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This study aims to enhance merging of additive manufacturing (AM) techniques with powder injection molding (PIM). In this way, the prototypes could be 3D-printed and mass production implemented using PIM. Thus, the surface properties and mechanical performance of parts produced using powder/polymer binder feedstocks [material extrusion (MEX) and PIM] were investigated and compared with powder manufacturing based on direct metal laser sintering (DMLS).

PIM parts were manufactured from 17-4PH stainless steel PIM-quality powder and powder intended for powder bed fusion compounded with a recently developed environmentally benign binder. Rheological data obtained at the relevant temperatures were used to set up the process parameters of injection molding. The tensile and yield strengths as well as the strain at break were determined for PIM sintered parts and compared to those produced using MEX and DMLS. Surface properties were evaluated through a 3D scanner and analyzed with advanced statistical tools.

Advanced statistical analyses of the surface properties showed the proximity between the surfaces created via PIM and MEX. The tensile and yield strengths, as well as the strain at break, suggested that DMLS provides sintered samples with the highest strength and ductility; however, PIM parts made from environmentally benign feedstock may successfully compete with this manufacturing route.

This study addresses the issues connected to the merging of two environmentally efficient processing routes. The literature survey included has shown that there is so far no study comparing AM and PIM techniques systematically on the fixed part shape and dimensions using advanced statistical tools to derive the proximity of the investigated processing routes.

Intrinsic values to the field of special education include advocacy, inclusivity, individuality, and empiricism. From early days of providing custodial care in segregated settings, special education has evolved into a program that seeks to educate students with a wide range of learning needs in inclusive settings and identify a robust research base that informs its policies and practices. Important concepts such as inclusion and continuum of services have not only been valuable in conceptualizing and in providing intervention for students with disabilities but have also been valuable in advancing the field. Research in special education and students with disabilities has been instrumental in moving the field forward. In the future, special education will continue to be valuable in supporting students whose learning and survival needs deviate from the norm in meaningful ways by delivering responsive evidence-based instruction.

This study was conducted to address the methodical shortcomings and high associated cost of understanding the use of new, poorly understood architectural spaces, such as makerspaces. The proposed quantified method of enhancing current post-occupancy evaluation (POE) practices aims to provide architects, engineers and building professionals with accessible and intuitive data that can be used to conduct comparative studies of spatial changes, understand changes over time (such as those resulting from COVID-19) and verify design intentions after construction through a quantified post-occupancy evaluation.

In this study, we demonstrate the use of ultra-wideband (UWB) technology to gather, analyze and visualize quantified data showing interactions between people, spaces and objects. The experiment was conducted in a makerspace over a four-day hackathon event with a team of four actively tracked participants.

The study shows that by moving beyond simply counting people in a space, a more nuanced pattern of interactions can be discovered, documented and analyzed. The ability to automatically visualize findings intuitively in 3D aids architects and visual thinkers to easily grasp the essence of interactions with minimal effort.

By providing a method for better understanding the spatial and temporal interactions between people, objects and spaces, our approach provides valuable feedback in POE. Specifically, our approach aids practitioners in comparing spaces, verifying design intent and speeding up knowledge building when developing new architectural spaces, such as makerspaces.

To increase the understanding of how entrepreneurship education impacts entrepreneurial careers, the purpose of the paper is to investigate the role that a venture creation program (VCP) might have in mitigating or surpassing a lack of other antecedents of entrepreneurial careers. In particular, the authors focus on entrepreneurial pedigree and prior entrepreneurial experience.

Data from graduates of VCPs at three universities in Northern Europe were collected through an online survey. Questions addressed graduate background prior to education, yearly occupational employment subsequent to graduation and graduates' own perceptions of entrepreneurial activity in employment positions. The survey was sent to 1,326 graduates and received 692 responses (52.2% response rate).

The type of VCP, either independent (Ind-VCP) or corporate venture creation (Corp-VCP), influenced the mitigation of prior entrepreneurial experience. Prior entrepreneurial experience, together with Ind-VCP, made a career as self-employed more likely. However, this was not the case for Corp-VCP in subsequently choosing intrapreneurial careers. Entrepreneurial pedigree had no significant effect on career choice other than for hybrid careers.

Entrepreneurial experience gained from VCPs seems to influence graduates toward future entrepreneurial careers. Evidence supports the conclusion that many VCP graduates who lack prior entrepreneurial experience or entrepreneurial pedigree can develop sufficient entrepreneurial competencies through the program.

This study offers novel evidence that entrepreneurship education can compensate for a lack of prior entrepreneurial experience and exposure for students preparing for entrepreneurial careers.

Sarcasm is a linguistic expression that usually carries the opposite meaning of what is being said by words, thus making it difficult for machines to discover the actual meaning. It is mainly distinguished by the inflection with which it is spoken, with an undercurrent of irony, and is largely dependent on context, which makes it a difficult task for computational analysis. Moreover, sarcasm expresses negative sentiments using positive words, allowing it to easily confuse sentiment analysis models. This paper aims to demonstrate the task of sarcasm detection using the approach of machine and deep learning.

