Background: Neonatal Septicemia (NNS) is generalized microbial symptomatic infection during the first 28 days of life.It>s the most serious complication in Neonatal Intensive Care Units (NICU) that demand urgent diagnosis and accurate treatment.Objective: To reveal the relationship of neonatal septicemia with birth weight (one of the neonatal risk factors).Patients and Methods: Blood sample was obtained from 76 neonates aged 1 hour-28 days who were diagnosed clinically (poor feeding, respiratory distress, fever, hypothermia, gastrointestinal and/or central nervous system symptoms)and bacteriologically to have neonatal septicemia.Results:One of the most important neonatal factor predisposing to infection is low birth weight, signi

4 Blood Res 2018;53:314-319. Received on August 11, 2018 Revised on August 30, 2018 Accepted on August 30, 2018 Background Iron overload is a risk factor affecting all patients with thalassemia intermedia (TI). We aimed to determine whether there is a relationship of serum ferritin (SF) and alanine ami- notransferase (ALT) with liver iron concentration (LIC) determined by R2 magnetic reso- nance imaging (R2-MRI), to estimate the most relevant degree of iron overload and best time to chelate in patients with TI. Methods In this cross-sectional study, 119 patients with TI (mean age years) were randomly se- lected and compared with 120 patients who had a diagnosis of thalassemia major (TM). Correlations of LIC, as determined by R2-MRI, with SF

The aim of this study was to critically appraise and synthesize the best available evidence on the effectiveness of interventions suitable for delivery by nurses, designed to enhance cardiac patients' adherence to their prescribed medications.

This paper studies a novel technique based on the use of two effective methods like modified Laplace- variational method (MLVIM) and a new Variational method (MVIM)to solve PDEs with variable coefficients. The current modification for the (MLVIM) is based on coupling of the Variational method (VIM) and Laplace- method (LT). In our proposal there is no need to calculate Lagrange multiplier. We applied Laplace method to the problem .Furthermore, the nonlinear terms for this problem is solved using homotopy method (HPM). Some examples are taken to compare results between two methods and to verify the reliability of our present methods.

In this Paper, we proposed two new predictor corrector methods for solving Kepler's equation in hyperbolic case using quadrature formula which plays an important and significant rule in the evaluation of the integrals. The two procedures are developed that, in two or three iterations, solve the hyperbolic orbit equation in a very efficient manner, and to an accuracy that proves to be always better than 10-15. The solution is examined with and with grid size , using the first guesses hyperbolic eccentric anomaly is and , where is the eccentricity and is the hyperbolic mean anomaly.

The aim of this paper is to propose a reliable iterative method for resolving many types of Volterra - Fredholm Integro - Differential Equations of the second kind with initial conditions. The series solutions of the problems under consideration are obtained by means of the iterative method. Four various problems are resolved with high accuracy to make evident the enforcement of the iterative method on such type of integro differential equations. Results were compared with the exact solution which exhibits that this technique was compatible with the right solutions, simple, effective and easy for solving such problems. To evaluate the results in an iterative process the MATLAB is used as a math program for the calculations.

In this paper Volterra Runge-Kutta methods which include: method of order two and four will be applied to general nonlinear Volterra integral equations of the second kind. Moreover we study the convergent of the algorithms of Volterra Runge-Kutta methods. Finally, programs for each method are written in MATLAB language and a comparison between the two types has been made depending on the least square errors.

Scheduling Timetables for courses in the big departments in the universities is a very hard problem and is often be solved by many previous works although results are partially optimal. This work implements the principle of an evolutionary algorithm by using genetic theories to solve the timetabling problem to get a random and full optimal timetable with the ability to generate a multi-solution timetable for each stage in the collage. The major idea is to generate course timetables automatically while discovering the area of constraints to get an optimal and flexible schedule with no redundancy through the change of a viable course timetable. The main contribution in this work is indicated by increasing the flexibility of generating opti