41 research outputs found

    Overscreening Diamagnetism in Cylindrical Superconductor-Normal Metal-Heterostructures

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    We study the linear diamagnetic response of a superconducting cylinder coated by a normal-metal layer due to the proximity effect using the clean limit quasiclassical Eilenberger equations. We compare the results for the susceptibility with those for a planar geometry. Interestingly, for R∼dR\sim d the cylinder exhibits a stronger overscreening of the magnetic field, i.e., at the interface to the superconductor it can be less than (-1/2) of the applied field. Even for R≫dR\gg d, the diamagnetism can be increased as compared to the planar case, viz. the magnetic susceptibility 4πχ4\pi\chi becomes smaller than -3/4. This behaviour can be explained by an intriguing spatial oscillation of the magnetic field in the normal layer

    Effects of Combination Antiretroviral Therapies on the Risk of Myocardial Infarction Among HIV Patients

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    Cohort studies have demonstrated greater risk of myocardial infarction (MI) associated with specific antiretroviral use, while meta-analyses of randomized controlled trials have not. These differences may be due to inherent biases in the observational study design or to the limited duration of randomized trials. We conducted a new-user, active-comparator cohort study emulating a randomized controlled trial comparing initiation of several antiretrovirals as part of combination antiretroviral therapy (cART) and MI

    Validation of Medicaid Claims-based Diagnosis of Myocardial Infarction Using an HIV Clinical Cohort

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    In non-experimental comparative effectiveness research using healthcare databases, outcome measurements must be validated to evaluate and potentially adjust for misclassification bias. We aimed to validate claims-based myocardial infarction algorithms in a Medicaid population using an HIV clinical cohort as the gold standard

    An efficient method for computing steady state solutions with Gillespie’s direct method

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    Gillespie’s direct method is a stochastic simulation algorithm that may be used to calculate the steady state solution of a chemically reacting system. Recently the all possible states method was introduced as a way of accelerating the convergence of the simulations. We demonstrate that while the all possible states (APS) method does reduce the number of required trajectories, it is actually much slower than the original algorithm for most problems. We introduce the elapsed time method, which reformulates the process of recording the species populations. The resulting algorithm yields the same results as the original method, but is more efficient, particularly for large models. In implementing the elapsed time method, we present robust methods for recording statistics and empirical probability distributions. We demonstrate how to use the histogram distance to estimate the error in steady state solutions
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