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The purpose of this paper is to develop high-performance Au-coated Ag alloy wires (ACAA wires) and demonstrate the effect of Au coating layers on the bonding performance and oxidation resistance for stable and reliable electronic packaging applications.

ACAA wire with a diameter of approximately 25 µm and Au layer thickness of approximately 100 nm were prepared by the continuous casting, plating and wire drawing method. The bonding performance of the ACAA wires were studied through bonding on 3,535 chips. The oxidation resistance of ACAA wires and Ag alloy wires (AA wires) were comparatively studied by means of chemical oxidation tests, accelerated life tests and electrochemical tests systematically.

ACAA wires could form axi-symmetrical spherical free air balls with controllable diameter of 1.5∼2.5 times of the wire diameter after electric flame-off process. The ball shear strength of ACAA wire was higher than that of AA wires. Most importantly, because of the surface Au coating layer, the oxidation resistance of ACAA wires was much enhanced.

ACAA wires with different lengths of heat affected zone were not developed in this study, which limited their application with different loop height requirements.

With higher bonding strength and oxidation resistance, ACAA wires would be a better choice than previous reported AA wire in chip packaging which require high stability and reliability.

This paper provides a kind of novel ACAA wire, which possess the merits of high bonding strength and reliability, and show great potential in electronic packaging applications.

This paper aims to present a novel robotic system for airport pavement inspection tasks.

The cloud-edge-terminal-based distributed architecture is designed for the proposed robotic system. Then, the following three major parts are designed and deployed, respectively: Terminal: the wheeled-robot-based data collection system. Edge: remote monitoring and data analysis system. Cloud: shared database center of the inspection data and knowledge.

Validation and application results show that the proposed system satisfies the demands of automated airport pavement inspection tasks and saves the cost of manpower and time.

The proposed system provides a novel solution for the full process of airport pavement inspection. Compared with the traditional manual method, the robotic system can guarantee complete coverage and provide high-precision pavement inspection results with less time and labor costs.

As an important participant in capital market, institutional investors play a principal role in improving corporate governance. Most existing studies have focused on institutional ownership and its economic consequences. Nevertheless, they have not provided sufficient insight on the governance behavior of institutional investors as well as the underlying incentive mechanism. This paper aims to analyze the governance role of institutional investors in information disclosure and provide related evidence.

The authors propose a novel theory to analyze the institutional investors’ behavior of active governance and shows that such behavior significantly improves the quality of corporate information disclosure. The authors then conduct an empirical test by using the hand-collected data of institutional investors’ corporate visits during 2009-2014 in ChiNext.

This paper finds that the firms visited by institutional investors are more likely to have a greater tendency of disclosing more information than the firms that have never been visited. In particular, a higher frequency of visits or a larger number of participating institutional investors leads to a higher degree of disclosure. Consistent with the notion that on-site visits endow institutional investors with more frequent and active interaction with the firms, the authors find that the results are stronger for firms which are visited on-site, when compared with other information acquisition activities such as online meetings, conference calls and investor meetings. In addition, the effect of a site visit is greater when the site visit is conducted by securities companies or funds rather than insurance companies or QFIIs. Finally, the test of the direction of causality suggests that visits conducted by institutional investors leads to more information disclosure, rather than the reverse. Collectively, these results show that institutional investors’ participation enhances corporate information disclosure.

This paper explores the internal mechanism that institutional investors affect corporate governance by improving information disclosure through their corporate visits. This is the first study to investigate the influence of institutional investors’ corporate visits and their economic consequences.

In this digital age and risk society, this study aims to explore innovative strategies for E-retailers during supply chain disruptions to construct a more resilient supply chain system.

Various game theoretical models are constructed to analyze four supply chain scenarios. Meanwhile, sufficient numerical analysis was conducted to observe the impact of key parameters on supply chain strategies.

Multiple crucial factors exert a comprehensive influence on E-retailers’ decisions on sourcing and pricing, leading to the diversity and complexity of decision-making conditions. First, with the increased probability of disruption, the purchase quantities of the E-retailer from different suppliers are not in a linear changing pattern, and the total purchase quantity is allocated variably between different suppliers. Second, the variation in disruption severity (partial or complete) results in the shift of decisions between single-sourcing and dual-sourcing. Responsive pricing is conducive to increasing the purchase quantity and profits under partial disruption; its advantages are diminished when completely disrupted. Third, higher commission rates usually have a detrimental impact on profit, whereas responsive pricing may mitigate this impact.

