OpenLLM-France/wikimedia huggingface dataset:
# Dutch Defence
## 2. Nf3
## Theory table

For explanation of theory tables, see theory table and for notation, see algebraic notation.
    1. d4 f5 2. Nf3
| | 2 |
| Dutch | ... Nf6 | g3 | to 1...Nf6 2. Nf3 f5 |
| Queen's Pawn Game | ... e6 | g3 | to 1...e6 2. Nf3 f5 |
| | ... d5 | | |
When contributing to this Wikibook, please follow the Conventions for organization.
* Nunn's Chess Openings. 1999. John Nunn (Editor), Graham Burgess, John Emms, Joe Gallagher. ISBN 1-8574-4221-0.
* Modern Chess Openings: MCO-14. 1999. Nick de Firmian, Walter Korn. ISBN 0-8129-3084-3.
* Kasparov, Garry, & Keene, Raymond 1989 Batsford chess openings 2. ISBN 0-8050-3409-9.
# Dutch Defence

Towards this move black has basically two typical set ups and one theory based opening.
* One is a fortress like position with pawn structure f5-e6-d5. This is called the Stonewall defence. This type of position is considered solid, but perhaps too static.
* A dynamic choice is a Leningrad setup. The pawn structure is practically always g6-f5-d6. Black plays in this system, with only a few rare exceptions, his bishop to g7, knight to f6, and castles quickly.
* The more theoretical approach is the Bladel. Black plays Nh6 which allows white to play e4 and transforms the Dutch into an semi open game. Black delays to castle and instead fights for the center with c6 ... followed by d5. White trades off a center pawn for side pawn. White seeks to deliver an early checkmate in the middle game. Black has an additional center pawn which has proven to be a significant advantage in the end game.

## Theory table

For explanation of theory tables, see theory table and for notation, see algebraic notation. .
1. d4 f5 2. c4
| | 2 | 3 | 4 | 5 | 6 | 7 |
| Leningrad | ... g6 | g3 Nf6 | Bg2 Bg7 | Nf3 O-O | O-O d6 | Nc3 Qe8 | = |
| Stonewall Defence | c4 e6 | g3 Nf6 | Bg2 Be7 | Nf3 O-O | O-O d5 | Nc3 Qe8 | = |
| | ... Nf6 | |
| Bladel | .. g6 | Nc3 Nh6 | e4 fxe4 | Nxe4 Bg7 | Nf3 c6 | Bd3 d5 | = |
When contributing to this Wikibook, please follow the Conventions for organization.

## References

* Example from 1989 of play in main line by current world champion Vladimir Kramnik
* Example from 1992 of play in main line by Veselin Topalov
* Kasparov, Garry, & Keene, Raymond 1989 Batsford chess openings 2. ISBN 0-8050-3409-9.
# Chess Opening Theory/1. d4/1...f5/2. c4/2...g6

Dutch Defence

## With g6

A dynamic choice, the Dutch with g6 is a Leningrad setup. The pawn structure is practically always g6-f5-d6. Black plays in this system, with only a few rare exceptions, his bishop to g7, knight to f6, and castles quickly.
Leningrad Dutch main line is, with possible changes in move order: 1. d4 f5 2. c4 Nf6 3. g3 g6 4. Nf3 Bg7 5. Bg2 d6 6. 0-0 0-0 7. Nc3 Qe8 (Diagram).
With 7...Qe8 black plans e5. White usually either plays a pawn advance on queenside with b4-b5 etc., which is helped by the strong bishop on g2 or/and plays for center with e4 and d5. In fact the space advancing move 8 d5 is main line . The main alternatives to 7..Qe8 for black are 7...c6 and 7..Nc6. 7..c6 is considered quite solid and played by former world champion M Botvinnik in the end of his career. 7... Nc6 is an ultra sharp alternative where black usually plays for kingside attack.
On absolute top level Leningrad Dutch is today rarely played. But it is used occasionally and former world champion Vladimir Kramnik played it several times in his youth. Its considered an excellent way for black to play for win, especially below grandmaster level, but the slight weakening of kingside with pawn f5 makes it not the taste of every strong chessplayer.
When contributing to this Wikibook, please follow the conventions for organization.

