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Background: Data on electrocardiographic and echocardiographic pre-participation screening findings in paediatric athletes are limited.
Methods and results: 10-15 year-old athletes (n = 343) were screened using electro- and echocardiography. The electrocardiogram (ECG) was normal in 220 (64%), mildly abnormal in 108 (31%), and distinctly abnormal in 15 (4%) athletes. Echocardiographic upper reference limits (URL, 97.5 percentile) for the left ventricular (LV) wall thickness in 10-11-year-old boys and girls were 9-10 mm and 8-9 mm, respectively; in 12-13-year-old boys and girls 9-10 mm; and in 14-15-year-old boys and girls 10-11 mm and 9-10 mm, respectively. Three athletes were excluded from competitive sports: one for symptomatic Wolff-Parkinson-White syndrome with a normal echocardiogram; one for negative T-waves in V-1-V-4 and a dilated right ventricle by echocardiography suggestive of (arrhythmogenic) right ventricular disease; and one for normal ECG and biscupid aortic valve including an aneurysm of the ascending aorta detected by echocardiography. Related to echocardiographic findings, the sensitivity and specificity of the ECG to identify cardiovascular abnormalities was 38% and 64%, respectively. The ECG's positive-predictive and negative-predictive values were 13% and 88%, respectively. The numbers needed to screen and calculated costs were 172 for ECG ( 7049), 172 for echocardiography ( 11,530), and 114 combining ECG and echocardiography ( 9323).
Conclusions: Compared to adults, paediatric athletes presented with fewer distinctly abnormal ECGs, and there was no gender difference in paediatric athletes' ECG-pattern distribution. A combination of ECG and echocardiography for pre-participation screening of paediatric athletes is superior to ECG alone but 30% more costly.
Intrinsic decomposition refers to the problem of estimating scene characteristics, such as albedo and shading, when one view or multiple views of a scene are provided. The inverse problem setting, where multiple unknowns are solved given a single known pixel-value, is highly under-constrained. When provided with correlating image and depth data, intrinsic scene decomposition can be facilitated using depth-based priors, which nowadays is easy to acquire with high-end smartphones by utilizing their depth sensors. In this work, we present a system for intrinsic decomposition of RGB-D images on smartphones and the algorithmic as well as design choices therein. Unlike state-of-the-art methods that assume only diffuse reflectance, we consider both diffuse and specular pixels. For this purpose, we present a novel specularity extraction algorithm based on a multi-scale intensity decomposition and chroma inpainting. At this, the diffuse component is further decomposed into albedo and shading components. We use an inertial proximal algorithm for non-convex optimization (iPiano) to ensure albedo sparsity. Our GPU-based visual processing is implemented on iOS via the Metal API and enables interactive performance on an iPhone 11 Pro. Further, a qualitative evaluation shows that we are able to obtain high-quality outputs. Furthermore, our proposed approach for specularity removal outperforms state-of-the-art approaches for real-world images, while our albedo and shading layer decomposition is faster than the prior work at a comparable output quality. Manifold applications such as recoloring, retexturing, relighting, appearance editing, and stylization are shown, each using the intrinsic layers obtained with our method and/or the corresponding depth data.
The self-assembly of double-hydrophilic poly(ethylene oxide)-poly(2-methyl-2-oxazoline) diblock copolymers in water has been studied. Isothermal titration calorimetry, small-angle X-ray scattering, and analytical ultracentrifugation suggest that only single polymer chains are present in solution. In contrast, light scattering and transmission electron microscopy detect aggregates with radii of ca. 100 nm. Pulsed field gradient NMR spectroscopy confirms the presence of aggregates, although only 2% of the polymer chains undergo aggregation. Water uptake experiments indicate differences in the hydrophilicity of the two blocks, which is believed to be the origin of the unexpected aggregation behavior (in accordance with an earlier study by Ke et al. [Macromolecules 2009, 42, 5339-5344]). The data therefore suggest that even in double-hydrophilic block copolymers, differences in hydrophilicity are sufficient to drive polymer aggregation, a phenomenon that has largely been overlooked or ignored so far.