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Combining Diacritical Marks for Symbols. Combining Diacritical Marks for Symbols is a Unicode block containing arrows, dots, enclosures, and overlays for modifying symbol characters. Its block name in Unicode 1.0 was simply Diacritical Marks for Symbols. [3]
Combining Diacritical Marks is a Unicode block containing the most common combining characters. It also contains the character " Combining Grapheme Joiner ", which prevents canonical reordering of combining characters, and despite the name, actually separates characters that would otherwise be considered a single grapheme in a given context.
Combining characters have been used to create Zalgo text, which is text that appears "corrupted" or "creepy" due to an overuse of combining characters. This causes the text to extend vertically, overlapping other text. [2] This is mostly used in horror contexts on the Internet.
The Rotter Incomplete Sentences Blank is a projective psychological test developed by Julian Rotter and Janet E. Rafferty in 1950. [1] It comes in three forms i.e. school form, college form, adult form for different age groups, and comprises 40 incomplete sentences which the S's has to complete as soon as possible but the usual time taken is ...
A worksheet, in the word's original meaning, is a sheet of paper on which one performs work. They come in many forms, most commonly associated with children's school work assignments, tax forms, and accounting or other business environments. Software is increasingly taking over the paper-based worksheet.
15 Games Like Connections. 1. Wordle. This popular word game gives a player six chances to correctly guess a five-letter word. While it may seem easy to do if you’ve never played it, you’ll ...
One example: Chinese: 妈妈骑马马慢妈妈骂马; pinyin: māma qí mǎ, mǎ màn, māma mà mǎ; lit. 'Mother is riding a horse', 'the horse is slow', 'mother scolds the horse'. [36] Lion-Eating Poet in the Stone Den: poem of 92 characters, all with the sound shi (in four different tones) when read in Modern Standard Mandarin.
e. Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words. The word2vec algorithm estimates these representations by modeling text in a large corpus. Once trained, such a model can detect synonymous ...