Mass transfer correlations for iron rotating cylinder electrode in chloride/sulphate solution, under isothermal and
controlled heat transfer conditions, were derived. Limiting current density values for the oxygen reduction reaction from
potentiostatic experiments at different bulk temperatures and various turbulent flow rates, under isothermal and heat
transfer conditions, were used for such derivation. The corelations were analogous to that obtained by Eisenberg et all
and other workers.

The present study aims to establish an empirical correlation between biochemical oxygen demand (BOD5) and chemical oxygen demand (COD) of the sewage flowing in Al-Diwaniyah wastewater treatment plant. The strength of the wastewater entering the plant varied from medium to high. High concentrations of BOD5 and COD in the effluent were obtained due to the poor performance of the plant. This was observed from the BOD5 /COD ratios that did not confirm with the typical ratios for the treated sewage. Regression equations for BOD5 and COD removal percentages were suggested which can be used to evaluate rapid effluent assessment after the treatment processes or optimal process control to improve the performance of wastewater treatment plants.

The performance of sewage pumps stations affected by many factors through its work time which produce undesired transportation efficiency. This paper is focus on the use of artificial neural network and multiple linear regression (MLR) models for prediction the major sewage pump station in Baghdad city. The data used in this work were obtained from Al-Habibia sewage pump station during specified records- three years in Al-Karkh district, Baghdad. Pumping capability of the stations was recognized by considering the influent input importance of discharge, total suspended solids (TSS) and biological oxygen demand (BOD).  In addition, the chemical oxygen demands (COD), pH and chloride (Cl). The proposed model performanc

The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be

The formation of a Schiff-base with N2O2 donor atoms derived from the hydrazine segment and its metal complexes are reported. The Schiff-base ligand; N’-((1R,2S,4R,5S,Z)-2,4-diphenyl-3-azabicyclo[3.3.1]nonan-9-ylidene)furan-2-carbohydrazide (HL) was prepared from the reaction of furan-2-carbohydrazide with (1R, 2R, 4R, 5S)-2,4-diphenyl-3-azabicyclo[3.3.1]nonan-9-one (M1) in ethanol medium. The reaction of the title ligand with selected metal ions Cr(III), Mn(II), Ni(II), Cu(II), Zn(II) and Cd(II) gave complexes with the general formula [M(L)Cl2], (where: M = Cr(III), Mn(II), Ni(II), Cu(II), Zn(II) and Cd(II)). Spectroscopic analyses Fourier transform infrared (FT-IR), Nuclear Magnetic Resonance (NMR) Carbon-13 nuclear magnetic res

In order for the process of removing pollutants, including dyes, from the aquatic environment to be effective, plant wastes such as banana peels were used as adsorbent surfaces by thermally activating them (ABP) and modifying them with iron oxide nanoparticles (MABP), which were characterized using Fourier transform infrared (FT-IR) and X-ray diffraction (XRD) techniques. They were applied in the field of Janus green (JG) dye adsorption for the batch system and studied the effect of several factors (adsorbent weight, contact time, initial concentration, and temperature). Their data were analyzed kinetically using first- and second-order kinetic models and they were found to follow the second order. Their data were also analyzed thro

Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

Silver/polyvinyl alcohol (Ag/PVA) nanocomposite films were synthesized via solution casting with varying concentrations of Ag nanoparticles (1–5 wt%). A comprehensive investigation was conducted to understand the influence of Ag content on the structural, optical, mechanical, thermal, electrical, and antibacterial properties of the composites. UV-Vis spectroscopy revealed a red shift in absorption peaks and a reduction in the optical band gap, which decreased from 3.78 eV for pure PVA to 3.37 eV for the 5 wt% Ag composite. FTIR and SEM analyses confirmed successful nanoparticle incorporation and morphological changes. The nanocomposites exhibited enhanced tensile strength, elongation at break, Young’s modulus, and hardness due t