ABSTRACT
With the rapid development of China's economy, enterprises need to plan their logistics transportation routes reasonably in advance. This will make the transportation service more efficient. For the supplier's transportation service problem, an analysis method of critical path nodes is provided and a multi-supplier collaborative transportation strategy is designed in this article. First, a model for minimising the transportation cost was established, then a path diagram was simulated and the optimal and alternative transportation paths of suppliers based on the k-shortest path algorithm were calculated. In addition, path node availability during COVID-19 is used as a research context in this article. A multi-stage path analysis method was provided by discussing different cases of critical path nodes, which can make a reasonable selection of paths in a timely and effective manner. Finally, simulations of collaborative transportation for suppliers were performed in three scenarios and the results verified the effectiveness of the collaborative transportation strategy. The proposed collaborative transportation strategy of suppliers not only strengthened the synergistic cooperation among suppliers, but also cultivated the potential customer for suppliers in this article. Furthermore, the strategy could improve the flexibility of the supply chain, maximise the overall efficiency and also provide a new solution for the development of logistics and transportation services.
ABSTRACT
From the perspectives of IT Affordances, this paper attempts to explore the influence of the characteristics of live streaming on purchase intention, and to consider the elements required for live streaming service and customers' perceptions thereof in post-COVID-19. Through empirical research, this study establishes a framework emphasizing the major factors promoting customer immersion and the moderating effect of situational involvement that contributes to customer purchase intention in a live stream commerce context. The research model was tested using structural equation model analysis. Based on 428 valid responses, we identify that the quality of live streaming has a direct significant effect on customers' purchase intention. Specifically, relationship between platform stability, customer relationship, anchors' professional knowledge, and purchase intention is significant positive from the Affordance perspectives. The results emphasize the importance of platform stability which allows real-time communication, in-depth interaction, and real scenes for the benefits of sellers using such internet platforms. © 2022 Authors. All rights reserved.
ABSTRACT
Pandemic-tracking apps may form a future infrastructure for public health surveillance. Yet, there has been relatively little exploration of the potential societal implications of such an infrastructure. In semi-structured interviews with 23 participants from India, the Middle East and North Africa (MENA), and the United States, we discussed attitudes and preferences regarding the deployment of apps that support contact tracing to contain the spread of COVID-19. Through interpretive analysis, we examined the relationship between persistent discomfort and vulnerability when using such apps. Such an examination yielded three temporal forms of vulnerability: real, anticipatory, and speculative. By identifying and defining the temporalities of vulnerability through an analysis of people's pandemic-related thoughts and experiences, we develop the overlapping discourses of humanistic infrastructure studies and infrastructural speculation. In doing so, we explore the concept of vulnerability itself and present implications for the study of vulnerability in Human-Computer Interaction (HCI) and for the oversight of app-based public health surveillance. © 2022 Owner/Author.
ABSTRACT
The link between the supply and demand sides of manufacturing has become increasingly frail as a result of the COVID-19 outbreak. In this paper, we analyze the key path nodes and propose a closed-loop path value-added strategy for logistics services to optimize the path cost on the supply and demand side under the influence of the COVID-19 epidemic. First, the k shortest path algorithm determines the optional paths in accordance with the structure of the road network made up of all path nodes. Second, closed-loop transportation routes for both forward and reverse transit are constructed using the optional paths. Finally, the transportation service strategy with the optimal choice of transportation cost and transportation time under a multi-stage epidemic is obtained. The method can provide a reference for logistics services. © 2022 IEEE.
ABSTRACT
Because of the impact of the COVID-19 pandemic, more and more people are choosing to buy food online, including eggs. Although this mode of shopping is very modern, many Chinese consumers lack scientific knowledge when selecting eggs. In this study, we used the multivariate statistical analysis and sensory analysis to evaluate and compare the qualities of online sale of free-range and cage eggs. How feeding conditions influence the quality of eggs and how physical characteristics influence the price of eggs were also studied in this work. Our research showed that there is a lack of scientific support for distinguish free-range eggs from cage eggs on the appearance, the color of the yolk does not represent the amount of protein in yolk which may actually be affected by fodders. Moreover, the nutritional quality of free-range eggs is no better than that of cage eggs. Sensory analysis showed that free-range eggs taste better, which is likely because of the higher yolk ratio. Multivariate linear regression analysis showed that Rearing systems, fodder type and yolk color have significant impact on the price (Price = 0.428 × Rearing system −0.235 × Fodder type + 0.191 × Yolk color). © 2023, Sociedade Brasileira de Ciencia e Tecnologia de Alimentos, SBCTA. All rights reserved.
