OpenLLM-France/wikimedia huggingface dataset:
# Chess Opening Theory/1. e4/1...c5/2. Nf3/2...Nc6/3. c3
## Sicilian Defense: Delayed Alapin Variation

The Opening Line 1. e4 c5 2. Nf3 Nc6 can transform from the Old Sicilian to the Alapin variation with 3. c3. The ideas of this line are the same as the regular Alapin.

### Common Responses

The common responses to 3. c3 are 3...Nf6, 3...d5 and 3...e6.

#### 3...Nf6

The idea behind this move is to develop a knight, and strike at White's e4-pawn. Common replies to this move are 4. e5 attacking Black's knight and forcing it to move. The most common and best square to lace the knight is d5 with the move 4...Nd5. The knight on this square is now only subject to attack from the c4-pawn where if 5. c4?! Black can move the knight to b6, gaining an attack on the d-pawn and still controlling d5.

#### 3...d5

This move provokes the center and Black demonstrates their wish to control the game. The move 3. d5 seeks to undermine the white pawn on e4 by trading it with Black's d-pawn. It also seeks to bring the queen out to the center where Black has chances to build huge center control. The move of 3. c3 prevents White's knight from coming out and attacking the queen, making it harder to expel the black queen from the center. By far the most common continuation after 3...d5 is 4. exd5 Qxd5. White has a few choices following the queen taking on d5. If White plays 5. d4 he enters the Sicilian Defense Alapin Variation, Barmen Defense. Black has many response but the best are developing a piece rather than the playable but slightly worse cxd4. Other responses to 3...d5 are d3 defending White's pawn as White seeks to maintain his stake of the center. Black's best responses to this are playing 4...e6 as Black also seeks to maintain his center. Another rare response is 4. e5?!, which Black can exploit by playing 4...Bg4.

#### 3...e6

The pawn move of 3...e6 opens the diagonal for Black's bishop to protect the c5-pawn while preparing the push of d5. Common replies to 3...e6 are 4. d4 where Black responds with 4...d5 or the slightly worse 4...cxd5. The move 4...d5 keeps the tension in the center giving White the choice of opening the game and losing some control of the center. Common responses to the move 4...d5 are 5. e5 reaching the same position as the French Defense: Advanced, Paulsen Attack.
When contributing to this Wikibook, please follow the Conventions for organization.
# Chess Opening Theory/1. e4/1...c5/2. Nf3/2...Nc6/3. Nc3
## 3. Nc3

Most of the time in the Sicilian, White puts his Knight on c3. White may yet play d4, but for the moment the question is yet to be answered. White's second move suggests the possibility of NOT playing d4 (avoiding the exchange), and playing a closed position instead of the slashing, attacking types of position, that are more common to the Sicilian Defence. Leads to 3.g3 g6 4.Bg2 Bg7 5.d3 d6
3...d6 This is the main line and is a non-committal move. Black retains flexibility to wait and see if white opens up the game with d4 or opts to keep it closed such as d3 and maybe c3 to prepare the hallmark d4 push and locking up the center.

## Theory table

For explanation of theory tables, see theory table and for notation, see algebraic notation. .
1.e4 c5 2.Nf3 Nc6 3.Nc3
| | 3 |
| Sicilian, Taimanov | ... e6 | d4 |
| Sicilian | ... d6 | d4 |
When contributing to this Wikibook, please follow the Conventions for organization.

## References

* Kasparov, Garry, & Keene, Raymond 1989 Batsford chess openings 2. ISBN 0-8050-3409-9.
# Chechen/Quiz 1

Chechen — Содержани | Чудигар | Нохчийн абат | 01 | 02 | 03 | Талламанболх 1 | 04 | Хаархаттар
Талламанболх 1 Practice Quiz 1
It's time now to test what you have learned in the past 3 lessons and alphabet. This exam will test your knowledge in the alphabet, vocabulary, grammar, and culture. If you have scored at least more than a 70%, then you should be safe in moving on to the next lessons. If not, you should go back and review the past few lessons and work on the topics that stumped you the most. Good luck, аьтто хийла!
Chechen — Содержани | Чудигар | Нохчийн абат | 01 | 02 | 03 | Талламанболх 1 | 04 | Хаархаттар
# Chechen/Vocabulary/Crustaceans

