53 research outputs found

    Similarities between structural distortions under pressure and chemical doping in superconducting BaFe2As2

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    The discovery of a new family of high Tc materials, the iron arsenides (FeAs), has led to a resurgence of interest in superconductivity. Several important traits of these materials are now apparent, for example, layers of iron tetrahedrally coordinated by arsenic are crucial structural ingredients. It is also now well established that the parent non-superconducting phases are itinerant magnets, and that superconductivity can be induced by either chemical substitution or application of pressure, in sharp contrast to the cuprate family of materials. The structure and properties of chemically substituted samples are known to be intimately linked, however, remarkably little is known about this relationship when high pressure is used to induce superconductivity in undoped compounds. Here we show that the key structural features in BaFe2As2, namely suppression of the tetragonal to orthorhombic phase transition and reduction in the As-Fe-As bond angle and Fe-Fe distance, show the same behavior under pressure as found in chemically substituted samples. Using experimentally derived structural data, we show that the electronic structure evolves similarly in both cases. These results suggest that modification of the Fermi surface by structural distortions is more important than charge doping for inducing superconductivity in BaFe2As2

    Proximity of Iron Pnictide Superconductors to a Quantum Tricritical Point

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    We determine the nature of the magnetic quantum critical point in the doped LaFeAsO using a set of constrained density functional calculations that provide ab initio coefficients for a Landau order parameter analysis. The system turns out to be remarkably close to a quantum tricritical point, where the nature of the phase transition changes from first to second order. We compare with the effective field theory and discuss the experimental consequences.Comment: 4 pages, 4 figure

    Clinical and neuroimaging correlates of antiphospholipid antibodies in multiple sclerosis: a preliminary study

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    <p>Abstract</p> <p>Background</p> <p>The presence of antiphospholipid antibodies (APLA) in multiple sclerosis (MS) patients has been reported frequently but no clear relationship between APLA and the clinical and neuroimaging features of MS have heretofore been shown. We assessed the clinical and neuroimaging features of MS patients with plasma APLA.</p> <p>Methods</p> <p>A consecutive cohort of 24 subjects with relapsing-remitting (RR) MS were studied of whom 7 were in remission (Rem) and 17 in exacerbation (Exc). All subjects were examined and underwent MRI of brain. Patients' plasma was tested by standard ELISA for the presence of both IgM and IgG antibodies using a panel of 6 targets: cardiolipin (CL), β2 glycoprotein I (β2GPI), Factor VII/VIIa (FVIIa), phosphatidylcholine (PC), phosphatidylserine (PS) and phosphatidylethanolamine (PE).</p> <p>Results</p> <p>In exacerbation up to 80% of MS subjects had elevated titers of IgM antibodies directed against the above antigens. However, in remission, less than half of MS patients had elevated titers of IgM antibodies against one or more of the above antigens. This difference was significant, p < 0.01, for all 6 target antigens. Interestingly, none of the MS patients had elevated plasma titers of IgG against any of the target antigens tested. Correlation analysis between MRI enhancing lesions and plasma levels of APLA revealed high correlation for aPC, aPS and aFVIIa (p ≤ 0.0065), a trend for aPE and aCL (p = 0.056), and no correlation for aβ2GP1. The strongest correlation was for aFVIIa, p = 0.0002.</p> <p>Conclusion</p> <p>The findings of this preliminary study show that increased APLA IgM is associated with exacerbations of MS. Currently, the significance of this association in pathogenesis of MS remains unknown. However, systematic longitudinal studies to measure APLA in larger cohorts of patients with relapsing-remitting MS, particularly before and after treatment with immunomodulatory agents, are needed to confirm these preliminary findings.</p

    Fault diagnosis for uncertain networked systems

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    Fault diagnosis has been at the forefront of technological developments for several decades. Recent advances in many engineering fields have led to the networked interconnection of various systems. The increased complexity of modern systems leads to a larger number of sources of uncertainty which must be taken into consideration and addressed properly in the design of monitoring and fault diagnosis architectures. This chapter reviews a model-based distributed fault diagnosis approach for uncertain nonlinear large-scale networked systems to specifically address: (a) the presence of measurement noise by devising a filtering scheme for dampening the effect of noise; (b) the modeling of uncertainty by developing an adaptive learning scheme; (c) the uncertainty issues emerging when considering networked systems such as the presence of delays and packet dropouts in the communication networks. The proposed architecture considers in an integrated way the various components of complex distributed systems such as the physical environment, the sensor level, the fault diagnosers, and the communication networks. Finally, some actions taken after the detection of a fault, such as the identification of the fault location and its magnitude or the learning of the fault function, are illustrated

    Timing is crucial

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