2,274 research outputs found

    Cosmic Rays from Gamma Ray Bursts in the Galaxy

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    The rate of terrestrial irradiation events by galactic gamma-ray bursts (GRBs) is estimated using recent standard-energy results. We assume that GRBs accelerate high-energy cosmic rays, and present results of three-dimensional simulations of cosmic rays moving in the Galactic magnetic field and diffusing through pitch-angle scattering. An on-axis GRB extinction event begins with a powerful prompt gamma-ray and neutron pulse, followed by a longer-lived phase from cosmic-ray protons and neutron-decay protons that diffuse towards Earth. Our results force a reinterpretation of reported ~ 10^{18} eV cosmic-ray anisotropies and offer a rigorous test of the model where high-energy cosmic rays originate from GRBs, which will soon be tested with the Auger Observatory.Comment: 9 pages, 4 figures, ApJ Letters, in press. Clarified limit of test-particle approximation, prediction that Auger will not confirm SUGAR source. (Data may not appear onscreen at low magnification.) Simulations at http://heseweb.nrl.navy.mil/gamma/~dermer/invest/sim/index.ht

    Maximum Waring Ranks of Monomials and Sums of Coprime Monomials

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    We show that monomials and sums of pairwise coprime monomials in four or more variables have Waring rank less than the generic rank, with a short list of exceptions. We asymptotically compare their ranks with the generic rank

    COMM 1311: Fundamentals of Speech Communication

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    This OER packet contains the course materials for COMM 1311: Fundamentals of Speech Communication that introduce you to why do we/I need to take a public speaking course. The answer is also always the same. “Because it is required.” However, you the reader, and us as the authors/editors, know that this doesn’t answer the question. The real answer can be complicated, but this author/editor believes that the skills gained by public speaking will help you in any field, despite whether or not you end up working in a field that requires public speaking.https://digitalcommons.pvamu.edu/pv-open-education-resources/1009/thumbnail.jp

    “Surprise” and the Bayesian Brain: Implications for Psychotherapy Theory and Practice

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    The free energy principle (FEP) has gained widespread interest and growing acceptance as a new paradigm of brain function, but has had little impact on the theory and practice of psychotherapy. The aim of this paper is to redress this. Brains rely on Bayesian inference during which “bottom-up” sensations are matched with “top-down” predictions. Discrepancies result in “prediction error.” The brain abhors informational “surprise,” which is minimized by (1) action enhancing the statistical likelihood of sensory samples, (2) revising inferences in the light of experience, updating “priors” to reality-aligned “posteriors,” and (3) optimizing the complexity of our generative models of a capricious world. In all three, free energy is converted to bound energy. In psychopathology energy either remains unbound, as in trauma and inhibition of agency, or manifests restricted, anachronistic “top-down” narratives. Psychotherapy fosters client agency, linguistic and practical. Temporary uncoupling bottom-up from top-down automatism and fostering scrutinized simulations sets a number of salutary processes in train. Mentalising enriches Bayesian inference, enabling experience and feeling states to be “metabolized” and assimilated. “Free association” enhances more inclusive sensory sampling, while dream analysis foregrounds salient emotional themes as “attractors.” FEP parallels with psychoanalytic theory are outlined, including Freud’s unpublished project, Bion’s “contact barrier” concept, the Fonagy/Target model of sexuality, Laplanche’s therapist as “enigmatic signifier,” and the role of projective identification. The therapy stimulates patients to become aware of and revise the priors’ they bring to interpersonal experience. In the therapeutic “duet for one,” the energy binding skills and non-partisan stance of the analyst help sufferers face trauma without being overwhelmed by psychic entropy. Overall, the FEP provides a sound theoretical basis for psychotherapy practice, training, and research

    K-OPLS package: Kernel-based orthogonal projections to latent structures for prediction and interpretation in feature space

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    <p>Abstract</p> <p>Background</p> <p>Kernel-based classification and regression methods have been successfully applied to modelling a wide variety of biological data. The Kernel-based Orthogonal Projections to Latent Structures (K-OPLS) method offers unique properties facilitating separate modelling of predictive variation and structured noise in the feature space. While providing prediction results similar to other kernel-based methods, K-OPLS features enhanced interpretational capabilities; allowing detection of unanticipated systematic variation in the data such as instrumental drift, batch variability or unexpected biological variation.</p> <p>Results</p> <p>We demonstrate an implementation of the K-OPLS algorithm for MATLAB and R, licensed under the GNU GPL and available at <url>http://www.sourceforge.net/projects/kopls/</url>. The package includes essential functionality and documentation for model evaluation (using cross-validation), training and prediction of future samples. Incorporated is also a set of diagnostic tools and plot functions to simplify the visualisation of data, e.g. for detecting trends or for identification of outlying samples. The utility of the software package is demonstrated by means of a metabolic profiling data set from a biological study of hybrid aspen.</p> <p>Conclusion</p> <p>The properties of the K-OPLS method are well suited for analysis of biological data, which in conjunction with the availability of the outlined open-source package provides a comprehensive solution for kernel-based analysis in bioinformatics applications.</p

    Misdiagnosis, Mistreatment, and Harm - When Medical Care Ignores Social Forces.

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    The Case Studies in Social Medicine demonstrate that when physicians use only biologic or individual behavioral interventions to treat diseases that stem from or are exacerbated by social factors, we risk harming the patients we seek to serve

    Constructive Duality for Mixed Integer Programming: Part I, Theory

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