Chechen — Содержани | Чудигар | Нохчийн абат | 01 | 02 | 03 | Талламанболх 1 | 04 | Хаархаттар
Искогбергаш - Crustaceans :
| Нохчийн | Ингалсан |
| искогберг | crustacean |
| иског | crayfish |
| краб | crab |
| креветка | shrimp |
| омар | lobster |
Chechen — Содержани | Чудигар | Нохчийн абат | 01 | 02 | 03 | Талламанболх 1 | 04 | Хаархаттар
# Chechen/Vocabulary/Family

Chechen — Содержани | Чудигар | Нохчийн абат | 01 | 02 | 03 | Талламанболх 1 | 04 | Хаархаттар
Доьзал - Family :
| Нохчийн | Ингалсан |
| бер бераш | grandchildren |
| ваша | brother |
| веши йоI | niece (brother's child) |
| веши кIант | nephew (brother's child) |
| да | father |
| дада | grandfather (father's side) |
| де нана | grandmother (father's side) |
| ден ден нана | great grandmother |
| доттагI | friend |
| доьзал | family |
| да-нана | parents |
| де ваша | uncle (father's side) |
| зуда | wife |
| жима бер | baby |
| йиша | sister |
| йиши йоI | niece (sister's child) |
| йиши кIант | nephew (sister's child) |
| йоI | daughter |
| йоьIан йоI | grandson (daughter's child) |
| йоьIан кIант | grandson (daughter's child) |
| кIант | son |
| кIентан йоI | granddaughter (son's child) |
| кIентан кIант | grandson (son's child) |
| майра | husband |
| марйиша | sister-in-law |
| марнана | mother-in-law |
| нана | mother |
| ненан ваша | uncle (mother's side) |
| ненан да | grandfather (mother's side) |
| ненан ден да | great grandfather |
| ненан нана | grandmother (mother's side) |
| неца | aunt |
| нус | daughter-in-law |
| нуц | son-in-law |
| стунваша | brother-in-law |
| стунда | father-in-law |
| стуннана | mother-in-law |
| шича | cousin |
Chechen — Содержани | Чудигар | Нохчийн абат | 01 | 02 | 03 | Талламанболх 1 | 04 | Хаархаттар
# Chemical Dynamics/Electrostatics/Fourier Transforms

The Fourier transform is a useful mathematical transformation often utilized in many scientific and engineering fields. Here we extract useful concepts of Fourier transformation and logically arrange them to form a foundation for the Ewald summation and other related methods in electrostatics. Readers could check out other more mathematically formal introduction of Fourier transform

## Definition

We use the following convention in which the Fourier transform is a unitary transformation on the 3-D Cartesian space R$^3$, the Fourier transform and its inverse transform are symmetric:
    ${\hat {f}}(\mathbf {k} )={\frac {1}{(2\pi )^{3/2}}}\int f(\mathbf {r} )e^{-i\mathbf {k} \cdot \mathbf {r} }\,d^{3}\mathbf {r}$
    $f(\mathbf {r} )={\frac {1}{(2\pi )^{3/2}}}\int {\hat {f}}(\mathbf {k} )e^{i\mathbf {k} \cdot \mathbf {r} }\,d^{3}\mathbf {k}$

