Image processing applications using a novel parallel computing machine based on reconfigurable logic

Zelig is a 32 physical node fine-grained computer employing field-programmable gate arrays. Its application to the high speed implementation of various image pre-processing operations (in particular binary morphology) is described together with typical speed-up result

Siberian snow forcing in a dynamically bias-corrected model

We investigate the effect of systematic model biases on teleconnections influencing the Northern Hemisphere wintertime circulation. We perform a two-step nudging and bias-correcting scheme for the dynamic variables of the ECHAM6 atmospheric model to reduce errors in the model climatology relative to ERA-Interim. One result is a significant increase in the strength of the Northern Hemisphere wintertime stratospheric polar vortex, reducing errors in the December–February mean zonal stratospheric winds by up to 75%. The bias corrections are applied to the full atmosphere or the stratosphere only. We compare the response of the bias-corrected and control runs to an increase in Siberian snow cover in October—a surface forcing that, in our experiments, weakens the stratospheric polar vortex from October to December. We find that despite large differences in the vortex strength the magnitude of the stratospheric weakening is similar among the different climatologies, with some differences in the timing and length of the response. Differences are more pronounced in the stratosphere–troposphere coupling, and the subsequent surface response. The snow forcing with the stratosphere-only bias corrections results in a stratospheric response that is comparable to control, yet with an enhanced surface response that extends into early January. The full-atmosphere bias correction’s snow response also has a comparable stratospheric response but a somewhat suppressed surface response. Despite these differences, our results show an overall small sensitivity of the Eurasian snow teleconnection to the background climatology

Mechanisms Driving the Effect of Weight Loss on Arterial Stiffness

Aims Arterial stiffness decreases with weight loss in overweight and obese adults, but the mechanisms by which this occurs are poorly understood. We aimed to elucidate these mechanisms. Methods We evaluated carotid-femoral pulse wave velocity (cfPWV), a measure of aortic stiffness, and brachial-ankle pulse wave velocity (baPWV), a mixed measure of central and peripheral arterial stiffness, in 344 young adults (mean age 38 yrs, mean body mass index (BMI) 32.9 kg/m2, 23% male) at baseline, 6 and 12 months in a behavioral weight loss intervention. Linear mixed effects models were used to evaluate associations between weight loss and arterial stiffness and to examine the degree to which improvements in obesity-related factors explained these associations. Pattern-mixture models using indicator variables for dropout pattern and Markov Chain Monte Carlo multiple imputation were used to evaluate the influence of different missing data assumptions. Results At 6 months (7% mean weight loss from baseline), there was a statistically significant median decrease of 47.5 cm/s (interquartile range (IQR) -44.5, 148) in cfPWV (p<0.0001) and a mean decrease of 11.7 cm/s (standard deviation (SD) 91.4) in baPWV (p=0.049). At 12 months (6% mean weight loss from baseline) only cfPWV remained statistically significantly reduced from baseline (p=0.02). Change in BMI (p=0.01) was statistically significantly positively associated with change in cfPWV after adjustment for changes in mean arterial pressure (MAP) or any other measured obesity-related factor. Common carotid artery diameter (p=0.003) was associated and heart rate (p=0.08) and MAP (p=0.07) marginally associated longitudinally with cfPWV. Reductions in heart rate (p<0.0001) and C-reactive protein (p=0.02) were associated with reduced baPWV, and each removed the statistical significance of the effect of weight loss on baPWV. Pattern-mixture modeling revealed several differences between completers and non-completers in the models for cfPWV, but marginal parameter estimates changed little from the original models for either PWV measure. Conclusions The public health importance of this thesis is that firstly, weight loss improves arterial stiffness in overweight and obese young adults. Secondly, its effect on baPWV may be explained by concurrent reductions in heart rate and inflammation. Missing data did not appear to bias these results

Negotiating Brexit: migrant spatialities and identities in a changing Europe [Introduction to special issue]

