OpenLLM-France/wikimedia huggingface dataset:
# Radioactive Waste Management
## Table of Contents

* Introduction
* Radiation Interaction Fundamentals
* Classifications of Radioactive Waste
* Low Level waste
* Mixed Waste
* Spent Nuclear Fuel
* High Level Waste
* Waste Produced from the Nuclear Fuel Cycle
* Waste Produced from Weapons Development
* Future Research in Waste Management
# Radio and Television/How to setup a RadTV Program
## At the beginning

It's hard to help someone begin a Radio and Television program without first knowing how much access to funds and equipment they have. I fundamentally believe that this class could be taught with access to only one computer and one camera, but in an ideal world students will have access to some equipment. Below is a recommendation of how much to acquire in the way of equipment (or maybe better stated, what to acquire and in what order.

### Starting from Nothing

In order to begin teaching something about Radio and Television Production, you are going to need something that records both video and sound, and have some device to edit the video and sound with. Luckily for the modern teacher, many of our students carry around such a device in their pockets everyday (Their Smartphone!). This is a good place to start, especially if grants and funding have yet to kick in.

### Mid-Sized New Media Program

This is really the size program I am trying to focus on. Many of us, especially at small schools, will never have the funds to move beyond programs of this size, but that does not mean that these students are any less deserving in a high quality media literacy program

#### Student Needs

I have a few recommendations about what Students need to add to a back to school shopping list to make a program run smoothly

##### Musts

* Recording Media (Normally SD Cards, ideally of high speed and capacity)
* A scratch disk (Either a portable hard drive, portable solid state drive, or assigned storage space space on a networked server)

##### Good Ideas

* Headphones
* A smartphone

#### Facility Needs

* Computers capable of editing HD Video
* Cameras
* Camera Stabilizers (Tripods, Gimbals, etc.)
* A variety of Microphones (for field and studio recording)
* A green screen or Infinity wall.
* Lighting equipment (a Cheap LED set will get you started)
* Internet Access
* Editing software (Preferably Adobe, or something with transferable professional skills)

### Large Schools with a TV Studio

It is my sincere hope that as many of us will never have access to facilities like yours at the high school level, that you come from a career in Broadcast television, and are well versed in the equipment you have been given. For assistance in making future purchasing decisions, I recommend working with industry connections and vendors. For most of you, this textbook will be a framework that you will have to adapt to the amount of expensive toys you have.
# DESCRIPTION:

Print file (shell shortcut function).
MORE is a function value.

# ARGUMENTS:

* file -- Accepts %file, :variables and just words (as file names) (Type: file word path string paren)

# (SPECIAL ATTRIBUTES)

* catch
# DESCRIPTION:

Returns TRUE for native values.
NATIVE? is an action value.

# ARGUMENTS:

* value -- (Type: any-type)
# DESCRIPTION:

Returns TRUE if the number is negative.
NEGATIVE? is an action value.

# ARGUMENTS:

* number -- (Type: number char money time)
# DESCRIPTION:

Returns TRUE for money values.
MONEY? is an action value.

# ARGUMENTS:

* value -- (Type: any-type)
# DESCRIPTION:

(undocumented)
NATIVE is a native value.

# ARGUMENTS:

* spec -- (Type: block)
# DESCRIPTION:

Move a value or span of values in a series.
MOVE is a function value.

# ARGUMENTS:

* source -- Source series (Type: series)
* offset -- Offset to move by, or index to move to (Type: integer)

# REFINEMENTS:

* /part -- Move part of a series
** length -- The length of the part to move (Type: integer)
* /skip -- Treat the series as records of fixed size
** size -- Size of each record (Type: integer)
* /to -- Move to an index relative to the head of the series

# (SPECIAL ATTRIBUTES)

* catch
# DESCRIPTION:

Returns the first value multiplied by the second.
MULTIPLY is an action value.

# ARGUMENTS:

* value1 -- (Type: number pair char money time tuple)
* value2 -- (Type: number pair char money time tuple)
# DESCRIPTION:

Changes the sign of a number.
NEGATE is an action value.

