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In this chapter, the author dwells on the effects of documenting and the failure to document, border lives and deaths. Despite their apparent differences, both practices function as forms of erasure. While the Australian government has historically been keen to document the number of asylum seeker arrivals in this country, it has shown no interest in the numbers and names of those who have died in attempting to arrive here. In contrast, those who manage to cross the border, are subject to intense classificatory and numbering regimes. The latter manifests in bureaucratic control and excessive intervention, while the former reveals governmental denial of complicity in these deaths by not acknowledging them. Both practices share a refusal to encounter the other on ethical terms, reflecting the politics of numbers (Andreas & Greenhill, 2010) at and within the border. This also reveals a paradox, between being represented and not being represented. In the lacuna of details about border deaths, human rights organisations, researchers and advocacy groups have sought both to honour these deaths and to ensure that the scale of border violence is marked by statistical records on the numbers of border deaths. While it might seem that being ‘counted’ – or in Butler’s (2003, p. 41) terms – ‘represented’ is better than not being counted/represented at all, representation is never straightforward (Szörényi, 2009b, p. 185): being counted is often barely a form of representation, with such ‘numbering’ practices contributing to the effacement, rather than the recognition of refugees’ humanity.

Motivated by recent research indicating the significant challenges posed by imbalanced datasets in industrial settings, this paper presents a novel framework for Industrial Data-driven Modeling for Imbalanced Fault Diagnosis, aiming to improve fault detection accuracy and reliability.

This study addressing the challenge of imbalanced datasets in predicting hard drive failures is both innovative and comprehensive. By integrating data enhancement techniques with cost-sensitive methods, the research pioneers a solution that directly targets the intrinsic issues posed by imbalanced data, a common obstacle in predictive maintenance and reliability analysis.

In real industrial environments, there is a critical demand for addressing the issue of imbalanced datasets. When faced with limited data for rare events or a heavily skewed distribution of categories, it becomes essential for models to effectively mine insights from the original imbalanced dataset. This involves employing techniques like data augmentation to generate new insights and rules, enhancing the model’s ability to accurately identify and predict failures.

Previous research has highlighted the complexity of diagnosing faults within imbalanced industrial datasets, often leading to suboptimal predictive accuracy. This paper bridges this gap by introducing a robust framework for Industrial Data-driven Modeling for Imbalanced Fault Diagnosis. It combines data enhancement and cost-sensitive methods to effectively manage the challenges posed by imbalanced datasets, further innovating with a bagging method to refine model optimization. The validation of the proposed approach demonstrates superior accuracy compared to existing methods, showcasing its potential to significantly improve fault diagnosis in industrial applications.

Performing accurate numerical simulations of electrical drives, the precise knowledge of the local magnetic material properties is of utmost importance. Due to the various manufacturing steps, e.g. heat treatment or cutting techniques, the magnetic material properties can strongly vary locally, and the assumption of homogenized global material parameters is no longer feasible. This paper aims to present the general methodology and two different solution strategies for determining the local magnetic material properties using reference and simulation data.

The general methodology combines methods based on measurement, numerical simulation and solving an inverse problem. Therefore, a sensor-actuator system is used to characterize electrical steel sheets locally. Based on the measurement data and results from the finite element simulation, the inverse problem is solved with two different solution strategies. The first one is a quasi Newton method (QNM) using Broyden's update formula to approximate the Jacobian and the second is an adjoint method. For comparison of both methods regarding convergence and efficiency, an artificial example with a linear material model is considered.

The QNM and the adjoint method show similar convergence behavior for two different cutting-edge effects. Furthermore, considering a priori information improved the convergence rate. However, no impact on the stability and the remaining error is observed.

The presented methodology enables a fast and simple determination of the local magnetic material properties of electrical steel sheets without the need for a large number of samples or special preparation procedures.

Magnetic hysteresis holds significant technical and physical importance in the design of electromagnetic components. Despite extensive research in this area, modeling magnetic hysteresis remains a challenging task that is yet to be fully resolved. The purpose of this paper is to study vector hysteresis play models for anisotropic ferromagnetic materials in a physical, thermodynamical approach.

