ABSTRACT
Under the influence of the fifth industrial revolution and the outbreak of COVID-19, the digital transformation of enterprises has entered a new stage of rapid development. Digital transformation has become the trend of enterprise operation in the digital economy era. In this context, enterprise laboratory asset operation has also become an important aspect of enterprise digital operation. It is urgent to build a set of enterprise laboratory asset digital evaluation system to assist the implementation of enterprise digital strategy. Based on the characteristics of laboratory assets and the closed-loop theory of asset operation management, this paper analyzes and studies the laboratory asset management, establishes a targeted evaluation index system of digital asset management, focuses on the composition of the digital operation system of laboratory assets, and constructs a management index evaluation system of assets, efficiency, cost and other dimensions, so as to create a real-time, comprehensive and comprehensive evaluation system The closed-loop and full cycle digital management ecological environment realizes the effective integration of laboratory resource fragmentation information and the complete embodiment of digitization, provides service support for continuously improving asset management performance, and provides support for further improving enterprise economic efficiency and operation level. © 2022 SPIE.
ABSTRACT
Under the influence of the fifth industrial revolution and the outbreak of COVID-19, the digital transformation of enterprises has entered a new stage of rapid development. Digital transformation has become the trend of enterprise operation in the digital economy era. In this context, enterprise laboratory asset operation has also become an important aspect of enterprise digital operation. It is urgent to build a set of enterprise laboratory asset digital evaluation system to assist the implementation of enterprise digital strategy. Based on the characteristics of laboratory assets and the closed-loop theory of asset operation management, this paper analyzes and studies the laboratory asset management, establishes a targeted evaluation index system of digital asset management, focuses on the composition of the digital operation system of laboratory assets, and constructs a management index evaluation system of assets, efficiency, cost and other dimensions, so as to create a real-time, comprehensive and comprehensive evaluation system The closed-loop and full cycle digital management ecological environment realizes the effective integration of laboratory resource fragmentation information and the complete embodiment of digitization, provides service support for continuously improving asset management performance, and provides support for further improving enterprise economic efficiency and operation level. © 2022 SPIE.
ABSTRACT
As a typical representative of the regional economies' integration, the Yangtze River Delta region presents the development trend of emergency logistics integration under the background of the global epidemic of COVID-19, especially the outbreak in Shanghai. A scientific evaluation of the integration level of regional emergency logistics is crucial to the accurate construction of a post-epidemic emergency logistics system in the Yangtze River Delta region. This paper defines regional integration of emergency logistics as two dimensions of high-quality development and equilibrium development, and constructs a regional emergency logistics integration level evaluation index system containing 14 indicators for four factors: emergency logistics infrastructure, resource support, information sharing and mechanisms. A two-stage evaluation model is used to evaluate the integration level of emergency logistics in the Yangtze River Delta region, and the results are compared with the Beijing-Tianjin-Hebei region. According to the results, the integration of emergency logistics in the Yangtze River Delta region is at a medium level, with the highest integration level of emergency logistics infrastructure, the lowest integration level of emergency logistics information sharing, and the medium integration level of emergency logistics resource support and emergency logistics institutional mechanism. The density of integrated transport network and the efficiency of single-vehicle freight completion have the highest and lowest integration levels in the Yangtze River Delta region, respectively. And the integrated development level of emergency logistics in the Yangtze River Delta region is better than that in the Beijing-Tianjin-Hebei region, but there is little difference between the two, mainly due to the high level of integration of emergency logistics infrastructure and emergency logistics resource support. © 2022 IEEE.
