Effect of Native Defects on Optical Properties of InxGa1-xN Alloys

The energy position of the optical absorption edge and the free carrier populations in InxGa1-xN ternary alloys can be controlled using high energy 4He+ irradiation. The blue shift of the absorption edge after irradiation in In-rich material (x > 0.34) is attributed to the band-filling effect (Burstein-Moss shift) due to the native donors introduced by the irradiation. In Ga-rich material, optical absorption measurements show that the irradiation-introduced native defects are inside the bandgap, where they are incorporated as acceptors. The observed irradiation-produced changes in the optical absorption edge and the carrier populations in InxGa1-xN are in excellent agreement with the predictions of the amphoteric defect model

Walks on weighted networks

We investigate the dynamics of random walks on weighted networks. Assuming that the edge's weight and the node's strength are used as local information by a random walker, we study two kinds of walks, weight-dependent walk and strength-dependent walk. Exact expressions for stationary distribution and average return time are derived and confirmed by computer simulations. We calculate the distribution of average return time and the mean-square displacement for two walks on the BBV networks, and find that a weight-dependent walker can arrive at a new territory more easily than a strength-dependent one.Comment: 4 pages, 5 figures. minor modifications. Comments and suggestions are favored by the author

Quantum theory of electronic double-slit diffraction

The phenomena of electron, neutron, atomic and molecular diffraction have been studied by many experiments, and these experiments are explained by some theoretical works. In this paper, we study electronic double-slit diffraction with quantum mechanical approach. We can obtain the results: (1) When the slit width $a$ is in the range of $3\lambda\sim 50\lambda$ we can obtain the obvious diffraction patterns. (2) when the ratio of $\frac{d+a}{a}=n (n=1, 2, 3,\cdot\cdot\cdot)$, order $2n, 3n, 4n,\cdot\cdot\cdot$ are missing in diffraction pattern. (3)When the ratio of $\frac{d+a}{a}\neq n (n=1, 2, 3,\cdot\cdot\cdot)$, there isn't missing order in diffraction pattern. (4) We also find a new quantum mechanics effect that the slit thickness $c$ has a large affect to the electronic diffraction patterns. We think all the predictions in our work can be tested by the electronic double-slit diffraction experiment.Comment: 9pages, 14figure

Low-complexity detectors for space-time block coded differential spatial modulation

Space-time block coded differential spatial modulation (STBC-DSM) is a recently proposed DSM-based multiple-input-multiple-output (MIMO) transmission technique with high diversity gain. The existing low-complexity detectors for STBC-DSM can be further designed to reduce complexity. In this paper, we propose an ordered antenna index vector detector (OVD) for STBC-DSM, and an OV-low repetition detector (OV-LRD) for further simplification. The OVD detects the symbols in a designed order, and the OV-LRD fully uses the STBC structure to simplify the OVD. Simulation results show that the OVD achieves near-optimal performance, and the OV-LRD significantly reduces complexity with negligible performance loss

Growth and characterization of A_{1-x}K_xFe_2As_2 (A = Ba, Sr) single crystals with x=0 - 0.4

Single crystals of A$_{1-x}$K$_x$Fe$_2$As$_2$ (A=Ba, Sr) with high quality have been grown successfully by FeAs self-flux method. The samples have sizes up to 4 mm with flat and shiny surfaces. The X-ray diffraction patterns suggest that they have high crystalline quality and c-axis orientation. The non-superconducting crystals show a spin-density-wave (SDW) instability at about 173 K and 135 K for Sr-based and Ba-based compound, respectively. After doping K as the hole dopant into the BaFe$_2$As$_2$ system, the SDW transition is smeared, and superconducting samples with the compound of Ba$_{1-x}$K$_x$Fe$_2$As$_2$ (0 $< x \leqslant$ 0.4) are obtained. The superconductors characterized by AC susceptibility and resistivity measurements exhibit very sharp superconducting transition at about 36 K, 32 K, 27 K and 23 K for x= 0.40,0.28,0.25 and 0.23, respectively.Comment: 9 pages, 6 figures, 1 table. This paper together with new data are modified into a new pape

A fully-automated paper ECG digitisation algorithm using deep learning

There is increasing focus on applying deep learning methods to electrocardiograms (ECGs), with recent studies showing that neural networks (NNs) can predict future heart failure or atrial fibrillation from the ECG alone. However, large numbers of ECGs are needed to train NNs, and many ECGs are currently only in paper format, which are not suitable for NN training. We developed a fully-automated online ECG digitisation tool to convert scanned paper ECGs into digital signals. Using automated horizontal and vertical anchor point detection, the algorithm automatically segments the ECG image into separate images for the 12 leads and a dynamical morphological algorithm is then applied to extract the signal of interest. We then validated the performance of the algorithm on 515 digital ECGs, of which 45 were printed, scanned and redigitised. The automated digitisation tool achieved 99.0% correlation between the digitised signals and the ground truth ECG (n = 515 standard 3-by-4 ECGs) after excluding ECGs with overlap of lead signals. Without exclusion, the performance of average correlation was from 90 to 97% across the leads on all 3-by-4 ECGs. There was a 97% correlation for 12-by-1 and 3-by-1 ECG formats after excluding ECGs with overlap of lead signals. Without exclusion, the average correlation of some leads in 12-by-1 ECGs was 60–70% and the average correlation of 3-by-1 ECGs achieved 80–90%. ECGs that were printed, scanned, and redigitised, our tool achieved 96% correlation with the original signals. We have developed and validated a fully-automated, user-friendly, online ECG digitisation tool. Unlike other available tools, this does not require any manual segmentation of ECG signals. Our tool can facilitate the rapid and automated digitisation of large repositories of paper ECGs to allow them to be used for deep learning projects

High-T_c superconductivity induced by doping rare earth elements into CaFeAsF

We have successfully synthesized the fluoride-arsenide compounds Ca$_{1-x}$RE$_x$FeAsF (RE=Nd, Pr; x=0, 0.6). The x-ray powder diffraction confirmed that the main phases of our samples are Ca$_{1-x}$RE$_x$FeAsF with the ZrCuSiAs structure. By measuring resistivity, superconductivity was observed at 57.4 K in Nd-doped and 52.8 K in Pr-doped samples with x=0.6. Bulk superconductivity was also proved by the DC magnetization measurements in both samples. Hall effect measurements revealed hole-like charge carriers in the parent compound CaFeAsF with a clear resistivity anomaly below 118 K, while the Hall coefficient $R_H$ in the normal state is negative for the superconducting samples Ca$_{0.4}$Nd$_{0.6}$FeAsF and Ca$_{0.4}$Pr$_{0.6}$FeAsF. This indicates that the rare earth element doping introduces electrons into CaFeAsF which induces the high temperature superconductivity.Comment: 4 pages, 4 figure