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1.
Journal of Environmental and Occupational Medicine ; 40(1):76-82 and 94, 2023.
Article in Chinese | EMBASE | ID: covidwho-2314422

ABSTRACT

[Background] Since the outbreak of COVID-19, primary health care workers have been facing un-precedented work pressure, and their occupational stress should be taken seriously. [Objective] To analyze the occupational stress situation and its influencing factors of primary health care workers in Guangdong Province, and to propose targeted interventions. [Methods] Using a multi-stage stratified random sampling method, each prefecture-level city in Guangdong Province was classified into "good", "medium", or "poor" category based on its gross domestic product (GDP) in 2019 released by the Guangdong Provincial Bureau of Statistics. In September 2021, four primary health care institutions were randomly selected from each stra-tum, and a total of 1 327 staff members were selected for the study. The Core Occupational Stress Scale (COSS) and a basic information questionnaire designed by the authors were used. Mann-Whitney U test was used to compare the means between two groups, and Kruskal-Walis H test was used to compare the means among multiple groups. The comparison of categorical data was performed by trend chi2 test or Pearson chi2 test;the analysis of factors influencing occupational stress was performed by dichotomous multiple logistic regression analysis. [Results] There were 365 health care workers reporting occupational stress in this survey, and the positive rate of occupational stress was 27.5%. The total occupational stress score in M (P25, P75) and the scores of social support, organization and reward, demand and effort, and control were 45.0 (40.0, 50.0), 20.0 (17.0, 21.0), 14.0 (12.0, 17.0), 12.0 (10.0, 15.0), and 5.0 (4.0, 6.0), re-spectively. The results of dichotomous multiple logistic regression analysis showed that high education, low income, doctor positions, long working hours in a day, and shift work were associated with the occurrence of reporting occupational stress (P < 0.05). [Conclusion] Education, average monthly income, job category, daily working hours, and shifts are factors influencing the occurrence of reporting occupational stress in primary health care workers;targeted interventions should be implemented to reduce their occupational stress levels.Copyright © 2023, Shanghai Municipal Center for Disease Control and Prevention. All rights reserved.

2.
24th IEEE International Conference on High Performance Computing and Communications, 8th IEEE International Conference on Data Science and Systems, 20th IEEE International Conference on Smart City and 8th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Application, HPCC/DSS/SmartCity/DependSys 2022 ; : 366-371, 2022.
Article in English | Scopus | ID: covidwho-2305589

ABSTRACT

Exercise at home has already been a common behavior in the current world, especially in the post-COVID-19 era, even some athletes need to do physical fitness at home to keep their state due to the quarantine. So, the importance of online physical training and evaluation is highly increasing. In this work, we build an online 8-form Tai Chi Chuan (TCC) training and evaluation system, which provides a platform for coaches and users to conduct TCC training and evaluation online. Coaches formulate an evaluation rule and upload coaching videos to the platform, then users watch videos online and submit their own recordings, finally, users will get a score of their recordings. To complete this task, we propose a video capture method to record users' sports exercise videos from different perspectives, construct a 3D pose estimation model to identify human pose from captured video, and propose an evaluation model which can judge users' performance and assign a score to each video. To test our proposed models, we make a dataset consisting of key pose frames of TCC, and the key pose frames are extracted from users' TCC exercise videos. We use the dataset to train our models and assign scores to key poses, then compare the results with scores given by professional TCC players. In addition, we add all key pose scores from every single user together and obtain the whole score of an exercise video. The experiment results show that the error between scores assigned by our models and scores given by professional players does not exceed 1.6 in most scoring of a whole exercise video, and Root Mean Square Error (RMSE) is about 0.75 in the scoring of each key pose. © 2022 IEEE.

