---
layout: default
title: The People of the Osmonauts Group
---
Neuroscience Institute
New York University
After receiving my Ph.D. in Physics from Weizmann Institute of Science, I switched to Neurobiology. My adventure in olfactory processing started with discovering dramatic differences between olfactory bulb dynamics in awake and anesthetized mice (Rinberg-2006). The work of my lab in Janelia Farm (2006-2012) led to establishing temporal limits of behavior and neural processing in the sense of smell. I joined NYU Medical School in 2012.
Monell Chemical Senses Center, School of Medicine
University of Pennsylvania
A fundamental problem in neuroscience is mapping the physical properties of a stimulus to perceptual characteristics. In vision, wavelength translates into color; in audition, frequency translates into pitch. By contrast, the mapping from chemical structure to olfactory percept is unknown. In other words, there is not a scientist or perfumer in the world who can view a novel molecular structure and predict how it will smell. My research goal is to develop a predictive model relating molecular structure and olfactory perception using a combined psychophysical and molecular approach.
Department of Neuroscience
Brown University
My laboratory is interested in how neural circuits generate sensory perception and behavior. We use a combination of molecular genetic, in vivo imaging, computational and behavioral approaches to determine fundamental functional properties of neural networks in the mouse olfactory cortex. I have joined the Brown Neuroscience Department in January 2018.
School of Life Sciences
Arizona State University
I work on developing data-driven validation tests for neuroscience models, especially those at the level of neurons, synapses, and ion channels. I also contribute to several large open source computational neuroscience software projects. I also build statistical models of human and rodent olfaction.
Department of Neurobiolog
Harvard Medical School
The goal of our research is to address a core problem in neurobiology — how is the brain wired to extract information from the environment and convert that information into action? Our laboratory seeks to answer this question by studying the mammalian olfactory system, which affords most animals the ability to detect and appropriately respond to crucial environmental cues. The central hypothesis of our laboratory is that the neural circuits recruited by ethologically-relevant odors (such as those from food, predators and mates) are anatomically and genetically stereotyped; we leverage the invariance of this specific type of neural circuit to understand how odor inputs are detected in the sensory periphery, encoded by patterns of coordinated activity in the brain, and then decoded to generate meaningful patterns of action.
Department of Neurobiology
Duke University
Kevin first learned about the plasticity of ocular dominance columns as an undergraduate studying Biomedical Science and Philosophy and has been fascinated about how experience shapes perception ever since. His Ph.D. work, with Terry Sejnowski at UCSD, involved modeling synaptic transmission and postsynaptic calcium dynamics. As a postdoc, first with Jeffry Isaacson at UCSD and then with Richard Axel and Steve Siegelbaum at Columbia, Kevin functionally and anatomically characterized piriform cortex. circuitry. In spite of the constant ridicule, Kevin continues to enjoy an orange at exactly 5 o’clock every afternoon.
Cold Spring Harbor Laboratory
Alexei Koulakov and colleagues are trying to determine the mathematical rules by which the brain assembles itself, with particular focus on the formation of sensory circuits such as those involved in visual perception and olfaction. The visual system of the mouse was chosen for study in part because its components, in neuroanatomical terms, are well understood. What is not known is how projections are generated that lead from the eye through the thalamus and into the visual cortex, how an individual’s experience influences the configuration of the network, and what parameters for the process are set by genetic factors. Even less is known about the assembly of the neural net within the mouse olfactory system, which, in the end, enables the individual to distinguish one smell from another with astonishing specificity and to remember such distinctions over time. These are among the challenges that engage Koulakov and his team.
Center for Genetic Medicine | Chemistry of Life Processes Institute
Northwestern University
Molecular recognition underlies all biological processes. A fundamental question in biology is how systems, from individual proteins to organisms, recognize molecular structure. The vertebrate olfactory system is a remarkable molecular recognition device. Animals can detect odorous chemicals at extremely low concentrations, and can discriminate among an enormous number of structurally diverse molecules. The long-term goal of our work is to understand how the nervous system encodes molecular information, and how neural circuits give rise to learned and innate olfactory-driven behaviors.
Current Students
Graduate Student, Datta Lab
Harvard Medical School, Harvard University
Postdoctoral Fellow, Datta Lab
Harvard Medical School, Harvard University
Postdoctoral Fellow, Datta Lab
Harvard Medical School, Harvard University
Interdisciplinary Neuroscience PhD,
ICON Lab
Arizona State University
Large-Scale Modeling of the Olfactory System
NeuroML-DB: Online Database of NeuroML models
BlenderNEURON: Simulation Visualization Software
SwarmSight: Insect Antenna Tracking Software
Collaborator: Brian Smith
Graduate Student, The Franks Lab
Department of Neurobiology, Duke University
Robin is a Neurobiology student who joined the program in 2018. She graduated from Duke University in 2017
with degrees in Biology and Spanish.
Interdisciplinary Neuroscience PhD,
ICON Lab
Arizona State University
Reduced Neuron Model Validation
Graduate Student, The Franks Lab
Department of Neurobiology, Duke University
Shiva is a second-year graduate student in Neurobiology and is studying odor memory, specifically how odors
are accurately and reliably recognized across multiple exposures.
Technician, The Franks Lab
Department of Neurobiology, Duke University
Fernando is from Oaxaca, Mexico and received his undergraduate degree in Psychology from Universidad La
Salle in Mexico.
Research Technician, The Bozza Lab
Northwestern University
Research Technician, The Bozza Lab
Northwestern University
Graduate Student, Fleischmann Lab
Brown University
Graduate Student, Fleischmann Lab
Brown University
Research Assistant, Fleischmann Lab
Brown University
Software Engineer, Fleischmann Lab
Brown University
Postdoctoral Fellow
Monell Chemical Senses Center
Postdoctoral Fellow
Monell Chemical Senses Center
Computer Science Undergraduate Student, ICON Lab
Arizona State University
Statistics Undergraduate Student, ICON Lab
Arizona State University
Biological Sciences Undergraduate Student, ICON Lab
Arizona State University
Computer Science Undergraduate Student, ICON Lab
Arizona State University


A story about about Carloes Bedesus, an employee at Stop One Deli, and his perspective on the Lower East Side's changing enviroment. As new buildings pop up throughout the neighborhood, locals are being forced to leave as prices rise.
top One Deli is located on the corner of Suffolk and Rivington. It's one of four bodegas within a block radius.
As a family owned establishment, the Stop One Deli prides itself in providing locals with gourmet foods since 1982.
" Most of the customers that come in, the regular customers, they come here a lot because we give them good customer service," said Bedesus.
Above: Carlos working behind the deli counter.
Carlos Bedesus, 29, is a former taxi driver who now works behind the sandwich bar of the deli, listening to the radio. His hands are covered by opaque gloves for sandwich making. He wears black brimmed Dolce & Gabanna glasses, and diamond studs the size of macadamian nuts.
Bedesus has worked at the Stop One Deli for six months now, and seems to be right at home. Everyday he commutes from Staten Island to the Lower East Side for work.
"I used to be a taxi driver," Bedesus said. "I thought that was a cool experience but working here in the city is crazy."
Above: Is a map, courtesy of OpenMaps, that shows how far Carloes has to travel to and from work.
"It takes about 35-40 minutes because I drive," Bedesus said. "It usually takes longer in the day, but when I leave at night I get home pretty quickly."
As the Lower East side invites a number of new buildings into the area, the price of rent rises, pushing people out who can't afford it and attracting those who can.
Bedesus believes that the genetrification in the area has both positive and negative aspects to it.
The bad being the rising rent, and the good being it's bringing in smarter people, according to Bedesus.
"I think it's pretty good in some ways but in other ways it is kind of backwards," Bedesus said. "A lot of people are having to move from the area. It's getting so expensive they can't afford it. But at the same time it changes the way people used to see the Lower East Side."
On the other end of the spectrum is the manager Josefine Rodriguez. In an interview with NPR, she spoke about how she believes that with all of the new, the old is getting pushed out.
"We're Spanish people. We got to keep our culture and our things together," she says. "You can't just get rid of pepole just like that."


Update your personal account information.
Review your past seasons, win-loss records, most used players, favorite teams and more.


"AGRIPPA II". Son Of The Foregoing, Was Born At Rome, A.D. 27. He Was The Brother Of Bernice And Drusilla. The Emperor Claudius (A.D. 48) Invested Him With The Office Of Superintendent Of The Temple Of Jerusalem, And Made Him Governor (A.D. 50) Of Chalcis. He Was Afterwards Raised To The Rank Of King, And Made Governor Over The Tetrarchy Of Philip And Lysanias (Acts 25:13; 26:2, 7). It Was Before Him That Paul Delivered (A.D. 59) His Speech Recorded In Acts 26. His Private Life Was Very Profligate. He Died (The Last Of His Race) At Rome, At The Age Of About Seventy Years, A.D. 100.
"AGRIPPA II". Son Of The Foregoing, Was Born At Rome, A.D. 27. He Was The Brother Of Bernice And Drusilla. The Emperor Claudius (A.D.
48) Invested Him With The Office Of Superintendent Of The Temple Of Jerusalem, And Made Him Governor (A.D. 50) Of Chalcis. He Was Afterwards Raised To The Rank Of King, And Made Governor Over The Tetrarchy Of Philip And Lysanias (Acts 25:13; 26:2, 7). It Was Before Him That Paul Delivered (A.D. 59) His Speech Recorded In Acts 26. His Private Life Was Very Profligate. He Died (The Last Of His Race) At Rome, At The Age Of About Seventy Years, A.D. 100.


