41,183 research outputs found

    Dynamo effect in parity-invariant flow with large and moderate separation of scales

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    It is shown that non-helical (more precisely, parity-invariant) flows capable of sustaining a large-scale dynamo by the negative magnetic eddy diffusivity effect are quite common. This conclusion is based on numerical examination of a large number of randomly selected flows. Few outliers with strongly negative eddy diffusivities are also found, and they are interpreted in terms of the closeness of the control parameter to a critical value for generation of a small-scale magnetic field. Furthermore, it is shown that, for parity-invariant flows, a moderate separation of scales between the basic flow and the magnetic field often significantly reduces the critical magnetic Reynolds number for the onset of dynamo action.Comment: 44 pages,11 figures, significantly revised versio

    Trends in the design and use of elastin-like recombinamers as biomaterials

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    Producción CientíficaElastin-like recombinamers (ELRs), which derive from one of the repetitive domains found in natural elastin, have been intensively studied in the last few years from several points of view. In this mini review, we discuss all the recent works related to the investigation of ELRs, starting with those that define these polypeptides as model intrinsically disordered proteins or regions (IDPs or IDRs) and its relevance for some biomedical applications. Furthermore, we summarize the current knowledge on the development of drug, vaccine and gene delivery systems based on ELRs, while also emphasizing the use of ELR-based hydrogels in tissue engineering and regenerative medicine (TERM). Finally, we show different studies that explore applications in other fields, and several examples that describe biomaterial blends in which ELRs have a key role. This review aims to give an overview of the recent advances regarding ELRs and to encourage further investigation of their properties and applications.Comisión Europea (project NMP-2014-646075)Ministerio de Economía, Industria y Competitividad (projects PCIN-2015-010 / MAT2016-78903-R / BES-2014-069763)Junta de Castilla y León (project VA317P18

    Information Extraction in Illicit Domains

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    Extracting useful entities and attribute values from illicit domains such as human trafficking is a challenging problem with the potential for widespread social impact. Such domains employ atypical language models, have `long tails' and suffer from the problem of concept drift. In this paper, we propose a lightweight, feature-agnostic Information Extraction (IE) paradigm specifically designed for such domains. Our approach uses raw, unlabeled text from an initial corpus, and a few (12-120) seed annotations per domain-specific attribute, to learn robust IE models for unobserved pages and websites. Empirically, we demonstrate that our approach can outperform feature-centric Conditional Random Field baselines by over 18\% F-Measure on five annotated sets of real-world human trafficking datasets in both low-supervision and high-supervision settings. We also show that our approach is demonstrably robust to concept drift, and can be efficiently bootstrapped even in a serial computing environment.Comment: 10 pages, ACM WWW 201

    Growth rate distribution and intermittency in kinematic turbulent dynamos : which moment predicts the dynamo onset?

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    We consider the generation of magnetic field by a turbulent flow. For the linear induction equation (i.e. the kinematic dynamo problem), we show that the statistical moments of the magnetic field display multiscaling and in particular moments of different order turn unstable for different values of the control parameter. On a canonical example, we map the problem onto the calculation of the injected power by a time correlated fluctuating force acting on a Brownian particle. We are then able to calculate analytically the growth rate of the moments of the magnetic field and explain the origin of this intermittency. We finally show that the onset for the nonlinear problem is predicted by the linear onset of the moment of order 0 + (i.e. the logarithm of the magnetic field

    Aircraft adaptive learning control

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    The optimal control theory of stochastic linear systems is discussed in terms of the advantages of distributed-control systems, and the control of randomly-sampled systems. An optimal solution to longitudinal control is derived and applied to the F-8 DFBW aircraft. A randomly-sampled linear process model with additive process and noise is developed
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