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A W-band antennas-in-packages (AIP) module with a hybrid stacked glass-compound wafer level fan-out process was presented. Heterogeneous radio frequency (RF) chips were integrated into one single module with a microscale fan-out process. This paper aims to find a new strategy for 5G communication with 3D integration of multi-function chips.

The AIP module was composed of two stacked layers: the antenna layer and RF layer. After architecture design and performance simulation, the module was fabricated, The 8 × 8 antenna array was lithography patterned on the 12 inch glass wafer to reduce the parasitic parameters effect, and the signal feeding interface was fabricated on the backside of the glass substrate.

AIP module demonstrates a size of 180 mm × 180mm × 1mm, and its function covers the complete RF front-end chain from the antenna to signal to process and can be applied in 5 G communication and automotive components.

With three RF multi-function chips and two through silicon via (TSV) chips were embedded in the 12 inch compound wafer through the fan-out packaging process; two layers were interconnected with TSV and re-distributed layers.

Accounting scandals and earnings management problems at large firms such as Global Crossing and Enron have resulted in lots of wealth loss not only to corporate investors but also led tremendous damage to societies. Hence, policymakers and academic researchers have started to explore mechanisms to prevent improprieties in financial reporting and further enhance firm value. Using data from United States (US)-listed companies between 2000 and 2018, this article explores the effect of ex-military executives on earnings quality, the role of financial analysts in their interplay and the firm value implication of earnings quality driven by ex-military executives.

This study employs a firm fixed-effects model to validate the main conjecture and adopts the weighted least squares, Granger causality analysis, instrumental variable approach, propensity score matching, entropy balancing approach and dynamic system Generalized Method of Moments (GMM) estimator to address robustness and endogeneity issues.

Authors reveal that companies run by ex-military senior executives exhibit lower levels of accruals-based and real earnings management than those without. The effect of management military leadership on constraining earnings management is more prominent for companies with low analyst coverage, suggesting that the military experience of executives could be a substitute for external monitoring. Authors also find that these ethical managers alleviate the negative impact of earnings management on firm value and that companies managed by these managers exhibit higher firm performance.

This study highlights the importance of the intrinsic motivation behind the effect of military experience on senior managers' personalities and offers essential stakeholder-related implications regarding the effect of military experience. The military experience of senior managers helps facilitate the attainment of broader corporate governance and economic objectives.

This article adds new insights to the literature on the role of managerial military experience in decision-making processes, financial reporting outcomes and firm performance by employing the upper echelons and imprinting theoretical perspectives.

The safety performance of cooperative robots is particularly important. This paper aims to study collision detection and response of cooperative robots, which meet the lightweight requirements of cooperative robots and help to ensure the safety of humans and robots.

This paper proposes a collision detection, recognition and response method based on dynamic models. First, this paper identifies the dynamic model of the robot. Second, an external torque observer is established based on the model, and a dynamic threshold collision detection method is designed to reduce the interference of model uncertainty on collision detection. Finally, a collision position and direction estimation method is designed, and a robot collision response strategy is proposed to reduce the harm caused by collisions to humans.

Comparative experiments are conducted on static threshold and dynamic threshold collision detection, and the results showed that the static threshold only detected one collision while the dynamic threshold could detect all collisions. Conducting collision position and direction estimation and collision response experiments, and the results show that this method can determine the location and direction of collision occurrence, and enable the robot to achieve collision separation.

This paper designs a dynamic threshold collision detection method that does not require external sensors. Compared with static threshold collision detection methods, this method can significantly improve the sensitivity of collision detection. This paper also proposes a collision position direction estimation method and collision separation response strategy, which can enable robots to achieve post collision separation and improve the safety of cooperative robots.

The purpose of the study was to prepare melamine-urea-formaldehyde (MUF) resin that would be resistant to boiling water and high temperature and exhibit low formaldehyde emission.

The authors prepared MUF resin with different F/(M + U) and changed the amount of melamine added, through the analysis of MUF resin properties to get the best reaction parameters, and used different amino acid cure systems including NH₄Cl cured the resin.

