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                <text>Wen Zhu, Yongwei Zheng, Mei Yu, Jianhui Wei, Yongguang Zhang, Paytsar Topchyan, Christine Nguyen, Rae Janecke, Lisa Baumann Kreuziger, Gilbert C White, Parameswaran Hari, Richard Aster, Weiguo Cui, Shawn Jobe, Mary Beth Graham, Demin Wang, Renren Wen</text>
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                <text>Severe COVID-19 is associated with unprecedented thromboembolic complications. We found that hospitalized COVID-19 patients develop immunoglobulin Gs (IgGs) that recognize a complex consisting of platelet factor 4 and heparin similar to those developed in heparin-induced thrombocytopenia and thrombosis (HIT), however, independent of heparin exposure. These antibodies activate platelets in the presence of TLR9 stimuli, stimuli that are prominent in COVID-19. Strikingly, 4 out of 42 antibodies cloned from IgG1 + RBD-binding B cells could activate platelets. These antibodies possessed, in the heavy-chain complementarity-determining region 3, an RKH or Y 5 motif that we recently described among platelet-activating antibodies cloned from HIT patients. RKH and Y 5 motifs were prevalent among published RBD-specific antibodies, and 3 out of 6 such antibodies tested could activate platelets. Features of platelet activation by these antibodies resemble those by pathogenic HIT antibodies. B cells with an RKH or Y 5 motif were robustly expanded in COVID-19 patients. Our study demonstrates that SARS-CoV-2 infection drives the development of a subset of RBD-specific antibodies that can activate platelets and have activation properties and structural features similar to those of the pathogenic HIT antibodies.</text>
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                <text>Using a Text Mining Approach to Hear Voices of Customers from Social Media toward the Fast-Food Restaurant Industry</text>
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                <text>Wen-Kuo Chen, Dalianus Riantama, Long-Sheng Chen</text>
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                <text>Due to the COVID-19 pandemic, the sales of fast-food businesses have dropped sharply. Customer satisfaction has always been one of the key factors for the sustainable development of enterprises. However, in the fast-food restaurant business, gaining the knowledge of customer satisfaction is one of the critical tasks. Moreover, text reviews in social media have become one of important reference sources for customers’ decisions in buying services and products. Therefore, the main purpose of this study is to explore whether customer voices from social media reviews are different during the COVID-19 outbreak and to propose a new method to reduce interpersonal contact when collecting data. A text mining scheme which includes least absolute shrinkage and selection operator (LASSO) and decision trees (DT) are presented to discover the essential factors for customers to increase their satisfaction from unstructured online customer reviews. Finally, three real world review sets were employed to validate the effectiveness of the presented text mining scheme. Experimental results can help companies to properly adapt to similar epidemic situations in the future and facilitate their sustainable development.</text>
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                <text>text mining, Feature selection, customer satisfaction, online customer reviews</text>
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                <text>Biotemas</text>
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                <text>Universidade Federal de Santa Catarina</text>
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            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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                <text>Environmental effects of industries and plants, Renewable energy sources, Environmental sciences</text>
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                  <text>Dominio científico: Coronavirus</text>
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                <text>Genetic Analysis of Avian Coronavirus Infectious Bronchitis Virus in Yellow Chickens in Southern China over the Past Decade: Revealing the Changes of Genetic Diversity, Dominant Genotypes, and Selection Pressure</text>
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                <text>Wen-Sheng Fan, Ning Tang, Zhihua Dong, Jiming Chen, Wen Zhang, Changrun Zhao, Yining He, Meng Li, Cuilan Wu, Tian-Chao Wei, Teng Huang, Mei-Lan Mo, Ping Wei</text>
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                <text>The high mutation rates of infectious bronchitis virus (IBV) pose economic threats to the poultry industry. In order to track the genetic evolutionary of IBV isolates circulating in yellow chickens, we continued to conduct the genetic analyses of the structural genes S1, E, M, and N from 64 IBV isolates in southern China during 2009&amp;#8722;2017. The results showed that the dominant genotypes based on the four genes had changed when compared with those during 1985&amp;#8722;2008. Based on the S1 gene phylogenetic tree, LX4-type (GI-19) was the most dominant genotype, which was different from that during 1985&amp;#8722;2008. The second most dominant genotype was LDT3-A-type, but this genotype disappeared after 2012. New-type 1 (GVI-1) isolates showed increasing tendency and there were four aa (QKEP) located in the hypervariable region (HVR) III and one aa (S) insertion in all the New-type 1 isolates. Both the analyses of amino acid entropy and molecular evolutionary rate revealed that the variations from large to small were S1, E, M, and N. Purifying selection was detected in the S1, E, M, and N gene proteins, which was different from the positive selection during 1985&amp;#8722;2008. Six isolates were confirmed to be recombinants, possibly generated from a vaccine virus of the 4/91-type or LDT3-A-type and a circulating virus. The estimated times for the most recent common ancestors based on the S1, E, M, and N genes were the years of 1744, 1893, 1940, and 1945, respectively. Bayesian skyline analysis revealed a sharp decrease in genetic diversity of all the four structural genes after 2010 and since late 2015, the viral population rapidly rose. In conclusion, the IBVs circulating in southern China over the past decade have experienced a remarkable change in genetic diversity, dominant genotypes, and selection pressure, indicating the importance of permanent monitoring of circulating strains and the urgency for developing new vaccines to counteract the emerging LX4-type and New-type IBVs.</text>
