Using internet search data as economic indicators

Data on the volume of online searches can be used as indicators of economic activity. This article examines the use of these data for labour and housing markets in the United Kingdom. These data provide some additional information relative to existing surveys. And with further development, internet search data could become an important tool for economic analysis.

Artificial grass: A conceptual model for degradation in performance

AbstractArtificial grass pitches (AGPs), with long fibres and sand and rubber infill, have seen growth within many sports at both professional and community levels. Academic research has tended to focus on athleticism, injuries and the development of equipment and test standards, while research and development for the turf, infill and shockpad layers has generally been undertaken by the manufacturers. This has led to an under researching and / or reporting of the factors influencing AGP degradation and the subsequent effects on pitch performance. Long term testing has shown that as rubber filled AGPs age their performance worsens; they generally become harder and play faster with ball roll often reported as one of the first standards to be affected. This paper presents a hypothesised model to describe the numerous factors causing degradation and their effects on performance. It is designed as a useful tool for research aimed at assessing and improving current maintenance operations which will ultimately lead to increasing the useful life of AGPs

Intercomparison of long-term sea surface temperature analyses using the GHRSST Multi-Product Ensemble (GMPE) system

Six global, gridded, gap-free, daily sea surface temperature (SST) analyses covering a period of at least 20 years have been intercompared: ESA SST CCI anal- ysis long-term product v1.0, MyOcean OSTIA reanalysis v1.0, CMC 0.2 degree, AVHRR ONLY Daily 1/4 degree OISST v2.0, HadISST2.1.0.0 and MGDSST. A seventh SST product of the ensemble median of all six has also been produced using the GMPE (Group for High Resolution SST Multi-Product Ensemble) sys- tem. Validation against independent near-surface Argo data, a long timeseries of moored buoy data from the tropics and anomalies to the GMPE median have been used to examine the temporal and spatial homogeneity of the analyses. A comparison of the feature resolution of the analyses has also been undertaken. A summary of relative strengths and weaknesses of the SST datasets is presented, intended to help users to make an informed choice of which analysis is most suitable for their proposed application

The Atacama Cosmology Telescope: Detection or Sunyaev-Zel'Dovich Decrement in Groups and Clusters Associated with Luminous Red Galaxies

We present a detection of the Sunyaev-Zel'dovich (SZ) decrement associated with the Luminous Red Galaxy (LRG) sample of the Sloan Digital Sky Survey. The SZ data come from 148 GHz maps of the equatorial region made by the Atacama Cosmology Telescope (ACT). The LRG sample is divided by luminosity into four bins, and estimates for the central Sunyaev-Zel'dovich temperature decrement are calculated through a stacking process. We detect and account for a bias of the SZ signal due to weak radio sources. We use numerical simulations to relate the observed decrement to Y(sub 200) and clustering properties to relate the galaxy luminosity bins to mass. We also use a relation between BCG luminosity and cluster mass based on stacked gravitational lensing measurements to estimate the characteristic halo masses. The masses are found to be in the range approx.10(exp 13) - 10(exp 14)/h Stellar Mass, a lower range than has been previously probed

The Atacama Cosmology Telescope: Cosmological parameters from three seasons of data

