Johannes Kepler University of Linz

About: Johannes Kepler University of Linz is a education organization based out in Linz, Oberösterreich, Austria. It is known for research contribution in the topics: Computer science & Thin film. The organization has 6605 authors who have published 19243 publications receiving 385667 citations.

Cholesterol modulates Orai1 channel function

Abstract: STIM1 (stromal interaction molecule 1) and Orai proteins are the essential components of Ca(2+) release-activated Ca(2+) (CRAC) channels. We focused on the role of cholesterol in the regulation of STIM1-mediated Orai1 currents. Chemically induced cholesterol depletion enhanced store-operated Ca(2+) entry (SOCE) and Orai1 currents. Furthermore, cholesterol depletion in mucosal-type mast cells augmented endogenous CRAC currents, which were associated with increased degranulation, a process that requires calcium influx. Single point mutations in the Orai1 amino terminus that would be expected to abolish cholesterol binding enhanced SOCE to a similar extent as did cholesterol depletion. The increase in Orai1 activity in cells expressing these cholesterol-binding-deficient mutants occurred without affecting the amount in the plasma membrane or the coupling of STIM1 to Orai1. We detected cholesterol binding to an Orai1 amino-terminal fragment in vitro and to full-length Orai1 in cells. Thus, our data showed that Orai1 senses the amount of cholesterol in the plasma membrane and that the interaction of Orai1 with cholesterol inhibits its activity, thereby limiting SOCE.

A critical-pair/completion algorithm for finitely generated ideals in rings

Abstract: In 1965, the author introduced a "critical-pair/completion" algorithm that starts from a finite set F of polynomials in K[x1,...,xn] (K a field) and produces a set G of polynomials such that the ideals generated by F and G are identical, but G is in a certain standard form (G is a "Grobner-basis"), for which a number of important decision and computability problems in polynomial ideal theory can be solved elegantly. In this paper, it is shown how the critical-pair/completion approach can be extended to general rings. One of the difficulties lies in the fact that, in general, the generators of an ideal in a ring do not naturally decompose into a "head" and a "rest" (left-hand side and right-hand side). Thus, the crucial notions of "reduction" and "critical pair" must be formulated in a new way that does not depend on any "rewrite" nature of the generators. The solution of this problem is the starting point of the paper. Furthermore, a set of reduction axioms is given, under which the correctness of the algorithm can be proven and which are preserved when passing from a ring R to the polynomial ring R[x1,...,,xn]. Z[x1,...,xn] is an important example of a ring in which the critical-pair/completion approach is possible.

Bearingless Segment Motor With Five Stator Elements—Design and Optimization

Abstract: Bearingless motors and active magnetic bearings work completely contactless and wearless. With these properties, hermetically sealed and lubricant-free rotating systems for various applications can be designed. It is possible to stabilize three degrees of freedom by reluctance forces when a permanent-magnet excited rotor disc is used. Hence, only the remaining three degrees of freedom are actively controlled. A subtype of this constructional design called bearingless slice motor is the bearingless segment motor. This paper comprises the design process of a bearingless segment motor with five equal stator elements and concentrated windings. Finite-element simulations are applied to maximize the bearing forces and the motor torque per ampere and minimize the reluctance forces. However, the mathematical model of the system is nonlinear, therefore, an appropriate nonlinear control scheme has to be applied to put the system into operation. The introduction of a prototype, together with first measurements, completes the paper.

On Landweber iteration for nonlinear ill-posed problems in Hilbert scales

Abstract: In this paper we derive convergence rates results for Landweber iteration in Hilbert scales in terms of the iteration index \(k\) for exact data and in terms of the noise level \(\delta\) for perturbed data. These results improve the one obtained recently for Landweber iteration for nonlinear ill-posed problems in Hilbert spaces. For numerical computations we have to approximate the nonlinear operator and the infinite-dimensional spaces by finite-dimensional ones. We also give a convergence analysis for this finite-dimensional approximation. The conditions needed to obtain the rates are illustrated for a nonlinear Hammerstein integral equation. Numerical results are presented confirming the theoretical ones.

Deep Linear Discriminant Analysis

Abstract: We introduce Deep Linear Discriminant Analysis (DeepLDA) which learns linearly separable latent representations in an end-to-end fashion. Classic LDA extracts features which preserve class separability and is used for dimensionality reduction for many classification problems. The central idea of this paper is to put LDA on top of a deep neural network. This can be seen as a non-linear extension of classic LDA. Instead of maximizing the likelihood of target labels for individual samples, we propose an objective function that pushes the network to produce feature distributions which: (a) have low variance within the same class and (b) high variance between different classes. Our objective is derived from the general LDA eigenvalue problem and still allows to train with stochastic gradient descent and back-propagation. For evaluation we test our approach on three different benchmark datasets (MNIST, CIFAR-10 and STL-10). DeepLDA produces competitive results on MNIST and CIFAR-10 and outperforms a network trained with categorical cross entropy (same architecture) on a supervised setting of STL-10.