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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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IoT Monitoring of Urban Tree Ecosystem Services: Possibilities and Challenges

Forests. 2020. No. 11. Article 775.
Matasov V., Belelli L., Yaroslavtsev A., Sala G., Fareeva O., Seregin I., Castaldi S., Vasenev V., Valentini R.

Urban green infrastructure plays an increasingly significant role in sustainable urban development planning as it provides important regulating and cultural ecosystem services. Monitoring of such dynamic and complex systems requires technological solutions which provide easy data collection, processing, and utilization at affordable costs. To meet these challenges a pilot study was conducted using a network of wireless, low cost, and multiparameter monitoring devices, which operate using Internet of Things (IoT) technology, to provide real-time monitoring of regulatory ecosystem services in the form of meaningful indicators for both human health and environmental policies. The pilot study was set in a green area situated in the center of Moscow, which is exposed to the heat island effect as well as high levels of anthropogenic pressure. Sixteen IoT devices were installed on individual trees to monitor their ecophysiological parameters from 1 July to 31 November 2019 with a time resolution of 1.5 h. These parameters were used as input variables to quantify indicators of ecosystem services related to climate, air quality, and water regulation. Our results showed that the average tree in the study area during the investigated period reduced extreme heat by 2 °C via shading, cooled the surrounding area by transferring 2167 ± 181 KWh of incoming solar energy into latent heat, transpired 137 ± 49 mm of water, sequestered 8.61 ± 1.25 kg of atmospheric carbon, and removed 5.3 ± 0.8 kg of particulate matter (PM10). The values of the monitored processes varied spatially and temporally when considering different tree species (up to five to ten times), local environmental conditions, and seasonal weather. Thus, it is important to use real-time monitoring data to deepen understandings of the processes of urban forests. There is a new opportunity of applying IoT technology not only to measure trees functionality through fluxes of water and carbon, but also to establish a smart urban green infrastructure operational system for management.

Research target: Earth Sciences Biology Effective Natural Resource Management
Language: English
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DOI
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Keywords: smart citiessustainabilityecological engineeringreal-time monitoringtreetalkerurban forestsecosystem services indicators
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