Development of contrast enhancement after long-term observation of a dysembryoplastic neuroepithelial tumor

ManuscriptDysembryoplastic neuroepithelial tumors (DNET) are usually benign lesions that arise in cortical regions and are discovered after new onset of seizure. These lesions have many different imaging characteristics. We report a patient with a presumed low-grade medial temporal lobe lesion that was followed for many years without any change in size or imaging characteristics. This previously non-enhancing tumor evolved to become contrast enhanced on routine imaging without apparent tumor growth. The patient underwent surgery, and the pathology was confirmed as a DNET with no atypical changes. This case demonstrates the potential that DNETs may exhibit a changing MRI pattern over time. Natural history, imaging characteristics, and management are reviewed

Fine properties of metric space-valued mappings of bounded variation in metric measure spaces

Here we consider two notions of mappings of bounded variation (BV) from the metric measure space into the metric space; one based on relaxations of Newton-Sobolev functions, and the other based on a notion of AM-upper gradients. We show that when the target metric space is a Banach space, these two notions coincide with comparable energies, but for more general target metric spaces, the two notions can give different function-classes. We then consider the fine properties of BV mappings (based on the AM-upper gradient property), and show that when the target space is a proper metric space, then for a BV mapping into the target space, co-dimension $1$-almost every point in the jump set of a BV mapping into the proper space has at least two, and at most $k_0$, number of jump values associated with it, and that the preimage of balls around these jump values have lower density at least $\gamma$ at that point. Here $k_0$ and $\gamma$ depend solely on the structural constants associated with the metric measure space, and jump points are points at which the map is not approximately continuous

Production cross-sections and momentum distributions of fragments from neutron-deficient 36Ar at 1.05 A.GeV

We have measured production cross sections and longitudinal momentum distributions of fragments from neutron-deficient 36Ar at 1.05 A.GeV. The production cross-sections show excellent agreement with the predictions of the semiempirical formula EPAX. We have compared these results, involving extremly neutron deficient nuclei, with model calculations to extract informa tion about the response of these models close to the driplines. The longitudinal momentum distributions have also been extracted and are compared with the Goldhaber and Morrissey systematics.Comment: 16 pages, 6 figure

Unifying compactly supported and Matern covariance functions in spatial statistics

The Matern family of covariance functions has played a central role in spatial statistics for decades, being a flexible parametric class with one parameter determining the smoothness of the paths of the underlying spatial field. This paper proposes a family of spatial covariance functions, which stems from a reparameterization of the generalized Wendland family. As for the Matern case, the proposed family allows for a continuous parameterization of the smoothness of the underlying Gaussian random field, being additionally compactly supported.More importantly, we show that the proposed covariance family generalizes the Matern model which is attained as a special limit case. This implies that the (reparametrized) Generalized Wendland model is more flexible than the Matern model with an extra-parameter that allows for switching from compactly to globally supported covariance functions.Our numerical experiments elucidate the speed of convergence of the proposed model to the Matern model. We also inspect the asymptotic distribution of the maximum likelihood method when estimating the parameters of the proposed covariance models under both increasing and fixed domain asymptotics. The effectiveness of our proposal is illustrated by analyzing a georeferenced dataset of mean temperatures over a region of French, and performing a re-analysis of a large spatial point referenced dataset of yearly total precipitation anomalies. (C) 2022 Published by Elsevier Inc

Assessment and modelling of chiropractic and allied healthcare in Australia: Background and need for a formal investigation

There is need for a detailed investigation on the availability and impact of chiropractic and allied healthcare services, on healthcare choice and healthcare costs, as well as the delivery and spatial distribution of chiropractors in Australia. The goal of this paper is to discuss the background and to propose our intent to conduct an interdisciplinary assessment and modelling of the determinant factors of adoption of healthcare choices in Australia. Due to the highly complex nature of selecting a healthcare choice amongst available alternatives in today's world, it has been decided to design a research project using a new and innovative approach to the study of knowledge and knowledge systems in a social group. It was determined that the theory base of social interpretation of knowledge and knowledge implementation and change will drive this study. the study design will entail mixed methods including surveys, extensive document review, and a series of interviews of key stakeholders in the allied health professions within Australia. Studies such as this have potential to guide the planning process for federal and state governance bodies in chiropractic, in facilitating consumer choice between alternatives in healthcare. the knowledge gained through this study can drive healthcare change into the 21st century with chiropractic as a potential change agent

A selective view of climatological data and likelihood estimation

This article gives a narrative overview of what constitutes climatological data and their typical features, with a focus on aspects relevant to statistical modeling. We restrict the discussion to univariate spatial fields and focus on maximum likelihood estimation. To address the problem of enormous datasets, we study three common approximation schemes: tapering, direct misspecification, and composite likelihood for Gaussian and nonGaussian distributions. We focus particularly on the so-called 'sinh-arcsinh distribution', obtained through a specific transformation of the Gaussian distribution. Because it has flexible marginal distributions - possibly skewed and/or heavy-tailed - it has a wide range of applications. One appealing property of the transformation involved is the existence of an explicit inverse transformation that makes likelihood-based methods straightforward. We describe a simulation study illustrating the effects of the different approximation schemes. To the best of our knowledge, a direct comparison of tapering, direct misspecification, and composite likelihood has never been made previously, and we show that direct misspecification is inferior. In some metrics, composite likelihood has a minor advantage over tapering. We use the estimation approaches to model a high-resolution global climate change field. All simulation code is available as a Docker container and is thus fully reproducible. Additionally, the present article describes where and how to get various climate datasets. (c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND licens

Satellite selection in the context of an operational GBAS

When incorporating multiple constellations into future ground based augmentation systems (GBAS), a problem with limited VDB (VHF data broadcast) capacity might arise. Furthermore, the number of airborne receiver tracking channels could be insufficient to use all visible satellites. One way to cope with these issues is to perform a satellite selection to limit the number of used satellites with minor impact on performance. This paper investigates different factors that constrain the approach of simply selecting "the best set in every epoch" and shows how to overcome some limitations. These constraints include limitations in satellite visibility, loss of satellites during approach (i.e. in curves), and convergence times in the airborne processing until satellites are usable. Various protection level simulations are performed to show the influence of the named factors on the nominal performance. Taking into account all these contextual influences, results show satellite selection is still applicable in GBAS ground stations