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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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Оценка влияния уголовного преследования предпринимателей на развитие малого и среднего бизнеса в России

Вопросы экономики. 2022. № 7. С. 68–84.
И. Б. Юдин, Г. А. Поросенков

A significant proportion of entrepreneurs as well as Russian population in general consider the possibility of criminal prosecution to be one of the main problems that hinders business development in Russia. However, only a small proportion of entrepreneurs are subjected to this type of prosecution. The current study attempts to empirically test the hypothesis about the negative impact of unjustified criminal prosecution on entrepreneurial activity. First, we examine the mechanism of unjustified criminal prosecution of entrepreneurs and then using mixed effects regression modelling on panel data for 2017—2021 assess its impact on the growth rate of the number of small and medium-sized enterprises (SMEs). The number of appeals reviewed by the Center for Public Procedures “Business against corruption” (CPP “BAC”) is used as an indicator of unjustified criminal prosecution. The results show that each additionally handled appeal reduces the rate of growth in the number of SMEs in the medium term. This relationship is explained via the theory of signals: appeals to the CPP “BAC” serve as indicators of unjustified prosecution problem for entrepreneurs. If this problem persists, a decrease in the growth rates of firms, and an increase in their number in the shadow economy can also be expected.

Research target: Economics and Management Sociology (including Demography and Anthropology Law
Language: Russian
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Keywords: предпринимательствокоррупциямалый и средний бизнесэкономические преступленияуголовное преследование
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