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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.
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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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Долгосрочный прогноз компенсаторной миграции в России

Журнал Новой экономической ассоциации. 2023. № 1(58). С. 48–64.
Yumaguzin V., Vinnik M. V.

The population of Russia was declining since 2018 due to the growth of natural loss and the uneven dynamics of net migration, which only partially compensated for it. In the short term, even the most favorable scenario of Russia’s demographic development, which provides for high levels of fertility, life expectancy and migration, leads to a decrease in the population from the current 146.2 to 145.2 million persons in 2026, and only after that point, a growth can be expected. According to the medium and low options, the population will decrease to 137.5 and 84.4 million persons respectively by the end of the century. This makes necessary to calculate a level of the replacement migration, which would compensate the natural decline and maintain the current population of Russia. The cohort- component method was used in forecasting, the population as of 01.01.2021 was taken as the base. Depending on various scenarios of fertility and mortality, the level of annual replacement migration growth in 2021–2023 should correspond to 460–1200 thousand persons, which is 2–6 times higher than suggested by the average, most realistic, migration scenario. The value is also 1.5–4.5 times higher than in high migration scenario. After that, the urgency for replacement migration decreases and from the 2040s, according to the average variant, the net migration will correspond to the upper, optimistic, migration scenario (450–500 thousand persons), which implies a greater probability of achieving it. In 2077, the level of replacement migration intersects with the average scenario of net migration (250 thousand persons), and in the period 2084–2100 corresponds to the lower scenario (60–70 thousand persons). According to the high variant, the level of replacement migration is rapidly decreasing due to a signifi cant increase in fertility and life expectancy and since the late 2030s even in the case of migration decline the population would not shrink. With negative trends of natural movement in the low variant, the level of required replacement migration throughout the forecast period is extremely high and unlikely, 1–1.2 million persons annually, which indicates the impossibility of stabilizing the population in this variant. Higher levels of immigration make possible to recoup the growth of the demographic burden only in the medium term, subsequently, the aging of the arrived contingents of migrants leads to an increase in the demographic burden of the elderly. Thus, to preserve the population, it is necessary to fi nd a balance between relatively easy-to-manage migration fl ows and solving fundamental issues in the fi eld of reducing mortality and creating favorable conditions for the birth of the desired number of children in families.

Research target: Sociology (including Demography and Anthropology Economics and Management
Language: Russian
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Keywords: численность населенияpopulation sizeзамещающая миграцияdemographic burdenдемографическая нагрузкадемографический прогнозdemographic forecastcompensatory migrationreplacement migrationкомпенсаторная миграция
Publication based on the results of:
Spatial measurement of demographic dynamics in Russia: long-term and short-term changes in the diversity of human reproduction regimes, migration and demographic structures of the population at the regional level (2022)
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