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This paper aims to explore the impact of Sc element on the microstructure and corrosion properties of Mg-0.5Zn alloy.

Three kinds of Mg-0.5Zn-xSc (x = 0.1, 0.3 and 0.5 Wt.%) alloys were obtained, and the microstructure and corrosion properties were both analyzed.

As the Sc concentration increases, the corrosion resistance of the alloys initially improves and subsequently deteriorates. The trace addition of Sc can effectively reduce the grain size of Mg-Zn-Sc alloys and enhance the density of the corrosion products film. Consequently, an appropriate amount of Sc can reduce the corrosion rate of Mg-0.5Zn alloy.

However, the addition of Sc also introduces the second phase particles in the alloy, leading to galvanic corrosion, which adversely affects the corrosion resistance of Mg-0.5Zn alloy. Therefore, the amount of Sc added should be carefully controlled.

Drawing upon the Conservation of Resources theory and Relational Demography Theory, we examine the crossover of supervisor family experiences to subordinates in the workplace. We posit that supervisor family-to-work enrichment and conflict influence subordinate perceptions of supervisor support for work–family, which, in turn, positively affects subordinate work engagement and job satisfaction and negatively affects subordinate turnover intentions. The effects of supervisor family-to-work enrichment and conflict on perceptions of supervisor support are respectively suggested to be strengthened and weakened by the demographic similarity between the supervisor and the subordinate.

Using a sample of 496 employees nested within 83 supervisors from China, we conducted a multilevel analysis.

Our results indicate that supervisor family-to-work conflict and supervisor family-to-work enrichment have negative and positive effects (respectively) on subordinates’ perceptions of supervisor work–family support, and this effect is moderated by low, rather than high, similarity in the supervisor–subordinate dyad. An overall indirect effect of supervisor family-to-work enrichment and family-to-work conflict on subordinate work engagement, job satisfaction and turnover intentions through the mediator of perceived supervisor work–family support is also confirmed.

From a practical standpoint, our research emphasizes the importance for organizations to support supervisors in achieving work–family balance in order to promote positive employee work-related outcomes.

Our study contributes to work–family literature by unraveling how and when resources may travel through supervisors to affect the generation of new resources (i.e. supervisor support for work–family) and ultimately affect subordinate outcomes in the workplace.

The purpose of this paper is to investigate the accurate monitoring and assessment of steel bar corrosion in concrete based on deep learning multi-sensor information fusion method. The paper addresses the issue of traditional corrosion assessment models relying on sufficient data volume and low evaluation accuracy under small sample conditions.

A multi-sensor integrated corrosion monitoring equipment for reinforced concrete is designed to detect corrosion parameters such as corrosion potential, current, impedance, electromagnetic signal and steel bar stress, as well as environmental parameters such as internal temperature, humidity and chloride ion concentration of concrete. To overcome the small amount of monitoring data and improve the accuracy of evaluation, an improved Siamese neural network based on the attention mechanism and multi-loss fusion function is proposed to establish a corrosion evaluation model suitable for small sample data.

The corrosion assessment model has an accuracy of 98.41%, which is 20% more accurate than traditional models.

Timely maintenance of buildings according to corrosion evaluation results can improve maintenance efficiency and reduce maintenance costs, which is of great significance to ensure structural safety.

The corrosion monitoring equipment for reinforced concrete designed in this paper can realize the whole process of monitoring inside the concrete. The proposed corrosion evaluation model for reinforced concrete based on Siamese neural network has high accuracy and can provide a more accurate assessment model for structural health testing.

Assisted training using upper limb rehabilitation robots is beneficial for flaccid paralysis patients in recovering their functional abilities. In the assisted training mode, the patient’s motor ability is limited by factors such as limb muscle tension, and it is prone for the rehabilitation robot to deviate from the prescribed training trajectory. A sliding mode control method based on a fixed time observer is proposed to address the problem of delayed trajectory tracking response of upper limb rehabilitation robots caused by external disturbances such as patient limbs.

First, aiming at the problem of estimating and compensating for external disturbances in the upper limb rehabilitation robot system, a fixed time observer was designed based on the robot’s dynamic model. Second, the composite sliding mode reaching law combining the smooth function and the power-exponential function is proposed to shorten the convergence time of system states in the startup phase, thereby reducing chattering in the control process and realizing the real-time tracking of the training trajectory by the control system.

The proposed method provides a solution for the trajectory tracking speed of upper limb rehabilitation robot controllers. In the circular trajectory tracking control, compared to the sliding-mode control method combined with the variable-exponential composite reaching law based on the fixed-time observer, the method in this paper reduces the time for the system state to reach the sliding surface by 0.89 s and improves the response speed by 0.66%.

The composite sliding mode approach law based on smooth function and power exponent function can reduce the time it takes for the system state to reach and remain on the sliding surface and improve the trajectory tracking speed of upper limb rehabilitation robots. This controller improves the accuracy of trajectory control and ensures the robustness of auxiliary rehabilitation training.

The purpose of this study is to investigate the influence of rotational speed on the oil film stability of the hydrostatic rotary table having double rectangular oil pads. The oil film stability is evaluated based on the oil film stiffness under constant load condition and the displacement response amplitude of the oil film under disturbance load condition.

The oil film stability theoretical equations of the double rectangular oil cavity are deduced such as oil film stiffness, damping and dynamic equations. A simulation model is developed to analyze the relationship among oil film temperature, oil film pressure fields and oil film stability. The user-defined function programs are used to control the rotational speed, lubricant viscosity and oil film thickness during the simulation. In addition, an experimental rig is built to test the simulation results.

This study shows that oil film stability decreases with increasing rotational speed under constant load and disturbance load. The trend of oil film stability decreased slowly within 30 r/min, and then rapidly. However, since the hydrodynamic pressure effect, the decrease rate of stability is mitigated under constant load and high rotational speeds.

