Search results

This study aims to investigate the effects of process input parameters (welding current, welding time, electrode pressure and holding time) on the output responses (nugget diameter, peak load and indentation) that control the mechanical properties and quality of the joints in dissimilar resistance spot welding (RSW) for the third generation of advanced high-strength steel (AHSS) quenching and partitioning (Q&P980) and (SPFC780Y) high-strength steel spot welds.

Design of experiment approach with two level factors and center points was adopted. Destructive peel and shear tensile strengths were used to measure the responses. The significant factors were determined using analysis of variance implemented by Minitab 18 software. Finally, multiresponse optimization was carried out using the desirability function analysis method.

Holding time was the most significant factor influencing nugget diameter, whereas welding current had the greatest impact on peak load and indentation. Multiresponse optimization revealed that the optimal settings were a welding current of 12.5 KA, welding time of 18 cycles, electrode pressure of 420 Kgf and holding time of 10 cycles. These settings produced a nugget diameter of 8.0 mm, a peak load of 35.15 KN and an indentation of 22.5%, with a composite desirability function of 0.764.

This study provides an effective approach for multiple response optimization to the mechanical behavior of RSW joints, even though there have been few studies on the third generation of AHSS joints and none on the dissimilar joints of the materials used in this study.

Based on the job-demands resources (JD-R) model and the self-determination theory (SDT), this paper aims to explore team empowerment (TEMP) as a mediating mechanism through which team climate (TC) marked by innovativeness, cohesion and trust and knowledge management (KM) in teams.

Using a convenience sampling method, data were gathered from 246 employees of Tunisian knowledge-intensive firms (KIFs) and involved within 69 R&D teams. The partial least square-structural equation modeling approach through SMART PLS 3.2 software was used to evaluate the constructs’ psychometric properties and hypotheses. The mediating effect in the model was evaluated through the non-parametric bootstrapping method.

Results highlight that TC marked by innovativeness, cohesion and trust represents a key team contextual antecedent promoting TEMP and KM in teams. In turn, TEMP, as a critical intrinsic task motivation factor, is revealed as a driver of KM practices. This research demonstrates that TEMP partially mediates the relationship between TC and KM in teams.

This study pioneers the examination of TEMP’s mediating role between a TC marked by innovativeness, trust and cohesion and KM. By applying insights from the JD-R model and SDT to team-level dynamics, it uniquely positions TEMP as an intrinsic motivational factor explaining the mechanism through which the contextual resources provided by a supportive TC promote KM practices. It provides practical insights for KIFs’ managers through highlighting how intrinsically motivated teams of knowledge workers, empowered by a cohesive, innovative and trust-based TC, can effectively navigate the challenges inherent in knowledge-intensive teamwork, leading to enhanced KM practices.

This study uses a comprehensive literature review and analysis of recent research, policy documents and program evaluations related to Supplemental Nutrition Assistance Program Education (SNAP-Ed) and policy, systems and environmental (PSE) strategies. Key sources include peer-reviewed articles, the 2025 SNAP-Ed Plan Guidance and case studies of successful PSE interventions. The Social-Ecological Model serves as a framework to organize and analyze the multilevel impacts of PSE interventions. The method involves identifying relevant information, synthesizing key themes and patterns and critically examining the potential impact of PSE strategies on nutrition security and health equity.

This paper examines the evolution of the SNAP-Ed from direct nutrition education to a comprehensive approach integrating PSE change strategies. It aims to analyze the rationale, implementation and potential impact of PSE approaches in SNAP-Ed on nutrition security and health equity in the USA. The study explores how these strategies address social determinants of health, promote sustainable population-level changes in nutrition environments, and their capacity to reduce health disparities in low-income communities. It seeks to identify challenges, opportunities and future research directions in implementing PSE strategies within SNAP-Ed.

The review reveals that PSE strategies in SNAP-Ed show promise in creating sustainable, population-level changes in nutrition environments and health outcomes. Successful examples, such as healthy corner store initiatives and workplace wellness programs, demonstrate the potential of PSE approaches to improve access to healthy food options and physical activity opportunities. The integration of PSE strategies has enhanced SNAP-Ed’s capacity to address social determinants of health and promote health equity. However, challenges including resource constraints, political opposition and the need for cross-sector collaboration persist. The effectiveness of PSE interventions relies heavily on community engagement, partnerships and supportive policies.

