The Objects of Modernity: an Investigation of Material Culture and Mass Consumption

This thesis examines the impact of the objects that surrounds us and the practices of consumption in which we engage on the cultural constructions we live and vice versa taking its point of departure in an examination of the objects and consumption practices that have been used in the definition of the construct of modernity in various cultures. Theoretically it develops a framework based on speech act theory and ritual studies, which is then applied to a range of case studies coming from all over the world. It then builds this into an argument for attributing increased importance to the material world and material culture, when doing anthropology

Approximate Solutions to Abstract Argumentation Problems Using Graph Neural Networks

This thesis explores a new approach to approximating decision problems in abstract argumentation using Graph Convolutional Networks (GCN). It demonstrates that such an approach can reach well-balanced accuracy levels above 90 \% across a range of different decision problems, argumentation semantics, and benchmarks. This thesis develops a new Deep Neural Network (DNN) architecture adapted from the classic GCN that better addresses the specific issues found in abstract argumentation. Likewise, it develops a training approach that produces superior results for abstract argumentation data sets by introducing structured randomness and dynamic adaptation to the training data. Then, the thesis systematically applies this architecture to a large argumentation dataset across the main argumentation semantics used in the biannual ICCMA competition. It evaluates the performance of the model in a variety of different settings and across benchmarks, size bands, and model variants. The main models show good performance in the majority of cases, although there is some variation. Having created the core model, the thesis goes on to explore additional extensions of the core work. This first focuses on combining the approximate approach with exact approaches using a deterministic algorithm and a SAT solver, showing an improvement by solving six additional hard instances relative to existing solvers. Second, we explore a visualisation approach that can give new insights into argumentation graphs by applying a dimensionality reduction technique to weights from the trained GCN models, showing new insights in explaining benchmark performance. Finally, we explore using the same basic architecture to address another problem that can be structured using abstract argumentation. In this case, we apply the approach to the prediction of misinformation in tweets and achieve good performance on a key dataset

DESIGN FOR LONGEVITY - A FRAMEWORK TO SUPPORT THE DESIGNING OF A PRODUCT\u27S OPTIMAL LIFETIME

Extending the lifespan of products and parts is seen as a solution in the transition towards a circular economy. There are many proposed design approaches argued to facilitate this. However, extending the lifespan of products and parts is not always desirable, and product developers should instead strive to design for a specific longevity; the product\u27s optimal lifetime. The latter in turn depends on many various contextual factors, and this paper has identified the three main contextual factors as; the user, the business, and the resource efficiency. Considering these three appropriately can help product developers to define their product\u27s optimal lifetime. Altogether, these components promote the mindset of Design for Longevity. Specifically, as extracted from this paper: “Design for Longevity aims at designing products with an optimal lifetime, where optimal means taking the user, the business and the resource efficiency perspectives into account when designing the life of a product”. A Design for Longevity framework is proposed and evaluated in this paper, and it is concluded that the proposed Design for Longevity framework can support product developers to implement the Design for Longevity mindset

Nanometer table-top proximity x-ray lithography with liquid-target laser-plasma source

A compact laser-plasma proximity x-ray lithography system suitable for laboratory-scale low-volume nanometer patterning is presented. The laser-plasma source, which is based on a fluorocarbon liquid-jet target, generates high-brightness lambda = 1.2-1.7 nm x-ray emission with only negligible debris production. The Au/SiNx x-ray mask is fabricated by employing ion milling and a high-contrast e-beam resist. With SAL-601 chemically enhanced resist we demonstrate fabrication of high-aspect-ratio, sub-100 nm structures. The exposure time is currently 20 min using a compact 10 Hz, lambda = 532 nm, 70 mJ/pulse mode-locked Nd:YAG laser. However, the regenerative liquid-jet target is designed for operation with future, e.g., 1000 Hz, lasers resulting in projected exposure times of similar to 10 s. (C) 1997 American Vacuum Society

Gestational Diabetes and Preeclampsia in Association with Air Pollution at Levels below Current Air Quality Guidelines.

Background: Several studies have estimated associations between air pollution and birth outcomes, but few have evaluated potential effects on pregnancy complications.Objective: We investigated whether low-level exposure to air pollution is associated with gestational diabetes and preeclampsia.Methods: High-quality registry information on 81,110 singleton pregnancy outcomes in southern Sweden during 1999-2005 was linked to individual-level exposure estimates with high spatial resolution. Modeled exposure to nitrogen oxides (NOx), expressed as mean concentrations per trimester, and proximity to roads of different traffic densities were used as proxy indicators of exposure to combustion-related air pollution. The data were analyzed by logistic regression, with and without adjusting for potential confounders.Results: The prevalence of gestational diabetes increased with each NOx quartile, with an adjusted odds ratio (OR) of 1.69 (95% CI: 1.41, 2.03) for the highest (> 22.7 µg/m3) compared with the lowest quartile (2.5-8.9 µg/m3) of exposure during the second trimester. The adjusted OR for acquiring preeclampsia after exposure during the third trimester was 1.51 (1.32, 1.73) in the highest quartile of NOx compared with the lowest. Both outcomes were associated with high traffic density, but ORs were significant for gestational diabetes only.Conclusion: NOx exposure during pregnancy was associated with gestational diabetes and preeclampsia in an area with air pollution levels below current air quality guidelines

Lessons Learned from Student Satisfaction Surveys of CDIO Project Courses

The paper reports on a study of student satisfaction in CDIO project courses. The aims are to\ua0investigate if there are statistically significant differences in levels and variation of student\ua0satisfaction metrics between CDIO project courses and “traditional” courses, and to identify\ua0possible causes for these differences. The study was carried out at Chalmers University of\ua0Technology and focused on courses in its mechanical, automation and industrial design\ua0engineering programs. In these programs, about 20 CDIO project courses and 235 traditional\ua0courses are offered each year. In the study, student satisfaction and some other quantified\ua0metrics collected from Chalmers’ course evaluation system are compared for the two groups\ua0of courses. Further, the paper examines in more detail selected CDIO project courses, with\ua0high and low student satisfaction ratings. The results of the study provide support for the\ua0hypothesis that there are significant differences in ratings. A number of causes are identified\ua0and discussed, including course leadership, perceived workload, assessment, and freedom\ua0to select task