No abstract available

Pearling: stroke segmentation with crusted pearl strings

We introduce a novel segmentation technique, called Pearling, for the semi-automatic extraction of idealized models of networks of strokes (variable width curves) in images. These networks may for example represent roads in an aerial photograph, vessels in a medical scan, or strokes in a drawing. The operator seeds the process by selecting representative areas of good (stroke interior) and bad colors. Then, the operator may either provide a rough trace through a particular path in the stroke graph or simply pick a starting point (seed) on a stroke and a direction of growth. Pearling computes in realtime the centerlines of the strokes, the bifurcations, and the thickness function along each stroke, hence producing a purified medial axis transform of a desired portion of the stroke graph. No prior segmentation or thresholding is required. Simple gestures may be used to trim or extend the selection or to add branches. The realtime performance and reliability of Pearling results from a novel disk-sampling approach, which traces the strokes by optimizing the positions and radii of a discrete series of disks (pearls) along the stroke. A continuous model is defined through subdivision. By design, the idealized pearl string model is slightly wider than necessary to ensure that it contains the stroke boundary. A narrower core model that fits inside the stroke is computed simultaneously. The difference between the pearl string and its core contains the boundary of the stroke and may be used to capture, compress, visualize, or analyze the raw image data along the stroke boundary

Does Obesity Cause Thyroid Cancer? A Mendelian Randomization Study

Background: The incidence of thyroid cancer is rising, and relatively little is known about modifiable risk factors for the condition. Observational studies have suggested a link between adiposity and thyroid cancer; however, these are subject to confounding and reverse causality. Here, we used data from the UK Biobank and Mendelian randomization approaches to investigate whether adiposity causes benign nodular thyroid disease and differentiated thyroid cancer. Methods: We analyzed data from 379 708 unrelated participants of European ancestry in the UK Biobank and identified 1812 participants with benign nodular thyroid disease and 425 with differentiated thyroid carcinoma. We tested observational associations with measures of adiposity and type 2 diabetes mellitus. One and 2-sample Mendelian randomization approaches were used to investigate causal relationships. Results: Observationally, there were positive associations between higher body mass index (odds ratio [OR], 1.15; 95% confidence interval [CI], 1.08-1.22), higher waist-hip ratio (OR, 1.16; 95% CI, 1.09-1.23), and benign nodular thyroid disease, but not thyroid cancer. Mendelian randomization did not support a causal link for obesity with benign nodular thyroid disease or thyroid cancer, although it did provide some evidence that individuals in the highest quartile for genetic liability of type 2 diabetes had higher odds of thyroid cancer than those in the lowest quartile (OR, 1.45; CI, 1.11-1.90). Conclusions: Contrary to the findings of observational studies, our results do not confirm a causal role for obesity in benign nodular thyroid disease or thyroid cancer. They do, however, suggest a link between type 2 diabetes and thyroid cancer.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.WT_/Wellcome Trust/United Kingdompublished version, accepted version (12 month embargo), submitted versio

Global Existence and Regularity for the 3D Stochastic Primitive Equations of the Ocean and Atmosphere with Multiplicative White Noise

The Primitive Equations are a basic model in the study of large scale Oceanic and Atmospheric dynamics. These systems form the analytical core of the most advanced General Circulation Models. For this reason and due to their challenging nonlinear and anisotropic structure the Primitive Equations have recently received considerable attention from the mathematical community. In view of the complex multi-scale nature of the earth's climate system, many uncertainties appear that should be accounted for in the basic dynamical models of atmospheric and oceanic processes. In the climate community stochastic methods have come into extensive use in this connection. For this reason there has appeared a need to further develop the foundations of nonlinear stochastic partial differential equations in connection with the Primitive Equations and more generally. In this work we study a stochastic version of the Primitive Equations. We establish the global existence of strong, pathwise solutions for these equations in dimension 3 for the case of a nonlinear multiplicative noise. The proof makes use of anisotropic estimates, $L^{p}_{t}L^{q}_{x}$ estimates on the pressure and stopping time arguments.Comment: To appear in Nonlinearit