OpenLLM-France/wikimedia huggingface dataset:
# KnitR/Installation
## Installation of KnitR

KnitR comes as a CRAN package, hence can be installed as any CRAN package either with your R package manager, if you use one, for example that which comes with your IDE or simple from the R command line by typing
where the part about the dependencies automatically installs all packages that are needed for the use of knitR.

## Output Formats

You need for specific output formats additional software for the KnitR document generation. This section explains the additional software required for specific output formats:
* PDF-output: LaTeX must be installed on your computer to render the generated output in PDF.
* ODT-output: Install LibreOffice to edit the generated text by KnitR
# KnitR/Pitfalls

Learning about common pitfalls for advanced users provide insights in the structure of document generation. The provide solutions are templates for generic problem solving in document generation in KnitR. This section is not meant to be a debugging resource. So add KnitR problems with additional comments, so that learners understand more about the basic principles of dynamic document generation.

## PDF Output

PDF output uses LateX to render the output:

### Lower Symbol in LaTeX Expression in R-Markdown

* Date: 2019/07/05
* Topic: Math delimiters and Symbols

#### Document with Bug

The mathematical expression with a lower sign $y_{k}<\alpha$ causes a problem in the PDF rendering of the following R-markdown source document:

#### Expected output

The latex expression should render to:
       The equation $y_{k}<\alpha$ is not rendered properly in R-Markdown with PDF output

#### Error Message

Explanation: the lower symbol is replace by the textless command, which is OK when the less symbol is used in regular text mode. But if the replacement is performed in the math environment in R-Markdown, this replacement causes a problem for document rendering due to fact that the textless-command in LaTeX is meant to used in text mode and not in a math environment.

### Solution

Wrap the less-symbol with Dollar-character, so that the textless-command is in text environement for rendering.

### Lesson learnt

The general recommendation (lesson learnt) is to use the <-Symbol in R-Markdown outside the math-delimiters (i.e. Dollor-symbol $).
# Klingon prefixes
## Prefixes

| Subject | Object | Object | Object | Object | Object | Object | Object |
| Subject | none | me | you (sing.) | him/her/it | us | you (plural) | them |
| I | jI- | | qa- | vI- | | Sa- | vI- |
| you (sing.) | bI- | cho- | | Da- | ju- | | Da- |
| he/she/it | none | mu- | Du- | none | nu- | lI- | none |
| we | ma- | | pI- | wI- | | re- | DI- |
| you (plural) | Su- | tu- | | bo- | che- | | bo- |
| they | none | mu- | nI- | lu- | nu- | lI- | none |
none indicates that no prefix is required. For the blank entries, the object is translated by -'egh or -chuq.

## Imperative Prefixes

| Subject | Object | Object | Object | Object | Object |
| Subject | none | me | him/her/it | us | them |
| you (sing.) (addressed to one person) | yI- | HI- | yI- | gho- | tI- |
| you (plural) (addressed to several people) | pe- | HI- | yI- | gho- | tI- |
Topic:Klingon
# Knee exam
## Observation (supine)

* Ecchymosis (bruise)? Surgical scars?
* Erythema or overlying rash/celulitis
* Knee resting position
* Knee effusion with obscured landmarks
* Quadriceps muscle atrophy

## Observation (standing)

* Balanced weight on each leg
* Genu varum or genu valgum deformity
* Gait analysis
* Hip, knee and ankle alignment
* Presence of Baker cysts (inspect popliteal fossa with patient standing)

## Palpation

* Temperature
* Joint line tenderness
* Bony structures
* Bursae and tendons

## Range of motion

* Normal flexion = 130 degrees
** look for pain and crepitus
** do active vs passive ROM
* Normal extension = 10 degrees above horizontal

## Knee effusion tests

* patellar ballotment
* knee milking
* swipe test/bulge sign

## Anterior Cruciate Ligament (ACL) Stability Tests

* Lachman's Test (most sensitive)
* Anterior drawer sign

## Posterior Cruciate Ligament (PCL) Tests

* Posterior drawer test
* PCL sag test

## Collateral ligament evalutation

* Knee valgus stress test (Medial collateral ligament)
* Knee varus stress test (Lateral colalteral ligament)

