5,562 research outputs found

    Origin, evolution and dynamic context of a Neoglacial lateral-frontal moraine at Austre Lovénbreen, Svalbard

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    Moraines marking the Neoglacial limits in Svalbard are commonly ice cored. Investigating the nature of this relict ice is important because it can aid our understanding of former glacier dynamics. This paper examines the composition of the lateral–frontal moraine associated with the Neoglacial limit at Austre Lovénbreen and assesses the likely geomorphological evolution. The moraine was investigated using ground-penetrating radar (GPR), with context being provided by structural mapping of the glacier based on an oblique aerial image from 1936 and vertical aerial imagery from 2003. Multiple up-glacier dipping reflectors and syncline structures are found in the GPR surveys. The reflectors are most clearly defined in lateral positions, where the moraine is substantially composed of ice. The frontal area of the moraine is dominantly composed of debris. The core of the lateral part of the moraine is likely to consist of stacked sequences of basal ice that have been deformed by strong longitudinal compression. The long term preservation potential of the ice-dominated lateral moraine is negligible, whereas the preservation of the debris-dominated frontal moraine is high. A glacier surface bulge, identified on the 1936 aerial imagery, provides evidence that Austre Lovénbreen has previously displayed surge activity, although it is highly unlikely to do so in the near future in its current state. This research shows the value of relict buried ice that is preserved in landforms to aiding our understanding of former glacier characteristics

    Bayesian models for syndrome- and gene-specific probabilities of novel variant pathogenicity

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    BACKGROUND: With the advent of affordable and comprehensive sequencing technologies, access to molecular genetics for clinical diagnostics and research applications is increasing. However, variant interpretation remains challenging, and tools that close the gap between data generation and data interpretation are urgently required. Here we present a transferable approach to help address the limitations in variant annotation. METHODS: We develop a network of Bayesian logistic regression models that integrate multiple lines of evidence to evaluate the probability that a rare variant is the cause of an individual's disease. We present models for genes causing inherited cardiac conditions, though the framework is transferable to other genes and syndromes. RESULTS: Our models report a probability of pathogenicity, rather than a categorisation into pathogenic or benign, which captures the inherent uncertainty of the prediction. We find that gene- and syndrome-specific models outperform genome-wide approaches, and that the integration of multiple lines of evidence performs better than individual predictors. The models are adaptable to incorporate new lines of evidence, and results can be combined with familial segregation data in a transparent and quantitative manner to further enhance predictions. Though the probability scale is continuous, and innately interpretable, performance summaries based on thresholds are useful for comparisons. Using a threshold probability of pathogenicity of 0.9, we obtain a positive predictive value of 0.999 and sensitivity of 0.76 for the classification of variants known to cause long QT syndrome over the three most important genes, which represents sufficient accuracy to inform clinical decision-making. A web tool APPRAISE [http://www.cardiodb.org/APPRAISE] provides access to these models and predictions. CONCLUSIONS: Our Bayesian framework provides a transparent, flexible and robust framework for the analysis and interpretation of rare genetic variants. Models tailored to specific genes outperform genome-wide approaches, and can be sufficiently accurate to inform clinical decision-making

    Evolution of high-Arctic glacial landforms during deglaciation

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    Glacial landsystems in the high-Arctic have been reported to undergo geomorphological transformation during deglaciation. This research evaluates moraine evolution over a decadal timescale at Midtre Lovénbreen, Svalbard. This work is of interest because glacial landforms developed in Svalbard have been used as an analogue for landforms developed during Pleistocene mid-latitude glaciation. Ground penetrating radar was used to investigate the subsurface characteristics of moraines. To determine surface change, a LiDAR topographic data set (obtained 2003) and a UAV-derived (obtained 2014) digital surface model processed using structure-from-motion (SfM) are also compared. Evaluation of these data sets together enables subsurface character and landform response to climatic amelioration to be linked. Ground penetrating radar evidence shows that the moraine substrate at Midtre Lovénbreen includes ice-rich (radar velocities of 0.17 m ns−1) and debris-rich (radar velocities of 0.1–0.13 m ns−1) zones. The ice-rich zones are demonstrated to exhibit relatively high rates of surface change (mean thresholded rate of −4.39 m over the 11-year observation period). However, the debris-rich zones show a relatively low rate of surface change (mean thresholded rate of −0.98 m over the 11-year observation period), and the morphology of the debris-rich landforms appear stable over the observation period. A complex response of proglacial landforms to climatic warming is shown to occur within and between glacier forelands as indicated by spatially variable surface lowering rates. Landform response is controlled by the ice-debris balance of the moraine substrate, along with the topographic context (such as the influence of meltwater). Site-specific characteristics such as surface debris thickness and glaciofluvial drainage are, therefore, argued to be a highly important control on surface evolution in ice-cored terrain, resulting in a diverse response of high-Arctic glacial landsystems to climatic amelioration. These results highlight that care is needed when assessing the long-term preservation potential of contemporary landforms at high-Arctic glaciers. A better understanding of ice-cored terrain facilitates the development of appropriate age and climatic interpretations that can be obtained from palaeo ice-marginal landsystems

