Noise properties of direct current SQUIDs with quasiplanar YBa2Cu3O7 Josephson junctions

We describe the noise performance of dc SQUIDs fabricated with quasiplanar ramp‐type Josephson junctions on the basis of c‐axis‐oriented YBa2Cu3O7/PrBa2Cu3O7 thin‐film heterostructures. The noise spectrum of the dc SQUIDs was measured with dc‐ and ac‐bias schemes at different temperatures and showed values below 10−5 Φ0/Hz1/2 down to frequencies of about 1 Hz at 70 K. Up to now for the magnetic fluxnoise and the energy resolution obtained at 1 kHz and 77 K the best values were 2.5×10−6, Φ0/Hz1/2 and 3×10−31 J/Hz, respectively. A study of the white and 1/fnoises of the SQUIDs was performed. The influence of magnetic flux, bias current, high static magnetic fields, and aging on the SQUID noise were investigated. The junctions and devices do not degrade due to aging in air or thermal cycling

Transformation of in-plane ρ(T)\rho (T) in YBa2Cu3O7−δYBa_{2}Cu_{3}O_{7-\delta} at fixed oxygen content

This paper reveals the origin of variation in the magnitude and temperature dependence of the normal state resistivity frequently observed in different YBCO single crystal or thin film samples with the same $T_{c}$. We investigated temperature dependence of resistivity in $YBa_{2}Cu_{3}O_{7-\delta}$ thin films with 7- $\delta = 6.95$ and 6.90, which were subjected to annealing in argon at 400-420 K ($120-140^{o}C$). Before annealing these films exhibited a non-linear $\rho_{ab}(T)$, with a flattening below 230 K, similar to $\rho_{b}(T)$ and $\rho_{ab}(T)$ observed in untwinned and twinned YBCO crystals, respectively. For all films the annealing causes an increase of resistivity and a transformation of $\rho_{ab}(T)$ from a non-linear dependence towards a more linear one (less flattening). In films with 7- $\delta = 6.90$ the increase of resistivity is also associated with an increase in $T_{c}$. We proposed the model that provides an explanation of these phenomena in terms of thermally activated redistribution of residual O(5) oxygens in the chain-layer of YBCO. Good agreement between the experimental data for $\rho_{ab}(t,T)$, where t is the annealing time, and numerical calculations was obtained.Comment: 8 pages, 9 figures, submitted to PR

GRIDDS - A Gait Recognition Image and Depth Dataset

Several approaches based on human gait have been proposed in the literature, either for medical research reasons, smart surveillance, human-machine interaction, or other purposes, whose validation highly depends on the access to common input data through available datasets, enabling a coherent performance comparison. The advent of depth sensors leveraged the emergence of novel approaches and, consequently, the usage of new datasets. In this work we present the GRIDDS - A Gait Recognition Image and Depth Dataset, a new and publicly available gait depth-based dataset that can be used mostly for person and gender recognition purposes. (c) Springer Nature Switzerland AG 2019

Electron and hole transmission through superconductor - normal metal interfaces

We have investigated the transmission of electrons and holes through interfaces between superconducting aluminum (Tc = 1.2 K) and various normal non-magnetic metals (copper, gold, palladium, platinum, and silver) using Andreev-reflection spectroscopy at T = 0.1 K. We analyzed the point contacts with the modified BTK theory that includes Dynes' lifetime as a fitting parameter G in addition to superconducting energy gap 2D and normal reflection described by Z. For contact areas from 1 nm^2 to 10000 nm^2 the BTK Z parameter was 0.5, corresponding to transmission coefficients of about 80 %, independent of the normal metal. The very small variation of Z indicates that the interfaces have a negligible dielectric tunneling barrier. Fermi surface mismatch does not account for the observed transmission coefficient.Comment: 9 pages, 4 figures, submitted to Proceedings of the 19th International Conference on Magnetism ICM2012 (Busan 2012

Comprehensive evaluation of deconvolution methods for human brain gene expression

Transcriptome deconvolution aims to estimate the cellular composition of an RNA sample from its gene expression data, which in turn can be used to correct for composition differences across samples. The human brain is unique in its transcriptomic diversity, and comprises a complex mixture of cell-types, including transcriptionally similar subtypes of neurons. Here, we carry out a comprehensive evaluation of deconvolution methods for human brain transcriptome data, and assess the tissue-specificity of our key observations by comparison with human pancreas and heart. We evaluate eight transcriptome deconvolution approaches and nine cell-type signatures, testing the accuracy of deconvolution using in silico mixtures of single-cell RNA-seq data, RNA mixtures, as well as nearly 2000 human brain samples. Our results identify the main factors that drive deconvolution accuracy for brain data, and highlight the importance of biological factors influencing cell-type signatures, such as brain region and in vitro cell culturing.Gavin J. Sutton, Daniel Poppe, Rebecca K. Simmons, Kieran Walsh, Urwah Nawaz, Ryan Lister, Johann A. Gagnon-Bartsch, Irina Voineag