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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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Discourses of public breastfeeding on Russophone social media. A discursive-material analysis of VKontakte discussions

.
Semykina K., Dorofeeva O.

This paper draws on the discursive-material analysis framework to analyse discussions about public breastfeeding on VKontakte, a popular social media platform in Eastern Europe and Asia. The study zooms in on two types of discussion sites: groups for mothers and e-bile groups dedicated to mocking mothers. To analyse this discourse and social media practices relevant to it, posts and comments in selected groups devoted to the topic of public breastfeeding were collected through the VKontakte API. Drawing on the framework of discursive-material analysis, we identified the major nodal points of the discourse on public breastfeeding: naturalness, aesthetics, intimacy, social norms, and needs of the child. These nodal points constitute the core of the discursive structure, stabilising the discourse on public breastfeeding. We also analyse how social media features, such as platform affordances and user practices, contribute to shaping the digital discourse on public breastfeeding. We focus specifically on recontextualisation and engaging in conflict in the digital context as key practices. The chapter concludes with a discussion of the social and digital contexts constructing the issue of public breastfeeding.

Language: English
Keywords: discourse social mediapublic breastfeeding
Publication based on the results of:
Russians’ Daily Social Practices under Exogenous Shocks (2024)

In book

Discourse in the Digital Age. Social Media, Power, and Society
NY: Routledge, 2023.
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