# ARGUMENTS:

* number -- (Type: number pair money time bitset)
# Rebol Programming/navy

NAVY is a tuple of value: 0.0.128
# Spanish/Contents/Valuable noun-related phrases

The following are phrases built around nouns to assist beginners in learning both nouns and the present tense and past tense usage.
* Yo tengo una pluma. = I have a pen.
* Este soy yo. = This is me.
* Tengo hambre = I am hungry
* Tengo sed = I am thirsty.
* una manzana = an apple
* una uva = a grape
* una sandía = a watermelon
* el mango = the mango
* la naranja = the orange
* la toronja = the grapefruit
* la pera = the pear
* la fresa = strawberry
* la carne = the meat
* el pollo = the chicken
* la leche = the milk
* el jugo = the juice
* el agua = the water
# Spanish/Exercises/Articles

^Lesson 2^

### Fill in the blank

Por favor, rellena los espacios en blanco con el articulo correcto: Please, fill in the blank with the correct article:
1. ____ mesa (a table)
2. ____ caballos (some horses)
3. ____ gato (the cat)
4. ____ ciudad (the city)
5. ____ casas (some houses)
6. ____ hijos (the sons)
7. ____ hijas (the daughters)
8. ____ perro (a dog)
Soluciones a los ejercicios Solutions to exercices
^Lesson 2^
# Spanish/Dictionary
## Diccionarios Español-Ingles y Inglés-Español

* Wiktionary Spanish index (not much content yet, but together we can build it up)
* Spanish dictionary
* Diccionarios.com (very limited translations per day)
* Wordreference.com
* English Spanish Dictionaries
* Word Magic English Spanish Dictionary
# Spanish/Exercises

This page is a list of links to the exercises in this Wikibook. The solutions can be found here.
Also, when you complete these exercises please do not modify the Wikibooks page containing them by actually filling in the blank or writing in the time or whatever else is called for in the instructions. These exercises are designed to be completed on a separate piece of paper and then checked using the solutions page.

## Lesson 1

* Greetings
* Personal Pronouns
* Ser and Estar

## Lesson 2

* Articles
* Mathematics
* Telling Time

## Lesson 3

* Regular Verbs

## Lesson 4

* Stem Changing Verbs

## Lesson 5

* Comparisons
* Possessive Adjectives
* Questions

## Lesson 6

* Object Pronouns

## Lesson 7

* Preterite
* Preterite vs. Imperfect
# Spanish/Exercises/Articles - Solutions
## Fill in the blank

Rellena los espacios en blanco con el articulo correcto (Fill in the blank with the correct article)
* una mesa (a table)
* unos caballos (some horses)
* el gato (the cat)
* la ciudad (the city)
* unas casas (some houses)
* los hijos (the sons)
* las hijas (the daughters)
* un perro (a dog)
# Spanish/Exercises/Comparisons

^Lesson 5^

### Llena los blancos. Fill in the blank

1. Mario es __________ alto como Luigi.
2. El Sr. Perez tiene __________ perros como Sr. Gonzales.
3. Serena es __________ fuerte que Venus.
4. Mi carro cuesta __________ dinero como tu carro.
5. Los niños juegan __________ horas que los mayores.
6. México es __________ hermoso como España.
7. El abuelo tiene __________ pelo como su hijo.
8. Los gatos son __________ atrevidos como los tigres.
9. Argentina tiene __________ personas como Colombia.
Soluciones a los ejercicios Solutions to exercices
^Lesson 5^
# Spanish/Contributors

The Spanish Wikibook was created on August 2, 2003 by ThomasStrohmann; it was the first language book on Wikibooks. During December 2006, it underwent a complete archive and rewrite, by Celestianpower. A list of major contributors — past and present — can be found below.
* ThomasStrohmann (discuss · email · contribs · logs · count)
* Karl Wick (discuss · email · contribs · logs · count)
* Wintermute (discuss · email · contribs · logs · count)
* Mariela Riva (discuss · email · contribs · logs · count)
* Mxn (discuss · email · contribs · logs · count)
* Sabbut (discuss · email · contribs · logs · count)
* Javier Carro (discuss · email · contribs · logs · count)
* Fenoxielo (discuss · email · contribs · logs · count)
* Think Fast (discuss · email · contribs · logs · count)
* Celestianpower (discuss · email · contribs · logs · count)
* John D'Adamo (discuss · email · contribs · logs · count)
* AnthonyBaldwin (discuss · email · contribs · logs · count)
* Flickts (discuss · email · contribs · logs · count)
* Neoptolemus (discuss · email · contribs · logs · count)
* Akhram (discuss · email · contribs · logs · count)
* ¡Aprovéchalo!
* Learn the Spanish language
* Contents •
* Introduction
* Lesson one •
* Lesson two •
* Lesson three
* Lesson four •
* Lesson five •
* Lesson six
* Lesson seven •
* Lesson eight •
* Lesson nine
* Pronunciation • Contributors
# Spanish/Cover

