Multimodal magnetic resonance imaging for Alzheimer's disease diagnosis using hybrid features extraction and ensemble support vector machines

Magnetic resonance imaging (MRI) is increasingly used in the diagnosis of Alzheimer's disease (AD) in order to identify abnormalities in the brain. Indeed, cortical atrophy, a powerful biomarker for AD, can be detected using structural MRI (sMRI), but it cannot detect impairment in the integrity of the white matter (WM) preceding cortical atrophy. The early detection of these changes is made possible by the novel MRI modality known as diffusion tensor imaging (DTI). In this study, we integrate DTI and sMRI as complementary imaging modalities for the early detection of AD in order to create an effective computer-assisted diagnosis tool. The fused Bag-of-Features (BoF) with Speeded-Up Robust Features (SURF) and modified AlexNet convolutional neural network (CNN) are utilized to extract local and deep features. This is applied to DTI scalar metrics (fractional anisotropy and diffusivity metric) and segmented gray matter images from T1-weighted MRI images. Then, the classification of local unimodal and deep multimodal features is first performed using support vector machine (SVM) classifiers. Then, the majority voting technique is adopted to predict the final decision from the ensemble SVMs. The study is directed toward the classification of AD versus mild cognitive impairment (MCI) versus cognitively normal (CN) subjects. Our proposed method achieved an accuracy of 98.42% and demonstrated the robustness of multimodality imaging fusion.     

Identification of microstructural mechanisms during densification of a TiAl alloy by spark plasma sintering

This work aims at identifying, by coupled scanning and transmission electron microscopy (SEM and TEM) observations, the densification mechanisms occurring when an atomized Ti-47Al-1W-1Re-0.2Si powder is densified by spark plasma sintering (SPS). For this purpose, interruptions of the SPS cycle have been performed to follow the evolution of the microstructure step by step. The powder particles exhibit a classical dendritic microstructure containing a large amount of out-of-equilibrium α phase. During heating-up, the microstructure undergoes successive transformations. At T = 525-875 °C the α phase transforms into γ. The γ phase formed is supersaturated in W and Re. It de-saturates for T above 875 °C by discontinuous precipitation of W and Re-rich B2 phase. Densification takes place for T between 900 °C and 1150 °C by plastic deformation of the powder particles. TEM observations show that the repartition of the plastic deformation is correlated to the dendritic microstructure, and that dynamic recrystallization mechanisms occur. Microstructural phenomena directly resulting from the high currents involved in the SPS process have not been observed.     

Exact analytic solitary wave solutions for the RKL model

Interest in finding exact solitary wave solutions of nonlinear evolution equations by means of different methods has grown steadily in recent years. These exact solutions are important to understand the mechanism of the complicated nonlinear physical phenomena. By use of the Jacobi elliptic function method, we find the exact analytic solitary wave solutions for the RKL model with cubic-quintic non-Kerr terms, describing the propagation of extremely short pulses in optical fibers. These new solutions may be useful for describing the propagation of optical pulses in non-Kerr media.     

Assessment of Algerian sorghum protein quality [Sorghum bicolor (L.) Moench] using amino acid analysis and in vitro pepsin digestibility

To assess the protein quality and the nutritive value of seven Algerian local sorghum cultivars, the in vitro pepsin digestibility was determined, which ranged from 25.0% to 65.0%, and the amino acid composition of each cultivar was compared with other sorghum cultivars. In addition, the amino acid scores (AAS) and the protein digestibility-corrected amino acid scores (PDCAAS) were calculated. Relative to the WHO protein standard, most of the sorghum cultivars tested, scored very high AAS, with values ranging between 0.9 and 2.6 except for lysine, methionine and cysteine. The PDCAAS were high for Ain Salah cultivars AS1 and AS3, however, all other cultivars showed low values except for leucine. This study confirmed that in terms of both quantity and quality, sorghum proteins could serve as a source of essential amino acids and as a potential source of proteins in the future.     