We present constraints on cosmological and astrophysical parameters from high-resolution microwave background maps at 148 GHz and 218 GHz made by the Atacama Cosmology Telescope (ACT) in three seasons of observations from 2008 to 2010. A model of primary cosmological and secondary foreground parameters is fit to the map power spectra and lensing deflection power spectrum, including contributions from both the thermal Sunyaev-Zeldovich (tSZ) effect and the kinematic Sunyaev-Zeldovich (kSZ) effect, Poisson and correlated anisotropy from unresolved infrared sources, radio sources, and the correlation between the tSZ effect and infrared sources. The power ell^2 C_ell/2pi of the thermal SZ power spectrum at 148 GHz is measured to be 3.4 +\- 1.4 muK^2 at ell=3000, while the corresponding amplitude of the kinematic SZ power spectrum has a 95% confidence level upper limit of 8.6 muK^2. Combining ACT power spectra with the WMAP 7-year temperature and polarization power spectra, we find excellent consistency with the LCDM model. We constrain the number of effective relativistic degrees of freedom in the early universe to be Neff=2.79 +\- 0.56, in agreement with the canonical value of Neff=3.046 for three massless neutrinos. We constrain the sum of the neutrino masses to be Sigma m_nu < 0.39 eV at 95% confidence when combining ACT and WMAP 7-year data with BAO and Hubble constant measurements. We constrain the amount of primordial helium to be Yp = 0.225 +\- 0.034, and measure no variation in the fine structure constant alpha since recombination, with alpha/alpha0 = 1.004 +/- 0.005. We also find no evidence for any running of the scalar spectral index, dns/dlnk = -0.004 +\- 0.012.Comment: 26 pages, 22 figures. This paper is a companion to Das et al. (2013) and Dunkley et al. (2013). Matches published JCAP versio

The Atacama Cosmology Telescope: Detection of Sunyaev-Zel'dovich Decrement in Groups and Clusters Associated with Luminous Red Galaxies

We present a detection of the Sunyaev-Zel'dovich (SZ) decrement associated with the Luminous Red Galaxy (LRG) sample of the Sloan Digital Sky Survey. The SZ data come from 148 GHz maps of the equatorial region made by the Atacama Cosmology Telescope (ACT). The LRG sample is divided by luminosity into four bins, and estimates for the central Sunyaev-Zel'dovich temperature decrement are calculated through a stacking process. We detect and account for a bias of the SZ signal due to weak radio sources. We use numerical simulations to relate the observed decrement to Y200 and clustering properties to relate the galaxy luminosity bins to mass. We also use a relation between brightest cluster galaxy luminosity and cluster mass based on stacked gravitational lensing measurements to estimate the characteristic halo masses. The masses are found to be around 1e14 M_sun.Comment: Accepted in ApJ. 14 pages, 6 figure

Targeted genetic analysis in a large cohort of familial and sporadic cases of aneurysm or dissection of the thoracic aorta

PURPOSE: Thoracic aortic aneurysm/aortic dissection (TAAD) is a disorder with highly variable age of onset and phenotype. We sought to determine the prevalence of pathogenic variants in TAAD-associated genes in a mixed cohort of sporadic and familial TAAD patients and identify relevant genotype–phenotype relationships. METHODS: We used a targeted polymerase chain reaction and next-generation sequencing–based panel for genetic analysis of 15 TAAD-associated genes in 1,025 unrelated TAAD cases. RESULTS: We identified 49 pathogenic or likely pathogenic (P/LP) variants in 47 cases (4.9% of those successfully sequenced). Almost half of the variants were in nonsyndromic cases with no known family history of aortic disease. Twenty-five variants were within FBN1 and two patients were found to harbor two P/LP variants. Presence of a related syndrome, younger age at presentation, family history of aortic disease, and involvement of the ascending aorta increased the risk of carrying a P/LP variant. CONCLUSION: Given the poor prognosis of TAAD that is undiagnosed prior to acute rupture or dissection, genetic analysis of both familial and sporadic cases of TAAD will lead to new diagnoses, more informed management, and possibly reduced mortality through earlier, preclinical diagnosis in genetically determined cases and their family members

Fine mapping of type 1 diabetes susceptibility loci and evidence for colocalization of causal variants with lymphoid gene enhancers.

