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1.
IEEE Access ; 11:46956-46965, 2023.
Article in English | Scopus | ID: covidwho-20241597

ABSTRACT

Knowledge payment is a new method of electronic learning that has developed in the era of social media. With the impact of the COVID-19 pandemic, the market for knowledge payment is rapidly expanding. Exploring the factors that influence users' sustained willingness is beneficial for better communication between knowledge payment platforms and users, and for achieving a healthier and more sustainable development of the knowledge payment industry. The model of unsustainable usage behavior of knowledge payment users was constructed on the basis of expectation inconsistency theory, price equilibrium theory, and perceived value theory, using the 'cognitive-emotional-behavioral' model framework of cognitive emotion theory. The data were collected from 348 users through a web-based questionnaire and analyzed using structural equation modeling. Findings show that expectation inconsistency, price equilibrium, and quality value, emotional value, and social value have significant effects on discontinuous use intentions. Discontinuous use intentions also significantly affect discontinuous use behavior. © 2013 IEEE.

2.
Physics of Fluids ; 35(2), 2023.
Article in English | Scopus | ID: covidwho-2287072

ABSTRACT

We have modeled the transmission of coronavirus 2019 in the isolation room of a patient suffering from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at the Royal Brompton Hospital in London. An adaptive mesh computational fluid dynamics model was used for simulation of three-dimensional spatial distribution of SARS-CoV-2 in the room. The modeling set-up is based on data collected in the room during the patient stay. Many numerical experiments have been carried out to provide an optimal design layout of the overall isolation room. Our focus has been on (1) the location of the air extractor and filtration rates, (2) the bed location of the patient, and (3) consideration of the health and safety of the staff working in the area. © 2023 Author(s).

3.
International Journal of Bank Marketing ; 2023.
Article in English | Scopus | ID: covidwho-2213058

ABSTRACT

Purpose: The purpose of this study is to examine the association between employment status and financial resilience during the COVID-19 pandemic. Design/methodology/approach: This study employed US nationally representative data. A financial resilience index was created based on households' ability to pay for basic living expenses and the resources used to meet such needs. Employment status was categorized into seven groups based on whether the respondent worked for pay in the last seven days, experience of income shock since the start of the pandemic for workers' household and reasons for not working for non-workers' household. A generalized linear model (GLM) model was used to examine the relationship between respondent employment status and household financial resilience. An ordinary least square (OLS) logistic regression with no proportional odds assumption was employed to investigate the association between the respondent's employment status and household ability to pay for basic living expenses. A logistic regression was utilized to explore the relationship between respondent employment status and resources used by the household to pay for basic living expenses. Findings: The top three least financially resilient households include those in which the respondent's work was affected by the pandemic, the respondent did not work due to being sick with COVID or caring for someone with COVID and the respondent did not work due to fear of COVID. Research limitations/implications: Future research should distinguish the reasons for not working when examining the association between unemployment and household financial resilience as well as their overall financial wellbeing. Cross-sectional data cannot establish a causal relationship. Findings using US data may not be generalized to other countries. Practical implications: Workers with health and employment risks and financial professionals working with these clients should consider these risks when building household financial safety net. Policymakers should develop measures to allow normal business operations while effectively contain the spread of the COVID-19 virus. Originality/value: This study created a financial resilience index that considers various household situations, allows both internal and external resources to be utilized to cover basic living expenses and reflects the diverse nature of financial resilience. This study is the first to look into voluntary and involuntary labor force separation for COVID-19 and non-COVID-19 related reasons. © 2023, Emerald Publishing Limited.

4.
IEEE Transactions on Artificial Intelligence ; : 1-11, 2022.
Article in English | Scopus | ID: covidwho-2192073

ABSTRACT

Automatic diagnosis of COVID-19 using chest CT images is of great significance for preventing its spread. However, it is difficult to precisely identify COVID-19 due to the following problems: 1) the location and size of lesions can vary greatly in CT images;2) its unique characteristics are often imperceptible in imaging findings. To solve these problems, a Deep Dual Attention Network (<inline-formula><tex-math notation="LaTeX">$\textrm {D}

