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Experimental and Theoretical Analysis of Lead Pb2+ and Cd2+ Retention from a Single Salt Using a Hollow Fiber PES Membrane
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The present work reports the performance of three types of polyethersulfone (PES) membrane in the removal of highly polluting and toxic lead Pb2+ and cadmium Cd2+ ions from a single salt. This study investigated the effect of operating variables, including pH, types of PES membrane, and feed concentration, on the separation process. The transport parameters and mass transfer coefficient (k) of the membranes were estimated using the combined film theory-solution-diffusion (CFSD), combined film theory-Spiegler-Kedem (CFSK), and combined film theory-finely-porous (CFFP) membrane transport models. Various parameters were used to estimate the enrichment factors, concentration polarization modulus, and Péclet number. The pH values significantly affected the permeation flux of the Pb2+ solution but only had a slight effect on the Cd2+ solution. However, Cd2+ rejection was highly improved by increasing the pH value. The rejection of the PES membranes increased greatly as the heavy metal concentration rose, while the heavy metal concentration moderately affected the permeation flux. The maximum rejection of Pb2+ in a single-salt solution was 99%, 97.5%, and 98% for a feed solution containing 10 mg Pb/L at pH 6, 6.2, and 5.7, for PES1, PES2, and PES3, respectively. The maximum rejection of Cd2+ in single-salt solutions was 78%, 50.2%, and 44% for a feed solution containing 10 mg Cd/L at pH 6.5, 6.2, and 6.5, for PES1, PES2, and PES3, respectively. The analysis of the experimental data using the CFSD, CFSK, and CFFP models showed a good agreement between the theoretical and experimental results. The effective membrane thickness and active skin layer thickness were evaluated using the CFFP model, indicating that the Péclet number is important for determining the mechanism of separation by diffusion.

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A Developed Colorimetric Assay Using Unmodified Gold Nanoparticles for the Identification of Acinetobacter baumannii Isolates from Different Clinical Samples
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  Acinetobacter baumannii (A. baumannii ) is considered a critical healthcare problem for patients in intensive care units due to its high ability to be multidrug-resistant to most commercially available antibiotics. The aim of this study is to develop a colorimetric assay to quantitatively detect the target DNA of A. baumannii based on unmodified gold nanoparticles (AuNPs) from different clinical samples (burns, surgical wounds, sputum, blood and urine). A total of thirty-six A. baumannii clinical isolates were collected from five Iraqi hospitals in Erbil and Mosul provinces within the period from September 2020 to January 2021. Bacterial isolation and biochemical identification of isolates

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Publication Date
Sat Jun 01 2024
Journal Name
Case Studies In Chemical And Environmental Engineering
Optimization of photocatalytic process with SnO2 catalyst for COD reduction from petroleum refinery wastewater using a slurry bubble photoreactor
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Publication Date
Thu Oct 31 2013
Journal Name
Al-khwarizmi Engineering Journal
Influence of the Applied Potential and Temperature on the Electrode position of the Lead Dioxide
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The excellent specifications of electrodes coated with lead dioxide material make it of great importance in the industry. So it was suggested this study, which includes electrodeposition of lead dioxide on graphite substrate, knowing that the electrodeposition of lead dioxide on graphite studied earlier in different ways.

In this work the deposition process for lead dioxide conducted using electrolytic solution containing lead nitrate concentration 0.72 M with the addition of some other material to the solution, such as copper nitrate, nickel nitrate, sodium fluoride and cetyl trimethyl ammonium bromide, but only in very small concentrations. As for the operating conditions, the effect of change potential and temperature as well

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Publication Date
Sun Aug 22 2021
Journal Name
Biochemical & Cellular Archives
THE EFFICIENCY OF NERIUM OLEANDER PLANT IN PHYTOREMEDIATION OF SOILS CONTAMINATED WITH LEAD AND CADMIUM
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Publication Date
Thu Jun 16 2022
Journal Name
Al-khwarizmi Engineering Journal
Estimate and Analysis the Availability of Generator in Electric Power Plant Using ANN
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The large number of failure in electrical power plant leads to the sudden stopping of work. In some cases, the necessary reserve materials are not available for maintenance which leads to interrupt of power generation in the electrical power plant unit. The present study, deals with the determination of availability aspects of generator in unit 5 of Al-Dourra electric power plant. In order to evaluate this generator's availability performance, a wide range of studies have been conducted to gather accurate information at the level of detail considered suitable to achieve the availability analysis aim. The Weibull Distribution is used to perform the reliability analysis via Minitab 17, and Artificial Neural Networks (ANNs) by approaching o