ABSTRACT
Study Objectives: In response to worldwide shortages of N95 masks during the SARS-CoV2 pandemic, the Centers for Disease Control and Prevention (CDC) has highlighted various conservation and reuse strategies including isolation and vaporized hydrogen peroxide but with limitations of "safe" reuse of N95 masks up to five times. The aim of this project was to evaluate the results of NIOSH quantitative fit testing after five trials of donning on a specific manufacturer's "duckbill" type N95 masks with/without repeated sterilization using vaporized hydrogen peroxide. Method(s): The cumulative effects of both repeated donning and doffing combined with repeated sterilization was evaluated using NIOSH Quantitative fit testing. Quantitative Fit testing generates an objective overall score across five separate tasks using an automated particle detection device to evaluate the integrity of both the mask materials and the seal on the participant. Two cohorts of duckbill type N95 masks were subjected to repeated cycles of 35% vaporized hydrogen peroxide (VHP) sterilization (five and ten cycles) and compared to one cohort of new unsterilized masks. All three cohorts were subjected to five trials of NIOSH quantitative fit testing following the protocol of donning the mask, NIOSH fit testing, then removal of the mask, with isolation for 24hrs. This cycle was repeated for five trials for each mask in each cohort. The fit testing trials were conducted on a single participant who has been fit tested and passed on this type and manufacturer's N95 mask. This repeated-measures design was chosen to remove the variability of facial size/shape for this study. Result(s): Overall, a total of 150 fit testing trials were conducted, 5 trials on 30 total masks, with 10 masks in each cohort (New vs 5x sterilized vs 10x sterilized). There were a total of 21/150 (14%) fit testing trial failures, with 13/30 (43%) individual masks failing at least one fit testing trial and 4/30 (17%) masks that failed a variable number of fit testing trials spread across all five trials per mask. Chi-square analysis showed a significant increase in the percentages of masks that failed fit testing in both mask cohorts which underwent VHP compared to unsterilized/New masks (New p=0.09, 5x p=0.03, 10x p=0.03). Conclusion(s): This data shows that this manufacturer's type and model "duckbill" N95 masks have a variable failure rate across repeated Quantitative NIOSH fit testing. There was an increased failure rate for masks that underwent sterilization. Our partner health system's mask recycling program thus discarded these type masks due to this variable failure rate. Health systems should thus consider individual testing to inform their overall policies on future mask reuse and/or recycling. No, authors do not have interests to disclose Copyright © 2022
ABSTRACT
A highly visual practice, dermatology as a field has significant potential to use emerging technology such as mobile applications for research and patient-centered mapping of the disease process. The UCSF team is working to create SkinTracker, a mobile application for patients with skin disease to remotely participate in clinical trials and research studies. The initial iteration of the application focuses on atopic dermatitis. The application includes an enrollment and consent module, validated surveys including the Patient Oriented Eczema Measure (POEM), Dermatology Life Quality Index (DLQI), Numerical Rating Scale (NRS) for itch, link to a wearable device that collects biometric data, a voice diary, and a patient-directed photography module to facilitate physician evaluation of disease. Also included is the ability to report medication use, adverse events, and the ability to chat with the study team. The patient information is available to the research team on a secure online website, where researchers can assess patient photographs to perform Eczema Area and Severity Index (EASI) scoring, note important patient observations from the voice diary, and view quantitative data from both patient surveys and health measures like physical activity, sleep, and environmental factors. We believe this application and website will facilitate patient interest and participation in research, continue research despite in-person restrictions placed during the COVID-19 pandemic, and allow enrollment of more diverse patients for clinical studies who would otherwise be less likely to participate in research due to time or financial constraints.
