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1.
Communications in Transportation Research ; 3, 2023.
Article in English | Scopus | ID: covidwho-2228261

ABSTRACT

The transit bus environment is considered one of the primary sources of transmission of the COVID-19 (SARS-CoV-2) virus. Modeling disease transmission in public buses remains a challenge, especially with uncertainties in passenger boarding, alighting, and onboard movements. Although there are initial findings on the effectiveness of some of the mitigation policies (such as face-covering and ventilation), evidence is scarce on how these policies could affect the onboard transmission risk under a realistic bus setting considering different headways, boarding and alighting patterns, and seating capacity control. This study examines the specific policy regimes that transit agencies implemented during early phases of the COVID-19 pandemic in USA, in which it brings crucial insights on combating current and future epidemics. We use an agent-based simulation model (ABSM) based on standard design characteristics for urban buses in USA and two different service frequency settings (10-min and 20-min headways). We find that wearing face-coverings (surgical masks) significantly reduces onboard transmission rates, from no mitigation rates of 85% in higher-frequency buses and 75% in lower-frequency buses to 12.5%. The most effective prevention outcome is the combination of KN-95 masks, open window policies, and half-capacity seating control during higher-frequency bus services, with an outcome of nearly 0% onboard infection rate. Our results advance understanding of COVID-19 risks in the urban bus environment and contribute to effective mitigation policy design, which is crucial to ensuring passenger safety. The findings of this study provide important policy implications for operational adjustment and safety protocols as transit agencies seek to plan for future emergencies. © 2023

2.
Engineering Management in Production and Services ; 14(4):61-76, 2022.
Article in English | Scopus | ID: covidwho-2224699

ABSTRACT

Within the context of the COVID-19 pandemic, community-level medical institutions as health service centres have been gaining importance in the medical reform expansion. As prior research has not fully addressed how to index and evaluate the quality of medical service, this article proposes a framework based on the service quality gap theory and the three-faceted "structure-process-outcome"quality evaluation theory. The study took the medical services at Beijing's Tianqiao Community Health Service Centre as an example to construct an index system for medical service quality evaluations. Data was collected from 211 people, and SPSS software was used for data processing and analysis. Due to the COVID-19 pandemic, patients without serious diseases tend to choose community hospitals to reduce their infection risk. As a result, they have growing requirements for clinics to have more departments and specialists. The studied community health service centre has encountered difficulties connected to low patient expectations, a poor medical environment, outdated hardware and equipment, and a low level of medical services. Some suggestions have been made to add specialised departments and consider the convenience of medical treatment for the elderly. © 2022 Qiong He et al., published by Sciendo.

3.
Acupuncture and Herbal Medicine ; 2(3):172-83, 2022.
Article in English | PubMed Central | ID: covidwho-2161215

ABSTRACT

Respiratory symptoms are most commonly experienced by patients in the early stages of novel coronavirus disease 2019 (COVID-19). However, with a better understanding of COVID-19, gastrointestinal symptoms such as diarrhea, nausea, and vomiting have attracted increasing attention. The gastrointestinal tract may be a target organ of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The intestinal microecological balance is a crucial factor for homeostasis, including immunity and inflammation, which are closely related to COVID-19. Herbal medicine can restore intestinal function and regulate the gut flora structure. Herbal medicine has a long history of treating lung diseases from the perspective of the intestine, which is called the gut–lung axis. The physiological activities of guts and lungs influence each other through intestinal flora, microflora metabolites, and mucosal immunity. Microecological modulators are included in the diagnosis and treatment protocols for COVID-19. In this review, we demonstrate the relationship between COVID-19 and the gut, gut–lung axis, and the role of herbal medicine in treating respiratory diseases originating from the intestinal tract. It is expected that the significance of herbal medicine in treating respiratory diseases from the perspective of the intestinal tract could lead to new ideas and methods for treatment.Graphical :: http://links.lww.com/AHM/A33.

