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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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Application of the Nonlinear Oscillations Theory to the Study of Non-equilibrium Financial Market

P. 375–381.
Markov N., Dmitriev V., Maltseva S. V., Dmitriev A.

The research deals with the construction, implementation and analysis of the model of non-equilibrium financial market using econophysical approach and the theory of nonlinear oscillations. We used scaled variation of supply and demand prices and elasticity of these two variables as dynamic variables in the simulation of the nonequilibrium financial market. View of the dynamical variables data was determined on the strength of econophysical prerequisites using the model of hydrodynamic type. As a result, we found that non-equilibrium market can be described with a good degree of accuracy with oscillator models with nonlinear rigidity and self-oscillating system with inertial self-excitation. The most important states of model of oscillation non-equilibrium model of the market were found, including the appearance of chaos and its mechanisms.

Language: English
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Keywords: financial marketfinancial time seriesnon-equilibrium modelnonlinear oscillationsLorenz systemdynamical chaosask pricebid price

In book

European Financial Systems 2015. Proceedings of the 12th International Scientific Conference
Brno: Masarykova univerzita, 2015.
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