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Social Networks, Health Support, and Dietary Intake in Mothers Receiving Home Visiting Services.
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Center for Economic and Social Research, Arts and Sciences, Dornsife College of Letters, University of Southern California, Los Angeles, USA.
Home visiting programs (HVPs) provide services to pregnant individuals and parents of young children to improve families' health and well-being. However, little is known about these families' social contexts. This study explores the social networks and dietary intake of mothers enrolled in a HVP, focusing on health support and health undermining.
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Anhui BioX-Vision Biological Technology Co., Ltd, Hefei, 230031, Anhui, China.
The identification and categorization of circulating tumor cells (CTCs) in peripheral blood are imperative for advancing cancer diagnostics and prognostics. The intricacy of various CTCs subtypes, coupled with the difficulty in developing exhaustive datasets, has impeded progress in this specialized domain. To date, no methods have been dedicated exclusively to overcoming the classification challenges of CTCs.
View Article and Find Full Text PDFAdvancements and challenges of onboard carbon capture and storage technologies for the maritime industry: a comprehensive review.
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CMMI-Cyprus Marine & Maritime Institute, CMMI House-Vasileos Pavlou Square, P.O. Box 40930, 6023 Larnaca, Cyprus.
In response to the growing demand of reducing greenhouse gas (GHG) emissions within maritime sector, Onboard Carbon Capture and Storage (OCCS) technologies provide as key solutions for tackling carbon dioxide (CO) emissions from ships. This review paper offers a comprehensive overview of recent developments, challenges, and prospects of Carbon Capture and Storage (CCS) technologies considering specifically for onboard ship applications. Various Carbon Capture (CC) methods, ranging from post-combustion and pre-combustion capture to oxy-fuel combustion, are critically analysed concerning their operating principles, advantages, disadvantages and applicability in the maritime context.
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Quant Imaging Med Surg
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Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Background And Objective: Computed tomography (CT) imaging plays a crucial role in the early detection and diagnosis of life-threatening diseases, particularly in respiratory illnesses and oncology. The rapid advancement of deep learning (DL) has revolutionized CT image analysis, enhancing diagnostic accuracy and efficiency. This review explores the impact of advanced DL methodologies in CT imaging, with a particular focus on their applications in coronavirus disease 2019 (COVID-19) detection and lung nodule classification.
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School of Computer and Control Engineering, Yantai University, Yantai, China.
Background: Skin lesion segmentation plays a significant role in skin cancer diagnosis. However, due to the complex shapes, varying sizes, and different color depths, precise segmentation of skin lesions is a challenging task. Therefore, the aim of this study was to design a customized deep learning (DL) model for the precise segmentation of skin lesions, particularly for complex shapes and small target lesions.
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