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As important combat platforms, large warships have the characteristics of compact internal space and dense personnel. Once infectious diseases occur, they are very easy to spread. Therefore, it is very important to select suitable forecasting models for infectious diseases in this environment. This paper introduces 4 classic dynamics models of infectious diseases, summarizes various kinds of compartmental models and their key characteristics, and discusses several common practical simulation requirements, helping relevant health personnel to cope with the challenges in health and epidemic prevention such as the prevention and control of coronavirus disease 2019.Copyright © 2022, Second Military Medical University Press. All rights reserved.
ABSTRACT
As important combat platforms, large warships have the characteristics of compact internal space and dense personnel. Once infectious diseases occur, they are very easy to spread. Therefore, it is very important to select suitable forecasting models for infectious diseases in this environment. This paper introduces 4 classic dynamics models of infectious diseases, summarizes various kinds of compartmental models and their key characteristics, and discusses several common practical simulation requirements, helping relevant health personnel to cope with the challenges in health and epidemic prevention such as the prevention and control of coronavirus disease 2019.Copyright © 2022, Second Military Medical University Press. All rights reserved.
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This paper merges three textual models to construct a series of indicators, which can yield more refined proxies for financial media coverage, to measure the impacts of COVID-19 on Chinese financial markets. Results show that the basic indicator Granger causes the volatilities of bond and stock markets and contributes more to the stock market after the outbreak of COVID-19. Next, four specific market-related indicators have significant effects on the corresponding financial market after the outbreak. Finally, the policy-related indicator has a significant effect on four financial markets after the outbreak, and it causes greater volatility in the stock market. This paper can help the government to stabilize the financial market by managing financial media attention. © 2023 Taylor & Francis Group, LLC.
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The outbreak of the coronavirus disease 2019 (COVID-19) has become the worst public health event in the whole world, threatening the physical and mental health of hundreds of millions of people. However, because of the high survivability of the virus, it is impossible for humans to eliminate viruses completely. For this reason, it is particularly important to strengthen the prevention of the transmission of viruses and monitor the physical status of the crowd. Wireless sensors are a key player in the fight against the current global outbreak of the Covid-19 pandemic, where they are playing an important role in monitoring human health. The Wireless Body Area Network (WBAN) composed of these wireless sensor devices can monitor human health data without interference for a long time, and update the data in almost real time through the Internet of Things (IoT). However, because the data monitored by the devices is relatively large and the transmission distance is long, only transmitting the data to medical centers through the personal devices (PB) cannot get feedback in time. We propose a non-cooperative game-based server placement method, which is named ESP-19 to improve the efficiency of transmission data of wireless sensors. In this paper, experimental tests are conducted based on the distribution of Shanghai Telecom's base stations, and then the performance of ESP-19 is evaluated. The results show that the proposed method in this paper outperforms the comparison method in terms of service delay. © 2022 IEEE.
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Due to the wide variety of pathogens causing respiratory tract infection and the close symptoms, coronavirus disease 2019 (COVID-19) needs to be differentiated from other common infections. Early comprehensive detection and accurate identification of respiratory infection pathogens is of great value for early diagnosis, curative effect, as well as monitor of the diseases. Combined detection of multiple pathogens can quickly and accurately detect and distinguish the pathogens, then provide rapid and reliable laboratory diagnostic basis for further treatment. This article elaborates the application and development of multiplex detection assay in the diagnosis of COVID-19 according to the recent research.
Subject(s)
COVID-19 , Respiratory Tract Infections , Humans , COVID-19/diagnosis , Respiratory Tract Infections/diagnosis , Respiratory Tract Infections/therapy , Sensitivity and SpecificityABSTRACT
Bleeding and thrombotic diseases are closely related to various clinical departments. Laboratory‐related tests play an important role in disease diagnosis and differential diagnosis, risk assessment, cause finding, and efficacy monitoring. Clot waveform analysis (CWA), as an automated coagulation detection technology, can provide more valuable information about the entire coagulation process of a plasma sample. A large number of studies have showed that CWA has certain value in the evaluation of coagulation status of COVID‐19 patients, the judgment of clinical phenotype of hemophilia A (HA) patients, and the monitoring of direct oral anticoagulant drugs (DOAC). In‐depth interpretation and application of CWA in different clinical settings can provide more laboratory information for diagnosis and treatment of bleeding and thrombotic diseases. © 2021 Chinese Medical Journals Publishing House Co.Ltd. All rights reserved.
