This research has tackled a scientific figure belongs to Koofi grammatical school. He is Abdullah Al-Tuaal who has occupied the fourth layer among the Koofi grammarians. There was a confusion between him and another Koofi grammarian from the same layer (Mohammed Bin Qaadim) in some old references. This research has clarified this confusion to affirm that they are two different grammarians.This research also tackles the scientific status of Al-Tuaal and the grammatical views that have been ascribed to him in addition to the analysis and discussion of these views. All this in the light of what has been mentioned in grammar books about the issues in which these views were stated.

In this investigation, metal matrix composites (MMC_s) were manufactured by using powder technology. Aluminum 6061 is reinforced with two different ceramics particles (SiC and B₄C) with different volume fractions as (3, 6, 9 and 12 wt. %). The most important applications of particulate reinforcement of aluminum matrix are: Pistons, Connecting rods etc. The specimens were prepared by using aluminum powder with 150 µm in particle size and SiC, B₄C powder with 200 µm in particle size. The chosen powders were mixed by using planetary mixing setup at 250 rpm for 4hr.with zinc stearate as an activator material in steel ball milling. After mixing process the powders were compacted by hydraulic

Accurate pore and fracture pressure detection is a major step in successful drilling operations design. The overestimation of these parameters absolutely leads to serious problems throughout and after well drilling. This study is concerned with the characterization and analysis of the most significant diagenetic processes that degrade or improve the reservoir characteristics of the Mauddud Formation in the Badra oil field. The primary goal of this research is to estimate the pore pressure and fracture pressure using well logging data by Techlog 2015 software in order to assess the impact on the estimation of the mud weight window (MWW). The estimated values of formation pressures are then analyzed according to different diagenetic p

Background: Multi- drug resistant (MDR) Staphylococcus aureus infections have become a major public health concern in both hospital and community settings.Objective: to investigate the antibacterial activity of T. Foenum- groecum essential oil against skin infection with S. aureus and to study probable synergistic activity in combination with Clindamycin.Type of the study: Cross-sectional study.

Methods: Antibacterial activity of T. Foenum- groecum essential oil extract (1.2gm/100 µl) was investigated in multi- drug resistance (MDR) Staphylococcus aureus specimen isolated from patients with skin infection in Baghdad. T. Foenum- groecum use externally for cellulites and skin inflammation due to the presence of diosgenin .fast liq

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 present work elucidates the utilization of activated carbon (AC) and activated carbon loaded with silver nanoparticles (AgNPs-AC) to remove tetracycline (TC) from synthetically polluted water. The activated carbon was prepared from tea residue and loaded with silver nanoparticles. Scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and Brunauer-Emmett-Teller (BET) were used to characterize the activated carbon (AC) and silver nanoparticles-loaded activated carbon (AgNPs-AC). The impact of various parameters on the adsorption effectiveness of TC was examined. These variables were the initial adsorbate concentration (Co), solution acidity (pH), adsorption time (t), and dosag