ABSTRACT
The contamination of Atlantic salmon with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has impeded the development of the cold-chain food industry and posed possible risks to the population. Electron beam (E-beam) irradiation under 2, 4, 7, and 10 kGy can effectively inactivate SARS-CoV-2 in cold-chain seafood. However, there are few statistics about the quality changes of salmon exposed to these irradiation dosages. This work demonstrated that E-beam irradiation at dosages capable of killing SARS-CoV-2 induced lipid oxidation, decreased vitamin A content, and increased some amino acids and ash content. In addition, irradiation altered the textural features of salmon, such as its hardness, resilience, cohesiveness, and chewiness. The irradiation considerably affected the L*, a*, and b* values of salmon, with the L* value increasing and a*, b* values decreasing. There was no significant difference in the sensory evaluation of control and irradiated salmon. It was shown that irradiation with 2−7 kGy E-beam did not significantly degrade quality. The inactivation of SARS-CoV-2 in salmon is advised at a dose of 2 kGy. © 2022
ABSTRACT
Wireless sensor networks (WSNs) are composed of a large number of spatially distributed sensor nodes to monitor and transmit information from the environment. However, the batteries used by these sensor nodes have limited energy and cannot be charged or replaced due to the harsh deployment environment. This energy limitation will seriously affect the lifetime of the network. Therefore, the purpose of this research is to reduce energy consumption and balance the load of sensor nodes by clustering routing protocols, so as to prolong the lifetime of the network. First, the coronavirus herd immune optimizer is improved and used to optimize the network clustering. Second, the cluster heads (CHs) are selected according to the energy and location factors in the clusters, and a reasonable CH replacement mechanism is designed to avoid the extra communication energy consumption caused by the frequent replacement of CHs. Finally, a multihop routing mechanism between the CHs and the base station is constructed by Q-learning. Simulation results show that the proposed work can improve the structure of clusters, enhance the load balance of nodes, reduce network energy consumption, and prolong the network lifetime. The appearance time of the first energy-depleted node is delayed by 25.8%, 85.9%, and 162.2% compared with IGWO, ACA-LEACH, and DEAL in the monitoring area of $300×300 m, respectively. In addition, the proposed protocol shows better adaptability in varying dynamic conditions. © 2001-2012 IEEE.
ABSTRACT
The spread of COVID-19 has a great impact on public transport which is closely related to social life. As an essential carrier of the cities, metro has become an important object of concern during the epidemic. Due to the high infection risk of COVID-19 in public space, it is necessary to quantitatively evaluate and perform corresponding epidemic control measures on reducing public health risks in metro station. In this paper, three strategies of passenger rescheduling, i.e. controlling the flows of inbound and outbound passengers in the station, setting route guidance in the crucial areas and shortening the interval time of train, are simulated and analyzed based on Anylogic. The performances of different strategies are characterized and evaluated by the important parameters, which include local passengers' density, inbound and outbound time. Finally, the optimization experiments based on an objective function are carried out to obtain the best strategy combination considering passengers' health safety and travel efficiency. The crucial areas with high density are obtained from the simulation results of the initial model. The three independent strategies are helpful in reducing the maximum passengers' density and average travel time. The optimization results of strategy combination and the specific parameters of each strategy are obtained by the final simulation experiment. The research findings are important reference to enhance the present health risk management level and provide specific measures of passenger organization in metro station under COVID-19. © 2023 Elsevier Ltd
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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. © 2021 Informa UK Limited, trading as Taylor & Francis Group.
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In pricing extreme mortality risk, it is commonly assumed that interest rate and mortality rate are independent. However, the COVID-19 pandemic calls this assumption into question. In this paper, we employ a bivariate affine jump-diffusion model to describe the joint dynamics of interest rate and excess mortality, allowing for both correlated diffusions and joint jumps. Utilizing the latest U.S. mortality and interest rate data, we find a significant negative correlation between interest rate and excess mortality, and a much higher jump intensity when the pandemic experience is considered. Moreover, we construct a risk-neutral pricing measure that accounts for both diffusion and jump risk premia, and we solve for the market prices of risk based on mortality bond prices. Our results show that the pandemic experience can drastically change investors' perception of the mortality risk market in the post-pandemic era. © 2022 Elsevier B.V.
