The nuclear matter density distributions, elastic electron scattering charge formfactors and root-mean square (rms) proton, charge, neutron and matter radii arestudied for neutron-rich 6,8He and 19C nuclei and proton-rich 8B and 17Ne nuclei. Thelocal scale transformation (LST) are used to improve the performance radial wavefunction of harmonic-oscillator wave function in order to generate the long tailbehavior appeared in matter density distribution at high . A good agreement resultsare obtained for aforementioned quantities in the used model.

Background: There are so many evidences that there was antimicrobial resistance, and there were many strains that emerged which were difficult to treat. We are living in a situation that the dissemination of multiple drug resistant bacteria can lead us to the situation, in which no treatment could be offered for bacterial infection in future.

Aim of study: Assessment of nurses’ knowledge, attitude, and practices on antibiotic use and resistance in Fatima Al Zahra hospital in Baghdad.

Subjects and Methods:  A cross-sectional study. The study was carried on from 1st of February to 31st of March 2021.  A questionnaire was constructed by the research team based on literature review and was adapted to asses

Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia

The determination hardness in water raised to rivers caused several problem in the validity of the water used depends on where determination ions concentration calcium and magnesium in salts carbonate and sulfate , this possibility of separation between of these ions and the resulting impact on concentration and determination the degree of hardness water and appreciation between the insolvent water quality . It study the effect of the impact of concentration magnesium ion in determination the quality of the water has turned out to be Mg concentration more than 60% of the total content of hardness is borderline in hardness effect the determination. Adopted in this research determination the ions in two method titration by EDTA solution and

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an