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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?
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Nelepoli.ru: комментированное электронное издание «Слова о полку Игореве»

Vox Medii Aevi. 2025. № 2(11). С. 105–117.
Фитискина А. А., Фитискин А. А.

Abstract

This article presents a new commented open-source electronic edition of the Tale of Igor's Campaign (nelepoli.ru). The Old Russian text of the Tale and its new collective linguistic translation into modern Russian serve as the basis of the edition. The text is supplemented by three types of commentaries (linguistic, historical, and zoological) and is accompanied by a genealogical tree of the Rurikids, as well as a geographical map. The primary goal of the project is to provide the general reader with the tools necessary for a deep immersion into the Old Russian text. For this purpose, an interactive reading mechanism has been developed. Firstly, the reader can customise the reading mode and read either only the Old Russian text, or only the translation, or both simultaneously. Secondly, they can adjust the types of displayed commentaries, include or exclude morphological markup and accentological reconstruction, read the text either in a ‘modernized’ form, with numbered segments and modern punctuation, or in a form closer to how the text would have appeared in the burned manuscript of the 15th or 16th century. In the most complex cases where a sequence of symbols can have multiple interpretations (for example, it can be read as one, two, or three words), the reader may choose their preferred option, which changes the display of this sequence on the page and its translation (by default, the interpretation considered most preferable by the editors is selected). The publication of the project is planned for the first half of 2025.

Research target: Philology and Linguistics
Language: Russian
Full text
DOI
Text on another site
Keywords: древнерусская литератураСлово о полку Игоревеэлектронное изданиеdigital publishingOld Russian literaturedigital humanities projectsцифровые гуманитарные проекты
Publication based on the results of:
Russian Literature in the Social Dimension: SOCIOLIT – An Analytic Computation Platform (2023)
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