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With the wide spread of COVID-19, numerous cases demonstrate that proper ventilation method can reduce the cross-infection risk obviously. Interactive cascade ventilation (ICV) as a recently proposed ventilation method, the advantage of indoor environment construction has been proven. However, few studies are conducted to investigate the virus prevention and control characteristics of ICV, which is particularly important under epidemic normalizing. Hence, this study explored and compared the cross-infection control performance of three ventilation strategies, namely mixing ventilation (MV), stratum ventilation (SV), and interactive cascade ventilation (ICV), with a validated CFD model. A typical office was selected as the background scene, where an infected person coughs, sneezes with standing or sitting at different positions. Exposure doses, health infection risk, and disease burden (DB) were employed as the evaluation indicators under different ventilation methods of multi-scenario. The research results indicated that the average aerosol exposure dose among the human respiratory region under ICV was 0.29 g/day, which was reduced by 67 % and 50 % compared with MV and SV. In addition, only in ICV can the health infection risk meets the EPA standard. The average disease health burden for exposed persons under ICV was 0.93 × 10−6 DALYs pppy, which was 37 % and 70 % lower than SV and MV. The findings obtained from this study confirm that ICV performs excellently in reducing the cross-infection risk, providing the theoretical basis for future epidemic prevention and control. © 2022 Elsevier Ltd
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It is necessary to accurately calculate ship carbon emissions for shipping suitability. The state-of-the-art approaches could arguably not be able to estimate ship carbon emissions accurately due to the uncertainties of Ship Technical Specification Database (STSD) and the geographical and temporal breakpoints in Automatic Identification System (AIS) data, hence requiring a new methodology to be developed to address such defects and further improve the accuracy of emission estimation. Firstly, a novel STSD iterative repair model is proposed based on the random forest algorithm by the incorporation of13 ship technical parameters. The repair model is scalable and can substantially improve the quality of STSD. Secondly, a new ship AIS trajectory segmentation algorithm based on ST-DBSCAN is developed, which effectively eliminates the impact of geographical and temporal AIS breakpoints on emission estimation. It can accurately identify the ships' berthing and anchoring trajectories and reasonably segment the trajectories. Finally, based on this proposed framework, the ship carbon dioxide emissions within the scope of domestic emission control areas (DECA) along the coast of China are estimated. The experiment results indicate that the proposed STSD repair model is highly credible due to the significant connections between ship technical parameters. In addition, the emission analysis shows that, within the scope of China's DECA, the berthing period of ships is longer owing to the joint effects of coastal operation features and the strict quarantine measures under the COVID-19 pandemic, which highlights the emissions produced by ship auxiliary engines and boilers. The carbon intensity of most coastal provinces in China is relatively high, reflecting the urgent demand for the transformation and updates of the economic development models. Based on the theoretical models and results, this study recommends a five-stage decarbonization scheme for China's DECA to advance its decarbonization process. © 2022 Elsevier Ltd
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Modular construction has been implemented to achieve shorter project duration, lower cost, and higher productivity for construction projects. This option is especially helpful to reduce on-site activities and interaction under and after COVID impact. However, additional planning and support in engineering, procurement, and delivery are required to facilitate modular construction. Unreliable prefabrication and delivery can deteriorate subsequent activity productivity and overall project performance. This research aims to develop an automatic incentive—penalty enforcement system for modular construction based on the situation awareness of delivery tracking. The research selected a high-rise residential project in Singapore as a case study. The project used modular construction for making and installing 120 Prefabricated Bathroom Units. Based on the empirical data of delivery, on-site lifting, and installation, we built STROBOSCOPE simulation models to understand the impact on productivity and schedule from five scenarios at various delivery reliability levels of the Prefabricated Bathroom Units. Smart Contract rules were developed based on the impact. A Blockchain platform was established so that once a real-time delivery is identified and the information is entered into the Smart Contract, the associated incentive or penalty can be triggered instantly. The Smart Contract based incentive—penalty enforcement system will be beneficial for construction projects to monitor and track modular delivery, motivate reliable supply, reduce payment disputes, and improve productivity. © 2023, Canadian Society for Civil Engineering.
