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Purpose: The purpose of this paper is exploring the effects of segment dynamic and temporal dynamic triggered by the COVID-19 pandemic on classifying service quality attributes, thereby formulating improvement strategies to satisfy customers and respond to threats. Design/methodology/approach: Given the dynamics of the attractive quality theory, this paper designs a framework with four phases by embedding techniques of text mining and deep learning based on evidence from online reviews. Findings: This paper figures out dynamics of service quality attributes for distinct segments and their dynamic proportion along with different stages of the pandemic. Another finding demonstrates segment dynamic and temporal dynamic effects of sentiments toward service quality attributes on customer satisfaction under the impacts of pandemic. Classification results and improvement strategies are derived for varying segments at different pandemic situations. Practical implications: This paper reveals dynamic effects on classifying service quality attributes, which contributes to assisting hospitality practitioners from different segments in improving service quality when facing with the challenges of crisis and potential risks. Originality/value: Given hospitality industry is time- and segment-sensitive, the authors achieve the quantification of dynamics of attractive quality theory and extend it into hospitality marketing and crisis management from the perspective of dynamics with evidence from online reviews. © 2022, Emerald Publishing Limited.
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A series of lockdown measures in response to the Corona Virus Disease 2019 (COVID-19) outbreak resulted in a drop in anthropogenic emissions and changes in concentrations of PM2.5 and O-3. Backward trajectories analysis, cluster analysis, potential source contribution function (PSCF) and concentration weighted trajectory (CWT) technologies were conducted to reveal the characteristics and potential source areas of pollutants in Beijing before the COVID-19 outbreak (BCO period), during the outbreak (COB period) and after the outbreak (ACO period), as well as the contemporaneous period in 2019 (CCO period), which is critical for exploring the efficient control measures and making policy. The results indicated that despite the significant reduction in anthropogenic emissions during the epidemic, the PM2.5 concentrations increased by 1.0% caused by unfavorable meteorological conditions. O-3 concentrations increased by 174.8% compared to that during the BCO period due to the increased temperature and inappropriate precursor reduction ratios. A considerable decrease of NO3- in PM2.5 was observed under the influence of significant reductions in vehicle emissions during the lockdown. The cluster analysis revealed that short-range transport played a significant role in the accumulation of local PM2.5 pollution, while long-range northwest airflows contributed more to O-3 accumulation, and weakened as the season changed. The PSCF and CWT analysis demonstrated that potential source areas of PM2.5 were mostly located in the central and southern Hebei, the southwestern Shandong in the CCO period, and expanded to central Inner Mongolia and northern Shanxi in the COB period. These areas were highly compatible with the high emission areas of the emission inventory statistics. After the outbreak, the source areas of O-3 were centered in the Beijing-Tianjin-Hebei region and Shandong province, with a radial dispersion in all directions, while they were distributed in the central Mongolia and Inner Mongolia during the other periods.
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Purpose The purpose of this paper is exploring the effects of segment dynamic and temporal dynamic triggered by the COVID-19 pandemic on classifying service quality attributes, thereby formulating improvement strategies to satisfy customers and respond to threats. Design/methodology/approach Given the dynamics of the attractive quality theory, this paper designs a framework with four phases by embedding techniques of text mining and deep learning based on evidence from online reviews. Findings This paper figures out dynamics of service quality attributes for distinct segments and their dynamic proportion along with different stages of the pandemic. Another finding demonstrates segment dynamic and temporal dynamic effects of sentiments toward service quality attributes on customer satisfaction under the impacts of pandemic. Classification results and improvement strategies are derived for varying segments at different pandemic situations. Practical implications This paper reveals dynamic effects on classifying service quality attributes, which contributes to assisting hospitality practitioners from different segments in improving service quality when facing with the challenges of crisis and potential risks. Originality/value Given hospitality industry is time- and segment-sensitive, the authors achieve the quantification of dynamics of attractive quality theory and extend it into hospitality marketing and crisis management from the perspective of dynamics with evidence from online reviews.
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Introduction: COVID-19, the infectious disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), often presents with a spectrum of symptoms at varying levels of severity, ranging from asymptomatic patients to those with fatal complications, such as myocarditis. With increased availability of COVID-19 vaccines, the awareness of possible side effects has expanded as reports surface. This study reviewed cases of myocarditis following COVID-19 vaccination and with existing literature on COVID-19 infection-induced myocarditis to compare clinical courses and analyze possible mechanisms of action. Methods: A systematic review of literature was conducted to identify published case reports (as of February 3, 2022) pertaining to the development of myocarditis following COVID-19 vaccination with either Pfizer or Moderna for an in-depth analysis. Additional subgroup analyses were conducted based on age, past medical history, vaccine manufacturer, and dose number. Results: There were 53 eligible case reports that were included in this study. Patients were mostly male with a median age of 24 years, and the most reported symptom upon presentation was chest pain. Seventy percent of the cases involved the Pfizer vaccine with a majority of myocarditis developing subsequent to second dose. Resolution of symptoms was achieved in all but one patient. Clinical severity, as measured primarily by left ventricular ejection fraction, appeared to be worse among adult patients than pediatric, as well as for patients with comorbidities. Conclusion: This study revealed an observable association between COVID-19 vaccines and myocarditis. However, the clinical course and prognosis seem favorable and less prevalent than those conferred from natural infection.
