The fabrication of Solid and Hollow silver nanoparticles (Ag NPs) has been achieved and their characterization was performed using transmission electron microscopy (TEM), zeta potential, UV–VIS spectroscopy, and X-ray diffraction (XRD). A TEM image revealed a quasispherical form for both Solid and Hollow Ag NPs. The measurement of surface charge revealed that although Hollow Ag NPs have a zeta potential of -43 mV, Solid Ag NPs have a zeta potential of -33 mV. According to UV-VIS spectroscopy measurement Solid and Hollow Ag NPs both showed absorption peaks at wavelengths of 436 nm and 412 nm, respectively. XRD pattern demonstrates that the samples' crystal structure is cubic, similar to that of the bulk materials, with

Objective(s): current study aims to find the effect of electronic games on children's behavior, and find the
relationship between child demographic data and the effect of electronic games on the child's behavior.
Methodology: A descriptive-analytic study was conducted for assessing the Effect of electronic games on
children's behaviors that attending to teaching hospitals in Baghdad city during the period of (October/ 20th
/2017 to March/1st /2018). A (50) purposive (non- probabilistic) sample from: Child Protection teaching
Hospital, Child Central Hospital in AL-Iskan. The sample is selected according to the criteria: Children who
visited the consulting unit of children in the hospitals in the first visit, children in

 Researchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods were used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial intelligence, which is the method of artificial neural network (ANN) as it gives a high-precision estimate commensurate with the dat

Objectives: The aim of this study to assess instructional labor support behaviors among laboring
women in teaching hospitals in Hilla city.
Methodology: A descriptive analytic study was concluded to select a sample purposely of one hundred
multipara laboring women in maternity hospital in Hilla city and data was collected through
questionnaire form during February (1
st to March 30th) 2014. A descriptive statistical method was used
to analyze the data.
Results: The result showed that the highest percentage of study sample was at age (20-24) years, most
of them was house wife, more than third graduate from primary school, and more than half of them
lived in rural area, (86%) of study sample delivered normal deli

Research aims to know the impact beyond the defined in the collection. The research community is the second school students at Baghdad University and a research sample (63) students, the number of experimental group (27) students and a control group (30) students.  The researcher was rewarded in variable lifetime for students and educational attainment and educational level of the parents and the educational level of mothers. The researcher has developed a test took the number of paragraphs (20).  A test was true after it has been submitted to the Group of arbitrators. The test was consistent with test method used and the reliability coefficient (0, 88). Either the statistical methods used by the researcher are: Pearson correla

The aim of this paper is to derive a posteriori error estimates for semilinear parabolic interface problems. More specifically, optimal order a posteriori error analysis in the - norm for semidiscrete semilinear parabolic interface problems is derived by using elliptic reconstruction technique introduced by Makridakis and Nochetto in (2003). A key idea for this technique is the use of error estimators derived for elliptic interface problems to obtain parabolic estimators that are of optimal order in space and time.

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

Objective: The study aims to evaluate nurses' knowledge toward care of unconscious adult patients and identify the relationship between nurses’ knowledge toward care of unconscious adult patient and their demographic characteristics of age, gender, Marital Status, level of qualification and years of experience. Methodology: A descriptive study (quantitative design) was carried out by using quasi experimental design to study nurses' knowledge, attitudes and practices toward care of unconscious adult patients at teaching hospitals in Al-Hilla City from September 2018 up to June 2019. A purposively sample has been chosen in which included 60 nurses who work in ICUs within two hospitals (Imam Al-Sadiq teaching hospital and Al-Hilla general

Women with diabetes in pregnancy (type 1, type 2 and gestational) are at increased risk for adverse pregnancy outcomes which also include infant development of congenital heart disease and even fetal death. Adequate glycemic control before and during pregnancy is crucial to improve outcome