text:
Mathematical Proof/Functions

Introduction
In the previous chapter, we have discussed the concept of. There are not much restrictions on the relations. For instance, for a relation from set $$A$$ to set $$B$$, every element of $$A$$ can be related to no elements of $$B$$, exactly one element of $$B$$, or multiple elements of $$B$$. In this chapter, we will focus on a particular type of relations from set $$A$$ to set $$B$$ where element in $$A$$ is related to  (or an ) element of $$B$$.

You should have encountered the concept of before, e.g. a function defined by $$f(x)=x^2$$ gives you a value of $$f(x)$$ for every given value of $$x$$. The functions you have encountered are likely to be in the above form, i.e. in the form of an equation. Also, the value of $$x$$ and $$f(x)$$ are likely to be real numbers.

But we can generalize such ideas to more general situations where $$x$$ and $$f(x)$$ are not necessarily real numbers (e.g., they can be elements of certain sets), and the functions need not be expressed by a formula like above. As a result, the concept and definition of functions discussed here may seem foreign to you, and look quite different from what you have previously learnt about functions.

Definitions
We should be aware that the codomain of a function is not necessarily the same as the range of a function. The following is the definition of the of a function (same as the definition for a relation).

Since the domain and codomain, in addition to the "way" of the mapping, all affect the "behaviour" and properties of a function, it is natural to incorporate all these features into the definition of of functions:

Injective, surjective and bijective functions
In this section, we will discuss some important properties that a function may possess, namely injectivity, surjectivity, and bijectivity.

Composition of functions
Let $$A,B$$ and $$C$$ be nonempty sets, and let $$f:A\to B$$ and $$g:B\to C$$ be two functions. In this section, we are going to discuss a way to create a new function from "combining" the two functions $$f$$ and $$g$$, called their :

Although the composition of functions is not commutative, it is.

Now, let us study some results that are related to the composition, injectivity, surjectivity, and bijectivity.

After knowing such results, it is natural to question that whether the of the above proposition holds. Indeed, the converse does not hold, and we have the following results:

To summarize the results, we have the following table:

Inverse functions
Recall that a function $$f:A\to B$$ is a special relation from set $$A$$ to set $$B$$ satisfying some requirements. Also, recall that given a relation from $$A$$ to $$B$$, the $$R^{-1}$$ is defined to be $$R^{-1}=\{(b,a):(a,b)\in R\}\subseteq B\times A.$$ We know that the inverse relation is always a relation itself. However, is the inverse relation of a $$f:A\to B$$ always a  from $$B$$ to $$A$$ itself? The answer is, indeed, no. Consider the following example.

Of course, when the inverse relation of a function $$f:A\to B$$ turns out to be also a function from $$B$$ to $$A$$, it is natural to define it as the of $$f$$:

We are then interested in knowing under what conditions the inverse relation $$f^{-1}$$ is a function from $$B$$ to $$A$$, so that the.

First, in order for $$f^{-1}$$ to be a function from $$B$$ to $$A$$, we must have $$\operatorname{dom}f^{-1}=B$$. So, we need to ensure that element of $$B$$ is related to some elements in $$A$$, so that when we "reverse" the ordered pairs in $$f$$ to get $$f^{-1}$$, there is at least one image for every $$b\in B$$. This means $$\operatorname{ran}f=B$$, i.e., $$f$$ needs to be surjective.

Of course, we also need to ensure that there is a image for every $$b\in B$$. Under the condition that $$f$$ is surjective, there is at least one image for every $$b\in B$$ already. So, it remains to ensure that there is one image for every $$b\in B$$.

To ensure this, we need the function $$f$$ to be injective, since, if $$f$$ is injective, then every element of $$B$$ has at most one pre-image. So, when we "reverse" the ordered pairs in $$f$$ to get $$f^{-1}$$, every element of $$B$$ has at most one.

From this discussion, we know that if $$f^{-1}$$ is a function from $$B$$ to $$A$$, then $$f$$ has to be injective and surjective, i.e. bijective. This shows that the bijectivity of $$f$$ is the necessary condition for the existence of the inverse function. Is it also the sufficient condition? It turns out that the bijectivity of $$f$$ is actually the condition for the existence of the inverse function:

Hence, from this theorem, we know that it is only meaningful to talk about inverse function of $$f$$ when $$f$$ is bijective. If $$f$$ is not bijective, then its inverse function does not exist at all, and it is meaningless to talk about it. The following theorem further suggests that the inverse function must also be bijective.

Another common definition of inverse function is that the inverse function of $$f$$, denoted by $$f^{-1}$$, is a function satisfying $$f^{-1}\circ f=id_A\text{ and }f\circ f^{-1}=id_B.$$ It turns out that these two definitions of inverse function are indeed (logically) equivalent. Consider the following theorem.

The converse of the above theorem is also true. More precisely, if $$f$$ is bijective, and thus its inverse function $$f^{-1}$$ exists, then we have $$f\circ f^{-1}=id_A$$ and $$f^{-1}\circ f=id_B$$. (Details are left to the following exercise.) Hence, the two definitions are actually logically equivalent, in the sense that It then follows that the function $$g$$ satisfying $$f\circ g=id_A$$ and $$g\circ f=id_B$$ is unique, since the inverse function is unique.
 * by the above theorem, the conditions in the alternative definition imply the conditions in our definition.
 * by the above remark, the conditions in our definition imply the conditions in the alternative definition.

Here, we will introduce an approach to find a formula for the inverse function. But this approach does not work.

In this approach, we use some algebraic manipulation to find the inverse function. However, such method is not always possible. For instance, the function $$f:\mathbb R\to(0,\infty)$$ defined by $$f(x)=e^x$$ is bijective, but its inverse function $$f^{-1}:(0,\infty)\to\mathbb R$$ is given by (indeed, defined to be) $$f^{-1}(x)=\ln x$$. In this case, such inverse function cannot be obtained by such algebraic manipulation.

Image sets and preimage sets
The concepts discussed in this section are the generalizations of the concepts of and.

Graphically, the image set looks like: A             B The preimage set looks like A             B
 * . X |      | f(X) |
 * . X |      | f(X) |
 * . X |      | f(X) |
 * f-1(Y)|      |      |
 * .  |       |  Y   |
 * .  |       |  Y   |

Cardinalities of sets
Recall that a set is $$S$$ if it contains a finite number of elements, i.e., $$S=\varnothing$$ or $$|S|=n$$ for some $$n\in\mathbb N$$. On the other hand, a set is infinite if it is not finite. Previously, we have studied cardinalities of finite sets, and we have left cardinalities of sets undefined. But, it turns out that we can define cardinalities of infinite sets in a more complicated way, using.

It may now seem that we can write something like $$|S|=\infty$$ for an infinite set $$S$$. But it turns out that this is not quite meaningful, and as we shall see, infinite sets can have different cardinalities, or different "sizes". That is, there are different sizes of infinity! (in some sense).

To motivate the definition for the cardinalities of infinite sets, let us first consider a simple example of sets.

This example suggests that for two finite (nonempty) sets $$A$$ and $$B$$, they have the if there exists a bijective function from $$A$$ to $$B$$ (or from $$B$$ to $$A$$. One such function is given by the  of the bijective function from $$A$$ to $$B$$.) This leads us to the following definition:

The result in this example may seem strange and counter-intuitive, since $$\mathbb Z$$ seems to be twice as large as $$E$$, and $$E$$ is a proper subset of $$\mathbb Z$$, but they turn out to have the same cardinality. Such phenomenon is actually quite common when we deal with the cardinalities of.

Fortunately, the numerical equivalence has some nice properties: reflexivity, symmetry and transitivity:

Now, let us focus on the set $$\mathbb N$$, and consider the (infinite) sets having the same cardinality as $$\mathbb N$$. We give a special name for such sets:

Using this definition, we can further define another property of a set:

We now know that $$\mathbb N$$ and $$\mathbb Z$$ have the same cardinality. It is then natural to consider the set of all rational numbers, $$\mathbb Q$$. It appears that $$\mathbb Q$$ is much larger than $$\mathbb Z$$, so it may seem that $$\mathbb Q$$ should no longer be denumerable, and be uncountable. But it turns out that $$\mathbb Q$$ is also denumerable.

So, we have proved that $$|\mathbb N|=|\mathbb Z|=|\mathbb Q|$$. It turns out that even if $$\mathbb Q$$ seems much larger than $$\mathbb N$$ and $$\mathbb Z$$, it still has the same cardinality as them. A natural question then arises: is there any uncountable set at all? The answer is yes, and the best known example is the set of all real numbers, $$\mathbb R$$. In other words, there does not exist a bijective function from $$\mathbb N$$ to $$\mathbb R$$. Since $$\mathbb R$$ is uncountable, this suggests that the "size" of $$\mathbb R$$ is different from the "size" of $$\mathbb N$$, i.e., there are different sizes of infinity (in some sense).

The following results may be useful for comparing denumerable or uncountable sets.

title: Mathematical Proof/Functions


text:
AI Art Generation Handbook/Out-painting

1st step: Select the images and place it at the canvas

Final Step: Select the suitable images and save the images

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/

title: AI Art Generation Handbook/Out-painting


text:
Fractals/png

PNG features:
 * for png color depth can range from 1 to 64 bits per pixel
 * All PNG images contain a single static image
 * 1-, 2-, 4- and 8-bit palette support (like GIF)
 * 1-, 2-, 4-, 8- and 16-bit grayscale support
 * 8- and 16-bit-per-sample (that is, 24- and 48-bit) truecolor support
 * full alpha transparency in 8- and 16-bit modes
 * "palette-alpha" mode, effectively transforming normal RGB palette into RGBA
 * gamma correction for cross-platform "brightness" control

=png file versions= PNGN = PNG N bit_per_color ( = nr_of_channels * bits_per_channel)
 * PNG8 has 2^8 = 256 shades of gray or 256 indexed-color with 8-bit samples, usually means opaque or with GIF-like, binary transparency, but sometimes includes translucency
 * PNG16
 * gray:
 * Such images are typically used only in science, medicine, and the film industry
 * It splits the color space evenly to $$2^{16} = 65\ 536$$ shades of grey
 * Note that it may be converted down to 8-bit for display, when display devices don't support 16 bits. Any values greater then 256 will simply be clipped to 255.
 * PNG24 has a color depth of 8 x 3 channels ( RGB) which is 24 bits per pixel color  = $$(2^8)^3 = 2^{8*3}   = 2^{24} = 16\ 777\ 216$$ total colours and 2^8 = 256 shades of gray = Truecolor
 * PNG32 has a color depth of 8 x 4 channels ( RGBA) which is 32 bits per pixel color = $$(2^8)^4 = 2^{8*4}   = 2^{32} = 4\ 294\ 967\ 296$$ colors =  Truecolor and alpha
 * PNG48
 * RGBA: has a color depth of 12 x 4 channels ( RGBA) which is 48 bits per pixel color = $$(2^{12})^4 = 2^{12*4} = 2^{48} = 281\ 474\ 976\ 710\ 656$$ colors = Truecolor and alpha
 * RGB:
 * PNG64 has a color depth of 16 x 4 channels ( RGBA) which is 64 bits per pixel color = $$(2^{16})^4 = 2^{16*4} = 2^{64} = 18\ 446\ 744\ 073\ 709\ 551\ 616$$ colors

=Key words=
 * sample = intersection of a channel and a pixel in an image.
 * sample depth = number of bits used to represent a sample value. In an indexed-colour PNG image, samples are stored in the palette and thus the sample depth is always 8 by definition of the palette. In other types of PNG image it is the same as the bit depth
 * An tagged image is an image that is explicitly assigned a color profile, as defined by the image format. This is usually done by including an International Color Consortium (ICC) profile [ICC].

