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News
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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Microplastics distribution in the Eurasian Arctic is affected by Atlantic waters and Siberian rivers

Communications earth & environment. 2021. No. 2. Article 23.
Yakushev E., Gebruk A., Osadchiev A., Semiletov I.

Plastic pollution is globally recognised as a threat to marine ecosystems, habitats, and wildlife, and it has now reached remote locations such as the Arctic Ocean. Nevertheless, the distribution of microplastics in the Eurasian Arctic is particularly underreported. Here we present analyses of 60 subsurface pump water samples and 48 surface neuston net samples from the Eurasian Arctic with the goal to quantify and classify microplastics in relation to oceanographic conditions. In our study area, we found on average 0.004 items of microplastics per m3 in the surface samples, and 0.8 items per m3 in the subsurface samples. Microplastic characteristics differ significantly between Atlantic surface water, Polar surface water and discharge plumes of the Great Siberian Rivers, allowing identification of two sources of microplastic pollution (p < 0.05 for surface area, morphology, and polymer types). The highest weight concentration of microplastics was observed within surface waters of Atlantic origin. Siberian river discharge was identified as the second largest source. We conclude that these water masses govern the distribution of microplastics in the Eurasian Arctic. The microplastics properties (i.e. abundance, polymer type, size, weight concentrations) can be used for identification of the water masses.

Research target: Chemistry Earth Sciences
Language: English
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Keywords: environmental impactsвоздействие на окружающую средуMarine chemistryPhysical oceanographyPollution remediationМорская химияФизическая океанографияУстранение загрязнения
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