25 research outputs found

    The Formation of Short Period Binary Star Systems From Stable, Self-Gravitating, Gaseous Bars.

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    Although we have a general understanding of how stars form, and there. are accepted theories that explain the formation of long-period binaries, we do not yet understand how short period binaries form. Here we present simulations that clearly demonstrate how such systems may form naturally from dense interstellar gas clouds. First, we present two models of compressible, self-gravitating fluid configurations with bar-like structures and supersonic internal motions. Both models have been constructed via dynamical simulations that have started from initially axisymmetric, rapidly rotating polytropes that were known to be dynamically unstable toward the development of a bar-like or two-armed spiral structure. The two initial models differed mainly in their initial angular momentum distributions. In each case, the nonlinear development of the dynamical instability results in the formation of a bar-like configuration that is spinning with a well-defined pattern speed. By all accounts, these models appear to be compressible analogs of Riemann ellipsoids. Our final steady-state configurations appear to be dynamically stable and include a mild standing shock front. We have allowed one of these dynamically stable, triaxial configurations to cool slowly and have continually followed its dynamical evolution. A binary instability, results after reducing the mean pressure of the configuration to ∼50% of its original value. The instability appears as an oscillation between two configurations: One that resembles a common envelope binary system with circulation around the two local density maxima, and the other that appears to be an ellipsoidal configuration with density maxima near the center. Unfortunately, as the model cools, it continues to contract and becomes less well resolved in our numerical grid. Hence, we have not been able to follow this instability to its ultimate fate. However, the strength and nature of the instability lead us to conclude that fission will be the outcome. This work provides the strongest evidence, to date, that short period binary stars form in a very natural way through a fission instability, as proposed by Lebovitz (1987), that fission is the only possible outcome

    Alternative Fourier Expansions for Inverse Square Law Forces

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    Few-body problems involving Coulomb or gravitational interactions between pairs of particles, whether in classical or quantum physics, are generally handled through a standard multipole expansion of the two-body potentials. We discuss an alternative based on a compact, cylindrical Green's function expansion that should have wide applicability throughout physics. Two-electron "direct" and "exchange" integrals in many-electron quantum systems are evaluated to illustrate the procedure which is more compact than the standard one using Wigner coefficients and Slater integrals.Comment: 10 pages, latex/Revtex4, 1 figure

    Intronic Cis-Regulatory Modules Mediate Tissue-Specific and Microbial Control of angptl4/fiaf Transcription

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    The intestinal microbiota enhances dietary energy harvest leading to increased fat storage in adipose tissues. This effect is caused in part by the microbial suppression of intestinal epithelial expression of a circulating inhibitor of lipoprotein lipase called Angiopoietin-like 4 (Angptl4/Fiaf). To define the cis-regulatory mechanisms underlying intestine-specific and microbial control of Angptl4 transcription, we utilized the zebrafish system in which host regulatory DNA can be rapidly analyzed in a live, transparent, and gnotobiotic vertebrate. We found that zebrafish angptl4 is transcribed in multiple tissues including the liver, pancreatic islet, and intestinal epithelium, which is similar to its mammalian homologs. Zebrafish angptl4 is also specifically suppressed in the intestinal epithelium upon colonization with a microbiota. In vivo transgenic reporter assays identified discrete tissue-specific regulatory modules within angptl4 intron 3 sufficient to drive expression in the liver, pancreatic islet Ξ²-cells, or intestinal enterocytes. Comparative sequence analyses and heterologous functional assays of angptl4 intron 3 sequences from 12 teleost fish species revealed differential evolution of the islet and intestinal regulatory modules. High-resolution functional mapping and site-directed mutagenesis defined the minimal set of regulatory sequences required for intestinal activity. Strikingly, the microbiota suppressed the transcriptional activity of the intestine-specific regulatory module similar to the endogenous angptl4 gene. These results suggest that the microbiota might regulate host intestinal Angptl4 protein expression and peripheral fat storage by suppressing the activity of an intestine-specific transcriptional enhancer. This study provides a useful paradigm for understanding how microbial signals interact with tissue-specific regulatory networks to control the activity and evolution of host gene transcription

    The iPlant Collaborative: Cyberinfrastructure for Plant Biology

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    The iPlant Collaborative (iPlant) is a United States National Science Foundation (NSF) funded project that aims to create an innovative, comprehensive, and foundational cyberinfrastructure in support of plant biology research (PSCIC, 2006). iPlant is developing cyberinfrastructure that uniquely enables scientists throughout the diverse fields that comprise plant biology to address Grand Challenges in new ways, to stimulate and facilitate cross-disciplinary research, to promote biology and computer science research interactions, and to train the next generation of scientists on the use of cyberinfrastructure in research and education. Meeting humanity's projected demands for agricultural and forest products and the expectation that natural ecosystems be managed sustainably will require synergies from the application of information technologies. The iPlant cyberinfrastructure design is based on an unprecedented period of research community input, and leverages developments in high-performance computing, data storage, and cyberinfrastructure for the physical sciences. iPlant is an open-source project with application programming interfaces that allow the community to extend the infrastructure to meet its needs. iPlant is sponsoring community-driven workshops addressing specific scientific questions via analysis tool integration and hypothesis testing. These workshops teach researchers how to add bioinformatics tools and/or datasets into the iPlant cyberinfrastructure enabling plant scientists to perform complex analyses on large datasets without the need to master the command-line or high-performance computational services

    BIEN2 grafted phylogeny (rep. 1)

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    Phylogeny of 81,274 terrestrial vascular plants found in the BIEN2 database (Enquist et al. 2016). To assemble this phylogeny a species-level multi-gene tree for ~65,000 species was made from the atpB-rbcL, ndhF, psbA, psbA-psbH, rbcL, and trnT-trnL-trnF regions via the software program PHLAWD (Smith et al. 2009), which automatically queries GenBank sequence records. The tree was estimated using RAxML 7.3.0 (Stamatakis 2006) with the unconstrained maximum likelihood search method and treePL[2] (Smith & O’meara 2012) was used to estimate divergence times. Remaining taxa from the 88,824 in the BIEN2 database without genetic data were randomly placed within their genus or removed if generic affinities were not known. REFERENCES Enquist, B.J., Condit, R., Peet, R.K., Schildhauer, M. & Thiers, B.M. (2016). Cyberinfrastructure for an integrated botanical information network to investigate the ecological impacts of global climate change on plant biodiversity. PeerJ Preprints, e2615v1. Smith, S.A., Beaulieu, J.M. & Donoghue, M.J. (2009). Mega-phylogeny approach for comparative biology: an alternative to supertree and supermatrix approaches. BMC Evolutionary Biology, 9, 37. Smith, S.A. & O’meara, B.C. (2012). treePL: divergence time estimation using penalized likelihood for large phylogenies. Bioinformatics, 28, 2689-2690. Stamatakis, A. (2006). RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics, 22, 2688-2690
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