=File format=
 * A PNG file starts with an 8-byte signature ( file header)
 * After the header, comes a series of chunks

A chunk consists of four parts:
 * length (4 bytes, big-endian),
 * chunk type/name (4 bytes )
 * chunk data (length bytes)
 * CRC (cyclic redundancy code/checksum; 4 bytes ). The CRC is a network-byte-order CRC-32 computed over the chunk type and chunk data, but not the length.

file header

The first eight bytes of a PNG file is an 8-byte signature ( a magic signature) with the following (decimal) values"

DEC: 137 80 78 71 13 10 26 10 HEX: 89 50 4E 47 0D 0A 1A 0A ASC: NA  P  N  G \r \n NA \n

Critical chunks

 * must be the first chunk; it contains (in this order) the image's
 * width (4 bytes)
 * height (4 bytes)
 * bit depth (1 byte) Bit depth is a single-byte integer giving the number of bits per sample or per palette index (not per pixel). Valid values are 1, 2, 4, 8, and 16, although not all values are allowed for all colour types. See the table below
 * color type (1 byte, values 0, 2, 3, 4, or 6)
 * compression method (1 byte, value 0)
 * filter method (1 byte, value 0)
 * interlace method (1 byte, values 0 "no interlace" or 1 "Adam7 interlace") (13 data bytes total).
 * contains the palette: a list of colors.
 * contains the image, which may be split among multiple IDAT chunks. Such splitting increases filesize slightly, but makes it possible to generate a PNG in a streaming manner. The IDAT chunk contains the actual image data, which is the output stream of the compression algorithm.
 * marks the image end; the data field of the IEND chunk has 0 bytes/is empty.

Ancillary chunks

 * gives the default background color. It is intended for use when there is no better choice available, such as in standalone image viewers (but not web browsers; see below for more details).
 * gives the chromaticity coordinates of the display primaries and white point.
 * is for storing digital signatures.
 * stores Exif metadata.
 * specifies gamma. The gAMA chunk contains only 4 bytes, and its value represents the gamma value multiplied by 100,000; for example, the gamma value 1/3.4 calculates to 29411.7647059 ((1/3.4)*(100,000)) and is converted to an integer (29412) for storage.
 * can store the histogram, or total amount of each color in the image.
 * is an ICC color profile
 * contains a keyword and UTF-8 text, with encodings for possible compression and translations marked with language tag. The Extensible Metadata Platform (XMP) uses this chunk with a keyword 'XML:com.adobe.xmp'
 * holds the intended pixel size (or pixel aspect ratio); the pHYs contains "Pixels per unit, X axis" (4 bytes), "Pixels per unit, Y axis" (4 bytes), and "Unit specifier" (1 byte) for a total of 9 bytes.
 * (significant bits) indicates the color-accuracy of the source data; this chunk contains a total of between 1 and 5 bytes, depending on the color type.
 * suggests a palette to use if the full range of colors is unavailable.
 * indicates that the standard sRGB color space is used; the sRGB chunk contains only 1 byte, which is used for "rendering intent" (4 values—0, 1, 2, and 3—are defined for rendering intent).
 * stereo-image indicator chunk for stereoscopic images.
 * can store text that can be represented in ISO/IEC 8859-1, with one key-value pair for each chunk. The "key" must be between 1 and 79 characters long. Separator is a null character. The "value" can be any length, including zero up to the maximum permissible chunk size minus the length of the keyword and separator. Neither "key" nor "value" can contain null character. Leading or trailing spaces are also disallowed.
 * stores the time that the image was last changed.
 * contains transparency information. For indexed images, it stores alpha channel values for one or more palette entries. For truecolor and grayscale images, it stores a single pixel value that is to be regarded as fully transparent.
 * contains compressed text (and a compression method marker) with the same limits as.

Rendering intent values (Value	Name	Description)
 * 0	= Perceptual	for images preferring good adaptation to the output device gamut at the expense of colorimetric accuracy, such as photographs.
 * 1	= Relative colorimetric	for images requiring colour appearance matching (relative to the output device white point), such as logos.
 * 2	= Saturation	for images preferring preservation of saturation at the expense of hue and lightness, such as charts and graphs.
 * 3	= Absolute colorimetric	for images requiring preservation of absolute colorimetry, such as previews of images destined for a different output device (proofs).

= Examples =

Displayed in the fashion of hex editors, with on the left side byte values shown in hex format, and on the right side their equivalent characters from w:ISO-8859-1 with unrecognized and control characters replaced with periods. Additionally the PNG signature and individual chunks are marked with colors. Note they are easy to identify because of their human readable type names (in this example PNG, IHDR, IDAT, and IEND).

PNG Signature(8 bytes): 89 50 4E 47 0D 0A 1A 0A =======Chunk start======= IHDR Chunk: IHDR chunk length(4 bytes): 00 00 00 0D IHDR chunk type(Identifies chunk type to be IHDR): 49 48 44 52 Image width in pixels(variable 4): xx xx xx xx       Image height in pixels(variable 4): xx xx xx xx        Flags in the chunk(variable 5 bytes): xx xx xx xx xx        CRC checksum(variable 4 bytes): xx xx xx xx     =======Chunk end=======

read png
Read png with od program

od -c test.png | head -4 Example output: 0000000 211  P   N   G  \r  \n 032  \n  \0  \0  \0 004   C   g   B   I 0000020   P  \0     002   + 325 263 177  \0  \0  \0  \r   I   H   D   R 0000040  \0  \0  \0   `  \0  \0  \0   `  \b 006  \0  \0  \0 342 230   w 0000060   8  \0  \0  \0       c   H   R   M  \0  \0   z   %  \0  \0 200

Programs:
 * pngcheck a command-line program by Greg Roelofs

pngcheck -c *.png pngcheck -cvt *.png

=code=
 * ImageMagic creating png in polish wikibooks
 * rpng is a simple and easy-to-use C library to manage png chunks by raysan5

octave
Octave code that creates array ( memory image) and saves it to the file

=collection of images=
 * PngSuite created by Willem van Schaik  The "official" test-suite for PNG
 * Rich Franzen's PNG Gallery
 * 16-bit integer ProPhotoRGB png : saturated-colors.png

=Creating png files=
 * Image Magic

=Checking png files=

file p.png

ICC embaded profile
 * PNG-ICC-tests
 * results

=Editing png files=
 * hex editors:
 * editing of pixel data in a hex editor is pretty much impossible because of of the compression algorithm
 * one can edit header,
 * use an online crc calculator to calculate the checksum for the png
 * use TS/JS
 * pngcheck

Hexdump

hexdump --canonical p.png

To show the output of the PNG header as described by the official libpng spec
 * to process the PNG file in 8-byte chunks
 * the PNG spec is documented in decimal, which is represented by %d according to the hexdump documentation
 * make the output perfect by adding a blank space after each integer

hexdump -n8 -e'8/1 "%d ""\n"' p.png

ICC profile tasks
 * Extract ICC profile from the file
 * To remove an ICC profile
 * To embed an ICC prolile

Extract ICC profile from the file:

exiftool -icc_profile -b -w icc somefile.png

To remove an ICC profile

pngcrush -rem iCCP foo.png result.png

=See also=
 * png-embedded-malicious-payload-hidden-in-a-png-file by THIAGO MARQUES
 * png compatybility
 * pngquant

=References=

title: Fractals/png


text:
Pokémon/Pokédex/Mabosstiff

Description
A doglike Pokémon.

How to Evolve
Maschiff evolves into Mabosstiff when it reaches level 30.

Name
The name continues the "Mastiff" inspiration, while adding the word "boss" in the middle.

title: Pokémon/Pokédex/Mabosstiff


text:
Pokémon/Pokédex/Lucario

Description
Lucario is a bipedal Pokémon, with a blue and black motif.

Base Statistics
Lucario is a dual type Pokémon, possessing both fighting and steel types.

How to Evolve
Riolu evolves into Lucario.

title: Pokémon/Pokédex/Lucario


text:
Pokémon/Pokédex/Riolu

How to Evolve
Riolu evolves into Lucario.

title: Pokémon/Pokédex/Riolu


text:
Cookbook:Salsa

Salsa (literally "sauce") refers to a variety of condiments associated with Latin American and Spanish cuisine. It has been claimed to originate in the cuisines of the Inca, Aztec, and Maya cultures.

Characteristics
There exists a wide range of salsas, with varying characteristics. They all tend to be spicy fruit/vegetable-based condiments, but they differ in composition and method of preparation. Many salsas in the United States contain tomatoes, onions, garlic, chiles, and lime or vinegar. Other varieties may include papaya, mango, plantain, corn, beans, bell pepper, peaches, and more. They are often seasoned with cumin and cilantro. Salsas may be cooked or fresh, thick or thin, smooth to coarse in texture, mild to hot in spice levels, smoky, and/or sweet.

Fruit salsa
Fruit salsas are typically fresh, chunky, spicy salsas featuring a range of fruits other than/in addition to tomato. These can include mango, pineapple, melon, papaya, grape, and more. They are sweet and refreshing.

Picante salsa
Picante salsa in the US is a red, tomato-based salsa containing onions and chiles. It tends to be smoother and more finely-chopped rather than chunky. It should not be confused with the Mexican salsa picante, which is more akin to a hot sauce.

Pico de gallo
Pico de gallo is a fresh salsa (sometimes accordingly called salsa fresca) made of rough-chopped tomatoes, chiles, onions, cilantro, and lime juice. Because it is raw and chunky, it has a lively assortment of colors.

Salsa de aguacate
Salsa de aguacate is a smooth salsa made of avocados, tomatillos, and chiles (often serrano). It is creamy and smooth, almost always served raw. Although it contains avocado, it should not be confused with guacamole.

Salsa roja
Salsa roja, or red salsa, tends to contain red tomatoes, red chiles, and onions. It can be raw or cooked, and the consistency can be smooth or chunky. It is very common in United States grocery stores, and many in the US will think of salsa roja as "generic" salsa.

Salsa taquera
Taco salsa is a variety of smooth and spicy tomato salsa. It features spicy peppers and is often used as an accompaniment to tacos.

Salsa verde
Salsa verde, or green salsa, is a Mexican salsa variety made of tomatillos and green chiles. It may also include onion and cilantro. It has a bright flavor and smooth texture, and it can be cooked or raw. Because of the high acidity in tomatillos, this salsa tends not to need an additional acid.

Production
Salsa is traditionally made with a mortar and pestle or molcajete, which allows the ingredients to be ground together to the desired consistency. Salsas may also be chopped by hand or puréed in a blender or food processor. Fresh salsas should be allowed to sit for a short period to allow the flavors to meld, then eaten as soon as possible.

Use
Salsas can be served with a wide variety of foods. They commonly accompany Mexican and Tex-Mex dishes in the United States, such as burritos, tacos, enchiladas, quesadillas, eggs, and more. They are also often served as a dip with chips.

Recipes

 * Salsa
 * Salsa (Fermented)
 * Anchovy Herb Salsa Verde
 * Eärgon Salsa
 * California Fusion Peach Salsa
 * Creamy Aioli Salsa
 * Mango Avocado Salsa
 * Pico de Gallo

title: Cookbook:Salsa


text:
Lombard/Dictionaries and Wiktionary

Lombard language dictionaries
In the module about the orthography it was explained that Lombard historically has never had a common orthography, but there are different orthographies, each linked to the literary tradition of the main town and cities. For this reason it is difficult to find real dictionaries of Lombard language on the market, which as already mentioned is a cluster of dialects, but rather dictionaries of local dialects written in their historical orthographies. Furthermore, the available dictionaries do not give definitions in Lombard, but in reality translations from Lombard to Italian or from Italian to one of the variants of Lombard in a certain orthography. Furthermore, as regards the dictionaries, those available online are written in an archaic Italian, that of the mid-nineteenth century. Anyone wishing to write Lombard using the New Lombard Orthography could however get into trouble due to the need to convert words written with another orthography into the New Lombard Orthography. Precisely for this reason, within this course there will be modules whose purpose is to help in this orthographic conversion into the New Lombard Orthography, while the Lombard language wikictionary, written above all in New Lombard Orthography, aims to show within the same page the different ways of writing and pronouncing the same word in the different variants of the Lombard language.

