Incumbency Effects in German and British Elections: A Quasi- Experimental Approach

Following the recent turn towards quasi-experimental approaches in the US literature on the incumbency advantage (Lee, 2001; Lee, forthcoming), we employ a Regression Discontinuity Design (RDD) to identify the causal effects of party incumbency in British and German post-World War II elections. The RDD framework exploits the randomized variation in incumbency status that occurs when a district race is close. Based on the assumption that parties do not exert perfect control over their observed vote shares, incumbents that barely won a race should be similar in their distribution of observed and unobserved confounders to non-incumbents that barely lost. This provides us with a naturally occurring counterfactual exploitable for causal inference under a weaker set of assumptions than conventional regression designs commonly used in the incumbency literature. In both British and German federal elections, we find that party incumbency has a signifcant positive impact on vote shares and the probability of winning in marginal districts, the sub- population of interest for which incumbency advantage is likely to make a difference. This stands in contrast to previous more ambiguous findings.incumbency advantage, quasi-experiment, Germany, Great Britain, elections, causal inference

Linear Elliptic Boundary Value Problems with Non-smooth Data: Normal Solvability on Sobolev-Campanato Spaces

In this paper linear elliptic boundary value problems of second order with non-smooth data (L∞-coefficients, Lipschitz domains, regular sets, non-homogeneous mixed boundary conditions) are considered. It is shown that such boundary value problems generate Fredholm operators between appropriate Sobolev-Campanato spaces, that the weak solutions are Hölder continuous up to the boundary and that they depend smoothly (in the sense of a Hölder norm) on the coefficients and on the right hand sides of the equations and boundary conditions

Local existence, uniqueness, and smooth dependence for nonsmooth quasilinear parabolic problems

A general theory on local existence, uniqueness, regularity, and smooth dependence in Hölder spaces for a general class of quasilinear parabolic initial boundary value problems with nonsmooth data has been developed. As a result the gap between low smoothness of the data, which is typical for many applications, and high smoothness of the solutions, which is necessary for the applicability of differential calculus to the abstract formulations of the initial boundary value problems, has been closed. The main tools are new maximal regularity results of the first author in Sobolev-Morrey spaces, linearization techniques and the Implicit Function Theorem. Typical applications are transport processes of charged particles in semiconductor heterostructures, phase separation processes of nonlocally interacting particles, chemotactic aggregation in heterogeneous environments as well as optimal control by means of quasilinear elliptic and parabolic PDEs with nonsmooth data

Local existence, uniqueness, and smooth dependence for nonsmooth quasilinear parabolic problems

A general theory on local existence, uniqueness, regularity, and smooth dependence in H"older spaces for a general class of quasilinear parabolic initial boundary value problems with nonsmooth data has been developed. As a result the gap between low smoothness of the data, which is typical for many applications, and high smoothness of the solutions, which is necessary for the applicability of differential calculus to the abstract formulations of the initial boundary value problems, has been closed. The main tools are new maximal regularity results of the first author in Sobolev-Morrey spaces, linearization techniques and the Implicit Function Theorem. Typical applications are transport processes of charged particles in semiconductor heterostructures, phase separation processes of nonlocally interacting particles, chemotactic aggregation in heterogeneous environments as well as optimal control by means of quasilinear elliptic and parabolic PDEs with nonsmooth data

Anti-inflammatory treatment strategies for ischemia/reperfusion injury in transplantation

Inflammatory reactions in the graft have a pivotal influence on acute as well as long-term graft function. The main reasons for an inflammatory reaction of the graft tissue are rejection episodes, infections as well as ischemia/reperfusion (I/R) injury. The latter is of particular interest as it affects every solid organ during the process of transplantation. I/R injury impairs acute as well as long-term graft function and is associated with an increased number of acute rejection episodes that again affect long-term graft outcome

