8 Mediation
https://crumplab.github.io/psyc7709/book/docs/bootstrapped-mediation-tutorial.html
https://www.annualreviews.org/doi/pdf/10.1146/annurev.psych.58.110405.085542
We will use the responses to the questions about perceived urgency and sympathy toward the patient as variables in a mediation analysis to explore their role in mediating metaphor’s effect on donation amounts.
Steps to establishing mediation via tests of causal steps, from Baron & Kenny (1986) [BK86]:
- “a significant relation of the independent variable to the dependent variable is required”
- “a significant relation of the independent variable to the hypothesized mediating variable is required”
- “the mediating variable must be significantly related to the dependent variable when both the independent variable and mediating variable are predictors of the dependent variable”
Alternatively, we may use resampling techniques (e.g. bootstrap) to create confidence intervals on the indirect effect and therefore construct a NHT.
The two mediation techniques aren’t neccessarily mutually exclusive, however using BCa bootstrapped CIs tends to lead to much higher power (Fritz & MacKinnon, 2007) and doesn’t rely on the same assumptions (although similarities exists).
library(crayon)
library(mediation)
## Loading required package: MASS
##
## Attaching package: 'MASS'
## The following object is masked from 'package:dplyr':
##
## select
## Loading required package: Matrix
##
## Attaching package: 'Matrix'
## The following objects are masked from 'package:tidyr':
##
## expand, pack, unpack
## Loading required package: mvtnorm
## Loading required package: sandwich
## mediation: Causal Mediation Analysis
## Version: 4.5.0
Set up a few helper functions to identify mediation models worth running.
check_BK86_assumption_1 = function (total_effect_pvalue, type_i_error) {
if (total_effect_pvalue < type_i_error) print(glue_col("{green The total effect of X on Y is significant.}"))
else print(glue_col("{red The total effect of X on Y is not significant.}"))
}
check_BK86_assumption_2 = function (alpha_pvalue, type_i_error) {
if (alpha_pvalue < type_i_error) print(glue_col("{green The effect of X on M is significant.}"))
else print(glue_col("{red The effect of X on M is not significant.}"))
}
check_BK86_assumption_3 = function (beta_pvalue, type_i_error) {
if (beta_pvalue < type_i_error) print(glue_col("{green The effect of M on Y controlled for X is significant.}"))
else print(glue_col("{red The effect of M on Y controlled for X is not significant.}"))
}
check_BK86_assumption_4 = function (direct_effect, total_effect, direct_effect_pvalue, type_i_error) {
partial <- abs(direct_effect) < abs(total_effect)
if (direct_effect_pvalue >= type_i_error) {
print(glue_col("{green The direct effect of X on Y adjusted for M is non-significant.}"))
} else if (partial) {
print(glue_col("{yellow The direct effect of X on Y adjusted for M is less than the total effect of X on Y.}"))
} else {
print(glue_col("{red The direct effect is significant or greater than the total effect.}"))
}
}
check_mediation_assumptions = function (dv, md, iv, iv_key, data) {
formula_covars <- as.character(base.formula)[2]
type_i_error <- 0.1
model_x_m <- summary(lm(reformulate(c(formula_covars, iv), md), data = data))
model_mx_y <- summary(lm(reformulate(c(formula_covars, md, iv), dv), data = data))
model_x_y <- summary(lm(reformulate(c(formula_covars, iv), dv), data = data))
total_effect <- model_x_y$coefficients[iv_key, ]
direct_effect <- model_mx_y$coefficients[iv_key, ]
beta <- model_mx_y$coefficients[md, ]
alpha <- model_x_m$coefficients[iv_key, ]
print(glue("total effect = {round(total_effect[1] / total_effect[2], 2)}, direct effect = {round(direct_effect[1] / direct_effect[2], 2)}, beta = {round(beta[1] / beta[2], 2)}, alpha = {round(alpha[1] / alpha[2], 2)}"))
print(glue("indirect effect = {round((alpha[1] / alpha[2]) * (beta[1] / beta[2]),3)}"))
check_BK86_assumption_1(model_x_y$coefficients[iv_key, 4], type_i_error)
check_BK86_assumption_2(model_x_m$coefficients[iv_key, 4], type_i_error)
check_BK86_assumption_3(model_mx_y$coefficients[md, 4], type_i_error)
check_BK86_assumption_4(direct_effect[1], total_effect[1], model_mx_y$coefficients[iv_key, 4], type_i_error)
}
8.1 Any Metaphor to Literal condition
The presence of Any Metaphor did not significantly predict donation, so mediation analysis is irrelevant here for sympathy and urgency.
8.2 Battle to Literal condition
8.2.1 Sympathy
Does Sympathy mediate the relation between metaphor condition (between battle and literal conditions) and donation amounts?
mask <- trials$cond_metaphor != "journey"
check_mediation_assumptions("donation", "sympathy", "cond_metaphor", "cond_metaphorbattle", trials[mask, ])
## total effect = 1.29, direct effect = 1.23, beta = 15.66, alpha = 0.38
## indirect effect = 5.952
## The total effect of X on Y is not significant.
## The effect of X on M is not significant.
## The effect of M on Y controlled for X is significant.
## The direct effect of X on Y adjusted for M is non-significant.
8.2.2 Urgency
Does Urgency mediate the relation between metaphor condition (between battle and literal conditions) and donation amounts?
mask <- trials$cond_metaphor != "journey"
check_mediation_assumptions("donation", "urgent", "cond_metaphor", "cond_metaphorbattle", trials[mask, ])
## total effect = 1.29, direct effect = 0.51, beta = 14.93, alpha = 3.07
## indirect effect = 45.865
## The total effect of X on Y is not significant.
## The effect of X on M is significant.
## The effect of M on Y controlled for X is significant.
## The direct effect of X on Y adjusted for M is non-significant.
8.3 Journey to Literal condition
8.3.1 Sympathy
Does Sympathy mediate the relation between metaphor condition (between journey and literal conditions) and donation amounts?
mask <- trials$cond_metaphor != "battle"
check_mediation_assumptions("donation", "sympathy", "cond_metaphor", "cond_metaphorjourney", trials[mask, ])
## total effect = -0.89, direct effect = -1.02, beta = 14.88, alpha = 0.39
## indirect effect = 5.745
## The total effect of X on Y is not significant.
## The effect of X on M is not significant.
## The effect of M on Y controlled for X is significant.
## The direct effect of X on Y adjusted for M is non-significant.
8.3.2 Urgency
Does Urgency mediate the relation between metaphor condition (between journey and literal conditions) and donation amounts?
mask <- trials$cond_metaphor != "battle"
check_mediation_assumptions("donation", "urgent", "cond_metaphor", "cond_metaphorjourney", trials[mask, ])
## total effect = -0.89, direct effect = -0.87, beta = 14.89, alpha = -0.2
## indirect effect = -2.965
## The total effect of X on Y is not significant.
## The effect of X on M is not significant.
## The effect of M on Y controlled for X is significant.
## The direct effect of X on Y adjusted for M is non-significant.
8.4 Battle to Journey condition
These tests of mediation are the only ones which satisfy the first causal step for determining mediation (an alternative to resampling). This is a critical relationship, and because it holds here, we will also test the significance of the indirect effect using the bootstrap.
8.4.1 Sympathy
Does Sympathy mediate the relation between metaphor condition (between battle and journey conditions) and donation amounts?
mask <- trials$cond_anymet
check_mediation_assumptions("donation", "sympathy", "cond_metaphor", "cond_metaphorjourney", trials[mask, ])
## total effect = -2.1, direct effect = -2.21, beta = 14.95, alpha = 0.14
## indirect effect = 2.021
## The total effect of X on Y is significant.
## The effect of X on M is not significant.
## The effect of M on Y controlled for X is significant.
## The direct effect is significant or greater than the total effect.
We remove the OptOut level of the gender factor due to numerical computation issues.
temp_data <- trials[mask, ] %>%
filter(gender != "OO") %>%
mutate(cond_metaphor = factor(cond_metaphor))
model_x_m <- lm(update(base.formula, sympathy ~ . + cond_metaphor),
data = temp_data)
model_mx_y <- lm(update(base.formula, donation ~ . + sympathy + cond_metaphor),
data = temp_data)
# med.anlys <- mediate(model.m = model_x_m,
# model.y = model_mx_y,
# treat = "cond_metaphor",
# mediator = "sympathy",
# boot = T,
# boot.ci.type = "bca",
# sims = 2000)
#
# summary(med.anlys)
Based upon Baron & Kenny’s (1986) causal-steps, sympathy cannot mediate the relation between metaphor condition and donation amount. Moreover, based upon resampling, the same conclusion is also drawn.
8.4.2 Urgency
Does Urgency mediate the relation between metaphor condition (between battle and journey conditions) and donation amounts?
mask <- trials$cond_anymet
check_mediation_assumptions("donation", "urgent", "cond_metaphor", "cond_metaphorjourney", trials[mask, ] %>% sample_n(1000))
## total effect = -1.12, direct effect = -0.65, beta = 7.23, alpha = -2.14
## indirect effect = -15.495
## The total effect of X on Y is not significant.
## The effect of X on M is significant.
## The effect of M on Y controlled for X is significant.
## The direct effect of X on Y adjusted for M is non-significant.
For an alpha of magnitude -0.15 and a beta of magnitude 3.23, we should expect, according to Fritz and MacKinnon (2007), a required sample size of 385 participants for 80% power (and 5% type I error). We’ll keep this in mind for testing the hold-out set.
temp_data <- trials[mask, ] %>%
filter(gender != "OO")
model_x_m <- lm(update(base.formula, urgent ~ . + cond_metaphor),
data = temp_data)
model_mx_y <- lm(update(base.formula, donation ~ . + urgent + cond_metaphor),
data = temp_data)
# med.anlys <- mediate(model.m = model_x_m,
# model.y = model_mx_y,
# treat = "cond_metaphor",
# mediator = "urgent",
# boot = T,
# boot.ci.type = "bca",
# sims = 2000)
#
# summary(med.anlys)
# library(lavaan)
# full_med <- '
# urgent ~ cond_metaphor + cond_sex + past_donations.z + age.z
# donation ~ urgent + cond_sex + past_donations.z + age.z
# '
#
# sem_full <- sem(full_med, data = temp_data %>%
# mutate(
# cond_metaphor = scale(as.integer(cond_metaphor)),
# cond_sex = scale(as.integer(cond_sex))))
#
# partial_med <- '
# urgent ~ cond_metaphor + cond_sex + past_donations.z + age.z
# donation ~ cond_metaphor + urgent + cond_sex + past_donations.z + age.z
# '
#
# sem_partial <- sem(partial_med, data = temp_data %>%
# mutate(
# cond_metaphor = scale(as.integer(cond_metaphor)),
# cond_sex = scale(as.integer(cond_sex))))
# summary(sem_partial)
Based upon Baron & Kenny’s (1986) causal-steps, urgency does fully mediate the relation between metaphor condition and donation amount. Moreover, based upon resampling methods, the same conclusion can be drawn.
8.5 Summary
Any Metaphor did not significantly predict donation amounts, so we skipped those two mediation checks all together.
Next, we looked at whether the relation between the battle condition compared to the literal condition and donation amounts was mediated. The metaphor condition did not predict donation amounts, so we don’t run these mediation analyses either.
A similar story holds for the journey condition compared to the literal condition.
Lastly, we checked whether the relation between the battle condition compared to the journey condition and donation amounts was mediated. This is the most promising exploration, since we see a significant difference between the two metaphor conditions. We find that according to BK86, sympathy fails to mediate the relationship since the metaphor condition did not predict sympathy. Likewise, a BCa bootstrap mediation analysis also reports a direct effect and no causal mediation effect. Yet, all four assumptions of BK86 were met when testing urgency’s mediation on the conditions. Similarly, a BCa bootstrap mediation analysis reports a highly significant decrease in donation amounts given the journey condition as a direct “causal” mediation of lowered urgency compared to the battle condition.