Dictionaries available on line
Among the dictionaries that can be consulted online we can list:

Note

 * = fundamental
 * = of medium importance
 * = rare

Wiktionary in Lombard language
The image below shows the main page of the Lombard language Wiktionary. To search for a word, simply write the word in the search box and then click on "search for the right word" or "ENTER" on the computer keyboard. Inside the Wiktionary pages, as shown in the example below, there are: As with all Wiki projects, anyone can contribute by accepting to release a contribution under the conditions of the GNU Free Documentation License.
 * Definitions in Lombard;
 * The spellings of the same word in different orthographies and dialects;
 * The pronunciation of the same word in different dialects;
 * The etymology;
 * Translation into several languages;

Automatic translators
Nowadays there are no automatic translators specifically dedicated to Lombard language, since the end of 2022 the progress of the articial intelligence, in particular make available by OpenAI are starting to allow the automatic translation of the Lombard language, the operation will be explained in the paragraph below.

The openAI chat
To use the open AI chat you must go to the site "https://chat.openai.com/auth/login" and register. Once you have registered, you can log in with your username and your password. After logging in you will have an automatic chat that gives answers thanks to artificial intelligence taking as source material what foeund on the web.

To obtain translations from Lombard to Ensglish you must write in the chat: "translate from Lombard into English:" followed by the text to be translated. We proceed in a similar way to obtain translations from Italian to English.

Nowadays translations do not always provide accurate and correct results. Translations from English to Lombard are not always successful, and anyway, given the widespread presence of errors, can be used mainly by a person who knows Lombard as a starting point to speed up a translation; this is comprehensible since artificial intelligence draws from online materials that are written in different orthographies and dialects. We could expect an improvement in the coming years if the lombard writers converge in the use of a single orthography. Translations from Lombardy to English are better, although also in this case they are not 100% accurated.
 * Note

title: Lombard/Dictionaries and Wiktionary


text:
Template:Wt/lmo/+CrCR

CrCR

title: Template:Wt/lmo/+CrCR


text:
Talk:Lombard/Dictionaries and Wiktionary

Translated from
Transalated from https://it.wikibooks.org/wiki/Lombardo/Dizionari_e_Wikizionario on 18 Desember 2022 Gat lombard (discuss • contribs) 21:34, 18 December 2022 (UTC)


text: Talk:Structural Biochemistry/Warfarin

title: Talk:Structural Biochemistry/Warfarin


text:
Cookbook:Kirsch

Kirsch or kirschwasser is a type of eau-de-vie brandy made from cherries. It originates from Germany and German-speaking regions of Switzerland. It should not be confused with other types of cherry brandy.

Characteristics
Kirsch is a clear, colorless liqueur. It is dry (as opposed to sweet), with a cherry fragrance and notes of almond flavor from the cherry pits. It has a high alcohol content, ranging from 90–100 proof.

Production
First, whole sour or sweet cherries are mashed into a pulp, crushing some of the pits in the process. This entire mixture is then left to ferment before transfer to a pot still, where it is distilled twice. The distillate is either unaged or aged in wax-coated barrels, which produces a clear colorless liqueur.

Use
Kirsch can be serve neat and on its own. It can also be incorporated into cocktails and mixed drinks, such as the Lady Finger or Florida Cocktail. It is also used often as a flavoring in cooking and baking, such as in black forest cake, whipped cream, and a variety of chocolate desserts. It can be substituted by plum or pear eau-de-vie.

Recipes

 * Schwarzwälder Kirschtorte (Black Forest Cake)

title: Cookbook:Kirsch


text:
Cookbook:Fried Pita Bread with Eggs

This is a westernized version of a dish from Yemen.

Ingredients

 * 1 tbsp extra-virgin olive oil
 * 1 pita bread
 * 2 eggs
 * Salt
 * Black pepper

Procedure

 * 1) In a heavy skillet, heat the oil at medium-low temperature.
 * 2) Tear the pita into small pieces, and add to the hot oil.
 * 3) Cook, stirring frequently, until the bread is lightly browned and crispy.
 * 4) Add the eggs and scramble them with the bread.
 * 5) Season with salt and ground black pepper to taste. Serve hot.

title: Cookbook:Fried Pita Bread with Eggs


text:
Chess Opening Theory/1. e4/1...e5/2. Nf3/2...Nc6/3. Bc4/3...Nf6/4. d4/4...exd4/5. O-O/5...Nxe4/6. Nc3/6...dxc3/7. Bxf7/7...Kxf7/8. Qd5

= Nakhmanson Gambit =

8. Qd5+
White has played the Nakhmanson Gambit, a hair-raising sacrifice of a whole knight  for an assault on the wandering Black king.

Good news for Black players: the Nakhmanson Gambit simply doesn't work. There is a way to emerge from the complications into a peaceful position with at least an extra pawn.

Bad news for Black players: the Nakhmanson Gambit is a nasty surprise if you haven't seen it before, thanks to this position. The natural plan of retreating the king to e8, followed by putting the bishop on e7 to shield the king from checks, is what White wants. It allows White to escape with a draw even if Black finds the best defensive moves.

Black's route to advantage instead begins with the ridiculous 8...Kf6! This just happens to work, though a player searching for some principle behind it might note that the king is  temporarily immune from checks on f6, until the e4-knight is captured. This means Black gets a crucial tempo to put a defensive piece on e7 without it immediately getting pinned along the e-file.


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Chess Opening Theory/1. e4/1...e5/2. Nf3/2...Nc6/3. Bc4/3...Nf6/4. d4/4...exd4/5. O-O/5...Nxe4/6. Nc3/6...dxc3/7. Bxf7/7...Kxf7/8. Qd5/8...Kf6

= Nakhmanson Gambit, Kf6 Defence =

8...Kf6
Black is still up two pieces and a pawn, but the knight on e4 is toast. With
 * 9. Qxe4 White can capture it immediately, or with
 * 9. Re1 White can take advantage of the fact that it's not going anywhere, due to the threat of Bg5+ picking up the Black queen.

White's two moves require two distinct responses from Black, but don't worry: picking the wrong one will lead to instant death, and then you can start a new game with your king back on e8.


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Chess Opening Theory/1. e4/1...e5/2. Nf3/2...Nc6/3. Bc4/3...Nf6/4. d4/4...exd4/5. O-O/5...Nxe4/6. Nc3/6...dxc3/7. Bxf7/7...Kxf7/8. Qd5/8...Kf6/9. Qxe4

= Nakhmanson Gambit, Kf6 Defence, Queen Capture =

9. Qxe4
White now has the very simple threat of Bg5+ winning the Black queen.

Let's look at some obvious defences that don't work:

 * 9...h6?? 10.Nh4! sees the White queen invade on g6 in combination with a rook on e1, for example
 * 10...g5 11.Qg6+ Ke5 (Ke7 12.Nf5#) 12.Re1+ Kd5 13.Qe4+ Kc5 14.Be3+ Kb5 15.a4+ 1-0
 * 10...d6 11.Qg6+ Ke7 12.Re1+ Ne5 13.Bf4 Kd7 14.Bxe5 Qxh4 (or 14...dxe5 15.Rxe5 with threats of Qf7+, Qe6+ and Qg4+) 15.Bf6! 1-0
 * 10...Ne7 (to control g6 and stop that from happening) 11.Qf4+ Ke6 12.Re1+ Kd5 13.Re5+ with mate in 2
 * 9...d5?? 10.Bg5+ Kf7 11.Qf4+ 1-0
 * 9...Ne7?? would be the correct move against 9.Re1, but here it fails quickly to 10.Qf4+ when 10...Nf5 11.Qg5+ wins the queen anyway, and 10...Kg6 or 10...Ke6 allow the f3-knight in with check.

The correct move is to indirectly control g5 with 9...Be7! which also vacates the f8 square on which the Black king can shelter from e-file checks. Black's Plan A is to make an immediate dash for f8, but this isn't always possible.


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JavaScript/Handling DOM events/Exercises

Topic: Event handling

We use the following HTML page for the exercises.

1. Implement a 'click' event handler that toggles the 'A' area between the background colors 'silver' and 'gold'.

2. Implement a 'mouseover' event handler. With each mouse movement on the 'B' area its background color changes from "blue" to "lime", "red", "yellow", "green", and back to "blue".

3. Implement two event handlers for the 'C' area, 'mouseenter' and 'mouseleave'. When the mouse pointer enters the area, its background color changes to "red"; when it leaves the area, its background color changes to "green".

4. Bring the above 3 solutions together. We will have a page that reacts on 4 different event types.


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Fractals/scanning

Scanning, sampling

Sampling
 * process of getting a finite number of values from a function, map, image.
 * In statistics, quality assurance, and survey methodology, sampling is the selection of a subset (a statistical sample) of individuals from within a statistical population to estimate characteristics of the whole population. Statisticians attempt to collect samples that are representative of the population in question. Sampling has lower costs and faster data collection than measuring the entire population and can provide insights in cases where it is infeasible to measure an entire population.

Criteria for classifications:
 * number of passes ( single pass, multiple pass)
 * grid ( regular = uniform / irregular or adaptive )
 * random ( stochastic)/ not-random
 * with or without decomposition

Sampling types by range
 * point-sampling = Point-sampling method. A seed is a defined, rationally complex number which represents a pixel = pixel center. Note that one can find infinitely many points inside one pixel, and many of such point can have different color/ behaviour then the pixel center.
 * Spatial sampling ( what happens between samples ? ) : a manually-defined homogeneous grid = uniform sampling
 * 1 pixel approximation = image shows "the set of points in the plane whose distance  to the filled Julia set is at most the diameter of a pixel"
 * supersampling = sub-pixel aproximation ( resolution)

Sampling by adaptation
 * regular, uniform ( non-adaptive) sampling
 * adaptive ( non-uniform)sampling =  Adaptive Mesh Refinement (AMR)
 * Detail Enhancement Based on Local Fractal Analysis of Gradient: The key concept of fractal-based image model is the fractal dimension is capable of representing intrinsic structural information of image robustly.
 * a quadtree decomposition of the complex plane with adaptive refinement gives adaptive approximation
 * Adaptive Subdivision
 * "Mathematica automatically samples more points when needed to create a smooth function visualization"
 * Adaptive Sampling for precise Plotting Math Curve

=Types=
 * standard scanning: rendering the whole image (in full resolution) in one step
 * fractint Drawing_Methods
 * circular rendering on each successive refinement step

Steps:
 * preview
 * final render

Types by transformation or plane type ( parameter or dynamic)
 * scaning the standard c plane
 * scanning the exponential plane

standard
Scan the plane :
 * all pixels ( plane is scanned pixel by pixel ) in one pass
 * the same pixel size ( regular, uniform grid )

It depends also on the plane description

corners
Here in Lisp

and in C

Normal grid-scan plotting by Robert Munafo

radius
another version

quadtree
Quadtree types
 * Region quadtree
 * point quadtree

 * distance_estimation, Koebe 1/4-theorem by Claude Heiland-Allen
 * fast-mandelbrot-set-by-quadtree by Mandrian
 * The Mariani-Silver Algorithm for Drawing the Mandelbrot Set by Rico Mariani
 * Mariani/Silver Algorithm from the Mandelbrot Set Glossary and Encyclopedia, by Robert Munafo, (c) 1987-2022.
 * openprocessing : Quad-tree by Naoki Tsutae

// Quad-tree by Naoki Tsutae in Processing // https://openprocessing.org/sketch/1769288 quadTree = (x, y, size) => { if (size < minRectSize) return; const n = noise((x + posx) * 0.001, (y + posy) * 0.001, variation); if (abs(n - 0.45) > size / maxRectSize) { rect(x, y, size); } else { size /= 2; const d = size / 2; quadTree(x + d, y + d, size); quadTree(x + d, y - d, size); quadTree(x - d, y + d, size); quadTree(x - d, y - d, size); } };

Region quadtree
The region quadtree represents a partition of space in two dimensions by decomposing the region into four equal quadrants, subquadrants, and so on with each leaf node containing data corresponding to a specific subregion. Each node in the tree either has
 * exactly four children
 * or has no children (a leaf node).