In this work, hysteresis play models are implemented to interpret magnetic properties, drawing upon classical rate-independent plasticity principles derived from continuum mechanics theory. By conducting qualitative and quantitative verification and validation, various aspects of ferromagnetic vector hysteresis were thoroughly examined. By directly incorporating the hysteresis play models into the primal formulations using fixed point method, the proposed model is validated with measurements in a finite element (FE) environments.

The proposed vector hysteresis play model is verified with fundamental properties of hysteresis effects. Numerical analysis is performed in an FE environment. Measured data from a rotational single sheet tester (RSST) are validated to the simulated results.

The results of this work demonstrates that the essential properties of the hysteresis effects by electrical steel sheets can be represented by the proposed vector hysteresis play models. By incorporation of hysteresis play models into the weak formulations of the magnetostatic problem in the h-based magnetic scalar potential form, magnetic properties of electrical steel sheets can be locally analyzed and represented.

We studied the relationship between job engagement and systematic problem solving (SPS) among shop-floor employees and how lean production (LP) and Internet of Things (IoT) systems moderate this relationship.

We collected data from a sample of 440 shop floor workers in 101 manufacturing work units across 33 plants. Because our data is nested, we employed a series of multilevel regression models to test the hypotheses. The application of IoT systems within work units was evaluated by our research team through direct observations from on-site visits.

Our findings indicate a positive association between job engagement and SPS. Additionally, we found that the adoption of lean bundles positively moderates this relationship, while, surprisingly, the adoption of IoT systems negatively moderates this relationship. Interestingly, we found that, when the adoption of IoT systems is complemented by a lean management system, workers tend to experience a higher effect on the SPS of their engagement.

One limitation of this research is the reliance on the self-reported data collected from both workers (job engagement, SPS and control variables) and supervisors (lean bundles). Furthermore, our study was conducted in a specific country, Italy, which might have limitations on the generalizability of the results since cross-cultural differences in job engagement and SPS have been documented.

Our findings highlight that employees’ strong engagement in SPS behaviors is shaped by the managerial and technological systems implemented on the shop floor. Specifically, we point out that implementing IoT systems without the appropriate managerial practices can pose challenges to fostering employee engagement and SPS.

This paper provides new insights on how lean and new technologies contribute to the development of learning-to-learn capabilities at the individual level by empirically analyzing the moderating effects of IoT systems and LP on the relationship between job engagement and SPS.

The purpose of this study is to examine the underexplored link between entrepreneurship education (EE) and graduate employability in the higher education (HE) sector in the United Kingdom (UK).

The study draws on a thematic content analysis of semi-structured interviews with 45 professionals in UK HE, representing the “supply” side of EE.

The findings demonstrate a unidirectional link between EE and employability outcomes. This link is affected by societal, stakeholder-related, and teaching and learning-related factors.

Although the value of universities’ initiatives connecting EE and employability for economic development is emphasized, the study does not provide direct empirical evidence for this effect. Macroeconomic research is needed.

EE and employability would benefit from knowledge exchange between universities’ stakeholders and a broader understanding of what constitutes a valuable graduate outcome.

The study reveals the benefits of EE on a micro level. Participation in EE supports the connection between individual investments in HE and employability.

Based on human capital theory, many policymakers regard EE as a vehicle through which the relationship between investments in HE and career success on a micro level and economic growth on a macro level can be nurtured. Challenging this logic, the study highlights the potential of institutional theory to explain a contextualization of the link between EE and employability on a national level.

Many refugees and asylum seekers in Germany experience a high disease burden and low health literacy. The current study aims to focus on assessing these issues among African refugees and asylum seekers in Bavaria, Germany. The authors evaluated their self-perceived health status and health literacy, and identified barriers and gaps in health care utilization, intending to improve health care services for this group.

The authors conducted a cross-sectional, questionnaire-based study involving 69 refugees and asylum seekers from Ethiopia, Eritrea and Nigeria. The authors performed descriptive and exploratory statistical analyses.

The authors found a substantial disease burden in the early stages of resettlement in Germany, particularly mental health symptoms (53.6%) and musculoskeletal problems (47.8%). Challenges in health literacy were observed, such as difficulties in understanding health information and managing emergency situations. Access to interpreters was limited, and understanding treatment certificates was more challenging than using electronic health cards, with 18.2% of participants reporting denial of medical treatment.

