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Understanding the effect of process parameters on interfaces and interfacial bonding between two materials during multi-material additive manufacturing (MMAM) is crucial to the fabrication of high-quality and strong multi-material structures. The purpose of this paper is to conduct an experimental and statistical study to investigate the effect of process parameters of soft and hard materials on the flexural behavior of multi-material structures fabricated via material extrusion-based MMAM.

Sandwich beam samples composed of a soft core and hard shells are fabricated via MMAM under different printing conditions. A design of experiments is conducted to investigate the effect of the print speed and nozzle temperature on the flexural behavior of soft-hard sandwich beams. Analysis of variance and logistic regression analysis are used to analyze the significance of each process parameter. The interfacial morphology of the samples after the flexural tests is characterized. Thermal distributions during the MMAM process are captured to understand the effect of process parameters on the flexural behavior based on inter-bonding formation mechanisms.

Experimental results show that the soft-hard sandwich beams exhibited two different failure modes, including shell failure and interfacial failure. A transition of failure modes from interfacial failure to shell failure is observed as the nozzle temperatures increase. The samples that fail because of interfacial cracking exhibit a pure adhesive failure because of weak interfacial fracture properties. The samples that fail because of shell cracking exhibit a mixed adhesive and cohesive failure. The flexural strength and modulus are affected by the nozzle temperature for the hard material and the print speeds for both hard and soft materials significantly.

This paper first investigates the effect of process parameters for soft and hard materials on the flexural behavior of additively manufactured multi-material structures. Especially, the ranges of the selected process parameters are distinct, and the effect of all possible combinations of the process parameters on the flexural behavior is characterized through a full factorial design of experiments. The experimental results and conclusions of this paper provide guidance for future research on improving the interfacial bonding and understanding the failure mechanism of multi-material structures fabricated by MMAM.

Five-level rectifiers have received widespread attention because of their excellent performance in high-voltage and high-power applications. Taking a five-level rectifier with only four-IGBT for this study, a sliding mode predictive control (SMPC) algorithm is proposed to solve the problem of poor dynamic performance and poor anti-disturbance ability under the traditional model predictive control with the PI outer loop.

First, mathematical models under the two-phase stationary coordinate system and two-phase synchronous rotating coordinate system are established. Then, the design of the outer-loop sliding mode controller is completed by establishing the sliding mode surface and design approach rate. The design of the inner-loop model predictive controller was completed by discretizing the mathematical model equations. The modulation part uses a space vector modulation technique to generate the PWM wave.

The sliding mode predictive control strategy is compared with the control strategy with a PI outer loop and a model predictive inner loop. The proposed control strategy has a faster dynamic response and stronger anti-interference ability.

For the five-level rectifier, the advantages of fast dynamic influence and parameter insensitivity of sliding mode control are used in the voltage outer loop to replace the traditional PI control, and which is integrated with the model predictive control used in the current inner loop to form a novel control strategy with a faster dynamic response and stronger immunity to disturbances. This novel strategy is called sliding mode predictive control (SMC).

Sufficient sample data are the necessary condition to ensure high reliability; however, there are relatively poor fatigue test data in the engineering, which affects fatigue life's prediction accuracy. Based on this, this research intends to analyze the fatigue data with small sample characteristics, and then realize the life assessment under different stress levels.

Firstly, the Bootstrap method and the principle of fatigue life percentile consistency are used to realize sample aggregation and information fusion. Secondly, the classical outlier detection algorithm (DBSCAN) is used to check the sample data. Then, based on the stress field intensity method, the influence of the non-uniform stress field near the notch root on the fatigue life is analyzed, and the calculation methods of the fatigue damage zone radius and the weighting function are revised. Finally, combined with Weibull distribution, a framework for assessing multiaxial low-cycle fatigue life has been developed.

The experimental data of Q355(D) material verified the model and compared it with the Yao’s stress field intensity method. The results show that the predictions of the model put forward in this research are all located within the double dispersion zone, with better prediction accuracies than the Yao’s stress field intensity method.

