Scanning tunneling spectroscopy of superconducting LiFeAs single crystals: Evidence for two nodeless energy gaps and coupling to a bosonic mode

The superconducting compound, LiFeAs, is studied by scanning tunneling microscopy and spectroscopy. A gap map of the unreconstructed surface indicates a high degree of homogeneity in this system. Spectra at 2 K show two nodeless superconducting gaps with $\Delta_1=5.3\pm0.1$ meV and $\Delta_2=2.5\pm0.2$ meV. The gaps close as the temperature is increased to the bulk $T_c$ indicating that the surface accurately represents the bulk. A dip-hump structure is observed below $T_c$ with an energy scale consistent with a magnetic resonance recently reported by inelastic neutron scattering

Les microARNs

MiRNAs are small non-coding RNAs ensuring the post-transcriptional regulation of gene expression. Their expression is tissue-specific and some miRNAs have diagnostic and / or prognostic value for tumor classes. MiRNAs are involved in tumorigenesis by two mechanisms: amplification or deletion of chromosomal regions containing clusters of genes encoding miRNAs (quantitative effect) or modification of the effects of miRNAs on their target genes by mutation in the region of interaction with the mRNA (qualitative effect). Their specificity, the possibility for miRNA measurement in blood, must now lead to consider miRNAs as markers for therapeutic management. A better understanding of the different regulatory mechanisms involving miRNAs will also consider new therapeutic approaches

Characterizing Distances of Networks on the Tensor Manifold

At the core of understanding dynamical systems is the ability to maintain and control the systems behavior that includes notions of robustness, heterogeneity, or regime-shift detection. Recently, to explore such functional properties, a convenient representation has been to model such dynamical systems as a weighted graph consisting of a finite, but very large number of interacting agents. This said, there exists very limited relevant statistical theory that is able cope with real-life data, i.e., how does perform analysis and/or statistics over a family of networks as opposed to a specific network or network-to-network variation. Here, we are interested in the analysis of network families whereby each network represents a point on an underlying statistical manifold. To do so, we explore the Riemannian structure of the tensor manifold developed by Pennec previously applied to Diffusion Tensor Imaging (DTI) towards the problem of network analysis. In particular, while this note focuses on Pennec definition of geodesics amongst a family of networks, we show how it lays the foundation for future work for developing measures of network robustness for regime-shift detection. We conclude with experiments highlighting the proposed distance on synthetic networks and an application towards biological (stem-cell) systems.Comment: This paper is accepted at 8th International Conference on Complex Networks 201

Cleaving-temperature dependence of layered-oxide surfaces

The surfaces generated by cleaving non-polar, two-dimensional oxides are often considered to be perfect or ideal. However, single particle spectroscopies on Sr2RuO4, an archetypal non-polar two dimensional oxide, show significant cleavage temperature dependence. We demonstrate that this is not a consequence of the intrinsic characteristics of the surface: lattice parameters and symmetries, step heights, atom positions, or density of states. Instead, we find a marked increase in the density of defects at the mesoscopic scale with increased cleave temperature. The potential generality of these defects to oxide surfaces may have broad consequences to interfacial control and the interpretation of surface sensitive measurements

Statistically Motivated Second Order Pooling

Second-order pooling, a.k.a.~bilinear pooling, has proven effective for deep learning based visual recognition. However, the resulting second-order networks yield a final representation that is orders of magnitude larger than that of standard, first-order ones, making them memory-intensive and cumbersome to deploy. Here, we introduce a general, parametric compression strategy that can produce more compact representations than existing compression techniques, yet outperform both compressed and uncompressed second-order models. Our approach is motivated by a statistical analysis of the network's activations, relying on operations that lead to a Gaussian-distributed final representation, as inherently used by first-order deep networks. As evidenced by our experiments, this lets us outperform the state-of-the-art first-order and second-order models on several benchmark recognition datasets.Comment: Accepted to ECCV 2018. Camera ready version. 14 page, 5 figures, 3 table

Interplay between magnetic anisotropy and interlayer coupling in nanosecond magnetization reversal of spin-valve trilayers

The influence of magnetic anisotropy on nanosecond magnetization reversal in coupled FeNi/Cu/Co trilayers was studied using a photoelectron emission microscope combined with x-ray magnetic circular dicroism. In quasi-isotropic samples the reversal of the soft FeNi layer is determined by domain wall pinning that leads to the formation of small and irregular domains. In samples with uniaxial magnetic anisotropy, the domains are larger and the influence of local interlayer coupling dominates the domain structure and the reversal of the FeNi layer

Observations of the post shock break-out emission of SN 2011dh with XMM-Newton

After the occurrence of the type cIIb SN 2011dh in the nearby spiral galaxy M 51 numerous observations were performed with different telescopes in various bands ranging from radio to gamma-rays. We analysed the XMM-Newton and Swift observations taken 3 to 30 days after the SN explosion to study the X-ray spectrum of SN 2011dh. We extracted spectra from the XMM-Newton observations, which took place ~7 and 11 days after the SN. In addition, we created integrated Swift/XRT spectra of 3 to 10 days and 11 to 30 days. The spectra are well fitted with a power-law spectrum absorbed with Galactic foreground absorption. In addition, we find a harder spectral component in the first XMM-Newton spectrum taken at t ~ 7 d. This component is also detected in the first Swift spectrum of t = 3 - 10 d. While the persistent power-law component can be explained as inverse Compton emission from radio synchrotron emitting electrons, the harder component is most likely bremsstrahlung emission from the shocked stellar wind. Therefore, the harder X-ray emission that fades away after t ~ 10 d can be interpreted as emission from the shocked circumstellar wind of SN 2011dh.Comment: Accepted for publication as a Research Note in Astronomy and Astrophysic