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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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Региональные особенности реформы сиротских учреждений в России

Журнал социологии и социальной антропологии. 2018. Т. 21. № 3. С. 115–139.
Tarasenko A.

The analysis is focused on the particularities of the reform of social provision for children left without parental care in Russian regions. Theoretically, the paper considers the reform as a process of deinstitutionalization, implying the transformation of the scope and the content of the activity of public and non-state organisations. The key goal is to identify conditions of the inertia of the deinstitutionalization. The first part of the article is devoted to the literature observation to formulate assumptions about factors that impact or impede deinstitutionalization of child’s care. Three assumptions are formulated about the influence of the social-economic development, conservative or innovative ideology and the activity of the nonprofit organisations and associations of citizens. The second part of the article works with the statistical data on the scope and the positive dynamic of the reduction of state providers and particularities of the attraction of non-state providers. The empirical analysis shows the scope of retrenchment of the institutional care in various Russian regions and particularities of non-state activity (nonprofit organisations and private companies). The analysis enabled to identify three main types of nonprofit organisations involved as service providers: SOS villages, associations of foster families and civic organisations affiliated with the Russian Orthodox Church. In the third part of the article, the detailed empirical analysis of two Russian regions with the largest scope of institutionalized care for children (Ulianovskaia oblast’ and Amurskaia oblast’) has been conducted. On the basis of these two regional cases assumptions about the social-economic and political factors have been examined.

Research target: Political Science, International Relations, and Public Administration
Priority areas: sociology
Language: Russian
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Keywords: социальная политикаsocial policy реформаsocial reforms in Russiaresidential care for childrenсиротские учреждения
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