353 research outputs found

    Issue framing and public opinion of the U.S. Supreme Court: an examination of the 2012 healthcare decision

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    Two years after its signing into law, the Patient Protection and Affordable Care Act (PPACA), commonly called the Affordable Care Act (ACA), underwent a constitutional challenge at the Supreme Court. The Court’s decision to uphold the power of Congress in enacting most of the provisions of the ACA was regarded as a highly salient decision that is thought to have affected the public perception of the law. The focus of this thesis is to determine whether the Supreme Court was able to frame arguments used for or against the ACA in relation to the decision. By organizing and analyzing open-ended responses gathered from a panel survey both before and after the 2012 decision, I sought to determine how arguments used in discussion about the law and institutions regarding it varied after the decision. Findings show that the argument types used to explain individuals’ policy perceptions remained relatively stable throughout the waves. The study presented here offers an in-depth, micro-level effects of a real Court decision on individuals. By focusing on within-subject language change in a tight window around the decision, this approach helps clarify thinking about the relationship between the Court and public opinion

    Mixed Logit Models and Network Formation

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    The study of network formation is pervasive in economics, sociology, and many other fields. In this paper, we model network formation as a ``choice'' that is made by nodes in a network to connect to other nodes. We study these ``choices'' using discrete-choice models, in which an agent chooses between two or more discrete alternatives. One framework for studying network formation is the multinomial logit (MNL) model. We highlight limitations of the MNL model on networks that are constructed from empirical data. We employ the ``repeated choice'' (RC) model to study network formation \cite{TrainRevelt97mixedlogit}. We argue that the RC model overcomes important limitations of the MNL model and is well-suited to study network formation. We also illustrate how to use the RC model to accurately study network formation using both synthetic and real-world networks. Using synthetic networks, we also compare the performance of the MNL model and the RC model; we find that the RC model estimates the data-generation process of our synthetic networks more accurately than the MNL model. We provide examples of qualitatively interesting questions -- the presence of homophily in a teen friendship network and the fact that new patents are more likely to cite older, more cited, and similar patents -- for which the RC model allows us to achieve insights

    Maxillofacial Prosthetic Materials: A Literature Review

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    Rehabilitation of patients with disabilities of head and neck region, due to either congenital or acquired defects is a challenging task. These defects range from minor cosmeticdiscrepancies to major functional limitation. The prosthodontics management of these patients should aim at not only restoring the functional and esthetic handicap, but also ensurepsychological well being. For facial rehabilitation assessment of materials used in maxillofacial prosthesis is necessary. Till date we have come a cross various materials which exhibitsome excellent properties but also have many deficiencies. This article will review various materials used in maxillofacial prosthesis

    [Re] Double Sampling Randomized Smoothing

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    This paper is a contribution to the reproducibility challenge in the field of machine learning, specifically addressing the issue of certifying the robustness of neural networks (NNs) against adversarial perturbations. The proposed Double Sampling Randomized Smoothing (DSRS) framework overcomes the limitations of existing methods by using an additional smoothing distribution to improve the robustness certification. The paper provides a clear manifestation of DSRS for a generalized family of Gaussian smoothing and a computationally efficient method for implementation. The experiments on MNIST and CIFAR-10 demonstrate the effectiveness of DSRS, consistently certifying larger robust radii compared to other methods. Also various ablations studies are conducted to further analyze the hyperparameters and effect of adversarial training methods on the certified radius by the proposed framework

    Trapping and sorting active particles: motility-induced condensation & smectic defects

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    We present an experimental realization of the collective trapping phase transition [Kaiser et al., PRL 108, 268307 (2012)], using motile polar granular rods in the presence of a V-shaped obstacle. We offer a theory of this transition based on the interplay of motility-induced condensation and liquid-crystalline ordering and show that trapping occurs when persistent influx overcomes the collective expulsion of smectic defect structures. In agreement with the theory, our experiments find that a trap fills to the brim when the trap angle θ\theta is below a threshold θc\theta_c, while all particles escape for θ>θc\theta > \theta_c. Our simulations support a further prediction, that θc\theta_c goes down with increasing rotational noise. We exploit the sensitivity of trapping to the persistence of directed motion to sort particles based on the statistical properties of their activityComment: 6 pages, 5 figures, for supplementary mpg files, see "https://www.dropbox.com/sh/3cmswfoysdn0sb6/AACpEp-G3768B6Y62nDFj_Hea?dl=0". This paper supersedes our earlier version arXiv:1603.08535 and contains substantial new results including revised theoretical treatmen
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