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This paper endeavors to create a predictive model for the energy consumption associated with the multi-material fused deposition modeling (FDM) printing process.

An online measurement system for monitoring power and temperature has been integrated into the dual-extruder FDM printer. This system enables a comprehensive study of energy consumption during the dual-material FDM printing process, achieved by breaking down the entire dual-material printing procedure into distinct operational modes. Concurrently, the analysis of the G-code related to the dual-material FDM printing process is carried out.

This work involves an investigation of the execution instructions that delineate the tooling plan for FDM. We measure and simulate the nozzle temperature distributions with varying filament materials. In our work, we capture intricate details of energy consumption accurately, enabling us to predict fluctuations in power demand across different operational phases of multi-material FDM 3D printing processes.

This work establishes a model for quantifying the energy consumption of the dual-material FDM printing process. This model carries significant implications for enhancing the design of 3D printers and advancing their sustainability in mobile manufacturing endeavors.

This study aims to investigate the corrosion behavior of cold-rolled Fe₃₅Ni₂₀C_r12Mn_(28-x)Al_x high-entropy alloys (HEAs) using the potentiodynamic polarization technique in 1 M H₂SO₄ acid. Additionally, the influence of molybdenum (Mo) additions as inhibitors and the effect of variations in cold rolling reduction ratios and Al content on corrosion behavior are examined.

Two cold rolling reduction ratios, namely, 50% (R50) and 90% (R90), were examined for the cold-rolled Fe₃₅Ni₂₀Cr₁₂Mn₂₈Al₅ (Al₅) and Fe₃₅Ni₂₀Cr₁₂Mn₂₃Al₁₀ (Al₁₀) HEAs. Mo inhibitor additions were introduced at varying concentrations of 0.3, 0.6 and 0.9 Wt.%. The potentiodynamic polarization technique was used to evaluate the corrosion rates (CRs) under different experimental conditions.

The results indicate that the addition of 0.3 Wt.% Mo in 1 M H₂SO₄ yielded the lowest CR for both R50 and R90, irrespective of the Al content in the HEAs. However, the highest CR was observed at 0.6 Wt.% Mo addition. Furthermore, increasing the concentration of Al resulted in a corresponding rise in the CR. Comparatively, the CR decreased significantly when the cold rolling reduction ratio increased from R50 to R90.

This research provides valuable insights into the intricate relationship between Mo inhibitors, cold rolling reduction ratio, Al content and the resulting corrosion behavior of Fe₃₅Ni₂₀Cr₁₂Mn_(28-x)Al_x HEAs. The comprehensive analysis of corroded HEAs, including surface morphology, compositions and elemental distribution mapping, contributes to the understanding of the corrosion mechanisms and offers potential strategies for enhancing the corrosion behavior of HEAs.

This study aims to evaluate the drivers influencing the integration of distributed ledger technologies (DLTs) in the Nigerian construction industry to provide a comprehensive analysis of the factors that shape the adoption and utilization of this transformative technology within the sector.

This objective was achieved through a quantitative research approach, utilizing a structured questionnaire to systematically gather data from various stakeholders in the Nigerian construction sector. Data obtained were analyzed using descriptive statistics, alongside inferential statistical techniques like the Kruskal-Wallis H-test, the Shapiro-Wilk test and exploratory factor analysis.

The most highly ranked drivers for DLT within the construction industry are security and fraud resistance, traceability and transparency, government support, compliance and reporting and trust building. Further analysis unveiled five distinct factors of application areas, namely: technological and operational drivers, economic and financial drivers, regulatory and government drivers, collaborative and stakeholder drivers and environmental and sustainability drivers.

The practical implications emphasize the need for construction industry stakeholders to focus on security, transparency and trust-building when considering DLT adoption. This study also offers valuable insights for investors and technology providers seeking opportunities in the Nigerian construction sector.

This study sheds light on the factors most critical for DLT adoption in the Nigerian construction sector. Unlike previous research, this study pinpoints security and fraud resistance, along with traceability and transparency, as the most influential drivers. This highlights the Nigerian construction industry’s particular vulnerability to fraud and its emphasis on clear audit trails.

Unethical pro-organizational behavior (UPB) harms organizations’ long-term development; hence, all sectors of society view it as highly concerning. Optimizing leadership and curbing this behavior is a key managerial challenge. This study takes the relationship between temporal leadership and UPB as its object and examines the direct and indirect paths of temporal leadership’s influence on UPB based on the conservation of resources theory. It further dissects the mediating mechanism of emotional exhaustion and the regulating mechanism of job complexity and constructs the mechanism through which temporal leadership affects UPB.

