Emerging Anisotropic Compact Stars in f(G,T)f(\mathcal{G},T) Gravity

The possible emergence of compact stars has been investigated in the recently introduced modified Gauss-Bonnet $f(\mathcal{G},T)$ gravity, where $\mathcal{G}$ is the Gauss-Bonnet term and ${T}$ is the trace of the energy-momentum tensor. Specifically, for this modified $f(\mathcal{G}, T)$ theory, the analytic solutions of Krori and Barua have been applied to anisotropic matter distribution. To determine the unknown constants appearing in Krori and Barua metric, the well-known three models of the compact stars namely 4U1820-30, Her X-I, and SAX J 1808.4-3658 have been used. The analysis of the physical behavior of the compact stars has been presented and the physical features like energy density and pressure, energy conditions, static equilibrium, stability, measure of anisotropy, and regularity of the compact stars, have been discussed.Comment: 27 pages, 43 figures, 1 table, minor change

Prevention of arthritis by interleukin 10-producing B cells

In this study we have shown that activation of arthritogenic splenocytes with antigen and agonistic anti-CD40 gives raise to a B cell population that produce high levels of interleukin (IL)-10 and low levels of interferon (IFN)-{gamma}. Transfer of these B cells into DBA/1-TcR-ß-Tg mice, immunized with bovine collagen (CII) emulsified in complete Freund's adjuvant inhibited T helper type 1 differentiation, prevented arthritis development, and was also effective in ameliorating established disease. IL-10 is essential for the regulatory function of this subset of B cells, as the B cells population isolated from IL-10 knockout mice failed to mediate this protective function. Furthermore, B cells isolated from arthritogenic splenocytes treated in vitro with anti–IL-10/anti–IL-10R were unable to protect recipient mice from developing arthritis. Our results suggest a new role of a subset of B cells in controlling T cell differentiation and autoimmune disorders

Signal Detection for QPSK Based Cognitive Radio Systems using Support Vector Machines

Cognitive radio based network enables opportunistic dynamic spectrum access by sensing, adopting and utilizing the unused portion of licensed spectrum bands. Cognitive radio is intelligent enough to adapt the communication parameters of the unused licensed spectrum. Spectrum sensing is one of the most important tasks of the cognitive radio cycle. In this paper, the auto-correlation function kernel based Support Vector Machine (SVM) classifier along with Welch's Periodogram detector is successfully implemented for the detection of four QPSK (Quadrature Phase Shift Keying) based signals propagating through an AWGN (Additive White Gaussian Noise) channel. It is shown that the combination of statistical signal processing and machine learning concepts improve the spectrum sensing process and spectrum sensing is possible even at low Signal to Noise Ratio (SNR) values up to -50 dB

A space-time pseudospectral discretization method for solving diffusion optimal control problems with two-sided fractional derivatives

We propose a direct numerical method for the solution of an optimal control problem governed by a two-side space-fractional diffusion equation. The presented method contains two main steps. In the first step, the space variable is discretized by using the Jacobi-Gauss pseudospectral discretization and, in this way, the original problem is transformed into a classical integer-order optimal control problem. The main challenge, which we faced in this step, is to derive the left and right fractional differentiation matrices. In this respect, novel techniques for derivation of these matrices are presented. In the second step, the Legendre-Gauss-Radau pseudospectral method is employed. With these two steps, the original problem is converted into a convex quadratic optimization problem, which can be solved efficiently by available methods. Our approach can be easily implemented and extended to cover fractional optimal control problems with state constraints. Five test examples are provided to demonstrate the efficiency and validity of the presented method. The results show that our method reaches the solutions with good accuracy and a low CPU time.Comment: This is a preprint of a paper whose final and definite form is with 'Journal of Vibration and Control', available from [http://journals.sagepub.com/home/jvc]. Submitted 02-June-2018; Revised 03-Sept-2018; Accepted 12-Oct-201

Finite AG-groupoid with left identity and left zero

A groupoid G whose elements satisfy the left invertive law: (ab)c=(cb)a is known as Abel-Grassman's groupoid (AG-groupoid). It is a nonassociative algebraic structure midway between a groupoid and a commutative semigroup. In this note, we show that if G is a finite AG-groupoid with a left zero then, under certain conditions, G without the left zero element is a commutative group

The role of endoproteolytic processing in neurodegeneration

Endoproteolysis is a normal post-translational process in the eukaryotic cell that had played a role early on in protein evolution allowing protein catabolism and the generation of amino acids. Endoproteolytic cleavage regulates many crucial cellular processes including the activity of many proteins, their protein-protein interactions and the amplification of cell signals. Not surprisingly, disruption or alternation of endoproteolytic cleavage maybe the root cause of many human diseases such as Alzheimer’s disease, Huntington’s disease and prion diseases. Most neurodegenerative diseases (ND) are caused by the build-up of misfolded proteins and the promotion of aggregation events. A common event that occurs in these ND is the alteration of endoproteolytic cleavage due to genetic mutations of the associated-proteases or in the target substrate. Endoproteolytic cleavage resulting in protein truncation has significant effects on the structure and function of a protein representing a common feature of ND. In this review, we will discuss the endoproteolytic cleavage events that lead to ND, namely Alzheimer’s disease, Huntington’s disease and prion diseases