Lesion Detection in Breast Ultrasound Images Using Tissue Transition Analysis

Breast cancer is one of the leading cause of cancer related deaths in women and early detection is crucial for reducing mortality rates. In this paper, we present a novel and fully automated approach based on tissue transition analysis for lesion detection in breast ultrasound images. Every candidate pixel is classified as belonging to the lesion boundary, lesion interior or normal tissue based on its descriptor value. The tissue transitions are modeled using a Markov chain to estimate the likelihood of a candidate lesion region. Experimental evaluation on a clinical dataset of 135 images show that the proposed approach can achieve high sensitivity (95 %) with modest (3) false positives per image. The approach achieves very similar results (94 % for 3 false positives) on a completely different clinical dataset of 159 images without retraining, highlighting the robustness of the approach.

Temperature dependent electrical characterisation of Pt/HfO2/n-GaN metal-insulator-semiconductor (MIS) Schottky diodes

This paper reports an improvement in Pt/n-GaN metal-semiconductor (MS) Schottky diode characteristics by the introduction of a layer of HfO2 (5 nm) between the metal and semiconductor interface. The resulting Pt/HfO2/n-GaN metal-insulator-semiconductor (MIS) Schottky diode showed an increase in rectification ratio from 35.9 to 98.9(@ 2V), increase in barrier height (0.52 eV to 0.63eV) and a reduction in ideality factor (2.1 to 1.3) as compared to the MS Schottky. Epitaxial n-type GaN films of thickness 300nm were grown using plasma assisted molecular beam epitaxy (PAMBE). The crystalline and optical qualities of the films were confirmed using high resolution X-ray diffraction and photoluminescence measurements. Metal-semiconductor (Pt/n-GaN) and metal-insulator-semiconductor (Pt/HfO2/n-GaN) Schottky diodes were fabricated. To gain further understanding of the Pt/HfO2/GaN interface, I-V characterisation was carried out on the MIS Schottky diode over a temperature range of 150 K to 370 K. The barrier height was found to increase (0.3 eV to 0.79 eV) and the ideality factor decreased (3.6 to 1.2) with increase in temperature from 150 K to 370 K. This temperature dependence was attributed to the inhomogeneous nature of the contact and the explanation was validated by fitting the experimental data into a Gaussian distribution of barrier heights. (C) 2015 Author(s).

Interplay of Substrate Conductivity, Cellular Microenvironment, and Pulsatile Electrical Stimulation toward Osteogenesis of Human Mesenchymal Stem Cells in Vitro

The influences of physical stimuli such as surface elasticity, topography, and chemistry over mesenchymal stem cell proliferation and differentiation are well investigated. In this context, a fundamentally different approach was adopted, and we have demonstrated the interplay of inherent substrate conductivity, defined chemical composition of cellular microenvironment, and intermittent delivery of electric pulses to drive mesenchymal stem cell differentiation toward osteogenesis. For this, conducting polyaniline (PANI) substrates were coated with collagen type 1 (Coll) alone or in association with sulfated hyaluronan (sHya) to form artificial extracellular matrix (aECM), which mimics the native microenvironment of bone tissue. Further, bone marrow derived human mesenchymal stem cells (hMSCs) were cultured on these moderately conductive (10(-4)10(-3) S/cm) aECM coated PANI substrates and exposed intermittently to pulsed electric field (PEF) generated through transformer-like coupling (TLC) approach over 28 days. On the basis of critical analysis over an array of end points, it was inferred that Coll/sHya coated PANI (PANI/Coll/sHya) substrates had enhanced proliferative capacity of hMSCs up to 28 days in culture, even in the absence of PEF stimulation. On the contrary, the adopted PEF stimulation protocol (7 ms rectangular pulses, 3.6 mV/cm, 10 Hz) is shown to enhance osteogenic differentiation potential of hMSCs. Additionally, PEF stimulated hMSCs had also displayed different morphological characteristics as their nonstimulated counterparts. Concomitantly, earlier onset of ALP activity was also observed on PANI/Coll/sHya substrates and resulted in more calcium deposition. Moreover, real-time polymerase chain reaction results indicated higher mRNA levels of alkaline phosphatase and osteocalcin, whereas the expression of other osteogenic markers such as Runt-related transcription factor 2, Col1A, and osteopontin exhibited a dynamic pattern similar to control cells that are cultured in osteogenic medium. Taken together, our experimental results illustrate the interplay of multiple parameters such as substrate conductivity, electric field stimulation, and aECM coating on the modulation of hMSC proliferation and differentiation in vitro.

