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bsj-2288
Bioadsorption of Heavy Metals From Industrial Wastewater Using Some Species of Bacteria
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Three isolated bacteria were examined to remove heavy metals from the industrial wastewater of the Diala State Company of Electrical Industries, Diyala-Iraq. The isolated bacteria were identified as Pseudomonas aeruginosa, Escherichia coli and Sulfate Reducing Bacteria (SRB). The three isolates were used as an adsorption factor for different concentrations of Lead and Copper (100, 150, and 200 ppm.), in order to examine the adsorption efficiency of these isolates. In addition, the effect of three factors on heavy metals adsorption were examined; temperature (25, 30, and 37 ?C), pH (3 and 4.5) and contact time (2 and 24 hrs). The results showed that the highest level of lead adsorption was obtained at 37 ?C by E. coli, P, aerugenosa and SRB with percentage of 95, 95.3 and 99.7 % respectively, whereas, E. coli, P. Aerugenosa and SRB gave a copper adsorption percentage of (40.63, 50.51 and 80.57%) respectively at 37 ?C. Moreover, E.coli showed different percentage of metal adsorption ranged from 6.4% to 95 % with lead concentration of 100 and 200 ppm at pH4.5 and for each of 2 and 24 hrs contact time, whereas, it exerts percentage of copper adsorption ranged from 3.5 % to 40.63 % at 100 and 200 ppm and pH value of 4.5 for similar contact time. P. aerugenosa was also shown to be involved in metal adsorption with percentage ranged from 1.39 % for lead concentration of 150 ppm to 97.9 % for 200ppm under pH of 3 and contact times of 2 and 24 hrs. Interestingly, SRB exhibits significant differences in metal absorption values ranged from 14.97 % for lead (100 ppm) to 99.32 % at 200 ppm with a pH value of 3 and contact times of 2 and 24 hrs and under different temperatures.

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Publication Date
Sun Mar 31 2019
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Behavior of Plain Concrete Beam Analyzed Using Extended Finite Element Method
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In this study, plain concrete simply supported beams subjected to two points loading were analyzed for the flexure. The numerical model of the beam was constructed in the meso-scale representation of concrete as a two phasic material (aggregate, and mortar). The fracture process of the concrete beams under loading was investigated in the laboratory as well as by the numerical models. The Extended Finite Element Method (XFEM) was employed for the treatment of the discontinuities that appeared during the fracture process in concrete. Finite element method with the feature standard/explicitlywas utilized for the numerical analysis. Aggregate particles were assumedof elliptic shape. Other properties such as grading and sizes of the aggr

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Publication Date
Fri Nov 13 2020
Journal Name
Mechanics Of Advanced Materials And Structures
Enhancing the strength of reinforced concrete columns using steel embedded tubes
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This paper demonstrates an experimental and numerical study on the behavior of reinforced concrete (RC) columns with longitudinal steel embedded tubes positioned at the center of the column cross-section. A total of 12 pin-ended square sectional columns of 150 × 150 mm having a total height of 1400 mm were investigated. The considered variables were the steel tube diameters of 29, 58, and 76 mm and the load eccentricity (0, 50, and 150) mm. Accordingly, these columns were divided into three groups (four columns in each group) depending on the load eccentricity (e) to column depth (h) ratio (e/h = 0, 1/3, and 1). For each group, one column was solid (reference), and the other three columns contained steel tubes with hollow rat

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Publication Date
Mon Jan 01 2024
Journal Name
Medical Journal Of Babylon
Characterization and antibacterial activity of biogenic iron nanoparticles using Proteus mirabilis
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Abstract<sec> <title>Background:

The green production of iron oxide nanoparticles (FeONPs) due to its numerous biotechnological uses has attracted a lot of attention and clean and eco-friendly approaches in the medical field.

Objectives:

The objectives of this study are to demonstrate the biogenic creation of FeONPs. The search for alternative antimicrobial medicines has been prompted by growing worries about multidrug resistance.

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Detection of Suicidal Ideation on Twitter using Machine Learning & Ensemble Approaches
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Suicidal ideation is one of the most severe mental health issues faced by people all over the world. There are various risk factors involved that can lead to suicide. The most common & critical risk factors among them are depression, anxiety, social isolation and hopelessness. Early detection of these risk factors can help in preventing or reducing the number of suicides. Online social networking platforms like Twitter, Redditt and Facebook are becoming a new way for the people to express themselves freely without worrying about social stigma. This paper presents a methodology and experimentation using social media as a tool to analyse the suicidal ideation in a better way, thus helping in preventing the chances of being the victim o

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Publication Date
Mon Apr 01 2019
Journal Name
2019 4th Scientific International Conference Najaf (sicn)
Pneumatic Control System of Automatic Production Line Using SCADA Implement PLC
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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Bioremediation of Soil Contaminated with 2,4-D Herbicide Using Bioslurry Reactor
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Ex-situ bioremediation of 2,4-D herbicide-contaminated soil was studied using a slurry bioreactor operate at aerobic conditions. The performance of the slurry bioreactor was tested for three types of soil (sand, sandy loam and clay) contaminated with different concentration of 2,4-D, 200,300and500mg/kg soil. Sewage sludge was used as an inexpensive source of microorganisms which is available in large quantities in wastewater treatment plants. The results show that all biodegradation experiments demonstrated a significant decreases in 2,4-D concentration in the tested soils. The degradation efficiency in the slurry bioreactor decreases as the initial concentration of 2,4-D in the soils increases.A 100 % removal was achieved at initial con

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Publication Date
Mon Dec 10 2018
Journal Name
Day 1 Mon, December 10, 2018
Wellbore Trajectory Optimization Using Rate of Penetration and Wellbore Stability Analysis
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Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

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Publication Date
Thu Mar 09 2023
Journal Name
Coatings
Nondestructive Evaluation of Fiber-Reinforced Polymer Using Microwave Techniques: A Review
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Carbon-fiber-reinforced polymer (CFRP) is widely acknowledged as a leading advanced material structure, offering superior properties compared to traditional materials, and has found diverse applications in several industrial sectors, such as that of automobiles, aircrafts, and power plants. However, the production of CFRP composites is prone to fabrication problems, leading to structural defects arising from cycling and aging processes. Identifying these defects at an early stage is crucial to prevent service issues that could result in catastrophic failures. Hence, routine inspection and maintenance are crucial to prevent system collapse. To achieve this objective, conventional nondestructive testing (NDT) methods are utilized to i

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Performance Assessment of Solar-Transformer-Consumption System Using Neural Network Approach
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Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so

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Publication Date
Wed Dec 31 2008
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Bio Chemical Study of Antithyroid Peroxidase Auto Antibodies , Magnesium and Cobalt in Hyperthyroidism Patients From Different Regions of Iraq.
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