Modified bentonite has been used as effective sorbent material for the removal of acidic dye (methyl orange) from aqueous solution in batch system. The natural bentonite has been modified using cationic surfactant (cetyltrimethyl ammonium bromide) in order to obtain an efficient sorbent through converting the properties of bentonite from hydrophilic to organophilic. The characteristics of the natural and modified bentonite were examined through several analyses such as Scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and Surface area. The batch study was provided the maximum dye removal efficiency of 88.75 % with a sorption capacity of 555.56 mg/g at specified conditions (150 min, pH= 2, 250 rpm, and 0.

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

Organogel as a system was to estimate its capacity to delay and slow the drug release in the duodenum. The gelators, 12HSA (12-hydroxystearic acid), span 60. span 40 were used; the castor oil (CO) and anise oil (AO) also represented the liquid phase. To achieve the goal of this work was by using diclofenac sodium (DS). Organogels specifications were by estimating thermal attitude using tabletop rheology and differential scanning calorimetry (DSC). The organogel strength study was by applying oscillatory rheology tests the amplitude sweep and the frequency sweep. Realizing the morphology of the organogel was done utilizing an optical microscope. CO and AO binding capacity was also manifested. The transition temperatures for all organogels

A Ligand (ECA) methyl 2-((1-cyano-2-ethoxy-2-oxoethyl)diazenyl)benzoate with metals of (Co²⁺, Ni²⁺, Cu²⁺) were prepared and characterization using H-NMR, atomic absorption spectroscopy, ultra violet (UV) visible, magnetic moments measurements, bioactivity, and Molar conductivity measurements in soluble ethanol. Complexes have been prepared using a general formula which was suggested as [M (ECA)₂] Cl₂, where M = (Cobalt(II), Nickel(II) and Copper(II), the geometry shape of the complexes is octahedral.

Background: Although bleaching is typically considered a safe procedure, various investigations have found minor negative effects and changes in mineral composition. The aim was to Evaluate and compare the efficacy of using Nanohydroxyapatite serum on surface microhardness of enamel surface before and after bleaching with chemically cured Boost bleaching. Material and methods: ten sound human permanent upper and lower premolar teeth were used and their roots were removed 2 mm apically to the cementoenamel junction, the crowns were sectioned mesiodistally into two halves buccal and lingual/palatal, the buccal surface was further subdivided into two halves. The samples were embeded in an acrylic resin, resulting in 30 specimens divide

Reservoir characterization is an important component of hydrocarbon exploration and production, which requires the integration of different disciplines for accurate subsurface modeling. This comprehensive research paper delves into the complex interplay of rock materials, rock formation techniques, and geological modeling techniques for improving reservoir quality. The research plays an important role dominated by petrophysical factors such as porosity, shale volume, water content, and permeability—as important indicators of reservoir properties, fluid behavior, and hydrocarbon potential. It examines various rock cataloging techniques, focusing on rock aggregation techniques and self-organizing maps (SOMs) to identify specific and