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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
'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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Waste Management in Green and Smart Cities: A Case Study of Russia

Sustainability. 2020. No. 12(1). P. 1–17.
Mingaleva Z., Vukovic N., Volkova I., Salimova T.

This article aims to investigate the role of waste management in the development of modern green and smart cities and to determine the existence of several key points in programs transforming cities into green cities with smart technologies. The relevance of the research is determined by the need to develop a theoretical and methodological basis for the green and smart city concepts. The research process involved the following methods: Scientific analysis, comparison, and synthesis. The research results of the case study of Russia determined that for urban territories with great distances between urban districts, waste sorting stations should be located as parts of so-called waste recycling complexes at intermunicipal landfills. This will allow a more fully implementation of the concept of recycling economy not only in Russian cities, but also in other cities with sparse populations across the world. Further, the authors conclude that the effectiveness of green technologies in modern cities, especially in waste management, depends on the level of participation of citizens. People are active participants in the life processes of cities and have a direct impact on the urban environment. Consequently, the introduction of green technologies can only be achieved in harmony with the well-established behavioral attitudes of city residents together with the implementation of green and smart urban technologies

Research target: Effective Natural Resource Management Economics and Management
Priority areas: management
Language: English
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DOI
Text on another site
Keywords: recyclinggreen economySmart Citywaste managementgreen city
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