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The development of globalization has brought about obvious differences in the resilience of different regions against economic crises. Regional economic resilience refers to the ability of a region's economy to resist shocks when faced with external disturbances or to break away from its existing growth model in favor of a better path, Resilience represents the region's adaptability, innovation, and sustainability. This paper describes an empirical analysis on the 60 designated industrial park developments under the Industrial Development Bureau in Taiwan. Over a period of short-term disturbances, the industrial parks are analyzed from four aspects: industrial structure, regional development foundation, enterprise competitiveness and labor conditions, and government governance and policy systems. Through discriminant analysis, we analyze the characteristics of factors that mainly affect the economic resilience of 60 industrial parks faced with shocks such as the subprime mortgage crisis in 2008, the five-day work week in 2016, and the COVID-19 outbreak in 2019. We found that industrial structure, specifically diversified industrial structure, is the major factor behind enhanced regional economic resilience. If the scale of specialized industries is large enough, they can form sufficient capacity to resist external changes and also be economically resilient. Under the negative impact, the amount of innovation can be an important part of post-disaster recovery, and stable innovation input will become a main factor for the sustainable development of industrial parks. The pressure of the uncertainty of global economic development and the transformation and upgrading of the domestic economy underscore that enterprises urgently need automation and digital transformation to enhance their competitiveness. In order to enhance economic resilience to adapt to changes in the overall environment, the industrial parks need to adjust adaptively, improve their industrial structure, and promote innovation, hoping that the regional economy will move towards a more stable and sustainable development path. © 2023 by the authors.
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Objective To analyze the clinical characteristics and changes of serum IgG, IgM antibodies in patients infected with the SARS-CoV-2 B.1.1.529 (Omicron) variant. Methods The clinical data of 82 patients with SARS-CoV-2 B.1.1.529 variant was analyzed retrospectively. Based on the presence of pneumonia on chest CT, the patients were divided into pneumonia group and non-pneumonia group. Serum IgG, IgM antibodies were observed at 5 time points T1 (1~<4 d), T2 (4~<8 d), T3 (8~<15 d), T4 (15~<22 d) and T5 (22~<30 d) after admission. Results Among the 82 patients infected with the SARSCoV-2 B.1.1.529 variant strain, there were 62 cases of cough, 31 cases of fever, 33 cases of throat discomfort, 5 cases of muscle soreness and 3 cases of diarrhea. The serum IgG antibody levels at 5 time points were 50.22 (142.20) AU/mL, 326.50 (220.63) AU / mL, 368.23 (76.21) AU / mL, 368.65 (79) AU / mL, and 385.26 (113.10) AU / mL, respectively. The level of serum IgG antibody in the pneumonia group was lower than that of the non-pneumonia group at T1 and T4 time points, and the differences were statistically significant (P<0.05), the positive rate of serum IgG antibody in the pneumonia group was lower than that of the non-pneumonia group at the T1 time point, and the difference was statistically significant (P<0.05) . The serum IgM antibody levels at 5 time points were 0.41 (0.81) AU/mL, 0.95 (1.62) AU/mL, 1.09 (2.42) AU/mL, 0.74 (3) AU/mL, and 0.81 (3.10) AU / mL respectively, and there was no significant difference between the two groups. Conclusion The clinical symptoms of patients infected with the SARS-CoV-2 B.1.1.529 variant strain are mild. Serum IgG antibodies increased after infection, but there are some differences between the pneumonia group and the non-pneumonia group, whether serum IgG has a protective effect needs further research;the serum IgM antibodies do not increase highly after infection, there are some differences between individuals. © 2022 Editorial Office of Chinese Journal of Schistosomiasis Control. All rights reserved.
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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.
