306 research outputs found

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

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    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

    New measures to capture end of life concerns in Huntington disease: Meaning and Purpose and Concern with Death and Dying from HDQLIFE (a patient-reported outcomes measurement system).

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    PURPOSE: Huntington disease (HD) is an incurable terminal disease. Thus, end of life (EOL) concerns are common in these individuals. A quantitative measure of EOL concerns in HD would enable a better understanding of how these concerns impact health-related quality of life. Therefore, we developed new measures of EOL for use in HD. METHODS: An EOL item pool of 45 items was field tested in 507 individuals with prodromal or manifest HD. Exploratory and confirmatory factor analyses (EFA and CFA, respectively) were conducted to establish unidimensional item pools. Item response theory (IRT) and differential item functioning analyses were applied to the identified unidimensional item pools to select the final items. RESULTS: EFA and CFA supported two separate unidimensional sets of items: Concern with Death and Dying (16 items), and Meaning and Purpose (14 items). IRT and DIF supported the retention of 12 Concern with Death and Dying items and 4 Meaning and Purpose items. IRT data supported the development of both a computer adaptive test (CAT) and a 6-item, static short form for Concern with Death and Dying. CONCLUSION: The HDQLIFE Concern with Death and Dying CAT and corresponding 6-item short form, and the 4-item calibrated HDQLIFE Meaning and Purpose scale demonstrate excellent psychometric properties. These new measures have the potential to provide clinically meaningful information about end-of-life preferences and concerns to clinicians and researchers working with individuals with HD. In addition, these measures may also be relevant and useful for other terminal conditions

    Computational Physics on Graphics Processing Units

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    The use of graphics processing units for scientific computations is an emerging strategy that can significantly speed up various different algorithms. In this review, we discuss advances made in the field of computational physics, focusing on classical molecular dynamics, and on quantum simulations for electronic structure calculations using the density functional theory, wave function techniques, and quantum field theory.Comment: Proceedings of the 11th International Conference, PARA 2012, Helsinki, Finland, June 10-13, 201

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

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    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

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

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    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

    Real-time gradient-domain painting

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    A Full-Depth Amalgamated Parallel 3D Geometric Multigrid Solver for GPU Clusters

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    Numerical computations of incompressible flow equations with pressure-based algorithms necessitate the solution of an elliptic Poisson equation, for which multigrid methods are known to be very efficient. In our previous work we presented a dual-level (MPI-CUDA) parallel implementation of the Navier-Stokes equations to simulate buoyancy-driven incompressible fluid flows on GPU clusters with simple iterative methods while focusing on the scalability of the overall solver. In the present study we describe the implementation and performance of a multigrid method to solve the pressure Poisson equation within our MPI-CUDA parallel incompressible flow solver. Various design decisions and algorithmic choices for multigrid methods are explored in light of NVIDIA’s recent Fermi architecture. We discuss how unique aspects of an MPI-CUDA implementation for GPU clusters is related to the software choices made to implement the multigrid method. We propose a new coarse grid solution method of embedded multigrid with amalgamation and show that the parallel implementation retains the numerical efficiency of the multigrid method. Performance measurements on the NCSA Lincoln and TACC Longhorn clusters are presented for up to 64 GPUs

    Rationale, design, and methodology for the optimizing outcomes in women with gestational diabetes mellitus and their infants study