Effect of Sm3+-Gd3+ on structural, electrical and magnetic properties of Mn-Zn ferrites synthesized via combustion route

Nanocrystalline Mn0.4Zn0.6SmxGdyFe2-(x+y)O4 (x = y = 0.01, 0.02, 0.03, 0.04 and 0.05) were synthesized by combustion route. The detailed structural studies were carried out through X-ray diffractometer (XRD), Fourier transform infrared spectroscopy (FTIR), transmission electron microscopy (TEM). The results confirms the formation of mixed spine phase with cubic structure due to the distortion created with co-dopants substitution at Fe site in Mn-Zn ferrite lattice. Further, the crystallite size increases with an increase of Sm3+-Gd3+ ions concentration while lattice parameter and lattice strain decreases. Furthermore, the effect of Sm-Gd co-doping in Mn-Zn ferrite on the room temperature electrical (dielectric studies) studies were carried out in the wide frequency range 1 GHz-5 GHz. The magnetic studies were carried out using vibrating sample magnetometer (VSM) under applied magnetic field of 1.5T and also room temperature electron paramagnetic resonance (EPR) spectra's were recorded. From the results of dielectric studies, it shows that the real and imaginary part of permittivities are increasing with variation of Gd3+ and Sm3+ concentration. The magnetic studies reveal the decrease of remnant, saturation magnetization and coercivity with increasing of Sm3+-Gd3+ ion concentration. The g-value, peak-to-peak line width and spin concentration evaluated from EPR spectra correlated with cations occupancy. The electromagnetic properties clearly indicate that these materials are the good candidates which are useful at L and C band frequency. (C) 2015 Elsevier B.V. All rights reserved.

Multi-dimensional Goodness-of-Fit Tests for Spectrum Sensing Based on Stochastic Distances

In this paper, we study two multi-dimensional Goodness-of-Fit tests for spectrum sensing in cognitive radios. The multi-dimensional scenario refers to multiple CR nodes, each with multiple antennas, that record multiple observations from multiple primary users for spectrum sensing. These tests, viz., the Interpoint Distance (ID) based test and the h, f distance based tests are constructed based on the properties of stochastic distances. The ID test is studied in detail for a single CR node case, and a possible extension to handle multiple nodes is discussed. On the other hand, the h, f test is applicable in a multi-node setup. A robustness feature of the KL distance based test is discussed, which has connections with Middleton's class A model. Through Monte-Carlo simulations, the proposed tests are shown to outperform the existing techniques such as the eigenvalue ratio based test, John's test, and the sphericity test, in several scenarios.

Event-triggered Sampling and Reconstruction of Sparse Real-valued Trigonometric Polynomials

We propose data acquisition from continuous-time signals belonging to the class of real-valued trigonometric polynomials using an event-triggered sampling paradigm. The sampling schemes proposed are: level crossing (LC), close to extrema LC, and extrema sampling. Analysis of robustness of these schemes to jitter, and bandpass additive gaussian noise is presented. In general these sampling schemes will result in non-uniformly spaced sample instants. We address the issue of signal reconstruction from the acquired data-set by imposing structure of sparsity on the signal model to circumvent the problem of gap and density constraints. The recovery performance is contrasted amongst the various schemes and with random sampling scheme. In the proposed approach, both sampling and reconstruction are non-linear operations, and in contrast to random sampling methodologies proposed in compressive sensing these techniques may be implemented in practice with low-power circuitry.

Effect Of High Pressure On The Electrical Resistivity Of Ge-Te In Glasses

The variation in the electrical resistivity of the chalcogenide glasses Ge15Te85-x has been studied as a function of high pressure for pressures up to 8.5GPa. All the samples studied undergo a semi-conductor to metallic transition in a continuous manner at pressures between 1.5-2.5GPa. The transition pressure at which the samples turn metallic increases with increase in percentage of Indium. This increase is a direct consequence of the increase in network rigidity with the addition of Indium. At a constant pressure of 0.5GPa, the normalized resistivity shows some signature of the existence of the intermediate phase. Samples recovered after a pressure cycle remain amorphous suggesting that the semi-conductor to metallic transition arises from a reduction of the band gap due to pressure or the movement of the Fermi level into the conduction or valence band.