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The influence of asymptomatic patients on disease transmission has attracted more and more attention, but the mechanism of some factors affecting disease transmission needs to be studied urgently. Considering the self-healing rate of asymptomatic patients, the cure rate of symptomatic patients, the transformation rate from asymptomatic to symptomatic and the infection delay, a type of infectious disease dynamics model SIsIaS with asymptomatic infection and infection delay is established in this paper. It is found that both the infection delay and the difference size between the cure rate and the self-healing rate not only affect the minimum value of the total number of patients in the persistent state of the disease, but also lead to disease extinction to be controlled by the proportion of symptomatic patients in patients. Moreover, the infection delay can lead to local Hopf bifurcation of periodic solutions. By using the normal form and center manifold theory the direction of Hopf bifurcations and the stability of bifurcated periodic solutions are discussed. At last, sensitivity analysis shows that the infection delay can change the correlation of the proportion of symptomatic patients in patients and the transformation rate to the total number of patients. (C) 2022 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.
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Purpose This paper aims to unveil the importance of knowledge management on a firm's strategic emergency response during the great negative shock from global public health threats. Through analyzing how representative firms in China's new economy industries dealt with the COVID-19 pandemic before, during and after the crisis, the significant problems confronted by these firms are pointed out, and the important role knowledge management capabilities played in solving these problems is proven. Design/methodology/approach The open data of listed companies regarding the important role knowledge management played in firms' strategic emergency response during the COVID-19 pandemic are qualitatively analyzed. Based on theoretical sampling, this paper selects representative samples of enterprises and analyzes the positive response measures they took after being hit by this public health event to gain qualitative insight into the importance of knowledge management capabilities in strategic emergency response. Findings Three aspects of the important role of knowledge management capabilities in a firm's strategic emergency response during the COVID-19 pandemic are introduced: before the crisis, firms should strengthen the acquisition, sharing and integration of knowledge so that they can intensify their monitoring for uncertain risks;during the crisis, firms should boost the transmission, transformation and diffusion of knowledge to improve emergency cooperation;and after the crisis, companies should reinforce knowledge evaluation, creation and application to enhance "immunity" in similar emergencies. Research limitations/implications This paper has important implications for bolstering strategic emergency management practice and knowledge management capability among firms. Future research must focus on the following two aspects for further investigation: the dynamic relationship between firm knowledge management capability and strategic emergency response ability;and the collaboration system between firm knowledge management and strategic emergency response behaviors. Originality/value This paper discusses the important role knowledge management capabilities play in firms' strategic emergency responses based on insights gained from the significant changes that the COVID-19 pandemic caused to representative Chinese new economy firms. By analyzing the three stages of before, during and after the emergency, this paper proposes the exact efforts that new economy companies should make in improving knowledge management capability.
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Source emissions with high covariance degrade the performance of multivariate models, and often highly-time resolved data is needed to accurately extract the contribution of different emissions. Here, we use highly time-resolved size segregated elemental composition data to apportion the sources of the elemental fraction of PM in Zürich (May 2019–May 2020). For data collection, we have used an ambient metals monitor, Xact 625i, equipped with a sampling inlet alternating between PM2.5 and PM10. By implementing interpolation and a newly proposed uncertainty estimation methodology, it was possible to obtain and use in PMF a combined dataset of PM2.5 and PMcoarse (PM10-2.5) having data from only one instrument. The combination of the inlet switching system, the instrument's high time resolution, and the use of advanced source apportionment approaches yielded improved source apportionment results in terms of the number of identified sources, as the model, additionally to the diurnal and seasonal variation of the dataset, also utilizes the variation from the size segregated data. Thirteen sources of elements were identified, i.e., sea salt (5.4%), biomass burning (7.2%), construction (4.3%), industrial (3.3%), light-duty vehicles (5.4%), Pb (0.7%), Zn (0.7%), dust (22.1%), transported dust (9.5%), sulfates (15.4%), heavy-duty vehicles (17%), railway (6.6%) and fireworks (2.4%). The Covid-19 lockdown effect in PM sources in the area was also quantified. High-intensity events disproportionally affect the PMF solution, and in many cases, they are getting discarded before analysis, removing thus valuable information from the dataset. In this study, a three-step source apportionment approach was used to get a well-resolved unmixed solution when firework data points were included in the analysis. This approach can also be used for other sources and/or events with very high contributions that distort source apportionment analysis. Optimized source apportionment techniques are necessary for effective air pollution monitoring.
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Public Policy Relevance Statement This research shows that people turn to media to cope with significant stressors as much as, if not more than, strategies typically recommended by health professionals. Furthermore, across all coping strategies, only TV/movie viewing seemed to mitigate the negative effects of stress on both coping efficacy and proactive coping behavior. Combined, these findings highlight the critical role media can play in helping people cope meaningfully with stress. The COVID-19 pandemic presented a unique opportunity to answer the critical question: How does media use aid (or subvert) emotion- and problem-focused coping with significant life stressors? Based on a national survey (N = 564) conducted on March 20-25, 2020, the week after COVID-19 was declared a U.S. national emergency, evidence offered strong support for the use and value of media, entertainment media in particular, as key aids to coping processes. Looking across a range of coping techniques, only TV/movie and music consumption emerged as a significant mediator between stress and coping efficacy, which, in turn, was significantly associated with social distancing likelihood. These and other results provide evidence for the important role that media consumption can play in supporting coping processes in ways both unique from more basic emotional regulation and beyond techniques typically recommended by health professionals.
