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June 5, 2026
Neural Network Maps as a Method for Constructing Mathematical Models
Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
June 5, 2026
‘In the Age of Technology, It Is Interesting to Look into the Past and Think about What We Can Take from It
Polina Tabakova decided to apply for a Philology degree at HSE in Nizhny Novgorod because she grew up in Mari El and did not want to move far away from the Russian forests. In an interview for the Young Scientists of HSE University project, she spoke about the genre of the campus novel, the existential drama of Kolobok, and a blackout version of Eugene Onegin.
June 5, 2026
HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.

 

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Conceptual Research Model of Metropolis Residents’ Pro-Environmental Behavior

Emerging Science Journal. 2025. Vol. 9. No. 3. P. 1285–1307.
Lukina A., Mkhitaryan S., Sidorchuk R. R., Petr Nevostruev, Lukina E.

The study develops a conceptual research model of demonstration of pro-environmental behavior (PEB) patterns of individuals living in the metropolis. This study aims to determine the impact of several factors (education, age, income, labor status, and individual’s social surroundings) on the PEB of metropolis residents and identify triggers that influence the activation of PEB. An online survey was conducted using the CAWI method on a quota sample of 1,502 respondents living in the metropolis of Moscow. The research hypotheses were tested using descriptive statistics, variance analysis and appropriate visualization tools. The study analyzed 28 patterns of PEB. It was found that people with higher education tend to exhibit a wide range of pro-environmental behavior types. Young people will be more active in a variety of PEB patterns, with the youngest (18–19-year-old group) showing the largest number of patterns 17 out of 28. People with above-average and average income are more actively engaged in PEB. Individual pro-environmental behavior depends most strongly on the pro-environmental behavior of individual’s social surroundings. The novelty of this study lies in identifying differences in the manifestation of metropolis residents’ pro-environmental behavior related to the purchase of goods, disposal of consumer waste, and their transport behavior.

Research target: Economics and Management
Language: English
DOI
Text on another site
Keywords: проэкологическое поведениеonline surveypro-environmental behaviorPEB PatternsBehavior of IndividualsMetropolis Residents’ BehaviorPEBпаттерны проэкологического поведенияонлайн-опросповедение индивидовповедение жителей мегаполисаПЭП
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