4.
Chinese Journal of General Surgery ; 31(5):631-639, 2022.
Article in Chinese | Scopus | ID: covidwho-2145055

ABSTRACT

Background and Aims: Breast cancer is the most prevalent malignancy in women worldwide, and chemotherapy is one of the most important treatment modalities for breast cancer. Recent studies have shown that chemotherapy may exert anti-tumor effects by enhancing anti-tumor immunity in the tumor microenvironment. Therefore, this study was conducted to identify the changes in tumor-associated macrophages (TAMs) and relevant genes before and after neoadjuvant chemotherapy (NAC) in breast cancer patients by bioinformatics analysis and to evaluate the effect of NAC on immune functions in breast cancer patients. Methods: Information searching was performed by entering "Breast Cancer", "TAMs", "Chemotherapy" and selecting the human breast cancer tissue in the GEO database, and the GSE134600 dataset was selected for analysis. Differentially expressed genes (DEGs) in tissue samples from breast cancer patients before and after NAC were screened by R package (limma function). GO function enrichment and KEGG pathway analysis were performed for all DRGs. The protein interaction network of DEGs was visualized by Cytoscape software, and hub genes were screened and 10 hub genes were analyzed for mutations by cBioPortal. Immune cell distribution and correlation in GSE134600 data were evaluated using the R package“CIBERSORT”. Results: A total of 751 DEGs (409 up-regulated and 342 down-regulated genes) were identified before and after NAC for breast cancer. The biology of DEGs was analyzed by GO enrichment for biological process(BP), cellular component (CC), and molecular function(MF). In BP function, they were mainly enriched in type I interferon(IFN-I) signaling pathway/viral response and defense and viral life cycle;in CC function, they were mainly enriched in extrinsic components of cell membrane and cytoplasmic side of cell membrane;in MF function, they were mainly enriched in cytokine receptor binding, double-stranded RNA binding and lipopeptide binding. In the analysis of KEGG pathway enrichment, DEGs were mainly enriched in influenza A (H1N1), measles, hepatitis C, coronavirus disease COVID-19, NF-κB signaling pathway, EBV virus infection, NOD-like receptor signaling pathway, and amoeba disease signaling pathway. The top 10 hub genes with the highest degree of interaction with TAMs before and after NAC for breast cancer were screened by CytoHubba plug-in: IFIT1, ISG15, MX1, MX2, IRF7, RSAD2, IFIT3, IFI35, IFI6, and IFITM1. Multi-omics analysis revealed that IFIT1, MX1 and MX2 were mainly deletion mutations, IFIT1 mainly had deep gene deletion, while MX1 and MX2 were mainly associated with gene amplifications. The content of M0 macrophages, CD8+T cells and M2 macrophages in breast cancer tissues decreased after NAC, and M0 macrophages were positively correlated with memory B cells (r=0.64) and negatively correlated with unactivated CD4+ memory T cells (r=-0.66). Conclusion: The identified DEGs associated with TAMs in breast cancer patients before and after NAC are closely related to interferon signaling pathway, suggesting that interferon signaling pathway may play an important role by altering TAMs in NAC. Meanwhile, M0 macrophages are significantly altered before and after NAC, indicating that chemotherapy may regulate the immune response to tumor by changing the distribution of M0 macrophages and immune function. © 2022 Central South University. All right reserved.

5.
2022 IEEE World Congress on Services, SERVICES 2022 ; : 23, 2022.
Article in English | Scopus | ID: covidwho-2052073
6.
IEEE Transactions on Network Science and Engineering ; : 1-13, 2022.
Article in English | Scopus | ID: covidwho-2037845

ABSTRACT

Infectious diseases pose a severe threat to human health, especially the outbreak of COVID-19. After the infectious disease enters the stage of large-scale epidemics, vaccination is an effective way to control infectious diseases. However, when formulating a vaccination strategy, some restrictions still exist, such as insufficient vaccines or insufficient government funding to afford everyone's vaccination. Therefore, in this paper, we propose a vaccination optimization problem with the lowest total cost based on the susceptible-infected-recovered (SIR) model, which is called the Lowest Cost Of Vaccination Strategy (LCOVS) problem. We first establish a mathematical model of the LCOVS problem. Then we propose a practical Differential Evolution based Simulated Annealing (DESA) method to solve the mathematical optimization problem. We use the simulated annealing algorithm (SA) as a local optimizer for the results obtained by the differential evolution algorithm (DE) and optimized the mutation and crossover steps of DE. Finally, the experimental results on the six data sets demonstrate that our proposed DESA can achieve a more low-cost vaccination strategy than the baseline algorithms. IEEE

