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Many studies have analyzed the asymmetric relationship between hotel service quality attributes and satisfaction, and tried to find consumers' satisfiers and dissatisfiers, aiming at enhancing satisfaction more efficiently. However, the impact of COVID-19 has led to changes in consumers' expectations for hotel services, and the above findings might face invalidation. To date, we are still unknown whether consumers' satisfiers/dissatisfiers changed. This study fills this research gap by mining online reviews of five-star hotels from Shanghai and Beijing before and during the pandemic. The results found that the asymmetric categories of Sleep quality and Internet/Wi-Fi attributes have changed. Specifically, Sleep quality and Internet/Wi-Fi became dissatisfiers from hybrids, indicating that hoteliers only need to maintain their normal performance, and do not invest too many resources because they bring no satisfaction;attributes like Room, decoration, etc. remain hybrids. Additionally, we performed opinion extraction for the dissatisfier attributes to further understand what causes consumer dissatisfaction. The results contribute to the literature by shedding light on the pandemic's impacts on the asymmetric effects of service quality attributes. The cause analysis can help hoteliers develop specific measures to mitigate the adverse effects of COVID-19.
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Background The coronavirus disease 2019 (COVID-19) cases continue to rise, and the demand for medical treatment and resources in healthcare systems surges. Assessing the viral shedding time (VST) of patients with COVID-19 can facilitate clinical decision making. Although some studies have been conducted on the factors affecting the VST of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2), few prediction models are currently available. Methods This retrospective study included the consecutive patients with COVID-19 admitted to Xi'an Chest Hospital in Shaanxi, China, for treatment between December 19, 2021 and February 5, 2022. The clinical data of the patients were extracted from their electronic medical records. Combining significant factors affecting the VST, a nomogram was developed to predict the VST of the SARS-CoV-2 Delta variant in patients with COVID-19. Results We included 332 patients in this study. The average VST was 21 d. VST was significantly prolonged in patients with severe clinical symptoms, sore throat, old age, long time from onset to diagnosis, and an abnormal white blood cell count. Consequently, we developed a nomogram prediction model using these 5 variables. The concordance index (C-index) of this nomogram was 0.762, and after internal validation using bootstrapping (1000 resamples), the adjusted C-index was 0.762. The area under the nomogram's receiver operator characteristic curve showed good discriminative ability (0.965). The calibration curve showed high consistency. The VST was prolonged in the group with lower model fitting scores according to the Kaplan-Meier curve (χ2=286, log-rank P < 0.001). Conclusions We developed a nomogram for predicting VST based on 5 easily accessible factors. It can effectively estimate the appropriate isolation period, control viral transmission, and optimize clinical strategies. © Wolters Kluwer Health, Inc. All rights reserved.
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Spike proteins of coronaviruses are highly glycosylated and responsible for host recognition and viral entry. The glycans provide a camouflaging shield to help coronaviruses evade host immunity and, in some cases, modulate functional domain structures and dynamics pertinent to host recognition. However, the glycans are chemically and conformationally heterogeneous, making it challenging to determine the chemical compositions and conformations quantitatively. Combining cryo-electron microscopy, mass spectrometry, and molecular modeling, we systematically characterize a panel of spike protein variants of human and animal coronaviruses, including those of the variants of concern of SARS-CoV-2. We have established a robust workflow to quantify the heterogeneity of individual N-glycans by mass spectrometry. We also demonstrated the ability to visualize long glycan structures directly in regions where the dynamics are restricted. In places where the N-glycans are too dynamic, their structural information is generally lost after extended cryo-EM data processing that aims to achieve high resolution. To address this issue, we developed a computational tool called GlycoSHIELD to generate ensembles of glycan conformers to recapitulate the fuzzy structures that are in quantitative agreement with the experimental cryo-EM data. The ability to generate fully glycosylated spike protein models enables the prediction of hitherto unknown receptor and antibody binding sites. This work was supported by Academia Sinica intramural fund, an Academia Sinica Career Development Award, Academia Sinica to STDH (AS-CDA-109- L08), an Infectious Disease Research Supporting Grant to STDH (AS-IDR- 110-08), and the Ministry of Science and Technology (MOST), Taiwan (MOST 109-3114-Y-001-001, MOST 110-2113-M-001- 050-MY3 and MOST 110-2311-B-001-013-MY3) to STDH.Copyright © 2023 The American Society for Biochemistry and Molecular Biology, Inc.