Data gathered from a sample of 380 employees in 24 provinces and cities were employed for empirical testing using validated factor analysis, hierarchical regression analysis, and a bootstrap method.

The results show that temporal leadership inhibits UPB, while emotional exhaustion partially mediates the relationship between temporal leadership and UPB. That is, temporal leadership inhibits pro-organizational unethical behavior by alleviating emotional exhaustion. In addition, job complexity negatively moderates the relationship between emotional exhaustion and UPB and positively moderates the mediating role of emotional exhaustion between temporal leadership and UPB.

First, although the data used in the study were collected at two different times, they were obtained through self-assessment; therefore, the subjective component and the potential problem of common method bias is evident. Second, the study’s sample size and types of respondents are limited.

1. This study found that temporal leadership can inhibit UPB by reducing employee emotional exhaustion. Therefore, organizations should place greater emphasis on the time factor. 2. In terms of emotional factors, organizations should actively focus on the impact of emotional exhaustion on employees' UPBs. 3. In management practice, managers should adjust their leadership modeling behaviors according to the different degrees of job complexity to replace UPBs with conscious and rational behaviors.

The study reveals how temporal leadership affects UPB and provides a theoretical basis for organizations to mitigate employees' UPB by optimizing their leadership style.

Current research on temporal leadership primarily focuses on the positive predictive effects on individual behaviors and attitudes (Zhang and Ling, 2016), but neglects its effects on negative behaviors. This study’s results complement research on the relationship between temporal leadership and employees' negative behaviors and responds to the call by Zhang and Ling (2015) to conduct research related to temporal leadership in China. On the other hand, current research on employees’ UPB largely focuses on its causative factors, while less research has been conducted on the disincentives for UPB, which to some extent limits systematic and sound research on UPB.

In response to the challenge of reduced efficiency or failure of robot motion planning algorithms when faced with end-effector constraints, this study aims to propose a new constraint method to improve the performance of the sampling-based planner.

In this work, a constraint method (TC method) based on the idea of cross-sampling is proposed. This method uses the tangent space in the workspace to approximate the constrained manifold pattern and projects the entire sampling process into the workspace for constraint correction. This method avoids the need for extensive computational work involving multiple iterations of the Jacobi inverse matrix in the configuration space and retains the sampling properties of the sampling-based algorithm.

Simulation results demonstrate that the performance of the planner when using the TC method under the end-effector constraint surpasses that of other methods. Physical experiments further confirm that the TC-Planner does not cause excessive constraint errors that might lead to task failure. Moreover, field tests conducted on robots underscore the effectiveness of the TC-Planner, and its excellent performance, thereby advancing the autonomy of robots in power-line connection tasks.

This paper proposes a new constraint method combined with the rapid-exploring random trees algorithm to generate collision-free trajectories that satisfy the constraints for a high-dimensional robotic system under end-effector constraints. In a series of simulation and experimental tests, the planner using the TC method under end-effector constraints efficiently performs. Tests on a power distribution live-line operation robot also show that the TC method can greatly aid the robot in completing operation tasks with end-effector constraints. This helps robots to perform tasks with complex end-effector constraints such as grinding and welding more efficiently and autonomously.

This article delves into the antecedents of business performance. The main aim of this study is to analyze the effect of knowledge transformation on business performance in firms in the tourism industry and how cognitive and structural social capital heterogeneously moderate this relationship.

The empirical study was conducted on a sample of 300 firms from the tourism industry in Arequipa-Perú. The analysis was performed by means of partial least squares structural equation modeling, using the Smart PLS software.

Our findings show that knowledge transformation is key factor for increasing business performance. The results also highlight the significance of interorganizational relationships in this effect and the importance of analyzing each dimension of social capital separately. Thus, it is observed that cognitive social capital enhances the relationship between knowledge transformation and business performance, while (Sari and Indriani, 2023) structural social capital hinders it.

The findings assist practitioners in developing a shared culture, values and goals with their contacts to improve business performance. Furthermore, firms should establish bridging ties with external agents to avoid be stuck in excessively dense networks. Relationships with institutions can act as a bridging agent.

This paper analyses the unresolved question of how knowledge transformation affects the business performance of companies in the tourism sector as well as how different dimensions of social capital influence in this relationship. Addressing these two critical, but as yet unresolved questions, this study draws on absorptive capacity and social capital theories as an overarching framework to present a conceptual model that integrates both theories in order to analyze the effect of knowledge transformation on business performance in tourism firms and the role of structural and cognitive capital on this relationship.

