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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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КВАНТОВЫЙ РАЗМЕРНЫЙ ЭФФЕКТ В ЧИСТЫХ ПЛЕНКАХ АЛЮМИНИЯ

Известия Уфимского научного центра РАН. 2024. № 1. С. 55–60.
Безымянных Д. Г., Pugach N., Sedov E., Arutyunov K., Екомасов Е. Г., Lvov B. G.

In the modern world, there's a notable trend towards the active miniaturization of electronic devices. With technological advances enabling the manipulation of nanostructures, there's an increasing focus on exploring quantum effects pivotal to such designs. One distinguishing feature of nanostructures is the quantum nature of the electron's energy spectrum. This spectrum becomes discrete in directions where electrons move. Depending on the direction of this confinement, structures can be categorized as nanoplates, quantum wires, or quantum dots. The properties of such structures can significantly differ from those observed in large-scale systems. When discussing superconductivity, particular emphasis is placed on its macroscopic quantum properties. The influence on electronic wave functions is reflected in the characteristics of the superconducting state on broader scales. The Bardeen-Cooper-Schrieffer (BCS) theory is frequently utilized to analyze these nanostructures. The Gor’kov equations method serves as a potent tool for tasks related to the BCS theory. For instance, it can determine the parameters of the superconducting state, critical temperature, and current. Components of these equations, like Green's functions, are associated with various system properties. Research in the early stages of superconductivity studies revealed that the critical temperature (Tc) – the temperature at which a material transitions to a superconducting state – can differ significantly between thin films and bulk materials. Intriguingly, reducing the film's thickness can both decrease (e.g., in niobium) and increase (e.g., in aluminum) the Tc value. This study delves into the quantum size effect in thin aluminum films, paving the way for materials with higher transition temperatures. Such advancements can simplify and make the maintenance of superconducting systems more cost-effective. In this study, a theoretical relationship between the critical temperature of a thin aluminum film and its thickness was derived. The Green's function method was chosen, which hadn't been previously employed for this computation. This approach offers greater potential compared to other superconductivity theory methods, presenting extensive avenues for theoretical exploration in this domain. The authors are confident that this work will contribute to further research on quantum dimensional effects in low-dimensional superconducting structures.

Research target: Physics
Language: Russian
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Keywords: сверхпроводниковые тонкие пленкиквантовый размерный эффект
Publication based on the results of:
Квантовые эффекты в низкоразмерных гибридных наноструктурах  (2025)
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Added: September 15, 2022
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