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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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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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Распределение внимания в ходе категориального научения детей с расстройствами аутистического спектра

Клиническая и специальная психология. 2026. Т. 15. № 1. С. 51–63.
Luzhnova K., Котова Т. Н., Kotov A. A.

Context and relevance. Category learning plays a key role in cognitive development from infancy. In the process of category learning, adults tend to use selective attention, focusing on the main features of objects, while children use distributed attention, analyzing multiple features simultaneously. The use of selective attention can lead to learning difficulties in new conditions, where the previously learned rule becomes ineffective, and a new one needs to be identified. In such situations, adults, due to selective attention, are less successful than children. Studies indicate that children with autism spectrum disorder (ASD) might demonstrate unique patterns of attention distribution in contrast to neurotypical children during category learning tasks. Objective. This study investigates attention allocation during category learning in children with autism spectrum disorder (ASD). Methods and materials. Involving 39 participants, including neurotypical children and adults, the research assessed how they distinguished categories based on a single rule before shifting to a new one with different relevant features. Results. Findings revealed that both adults and children with ASD struggled more after this shift, with children with ASD showing a significant drop in success rates. This suggests that difficulties in learning within this group are associated with the use of selective attention and the processing of new information.

Research target: Psychology
Language: Russian
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Keywords: категориальное научениерасстройства аутистического спектраcategory learningautism spectrum disorderселективное вниманиеselective attention
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