Within the framework of the shell model, the single-particle wave functions of Hartree-Fock approximation adopted with Skyrme interactions like kxtb, Skxs25, Sly4 and Bsk9 to get the thickness of the neutron skin, the mirror radii and the charges mirror radii for 18Ne-18O pair mirror nucleus. The wave functions were calculated using the NuShellX@MSU shell model code. The computed values of root-mean-square-radii are inuenced by the type of interaction employed. The symmetry energy and its slope at nuclear saturation density and the mirror energy displacement were also determined. Comparisons between theoretical and experimental data were made and it was concluded that the data are well described in of this pair mirror nucleus

Objective: The aims of present study to detect the effectiveness of instruction program of non-pharmacological guideline on blood pressure and laboratory test.

Methodology: A pre-experimental study was conducted in Al-Sader Teaching Hospital   from 8^th of September 2019 to 25^th of May 2020, in order to find out the effectiveness of instruction program concerning non-pharmacological guideline on controlling essential hypertension among patients. A non- probability (purposive sample) of 50 patients with essential hypertension is selected. Those patients are already diagnosed with Essential Hypertension

The purpose of this study was to evaluate the epidemiological characteristics of the mandibular fractures relating to gender, age, the etiology of injury, and the rendered treatment modalities and complications. The data of the patients who sustained mandibular fractures were retrieved and were analyzed retrospectively, and based on these data a descriptive analysis was conducted. A total of 112 patients were included in this study; the most common cause was road traffic accidents (RTAs) followed by assaults and missile injuries. The most frequently involved age group was 11 to 20 years, treatment modalities included conservative, closed reduction and indirect fixation, and open reduction and internal fixation (ORIF) in 11.6, 79.5, and 8.9%

One of the concerns of adopting an e-voting systems in the pooling place of any critical elections is the possibility of compromising the voting machine by a malicious piece of code, which could change the votes cast systematically. To address this issue, different techniques have been proposed such as the use of vote verification techniques and the anonymous ballot techniques, e.g., Code Voting. Verifiability may help to detect such attack, while the Code Voting assists to reduce the possibility of attack occurrence. In this paper, a new code voting technique is proposed, implemented and tested, with the aid of an open source voting. The anonymous ballot improved accordingly the paper audit trail used in this machine. The developed system,

Predicting peterophysical parameters and doing accurate geological modeling which are an active research area in petroleum industry cannot be done accurately unless the reservoir formations are classified into sub-groups. Also, getting core samples from all wells and characterize them by geologists are very expensive way; therefore, we used the Electro-Facies characterization which is a simple and cost-effective approach to classify one of Iraqi heterogeneous carbonate reservoirs using commonly available well logs.

The main goal of this work is to identify the optimum E-Facies units based on principal components analysis (PCA) and model based cluster analysis(MC

Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed