Research on Distribution Capacity of Fresh Food E-commerce Company Based on Fuzzy Synthetic Evaluation

With the introduction of the new retail model and the explosion of COVID-19, more and more community residents are using fresh food e-commerce companies to buy the fresh produce they need on a daily basis. In this paper, three fresh produce e-commerce companies with a high market share were selected as research subjects and their company financial reports were used as raw data, and then the intra-city distribution capability of fresh food e-commerce companies was studied based on the raw data. Firstly, the weights of the primary and secondary indicators were calculated using the hierarchical analysis and entropy methods respectively, and the weights were fused. After that, a fuzzy synthetic evaluation of each of the three fresh food e-commerce companies was conducted, which in turn quantified the evaluation results. Finally, the quantified evaluation results are compared and appropriate recommendations are given for each fresh food e-commerce company. © 2022 IEEE.

Resilience of urban public health system in cases of epidemic crisis

To effectively cope with urban public health crisis, the resilience of public health system is critical. With the successful prevention experience of COVID-19 epidemic in Wuhan as an example, grounded theoretical method was used to analyze concepts and behaviors of the government, communities, hospitals, media and Non-Governmental Organizations in the prevention and control of the epidemic. 10 main categories and 52 corresponding sub-categories, which reflected system resilience, were identified, including disease surveillance system, epidemic prevention resource management, and collaborative governance capabilities. It is found that public health system resilience can be divided into functional resilience, process resilience and integral resilience. A hierarchical structure model can be constructed to improve its resilience by means of interpretation structure modeling (ISM). And by integrating factors of multiple social subjects, including social epidemic prevention foundation, epidemic prevention technology and culture, and comprehensive governance of epidemic risks for gradual emergency preparedness, the resilience of the urban public health system can be upgraded. © 2022, Editorial Department of China Safety Science Journal. All rights reserved.

CSDLEEG: Identifying Confused Students Based on EEG Using Multi-View Deep Learning

Distance learning has dramatically increased in recent years because of advanced technology. In addition, numerous universities had to offer courses in online mode in 2020 and 2021 because of the COVID-19 pandemic. However, there are more challenges in distance learning than in the traditional learning method (e.g., feedback and interaction). Recently, researchers started using simple EEG headsets to identify confused students during online courses based on machine learning approaches. However, they faced unpleasant accuracy using traditional machine learning algorithms or nondeep neural networks. In this paper, we present a data-driven approach based on a multi-view deep learning technique called CSDLEEG to identify confused students. We employ the students' demographic information and EEG signals to feed our novel neural networks. The results show that our proposed approach is superior to state-of-the-art methods for 98% accuracy and 98% F1-score. © 2022 IEEE.

Exploring the Role of Shared Mobility in Alleviating Private Car Dependence and On-Road Carbon Emissions in the Context of COVID-19

Shared mobility is becoming increasingly popular worldwide, and travelers show more complex choice preferences during the post-pandemic era. This study explored the role of shared mobility in the context of coronavirus disease (COVID-19) by comparing the travel mode choice behavior with and without shared mobility. Considering the shared mobility services of ride-hailing, ride-sharing, car-sharing, and bike-sharing, the stated preference survey was designed, and the mixed logit model with panel data was applied. The results show that if shared mobility is absent, approximately 50% of motorized mobility users and 84.62% of bike-sharing adopters will switch to using private car and public transport, respectively. The perceived pandemic severity positively affects the usage of car-sharing and bike-sharing, while it negatively affects the ride-sharing usage. Under different pandemic severity levels, the average probabilities of private car choice with and without shared mobility are 38.70 and 57.77%, respectively;thus, shared mobility would alleviate the dependence on private car in post-pandemic future. It also helps to decrease the on-road carbon emissions when the pandemic severity is lower than 53. These findings suggest policymakers to maintain the shared mobility ridership and simultaneously contain the pandemic. Additionally, pricing discount and safety enhancement are more effective than reducing detour time to protect ride-sharing against COVID-19. Copyright © 2022 Zhang, Shao, Wang, Huang, Mi and Zhuang.