¡Bienvenidos!
Welcome!
| Argentina | Bolivia | Chile | Colombia | Costa Rica | Cuba |
| Ecuador | El Salvador | España | Estados Unidos | Guatemala | Honduras |
| México | Nicaragua | Panamá | Paraguay | Perú | Puerto Rico |
| República Dominicana | República Dominicana | Uruguay | Uruguay | Venezuela | Venezuela |
# Regions of the United States/Economics, agriculture and industry

Economic activity is a strong force for regionalization. Ohmae, in The Rise of the Region State, argues that regions are "drawn by the deft but invisible hand of the global market for goods and services. ... Region states are natural economic zones."
To Ohmae, region states have between five million and 20 million people. They are "small enough for ... citizens to share certain economic and consumer interests but of adequate size to justify the infrastructure". This infrastructure is a link to the global economy: an international airport, a large harbor, a market for purchase and consumption of imported goods.

## References

* 1 2 Ohmae, Kenichi (1993), "The Rise of the Region State", Foreign Affairs, 72 (2): 78–87, doi:10.2307/20045526
# Regular Expressions/Implementation
### Implementations and running times

There are at least 3 different algorithms that decide if (and how) a given string matches a regular expression. They are based on different representations of the regular expression as a Finite Automaton and on the amount of functionality present in the matcher.
* An NFA based matcher without back-references and look ahead/behind. An input of size O(n) can be tested against a regular expression of size O(m) in time O(nm), and additional O(m) extra space by simulating an NFA using Thompson's algorithm. If c sub-match capture groups are to be recorded, then the running time increases to O(nm log c), but the space requirement remains O(m).
* An NFA based matcher with back-references and look ahead/behind. Such a matcher needs to be implemented using backtracking. An input of size O(n) can be tested against a regular expression of size O(m) in time O(2$^m$n) using backtracking. Some effort is needed to ensure that the backtracking based matcher doesn't enter an infinite loop, testing the same path over and over again.
* A DFA based matcher. DFA based matchers can't support back-references, sub-match captures, or look ahead/behind. This is the oldest and fastest kind of matcher and relies on a result in formal language theory that allows every nondeterministic Finite State Machine (NFA) to be transformed into a deterministic finite state machine (DFA). The algorithm performs or simulates this transformation and then runs the resulting DFA on the input string, one symbol at a time. The latter process (DFA matching) takes time that is proportional to the length of the input string. More precisely, a regular expression of size m on an input alphabet of size S can be converted into a DFA in time O(2$^m$S), and subsequently an input string of size n can be tested against a DFA of any size in time O(n).
The DFA based algorithm is fast to match input against a regular expression, but can be used only for matching and not for recalling grouped subexpressions. There is a variant that can recall grouped subexpressions, but its running time slows down to O(n$^2$m).
The running time of the backtracking based algorithm can be exponential, which simple implementations exhibit when matching against expressions like "(a|aa)*b" that contain both alternation and unbounded quantification and force the algorithm to consider an exponential number of subcases. More complex implementations identify and speed up various common cases where they would otherwise run slowly.
Even though backtracking implementations only give an exponential guarantee in the worst case, they allow much greater flexibility and provide more expressive power. For instance any implementation that allows the use of backreferences, or implements the various improvements that Perl introduced, must use a backtracking implementation.
Some implementations try to provide the best of both algorithms by first running a fast DFA match to see if the string matches the regular expression at all, and only in that case perform a potentially slower backtracking match.
← syntax · Examples →
# Regular Expressions

This book helps you understand how to read, write, and use regular expressions.