## The translation theorem

Given a fixed position vector R$_0$, if g(r) = ƒ(r − R$_0$), then
${\hat {g}}(\mathbf {k} )=e^{-i\mathbf {k} \cdot \mathbf {R} _{0}}{\hat {f}}(\mathbf {k} ).$
    ${\hat {g}}(\mathbf {k} )={\frac {1}{(2\pi )^{3/2}}}\int g(\mathbf {r} )e^{-i\mathbf {k} \cdot \mathbf {r} }\,d^{3}\mathbf {r}$
    $={\frac {1}{(2\pi )^{3/2}}}\int f(\mathbf {r} -\mathbf {R} _{0})e^{-i\mathbf {k} \cdot \mathbf {r} }\,d^{3}\mathbf {r}$
    $={\frac {1}{(2\pi )^{3/2}}}\int f(\mathbf {r} -\mathbf {R} _{0})e^{-i\mathbf {k} \cdot \mathbf {r} }\,d^{3}\mathbf {r}$
Now, change r to a new variable by: $\mathbf {r'} =\mathbf {r} -\mathbf {R} _{0}$
    ${\hat {g}}(\mathbf {k} )={\frac {1}{(2\pi )^{3/2}}}\int f(\mathbf {r'} )e^{-i\mathbf {k} \cdot (\mathbf {r'} +\mathbf {R} _{0})}\,d^{3}\mathbf {r'}$
    $={\frac {1}{(2\pi )^{3/2}}}e^{-i\mathbf {k} \cdot \mathbf {R} _{0}}\int f(\mathbf {r'} )e^{-i\mathbf {k} \cdot \mathbf {r'} }\,d^{3}\mathbf {r'}$
    $={\frac {1}{(2\pi )^{3/2}}}e^{-i\mathbf {k} \cdot \mathbf {R} _{0}}\int f(\mathbf {r} )e^{-i\mathbf {k} \cdot \mathbf {r} }\,d^{3}\mathbf {r}$
    $=e^{-i\mathbf {k} \cdot \mathbf {R} _{0}}{\hat {f}}(\mathbf {k} ).$

## The convolution theorem

The convolution of f and g is usually denoted as f∗g, using an asterisk or star. It is defined as the integral of the product of the two functions after one is reversed and shifted:
    $(f*g)(t){\stackrel {\mathrm {def} }{=}}\ \int _{-\infty }^{\infty }f(\tau )\,g(t-\tau )\,d\tau$
The convolution theorem for the Fourier transform says:
If
    $h(\mathbf {r} )=(f*g)(\mathbf {r} )$
then
    ${\hat {h}}(\mathbf {k} )={\hat {f}}(\mathbf {k} )\cdot {\hat {g}}(\mathbf {k} )$.
    ${\hat {h}}(\mathbf {k} )=\int {e^{-i\mathbf {k} \cdot \mathbf {r} }h(\mathbf {r} )}d\mathbf {r}$
    $=\int {e^{-i\mathbf {k} \cdot \mathbf {r} }\int f(\mathbf {r} )g(\mathbf {r'} -\mathbf {r} )}d^{3}\mathbf {r'} d^{3}\mathbf {r}$
# Chechen/Vocabulary/Mammals

Chechen — Содержани | Чудигар | Нохчийн абат | 01 | 02 | 03 | Талламанболх 1 | 04 | Хаархаттар
Декха дийнаташ - Mammals :
| Нохчийн | Ингалсан |
| бож | goat |
| вир | donkey |
| говр, дин | horse |
| гомаш | buffalo |
| дахка | mouse |
| дийнат | animal |
| етт | cow |
| жий | sheep |
| жIаьла | dog |
| котам | chicken |
| лергъяхар | rabbit |
| лом | lion |
| маймал | monkey |
| муха дахка | rat |
| пхьагал | hare |
| сай | deer |
| уьстагI | ram |
| хьакха | pig |
| цIоькъа лом | tiger |
| ча | bear |
| цициг | cat |
| цхьогал | fox |
| эмкал | camel |
| борз | wolf |
Chechen — Содержани | Чудигар | Нохчийн абат | 01 | 02 | 03 | Талламанболх 1 | 04 | Хаархаттар
# Chemical Dynamics/Electrostatics

* Classical Electrostatics in Vacuo: Coulomb's law and Poisson's Equation
* Multipole Expansions
* Fast­multipole Methods
* Variational Principles
* Solvation Models in Modeling and Simulations
* Fourier Transforms
* Ewald Sums
* PME Methods
# Analog and Digital Conversion/Analog vs Digital
## Signals

What is a "signal", exactly? A signal in the sense that we will be considering in this book is changing value of electric voltage or current through a transmission medium. There are two general types of signals: periodic and aperiodic. Periodic signals repeat themselves after a certain period of time—after they have cycled through one period, following periods don't contain any new information. Aperiodic signals, on the other hand, don't repeat themselves, and therefore can contain information. Signals also can be analog or digital signals, and we will discuss them both below.