## Theory table

For explanation of theory tables, see theory table and for notation, see algebraic notation. .
1. d4 f5 2. c4 g6
| | 3 | 4 | 5 | 6 | 7 |
| Leningrad | g3 Nf6 | Bg2 Bg7 | Nf3 O-O | O-O d6 | Nc3 Qe8 | = |
| Bladel | Nc3 Nh6 | e4 fxe4 | Nxe4 Bg7 | Nf3 c6 | Bd3 d5 | = |
When contributing to this Wikibook, please follow the Conventions for organization.

## References

* Example from 1989 of play in main line by current world champion Vladimir Kramnik
* Example from 1992 of play in main line by Veselin Topalov
* Kasparov, Garry, & Keene, Raymond 1989 Batsford chess openings 2. ISBN 0-8050-3409-9.
# Chess Opening Theory/1. d4/1...f5/2. c4/2...g6/3. Nc3/3...Nh6/4. e4/4...fxe4/5. Nxe4/5...Bg7/6. Nf3

=Bladel Modern Variations=

## 2.c4 g6, 3.Nc3 Nh6, 4.e4 fxe4, 5.Nxe4 Bg7, 6.Nf3 - Dutch Defence, Bladel Modern Variations

The move Nf3 on move 6 enters the Bladel Modern Variations. White is trying to gain as much space in the center as possible. Black has delayed to play the pawn into the center so far and instead controls the center with the minor pieces from the outside in hyper modern fashion. Usually, black attacks the center with ... c6 fallowed by d5. Superficially the arrangement of the white knights looks a bit like an open Sicilian. In the Sicilian, both knights are facing towards the queen's side. In the Bladel Modern Variation, both white knights are facing towards the king side. In addition white has an additional pawn in the center.
White has made a concession. White has trade off a center pawn for a side pawn. As a result of that, white will have to deliver a check mate in the middle game. Black has an additional center pawn, which is a significant advantage in the end game. If black survives the attack, black will play for the win in the end game. Again this very similar to the open Sicilians.

## Theory table

For explanation of theory tables, see theory table and for notation, see algebraic notation.
1. d4 f5 2.c4 c6 3.Nc3 Nh6 4.e4 fxe4 5.Nxe4 Bg7 6.Nf3
| | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 |
| Bladel Side Lines | .. O-O | Beg5 d5 | cxd5 Qxd5 | b3 Kh8 | Bxc4 Qd6 | O-O ... | | | +/= |
| | .. d6 | h4 Na6 | c5 dxc5 | Bxh6 Bxh6 | Bxa6 bxa6 | Qb3 ... | | | +/= |
| | .. Nf7 | h4 d5 | cxd5 Qxd5 | Nc3 Qa5 | Bd2 Nc6 | Bc4 ... | | | +/= |
| Bladel Main Lines | .. c6 | Bd3 d5 | cxd5 cxd5 | Bb5+ Nc6 | Bxc6+ bxc6 | Nc5 ... | | | +/= |
| | .. c6 | Bd3 d5 | cxd5 cxd5 | Bb5+ Nc6 | Bxc6+ bxc6 | Nc5 O-O | Bxh6 Bxh6 | Qb3 Qb5+ | = |
| | .. c6 | Bd3 d5 | cxd5 cxd5 | Bb5+ Nc6 | Bxc6+ bxc6 | Nc5 O-O | O-O Bg4 | Re1 Qc8 | = |
| | .. c6 | Bd3 d5 | cxd5 cxd5 | Bb5+ Nc6 | Bxc6+ bxc6 | Nc5 O-O | Qc2 Bh3 | Rg1 Bf5 | +/= |
| | .. c6 | Bd3 d5 | cxd5 cxd5 | Bb5+ Nc6 | Bxc6+ bxc6 | Nc5 O-O | O-O Rb8 | Re1 Bg4 | +/= |
When contributing to this Wikibook, please follow the Conventions for organization.