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Setup
Note: make sure you have setup your Raspberry Pi to connect with the PiLite before running any of the examples below.
Design a picture using the grid:
Draw a picture by clicking or dragging over the grid below.
To select multiple blocks, you will need to hold the multi-select button on your keyboard. (alt on Windows, cmd on Mac)
Once you've finished your drawing you will see an output string at the bottom of the page: e.g.
000000000001110000011111000011111100001111110000111111000111111001111110011111100011111000001110000000000000000000000000000000
Simply copy and paste the output string into one of the methods below to view it on the PiLite.
Output:
Using the Python script
Design a picture using the webpage as described above.
Run python ./DrawBoard
Paste the output binary string once prompted.
Using Minicom:
Design a picture using the webpage as described above.
Run minicom through the terminal on the device: e.g.
minicom -b 9600 -o -D /dev/ttyAMA0
Type: $$$
in the minicom terminal to go to command mode, it should display OK on the terminal screen.
Type: F
Paste the output binary string into minicom and press carriage return.
Your picture should now be displayed on the PiLite LED Board.
To clear the text, press carriage return.


dataset check COLLECTION_NAME [COLLECTION_NAME ...]
Check reviews one or more collections and reports if any problems
are identified based on the collection.json
file found in the
folder holding the collection’s pairtree. Check only works on local
disc based collections. If you are storing your collection in
the cloud (e.g. S3 or Google Cloud Storage) then download a copy
before running check.
If multiple instances of dataset write (e.g. create or update) to
a collection then it is possible that the JSON file collection.json
will become inaccurate.
dataset check MyRecordCollection.ds
dataset check MyBrokenCollection.ds MyRecordCollection.ds
Related topics: repair


Result goes here…
Features
- Light-weight, no dependencies. It uses vanilla JavaScript.
- File-agnostic. Language modes are named after the file extensions that are usually assigned to the file (except for some non-file syntax such as HTTP syntax).
Limitations
- Currently not possible to preserve HTML tags in the source code.
- Mixed PHP expression within HTML tags likely will break.
- There aren’t any automatic language detection feature. You have to determine the syntax highlighting mode in the source element manually.
- Currently does not support nested syntax highlighting. This syntax highlighter was intended to highlight syntax within a file as a preview utility, to help users focus only on the important parts of the file. For example, in a HTML file, only HTML tags are highlighted. CSS and JavaScript syntax that appear in it will not be highlighted.
Usage
<!DOCTYPE html>

<meta charset="utf-8">
<link href="ash.min.css" rel="stylesheet">

{"foo":1}

Examples
Settings
let ash = new ASH(source, prefix);
let ash = new ASH(source, state = {
class: 'ash'
});
- source → The source element that holds the initial code snippet. Usually a

element. - prefix → The default class prefix.
- state → The configuration data.
- state.class → The default class prefix.
Methods and Properties
ASH.esc(content)
Escape special characters in regular expression.
ASH.h(type, content, fn)
Static method to highlight a string input.
let code = document.querySelector('code');
ASH.h('xml', code.textContent, result => {
code.className = 'ash ash-xml';
code.innerHTML = result;
});
ASH.instances
Return the syntax highlighter instances.
for (let key in ASH.instances) {
console.log(key);
console.log(ASH.instances[key]);
}
ASH.state
This property stores the initial values of ash.state
.
let ash = new ASH(source, {
foo: ['bar', 'baz', 'qux']
});
console.log([ASH.state, ash.state]);
ASH.version
Return the syntax highlighter version.
let version = ASH.version,
major = version.split('.')[0];
if (+major < 2) { … }
ASH.x
List of regular expression’s special characters.
ash.state
Return the modified syntax highlighter states.
ash.source
Return the syntax highlighter source element that holds the initial code snippet.
ash.source.addEventListener('click', function() {
console.log(this.nodeName);
}, false);
ash.pop()
Remove syntax highlighting from the source element.
Languages
Currently support these languages:
- Apache
- CSS
- CSV (also TSV)
- HTML
- HTTP
- JavaScript
- JSON
- Markdown
- PHP
- SGML
- Text
- TSV
- Twig
- XML (also SVG)
- YAML
Regular expressions and class naming specifications are very inspired by the Highlight.js project. API may be very ugly, but I want to prioritize performance and size of the file for now.
Regular Expression Specifications
If you already know that some tokens have a consistent pattern, you can define the pattern as constant to be used later across languages that could possibly benefit from it:
ASH.LOG = '\\b(?:false|null|true)\\b';
ASH.NUM = '\\b-?(?:\\d+?\\.)?\\d+\\b';
ASH.STR = '"(?:\\\\.|[^"])*"|\'(?:\\\\.|[^\'])*\'';
Class Naming Specifications
Every language syntax basically have a structure, and usually they have the same kind of categorization. For example, although CSS and JavaScript are two different languages, they obviously have a unified tokens such as function, keyword, number, and string. The following are standard class names that likely would apply to all kind of language syntax:
| Name | Description |
|---|---|
cla |
Class. |
com |
Comment. |
con |
Constant. |
exp |
Expression. Regular expression. |
fun |
Function. A function declaration. |
key |
Key. Should be paired with val . |
lib |
Library. Built-in objects or classes. |
log |
Three-valued logic. Includes false , null , true . |
mar |
Markup. As in HTML tags or Markdown syntax. |
nam |
Name. Name of function, HTML tag, etc. |
num |
Number. Including units and modifiers, if any. |
str |
String. Literal string. |
sym |
Symbol. Smiley, HTML entities, etc. |
typ |
Type. Document type or identifier. |
val |
Value. Should be paired with key . |
var |
Variable. In general, it should not be highlighted unless it has special pattern such as PHP variables. |
wor |
Word. Special words that are reserved by the language parser such as do , else , function , if , var , while , etc. |
Others are free to be defined by developers. Each category must at least be compatible with the existing classes, and must consist of a maximum of three letters. For example, you may want to distinguish between float and integer number. You can add flo
class together with num
. Or, you may want to make a sub-category for number that is represented in HEX format. You can add hex
class together with num
. Sub-category coloring can be added by the syntax highlighter theme designer optionally. The default color for numbers will always inherit to the num
class.
| Name | Description |
|---|---|
att |
Attribute. As in attribute selector in CSS. |
bul |
Bullet. As for list and YAML array sequence. |
cod |
Code. As in Markdown syntax for codes. |
id |
ID. As in ID selector in CSS. |
ima |
Image. As in Markdown syntax for images. |
lin |
Link. As in Markdown syntax for links. |
pse |
Pseudo. As in pseudo class or element selector in CSS. |
quo |
Quote. As in Markdown syntax for quotes. |
que |
Query. As in CSS selector. |
sec |
Section. As in INI syntax for sections, or in Markdown syntax for heading elements. |
uri |
URI. Just in case you want to highlight URI. |
Adding Your Own Syntax Highlighter
I don’t want to look fancy here. The main feature of this syntax highlighter is the ability to load language definition asynchronously. About the way you will mark the tokens is up to you. All you have to do is define a language category based on the file extension like so:
ASH.token.css = function(content) {};
ASH.token.html = function(content) {};
ASH.token.js = function(content) {};
// You can also make alias
ASH.token.jsx = 'js';
ASH.token.ts = ASH.token.js;
Defining languages together with the core will make the highlighting work synchronously. To make it asynchronous, you will need to store them as separate files:
.\
├── ash\
│ ├── css.js
│ ├── html.js
│ └── js.js
└── ash.js
The first function parameter contains the plain text version of the source element contents. this
refers to the ASH
instance. You can get the available methods and properties from there:
ASH.token.json = function(content) {
// Mark the desired parts of your syntax here
content = content.replace(/[\{\}\[\]:,]/g, '$&');
// Then return the modified content
return content;
};
Below is a simple example of using the array method to mark portions of a JSON file using regular expressions:
ASH.token.json = [
['(' + ASH.STR + ')(\\s*:)', [0, 'key', 0]],
[ASH.STR, ['val.str']],
[ASH.LOG, ['val.log']],
[ASH.NUM, ['val.num']]
];
The order in which the patterns are given is very important. You can also make sub-pattern tasks:
ASH.token.css = [
['(#)((?:[a-fA-F\\d]{1,2}){3,4})', ['val', 0, 'num.hex']],
['(\\brgba?\\([^)]+\\))', ['val', [
['([\\w-]+)(\\()', [0, 'fun', 'pun']],
['-?\\d*\\.\\d+', ['num.flo']],
['-?\\d+', ['num.int']],
['[,)]', ['pun']]
]],
[ … ],
[ … ],
…
…
];
Current implementation of syntax highlighter relies on regular expressions. I know this is bad, but to handle short code snippets, it should be enough. If you want to handle more complex cases, a syntax highlighter library such as Highlight.js will be more appropriate.
License
Use it for free, pay if you get paid. So, you’ve just benefited financially after using this project? It’s a good idea to share a little financial support with this open source project too. Your support will motivate me to do any further development, as well as to provide voluntary support to overcome problems related to this project.
Thank you! ❤


val timestampNs: Long
Timestamp in nanoseconds at which the video frame was captured from some system monotonic clock. Will be aligned and converted to NTP (Network Time Protocol) within AmazonChimeSDKMedia library, which will then be converted to a system monotonic clock on remote end. May be different on frames emanated from AmazonChimeSDKMedia library.
See DefaultSurfaceTextureCaptureSource for usage of a AmazonChimeSDKMedia library class which can convert to the clock used by the library


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--- layout: page title: About header-img: "img/about-bg.png" ---
This blog will tell you about my experiences as I trudge along learning to code. It will also serve as a time-capsule so that when I complete this program i can look back and laugh about what a n00b I was trying to figure all this out.


