In this work, the adsorption of crystal violet dye from aqueous solution on charcoal and rice husk has been investigated, where the impact of variable factors (contact time; the dosage of adsorbent, pH, temperature, and ionic strength) have been studied. It has been found that charcoal and rice husk have an appropriate adsorption limit with regards to the expulsion of crystal violet dye from fluid arrangements. The harmony adsorption is for all intents and purposes accomplished in 45 min for charcoal and 60 min for rice husk. The amount of crystal violet dye adsorbed (0.4 g of charcoal and 0.5 g of rice husk) increased with an increasing pH and the value of 11 is the best

    The study area comprises Injana Formation (Late Miocene), exposed on the hills nearby of Tharthar Lake and about 120 km north of Baghdad city. This study depends on sedimentologic and facies analysis to recognize paleoenvironment and recognize the kinds of vertebrate bone fossils during Late Miocene. Sedimentologic and facies analysis showed many sedimentary facies: facies (Se) of scoured erosional surface, facies of (Sp) cross- bedded sandstones, facies (Fs) of fine sandstone facies, facies of (Fc) claystone, and facies of (C) calcareous clay. Facies analysis referred to the sub environments which are: point bar, over bank and floodplain in addition to fining upward cycles of deposition, which refers to meandering flu

n this work, the adsorption of crystal violet dye from aqueous solution on charcoal and rice husk has been investigated, where the impact of variable factors (contact time; the dosage of adsorbent, pH, temperature, and ionic strength) have been studied. It has been found that charcoal and rice husk have an appropriate adsorption limit with regards to the expulsion of crystal violet dye from fluid arrangements. The harmony adsorption is for all intents and purposes accomplished in 45 min for charcoal and 60 min for rice husk. The amount of crystal violet dye adsorbed (0.4 g of charcoal and 0.5 g of rice husk) increased with an increasing pH and the value of 11 is the best. The effect of temperature on the adsorption process was studied

Background: Medicinal plants that possess antimicrobial and antioxidant properties have garnered significant attention for their role in maintaining food quality, improving safety, and impeding spoilage. They also can aid in controlling food contamination risks and augmenting the nutritional value of foods. Objective: The study aimed to obtain botanical extracts possessing antimicrobial capabilities and use them to inhibit the growth of molds and yeasts. Additionally, these extracts are aimed at prolonging product shelf life by harnessing their antioxidant attributes. Methods: Several microorganisms, including E. coli and Pseudomonas, were subjected to testing. Ethanolic alcohol, chloroform, and essential oil extracts were prepared;

A novel ligand, (E)-5-((2-hydroxy-4,6-dimethylphenyl)diazenyl)-2,3-dihydrophthalazine-1,4- dione, was synthesized through the reaction of 3,5-dimethylphenol with the diazonium salt of 5-amino-2,3-dihydrophthalazine-1,4-dione. The ligand underwent characterization through the utilization of diverse spectroscopic methods, including UV-Vis, FT-IR, 13C, and 1H-NMR, alongside Mass spectroscopy and micro elemental analysis (Carbon, Hydrogen, Nitrogen, and Oxygen). Metal chelates of transition metals were prepared and analyzed using elemental analysis, mass spectra, atomic absorption, UV-Vis, FT-IR spectral analysis, as well as conductivity and magnetic measurements. The investigation into the compounds’ nature was conducted by utilizing mole r

In this work, a deep computational study has been conducted to assign several qualities for the graph ⁠. Furthermore, determine the amount of the dihedral subgroups in the Held simple group He through utilizing the attributes of gamma.

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes