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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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The Impact of Uncertainty in Economic Policy on the Load Capacity Factors in China and the United States (US): New Evidence from Novel Fourier Bootstrap ARDL Approach

Journal of Sustainability Research. 2025. Vol. 7. No. 1. Article e250002.
Kilinc-Ata N., Camkaya S., Akca M., Topal S.

The body of research on how uncertainty in economic policy affects load capacity factors has expanded quickly in recent years as concerns over the possible detrimental consequences of policy uncertainty on environmental sustainability are growing among scholars and policymakers. In this context, the primary aim of this research is to use annual data from the United States and China collected between 1985 and 2018 to examine the short- and long-term impacts of economic policy uncertainty on the load capacity factor. The study employed the Fourier Autoregressive Distributed Lag method to investigate the long- and shortterm effects of energy intensity and economic growth while the FourierToda-Yamamoto causality approach was utilized to assess the causal relationship between the variables. Findings show that whereas economic policy uncertainty temporarily improves environmental quality in China, it only has a long-term detrimental effect on environmental quality in the United States. Additionally, the findings demonstrate that energy intensity in both nations dramatically lowers environmental quality. Furthermore, there is also a causal relationship between economic policy uncertainty and economic growth in the United States along with economic growth and load capacity factor and energy intensity in China. These unidirectional causal relationships demonstrate the existence of a causal relationship. Effective policies should be developed to enhance environmental quality in China and the United States, taking into consideration the findings.

Research target: Economics and Management
Language: English
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Keywords: Economic policy uncertaintySustainabilityEnvironmental qualityClimate change
Publication based on the results of:
Trends and factors of sustainable science and technology development (2025)
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