We are always on call to communicate with our existing and prospective clients. Please feel free to use the form below to contact us for any reason at all. A member of our team will respond promptly.


I just got the following crash in my Gecode/J program: java: /home/malcolmr/include/gecode/int/extensional/tuple-set.icc:88: bool Gecode::TupleSet::TupleSetI::finalized() const: Assertion `(excess == -1 && domsize >= 0) || (excess != -1 && domsize == -1)' failed. I'll look into it and see if I can reproduce it reliably. Malcolm


{% include "console/components/placeholders/table_placeholder.html" with
height='200px'
image='console/images/illustrations/outline/lab_inventory.svg'
message='No items were found for your active license.'
title='No Items Found'
url='/traceability/items/items?new=true'
only
%}


A suite of polyfills supporting the Web Components specs:
Custom Elements: allows authors to define their own custom tags (spec).
HTML Imports: a way to include and reuse HTML documents via other HTML documents (spec).
Shadow DOM: provides encapsulation by hiding DOM subtrees under shadow roots (spec).
This also folds in polyfills for MutationObserver
and WeakMap
.
Pre-built (concatenated & minified) versions of the polyfills are maintained in the tagged versions of this repo. There are two variants:
webcomponents.js
includes all of the polyfills.
webcomponents-lite.js
includes all polyfills except for shadow DOM.
Our polyfills are intended to work in the latest versions of evergreen browsers. See below for our complete browser support matrix:
| Polyfill | IE10 | IE11+ | Chrome* | Firefox* | Safari 7+* | Chrome Android* | Mobile Safari* |
|---|---|---|---|---|---|---|---|
| Custom Elements | ~ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| HTML Imports | ~ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| Shadow DOM | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| Templates | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
*Indicates the current version of the browser
~Indicates support may be flaky. If using Custom Elements or HTML Imports with Shadow DOM, you will get the non-flaky Mutation Observer polyfill that Shadow DOM includes.
The polyfills may work in older browsers, however require additional polyfills (such as classList) to be used. We cannot guarantee support for browsers outside of our compatibility matrix.
If you wish to build the polyfills yourself, you'll need node
and gulp
on your system:
npm
to install gulp.js: npm install -g gulp
Now you are ready to build the polyfills with:
# install dependencies
npm install
# build
gulp build
The builds will be placed into the dist/
directory.
See the contributing guide
Everything in this repository is BSD style license unless otherwise specified.
Copyright (c) 2015 The Polymer Authors. All rights reserved.
WebComponentsReady
Under native HTML Imports, <script>
tags in the main document block the loading of such imports. This is to ensure the imports have loaded and any registered elements in them have been upgraded.
The webcomponents.js and webcomponents-lite.js polyfills parse element definitions and handle their upgrade asynchronously. If prematurely fetching the element from the DOM before it has an opportunity to upgrade, you'll be working with an HTMLUnknownElement
.
For these situations (or when you need an approximate replacement for the Polymer 0.5 polymer-ready
behavior), you can use the WebComponentsReady
event as a signal before interacting with the element. The criteria for this event to fire is all Custom Elements with definitions registered by the time HTML Imports available at load time have loaded have upgraded.
window.addEventListener('WebComponentsReady', function(e) {
// imports are loaded and elements have been registered
console.log('Components are ready');
});
Under native Shadow DOM, CSS selectors cannot cross the shadow boundary. This means document level styles don't apply to shadow roots, and styles defined within a shadow root don't apply outside of that shadow root. Several selectors are provided to be able to deal with the shadow boundary.
The Shadow DOM polyfill can't prevent document styles from leaking into shadow roots. It can, however, encapsulate styles within shadow roots to some extent. This behavior isn't automatically emulated by the Shadow DOM polyfill, but it can be achieved by manually using the included ShadowCSS shim:
WebComponents.ShadowCSS.shimStyling( shadowRoot, scope );
... where shadowRoot
is the shadow root of a DOM element, and scope
is the name of the scope used to prefix the selectors. This removes all <style>
elements from the shadow root, rewrites it rules using the given scope and reinserts the style as a document level stylesheet. Note that the :host
and :host-context
pseudo classes are also rewritten.
For a full explanation on the implementation and both the possibilities and the limitations of ShadowCSS please view the documentation in the ShadowCSS source.
The Shadow DOM polyfill is implemented by wrapping DOM elements whenever possible. It does this by wrapping methods like document.querySelector
to return wrapped DOM elements. This has a few caveats:
document
, window
, document.body
, document.fullscreenElement
and others are non-configurable and thus cannot be overridden.HTMLElement.childNodes
and HTMLFormElement.elements
. All NodeLists are snapshotted upon read. See #217 for an explanation.In order to work around these limitations the polyfill provides the ShadowDOMPolyfill.wrap
and ShadowDOMPolyfill.unwrap
methods to respectively wrap and unwrap DOM elements manually.
See #215 for background.
In Safari and IE, instances of Custom Elements have a constructor
property of HTMLUnknownElementConstructor
and HTMLUnknownElement
, respectively. It's unsafe to rely on this property for checking element types.
It's worth noting that customElement.__proto__.__proto__.constructor
is HTMLElementPrototype
and that the prototype chain isn't modified by the polyfills(onto ElementPrototype
, etc.)
Using the MutationObserver polyfill, it isn't possible to monitor mutations of an element marked contenteditable
.
See the mailing list
See #16 for background.
Under the shadow DOM polyfill, rules like:
:host-context(.foo):host(.bar) {...}
don't work, despite working under native Shadow DOM. The solution is to use polyfill-next-selector
like:
polyfill-next-selector { content: '.foo :host.bar, :host.foo.bar'; }
ShadowCSS :host()
rules can only have (at most) 1-level of nested parentheses in its argument selector under ShadowCSS. For example, :host(.zot)
and :host(.zot:not(.bar))
both work, but :host(.zot:not(.bar:nth-child(2)))
does not.
In native HTML Imports, document.currentScript.ownerDocument references the import document itself. In the polyfill use document._currentScript.ownerDocument (note the underscore).
See #212
execCommand
, and contenteditable
aren't supported under the ShadowDOM polyfill, with commands that insert or remove nodes being especially prone to failure.


注解
部分文章需要科学上网
http://sijinjoseph.com/programmer-competency-matrix/
https://github.com/bannedbook/fanqiang/wiki
https://fanqiang.software-download.name/
https://shan333.cn/2018/10/07/Proxy/
Standard C++
cppreference
https://blog.csdn.net/haoel/article/details/2886
https://blog.csdn.net/haoel/article/details/2887
https://blog.csdn.net/haoel/article/details/2888
https://blog.csdn.net/haoel/article/details/2889
https://blog.csdn.net/haoel/article/details/2890
https://blog.csdn.net/haoel/article/details/2891
https://blog.csdn.net/haoel/article/details/2892
https://blog.csdn.net/haoel/article/details/2893
https://blog.csdn.net/haoel/article/details/2894
https://blog.csdn.net/haoel/article/details/2895
https://blog.csdn.net/haoel/article/details/2896
https://blog.csdn.net/haoel/article/details/2897
https://blog.csdn.net/haoel/article/details/2898
https://blog.csdn.net/haoel/article/details/2899
https://blog.csdn.net/u014044812/article/details/80723009
https://blog.csdn.net/u014044812/article/details/80782448
https://blog.csdn.net/u014044812/article/details/80866759
7 steps to become a UI/UX designer
团队中的Git实践
A successful Git branching model
使用 git rebase 避免無謂的 merge
Git: 教你如何在Commit时有话可说
关于模运算的思考


Equations are formatted in plain text as: x^2+3x-5 which results in: x^2+3x-5
To render symbols such as theta simply type the name, in this case: theta


%# LuCI - Lua Configuration Interface (c) 2009 Daniel Dickinson Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 $Id$ -%> <%+header%>
<%:l_v_d_di_voicediag1%>
<%:l_v_d_di_voicediag2%>
<%+footer%>


Michaela's Pizzeria
Create a custom pizza that will be "ready" in seconds!
Sizes:
Small
10"
$8.00
Large
14"
$14.00
Extra Large
16"
$17.00
Toppings:
Cheese
($.75 each)
Mozzarella
Parmesan
Cheddar
Meat
($1.50 each)
Pepperoni
Bacon
Salami
Vegetables
($1.00 each)
Artichokes
Black Olives
Fresh Basil
Mushrooms
Pineapple
Sun-dried Tomatoes
Calculate Price
Price:
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Messageformat editor
Github project
Enable linting
The syntax highlighter is able to handle plain strings, escaped characters \{ \# \u1234, wrongly escaped characters \u12z1 \u123 \ } and it recovers from errors. It highlights multiple consecutive space characters, tabs and trailing space An interpolated {VAR} variable A missing {} variable name A trailing comma {VAR,} after the variable name SelectFormat: {VAR, select, a {a} =0 {equal sign in keys is not allowed for selects} {missing key} x {and the syntax highlighter recovers} } PluralFormat: {NUM, plural, one {a} two {b} =10 {10} some {another string} other {x} } selectordinal {NUM, selectordinal, other {x} =10 {10} } user defined functions: {NOW, date} and {NOW, date, full} The linter marks PluralFormats and SelectFormats without "other" key: {VAR, select, male {He} female {She} } and it marks duplicate keys. nesting: {PERSON_CNT, select, unknown {an unknown number of persons} other {{PERSON_CNT, plural, =0 {no one} =0 {noone} =2 {two persons} one {one person} =2 {2 persons} other {# persons} }} }