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                <text>2019</text>
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                <text>infectious bronchitis virus, Genotype, Entropy, molecular evolutionary rate, recombination, Selection pressure</text>
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                <text>DOI: 10.3390/v11100898</text>
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                <text>Viruses</text>
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                <text>MDPI AG</text>
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                <text>Microbiology</text>
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            <description>An entity primarily responsible for making the resource</description>
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                <text>Wen-Ta Chiu, Shin-Han Tsai, Mark Olsen, Yung-Chia Pai, Lihua Lu, Chiu-Man Tsang, Hsueh-Ru Wu</text>
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                <text>2004</text>
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                <text>infection control, infectious diseases, Emerging, severe acute respiratory syndrome, communicable disease, Aviation Medicine</text>
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                <text>DOI: 10.3201/eid1007.030608</text>
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                <text>Emerging Infectious Diseases</text>
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                <text>Infectious and parasitic diseases, Medicine</text>
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                <text>Wen-Tsao Pan, Qiu-Yu Huang, Zi-Yin Yang, Fei-Yan Zhu, Yu-Ning Pang, Mei-Er Zhuang</text>
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                <text>This paper examines the determinants of tourism stock returns in China from October 25, 2018, to October 21, 2020, including the COVID-19 era. We propose four deep learning prediction models based on the Back Propagation Neural Network (BPNN): Quantum Swarm Intelligence Algorithms (QSIA), Quantum Step Fruit-Fly Optimization Algorithm (QSFOA), Quantum Particle Swarm Optimization Algorithm (QPSO) and Quantum Genetic Algorithm (QGA). Firstly, the rough dataset is used to reduce the dimension of the indices. Secondly, the number of neurons in the multilayer of BPNN is optimized by QSIA, QSFOA, QPSO, and QGA, respectively. Finally, the deep learning models are then used to establish prediction models with the best number of neurons under these three algorithms for the non-linear real stock returns. The results indicate that the QSFOA-BPNN model has the highest prediction accuracy among all models, and it is defined as the most effective feasible method. This evidence is robust to different sub-periods.</text>
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                <text>Since the outbreak of COVID-19 in China in December 2019, a pandemic has rapidly developed on a scale that has overwhelmed health services in a number of countries. COVID-19 has the potential to lead to severe hypoxia; this is usually the cause of death if it occurs. In a substantial number of patients, adequate arterial oxygenation cannot be achieved with supplementary oxygen therapy alone. To date, there has been no clear guideline endorsement of ward-based non-invasive pressure support (NIPS) for severely hypoxic patients who are deemed unlikely to benefit from invasive ventilation. We established a ward-based NIPS service for COVID-19 PCR-positive patients, with severe hypoxia, and in whom escalation to critical care for invasive ventilation was not deemed appropriate. A retrospective analysis of survival in these patients was undertaken. Twenty-eight patients were included. Ward-based NIPS for severe hypoxia was associated with a 50% survival in this cohort. This compares favourably with Intensive Care National Audit and Research Centre survival data following invasive ventilation in a less frail, less comorbid and younger population. These results suggest that ward-based NIPS should be considered as a treatment option in an integrated escalation strategy in all units managing respiratory failure secondary to COVID-19.</text>
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                <text>Korean Society of Epidemiology</text>
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                <text>Objetivo: lograr una comprensión profunda de la experiencia de inseguridad alimentaria (lA) a nivel del hogar y con base en este entendimiento, desarrollar y validar un instrumento para su medición.</text>
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                <text>Perspectivas en Nutrición Humana</text>
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                <text>Universidad de Antioquia</text>
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                <text>Child abuse review (Chichester, England : 1992)</text>
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