Resin’s heat resistance and water resistance are mainly determined by the amount of melamine added, and formaldehyde emission of the plywood can be changed by adjusting F/(M + U). The peak temperature of the curing agent-cured resin increases as compared with the self-curing resin. Stronger the acidity of curing agent, faster the viscosity increased in probation period and lower the bonding strength and heat resistance of the resin.

Melamine improves the heat resistance and water resistance of the resin. When the amount of melamine is more than a certain value, water resistance of the resin decreased.

MUF resin that is resistant to boiling water and exhibits low formaldehyde emission can be used in high temperature, high humidity and strict formaldehyde emission environment and can also be combined with other materials.

It was helpful to reduce the effect of formaldehyde emission on people’s health and environmental pollution and is also beneficial for the expansion of the application range of aldehyde resin.

The originality is twofold: the influence of the acid strength of curing agent on the bonding strength of the resin adhesive and the method for preparing high performance MUF resin by following the traditional process.

Vehicle fault diagnosis is a key factor in ensuring the safe and efficient operation of the railway system. Due to the numerous vehicle categories and different fault mechanisms, there is an unbalanced fault category problem. Most of the current methods to solve this problem have complex algorithm structures, low efficiency and require prior knowledge. This study aims to propose a new method which has a simple structure and does not require any prior knowledge to achieve a fast diagnosis of unbalanced vehicle faults.

This study proposes a novel K-means with feature learning based on the feature learning K-means-improved cluster-centers selection (FKM-ICS) method, which includes the ICS and the FKM. Specifically, this study defines cluster centers approximation to select the initialized cluster centers in the ICS. This study uses improved term frequency-inverse document frequency to measure and adjust the feature word weights in each cluster, retaining the top τ feature words with the highest weight in each cluster and perform the clustering process again in the FKM. With the FKM-ICS method, clustering performance for unbalanced vehicle fault diagnosis can be significantly enhanced.

This study finds that the FKM-ICS can achieve a fast diagnosis of vehicle faults on the vehicle fault text (VFT) data set from a railway station in the 2017 (VFT) data set. The experimental results on VFT indicate the proposed method in this paper, outperforms several state-of-the-art methods.

This is the first effort to address the vehicle fault diagnostic problem and the proposed method performs effectively and efficiently. The ICS enables the FKM-ICS method to exclude the effect of outliers, solves the disadvantages of the fault text data contained a certain amount of noisy data, which effectively enhanced the method stability. The FKM enhances the distribution of feature words that discriminate between different fault categories and reduces the number of feature words to make the FKM-ICS method faster and better cluster for unbalanced vehicle fault diagnostic.

User value co-creation behaviors are crucial for the sustainable development of Virtual Brand Communities. This research, grounded in social exchange theory, investigates the impact of community satisfaction and identification on customer value co-creation behaviors and further explores how the reciprocity norm moderates these relationships.

Our research data were collected from users across multiple brand communities, totaling 481 survey responses. Structural equation modeling was performed to test the research hypotheses.

These results provide in-depth insights into the nexus between user-community relationships and customer value co-creation behaviors. While community satisfaction and identification positively influence co-creation, their effects vary across different value co-creation behaviors. Notably, the reciprocity norm within the community dampens the relationship between community satisfaction and value co-creation behaviors.

Unlike previous studies focusing on customer value co-creation behaviors, our research emphasizes social exchange, unveiling the mechanisms behind customer value co-creation. Our findings not only enrich the body of knowledge on customer value co-creation but also deepen our understanding of online collective behavior and knowledge sharing, offering valuable insights for the development of virtual communities.

The purpose of this study is to evaluate the effect of graphene, basalt flakes and their synergy on the corrosion resistance of zinc-rich coatings. As the important heavy-duty anticorrosion coatings, zinc-rich coatings provided cathodic protection for the substrate. However, to ensure cathodic protection, a large number of zinc powder made the penetration resistance known as the weakness of zinc-rich coatings. Therefore, graphene and basalt flakes were introduced into zinc-rich coatings to coordinate its cathodic protection and shielding performance.