## Meniscus Evaluation

* McMurrays Test (external rotation and extension from full knee flexion for medial meniscal tear, internal rotation and extension for lateral mensicusus)
* Apley's compression test (grind home test)
# Happiness

Happiness is a mental or emotional state of well-being characterized by positive or pleasant emotions ranging from contentment to intense joy. A variety of biological, psychological, religious, and philosophical approaches have striven to define happiness and identify its sources.
Wikipedia Happiness: Various research groups, including Positive psychology, endeavor to apply the scientific method to answer questions about what "happiness" is, and how we might attain it. Philosophers and religious thinkers often define happiness in terms of living a good life, or flourishing, rather than simply as an emotion. Happiness in this sense was used to translate the Greek Eudaimonia, and is still used in virtue ethics. Happiness economics suggests that measures of public happiness should be used to supplement more traditional economic measures when evaluating the success of public policy.
---> Download the Wikiversity Book Happiness (basic version 2012) in various formats (PDF, Epub, Kindle) for reading and give away.

## Contents

* Philosophy of Happiness
* Happiness research
* Positive thinking
* Everyone needs a spiritual centering
* The Five Principles of Health
* Have a Happy Relationship
* Have a Happy Family
* Be a Happy Single
* Have a Happy Old Age
* Have a Happy Job
* Happiness and Life
* Happiness and Enlightenment
* Laughter Yoga
* A World of Peace, Love and Happiness
* Happiness oracle (Tarot)
* Optimism

## Jokes

Angel oracle: Laugh at life. Who rests in his own happiness, can laugh at the chaos of life. The angel of humor. He lives the joy. He makes jokes. He sees life as a game. Be positive as you go through the day. Do not take things too seriously. Today you can be a little wild and crazy. Have fun. :-) :-) ;-) :-)
Men and women
Nils: Men and women are different. There is no doubt about it. But rather than focus on the negative characteristics of men and women, why not praise the positives? Let's start with the women: women are compassionate, caring, and socially. Women cry when they are happy. Women bring joy and laughter in this world. Women are kind and loyal. They will not give up under any circumstances to get for the best for their children. Women have the ability to smile when they are so tired that she can hardly stand up. They know how to make a simple meal into a feast. They know how to comfort a sad friend. They know how to deal with children for endless hours! They know how to give a man the feeling to be king. Women make the world to a happier place.
Sybilla: WOW. Thank you .... ;-)) That feels really good just now!
Sonja: ..... Thaaaaaaaaaank you. Dear Nils, you nearly were a man to marry. Lol :)))
Nils: Alll my ten ex-women had an other point of view!
# Hanja/恕
## 恕

* (용서할 서) to forgive
* (헤아릴 서) to infer, reason
* (어질 서) to be considerate, sympathize
** 論語/衛靈公第十五
    子貢問曰 有一言而可以終生行之者乎. 子曰 其恕乎 己所不欲勿施於人.
    자공문왈 유일언이가이종생행지자호. 자왈 기서호 기소불욕물시어인.
    Zigong asks if there is a single word worth doing for life. Confucius says that it is considerateness -- what one wouldn't like shouldn't be done to the other.

## Wiktionary

* 己所不欲勿施於人
* 역지사지
* do unto others as you would have them do unto you
# Linear mapping/Change of basis/No proof/Section
## Lemma

Let $K$ denote a field, and let $V$ and $W$ denote finite-dimensional $K$-vector spaces. Let ${\mathfrak {v}}$ and ${\mathfrak {u}}$ be bases of $V$ and ${\mathfrak {w}}$ and ${\mathfrak {z}}$ bases of $W$. Let
    $\varphi \colon V\longrightarrow W$
denote a linear mapping, which is described by the matrix $M_{\mathfrak {w}}^{\mathfrak {v}}(\varphi )$ with respect to the bases ${\mathfrak {v}}$ and ${\mathfrak {w}}$. Then $\varphi$ is described with respect to the bases ${\mathfrak {u}}$ and ${\mathfrak {z}}$ by the matrix
    $M_{\mathfrak {z}}^{\mathfrak {w}}\circ (M_{\mathfrak {w}}^{\mathfrak {v}}(\varphi ))\circ (M_{\mathfrak {u}}^{\mathfrak {v}})^{-1},$
where $M_{\mathfrak {u}}^{\mathfrak {v}}$ and $M_{\mathfrak {z}}^{\mathfrak {w}}$ are the transformation matrices, which describe the change of basis from ${\mathfrak {v}}$ to ${\mathfrak {u}}$ and from
${\mathfrak {w}}$
${\mathfrak {z}}$