Spatiotemporal Distribution and Ecological Risk Assessment of Plastic Additives in Taihu Lake

To reveal the spatiotemporal distribution and risks of plastic additives in Taihu Lake during the COVID-19 pandemic, the occurrences of typical bisphenols, phthalate esters, and benzotriazoles in the surface water of Taihu Lake were investigated. The plastic additives in 19 sites in Taihu Lake were monitored in four seasons, and their potential ecological risks were evaluated. Diethylphthalate (DEP), dimethoxyethyl phthalate (DMEP), benzyl butyl phthalate (BBP), bisphenol A (BPA), and 2-(2H-benzotriazol-2-yl)-4, 6-di-tert-pentylphenol (UV-328) were detected, with detection rates of 100%, 97%, 58%, 98%, and 7%, respectively. During the COVID-19 pandemic, the sharply increasing usage of plastic products did not result in a significant increase in the plastic additives pollution in Taihu Lake. Conversely, the pollution of plastic additives showed a decreasing trend due to reduced human activities. There were significant seasonal differences in the concentrations of plastic additives in Taihu Lake. The average concentrations of plastic additives in spring and summer were 104.7 and 100.3 ng•L-1, respectively, which were higher than those in autumn (30.7 ng•L-1) and winter (29.9 ng•L-1). The plastic additive pollution also showed some differences in spatial distribution. The concentrations of plastic additives near the southwest coast of Taihu Lake were higher than those in other monitoring sites. The presence of plastic additives in Taihu Lake showed low risks to algae with the proportion of 30%. The risks in autumn and winter were higher than those in spring and summer. BPA and UV-328 may have been the main risk factors, which should be of concern. © 2022, Science Press. All right reserved.

Achieving Domestic Internationalization and Global Competence Through On-Campus Activities and Globally Responsive Education

The impacts of the COVID-19 pandemic on students and educators are well known. However, there is a paucity of literature available on its impact on educational institutions in the context of their abilities to develop global competence in the middle of an ongoing pandemic. The virtual communication and remote delivery of educational content have been a popular trend for many universities to adapt to the pandemic challenges and re-think their internationalization strategies. The limited travel opportunities because of the pandemic have highlighted a big need for the domestic internationalization mechanism at educational institutions. In this paper, the authors discuss how the Globally Responsive Education and Teaching (GREAT) program at Missouri State University is promoting globally responsive and inclusive teaching and learning among faculty and internationalization of the curriculum. It provides an overview of the activities and program structure of the GREAT program. In addition, it covers how culturally responsive teaching and global learning are being promoted for global competence by increased domestic Internationalization efforts. The importance of exploring global teaching and learning models and the significance of faculty engagement are emphasized in this paper. It also discusses how international virtual exchange learning gained popularity because of COVID-19 and how the GREAT program plans to integrate it by offering a grant to support faculty with an aim to promote the internationalization of the curriculum and global learning for all. This paper also discusses how lessons learned from teaching abroad and international education are being incorporated for domestic internationalization to provide similar international learning experiences for both domestic and international students. © American Society for Engineering Education, 2021

Synthesis and Primary Biological Evaluation of Triazole-Modified Picroside II Compounds

Picroside II, an iridoid glycoside, has anti-cancer, anti-virus, anti-apoptotic, nervous and myocardial protection effects and so on. However, the oral bioavailability of Picroside II is low, and the half-life in vivo is short, so it is limited to use in clinic. Triazole is a highly stable heterocyclic ring, which can be interacted with various enzymes or receptors in the organism through non-covalent interactions, and many of its good pharmacological activities in vitro and in vivo have been reported. Based on the advantages of triazole and Picroside II, a series of triazole-modified Picroside II derivatives (5 a–5 i) were synthesized by using drug combination principles for the first time. The structures were confirmed by different spectroscopic techniques including 1H NMR, 13C NMR and HRMS, and the primary biological evaluation of anti-breast cancer, anti-colorectal cancer, the effect on SARS-CoV-2 3CLpro inhibitor, and CD47-SIRPα protein were screened as well. Compound 5 e has anti-breast cancer activity, and compounds 3 and 5 i have anti-colorectal cancer activity. © 2021 Wiley-VCH GmbH

PORT: Pooled Ordered Rectangular Testing for Improved Public Health Screening

COVID19 has challenged the current day's medical testing capability. Pooled testing is an effective approach that can increase scale with limited resources and reduce the overall costs considerably. Current pooled testing techniques usually make the assumption that the entire population has a uniform probability of infection. However, symptomatic and asymptomatic patients have vastly different probabilities of testing positive, and positivity rates vary widely based on geographic regions. In this paper, we introduce a novel pooled testing technique that improves efficiency when handling the non-uniform likelihood of infection. We derive the expected cost for any rectangular pooling, using different pool sizes that suit different sub-populations. We develop a software system that takes in samples with varying probabilities and outputs optimized designs. Experiments with our software show that our approach is significantly more efficient than the 'optimal' double-pooled design and classic Dorfman-style single-pooled testing, with the efficiency gain depending on the positivity rates of the sub-populations mixtures. A simple restructuring using an estimated probability of infection can significantly reduce the costs of COVID19 or another testing. We provide open-source code and web-based services. © 2021 IEEE.

