In the petroleum industry, multiphase flow dynamics within the tubing string have gained significant attention due to associated challenges. Accurately predicting pressure drops and wellbore pressures is crucial for the effective modeling of vertical lift performance (VLP). This study focuses on predicting the multiphase flow behavior in four wells located in the Faihaa oil field in southern Iraq, utilizing PIPESIM software. The process of selecting the most appropriate multiphase correlation was performed by utilizing production test data to construct a comprehensive survey data catalog. Subsequently, the results were compared with the correlations available within the PIPESIM software. The outcomes reveal that the Hagedorn and Brown (H

Electrochemical Grinding (ECG) process is a mechanically assisted electrochemical process for material processing. The process is able to successfully machine electrically conducting harder materials at faster rate with improved surface finish and dimensional control. This research studies the effect of applied current, electrolyte concentration, spindle speed and the gap between workpiece and tool on hardness and material removal rate during electrochemical grinding for stainless steel 316. The characteristic features of the electrochemical grinding process are explored through Taguchi-design-based experimental studies. The better hardness can be obtained at 10 A of the current, 150 g/l of the electrolyte concentration, 0.3 mm of gap an

The current study investigated the stability and the extraction efficiency of emulsion liquid membrane (ELM) for Abamectin pesticide removal from aqueous solution. The stability was investigated in terms of droplet emulsion size distribution and emulsion breakage percent. The proposed ELM included a mixture of corn oil and kerosene (1:1) as a diluent, Span 80 (sorbitan monooleate) as a surfactant and hydrochloric acid (HCl) as a stripping agent without utilizing a carrier agent. Parameters such as homogenizer speed, surfactant concentration, emulsification time and internal to organic volume ratio (I/O) were evaluated. Results show that the lower droplet size of 0.9 µm and higher stable emulsion in terms of breakage percent of 1.12 % we

New complexes have been prepared from the new ligand [N1,N5-bis(3-hydroxyphenyl)-2- oxopentanediamide] derived from 2-Oxoglutaric acid and 3-aminophenol. Accordingly its binudear Mn(II),Co(II),Ni(II),Pd(II) and VO(II) complexes were prepared.. These compounds have been characterized by FT-IR, UV-Vis,Mass, 1H-NMR spectra, TGA curve, Chloride containing ,Molar conductance and atomic absorption. The characterization results gave binuclear complexes and pentadentate coordination and tetrahedral geometry for each Cobalt, Nickel, Manganese and Copper complexes otherwise Palladium complex gave a square planar geometry and Vanadium complex gave a square pyramidal geometry and the ligand is tetradentate. The biological activities for the new compoun

Cholesteryl ester transfer protein gene contains some single nucleotide polymorphisms, which have been associated with serum high-density lipoprotein concentration and other lipoproteins. This study is done for determining of cholesteryl ester transfer protein polymorphism and evaluate its effect on serum lipid profile concentrations in some hyperlipidemic patients compared with healthy subjects in Salah Al-din governorate-Iraq. Blood samples were taken from (90) patients suffering from hyperlipidemia, and (70) samples that were apparently healthy controls.  Serum lipid concentrations were measured by enzymatic assays. The polymorphism was genotyped using polymerase chain reaction restriction fragment length polymorphism analysis.&n

Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s