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The Corona Virus Disease 2019 has a great impact on public health and public psychology. People stay at home for a long time and rarely go out. With the improvement of the epidemic situation, people began to go to different places to check in. To maintain public mental health, it is necessary to propose a point-of-interest (POI) prediction model which can mine users' interests. However, the current techniques suffer from lower precision during prediction and the practical value is poor, which is due to the sparse data of users' check-in. Faced with this challenge, we propose an attention-based bidirectional gated recurrent unit (GRU) model for POI category prediction (ABG_poic). We regard the user's POI category as the user's interest preference because the fuzzy POI category is easier to reflect the user's interest than the POI. This method can alleviate the data sparsity, and protect users' location privacy. Since users' preferences are variable, we utilize a bidirectional GRU to capture the dynamic dependence of users' check-ins. Furthermore, since the neural network is similar to a “black box” in feature learning, the decision-making stage is opaque. Thus, we combine the attention mechanism with bidirectional GRU to selectively focus on historical check-in records, which can improve the interpretability of the model. Considering the time impact on users' check-in, we utilize the time sliding window in the ABG_poic model. Experiments on two data sets demonstrate that our ABG_poic outperforms the comparison models for POI category prediction on sparse check-in data. © 2021 Wiley Periodicals LLC
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Decorating liquid crystals (LCs) with stimuli-responsive materials provides a bridge between the LCs and the biochemical interactions. The alignments of the LC molecules are particularly sensitive. Even small perturbations to the LC interface can substantially direct the orientation of bulk LC phases, which results in transduction and amplification of the chemical and biological events into readily detectable optical outputs. These characteristics make the LCs extremely alluring for the development of biosensors that allow highly sensitive and label-free detection of biomarkers at the aqueous/LC interface. In this review, we organize the LC-based sensing systems into six groups, including monolayer formation, monolayer removal, monolayer disruption, floating LC droplets, sessile LC droplets, and LC elastomer microspheres. The principle, utilization, advancement, and limitations of each platform for the detection of various biomarkers are discussed in detail, which will help expand our understanding of the development of LC-based sensors for advanced diagnostic and therapeutic approaches.
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The coming-of-age of digital media has transformed the translation landscape, (con)fusing to a certain extent the Source and the Target. Not only has there been a shift in the way the agents of a translation interact with the text, but source text readers have also been brought into the picture as potentially important players in the (co)production of the target text. Using the controversial Wuhan Diary about the Covid-19 crisis in China as a case study, this paper examines the role of source text readers as censors of the paratexts of the Diary’s English translation. The active participation of source text readers created much tension with the source text author, and also gave rise to conflicts with other agents such as the translator and publisher. The resolution of what were often ideological conflicts was reflected in the fluidity of the paratexts of the target text, a fluidity facilitated and enabled by digital media. © 2021 Informa UK Limited, trading as Taylor & Francis Group.
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OBJECTIVE: It has recently been reported that some COVID-19 patients have long-term positive fecal nucleic acid after discharging from the hospital with negative nucleic acid in the respiratory tract, but it is unclear whether COVID-19 patients with positive long-term fecal nucleic acid tests have the risk of self-infection. PATIENTS AND METHODS: From January 25, 2020 to March 9, 2020, 5 COVID-19 patients with negative respiratory tract nucleic acid and positive fecal nucleic acid were observed and studied to explore whether these patients can re-infect themselves. Five patients with COVID-19 accompanied by diarrhea as the main gastrointestinal symptoms were carefully observed through clinical symptoms, imaging and other auxiliary examinations. The RT-PCR technology was used to continuously detect fecal and respiratory viral nucleic acids. The IgM antibody was detected on the 7th day of admission and IgM/IgG at the time of discharge. RESULTS: All 5 patients had symptoms of fever and diarrhea upon admission. The fecal nucleic acid was positive, as well as the throat swab was positive. All COVID-19 patients had positive IgM antibodies on the 7th day of admission and positive IgM and IgG at the time of discharge, and there were no abnormalities in the gastrointestinal examination on discharge. All 5 fecal nucleic acid tests were positive at the time of discharge. After continuous dynamic follow-up for 3-15 days, no clinical symptoms recurred, and the last nucleic acid test was negative. CONCLUSIONS: There is no risk of self-infection for COVID-19 patients with long-term 2019-nCoV nucleic acid positive in feces.