Quantifying the COVID-19-affected tourism education in China: a potential crisis in tourism recovery

Human resources is a crucial factor in supporting the development of tourism as a labour-intensive industry. This research enhances the understanding of China's tourism education associated with the spread of COVID-19 and its implications for tourism recovery. Initial findings imply that: COVID-19 had a profound lagging negative effect on the intention to apply for tourism-related majors of examinees, which is severe challenging for tourism recovery, and the impact was more pronounced in typical tourism-dependent cities than in non-tourism-dependent cities. The MICE Economics and Management was least affected, while the Sports Tourism was most affected. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

Growth mindset predicts teachers' life satisfaction when they are challenged to innovate their teaching

Teaching innovations can improve the quality of education and facilitate adaptation to environmental shifts caused by global shocks such as the COVID pandemic. However, the pressure to innovate and change may also cause erosion of teachers' life satisfaction, especially when job resources are insufficient and support for the changes is inadequate, or when teachers lack confidence in mastering new teaching technology. In the present research, we showed that compared to those who did not, teachers who presented a growth mindset-the belief that one's abilities can grow by mobilizing effective effort-had a greater tendency to accept a new initiative in teaching and had higher life satisfaction, particularly when they perceived resources and support for the change were insufficient (Study 1). In addition, when schools needed to switch to online teaching because of school closure during the COVID-19 pandemic, teachers who presented a growth mindset, compared to those who did not, felt more self-efficacious in mastering online teaching and had higher life satisfaction (Study 2). We discuss these findings in terms of their implications on the management of teacher well-being and teachers' professional development during significant environmental shifts.

Personal qualities are malleable and fixed: Ambivalent mindset, capability ranking reinforcement, and parent-child relationship among Hong Kong Chinese parents

Past research showed that people may hold contradictory ideas about something or someone. Mindset ambivalence refers to the psychological state in which a person holds contradictory beliefs about the malleability of a valued attribute and spontaneously expresses agreement with both the fixed and growth mindsets. Our past findings showed that a sizable proportion of Hong Kong Chinese adults possess the ambivalent mindset. In the present study, 101 Hong Kong Chinese parents completed a survey during the COVID-19 pandemic. The findings provided further support for the prevalence of the ambivalent mindset. In addition, we found that parents with the ambivalent mindset tended to support several parental practices that would reinforce the relative ability rankings of their children. These practices included person praise, mobilization of effort to compensate for low ability, and lowering of expectation to avoid future failures. Finally, the use of these parental practices was accompanied by deterioration of parent-child relationship when children displayed undesirable self-regulatory behaviors. We discuss these findings' implications for growth mindset interventions in Chinese societies.

Comparative Study on the Review Text of COVID-19 Epidemic Prevention and Control Policy Between China and Japan

COVID-19 continues to spread and spread, and the epidemic situation in China and Japan is not optimistic, which brings huge hidden dangers and serious impact to the economic cooperation and development of China and Japan. Aiming at the comments and feedback of Chinese and Japanese people on government policies, this paper proposes a text emotional tendency analysis method based on maximum entropy model, which extracts word relation features and semantic features from the comment context. The maximum entropy model is used to identify the emotional tendency of words, and the smoothing technique is used to solve the problem of sparse features. At the same time, through the weighting and normalization of specific emotional words and punctuation marks, the uncertainty of the emotional tendency of words in the context is further reduced, and the experimental results verify the effectiveness of the model.

Age Estimation with Synthetic Mask Generation Based on MobileNet and Facial Keypoint Detection

Facial age estimation is one of the most important tasks in the field of face recognition and recommendation system. Since the COVID-19 pandemic, people have been required to wear masks, which can be a challenge for traditional recognition methods. In this paper, an improved convolutional neural network architecture based on MobileNet is proposed to perform age estimation. For the challenge of masked faces, an innovative mask generation method using face keypoint detection is adopted, extracting the key points of the faces in order to add synthetic masks to simulate the real situations. Then we compare the estimation results of the original images and the synthetic images. Our method is applied to the WIKI Face dataset containing more than 150,000 images, and achieves MAE of 3.79 and 6.54 on unmasked and masked faces, respectively, which demonstrates the effectiveness of the proposed model. © 2022 IEEE.