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During the COVID-19 epidemic, the online prescription pattern of Internet healthcare pro-vides guarantee for the patients with chronic diseases and reduces the risk of cross-infection, but it also raises the burden of decision-making for doctors. Online drug recommendation system can effectively assist doctors by analysing the electronic medical records (EMR) of patients. Unlike commercial recommendations, the accuracy of drug recommendations should be very high due to their relevance to patient health. Besides, concept drift may occur in the drug treatment data streams, handling drift and location drift causes is critical to the accuracy and reliability of the rec-ommended results. This paper proposes a multi-model fusion online drug recommendation system based on the association of drug and pathological features with online-nearline-offline architecture.The system transforms drug recommendation into pattern classification and adopts interpretable concept drift detection and adaptive ensemble classification algorithms. We apply the system to the Percutaneous Coronary Intervention (PCI) treatment process. The experiment results show our system performs nearly as good as doctors, the accuracy is close to 100%.
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Purpose: Virtual tourism has become popular in recent years. However, there is still a research gap on virtual tourist motivation. This study aims to identify virtual tourist motivation and explore the relationship between virtual tourism and on-site tourism. Design/methodology/approach: This research identifies virtual tourist motivation based on Means-end chain (MEC) theory. Laddering interviews with 32 respondents were conducted to construct a hierarchical value map. Additionally, a motivation analysis of virtual tourism and on-site tourism was developed based on a review of the relevant literature. Findings: This exploratory study revealed 12 attributes, 9 results and 4 values that virtual tourists wish to achieve and identified 5 means-end chains where self-satisfaction is the most important value-led motivation. Compared with on-site tourism motivations, virtual tourism shows possibilities of replacing, complementing and extending on-site tourism under certain circumstances. However, it significantly depends on whether tourists are attracted by the technical characteristics, security and experience conditions of virtual tourism. Originality/value: This study contributes to understanding virtual tourist motivation and offers motivation-based insights into the relationship between virtual and on-site tourism. Managerial implications on how to attract potential online tourists are also provided. © 2023, Emerald Publishing Limited.
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Digital microfluidic (DMF) has emerged as one of the most popular microfluidic platforms for sample-preparation in biochemical analysis and lab-on-a-chip applications. Operated with electrowetting on dielectric (EWOD) mechanism, DMF conventionally requires an external power source to provide the actuation voltage, which limited its portability and broader applications in point-of-care testing (POCT) environment. Herein, a DMF device, self-powered by triboelectric nanogenerator (TENG) is presented. TENG possesses a number of unique characteristics, and is very attractive to be integrated with DMF. It only requires a simple configuration with low-cost fabrication that can improve the DMF portability, but it also provides high voltage, low current output characteristics that are consistent with the EWOD actuation requirements. Basic droplet manipulations, including transportation, split, merge, dispense, and even elongate to follow the electrode patterns of alphabets, on a DMF device powered with manually-rotated Disk-TENG are demonstrated for the first time. Further, droplets containing samples and reagents are transported and mixed on the programmed electrode patterns on the chip to conduct chemical reactions, including nucleic acid amplification and phenol red test, showing that Disk-TENG can serve as the power source for DMF chips in POCT applications. © 2023 Elsevier Ltd
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Viruses lacking the capacity to infect mammals exhibit minimal toxicity, good biocompatibility, and well-defined structures. As self-organized biomolecular assemblies, they can be produced from standard biological techniques on a large scale at a low cost. Genetic, chemical, self-assembly, and mineralization techniques have been applied to allow them to display functional peptides or proteins, encapsulate therapeutic drugs and genes, assemble with other materials, and be conjugated with bioactive molecules, enabling them to bear different biochemical properties. So far, a variety of viruses (infecting bacteria, plants, or animals), as well as their particle variants, have been used as biomaterials to advance human disease prevention, diagnosis, and treatment. Specifically, the virus-based biomaterials can serve as multifunctional nanocarriers for targeted therapy, antimicrobial agents for infectious disease treatment, hierarchically structured scaffolds for guiding cellular differentiation and promoting tissue regeneration, versatile platforms for ultrasensitive disease detection, tissue-targeting probes for precision bioimaging, and effective vaccines and immunotherapeutic agents for tackling challenging diseases. This review provides an in-depth discussion of these exciting applications. It also gives an overview of the viruses from materials science perspectives and attempts to correlate the structures, properties, processing, and performance of virus-based biomaterials. It describes the use of virus-based biomaterials for preventing and treating COVID-19 and discusses the challenges and future directions of virus-based biomaterials research. It summarizes the progressive clinical trials of using viruses in humans. With the impressive progress made in the exciting field of virus-based biomaterials, it is clear that viruses are playing key roles in advancing important areas in biomedicine such as early detection and prevention, drug delivery, infectious disease treatment, cancer therapy, nanomedicine, and regenerative medicine. © 2023 Elsevier B.V.