The findings underscore the importance of adopting comprehensive, multilevel approaches in nutrition education and obesity prevention programs. For SNAP-Ed implementers, this implies a need to develop expertise in PSE strategies, foster cross-sector partnerships and engage communities in intervention design and implementation. Policymakers should consider increasing support and resources for PSE approaches within SNAP-Ed and similar programs. Public health practitioners can use these insights to design more effective, equitable interventions that address root causes of nutrition insecurity. The study also highlights the need for improved evaluation methods to assess the long-term impact of PSE strategies on population health outcomes.

This study highlights the importance of addressing social determinants of health, such as poverty and access to healthy food options, to promote equitable health outcomes. It underscores the potential of community-driven, multilevel interventions in building a more just and equitable food system accessible to all.

This paper provides a comprehensive analysis of the shift toward PSE strategies in SNAP-Ed, offering valuable insights into the program’s evolution and its potential to address complex public health challenges. By examining both successes and challenges, it contributes to the growing body of evidence on the effectiveness of multilevel interventions in promoting nutrition security and health equity. The study’s emphasis on the role of community engagement and partnerships in PSE implementation offers practical guidance for program planners and policymakers.

The purpose of this paper is to conduct a thorough study of the current research status and trends of Artificial Intelligence-Generated Content (AIGC), which is thriving and exerting significant influences on society, the economy and technology. This study will encompass both the ample opportunities and the array of emerging risks and challenges associated with AIGC. Furthermore, this paper seeks to propose practical optimization strategies to facilitate its continued development.

A total of 12,702 documents in Scopus, CNKI and Altmetric.com databases are analyzed in this paper. The visualization tools of CiteSpace and Netdraw are used to systematically analyze AIGC from macro, meso and micro perspectives based on bibliometric indicators. The analysis is combined with altmetrics indicators to identify hotspots in AIGC-related research and predict future development trends. Finally, substantive optimization suggestions for the development of AIGC are put forward.

Research has found that firstly, both domestic and international research in the field of AIGC is actively catching up with the pace of the era. Institutions and authors recognize the indispensability of collaboration, leading to the emergence of interdisciplinary cooperation trends. Secondly, at the thematic research level, both domestic and international studies cover the overall trends of AIGC, including technology, applications, challenges and coping strategies. However, international scholars tend to focus more on technological breakthroughs, while domestic researchers emphasize the formulation of national laws and regulations. Finally, through the analysis of hotspots and trends, it is predicted that future research will focus more on addressing the legal issues regarding the originality of AIGC, enhancing its interactivity, optimizing its applications, emphasizing ethical considerations and efficiently addressing major social issues such as pandemics using AIGC technology. Corresponding optimization strategies are proposed to ensure the development of AIGC is consistent with global consensus and values, creating a beneficial environment for its sustainable development.

Firstly, this paper integrates data from three databases and uses multiple software tools to conduct a comparative analysis of the research trends in AIGC from both domestic and international perspectives. Secondly, this paper not only analyzes the academic influence of AIGC-related research through bibliometric indicators but also combines altmetrics indicators to explore the public’s attitude toward AIGC. This method systematically reveals the overall development trends, leading institutions and researchers, thematic research areas, hotspot evolution and future development trends of AIGC-related research, providing theoretical references for subsequent scholars in AIGC research. Additionally, this paper helps governments, institutions and organizations to precisely and wisely formulate policies and investments, as well as to effectively comprehend the development trends of AIGC and promote the advancement of AIGC technology and applications.

This chapter describes the MASK concept model as a hierarchical taxonomy and an ontology developed for knowledge-based systems. The authors differentiate concepts from terms and explain the value of a concept map. Everyday examples of concept models are described. A step-by-step methodology for constructing a concept model is provided.

The purpose of this study is to assess the performance of fuel blends containing ethanol and gasoline in spark ignition engines. The aim is to explore alternative fuels that can enhance performance while minimizing or eliminating adverse environmental impacts, particularly in the context of limited fossil fuel availability and the need for sustainable alternatives.

