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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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Proceedings of the 19th Annual International Conference on Digital Government Research: Governance in the Data Age

NY : Association for Computing Machinery (ACM), 2018.
Under the general editorship: M. Janssen, S. A. Chun, V. Weerakody

The dg.o conference is the flagship conference of the Digital Government Society (DGS), and has positioned itself to be a top-ranking conference in this interdisciplinary academic field. It brings high quality research contributions and plays a major role in the advancement of knowledge in the field of digital government. The continue growing number of scholars and the growing number of members will continue to reinforce the position of DGS as a research and practice platform where researchers and practitioners can meet, exchange ideas, and build new relationships.

Chapters
Toward an ethics of digital government: a first discussion
Domanski R., Estevez E., Styrin E. M. et al., , in: Proceedings of the 19th Annual International Conference on Digital Government Research: Governance in the Data Age.: NY: Association for Computing Machinery (ACM), 2018. Ch. 123 P. 1–4.
In this panel, scholars discuss involving data, computational analysis, and information technology that has the potential to present ethical quandaries in the course of decision making related to digital government. More specifically, the presentations focus on algorithm-based decision making, personally identifiable information, and the manipulation of public opinion in social media channels. Discussion following the ...
Added: June 9, 2018
Research target: Economics and Management
Priority areas: state and public administration
Language: English
DOI
Text on another site
Keywords: governmentopen governmente-GovernmentSmart CityBlockchainbig and open data Internet of Things
Proceedings of the 19th Annual International Conference on Digital Government Research: Governance in the Data Age
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