7.
Chemical Engineering Journal ; 451, 2023.
Article in English | Web of Science | ID: covidwho-2014984

ABSTRACT

The spread of drug-resistance bacteria is a serious issue of environment. Tools allowing to image single-cell genes can provide key information about the spatial pattern and heterogeneity of cell population. Herein, we explored the possibility of in situ activation of collateral trans-cleavage activity of CRISPR/Cas12a inside cells, to achieve a direct detection of single-cell non-repetitive genes. CRISPR/Cas12a allows to recognize target genes without the need for denaturation or digestion process. Particularly, the target gene-activated trans-cleavage by CRISPR/ Cas12a inside cells outputs an amplified signal for the gene recognition, allowing to visualize non-repetitive genes. The signal-to-background ratio for imaging drug-resistance gene, oqxB in the Salmonella enterica subsp. enterica serovar Typhimurium (S. Typhimurium) was further improved by combining multiple binding of Cas12a, enabled imaging of drug-resistance S. Typhimurium isolated from poultry farm and in the intestinal tract sec-tions. Single-cell investigation of S. Typhimurium under salt stress indicated that drug-sensitive strain owned a survival advantage over drug-resistance strain at high-content salt environment. This gene imaging methods holds potential for detecting the spread of drug resistance in the environment and serves as a means to inves-tigate the relationship between genotype and phenotype at single-cell level.

8.
Social Psychology Quarterly ; 2022.
Article in English | Web of Science | ID: covidwho-1997269
9.
IEEE Transactions on Computational Social Systems ; : 1-10, 2022.
Article in English | Scopus | ID: covidwho-1992674

ABSTRACT

Misinformation and rumors can spread rapidly and widely through online social networks, seriously endangering social stability. Therefore, rumor blocking on social networks has become a hot research topic. In the existing research, when users receive two opposing opinions, they tend to believe the one arrives first. In this article, we argue that users will dialectically trust the information based on their own opinions rather than the rule of first-come-first-listen. We propose a confidence-based opinion adoption (CBOA) model, which considers the opinion and confidence according to the traditional linear threshold (LT) model. Based on this model, we propose the directed graph convolutional network (DGCN) method to select the <inline-formula> <tex-math notation="LaTeX">$k$</tex-math> </inline-formula> most influential positive cascade nodes to suppress the propagation of rumors. Finally, we verify our method on four real network datasets. The experimental results show that our method can sufficiently suppress the propagation of rumors and obtains smaller number of rumor nodes than the baseline algorithms. IEEE

10.
IEEE Transactions on Affective Computing ; : 1-15, 2022.
Article in English | Scopus | ID: covidwho-1922769

ABSTRACT

The long-lasting global pandemic of Coronavirus disease 2019 (COVID-19) has changed our daily life in many ways and put heavy burden on our mental health. Having a predictive model of negative emotions during COVID-19 is of great importance for identifying potential risky population. To establish a neural predictive model achieving both good interpretability and predictivity, we have utilized a large-scale (n =542) longitudinal dataset, alongside two independent samples for external validation. We built a predictive model based on psychologically meaningful resting state neural activities. The whole-brain resting-state neural activity and social-psychological profile of the subjects were obtained from Sept. to Dec. 2019 (Time 1). Their negative emotions were tracked and re-assessed twice, on Feb 22 (Time 2) and Apr 24 (Time 3), 2020, respectively. We first applied canonical correlation analysis on both the neural profiles and psychological profiles collected on Time 1, this step selects only the psychological meaningful neural patterns for later model construction. We then trained the neural predictive model using those identified features on data obtained on Time 2. It achieved a good prediction performance (r =0.44, p =8.13 ×10-27). The two most important neural predictors are associated with self-control and social interaction. This study established an effective neural prediction model of negative emotions, achieving good interpretability and predictivity. It will be useful for identifying potential risky population of emotional disorders related to COVID-19. IEEE

11.
19th IEEE International Symposium on Biomedical Imaging, ISBI 2022 ; 2022-March, 2022.
Article in English | Scopus | ID: covidwho-1846117

