Work–family conflict, educational involvement, and adolescent academic engagement during COVID-19: An investigation of developmental differences

Objective: In this research, we examine the mediating effect of educational involvement between parental work–family conflict and adolescent academic engagement during COVID-19, as well as the differences among developmental stages. Background: Online learning during the COVID-19 lockdown created challenges for adolescent academic engagement. One of the toughest challenges was that parents experienced increased work–family conflict, making it difficult for them to be involved in adolescent education. In this context, it is essential to understand the impact of parental work–family conflict on adolescent academic engagement. Method: A total of 886 dual-income families participated in the study. Mothers and fathers completed the questionnaire, including questions regarding work–family conflict and educational involvement. Adolescents completed an academic engagement scale. Results: The structural equation model in the total sample showed that parental educational involvement mediated the effect of maternal work–family conflict on adolescent academic engagement. In addition, paternal educational involvement mediated the effect of paternal work–family conflict on adolescent academic engagement. Multigroup analysis indicated the impact of work–family conflict only existed in middle and late adolescence, and mother played a more important role in late adolescence. Conclusion: The study results confirmed the mediating role of parental educational involvement between the relationship of paternal work–family conflict and adolescent academic engagement. Furthermore, this relationship may vary for families with an adolescent at different developmental stages. © 2023 National Council on Family Relations.

Recognition of the standardization of wearing masks during the epidemic of COVID-19

In face of COVID-19, it is very important to wear masks in public. In this article, we use a kind of improved convolutional neural network algorithm DFS (detection with feature fusion and segmentation supervision) for face detection, and YCrCb elliptic skin color model is used for mask recognition. We expect to better supervise the standardization of people wearing masks, through the application of this project in public places such as public transport. With the applying of this project, the risk of human infection can be reduced, so as to better prevent and control the epidemic. © 2021 IEEE.

Improved SEIR prediction model based on particle swarm optimization

This article analyzes the epidemic situation in all provinces of China, considering the impact of population mobility in all provinces during the Spring Festival transportation without restricting people's free movement in Wuhan. According to the characteristics of novel Coronavirus, we choose the SEIR model to establish the required differential equations. On this basis, we establish different differential equations according to the characteristics of Wuhan and all provinces of China. By collecting relevant data and using particle swarm optimization algorithm for data fitting, we predict the epidemic situation of domestic provinces during the period from the first case to March 1

Refinement and Validation of Humoral Immunity Based on Event-B

By the outbreak of Covid-19, we should focus more eyesight on the human immune system. Humoral immunity plays an important role in the immunologic mechanism. In this process, B cells and other immune cells cooperate each other to produce antibodies and eliminate antigens by series of interactions, activation, proliferation and differentiation. In this paper, we use the formal language Event-B to model the humoral immunity process on the development tool called Rodin. Humoral immunity process is abstract and has complexity in system design. Accidentally, the formal method is used to verify the correctness and consistency of the complex systems, which is an appropriate approach to model this immunity process by stepwise refinements and validation. We also present an instance to demonstrate the differences between the immunity responses after the invasion of influenza viruses and coronavirus respectively in the last refinement and validate it using proof obligations. Experimental results show that events in our model are all validated by the automatic certification tool on Rodin platform. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

[Preliminary study of the relationship between novel coronavirus pneumonia and liver function damage: a multicenter study].

Objective: To analyze the clinical characteristics of cases of novel coronavirus pneumonia and a preliminary study to explore the relationship between different clinical classification and liver damage. Methods: Consecutively confirmed novel coronavirus infection cases admitted to seven designated hospitals during January 23, 2020 to February 8, 2020 were included. Clinical classification (mild, moderate, severe, and critical) was carried out according to the diagnosis and treatment program of novel coronavirus pneumonia (Trial Fifth Edition) issued by the National Health Commission. The research data were analyzed using SPSS19.0 statistical software. Quantitative data were expressed as median (interquartile range), and qualitative data were expressed as frequency and rate. Results: 32 confirmed cases that met the inclusion criteria were included. 28 cases were of mild or moderate type (87.50%), and four cases (12.50%) of severe or critical type. Four cases (12.5%) were combined with one underlying disease (bronchial asthma, coronary heart disease, malignant tumor, chronic kidney disease), and one case (3.13%) was simultaneously combined with high blood pressure and malignant tumor. The results of laboratory examination showed that the alanine aminotransferase (ALT), aspartate aminotransferase (AST), albumin (ALB), and total bilirubin (TBil) for entire cohort were 26.98 (16.88 ~ 46.09) U/L and 24.75 (18.71 ~ 31.79) U/L, 39.00 (36.20 ~ 44.20) g/L and 16.40 (11.34 ~ 21.15) µmol/L, respectively. ALT, AST, ALB and TBil of the mild or moderate subgroups were 22.75 (16.31 ~ 37.25) U/L, 23.63 (18.71 ~ 26.50) U/L, 39.70 (36.50 ~ 46.10) g/L, and 15.95 (11.34 ~ 20.83) µmol/L, respectively. ALT, AST, ALB and TBil of the severe or critical subgroups were 60.25 (40.88 ~ 68.90) U/L, 37.00 (20.88 ~ 64.45) U/L, 35.75 (28.68 ~ 42.00) g/L, and 20.50 (11.28 ~ 25.00) µmol/L, respectively. Conclusion: The results of this multicenter retrospective study suggests that novel coronavirus pneumonia combined with liver damage is more likely to be caused by adverse drug reactions and systemic inflammation in severe patients receiving medical treatment. Therefore, liver function monitoring and evaluation should be strengthened during the treatment of such patients.