The height of quadtrees that follow this decomposition strategy (i.e. subdividing subquadrants as long as there is interesting data in the subquadrant for which more refinement is desired) is sensitive to and dependent on the spatial distribution of interesting areas in the space being decomposed. The region quadtree is a type of trie.

A region quadtree with a depth of n may be used to represent an image consisting of 2n × 2n pixels, where each pixel value is 0 or 1. The root node represents the entire image region. If the pixels in any region are not entirely 0s or 1s, it is subdivided. In this application, each leaf node represents a block of pixels that are all 0s or all 1s. Note the potential savings in terms of space when these trees are used for storing images; images often have many regions of considerable size that have the same colour value throughout. Rather than store a big 2-D array of every pixel in the image, a quadtree can capture the same information potentially many divisive levels higher than the pixel-resolution sized cells that we would otherwise require. The tree resolution and overall size is bounded by the pixel and image sizes.

A region quadtree may also be used as a variable resolution representation of a data field. For example, the temperatures in an area may be stored as a quadtree, with each leaf node storing the average temperature over the subregion it represents.

Koebe quarter theorem:

Once b [the exterior distance estimate for c] is found, by the Koebe 1/4-theorem, we know there's no point of the Mandelbrot set with distance from c smaller than b/4.

Antialiasing and supersampling

Supersampling or supersampling anti-aliasing (SSAA) is a spatial anti-aliasing method, i.e. a method used to remove aliasing (jagged and pixelated edges, colloquially known as "jaggies") from images rendered in computer games or other computer programs that generate imagery. Aliasing occurs because unlike real-world objects, which have continuous smooth curves and lines, a computer screen shows the viewer a large number of small squares. These pixels all have the same size, and each one has a single color. A line can only be shown as a collection of pixels, and therefore appears jagged unless it is perfectly horizontal or vertical. The aim of supersampling is to reduce this effect. Color samples are taken at several instances inside the pixel (not just at the center as normal), and an average color value is calculated. This is achieved by rendering the image at a much higher resolution than the one being displayed, then shrinking it to the desired size, using the extra pixels for calculation. The result is a downsampled image with smoother transitions from one line of pixels to another along the edges of objects.

The number of samples determines the quality of the output.

 * TechInfo -AntiAliasing by Michael Condron
 * Fract (Lisp code) by Yannick Gingras
 * Spatial anti aliasing at wikipedia
 * fractalforums discussion: Antialiasing fractals - how best to do it?

Supersampling, other names:
 * antigrain geometry
 * Supersampling (downsampling)
 * downsizing
 * downscaling
 * subpixel accuracy

Computational cost and adaptive supersampling
Supersampling is computationally expensive because it requires much greater video card memory and memory bandwidth, since the amount of buffer used is several times larger. A way around this problem is to use a technique known as adaptive supersampling, where only pixels at the edges of objects are supersampled.

Initially only a few samples are taken within each pixel. If these values are very similar, only these samples are used to determine the color. If not, more are used. The result of this method is that a higher number of samples are calculated only where necessary, thus improving performance.

Types
When taking samples within a pixel, the sample positions have to be determined in some way. Although the number of ways in which this can be done is infinite, there are a few ways which are commonly used.

Grid
The simplest algorithm. The pixel is split into several sub-pixels, and a sample is taken from the center of each. It is fast and easy to implement. Although, due to the regular nature of sampling, aliasing can still occur if a low number of sub-pixels is used.

Random
Also known as stochastic sampling, it avoids the regularity of grid supersampling. However, due to the irregularity of the pattern, samples end up being unnecessary in some areas of the pixel and lacking in others.

Poisson disk
The poisson disk sampling algorithm places the samples randomly, but then checks that any two are not too close. The end result is an even but random distribution of samples. However, the computational time required for this algorithm is too great to justify its use in real-time rendering, unless the sampling itself is computationally expensive compared to the positioning of the sample points or the sample points are not repositioned for every single pixel.

Poisson-disk sampling (blue noise) is the best sampling pattern. It maximizes the uniformity of the samples in addition to the randomness of their placement, which gets you the most bang for your buck with respect to the contribution of each sample. quaz0r on FF

Links
 * poisson-disc-sampling-in-python by christian on 22 Apr 2017

Jittered
A modification of the grid algorithm to approximate the Poisson disk. A pixel is split into several sub-pixels, but a sample is not taken from the center of each, but from a random point within the sub-pixel. Congregation can still occur, but to a lesser degree. Jitter is also recommended to avoid Moiré artifacts.

Rotated grid
A 2×2 grid layout is used but the sample pattern is rotated to avoid samples aligning on the horizontal or vertical axis, greatly improving antialiasing quality for the most commonly encountered cases. For an optimal pattern, the rotation angle is $arctan (1⁄2)$ (about 26.6°) and the square is stretched by a factor of $$\frac{\sqrt{5}}{2}$$

An example of an image with extreme pseudo-random aliasing
Because fractals have unlimited detail and no noise other than arithmetic round-off error, they illustrate aliasing more clearly than do photographs or other measured data. The escape times, which are converted to colours at the exact centres of the pixels, go to infinity at the border of the set, so colours from centres near borders are unpredictable, due to aliasing. This example has edges in about half of its pixels, so it shows much aliasing. The first image is uploaded at its original sampling rate. (Since most modern software anti-aliases, one may have to download the full-size version to see all of the aliasing.) The second image is calculated at five times the sampling rate and down-sampled with anti-aliasing. Assuming that one would really like something like the average colour over each pixel, this one is getting closer. It is clearly more orderly than the first.

In order to properly compare these images, viewing them at full-scale is necessary.

code

 * Cpp code by User Geek3
 * command line version of Aptus (python and c code) by Ned Batchelder  (see aptuscmd.py) is using  a high-quality downsampling filter thru PIL function resize
 * Java code by Josef Jelinek: supersampling with grid algorithm, computes 4 new points (corners), resulting color is an average of each color component:

 * one can make big image (like 10 000 x 10 000) and convert/resize it (downsize). For example using ImageMagick:

downsampling and interpolating is essentially compression, low frequency components, ie:
 * slow changing colours that change slower than half sampling freq, will get preserved
 * the high frequency detail will be lost

Interval arithmetic

 * adaptive algorithms for generating guaranted images of Julia sets
 * True Shape Algorithm ( TSA)

= How do I optimize searching for the nearest point ?=
 * gamedev.stackexchange question: how-do-i-optimize-searching-for-the-nearest-point ?

=See also=
 * Tessellation is the process of partitioning space into a set of smaller polygons
 * 2D grid types
 * commons:Category:Mesh in computer graphics
 * sampling and the image noise - dither to more accurately display graphics containing a greater range of colors than the display hardware is capable of showing
 * Fractint Drawing Methods
 * Fratal Witchcraft drawing methods by Steven Stoft
 * AlmondBread algorithms
 * rugh set method
 * cell mapping based on interval arithmetic with label propagation in graphs to avoid function iteration and rounding errors
 * "We combine cell mapping based on interval arithmetic with label propagation in graphs to avoid function iteration and rounding errors." - Luiz Henrique de Figueiredo et al.
 * using exterior distance estimates and Koebe quarter theorem
 * usung symmetry

=References=
 * Serious Statistics: The Aliasing Adventure By Guest_Jim March 17, 2019

title: Fractals/scanning


text:
Cookbook:Halva (Wheat-based)

Ingredients

 * 1 cup all-purpose flour
 * 1 cup butter or margarine
 * 1¼ cup granulated sugar
 * 5 cups water

Procedure

 * 1) Heat the margarine very gently in a saucepan. Add the flour, and cook for 40 minutes over low to moderate heat until golden brown.
 * 2) When the flour turns light golden, combine the sugar and water in a separate saucepan. Boil gently to make a syrup.
 * 3) Add the syrup to the saucepan with flour, and simmer for 20 minutes.
 * 4) Scoop out small portions of halva with a wooden spoon, form into balls, and place on a serving plate.
 * 5) Serve warm.

title: Cookbook:Halva (Wheat-based)


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User:Missnishamalik

Here we will discuss about the upcoming exams, so please be ready with what you've prepared so far...

title: User:Missnishamalik


text:
Lombard/Object and term personal pronouns

In Lombard the personal object pronouns are equal to subject personal pronouns, even those that act as a complement of term or advantage are equal to subject pronouns but preceded by the preposition a. The personal pronouns for direct object and complement of term can also be expressed through pronominal particles (See ►►► Pronominal particles)


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User:JPazguez/sandbox

The Barbarian in a Civilized Society

J.M Coetzee’s Waiting for the Barbarians tells the story of a colonist Empire’s effort to maintain its grand narrative of the coming “barbarian” invasion and the man of conscience who questions the Empire he serves. To maintain the narrative, Empire or civilization labels the nomads as “barbarians,” torturing and neglecting them and spreading rumors or creating propaganda. Yet the man of conscience, the Magistrate or M - as I’d call him for short - sees the “barbarians” as the nomads, peaceful and “living in fear of everyone, skulking in the reeds, what can they possibly know of a great barbarian enterprise against the Empire?” (Coetzee 20). How does the Empire determine the “barbarian” from the civilized? Through the lens of the Magistrate, we learn how the Empire uses the “barbarian” to keep control of its subjects.

At the start of the novel, Colonel Joll and the Magistrate, imperial officers of the Empire, begin questioning a boy and a man who are described as “prisoners.” But in M’s civilized society prisoners are rare because “there is not much crime here and the penalty is usually a fine” (4), so the only prisoners they are capable of having are the ones they call “barbarians,” the nomads who live in the Empire’s borderlands off the settlement in the story. In post-colonial theory, the two terms - “barbarian” and civilized - are a pair, a binary pair, a signified to a signifier, civilization to “barbarian” (Ashcroft 18). To further understand the relationship between the terms, Maria Boletsi explains in her essay “Barbaric Encounters: Rethinking Barbarism in C.P. Cavefy’s and J.M. Coetzee’s Waiting for the Barbarians '' that “barbarian” and civilized form an interdependent relationship that “feeds the superiority of the civilized… Simultaneously, the definition suggests that the civilized has an unwillingness to understand the other’s language and thus to make the encounter with the other a communicative occasion” (Boletsi 68). Boletsi argues that in order for the civilized society to be recognized, they outcast the uncivilized, identify them, and are willfully ignorant of the other to not taint the civilized way of life. Within the context of the story, the relationship formed between the civilized and the “barbarian” comes from the Colonel’s search for truth about the barbarian uprising and M’s search for understanding the “barbarian” experience, with the communicative occasion being the torture of the “barbarians.”

While not actively participating in torture as the Colonel does, the Magistrate experiences it second-hand when he addresses the boy at the beginning of the novel and when he no longer hears the cries of the baby when the “barbarians” are imprisoned in the barracks, but he does experience a type of torture first-hand, as the interrogator, when he takes care of and examines the “barbarian” girl. When M addresses the boy after a session of interrogations, “have you had anything to eat?” (Coetzee 8), he does so with decency and sympathy, defining his position on the civilization - “barbarian” relationship. When he no longer hears the baby cry, a feeling of frustration comes to him that is a consequence of Colonel Joll’s presence and actions, “I curse Colonel Joll for all the trouble he has brought me, and for the shame too” (22). The Magistrate’s position is again defined. It is not until he houses the “barbarian” girl that he realizes he might as well have been as bad as the Colonel he curses so much, “I behave in some ways like a lover - I undress her, I bathe her, I stroke her, I sleep beside her - but I might equally well tie her to a chair and beat her, it would be no less intimate” (49). Here is when his position becomes less defined and the definition of “barbarian” is slightly altered according to whoever behaves like one instead of the definitive distinction between the civilized and the “barbarian.”

