Prussian Blue-coated interdigitated array electrodes for possible analytical application

Thin films of iron(III) hexacyanoferrate(II) (Prussian Blue) were electrochemically deposited on interdigitated array (IDA) electrodes, yielding systems which can be considered as chemiresistors in sensing alkali metal ion concentrations in an adjacent electrolyte. This is due to the fact that the conductivity of the film being measured by a steady-state current on application of a voltage to the two-fingered electrodes of the IDA depends on both the redox stare of the film and the cation concentration in the electrolyte. From the dependence of the steady-state current on the electrode (bias) potential at variable cation concentrations for different alkali metal ions and for mixtures of alkali metal ions, the possibilities of analytical application were elucidated. In addition, by using the methods of staircase coulometry and scanning conductivity, the electron diffusion coefficient De was determined as a function of the redox state of Prussian Blue. It is concluded that Prussian Blue-coated IDA electrodes are, in principle, suitable as chemiresistors for the determination of alkali metal ion concentrations with increasing selectivity in the series Li < Na < K < Rb < Cs

A Terrestrial Multiple-Receiver Radio Link Experiment at 10.7 GHz - Comparisons of Results with Parabolic Equation Calculations

This work presents the results of a terrestrial multiple-receiver radio link experiment at 10.7 GHz. Results are shown in the form of the power levels recorded at several antennas attached to a receiving mast. Comparisons of the measurement data with theoretical predictions using a parabolic equation technique show that, due to the complex propagation environment of the troposphere in terms of the refractive index of air, closer agreement between measurements and simulations can be achieved during periods of standard refractive conditions

Visual on-line learning in distributed camera networks

Automatic detection of persons is an important application in visual surveillance. In general, state-of-the-art systems have two main disadvantages: First, usually a general detector has to be learned that is applicable to a wide range of scenes. Thus, the training is time-consuming and requires a huge amount of labeled data. Second, the data is usually processed centralized, which leads to a huge network traffic. Thus, the goal of this paper is to overcome these problems, which is realized by a person detection system, that is based on distributed smart cameras (DSCs). Assuming that we have a large number of cameras with partly overlapping views, the main idea is to reduce the model complexity of the detector by training a specific detector for each camera. These detectors are initialized by a pre-trained classifier, that is then adapted for a specific camera by co-training. In particular, for co-training we apply an on-line learning method (i.e., boosting for feature selection), where the information exchange is realized via mapping the overlapping views onto each other by using a homography. Thus, we have a compact scenedependent representation, which allows to train and to evaluate the classifiers on an embedded device. Moreover, since the information transfer is reduced to exchanging positions the required network-traffic is minimal. The power of the approach is demonstrated in various experiments on different publicly available data sets. In fact, we show that on-line learning and applying DSCs can benefit from each other. Index Terms — visual on-line learning, object detection, multi-camera networks 1

Global first-passage times of fractal lattices

The global first passage time density of a network is the probability that a random walker released at a random site arrives at an absorbing trap at time T. We find simple expressions for the mean global first passage time for five fractals: the d-dimensional Sierpinski gasket, T fractal, hierarchical percolation model, Mandelbrot-Given curve, and a deterministic tree. We also find an exact expression for the second moment and show that the variance of the first passage time, Var(T), scales with the number of nodes within the fractal N such that Var(T)similar to N(4/d), where d is the spectral dimension

Tissue-specific expression of high-voltage-activated dihydropyridine-sensitive L-type calcium channels

The cloning of the cDNA for the α1 subunit of L-type calcium channels revealed that at least two genes (CaCh1 and CaCh2) exist which give rise to several splice variants. The expression of mRNA for these α1 subunits and the skeletal muscle α2/δ, β and γ subunits was studied in rabbit tissues and BC3H1 cells. Nucleic-acid-hybridization studies showed that the mRNA of all subunits are expressed in skeletal muscle, brain, heart and aorta. However, the α1-, β- and γ-specific transcripts had different sizes in these tissues. Smooth muscle and heart contain different splice variants of the CaCh2 gene. The α1, β and γ mRNA are expressed together in differentiated but not in proliferating BC3H1 cells. A probe specific for the skeletal muscle α2/δ subunit did not hybridize to poly(A)-rich RNA from BC3H1 cells. These results suggest that different splice variants of the genes for the α1, β and γ subunits exist in tissues containing L-type calcium channels, and that their expression is regulated in a coordinate manner

Photogenerated Carriers in SrTiO3 Probed by Mid-Infrared Absorption

Infrared absorption spectra of SrTiO$_3$ have been measured under above-band-gap photoexcitations to study the properties of photogenerated carriers, which should play important roles in previously reported photoinduced phenomena in SrTiO$_3$. A broad absorption band appears over the entire mid-infrared region under photoexcitation. Detailed energy, temperature, and excitation power dependences of the photoinduced absorption are reported. This photo-induced absorption is attributed to the intragap excitations of the photogenerated carriers. The data show the existence of a high density of in-gap states for the photocarriers, which extends over a wide energy range starting from the conduction and valence band edges.Comment: 5 pages, 5 figures, submitted to J. Phys. Soc. Jp

Long-Term Visual Object Tracking Benchmark

We propose a new long video dataset (called Track Long and Prosper - TLP) and benchmark for single object tracking. The dataset consists of 50 HD videos from real world scenarios, encompassing a duration of over 400 minutes (676K frames), making it more than 20 folds larger in average duration per sequence and more than 8 folds larger in terms of total covered duration, as compared to existing generic datasets for visual tracking. The proposed dataset paves a way to suitably assess long term tracking performance and train better deep learning architectures (avoiding/reducing augmentation, which may not reflect real world behaviour). We benchmark the dataset on 17 state of the art trackers and rank them according to tracking accuracy and run time speeds. We further present thorough qualitative and quantitative evaluation highlighting the importance of long term aspect of tracking. Our most interesting observations are (a) existing short sequence benchmarks fail to bring out the inherent differences in tracking algorithms which widen up while tracking on long sequences and (b) the accuracy of trackers abruptly drops on challenging long sequences, suggesting the potential need of research efforts in the direction of long-term tracking.Comment: ACCV 2018 (Oral

Online, Real-Time Tracking Using a Category-to-Individual Detector

A method for online, real-time tracking of objects is presented. Tracking is treated as a repeated detection problem where potential target objects are identified with a pre-trained category detector and object identity across frames is established by individual-specific detectors. The individual detectors are (re-)trained online from a single positive example whenever there is a coincident category detection. This ensures that the tracker is robust to drift. Real-time operation is possible since an individual-object detector is obtained through elementary manipulations of the thresholds of the category detector and therefore only minimal additional computations are required. Our tracking algorithm is benchmarked against nine state-of-the-art trackers on two large, publicly available and challenging video datasets. We find that our algorithm is 10% more accurate and nearly as fast as the fastest of the competing algorithms, and it is as accurate but 20 times faster than the most accurate of the competing algorithms

Average distances on self-similar sets and higher order average distances of self-similar measures

The purpose of this paper is twofold: (1) we study different notions of the average distance between two points of a self-similar subset of ℝ, and (2) we investigate the asymptotic behaviour of higher order average moments of self-similar measures on self-similar subsets of ℝ

Laplace Operators on Fractals and Related Functional Equations

We give an overview over the application of functional equations, namely the classical Poincar\'e and renewal equations, to the study of the spectrum of Laplace operators on self-similar fractals. We compare the techniques used to those used in the euclidean situation. Furthermore, we use the obtained information on the spectral zeta function to define the Casimir energy of fractals. We give numerical values for this energy for the Sierpi\'nski gasket