N-body simulations of gravitational dynamics

We describe the astrophysical and numerical basis of N-body simulations, both of collisional stellar systems (dense star clusters and galactic centres) and collisionless stellar dynamics (galaxies and large-scale structure). We explain and discuss the state-of-the-art algorithms used for these quite different regimes, attempt to give a fair critique, and point out possible directions of future improvement and development. We briefly touch upon the history of N-body simulations and their most important results.Comment: invited review (28 pages), to appear in European Physics Journal Plu

Identification of a multiplex biomarker panel for hypertrophic cardiomyopathy using quantitative proteomics and machine learning

Hypertrophic cardiomyopathy (HCM) is defined by pathological left ventricular hypertrophy (LVH). It is the commonest inherited cardiac condition and a significant number of high risk cases still go undetected until a sudden cardiac death (SCD) event. Plasma biomarkers do not currently feature in the assessment of HCM disease progression, which is tracked by serial imaging, or in SCD risk stratification, which is based on imaging parameters and patient/family history. There is a need for new HCM plasma biomarkers to refine disease monitoring and improve patient risk stratification. To identify new plasma biomarkers for patients with HCM, we performed exploratory myocardial and plasma proteomics screens and subsequently developed a multiplexed targeted liquid chromatography-tandem/mass spectrometry-based assay to validate the 26 peptide biomarkers that were identified. The association of discovered biomarkers with clinical phenotypes was prospectively tested in plasma from 110 HCM patients with LVH (LVH+ HCM), 97 controls, and 16 HCM sarcomere gene mutation carriers before the development of LVH (subclinical HCM). Six peptides (aldolase fructose-bisphosphate A, complement C3, glutathione S-transferase omega 1, Ras suppressor protein 1, talin 1, and thrombospondin 1) were increased significantly in the plasma of LVH+ HCM compared with controls and correlated with imaging markers of phenotype severity: LV wall thickness, mass, and percentage myocardial scar on cardiovascular magnetic resonance imaging. Using supervised machine learning (ML), this six-biomarker panel differentiated between LVH+ HCM and controls, with an area under the curve of ≥ 0.87. Five of these peptides were also significantly increased in subclinical HCM compared with controls. In LVH+ HCM, the six-marker panel correlated with the presence of nonsustained ventricular tachycardia and the estimated five-year risk of sudden cardiac death. Using quantitative proteomic approaches, we have discovered six potentially useful circulating plasma biomarkers related to myocardial substrate changes in HCM, which correlate with the estimated sudden cardiac death risk

Intra‐clinothem variability in sedimentary texture and process regime recorded down slope profiles

Shelf‐margin clinothem successions can archive process interactions at the shelf to slope transition, and their architecture provides constraints on the interplay of factors that control basin‐margin evolution. However, detailed textural analysis and facies distributions from shelf to slope transitions remain poorly documented. This study uses quantitative grain‐size and sorting data from coeval shelf and slope deposits of a single clinothem that crops out along a 5 km long, dip‐parallel transect of the Eocene Sobrarbe Deltaic Complex (Ainsa Basin, south‐central Pyrenees, Spain). Systematic sampling of sandstone beds tied to measured sections has captured vertical and basinward changes in sedimentary texture and facies distributions at an intra‐clinothem scale. Two types of hyperpycnal flow‐related slope deposits, both rich in mica and terrestrial organic matter, are differentiated according to grain size, sorting and bed geometry: (i) sustained hyperpycnal flow deposits, which are physically linked to coarse channelized sediments in the shelf setting and which deposit sand down the complete slope profile; (ii) episodic hyperpycnal flow deposits, which are disconnected from, and incise into, shelf sands and which are associated with sediment bypass of the proximal slope and coarse‐grained sand deposition on the medial and distal slope. Both types of hyperpycnites are interbedded with relatively homogenous, organic‐free and mica‐free, well‐sorted, very fine‐grained sandstones, which are interpreted to be remobilized from wave‐dominated shelf environments; these wave‐dominated deposits are found only on the proximal and medial slope. Coarse‐grained sediment bypass into the deeper‐water slope settings is therefore dominated by episodic hyperpycnal flows, whilst sustained hyperpycnal flows and turbidity currents remobilizing wave‐dominated shelf deposits are responsible for the full range of grain sizes in the proximal and medial slope, thus facilitating clinoform progradation. This novel dataset highlights previously undocumented intra‐clinothem variability related to updip changes in the shelf process‐regime, which is therefore a key factor controlling downdip architecture and resulting sedimentary texture

Multiscale Computing in the Exascale Era

We expect that multiscale simulations will be one of the main high performance computing workloads in the exascale era. We propose multiscale computing patterns as a generic vehicle to realise load balanced, fault tolerant and energy aware high performance multiscale computing. Multiscale computing patterns should lead to a separation of concerns, whereby application developers can compose multiscale models and execute multiscale simulations, while pattern software realises optimized, fault tolerant and energy aware multiscale computing. We introduce three multiscale computing patterns, present an example of the extreme scaling pattern, and discuss our vision of how this may shape multiscale computing in the exascale era

Search for jet extinction in the inclusive jet-pT spectrum from proton-proton collisions at s=8 TeV

Published by the American Physical Society under the terms of the Creative Commons Attribution 3.0 License. Further distribution of this work must maintain attribution to the author(s) and the published articles title, journal citation, and DOI.The first search at the LHC for the extinction of QCD jet production is presented, using data collected with the CMS detector corresponding to an integrated luminosity of 10.7  fb−1 of proton-proton collisions at a center-of-mass energy of 8 TeV. The extinction model studied in this analysis is motivated by the search for signatures of strong gravity at the TeV scale (terascale gravity) and assumes the existence of string couplings in the strong-coupling limit. In this limit, the string model predicts the suppression of all high-transverse-momentum standard model processes, including jet production, beyond a certain energy scale. To test this prediction, the measured transverse-momentum spectrum is compared to the theoretical prediction of the standard model. No significant deficit of events is found at high transverse momentum. A 95% confidence level lower limit of 3.3 TeV is set on the extinction mass scale

Mouse Chromosome 11

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46996/1/335_2004_Article_BF00648429.pd

The James Webb Space Telescope mission

Instrumentatio

YIELD OF SPRING WHEAT IN RELATION TO LEVEL OF INFESTATION BY GREENBUGS (HOMOPTERA: APHIDIDAE)

AbstractThe effect of greenbug, Schizaphis graminum (Rondani), infestations on yield components of early- and late-planted spring wheat, Triticum aestivum L., were measured in 2 successive years in eastern South Dakota. Greenbug populations in plots generally increased rapidly and peaked when wheat plants were in boot stage. Populations then began a steady decrease until anthesis, at which time they were near zero. The number of seeds per spikelet and the number of spikelets per square metre were consistently significantly negatively correlated with aphid-days, whereas average seed weight was significantly negatively correlated with aphid-days for only one planting. A linear regression model that included different intercepts for each spring wheat planting and a common slope relating yield to greenbug feeding days (aphid-days) provided a good fit to the data. Based on the model, a loss of 41 kg of grain per hectare is expected for each 100 aphid-days that accumulate per tiller.</jats:p