Mexican official says Mexico has granted asylum to Bolivian ex-president Evo Morales
by EndPlayMEXICO CITY - MEXICO CITY (AP) - Mexican official says Mexico has granted asylum to Bolivian ex-president Evo Morales .
MEXICO CITY - MEXICO CITY (AP) - Mexican official says Mexico has granted asylum to Bolivian ex-president Evo Morales .


Drawing Profile
Overview
The Profile tool can display the cross-section of pixel intensity values (the "Profile")
along any line (baseline) across an image. When the profile dialog box is open, POW is in
the "profile" mode. In this mode, the user can create, move, rotate, and stretch the
baseline with the mouse, and the corresponding "Profile" plot is displayed in the separate
panel. The coordinates of the starting and stopping points of the profile are also displayed
in the dialog box.
Creating profile
The Baseline can be drawn on the image by placing the mouse at the desired starting
location and click-and-drag with the right mouse button held down to the end location.
When the mouse button is released, a "profile" plot will appear in the separate panel.
Manipulating profile
The position of the current profile can be manipulated using the mouse by grabbing
and moving either of the end point handles, or the baseline itself.
To rotate and stretch the baseline, position the mouse over the endpoint you want to move.
Press either mouse button, drag it to the desired new position, and release it. The
profile plot will be updated.
To move the whole baseline, position the mouse over any part of the baseline except two
ends. Press the left mouse button, drag it to the new position, and release it. The
profile plot will be updated.
Saving profile
By clicking the "Record" button on the dialog box, one can save the coordinates of
the profile plot to an ASCII text file. The data in the saved file contains 4 elements
per line: the X and Y graph coordinates of each point, the Pixel Index number (starting
with 1), and the intensity value of the image at that position.


module File:sig
..end
typet =
Useri.Drop.file
val path : Useri.Drop.file -> string
path f
is f
's file system path.val prepare : Useri.Drop.file ->
(Useri.Drop.file -> [ `Error of string | `Ok of unit ] -> unit) -> unit
prepare f k
prepares files f
for reading, calling k f r
whenever
f
is ready to be read from (e.g. with Pervasives.open_in
).
This is mainly used to hide the upload of the file in
js_of_ocaml
's pseudo file system (e.g. on the
`Tsdl
backend it will immediately call k
). If you need more
control over the upload process you should access the JavaScript file
object directly with Useri_jsoo.Drop.File.to_js
.


(html (head "\n (script Asrc /foo.js " )script "\n (script Asrc /foo.js " )script "\n )head (body )body )html


|
Komodo Engine
C PROJECT_LOGO=
|
Manages all the underlying graphics resources and devices. More...
Public Member Functions | |||
| GraphicsManager (Game game) | |||
| |||
| void | ApplyChanges () | ||
| Applies pending changes to the Microsoft.Xna.Framework.GraphicsDeviceManager. More... | |||
| void | Clear (Color clearColor) | ||
| Clears the screen with a given Microsoft.Xna.Framework.Color. More... | |||
| Texture | CreateTexture (Color[] data, int width, int height) | ||
| Creates a new Komodo.Core.Engine.Graphics.Texture from raw Microsoft.Xna.Framework.Color data and dimensions. More... | |||
| Texture | CreateTexture (Color[,] data) | ||
| Creates a new Komodo.Core.Engine.Graphics.Texture from raw Microsoft.Xna.Framework.Color data. More... | |||
| void | Initialize () | ||
| Called after all framework resources have been initialized and allocated. More... | |||
| void | SetFullscreen (bool isFullscreen, bool shouldApplyChanges=true) | ||
| Sets the game window to render either in fullscreen or windowed mode. More... | |||
| void | SetResolution (Resolution resolution, bool shouldApplyChanges=true) | ||
| Sets the game window resolution. More... | |||
| void | ToggleFullscreen (bool shouldApplyChanges=true) | ||
| Toggles whether or not the game window renders in fullscreen or windowed mode More... | |||
Public Attributes | |
| Viewport | ViewPort => GraphicsDeviceManager.GraphicsDevice.Viewport |
| Current Microsoft.Xna.Framework.Graphics.Viewport for the Microsoft.Xna.Framework.Graphics.GraphicsDevice. More... | |
Properties | |
| Game | Game [get] |
| Reference to current Komodo.Core.Game instance. More... | |
| bool? | IsMouseVisible [get, set] |
| Whether or not to show the mouse in the game window. More... | |
| List< Resolution >??? | Resolutions [get] |
| Supported resolutions for the current graphics device. More... | |
| GraphicsDeviceManager | GraphicsDeviceManager [get] |
| Underlying Microsoft.Xna.Framework.GraphicsDeviceManager, providing access to the underlying Microsoft.Xna.Framework.Graphics.GraphicsDevice. More... | |
| SpriteBatch | SpriteBatch [get, set] |
| Current Microsoft.Xna.Framework.Graphics.SpriteBatch for the underlying Microsoft.Xna.Framework.Graphics.GraphicsDevice. More... | |
| bool | VSync [get, set] |
| Whether or not to render using vertical sync. More... | |
Manages all the underlying graphics resources and devices.
| void Komodo.Core.Engine.Graphics.GraphicsManager.ApplyChanges | ( | ) |
Applies pending changes to the Microsoft.Xna.Framework.GraphicsDeviceManager.
| void Komodo.Core.Engine.Graphics.GraphicsManager.Clear | ( | Color | clearColor | ) |
Clears the screen with a given Microsoft.Xna.Framework.Color.
| clearColor | Microsoft.Xna.Framework.Color to clear the Microsoft.Xna.Framework.Graphics.GraphicsDevice with. |
| Texture Komodo.Core.Engine.Graphics.GraphicsManager.CreateTexture | ( | Color | data[,] | ) |
Creates a new Komodo.Core.Engine.Graphics.Texture from raw Microsoft.Xna.Framework.Color data.
| data | 2D array of Microsoft.Xna.Framework.Color. |
| Texture Komodo.Core.Engine.Graphics.GraphicsManager.CreateTexture | ( | Color[] | data, |
| int | width, | ||
| int | height | ||
| ) |
Creates a new Komodo.Core.Engine.Graphics.Texture from raw Microsoft.Xna.Framework.Color data and dimensions.
| data | 1D array of Microsoft.Xna.Framework.Color. |
| width | Width of the Komodo.Core.Engine.Graphics.Texture to generate. |
| height | Height of the Komodo.Core.Engine.Graphics.Texture to generate. |
| void Komodo.Core.Engine.Graphics.GraphicsManager.Initialize | ( | ) |
Called after all framework resources have been initialized and allocated.
Before Initialize is called, MonoGame will not have set up the Microsoft.Xna.Framework.Graphics.GraphicsDevice yet, preventing Komodo.Core.Engine.Graphics.Texture or Komodo.Core.Engine.Graphics.Model from being generated.
| void Komodo.Core.Engine.Graphics.GraphicsManager.SetFullscreen | ( | bool | isFullscreen, |
| bool | shouldApplyChanges = true |
||
| ) |
Sets the game window to render either in fullscreen or windowed mode.
| isFullscreen | Whether or not to render in fullscreen. |
| shouldApplyChanges | Whether or not to apply the graphics changes immediately. |
| void Komodo.Core.Engine.Graphics.GraphicsManager.SetResolution | ( | Resolution | resolution, |
| bool | shouldApplyChanges = true |
||
| ) |
Sets the game window resolution.
| resolution | New resolution to display. |
| shouldApplyChanges | Whether or not to apply the graphics changes immediately. |
| void Komodo.Core.Engine.Graphics.GraphicsManager.ToggleFullscreen | ( | bool | shouldApplyChanges = true | ) |
Toggles whether or not the game window renders in fullscreen or windowed mode
| shouldApplyChanges | Whether or not to apply the graphics changes immediately. |
| Viewport Komodo.Core.Engine.Graphics.GraphicsManager.ViewPort => GraphicsDeviceManager.GraphicsDevice.Viewport |
Current Microsoft.Xna.Framework.Graphics.Viewport for the Microsoft.Xna.Framework.Graphics.GraphicsDevice.
|
get |
Reference to current Komodo.Core.Game instance.
|
get |
Underlying Microsoft.Xna.Framework.GraphicsDeviceManager, providing access to the underlying Microsoft.Xna.Framework.Graphics.GraphicsDevice.
|
getset |
Whether or not to show the mouse in the game window.
|
get |
Supported resolutions for the current graphics device.
|
getset |
Current Microsoft.Xna.Framework.Graphics.SpriteBatch for the underlying Microsoft.Xna.Framework.Graphics.GraphicsDevice.
|
getset |
Whether or not to render using vertical sync.


{% extends "base.html" %} {% block title %} Signup {% endblock title %} {% block content %}
Sign up
{{ field.label_tag }}
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or sign up with:
By clicking Sign up you agree to our terms of service and terms of service.


genes expression cells infection OpenUrl gene type virus response MHV Figure up-regulated epithelial viruses respiratory compared CrossRef host responses IFN changes change human induced significantly viral infection. mouse cell different mock number mice murine Abstract genes, FREE Text MHV- altered fold influenza shared infected used differences disease viruses. vs. PR, down-regulated using RVB time Science cells. line rhinovirus Web airway alveolar immune signature significant susceptible (slope IFN-induced IFNs RV, Virol effects genes. infections involved log lung severe signaling uniquely values IFN-related hepatitis model receptor timing unique Gene Type Venn analysis functional identified microarray numbers occur point replication shown strain transcription MHV, Mouse S). antiviral coronavirus data included induces interferon larger mediated mock-inoculated strains studies up-regulation viruses, -fold Dr. Genes Interferome cellular differential differentially expressed followed including induction levels mice. mock, pathogenesis primary similar study treatment up- virus. vitro (Table ;<;div A). A/J Cell Download Hershenson, However, Immunol MHC Open RNA RV. Virus Wang, acute class compare constant data-hide-link-title=""> data-icon-position="" database defense degradation detected diagram diverse early figure function generated induce inflammatory known large level mRNA new observed pathways pattern processing proportion rate resistant responses. resulted rhinovirus-induced set shows small tab tract (a) (b) Biol Differential Johnston, Lee, MHV. Miura, Nagarkar, Respir Rhinovirus Sajjan, Signature Smith, University Virology Weiss, additional asthma cells, confidence contrast, contribute experimental factors family groups highly hypothesis identify indicated largest log<;sub>;<;/sub>; maps mechanisms medium models names obtained pathology proteins represented right role row severity specific subtypes tissue transcriptional upregulated vivo


{% extends 'layouts/base-fullscreen.html' %} {% block title %} Login {% endblock title %} {% block stylesheets %}{% endblock stylesheets %} {% block content %}
Your username and password didn't match. Please try again.
{% else %}Iniciar Sesion
{% endif%}


Loading...
How to play: Use your arrow keys or swipe to move the tiles. When two tiles with the same shoe touch, they merge into one to create another pair of chic shoes!
Created by Sarah Watson, Jeania Pang and Erik Portin. Based on 2048 by Gabriele Cirulli which is based on 1024 by Veewo Studio and conceptually similar to Threes by Asher Vollmer. Leaderboard hosted on clay.io. Volunteer tester Joao Palas Nogueira.


{% extends 'base.html' %} {% block title %}Error{% endblock %} {% block page_content %}
Some sort of glitch has been hit. Please contact a site administrator.


