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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
Tue Oct 10 2023
Journal Name
Journal Of Craniofacial Surgery
Cone Beam Computed Tomographic Evaluation of Schneiderian Membrane Thickness
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This study aimed to determine the measurements and classification of Schneider membrane thickness correlated to age and sex factors using cone beam computed tomography (CBCT). Methods: The study included CBCT images for 100 maxillary sinuses of 50 consecutive patients, and the thickness of the maxillary sinus membrane (Schneiderian membrane) was measured in coronal view from the lowest point in the floor of the maxillary sinus to the highest point. The thickness of the Schneiderian membrane was classified into 4 types. Results: The study result revealed that out of the total cases, 45% of sinus membranes were classified as type 2, while only 10% were classified as type 4. The most frequent type of membrane thickness diagnosed in the age gro

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Publication Date
Mon Sep 01 2008
Journal Name
Journal Of Engineering
MATHEMATICAL SIMULATION OF UNSTEADY FLOW THROUGH HOLLOW FIBER MEMBRANE
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Publication Date
Tue Dec 30 2014
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
PREPARATION OF PVC HOLLOW FIBER MEMBRANE USING (DMAC/ACETONE)
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Membrane manufacturing system was operated using dry/wet phase inversion process. A sample of hollow fiber membrane was prepared using (17% wt PVC) polyvinyl chloride as membrane material and N, N Dimethylacetamide (DMAC) as solvent in the first run and the second run was made using (DMAC/Acetone) of ratio 3.4 w/w. Scanning electron microscope (SEM) was used to predict the structure and dimensions of hollow fiber membranes prepared. The ultrafiltration experiments were performed using soluble polymeric solute poly ethylene glycol (PEG) of molecular weight (20000 Dalton) 800 ppm solution 25 °C temperature and 1 bar pressure. The experimental results show that pure water permeation increased from 25.7 to 32.2 (L/m2.h.bar) by adding aceton

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Publication Date
Fri Mar 20 2026
Journal Name
Baghdad Science Journal
Determination of Trace Pyridoxine Hydrochloride (Vitamin B6) in Dosage Forms and Redbull Samples Using Dispersive Liquid-Liquid Microextraction Technique Coupled with Spectrophotometry
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Publication Date
Wed Apr 01 2015
Journal Name
Mathematical Methods In The Applied Sciences
An inverse problem of finding the time-dependent diffusion coefficient from an integral condition
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Publication Date
Sun Jun 05 2022
Journal Name
Network
A Computationally Efficient Gradient Algorithm for Downlink Training Sequence Optimization in FDD Massive MIMO Systems
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Future wireless networks will require advance physical-layer techniques to meet the requirements of Internet of Everything (IoE) applications and massive communication systems. To this end, a massive MIMO (m-MIMO) system is to date considered one of the key technologies for future wireless networks. This is due to the capability of m-MIMO to bring a significant improvement in the spectral efficiency and energy efficiency. However, designing an efficient downlink (DL) training sequence for fast channel state information (CSI) estimation, i.e., with limited coherence time, in a frequency division duplex (FDD) m-MIMO system when users exhibit different correlation patterns, i.e., span distinct channel covariance matrices, is to date ve

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Publication Date
Sat Aug 25 2012
Journal Name
Wireless Personal Communications
Multi-Objective Evolutionary Algorithm Based on Decomposition for Energy Efficient Coverage in Wireless Sensor Networks
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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

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Publication Date
Thu Oct 01 2020
Journal Name
Biochemical & Cellular Archives
RAPID SPECTROPHOTOMETRIC ESTIMATION OF TRACE AMOUNTS OF MEFENAMIC ACID BASED DISPERSIVE LIQUID-LIQUID MICROEXTRACTION OF IN PHARMACEUTICAL PREPARATIONS.
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A dispersive liquid-liquid microextraction combines with UV-V is spectrophotometry for the preconcentration and determination of Mefenamic acid in pharmaceutical preparation was developed and introduced. The proposed method is based on the formation of charge transfer complexation between mefenamic acid and chloranil as an n-electron donor and a p-acceptor, respectively to form a violet chromogen complex measured at 542 nm. The important parameters affecting the efficiency of DLLME were evaluated and optimized. Under the optimum conditions, the calibration graphs of standard and drug, were ranged 0.03-10 µg mL-1. The limits of detection, quantification and Sandell's sensitivity were calculated. Good recoveries of MAF Std. and drug at 0.05,

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