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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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Triclusters of Close Values for the Analysis of 3D Data

Automation and Remote Control. 2022. Vol. 83. No. 6. P. 894–902.
Egurnov D., Ignatov D. I.

Abstract: The paper deals with the problem of triclustering in multivalued triadic contexts in termsof one multidimensional extension of formal concept analysis; triclustering can be viewed as asearch for dense subtensors in three-dimensional tensors over the field of real numbers. Twomethods are proposed for solving this problem, namely, NOAC—a version of the OACtriclustering method for numerical data based on delta operators—and a triadic version ofthek-means method with an improved metric based on Manhattan distance andproximity predicates in each of the three dimensions. Numerical experiments are carried out bothon real and synthetic data and confirm the superiority of the NOAC method in terms of theperformance criteria for the resulting triclusters. © 2022, Pleiades Publishing, Ltd.

Research target: Computer Science Mathematics
Language: English
DOI
Keywords: Formal Concept Analysistriclustering3D tensormultivalued context
Publication based on the results of:
Development of mathematical models and methods for natural language processing, knowledge discovery in data and recommender systems (2022)
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