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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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Спортивная идентичность как предиктор самоэффективности у людей с разным уровнем вовлеченности в физическую активность

Национальный психологический журнал. 2021. Т. 3. № 43. С. 43–49.
Кушнирук А. В.

Background. Success and obtaining the highest results are one of the most important phenomena in modern society. Self-eff ectiveness directly infl uences the indicators that are the most topical in the context of maximal achievement, namely in professional sport. Scientists have earlier found positive correlation between physical activity and self-effi - cacy. However, the question on the place of athletic identity in connection between physical activity and self-effi cacy remains unsolved.

Objective. Th e study of correlation between physical activity, athletic identity and self-effi cacy.

Design. 200 participants with diff erent levels of involvement into physical activity and sport took part in our study. In ourstudy B.W. Brewer’s “Athletic identity measurement scale” and R. Schwarzer and M. Jerusalem’s “General self-effi cacy scale” were used.

Results. We statistically proved that there is positive correlation between physical activity level, athletic identity and self-effi cacy.

Conclusion. Athletic identity is a predictor of self-effi cacy among people who are involved in sport and physical activity and the higher is the level of athletic identity the higher is self-effi cacy. Correlation of these phenomena among people who are uninvolved into physical activity is not found.

Research target: Psychology
Language: Russian
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Keywords: самоэффективностьпрофессиональный спортself-efficacyprofessional sportamateur sportathletic identityспортивная идентичностьлюбительский спорт
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