Hardware Design Improvements to the Major Constituent Analyzer

The Major Constituent Analyzer (MCA) onboard the International Space Station (ISS) is designed to monitor the major constituents of the ISS's internal atmosphere. This mass spectrometer based system is an integral part of the Environmental Control and Life Support System (ECLSS) and is a primary tool for the management of ISS atmosphere composition. As a part of NASA Change Request CR10773A, several alterations to the hardware have been made to accommodate improved MCA logistics. First, the ORU 08 verification gas assembly has been modified to allow the verification gas cylinder to be installed on orbit. The verification gas is an essential MCA consumable that requires periodic replenishment. Designing the cylinder for subassembly transport reduces the size and weight of the maintained item for launch. The redesign of the ORU 08 assembly includes a redesigned housing, cylinder mounting apparatus, and pneumatic connection. The second hardware change is a redesigned wiring harness for the ORU 02 analyzer. The ORU 02 electrical connector interface was damaged in a previous on-orbit installation, and this necessitated the development of a temporary fix while a more permanent solution was developed. The new wiring harness design includes flexible cable as well as indexing fasteners and guide-pins, and provides better accessibility during the on-orbit maintenance operation. This presentation will describe the hardware improvements being implemented for MCA as well as the expected improvement to logistics and maintenance

Commentaries on viewpoint : physiology and fast marathons

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Measurement of the reaction gamma*p->phi p in deep, inelastic e(+)p scattering at HERA

The production of phi mesons in the reaction e(+)p --> e(+)phi p (phi --> K+K-), for 7 phi p cross section rises strongly with W. This behaviour is similar to that previously found for the gamma*p --> rho(0)p cross section. This strong dependence cannot be explained by production through soft pomeron exchange, It is, however, consistent with perturbative QCD expectations, where it reflects the rise of the gluon momentum density in the proton at small x. The ratio of sigma(phi)/sigma(rho(0)), which has previously been determined by ZEUS to be 0.065 +/- 0.013 (stat.) in photoproduction at a mean W of 70 GeV, is measured to be 0.18 +/- 0.05 (stat.) +/- 0.03 (syst.) at a mean Q(2) of 12.3 GeV2 and mean W of approximate to 100 GeV and is thus approaching at large Q(2) the value of 2/9 predicted from the quark charges of the vector mesons and a flavour independent production mechanism

Predicting Fusarium head blight epidemics with boosted regression trees

Citation: Shah, D., . . . & Madden, L. (2014). Predicting Fusarium Head Blight Epidemics with Boosted Regression Trees. Phytopathology, 104(7), 702-714. https://doi.org/0.1094/PHYTO-10-13-0273-RPredicting major Fusarium head blight (FHB) epidemics allows for the judicious use of fungicides in suppressing disease development. Our objectives were to investigate the utility of boosted regression trees (BRTs) for predictive modeling of FHB epidemics in the United States, and to compare the predictive performances of the BRT models with those of logistic regression models we had developed previously. The data included 527 FHB observations from 15 states over 26 years. BRTs were fit to a training data set of 369 FHB observations, in which FHB epidemics were classified as either major (severity ≥ 10%) or non-major (severity < 10%), linked to a predictor matrix consisting of 350 weather-based variables and categorical variables for wheat type (spring or winter), presence or absence of corn residue, and cultivar resistance. Predictive performance was estimated on a test (holdout) data set consisting of the remaining 158 observations. BRTs had a misclassification rate of 0.23 on the test data, which was 31% lower than the average misclassification rate over 15 logistic regression models we had presented earlier. The strongest predictors were generally one of mean daily relative humidity, mean daily temperature, and the number of hours in which the temperature was between 9 and 30°C and relative humidity ≥ 90% simultaneously. Moreover, the predicted risk of major epidemics increased substantially when mean daily relative humidity rose above 70%, which is a lower threshold than previously modeled for most plant pathosystems. BRTs led to novel insights into the weather–epidemic relationship

Textural analysis in FDG PET of locally advanced non-small cell lung cancer: Prognostic value of entropy

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