642 research outputs found

    A Software Platform for Post-Processing Waveform-Based NDE

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    Ultrasonic, microwave, and terahertz nondestructive evaluation imaging systems generally require the acquisition of waveforms at each scan point to form an image. For such systems, signal and image processing methods are commonly needed to extract information from the waves and improve resolution of, and highlight, defects in the image. Since some similarity exists for all waveform-based NDE methods, it would seem a common software platform containing multiple signal and image processing techniques to process the waveforms and images makes sense where multiple techniques, scientists, engineers, and organizations are involved. This presentation describes NASA Glenn Research Center's approach in developing a common software platform for processing waveform-based NDE signals and images. This platform is currently in use at NASA Glenn and at Lockheed Martin Michoud Assembly Facility for processing of pulsed terahertz and ultrasonic data. Highlights of the software operation will be given. A case study will be shown for use with terahertz data. The authors also request scientists and engineers who are interested in sharing customized signal and image processing algorithms to contribute to this effort by letting the authors code up and include these algorithms in future releases

    Ethnic differences in the prevalence of inherited thrombophilic polymorphisms in an asymptomatic Australian prenatal population

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    Differences in the prevalence of thrombophilias in different ethnic populations have been demonstrated. Because the Australian population includes many different ethnic groups, we sought to assess the effect of ethnicity in our Australian prenatal population on the prevalence of thrombophilic polymorphisms. Asymptomatic, nulliparous women (n = 1,129) recruited for a large prospective study were included in this analysis. These women had no personal or family history of venous thromboembolism and were not known to be carrying an inherited or acquired thrombophilia. Ethnicity was determined at recruitment, and women were categorized as being of Northern European, Southern European, Middle Eastern, Asian, or Other ethnicity. These women underwent genotyping for the following polymorphisms: factor V Leiden G1691A, prothrombin gene A20210G mutation, methylenetetrahydrofolate reductase (MTHFR) C677T and A1298C, and thrombomodulin C1418T. The factor V Leiden allele was seen significantly more frequently in patients of Middle Eastern background compared to those of Northern European and Asian ethnicity (p < 0.05). The prothrombin gene mutation was seen significantly more frequently in patients of Southern European ethnicity compared to those of Northern European or Asian ethnicity (p < 0.05). The MTHFR C677T allele (mutant) was significantly less common in those of Asian ethnicity compared to patients of Northern European and Southern European ethnicity (p < 0.0005). There were no significant differences seen with the MTHFR A1298C polymorphism. The mutant thrombomodulin allele was seen significantly more frequently in Asian women compared to Northern European, Southern European, or Middle Eastern women (p < 0.005). There are important ethnic differences in the prevalence of thrombophilic polymorphisms in the Australian prenatal population

    Ocean processes at the Antarctic continental slope

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    The Antarctic continental shelves and slopes occupy relatively small areas, but, nevertheless, are important for global climate, biogeochemical cycling and ecosystem functioning. Processes of water mass transformation through sea ice formation/melting and ocean-atmosphere interaction are key to the formation of deep and bottom waters as well as determining the heat flux beneath ice shelves. Climate models, however, struggle to capture these physical processes and are unable to reproduce water mass properties of the region. Dynamics at the continental slope are key for correctly modelling climate, yet their small spatial scale presents challenges both for ocean modelling and for observational studies. Cross-slope exchange processes are also vital for the flux of nutrients such as iron from the continental shelf into the mixed layer of the Southern Ocean. An © 2014 The Authors

    How Universal is the Relationship Between Remotely Sensed Vegetation Indices and Crop Leaf Area Index? A Global Assessment

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    Leaf Area Index (LAI) is a key variable that bridges remote sensing observations to the quantification of agroecosystem processes. In this study, we assessed the universality of the relationships between crop LAI and remotely sensed Vegetation Indices (VIs). We first compiled a global dataset of 1459 in situ quality-controlled crop LAI measurements and collected Landsat satellite images to derive five different VIs including Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), two versions of the Enhanced Vegetation Index (EVI and EVI2), and Green Chlorophyll Index (CI(sub Green)). Based on this dataset, we developed global LAI-VI relationships for each crop type and VI using symbolic regression and Theil-Sen (TS) robust estimator. Results suggest that the global LAI-VI relationships are statistically significant, crop-specific, and mostly non-linear. These relationships explain more than half of the total variance in ground LAI observations (R2 greater than 0.5), and provide LAI estimates with RMSE below 1.2 m2/m2. Among the five VIs, EVI/EVI2 are the most effective, and the crop-specific LAI-EVI and LAI-EVI2 relationships constructed by TS, are robust when tested by three independent validation datasets of varied spatial scales. While the heterogeneity of agricultural landscapes leads to a diverse set of local LAI-VI relationships, the relationships provided here represent global universality on an average basis, allowing the generation of large-scale spatial-explicit LAI maps. This study contributes to the operationalization of large-area crop modeling and, by extension, has relevance to both fundamental and applied agroecosystem research

    Garden and landscape-scale correlates of moths of differing conservation status: significant effects of urbanization and habitat diversity

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    Moths are abundant and ubiquitous in vegetated terrestrial environments and are pollinators, important herbivores of wild plants, and food for birds, bats and rodents. In recent years, many once abundant and widespread species have shown sharp declines that have been cited by some as indicative of a widespread insect biodiversity crisis. Likely causes of these declines include agricultural intensification, light pollution, climate change, and urbanization; however, the real underlying cause(s) is still open to conjecture. We used data collected from the citizen science Garden Moth Scheme (GMS) to explore the spatial association between the abundance of 195 widespread British species of moth, and garden habitat and landscape features, to see if spatial habitat and landscape associations varied for species of differing conservation status. We found that associations with habitat and landscape composition were species-specific, but that there were consistent trends in species richness and total moth abundance. Gardens with more diverse and extensive microhabitats were associated with higher species richness and moth abundance; gardens near to the coast were associated with higher richness and moth abundance; and gardens in more urbanized locations were associated with lower species richness and moth abundance. The same trends were also found for species classified as increasing, declining and vulnerable under IUCN (World Conservation Union) criteria

    Aptamer-based multiplexed proteomic technology for biomarker discovery

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    Interrogation of the human proteome in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 [mu]L of serum or plasma). Our current assay allows us to measure ~800 proteins with very low limits of detection (1 pM average), 7 logs of overall dynamic range, and 5% average coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding DNA aptamer concentration signature, which is then quantified with a DNA microarray. In essence, our assay takes advantage of the dual nature of aptamers as both folded binding entities with defined shapes and unique sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to discover unique protein signatures characteristic of various disease states. More generally, we describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine
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