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July 1, 2026
Scientists Discover Why Europium 'Misbehaves'
Europium is a rare-earth metal responsible for the pure red glow in displays and other luminescent materials. For a long time, however, it refused to emit light when surrounded by certain organic molecules known as acylpyrazolone ligands. Chemists have now uncovered the reason: in europium complexes with these ligands, a 'black window' appears—a charge-transfer state in which the energy absorbed by the ligand is dissipated as heat rather than emitted as light. Understanding this mechanism opens the way to designing more efficient red-emitting materials for displays, fluorescent thermometers, and chemical sensors. The results have been published in Dalton Transactions.
June 30, 2026
HSE Economists Reveal How the Wage Gap Emerges Among Vocational School Graduates
HSE researchers examined the careers of 600,000 graduates of Russian secondary vocational education programmes and found that at the start of their careers, the gender wage gap reaches 23%, doubling after three years. This disparity is largely due to male and female students choosing different occupations when enrolling in vocational schools. These were the findings made by Sergey Roshchin, Natalya Yemelina, and Ksenia Rozhkova from of the HSE Faculty of Economic Sciences. The article has been published in Educational Studies.
June 25, 2026
HSE Researchers Make Aldehydes Perform Dual Function
Chemists from HSE University have discovered a way to carry out a reductive addition reaction without using an external reducing agent. Instead, the required 'resource' is supplied by the aldehyde itself, one of the reaction participants. This approach helps prevent unwanted side reactions, reduces toxicity, and simplifies the production and synthesis of organic molecules, including those used in the manufacture of medicines. The study has been published in Journal of Catalysis.

 

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Educating Engineers for Future Industrial Revolutions. ICL 2020, vol 1. Advances in Intelligent Systems and Computing

Vol. 1328. Springer, 2021.
Academic editor: M. E. Auer, R. Tiia

This book contains papers in the fields of collaborative learning, new learning models and applications, project-based learning, game-based education, educational virtual environments, computer-aided language learning (CALL) and teaching best practices.
We are currently witnessing a significant transformation in the development of education and especially post-secondary education. To face these challenges, higher education has to find innovative ways to quickly respond to these new needs. There is also pressure by the new situation in regard to the Covid pandemic.
These were the aims connected with the 23rd International Conference on Interactive Collaborative Learning (ICL2020), which was held online by University of Technology Tallinn, Estonia from 23 to 25 September 2020. 
Since its beginning in 1998, this conference is devoted to new approaches in learning with a focus on collaborative learning. Nowadays the ICL conferences are a forum of the exchange of relevant trends and research results as well as the presentation of practical experiences in Learning and Engineering Pedagogy. In this way, we try to bridge the gap between ‘pure’ scientific research and the everyday work of educators. 
Interested readership includes policymakers, academics, educators, researchers in pedagogy and learning theory, school teachers, learning industry, further and continuing education lecturers, etc.

Chapters
The Lessons of Forced Distance Learning: Software Engineering Approach in the Gap of Generations of Educational Software
Beresneva E., Gordenko M., Maksimenkova O. V. et al., , in: Educating Engineers for Future Industrial Revolutions. ICL 2020, vol 1. Advances in Intelligent Systems and ComputingVol. 1328.: Springer, 2021. P. 54–65.
Added: October 9, 2020
Priority areas: IT and mathematics
Language: English
DOI
Text on another site
Keywords: collaborative learning lifelong learningknowledge management research
Educating Engineers for Future Industrial Revolutions. ICL 2020, vol 1. Advances in Intelligent Systems and Computing
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Hessian-based lightweight neural network for brain vessel segmentation on a minimal training dataset
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