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News
July 2, 2026
Researchers Discover How Spelling Errors Slow Down Reading in Russian
Psycholinguists from the Centre for Language and Brain at HSE University–St Petersburg have shown that words that are frequently misspelled are processed more slowly by readers, even when presented with the correct spelling. The researchers confirmed this effect for the first time using Russian-language materials and found that response speed is most strongly linked to how confidently individuals can distinguish the correct spelling of a word from an incorrect one. The study has been published in The Mental Lexicon.
July 2, 2026
HSE Develops App for Assessing Phonological Processing in Children
Researchers at the HSE Centre for Language and Brain have developed a new digital tool for assessing children's phonological processing skills—the ZARYA (Sound Analysis of the Russian Language) test battery. It is the first standardised application in Russia designed to provide a fast and reliable assessment of children's ability to distinguish speech sounds, retain them in working memory, and perform phonemic analysis. The app runs on Android tablets and smartphones and is available for download from RuStore. Details of the test validation have been published in the Journal of Speech, Language, and Hearing Research.
July 1, 2026
Scientists Discover Why Europium 'Misbehaves'
Europium is a rare-earth metal responsible for the pure red glow in displays and other luminescent materials. For a long time, however, it refused to emit light when surrounded by certain organic molecules known as acylpyrazolone ligands. Chemists have now uncovered the reason: in europium complexes with these ligands, a 'black window' appears—a charge-transfer state in which the energy absorbed by the ligand is dissipated as heat rather than emitted as light. Understanding this mechanism opens the way to designing more efficient red-emitting materials for displays, fluorescent thermometers, and chemical sensors. The results have been published in Dalton Transactions.

 

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Нейросетевая система прогнозирования результатов сезона итальянской футбольной лиги "Серия А"

Вестник Пермского университета. Серия: Математика. Механика. Информатика. 2023. № 1(60). С. 84–92.
Бутина Д., Yasnitsky L.

The article describes the development of neural network system for predicting the Italian football Lega Serie A season results. To select the initial set, thematic sites containing complete statistics on the necessary characteristics were used. The system based on cost characteristics has 12 input parameters. The average testing error of this system was 3 %. The system allows to evaluate the performance of a football team in a season within the ranking from 1 to 5 positions, where 1 is 1–4 places and entry into the Champions League, and 5 is the team leaving the league. The significance of the input parameters is revealed. The influence of input parameters on the result is also shown.

Research target: Computer Science Other social sciences
Language: Russian
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Keywords: forecastingнейронная сетьпрогнозfootballфутболsportСПОРТArtipcial neural network
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