--- layout: profile ---
I’m a reality tv editor turned programmer. I just wrapped up my training at Flatiron School and I’m excited to combine my new software engineering skills with my years of experience interfacing with clients, piecing together puzzles, and clarifying chaos to build technology that will help real people simplify the chaos of their own lives.
For some people, technology is a lifestyle. But for me, it’s functional. It’s useful. It’s about lessening my mental load or remembering something for some unknown time in the future. It’s about removing or simplifying boring, frustrating, or unwanted tasks from my life to give me with more free time to do something I actually enjoy...spending with my family, going for a run, working on a hobby. I love development because it allows me to create or improve on something that is a helping hand which in turn saves people time and frustration -- making lives a little lighter than they otherwise would have been.
Visit my blog for to learn more about me and my coding journey.Ruby | JavaScript | React | Redux | Rails | Sinatra | JSON | SQL | HTML | CSS
A React app with a Ruby on Rails API backend that allows you to learn about the current real estate market to inform your home buying/selling/investing experience using the Zillow API.
Wrangle your yarn stash to keep your crafty projects organized and under control with this Ruby on Rails app with a JavaScript front end.
Explore spells from the Harry Potter universe, as scraped from the Harry Potter Wiki, with this Ruby CLI.


The Game A review by David Wilcock (C)1997 David Wilcock
Starring Michael Douglas and Sean Penn Directed By David Fincher A Polygram Pictures Release
Following the dark and disturbing Seven, David Fincher brings us this dark and disturbing comedy about a man driven to the edge over a dumb game. The man is Nicolas Van Orten, (or Gorden Gekko) played by Douglas, who is invited to play a game by his slightly mad brother, played by Penn. Douglas, bizzarely, accepts, and his life is turned upside down. While for Douglas, the game is a scary experience, for the audience, it's all a bit silly. One of the problems with this film is that it inserts far too many twists into the tale, some of them making no sense at all. Whenever the film feels like it, it will put a twist in. This is fine for some movies, but in The Game, it frankly gets really dumb. Also, the ending can't hold up to explain why there are all these twists!
 I've seen this bad endings (like Halloweens) but this one's is really pathetic. After having releative fun (I just ignored the twists after a while) the ending just spoiled the whole thing. Tragic.
So, what are the high points? Well, the film is reasonably good fun (if a bit overlong) and it is bound to keep you entertained until the last ten minutes. Douglas gives us a fine performance (even though he had already played the same character in Oliver Stones Wall Street) and Penn is good as the brother. Douglas's 'girlfriend' during the film is alright, and the supporting cast are all OK as well. The direction is adequete, if occasionaly a little dull, but it never reaches the dizzy heights of Seven. Fincher has given us a film that is a little better than Alien 3 (although I quite enjoyed that movie) but nowhere near as good as Seven.  Which is a shame.
Overall Rating=**1/2 out of ***** (Silly, and with a poor ending, yet quite enjoyable. Overlong, though, aswell.)
Review By David Wilcock
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


This country's Founding Fathers such as Benjamin Franklin and Thomas Jefferson intended for the United States Of America to become a place with “life, liberty, and the pursuit of happiness” for every citizen and resident of this nation, while establishing a foundation for freedom and equal opportunity for all, regardless of their race, religion, gender, and sex.
According to an NPR article titled, “Why America’s Schools Have A Money Problem,” in 2013, the Chicago Ridge School District in Chicago spent $9,794 per child, while a school in Chicago’s affluent northern suburbs, Rondout School, spent $28,639 on each of its 145 students and 22 teachers. Urban schools such as those part of the Chicago Ridge School District suffer from diminishing resources such as teachers and classrooms, simply due to the fact that they cannot afford those extra things, whereas, in suburban schools such as Rondout School, every student has an “individualized learning plan” and also have teachers that are extremely qualified with “a decade of experience.”
Dr. Linda Lemasters, an associate professor at George Washington University, in her article, “Disparities Between Urban and Suburban Schools,” emphasizes the consequences of the funding disparities in urban schools when mentioning that they are prone to “inferior facilities, less adequate teachers, and an incomparable curriculum” (qtd in Wright) when compared to suburban schools with adequate funding (EFC.org). Due to studies like these and their findings, many Americans find the urban students culpable for their shortcomings, however they are unable to see that the failures of the students are the unfortunate consequences of an underdeveloped and underfunded educational system.
Since almost 30% of urban students are likely to be living in poverty than a mere 13% of suburban students, according to a study conducted by the National Center for Education Statistics, urban students were more likely to attend schools with higher concentrations of low income students. Due to the the fact that a majority of urban high school students seem to come from imperfect households, student morale and expectations such as doing homework and participating in after school activities start diminishing, ultimately hindering the growth that the students could demonstrate if they had access to the the right resources and environment.
Other than raising awareness to frequent racial stereotyping and providing teens of color with a platform to share and comprehend such experiences, it is also our goal to provide those underpriveleged teens of Chicago's urban, underdevloped public schools with the resources and support that priveleged, suburban students have always had access to.
Pursing a Higher Education
College
The first step to pursuing a higher education is finding a passion that can transform into a successful career. Take this personality quiz to find your prospective careers. The second step in this process is to find a major that aligns with your chosen career. Once you've chosen a career and a major, it is time for the third step where you find a university that is perfect for you in terms of the size, teacher to student ratio, tuition, location, etc.
While trying to find the right unversity, here are some tips to follow and red flags to avoid during the college application process from the college admissions counselors themselves.
The College Board is an excellent resource to refer to in order to find a way to pay for the college tuition, which is the last and final step to pursuing a higher education.
Community College
If you are one who is not interseted in going to a four or two year university, attending a community college is an excellent, and less expensive alternative to obtaining a degree, and then purusing a successful career. Once you have identified your passions, your career, and your major, the last step is to find a community college near you.


Lascaux is a free tool for printing customized, high resolution maps. To get started, select a paper size, output format, map style and then pan and zoom the map to the area you want to print. You can increase the size of the covered area by zooming out the print resolution.
When you're done click Download map to get your printable map!