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    Background Women who are diagnosed with gestational diabetes mellitus (GDM) are at increased risk for developing prediabetes and type 2 diabetes mellitus (T2DM). To date, there have been few interdisciplinary interventions that target predominantly ethnic minority low-income women diagnosed with GDM. This paper describes the rationale, design and methodology of a 2-year, randomized, controlled study being conducted in North Carolina. Methods/Design Using a two-group, repeated measures, experimental design, we will test a 14- week intensive intervention on the benefits of breastfeeding, understanding gestational diabetes and risk of progression to prediabetes and T2DM, nutrition and exercise education, coping skills training, physical activity (Phase I), educational and motivational text messaging and 3 months of continued monthly contact (Phase II). A total of 100 African American, non-Hispanic white, and bilingual Hispanic women between 22–36 weeks of pregnancy who are diagnosed with GDM and their infants will be randomized to either the experimental group or the wait-listed control group. The first aim of the study is to determine the feasibility of the intervention. The second aim of study is to test the effects of the intervention on maternal outcomes from baseline (22–36 weeks pregnant) to 10 months postpartum. Primary maternal outcomes will include fasting blood glucose and weight (BMI) from baseline to 10 months postpartum. Secondary maternal outcomes will include clinical, adiposity, health behaviors and self-efficacy outcomes from baseline to 10 months postpartum. The third aim of the study is to quantify the effects of the intervention on infant feeding and growth. Infant outcomes will include weight status and breastfeeding from birth through 10 months of age. Data analysis will include general linear mixed-effects models. Safety endpoints include adverse event reporting. Discussion Findings from this trial may lead to an effective intervention to assist women diagnosed with GDM to improve maternal glucose homeostasis and weight as well as stabilize infant growth trajectory, reducing the burden of metabolic disease across two generations. Trial registration NCT0180943

    HDQLIFE: Development and Assessment of Health-Related Quality of Life in Huntington Disease (HD)

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    PURPOSE: Huntington disease (HD) is a chronic, debilitating genetic disease that affects physical, emotional, cognitive, and social health. Existing patient-reported outcomes (PROs) of health-related quality of life (HRQOL) used in HD are neither comprehensive, nor do they adequately account for clinically meaningful changes in function. While new PROs examining HRQOL (i.e., Neuro-QoL-Quality of Life in Neurological Disorders and PROMIS-Patient-Reported Outcomes Measurement Information System) offer solutions to many of these shortcomings, they do not include HD-specific content, nor have they been validated in HD. HDQLIFE addresses this by validating 12 PROMIS/Neuro-QoL domains in individuals with HD and by using established PROMIS methodology to develop new, HD-specific content. METHODS: New item pools were developed using cognitive debriefing with individuals with HD, and expert, literacy, and translatability reviews. Existing item banks and new item pools were field tested in 536 individuals with prodromal, early-, or late-stage HD. RESULTS: Moderate to strong relationships between Neuro-QoL/PROMIS measures and generic self-report measures of HRQOL, and moderate relationships between Neuro-QoL/PROMIS and clinician-rated measures of similar constructs supported the validity of Neuro-QoL/PROMIS in individuals with HD. Exploratory and confirmatory factor analysis, item response theory, and differential item functioning analyses were utilized to develop new item banks for Chorea, Speech Difficulties, Swallowing Difficulties, and Concern with Death and Dying, with corresponding six-item short forms. A four-item short form was developed for Meaning and Purpose. CONCLUSIONS: HDQLIFE encompasses both validated Neuro-QoL/PROMIS measures, as well as five new scales in order to provide a comprehensive assessment of HRQOL in HD

    Deviant Peer Affiliation and Antisocial Behavior: Interaction with Monoamine Oxidase A (MAOA) Genotype

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    Although genetic and environmental factors are separately implicated in the development of antisocial behavior (ASB), interactive models have emerged relatively recently, particularly those incorporating molecular genetic data. Using a large sample of male Caucasian adolescents and young adults from the National Longitudinal Study of Adolescent Health (Add Health), the association of deviant peer affiliation, the 30-base pair variable number tandem repeat polymorphism in promoter region of the monoamine oxidase-A (MAOA) gene, and their interaction, with antisocial behavior (ASB) was investigated. Weighted analyses accounting for over-sampling and clustering within schools as well as controlling for age and wave suggested that deviant peer affiliation and MAOA genotype were each significantly associated with levels of overt ASB across a 6-year period. Only deviant peer affiliation was significantly related to covert ASB, however. Additionally, there was evidence suggestive of a gene-environment interaction (G Ă— E) where the influence of deviant peer affiliation on overt ASB was significantly stronger among individuals with the high-activity MAOA genotype than the low-activity genotype. MAOA was not significantly associated with deviant peer affiliation, thus strengthening the inference of G Ă— E rather than gene-environment correlation (rGE). Different forms of gene-environment interplay and implications for future research on ASB are discussed
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