Mechanisms of action (MOA) for proxalutamide, an androgen receptor (AR) antagonist, for the treatment of mild, moderate and severe COVID-19 patients

As of November 2021, there were 21 million confirmed active cases of COVID-19, including 77,016 patients in serious or critical condition (virusncov.com). However, there are no effective oral drugs for the treatment of severe COVID 19 patients. We here discuss the mechanism of action for Proxalutaminde to treat mild, moderate and severe COVID-19 Patients. Cellular entry and infection of SARS-CoV-2 virus are mediated by two key proteins in host cells, angiotensin converting enzyme 2 (ACE2), a host transmembrane protein, providing the binding sites for SARS-CoV-2 on the host cell surface, and transmembrane protease serine 2 protein (TMPRSS2), priming the S protein of SARS-Cov-2 to facilitate the viral entry into the host cells. Both ACE2 and TMPRSS2 proteins are regulated by androgen receptor (AR) signaling. Previously, Proxalutamide has been reported to downregulate the expression of ACE2 and TMPRSS2 in cells derived from prostate, lung cancer and normal lung epithelial cells. In this study, we demonstrate that Proxalutamide inhibited the infection of SARS-COV-2 wild type, alpha and delta variants, with IC50s of 69, 48 and 39 nM, respectively. Moreover, Proxalutamide reduced SARS-COV-2 viral load in outpatients with COVID-19 (82% viral RT-PCR negative rate in active group vs. 31% in placebo group after treatment for 7 days (p-value<0.0001). Severe COVID-19 disease leads to cytokine storm resulting in pulmonary inflammation and extensive damage in lung and other organs. Anti-inflammatory drugs, including Baricitinib and dexamethasone, have shown limited clinical benefit for hospitalized COVID-19 patients. Therefore, more effective drugs are in urgent need for patients suffering from severe COVID-19. Recently, Proxalutamide has been reported to reduce the mortality rate (HR=0.16) and lung injury (by 57%, active drug vs placebo groups) in hospitalized patients with COVID-19 in an IIT phase III study. We presented here the mechanism of action of Proxalutamide for targeting cytokine storm in severe COVID-19 patients. Proxalutamide was demonstrated to activate nuclear factor erythroid 2-related factor 2 (Nrf2) in macrophages, which stimulates the antioxidant response element (ARE) for reducing cytokine storm-induced organ damage in COVID-19. In addition, Proxalutamide inhibited TNF alpha and IL-6 expression and blocked INF gamma signaling by downregulating STAT1 expression in immune cells. Importantly, Proxalutamide reduced inflammatory cells in lungs in a Poly (I:C), pseudoviral induced-lung injury animal models. Further, Proxalutamide decreased C-reactive protein, D-Dimer and improved lymphocyte count, biomarkers for COVID-19 progression in clinical studies. Together, these results provide a strong rationale for the treatment of severe COVID-19 patients with Proxalutamide.

[Progress in the study of antiviral activity of cepharanthine against SARS-CoV-2].

As a member of the dibenzyl isoquinoline alkaloid family, cepharathine is an alkaloid from the traditional Chinese medicine cepharathine, which is mainly used for treatment of leukopenia and other diseases. Recent studies of the inhibitory effect of cepharathine against SARS-CoV-2 have attracted widespread attention and aroused heated discussion. As the original discoverer of the anti-SARS-CoV-2 activity of cepharanthine, here we briefly summarize the discovery of cepharanthine and review important progress in relevant studies concerning the discovery and validation of anti-SARS-CoV-2 activity of cepharathine, its antiviral mechanisms and clinical trials of its applications in COVID-19 therapy.

New Advances in Nanomaterial-Based Antiviral Strategies

The ongoing coronavirus disease 2019 (COVID-19) pandemic and other major viral infectious diseases have become a significant threat to people's life and economic/social development. In recent years, with the development of nanotechnology, nanomaterial-based antiviral agents have been extensively studied. However, the clinical applications of antiviral nanomaterials are still limited. Herein, the recent advances in nanomaterial-based antiviral strategies, mainly including antiviral nanodrugs, drug nanocarriers, and nanovaccines, are summarized. The clinical challenges and prospects of nanomaterial-based antiviral strategies are also discussed.

Intelligent System for Distributed Social Governance Based on Big Data

In recent years, promoting the synergy and intelligence of social governance, and improving the social governance system of co-construction, co-governance and sharing are important development directions for the country. As a production factor, data plays an increasingly critical role in social governance. How to realize the secure query, collaborative management, and intelligent analysis of multi-party massive data is the key issue to improve the effectiveness of social governance. In major public events such as the prevention and control of the COVID-19, distributed social governance faces low computing efficiency, poor multi-party credible coordination, and difficult decision-making for complex tasks. In response to the above challenges, this study proposes on big data based distributed social governance intelligent system based on secure multi-party computing, blockchain technology, and precise intelligence theory. The proposed system can support various applications of social governance that provide decision-making support for the improvement of social governance in the new era. © Copyright 2022, Institute of Software, the Chinese Academy of Sciences. All rights reserved.