These findings highlight the need for early and tailored health support for refugees, with a particular focus on mental health. Efforts should be made to reduce language barriers and improve navigational skills within the health-care system, particularly in emergency situations. Addressing the restricted access to health care and bureaucratic obstacles is crucial for improved health outcomes among refugees.

To the best of the authors’ knowledge, this research is the first to specifically explore the self-reported health status and health literacy of African refugees and asylum seekers in Bavaria, Germany, providing valuable insights into the unique healthcare challenges of this often underrepresented and overlooked population.

Diversifying the teaching profession has been of international concern for several decades. While most attention has been devoted to issues of ‘race’ and ethnicity, in comparison, social class has been relatively invisible. Research suggests that those from working class backgrounds experience challenges with regard to belonging in what has been regarded as a middle class teaching profession. An area unexplored has been the complexities of researching with student teachers from under-represented groups, including those from working class backgrounds. This chapter draws on research conducted as part of the Access to Post-primary Teaching (APT) project funded under the Higher Education Authority's Programme for Access to Higher Education (PATH): Strand 1 – Equity of Access to Initial Teacher Education. APT supports the participation of student teachers from lower socio-economic groups in initial teacher education. Following the introduction and literature review, we provide information about the methodology of the overall project, as well as the data upon which we draw in this chapter. Next, we present a critical reflective analysis of working with APT participants over the last six years, drawing on our own critical reflections as researchers, as well as the voices of our participants through the project's research strand. Here we highlight concerns pertaining to relative researcher-participant positionality, and issues of identity and disclosure. Finally, we interrogate our analysis using the methodological literature about researching with marginalised groups and end with recommendations for supporting researcher reflexivity.

The “chiralisation” of Euclidean polygonal tessellations is a novel, recent method which has been used to design new auxetic metamaterials with complex topologies and improved geometric versatility over traditional chiral honeycombs. This paper aims to design and manufacture chiral honeycombs representative of four distinct classes of 2D Euclidean tessellations with hexagonal rotational symmetry using fused-deposition additive manufacturing and experimentally analysed the mechanical properties and failure modes of these metamaterials.

Finite Element simulations were also used to study the high-strain compressive performance of these systems under both periodic boundary conditions and realistic, finite conditions. Experimental uniaxial compressive loading tests were applied to additively manufactured prototypes and digital image correlation was used to measure the Poisson’s ratio and analyse the deformation behaviour of these systems.

The results obtained demonstrate that these systems have the ability to exhibit a wide range of Poisson’s ratios (positive, quasi-zero and negative values) and stiffnesses as well as unusual failure modes characterised by a sequential layer-by-layer collapse of specific, non-adjacent ligaments. These findings provide useful insights on the mechanical properties and deformation behaviours of this new class of metamaterials and indicate that these chiral honeycombs could potentially possess anomalous characteristics which are not commonly found in traditional chiral metamaterials based on regular monohedral tilings.

To the best of the authors’ knowledge, the authors have analysed for the first time the high strain behaviour and failure modes of chiral metamaterials based on Euclidean multi-polygonal tessellations.

Based on the cognitive appraisal theory of emotion and social comparison theory, this study explores the mediating mechanism and boundary conditions of supervisor bottom-line mentality on employee presenteeism.

Using hierarchical regression and bootstrapping, we test the hypothesized relationships with three-stage data from 265 full-time employees in China.

Supervisor bottom-line mentality has a significant positive influence on employee presenteeism. Workplace fear of missing out plays a mediating role between supervisor bottom-line mentality and employee presenteeism. Employees’ status-striving motivation positively moderates the influence of supervisor bottom-line mentality on employees’ workplace fear of missing out and enhances the mediating effect of workplace fear of missing out.

Presenteeism can be detrimental to employees’ health, and ultimately leads to a decrease in organizational productivity. Research conclusions warn companies to be vigilant about supervisors’ bottom-line mentalities and to strengthen employee health management.

This study explains when and how supervisor bottom-line mentality affects employee health, contributing to the literature on the antecedents of presenteeism and enriching the research on supervisor bottom-line mentalities and employee and organizational outcomes. This study clarifies the emotional mechanisms and boundary conditions of supervisor bottom-line mentality affecting presenteeism.