3.
Journal of Environmental Informatics Letters ; 8(1):12-20, 2022.
Article in English | Scopus | ID: covidwho-2305454

ABSTRACT

During June to July, 2020, persistent heavy precipitation in the Yangtze River Basin (YRB) is resulting in extensive flooding, with over 158 fatalities and tremendous economic losses. This year's disastrous flooding extreme is exceptionally different from those of other years. It contains over 1000-year return period events (for 30-day cumulative precipitation) as observed in Anhui, Guizhou and Sichuan Provinces. The mean precipitation is 308 mm in July 2020, being 54 mm higher than that of July 1998, when serious floods affected the entire Basin causing tremendous socio-economic consequences. Compared with 1998, the short-term (e.g., 1 day) precipitation in YRB did not show significant increases, while the long-term (e.g., 30 days) cumulative precipitation increases significantly. The highest observed 30-day cumulative precipitation is 1221 mm (in Anhui Province) in 2020, while the highest one in 1998 was 1028 mm (in Jiangxi Province). We thus find that this persistent heavy precipitation is the main cause of flooding in 2020. At the same time, TGR may mitigate up 43% of upstream flood, although the main contributors to this year's YRB flood are in the middle and lower reaches. Affected by COVID-19, the number of people at risk in the threatened area are increased, and their capacities to mitigate the dual impacts of COVID-19 pandemic and flooding are hindered since (a) the flooding-caused mitigations may limit people's ability to prevent from virus spreading, and (b) the pandemic is retaining a large amount of migrant workers being within YRB and subject to flooding impacts. Overall, our main discovery is that, although the short-term precipitation in YRB did not increase significantly in 2020, the cumulative one increased significantly in 2020!. © 2022 ISEIS All rights reserved.

4.
22nd IEEE International Conference on Software Quality, Reliability and Security Companion, QRS-C 2022 ; : 340-346, 2022.
Article in English | Scopus | ID: covidwho-2299290

ABSTRACT

The existing studies have applied metamorphic testing technique to testing the medical image classification models, effectively alleviating the test oracle problem and reducing the testing difficulty. However, existing methods mainly focus on constructing metamorphic relations by using general image transformation methods, without combining the knowledge characteristics of medical imaging domain, resulting in problems such as low validity of metamorphic relations. According to the above problems, this paper based on the premise of conforming to the real scenario of image diagnosis, combining the key information of medical image semantics, and constructing general metamorphic relations in this field from three dimensions: the characteristics of medical images in real environment, the regular changes of lesion stage in images and the motion artifacts produced by patients in the process of filming. The medical images classification models of COVID-19 were also selected for instance validation, and the metamorphic relations were quantitatively analyzed to detect inconsistency in the classification results of different models and to assess the robustness of the model. The experimental results show that the constructed metamorphic relations by the key information of medical image semantics are able to detect inconsistencies in the models with a high detection capability, with the inconsistency percentage reaching up to 38.05%. This method can also be extended to test different types of medical image classification models. © 2022 IEEE.

5.
Nature Machine Intelligence ; 2023.
Article in English | Scopus | ID: covidwho-2260047

ABSTRACT

The identification of the mechanisms by which T-cell receptors (TCRs) interact with human antigens provides a crucial opportunity to develop new vaccines, diagnostics and immunotherapies. However, the accurate prediction and recognition of TCR–antigen pairing represents a substantial computational challenge in immunology. Existing tools only learn the binding patterns of antigens from many known TCR binding repertoires and fail to recognize antigens that have never been presented to the immune system or for which only a few TCR binding repertoires are known. However, the binding specificity for neoantigens or exogenous peptides is crucial for immune studies and immunotherapy. Therefore, we developed Pan-Peptide Meta Learning (PanPep), a general and robust framework to recognize TCR–antigen binding, by combining the concepts of meta-learning and the neural Turing machine. The neural Turing machine adds external memory to avoid forgetting previously learned tasks, which is used here to accurately predict TCR binding specificity with any peptide, particularly unseen ones. We applied PanPep to various challenging clinical tasks, including (1) qualitatively measuring the clonal expansion of T cells;(2) efficiently sorting responsive T cells in tumour neoantigen therapy;and (3) accurately identifying immune-responsive TCRs in a large cohort from a COVID-19 study. Our comprehensive tests show that PanPep outperforms existing tools. PanPep also offers interpretability, revealing the nature of peptide and TCR interactions in 3D crystal structures. We believe PanPep can be a useful tool to decipher TCR–antigen interactions and that it has broad clinical applications. © 2023, The Author(s), under exclusive licence to Springer Nature Limited.

