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The skin and skeleton of aircraft are connected by adhesives or rivets to bear and transfer aerodynamic load. It is easy for crack and fracture damage to occur under the action of cyclic load, thus reducing aircraft bearing capacity/integrity and causing serious security risks. Therefore, it is particularly important that passive wireless radio frequency identification (RFID) sensors be used for the health monitoring of aircraft skin in its whole life cycle. This paper aims to investigate the influence of miniaturization on the coupling effect between RFID tag sensors.

Two groups of crack sensing systems based on RFID tags were designed. Gain and mutual impedance of sensor tags were analyzed via mode analysis. The reliability of crack detection of both sensing systems was compared using a preset experimental scheme.

Miniaturized antennas can reduce edge influence and the coupling effect. Gain and mutual impedance decrease with the increase in distance between dual tags. Backscatter power shows a decreasing trend and threshold power to activate tags in reader antenna increases. Results show that the miniaturization of size is more suitable for the application of multiple sensors.

By comparing two groups of sensing systems, the consistency of crack detection sensitivity is better when small tags are placed in parallel, which provides a theoretical basis for the application of small, passive and densely distributed crack sensors in the future.

This paper aims to investigate the impact of open innovation (OI) in Chinese enterprises on enterprise value (EV). At the same time, this research explores the effects of OI in environmental, social and governance (ESG) and also reveals the intermediary role of ESG in the impact of OI on improving EV.

This study builds a theoretical framework to define a set of hypotheses verified in empirical research. Based on the panel data of Chinese listed companies removing missing data from 2011 to 2020, a two-way fixed effect model is used to study the relationship between OI, ESG and EV.

The research shows that OI of enterprises has effectively improved their value. At the same time, OI can also improve the ESG of enterprises. That OI increases EV is partly by the mediating path of ESG.

This study determines the influence of OI on EV from a stakeholder and sustainable development perspective, clarifying the mediating pathway of ESG in the relationship. Doing so could inspire companies to improve their OI and desire to enhance competitiveness. It will also prompt enterprises to pay attention to social responsibility activities.

Unconventional machining processes, particularly ultrasonic vibration cutting (UVC), can overcome such technical bottlenecks. However, the precise mechanism through which UVC affects the in-service functional performance of advanced aerospace materials remains obscure. This limits their industrial application and requires a deeper understanding.

The surface integrity and in-service functional performance of advanced aerospace materials are important guarantees for safety and stability in the aerospace industry. For advanced aerospace materials, which are difficult-to-machine, conventional machining processes cannot meet the requirements of high in-service functional performance owing to rapid tool wear, low processing efficiency and high cutting forces and temperatures in the cutting area during machining.

To address this literature gap, this study is focused on the quantitative evaluation of the in-service functional performance (fatigue performance, wear resistance and corrosion resistance) of advanced aerospace materials. First, the characteristics and usage background of advanced aerospace materials are elaborated in detail. Second, the improved effect of UVC on in-service functional performance is summarized. We have also explored the unique advantages of UVC during the processing of advanced aerospace materials. Finally, in response to some of the limitations of UVC, future development directions are proposed, including improvements in ultrasound systems, upgrades in ultrasound processing objects and theoretical breakthroughs in in-service functional performance.

This study provides insights into the optimization of machining processes to improve the in-service functional performance of advanced aviation materials, particularly the use of UVC and its unique process advantages.

This study aims to explore the effect of chief executive officer education on firms’ action timing and acquisition performance in industry merger waves. In addition, this study investigated the moderating influence of CEO duality and firm cash flow on the relationship between education and entry timing.

Following the methodology for determining merger waves in previous studies, the authors identified 16 industry merger waves of Chinese listed firms from 2008 to 2019. Multiple linear regression was employed to examine the hypotheses.

The results showed that higher CEO education was associated with early participation in merger waves. CEO duality negatively moderated the education-entry timing relation. The effect of CEO education on entry timing was more pronounced when firms had higher cash flow. Moreover, more educated CEOs materially enhanced acquisition performance in merger waves.

Entry timing in industry merger waves has important implications, as early movers establish competitive advantages and achieve higher acquisition performance. However, the managerial characteristics determining entry timing have not received adequate attention. Meanwhile, studies examining the effect of CEO education on acquisitions are limited. This study explored the effect of CEO education on firms’ entry timing and acquisition performance in merger waves, thereby contributing to the literature on merger waves and managerial characteristics. This study’s findings regarding the moderators of the education-entry timing relation enrich the literature on corporate governance and agency theory.

The economy of Fujian has caused tremendous development momentum and increased the economic exchanges between Taiwan and the mainland since the establishment of the free trade area of Fujian province. However, the contradiction between ecological protection and economic development should be considered on the basis of solving the problem of building trade zones. Performing regional trade zone planning from the ecological and economic perspectives is difficult, not only should the ecological and economic perspectives meet and emphasize the ecological and economical levels of interaction, but also achieve the optimization of eco-economic development potential of the free trade zone. In view of the above problems, according to the economy and resource allocation base of the new trade zone in Fujian Province, the space planning strategy development was carried out in this paper. In the overall layout of the new trade zone, the chain service area, the high-end service area, and the city near the port are taken as a major planning axis. North and South regions are gathering areas of shipping, logistics and new industries, developing on three partitions of function, improvement and advance around Haijing Road. The landscape is divided into Cai Jianwei mountain and Jing Kouyan mountain as the basis, and the third South China Sea Road and Haixin road form six corridors between mountain and sea. With the foundation of international cruise port development planning, the ease of east harbors should be promoted to north, and the development rhythm od airport planning areas should be strictly controlled, which can prepare for the later spatial release of the relocation of the airport from city planning areas. The main line of the important traffic node is reserved to improve the stock space, and the industrial neighborhood area near the central fishing port of Fujian and Taiwan is reserved, which can provide the regional space preparation for the planning of the new trade zone.

