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News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Тренировки представления движения и интерфейс мозг-компьютер в когнитивной реабилитации

Журнал неврологии и психиатрии им. С.С. Корсакова. 2025. Т. 125. № 11. С. 27–35.
Лабор В. В., Mokienko O., Черкасова А. Н., Иконникова Е. С., Люкманов Р. Х., Супонева Н. А.
Research target: Medical Technologies Clinical Medicine Psychology Computer Science
Language: Russian
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DOI
Text on another site
Keywords: нейрореабилитацияcognitive functionкогнитивные функцииneurorehabilitationmotor imagerybrain-computer interfaceинтерфейс мозг-компьютерпредставление движения
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ИНФОРМАЦИОННЫЕ ТЕХНОЛОГИИ И ТЕХНИЧЕСКИЕ СРЕДСТВА УПРАВЛЕНИЯ (ICCT-2024)
М.: Институт проблем управления им. В.А. Трапезникова РАН, 2024.
В сборник вошли материалы VIII Международной научной конференции «Информационные технологии и технические средства управления» (ICCT-2024). На конференции были рассмотрены вопросы, касающиеся перспектив развития научного приборостроения в телекоммуникационных и управляющих системах, биомедицинской информатики, аппаратного и программного обеспечения информационнокоммуникационных систем, надежности, диагностики и неразрушающего контроля, систем управления и автоматизации, цифровых экосистем, управления производством и логистикой, методов математического ...
Added: May 27, 2026
Non-linear in-band interference cancellation on base of conjugate gradients method
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This paper investigates one possible solution to the problem of self-interference cancellation (SIC) arising in the design of in-band full-duplex (IBFD) communication systems. Self-interference cancellation is performed in the digital domain using multilayer nonlinear models adapted via gradient-based optimization. The presence of local minima and saddle points during the adaptation of multilayer models limits the ...
Added: May 26, 2026
Heritability of Functional Literacy: Evidence from a Classical Twin Design
Kolachev N., Kovaleva G., Behavior Genetics 2026
Functional literacy—the ability to apply reading, mathematical, and scientific knowledge in authentic contexts as operationalized by the PISA framework—is a key predictor of educational attainment, labour-market outcomes, and economic growth. Despite extensive behavioral-genetic research on cognitive ability, the heritability of competency-based literacy measures remains largely unexamined, particularly outside Western populations. The present study addresses this ...
Added: May 26, 2026
Comparative Study of Training Methods and Architectures of Echo State Networks
Androsov I., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 3 P. 87–114
This paper examines echo state networks (ESNs), one of the most prevalent approaches to implementing reservoir computing. An ESN consists of a recurrent neural network with fixed (untrained) weights and a readout layer that is typically linear and trainable. This approach enables the creation of energyefficient and computationally efficient neural networks capable of real-time learning. However, since ...
Added: May 26, 2026
How virtual urban green spaces influence stress and risk-taking
Dorri Sedeh S., Kosonogov V., Kerimova N. et al., Frontiers in Psychology 2026 Vol. 17 Article 1710257
Introduction:  As cities continue to grow, access to natural environments is becoming more limited, contributing to increased stress levels in urban populations. Panoramic 360° videos provide a creative and scalable means of simulating natural environments, potentially reducing stress in city residents under controlled settings. Here, we examined whether short immersive experiences in different urban environments support ...
Added: May 25, 2026
Novelty, Category and Orientation Tuning for Printed Characters: A Magnetoencephalography Study with Fast Periodic Visual Stimulation
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Letter recognition is assumed to involve several levels of analysis, including coarse tuning for category and novelty and more fine tuning for specific features, related to letter orientation. We employed an oddball fast periodic visual stimulation (FPVS) paradigm with magnetoencephalography (Elekta VectorView, 306 sensors) to study neural discrimination responses in the source space. Using contrasts ...
Added: May 24, 2026
Рефакторинг исходного кода на основе LLM и расширения UML
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В статье представлен метод рефакторинга исходного кода на основе интеграции большой языковой модели (LLM) и расширенной UML-модели программного кода. Предложенный подход позволяет выявлять проблемные участки кода с использованием функций тревожности и структурных метрик классов, а затем выполнять автоматизированный рефакторинг. Ключевой особенностью метода является использование LLM для генерации формальных спецификаций на языке OCL (Object Constraint Language), ...
Added: May 24, 2026
Coping with AI errors with provable guarantees
Tyukin I., Tyukina T., van Helden D. P. et al., Information Sciences 2024 Vol. 678 Article 120856
AI errors pose a significant challenge, hindering real-world applications. This work introduces a novel approach to cope with AI errors using weakly supervised error correctors that guarantee a specific level of error reduction. Our correctors have low computational cost and can be used to decide whether to abstain from making an unsafe classification. We provide ...
Added: May 23, 2026
Overcoming the Curse of Dimensionality with Synolitic AI
Zaikin A., Sviridov I., Sosedka A. et al., Technologies 2026 Vol. 14 No. 2 Article 84
High-dimensional tabular data are common in biomedical and clinical research, yet conventional machine learning methods often struggle in such settings due to data scarcity, feature redundancy, and limited generalization. In this study, we systematically evaluate Synolitic Graph Neural Networks (SGNNs), a framework that transforms high-dimensional samples into sample-specific graphs by training ensembles of low-dimensional pairwise ...
