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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
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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Processing Conditional Perfection in promises and threats: The role of negation, clause order and incentive

Journal of Psycholinguistic Research. 2021. Vol. 50. P. 1557–1573.
Zevakhina N., Prigorkina V.

The paper reports on two experiments that investigate whether polarity, clause order and incentive influence derivation of Conditional Perfection in two types of inducements (promises and threats). Both experiments are designed as inference tasks, additionally measuring reaction times to inferences. The paper shows that the derivation of Conditional Perfection is endorsed in both types of inducements. However, the negative consequent bias (i.e. higher rates of Conditional Perfection in conditionals with a negative consequent than in conditionals with an affirmative consequent) and the double negation effect (i.e. slowdown of reaction times to Conditional Perfection with a double negation in a consequent) hold for threats, but not for promises. The paper also reveals a parallel double negation effect (i.e. facilitation of Conditional Perfection in conditionals with negation in both clauses) in threats, but not in promises. Last but not least, the paper demonstrates that the effect of clause order and incentive on the derivation of Conditional Perfection is rather moderate. The paper supports the view that the derivation of Conditional Perfection is not effortful (Van Tiel and Schaeken 2016) and has some indirect arguments for treating Conditional Perfection and scalar implicatures as separate phenomena.

Research target: Philology and Linguistics
Priority areas: humanitarian
Language: English
DOI
Keywords: психолингвистикаpsycholinguisticsлингвистическая прагматикаconditional clausesусловные конструкциипрагматика и семантика языкаexperimental pragmaticsneo-Gricean pragmaticsнео-грайсианская прагматика
Publication based on the results of:
Эксперименты на стыке лингвистики и логики (2020)
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