ABSTRACT
The outbreak of coronavirus disease (COVID-19) in 2019 has highlighted the need for automatic diagnosis of the disease, which can develop rapidly into a severe condition. Nevertheless, distinguishing between COVID-19 pneumonia and community-acquired pneumonia (CAP) through computed tomography scans can be challenging due to their similar characteristics. The existing methods often perform poorly in the 3-class classification task of healthy, CAP, and COVID-19 pneumonia, and they have poor ability to handle the heterogeneity of multi-centers data. To address these challenges, we design a COVID-19 classification model using global information optimized network (GIONet) and cross-centers domain adversarial learning strategy. Our approach includes proposing a 3D convolutional neural network with graph enhanced aggregation unit and multi-scale self-attention fusion unit to improve the global feature extraction capability. We also verified that domain adversarial training can effectively reduce feature distance between different centers to address the heterogeneity of multi-center data, and used specialized generative adversarial networks to balance data distribution and improve diagnostic performance. Our experiments demonstrate satisfying diagnosis results, with a mixed dataset accuracy of 99.17% and cross-centers task accuracies of 86.73% and 89.61%.
ABSTRACT
Introduction: The ongoing 2019 coronavirus disease pandemic (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and its variants, is a global public health threat. Early diagnosis and identification of SARS-CoV-2 and its variants plays a critical role in COVID-19 prevention and control. Currently, the most widely used technique to detect SARS-CoV-2 is quantitative reverse transcription real-time quantitative PCR (RT-qPCR), which takes nearly 1 hour and should be performed by experienced personnel to ensure the accuracy of results. Therefore, the development of a nucleic acid detection kit with higher sensitivity, faster detection and greater accuracy is important. Methods: Here, we optimized the system components and reaction conditions of our previous detection approach by using RT-RAA and Cas12b. Results: We developed a Cas12b-assisted one-pot detection platform (CDetection.v2) that allows rapid detection of SARS-CoV-2 in 30 minutes. This platform was able to detect up to 5,000 copies/ml of SARS-CoV-2 without cross-reactivity with other viruses. Moreover, the sensitivity of this CRISPR system was comparable to that of RT-qPCR when tested on 120 clinical samples. Discussion: The CDetection.v2 provides a novel one-pot detection approach based on the integration of RT-RAA and CRISPR/Cas12b for detecting SARS-CoV-2 and screening of large-scale clinical samples, offering a more efficient strategy for detecting various types of viruses.
ABSTRACT
The COVID‐19 pandemic has put online shopping at the forefront of retailing;however, the issue related to shopping cart abandonment remains an eternal nemesis of e‐retailers. To understand extant research on online shopping cart abandonment (OSCA), a framework‐based systematic literature review was conducted with the purpose of gaining more insights into existing studies in this context. Specifically, this review examined the literature related to OSCA in terms of theory, context, characteristics, and methods to provide (i) a comprehensive review of the current state of research and (ii) constructive future research agenda in the area. Using scientific procedures, a total of 52 research articles were retrieved from Scopus and Web of Science databases published during the period 2003–2022. The results revealed that most research was founded by the stimulus‐organism‐response (S‐O‐R) model and the buyer behavior theory, focused in the context of the United States and China, and appeared to use quantitative methods. As a result, this review is expected to assist researchers in better understanding the OSCA context, thus paving the way for further research and development in the area. In addition, providing practitioners with a better panorama to address the issue by expanding the literature review and highlighting the inhibiting factors of OSCA.
ABSTRACT
The COVID-19 pandemic has put online shopping at the forefront of retailing;however, the issue related to shopping cart abandonment remains an eternal nemesis of e-retailers. To understand extant research on online shopping cart abandonment (OSCA), a framework-based systematic literature review was conducted with the purpose of gaining more insights into existing studies in this context. Specifically, this review examined the literature related to OSCA in terms of theory, context, characteristics, and methods to provide (i) a comprehensive review of the current state of research and (ii) constructive future research agenda in the area. Using scientific procedures, a total of 52 research articles were retrieved from Scopus and Web of Science databases published during the period 2003-2022. The results revealed that most research was founded by the stimulus-organism-response (S-O-R) model and the buyer behavior theory, focused in the context of the United States and China, and appeared to use quantitative methods. As a result, this review is expected to assist researchers in better understanding the OSCA context, thus paving the way for further research and development in the area. In addition, providing practitioners with a better panorama to address the issue by expanding the literature review and highlighting the inhibiting factors of OSCA.
ABSTRACT
Despite the widespread prevalence of online shopping cart abandonment (OSCA) and allusions to this behavior in popular press, scholars have yet to examine the key determinants of OSCA. This study used the stimulus-organism-response (S–O-R) model to explore the factors influencing consumers' OSCA and decision to buy from a land-based retailer. Two studies were carried out to test the proposed hypotheses among Mainland China's Generation Y consumers. Data was collected based on two product categories (i.e., apparel and electrical appliances) at two different time scenarios (i.e., pre- and post-pandemic). The findings reveal that hesitation at checkout increases OSCA, while consumers' decision to buy from a land-based retailer is influenced by their emotional ambivalence and OSCA. Furthermore, fear appeals appear to weaken the relationship between OSCA and the decision to buy from a land-based retailer. This study has implications for researchers and practitioners who seek to effectively reduce the rate of OSCA.
ABSTRACT
AIMS/INTRODUCTION: The coronavirus disease 2019 (COVID-19) pandemic urged authorities to impose rigorous quarantines and brought considerable changes to people's lifestyles. The impact of these changes on glycemic control has remained unclear, especially the long-term effect. We aimed to investigate the impact of COVID-19 lockdown on glycemic control in children and adolescents with type 1 diabetes. MATERIALS AND METHODS: This observational study enrolled children with type 1 diabetes using continuous glucose monitoring. Continuous glucose monitoring data were extracted from the cloud-based platform before, during and after lockdown. Demographics and lifestyle change-related information were collected from the database or questionnaires. We compared these data before, during and after lockdown. RESULTS: A total of 43 children with type 1 diabetes were recruited (20 girls; mean age 7.45 years; median diabetes duration 1.05 years). We collected 41,784 h of continuous glucose monitoring data. Although time in range (3.9-10.0 mmol/L) was similar before, during and after lockdown, the median time below range <3.9 mmol/L decreased from 3.70% (interquartile range [IQR] 2.25-9.53%) before lockdown to 2.91% (IQR 1.43-5.95%) during lockdown, but reversed to 4.95% (IQR 2.11-9.42%) after lockdown (P = 0.004). Time below range <3.0 mmol/L was 0.59% (IQR 0.14-2.21%), 0.38% (IQR 0.05-1.35%) and 0.82% (IQR 0.22-1.69%), respectively (P = 0.008). The amelioration of hypoglycemia during lockdown was more prominent among those who had less time spent <3.9 mmol/L at baseline. During lockdown, individuals reduced their physical activity, received longer sleep duration and spent more time on diabetes management. In addition, they attended outpatient clinics less and turned to telemedicine more frequently. CONCLUSION: Glycemic control did not deteriorate in children and teenagers with type 1 diabetes around the COVID-19 pandemic. Hypoglycemia declined during lockdown, but reversed after lockdown, and the changes related to lifestyle might not provide a long-term effect.