## Contents

* Introduction
* Syntaxes
** Simple Regular Expressions
** Basic Regular Expressions
** Perl-Compatible Regular Expressions
** POSIX Basic Regular Expressions
** POSIX-Extended Regular Expressions
** Non-POSIX Basic Regular Expressions
** Emacs Regular Expressions
** Shell Regular Expressions
* Implementation
* Glossary
* Links
* Index
# Regular Expressions/Emacs Regular Expressions

Notes on regular expressions used in text editor Emacs:
* For backslash escaping (magic vs literal), Emacs uses a mixture of BRE and ERE. Like in ERE, Emacs supports unescaped +, ?. Like in BRE, Emacs supports escaped \(, \), \|, \{, \}.
* GNU extensions to regular expressions supported by Emacs include \w, \W, \b, \B, \<, \>, \` , \' (start and end of buffer)
* No "\s" like in PCRE; whitespace is matched by "\s-".
* No "\d" like in PCRE; use [0-9] or [[:digit:]]
* No lookahead and no lookbehind like in PCRE
* Emacs regexp can match characters by syntax using mode-specific syntax tables ("\sc", "\s-", "\s ") or by categories ("\cc", "\cg").

## Use in Tools

Tools and languages that utilize this regular expression syntax include:
* Emacs

## Links

* Regular Expressions at emacswiki.org
* Perl and Emacs regular expressions compared at lemoda.net
# Regular Expressions/Basic Regular Expressions

Basic Regular Expressions: Note that particular implementations of regular expressions interpret the backslash symbol differently in front of some of the metacharacters. For example, egrep and perl interpret unbackslashed parentheses and vertical bars as metacharacters, reserving the backslashed versions to mean the literal characters themselves. Old versions of grep did not support the pipe alternation operator.
Operators :
| Operator | Effect |
| . | The dot operator matches any single character. |
| [ ] | A box enables a single character to be matched against a character list or character range. |
| [^ ] | A compliment box enables a single character not within a character list or character range to be matched. |
| * | An asterisk specifies zero or more characters to match. |
| ^ | The caret anchor matches the beginning of the line. |
| $ | The dollar anchor matches the end of the line. |
Examples: :
| Example | Match |
| ".at" | any three-character string like hat, cat or bat |
| "[hc]at" | hat and cat |
| "[^b]at" | all the matched strings from the regex ".at" except bat |
| "^[hc]at" | hat and cat, but only at the beginning of a line |
| "[hc]at$" | hat and cat, but only at the end of a line |
Many ranges of characters depend on the chosen locale setting. For example, in some settings letters are organized as abc..yzABC..YZ, while in some they are organized as aAbBcC..yYzZ.
The Posix Basic Regular Expressions syntax provided extensions for consistency between utility programs such as grep, sed and awk. These extensions are not supported by some traditional implementations of Unix tools.

## Use in Tools

Tools and languages that utilize this regular expression syntax include: TBD
# Regular Expressions/Example
## Simple Patterns

The simplest and crudest kind of search pattern that can be specified is a simple string, enclosed in slash symbols. For example, the following regular expression searches for any line that contains the string "The". This will not match "the" because regular expressions are case sensitive. It will match words like "There" or "Them".

## Symbols in a regular expression

Some symbols can be used within a regular expression to make the search more specific. For example, the caret symbol acts as an anchor that matches the beginning of the line. Preceding the regular expression with a caret causes only the string at the beginning of the line to be considered for a match. The following regular expression matches any line that begins with the string "The". Lines that contain "The" but do not start with it will not be matched.
/^The/
Similarly, the dollar symbol acts as an anchor that matches the end of the line. Following the regular expression with a dollar matches any line that ends with search pattern. Lines that do not end with "The" will not be matched in this example.
/The$/

## Negation

The following example uses the caret and bracket metacharacters to match any pattern except the word undefined:
/[^(undefined)].*[^(undefined)]/

## Character Mapping

The following examples match punctuation characters and replace them with the equivalent XML entity codes:
Ellipsis:
Emdash:
Endash:
# Regions of the United States

The United States of America is a vast country: third largest in land and population. Local cultures within the United States have been influenced by factors like the identity of nearby peoples, particular economic strengths of each area, and immigration patterns. The country's long, broad history has led to specific regional as well as national identities. Some regions, such as New England, are as old as the nation itself. Other regions, such as Silicon Valley, are thoroughly modern.
This text explores regionalization patterns of the United States, focusing on the forces that led to particular separations. It is a book about borderlands and geographic identity.

## What is a region?

A geographic region is some portion of a larger geographic entity. Region boundaries may be artificial, political, and precise, but more often they are blurry and ill-defined. In The Rise of the Region State, Kenichi Ohmae writes that the "boundaries of the region state are not imposed by political fiat. ... They follow, rather than precede, real flows of human activity, creating nothing new but ratifying existing patterns manifest in countless individual decisions. They represent no threat to the political borders of any nation, and they have no call on any taxpayer's money to finance military forces to defend such borders."