To have more insight about M’s position in the civilization - “barbarian” relationship, author J.M. Coetzee shares knowledge on the torture chamber in his article “Into the Dark Chamber: The Novelist and South Africa.” Coetzee explains that the “torture room provide[s] a metaphor, bare and extreme, for relations between authoritarianism and its victims… with the purpose, if not of destroying him, then at least of destroying the kernel of resistance within him” (Coetzee 61). The resistance of the “barbarian” girl is present when he asks her about her torture and when she does not have sex with him. I argue that her resistance comes down when they finally have sex because she says to M, “yes, there were other men. I did not have a choice. That was how it had to be” (61). Her resistance was there even before him, as it was with the other men, but since her choice was never present, it is fair to assume that she suspected the same behavior of the other men in M, since he is an imperial officer. Even the civilized can act barbaric.

To maintain and preserve a civilized way of life, defensive strategies are to be put in place, and a threat has to be imminent. Because the Magistrate does not believe in the barbarian threat (Coetzee 9), the threat is believed - by him and us - to be conjured up, gossip that comes from a source of civilization, the capital. Rumors of danger are spread and framed in a way that brings urgency and whatever means are necessary to address the danger. In their article, “The Empire as the Embodiment of Modern Intellect: a Critical Reading of Coetzee’s Waiting for the Barbarians through Levinas”, Mahdi Teimouri cites Judith Butler’s Frames of war, an exploration of modern war and portrayal of state violence, saying “any representation presupposes certain degree of framing which regulates one’s emotional and intellectual response to an event or situation” (Teimouri 358). Teimouri argues that framing the situation is equally important as the situation at hand in order to bring out the proper and desired reaction from the target audience. After Colonel Joll leaves the settlement, the Magistrate is confronted with and appalled by prisoners that have been detained “because they were hiding” (Coetzee 20). So they are deemed prisoners for hiding, and will be treated horribly because of the same reason, but the reason does not matter, for the only thing that matters is that they are “barbarians” and they are prisoners. It is because of this framing, and the knowledge from living on the settlement and encouraging commerce with the nomads, that M does not blindly believe the stories the Empire spreads about the “barbarians”.

The man of conscience, by the end of the novel, reaches an impasse. He cannot change the ways of the Empire alone and he cannot run the settlement as he genuinely wishes. The only thing he has power over are his actions to the treatment of the “barbarians”, while everyone else in civilization continues to believe the stories of the “barbarians”. The woman M sleeps with at the end of the novel says to him, “I am terrified to think what is going to become of us… I don’t know what to do any more. I can only think of the children” (176). He then reassures her that no harm will come to her.

Waiting for the Barbarians provides colonial context to the “civilization” - “barbarian” definitions and provides an understanding of how they are used in civilized society. By looking into the positions of the Magistrate and Colonel Joll, J.M. Coetzee shares how the Empire controls and maintains power over its subjects.

title: User:JPazguez/sandbox


text:
Chess Opening Theory/1. e4/1...e5/2. Nf3/2...Nc6/3. Bc4/3...Nf6/4. d4/4...exd4/5. O-O/5...Nxe4/6. Nc3/6...dxc3/7. Bxf7/7...Kxf7/8. Qd5/8...Kf6/9. Qxe4/9...Be7

= Nakhmanson Gambit, Kf6 Defence, Queen Capture =

9...Be7
Black has vacated f8 for the king, and Plan A is to make an immediate dash for f8. For example, if White pretends the last move didn't happen and presses ahead with 10. Bg5+, Black has the simple 10...Kf7 11.Qd5+ Kf8 12.Rae1 Bf6! and all White's invasion routes are blocked.

White can take counter-measures against ...Kf7, though. After 10. Qf4+, the Black king must temporarily rest on g6 (pending ...Bf6 and then ...Kf7), and now one advantage of 9...Be7 becomes apparent: White doesn't have the crushing knight check on h4.

Another attempt to cut the king off from f7 is 10. Ng5, when Black has time to go 10...d5 11.Qf4 Bf5 12.g4 Qd7! and suddenly Black is better developed than White.

10. Re1 carries a subtler threat which, if Black reacts with the automatic 10...Kf7, allows White to escape with perpetual check:  11.Qd5+ Kf8 12.Ng5 and now Black must pin her own bishop with 12...Qe8 to  guard against the mate on f7, because the queen is trapped after 12...Bxg5?? 13.Bxg5. With the bishop paralysed, the White queen can check endlessly on d5 and f5.

The move that shows up 10.Re1 as a serious mistake is 10...d5! denying the queen both the d5 and f5 squares, although Black must not fall for either 11.Qf4+ Bf5?? 12.Qg5+ or 11.Qf4+ Kg6 12.Rxe7 Nxe7?? 13.Ne5+ Kh5 14.Qg5# (the king is safe on h5 after the correct 12...Qxe7 13.Nh4+ Kh5 14.h3 Qe1+ 15.Kh2 Qe5).

Finally there is 10. b4, which may be White's best move. She is trying to either distract the c6-knight away from the defence of e5 and d4 (10...Nxb4?? 11.Qf4+ Kg6 12.Ne5+ Kh5 13.Qg4#) or kick it away. 10...Kf7 is playable but invites 11.b5 with further complications including a future Ba3, so the critical move is again 10...d5! 11.Qf4+ Kg6 12.b5 Qd6! Here White has no good way to keep the queens on and so might as well take the knight, leaving Black with only one extra pawn and the bishop pair in a queenless middlegame.


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User:Ssjun/sandbox

The Futility of Personal Data Security: How Data Breaches Reveal Fundamental Issues in Data Harvesting.
The advent of the World Wide Web and the subsequent technology that built off of its eventual widespread availability in the twenty-first century, served to connect people from one end of the world to the next. And while no one can disparage the tremendous benefits the internet has brought, the other side of that gleaming technological coin should also be carefully considered. As limitless as the internet seems, the issues it brings to rise are as well. One of the most insidious issues that has come to rise alongside the progression of the internet is the sheer amount of information that people willingly, and often obligatorily provide about themselves.

Since the scandal of Facebook’s involvement with Cambridge Analytica in the 2016 election, companies selling personal information to third party apps and data harvesters have come into the awareness of the general public. However, the increased awareness of data tracking does not mean that the average person, specifically the average American, understands the extent of their data being tracked, and where this data may be going. Moreover, 2017 studies from the Pew Research Center have shown that a large percentage of Americans are unsure or misinformed about many topics on proper cybersecurity (Olmstead and Smith). Oftentimes, lack of awareness also comes from assumptions that basic security practices will prevent sites from collecting an individual’s data, or that a site only has the data that people have consciously entered, such as an individual’s username, password, date of birth, etc. that is often the basic sign-up procedure for most sites on the internet. However, this is barely the tip of what sites, especially the larger social media sites such as Facebook and its affiliates collect, and this is often revealed by bad-faith data breaches and the information those behind the breaches gain from site’s databases. Observing some of the largest data breaches, such as the Yahoo and Cambridge Analytica breaches lays out how often these breaches are out of the hands of the individual. Adding to the fact that Statista has reported an increase in the number of data breaches yearly, reform at a national level on what individual data can be collected in the U.S., like the General Data Protection Regulation (or GDPR) in the European Union, becomes a clear necessity.

Instances of data breaches have been occurring for as long as data has been collected, but the advent of the internet and subsequent movement of most data into digital storage has only served to increase the number of data breaches per year, while the number of people impacted per data breach has exponentially risen. While data breaches from stolen files and leaked information from employees was not unheard of in the past, data collected and stored online is uniquely vulnerable to anyone with malicious intent and the knowledge of getting past security systems. Granted, it is not the easiest thing in the world to get past robust security systems in place to protect people’s information, but security has not stopped–or even slowed successful breaches, regardless of any security advent. As shown in data collected by Statista since 2005, the number of data compromises has increased tenfold, from 157 instances in 2005 impacting 66.9 million records, to peaking in 2021 at 1,862 compromises and 298.08 million records impacted. This erosion of privacy was inevitable in a landscape where personal information has become a commodity to sell to the highest bidder, often to gain insight into user bases to manipulate individual choices.

The most spotlighted instance of personal information being used to manipulate user opinions was the data breach by whistleblower Christopher Wylie, revealing Cambridge Analytica’s data harvesting methods of Facebook users and subsequent targeted posts to sway voters during the 2016 U.S. presidential election. As explained by Wylie in an interview regarding the purpose of Cambridge Analytica, “We exploited Facebook to harvest millions of people’s profiles. And built models to exploit what we knew about them and target their inner demons. That was the basis the entire company was built on.” (Cadwalladr and Graham-Harrison). This was a breakdown of privacy at an unprecedented level, and the bigger issue was how Facebook handled the data breach following the reveal of Cambridge Analytica’s harvesting of millions of users’ data. Facebook was exceedingly slow in ensuring the security of its user’s data following the breach, only issuing a letter ordering the harvested data to be deleted months after the fact, and doing little to nothing to ensure that the data was out of third-party hands (Cadwallader and Graham-Harrison). Despite the evidence that Facebook was not doing its due diligence following the breach, data protection specialist and forefront investigator into Facebook’s involvement, Paul-Olivier Dehaye in an interview for the same article states, “Facebook has denied and denied and denied this. It has misled MPs and congressional investigators…. It has a legal obligation to inform regulators and individuals about this data breach, and it hasn’t,” (Cadwalladr and Graham-Harrison). Unfortunately, Facebook’s refusal to acknowledge the data breach for what it was, and subsequent lack of transparency regarding what happened to that data afterwards, is a common practice for companies to downplay their involvement and severity of a breach.

Currently, there is no federal standard of what is required of companies to disclose to the impacted persons of a data breach, and while most states have passed laws regarding transparency surrounding breaches, the requirements and charges for failure in compliance often vary. Troy Hunt, a cybersecurity expert, provided overviews of companies’ responses to data breaches while outlining what the best practices are when responding to a data breach, and where a companies’ moral responsibilities lie. From his comparisons, it becomes evident that while a few companies will respond promptly with transparency upon a data breach, it’s much more likely for a company to attempt to evade the issue until it has no choice but to address it (Hunt). In addition, companies will often attempt to obfuscate the importance of the data that was exposed, such as making statements assuring customers that no credit card or payment information tied to an account has been stolen, just e-mail addresses and similar, seemingly non-consequential information in comparison. However, the unencrypted information found through a data breach, especially a user’s personal information, is always connected to other aspects of a user’s online presence, and creates vulnerabilities in more than just the original breached site. In the experience of Megan Clifford, a victim of T-Mobile’s 2017 data breach,  hackers getting access to her phone number lead to their ability to access almost all of her accounts, as Alix Langone reported, “Now that someone had her phone number, they could get into her bank account and gain access the common apps she had on her phone, including Venmo and iTunes.” Aside from porting scams like the one Clifford faced, access to email lists often spawn targeted phishing scams, or can be sold to another party for further exploitation.

Without standardization on consequences of breaches, compensation and responsibility is often determined on a case-to-case basis, and the impacted users will rarely have legal recourse regarding stolen data, as the lower courts have struggled to define harm when it comes to data breaches. As Solove and Citron summarized in a thesis published in The Texas Law Review:"In the past two decades, plaintiffs in hundreds of cases have sought redress for data breaches caused by inadequate data security. In most instances, there is evidence that the defendants failed to use reasonable care in securing plaintiffs’ data. The majority of the cases, however, have not turned on whether the defendants were at fault. Instead, the cases have been bogged down with the issue of harm. No matter how derelict defendants might be with regard to security, no matter how much warning defendants have about prior hacks and breaches, if plaintiffs cannot show harm, they cannot succeed in their lawsuits. (739)"The thesis further provides examples of cases in which plaintiffs have failed in their lawsuits, even with clear evidence of potential harm from the data disseminated by the breach, because the courts could not define the harm in a concrete manner (Solove and Citron, 779). With the sheer amount of information that is being collected through usage of the internet on the individual, and the modern-day inaccessibility to existing without an online footprint in some way, the responsibility of bearing the burden of data breaches should not be left on the individual being affected. However, without regulation surrounding the data being collected and how this data is meant to be treated in the first place, the onus in the U.S. lands on the individual to handle.

