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This paper presents a new numerical approach for shape optimization of resistors with complex geometry. The aim of this method is to develop a systematic modification of resistor design in combination with the computation of the electric field, in order to optimize some chosen properties like homogenization of the power dissipation on the resistor surface.

The use of insects as food is a proposed solution for the increased demand for food worldwide, but it lacks acceptance because of restrictive emotional factors. This article aims to understand better customers' emotions’ role in considering and consuming insect-based food.

To assess their acceptance, an experiment was developed with 38 participants living in Portugal to identify how people feel when consuming processed insect bars compared to cereal bars (of equal flavour). A video was recorded “before”, “during” and “after” the consumption of such foods, and the triggered emotions and affective states were identified using the Facial Action Coding System (FACS) and the circumplex model of affect, respectively. After consumption, the Self-Assessment Manikin (SAM) was asked to be completed.

It was observed that the valence and arousal of the emotions and affective states triggered during consumption were higher in the insect bar than in the cereal bar. Its consumption resulted in surprise and a positive evaluation. Processed insect-based foods may result in a potentially increased acceptance of this new food alternative in the market.

Prior studies briefly identified disgust as a primary emotion activated by insect-based food. The current research deeply studied emotional responses to insect-based processed foods in the Western world using the dimensional emotional models. This study offers arguments for the insect-based food industry to invest in processed food justified by its potential for acceptance. In addition, it motivates further research focused on other insect-based products (e.g. non-processed ones).

Studies in psychology have long revealed that making personal choice involves multiple motivational consequences. It has only been recent, however, that the literature on neuroscience started to examine the neural underpinnings of personal choice and motivation. This chapter reviews this sparse, but emergent, body of neuroscientific literature to address possible neural correlates underlying personal choice. By conducting the review, we encourage future systematic research programs that address this topic under the new realm of “autonomy neuroscience.” The chapter especially focused on the following motivational aspects: (i) personal choice is rewarding, (ii) personal choice shapes preference, (iii) personal choice changes the perception of outcomes, and (iv) personal choice facilitates motivation and performance. The reviewed work highlighted different aspects of personal choice, but indicated some overlapping brain areas – the striatum and the ventromedial prefrontal cortex (vmPFC) – which may play a critical role in motivational processes elicited by personal choice.

Blockchain is an innovative and emerging technology that allows the structuring of open data in a secure and decentralized manner. This technology, coupled with artificial intelligence (AI), is a driver of digital transformation that permeates all sectors of the economy. In this context, it becomes relevant to understand the applicability of AI and blockchain in education, more specifically their use in higher education. Thus, the following problem arises: how can blockchain technology and AI be applied to higher education? To answer this problem, the following objective was set: to map by means of a scoping review how AI and blockchain can be applied in education as a technology for higher education. To this end, a bibliometric search was conducted in the Web of Science (WoS) and Scopus databases, adopting the PRiSM methodology for scoping review. The results showed that blockchain and AI can be used in higher education through a smart contract that serves to motivate teamwork and student involvement in activities performed in the school context and also to increase machine reliability by establishing a chain of information. It is also concluded that these technologies will help form a generation ready to work in a more collaborative way, adopting attitudes of sustainability in its local and global context for solving complex problems of everyday life in the 21st century.

This paper proposes a method for multi‐terminal resistor optimal design based on a stochastic optimization algorithm coupled with a high accuracy boundary element method numerical analysis module using spline boundary elements. The aim of the optimization process is to find out the optimal shape of the resistor so that the values of the partial resistances between its terminals can be globally reduced. In the first part of the paper, a short introduction to the boundary element method formulation using spline interpolation of the boundary unknowns is performed. Then, the genetic algorithm optimization method is briefly described, emphasising the numerical implementation particularities related to the actual application. In the second part of the paper, three numerical examples are proposed and the final conclusions are outlined.

Blockchain technology was once only associated with the financial industry, but it is now being used in a variety of industries, including education. Researchers all over the world take a keen interest in studying the various applications of blockchain technology for the last 4–5 years. The current study is a review of previously published studies on blockchain technology’s applicability in the sector of education. The systematic review was used to conduct the qualitative analysis using the PRISMA Framework (Preferred Reporting Items for Systematic Review and Meta-Analysis). For this comprehensive literature review analysis, 99 publications were chosen in the final stage of selection. Bibliometric analysis is employed to analyse the collected data. Authorship analysis, co-authorship analysis, keyword co-occurrences, and important applications of blockchain in education are the primary parts in which the literature’s findings are organised. Important directions are given for researchers and academicians involved in blockchain-related research who may use the bibliometric analysis of the present study as a reference.

