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August 25, 2026
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.
August 24, 2026
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Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’
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Social Integration: At the Crossroads of Knowledge and Values
The International Laboratory for Social Integration Research (ILSIR) at HSE University studies the challenges faced by vulnerable groups and explores ways to help them participate fully in everyday life. To develop effective solutions, the laboratory’s researchers combine cutting-edge methods with practical fieldwork. In this interview with the HSE News Service, Laboratory Head Elena Iarskaia-Smirnova discusses the laboratory’s work.

 

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Environmental rating of oil and gas companies in Russia: How assessment affects environmental transparency and performance

Business Strategy and the Environment. 2018. Vol. 27. No. 7. P. 1023–1038.
Shvarts E., Пахалов А. М., Книжников А. Ю., Аметистова Л. Е.

The article discusses the evolution and current state of transparency of environmental performance data in the Russian Oil and Gas sector. We build upon our first‐hand experience in a transparent, publicly available information and third‐party‐verified rating system. Based on 2014–16 successive annual ratings, we conclude that implementing “soft” responsibility mechanisms can improve environmental responsibility standards and transparency in the oil and gas industry. At the same time, in terms of improving environmental performance of oil and gas companies it is reasonable to assume an emerging trend. Its full realization will require (1) longer rating time, including that for public exposure to misleading environmental performance information and the use of poorly verified nonfinancial reporting; (2) application of independent analysis of satellite monitoring information to the professional audit and public verification of nonfinancial reporting; and (3) sophistication of guidelines for professional audit and public verification of nonfinancial reports.

Research target: Effective Natural Resource Management Economics and Management
Language: English
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Keywords: ratinginformation disclosureenvironmental managementenvironmental responsibilityenvironmental impactsRussian oil and gas industry
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