## Analog

Analog signals equate levels of electric voltage or current to amounts of information by applying some rule. Consider for instance, an analog clock, where the passage of time is displayed as the motion of the clock hands. In electric signals, a certain amount of voltage corresponds directly to a measured physical phenomenon. For instance, on an accelerometer, the amount of acceleration, measured in g's will correspond directly to volts. So at one g, we have 1 volt output, at 2 g's we have 2 volts output, etc. Analog signals have an advantage that they can represent any fractional quantity, by outputting an equivalent fractional quantity of voltage or current. Put in a different manner an Analog signal is continuous in time and also continuous in value.

### Uses of Analog

Analog signals have a number of uses. AM and FM radio, for instance, are signals that are transmitted in analog. Telephones (at least simple, older telephones) use analog signals to transmit voice data to the phone central office. Many electrical components, such as sensors, will output analog data, because of the accuracy that can be obtained from analog signals.

## Digital

Digital signals are different from analog signals in that there are generally only two levels of voltage: high and low. These different voltage levels are put into a sequence to describe the value being transmitted. For convenience, regardless of the actual voltage levels used, a "high" is called a 1, and a "low" is called a 0. Each signal level must be transmitted for at least a certain period of time called the Bit Time. A single signal level for a single bit time is called a Bit.
From bits, we have Binary Numbers, a collection of bits that can be arranged to form larger quantities than the simple numbers 0 and 1.

### Uses of Digital

Because bits can only be a 0 or a 1, digital transmissions don't have the same amount of accuracy as analog signals. Also, digital systems need to have complicated digital circuitry to read and understand the signals, that can cost more money than analog hardware does. However, the benefit is that digital signals can be manipulated, created, and read by computers and computer hardware.

### Examples

One of the best examples of digital signals are the control signals and data that are in use on your computer. Computers are almost completely digital, except for the sound card (which produced analog sound signals), and maybe a few other peripherals. Cellphones now are mostly digital, and the internet is a digital network.
# Analog and Digital Conversion

This book will attempt to explore the field of data conversion between analog and digital representations. This book will also explore some inherent problems in representing analog signals with digital data and vice versa, as well showing some common schemes for generating, coding, and transmitting the sampled data. Readers of this book would benefit strongly from a prior knowledge of the following subjects:
* Semiconductors
* Circuit Theory
* Digital Circuits
Once an analog signal is sampled, and represented in a digital domain, we can use techniques of Digital Signal Processing to manipulate the data. Those topics will not be covered in this book.
This book is in a very early stage of development, and many of the pages here will be stubs, or simply outlines. In time, more information will be filled in, but we need help from contributors like you. Feel free to help out and contribute!

## Table of Contents
### Section 1: Conversion Basics

* Introduction
* Analog vs Digital
* Sampling and Reconstruction

### Section 2: Sampling and Quantizing

* The Ideal Sampler
* Sampling Theorem
* Nyquist Sampling Rate
* Resolution and Bitrate
* Signed and Unsigned Quantities
* Spectral Effects
* Interpolation

### Section 3: Data Representation

* Differential Pulse-Coded Modulation (DPCM)
* Delta Modulation
* Continuously-Variable Slope Delta Modulation (CVSDM)

### Section 4: Signal Reconstruction

* Hold Circuits
* Other Reconstructors
* Reconstruction Effects

### Section 5: Quantization, Errors, Noise

* Uniform Quantization
* Non-Uniform Quantization
* Fixed Wordlength Effects
* Sources of Error

