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News
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
Researchers Develop Method for Direct Generation of Regulatory DNA
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.’
August 21, 2026
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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Пассивная агрессия на рабочем месте: адаптация опросника пассивной агрессии на русской выборке

Организационная психология. 2025. Т. 15. № 2. С. 145–157.
Gnipova S.

The relevance of the work lies in the absence of a Russian-language tool for assessing passive

aggression, which is important, since passive aggression negatively affects the well-being of employees

in the workplace. This will help to expand the methodology of studying this phenomenon. Purpose.

The aim of the work is to adapt The Scale of Passive Aggression into Russian (Lim, Suh, 2022). Method.

The sample consisted of 382 respondents (226 women and 156 men) working in Russia, aged 18 to 66

years (M = 33.4, SD = 9.84). In the process of adapting the Passive Aggression Scale, direct and reverse

translation was carried out, and cognitive interviews were conducted. To verify the validity of the

questionnaire, the neuroticism subscale of the Russian version of the Big Five questionnaire (Kalugin

et al., 2021) and the Dark Triad questionnaire (Jonason et al., 2020; Kornilova, Kornilov, Chumakova,

Talmach, 2015) were used. Results. The scale showed good consistency and validity. Confirmatory

factor analysis confirmed the presence of three factors and showed a satisfactory result. The value of

the results. A tool has been adapted to assess passive aggression in the workplace.

Research target: Psychology
Language: Russian
Keywords: организационная психологияприкладная психометрика
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