15,537 research outputs found

    Comment on "General nonlocality in quantum fields"

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    In this paper, we first incorporate the weak interaction into the theory of General Nonlocality by finding a appropriate metric for it. Accordingly, we suggest the theoretical frame of General Nonlocality as the candidate theory of unifying three microscope interactions in low energy limit. In this unifying scenario, the essential role of photon field is stressed.Comment: Only partial content published in the following reference. The part asserting the fermion mass problem now proved to be wrong, though remains in the versio

    Physico-chemical factors and bacteria in fish ponds

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    Analyses of pond water and mud samples show that nitrifying bacteria (including ammonifying bacteria, nitrite bacteria, nitrobacteria and denitrifying bacteria) are in general closely correlated with various physico-chemical factors, ammonifying bacteria are mainly correlated with dissolved oxygen; denitrifying bacteria are inversely correlated with phosphorus; nitrite bacteria are closely correlated with nitrites, nitrobacteria are inversely correlated with ammoniac nitrogen. The nitrifying bacteria are more closely correlated with heterotrophic bacteria. Nitrobacteria are inversely correlated with anaerobic heterotrophic bacteria. The correlation is quite weak between all the nitrite bacteria which indicates that the nitrite bacteria have a controlling and regulating function in water quality and there is no interdependence as each plays a role of its own. The paper also discusses how the superficial soil (pond mud down to 3.5 cm deep) and different layers of the mud affect the biomass of bacteria. The study shows that the top superficial layer (down to 1.5 cm deep) is the major area for decomposing and converting organic matter

    Doubly stochastic continuous-time hidden Markov approach for analyzing genome tiling arrays

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    Microarrays have been developed that tile the entire nonrepetitive genomes of many different organisms, allowing for the unbiased mapping of active transcription regions or protein binding sites across the entire genome. These tiling array experiments produce massive correlated data sets that have many experimental artifacts, presenting many challenges to researchers that require innovative analysis methods and efficient computational algorithms. This paper presents a doubly stochastic latent variable analysis method for transcript discovery and protein binding region localization using tiling array data. This model is unique in that it considers actual genomic distance between probes. Additionally, the model is designed to be robust to cross-hybridized and nonresponsive probes, which can often lead to false-positive results in microarray experiments. We apply our model to a transcript finding data set to illustrate the consistency of our method. Additionally, we apply our method to a spike-in experiment that can be used as a benchmark data set for researchers interested in developing and comparing future tiling array methods. The results indicate that our method is very powerful, accurate and can be used on a single sample and without control experiments, thus defraying some of the overhead cost of conducting experiments on tiling arrays.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS248 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

    Gauged Q ball in a piecewise parabolic potential

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    Q ball solutions are considered within the theory of a complex scalar field with a gauged U(1) symmetry and a parabolic-type potential. In the thin-walled limit, we show explicitly that there is a maximum size for these objects because of the repulsive Coulomb force. The size of Q ball will increase with the decrease of local minimum of the potential. And when the two minima degenerate, the energy stored within the surface of the Q ball becomes significant. Furthermore, we find an analytic expression for gauged Q ball, which is beyond the conventional thin-walled limit.Comment: 1 figure
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