Dynamics of self-similar sub-10-fs-pulses in an inhomogeneous highly nonlinear fibre amplifier

ABSTRACT

We study the propagation of ultrashort pulses of width around sub-10 femtosecond in an inhomogeneous highly nonlinear single-mode fibre within the framework of a generalized higher-order nonlinear Schrödinger equation with derivative non-Kerr nonlinear terms and spatially inhomogeneous coefficients. Additional effects to the cubic model include the distributed third-order dispersion, self-steepening, self-frequency shift due to stimulated Raman scattering, quintic nonKerr nonlinearity, derivative non-Kerr nonlinear terms, and gain or loss. The exact self-similar brightand dark-solitary-wave solutions of the governing equation are derived via a transformation connected with the constant-coefficient higher-order nonlinear Schrödinger equation with non-Kerr nonlinearity. The constraint relations among the optical fibre parameters for the existence of these self-similar structures are also discussed. Based on these exact solutions, we investigate the dynamical behaviours of self-similar localized pulses in a periodic distributed fibre system for different parameters.     

gef Gene Expression in MCF-7 Breast Cancer Cells is Associated with a Better Prognosis and Induction of Apoptosis by p53-Mediated Signaling Pathway

Breast cancer research has developed rapidly in the past few decades, leading to longer survival times for patients and opening up the possibility of developing curative treatments for advanced breast cancer. Our increasing knowledge of the biological pathways associated with the progression and development of breast cancer, alongside the failure of conventional treatments, has prompted us to explore gene therapy as an alternative therapeutic strategy. We previously reported that gef gene from E. coli has shown considerable cytotoxic effects in breast cancer cells. However, its action mechanism has not been elucidated. Indirect immunofluorescence technique using flow cytometry and immunocytochemical analysis were used to detect breast cancer markers: estrogen (ER) and progesterone (PR) hormonal receptors, human epidermal growth factor receptor-2 proto-oncogene (c-erbB-2), ki-67 antigen and p53 protein. gef gene induces an increase in ER and PR expressions and a decrease in ki-67 and c-erbB-2 gene expressions, indicating a better prognosis and response to treatment and a longer disease-free interval and survival. It also increased p53 expression, suggesting that gef-induced apoptosis is regulated by a p53-mediated signaling pathway. These findings support the hypothesis that the gef gene offers a new approach to gene therapy in breast cancer.     

Frequency Stabilization for Multi-area Thermal–Hydro Power System Using Genetic Algorithm-optimized Fuzzy Logic Controller in Deregulated Environment

Abstract—This article develops a model of load frequency control for an interconnected two-area thermal–hydro power system under a deregulated environment. In this article, a fuzzy logic controller is optimized by a genetic algorithm in two steps. The first step of fuzzy logic controller optimization is for variable range optimization, and the second step is for the optimization of scaling and gain parameters. Further, the genetic algorithm-optimized fuzzy logic controller is compared against a conventional proportional-integral-derivative controller and a simple fuzzy logic controller. The proposed genetic algorithm-optimized fuzzy logic controller shows better dynamic response following a step-load change with combination of poolco and bilateral contracts in a deregulated environment. In this article, the effect of the governor dead band is also considered. In addition, performance of genetic algorithm-optimized fuzzy logic controller also has been examined for various step-load changes in different distribution unit demands and compared with the proportional-integral-derivative controller and simple fuzzy logic controller.     

Calculation of timing and amplitude jitter in a dispersion-managed Korteweg–de Vries system

Propagation of weakly nonlinear long waves in a periodically inhomogeneous medium is considered in the framework of the variable-coefficients Korteweg–de Vries equation. Explicit formulas with which to compute timing and amplitude jitter caused by nonlinear interactions between adjacent solitary waves in a random data sequence are obtained. The results show that the timing jitter depends on the quadratic growth of the propagation distance, whereas the amplitude jitter exhibits a simple linear dependence in the considered periodically varying dispersion-managed Korteweg–de Vries system. By contrast, both timing and amplitude jitter are found to be in the form of a linear growth to distance in a transmission system with strong periodic dispersion management.