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The COVID-19 pandemic has caused severe health problems worldwide and unprecedented decimation of the global economy. Moreover, after more than 2 years, many populations are still under pressure of infection. Thus, a broader perspective in developing antiviral strategies is still of great importance. Inspired by the observed multiple benefits of heparin in the treatment of thrombosis, the potential of low molecular weight heparin (LMWH) for the treatment of COVID-19 have been explored. Clinical applications found that LMWH decreased the level of inflammatory cytokines in COVID-19 patients, accordingly reducing lethality. Furthermore, several in vitro studies have demonstrated the important roles of heparan sulfate in SARS-CoV-2 infection and the inhibitory effects of heparin and heparin mimetics in viral infection. These clinical observations and designed studies argue for the potential to develop heparin mimetics as anti-SARS-CoV-2 drug candidates. In this review, we summarize the properties of heparin as an anticoagulant and the pharmaceutical possibilities for the treatment of virus infection, focusing on the perspectives of developing heparin mimetics via chemical synthesis, chemoenzymatic synthesis, and bioengineered production by microbial cell factories. The ultimate goal is to pave the eminent need for exploring novel compounds to treat coronavirus infection-caused diseases.
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As a non-thermal food processing technology, Electron beam (E-beam) irradiation has been used to enhance microbial safety by deactivating unwanted spoilage and pathogenic microorganisms in food industry. This study evaluated the effects of E-beam irradiation at doses killing SARS-COV-2 on qualities and sensory attributes. The results showed that irradiation caused little effect on the proximate composition, amino acid content, texture, and sensory attributes (P > 0.05). However, E-beam increased TBARS (Thiobarbituric acid reactive substances) and lowered vitamin E content in dose-dependently. Irradiation up to 10 kGy significantly decreased unsaturated fatty acid (UFA) content and inhibited the increase in TVB-N (The total volatile basic nitrogen) while reducing cohesiveness and chewiness (P < 0.05). E-beam irradiation with 7–10 kGy caused greater ΔE values (ΔE > 5) via the significant increase of b*, accompanied by big visual difference in shrimp (P < 0.05). A dose of 4 kGy E-beam irradiation was recommended without altering its physicochemical properties and sensory attributes. © 2023 Elsevier Ltd
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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the worldwide spread of coronavirus disease-2019 (COVID-19) since its emergence in 2019. Virus replication and infection dynamics after its deposition on the respiratory tissues require detailed studies for infection control. This study focused primarily on SARS-CoV-2 dynamics in the mucus layer of the nasal cavity and nasopharynx, based on coupled computational fluid-particle dynamics (CFPD) and host-cell dynamics (HCD) analyses. Considering the mucus milieu, we coupled the target-cell limited model with the convection-diffusion term to develop an improved HCD model. The infection dynamics in the mucus layer were predicted by a combination of the mucus flow field, droplet deposition distribution, and HCD. The effect of infection rate, β, was investigated as the main parameter of HCD. The results showed that the time series of SARS-CoV-2 concentration distribution in the mucus layer strongly depended on diffusion, convection, and virus production. β affected the viral load peak, its arrival time, and duration. Although the SARS-CoV-2 dynamics in the mucus layer obtained in this study have not been verified by appropriate clinical data, it can serve as a preliminary study on the virus transmission mode in the upper respiratory tract. © The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/)
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The outbreak of COVID-19 made researchers notice some new points and change their focus, such as the economies of scale for residential energy use, energy dependency of societies, etc. This paper provides a bibliometric analysis of 497 articles by VOSviewer, finding that existing studies on building energy use during COVID-19 could be summarized into four keywords, i.e., building occupants, coronavirus, sustainability and monitoring and management. Significant increases in residential energy consumption are found with the increased duration of in-home-activity, while the growth rate varies between different neighborhoods, different times of day and different usage of energy. Attitudes vary toward the changing trend in the post-pandemic period, and the impacts of lockdown, new confirmed cases, social distancing, etc. on residential energy consumption have been given special attention in recent studies. Policy implications are concluded for maintaining normal operation of residential energy systems under the shock of public health emergencies. © 2023 Newcastle University.