Factors affecting recurrent positive RT-PCR results in clinically cured COVID-19 patients: a multicenter study

The aim of this study was to evaluate factors affecting the recurrence of positive RT-PCR results. By performing a retrospective analysis, we evaluated the clinical data of recurrent positive coronavirus disease 2019 (COVID-19) patients in multiple medical institutions in Wuhan. We recruited COVID-19 patients who were hospitalized from January 1 to March 10, 2020, in three tertiary hospitals in Wuhan, met the discharge criteria and received at least one additional nucleic acid test before leaving the hospital. According to the RT-PCR results, patients were split into a recurrent positive group (RPos group) and a nonrecurrent positive group (non-RPos group). Clinical characteristics, therapeutic schedules and antibody titers were compared between the two groups. AI-assisted chest high-resolution computed tomography (HRCT) technology was applied to investigate pulmonary inflammatory exudation and compare the extent of lung areas with different densities. This study involved 122 COVID-19 patients. There were no significant differences in age, sex, preexisting diseases, clinical symptoms, clinical classification, course of disease, therapeutic schedules or serum-specific antibodies between the two groups. A higher proportion of patients who showed pulmonary inflammatory exudation on HRCT scans were recurrent positive at the time of discharge than other patients (81.6% vs 13.7%, P < 0.01). In addition, the degree of pulmonary fibrosis was higher in the RPos group than in the non-RPos group (P < 0.05). Subpleural exudation at the peripheral edge of the lung and extensive pulmonary fibrosis at the time of discharge represent risk factors for the recurrence of COVID-19.

Impact of COVID-19 on the clinical status of patients with Wilson disease

The coronavirus disease 2019 (COVID-19) pandemic has greatly impacted health systems. Many guidelines on chronic liver diseases have been released to optimize the use of medical resources and patient management. However, most of these guidelines have been established through expert consensus because the existing data do not provide strong evidence for developing effective recommendations. As Wilson disease (WD) is a rare chronic liver disease, the impact of COVID-19 on the clinical status of patients with WD is unclear. The present study showed a marked shortage of medical resources for clinically managing patients with WD during the pandemic. Although patients with WD who consistently took anticopper therapy showed no significant differences in hepatic and extrahepatic markers before and after the pandemic, their complication incidences, especially the infection incidence, were significantly increased during the study period. Therefore, patients with WD should be encouraged to adhere to anticopper therapy and be closely monitored to prevent infections and other complications. The present study provides a clinical basis for further managing WD during the pandemic.

EXAM: An Explainable Attention-based Model for COVID-19 Automatic Diagnosis

The ongoing coronavirus disease 2019 (COVID-19) is still rapidly spreading and has caused over 7,000,000 infection cases and 400,000 deaths around the world. To come up with a fast and reliable COVID-19 diagnosis system, people seek help from machine learning area to establish computer-Aided diagnosis systems with the aid of the radiological imaging techniques, like X-ray imaging and computed tomography imaging. Although artificial intelligence based architectures have achieved great improvements in performance, most of the models are still seemed as a black box to researchers. In this paper, we propose an Explainable Attention-based Model (EXAM) for COVID-19 automatic diagnosis with convincing visual interpretation. We transform the diagnosis process with radiological images into an image classification problem differentiating COVID-19, normal and community-Acquired pneumonia (CAP) cases. Combining channel-wise and spatial-wise attention mechanism, the proposed approach can effectively extract key features and suppress irrelevant information. Experiment results and visualization indicate that EXAM outperforms recent state-of-Art models and demonstrate its interpretability. © 2020 ACM.

[Analysis on the cluster epidemic of coronavirus disease 2019 in Guangdong Province].