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CYPRESS
City of Toronto
Ranking of Current Reports
Vote on which problems are more important by clicking the "+1" button. Use the "-1" button to vote on a problem as less important.
Address:
$scope.chosen="Utility failures"
Problem at site:
Rank:
+1
-1


---
layout: archive
title: Lean Prover Zulip Chat Archive
permalink: 113488general/29580sorryinmathlibbuild.html
---
The archive URL format has changed. Please find this page at:
https://leanprover-community.github.io/archive/stream/113488-general/topic/.22sorry.22.20in.20mathlib.20build.html


A Golden Demonstration
Try resizing your browser or viewing this page on different devices. Use the icon in the upper right corner to see an overlay of the grid. It works by folding your screen sizes in half. Just like DIN paper sizes.
Trust me. You don't need rows.
You don't even need to worry about your columns. Everything is already in the column. Unless you really want more than 1 column.
But there's more than just 1 column size...
A two-way split
These two blocks of text will float side by side with some empty columns on the sides on large screens. On medium-sized screens the empty columns will disappear, and on small screens the blocks will be stacked vertically.
By the way
If you're viewing this page on an iOS device, it might zoom in wonkily when you rotate your device. This is because of a Mobile Safari bug.
Like me...
You might need more options for sizing your columns. Simply splitting them just won't cut it. You may want to try out my four-way splits.
My four-some
These 4 columns here will hold up splited on all screen sizes except the iPad mini and phone sizes. The whole folding in half idea means you can keep a golden ratio to all your columns sizes.
Which means
You can actually count on designing your site once and not worrying about display. Thus every folding will result in half the number of columns available.
But why?
The maximum layout width is based on 16 columns, only visible on big screens. Laptops will most likely use 8 columns, while phone and tablets will use only 4 columns at a time. Get it?
You need components? We gots them!

Let me guess now.
You like Utility Classes!
This has more space on the top.
This should go to the left.
This should go to the center.
This should go to the right.
What about media?
Let's try it out shall we?
All media is fluid. Here's a kitty cat:
I know.
Icon fonts. Right?
We are using Font Awesome. Cuz awesome.


Learners of English often find two-word verbs a challenge to learn.
A two-word verb is composed of a verb and a preposition, which together form a single
meaning. For
example, the two-word verb, look into means to investigate. The verb and
preposition together form
the meaning.
In this unit's introduction and reading passage, some two-word verbs are used. Some examples of
two-word verbs in this unit are: carry out, carry on, break out, and call upon.
Some two-word verbs, such as carry out, can take a direct object, as in the
sentence,
"UN peacekeepers carry out their mandates."
There are two types of two-word verbs: separable and unseparable two-word verbs.
The above example The direct object can have two possible positions:
| Between the verb and its preposition | After the preposition |
|---|---|
| UN peacekeepers carry their mandates out. | UN peacekeepers carry out their mandates. |
However, if the direct object is a pronoun, it has only one possible position—between the verb and its preposition.
| Correct | Incorrect |
|---|---|
| UN peacekeepers carry them out. | UN peacekeepers carry out them. |
However, some two-word verbs do NOT take direct objects. Some examples of such verbs used in this unit's reading are call upon and break out. In their usage in this unit, both these two-word verbs are inseparable; that is, the verbs and their prepositions must be kept together.


This morning I learned, a tad belatedly, that Hooting Yard has been voted 64th in a list of the Top 100 Liberal Democrat blogs. I confess to being utterly beflummoxed by this news, chiefly because I'm not a Liberal Democrat, have never voted Liberal Democrat, and doubt that I ever would vote Liberal Democrat. In the unlikely event that the “votes” cast in this poll were the result of human agency, as opposed to a fiendish electronic crunching exercise, then I applaud the good sense of those who voted. To reciprocate, here at Hooting Yard we did a quick straw poll to vote on our favourite Liberal Democrat. No prizes for guessing that the winner is, of course, Lembit Opik.
One brief footnote: while we're on the subject of party politics, I am reliably informed that Michael Meacher keeps an A3 copy of the famous Hooting Yard Pontiff Mnemonic on his office wall.


ABOUT US
Pat was walking through Pike Place Market eating a giant cookie when a great idea hit him.  One bite and hospital ride later Pat couldn't get his mind off the delicious taste of salmon and cookie so he set out to make it a reality. Today Pat's Salmon Cookies is a world renowned international franchise.


--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/chess.html ---
I just had a strange idea: can we prove that certain positions in chess are "white to play, checkmate in 3" etc? Maybe this would be a fun project
Sounds like a job for a tactic!
(case exhaustion)
I was thinking about this the other day. I wouldn't mind seeing non-brute-forcy proofs of certain endgame positions.
It sounds like it would take a while to formalize the rules of chess. Maybe "chess is a draw" should be a Fabstracts theorem.
Prove that this position is a draw with white to move, and a win for white with black to move. (And assume the board is n squares long so you can't brute force it) Screenshot-2019-06-11-at-13.02.42.png
ah, the direct opposition
looks like if we do this then we should start setting up a game theory library
A doable example might be to prove the winning strategy for this game. https://chessplus.net/the-opposition-game/
wait am I being an idiot, how can you win if there are only the kings left?
The game isn't chess.
The aim is to get your king into the opposite corner.
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


logLik
returns the current log-likelihood of the fit in a Cyclops model fit object
# S3 method for cyclopsFit logLik(object, ...)
| object | A Cyclops model fit object |
|---|---|
| ... | Additional arguments |
#Generate some simulated data: sim <- simulateCyclopsData(nstrata = 1, nrows = 1000, ncovars = 2, eCovarsPerRow = 0.5, model = "poisson")#> Sparseness = 76.3 %cyclopsData <- convertToCyclopsData(sim$outcomes, sim$covariates, modelType = "pr", addIntercept = TRUE)#> Sorting covariates by covariateId and rowId#Define the prior and control objects to use cross-validation for finding the #optimal hyperparameter: prior <- createPrior("laplace", exclude = 0, useCrossValidation = TRUE) control <- createControl(cvType = "auto", noiseLevel = "quiet") #Fit the model fit <- fitCyclopsModel(cyclopsData,prior = prior, control = control)#> Using cross-validation selector type byRow #> Performing 10-fold cross-validation [seed =<PHONE_NUMBER>] with data partitions of sizes 100 100 100 100 100 100 100 100 100 100 #> Using 1 thread(s) #> Starting var = 0.237 (default) #> Running at Laplace(2.90496) None Grid-point #1 at 0.237 Fold #1 Rep #1 pred log like = 81.7154 #> Running at Laplace(2.90496) None Grid-point #1 at 0.237 Fold #2 Rep #1 pred log like = 84.3058 #> Running at Laplace(2.90496) None Grid-point #1 at 0.237 Fold #3 Rep #1 pred log like = 44.7229 #> Running at Laplace(2.90496) None Grid-point #1 at 0.237 Fold #4 Rep #1 pred log like = 67.5691 #> Running at Laplace(2.90496) None Grid-point #1 at 0.237 Fold #5 Rep #1 pred log like = 102.612 #> Running at Laplace(2.90496) None Grid-point #1 at 0.237 Fold #6 Rep #1 pred log like = -1.50097 #> Running at Laplace(2.90496) None Grid-point #1 at 0.237 Fold #7 Rep #1 pred log like = 92.0468 #> Running at Laplace(2.90496) None Grid-point #1 at 0.237 Fold #8 Rep #1 pred log like = 37.2992 #> Running at Laplace(2.90496) None Grid-point #1 at 0.237 Fold #9 Rep #1 pred log like = 83.6135 #> Running at Laplace(2.90496) None Grid-point #1 at 0.237 Fold #10 Rep #1 pred log like = 30.8871 #> AvgPred = 62.327 with stdev = 31.3759 #> Completed at 0.237 #> Next point at 2.37 with value 0 and continue = 1 #> search[ 0.237 ] = 62.327(31.3759) #> #> Running at Laplace(0.91863) None Grid-point #2 at 2.37 Fold #1 Rep #1 pred log like = 81.7226 #> Running at Laplace(0.91863) None Grid-point #2 at 2.37 Fold #2 Rep #1 pred log like = 84.2611 #> Running at Laplace(0.91863) None Grid-point #2 at 2.37 Fold #3 Rep #1 pred log like = 44.7842 #> Running at Laplace(0.91863) None Grid-point #2 at 2.37 Fold #4 Rep #1 pred log like = 67.5706 #> Running at Laplace(0.91863) None Grid-point #2 at 2.37 Fold #5 Rep #1 pred log like = 102.538 #> Running at Laplace(0.91863) None Grid-point #2 at 2.37 Fold #6 Rep #1 pred log like = -1.49342 #> Running at Laplace(0.91863) None Grid-point #2 at 2.37 Fold #7 Rep #1 pred log like = 91.9862 #> Running at Laplace(0.91863) None Grid-point #2 at 2.37 Fold #8 Rep #1 pred log like = 37.3588 #> Running at Laplace(0.91863) None Grid-point #2 at 2.37 Fold #9 Rep #1 pred log like = 83.6881 #> Running at Laplace(0.91863) None Grid-point #2 at 2.37 Fold #10 Rep #1 pred log like = 30.8629 #> AvgPred = 62.3279 with stdev = 31.3558 #> Completed at 2.37 #> Next point at 23.7 with value 0 and continue = 1 #> search[ 0.237 ] = 62.327(31.3759) #> search[ 2.37 ] = 62.3279(31.3558) #> #> Running at Laplace(0.290496) None Grid-point #3 at 23.7 Fold #1 Rep #1 pred log like = 81.7245 #> Running at Laplace(0.290496) None Grid-point #3 at 23.7 Fold #2 Rep #1 pred log like = 84.2464 #> Running at Laplace(0.290496) None Grid-point #3 at 23.7 Fold #3 Rep #1 pred log like = 44.8033 #> Running at Laplace(0.290496) None Grid-point #3 at 23.7 Fold #4 Rep #1 pred log like = 67.5705 #> Running at Laplace(0.290496) None Grid-point #3 at 23.7 Fold #5 Rep #1 pred log like = 102.514 #> Running at Laplace(0.290496) None Grid-point #3 at 23.7 Fold #6 Rep #1 pred log like = -1.49139 #> Running at Laplace(0.290496) None Grid-point #3 at 23.7 Fold #7 Rep #1 pred log like = 91.9666 #> Running at Laplace(0.290496) None Grid-point #3 at 23.7 Fold #8 Rep #1 pred log like = 37.3773 #> Running at Laplace(0.290496) None Grid-point #3 at 23.7 Fold #9 Rep #1 pred log like = 83.7113 #> Running at Laplace(0.290496) None Grid-point #3 at 23.7 Fold #10 Rep #1 pred log like = 30.8547 #> AvgPred = 62.3278 with stdev = 31.3495 #> Completed at 23.7 #> Next point at 5.15795 with value 62.328 and continue = 0 #> search[ 0.237 ] = 62.327(31.3759) #> search[ 2.37 ] = 62.3279(31.3558) #> search[ 23.7 ] = 62.3278(31.3495) #> #> #> Maximum predicted log likelihood (62.328) estimated at: #> 5.15795 (variance) #> 0.622697 (lambda) #> #> Fitting model at optimal hyperparameter #> Using prior: Laplace(0.622697) None#> [1] 5.157948#> 'log Lik.' -1691.249 (df=3)#> (Intercept) 1 2 #> -4.39513986 -0.04641266 -0.55810190#> Using 1 thread(s)#> covariate 2.5 % 97.5 % evaluations #> [1,] 0 -4.439663 -4.351258 20