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With the COVID-19 pandemic sweeping worldwide, much attention has been paid to infectious viruses. Because of the different sizes of pathogen-carrying droplets exhaled by individuals infected with COVID-19, the influence of gravity and inertia on the droplets varies, which leads to different modes of transmission of the virus. Ventilation changes the air distribution in a room, and affects virus transmission. An appropriate ventilation method that reduces the floating time of viruses and the exposure rate of the human body should be selected. Although previous studies have extensively reviewed methods to reduce the airborne transmission of viruses, research on ventilation methods remain limited. This review aimed to explore a ventilation mode that could ensure the thermal comfort and maintain low exposure and infection rates in the human body. This study investigated the transmission modes of the virus and the importance of particle size. The effects of mixing ventilation, displacement ventilation, impinging jet ventilation, and stratum ventilation on the removal of different particle sizes and applications at various locations were compared. The results of this study can contribute to reducing the indoor virus concentrations during the COVID-19 pandemic. © The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/)
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With the rapid development of China's new energy industry, the consumption demand for copper resources is increasing. As a key raw material, copper resources are becoming increasingly important. Taking the demand for copper commodities in China's new energy development as the research background and the international trade environment and pattern of copper supply as the research perspective, this paper makes an overall assessment of the commodity supply risk of China's copper industrial chain from 2010 to 2021 using the complex network and the newly established three-dimensional risk assessment model and finally reaches the following conclusions. The supply risk of commodities in China's copper industrial chain has been rising continuously since 2019 after experiencing fluctuating development in the early stage and a continuous decline in recent years, and there may be a trend of continuing to rise. The supply risk of China's copper industrial chain was gradually reduced from upstream to midstream and downstream, and the supply risk of copper smelting was more severe. The disruption potential risk of China's copper industrial chain was relatively low, and the international import market structure of copper commodities was relatively reasonable. The supply risk characteristics of each link in China's copper industrial chain were different. Due to the influence of import dependence, the copper mining industry had a high risk of trade exposure. However, the smelting and copper processing industries had certain limitations in production management, operation management and technology research and development, and their ability to withstand risks was weak. In addition, the impact of the domestic COVID-19 epidemic ha caused a high industrial chain vulnerability risk. © 2023 Elsevier Ltd
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Objective To analyze the prescription rules for pestilence in ancient books of case records, and provide reference for treatment of coronavirus disease 2019 (COVID19);Methods The medical cases of warm diseases in ancient times were selected as the source before data extraction rules were made. TCM Miner was used to conduct the counts and analysis of association rules, and Cloud Platform of Ancient and Modern Medical Cases was used for complex network analysis. Results A total of141 medical cases were found in the 14 ancient books of case records, involving 66 formulae and 142 Chinese medicinals. The formulae mainly included Xiao Chaihu Tang (Minor Bupleurum Decoction), Dayuan Yin (Membrane Source-Opening Beverage), and JiuweiQianghuo Tang (Nine Ingredients Notopterygium Decoction), while the medicinals mainly included Lianqiao (Fructus Forsythiae), Fuling (Poria), and Shichangpu (RhizomaAcoriTatarinowii). Conlusion The prescriptions against pestilence in ancient times highlight clearing heat and toxins, cooling the blood, resolving dampness and opening the orifices, which is also combined with releasing the exterior. © 2022 IEEE.
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Due to the coronavirus pandemic, portable electrical impedance tomography (EIT) systems [1]-[3] have been considered as the only variable wearable medical lung imaging solution for monitoring the treatment of pneumonia patients and their recovery. Generally, the EIT system is classified into passive EIT (P-EIT) [3]-[6] or active electrode EIT (AE-EIT) [2]. The AE-EIT system is preferred as it amplifies and digitalizes the small signals while minimizing the noises incurred by motion artifacts, complex long wire connection, large variation in electrode contact, and stray capacitance problems, which is important for high-performance imaging applications. © 2022 IEEE.
