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http://dx.doi.org/10.1097/MPA.0000000000002536 | DOI Listing |
Proc Natl Acad Sci U S A
September 2025
Max Planck Institute for Solar System Research, Göttingen 37077, Germany.
Turbulent convection governs heat transport in both natural and industrial settings, yet optimizing it under extreme conditions remains a significant challenge. Traditional control strategies, such as predefined temperature modulation, struggle to achieve substantial enhancement. Here, we introduce a deep reinforcement learning (DRL) framework that autonomously discovers optimal control policies to maximize heat transfer in turbulent Rayleigh-Bénard convection.
View Article and Find Full Text PDFPLoS One
September 2025
Department of Pathology, Hospital Tuanku Fauziah, Jalan Tun Abdul Razak, Kangar, Perlis, Malaysia.
Cervical cancer remains a significant cause of female mortality worldwide, primarily due to abnormal cell growth in the cervix. This study proposes an automated classification method to enhance detection accuracy and efficiency, addressing contrast and noise issues in traditional diagnostic approaches. The impact of image enhancement on classification performance is evaluated by comparing transfer learning-based Convolutional Neural Network (CNN) models trained on both original and enhanced images.
View Article and Find Full Text PDFDisabil Rehabil Assist Technol
September 2025
School of Foreign Languages, Ningbo University of Technology, Ningbo, China.
The speech and language rehabilitation are essential to people who have disorders of communication that may occur due to the condition of neurological disorder, developmental delays, or bodily disabilities. With the advent of deep learning, we introduce an improved multimodal rehabilitation pipeline that incorporates audio, video, and text information in order to provide patient-tailored therapy that adapts to the patient. The technique uses a cross-attention fusion multimodal hierarchical transformer architectural model that allows it to jointly design speech acoustics as well as the facial dynamics, lip articulation, and linguistic context.
View Article and Find Full Text PDFIEEE Trans Cybern
September 2025
Learning to optimize and automated algorithm design are attracting increasing attention, but it is still in its infancy in constrained multiobjective optimization evolutionary algorithms (CMOEAs). Current learning-assisted CMOEAs are typically crafted by human experts using manually designed techniques, which tend to be overly tuned, ad hoc, and lacking versatility. To alleviate these limitations, this work proposes transforming the online configuration of CMOEA into determinations of discrete and continuous parameters, which are then solved by deep reinforcement learning (DRL) techniques.
View Article and Find Full Text PDFIEEE J Biomed Health Inform
September 2025
The multi-user motor imagery brain-computer interface (BCI) is a new approach that uses information from multiple users to improve decision-making and social interaction. Although researchers have shown interest in this field, the current decoding methods are limited to basic approaches like linear averaging or feature integration. They ignored accurately assessing the coupling relationship features, which results in incomplete extraction of multi-source information.
View Article and Find Full Text PDF