|
SGCoreCpp
v1.2.1
SenseGlove C++ API
|
Represents a pose of a Sense Glove exoskeleton. More...
#include <SG_GlovePose.h>
Public Member Functions | |
| SG_GlovePose () | |
| Basic Constructor More... | |
| SG_GlovePose (bool right, std::vector< std::vector< Kinematics::Vect3D > > positions, std::vector< std::vector< Kinematics::Quat > > rotations, std::vector< std::vector< Kinematics::Vect3D > > jointAngles) | |
| Creates a new instance of a SG_GlovePose More... | |
| ~SG_GlovePose () | |
| Basic Destructor More... | |
| std::vector< Kinematics::Vect3D > | ThimblePositions () |
| The position of the tip of the 'thimbles', the furthest link on each glove link. More... | |
| std::vector< Kinematics::Quat > | ThimbleRotations () |
| summary> Sum of the Sensor angles in each (xyz) direction. "Total Pronation / Flexion / Abduction" More... | |
| std::vector< Kinematics::Vect3D > | TotalGloveAngles () |
| std::vector< Kinematics::Vect3D > | CalculateFingerTips (SG_HandProfile &profile) |
| Calculate fingertip positions based on a user profile. More... | |
| std::vector< Kinematics::Vect3D > | CalculateFingerTips (std::vector< Kinematics::Vect3D > &fingerOffsets) |
| Calculate fingertip positions, knowing the offset between thimble and fingertips. More... | |
| bool | Equals (SG_GlovePose other) |
| Returns true if this glove pose equals another. More... | |
| std::string | ToString (bool shortFormat=true) |
| Returns a user-friendly string representation of this GlovePose for reporting. More... | |
| std::string | Serialize () |
| Serialize this GlovePose into a string representation More... | |
Static Public Member Functions | |
| static SG_GlovePose | IdlePose (SG_GloveInfo glove) |
| Returns an idle pose for the Sense Glove if no data can be found. More... | |
| static SG_GlovePose | Deserialize (std::string serializedString) |
Public Attributes | |
| std::vector< std::vector< Kinematics::Vect3D > > | jointPositions |
| Positions of each glove joint, relative to the Glove's Origin. More... | |
| std::vector< std::vector< Kinematics::Quat > > | jointRotations |
| Quaternion rotation of each glove joint, relative to the Glove Origin. More... | |
| std::vector< std::vector< Kinematics::Vect3D > > | gloveAngles |
| Glove joint angles in euler notation, relative to the last segment. More... | |
| bool | isRight |
Represents a pose of a Sense Glove exoskeleton.
| SGCore::SG::SG_GlovePose::SG_GlovePose | ( | ) |
Basic Constructor
| SGCore::SG::SG_GlovePose::SG_GlovePose | ( | bool | right, |
| std::vector< std::vector< Kinematics::Vect3D > > | positions, | ||
| std::vector< std::vector< Kinematics::Quat > > | rotations, | ||
| std::vector< std::vector< Kinematics::Vect3D > > | jointAngles | ||
| ) |
Creates a new instance of a SG_GlovePose
| SGCore::SG::SG_GlovePose::~SG_GlovePose | ( | ) |
Basic Destructor
| std::vector< Kinematics::Vect3D > SGCore::SG::SG_GlovePose::CalculateFingerTips | ( | SG_HandProfile & | profile | ) |
Calculate fingertip positions based on a user profile.
| std::vector< Kinematics::Vect3D > SGCore::SG::SG_GlovePose::CalculateFingerTips | ( | std::vector< Kinematics::Vect3D > & | fingerOffsets | ) |
Calculate fingertip positions, knowing the offset between thimble and fingertips.
|
static |
| bool SGCore::SG::SG_GlovePose::Equals | ( | SG_GlovePose | other | ) |
Returns true if this glove pose equals another.
|
static |
Returns an idle pose for the Sense Glove if no data can be found.
| std::string SGCore::SG::SG_GlovePose::Serialize | ( | ) |
Serialize this GlovePose into a string representation
summary> Deserialize a HandProfile back into useable values.
summary> Deserialize a GlovePose back into useable values.
| std::vector< Kinematics::Vect3D > SGCore::SG::SG_GlovePose::ThimblePositions | ( | ) |
The position of the tip of the 'thimbles', the furthest link on each glove link.
summary> The (quaternion) rotation of the 'thimbles', the furthest link on each link.
| std::vector< Kinematics::Quat > SGCore::SG::SG_GlovePose::ThimbleRotations | ( | ) |
summary> Sum of the Sensor angles in each (xyz) direction. "Total Pronation / Flexion / Abduction"
| std::string SGCore::SG::SG_GlovePose::ToString | ( | bool | shortFormat = true | ) |
Returns a user-friendly string representation of this GlovePose for reporting.
summary> Serialize this HandProfile into a string representation
| std::vector< Kinematics::Vect3D > SGCore::SG::SG_GlovePose::TotalGloveAngles | ( | ) |
| std::vector< std::vector< Kinematics::Vect3D > > SGCore::SG::SG_GlovePose::gloveAngles |
Glove joint angles in euler notation, relative to the last segment.
Essentially sensor angles, though placed in their proper xyz notation
summary> Whether or not this Glove Pose was created for be a right- or left hand.
| bool SGCore::SG::SG_GlovePose::isRight |
| std::vector< std::vector< Kinematics::Vect3D > > SGCore::SG::SG_GlovePose::jointPositions |
Positions of each glove joint, relative to the Glove's Origin.
| std::vector< std::vector< Kinematics::Quat > > SGCore::SG::SG_GlovePose::jointRotations |
Quaternion rotation of each glove joint, relative to the Glove Origin.


Question 1
The University should only contract with businesses that have demonstrated sustainable practices.
Strongly agree
Agree
Disagree
Don't care
How important is this issue to you?
Question 2
To address inadequate resources for mental health issues, the University should fund Boynton Health Services using tuition instead of student services fees.
Very Not at all
Question 3
University athletes should be compensated with stipends.
Question 4
Professors across campus should make use of trigger warnings in order to warn students of potentially triggering class materials.
Question 5
The U-Pass should be universal and paid for using student services fees.
Question 6
Students should have access to full course descriptions and syllabi before registration.
Question 7
The affirmative consent policy is an effective tool for approaching the issue of campus sexual assault.
Question 8
Efforts need to be directed toward dealing with issues of toxic masculinity, inclusion, and diversity in the University's greek community.
Question 9
The University needs to invest in constructing more residential halls in order to provide adequate housing for first- and second-year students.
Question 10
UDS should only provide fair-trade and non-GMO food from local and ecologically friendly sources.
Question 11
Extremely controversial speakers should be allowed to host events on campus.
Question 12
The University should continue its stem cell research efforts.
Question 13
The University's faculty members should unionize.
Question 14
It should be mandatory for UMPD to be involved in involved in investigating student complaints of sexual assault.
Question 15
University of Minnesota students should be required to take at least one course from an ethnic studies department.


Bryan Liang
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\(f(t)^1\) is the daily time budget distribution for public transport.
\(^1\) Robert Kölbl, Dirk Helbing. Energy laws in human travel behaviour. New Journal of Physics 5, 48 IOP Publishing, 2003.
Sociality Score:
Consider the populations inside the Isochrone a time \(t\) computed in \(P\):
\begin{equation}
s(t,P) = \sum_{i \mid t_i(P) < t} p(h_i),
\end{equation}
we sum over all the hexagons with time \(t_i\) less than \(t\) and \(p(h_i)\) is the population within \(h_i\).
The future of public transports in cities
Bad ending for my current research, but happing ending for public transport in the cities?
Cars per 1000 inhabitants
Italy togheter with USA has the highest level of car ownership.
Italy
cars
Europe
cars
Rome
800
Paris
225
Milan
596
London
298
Turin
600
Barcellona
350
Catania
700
Berlin
297
Average person per car 1.2
95% of the time the cars are parked
Self driving cars (they are around us)
No property - No Parking
Boost in efficency
Sharing Trips
from taxy sharing to trip sharing\(^{1,2,3}\)
At least 50% less cars circulating
Public transport on demand
shrinking of the cost urban transportation of almost 10 times.
1. P. Santi, G. Resta, M. Szell, S. Sobolevsky, S. Strogatz, C. Ratti. Taxi pooling in New York City: a network-based approach to social sharing problems (2013).


