ABSTRACT
Our research contributes a new point of view on China's rare earth dynamic risk spillover measurement;this was performed by combining complex network and multivariate nonlinear Granger causality to construct the time-varying connectedness complex network and analyze the formation mechanism using the impulse response. First, our empirical research found that for the dynamic characteristics of China's rare earth market, due to instability, uncertainty, and geopolitical decisions, disruption can be captured well by the TVP-VAR-SV model. Second, except for praseodymium, oxides are all risk takers and are more affected by the impact of other assets, which means that the composite index and catalysts are main sources of risk spillovers in China's rare earth trading complex network system. Third, from the perspective of macroeconomic variables, there are significant multivariate nonlinear impacts on the total connectedness index of China's rare earth market, and they exhibit asymmetric shock characteristics. These findings indicate that the overall linkage of the risk contagion in China's rare earth trading market is strong. Strengthening the interconnections among the rare earth assets is of important practical significance. Empirical results also provide policy recommendations for establishing trading risk protection measures under macro-prudential supervision. Especially for investors and regulators, rare earth oxides are important assets for risk mitigation. When rare earth systemic trading risk occur, the allocation of oxide rare earth assets can hedge part of the trading risk.
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In the present paper, the SIR model with nonlinear recovery and Monod type equation as incidence rates is proposed and analyzed. The expression for basic reproduction number is obtained which plays a main role in the stability of disease-free and endemic equilibria. The nonstandard finite difference (NSFD) scheme is constructed for the model and the denominator function is chosen such that the suggested scheme ensures solutions boundedness. It is shown that the NSFD scheme does not depend on the step size and gives better results in all respects. To prove the local stability of disease-free equilibrium point, the Jacobean method is used;however, Schur–Cohn conditions are applied to discuss the local stability of the endemic equilibrium point for the discrete NSFD scheme. The Enatsu criterion and Lyapunov function are employed to prove the global stability of disease-free and endemic equilibria. Numerical simulations are also presented to discuss the advantages of NSFD scheme as well as to strengthen the theoretical results. Numerical simulations specify that the NSFD scheme preserves the important properties of the continuous model. Consequently, they can produce estimates which are entirely according to the solutions of the model.
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In this paper, we will consider three deterministic models for the study of the interaction between the human immune system and a virus: the logistic model, the Gompertz model, and the generalized logistic model (or Richards model). A qualitative analysis of these three models based on dynamical systems theory will be performed by studying the local behavior of the equilibrium points and obtaining the local dynamics properties from the linear stability point of view. Additionally, we will compare these models in order to understand which is more appropriate to model the interaction between the human immune system and a virus. Some natural medical interpretations will be obtained, which are available for all three models and can be useful to the medical community.
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The City of Zagreb in Croatia and its surroundings have experienced two strong earthquakes within nine months of 2020. Putting this in the context of the increased workload of healthcare facilities due to Covid-19, the distribution system operator (DSO) is encouraged to look for unconventional solutions such as integrating the battery energy storage system (BESS) to supply healthcare facilities during network fault conditions or other extreme network events. The BESS size and location are determined by optimization model, while the control system of the BESS converter, based on the virtual synchronous machine (VSM) concept, is define to test BESS ability to supply critical consumers in the off-grid mode. The models are tested and verified on several real world situations in Zagreb MV distribution network. Future developments and scenarios are also simulated to verify the robustness of the proposed investment. © 2022 IEEE.
ABSTRACT
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19, has been a global concern. While there have been some vaccines and drugs, the rapid emergence of variants due to mutations has threatened public health. As the de novo drug development process is expensive and time-consuming, repurposing existing antiviral drugs against SARS-CoV-2 is an alternative and promising approach to mitigate the current situation. Several studies have indicated that some natural products exhibit inhibitory activities against SARS-CoV-2. This study is aimed at analyzing the potential of natural alkaloids, using various computational tools, as drug candidates against SARS-CoV-2. The molecular docking analysis predicted that naturally occurring alkaloids can bind with RNA-dependent RNA-polymerase (RdRP). The QSAR analysis was conducted by using the way2drug/PASS online web resource, and the pharmacokinetics and toxicity properties of these alkaloids were predicted using pkCSM, SwissADME, and ProTox-II webserver. Among the different alkaloids studied, neferine and berbamine were repurposed as potential drug candidates based on their binding affinity and interactions with RdRP. Further, molecular dynamics simulation of 90 ns revealed the conformational stability of the neferine-RdRP complex.
