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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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Снижение учебного стресса студентов высшей школы в рамках занятий по физической культуре

Теория и практика физической культуры. 2025. № 9. С. 44–46.
Пахарева А. П., Родичкин П. В., Kostov F., Пономарев Г. Н.

Objective of the study is to assess the stress resistance of female university students who regularly engage in physical education. Methods and structure of the study. The research involved first- and second-year students of the National Research University Higher School of Economics in St. Petersburg who regularly attend physical education classes at the university (n=18). The following psychodiagnostic tools were used: the “Spectrum of Psychological Health” method, the “Reader Psychological Health Scale”, the “Stress Resistance Test” (Yu.V. Shcherbatykh) and the “Stress-FIE test”. The Wilcoxon t-test was used as a statistical criterion. Results and conclusions. It was found that first- and second-year female students, thanks to regular physical exercise, partially manage to resist academic stress, but as the session approaches, a deterioration in emotional and psychological well-being is noted with an increase in stress sensitivity and information stress. As a result, the development of new methods for increasing female students' resistance to academic stress by means of physical education becomes relevant.

Research target: Health Studies Education Psychology
Language: Russian
Full text
Keywords: студентыstudentsфизическая нагрузкаphysical activityphysical exercisesфизические упражненияacademic stressУчебный стресс
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