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alkej-605
Extraction of Phenol From Industrial Water Using Different Solvents
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The analysis and efficiency of phenol extraction from the industrial water using different solvents, were investigated. To our knowledge, the experimental information available in the literature for liquid-liquid equilibria of ternary mixtures containing the pair phenol-water is limited. Therefore the purpose of the present investigation is to generate the data for the water-phenol with different solvents to aid the correlation of liquid-liquid equilibria, including phase diagrams, distribution coefficients of phenol, tie-lines data and selectivity of the solvents for the aqueous phenol system.

                The ternary equilibrium diagrams and tie-lines data for systems containing Water-Phenol-Benzene, Water-Phenol-Chloroform, Water-Phenol-iso-Butyl Acetate, Water-Phenol-Butanol, Water-Phenol-Ethyl Methyl Keton and Water-Phenol-Toluene, were determined at 303 K and atmospheric pressure.

                The capacity and selectivity of these organic solvents in each of these systems were determined from the tie-lines data. The capacity of the isobutyle acetate was found to be the highest among the other solvents, and its selectivity was also the highest. Similar results also were obtained for the ethyl methyl keton but gave less capacity and selectivity as compared to the isobutyle acetate. It can be concluded that both isobutyle acetate and ethyl methyl keton are good solvents for extraction of phenol from industrial water.

                The liquid-liquid equilibrium data of ternary systems were correlated to the NRTL, UNIQUAC and UNIFAC models of activity coefficient to determine their adjustable parameters. The standard deviations from experimental compositions were calculated. Results show that the correlation may be greatly improved by applying the NRTL model with the regression criteria based on minimizing the experimental and calculating distribution coefficients SK to give an average value of the root mean square deviation about 1.436 % and in terms of the average errors in the distribution ratio for all tie-lines about 10.776 %.

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Engineering/
Water quality assessment and total dissolved solids prediction using artificial neural network in Al-Hawizeh marsh south of Iraq
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The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Engineering
Upgrading of Alum Preparation and Dosing Unit for Sharq Dijla Water Treatment Plant by Using Programmable Logic Controller System
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One of the important units in Sharq Dijla Water Treatment Plant (WTP) first and second extensions are the alum solution preparation and dosing unit. The existing operation of this unit accomplished manually starting from unloading the powder alum in the preparation basin and ending by controlling the alum dosage addition through the dosing pumps to the flash mix chambers. Because of the modern trend of monitoring and control the automatic operation of WTPs due to the great benefits that could be gain from optimum equipment operation, reducing the operating costs and human errors. This study deals with how to transform the conventional operation to an automatic monitoring and controlling system depending on a Programmable

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Estimating concentration of toxic ions Arsenic in water by using Photonic Crystal Fiber based on Surface Plasmon Resonance (SPR)
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In this work, an enhanced Photonic Crystal Fiber (PCF) based on Surface Plasmon Resonance (SPR) sensor using a sided polished structure for the detection of toxic ions Arsenic in water was designed and implemented. The SPR curve can be obtained by polishing the side of the PCF after coating the Au film on the side of the polished area, the SPR curve can be obtained. The proposed sensor has a clear SPR effect, according to the findings of the experiments. The estimated signal to Noise Ratio (SNR), sensitivity (S), resolution (R), and Figures of merit (FOM) are approaching; the SNR is 0.0125, S is 11.11 μm/RIU, the resolution is 1.8x〖10〗^(-4), and the FOM is 13.88 for Single-mode Fiber- Photonic Crystal Fiber- single mode Fiber (SMF-P

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Publication Date
Mon Mar 01 2021
Journal Name
Microporous And Mesoporous Materials
Using the ash of common water reeds as a silica source for producing high purity ZSM-5 zeolite microspheres
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Publication Date
Tue Mar 27 2018
Journal Name
Mustansiria Dental Journal
The Effect of Modified Carisolv Gel on Surface Roughness of two Different Types of Ceramic Materials Using Light Polarizing Microscope
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This in vitro study evaluated the influence of chemomechanical caries removal solution on the surface topography of metal-ceramic feldspar porcelain (MAJOR ceramic) and All-ceramic feldspar porcelain (Vita Alpha) using light polarizing microscope. Forty specimens of MAJOR ceramic and forty specimens of Vita Alpha ceramic of (12mm diameter & 3mm height) were prepared .All specimens were polished with silicon polishing burs, cleaned, autoglazed and stored in 37°C before exposure to Carisolv. Thirty specimens of each material randomly exposed to Carisolv gel for 5, 10 and 20 minutes respectively, other ten specimens were not, to act as control group. All specimens were subjected to surface roughness test by profilometer and evalua

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Publication Date
Thu Nov 02 2023
Journal Name
Journal Of Engineering
The Effect of Using Different Aspect Ratios of Sustainable Copper Fiber on Some Mechanical Properties of High-Strength Green Concrete
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To achieve sustainability, use waste materials to make concrete to use alternative components and reduce the production of Portland cement. Lime cement was used instead of Portland cement, and 15% of the cement's weight was replaced with silica fume. Also used were eco-friendly fibers (copper fiber) made from recycled electrical. This work examines the impact of utilizing sustainable copper fiber with different aspect ratios (l/d) on some mechanical properties of high-strength green concrete. A high-strength cement mixture with a compressive strength of 65 MPa in line with ACI 211.4R was required to complete the assignment. Copper fibers of 1% by volume of concrete were employed in mixes with four different aspect ratios

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Publication Date
Sun Jan 01 2023
Journal Name
Brazilian Dental Science
The Effect of Immediate Dentin Sealing on the Marginal Adaptation of LithiumDisilicate Overlay Restorations using different types of luting agents
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Objective: This study evaluated the effect of immediate dentin sealing on the marginal adaptation of lithium disilicate overlays with three different types of resin-luting agents: preheated composite, dual-cure adhesive resin, and flowable composite. Materials and Methods: Forty-eight maxillary first premolars of similar size were prepared with a butt joint preparation design. The teeth were separated into two primary groups, each with twenty-four teeth: Group DDS: Delay dentin sealing (non-IDS) teeth were not treated. Group IDS: dentin sealing was applied immediately after teeth preparation. Each group was subsequently separated into three separate subgroups. Subgroups (DDS+Phc, IDS+Phc): cemented with preheated composite (Enamel plus HRi,

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach
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Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

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Publication Date
Thu Jul 01 2021
Journal Name
Computers & Electrical Engineering
A new proposed statistical feature extraction method in speech emotion recognition
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Publication Date
Fri Mar 26 2021
Journal Name
Chemical Papers
DFT, anticancer, antioxidant and molecular docking investigations of some ternary Ni(II) complexes with 2‑[(E)‑[4‑(dimethylamino) phenyl]methyleneamino]phenol
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The biological activities of some ternary nickel complexes with a Schiff base obtained from 4-dimethylaminobenzaldehyde and 2-aminophenol have been reported. The Schiff base ( HL1) acts as a primary ligand whereas, anthranilic acid ( HL2), 2-nitroaniline ( HL3), alanine ( HL4) and histidine ( HL5) act as secondary ligand or co-ligand. The anticancer activity of these compounds was studied against human colon carcinoma (HCT-116), human hepatocellular liver carcinoma (HEPG-2) and human breast carcinoma (MCF-7) cell lines. As per the results, the compounds were active against the cell lines. The antioxidant activity of the same compounds was evaluated using DPPH (1,1-diphenyl-2-picryl-hydrazyl) radical scavenging and compared with ascorbic aci

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