5.
Vojnosanitetski Pregled ; 79(6):539-547, 2022.
Article in English | Web of Science | ID: covidwho-1978989

ABSTRACT

Background/Aim. The novel severe acute respiratory syn-drome coronavirus 2 (SARS Cov-2) has triggered a pandem-ic that causes a disease with complex clinical manifestations (coronavirus disease 2019, COVID-19). Soon it became clear that patients who had some comorbidities had a bigger chance of getting the severe form of COVID-19. The aim of the study was to investigate if there was a link between cardiac injury and COVID-19 severity and mortality in pa-tients. Methods. All consecutive patients with laboratory -confirmed COVID-19 were included and followed up until discharge or death from January 30, 2020, to April 5, 2020. Results. A total of 261 COVID-19 patients were included, and 29 (11.1%) had cardiac injury on admission. Patients with cardiac injury were older than those without cardiac in-jury (72.8 vs 55.8 years old) and more likely to be male (82.8% vs 42.2%). Patients with cardiac injury were also more likely to be smokers (31.0% vs 12.5%), more likely to have chronic cardiovascular disease (24.1% vs 7.8%), chron-ic pulmonary disease (17.2% vs 3.0%), and chronic kidney disease (10.3% vs 2.2%) compared to patients without cardi-ac injury. Laboratory findings suggested that patients with cardiac injury were more likely to have leukocyte counts > 10 x 109/L, pronounced lymphopenia, direct bilirubin, myohemoglobin, blood urea nitrogen, C-reactive protein, and pro-B-type natriuretic peptide but lower levels of se-rum total protein and estimated glomerular filtration rates compared to patients without cardiac injury. Patients with cardiac injury experienced more complications (72.4% vs 47.8%), including acute respiratory distress syndrome (20.7% vs 2.7%), acute kidney injury (10.3 vs 0.4%), severe COVID-19 (58.6% vs 11.6%) and death (55.2% vs 3.9%) compared to patients without cardiac injury. Multivariate analyses showed that cardiac injury was associated with an increased risk of severe COVID-19 [hazard ratio (HR) = 8.71, 95% confidence interval (CI) = 2.37-32.04] and death (HR = 20.84, 95% CI = 1.32-328.22). Conclusion. Cardiac injury on admission was associated with a higher risk of disease progression and death in patients with COVID-19.

6.
Epidemiology and Infection ; 2021.
Article in English | EMBASE | ID: covidwho-1586095

ABSTRACT

COVID-19 elicits a range of different responses in patients and can manifest into mild to very severe cases in different individuals, depending on many factors. We aimed to establish a prediction model of severe risk in COVID-19 patients, to help clinicians achieve early prevention, intervention, and aid them in choosing effective therapeutic strategy. We selected confirmed COVID-19 patients who admitted to First Hospital of Changsha city between January 29 and February 15, 2020 and collected their clinical data. Multivariate logical regression was used to identify the factors associated with severe risk. These factors were incorporated into the nomogram to establish the model. The ROC curve, calibration plot and decision curve were used to assess the performance of the model. 228 patients were enrolled and 33 (14.47%) patients developed severe pneumonia. Univariate and multivariate analysis showed that shortness of breath, fatigue, creatine kinase, lymphocytes and h CRP were independent factors for severe risk in COVID-19 patients. Incorporating age, COPD and these factors, the nomogram achieved good concordance indexes of 0.89 (95% CI: 0.832-0.949), and well-fitted calibration plot curves (Hosmer-Lemeshow test: P=0.97). The model provided superior net benefit when clinical decision thresholds were between 15-85% predicted risk. Using the model, clinicians can intervene early, improve therapeutic effects and reduce the severity of COVID-19, thus ensuring more targeted and efficient use of medical resources.

7.
Signa Vitae ; 17(3):112-120, 2021.
Article in English | Web of Science | ID: covidwho-1257440

ABSTRACT

Objectives: To explore the relationship between alcohol consumption and COVID-19 severity of illness and hospital death. Methods: This study included 1,087 COVID-19 patients confirmed by laboratory tests in many hospitals in Sichuan Province and Hubei Province during the COVID-19 epidemic. The patients were divided into a drinking group and a nondrinking group. For better baseline feature comparability between the two groups. we used propensity score matching (PSM) to generate a new cohort with a ratio of 1 : 2 (drinking group, n = 167;nondrinking group, n = 334) to compare the clinical symptoms, complications, complications, ICU admission and in-hospital death between the drinking group and the nondrinking group and to analyze the factors affecting ICU admission and the prognosis of in-hospital mortality of COVID-19 patients. Results: The incidence of wheezing symptoms in the nondrinking group was higher than that in the drinking group (11.2% vs. 6.6%, P = 0.044) after PSM (12.3% vs. 6.6%, P = 0.032), and them was no difference in the incidence of other symptoms between the two groups. The incidence of stroke was lower in the drinking group than in the nondrinking group (0.0% vs. 2.4%, P = 0.025) after PSM (0.0% vs. 2.7%, P = 0.025). The multivariate analysis showed that drinking was not associated with ICU admission (OR = 1.240, 95% CI 0.322-4.772, P = 0.755) or in-hospital mortality outcomes (OR = 2.582, 95% CI 0.689-9.670, P = 0.159). Conclusions: Drinking is not associated with patient ICU admission or hospital mortality. However, COVID-19 patients who drink alcohol have fewer wheezing symptoms and fewer stroke complications.

