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News
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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Leveraging the Macro-Level Environment to Balance Work and Life: An Analysis of Female Entrepreneurs’ Job Satisfaction

Small Business Economics. 2021. Vol. 56. No. 4. P. 1361–1384.
De Clercq D., Brieger S., Welzel C.

This study investigates the interactive effect of female entrepreneurs’ experience of work–life imbalance and gender-egalitarian macro-level conditions on their job satisfaction, with the prediction that the negative linear relationship between work–life imbalance and job satisfaction may be buffered by the presence of women-friendly action resources, emancipative values, and civic entitlements. Data pertaining to 7392 female entrepreneurs from 44 countries offer empirical support for these predictions. Female entrepreneurs who are preoccupied with their ability to fulfill both work and life responsibilities are more likely to maintain a certain level of job satisfaction, even if they experience significant work–life imbalances, to the extent that they operate in supportive macro-level environments.

Research target: Social Sciences Sociology (including Demography and Anthropology
Language: English
DOI
Text on another site
Keywords: работаудовлетворенность работойгендерное равенствоgender equalityworkjob satisfactionmultilevel analysisженское предпринимательствомультиуровневый анализfemale entrepreneurshiplife imbalanceжизненный дисбаланс
Publication based on the results of:
Exploring cultures: historical legacy and recent challenges (2021)
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