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News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Оценка взаимосвязи состояния здоровья и занятости россиян в конце 2010-х годов

Социологические исследования. 2021. № 7. С. 61–72.
Karavay A.

The article deals with the problems of the influence of individuals’ health status on the probability of their employment. Also, we assessed the effectiveness of various methods of measuring individuals’ health status in sociological surveys. The results of the regression analysis show that there is a statistically significant relationship between a person’s employment and their health status, as well as the feasibility of including health indicators in the corresponding regression models. Optimal in this case is a combination of objective (the presence of disability) and subjective (self-perceived health status) indicators. We demonstrate the place of health status among other factors of employment and the key ones are highlighted, both in general and separately for men and women since the population of the country still retains the ideas of gender social roles characteristic of Russian culture. These roles cause differences in the set of factors that affect the probability of men’s and women’s employment, including considering health status. It is also shown that weak health, even without disability, severely limits individuals’ chances of employment, and this situation has remained unchanged since at least the mid-1990s. At the same time, good health status in comparison with the situation of the mid-2000s has now begun to increase the probability of employment in Russia in comparison with even average health status. At the same time, the elements of a healthy lifestyle associated with a healthy diet and physical activity are still not sufficiently widespread, although there are fewer adepts of bad habits among Russians.

Research target: Sociology (including Demography and Anthropology
Language: Russian
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DOI
Text on another site
Keywords: здоровый образ жизниhealthy lifestyleгендерные стереотипыздоровье россиянlabor forceemployment factorsрабочая силаgender stereotypesRussians’ health statusфакторы занятости
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