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News
August 25, 2026
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.
August 24, 2026
Researchers Develop Method for Direct Generation of Regulatory DNA
Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’
August 21, 2026
Social Integration: At the Crossroads of Knowledge and Values
The International Laboratory for Social Integration Research (ILSIR) at HSE University studies the challenges faced by vulnerable groups and explores ways to help them participate fully in everyday life. To develop effective solutions, the laboratory’s researchers combine cutting-edge methods with practical fieldwork. In this interview with the HSE News Service, Laboratory Head Elena Iarskaia-Smirnova discusses the laboratory’s work.

 

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Программное обеспечение для анализа движений захвата и переноса рукой: возможности применения в когнитивных и нейрофизиологических исследованиях

Нервно-мышечные болезни. 2025. Т. 15. № 2. С. 28–36.
Viazmin A., Чапанова М. Р., Морозов М. С., Aksenov S. A., Feurra M.

Objective. To present Kinematic 4, a software tool designed for automated analysis of reach-to-grasp and object transport movements using data obtained from motion capture systems.
Materials and Methods. The software was developed in Python and implements algorithms for automatic detection of key temporal events in motor actions. Initially validated in MATLAB, the algorithmic framework was adapted into a cross-platform desktop application with a graphical user interface. Kinematic 4 processes coordinate data from markers placed on the thumb, index finger, wrist, object, and specialized glasses with a movable shutter. The program identifies six critical time points: experiment onset, hand lifting, finger opening, maximum grasp aperture, object lifting, and object placement.
Results. Comparison between results obtained using Kinematic 4 and those generated by the original MATLAB script demonstrated full consistency. The software was successfully validated on experimental datasets and showed high stability. Its user-friendly interface and automated workflow make it a reliable and reproducible tool for both research and clinical applications.
Conclusions. Kinematic 4 can be effectively used for assessing upper-limb movements in neuroscience and clinical contexts, including the diagnosis of motor impairments and monitoring of recovery dynamics. Future development may include integration with other biosignals and machine learning modules for predictive analytics.
 

Research target: Biology Medical Biotechnologies Psychology
Language: Russian
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Keywords: pythonrehabilitationреабилитацияmotion capture systemsmotor planningмоторное планированиеKinematic analysisPythonHand graspingкинематический анализneurodiagnosticсистемы захвата движениянейродиагностика
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