Operating Manual
MIELE HS15 Vaccuum Cleaner
MIELE
HS15
Warning and Safety Instructions
This vacuum cleaner complies with statutory safety requirements.
Improper use can, however, lead to personal injury and damage to property.
To avoid the risk of accidents and damage to the vacuum
cleaner, please read these instructions carefully before using it
for the first time. They contain important information on its safety,
operation and maintenance.
Keep these instructions in a safe place and ensure that new users
are familiar with the content. Pass them on to any future owner.
Maintainance & Care
Correctly changing the dustcompartment filter
Open the dust compartment lid.
Pull the dustbag out by the grip next to the self-closing flap on the collar.


- 1. How do you visit Choies?
Please complete this question.
- A. PC
- B. Tablet
- C. Smart Phone
- 2. Which Broswer do you use to visit Choies?
Please complete this question.
- A. Chrome
- B. Safari
- C. Firefox
- D. Opera
- E. Internet Explorer
- F. Others
- 3. How do you get access to Choies?
Please complete this question.
- A. From promoted Pins or pins from pin society
- B. From facebook ads in News Feed or Right Column Ads via desktop or phone
- C. From publishers like Rewardstyle and coupon code site like Retailmenot.com
- D. From Google Shopping, google search engine or google partner sites
- E. From recommendations by bloggers or youtubers
- F. From Marketing & Promotion Emails
- G. Directly visit Choies site
- 4. For the access you have chosen in Question 3, how long does it take to load to Choies site?
Please complete this question.
- A. 1-3 seconds
- B. 3-5 seconds
- C. 5-10 seconds
- D. More than 10 seconds
- 5. For the access you have chosen in Question 3, what is the first page you have been loaded to Choies?
Please complete this question.
- A. Home page
- B. Catagory page
- C. Product page
- D. Activity page
- 6. How many pages do you usually browse with Choies?
Please complete this question.
- A. 3-5 pages
- B. 5-7 pages
- C. 7-10 pages
- D. More than 10 pagese
- 7. What is the most possible reason for you to bounce from Choies?
Please complete this question.
- A. The loading speed is too slow
- B. Having not found the wanted products
- C. The actual product/activity page is not the same as the description in the ads
- D. Have no faith in Choies brand
- 8. How long do you think is acceptable for the pages to load?
Please complete this question.
- A. 0-3 seconds
- B. 3-5 seconds
- C. 5-7 second
- D. 7-10 seconds
- 8. Which one of the following styles do you like best?
Please complete this question.
- A. Ballerina Sports luxe style
- B. Coachella (music festival)+ Boho style
- C. 90's School Girl style（grunge/ ringer tee)
- D. Minimal style (90's, little black dress)
- E. Country girl style (T-shirt, denim, white shirt)
- 8. What is your experience of "The actual product/activity page is not the same as the description in the ads"?
Please complete this question.
- A. The price difference (The actual price is higher than the advertised one)
- B. The product difference (The product image is not the same as the model show)
- C. The promotion difference (The promotion is not the same as it's said in the ad)
- D. The Advertisement expires
- 9. What's your favorite promotion form?
Please complete this question.
 From $5.99
- 10. What may be the reason for you not to complete your payment after checkout?
Please complete this question.
- A. Don't want to wait for the slow confirming response
- B. Not loading to the right payment page
- C. Thinking twice before paying
- D. The payment method you want is not acceptable
At last, thanks so much for completing the questionnaire. We will announce the 5 $100 Gift Card winners on March 16th.
If you come across with any problems when visiting Choies.com, please follow the 2 steps below:
Step 1. Take the screenshot of the problem page
Step 2. Send the screenshot with the detailed problem description to<EMAIL_ADDRESS>And you will be offered amazing gifts according to the problems you submit.


Hyperbolic discounting — The irrational behavior that might be rational after all
04 Feb 2018When I was in grad school I occasionally overheard people talk about how humans do something called “hyperbolic discounting”. Apparently, hyperbolic discounting was considered irrational under standard economic theory.
I recently decided to learn what hyperbolic discounting was all about, so I set out to write this blog post. I have to admit that hyperbolic discounting has been pretty hard for me to understand, but I think I now finally have a good enough handle on it to write about it. Along the way, I learned something interesting: Hyperbolic discounting might be rational after all.
Rational and irrational discounting
If I offered you $50 now or $100 in 6 months, which would you pick? It’s not crazy to choose the $50 now. One reason is that it’s a safer bet. If you had chosen the delayed $100, there’s a risk that I might forget about the deal when the time came to pay [personal note: I wouldn’t], and you would never get your money. Another reason is that if you invest the $50 now, you might be able to make up some of the remainder in interest.
Valuing immediate money more than future money is a rational behavior known as discounting. Everybody has their own discount factor. Some people might value money in 6 months at, say, 75% of what they’d value it today. Others might value it at 90%.
In the early 1980s, psychologist George Ainslie discovered something peculiar. He found that while a lot of people would prefer $50 immediately rather than $100 in 6 months, they would not prefer $50 in 3 months rather than $100 in 9 months. These two different scenarios are shown in the diagram below, where the green checks indicate the options that people tended to choose.
If you think about it, there’s something inconsistent about this behavior. The two scenarios are actually identical, just shifted by 3 months, and yet the same people behave differently depending on when the scenario would be presented. If we waited 3 months and then asked them again if they would prefer $50 immediately or $100 in 6 months, their original response to Scenario 1 implies they would prefer the fast money (i.e. they would have a high discount rate), but their original response to Scenario 2 implies they would prefer the delayed money (i.e. they would have a low discount rate). In other words, their present self today would make a decision in Scenario 2 that three months from now they will have regretted making. This behavior is time-inconsistent and is therefore considered irrational according to standard economic theory.
The usual way to achieve rational time-consistent discounting is with an exponential discount curve, where the value of receiving something at future time \(t\) is a fixed fraction \(s(t)\) of its present value, and where \(\lambda\) is the constant discount rate.
\[s(t) = e^{-\lambda t}\]With an exponential curve, a dollar delayed by six months is always worth the same fixed fraction of a dollar at the baseline date, no matter what the baseline date it is. If you are indifferent between $100 now and $50 in 6 months, you should also be indifferent between $100 in 3 months and $50 in 9 months. The discount rate is constant.
In contrast to an exponential curve, humans tend to show a hyperbolic discount curve, which is considered irrational according to standard economic theory. Confusingly, the hyperbolic discount curve is not defined by one of the hyperbolic functions you may remember from high school. Instead, it is defined as follows, where \(\tau\) is the relative time from now:
\[s(\tau) = \frac{1}{1+k \tau}\]Whereas an exponential curve has a constant discount rate, a hyperbolic discount curve has a higher discount rate in the near future and lower discount rate in the distant future. That’s why the participants in Ainslie’s experiment cared more about the delay from 0 to 6 months than about the same delay from 3 to 9 months.
The apparent rationality of an exponential function is often presented either with a hazard rate interpretation or an interest rate interpretation. It turns out, however, that both of these interpretations make implausible assumptions about the world. The rest of this blog post describes how if we make some more plausible assumptions, hyperbolic discount function becomes rational.
Hazard Rate interpretation
According to the hazard-based interpretation of discounting, you should prefer immediate money to future money because there is a risk that the future money will never be delivered. This interpretation is more common in the animal behavior literature. (Pigeons, rats, and monkeys all show hyperbolic discounting.)
Apparent rationality of exponential discounting
Imagine that there could be an event at some time that could cause you to no longer receive your reward. Perhaps the person who owes you the money could die or lose their assets. Assuming a constant hazard rate (i.e. assuming the event is equally likely to happen at any time), the probability that the event has not happened by time \(\tau\) is:
\[s(\tau) = e^{-\lambda \tau}\]The \(s(\tau)\) function is called a “survival” function because it describes the probability that the deal is still “alive” by time \(\tau\). The \(\lambda\) parameter is the constant hazard rate.
A key insight here is that the survival function can also be interpreted as a discount function. If someone says you can receive your reward at time \(\tau\) if you’re willing to wait for it, and if there’s only a 60% chance you’ll actually receive it, you should value that offer at 60% of the current value of the reward. Since the survival function is exponential, and since the survival function is the discount function, your discount function is also exponential, at least according to standard economic theory.
Rationality of hyperbolic discounting
The problem with assuming an exponential survival function is that it assumes you know the hazard rate \(\lambda\). In most situations, you don’t know exactly what the hazard rate is. Instead you have uncertainty around the parameter. Souza (2015) proposes an exponential prior distribution over the hazard rate.
\[p(\lambda) = \frac{1}{k} e^{-\frac{\lambda}{k}}\]The exponential prior is shown in the graph below. Although this curve looks like a discount function, it is not. It is a distribution over a parameter.
According to Souza, if you average over all the possible exponential survival functions generated by this prior, you get a hyperbolic survival function, or equivalently, a hyperbolic discount function. Let’s see this in action.
In the plot below, I’ve drawn 30 exponential survival functions in blue, each with a \(\lambda\) sampled from the \(p(\lambda)\) prior distribution defined above. The pink curve is the mean of all of them. Notice that whereas the individual survival curves are all exponential, their mean is hyperbolic, with a distant future characterized by a flat slope and relatively high survival values.
As a consequence, the further you look into the future, the lower your discount rate. This is exactly what hyperbolic discounting is and exactly what humans do. For the choice between $50 now and $100 in 6 months, we apply a heavy discount rate. For the choice between $50 in 3 months and $100 in 9 months, we apply a lighter discount rate.
For a more qualitative intuition, you can think of it this way: When you make a deal with someone, you don’t know what the hazard rate is going to be. But if the deal is still alive after 80 months, then your hazard rate is probably favorable and thus the deal is likely to still be alive after 100 months. You can therefore have a light discount rate between 80 months and 100 months.
Interest Rate interpretation
While hazard functions are one way to explain discounting, another common explanation involves interest rates. A dollar now is worth more than a dollar in a year, because if you take the dollar now and invest it, it will worth more in a year.
Apparent rationality of exponential discounting
If the interest rate is 5%, you should be indifferent between $100 today and $105 in a year, since you could just invest the $100 today and get the same amount in a year. If the interest rate is constant, the value of the dollar will rise exponentially, according to \(v(\tau) = e^{0.05\tau}\), where \(v\) is the value. To rationally maintain indifference between a dollar and its equivalent value in the future after investment, your discount function should decay exponentially, according to \(s(\tau) = e^{-0.05\tau}\).
Rationality of hyperbolic discounting
The problem with this story is that it only works if you assume that the interest rate is constant. In the real world, the interest rate fluctuates.
Before taking on the fluctuating interest rate scenario, let’s first take on a different assumption that is still somewhat simplified. Let’s assume that the interest rate is constant but we don’t know what it is, just as we didn’t know what the hazard rate was in the previous interpretation. With this assumption, the justification for hyperbolic discounting becomes similar to the explanation in the blue and pink plots above. When you do a probability-weighted average over these decaying exponential curves, you get a hyperbolic function.
The previous paragraph assumed that the interest rate was constant but unknown. In the real world, the interest rate is known but fluctuates over time. Farmer and Geanakoplos (2009) showed that if you assume that interest rate fluctuations follow a geometric random walk, hyperbolic discounting becomes optimal, at least asymptotically as \(\tau \rightarrow \infty\). In the near future, you know the interest rate with reasonable certainty and should therefore discount with an exponential curve. But as you look further into the future, your uncertainty about the interest rate increases and you should therefore discount with a hyperbolic curve.
Is the geometric random walk a process that was cherry picked by the authors to produce this outcome? Not really. Newell and Pizer (2003) studied US bond rates in the 19th and 20th century and found that the geometric random walk provided a better fit than any of the other interest rate models tested.
Summary
When interpreting discounting as a survival function, a hyperbolic discounting function is rational if you introduce uncertainty into the hazard parameter via an exponential prior (Souza, 2015). When interpreting the discount rate as an interest rate, a hyperbolic discounting function is asymptotically rational if you introduce uncertainty in the interest rate via a geometric random walk (Farmer and Geanakoplos, 2009).


