Mesostructured ZnO/Au nanoparticle composites with enhanced photocatalytic activity

Ease of catalyst separation from reaction mixtures represents a significant advantage in heterogeneous photocatalytic wastewater treatment. However, the activity of the catalyst strongly depends on its surface-to-volume ratio. Here, we present an approach based on cylindrical polybutadiene-block-poly(2-vinylpyridine) polymer brushes as template, which can be simultaneously loaded with zinc oxide (ZnO) and gold (Au) nanoparticles. Pyrolytic template removal of the polymer yields in mesostructured ZnO/Au composites, showing higher efficiencies in the photocatalytic degradation of ciprofloxacin and levofloxacin (generic antibiotics present in clinical wastewater) as compared to neat mesostructured ZnO. Upscaling of the presented catalyst is straightforward promising high technical relevance

The continuous stop location problem in public transportation networks

In this paper we consider the location of stops along the edges of an already existing public transportation network. This can be the introduction of bus stops along some given bus routes, or of railway stations along the tracks in a railway network. The positive effect of new stops is given by the better access of the potential customers to their closest station, while the increasement of travel time caused by the additional stopping activities of the trains leads to a negative effect. The goal is to cover all given demand points with a minimal amount of additional traveling time, where covering may be defined with respect to an arbitrary norm (or even a gauge). Unfortunately, this problem is NP-hard, even if only the Euclidean distance is used. In this paper, we give a reduction to a finite candidate set leading to a discrete set covering problem. Moreover, we identify network structures in which the coefficient matrix of the resulting set covering problem is totally unimodular, and use this result to derive efficient solution approaches. Various extensions of the problem are also discussed

Algorithm Engineering in Robust Optimization

Robust optimization is a young and emerging field of research having received a considerable increase of interest over the last decade. In this paper, we argue that the the algorithm engineering methodology fits very well to the field of robust optimization and yields a rewarding new perspective on both the current state of research and open research directions. To this end we go through the algorithm engineering cycle of design and analysis of concepts, development and implementation of algorithms, and theoretical and experimental evaluation. We show that many ideas of algorithm engineering have already been applied in publications on robust optimization. Most work on robust optimization is devoted to analysis of the concepts and the development of algorithms, some papers deal with the evaluation of a particular concept in case studies, and work on comparison of concepts just starts. What is still a drawback in many papers on robustness is the missing link to include the results of the experiments again in the design

Rotating Stars in Relativity

Rotating relativistic stars have been studied extensively in recent years, both theoretically and observationally, because of the information one could obtain about the equation of state of matter at extremely high densities and because they are considered to be promising sources of gravitational waves. The latest theoretical understanding of rotating stars in relativity is reviewed in this updated article. The sections on the equilibrium properties and on the nonaxisymmetric instabilities in f-modes and r-modes have been updated and several new sections have been added on analytic solutions for the exterior spacetime, rotating stars in LMXBs, rotating strange stars, and on rotating stars in numerical relativity.Comment: 101 pages, 18 figures. The full online-readable version of this article, including several animations, will be published in Living Reviews in Relativity at http://www.livingreviews.org

Coronavirus-Pandemie: Die Feiertage und den Jahreswechsel für einen harten Lockdown nutzen : 7. Ad-hoc-Stellungnahme zr Coronavirus-Pandemie - 08.Dezember 2020

Die gegenwärtige Situation ist nach wie vor ernst und droht sich weiter zu verschärfen. Trotz des seit Anfang November in Deutschland geltenden Teil-Lockdowns sind die Infektionszahlen auf einem sehr hohen Niveau. Jeden Tag sterben mehrere Hundert Menschen. Die Krankenhäuser und insbesondere das medizinische Personal sind bereits jetzt an ihren Grenzen und die Gesundheitsämter überlastet. Um die Kontrolle über das Infektionsgeschehen zurückzuerlangen, empfiehlt die Nationale Akademie der Wissenschaften Leopoldina in der Ad-hoc-Stellungnahme „Coronavirus-Pandemie: Die Feiertage und den Jahreswechsel für einen harten Lockdown nutzen“ ein zweistufiges Vorgehen. Die Rahmenbedingungen ‒ Weihnachtsferien in Bildungseinrichtungen und eingeschränkter Betrieb in vielen Unternehmen und Behörden – bieten die Chance, in der Eindämmung der Pandemie ein großes Stück voranzukommen

Median hyperplanes in normed spaces

In this paper we deal with the location of hyperplanes in n-dimensional normed spaces. If d is a distance measure, our objective is to find a hyperplane H which minimizes f(H) = sum_{m=1}^{M} w_{m}d(x_m,H), where w_m ge 0 are non-negative weights, x_m in R^n, m=1, ... ,M demand points and d(x_m,H)=min_{z in H} d(x_m,z) is the distance from x_m to the hyperplane H. In robust statistics and operations research such an optimal hyperplane is called a median hyperplane. We show that for all distance measures d derived from norms, one of the hyperplanes minimizing f(H) is the affine hull of n of the demand points and, moreover, that each median hyperplane is (ina certain sense) a halving one with respect to the given point set