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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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Towards building a multi perspective policy development framework for transition into renewable energy

Sustainable Energy Technologies and Assessments. 2017. Vol. 21. P. 67–88.
Abotah R., Daim T.

The objective of this research is to evaluate the effectiveness of energy policy instruments on increasing the adoption of renewable energy by developing a comprehensive evaluation model. Criteria used in this assessment depend on five perspectives that are perceived by decision makers as important for adoption process. The decision model linked the perspectives to policy targets and various energy policy instruments. These perspectives are: economic, social, political, environmental and technical. The research implemented the hierarchical decision model (HDM) to construct a generalized policy assessment framework. Results of this research identified economic feasibility improvement of renewable energy projects as the most influential perspective and that renewable portfolio standards and tax credits are the two most effective criteria to accomplish that.

Language: English
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Keywords: renewable energytechnology policytechnology assessmentMulti criteria decision makingHierarchical decision modeling
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