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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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Кто и почему ищет государственной поддержки в новой России?

Мир России: Социология, этнология. 2020. Т. 29. № 1. С. 31–52.
Anikin V. A., Lezhnina Y. P., Mareeva S., Slobodenyuk E.

The paper addresses the question, what is the underling nature of the Russians’ demand for the state support in three fields such as labour market and employment, social investments, and material support. Based on the recent findings from social policy studies, the authors have tested four different mechanisms, which are as follows: (a) demographic features of the population, (b) household incomes and disposable assets including human and social capital, (c) interests, and (d) locus control and cultural settings. Drawing on the all-Russia representative Monitoring survey conducted by the Institute of Sociology of the Federal Center of Theoretical and Applied Sociology of the Russian Academy of Sciences in 2018, the authors argued that population’s demands for the state support has very complex nature. Moreover, the relative impact of income has a paradoxical nature. On the one hand, the Russian data confirm the hypothesis of ‘altruistic reach’ developed in recent studies, which predicts that, in societies with high inequalities, higher incomes boost the probability of demands for the redistributive settings. On the other hand, higher incomes foster state escapism of those Russians who do not consider state as a reliable agent capable to solve their problems.

Research target: Humanities Social Sciences
Priority areas: economics sociology management state and public administration law humanitarian
Language: Russian
Full text
DOI
Keywords: социальная политикагосударственная политика занятостиsocial policyгосударственная поддержкагосударство всеобщего благосостоянияwelfare statesolidaritysocial investmentsgovernment supportNew Russiaemployabilitystate and societyredistributionstatismсоциальное инвестированиеновая Россия
Publication based on the results of:
Mobilization and improvement in human capital of the middle class and vulnerable groups (2019)
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