First principle studies of structural, elastic, electronic and optical properties of Zn-chalcogenides under pressure

Structural, elastic, electronic and optical properties ofzinc-chalcogenides （viz. ZnX, X = S, Se and Te） are studied in zinc-blende structure under hydrostatic pressure using the full-potential linearized augmented plane wave method. Generalized gradient approximation is used for exchange correlation potentials. Pressure-dependent lattice constants and bulk moduli are obtained using the optimization method. Young＇s modulus, Poisson＇s ratio, internal strain parameter and anisotropy are also calculated. The higher values of Young＇s modulus in comparison to the bulk modulus show that these materials are hard to break. Poisson＇s ratio is computed for the first time for these materials to the best of our knowledge and its values show higher ionic contribution in these materials. Modified Becke and Johnson （mBJ） method is used to study band gaps, density of states, dielectric function and refractive index. Electronic study shows direct band gaps convert to indirect band gaps with increasing pressure in the case of ZnS and ZnTe. We compared our results with other theoretical and experimental results. Our results are far better than other theoretical results because mBJ is the best technique to treat Ⅱ-Ⅵ semiconductors.     

Robust information gain based fuzzy c-means clustering and classification of carotid artery ultrasound images

In this paper, a robust method is proposed for segmentation of medical images by exploiting the concept of information gain. Medical images contain inherent noise due to imaging equipment, operating environment and patient movement during image acquisition. A robust medical image segmentation technique is thus inevitable for accurate results in subsequent stages. The clustering technique proposed in this work updates fuzzy membership values and cluster centroids based on information gain computed from the local neighborhood of a pixel. The proposed approach is less sensitive to noise and produces homogeneous clustering. Experiments are performed on medical and non-medical images and results are compared with state of the art segmentation approaches. Analysis of visual and quantitative results verifies that the proposed approach outperforms other techniques both on noisy and noise free images. Furthermore, the proposed technique is used to segment a dataset of 300 real carotid artery ultrasound images. A decision system for plaque detection in the carotid artery is then proposed. Intima media thickness (IMT) is measured from the segmented images produced by the proposed approach. A feature vector based on IMT values is constructed for making decision about the presence of plaque in carotid artery using probabilistic neural network (PNN). The proposed decision system detects plaque in carotid artery images with high accuracy. Finally, effect of the proposed segmentation technique has also been investigated on classification of carotid artery ultrasound images.     

Physicochemical Characteristics,Functional Properties,and Nutritional Benefits of Peanut Oil: A Review

The legume Arachis hypogaea, commonly known as peanut or groundnut, is a very important food crop throughout the tropics and subtropics. Peanut is one of the most widely used legumes due to its nutrition and taste, and it occupies a rank of major oilseed crop in the world. It has been recognized as a functional food due to its role in a health promoting effect. Peanut oil contains a well-balanced fatty acid and antioxidant profile that provide protection against harmful substances especially free radicals. This paper gives an overview of scientific literature available on phytochemical and functional properties of peanut oil. Owing to its unique organoleptic properties associated with its cardioprotective and anti-inflammatory properties, peanut oil has found, recently, its place on the highly competitive international edible oil market.     

Intelligent computing for the dynamics of fluidic system of electrically conducting Ag/Cu nanoparticles with mixed convection for hydrogen possessions

The present study aims to provide an innovative stochastic numerical solver's application by the use of neural networks with Levenberg-Marquardt backpropagation to examine the dynamics of hydrogen possessions and variable viscosity in the fluidic system of electrically conducting copper and silver nanoparticles with mixed convection. The system of PDEs obtained by mathematical modeling of the physical phenomena are reduced into non-linear ODEs by utilizing suitable transformations. The ODEs dataset is constructed through Adams numerical solver and target parameters for input and output parameter of neural networks. The testing, validation and training processes are exploited in neural network models with learning based on backpropagation of LM method to calculate the solution for different scenarios created on variation of physical parameters of the proposed flow of Reynolds and Vogel models. Validation and verification of neural network model to find the solution of fluid flow problem is endorsed on the assessment of achieved accuracy through mean squared error, error histograms and regression studies.     

Influence of Hall and Joule heating on a magnetic nanofluid (Fe3O4) flow on a rotating disk with generalized slip condition

This study analyzes Hall current and Joule heating effects on the ferro-nanofluid flow by the rotation of the disk incorporated with generalized slip condition. By using the well-known Von Karman transformation, formulated flow equations are modeled into ordinary differential equations. Numerical solutions of the governing flow equations are attained by utilizing the shooting method consolidated with the fourth-order Runge–Kutta scheme. The impacts of different parameters on skin friction coefficient, velocity, temperature, and Nusselt number are given in graphs and tables and investigated in detail. Furthermore, an association with formerly published articles is given and met in remarkable correspondence.     

Backstepping and Synergetic Controllers for the Chemotherapy of Brain Tumor

International Journal of Control, Automation and Systems - The treatment of brain tumors by chemotherapy through the controlled rate of drug has been a challenging task since long. Two nonlinear...     

A novel method for vehicle detection in high-resolution aerial remote sensing images using YOLT approach

Multimedia Tools and Applications - Owing to the innovative challenge stood by an intergovernmental military alliance, we have proposed a model to find novel solutions in the areas of data...