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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 трансформации роста китайской экономики в «эпоху Си»

Экономический журнал Высшей школы экономики. 2026. Т. 30. № 2. С. 344–376.
Lola I. S., Asoskov D.

The article analyzes the transformation of China's economic growth mechanisms in the period after Xi Jinping came to power, with a focus on interprovincial heterogeneity. Based on panel data for 29 provinces of China for 2001-2024, the Bayesian hierarchical regression model is estimated, which makes it possible to identify both average (fixed) and provincial-specific (random and total) effects of key intra-system macroeconomic factors, including export growth rates, R&D expenditures, retail sales and budget deficits. It is emphasized that the observed slowdown in the Chinese economy is not temporary, but structural, determined by the existing imbalances in the economy, including at the regional level.

The empirical strategy assumes an explicit division of the sample into the periods before and after 2012 (the year Xi Jinping came to power), which makes it possible to identify changes in the role of these factors in the context of the discussed transition from an export-oriented growth model to a reliance on domestic consumption and innovation. However, the results show that in 2013-2024 exports remain the main driving force, while role of R&D activity has strengthened extremely, domestic consumption loses its leading position, and government spending ceases to influence the dynamics of economic development in any way, which casts doubt on the success of the “dual circulation” policy. It is also worth noting that after 2012, the interprovincial variability in the contributions of growth factors is decreasing, and 3 types of growth mechanism identified as a result of cluster analysis of the combined effects which existed in 2001-2012 are subsequently reduced to 2.

The findings complement the literature on the “new normal” of the Chinese economy and contribute to research on regional inequality, demonstrating that the transformation of the growth model is accompanied not only by changes in average effects, but also by a contraction of the space of regional economic divergence.

Research target: Economics and Management
Language: Russian
DOI
Keywords: экспортэкономический ростeconomic growthexportНИОКР R&Dtransformation of growthBayesian regression model"Xi era"трансформация ростабайесовская регрессионная модель"эпоха Си"
Publication based on the results of:
Assessment of the business climate based on the results of conjuncture surveys in the conditions of formation of a new model of economic growth (2025)
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