The IOC Ocean InfoHub Project (OIH) is a new initiative to streamline access to ocean science data and information for management and sustainable development. The OIH will establish and anchor a network of regional and thematic nodes that will improve online access to and synthesis of existing global, regional and national data, information and knowledge resources. The project will center on an openly accessible web platform designed to support interlinkages and interoperability between distributed resources including existing clearinghouse mechanisms.


Lukas Taegert, @JS CraftCamp 2016, Munich
How to keep the animation loop looping
function printTimeStamp(timeStamp) {
console.log(timeStamp);
}
// Those all fire at the same time
requestAnimationFrame(printTimeStamp);
for (let i = 0; i < 1000; i++) {}
requestAnimationFrame(printTimeStamp);
requestAnimationFrame(printTimeStamp);
for (let i = 0; i < 1000; i++) {}
requestAnimationFrame(printTimeStamp);
You can measure your frame rate with an
let startTimeStamp = 0, counter = 0;
function measureFrameRate(timeStamp) {
if (counter < 9) counter++;
else {
counter = 0;
document.querySelector('#out').textContent =
10000 / (timeStamp - startTimeStamp);
startTimeStamp = timeStamp;
}
requestAnimationFrame(measureFrameRate);
}
requestAnimationFrame(measureFrameRate);
If there are long running calculations or
if all your animation frames together
take longer than 16ms, you will
console.time('myTimer');
for (let i = 0; i < 10000; i++) {}
console.timeEnd('myTimer');
Nice library to split up code:
Countless patterns to make
common control flow structures asynchronous
Let's calculate pi
let pi = 0, count = 1;
function makeBetterPi() {
pi += 4 * Math.pow(-1, count + 1)/(2*count - 1);
count++;
}
while (count < 1000000) {
makeBetterPi();
document.querySelector('#out').textContent = pi;
}
Using async
async.timesSeries(1000, (n, done) => {
do makeBetterPi();
while (count % 1000 !== 0);
document.querySelector('#out').textContent = pi;
setTimeout(done);
});
but:
Is there a way to optimize the chunk size?
A self-optimizing loop:
let pi = 0, count = 1;
function makeBetterPi() {
pi += 4 * Math.pow(-1, count + 1)/(2*count - 1);
count++;
}
async.whilst(() => count < 1000000, done => {
const startTime = performance.now();
do makeBetterPi();
while (performance.now() - startTime < 5);
document.querySelector('#out').textContent = pi;
setTimeout(done);
});
Much faster! But we can do even more...
Browsers may throttle setTimeout to
(and >1000ms in inactive tabs!)
const startTime = performance.now();
function printTime() {
console.log('received after ' + (performance.now() - startTime));
}
window.addEventListener('message', printTime, true);
window.postMessage('mymessage', '*');
Nice polyfills:
Maxing out JavaScript performance
Don't optimize what does not need optimizing!
A useful shortcut:
function measure(func) {
const startTime = performance.now();
func();
console.log(performance.now() - startTime);
}
push() is not always efficient:
let array = []; array.length = 10000;
measure(() => {
for (let i = 0; i < 10000; i++) array[i] = i;
});
vs.
array = [];
measure(() => {
for (let i = 0; i < 10000; i++) array.push(i);
});
Pushing into arrays as well as out-of-bounds writing
can lead to multiple small memory allocations.
If you can, set the array length first, than write its contents.
If you use indexOf() more than once,
consider building an inverse map:
let source = [];
for (let i = 0; i < 10000; i++) source.push(-i);
let test = [];
for (let i = 0; i < 10000; i++)
test.push(-Math.floor(Math.random() * 10000));
measure(() => {
test.forEach(value => source.indexOf(value));
});
vs.
measure(() => {
let sourceMap = {};
source.forEach((value, index) => sourceMap[value] = index);
test.forEach(value => sourceMap[value]);
});
Building an inverse map is an O(n) operation
that can sometimes prevent an O(n
2
) operation!
Accessing instance variables:
class MyClass {
constructor() {
this.awesomeValue = 'my string';
}
getValue() {
return this.awesomeValue;
}
}
const classObject = new MyClass();
measure(() => {
for (let i = 0; i< 10000; i++) classObject.getValue();
});
Accessing closure variables:
const myFunctionScope = () => {
const awesomeValue = 'my string';
const getValue = () => awesomeValue;
return {getValue};
};
const functionObject = myFunctionScope();
measure(() => {
for (let i = 0; i< 10000; i++) functionObject.getValue();
});
Function scopes are faster with regard to variable access.
Classes are faster when multiple objects
need to be created due to
better code re-use.
Use a factory pattern to hide your implementation details!
delete can be expensive:
let object = {};
for (let i = 0; i < 10000; i++) object[i] = i;
measure(() => {
for (let i = 0; i < 10000; i++) delete object[i];
});
vs.
measure(() => {
for (let i = 0; i < 10000; i++) object[i] = null;
});
function testDirect(value1, value2, value3) {}
measure(() => {
for (let i = 0; i < 10000; i++) testDirect(1, 2, 3);
});
vs.
function testObject({value1, value2, value3}) {}
measure(() => {
for (let i = 0; i < 10000; i++)
testObject({value1: 1, value2: 2, value3: 3});
});
Can create lots of small objects
that need to be garbage collected


{{gamedata.miners}}
{{miningRate()}}/sec
{{miningLevel()}}
{{gamedata.farmers}}
{{farmingRate()}}/sec
{{farmingLevel()}}
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Who are Glastonbury organisers Michael and Emily Eavis?
The names of Michael Eavis and his daughter Emily are synonymous with Glastonbury Festival.
Michael, a dairy farmer by trade, co-founded the festival in September 1970, while Emily’s influence, both music and political, has grown steadily since 1999.
Athelstan Joseph Michael Eavis was born in 1935, his father a Methodist preacher, and educated at the Wells Cathedral School.
He left at 15 to join the Union-Castle Line, part of the British Merchant Navy, as a trainee midshipman, which took him from Britain to Kenya and South Africa.
When he returned to the UK following the death of his father from cancer in 1954, he reluctantly agreed to inherit the family’s land and herd.
He eventually came to love the job and still, when asked in interviews, gives his occupation as “dairy farmer”.
During the festival, he chooses to walk among the punters instead of travel through the site’s myriad rat runs, and is often seen taking selfies with fans.
The driving force behind the festival’s politics, Michael is a life-long supporter of the Labour Party, even unsuccessfully standing as a candidate in the 1997 general election in Wells.
This foray came after he sought treatment for stomach cancer.
In 2004 he suggested voters disillusioned with Tony Blair should switch to the Green party in protest against the Iraq War.
However, he returned to Labour in 2010 and has been an advocate for Jeremy Corbyn’s anti-nuclear and anti-austerity policies, calling him “the hero of the hour” and inviting him to the festival in 2017.
Michael has also been vocal in his support for fox hunting, trophy hunting and badger culling, prompting anger from animal rights activist including Queen guitarist Brian May, who has claimed he will never play the festival in protest.
He holds honorary degrees from the University of Bath and the University of Bristol, and was awarded a CBE for services to music in the Queen’s 2007 birthday honours list.
Emily was born in 1979 to Michael and Jean Eavis, her father’s second wife, and like her father attended Wells Cathedral School.
She has not, however, always walked in her father’s shadow.
Emily was responsible for the majority of the event’s recent high-profile bookings, securing the likes of The Rolling Stones, Adele, Bruce Springsteen, Kanye West, Stevie Wonder and Dolly Parton.
She was also instrumental in the increase in African and Middle Eastern acts at the festival, bringing Amadou and Mariam, Rokia Traore and the Syrian National Orchestra for Arabic Music to the Pyramid Stage.
Like her father, she remains invested in charitable work, regularly organising gigs in aid of Oxfam.
Growing up on Worthy Farm, Emily’s first memories were of the festival.
She performed a rendition of Twinkle, Twinkle, Little Star on the vast Pyramid Stage in 1985, aged five, before that year’s headliners, Paul Weller’s The Style Council.
Following her mother’s death in 1999 from cancer, she dropped her teaching career to return to the farm and take on more responsibility.
Alongside her husband Nick Dewey, who has managed bands including the Chemical Brothers, Emily worked first on The Park area, later taking over full responsibility for the line-up.
The pair married in 2009 and have three children.
Like her father, she has expressed support for the view that the UK should remain in the European Union.


Faraday Motors is an up-and-coming electric car startup that is revving up production of our first vehicle. We are data scientists trying to help all aspects of business be driven by information and wisdom gleaned from data.
Without any prior sales data, our marketing team has no historic information to base marketing strategies on. Additionally, constrained by a limited budget, they wish to make efficient and effective data driven decisions to find optimal markets and leads.
Our company's success is highly dependent on how many people buy our cars. Capitalizing quickly on the first mover advantage by effective marketing will help us survive, compete and grow against the bigger players planning to offer their own electric cars.


