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Efficient Removal of Brilliant Green Dye Using Mesoporous Attapulgite Clay: Investigating Adsorption Kinetics, Isotherms, and Mechanisms
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The study involved the effectiveness of Iraqi attapulgite (IQATP) clay as an environmentally friendly material that easily adsorbs brilliant green (BG) dye from water systems and is identified by various complementary methods (e.g., FTIR, SEM‐EDS, XRD, ICP‐OES, pHpzc, and BET), where the result reported that the IQATP specific surface area is 29.15 m2/g. A systematic analysis was selected to evaluate the impact of different effective adsorption performance variables on BG dye decontamination. These variables included IQATP dosage (0.02–0.8 g/L), solution pH (3.05–8.15), contact time (ranging from 2 to 25 min), and initial BG dye concentration from 20 to 80 mg/L. The parameters of kinetic profiles were best represented by the (P‐2‐O) model with the determination of coefficient (R2, 0.99), and the corresponding equilibrium data of dye provided a good fit of the Freundlich adsorption model with a maximal multilayer IQATP adsorption capacity (Qmax, = 1.41 mg/g) under optimum conditions (temperature 318 K, pH 3.05, optimum equilibrium time 25 min, and IQATP dosage 0.2 g/L) for BG dye removal. Thermodynamic parameters, including ΔG = −5.67, −6.10, and −7.56 kJ/mol, ΔH = 29.89 kJ/mol, ΔS = 118.73 J/mol·K, and activation energy Ea = 14.38 kJ/mol, were calculated to understand the adsorption process. This trend indicates an endothermic, spontaneous, and favorable adsorption profile for basic dye by IQATP. The adsorption mechanism was elucidated, indicating the involvement of electrostatic attractions, hydrogen bonding, and n − π interactions in the adsorption of cationic dye. Desorption experiments of BG by IQATP with five repetition cycles showed a great desorption percentage when using 0.1 M hydrochloric acid (HCl), as the eluting agent. Overall, the findings highlight IQATP as a promising and desirable natural adsorbent for the efficient removal of cationic dyes.

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Synthesizing and Using Iron Oxide Nanoparticles as Nanocomposite in Cotton Fabrics Nanofinishing
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Metal oxide nanoparticles, including iron oxide, are highly considered as one of the most important species of nanomaterials in a varied range of applications due to their optical, magnetic, and electrical properties. Iron oxides are common compounds, extensive in nature, and easily synthesized in the laboratory. In this paper, iron oxide nanoparticles were prepared by co-precipitation of (Fe+2) and (Fe+3) ions, using iron (II and III) sulfate as precursor material and NH4OH solution as solvent at 90°C. After the synthesis of iron oxide particles, it was characterized using X-ray diffraction (XRD), infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). These tests confirmed the obtaining o

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Publication Date
Thu Feb 01 2018
Journal Name
Iet Signal Processing
Signal compression and enhancement using a new orthogonal‐polynomial‐based discrete transform
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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
On Light Mapping and Certain Concepts by Using m_X N-Open Sets
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The aim of this paper is to present a weak form of -light functions by using -open set which is -light function, and to offer new concepts of disconnected spaces and totally disconnected spaces. The relation between them have been studied. Also, a new form of -totally disconnected and inversely -totally disconnected function have been defined, some examples and facts was submitted.

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Mining categorical Covid-19 data using chi-square and logistic regression algorithms
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Publication Date
Wed Mar 05 2025
Journal Name
Lecture Notes In Networks And Systems
Using Artificial Intelligence to Enhance Family Cohesion and Promote Positive Social Values
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Publication Date
Wed Sep 01 2010
Journal Name
Journal Of Economics And Administrative Sciences
Using simulation to estimate parameters and reliability function for extreme value distribution
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   This study includes Estimating scale parameter, location parameter  and reliability function  for Extreme Value (EXV) distribution by two methods, namely: -
- Maximum Likelihood Method (MLE).
- Probability Weighted Moments Method (PWM).

 Used simulations to generate the required samples to estimate the parameters and reliability function of different sizes(n=10,25,50,100) , and give real values for the parameters are and , replicate the simulation experiments (RP=1000)

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Publication Date
Fri Jan 01 2021
Journal Name
Int. J. Nonlinear Anal. Appl.
Feeble regular and feeble normal spaces in α-topological spaces using graph
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This paper introduces some properties of separation axioms called α -feeble regular and α -feeble normal spaces (which are weaker than the usual axioms) by using elements of graph which are the essential parts of our α -topological spaces that we study them. Also, it presents some dependent concepts and studies their properties and some relationships between them.

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Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
Image Compression Using Tap 9/7 Wavelet Transform and Quadtree Coding Scheme
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This paper is concerned with the design and implementation of an image compression method based on biorthogonal tap-9/7 discrete wavelet transform (DWT) and quadtree coding method. As a first step the color correlation is handled using YUV color representation instead of RGB. Then, the chromatic sub-bands are downsampled, and the data of each color band is transformed using wavelet transform. The produced wavelet sub-bands are quantized using hierarchal scalar quantization method. The detail quantized coefficient is coded using quadtree coding followed by Lempel-Ziv-Welch (LZW) encoding. While the approximation coefficients are coded using delta coding followed by LZW encoding. The test results indicated that the compression results are com

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Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
Satellite Images Unsupervised Classification Using Two Methods Fast Otsu and K-means
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Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

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Publication Date
Tue Dec 03 2013
Journal Name
Baghdad Science Journal
Satellite Images Unsupervised Classification Using Two Methods Fast Otsu and K-means
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