Study on Low Temperature DC Electrical Conductivity of SnO2 Nanomaterial Synthesized by Simple Gel Combustion Method

Nanocrystalline tin oxide (SnO2) material of different particle size was synthesized using gel combustion method by varying oxidizer (HNO3) and keeping fuel as a constant. The prepared samples were characterized by X-Ray Diffraction (XRD), Scanning Electron Microscope (SEM) and Energy Dispersive Analysis X-ray Spectroscope (EDAX). The effect of oxidizer in the gel combustion method was investigated by inspecting the particle size of nano SnO2 powder. The particle size was found to be increases with the increase of oxidizer from 8 to 12 moles. The X-ray diffraction patterns of the calcined product showed the formation of high purity tetragonal tin (IV) oxide with the particle size in the range of 17 to 31 nm which was calculated by Scherer's formula. The particles and temperature dependence of direct (DC) electrical conductivity of SnO2 nanomaterial was studied using Keithley source meter. The DC electrical conductivity of SnO2 nanomaterial increases with the temperature from 80 to 300K and decrease with the particle size at constant temperature.

Thermal, magnetic and electrical properties of Tb1-xDyxMnO3 multiferroics

A series of multiferroic materials with the compositional formula, Tb1 - xDyxMnO3 (where x=0, 0.1, 0.2, 0.3 and 0.4) were prepared by the sol gel method. After characterizing the samples structurally, a systematic investigation of specific heat, magnetization and dielectric properties over the temperature range, 4-300 K, was undertaken. Based on these studies, it was found that all the samples exhibit a transition at 40 K and the observed behavior may be attributed to the ordering of Mn3+ ions. Further, all the five samples are found to exhibit a ferroelectric transition in the temperature range 20-24 K. Finally, yet another transition was also exhibited by all the samples at temperatures below 10 K and is attributed to the antiferromagnetic (AF) ordering of rare-earth ionic moments. The magnetic entropy of all the samples was also computed with the help of their heat capacity data. (C) 2015 Elsevier B.V. All rights reserved.

Magnitude and Origin of Electrical Noise at Individual Grain Boundaries in Graphene

Grain boundaries (GBs) are undesired in large area layered 2D materials as they degrade the device quality and their electronic performance. Here we show that the grain boundaries in graphene which induce additional scattering of carriers in the conduction channel also act as an additional and strong source of electrical noise especially at the room temperature. From graphene field effect transistors consisting of single GB, we find that the electrical noise across the graphene GBs can be nearly 10 000 times larger than the noise from equivalent dimensions in single crystalline graphene. At high carrier densities (n), the noise magnitude across the GBs decreases as proportional to 1/n, suggesting Hooge-type mobility fluctuations, whereas at low n close to the Dirac point, the noise magnitude could be quantitatively described by the fluctuations in the number of propagating modes across the GB.

l(1)-K-SVD: A robust dictionary learning algorithm with simultaneous update

We develop a new dictionary learning algorithm called the l(1)-K-svp, by minimizing the l(1) distortion on the data term. The proposed formulation corresponds to maximum a posteriori estimation assuming a Laplacian prior on the coefficient matrix and additive noise, and is, in general, robust to non-Gaussian noise. The l(1) distortion is minimized by employing the iteratively reweighted least-squares algorithm. The dictionary atoms and the corresponding sparse coefficients are simultaneously estimated in the dictionary update step. Experimental results show that l(1)-K-SVD results in noise-robustness, faster convergence, and higher atom recovery rate than the method of optimal directions, K-SVD, and the robust dictionary learning algorithm (RDL), in Gaussian as well as non-Gaussian noise. For a fixed value of sparsity, number of dictionary atoms, and data dimension, l(1)-K-SVD outperforms K-SVD and RDL on small training sets. We also consider the generalized l(p), 0 < p < 1, data metric to tackle heavy-tailed/impulsive noise. In an image denoising application, l(1)-K-SVD was found to result in higher peak signal-to-noise ratio (PSNR) over K-SVD for Laplacian noise. The structural similarity index increases by 0.1 for low input PSNR, which is significant and demonstrates the efficacy of the proposed method. (C) 2015 Elsevier B.V. All rights reserved.

