The MPD thruster program at JPL

The topics covered are presented in viewgraph form and include the following: engine lifetime assessment; lithium magnetoplasmadynamic (MPD) thruster development; and radiation-cooled, applied-field engine testing

JPL nuclear electric propulsion task

The development of lithium magnetoplasmadynamic (MPD) thrusters at JPL is discussed. The following topics are presented in vugraph form: mercury vapor mass flow control; porous tungsten vaporizer and housing; the lithium vaporizer experiment; a dry box for handling solid lithium; MPD thruster electrode modeling; engine lifetime definitions; cathode failure modeling; cathode erosion modeling; cathode thermal modeling; near cathode plasma model regions; cathode work function modeling; anode work function modeling; and radiation-cooled anodes

FDive: Learning Relevance Models using Pattern-based Similarity Measures

The detection of interesting patterns in large high-dimensional datasets is difficult because of their dimensionality and pattern complexity. Therefore, analysts require automated support for the extraction of relevant patterns. In this paper, we present FDive, a visual active learning system that helps to create visually explorable relevance models, assisted by learning a pattern-based similarity. We use a small set of user-provided labels to rank similarity measures, consisting of feature descriptor and distance function combinations, by their ability to distinguish relevant from irrelevant data. Based on the best-ranked similarity measure, the system calculates an interactive Self-Organizing Map-based relevance model, which classifies data according to the cluster affiliation. It also automatically prompts further relevance feedback to improve its accuracy. Uncertain areas, especially near the decision boundaries, are highlighted and can be refined by the user. We evaluate our approach by comparison to state-of-the-art feature selection techniques and demonstrate the usefulness of our approach by a case study classifying electron microscopy images of brain cells. The results show that FDive enhances both the quality and understanding of relevance models and can thus lead to new insights for brain research.Comment: 12 pages, 7 figures, 2 tables, LaTeX; corrected typo; added DO

Consortium-based genome-wide meta-analysis for childhood dental caries traits

Prior studies suggest dental caries traits in children and adolescents are partially heritable, but there has been no large-scale consortium genome-wide association study (GWAS) to date. We therefore performed GWAS for caries in participants aged 2.5–18.0 years from nine contributing centres. Phenotype definitions were created for the presence or absence of treated or untreated caries, stratified by primary and permanent dentition. All studies tested for association between caries and genotype dosage and the results were combined using fixed-effects meta-analysis. Analysis included up to 19 003 individuals (7530 affected) for primary teeth and 13 353 individuals (5875 affected) for permanent teeth. Evidence for association with caries status was observed at rs1594318-C for primary teeth [intronic within ALLC, odds ratio (OR) 0.85, effect allele frequency (EAF) 0.60, P 4.13e-8] and rs7738851-A (intronic within NEDD9, OR 1.28, EAF 0.85, P 1.63e-8) for permanent teeth. Consortium-wide estimated heritability of caries was low [h2 of 1% (95% CI: 0%: 7%) and 6% (95% CI 0%: 13%) for primary and permanent dentitions, respectively] compared with corresponding within-study estimates [h2 of 28% (95% CI: 9%: 48%) and 17% (95% CI: 2%: 31%)] or previously published estimates. This study was designed to identify common genetic variants with modest effects which are consistent across different populations. We found few single variants associated with caries status under these assumptions. Phenotypic heterogeneity between cohorts and limited statistical power will have contributed; these findings could also reflect complexity not captured by our study design, such as genetic effects which are conditional on environmental exposure

Conceptual Design of the Nuclear Electronic Xenon Ion System (NEXIS)

In support of the NEXIS program, Aerojet-Redmond Operations, with review and input from the JPL and Boeing, has completed the design for a development model (DM) discharge chamber assembly and main discharge cathode assembly. These efforts along with the work by JPL to develop the carbon-carbon-composite ion optics assembly have resulted in a complete ion engine design. The goal of the NEXIS program is to significantly advance the current state of the art by developing an ion engine capable of operating at an input power of 20kW, an Isp of 7500 sec and have a total xenon through put capability of 2000 kg. In this paper we will describe the methodology used to design the discharge chamber and cathode assemblies and describe the resulting final design. Specifics will include the concepts used for the mounting of the ion optics along with the concepts used for the gimbal mounts. In addition, we will present results of a vibrational analysis showing how the engine will respond to a typical Delta IV heavy vibration spectrum

Visual Analytics of Volunteered Geographic Information : Detection and Investigation of Urban Heat Islands

Urban heat islands are local areas where the temperature is much higher than in the vicinity and are a modern phenomenon that occurs mainly in highly developed areas, such as large cities. This effect has a negative impact on energy management in buildings and also has a direct impact on human health, especially for elderly people. With the advent of volunteered geographic information from private weather station networks, more high resolution data is now available within cities to better analyze this effect. However, such data sets are large and have heterogeneous characteristics requiring visualinteractive applications to support further analysis. We use machine learning methods to predict urban heat islands occurrences and utilize temporal and spatio-temporal visualizations to contextualize the emergence of urban heat islands to comprehend the influencing causes and their effects. Subsequently, we demonstrate the analysis capabilities of our application by presenting two use cases.publishe