Quiescent optical solitons with complex Ginzburg-Landau equation having a dozen forms of self-phase modulation.

The current study focuses on the recovery of quiescent optical solitons through the use of the complex Ginzburg-Landau equation when the chromatic dispersion is rendered to be nonlinear. A dozen forms of self-phase modulation structures are taken into consideration. The utilization of the enhanced Kudryashov's scheme has led to the emergence of singular, dark, and bright soliton solutions. The existence of such solitons is subject to certain parametric restrictions, which are also discussed in this paper.

Dispersive optical solitons and conservation laws of Radhakrishnan-Kundu-Lakshmanan equation with dual-power law nonlinearity.

The current paper implements three elegant approaches to recover a complete spectrum of optical solitons to the Radhakrishnan-Kundu-Lakshmanan equation with dual-power law of nonlinear refractive index. The conservation laws are also recovered by the usage of multipliers approach. The parameter constraints for the existence of such solitons are also enumerated. The numerical simulations of the recovered soliton solutions are also presented.

Combining Sparse and Dense Features to Improve Multi-Modal Registration for Brain DTI Images.

A new solution to overcome the constraints of multimodality medical intra-subject image registration is proposed, using the mutual information (MI) of image histogram-oriented gradients as a new matching criterion. We present a rigid, multi-modal image registration algorithm based on linear transformation and oriented gradients for the alignment of T2-weighted (T2w) images (as a fixed reference) and diffusion tensor imaging (DTI) (b-values of 500 and 1250 s/mm2) as floating images of three patients to compensate for the motion during the acquisition process. Diffusion MRI is very sensitive to motion, especially when the intensity and duration of the gradient pulses (characterized by the b-value) increases. The proposed method relies on the whole brain surface and addresses the variability of anatomical features into an image stack. The sparse features refer to corners detected using the Harris corner detector operator, while dense features use all image pixels through the image histogram of oriented gradients (HOG) as a measure of the degree of statistical dependence between a pair of registered images. HOG as a dense feature is focused on the structure and extracts the oriented gradient image in the x and y directions. MI is used as an objective function for the optimization process. The entropy functions and joint entropy function are determined using the HOGs data. To determine the best image transformation, the fiducial registration error (FRE) measure is used. We compare the results against the MI-based intensities results computed using a statistical intensity relationship between corresponding pixels in source and target images. Our approach, which is devoted to the whole brain, shows improved registration accuracy, robustness, and computational cost compared with the registration algorithms, which use anatomical features or regions of interest areas with specific neuroanatomy. Despite the supplementary HOG computation task, the computation time is comparable for MI-based intensities and MI-based HOG methods.

Solitions in magneto-optic waveguides with anti-cubic nonlinearity.

Optical soliton solutions are recovered for magneto-optic waveguides that maintains anti-cubic form of nonlinear refractive index. The analytical scheme is Jacobi's elliptic function approach. Once the solutions to the governing model are obtained in terms of Jacobi's elliptic functions, the limiting value to it's modulus of ellipticity reveals the complete spectrum of soliton solutions.

The similarities and differences of different plane solitons controlled by (3 + 1) - Dimensional coupled variable coefficient system.

In this paper, a system with controllable parameters for describing the evolution of polarization modes in nonlinear fibers is studied. Using the Horita's method, the coupled nonlinear Schrödinger equations are transformed into the bilinear equations, and the one- and two- bright soliton solutions of system (3) are obtained. Then, the influencing factors on velocity and intensity in the process of soliton transmission are analyzed. The fusion, splitting and deformation of the solitons caused by their interactions are discussed. Finally, a method for adjusting the inconsistencies of sine-wave soliton transmission is given. The conclusions of this paper may be helpful for the related research of wavelength division multiplexing systems.

Cubic-quartic bright optical solitons with improved Adomian decomposition method.

This paper numerically retrieves cubic-quartic solitons having power law of nonlinearity refractive index. An improvement of the Adomian decomposition scheme is the adopted algorithm of this work. The results are displayed along with the established error analysis.

Gaussian mixture model for texture characterization with application to brain DTI images.

A Gaussian mixture model (GMM)-based classification technique is employed for a quantitative global assessment of brain tissue changes by using pixel intensities and contrast generated by b-values in diffusion tensor imaging (DTI). A hemisphere approach is also proposed. A GMM identifies the variability in the main brain tissues at a macroscopic scale rather than searching for tumours or affected areas. The asymmetries of the mixture distributions between the hemispheres could be used as a sensitive, faster tool for early diagnosis. The k-means algorithm optimizes the parameters of the mixture distributions and ensures that the global maxima of the likelihood functions are determined. This method has been illustrated using 18 sub-classes of DTI data grouped into six levels of diffusion weighting (b = 0; 250; 500; 750; 1000 and 1250 s/mm2) and three main brain tissues. These tissues belong to three subjects, i.e., healthy, multiple haemorrhage areas in the left temporal lobe and ischaemic stroke. The mixing probabilities or weights at the class level are estimated based on the sub-class-level mixing probability estimation. Furthermore, weighted Euclidean distance and multiple correlation analysis are applied to analyse the dissimilarity of mixing probabilities between hemispheres and subjects. The silhouette data evaluate the objective quality of the clustering. By using a GMM in the present study, we establish an important variability in the mixing probability associated with white matter and grey matter between the left and right hemispheres.