The purpose of this research is to explore the transformative impact of AI-augmented tools on design pedagogy. It aims to understand how artificial intelligence technologies are being integrated into educational settings, particularly in creative design courses, and to assess the potential advancements these tools can bring to the field.

The research adopts a case-study approach, examining three distinct courses within a creative technology curriculum. This methodology involves an in-depth investigation of the role and impact of AI in each course, focusing on how these technologies are incorporated into different creative disciplines such as production design, fine arts, and digital artistry.

The research findings highlight that the integration of AI with creative disciplines is not just a passing trend but signals the onset of a new era in technological empowerment in creative education. This amalgamation is found to potentially redefine the boundaries of creative education, enhancing various aspects of the learning process. However, the study also emphasizes the irreplaceable value of human mentorship in cultivating creativity and advancing analytical thinking.

The limitations of this research might include the scope of the case studies, which are limited to three courses in a specific curriculum. This limitation could affect the generalizability of the findings. The implications of this research are significant for educational institutions, as it suggests the need for a balanced interaction between AI's computational abilities and the intrinsic qualities of human creativity, ensuring that the core essence of artistry is preserved in the age of AI.

The originality of this paper lies in its specific focus on the intersection of AI and creative education, a relatively unexplored area in design pedagogy. The value of this research is in its contribution to understanding how AI can be harmoniously integrated with traditional creative teaching methods. It offers insights for educational institutions preparing for this technological transformation, highlighting the importance of maintaining a balance between technological advancements and humanistic aspects of creative education.

This paper examines the dynamic interplay between Circular Economy (CE) and Supply Chain (SC). Further, this paper develops a framework indicating the transition from conventional SC to SC 4.0. As it addresses the separate bodies of literature on CE and SC 4.0, the study attempts to bridge the gap by examining barriers to SC 4.0 adoption in CE.

The article integrates bibliometric analysis with Total Interpretive Structural Modeling (TISM) and MICMAC analysis, thereby enriching the methodological rigour in investigating the barriers to SC 4.0 adoption within the CE context.

The paper provides insights into research trends, influential scholars, journals and prominent institutions through bibliometric analysis. Also, the findings identify four broad areas of driving, autonomous, linkage and dependent barriers to facilitate a comprehensive understanding of their impact and interdependencies.

The findings imply that effective policy interventions, enhanced management practices, and the adoption of technological innovations are essential for overcoming barriers to SC 4.0. The research recommends that stakeholders focus on fostering collaborative networks, building competencies in line with CE requirements, and leveraging big data for strategic supply chain decision-making.

This work contributes to the advancement of the circular digital supply field by consolidating research streams, uncovering innovation prospects, and shaping a well-informed research agenda. The distinct contribution lies in its categorization of these barriers into driving, autonomous, linkage, and dependent barriers, offering a novel perspective on the structural dynamics impeding the integration of SC 4.0 in CE.

The shift toward a circular economy (CE) represents a collaborative endeavor necessitating the presence of efficient frameworks, conducive contexts and a common comprehension. This research serves as a pivotal stride towards this goal, presenting an exclusive prospect for the investigation and fusion of these frameworks, with particular emphasis on the Quintuple Helix Model (5HM), into a unified theoretical framework that underscores the core principles of the CE. This study is centered on three pivotal questions aimed at decoding the CE transition in specific regional settings.

Adopting an abductive approach firmly anchored in a two-stage qualitative process, this study specifically merges the foundational principles from institutional theory, entrepreneurship literature and CE frameworks to provide insights into the dynamics of circular ecosystems, with a specific focus on the Huelva region in Spain.

The findings demonstrate significant potential in the CE, ranging from the integration of product and service systems to innovations in eco-industrial practices. Yet, a notable deficiency exists: the absence of institutional entrepreneurs, highlighting the essential role that universities can play. As recognized centers of innovation, universities are suggested to be key contributors to the transformation toward a CE, aligning with their societal and economic responsibilities.

This study highlights the importance of managing relationships with entities like SMEs and policymakers or academia for effective CE adoption. Policymakers can refine strategies based on the research’s insights, while the impact of university-driven circular ecosystems on sustainable societies is another crucial area for research.

The sustainability models cited in CE literature may not be comprehensive enough to prevent problem shifting, and it can be argued that they lack a sound theoretical and conceptual basis. Furthermore, the connections between sustainability objectives and the three levels of the CE operating system remain vague. Additionally, there is insufficient information on how regions foster the involvement of the environment in fivefold helix cooperation and how this impacts the CE.