## Regionalization forces

* Culture, language, faith, race and ethnicity
* Economics, agriculture and industry
* Natural geography, ecology and weather

## References

* ↑ Ohmae, Kenichi (1993), "The Rise of the Region State", Foreign Affairs, 72 (2): 78–87, doi:10.2307/20045526
# SPARC Assembly/Ultra SPARC

This page is going to discuss the upgrades in Ultra SPARC, and will discuss some issues thereof.
The UltraSPARC processors were designed by Sun Microsystems and implement the SPARC version 9 (sparcv9) architecture. This architecture natively supports 64 bit processing by extending the virtual address space to 64 bits and widening the general purpose registers to 64 bits.
# SPARQL/Bad aggregate

The error Bad aggregate might appear when coding mistakes upon using GROUP BY. See also the chapter modifiers for a description of GROUP BY.
The error "Bad aggregate" does not specify what exactly is the mistake, hence this explanation to help you find out the cause.
This is a correct example. This list the children of Bach, grouped by their mother:
Try it!
The first condition is that the grouping variables should match.
* In the SELECT the grouping is by both variables ?mother and ?motherLabel.
* In the GROUP BY the same variables ?mother ?motherLabel should be listed.
Try for yourself what happens when you use GROUP BY ?mother. At the bottom of the long list of the errors you might find the text "Non-aggregate variable in select expression: motherLabel". If the GROUP BY is left out completely the error message is similar "Non-aggregate variable in select expression: mother".
The second condition is that the rest of the variables in the SELECT should each result into one value.
* You need expressions that will result into one value, for instance COUNT or one of the other Aggregate functions MIN, MAX, SUM or AVG.
* You can also use GROUP_CONCAT to list all values into one variable, as all values of ?childLabel into ?names.
* All variables should be converted with expressions as described above, even if a variable has one value only.
Try for yourself what happens when you change in the rest of the SELECT code. If for instance you would use ?childLabel you might find at the bottom of the long list of the errors the text "Non-aggregate variable in select expression: childLabel".
The error message is always "Non-aggregate variable in select expression: xxxxx", whether a variable is missing from the GROUP BY or a variable not aggregated at the SELECT clause.
# SPARQL/Aggregate functions

Aggregate functions are used in combination with modifier GROUP BY.
Available aggregate functions are:
* COUNT: the number of elements. You can also write COUNT(*) to simply count all results.
* SUM, AVG: the sum or average of all elements, respectively. If the elements aren't numbers, you'll get weird results.
* MIN, MAX: the minimum or maximum value of all elements, respectively. This works for all value types; numbers are sorted numerically, strings and other types lexically.
* SAMPLE: any element. This is occasionally useful if you know there's only one result, or if you don't care which one is returned.
* GROUP_CONCAT: concatenates all elements.

## Aggregate functions with GROUP BY

See modifier GROUP BY for examples.
When using aggregate functions of a label, all labels should be defined explicitly in the SERVICE.
Additionally, you can add a DISTINCT modifier for any of these functions to eliminate duplicate results. For example, if there are two results but they both have the same value in ?var, then COUNT(?var) will return 2 but COUNT(DISTINCT ?var) will only return 1. You often have to use DISTINCT when your query can return the same item multiple times – this can happen if, for example, you use ?item wdt:P31/wdt:P279* ?class, and there are multiple paths from ?item to ?class: you will get a new result for each of those paths, even though all the values in the result are identical. (If you're not grouping, you can also eliminate those duplicate results by starting the query with SELECT DISTINCT instead of just SELECT.)

## Aggregate functions with HAVING

Aggregate functions can also be used with the HAVING modifier.
See for instance this query to check for duplicate IATA codes for airports:
Try it!

## References

* A Guide To WDQS
# SPARC Assembly/Sparc V8

Some examples of 32bit SPARC V8 computers are the sun4m architecture as well as the embedded systems based on the LEON SPARC which is compatible with the SPARC V8 instruction set.
# SPARC Assembly/Subroutines

This page is going to discuss the use of subroutines in SPARC Assembly.

## Subroutine Linkage

A typical (non-leaf) subroutine has a procedure prologue and epilogue something like this:

## Further reading

* ↑ Peter Magnusson. "Understanding stacks and registers in the Sparc architecture(s)".
* ↑ Mark Smotherman. "SPARC Subroutines".