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Aircraft assembly is the crucial part of aircraft manufacturing, and to meet the high-precision and high-efficiency requirements, cooperative measurement consisting of multiple measurement instruments and automatic assisted devices is being adopted. To achieve the complete data of all assembly features, measurement devices need to be placed at different positions, and the flexible and efficient transfer relies on Automated Guided Vehicles (AGVs) and robots in the large-size space and close range. This paper aims to improve the automatic station transfer in accuracy and flexibility.

A transferring system with Light Detection and Ranging (LiDAR) and markers is established. The map coupling for navigation is optimized. Markers are distributed according to the accumulated uncertainties. The path planning method applied to the collaborative measurement is proposed for better accuracy. The motion planning method is optimized for better positioning accuracy.

A transferring system is constructed and the system is verified in the laboratory. Experimental results show that the proposed system effectively improves positioning accuracy and efficiency, which improves the station transfer for the cooperative measurement.

A Transferring system for collaborative measurement is proposed. The optimized navigation method extends the application of visual markers. With this system, AGV is capable of the cooperative measurement of large aircraft structural parts.

Due to the advantages of fast response, high positioning precision and large stiffness, the piezoelectric-actuated nanopositioning stage is widely used in the micro/nanomachining fields. However, due to the inherent nonlinear hysteresis of the piezoelectric-actuator, the positioning accuracy of nanopositioning stage is greatly degraded. Besides, the nanopositioning stage is always performed with repetitive trajectories as the reference signals in applications, which makes the hysteresis behavior periodic. To this end, an adaptive resonance suppression iterative learning control (ARS-ILC) is proposed to address the hysteresis effect. With this effort, the positioning accuracy of the nanopositioning stage is improved.

The hysteresis behavior is identified by the Prandtl–Ishlinskii model. By establishing a convergence function, it is demonstrated that the learnable band of ILC is restricted by the lightly damping resonance of nanopositioning stage. Then, an adaptive notch filter (ANF) with constrained poles and zeros is adopted to suppress the resonant peak. Finally, online stability supervision (OSS) is used to ensure that the estimated frequency converges to the resonant frequency.

A series of experiments were carried out in the nanopositioning stage, and the results validated that the OSS is available to ensure the convergence of the ANF. Furthermore, the learnable band was extended via ARS-ILC; thus, the hysteresis behavior of nanopositioning stage has been canceled.

Due to high accuracy and easy implementation, the ARS-ILC can be used in not only nanopositioning stage control but other fabrication process control with repetitive motion.

This study aims to provide a comprehensive review and bibliometric analysis of the literature in the field of science, technology, engineering and mathematics (STEM) education over the past 15 years, with a specific focus on global distribution and research trends.

This study collected 1,718 documents from the Web of Science (WOS) database and analyzed their timeline distribution, geographical distribution, research topics, subject areas, learning stages and citation burst using a bibliometric approach with VOSviewer and Citespace.

Results indicated that: overall, STEM education has increasingly gained scholarly attention and is developing diversely by emphasizing interdisciplinary, cross-domain and regional collaboration. In terms of global collaboration, a collaborative network with the USA in the center is gradually expanding to a global scope. In terms of research themes, four key topics can be outlined including educational equity, pedagogy, empirical effects and career development. Social, cultural and economic factors influence the way STEM education is implemented across different countries. The developed Western countries highlighted educational equity and disciplinary integration, while the developing countries tend to focus more on pedagogical practices. As for research trends, eastern countries are emphasizing humanistic leadership and cultural integration in STEM education; in terms of teachers’ professional development, teachers’ abilities of interdisciplinary integration, technology adoption and pedagogy application are of the greatest importance. With regards to pedagogy, the main focus is for developing students’ higher-order abilities. In terms of education equity, issues of gender and ethnicity were still the hottest topics, while the unbalanced development of STEM education across regions needs further research.

This study provides a global landscape of STEM education along the timeline, which illustrates the yearly progressive development of STEM education and indicates the future trends.

Political factors play a crucial role in China's initial public offering (IPO) market due to its distinctive institutional context (i.e. “economic decentralization” and “political centralization”). Given the significant level of IPO underpricing in China, we examine the impact of local political uncertainty (measured by prefecture-level city official turnover rate) on IPO underpricing.

Using 2,259 IPOs of A-share listed companies from 2001 to 2019, we employ a structural equation model (SEM) to examine the channel (voluntarily lower the issuance price vs aftermarket trading) through which political uncertainty affects IPO underpricing. We check the robustness of the results using bootstrap tests, adopting alternative proxies for political uncertainty and IPO underpricing and employing subsample analysis.

Local official turnover-induced political uncertainty increases IPO underpricing by IPO firms voluntarily reducing the issuance price rather than by affecting investor sentiment in aftermarket trading. These relations are stronger in firms with pre-IPO political connections. The effect of political uncertainty on IPO underpricing is also contingent upon the industry and the growth phase of an IPO firm, more pronounced in politically sensitive industries and firms listed on the growth enterprise market board.

Local government officials in China usually have a short tenure and Chinese firms witness significantly severe IPO underpricing. By introducing the SEM model in studying China IPO underpricing, this study identifies the channel through which local government official turnover to political uncertainty on IPO underpricing.

Hedonic social applications have been increasingly popular among health information consumers. However, it remains unclear what motivates consumers to adopt health information in hedonic applications when they have alternative choices of more formal health information sources. Building on the self-determination theory and the affordances lens, this study aims to investigate how different affordances on hedonic social applications affect consumers' basic psychological needs and further influence their intention to adopt health information on such applications.

As TikTok demonstrated great potential in disseminating health information, we developed a model that we analyze using the PLS-SEM technique with data collected from a valid research sample of 384 respondents with health information seeking or encountering experience in TikTok.