Phase shift, amplification, oscillation and attenuation of solitons in nonlinear optics.

In nonlinear optics, the soliton transmission in different forms can be described with the use of nonlinear Schrödinger (NLS) equations. Here, the soliton transmission is investigated by solving the NLS equation with the reciprocal of the group velocity ß 1 ( z ) , the group velocity dispersion coefficient ß 2 ( z ) and nonlinear coefficient γ ( z ) . Two-soliton solutions for the NLS equation are obtained through the Hirota method. According to the solutions obtained, ß 1 ( z ) and γ ( z ) with different function forms are taken to study the characteristics of solitons. The effect of the phase shift on the soliton interaction is discussed, and the non-oscillating soliton amplification, which is transmitted in a bound state, is explored. Parabolic solitons with oscillations are analysed. Moreover, parabolic solitons can be reduced to dromion-like structures. Results indicate that the transmission of solitons can be adjusted with the group velocity dispersion and Kerr nonlinearity coefficients. The phase shift, amplification, oscillation and attenuation of solitons can also be controlled by other related parameters. This work accomplishes the theoretical study of transmission characteristics of optical solitons in spatially dependent inhomogeneous optical fibres. The conclusions of this research have theoretical guidance for the research of optical amplifier, all-optical switches and mode-locked lasers.

Robust Skull-Stripping Segmentation Based on Irrational Mask for Magnetic Resonance Brain Images.

This paper proposes a new method for simple, efficient, and robust removal of the non-brain tissues in MR images based on an irrational mask for filtration within a binary morphological operation framework. The proposed skull-stripping segmentation is based on two irrational 3 × 3 and 5 × 5 masks, having the sum of its weights equal to the transcendental number π value provided by the Gregory-Leibniz infinite series. It allows maintaining a lower rate of useful pixel loss. The proposed method has been tested in two ways. First, it has been validated as a binary method by comparing and contrasting with Otsu's, Sauvola's, Niblack's, and Bernsen's binary methods. Secondly, its accuracy has been verified against three state-of-the-art skull-stripping methods: the graph cuts method, the method based on Chan-Vese active contour model, and the simplex mesh and histogram analysis skull stripping. The performance of the proposed method has been assessed using the Dice scores, overlap and extra fractions, and sensitivity and specificity as statistical methods. The gold standard has been provided by two neurologist experts. The proposed method has been tested and validated on 26 image series which contain 216 images from two publicly available databases: the Whole Brain Atlas and the Internet Brain Segmentation Repository that include a highly variable sample population (with reference to age, sex, healthy/diseased). The approach performs accurately on both standardized databases. The main advantage of the proposed method is its robustness and speed.

Management of experimental hypochlorhydria with iron deficiency by the composite extract of Fumaria vaillantii L. and Benincasa hispida T. in rat.

The aim of the present study was to search the effective ratio of whole plant of Fumaria vaillantii Loisel (Fumaria vaillantii L.) and fruit of Benincasa hispida Thunb. (Benincasa hispida T.) in composite form, namely "FVBH" for the management of hypochlorhydria along with iron deficiency in male albino rats. Hypochlorhydria refers to suppression of hydrochloric acid secretion by the stomach. Hypochlorhydria was induced by ranitidine in this study. We used four composite extracts of the mentioned plant and fruit with different ratios (1:1, 1:2, 2:1, and 3:2) for searching the most effective composite extract for the correction of hypochlorhydria. Gastric acidity is an important factor for iron absorption. Thus, hypochlorhydria causes iron deficiency in rat and it was prevented significantly by the extract treatment at the ratio of 1:1 of the said plant and fruit. The correction of iron deficiency by the composite extract was compared with iron supplementation to hypochlorhydric rat. It was found that preadministration followed by coadministration of FVBH-1 (1:1) able to prevent the ranitidine-induced hypochlorhydria and iron deficiency. The composite extract, FVBH-1 (1:1) significantly (P<0.05) increased the pepsin concentration, chloride level in gastric juice, iron levels in serum and liver along with blood hemoglobin level than other ratios used here. Hence, it can be concluded that FVBH-1 (1:1) is an effective herbal formulation for the management of hypochlorhydria and related iron deficiency.

Optimization of breast lesion segmentation in texture feature space approach.

