The role of attentional resources and affective stimuli on temporal selective attention in the rapid serial visual presentation (RSVP) paradigm under acute stress was explored among women. Seventy-three female undergraduates were randomly assigned to the Trier Social Stress Test (TSST) group or control group. We found that when the first target was negative, stress increased its accuracy. Stress promoted the recognition of neutral target two (T2) only at lag2, and there was no interaction with theemotionality of target one (T1). In addition, the accumulated effect of stress enhanced temporal selective attention, predominately 20-40 min after the TSST task; cortisol concentration during this time period could significantly predict AB task performance. In summary, when attentional resources were severely insufficient, individuals under stress were more able to focus on the current target; that is, stress facilitated selective attention. A novel result was that participants were exempt from the affective influence of previous targets, which may have been caused by activation of the autonomic nervous system and gender differences.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.concog.2019.102796 | DOI Listing |
Sensors (Basel)
January 2025
School of Information Engineering, China University of Geosciences, Beijing 100083, China.
Extracting fragmented cropland is essential for effective cropland management and sustainable agricultural development. However, extracting fragmented cropland presents significant challenges due to its irregular and blurred boundaries, as well as the diversity in crop types and distribution. Deep learning methods are widely used for land cover classification.
View Article and Find Full Text PDFSensors (Basel)
January 2025
College of Information Science and Engineering, Hohai University, Changzhou 213200, China.
Fast Fourier Transform-based Space-Time Image Velocimetry (FFT-STIV) has gained considerable attention due to its accuracy and efficiency. However, issues such as false detection of MOT and blind areas lead to significant errors in complex environments. This paper analyzes the causes of FFT-STIV gross errors and then proposes a method for validity identification and rectification of FFT-STIV results.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Information Technology, Quaid e Awam University, Nawabshah 67450, Pakistan.
Detection of anomalies in video surveillance plays a key role in ensuring the safety and security of public spaces. The number of surveillance cameras is growing, making it harder to monitor them manually. So, automated systems are needed.
View Article and Find Full Text PDFSensors (Basel)
January 2025
State Key Laboratory of Intelligent Vehicle Safety Technology, Chongqing 401133, China.
With the advancement of federated learning (FL), there is a growing demand for schemes that support multi-task learning on multi-modal data while ensuring robust privacy protection, especially in applications like intelligent connected vehicles. Traditional FL schemes often struggle with the complexities introduced by multi-modal data and diverse task requirements, such as increased communication overhead and computational burdens. In this paper, we propose a novel privacy-preserving scheme for multi-task federated split learning across multi-modal data (MTFSLaMM).
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China.
Unmanned aerial vehicles (UAVs) furnished with computational servers enable user equipment (UE) to offload complex computational tasks, thereby addressing the limitations of edge computing in remote or resource-constrained environments. The application of value decomposition algorithms for UAV trajectory planning has drawn considerable research attention. However, existing value decomposition algorithms commonly encounter obstacles in effectively associating local observations with the global state of UAV clusters, which hinders their task-solving capabilities and gives rise to reduced task completion rates and prolonged convergence times.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!