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The purpose of this study is to model the global dynamic hysteresis properties with an improved Jiles–Atherton (J-A) model through a unified set of parameters.

First, the waveform scaling parameters β, λ_k and λ_c are used to improve the calculation accuracy of hysteresis loops at low magnetic flux density. Second, the Riemann–Liouville (R-L) type fractional derivatives technique is applied to modified static inverse J-A model to compute the dynamic magnetic field considering the skin effect in wideband frequency magnetization conditions.

The proposed model is identified and verified by modeling the hysteresis loops whose maximum magnetic flux densities vary from 0.3 to 1.4 T up to 800 Hz using B30P105 electrical steel. Compared with the conventional J-A model, the global simulation ability of the proposed dynamic model is much improved.

Accurate modeling of the hysteresis properties of electrical steels is essential for analyzing the loss behavior of electrical equipment in finite element analysis (FEA). Nevertheless, the existing inverse Jiles–Atherton (J-A) model can only guarantee the simulation accuracy with higher magnetic flux densities, which cannot guarantee the analysis requirements of considering both low magnetic flux density and high magnetic flux density in FEA. This paper modifies the dynamic J-A model by introducing waveform scaling parameters and the R-L fractional derivative to improve the hysteresis loops’ simulation accuracy from low to high magnetic flux densities with the same set of parameters in a wide frequency range.

Electrification is a promising solution for decarbonising the road freight transport system, but it is challenging to understand its impact on the system. The purpose of this research is to provide a system-level understanding of how electrification impacts the road freight transport system. The goal is to develop a model that illustrates the system and its dynamics, emphasising the importance of understanding these dynamics in order to comprehend the effects of electrification.

The main methodological contribution of the study is the combination of the multi-layer model with system dynamics methodology. A mixed methods approach is used, including group model building, impact analysis, and literature analysis.

The study presents a conceptual multi-layer dynamic model, illustrating the complex causal relationships between variables in the different layers and how electrification impacts the system. It distinguishes between direct and induced impacts, along with potential policy interventions. Moreover, two causal loop diagrams (CLDs) provide practical insights: one explores factors influencing electric truck attractiveness, and the other illustrates the trade-off between battery size and fast charging infrastructure for electric trucks.

The study provides stakeholders, particularly policymakers, with a system-level understanding of the different impacts of electrification and their ripple effects. This understanding is crucial for making strategic decisions and steering the transition towards a sustainable road freight transport system.

While previous research in career studies has highlighted the positive impact of several leadership behaviors on followers’ work and career success, less is known about how the emergent topic of inclusive leadership shapes followers’ task performance. Using an inclusive leadership approach and job demands-resources theory, we developed a novel sequential mediation model in which inclusive leadership indirectly facilitates followers’ performance through self-initiating behavior and work motivation. Specifically, we aimed to investigate whether inclusive leaders encourage followers to show enhanced task performance through strengths use and work engagement.

A representative sample of 278 Dutch employees from diverse organizations was surveyed at three different time points.

The results of structural equation modeling evidenced that inclusive leadership was indirectly related to follower task performance, initially through the utilization of strengths and subsequently through work engagement over time. When leaders exhibited behaviors that were inclusive in nature, they encouraged their followers to make use of their strengths at work. Such leadership actions boosted the work engagement of their followers and led to enhanced task performance.

We develop and test a novel sequential mediation model that explores how inclusive leadership fosters improved task performance among followers by promoting the utilization of strengths and subsequent work engagement. This sheds light on the mechanisms through which inclusive leadership contributes to follower performance, a crucial indicator in shaping sustainable career trajectories.

The circular economy (CE) is a sustainable economic model that has the potential to create new opportunities, reduce environmental impact and enhance social well-being. Ho Chi Minh City (HCMC), the largest city in Vietnam, has experienced rapid economic growth in recent years, but at the cost of the environment and public health. The city could reduce waste, conserve resources and promote sustainable production and consumption by adopting CE principles. Employing qualitative research, including content analysis, we construct a SWOT analysis to assess HCMC's strengths, weaknesses, opportunities and threats in the CE context. The city possesses several strengths, such as a vast potential for a CE and a robust economic foundation. However, it also faces multiple weaknesses, including insufficient infrastructure, inadequate citizen and business awareness and participation, ineffective policy enforcement and a deficiency of standards for recycled products. This chapter will conclude that the CE presents an opportunity for HCMC to reduce its dependence on imported raw materials, increase local value creation and create new jobs in the CE sector.

