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Beyond prototyping: mapping the relative advantages of adopting additive manufacturing for industrial production
Get PDFAdditive Manufacturing (AM) offers significant potential for product and process transformation due to a range of Relative Advantages (RA) it holds over rival Traditional Manufacturing (TM) for low-volume industrial production. However, its adoption levels have fallen short of expectations, partly due to insufficient understanding on how to leverage combinations of its RAs in different applications and the contextual factors to support its adoption case. This paper investigates the RAs influencing AM adoption decisions for low-volume industrial production. We employ a qualitative approach to explore AM adoption decisions of 18 low-volume applications across Aerospace, Automotive, Power Generation, Rail and Marine sectors. We contribute to the extant AM adoption literature by developing two frameworks. The first framework identifies 11 key sources of RA which contribute to product performance, process cost and process speed, within a set of four contextual factors, partly explaining the underlying logic guiding adoption decisions. We elaborate DOI theory, through specification of the RA construct by enriching it with empirically grounded sub-dimensions and contextual factors for more accurate predictions of managers’ intention to adopt AM. The second framework defines seven types of adoption decisions to explain the RA rationale for adopting AM for industrial end-use components. Our framework offers managers a guide for manufacturing strategy decisions for low-volume components
Exploiting chemical bonding principles to design high performance thermoelectric materials
Get PDFThermoelectric materials offer unique opportunities to convert otherwise wasted thermal energy into useful electrical energy. Many of the traditional thermoelectric materials, such as bismuth telluride and lead telluride contain scarce and toxic elements. This has motivated the search for new high-performance materials containing readily-available and environmentally-less-damaging elements. Numerous advances in the development of high-performance thermoelectric materials exploit fundamental chemical-bonding principles. Much of the thermoelectric literature lies at the interface of chemistry, physics, and materials science. In this Review, progress in the design of high-performance materials is discussed in terms of ideas that are familiar in chemistry. This includes the influence of concepts such as bonding heterogeneity, covalency, polarizability, lone pairs, and different bonding models, including multi-center, metallic, and iono-covalent archetypes. In this way, we seek to present aspects of this diverse field of research in terms that are accessible to the chemistry community
Enhancing architecture frameworks by including modern stakeholders and their views/viewpoints
Get PDFVarious architecture frameworks for software, systems, and enterprises have been proposed in the literature. They identified several stakeholders and defined modeling perspectives, architecture viewpoints, and views to frame and address stake-holder concerns. However, the stakeholders with data science and Machine Learning (ML) related concerns, such as data scientists and data engineers, are yet to be included in existing architecture frameworks. Only this way can we envision a holistic system architecture description of an ML-enabled system. Note that the ML component behavior and functionalities are special and should be distinguished from traditional software system behavior and functionalities. The main reason is that the actual functionality should be inferred from data instead of being specified at design time. Additionally, the structural models of ML components, such as ML model architectures, are typically specified using different notations and formalisms from what the Software Engineering (SE) community uses for software structural models. Yet, these two aspects, namely ML and non-ML, are becoming so intertwined that it necessitates an extension of software architecture frameworks and modeling practices toward supporting ML-enabled system architectures. In this paper, we address this gap through an empirical study using an online survey instrument. We surveyed 61 subject matter experts from over 25 organizations in 10 countries
Sexual violence and military justice in the occupied South
No full textThis article examines the responses of Union military officers to sexual violence committed by white soldiers against Black women and girls during the Civil War. This article centers on the resulting courts martial to examine changing understandings of race, gender, and sexuality during the conflict. Through highlighting officers’ interventions in trials, this article reveals efforts to balance military discipline with the moral imperatives of protecting vulnerable people. These cases illustrate the broader federal initiative to impose racial equality in military justice, though this project often fell short of true equity. This article also examines the challenges and stereotypes faced by Black women in seeking justice, emphasizing how their testimonies and the support they received from some officers marked a radical departure from the prevailing nineteenth-century social and legal frameworks. This shift underscored the importance of Black communities to the Union war effort and the broader implications for post-war racial and gender dynamics
A pluralistic framework for measuring, interpreting and decomposing heterogeneity in meta‐analysis
