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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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Расчёт трудового потенциала организации на примере ОАО «Литейно-механический завод»

Теоретическая и прикладная экономика. 2021. № 3. С. 14–29.
Troitskaya A.

This article is dedicated to practical implementation of quantitative assessment of labor potential of the company. The author provides the results of implementation of the original methodology for calculating labor potential of the company on the example of “Foundry and Mechanical Plant” OJSC in the city of Semyonov of Nizhny Novgorod region. In the course of development of this methodology on the basis of expert assessments, the author determines the elements of labor potential and establishes correlation between them in order to calculate labor potential of the company in points. To determine the score of labor potential of the company is used the system of private indicators that characterize and substantiate each element: human resources, educational, professional, innovative, social, and economic. This process was implemented at the plant in cooperation with its management; all necessary data was collected; intermediate and total scores were calculated. The obtained total score for 2020 was 101.130 points, which is higher than the standard value of 100 points, and testifies to the good labor potential and positive dynamics of the company. The theoretical importance of the acquired results lies in the fact that they can serve as the foundation for the development of methodological guidelines for quantitative assessment of labor potential of the company. Practical relevance lies in the possibility of their actual application in human resource management of the company “Foundry and Mechanical Plant” OJSC.

Research target: Economics and Management
Language: Russian
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DOI
Text on another site
Keywords: количественная оценкаинновационная активностьinnovative activityинтегральный показательquantitative assessmentкомпонентнормативбазисbasislabor potentialcomponentintegral indicator трудовой потенциалstandardcalculation methodplantparticular indicatorчастный показательзаводметодика расчёта
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