1,139 research outputs found

    CAT-generating mechanisms

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    The development of instability configurations; the transition from unstable growth of these configurations into turbulence; a description of the nature of that turbulence; the question of decay of turbulence; and the existence of what is called fossil turbulence are discussed

    Magnetic Field Generation from Self-Consistent Collective Neutrino-Plasma Interactions

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    A new Lagrangian formalism for self-consistent collective neutrino-plasma interactions is presented in which each neutrino species is described as a classical ideal fluid. The neutrino-plasma fluid equations are derived from a covariant relativistic variational principle in which finite-temperature effects are retained. This new formalism is then used to investigate the generation of magnetic fields and the production of magnetic helicity as a result of collective neutrino-plasma interactions.Comment: 23 page

    The Predicament of Chaucer's Wife of Bath: St. Jerome on Virginity

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    The Bane of Flattery in the World of Chaucer and Langland

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    Suppression of feedback oscillations in free electron lasers

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    Automatic extraction of biomolecular interactions: an empirical approach

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    Background We describe a method for extracting data about how biomolecule pairs interact from texts. This method relies on empirically determined characteristics of sentences. The characteristics are efficient to compute, making this approach to extraction of biomolecular interactions scalable. The results of such interaction mining can support interaction network annotation, question answering, database construction, and other applications. Results We constructed a software system to search MEDLINE for sentences likely to describe interactions between given biomolecules. The system extracts a list of the interaction-indicating terms appearing in those sentences, then ranks those terms based on their likelihood of correctly characterizing how the biomolecules interact. The ranking process uses a tf-idf (term frequency-inverse document frequency) based technique using empirically derived knowledge about sentences, and was applied to the MEDLINE literature collection. Software was developed as part of the MetNet toolkit (http://www.metnetdb.org). Conclusions Specific, efficiently computable characteristics of sentences about biomolecular interactions were analyzed to better understand how to use these characteristics to extract how biomolecules interact. The text empirics method that was investigated, though arising from a classical tradition, has yet to be fully explored for the task of extracting biomolecular interactions from the literature. The conclusions we reach about the sentence characteristics investigated in this work, as well as the technique itself, could be used by other systems to provide evidence about putative interactions, thus supporting efforts to maximize the ability of hybrid systems to support such tasks as annotating and constructing interaction networks
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