Regulations in personal data privacy clearly need to be passed and fortunately, a functioning example to structure federal regulations already exists in the form of the GDPR, passed in effect over the European Union in May of 2018. The goal of the GDPR was to put the power of personal data back into the hands of users to minimize the risk and more forward with transparency in the event a data breach was to occur. The GDPR has proven to be complex for companies to fall under compliance but essentially, it aims to allow users to request information on what data a site is collecting, and permanent erasure of data records if desired. The GDPR also has fines that may be levied to companies that fail to report data breaches within a timely and in a transparent manner, with delays incurring heavier fines the more time that passes since the initial notice of a breach. Security expert Saryu Nayyar writes for the implementation of something akin to the GDPR in her Forbes article, “For simplicity’s sake, businesses want one unified and standard set of regulatory requirements to meet. This is precisely what the GDPR did, replacing numerous disparate regulations instituted by various EU member states.” As she points out in the article, states have begun to pass laws surrounding data breaches, but the lack of standardization creates a difficult environment for companies to be compliant, and loopholes for ones that are not looking to be. Users in the U.S. have seen the effects of the GDPR from companies that have had to change their privacy policies to comply with the GDPR, and federal regulations regarding data privacy exist for specific sets of data already, like the FTC’s regulations for breaches in medical records. With these systems already in place and functioning, unified regulation is less unimaginable.

Like any market, data collection needs to be regulated and have enforced rules in place to protect the consumers from bad business practices, whether intentionally malicious or otherwise. And while the necessity is becoming more of a forefront issue, there has yet to be any significant change on a federal level regarding data collection and response to data breaches. Until change is demanded enough, it is ultimately up to the individual in the U.S. to protect their own data and information accessible on the internet. Cybersecurity experts recommend using unique and strong passwords for every account created with two factor authentication enabled, and to manage those under a password manager. In addition, investing in a VPN to obscure internet activity and IP addresses from providers and affiliated companies is good practice, as is using internet browsers that do not profit from collecting user data. However, this is ultimately a band-aid on a larger issue of unnecessary and excessive data collection, which only something akin to the GDPR passing could even begin to address.

title: User:Ssjun/sandbox


text:
Chess Opening Theory/1. e4/1...e5/2. Nf3/2...Nc6/3. Bc4/3...Nf6/4. d4/4...exd4/5. O-O/5...Nxe4/6. Nc3/6...dxc3/7. Bxf7/7...Kxf7/8. Qd5/8...Kf6/9. Re1

= Nakhmanson Gambit, Kf6 Defence, Rook Attack =

9. Re1
The prospect of White's rook joining the attack should set off alarm bells for Black, and indeed this position with White to play would be mate in 8 starting with Rxe4. More annoyingly, the same move 9...Be7?? that is recommended against 9.Qxe4, fails in comical fashion against the Rxe4 threat: 10.Rxe4 Qe8 (to guard against Rf4 followed by Qf7) 11.Bg5+ Kg6 12.Nh4+ Kh5 13.g4#. Checkmate by five unique pieces!

The e4-knight can't be defended, but Black can threaten to defend it with the accurate 9...Ne7! to ensure that it's a queen and not a rook that captures it.

So Black's responses to both 9. Qxe4 and 9. Re1 entail putting a minor piece on e7, but you have to pick the right one, and if you pick the wrong one you get checkmated. To remember which is which, think: Attack the queen if you can. If the queen's on d5 because White has played Re1, you can attack it with 9...Ne7. If the queen's on e4 because White has played Qxe4, you can't attack it, so play 9...Be7 instead.


text:
Chess Opening Theory/1. e4/1...e5/2. Nf3/2...Nc6/3. Bc4/3...Nf6/4. d4/4...exd4/5. O-O/5...Nxe4/6. Nc3/6...dxc3/7. Bxf7/7...Kxf7/8. Qd5/8...Kf6/9. Re1/9...Ne7

= Nakhmanson Gambit, Kf6 Defence, Rook Attack =

9...Ne7
White's queen is attacked and Black is threatening to hold on to the e4-knight with  …d5, so White is forced to go 10. Qxe4.

10. Bg5+ doesn't work. 10…Nxg5 11.Qd4 Kf7 12.Nxg5+ Kg8 13.Rxe7 would be checkmate if Black was forced to take the rook, but she isn't; she gets  13...d5! in after all, and after something like 14.Re5 she has time to start driving pieces off with 14...h6.


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Talk:Introduction to Psychology/Surveys

PSYCHOLOGY
Write merits of survey method of psychology 2409:4061:218:B5B1:ED10:92B:458F:661C (discuss) 12:23, 20 December 2022 (UTC)

title: Talk:Introduction to Psychology/Surveys


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User:Milan Lukáč

Milan Lukáč, DiS.art (* 26.august 1998, Topoľčany ) slovenský hudobník, bubeník, učiteľ hudby, politik a člen politickej strany SMER - sociálna demokracia.

Mladosť a štúdium Milan Lukáč sa narodil 26. augusta 1998 v Topoľčanoch. Pochádza z hudobnej rodiny. Od štyroch do svojich pätnástich rokov navštevoval Základnú umeleckú školu Ladislava Mokrého, kde vyštudoval hru na bicích nástrojoch.

V hudobnom štúdiu pokračoval na Súkromnom konzervatóriu Dezidera Kardoša v Topoľčanoch kde od roku 2014 do roku 2020 študoval hru na bicích nástrojoch a taktiež vyštudoval učiteľstvo hudby.

Hudobná kariéra  Aktívne začal hrávať popri štúdiu na konzervatóriu. Milo Suchomel, ktorý bol jeho učiteľ na škole, ho pozdvihol a začal ho brávať hrať na koncerty. Vtedy sa viac začal zaujímať o produkovanie hudby, o klasickú jazzovú hudbu. Vystupuje so známymi hudobníkmi akými sú: Milo Suchomel, Pavol Bereza, Alexander Rikoň a iní. Hráva na činely značky Zildjian. Politika  V roku 2019/2020 sa začal zaujímať o politiku. Začal čítavať knihy od Karla Marxa, Friedricha Engelsa ale aj cirkevné knihy. Začal podporovať ľavičiarsku politiku ale hlavne konzervativizmus. V roku 2021 sa rozhodol vstúpiť do politickej strany SMER-sociálna demokracia. O rok neskôr ( v roku 2022 ) sa dostal do mestského výboru z radu občanov.

title: User:Milan Lukáč


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Cookbook talk:Yoda Soda

THIS IS DISGUSTING!!!
''' DO NOT. ''' 207.191.207.146 (discuss) 16:48, 20 December 2022 (UTC)

title: Cookbook talk:Yoda Soda


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User:William Leismer

Background
My core identity flows from my Lord and Savior Jesus Christ. Everything I am and steward are ultimately His. I pray continually to be transformed by the Holy Spirit through the renewing of my mind, by His grace alone and not by any assumed merit of my own. God has blessed me with interests that lie in the world of technology, the trades, and some machinery.

I graduated from Trine University in 2015 with a Bachelor of Science in Electrical Engineering. I have worked in the automotive industry in Southeast Michigan for all of my professional life on products ranging from ignition coils & spark plugs, instrument clusters & heads up displays, to various ECUs deployed on vehicles and some low-speed electrical vehicles within the autonomous/tele-operation space. I currently work at a small company under Ford's Research & Advanced Engineering/Development group.

Interests
My core interests lie in electrical engineering, specifically the design and manufacture of embedded systems. I have some programming experience, but I typically do not dive into that world very much. I also have found an interest and "hobby" in working around my house on the electrical systems, plumbing, and automotive repair. I enjoy science fiction & fantasy novels and TV shows/movies.

Goals for Wikibooks
My primary goal for contributing to Wikibooks is two-fold. I wanted an outlet to which I can share what I learn as I move through my professional career. Sharing what I learn helps to both solidify the lessons in my own mind as well as provide a resource for others to use/correct me for the benefit of everyone.

title: User:William Leismer


text:
Chess Opening Theory/1. e4/1...e5/2. Nf3/2...Nc6/3. Bc4/3...Nf6/4. d4/4...exd4/5. O-O/5...Nxe4/6. Nc3/6...dxc3/7. Bxf7/7...Kxf7/8. Qd5/8...Kf6/9. Re1/9...Ne7/10. Qxe4

= Nakhmanson Gambit, Kf6 Defence, Rook Attack =

10. Qxe4
In the analogous position with a knight on c6 and a bishop on e7, Black needs to  play 10…d5 to avoid a draw by repetition. Here 10…d5 would be inaccurate, but not immediately fatal: 11.Qf4+ forces Black to self-pin with 11…Bf5 (11…Nf5??  12.Qg5+) and then White has a pleasant choice between g4 and Nd4 to exploit  the pin.

Black preserves the piece and the advantage by simply running away with 10...Kf7. Now that the e7-knight covers d5 and f5, the king can hide on g8 without getting checkmated by a queen on d5, which is always a  plus.


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Chess Opening Theory/1. e4/1...e5/2. Nf3/2...Nc6/3. Bc4/3...Nf6/4. d4/4...exd4/5. O-O/5...Nxe4/6. Nc3/6...dxc3/7. Bxf7/7...Kxf7/8. Qd5/8...Kf6/9. Re1/9...Ne7/10. Qxe4/10...Kf7

= Nakhmanson Gambit, Kf6 Defence, Rook Attack =

10...Kf7
Black's king is heading for the safety of g8. If White sees the king slipping through her fingers and plays a panic check, obvious moves will be enough for Black  to stave off checkmate: 11.Qf4+ Kg8 12.Ng5 (or 11.Ng5+ Kg8 12.Qf4) Qe8  13.Qc4+ d5:

 * 14.Rxe7 Bxe7 15.Qxd5+ Kf8 16.Qf3+ Bf6 0-1
 * 14.Qxc7 h6 makes a hidey-hole for the king on h7. If the White knight had checked on e5 instead of g5, Black would now have 14...Nc6! taking advantage  of the undefended rook on e1.

So White needs to forget about checkmate and focus on winning back the piece with 11. Bg5.


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Analog and Digital Conversion/Sources of Error

Introduction
Recall that in an ideal ADC, a continuously variable analog input waveform will be quantized (converted to a discrete digital value). Imagine a linear analog input signal starting at 0V and ending at its full-scale range value (e.g. 5V, 10V, 15V, or some other maximum value). An ideal ADC will read those analog values in and convert the analog voltages to a perfect stair step digital representation. A non-ideal ADC will read those analog values in and be influenced by both noise and errors in the system. Four main error sources exist:

 * 1) Offset Error - X-intercept Shifting
 * 2) Gain Error - Slope Shifting
 * 3) Differential Non-linearity Error (DNL) - Maximum single step error
 * 4) Integral Non-linearity Error (INL) - Maximum accumulative step error

Offset Error
Offset error can be simply understood as an error that shifts the x-intercept of the end-point correlation line. The end-point correlation line is a line drawn from bit 1 to the final bit in the non-ideal transfer curve (i.e. the quantized stair step). For example, if the ideal quantized value corresponding to 1V is 819 bits and the offset error is +2 bits, then the non-ideal quantized value will be 821 bits.

Gain Error
Gain error can be simply understood as an error that shifts the slope of the end-point correlation line. Because gain error compounds over the range of the analog input, gain error can be negligible in one part of the full scale input range while being significant in another.

Differential Non-linearity Error
Differential non-linearity error can be simply understood as the maximum deviation that appears between the ideal quantized value and the actual one. For example, the non-ideal transfer curve may deviate from the ideal transfer curve by 1 bit in some places, however if it deviates from the ideal transfer curve by a maximum of 2 bits in one place, then the differential (difference, or delta) non-linearity error is considered to be 2 bits.

