Effects of Precipitation on the Air Quality Index, PM2.5 Levels and on the Dry Deposition of PCDD/Fs in the Ambient Air

The effects of 9 precipitation events in Suzhou City in Anhui Province, China, on the air quality index (AQI), PM2.5, and dry deposition flux of PCDD/Fs (polydibenzo-p-dioxins and polydibenzofurans) were investigated. A total of 7 precipitation events were positive contributes to the reduction of AQI;among them, the AQI were between 23 and 216, with an average of 75, the PM2.5 concentrations were between 5.0 and 169 mu g m-3, with an average of 25 mu g m-3, while the total-PCDD/F-TEQ dry deposition flux ranged from 149 to 1034 pg WHO2005-TEQ m-2 day-1 and averaged 315 pg WHO2005-TEQ m-2 day-1. By comparing the average AQI and PM2.5, respectively, during and after rainfall with that before rainfall, the results indicated that the average reduction fractions of AQI were 26% and 44%, respectively, while those of PM2.5 were 58% and 43%. In addition, the effect of precipitation on the average reduction fraction of total PCDD/F-TEQ dry deposition flux was 31%. However, in the other 2 AQI elevation events, the AQI were between 23 and 100, and averaged 51;when comparing the average AQI and PM2.5 concentrations, during and after the rain with that before the rain, the increases in AQI were 42% and 49%, respectively, while the increases in PM2.5 concentration were 26% and 29%, respectively. The above results show that, on the whole, rain and snow improved the air quality. This is because rainwater removes particles or dissolved gaseous pollutants from the atmosphere and brings aerosols to the ground. However, in some cases, the increase of source emissions and atmospheric vertical convection, the effect of precipitation or air humidity increased the AQI and elevated the concentration of PM2.5, and dry deposition flux of PCDD/Fs. The results of this study provide useful information for both scientific communities and air quality management.

Stability analysis of time-delayed SAIR model for duration of vaccine in the context of temporary immunity for COVID-19 situation

As the COVID-19 continues threatening public health worldwide, when to vaccinate the booster shots becomes the hot topic. In this paper, based on the characteristics of COVID-19 and its vaccine, an SAIR model associated with temporary immunity is proposed to study the effect on epidemic situation. Second, we theoretically analyze the existence and stability of equilibrium and the system undergoes Hopf bifurcation when delay passes through some critical values. Third, we study the dynamic properties of Hopf bifurcation and derive the normal form of Hopf bifurcation to determine the stability and direction of bifurcating periodic solutions. After that, numerical simulations are carried out to demonstrate the application of the theoretical results. Particularly, in order to ensure the validity, statistical analysis of data is conducted to determine the values for model parameters. Next, we study the impact of the infection rates on booster vaccination time to simulate the mutants, and the results are consistent with the facts. Finally, we predict the mean time of completing a round of vaccination worldwide with the help fitting and put forward some suggestions by comparing with the critical time of booster vaccination.

Collaborative adoption of blockchain technology: A supply chain contract perspective

The outbreak of COVID-19 has significantly affected the development of enterprises. In the post-pandemic era, blockchain technology has become one of the important technologies to help enterprises quickly gain market competitiveness. The heavy investment required of supply chain stakeholders to employ blockchain technology has hindered its adoption and application. To tackle this issue, this study aims to facilitate the adoption of blockchain technology in a supply chain consisting of a core enterprise and a small/medium-sized enterprise through an effective supply chain contract. We analyze the performance of a cost-sharing (CS) contract and a revenue-sharing (RS) contract and propose a new hybrid CS-RS contract for better performance. We conduct comparative analyses of the three contracts and find that the hybrid CS-RS contract can more effectively incentivize both parties to reach the highest level of blockchain technology adoption and achieve supply chain coordination.

An Automated Detection Approach of Protective Equipment Donning for Medical Staff under COVID-19 Using Deep Learning

Personal protective equipment (PPE) donning detection for medical staff is a key link of medical operation safety guarantee and is of great significance to combat COVID-19. However, the lack of dedicated datasets makes the scarce research on intelligence monitoring of workers??? PPE use in the field of healthcare. In this paper, we construct a dress codes dataset for medical staff under the epidemic. And based on this, we propose a PPE donning automatic detection approach using deep learning. With the participation of health care personnel, we organize 6 volunteers dressed in different combinations of PPE to simulate more dress situations in the preset structured environment, and an effective and robust dataset is constructed with a total of 5233 preprocessed images. Starting from the task???s dual requirements for speed and accuracy, we use the YOLOv4 convolutional neural network as our learning model to judge whether the donning of different PPE classes corresponds to the body parts of the medical staff meets the dress codes to ensure their self-protection safety. Experimental results show that compared with three typical deep -learning-based detection models, our method achieves a relatively optimal balance while ensuring high detection accuracy (84.14%), with faster processing time (42.02 ms) after the average analysis of 17 classes of PPE donning situation. Overall, this research focuses on the automatic detection of worker safety protection for the first time in healthcare, which will help to improve its technical level of risk management and the ability to respond to potentially hazardous events.