ABSTRACT

The spread of the novel coronavirus disease 2019 (COVID-19) has claimed millions of lives. Automatic segmentation of lesions from CT images can assist doctors with screening, treatment, and monitoring. However, accurate segmentation of lesions from CT images can be very challenging due to data and model limitations. Recently, Transformer-based networks have attracted a lot of attention in the area of computer vision, as Transformer outperforms CNN at a bunch of tasks. In this work, we propose a novel network structure that combines CNN and Transformer for the segmentation of COVID-19 lesions. We further propose an efficient semi-supervised learning framework to address the shortage of labeled data. Extensive experiments showed that our proposed network outperforms most existing networks and the semi-supervised learning framework can outperform the base network by 3.0% and 8.2% in terms of Dice coefficient and sensitivity. © 2022 IEEE.

12.
INFORMS International Conference on Service Science, ICSS 2020 ; : 255-260, 2022.
Article in English | Scopus | ID: covidwho-1750467

ABSTRACT

Since December 2019, the COVID-19 outbreak has spread in over 100 countries and regions at a stunning pace. To prevent humanitarian health hazards such as COVID-19, people are strongly suggested to purchase and use Personal Protective Equipments (PPEs) for self-protection. However, the fraction of the population who refused to comply with the PPEs is high (and also much higher in some regions than others). In this paper, we focus on an empirically tested behavioral explanation for the compliance obstacle (a lack of self-control) based on the present-bias effect, which means the trend to give a higher valuation to a present reward but a lower valuation to a future reward (O’Donoghue & Rabin, 2006). Since the utility of PPEs is realized in the future, a consumer may postpone his purchase decision but finally abandon his purchase plan in the future period due to this present-bias effect. The key take-away we focus on is that advance selling can be beneficial to the consumers as a commitment device (Bryan et al., 2010). However, the effect of advance selling may be limited, especially for consumers with low valuation, and can only encourage a part of consumers to purchase PPEs. Advance selling alone cannot fully address the compliance obstacles in PPEs. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

13.
Medical Journal of Wuhan University ; 43(2):184-188, 2022.
Article in Chinese | Scopus | ID: covidwho-1687526

ABSTRACT

Objective: To assess the level of pulmonary ventilation function in patients with COVID‑19 after six months post⁃discharge and analyze the relevant influencing factors. Methods: In November 2020, patients with COVID‑19 were investigated in a district of Wuhan City, Hubei Province. Their pulmonary ventilation function indicators were measured, including forced vital capacity of percent predicted (FVC%pred), forced expiratory volume in one second of percent predicted (FEV1%pred), FEV1/FVC ratio (FEV1/FVC%), forced expiratory flow at 50% of percent predicted (FEF50%pred), forced expiratory flow at 75% of percent predicted (FEF75%pred), mean forced expiratory flow between 25% and 75% of percent predicted (MMEF%pred). The related factors affecting pulmonary ventilation function were analyzed. Results: A total of 151 discharged cases were recruited, which included 64 cases of mild illness, 87 cases of moderate illness. The average age of both men and women in the mild group was significantly higher than that in the moderate group (P<0.05). The mean values of the lung ventilation function indexes were all within the normal range. The FVC%pred in both male and female and FEV1%pred in female were better in the mild group than that in the moderate group (P<0.05). Some patients had mild abnormal pulmonary ventilation function and 11 cases in the mild group, 46 cases in the moderate group. Multi‑factor logistic regression analysis showed that women [OR=3.012, 95%CI(1.249,7.264)], the presence of a previous history of chronic disease [OR=2.739, 95%CI(1.186,6.326)], and cases of moderate illness [OR=6.365, 95%CI(2.730,14.840)] were the risk factors for abnormal pulmonary ventilation function after discharge. Conclusion: Half a year after discharge, the pulmonary ventilation function of both mild and moderate group patients recovered well. Women and those with chronic disease in the past should have more targeted health guidance during the post‑discharge recovery period. © 2022, Editorial Board of Medical Journal of Wuhan University. All right reserved.