Simultaneous enhancement of electrical conductivity and thermopower in Bi2S3 under hydrostatic pressure

The inverse coupled dependence of electrical conductivity and thermopower on carrier concentration presents a big challenge in achieving a high figure of merit. However, the simultaneous enhancement of electrical conductivity and thermopower can be realized in practice by carefully engineering the electronic band structure. Here by taking the example of Bi2S3, we report a simultaneous increase in both electrical conductivity and thermopower under hydrostatic pressure. Application of hydrostatic pressure enables tuning of electronic structure in such a way that the conductivity effective mass decreases and the density of states effective mass increases. This dependence of effective masses leads to simultaneous enhancement in electrical conductivity and thermopower under n-type doping leading to a huge improvement in the power factor. Also lattice thermal conductivity exhibits very weak pressure dependence in the low pressure range. The large power factor together with low lattice thermal conductivity results in a high ZT value of 1.1 under n-type doping, which is nearly two times higher than the previously reported value. Hence, this pressure-tuned behaviour can enable the development of efficient thermoelectric devices in the moderate to high temperature range. We further demonstrate that similar enhancement can be observed by generating chemical pressure by doping Bi2S3 with smaller iso-electronic elements such as Sb at Bi sites, which can be achieved experimentally.

Electrical and Plasmonic Properties of Ligand-Free Sn4+-Doped In2O3 (ITO) Nanocrystals

Sn4+-doped In2O3 (ITO) is a benchmark transparent conducting oxide material. We prepared ligand-free but colloidal ITO (8nm, 10% Sn4+) nanocrystals (NCs) by using a post-synthesis surface-modification reaction. (CH3)(3)OBF4 removes the native oleylamine ligand from NC surfaces to give ligand-free, positively charged NCs that form a colloidal dispersion in polar solvents. Both oleylamine-capped and ligand-free ITO NCs exhibit intense absorption peaks, due to localized surface plasmon resonance (LSPR) at around =1950nm. Compared with oleylamine-capped NCs, the electrical resistivity of ligand-free ITO NCs is lower by an order of magnitude (approximate to 35mcm(-1)). Resistivity over a wide range of temperatures can be consistently described as a composite of metallic ITO grains embedded in an insulating matrix by using a simple equivalent circuit, which provides an insight into the conduction mechanism in these systems.

Tailored electrical conductivity, electromagnetic shielding and thermal transport in polymeric blends with graphene sheets decorated with nickel nanoparticles

Electromagnetic interference shielding (EMI) materials were designed using PC (polycarbonate)/SAN poly(styrene-co-acrylonitrile)] blends containing few-layered graphene nanosheets decorated with nickel nanoparticles (G-Ni). The graphene nanosheets were decorated with nickel nanoparticles via the uniform nucleation of the metal salt precursor on graphene sheets as the substrate. In order to localize the nanoparticles in the PC phase of the PC/SAN blends, a two-step mixing protocol was adopted. In the first step, graphene sheets were mixed with PC in solution and casted into a film, followed by dilution of these PC master batch films with SAN in the subsequent melt extrusion step. The dynamic mechanical properties, ac electrical conductivity, EMI shielding effectiveness and thermal conductivity of the composites were evaluated. The G-Ni nanoparticles significantly improved the electrical and thermal conductivity in the blends. In addition, a total shielding effectiveness (SET) of -29.4 dB at 18 GHz was achieved with G-Ni nanoparticles. Moreover, the blends with G-Ni exhibited an impressive 276% higher thermal conductivity and 29.2% higher elastic modulus with respect to the neat blends.

A Novel Approach for Multispectral Satellite Image Classification Based on the Bat Algorithm

Among the multiple advantages and applications of remote sensing, one of the most important uses is to solve the problem of crop classification, i.e., differentiating between various crop types. Satellite images are a reliable source for investigating the temporal changes in crop cultivated areas. In this letter, we propose a novel bat algorithm (BA)-based clustering approach for solving crop type classification problems using a multispectral satellite image. The proposed partitional clustering algorithm is used to extract information in the form of optimal cluster centers from training samples. The extracted cluster centers are then validated on test samples. A real-time multispectral satellite image and one benchmark data set from the University of California, Irvine (UCI) repository are used to demonstrate the robustness of the proposed algorithm. The performance of the BA is compared with two other nature-inspired metaheuristic techniques, namely, genetic algorithm and particle swarm optimization. The performance is also compared with the existing hybrid approach such as the BA with K-means. From the results obtained, it can be concluded that the BA can be successfully applied to solve crop type classification problems.