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News
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.
September 7, 2026
Biologists Discover 'Molecular Fingerprint' of Preeclampsia
Researchers at HSE University employed a new method to model hypoxia in placental cells during pregnancies complicated by preeclampsia and identified molecular markers of tissue hypoxia. Since hypoxia is one of the key mechanisms underlying preeclampsia, these findings are important for a more accurate and timely diagnosis of the disease and for the development of effective treatment methods. The paper has been published in Placenta.

 

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Методика создания комплексной экономико-математической модели массовой оценки стоимости объектов недвижимости на примере квартирного рынка города Перми

Вестник Пермского университета. Серия: Экономика. 2016. № 2(29). С. 54–69.
Yasnitsky L., Ясницкий В. Л.

Currently, there are a number of economic and mathematical models designed for mass appraisal of real estate, tailored to their construction and performance properties, but taking no account of the evolving macroeconomic situation in the country and the world. The disadvantage of such static models is their rapid obsolescence, the need for constant updating, and unsuitability for medium-term forecasting. On the other hand, there are dynamic models that take into account the current macroeconomic situation; however, they are intended for predicting and studying the overall price situation in the real estate market, but not for mass appraisal of real estate with their variety of construction and performance properties. In this regard, the aim of this research is to develop methods of creating complex models having the properties of the static and dynamic models mentioned, i.e., taking into account construction and performance properties, as well as changing macroeconomic situation in the country and in the world. Methods and models are developed with the use of neural network technology basing on the example of the residential real estate in Perm and on statistical information of the market over the period from 2005 to 2015. In addition to its primary purpose – mass appraisal of apartments, the model is suitable for medium-term forecasting and identification of the real estate market regularities. For example, it has been found out that the price of Perm apartments as a whole tends to increase due to the rise of the oil prices, but the dependence of the cost of apartments on the price of oil is stable and direct only when the latter exceeds $ 60 – 80 per barrel. In case the volume of mortgage lending rises, the price of apartments in Perm will increase. However, the growth rate of the cost of elite four-room apartments will begin to slow down, with an increase in mortgage lending volumes above 2400 – 2700 million rubles, whereas this effect will not be apparent for cheap one- and two-bedroom apartments. Further housing construction in Perm to 1,400 sq m in the short term will not cause a noticeable change in residential property prices in Perm, which suggests that the market is still far from saturation.

Research target: Computer Science Economics and Management
Priority areas: economics state and public administration IT and mathematics
Language: Russian
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Keywords: рынок недвижимостинейронная сетьmass appraisalмассовая оценкаreal estate marketartificial neural networksmacroeconomic indicators экономическое прогнозированиеanalytical forecasting
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