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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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Experience in Calculating Distances between Different Types of Population Centers in Russia (to Estimate the distance of Population Migration)

Regional Research of Russia. 2024. Vol. 14. No. 2. P. 213–226.
Karachurina L. B., Mkrtchyan N. V.

The problem of measuring distances in migration is a nontrivial, but important problem, e.g., for delimiting the concepts of population migration and residential mobility. With limited access to detailed spatial data, researchers address this problem in different ways. Only a few countries, e.g., Sweden, have the ability to calculate migration distances between point locations using Euclidean distance. This article examines the measure of correspondence of Euclidean distances (measured taking into account the curvature of the globe) to real distances along transport routes for the case of Russia. For this, 3407 pairs of distances were calculated for randomly selected 23 municipal districts in Russia directly and along transport routes—roads. Also, 411 pairs of distances were calculated for population centers with no road connections by using air service. These distances give an idea of migrations of different distances in Russia. As a result, for hypothetical relocations within the selected municipal districts, real distances on roads exceed Euclidean distances by 51%; for relocations between the centers of districts and urban okrugs within a region, by 40%; for interregional relocations, 33%. The air service used “straightens” distances, but even taking this into account, real distances (mainly long-distance, interregional) exceed Euclidean distances by 28.5%. The calculations give an idea of the deviations of real transport distances from the relatively simple Euclidean distances, which can be used in analyzing migration distances in Russia.

Research target: Sociology (including Demography and Anthropology Earth Sciences
Language: English
Full text
DOI
Keywords: municipalitiesrange Russian regionsEuclidean distancetransport distance population migration
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