After C. L. Folk, R. W. Remington, and J. C. Johnston (1992) proposed their contingent-orienting hypothesis, there has been an ongoing debate over whether purely stimulus-driven attentional capture can occur for visual events that are salient by virtue of a distinctive static property (as opposed to a dynamic property such as abrupt onset). The present study identified 3 methodological criteria for establishing that attentional capture is stimulus driven and not contingent on top-down attentional control settings. In 5 experiments, attentional capture occurred for a static discontinuity at the boundary between one group of homogeneous items (red Xs) abutted next to a group of homogeneous items that were featurally different (green Xs) within a single row. Experiment 1 intentionally violated one of the criteria for demonstrating stimulus-driven capture so as to establish that contingent attentional capture can occur for this novel type of static cue. In the remaining 4 experiments, even with all 3 criteria for stimulus-driven capture partially or completely satisfied, the static discontinuity captured attention. These attentional capture effects are the first to be obtained when all 3 criteria for establishing that they are purely stimulus driven have been satisfied.
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Sci Rep
December 2024
College of Electrical Engineering, Northeast Electric Power University, Jilin, 132012, China.
The scattering of tiny particles in the atmosphere causes a haze effect on remote sensing images captured by satellites and similar devices, significantly disrupting subsequent image recognition and classification. A generative adversarial network named TRPC-GAN with texture recovery and physical constraints is proposed to mitigate this impact. This network not only effectively removes haze but also better preserves the texture information of the original remote sensing image, thereby enhancing the visual quality of the dehazed image.
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December 2024
School of Electronic Information and Electrical Engineering, Yangtze University, Jingzhou, 434100, Hubei, China.
Emotions play a crucial role in human thoughts, cognitive processes, and decision-making. EEG has become a widely utilized tool in emotion recognition due to its high temporal resolution, real-time monitoring capabilities, portability, and cost-effectiveness. In this paper, we propose a novel end-to-end emotion recognition method from EEG signals, called MSDCGTNet, which is based on the Multi-Scale Dynamic 1D CNN and the Gated Transformer.
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December 2024
Anesthesiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.
Background: There is an under-reporting of anaesthesia-related safety events. Incident-capturing systems (ICSs) are essential for patient safety monitoring, identifying risks and ongoing opportunities for improvement. After a literature review and assessment of our current ICSs, we concluded that our institution lacked a reliable anaesthesia-specific ICS system, leading to under-reporting of anaesthesia-related safety events.
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December 2024
Henan University of Engineering, Zhengzhou, 451191, China.
Social media generates vast amounts of spatio-temporal sequential data. However, current methods often ignore the complex spatio-temporal correlations within these data. This oversight makes it difficult to fully capture the dynamic features of the data.
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December 2024
School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao, 266520, China.
This paper presents a deep learning model based on an active learning strategy. The model achieves accurate identification of vegetation types in the study area by utilizing multispectral data obtained from preprocessing of unmanned aerial vehicle (UAV) remote sensing equipment. This approach offers advantages such as high data accuracy, mobility, and easy data collection.
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