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Medical image classification often relies on Convolutional Neural Network (CNN) for its powerful ability to obtain accurate predictions. However, considering novel diseases such as COVID variants and complications, the medical and clinical field desires diagnosis that is both fast and accurate. This paper proposes a lightweight method that conducts deep learning-based classification in the Fourier domain without convolution operation and reduces the computational cost. The paper focuses specifically on pneumonia, which is a lung infection and a typical COVID complication. To achieve a decent accuracy that is comparable to the CNN performance, signal processing techniques, namely Fourier transform is utilized to extract features from the frequency domain. The proposed method uses Discrete Cosine Transform (DCT) to find the frequency domain values as well as other useful parameters. As part of the methodology, a fundamental Artificial Neural Network (ANN) is built to perform the classification task. In the meanwhile, two pre-trained CNN architectures, ResNet50V2 and VGG19, are implemented under the same environment as standards for comparison. With the same hyperparameters and training epochs, the ANN obtained a validation accuracy that is 2.35% lower than the CNNs but 15 times faster in training. The experimental result demonstrates the advantage of the proposed method in inference speed and model size, indicating that the overall objective is attained. The findings also open the possibility of generalizing such an approach for other medical diagnosis in the future. © 2022 IEEE.
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Nucleic acid detection has been one of the most valued tools in point-of-care diagnostics from life science, agriculture, food safety and environmental surveillance, because of its high sensitivity, great specificity and simple operation. Since polymerase chain reactions (PCR) were discovered, more and more researchers attach importance to exploring ultrafast nucleic acid amplification methods for further expediting the process of detection and curbing infectious diseases' high spread rate, especially after the coronavirus disease 2019 (COVID-19) worldwide pandemic event. Nowadays, nanotechnology as one of the most cut-ting-edge technologies has aroused growing attention. In this review, we describe new advances in na-notechnology research for ultrafast nucleic acid amplification. We have introduced commonly used nanotechnologies, namely nanofluidics, nanoporous materials, nanoparticles and so on. Recent advances in these nanotechnologies for ultrafast sample pretreatments, accelerated enzymatic amplification and rapid heating/cooling processes was summarized. Finally, challenges and perspectives for the future applications of ultrafast nucleic acid amplification are presented.(c) 2022 Elsevier Ltd. All rights reserved.
