41,285 research outputs found

    Simulating star formation in molecular cloud cores I. The influence of low levels of turbulence on fragmentation and multiplicity

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    We present the results of an ensemble of simulations of the collapse and fragmentation of dense star-forming cores. We show that even with very low levels of turbulence the outcome is usually a binary, or higher-order multiple, system. We take as the initial conditions for these simulations a typical low-mass core, based on the average properties of a large sample of observed cores. All the simulated cores start with a mass of M=5.4MM = 5.4 M_{\odot}, a flattened central density profile, a ratio of thermal to gravitational energy αtherm=0.45\alpha_{\rm therm} = 0.45 and a ratio of turbulent to gravitational energy αturb=0.05\alpha_{\rm turb} = 0.05 . Even this low level of turbulence is sufficient to produce multiple star formation in 80% of the cores; the mean number of stars and brown dwarfs formed from a single core is 4.55, and the maximum is 10. At the outset, the cores have no large-scale rotation. The only difference between each individual simulation is the detailed structure of the turbulent velocity field. The multiple systems formed in the simulations have properties consistent with observed multiple systems. Dynamical evolution tends preferentially to eject lower mass stars and brown dwarves whilst hardening the remaining binaries so that the median semi-major axis of binaries formed is 30\sim 30 au. Ejected objects are usually single low-mass stars and brown dwarfs, yielding a strong correlation between mass and multiplicity. Our simulations suggest a natural mechanism for forming binary stars that does not require large-scale rotation, capture, or large amounts of turbulence.Comment: 20 pages, 12 figures submitted to A&

    Searching for Globally Optimal Functional Forms for Inter-Atomic Potentials Using Parallel Tempering and Genetic Programming

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    We develop a Genetic Programming-based methodology that enables discovery of novel functional forms for classical inter-atomic force-fields, used in molecular dynamics simulations. Unlike previous efforts in the field, that fit only the parameters to the fixed functional forms, we instead use a novel algorithm to search the space of many possible functional forms. While a follow-on practical procedure will use experimental and {\it ab inito} data to find an optimal functional form for a forcefield, we first validate the approach using a manufactured solution. This validation has the advantage of a well-defined metric of success. We manufactured a training set of atomic coordinate data with an associated set of global energies using the well-known Lennard-Jones inter-atomic potential. We performed an automatic functional form fitting procedure starting with a population of random functions, using a genetic programming functional formulation, and a parallel tempering Metropolis-based optimization algorithm. Our massively-parallel method independently discovered the Lennard-Jones function after searching for several hours on 100 processors and covering a miniscule portion of the configuration space. We find that the method is suitable for unsupervised discovery of functional forms for inter-atomic potentials/force-fields. We also find that our parallel tempering Metropolis-based approach significantly improves the optimization convergence time, and takes good advantage of the parallel cluster architecture

    Aggregates of two-dimensional vesicles: Rouleaux and sheets

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    Using both numerical and variational minimization of the bending and adhesion energy of two-dimensional lipid vesicles, we study their aggregation, and we find that the stable aggregates include an infinite number of vesicles and that they arrange either in a columnar or in a sheet-like structure. We calculate the stability diagram and we discuss the modes of transformation between the two types of aggregates, showing that they include disintegration as well as intercalation.Comment: 4 figure

    Validation of a novel scoring system for changes in skeletal manifestations of hypophosphatasia in newborns, infants, and children: The Radiographic Global Impression of Change scale

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    Hypophosphatasia (HPP) is the heritable metabolic disease characterized by impaired skeletal mineralization due to low activity of the tissue-nonspecific isoenzyme of alkaline phosphatase. Although HPP during growth often manifests with distinctive radiographic skeletal features, no validated method was available to quantify them, including changes over time. We created the Radiographic Global Impression of Change (RGI-C) scale to assess changes in the skeletal burden of pediatric HPP. Site-specific pairs of radiographs of newborns, infants, and children with HPP from three clinical studies of asfotase alfa, an enzyme replacement therapy for HPP, were obtained at baseline and during treatment. Each pair was scored by three pediatric radiologists ( raters ), with nine raters across the three studies. Intrarater and interrater agreement was determined by weighted Kappa coefficients. Interrater reliability was assessed using intraclass correlation coefficients (ICCs) and by two-way random effects analysis of variance (ANOVA) and a mixed-model repeated measures ANOVA. Pearson correlation coefficients evaluated relationships of the RGI-C to the Rickets Severity Scale (RSS), Pediatric Outcomes Data Collection Instrument Global Function Parent Normative Score, Childhood Health Assessment Questionnaire Disability Index, 6-Minute Walk Test percent predicted, and Z-score for height in patients aged 6 to 12 years at baseline. Eighty-nine percent (8/9) of raters showed substantial or almost perfect intrarater agreement of sequential RGI-C scores (weighted Kappa coefficients, 0.72 to 0.93) and moderate or substantial interrater agreement (weighted Kappa coefficients, 0.53 to 0.71) in patients aged 0 to 12 years at baseline. Moderate-to-good interrater reliability was observed (ICC, 0.57 to 0.65). RGI-C scores were significantly (p ≤ 0.0065) correlated with the RSS and with measures of global function, disability, endurance, and growth in the patients aged 6 to 12 years at baseline. Thus, the RGI-C is valid and reliable for detecting clinically important changes in skeletal manifestations of severe HPP in newborns, infants, and children, including during asfotase alfa treatment. © 2018 The Authors. Journal of Bone and Mineral Research Published by Wiley Periodicals Inc