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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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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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Synthesis and Properties of a Composite Material Based on Polyethylene, Bismuth Oxide, and Boron Carbide

Inorganic Materials: Applied Research. 2026. Vol. 17. No. 2. P. 276–282.
Pavlenko V. I., Bondarenko G.G., Cherkashina N. I., Romanyuk D. S.

A composite material based on polyethylene, boron carbide (B4C), and bismuth oxide (Bi2O3) is
synthesized by the method of joint cryogenic milling of all components in liquid nitrogen environment followed
by pressing. The effect of cryogenic milling on the distribution of fillers in a composite is studied and
the prospects of using this method are assessed in comparison with traditional methods of mixing components
of polymer composites. The structure and properties of the finished composite are studied using scanning
electron microscopy (SEM), IR Fourier spectroscopy, and X-ray phase analysis. The strength characteristics
of a composite material with different filler contents are determined. It is shown that the optimal
composition is one containing 55 wt % of polyethylene, 5 wt % of boron carbide, and 40 wt % of bismuth
oxide, which provides a good balance of strength. Cryogenic milling results in a uniform distribution of filler
particles in the matrix and improves strength characteristics of the material. The composite is stable up to
250°C and has high thermal properties, which makes it to be promising for use in space constructions requiring
materials with high heat resistance and radiation protection.

Research target: Materials Technologies
Language: English
Full text
DOI
Keywords: синтезsynthesisсвойстваpropertiesкомпозитный материал composite material
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