### Proof

$\Box$

## Corollary

Let $K$ denote a field, and let $V$ denote a $K$-vector space of finite dimension. Let
    $\varphi \colon V\longrightarrow V$
be a linear mapping. Let ${\mathfrak {u}}$ and ${\mathfrak {v}}$ denote bases of $V$. Then the matrices which describe the linear mapping with respect to ${\mathfrak {u}}$ and ${\mathfrak {v}}$ respectively (on both sides), fulfil the relation
    $M_{\mathfrak {u}}^{\mathfrak {u}}(\varphi )=M_{\mathfrak {u}}^{\mathfrak {v}}\circ M_{\mathfrak {v}}^{\mathfrak {v}}(\varphi )\circ (M_{\mathfrak {u}}^{\mathfrak {v}})^{-1}\,.$

### Proof

This follows directly from fact.
$\Box$

## Definition

Two square matrices $M,N\in \operatorname {Mat} _{n}(K)$ are called similar, if there exists an invertible matrix $B$ with
$M=BNB^{-1}$
Due to fact, for a linear mapping $\varphi \colon V\rightarrow V$, the describing matrices with respect to several bases are similar.
# Linear mapping/Composition/Fact

Let $K$ denote a field, and let $U,V,W$ denote vector spaces over $K$. Suppose that
    $\varphi :U\longrightarrow V\,\,{\text{ and }}\,\,\psi :V\longrightarrow W$
are linear mappings.
composition
    $\psi \circ \varphi \colon U\longrightarrow W$
# Linear mapping/Determination on basis/Fact

Let $K$ be a field, and let $V$ and $W$ be $K$-vector spaces. Let $v_{i}$, $i\in I$, denote a basis of $V$, and let $w_{i}$, $i\in I$, denote elements in $W$.
linear mapping
    $f\colon V\longrightarrow W$
with
    $f(v_{i})=w_{i}{\text{ for all }}i\in I.$
# Linear mapping/Composition/Price/Salary/Exercise

Lucy Sonnenschein works as a bicycle messenger, she earns $12$ € per hour. At the fruit market, the price (per $100$ gram) for raspberries is $3$ €, for strawberries the price is $2$ €, and for apples the price is $0,4$ €. Describe the mapping, which assigns to any purchase of fruits, the time, how long Lucy has to work for it, as a composition of linear mappings.
# Linear mapping/Determinant/Introduction/Section

Let
    $\varphi \colon V\longrightarrow V$
be a linear mapping from a vector space of dimension $n$ into itself. This is described by a matrix $M\in \operatorname {Mat} _{n}(K)$ with respect to a given basis. We would like to define the determinant of the linear mapping, by the determinant of the matrix. However, we have here the problem whether this is well-defined, since a linear mapping is described by quite different matrices, with respect to different bases. But, because of fact, when we have two describing matrices $M$ and $N$, and the matrix $B$ for the change of bases, we have the relation $N=BMB^{-1}$. The multiplication theorem for determinants yields then
    $\det N=\det {\left(BMB^{-1}\right)}=(\det B)(\det M){\left(\det B^{-1}\right)}=(\det B){\left(\det B^{-1}\right)}(\det M)=\det M\,,$
so that the following definition is in fact independent of the basis chosen.