Integral Non-linearity Error
Integral non-linearity error can be simply understood as the maximum deviation that occurs between the non-ideal transfer curve and its end-point correlation line. For example, as various errors stack up along the non-ideal transfer curve, eventually there will be a summing effect of errors which is considered the integral (summing) non-linearity error.


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Analog and Digital Conversion/Reference Materials

Links
ADC Accuracy Part 1: Is accuracy different from resolution?

ADC Accuracy Part 2: Total unadjusted error explained

Understanding Data Converters (Texas Instruments)

Understanding Noise, ENOB, and Effective Resolution in Analog-to-Digital Converters

Peak-to-Peak Resolution Versus Effective Resolution

ADC Input Noise: The Good, The Bad, and The Ugly. Is No Noise Good Noise?

Resistor Noise: Deafening and Hard to Reduce


text:
Chess Opening Theory/1. e4/1...e5/2. Nf3/2...Nc6/3. Bc4/3...Nf6/4. d4/4...exd4/5. O-O/5...Nxe4/6. Nc3/6...dxc3/7. Bxf7/7...Kxf7/8. Qd5/8...Kf6/9. Re1/9...Ne7/10. Qxe4/10...Kf7/11. Bg5

= Nakhmanson Gambit, Kf6 Defence, Rook Attack =

11. Bg5
The immediate 11...Kg8 is too compliant. With the e7-knight pinned, White doesn't have to take three times on e7 straight away, but can resolve the pawn  situation with 12.bxc3 and restore material equality.

Black can't remove the pin just yet. 11…Qe8 is just stepping out of one pin into another, and does nothing to free the knight. But with 11...d5, Black can at least prepare to remove the pin.

Or Black can resolve the pawn situation herself with 11...cxb2, now that the bishop can't recapture from c1.

It turns out that with best play 11...d5 and 11...cxb2 transpose into each other, but 11...d5 is a better practical choice because the juicy morsel on c3 might tempt White into accidentally losing a piece.


text:
Chess Opening Theory/1. e4/1...e5/2. Nf3/2...Nc6/3. Bc4/3...Nf6/4. d4/4...exd4/5. O-O/5...Nxe4/6. Nc3/6...dxc3/7. Bxf7/7...Kxf7/8. Qd5/8...Kf6/9. Re1/9...Ne7/10. Qxe4/10...Kf7/11. Bg5/11...d5

= Nakhmanson Gambit, Kf6 Defence, Rook Attack =

11...d5
Black is threatening to unpin the knight with ...Qd7 or ...Qd6. White's hopes of capturing the knight rest on immediately driving off one of its three  defenders, while keeping three attackers on it (so, not blocking the rook  with Ne5+). The only move that accomplishes this is 12. Qf4+, intending Qh4.


text:
Chess Opening Theory/1. e4/1...e5/2. Nf3/2...Nc6/3. Bc4/3...Nf6/4. d4/4...exd4/5. O-O/5...Nxe4/6. Nc3/6...dxc3/7. Bxf7/7...Kxf7/8. Qd5/8...Kf6/9. Re1/9...Ne7/10. Qxe4/10...Kf7/11. Bg5/11...d5/12. Qf4

= Nakhmanson Gambit, Kf6 Defence, Rook Attack =

12. Qf4
Black is trying not to get checkmated, so plays 12...Kg8.


text:
Chess Opening Theory/1. e4/1...e5/2. Nf3/2...Nc6/3. Bc4/3...Nf6/4. d4/4...exd4/5. O-O/5...Nxe4/6. Nc3/6...dxc3/7. Bxf7/7...Kxf7/8. Qd5/8...Kf6/9. Re1/9...Ne7/10. Qxe4/10...Kf7/11. Bg5/11...d5/12. Qf4/12...Kg8

= Nakhmanson Gambit, Kf6 Defence, Rook Attack =

12...Kg8
White has to play 13.Qh4 here to guarantee winning the piece back. If White tries 13.bxc3, Black simply steps out of the pin with 13...Qd7.

After 13.Qh4, Black can throw in 13...cxb2 14.Rab1, arriving at the same position as after 11...cxb2 12.Rab1 d5 13.Qf4+ Kg8 14.Qh4, but then comes the  moment of truth: Black has to find 14...Ng6! (or the identical 14...Nf5!) allowing White to take the piece only at the cost of trading queens.

15.Bxd8 Nxh4 16.Bxh4 follows, then there's no point trying to save the pawn with 16...Ba3? due to the rook check on e8, so Black must settle for 16...h5 developing the rook via h6. Black is a healthy pawn up with a safe king and the bishop pair, and should be able to tune into Channel 0-1 from here.


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User:ArchiRuby222/sandbox

The novel opens with the main protagonist, Dana, who is in the present time where she and her husband have just moved into their new home. She becomes dizzy and faints resulting in her getting pulled into the past and is in a situation where she has to save a white child she witnesses drowning. After saving the child, instead of receiving praise she is met with a shotgun to her face from a man. She faints again and is brought back to her present time, year 1979. After a couple of these trips back and forth, Dana has realized she is time-traveling into the past to meet her ancestors, mainly a white man, the boy she saved from drowning, who is related to her. Dana watches him grow up from the time of his childhood to his adulthood.

title: User:ArchiRuby222/sandbox


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Mirad Thesaurus/School

 * tiser....to learn
 * tisut....pupil
 * tisutyan....class
 * tistem....school hall, lecture hall
 * tistim....school room
 * tistam....school, schoolhouse
 * tistam det....schoolmate
 * tistam deym....schoolyard
 * tistam dyes....text book
 * tistam jab....schoolyear
 * tistam joyeb....school term, school session
 * tistam neg....school grade
 * tistameb....principal
 * tistamper....attend school, matriculate
 * tistim....schoolroom, classroom
 * tisef....curiosity
 * tisefa....curious
 * tisnad....curriculum
 * tisnog....grade
 * tisun....lesson
 * tisya....learned, wise
 * tisyat....learned person, wise person
 * tisyan....wisdom
 * tisyaf....intelligence
 * tisyafa....intelligent
 * tisyafwa....intelligible
 * tisyafwan....intelligibility
 * tisyik....difficulty learning
 * tisyika....mentally challenged
 * tisyikat....mentally challenged person, slow learner
 * tisyikwa....hard to grasp
 * tisyof....inability to learn
 * tisyofa....stupid, dumb, unintelligent
 * tixer....to study
 * tixut....student
 * tixutyan....student body
 * tixem....study hall
 * tixnad....discipline, line of study
 * tixum....study pod
 * tixifa....erudite
 * tixifan....erudition
 * tixyafa....docile
 * tixyea....studious
 * tixa....didactic
 * tuxer....to teach, indoctrinate
 * tuxut....teacher, lecturer
 * tuxutseym....lectern, podium
 * tuxen....''teaching, indoctrination'
 * tuxena....pedagogical
 * tuxen seym....lecture podium
 * tuxim....lecture hall
 * tuxtun....pedagogy
 * tuxtuna....pedagogical
 * tuxtut....doctor of teaching, pedagog
 * tuxtuta....doctoral
 * tuxtutan....doctorate
 * tuxun....lecture
 * tuxwa....indoctrinated, schooled, taught
 * tuyxer....raise, bring up, educate, train, tutor
 * tuyxut....tutor
 * tuyxutan....tutorship, tutelage
 * tuyxutyena....tutelary
 * tuyxwa....raised, tutored
 * tuyxwat....trainee, pupil, tutee
 * fituyxwa....well-raised
 * futuyxwa....poorly-raised
 * otuyxwa....untutored
 * fituxwa....well-taught
 * otuxwa....unindoctrinated, unschooled
 * tuxwat....pundit
 * tuxyafwa....teachable
 * tuxyofwa....unteachable, undocile, ineducable

title: Mirad Thesaurus/School


text:
Mirad Thesaurus/Mathematics

 * sag....number
 * saga....numerical
 * sagder....to count, enumerate
 * sagden....counting, enumeration
 * sagdenseym....counter
 * sagdyafwa....countable
 * sagdyofwa....uncountable, innumerable
 * sagdar....enumerator
 * sagdyun....numeral
 * sagsin....figure
 * sagsiyn....number sign
 * sagtun....mathematics, math
 * sagtuna....mathematical
 * sagtuna kyasiun....mathematical variable
 * sagtut....mathematician
 * asagtun....arithmetic
 * asagtuna....arithmetical
 * asagtut....arithmetician
 * 'esagtun....geometry
 * esagtuna....geometrical
 * isagtun....trigonometry
 * usagtun....algebra
 * usagtuna....algebraic
 * yosagtun....calculus
 * sagtuun....statistic
 * sagtuuna....statistical
 * sagtuunut....statistician
 * saguka....numberless
 * sagun....digit
 * saguna....digital
 * sagunxer....digit(al)ize
 * sagier....reckon, count on, take into account
 * sagmus....index, numeric scale
 * sagmusber....to index
 * sagmusben....indexing
 * sagmusbwa....indexed
 * sagnapa....in numerical order
 * sagnapxer....arrange in numerical order
 * sagtuin....numerology
 * sagtuina....numerological
 * sagtuit....numerologist
 * veksag....odds
 * mola sag....natural number
 * euna sag....even number
 * oleuna sag....odd number
 * kyea sag....random number
 * ayna sag....whole number
 * vyama sag....real number
 * vyatepa sag....rational number
 * ovyatepa sag....irrational number
 * vyatepxer....to rationalize
 * yikla sag....complex number
 * vaosag....integer
 * vaa sag....positive number
 * voa sag....negative number
 * golsag....fraction
 * nodsag....decimal

 * go....more
 * gab....plus
 * gaber....to add
 * gala....additional
 * gabus....adder, augent, sumand
 * gabwas....addend, addendum
 * gabun....addition, add-on, additive
 * gabsiyn....plus sign, cross
 * gabix....sum
 * go....less
 * gob....minus
 * gober....to subtract
 * gobus....minuend, substractor
 * gobwas....subtrahend, deduction
 * gobun....decrement
 * gobsiyn....minus sign, dash
 * gal....times
 * galer....to multiply
 * gala....multiple
 * galus....multiplier
 * galwas....multiplicand
 * gol....divided by
 * goler....to divide
 * golus....denominator, divisor
 * golwas....dividend
 * golun....division, fraction
 * golix....quotient
 * gar....raised to, exponentiated
 * garer....raise to the power of, exponentiate
 * gara....exponential
 * garus....exponent
 * garwas....number raised
 * garsyob....base
 * garsag....logarithm
 * garsaga....logarithmic
 * garsagsyob....log
 * garsiyn....exponent sign
 * garix....root
 * garewa....squared
 * gariwa....cubed
 * gor....to the negative power of
 * gorer....derive the root of
 * gorus....degree
 * gorix....negative root
 * gorsiyn....radical sign
 * ge....equal, as
 * gea....equal
 * ogea....unequal
 * gesign....equal sign
 * geaxer....equalize
 * geser....to equal
 * gese....equals, is equal to
 * gexer....to equate
 * gexen....equation
 * unkuna gexen....quadrilateral equation
 * geeksag....even score, tie
 * geta....identical
 * getan....identity

title: Mirad Thesaurus/Mathematics


text:
Mirad Thesaurus/Government

 * dob....state, état
 * doba....of the state
 * dobtun....statecraft
 * dobtuna....political
 * dobtut....statesman
 * dobifa....patriotic
 * dobifan....patriotism
 * dobifut....patriot
 * dobin....etatism
 * dobsoni....affairs of state
 * dobnastun....economy
 * dobnastuna....economic
 * dobnastut....economist
 * dobnix....tax, revenue
 * dobnux....pension
 * dobnad....border, frontier
 * dobnadut....frontiersman
 * dobnadib....customs bureau
 * dobnadibut....customs official
 * dobyena....official
 * dobier....take over
 * dobpyox....coup d'état