Aiming at the fatigue test data with small sample characteristics, this research has presented a new method of notch fatigue analysis based on the stress field intensity method, which is combined with the Weibull distribution to construct a low-cycle fatigue life analysis framework, to promote the development of multiaxial fatigue from experimental studies to practical engineering applications.

Due to the limitation of experimental conditions and budget, fatigue data of mechanical components are often scarce in practical engineering, which leads to low reliability of fatigue data and reduces the accuracy of fatigue life prediction. Therefore, this study aims to expand the available fatigue data and verify its reliability, enabling the achievement of life prediction analysis at different stress levels.

First, the principle of fatigue life probability percentiles consistency and the perturbation optimization technique is used to realize the equivalent conversion of small samples fatigue life test data at different stress levels. Meanwhile, checking failure model by fitting the goodness of fit test and proposing a Monte Carlo method based on the data distribution characteristics and a numerical simulation strategy of directional sampling is used to extend equivalent data. Furthermore, the relationship between effective stress and characteristic life is analyzed using a combination of the Weibull distribution and the Stromeyer equation. An iterative sequence is established to obtain predicted life.

The TC4–DT titanium alloy is selected to assess the accuracy and reliability of the proposed method and the results show that predicted life obtained with the proposed method is within the double dispersion band, indicating high accuracy.

The purpose of this study is to provide a reference for the expansion of small sample fatigue test data, verification of data reliability and prediction of fatigue life data. In addition, the proposed method provides a theoretical basis for engineering applications.

This paper aims to reflect on the special issue that has collected studies by the research community in China pertinent to the country’s recent developments in sustainability accounting, management and policy, as well as to suggest possible future avenues of studies.

This paper articulates the current status of researching sustainability accounting, management and policy in China that is instigated by the country’s regulatory initiatives under its political economy. It highlights the papers accepted for the special issue, their areas of focus and the underlying characteristics.

It points out that the accepted research papers concentrate on issues related to corporate social responsibility disclosures, sustainability reporting and environmental management in China from the perspectives of the domestic stakeholders.

Future studies are likely to be increasingly interdisciplinary in nature and requires academia, policymakers and practitioners to make better collaborative efforts in researching about China’s sustainability and the efficacy of their engagement with stakeholders.

Studies on alignment between China’s further developments and UN’s sustainable development goals (SDGs) are particularly considered desirable as the country continues its globalization initiatives. Education about sustainability accounting for the working professionals and their next generation is much needed for China in support of developing a more sustainable economy aligned with UN's SDGs.

Scholars in China actively developing their research interests in this field reflect critical thinking about the country’s pursuit of sustainable development within a social-political economy that is dissimilar to the West. In the meantime, the country continues to develop into a significant stakeholder of the world’s sustainability implying expectation of transparency in sustainability performance.

With reference to the review exercise conducted for the special issue, it suggests that there are surging interests in researching accountability for sustainability across the local and international communities to facilitate much needed knowledge exchange. The country and indigenous culture of China, as well as its institutions in relation to sustainability, would require much further exploration in our world under globalization.

Accurate glide path tracking is vital to the automatic carrier landing task of unmanned aerial vehicle (UAV). The purpose of this paper is to develop a reliable flight controller that can simultaneously deal with external disturbance, structure fault and actuator fault.

The automatic carrier landing task is resolved into the glide path tracking problem and attitude tracking problem. The disturbance observer-based adaptive sliding mode control scheme is proposed for system stabilization, disturbance rejection and fault tolerance.

Both the Lyapunov method and exemplary simulations can prove that the disturbance estimation error and the attitude tracking error converge in finite time in the presence of external disturbances and various faults.

The presented algorithm is testified by a UAV automatic carrier landing simulation, which shows the potential of practical usage.

The barrier function is introduced to adaptively update both the sliding mode observer gain and sliding mode controller gain, so that the sliding mode surface could converge to a predefined region without overestimation. The proposed flight controller ensures a secure carrier landing task.

