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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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Экономический статус занятого населения России: объективное и субъективное измерения

Вестник Института социологии. 2018. № 24. С. 76–94.
Коленникова Н. Д.

This article examines peculiarities when it comes to the distribution of economic statuses among the working population of Russia, as well as the interconnections of said statuses with various factors which affect an individual’s economic prosperity. Presented is a method for structuring a certain index, the purpose of which is to measure objective parameters of the economic status of modern Russia’s working population. In developing this methodology the author adheres to the neo-Weberian tradition, assuming that an individual’s economic status consists of a set of objective indexes which can be measured quantitatively. In this case these characteristics are as follows: income, the possession of additional real estate aside from the main place of residence, as well as the possession of savings. It is shown that the economic status of the population’s majority has a clearly pronounced “norm”, which is relatively low-level, together with the fact that the possession of additional economic resources such as real estate tends to lower Russian people’s motivation when it comes to increasing their current level of income. Also presented is a series of conclusions which have to do with the specifics of the economic status of Russia’s working people from various educational and professional groups. A certain hypothesis is brought forward and validated, concerning the insignificant effect of educational resource and professional affiliation on the economic status of common Russians. Examined is the effect of employment form on economic status scale indexes, as well as peculiarities when it comes to the distribution of its parameters among age groups. The following conclusion is made: within each successive age cohort there is a decrease in the amount of workers with an economic status corresponding to the Russian “norm”, as well as the amount of those workers whose status exceeds said norm. The objective parameters of Russian people’s economic status are compared with their subjective evaluation of said status. Given the presence of a considerable discrepancy between them, the author comes to the conclusion that objective parameters are not consistent with subjective evaluation. Data from the 24th wave of the yearly RLMS-HSE survey, conducted at the end of 2015, was used as an empirical base for analysis.

Research target: Economics and Management Sociology (including Demography and Anthropology
Priority areas: economics sociology
Language: Russian
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Keywords: человеческий капиталобразованиеeducationэкономический ресурсhuman capitalstatus consistencyeconomic statusстатусная консистентностьэкономический статусeconomic resourseproffesional affiliationпрофессиональная принадлежность
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