The main purpose of this paper, is to characterize new admissible classes of linear operator in terms of seven-parameter Mittag-Leffler function, and discuss sufficient conditions in order to achieve certain third-order differential subordination and superordination results. In addition, some linked sandwich theorems involving these classes had been obtained.  

In this study, a double frequency Q-switching Nd:YAG laser beam (1064 nm and λ= 532 nm, repetition rate 6 Hz and the pulse duration 10ns) have been used, to deposit TiO2 pure and nanocomposites thin films with noble metal (Ag) at various concentration ratios of (0, 10, 20, 30, 40 and 50 wt.%) on glass and p-Si wafer (111) substrates using Pulse Laser Deposition (PLD) technique. Many growth parameters have been considered to specify the optimum condition, namely substrate temperature (300˚C), oxygen pressure (2.8×10-4 mbar), laser energy (700) mJ and the number of laser shots was 400 pulses with thickness of about 170 nm. The surface morphology of the thin films has been studied by using atomic force microscopes (AFM). The Root Mean Sq

Light isotopes, especially closed shell nuclei, have significance in thermonuclear reactions of the Carbon-Nitrogen-Oxygen (CNO) cycle in stars. In this research, 12C(p, γ) 13N and 14N(p, γ) 15O reactions have been calculated by means of Matlab codes to find the reaction rate across a temperature range of 0.006 to 10 GK using non-resonant parts, as well as the astrophysical S- factor S(E) at low energies. It was concluded that the high binding energy of 12C and 14N nuclei make the reaction less probable thus enabling other competitive processes to develop, which enhances the probability of other competitive proton reactions in the CNO cycle.

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

Sphingolipids (SLs) are major structural constituents of eukaryotes, including the kinetoplastid parasite Leishmania. SLs are important for cellular trafficking and signaling and participate in different cell functions, such as, differentiation and cell death (apoptosis). In this study we have investigated the viability of Leishmania major wild type (W.T) and L. major knockout LmLCB2, one of two subunits of serine palmitoyl transferase (SPT) after treatment with myriocin (potent inhibitor of SPT) in order to detect the survival and proliferation of the parasites in vitro. This is to focus on the de novo sphingolipids biosynthesis pathway in both Leishmania wild type which can synthesize SPT and knockout Leishmania which genetically ablated

A new modified differential evolution algorithm DE-BEA, is proposed to improve the reliability of the standard DE/current-to-rand/1/bin by implementing a new mutation scheme inspired by the bacterial evolutionary algorithm (BEA). The crossover and the selection schemes of the DE method are also modified to fit the new DE-BEA mechanism. The new scheme diversifies the population by applying to all the individuals a segment based scheme that generates multiple copies (clones) from each individual one-by-one and applies the BEA segment-wise mechanism. These new steps are embedded in the DE/current-to-rand/bin scheme. The performance of the new algorithm has been compared with several DE variants over eighteen benchmark functions including sever

     This paper describes the application of consensus optimization for Wireless Sensor Network (WSN) system. Consensus algorithm is usually conducted within a certain number of iterations for a given graph topology. Nevertheless, the best Number of Iterations (NOI) to reach consensus is varied in accordance with any change in number of nodes or other parameters of . graph topology. As a result, a time consuming trial and error procedure will necessary be applied
to obtain best NOI. The implementation of an intellig ent optimization can effectively help to get the optimal NOI. The performance of the consensus algorithm has considerably been improved by the inclusion of Particle Swarm Optimization (PSO). As a case s

In recent years, the migration of the computational workload to computational clouds has attracted intruders to target and exploit cloud networks internally and externally. The investigation of such hazardous network attacks in the cloud network requires comprehensive network forensics methods (NFM) to identify the source of the attack. However, cloud computing lacks NFM to identify the network attacks that affect various cloud resources by disseminating through cloud networks. In this paper, the study is motivated by the need to find the applicability of current (C-NFMs) for cloud networks of the cloud computing. The applicability is evaluated based on strengths, weaknesses, opportunities, and threats (SWOT) to outlook the cloud network. T

In this research, deposition of titanium oxide (TiO₂) and vanadium oxide (V₂O₅) thin film  in different mixing percentage  (0, 25 ,50, 75 and100)%   on the substrate of glass .The coating thickness was ( 50 nm  ).

In this research contact angle was measured and the effect of weather conditions. Results showed that the value of the contact angle of the prepared films reached its highest value at 50% (TiO₂+V₂O₅) was 160º.

The results showed that the optical transmittance of TiO₂ and V₂O₅ thin film decrease with increasing the deposition angle and decrease with increasing V₂O₅ pro

Polyacetal was synthesized from the reaction of PVA with para-methyoxy benzaldehyde. Polymer metal complexwas prepared by reaction with Cu, polymer blend with Chitosan was prepared through the technique of solution casting method.All prepared compounds have been characterized through FT-IR, DSC, SEM as well as the Biological activity. The FT-IR results indicated the formation of polyacetal. The DSC results indicated the thermal stability regarding prepared polymer, polymermetal complex and Chitosan polymer blends. Antibacterial potential related to synthesized polyacetal, its metal complex andChitosan blend against four types of bacteria namely, Staphylococcus aureas, Psedomonas aeruginosa, Bacillus subtilis, Escherichia coli was examined a