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News
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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When Sexism is Not a Problem: The Role of Perceived Intelligence in Willingness to Interact with Someone Who is Sexist

Journal of Social Psychology. 2021. Vol. 161. No. 3. P. 287–303.
Agadullina E.

Two studies examined factors that would influence people’s preferences for interaction with a perpetrator of sexism. In Study 1 (n = 348), participants preferred to interact (being friends or developing a relationship) with an intelligent person regardless of whether or not that person was sexist. Study 2 (n = 614) replicated this finding and confirmed that where a perpetrator had a high level of intelligence, people were more willing to interact with them, regardless of the perpetrator’s sex and the perceived commission or non-commission of sexist behavior. Moreover, Study 2 provides evidence that participants’ hostile sexism beliefs are a significant covariate of a willingness to interact with unintelligent women. The results are discussed in terms of their implications for the understanding of person perception.

Research target: Psychology
Priority areas: humanitarian
Language: English
Full text
DOI
Keywords: intelligencesexismhalo effectperson perception
Publication based on the results of:
«Умным все дозволено»: имплицитные теории интеллекта и оправдание предубеждений (2018)
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