ABSTRACT
The environmental-climate changes and the Covid-19 emergency have highlighted the weakness of urban systems by raising the attention on adequate tools able to support the improvement of multi-events resilience. The social, natural and economic features that characterize the urban environment, make it a complex system that need to be comprehensively assessed for taking into account all the relevant factors that contributes on their resilience. Aim of the work is to define a multicriteria-based methodology able to create a geo-referenced Urban Resilience Index (IUR) that represents the capacity of the territory to face socio-economic diseases and natural disaster. The proposed protocol consists of a step by step guide for creating the IUR with the adoption of the Analytic Hierarchy Process technique for structuring and aggregating the system of indicators that represent the relevant economic, environmental and social contributions to the resilience of a certain territorial scale, and the geographic information system for the visualization of the different spatial distribution of the resilience. The proposed methodology can be used as a decision support tool for public-private partnership’s urban intervention aimed at achieving the Sustainable Development Goals of the Agenda 2030 and the European Green Deal targets. Its flexibility makes it implementable for several sustainable urban planning decision at different scale and it can be adopted for an ex ante evaluation of the urban parameters from which derive the balance sheets and the pressures on the environment. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
The impact of climate change has been evidenced in several tourist destinations, and triggered concerns on the destination development. Low-carbon tourism has become a national, if not, global agenda that can be used to mitigate the climate change impact caused by the tourist destinations. To respond to this timely agenda and the United Nation World Tourism Organisation's (UNWTO) callout, this study establishes and verifies important components and attributes of low-Carbon destinations, particularly on island destination, which are still unexamined in the literature. Taking on the perspective of tourists, this study is driven by Stimulus-Organism-Response (S-O-R) theory which is a consolidative theoretical framework that integrates environmental input (external), emotional status (internal) and behavioural responses to explain actual behaviours of low-carbon tourists. Integrated generalised structured component analysis (IGSCA) and multigroup analysis were performed on 1808 travellers who posed different degrees of psychological fear of the COVID-19 pandemic. During COVID-19, health and safety risks have become a critical concern;therefore, this study further explores the moderating effect of risk from the perspective of the low- and high-perceived risk travellers, before identifying the attitude-behaviour gaps of these two groups. The study provides theoretical insights into low-carbon tourism experience at the island destinations and offers useful managerial implications on low-carbon destination development.
ABSTRACT
The novel coronavirus, SARS-CoV-2 pandemic has posed new challenges for physiotherapist due to unprecedented acute care patients' surge. It contributed to minimize physical activity, especially reducing the elbow range of motion (ROM). Early rehabilitation and physiotherapy are recommended to combat the adverse effects of extended immobility. However, the increased patient-physiotherapist interaction increased risks of disease transmission. There emerges a need to minimize this interaction and disease transmission probability. This study aims to speed-up the return to regular ROM of COVID-19 patients by developing a self-assisted device for successful elbow therapy. The proposed device referred as 'self-assisted', reflects the idea of active and passive patient intervention and early rehabilitation. The device is designed and programmed to characterize the patients into three levels, depending on their ROM vulnerability: level 1 below 50 degrees, level 2 50 degrees-100 degrees and level 3 above 100 degrees. To examine the efficacy and accuracy of SAPT-COVID-19, eight volunteers with varying ages were selected, who were home-bound due to prolong COVID-19 pandemic and compromised their functional ROM. SAPT-COVID-19 substantially strengthened the elbow ROM for the volunteers and hit the maximum functional ROM over 14 -days exercise session, resulting in approximately 10 improvement in elbow ROM The degree of efficiency of active and passive exercise has also been widely examined. SAPT-COVID-19 is supposed to prevent elbow ROM deterioration and reduce hospitalization, with therapeutic and economic gain and minimized the physiotherapist-patient interactions.
ABSTRACT
Building the index system of China's natural gas security and measuring the index have important meanings for on-line monitoring of natural gas safety, vigilance against potential risks of natural gas and guarantee of energy security. This paper innovatively applies the DMA-TVP-FAVAR model to build China's natural gas security comprehensive index (NGSI) from a dynamic perspective and systematically reviews its dynamic characteristics and transmission mechanism combined with the EEMD method and BP structure breaks test. The main conclusions are as follows: Since 2001, NGSI has shown a wavelike decrease. Specifically, short-term unbalanced factors mainly cause short-term fluctuation of NGSI, the effects of significant events are the main driving force for medium-term fluctuation of NGSI, and natural gas supply and demand fundamentals are the long-term inherent trend of NGSI. Besides, different monetary policy tools have different efficiency on NGSI, and price-based monetary policy instruments are more effective than quantitative monetary policy instruments. © 2022, Editorial Board of Journal of Systems Engineering Society of China. All right reserved.
