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Subject
News
July 24, 2026
'Physics Is What the World Is Literally Built On'
Physicist Nina Dzhanayeva, recipient of a Vladimir Potanin Foundation scholarship, focuses her research on nanophotonics. In this interview for the HSE Young Scientists project, she discusses nanowells, scientific intuition, and how physics can help in making frangipane cream puffs.
July 20, 2026
Scientists Create Open Dataset for Studying Concentration
A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.
July 20, 2026
‘Science Is Universal-It Knows No Borders
Fuad Aleskerov, Tenured Professor and Director of the International Centre of Decision Choice and Analysis at HSE University, together with his colleagues, has developed methods of network analysis in bibliometrics that have made it possible to identify patterns in the appearance and citation of publications in academic journals, as well as their influence on each other. When one or a number of studies are frequently cited by a wide range of journals, this is an indicator that the research is of high quality. By contrast, extensive cross-citation within a limited group of journals increases the likelihood of identifying a network of predatory publications.

 

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Построение и анализ моделей русского языка в связи с исследованиями криптографических алгоритмов

Чебышевский сборник. 2022. Т. 23. № 2. С. 151–160.
Малашина А. Г., Los A.

The article provides a statistical analysis of the properties of lexical and n-gram models of the Russian language based on the news text corpus. A specialized corpus of political news articles of recent years has been created, reflecting a narrow area of language use. The token and n-gram dictionaries are compiled, the coverage values are found, as well as the values of entropy. Lemmatization of the original text corpus and extrapolation of the dictionary volumes are performed.

Research target: Computer Science Mathematics
Language: Russian
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DOI
Text on another site
Keywords: словари n-граммэнтропия n-граммосмысленные текстыn-gram dictionariesn-gram entropymeaningful texts
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