Background: MRSA (methicillin-resistant Staphylococcus aureus) is a global health problem. Many people are looking for new ways to combat MRSA, for example by using bacteriophages (phages). It has been extremely challenging to isolate a sufficient quantity of lytic anti-MRSA phages. Therefore, new techniques for separating, refining, and reworking anti-MRSA phages were sought in this study.

Methods: Of 437 S. aureus isolates, nine clinical MRSA isolates were obtained from three hospitals in Baghdad, Iraq and two ATCC MRSA strains were used to separate wild anti-MRS

This research proposes the application of the dragonfly and fruit fly algorithms to enhance estimates generated by the Fama-MacBeth model and compares their performance in this context for the first time. To specifically improve the dragonfly algorithm's effectiveness, three parameter tuning approaches are investigated: manual parameter tuning (MPT), adaptive tuning by methodology (ATY), and a novel technique called adaptive tuning by performance (APT). Additionally, the study evaluates the estimation performance using kernel weighted regression (KWR) and explores how the dragonfly and fruit fly algorithms can be employed to enhance KWR. All methods are tested using data from the Iraq Stock Exchange, based on the Fama-French three-f

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a

In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe

In Computer-based applications, there is a need for simple, low-cost devices for user authentication. Biometric authentication methods namely keystroke dynamics are being increasingly used to strengthen the commonly knowledge based method (example a password) effectively and cheaply for many types of applications. Due to the semi-independent nature of the typing behavior it is difficult to masquerade, making it useful as a biometric. In this paper, C4.5 approach is used to classify user as authenticated user or impostor by combining unigraph features (namely Dwell time (DT) and flight time (FT)) and digraph features (namely Up-Up Time (UUT) and Down-Down Time (DDT)). The results show that DT enhances the performance of digraph features by i

This paper is dealing with non-polynomial spline functions "generalized spline" to find the approximate solution of linear Volterra integro-differential equations of the second kind and extension of this work to solve system of linear Volterra integro-differential equations. The performance of generalized spline functions are illustrated in test examples

Background: Cytology is one of the important diagnostic tests done on effusion fluid. It can detect malignant cells in up to 60% of malignant cases. The most important benign cell present in these effusions is the mesothelial cell. Mesothelial atypia can be striking andmay simulate metastatic carcinoma. Many clinical conditions may produce such a reactive atypical cells as in anemia,SLE, liver cirrhosis and many other conditions. Recently many studies showed the value of computerized image analysis in differentiating atypical cells from malignant adenocarcinoma cells in effusion smears. Other studies support the reliability of the quantitative analysisand morphometric features and proved that they are objective prognostic indices. Method