Objective: Analysis of clustering characteristics of coronavirus disease 2019 (COVID-19) in Guangdong Province. Methods: The COVID-19 cases in Guangdong Province onset from January 1 to February 29, 2020 were collected from Chinese information system for disease control and prevention and Emergency Public Reporting System. Obtain the epidemiological survey data of the cluster epidemic situation, and clarify the scale of cluster epidemic situation, the characteristics of the index cases, family and non-family subsequent cases. Calculate serial interval according to the onset time of the index cases and subsequent cases, secondary attack rate based on the close contacts tracking results, the characteristics of different cases in the clustered epidemic were compared. Results: A total of 283 cluster were collected, including 633 index cases, 239 subsequent cases. Families are mainly clustered, the total number involved in each cluster is in the range of 2-27, M (P25, P75) are 2.0 (2.0, 4.0). During January 15 to February 29, the secondary attack rate is 2.86% (239/8 363) in Guangdong Province, the family secondary attack rate was 4.84% (276/3 697), and the non-family secondary attack rate was 1.32% (61/4 632). According to the reporting trend of the number of cases in Guangdong Province, it can be divided into four stages, the rising stage, the high platform stage, the descending stage and the low level fluctuation period. The secondary attack rate of the four stages were 3.5% (140/3 987), 2.3% (55/2 399), 2.6% (37/1 435), 1.3% (7/542), respectively. The difference was statistically significant (P=0.003). Conclusion: COVID-19 cluster mainly occurs in families in Guangdong Province. The scale of the clustered epidemic was small; the serial interval was short; and the overall secondary attack rate was low.

[Clinical outcomes of COVID-19 cases and influencing factors in Guangdong province].

Objective: To analyze the clinical courses and outcomes of COVID-19 cases and the influencing factors in Guangdong province and provide basis for the formulation or adjustment of medical care and epidemic control strategy for COVID-19. Methods: We collected demographic data, medical histories, clinical courses and outcomes of 1 350 COVID-19 patients reported in Guangdong as of 4 March 2020 via epidemiological investigation and process tracking. Disease severity and clinical course characteristics of the patients and influencing factors of severe illness were analyzed in our study. Results: Among 1 350 cases of COVID-19 cases in Guangdong, 72 (5.3%) and 1 049 (77.7%) were mild and ordinary cases, 164 (12.1%) were severe cases, 58 (4.3%) were critical cases and 7 (0.5%) were fatal. The median duration of illness were 23 days (P(25), P(75): 18, 31 days) and the median length of hospitalization were 20 days (P(25), P(75): 15,27 days). For severe cases, the median time of showing severe manifestations was on the 12(th) day after onset (P(25), P(75): 9(th) to 15(th) days), and the median time of severe manifestation lasted for 8 days (P(25), P(75): 4, 14 days). Among 1 066 discharged/fetal cases, 36.4% (36/99) and 1.0% (1/99) of the mild cases developed to ordinary cases and severe cases respectively after admission; and 5.2% (50/968) and 0.6% (6/968) of the ordinary cases developed to severe cases, and critical cases respectively after admission. In severe cases, 11.4% developed to critical cases (10/88). The influencing factors for severe illness or worse included male (aHR=1.87, 95%CI: 1.43-2.46), older age (aHR=1.67, 95%CI: 1.51-1.85), seeking medical care on day 2-3 after onset (aHR=1.73, 95%CI: 1.20-2.50) pre-existing diabetes (aHR=1.75, 95%CI: 1.12-2.73) and hypertension (aHR=1.49, 95%CI: 1.06-2.09). Conclusions: The course of illness and length of hospitalization of COVID-19 cases were generally long and associated with severity of disease clinical outcomes. The severe cases were mainly occurred in populations at high risk. In the epidemic period, classified management of COVID-19 cases should be promoted according to needs for control and prevention of isolation and treatment for the purpose of rational allocation of medical resources.

[Epidemiological investigation of a family clustering of COVID-19].

Objective: To investigate the epidemiological characteristics of a family clustering of COVID-19. Methods: Field epidemiological survey was conducted. Results: Case 1 of the long-term residents from Hubei province was the source of infection of this family clustering. There were 6 cases (from case 2 to case 7) infected in the whole incubation period. The incubation period was more than 14 days for 3 of the second-generation cases. Routes of transmission included respiratory droplets (from case 1 transmitted to case 6, from case 1 to her family members) and close contact (from case 1 to other cases in her family). All the age groups were generally susceptible, while elderly were easier to progress to critically ill. Besides respiratory symptoms, there were also gastrointestinal symptoms, of which diarrhea was the most common one. Conclusions: Family clustering had been an important part for COVID-19 cases.