About Us
SCR0LL is a design collective interested in innovating the online
experience. We want to create something that is transcending the
barriers of the digital and physical spaces. Our platform aims to
encourage people to develop their creativity through audience
interactions during a series of different creative events.
Smile!
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UN Climate Change Conference – Nairobi 2006
15-Nov-06 — original report
In the morning, SBSTA adopted the agenda ( FCCC/SBSTA/2006/6 ).
Chair Kumarsingh reported agreement that a sub-item on SIDS would be taken up only under the SBI.
Jawed Ali Khan (Pakistan) was elected rapporteur for SBSTA 25-26.
Conference Secretary Richard Kinley informed SBSTA of the financial implications of SBSTA 25 decisions and conclusions, and SBSTA adopted the report of the session ( FCCC/SBSTA/2006/L.18 ).
Chair Kumarsingh closed SBSTA 25 at 6:49 pm.
Chair Becker reported agreement on a SIDS agenda item resulting in its inclusion under Other Matters.
SBI adopted the agenda (FCCC/SBI/2006/12/Add.1).
The SBI elected József Feiler (Hungary) as SBI Vice-Chair and Margaret Mukahanana-Sangarwe (Zimbabwe) as Rapporteur for SBI 26 and 27.
Angela Churie-Kallhauge (Sweden) reported on consultations, noting no agreement, and said that the outcomes of two expert meetings could be used as the basis of further discussion.
Chair Becker said the item would be taken up at SBI 26.
SBI adopted conclusions on matters relating to the LDCs ( FCCC/SBI/2006/L.23 ).
Chair Becker noted changes in LDC Expert Group membership.
Harald Dovland (Norway) reported agreement during informal consultations to, inter alia , maintain current practices on travel for members of constituted bodies, and consider continuing review of the Secretariat at SB 27.
SBI adopted conclusions and draft decisions (FCCC/SBI/2006/L.21 & Adds.1 & 2). EDUCATION, AWARENESS AND TRAINING (ARTICLE 6): Draft conclusions ( FCCC/SBI/2006/L.26 ) were adopted outlining the review of the New Delhi work programme in 2007, information exchange on CC:iNet and two recommendations for the GEF.
Al Waleed Hamad Al-Malik (UAE) reported lack of agreement over whether the group should focus on substance or procedure, particularly whether to focus on a recent workshop or on proposals to merge this item with discussions under Protocol Article 2.3.
Chair Becker noted that the absence of agreed conclusions will be reflected in the SBI 25 report and the item will be included on the SBI 26 agenda.
Henriette Bersee (Netherlands) reported agreement on the work of the Consultative Group of Experts on National Communications (FCCC/SBI/2006/L.25) and on provision of financial and technical support (FCCC/SBI/2006/L.24).
The conclusions were adopted by the SBI.
The G-77/CHINA called on developed countries, through the GEF, to meet the full costs incurred by developing countries when preparing second and subsequent national communications.
Arthur Rolle (Bahamas) reported on small group negotiations on the synthesis of reports demonstrating progress in accordance with Protocol Article 3.2.
He reported no agreement on draft conclusions or on a draft decision acknowledging the progress of Annex I parties and addressing late submission of reports demonstrating progress, and the increasing trend of Annex I parties ' emissions.
Chair Becker said the issue will be taken up at SBI 26.
Chair Becker reported that the SBI had agreed to consider this at SBI 26 with a view to completing consideration at SBI 27.
He undertook to make an oral report to the COP/MOP on Friday.
JAPAN expressed concerns regarding payment and timing of fees relating to this issue.
SBI adopted the conclusions ( FCCC/SBI/2006/L.28 ).
Soobaraj Nayroo Sok Appadu (Mauritius) reported on agreement to consider revised UNFCCC reporting guidelines on global climate change observing systems at SBI 27, and advance the implementation of actions outlined in a regional workshop programme submitted by the GCOS secretariat.
SBSTA adopted the conclusions ( FCCC/SBSTA/2006/L.22 ).
Paul Watkinson (France) reported discussions on procedural matters, and proposed continuing discussions in 2007.
SBI adopted conclusions and a draft COP/MOP decision ( FCCC/SBI/2006/L.22 ).
Adrian Macey (New Zealand) reported agreement on a draft COP/MOP decision, saying it was a significant step forward in operationalizing the Fund.
He emphasized that the Fund's principles and modalities were developed without prejudging the final institutional arrangements. SBI adopted conclusions and a draft COP/MOP decision ( FCCC/SBI/2006/L.29 & Add.1).
The G-77/CHINA noted it is an innovative solidarity fund, the EU said it built new trust among parties, JAPAN hoped the choice of institution will reflect the Fund's agreed principles and modalities, and TUVALU said the Fund will be a small lifeline to SIDS.
Third review of the financial mechanism: Tina Guthrie (Canada) reported on the outcomes of the contact group where delegates resolved the outstanding issue on the fourth review of the financial mechanism. SBI adopted conclusions and a draft COP decision ( FCCC/SBI/2006/L.32 & Add.1).
The G-77/CHINA stressed the need for the financial mechanism to be fully responsive to developing countries ' needs, while the EU and AUSTRALIA highlighted the value of looking at all sources of funding for the Convention's implementation.
Report of the
SBI adopted conclusions ( FCCC/SBI/2006/L.30 ).
Tina Guthrie reported lack of agreement in the contact group as reflected in the draft conclusions ( FCCC/SBI/2006/L.31 ).
The SBI adopted the conclusions and Chair Becker said he had been mandated by the COP President to continue consultations.
Bubu Jallow (Gambia) reported on progress achieved in the contact group.
Noting that the text from the group still contained some brackets, Chair Becker introduced his proposal for a draft decision (FCCC/SBI/2006/L.33), which was adopted without amendment.
Crispin d'Auvergne (Saint Lucia) reported that the contact group had eventually agreed on conclusions and a draft COP decision (FCCC/SBI/2006/L.35 & Add.1), setting out steps to regularly monitor the implementation of capacity building.
These were adopted by SBI.
The SBI adopted conclusions and a draft COP/MOP decision (FCCC/SBI/2006/L.34 & Add.1).
During the contact group, consensus was finally reached to reflect the work of the CDM Executive Board and the needs of LDCs and SIDS.
The EU and JAPAN expressed concern with duplication between contact groups on these issues.
Level of emissions for Croatia's base year: Jim Penman (UK) reported on the outcomes of informal consultations, and the SBI adopted the draft decision (FCCC/SBI/2006/L.20).
The EU noted that the decision does not affect Croatia's baseline for the purposes of implementation of Protocol Article 3.4 (LULUCF additional activities).
SBI adopted conclusions on SIDS ( FCCC/SBI/2006/L.27 ).
Tuvalu, for AOSIS, the EU and AUSTRALIA welcomed the outcome.
Convention: SBSTA adopted conclusions on issues relating to greenhouse gas inventories under the Convention ( FCCC/SBSTA/2006/L.20 & Add.1).
Conference Secretary Richard Kinley informed parties of the new financial implications of SBI 25 decisions and conclusions, and SBI adopted the report of the session ( FCCC/SBI/2006/L.19 ).
Chair Becker closed SBI at 10:20 pm.
AWG 2 convened for its closing plenary on Tuesday evening.
In a final contact group meeting held earlier, Chair Zammit Cutajar distributed revised draft conclusions that set out a vision, schedule and work programme.
The EU said the draft lacked vision.
INDIA stated that the AWG would have to wait until 2008 before parties could see what Annex I parties were prepared to accept.
He proposed deleting text that notes the willingness of Annex I parties to present further information on determining further commitments.
The G-77/CHINA said the Chair had achieved a remarkable balance of concerns, leaving everyone equally unhappy.
Parties agreed to the draft conclusions with the exception of the reference to the willingness of Annex I parties to present further information.
In the plenary, AWG adopted conclusions (FCCC/KP/AWG/2006/L.4).
JAPAN expressed concern about a reference to the Protocol market mechanisms.
The EU expressed regret that not all parties could agree to the 2 ºC objective, and AOSIS added that for vulnerable countries a 2 ºC increase is too high.
The G-77/CHINA and AFRICA GROUP expressed disappointment at the absence of a deadline for completing the work programme.
AWG adopted the report of the session (FCCC/KP/AWG/2006/L.3), and the Chair closed AWG 2 at 7:47 pm.
Thelma Krug (Brazil) chaired a second informal consultation on the Belarus proposal to amend Annex B by specifying a reduction commitment at 95% of its 1990 base year.
Several developed countries said the level of commitment should take into account scientific and technical information.
Parties noted assurances that Belarus would not take advantage of the forest management provisions under Article 3.4 for the first commitment period, and would review the use of carbon trading.
Informal discussions continued in the afternoon with disagreements reported on the issue of remuneration of JISC members.
Delegates were surprised at the relative speed with which the SCCF issue was concluded Tuesday and speculated that this might be linked to progress on the Adaptation Fund.
Skeptics, however, recalled the climate process is in the habit of collecting empty funds.
Nevertheless, with agreement on the majority of items under the financial mechanism, some delegates reportedly glimpsed the first steps in the confidence building process that will be required to pull together a post-2012 regime.
Others observed the beginnings of attempts to tie up the Russian proposal, the AWG and the Article 9 review in a special Christmas package of negotiating opportunities and issue linkages.
An Indian delegate caught the mood of negotiations on future commitments when he compared the long wait that will precede the unveiling of future Annex I commitments with marriage customs where the groom must await the wedding night before viewing the bride.
SBSTA adopted short conclusions ( FCCC/SBSTA/2006/L.23 ) noting that the issue had not been resolved.
CHINA expressed disappointment that agreement had not been possible.
SBSTA adopted conclusions and a draft COP/MOP decision (FCCC/SBSTA/2006/L.21 & Add.1).
Hernán Carlino (Argentina) highlighted agreement on holding a second workshop.
JAPAN urged consideration of social and economic impacts of deforestation.
SINGAPORE highlighted the impact of emissions from peatlands.
SBSTA adopted conclusions (FCCC/SBSTA/2006/L.25).
SBSTA adopted conclusions on the continuation of activities implemented jointly under the pilot phase, and a draft COP decision ( FCCC/SBSTA/2006/L.19 & Add.1).
SBSTA also adopted conclusions on an in-session workshop on carbon dioxide capture and storage (FCCC/SBSTA/2006/L.24).
Helen Plume (New Zealand) reported agreement on activities of the programme of work on adaptation up to 2008.
Many parties stressed the importance of the programme.
MARSHALL ISLANDS, with MICRONESIA, noted that the programme does not deliver adaptation projects.
The UK announced contributions to the work programme, and CANADA welcomed recognition of indigenous knowledge.
SBSTA adopted the conclusions ( FCCC/SBSTA/2006/L.26 ).
Informal consultations on Tuesday resulted in agreement to extend EGTT's mandate and membership for one year, and to forward the draft negotiating texts to SBSTA 26.
SBSTA adopted conclusions and a draft COP decision ( FCCC/SBSTA/2006/L.27 & Add.1).


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TE COMP EndSem: Computer Networks
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TE COMP EndSem: Information Systems & Engineering Economics
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TE COMP EndSem: Theory of Computation


TABLE OF INTERACTIONS WITH
ASCORBIC ACID
from the French ANSM drug interactions document of September 2016, p. 5
ASCORBIC ACID RxNorm: 1151 ATC: A11GA 11GA01 A11GA01 A11GB A11GB01 G01AD03 S01XA15 |
DEFEROXAMINE RxNorm: 3131 ATC: V03AC01 |
With large doses of ascorbic acid and by intravenous route: cardiac function anomalies, even acute heart failure (generally reversible by ending the administration of the Vitamin C). |
Precaution for use In the case of hemochromatosis, only give Vitamin C after having started the treatment with the deferoxamine. Monitor cardiac function when these substances are administered together. |


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I am currently actively working as writer on two personal blogs:
- FritzenLab, A blog about embedded systems programming,
electronic circuits projects and DIY stuff (in Brazilian Portuguese language)
- FritzenMaker, A blog about embedded systems programming,
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Free access to detailed and up to date UK Labour Market statistics from official sources.
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Free access to a summary of your neighbourhood and small area data covering: the census, deprivation, health, local economy, education, housing and crime.
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Data explorer allows you to:


2019
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2019/01/21 The R-Podcast
Nick Tierney
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2019/01/21 The R-Podcast
Hilary Parker
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2019/01/20 Statistical Modeling, Causal Inference, and Social Science
Moneyball for evaluating community colleges
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2019/01/20 Statistical Modeling, Causal Inference, and Social Science
Julia Child (2) vs. Ira Glass; Dorothy Parker advances
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2019/01/19 Statistical Modeling, Causal Inference, and Social Science
“Either the results are completely wrong, or Nasa has confirmed a major breakthrough in space propulsion.”
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2019/01/19 Statistical Modeling, Causal Inference, and Social Science
Dorothy Parker (2) vs. Simone Biles; Liebling advances
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2019/01/18 Statistical Modeling, Causal Inference, and Social Science
A ladder of responses to criticism, from the most responsible to the most destructive
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2019/01/18 Statistical Modeling, Causal Inference, and Social Science
Google on Responsible AI Practices
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2019/01/18 Statistical Modeling, Causal Inference, and Social Science
Anthony Bourdain (3) vs. A. J. Liebling; Steve Martin advances
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2019/01/18 Simply Statistics
The Tentpoles of Data Science
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2019/01/18 Rob J Hyndman
forecast 8.5
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2019/01/17 Statistical Modeling, Causal Inference, and Social Science
A thought on the hot hand in basketball and the relevance of defense
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2019/01/17 Statistical Modeling, Causal Inference, and Social Science
Steve Martin (4) vs. David Letterman; Serena Williams advances
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2019/01/16 Statistical Modeling, Causal Inference, and Social Science
M. F. K. Fisher (1) vs. Serena Williams; Oscar Wilde advances
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2019/01/16 Statistical Modeling, Causal Inference, and Social Science
Data partitioning as an essential element in evaluation of predictive properties of a statistical method
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2019/01/16 Statistical Modeling, Causal Inference, and Social Science
Causal inference data challenge!
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2019/01/15 Statistical Modeling, Causal Inference, and Social Science
Oscar Wilde (1) vs. Joe Pesci; the Japanese dude who won the hot dog eating contest advances
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2019/01/15 Statistical Modeling, Causal Inference, and Social Science
Does Harvard discriminate against Asian Americans in college admissions?
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2019/01/14 Statistical Modeling, Causal Inference, and Social Science
Carol Burnett (4) vs. the Japanese dude who won the hot dog eating contest; Albert Brooks advances
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2019/01/14 Statistical Modeling, Causal Inference, and Social Science
Storytelling: What’s it good for?
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2019/01/14 Blog on rOpenSci - open tools for open science
rOpenSci's new Code of Conduct
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2019/01/13 Jay's Notes
Coping with worst loss at home
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2019/01/13 Statistical Modeling, Causal Inference, and Social Science
How post-hoc power calculation is like a shit sandwich
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2019/01/13 Statistical Modeling, Causal Inference, and Social Science
John van Neumann (3) vs. Albert Brooks; Paul Erdos advances
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2019/01/13 Statistical Modeling, Causal Inference, and Social Science
Coursera course on causal inference from Michael Sobel at Columbia
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2019/01/13 DNA confesses Data speak on DNA confesses Data speak
Understanding p value, multiple comparisons, FDR and q value
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2019/01/13 Econometrics and Free Software
Making sense of the METS and ALTO XML standards
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2019/01/12 Statistical Modeling, Causal Inference, and Social Science
This is one offer I can refuse
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2019/01/12 Statistical Modeling, Causal Inference, and Social Science
Johnny Carson (2) vs. Paul Erdos; Babe Didrikson Zaharias advances
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2019/01/12 Homepage on Liechi | 張列弛
李白的诗
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2019/01/11 Wannabe Rstats-fu
A Tip to Debug ggplot2
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2019/01/11 Statistical Modeling, Causal Inference, and Social Science
NYC Meetup Thursday: Under the hood: Stan’s library, language, and algorithms
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2019/01/11 Statistical Modeling, Causal Inference, and Social Science
New blog hosting!
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2019/01/11 Statistical Modeling, Causal Inference, and Social Science
Becker on Bohm on the important role of stories in science
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2019/01/11 Homepage on Liechi | 張列弛
床前看月光
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2019/01/10 Blog on rOpenSci - open tools for open science
vitae: Dynamic CVs with R Markdown
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2019/01/10 Andriy V. Koval on Andriy V. Koval
Time to gather, time to spread. Part 1.
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2019/01/10 Statistical Modeling, Causal Inference, and Social Science
MRP (multilevel regression and poststratification; Mister P): Clearing up misunderstandings about
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2019/01/10 Statistical Modeling, Causal Inference, and Social Science
Babe Didrikson Zaharias (2) vs. Adam Schiff; Sid Caesar advances
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2019/01/09 Simply Statistics
How Data Scientists Think - A Mini Case Study
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2019/01/09 Statistical Modeling, Causal Inference, and Social Science
Reproducibility and Stan
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2019/01/09 Statistical Modeling, Causal Inference, and Social Science
Ed Sullivan (3) vs. Sid Caesar; DJ Jazzy Jeff advances
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2019/01/08 Blog on rOpenSci - open tools for open science
Continuing to Grow Community Together at ozunconf, 2018
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2019/01/08 Statistical Modeling, Causal Inference, and Social Science
Philip Roth (4) vs. DJ Jazzy Jeff; Jim Thorpe advances
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2019/01/08 Statistical Modeling, Causal Inference, and Social Science
“The Book of Why” by Pearl and Mackenzie
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2019/01/08 Statistical Modeling, Causal Inference, and Social Science
Did she really live 122 years?
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2019/01/07 Statistical Modeling, Causal Inference, and Social Science
The seminar speaker contest begins: Jim Thorpe (1) vs. John Oliver
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2019/01/07 Statistical Modeling, Causal Inference, and Social Science
On deck for the first half of 2019
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2019/01/06 Statistical Modeling, Causal Inference, and Social Science
Objective Bayes conference in June
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2019/01/06 Statistical Modeling, Causal Inference, and Social Science
Announcing the ultimate seminar speaker contest: 2019 edition!
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2019/01/06 一路嘿嘿
ROC曲线与AUC值
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2019/01/05 Statistical Modeling, Causal Inference, and Social Science
“Dissolving the Fermi Paradox”
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2019/01/04 About on Likan Zhan | 战立侃
An interactive learning widget for R
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2019/01/04 DNA confesses Data speak on DNA confesses Data speak
permutation test for PCA components
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2019/01/04 Statistical Modeling, Causal Inference, and Social Science
Back by popular demand . . . The Greatest Seminar Speaker contest!
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2019/01/04 Statistical Modeling, Causal Inference, and Social Science
Robin Pemantle’s updated bag of tricks for math teaching!
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2019/01/04 Econometrics and Free Software
Looking into 19th century ads from a Luxembourguish newspaper with R
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2019/01/03 Statistical Modeling, Causal Inference, and Social Science
Published in 2018
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2019/01/02 Statistical Modeling, Causal Inference, and Social Science
What to do when you read a paper and it’s full of errors and the author won’t share the data or be open about the analysis?
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2019/01/01 Statistical Modeling, Causal Inference, and Social Science
“Principles of posterior visualization”
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2019/01/01 Rob J Hyndman
Macroeconomic forecasting for Australia using a large number of predictors
2018
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2018/12/31 Statistical Modeling, Causal Inference, and Social Science
Authority figures in psychology spread more happy talk, still don’t get the point that much of the published, celebrated, and publicized work in their field is no good (Part 2)
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2018/12/30 Statistical Modeling, Causal Inference, and Social Science
Combining apparently contradictory evidence
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2018/12/30 Econometrics and Free Software
R or Python? Why not both? Using Anaconda Python within R with {reticulate}
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2018/12/29 Mara Averick
Top Tweets of 2018
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2018/12/29 Statistical Modeling, Causal Inference, and Social Science
“Check yourself before you wreck yourself: Assessing discrete choice models through predictive simulations”
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2018/12/28 DNA confesses Data speak on DNA confesses Data speak
The end of 2018
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2018/12/28 Statistical Modeling, Causal Inference, and Social Science
Using multilevel modeling to improve analysis of multiple comparisons
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2018/12/27 Statistical Modeling, Causal Inference, and Social Science
Back to the Wall
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2018/12/27 Econometrics and Free Software
Some fun with {gganimate}
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2018/12/26 ZedR Blog - Data Science . R . Stock Markets
Deploying Metabase through Heroku App
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2018/12/26 Homepage on Yihui Xie | 谢益辉
On Marketing (on Social Media)
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2018/12/26 Statistical Modeling, Causal Inference, and Social Science
What is probability?
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2018/12/25 Statistical Modeling, Causal Inference, and Social Science
“Thus, a loss aversion principle is rendered superfluous to an account of the phenomena it was introduced to explain.”
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2018/12/24 Homepage on Yihui Xie | 谢益辉
On Disagreement
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2018/12/24 Statistical Modeling, Causal Inference, and Social Science
Zak David expresses critical views of some published research in empirical quantitative finance
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2018/12/24 Statistical Modeling, Causal Inference, and Social Science
June is applied regression exam month!
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2018/12/24 Econometrics and Free Software
Objects types and some useful R functions for beginners
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2018/12/23 Statistical Modeling, Causal Inference, and Social Science
“When Both Men and Women Drop Out of the Labor Force, Why Do Economists Only Ask About Men?”
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2018/12/23 Jan's Page
Univariate Fans of Majorizers
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2018/12/23 Jan's Page
Convergence Rate of Majorization Algorithms with Constraints
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2018/12/23 Jan's Page
Some Incomplete Papers
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2018/12/22 Statistical Modeling, Causal Inference, and Social Science
Carol Nickerson explains what those mysterious diagrams were saying
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2018/12/22 Rob J Hyndman
Network for early career researchers in forecasting
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2018/12/21 Statistical Modeling, Causal Inference, and Social Science
The causal hype ratchet
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2018/12/21 Econometrics and Free Software
Using the tidyverse for more than data manipulation: estimating pi with Monte Carlo methods
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2018/12/21 Rob J Hyndman
A brief history of forecasting competitions
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2018/12/20 ewen
listening, EOY 2018
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2018/12/20 Statistical Modeling, Causal Inference, and Social Science
Exploring model fit by looking at a histogram of a posterior simulation draw of a set of parameters in a hierarchical model
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2018/12/20 一路嘿嘿
线性判别分析LDA
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2018/12/19 Homepage on Yihui Xie | 谢益辉
渴望
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2018/12/19 Simply Statistics
The Netflix Data War
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2018/12/19 DNA confesses Data speak on DNA confesses Data speak
A tale of two heatmap functions
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2018/12/19 Statistical Modeling, Causal Inference, and Social Science
When “nudge” doesn’t work: Medication Reminders to Outcomes After Myocardial Infarction
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2018/12/19 Rob J Hyndman
Early classification of spatio-temporal events using time-varying models
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2018/12/18 Posts on datascienceblog.net: R for Data Science
An Introduction to Forecasting
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2018/12/18 Blog on rOpenSci - open tools for open science
rcites - The story behind the package
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2018/12/18 DNA confesses Data speak on DNA confesses Data speak
PCA in action
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2018/12/18 Statistical Modeling, Causal Inference, and Social Science
Comparing racism from different eras: If only Tucker Carlson had been around in the 1950s he could’ve been a New York Intellectual.
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2018/12/18 Statistical Modeling, Causal Inference, and Social Science
Classifying yin and yang using MRI
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2018/12/18 Rob J Hyndman
Why doesn't auto.arima() return the model with the lowest AICc value?
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2018/12/18 一路嘿嘿
主成分分析
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2018/12/17 Statistical Modeling, Causal Inference, and Social Science
Why do sociologists (and bloggers) focus on the negative? 5 possible explanations. (A post in the style of Fabio Rojas)
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2018/12/16 Statistical Modeling, Causal Inference, and Social Science
Surprise-hacking: “the narrative of blindness and illusion sells, and therefore continues to be the central thesis of popular books written by psychologists and cognitive scientists”
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2018/12/16 一路嘿嘿
矩阵分解
-
2018/12/15 Statistical Modeling, Causal Inference, and Social Science
“My advisor and I disagree on how we should carry out repeated cross-validation. We would love to have a third expert opinion…”
-
2018/12/15 Econometrics and Free Software
Manipulate dates easily with {lubridate}
-
2018/12/14 Statistical Modeling, Causal Inference, and Social Science
A couple of thoughts regarding the hot hand fallacy fallacy
-
2018/12/13 Statistical Modeling, Causal Inference, and Social Science
Oh, I hate it when work is criticized (or, in this case, fails in attempted replications) and then the original researchers don’t even consider the possibility that maybe in their original work they were inadvertently just finding patterns in noise.
-
2018/12/12 Statistical Modeling, Causal Inference, and Social Science
Time series of Democratic/Republican vote share in House elections
-
2018/12/12 Rob J Hyndman
Using ggplot2 for functional time series
-
2018/12/11 Simply Statistics
The Role of Theory in Data Analysis
-
2018/12/11 Blog on rOpenSci - open tools for open science
Generating reasonable starting trees for complex phylogenetic analyses
-
2018/12/11 Statistical Modeling, Causal Inference, and Social Science
“Do you have any recommendations for useful priors when datasets are small?”
-
2018/12/11 Rob J Hyndman
Data visualization for functional time series
-
2018/12/10 ewen
understatr
-
2018/12/10 Statistical Modeling, Causal Inference, and Social Science
Prior distributions for covariance matrices
-
2018/12/09 Posts on datascienceblog.net: R for Data Science
Prediction vs Forecasting
-
2018/12/09 Statistical Modeling, Causal Inference, and Social Science
Should we be concerned about MRP estimates being used in later analyses? Maybe. I recommend checking using fake-data simulation.
-
2018/12/09 Rob J Hyndman
Seasonal functional autoregressive models
-
2018/12/08 Posts on datascienceblog.net: R for Data Science
Interpreting ROC Curves, Precision-Recall Curves, and AUCs
-
2018/12/08 Statistical Modeling, Causal Inference, and Social Science
My footnote about global warming
-
2018/12/07 Posts on datascienceblog.net: R for Data Science
Inference vs Prediction
-
2018/12/07 Statistical Modeling, Causal Inference, and Social Science
Latour Sokal NYT
-
2018/12/06 Statistical Modeling, Causal Inference, and Social Science
A parable regarding changing standards on the presentation of statistical evidence
-
2018/12/05 Blog on rOpenSci - open tools for open science
Community Call - Governance strategies for open source research software projects
-
2018/12/05 Statistical Modeling, Causal Inference, and Social Science
Niall Ferguson and the perils of playing to your audience
-
2018/12/05 Rob J Hyndman
High-dimensional time series analysis
-
2018/12/04 Posts on datascienceblog.net: R for Data Science
Performance Measures for Multi-Class Problems
-
2018/12/04 Blog on rOpenSci - open tools for open science
Detecting spatiotemporal groups in relocation data with spatsoc
-
2018/12/04 Statistical Modeling, Causal Inference, and Social Science
“Statistical insights into public opinion and politics” (my talk for the Columbia Data Science Society this Wed 9pm)
-
2018/12/04 Statistical Modeling, Causal Inference, and Social Science
Bayes, statistics, and reproducibility: “Many serious problems with statistics in practice arise from Bayesian inference that is not Bayesian enough, or frequentist evaluation that is not frequentist enough, in both cases using replication distributions that do not make scientific sense or do not reflect the actual procedures being performed on the data.”
-
2018/12/03 Statistical Modeling, Causal Inference, and Social Science
StanCon 2018 Helsinki talk slides, notebooks and code online
-
2018/12/03 Statistical Modeling, Causal Inference, and Social Science
My talk tomorrow (Tues) noon at the Princeton University Psychology Department
-
2018/12/03 Statistical Modeling, Causal Inference, and Social Science
In which I demonstrate my ignorance of world literature
-
2018/12/03 Peng Zhao on Peng Zhao
R, Open Science, and Reproducible Research
-
2018/12/02 Posts on datascienceblog.net: R for Data Science
Behind the Scenes: The First Month of datascienceblog.net
-
2018/12/02 Statistical Modeling, Causal Inference, and Social Science
The p-value is 4.76×10^−264
-
2018/12/02 Econometrics and Free Software
What hyper-parameters are, and what to do with them; an illustration with ridge regression
-
2018/12/01 Statistical Modeling, Causal Inference, and Social Science
“James Watson in his own words”
-
2018/11/30 Homepage on Yihui Xie | 谢益辉
老人的故事
-
2018/11/30 Statistical Modeling, Causal Inference, and Social Science
Stephen Wolfram explains neural nets
-
2018/11/30 Rob J Hyndman
Forecasting competitions
-
2018/11/29 Blog on rOpenSci - open tools for open science
Community Call Summary - Code Review in the Lab
-
2018/11/29 Statistical Modeling, Causal Inference, and Social Science
“And when you did you weren’t much use, you didn’t even know what a peptide was”
-
2018/11/28 Statistical Modeling, Causal Inference, and Social Science
Another Stan related job in baseball!
-
2018/11/28 Rob J Hyndman
M4 Forecasting Conference
-
2018/11/28 Homepage on Liechi | 張列弛
是人格造就了伟大的科学家
-
2018/11/27 Homepage on Yihui Xie | 谢益辉
脱不花的三盏灯
-
2018/11/27 Blog on rOpenSci - open tools for open science
Co-localization analysis of fluorescence microscopy images
-
2018/11/27 Statistical Modeling, Causal Inference, and Social Science
$ vs. votes
-
2018/11/27 Home on Another Random Blog
My sublime text setup (and packages)
-
2018/11/26 Homepage on Yihui Xie | 谢益辉
再论如何完成自己不喜欢的事情
-
2018/11/26 Homepage on Yihui Xie | 谢益辉
文明及其缺憾
-
2018/11/26 Statistical Modeling, Causal Inference, and Social Science
“Economic predictions with big data” using partial pooling
-
2018/11/26 Rob J Hyndman
Feature-based time series analysis
-
2018/11/25 Homepage on Yihui Xie | 谢益辉
文非加粗描红不能读也？
-
2018/11/25 Statistical Modeling, Causal Inference, and Social Science
These 3 problems destroy many clinical trials (in context of some papers on problems with non-inferiority trials, or problems with clinical trials in general)
-
2018/11/25 Econometrics and Free Software
A tutorial on tidy cross-validation with R
-
2018/11/24 Statistical Modeling, Causal Inference, and Social Science
The evolution of pace in popular movies
-
2018/11/23 Wannabe Rstats-fu
How To Convert A Human To Waves By Magick Package
-
2018/11/23 Statistical Modeling, Causal Inference, and Social Science
Hey! There are mathematicians out there who’ve never read Proofs and Refutations. Whassup with that??
-
2018/11/22 Statistical Modeling, Causal Inference, and Social Science
“She also observed that results from smaller studies conducted by NGOs – often pilot studies – would often look promising. But when governments tried to implement scaled-up versions of those programs, their performance would drop considerably.”
-
2018/11/21 Homepage on Yihui Xie | 谢益辉
盲人 R 用户
-
2018/11/21 Statistical Modeling, Causal Inference, and Social Science
A Bayesian take on ballot order effects
-
2018/11/21 Econometrics and Free Software
The best way to visit Luxembourguish castles is doing data science + combinatorial optimization
-
2018/11/21 L. Collado-Torres on L. Collado-Torres
Non-coding Class Switch Recombination-Related Transcription in Human Normal and Pathological Immune Responses
-
2018/11/20 Homepage on Yihui Xie | 谢益辉
加餐
-
2018/11/20 Blog on rOpenSci - open tools for open science
Checklist Recipe - How we created a template to standardize species data
-
2018/11/20 Statistical Modeling, Causal Inference, and Social Science
“The hype economy”
-
2018/11/19 Homepage on Yihui Xie | 谢益辉
编程之道
-
2018/11/19 Statistical Modeling, Causal Inference, and Social Science
Tom Wolfe
-
2018/11/18 Statistical Modeling, Causal Inference, and Social Science
Graphs and tables, tables and graphs
-
2018/11/17 Statistical Modeling, Causal Inference, and Social Science
“Using numbers to replace judgment”
-
2018/11/16 Statistical Modeling, Causal Inference, and Social Science
Hey, check this out: Columbia’s Data Science Institute is hiring research scientists and postdocs!
-
2018/11/16 Statistical Modeling, Causal Inference, and Social Science
2018: How did people actually vote? (The real story, not the exit polls.)
-
2018/11/16 Econometrics and Free Software
Using a genetic algorithm for the hyperparameter optimization of a SARIMA model
-
2018/11/15 Statistical Modeling, Causal Inference, and Social Science
The State of the Art
-
2018/11/15 Econometrics and Free Software
Searching for the optimal hyper-parameters of an ARIMA model in parallel: the tidy gridsearch approach
-
2018/11/14 Statistical Modeling, Causal Inference, and Social Science
Robustness checks are a joke
-
2018/11/14 Econometrics and Free Software
Easy time-series prediction with R: a tutorial with air traffic data from Lux Airport
-
2018/11/13 Blog on rOpenSci - open tools for open science
The Antarctic/Southern Ocean rOpenSci community
-
2018/11/13 Andriy V. Koval on Andriy V. Koval
Health System Impact Fellowship
-
2018/11/13 Andriy V. Koval on Andriy V. Koval
Data Science Studio
-
2018/11/13 Statistical Modeling, Causal Inference, and Social Science
Chocolate milk! Another stunning discovery from an experiment on 24 people!
-
2018/11/12 Homepage on Yihui Xie | 谢益辉
接受自己的普通
-
2018/11/12 Rbind Support
Data Science Blog: My Experiences with Data Science, Blogging, and R
-
2018/11/12 Statistical Modeling, Causal Inference, and Social Science
“Law professor Alan Dershowitz’s new book claims that political differences have lately been criminalized in the United States. He has it wrong. Instead, the orderly enforcement of the law has, ludicrously, been framed as political.”
-
2018/11/12 L. Collado-Torres on L. Collado-Torres
Asking for help is challenging but is typically worth it
-
2018/11/11 ZedR Blog - Data Science . R . Stock Markets
#DataHack4Fi twitter data
-
2018/11/11 Statistical Modeling, Causal Inference, and Social Science
Hey! Here’s what to do when you have two or more surveys on the same population!
-
2018/11/10 Statistical Modeling, Causal Inference, and Social Science
Matching (and discarding non-matches) to deal with lack of complete overlap, then regression to adjust for imbalance between treatment and control groups
-
2018/11/10 Statistical Modeling, Causal Inference, and Social Science
2018: Who actually voted? (The real story, not the exit polls.)
-
2018/11/10 Statistical Modeling, Causal Inference, and Social Science
2018: What really happened?
-
2018/11/10 Econometrics and Free Software
Analyzing NetHack data, part 2: What players kill the most
-
2018/11/09 Homepage on Yihui Xie | 谢益辉
Some of My JS Tricks to Enhance the HTML Output of Markdown
-
2018/11/09 Homepage on Yihui Xie | 谢益辉
On Cosmetic Changes in Pull Requests
-
2018/11/09 Homepage on Yihui Xie | 谢益辉
My Biggest Regret in the knitr Package
-
2018/11/09 Statistical Modeling, Causal Inference, and Social Science
“Recapping the recent plagiarism scandal”
-
2018/11/08 Homepage on Yihui Xie | 谢益辉
The Two Surprisingly Hard Things about the Otherwise Simple Markdown
-
2018/11/08 Homepage on Yihui Xie | 谢益辉
Things are Getting Better and Better
-
2018/11/07 ZedR Blog - Data Science . R . Stock Markets
African Markets indices tracker
-
2018/11/07 Homepage on Yihui Xie | 谢益辉
Winners Take All in the Dependency World (or Hell)
-
2018/11/07 Statistical Modeling, Causal Inference, and Social Science
“35. What differentiates solitary confinement, county jail and house arrest” and 70 others
-
2018/11/06 Statistical Modeling, Causal Inference, and Social Science
“Statistical and Machine Learning forecasting methods: Concerns and ways forward”
-
2018/11/06 Statistical Modeling, Causal Inference, and Social Science
Postdocs and Research fellows for combining probabilistic programming, simulators and interactive AI
-
2018/11/06 L. Collado-Torres on L. Collado-Torres
A knot of threads: from CSHL to LCG-UNAM to Aldo Barrientos to diversity scholarship opportunities
-
2018/11/05 Statistical Modeling, Causal Inference, and Social Science
Why it can be rational to vote
-
2018/11/05 Statistical Modeling, Causal Inference, and Social Science
The purported CSI effect and the retroactive precision fallacy
-
2018/11/03 ewen
ewenthemes (AKA how to mod hrbrthemes)
-
2018/11/03 Statistical Modeling, Causal Inference, and Social Science
“We are reluctant to engage in post hoc speculation about this unexpected result, but it does not clearly support our hypothesis”
-
2018/11/03 Econometrics and Free Software
Analyzing NetHack data, part 1: What kills the players
-
2018/11/03 Homepage on Liechi | 張列弛
进化之一点点-3
-
2018/11/02 Homepage on Yihui Xie | 谢益辉
English is Still Hard for Me, and Thoughts on (Computer) Language Wars
-
2018/10/31 Rob J Hyndman
A framework for automated anomaly detection in high frequency water-quality data from in situ sensors
-
2018/10/30 Rob J Hyndman
Predicting Sediment and Nutrient Concentrations in Rivers Using High Frequency Water Quality Surrogates
-
2018/10/12 About on Likan Zhan | 战立侃
R Used in Literature
2017
0001
-
0001/01/01 Home on Emi's Blog
About


