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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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A preliminary study on the role of personal history of infectious and parasitic diseases on self-reported health across countries

Public Health. 2025. Vol. 242. P. 220–227.
Pfuhl G., Prazeres F., Kowal M., Aavik T., Abad-Villaverde B., Afhami R., Aguilar L., Grigoryev D.

Objectives

Infectious diseases are often associated with decline in quality of life. The aim of this study is to analyze the relationship between personal history of communicable, i.e., infectious and parasitic diseases and self-rated health.

Study design

Secondary analysis of a large dataset multi-country observational study.

Methods

We used a four-pronged analysis approach to investigate whether personal history of infectious and parasitic diseases is related to self-reported health, measured with a single item.

Results

Three of the four analyses found a small positive effect on self-reported health among those reporting a history of pathogen exposure. The meta-analysis found no support but large heterogeneity that was not reduced by two classifications of countries.

Conclusion

Personal history of infectious and parasitic diseases does not reduce self-reported health across a global sample.

Research target: Health Studies Medical and Health Sciences Social Sciences
Language: English
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DOI
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Keywords: mental healthglobal healthcommunicable diseases
Publication based on the results of:
Comparative studies of culture and subjective well-being: differentiation and integration of societies in the context of global challenges (2025)
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