Target Capital Structure Determinants and Speed of Adjustment Analysis to Address the Keynes-Hayek Debate

According to F. A. Hayek, Keynes' General Theory neglects an analysis of the production structure. As a contribution to this research gap, we look at companies' decisions to finance investments and at their agility to adjust their capital structure. We thus study the relationship between capital structure to finance corporate production and shifts in aggregate demand. Target capital structure determinants and speeds of adjustment to these target capital structures will be analyzed for a geographically comprehensive sample of 2,706 companies listed in Asia, Europe and the U.S.A. in the period 1995 – 2009. Aggregate demand turns out to be the coordinating force which determines managers' choices of target capital structures. The speed of adjustments towards target capital structures indicate that firms are agile in adapting to their targets. Our results provide evidence on Keynes' General Theory from a firm level perspective: Firms respond quickly to shifts in aggregate demand by adjusting capital and production structure correspondingly

A Bramble-Pasciak conjugate gradient method for discrete Stokes equations with random viscosity

We study the iterative solution of linear systems of equations arising from stochastic Galerkin finite element discretizations of saddle point problems. We focus on the Stokes model with random data parametrized by uniformly distributed random variables and discuss well-posedness of the variational formulations. We introduce a Bramble-Pasciak conjugate gradient method as a linear solver. It builds on a non-standard inner product associated with a block triangular preconditioner. The block triangular structure enables more sophisticated preconditioners than the block diagonal structure usually applied in MINRES methods. We show how the existence requirements of a conjugate gradient method can be met in our setting. We analyze the performance of the solvers depending on relevant physical and numerical parameters by means of eigenvalue estimates. For this purpose, we derive bounds for the eigenvalues of the relevant preconditioned sub-matrices. We illustrate our findings using the flow in a driven cavity as a numerical test case, where the viscosity is given by a truncated Karhunen-Lo\`eve expansion of a random field. In this example, a Bramble-Pasciak conjugate gradient method with block triangular preconditioner outperforms a MINRES method with block diagonal preconditioner in terms of iteration numbers.Comment: 19 pages, 1 figure, submitted to SIAM JU

Ein nüchternes Theoriemodell für religiöse Gefühle? : Gernot Böhmes Atmosphärekonzept als pastoraltheologisches Theorie-Werkzeug

Wahrnehmungen und Gefühle, die von religiösen Menschen durch Modelle mit Bezug zu ihrem jeweiligen Bekenntnissystem gedeutet werden, werden möglicherweise auch von anderen Menschen empfunden, ohne dass dabei entsprechende Deutungskategorien zum Einsatz kommen. Diese Erfahrungen müssen also auch ohne theologischen bzw. theologalen Bezug erschlossen werden können. Die von Gernot Böhme entwickelte Atmosphäre-Theorie kann dabei ein hilfreiches Mittel sein, das auch zur kritischen Betrachtung der religiösen Deutung etwas beizutragen hat. Perceptions and feelings that are interpreted by religious persons through modelling with reference to their confessional system may also be felt by other people without the use of those interpretive categories. It must therefore be possible to understand these experiences without theological reference or the idea of transcendence. The theory of atmosphere developed by Gernot Böhme can be a helpful tool here, which also contributes to the critical consideration of religious paradigm

POD model order reduction with space-adapted snapshots for incompressible flows

We consider model order reduction based on proper orthogonal decomposition (POD) for unsteady incompressible Navier-Stokes problems, assuming that the snapshots are given by spatially adapted finite element solutions. We propose two approaches of deriving stable POD-Galerkin reduced-order models for this context. In the first approach, the pressure term and the continuity equation are eliminated by imposing a weak incompressibility constraint with respect to a pressure reference space. In the second approach, we derive an inf-sup stable velocity-pressure reduced-order model by enriching the velocity reduced space with supremizers computed on a velocity reference space. For problems with inhomogeneous Dirichlet conditions, we show how suitable lifting functions can be obtained from standard adaptive finite element computations. We provide a numerical comparison of the considered methods for a regularized lid-driven cavity problem

Who am I talking with? A face memory for social robots

In order to provide personalized services and to develop human-like interaction capabilities robots need to rec- ognize their human partner. Face recognition has been studied in the past decade exhaustively in the context of security systems and with significant progress on huge datasets. However, these capabilities are not in focus when it comes to social interaction situations. Humans are able to remember people seen for a short moment in time and apply this knowledge directly in their engagement in conversation. In order to equip a robot with capabilities to recall human interlocutors and to provide user- aware services, we adopt human-human interaction schemes to propose a face memory on the basis of active appearance models integrated with the active memory architecture. This paper presents the concept of the interactive face memory, the applied recognition algorithms, and their embedding into the robot’s system architecture. Performance measures are discussed for general face databases as well as scenario-specific datasets