ABSTRACT
Since the outbreak of the COVID-19, small and medium-sized enterprises have been greatly affected. In order to cope with the difficulty of capital turnover for small and medium-sized enterprises, the government has successively introduced a series of financial policies to increase credit support and reduce financing costs. The rapid development of technology has also prompted further innovations in the operating models of banks and other credit platforms. However, banks and credit platforms must consider practical issues such as their own capital costs and risk assessment while they help small and medium-sized enterprises reduce financing costs. This paper aims to study and design a credit risk assessment system based on big data technology and machine learning algorithms. It is hoped that the system will enhance the bank's ability to identify the credit risks of small and medium-sized enterprises, so as to solve the problem of difficult and expensive financing for small and medium-sized enterprises. At the same time, it will reduce the bank's own bad loan ratio and increase profit margins. Achieving a win-win situation for small and medium-sized enterprises and banks, it's crucial to promote jointly the development of economy.
ABSTRACT
Since late December 2019, it has been reported an outbreak of atypical pneumonia, now known as COVID-19 caused by the novel coronavirus. Cases have spread to more than 200 countries and regions internationally. World Health Organization (WHO) officially declares the coronavirus outbreak a pandemic and the public health emergency has caused world-wide impact to daily lives: people are advised to keep social distance, in-person events have been moved online, and some function facilitates have been locked-down. Alternatively, the Web becomes an active venue for people to share information. With respect to the on-going topic, people continuously post questions online and seek for answers. Yet, sharing global information conveyed in different languages is challenging because the language barrier is intrinsically unfriendly to monolingual speakers. In this paper, we propose a multilingual COVID-QA model to answer people's questions in their own languages while the model is able to absorb knowledge from other languages. Another challenge is that in most cases, the information to share does not have parallel data in multiple languages. To this end, we propose a novel framework which incorporates (unsupervised) translation alignment to learn as pseudo-parallel data. Then we train multilingual question-answering mapping and generation. We demonstrate the effectiveness of our proposed approach compared against a series of competitive baselines. In this way, we make it easier to share global information across the language barriers, and hopefully we contribute to the battle against COVID-19. © 2021 ACM.
ABSTRACT
Introduction: COVID-19, a disease caused by coronavirus SARS-CoV-2, has drawn public attention worldwide. The virus is also associated with carcinogenesis. Epstein-Barr virus (EBV) was reported to be related to pulmonary lymphoepithelioma-like carcinoma (PLELC), a rare subtype of non-small cell lung cancer (NSCLC). However, the understanding of the treatment for EBV-infected NSCLC was still elusive. Immunotherapy that targets PD-1/PD-L1 has been utilized as a novel clinical treatment in recent years. Here, we focus on the genomic landscapes of lung cancers with EBV-infection and its correlation with PD-L1. Methods: Patients with both PD-L1 expression detection and genomic information were screened in HapLab database. HaploX 605-gene panel sequencing, covering 1.31 MB genome, was performed to analyze the genomic data of patients. PD-L1 expression was detected by immunochemistry. Bioinformatic analysis of genomic mutations and the correlation with the expression of PD-L1 were studied. Results: We analyzed the genomic profiles of 23 EBV-infected NSCLC patients. 