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Based on the SEIR model, two compartments for self-protection and isolation are introduced, and a more general infectious disease transmission model is proposed.Through qualitative analysis of the model, the basic reproduction number of the model is calculated, and the local asymptotic stability of the disease-free equilibrium point and the endemic equilibrium point of the model is analyzed through eigenvalue theory and Routh-Hurwitz criterion.The numerical simulation and fitting results of COVID-19 virus show that the proposed SEIQRP model can effectively describe the dynamic transmission process of the infectious disease.In the model, the three parameters, i.e.protection rate, incubation period isolation rate, and infected person isolation rate play a very critical role in the spread of the disease.Raising people's awareness of self-protection, focusing on screening for patients in the incubation period, and isolating and treating infected people can effectively reduce the spread of infectious diseases. © 2023 Northeastern University.All rights reserved.
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In 2021, the airline industry was affected by COVID-19, and many airlines suffered losses. The main reason for the loss were the decline in revenue and the surge in costs. Therefore, in terms of creating the competitive advantage of airlines, "price war" is no longer applicable, and improving service quality has become an effective means. Customer satisfaction is the most effective indicator to measure service quality. In this study, a satisfaction evaluation system is established based on structural equation model and customer satisfaction importance matrix. Then, a questionnaire is designed to analyze the influence of different factors on customer satisfaction. The research finds that brand image and perceived quality have a great impact on customer satisfaction. In addition, some suggestions for airlines to improve customer satisfaction are given. © 2023 SPIE.
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With frequent outbreaks of COVID-19, the rapid and effective construction of large-space buildings into Fangcang shelter hospitals has gradually become one of the effective means to control the epidemic. Reasonable design of the ventilation system of the Fangcang shelter hospital can optimize the indoor airflow organization, so that the internal environment can meet the comfort of patients and at the same time can effectively discharge pollutants, which is particularly important for the establishment of the Fangcang shelter hospital. In this paper, through the reconstruction of a large-space gymnasium, CFD software is used to simulate the living environment and pollutant emission efficiency of the reconstructed Fangcang shelter hospital in summer under different air supply temperatures, air supply heights and exhaust air volume parameters. The results show that when the air supply parameters are set to an air supply height of 4.5 m, an air supply temperature of 18 °C, and an exhaust air volume of a single bed of 150 m3/h, the thermal comfort can reach level I, and the ventilation efficiency for pollutants can reach 69.6%. In addition, the ventilation efficiency is 70.1% and 70.3% when the exhaust air volume of a single bed is continuously increased to 200 and 250 m3/h, which can no longer effectively improve the pollutant emission and will cause an uncomfortable blowing feeling to patients. © 2023 by the authors.
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Objective To understand the knowledge of COVID-19 and plague prevention and control in Qinghai Province, so as to carry out targeted health education and improve people's ability to prevent and control COVID–19, plague and other publichealth emergencies. Methods Six counties were randomly selected from three cities (states) by two-stage sampling. A self- designed questionnaire was randomly distributed to the public to investigate the awareness and behavior of COVID-19 and plague prevention and control. The Chinese version of Epidate was used for database construction and data entry. After checking and verifying, the data was exported as an Excel file and analyzed by SPSS 21.0 software. Results Accordign to the recovered questionnaires, the passing rate of knowledge of COVID-19 prevention and control was 78.46%, and the average score was (75. 82±16.43). The passing rate of plague prevention and control knowledge was 91.89%, and the average score was (86.46±15.94). The survey area, occupation category, gender and education level affected the knowledge of COVID-19 prevention and control. The average score was statistically significant (P<0.05). The survey area, occupation category, age and education level affected the knowledge of plague prevention and control, and the average score was statistically significant (P<0. 05). Conclusion People in Qinghai have poor knowledge of COVID - 19 prevention and control, but have good knowledge of plague prevention and control. Health education and health promotion activities on COVID - 19 and plague prevention and control should be increased in the future. © 2023, Editorial Department of Medical Pest Control. All rights reserved.
