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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.
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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.
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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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Секреция микромицетами протеиназ с активностью, подобной активности белков системы гемостаза

Вестник Московского университета. Серия 16: Биология. 2020. Т. 75. № 1. С. 37–42.
Лукьянова А. А., Корниенко Е. И., Виган П. А., Крейер В. Г., Кураков А. В., Osmolovsky A.

Using the chromogenic peptide substrates, proteolytic activity against proteins of the hemostasis system was studied in 9 micromycetes belonging to different ecological-trophic groups: phyto-, nemato-, myco- and entomopathogens, as well as human pathogens. It is shown that the investigated micromycetes secrete proteases with broad substrate specificity, but among them there are producers with pronounced both plasmin-like and urokinase (Arthrobotrys longa 1, Sarocladium strictum 203) also as TAP-like (Purpureocillium lilacinum k1) activity. The most active producer of proteases with fibrinolytic and activator activity to plasminogen activity was S. strictum 203 micromycete. The activity of proteinases formed by S. strictum 203 is about 50% of the fibrinolytic activity of plasminogen, which makes it a promising producer of fibrinolytic enzymes.

Language: Russian
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Keywords: протеиназы микромицетовфибринолитические ферментытромболитические средстваплазминоподобная активностьактиваторы плазминогенахромогенные пептидные субстраты
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