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In what follows, I first unpack the context of East Asia where fast economic growth, demographic transition, shifting public policies, and historical legacies as well as emerging trends of family norms and practices jointly influence children's and youths' everyday lives and well-being. I show that albeit intraregional and intrasociety heterogeneities, childhood is part and parcel of the modernization project in this part of the world, which has attracted concerted efforts of intense investment from the state and the family, shaping a trajectory of childhood that is increasingly scholarized. I then sketch the landscape of childhood and youth studies in this region, calling for the intervention of childhood sociology as an approach to bring young people's own perspectives, voices, subjectivities, and actions to the fore. This is followed by an introduction to four compelling contributions that offer rich and nuanced insights into the pains and gains, pressures and perseverance of the growing up experiences of the young in rapidly changing East Asian societies.

The purpose of this paper is to show how the EStra-Many method works on optimization problems characterized by high-dimensionality of the objective space. Moreover, a comparison with a more classical approach (a constrained bi-objective problem solved by means of NSGA-II) is done.

The six reactances of a compensation network (CN) for a wireless power transfer system (WPTS) are synthesized by means of an automated optimal design. In particular, an evolutionary algorithm EStra-Many coupled with a sorting strategy has been applied to an optimization problem with four objective functions (OFs). To assess the obtained results, a classical genetic algorithm NSGA-II has been run on a bi-objective problem, constrained by two functions, and the solutions have been analyzed and compared with the ones obtained by EStra-Many.

The proposed EStra-Many method identified a solution (CN synthesis) that enhances the WPTS, considering all the four OFs. In particular, to assess the synthesized CN, the Bode diagram of the frequency response and a circuital simulation were evaluated a posteriori; they showed good performance of the CN, with smooth response and without unwanted oscillations when fed by a square wave signal with offset. The EStra-Many method has been able to find a good solution among all the feasible solutions, showing potentiality also for other fields of research, in fact, a solution nondominated with respect to the starting point has been identified. From the methodological viewpoint, the main finding is a new formulation of the many-objective optimization problem based on the concept of degree of conflict, which gives rise to an implementation free from hierarchical weights.

The new approach EStra-Many used in this paper showed to properly find an optimal solution, trading-off multiple objectives. The compensation network so synthesized by the proposed method showed good properties in terms of frequency response and robustness. The proposed method, able to deal effectively with four OFs, could be applied to solve problems with a higher number of OFs in a variety of applications because of its generality.

This study aims to examine the impact of the gameful experience on behavioural outcomes. Drawing from stimulus–organism–response theory, it proposes and tests a new model that investigates the relationship between the gameful experience, brand loyalty and intention to use gamified branded applications in the sports context. In addition, it explores the mediating role of customer–brand engagement (CBE) and the moderating role of self-image congruity (SIC).

A sample of 436 active users of sport-related branded gamified applications was used to test the model. Data was collected from online sports forums, brands’ Facebook communities and during sporting events.

Results indicate that the gameful experience positively and directly impacts behavioural intentions but does not directly influence brand loyalty. This relationship becomes partially significant when mediated by CBE. In addition, results show that users with high levels of SIC are more likely to continue using the gamified application, whereas users with low levels are more likely to engage with the brand.

This study expands the gamification literature in the sports sector by revealing the importance of the gameful experience in driving loyalty, behavioural intentions and CBE. It proposes a new model that sheds light on the emotional aspect of the interaction between a user and a gamified system and the importance of exploring the effects of moderators, such as SIC, in these relationships.

This study aims to explore the implementation of artificial intelligence (AI) in archival practice by presenting the thoughts and opinions of working archival practitioners. It contributes to the extant literature with a fresh perspective, expanding the discussion on AI adoption by investigating how it influences the perceptions of digital archival expertise.

In this study a two-phase data collection consisting of four online focus groups was held to gather the opinions of international archives and digital preservation professionals (n = 16), that participated on a volunteer basis. The qualitative analysis of the transcripts was performed using template analysis, a style of thematic analysis.

Four main themes were identified: fitting AI into day to day practice; the responsible use of (AI) technology; managing expectations (about AI adoption) and bias associated with the use of AI. The analysis suggests that AI adoption combined with hindsight about digitisation as a disruptive technology might provide archival practitioners with a framework for re-defining, advocating and outlining digital archival expertise.

The volunteer basis of this study meant that the sample was not representative or generalisable.

Although the results of this research are not generalisable, they shed light on the challenges prospected by the implementation of AI in the archives and for the digital curation professionals dealing with this change. The evolution of the characterisation of digital archival expertise is a topic reserved for future research.