12,703 research outputs found

    Heavy Quark Thermalization in Classical Lattice Gauge Theory: Lessons for Strongly-Coupled QCD

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    Thermalization of a heavy quark near rest is controlled by the correlator of two electric fields along a temporal Wilson line. We address this correlator within real-time, classical lattice Yang-Mills theory, and elaborate on the analogies that exist with the dynamics of hot QCD. In the weak-coupling limit, it can be shown analytically that the dynamics on the two sides are closely related to each other. For intermediate couplings, we carry out non-perturbative simulations within the classical theory, showing that the leading term in the weak-coupling expansion significantly underestimates the heavy quark thermalization rate. Our analytic and numerical results also yield a general understanding concerning the overall shape of the spectral function corresponding to the electric field correlator, which may be helpful in subsequent efforts to reconstruct it from Euclidean lattice Monte Carlo simulations.Comment: 22 pages. v2: a reference and clarifications added; published versio

    On the Hierarchy of Block Deterministic Languages

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    A regular language is kk-lookahead deterministic (resp. kk-block deterministic) if it is specified by a kk-lookahead deterministic (resp. kk-block deterministic) regular expression. These two subclasses of regular languages have been respectively introduced by Han and Wood (kk-lookahead determinism) and by Giammarresi et al. (kk-block determinism) as a possible extension of one-unambiguous languages defined and characterized by Br\"uggemann-Klein and Wood. In this paper, we study the hierarchy and the inclusion links of these families. We first show that each kk-block deterministic language is the alphabetic image of some one-unambiguous language. Moreover, we show that the conversion from a minimal DFA of a kk-block deterministic regular language to a kk-block deterministic automaton not only requires state elimination, and that the proof given by Han and Wood of a proper hierarchy in kk-block deterministic languages based on this result is erroneous. Despite these results, we show by giving a parameterized family that there is a proper hierarchy in kk-block deterministic regular languages. We also prove that there is a proper hierarchy in kk-lookahead deterministic regular languages by studying particular properties of unary regular expressions. Finally, using our valid results, we confirm that the family of kk-block deterministic regular languages is strictly included into the one of kk-lookahead deterministic regular languages by showing that any kk-block deterministic unary language is one-unambiguous

    Rethinking the Penalty for the Failure to File Gift Tax Returns

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    In this article, the authors argue that Congress must reform the penalty structure associated with the failure to file gift tax returns if it wants to maintain the integrity of the transfer tax system

    Two-sample Bayesian Nonparametric Hypothesis Testing

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    In this article we describe Bayesian nonparametric procedures for two-sample hypothesis testing. Namely, given two sets of samples y(1)  \mathbf{y}^{\scriptscriptstyle(1)}\;\stackrel{\scriptscriptstyle{iid}}{\s im}  F(1)\;F^{\scriptscriptstyle(1)} and y(2)  \mathbf{y}^{\scriptscriptstyle(2 )}\;\stackrel{\scriptscriptstyle{iid}}{\sim}  F(2)\;F^{\scriptscriptstyle( 2)}, with F(1),F(2)F^{\scriptscriptstyle(1)},F^{\scriptscriptstyle(2)} unknown, we wish to evaluate the evidence for the null hypothesis H0:F(1)≡F(2)H_0:F^{\scriptscriptstyle(1)}\equiv F^{\scriptscriptstyle(2)} versus the alternative H1:F(1)≠F(2)H_1:F^{\scriptscriptstyle(1)}\neq F^{\scriptscriptstyle(2)}. Our method is based upon a nonparametric P\'{o}lya tree prior centered either subjectively or using an empirical procedure. We show that the P\'{o}lya tree prior leads to an analytic expression for the marginal likelihood under the two hypotheses and hence an explicit measure of the probability of the null Pr(H0∣{y(1),y(2)})\mathrm{Pr}(H_0|\{\mathbf {y}^{\scriptscriptstyle(1)},\mathbf{y}^{\scriptscriptstyle(2)}\}\mathbf{)}.Comment: Published at http://dx.doi.org/10.1214/14-BA914 in the Bayesian Analysis (http://projecteuclid.org/euclid.ba) by the International Society of Bayesian Analysis (http://bayesian.org/

    Teaching Population Health: Innovations in the integration of the healthcare and public health systems

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    Population health is a critical concept in healthcare delivery today. Many healthcare administrators are struggling to adapt their organization from fee-for-service to value delivery. Payers and patients expect healthcare leaders to understand how to deliver care under this new model. Health administration programs play a critical role in training future leaders of healthcare organizations to be adaptable and effective in this dynamic environment. The purpose of this research was to: (a) engage current educators of health administration students in a dialogue about the best practices of integrating the healthcare and public health systems; (b) identify the content and pedagogy for population health in the undergraduate and graduate curricula; and (c) discuss exemplar population health curriculum models, available course materials, and curriculum integration options. Authors conducted focus groups of participants attending this educational session at the 2017 annual AUPHA meeting. Qualitative analysis of the focus group discussions was performed and themes identified by a consensus process. Study findings provide validated recommendations for population health in the health administration curriculum. The identification of key content areas and pedagogical approaches serves to inform health educators as they prepare future health administrators to practice in this new era of population health

    Alien Registration- Caron, Wilfred A. (Brunswick, Cumberland County)

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    https://digitalmaine.com/alien_docs/31432/thumbnail.jp

    SEC Disclosure Requirements for Contingent Environmental Liability

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    Analyzing {\gamma}-rays of the Galactic Center with Deep Learning

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    We present a new method to interpret the γ\gamma-ray data of our inner Galaxy as measured by the Fermi Large Area Telescope (Fermi LAT). We train and test convolutional neural networks with simulated Fermi-LAT images based on models tuned to real data. We use this method to investigate the origin of an excess emission of GeV γ\gamma-rays seen in previous studies. Interpretations of this excess include γ\gamma rays created by the annihilation of dark matter particles and γ\gamma rays originating from a collection of unresolved point sources, such as millisecond pulsars. Our new method allows precise measurements of the contribution and properties of an unresolved population of γ\gamma-ray point sources in the interstellar diffuse emission model.Comment: 24 pages, 11 figure
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