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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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Nascent entrepreneurs’ progress in the venturing process: the role of proactiveness and cultural values

Journal of Small Business and Entrepreneurship. 2025. Vol. 37. No. 1. P. 111–145.
Emilia Karpinskaia, Louisa Selivanovskikh, Galina Shirokova, Bodolica V.

Understanding what entrepreneurs do and how their actions relate to successful new venture creation is a central research topic in the field of entrepreneurship. However, a comprehensive understanding of what leads to venture success is currently lacking. In our study, we explore the role of nascent entrepreneurs’ proactiveness in the process of new venture creation in different national cultural settings. We use a generalized linear model estimation with a negative binomial probability distribution to analyze a sample of 22,163 nascent entrepreneurs from 32 countries to assess the effects of proactiveness and national culture on venturing progress. Our findings demonstrate that individual proactiveness positively relates to the progress of new venture creation by nascent entrepreneurs. The dominance of embeddedness and harmony values is associated with lower levels of progress in the venturing process, although in more autonomous and mastery cultures the effect of proactiveness on venturing process is stronger. Our research highlights the importance of both individual-level characteristics and country-level contextual variables when studying nascent entrepreneurship.

Research target: Economics and Management
Language: English
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Keywords: nascent entrepreneursGUESSS national cultureproactivenessventuring process
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