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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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Populism on the American Left: How Populist is the Sanders Electorate?

Interdisciplinary Journal of Populism. 2021. No. 2. P. 7–31.
Sawyer P., Moore A.

Since the 2016 US presidential elections, political commentators and academics have often attributed the rise of both Bernie Sanders and Donald Trump to a general 'populist' wave affecting the country. While the two politicians are often juxtaposed with each other in terms of their alleged 'populism', there are grounds to question this characterisation for Bernie Sanders on the left. While others have articulated their doubts as to the level of populist attitudes in the Sanders movement, in our study, we move in the direction of analysing the political beliefs of Sanders' supporters. With the use of ANES survey data, our regression models demonstrate that while a small cohort of populist voters did support Sanders during the 2016 primary, they were much smaller in size than traditional left-wing groups that exhibited negative correlations with populist attitudes. When compared with other presidential candidates running in the 2016 primaries, the results demonstrate that those with populist attitudes were much more inclined to vote for the Republican candidate Donald Trump than the Bernie Sanders. Finally, when we run regressions on the disaggregated components of our index for populist attitudes, the results only demonstrate positive relationships with certain components of the populist worldview, such as anti-elitism, but not for others. Our results, thus, bring significant contributions to the study of populism in the United States by pointing primarily to a populist revolt from the right and less so on the left.

Research target: Political Science, International Relations, and Public Administration Sociology (including Demography and Anthropology Social Sciences
Language: English
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Keywords: популизмполитические ценностиpopulismполитическое поведениеpolitical valuespolitical behaviorсоциал-демократияDonald TrumpLeftism2016radical LeftДональд Трампsocial democracyрадикальные левыеBernie SandersUS Electionsdemocratic SocialismлевыйБерни Сандерсвыборы в СШАдемократический социализм
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