## Definition

Let $K$ denote a field, and let $V$ denote a $K$-vector space of finite dimension. Let
    $\varphi \colon V\longrightarrow V$
be a linear mapping, which is described by the matrix $M$, with respect to a basis. Then
    $\det \varphi :=\det M\,$
$\varphi$
# Linear mapping/Determine image and kernel/Exercise

Determine the image and the kernel of the linear map
    $f\colon \mathbb {R} ^{4}\longrightarrow \mathbb {R} ^{4},{\begin{pmatrix}x_{1}\\x_{2}\\x_{3}\\x_{4}\end{pmatrix}}\longmapsto {\begin{pmatrix}1&3&4&-1\\2&5&7&-1\\-1&2&3&-2\\-2&0&0&-2\end{pmatrix}}\cdot {\begin{pmatrix}x_{1}\\x_{2}\\x_{3}\\x_{4}\end{pmatrix}}.$
# Linear mapping/Composition/Fact/Proof/Exercise

Let $K$ be a field, and let $U,V,W$ be vector spaces over $K$. Let $\varphi \colon U\rightarrow V$ and $\psi \colon V\rightarrow W$ be linear maps. Prove that also the composite mapping
    $\psi \circ \varphi \colon U\longrightarrow W$
is a linear map.
# Linear mapping/Determination theorem/Finite-dimensional/Section

Behind the following statement (the determination theorem), there is the important principle that in linear algebra (of finite-dimensional vector spaces), the objects are determined by finitely many data.

## Theorem

Let $K$ be a field, and let $V$ and $W$ be $K$-vector spaces. Let $v_{i}$, $i\in I$, denote a basis of $V$, and let $w_{i}$, $i\in I$, denote elements in $W$. Then there exists a unique linear mapping
    $f\colon V\longrightarrow W$
with
    $f(v_{i})=w_{i}{\text{ for all }}i\in I.$

### Proof

$\Box$

## Example

The easiest
linear mappings are (beside the null mapping) the linear maps from $K$ to $K$. Such a linear mapping
    $\varphi \colon K\longrightarrow K,x\longmapsto \varphi (x),$
is determined (by fact, but this is also directly clear) by $\varphi (1)$, or by the value $\varphi (t)$ for an single element $t\in K$, $t\neq 0$. In particular, $\varphi (x)=ax$, with a uniquely determined $a\in K$. In the context of physics, for $K=\mathbb {R}$, and if there is a linear relation between two measurable quantities, we talk about proportionality, and $a$ is called the proportionality factor. In school, such a linear relation occurs as "rule of three“.
# Linear system/Parameter/1/Exercise

Determine, in dependence of the parameter $a\in \mathbb {R}$, the solution space $L_{a}\subseteq \mathbb {R} ^{3}$ of the system of linear equations
    $5x+ay+(1-a)z=0\,,$
    $2ax+a^{2}y+3z=0\,.$
# Linear system/Snowdrops and mistletoes/Exercise

Kevin pays $2.50$€ for a winter bunch of flowers with $3$ snowdrops and $4$ mistletoes, and Jennifer pays $2.30$€ for a bunch with $5$ snowdrops and $2$ mistletoes. How much does a bunch with one snowdrop and $11$ mistletoes cost?
# Linear system/Snowdrops and mistletoes/Exercise/Solution

Let $x$ denote the price of a snowdrop and let $y$ denote the price of a mistletoe. Then
    $3x+4y=2{.}50\,$
and
    $5x+2y=2{.}30\,.$
Subtracting from the first row the double of the second row, we get
    $-7x=-2{.}10\,$
and hence
    $x=0{.}30\,.$
Therefore we get
    $y=0{.}40\,$
and so the price of the looked-for bunch equals
    $1\cdot 0{.}3+11\cdot 0{.}4=4{.}70\,.$
# Linear system/Q/Equivalent over Z/Exercise

Show that for every system of linear equations over $\mathbb {Q}$, there exists an equivalent linear system with the property that all coefficients are integers.
# Linear system/Solution space/Orthogonal space/Example