Investigation and analysis of work situation of professional and technical personnel in Beijing Centers for Disease Prevention and Control during the COVID-19 epidemic

Objective To analyze the work situation of the personnel in Beijing Centers for Disease Prevention and Control during the novel coronavirns disease 2019 (C0VID-19) epidemic，and to provide references for improving the construction of the capital5 s disease control and prevention system. Methods Cross-sectional survey and cluster sanpling methods were used. A total of 422 municipal-level and 664 district-level professional technicians from CDCs who were mainly involved in epidemic prevention and control in Beijing were included in the study. Self-designed questionnaires were used to collect the basic information, work intensity and satisfaction and other data. The statistical description and test analysis were carried out. Results Among professionals, 64. 36% had nornal workload, and 76. 89% had overload during the epidemic prevention and control period. The proportion of disease control personnel expressing dissatisfaction "with the usual salary level "was 54. 51%, and the satisfaction with the professional title promotion w-as mostly at the average level (45. 58%). The proportions of satisfaction with the prevention and control work arrangements and logistical support during the COVID-19 epidemic were 49. 08% and 54. 42%, respectively. Only 21. 73% professionals were satisfied with the temporar w-ork subsidy. From the perspective of population distribution, staffs at the municipal and district levels and in different job positions were mainly dissatisfied with the salar level (all P<0. 05). Most of staffs who undertook different prevention and control responsibilities were satisfied with the work arrangements and logistics support (all P<0. 05), but they w-ere dissatisfied with the temporar work subsidies (H = 27. 076, P = 0. 012). Among the survey respondents, 44.48% had thoughts of resigning. Regardless of the municipal and district levels, different professional titles or positions, the wdllingness to resign was generally high (all P>0. 05). The primar reason for wanting to leave was the low salary level, followed by difficulty in promotion of professional titles and poor development prospects which were also major considerations. Conclusion It is suggested to improve the stability of CDCs staffs and promote the high-quality and sustainable development of the disease control and prevention system by improving the personnel allocation, strengthening the interdisciplinary talent reserve, improving the salary system and optimizing the professional title appointment mechanism.

Prediction and Analysis of COVID-19 Epidemic Situation via Modified SEIR Model with Asymptomatic Infection

This paper deals with the prediction and analysis of COVID-19 epidemic situation based on a modified SEIR model with asymptomatic infection. First, by considering the self-isolation and asymptomatic infection, a modified SEIR model is proposed to predict and evaluate the epidemic situation of COVID-19 in Hubei Province, China. Then, based on the daily data reported by the Health Commission of Hubei Province, the modified SEIR model is solved numerically, and the parameters of the modified model are inverted by the least square method. Third, based on the modified model, the epidemic situation of COVID-19 in Hubei Province is predicted and verified. The simulation results show that the modified SEIR model is significant and reliable to describe the spread property of the COVID-19, thereby providing a potential theoretical support for the decision-making of epidemic prevention and control in the future. © 2021 IEEE.

Reversibility between 'cocreation' and 'codestruction': evidence from Chinese travel livestreaming

Travel livestreaming has brought light to the tourism industry during the darkness of the COVID-19 pandemic. Although travel livestreaming is in full swing in practice, academic research on this subject is somewhat lagging. Value dimensions/drivers derived from service field may contribute to the overall value of relevant stakeholders. The aim of this preliminary study is to identify emotional experiences from the perspective of travel livestream viewers, revealing the drivers of value cocreation and codestruction. Based on grounded theory, data were collected through in-depth semistructured interviews, and 11 functional dimensions were revealed, namely, authenticity and immersion, entertainment, remuneration, uniqueness, symmetry, utility and convenience, interactivity, technical support, livestreamer characteristics, and regulators. These dimensions are contributed by multiple entities, including travel suppliers, livestreamers, live platforms, other viewers, individuals, and the external environment. These findings provide evidence of the reversibility of cocreation and codestruction and makes contributions to both theory and practice, especially regarding implications for future research.

Negotiating interdisciplinary practice under the COVID-19 crisis: opportunities and challenges for tourism research

Purpose COVID-19 is currently the most serious crisis facing the world, and scholars in the medical and social sciences are working to save lives and mitigate the societal effects of the pandemic. This global public health emergency requires interdisciplinary work to provide comprehensive insight into a rapidly changing situation. However, attempts to integrate the medical and social sciences have met several barriers. This paper aims to identify feasible research opportunities for interdisciplinary studies across tourism and public health regarding COVID-19. Design/methodology/approach This paper presents a critical review of the literature and generates corresponding conceptual and theoretical frameworks to provide an in-depth discussion. Findings Tourism-related issues of destination management policies and capital are addressed from an interdisciplinary perspective. The conclusions encourage interdisciplinary research into global health problems, which will promote tourism's renaissance and sustainable development while enhancing social welfare. Practical implications This study focuses on integrating tourism and public health to offer stakeholders recommendations regarding destination management and tourism industry recovery amid COVID-19. Originality/value This paper represents a frontier study, critically uncovering a host of innovative interdisciplinary research directions and tourism-focused collaboration opportunities related to COVID-19.

