Younger adults have difficulties identifying emotional facial expressions from faces covered by face masks. It is important to evaluate how face mask wearing might specifically impact older people, because they have lower emotion identification performance than younger adults, even without face masks. We compared performance of 62 young and 38 older adults in an online task of emotional facial expression identification using masked or unmasked pictures of faces with fear, happiness, anger, surprise, and neutral expression, from different viewpoints. Face masks affected performance in both age groups, but more so in older adults, specifically for negative emotions (anger, fear), in favour of the saliency hypothesis as an explanation for the positive advantage. Additionally, face masks more affected emotion recognition on profile than on three-quarter or full-face views. Our results encourage using clearer and full-face expressions when dealing with older people while wearing face masks.
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http://dx.doi.org/10.1684/pnv.2024.1175 | DOI Listing |
J Infect Dev Ctries
December 2024
Faculdade de Medicina de Campos, Campos dos Goytacazes, Brazil.
Introduction: Despite efforts by health organizations to share evidence-based information, fake news hindered the promotion of social distancing and vaccination during the coronavirus disease 2019 (COVID-19) pandemic. This study analyzed COVID-19 knowledge and practices in a vulnerable area in northern Rio de Janeiro, acknowledging the influence of the complex social and economic landscape on public health perceptions.
Methodology: This cross-sectional study was conducted in Novo Eldorado - a low-income, conflict-affected neighborhood in Campos dos Goytacazes - using a structured questionnaire, following the peak of COVID-19 deaths in Brazil (July-December 2021).
J Infect Dev Ctries
December 2024
Institute of Public Health, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Introduction: Significant challenges to implementing international health regulations (IHR) at points of entry (PoEs) have been highlighted by the coronavirus disease 2019 (COVID-19) pandemic. Better assessment of the capacities of the PoEs may promote focused interventions. This study aimed to assess the capacities and practices at PoEs.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Electrical Electronical Engineering, Yaşar University, Bornova, İzmir, Turkey.
We aimed to build a robust classifier for the MGMT methylation status of glioblastoma in multiparametric MRI. We focused on multi-habitat deep image descriptors as our basic focus. A subset of the BRATS 2021 MGMT methylation dataset containing both MGMT class labels and segmentation masks was used.
View Article and Find Full Text PDFEnviron Pollut
January 2025
Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, School of Environmental Science and Engineering, Institute of Environmental Health and Pollution Control, Guangdong University of Technology, Guangzhou 510006, China.
Airborne microorganisms in hospitals present significant health risks to both patients and employees. However, their pollution profiles and associated hazards in different hospital areas remained largely unknown during the extensive use of masks and disinfectants. This study investigated the characteristics of bioaerosols in an urban general hospital during the COVID-19 pandemic and found that airborne bacteria and fungi concentrations range from 87±35 to 1037±275 CFU/m and 21±15 to 561±132 CFU/m, respectively, with the outpatient clinic and internal medicine ward showing the highest levels.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Shanghai Film Academy, Shanghai University, Shanghai 200072, China.
The advancement of neural radiance fields (NeRFs) has facilitated the high-quality 3D reconstruction of complex scenes. However, for most NeRFs, reconstructing 3D tissues from endoscopy images poses significant challenges due to the occlusion of soft tissue regions by invalid pixels, deformations in soft tissue, and poor image quality, which severely limits their application in endoscopic scenarios. To address the above issues, we propose a novel framework to reconstruct high-fidelity soft tissue scenes from low-quality endoscopic images.
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