113 research outputs found

    Synthetic LISA: Simulating Time Delay Interferometry in a Model LISA

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    We report on three numerical experiments on the implementation of Time-Delay Interferometry (TDI) for LISA, performed with Synthetic LISA, a C++/Python package that we developed to simulate the LISA science process at the level of scientific and technical requirements. Specifically, we study the laser-noise residuals left by first-generation TDI when the LISA armlengths have a realistic time dependence; we characterize the armlength-measurements accuracies that are needed to have effective laser-noise cancellation in both first- and second-generation TDI; and we estimate the quantization and telemetry bitdepth needed for the phase measurements. Synthetic LISA generates synthetic time series of the LISA fundamental noises, as filtered through all the TDI observables; it also provides a streamlined module to compute the TDI responses to gravitational waves according to a full model of TDI, including the motion of the LISA array and the temporal and directional dependence of the armlengths. We discuss the theoretical model that underlies the simulation, its implementation, and its use in future investigations on system characterization and data-analysis prototyping for LISA.Comment: 18 pages, 14 EPS figures, REVTeX 4. Accepted PRD version. See http://www.vallis.org/syntheticlisa for information on the Synthetic LISA software packag

    Logarithmic growth dynamics in software networks

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    In a recent paper, Krapivsky and Redner (Phys. Rev. E, 71 (2005) 036118) proposed a new growing network model with new nodes being attached to a randomly selected node, as well to all ancestors of the target node. The model leads to a sparse graph with an average degree growing logarithmically with the system size. Here we present compeling evidence for software networks being the result of a similar class of growing dynamics. The predicted pattern of network growth, as well as the stationary in- and out-degree distributions are consistent with the model. Our results confirm the view of large-scale software topology being generated through duplication-rewiring mechanisms. Implications of these findings are outlined.Comment: 7 pages, 3 figures, published in Europhysics Letters (2005

    The Verifying Compiler: A Grand Challenge for Computing Research

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    Abstract. This contribution proposes a set of criteria that distinguish a grand challenge in science or engineering from the many other kinds of short-term or long-term research problems that engage the interest of scientists and engineers. As an example drawn from Computer Science, it revives an old challenge: the construction and application of a verifying compiler that guarantees correctness of a program before running it. Introduction. The primary purpose of the formulation and promulgation of a grand challenge is the advancement of science or engineering. A grand challenge represents a commitment by a significant section of the research community to work together towards a common goal, agreed to be valuable and achievable by a team effort within a predicted timescale. The challenge is formulated by th

    An Agent-Based Model to study the epidemiological and evolutionary dynamics of Influenza viruses

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    <p>Abstract</p> <p>Background</p> <p>Influenza A viruses exhibit complex epidemiological patterns in a number of mammalian and avian hosts. Understanding transmission of these viruses necessitates taking into account their evolution, which represents a challenge for developing mathematical models. This is because the phrasing of multi-strain systems in terms of traditional compartmental ODE models either requires simplifying assumptions to be made that overlook important evolutionary processes, or leads to complex dynamical systems that are too cumbersome to analyse.</p> <p>Results</p> <p>Here, we develop an Individual-Based Model (IBM) in order to address simultaneously the ecology, epidemiology and evolution of strain-polymorphic pathogens, using Influenza A viruses as an illustrative example.</p> <p>Conclusions</p> <p>We carry out careful validation of our IBM against comparable mathematical models to demonstrate the robustness of our algorithm and the sound basis for this novel framework. We discuss how this new approach can give critical insights in the study of influenza evolution.</p

    Two forms of death in ageing Caenorhabditis elegans

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    Ageing generates senescent pathologies, some of which cause death. Interventions that delay or prevent lethal pathologies will extend lifespan. Here we identify life-limiting pathologies in Caenorhabditis elegans with a necropsy analysis of worms that have died of old age. Our results imply the presence of multiple causes of death. Specifically, we identify two classes of corpse: early deaths with a swollen pharynx (which we call ‘P deaths’), and later deaths with an atrophied pharynx (termed ‘p deaths’). The effects of interventions on lifespan can be broken down into changes in the frequency and/or timing of either form of death. For example, glp-1 mutation only delays p death, while eat-2 mutation reduces P death. Combining pathology and mortality analysis allows mortality profiles to be deconvolved, providing biological meaning to complex survival and mortality profiles

    Dissecting cause and effect in host-microbiome interactions using the combined worm-bug model system

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    High-throughput molecular studies are greatly advancing our knowledge of the human microbiome and its specific role in governing health and disease states. A myriad of ongoing studies aim at identifying links between microbial community disequilibria (dysbiosis) and human diseases. However, due to the inherent complexity and heterogeneity of the human microbiome we need robust experimental models that allow the systematic manipulation of variables to test the multitude of hypotheses arisen from large-scale ‘meta-omic’ projects. The nematode C. elegans combined with bacterial models offers an avenue to dissect cause and effect in host-microbiome interactions. This combined model allows the genetic manipulation of both host and microbial genetics and the use of a variety of tools, to identify pathways affecting host health. A number of recent high impact studies have used C. elegans to identify microbial pathways affecting ageing and longevity, demonstrating the power of the combined C. elegans-bacterial model. Here I will review the current state of the field, what we have learned from using C. elegans to study gut microbiome and host interactions, and the potential of using this model system in the future
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