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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'
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May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
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Особенности демографического развития Тувы: вклад миграции в демографический баланс

Новые исследования Тувы. 2021. № 4. С. 131–142.
Abylkalikov S.

The article highlights the features of the population dynamics in Tuva from the mid-20th century to the present taking different components of the demographic balance into account. The main research methods the author uses are the demographic balance equation, which allows us to estimate the ratio between natural and migration growth of the entire population and of urban and rural populations separately, as well as the analysis of lifelong population migrations on the basis of information about place of birth and place of residence. These methods are applied to study demographic processes in Tuva for the first time. The calculations are based on the official statistics — data from the population censuses of 1989, 2002 and 2010, current record of natural population movement and sample surveys.

There are underestimation of those who leave the territory of the Republic of Tuva and overestimation of return migration that “virtually” arises due to the expiration of the temporary registration period of those who have left it earlier. It has been found out that high rates of natural growth, especially in rural regions, are compensated by the migration outflow of the population from villages to cities and outside the Republic.

It is noted that the Republic has the closest migration relations with neighboring Siberian regions, but the significance of both metropolitan agglomerations — Moscow and St. Petersburg — is increasing. At the same time, there is a decrease in the share of those who have come to Tuva from other regions of Russia and an increase in the share of the natives who have left it. The data of the sample survey of the labor force allow us to identify the increasing importance of interregional labor migration for Tuva in recent years. Meanwhile the number of incoming and especially outgoing domestic labor migrants is noticeably lower than in neighboring regions.

The accumulation of a large error in closing the balance due to the long time that has passed since the previous population census and a change in the migration accounting methodology may lead to a significant reevaluation of the population of the Republic if we consider the results of the next population census.

Research target: Sociology (including Demography and Anthropology
Language: Russian
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Keywords: трудовая миграциявнутренняя миграцияперепись населенияpopulation censusinternal migration labor migrationмикроперепись населенияlifetime migrationdemographic balanceдемографический баланспожизненная миграцияТываTuvaТува
Publication based on the results of:
Демографические факторы развития человеческого потенциала в регионах России (2023)
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