6.
Quarterly Review of Economics and Finance ; 87:42005.0, 2023.
Article in English | Scopus | ID: covidwho-2240596

ABSTRACT

In this paper, we exploit the natural experiment of the COVID-19 outbreak and investigate the role of collaborative integration and workplace flexibility in scholarly productivity. Using data on the quantity and quality of the journal and working paper submissions, we first identify a discontinuity pattern in the productivity of Chinese scholars around the Chinese New Year (CNY). Second, we find that COVID-19 has a negative impact on the productivity of Chinese scholars in terms of quantity and quality post-CNY. Furthermore, the short-term detrimental effect on scholarly productivity is induced mainly through the channel of collaborative integration and workplace flexibility due to mitigation policy shocks in terms of social distancing and working-from-home arrangements. The results suggest while advances in virtual communication technologies can facilitate productivity by lowering collaboration costs, virtual team communication cannot be a perfect substitute for face-to-face communication in collaborative integration. In addition, higher workplace flexibility might hinder productivity in sectors relying more on the skills of self-management and discipline. © 2022 Board of Trustees of the University of Illinois

7.
16th ROOMVENT Conference, ROOMVENT 2022 ; 356, 2022.
Article in English | Scopus | ID: covidwho-2237175

ABSTRACT

With the large-scale outbreak of the COVID-19, people have gradually realized the importance of bioaerosols in the environment, and how to efficiently filter out microbial aerosols in the air, so as to create a safe and healthy air environment is urgent. The non-bacteriostatic F6 non-woven filter material and the synthesized new reduced graphene oxide air filter were tested and analyzed in this paper, and the filtration performance of the material against bacterial aerosols in the atmosphere at the initial stage of heating. The results showed that during the initial stage of heating, the particle size distributions of aerosols in the atmosphere during working days were stageⅠ(>7.0μm)4.34%, stageⅡ(4.7~7.0μm)4.62%, stageⅢ(3.3~4.7μm)13.30%, stageⅣ(2.1~3.3μm)21.11%, stageⅤ(1.1~2.1μm)38.70%, stageⅥ(0.65~1.1μm)17.92%. The particle size distributions of aerosols in the atmosphere on non-working days were stageⅠ(>7.0μm)4.52%, stageⅡ(4.7~7.0μm)13.66%, stageⅢ(3.3~4.7μm)23.04%, stageⅣ(2.1~3.3μm)31.82%, stageⅤ(1.1~2.1μm)15.18%, stageⅥ (0.65~1.1μm)11.78%. The new reduced graphene oxide filter material had a 10% increase in the filtration efficiency of the total bacterial aerosol compared with the ordinary non-woven filter material. Among them, the filtration efficiency of the respirable bacterial aerosol (particle size <4.7μm) was significantly improved by 40%. The results of this study could provide a certain reference for building a safe interior in the post-epidemic era, and also provided reference value for the research and development of functional air filters. © 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/)

8.
16th ROOMVENT Conference, ROOMVENT 2022 ; 356, 2022.
Article in English | Scopus | ID: covidwho-2232613

ABSTRACT

The ongoing COVID-19 pandemic made us re-realize the importance of environmental disinfection in indoor areas. Several studies have documented that the air purification system combining UV light and high-efficiency particulate air (HEPA) filtration can successfully remove the virus from the air. However, UV light cannot penetrate deep into the HEPA, which causes the pathogens inside cannot be killed. In this study, we analyzed the potential of three-dimensional(3D) filter media combining with UV sterilization for the treatment of pathogen aerosols. Through geometric ray analysis, it is concluded that the transmittance attenuation of 3D filter material is linear, while that of ordinary fabric filter material is abrupt, which means UV light combining with common fabric filter can only kill the microorganisms on the surface. In order to prove that 3D filter with UV irradiation can eliminate microorganisms inside the 3D filter, we carried out an experimental verification. The results of the experiment shows that the bactericidal rate increased with UV dose and the k value is 3.75*10-4, much smaller than that in air UV disinfection. This indicates that although it is more difficult to kill pathogens on the surface of fibers than in air, 3D filter material with UV can kill the pathogens inside. © 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/)