Industry 4.0 with artificial intelligence (AI), the Internet of Things, and automation are giving way to Industry 5.0 which places emphasis on workers' well-being, people, and society. The new era accentuates interaction between humans and smart machines to drive prosperity and induce sustainable contribution of industry to society. It must build a resilient economy to cope with future uncertainties or external shocks. Moreover, the sustainability effort of companies demanded by consumers, employees, shareholders, governments, and civil society requires sustainability transformation of business strategies. Applying sustainability principles in product design implies the consideration of a product's entire life cycle. Technologies accelerate sustainable production and support using natural resources efficiently taking into consideration planetary boundaries. This condition also makes for a novel perception of products, including financial products. Under the current circumstances of a volatile, uncertain, complex, and ambiguous environment, the focus on consumers and recognition of their dominance play a pivotal role in business models to maintain customer relationships. Thus, the digital, sustainable, human-centric industry is emerging. This chapter deals with digital products to enable twin transition and accomplish a sustainable business strategy simultaneously. It examines the reciprocal reinforcement of sustainability and digitalization and discusses the impact of digital sustainability on products. In this sense, this chapter also outlines the business contribution to sustainable development through digitalization. Finally, a holistic model for a hypothetical financial remittance product is offered to demonstrate how a digital product can contribute to sustainable development.

In recent years, scholarly focus has shifted towards exploring the applications of disruptive technologies in professional services. These studies emphasise the need for further research in this domain. This research aims to comprehensively review the existing literature on the uses of blockchain, artificial intelligence (AI) and machine learning (ML) algorithms in professional services such as higher education, healthcare, financial securities firms and smart energy consulting. The rapid innovation and advancement in technology have led to substantial improvements in work efficiency and productivity. As industries transition towards sustainability and digitalisation, the role of energy-efficient systems becomes important in shaping smart factory designs and in further implementations. The uses of AI and other disruptive technologies for business operations not only boost production efficiency but also enhance customer satisfaction. Central to this transformation are strategies like deep learning and data/text mining, which facilitate the shift from conventional manufacturing practices to smart manufacturing. Apart from smart energy systems, the fields of higher education, healthcare and financial securities are witnessing a surge in the applications of AI, ML algorithms and blockchain technology and their contributions in emerging service economy. This study undertakes a comprehensive investigation into various factors associated with the application of disruptive technologies, evaluating their impact on the operational efficiency of professional service firms (PSFs). Through this research, we aim to identify gaps in the current literature and will suggest the directions for future research.

This paper reviews the synergy of Industry 4.0 and additive manufacturing (AM) and discusses the integration of data-driven manufacturing systems and product service systems as a key component of the Industry 4.0 revolution. This paper aims to highlight the potential effects of Industry 4.0 on AM via tools such as digitalisation, data transfer, tagging technology, information in Industry 4.0 and intelligent features.

In successive phases of industrialisation, there has been a rise in the use of, and dependence on, data in manufacturing. In this review of Industry 4.0 and AM, the five pillars of success that could see the Internet of Things (IoT), artificial intelligence, robotics and materials science enabling new levels of interactivity and interdependence between suppliers, producers and users are discussed. The unique effects of AM capabilities, in particular mass customisation and light-weighting, combined with the integration of data and IoT in Industry 4.0, are studied for their potential to support higher efficiencies, greater utility and more ecologically friendly production. This research also illustrates how the digitalisation of manufacturing for Industry 4.0, through the use of IoT and AM, enables new business models and production practices.

The discussion illustrates the potential of combining IoT and AM to provide an escape from the constraints and limitations of conventional mass production whilst achieving economic and ecological savings. It should also be noted that this extends to the agile design and fabrication of increasingly complex parts enabled by simulations of complex production processes and operating systems. This paper also discusses the relationship between Industry 4.0 and AM with respect to improving the quality and robustness of product outcomes, based on real-time data/feedback.

This research shows how a combined approach to research into IoT and AM can create a step change in practice that alters the production and supply paradigm, potentially reducing the ecological impact of industrial systems and product life cycle. This paper demonstrates how the integration of Industry 4.0 and AM could reshape the future of manufacturing and discusses the challenges involved.

This paper proposes to extend the combination of Extended Finite Element Method (XFEM) and Level Set Method (LSM) from structural mechanics to electromagnetics. Based on this approach, the actual stage of the research work, dedicated to the investigation, development, implementation and validation of a shape optimization methodology, particularly tailored for 2D electric structures is described.

The proposed numerical approach is based on the efficiency of the XFEM and the flexibility of the LSM, to handle moving material interfaces without remeshing the whole studied domain at each optimization step.

This approach eliminates the conventional use of discrete finite elements and provides efficient, stable, accurate and faster computation schemes in comparison with other methods.

This research is limited to shape optimization of two‐dimensional electric structures, however, the work can be extended to 3D ones too.

The implementation of the proposed numerical approach for the shape optimization of a planar resistor is hereby described.

The main value of the proposed approach is a powerful and robust numerical shape optimization algorithm that demonstrates outstanding suppleness of handling topological changes, fidelity of boundary representation and a high degree of automation in comparison with other methods.