Electronic compressibility and charge imbalance relaxation in cuprate superconductors

In the material SmLa$_{1-x}$Sr$_x$CuO$_{4-\delta}$ with alternating intrinsic Josephson junctions we explain theoretically the relative amplitude of the two plasma peaks in transmission by taking into account the spatial dispersion of the Josephson Plasma Resonance in $c$ direction due to charge coupling. From this and the magnetic field dependence of the plasma peaks in the vortex solid and liquid states it is shown that the electronic compressibility of the CuO$_2$ layers is consistent with a free electron value. Also the London penetration depth $\lambda_{ab} \approx 1100 {\rm \AA}$ near $T_c$ can be determined. The voltage response in the $IV$-curve of a Bi$_2$Sr$_2$CaCu$_2$O$_8$ mesa due to microwave irradiation or current injection in a second mesa is related to the nonequilibrium charge imbalance of quasiparticles and Cooper pairs and from our experimental data the relaxation time $\sim 100 {\rm ps}$ is obtained.Comment: 2 pages, 2 figures, phc-proc4-auth.cls, to be published in Physica C as a proceeding of M2S-HTSC Rio 200

Intrinsic Tunneling in Cuprates and Manganites

The most anisotropic high temperature superconductors like Bi2Sr2CaCu2O8, as well as the recently discovered layered manganite La1.4Sr1.6Mn2O7 are layered metallic systems where the interlayer current transport occurs via sequential tunneling of charge carriers. As a consequence, in Bi2Sr2CaCu2O8 adjacent CuO2 double layers form an intrinsic Josephson tunnel junction while in in La1.4Sr1.6Mn2O7 tunneling of spin polarized charge carriers between adjacent MnO2 layers leads to an intrinsic spin valve effect. We present and discuss interlayer transport experiments for both systems. To perform the experiments small sized mesa structures were patterned on top of single crystals of the above materials defining stacks of a small number of intrinsic Josephson junctions and intrinsic spin valves, respectively.Comment: 6 pages, 8 figure

Charge-imbalance effects in intrinsic Josephson systems

We report on two types of experiments with intrinsic Josephson systems made from layered superconductors which show clear evidence of nonequilibrium effects: 1. In 2-point measurements of IV-curves in the presence of high- frequency radiation a shift of the voltage of Shapiro steps from the canonical value hf/(2e) has been observed. 2. In the IV-curves of double-mesa structures an influence of the current through one mesa on the voltage measured on the other mesa is detected. Both effects can be explained by charge-imbalance on the superconducting layers produced by the quasi-particle current, and can be described successfully by a recently developed theory of nonequilibrium effects in intrinsic Josephson systems.Comment: 8pages, 9figures, submitted to Phys. Rev.

Ingestion of Diet Soda Before a Glucose Load Augments Glucagon-Like Peptide-1 Secretion

OBJECTIVE — The goal of this study was to determine the effect of artificial sweeteners on glucose, insulin, and glucagon-like peptide (GLP)-1 in humans. RESEARCH DESIGN AND METHODS — For this study, 22 healthy volunteers (mean age 18.5 � 4.2 years) underwent two 75-g oral glucose tolerance tests with frequent measurements of glucose, insulin, and GLP-1 for 180 min. Subjects drank 240 ml of diet soda or carbonated water, in randomized order, 10 min prior to the glucose load. RESULTS — Glucose excursions were similar after ingestion of carbonated water and diet soda. Serum insulin levels tended to be higher after diet soda, without statistical significance. GLP-1 peak and area under the curve (AUC) were significantly higher with diet soda (AUC 24.0 � 15.2 pmol/l per 180 min) versus carbonated water (AUC 16.2 � 9.0 pmol/l per 180 min; P � 0.003). CONCLUSIONS — Artificial sweeteners synergize with glucose to enhance GLP-1 release in humans. This increase in GLP-1 secretion may be mediated via stimulation of sweet-taste receptors on L-cells by artificial sweetener. Consumption of sodas containing artificial sweeteners is common practice in both children and adults. It is generally assumed that glucose metabolism is not altered because these sodas contain no or extremely few calories from carbohydrate. However, recent data obtained from animal studies demonstrate that artificial sweeteners play an active metabolic role within the gastrointestinal tract. Sweet-taste receptors, including the T1R family and �-gustducin, respond not only to caloric sugars such as sucrose but also to artificial sweeteners, including sucralose (Splenda) and acesulfame-K (1,2). In both humans and animals, these receptors have been shown to be present in glucagon-like peptide (GLP)-1–secreting L-cells of the gut mucosa as well as in lingual taste buds (3–5) and serve as critical mediators of GLP-1 secretion (5). In Diabetes Care 32:2184–2186, 2009 this study, we examined the effect of artificial sweeteners in a commercially available soft drink on glucose, insulin, and GLP-1 in humans

Image Co-localization by Mimicking a Good Detector's Confidence Score Distribution

Given a set of images containing objects from the same category, the task of image co-localization is to identify and localize each instance. This paper shows that this problem can be solved by a simple but intriguing idea, that is, a common object detector can be learnt by making its detection confidence scores distributed like those of a strongly supervised detector. More specifically, we observe that given a set of object proposals extracted from an image that contains the object of interest, an accurate strongly supervised object detector should give high scores to only a small minority of proposals, and low scores to most of them. Thus, we devise an entropy-based objective function to enforce the above property when learning the common object detector. Once the detector is learnt, we resort to a segmentation approach to refine the localization. We show that despite its simplicity, our approach outperforms state-of-the-art methods.Comment: Accepted to Proc. European Conf. Computer Vision 201

Deep Learning for Vanishing Point Detection Using an Inverse Gnomonic Projection

We present a novel approach for vanishing point detection from uncalibrated monocular images. In contrast to state-of-the-art, we make no a priori assumptions about the observed scene. Our method is based on a convolutional neural network (CNN) which does not use natural images, but a Gaussian sphere representation arising from an inverse gnomonic projection of lines detected in an image. This allows us to rely on synthetic data for training, eliminating the need for labelled images. Our method achieves competitive performance on three horizon estimation benchmark datasets. We further highlight some additional use cases for which our vanishing point detection algorithm can be used.Comment: Accepted for publication at German Conference on Pattern Recognition (GCPR) 2017. This research was supported by German Research Foundation DFG within Priority Research Programme 1894 "Volunteered Geographic Information: Interpretation, Visualisation and Social Computing