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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.
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Climate signal strength in tree-ring width of spruce growing in the Solovetsky Islands (Russia)

Dendrochronologia. 2022. Vol. 76. Article 126012.
Dolgova E., Olga N. Solomina, Vladimir V. Matskovsky, Cherenkova E., Semenyak N.

In this study we used 14 spruce tree-ring width local chronologies from sites that are located in different landscape conditions. The climatic response function for the entire period (116 years) shows that all local chronologies without exception have a positive relationship with June temperature (from 0.196 to 0.408) despite quite different local environmental conditions. This finding allowed us to combine all tree-ring width local chronologies into a composite spruce chronology covering the period of 1676–2016 CE with EPS exceeding the 0.85 threshold. The composite chronology was scaled against June air temperatures (CRU TS 4.01) in order to reconstruct it. Monthly air temperature records from the Arkhangelsk weather station were used as an additional source to validate tree-ring based June temperature reconstruction. It is quite remarkable that our reconstruction matches the Archangelsk records not only in the 20th-early 21st centuries but also in the 19th century, confirming the reliability of the reconstruction over more than two centuries. We also used daily records from the nearest Kem’-Port station to identify a more precise target-window. Current research shows that the spruce response to daily temperature is not limited by June, but also extends up to almost half of July. The warmest reconstructed year occurred in 1856 as confirmed by the data published in the local chronicle. The cooling recorded in the historical evidences (describing extremely severe ice conditions in the Arctic seas during the Great Northern Expedition (1733–1743)) was not corroborated by our reconstruction. In the study, we discuss the reasons of the discrepancies found between Solovki June temperature reconstructions and other data such as different seasonality of the compared records, real local climate warming in Solovki, the applied standardization technique, and low of chronologies’ replication. The most reliable part of the reconstruction part lasting from the early 19th to the early 21st centuries is also discussed in terms of its properties like wavelength analyses, and the assessment of influence of volcanic eruptions.

Research target: Earth Sciences
Language: English
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Keywords: dendroclimatologyдендроклиматология
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