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Deep learning methods have achieved great performances in face recognition. However, the performances of deep learning methods deteriorate in case of wearing a mask. Recently, due to the world-wide COVID-19 pandemic, masked face recognition attracts more attention. It is non-trivial and urgent to improve the performances in masked face recognition. In this work, a simple and effective data augmentation method, named MaskOut, is proposed. MaskOut replaces a random region below the nose of a face with a random mask template to mask out original face features. Our method is computing and memory efficient and convenient to combine with other methods. The experimental results show that the performances in masked face recognition are improved by a large margin with MaskOut. Besides, we construct a real-life masked face dataset, named MCPRL-Mask, to evaluate the performance of masked face recognition models.
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Recent pandemic outbreak of the corona-virus disease 2019 (COVID-19) has raised widespread concerns about the importance of the bioaerosols. Bioaerosols are an important part of atmospheric aerosols. Due to its physico-chemical properties and inherent biological characteristics, bioaerosols play a key role in global ecosystem, climate change, air quality and public health. A large number of studies have been focused on the sampling and detection techniques of bioaerosols, disinfection protection, effects on health and environment. However, little is known about the source characteristics of bioaerosols. Therefore, the research status of airborne microbes source was focused, and the progress on the emission characteristics of natural and anthropogenic source of bioaerosols in the past 20 years was comprehensively summarized. Combined with our study, the main factors affecting the source emission and transport process were also highlighted, such as biogeographic regions, land-use types, and environmental factors. Subsequently, the various source analysis methods of current bioaerosols were discussed. Finally, the future work prospects of bioaerosols source characteristics were prospected. It is expected to provide reference for in-depth understanding of the source and transmission change mechanism of bioaerosols, and to better evaluate the level of atmospheric microbial pollution and monitor the aerosol transmission of pathogens. © 2021, Editorial Department of Journal of Earth Sciences and Environment. All right reserved.
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Purpose/Objective(s): The delivery of safe and effective radiation therapy relies on accurate target delineation, particularly in the era of highly conformal treatment techniques. Contouring resources can improve accuracy but are fragmented and underused. We report the 5-year development and usage outcomes of a free, online, easily accessible web-based interactive contouring atlas. Materials/Methods: eContour (https://econtour.org) was developed using modern web technologies, including HTML5, Python, and an interpreted computer programming language, to interactively display images and contours from real patient cases. The viewer has standard tools for image manipulation, contour display, image overlays, and radiation dose distribution. Information from evidence-based guidelines and clinical pearls are summarized and presented next to each case. Mixpanel software was used to collect web usage statistics, including user demographics, geography, and case views. Results: In the first 5 years of operation (February 1, 2016 to February 1, 2021), a total of 22,889 users registered on eContour. Users represented a total of 146 countries, with the largest cohort from the United States (7,096, 31%). Other countries with > 700 registered users included Spain, India, Brazil, China, and Russia. The majority of registered users (58%) reported their profession as physicians, including 10,869 practicing radiation oncologists (47%) and 2,583 resident physicians (11%). There are 3,107 users who identified as physicians and were geographically within the US. The remaining users identified as radiation therapists (10%), dosimetrists (10%), medical physicists (8.7%), and medical students (6.6%). As of February 2021, a total of 65 cases have been developed covering 9 disease sites. The most commonly viewed disease site was head and neck (23% of all case views), followed by gynecological, gastrointestinal, and breast cancer. The most commonly viewed cases include pre-operative rectal cancer, head and neck organs-at-risk, and intact prostate cancer. Over 5 years, usage of eContour has increased both in terms of total users and case views. Total users have grown > 600% since 2017;3,613 (2017), to 12,248 (2019), to 22,889 cumulative total users (2021). In the fourth quarter of 2020, eContour averaged 1,018 case views per weekday. Since the onset of the COVID pandemic, usage of eContour has accelerated. Annual case views increased 56% year-over-year from 2019 to 2020 (147,846 to 230,304 views) as compared to essentially stable from 2018 to 2019 (144,769 to 147,846). Conclusion: With approximately 5,000 radiation oncologists in the US, we estimate 60% of US radiation oncologists are registered users. Growth in users and web site traffic over the first 5 years of eContour show its strong potential to increase the use of evidence-based contouring information at the point of care.