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In recent years, the soft subspace clustering algorithm has shown good results for high-dimensional data, which can assign different weights to each cluster class and use weights to measure the contribution of each dimension in various features. The enhanced soft subspace clustering algorithm combines interclass separation and intraclass tightness information, which has strong results for image segmentation, but the clustering algorithm is vulnerable to noisy data and dependence on the initialized clustering center. However, the clustering algorithm is susceptible to the influence of noisy data and reliance on initialized clustering centers and falls into a local optimum;the clustering effect is poor for brain MR images with unclear boundaries and noise effects. To address these problems, a soft subspace clustering algorithm for brain MR images based on genetic algorithm optimization is proposed, which combines the generalized noise technique, relaxes the equational weight constraint in the objective function as the boundary constraint, and uses a genetic algorithm as a method to optimize the initialized clustering center. The genetic algorithm finds the best clustering center and reduces the algorithm's dependence on the initial clustering center. The experiment verifies the robustness of the algorithm, as well as the noise immunity in various ways and shows good results on the common dataset and the brain MR images provided by the Changshu First People's Hospital with specific high accuracy for clinical medicine.
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Objective Based on text mining technology and biomedical database, data mining and analysis of coronavirus disease 2019 (COVID-19) were carried out, and COVID-19 and its main symptoms related to fever, cough and respiratory disorders were explored. Methods The common targets of COVID-19 and its main symptoms cough, fever and respiratory disorder were obtained by GenCLiP 3 website, Gene ontology in metascape database (GO) and pathway enrichment analysis, then STRING database and Cytoscape software were used to construct the protein interaction network of common targets, the core genes were screened and obtained. DGIdb database and Symmap database were used to predict the therapeutic drugs of traditional Chinese and Western medicine for the core genes. Results A total of 28 gene targets of COVID-19 and its main symptoms were obtained, including 16 core genes such as IL2, IL1B and CCL2. Through the screening of DGIdb database, 28 chemicals interacting with 16 key targets were obtained, including thalidomide, leflunomide and cyclosporine et al. And 70 kinds of Chinese meteria medica including Polygonum cuspidatum, Astragalus membranaceus and aloe. Conclusion The pathological mechanism of COVID-19 and its main symptoms may be related to 28 common genes such as CD4, KNG1 and VEGFA, which may participate in the pathological process of COVID-19 by mediating TNF, IL-17 and other signal pathways. Potentially effective drugs may play a role in the treatment of COVID-19 through action related target pathway.Copyright © 2022 Tianjin Press of Chinese Herbal Medicines. All Rights Reserved.
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Objective To explore the core targets and important pathways of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) induced atherosclerosis (AS) progression from the perspective of immune inflammation, so as to predict the potential prevention and treatment of traditional Chinese medicine (TCM). Methods Microarray data were obtained from the Gene Expression Omnibus (GEO) database for coronavirus disease 2019 (COVID-19) patients and AS patients, and the "limmar" and "Venn" packages were used to screen out the common differentially expressed genes (DEGs) genes in both diseases. The gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses were performed on the common DEGs to annotate their functions and important pathways. The two gene sets were scored for immune cells and immune function to assess the level of immune cell infiltration. The protein-protein interaction (PPI) network was constructed by STRING database, and the CytoHubba plug-in of Cytoscape was used to identify the hub genes. Two external validation datasets were introduced to validate the hub genes and obtain the core genes. Immuno-infiltration analysis and gene set enrichment analysis (GSEA) were performed on the core genes respectively. Finally the potential TCM regulating the core genes were predicted by Coremine Medical database. Results A total of 7898 genes related to COVID-19, 471 genes related to AS progression;And 51 common DEGs, including 32 highly expressed genes and 19 low expressed genes were obtained. GO and KEGG analysis showed that common DEGs, which were mainly localized in cypermethrin-encapsulated vesicles, platelet alpha particles, phagocytic vesicle membranes and vesicles, were involved in many biological processes such as myeloid differentiation factor 88 (MyD88)-dependent Toll-like receptor signaling pathway transduction, interleukin-8 (IL-8) production and positive regulation, IL-6 production and positive regulation to play a role in regulating nicotinamide adenine dinucleotide phosphate oxidase activity, Toll-like receptor binding and lipopeptide and glycosaminoglycan binding through many biological pathways, including Toll-like receptor signaling pathways, neutrophil extracellular trap formation, complement and coagulation cascade reactions. The results of immune infiltration analysis demonstrated the state of immune microenvironment of COVID-19 and AS. A total of 5 hub genes were obtained after screening, among which Toll-like receptor 2 (TLR2), cluster of differentiation 163 (CD163) and complement C1q subcomponent subunit B (C1QB) genes passed external validation as core genes. The core genes showed strong correlation with immune process and inflammatory response in both immune infiltration analysis and GSEA enrichment analysis. A total of 35 TCMs, including Chuanxiong (Chuanxiong Rhizoma), Taoren (Persicae Semen), Danggui (Angelicae Sinensis Radix), Huangqin (Scutellariae Radix), Pugongying (Taraxaci Herba), Taizishen (Pseudostellariae Radix), Huangjing (Polygonati Rhizoma), could be used as potential therapeutic agents. Conclusion TLR2, CD163 and C1QB were the core molecules of SARS-CoV-2-mediated immune inflammatory response promoting AS progression, and targeting predicted herbs were potential drugs to slow down AS progression in COVID-19 patients.Copyright © 2023 Editorial Office of Chinese Traditional and Herbal Drugs. All rights reserved.
