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

Abstract

Research aims : The aim of the research is to evaluate the reality of the inspection teams' work in the health institutions belonging to Dhi-Qar health office .

Purpose: This research seeks to present a point of view based on knowing the extent of health service quality in Dhi-Qar governorate and discover the role of the inspection teams in enhancing the health service.

Design / Methodology/ Approach: The experimental method has been used and the questionnaire has also been used to collect data in order to develop a reliable and correct measurement model for the research's variables . The research's hypotheses have been tested through using some statistical treat

Scrophularia. striata from Scrophulariacea family has been used in Iranian folk medicine for the treatment of infectious diseases. In this study we evaluated the synergistic effect of S. striata   hydroalcoholic extract (SSE) and commercially available antibiotics against P. aeroginosa and Methicillin- resistant Staphylococcus aureus (MRSA). The resazurin-based microdilution method was used to determine the minimum inhibitory concentration (MIC) values of plan extract and standard antibiotics. The interaction between standard antibiotics and SSE was evaluated by using checkerboard method. The results of this study revealed that SSE enhance the antibacterial activity of antibiotics. The combin

Levofloxacin belongs to the fluoroquinolone family; it is a potent broad-spectrum bactericidal agent. The pharmacophore required for significant antibacterial activity is the C-3 carboxylic acid group and the 4-pyridine ring with the C-4 carbonyl group, into which binding to the DNA bases occur. In this work, we tried to show that by masking the carboxyl group through amide formation using certain amines to form levofloxacin carboxamides, an interesting activity is kept. Levofloxacin carboxamides on the C-3 group were prepared, followed by the formation of their copper complexes. The target compounds were characterized by FT-IR, elemental analysis. The antimicrobial activity of the target compounds was evaluated and showed satisfactory resu