9.
3rd International Conference on Computer Science and Communication Technology, ICCSCT 2022 ; 12506, 2022.
Article in English | Scopus | ID: covidwho-2223550

ABSTRACT

With the relatively uneven distribution of medical resources in China and a new outbreak of COVID-19 at the end of 2019, we developed an intelligent medicine cabinet to alleviate the problem of high pressure and difficulty in accessing medical care in hospitals around the country. The medicine cabinet has a signal transmission circuit system based on 51 microcontroller and a new X-Y trajectory control module, which controls the Pulse Width Modulation (PWM) signal by Proportion Integration Differentiation (PID) algorithm to improve the accuracy of the DC motor. It has the functions of online drug selection, drug sales, drug transmission, etc. Meanwhile, the online drug purchase system based on the WeChat applet can reduce the probability of infection by a new coronavirus. And the new X-Y cargo track will significantly improve the safety of fragile drugs while ensuring their delivery. The development of this medicine cabinet will greatly reduce the operating cost of pharmacies and meet the demand of people to purchase medicine at night. © 2022 SPIE.

10.
9th Research in Engineering Education Symposium and 32nd Australasian Association for Engineering Education Conference: Engineering Education Research Capability Development, REES AAEE 2021 ; 1:543-550, 2021.
Article in English | Scopus | ID: covidwho-2207007

ABSTRACT

CONTEXT The key purpose of Work Integrated Learning (WIL) is to offer domestic and international students the opportunity to explore and participate in real-life projects offered by industry or community integrating theory with practice. There are a variety of structured activities, for example, internships, field trips, industry guest speakers, and the industry or community projects. These activities are aligned with students' needs in gaining professional experience and enhancing their employability skills, as well as with engineering curriculum requirements. The literature presents numerous papers discussing students' WIL practices and students' expectations;however, it becomes more complex when international students need to be prepared for and made capable of understanding and navigating the cultural nuances and workplace differences. Previous studies (Jackson, 2017;Jackson, Rowbottom, Ferns, & McLaren, 2017;Kaider, Friederika;Suri, Harsh;Read, Wayne;Russell, Leoni;& Marlow, 2020) discussed the relevance of WIL program and the difficulties faced by the international students in Australia. PURPOSE OR GOAL In addition to providing equal opportunity to domestic and international students to gain hands-on skills and job readiness via WIL activities, the industrial experience component is compulsory for accreditation purposes in most engineering courses. This study aims to evaluate international students' experience and challenges faced by them in seeking local industry placements. Naturally, some strategies published previously do not address the COVID-19 situation and its effects on WIL. The pandemic has introduced significant challenges in effectively implementing WIL and industry placements. This paper observes and evaluates the current challenges faced by international students in gaining meaningful experiences. It also seeks to better understand students' perspectives and assess the effectiveness of the mitigation strategies put in place during the pandemic APPROACH OR METHODOLOGY/METHODS Exploratory research is the most suitable method to support the main objectives of this study. Desktop research covers recent journal and conference publications in the field, government statistics, and reports from Engineering Educational institutes. The questionnaire-based on the Likert scale will provide insights of student motivation level with industry placement, job readiness, and knowledge gain of local professional practice. The semi-structured interviews include questions focused on new technical and personal skills gained to enhance students' competitiveness to find a job in the engineering industry under the global pandemic scenario ACTUAL OR ANTICIPATED OUTCOMES It is ongoing research that will be completed in the coming months. Currently, international students require more support to overcome the challenging time due to COVID-19. The anticipated outcomes include the new challenges associated with work integrated learning programs posed by COVID-19 and the effectiveness of various measures in conquering the difficulty. Copyright © Indumathi V, Ana Evangelista, Arti Siddhpura, Yuanyuan Fan and Milind Siddhpura, 2021.