### Section 6: Building Converters

* ADC Converters
* DAC Converters

### Section 7: Appendices

* Reference Materials

## Further reading

* Control Systems
* Communication Systems
* Electronics (Analog-to-Digital and Digital-to-Analog Converters)
* Signals and Systems
* Digital Signal Processing
* "The Five Steps to Data Acquisition"
# Analog and Digital Conversion/Continuously-Variable Slope Delta Modulation
## CVSDM

This section of the Analog and Digital Conversion wikibook is a stub. You can help by expanding this section.
# Analog and Digital Conversion/ADC Converters
## ADC Converter Steps

An Analog to Digital Converter (ADC) takes an analog input signal and converts the input, through a mathematical function, into a digital output signal. While there are many ways of implementing an ADC, there are three conceptual steps that occur:
* The anti-aliasing filter blocks unwanted frequencies.
* The signal is sampled.
* The sampled signal is quantized.
* The quantized signal is digitally coded.

## Flash Converters ADC

Flash ADC's are the fastest ADC as it takes only on clock pulse to produce digital output. It is a direct compare type architecture. It requires 2^n-1 comparator, 2^n Resistor and a thermometer to binary encoder.

## Successive Approximation ADC

Successive approximation is one of the most widely used popular method due its efficiency The block diagram of SAR ADC s as shown:
Working: Initially, let us set the MSB bit of SAR register i.e. d1 = 1. It is applied to 4-bit D to A converter i.e. as 1000. The D/A converter will generate its analog value and send to control logic The output of control logic is VR. Now at the comparator, there are two inputs VR (Reference voltage) and VA (Input analog). If VR > VA  output of comparator is low and bit d1 is reset correspondingly. If VR <VA  output of comparator is high and bit d1 remains high. The same procedure is repeated for all bits i e for d2, d3,…. dn, and output may be taken in serial or parallel manner. Advantage: The conversion time is fixed as it does not depend upon amplitude of analog input.

## Sigma-Delta ADC

In systems that requires at least 16 bits of resolution, such as audio electronics, by far the most common type of ADC converter is the sigma-delta converter.
The sigma-delta converters, unlike other kinds of ADCs, never sample the signal at any particular point in time. Instead, the output digital number is a weighted average of the signal over the entire sampling time.

## Further reading

* "Signals From Noise: Constructing SINCk Decimators With A Subtractor" by Dave Van Ess
# Analog and Digital Conversion/DAC Converters
## DAC Converter Steps

An Digital to Analog converter (DAC) takes a digital signal and converts it, through a mathematical function, into an analog signal. Again, the DAC may be implemented in a number of ways, but conceptually it contains two steps:
* Convert each time step of the digital signal into an "impulse" with the appropriate energy. In a real system, this could be accomplished by creating short pulses that have the same voltage, but whose total power is modified by changing the pulse length. This pulse train produces a signal whose frequency response is periodic (and theoretically extends to infinity).
* Apply a low-pass filter or an appropriate holding circuit to the time sequence of impulses. This removes all of the high-frequency periodicities, leaving only the reconstructed signal.
# Analog and Digital Conversion/Differential Pulse-Coded Modulation
## Pulse Code Modulation

Pulse Code Modulation is a method of digital transmission of analog signal. PCM converts the analog to Digital signal. Process of PCM: sampling--> Quantization--->Channel--->Hold Ckt--->LPF--->original signal.

## Bandwidth

This section of the Analog and Digital Conversion wikibook is a stub. You can help by expanding this section.
# Conlang/Intermediate/Sounds/Phonotactics

Phonemes don't just randomly combine to make a language. They have to be arranged according to certain rules. For example, if you take the phonemes out of "complexity" and rearrange these randomly, you don't get an English word:
So what is phonotactics? Basically, it tells you what sounds can go where, and what sounds can't. In English, for example, a word can begin with spl- (split, splash), and spr- (spray, spread), but not slr- or srl-, or slp- or srp-. That's just how it works in English. On the other hand, words in Russian can begin with vstr- and dn-, which you wouldn't be seeing any time soon in English. Words in Japanese, on the other hand, can't begin with spr- or spl- or even sp-; it has to begin with a single consonant, or none at all. (When Japanese people pronounce "splash", they tend to say "suh-puh-la-shuh" /s@p@l&S@/ — For comparison, try pronouncing the Ukrainian city of "Dnipropetrovs'k".)

