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September 4, 2026
‘Hedgehog Versus ‘Relatives: Researchers Measure How the Brain Responds to Unexpected Words During Natural Speech
Russian neurophysiologists, including researchers from HSE University, have demonstrated the feasibility of using event-related fields (ERFs) to study brain activity during natural speech perception. The researchers showed that this approach can be applied not only to individual words but also to continuous speech. Their findings indicate that words whose meanings differ significantly from the preceding context require longer processing times. The study also reveals that the brain processes function words in two stages: first, it identifies their grammatical role and then uses this information to predict the next word. The study has been published in Frontiers in Human Neuroscience.
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.’

 

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Влияние социального капитала на политическую коммуникацию в соседских онлайн-сообществах

Вестник Московского университета. Серия 12: Политические науки. 2025. № 4. С. 126–152.
Бабкин А. А.

In the digital age, neighborhood communication has shifted to the online space, altering the traditional nature of interactions. This raises questions about the applicability of traditional knowledge about neighborhoods to their online counterparts. This study examines the impact of social capital within online neighborhood com- munities on political communication among their members. To do so, we analyzed the digital footprints of online neighborhood communities in the city of Volgograd, including all districts and types of buildings. Using machine learning techniques for natural language processing and network analysis, we examined over 79,000 posts over a 17-year period to evaluate the impact of both structural and relational dimensions of social capital. The results indicated that the characteristics of social capital in online communities influence political communication in a similar way to traditional interactions. A sense of community, high density, and the clustering of the network, as well as the presence of key intermediary nodes, contribute to discussions about political topics. This suggests that digital platforms can replicate the social mechanisms found in offline environments, and that previously accumulated knowledge about the impact of neighborhoods on political participation can be applied in a digital context.

Language: Russian
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Keywords: социальный капиталsocial capitalполитическая коммуникацияpolitical communicationцифровые следыdigital tracesneighborhood online communitiesсоседские онлайн-сообществаneighborhood communicationсоседская коммуникация
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