11 cases of lung squamous-cell carcinoma (LUSC), 4 cases of lung adenocarcinoma (LUAD), 5 cases of lung pulmonary lymphoepithelioma-like carcinoma (PLELC), and 3 unidentified cases were included in this study. Collectively, 93 genome mutations of 67 genes were detected in 23 EBV-infection cases. Top 3 frequently mutated genes were TP53 (27%), CSMD3 (18%) and KMT2D (18%). The EBV-infected patients exhibited a low level of tumor mutation burden (TMB). The median TMB was 1.53 Muts/MB (ranging from 0 to 14.5 Muts/MB). Only 3 of 23 patients (13.0%) harbored the canonical driver mutations in NSCLC. Interestingly, 10/23 patients (43.5%) showed high expression of PD-L1, while 13/23 patients (56.5%) showed low expression. We also assessed the expression of PD-L1 in lung cancers with no EBV-infection (867 cases). Only 118/867 (13.6%) patients without EBV-infection presented high PD-L1 expression, while 749/867 (86.4%) presented low PD-L1 expression. Conclusion: EBV-infection can occur in different kinds of NSCLC, including LUSC, LUAD, and PLELC. TMB and driver mutations of EBV-infected NSCLC were not frequently observed as normal lung cancers, implying a different mechanism leading to EBV-infected lung cancers. Interestingly, EBV-infected NSCLC tended to have a high correlation with the expression of PD-L1. This may give a hint on the application of checkpoint blockade immunotherapy on EBV-infected NSCLC. [Formula presented] Keywords: Epstein-Barr virus (EBV), PD-L1 expression, non-small cell lung cancer (NSCLC)
ABSTRACT
Purpose: The authors examine the Taiwanese government's budgetary responses to COVID-19, with a focus on the special budgets created for containing the virus, undertaking bailouts and providing economic stimulus. The authors assess the short-term and long-term fiscal implications of the budgetary measures and discuss how Taiwan's experiences could provide lessons for other countries for future emergencies. Design/methodology/approach: The authors collect data from Taiwan's official documents and news reports and compare the special budgets proposed by the Taiwanese government during the Great Recession and the COVID-19 pandemic. The authors discuss lessons learned from the 2008–09 special budget and possible concerns of the 2020 special budgets. In the conclusions, the authors discuss potential long-term implications for Taiwan's budgetary system as well as possible lessons for other countries based on Taiwan's experiences Findings: The authors found that the 2008–09 special budgets focused only on economic stimulus, whereas the 2020 special budgets covered COVID-19 treatments, bailouts and economic stimulus. In 2020, the Taiwanese government devised targeted bailout plans for industries and individuals most affected by the pandemic and created the Triple Stimulus Vouchers to boost the economy. Since the special budgets were largely funded through borrowing, the authors pointed out concerns for fiscal sustainability and intergenerational equity. Originality/value: COVID-19 has changed how the world functions massively. This work adds to the literature on COVID-19 by providing Taiwan's budgetary responses to the pandemic. This work also identifies ways for Taiwan to improve the existing budgetary system and discusses lessons for other countries. © 2020, Emerald Publishing Limited.
ABSTRACT
At present, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread all over the world, and the best way to effectively carry out drug diagnosis and treatment presents difficulties for all medical staff. In China, some traditional Chinese medicines (TCMs) have been successfully applied to the treatment of SARS-CoV-2 and have achieved good clinical results, including the Reyanning mixture. In this study, we systematically analyzed the mechanism of the Reyanning mixture and its effects against SARS-CoV-2 based on the method of network pharmacology. Here, we used the TCM Systems Pharmacology database and employed a similarity algorithm to screen and identify the bioactive ingredients and potential targets of the Reyanning mixture. The GeneCards database was used to predict and screen the disease targets and build the active ingredient target network diagram. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to construct the target signal pathway associations. The STRING tool was used to reconstruct the protein-protein interaction network. As a result, 27 candidate targets, such as tumor necrosis factor, interferon gamma, tumor protein P53, C-reactive protein, and peroxisome proliferator-activated receptor gamma, were identified among the 33 bioactive ingredients of the 4 TCMs in the Reyanning mixture with effects on treating SARS-CoV-2. These targets were significantly enriched in 20 KEGG pathways and associated with 48 diverse GO terms. All of these targets may play a role in inhibiting inflammatory reactions, regulating immune function, and reducing lung injury to achieve the purpose of treating SARS-CoV-2.
