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- Bernisson, Maud
(författare)
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The Public Interest in the Data Society : Deconstructing the Policy Network Imaginary of the GDPR
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- When Facebook censored the Pulitzer Prize-winning photograph The Napalm Girl, it provoked a global outcry. It also showed digital media’s ability to redefine freedom of expression and information. Redefining fundamental rights and freedoms involves drawing limits upon other fundamental freedoms and rights like the right to privacy. It is therefore crucial to study the changing role of the public interest, which ensures conditions for all to exercise fundamental freedoms and rights, including the right to privacy. This thesis aims at analysing definitions and uses of the public interest during the policymaking process of the General Data Protection Regulation (GDPR). The policymaking process is approached through the policy network theory (Rhodes, 2007). Policy network theory permits researchers to study norms and beliefs that drive stakeholders’ strategies to construct knowledge during the policymaking process. The construction of knowledge is influenced by a shared imaginary (Ricœur, 1984), which frames shared knowledge at the societal level. Metaphors permit tracing imaginaries. The public interest, as a metaphor defined during the policymaking process of the GDPR, enables the reconstruction of the policy network imaginary of the GDPR. I use two methods, the assessment of the degree of preference attainment (DPA) and the discourse-historical approach (DHA), which belongs to the field of critical discourse studies. Assessing DPA allows a comparison of key definitions in the texts produced during the policymaking process by different groups of actors—like Google and the European Commission—with corresponding definitions in the GDPR. The DHA permits the contextualization of definitional changes, the identification of power games within the policy network, and the reconstruction of the policy network imaginary.Results show that the policy network imaginary corresponds to a techno-economic ideology. This ideology underlies a preconceived context, the data society, and frames societal phenomena to regulate through beliefs and norms. This ideology is taking over the public interest ideology. Technological and economic determinism drove the design of the GDPR, which limits capacities to regulate and aligns with the interest of the dominant tech and economic actors. The member states favoured specific topics related to the public interest, like security, to be implemented at the EU level, at the expense of other topics, such as freedom of expression and information, to be implemented at the national level.
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| 2. |
- Drott, Carl Johan, 1984-
(författare)
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Influence of Islet-derived Factors in Islet Microcirculation and Endocrine Function
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Diabetes mellitus is a disorder with complex pathology and is frequently associated with vascular complications. In the islet micro milieu locally generated factors may affect both the physiology and the morphology of the tissue. This thesis examines the impact of four different islet-derived factors; thrombospondin-1 (TSP-1), ghrelin, Cocaine and amphetamine regulated transcript (CART) and irisin, and how they influence the endocrine pancreas.TSP-1 is an angiogenesis inhibitor. Islets from TSP-1 deficient mice were hypervascular, but with normal endocrine mass. Beta-cell dysfunction was present in islets of TSP-1 deficient mice, both in vivo and in vitro. When trying to reconstitute TSP-1 in islets of TSP-1 deficient animals through a transplantation model, adult islets failed to recover, showing the importance of TSP-1 for glucose stimulated insulin secretion and thereby glucose homeostasis.Ghrelin inhibited glucose stimulated insulin secretion and decreased the islet blood flow, while the ghrelin receptor antagonist GHRP-6 in fasted, but not fed, rats increased the islet blood flow fourfold and improved the peak insulin response to glucose. The ghrelin receptor GHS-R1α was identified in the alpha cells and the islet arterioles.CART selectively reduced the islet blood flow in the pancreas, and this effect was unaltered by simultaneous administration of an endothelin-A receptor antagonist. CART administration did not affect insulin release, neither in insulin release from isolated islets or in an intravenous glucose tolerance test. Irisin was confirmed located within the pancreatic islets predominately in the alpha-cells. Irisin reduced islet and white adipose tissue blood flow. Irisin was secreted as a response to increased glucose concentrations in vivo. Irisin had no direct effect on insulin secretion.In conclusion, all factors investigated proved to have roles locally in the endocrine pancreas. TSP-1 deficiency caused vascular morphological alterations, and chronic β-cell dysfunction. Ghrelin, CART and irisin all decreased islet blood flow. Ghrelin acted directly through its receptor GHS-R1α in islet arterioles, thereby restricting the insulin response to hyperglycemia, whereas for CART and irisin the specific mechanism continues to be unknown, without identification of a receptor. In order to reach full physiological understanding, the receptors for CART and irisin need to be identified. All four islet-derived factors hold potential for the treatment of type 2 diabetes.
