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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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Анализ структур экспорта и импорта с использованием сетевых методов (на примере рынка агропромышленных товаров)

Вестник Санкт-Петербургского университета. Серия 5. Экономика. 2020. Т. 36. № 3. С. 421–446.
Lapinova S. A., Аникина А. И., Osharin A.

Analysis of trade cooperation between countries and identification of the most significant market participants is of great importance, both theoretically and empirically. The global trading community forms a network of international relations defined by trade contracts in various industries. Export-import trade flows are one of the key indicators of the level of cooperation among countries and the state of the global economy. The high intensity of such contacts across groups of countries suggests the existence of clusters in this market segment, consisting of central players—exporters and importers, who often define rules for other participants. Understanding the existence and identification of such a center helps to develop an optimal international trade strategy. The purpose of this contribution is to identify factors affecting trade flows among different countries. Statistical analysis of the international trade relations does not always reveal all the essential aspects of cooperation. This paper combines the methods of graph theory and econometric analysis to study the parameters of trade flows among countries. The parameters used in the network analysis make it possible to obtain additional characteristics of market participants, which help to evaluate their significance in the world trade. The paper also identifies some key mathematical and economic characteristics of export-import flows connecting destination countries. We have analyzed the directions of changes in world trade and established correspondences between metric characteristics of graph vertices and parameters of world trade models. The Russian indicators in export/import categories and its largest sales agents are estimated. The identification of the key intermediaries and importers (centers and authorities) on each of the markets in question has been carried out. As an example for this identification the market of agricultural products among the world's largest exporters and importers of the product were used.

Research target: Economics and Management Mathematics Computer Science
Priority areas: economics IT and mathematics
Language: Russian
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Keywords: econometric modelingэконометрические моделитеория графовinternational trade theorygraph theoryмодели экспорта и импорта
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