11.
Huanjing Kexue/Environmental Science ; 43(12):5522-5533, 2022.
Article in Chinese | Scopus | ID: covidwho-2203843

ABSTRACT

During the CIVID-19 pandemic, water samples were collected from 26 sampling points in 18 typical drinking water sources in Wuhan, located in the middle reaches of the Yangtze River. Ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) methods were used to measure the concentrations of 31 pharmaceuticals and personal care products (PPCPs) in the water samples. The pollution characteristics of PPCPs were analyzed and their ecological and health risks were assessed. The results showed that a total of 23 PPCPs were detected in the 26 sampling points. Among them, five types of PPCPs were detected with a detection rate of 100%, with total concentrations ranging from 102.44 ng•L -1 to 745.78 ng•L -1, and the average concentration was 206.87 ng•L -1. The highest concentrations were in salicylic acid (SA) and doxycycline (DIC), ranging from 28.24 to 534.24 ng•L -1 and 28.72 to 416.6 ng•L -1, respectively. According to the spatial distribution of PPCPs, the concentration of antibiotics in the Hanjiang River was higher than that in the Yangtze River, whereas the concentration of other types of PPCPs in the Yangtze River was higher than that in the Hanjiang River. The ecological risk assessment results showed that the toxic risk in algae was higher than those in invertebrates and fish. The risks of salicylic acid (SA), doxycycline (DIC), lincomycin (LIN), and chlortetracycline (CTE) to algae were at a high level, and the ecological risk of PPCPs in the Hanjiang River was generally higher than that in the Yangtze River. The health risk assessment results showed that the risk to adults and children by drinking water ranged from 1.14 × 10 -4 to 0.136 and from 1.04 × 10 -4 to 0.821, respectively. The health risk to children was higher than that to adults, although their levels were low. Compared with the concentrations of PPCPs in drinking water sources of Wuhan in recent years, under the CIVID-19 pandemic, the pollution status of PPCPs in the Yangtze River was at a medium level, whereas it was at a high level in the Hanjiang River. © 2022 Science Press. All rights reserved.

12.
2022 IET International Conference on Engineering Technologies and Applications, IET-ICETA 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2191942

ABSTRACT

In this paper, we proposed 'YOLO-R based mask recognition system with Winograd convolution acceleration chip.' In order to prevent the spread of COVID-19, we proposed a mask recognition system based on YOLO-R that adopted the CSP backbone architecture and used prediction refinement to predict, optimize, and obtain high recognition results. In addition, we designed the Winograd convolution acceleration chip to accelerate the operation of the YOLO-R neural network, so that the system can achieve real-time computing. © 2022 IEEE.

13.
2022 IET International Conference on Engineering Technologies and Applications, IET-ICETA 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2191941

ABSTRACT

In this paper, we proposed COVID-19 lung CT (computed tomography) images recognition with superscalar winograd circuit based on VGG19. We adopt the VGG-19 machine learning architecture to recognize lung CT images and speed up neural network operations through Superscalar Winograd Circuit. After a series of experiments, our proposed method has a high pneumonia recognition rate and high computational efficiency. © 2022 IEEE.

14.
9th International Conference on Dependable Systems and Their Applications, DSA 2022 ; : 178-183, 2022.
Article in English | Scopus | ID: covidwho-2136156

ABSTRACT

The application of machine learning classification algorithms to COVID-19 for CT images assisted diagnosis not only reduces the workload of radiologists in reviewing films, but also improves the accuracy and efficiency of the assisted diagnosis results. However the instability of such machine learning models may lead to misclassification of results, and the expected output of the models may not be available due to the lack of transparency, which make the obtaining of test oracle difficultly. Thus in this paper, the metamorphic testing technique is applied to test the intelligent diagnosis classification program of COVID-19. The metamorphic relation is constructed by analyzing the characteristics of the lesion areas in the CT images of COVID-19, and compare consistency of the follow up test cases with the original test cases, that is how the failure detection rate of the program can be verified. The experimental results show that this method can detect the inconsistency of this program and it can be extended to test intelligent diagnosis classification programs of different diseases, thus further improving the accuracy of diagnosis classification programs. © 2022 IEEE.

