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  • Пространственные закономерности распространения трихинеллеза на юге Дальнего Востока России
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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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Пространственные закономерности распространения трихинеллеза на юге Дальнего Востока России

Медицинская паразитология и паразитарные болезни. 2022. № 4. С. 31–37.
Mironova V., Карабанова Е. А., Shartova N.

The registered cases of trichinosis among the population of four federal entities of the south of the Far East (Amur Region, Jewish Autonomous Region, Transbaikal Territory and Khabarovsk Territory) in 2000-2020 were considered. A spatial analysis, mapping and visualization was carried out on the basis of data derived from state reports of the Rospotrebnadzor on the number of cases and the frequency of their registration in the context of municipalities. A typological classification of territories has been built using the developed scoring and the identification of statistically significant "hot" and "cold" spots has been provided. It has been established that the incidence of trichinosis in humans is associated with both the consumption of meat of wild animals and domestic pigs, which, apparently, is associated with the Trichinella species prevailing in each specific area. Regions with stably recorded incidence have been identified, however, the establishment of more obvious spatial patterns of the spread of trichinosis is hindered by the insufficiency and incompleteness of published data, in particular, the lack or inaccessibility of information on the Trichinella species composition and the fragmentation of data on the results of epidemiological investigations. The tested method gives an idea of the levels of risk of infection with trichinosis for the population of the region and can be used for more in-depth studies in the future

Research target: Health Studies Earth Sciences
Language: Russian
Full text
DOI
Text on another site
Keywords: risk assessmentоценка рискаtrichinosisspatial statisticshot and cold spotsтрихинеллезыпространственная статистика«горячие» и «холодные» точки
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