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November 10, 2026
Physicists Train AI to Optimise Particle Beams in Accelerators
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science and the Budker Institute of Nuclear Physics at the Siberian Branch of the Russian Academy of Sciences have developed RLABC (Reinforcement Learning for Accelerator Beamline Control), a framework that uses reinforcement learning to identify optimal settings for a particle accelerator. In a computer simulation, RLABC optimised the accelerator's parameters to achieve a particle transmission rate of 70%. The study has been published in Computer Physics Communications.
November 9, 2026
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The Laboratory of Molecular Physiology at the HSE Faculty of Biology and Biotechnology investigates how molecular regulators known as microRNAs control gene expression and contribute to the development of diseases, including cancer, viral and inflammatory conditions, and pregnancy complications. At HSE University, researchers develop organ-on-a-chip models: miniature devices containing living cells that mimic the functions of human organs, such as the placenta and intestines. These models help researchers understand how diseases develop and how drugs affect them. HSE News Service spoke with Evgeny Knyazev, Head of the Laboratory.
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Flattened Terrain Models Underestimate Vehicle-to-Vehicle Communication Outages
Researchers at HSE MIEM have shown that widely used simulators of vehicle-to-vehicle communication significantly overestimate its reliability because they assume flat terrain. When terrain features, bridges, and tunnels are taken into account, the outage rate on a mountain serpentine road rises from 21% to 30%, on an overpass from 20% to 33%, and in a tunnel from 0% to 80%. The results have been published in Future Transportation.

 

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Runet Users' Attitude to Outrageous Content in Virtual Social Environments

Academic Journal of Interdisciplinary Studies. 2022. Vol. 11. No. 1. P. 258–268.
Inna V. Goncharova, Pronchev G., Rodionova M., Krichever E.

This study of the Runet virtual social environments deals with identifying and analyzing user reactions to watching a video clip containing outrageous behavior, and studying social attitudes of the respondents. The Celebrium-X platform employing the adjoint ideomotion technology for remote collection and processing of group neuro-responses was chosen as a research tool. As the empirical basis of the research, the raw data obtained as a result of the conducted survey was used. The results of the study have shown the respondents' negative attitude to publishing of outrageous video clips in virtual social environments. The Internet audience realizes a negative effect produced by the aggressive content on people's psychological sphere and social behavior.

Research target: Social Sciences Education Media and Communications
Language: English
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DOI
Text on another site
Keywords: Internetpublic opinionдевиантное поведениеобщественное мнениеdeviant behaviorИнтернетvirtual social environmentsCelebrium-X platformвиртуальная социальная средаCelebrium-X
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