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Ribavirin is an important antiviral with demonstrated activity against coronaviruses such as severe acute respiratory syndrome coronavirus and coronavirus disease 2019 virus. However, abuse of ribavirin will cause great environmental damage and threaten human health owing to its reproductive toxicity and teratogenicity. Therefore, an innovative detection method is demanded for simple and sensitive detection of ribavirin. This work reports an imprinted colloidal crystal array (ICCA) for ribavirin sensing. The building blocks of the ICCA are ribavirin imprinted spheres, which possess superior binding efficiency toward ribavirin. Benefiting from the highly ordered structure, the ICCA exhibits optical properties which change upon binding ribavirin. The changes in reflectance wavelength enable a fast and label-free detection of ribavirin between 21 and 245 μmol L−1. Moreover, the sensor shows excellent selectivity for ribavirin detection in river water. Overall, all the results reported in this work demonstrate that the ICCA should be a promising detection tool for antivirals. © 2023 Society of Industrial Chemistry. © 2023 Society of Industrial Chemistry.
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The Zero Suicide (ZS) approach to health system quality improvement (QI) aspires to reduce/eliminate suicides through enhancing risk detection and suicide prevention services. This first report from our randomized trial evaluating a stepped care for suicide prevention intervention within a health system conducting ZS-QI describes (1) our screening and case identification process, (2) variation among adolescents versus young adults, and (3) pandemic-related patterns during the first COVID-19 pandemic year. Between April 2017 and January 2021, youths aged 12-24 years with elevated suicide risk were identified through an electronic health record (EHR) case-finding algorithm followed by direct assessment screening to confirm risk. Eligible/enrolled youth were evaluated for suicidality, self-harm, and risk/protective factors. Case finding, screening, and enrollment yielded 301 participants showing suicide risk indicators: 97% past-year suicidal ideation, 83% past suicidal behavior;and 90% past non-suicidal self-injury (NSSI). Compared to young adults, adolescents reported more past-year suicide attempts (47% vs. 21%, p <.001) and NSSI (past 6 months, 64% vs. 39%, p <.001);less depression, anxiety, posttraumatic stress, and substance use;and greater social connectedness. Pandemic onset was associated with lower participation of racial-ethnic minority youths (18% vs. 33%, p <.015) and lower past-month suicidal ideation and behavior. Results support the value of EHR case-finding algorithms for identifying youths with potentially elevated risk who could benefit from suicide prevention services, which merit adaptation for adolescents versus young adults. Lower racial-ethnic minority participation after the COVID-19 pandemic onset underscores challenges for services to enhance health equity during a period with restricted in-person health care, social distancing, school closures, and diverse stresses.Copyright © 2023 Society of Clinical Child and Adolescent Psychology.
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In light of the fast-spreading number of COVID-19 cases worldwide, contact tracing proved to be an effective measure to slow down the infection rate and mitigate the casualties caused by this virus. However, because of several concerns in terms of privacy, as well as security, several countries and their population around the globe are reluctant to adopt contact tracing solutions to contain the spread of the virus. Because of its distributed, public, and auditable nature, blockchain can be a groundbreaking solution contact tracing, given that it would provide a privacy-oriented contact tracing solution. Therefore, in this chapter, we discuss and compare the two alternatives proposed by the BeepTrace framework, active and passive, and also present some initial results based on an early implementation of it. As it can be seen, by utilizing blockchain together with contact tracing, user privacy, security, and decentralization can be guaranteed, giving back the trust needed for these applications to work. © 2022 by John Wiley & Sons Ltd. All rights reserved.
