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Graz, Austria

The Graz University of Technology is the second largest university in Styria, Austria, after the University of Graz. Austria has three universities of technology – in Graz, in Leoben, and in Vienna. The Graz University of Technology was founded in 1811 by Archduke John of Austria. TU Graz is a public university. In the academic year 2013/14, 15.9% of the students were from abroad and 22.6% of the students were female out of the 12,565 students enrolled at the TU Graz. Wikipedia.

Schreuer A.,Graz University of Technology
Energy Research and Social Science | Year: 2016

This paper looks at citizen power plants in Austria - wind farms and photovoltaics plants jointly owned and operated by groups of citizens - and asks whether their establishment can be interpreted as a process of empowerment. To this end I draw on resource-based notions of power, understanding empowerment as the increase of disadvantaged actors' ability to mobilize and use resources for their goals. I argue that the establishment of citizen power plants constitutes a process of successive resource mobilization in which bottom-up actors have been able to access an increasing amount of resources. At first sight this suggests that the establishment of citizen power plants in Austria indeed constitutes a process of empowerment. However, I also discuss three qualifications to such an interpretation. Firstly, the modulation of ends to which resources are put (assimilation and incorporation to established structures); secondly, the persistence of dependency relations for resource access; and thirdly, a bias of citizen power plant initiatives toward already better-resourced individuals and communities. © 2015 Elsevier Ltd. All rights reserved. Source

Hergarten S.,Graz University of Technology | Hergarten S.,University of Graz
Physical Review Letters | Year: 2012

A self-organized critical branching process based on a local interaction rule is presented. In accordance with the self-organized branching process model introduced by Zapperi, Lauritsen, and Stanley, its event-size distribution follows a power law with scaling exponent τ=32, but the new model does not require a global variable to self-organize to a critical point. The self-organized critical behavior of the model seems to be extremely robust. The model may be seen as a new paradigm for progressive mechanical failure (e.g., earthquakes or landslides) or other avalanching phenomena, and perhaps even for self-organized criticality in general. Source

Steinbach O.,Graz University of Technology
Computational Mechanics | Year: 2013

In this paper we discuss the use of single and double layer boundary integral equations for the numerical solution of linear elasticity problems with boundary conditions of mixed type, and the one-equation coupling of finite and boundary element methods to solve a free space transmission problem. In particular we present a sufficient and necessary condition which ensures stability of the coupled approach for any choice of finite and boundary elements. These results justify the coupling of collocation and Galerkin one-equation boundary element methods with finite elements as used in many engineering and industrial applications. Hence one may avoid the use of the symmetric formulation of boundary integral equations, which is, although well established from a mathematical point of view and also used in some engineering applications, not so much accepted in particular in industrial applications. © 2012 Springer-Verlag. Source

Wriessnegger T.,Acib Austrian Center of Industrial Biotechnology | Pichler H.,Acib Austrian Center of Industrial Biotechnology | Pichler H.,Graz University of Technology
Progress in Lipid Research | Year: 2013

Terpenoids comprise various structures conferring versatile functions to eukaryotes, for example in the form of prenyl-anchors they attach proteins to membranes. The physiology of eukaryotic membranes is fine-tuned by another terpenoid class, namely sterols. Evidence is accumulating that numerous membrane proteins require specific sterol structural features for function. Moreover, sterols are intermediates in the synthesis of steroids serving as hormones in higher eukaryotes. Like steroids many compounds of the terpenoid family do not contribute to membrane architecture, but serve as signalling, protective or attractant/repellent molecules. Particularly plants have developed a plenitude of terpenoid biosynthetic routes branching off early in the sterol biosynthesis pathway and, thereby, forming one of the largest groups of naturally occurring organic compounds. Many of these aromatic and volatile molecules are interesting for industrial application ranging from foods to pharmaceuticals. Combining the fortunate situation that sterol biosynthesis is highly conserved in eukaryotes with the amenability of yeasts to genetic and metabolic engineering, basically all naturally occurring terpenoids might be produced involving yeasts. Such engineered yeasts are useful for the study of biological functions and molecular interactions of terpenoids as well as for the large-scale production of high-value compounds, which are unavailable in sufficient amounts from natural sources due to their low abundance. © 2013 Elsevier Ltd. All rights reserved. Source

Pock T.,Graz University of Technology | Chambolle A.,French National Center for Scientific Research
Proceedings of the IEEE International Conference on Computer Vision | Year: 2011

In this paper we study preconditioning techniques for the first-order primal-dual algorithm proposed in [5]. In particular, we propose simple and easy to compute diagonal preconditioners for which convergence of the algorithm is guaranteed without the need to compute any step size parameters. As a by-product, we show that for a certain instance of the preconditioning, the proposed algorithm is equivalent to the old and widely unknown alternating step method for monotropic programming [7]. We show numerical results on general linear programming problems and a few standard computer vision problems. In all examples, the preconditioned algorithm significantly outperforms the algorithm of [5]. © 2011 IEEE. Source

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