Unlike the previous single perspective, this study innovatively explores strategies from the hybrid perspective of sourcing and pricing. By extracting two key factors (disruption probability and severity), it realizes the scientific characterization of supply chain disruptions. These achievements boost theoretical innovation. Concentrating on E-retailers, it avoids the generalization of conclusions and enhances the application value.

According to relevant research, non-uniform speed has a significant impact on the vehicle-track systems. Up to now, research work on it is still very limited. In this paper, the PEM is adopted to further transform it into a deterministic process to solve the vehicle’s problem of running at a non-uniform speed.

The multi-body vehicle model has 10 degrees of freedom and the track is regarded as a finite long beam supported by lumped sleepers and ballast blocks. They are connected via linear Hertz springs. The vertical track irregularity is a Gaussian stationary process in the space domain. It is transformed into a uniformly modulated nonstationary random process in the time domain with respect to the non-uniform vehicle speed. By solving the equation of motion of the coupled vehicle-track system with the pseudo-excitation method, the pseudo-response and consequently the power spectral density and the standard deviation of the structural response can be obtained.

Two kinds of vehicle braking programs are taken in the numerical example and some beneficial conclusions are drawn.

The pseudo-excitation method (PEM) was used to perform the random vibration analysis of a coupled non-uniform speed vehicle-track system. Transforming the track irregularity into a uniformly modulated nonstationary random process in time domain with respect to the non-uniform vehicle speed was undertaken. The pseudo-response of the coupled system is solved by applying the Newmark algorithm with constant space integral steps. The random vibration transfer mechanism of the coupled system is fully discussed.

The crowdsourcing software development platforms organize geographically distributed developers to complete various developing tasks, bringing convenience and efficiency to users. However, with the increasing number of both developers and tasks, it becomes more and more challenging to match tasks and suitable developers, especially for imbalanced data. The purpose of this paper is to propose an accurate and diverse recommendation model for crowdsourcing tasks.

A revised circle loss function is applied to achieve a certain adaptive ability, which is critical for imbalanced data, it guarantees diversity by maximizing the target label score and leveraging mathematical approximation to automatically balance the weights. Besides, the authors leverage the capsule network to obtain the semantic feature of tasks’ descriptions, modify the dynamic routing mechanism to better learn users’ preferences and improve the recommendation accuracy.

The comprehensive experiments conducted on real crowdsourcing platform data demonstrate that the proposed Crowd-CapsNet model can achieve high recommendation accuracy with a certain diversity. It improves around 1% accuracy with only 37% training time of the LSFA approach.

This paper proposes Crowd-CapsNet, an adaptive crowdsourcing task recommendation model. A relatively general feature pre-processing method describes crowd-sourcing tasks and the modified capsule network further obtains the semantic features to improve the recommendation accuracy and diversity.

Wellness tourism is growing in importance as increasing numbers of travelers place a priority on their health and well-being by traveling. This study examined the relationships between wellness tourism destination attributes, perceived quality, perceived mental health, eudaimonic well-being, overall satisfaction and behavioral loyalty to corroborate a model explaining wellness tourism destination loyalty in Thailand.

The conceptual model of this study was examined using a survey research design. The survey questionnaire was distributed to Chinese tourists who had previously traveled to Thailand and engaged in wellness tourism activities during their trip.

The findings revealed that healthful food choices, core facilities and staff service significantly influenced perceived quality. This perceived quality was a crucial factor in determining perceived mental health, which in turn impacted eudaimonic well-being. Overall satisfaction was directly influenced by perceived quality, perceived mental health and eudaimonic well-being. Additionally, perceived quality had a direct effect on behavioral loyalty.

With the growing global interest in wellness and travel, this study offers valuable insights for tourism marketers in Thailand to enhance their wellness tourism strategies. Tourism organizations should emphasize the quality of food, facilities and staff service to attract wellness-oriented travelers.