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The process through which people and society begin to see and frame something as risky is complex. As risk communication practitioners play a critical role in fostering real-world risk governance, this study emphasizes the performative role of language in mobilizing symbolic resources to build and control risks from a communication standpoint. Critical discourse analysis (CDA) was used to reveal patterns of how two events - the COVID-19 pandemic and the Russia-Ukraine dispute - were covered by the Chinese media, and speculate about the relationship between risk communication practice and its wider geopolitical context. Results revealed different frames were used for the two events, and that 'threat' was most frequently used when addressing the Russia-Ukraine dispute, whereas 'risk' was adopted for most COVID-19-related articles. Two themes were generated when interpreting the discourse through a critical geopolitical approach: 'From the COVID-19 Approach to the Political Systems' and 'China as a global Player through its peaceful Rise'. While China prefers to maintain peace in its interaction with other global actors, the Chinese government does not simply accept adversity, particularly when it comes to geopolitical conflicts derived from arbitrary ideological disagreements. The study adds to the current literature on the relationship between the practice and context of risk communication, as well as to the underrepresented regional online news coverage of risks and conflicts that focus on China.
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Electronic healthcare (e-health) systems have received renewed interest, particularly in the current COVID-19 pandemic (e.g., lockdowns and changes in hospital policies due to the pandemic). However, ensuring security of both data-at-rest and data-in-transit remains challenging to achieve, particularly since data is collected and sent from less insecure devices (e.g., patients' wearable or home devices). While there have been a number of authentication schemes, such as those based on three-factor authentication, to provide authentication and privacy protection, a number of limitations associated with these schemes remain (e.g., (in)security or computationally expensive). In this study, we present a privacy-preserving three-factor authenticated key agreement scheme that is sufficiently lightweight for resource-constrained e-health systems. The proposed scheme enables both mutual authentication and session key negotiation in addition to privacy protection, with minimal computational cost. The security of the proposed scheme is demonstrated in the Real-or-Random model. Experiments using Raspberry Pi show that the proposed scheme achieves reduced computational cost (of up to 89.9% in comparison to three other related schemes).
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Disturbance such as COVID-19, pollution or policy variation to the economic and financial system has significant effect in the big data applications. Hence to study the effect of the disturbance on the related time series plays important role in further applying the big data in economic and financial system. Generalized Weierstrass-Mandelbrot Function is presented to study the complexity of the related time series theoretically and simultaneously. The results show that the disturbance indicated as the exponential form can generate multifractal features for the related time series. And the irregularity and long memory are also simulated by this model and described by the R/S method and multifractal analysis. © 2023 IEEE.
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Objective To assess the case-based malaria surveillance and response during the period of COVID-19 outbreak in China, in order to provide reference for malaria elimination under the COVID-19 pandemic. Methods Information of malaria cases reported during the four months pre - and post-COVID -19 outbreak (December 1, 2019-March 31, 2020) and in the same time period of past two years in China (excluding Hong Kong, Macau and Taiwan regions) was obtained from the Parasitic Disease Control Information Management System. Cross-sectional survey and comparison were conducted for malaria surveillance and response data in 3 four-month time periods (December 1, 2019 to January 22, 2020;January 23 to March 17, 2020;and March 18-31, 2020). The number of malaria cases including deaths, the median and average time interval from disease onset to the first visit, the median and average of time interval from the first visit to the confirmed diagnosis, the completion status of the #1-3-7$ task and the source of infections in each period were analyzed and compared to the same times in the past two years. Results From December 1, 2019 to March 31, 2020, a total of 750 malaria cases, which were all imported cases, were reported in China, decreased by 9.2% from that reported during December 2018 and March 2019 (826 cases) and by 13.1% from that reported during December 2017 to March 2018 (863 cases). The decrease mainly occurred in February and March in 2020;there were no statistical differences in the time interval from onset to first visit (median 1 day, mean 2.0 days), time interval from first visit to confirmed diagnosis (median 1 day, mean 1.8 days), case reporting rate within 1 day (100%), case epidemiological investigation rate within 3 days (98.4%), epidemic site disposal rate within 7 days (100%) between the time period of COVID-19 outbreak and the same time in the past year (December 2018 to March 2019). In addition, no statistical difference (! > 0.05) was found in the time intervals from onset to first visit among the first period [median 1 d, average (1.9 +/- 0.2) d], the second period [median 1 d, average (2.1 +/- 0.3) d] and the third period [median 1 d, mean (1.5 +/- 0.3) d], while the time interval from the first visit to the confirmed diagnosis was statistically different (! X 0.05) among the first period [median 0 d, average (1.5 +/- 0.2) d], the second period [median 1 d, mean (2.3 +/- 0.3) d] and the third period [median 0.5 d, average (1.5 +/- 0.4) d], where the time interval in the second period was longer than that in the first period (! X 0.01). Conclusion China' s core measures to eliminate malaria have been carried out as planned, although the timely malaria diagnosis was slightly affected in the second time period (January 23 to March 17, 2020).Copyright © 2021, National Institute of Parasitic Diseases. All rights reserved.
