7,242 research outputs found

    Direct observation of the quantum critical point in heavy fermion CeRhSi3_3

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    We report on muon spin rotation studies of the noncentrosymmetric heavy fermion antiferromagnet CeRhSi3_3. A drastic and monotonic suppression of the internal fields, at the lowest measured temperature, was observed upon an increase of external pressure. Our data suggest that the ordered moments are gradually quenched with increasing pressure, in a manner different from the pressure dependence of the N\'eel temperature. At \unit{23.6}{kbar}, the ordered magnetic moments are fully suppressed via a second-order phase transition, and TNT_{\rm{N}} is zero. Thus, we directly observed the quantum critical point at \unit{23.6}{kbar} hidden inside the superconducting phase of CeRhSi3_3

    SONiCS: PCR stutter noise correction in genome-scale microsatellites

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    Motivation Massively parallel capture of short tandem repeats (STRs, or microsatellites) provides a strategy for population genomic and demographic analyses at high resolution with or without a reference genome. However, the high Polymerase Chain Reaction (PCR) cycle numbers needed for target capture experiments create genotyping noise through polymerase slippage known as PCR stutter. Results We developed SONiCS—Stutter mONte Carlo Simulation—a solution for stutter correction based on dense forward simulations of PCR and capture experimental conditions. To test SONiCS, we genotyped a 2499-marker STR panel in 22 humpback dolphins (Sousa sahulensis) using target capture, and generated capillary-based genotypes to validate five of these markers. In these 110 comparisons, SONiCS showed a 99.1% accuracy rate and a 98.2% genotyping success rate, miscalling a single allele in a marker with low sequence coverage and rejecting another as un-callable. Availability and implementation Source code and documentation for SONiCS is freely available at https://github.com/kzkedzierska/sonics. Raw read data used in experimental validation of SONiCS have been deposited in the Sequence Read Archive under accession number SRP135756

    Elastic Scattering by Deterministic and Random Fractals: Self-Affinity of the Diffraction Spectrum

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    The diffraction spectrum of coherent waves scattered from fractal supports is calculated exactly. The fractals considered are of the class generated iteratively by successive dilations and translations, and include generalizations of the Cantor set and Sierpinski carpet as special cases. Also randomized versions of these fractals are treated. The general result is that the diffraction intensities obey a strict recursion relation, and become self-affine in the limit of large iteration number, with a self-affinity exponent related directly to the fractal dimension of the scattering object. Applications include neutron scattering, x-rays, optical diffraction, magnetic resonance imaging, electron diffraction, and He scattering, which all display the same universal scaling.Comment: 20 pages, 11 figures. Phys. Rev. E, in press. More info available at http://www.fh.huji.ac.il/~dani

    A conserved phosphorylation site regulates the transcriptional function of ETHYLENE-INSENSITIVE3-like1 in tomato

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    ETHYLENE-INSENSITIVE3/ETHYLENE-INSENSITIVE3-like (EIN3/EIL) transcription factors are important downstream components of the ethylene transduction pathway known to regulate the transcription of early ethylene-responsive genes in plants. Previous studies have shown that phosphorylation can repress their transcriptional activity by promoting protein degradation. The present study identifies a new phosphorylation region named EPR1 (EIN3/EIL phosphorylation region 1) in tomato EIL1 proteins. The functional significance of EPR1 was tested by introducing mutations in this region of the Sl-EIL1 gene and by expressing these mutated versions in transgenic tomato plants. Transient expression data and phenotypic analysis of the transgenic lines indicated that EPR1 is essential for the transcriptional activity of Sl-EIL1. Moreover, mutation in the EPR1 site that prevents phosphorylation abolishes ethylene constitutive responses normally displayed by the Sl-EIL1-overexpressing lines. Bimolecular fluorescence complementation (BiFC) studies showed that the presence of a functional phosphorylation site within EPR1 is instrumental in the dimerization of Sl-EIL1 proteins. The results illuminate a new molecular mechanism for the control of EIN3/EIL activity and propose a model where phosphorylation within the EPR1 promotes the dimerization process allowing the initiation of EIL-mediated transcription of early ethylene-regulated genes

    Real-space mapping of tailored sheet and edge plasmons in graphene nanoresonators

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    Plasmons in graphene nanoresonators have many potential applications in photonics and optoelectronics, including room-temperature infrared and terahertz photodetectors, sensors, reflect arrays or modulators1, 2, 3, 4, 5, 6, 7. The development of efficient devices will critically depend on precise knowledge and control of the plasmonic modes. Here, we use near-field microscopy8, 9, 10, 11 between λ0 = 10–12 μm to excite and image plasmons in tailored disk and rectangular graphene nanoresonators, and observe a rich variety of coexisting Fabry–Perot modes. Disentangling them by a theoretical analysis allows the identification of sheet and edge plasmons, the latter exhibiting mode volumes as small as 10−8λ03. By measuring the dispersion of the edge plasmons we corroborate their superior confinement compared with sheet plasmons, which among others could be applied for efficient 1D coupling of quantum emitters12. Our understanding of graphene plasmon images is a key to unprecedented in-depth analysis and verification of plasmonic functionalities in future flatland technologies.Peer ReviewedPostprint (author's final draft

    BrainPrint: Identifying Subjects by Their Brain

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    Introducing BrainPrint, a compact and discriminative representation of anatomical structures in the brain. BrainPrint captures shape information of an ensemble of cortical and subcortical structures by solving the 2D and 3D Laplace-Beltrami operator on triangular (boundary) and tetrahedral (volumetric) meshes. We derive a robust classifier for this representation that identifies the subject in a new scan, based on a database of brain scans. In an example dataset containing over 3000 MRI scans, we show that BrainPrint captures unique information about the subject’s anatomy and permits to correctly classify a scan with an accuracy of over 99.8%. All processing steps for obtaining the compact representation are fully automated making this processing framework particularly attractive for handling large datasets.Alexander von Humboldt-StiftungAthinoula A. Martinos Center for Biomedical Imaging (P41-RR014075)Athinoula A. Martinos Center for Biomedical Imaging (P41-EB015896)National Alliance for Medical Image Computing (U.S.) (U54-EB005149)Neuroimaging Analysis Center (U.S.) (P41-EB015902

    Crisaborole Ointment, 2%, for Treatment of Patients with Mild-to-Moderate Atopic Dermatitis:Systematic Literature Review and Network Meta-Analysis

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    The authors would like to replace 2 small sections of the published manuscript that refer to a qualitative review of safety data for included studies (together with an associated safety table), to provide some further clarifications on these safety data and to include some quantitative updates for rates

    Flux Creep and Flux Jumping

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    We consider the flux jump instability of the Bean's critical state arising in the flux creep regime in type-II superconductors. We find the flux jump field, BjB_j, that determines the superconducting state stability criterion. We calculate the dependence of BjB_j on the external magnetic field ramp rate, B˙e\dot B_e. We demonstrate that under the conditions typical for most of the magnetization experiments the slope of the current-voltage curve in the flux creep regime determines the stability of the Bean's critical state, {\it i.e.}, the value of BjB_j. We show that a flux jump can be preceded by the magneto-thermal oscillations and find the frequency of these oscillations as a function of B˙e\dot B_e.Comment: 7 pages, ReVTeX, 2 figures attached as postscript file
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