The results suggested that health information adoption in hedonic social applications is significantly predicted by the satisfaction of consumers' basic psychological needs, namely autonomy, relatedness and competence. Moreover, the satisfaction of basic psychological needs is positively affected by affordances provided by the hedonic social applications. The hedonic affordances positively influence autonomy satisfaction, while the connective affordances positively affect relatedness satisfaction, and the utilitarian affordances positively support competence satisfaction.

The study indicates that hedonic social applications such as TikTok could be an important channel for consumers to access and adopt health information. The study contributes to the literature by proposing a theoretical model that explains consumers' health information adoption and yields practical implications for designers and service providers of hedonic social applications.

Servitization and research and development (R&D) innovation provide new developmental opportunities for transformation in the construction industry. This study aims to explore the transformative impact of servitization and R&D innovation on the value added of the construction industry, offering new insights into industry transformation and growth.

This study utilizes panel data from Chinese listed construction companies from 2014 to 2022 to empirically investigate the relationship among servitization, R&D innovation and value added in the construction industry. The data analysis is augmented by incorporating text mining techniques to rigorously investigate the interplay among servitization, R&D innovation and the value added within the construction industry.

The research findings indicate that the impact of servitization on value added follows a positive U-shaped relationship, while the influence of R&D innovation on value added exhibits an inverted U-shaped relationship. Additionally, innovation investment plays a negative moderating role in the relationship between servitization and value added.

This study reveals a fresh perspective on how construction companies can leverage servitization as a strategic pathway for transformation and competitive advantage. The research also lays a theoretical groundwork for future innovation investment strategies in the construction industry, emphasizing the need for a balanced approach to innovation investments to maximize value added.

The purpose of this paper is to address the urgent need for transformation and upgrading in the construction industry amid the accelerating industrialization process. The focus is on understanding how value-added for construction enterprises can be achieved through servitization.

Grounded in the perspective of added value of construction enterprises, this paper uses a multicase analysis method, selecting four internationally renowned construction enterprises as the research subjects. The analysis investigates how these case study enterprises transition toward servitization and explores the trends in servitization in construction.

The research results indicate that servitization manifests in two aspects: contractor transition to servitization, and the shift of the construction industry toward integrated delivery. Furthermore, servitization in construction can achieve value-adding through three pathways: increasing product value, creating market demand and providing customized services.

This study contributes by providing insights into the manifestations of servitization and pathways for value-added. It provides a reference for the overall direction and basic strategy of servitization in construction.

Tip leakage vortex flow (TLV) is a common flow phenomenon in the axial-flow hydraulic machinery. High-efficiency simulation of TLV is still not an easy task because of the complex turbulent vortex-cavitation interactions. As an important basis of CFD, turbulence model directly affects the efficient computation of TLV. The purpose of this paper is to evaluate the newly developed MST turbulence model in predicting the TLV flows.

By using the MST turbulence model and the ZGB cavitation model, numerical simulations of the TLV generated by a NACA0009 hydrofoil were performed under the cavitation-free and cavitation conditions, and the results were compared with the available experimental data.

The important features of TLV are well captured by the MST-based simulation scheme, and the problem of under-predicting the cavitating TLV tube is well solved. Turbulent viscosity is reasonably adjusted in the TLV core regions, and the LES-like mode is activated, which is beneficial to obtain more turbulent information on the same URANS grids. The requirements of grid size and time step of the MST model are much lower than that of the LES method, thereby weighing a good balance between the simulation accuracy and computation cost.

The MST turbulence model is suitable for the high-efficiency simulation of the TLV flows, which can lay a good foundation for efficient engineering computations of the cavitating TLV in the axial-flow hydraulic machinery.

This paper aims to solve the problems of low stacking efficiency and long production time in the supercapacitor module assembly process, a stacking system based on monocular vision is proposed, including bracket visual positioning, grasping and stacking, and it is applied in actual production.

To enhance the robustness of the workpiece location method and improve the location accuracy, the improved U-Net network and image processing algorithms are used to segment the collected images. In addition, for the extracted feature points, the objective function that can be globally optimized is obtained by parameterizing the rotation matrix to construct a polynomial equation system and, finally, the equation system is solved to obtain the final pose estimation, which could improve the accuracy of workpiece location.

The result indicates that the proposed method is successfully performed on the manipulator. Besides, this method can well solve the problem of object reflection on the conveyor belt. The Intersection over Union of the image segmentation of the object is 0.9948, and the Pixel Accuracy is 0.9973, which has a high segmentation accuracy for the image. The error range between the method proposed in this paper and the pose estimation is within 2 mm, and the qualified rate of supercapacitor module stacking products is over 99.8%.

This paper proposes a method of accurately extracting feature points by integrating an improved U-Net network and image processing and uses the workpiece positioning algorithm of the optimal solution PnP problem algorithm. The calculation results show that the algorithm improves the positioning accuracy of the workpiece, realizes the assembly of stacked supercapacitor modules and is applied in industrial production.

This paper examines how the level of low-carbon awareness (LCA) affects the remanufacturing strategy in a supply chain with an original equipment manufacturer (OEM) and an independent remanufacturer (IR) competing with each other.

Game theory and operations optimization.

The studies analytically characterize the threshold levels of the LCA in response to which the OEM and the IR will change their remanufacturing strategies from no remanufacturing to partial remanufacturing and then to full remanufacturing. In addition, the studies reveal that as compared with the OEM, the IR has more flexibility in terms of the market entry to remanufacturing with the level of LCA increasing. With the extended studies, it is exhibited that the above findings are robust to a good extent.

It can provide decision support for remanufacturing enterprises.