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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.
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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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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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Non-extensive (Tsallis) q-statistics and auroral glow

Physica A: Statistical Mechanics and its Applications. 2024. Vol. 639. Article 129661.
Chernyshov A., Kozelov B. V., Mogilevsky M. M.

It is well-known that the auroral region of the magnetosphere–ionosphere interaction is an open, nonlinear dissipative system far from the equilibrium state. It is in this region that auroras are regularly observed, demonstrating not only a wide variety of dynamic forms but also a wide range of temporal and spatial scales. Due to the memory effects and fractal properties of auroral plasma, as well as strong correlations between its individual parts, the dynamics of the
high-latitude system are primarily determined by long-range electromagnetic forces. Therefore, it is expected that non-additive and non-extensive thermodynamic principles may characterize their macroscopic behavior. In the presented study, it is shown that pulsating auroras exhibit non-extensive properties and can be described by q-statistics. The correlation of the parameter 𝑞 with traditional indicators of nonlinear dynamics, such as the flatness coefficient, standard deviation, and scaling index, has been investigated. Small-scale changes are superimposed on large-scale processes characterized by a low correlation dimension, and this leads to an increase in the correlation dimension during geomagnetic activity, which approximately coincides with increased values of 𝑞. It is concluded that the q-statistics (Tsallis distribution) can be used to analyze optical phenomena in the auroral region.

Research target: Earth Sciences Physics
Language: English
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Keywords: correlation dimensionкорреляционная размерностьнеэкстенсивная термодинамикаNon-extensive q-statisticsaurorasauroral ionosphereполярные сиянияавроральная ионосфера
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