Genetic studies of type 1 diabetes (T1D) have identified 50 susceptibility regions, finding major pathways contributing to risk, with some loci shared across immune disorders. To make genetic comparisons across autoimmune disorders as informative as possible, a dense genotyping array, the Immunochip, was developed, from which we identified four new T1D-associated regions (P < 5 × 10(-8)). A comparative analysis with 15 immune diseases showed that T1D is more similar genetically to other autoantibody-positive diseases, significantly most similar to juvenile idiopathic arthritis and significantly least similar to ulcerative colitis, and provided support for three additional new T1D risk loci. Using a Bayesian approach, we defined credible sets for the T1D-associated SNPs. The associated SNPs localized to enhancer sequences active in thymus, T and B cells, and CD34(+) stem cells. Enhancer-promoter interactions can now be analyzed in these cell types to identify which particular genes and regulatory sequences are causal.This research uses resources provided by the Type 1 Diabetes Genetics Consortium, a collaborative clinical study sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), the National Institute of Allergy and Infectious Diseases (NIAID), the National Human Genome Research Institute (NHGRI), the National Institute of Child Health and Human Development (NICHD) and JDRF and supported by grant U01 DK062418 from the US National Institutes of Health. Further support was provided by grants from the NIDDK (DK046635 and DK085678) to P.C. and by a joint JDRF and Wellcome Trust grant (WT061858/09115) to the Diabetes and Inflammation Laboratory at Cambridge University, which also received support from the NIHR Cambridge Biomedical Research Centre. ImmunoBase receives support from Eli Lilly and Company. C.W. and H.G. are funded by the Wellcome Trust (089989). The Cambridge Institute for Medical Research (CIMR) is in receipt of a Wellcome Trust Strategic Award (100140). We gratefully acknowledge the following groups and individuals who provided biological samples or data for this study. We obtained DNA samples from the British 1958 Birth Cohort collection, funded by the UK Medical Research Council and the Wellcome Trust. We acknowledge use of DNA samples from the NIHR Cambridge BioResource. We thank volunteers for their support and participation in the Cambridge BioResource and members of the Cambridge BioResource Scientific Advisory Board (SAB) and Management Committee for their support of our study. We acknowledge the NIHR Cambridge Biomedical Research Centre for funding. Access to Cambridge BioResource volunteers and to their data and samples are governed by the Cambridge BioResource SAB. Documents describing access arrangements and contact details are available at http://www.cambridgebioresource.org.uk/. We thank the Avon Longitudinal Study of Parents and Children laboratory in Bristol, UK, and the British 1958 Birth Cohort team, including S. Ring, R. Jones, M. Pembrey, W. McArdle, D. Strachan and P. Burton, for preparing and providing the control DNA samples. This study makes use of data generated by the Wellcome Trust Case Control Consortium, funded by Wellcome Trust award 076113; a full list of the investigators who contributed to the generation of the data is available from http://www.wtccc.org.uk/.This is the author accepted manuscript. The final version is available via NPG at http://www.nature.com/ng/journal/v47/n4/full/ng.3245.html

Extremely low-coverage sequencing and imputation increases power for genome-wide association studies

Genome wide association studies (GWAS) have proven a powerful method to identify common genetic variants contributing to susceptibility to common diseases. Here we show that extremely low-coverage sequencing (0.1–0.5x) captures almost as much of the common (>5%) and low-frequency (1–5%) variation across the genome as SNP arrays. As an empirical demonstration, we show that genome-wide SNP genotypes can be inferred at a mean r2 of 0.71 using off-target data (0.24x average coverage) in a whole-exome study of 909 samples. Using both simulated and real exome sequencing datasets we show that association statistics obtained using ultra low-coverage sequencing data attain similar P-values at known associated variants as genotyping arrays, without an excess of false positives. Within the context of reductions in sample preparation and sequencing costs, funds invested in ultra low-coverage sequencing can yield several times the effective sample size of SNP-array GWAS, and a commensurate increase in statistical power

The ATLAS Data Acquisition and High-Level Trigger: Concept, Design and Status

The Trigger and Data Acquisition system (TDAQ) of the ATLAS experiment at the CERN Large Hadron Collider is based on a multi-level selection process and a hierarchical acquisition tree. The system, consisting of a combination of custom electronics and commercial products from the computing and telecommunication industry, is required to provide an online selection power of 105 and a total throughput in the range of Terabit/sec. This paper introduces the basic system requirements and concepts, describes the architecture of the system, discusses the basic measurements supporting the validity of the design and reports on the actual status of construction and installation