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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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Обсуждение генетики в социальных медиа: анализ представлений пользователей YouTube о науке и технологиях

Философия науки и техники. 2024. № 2. С. 47–60.
Dolgov A.

The article is devoted to the study of social media users’ views on genetics and genetic tech­nologies. The study of this issue is important because the development of genetic technologies in Russia is considered one of the priority tasks, and the implementation of innovations largely depends on the attitude towards it in society. Fundamental scientific knowledge about genetics has begun to spread beyond scientific laboratories and institutes, and new non-professional representations of corporeality, health and illness, ancestry, identity, and kinship have been ac­tively promoted. So-called direct-to-consumer genomics – commercial DNA testing services – is also growing in popularity. In order to understand what representations of genetics are present in Russian social media, we analyzed three videos posted on YouTube, a popular video hosting site, as well as user comments under them. The selected videos demonstrate three dif­ferent research cases: 1) a popularization speech of a scientist (interview) talking about gene­tics; 2) a journalistic video about the use of genetic technologies in Russia; 3) a story of a lay­man (blogger) about his personal experience of using a DNA test. Using thematic analysis of comments to these videos, the main themes were formed, demonstrating: what non-specia­lists understand by genetics; why, from their point of view, genetic tests are needed; what young people are interested in genetic technologies and what they see as dangerous in them. The conclusions formulate the main problems that may face the development of genetic tech­nologies in Russia at the level of their acceptance by society.

Research target: Sociology (including Demography and Anthropology
Language: Russian
DOI
Text on another site
Keywords: YouTubeгенетикагенетические технологии
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