Efficient parallel generation of partitioned, unstructured meshes

In this paper we introduce a method for generating unstructured meshes in parallel which are partitioned in a ‘good’ way. When solving a partial differential equation on a parallel distributed memory machine, the mesh should be decomposed so that the communication requirement of the numerical solver is minimised and also the amount of work to be performed on each processor is approximately equal. Most previous work in this area has concentrated on partitioning a mesh that has already been generated. We introduce a method which actually generates the partitioned mesh in parallel whilst producing a good quality decomposition and compare this method with other approaches

Rational Design of Mechanism-Based Inhibitors and Activity-Based Probes for the Identification of Retaining α-l-Arabinofuranosidases

Identifying and characterizing the enzymes responsible for an observed activity within a complex eukaryotic catabolic system remains one of the most significant challenges in the study of biomass-degrading systems. The debranching of both complex hemicellulosic and pectinaceous polysaccharides requires the production of α-l-arabinofuranosidases among a wide variety of coexpressed carbohydrate-active enzymes. To selectively detect and identify α-l-arabinofuranosidases produced by fungi grown on complex biomass, potential covalent inhibitors and probes which mimic α-l-arabinofuranosides were sought. The conformational free energy landscapes of free α-l-arabinofuranose and several rationally designed covalent α-l-arabinofuranosidase inhibitors were analyzed. A synthetic route to these inhibitors was subsequently developed based on a key Wittig-Still rearrangement. Through a combination of kinetic measurements, intact mass spectrometry, and structural experiments, the designed inhibitors were shown to efficiently label the catalytic nucleophiles of retaining GH51 and GH54 α-l-arabinofuranosidases. Activity-based probes elaborated from an inhibitor with an aziridine warhead were applied to the identification and characterization of α-l-arabinofuranosidases within the secretome of A. niger grown on arabinan. This method was extended to the detection and identification of α-l-arabinofuranosidases produced by eight biomass-degrading basidiomycete fungi grown on complex biomass. The broad applicability of the cyclophellitol-derived activity-based probes and inhibitors presented here make them a valuable new tool in the characterization of complex eukaryotic carbohydrate-degrading systems and in the high-throughput discovery of α-l-arabinofuranosidases

Testing the predictability of morphological evolution in contrasting thermal environments

Gaining the ability to predict population responses to climate change is a pressing concern. Using a “natural experiment,” we show that testing for divergent evolution in wild populations from contrasting thermal environments provides a powerful approach, and likely an enhanced predictive power for responses to climate change. Specifically, we used a unique study system in Iceland, where freshwater populations of threespine sticklebacks (Gasterosteus aculeatus) are found in waters warmed by geothermal activity, adjacent to populations in ambient-temperature water. We focused on morphological traits across six pairs from warm and cold habitats. We found that fish from warm habitats tended to have a deeper mid-body, a subterminally orientated jaw, steeper craniofacial profile, and deeper caudal region relative to fish from cold habitats. Our common garden experiment showed that most of these differences were heritable. Population age did not appear to influence the magnitude or type of thermal divergence, but similar types of divergence between thermal habitats were more prevalent across allopatric than sympatric population pairs. These findings suggest that morphological divergence in response to thermal habitat, despite being relatively complex and multivariate, are predictable to a degree. Our data also suggest that the potential for migration of individuals between different thermal habitats may enhance nonparallel evolution and reduce our ability to predict responses to climate change

The Majorana Neutrinoless Double-Beta Decay Experiment

The proposed Majorana double-beta decay experiment is based on an array of segmented intrinsic Ge detectors with a total mass of 500 kg of Ge isotopically enriched to 86% in 76Ge. A discussion is given of background reduction by: material selection, detector segmentation, pulse shape analysis, and electro-formation of copper parts and granularity. Predictions of the experimental sensitivity are given. For an experimental running time of 10 years over the construction and operation of Majorana, a half-life sensitivity of ~4x10^27 y (neutrinoless) is predicted. This corresponds to an effective Majorana mass of the electron neutrino of ~0.03-0.04 eV, according to recent QRPA and RQRPA matrix element calculations.Comment: 10 pages, 7 figure

Manifesto of computational social science

The increasing integration of technology into our lives has created unprecedented volumes of data on society's everyday behaviour. Such data opens up exciting new opportunities to work towards a quantitative understanding of our complex social systems, within the realms of a new discipline known as Computational Social Science. Against a background of financial crises, riots and international epidemics, the urgent need for a greater comprehension of the complexity of our interconnected global society and an ability to apply such insights in policy decisions is clear. This manifesto outlines the objectives of this new scientific direction, considering the challenges involved in it, and the extensive impact on science, technology and society that the success of this endeavour is likely to bring about.The publication of this work was partially supported by the European Union’s Seventh Framework Programme (FP7/2007–2013) under grant agreement No. 284709, a Coordination and Support Action in the Information and Communication Technologies activity area (‘FuturICT’ FET Flagship Pilot Project). We are grateful to the anonymous reviewers for the insightful comments.Publicad

Novel genetic loci associated with hippocampal volume

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (rg =-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness