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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.’
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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Extending the “Extended Privacy Calculus model”: Relating privacy behavior and well-being in a representative sample of Vkontakte SNS users

Current Psychology. 2026. Vol. 45. Article 728.
Sinyavskaya Y., Koltsova O.

The privacy calculus model has been widely applied to examine how social networking site (SNS) users balance perceived risks and benefits in their privacy decisions. However, it remains unclear how this risk–benefit evaluation, after translating into corresponding privacy behaviors, subsequently affects users’ well-being. This study proposes an extended model in which several measures of well-being serve as outcomes of this privacy calculus process. Using a cross-sectional survey and digital trace data on privacy settings from a demographically stratified sample of Russian VKontakte SNS users (N = 895), we found that users who anticipated greater benefits from SNS use disclosed more personal information, whereas those perceiving higher privacy risks engaged in stronger protective behaviors. As expected, higher self-disclosure further translated into greater psychological well-being and perceived social capital. In contrast, although privacy concerns were positively related to protective behavior, they showed an association with only one component of well-being —perceived bonding social capital —and this link was not mediated by privacy protection. Overall, by integrating motivational and behavioral dimensions and considering both self-disclosure and protection within a single framework, this cross-sectional study demonstrates an asymmetric role of the two privacy-calculus components in shaping well-being in online contexts.

Research target: Social Sciences
Language: English
DOI
Text on another site
Keywords: social capitalstructural equation modeling (SEM) satisfaction with life well-beingprivacy behaviorprivacy calculussocial networking sites (SNS)
Publication based on the results of:
Analysis of Human Interaction with Information and Improvement of Algorithms of Information Processing (2025)
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