Dynamic Safety Assessment and Enhancement of Port Operational Infrastructure Systems during the COVID-19 Era

Seaports function as lifeline systems in maritime transportation, facilitating critical processes like shipping, distribution, and allied cargo handling. These diverse subsystems constitute the Port Infrastructure System (PIS) and have intricate functional interdependencies. The PIS is vulnerable to several external disruptions, and the impact of COVID-19 is severe and unprecedented in this domain. Therefore, this study proposes a novel general port safety framework to cope with recurring hazards and crisis events like COVID-19 and to augment PIS safety through a multi-state failure system. The PIS is divided into three critical subsystems: shipping, terminal, and distribution infrastructure, thereby capturing its functional interdependency and intricacy. A dynamic input-output model is employed, incorporating the spatial variability and average delay of the disruption, to determine the PIS resilience capacity under the stated disruptions. This study simulates three disruption scenarios and determines the functional failure capacity of the system by generating a functional change curve in Simulink. This study offers viable solutions to port managers, terminal operators, and concerned authorities in the efficient running of intricate interdependent processes and in devising efficient risk control measures to enhance overall PIS resilience and reliability. As part of future studies, given the difficulty in obtaining relevant data and the relatively limited validation of the current model, we aim to improve the accuracy and reliability of our model and enhance its practical applicability to real-world situations with data collected from a real-world case study of a PIS system.

A GIS-based analytical framework for evaluating the effect of COVID-19 on the restaurant industry with big data

COVID-19 cripples the restaurant industry as a crucial socioeconomic sector that contributes immensely to the global economy. However, what the current literature less explored is to quantify the effect of COVID-19 on restaurant visitation and revenue at different spatial scales, as well as its relationship with the neighborhood characteristics of customers' origins. Based on the Point of Interest (POI) measures derived from SafeGraph data providing mobility records of 45 million cell phone users in the US, our study takes Lower Manhattan, New York City, as the pilot study, and aims to examine 1) the change of restaurant visitations and revenue in the period prior to and after the COVID-19 outbreak, 2) the areas where restaurant customers live, and 3) the association between the neighborhood characteristics of these areas and lost customers. By doing so, we provide a geographic information system-based analytical framework integrating the big data mining, web crawling techniques, and spatial-economic modelling. Our analytical framework can be implemented to estimate the broader effect of COVID-19 on other industries and can be augmented in a financially monitoring manner in response to future pandemics or public emergencies.

Impacts of epidemics on innovation: An empirical analysis

Using data from 112 countries from 1998 to 2018, this study quantifies the overall impact of epidemics on innovation and identifies the underlying channels. Our results show that a 1% increase in the severity of an epidemic can significantly lead to a 0.059% decrease in patent applications and a 0.092% decrease in trademark applications. This negative impact can be explained by GDP, population and R & D expenditure channels. Further, our findings indicate that an increase in international personnel exchange (IPE) and foreign direct investment (FDI) can mitigate this negative impact. Finally, we discuss the policy implications of our results.

Demographic Groups' Differences in Restorative Perception of Urban Public Spaces in COVID-19

The health-promoting functions of one's spatial environment have been widely recognized. Facing the huge loss of mental resources caused by the COVID-19 pandemic, visiting and perception of urban public spaces with restorative potential should be encouraged. However perceived, restorativeness differs from individual features. Moreover, the COVID-19 pandemic has considerable effects on residents' leisure travel and psychological states. Therefore, the aim of our research is to identify the demographic variables influencing restorative perception of typical urban public spaces under the social background of the COVID-19 pandemic. The research consists of 841 residents' restorative evaluation of four kinds of urban public spaces according to the Chinese version of the Perceived Restorativeness Scale, including urban green spaces, exhibition spaces, commercial spaces and sports spaces. Then, 10 individual factors were recorded which represented their demographic features and the influence of COVID-19. Then, the relationship between individual features and perceived restoration of different urban public spaces was analyzed, respectively, by using One-way ANOVA and regression analysis. The results show that the urban green spaces were ranked as the most restorative, followed by commercial spaces, sports spaces and exhibition spaces. Further, the findings indicate that significant factors affect the restoration of four typical urban public spaces.

Utilizing integrating network pharmacological approaches to investigate the potential mechanism of Ma Xing Shi Gan Decoction in treating COVID-19.

Beginning in December 2019, coronavirus disease 2019 (COVID-19), due to 2019-nCoV infection, emerged in Wuhan and spread rapidly throughout China and even worldwide. Employing combined therapy of modern medicine and traditional Chinese medicine has been proposed, in which Ma Xing Shi Gan Decoction (MXSGD) was recommended as a basic prescription and applied widely in the clinical treatment of COVID-19. We investigated the underlying mechanism of MXSGD in treating COVID-19 utilizing the approaches of integrating network pharmacology. A total of 97 active ingredients of MXSGD were screened out, and 169 targets were predicted. The protein-protein interaction network exhibited hub targets of MXSGD, such as Heat shock protein 90, RAC-alpha serine/threonine-protein kinase, Transcription factor AP-1, Mitogen-activated protein kinase 1, Cellular tumor antigen p53, Vascular endothelial growth factor A, and Tumour necrosis factor. Gene Ontology functional enrichment analysis demonstrated that the biological processes altered within the body after taking MXSGD were closely related to the regulation of such processes as the acute inflammatory response, chemokine production, vascular permeability, response to oxygen radicals, oxidative stress-induced apoptosis, T cell differentiation involved in the immune response, immunoglobulin secretion, and extracellular matrix disassembly. KEGG enrichment analysis indicated that the targets of MXSGD were significantly enriched in inflammation-related pathways, immunomodulation-related pathways, and viral infection-related pathways. The therapeutic mechanisms of MXSGD on COVID-19 may primarily involve the following effects: reducing inflammation, suppressing cytokine storm, protecting the pulmonary alveolar-capillary barrier, alleviating pulmonary edema, regulating the immune response, and decreasing fever.