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Objective To analyze the medication rules of related epidemic disease prescription in Treatise on Febrile Diseases based on data mining, and the mechanism of "Chaihu (Bupleuri Radix)-Huangqin (Scutellariae Radix)” as the core drugs in the treatment of coronavirus disease 2019 (COVID-19) by network pharmacology, in order to explore the contemporary value of classical prescriptions in the treatment of epidemic diseases. Methods The prescriptions for treating epidemic diseases in Treatise on Febrile Diseases were screened, and the medication rules such as drug frequency, flavor and meridian tropism as well as correlation, apriori algorithm were analyzed by using software such as R language. The mechanism of the core drugs in the medication pattern in the treatment of COVID-19 was explored by the network pharmacology. A "disease-drug-ingredient-target” network was constructed on the selected components and targets with Cytoscape. The key targets were introduced into String database for network analysis of protein-protein interaction (PPI), and gene ontology (GO) functional analysis and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were conducted in R language. Results A total of 61 prescriptions for treating epidemic diseases in Treatise on Febrile Diseases were included, including 52 traditional Chinese medicines (TCMs). In the top 20 high-frequency drugs, warm drugs, spicy drugs and qitonifying drugs were mainly used, mostly in the spleen and lung meridian. Chaihu (Bupleuri Radix) and Huangqin (Scutellariae Radix) herb pair had the strongest correlation. A total of five clusters were excavated: supplemented formula of Xiaochaihu Decoction (小柴胡汤), Sini Decoction (四逆汤), supplemented formule of Maxing Shigan Decoction (麻杏石甘汤), Fuling Baizhu Decoction (茯苓白术汤) and Dachengqi Decoction (大承气汤). A total of 45 active ingredients, 189 action targets of Bupleuri Radix-Scutellariae Radix herb pair, and 543 targets of COVID-19 were obtained from TCMSP and Genecards, and 64 intersection targets were generated. The results of the network analysis showed that the main components of core drugs pair against COVID-19 may be quercetin, wogonin, kaempferol baicalein, acacetin etc., and the core targets may be VEGFA, TNF, IL-6, TP53, AKT1, CASP3, CXCL8, PTGS2, etc. A total of 1871 related entries and 164 pathways were obtained by GO and KEGG enrichment analysis, respectively. Conclusion In Treatise on Febrile Diseases, the treatment of epidemic diseases mainly chose pungent, warm, spleen-invigorating and qi-tonifying herbs, such as Xiaochaihu Decoction, Sini Decoction and Dachengqi Decoction, etc. It was found that Bupleuri Radix-Scutellariae Radix core herb pair prevent and treat COVID-19 through multi-target targets such as PTGS2, IL-6 and TNF. The ancient prescriptions for treating epidemic disease in Treatise on Febrile Diseases may have significant reference value for the prevention and treatment of new epidemic diseases today. © 2023 Editorial Office of Chinese Traditional and Herbal Drugs. All rights reserved.
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Introduction: The COVID-19 pandemic has deeply influenced the primary healthcare system in Portugal. Knowing that the first two years of life are a period of major development, it is necessary to comply with all the standard moments of screening, surveillance, and immunization during this period. This study aimed to characterize health surveillance in the first two years and evaluate the fulfillment of guideline 008/2020 released on 26th March 2020 by Direção Geral da Saúde during the COVID-19 pandemic. Methods: This cross-sectional study was conducted based on the application of an anonymous questionnaire to caretakers of children under 24 months of age through social media. The data refers to the period of March 2020 to March 2021. Results: This study included 452 children. The coverage of the newborn metabolic screening was 99.6%. Regarding vaccination, 81.9% of the children fulfilled the national program on time and 15.9% with delay. Around one third of the children experienced delay and/or cancelation of the routine consultations. In the group of children aged between 12-18 months (n = 150), 69.3% complied with the minimum of six consultations during the first year of life, while in the group aged between 18-24 months (n = 116), 72.4% complied with the minimum of one consultation during this period. Conclusion: It is necessary to create strategies to improve compliance with the 008/2020 guideline, especially regarding immunization and consultations at the defined ages to optimize children's health surveillance even during pandemics. © Author(s) (or their employer(s)) and Portuguese Journal of Pediatrics 2023. Re-use permitted under CC BY-NC. No commercial re-use.
