ABSTRACT
In this COVID-19 epidemic, due to insufficient awareness of the impact of sudden public health emergencies on agricultural logistics at this stage, agricultural products were left unsold, stocks were backlogged, and losses were severe. In the process of distribution, we should not only ensure a short time cycle and avoid the contamination of agricultural products by foreign bacteria, but also pay attention to the waste of human, material, and financial resources. Therefore, this study mainly adopts the combination of the petrochemical network and block chain to build an agricultural products emergency logistics model. This paper first shows the operation mechanism of the petri dish network and blockchain coupling in the form of a graph and then uses the culture network modelling and simulation tool PIPE to directly verify the construction model. It is proved that the structure and overall business process of the agricultural products logistics system constructed by combining the Petri net and block chain are reasonable, reliable, and feasible in practical application and development. It is hoped that this study can provide a reference direction for agricultural emergency logistics.
ABSTRACT
The Coronavirus Disease 2019 (COVID-19) has shown us the necessity to understand its transmission mechanisms in detail in order to establish practice in controlling such infectious diseases. An important instrument in doing so are mathematical models. However, they do not account for the spatiotemporal heterogeneity introduced by the movement and interaction of individuals with their surroundings. Computational fluid dynamics (CFD) simulations can be used to analyze transmission on micro- and mesostructure level, however become infeasible in larger scale scenarios. Agent-based modeling (ABM) on the other hand is missing means to simulate airborne virus transmission on a micro- and mesostructure level. Therefore, we present a system that combines CFD simulations with the dynamics given by trajectories from an ABM to form a basis for producing deeper insights. The proposed system is still work in progress;thus we focus on the system architecture and show preliminary results.
ABSTRACT
The covid-19 has severely hindered the development of tourism, so it is necessary to study the tourism under the pandemic situation. Travel websites provide a lot of data and topic model is a commonly used model to mining online review. However, the traditional topic model will lead to serious sparsity problem when dealing with short text due to lack of word frequency and context information and will be interfered by bridge words. Therefore, we proposed BW-BTM which is effective and superior to the traditional model to learn higher quality topics from short text with the large number of bridge words. Finally, we found out five aspects that tourists paid more attention to during the epidemic period through detecting topic, they are entry and exit, ticket refund service, epidemic prevention in scenic spots, hotel epidemic prevention requirements and public transportation epidemic prevention.
ABSTRACT
Introduction Severe acute respiratory syndrome coronavirus-2 (SARS-CoV2) can induce a strong host immune response. Several groups have investigated the course of antibody responses in patients recovering from SARS-CoV-2 infections but little is known about the recovery of cellular immunity. This study investigated the cellular immune response in people who had recovered from SARS-CoV2 infection. Methods 162 coronavirus disease 2019 (COVID-19) convalescent plasma donors (CCD) and 40 healthy donor (HD) controls were enrolled prospectively in an IRB-approved protocol (Clinical Trials Number: NCT04360278) and provided written informed consent to participate in the study. Using the nCounter platform and host response panel with 785 genes across more than 50 pathways, we compared transcriptomic profiles on RNA samples obtained from the peripheral blood leukocytes of these 162 CCD and 40 HD. Additionally, in 69 of the 162 CCD samples, we evaluated transcriptomic trends at more than one-time point during the convalescent period. Results Age, sex, ethnicity, and body mass index distributions were similar among the CCD and HD. With respect to baseline complete blood counts, hemoglobin, platelets, and absolute basophil and eosinophil counts, all were similar among CCD and HD (Table 1). However, despite sample collections occurring several days after convalescence, mean counts for absolute neutrophil counts, absolute monocyte counts, and absolute lymphocyte counts were significantly higher among CCD compared to HD. 30-90 days after diagnosis, 19 of 773 genes differed (FDR < 0.05) between the average CCD and HD samples. Up-regulated genes included MAFB, CTLA4, PTGS2, and the chemokine signaling genes CXCR4, CXCL5, CXCL2 and CCR4. Down-regulated genes included PTGER2, CASP8, and the interleukins IL36A, IL31, IL20 and IL21 (Figure 1 a,b). Differential gene expression persisted for months. At 90-120 days, 13 genes were differentially regulated, including again MAFB CXCR4, PTGS2, CXCL2 and PTGER2, plus SMAD4. At 120-150 days post-diagnosis, 58 genes were differentially expressed (FDR < 0.05) compared to HD. Pathways with up-regulated genes included Treg differentiation, type III interferon signaling and chemokine signaling. 