ABSTRACT
BACKGROUND: Multicentre cohort investigations of patients with coronavirus disease 2019 (COVID-19) have been limited. We investigated the clinical and chest computed tomography characteristics of patients with COVID-19 at the peak of the epidemic from multiple centres in China. METHODS: We retrospectively analysed the epidemiologic, clinical, laboratory, and radiological characteristics of 189 patients with confirmed COVID-19 who were admitted to seven hospitals in four Chinese provinces from 18 January 2020 to 3 February 2020. RESULTS: The mean patient age was 44 years and 52.9% were men; 186/189 had ≥1 co-existing medical condition. Fever, cough, fatigue, myalgia, diarrhoea, and headache were common symptoms at onset; hypertension was the most common co-morbidity. Common clinical signs included dyspnoea, hypoxia, leukopenia, lymphocytopenia, and neutropenia; most lesions exhibited subpleural distribution. The most common radiological manifestation was mixed ground-glass opacity with consolidation (mGGO-C); most patients had grid-like shadows and some showed paving stones. Patients with hypertension, dyspnoea, or hypoxia exhibited more severe lobe involvement and diffusely distributed lesions. Patients in severely affected areas exhibited higher body temperature; more fatigue and dyspnoea; and more manifestations of multiple lesions, lobe involvement, and mGGO-C. During the Wuhan lockdown period, cough, nausea, and dyspnoea were alleviated in patients with newly confirmed COVID-19; lobe involvement was also improved. CONCLUSIONS: Among patients with COVID-19 hospitalised at the peak of the epidemic in China, fever, cough, and dyspnoea were the main symptoms at initial diagnosis, accompanied by lymphocytopenia and hypoxaemia. Patients with severe disease showed more severe lobe involvement and diffuse pulmonary lesion distribution.
Subject(s)
COVID-19/diagnostic imaging , Pneumonia, Viral/diagnostic imaging , Radiography, Thoracic , Tomography, X-Ray Computed , Adult , COVID-19/epidemiology , China/epidemiology , Comorbidity , Female , Hospitalization , Humans , Male , Pneumonia, Viral/epidemiology , Pneumonia, Viral/virology , Retrospective Studies , SARS-CoV-2 , Severity of Illness IndexABSTRACT
Objective: To construct and evaluate a diagnosis pathway (Xiangya pathway) for Corona Virus Disease 2019 (COVID-19). Methods: Consecutive subjects aged ≥12 years old who were screened for COVID-19 were included in Xiangya Hospital of Central South University from January 23 to February 3, 2020, and the subjects were further divided into the inception cohort and the validation cohort. The gender, age, onset time of disease of the subjects were recorded. The information of epidemiological history, fever, and the declined blood lymphocytes were collected as clinical indicators, CT scan was used to evaluate the possibility of COVID-19 and range of lung involvement. According to the current Chinese national standards, throat swabs of suspected cases were collected and the nucleic acid of COVID-19 was detected by reverse transcription-polymerase chain reaction (RT-PCR). The Xiangya pathway was constructed with multi-indexes, compared with clinical indicators, CT results and Chinese national standards, their effectiveness of detecting confirmed cases were verified in the inception and validation cohort. Results: A total of 382 consecutive adults who was screened for COVID-19 were included, and 261 cases were in the inception cohort and 121 cases were in the validation cohort. Among the 382 cases, 192 were males (50.3%) and 190 were females (49.7%), with a median age of 35 years (range: 15-92 years). There were 183 cases (47.9%) with epidemiological history, 275 cases (72.0%) with fever, 212 cases (55.5%) with decreased peripheral blood lymphocytes, 114 cases (29.8%) with positive CT findings, 43 cases (11.3%) with positive CT-COVID-19, and 30 cases (7.9%) with positive virus nucleic acid by throat swab. Compared with clinical indicators, the sensitivity and specificity of CT were 0.950 and 0.704, respectively. The accuracy of CT to make a definite diagnosis was higher than that of epidemiological history, fever, and declined blood lymphocyte count (0.809 vs 0.660, 0.532, 0.596, P=0.001, 0.002, 0.003, respectively). The sensitivity of this pathway and the pathway recommended by the Health Commission of China were both high (all were 1.000), while the specificity and accuracy of the Xiangya pathway were higher than the one recommended by the Health Commission (0.872 vs 0.765, 0.778 vs 0.592, both P<0.001). The CT-COVID-19 reduced the missed diagnosis rate caused by false negative of nucleic acid test (31 vs 64), with difference rate of 51.6%, and the positive rate of nucleic acid test was 64.5% (20/31). In validation cohort, the specificity and accuracy of the Xiangya pathway was 0.967, the positive rate of nucleic acid test was 76.9%(10/13). Conclusions: The Xiangya pathway can predict the nucleic acid test results of COVID-19, and can be applied as a reliable strategy to screen patients with suspected COVID-19 among people aged ≥12 years in areas other than Hubei during the epidemic period of COVID-19. The cohort size needs to be increased for further validation.