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Exploring electromembrane extraction and liquid membrane for efficient removal of heavy metals from aqueous solutions: An overview
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Environmental pollution is experiencing an alarming surge within the global ecosystem, warranting urgent attention. Among the significant challenges that demand immediate resolution, effective treatment of industrial pollutants stands out prominently, which for decades has been the focus of most researchers for sustainable industrial development aiming to remove those pollutants and recover some of them. The liquid membrane (LM) method, specifically electromembrane extraction (EME), offers promise. EME deploys an electric field, reducing extraction time and energy use while staying eco-friendly. However, there's a crucial knowledge gap. Despite strides in understanding and applying EME, optimizing it for diverse industrial pollutants and environmental conditions remains uncharted. Future research must expand EME's applicability, assess its environmental impact versus other methods, and boost scalability, cost-effectiveness, and energy efficiency in industry. Advances in novel liquid membrane materials can enhance extraction efficiency and selectivity, aiming to provide efficient, sustainable industrial pollutant treatment. This research provides a review of the existing practices in the field of liquid membranes when coupled with the application of an electric field.

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Publication Date
Thu Oct 01 2020
Journal Name
Chemical Engineering And Processing - Process Intensification
Cobalt Removal from Simulated Wastewaters Using a Novel Flow-by Fixed Bed Bio-electrochemical Reactor
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Publication Date
Tue Dec 24 2024
Journal Name
Malaysian Journal Of Mathematical Sciences
Exploring the Role of Hunting Cooperation, and Fear in a Prey-Predator Model with Two Age Stages
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The aim of this study is to utilize the behavior of a mathematical model consisting of three-species with Lotka Volterra functional response with incorporating of fear and hunting cooperation factors with both juvenile and adult predators. The existence of equilibrium points of the system was discussed the conditions with variables. The behavior of model referred by local stability in nearness of any an equilibrium point and the conditions for the method of approximating the solution has been studied locally. We define a suitable Lyapunov function that covers every element of the nonlinear system and illustrate that it works. The effect of the death factor was observed in some periods, leading to non-stability. To confirm the theore

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Advanced Pharmaceutical Technology & Research
Exploring the modulation of MLH1 and MSH2 gene expression in hesperetin-treated breast cancer cells (BT-474)
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A<sc>BSTRACT</sc> <p>The major mortality factor for women globally is breast cancer, and current treatments have several adverse effects. Hesperetin (HSP) is a flavone that occurs naturally with anti-tumor capabilities and has been investigated as a potential treatment for cancer. This study aimed to investigate the cytotoxic and anti-malignant potential of HSP on breast cancer cells (BT-474) and normal cells (MCF-10a). The results indicated that HSP has dose-dependent cytotoxicity in BT-474 and MCF-10a cells. The elevated concentration of HSP lowered cell viability and proliferation. The half-maximal inhibitory concentration (IC<sub>50</sub>) of HSP in BT-</p> ... Show More
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Publication Date
Thu Jun 01 2017
Journal Name
American Journal Of Pharmaceutical Education
Exploring Electronic Communication Modes Between Iraqi Faculty and Students of Pharmacy Schools Using the Technology Acceptance Model
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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Effect of Operating Conditions on Reverse Osmosis (RO) Membrane Performance
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The aim of this research is to study the effect of high concentrations of salts, pressure and temperature on the performance of the RO membrane with time. Four different (Na2CO3) concentrations (5000, 15000, 25000 and 35000) ppm and various pressures such as (1, 3 and 5) bars at different temperatures of the feed solution (i.e., 25, 35 and 45) ◦C were used in this work. It was found that, as the concentration of salt and feed temperatures increase, the rejection of the salt decrease. While the salt rejection of the membranes increases with increase of transmembrane pressure.

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Publication Date
Sun Oct 15 2023
Journal Name
Sumer 4
CYTOTOXIC IMPACT OF OUTER MEMBRANE NANOVESICLES (OMVS) ON OVARIAN CANCER
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This study focused on extracting the outer membrane nanovesicles (OMVs) from Escherichia coli BE2 (EC- OMVs) by ultracentrifugation, and the yield was 2.3mg/ml. This was followed by purification with gel filtration chromatography using Sephadex G-150, which was 2mg/ml. The morphology and size of purified EC-OMVs were confirmed by transmission electron microscopy (TEM) at 40-200 nm. The nature of functional groups in the vesicle vesicle was determined by Fourier transforms infrared spectroscopy (FT-IR) analysis. The antitumor activity of EC-OMVs was conducted in vitro by MTT assay in human ovarian (OV33) cancer cell line at 24,48 and 96hrs. The cytotoxicity test showed high susceptibility to the vesicles in ovarian compared to normal

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Artificial Neural Network (ANN) for Prediction of Viscosity Reduction of Heavy Crude Oil using Different Organic Solvents
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The increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests  and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a  heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage  (5, 10 and  20 wt.% )  of  (n-heptane, toluene, and a mixture of  different ratio

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Publication Date
Tue Mar 19 2019
Journal Name
Al-khwarizmi Engineering Journal
Optimization of Material Removal Rate and Temperature in Magnetic Abrasive Finishing Process for Stainless Steel 304
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The effect of the magnetic abrasive finishing (MAF) method on the temperature rise (TR), and material removal rate (MRR) has been investigated in this paper. Sixteen runs were to determine the optimum temperature in the contact area (between the abrasive powder and surface of workpiece) and the MRR according to Taguchi orthogonal array (OA). Four variable technological parameters (cutting speed, finishing time, working gap, and the current in the inductor) with four levels for each parameter were used, the matrix is known as a L16 (44) OA. The signal to noise ratio (S/N) ratio and analysis of the variance (ANOVA) were utilized to analyze the results using (MINITAB17) to find the optimum condition and identify the significant p

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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Geological Journal
Multiple and Coherent Noise Removal from X-Profile 2D Seismic Data of Southern Iraq Using Normal Move Out-Frequency Wavenumber Technique
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Multiple eliminations (de-multiple) are one of seismic processing steps to remove their effects and delineate the correct primary refractors. Using normal move out to flatten primaries is the way to eliminate multiples through transforming these data to frequency-wavenumber domain. The flatten primaries are aligned with zero axis of the frequency-wavenumber domain and any other reflection types (multiples and random noise) are distributed elsewhere. Dip-filter is applied to pass the aligned data and reject others will separate primaries from multiple after transforming the data back from frequency-wavenumber domain to time-distance domain. For that, a suggested name for this technique as normal move out- frequency-wavenumber domain

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