Objectives: The study aimed at the assessment of nurses' knowledge and practice concerning Cesarean Section.
Methodology: ٨ non-experimental approach was carried out throughout the present study with the application
of a descriptive design a for the study subject. The study was carried out at two maternity hospitals in Mosul
city namely Al-Barolo and AL Khansa Hospitals. ٨ purposively sample consist of (20) Nurse who are working
in operation theater. The questionnaire was used as a means of data collection; it comprised (3) major parts. Part
one presented the demographic data. Part two, consisted of items of Nurses’ knowledge about Cesarean Section.
While, part three consisted of items of Nurses’ practices about Cesarean Section. Content validity was
determined by presenting the items to a panel of experts. Reliability of the questionnaire was determined
through the use of test and re-test approach.
Results: It has been found that the mean age of the nurses was 35.85 ± 10.44 years, and 15% of them was less
than 26 years. Sixty percent of them were married. For the level of education of the nurses, 55% of them were
graduated from intermediate nursing schools. The mean duration of nursing work in hospitals was 17.95 ± 1 1.50
years, and about 20% of them have more than 30 years in nursing work. Additionally, about half of them have
not worked in obstetric and gynecology departments.
Recommendation: The researcher recommends that the Ministry of Health should conduct training courses for
the Nurses who have qualifications to teach how to deal with Cesarean Section and the Nurses who work in
maternity unit need clear policy, job description by Ministry of Health in the operation theater.
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The behaviour of certain dynamical nonlinear systems are described in term as chaos, i.e., systems' variables change with the time, displaying very sensitivity to initial conditions of chaotic dynamics. In this paper, we study archetype systems of ordinary differential equations in two-dimensional phase spaces of the Rössler model. A system displays continuous time chaos and is explained by three coupled nonlinear differential equations. We study its characteristics and determine the control parameters that lead to different behavior of the system output, periodic, quasi-periodic and chaos. The time series, attractor, Fast Fourier Transformation and bifurcation diagram for different values have been described.
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Green synthesis of silver nanoparticles (AgNPs) using different plant parts has shown a great potential in medicinal and industrial applications. In this study, AgNPs were in vitro green synthesized using A. graecorum, and its antifungal and antitumoractivities were investigated. Scanning electron microscopy (SEM) image result indicated spherical shape of AgNPs with a size range of 22-36 nm indicated by using Image J program. The functional groups indicated by Fourier-transform infrared spectroscopy (FTIR) represented the groups involved in the reduction of silver ion into nanoparticles. Alhagi graecorum AgNPs inhibited MCF-7 breast cancer cell line growth in increased concentration depend manner, significant differences shown at
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A theoretical study on corrosion inhibitors was done by quantum calculations includes semi-empirical PM3 and Density Functional Theory (DFT) methods based on B3LYP/6311++G (2d,2P). Benzimidazole derivative (oxo(4- ((phenylcarbamothioyl) carbamoyl)phenyl) ammonio) oxonium (4NBP) and thiourea derivative 2-((4- bromobenzyl)thio) -1H-benzo[d] imidazole (2SB) were used as corrosion inhibitors and an essential quantum chemical parameters correlated with inhibition efficiency, EHOMO (highest occupied molecular orbital energy) and ELUMO (lowest molecular orbital energy). Other parameters are also studied like energy gap [ΔE (HOMO-LUMO)], electron affinity (EA), hardness (Δ), dipole moment (μ), softness (S), ionization potential (IE), absolut
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Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty
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In this research, the degradation of Dazomet has been studied by using thermal Fenton process and photo-Fenton processes under UV and lights sun. The optimum values of amounts of the Fenton reagents have been determined (0.07g FeSO4 .7H2O, 3.5µl H2O2) at 25 °C and at pH 7 where the degradation percentages of Dazomet were recorded high. It has been found that solar photo Fenton process was more effective in degradation of Dazomet than photo-Fenton under UV-light and thermal Fenton processes, the percentage of degradation of Dazomet by photo-Fenton under sun light are 88% and 100% at 249 nm and 281 nm respectively, while the percentages of degradation for photo-Fenton under UV-light are 87%, 96% and for thermal Fenton are 70% and 66.8% at 2
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