The sensor object can be used to access numerous sensors of your device.
sns = app.CreateSensor(
type,
options )
→
app object: Sensor
You can use the SetOnChange function of the Sensor to set the name of a function you want to be called when a the changes occur.
Change the rate that a sensor checks for changes by adding one the options “Fastest”, “Fast”, “Medium” or “Slow”. “Slow” is the default.
Example - GetNames
function OnStart()
{
sns = app.CreateSensor();
var names = sns.GetNames();
app.Alert(names.replace(/,/g, ",\n"), "Sensor Names");
}
Example - Accelerometer
function OnStart()
{
lay = app.CreateLayout( "Linear", "VCenter,FillXY" );
txt = app.CreateText( "", 0.8, 0.3, "Multiline" );
lay.AddChild( txt );
app.AddLayout( lay );
sns = app.CreateSensor( "Accelerometer" );
sns.SetOnChange( sns_OnChange );
sns.Start();
}
function sns_OnChange( x, y, z, time )
{
txt.SetText( "x=" + x + "\n y=" + y + "\n z=" + z );
}
Example - Orientation
function OnStart()
{
lay = app.CreateLayout( "Linear", "VCenter,FillXY" );
txt = app.CreateText( "", 0.8, 0.3, "Multiline" );
lay.AddChild( txt );
app.AddLayout( lay );
sns = app.CreateSensor( "Orientation" );
sns.SetOnChange( sns_OnChange );
sns.Start();
}
function sns_OnChange( azimuth, pitch, roll, time )
{
var msg = " azimuth = " + azimuth.toFixed(1);
msg += "\n pitch = " + pitch.toFixed(1);
msg += "\n roll = " + roll.toFixed(1);
txt.SetText( msg );
}
Example - Light
function OnStart()
{
lay = app.CreateLayout( "Linear", "VCenter,FillXY" );
txt = app.CreateText( "", 0.8, 0.3 );
lay.AddChild( txt );
app.AddLayout( lay );
sns = app.CreateSensor( "Light" );
sns.SetOnChange( sns_OnChange );
sns.Start();
}
function sns_OnChange( lux )
{
txt.SetText( "level = " + lux + " lux" );
}
Methods
The following methods are available on the Sensor object:
GetNames() →
string: comma “,” separated
number
string
number: milliseconds
string: “Accelerometer” or “MagneticField” or “Orientation” or “Light” or “Proximity” or “Temperature” or “GameRotation” or “GeomagneticRotation” or “Gravity” or “Gyroscope” or “HeartRate” or “Acceleration” or “Pressure” or “Humidity” or “RotationMotion” or “StepCounter” or “StepDetector”
string: comma “,” separated: “Slow” or “Medium” or “Fast” or “Fastest”
list: boolean,char,byte,short,int,long,float,double,String,CharSequence,...
sns.GetAzimuth
Returns the first/x/azimuth value of a sensor.
sns.GetNames
Returns a list of builtin sensors in your device.
sns.GetPitch
Returns the second/y/pitch value of a sensor.
sns.GetRoll
Returns the third/z/roll value of a sensor.
sns.GetType
Returns the control class name.
sns.GetValues
Returns all values of a sensor.
sns.MethodAllows access to other functions defined on the object in Java via reflection.
Note: This function is a premium feature. Please consider subscribing to Premium to use this feature and support DroidScript in its further development.
sns.SetMaxRate
Define a minimum timeout between two OnChage calls.
sns.SetMinChange
Define a minimum threshold value which triggers a OnChange call.
sns.SetOnChange
Define a callback function which is called when a sensor value has changed.
sns.Start
Start reading from the sensor.
sns.Stop
Stop reading from the sensor.