In recent years, deep learning and extended reality (XR) technologies have gained popularity in the built environment, especially in construction engineering and management. A significant amount of research efforts has been thus dedicated to the automation of construction-related activities and visualization of the construction process. The purpose of this study is to investigate potential research opportunities in the integration of deep learning and XR technologies in construction engineering and management.

This study presents a literature review of 164 research articles published in Scopus from 2006 to 2021, based on strict data acquisition criteria. A mixed review method, consisting of a scientometric analysis and systematic review, is conducted in this study to identify research gaps and propose future research directions.

The proposed research directions can be categorized into four areas, including realism of training simulations; integration of visual and audio-based classification; automated hazard detection in head-mounted displays (HMDs); and context awareness in HMDs.

This study contributes to the body of knowledge by identifying the necessity of integrating deep learning and XR technologies in facilitating the construction engineering and management process.

The purpose of this study is to examine how cloud computing assimilation reduces supply chain financing (SCF) risks of small and medium enterprises (SMEs). This study also investigated the mediating roles of internal and external supply chain integration between cloud computing assimilation and the SCF risks of SMEs, as well as the moderating role of environmental competitiveness.

Data was collected from surveys of SMEs located in China. Multiple regression analysis was used to validate the proposed theoretical model and research hypotheses.

The findings show that cloud computing assimilation could reduce the SCF risks of SMEs directly. The results also indicate that both internal and external supply chain integration mediate the relationship between cloud computing assimilation and SCF risks. Furthermore, environmental competitiveness inhibits the effects of cloud computing assimilation on SCF risks.

To our best knowledge, this is the preliminary study to explore the role of cloud computing assimilation in reducing the SCF risks of SMEs. Also, this study attempted to investigate the process by which cloud computing assimilation affects the SCF risks of SMEs.

The purpose of this paper is to solve the problem of quality prediction in the equipment production process and provide a method to deal with abnormal data and solve the problem of data fluctuation.

The analytic hierarchy process-process failure mode and effect analysis (AHP-PFMEA) structure tree is established based on the analytic hierarchy process (AHP) and process failure mode and effect analysis (PFMEA). Through the failure mode analysis table of the production process, the weight of the failure process and stations is determined, and the ranking of risk failure stations is obtained so as to find out the serious failure process and stations. The spectrum analysis method is used to identify the fault data and judge the “abnormal” value in the fault data. Based on the analysis of the impact, an “offset operator” is designed to eliminate the impact. A new moving average denoise operator is constructed to eliminate the “noise” in the original random fluctuation data. Then, DGM (1,1) model is constructed to predict the production process quality.

It is discovered the “offset operator” can eliminate the impact of specific shocks effectively, moving average denoise operator can eliminate the “noise” in the original random fluctuation data and the practical application of the shown model is very effective for quality predicting in the equipment production process.

The proposed approach can help provide a good guidance and reference for enterprises to strengthen onsite equipment management and product quality management. The application on a real-world case showed that the DGM (1,1) grey discrete model is very effective for quality predicting in the equipment production process.

The offset operators, including an offset operator for a multiplicative effect and an offset operator for an additive effect, are proposed to eliminate the impact of specific shocks, and a new moving average denoise operator is constructed to eliminate the “noise” in the original random fluctuation data. Both the concepts of offset operator and denoise operator with their calculation formulas were first proposed in this paper.

The purpose of this paper is to synthesize a new kind of conductive grease which possesses a prominent conductive capacity and good tribological properties.

A two-step method was used to prepare complex lithium-based grease. Ketjen black (KB), acetylene black (AB) and carbon black (CB) were characterized by transmission electron microscope and used as lubricant additives to prepare conductive greases. Conductive capacity was evaluated by a conductivity meter, a surface volume resistivity meter and a circuit resistance meter. Tribological properties were investigated by a reciprocating friction and wear tester (MFT-R4000). The worn surfaces were analyzed by a scanning electron microscope, Raman spectroscopy, energy-dispersive X-ray spectroscopy and X-ray photoelectron spectroscope.

The conductive grease prepared with KB has a prominent conductive capacity at room temperature, 100°C and 150°C. Further, this conductive grease also possesses better tribological properties than AB and KB greases. When the concentration of KB is 1.8 Wt.%, the coefficient of friction and wear width reduced by 11 and 14 per cent, respectively.

This work is a new application of nanometer KB as a lubricant additive in grease, which provides a direction for preparing conductive grease. The conductivity and tribology experiments have been carried out though the variation of experiment conductions.

This study aims to investigate the thermohydrodynamic (THD) and thermoelastohydrodynamic (TEHD) performance of an air-lubricated thrust bearing under different slip conditions, especially the slip length effect.

In this study, a new modified boundary slip model was established to investigate thrust bearing performance. The THD and TEHD bearing characteristic distribution was analyzed with fluid–thermal–structure interaction approach. The effect of the slip length on the bearing performance was studied using various bearing structure parameters.

The increased slip length changed the classical feature distribution of the film pressure and temperature. The sacrifice of the bearing load capacity effectively compensated for the aerodynamic thermal effect and friction torque under the slip condition. The TEHD model has a lower film pressure and load capacity than the THD model. However, it also has lower film temperature, lower friction torque and smaller Knudsen number (Kn).

The bearing THD and TEHD performances of the modified boundary slip model were compared with those of a traditional no-slip bearing. The results help to guide the selection of the bearing surface materials and processing technology of rotor and foil, so as to fully control the degree of slip and make use of it.