We propose a new CQ algorithm which combines the inertial technique and correction terms for solving the split feasibility problem with multiple output sets in Hilbert spaces. Under suitable conditions, we prove the weak convergence. Moreover, we demonstrate the linear convergence when the split feasibility problem with multiple output sets satisfies some bounded linear regularity property. Finally, numerical experiments are conducted to demonstrate superiority of our method over related inertial CQ method and classical CQ method for the split feasibility problem with multiple output sets.

The leader–follower consensus problem in the presence of parameter uncertainty and external disturbances is investigated for multiagent systems (MASs) with actuator faults, which are based on event‐triggered control. First, a new distributed event triggering strategy is proposed which avoids continuous communication between agents and is based on the state estimation of neighbouring agents. Instead, the growing estimation error is reset by communication updates. An adaptive update mechanism is also proposed which does not need any knowledge of the global aspects of the communication topology graph and does not need an upper threshold for parameter uncertainty and external disturbances in the protocol. The results show that the tracking error under the event‐triggered protocol asymptotically converges to zero, while avoiding Zeno behaviour. Finally, a numerical simulation confirms the feasibility of the theoretical results.

This study aims to explore the dynamic relationships among economic policy uncertainty (EPU), Bitcoin trading activity, and the NASDAQ index over the period from January 2, 2014, to March 21, 2023. Employing the dynamic conditional correlation–generalized autoregressive conditional heteroskedasticity (DCC‐GARCH) model, this research reveals significant time‐varying interdependencies between EPU and financial markets, with a specific focus on the Bitcoin sector. This paper extends the literature by examining EPU’s influence on trading volume and volatility spillovers during different market regimes and crisis events, including the COVID‐19 pandemic. The results demonstrate that the correlations between EPU and both Bitcoin and the NASDAQ index are dynamic and sensitive to market phases, with stronger effects observed during bull markets and heightened volatility during the pandemic. The findings provide new empirical evidence on the evolving role of EPU in shaping investor behavior and financial asset comovement. This study offers practical implications for investors, regulators, and policymakers, especially in designing risk management strategies under uncertainty.

Power network is one of the critical infrastructures, aiming to supply a reliable power. In general, some accidental and/or deliberate attacks may lead to large losses of power supply with severe social consequences. This paper considers a coarse‐grained model of power networks using a swing equation depending on the synchronous machine. Furthermore, we investigate the dynamical cascades failure, which is induced by power flows exceeding the capacity threshold of the transmission line. Therefore, a simple and flexible condition for synchronization is derived, which provides a new perspective for preventing cascading failure in oscillatory power network. The developed control approach is applied to several power network models to demonstrate its capability for suppressing cascading failures. In addition, it is found that the control effect strongly depends on the choice of control law. The study might be useful for enhancing the robustness of the power network or providing a more robust power supply.

Using data from Chinese A‐share listed companies from 2007 to 2022, we employ quantile regression to examine the impact of institutional ownership on corporate tax avoidance. The findings demonstrate that institutional ownership significantly reduces extreme short‐term tax avoidance behavior by companies and also influences their long‐term tax avoidance strategies. Moreover, institutional ownership effectively narrows the gap between a company’s effective tax rate and the industry average tax rate, indicating an optimizing effect on corporate tax planning. Additional analysis reveals the dynamic adjustment effect of institutional ownership on corporate tax avoidance strategies. Furthermore, the impact of institutional ownership on corporate tax avoidance significantly diminishes after controlling for the number of institutional investors. These findings contribute to a deeper understanding of the supervisory and governance role of institutional ownership in the operation of listed companies.

In this paper, chaos of a new exponential logistic map modulated by Gaussian function is investigated. Firstly, the stability of the fixed point is analyzed, and the occurrence of period doubling bifurcation in the system is verified theoretically. Subsequently, the chaotic behavior of the system is analyzed using bifurcation diagrams, phase portraits, and Lyapunov exponents. The numerical results confirm the existence of chaos in the exponential logistic map within a specific parameter range. In addition, the proposed map has additional parameter degrees of freedom compared to the existing generalized logistic maps, which provides different chaotic characteristics and enhances design flexibility required for diverse applications. At last, we further study the two‐dimensional coupled exponential logistic map and find that the system enters chaos through two routes: period doubling bifurcation and Hopf bifurcation.

In this article, the reaction‐diffusion Brusselator system and the Radhakrishnan, Kundu, and Laskshmanan (RKL) equation are discussed. The investigation is focused on the solution procedure of the nonlinear evolution equations in chemical and biological processes. Two approaches, namely the tan(θ/2)‐expansion approach and the exp(−Ω(η))‐expansion approach, are considered. A multitude of precise solutions is derived for the aforementioned equation. The phase portraits are generated using the Maple program by specifying predefined parameters. The solutions of the stated equations include the tan‐expansion function solutions, the kink solitary wave solutions, and the solitary wave solutions. The obtained results using both methods are useful and constructive and also are reliable for solving nonlinear partial differential equations used in nonlinear sciences.

As a new paradigm to provide services by acquiring and processing data, Internet of Things (IoT) has become one of the hot topics in academic and industrial areas. In this paper, we construct a tripartite evolutionary game model consisting data providers, service providers, and demanders. High quality of service mainly depends on the high quality of data and is important for improving the quality of experience of demanders. The model also considers the collusion between data providers and service providers, which can make it more realistic. To prevent free‐riding and false‐reporting problems, reward and punishment strategies are provided. Finally, the system stability of the equilibrium points of the model is verified through comprehensive simulation experiments, and effective methods are proposed to motivate all stakeholders to choose the best strategy. Through the representative evolutionary game model, the paper provides a new solution to the sustainable development of IoT.

In practice, trade‐in programs have been widely used to collect the old smart interconnected products (which are abbreviated as SIPs) and promote the new ones for sale. The SIPs trade‐in pricing strategy is studied when the digital intelligence level is considered by using the game‐theoretical method in our paper. The results show that the digital intelligence level has a positive effect on the selling price of SIPs and the demand under the dynamic pricing (which is abbreviated as DP) strategy. In the extended model, when the digital intelligence level is very high, it is suitable for the firm to select the DP strategy. On the other hand, the firm selects the static pricing (which is abbreviated as SP) strategy. When customers prefer to purchase the second‐generation SIPs, the firm chooses the single rollover (which is abbreviated as SR) strategy or selects the dual rollover (which is abbreviated as DR) strategy. The firm obtains the same profit under two different strategies.

This paper discusses the impact of trade policy uncertainty (TPU) on innovative behavior in export‐oriented enterprises using data of nonfinancial Chinese A‐share listed companies from 2007 to 2021. TPU index is constructed using a tariff measurement method and a text mining method after China’s accession to the WTO. The findings reveal that (1) the decrease in TPU promotes export‐oriented enterprises’ innovative input and output, and the positive effect is even more pronounced in eastern export‐oriented enterprises, general trade enterprises, and enterprises whose export destination is the high‐income countries. (2) For analyzing the transmission mechanism, it is found that the export scale, the financing restriction, and the digital transformation play positive intermediary roles, respectively, in the innovative behavior. The conclusions provide not only theoretical support to cope with TPU but also decision‐making reference on improving the innovative performance of export‐oriented enterprises.