65 research outputs found
The UKIDSS Galactic Plane Survey
'The definitive version is available at www.blackwell-synergy.com .' Copyright Blackwell Publishing DOI: 10.1111/j.1365-2966.2008.13924.xThe UKIDSS Galactic Plane Survey (GPS) is one of the five near-infrared Public Legacy Surveys that are being undertaken by the UKIDSS consortium, using the Wide Field Camera on the United Kingdom Infrared TelescopePeer reviewe
TRY plant trait database – enhanced coverage and open access
Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives
Supernova neutrino detection in NOvA
The NOvA long-baseline neutrino experiment uses a pair of large, segmented, liquid-scintillator calorimeters to study neutrino oscillations, using GeV-scale neutrinos from the Fermilab NuMI beam. These detectors are also sensitive to the flux of neutrinos which are emitted during a core-collapse supernova through inverse beta decay interactions on carbon at energies of O(10 MeV). This signature provides a means to study the dominant mode of energy release for a core-collapse supernova occurring in our galaxy. We describe the data-driven software trigger system developed and employed by the NOvA experiment to identify and record neutrino data from nearby galactic supernovae. This technique has been used by NOvA to self-trigger on potential core-collapse supernovae in our galaxy, with an estimated sensitivity reaching out to 10 kpc distance while achieving a detection efficiency of 23% to 49% for supernovae from progenitor stars with masses of 9.6 M☉ to 27 M☉, respectively
Hydrothermal petrology in the Costa Rica Rift
Available from British Library Document Supply Centre- DSC:DX76931 / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo
Automatic intracranial space segmentation for computed tomography brain images
Craniofacial disorders are routinely diagnosed using computed tomography imaging. Corrective surgery is often performed early in life to restore the skull to a more normal shape. In order to quantitatively assess the shape change due to surgery, we present an automated method for intracranial space segmentation. The method utilizes a two-stage approach which firstly initializes the segmentation with a cascade of mathematical morphology operations. This segmentation is then refined with a level-set-based approach that ensures that low-contrast boundaries, where bone is absent, are completed smoothly. We demonstrate this method on a dataset of 43 images and show that the method produces consistent and accurate results
Scratch durability of automotive clear coatings: A quantitative, reliable and robust methodology
Circulating pluripotent haemopoietic cells in patients with myeloproliferative disorders
Detailed CAD Phenotyping by Angiography, Dynamic Perfusion and Scar Imaging Sharpens CT Prognostic Power
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