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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
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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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ESG Transformation in the Largest Emerging Capital Market of China. A Literature Review

Journal of Corporate Finance Research. 2023. Vol. 17. No. 4. P. 132–150.
Wu Y.

The paper provides a scholarly examination of academic studies of the ESG landscape in China through a systematic literature review with a major focus on the nature and intensity of regulatory guidelines and policies. While many studies indicate positive effects of Chinese ESG policies on corporate ESG performance and investment, they primarily focus on environmental aspects. This analysis of China’s ESG rating system exposes relationships between ESG ratings, corporate performance, financing costs, including both debt and equity financing. The research on equity financing costs is inconsistent and limited in scope, indicating the need for additional investigation. Of the factors influencing ESG, the past year has seen a surge in research on the topic of digital transformation and ESG performance. Most studies demonstrate that
digital transformation contributes to ESG performance, and a few suggest that digital transformation positively moderates the effect of ESG performance on firm value enhancement. This review discusses the growth of ESG investment in China, focusing on pension funds, commercial banks, and ESG funds, as well as investor preferences. Despite the growing role of ESG in investment decisions, extant research is largely theoretical, underscoring the need for more empirical and quantitative studies. The research identifies gaps in studies devoted to ESG investment, including the need for comprehensive studies on the impact of ESG across various insurance types and industries, and the development of effective ESG quality assessment methods. This review is among the first academic resources summarizing and integrating various studies, and highlighting areas for future ESG research in China.

Language: English
DOI
Text on another site
Keywords: corporate performanceDigital Finance ChinaESG ratingsDigital transformation (DT)ESG DevelopmentESG InvestmentFinancing CostsPolicy response
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