Let a homogeneous linear system
    ${\begin{matrix}a_{11}x_{1}+a_{12}x_{2}+\cdots +a_{1n}x_{n}&=&0\\a_{21}x_{1}+a_{22}x_{2}+\cdots +a_{2n}x_{n}&=&0\\\vdots &\vdots &\vdots \\a_{m1}x_{1}+a_{m2}x_{2}+\cdots +a_{mn}x_{n}&=&0\end{matrix}}$
over a field $K$ be given. We consider the $i$-th equation as a kernel condition for the linear form
    $L_{i}\colon K^{n}\longrightarrow K,\left(x_{1},\,\ldots ,\,x_{n}\right)\longmapsto \sum _{j=1}^{n}a_{ij}x_{j}.$
Let
    $F=\langle L_{1},\ldots ,L_{m}\rangle \,$
denote the linear subspace of the dual space ${K^{n}}^{*}$ generated by these linear forms. Then $F^{\perp }$ is the solution space of this linear system.
# Distillation of alcohol

This resource is a candidate to be moved to Wikibooks. If you disagree, remove this template and explain your opinion on the talk page.
The process of creating ethanol, or drinking alcohol, is incredibly simple. Alcohol is the left over waste product from yeast breaking down complex sugars for their use as fuel. This process is so easy to do, that it only takes a short space to explain it.
* Heat water and dissolve as much sugar, either table sugar, sucrose, or molasses, etc, as you can.
* Wait for the water to cool back to room temperature, and then add a teaspoon of bread yeast, or a special kind of brewing yeast to the water. Waiting for the water to cool is crucial, because if it is too hot, it will kill the yeast.
* Within a short period of time, the mixture should begin to bubble. It does so because CO2 is a major byproduct of alcohol production. Be careful not to seal the container it is in, as this may result in an explosion. The best thing to do is to have a cover which just sits on top of the containing vessel, so that things do not fall into the mixture, and at the same time, so gases can escape.
* Wait a few days until the mixture stops bubbling, this is the sign that the fermentation process is complete.
* Filter your liquid through a coffee filter to remove the yeast and other impurities.
* The result should be approximately the equivalent of a 40 proof liquor. Do not worry, this process creates no toxic chemicals such as methanol, so no further refinement is needed to create a consumable product.
* Add flavoring if desired, and enjoy!
# Divergence

The divergence is a way of expressing a certain type of derivative of a vector field. It is typically defined for fields of 3-dimensional vectors on 3-dimensional space, but other dimensions are possible. The divergence of a vector field is a scalar field, that is, just a number at each point in space.
The divergence is written as though it were the dot product of the special symbol "$\nabla$" (which is commonly called "del" or "nabla"), with the given vector field, like this: $\nabla \cdot {\vec {V}}$. This is usually pronounced "div V" or "del dot V".
In ordinary Cartesian coordinates, the divergence is calculated as:
    $\nabla \cdot {\vec {V}}={\frac {\partial V_{x}}{\partial x}}+{\frac {\partial V_{y}}{\partial y}}+{\frac {\partial V_{z}}{\partial z}}$
or, using suitable notation,
    $\nabla \cdot {\vec {V}}=\sum _{i=1}^{3}{\frac {\partial V_{i}}{\partial x_{i}}}$
If one thinks of $\nabla$ as being a fictional vector field with components $\left({\frac {\partial }{\partial x}},{\frac {\partial }{\partial y}},{\frac {\partial }{\partial z}}\right)$, one can sort of see that the dot product notation makes sense. This is also useful for remembering how to calculate a divergence.
The divergence is a true vector field operation—the result is independent of the coordinate system that is used. The proof of that, and its ramifications, are beyond the scope of this page.
The divergence is an extremely important operation in physics, mathematics, and engineering. It is perhaps most famous for its appearance in Maxwell's Equations.
Intuitively, the divergence measures the degree to which the vector field is diverging from a given point. If you were to measure the divergence of the vector field of wind speed in the vicinity of a meteorological high pressure area, it would be positive, because the net motion of air is outward. If measured near a low pressure area, the divergence would be negative.
Vector fields with a divergence of zero are called solenoidal.
# Distinction between Economic Growth and Economic Development

