23,394 research outputs found


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    Purpose: To evaluate the efficacy of a fluoride-containing orthodontic primer in preventing demineralization adjacent to brackets and compare the quality of enamel on tooth surfaces that received interproximal reduction (IPR). Methods: Patients at the VCU Orthodontic clinic who consented to orthodontic treatment involving extraction of at least 2 premolars were recruited to this pilot clinical study. Brackets were bonded to premolars using one of two primers, fluoride-containing experimental or control. IPR was also performed, and the experimental primer was applied to randomly selected teeth. Extracted teeth were analyzed visually for the presence of white spot lesions (WSLs). Micro-CT analyses were also performed to evaluate demineralization and measure the lesions. Results: A total of 18 teeth from 6 subjects were included in the following analyses. Based on micro-CT imaging, lesions were found on 89% of teeth treated with the experimental primer compared to 67% with the control primer, but this difference was not statistically significant (p=0.5765). There was also no significant difference between the depths of the lesions (p=1.00), handedness (p=0.5765), hygiene (p=0.7804), or time in the mouth (p=0.5601). According to visual examination, there was no significant difference in the incidence of WSLs between the two groups (89% and 89%; p=1.00) Also, there was no association with treatment (p=1.00), handedness (p=1.00), hygiene (p=0.1373), or time in the mouth (p=0.2987). No differences were noted on the microstructural characteristics of enamel at the IPR sites. Conclusion: Fluoride-containing primers do not seem to provide any additional benefit over conventional non-fluoride primers in orthodontic patients

    alpha :a constant that is not a constant?

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    We review the observational information on the constancy of the fine structure constant alpha. We find that small improvements on the measurement of ^{187}Re lifetime can provide significant progress in exploring the range of variability suggested by QSO data. We also discuss the effects of a time varying alpha on stellar structure and evolution. We find that radioactive dating of ancient stars can offer a new observational window.Comment: 9 pages with 3 ps figures included, to appear on the Proc. of ESO-CERN-ESA Symposium on Astronomy, Cosmology and Fundamental Physics, Garching bei Munchen, Germany March 4-7, 200

    Helioseismic tests of diffusion theory

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    We present a quantitative estimate of the accuracy of the calculated diffusion coefficients, by comparing predictions of solar models with observational data provided by helioseismology. By taking into account the major uncertainties in building solar models we conclude that helioseismology confirms the diffusion efficiency adopted in SSM calculations, to the 10% level.Comment: 5 pages with 1 ps figure included, LaTeX file with l-aa.sty, submitted to Astronomy and Astrophysic

    Explicit generation of the branching tree of states in spin glasses

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    We present a numerical method to generate explicit realizations of the tree of states in mean-field spin glasses. The resulting study illuminates the physical meaning of the full replica symmetry breaking solution and provides detailed information on the structure of the spin-glass phase. A cavity approach ensures that the method is self-consistent and permits the evaluation of sophisticated observables, such as correlation functions. We include an example application to the study of finite-size effects in single-sample overlap probability distributions, a topic that has attracted considerable interest recently.Comment: Version accepted for publication in JSTA

    Fast ALS-based tensor factorization for context-aware recommendation from implicit feedback

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    Albeit, the implicit feedback based recommendation problem - when only the user history is available but there are no ratings - is the most typical setting in real-world applications, it is much less researched than the explicit feedback case. State-of-the-art algorithms that are efficient on the explicit case cannot be straightforwardly transformed to the implicit case if scalability should be maintained. There are few if any implicit feedback benchmark datasets, therefore new ideas are usually experimented on explicit benchmarks. In this paper, we propose a generic context-aware implicit feedback recommender algorithm, coined iTALS. iTALS apply a fast, ALS-based tensor factorization learning method that scales linearly with the number of non-zero elements in the tensor. The method also allows us to incorporate diverse context information into the model while maintaining its computational efficiency. In particular, we present two such context-aware implementation variants of iTALS. The first incorporates seasonality and enables to distinguish user behavior in different time intervals. The other views the user history as sequential information and has the ability to recognize usage pattern typical to certain group of items, e.g. to automatically tell apart product types or categories that are typically purchased repetitively (collectibles, grocery goods) or once (household appliances). Experiments performed on three implicit datasets (two proprietary ones and an implicit variant of the Netflix dataset) show that by integrating context-aware information with our factorization framework into the state-of-the-art implicit recommender algorithm the recommendation quality improves significantly.Comment: Accepted for ECML/PKDD 2012, presented on 25th September 2012, Bristol, U
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