rec_room.recommenders package¶
Subpackages¶
Module contents¶
-
class
rec_room.recommenders.
BaseRS
(args, path)¶ Bases:
abc.ABC
Base class for all Recommender Systems
All Recommender Systems integrated into the Recommender Room must inherit from the BaseRS class to ensure the appropriate methods and properties are defined. The Rec Room will call the methods or use the properties at runtime.
-
abstract property
dataset
¶ return the dataset and labels
-
abstract property
model
¶ return the trained model
-
abstract
recommend
(args)¶ make a recommendation
-
abstract
render
()¶ return HTML
-
abstract
visualize
(args)¶ return config options for chart.js
-
abstract property
-
class
rec_room.recommenders.
USCollegesRS
(rs_args: Dict[str, str] = None, rs_dir: str = None)¶ Bases:
rec_room.recommenders._base.BaseRS
The US Colleges Recommender System.
This RS outputs a university recommendation based on 3 criteria: gpa, gpa, and rank. A Nearest Neighbor model was trained to output university recommendations. The data used by this RS was obtained from:
- Parameters
rs_args (Dict) – User specified arguments for preferences or constraints
rs_dir (Str) – Directory to where the RS is located.
-
model
¶ The trained model that has been loaded.
- Type
sklearn.linear_model.NearestNeighbor
-
labels
¶ The labels used by the model
- Type
DataFrame
-
template
¶ The filepath to the HTML that will populate the Parameters section in the Recommender page
- Type
str
-
viz
¶ The filepath to the JavaScript options that will be used to parameterize the chart.js library in the Recommender page
- Type
str
-
requires
¶ Metadata required to be captured in the Recommender page in order to make a recommendation
- Type
Dict
-
dtypes
¶ Specifies the appropriate data type for the evaluation criteria used by the RS
- Type
Dict
-
META
= {'dataset': 'us_colleges.csv', 'labels': 'us_colleges_labels.sav', 'model': 'us_colleges_model.sav', 'path': 'us_colleges_rs', 'template': 'us_colleges_render.html', 'visualize': 'us_colleges_results.yaml'}¶
-
property
dataset
¶ Return the US Colleges dataset.
-
property
labels
Return the saved labels used by the Recommender System
-
property
model
Return the saved model used by the Recommender System.
The US COlleges RS uses a Nearest Neighbor model from the scikit-learn libary with the following parameters:
- NearestNeighbors(algorithm=’auto’, leaf_size=30, metric=’minkowski’,
metric_params=None, n_jobs=None, n_neighbors=161, p=2, radius=1.0)
-
recommend
(args: Dict[str, str] = None) → Dict[str, str]¶ Make a Recommendation for US Colleges.
This function calls the pre-trained self.model and self.labels to make the best prediction, or recommendation, for the provided instance arguments.
- Parameters
args (Dict) – User specified arguments for preferences or constraints
- Returns
recs – The recommendation results
- Return type
Dict
-
render
() → str¶ Return the HTML to be rendered.
The HTML will be populated in the Parameters component of the Recommender page.
- Returns
html – HTML text to be rendered by the browser
- Return type
str
-
visualize
(data: List[Dict]) → Dict[str, Dict]¶ Return the formatted options Dict for the chart.js library.
- Parameters
data (list) – The arguments specified by the user to be formatted for plotting
- Returns
js – The arguments that will be used to create the chart/plot on the Results section of the Recommender page.
- Return type
dict
-
class
rec_room.recommenders.
OMSCoursesRS
(rs_args: Dict[str, str] = None, rs_dir: str = None)¶ Bases:
rec_room.recommenders._base.BaseRS
The OMS Courses Recommender System.
This RS outputs course recommendations based on 3 criteria: rating, difficulty, and workload. A Logistc Regression classifier was trained to output course recommendations. The data used by this RS was obtained from:
www.omscentral.com
- Parameters
rs_args (Dict) – User specified arguments for preferences or constraints
rs_dir (Str) – Directory to where the RS is located.
-
model
¶ The trained model that has been loaded.
- Type
sklearn.linear_model.LogisticRegression
-
labels
¶ The labels used by the model
- Type
sklearn.preprocessing.LabelEncoder
-
template
¶ The filepath to the HTML that will populate the Parameters section in the Recommender page
- Type
str
-
viz
¶ The filepath to the JavaScript options that will be used to parameterize the chart.js library in the Recommender page
- Type
str
-
stats
¶ Relevant statistical data from the RS’s dataset
- Type
DataFrame
-
requires
¶ Metadata required to be captured in the Recommender page in order to make a recommendation
- Type
Dict
-
dtypes
¶ Specifies the appropriate data type for the evaluation criteria used by the RS
- Type
Dict
-
META
= {'dataset': 'oms_courses.csv', 'labels': 'oms_courses_labels.sav', 'model': 'oms_courses_model.sav', 'path': 'oms_courses_rs', 'template': 'oms_courses_render.html', 'visualize': 'oms_courses_results.yaml'}¶
-
property
dataset
¶ Return the OMS Courses dataset.
-
property
labels
Return the saved labels used by the Recommender System
-
property
model
Return the saved model used by the Recommender System.
The OMS Course RS uses a logistic regression classifier from the scikit-learn library with the following parameters:
- LogisticRegression(C=1.0, class_weight=None, dual=False,
fit_intercept=True, intercept_scaling=1, l1_ratio=None, max_iter=5000, multi_class=’auto’, n_jobs=None, penalty=’l2’, random_state=0, solver=’saga’, tol=0.0001, verbose=0, warm_start=False)
-
recommend
(args: Dict[str, str] = None) → Dict[str, str]¶ Make a Recommendation for OMS Courses.
This function calls the pre-trained self.model and self.labels to make the best prediction, or recommendation, for the provided instance arguments.
- Parameters
args (Dict) – User specified arguments for preferences or constraints
- Returns
recs – The recommendation results
- Return type
Dict
-
render
() → str¶ Return the HTML to be rendered.
The HTML will be populated in the Parameters component of the Recommender page.
- Returns
html – HTML text to be rendered by the browser
- Return type
str
-
visualize
(data: List[Dict]) → Dict[str, Dict]¶ Return the formatted options Dict for the chart.js library.
- Parameters
data (list) – The arguments specified by the user to be formatted for plotting
- Returns
js – The arguments that will be used to create the chart/plot on the Results section of the Recommender page.
- Return type
dict


parent works!
Sharing Data via ViewChild (Child to Parent): {{msgFromChild}}
Sharing Data via Output() and EventEmitter (Child to Parent): {{msgFromChild2}}


--- layout: default title: Download subtitle: Download Go Server and Go Agent for Free ---
You need to download both the server and the agent in order to use Go.
If you need help downloading, installing or using Go please join the Go Users Google Group. ThoughtWorks also provides commercial help for Go. They can be reached at<EMAIL_ADDRESS>|
Operating System
Go supports following OS
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Revisions
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public class TimeStampResponseGenerator
extends java.lang.Object
New generate methods have been introduced to give people more control over what ends up in the message. Unfortunately it turns out that in some cases fields like statusString must be left out otherwise a an otherwise valid timestamp will be rejected.
If you're after the most control with generating a response use:TimeStampResponse tsResp; try { tsResp = tsRespGen.generateGrantedResponse(request, new BigInteger("23"), new Date()); } catch (Exception e) { tsResp = tsRespGen.generateRejectedResponse(e); }The generate method does this, but provides a status string of "Operation Okay".
It should be pointed out that generateRejectedResponse() may also, on very rare occasions throw a TSPException. In the event that happens, there's a serious internal problem with your responder.
| Constructor and Description |
|---|
TimeStampResponseGenerator(TimeStampTokenGenerator tokenGenerator,
java.util.Set acceptedAlgorithms) |
TimeStampResponseGenerator(TimeStampTokenGenerator tokenGenerator,
java.util.Set acceptedAlgorithms,
java.util.Set acceptedPolicies) |
TimeStampResponseGenerator(TimeStampTokenGenerator tokenGenerator,
java.util.Set acceptedAlgorithms,
java.util.Set acceptedPolicies,
java.util.Set acceptedExtensions) |
| Modifier and Type | Method and Description |
|---|---|
TimeStampResponse |
generate(TimeStampRequest request,
java.math.BigInteger serialNumber,
java.util.Date genTime)
Return an appropriate TimeStampResponse.
|
TimeStampResponse |
generateFailResponse(int status,
int failInfoField,
java.lang.String statusString)
Generate a non-granted TimeStampResponse with chosen status and FailInfoField.
|
TimeStampResponse |
generateGrantedResponse(TimeStampRequest request,
java.math.BigInteger serialNumber,
java.util.Date genTime)
Return a granted response, if the passed in request passes validation.
|
TimeStampResponse |
generateGrantedResponse(TimeStampRequest request,
java.math.BigInteger serialNumber,
java.util.Date genTime,
java.lang.String statusString)
Return a granted response, if the passed in request passes validation with the passed in status string.
|
TimeStampResponse |
generateRejectedResponse(java.lang.Exception exception)
Generate a generic rejection response based on a TSPValidationException or
an Exception.
|
public TimeStampResponseGenerator(TimeStampTokenGenerator tokenGenerator, java.util.Set acceptedAlgorithms)
tokenGenerator
- acceptedAlgorithms
- a set of OIDs giving accepted algorithms.public TimeStampResponseGenerator(TimeStampTokenGenerator tokenGenerator, java.util.Set acceptedAlgorithms, java.util.Set acceptedPolicies)
tokenGenerator
- acceptedAlgorithms
- a set of OIDs giving accepted algorithms.acceptedPolicies
- if non-null a set of policies OIDs we are willing to sign under.public TimeStampResponseGenerator(TimeStampTokenGenerator tokenGenerator, java.util.Set acceptedAlgorithms, java.util.Set acceptedPolicies, java.util.Set acceptedExtensions)
tokenGenerator
- acceptedAlgorithms
- a set of OIDs giving accepted algorithms.acceptedPolicies
- if non-null a set of policies OIDs we are willing to sign under.acceptedExtensions
- if non-null a set of extensions OIDs we are willing to accept.public TimeStampResponse generate(TimeStampRequest request, java.math.BigInteger serialNumber, java.util.Date genTime) throws TSPException
If genTime is null a timeNotAvailable error response will be returned. Calling generate() is the equivalent of:
TimeStampResponse tsResp; try { tsResp = tsRespGen.generateGrantedResponse(request, serialNumber, genTime, "Operation Okay"); } catch (Exception e) { tsResp = tsRespGen.generateRejectedResponse(e); }
request
- the request this response is for.serialNumber
- serial number for the response token.genTime
- generation time for the response token.TSPException
public TimeStampResponse generateGrantedResponse(TimeStampRequest request, java.math.BigInteger serialNumber, java.util.Date genTime) throws TSPException
If genTime is null a timeNotAvailable or a validation exception occurs a TSPValidationException will be thrown. The parent TSPException will only occur on some sort of system failure.
request
- the request this response is for.serialNumber
- serial number for the response token.genTime
- generation time for the response token.TSPException
- on validation exception or internal error.public TimeStampResponse generateGrantedResponse(TimeStampRequest request, java.math.BigInteger serialNumber, java.util.Date genTime, java.lang.String statusString) throws TSPException
If genTime is null a timeNotAvailable or a validation exception occurs a TSPValidationException will be thrown. The parent TSPException will only occur on some sort of system failure.
request
- the request this response is for.serialNumber
- serial number for the response token.genTime
- generation time for the response token.TSPException
- on validation exception or internal error.public TimeStampResponse generateRejectedResponse(java.lang.Exception exception) throws TSPException
exception
- the exception thrown on validating the request.TSPException
- if a failure response cannot be generated.public TimeStampResponse generateFailResponse(int status, int failInfoField, java.lang.String statusString) throws TSPException
status
- the PKIStatus to set.failInfoField
- the FailInfoField to set.statusString
- an optional string describing the failure.TSPException
- in case the response could not be created