150-360 days post-diagnosis, 4 genes remained up-regulated on average (FDR < 0.05): PTGS2, PIK3CR, CXCL1 and SMAD4 (Figure 1 c,d). Individual patients varied considerably from the mean trend. Scoring samples by their similarity to the gene expression profile of the mean HD sample, 21 CCD samples from 20 unique patients (12%) were identified as highly perturbed from HD. 84% of these highly perturbed samples were collected > 90 days post-diagnosis. Of these 21 samples, 6 were distinguished by > 2-fold up-regulation of a cluster of interleukin and type-1 interferon genes (Figure 2). Conclusions Overall, our study identified important gene expression trends in CCD compared to HD in the post-acute period. The changes varied with time and among donors. As the expression of T-cell inhibitory molecule CTLA4 fell, the number of differentially expressed increased with the most marked changes occurring 120 to 150 days post-diagnosis in genes in chemokine signaling, type III interferon signaling and Treg pathways. Persistent alterations in inflammatory pathways and T-cell activation/exhaustion markers for months after active infection may help shed light on the pathophysiology of a prolonged post-viral syndrome observed in individuals following recovery from COVID-19 infection. Our data may serve as the basis for risk modification strategies in the period of active infection. Future studies may inform the ability to identify druggable targets involving these pathways to mitigate the long-term effects of COVID-19 infection. [Formula presented] Disclosures: Danaher: NanoString Technologies: Current Employment, Current holder of individual stocks in a privately-held company.
ABSTRACT
The catering industry is one of the industries most seriously affected by Covid-19, it is significant for us to understand the customers' concerns and find the epidemic prevention loopholes in the catering industry by analyzing the pandemic related topics through online reviews. However, topic detection of short texts such as online reviews has always been a difficult problem in this field. In addition, the interference of background topics related to diet makes this study more difficult. This paper proposes a topic detection method based on topic model and feature embedding. The proposed method called ER-BTM solves the long tail problem of online text by embedding and topic estimation uses feature-pairs instead of features to optimize the process of parameter estimation. The experimental results show that the proposed method can effectively identify epidemic related topics on word-of-mouth platforms such as Yelp. Its performance is also better than control methods on public datasets, it is a powerful tool in online topic detection and epidemic prevention. © 2021 IEEE.
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The covid-19 has strongly hit the tourism industry, leading to downturn in tourism stock market. The bearish events in tourism industry can evoke public panic about future stock market. Tourism companies struggled to maintain their business and positively coped with the emergencies. Meanwhile, the influence of covid-19 was gradually weakened. As situation improved, some investors started to be optimistic about tourism stock prices in the long term. From the phenomenon, we reckon the investor sentiment can influence stock prices. Besides, news about finance and tourism can represent the industry situations and influence the stock prices. In our work, we used investor sentiment and news sentiment polarity combining history stock transaction data to build features in stock price prediction. Multinomial Naive Bayes was used to train and obtain amounts of investor comments sentiment. Lexicon based approach was used to obtain news sentiment polarity. We used XGBoost model to do stock price prediction based on the features we built. The results showed it's an effective way to use sentiment do tourism stock price since the sentiment attributes increased prediction precision. And we also found that XGBoost combined sentiment feature performed better than other algorithm such as SVM and ANN in prediction. © 2021 IEEE.
ABSTRACT
As a testimony to the lockdown life in Wuhan caused by the COVID-19 pandemic, Fang Fang’s Wuhan Diary received worldwide attention while triggering extensive controversies in China. Drawing on the concepts of agent and voice in translation studies, this article explores the contextual, paratextual and textual voices of translation agents in the English translation of Wuhan Diary (2020) and their power negotiations, to reveal who has the final say in positioning and rendering the text for an Anglophone readership. In so doing, the article shows that the author rather than the publisher plays a decisive role in producing the paratextual materials for the translation, and that the translator tend to employ the translation technique of omission to protect the author and himself. Furthermore, it finds that the author’s request for the revision of such paratexts as the title and blurb, in conjunction with the translator’s technique of omission in the translated text, boil down to responses to the critical voices from Chinese readers. Therefore, this article argues that the critical voices from Chinese readers have had the final say in the production and presentation of the English translation of Wuhan Diary. © 2021 Informa UK Limited, trading as Taylor & Francis Group.