## References

* Lichess Studies, Dutch Defence, Bladel Family
* Chess.com, Library: Bladel Modern Variations
* Gamenot.com, annotated games: Dutch Defence Bladel Open
* Nunn's Chess Openings. 1999. John Nunn (Editor), Graham Burgess, John Emms, Joe Gallagher. ISBN 1-8574-4221-0.
* Kasparov, Garry, & Keene, Raymond 1989 Batsford chess openings 2. ISBN 0-8050-3409-9.
# DBMS/Recovery

To restore a physical backup of a data file or control file is to reconstruct it and make it available to the Oracle database server. To recover a restored data file is to update it by applying archived redo logs and online redo logs, that is, records of changes made to the database after the backup was taken. If you use RMAN, then you can also recover data files with incremental backups, which are backups of a data file that contain only blocks that changed after a previous incremental backup.
# DBMS/Relational Database

A database based on relational algebra or relation model is called relation database

## Relational data model
### relation

    a table in a relational database is called relation in the mathematical language of relational algebra. relations are unordered.

### attribute

    column of a table in database table is called attributes. columns or attributes have names.

### domain

    set of permissible values for an attribute ( or column) is called domain.

### tuple

    a row in the database table is called tuple in the mathematical language of relational algebra. order of tuples in a relation has no significance.

### database

    a database is a collection of multiple relations.

### schema

    a database design is called schema, alternatively, a schema can refer to namespace within a database.

### cardinality of a relation

    number of tuples in a relation is called cardinality of the relation.
Normalization theory deals with design of relational database schema.

## Keys
### key

    any subset of a relation is called key.

### super key

    a key is called super key if it is sufficient to identify a unique tuple of a relation.

### candidate key

    a minimal super key is called candidate key i.e. no proper subset of a candidate key is super key.

### primary key

    a candidate key chosen as a principal to identify a unique tuple of a relation.It Restrict User Inputs like "Null Values" , "Duplicate Values" etc.

### foreign key

    a key of a relation which is a primary key of some other relation in the relational schema.
# DBMS/Storage Manager

Storage manager module of the database provides the interface between the following component:
* data stored in the database
* the application programs
* queries submitted to the system

### Components of a Storage Manager
#### file manager

function of the file manager is to manage disk space for storage and manage data structure used for storing information.

#### buffer manager

The buffer manager reads disk pages into a main memory page as needed. The collection of main memory pages (called frames) used by the buffer manager for this purpose is called the buffer pool. This is just an array of Page objects. The buffer manager is used by (the code for) access methods, heap files, and relational operators to read / write /allocate / de-allocate pages. The Buffer Manager makes calls to the underlying DB class object, which actually performs these functions on disk pages.
Replacement policies for the buffer manager can be changed easily at compile time.

#### Authorisation and integrity manager

Checks the authorization of users to access data and tests integrity constraints

#### transaction manager
### Indexing and hashing

Many queries reference only a small proportion of records in a file. For example, finding all records at Perryridge branch only returns records where bname = ``Perryridge''. We should be able to locate these records directly, rather than having to read every record and check its branch-name. We then need extra file structuring.

### Evaluation

As we know that, computer has two storage memories 1.primary storage 2.secondary storage
# DBMS/Query Languages
## Query Languages
### query

    the retrieval of tuples from the relations of a relational schema

### query language

    a language used to retrieve information (tuples) from the relations of a relational schema.
types of query language
* procedural language
* non-procedural language
Mathematical query languages
* Relational algebra
* Tuple relational calculus
* Domain relational calculus

### Relational algebra

relational algebra is a procedural query language
** operations
*** selection (r σ s) -
*** projection (r ∏ s) -
*** union: (r ∪ s)
*** set difference: (r – s)
*** Cartesian product: (r X s)
*** rename: ( ρr )
*** intersection:
*** natural join:
*** division:
*** union:
*** intersection:
*** outer join
BY:NA

### Tuple relational calculus

A tuple variable is variable that takes on tuples of a particular relation schema as values. That is, every value assigned to a given tuple variable has the same number and type of fields. A tuple relation calculus query has the form {T I p(t)} where T is a tuple variable and p(T) denotes a formula that describes T; The result of this query is the set of all tuples t for which the formula p(T)evaluates to true with T=t.
# DBMS/XML