Get PDFMeasuring heterogeneity, or inconsistency, among effect sizes is a crucial step for interpreting meta‐analytic evidence across diverse taxonomic groups and spatiotemporal contexts. However, ecologists and evolutionary biologists often interpret overall mean effects (mean population effects) as consistent across contexts, either explicitly or implicitly, without properly quantifying and interpreting heterogeneity. Here, we present a pluralistic approach that aims to quantify heterogeneity by introducing complementary metrics, each of which decomposes heterogeneity into within‐study, between‐study and between‐species (species and phylogenetic) variances. These metrics include the traditional I2 (variance‐standardized metric), the newly derived coefficient of variation for heterogeneity (CVH family; mean‐standardized metric), the second‐order coefficient of variation (M family; variance–mean‐standardized metric) and their stratified variants. To demonstrate the benefits of the combined use of these measures, we synthesize heterogeneity estimates from 512 ecological and evolutionary meta‐analyses. We show that total heterogeneity (variance of true effects) is, on average, 10 times larger than statistical noise (sampling error variance), contributing to 91% of the observed variance (median I2 = 91%). This amount of heterogeneity is nearly twice the size of the mean population effect (median CVH = 1.8 and M = 0.6), indicating substantial variation among studies within a meta‐analysis. Moreover, different effect size types yield different values of heterogeneity metrics because they are inherently influenced by statistical properties of their effect size estimators. As such, comparisons of heterogeneity across effect size types should be made with caution, albeit the proposed heterogeneity metrics are unit‐free. Our large‐scale synthesis also provides new benchmarks for the interpretation of heterogeneity and recommendations on how to quantify and report heterogeneity. New extensions for stratifying heterogeneity metrics will clarify our understanding of the generalisability, and at what level of meta‐analytic effects in ecology and evolution
Office of Fair Trading v Abbey National plc [2009] UKSC 6: reverse Robin Hood and banking charges
No full textBeckett and the aesthetics of Black inexpression
Get PDFAn essay on the influence of Samuel Beckett on three contemporary Black artists/writers
Advancing inclusive recruitment: a practice lens on navigating barriers to refugee employment
Get PDFScholarly interest in refugee employment often centers on the barriers faced by this group of jobseekers. This study shifts focus to employers, exploring how their practices address recruitment challenges. Our qualitative investigation of 39 Australia-based employers identifies two sets of barriers—proximal and distal—and the corresponding practices employers adopt to overcome them. We find that these barriers differ in the assumed scale, locus of influence, and the nature of impact. Through a practice theory lens, we demonstrate how employers’ responses to these barriers have the capacity to reproduce or alter the socio-structural conditions in which refugee employment takes place. While most employers focus on adaptive practices targeting proximal barriers, transformative practices aimed at tackling the distal barriers play a key role in rectifying structural disparities in the recruitment of disadvantaged groups. Our study advances refugee employment literature by demonstrating how employers’ assumptions around the barriers can deter employer engagement and limit impact. We highlight the managerial implications by demonstrating how employers can drive meaningful change in areas traditionally considered the domain of other actors, effectively addressing challenges in the employment landscape
Professor Michael Twyman
Get PDFAn invited paper in memory of the work of Prof Michael Twyman, 1934–202
Temperate rainforests in the UK and climate change: a pilot study
No full textTemperate rainforests are globally-rare habitats of which fragments remain in western parts of the UK. They are fundamentally defined by climate, so are potentially exposed to the effects of climate change. This report presents a pilot assessment of the potential effects of climate change on temperate rainforests in the UK. It uses a definition of the climatic suitability for temperate rainforests and a set of seven climate indicators relevant to their sustainability. Climate change impacts through the 21st century are assessed for different levels of global warming ranging from an increase in global average temperatures of just 1.5oC by 2100 to the increases of more than 5oC in emissions pathway RCP8.5. The climate scenarios are based on the UKCP18 climate projections and are applied at a spatial resolution of 12x12km across the UK.
The three key conclusions are: (i) risks to the viability of temperate rainforests depend strongly on emissions pathway and, for a given pathway, the range of climate projections used, (ii) the key drivers of climate change-induced risk to temperate rainforests increase across all of the UK apart from northern Scotland, and (iii) envelopes describing climatic suitability for temperate rainforest do not provide a robust means of assessing future climate risks because impacts are very sensitive to the (unknown) upper temperature limit.
Whilst the assessment has shown that climate change has the potential to adversely affect temperate rainforest habitats across most of the UK, it has also identified four key uncertainties and knowledge gaps affecting the development of policy towards temperate rainforest restoration. There is a need for (i) better understanding of where temperate rainforests can currently be found, (ii) better understanding of their climatic limits and the key climate drivers, (iii) a more detailed analysis with a wider range of climate projections, (iv) better understanding of how climate change would differentially affect different species in temperate rainforests and therefore rainforest character, and (v) a detailed assessment of how changes in rainforest microclimates are linked to changes in local and regional climate