Hey, my name is Victor! I am currently a fourth year student in the Computer Science program at the University of Waterloo. I love learning new skills, whether it is in a classroom or in my free time, and have experience with front-end and full-stack web development.
I'm an avid basketball fan (We the NORTH 🦖)! My other hobbies include playing violin, working out, gardening and playing video games.
Currently seeking Winter & Spring 2023 Intenship Opportunities! You can reach out to me any way you want. I look forward to getting in touch!
Direct is an easy to use video call web app aimed to connect instructors and students and streamline the payment process. Created using React and Firebase. Implements Stripe API for payment as well as WebRTC for video calling feature.
🏆 Winner of 2020 E-Launch Award for 5,000$ prize money among 50+ startups
View DetailsFashiony is a full-stack web app made using Firebase, React.js and Node.js. Firebase allows for real-time database storage of posts and comments as well as for user authentication.
View Details See App DemoMapChat is a full-stack web app made with MongoDB, Express.js, React.js and Node.js (MERN). MongoDB was used to store the map entries as well as messages in the chatrooms. Socket.io was implemented in order to allow real-time, bidirectional and event-based communication between users.
View Details See App DemoStock Tracker was made using Javascript and Node. Various packages, such as puppeteer, were added to implement the webscraping feature. Data taken directly from Market Beat Stock Market News and Research Tool. User can view current stock price, P/E ratio and experts' opinion.
View DetailsA React app using Mapbox API to generate interactive app as well as updated information from John Hopkins University taken from this API (https://corona.lmao.ninja/v2/jhucsse). Each country and province affected will have a marker, whose colour and size depends on the severity of the disease there. The user can hover over it to see more information. Deployed using Netlify.
View Details See App DemoCandidate for Bachelor of Computer Science
2019 - Present
Received DEC in Honours Health Science
2017-2019
High school diploma obtained after 5 years of IB program and Personal Project
2012-2017


COVID- (), cases coronavirus {border-style patients px;} respiratory #ffffff;} clinical health viral novel April, Wuhan, (.%) Indian []. infected infections laboratory-confirmed various deaths diagnosis infection India affected number public spread virus viruses (.%), April COVID-. Fig.Â px; {font-family Pradesh countries font-size global high human large pneumonia positive rate Coronavirus MERS-CoV SARS admitted double; emerging majority mortality person persons responsible similar symptoms total Distribution India, Pradesh, border-color border-width causes confirmed genome highly like mild molecular parts receptor solid; specific states transmission upper world {font-style {font-weight (https://www.mohfw.gov.in/seen China Delhi Health India. MERS Med SARS-CoV Source: Virus [], animal assay basis bold case compared contagious control coronaviruses country courier; death early em; envelope genomic https://www.mohfw.gov.in/seen infection. influenced low outbreaks people potential produced pt;} recovered severe shown suspected travel treatment virus, viruses,


A platform that generates employment
VIEW OUR TEAMWe at Recruitcare aim to provide a easy to use platform for people who need specific types of services and products to contact and connect with the people who are skilled enough in their field but lack resources and opportunities to work individually. We also have a section where young aspiring students can avail a low cost practical knowledge experience which would be provided by people with a great work background.
We have three different sections namely labourers, females and students for catering to the employment needs of common people across India. The people and their details listed on this website are verified by various levels of background checks conducted by us. Please note that these people our not our employees. The expenses incurred and the quality of service provided, though previously intimidated, are subject to change as per the service provider’s means. However, you can free feel to contact us in case of any issue. We would try our best to sort it out. We also have a section where you can refer someone whom you know and help him/her register themselves on this site and increase their chances of getting a job as soon as possible. It would mean a lot for us and would help us in our goal to create more and more job opportunities to the underprivileged.
Females constitute the major part of our economy and thus, their contribution matters too.
So, this section is for all the females who do not have the resources and opportunities to exhibit their skills or talent. for example: weaving, sewing, baking, household etc. Here, you can reach out to the ones who need work to get your work done. And thus tending to contribute in lives of many by helping them to achieve their desired goal and thus, bringing the required change for the future.
Without labour, no industry or no sector can every progress. It is the labour that helps to build new industries. When new industries are built, job opportunities are created and the employment rate improves. A country improves it economy with the help of good labour.
We provide the labourers with the platform that can provide them with the surety of their wages.
for example: If you need someone to fix a leak or change your tubelight. Look ahead. Maybe you can find someone you need. 😊
Individuals aspires for learning something new and that new is practical knowledge. Practical knowledge that one can use in actual world.
So, this section provides the entusiastic individuals who have the seal to learn new technologies and work enthusiastically with apropriate opportunity. Here you can teach and can also be taught. Being new in any field, if someone wants to know what actually future demands from them and for them we provide them with the opprtunity. In this section, we tend to collaborate the new learning individuals with the experienced ones so that they can learn and incorporate the skills. We provide you with the opporutnity to learn from the experienced and get advancement in the field and also to contribute in lives of many by helping them to achieve their desired goal and thus, bringing the required change for the future.


Java allows such qualification for classes, but such calls may indicate a subtle confusion of inheritance and overriding.
Example:
class Parent {
public static void print(String str) {}
}
class Child extends Parent {}
Child.print("Hello, world!");
After the quick-fix is applied:
Parent.print("Hello, world!");


Inpage workflow 1: Both fields should be filled then a page change should occur followed by the fields 3+4 being filled.