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|
Click
|
Manages Click name databases. More...
Public Types | |
| enum | DBType { T_NONE = 0, T_SCHEDULEINFO = 0x00000001, T_ANNOTATION = 0x00000002, T_SCRIPT_INSN = 0x00000003, T_SIGNO = 0x00000004, T_SPINLOCK = 0x00000005, T_ETHERNET_ADDR = 0x01000001, T_IP_ADDR = 0x04000001, T_IP_PREFIX = 0x04000002, T_IP_PROTO = 0x04000003, T_IPFILTER_TYPE = 0x04000004, T_TCP_OPT = 0x04000005, T_IPREWRITER_PATTERN = 0x04000006, T_ICMP_TYPE = 0x04010000, T_ICMP_CODE = 0x04010100, T_IP_PORT = 0x04020000, T_TCP_PORT = 0x04020006, T_UDP_PORT = 0x04020011, T_IP_FIELDNAME = 0x04030000, T_ICMP_FIELDNAME = 0x04030001, T_TCP_FIELDNAME = 0x04030006, T_UDP_FIELDNAME = 0x04030011, T_IP6_ADDR = 0x06000001, T_IP6_PREFIX = 0x06000002 } |
| Known name database types. More... | |
Public Member Functions | |
| NameInfo () | |
| Construct a NameInfo element. More... | |
| ~NameInfo () | |
| Destroy a NameInfo object. More... | |
Static Public Member Functions | |
| static void | static_initialize () |
| Static initialization for NameInfo. More... | |
| static void | static_cleanup () |
| Static cleanup for NameInfo. More... | |
| static NameDB * | getdb (uint32_t type, const Element *context, size_t value_size, bool create) |
| Find or create a name database. More... | |
| static void | installdb (NameDB *db, const Element *context) |
| Install a name database. More... | |
| static void | uninstalldb (NameDB *db) |
| Uninstall a name database. More... | |
| static bool | query (uint32_t type, const Element *context, const String &name, void *value_store, size_t value_size) |
| Query installed databases for name. More... | |
| static bool | query_int (uint32_t type, const Element *context, const String &name, int32_t *value_store) |
| Query installed databases for name, returning a 32-bit integer value. More... | |
| static bool | query_int (uint32_t type, const Element *context, const String &name, uint32_t *value_store) |
| static String | revquery (uint32_t type, const Element *context, const void *value, size_t value_size) |
| Query installed databases for value. More... | |
| static String | revquery_int (uint32_t type, const Element *context, int32_t value) |
| Query installed databases for a 32-bit integer value. More... | |
| static bool | define (uint32_t type, const Element *context, const String &name, const void *value, size_t value_size) |
| Define name to equal value in the installed databases. More... | |
| static bool | define_int (uint32_t type, const Element *context, const String &name, int32_t value) |
| Define name to equal 32-bit integer value in the installed databases. More... | |
Manages Click name databases.
NameInfo is the user interface to Click's name databases, a general mechanism for mapping names to values. NameInfo and NameDB implement generally useful properties like names local to a compound element context.
Every name database maps names, which are nonempty strings, to values, which are sequences of bytes. A database is identified by its type, which indicates the kind of name stored in the database, and, optionally, its compound element context, which is a pair of router and element name prefix. The database is used for queries that take place in the given context. A query bubbles up through the databases, starting with the most specific context and getting more general, until it succeeds. A database stores values with a fixed size; it is an error to query a database with the wrong size.
Many common types are defined in the NameDB::DBType enumeration, but NameInfo allows arbitrary other types to be added at run time.
Here's an example of how to query NameInfo:
Many elements also add their own databases to NameInfo; see, for example, the IPNameInfo or IPFilter elements for examples.
| enum NameInfo::DBType |
Known name database types.
| Enumerator | |
|---|---|
| T_NONE | Nonexistent names database. |
| T_SCHEDULEINFO | ScheduleInfo database. |
| T_ANNOTATION | Packet annotation database. |
| T_SCRIPT_INSN | Script instruction names database. |
| T_SIGNO | User-level signal names database. |
| T_SPINLOCK | Spinlock names database. |
| T_ETHERNET_ADDR | Ethernet address names database. |
| T_IP_ADDR | IP address names database. |
| T_IP_PREFIX | IP prefix names database. |
| T_IP_PROTO | IP protocol names database. |
| T_IPFILTER_TYPE | IPFilter instruction names database. |
| T_TCP_OPT | TCP option names database. |
| T_IPREWRITER_PATTERN | IPRewriterPattern database. |
| T_ICMP_TYPE | ICMP type names database. |
| T_ICMP_CODE | ICMP code names database. |
| T_IP_PORT | Starting point for IP per-protocol port names databases. |
| T_TCP_PORT | TCP port names database. |
| T_UDP_PORT | UDP port names database. |
| T_IP_FIELDNAME | Starting point for IP per-protocol field names databases. |
| T_ICMP_FIELDNAME | ICMP field names database. |
| T_TCP_FIELDNAME | TCP field names database. |
| T_UDP_FIELDNAME | UDP field names database. |
| T_IP6_ADDR | IPv6 address names database. |
| T_IP6_PREFIX | IPv6 prefix names database. |
| NameInfo::NameInfo | ( | ) |
Construct a NameInfo element.
Users never need to call this.
| NameInfo::~NameInfo | ( | ) |
|
static |
|
static |
|
static |
Find or create a name database.
| type | database type |
| context | compound element context |
| value_size | size of values stored in database |
| create | whether to create a DynamicNameDB if no database exists |
Returns an installed name database matching type and context. (If context is non-null, then the database matches the implied router and compound element context. Otherwise, the database is the unique global database for the given type.) If create is true, and no database exists exactly matching type and context, then a DynamicNameDB is created and installed with that type, context, and value_size. Otherwise, the search bubbles up through the prefixes of context until an installed database is found.
Returns null if no installed database is found. value_size must match the value size in the returned database.
Most users will use query() and define() directly, not call getdb().
Install a name database.
| db | name database |
| context | compound element context |
Installs the given name database for the compound element context implied by context. (If context is non-null, then the database is installed for the implied router and compound element context. If it is null, the database is installed globally.) The query() and define() operations apply only to installed databases.
It is an error to install a database that has already been installed. It is also an error to install a database for a compound element context that already has a different database installed. An installed NameDB is automatically destroyed when its containing NameInfo is destroyed (for example, when context's router is destroyed).
|
static |
Uninstall a name database.
| db | name database |
Undoes the effects of installdb(). The given database will no longer be used for query() and define() operations.
|
static |
Query installed databases for name.
| type | database type |
| context | compound element context |
| name | name to look up |
| value_store | value storage |
| value_size | size of value storage |
Queries all installed type databases that apply to the compound element context, returning the most specific value matching name. The value is stored in value_store. The installed databases must have the given value_size.
|
static |
Query installed databases for name, returning a 32-bit integer value.
| type | database type |
| context | compound element context |
| name | name to look up |
| value_store | value storage |
Queries all installed type databases that apply to the compound element context, returning the most specific value matching name. The value is stored in value_store. The installed databases must have a value size of 4.
If no matching name is found, query_int checks whether name unparses into a 32-bit integer value (for example, "30"). If so, *value_store is set to the corresponding integer and true is returned. Otherwise, false is returned.
|
static |
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
|
static |
Query installed databases for value.
| type | database type |
| context | compound element context |
| value | points to value to look up |
| value_size | size of value |
Queries all installed type databases that apply to the compound element context, returning the name in the most specific database whose value matches value, or the empty string if the relevant databases don't support reverse queries or no such value exists. The installed databases must have the given value_size.
|
inlinestatic |
Query installed databases for a 32-bit integer value.
| type | database type |
| context | compound element context |
| value | value to look up |
Queries all installed type databases that apply to the compound element context, returning the name in the most specific database whose value matches value, or the empty string if the relevant databases don't support reverse queries or no such value exists. The installed databases must have value size 4.
|
inlinestatic |
Define name to equal value in the installed databases.
| type | database type |
| context | compound element context |
| name | name to define |
| value | points to defined value |
| value_size | size of value |
Defines the given name to value in the installed type database with compound element context. If no database exists exactly matching that type and context, a new DynamicNameDB is created and installed with those values (and the given value_size). A name might not be defined if the existing database for that type and context doesn't support definitions, or if no new database can be created. If any database exists, it must match the given value_size.
|
inlinestatic |
Define name to equal 32-bit integer value in the installed databases.
| type | database type |
| context | compound element context |
| name | name to define |
| value | defined value |
Defines the given name to value in the installed type database with compound element context. If no database exists exactly matching that type and context, a new DynamicNameDB is created and installed with those values (and value size 4). A name might not be defined if the existing database for that type and context doesn't support definitions, or if no new database can be created. If any database exists, it must have value size 4.


Last Name
First Name
Address
City
State
Zip/Postal Code
Country
Albania
Bulgaria
Some other country
Yet another country
OK this is the last one
Phone (country code, area code, number)
(+
)
-
E-mail
Birth date
Month
Day
Year (4 digit)
Gender
Male
Female
Undecided
Starting date
Spring 2006
Summer 2006
Comments/Questions


This example shows how to use the DropboxTeam class and the .actAsUser() method, to retreive a Dropbox class that is acting as a specific user on the team.
Open your console to see the results.


|
Custard
prerelease
C++ Goodies for Nintendo DS Homebrew Development
|
This structure is a bit field overlay for the display control registers. More...
#include <custard/display.hpp>
This structure is a bit field overlay for the display control registers.
You should not use _dispcnt_overlay directly. Use the derived classes custard::display::config and custard::display::main_config instead, as these provide convenient methods for configuring overlays and updating the display control registers. However, you should still expect to access some of the fields inherited from _dispcnt_overlay directly.
The NDS has two display control (DISPCNT) registers, one for each 2D rendering engine. The libnds macros for these registers are REG_DISPCNT and REG_DISPCNT_SUB. Each register is 32 bits and controls the function of its corresponding rendering engine. The registers contain the same fields, but some fields are only used by the main (A) engine.
The _dispcnt_overlay structure contains a member for each of the fields present in the DISPCNT registers. The member mask encapsulates all of the fields in a 32-bit unsigned integer that may be directly read from, or written to, either of the DISPCNT registers.
Public Attributes | |
| union { | |
| struct { | |
| uint32_t bg_mode: 3 | |
| BG Mode: Assigns graphics modes to all backgrounds.  More... | |
| uint32_t vram_block: 2 | |
| VRAM bank in [A..D] to use for display capture or frame buffer display mode (MAIN ENGINE ONLY) More... | |
| uint32_t tile_obj_1d_boundary: 2 | |
| Tile Sprite 1D Stride: {32,64,128,256}B. | |
| uint32_t bmp_obj_1d_boundary: 1 | |
| Bitmap Sprite 1D Stride: 0=128B, 1=256B. | |
| uint32_t hblank_oam_access: 1 | |
| Enable access to OAM during horizontal blanking. | |
| uint32_t char_base: 3 | |
| Additional global tile base offset as multiple of 64K (MAIN ENGINE ONLY) | |
| uint32_t screen_base: 3 | |
| Additional global map base offset as multiple of 64K (MAIN ENGINE ONLY) | |
| uint32_t bg_ext_palettes: 1 | |
| Enable background extended palettes. | |
| uint32_t obj_ext_palettes: 1 | |
| Enable sprite extended palettes. | |
| } | |
| uint32_t mask | |
| }; | |
| uint32_t custard::display::_dispcnt_overlay::bg_mode |
BG Mode: Assigns graphics modes to all backgrounds.
| Value | BG0 & BG1 | BG2 | BG3 |
|---|---|---|---|
| 0 | Text | Text | Text |
| 1 | Text | Text | Affine |
| 2 | Text | Affine | Affine |
| 3 | Text | Text | Extended |
| 4 | Text | Affine | Extended |
| 5 | Text | Extended | Extended |
| 6 * | - | Large Bitmap | - |
(*) Only a 512K 8bpp rotoscale bitmap and 3D engine output may be displayed (MAIN ENGINE ONLY)
| uint32_t custard::display::_dispcnt_overlay::display_mode |
Display enable and mode selection.
| Value | Function |
|---|---|
| 0 | None (screen is white) |
| 1 | Normal graphics display (backgrounds, sprites, 3D) |
| 2 | Read frame buffer from VRAM (MAIN ENGINE ONLY) |
| 3 | Transfer frame buffer from main RAM (MAIN ENGINE ONLY) |
| uint32_t custard::display::_dispcnt_overlay::vram_block |
VRAM bank in [A..D] to use for display capture or frame buffer display mode (MAIN ENGINE ONLY)
Values: 0=A, 1=B, 2=C, 3=D
The selected bank must be mapped to its LCDC address.


|
|
|
Signalling cascade stimulated by the TCR showing the key protein components. Reprinted from Immunology 113, T. Razzaq, P. Ozegbe, E. Jury, P. Sembi, N. Blackwell and P. Kabouridis, Regulation of T-cell receptor signalling by membrane microdomains, PP.413-426, 2004, PMID: 15554919. |
The TCR is a transmembrane heterodimer composed of an a and a b chain, but is insufficient on its own to transduce a signal, in part due to their short cytoplasmic tails. TCRs are in close contact with CD3 (composed of subunits CDe(2)-CDg-CDd) and z (also called zeta, or CDz) transmembrane proteins, which together form the TCR complex (pictured above). The CD3 and z proteins are responsible for transmitting the signal into the cell via conserved motifs (immunoreceptor tyrosine-based activation motif, or ITAM) in their cytoplasmic domains, which act as tyrosine kinase substrates, and once phosphorylated, as binding sites for other kinases. The TCR complex is coupled to cytoplasmic tyrosine kinases (such as from the Src (Lck) and Syk (Zap-70) families), which act in conjunction with a myriad of adaptor proteins to initiate signals that bring about T cell activation.
However, antigen binding does not always mount an immune response; for instance as occurs with TCR binding to self-antigens which elicits immune tolerance. To mount an immunological response, the T cell needs to receive a second signal from an antigen-presenting cell in the form of a costimulatory molecule. Costimulatory molecules act through different T cell receptors, such as the CD28 and TNFR (tumour necrosis factor receptor) families, producing a second signal that induces T-cell activation and proliferation. The CD28 and TNFR costimulatory receptors possibly exert their effect through promoting more efficient signalling by concentrating the kinases and substrates that are required to initiate a signal. Many different costimulatory molecules have been identified, some of which can have a negative effect on signal initiation, such as B and T lymphocyte attenuator (BTLA).
Changes in the activity of T cell signalling pathways can lead to pathological conditions, such as autoimmunity (breaking of self-tolerance) and AIDS. HIV binds to CD4 molecules, enabling them to infect CD4+ T cells, resulting in the reduction of both infected and uninfected T cells.


