Experimental Study of High-Z Gas Buffers in Gas-Filled ICF Engines

ICF power plants, such as the LIFE scheme at LLNL, may employ a high-Z, target-chamber gas-fill to moderate the first-wall heat-pulse due to x-rays and energetic ions released during target detonation. To reduce the uncertainties of cooling and beam/target propagation through such gas-filled chambers, we present a pulsed plasma source producing 2-5 eV plasma comprised of high-Z gases. We use a 5-kJ, 100-ns theta discharge for high peak plasma-heating-power, an electrode-less discharge for minimizing impurities, and unobstructed axial access for diagnostics and beam (and/or target) propagation studies. We will report on the plasma source requirements, design process, and the system design

Assessment of Dietary Intake, Energy Status, and Factors Associated With RED-S in Vocational Female Ballet Students

Elite ballet dancers are at risk of health issues associated with Relative Energy Deficiency in Sport (RED-S). This study determined the nutritional status, estimated energy status, and assessed factors related to RED-S in vocational female ballet students. Using a cross-sectional study design, we measured dietary intake (n=20; food diaries and 24hr dietary-recall) and energy expenditure (n=18; accelerometry) in vocational female ballet students (age: 18.1±1.1 years; body mass index: 19.0±1.6 kg·m2; body fat: 22.8±3.4 %) over 7 days, including 5 weekdays (with dance training) and 2 weekend days (without scheduled dance training). Furthermore, we assessed eating behaviours, menstrual function, risk of RED-S (questionnaires), and body composition (dual x-ray absorptiometry). Energy and macronutrient intakes of vocational ballet students were similar during weekdays and weekend days (P > 0.050), whereas total energy expenditure was greater on weekdays than weekend days (P < 0.010; 95% CI: 212, 379). Energy balance was lower on weekdays (-425±465 kcal·day-1) than weekend days (-6±506 kcal·day-1, P=0.015; 95% CI: -748, -92). Exercise energy expenditure was greater on weekdays (393±103 kcal·day-1) than weekend days (213±129 kcal·day-1;

Sequential Monte-Carlo Framework for Dynamic Data-Driven Event Reconstruction for Atmospheric Release

The release of hazardous materials into the atmosphere can have a tremendous impact on dense populations. We propose an atmospheric event reconstruction framework that couples observed data and predictive computer-intensive dispersion models via Bayesian methodology. Due to the complexity of the model framework, a sampling-based approach is taken for posterior inference that combines Markov chain Monte Carlo (MCMC) and sequential Monte Carlo (SMC) strategies

Maintaining distances with the engineer: patterns of coexistence in plant communities beyond the patch-bare dichotomy

Two-phase plant communities with an engineer conforming conspicuous patches and affecting the performance and patterns of coexisting species are the norm under stressful conditions. To unveil the mechanisms governing coexistence in these communities at multiple spatial scales, we have developed a new point-raster approach of spatial pattern analysis, which was applied to a Mediterranean high mountain grassland to show how Festuca curvifolia patches affect the local distribution of coexisting species. We recorded 22 111 individuals of 17 plant perennial species. Most coexisting species were negatively associated with F. curvifolia clumps. Nevertheless, bivariate nearest-neighbor analyses revealed that the majority of coexisting species were confined at relatively short distances from F. curvifolia borders (between 0-2 cm and up to 8 cm in some cases). Our study suggests the existence of a fine-scale effect of F. curvifolia for most species promoting coexistence through a mechanism we call 'facilitation in the halo'. Most coexisting species are displaced to an interphase area between patches, where two opposite forces reach equilibrium: attenuated severe conditions by proximity to the F. curvifolia canopy (nutrient-rich islands) and competitive exclusion mitigated by avoiding direct contact with F. curvifolia

Reconstructing the reproductive mode of an Ediacaran macro-organism.

Enigmatic macrofossils of late Ediacaran age (580-541 million years ago) provide the oldest known record of diverse complex organisms on Earth, lying between the microbially dominated ecosystems of the Proterozoic and the Cambrian emergence of the modern biosphere. Among the oldest and most enigmatic of these macrofossils are the Rangeomorpha, a group characterized by modular, self-similar branching and a sessile benthic habit. Localized occurrences of large in situ fossilized rangeomorph populations allow fundamental aspects of their biology to be resolved using spatial point process techniques. Here we use such techniques to identify recurrent clustering patterns in the rangeomorph Fractofusus, revealing a complex life history of multigenerational, stolon-like asexual reproduction, interspersed with dispersal by waterborne propagules. Ecologically, such a habit would have allowed both for the rapid colonization of a localized area and for transport to new, previously uncolonized areas. The capacity of Fractofusus to derive adult morphology by two distinct reproductive modes documents the sophistication of its underlying developmental biology.This work has been supported by the Natural Environment Research Council [grant numbers NE/I005927/1 to C.G.K., NE/J5000045/1 to J.J.M., NE/L011409/1 to A.G.L. and NE/G523539/1 to E.G.M.], and a Henslow Junior Research Fellowship from Cambridge Philosophical Society to A.G.L.This is the author accepted manuscript. The final version is available from NPG via http://dx.doi.org/10.1038/nature1464