15.
4th Conference on Blockchain Research and Applications for Innovative Networks and Services, BRAINS 2022 ; : 49-50, 2022.
Article in English | Scopus | ID: covidwho-2136125

ABSTRACT

In response to the coronavirus pandemic, COVID-19, the use of online media and teaching tools has soared, leading to rampant cheating and plagiarism. To provide a better online environment, A copyright-aware Blockchain-enabled Knowledge Sharing platform named as BeSharing, enables students to share part of their assignments or ideas without the worry of being plagiarized. Thanks to blockchain technology which ensures the safety of encrypted shared files and the immutability of the shared records, the intellectual property rights of students can be protected whenever plagiarism issues occur. At present, we have released the platform with the realization of relevant functions and finished the alpha test. We believe this platform has great potential to foster collaboration among students while protecting their ideas. © 2022 IEEE.

16.
Chemical Engineering Transactions ; 94:1-12, 2022.
Article in English | Scopus | ID: covidwho-2089744

ABSTRACT

The paper provides an updated overview of the main achievements and ideas presented at the most recent PRES conferences and in the fields which have been covered by them. The conference history now reached a quarter of the century - from 1998 to 2022. The PRES conferences have become one of the main vehicles for spreading Process Integration (PI) into various research directions and fields of possible implementation. The PRES went successfully during the last period challenged by COVID-19 pandemics. Not all conferences managed to adapt well. However, PRES successfully implemented the hybrid mode and learned how to use it efficiently for enlarging the number of speakers as well as the audience while still keeping very intensive and beneficial cross-fertilisation and networking. Some experiences have been shared in this paper. The hybrid mode helped successfully intensify the research efforts on the research challenge, which remained as a consequence of the COVID-19 pandemics - an increased amount of waste and during the life and economy recovery also increasing environmental footprints. This short overview includes (i) Process Integration with Pinch Analysis (ii) Process Integration with another approach (iii) Development of heat exchanger systems for Process Integration (iv) Other extensions of Process Integration for wider Process Systems Engineering and recently (v) Circular economy (vi) Environmental footprints and nexuses and just (vii) COVID-19 pandemics energy and environmental consequences and recovery. This paper presents an attempt to demonstrate and make suggestions for the future growth of the Process Integration branching out during the next years. Copyright © 2022, AIDIC Servizi S.r.l.

17.
Chinese Medical Ethics ; 35(3):326-331, 2022.
Article in Chinese | Scopus | ID: covidwho-1988514

ABSTRACT

In order to understand the current status of the knowledge, attitude and practice (KAP) about prevention and control of COVID-19 in college students, and to provide theoretical basis for prevention and control work in college campus. This study investigated the KAP of COVID-19 of 1 847 college students in Shaanxi province by questionnaire using the convenience sampling method. Chisquare test and multivariate logistic regression analysis were used to analyze the influencing factors for the KAP of COVID-19. The results demonstrated that 48.3% of the students had a higher knowledge level of COVID-19, 11.7% had a fear attitude and 39.6% had good protective practices. Logistic regression results showed that female and urban household college students had higher cognitive level of COVID-19. The college students with anxiety state were more likely to have fear attitude. Students of female, urban household, anxiety, higher cognition and fear attitude showed better protective practices. The above results indicated that the knowledge level of COVID-19 in college students are not enough, and the attitude and protective practices need to be further improved. Therefore, relevant departments should follow the rules of KAP, carry out targeted propaganda and education on COVID-19 for college students, to improve their ability to cope with public health emergencies. © 2022, Editorial department of Chinese Medical Ethics. All rights reserved.