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Objective To analyze the medication rules of related epidemic disease prescription in Treatise on Febrile Diseases based on data mining, and the mechanism of "Chaihu (Bupleuri Radix)-Huangqin (Scutellariae Radix)" as the core drugs in the treatment of coronavirus disease 2019 (COVID-19) by network pharmacology, in order to explore the contemporary value of classical prescriptions in the treatment of epidemic diseases. Methods The prescriptions for treating epidemic diseases in Treatise on Febrile Diseases were screened, and the medication rules such as drug frequency, flavor and meridian tropism as well as correlation, apriori algorithm were analyzed by using software such as R language. The mechanism of the core drugs in the medication pattern in the treatment of COVID-19 was explored by the network pharmacology. A "disease-drug-ingredient-target" network was constructed on the selected components and targets with Cytoscape. The key targets were introduced into String database for network analysis of protein-protein interaction (PPI), and gene ontology (GO) functional analysis and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were conducted in R language. Results A total of 61 prescriptions for treating epidemic diseases in Treatise on Febrile Diseases were included, including 52 traditional Chinese medicines (TCMs). In the top 20 high-frequency drugs, warm drugs, spicy drugs and qitonifying drugs were mainly used, mostly in the spleen and lung meridian. Chaihu (Bupleuri Radix) and Huangqin (Scutellariae Radix) herb pair had the strongest correlation. A total of five clusters were excavated: supplemented formula of Xiaochaihu Decoction (), Sini Decoction (), supplemented formule of Maxing Shigan Decoction (), Fuling Baizhu Decoction () and Dachengqi Decoction (). A total of 45 active ingredients, 189 action targets of Bupleuri Radix-Scutellariae Radix herb pair, and 543 targets of COVID-19 were obtained from TCMSP and Genecards, and 64 intersection targets were generated. The results of the network analysis showed that the main components of core drugs pair against COVID-19 may be quercetin, wogonin, kaempferol baicalein, acacetin etc., and the core targets may be VEGFA, TNF, IL-6, TP53, AKT1, CASP3, CXCL8, PTGS2, etc. A total of 1871 related entries and 164 pathways were obtained by GO and KEGG enrichment analysis, respectively. Conclusion In Treatise on Febrile Diseases, the treatment of epidemic diseases mainly chose pungent, warm, spleen-invigorating and qi-tonifying herbs, such as Xiaochaihu Decoction, Sini Decoction and Dachengqi Decoction, etc. It was found that Bupleuri Radix-Scutellariae Radix core herb pair prevent and treat COVID-19 through multi-target targets such as PTGS2, IL-6 and TNF. The ancient prescriptions for treating epidemic disease in Treatise on Febrile Diseases may have significant reference value for the prevention and treatment of new epidemic diseases today. Copyright © 2023 Editorial Office of Chinese Traditional and Herbal Drugs. All rights reserved.
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The study of information spreading is important and necessary, especially during the Coronavirus, when plenty of opinions aroused in the Chinese Sina-microblog. On the basis of previous studies, we propose a comprehensive susceptible-reading-forwarding-immune (SRFI) model with considering user active search. We establish differential equations introducing average active reading rate to describe the multi-information propagation process. By using typical event about COVID-19 during the outbreak of public opinion to carry out the numerical fitting experiment to estimate model parameters, fit real data, and analyze the calculated information transmission indexes, we verify the validity of the model. We analyze the sensitivity of multiple parameters to multi-information transmission index based on reading and forwarding and the effect of average active reading rate to show the influence of the new parameter on multi-information transmission. In addition, to compare the predictive ability of the previous model with our new model, we use the early prediction method. Result shows that our new model can forecast the process of multi-information transmission faster and more exactly. The conclusions above indicate that the role of user active search is not negligible and the I-SRFI model can help us design effective communication strategies for rapid implementation of public health interventions. © 2022 IEEE.
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Objective: To summarize the management and short-term outcomes of neonates delivered by mothers infected with SARS-CoV-2 Omicron variant. Methods: A retrospective study was performed on 158 neonates born to mothers infected with SARS-CoV-2 Omicron variant admitted to the isolation ward of Children's Hospital of Fudan University from March 15th, 2022 to May 30th, 2022. The postnatal infection control measures for these neonates, and their clinical characteristics and short-term outcomes were analyzed. They were divided into maternal symptomatic group and maternal asymptomatic group according to whether their mothers had SARS-CoV-2 symptoms. The clinical outcomes were compared between the 2 groups using Rank sum test and Chi-square test. Results: All neonates were under strict infection control measures at birth and after birth. Of the 158 neonates, 75 (47.5%) were male. The gestational age was (38+3±1+3) weeks and the birth weight was (3 201±463)g. Of the neonates included, ten were preterm (6.3%) and the minimum gestational age was 30+1 weeks. Six neonates (3.8%) had respiratory difficulty and 4 of them were premature and required mechanical ventilation. All 158 neonates were tested negative for SARS-COV-2 nucleic acid by daily nasal swabs for the first 7 days. A total of 156 mothers (2 cases of twin pregnancy) infected with SARS-CoV-2 Omicron variant, the time from confirmed SARS-CoV-2 infection to delivery was 7 (3, 12) days. Among them, 88 cases (56.4%) showed clinical symptoms, but none needed intensive care treatment. The peripheral white blood cell count of the neonates in maternal symptomatic group was significantly higher than that in maternal symptomatic group (23.0 (18.7, 28.0) × 109 vs. 19.6 (15.4, 36.6) × 109/L, Z=2.44, P<0.05). Conclusions: Neonates of mothers infected with SARS-CoV-2 Omicron variant during third trimester have benign short-term outcomes, without intrauterine infection through vertical transmission. Strict infection control measures at birth and after birth can effectively protect these neonates from SARS-CoV-2 infection.
