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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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Effects of Specific Alcohol Control Policy Measures on Alcohol-Related Mortality in Russia from 1998 to 2013

Alcohol and Alcoholism. 2015. Vol. 50. No. 5. P. 588–601.
Korotayev A., Khaltourina D.

Aims To elucidate the possible effects of alcohol control policy measures on alcohol-related mortality in Russia between 1998 and 2013. Methods Trends in mortality, alcohol production and sales were analyzed in conjunction with alcohol control legislative measures. Correlation analysis of health and alcohol market indicators was performed. Results Ethyl alcohol production was the strongest correlate of alcohol-related mortality, which is probably due to the fact that ethyl alcohol is used for both recorded and unrecorded alcohol production. Measures producing greatest mortality reduction effect included provisions which reduced ethyl alcohol production (introduction of minimum authorized capital for ethyl alcohol and liquor producers in 2006 and the requirement for distillery dreg processing), as well as measures to tax and denaturize ethanol-containing liquids in 2006. Liquor tax decrease in real terms was associated with rising mortality in 1998–1999, while excise tax increase was associated with mortality reduction in 2004 and since 2012. Conventional alcohol control measures may also have played a moderately positive role. Conclusions. Countries with high alcohol-related mortality should aim for a reduction in spirits consumption as a major health policy. Alcohol market centralization and reduction of the number of producers can have immediate strong effects on mortality. These measures should be combined with an increase in alcohol taxes and prices, as well as other established alcohol policy measures. In 2015 in Russia, this is not being implemented. In Russia, legislation enforcement including excise tax collection remains the major challenge. Another challenge will be the integration into the Eurasian Economic Union. 

 

Research target: Economics and Management Mathematics Sociology (including Demography and Anthropology Political Science, International Relations, and Public Administration History and Archeology
Priority areas: economics sociology law IT and mathematics mathematics
Language: English
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Keywords: демографиясмертностьРоссияRussiamortalitydemographyalcoholалкогольная смертность
Publication based on the results of:
Monitoring of risks of socio-political destabilization in the "Afro-Asian" zone of instability (2015)
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