The study evaluated endophytic communities associated with five oil-bearing plants, including sesame, corn, sunflower, olives and castor, which were collected from Baghdad and Diyala (Iraq), evaluated their oil production capacity and identified metabolites from the lipid fraction. Out of 151 isolates were collected from 21 taxa. Aspergillus niger showed the highest frequency (6.62 %), while the genera Aspergillus and Fusarium were the most dominant endophytes. The highest oil yield was identified and recorded in Aspergillus terreus (24.12 %). While the lowest oil yield was observed in Sclerotinia spp. (3.96 %). Gas chromatography-mass spectrometry (GC-MS) analysis of A. terreus revealed a profile dominated by pentadecyl acrylate (2

The research examines the mechanism of application of )ISO 21001: 2018( in the Energy Branch- Electromechanical Engineering at the University of Technology to achieve the quality of the educational service to prepare the branch to obtain the certificate of conformity with the requirements of) ISO 21001: 2018(, the necessary data were collected Depending on the (CHEKLIST) of (ISO 21001: 2018), field interviews and records of the concerned department, The researchers reached a number of results, the most prominent of which was the adoption of high quality leadership leaders and their willingness to implement the standard requirements, The university has a basic structure that qualifies it to implement the international standard, as

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

The behavior corrosion inhibition of aluminum alloy (Al6061) in acidic (0.1 M HCl) and saline (3.5% NaCl) solutions was investigated in the absence and the presence of expired diclofenac sodium drug (DSD) as a corrosion inhibitor. The influence of temperature and was studied using electrochemical techniques. In addition, scanning electron microscopy (SEM) was used to study the surface morphology. The results showed that DSD acted as a powerful inhibitor in acidic solutions, while a moderate influence was observed with saline one. Maximum inhibition efficiency was 99.99 and 83.32% in acidic and saline solutions at 150 ppm of DSD, respectively. Corrosion current density that obtained using electrochemical technique was increased with temperat