The conclusions can provide a theoretical basis for improving the oil film stability of machines with similar hydrostatic support structure.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2024-0267/

This paper aims to develop an innovative 3D printer based on material extrusion to expand applied material field and shorten the production cycle. The developed 3D printer can fabricate products directly using various powders, including polymers and fillers. In addition, the influence of extrusion on the orientation of thermal conductive filler is also investigated.

To ensure the plasticizing effect and the mixing ability, the printing head is a conical twin-screw extruder, which have a smaller volume. PA12 and h-BN powders were selected for printing as matrix and filler, respectively. The properties of printing products were characterized.

The results show that the new printer can fabricate products directly using polymer powders because of the mixing ability of the twin-screw. The h-BN filler orient in the PA12 matrix and form thermal conduction paths due to the extrusion process, which make the printed samples have an anisotropic thermal conductivity.

The innovative 3D printer provides a method of printing products directly using powders, which can expand material field and shorten the production cycle. For composites, the extrusion process can make fillers orient in the matrix to fabricate products with anisotropic characteristics.

This study aims to explore the influence of construction project manager competencies on team performance, using structural equation modeling (SEM) within the framework of social information processing theory. It investigates the multidimensional nature of project manager competencies and their impact on team processes and outcomes. Additionally, the study examines the mediating role of team processes in the relationship between competencies and team performance.

Drawing on data collected from 483 construction professionals in China, this study uses SEM to analyze the relationships among project manager competencies, team processes and team performance.

The results demonstrate a significant and positive effect of competencies on team performance. Specifically, task-related competencies directly contribute to performance, while people-related competencies enhance leader-member relations, and self-related competencies exert a gradual, cumulative influence. Moreover, the research confirms a three-factor competency structure and elucidates the nuanced mediating roles of team learning, monitoring and climate in the competency-performance relationship, shedding light on how specific competencies affect different stages of team development.

This study contributes to project management literature by applying social information processing theory to elucidate how project managers influence team cognition through competencies. From a practical standpoint, it advocates for a competency-based approach to project manager selection and training, aiming to enhance team performance. Overall, this research advances the understanding of the intricate interplay between project manager competencies and team performance, using SEM and a theoretical perspective rooted in social information processing theory.

In the era of the digital economy, higher demands are placed on versatile talents, and the cultivation of students with innovative and entrepreneurial abilities has become an important issue for the further development of higher education, thus leading to extensive and in-depth research by many scholars. The study summarizes the characteristics and patterns of dual-innovation education at different stages of development, hoping to provide a systematic model for the development of dual-innovation education in China and make up for the shortcomings.

This paper uses Citespace software to visualize and analyze the relevant literature in CNKI and Web of Science databases from a bibliometric perspective, focusing on quantitative analysis in terms of article trends, topic clustering, keyword co-linear networks and topic time evolution, etc., to summarize and sort out the development of innovation and entrepreneurship education research at home and abroad.

The study found that the external characteristics of the literature published in the field of bi-innovation education in China and abroad are slightly different, mainly in that foreign publishers are more closely connected and have formed a more stable ecosystem. In terms of research hotspots, China is still in a critical period of reforming its curriculum and teaching model, and research on the integration of specialization and creative education is in full swing, while foreign countries focus more on the cultivation of students' entrepreneurial awareness and the enhancement of individual effectiveness. In terms of cutting-edge analysis, the main research directions in China are “creative education”, “new engineering”, “integration of industry and education” and “rural revitalization”.

Innovation and entrepreneurship education in China is still in its infancy, and most of the studies lack an overall overview and comparison of foreign studies. Based on the econometric analysis of domestic and foreign literature, this paper proposes a path for domestic innovation and entrepreneurship education reform that can make China's future education reform more effective.

This paper aims to present an unmarked method including entire two-dimensional (2D) and three-dimensional (3D) methods to recover absolute 3D humanoid robot poses from multiview images.

The method consists of two separate steps: estimating the 2D poses in multiview images and recovering the 3D poses from the multiview 2D heatmaps. The 2D one is conducted by High-Resolution Net with Epipolar (HRNet-Epipolar), and the Conditional Random Fields Humanoid Robot Pictorial Structure Model (CRF Robot Model) is proposed to recover 3D poses.

The performance of the algorithm is validated by experiments developed on data sets captured by four RGB cameras in Qualisys system. It illustrates that the algorithm has higher Mean Per Joint Position Error than Direct Linear Transformation and Recursive Pictorial Structure Model algorithms when estimating 14 joints of the humanoid robot.

A new unmarked method is proposed for 3D humanoid robot pose estimation. Experimental results show enhanced absolute accuracy, which holds important theoretical significance and application value for humanoid robot pose estimation and motion performance testing.

This study aims to investigate the mediating role of green employee empowerment (GEE) in the relationship between green discipline management and green involvement with green employee creativity and innovation (GECI) within public universities in Yemen. The research explores how the components of green human resource management (GHRM) influence green creativity and innovation through employee empowerment.

The study utilizes both primary and secondary data. The primary data were gathered through structured questionnaires distributed to 363 employees in public universities in Yemen. The data were analyzed using structural equation modeling (SEM) with AMOS to assess the relationships among the variables.

The findings reveal that green discipline management and green involvement have a significantly positive impact on GEE and GECI. Furthermore, GEE partially mediates this relationship, which demonstrates that empowered employees are more likely to contribute to environmentally sustainable creativity and innovation.

This research helps better understand how GHRM practices, such as discipline management and involvement, can promote green creativity and innovation through employee empowerment. By examining the mediating role of GEE, the study provides valuable insights for academic institutions and organizational leaders seeking to integrate sustainability into human resource (HR) practices and policies.