Using agent-based simulation to assess disease prevention measures during pandemics_

Despite the growing interest in macroscopic epidemiological models to deal with threats posed by pandemics such as COVID-19, little has been done regarding the assessment of disease spread in day-to-day life, especially within buildings such as supermarkets where people must obtain necessities at the risk of exposure to disease. Here, we propose an integrated customer shopping simulator including both shopper movement and choice behavior, using a force-based and discrete choice model, respectively. By a simple extension to the force-based model, we implement the following preventive measures currently taken by supermarkets;social distancing and one-way systems, and different customer habits, assessing them based on the average individual disease exposure and the time taken to complete shopping (shopping efficiency). Results show that maintaining social distance is an effective way to reduce exposure, but at the cost of shopping efficiency. We find that the one-way system is the optimal strategy for reducing exposure while minimizing the impact on shopping efficiency. Customers should also visit supermarkets less frequently, but buy more when they do, if they wish to minimize their exposure. We hope that this work demonstrates the potential of pedestrian dynamics simulations in assessing preventative measures during pandemics, particularly if it is validated using empirical data. © 2021 Chinese Physical Society.

Using agent-based simulation to assess disease prevention measures during pandemics*

Despite the growing interest in macroscopic epidemiological models to deal with threats posed by pandemics such as COVID-19, little has been done regarding the assessment of disease spread in day-to-day life, especially within buildings such as supermarkets where people must obtain necessities at the risk of exposure to disease. Here, we propose an integrated customer shopping simulator including both shopper movement and choice behavior, using a force-based and discrete choice model, respectively. By a simple extension to the force-based model, we implement the following preventive measures currently taken by supermarkets;social distancing and one-way systems, and different customer habits, assessing them based on the average individual disease exposure and the time taken to complete shopping (shopping efficiency). Results show that maintaining social distance is an effective way to reduce exposure, but at the cost of shopping efficiency. We find that the one-way system is the optimal strategy for reducing exposure while minimizing the impact on shopping efficiency. Customers should also visit supermarkets less frequently, but buy more when they do, if they wish to minimize their exposure. We hope that this work demonstrates the potential of pedestrian dynamics simulations in assessing preventative measures during pandemics, particularly if it is validated using empirical data.

3D Printed Mask Frames Improve the Inward Protection Efficiency of a Cloth Mask

Here, we show that improving the fit of a cloth mask using a low-cost 3D-printed frame significantly improves its inward protection efficiency for airborne particles known to transmit SARS-CoV-2. We found that a 3D-printed flexible frame (i.e., brace) increased the inward protection efficiency of a cotton-based cloth mask by 13-43% for particles ranging in size from 0.5-2 mu m relative to the efficiency obtained in the absence of the frame. For example, the use of a flexible form-fitting frame increased the inward protection efficiency for 0.5 and 1 mu m particles by 31 and 40%, respectively. Rapid prototyping of the mask frame geometry and material properties was also highlighted for optimization of the facial contact area and mechanical matching. This work demonstrates the opportunity for leveraging additive manufacturing processes for rapid prototyping of personalized and form-fitting personal protective equipment components at home and at point-of-care settings, such as mask frames.

Unveiling Potential Active Constituents and Pharmacological Mechanisms of Pudilanxiaoyan Oral Liquid for Anti-Coronavirus Pneumonia Using Network Pharmacology

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.

Factors for optimizing time performance of Modular Construction: A review and evidence from Huoshenshan Hospital construction

Modular Construction is one of the emerging construction technologies, which play an important role in saving construction time and have gradually become a hot topic in the field of construction. In order to further understand the advantage of Modular Construction in terms of time performance, the research aims to identify key factors that can affect the duration of Modular Construction projects. Based on the literature review of 23 related papers, 13 factors that have significant impacts on the duration of Modular Construction have been identified and summarized into five categories, namely cooperation among stakeholders, design, construction, abundant resources, and the support of the government. How these key factors have shortened the duration of Modular Construction in practice is also explained by the case of Huoshenshan hospital, a well-known emergency hospital built for COVID-19 in China, which used the Modular Construction method. © 2021 IEEE.

