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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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The evolution of Foresight: What evidence is there in scientific publications?

Futures. 2022. Vol. 137. Article 102916.
Saritas O., Burmaoglu S., Ozdemir D.

This study examines the recent evolution of Foresight as a well-recognized tool for long-term policy and strategy making and discusses the future directions the activity might take. The science mapping approach is used for the analysis. Drawing on big data, science mapping provides an evolutionary overview of scientific domains across time and helps to identify patterns showing the research agenda and directions of development of those domains. In the present study, we demonstrate the use of the science mapping approach with the case of the Foresight field. The results of our analysis confirm earlier academic studies on the evolution of Foresight; hence show the validity of the science mapping approach. Besides demonstrating the evolution of the field with the scientific publications in the last couple of decades, the study seeks scientific evidence for the next generations of Foresight to emerge towards the 2030s.

Research target: Economics and Management
Language: English
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DOI
Text on another site
Keywords: big dataForesightForesight evolutionForesight-on-siteScience mapping
Publication based on the results of:
The new science, technology, and innovation agenda to address the grand challenges (2022)
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