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| 3. |
- Hagman, Jens, 1984-
(författare)
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Diffusion of Battery Electric Vehicles : The Role of Total Cost of Ownership
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Due to their high efficiency, zero tailpipe emissions and possibilities of using renewable electricity, Battery Electric Vehicles (BEVs) have been proposed as a way to alleviate the negative consequences of transport. However, as with other energy-efficient innovations market uptake or diffusion of BEVs have so far been limited. Three main barriers for BEV diffusion have been identified in the literature: limited range, lack of charging and high purchase price. Range and charging have been extensively studied. The high purchase price and other ownership costs of BEVs has not received the same amount of attention. The focus of this thesis is to go beyond the purchase price of BEVs, that in general is higher than for Internal Combustion Engine Vehicles (ICEVs). This thesis will center on costs; as the low running cost of BEVs validates further investigations regarding the Total Cost of Ownership (TCO) compared to ICEVs. The aim of this thesis is therefore to investigate the TCO of BEVs for both private and professional use-cases relative to the TCO of ICEVs, and further, to explore to which degree TCO is incorporated in the vehicle choice process. The main theoretical underpinnings of this thesis are innovation diffusion theory, a set of theories that describes the process by which an innovation is adopted among the members of a social system. In a narrower consumer behavior setting, rational choice and the emerging literature in behavior economics also forms an important theoretical basis for this thesis. The method choices in the four studies included in this thesis reflects the complex socio-technical system that BEVs inhabits. A mix of quantitative (e.g. surveys and driving data) and qualitative (interviews) methods have been used.The results of Total Cost of Ownership (TCO) computations in this thesis indicate that the actual cost of BEVs can be lower than for equivalent ICEVs. This has been validated for different contexts and use-cases in both private and professional settings. However, the actual TCO of BEVs is likely to have a small influence on vehicle choice. The results indicate that only a small minority (4 %) of mainstream vehicle buyers conducted a complete TCO analysis and that the majority (58 %) did not calculate any ownerships costs into their vehicle choice process. In addition, vehicle buyers have a poor understanding of on-going vehicle ownership costs of their present vehicle. Thus, they are uninformed about vehicle costs in general and of TCO in particular. Calculating TCO is a challenging task for consumers, requiring both cognitive efforts and time. It can be suspected that vehicle buyers instead use purchase price as a proxy for TCO. Approximation of costs through purchase price could yield significant overestimation in the cost of owning and operating a BEV. This thesis argues that the market introduction of BEVs requires a new approach to evaluate vehicle costs among the stakeholders involved. The relationship between high effort costs and unknown ownership cost is radically altered due to the low ownership costs of BEVs. The potential rewards of being attentive to TCO are thus larger in the case of BEVs compared to ICEVs. Several aspects have been found to correlate to being more TCO attentive: higher income, higher educational level, having a larger comparison set of vehicles and increased stated importance of TCO in vehicle choice. However, vehicle buyers receive little assistance from vehiclesalespeople in estimating TCO of BEVs. Vehicle salespeople often focus on purchase price instead of taking the time to estimate TCO. Lower financial incentives for selling BEVs could be an underlying cause for vehicle salespeople not to emphasize the potential cost superiorities of BEVs in relation to ICEVs. In addition, the results allude that additional barriers related to BEV diffusion remains important. This is exemplified in the professional use-case of taxis that was investigated in this thesis, where range and charging limitations of BEVs negatively affected work conditions.Four main conclusions can be drawn based on the results of this thesis: BEVs can be TCO competitive with ICEVs, TCO is rarely applied in the vehicle choice process, the market introduction of BEVs requires a new approach to evaluate vehicle costs among the stakeholders involved, and that improved understanding and application of vehicle TCO would improve the diffusion outlook of BEVs by improving their relative advantage. Based on these conclusions it is recommend that industry and public policy address the apparent misalignment between perceived and actual TCO of BEVs. This can be done by: improving knowledge of TCO among vehicle buyers, creating a comprehensive yet simple to use TCO computational tool and increasing the financial incentives of selling BEVs for vehicle salespeople.
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| 4. |
- Jansson, Johan
(författare)
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Multiscale Constitutive Modeling of Heterogeneous Engineering Materials
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This work deals with different methods used to determine heterogeneous constitutive model parameters for macro-scale finite element models, based on microstructural variations, caused by the manufacturing process. These methods could be applied to decrease modeling errors associated with the material behavior, improving the predictive capabilities of structural analyses in simulation-driven industrial product development. By providing engineers with more sophisticated tools and methods which lets them consider the complex relationships between the manufacturing process, the resulting microstructure and the final properties, manufactured components have the potential to be further optimized with respect to both weight and performance, reducing their cost and environmental impact.An empirical approach for cast components is presented in Papers I & II, where material testing is used as a basis for constitutive model parameter extraction via optimization. Linear models were created for both thermo-mechanical and thermo-physical material properties, by characterizing specimens extracted from different regions in a lamellar graphite cast iron cylinder head. These models were used to generate heterogeneous constitutive model parameters for the cylinder head, based on the solidification time as predicted by casting process simulations. The influence of several commonly made casting-specific engineering simplifications were investigated, and it was shown that non-trivial errors of a potentially large magnitude are introduced by not considering e.g. the compressive behavior of the material, residual stresses from the casting process, the temperature dependency of the material, or the process-induced heterogeneity.Paper III describes a statistical homogenization-based method, for modeling of anisotropic fiber reinforced materials. A non-linear anisotropic constitutive model was developed and implemented in commercial finite element codes, which is able to consider heterogeneous fiber orientations using only one material definition. The anisotropic elastic constitutive tensor is determined from fiber-matrix homogenization, and orientation averaging using second- and fourth order fiber orientation tensors provided by injection molding simulations. The plastic constitutive parameters are determined by optimization against experimental tensile tests using specimens with different fiber orientations. The method was demonstrated using a injection molded 50 wt.% short glass fiber reinforced plastic.A pixel/voxel-based method is presented in Papers IV (2D) & V (3D), for simple and efficient generation of reduced numerical microstructure models using imaging data as input. The input micrograph or image stack is split into subdomains, which are evaluated individually using numerical or semi-analytical homogenization. The constitutive tensor of each subdomain is mapped to a new, reduced numerical model. The purpose of this approach was to support component level analyses, by representing process-induced microstructural imperfections like e.g. porosity on the macro-scale, in a computationally efficient way. The geometrical description of the microstructure can be retrieved from experimental imaging methods like Scanning Electron Microscopy (SEM) or X-ray based Computed Tomography (CT). Alternatively, it can be approximated from phase field or manufacturing process simulations. The method was demonstrated by reducing a 2D aluminium micrograph by 99.89%, with material property errors of less than 0.5% in Paper IV. Also, in paper V by reducing a complex high-resolution 3D aluminum shrinkage porosity by 99.2%, with a material property error of approximately 1%. The method significantly reduces the complexity of building finite element models of complex microstructures, where the pre-processing step is replaced by image segmentation.
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