256,770 research outputs found

    Single neutral heavy lepton production at electron-muon colliders

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    New heavy Majorana and Dirac neutrinos production at future electron-muon colliders are investigated. The production of a single heavy neutrino is shown to be more relevant than pair production when comparing cross sections and neutrino mass ranges. The process e±Ό∓⟶Μℓ±W∓e^\pm \mu^\mp \longrightarrow {\nu} \ell^{\pm} W^{\mp} is studied including on-shell and off-shell heavy neutrino effects. Distributions are calculated including hadronization effects and experimental cuts that suppress background, in order to have a clear signal for heavy neutral leptons.Comment: 4 pages, 14 jpg figures, Published Phys.Lett B494 (2000) 273-27

    WAVELET BASED NONLINEAR SEPARATION OF IMAGES

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    This work addresses a real-life problem corresponding to the separation of the nonlinear mixture of images which arises when we scan a paper document and the image from the back page shows through. The proposed solution consists of a non-iterative procedure that is based on two simple observations: (1) the high frequency content of images is sparse, and (2) the image printed on each side of the paper appears more strongly in the mixture acquired from that side than in the mixture acquired from the opposite side. These ideas had already been used in the context of nonlinear denoising source separation (DSS). However, in that method the degree of separation achieved by applying these ideas was relatively weak, and the separation had to be improved by iterating within the DSS scheme. In this paper the application of these ideas is improved by changing the competition function and the wavelet transform that is used. These improvements allow us to achieve a good separation in one shot, without the need to integrate the process into an iterative DSS scheme. The resulting separation process is both nonlinear and non-local. We present experimental results that show that the method achieves a good separation quality

    Development of Integrative Bioinformatics Applications using Cloud Computing resources and Knowledge Organization Systems (KOS).

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    Use of semantic web abstractions, in particular of domain neural Knowledge Organization Systems (KOS), to manage distributed, cloud based, integrative bioinformatics infrastructure. This presentation derives from recent publication:

Almeida JS, Deus HF, Maass W. (2010) S3DB core: a framework for RDF generation and management in bioinformatics infrastructures. BMC Bioinformatics. 2010 Jul 20;11(1):387. [PMID 20646315].

These PowerPoint slides were presented at Semantic Web Applications and Tools for Life Sciences December 10th, 2010, Berlin, Germany (http://www.swat4ls.org/2010/progr.php), keynote 9-10 am

    Programming matrix optics into Mathematica

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    The various non-linear transformations incurred by the rays in an optical system can be modelled by matrix products up to any desired order of approximation. Mathematica software has been used to find the appropriate matrix coefficients for the straight path transformation and for the transformations induced by conical surfaces, both direction change and position offset. The same software package was programmed to model optical systems in seventh-order. A Petzval lens was used to exemplify the modelling power of the program.Comment: 15 page

    Fractional variational problems with the Riesz-Caputo derivative

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    In this paper we investigate optimality conditions for fractional variational problems, with a Lagrangian depending on the Riesz-Caputo derivative. First we prove a generalized Euler-Lagrange equation for the case when the interval of integration of the functional is different from the interval of the fractional derivative. Next we consider integral dynamic constraints on the problem, for several different cases. Finally, we determine optimality conditions for functionals depending not only on the admissible functions, but on time also, and we present a necessary condition for a pair function-time to be an optimal solution to the problem. © 2011 Elsevier Ltd. All rights reserved.FCTCIDM

    J. Joseph Garrahy: Servant Leader

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