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label
- Variable in class fsb.ast.
Statement
lamportCritSec
- Static variable in class fsb.parser.
Main
last
- Variable in class fsb.semantics.eagerpso.
SharedResVal.AbstractBuffer
last
- Variable in class fsb.semantics.empeagerpso.
SharedResVal.AbstractBuffer
lastMem
- Variable in class fsb.explore.
SBState
LAZY_COPY
- Static variable in class fsb.utils.
Options
left
- Variable in class fsb.ast.
AssertComparsionBool
left
- Variable in class fsb.ast.
AssertComplexBool
left
- Variable in class fsb.ast.
ComparsionBool
left
- Variable in class fsb.ast.
ComplexAritExpr
left
- Variable in class fsb.ast.
ComplexBool
LEFTBRACE
- Static variable in class fsb.parser.
sym
LEFTCURLY
- Static variable in class fsb.parser.
sym
LEFTPAREN
- Static variable in class fsb.parser.
sym
length()
- Method in class ags.constraints.
BitSet
Returns the logical number of bits actually used by this bit set.
length()
- Method in class ags.graph.
Trace
LESS
- Static variable in class fsb.parser.
sym
Lexer
- Class in
fsb.parser
This class is a scanner generated by
JFlex
1.4.3 on 4/16/12 8:26 PM from the specification file
blender.jflex
Lexer(Reader)
- Constructor for class fsb.parser.
Lexer
Creates a new scanner There is also a java.io.InputStream version of this constructor.
Lexer(InputStream)
- Constructor for class fsb.parser.
Lexer
Creates a new scanner.
lexer
- Variable in class fsb.parser.
parser
lhs
- Variable in class ags.constraints.
AtomicPredicateDictionary.Coords
lhsID
- Variable in class ags.constraints.
LocationAtomicPredicate
limit
- Variable in class fsb.semantics.pso.
PSOSemantics
Load
- Class in
fsb.ast
Load(SharedVal, String)
- Constructor for class fsb.ast.
Load
LOAD
- Static variable in class fsb.parser.
sym
local
- Variable in class fsb.ast.
AssertLocal
local
- Variable in class fsb.ast.
Declarations
local
- Variable in class fsb.ast.
LocalExpr
LOCAL
- Static variable in class fsb.parser.
sym
LOCAL_NOP
- Static variable in class fsb.utils.
Options
LocalExpr
- Class in
fsb.ast
LocalExpr(String)
- Constructor for class fsb.ast.
LocalExpr
locals
- Variable in class fsb.explore.
SBState
LocationAtomicPredicate
- Class in
ags.constraints
A LocationAtomicPredicate is of the form [id1, id2].
LocationAtomicPredicate(int, int)
- Constructor for class ags.constraints.
LocationAtomicPredicate
lock
- Static variable in class ags.constraints.
BDDFormula
LONG_MASK
- Static variable in class ags.constraints.
BitSet
A common mask.
low
- Variable in class ags.constraints.
IfFormula
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The following tutorial shows in brief steps how to setup the Posting of Twitter-Notifications (e.g. Flood-Warnings).
Hint: A Twitter Account is needed to publish Notifications. You can create one here.
Go to the Twitter-Application-Management area and create a new Application
Click here to create a new Twitter-Application.
Enter all necessary informations in the folowing dialog
Now, after you successfully created an application you will receive access to Application keys and Access Tokens (avaiblibe under “Keys and Access Tokens”
in the applications options.
Finally add the Keys and Tokens to your WoT-Acount:
Login into your account and click the button “Edit Profile Settings”.
In the following dialog you can enter your keys and tokens as shown in your Twitter Account.


13 Dock Workers (Regulation of Employment) Act, 1948 14 Electricity (Supply) Act, 1948 15 Employees State Insurance Act, 1948 16 Factories Act, 1948 17 Industrial Finance Corporation Act, 1948 18 Banking Regulatio Act, 1949 19 Representation of the People Act, 1950 20 Telegraph Wires (Unlawful Possession) Act, 1950 21 Industries (Development and Regulation) Act, 1951 22 The Marking of Heavy Packages Act, 1951 23 The State Financial Corporations Act, 1951 24 Employees Provident Funds and Miscellaneous Provisions Act, 1952 25 Notaries Act, 1952 26 Delivery of Books and Newspapers (Public Libraries) Act, 1954 27 Essential Commodities Act, 1955 28 Companies Act, 1956 29 Newspaper (Price and Page) Act, 1956 30 Securities Contracts (Regulation) Act, 1956 31 Mines and Minerals (Development and Regulation) Act, 1957 32 Delhi Rent Control Act, 1958 33 Children Act, 1960 34 Geneva Conventions Act, 1960 35 Apprentices Act, 1961 36 Deposit Insurance and Credit Guarantee Corporation Act, 1961 37 Motor Transport Workers Act, 1961 38 Customs Act, 1962 39 The Warehousing Corporations Act, 1962 40 The Unit Trust of India Act, 1963 41 The Food Corporation Act, 1964 42 Payment of Bonus Act, 1965 43 Monopolistic and Restrictive Trade Practices Act, 1969 44 Contract Labour (Regulation and Abolition) Act, 1970 45 Antiquities and Art Treasures Act, 1972 46 Architects Act, 1972 47 Limestone and Dolomite Mines Labour Welfare Fund Act, 1972 48 Payment of Gratuity Act, 1972 49 Wild Life (Protection) Act, 1972 50 Foreign Exchange Regulation Act, 1973 51 Esso (Acquisition of Undertakings in India) Act, 1974 52 Water (Prevention and Control of Pollution) Act, 1974 53 Burmah shell (Acquisitio of Undertakings in India) Act, 1976 54 Equal Remuneration Act, 1976 55 Iron Ore Mines, Manganese Ore Mines and Chrome Ore Mines Labour Welfare Cess Act, 1976 56 Standards of Weights and Measures Act, 1976 57 Urban Land (Ceiling and Regulation) Act, 1976 CRM-790-MA-2010 final - 87 -
58 Caltex [Acquisition of Shares of Caltex Oil Refining (India) Limited and of the Undertakings in India of Caltex (India) Limited] Act, 1977 59 Water (Prevention and Control of Pollution) Cess Act, 1977 60 Bolani Ores Limited (Acquisition of Shares) and Miscellaneous Provisions Act, 1978 61 Inter-State Migrant Workmen (Regulation of Employment and Conditions of Service) Act, 1979 62 Air (Prevention and Control of Pollution) Act, 1981 63 British India Corporation Limited (Acquisition of Shares) Act, 1981 64 Burmah Oil Company ([acquisition of shares of Oil India Limited and of the Undertaking in India of Assam Oil Company limited and the Burmah Oil Company (India Trading ) Limited ] Act ,1981 65 Cine Workers and Cinema Theatre Workers (Regulation of Employment) Act, 1981 66 Dangerous Machines (Regulation) Act, 1983 67 Indian Veterinary Council Act, 1984 68 Narcotic Drugs and Psychotropic Substances Act, 1985 69 Sick Industrial Companies (Special Provisions) Act, 1985 70 Environment (Protection) Act, 1986 71 National Housing Bank Act, 1987 72 Railways Act, 1989 73 Public Liability Insurance Act, 1991 74 Infant Milk Substitutes, Feeding Bottles and Infant Foods (Regulation of Production, Supply and Distribution) Act, 1992 75 Rehabilitation Council of India Act, 1992 76 The Securities And Exchange Board of India Act, 1992 77 Employment of Manual Scavengers and Construction of Dry Latrines (Prohibition) Act, 1993 78 Airports Authority of India Act, 1994 79 Pre-Conception and Pre-Natal Diagnostic Techniques (Prohibition of Sex Selection) Act, 1994 80 Transplantation of Human Organs and Tissues Act, 1994 81 Cable Television Networks (Regulation) Act, 1995 82 Wakf Act, 1995 83 Building and Other Construction Workers Welfare Cess Act, 1996 84 Telecom Regulatory Authority of India Act, 1997 85 Electricity Regulatory Commissions Act, 1998 86 Geographical Indications of Goods (Registration and Protection) Act, 1999 87 Trade Marks Act, 1999 88 Information Technology Act, 2000 89 The Semiconductor Integrated Circuits Layout-Design Act, 2000 90 Electricity Act, 2003 91 Coastal Aquaculture Authority Act, 2005 92 Credit Information Companies (Regulation) Act, 2005 93 Disaster Management Act, 2005 94 Government Securities Act, 2006 95 The Petroleum and Natural Gas Regulatory Board Act, 2006 96 Payment and Settlement Systems Act, 2007 97 Warehousing (Development and Regulation) Act, 2007 98 Airports Economic Regulatory Authority of India Act, 2008 99 Collection of Statistics Act, 2008 100 National Green Tribunal Act, 2010 101 The Factoring Regulation Act, 2011


Hey! I am an interdiscplinary scientist in the making. From nanotechnology to high-throughput molecular biology and bioinformatics, I am interested in many things. I am inclined to a research-driven career, combining wet-lab, engineering, and computational approaches for understanding why one would think of puppies when specifically asked to not to think about them (other adorable animals are just as applicable).
On-boarding and assisting customers with BC Platforms' lines of products. Pipeline building (DNAseq, RNAseq). Application installation on on-prem VM or cloud (Google Cloud, Microsoft Azure).
Pipeline investigation, development, and validation for high throughput molecular biology testing (Prodia Genomics), including DNA microarray for polygenic risk score disease risk estimation and NGS-based non-invasive prenatal testing of chromosomal aneuploidies.
Master's thesis project undertaken at in vitro neural systems lab.
View AbstractA group project with the goal of investigating differentially expressed genes across 4 disease state progressions. Conducted at KTH Royal Institute of Technology.
View ProjectIndividual research project comparing support vector machine, decision tree, and random forest methods. Undertaken at Stockholm University.
View Project


--- layout: null section-type: about title: About me --- ## Self-introduce 640 KB outht to be enough for anybody. -- Bill Gates
Abel Zhu


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I am a principal software engineer at Samsung Research, Samsung Electronics. Currently, I am working on building and optimizing large scale high-performance computing (HPC) systems for deep learning (DL) applications.
My research interests are in DL technologies, in particular, how to efficiently train massive DL datasets in a cluster of HPC systems. In the past, I worked on Web technologies for memory-constraint devices such as TV and smart watches.
I obtained my Ph.D in Computer Science in 2010, and a B.Eng in Software Engineering in 2005 both from The University of New South Wales. I started my industry career as a software engineer at Software R&D Center (which has now become Samsung Research) in 2013, after a two years of research fellow appointment at KAIST.


