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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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Multicomponent framework for students' subjective well-being in elementary school

School Psychology. 2020. Vol. 35. No. 5. P. 321–331.
Kanonire T., Federiakin D., Uglanova I.

The study proposes a multicomponent model of subjective well-being (SWB) in elementary school. The model includes satisfaction with school, affect toward school, well-being related to communication with peers, and subjective physical well-being. The aim of this study is to verify whether well-being related to different aspects of school life can be explained by a general SWB factor in school. A sample of 1,704 third-grade students (M age  8.89; SD  0.4; 48.4% girls) was asked to complete a survey consisting of Likert-type scales. The psychometric analysis investigated the internal structure of the data. Multidimensional models from the Rasch modeling framework of item response theory were applied. A correlated factors model, a bifactor model, and oblique bifactor models were compared. Two models fit the data well: the extended Rasch testlet model and the correlated factor model. The findings indicate that a general SWB factor can be extracted from the data through the extended Rasch testlet model. However, the extended Rasch testlet model provides only 1 usable general factor. For the extraction of detailed information by means of scales, the correlated factor model can be applied. Implications for practitioners and limitations of the study are also discussed.

Research target: Education Psychology
Priority areas: humanitarian
Language: English
DOI
Text on another site
Keywords: subjective well-beingelementary schoolItem Response Theorymultidimensional item response modelbifactor item response model
Publication based on the results of:
Estimating the progress of cognitive and non-cognitive development of primary school students (2018)
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