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bsj-2294
The Removal of Zinc from Aqueous Solutions Using Malvaparviflora
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In this study, the adsorption of Zn (NO3)2 is carried out by using surfaces of malvaparviflora. The validity of the adsorption is evaluated by using atomic absorption Spectrophotometry through determination the amount of adsorbed Zn (NO3)2. Various parameters such as PH, adsorbent weight and contact time are studied in terms of their effect on the reaction progress. Furthermore, Lagergren’s equation is used to determine adsorption kinetics. It is observed that high removal of Zn (NO3)2 is obtained at PH=2. High removal of Zn (NO3)2 is at the time equivalent of 60 min and reaches equilibrium,where 0.25gm is the best weight of adsorbant . For kinetics the reaction onto malvaparviflora follows pseudo first order Lagergren’s equation.

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Publication Date
Mon Jan 01 2018
Journal Name
Materials Research Bulletin
Understanding the impacts of Al+3-substitutions on the enhancement of magnetic, dielectric and electrical behaviors of ceramic processed nickel-zinc mixed ferrites: FTIR assisted studies
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Publication Date
Tue Aug 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Effect of Foliar Spray of Zinc and Irrigating with Smoking-Water on Growth of Citrus Rootstock C35
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This study was conducted in fruit production lathe house of the Department Of Horticulture And Landscape Gardening, in the station (B), College Of Agricultural Engineering Sciences, University Of Baghdad, Al-Jaadria for 8 months, began from 1/3/2019 to 1/9/2019 to investigate the responses of C35 Citrus rootstock to influence of foliar spraying of zinc and irrigation with smoking-water at 2 years old saplings. the study included two factors, first factor was three concentrations of Zinc Element Z0(0 mg.l-1), Z1(50 mg.l-1) and Z2(75 mg.l-1) that sprays at leave. The second factor was watering saplings with smoke-water in three concentrations S0(0 vol.vol-1), S1(0.1 vol.vol-1) and (0.2vol.vol-1), and their interaction. The experiment was fact

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Wed Sep 01 2010
Journal Name
Al-khwarizmi Engineering Journal
Extraction of Monocyclic Aromatic Hydrocarbons From Petroleum Products Using Sulfolane as Industrial Solvent
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            Liquid – liquid equilibria data were measured at 293.15 K for the pseudo ternary system (sulfolane + alkanol) + octane + toluene. It is observed that the selectivity of pure sulfolane increases with cosolvent methanol but decreases with increasing the chain length of hydrocarbon in 1-alkanol. The nonrandom two liquid (NRTL) model, UNIQUAC model and UNIFAC model were used to correlate the experimental data and to predict the phase composition of the systems studied. The calculation based on NRTL model gave a good representation of the experimental tie-line data for all systems studied. The agreement between the correlated and the experimental results was very good

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Wed Sep 18 2024
Journal Name
International Journal Of Renewable Energy Development
Production of biodiesel by using CaO nano-catalyst synthesis from mango leaves extraction
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Development and population expansion have the lion's share of driving up the fuel cost. Biodiesel has considerable attention as a renewable, ecologically friendly and alternative fuel source. In this study, CaO nanocatalyst is produced from mango leaves as a catalysis for the transesterification of waste cooking oil (WCO) to biodiesel. The mango tree is a perennial plant, and its fruit holds significant economic worth due to its abundance of vitamins and minerals. This plant has a wide geographical range and its leaves can be utilized without any negative impact on its growth and yield. An analysis was conducted to determine the calcium content in the fallen leaves, revealing a significant quantity of calcium that holds potential fo

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Publication Date
Tue Jun 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Adsorption of heavy metal ions using activated carbon derived from Eichhornia (water hyacinth)
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Abstract<p>Removal of heavy metal ions such as, cadmium ion (Cd <sup>2+</sup>) and lead ion (Pb <sup>2+</sup>) from aqueous solution onto Eichhornia (water hyacinth) activated carbon (EAC) by physiochemical activation with potassium hydroxide (KOH) and carbon dioxide (CO<sub>2</sub>) as the activating agents were investigated. The Eichhornia activated carbon was characterized by Brunauer Emmett Teller (BET), Fourier Transform Infrared spectroscopy (FTIR), and Scanning Electron Microscopy (SEM) techniques. Whereas, the effect of adsorbent dosage, contact time of pH, and metal ion concentration on the adsorption process have been investigated using the batch process t</p> ... Show More
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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
Wed Jan 01 2020
Journal Name
Journal Of Research In Medical And Dental Science
Evaluation of the Serum Level of Interleukin-6 in Patients Undergoing Surgical Removal of Impacted Mandibular Third Molars
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Evaluation of the Serum Level of Interleukin-6 in Patients Undergoing Surgical Removal of Impacted Mandibular Third Molars, Hussain A Taher*, Salwan Y Bede

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Publication Date
Wed Apr 01 2020
Journal Name
International Journal Of Pharmaceutical Research
Molecular Interaction in Aqueous Solution of Butanol Isomers at 298.15 K
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