This paper aims to propose the automatic carrier landing system with the fault-tolerant ability for carrier-based aircraft in the presence of deck motion, external airwake disturbance and actuator fault, which consists of the reference trajectory generation module and flight control module.

The longitudinal and lateral basic controllers are designed based on the optimal preview control (OPC), which can ensure favorable tracking performance and anti-disturbance ability of system. Furthermore, based on the OPC, the robust fault-tolerant preview control scheme is proposed to attenuate the impact of actuator fault on system, which ensures the safe landing of carrier-based aircraft in case of actuator failure.

Both the Lyapunov method and simulations prove that the tracking errors can converge to zero and system states can be asymptotically stable both in normal and fault operations.

The fault-tolerant control strategy is introduced into preview control to deal with actuator fault, which combines feedforward control based on future previewable information and feedback control based on current information to improve the system performance.

The paper provides an overview of material helpful in placing the subsequent papers in context, as well as a summary of the research contributions made by the individual papers themselves.

We begin with a timeline of China’s Economic Reform, including both major events that permitted the opening and expansion of the nation’s economy, and important milestones of the historical movement. We then consider the impact of philosophy and culture (particularly, Confucianism and socialism) on China’s society and government, which leads naturally to certain observations regarding the political-economic model in which state-owned enterprises play a central role. In the final section, we briefly summarize the contents of the remaining papers.

This study aims to introduce an innovative approach that uses a decoder with multiple layers to accurately identify Chinese nested entities across various nesting depths. To address potential human intervention, an advanced optimization algorithm is used to fine-tune the decoder based on the depth of nested entities present in the data set. With this approach, this study achieves remarkable performance in recognizing Chinese nested entities.

This study provides a framework for Chinese nested named entity recognition (NER) based on sequence labeling methods. Similar to existing approaches, the framework uses an advanced pre-training model as the backbone to extract semantic features from the text. Then a decoder comprising multiple conditional random field (CRF) algorithms is used to learn the associations between granularity labels. To minimize the need for manual intervention, the Jaya algorithm is used to optimize the number of CRF layers. Experimental results validate the effectiveness of the proposed approach, demonstrating its superior performance on both Chinese nested NER and flat NER tasks.

The experimental findings illustrate that the proposed methodology can achieve a remarkable 4.32% advancement in nested NER performance on the People’s Daily corpus compared to existing models.

This study explores a Chinese NER methodology based on the sequence labeling ideology for recognizing sophisticated Chinese nested entities with remarkable accuracy.

This paper aims to verify whether the legitimate pressure of external forces on heavily polluting firms’ corporate social responsibility (CSR)-related behaviors affect firms’ assurance strategy in the Chinese context. The authors argue that, under external pressure, as a source of legitimacy, the assurance over CSR reports allows the business behaviors of heavy polluters to be recognized by society.

This paper sampled listed heavy polluters in China from 2011 to 2018 and used the multiperiod logit model to examine the effects of external corporate governance on firms’ assurance decisions. Principal component analysis methods were used to construct a comprehensive framework of external corporate governance. The indicators were obtained from the China Stock Market and Accounting Research databases, the NERI Report and the China Urban Statistical Yearbook.

This paper confirms that external corporate governance positively affects firms’ assurance decisions, and good financial conditions, well-governed internal controls and sufficient government subsidies positively moderate this effect.

The findings provide feasible ways to encourage firms’ high-quality corporate environmental information disclosure, thus providing valuable guidance for policymakers and other stakeholders to effectively supervise firms’ CSR behaviors.

The findings are of great importance in encouraging high-quality corporate environmental information disclosures, improving the support of capital markets among developing countries and drawing social attention to the environmental protection and social responsibility of heavy polluters.

The research extends the current research in the field of social environmental accounting by using legitimacy theory to explain firms’ assurance motivations. Additionally, this paper focuses on the practices of assurance services in the emerging economy and provides suggestions for developing assurance over CSR reports.