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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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Relational and Algebraic Methods in Computer Science - 19th International Conference, RAMiCS 2021, Marseille, France, November 2-5, 2021, Proceedings

Vol. 13027. Springer, 2021.
Zakharyaschev M., Kurucz A., Savateev Y., Ryzhikov V.

We prove that, similarly to known PSPACEPSPACE-completeness of recognising 𝖥𝖮(<)FO(<)-definability of the language 𝐿(𝔄)L(A) of a DFA 𝔄A, deciding both 𝖥𝖮(<,≡)FO(<,≡)- and 𝖥𝖮(<,𝖬𝖮𝖣)FO(<,MOD)-definability (corresponding to circuit complexity in AC0AC0 and ACC0ACC0) are PSPACEPSPACE-complete. We obtain these results by first showing that known algebraic characterisations of FO-definability of 𝐿(𝔄)L(A)can be captured by ‘localisable’ properties of the transition monoid of 𝔄A. Using our criterion, we then generalise the known proof of PSPACEPSPACE-hardness of 𝖥𝖮(<)FO(<)-definability, and establish the upper bounds not only for arbitrary DFAs but also for 2NFAs.

Research target: Computer Science
Language: English
DOI
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Keywords: regular languagesfirst-order definability
Publication based on the results of:
Синтез логических и статистических методов машинного обучения для междисциплинарных приложений (2021)
Relational and Algebraic Methods in Computer Science - 19th International Conference, RAMiCS 2021, Marseille, France, November 2-5, 2021, Proceedings
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