A comparative single-evaluation cross-sectional study was performed to evaluate cognitive damage in post-COVID-19 patients. The psychophysics tests of Two-Alternative Forced Choice (2AFC) and Simple Reaction Time (SRT), under a designed virtual environment, were used to evaluate the cognitive processes of decision-making, visual attention, and information processing speed. The population under study consisted of 147 individuals, 38 controls, and 109 post-COVID patients. During the 2AFC test, an Emotiv EPOC+® headset was used to obtain EEG signals to evaluate their Focus, Interest, and Engagement metrics. Results indicate that compared to healthy patients or recovered patients from mild-moderate COVID-19 infection, patients who recovered from a severe-critical COVID infection showed a poor performance in different cognitive tests: decision-making tasks required higher visual sensitivity (p = 0.002), Focus (p = 0.01) and information processing speed (p < 0.001). These results signal that the damage caused by the coronavirus on the central nervous and visual systems significantly reduces the cognitive processes capabilities, resulting in a prevalent deficit of 42.42% in information processing speed for mild-moderate cases, 46.15% for decision-making based on visual sensitivity, and 62.16% in information processing speed for severe-critical cases. A psychological follow-up for patients recovering from COVID-19 is recommended based on our findings.
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http://dx.doi.org/10.3390/brainsci12091258 | DOI Listing |
Curr Res Food Sci
December 2024
Medical Food Laboratory, Shanghai Key Laboratory of Pediatric Gastroenterology and Nutrition, Shanghai Institute for Pediatric Research, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China.
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View Article and Find Full Text PDFBiomed Opt Express
January 2025
Department of Robotics, University of Michigan, USA.
Conventional scanned optical coherence tomography (OCT) suffers from the frame rate/resolution tradeoff, whereby increasing image resolution leads to decreases in the maximum achievable frame rate. To overcome this limitation, we propose two variants of machine learning (ML)-based adaptive scanning approaches: one using a ConvLSTM-based sequential prediction model and another leveraging a temporal attention unit (TAU)-based parallel prediction model for scene dynamics prediction. These models are integrated with a kinodynamic path planner based on the clustered traveling salesperson problem to create two versions of ML-based adaptive scanning pipelines.
View Article and Find Full Text PDFPhilos Trans A Math Phys Eng Sci
January 2025
IBM Research-Europe, 8803 Rüschlikon, Zurich, Switzerland.
Encryption and decryption of data with very low latency and high energy efficiency is desirable in almost every application that deals with sensitive data. The advanced encryption standard (AES) is a widely adopted algorithm in symmetric key cryptography with numerous efficient implementations. Nonetheless, in scenarios involving extensive data processing, the primary limitations on performance and efficiency arise from data movement between memory and the processor, rather than data processing itself.
View Article and Find Full Text PDFJ Food Sci
January 2025
College of Food Science and Engineering, Henan University of Technology, Zhengzhou, China.
Flaxseed gum (FSG) has promising applications in the field of nano/microencapsulation for its biocompatibility and excellent physicochemical properties. In this study, FSG-based nano-microcapsules (FSG NPs) were prepared using high-speed shear homogenization combined with ultrasound for efficient encapsulation of secoisolariciresinol diglucoside (SDG). The particle size of FSG stands for nano-microcapsules (NP) was determined to be 336.
View Article and Find Full Text PDFA parallel Hilbert transform arctangent phase demodulation (PHT-ATAN) method based on overlapping computation is proposed for phase demodulation of laser heterodyne Doppler vibrometers. The method suppresses the end point effects by utilizing overlapping computation and data concatenation and accelerates phase demodulation through parallel processing. Simulation and experimental results demonstrate that when the algorithm's parallelism is ≥4, the computation speed of this method increases by over 100% compared to traditional methods, while maintaining the signal-to-noise ratio and accuracy of the phase demodulation results.
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