Extensible Mark-up Language.
XML stands for EXtensible Markup Language XML is a markup language much like HTML XML was designed to carry data, not to display data XML tags are not predefined. You must define your own tags XML is designed to be self-descriptive XML is a W3C Recommendation
XML
# DChip/Classify Genes

Classify genes by annotation terms
After a list of genes is obtained by “Compare samples” or “Filter genes”, we can use the “Tools/Classify Genes” dialog to classify these genes into different groups according to GeneOntology or other annotational terms. Gene groups have header lines such as “Found 15 GeneOntology 'response to external stimulus' genes in a 120-group (all: 1068/7734, PValue: 0.661181)”. The p-values are calculated in the same way as for the significant gene clusters. Here 120 is the number of genes having GeneOntology annotation in the input gene list, thus may be fewer than the actual number of genes in the list. Note that at "Tools/Classify genes", the whole gene list is considered to assess the significant enrichment; while at clustering, every gene clusters with at least 4 annotated genes is considered. Thus the former gives fewer significant gene groups than the latter.
Significant p-values as defined in the “Tools/Options/Clustering” dialog are suffixed by stars (“***”) in the output file. Also one may check the “Only report significant results” box to output only gene groups with significant p-values. The additional data columns such as expression values or fold changes of the “gene list file” will be copied into the output “classified file”.
To prevent multiple probe sets for the same gene from biasing the result of the functional significance computation, it is best to check “Analysis/Open group/Options/Analysis/Mask redundant probe sets” to exclude the redundant probe sets (identified by LocusLink ID) from a gene list. This can also be done at “Tools/Options/Analysis/Mask redundant probe sets”, but redoing “Analysis/Open group” is desired since the array background information on gene annotation is computed after reading in the “gene information file”.
# DBMS/Transaction
## transaction

    collection logically related operations in a database application.

## Transaction-management

    ensures that the database remains in a consistent (correct) state despite system failures (e.g., power failures and operating system crashes) and transaction failures.
# DBMS/SQL

SQL stands for Structured Query Language. SQL is a non procedural language.
References
* A Gentle Introduction to SQL at SQLzoo
* SQL Tutorial at W3CSchools
relational algebra
# DChip
## Introduction

DNA-Chip Analyzer (dChip) is a software package implementing model-based expression analysis of oligonucleotide arrays (Li and Wong 2001a) and several high-level analysis procedures. The model-based approach allows probe-level analysis on multiple arrays. By pooling information across multiple arrays, it is possible to assess standard errors for the expression indexes. This approach also allows automatic probe selection in the analysis stage to reduce errors due to cross-hybridizing probes and image contamination. High-level analysis in dChip includes comparative analysis and hierarchical clustering. Also see the comparison with Affy MAS software.
The archived dChip website: https://web.archive.org/web/20050611084647/http://www.dchip.org/

## Table of Contents

* Installation
* Support
* Example Method Description
* Design Experiments
* Classify Genes

## Migration

This is an ongoing effort to move dChip manual and useful discussions at dChip Yahoo group to this WikiBook. Feel free to help out or share your own dChip experiences here, e.g. by adding data analysis examples or links to your paper using dChip.
# Freistil/"Freiwillige Ausreise" Unwort des Jahres 2006

