337 research outputs found

    Lucretian moments in modern Greek poetry

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    Cavafy's quarrel with Tennyson

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    Tendon Rehabilitator

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    Our goal was to provide a cheap, portable and easy way for those suffering from medial epicondylitis tendinosis, or golfers elbow, to perform rehabbing exercises

    The progress of poesy: Kalvos, Gray and the revival of ancient literary language

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    Kalvos' poetry is, to an unusually high degree, based on what, as he saw it, "the age demanded" 1 His command of Greek, ancient or modern, was far from flawless, his sensitivity to language greater than his reading: we are not talking here of a Hellenist of the calibre of a Leopardi or a HOlderlin. Kalvos' decision to write his odes in Greek was undoubtedly a self-imposed handicap, gladly assumed in order to aid the national cause.

    Elastodynamic modeling of fluid-loaded cylindrical shells with multiple layers and internal attachments

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Ocean Engineering, 1994.Includes bibliographical references (175-181).by David C. Ricks.Ph.D

    Can community volunteers work to trace patients defaulting from scheduled psychiatric clinic appointments?

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    Reproduced with permission of the publisher

    Uniaxial Tensile Properties of AS4 3D Woven Composites with Four Different Resin Systems: Experimental Results and Analysis: Property Computations

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    As a part of the NASA Composite Technology for Exploration project, eight different AS4 3D orthogonal woven composite panels were manufactured and were subjected to mechanical testing including uniaxial tension along the weaves' warp direction. Each set, with four different resin systems (KCR-IR6070, EP2400, RTM6, and RS-50), included weave architectures designed using 12K and 6K AS4 carbon fiber yarns. For the tension testing conducted at Room Temperature Ambient (RTA) conditions, the elastic modulus and strength of these eight panels (as-processed and thermally-cycled) were measured and compared while the potential evolution of micro-cracking before and after thermal cycling were monitored via optical microscopy and X-Ray Computed Tomography. The data set also included test results of the as-processed materials at Elevated Temperature Wet (ETW) conditions. In the second part of this study, efforts were made to compute elastic constants for AS4 6K/RTM6 and AS4 12K/RTM6 materials by implementing a finite element approach and the Multiscale Generalized Method of Cells (MSGMC) technique developed at NASA Glenn Research Center. Digimat-FE was used to model the weave architectures, assign properties, calculate yarn properties, create the finite element mesh, and compute the elastic properties by applying periodic boundary conditions to finite element models of each repeating unit cell. The required input data for MSGMC was generated using Matlab from Digimat exported weave information. Experimental and computational results were compared, and the differences and limitations in correlating to the test data were briefly discussed

    Evaluation of a 2-1-1 Telephone Navigation Program to increase Cancer Control Behaviors: Results From a Randomized Controlled Trial

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    PURPOSE: to evaluate the effectiveness of a telephone navigation intervention for increasing use of cancer control services among underserved 2-1-1 callers. DESIGN: Randomized controlled trial. SETTING: 2-1-1 call centers in Houston and Weslaco, Texas (located in the Rio Grande Valley near the Mexican border). PARTICIPANTS: 2-1-1 callers in need of Pap test, mammography, colorectal cancer screening, smoking cessation counseling, and/or HPV vaccination for a daughter (n = 1,554). A majority were low-income and described themselves as Black or Hispanic. INTERVENTION: Participants were randomly assigned to receive either a cancer control referral for the needed service(s) with telephone navigation from a trained cancer control navigator (n = 995) or a referral only (n = 559). MEASURES: Uptake of each individual service and any needed service. ANALYSIS: Assessed uptake in both groups using bivariate chi-square analyses and multivariable logistic regression analyses, adjusted for sociodemographic covariates. Both per-protocol and intent-to-treat approaches were used. RESULTS: Both interventions increased cancer control behaviors. Referral with navigation intervention resulted in significantly greater completion of any needed service (OR = 1.38; p = .042), Pap test (OR = 1.56; p = .023), and smoking cessation counseling (OR = 2.66; p = .044), than referral-only condition. Other outcomes showed the same trend although the difference was not statistically significant: mammography (OR = 1.53; p = .106); colorectal cancer screening (OR = 1.80; p = .095); and HPV vaccination of a daughter (OR = 1.61; p = .331). CONCLUSION: Adding cancer control referrals and navigation to an informational service like the 2-1-1 program can increase overall participation in cancer control services

    Optimistic Planning for Markov Decision Processes

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    International audienceThe reinforcement learning community has recently intensified its interest in online planning methods, due to their relative independence on the state space size. However, tight near-optimality guarantees are not yet available for the general case of stochastic Markov decision processes and closed-loop, state-dependent planning policies. We therefore consider an algorithm related to AO* that optimistically explores a tree representation of the space of closed-loop policies, and we analyze the near-optimality of the action it returns after n tree node expansions. While this optimistic planning requires a finite number of actions and possible next states for each transition, its asymptotic performance does not depend directly on these numbers, but only on the subset of nodes that significantly impact near-optimal policies. We characterize this set by introducing a novel measure of problem complexity, called the near-optimality exponent. Specializing the exponent and performance bound for some interesting classes of MDPs illustrates the algorithm works better when there are fewer near-optimal policies and less uniform transition probabilities
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