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Do immediate supervisors underestimate burnout in subordinates? A comparison between burnout self-assessment by nurses and assessment by immediate supervisors.
Arh Hig Rada Toksikol
December 2024
University Hospital Centre Zagreb, Department for Quality Assurance and Improvement in Healthcare, Zagreb, Croatia.
The burnout syndrome has been in the focus of occupational health experts for several decades, and a new diagnostic tool - Burnout Assessment Tool (BAT-23) - has given a strong impetus to its research. The tool is designed to self-assess four core dimensions of the burnout syndrome: chronic exhaustion, cognitive and emotional impairment at work, and mental distancing from work. However, little is known about how burnout is assessed from the perspective of a colleague.
View Article and Find Full Text PDFPharmacotherapy for the core symptoms of autism spectrum disorder.
J Zhejiang Univ Sci B
November 2024
Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, South China Normal University, Guangzhou 510631, China.
Autism spectrum disorder (ASD) is a range of neurodevelopmental diseases characterized by social dysfunction and stereotypic behaviors. The etiology of ASD remains largely unexplored, resulting in a diverse array of described clinical manifestations and varying degrees of severity. Currently, there are no drugs approved by a supervisory organization that can effectively treat the core symptoms of ASD.
View Article and Find Full Text PDFConfident learning-based Gaussian mixture model for leakage detection in water distribution networks.
Water Res
October 2023
College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China. Electronic address:
Leakage detection in the water distribution system not only helps to reduce water waste but also decreases the risk of drinking water pollution. To reduce reliance on hardware devices and enable real-time detection, the water utilities are transitioning towards the data-driven based approach that relies on the analysis of the flow and pressure data collected from the supervisory control and data acquisition (SCADA) system. Due to the lack of leakage data, most of these methods are unsupervised methods that rely heavily on assumptions about the distribution of anomalies; whereas, the water utility's repair records contain much valid information about the leakage and normal characteristics.
View Article and Find Full Text PDFBoundary-Aware Prototype in Semi-Supervised Medical Image Segmentation.
IEEE Trans Image Process
October 2024
The true label plays an important role in semi-supervised medical image segmentation (SSMIS) because it can provide the most accurate supervision information when the label is limited. The popular SSMIS method trains labeled and unlabeled data separately, and the unlabeled data cannot be directly supervised by the true label. This limits the contribution of labels to model training.
View Article and Find Full Text PDFCrowd Counting Using Meta-Test-Time Adaptation.
Int J Neural Syst
November 2024
Department of Computer Science and Software Engineering, Concordia University, Montreal, QC H3H 2L9, Canada.
Article Synopsis
- Machine learning algorithms are used for counting people in crowds, and test-time adaptation methods help models adjust to specific conditions during testing by altering model parameters and using additional data augmentation.
- Unlike traditional methods that require extensive unannotated data for each new target domain, the proposed CrowdTTA approach combines test-time adaptation with meta-learning for better adaptability in unknown conditions.
- CrowdTTA generates pseudo labels using uncertainty from a dropout layer, facilitating dual-level optimization which improves model performance and accuracy in counting people under various crowd densities and scales during testing.
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