Geostatistical analysis of an experimental stratigraphy

[1] A high-resolution stratigraphic image of a flume-generated deposit was scaled up to sedimentary basin dimensions where a natural log hydraulic conductivity (ln( K)) was assigned to each pixel on the basis of gray scale and conductivity end-members. The synthetic ln( K) map has mean, variance, and frequency distributions that are comparable to a natural alluvial fan deposit. A geostatistical analysis was conducted on selected regions of this map containing fluvial, fluvial/ floodplain, shoreline, turbidite, and deepwater sedimentary facies. Experimental ln(K) variograms were computed along the major and minor statistical axes and horizontal and vertical coordinate axes. Exponential and power law variogram models were fit to obtain an integral scale and Hausdorff measure, respectively. We conclude that the shape of the experimental variogram depends on the problem size in relation to the size of the local-scale heterogeneity. At a given problem scale, multilevel correlation structure is a result of constructing variogram with data pairs of mixed facies types. In multiscale sedimentary systems, stationary correlation structure may occur at separate scales, each corresponding to a particular hierarchy; the integral scale fitted thus becomes dependent on the problem size. The Hausdorff measure obtained has a range comparable to natural geological deposits. It increases from nonstratified to stratified deposits with an approximate cutoff of 0.15. It also increases as the number of facies incorporated in a problem increases. This implies that fractal characteristic of sedimentary rocks is both depositional process - dependent and problem-scale-dependent

HTC Scientific Computing in a Distributed Cloud Environment

This paper describes the use of a distributed cloud computing system for high-throughput computing (HTC) scientific applications. The distributed cloud computing system is composed of a number of separate Infrastructure-as-a-Service (IaaS) clouds that are utilized in a unified infrastructure. The distributed cloud has been in production-quality operation for two years with approximately 500,000 completed jobs where a typical workload has 500 simultaneous embarrassingly-parallel jobs that run for approximately 12 hours. We review the design and implementation of the system which is based on pre-existing components and a number of custom components. We discuss the operation of the system, and describe our plans for the expansion to more sites and increased computing capacity

Exploring content and psychometric validity of newly developed assessment tools for itch and skin pain in atopic dermatitis.

BackgroundAtopic dermatitis (AD) is a common skin disorder characterized by chronic inflammation, altered skin barrier function, and inflammatory cell skin infiltration that decreases health-related quality of life (HRQoL). The study objective was to understand the patient perspective of AD burden and determine suitable patient-reported outcome (PRO) measures.MethodsThis mixed methods study involved the collection of qualitative and quantitative information from adults (≥ 18 years old) and adolescents (12 - 17 years old) with clinician-confirmed AD regarding their experiences of AD symptoms and its impact on HRQoL. The first part of the study included three stages: in-person concept elicitation (CE) interviews, a 2-week daily electronic diary (eDiary) study, and in-person cognitive debriefing (CD) interviews. An Itch numeric rating scale (NRS) (v1.0) and a Skin Pain NRS (v1.0) evaluation during CD interviews required participants to think about their 'worst' itch and 'worst' skin pain in the past 24 h. Other PRO measures allowed for psychometric testing. The second part of the study involved telephone-depth interviews (TDIs) and qualitative feedback from participants who had not participated in the CD interviews. Qualitative data were thematically analyzed. Psychometric evaluation of NRS measures was performed using eDiary data.ResultsIn the CE interviews, itch and/or itching and skin pain were the most prevalent symptoms consistently discussed by participants. Both NRS measures demonstrated strong psychometric reliability and were applicable across ages with suitable concurrent validity. During the CD interviews, some participants focused their answers on their 'average' itch/itching in the past 24 h, rather than their 'worst' itch. Some participants answered the Skin Pain NRS thinking about general pain or other types of pain, rather than skin pain specifically. Consequently, modifications to both measures addressed these issues and re-tested as paper-and-pen versions in subsequent TDIs. Itch NRS (v2.0) modifications helped participants focus on their worst itching. Most participants preferred Skin Pain NRS v2.0b, which included skin pain descriptors.ConclusionsItching and skin pain are the most important and relevant AD symptoms. The Itch NRS (v2.0) and Skin Pain NRS (v2.0b) appear to be appropriate endpoints for the assessment of itching and skin pain severity for clinical trials with adults and adolescents with AD