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Objective: To understand the epidemiological characteristics of three local COVID-19 epidemics in Guangzhou and provide reference for optimizing strategies and measures of COVID-19 prevention and control. Methods: The data of local COVID-19 cases in Guangzhou reported as of June 18, 2021 were collected from National Notifiable Disease Report System of China. The software Excel 2019 and SPSS 22.0 were applied for data cleaning and statistical analysis. Results: A total of 726 COVID-19 cases were reported in the three local epidemics in Guangzhou. In the epidemic associated with the outbreak of COVID-19 in Hubei province, 366 cases were reported. Most cases were female (51.6%, 189/366), aged 18-65 years (81.4%, 298/366), jobless/unemployed (32.2%, 118/366) and retired persons (20.2%,74/366). The initial symptoms of most cases were fever (71.6%, 250/349) and cough (60.7%, 212/349). In the epidemic associated with the imported COVID-19 cases from Africa, 207 cases were reported. Most cases were aged 18-40 years (72.9%, 151/207), male (69.6%, 144/207), and engaged in commercial services (62.3%,129/207). The initial symptoms of most cases were no obvious discomfort (55.6%, 15/27) and cough (37.0%, 10/27). In the epidemic associated with Delta variant of SARS-CoV-2, 153 cases were reported, in which women accounted for 58.8% (90/153), most cases were over 41 years old (64.7%,99/153), and retired persons accounted for the highest proportion (32.0%,49/153). The initial symptoms of most cases were cough (32.9%, 48/146) and no obvious discomfort (28.1%, 41/146). The household secondary attack rates of the three local epidemics were 11.2%, 5.7% and 11.5%, respectively. The median (P25, P75) of incubation periods were 6.5 (4.0,10.8) d, 4.0 (2.5, 6.0) d and 4.0 (3.0,5.0) d. The serial intervals median (P25, P75) were 4.0 (3.0, 8.0) d, 4.0 (2.5, 6.0) d and 3.0 (2.0,5.0) d. There were significant differences in gender, age, occupation, initial symptoms, household secondary attack rate and incubation period among the three local COVID-19 epidemics (all P<0.05). In the proportion of the case finding way, passive detection in patient treatment were mainly 44.3%(162/366) in the epidemic associated with the outbreak of COVID-19 in Hubei province,but active community case screening [58.5% (121/207) and 27.5% (24/153)] and close contact management in imported case were mostly [33.3% (69/207) and 67.3% (103/153)] in the epidemic associated with the imported COVID-19 cases from Africa and with Delta variant of SARS-CoV-2, respectively. Conclusions: Due to the different sources of infection, strain types and prevention and control strategies, the epidemiological characteristics of the three local COVID-19 epidemics in Guangzhou differed in demographics, clinical symptoms, transmission routes and case finding, which suggested that it is necessary to improve the key population and common symptom monitoring in the routine prevention and control of COVID-19 to prevent the reemerge of the epidemic.
Subject(s)
COVID-19 , Epidemics , Adult , China/epidemiology , Female , Humans , Male , SARS-CoV-2ABSTRACT
Objective: Due to a continued increase in viral pneumonia incidence and resulting high mortality, fast and accurate diagnosis is important for effective management. This investigation examined the significance of blood biomarkers and the CT score in the early diagnosis of viral pneumonia. Methods: Patients who were hospitalized due to radiologically-confirmed pneumonia and underwent virus antigen rapid test were enrolled. Their clinical information was compared. Blood mononuclear cell count, LDH, and plasma D-dimer were obtained. To evaluate the utility of biomarker levels in differentiating viral pneumonia from other pneumonia, ROC curves were developed to analyze the AUC. The optimal cut-off thresholds, specificity, sensitivity, and predictive values were assessed using the Youden index. The added value of the multi-marker approach was delineated using IDI and Reclassification analyses using NRI;IDI and NRI values were examined with 95% CI. Results: Overall, 1163 inpatients were recruited between January 2017 and January 2021. They were sub-divided into the viral pneumonia (n = 563) and non-viral pneumonia (n = 600) categories. We found that the CT score, blood mononuclear cell count, LDH, and plasma D-dimer were markedly elevated in viral pneumonia patients. At an LDH threshold of 693.595 U/L, an AUC of ROC was 0.805 in differentiating viral pneumonia. The combination of CT score and blood biomarkers had an ROC AUC value of 0.908. Conclusions: Combining elevated biomarkers with CT assessments outperformed the CT score alone in identifying viral pneumonia. It is crucial to better characterize the significance of biomarkers in combination with CT assessments in the diagnosis of viral pneumonia.