Added: May 23, 2026
Stable On-the-Fly Learning for Dynamic Neural Networks With Delayed Inputs
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Added: May 22, 2026
Опыт применения сетевого анализа (SNA) в историческом нарративе полисубъектного региона (на примере валлийской хроники Brut y Tywysogyon)
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Added: May 22, 2026
Embodied language and early motor restriction: evidence from children with obstetric brachial plexus palsy and arthrogryposis
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Embodied and embedded cognition (EEC) theory proposes that language and cognitive development emerge from bodily interactions with the environment, yet empirical tests of this claim in clinical developmental populations remain rare. This mini-review synthesizes behavioral, electrophysiological, and structural neuroimaging evidence from children with serious early motor disorders—obstetric brachial plexus palsy and arthrogryposis multiplex congenita—which restrict ...
Added: May 20, 2026
Влияние стресс-факторов городской среды на психическое здоровье: обзор зарубежных исследований
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Context and relevance. The problem of the impact of urban stress factors on mental health is becoming increasingly relevant in the context of urbanization. Living in cities is accompanied by increased psychophysiological stress, which leads to an increase in the prevalence of mental disorders among urban residents. Objective. The purpose of the article is to ...
Added: May 19, 2026
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A fast simulation of the detector response is a vital task in high-energy physics (HEP). Traditional Monte-Carlo methods form the backbone of modern particle physics simulation software but are computationally expensive. We present a machine-learning-based approach to fast simulation of the Focusing Aerogel Ring Imaging Cherenkov (FARICH) detector response. Given a particle track and momentum, ...
Added: May 19, 2026
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Added: May 19, 2026
Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 3: System Demonstrations)
Rabat: Association for Computational Linguistics, 2026.
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Added: May 19, 2026
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Motor imagery (MI) allows individuals to mentally simulate movements without execution, engaging neural pathways that overlap with those used during real actions. However, how imagery perspective influences corticospinal excitability across different effectors remains unclear. Using neuronavigated transcranial magnetic stimulation (TMS), we compared kinesthetic (KMI), first-person visual (VMI-1PP), and third-person visual (VMI-3PP) imagery of elbow flexion-extension ...
Added: May 5, 2026
Интерфейсы мозг–компьютер для восстановления движений руки после инсульта: текущий статус и перспективы разработок (обзор)
Mokienko O., Люкманов Р. Х., Бобров П. Д. et al., Современные технологии в медицине 2023 Т. 15 № 6 С. 63–73
Brain–computer interfaces (BCIs) are a group of technologies that allow mental training with feedback for post-stroke motor recovery. Varieties of these technologies have been studied in numerous clinical trials for more than 10 years, and their construct and software are constantly being improved. Despite the positive treatment results and the availability of registered medical devices, ...
Added: March 19, 2026
Инвазивные интерфейсы мозг–компьютер: 25 лет клинических испытаний, научные и практические вопросы
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A brain-computer interface (BCI) is a system that measures brain activity and converts it in real-time into functionally useful outputs to replace, restore, enhance, supplement, and/or improve the natural outputs of the brain. In invasive BCIs, electrodes are placed intracranially for more accurate and faster data exchange between the brain and external devices. The primary ...
Added: March 18, 2026
Влияние выбора стратегии формирования обучающего множества и способа фильтрации на эффективность ИМК, основанного на спектрометрии в ближнем инфракрасном диапазоне
Исаев М. Р., Бобров П. Д., Журнал высшей нервной деятельности им. И.П. Павлова 2022 Т. 72 № 5 С. 728–738
The paper proposes methods for brain–computer interface, based on the hemodynamic activity registration using near–infrared spectroscopy (NIRS) and adapted for using in the movement disorders rehabilitation. Methods include a filtration adapted to the instructions frequency, step by step classification of the rest state and active tasks, as well as training of the interface classifier on ...
Added: March 18, 2026
Интерфейс мозг–компьютер, основанный на спектроскопии в ближней инфракрасной области, в двигательной реабилитации после инсульта: описание серии случаев
Люкманов Р. Х., Исаев М. Р., Mokienko O. et al., Анналы клинической и экспериментальной неврологии 2023 Т. 17 № 4 С. 82–88
Introduction. Non-invasive brain–computer interfaces (BCIs) enable feedback motor imagery [MI] training in neurological patients to support their motor rehabilitation. Nowadays, the use of BCIs based on functional near-infrared spectroscopy (fNIRS) for motor rehabilitation is yet to be investigated. Objective: To evaluate the potential fNIRS BCI use in hand MI training for comprehensive post-stroke rehabilitation. Materials ...
Added: March 18, 2026
Потенциал терапевтического применения спектроскопии в ближней инфракрасной области после инсульта (обзор)
Mokienko O., Современные технологии в медицине 2025 Т. 17 № 2 С. 73–85
The advancement of novel technologies for the rehabilitation of post-stroke patients represents a significant challenge for a range of interdisciplinary fields. Near-infrared spectroscopy (NIRS) is an optical neuroimaging technique based on recording local hemodynamic changes at the cerebral cortex level. The technology is typically employed in post-stroke patients for diagnostic purposes, including the assessment of ...
Added: March 18, 2026
Динамика синхронизации и десинхронизации ЭЭГ при выполнении реального и мысленного движения руки, направленного к видимой цели
Курганская М. Е., Исаев М. Р., Бобров П. Д., Журнал высшей нервной деятельности им. И.П. Павлова 2024 Т. 74 № 2 С. 210–222
The work investigates spatial and temporal EEG patterns during real and imagined execution of hand reaching. Six independent sources of electrical activity were identified in the EEG recordings. The sources corresponded to the premotor areas, supplementary motor area, primary motor areas, and posterior parietal cortex. Their activation patterns in the alpha and beta range were ...
Added: March 11, 2026
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