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For scholars based in North America who study various topics in China, the global spread of COVID-19 and resulting travel restrictions imposed by governments and research institutions have erected new barriers to field sites and local contacts. New disease-related travel restrictions are overlaid upon constrained political conditions for some research activities and a general climate of mistrust between the governments of the United States and China observed in recent years. How have scholars responded to these conditions? What research tools do scholars have at their disposal to see their research through? How has COVID-19 compelled or inspired scholars to reconsider their methods, their research subjects, and the ethics of interacting with people in new ways? This chapter assembles insights from a diverse group of scholars working in North American institutions who are re-tooling their China-related research during these times of great uncertainty. They discuss new methods to allow for continued engagement and note the limitations and possibilities that the pause in fieldwork presents for generating new knowledge. The overall picture is a frank assessment of a research landscape characterized by unprecedented constraints and new types of risks which may persist well into the future. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
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Since the outbreak of COVID-19, it has caused a startling stun to both society and economy in numerous nations, where different industries suffered unequally. This paper reviews the various performance of the Capital Asset Pricing Model (CAPM), and the Fama-French three-factor model and the five-factor model in different regions and industries. To metric the performance, various statistics models and scaling are applied including Pearson correlation, linear regression, R2 scores, t-test, etc. Specifically, this paper demonstrates the different performances of the CAPM model on the US and Egyptian stock markets, whereas using generalized method of moments in a panel data analysis to evaluate the performance in the U.S. market and the paired sample t-test and Wilcoxon signed-rank to evaluate the performance in the Egyptian market. The Fama-French three-factor model and five-factor model are both based on the U.S. market and analyze the model's performance (measured by significant level) in the U.S. market in general and in individual sectors, respectively. Whereas, in terms of three-factors model, the OLS estimation and relapse expected excess return are used onto the variables and multiple linear regression method was used to study the significance of factors in three sub-industries. Regarding to five-factors model, a multivariate regression with covariates and OLS estimation are the method for evaluation. These results shed light for deeply understanding the model and recognizing the impact on the security market of the COVID-19. © 2023 SPIE.
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An epidemiological investigation was conducted on a cluster epidemic of COVID-19 in the vaccinated population in Beijing in 2022, and serum samples were collected from 21 infected cases and 61 close contacts (including 20 cases with positive nucleic acid in the isolation observation period). The results of antibody detection showed that the IgM antibody of two infected persons was positive, and the IgG antibody positive rates of patients who were converted, not converted to positive and infected persons were 36.84% (7/19), 63.41% (26/41) and 71.43% (15/21), respectively. About 98.78% of patients had been vaccinated with the SARS-CoV-2 inactivated vaccine. The positive rate of IgG antibody in patients immunized with three doses of vaccine was 86.00% (43/50), which was higher than that in patients with one or two doses [16.12% (5/31)]. The antibody level of M (Q1, Q3) in patients immunized with three doses was 4.255 (2.303, 7.0375), which was higher than that in patients with one or two doses [0.500 (0.500, 0.500)] (all P values<0.001). The antibody level of patients who were vaccinated less than three months [7.335 (1.909, 7.858)] was higher than that of patients vaccinated more than three months after the last vaccination [2.125 (0.500, 4.418)] (P=0.007). The positive rate and level of IgG antibody in patients who were converted to positive after three doses were 77.78% (7/9) and 4.207 (2.216, 7.099), respectively, which were higher than those in patients who were converted after one or two doses [0 and 0.500 (0.500, 0.500)] (all P values<0.05).