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Publication Date
Thu Dec 28 2023
Journal Name
The Iraqi Journal Of Veterinary Medicine
Molecular Identification and Phylogenetic Analysis of Salmonella‎ species ‎Isolated from Diarrheal Children and Dogs in Baghdad Governorate, ‎Iraq‎
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This work aimed to use conventional PCR to identify Salmonella‎ spp. that ‎were isolated from diarrheal children and healthy and diarrheic dogs based on four ‎virulence genes, hilA, stn, spvR‎, and marT. Sixteen Salmonella‎ isolates including: 9 ‎isolated from children's diarrhea from three species (S. Typhimurium, S. Enteritidis, S. ‎Typhi) and seven isolated from dogs including (S. Typhimurium, S. Enteritidis, S. ‎Muenchen), were identified primarily by several methods. The PCR products of the 16S ‎rRNA gene were sequenced and examined using BLAST analysis to find differences and ‎similarities between these Iraqi isolates and already-known global strains in order to ‎construct the phylogenetic tree of S.

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Publication Date
Tue Jan 01 2019
Journal Name
Advances On Computational Intelligence In Energy
A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption
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Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

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Publication Date
Tue Apr 01 2025
Journal Name
Iop Conference Series: Earth And Environmental Science
A Comparative Study of Organic and Mineral Acids in the Release of Potassium from Potassium Feldspar Minerals
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Abstract<p>A study conducted a laboratory experiment to measure the release of potassium and the dissolution of feldspar minerals in soils from different locations in Karbala Province (Ain Al-tamur, Qasr Al-Akhyar, Fadak Farm). The study involved the addition of organic acids (fulvic and humic) and mineral acids (sulfuric and phosphoric) at concentrations of 5% and 10% to sand-separated soil samples obtained through wet sieving. Feldspar minerals were identified using a polarized light microscope, and the percentage of each type of feldspar mineral was calculated. The results demonstrated that organic acids outperformed mineral acids in releasing potassium at both concentrations. Among the organ</p> ... Show More
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Publication Date
Tue Dec 16 2025
Journal Name
Radioelectronics. Nanosystems. Information Technologies.
Intelligent Control and Stability Analysis of Smart Grids Using CNN-LSTM Network and Model Predictive Controller
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It is important that real time stability in smart grids is ensured as the integration of renewables and the complexity of the systems grows. In this paper, we provide a solid architecture, which combines a Residual CNNLSTM deep neural network predictor, FPGA-accelerated Model Predictive Control (MPC), and SHAP-based explainability. The proposed method predicted with 99.8% accuracy using the Electrical grid Stability Simulated Dataset (UCI) and minimized the instability rates surpassing 85 percent in all operating conditions. Meeting real-time operating needs, FPGA deployment on a Xilinx Zynq UltraScale+ provided 3.1 ms latency and 5 times reduced energy consumption against CPU processing. By emphasizing bus voltage and frequency as major in

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Publication Date
Mon Dec 24 2018
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
MOLECULAR IDENTIFICATION AND PHYLOGENETIC-TREE ANALYSIS OF MONIEZIA SPECIES FROM SHEEP IN AL-DIWANIYAH CITY
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    The present study was performed to detect the molecular and the phylogenetic identification of species that belonging to the genus of Moniezia Blanchard, 1891 which affected intestines of sheep in Al-Diwaniyah city, Iraq; fifty intestine samples were sought for the infestation of Moniezia spp. from the city slaughterhouse from 1 October to 30 November 2017, this tapeworm was found to infest the intestines of 13 sheep.

 

    For morphological identify the genus of this tapeworm, eggs from one gravid proglottid of the thirteen worms were examined, polymerase chain reaction (PCR) and the PCR-product-based sequencing were applied on 4 Moniezia tapeworms targeti

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