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This paper aims to examine the impacts of unstable off-farm employment on the probability and stability of farmland rent-out and explore its mechanisms.

The paper adopts Ordinary Least Squares (OLS), Probit, Tobit, Order probit models with two-way fixed effects to conduct empirical analysis based on the balanced panel data collected in 2016 and 2023 with a national representativeness sample of 1,206 rural households in 100 villages across 5 provinces in China.

The empirical results showed that unstable off-farm employment had negative effects on the probability of farmland rent-out, but it had no effects on the stability of farmland rent-out. The mechanism analysis showed that unstable off-farm employment affected the probability of farmland rent-out by decreasing the probability of purchasing houses in city and endowment insurance with high pension. Heterogeneity analysis indicated that the negative effect of unstable off-farm employment was much larger for the households with higher share of labor engaging in off-farm employment outside home county, elder members in the households and those located in the villages of mountain areas.

This paper is the first to define the unstable off-farm employment from the perspective of incontiguous off-farm employment for several years, which could capture the normality rather than particular case in a certain year of off-farm employment among rural labors. Using these new measurements of unstable off-farmland, this paper examined the impacts and mechanisms of share of unstable off-farm employment on the probability and stability of farmland rent-out.

This paper is concerned with non-fragile robust H_∞ control problems for nonlinear networked control systems (NCSs) with time-varying delay and unknown actuator failures. The paper aims to discuss these issues.

The system parameters are allowed to have time-varying uncertainties and the actuator faults are unknown but whose upper and lower bounds are known. By using some lemmas, uncertainties can be replaces with the known values. By taking the exogenous disturbance and network transmission delay into consideration, a delay nonlinear system model is constructed.

Based on Lyapunov stability theory, linear matrix inequalities (LMIs) and free weighting matrix methods, the sufficient conditions for the existence of the non-fragile robust H_∞ controller gain are derived and which can obtained by solving the LMIs. Finally, a numerical example is provided to illustrate the effectiveness of the proposed methods.

The introduced approach is interesting for NCSs with time-varying delay and unknown actuator failures.

As an emerging technology, medical artificial intelligence (AI) plays an important role in the healthcare system. However, the service failure of medical AI causes severe violations to user trust. Different from other services that do not involve vital health, customers' trust toward the service of medical AI are difficult to repair after service failure. This study explores the links among different types of attributions (external and internal), service recovery strategies (firm, customer, and co-creation), and service recovery outcomes (trust).

Empirical analysis was carried out using data (N = 338) collected from a 2 × 3 scenario-based experiment. The scenario-based experiment has three stages: service delivery, service failure, and service recovery. The attribution of service failure was divided into two parts (customer vs. firm), while the recovery of service failure was divided into three parts (customer vs. firm vs. co-creation), making the design full factorial.

The results show that (1) internal attribution of the service failure can easily repair both affective-based trust (AFTR) and cognitive-based trust (CGTR), (2) co-creation recovery has a greater positive effect on AFTR while firm recovery is more effective on cognitive-based trust, (3) a series of interesting conclusions are found in the interaction between customers' attribution and service recovery strategy.

The authors' findings are of great significance to the strategy of service recovery after service failure in the medical AI system. According to the attribution type of service failure, medical organizations can choose a strategy to more accurately improve service recovery effect.

China has recently introduced a new audit law that aims to increase the scope of audit supervision and raise the standards for preventing risks in auditing national public projects. This paper presents a systematic research study on the causes of audit risks in national public projects and discusses the process by which these causes contribute to the emergence of such risks. Furthermore, the paper investigates the core risk sources in various types of national construction project audit. This paper aims to provide theoretical support for auditors of national construction projects in risk avoidance when conducting audits.

In this study, the authors carefully selected five national public audit projects from China and performed a comprehensive analysis of 85 relevant audit documentation. The textual analysis was conducted using Nvivo12 software, and the grounded theory approach was adopted for generalization purposes.

Based on the research results, the findings suggest that there are five key causes contributing to the audit risk of national construction projects: professional competence, risk awareness, management capacity, level of attention and deliberate fraud. The most critical factor identified is management capability, with 59.93% of the data supporting this view. This conclusion was based on an analysis of state-owned enterprises, administrative organs and public institutions. Building upon this, a framework titled “the mechanism of audit risk factors with management capability as the core” was constructed.

This paper employs qualitative analysis methods to examine national construction projects in China, contributing new literature to the theoretical study of audit risk management. The article also provides practical recommendations for auditors on how to mitigate audit risks and improve the quality of audit services in national project governance.

A switching depth controller based on a variable buoyancy system (VBS) is proposed to improve the performance of small autonomous underwater vehicles (AUVs). First, the requirements of VBS for small AUVs are analyzed. Second, a modular VBS with high extensibility and easy integration is proposed based on the concepts of generality and interchangeability. Subsequently, a depth-switching controller is proposed based on the modular VBS, which combines the best features of the linear active disturbance rejection controller and the nonlinear active disturbance rejection controller.

The controller design and endurance of tiny AUVs are challenging because of their low environmental adaptation, limited energy resources and nonlinear dynamics. Traditional and single linear controllers cannot solve these problems efficiently. Although the VBS can improve the endurance of AUVs, the current VBS is not extensible for small AUVs in terms of the differences in individuals and operating environments.

The switching controller’s performance was examined using simulation with water flow and external disturbances, and the controller’s performance was compared in pool experiments. The results show that switching controllers have greater effectiveness, disturbance rejection capability and robustness even in the face of various disturbances.

A high degree of standardization and integration of VBS significantly enhances the performance of small AUVs. This will help expand the market for small AUV applications.

This solution improves the extensibility of the VBS, making it easier to integrate into different models of small AUVs. The device enhances the endurance and maneuverability of the small AUVs by adjusting buoyancy and center of gravity for low-power hovering and pitch angle control.