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News
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
'Organ-on-a-Chip Technology Could Eliminate the Need for Animal Testing'
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.
November 9, 2026
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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Similar outputs, different positions: convergence and divergence in research activity of public and private universities in EU candidate countries

Higher Education. 2026. P. 1–20.
Yudkevich M., Matveeva N.

This study draws on neo-institutional theory and the convergence/divergence debate in higher education research to examine whether public and private universities in EU candidate countries converge or diverge in their research activity and collaboration patterns. We analyse Scopus-indexed publication data for 43 universities across Albania, Bosnia and Herzegovina, Georgia, North Macedonia and Serbia for the period 2010–2022. The Wilcoxon signed-rank test was applied to assess significant differences between the two university groups. The blockmodelling procedure was applied to both non-normalised and normalised co-authorship networks of the universities to estimate the similarity of universities’ collaboration patterns. Our findings reveal that convergence and divergence operate simultaneously but at different analytical layers. At the surface layer of publication output and collaboration indicators, public and private universities are remarkably similar: they do not differ significantly in research productivity per person, share of high-quality output or international collaboration rates. At the structural layer of network positioning, however, private universities systematically occupy peripheral positions within national co-authorship networks, rarely collaborating with each other and mostly collaborating with one or two public universities. These findings suggest the convergence thesis: isomorphic pressures produce similar surface outputs but leave structural inequalities between sectors intact.

Research target: Economics and Management
Language: English
DOI
Text on another site
Keywords: EU enlargementCo-authorship networksResearch collaboration higher educationPrivate universitiesConvergence and Divergence of Universities
Publication based on the results of:
The diversity of forms, effects and barriers to integration of modern Russian society in synchronic and diachronic dimensions (2025)
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Added: October 6, 2026
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