Combining genetic algorithm and Sinc-Galerkin method for solving an inverse diffusion problem

A numerical approach combining the use of a genetic algorithm with the solution of the Sinc-Galerkin method is proposed for the determination of an unknown time-dependent diffusivity a(t) in an inverse diffusion problem (IDP). At the beginning of the numerical algorithm, Sinc-Galerkin method is employed to solve the direct diffusion problem. The present approach is to rearrange the matrix forms of the governing equations. Then, the genetic algorithm is adopted to find the solution of IDP. The genetic algorithm used in this work is not a classical genetic algorithm. Instead, the application of the genetic algorithm to this discrete-time optimal control problem is called a real-valued genetic algorithm(RVGA). Some numerical experiments confirm the utility of this algorithm as the results are in good agreement with the exact data. Results Show that a reasonable estimation can be obtained by combining the genetic algorithm and Sinc-Galerkin method within a CPU with clock speed 2.7 GHz.Publisher's Versio

deepFDEnet: A Novel Neural Network Architecture for Solving Fractional Differential Equations

The primary goal of this research is to propose a novel architecture for a deep neural network that can solve fractional differential equations accurately. A Gaussian integration rule and a $L_1$ discretization technique are used in the proposed design. In each equation, a deep neural network is used to approximate the unknown function. Three forms of fractional differential equations have been examined to highlight the method's versatility: a fractional ordinary differential equation, a fractional order integrodifferential equation, and a fractional order partial differential equation. The results show that the proposed architecture solves different forms of fractional differential equations with excellent precision

Cloning and expression of the V-domain of the CD166 in prokaryotic host cell

Purpose: CD166/ALCAM (Activated leukocyte cell adhesion molecule) as an immunoglobulin is implicated in cell migration. It is also involved in tumorigenesis of CRC (colorectal cancer) and known as a cancer stem cell marker. CD166, as a membrane protein, potentially represents either diagnostic or therapeutic capacities for CRC.Methods: In this study, the sequence of V domain was optimized for expression in prokaryotic host using online tools and cloned into pET-28a plasmid. The recombinant pET28a was transformed into the E. coli BL21DE3 using heat shock method and expression of recombinant V domain was examined using SDS-PAGE (sodium dodecyl sulfate polyacrylamide gel electrophoresis).Results: The results confirmed protein expression of recombinant 22.77 kDa V domains in bacterial expression system.Conclusion: V domain of the CD166 was expressed successfully in E. coli bacteria. This recombinant fragment can be introduced as a suitable diagnostic and therapeutic candidate for screening and cancer-therapy of CRC patients, respectively.

An innovative method for text steganography in images with gif format

In this paper, an innovative method based on odd or even the values of the elements of image matrix with GIF format is suggested for the text cryptography. The results of the implementation of this method for steganography text on an image in GIF format, which shows the efficiency and suitability of this metho