Wool fiber is accepted as one of the natural and renewable sources and has been used in the apparel and textile industry since ancient times. However, wool fiber has the highest global warming potential value among conventional fibres due to its high land use and high methane gas generation. This study aimed to recycle the wool fabric wastes and also to create a mini eco-collection by using the produced yarns.

This manuscript aimed to evaluate the fabric wastes of a woolen fabric producer company. Fabric wastes were opened with two different opening systems and fiber properties were determined. First, conventional ring yarns were produced in the company’s own spinning mill by mixing the opened fibres with the long fiber wastes of the company. In addition, opening wastes were mixed with different fibres (polyester, long wool waste, and Tencel fibres) between 25% and 70% in the short-staple yarn spinning mill and used in the production of conventional ring and OE-rotor yarns. Most of the yarns contained waste fibres at 50%. Recycled and virgin yarns were used as a weft and warp yarn and a total of 270 woven fabric samples were obtained and fabric properties were examined. Also, a fabric collection was created. A life cycle assessment (LCA) was made for one of the selected yarns.

At the end of the study, it was determined that it was possible to produce yarn and fabric samples from fiber blends containing high waste fiber ratios beyond 50%. All the woven fabric samples produced from conventional ring and OE-rotor yarns gave higher breaking, tearing and stitch slip strength values in the weft and warp direction than limit quality values of the company. In addition, abrasion resistance and WIRA steam stability properties of the fabric samples were also sufficient. Environmental analysis of the recycling of the wastes showed a possible decrease of about 9940034.3 kg CO2e per year in the global warming potential. In addition, fiber raw material expenses reduced yarn production cost about 50% in case of opened fabric waste usage. However, due to insufficient pilling resistance results, it was decided to evaluate the woven fabrics for the product groups such as shawls and blankets, where pilling resistance is less sought.

The original aspects of the article can be summarized under two headings. First, there are limited studies on the evaluation of wool wastes compared to cotton and polyester fibres and the number of samples examined was limited. However, this study was quite comprehensive in terms of opening type (rag and tearing), spinning systems (long and short spinning processes), fiber blends (waste 100% and blends with polyester, long wool waste and Tencel fibres) and yarn counts (coarser and finer). Recycled and virgin yarns were used as a weft and warp yarn and a total of 270 woven fabric samples were obtained using different colour combinations and weave types. All processes from fabric waste to product production were followed and evaluated. Life cycle assessment (LCA) and cost analysis was also done. The second unique aspect is that the problem of a real wool company was handled by taking the waste of the woolen company and a collection was created for the customer group of the company. Production was made under real production conditions. Therefore, this study will provide important findings to the research field about recycling, sustainability etc.

This paper aims to explore how graphene can improve the mechanical and anti-corrosion properties of TiO₂-SiO₂ sol-gel coating. This sol-gel coating has been prepared on aluminum alloy substrate using graphene as both nano-filler and corrosion inhibitor.

To examine the effect of graphene on mechanical properties of sol-gel coating, the abrasion resistance, adhesion strength and scratch resistance of coating have been evaluated. To reveal the effect of graphene on the anti-corrosion property of coating for aluminum alloy, the electrochemical impedance spectroscopy (EIS) has been conducted in 3.5 Wt.% NaCl medium.

Scanning electron microscopy images indicate that graphene nanoplatelets (GNPs) have been homogeneously dispersed into the sol-gel coating matrices (at the contents from 0.1 to 0.5 Wt.%). Mechanical tests of coatings indicate that the graphene content of 0.5 Wt.% provides highest values of adhesion strength (1.48 MPa), scratch resistance (850 N) and abrasion strength (812 L./mil.) for the sol-gel coating. The EIS data show that the higher content of GNPs improve both R₁ (coating) and R₂ (coating/Al interface) resistances. In addition to enhancing the coating barrier performance (graphene acts as nanofiller/nano-reinforcer for coating matrix), other mechanism can be at work to account for the role of the graphene inhibitor in improving the anticorrosive performance at the coating/Al interface.