A distinction should be made between Economic Growth and Economic Development.
Economic Development is made possible by innovation and a series of innovations. Development involves fundamental changes within the society where as growth is the improving of a societies efficiency. Growth ideally involves being free from economic instabilities.
Growth = More output Development = More output + changes
Examples
India
India is still developing because it is still undergoing drastic societal changes as well as growing economically.
U.S.A.
The United States is growing economically because it is no longer undergoing societal changes but is rather streamlining the efficiency of its economy.
Libya
Libya is growing and not developing because the increase in oil revenues is not affecting any changes.
# Distances/Angular momenta/Quiz

Angular momentum is a lecture from the radiation astronomy department about a classical topic of Newtonian kinetics.
You are free to take this quiz based on angular momenta at any time.
To improve your score, read and study the lecture, the links contained within, listed under See also, External links, and in the {{radiation astronomy resources}} template. This should give you adequate background to get 100 %.
As a "learning by doing" resource, this quiz helps you to assess your knowledge and understanding of the information, and it is a quiz you may take over and over as a learning resource to improve your knowledge, understanding, test-taking skills, and your score.
Suggestion: Have the lecture available in a separate window.
To master the information and use only your memory while taking the quiz, try rewriting the information from more familiar points of view, or be creative with association.
Enjoy learning by doing!

## Hypotheses

* Angular momenta can be created, enhance, countered or eliminated by charge distributions.
# Distances/Vectors/Quiz

Distances/Vectors is a lecture about the application of laboratory physics to astronomical distances. It is a joint offering from the radiation astronomy department and the physics department of the school of physics and astronomy. On the plate from Sidney Hall on Urania's Mirror, directions of North, East, West, and South are indicated.
You are free to take this quiz based on Distances/Vectors at any time.
To improve your score, read and study the lecture, the links contained within, listed under See also, External links, and in the {{radiation astronomy resources}} and {{physics resources}} templates. This should give you adequate background to get 100 %.
As a "learning by doing" resource, this quiz helps you to assess your knowledge and understanding of the information, and it is a quiz you may take over and over as a learning resource to improve your knowledge, understanding, test-taking skills, and your score.
Suggestion: Have the lecture available in a separate window.
To master the information and use only your memory while taking the quiz, try rewriting the information from more familiar points of view, or be creative with association.
Enjoy learning by doing!

## Hypotheses

* More questions aimed at distances and vectors may be better.
# Informal learning activities/Wp

[[w:{{{1}}}|{{{1}}}]]
A short way of including Wikipedia links.
# Informal learning activities/WMxSu

Women & Menː S⇒ U__  O ther initialsː   Ac  Df
 Gi  Jl
 Mo  Pr
(«»Su⇑⇑)
 Vz
* Cleopatra  Selene +0   (monarch) 
* Caterina  Sforza 14.  (countess) 
* Betty  Shabazz 19  (educator)  • Grace  Sherwood +17  (witch)  • Carolyn  Shoemaker 19:  (astronomer) 
* William  Smellie .17  (obstetrician) 
* Herbert  Spencer 18.  (polymath)  • Tom  Spring .18  (boxer) 
* Obed  Starbuck .18  (whaler)  • Antonio  Stradivari 16+  (luthier)  • Fran  Striker 19  (writer) 
*  Suzzanna 19.  (actress) 
* William  Symington 17+  (inventor) 
* István  Széchenyi .18  (statesman)
Women & Menː T__
* Bazy  Tankersley 19:  (breeder)  • Torquato  Tasso 15  (poet)  • Hiwi  Tauroa 19:  (Māori)  • Recy  Taylor 19:  (victim) 
* Jean de  Thévenot 16  (traveller)  • Karl  Thiersch 18  (surgeon)  • Tom  Thomson 18:  (artist)  • Edgar  Thurston 18+  (zoologist) 
*  Tribonian :5  (jurist) 
* Gene  Tunney .19  (boxer) 
* John  Twenge 13  (saint) 
* Mary  Tytler 18+  (designer)
Women & Menː U__
* Nora  Unwin 19  (illustrator) 
* Thomas  Urquhart 16  (translator) 
* Octave  Uzanne 18+  (bibliophile)