Aim This study is an overview of NPEV investigated during AFP surveillance programs for the period 2010–2017 in Iraq. Methods Stool samples from 4296 AFP cases and 2933 healthy contacts among children less than 15 years of age were processed for virus isolation as a part of AFP surveillance for the Global Polio Eradication Program in Iraq at National Polio Laboratory. NPEV detection was performed by virus isolation on cell culture according to WHO recommendations. Results The NPEV isolation rate was 14% of total AFP cases and 14.5% of healthy contacts. The infection rate was higher in males than females with a male/female ratio of 1.5: 1. The highest NPEV infection rate was observed among the children aged 1-2 years and decrease significa

In this paper, we will provide a proposed method to estimate missing values for the Explanatory variables for Non-Parametric Multiple Regression Model and compare it with the Imputation Arithmetic mean Method, The basis of the idea of this method was based on how to employ the causal relationship between the variables in finding an efficient estimate of the missing value, we rely on the use of the Kernel estimate by Nadaraya – Watson Estimator , and on Least Squared Cross Validation (LSCV) to estimate the Bandwidth, and we use the simulation study to compare between the two methods.

Thin films of CuPc of various thicknesses (150,300 and 450) nm have been deposited using pulsed laser deposition technique at room temperature. The study showed that the spectra of the optical absorption of the thin films of the CuPc  are two bands of absorption one in the visible region at about 635 nm, referred to as Q-band, and the second in ultra-violet region where B-band is located at 330 nm. CuPc thin films were found to have direct band gap with values around (1.81 and 3.14 (eV respectively. The vibrational studies were carried out using Fourier transform infrared spectroscopy (FT-IR). Finally, From open and closed aperture Z-scan data non-linear absorption coefficient and non-linear refractive index have been calculated res

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

Objectives: To evaluate the effect of non-pharmacological pain relief methods on duration of labor stage.Methodology: A quasi-experimental study design was conducted during the period of (4th July 2018 through 24th October 2018) on non-probability of (60) women (30) of them were a control group and (30) were the study group whom admitted to Al-Elwyia Maternity Teaching Hospital suffering from labor pain. A questionnaire was used as a tool of data collection Descriptive& Inferential statistical analyses were used to analyze the data.Result: The highest percentages of study and control groups were in age group (< 20) years old, primary schools graduates, housewife, from "urban area", within low category of socioeconomic scale,

Objectives: To evaluate the effect of non-pharmacological pain relief methods on duration of labor stage.
Methodology: A quasi-experimental study design was conducted during the period of (4th July 2018 through 24th October 2018) on non-probability of (60) women (30) of them were a control group and (30) were the study group whom admitted to Al-Elwyia Maternity Teaching Hospital suffering from labor pain. A questionnaire was used as a tool of data collection Descriptive& Inferential statistical analyses were used to analyze the data.
Result: The highest percentages of study and control groups were in age group (< 20) years old, primary schools graduates, housewife, from "urban area", within low category of socioeconomic scal

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