1,067 research outputs found

    Development of the Vertebral Joints (C3 through T2) in Man

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    Anatomische Besonderheiten der Wirbelsäule

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    Systematic coarse-graining of the dynamics of entangled polymer melts: the road from chemistry to rheology

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    For optimal processing and design of entangled polymeric materials it is important to establish a rigorous link between the detailed molecular composition of the polymer and the viscoelastic properties of the macroscopic melt. We review current and past computer simulation techniques and critically assess their ability to provide such a link between chemistry and rheology. We distinguish between two classes of coarse-graining levels, which we term coarse-grained molecular dynamics (CGMD) and coarse-grained stochastic dynamics (CGSD). In CGMD the coarse-grained beads are still relatively hard, thus automatically preventing bond crossing. This also implies an upper limit on the number of atoms that can be lumped together and therefore on the longest chain lengths that can be studied. To reach a higher degree of coarse-graining, in CGSD many more atoms are lumped together, leading to relatively soft beads. In that case friction and stochastic forces dominate the interactions, and actions must be undertaken to prevent bond crossing. We also review alternative methods that make use of the tube model of polymer dynamics, by obtaining the entanglement characteristics through a primitive path analysis and by simulation of a primitive chain network. We finally review super-coarse-grained methods in which an entire polymer is represented by a single particle, and comment on ways to include memory effects and transient forces.Comment: Topical review, 31 pages, 10 figure

    Variational Perturbation Theory for Markov Processes

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    We develop a convergent variational perturbation theory for conditional probability densities of Markov processes. The power of the theory is illustrated by applying it to the diffusion of a particle in an anharmonic potential.Comment: Author Information under http://www.physik.fu-berlin.de/~kleinert/institution.html Latest update of paper also at http://www.physik.fu-berlin.de/~kleinert/33

    Implementing measurement-based care (iMBC) for depression in community mental health: a dynamic cluster randomized trial study protocol

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    BACKGROUND: Measurement-based care is an evidence-based practice for depression that efficiently identifies treatment non-responders and those who might otherwise deteriorate [1]. However, measurement-based care is underutilized in community mental health with data suggesting fewer than 20 % of behavioral health providers using this practice to inform treatment. It remains unclear whether standardized or tailored approaches to implementation are needed to optimize measurement-based care fidelity and penetration. Moreover, there is some suggestion that prospectively tailored interventions that are designed to fit the dynamic context may optimize public health impact, though no randomized trials have yet tested this notion [2]. This study will address the following three aims: (1) To compare the effect of standardized versus tailored MBC implementation on clinician-level and client-level outcomes; (2) To identify contextual mediators of MBC fidelity; and (3) To explore the impact of MBC fidelity on client outcomes. METHODS/DESIGN: This study is a dynamic cluster randomized trial of standardized versus tailored measurement-based care implementation in Centerstone, the largest provider of community-based mental health services in the USA. This prospective, mixed methods implementation-effectiveness hybrid design allows for evaluation of the two conditions on both clinician-level (e.g., MBC fidelity) and client-level (depression symptom change) outcomes. Central to this investigation is the focus on identifying contextual factors (e.g., attitudes, resources, process, etc.) that mediate MBC fidelity and optimize client outcomes. DISCUSSION: This study will contribute generalizable and practical strategies for implementing systematic symptom monitoring to inform and enhance behavioral healthcare. TRIAL REGISTRATION: Clinicaltrials.gov NCT02266134

    Low Reynolds number hydrodynamics of asymmetric, oscillating dumbbell pairs

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    Active dumbbell suspensions constitute one of the simplest model system for collective swimming at low Reynolds number. Generalizing recent work, we derive and analyze stroke-averaged equations of motion that capture the effective hydrodynamic far-field interaction between two oscillating, asymmetric dumbbells in three space dimensions. Time-averaged equations of motion, as those presented in this paper, not only yield a considerable speed-up in numerical simulations, they may also serve as a starting point when deriving continuum equations for the macroscopic dynamics of multi-swimmer suspensions. The specific model discussed here appears to be particularly useful in this context, since it allows one to investigate how the collective macroscopic behavior is affected by changes in the microscopic symmetry of individual swimmers.Comment: 10 pages, to appear in EPJ Special Topic

    OpenPNM: A Pore Network Modeling Package

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    Pore network modeling is a widely used technique for simulating multiphase transport in porous materials, but there are very few software options available. This work outlines the OpenPNM package that was jointly developed by several porous media research groups to help address this gap. OpenPNM is written in Python using NumPy and SciPy for most mathematical operations, thus combining Python's ease of use with the performance necessary to perform large simulations. The package assists the user with managing and interacting with all the topological, geometrical, and thermophysical data. It also includes a suite of commonly used algorithms for simulating percolation and performing transport calculations on pore networks. Most importantly, it was designed to be highly flexible to suit any application and be easily customized to include user-specified pore-scale physics models. The framework is fast, powerful, and concise. An illustrative example is included that determines the effective diffusivity through a partially water-saturated porous material with just 29 lines of code
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