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In laser powder bed fusion (L-PBF) additive manufacturing, spatter particles are ejected from the melt pool and can be detrimental to material performance and powder recycling. Quantifying spatter generation with respect to processing conditions is a step toward mitigating spatter and better understanding the phenomenon. This paper reveals process insights of spatter phenomena by automatically annotating spatter particles in high-speed video observations using machine learning.

A high-speed camera was used to observe the L-PBF process while varying laser power, laser scan speed and scan strategy on a constant geometry on an EOSM290 using Ti-6Al-4V powder. Two separate convolutional neural networks were trained to segment and track spatter particles in captured high-speed videos for spatter characterization.

Spatter generation and ejection angle significantly differ between keyhole and conduction mode melting. High laser powers lead to large ejections at the beginning of scan lines. Slow and fast build rates produce more spatter than moderate build rates at constant energy density. Scan strategies with more scan vectors lead to more spatter. The presence of powder significantly increases the amount of spatter generated during the process.

With the ability to automatically annotate a large volume of high-speed video data sets with high accuracy, an experimental design of observed parameter changes reveals quantitively stark changes in spatter morphology that can aid process development to mitigate spatter occurrence and impacts on material performance.

Controversy has long swirled over the claim that Donald Trump's base has deeply rooted authoritarian tendencies, but Trump himself seems to have few doubts. Asked whether his stated wish to be dictator “on day one” of second term in office would repel voters, Trump said “I think a lot of people like it.” It is one of his invariable talking points that 74 million voters supported him in 2020, and he remains the unrivaled leader of the Republican Party, even as his rhetoric escalates to levels that cautious observers now routinely call fascistic.

Is Trump right that many people “like” his talk of dictatorship? If so, what does that mean empirically? Part of the answer to these questions was apparent early, in the results of the 2016 American National Election Study (ANES), which included survey questions that we had proposed which we drew from the aptly-named “Right-Wing Authoritarianism” scale. Posed to voters in 2012–2013 and again in 2016, those questions elicited striking responses.

In this chapter, we revisit those responses. We begin by exploring Trump's escalating anti-democratic rhetoric in the light of themes drawn from Max Weber and Theodor W. Adorno. We follow this with the text of the 2017 conference paper in which we first reported that 75% of Trump's voters supported him enthusiastically, mainly because they shared his prejudices, not because they were hurting economically. They hoped to “get rid” of troublemakers and “crush evil.” That wish, as we show in our conclusion, remains central to Trump's appeal.

The purpose of this study is to investigate the relationship between work-life balance and the mental health of Indian managers and to explore the moderating role of emotional intelligence (EI) and gender.

Work-life balance scale (Hayman 2005), Mental Health Inventory (Viet and Ware, 1983) and EI scale (Wong and Law, 2002) were administered to 202 (102 males and 100 females) Indian managers. Based on the Conservation of Resource theory, a theoretical model has been designed and hypotheses were tested by descriptive, correlation and moderation analysis.

The results of this study indicated that work-life balance is positively correlated with psychological well-being and mental health, while negatively correlated with the psychological distress of managers. EI has emerged as a potential moderator that positively influences the relationship between work-life balance and the mental health of managers. At the same time, gender did not show any moderating effect.

This research has theoretical, practical as well as social implications.

This study is aligned with SDG 3 and SDG 5 of the UN Sustainable Development Goals 2023. This paper provides valuable inputs in promoting mental health at the workplace and formulating gender-neutral work-life balance policies and programs in Indian organizations.

This study is aligned with SDG 3 (Health and well-being) and SDG 5 (Gender equality) of the UN Sustainable Development Goals 2023.

This study is an empirical research paper backed by a sound theoretical framework, which addresses the work-life balance and mental health issues of managers and highlights the positive role of EI in managing their personal and professional lives in a low gender-egalitarian Indian work–family culture.

Staff in secure mental health-care settings face unique occupational challenges that may conflict with their personal or professional moral code. Initial research has established the presence of moral injury in this population, though insight into the specific sources and driving factors at the root of this syndrome is limited. The purpose of this study was to identify potentially morally injurious events and associated risk factors for secure mental healthcare staff.

To address this gap, a three-round expert Delphi survey was conducted to gain consensus on the conceptualisation, types and drivers of potentially morally injurious experiences (PMIEs) for secure mental health-care workers. Health-care professionals and academics in the field were recruited.

A high level of consensus (= 80%) was achieved on several sources of moral injury, which related to aspects of the health-care system, the secure context, relational dynamics and individual practices, behaviours and attitudes. Experts also agreed on several items relating to the definition of a PMIE, the factors driving the occurrence of PMIEs and the factors increasing risk for the subsequent development of moral injury.

The findings suggest that current definitions of PMIEs may, in isolation, be too narrow, prompting the need to attend to the broad range of PMIEs experienced by secure mental health-care staff. In addition, recommendations for the primary and secondary prevention of moral injury in secure mental health-care staff are offered, recognising the particular need for intervention at a systemic level.

To the best of the authors’ knowledge, this study is the first to consider the range of sources of moral injury faced by staff providing for people with complex forensic and mental health needs.

The purpose of this paper is to critically examine the existing literature on workplace mindfulness and suggest positive organizational behavior (POB) scholarship as a suitable domain to understand the scientific and secular nature of mindfulness.

This conceptual paper is based on the critical analysis of the literature on POB and contemporary mindfulness at work. This paper highlights the limitations of workplace mindfulness in terms of its research and practice. Then, the limitations of workplace mindfulness are analyzed in relation to POB scholarship to suggest a way forward for research and practice.

The findings imply that contemporary mindfulness meets the inclusion criteria of psychological capital and thus it can be adopted and investigated in the workplace using the POB scholarship.

It suggests implications for research and practice by considering mindfulness as a psychological capital construct in the workplace context.

Mindfulness is an interesting topic for organizational researchers, and many organizations are adopting mindfulness to improve their workplace functioning. In recent years, scholars have highlighted potential ethical issues with the adoption of the spiritual and religious nature of mindfulness for workplace benefits. In this regard, the understanding of the scientific and secular nature of mindfulness is limited in organizational literature. This paper advances the knowledge of the literature on contemporary mindfulness and POB and argues the importance of the inclusion of mindfulness in psychological capital.

This study aims to explore the safe-haven properties of sukuk and analyze the co-movement and interdependence between sukuk and conventional bond indices to provide insights into the potential role of diversification.

The study uses the data set from 2012 to 2022, retrieved from the Eikon Reuter database. Different machine learning tools such as decision trees, random forests, gradient boosting and deep neural networks have been applied to capture the non-linear relationship and co-movement among the variables. Furthermore, K-clustering captures the hidden patterns and periods of high and low co-movements.

The results state that the sukuk and conventional bond indices exhibit various degrees of co-movement influenced by regional and global market sentiments. The clustering analysis shows strong positive and negative correlations. The sukuk shows some instances of zero co-movement, but the results are inconsistent across all scenarios. Moreover, investors need to do their research first before investing in sukuk.

This study uniquely applies K-clustering and advanced machine learning tools to understand the nonlinear relationship among variables better. In contrast, the previous studies mainly focused on linear relationships. It is critical to understand that financial variables tend to have nonlinear relationships, and these techniques best suit those needs.