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COVID-19 pandemic affected the entire globe and resulted in millions of deaths. Besides human-to-human respiratory droplets transmission, contact with aerosol-infected surfaces is an important way of transmitting this virus. The virus can be detected on many surfaces for a long time, in aerosols for at least 3 hours, and on plastic surfaces for up to 72 hours. Hence, it is crucial to determine how to disinfect the environment. Several biocidal agents have been used to clean the environment. Apart from biocidal agents, ultraviolet (UV) irradiation had also been used for environmental disinfection. However, there are several UV sources and systems with different wavelengths were used for disinfection and there was a wide range of effectiveness in disinfection with different modules. Thus, it was necessary to comprehensively review the current understanding of UV light used in disinfection to advise regarding UV light for environmental disinfection. Using the keywords COVID-19, UV light, and disinfection from 2020 to 2022, we searched various databases for articles online. We found various devices that had been studied for disinfection of SARS-CoV-2 with UV, such as monochromatic UV-C lamps, UV-LED light, broad- spectrum UV light devices, and excimer lamps. As a monochromatic UV source, different types of lamps were reported to have an excellent effect on disinfection, with the most common wavelength used for disinfection being 254 nm. As a broad-spectrum wavelength light, which is from 200 to 280 nm, one- minute exposure is enough to cause a 3 log10 reduction of viral load, which means 99.97% in disinfection. UV light are effective in coronavirus disinfection. Compared with the chemical agent, it is more environmentally friendly. To apply the UV light to environmental disinfection, five minutes is enough to reach 99.99% disinfection of the SARS-CoV-2 virus, for broad-spectrum wavelength light placed within one meter from the target surface. [ FROM AUTHOR] Copyright of International Journal of Infectious Diseases is the property of Elsevier B.V. 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.)
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The emergence of the Covid-19 pandemic has drawn great attention to vulnerable people affected by major diseases. Among them, Alzheimer's disease (AD) is the most prevalent disease. However, a long-standing challenge is to achieve early diagnosis of AD by detecting biomarkers such as amyloid beta (Aβ42), thus avoiding the labor of specialized hospital personnel and the high cost of imaging examinations using positron emission tomography. In this paper, we report a straightforward approach to realize a non-invasive lab-around fiber (LaF) optical sensor for AD biomarker detection, which is based on a tilted fiber Bragg grating (TFBG) combined with a nanoscale metallic thin film. We successfully demonstrated the detection of Aβ42 in complex biological matrices with a detection limit of 5 pg/mL. Therefore, our TFBG-SPR biosensor platform enables large-scale early disease screening and has great potential for clinical applications in early AD diagnosis. © 2022 IEEE.
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Due to the impact of the COVID-19, online teaching has become a common teaching method at present, and in-depth research on online teaching methods is of great practical significance. In the computer network course, we organize the online teaching process according to the BOPPPS model combined with online teaching tools such as DingTalk and Rain Classroom. We use Rain Classroom to seize the pre-class preview and use DingTalk to achieve participatory online interactive teaching and complete homework correction and online Q&A. The results of the questionnaire show that the above-mentioned teaching organization method can enable students to actively participate in interactive teaching, and students' approval of online teaching is relatively high. © 2022 IEEE.
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By using a technology acceptance model (TAM) on survey results collected from medical universities of China, this paper aims to uncover the major factors that affect medical students' acceptance of blended learning during the Covid-19 period. 1238 medical students completed the study survey after experiencing 3 months of blended learning. The results show that the social influence (SIN) and perceived ease of use (PEOU) have positive impacts on perceived usefulness (PU);PU has positive impacts on learning motivation (LM);LM can moderately affect learning satisfaction (LS). There is also a positive relationship between SIN and LS. It is worth noting that SIN as an intermediary factor directly affects PEOU, PU and LS. In fact, SIN is considered the key factor that affect student satisfaction of blended learning during Covid-19. © 2022 IEEE.
