Causal effects and functional mechanisms of the Internet on residents' physical fitness-An empirical analysis based on China family panel survey.

Introduction: Physical fitness is an essential part of a healthy lifestyle that concerns the overall health of the nation. Research on the relationship between the Internet and physical fitness has long been caught in the dilemma of "media mobilization" and "media suppression," and previous studies have rarely examined the causal relationship and functional mechanism. Methods: This study selected the data of 23,989 samples successfully followed in all three surveys of the China Family Panel Survey (CFPS) from 2014 to 2018 to explore the correlation and causal inference between the Internet and physical fitness by using the Time Fixed Effects Model and cross-lagged models, respectively; meanwhile, the data of 24,687 samples in CFPS 2020 to examine the functional mechanism of the Internet's effect on residents' physical fitness behavior by the KHB method. Results: We obtained three valuable conclusions as follows: First, there is a significant correlation between the Internet and physical fitness behavior. Second, the Internet use is the cause for the increase in fitness frequency, and there is a rival relationship between Internet duration and fitness time. Third, under regular prevention and control of the COVID-19 epidemic, social capital and health risk perceptions are the functional mechanisms of the Internet influencing fitness behavior, and the mediating effect of psychological health risk perceptions is higher than that of social capital. Discussion: It's necessary to create an intelligent, informative, and digital sports public service system by enriching and optimizing sports media and facilitating the Internet to serve residents' physical fitness better. The new concept of "Internet plus Fitness" will be of great significance in the implementation of the "Healthy China Initiative."

Dendritic Deep Residual Learning for COVID‐19 Prediction

Deep residual network (ResNet), one of the mainstream deep learning models, has achieved groundbreaking results in various fields. However, all neurons used in ResNet are based on the McCulloch‐Pitts model which has long been criticized for its oversimplified structure. Accordingly, this paper for the first time proposes a novel dendritic residual network by considering the powerful information processing capacity of dendrites in neurons. Experimental results based on the challenging COVID‐19 prediction problem show the superiority of the proposed method in comparison with other state‐of‐the‐art ones. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Causal effects and functional mechanisms of the Internet on residents' physical fitness-An empirical analysis based on China family panel survey

Introduction Physical fitness is an essential part of a healthy lifestyle that concerns the overall health of the nation. Research on the relationship between the Internet and physical fitness has long been caught in the dilemma of "media mobilization” and "media suppression,” and previous studies have rarely examined the causal relationship and functional mechanism. Methods This study selected the data of 23,989 samples successfully followed in all three surveys of the China Family Panel Survey (CFPS) from 2014 to 2018 to explore the correlation and causal inference between the Internet and physical fitness by using the Time Fixed Effects Model and cross-lagged models, respectively;meanwhile, the data of 24,687 samples in CFPS 2020 to examine the functional mechanism of the Internet's effect on residents' physical fitness behavior by the KHB method. Results We obtained three valuable conclusions as follows: First, there is a significant correlation between the Internet and physical fitness behavior. Second, the Internet use is the cause for the increase in fitness frequency, and there is a rival relationship between Internet duration and fitness time. Third, under regular prevention and control of the COVID-19 epidemic, social capital and health risk perceptions are the functional mechanisms of the Internet influencing fitness behavior, and the mediating effect of psychological health risk perceptions is higher than that of social capital. Discussion It's necessary to create an intelligent, informative, and digital sports public service system by enriching and optimizing sports media and facilitating the Internet to serve residents' physical fitness better. The new concept of "Internet plus Fitness” will be of great significance in the implementation of the "Healthy China Initiative.”

Dendritic Deep Residual Learning for COVID‐19 Prediction

Deep residual network (ResNet), one of the mainstream deep learning models, has achieved groundbreaking results in various fields. However, all neurons used in ResNet are based on the McCulloch‐Pitts model which has long been criticized for its oversimplified structure. Accordingly, this paper for the first time proposes a novel dendritic residual network by considering the powerful information processing capacity of dendrites in neurons. Experimental results based on the challenging COVID‐19 prediction problem show the superiority of the proposed method in comparison with other state‐of‐the‐art ones. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ FROM AUTHOR] Copyright of IEEJ Transactions on Electrical & Electronic Engineering is the property of John Wiley & Sons, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Risk factors for mortality in critically ill patients with COVID-19 in Huanggang, China: A single-center multivariate pattern analysis.

To date, the coronavirus disease 2019 (COVID-19) has a worldwide distribution. Risk factors for mortality in critically ill patients, especially detailed self-evaluation indicators and laboratory-examination indicators, have not been well described. In this paper, a total of 192 critically ill patients (142 were discharged and 50 died in the hospital) with COVID-19 were included. Self-evaluation indicators including demographics, baseline characteristics, and symptoms and detailed lab-examination indicators were extracted. Data were first compared between survivors and nonsurvivors. Multivariate pattern analysis (MVPA) was performed to identify possible risk factors for mortality of COVID-19 patients. MVPA achieved a relatively high classification accuracy of 93% when using both self-evaluation indicators and laboratory-examination indicators. Several self-evaluation factors related to COVID-19 were highly associated with mortality, including age, duration (time from illness onset to admission), and the Barthel index (BI) score. When the duration, age increased by 1 day, 1 year, BI decreased by 1 point, the mortality increased by 3.6%, 2.4%, and 0.9% respectively. Laboratory-examination indicators including C-reactive protein, white blood cell count, platelet count, fibrin degradation products, oxygenation index, lymphocyte count, and d-dimer were also risk factors. Among them, duration was the strongest predictor of all-cause mortality. Several self-evaluation indicators that can simply be obtained by questionnaires and without clinical examination were the risk factors of all-cause mortality in critically ill COVID-19 patients. The prediction model can be used by individuals to improve health awareness, and by clinicians to identify high-risk individuals.

Longitudinal clinical and radiographic evaluation reveals interleukin-6 as an indicator of persistent pulmonary injury in COVID-19.

Rationale: Previous studies of coronavirus disease 2019 (COVID-19) were mainly focused on cross-sectional analysis. In this study, we sought to evaluate the dynamic changes of immunological and radiographic features, and the association with the outcome of pulmonary lesions in COVID-19 patients. Methods: Peripheral blood samples and radiographic data were collected longitudinally for up to 8 weeks from 158 laboratory-confirmed COVID-19 patients. The chest computed tomography (CT) scans were scored based on a semi-quantification assessment according to the extent of pulmonary abnormalities; the temporal change of the immunological and radiographic features was analyzed. Results: Compared with mild and moderate patients, severe patients had significantly decreased counts of lymphocytes, CD4+ T cells, CD8+ T cells, and CD19+ B cells but dramatically elevated counts of neutrophils and levels of interleukin (IL)-6. Sequential monitoring showed a sustained increase in lymphocytes counts and significantly decreased levels of IL-6 in severe patients during the disease course. Notably, patients with persistent pulmonary lesions (CT score ≥ 5 in week 8) showed high levels of IL-6 during the follow-up period, compared with those with recovery lesions (CT score < 5 in week 8). More importantly, the peak expression of IL-6 prior to the aggravated lung injury was mainly found in patients with persistent lesions, and multivariate analysis showed that IL-6 level upon admission was an independent factor associated with the persistent pulmonary injury. Conclusion: Prolonged elevation of IL-6 is associated with persistent pulmonary lesions in COVID-19 patients. Sequential monitoring and timely intervention of IL-6 may favor the clinical management of COVID-19.