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News
July 20, 2026
Scientists Create Open Dataset for Studying Concentration
A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.
July 20, 2026
‘Science Is Universal-It Knows No Borders
Fuad Aleskerov, Tenured Professor and Director of the International Centre of Decision Choice and Analysis at HSE University, together with his colleagues, has developed methods of network analysis in bibliometrics that have made it possible to identify patterns in the appearance and citation of publications in academic journals, as well as their influence on each other. When one or a number of studies are frequently cited by a wide range of journals, this is an indicator that the research is of high quality. By contrast, extensive cross-citation within a limited group of journals increases the likelihood of identifying a network of predatory publications.
July 20, 2026
Scientists Propose Method for More Efficient Resource Use in Machine Learning
An international group of researchers, including mathematicians from the AI and Digital Science Institute at the HSE Faculty of Computer Science, has provided a theoretical justification for a simple and computationally efficient method of estimating uncertainty in Stochastic Gradient Descent (SGD). The paper has been published on the scientific preprint server arXiv.org and presented at AISTATS 2026.

 

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1D Nanomaterials in Fe-Group Metals Obtained by Synthesis in the Pores of Polymer Templates: Correlation of Structure, Magnetic, and Transport Properties

Physica Status Solidi (A) Applications and Materials. 2021. Vol. 219. No. 3. Article 2100538.
Panina L., Dmitri L. Zagorskiy, Shymskaya A., Ilia M. Doludenko, Evstigneeva S., Melnikova P., Khairetdinova D., Lukkareva S., Gilimyanova A.

1D cylindrical magnetic nanostructures (FeNi, FeCo, FeCoP) of complex topology
such as nanowires (NWs), nanotubes (NTs), multilayered nanowires, and core–
shell structures are discussed from the perspective of engineering a wide variety of
magnetic materials from hard to semihard to soft. Most of recent data are given for
the materials synthesized in the pores of polymer ion-track membranes, which
makes it possible to tune systematically the geometrical parameters, morphology,
and composition. The key properties including crystal and micromagnetic structure,
magnetic anisotropy, and coercivity are analyzed. Co-based NWs with uniform
morphology demonstrate coercivity of more than 10 kOe due to the combination of
crystalline and shape anisotropies. In the case of NTs, the demagnetizing effect is
reduced owing to a helical arrangement of the magnetization, which leads to low
values of coercivity and remanence magnetization. Varying the geometrical
parameters of multilayered NWs, the alternating soft and semihard magnetic layers
can be made within a single nanowire, which is important for spin-valve magne-
toresistance. Au-coated ferromagnetic nanostructures are biocompatible and can be
used to enhance optical absorption. Ni@Au NTs used as substrates for Raman
spectroscopy demonstrate the enhancement factor of the order of 104
. Some
aspects related to applications of 1D magnets are briefl y overviewed.

Research target: Nanotechnologies Physics
Language: English
DOI
Keywords: трековые мембраныматричный синтезmatrix synthesisMagnetic nanowiresмагнитные нанопроволокиTrack etched membranes
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