Thermal performance test of the A-2H Apollo Extravehicular Mobility Unit, volume I

Thermal and pressure evaluation testing for Apollo Extravehicular Mobility Unit /EMU

Unmanned thermal performance evaluation of a Gemini extravehicular space suit. Volume 1 - Test report Gemini Bravo test series space environment simulator test

Thermal and space environment simulation testing of Gemini extravehicular space sui

Phalangid fauna of Trinidad

13 p. : ill. ; 24 cm.Includes bibliographical references

Space environment simulator test program. Volume 2 - Unmanned thermal performance evaluation of a Gemini extravehicular space suit Test report, May 1965

Temperature data plots of Gemini Bravo series space suit test

A Path Algorithm for Constrained Estimation

Many least squares problems involve affine equality and inequality constraints. Although there are variety of methods for solving such problems, most statisticians find constrained estimation challenging. The current paper proposes a new path following algorithm for quadratic programming based on exact penalization. Similar penalties arise in $l_1$ regularization in model selection. Classical penalty methods solve a sequence of unconstrained problems that put greater and greater stress on meeting the constraints. In the limit as the penalty constant tends to $\infty$, one recovers the constrained solution. In the exact penalty method, squared penalties are replaced by absolute value penalties, and the solution is recovered for a finite value of the penalty constant. The exact path following method starts at the unconstrained solution and follows the solution path as the penalty constant increases. In the process, the solution path hits, slides along, and exits from the various constraints. Path following in lasso penalized regression, in contrast, starts with a large value of the penalty constant and works its way downward. In both settings, inspection of the entire solution path is revealing. Just as with the lasso and generalized lasso, it is possible to plot the effective degrees of freedom along the solution path. For a strictly convex quadratic program, the exact penalty algorithm can be framed entirely in terms of the sweep operator of regression analysis. A few well chosen examples illustrate the mechanics and potential of path following.Comment: 26 pages, 5 figure

Scale-free vortex cascade emerging from random forcing in a strongly coupled system

The notions of self-organised criticality (SOC) and turbulence are traditionally considered to be applicable to disjoint classes of phenomena. Nevertheless, scale-free burst statistics is a feature shared by turbulent as well as self-organised critical dynamics. It has also been suggested that another shared feature is universal non-gaussian probability density functions (PDFs) of global fluctuations. Here, we elucidate the unifying aspects through analysis of data from a laboratory dusty plasma monolayer. We compare analysis of experimental data with simulations of a two-dimensional (2D) many-body system, of 2D fluid turbulence, and a 2D SOC model, all subject to random forcing at small scales. The scale-free vortex cascade is apparent from structure functions as well as spatio-temporal avalanche analysis, the latter giving similar results for the experimental and all model systems studied. The experiment exhibits global fluctuation statistics consistent with a non-gaussian universal PDF, but the model systems yield this result only in a restricted range of forcing conditions

Altruism can proliferate through group/kin selection despite high random gene flow

The ways in which natural selection can allow the proliferation of cooperative behavior have long been seen as a central problem in evolutionary biology. Most of the literature has focused on interactions between pairs of individuals and on linear public goods games. This emphasis led to the conclusion that even modest levels of migration would pose a serious problem to the spread of altruism in group structured populations. Here we challenge this conclusion, by analyzing evolution in a framework which allows for complex group interactions and random migration among groups. We conclude that contingent forms of strong altruism can spread when rare under realistic group sizes and levels of migration. Our analysis combines group-centric and gene-centric perspectives, allows for arbitrary strength of selection, and leads to extensions of Hamilton's rule for the spread of altruistic alleles, applicable under broad conditions.Comment: 5 pages, 2 figures. Supplementary material with 50 pages and 26 figure

Maternal super-obesity (body mass index ≥ 50) and adverse pregnancy outcomes

Abstract Objective. To determine if pregnancy complications are increased in super-obese (a body mass index (BMI) of 50 or more) compared to other, less obese parturients. Design. Cross-sectional study. Setting and population. All 19,700 eligible women, including 425 (2.2%) super-obese women with singleton births between 1996 and 2007 delivering at a tertiary referral center, identified using a perinatal research database. Methods. Bivariate and trend analyses were used to assess the relation between super-obesity and various pregnancy complications compared to other well-established BMI categories. Adjusted odds ratios (ORs) were calculated using multivariable logistic regression techniques. Main outcome measures. Outcomes for adjusted and unadjusted analyses were small-for-gestational age (SGA) birth, large-for-gestational age (LGA) birth, preeclampsia, gestational diabetes mellitus (GDM), fetal death, preterm birth, placental abruption, cesarean delivery, and Apgar scores < 7. Results. Compared to all other obese and non-obese women, super-obese women had the highest rates of preeclampsia, GDM, LGA, and cesarean delivery (all p < 0.05 for trend test). Super-obesity was also associated with a 44% reduction in SGA compared to all other women (OR 0.55, 95% confidence interval (CI) 0.40–0.76) and a 25% reduction compared to other, less obese women (OR 0.75, 95% CI 0.54–1.03). Super-obesity was positively associated with LGA, GDM, preeclampsia, cesarean delivery, and a 5-minute Apgar score < 7 compared to all other women after controlling for important confounders. Conclusion. Super-obesity is associated with higher rates of pregnancy complications compared to women of all other BMI classes, including other obese women

An MPI-CUDA Implementation for Massively Parallel Incompressible Flow Computations on Multi-GPU Clusters

Modern graphics processing units (GPUs) with many-core architectures have emerged as general-purpose parallel computing platforms that can accelerate simulation science applications tremendously. While multi-GPU workstations with several TeraFLOPS of peak computing power are available to accelerate computational problems, larger problems require even more resources. Conventional clusters of central processing units (CPU) are now being augmented with multiple GPUs in each compute-node to tackle large problems. The heterogeneous architecture of a multi-GPU cluster with a deep memory hierarchy creates unique challenges in developing scalable and efficient simulation codes. In this study, we pursue mixed MPI-CUDA implementations and investigate three strategies to probe the efficiency and scalability of incompressible flow computations on the Lincoln Tesla cluster at the National Center for Supercomputing Applications (NCSA). We exploit some of the advanced features of MPI and CUDA programming to overlap both GPU data transfer and MPI communications with computations on the GPU. We sustain approximately 2.4 TeraFLOPS on the 64 nodes of the NCSA Lincoln Tesla cluster using 128 GPUs with a total of 30,720 processing elements. Our results demonstrate that multi-GPU clusters can substantially accelerate computational fluid dynamics (CFD) simulations