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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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Математическая модель возникновения ошибок в работах проекта

Современная наука: актуальные проблемы теории и практики. Серия: Естественные и технические науки. 2016. № 11. С. 44–48.
Maron M.

Emergence of faults in the works is standard project’s risk. For an assessment of consequences of this risk, it is desirable to know probabilities of faults. At the same time, property of uniqueness of a project, as a rule, does not allow to find required probabilities by means of statistical data. In this article offered the mathematical model for definition of probabilities of faults at implementation of the project. In this model accepted duration of work as a measure of its complexity, and the flow of the arising faults considered as Poisson.

Research target: Economics and Management Computer Science
Priority areas: management engineering science
Language: Russian
Full text
Text on another site
Keywords: Poisson flowпуассоновский потокпроектный рискprobabilities of faults project’s risksвероятности ошибок
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