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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
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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Three-Dimensional Trait System: Binding together the main sources of diversity in personality traits

2019.
Shchebetenko S.
Why are there various personality traits and why are those traits revealed in widely-acclaimed models such as the Big Five?  The Three-Dimensional Trait System (3D-TRASY) states that any personality trait can be defined in terms of three basic sources.  The first source represents traits’ variability with regard to the brain’s functioning in terms of bottom-up and top-down processes.  The second source connects to positive (rewards) and negative (punishments) social reinforcements of the trait.  The third source reflects a multitude of situations in which a trait may unfold.  Thus, Extraversion can be defined as a proximate bottom-up positive while Conscientiousness is a distal top-down positive.  3D-TRASY provides a framework for formal, non-tautological definitions of traits; it provides explanations for various phenomena in trait research including the super-traits of Stability and Plasticity and the maturity principle of lifespan development.  3D-TRASY presumes that some traits can occasionally closely correlate and thus establish an amalgam, which exemplifies itself in Eysenckian Psychoticism and the Big-Five’s Agreeableness.  In the history of trait research, this amalgamation may explain controversies that would have facilitated emergence of novel models such as the Big Five or HEXACO.  The paper contains empirical demonstrations on how 3D-TRASY can explain apparently empirical artifacts.
Research target: Psychology
Language: English
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Keywords: Big Fivepersonality traitsчерты личностиindividual differencesиндивидуальные различия"Большая пятерка" личностных чертпятифакторная модель личностиструктура личностиpersonality structureБольшая пятеркаfive-factor modelHEXACOHEXACO
Publication based on the results of:
Психометрические испытания русскоязычной версии вопросника "Big Five Inventory-2" (2019)
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