Background: Individuals with alcohol use disorder (AUD) often display compromise in emotional processing and non-affective neurocognitive functions. However, relatively little empirical work explores their intersection. In this study, we examined working memory performance when attending to and ignoring facial stimuli among adults with and without AUD. We anticipated poorer performance in the AUD group, particularly when task demands involved ignoring facial stimuli. Whether this relationship was moderated by facial emotion or participant sex were explored as empirical questions.
Methods: Fifty-six controls (30 women) and 56 treatment-seekers with AUD (14 women) completed task conditions in which performance was advantaged by either attending to or ignoring facial stimuli, including happy, neutral, or fearful faces. Group, sex, and their interaction were independent factors in all models. Efficiency (accuracy/response time) was the primary outcome of interest.
Results: An interaction between group and condition (F = 6.03, p < .02) was detected. Individual comparisons suggested this interaction was driven by AUD-associated performance deficits when ignoring faces, whereas performance was equivalent between groups when faces were attended. Secondary analyses suggested little influence of specific facial emotions on these effects.
Conclusions: These data provide partial support for initial hypotheses, with the AUD group demonstrating poorer working memory performance conditioned on the inability to ignore irrelevant emotional face stimuli. The absence of group differences when scenes were to be ignored (faces remembered) suggests the AUD-associated inability to ignore irrelevance is influenced by specific stimulus qualities.
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http://dx.doi.org/10.1016/j.addbeh.2020.106731 | DOI Listing |
Sci Rep
December 2024
College of Sciences, National University of Defense Technology, 410073, Changsha, China.
Deep Convolutional Neural Networks (DCNNs), due to their high computational and memory requirements, face significant challenges in deployment on resource-constrained devices. Network Pruning, an essential model compression technique, contributes to enabling the efficient deployment of DCNNs on such devices. Compared to traditional rule-based pruning methods, Reinforcement Learning(RL)-based automatic pruning often yields more effective pruning strategies through its ability to learn and adapt.
View Article and Find Full Text PDFSAGE Open Med
December 2024
Haramaya University, College of Health and Medical Sciences, Harar City, Ethiopia.
Background: Adherence to the proper use of protective personal equipment (PPE) in health care facilities including public hospitals is challenging among sanitation workers(SWs) across the world in general and in developing countries in particular. Despite the emphasis inline up on various policies and guidelines for PPE use implementation, inconsistent use of PPE, disobedience to PPE regulations, negligence, ignorance, discomfort, and lacking infection prevention and control (IPC) practice have been identified as main associated factors. All these and other factors contributing for the non-compliance of PPE practice among SWs within the hospitals in nations with limited resources such as Ethiopia, as well as study regions.
View Article and Find Full Text PDFBMC Health Serv Res
December 2024
Wardliparingga Aboriginal Health Equity, South Australian Health and Research Institute, Kaurna Country, Adelaide, SA, Australia.
Background: The siloed nature of the health and social service system threatens access for clients engaging numerous organisations. Many Aboriginal and Torres Strait Islander people face adverse circumstances which contribute to multiple health and social needs. Effective relationships between health and social services are integral to coordinated service provision to meet the diverse needs of Aboriginal and Torres Strait Islander clients.
View Article and Find Full Text PDFBMC Cancer
December 2024
School of Nursing, Fujian Medical University, Fuzhou, China.
Background: Lung cancer is a commonly diagnosed cancer and the leading cause of cancer-related mortality worldwide. Cancer delay pose significant challenges for health systems globally, with patient delay being a primary factor contributing to late diagnoses, ultimately resulting in adverse outcomes and reduced survival rates. However, the underlying reasons for patient delay are not well understood, and there is a scarcity of studies that specifically examine the experiences related to patient delay among lung cancer patients.
View Article and Find Full Text PDFNeural Netw
December 2024
School of Computer and Artificial Intelligence, Zhengzhou University, Zhengzhou 450000, China.
Standard makeup transfer techniques mainly focus on facial makeup. The texture details of headwear in style examples tend to be ignored. When dealing with complex portrait style transfer, simultaneous correct headwear and facial makeup transfer often cannot be guaranteed.
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