Objective: To assess knowledge of pregnant women concerning prenatal care who attend primary health care
center in Baghdad city.
Methodology: A descriptive analytic study carried on (100) pregnant women who attend primary health care
centers in Baghdad city (50) of them from Al- Sheik Omer primary health care center \Resafa sector .and 50 from
Belat Al-Shuhadaa/ Al Karch sector, during the period from April to November 2011. The data were collected
through interview and use questionnaire format. Validity and Reliability of the questionnaire were determined
through panel of experts and pilot study, data were analysed through the application of descriptive statistical
analysis and inferential statistical analysis.
R

In the present paper, chitosan Schiff base has been synthesized from chitosan’s reaction with the salicyldehyde. The AuNPs was manufacture by extract of onion peels as a reducing agent. The Au NPs that have been prepared were characterized through the UV-vis spectroscopy, XRD analyses and SEM microscopy. The polymer blends of the chitosan Schiff base / PVP has been prepared through using the approach of solution casting. Chitosan Schiff base / PVP Au nano-composites was prepared. Nano composites and polymer blends have been characterized by FTIR which confirm the formation of Schiff base by revealing a new band of absorption at 1651cm-1 as a result of the (C=N) imine group. SEM, DSC and TGA confirms the thermal stability of the pr

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

Abstract: Urinary Tract Infections (UTIs) are the most common bacterial infection in humans and a major cause of morbidity and they are the most common cause of hospital visits worldwide. Proper knowledge in identifying factors associated with urinary tract infection may allow the intervention to easily control of the disease in a timely manner. Therefore, the purpose of the study is determining the prevalence of UTI, diagnosis of causative bacterial agents and identifying the factors associated to the urinary tract infection among patients attending Medical City Hospital in Baghdad, Iraq. A total of 237, morning mid-stream urine samples were collected aseptically and the samples were diagnosed according to the standard methods. I

In this study, manganese dioxide (MnO₂) nanoparticles (NPs) were synthesized via the hydrothermal method and utilized for the adsorption of Janus green dye (JG) from aqueous solutions. The effects of MnO₂ NPs on kinetics and diffusion were also analyzed. The synthesized NPs were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), energy-dispersive X-ray analysis (EDX), and Fourier-transform infrared spectroscopy (FT-IR), with XRD confirming the nanoparticle size of 6.23 nm. The adsorption kinetics were investigated using three models: pseudo-first-order (PFO), pseudo-second-order (PSO), and the intraparticle diffusion model. The PSO model provided the best fit (R² = 0.999), indicating that the adsorpti

Background This study establishes a mathematically consistent and computational framework for the simultaneous identification of two time-dependent coefficients in a one-dimensional second-order parabolic partial differential equation. The considered problem is governed by nonlocal initial, boundary, and integral overdetermination conditions. Methods The direct problem is solved using the Crank-Nicolson finite difference method (FDM), which ensures unconditional stability and second-order accuracy in both spatial and temporal discretizations. The corresponding inverse problem is reformulated as a nonlinear regularized least-squares optimization problem and efficiently solved used the MATLAB subroutine