Insights from ARPES for an undoped, four-layered, two-gap high-T_c superconductor

An undoped cuprate with apical fluorine and inner (i) and outer (o) CuO2-layers is a 60 K superconductor whose Fermi surface (FS) has large n- and p-doped sheets with the SC gap on the n-sheet twice that on the p -sheet (Y. Chen et al.). The Fermi surface is not reproduced by the LDA, but the screening must be substantially reduced due to electronic correlations, and oxygen in the o-layers must be allowed to dimple outwards. This charges the i-layers by 0.01|e|, causes an 0.4 eV Madelung-potential difference between the i and o -layers, quenches the i-o hopping, and localizes the n-sheets onto the i-layers, thus protecting their d-wave pairs from being broken by scattering on impurities in the BaF layers. The correlation-reduced screening strengthens the coupling to z-axis phonons.Comment: 4 pages, 3 figure

Identification of Long-lived Charged Particles using Time-Of-Flight Systems at the Upgraded LHC detectors

We study the impact of picosecond precision timing detection systems on the LHC experiments' long-lived particle search program during the HL-LHC era. We develop algorithms that allow us to reconstruct the mass of such charged particles and perform particle identification using the time-of-flight measurement. We investigate the reach for benchmark scenarios as a function of the timing resolution, and find sensitivity improvement of up to a factor of ten, depending on the new heavy particle mass.Comment: 20 pages, 13 figure

Semi-supervised Multi-sensor Classification via Consensus-based Multi-View Maximum Entropy Discrimination

In this paper, we consider multi-sensor classification when there is a large number of unlabeled samples. The problem is formulated under the multi-view learning framework and a Consensus-based Multi-View Maximum Entropy Discrimination (CMV-MED) algorithm is proposed. By iteratively maximizing the stochastic agreement between multiple classifiers on the unlabeled dataset, the algorithm simultaneously learns multiple high accuracy classifiers. We demonstrate that our proposed method can yield improved performance over previous multi-view learning approaches by comparing performance on three real multi-sensor data sets.Comment: 5 pages, 4 figures, Accepted in 40th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 15

GhostVLAD for set-based face recognition

The objective of this paper is to learn a compact representation of image sets for template-based face recognition. We make the following contributions: first, we propose a network architecture which aggregates and embeds the face descriptors produced by deep convolutional neural networks into a compact fixed-length representation. This compact representation requires minimal memory storage and enables efficient similarity computation. Second, we propose a novel GhostVLAD layer that includes {\em ghost clusters}, that do not contribute to the aggregation. We show that a quality weighting on the input faces emerges automatically such that informative images contribute more than those with low quality, and that the ghost clusters enhance the network's ability to deal with poor quality images. Third, we explore how input feature dimension, number of clusters and different training techniques affect the recognition performance. Given this analysis, we train a network that far exceeds the state-of-the-art on the IJB-B face recognition dataset. This is currently one of the most challenging public benchmarks, and we surpass the state-of-the-art on both the identification and verification protocols.Comment: Accepted by ACCV 201

Anisotropies in insulating La2−x_{2-x}Srx_xCuO4_4: angular resolved photoemission and optical absorption

Due to the orthorhombic distortion of the lattice, the electronic hopping integrals along the $a$ and $b$ diagonals, the orthorhombic directions, are slightly different. We calculate their difference in the LDA and find $t_{a}^{\prime}-t_{b}^{\prime}\approx 8$meV. We argue that electron correlations in the insulating phase of La$_{2-x}$Sr$_{x}$CuO$_{4}$, i. e. at doping $x\leq 0.055,$ dramatically enhance the $(t_{a}^{\prime}-t_{b}^{\prime})$-splitting between the $a$- and $b$-hole valleys. In particular, we predict that the intensity of both angle-resolved photoemission and of optical absorption is very different for the $a$ and $b$ nodal points

Surface-wave interferometry on single subwavelength slit-groove structures fabricated on gold films

We apply the technique of far-field interferometry to measure the properties of surface waves generated by two-dimensional (2D) single subwavelength slit-groove structures on gold films. The effective surface index of refraction measured for the surface wave propagating over a distance of more than 12 microns is determined to be 1.016 with a measurement uncertainty of 0.004, to within experimental uncertainty of the expected bound surface plasmon-polariton (SPP) value for a Au/Air interface of 1.018. We compare these measurements to finite-difference-time-domain (FDTD) numerical simulations of the optical field transmission through these devices. We find excellent agreement between the measurements and the simulations for the surface index of refraction. The measurements also show that the surface wave propagation parameter exhibits transient behavior close to the slit, evolving smoothly from greater values asymptotically toward the value expected for the SPP over the first 2-3 microns of slit-groove distance. This behavior is confirmed by the FDTD simulations

Urocortin 3 marks mature human primary and embryonic stem cell-derived pancreatic alpha and beta cells.

The peptide hormone Urocortin 3 (Ucn 3) is abundantly and exclusively expressed in mouse pancreatic beta cells where it regulates insulin secretion. Here we demonstrate that Ucn 3 first appears at embryonic day (E) 17.5 and, from approximately postnatal day (p) 7 and onwards throughout adult life, becomes a unifying and exclusive feature of mouse beta cells. These observations identify Ucn 3 as a potential beta cell maturation marker. To determine whether Ucn 3 is similarly restricted to beta cells in humans, we conducted comprehensive immunohistochemistry and gene expression experiments on macaque and human pancreas and sorted primary human islet cells. This revealed that Ucn 3 is not restricted to the beta cell lineage in primates, but is also expressed in alpha cells. To substantiate these findings, we analyzed human embryonic stem cell (hESC)-derived pancreatic endoderm that differentiates into mature endocrine cells upon engraftment in mice. Ucn 3 expression in hESC-derived grafts increased robustly upon differentiation into mature endocrine cells and localized to both alpha and beta cells. Collectively, these observations confirm that Ucn 3 is expressed in adult beta cells in both mouse and human and appears late in beta cell differentiation. Expression of Pdx1, Nkx6.1 and PC1/3 in hESC-derived Ucn 3(+) beta cells supports this. However, the expression of Ucn 3 in primary and hESC-derived alpha cells demonstrates that human Ucn 3 is not exclusive to the beta cell lineage but is a general marker for both the alpha and beta cell lineages. Ucn 3(+) hESC-derived alpha cells do not express Nkx6.1, Pdx1 or PC1/3 in agreement with the presence of a separate population of Ucn 3(+) alpha cells. Our study highlights important species differences in Ucn 3 expression, which have implications for its utility as a marker to identify mature beta cells in (re)programming strategies