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Synthesis of Mn-Co-Ni Composite Electrode by Anodic and Cathodic Electrodeposition for Indirect Electro-oxidation of Phenol – Optimization of the Removal by Response Surface Methodology
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In the present work, Response Surface Methodology (RSM) was utilized to optimize process variables and find the best circumstances for indirect electrochemical oxidation of mimicked wastewater to remove phenol contaminants using prepared ternary composite electrode. The electrodeposition process is used for the synthesis of a ternary composite electrode of Mn, Co, and Ni oxides. The selected concentrations of metal salts of these elements were 0.05, 0.1, and 1.5 M, with constant molar ratio, current density, and electrolysis time of 1:1:1, 25 mA/cm2, and 2 h. Interestedly, the gathered Mn-Co-Ni oxides were deposited at both the anode and cathode. X-ray diffraction (XRD) and scanning electron microscopy (SEM) facilitated the qualitative characterization of surface structure and morphology of the accumulated oxides. The energy dispersive X-ray (EDX) provided a semi-quantitative analysis of deposit composition. The atomic force microscopy (AFM) apparatus quantified the roughness. We examined the efficiency of composite electrodes in coinciding with the removal of Chemical Oxygen Demand (COD) under current densities of 40, 60, and 80 mA/cm2, pH values of 3, 4, and 5, and NaCl concentrations of 1, 1.5, 2 g/l. RSM covered the optimization of process parameters in conjunction with Central Composite Design (CCD). The COD represented the response function in the optimization procedure. The optimal current density, NaCl concentration, and pH magnitude were 80 mA/cm2, 1.717 g/l, and 3, respectively. The efficiency of COD elimination of 99.925% attained after 1 hour of indirect electrochemical oxidation with an energy consumption of 152.380 kWh per kilogram of COD. The COD elimination model is significant based on the correlation coefficient (R2) and F-values, and the experimental data fitted well to a second-order polynomial model with R2 of 98.93%.

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Publication Date
Wed May 31 2023
Journal Name
Iraqi Geological Journal
Studying the Effect of Permeability Prediction on Reservoir History Matching by Using Artificial Intelligence and Flow Zone Indicator Methods
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The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme

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Publication Date
Wed Jul 15 2020
Journal Name
Modern Physics Letters A
Nuclear matter distributions of neutron rich 6He, 11Li, 14Be and 17B halo nuclei studied by the Bear Hodgson potential
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The radial wave functions of the Bear–Hodgson potential have been used to study the ground state features such as the proton, neutron and matter densities and the as- sociated rms radii of two neutrons halo 6He, 11Li, 14Be and 17B nuclei. These halo nuclei are treated as a three-body system composed of core and outer two-neutron (Core + n + n). The radial wave functions of the Bear–Hodgson potential are used to describe the core and halo density distributions. The interaction of core-neutron takes the Bear–Hodgson potential form. The outer two neutrons of 6He and 11Li interact by the realistic interaction REWIL whereas those of 14Be and 17B interact by the realistic interaction of HASP. The obtained results show that this model succee

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Publication Date
Mon May 01 2017
Journal Name
The Journal Of Immunology
Combination of cannabinoids, Δ9- tetrahydrocannabinol (THC) and cannabidiol (CBD), mitigate experimental autoimmune encephalomyelitis (EAE) by altering the gut microbiome.
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Abstract<p>Multiple Sclerosis (MS), is a common autoimmune disease that affects the central nervous system. Currently, there is no cure for MS, and most treatments involve the use of immunosuppressive drugs that can have adverse effects or increased toxicity. Cannabis, commonly known as marijuana, is a product of the Cannabis sativa, and for several centuries has been used as an alternative medicine in many cultures. Cannabis sativa produces over 421 chemical compounds, including about 80 terpenophenols named phytocannabinoids, and include both psychotropic THC and non-psychoactive CBD. In the currently study, we show that a combination therapy using THC and CBD results in amelioration of EAE, a</p> ... Show More
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Publication Date
Fri Dec 20 2024
Journal Name
Baghdad Science Journal
Interference with quorum sensing of Klebsiella pneumoniae by some plant extracts can affect the biofilm formation and antibiotic resistance.
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Quorum sensing (QS) is a perfectly orchestrated molecular communication system. It is a boon for Klebsiella pneumoniae, and bane for the host. This system is believed to make K. pneumoniae a leading cause of multidrug-resistant (MDR) nosocomial infections. This study aimed to investigate the antibacterial and anti-biofilm potential of medicinal plant extracts through interfering with QS of K. pneumoniae. The effect of different concentrations of ethanolic extracts of cinnamon and clove on K. pneumoniae was determined by analyzing the growth curve, survival assay (MTT), Qualitative and quantitative biofilm formation, antibiotic resistance, along with studying gene expression of the genes encoding the above traits, using quantitative real tim

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Publication Date
Sat May 01 2021
Journal Name
Pharmacological Research
Resveratrol-mediated attenuation of superantigen-driven acute respiratory distress syndrome is mediated by microbiota in the lungs and gut
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Publication Date
Fri May 16 2025
Journal Name
Tikrit Journal Of Engineering Sciences
Comparative Study of Activated Carbon and Silver Nanoparticle-Loaded Activated Carbon Derived from Tea Waste for Removal of Tetracycline from Aqueous Solution
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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

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Publication Date
Thu Aug 18 2022
Journal Name
Dental Hypotheses
Microleakage Evaluation of Glass Hybrid Restoration Following Usage of Papain-Based Gel and Ceramic Bur for Caries Removal: An in Vitro Study
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Publication Date
Mon Jan 13 2020
Journal Name
Day 3 Wed, January 15, 2020
Numerical Simulation of Gas Lift Optimization Using Genetic Algorithm for a Middle East Oil Field: Feasibility Study
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<p>Gas-lift technique plays an important role in sustaining oil production, especially from a mature field when the reservoirs’ natural energy becomes insufficient. However, optimally allocation of the gas injection rate in a large field through its gas-lift network system towards maximization of oil production rate is a challenging task. The conventional gas-lift optimization problems may become inefficient and incapable of modelling the gas-lift optimization in a large network system with problems associated with multi-objective, multi-constrained, and limited gas injection rate. The key objective of this study is to assess the feasibility of utilizing the Genetic Algorithm (GA) technique to optimize t</p> ... Show More
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Publication Date
Tue Dec 31 2013
Journal Name
Al-khwarizmi Engineering Journal
Design of an Adaptive PID Neural Controller for Continuous Stirred Tank Reactor based on Particle Swarm Optimization
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 A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.

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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Global Pharma Technology
Using tobacco leaves as adsorbent for the orange-g dye removal from its aqueous solutions
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The removal of commercial orange G dye from its aqueous solution by adsorption on tobacco leaves (TL) was studied in respect to different factor that affected the adsorption process. These factors including the tobacco leaves does, period of orange G adsorption, pH, and initial orange G dye concentration .Different types of isotherm models were used to describe the orange G dye adsorption onto the tobacco leaves. The experimental results were compared using Langmuir, and frundlich adsorption isotherm, the constants for these two isotherm models was determined. The results fitted frundlich model with value of correlation coefficient equal to (0.981). The capacity of adsorption for the orange G dye was carried out using various kinetic models

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