Research progress on DNA vaccines against SARS-CoV-2

COVID-19 outbreak poses a serious threat to global public health. The research and development of COVID-19 vaccines around the world are moving forward with various technical tactics in a positive way. After the traditional live-attenuated virus vaccine, inactive virus vaccine and genetic engineering subunit vaccine, nucleic acid vaccine is called "the third generation vaccine technology" in the industry, including DNA vaccine and mRNA vaccine. Each has its own advantages. This article reviews the development history of DNA vaccine. With over ten years of improvement, the delivery efficiency of DNA vaccine has been greatly improved, especially in the treatment of emerging infectious diseases including SARS, highly pathogenic influenza, MERS, ZIKA and Rift Valley fever, the preliminary clinical benefit of which has been verified. This review aims to discuss the research and development of DNA vaccines against pandemics, especially the design, optimization, safety and effectiveness of COVID-19 DNA vaccines, and suggest the direction of improvement of DNA vaccine technology.

Medicinal chemistry strategies in seeking coronavirus inhibitors

The epidemic caused by coronavirus poses a serious threat to human health, but there is no specific drug or vaccine for the treatment of this kind of virus infection. Herein, this article selects typical case studies in recent years and reviews the medicinal chemistry strategies of anti-SARS-CoV, MERS-CoV and other coronavirus drugs from the perspective of medicinal chemistry, and tries to provide some clues to current drug research against-SARS-CoV-2.

Cloud-based Livestock Monitoring System Using RFID and Blockchain Technology

Food security and quality has become an increasingly concerned issue around the world. Recent food falsification cases have caused vast public health risk and economic damage while eroding consumers' trust. Ever more prevalent is the danger of infectious disease among livestock that may cause serious economic damage while adding uncertainty to the world's food supply. Animal-human transmitted diseases infect humans and are the culprits for the 2003 SARS, 2009 H1N1 Avian Flu, and 2019 Coronavirus outbreaks. Livestock monitoring is a promising approach in disease warning, authenticating food supply chain and tracking sources of contamination in the production cycle. One way of addressing the traceability issue and ensuring accountability is by utilizing blockchain technology as a ledger. This paper proposes a novel method to apply blockchain technology to ensure traceability and authenticity in the livestock supply chain, hence making the livestock farming process more scientific and trustworthy. © 2020 IEEE.

Cleaning and disinfection in health care settings during the COVID-19 outbreak

Cleaning and disinfection of the health care environment plays an important role in reducing indirect transmission of SARS-CoV-2 - the virus responsible for COVID-19. © 2020, International Centre for Eye Health.

Exploration on active compounds of Feiduqing for treatment of COVID-19 based on network pharmacology and molecular docking [Chinese]

Objective: To explore the active compounds of Feiduqing in the treatment of coronavirus disease 2019 (COVID-19) pneumonia. Method(s): The Chinese medicine system pharmacology analysis platform (TCMSP) was used to obtain the three Chinese medicine-related components and targets of Oroxylum indicum, Gardenia jasminoides and Sophora flavescens of Feiduqing, and the genes corresponding to the targets were queried through the UniProt database. The STRING platform was used to build the target PPI network. DAVID was used to perform GO biological processes and KEGG pathway enrichment analysis was used to perform network topology analysis on core targets. Cytoscape 3.7.0 was used to construct a component-target network analysis to predict the mechanism of Feiduqing. The core active compound of Feiduqing was molecularly docked with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) 3CL hydrolase, and the first three compounds with the lowest binding energy were docked with angiotensin converting enzyme II (ACE2). Result(s): The component-target network included 269 nodes and 4 204 edges, including 50 components such as quercetin, beta-sitosterol, kaempferol, etc, and key targets included JUN, AKT1, TP53, PTGS2, FOS, ESR1, etc. The function enrichment analysis of GO yielded 2 187 (P 0.05), including 1 877 biological process (BP) entries, 105 cellular components (CC) entries, and 205 molecular functions (MF) entries. Twenty-five signal pathways were screened by KEGG enrichment analysis (P 0.05), mainly including hepatitis B, pathways in cancer, TNF signaling pathway, pancreatic cancer, toxoplasmosis pathway, etc. The active ingredients with the lowest molecular docking binding energy acting on SARS-CoV-2 3CL hydrolase were luteolin (-26.78 kJ/mol), quercetin (-26.36 kJ/mol), 8-prenyl-kaempferol (-25.94 kJ/mol). Conclusion(s): The active compound of Feiduqing may have a therapeutic effect on COVID-19 through the action on targets such as JUN, AKT1, TP53, PTGS2, FOS, ESR1, binding with angiotensin converting enzyme II (ACE2) and regulating many signaling pathways. Copyright © 2020, Editorial Office of Chinese Traditional and Herbal Drugs. All right reserved.