Introduction
Introduction
Infrastructure development is the way to fast forward a country’s economy. To realize one’s design is of the utmost importance for it leads to a better engineering mind. Sristi 16 provides an opportunity to do the aforesaid. Get ready to use your creative genius innovation and energy to Bridge The Gap.
Rules
Prelims
•Each team should consist of four members with team name.
•Teams should collect question paper from helpdesk only, nowhere else.
•Teams have to submit their answer sheet within one hour of problem declaration to the helpdesk only, nowhere else.
•Teams are requested to bring their own pen, calculator and rough sheet.
•Negative marks would be applicable as per question rule.
•Some teams will be qualified for finals on the basis of their ranking.
•Teams should collect question paper from helpdesk only, nowhere else.
•Teams have to submit their answer sheet within one hour of problem declaration to the helpdesk only, nowhere else.
•Teams are requested to bring their own pen, calculator and rough sheet.
•Negative marks would be applicable as per question rule.
•Some teams will be qualified for finals on the basis of their ranking.
Finals
•Finals will be an over-night extravaganza.
•Timing for finals will be announced at help desk.
•Qualified teams would be provided with required materials from the coordinators. Else materials would not be entertained.
•Problem statement would be given at the venue before the finals start.
•Teams have to carry out their planning and execution within a certain time limit which would be announced at the help desk.
•Bonus marks will be provided for finishing early. (Bonus marks will be provided as per problem statement).
•First-aid kit will be available at the venue in case of emergency.
•Timing for finals will be announced at help desk.
•Qualified teams would be provided with required materials from the coordinators. Else materials would not be entertained.
•Problem statement would be given at the venue before the finals start.
•Teams have to carry out their planning and execution within a certain time limit which would be announced at the help desk.
•Bonus marks will be provided for finishing early. (Bonus marks will be provided as per problem statement).
•First-aid kit will be available at the venue in case of emergency.
Prize
Certificate Policy
1. Certificate of Excellence will be provided to the participants who qualify for the FINALS.
2. Certificate of Participation will be provided to all the participants taking part in the event.
3. The teams which get disqualified due to disobeying any of the rules provided will not be entertained with any kind of certification.
Prize money worth: will be updated soon


Due Monday, 09 March at 5 PM. Submissions may be printed or digital. Printed copies can be given to me during class, or dropped off at the Biology Office (Arey 101), or under my office door (Olin 216).If digital, please send as a .pdf.
Otto and Day wrote about applications mathematical modeling in understanding HIV. One paper, by Phillip (1996), used a mathematical model to test a hypothesis and come to a counterintuitive conclusion about the immune systems’s role in reducing HIV concentration within infected people. After reading the chapter, learning how to simulate (i.e., solve) a SIR model in R, I asked for you to try to recreate their model. I would like for you to do that in this problem. If you save your ode()
output to hiv_out
—like this hiv_out <- ode(
but continue with the rest of the code that goes in ode()
—you can paste the code below to recreate their figures more closely (with axes on a log scale, multiple curves per plot, and multiple y axes).
CD4 <- 1000*(1 - parm_vals["tau"]) + hiv_out[,2] + hiv_out[,3] + hiv_out[,4]
par(mar = c(4.5, 4.5, 1, 4.5), mfrow = c(1, 2))
plot(x = hiv_out[,1], y = CD4, type = "l", las = 1, xlab = "Days from infection", ylab = "CD4 lymphocytes", ylim = c(0, 1200), col = "purple")
par(new = T)
plot(x = hiv_out[,1], y = log(x = hiv_out[,5], base = 10), type = "l", xaxt = "n", yaxt = "n", xlab = "", ylab = "", col = "orange", ylim = c(-1, max(log(x = hiv_out[,5], base = 10))))
axis(side = 4, las = 1)
mtext(side = 4, text = bquote("Free virons, V ("~log[10]~")"), line = 2.25)
legend(x = "topright", bty = "n", col = c("purple", "orange"), lty = 1, legend = c("Total CD4", "Virons"), cex = 0.75)
plot(x = hiv_out[,1], y = hiv_out[,2], type = "l", xlab = "Days from infection", ylab = "R", col = "black", las = 1, ylim = c(0, 250))
par(new = T)
plot(x = hiv_out[,1], y = log(x = hiv_out[,3], base = 10), type = "l", xaxt = "n", yaxt = "n", xlab = "", ylab = "", col = "red", ylim = c(-1, max(log(x = c(hiv_out[,3], hiv_out[,4]), base = 10))))
lines(x = hiv_out[,1], y = log(x = hiv_out[,4], base = 10), col = "blue")
axis(side = 4, las = 1)
mtext(side = 4, bquote("L and E ("~log[10]~")"), line = 2.75)
legend(x = "topright", bty = "n", col = c("black", "red", "blue"), lty = 1, legend = c("Susceptible (R)", "Latent (L)", "Infectious (E)"), cex = 0.75)
Also remember that you can change the duration of the simulation. Include a figure of each (4 in total).
Below is some data I acquired for COVID-19:
first_date_I <- as.Date("2020-01-25")
first_date_R <- as.Date("2020-02-01")
last_date <- as.Date("2020-02-29")
infec_seq <- seq(from = first_date_I, to = last_date, by = 1)
rec_seq <- seq(from = first_date_R, to = last_date, by = 1)
infec <- c(1438, 2118, 2927, 5578, 6165, 8235, 10151, 12281, 16804, 19884, 24027, 27585, 30798, 34485, 37069, 40326, 42696, 44584, 45539, 60627, 66634, 69112, 71194, 73273, 75029, 75634, 77227, 76762, 77612, 80435, 78707, 79665, 82246, 82333, 83574, 85591)
rec <- c(288, 463, 617, 866, 1120, 1507, 2000, 2651, 3313, 3905, 4689, 5279, 6531, 7952, 9477, 10908, 12590, 14315, 16136, 18060, 19258, 22613, 23452, 25128, 27895, 30422, 33555, 36263, 39524)
plot(x = infec_seq, y = infec, pch = 16)
lines(x = infec_seq, y = infec)
points(x = rec_seq, y = rec, col = "blue", pch = 16)
lines(x = rec_seq, y = rec, col = "blue")
Please develop an SEIR model and change the parameter values by hand until you generate a set of curves that, when overlaid on the COVID-19 data, look similar. Please include the figure and the parameter values you used.


--- layout: post title: Help me, Lazyweb... date: 2007-12-31 00:00:00 category: personal ---
I want a file store which I can email stuff into. The subject lines of emails would be broken into tags, and attachments associated with the tags. I could get RSS feeds of specific tags - e.g. so I can email a file in, tag it "mobile" and "ui", and a colleague can subscribe to all new files tagged "ui" by RSS.
Does such a beast exist? Ideally open source software we can host at FPHQ rather than third-party hosted.


@(esi: Boolean, decision: String) @if(esi) { @decision match { case "IN" => {
You need to reassess the status if this engagement varies or changes.
} case "OUT" => {You need to reassess the status if this engagement varies or changes.
} case "UNKNOWN" => {We need more information to understand the working practices of this engagement.
} case _ => {We need more information to understand the working practices of this engagement.
} } } else { @decision match { case "IN" => {Based on the information you’ve given the working practices of this engagement fall within the scope of the intermediaries legislation.
The worker should pay tax and National Insurance as if they were an employee.
You should reassess the status of the role if there are changes to the engagement or the way the work is done.
} case "OUT" => {Based on the information you’ve given the working practices of this engagement fall outside the scope of the intermediaries legislation.
The worker should pay tax and National Insurance as a self-employed person.
You should reassess the status of the role if there are changes to the engagement or the way the work is done.
} case "UNKNOWN" => {We need more information to understand the working practices of this engagement.
} case _ => {We need more information to understand the working practices of this engagement.
} } }


2 Samuel 8:5
And when the Syrians of Damascus came to succor Hadadezer king of Zobah, David slew of the Syrians two and twenty thousand men.


| Runtime Days | {{$KPI-BACKTEST-DAYS}} | {{$KPI-DAYS-LIVE}} |
Drawdown | {{$KPI-DRAWDOWN}} | {{$KPI-LIVE-DRAWDOWN}} |
| Turnover | {{$KPI-TURNOVER}} | {{$KPI-LIVE-TURNOVER}} |
Probabilistic SR | {{$KPI-PSR}} | {{$KPI-LIVE-PSR}} |
| CAGR | {{$KPI-CAGR}} | {{$KPI-LIVE-CAGR}} |
{{$LIVE-MARKER}}Sharpe Ratio | {{$KPI-SHARPE}} | {{$KPI-LIVE-SHARPE}} |
| Markets | {{$KPI-MARKETS}} | {{$KPI-MARKETS}} |
Information Ratio | {{$KPI-INFORMATION-RATIO}} | {{$KPI-LIVE-INFORMATION-RATIO}} |
| Trades per Day | {{$KPI-TRADES-PER-DAY}} | {{$KPI-LIVE-TRADES-PER-DAY}} |
Strategy Capacity (USD) | {{$KPI-STRATEGY-CAPACITY}} |