Research on the neurobiology of COVID-19

More studies have shown the neurological manifestations of the novel corona virus (COVID-19) and have inferred the molecular mechanism by which it invades the nervous system. The neurological aspect of the COVID-19 pandemic has been differently interpreted and dealt with in different parts of the world. To review the neurological manifestations and the neurovirulent mechanism by which CoV attacks the human nervous system and to examine different perspectives on this very same topic, the research on PubMed and ScienceDirect is conducted. The mechanisms that CoV enter and attack the nervous system and the subsequent neurologic manifestations have been proposed and now seems quite clear. However, more studies have to be done directly on the effect of COVID-19 on the CNS as well as the PNS. © The Authors, published by EDP Sciences, 2021.

Prevalence and impact factors of recurrent positive SARS-CoV-2 detection in 599 hospitalized COVID-19 patients

OBJECTIVES: Repeat-positive tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in individuals with coronavirus disease 2019 (COVID-19) were common. We aimed to investigate the rate and risk factors of recurrent positive detection of SARS-CoV-2 in hospitalized individuals with COVID-19. METHODS: Oropharyngeal and nasopharyngeal swabs (n = 3513) were collected to detect SARS-CoV-2 during the hospitalization. We analysed the recurrent positive rate after consecutive negative results and its relationship to demographic characteristics. RESULTS: Among 599 enrolled individuals with COVID-19, the median time for viral RNA shedding was 24 days (interquartile range 19-33 days). The positive rates of RT-PCR were 35.9% (215/599), 17.0% (65/383) and 12.4% (23/185) after one, two and three consecutive negative RT-PCR test results, respectively. Medians of Ct values of initial positive test, rebound positive test after two consecutive negative results, and rebound positive after three consecutive negative results were 28.8, 32.8 and 36.1, respectively. Compared with male patients, females had a significantly higher rate of recurrent positive RT-PCR after three consecutive negative results (18.2%, 18/99, versus 5.8%, 5/86;p 0.013). Older individuals (>=55 years) had a significantly higher rate of recurrent positive RT-PCR after one negative result (42.3%, 165/390, versus 23.9%, 50/209;p < 0.001). Nasopharyngeal swab tests produced a higher positive rate than oropharyngeal swab tests (37.3%, 152/408, versus 35.8%, 1111/3105). CONCLUSION: Our study revealed the prevalence and dynamic characteristics of recurrent positive RT-PCR to SARS-CoV-2. We showed that around 17.0% (65/383) of patients tested positive for SARS-CoV-2 after two consecutive negative results. Patients with a rebound positive RT-PCR test had a low viral load. Older age and being female were risk factors for recurrent positive results.

The short-term impact of COVID-19 epidemic on the migration of Chinese urban population and the evaluation of Chinese urban resilience

The COVID-19 epidemic in 2020 has a severe impact on China's national economic and social development. Evaluating the short-term impact of the COVID-19 epidemic and the recovery of China's economy and society, as well as revealing its spatiotemporal characteristics, can provide a strong support for the economic situation research and urban restoration of the normalized epidemic prevention and control stage. Based on Baidu migration big data from January 13 to April 8 in 2020 and that of the same period in history, this paper constructs the Relative Recovery Index (RRI) and Recovery Gap Index (RGI). Furthermore, it reveals the daily characteristics, stage characteristics, and spatiotemporal patterns of the short-term impact of the COVID-19 epidemic at multiple scales. The results are as follows: (1) The outbreak did not affect the travel rush before the Spring Festival. The process after the Spring Festival experienced a recovery stagnation period, a rapid recovery period, and a slow recovery period. The overall degree of recovery nationwide rose from less than 20% during the stagnation period to about 60% at the end of the rapid recovery period. The slow recovery period began on March 3, with a recovery index of over 70%. It will take a long time to fully recover to the historical level. (2) The intercity activities on weekends and in holidays were significantly weakened, especially in the central and northeastern regions. (3) The impact of the epidemic on each region is significantly different, in terms of the RRI, the western region > eastern region > central region > northeastern region. (4) The degree of recovery varies significantly between cities. From the Spring Festival to April 8th, the spatial pattern was high in the south and low in the north. According to the severity of the epidemic, Guangzhou, Shenzhen and Chongqing are in the cluster of High confirmed case-High recovery;Hebei, Tianjin, Heilongjiang, Henan, Anhui and Hunan are in the cluster of Low confirmed case-Low recovery. (5) With the effective control of the epidemic, the recovery gap has shifted from the large-scale insufficiency of labor force in the urban agglomerations such as Beijing-Tianjin-Hebei, the Yangtze River Delta, and the Pearl River Delta into the insufficiency in the central cities and some provincial capital cities. The results of this paper show that the use of spatiotemporal big data for real-time impact assessment of major public health emergencies have good application prospects. © 2020, Science Press. All right reserved.