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Vaccines are crucial for controlling deadly diseases, and how to persuade people to get vaccinated has become a hot topic in enhancing public health benefits. One way to increase the vaccination rate is to raise public awareness of the importance of vaccines through advertising. As an effective and cost-friendly approach, goal framing has been widely used in vaccine advertising. However, the literature has mixed findings about whether positive or negative goal framing is more effective in persuading people to get vaccinated. The present study aims to investigate how temporal distance (present vs. future) interacts with different types of goal framing (positive vs. negative) in persuading people to get the COVID-19 vaccine. We hypothesized that negative goal framing is more persuasive when the advertising focuses on present outcomes, while positive goal framing is more effective when combined with future- focused outcomes. We further hypothesized that the inner mechanism is the intertemporal asymmetry of approach and avoidance motivation. More specifically, the avoidance motivation induced by a negative frame is stronger in the present, while the approach motivation induced by a positive frame is stronger in the future. The perceived risk of COVID-19 moderated this effect. Four studies were conducted to examine our hypotheses. Study 1 was conducted to preliminarily investigate how goal framing and temporal distance jointly influence willingness to get the COVID-19 vaccine. The aim of Study 2 was to verify the mediating effect of approach and avoidance motivation in a different advertising setting, as well as to rule out the potential mediators of the construal level and positive/ negative emotions. In Study 3, we further tested the mediators by manipulating participants' approach and avoidance motivation. Study 4 was a quasi-experiment in which we recruited participants from areas with different levels of COVID-19 risk to test how perceived risk moderated the interaction effect of goal framing and temporal distance. The results showed that a negative goal frame was more persuasive when combined with present-focused advertising, while a positive goal frame was more effective when combined with future- focused advertising (Study 1, N = 363). Avoidance motivation mediated the relationship between the goal frame and vaccine uptake in the present context, while approach motivation mediated the relationship between the goal frame and vaccine uptake in the future context (Study 2, N = 292). The results in Study 3 ( N = 347) revealed that approach motivation priming increases the persuasiveness of the present-positive frame, while avoidance motivation priming increases the persuasiveness of the future- negative frame. COVID-19 risk also had an impact on the relationship between goal framing and temporal distance on vaccine uptake. When the COVID-19 risk was high, the difference in vaccine uptake between present-positive and present-negative conditions disappeared, while the future-positive frame was still more persuasive than the future- negative frame (Study 4, N = 423). In conclusion, the present study found an interactive effect of goal framing and temporal distance in persuading people to get the COVID-19 vaccine. Avoidance/approach motivation mediates the relationship between goal framing and vaccine uptake in the present/future temporal context. The perceived COVID risk further moderated the interaction effect. The present study contributes to both the framing and approachavoidance motivation literature and sheds light on future practices in persuading people to get the COVID vaccine and promoting the uptake of other vaccines.
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With the rapid development of China's economy, enterprises need to plan their logistics transportation routes reasonably in advance. This will make the transportation service more efficient. For the supplier's transportation service problem, an analysis method of critical path nodes is provided and a multi-supplier collaborative transportation strategy is designed in this article. First, a model for minimising the transportation cost was established, then a path diagram was simulated and the optimal and alternative transportation paths of suppliers based on the k-shortest path algorithm were calculated. In addition, path node availability during COVID-19 is used as a research context in this article. A multi-stage path analysis method was provided by discussing different cases of critical path nodes, which can make a reasonable selection of paths in a timely and effective manner. Finally, simulations of collaborative transportation for suppliers were performed in three scenarios and the results verified the effectiveness of the collaborative transportation strategy. The proposed collaborative transportation strategy of suppliers not only strengthened the synergistic cooperation among suppliers, but also cultivated the potential customer for suppliers in this article. Furthermore, the strategy could improve the flexibility of the supply chain, maximise the overall efficiency and also provide a new solution for the development of logistics and transportation services.
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We construct a pandemic-induced fear (PIF) index to measure fear of the COVID-19 pandemic using Internet search volumes of the Chinese local search engine and empirically investigate the impact of fear of the pandemic on Chinese stock market returns. A reduced-bias estimation approach for multivariate regression is employed to address the issue of small-sample bias. We find that the PIF index has a negative and significant impact on cumulative stock market returns. The impact of PIF is persistent, which can be explained by mispricing from investors' excessive pessimism. We further reveal that the PIF index directly predicts stock market returns through noise trading. Investors' Internet search behaviors enhance the fear of the pandemic, and pandemic-induced fear determines future stock market returns, rather than the number of cases and deaths caused by the COVID-19 pandemic.
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When using the traditional SEIR infectious disease model to predict the trend of novel coronavirus pneumonia epidemic, numerous initial parameters need to be tuned, and the parameters cannot change over time during the prediction process, which reduces the accuracy of the model. Firstly, thesis used a logistic model to preprocess the SEIR model parameters and proposed a SEIR model based on time series recovery rate optimization with a new parameter of effective immunity rate. Secondly, the model was trained with epidemic data from domestic and foreign provinces and cities, and the usability of the model was demonstrated experimentally, and the mean absolute percentage error (MAPE) and goodness of fit (R2) were used to compare with other models, which proved the superiority of the model prediction and indicated further research directions. © 2022 IEEE.