| DOSE: T+ 0:00 |
320 mg |
oral |
Caffeine |
(liquid) |
| T+ 0:45 |
320 mg |
oral |
Caffeine |
(liquid) |
| T+ 1:00 |
1 glass |
oral |
Caffeine |
(liquid) |
Note: I do not know what effects are typical, or unique to me, I really wish there was more information on similar caffeine intoxications.
I'm a 24 year old male with Lupus for 2 years now. It's a rheumatic disease that saps my energy and makes me chronically achey, though my medications do work effectively enough for me to function sufficiently to hold a job. I have been taking Prednisone daily, which is a corticosteroid that modulates my immune system and controls the inflammatory symptoms, and I take 50mg of Azatioprine (Imuran) each day to further suppress immune function. Despite what I read... neither of these medications have caused me any side effects at all, and have only benefited me. Prednisone is a very 'liberating' medicine.
In the past I used to be an avid jogger and I loved weightlifting and being so fit and lively. I seriously miss those good old days. Since Iíve had Lupus Iíve had virtually no sex drive, or at least it's extremely difficult for me to find interest in most anything. Although I do have my occasional good days, they tend to be few and far between. However, I have found that whenever I tried your average everyday energy drink, I notice that I always have a really good day, no crashes or anything. But I only limited myself to occassional use, when I know I would need it, like if I had to do some housework, moving, or socializing. Although in recent times I got into the habit of having tea and coffee daily as most people do, and I would use instant coffee in particular, because I like the idea that I can control the concentrations. I'd often make myself a 'double' or triple serving. I noticed that the more I had, the better I felt. The more alive and energetic I felt.
I've been without a job for a couple months now, boredom, monotony, and loneliness begin to set in from being on an involuntary vacation. A nice caffeine buzz always made me feel better, even if I wasn't accomplishing anything. I've used caffeine to brighten my good moods... I think of caffeine as an 'Amplifier' for whatever I feel. I've Iím happy, it made me real happy. If I felt triumphant about something, it made me feel like I just won the lottery. If I just beat someone in an argument (which I love doing because of my rather egotistical Narcissistic personality) it made me feel like I owned the world or something.
It helps me think and concentrate very intensely on things, and I do not experience the typical jitteryness or tension that I see depicted in the typical 'too much coffee' stereotype. I notice I can type much faster and I can actually speak far quicker and more articulate than usual. I'm able to form more naturally coherent thought trains than I usually do, and thusly I obviously find this to be an attractive effect for me. Also, when I feel more energetic, I find it much more conducive to sexual activity too, though usually nothing too spectacular. The afterglow to a typical orgasm just coincides well with the alert feeling of the caffeine.
One Saturday when I had all day to myself and I figured I should go all the way and I figured Iíd give myself a treat by celebrating. I've just recently found out that I was right about something I felt very adamant about, so I decided to 'Augment' the feeling. I made myself a 4x serving of instant, using 4 heaping teaspoons of instant dissolved in only about 2 or 3 ounces of hot water.
I never saw the point of diluting coffee in an entire cup, it just seems so silly to me. I want the effects and I don't want to mess around with silly cream and sugar... In fact, I normally drink it straight up black, and the strong taste simply does not bother me... In fact, I have a positive association with the harsh bitter taste to the point that it makes me happy and excited just to smell it. Sometimes I would even just eat the instant powder itself, though it makes my mouth feel funny. Normally when I drink it, I like to hold it in my mouth for a while and swish it around thinking that it absorbs faster if I keep it in my mouth and esophagus as long as I can, rather than letting it go to my stomach where it has to sit and absorb there. I begin to feel it rather shortly within 10 minutes at the most. A faster heart rate was the most noticable thing.
Now... with my condition, my heart rate tends to run a little faster than the average person, around 85 to 90 BPM resting pulse, and my blood pressure actually tends to be a little low, like 105/60 or so.
When Iím wired on caffeine I typically feel much more motivated and alive, and in an all around great mood. This one morning I remember just grinning and smirking at nearly everything, feeling like I could beat anybody in an argument. I notice that I also tend to think and talk much more aggressively too, I describe it as being much more 'ballsy' or 'assholish'. That's probably just my personality coming out, but I end up cursing people out, even my own mom, and not feeling the least bit bad about it afterwards. But I have mixed feelings about it in retrospect.
I had taken a 4x serving early at about 9 in the morning, so that the buzz coincided with my medications kicking in. I generally feel my best around noon or early afternoons, so I wanted more caffeine to coincide with that time. I made another 4x cup of black sludge shortly after the first, and went to go sit down at the computer.
I just felt good and triumphant all over. Most notably, I was paying attention to how I felt, and my heart was pounding and I felt like taking long slow breaths. I measured my pulse to be at a constant 120 BPM. I remember feeling the occassional hot and cold flashes alternating, but I didn't mind. I kept feeling these wonderful adrenalin rushes in my gut that came in waves, and I also noticed a rather strong nauseating feeling in my 'core', but what I found odd, is that this nauseous feeling was actually quite nice, I liked it. I just accepted it altogether and let it happen. I felt confident that no matter what happens, it will pass, and Iíll just ride it out nicely.
I also had a popular energy drink in the fridge, and I decided to chug that rather quickly. I normally don't do that, but I wanted to go all out today. I don't really consider it to contribute that much to the caffeine buzz since I read that they don't have much more caffeine than a typical cup of coffee, but I figure the B vitamins would help bump it up some more. I was planning to enjoy another wonderfully selfish masturbation session, so I went off to a bathroom for nearly an hour. Now, admittedly it's been a while, but I went ahead and had not 1, but 2 of the most wonderful eyes-rolling-up anal orgasms ever. The second better than the first.  I find this to be a bit disturbing when I think about how I simply did not care at that point.
The 2nd orgasm was the most notable, since it resulted in me blacking out and passing out. Falling onto the bathroom floor for was I guess half a minute, but it felt much longer. I was overtaken by a black shadow that washed over me, and I felt like I was nowhere, I was nothing, I was everywhere... I guess that is similar to what's described as a 'Dissociative' effect, which makes me rather curious about other dissociatives like Ketamine now... Though... after reading up later, I surmise that what happened to me is a combination of the Vasoconstrictive effects of caffeine, combined with my general low blood pressure and blood pooling that caused me to have a Hypo-something syncope, essentially the same as drowning... so I said to myself 'damn... I really have got to stop doing that'...
When I was done I felt like I was glowing. It felt so good to just move around and stretch, I was amazed that I felt warm and tingly when I put my clothes back on, it just felt so nice. I sprawled out spread eagle on a king size bed, staring at the ceiling so I could enjoy the nice warm post-orgasmic afterglow that I love so much. Caffeine just really really seems to extend and amplify it.  My heart was still pounding steadily and I was taking long deep breathes. After more than an hour or so, I got up groggily and went back to my room to go back on the computer... all seemed normal until my mom came home at about 4pm...
The comedown:
This is perhaps the scariest part which lends a cautionary element. After 5pm my heart was still pounding steadily, and I was still getting those same adrenalin rushes and cold flashes with sweating, and I was feeling increasingly more nervous and anxious now. I was beginning to worry why I was still feeling the effects, and I became much more aware of my heart beating, I started to feel a sick sick cold fearful feeling filling my body, it made my hands and lips cold and slightly numb. I felt like I had a cold numbness in my mouth and the core of my gut behind my chest. I really began to feel like I was about to have a heart attack or have a seizure of some kind. I was afraid that this must be what it feels like just before it happens. I really felt like the world was coming to an end and 'this is it'.
I got up and started pacing around, trying not to think negative things, but they kept reverberating in my head, but I would try to shake them off. I've had similar Panic attack episodes in the past, and I tried to comfort myself in the fact that nothing bad has ever resulted from them, and most likely nothing will happen this time. I decided to go walk my dogs with my mom, I felt more comfortable with someone familiar, and I told her how I felt and she said 'oh... you're having a panic attack', and I immediately felt better when I realized I could now put a name to what I was feeling... though when we went back up I was still pacing, so I sat down, drank some water and watched some TV with my mom for a while, by about 7PM it finally started to subside. I only told my mom I had a lot of coffee, but not what Iíve actually been doing in recent times.
This panic attack lasted nearly 3 hours. Later on that night I read up on Panic Attacks and I was amazed that it was precisely what happened to me and I was greatly relieved to read that, as intensely frightening as they are, they present no real danger. I had an epiphany later that the cause was rooted in a phobia that I had. I had a phobia of having a heart attack or a seizure. Learning this increased my confidence, and I began laughing to myself about how silly it seemed now. I feel that with this knowledge of the chemical nature of what happened, I could prevent another panic attack from precipitating, or even help talk someone else down from one. It's important for people to know these kinds of things.
Withdrawal:
I decided to give myself a break and ween myself off of caffeine completely... For the next 3 days it felt like I had a fever, and I felt all out exhausted with a terrible pounding headache, and I was generally depressed, with my usual feelings of loneliness and hopelessness felt just utterly amplified. Negative thoughts had a reverberative quality, to the point where I was curled up in bed sobbing lightly for little reason, and I don't consider myself the type that cries easily.
The 4th day I felt a little better. During these days I felt like having another caffeinated drink, every time my eye caught the instant coffee container, I just had this unbearable urge to just grab it and pour it down my mouth. Maybe it wasn't such a good idea to just drop it cold turkey, but I was just really really disappointed with myself for what I've been doing. I realized that I do have a rather addictive personality. I found that I could distract myself by doing a bunch of watercolor paintings. I produced about 16 Watercolor paintings, mostly of boring seascapes with different color variations, but as long as I was painting, I wasn't thinking about getting tanked up again.
Perspective, and thoughts-
I still believe there is nothing wrong with regular casual use of caffeine, and now, knowing what I know, a part of me really wants to do it all again. A part of me is still very fond of these wonderful stimulant effects, and is often very tempted of the idea of getting caffeine pills and insufflating them. It just seems more efficient to me, and I like that. And I've read about how Caffeine is sometimes called 'Redneck Cocaine' for 'dumb kids who can't afford the real thing.' It makes me think, despite all the negative trip experiences, that perhaps Cocaine is the substance that my personality demands the most. I must admit that in spite of my better judgement, if the oppurtunity to use Cocaine is put in front of my face I will do it.
The fundamental problem with Caffeinism... 'it's not that I want 1 coffee... it's that I want 10...' The more more MORE aspect. For a while, plain average orgasms were like nothing to me, I would often use a caffeine buzz to 'multiply it out'. I used the analogy every day mundane orgasms as trying to fly by flapping my arms, and caffeine was like being hurled with a catapult. Sure I crash harder, but it sure felt better.
I feel that I am torn between my personality which fosters my hedonism. I consider my sexual tastes and appetites to be quite extreme and odd at times, though not entirely irrelevant to why I find the concept of substance abuse to be oddly romanticized for me, though that's a whole other can of worms. The fact is, I like pleasure, and I like lots of it. I like to feel good, and I grow tired of life's feeble natural 'peak experiences' that seem so infrequent and downright stingy.
I haven't taken any truly hard substances, aside from Morphine when I was hospitalized for a terrible Lupus flare-up, the most Godawful pain I've ever experienced, which I liken to being crushed by a car and set on fire with knives stuck in me, pain so bad that I could hardly breathe, so bad that for 2 days I could hardly sleep, and I woke my mom up at 3am to drive me to the Hospital a few months back. The Morphine was NOT the typical recreational dose, so it was nothing spectacular to note, other than what one typically hears... though admittedly, it left a permanent impression on me, and a part of me really, REALLY wants it again.
Seriously, I do romanticize about the beautiful, miraculous effects of Morphine just like the writers and poets of the 1800s, but that's a WHOLE other issue. I've also made poppyseed tea, but that was nothing spectacularly noteworthy either. But I surmise that that is what it's like. I really do sympathize with those who have trouble with addiction now, because I have had maybe a smaller parody of what it must be like. I am simply.. NOT supposed to feel good all the time. And I am comfortable with that now...
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.