
Bob Bloom is the film critic at the Journal and Courier. He can be reached by e-mail at<EMAIL_ADDRESS>or at<EMAIL_ADDRESS>The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


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Ephemerids
What is Ephemerids? Past events... just that. Some sites will be happy to
have Ephemerids to inform visitors on what's happened in the past exactly
in this day. The configuration is very easy. Ephemerids will show a box
on left side of the home. You need to activate this function in Preferences.
To add a new ephemerid select the day, month and write the year
and the description for that event. When your system reach the day and month
you will see what happened in the story on that day and in what year
happened the event. For example you can set one event like: Day 12, Month
10, Year 1492... when users comes to your page on October 12 of any year
they will see a box that says that Colon arrives to America.
To edit or delete an ephemerid just select the day and month
you want to edit/delete.


XMLmind has developed a robust, self-contained, W3C XML Schema for XHTML 5 which is as faithful to W3C Candidate Recommendation 17 December 2012 as an W3C XML Schema can be.
XMLmind has also developed XSLT 2 stylesheets allowing —with the help of the appropriate XSL-FO processor— to convert XHTML 1.0, 1.1 and 5.0 documents to PostScript, PDF, RTF, WordprocessingML, Office Open XML (.docx) and OpenOffice (.odt).
These XSLT 2 stylesheets
xsl:attribute-set
s.The W3C XML Schema for XHTML 5 and the XSLT 2 stylesheets for XHTML 1.0, 1.1 and 5.0 developed by XMLmind are open source software licensed under the terms of the MIT license. This means that you may freely use these resources outside XMLmind products.
Example: validate this document (which is valid XHTML 5) using Xerces2 Java Parser 2.11:
$ java -cp "$XERCES_HOME/xercesSamples.jar:$XERCES_HOME/xercesImpl.jar:$XERCES_HOME/resolver.jar" \ jaxp.SourceValidator \ -a xsd/xhtml5.xsd -i xhtml5_resources.README.html
The XSLT stylesheets require Saxon 9.3+ in order to work.
Example: convert this document (which is valid XHTML 5) to PDF using Apache FOP:
$ java -jar "$SAXON9_HOME/saxon9he.jar" -xsl:xsl/fo.xsl \ -s:xhtml5_resources.README.html \ -o:tmp.fo \ foProcessor=FOP $ fop tmp.fo xhtml5_resources.README.pdf
Note that the XSLT
stylesheets must be passed a foProcessor
parameter specifying
which XSL-FO processor is being used. This allows to take advantage of
extensions which are specific to the processor or or the contrary to
workaround limitations which are specific to the
processor.
Please send bug reports to<EMAIL_ADDRESS>a public, moderated, mailing list. (You don't need to be a list member to post a message.) More information in http://www.xmlmind.com/xmleditor/support.html.
-f
option of
jaxp.SourceValidator
; see above)set-outline-level
. When
XMLmind XSL-FO
Converter is used to convert the intermediate XSL-FO file to
RTF, .odt
, .docx
, etc, and the
value of this parameter is 'yes'
(the default
value), consider the h1
, h2
, ...,
h6
elements as being headings participating in the outline
of the MS-Word or OpenOffice/LibreOffice document. More information in
the
set-outline-level
XSLT stylesheet parameter.text-align
and vertical-align
when these
styles were specified on thead
, tfoot
,
tbody
or tr
.Updated xhtml5.xsd to reflect the specifications contained in W3C Working Draft 25 October 2012.
Bug fix: the XSL stylesheets now add attribute
xml:lang
to element fo:root
when attribute
lang
or xml:lang
is set on the html
root element of the source document. Previously, these stylesheets added a
language
attribute to element fo:page-sequence
but
this language
attribute possibly contained a combination of a
language code and a country code (e.g. "en-US
"), which is
incorrect.
Updated xhtml5.xsd to reflect the specifications contained in W3C Working Draft 29 March 2012.
Bug fix: table attribute rules="all"
was
not correctly processed.
Bug fix: the align
attribute specified on
thead
, tfoot
, tbody
or
tr
was not inherited by td
.
First release. Xhtml5.xsd, the W3C XML Schema for XHTML 5 developed by XMLmind corresponds to W3C Working Draft 25 May 2011.


FlutterBeaconPlugin class
Properties
-
bluetoothStateStream
→ Stream<
BluetoothState> -
Streaming broadcasting every change of the BluetoothState.
final
-
monitoringStream
→ Stream<
MonitoringResult> -
See startMonitoring
final
- permissions → PermissionTools
-
Set of permission tools for required permissions to scan beacons.
See
PermissionTools
final -
rangingStream
→ Stream<
RangingResult> -
See startRanging
final
- hashCode → int
-
The hash code for this object. [...]
read-only, inherited
- runtimeType → Type
-
A representation of the runtime type of the object.
read-only, inherited
Methods
-
startMonitoring(
{List< Region> regions}) → Future< void> -
Starts monitoring the specified
regions
. Listen to monitoringStream for MonitoringResults -
startRanging(
{List< Region> regions}) → Future< void> -
Starts ranging the specified
regions
Listen to rangingStream for RangingResults -
noSuchMethod(
Invocation invocation ) → dynamic -
Invoked when a non-existent method or property is accessed. [...]
inherited
-
toString(
) → String -
Returns a string representation of this object.
inherited
Operators
-
operator ==(
dynamic other ) → bool -
The equality operator. [...]
inherited
Static Properties
- instance → FlutterBeaconPlugin
-
Instance of FlutterBeaconPlugin.
final