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Background: This is a population-based retrospective study of neurological and cardiac complications of COVID-19 among Ontario visible minorities: Chinese and South Asian Canadians Methods: From January 1, 2020 to September 30, 2020, using the last name algorithm, rates and types of cardiac and neurological complication of these two cohorts along with the general population in Ontario with COVID-19 were analysed by Institue of Clinical Evaluative Sciences. Results: Preliminary results show that Chinese-Canadians (N= 1,186) with COVID-19 are older with a mean age of 50.74 years old compared to general population (N= 42,547) of 47.57 years old (P< .001), while South Asians (N= 3,459) have a younger mean age of 42.08 years old (P< .001). Total cardiac and neurological complication rates, hospitalization rates and ICU admission rates are all higher for Chinese-Canadians while they are lower in South Asians and all achieving statistical significance (P < .001). Overall mortality rate is significantly higher for Chinese-Canadians at 8.1% vs 5.0% general population (P < .001). Conclusions: Chinese-Canadians with COVID-19 in Ontario were much older and have higher cardiac and neurological complication rates and overall mortality rate than the general population. These data have significant implications for proper prevention and appropriate management for these vulnerble elderly Chinese-Canadians.
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This paper considers the novel fractional-order operator developed by Atangana-Baleanu for transmission dynamics of the SARS-CoV-2 epidemic. Assuming the importance of the non-local Atangana-Baleanu fractional-order approach, the transmission mechanism of SARS-CoV-2 has been investigated while taking into account different phases of infection and var-ious transmission routes of the disease. To conduct the proposed study, first of all, we shall formu-late the model by using the classical operator of ordinary derivatives. We utilize the fractional order derivative and the model will be extended to a model containing fractional order derivatives. The operator being used is the fractional differential operator and has fractional order U1. The model is analyzed further and some basic aspects of the model are investigated besides calculating the basic reproduction number and the possible equilibria of the proposed model. The equilibria of the model are examined for stability purposes and necessary conditions for stability are obtained. Stability is also necessary in terms of numerical setup. The theory of non-linear functional analysis is employed and Ulam-Hyers's stability of the model is presented. The approach of newton's polynomial is con-sidered and a new numerical scheme is developed which helped in presenting an iterative process for the proposed ABC system. Based on this scheme, sample curves are obtained for various values of U1 and a pattern is derived between the dynamics of the infection and the order of the derivative. Further simulations are presented which show the cruciality and importance of various parameters and the impact of such parameters on the dynamics and control of the disease is presented. The findings of this study will also provide strong conceptual insights into the mechanisms of contagious diseases, assisting global professionals in developing control policies.(c) 2022 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).
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The link between the supply and demand sides of manufacturing has become increasingly frail as a result of the COVID-19 outbreak. In this paper, we analyze the key path nodes and propose a closed-loop path value-added strategy for logistics services to optimize the path cost on the supply and demand side under the influence of the COVID-19 epidemic. First, the k shortest path algorithm determines the optional paths in accordance with the structure of the road network made up of all path nodes. Second, closed-loop transportation routes for both forward and reverse transit are constructed using the optional paths. Finally, the transportation service strategy with the optimal choice of transportation cost and transportation time under a multi-stage epidemic is obtained. The method can provide a reference for logistics services. © 2022 IEEE.
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Most of the previous studies on the impact of risk perception on travel intention are based on an individual psychological perspective, and the understanding based on the perspective of macropsychology is insufficient. Analyzing the temporal and spatial characteristics of risk perception theory at the macropsychological and regional levels will expand the scope of risk perception theory, which may help to promote the orderly recovery of tourism activities under the normalization of epidemics at the regional level. This study uses Baidu big data, through a panel VAR analysis, to explore the impact of people's epidemic risk perception on travelers intentions from a macropsychological level and to analyze the temporal and spatial differences of this impact. From a temporal perspective, this study found that the early stage of epidemic risk perception had a negative impact on travel intentions, and later, a compensatory effect on travelers intentions appeared. From the perspective of risks at different threat levels, the Wuhan epidemic with a high degree of threat had a greater impact, while foreign epidemics had less impact. From the perspective of spatial differences, this study indicated that the negative impact of attention to epidemics on attention to tourism basically shows a gradual decay from the core to secondary and then to peripheral areas. This research will reveal some new findings on the impact of perceived risk on behavior intention at the temporal and spatial levels, and will have certain reference value for regional tourism restoration and marketing under the influence of epidemics. © The Author(s) 2022.