14.
2021 IEEE International Ultrasonics Symposium, IUS 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1642563

ABSTRACT

This paper proposes a quantitative analysis method for lung ultrasound (LUS) images to evaluate the severity of COVID-19 pneumonia. Specifically, biomarkers related to the pleural line, including the thickness of pleural line (TPL) and the roughness of pleural line (RPL), and biomarkers related to the B-lines, including the accumulated width of B-lines (AWBL) and the acoustic coefficient of B-lines (ACBL), are extracted from LUS images to characterize the image patterns associated with the disease severity. 27 patients of COVID-19 pneumonia are enrolled in this study, including 13 moderate cases, 7 severe cases, and 7 critical cases. Patients of moderate cases are regarded as non-severe patients, and patients of severe and critical cases are regarded as non-severe patients. Biomarkers among different cases are compared, and the performances in the binary diagnosis of severe and non-severe patients are assessed using a support vector machine (SVM) classifier with all the biomarkers as the input. The classification performance is optimal using the SVM classifier (area under the receiver operating characteristics curve = 0.93, sensitivity = 0.93, specificity = 0.85). The proposed method may be a promising tool for the automatic grading and follow-up of patients with COVID-19 pneumonia. © 2021 IEEE.

15.
30th ACM International Conference on Information and Knowledge Management, CIKM 2021 ; : 4273-4282, 2021.
Article in English | Scopus | ID: covidwho-1528565

ABSTRACT

The ability to infer an individual's expertise for a given skill has proven to be crucial in creating economic opportunity for every talent of the global workforce. Applications ranging from recommending relevant job opportunities to talents to providing better candidate suggestions to recruiters, all benefit from deep understanding of the skill "proficiency"of the talent pool. LinkedIn's "Skill"profile section can be leveraged in this expert finding task. Whereas it is easy to incentivize members to put skills on their profile, estimating members' expertise is much more challenging for several reasons. First, the collection of ground-truth data at scale can be expensive and challenging. Second, "being proficient at a certain skill"can have very different meaning in different contexts - a professor in machine learning having deep theoretical knowledge might lack the practical skill for implementing a large-scale recommendation system unlike experienced ML practitioners. We present our proposed framework to infer a member's expertise in a certain skill based upon a multi-view, multi-task learning scheme that incorporates signals from multiple contexts. We show the efficacy of the proposed framework with offline evaluation results as well as online A/B testing in multiple products, from finding experts among friends, to recommending jobs to qualified members. We also show that our estimated proficiency can help alleviate the cold-start problem when applied to a new context (i.e., through transfer learning) where only a small amount of labeled data is needed to achieve reasonable performance. Finally, we share the insights that demonstrate the talent market is shocked disproportionately among members with different skill proficiency levels by COVID-19. © 2021 ACM.

16.
Frontiers in Education ; 6, 2021.
Article in English | Scopus | ID: covidwho-1346401

ABSTRACT

The COVID-19 epidemic has wreaked havoc on the economics of several countries. Downsizing, job shortages, and unemployment are among the significant effects. The markets are supported by the need to train and educate our youth to be job producers rather than job seekers. This study sought to investigate the role of universities in the formation of students’ attitudes toward entrepreneurship by analyzing the influence of locus of control, extracurricular activities, and curriculum on entrepreneurial intention among Pakistani university students. This study collected data from 536 students across 15 universities in Pakistan through a weblink questionnaire. SPSS and AMOS were used to test the theoretical model. Results confirmed that locus of control positively affects entrepreneurial intentions and is the strongest predictor among the other two variables. Extracurricular activities positively affect entrepreneurial intentions, and curriculum is also positively affecting entrepreneurial intentions. This study concluded that entrepreneurial education and acquaintance are essential in bringing entrepreneurial intentions among students. Locus of control is found to be the most substantial element in developing entrepreneurial intentions among students. Educational institutions can play a critical role by proactively contributing through their efficient and proficient curricula, professional and experienced teachers, and locus of control by combining curricular and co-curricular activities. © Copyright © 2021 Li, Pervaiz and He.

