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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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How to Measure AI: Trends, Challenges and Implications

NRU Higher School of Economics , 2020. No. 116.
Turovets Y., Vishnevskiy K., Altynov A.
How do comparable and similar indicators to measure artificial intelligence (AI) look across countries? In answering this question, our study addresses two main aims. Firstly, the paper introduces a holistic approach as operational tool to measure AI development (supply side) and adoption (demand side), which covers AI definition, AI technologies taxonomy, and a set of indicators. Secondly, the suggested methodology combines several sources of information like survey, bibliometric, and patent analysis. Next, by analyzing the results of a pilot survey and calculations, the reliability of indicators and a tentative assessment the state of the art of AI development and adoption in Russia is provided. Taking into consideration the complex nature of AI, the study represents a number of baseline parameters that give an overview of AI progress on a country level. The next step will be an elaboration of detailed indicators that at capture AI characteristics to a greater extent in different economic sectors
Language: English
Full text
Keywords: measurementartificial intelligenceindicatorsdigital technologiesAI definition
Publication based on the results of:
Development of new methods for global technology trends detection on the basis of intellectual big data analysis (2020)
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