History of Tweets
This study spans over a period of roughly 4 months, more specially from July 13th 2016 to November 10th 2016. This repesents the period from one month after the presidential primaries and caucuses to 2 days after the Election Day.
During this period, more than
1,000,000 tweets have been collected, cleaned, filtered, sorted, and otherwise processed. Of particular importance,
6,444 tweets have been collected from the candidates themselves and
199,456 tweets from the election day itself.
The
top 10 hashtags are extracted from this data, and is represented in the streamgraph below.
This streamgraph above attest to how (much) each of the top 10 hashtags change over time - including highlights for each of the
3 presidential debates. It is particularly interesting how Donald Trump has managed to maintain a strong and constant adaptation of the hastag and slogan
#MAGA (
Make
America
Great
Again) throughout the entire election period - this is in strong contrast to Hillary Clinton, whose campaign slogan
#ImWithHer has a fairly lower representation throughout. Moreover, 5 out of 10 hashtags are related to the Trump campaign, whereas only 3 is for the Clinton campaign. The remaining 2 hashtags are #Election16, and the anti-Trump hashtag #NeverTrump. However, the cumulative representation for the Trump campaign is much stronger during the entire election period. The empty period from August 16 to August 28 is due to missing data.
A Wordcloud representation for all the tweets originating from either Trump or Hillary is seen below. This illustration can be interpreted as which words defined the discourse during the election for each candidate:
From these wordclouds, it is clear that Clinton attempts to appeal to her followers'
pathos, using words like
family, country and
people, as well as focusing on
women. Trump has chosen a different approach, focusing on
jobs, personal attacks with
crooked (from #crookedHillary), as well as
thanking a lot of people.
The wordsclouds provides only part of the whole picture. From these tweets, a
sentiment analysis has been conducted on the candidates' tweets. This essentially shows how positively or negatively loaded their tweets have been throughout the election period. The following Calendar View shows the sentiment (or 'tone') on each day for each candidate. The mismatch between the two calendars is due to when each candidate started using Twitter:
It is interesting to see how the most positive of days for Clinton is when she receives endorsements from e.g. Barack Obama (POTUS) or Michelle Obama (FLOTUS). The rest of the days, her tone has been fairly evened out by both positive and negative tweets.
Clinton's calendar view is in stark contrast to Trump's, which shows much more variation. This is in part because of the many harsh personal attacks on Clinton, scare-tactics, and a lot of positivity, appreciation and 'thanks' for others.
Twitter Landscape
This election has exhibited the lowest voter turnout in almost 20 years
[1]. This is reflected in how many tweets originated from each state, indicating which states cared most about the election enough to tweet about it. This is illustrated in the US state map visualization below:
It can be seen that the normalized percentages never exceeds 5%. More interestingly,
only 2 swing states, Nevada & Florida, made an - albeit very small - effort to express themselves on Twitter during this election. This is surprising, given how swing states typically determine the election.
It is also worth noting that the
west coast, east coast, and southern border states have the strongest showing. This is consistent with some of the discourse found in the tweets, e.g. the topic of
immigration. These coast and border states takes in most immigrants
[2], which could prompt these states to address this online. Immigration and foreign policy is one of the biggest topics this election
[3].
Such correlations between states and topics will be further explored in the next section.
Candidates v. Voters
These visualizations have culminated in the correlation between candidates, voters, and topics. This section will explore which topics were most important to each state and candidate and their influence on the election. The top topics during the election has been put up against the states and candidates in the following parallel coordinates:
The parallel coordinate at the top illustrates which issues were most important for the voters in each state, while the bottom parallel coordinate illustrate how much the candidates addressed these issues. These parallel coordinates can be filtered based on political party affiliation. It is worth noting that the Swing States are more aligned with the Republicans than with Democrats, however this might fall within the margin of error.
Interestingly, Clinton's spread of tweets are more consistent with the voters' than Trump is. This follows the trend of Trump's general discourse, which tends to be more 'aggressive' than the norm on certain issues. For instance, Trump rates higher on immigration than both Clinton and the voters.
These diagrams show that the
Economy played a far bigger role on Twitter than the rest of the issues. It is followed by
Taxes, with
Immigration, Education, and
Corruption being close seconds for the voters. For Clinton, the top issues were
Economy, Taxes, and Education. Unsurprisingly, Trump's top issues are
Economy and
Immigration.
With the results of the election known, and based on these diagrams, an argument can be made that it is not simply enough for the candidates to align themselves with the voters tweets (populism), as is evident with Clinton. Rather, it is important to cut through the noise and outspeak the norm on key issues.


Trading
Firms
Resources
Economy Overview
Legacy View
Trade:
Firms:
Inventory:
Economy Overview
Tick:
| Firms:
| Activity:
| Trying to Expand:
| Season:
Prices:
Total Resources:
Total Firms:
Econ Sim
Pause
Tick
Esc
for pause,
T
for tick.
Tick:
| Firms:
| Activity:
| Trying to Expand:
| Season:


--- layout: default title: Management description: Management and bookink ---
{{ post.content | strip_html | truncatewords:25}}


8MM (1999) Reviewed by Eugene Novikov http://www.ultimate-movie.com/ Member: Online Film Critics Society
***1/2 out of four
Starring Nicholas Cage, Joaquin Phoenix, Michael Stormare. Rated R.
Director Joel Schumacher must be a very hated man. He is, after all, responsible for single-handedly destroying the whole Batman franchise with the embarrassing Batman & Robin. Is it fair, for Batman fans everywhere, to say that Schumacher redeems himself with 8MM? Well, perhaps not. And I suppose there is no form of redemption for making an awful movie; that'll stay with you forever. But in its own right, the new Nicolas Cage thriller 8MM is an excellent film.
The ordinary-man-suddenly-thrown-into-oblivion story has been told over and over, both by excellent films (Enemy of the State, A Simple Plan, The Man Who Knew Too Much) and not-so-excellent ones (In Dreams, etc.). And, I suppose, 8MM is another of these films, but instead of it being the whole movie, it uses that general storyline framework as a set-up for bigger and better things.  So, it is rather surprising to him when he is called in by the wife of a recently deceased millionare. It seems that she has found a film in her husband's safe that seems to depict a girl being brutally raped and murdered. Welles' mission, which he chooses to accept, is to find out whether that girl was really killed in that film.
He tackles the problem head-on by going to Cleveland and by visiting a part of that city known as an adult entertainment heaven. He enlists the help of an intelligent but destitute porn store clerk, Max, to acquaint him with the dark world of hard-core pornography.  For the uninitiated (God, I hope there are many of you out there), a "snuff" film is an unproffesionally made porno where one of the stars is beaten and killed.
>From a technical perspective, this is a fine achievement. Filmed in bleak, dark tones, 8MM is a beautifully moody picture, even if it doesn't present any original concept in cinematography (and it didn't have to, either). The movie's general style resembles that of last year's A Perfect Murder in camerawork, lighting and tone.
As Welles submerges himself in this insane world, he begins to wrestle with murderous instincts. But he is not a killer. At one point, in a very powerful scene, he has to call a family member of one of the victims to literally talk him into killing one of the villains.
Schumacher tries to touch on many philosophical concepts in 8MM. Some work, some don't, but his movie is really notable for many very suspenseful scenes, compelling action, and for building up a steady rhythm that really draws the audience in. Cage gives a none-too-subtle but still riveting performance as Welles, but his performance gets is quite overstated if you watch closely.
8MM is quite graphic in terms of depiction of these "snuff" films, but it manages not to stray into NC-17 category. Still, I would guess that many people would find much of this film disturbing, and some might even think of it as repulsive. But try and look beyond the violence. Welles' reaction to everything he sees is quite real. The villains' motives as depicted here are rather thought-provoking. When you really look, 8MM is quite a restrained, even timid picture when you think about what it could have been. Had it been an "exploitation" movie, much like the porn that it's about, my reaction would have certainly been different.
Nor is this a preachy "porn is bad" movie, as a matter of fact 8MM does not seem to be too concerned with porn. It seems to be trying to get a message through our heads that has to do with criminality in general. The notion that all criminals have a troubled past is what Schumacher seems to be trying to disprove ("I do these things because I want to. Because I like them"). Like last year's Enemy of the State, 8MM uses action and violence for something other than simply displaying action and violence.
This is Schumacher's breakthrough film, his first good one since Falling Down. It's a comlpex achievement; exciting, sad and profound at the same time. It's also one of the year's first pleasant surprises. ©1999 Eugene Novikov
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rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
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欢迎来到feather docs的文档！¶
- Feathers
- 指南
- API
- Feathers v3（秃鹰）
- Quick upgrade
- Updating client side applications
@feathersjs
npm scope- Documentation changes
- Framework independent
- Hooks in core
- Event channels and publishing
- Better separation of client and server side modules
- Node 6+
- A new Socket message format
- Deprecations and other API changes
- Backwards compatibility polyfills
- Feathers 安全
- 生态系统
- 救命！
- 常问问题
- What Node versions does Feathers support
- How do I create custom methods?
- How do I do nested or custom routes?
- Can you support another database?
- I am not getting real-time events
- How do I do search?
- Why am I not getting JSON errors?
- Why am I not getting the correct HTTP error code
- How can I do custom methods like
findOrCreate
? - Why are you using JWT for sessions
- How do I render templates?
- OAuth is not setting the cookie
- How do I create channels or rooms
- How do I do validation?
- How do I do associations?
- Sequelize models and associations
- What about Koa/Hapi/X?
- How do I access the request object in hooks or services?
- How do I mount sub apps?
- How do I do some processing after sending the response to the user?
- How do I debug my app
possible EventEmitter memory leak detected
warning- Why can’t I pass
params
from the client? - My queries with null values aren’t working
- Why are queries with arrays failing?
- I always get a 404 for my custom middleware
- How do I get OAuth working across different domains
- My configuration isn’t loaded
- How do I set up HTTPS?
- Is Feathers production ready?
- 特约
- 有许可证
- github
- 摘要


