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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.
July 20, 2026
Scientists Propose Method for More Efficient Resource Use in Machine Learning
An international group of researchers, including mathematicians from the AI and Digital Science Institute at the HSE Faculty of Computer Science, has provided a theoretical justification for a simple and computationally efficient method of estimating uncertainty in Stochastic Gradient Descent (SGD). The paper has been published on the scientific preprint server arXiv.org and presented at AISTATS 2026.

 

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Увидеть невидимое: в поисках локальной идентичности района Ясенево в Москве

ИНТЕРакция. ИНТЕРвью. ИНТЕРпретация. 2019. Т. 11. № 20. С. 133–163.
Аларушкина С. А., Borisov A., Воронина А. А., Гладун П. И., Гришунов Е. Л., Зиатдинова С. Г., Квеладзе М. Г., Кирюхин Д. Н., Mitin I., Mikhaylov A., Molodtsova V., Fatekhova A.

The article presents the results of complex cultural geographical research of Yasenevo area in Moscow . The research was aimed at revealing an interconnected system of unique spatial representations of this typical distant urban residential area. The methods and approaches of urban planning analysis, statistical method of ‘regional syndrome’, historical and fiction texts’ analysis and semi-structured in-depth interviews were combined together for data collection within the framework of the project, with one of the mental mapping methods (image-geographical maps) used to present the results of the study. As a result Yasenevo is represented as a ‘green’ area due to Bitsevsky park surrounding it and various small gardens and groves in the yards. It is important to mention, Yasenevo is a compact and clearly isolated area, separated by the green areas from the surroundings. It has a specific urban planning and architectural structure dating back to Soviet modernism with peculiar semicircular buildings and streets, spacious avenues and green areas inside the separated cozy quarters (‘states’). Yasenevo is imagined as a ‘young’ area. However this vision co-exists with the historical heritage of preserved and ruined former noble estates and Soviet modernism blocks. Those unique features of Yasenevo are regarded as the basics of currently only partial local identity formation, on the one hand, and as the identifiers of potential organic (identity-based) place branding, on the other hand.

Priority areas: sociology
Language: Russian
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DOI
Text on another site
Keywords: МоскваMoscowуникальностьтерриториальная идентичностьлокальная идентичностьuniquenessplace brandingбрендинг территорийcultural geographyкультурная географияlocal identityЯсеневоurban residential areaспальный район
Publication based on the results of:
Комплексное культурно-географическое исследование удалённых городских районов как инструмент стимулирования локальных идентичностей и брендинга территорий (2019)
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