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Welcome, friend!
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Thank you for making an account on Glossier.com, where you can sign in and access your order history, update your info, and edit your settings in the
Account Section
of our site.
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| And if you ever have a question, concern, or want to share your thoughts, email us at
<EMAIL_ADDRESS>|
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5 New Street Square, London, EC4A 3TW
www.glossier.com
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<EMAIL_ADDRESS>|
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Pierre Thalamy received his M.Sc. degree in Computer Science with high honors from Grenoble Institute of Technology - Ensimag, France in 2017. He then received his Ph.D. in Computer Science from the University of Bourgogne Franche-Comté, in the Optimization, Mobility, NetworkIng (OMNI) team at the Department of Computer Science for Complex Systems (DISC) of Institut FEMTO-ST, France.
He worked under the supervision of Prof. Julien Bourgeois, and Dr. Benoît Piranda. His thesis is about the design of efficient 3-dimensional self-reconfiguration methods for building programmable matter using modular robotic systems. He is also involved in the Programmable Matter, CO2Dim, and Claytronics projects, and was the lead developer of the VisibleSim modular robotic simulator from 2015 to 2020. His research interests include self-reconfiguration and locomotion using modular robotics systems, multi-agent systems, emergent control, and distributed algorithms.
Within the context of the Programmable Matter project, he has improved upon existing methods of 3D modular robot self-reconfiguration by building upon successful pre-existing research ideas and proposing new original ones, making them faster and more parallel in order to bring programmable matter-based display systems closer to reality.


You can actually visit the official website to get the full functionality for this service:
All images, logos and trademarks belong to their respective owners. Contact me at amatsagkas at gmail dot com to get anything you don't like having over here removed. :)


Fuckin' security measures at Heathrow airport
February 24 2007, 11:57 AM
As you might imagine, this post is not going to be a charm.
Thanks to the new EU law, I just missed my connection and I have to wait for the next flight to Madrid. Fortunately, I just have to wait one hour.
But what if there wasn't any place available in that one?
How long will people accept any law for some obscure security reasons just like sheep?
How many planes have blown up because a passenger had liquid in his hand luggage?
How many planes have crashed because a passenger had hidden explosive in a white liquid in a baby milk mug?
But you can still take a plane with polium120 as long as you take less than 100ml.
Worst, I took the plane with 3 batteries within those two were defect and had a high risk of explosion!!! (see my post about my 3 batteries to know more about those).

It's just a lobbying to put pressure on people and to let them know that the terrorist threat is always present and that to have to let our parlements vote laws that restrict even more and more our freedom.
And by the way, it's also a very good law to hide an increase in the airport taxes. Since now you have to pay 2 euros if you are just a bit thirsty.
Duty free should be very happy of this.
2£ for one Coca-Cola... thank you!
I remember when that law was voted by the european parliament. I was in Madrid and I was terrified to see in the newspaper that in overall, people agreed. The main argument was "if it is for our security...". These people probably never entered an airport.

If you do not agree with me, watch out to avoid bringing any liquid if you want to jump in my car. Unless you show me the evidence it's more dangerous to have liquids in a plane than in a car. But I'm really not convinced.
(P.S: Don't worry, from now on I will always have bottles of water in my car for selling at 5 euros each, just in case you may be thirsty).


$scroll
dotjem.routing
The $scroll
service offers a number of enhancements over the current @anchorScroll
and serves for a direct replacement.
When called with no parameter like $scroll()
the call is re-routed to $anchorScroll
otherwise $scroll
performs the scrolling.
Scrolling to named elements is dependant on the jemAnchor
directive which will register elements to be targets for the $scroll
service. This is
to allow elements that is being loaded as part of a transition to also work as targets after $scroll
has been called.


Hi, I'm Kristian Kim, a product designer living in New York.
I'm passionate in designing applications that are funtional and beautiful. When I'm not designing (or occasionally coding), you will find me playing games, playing with my 2yo daughter or washing the dishes.
I'm currently working as full time at Life Coded crafting a productivity app called Mosaic.
Previously, I've worked on The 8 App, a social network app (desktop and mobile) for creators, and Digital Cookie, an official Girl Scout mobile app for cookie sales transaction.
To see more of my works, please head to my Dribbble page.
(My full portfolio site is in the work.)


Phoebe Sengers, Bill Gaver
Referenced by Liz regarding the Atkinsons work.
"New domains such as domestic and
public environments, new influences from the arts and
humanities, and new techniques in HCI itself are converging
to suggest that multiple, potentially competing interpretations
can fruitfully co-exist. In this paper, we lay out the contours
of the new space opened by a focus on multiple
interpretations, which may more fully address the
complexity, dynamics and interplay of user, system, and
designer interpretation."


“once again, work too late, try to squeeze in too much, end up awake way too late. the circle of derp.” (RT @inflammatoryrit)
“once again, work too late, try to squeeze in too much, end up awake way too late. the circle of derp.” (RT @inflammatoryrit)


In order for GitHub to send webhook payloads, your server needs to be accessible from the Internet. We also highly suggest using SSL so that we can send encrypted payloads over HTTPS.
For more best practices, see our guide.
GitHub will send along several HTTP headers to differentiate between event types and payload identifiers. See webhook headers for details.