ABSTRACT
The magnitude of a disaster's severity cannot be easily assessed because there is no global method that provides real magnitudes of natural disaster severity levels. Therefore, a new universal severity classification scheme for natural disasters is developed and is supported by data. This universal system looks at the severity of disasters based on the most influential impact factor and gives a rating from zero to ten: Zero indicates no impact and ten is a worldwide devastation. This universal system is for all types of natural disasters, from lightning strikes to super-volcanic eruptions and everything in between, that occur anywhere in the world at any time. This novel universal severity classification system measures, describes, compares, rates, ranks, and categorizes impacts of disasters quantitatively and qualitatively. The severity index is useful to diverse stakeholder groups, including policy makers, governments, responders, and civilians, by providing clear definitions that help convey the severity levels or severity potential of a disaster. Therefore, this universal system is expected to avoid inconsistencies and to connect severity metrics to generate a clear perception of the degree of an emergency; the system is also expected to improve mutual communication among stakeholder groups. Consequently, the proposed universal system will generate a common communication platform and improve understanding of disaster risk, which aligns with the priority of the Sendai Framework for Disaster Risk Reduction 2015-2030. This research was completed prior to COVID-19, but the pandemic is briefly addressed in the discussion section.
ABSTRACT
The rapid development of Internet in recent years has led to a proliferation of social media networks as people who can gather online to share information, knowledge, and opinions. However, the network public opinion tends to generate strongly misleading and a large number of messages can cause shocks to the public once major emergencies appear. Therefore, we need to make correct prediction regarding and timely identify a potential crisis in the early warning of network public opinion. In view of this, this study fully considers the features of development and the propagation characteristics, so as to construct a network public opinion early warning index system that includes 4 first-level indicators and 13 second-level indicators. The weight of each indicator is calculated by the "CRITIC" method, so that the comprehensive evaluation value of each time point can be obtained and the early warning level of internet public opinion can be divided. Then, the Back Propagation neural network based on Genetic Algorithm (GA-BP) is used to establish a network public opinion early warning model. Finally, the major public health emergency, COVID-19 pandemic, is taken as a case for empirical analysis. The results show that by comparing with the traditional classification methods, such as BP neural network, decision tree, random forest, support vector machine and naive Bayes, GA-BP neural network has a higher accuracy rate for early warning of network public opinion. Consequently, the index system and early warning model constructed in this study have good feasibility and can provide references for related research on internet public opinion.
ABSTRACT
The ability to mitigate the damages caused by emergencies is an important symbol of the modernization of an emergency capability. When responding to emergencies, government agencies and decision makers need more information sources to estimate the possible evolution of the disaster in a more efficient manner. In this paper, an optimization model for predicting the dynamic evolution of COVID-19 is presented by combining the propagation algorithm of system dynamics with the warning indicators. By adding new parameters and taking the country as the research object, the epidemic situation in countries such as China, Japan, Korea, the United States and the United Kingdom was simulated and predicted, the impact of prevention and control measures such as effective contact coefficient on the epidemic situation was analyzed, and the effective contact coefficient of the country was analyzed. The paper strives to provide early warning of emergencies scientifically and effectively through the combination of these two technologies, and put forward feasible references for the implementation of various countermeasures. Judging from the conclusion, this study reaffirmed the importance of responding quickly to public health emergencies and formulating prevention and control policies to reduce population exposure and prevent the spread of the pandemic.
ABSTRACT
Ahead of Print article withdrawn by publisher.