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Objective: To describe the COVID-19 epidemic and its characteristics in Heilongjiang province, and provide evidence for the further prevention and control of COVID-19 in the province. Methods: The information of COVID-19 cases and clusters were collected from national notifiable disease report system and management information system for reporting public health emergencies of China CDC. The Software's of Excel 2010 and SPSS 23.0 were applied for data cleaning and statistical analysis on the population, time and area distributions of COVID-19 cases. Results: On January 22, 2020, the first confirmed case of COVID-19 was reported in Heilongjiang. By March 11, 2020, a total of 482 cases domestic case of COVID-19, The incidence rate was 1.28/100 000, the mortality rate was 2.70% (13/482) in 13 municipalities in Heilongjiang. There were 81 clusters of COVID-19, The number of confirmed cases accounted for 79.25% (382/482) of the total confirmed cases and 12 cases of deaths. The family clusters accounted for 86.42% (70/81). Compared with the sporadic cases, the mortality rate, proportion of elderly cases aged 60 or above and severe or critical cases of clinical classification were all higher in the clusters especially the family clusters, but the differences were not significant (P>0.05). There were 34 clusters involving more than 5 confirmed cases accounted for 41.98% (34/81) of the total clusters, the involved cases accounted for 68.31% (261/382) of the total cases of clusters. There were significant differences in age distribution of the cases among the case clusters with different case numbers. In the clusters involving 6-9 cases, the proportion of cases aged 65 years or above was more (26.53%, 39/147). Conclusions: The incidence rate of COVID-19 was relatively high and the early epidemic was serious in Heilongjiang, The number of cases was large in clusters especially family clusters.
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COVID-19/epidemiology , Epidemics , Aged , COVID-19/mortality , China/epidemiology , Cities , Family Health , Humans , Incidence , Middle AgedABSTRACT
This paper summarizes the infection control practice in coronavirus disease 2019 (COVID-19) wards of Wuhan Huoshenshan Hospital. By closely focusing on the three key elements of infectious diseases and strictly following the general prevention principles, we implement systematic management, including ward design, personnel management, disinfection measures, protection management, diagnosis and treatment path, clinical specimens, redisinfection of medical equipment and clearance of garbage. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid was detected in samples from critical patients and their surrounding environments, so as to indentify the possible contamination path to guide the prevention and control. During the mission, the systematic and meticulous infection control management in the wards effectively controlled cross infections, ensured the effective and safe treatment of COVID-19 patients, with no medical staff infections occurred, providing references for infection control of wards in similar epidemics in the future.
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Objective: To collect the clinical symptoms of novel coronavirus pneumonia, explore and analyze the clauses and prescriptions related to the clinical symptoms of 2019 novel coronavirus pneumonia in “Treatise on differentiation and treatment of epidemic febrile disease”, in order to provide a reference for clinical treatments of the disease. Methods: Searching literature from the databases CNKI and PubMed by entering “novel coronavirus” (in Chinese) and “2019 Novel Coronavirus” as key words, classifying typical symptoms depending on their reported frequencies of occurrence, comparing with related pathogenesis in “Treatise on differentiation and treatment of epidemic febrile disease”, and analyzing clauses and prescriptions combined with the sixth version of “New coronavirus pneumonia diagnosis and treatment scheme”. Results: We optimized 20 literatures published in Chinese or English for the review, in which, a total of 647 clinical cases were reported. Based on that, 28 typical symptoms were summarized, including respiratory symptoms, such as fever and cough;Gastrointestinal symptoms, such as poor appetite, nausea, vomiting, diarrhea;Other symptoms, such as myalgia, fatigue, and so forth. Among them, fever (558 cases), cough (395 cases), and fatigue (257 cases) were the top three clinical symptoms. By analysis, we optimized 15 clauses, 18 prescriptions, and 46 traditional Chinese medicines from “Treatise on differentiation and treatment of epidemic febrile disease”, including two clauses in the upper energizer, nine in the middle energizer, and four in the lower energizer;A total of seven prescriptions for treating dampness-heat, five for cold-dampness, and six for warm-heat diseases;as well as Chinese medicines Pinellia ternata (mentioned for six times), Cinnamomi Ramulus (five times), Tetrapanacis Medulla (five times), Poria cocos (four times), Talcum (four times), Coptis chinensis (four times) and Coicis Semen (four times), etc. P. ternata, Cinnamomi Ramulus, C. chinensis, Scutellaria baicalensis, and Zingiberis Rhizoma were selected to treat dampness-heat diseases, in order to “pungency opening and bitter discharging”;P. cocos, Tetrapanacis Medulla, Talcum, and Coicis Semen were selected for “eliminating dampness with bland medicinal”;Almond, Amomum kravanh, and Magnolia officinalis were used to “regulating qi movement”;Anemarrhenae Rhizoma, Gypsum Fibrosum, and Forsythiae Fructus were used to treat warm-hot diseases for “purging fire and removing toxin”. The formula of Sanren Decoction, Yiyizhuye Powder can be used for people in the stage of medical observation period;Sanren Decoction, Yiyizhuye Powder, Xingrenyiyi Decoction, Wuling Powder, Baihujiaguizhi Decoction, and Lingjiangzhugui Decoction for treating mild cases;Huangqin Huashi Tang, Xingren Huashi Decoction, and Fulingpi Decoction for severe cases;Jiaomei Decoction, Jianweiwumei Pill, Sini Decoction, and Taohua Porridge for critical patients, and Maidong Maren Decoction, Wuzhi Yin, and Niuru Yin for convalescents. Conclusion: The prescriptions of “Treatise on differentiation and treatment of epidemic febrile disease” can provide reference for the clinical treatments of 2019 novel coronavirus pneumonia.