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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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Executive Constraints and Economic Growth in Autocracies

Вестник Пермского университета. Серия: Политология. 2018. Vol. 12. No. 4. P. 106–121.
Mitrokhina E.

Authoritarian regimes differ by the degree to which the leader is constrained in his ability to influence the decision-making process. It has been argued that unlimited executive can either lead to adverse economic policy outcomes or improve economic performance. In this work, I reassess the effect of executive constraints on economic performance. While most of the previous research in this area focuses on regime typologies, I use observable indicators of power personalisation in 90 autocratic countries from 1960-2010 and estimate their effect on economic performance. I focus on power concentration, the extent of the decision-making power of chief executives and leaders’ ability to dismiss the elites form political institutions as the indicators for measuring leaders’ ability to influence the decision-making process. I discover that countries, where leaders are able to stay in office longer and are able to change the cabinet, concentrate more power in their hands and tend to be more opportunistic. The results imply that strong leaders establish such power-sharing mode that allows them to act in a self-interest way.

Research target: Political Science, International Relations, and Public Administration
Language: English
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Keywords: economic growthполитические режимыpolitical regimespower personalizationexecutive constraintsautocraciesограничение исполнительной властиперсонализация власти
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