Dynamic Data-Driven Event Reconstruction for Atmospheric Releases

Accidental or terrorist releases of hazardous materials into the atmosphere can impact large populations and cause significant loss of life or property damage. Plume predictions have been shown to be extremely valuable in guiding an effective and timely response. The two greatest sources of uncertainty in the prediction of the consequences of hazardous atmospheric releases result from poorly characterized source terms and lack of knowledge about the state of the atmosphere as reflected in the available meteorological data. In this report, we discuss the development of a new event reconstruction methodology that provides probabilistic source term estimates from field measurement data for both accidental and clandestine releases. Accurate plume dispersion prediction requires the following questions to be answered: What was released? When was it released? How much material was released? Where was it released? We have developed a dynamic data-driven event reconstruction capability which couples data and predictive models through Bayesian inference to obtain a solution to this inverse problem. The solution consists of a probability distribution of unknown source term parameters. For consequence assessment, we then use this probability distribution to construct a ''''composite'' forward plume prediction which accounts for the uncertainties in the source term. Since in most cases of practical significance it is impossible to find a closed form solution, Bayesian inference is accomplished by utilizing stochastic sampling methods. This approach takes into consideration both measurement and forward model errors and thus incorporates all the sources of uncertainty in the solution to the inverse problem. Stochastic sampling methods have the additional advantage of being suitable for problems characterized by a non-Gaussian distribution of source term parameters and for cases in which the underlying dynamical system is non-linear. We initially developed a Markov Chain Monte Carlo (MCMC) stochastic methodology and demonstrated its effectiveness by reconstructing a wide range of release scenarios, using synthetic as well as real-world data. Data for evaluation of our event reconstruction capability were drawn from the short-range Prairie Grass, Copenhagen, and Joint Urban 2003 field experiments and a continental-scale real-world accidental release in Algeciras, Spain. The method was tested using a variety of forward models, including a Gaussian puff dispersion model INPUFF, the regional-to-continental scale Lagrangian dispersion model LODI (the work-horse real-time operational dispersion model used by the National Atmospheric Release Advisory Center), the empirical urban model UDM, and the building-scale computational computational fluid dynamics code FEM3MP. The robustness of the Bayesian methodology was demonstrated via the use of subsets of the available concentration data and by introducing error into some of the measurements. These tests showed that the Bayesian approach is capable of providing reliable estimates of source characteristics even in cases of limited or significantly corrupted data. For more effective treatment of strongly time-dependent problems, we developed a Sequential Monte Carlo (SMC) approach. To achieve the best performance under a wide range of conditions we combined SMC and MCMC sampling into a hybrid methodology. We compared the effectiveness and advantages of this approach relative to MCMC using a set of synthetic data examples. Our dynamic data-driven event reconstruction capability seamlessly integrates observational data streams with predictive models, in order to provide the best possible estimates of unknown source term parameters, as well as optimal and timely situation analyses consistent with both models and data

Sequestration and Scavenging of Iron in Infection

The proliferative capability of many invasive pathogens is limited by the bioavailability of iron. Pathogens have thus developed strategies to obtain iron from their host organisms. In turn, host defense strategies have evolved to sequester iron from invasive pathogens. This review explores the mechanisms employed by bacterial pathogens to gain access to host iron sources, the role of iron in bacterial virulence, and iron-related genes required for the establishment or maintenance of infection. Host defenses to limit iron availability for bacterial growth during the acute-phase response and the consequences of iron overload conditions on susceptibility to bacterial infection are also examined. The evidence summarized herein demonstrates the importance of iron bioavailability in influencing the risk of infection and the ability of the host to clear the pathogen

Dust Devil Sediment Transport: From Lab to Field to Global Impact

The impact of dust aerosols on the climate and environment of Earth and Mars is complex and forms a major area of research. A difficulty arises in estimating the contribution of small-scale dust devils to the total dust aerosol. This difficulty is due to uncertainties in the amount of dust lifted by individual dust devils, the frequency of dust devil occurrence, and the lack of statistical generality of individual experiments and observations. In this paper, we review results of observational, laboratory, and modeling studies and provide an overview of dust devil dust transport on various spatio-temporal scales as obtained with the different research approaches. Methods used for the investigation of dust devils on Earth and Mars vary. For example, while the use of imagery for the investigation of dust devil occurrence frequency is common practice for Mars, this is less so the case for Earth. Modeling approaches for Earth and Mars are similar in that they are based on the same underlying theory, but they are applied in different ways. Insights into the benefits and limitations of each approach suggest potential future research focuses, which can further reduce the uncertainty associated with dust devil dust entrainment. The potential impacts of dust devils on the climates of Earth and Mars are discussed on the basis of the presented research results