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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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Uptake of ecosystem service concept in urban blue-green infrastructure planning and decision-making in Russia

Blue-Green Systems. 2024. Vol. 6. No. 2. P. 327–344.
Konstantinova A., Filyushkina A., Maximova O., Kerdivar K., Gromova A., Matasov V., Vasenev V.

In the scientific community, ecosystem services (ESs) are well-recognized as a promising concept to more actively consider and plan for the multitude of benefits provided by the green environment and thus promote sustainable urban development. Yet, to have an impact on decision-making, the concept must spread from academia to practice. To understand to what extent ES have been adopted in practice and decision-making in Russia, we conducted a series of interviews and an online survey with both practitioners and scientists and complemented it by document analysis. Our results showed that ES are not adequately reflected in urban decision-making and planning processes. Moreover, we found no explicit references to ES in strategic urban planning and landscape development projects, although there are few implicit references in several reviewed documents. Among the identified challenges for better uptake of the concept in practice were many disagreements associated with the lack of a unified terminology, typology, and methods. Stakeholders understand the potential of applying ES valuation in practice, which includes a necessity to develop methodological materials and different tools based on real-life cases. Finally, a list of proposals on possible ways to better include ES in urban planning and in decision-making processes was formed by the respondents.

Research target: Social and Economic Geography (including Urban and Transportation Studies) Effective Natural Resource Management
Language: English
DOI
Keywords: decision-makingurban developmentstakeholdersecosystem servicesblue-green infrastructure (BGI)
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