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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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Статистический анализ влияния гендерного признака на качество обучения математике студентов втуза

Сертификация. 2017. № 4. С. 31–35.
Maksimova O., Богомолова Е. П.

The transition to the competency standards of higher professional education requires an intensification of the educational process. To improve the quality of higher education should take into account not only the traditional long identified factors, but also new, come to the attention in recent decades. This article investigated the influence of gender-specific teaching of higher mathematics in engineering universities on the basis of statistical material collected one of the top technical universities in Moscow. In terms of gender be considered such factors as motivation and professional development of students, discipline and responsibility of homework, ability to geometric and algorithmic thinking, intrinsic and extrinsic motivation. Analyzes of teaching mathematics from a gender perspective in order to achieve the intensification and success in training in preparation for undergraduate engineering areas.

Research target: Mathematics Education
Priority areas: mathematics
Language: Russian
Full text
Keywords: качество высшего образованиястатистический анализпедагогикадисперсионный анализquality of higher educationгендерный признакgender educationanalysis of variance statistical analysisbox and whiskerящик с усами
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