What's worth learning? :
| bedeuten | (to) mean |
| verlassen | (to) leave |
| zuvorkommen | (to) forestall, (to) prevent |
| bilden | (to) form |
| ermitteln | (to) determine |
| die Steigerung | increase |
| weitere | further |
Das Unwort des Jahres wird seit 1991 jährlich von einer Experten-Jury der Universität Frankfurt am Main gewählt. Die Aktion bildet das Gegenstück zu den Wörtern des Jahres, die jährlich von der Gesellschaft für deutsche Sprache (GfdS) in Wiesbaden ermittelt werden. Unwort des Jahres 2005 war „Entlassungsproduktivität“, die Steigerung der Arbeitsproduktivität durch Entlassung von Angestellten. Weitere Beispiele sind „Humankapital“ (2004) und „Kollateralschaden“ (1999).
Wikinews: Unwort des Jahres 2006 gewählt. 19. Jan. 2007 Licensed under: CC-BY-2.5 Image: Wikimedia Commons: So many words Licensed under: CC-BY-2.0
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In detail: Overruling Stoiber's problem bear. :
* Edmund Stoiber, Bavarian prime minister and leader of the political party CSU, has always been good for a laugh. The man who, according to a German comedian, cannot only think different thoughts at the same time, but also utter them simultanesously, is famous for his contorted speeches. Unforgotten his Transrapid talk in which he presented the advantages of a high-speed train connection between Munich station and airport by claiming you'd board the station itself. Just as well his short talk about his hobbies in that he accidentally declared one of his famous morning activities was killing flowers and he'd instruct the gardener how to do his wife. This year's famous was the problem bear. In May 2006, a brown bear named JJ1 immigrated to Bavaria; though the migration at first was welcome by animal liberationists it soon turned out that the disturbed animal was a threat to people, making him a "problem bear" in Stoiber's eyes. The sentence undoubtedly was amongst last year's favorites.
# Freistil/Advanced

Fortgeschrittene
# Freistil/Index

This page lists all texts within the project Freistil, sorted by their date of appearance. You can also access the texts sorted by difficulty at Beginner, Mediocre and Advanced.
* Mittelstufe   Schäden von Orkan Kyrill auf rund sieben Milliarden Euro geschätzt 29.1.2007
* Mittelstufe   Mannheim feiert Stadtgründung vor 400 Jahren 24.1.2007
* Freistil/Beginner "Freiwillige Ausreise" Unwort des Jahres 2006 22.1.2007
* Mittelstufe   Erdwärme-Projekt löst Erdbeben aus 17.1.2007
* Fortgeschrittene   Kopftuchverbot in Bayern ist nicht verfassungswidrig 16.1.2007
* Freistil/Beginner Zerbröselnde Geldscheine 15.1.2007
# Freistil/A

A
# Freistil/Art

Freistil
Actual annotated German texts
How to use this book · Article wishes & feedback · Participate
| Nachrichten | Tratsch | Wirtschaft | Wissenschaft | Kunst | Sprache | Übungen |
# Freistil/Erdwärme-Projekt löst Erdbeben aus

What's worth learning? :
| etw. auslösen | (to) cause sth. |
| auftreten | (to) occur |
| der Schaden | damage |
| das Ziel | aim |
| etw. nutzen | (to) make use of sth. |
| laut jm. | according to so. |
| mit etw. rechnen | (to) anticipate sth. |
| immer wieder | again and again |
| entscheiden | (to) decide |
Ziel der Geothermie ist es, durch Bohrungen die Wärme des Erdbodens zur Energiegewinnung zu nutzen. Im Rahmen des Basler Projektes wird in 5 Kilometern Tiefe Wasser in das Gestein gepresst, um es durchlässiger zu machen. Laut dem Projektleiter, der Geothermischen Vereinigung aus dem niedersächsischen Geeste, ist dabei mit leichteren Erdbeben zu rechnen. Die seit dem 8. Dezember 2006 in Basel und Umgebung immer wieder aufgetretenen Erdbeben überraschten jedoch mit der bis zu 100-fachen Stärke selbst die Fachleute.
Voraussichtlich Ende Januar wird die Basler Regierung entscheiden, wie es mit den Arbeiten weitergehen soll.
Adapted from: Wikinews: Erdwärme-Projekt löst erneut Erdbeben aus. 16. Jan. 2007 Wikinews: Leichtes Erdbeben im Raum Weil am Rhein/Landkreis Lörrach. 19. Dez. 2006 Both licensed under: CC-BY-2.5
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# Freistil/How to use

