ABSTRACT
Tourism is linked to multiple dimensions, such as the economy, society, and environment, and the relationships among its influencing factors are complex, diverse, and overlapping. This study constructed an evaluation index system to measure the degree of coordinated development of tourism, transportation, and the regional economy, then built a tourism-transportation-based Spatial Durbin Model (SDM) regarding the process of the coordinated development of tourism in the Beijing-Tianjin-Hebei region (BTHR) from 2010 to 2020. This paper explains the current status of sustainable tourism development in the BTHR and the impact and spillover effects of transportation on tourism development. The results show that the normalized tourism coordinated development index (NTCDI) of the BTHR increased from 13.61 in 2010 to 18.75 in 2019, then decreased to 14.45 in 2020. The results of SDM show that different transportation modes have different spillover effects on tourism. Specifically, civil aviation transportation has a positive impact and significant spillover on a city's tourism revenue (TR), while high-speed railway transportation has a negative spillover effect. The model results also show that the degree of openness of the city and city economic development level have significant positive effects and spillover effects on tourism development. Finally, the implications of related variables are discussed, and some suggestions are put forward on tourism development in the BTHR. However, there are some limitations in this study. In the future, international cooperation and data sharing will be strengthened, and multivariate methods such as social network analysis, artificial intelligence, and machine learning will be further integrated to achieve accurate simulation and prediction of the spatial spillover effects of tourism transportation.
ABSTRACT
By the natural parents are the essentials of educating young generations. In China during Covid-19, especially the lock-down period, parents companied children at home and observed their learning behavior. Parental acceptance of online teaming can offer a valuable referencefor thefurther adaptation of online k-12 education. This study used an integrated model of technology acceptance and expected confirmation, demonstrating Parental acceptance by three variables: acceptance, satisfaction, and continuance intention. Moreover, an influential factor model of Parental acceptance was built, which including teacher support, perceive autonomy and interactivity, technology preference and experience. Measurement and structural data models are verified by using partial least squares regression (PLS), which supports all the hypotheses empirically.
ABSTRACT
In the beginning of 2020, COVID-19 pandemic emerged in many regions of China, and the spring semester of primary and middle schools was postponed At the call of "Suspension of Classes but not Learning" by MOE, all educational institutes adopted the online learning methods. However, the home-based online learning lacks teacher supervision, peer support, classroom environment constraints. These intensify students' attention difficulty when compared with face-to-face learning in the classroom, which makes students' learning engagement more important to ensure the learning effect. According to online focus group interviews with the education experts and K-12 teachers respectively, the researchers found out some possible influencing factors to K-12 students' online learning engagement: perceived teacher involvement, perceived parental involvement, students' self-discipline, and student emotion. Therefore, this study proposes a prediction model from the above four aspects. By using multivariate linear regression analysis and variance analysis, this study finds: (1) Perceived teacher involvement, perceived parent support, student selfdiscipline and student emotion all have significant positive effects on online learning engagement. (2) There are significant differences in students' online learning engagement for different learning stages and different network environments at home Students' online learning engagement has no significant difference between urban and rural areas.
ABSTRACT
The outbreak of novel coronavirus pneumonia (COVID-19), defined as a worldwide pandemic, has been a public health emergency of international concern. Pudilanxiaoyan oral liquid (PDL), an effective drug of Traditional Chinese Medicine (TCM), is considered to be an effective and alternative means for clinical prevention of COVID-19. The purpose of this study was to identify potential active constituents of PDL, and explore its underlying anti-COVID-19 mechanism using network pharmacology. Integration of target prediction (SwissTargetPrediction and STITCH database) was used to elucidate the active components of PDL. Protein-protein interaction network analyses, gene ontology, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses, network construction, and molecular docking were applied to analyze the prospective mechanisms of the predicted target genes. Our results showed that the key active ingredients in PDL were luteolin, apigenin, esculetin, chrysin, baicalein, oroxylin A, baicalin, wogonin, cymaroside, and gallic acid. A majority of the predicted targets were mainly involved in the pathways related to viral infection, lung injury, and inflammatory responses. An in vitro study further inferred that inhibiting the activity of nuclear factor (NF)-B signaling pathway was a key mechanism by which PDL exerted anti-COVID-19 effects. This study not only provides chemical basis and pharmacology of PDL but also the rationale for strategies to exploring future TCM for COVID-19 therapy.
ABSTRACT
As an important personal protective item against the COVID-19 pandemic, masks have recently attracted much attention in both academic and industrial contexts. We established a modified numerical model for investigating the dominant factors on the performance of masks, including the thickness and fill rate of melt-blown fibers for a filtering layer, as well as the diameters and surface charge density of the fibers. It is found that increasing the surface charge of melt-blown fibers can improve the filtration efficiency of the melt-blown layer with a low respiratory pressure drop. The relationship between the filtered particle diameter and filtration efficiency of respirators is also investigated, which demonstrated that particles with a diameter of 0.1-0.2 μm are the most difficult to filter out. Combined with molecular dynamics simulations and experimental verifications, the effect of hydrophobicity on the droplet adhesion and the water blocking performance was revealed. The knowledge obtained in this work provides reference for the design of high-performance masks. ©
ABSTRACT
This paper summarizes the infection control practice in coronavirus disease 2019 (COVID-19) wards of Wuhan Huoshenshan Hospital. By closely focusing on the three key elements of infectious diseases and strictly following the general prevention principles, we implement systematic management, including ward design, personnel management, disinfection measures, protection management, diagnosis and treatment path, clinical specimens, redisinfection of medical equipment and clearance of garbage. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid was detected in samples from critical patients and their surrounding environments, so as to indentify the possible contamination path to guide the prevention and control. During the mission, the systematic and meticulous infection control management in the wards effectively controlled cross infections, ensured the effective and safe treatment of COVID-19 patients, with no medical staff infections occurred, providing references for infection control of wards in similar epidemics in the future.