Simulation methods and error analysis for trawl processes and ambit fields

Trawl processes are continuous-time, stationary and infinitely divisible processes which can describe a wide range of possible serial correlation patterns in data. In this paper, we introduce new simulation algorithms for trawl processes with monotonic trawl functions and establish their error bounds and convergence properties. We extensively analyse the computational complexity and practical implementation of these algorithms and discuss which one to use depending on the type of Lévy basis. We extend the above methodology to the simulation of kernel-weighted, volatility modulated trawl processes and develop a new simulation algorithm for ambit fields. Finally, we discuss how simulation schemes previously described in the literature can be combined with our methods for decreased computational cost

Using carbon isotope fractionation to constrain the extent of methane dissolution into the water column surrounding a natural hydrocarbon gas seep in the northern Gulf of Mexico

Author Posting. © American Geophysical Union, 2018. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Using carbon isotope fractionation to constrain the extent of methane dissolution into the water column surrounding a natural hydrocarbon gas seep in the northern gulf of Mexico. Geochemistry Geophysics Geosystems, 19(11), (2018); 4459-4475., doi:10.1029/2018GC007705.A gas bubble seep located in the northern Gulf of Mexico was investigated over several days to determine whether changes in the stable carbon isotopic ratio of methane can be used as a tracer for methane dissolution through the water column. Gas bubble and water samples were collected at the seafloor and throughout the water column for isotopic ratio analysis of methane. Our results show that changes in methane isotopic ratios are consistent with laboratory experiments that measured the isotopic fractionation from methane dissolution. A Rayleigh isotope model was applied to the isotope data to determine the fraction of methane dissolved at each depth. On average, the fraction of methane dissolved surpasses 90% past an altitude of 400 m above the seafloor. Methane dissolution was also investigated using a modified version of the Texas A&M Oil spill (Outfall) Calculator (TAMOC) where changes in methane isotopic ratios could be calculated. The TAMOC model results show that dissolution depends on depth and bubble size, explaining the spread in measured isotopic ratios during our investigations. Both the Rayleigh and TAMOC models show that methane bubbles quickly dissolve following emission from the seafloor. Together, these results show that it is possible to use measurements of natural methane isotopes to constrain the extent of methane dissolution following seafloor emission.This research was made possible by two grants from the Gulf of Mexico Research Initiative: Gulf Integrated Spill Response (GISR) Consortium (awarded to J. D. K. and S. A. S.) and Center for Integrated Modeling and Assessment of the Gulf Ecosystem (C‐IMAGE) II (awarded to S. A. S.). Additional support was provided by the U.S. Department of Energy (DE‐FE0028980; awarded to J. D. K.). Data are publicly available through the Gulf of Mexico Research Initiative Information & Data Cooperative (GRIIDC). Methane concentration and isotopic ratio data can be found at https://data.gulfresearchinitiative.org/data/R1.x137.000:0025, and TAMOC model scripts and results are found at https://data.gulfresearchinitiative.org/data/R1.x137.000:0026. The coversion of methane isotopic ratio data used in this manuscript can be found at https://data.gulfresearchinitiative.org/data/R1.x137.000:0028. We want to thank the captain and crew of the E/V Nautilus and the operators of ROV Hercules and Argus during the GISR G08 cruise and Nicole Raineault for their outstanding support at sea. Acoustically identifying the bubble flare was managed by Andone Lavery, and support for collecting gas and water samples was provided by John Bailey. We also want to thank Sean Sylva for analytical assistance on shore, Inok Jun for helping create the sampling schematics, and David Brink‐Roby for helping create the sample site map.2019-04-2

Aerial course stabilization is impaired in motion-blind flies

Visual motion detection is among the best understood neuronal computations. As extensively investigated in tethered flies, visual motion signals are assumed to be crucial to detect and counteract involuntary course deviations. During free flight, however, course changes are also signalled by other sensory systems. Therefore, it is as yet unclear to what extent motion vision contributes to course control. To address this question, we genetically rendered flies motion-blind by blocking their primary motion-sensitive neurons and quantified their free-flight performance. We found that such flies have difficulty maintaining a straight flight trajectory, much like unimpaired flies in the dark. By unilateral wing clipping, we generated an asymmetry in propulsive force and tested the ability of flies to compensate for this perturbation. While wild-type flies showed a remarkable level of compensation, motion-blind animals exhibited pronounced circling behaviour. Our results therefore directly confirm that motion vision is necessary to fly straight under realistic conditions

Cardiac masses and the role of imaging in their diagnostic

Myxomas are the most common primary tumors of the adult heart and should be considered in the differential diagnosis of intracavitary cardiac masses, along with thrombi and vegetations

Recent Bayesian approaches for spatial analysis of 2-D images with application to environmental modelling

From remote sensing of the environment, to brain scans in medicine, the growth in the use of image data has motivated a parallel increase in statistical techniques for analysing these images. A particular area of growth has been in Bayesian models and corresponding computational methods. Bayesian approaches have been proposed to address the gamut of supervised and unsupervised inferential aims in image analysis. In this article we provide a general review of these approaches, with a focus on unsupervised analysis of 2-D images. Four exemplar methods that canvas the broad aims of image modelling and analysis are described. An exposition of these approaches is provided by applying them to an environmental case study involving the use of satellite data to assess water quality in the Great Barrier Reef, Australia. The techniques considered in detail are hidden Markov random fields (MRF), Gaussian MRF, Poisson/gamma random fields, and Voronoi tessellations. We also consider a variety of enabling computational algorithms, including MCMC, variational Bayes and integrated nested Laplace approximations. We compare the different aims and inferential capabilities of the models and discuss the advantages and drawbacks of the corresponding computational algorithms

Methods for quantitative susceptibility and R2* mapping in whole post-mortem brains at 7T applied to amyotrophic lateral sclerosis

Susceptibility weighted magnetic resonance imaging (MRI) is sensitive to the local concentration of iron and myelin. Here, we describe a robust image processing pipeline for quantitative susceptibility mapping (QSM) and R2* mapping of fixed post-mortem, whole-brain data. Using this pipeline, we compare the resulting quantitative maps in brains from patients with amyotrophic lateral sclerosis (ALS) and controls, with validation against iron and myelin histology. Twelve post-mortem brains were scanned with a multi-echo gradient echo sequence at 7T, from which susceptibility and R2* maps were generated. Semi-quantitative histological analysis for ferritin (the principal iron storage protein) and myelin proteolipid protein was performed in the primary motor, anterior cingulate and visual cortices. Magnetic susceptibility and R2* values in primary motor cortex were higher in ALS compared to control brains. Magnetic susceptibility and R2* showed positive correlations with both myelin and ferritin estimates from histology. Four out of nine ALS brains exhibited clearly visible hyperintense susceptibility and R2* values in the primary motor cortex. Our results demonstrate the potential for MRI-histology studies in whole, fixed post-mortem brains to investigate the biophysical source of susceptibility weighted MRI signals in neurodegenerative diseases like ALS