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Wind-driven snow redistribution can increase the spatial heterogeneity of snow accumulation on ice caps and ice sheets, and may prove crucial for the initiation and survival of glaciers in areas of marginal glaciation. We present a snowdrift model (Snow_Blow), which extends and improves the model of Purves, Mackaness and Sugden (1999, Journal of Quaternary Science 14, 313–321). The model calculates spatial variations in relative snow accumulation that result from variations in topography, using a digital elevation model (DEM) and wind direction as inputs. Improvements include snow redistribution using a flux routing algorithm, DEM resolution independence and the addition of a slope curvature component. This paper tests Snow_Blow in Antarctica (a modern environment) and reveals its potential for application in palaeoenvironmental settings, where input meteorological data are unavailable and difficult to estimate. Specifically, Snow_Blow is applied to the Ellsworth Mountains in West Antarctica where ablation is considered to be predominantly related to wind erosion processes. We find that Snow_Blow is able to replicate well the existing distribution of accumulating snow and snow erosion as recorded in and around Blue Ice Areas. Lastly, a variety of model parameters are tested, including depositional distance and erosion vs wind speed, to provide the most likely input parameters for palaeoenvironmental reconstructions.
This study aimed to assess the psychological well-being and quality of life in children with hypertrophic cardiomyopathy and the potential psychosocial impact of screening.
A total of 152 children (aged 3–18 years) attending a specialist paediatric hypertrophic cardiomyopathy clinic, and their parents completed the Generic Core Scales and Cardiac Module of the Paediatric Quality of Life Inventory (PedsQL) questionnaire as well as the Strengths and Difficulties Questionnaire; 21 patients (14%) had hypertrophic cardiomyopathy (group A); 23 children (15%) harboured hypertrophic cardiomyopathy-causing sarcomeric mutations with normal echocardiograms (group G); and 108 children (71%) had a family history of hypertrophic cardiomyopathy with normal investigations and attended for clinical cardiological screening (group S).
In group A, mean PedsQLTM total scores reported by children and parents were lower than those reported by unaffected children (p<0.001). There was no significant difference between unaffected and gene-positive patients. Mean Cardiac module PedsQLTM total scores by children and parents were lower in children with hypertrophic cardiomyopathy compared with unaffected patients [mean child-reported total score 86.4 in group S versus 72.3 in group A (p<0.001) and 80.2 in group G (p=0.25); mean parent-reported total score 91.6 in group S versus 71.4 in group A (p<0.001) and 87 in group G (p=0.4)]. There was no significant difference between group S and group G on any of the scales, or between the three groups of patients in the mean Strengths and Difficulties Questionnaire scores.
Children with hypertrophic cardiomyopathy have a significantly reduced quality of life. Importantly, Quality-of-Life scores among unaffected children attending for screening were not different compared with scores from a normative UK population.
In glacial environments particle-size analysis of moraines provides insights into clast origin, transport history, depositional mechanism and processes of reworking. Traditional methods for grain-size classification are labour-intensive, physically intrusive and are limited to patch-scale (1 m2) observation. We develop emerging, high-resolution ground- and unmanned aerial vehicle-based ‘Structure-from-Motion’ (UAV-SfM) photogrammetry to recover grain-size information across a moraine surface in the Heritage Range, Antarctica. SfM data products were benchmarked against equivalent datasets acquired using terrestrial laser scanning, and were found to be accurate to within 1.7 and 50 mm for patch- and site-scale modelling, respectively. Grain-size distributions were obtained through digital grain classification, or ‘photo-sieving’, of patch-scale SfM orthoimagery. Photo-sieved distributions were accurate to <2 mm compared to control distributions derived from dry-sieving. A relationship between patch-scale median grain size and the standard deviation of local surface elevations was applied to a site-scale UAV-SfM model to facilitate upscaling and the production of a spatially continuous map of the median grain size across a 0.3 km2 area of moraine. This highly automated workflow for site-scale sedimentological characterization eliminates much of the subjectivity associated with traditional methods and forms a sound basis for subsequent glaciological process interpretation and analysis.
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