El origen del endurecimiento de metales y aleaciones nanoestructurados

14 pages, 8 figures.[EN] Nanostructured metals and alloys have a variety of chemical and physical properties that are greatly modified by the nano-scale of their microstructure. At the same time, these materials generally show very high strength, although ductility or toughness may not be good. Strength increases as the microstructure scale reduces from the macro-micro level and even finer, but sometimes the strength appears to fall as the structure scale approaches the nano level. These strength variations are examined here, and the mechanisms responsible for both strengthening and weakening are discussed. The fall in ductility and toughness as materials become nanostructured is a complex topic that requires extensive analysis, but this will not be treated in the present overview.[ES] Los metales y aleaciones nanoestructuradas muestran una serie de propiedades químicas y físicas fuertemente modificadas cuando su microestructura entra en la escala nano. A la vez, estos materiales muestran generalmente alta resistencia pero mediocre ductilidad o tenacidad. La resistencia aumenta cuando baja la escala de la microestructura desde el nivel micro hacia el nivel nano, pero a veces la resistencia parece reducir por las microestructuras mas finas. Se examinan aquí todas estas variaciones y se discuten los mecanismos responsables del endurecimiento y ablandamiento. Los cambios de ductilidad o tenacidad cuando la microestructura entra en la escala nano necesitan un análisis detallado que no se trata en este articulo.Peer reviewe

Aliquoting structure for centrifugal microfluidics based on a new pneumatic valve

We present a new microvalve that can be monolithically integrated in centrifugally driven lab-on-a-chip systems. In contrast to existing operation principles that use hydrophobic patches, geometrically defined capillary stops or siphons, here we present a pneumatic principle. It needs neither additional local coatings nor expensive micro sized geometries. The valve is controlled by the spinning frequency and can be switched to be open when the centrifugal pressure overcomes the pneumatic pressure inside an unvented reaction cavity. We designed and characterized valves ranging in centrifugal burst pressure from 6700 Pa to 2100 Pa. Based on this valving principle we present a new structure for aliquoting of liquids. We experimentally demonstrated this by splitting 105 muL volumes into 16 aliquots with a volume CV of 3 %

Latent Dirichlet Allocation Uncovers Spectral Characteristics of Drought Stressed Plants

Understanding the adaptation process of plants to drought stress is essential in improving management practices, breeding strategies as well as engineering viable crops for a sustainable agriculture in the coming decades. Hyper-spectral imaging provides a particularly promising approach to gain such understanding since it allows to discover non-destructively spectral characteristics of plants governed primarily by scattering and absorption characteristics of the leaf internal structure and biochemical constituents. Several drought stress indices have been derived using hyper-spectral imaging. However, they are typically based on few hyper-spectral images only, rely on interpretations of experts, and consider few wavelengths only. In this study, we present the first data-driven approach to discovering spectral drought stress indices, treating it as an unsupervised labeling problem at massive scale. To make use of short range dependencies of spectral wavelengths, we develop an online variational Bayes algorithm for latent Dirichlet allocation with convolved Dirichlet regularizer. This approach scales to massive datasets and, hence, provides a more objective complement to plant physiological practices. The spectral topics found conform to plant physiological knowledge and can be computed in a fraction of the time compared to existing LDA approaches.Comment: Appears in Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence (UAI2012

Query optimization by using derivability in a data warehouse environment

Materialized summary tables and cached query results are frequently used for the optimization of aggregate queries in a data warehouse. Query rewriting techniques are incorporated into database systems to use those materialized views and thus avoid the access of the possibly huge raw data. A rewriting is only possible if the query is derivable from these views. Several approaches can be found in the literature to check the derivability and find query rewritings. The specific application scenario of a data warehouse with its multidimensional perspective allows the consideration of much more semantic information, e.g. structural dependencies within the dimension hierarchies and different characteristics of measures. The motivation of this article is to use this information to present conditions for derivability in a large number of relevant cases which go beyond previous approaches