17.
Chinese Journal of Pharmacology and Toxicology ; 34(8):575-583, 2020.
Article in Chinese | Scopus | ID: covidwho-1341770

ABSTRACT

Severe acute respiratory syndrome Coronavirus type 2 (SARS-CoV-2) infection leads to severe acute respiratory system diseases, and its clinical manifestations and pulmonary pathological features are similar to those of acute lung injury and acute respiratory distress syndrome. Angiotensin-converting enzyme (ACE) 2 was previously identified as a functional receptor for the SARS Coronavirus (SARS-CoV), but it was recently discovered that SARS-CoV-2 could also bind to ACE2 on the cell surface to infect cells, causing cytopathic and tissue immune damage. Human ACE2, a homologous of human ACE, is a new type of metallocarboxypeptidase, with many properties distinct from ACE. ACE2 plays a unique role in the renin-angiotensin system and is involved in maintaining normal lung function. Currently, no definite and effective treatment scheme has been found for patients with Coronavirus disease 2019 (COVID-19). ACE2, as a key factor in the pathological pathway of COVID-19, is of great significance in the clinical treatment of and drug development against COVID-19. © 2020 Chinese Journal of Pharmacology and Toxicology. All rights reserved.

18.
Electrochimica Acta ; 387:8, 2021.
Article in English | Web of Science | ID: covidwho-1291914

ABSTRACT

The development of COVID-19 detection strategies with high sensitivity and selectivity are urgent for early diagnosis. Herein, we constructed an electrochemical dual-aptamer biosensor based on the metal organic frameworks MIL-53(Al) decorated with Au@Pt nanoparticles and enzymes to determine SARSCoV-2 nucleocapsid protein (2019-nCoV-NP) via co-catalysis of the nanomaterials, horseradish peroxidase (HRP) and G-quadruplex DNAzyme. First, the two thiol-modified aptamers (N48 and N61), as recognition elements, were immobilized on the surface of gold electrode (GE) to capture the biomarker 2019nCoV-NP. Then, the nanomaterial composites Au@Pt/MIL-53 (Al) were decorated by HRP and hemin/Gquadruplex DNAzyme as signal nanoprobe. The designed nanoprobe was applied to amplifying the aptasensor signal via co-catalyzing the oxidation of hydroquinone in the presence of hydrogen peroxide. Finally, the aptamer-protein-nanoprobe sandwich electrochemical detection system was fabricated on the GE surface. The results demonstrated that this aptasensor had a wide linear range from 0.025 to 50 ng mL -1 and the detection limit was 8.33 pg mL -1 for 2019-nCoV-NP. This aptasensor has great potential in the early diagnosis of COVID-19 with high sensitivity, selectivity and reliability. (c) 2021 Elsevier Ltd. All rights reserved.

19.
Letters in Drug Design & Discovery ; 18(4):355-364, 2021.
Article in Chinese | Web of Science | ID: covidwho-1256217

ABSTRACT

Background: The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has attracted worldwide attention due to its high infectivity and pathogenicity. Objective: The purpose of this study is to develop drugs with therapeutic potentials for COVID-19. Methods: we selected the crystal structure of 3CL pm to perform virtual screening against natural products in the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Then, molecular dynamics (MD) simulation was carried out to explore the binding mode between compounds and 3CL pro. Results and Discussion: A total of 6 candidates with good theoretical binding affinity to 3CL pm were identified. The binding mode after MD shows that hydrogen bonding and hydrophobic interaction play an important role in the binding process. Finally, based on the free binding energy analysis, the candidate natural product Gypenoside LXXV may bind to 3CL pm with high binding affinity. Conclusion: The natural product Gypenoside LXXV may have good potential anti-SARS-COV-2 activity.

20.
Frontiers of Economics in China ; 15(4):626-641, 2020.
Article in English | Web of Science | ID: covidwho-1073515

ABSTRACT

In this paper, following Blanchard and Fischer (1989), I investigate how the presence of the COVID-19 pandemic-the increase in the probability of death-may affect growth and welfare in a scale-invariant R&D-based Schumpeterian model. Without money, the increase in the probability of death has no effect on long-run growth and a negative effect on welfare. By contrast, when money is introduced via the cash-in-advance (CIA) constraint on consumption, the increase in the probability of death decreases long-run growth and welfare under elastic labor supply. Calibration shows that the quantitative effect of an increase in the probability of death on welfare is much larger compared to that on growth.

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