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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.
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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Agricultural terraces of Dagestan: ancient legacy for climate change adaptation and building resilience of mountain communities

Geography, Environment, Sustainability. 2024. Vol. 17. No. 4. P. 205–216.
Raisa G. Gracheva, Vera V. Vinogradova, Alexander V. Sheludkov, Muduev S. S.

In agricultural mountain regions, changes in weather patterns force people to look for new agricultural activities, shift from agriculture to tourism services, or even leave the mountains. This study discusses the role of Dagestan’s agricultural terraces as a potential resource for mountain people to adapt agricultural activities to climate change, thereby demonstrating the community resilience grounded on local traditional practices. We selected eight mountainous administrative districts of Dagestan as a case study area and tracked the changes of average annual, summer, and winter temperatures and precipitation for different altitudes in 2011–2020 compared to 2000–2010. We also conducted 30 informal exploratory interviews with local farmers and officials (purposive sampling) aiming at revealing common local narratives regarding climate change and its impact on agricultural activities, including the use of terraces. According to our results, respondents perceive the warming and drying of the Dagestan mountains as a growing water scarcity due to decreased precipitation and reduced snow cover, and as an opportunity to expand agricultural activities to higher altitudes. Agricultural terraces are seen as a prime land resource, preventing erosion and conserving soil moisture. Including terraces as a tourist attraction could increase interest in the local landscape and its history and may also indirectly serve to strengthen the resilience of local communities. While climate change may make it difficult to farm in the mountains, tourism becomes an additional source of income for farmers and supports agriculture.

Research target: Earth Sciences Social and Economic Geography (including Urban and Transportation Studies)
Language: English
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Keywords: agricultureNorth CaucasusHistorical Heritagemountainsclimate change perception
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