18.
Contemporary Educational Technology ; 14(3), 2022.
Article in English | Scopus | ID: covidwho-1924945

ABSTRACT

Educators have increasingly turned to social media for their instructional, social, and emotional needs during the COVID-19 pandemic. In order to see where support and professional development would be needed and how the educational community interacted online, we sought to use existing Twitter data to examine potential educators’ networking and discourse patterns. Specifically, this mixed-methods study explores how educators used Twitter as a platform to seek and share resources and support during the transition to remote teaching around the start of massive school closures due to the pandemic. Based on a public COVID-19 Twitter chatter database, tweets from late March to early April 2020 were searched using educational keywords and analyzed using social network analysis and thematic analysis. Social network analysis findings indicate that the support networks for educators on Twitter were sparse and consisted of mainly small, exclusive communities. The networks featured one-on-one interactions during the early pandemic, highlighting that there were few large conversations that most educators were part of but rather many small ones. Thematic analysis findings further suggest that both informational and nurturant support were relatively equally present on Twitter among educators, particularly pedagogical content knowledge and gratitude. This study adds to an understanding of the educational networks as a means of professional and personal support. Additionally, findings present the discourse featured in educator networks at the onset of an educational emergency (i.e., COVID-19) as decentralized as well as desiring pedagogical content knowledge and emotional sharing. © 2022 by authors;licensee CEDTECH by Bastas, CY.

19.
2022 International Conference on Algorithms, Microchips and Network Applications ; 12176, 2022.
Article in English | Scopus | ID: covidwho-1923085

ABSTRACT

In order to overcome the trend influence of novel Coronavirus epidemic in the future, this paper proposes the panel data modeling method based on big data crawler technology, which is based on Python crawler technology to obtain a more effective estimation model from the dynamic perspective of time and cross section. The results showed that the fixed effect error rate established by the development of COVID-19 in China, Japan, South Korea, Germany and Italy was about 3%, and there is a positive correlation between cured cases and confirmed cases of COVID-19. The predicted confirmed cases of COVID-19 in week 63 will be 69, 11,908, 3156, 112293 and 147,545, respectively. © COPYRIGHT SPIE. Downloading of the is permitted for personal use only.

20.
Traditional Medicine Research ; 7(3), 2022.
Article in English | EMBASE | ID: covidwho-1822801

ABSTRACT

Coronaviruses exist widely in nature, can cause cross-species transmission, and pose serious threats to human and animal health. Over the past 20 years, coronaviruses have led to three major epidemics that have caused global panic, including severe acute respiratory syndrome, Middle East respiratory syndrome, and coronavirus disease-19. At present, coronavirus disease-19 not only spreads rapidly, but also mutates easily to escape host immune response, becoming more pathogenic. At present, there are no effective specific therapeutic drugs or vaccines. Drugs targeting severe acute respiratory syndrome coronavirus 2 and the host cell defense system that have been developed based on the structure and replication cycle of coronaviruses have a certain broad-spectrum antiviral effect;however, their efficacy still needs to be demonstrated in further clinical trials. Traditional Chinese medicine has an indispensable role in the ongoing response to coronavirus disease-19. Anti-virus treatment with traditional Chinese medicine has advantages such as broad-spectrum application, low toxicity and side effects, low susceptibility to drug resistance, and overall comprehensive regulation. Therefore, researches on effective components and mechanisms of action of the anti-viral effects of traditional Chinese medicine have increasingly gained attention. The present paper examines coronaviruses, specifically summarizing the genomes, replication mechanisms, and mutant strains. Afterward, the therapeutic effects and mechanisms of action of modern broad-spectrum anti-coronavirus drugs and traditional Chinese medicine are summarized. By considering the virus and the targets in the host comprehensively, in addition to the beneficial multi-target and multi-path antiviral effects of traditional Chinese medicines, this paper could guide the development of treatment strategies for broad-spectrum anti-coronavirus traditional Chinese medicines, and could facilitate the modernization and globalization of traditional Chinese medicine.

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