- beforeTextChanged(CharSequence, int, int, int) - Method in class com.stl.skipthelibrary.Validators.TextValidator
-
Triggers before text has changed
- Book - Class in com.stl.skipthelibrary.Entities
-
The book class.
- Book() - Constructor for class com.stl.skipthelibrary.Entities.Book
-
Empty constructor
- Book(BookDescription, String, String, ArrayList<ViewableImage>) - Constructor for class com.stl.skipthelibrary.Entities.Book
-
Constructor with some fields.
- Book(String, BookDescription, String, RequestHandler, ArrayList<ViewableImage>, Rating) - Constructor for class com.stl.skipthelibrary.Entities.Book
-
The full constructor.
- BOOK_ID - Static variable in class com.stl.skipthelibrary.BindersAndAdapters.BookRecyclerAdapter
-
- BOOK_ID - Static variable in class com.stl.skipthelibrary.BindersAndAdapters.NotificationRecyclerAdapter
-
- BookDescription - Class in com.stl.skipthelibrary.Entities
-
This class details the description of a book.
- BookDescription() - Constructor for class com.stl.skipthelibrary.Entities.BookDescription
-
The empty constructor
- BookDescription(String, String, String) - Constructor for class com.stl.skipthelibrary.Entities.BookDescription
-
The full constructor
- BookDescriptionReceiver - Class in com.stl.skipthelibrary.Helpers
-
This class is used to get the books description, it works with the BookWebAPIHelper
- BookDescriptionReceiver(String, TextView, TextView, TextView) - Constructor for class com.stl.skipthelibrary.Helpers.BookDescriptionReceiver
-
The constructor
- BookDescriptionTest - Class in com.stl.skipthelibrary
-
- BookDescriptionTest() - Constructor for class com.stl.skipthelibrary.BookDescriptionTest
-
- bookImage - Variable in class com.stl.skipthelibrary.BindersAndAdapters.BookImageViewHolder
-
- BookImageViewHolder - Class in com.stl.skipthelibrary.BindersAndAdapters
-
The view holder for the arraylist of book images
- BookImageViewHolder(View) - Constructor for class com.stl.skipthelibrary.BindersAndAdapters.BookImageViewHolder
-
The constructor, binds the UI items
- BookRatingReceiver - Class in com.stl.skipthelibrary.Helpers
-
This class is used to get the books rating, it works with the GoodReadsAPIHelper
- BookRatingReceiver(Context, Rating, String) - Constructor for class com.stl.skipthelibrary.Helpers.BookRatingReceiver
-
The constructor
- BookRecyclerAdapter - Class in com.stl.skipthelibrary.BindersAndAdapters
-
The recycler adapter for books.
- BookRecyclerAdapter(Context, ArrayList<Book>) - Constructor for class com.stl.skipthelibrary.BindersAndAdapters.BookRecyclerAdapter
-
The constructor
- BookRecyclerAdapter.ViewHolder - Class in com.stl.skipthelibrary.BindersAndAdapters
-
Inner Class ViewHolder defines all of the elements in the corresponding xml file.
- BookStatus - Enum in com.stl.skipthelibrary.Enums
-
Contains the 4 statuses a book may have
- BookTest - Class in com.stl.skipthelibrary
-
- BookTest() - Constructor for class com.stl.skipthelibrary.BookTest
-
- BookValidator - Class in com.stl.skipthelibrary.Validators
-
Determines if a newly added book is valid
- BookValidator(String, String, String, String) - Constructor for class com.stl.skipthelibrary.Validators.BookValidator
-
Constuctor
- BookWebAPIHelper - Class in com.stl.skipthelibrary.DatabaseAndAPI
-
This class is used to get the book's description from google's book api
- BookWebAPIHelper() - Constructor for class com.stl.skipthelibrary.DatabaseAndAPI.BookWebAPIHelper
-
Empty constructor
- BorrowersBooksActivity - Class in com.stl.skipthelibrary.Activities
-
This activity is where borrowers can see and filter all of the books they are interested in.
- BorrowersBooksActivity() - Constructor for class com.stl.skipthelibrary.Activities.BorrowersBooksActivity
-
- borrowerUserId - Static variable in class com.stl.skipthelibrary.UITestHelper
-


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--- layout: page title: Hannah Hellerstein / enderquestral subtitle: Student in Computer Science use-site-title: true ---
My name is Hannah Hellerstein, currently a 3rd-year undergrad student in Computer Science at Reed college. I'm pretty new to the tech world, all things considered! My current interests are Cyber Security and Software Engineering. I also have experience with game development. I currently work part-time as an AV assistant at Reed College.


San Jose Fire Incidents
Source: Fire incident data from
data.sanjose.gov
A
Code for San Jose project showing how open data can be used to provide insights
(For demonstration only. Not an official San Jose Government site)
Explore San Jose Fire Incidents for January 2015


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Psalm 131
A song of ascents; of David.
1 Yahweh, my heart is not proud or my eyes haughty.
I do not have great hopes for myself
or concern myself with things that are beyond me.
2 Indeed I have stilled and quieted my soul;
like a weaned child with his mother,
my soul within me is like a weaned child.
3 Israel, hope in Yahweh
now and forever.


"Generative art is an artwork partially or completely created by an autonomous system 🤖" - Music Generation with Magenta
Lets take our time machine and come back to the 18th century.
In 1792, a guy named Mozard created the Musikalisches Würfelspiel (musical dice) game.
The result of a dice roll determines which measure to add to the generated composition
The system is autonomous, because you don't decide the outcome
So basically the system is working for (with) you to reach a common goal: great music
But the result is as good as the system that creates it 😬.
Back in 2021, we're sitting on a pile of theorical knowledge about music, and lots of technology.
Brian Eno, who coined the term "generative music", who created numerous infinite albums
ORCA, one of many (esoteric) langages created for generative music.
Algorave, an underground music scene where the music is live-coded in front the audience (hence its name).
We have generative music tools to help us compose, produce, improvise, etc. 🚀
Claire Malrieux / Alexandre DuBreuil (skip to 11:00)
This generative artwork makes a relation between climate events (rain, tornados, etc.), the artist's drawings, and the music.
Generative text, generative voice, generative score (partition), generative audio, generative emotions!? 🤯
Some things are hard to do using traditional algorithm like text generation, voice generation, audio generation, etc. So we need a way of training a machine on human data...
With machine learning, you can use human data, and let the machine predict / generate based on what it has learned.
Claire Malrieux / Alexandre DuBreuil (skip to 10:50)
The machine tells us about its dream: "The street of the dream, interpretation too, I was very surprised that first I had..."
We go "full generative": generative dream text based on human dreams, analysing sentiments (sad, happy, etc.) of the text, generating speech, generating musical score...
Generating score based on style (rock, jazz, classical, etc.), emotion (sad, happy, etc.), instrument (drum, piano, etc.). With different neural networks (Recurrent Neural Networks, RNNs).
Generating audio is HARD, but we can generate sounds
based on cat meow!
Will neural networks take over the world?
No.
Remember: the generated music is only as good the generative system! And a generative system only reproduces what it knows.
Explore the role of deep learning in music generation and assisted music composition
Slides & More: alexandredubreuil.com/conferences


 Funds needed to support their activities are raised by adding an extra cost known as a precept to each householder’s council tax bill.
The parish/town councils are:


It (1927)
Grade: 61
Clara Bow's film career peaked in 1927 with two highly successful silent classics. One was "Wings", the aviation drama that was the first film to win the Academy Award for Best Picture. Her other great success for that year was "It". For the rest of her short career (her last film was in 1933) Bow would be known as the 'It' girl.
"It" was loosely based upon Elinor Glyn's pulp novelette, which defined 'it' essentially as a code word for overwhelming sex appeal. Paramount cleverly used Glyn and her 'it' concept, to promote Clara Bow as the epitome of 'it'. This led to Glyn being paid $50,000 for a brief appearance in the film, and to proclaim Bow as the 'it' girl.
"It" is also noted for having an early screen appearance by Gary Cooper, who has a brief role as a newspaper reporter. Cooper was reportedly one of Bow's many conquests. Scandals, both real and fabricated, helped drive Bow out of Hollywood.
"It" is one of the best preserved silent films that I have seen. There are no dancing lines or exploding white dots, no orange-yellow tones, and no obvious missing frames. Such problems are endemic to most 1920s films, but not this one.
The storyline would probably annoy feminists if the film was made today. Betty (Bow) works as an impoverished salesgirl in a large department store owned by dashing but humorless Waltham (Antonio Moreno). Betty's best friend is troubled unwed mother Molly (Priscilla Bonner), whose baby is the target of meddlesome social workers.
Betty works hard to catch the eye of Waltham, whose fiancee Jacqueline (Adela Van Norman) is attractive but boring. Betty uses grinning fop Monty (William Austin) to get access to Waltham, who doesn't stand a chance. Bow's vivacious, flirtatious personality struck a chord with film audiences who saw her as emancipated from the restrictive moral code that preceded the Jazz Age.
Yes, but how good is the movie? Producer Adolph Zukor's attention ensured a big budget with good sets. The characters are all stock, but the film has its charm, no doubt supplied more by Bow's presence than by Clarence Badger's direction.
<EMAIL_ADDRESS>http://members.tripod.com/~Brian_Koller/movies.html
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Perform wavelet analysis (orthogonal and translation invariant transforms) with applications to data compression or denoising. Most of the code is a port of 'MATLAB' Wavelab toolbox written by D. Donoho, A. Maleki and M. Shahram (<https://statweb.stanford.edu/~wavelab/>).
| Version: | 0.1.0 |
| Imports: | dplyr, signal |
| Suggests: | knitr, rmarkdown, imager |
| Published: | 2018-09-12 |
| Author: | F. Navarro and C. Chesneau |
| Maintainer: | Navarro Fabien <fabien.navarro at ensai.fr> |
| BugReports: | http://github.com/fabnavarro/rwavelet/issues |
| License: | LGPL-2 | LGPL-2.1 | LGPL-3 [expanded from: LGPL (≥ 2)] |
| URL: | http://github.com/fabnavarro/rwavelet |
| NeedsCompilation: | no |
| Citation: | rwavelet citation info |
| Materials: | README |
| CRAN checks: | rwavelet results |
| Reference manual: | rwavelet.pdf |
| Vignettes: |
Rwavelet Vignette |
| Package source: | rwavelet_0.1.0.tar.gz |
| Windows binaries: | r-devel: rwavelet_0.1.0.zip, r-release: rwavelet_0.1.0.zip, r-oldrel: rwavelet_0.1.0.zip |
| OS X binaries: | r-release: rwavelet_0.1.0.tgz, r-oldrel: rwavelet_0.1.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=rwavelet to link to this page.


|
Upx_Doxygen
https://github.com/upx/upx
|
Classes | |
| struct | LoopInfo |
Public Types | |
| enum | { LOOP_NONE, LOOP_SUBQ_L, LOOP_SUBQ_W, LOOP_DBRA } |
Public Member Functions | |
| void | reset () |
Public Attributes | |
| bool | need_reloc |
| LoopInfo | loop1 |
| LoopInfo | loop2 |
| LoopInfo | loop3 |
| unsigned | up21_d4 |
| unsigned | up21_a6 |
| unsigned | up31_base_d4 |
| unsigned | up31_base_a6 |
| unsigned | up31_d4 |
| unsigned | up31_a6 |
| unsigned | flush_cache_rts_offset |
| unsigned | clear_dirty_stack_len |
| unsigned | copy_to_stack_len |


Running the demo setup
- pre-requisites
- checkout the scs-commerce repositories
# prepare base folder (can be named anything)
mkdir scs-commerce
cd ./scs-commerce
# checkout services
# for further details take a look at the single repositories
# https://github.com/scs-commerce/
git clone git@github.com:scs-commerce/landing-page.git
git clone git@github.com:scs-commerce/products.git
git clone git@github.com:scs-commerce/order.git
git clone git@github.com:scs-commerce/assets.git
git clone git@github.com:scs-commerce/integration.git
- build integration project
cd ./integration
docker-compose build
docker-compose up
- visit landing page
open http://localhost