8.
2021 International Conference on Environmental and Engineering Management, EEM 2021 ; 253, 2021.
Article in English | Scopus | ID: covidwho-1246414

ABSTRACT

In the normal phenomenon, the restaurant industry strategic planning and future development trends are diverse, therefore, it is difficult to choose for. Existing literature does not provide effective guidance for the implementation of strategic plans in the catering industry under coVID-19. Taking RJ Restaurant in Chongqing as an example, this paper uses the method of combining qualitative and quantitative methods to study the difficulties that restaurants are facing now. This study clarifies that at the strategic level, the belief of medium-sized private restaurants to survive coVID-19 needs be based on identifying their deficiencies to establish cost strategy and differentiation strategy, which includes emphasizing the future development trends of intelligent use and "customized"services. There are two contributions to this study. First of all, this study provides a stereotyped municipal infrastructure framework for the study of private restaurants. In addition, this study studied the literature on strategic analysis of the catering industry from the perspective of coVID-19. © The Authors, published by EDP Sciences, 2021.

9.
2021 5th International Conference on Advances in Energy, Environment and Chemical Science, AEECS 2021 ; 245, 2021.
Article in English | Scopus | ID: covidwho-1233736

ABSTRACT

COVID-19 paused people lives and recombine various industry operation system. The China's Belt and Road Initiative have been intensively studied for their role in healthcare industry, the nations among them came together to defeat COVID-19 by building new healthcare system for protect public health condition. Pandemic periods inspect the previous healthcare supply chain system inefficiency in the operation situation matches with the current social development. This article compares the traditional healthcare supply chain management and novel one developing with the medical pandemic. Simultaneously, the new supply chain process illustrates the new pattern healthcare supply chain under COVID-19 in China's Belt and Road Initiative countries. Taken together, the results of this article, potentially representing a novel healthcare supply chain developing process during pandemic in China's Belt and Road Initiative. © The Authors, published by EDP Sciences, 2021.

11.
Asian Education and Development Studies ; 2021.
Article in English | Scopus | ID: covidwho-1054416

ABSTRACT

Purpose: This paper aims to take Chinese university teachers as the research objects to examine their self-evaluation of online teaching and analyze the main factors influencing their evaluation during COVID-19. Design/methodology/approach: According to the theory of educational ecology, the factors influencing teachers' self-evaluation of online teaching in this paper include university background, courses background and teachers' personal background from the macro- to micro-levels. Through exploratory factor analysis, independent sample T-test and one-way analysis of variance (ANOVA), the self-evaluation of online teaching of 13,997 teachers from 334 universities and their relationship with teachers' background have been subject to data statistics and analysis. Findings: Teachers' self-evaluation of online teaching mainly includes three dimensions: online teaching methods, online teacher–student interaction and online teaching techniques. There are significant differences in these three dimensions among teachers with different background characteristics, including regions, the types of universities, the nature of universities in macro background levels, the types and numbers of online courses in meso background levels, and the gender, years of teaching, professional titles and disciplines in micro background levels. Practical implications: To improve teachers' self-evaluation of online teaching, it is suggested to build an online teaching self-evaluation system for teachers, strengthen university support and guarantee, strengthen online teaching training and improve the information accomplishments of teachers. Originality/value: This large-scale empirical survey of online teaching evaluation of Chinese teachers can provide scholars with a deeper understanding of the implementation of online teaching in China and the self-evaluation of online teaching by teachers. © 2020, Emerald Publishing Limited.

12.
Annals of Translational Medicine ; 8(8), 2020.
Article in English | EMBASE | ID: covidwho-623484

ABSTRACT

Background: COVID-19 is currently rampant in China, causing unpredictable harm to humans. This study aimed to quantitatively and qualitatively investigate the research trends on coronaviruses using bibliometric analysis to identify new prevention strategies. Methods: All relevant publications on coronaviruses were extracted from 2000–2020 from the Web of Science database. An online analysis platform of literature metrology, bibliographic item co-occurrence matrix builder (BICOMB) and CiteSpace software were used to analyse the publication trends. VOSviewer was used to analyse the keywords and research hotspots and compare COVID-19 information with SARS and MERS information. Results: We found a total of 9,760 publications related to coronaviruses published from 2000 to 2020. The Journal of Virology has been the most popular journal in this field over the past 20 years. The United States maintained a top position worldwide and has provided a pivotal influence, followed by China. Among all the institutions, the University of Hong Kong was regarded as a leader for research collaboration. Moreover, Professors Yuen KY and Peiris JSM made great achievements in coronavirus research. We analysed the keywords and identified 5 coronavirus research hotspot clusters. Conclusions: We considered the publication information regarding different countries, institutions, authors, journals, etc. by summarizing the literature on coronaviruses over the past 20 years. We analysed the studies on COVID-19 and the SARS and MERS coronaviruses. Notably, COVID-19 must become the research hotspot of coronavirus research, and clinical research on COVID-19 may be the key to defeating this epidemic.

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