The research included preparation of new Schiff base (L) by two steps: preparation of precursor [bis(2-formyl-6-methoxyphenyl) succinate] (P) by reacting (3-methoxy salicyl aldehyde) with (succinoyl dichloride) as first step then react the prepared precursor (P) with (ethanethioamide) to have the new Schiff base [bis(2-((ethane thioyl imino) methyl)-6-methoxy phenyl) succinate] (L) as second step. Characterized compounds based on Mass spectra, 1 H, 13CNMR (for ligand (L)), FT-IR and UV spectrum, melting point, molar conduct, %C, %H, and %N, the percentage of the metal in complexes %M, magnetic susceptibility, while study corrosion inhibition (mild steel) in acid solution by weight loss. These measurements proved that by (Oxygen, Nitrogen, a

A simple physical technique was used in this study to create stable and cost-effective copper oxide (CuO) nanoparticles from pure copper metal using the pulsed laser ablation technique. The synthesis of crystalline CuO nanoparticles was confirmed by various analytical techniques such as particle concentration measurement using atomic absorption spectrometry (AAS), field emission scanning electron microscopy (FE-SEM), the energy dispersive X-ray (EDX), and X-ray diffraction (XRD) to determine the crystal size and identify of the crystal structure of the prepared particles. The main characteristic diffraction peaks of the three samples were consistent. The corresponding 2θ is also consistent, and the cytotoxicity of the nanoparticles was

Karbala province regarded one part significant zones in Iraq and considered an economic resource of vegetation such as trees of fruits, sieve and other vegetation. This research aimed to utilize Normalized Difference Vegetation index (NDVI) and Subtracted (NDVI) for investigating the current vegetation cover at last four decay. The Normalized Difference Vegetation Index (NDVI) is the most extensively used satellite index of vegetation health and density. The primary goals of this research are gather a gathering of studied area (Karbala province) satellite images in sequence time for a similar region, these image captured by Landsat (TM 1985, TM 1995, ETM+ 2005 and Landsat 8 OLI (Operational Land Imager) 2015. Preprocessing such gap filli

Abstract:
Objective: To self-evaluate the effect of SBAR (Situation, Background, Assessment, and Recommendation) educational program on nurse and midwives practices in maternal health report documentation accuracy.
Methods: A quasi- experimental design was carried with the application of pre- post test for nurses and midwives’ knowledge and practices regarding SBAR communication tool. The study was held in Al-Elwia maternity teaching hospital, Al –Karckh maternity hospital and Al-Yarmouk teaching Hospital. purposive sample as it was convenient with inclusion criteria consisted of (84) nurse and midwives. The questionnaire comprised of demographic data, nurses- midwives practices of SBAR using (5) level Likert scale for assessme

Industrial development has recently increased, including that of plastic industries. Since plastic has a very long analytical life, it will cause environmental pollution, so studies have resorted to reusing recycled waste plastic (sustainable plastic) to produce environmentally friendly concrete (green concrete). In this research, producing environmentally friendly load-bearing concrete masonry units (blocks) was considered where five concrete mixtures were compressed at the blocks producing machine. The cement content reduced from 400 kg/m³ (B-400) to 300 kg/m³ (B-300) then to 200 kg/m³ (B-200). While (B-380) was produced using 380 kg/m³ cement and 20 kg/m³ nano-sil

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