ITV Debate Live: UK leaders go head-to-head in TV debate
by Ross J Burland- The UK leaders, Corbyn and Johnson, go head to head in ITV live debate.
- GBP/USD falling back ahead of the vent on likely profit-taking.
Live from Salford in Greater Manchester, Boris Johnson and Jeremy Corbyn go head to head in their first TV debate.
The UK leaders will set out how they would break the political deadlock and heal a divided nation. The debate will be moderated by Julie Etchingham. Each leader will have one minute each for their opening statements and 45 seconds for closing statements in front of the live studio...
Additional information:
This will be the first of many debates in the lead up to the general election next month.
Sky News is proposing Nov 28 for their debate. The BBC also confirmed that they will also be holding two debates scheduled for Nov 29 and Dec 6. There will also be a series of Question Time specials.
Here are the times and dates of the events to watch out for:
- Johnson v Corbyn: The ITV Debate, Tuesday Nov 19 - 8pm (ITV).
- Sky News general election debate, Thursday Nov 28, TBC (Sky News).
- The BBC Election Debate, Friday Nov 29, TBC (BBC).
- The BBC Prime Ministerial Debate, Friday Dec 6, TBC (BBC).
Prior to today's debate, and following the announcement from ITV, Mr Corbyn was vocal on the matter and said on Twitter:
"This is a once in a generation election. So it's welcome that Boris Johnson has accepted our challenge of a head-to-head TV debate...The choice could not be clearer: Boris Johnson's Conservatives protecting the privileged few or a Labour government on the side of the many."
Watch live:
Immediately after the debate, stay watching for a special programme with reaction and analysis of the head-to-head.
Key notes:
- The great Brexit gamble – Rabobank
- GBP/USD: Firm around 4-week high, ignores Brexit news amid UK’s political optimism
- EU trade boss tells UK PM he will get ‘bare bones’ Brexit trade deal or none at all - The Sun
FX implications:
With respect to the pound, considering the lack of liquidity, there could be some movement depending n what is said and how much of the debate is related to Brexit. However, as analysts at TD Securities explained, "Leaders' debates are rarely decisive events, but in such an unpredictable general election, we'll be watching extra closely for any potential turning points." GBP/USD had ben as high as 1.2970 on the day but has given back some ground to the lowest point in the lead into the event down to 1.2910, likely on profit-taking – GBP/JPY is down to test the 200-hour moving average, (Yen is a safe haven and GBP/JPY can be a big mover).


Pushing, Publishing, and Viewing a Database¶
Pushing a database is the process of making a Google Earth Enterprise Fusion database available on a Google Earth Enterprise Server so that it can then be published for viewing with Google Earth EC.
The push operation copies all the necessary files associated with a given 2D/3D Fusion database version to Google Earth Enterprise Server and registers the database. Pushing is performed from Fusion.
The publish operation makes a previously pushed database available for serving at a specified publish point. Publishing is performed on Google Earth Enterprise Server.
Note
This lesson assumes that Google Earth Enterprise Fusion, the Google Earth Enterprise Server, and Google Earth EC are all installed on your local workstation. If any of these applications are installed elsewhere on your network, adjust the instructions in this lesson accordingly.
Note
This lesson describes the steps for pushing a 3D Fusion database. The same workflow is used to push a 2D Mercator database, but note that snippet profiles do not apply and that the published map can be viewed in a web browser, not Google Earth EC. See Creating a Map Database for more information.
Push Your Database to Google Earth Enterprise Server
After you define and build your database, you “push” your database to Google Earth Enterprise Server. Pushed databases appear on the Databases page of the Google Earth Enterprise Server Admin console, from which you can then publish them.
To push a database:
Select Asset Manager from the Tools menu. The Asset Manager appears.
Navigate to the SFHighways database you built in Defining and Building Databases.
Right-click the name of the database, and select Push from the context menu.
The Push Database dialog appears. The default server association is the only option on the Server Associations drop-down list. The most recent version of the selected database is the default selection on the Version drop-down list.
Click the Push button. Google Earth Enterprise Fusion pushes the database to Google Earth Enterprise Server, and displays a success message when it is done.
Note
If you get an error message, contact your Google Earth Enterprise Server administrator for help, or check the documentation on Before you Configure Google Earth Enterprise Fusion for more information.
Publish Your Database in Google Earth Enterprise Server
After you push your database to Google Earth Enterprise Server, you can publish it for viewing with Google Earth EC.
To publish a database:
Access the Google Earth Enterprise Server Admin console in a browser window by going to myserver.mydomainname.com/admin, replacing myserver and mydomainname with your server and domain.
Sign in with the default credentials or the username and password assigned to you:
- Default username: geapacheuser
- Default password:geeadmin
Note
If you do not know your username and password, contact your Google Earth Enterprise Server System Administrator.
Click Databases to display the list of databases pushed to the Server.
SFHighways-v001 is listed. The Description, Type, Date, and Size of the database are also noted.
Check the box next to SFHighways-v001. The Publish button on the Databases page appears.
Click Publish. The Publish dialog appears.
Change the default Publish point from SFHighways-v001 to BayAreaHighways.
Note
You can publish a database to multiple publish points, useful when you want to apply different search tabs, snippet profiles, and virtual host settings for different viewing needs.
Note
When publishing a database, the publish point you specify is case-insensitive. Upper and lower case are not differentiated. Make sure each publish point path name you specify is unique.
To learn more about the options available in the Publish dialog, see
Click the Publish button. The Databases page updates to indicate the published status of your database.
View Your Database
After you publish your database, you can view it in Google Earth EC. Google Earth EC can be downloaded from here.
To view your database:
Launch Google Earth EC.
The Login dialog appears.
Specify the Publish point by entering or selecting the URL or IP address of your server and database in the Server field. For this tutorial, the Publish point is myserver.mydomainname.com/BayAreaHighways, where myserver and mydomainname are specific to your server. An example URL would be http://myhostname/BayAreaHighways.
Click the Sign In button.
Double-click CAHighways to zoom in to your road data.
This concludes the basic lessons in this tutorial. If you want to continue with the advanced lessons, you can work through them in any order you like. Alternatively, you can start working with real data now and come back and work through the advanced lessons as you need them.


--- layout: post authors: ["Greg Wilson"] title: "Checking the Balance" date: 2016-02-16 time: "07:00:00" tags: ["Community"] ---
Added 2016-02-22: this strong critique of the Terrell et al preprint mentioned in the opening paragraph of this post is worth a careful read.
It's been a depressing couple of weeks. On top of yet more reports of universities turning a blind eye to sexual harassment for years, a new paper of gender bias in open source shows that, "...women's contributions tend to be accepted more often than men's. However, when a woman's gender is identifiable, they are rejected more often." This comes on top of earlier studies (like this one) showing that women are substantially under-represented in online forums like Stack Overflow, even when compared to computing as a whole.
This prompted me to take another look at how Software Carpentry is doing. To start, here are the number and percentage of qualified Software Carpentry instructors broken down by gender:
| Qualified Instructors by Gender | ||||
|---|---|---|---|---|
| Female | Male | Other | Unknown | |
| Number | 136 | 355 | 3 | 26 |
| %age | 26.2% | 68.3% | 0.6% | 5.0% |
Let's compare that to the number of people contributing to our core lesson repositories in January 2016 by gender. (I'd like to show number for a whole year, but my script won't fetch stuff from that far back.)
| Repository Contributors by Gender | ||||
|---|---|---|---|---|
| Female | Male | Other | Unknown | |
| Number | 19 | 79 | - | 14 |
| %age | 17.0% | 70.5% | - | 12.5% |
17% female is better than average for GitHub and Stack Overflow, but still pretty poor. The proportion is even worse when we count number of contributions rather than number of contributors:
| Repository Contributions by Gender | ||||
|---|---|---|---|---|
| Female | Male | Other | Unknown | |
| Number | 69 | 532 | - | 28 |
| %age | 11.0% | 84.6% | - | 4.5% |
This allows us to calculate contributions per person:
| Repository Contributions per Person by Gender | ||||
|---|---|---|---|---|
| Female | Male | Other | Unknown | |
| Number | 3.6 | 6.7 | 2 | - |
But now let's compare this to the stats for Software Carpentry's core mission: delivering workshops. Our next table shows the number of people who taught workshops in 2015:
| Workshop Instructors by Gender | ||||
|---|---|---|---|---|
| Female | Male | Other | Unknown | |
| Number | 89 | 193 | 121 | 3 |
| %age | 21.9% | 47.5% | 29.8% | 0.7% |
while this one shows the actual number of workshops taught (e.g., if I taught three times, I count as three points in the male column):
| Workshops Taught by Gender | ||||
|---|---|---|---|---|
| Female | Male | Other | Unknown | |
| Number | 182 | 406 | 163 | 4 |
| %age | 24.1% | 53.8% | 21.6% | 0.5% |
and this one shows the average number of workshops taught by each instructor:
| Repository Contributions per Person by Gender | ||||
|---|---|---|---|---|
| Female | Male | Other | Unknown | |
| Number | 2.0 | 2.1 | 1.3 | 1.3 |
Finally, here's the breakdown of contributors to our discussion mailing list for the three months Nov 2015 - Jan 2016:
| Email Contributors by Gender | ||||
|---|---|---|---|---|
| Female | Male | Other | Unknown | |
| Number | 22 | 95 | - | - |
| %age | 18.8% | 81.2% | - | - |
of messages sent:
| Email Messages by Gender | ||||
|---|---|---|---|---|
| Female | Male | Other | Unknown | |
| Number | 73 | 277 | - | - |
| %age | 20.9% | 79.1% | - | - |
and of messages per person:
| Email Messages per Person by Gender | ||||
|---|---|---|---|---|
| Female | Male | Other | Unknown | |
| Number | 3.3 | 2.9 | - | - |
I draw some comfort from the fact that our online balance isn't dramatically different from our in-person balance, and that both are much better than GitHub's or Stack Overflow's (though it would be hard for us to do worse), It's still clear, though, that women and other people who do not identify as male are under-represented both online and in person. What's worse is that as we grow, we're regressing to computing's unbalanced mean: over a third of our instructors were women in the summer of 2013. While I worry about the number of people who complete instructor training but never teach for us, I worry a lot more about that, and if we're going to try to fix something this year, that's what I'd like it to be.