## Syllable Structure

So how would you make these constraints up for your conlang? Well, the earlier section on syllables can help. Start by dividing your conlang's phonemes into different categories and then defining which categories can combine with others in what ways inside a syllable.
For instance, Toki Pona defines its allowed syllables as V or CV(n), where C is any consonant and V is any vowel; "n" represents itself /n/; and the parentheses mean "optional". So syllables like /sen/ and /jo/ are allowed in Toki Pona, but /stan/ and /pit/ are not. Konya allows C(S)V(N), where S is a semivowel (/j/ or /w/) and N is a nasal (/m/ or /n/). Vorlin allowed syllables of the form C$_1$VC$_2$, where C$_1$ is any consonant in Vorlin except /N/ and C$_2$ is any consonant in Vorlin except /h/.
English itself does not have simple phonotactics. It allows (C)(C)(C)V(C)(C)(C)(C)(C). "Strengths" for example is one of the longest allowed syllables even though it doesn't fully use up the allowed coda. But there are still constraints on what consonant clusters are allowed in the onset and coda.
How would you create your own syllable structure? By selecting what sounds can occur in the onset, nucleus, and coda of a syllable (remember back to the section on syllables). You will notice that all the examples above have V (any vowel) as their nucleus and that it's never in brackets (and thus not optional).

## Viable consonant clusters

Another way to specify phonotactics is to make a list of all consonant clusters that are allowed and then, by implication, you should know which consonant clusters can't appear in your language. For example, in the conlang Quenya, the consonant clusters /mb/, /nt/, and /lm/ are allowed, but the consonant clusters /pn/, /rl/, and /ln/ aren't.
Of course, these two ways to describe phonotactics are not mutually exclusive; one can perfectly state that, given the restrictions of syllabical structure, there are certain clusters that don't happen and others that do.

## External links

http://clas.mq.edu.au/speech/phonetics/phonology/syllable/syll_phonotactic.html A nice text about phonotactics. Could be used to improve this page.
# Conlang/Intermediate/Irregularities

If you look at any natural language you will quickly find that its grammar is not completely regular. Almost any language will have some words that don't fit in to the usual pattern. Adding irregularities to your conlang is a must if you want it to feel more 'naturalistic'.

## Types of irregularities

Despite their name, most kinds of irregularities can be classed into groups.

### Sound change

You should be familiar with sound changes from previous chapters (History and Common sound changes). This section aims to show how well-chosen sound changes can affect the regularity of a conlang.
This is probably the most common cause of irregularities. Sound changes cause irregularities by changing a word differently depending on what form it is in. For example, if you have a noun ono and its plural is formed by suffixing a t to the end then you have a perfectly regular relationship.
However, if you make a sound change rule which states that o becomes u at the end of a word, then the relationship is no longer so obvious because the o changes into a u in the singular but doesn't in the plural because the o is no longer at the end of the word.
Using the right sound changes for your conlang is a good way of adding irregularity to it.

### Suppletion

Suppletion is a slightly rarer phenomenon so if you decide to use it in your conlang then you should do so sparingly. But, of course, before you can use it, you need to know what it is:
Suppletion is when a completely separate word replaces one part of a paradigm. For example, the English word went is completely unrelated (etymologically speaking) to go. Went is actually the past tense of a mostly forgotten verb wend which means more or less the same thing as go. Because the verbs came to mean roughly the same thing, most people stopped using wend and used go instead. However, the past tense of wend survived and was used as the past tense of go.
Thus instead of the paradigm go/goes, is going, "goed" (ging), has/have gone, we now have go/goes, is going, went, has/have gone. Suppletion also affected the English verb to be (am/is/are, am/is/are being, was/were, has/have been).
# Conlang/Intermediate/Sound notation/Sources

References:
* IPA (in pdf format).
* Sound reference for the IPA (with audio samples).
* Interactive IPA chart (for cutting and pasting symbols).
* IPA–XSAMPA correspondences