Three kinds of coatings were prepared; they were graphene modified zinc-rich coatings, basalt flakes modified zinc-rich coatings and graphene-basalt flakes modified zinc-rich coatings. The anticorrosion behavior of painted steel was studied by using the electrochemical impedance spectroscopy (EIS) technique in chloride solutions. The equivalent circuit methods were used for EIS analysis to obtain the electrode process structure of the coated steel system. Simultaneously, the corrosion resistance of the three coatings was evaluated by water resistance test, salt water resistance test and salt spray test.

The study found that the addition of a small amount of graphene and basalt flakes significantly improved the anticorrosion performance of coatings by enhancing their shielding ability against corrosive media and increasing the resistance of the electrochemical reaction. The modified coatings exhibited higher water resistance, salt water resistance and salt spray resistance. The graphene-basalt flakes modified zinc-rich coatings demonstrated the best anticorrosion effect. The presence of basalt scales and graphene oxide in the coatings significantly reduced the water content and slowed down the water penetration rate in the coatings, thus prolonging the coating life and improving anticorrosion effects. The modification of zinc-rich coatings with graphene and basalt flakes improved the utilization rate of zinc powder and the shielding property of coatings against corrosive media, thus strengthening the protective effect on steel structures and prolonging the service life of anticorrosion coatings.

The significance of developing graphene-basalt flakes modified zinc-rich coatings lies in their potential to offer superior performance in corrosive environments, leading to prolonged service life of metallic structures, reduced maintenance costs and a safer working environment. Furthermore, such coatings can be used in various industrial applications, including bridges, pipelines and offshore structures, among others.

The purpose of this paper is to propose a numerical prediction method of buckling loads for shell structures under axial compression and thermal loads based on vibration correlation technique (VCT).

VCT is a non-destructive test method, and the numerical realization of its experimental process can become a promising buckling load prediction method, namely numerical VCT (NVCT). First, the derivation of the VCT formula for thin-walled structures under combined axial compression and thermal loads is presented. Then, on the basis of typical NVCT, an adaptive step-size NVCT (AS-NVCT) calculation scheme based on an adaptive increment control strategy is proposed. Finally, according to the independence of repeated frequency analysis, a concurrent computing framework of AS-NVCT is established to improve efficiency.

Four analytical examples and one optimization example for imperfect conical-cylindrical shells are carried out. The buckling prediction results for AS-NVCT agree well with the test results, and the efficiency is significantly higher than that of typical numerical buckling methods.

The derivation of the VCT formula for thin-walled shells provides a theoretical basis for NVCT. The adaptive incremental control strategy realizes the adaptive adjustment of the loading step size and the maximum applied load of NVCT with Python script, thus establishing AS-NVCT.

The purpose of this paper is to present a novel numerical approach to analyze the static performance of aerostatic thrust bearings by adopting a general finite element method calculation program.

The characteristics of a gas film are described by the Reynolds equation and the pressure distribution is solved using the finite element method. A root iterative method is proposed to meet the requirement of the mass-conservation law because multiple pocketed orifice-type restrictors are treated as a series of special boundary conditions.

The static performance of a rotary table using aerostatic thrust bearings, including load carrying capacity and stiffness, can be predicted by the method; moreover, it can be further confirmed through experiments on the designed rotary table.

The method combining the finite element and root iterative methods is highly accurate and has a low time-cost for analyzing aerostatic thrust bearings with multiple pocketed orifice-type restrictors.

China is a significant energy consumer with increasingly severe resource constraints and environmental problems, requiring low-carbon energy transformation and encouraging high-quality energy development (HED). Green finance significantly affects the effect on HED as a cutting-edge financial strategy to support environmental improvement and encourage green development.

Using panel data from 30 provinces from 2007 to 2019 and the system-generalized method of moments method, this paper investigates the impact of green finance on HED, and further explores their threshold effect, heterogeneous and asymmetry analysis.

The main results indicate that: (1) green finance positively affects HED in China; in other words, a 1% increase in the green finance index will boost HED by an average of 0.767%; (2) as the economy improves, the positive impact of green finance on HED will be even more significant and (3) the contribution of green finance to HED is more significant in the northern provinces and areas with lower HED levels.

This paper puts forward relevant policy suggestions to further improve the construction of the green financial system.