This package contains the platform-independent base classes and helper classes for the layout managers provided by the JGUIraffe library.
The most important class in this package is PercentLayoutBase
which implements the basic functionality of the percent layout layout
manager. Percent layout organizes components in a tabular structure.
For each cell of the table properties like the initial size, the alignment, or
a weight factor can be defined. The weight factor controls how additional space
that becomes available if the user resizes the window is assigned to the cells
comprising the layout. The properties of a cell are specified by an instance of
CellConstraints
.
The PercentLayout
class is the platform-independent implementation
of percent layout. Based on the same concepts there are some other
platform-independent layout manager implementations:
BorderLayout
provides the same functionality as the AWT layout
manager with the same name with some slight enhancements.ButtonLayout
is specialized on layouting the command buttons of
a dialog (e.g. a bar at the bottom of the dialog containing buttons like
Save, Cancel, or Help. All buttons have the same size
and space between them.The term platform-independent in this context means that the layout manager classes defined in this package implement the basic layouting algorithms, but they do not adhere to special layout manager interfaces. Other packages provide concrete sub classes of these classes that can be used in specific GUI toolkits, e.g. Swing.
$Id: package.html 205 2012-01-29 18:29:57Z oheger $


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Welcome to the Code With Friends, Spring 2020 Project Fair! Take a look at everyone else's projects on what they worked on and learned this month! Vote on your favorite projects here!


- Ness
- Forms
- FileUpload
- Forms
You can include this library to your code file by typing the below code;
use Ness\Forms\FileUpload
File Upload Class
Uploading files with Ness PHP framework is extremely easy. You can upload your files with a single
line.
UploadFile()
This function is the main function of class, used to upload the file
$var_name->UploadFile(string $file_uploader_form_element_name) : bool
$file_uploader_form_element_name: [IMPORTANT] Please enter the 'name' of attribute on your view / fileupload control.
OnlyImages()
This is a security function, you can set it true accept only image formats.
$var_name->OnlyImages(TRUE | FALSE) : $this
MaxFileSize()
This is a security function, you can set a max value for file size in bytes. By default alllowd upload size is: 50000 bytes
$var_name->MaxFileSize(int $MAX_ALLOWED_FILESIZE) : $this
setDirectory()
This function is used to set the folder name for your uploads. Your folder must be placed in 'application' folder.
$var_name->setDirectory(string $folder_Name) : $this
getDirectory()
This function is used to return the folder path.
$var_name->getDirectory() : String
getName()
This function is used to return the uploaded file name. This is useful when you need to store the name in database.
$var_name->getName() : String
AllowedExtensions()
This function is used to set allowed extension for your file uploads.
$var_name->AllowedExtensions(Array $extension_list) : $this
getErrors()
This function is used to return errors occurred in file upload
$var_name->getError() : Array
Example
First of all we need to create a view for our form, please add new item in application/view folder. uploadView.php
PHP:
use Ness\Forms\Form;
use Ness\Forms\FormElements;
$fileUpload = new Form("test");
.
..
...
....
echo $fileUpload->DefineForm(array("method"=>"post", "enctype"=>"multipart/form-data"));
$fileUpload->setModel("testModel");
echo $fileUpload->setElement(FormElements::Label("File", "mydata"));
echo $fileUpload->setElement(FormElements::FileUpload("mydata"));
echo $fileUpload->setElement(FormElements::Submit("test"));
$fileUpload->Call("upload");
In theese code lines we have defined that; we have a testModel.php file in Model folder and a upload() function in it. Now, we need to create the Model/testModel.php and code it to look like this:
PHP:
use Ness\Forms\FileUpload;
class testModel
{
public function upload()
{
$tryupload = new FileUpload("test");
if($tryupload->setDirectory("uploads")->OnlyImages(true)->UploadFile("mydata"))
{
echo "FILE UPLOADED SUCCESSFULLY";
}else{
var_dump($tryupload->getErrors());
}
}
}
thats all.


CommercialCreditCardResponse_CCC
- CCCMarketingState : List
The marketing state (promotional or regular) of the CCC Product.
- Identification : String
The unique ID that has been internally assigned by the financial institution to each of the Commercial Credit Card products they market to their retail and/or small to medium enterprise (SME) customers.
- Name : String
The name of the CCC product used for marketing purposes from a customer perspective. I.e. what the customer would recognise.
- Segment : List
Market segmentation is a marketing term referring to the aggregating of prospective buyers into groups, or segments, that have common needs and respond similarly to a marketing action. Market segmentation enables companies to target different categories of consumers who perceive the full value of certain products and services differently from one another. Read more: Market Segmentation http://www.investopedia.com/terms/m/marketsegmentation.asp#ixzz4gfEEalTd Follow us: Investopedia on Facebook With respect to CCC products, they are segmented in relation to different markets that they wish to focus on.
- Enum:


{% extends "horizon/common/_modal_form.html" %} {% load i18n %} {% block modal-header %}
{% trans "Scan the QRCode with yout mobile authentication device (Google Authenticator is fine) and the verify the TOTP token." %}
{% trans "Once the token has been verified, TOTP Two Factor Authentication will be enabled for your user." %}
{% endblock %}


--- layout: base title: ryan bonick :: plants permalink: /plants.html categories: plants ---
Plants are wonderful.
They're so green (except when they're not supposed to be!) and lush.
Enjoy these photos of my plants.


Card 1
Card 2
Card 3
Card 4
Card 5
Card 6
Card 7
Card 8
Article 1
Article Description
Article 2
Article 3


Test 1 checks if all the bytes we ask for actually get allocated.
Test 2 checks if malloc gracefully handles failing requests. This test assumes that malloc will eventually fail if one keeps allocating enough memory, instead of promising memory it can't deliver and then (perhaps) killing processes when it runs out. More detail regarding this condition can be found in comments in the source code.
Test 3 also checks if malloc gracefully handles failing requests, and thus has the same restrictions as test 2.
Test 4 attempts to check if malloc coalesces the free list properly. This test is only meant for first-fit, next-fit, or best-fit allocators; anything else will most likely confuse it. Running test 4 after other tests may confuse it as well.
Tests 5-7 are a randomized stress test. Test 5 uses pseudorandom seed 0. Test 6 seeds the random generator from the random: device. Test 7 prompts you for a specific seed.
Your system should pass all the malloctest tests, subject to the conditions described above, once your user-level malloc is complete.