 * adob....empire
 * adeb....emperor
 * edob....royalty
 * edeb....monarch
 * idob....principality
 * ideb....prince
 * udob....duchy
 * udeb....duke
 * yodob....marquisate
 * yudeb....marquis
 * yadob....earldom
 * yadeb....earl
 * yedob....fiefdom
 * yedeb....vassal
 * yidob....viscountcy
 * yideb....count
 * yudob....barony
 * yudeb....baron
 * alodob....tribe
 * alodeb....chief

 * dobem....homeland, metropolis
 * dobmem....territory
 * dobmemyan....commonwealth
 * dobamem....province, state, departement (Fr.)
 * dobemem....prefect, county
 * dobimem....canton
 * dobumem....commune

 * dom....city
 * domeb....mayor
 * doym....town, burg, burgh, thorp
 * doymeb....sheriff
 * doam....borough, township
 * doem....village, thorp, dale
 * doemeb....village head
 * doum....estate, manor
 * doumeb....lord

 * doab....fatherland
 * doeb....state, federal entity
 * doebyan....federation
 * doebyayn....confederation
 * doib....country, shire
 * doob....nation
 * dooba....national
 * dooban....nationality
 * doobin....nationalism
 * doof....flag
 * ebdooba....international
 * gladooba....multinational

 * dab....government, rule, -archy, -cracy
 * dabtuna....governmental
 * dabut....government official
 * daba....governmental
 * daber....to govern
 * dabtun....politics
 * dabtuna....political
 * dabtunaxer...to politicize
 * dabtut....politician

 * abdab....dominion, suzerain
 * anadab....dictatorship
 * dopanadab....junta
 * alodab....chiefdom
 * andab....autocracy
 * islamedab....sultanate
 * islamidab....emirate
 * memyuvdab....fiefdom
 * nazdab....meritocracy
 * nyazdab....plutocracy
 * obdab....protectorate
 * teydab....matriarchy
 * twedab....patriarchy
 * totdab....theocracy
 * toybdab....gynocracry
 * tyendab....technocracy
 * ditdab....republic
 * tyodab....democracy
 * utdab....autarchy
 * obdamem....colony

 * deb....leader
 * deber....to lead
 * adeb....emperor
 * aadeb....premier
 * andeb....autocrat, despot
 * anadeb....dictator
 * asondeb....centurion
 * azdeb....strongman
 * dezdeb....star (of stage)
 * ditdeb....president (of a republic)
 * doyovdeb....godfather, mafia boss
 * dyezdeb....star (of screen)
 * edeb....monarch
 * ideb....prince
 * imeradeb....emir
 * islamadeb....sultan
 * islamedeb....emir
 * memyuvdeb....feudal lord
 * nazideb....fuehrer
 * nuxdeb....paymaster
 * nyazdeb....plutocrat
 * obditdeb....vice president
 * obedeb....vice regent
 * posamdeb....stationmaster
 * slavedeb....czar
 * twedeb....patriarch
 * teydeb....matriarch
 * udeb....duke
 * yadeb....earl
 * yedeb....lord, vassal
 * yideb....count
 * yudeb....baron
 * yuydeb....thane

 * dib....administration
 * diber....to administer
 * bakdib....health administration
 * bakdibut....health administrator
 * dobnadib....customs bureau
 * dobnadibut....customs officer
 * donapdib....police department
 * donapdibut....police officer
 * dopvakdib....gendarmerie
 * dopvakdibut....gendarme
 * dosyagdib....census bureau
 * dosyagdibut....census official
 * dotvakdib....social security administration
 * dotvakdibut....social security official
 * dotnuxdib....social welfare administration
 * dotnuxdibut....social welfare official
 * dovakdib....police department, public safety administation
 * dovakdibut....police officer
 * doyevdib....judiciary
 * doyevdibut...judiciary officer
 * kotuunyandib....intelligence service
 * kotuunyandibut....intelligence agent
 * mimvakdib....coast guard
 * mimvakdibut....coast guard officer
 * vyankexdib....bureau of investigation
 * vyankexdibut....investigation official

title: Mirad Thesaurus/Government


text:
Mirad Thesaurus/Technology

 * tyen....skill, technique, art
 * tyenyan....technology, skillset

 * sar....tool, instrument (most often, a hand tool)
 * saryan....equipment, instrumentation
 * sir....machine
 * siryan....machinery
 * sur....motor, engine

Vehicles

 * par....vehicle, cart
 * anzyukpar....wheelbarrow
 * enzyukpar....bicycle
 * inzyukpar....tricycle
 * unzyukpar....wagon
 * kyispar....dolly
 * yomkipar....skate
 * malyomkipar....ski
 * mapkipar....wind surfer
 * yomkipar....iceskate
 * pir....small motorized vehicle
 * enzyukpir....motorcycle
 * igkipir....luge
 * yomkipir....sled, sleigh
 * yaobyomkipir....bobsled
 * pur....large motorized vehicle, car
 * mempur....land vehicle, automobile
 * mampur....airplane
 * enpatuba mampur....biplane
 * mapatub mampur....prop plane
 * zaypux mampur....jet plane
 * mimpur....ship
 * nyuxmimpur....cargo ship
 * adopmimpur....aircraft carrier
 * idopmimpur....frigate
 * udopmimpur....destroyer
 * zyinunmimpur....barge
 * nyebag mimpur....container ship
 * ifmimpur....cruise ship
 * kyispur....truck
 * alyizyuk kyispur....eighteen-wheeler
 * bixpur....train
 * belun bixpur....freight train
 * yuzpur....bus
 * domyuzpur....city bus
 * ebdomzyupur....intercity bus
 * aybnyif dompur....tram
 * yagpur....limousine
 * uzyupatupur....helicopter
 * yiga malpur....zeppelin
 * zaopur....ferry
 * sumpur....camper
 * nyifpur....funicular
 * nyempur....van
 * nuxpur....taxi

Weapons

 * dopar....weapon
 * apyexlun....assault weapon
 * tuab dopar....shoulder weapon
 * uzdopar....arch, bow
 * yokdopar....stun gun
 * igyizdopar....sidearm
 * yokdopar....stun gun
 * dopyonar....bayonet
 * adopar....gun
 * tuyab adopar....handgun, pistol
 * mavigar adopar....flintlock
 * edopar....rifle
 * utexea edopar....automatic rifle
 * eynutexea edopar....''semi-automatic rifle
 * apyexlun edopar....assault rifle
 * idopar....shotgun
 * udopar....musket
 * dopir....artillery
 * adopir....cannon
 * edopir....bazooka
 * idopir....howitzer
 * udopir....mortar
 * kyia udopir....heavy mortar
 * depatyan udopir....infantry mortar
 * utzaypuxwa udopir....self-propelled mortar
 * igdopir....machine gun
 * oybmimdopir....torpedo
 * zeumula dopir....nuclear weapon
 * ovmampur dopir....anti-aircraft gun
 * ovdepur dopir....anti-tank gun
 * naad dopir....railgun
 * dapur....fighter jet
 * depur....tank
 * dipur....battleship
 * oybdipur....submarine
 * dupur....space force vehicle

Tools

 * goblar....knife
 * abektuna goblar....scalpel
 * aybgolbar....paring knife
 * bilyug goblar....butter knife
 * bowie golbar....bowie knife
 * Cahema goblar....Swiss knife
 * dref goblar....paper cutter
 * dref gyoflar....paper shredder
 * gigoblar....dagger
 * goblarog....penknife
 * ofyujgoblar....jackknife
 * potkex goblar....hunting knife
 * taogoblar....butcher knife
 * tuyafyem goblar....pocket knife
 * sangoblar....carving knife
 * yaozgoblar....serrated knife, saw
 * yaozgoblir....electric saw
 * goypir....electric saw
 * faob goypar....wood saw
 * neyef goypur....chain saw
 * zyusa goypur....circular saw
 * goflari....scissors
 * goflarogi....nippers
 * nifar....needle
 * nefar....crochet needle
 * yanifir....sewing machine
 * nofir....loom
 * yonar....knife
 * giyonar....skewer
 * megyonar....tomahawk
 * sezyonar....chisel
 * dopyonar....sword, sabre
 * yagdopyonar....broadsword
 * yogyonar....dagger
 * suvabar....hammer
 * apyexrar....sledge hammer
 * uzyusuvabar....screwdriver
 * uklar....shovel, hoe, spade
 * melzyegar....earthmover, excavator
 * vabibiar....rake
 * mekobar....dust mop
 * mekobir....vacuum cleaner
 * tayevar....mop
 * vyiapaxrar....sweeper
 * apaxlar....broom
 * oybmasvyixar....floor sweeper
 * oybmasvyixir....electric sweeper
 * domep vyixur....street sweeper
 * novyilxar....washing machine
 * tolarvyilxir....dishwasher
 * novzyiar....iron
 * tayebar....comb
 * tayefar....brush
 * volzil tayefar....paintbrush
 * maltayefar....airbrush
 * teupib vyixar....toothbrush
 * yebmagxar....kiln, furnace
 * magelar....burner
 * telxur....cooker
 * maglir....oven
 * amxar....heater
 * malomxar....air conditioner
 * manar....lamp
 * melyexir....plow
 * vobibiur....reaper, harvester, crop picker
 * vabgoblir....lawn mover
 * yonibiar....sifter
 * mulyonxar....strainer, filter, sieve
 * myekxur....mill
 * uzyubea masof...treadmill
 * omxar....refrigerator
 * yomsam....freezer
 * yibdalir....telephone
 * num yibdalir....cellphone
 * yibsinibar....television (set)
 * alpibar....radio (set)
 * alpubar....radio transmitter
 * syaagar....calculator
 * syaagir....computer
 * gabar....abacus
 * nagar....meter, gauge
 * amnagar....thermometer
 * bixfeeelknagar....magnetometer
 * igrasnagar....accelerometer
 * imnagar....hygrometer
 * maalbalnagar....barometer
 * mepignagar....odometer
 * amvyabxar....thermostat
 * tyopagar....pedometer
 * yabnagar....altimeter
 * zyuknagar....cyclometer
 * yuijar....key
 * yujar....lock
 * kipyuijar....zipper
 * yanar....chain
 * pibar....fork
 * puxpibar....pitchfork
 * umvab puxar....hayrake
 * telar....fork
 * tilar....spoon
 * teilar....soup spoon
 * bexar....grip, handle
 * tolsyebbexar....potholder
 * givomuv bexar....cigarette holder
 * manufar....candlestick
 * abexar....clutch
 * abtaf pyoxar....coat hanger
 * belar....holster
 * duzar....musical instrument
 * teaxar....scope
 * sinuar....display, screen
 * teabar....glasses
 * enteabar....binoculars
 * anteabar....monocle
 * aoyebar....piston
 * aoyebuxrar....pump
 * balyontixar....breathalyzer
 * baoxlar....vibrator
 * bolar....prop, support
 * buixar....spring
 * byalar....lift
 * byaxar....erector, stand
 * dalazar....loudspeaker
 * drar....pencil
 * drir....typewriter
 * drur....printer
 * dodrur....printing press
 * drilar....pen
 * milzyabar....hose
 * doluar....muffler
 * dref kyis....paperweight
 * kyinar....balance, scales
 * suv....nail
 * uzyusuv....screw
 * grun....hook
 * ekar....toy
 * ilokovar....gasket
 * ilukxar....drain, flush
 * ilyuijar....faucet, spigot
 * ilyujar....plug, stopper, tap
 * izdar....index
 * mapxar....fan, blower
 * judar....calendar
 * jwadar....alarm
 * yaoblar....elevator
 * kyinyablar....crane
 * yuijbar....switch, valve
 * makigar....spark plug
 * siunar....signal
 * ovar....shield
 * mamilovar....umbrella
 * maarovar....parasol
 * pyexovar....fender
 * magovar....firewall
 * pyoxovar....parachute
 * mapovar....windshield

title: Mirad Thesaurus/Technology