This study highlights the interconnectedness of perceived quality, good mental health and eudaimonic well-being. High-quality experiences contribute to improved mental health and in turn enhance eudaimonic well-being.

Considering the impact of the Free Trade Zone (FTZ) policy on forecasting the port cargo throughput, this paper constructs a fractional grey multivariate forecasting model to improve the prediction accuracy of port cargo throughput and realize the coordinated development of FTZ policymaking and port construction.

Considering the effects of data randomization, this paper proposes a novel self-adaptive grey multivariate prediction model, namely FDCGM(1,N). First, fractional-order accumulative generation operation (AGO) is introduced, which integrates the policy impact effect. Second, the heuristic grey wolf optimization (GWO) algorithm is used to determine the optimal nonlinear parameters. Finally, the novel model is then applied to port scale simulation and forecasting in Tianjin and Fujian where FTZs are situated and compared with three other grey models and two machine learning models.

In the Tianjin and Fujian cases, the new model outperforms the other comparison models, with the least mean absolute percentage error (MAPE) values of 6.07% and 4.16% in the simulation phase, and 6.70% and 1.63% in the forecasting phase, respectively. The results of the comparative analysis find that after the constitution of the FTZs, Tianjin’s port cargo throughput has shown a slow growth trend, and Fujian’s port cargo throughput has exhibited rapid growth. Further, the port cargo throughput of Tianjin and Fujian will maintain a growing trend in the next four years.

The new multivariable grey model can effectively reduce the impact of data randomness on forecasting. Meanwhile, FTZ policy has regional heterogeneity in port development, and the government can take different measures to improve the development of ports.

Under the background of FTZ policy, the new multivariable model can be used to achieve accurate prediction, which is conducive to determining the direction of port development and planning the port layout.

The purpose of this work is to design the wire beam electrode (WBE) of P110 steel and study its corrosion behavior and mechanism under high temperature and pressure.

Packaging materials of the new type P110 steel WBE and high pressure stable WBE structure were designed. A metallurgical microscope (XJP-3C) and scanning electron microscopy (EV0 MA15 Zeiss) with an energy dispersive spectrometer were used to analyze the microstructure and composition of the P110 steel. The electrochemical workstation (CS310, CorrTest Instrument Co., Ltd) with a WBE potential and current scanner was used to analyze the corrosion mechanism of P110 steel.

According to the analysis of Nyquist plots at different temperatures, the corrosion resistance of P110 steel decreases with the increase of temperature under atmospheric pressure. In addition, R_p of P110 steel under high pressure is maintained in the range of 200 ∼ 375 Ωcm², while that under atmospheric pressure is maintained in the range of 20 ∼ 160 Ωcm², indicating that the corrosion products on P110 steel under high pressure is denser, which improves the corrosion resistance of P110 steel to a certain extent.

The WBE applied in high temperature and pressure environment is in blank. This work designed and prepared a WBE of P110 steel for high temperature and pressure environment, and the corrosion mechanism of P110 steel was revealed by using the designed WBE.

This study aims to investigate the mechanical and tribological behavior of 70Mn steel with different laser re-melted textured patterns.

Laser surface re-melting (LSR) was used to manufacture various textured patterns (i.e. line, grid and mixed) on both the original and heat-treated 70Mn steel plates. The micro-hardness, microstructure, tensile strength, yield strength, elongation, coefficients of friction (COF) and worn morphologies were characterized to evaluate the impact of different textured patterns on the overall performance.

The results show that re-melted unit exhibited the highest surface hardness on the subsurface. The increase in surface hardness of the re-melted unit for the heat-treated 70Mn steel samples was much lower than that of the original ones. The re-melted textured patterns did not improve the tensile strength, yield strength and elongation of either original or heat-treated 70Mn steel samples. The re-melted textured patterns effectively reduced the average COFs of heat-treated 70Mn steel samples, but increased friction of the non-heat-treated samples.

This study provides valuable insights into enhancing the mechanical properties and tribological characteristics of 70Mn steel, particularly in the automotive, heavy machinery and high-load application sectors. These industries have stringent requirements for durability and friction control, and the findings of this research are expected to effectively extend the lifespan of mechanical components.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2024-0443/