Versuch der monetären Bewertung ökologischer Leistungen des Biologischen Landbaus im Bereich Grund- und Trinkwasser am Beispiel des Einzugsgebietes der Fernwasserversorgung Mühlviertel/OÖ

Die tatsächlichen oder potentiellen volkswirtschaftlichen (externen) Kosten durch Umweltbelastung der intensiven Landbewirtschaftung werden der Allgemeinheit aufgebürdet, anstatt als Preis- bzw. Kostenfaktor in das betriebliche Rechnungswesen einzugehen. U.a. in Hinblick auf eine Verringerung externer Kosten der Landwirtschaft infolge Grund- und Trinkwasserbelastung wird der Ökologische Landbau als wirksame Alternative diskutiert. Eine Vielzahl wissenschaftlicher Untersuchungen belegt denn auch das hohe Maß an Grundwasserverträglichkeit des Biologischen Landbaus: So wiesen u. a. VEREIJKEN und WIJNANDS (1990),BRANDHUBER und HEGE (1992), MATTHEY (1992), SCHULTE (1996), BERG et al. (1997) sowie SCHLÜTER et al. (1997) deutlich niedrigere Nitratgehalte des Sickerwassers unter biologisch bewirtschafteten Flächen als unter konventionell oder integriert bewirtschafteten Vergleichsflächen nach. Aufgrund der Verringerung der Nitrat- und Vermeidung der Pestizidbelastung von Grund- und Trinkwasser durch Biologischen Landbau ist daher zu prüfen, in welchem Ausmaß durch diese Bewirtschaftungsform externe Kosten eingespart werden können

SPHS: Smoothed Particle Hydrodynamics with a higher order dissipation switch

We present a novel implementation of Smoothed Particle Hydrodynamics (SPHS) that uses the spatial derivative of the velocity divergence as a higher order dissipation switch. Our switch -- which is second order accurate -- detects flow convergence before it occurs. If particle trajectories are going to cross, we switch on the usual SPH artificial viscosity, as well as conservative dissipation in all advected fluid quantities (for example, the entropy). The viscosity and dissipation terms (that are numerical errors) are designed to ensure that all fluid quantities remain single-valued as particles approach one another, to respect conservation laws, and to vanish on a given physical scale as the resolution is increased. SPHS alleviates a number of known problems with `classic' SPH, successfully resolving mixing, and recovering numerical convergence with increasing resolution. An additional key advantage is that -- treating the particle mass similarly to the entropy -- we are able to use multimass particles, giving significantly improved control over the refinement strategy. We present a wide range of code tests including the Sod shock tube, Sedov-Taylor blast wave, Kelvin-Helmholtz Instability, the `blob test', and some convergence tests. Our method performs well on all tests, giving good agreement with analytic expectations.Comment: 21 pages; 15 Figures. Submitted to MNRAS. Comments welcom

Cosmic variance of the local Hubble flow in large-scale cosmological simulations

The increasing precision in the determination of the Hubble parameter has reached a per cent level at which large-scale cosmic flows induced by inhomogeneities of the matter distribution become non-negligible. Here, we use large-scale cosmological N-body simulations to study statistical properties of the local Hubble parameter as measured by local observers. We show that the distribution of the local Hubble parameter depends not only on the scale of inhomogeneities, but also on how one defines the positions of observers in the cosmic web and what reference frame is used. Observers located in random dark matter haloes measure on average lower expansion rates than those at random positions in space or in the centres of cosmic voids, and this effect is stronger from the halo rest frames compared to the cosmic microwave background (CMB) rest frame. We compare the predictions for the local Hubble parameter with observational constraints based on Type Ia supernova (SNIa) and CMB observations. Due to cosmic variance, for observers located in random haloes we show that the Hubble constant determined from nearby SNIa may differ from that measured from the CMB by ±0.8 per cent at 1σ statistical significance. This scatter is too small to significantly alleviate a recently claimed discrepancy between current measurements assuming a flat Λ cold dark matter (ΛCDM) model. However, for observers located in the centres of the largest voids permitted by the standard ΛCDM model, we find that Hubble constant measurements from SNIa would be biased high by 5 per cent, rendering this tension non-existent in this extreme case

