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News
September 11, 2026
How to Assess Students Knowledge in the Age of AI
A researcher at HSE University has proposed a flowchart to help lecturers decide how to assess students who use artificial intelligence. It shows where the use of AI should be restricted and where it can be incorporated into the learning process. The article has been published in IT Professional.
September 9, 2026
‘Balkan Hospitality Opens Doors: Studying Dialects on the Verge of Extinction
You cannot study spoken dialects from books. Instead, you need to go to a village, seek out its elders, and earn the trust of local residents before you can record hours of spontaneous stories. This is how Natalia Muravleva, Associate Professor at the Faculty of Humanities, conducts her research. Her internship in Serbia continued her long-standing study of dialects spoken by Macedonian settlers. In this interview, she discusses how diaspora cultural centres help researchers reach informants, why native speakers need to be interviewed only in their own language (otherwise, as she puts it, they may 'break'), and how a single field season helped her finalise her monograph. She also shares warm memories of autumn in Belgrade and of colleagues with whom grammar can be discussed in three languages at once.
September 9, 2026
Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.

 

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Самооценка состояния здоровья взрослого населения Российской Федерации: анализ динамики за 2019–2024 гг.

Здравоохранение стран СНГ. 2025. Т. 1. № 1. С. 42–49.
Сахарова Г. М., Антонов Н. С., Stadnik N.

Introduction. Self-rated health is the most widely used indicator of health, taking into account all its components - physical and mental health, emotional, social and financial well-being. Although individuals rate their health based on their own perceptions, when aggregated, the indicator accurately represents the health of the entire population. The purpose of the study: based on self-rated health, to analyze dynamics in health among the adult population, including across age groups, in 2019-2024.

Materials and methods. Self-rated health among the adult population of the Russian Federation was analyzed using microdata of the Selective observation of population health conducted by Rosstat in 2019-2024. The respondents rated their health as “very good”, “good”, “fair”, “poor”, and “very poor”. The dynamics in indicators were estimated by calculating relative change.

Results. In 2019-2024, there were changes across all categories of health: the proportion of adults who rated their health as “very good” and “good” increased from 9.0% to 9.3% and 47.3% to 49.7%, respectively. The proportion of adults who rated their health as “fair”, “poor” and “very poor” decreased from 35.7% to 34.9%, from 6.9% to 5.5% and 0.9% to 0.5%, respectively. Overall, 56.3% of adults rated their health as “very good” and “good” in 2019, and 50% in 2020, versus 60% in 2024. Among people aged 15-39, more than 80% rated their health as “very good” and “good” versus 65% of people aged 40-49. In older age groups, this proportion was gradually decreasing.

Conclusion. Self-rated health is a comprehensive indicator reflecting the impact of various aspects of life on human health, including diseases, age-related changes, and can be used to assess population health, as well as effectiveness of public health programs.

Research target: Clinical Medicine Sociology (including Demography and Anthropology
Language: Russian
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Keywords: здоровьеhealthсамооценка здоровьяself-rated healthпандемия COVID-19COVID-19 pandemics
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