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Introduction. Multi-criteria decision analysis (MCDA) is a useful tool in complex decision-making situations and has been used in medical fields to evaluate treatment options and drug selection. We aimed to provide valuable insights on the use ofMCDAin health care through examining the research focus of existing studies, major fields, major applications, most productive authors and countries, and most common journals in the domain using a scientometric and bibliometric analysis. Methods. Publications related to MCDA in health care were identified by searching the Web of Science Core Collection on 14 July 2021. Three bibliometric software programs (VOSviewer, Bibliometrix, and CiteSpace) were used to conduct the analysis. Results. A total of 410 publications were identified from 196 academic journals (average yearly growth rate of 32% from 1999 to 2021), with 23,637 co-cited references by 871 institutions from 70 countries or regions. The USA was the most productive country (n=80), while the Universiti Pendidikan Sultan Idris (n=16), Universite de Montreal (n= 13), and Syreon Research Institute (n=12) were the most productive institutions. The biggest nodes in every cluster of author networks were Aos Alaa Zaidan, Mireille Goetghebeur, and Zoltan Kalo. The top journals in terms of number of articles (n=17) and citations (n=1,673) were Value in Health and the Journal of Medical Systems, respectively. The research hotspots mainly included the analytic hierarchy process (AHP), decision-making, health technology assessment, and healthcare waste management. In the recent literature there was more emphasis on coronavirus disease 2019 (COVID-19) and fuzzy Technique for Order Preference by Similarities to Ideal Solution (TOPSIS). Big data, telemedicine, TOPSIS, and the fuzzy AHP, which are well-developed and important themes, may be the trends in future research. Conclusions. This study provides a holistic picture of the MCDArelated literature published in health care. MCDA has a broad application in different topic areas and would be helpful for practitioners, researchers, and decision makers working in health care when faced with complex decisions. It can be argued that the door is still open for improving the role ofMCDAin health care, both in its technologies and its application.
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Objective: Ixekizumab is a high-affinity monoclonal antibody that selectively targets interleukin-17A and is approved for treating moderate-to-severe psoriasis. This phase 3, multicenter, randomized, double-blind, placebo-controlled trial (NCT03364309;registered December 6, 2017) evaluated the safety and efficacy of ixekizumab in Chinese patients with moderate-to-severe psoriasis. Method(s): 438 patients were randomized 2:2:1 to 80 mg ixekizumab every 2 weeks (IXE Q2W, n = 176), 80 mg ixekizumab every 4 weeks (IXE Q4W, n = 174), or placebo (n = 88). Efficacy was assessed by evaluating the static Physician's Global Assessment score of 0 or 1 (sPGA [0,1]) and Psoriasis Area and Severity Index (PASI) 75/90/100 responses, and nonresponder imputation was used for handling missing data. The safety profile was evaluated by assessing treatment emergent adverse events (AEs) and serious AEs. Result(s): At week 12, the sPGA (0,1) response rates were 3.4%, 79.9%, and 86.4% in the placebo, IXE Q4W, and IXE Q2W groups, respectively. The PASI 75/90/100 response rates were 8.0%/2.3%/0.0%, 87.4%/75.9%/29.3%, and 93.8%/82.4%/33.0% in the placebo, IXE Q4W, and IXE Q2W groups, respectively. Ixekizumab led to rapid PASI 50 responses, as early as week 1, whereas PASI 75 and sPGA (0,1) responses were observed from week 2. sPGA (0,1) and sPGA (0) responses were maintained through week 60 in a higher proportion of patients receiving IXE Q4W vs. placebo. The safety profile was consistent with previous studies of ixekizumab in psoriasis. Conclusion(s): Ixekizumab showed a rapid onset of action and high efficacy that was maintained through 60 weeks and was well tolerated with no unexpected AEs, in Chinese patients with moderate-to-severe plaque psoriasis. Copyright © 2022 International Journal of Dermatology and Venereology. All right reserved.