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In this paper, we consider a fractional SIS epidemic system with logistic growth demographic and saturated incidence rate for susceptibles. First, we validate our model by proving the global existence, positivity as well as boundedness of solutions. Then, we give necessary and sufficient conditions for the extinction and persistence of the disease from the population. We also study the local asymptotic stability of the unique positive equilibrium point by analyzing the corresponding characteristic equation. We find that combining logistic growth and saturated incidence for susceptibles can lead the system dynamic behavior to exhibit stability switches. By choosing the growth rate and the carrying capacity of the population as the bifurcation parameters, the stability of the positive equilibrium and the existence of Hopf bifurcation are investigated. Finally, numerical simulations are performed to verify the theoretical results, to fit real-time data from 10 June to 25 November of 2020 and also to predict the number of cumulative cases for COVID-19 in Morocco during 2021.
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Carbon dioxide capture and utilization (CCU) technology is a significant means by which China can achieve its ambitious carbon neutrality goal. It is necessary to explore the behavioral strategies of relevant companies in adopting CCU technology. In this paper, an evolutionary game model is established in order to analyze the interaction process and evolution direction of local governments and coal-fired power plants. We develop a replicator dynamic system and analyze the stability of the system under different conditions. Based on numerical simulation, we analyze the impact of key parameters on the strategies of stakeholders. The simulation results show that the unit prices of hydrogen and carbon dioxide derivatives have the most significant impact: when the unit price of hydrogen decreases to 15.9 RMB/kg or the unit price of carbon dioxide derivatives increases to 3.4 RMB/kg, the evolutionary stabilization strategy of the system changes and power plants shift to adopt CCU technology. The results of this paper suggest that local governments should provide relevant support policies and incentives for CCU technology deployment, as well as focusing on the synergistic development of CCU technology and renewable energy hydrogen production technology.
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This work explores Routh–Hurwitz stability and complex dynamics in models for awareness programs to mitigate the spread of epidemics. Here, the investigated models are the integer-order model for awareness programs and their corresponding fractional form. A non-negative solution is shown to exist inside the globally attracting set (GAS) of the fractional model. It is also shown that the diseasefree steady state is locally asymptotically stable (LAS) given that R0 is less than one, where R0 is the basic reproduction number. However, as R0>1, an endemic steady state is created whose stability analysis is studied according to the extended fractional Routh–Hurwitz scheme, as the order lies in the interval (0,2]. Furthermore, the proposed awareness program models are numerically simulated based on the predictor-corrector algorithm and some clinical data of the COVID-19 pandemic in KSA. Besides, the model’s basic reproduction number in KSA is calculated using the selected data R0=1.977828168. In conclusion, the findings indicate the effectiveness of fractional-order calculus to simulate, predict, and control the spread of epidemiological diseases.
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Purpose>This study aims to answer the question of how business models (BMs) maintain stability while coping with environmental uncertainties. This study proposes a dynamic co-evolution of knowledge management and business model transformation based on a comparative analysis of the focal firms’ BMs and their main partners in two e-commerce ecosystems in China.Design/methodology/approach>The open data of listed companies regarding the introduction of emerging topics on the transformation tendency of BMs in the post-COVID-19 business world is qualitatively analysed. The theoretical foundation is based on a critical review of the literature.Findings>Three aspects of the co-evolution between knowledge management and business model transformation are introduced. These three aspects are as follows: knowledge integration helps with multi-system business integration and decision-making collaborations;knowledge sharing helps to enhance cognitive ability and network value based on businesses;and the creation of new knowledge helps enrich the knowledge base and promote the transformation of BMs.Research limitations/implications>Solely attributing a firm’s ability to cope with environmental uncertainties to its business model weakens the importance of its knowledge management. This study argues that the co-evolution between knowledge management and business model transformation also plays a key role in a firm’s response to issues post-COVID-19.Originality/value>This study calls for the development of a normative theory of co-evolution between knowledge management and business model transformation, implying uncharted territories of knowledge management based on interaction with business model designs in e-business ecosystems.