Subject(s)
COVID-19 , Humans , SARS-CoV-2 , Disease Outbreaks , COVID-19 Vaccines , Immunoglobulin G , Antibodies, ViralABSTRACT
The COVID-19 epidemic is running at a high level globally, affecting all aspects of society, and medical education is no exception. With the rapid development of medical science, continuing medical education is an important way for medical workers to receive lifelong education. Meanwhile, attending continuing medical education is an inevitable requirement to ensure clinical ability. Under the background of normalization of epidemic prevention and control and the new situation of medical development, the management of continuing medical education in hospitals must follow the current situation and keep pace with the times. Therefore, the Internet support system to continuing education has emerged. This study used PDSA method to explore the construction of the regional center of continuing medical education through Internet under the background of normalization of epidemic prevention and control, aiming to promote the integration of medical education resources under the new situation, expand the learning channels of medical staff, and improve the level of medical education and teaching. © 2022 IEEE.
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Objective: To investigate the incidence rates of anxiety and depression among the COVID-19 patients and their association with clinical features and laboratory variables. Methods: A total of 371 COVID-19 patients were recruited from Wuhan Leishenshan Hospital from Jan 20 to May 10, 2020. The anxiety and depression were assessed by using the Hosptial Anxiety and Depression Score (HAD), the Self-rating Anxiety Scale (SAS), and Self-rating Depression Scale (SDS). The clinical features and laboratory variables were collected through electronic medical record. Statistical analyses were used to investigate the influence factors associated with anxiety and depression. Results: Among the 371 COVID-19 patients, the frequency of anxiety measured by HAD or SAS was 22. 91% and 24. 26%, respectively. The frequency of depression based on HAD or SDS was 16. 17% and 9. 43%, respectively. There were more female unmarried individuals in the anxiety or depression group. Anxiety or depression scores were significantly inversely correlated with the time for nucleic acid test turning negative. D-dimer and interleukin-6 (IL-6) were significantly elevated in the individuals with anxiety and depression. Statistically significant downregulations of lymphocyte counts, hemoglobin, and creatinine were found in anxiety and depression group. There was a negative association between creatinine and anxiety or depression scores. One unit upregulation of IL-6 and downregula-tion of lymphocyte counts could increase the hazard odds ratio of anxiety or depression by 10. 7% and 68. 9%, respectively. Conclusion: The COVID-19 patients with anxiety or depression symptoms had several different clinical features and laboratory findings in comparison with the patients without, which could lead to a poor prognosis of this disease. Clinicians should pay more attention to these indicators for anxiety or depression. Targeted psychological interventions should be implemented to minimize the negative impact of the psychological burden and to improve the quality life and disease outcome. © 2023 Editorial Board of Medical Journal of Wuhan University. All rights reserved.
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Public health events are sudden, public in nature and have serious social hazards. The COVID-19 outbreak coincided with the Lunar New Year, which had a direct or indirect impact on all areas of society. Previous studies related to emergencies have found that a considerable number of college students lacked experience in dealing with emergencies, were not emotionally stable enough, lacked analysis and decision-making ability, were easily suggestible and acted more impulsively. Therefore, in this paper, based on the existing actual information, combined with the awareness and understanding of college students' mental health, and based on the existing research results, the Hopfield-mental health model is used as a theoretical basis to study the trend of changes in college students' mental health. The results of the study show that 83.21% of the people are more concerned about the situation of this new crown pneumonia epidemic and they think that the new crown epidemic has seriously affected their living habits;65.45% thought that this new crown pneumonia epidemic did not have any major impact on their school life. The five sources of psychological stress, including academic, employment, economic, interpersonal relationship and love, were calculated and analysed in the model, which showed that employment stress, academic stress and economic stress were the largest sources of psychological stress among college students in this new pneumonia epidemic, accounting for 89%, 81% and 93%, respectively. They were followed by interpersonal and romantic stress, with 31% and 52%, respectively. © 2022 Liping Zhang.