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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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Economic development and revolutions. A cross-national investigation

Conflict Management and Peace Science. 2026. P. 1–23.
Ustyuzhanin V., Fain E., Korotayev A.

In the field of civil war studies, there is a consensus that the risk of war decreases as income increases. Nevertheless, such consensus has not been reached in the field of civil resistance and unarmed revolutions. This paper proposes a curvilinear framework positing two opposite trends in economic development. On the one hand, it increases the state resources for preventing illegal displacement and makes revolt costly for rebels. Conversely, it boosts resources needed for civil resistance. Utilizing independent sources on revolutions and employing parametric and non-parametric methods, we have identified robust support for the inverted “U-shape” relationship between income level and the risk of unarmed revolutions. This finding reconciles the discrepancies observed in previous studies and provides a different perspective on the “middle-income trap.”

Research target: Political Science, International Relations, and Public Administration
Language: English
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Keywords: revolutionsреволюции
Publication based on the results of:
State Resilience and National Security of Russia in the Context of the World Order Transformation (2025)
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