Freistil. Actual annotated German texts. is a loose collection of German texts for foreign language learners. The texts, dealing with actual topics, are annotated with translations and spiced up with explanations and activities, so that you do not only learn new words but also how to use common phrases and typical grammatical structures.
You will find the following features:
* In-text annotations pop up when the mouse cursor hovers over a blue-coloured German word. Here, you find an in-context translation of the given vocabulary, saving you the time to consider an external dictionary.
* What's worth learning? boxes next to the text give you an idea of which vocabulary shows up frequently in daily language and thus is worth learning.
* In detail boxes give you background information and cultural knowledge that help you understand what's going on.
* Text levels at the beginning of the articles hint at the difficulty of the texts.
Before long, all texts will be separately available as PDF documents optimized for printing. In time, there will also be a compilation containing all articles as a complete book. Hopefully, there will be audio recordings of the texts as well.
# Freistil/Exercices

Freistil
Actual annotated German texts
How to use this book · Article wishes & feedback · Participate
| Nachrichten | Tratsch | Wirtschaft | Wissenschaft | Kunst | Sprache | Übungen |
Wörtersuche Finde möglichst viele Wörter, indem du senkrecht, waagrecht oder diagonal von Feld zu Feld springst. Buchstaben dürfen mehrmals verwendet werden, Umlaute dürfen zusammengesetzt werden (z. B. ue statt ü). Erlaubt sind deutsche Wörter in allen Formen, Namen aller Art sind ausgenommen. Viel Spaß!
| C | S | L | B |
| H | W | E | A |
| A | N | S | N |
| E | N | C | H |
Neuling: 5 Wörter. Erfahren: 15 Wörter. Experte: 30 Wörter. Mögliche Lösungen findest du auf der Diskussionsseite.
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# Freistil/Index/Beginner

This page lists all texts with difficulty Freistil/Beginner in chronological order:
* "Freiwillige Ausreise" Unwort des Jahres 2006 22.1.2007
* Zerbröselnde Geldscheine 15.1.2007
# Freistil/Content

Freistil
Actual annotated German texts
How to use this book · Article wishes & feedback · Participate
| Nachrichten | Tratsch | Wirtschaft | Wissenschaft | Kunst | Sprache | Übungen |
# Data Mining Algorithms In R/Packages/gausspred/assess prediction
## Description

These functions evaluate predictive probabilities with average minus log probabilities, error rate, and average loss for a deﬁned loss function, or calculate calibration table.

## Usage

comp_amlp (probs_pred, responses)
comp_er (probs_pred, responses)
comp_loss (probs_pred, y_true, Mloss)
cal_tab (probs_pred, true_y, ix_y, no_cat=10)

## Arguments

probs_pred, a matrix of the predictive probabilities, with rows for cases, columns for groups (different values of response).
Mloss, a matrix deﬁning a loss function, with rows for true values, and columns for predicted values.
responses, 'y_true', 'true_y', a vector of true values of response in test cases.
ix_y, the index of column used to produce calibration table.
no_cat, number of categories in producing calibration table.

## Value

comp_amlp, returns average minus log probabilities, comp_er returns error rate.
comp_loss, returns average loss, and expected loss.
cal_tab, returns a calibration data frame.
# Data Mining Algorithms In R/Packages/gausspred/data gau
## Description

Data generation and processing.

## Usage

gen_bayesgau (n,p,G,tau_nu=1,tau_mu=1,p_tau_x=c(2,1)).
order_features (features, response).

## Arguments

n, the number of cases.
p, the number of features.
G, the number of groups.
tau_nu, the inverse of variance of Gaussian distribution for generating ν.
tau_mu, the inverse of variance of Gaussian distribution for generating µ.
p_tau_x, a vector of 2 numbers, specifying the Gamma distribution as prior for the inverse of the variance for the distribution of features, the ﬁrst number is shape, the second is rate.
features, the features, with the rows for the cases.
response, the response values.

## Value

The function gendata_bayesgau returns the following items:
X, the features, with the row standing for the cases.
y, the response values.
mu, the values of mu, with columns for groups.
sigmas, the variance generating features.
nu, the value of nu for features.
vars, the indice of features, in decreasing order of F-statistic.
fstats, the values of F-statistic for features indexed by vars.

## Example

data <- gen_bayesgau (n = 100,p = 100,G = 2, tau_nu=100,tau_mu = 100, p_tau_x = c(4,1)) i_sel <- order_features (data$X, data$y)