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Previous studies have shown that perceptual performance can be modulated at specific frequencies phase-locked to self-paced motor actions, but findings have been inconsistent. To investigate this effect at the population level, we tested 50 participants who performed a self-paced button press followed by a threshold-level detection task, using both fixed- and random-effects analyses. Contrary to expectations, the aggregated data showed no significant action-related modulation.

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Large language models (LLMs) are being increasingly incorporated into scientific workflows. However, we have yet to fully grasp the implications of this integration. How should the advancement of large language models affect the practice of science? For this opinion piece, we have invited four diverse groups of scientists to reflect on this query, sharing their perspectives and engaging in debate.

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This paper introduces a novel approach for the offline estimation of stationary moving average processes, further extending it to efficient online estimation of non-stationary processes. The novelty lies in a unique technique to solve the autocorrelation function matching problem leveraging that the autocorrelation function of a colored noise is equal to the autocorrelation function of the coefficients of the moving average process. This enables the derivation of a system of nonlinear equations to be solved for estimating the model parameters.

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Electroencephalogram (EEG) during pinprick stimulation has the potential to unveil neural mechanisms underlying sensorimotor impairments post-stroke. A proof-of-concept study explored event-related peak pinprick amplitude and oscillatory responses in healthy controls and in people with acute and subuacute motor and sensorimotor stroke, their relationship, and to what extent EEG somatosensory responses can predict sensorimotor impairment. In this study, 26 individuals participated, 10 people with an acute and early subacute sensorimotor stroke, 6 people with an acute and early subacute motor stroke, and 10 age-matched controls.

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Smart oxygen monitoring in hospitals: a pilot study during COVID-19.

Sci Rep

January 2025

Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 70800, Ostrava, Czech Republic.

During 2020-2021, the COVID-19 pandemic exposed significant vulnerabilities in hospital safety, with oxygen-related fires and explosions occurring at twice the usual rate. This highlighted insufficient preparedness for increased oxygen therapy demands and the associated risks of oxygen-enriched atmospheres. This study aimed to develop and test a smart monitoring system to detect increased oxygen concentrations in hospital environments, mitigating the risk of fires.

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