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The COVID-19 pandemic has made reaching sustainability and net-zero goals more challenging. The primary emphasis on health-related concerns constrains the pro-environmental movements' ability to advance. Particularly in developing nations, financial institutions may be critical in promoting green recovery. This research uses data from 30 Chinese provinces from 2005 to 2021 to investigate whether adaptation preparation's financial mechanism affects the impact of climate change and green economic development (a measure of productivity growth). We applied numerous robustness tests for the validation of empirical findings of the study. The results shown that increased financial mechanisms have a considerable negative impact on economic development and productivity growth. However, the severity of these impacts depends heavily on the degree of adaptive preparedness. We find that increased financial inclusion may lead to a revival in economic development for provinces with improved adaptability capabilities (banking sector). On the other hand, climate change may have long-term negative effects on economic development and productivity growth in places with a limited capacity for adaptation. Therefore, in China financial mechanisms might affect green economic development and climate change mitigation are the quality of institutions and income level. The development plan must included by the practioners for furthure policy planning about climate adaptation.
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Objective: To explore the mechanism of Xuanbai chengqi decoction and Sangbei power in the treatment of epidemic-closed lung type COVID-19 by network pharmacology. Method(s): The potential blood active components and gene targets of Xuanbai chengqi decoction and Sangbei power were screened and predicted by TCMSP;The angiotensin converting enzyme 2(ACE2)related gene targets were downloaded;The PPI network of components-targets was plotted by STRING database.The intersection of ACE2-related genes and target genes of Xuanbai chengqi decoction and Sangbei power was extracted;The DAVID database was used to analyze and screen the key targets and mechanisms of Xuanbai chengqi decoction and Sangbei power. Result(s): A total of 496 active ingredients related to Xuanbai chengqi decoction and Sangbei power were retrieved from TCMSP database.According to the pharmacokinetic parameters, 78 active components in blood were screened and 761 targets were retrieved.5 556 ACE2-related genes were downloaded.49 key genes were obtained after the intersection of Chinese medicine component targets and ACE2 related gene targets;The genes affected by Xuanbai chengqi decoction and Sangbei power were mainly involved in cytoketone metabolism, intracellular protein transport, internal peptidase inhibitor activity and others, which were mainly related to the signaling pathway of the Jak-STAT, the intestinal immune network pathway of producing IgA, complement and coagulation cascade pathway, etc. Conclusion(s): Xuanbai chengqi decoction and Sangbei power can act on ACE2 through 49 gene loci, and its mechanism is related to cellular ketone metabolism and inhibition of protein entry into cells. Copyright © 2021, Central Station of Chinese Medicinal Materials Information, National Medical Products Administration. All right reserved.
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Parkinson's disease(PD) is a progressive neu-rodegenerative disease defined by clinical syndrome including bradykinesia, tremor and postural instability. The PD-related disability and impairment are usually monitored by clinicals using the MDS-UPDRS scale. However, due to COVID-19, it became much harder for the patients to reach hospitals and obtain necessary assessment and treatment. Nowadays, 2D videos are easily accessible and can be a promising so-lution for on-site and remote diagnosis of movement disorder. Inspired by the frequency-based video processing mechanism of human visual system, we propose a video-based SlowFast GCN network to quantify the gait disorder. The model consists of two parts: the fast pathway and the slow pathway. The former detects characteristics such as tremor and bilateral asymmetry, while the latter extracts characteristics such as bradykinesia and freezing of gait. Furthermore, in order to investigate the influence of age on the model performance, an aged control group and a young control group were set up for verification. The proposed model was evaluated on a video dataset collected from 68 participants. We achieved a balanced accuracy of 87.5% and precision of 87.9%, which outperformed existing competing methods. When replacing the young healthy controls with the same number of older controls, the balanced accuracy and precision were decreased by 10.4% and 9.7%, which indicates that age has a significant effect on the model perfomance. © 2022 IEEE.
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The classical SIR model is a fundamental building block in most epidemiological models. Despite its widespread use, its properties in filtering and estimation applications are much less well explored. Independently of how the basic SIR model is integrated into more complex models, the fundamental question is whether the states and parameters can be estimated from a fusion of available numeric measurements. The problem studied in this paper focuses on the parameter and state estimation of a stochastic SIR model from assumed direct measurements of the number of infected people in the population, and the generalisation to other measurements is left for future research. In terms of parameter estimation, two components are discussed separately. The first component is model parameter estimation assuming that the all states are measured directly. The second component is state estimation assuming known parameters. These two components are combined into an iterative state and parameter estimator. This iterative method is compared to a straightforward approach based on state augmentation of the unknown parameters. Feasibility of the problem is studied from an information-theoretic point of view using the Cramér Rao Lower Bound (CRLB). Using simulated data resembling the first wave of Covid-19 in Sweden, the iterative method outperforms the state augmentation approach. © 2022 IEEE.