pip_services3_components.connect package¶
Submodules¶
Module contents¶
pip_services3_components.connect.__init__¶
Contains implementation of connection parameters, using various connection strings, which are stripped of all credentials. If we need to configure a service, the port, ip address, protocol, and other parameters – we use the ConnectionParams object, and relevant helper classes (like ConnectionResolver), for acquiring these parameters, and for discovery of objects, components (which store and retrieve connection parameters).
### Discovery ###
Service that store a registry of various end-points (what services are where, and how to connect to them). It knows the end-points, but doesn’t have the credentials to connect to them. Separated for security reasons. IDiscovery – interface for creating registries. MemoryDiscovery – registry that is stored in memory.
- There exist 2 types of discovery:
- Static discovery:
- all services have static IP addresses (like DNS, which also works using static discovery) that are configured from the start and don’t change along the way. As of lately, used more often than dynamic, because it is simpler to use and more reliable.
- Proxy (or reverse proxy) is created with a dns name, and all the dynamics of starting/restarting/switching from one host to another – everything is nice and clear for the clients. Infrastructure does all the hard work out of the box.
- Configure sets the static registry.
- Dynamic discovery:
- every time a service starts, it registers its address in the discovery service (“Service name” at the following address “IP”). Clients then ask to resolve the address by which the requested service can be reached. The service has a general name, by which other services can resolve it.
- If a service stops working, you need to refresh its address, clean stale addresses, heartbeats must be used – lots of problems and challenges. One service can have more than one address.
- Static discovery:
| copyright: | Conceptual Vision Consulting LLC 2018-2019, see AUTHORS for more details. |
|---|---|
| license: | MIT, see LICENSE for more details. |
-
class
pip_services3_components.connect.
ConnectionParams
(map=None)¶ Bases:
pip_services3_commons.config.ConfigParams.ConfigParams
Contains connection parameters to connect to external services.
They are used together with credential parameters, but usually stored separately from more protected sensitive values.
### Configuration parameters ###
- discovery_key: key to retrieve parameters from discovery service
- protocol: connection protocol like http, https, tcp, udp
- host: host name or IP address
- port: port number
- uri: resource URI or connection string with all parameters in it
In addition to standard parameters ConnectionParams may contain any number of custom parameters
- Example:
- connection = ConnectionParams.from_tuples(“protocol”, “http”,
“host”, “<IP_ADDRESS>”,
“port”, “8080”,
“cluster”, “mycluster”)
- host = connection.get_host() // Result: “<IP_ADDRESS>”
- port = connection.get_port() // Result: 8080
- cluster = connection.get_as_nullable_string(“cluster”) // Result: “mycluster”
-
static
from_config
(config)¶ Retrieves a single ConnectionParams from configuration parameters from “connection” section. If “connections” section is present instead, then is returns only the first connection element.
Parameters: config – ConnectionParams, containing a section named “connection(s)”. Returns: the generated ConnectionParams object.
-
static
from_string
(line)¶ Creates a new ConnectionParams object filled with key-value pairs serialized as a string.
Parameters: line – a string with serialized key-value pairs as “key1=value1;key2=value2;…” Example: “Key1=123;Key2=ABC;Key3=2016-09-16T00:00:00.00Z” Returns: a new ConnectionParams object.
-
static
from_tuples
(*tuples)¶ Creates a new ConnectionParams object filled with provided key-value pairs called tuples. Tuples parameters contain a sequence of key1, value1, key2, value2, … pairs.
Parameters: tuples – the tuples to fill a new ConnectionParams object. Returns: a new ConnectionParams object.
-
get_discovery_key
()¶ Gets the key to retrieve this connection from DiscoveryService. If this key is null, than all parameters are already present.
Returns: the discovery key to retrieve connection.
-
get_host
()¶ Gets the host name or IP address.
Returns: the host name or IP address.
-
get_port
()¶ Gets the port number.
Returns: the port number.
-
get_protocol
(default_value=None)¶ Gets the connection protocol.
Parameters: default_value – (optional) the default protocol Returns: the connection protocol or the default value if it’s not set.
-
get_uri
()¶ Gets the resource URI or connection string. Usually it includes all connection parameters in it.
Returns: the resource URI or connection string.
-
static
many_from_config
(config)¶ Retrieves all ConnectionParams from configuration parameters from “connections” section. If “connection” section is present instead, than it returns a list with only one ConnectionParams.
Parameters: config – a configuration parameters to retrieve connections Returns: a list of retrieved ConnectionParams
-
set_discovery_key
(value)¶ Sets the key to retrieve these parameters from DiscoveryService.
Parameters: value – a new key to retrieve connection.
-
set_host
(value)¶ Sets the host name or IP address.
Parameters: value – a new host name or IP address.
-
set_port
(value)¶ Sets the port number.
Parameters: value – a new port number.
-
set_protocol
(value)¶ Sets the connection protocol.
Parameters: value – a new connection protocol.
-
set_uri
(value)¶ Sets the resource URI or connection string.
Parameters: value – a new resource URI or connection string.
-
use_discovery
()¶ Checks if these connection parameters shall be retrieved from DiscoveryService. The connection parameters are redirected to DiscoveryService when discovery_key parameter is set.
Returns: true if connection shall be retrieved from DiscoveryService
-
class
pip_services3_components.connect.
IDiscovery
¶ Bases:
object
Interface for discovery services which are used to store and resolve connection parameters to connect to external services.
-
register
(correlation_id, key, connection)¶ Registers connection parameters into the discovery service.
Parameters: - correlation_id – (optional) transaction id to trace execution through call chain.
- key – a key to uniquely identify the connection parameters.
- connection – a connection to be registered.
-
resolve_all
(correlation_id, key)¶ Resolves all connection parameters by their key.
Parameters: - correlation_id – (optional) transaction id to trace execution through call chain.
- key – a key to uniquely identify the connections.
Returns: a list with resolved connections.
-
resolve_one
(correlation_id, key)¶ Resolves a single connection parameters by its key.
Parameters: - correlation_id – (optional) transaction id to trace execution through call chain.
- key – a key to uniquely identify the connection.
Returns: a resolved connection.
-
-
class
pip_services3_components.connect.
ConnectionResolver
(config=None, references=None)¶ Bases:
pip_services3_commons.config.IConfigurable.IConfigurable
,pip_services3_commons.refer.IReferenceable.IReferenceable
Helper class to retrieve component connections.
If connections are configured to be retrieved from IDiscovery, it automatically locates IDiscovery in component references and retrieve connections from there using discovery_key parameter.
### Configuration parameters ###
- connection:
- discovery_key: (optional) a key to retrieve the connection from IDiscovery
- … other connection parameters
- connections: alternative to connection
- [connection params 1]: first connection parameters
- … connection parameters for key 1
- [connection params N]: Nth connection parameters
- … connection parameters for key N
- ### References ###
- :discovery::*:1.0 (optional) IDiscovery services to resolve connections
- Example:
- config = ConfigParams.from_tuples(“connection.host”, “<IP_ADDRESS>”, “connection.port”, 8080)
- connectionResolver = ConnectionResolver()
- connectionResolver.configure(config)
- connectionResolver.setReferences(references)
- connectionResolver.resolve(“123”)
- connectionResolver = ConnectionResolver()
-
add
(connection)¶ Adds a new connection to component connections
Parameters: connection – new connection parameters to be added
-
configure
(config)¶ Configures component by passing configuration parameters.
Parameters: config – configuration parameters to be set.
-
get_all
()¶ Gets all connections configured in component configuration. Redirect to Discovery services is not done at this point. If you need fully fleshed connection use resolve method instead.
Returns: a list with connection parameters
-
register
(correlation_id, connection)¶ Registers the given connection in all referenced discovery services. This method can be used for dynamic service discovery.
Parameters: - correlation_id – (optional) transaction id to trace execution through call chain.
- connection – a connection to register.
-
resolve
(correlation_id)¶ Resolves a single component connection. If connections are configured to be retrieved from Discovery service it finds a IDiscovery and resolves the connection there.
Parameters: correlation_id – (optional) transaction id to trace execution through call chain. Returns: resolved connection parameters or null if nothing was found.
-
resolve_all
(correlation_id)¶ Resolves all component connection. If connections are configured to be retrieved from Discovery service it finds a IDiscovery and resolves the connection there.
Parameters: correlation_id – (optional) transaction id to trace execution through call chain. Returns: a list of resolved connections.
-
set_references
(references)¶ Sets references to dependent components.
Parameters: references – references to locate the component dependencies.
-
class
pip_services3_components.connect.
MemoryDiscovery
(config=None)¶ Bases:
pip_services3_components.connect.IDiscovery.IDiscovery
,pip_services3_commons.config.IReconfigurable.IReconfigurable
Discovery service that keeps connections in memory.
### Configuration parameters ###
- [connection key 1]:
- … connection parameters for key 1
- [connection key 2]:
- … connection parameters for key N
- Example:
- config = ConfigParams.from_tuples(
“key1.host”, “<IP_ADDRESS>”,
“key1.port”, “8080”,
“key2.host”, “<IP_ADDRESS>”,
“key2.port”, “8082”)- discovery = MemoryDiscovery()
- discovery.read_connections(config)
- discovery.resolve(“123”, “key1”)
- discovery = MemoryDiscovery()
-
configure
(config)¶ Configures component by passing configuration parameters.
Parameters: config – configuration parameters to be set.
-
read_connections
(connections)¶ Reads connections from configuration parameters. Each section represents an individual Connectionparams
Parameters: connections – configuration parameters to be read
-
register
(correlation_id, key, connection)¶ Registers connection parameters into the discovery service.
Parameters: - correlation_id – (optional) transaction id to trace execution through call chain.
- key – a key to uniquely identify the connection parameters.
- connection – a connection to be registered.
-
resolve_all
(correlationId, key)¶ Resolves all connection parameters by their key.
Parameters: - correlation_id – (optional) transaction id to trace execution through call chain.
- key – a key to uniquely identify the connections.
Returns: a list with resolved connections.
-
resolve_one
(correlation_id, key)¶ Resolves a single connection parameters by its key.
Parameters: - correlation_id – (optional) transaction id to trace execution through call chain.
- key – a key to uniquely identify the connection.
Returns: a resolved connection.
-
class
pip_services3_components.connect.
DefaultDiscoveryFactory
¶ Bases:
pip_services3_components.build.Factory.Factory
Creates IDiscovery components by their descriptors.