On the potential of augmented reality for mathematics teaching with the application cleARmaths

Learning content in mathematics, such as vector geometry, is still predominantly taught in an abstract manner, as the visualization and interaction of three-dimensional problems are limited with classical forms of teaching such as blackboard lessons or exercise sheets. This research article proposes the use of augmented reality (AR) in mathematics education. The proposed approach aims at easing the learning process related to vector geometry currently taught in senior mathematics classes by using intuitive visualization. The article introduces the concept of AR and presents the didactic foundations and the influence on the learning process based on an extensive literature review. Although studies see great potential in the use of AR for teaching mathematics, the method has so far hardly been used in schools. This can be mainly explained by the technological entry barrier of AR and the lack of simple, robust AR applications, in particular for vector geometry. To fill this gap, the authors developed “cleARmaths”, a developed android application for augmented reality-based teaching in vector geometry that allows widespread use. As a didactical concept, some example exercises sessions with the app are proposed, demonstrating how the app could be used in a mathematics classroom. Finally, the app was evaluated in a mathematics class and the results analyzed in a detailed study. It was found by the teacher and students to be beneficial and amusing, demonstrating the potential for AR in mathematics classes

Simulating Turbulence Using the Astrophysical Discontinuous Galerkin Code TENET

In astrophysics, the two main methods traditionally in use for solving the Euler equations of ideal fluid dynamics are smoothed particle hydrodynamics and finite volume discretization on a stationary mesh. However, the goal to efficiently make use of future exascale machines with their ever higher degree of parallel concurrency motivates the search for more efficient and more accurate techniques for computing hydrodynamics. Discontinuous Galerkin (DG) methods represent a promising class of methods in this regard, as they can be straightforwardly extended to arbitrarily high order while requiring only small stencils. Especially for applications involving comparatively smooth problems, higher-order approaches promise significant gains in computational speed for reaching a desired target accuracy. Here, we introduce our new astrophysical DG code TENET designed for applications in cosmology, and discuss our first results for 3D simulations of subsonic turbulence. We show that our new DG implementation provides accurate results for subsonic turbulence, at considerably reduced computational cost compared with traditional finite volume methods. In particular, we find that DG needs about 1.8 times fewer degrees of freedom to achieve the same accuracy and at the same time is more than 1.5 times faster, confirming its substantial promise for astrophysical applications.Comment: 21 pages, 7 figures, to appear in Proceedings of the SPPEXA symposium, Lecture Notes in Computational Science and Engineering (LNCSE), Springe

Block-Diagonalization of Operators with Gaps, with Applications to Dirac Operators

We present new results on the block-diagonalization of Dirac operators on three-dimensional Euclidean space with unbounded potentials. Classes of admissible potentials include electromagnetic potentials with strong Coulomb singularities and more general matrix-valued potentials, even non-self-adjoint ones. For the Coulomb potential, we achieve an exact diagonalization up to nuclear charge Z=124 and prove the convergence of the Douglas-Kroll-He\ss\ approximation up to Z=62, thus improving the upper bounds Z=93 and Z=51, respectively, by H.\ Siedentop and E.\ Stockmeyer considerably. These results follow from abstract theorems on perturbations of spectral subspaces of operators with gaps, which are based on a method of H.\ Langer and C.\ Tretter and are also of independent interest

Machine learning for emergent middleware

Highly dynamic and heterogeneous distributed systems are challenging today's middleware technologies. Existing middleware paradigms are unable to deliver on their most central promise, which is offering interoperability. In this paper, we argue for the need to dynamically synthesise distributed system infrastructures according to the current operating environment, thereby generating "Emergent Middleware'' to mediate interactions among heterogeneous networked systems that interact in an ad hoc way. The paper outlines the overall architecture of Enablers underlying Emergent Middleware, and in particular focuses on the key role of learning in supporting such a process, spanning statistical learning to infer the semantics of networked system functions and automata learning to extract the related behaviours of networked systems