    Language Model Co-occurrence Linking for Interleaved Activity Discovery

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    As ubiquitous computer and sensor systems become abundant, the potential for automatic identification and tracking of human behaviours becomes all the more evident. Annotating complex human behaviour datasets to achieve ground truth for supervised training can however be extremely labour-intensive, and error prone. One possible solution to this problem is activity discovery: the identification of activities in an unlabelled dataset by means of an unsupervised algorithm. This paper presents a novel approach to activity discovery that utilises deep learning based language production models to construct a hierarchical, tree-like structure over a sequential vector of sensor events. Our approach differs from previous work in that it explicitly aims to deal with interleaving (switching back and forth between between activities) in a principled manner, by utilising the long-term memory capabilities of a recurrent neural network cell. We present our approach and test it on a realistic dataset to evaluate its performance. Our results show the viability of the approach and that it shows promise for further investigation. We believe this is a useful direction to consider in accounting for the continually changing nature of behaviours

    Visualizing 1D Regression

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    Regression is the study of the conditional distribution of the response y given the predictors x. In a 1D regression, y is independent of x given a single linear combination βTx of the predictors. Special cases of 1D regression include multiple linear regression, binary regression and generalized linear models. If a good estimate ˆb of some non-zero multiple cβ of β can be constructed, then the 1D regression can be visualized with a scatterplot of ˆbTx versus y. A resistant method for estimating cβ is presented along with applications

    A systematic review of the use of an expertise-based randomised controlled trial design

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    Acknowledgements JAC held a Medical Research Council UK methodology (G1002292) fellowship, which supported this research. The Health Services Research Unit, Institute of Applied Health Sciences (University of Aberdeen), is core-funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorates. Views express are those of the authors and do not necessarily reflect the views of the funders.Peer reviewedPublisher PD

    Estimating the volume of Alpine glacial lakes

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    Supraglacial, moraine-dammed and ice-dammed lakes represent a potential glacial lake outburst flood (GLOF) threat to downstream communities in many mountain regions. This has motivated the development of empirical relationships to predict lake volume given a measurement of lake surface area obtained from satellite imagery. Such relationships are based on the notion that lake depth, area and volume scale predictably. We critically evaluate the performance of these existing empirical relationships by examining a global database of glacial lake depths, areas and volumes. Results show that lake area and depth are not always well correlated (r2 = 0.38), and that although lake volume and area are well correlated (r2 = 0.91), and indeed are auto-correlated, there are distinct outliers in the dataset. These outliers represent situations where it may not be appropriate to apply existing empirical relationships to predict lake volume, and include growing supraglacial lakes, glaciers that recede into basins with complex overdeepened morphologies or that have been deepened by intense erosion, and lakes formed where glaciers advance across and block a main trunk valley. We use the compiled dataset to develop a conceptual model of how the volumes of supraglacial ponds and lakes, moraine-dammed lakes and ice-dammed lakes should be expected to evolve with increasing area. Although a large amount of bathymetric data exist for moraine-dammed and ice-dammed lakes, we suggest that further measurements of growing supraglacial ponds and lakes are needed to better understand their development

    Ethnic Differences in Carotid Intima-Media Thickness Between UK Children of Black African-Caribbean and White European Origin.

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    BACKGROUND AND PURPOSE: UK black African-Caribbean adults have higher risks of stroke than white Europeans and have been shown to have increased carotid intima-media thickness (cIMT). We examined whether corresponding ethnic differences in cIMT were apparent in childhood and, if so, whether these could be explained by ethnic differences in cardiovascular risk markers. METHODS: We conducted a 2-stage survey of 939 children (208 white European, 240 black African-Caribbean, 258 South Asian, 63 other Asian, 170 other ethnicity), who had a cardiovascular risk assessment and measurements of cIMT at mean ages of 9.8 and 10.8 years, respectively. RESULTS: Black African-Caribbean children had a higher cIMT than white Europeans (mean difference, 0.014 mm; 95% CI, 0.008-0.021 mm; P<0.0001). cIMT levels in South Asian and other Asian children were however similar to those of white Europeans. Among all children, cIMT was positively associated with age, systolic and diastolic blood pressure and inversely with combined skinfold thickness and serum triglyceride. Mean triglyceride was lower among black African-Caribbeans than white Europeans; blood pressure and skinfold thickness did not differ appreciably. However, adjustment for these risk factors had little effect on the cIMT difference between black African-Caribbeans and white Europeans. CONCLUSIONS: UK black African-Caribbean children have higher cIMT levels in childhood; the difference is not explained by conventional cardiovascular risk markers. There may be important opportunities for early cardiovascular prevention, particularly in black African-Caribbean children
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