The authors used the Ricardo Wave software to evaluate the performance of fuel blends with varying ethanol content (represented as E0, E10, E25, E40, E55, E70, E85 and E100) in comparison to gasoline. The assessment involved different composition percentages and was conducted at various engine speeds (1,500, 3,000, 4,500 and 6,000 rpm). This methodology aims to provide a comprehensive understanding of how different ethanol-gasoline blends perform under different conditions.

The study found that, across all fuel blends, the highest brake power (BP) and the highest brake-specific fuel consumption (BSFC) were observed at 6,000 rpm. Additionally, it was noted that the presence of ethanol in gasoline fuel blends has the potential to increase both the BP and BSFC. These findings suggest that ethanol can positively impact the performance of spark-ignition engines, highlighting its potential as an alternative fuel.

This research contributes to the ongoing efforts in the automotive industry to find sustainable alternative fuels. The use of Ricardo Wave software for performance assessment and the comprehensive exploration of various ethanol-gasoline blends at different engine speeds add to the originality of the study. The emphasis on the potential of ethanol to enhance engine performance provides valuable insights for motor vehicle manufacturers and researchers working on alternative fuel solutions.

The research focused on analysing a unique type of heat exchanger that uses swirling air flow over heated tubes. This heat exchanger includes a round baffle plate with holes and opposite-oriented trapezoidal air deflectors attached at different angles. The deflectors are spaced at various distances, and the tubes are arranged in a circular pattern while maintaining a constant heat flux.

This setup is housed inside a circular duct with airflow in the longitudinal direction. The study examined the impact of different inclination angles and pitch ratios on the performance of the heat exchanger within a specific range of Reynolds numbers.

The findings revealed that the angle of inclination significantly affected the flow velocity, with higher angles resulting in increased velocity. The heat transfer performance was best at lower inclination angles and pitch ratios. Flow resistance decreased with increasing angle of inclination and pitch ratio.

The average thermal enhancement factor decreased with higher inclination angles, with the maximum value observed as 0.94 at a pitch ratio of 1 at an angle of 30°.

The purpose of this paper is to verify the performance and function of the scale-up prototypes by predicting the material and energy consumption on the basis of dimension-reduced prototypes. Additive manufacturing (AM) costs determine carbon emissions in total life cycle, among which material and energy consumption are major components. Predicting material and energy consumption is fundamental to reducing costs.

This paper presents a material and energy co-optimization method for AM via multiple layers prediction (MLP). Material and energy consumption are predicted to reduce the AM costs. In particular, scalable, complex curved surface component is used to improve forecasting efficiency. Subsequently, the back pressure distribution is obtained by scale-up specimens, which can lay the foundation for the ergonomic conceptual design.

Taking evolutionary ergonomic product as an example, the relative gravity direction of backrest is calculated. The material and energy consumption are predicted with low deviation. Physical experiments were carried out to validate information. Digital and physical tests have revealed that material and energy co-optimization improves manufacturing efficiency.

The innovatively proposed MLP method predicts material and energy consumption of scale-up prototypes to reduce the costs. It is propitious to improve the carbon emission efficiency in life cycle of AM. The originality may be widely adopted alongside increasing environmental awareness.

This study aims to examine the critical success factors of global virtual teams (GVTs) working in the information technology industry in the UK. It also focuses on the ranking of the success factors and shedding light on the perceived cause-and-effect relationship between the factors.

Data was collected from executives working in the IT industry in the UK. Fuzzy DEMATEL analysis was incorporated to generate results.

The findings suggest that overcoming perceived and temporal distance, empowerment, integrative approach, members’ competencies and cultural intelligence are considered to be causal variables. In contrast, effective team leadership, trust, commitment to task and communication are regarded as an effect. In terms of the degree of importance, communication was ranked in first place. Effective team leadership and overcoming perceived and temporal distance were found to be in second and third place. Empowerment was found to be in the last position in terms of the degree of importance.

To the best of the authors’ knowledge, this paper is among the first research on GVTs in the UK IT industry context. Also, using the Fuzzy DEMATEL approach differentiates it from the previous studies. The perceived cause-and-effect analysis of the current study using the experts’ opinions has a direct policy-making application as well, which makes the finding easy to use by practitioners and policymakers at the same time.