For the purpose of sarcasm detection, machine and deep learning models were used on a data set consisting of 1.3 million social media comments, including both sarcastic and non-sarcastic comments. The data set was pre-processed using natural language processing methods, and additional features were extracted and analysed. Several machine learning models, including logistic regression, ridge regression, linear support vector and support vector machines, along with two deep learning models based on bidirectional long short-term memory and one bidirectional encoder representations from transformers (BERT)-based model, were implemented, evaluated and compared.

The performance of machine and deep learning models was compared in the task of sarcasm detection, and possible ways of improvement were discussed. Deep learning models showed more promise, performance-wise, for this type of task. Specifically, a state-of-the-art model in natural language processing, namely, BERT-based model, outperformed other machine and deep learning models.

This study compared the performance of the various machine and deep learning models in the task of sarcasm detection using the data set of 1.3 million comments from social media.

This chapter on anti-racism struggles applies an anti-racist activist framing, both critically examining and recognising the milestones achieved through centuries of pro-justice and anti-racism struggles. It delves into the arduous journey that the global fight for racial equity has undergone and highlights the significant progress as well as setbacks experienced during this lengthy struggle. The earliest history of the fight against racial oppression and domination goes back to anti-slavery and anti-colonial movements. Scholars have analysed the emergence, development and state of global anti-racism struggles in a variety of ways. I approach this subject from a sociological perspective, highlighting the role of social structures, groups and institutions that have contributed to shaping the outcomes of anti-racist initiatives. While recognising the role of individuals and leading political activists, this chapter emphasises anti-racism as a collective social justice struggle. To do this, I explore various local and global anti-racism endeavours and examine how they may influence discussions on race, racism and racial equity and their evolving trajectories across different societies.

In February 2018, Jerome Powell had taken over as chair of the FOMC. At first glance, the macroeconomic conditions inherited by Powell appeared favorable for continued stability: unemployment and inflation were low, and the economy had been steadily growing for nearly a decade. Yet despite the appearance of stability, the economy faced significant risks that required the Federal Reserve's attention. Was an uptick in inflation imminent, and if so, should Powell raise rates to limit any inflationary pressure? Or was the economy still operating below capacity, and if so, should the Federal Reserve take a more accommodative stance? To gain perspective, Powell needed to look back at the past fifty years of monetary policy in the United States.

This study aims to conduct a bibliometric analysis to provide a comprehensive picture and identify future research directions to enrich the existing literature on behavioral biases.

The data set comprises 518 articles from the Web of Science database. Performance analysis is used to highlight the significant contributors (authors, institutions, countries and journals) and contributions (highly influential articles) in the field of behavioral biases. In addition, network analysis is used to delve into the conceptual and social structure of the research domain.

The current review has identified four major themes: “Influence of behavioral biases on investment decisions,” “Determinants of home bias,” “Impact of biases on stock market variables” and “Investors’ decision-making under uncertainty.” These themes reveal that a majority of studies have focused on equity markets, and research on other asset classes remains underexplored.

This study extracted data from a single database (Web of Science) to ensure standardization of results. Consequently, future research could broaden the scope of the bibliometric review by incorporating multiple databases.

The novelty of this research is to provide valuable guidance by evaluating the existing literature and advancing the knowledge base on the conceptual and social structure of behavioral biases.

Racism occurs in many ways and varies across countries, evolving and adapting to sociocultural history, as well as contemporary economic, political and technological changes. This chapter discusses the multilevel dimensions of racism and its diverse manifestations across multiracial societies. It examines how different aspects of racism are mediated interpersonally, and embedded in institutions, social structures and processes, that produce and sustain racial inequities in power, resources and lived experiences. Furthermore, this chapter explores the direct and indirect ways racism is expressed in online and offline platforms and details its impacts on various groups based on their intersecting social and cultural identities. Targets of racism are those who primarily bear the adverse effects. However, racism also affects its perpetrators in many ways, including by limiting their social relations and attachments, and by imposing social and economic costs. This chapter thus analyses the many aspects of racism both from targets and perpetrators' perspectives.

The COVID-19 pandemic has prompted the fast growth of online music festivals. This paper explores how festivalgoers' experience affects their satisfaction and drives their loyalty to re-attend online music festivals in China.

Based on an understanding of the music festival experience and the characteristics of live-streamed performances, this paper investigates five factors that affect festivalgoers' satisfaction and loyalty, namely the music experience, ambience experience, separation experience, social experience and novelty experience. The relationships between festivalgoers' experience, satisfaction and loyalty are also explored using structural equation modelling techniques.

The empirical results suggest that four of the above-mentioned five factors of the online music festival experience directly affect festivalgoers' satisfaction and loyalty. The online mode is a rapid adaptation of and preferred alternative to offline music festivals, whilst the creation of the experience, along with satisfaction with and loyalty to the online music festival, are determined by different factors compared to offline modes. Overall festival satisfaction positively enhances the relationship between festivalgoers' experience and loyalty to online music festivals.

This study offers a range of practical and managerial implications for organisers of online music festival, similar activities such as live-streaming concerts and stage performances and hybrid events.

This study explores a phenomenon that has evolved quickly since COVID-19 and will, potentially, have an ongoing and enduring impact on the music festival sector. It differentiates the understanding of festivalgoers' experience in online and offline modes, which is a new addition to the literature. It also enriches the theoretical understanding of the experience of, satisfaction with and loyalty to online music festivals.