Knowledge based and interactive control for the Superfluid Helium On-orbit Transfer Project

NASA's Superfluid Helium On-Orbit Transfer (SHOOT) project is a Shuttle-based experiment designed to acquire data on the properties of superfluid helium in micro-gravity. Aft Flight Deck Computer Software for the SHOOT experiment is comprised of several monitoring programs which give the astronaut crew visibility into SHOOT systems and a rule based system which will provide process control, diagnosis and error recovery for a helium transfer without ground intervention. Given present Shuttle manifests, this software will become the first expert system to be used in space. The SHOOT Command and Monitoring System (CMS) software will provide a near real time highly interactive interface for the SHOOT principal investigator to control the experiment and to analyze and display its telemetry. The CMS software is targeted for all phases of the SHOOT project: hardware development, pre-flight pad servicing, in-flight operations, and post-flight data analysis

Climate and livestock disease: assessing the vulnerability of agricultural systems to livestock pests under climate change scenarios

Livestock as a sector is extremely important to the global economy and to rural livelihoods. As of 2013, there was an estimated 38 billion livestock in the world, or five animals for every person. Most (81%) were in developing countries. Around one billion smallholder farmers keep livestock, many of them women. The burden of animal disease in developing countries is high: livestock disease probably kills 20% of ruminants and more than 50% of poultry each year causing a loss of approximately USD 300 billion per year. Climate change can exacerbate disease in livestock, and some diseases are especially sensitive to climate change. Among 65 animal diseases identified as most important to poor livestock keepers, 58% are climate sensitive. Climate change may also have indirect effects on animal disease, and these may be greater than the direct effects

The Evolution of Dust Opacity in Galaxies

(Abridged) We investigate the evolution of the opacity of galaxies as a function of redshift, using simple assumptions about the metal and dust enrichment of the gas and the distribution of dust in galaxies. We use an iterative procedure to reconstruct the intrinsic Star Formation Rate (SFR) density of galaxies with redshift, by applying dust obscuration corrections to the observed UV emission. The iterative procedure converges to multiple solutions for the intrinsic SFR density, divided into two basic classes. The first class of solutions predicts relatively large UV attenuation at high redshift, with A(1500 A)=1.9 mag at z~3, and smaller attenuations at z<1, with A(2800 A)=1.25 mag. The SFR density of this set of solutions is constant for z>~1.2 and declines for z<1.2; it resembles in shape the ``monolithic collapse'' scenario for star formation. The second class of solutions predicts relatively low UV attenuations at high redshift, with A(1500 A)=0.75 mag at z~3, and larger attenuations at z<1, with A(2800 A)=1.50 mag. The SFR density in this case has a peak at z~1.2. The advantages and shortcomings of both classes are analyzed in the light of available observational constraints, including the opacity of galaxies at 0<z<1 and the intensity and spectral energy distribution of the cosmic infrared background from the COBE DIRBE and FIRAS data. We conclude that both classes of models are acceptable within the current uncertainties, but the ``monolithic collapse'' class matches the available observations better than the other one. We also investigate the dependence of our solutions on the different model assumptions.Comment: 54 pages, includes 1 embedded postscript Table and 22 embedded postscript Figures, Latex, uses AAS Latex macro. Accepted for publication in the Astrophysical Journa

Is cancer stage data missing completely at random? A report from a large population-based cohort of non-small cell lung cancer

IntroductionPopulation-based datasets are often used to estimate changes in utilization or outcomes of novel therapies. Inclusion or exclusion of unstaged patients may impact on interpretation of these studies.MethodsA large population-based dataset in Ontario, Canada of non-small cell lung cancer patients was examined to evaluate the characteristics and outcomes of unstaged patients compared to staged patients. Multivariable Poisson regression was used to evaluate differences in patient-level characteristics between groups. Kaplan-Meier estimates of survival and log-rank statistics were utilized.ResultsIn our Ontario cohort of 51,152 patients with NSCLC, 11.2% (n=5,707) were unstaged, and there was evidence that stage data was not missing completely at random. Those without assigned stage were more likely than staged patients to be older (RR [95%CI]), (70-79 vs. 20-59: 1.51 [1.38-1.66]; 80+ vs. 20-59: 2.87 [2.62-3.15]), have a higher comorbidity index (Score 1-2 vs 0: 1.19 [1.12-1.27]; 3 vs. 0: 1.49 [1.38-1.60]), and have a lower socioeconomic class (4 vs. 1 (lowest): 0.91 [0.84-0.98]; 5 vs. 1 (lowest): 0.89 [0.83-0.97]). Overall survival of unstaged patients suggested a mixture of early and advanced stage, but with a large proportion that are probably stage IV patients with more rapid death than those with reported stage IV disease.ConclusionIn this case study, evaluation of stage-specific health care utilization and outcomes for staged patients with stage IV disease at the population level may have a bias as a distinct subset of stage IV patients with rapid death are likely among those without a documented stage in administrative data

Locating poor livestock keepers at the global level for research and development targeting

P.K. Thornton, R.L. Kruska, P.M. Kristjanson, R.S. Reid and T.P. Robinson are ILRI authorsMany research and development agencies are committed to halving the number of people living in extreme poverty by 2015. Knowledge of where the poor are, and what characterises them, is patchy at best. Here we describe a global livestock and poverty mapping study designed to assist in targeting research and development activities concerning livestock. Estimates of the numbers of poor livestock keepers by production system and region are presented. While these estimates suffer from various problems, improvements in global databases are critical to improve the targeting of interventions that can meet the challenges posed by poverty and to chart progress against international development indicators