Subject(s)
COVID-19 , Pregnancy Complications, Infectious , Female , Humans , Infant , Infant, Newborn , Male , Pregnancy , Mothers , Pregnancy Complications, Infectious/diagnosis , Pregnancy Complications, Infectious/prevention & control , Retrospective Studies , SARS-CoV-2ABSTRACT
The sudden outbreak of COVID-19 has caused a surge in medical demand. It has inspired people to continuously explore how to transform public buildings such as gymnasiums in a fast, low-cost and green way during emergencies. The article studies the feasibility of applying gymnasium to sudden public events, discusses the design methods for the renovation of gymnasium space, water supply and drainage system, ventilation system and intelligent system in emergency situations. The focus is on preventing cross-contamination, preventing backflow contamination, pressure shaving, airflow organization, and system control. Through these design methods, the gymnasium has the characteristics of efficient, adaptable and inclusive epidemic prevention. The application prospect of green building technology in emergency reconstruction was explored, and a reference is put forward for the design and reconstruction of gymnasiums in the post-epidemic era with “combination of epidemic control” and improving the resilience space of gymnasiums. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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The outbreak of COVID-19 has been a critical social event in the past two years. The pandemic has seriously affected the world. Meanwhile, various forms of data about COVD-19 emerge on the Web endlessly, such as SNS discussions, Press releases, WHO statistics, etc. It is valuable work for government departments, news media, and health organizations to integrate and analyze these pandemics-related multi-source data on the web. In this work, we propose an interactive visual analytics system as CVAS that aims at mining and analyzing multi-source data concerned with COVD-19. Having been inspired by the Sankey diagram, we developed a view elaborately. Through appropriate interactions, massive patients' mobility data can be visualized, thus showing the spread features of the pandemic in time and space more specifically. In addition, we collected more than 10,000 trending topics and nearly 10 million related comments on the SNS as Sina Weibo. We performed NLP to analyze their sentiment, identifying key events since the outbreak and the impact of the pandemic on public sentiment. Part of our work was awarded at the China visualization and visual analysis conference (ChinaVis2020) and recognized by peers. © 2022 ACM.
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Under the serious influence of COVID-19, online teaching has become a mainstream teaching mode. During the online teaching, it is difficult for teachers to evaluate and intervene in students' learning in real time. Therefore, for students who lack self-control, it is possible to be stuck in low learning efficiency and even failure of course assessment. How to obtain valid information of students' learning status in time during the online teaching process is a hot research topic at present. This paper proposes a feedback service for teaching based on educational data mining. It can, through a reasonable analysis of the data submitted in form of students' homework, accurately screen out students who have difficulties in learning a certain course and give directions to achieve the purpose of optimizing the teaching. © 2022 IEEE.
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Although the government contributes to the tourism recovery, the influence of the government on the micro-perceptions of tourism managers remains limited. The results of 415 samples demonstrate that government crisis management restores managers' confidence through different mediation of the sense of gain. Information and communication management improve only their sense of spiritual gain, while human resource development enhance merely their sense of material gain. Moreover, environmental uncertainty shows no moderation on restoring the managers' confidence. This study develops a theoretical framework for tourism crisis management and provides policy implications for the development of small tourism enterprises in times of crisis.