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News
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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Territorial Differences in Mortality and Mortality Risk Factors in Russia

Studies on Russian Economic Development. 2025. No. 36. P. 506–513.
Revich B. A., Larionov A., Kharkova T. L.

This study discloses risk factors in territories with high population mortality rates. The study consists of two phases: in phase one, the list of such territories is determined by estimating regional standardized mortality coefficients (SMC); in phase two, a statistical estimation of mortality risk factors is made. The final sample includes 18 territories with high mortality rates. A panel data analysis is made for selected territories for identifying high population mortality risk factors. Three classes of indicators are used as explanatory variables: socioeconomic characteristics, medical and organizational measures, and public safety indicators for the period from 2010 to 2023. According to the study results, the specific proportion of urban population (for men) and a rise in the number of doctors have the greatest influence on the mortality rate reduction. A rise in mortality rates is caused by an uneven distribution of household income (high values of Gini’s coefficient) and by crime situation changes (an increased number of grievous and extremely grievous crimes).

Research target: Sociology (including Demography and Anthropology Political Science, International Relations, and Public Administration
Language: English
DOI
Text on another site
Keywords: смертностьmortality
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