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April 28, 2026
Scientists Develop Algorithm for Accurate Financial Time Series Forecasting
Researchers at the HSE Faculty of Computer Science benchmarked more than 200,000 model configurations for predicting financial asset prices and realised volatility, showing that performance can be improved by filtering out noise at specific frequencies in advance. This technique increased accuracy in 65% of cases. The authors also developed their own algorithm, which achieves accuracy comparable to that of the best models while requiring less computational power. The study has been published in Applied Soft Computing.
April 27, 2026
Fair Division: How Mathematics Helps to Divide the Indivisible
How can items be allocated among participants so that no one feels short-changed? Alexander Karpov, Assistant Professor at the Faculty of Economic Sciences, and his Singaporean colleague, Prof. Warut Suksompong, set out to find a mathematical answer to this question. In this interview, they discuss how a model of rational preferences is constructed, why one cannot rely on a simple sum of values, and where an algorithm that asks a minimal number of questions can be useful.
April 24, 2026
Electronics of the Future: Why Superconductors and Spintronics Work Together
It was once believed that superconductivity and magnetism avoided each other like the devil avoids holy water. However, modern nanostructures prove the opposite. A Russian theoretical physicist and Indian experimentalists have joined forces to create the electronics of the future—free from energy losses. Nataliya Pugach, Professor at the School of Electronic Engineering at HSE MIEM and Leading Research Fellow at the Quantum Nanoelectronics Laboratory, explains how a long-standing acquaintance in Cambridge grew into a mirror laboratory project with the Indian Institute of Technology Bombay (IIT Bombay), how superconducting spintronics works, and what surprises a researcher in India beyond the university campus.

 

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Altered neural synchronization in response to 2 Hz amplitude-modulated tones in the auditory cortex of children with Autism Spectrum Disorder: An MEG study

International Journal of Psychophysiology. 2024. Vol. 203. Article 112405.
Samoylov I., Arcara G., Buyanova I., Davydova E., Pereverzeva D., Sorokin A., Tyushkevich S., Mamokhina U., Danilina K., Dragoy O., Arutiunian V.

Objective: Some studies have hypothesized that atypical neural synchronization at the delta frequency band in the auditory cortex is associated with phonological and language skills in children with Autism Spectrum Disorder (ASD), but it is still poorly understood. This study investigated this neural activity and addressed the relationships between auditory response and behavioral measures of children with ASD. Methods: We used magnetoencephalography and individual brain models to investigate 2 Hz Auditory Steady-State Response (ASSR) in 20 primary-school-aged children with ASD and 20 age-matched typically developing (TD) controls. Results: First, we found a between-group difference in the localization of the auditory response, so as the topology of 2 Hz ASSR was more superior and posterior in TD children when comparing to children with ASD. Second, the power of 2 Hz ASSR was reduced in the ASD group. Finally, we observed a significant association between the amplitude of neural response and language skills in children with ASD. Conclusions: The study provided the evidence of reduced neural response in children with ASD and its relation to language skills. Significance: These findings may inform future interventions targeting auditory and language impairments in ASD population.

Research target: Psychology Philology and Linguistics
Language: English
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DOI
Text on another site
Keywords: Magnetoencephalography (MEG)магнитоэнцефалография (МЭГ)расстройства аутистического спектраAutism Spectrum Disorder (ASD)Auditory Steady-State Response (ASSR)
Publication based on the results of:
Neuroanatomical foundations of language disorders in children and adults: structural and functional correlates (2024)
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