This paper develops a method for semi-automatic detection of breast lesion boundaries by combining the snake evolution techniques with statistical texture information of images. We propose an efficient image energy function in segmentation based on image features, first-order textural features and four n×n masks. The segmentation results were evaluated by using area error rate. The image features were evaluated qualitatively by using the contrast-to-noise ratio and fractal dimension analysis. In our study, standard deviation, skewness and entropy are indicated as being the most relevant image features.

Domain wall and bifurcation analysis of the Klein-Gordon Zakharov equation in (1+2)-dimensions with power law nonlinearity.

This paper studies the Klein-Gordon Zakharov equation with power law nonlinearity in (1+2)-dimensions. The ansatz method will be applied to obtain the 1-soliton solution, also known as domain wall solution, along with several constraint conditions that naturally fall out. Subsequently, the bifurcation analysis is carried out where the phase portrait is given. Additionally, this analysis leads to several solutions to the equation with the traveling wave scheme. This gives soliton solution as well as singular periodic solutions. Finally, the numerical simulations for the domain wall solution were obtained where the finite difference scheme is applied.

Standalone functional CAD system for multi-object case analysis in hepatic disorders.

A new algorithm able to automatically diagnose the presence of the hemangioma areas in the hepatic ultrasonographic image is proposed. The algorithm uses a new multi-object approach which decomposes the image into three biological regions: a normal hepatic area, a hemangioma area and other areas. The de-noising process is efficiently accomplished for both Gaussian and Rayleigh noise distributions. Furthermore, a segmentation technique, based on gray level intensity analysis and the Moore-Neighbor contour tracing algorithm for a robust differentiation of the hemangioma area are employed. This new proposed technique is almost fully automatic, fast, and simple and its results are satisfactory.

Thyroid nodule recognition based on feature selection and pixel classification methods.

Statistical approach is a valuable way to describe texture primitives. The aim of this study is to design and implement a classifier framework to automatically identify the thyroid nodules from ultrasound images. Using rigorous mathematical foundations, this article focuses on developing a discriminative texture analysis method based on texture variations corresponding to four biological areas (normal thyroid, thyroid nodule, subcutaneous tissues, and trachea). Our research follows three steps: automatic extraction of the most discriminative first-order statistical texture features, building a classifier that automatically optimizes and selects the valuable features, and correlating significant texture parameters with the four biological areas of interest based on pixel classification and location characteristics. Twenty ultrasound images of normal thyroid and 20 that present thyroid nodules were used. The analysis involves both the whole thyroid ultrasound images and the region of interests (ROIs). The proposed system and the classification results are validated using the receiver operating characteristics which give a better overall view of the classification performance of methods. It is found that the proposed approach is capable of identifying thyroid nodules with a correct classification rate of 83 % when whole image is analyzed and with a percent of 91 % when the ROIs are analyzed.

Effect of different solvent extracts of Benincasa hispida T. on experimental hypochlorhydria in rat.

Hypochlorhydria is a common problem in any age of people like other gastric disorders. It has so many etiologies such as sympathetic dominance, antiseretory drug use, excess sugar and refined foods, etc. In the present study, our objective was to search out the effective solvent extract of fruit of Benincasa hispida T. for the management of hypochlorhydria in model male albino rats. Hypochlorhydria was induced in rat as per standard method by oral administration of ranitidine. Different solvent extracts (Hydro-methanol, ethyl acetate, and aqueous) of ripe fruit of B. hispida were prepared following the standard protocol. Various parameters in this concern like free acidity, total acidity, pH, pepsin concentration, chloride and vitamin C levels in gastric juice were measured by standard biochemical and titrimetric methods. It was found that pre-administration followed by co-administration of aqueous extract of B. hispida (ABH) resulted significant correction of ranitidine-induced hypochlorhydria in rat. This aqueous extract-treated group showed increased levels of vitamin C, pepsin, and chloride concentration in gastric juice as well as the antioxidant status significantly (P<0.05) in respect to other extract-treated groups. From the results, it can be concluded that the ABH has most effective anti-hypochlorhydric and antioxidative efficacy than other solvent extracts of said plant fruit.

An exact solution for the modified nonlinear Schrödinger's equation for Davydov solitons in alpha-helix proteins.

The solitons in alpha-helix proteins that are governed by the nonlinear Schrödinger's equation is investigated in presence of perturbation terms in this paper. The integration of this perturbed nonlinear Schrödinger's equation is carried out. The solitary wave ansatz is used to carry out the integration and the parameter domain is identified.

Collision-induced timing shifts in dispersion-managed soliton systems.

The frequency and timing shifts associated with dispersion-managed solitons in a wavelength-division multiplexed system are computed by the numerically efficient Poisson sum technique. Analytical formulas are attainable by use of this approach with a Gaussian approximation for the soliton. The results are favorably compared with known results for the frequency shift. The method also applies to quasi-linear return-to-zero transmission formats.