Making the music dance : dance connotations in Norwegian fiddling

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Influence of the isomeric composition of the acceptor on the performance of organic bulk heterojunction P3HT:bis-PCBM solar cells

We synthesized three isomeric subpopulations of bisadduct analogues of [6,6]-phenyl-C61-butyric acid methyl ester (bis-PCBM) via tether-directed control. Bulk heterojunction solar cells prepared using these isomers together with poly(3-hexylthiophene) (P3HT) resulted in an increase of Jsc from 72.4 to 79.6 A m-2, and an improvement in fill factor from 0.55 to 0.62, both with a Voc of 0.72 V resulting in an overall enhancement of the power conversion efficiency (PCE) from 2.9% to 3.5%, compared to conventional bis-PCBM.

Distributed Branching Bisimulation Minimization by Inductive Signatures

We present a new distributed algorithm for state space minimization modulo branching bisimulation. Like its predecessor it uses signatures for refinement, but the refinement process and the signatures have been optimized to exploit the fact that the input graph contains no tau-loops. The optimization in the refinement process is meant to reduce both the number of iterations needed and the memory requirements. In the former case we cannot prove that there is an improvement, but our experiments show that in many cases the number of iterations is smaller. In the latter case, we can prove that the worst case memory use of the new algorithm is linear in the size of the state space, whereas the old algorithm has a quadratic upper bound. The paper includes a proof of correctness of the new algorithm and the results of a number of experiments that compare the performance of the old and the new algorithms

A comparison of integration methods for atmospheric transport-chemistry problems

This paper is devoted to the time integration of atmospheric transport-chemistry problems. Due to the large number of species and the 3D nature off-the-shelf solvers are not feasible. This has led to the use of special techniques. Most popular is operator splitting. This paper presents a comparison between standard operator splitting, source splitting and approximate matrix factorization. All methods under consideration are comparable in costs measured step wise. The comparison is directed at real-life problems. For that purpose a regional air pollution model is used

Differential diagnosis of (inherited) amino acid metabolism or transport disorders

__Abstract__ Disorders of amino acid metabolism or transport are most clearly expressed in urine. Nevertheless the interpretation of abnormalities in urinary amino acid excretion remains difficult. An increase or decrease of almost every amino acid in urine can be due to various etiology. To differentiate between primary and secondary aminoacido-pathies systematic laboratory investigation is necessary. Early diagnosis of disorders of amino acid metabolism or transport is very important, because most of them can be treated, leading to the prevention of (further) clinical abnormalities. In those disorders, which cannot be treated, early diagnosis in an index-patient may prevent the birth of other siblings by means of genetic counseling and prenatal diagnosis. Primary aminoacidopathies can be due to genetically determined transport disorders and enzyme deficiencies in amino acid metabolism or degradation. Secondary aminoacidopathies are the result of abnormal or deficient nutrition, intestinal dysfunction, organ pathology or other metabolic diseases like organic acidurias. A survey of amino acid metabolism and transport abnormalities will be given, illustrated with metabolic pathways and characteristic abnormal amino acid chromatograms

Mining large-scale smartphone data for personality studies

In this paper, we investigate the relationship between automatically extracted behavioral characteristics derived from rich smartphone data and self-reported Big-Five personality traits (extraversion, agreeableness, conscientiousness, emotional stability and openness to experience). Our data stem from smartphones of 117 Nokia N95 smartphone users, collected over a continuous period of 17months in Switzerland. From the analysis, we show that several aggregated features obtained from smartphone usage data can be indicators of the Big-Five traits. Next, we describe a machine learning method to detect the personality trait of a user based on smartphone usage. Finally, we study the benefits of using gender-specific models for this task. Apart from a psychological viewpoint, this study facilitates further research on the automated classification and usage of personality traits for personalizing services on smartphone

Symbolic Reachability for Process Algebras with Recursive Data Types

Abstract. In this paper, we present a symbolic reachability algorithm for process algebras with recursive data types. Like the various saturation based algorithms of Ciardo et al, the algorithm is based on partitioning of the transition relation into events whose influence is local. As new fea-tures, our algorithm supports recursive data types and allows unbounded non-determinism, which is needed to support open systems with data. The algorithm does not use any specific features of process algebras. That is, it will work for any system that consists of a fixed number of communicating processes, where in each atomic step only a subset of the processes participate. As proof of concept we have implemented the algorithm in the context of the µCRL toolset. We also compared the per-formance of this prototype with the performance of the existing explicit tools on a set of typical case studies.