7,964 research outputs found

    Effects of c-axis Hopping in the Interlayer Tunneling Model of High-Tc Layered Cuprates

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    We consider the interlayer pair-tunneling model for layered cuprates, including an effective single particle hopping along the c-axis. A phenomenological suppression of the c-axis hopping matrix element, by the pseudogap in cuprate superconductors, is incorporated. At optimal doping, quantities characteristic to the superconducting state, such as the transition temperature and the superconducting gap are calculated. Results from our calculations are consistent with the experimental observations with the noteworthy point that, the superconducting gap as a function of temperature shows excellent match to the experimental data. Predictions within the model, regarding T_c variation with interlayer coupling, are natural outcomes which could be tested further.Comment: Latex file, 18 pages, 4 figures (postscript files included), to appear in Int. J. Mod. Phys.

    Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks

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    Over the last decade, Convolutional Neural Network (CNN) models have been highly successful in solving complex vision problems. However, these deep models are perceived as "black box" methods considering the lack of understanding of their internal functioning. There has been a significant recent interest in developing explainable deep learning models, and this paper is an effort in this direction. Building on a recently proposed method called Grad-CAM, we propose a generalized method called Grad-CAM++ that can provide better visual explanations of CNN model predictions, in terms of better object localization as well as explaining occurrences of multiple object instances in a single image, when compared to state-of-the-art. We provide a mathematical derivation for the proposed method, which uses a weighted combination of the positive partial derivatives of the last convolutional layer feature maps with respect to a specific class score as weights to generate a visual explanation for the corresponding class label. Our extensive experiments and evaluations, both subjective and objective, on standard datasets showed that Grad-CAM++ provides promising human-interpretable visual explanations for a given CNN architecture across multiple tasks including classification, image caption generation and 3D action recognition; as well as in new settings such as knowledge distillation.Comment: 17 Pages, 15 Figures, 11 Tables. Accepted in the proceedings of IEEE Winter Conf. on Applications of Computer Vision (WACV2018). Extended version is under review at IEEE Transactions on Pattern Analysis and Machine Intelligenc

    rbrothers: R Package for Bayesian Multiple Change-Point Recombination Detection.

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    Phylogenetic recombination detection is a fundamental task in bioinformatics and evolutionary biology. Most of the computational tools developed to attack this important problem are not integrated into the growing suite of R packages for statistical analysis of molecular sequences. Here, we present an R package, rbrothers, that makes a Bayesian multiple change-point model, one of the most sophisticated model-based phylogenetic recombination tools, available to R users. Moreover, we equip the Bayesian change-point model with a set of pre- and post- processing routines that will broaden the application domain of this recombination detection framework. Specifically, we implement an algorithm that forms the set of input trees required by multiple change-point models. We also provide functionality for checking Markov chain Monte Carlo convergence and creating estimation result summaries and graphics. Using rbrothers, we perform a comparative analysis of two Salmonella enterica genes, fimA and fimH, that encode major and adhesive subunits of the type 1 fimbriae, respectively. We believe that rbrothers, available at R-Forge: http://evolmod.r-forge.r-project.org/, will allow researchers to incorporate recombination detection into phylogenetic workflows already implemented in R

    A cross-sectional study of cutaneous drug reactions in a private dental college and government medical college in eastern India

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    Background: Cutaneous drug reactions are a common impediment in therapy, the incidence ranging from 2% to 8%. This cross-sectional study was designed to compare different trends of cutaneous drug reaction in two different socioeconomic groups of patients in the same region.Aims: The aim was to evaluate common drugs implicated in causing reactions, describe the adverse cutaneous drug reactions, study the characteristics of patients presenting with the reactions.Study Design: This is an observational study of cross-sectional type.Materials and Methods: The study was carried out in the department of Oral and Maxillofacial surgery in a Private dental College and department of General Medicine in a Medical College only on outdoor basis for 3 years. Out of 2000 patients observed in each college for their necessary treatment 75 patients in the dental College and 200 patients in the Medical College were reported to have various types of cutaneous drug reactions. Diagnosis was based on detailed history including temporal correlation between drug intake and onset of rash and thorough clinical examination Apart from history of drug intake, information regarding associated other allergy, comorbidity and severity (whether hospitalization was required or not) was recorded. Rechallenge with the drug was not possible due to ethical problem.Results: Out of 2000 patients observed in each college 75 patients in dental College and 200 patients in Medical College were documented to have different kinds of cutaneous drug reactions. A total of 30 were male and 45 female in dental college whereas 90 male and 110 female patients were enrolled in Medical College. The age group of the patients in both the colleges ranged from 18 to 75 years. Common culprits observed in this study were antibiotics and NSAIDs. They had contributed 53% and 40% of the total skin reactions respectively in dental college and 47.5% and 45% in Medical College. We encountered 6 patients of systemic lupus erythematosus (SLE), 20 patients with allergic rhinitis and 12 patients with bronchial asthma in the whole proceedings. The duration of drug intake varied from 15 minutes to 2 weeks. The most common reaction noted was maculopapular rash 37 (50.5%), urticaria 15 (20%), fixed drug eruption (FDR) 15 (20%), angioedema 6 (8%) in dental College whereas a little different trend was observed in the medical college. Hospitalization was required in two cases of Steven--Johnson syndrome caused by NSAIDS in the dental College whereas 11 patients were hospitalized for the same indication in the medical College. Except for maculopapular rash, all other skin reactions were observed more frequently with NSAIDS in dental College whereas Steven--Johnson syndrome is predominantly observed in Medical College with anticonvulsants. In all the cases causative drugs were withdrawn. A total 40% of the patients required only antihistaminic, 35% required antihistaminic and topical corticosteroid and rest required a combination of antihistaminic, oral and topical corticosteroids.Conclusion: Commonest drugs causing drug reactions are antibiotics mainly beta lactams and quinolones. Severe reactions were seen in our series with anticonvulsants and NSAIDS. Association with other diseases could not be inferred due to this modest patient pool

    New oil modified acrylic polymer for pH sensitive drug release:experimental results and statistical analysis

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    We report results of an experimental study, complemented by detailed statistical analysis of the experimental data, on the development of a more effective control method of drug delivery using a pH sensitive acrylic polymer. New copolymers based on acrylic acid and fatty acid are constructed from dodecyl castor oil and a tercopolymer based on methyl methacrylate, acrylic acid and acryl amide were prepared using this new approach. Water swelling characteristics of fatty acid, acrylic acid copolymer and tercopolymer respectively in acid and alkali solutions have been studied by a step-change method. The antibiotic drug cephalosporin and paracetamol have also been incorporated into the polymer blend through dissolution with the release of the antibiotic drug being evaluated in bacterial stain media and buffer solution. Our results show that the rate of release of paracetamol getss affected by the pH factor and also by the nature of polymer blend. Our experimental data have later been statistically analyzed to quantify the precise nature of polymer decay rates on the pH density of the relevant polymer solvents. The time evolution of the polymer decay rates indicate a marked transition from a linear to a strictly non-linear regime depending on the whether the chosen sample is a general copolymer (linear) or a tercopolymer (non-linear). Non-linear data extrapolation techniques have been used to make probabilistic predictions about the variation in weight percentages of retained polymers at all future times, thereby quantifying the degree of efficacy of the new method of drug delivery
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