Application of graphene-based sol-gel coating for protection of aluminum and its alloy is very promising.

The paper follows Jason Cope's (2011) vision of a holistic perspective on the failure-based learning process. By analyzing the research since Cope's first attempt, which is often fragmentary in nature, and providing novel empirical insights, the paper aims to draw a new comprehensive picture of all five phases of entrepreneurial learning and their interplay.

The study features an interpretative phenomenological analysis of in-depth interviews with 18 failed entrepreneurs. Findings are presented and discussed in line with experiential learning theory and Cope's conceptual framework of five interrelated learning timeframes spanning from the descent into failure until re-emergence.

The study reveals different patterns of how entrepreneurs experience failure, ranging from abrupt to gradual descent paths, different management and coping behaviors, and varying learning effects depending on the new professional setting (entrepreneurial vs non-entrepreneurial). Analyzing the entrepreneurs' experiences throughout the process shows different paths and connections between individual phases. Findings indicate that the learning timeframes may overlap, appear in different orders, loop, or (partly) stay absent, indicating that the individual learning process is even more dynamic and heterogeneous than hitherto known.

The paper contributes to the field of entrepreneurial learning from failure, advancing Cope's seminal work on the learning process and -contents by providing novel empirical insights and discussing them in the light of recent scientific findings. Since entrepreneurial learning from failure is a complex and dynamic process, using a holistic lens in the analysis contributes to a better understanding of this phenomenon as an integrated whole.

This study investigates the impact of large-scale teaching in higher education on students’ preparedness for the workforce within the context of evolving labour market demands, the expansion of higher education and the application of high-impact teaching strategies. It synthesizes perspectives on employer work readiness, the challenges and opportunities of large-scale teaching and strategies for fostering a dynamic academia-industry feedback loop. This multifaceted approach ensures the relevance of curricula and graduates’ preparedness while addressing the skills gap through practical recommendations for aligning teaching methodologies with employer expectations.

The research methodically examines the multifaceted challenges and opportunities inherent in large-scale teaching. It focuses on sustaining student engagement, maintaining educational quality, personalizing learning experiences and cultivating essential soft skills in extensive student cohorts.

This study highlights the critical role of transversal skills in work readiness. It also uncovers that despite its challenges, large-scale teaching presents unique opportunities. The diversity of large student groups mirrors modern workplace complexities, and technological tools aid in personalizing learning experiences. Approaches like peer networking, innovative teaching methods, real-world simulations and collaborative resource utilization enrich education. The importance of experiential learning for augmenting large-scale teaching in honing soft skills is emphasized.

This manuscript contributes to the discourse on large-scale teaching, aligning it with employer expectations and the dynamic requirements of the job market. It offers a nuanced perspective on the challenges and opportunities this educational approach presents, providing insights for crafting engaging and effective learning experiences in large cohorts. The study uniquely integrates experiential learning, co-creation in education and industry-academia feedback loops, underscoring their importance in enhancing student work readiness in large-scale teaching.

This paper aims to select an appropriate contact force model and apply it to the interaction model between the balls and the cage in the rolling bearings to describe the elastic–plastic collision phenomena between the two.

Taking the ball–disk collision mode as an example, several main contact force models were compared and analyzed through simulation and experiment. In addition, based on the consideration of yield strength of materials and initial collision velocity, a variable recovery coefficient model was proposed, and its validity and accuracy were verified by the ball–disk collision experiments. Then, respectively, the Flores model and the Hertz model were applied to the interaction between the balls and the cage, and the dynamics simulation results were compared.

The results indicate that the Flores model has good regression of recovery coefficient, indicating good applicability for both elastic and elastic–plastic contacts and can be applied to the contact collision situations of various materials. Under certain working conditions, there are significant differences in the dynamics results of rolling bearings simulated using the Flores model and Hertz model, respectively.

This paper applies the Flores model with variable recovery coefficients to the dynamics simulation analysis of ball bearings to solve the elastic–plastic collision problem between the rolling elements and the cage that cannot be reasonably handled by the Hertz model.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0138/