In this study, aluminum nanoparticles (Al NPs) were prepared using explosive strips method in double-distilled deionized water (DDDW), where the effect of five different currents (25, 50, 75, 100 and 125 A) on particle size and distribution was studied. Also, the explosive strips method was used to decorate zinc oxide particles with Al particles, where Al particles were prepared in suspended from zinc oxide with DDDW. Transmission electron microscopy (TEM), UV-visible absorption spectroscopy, and x-ray diffraction are used to characterize the nanoparticles. XRD pattern were examined for three samples of aluminum particles and DDDW prepared with three current values (25, 75 and 125 A) and three samples prepared with the same currents for zin

In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri

This study introduced the effect of using magnetic abrasive finishing method (MAF) for finishing flat surfaces. The results of experiment allow considering the MAF method as a perspective for finishing flat surfaces, forming optimum physical mechanical properties of surfaces layer, removing the defective layers and decreasing the height of micro irregularities. Study the characteristics which permit judgment parameters of surface quality after MAF method then comparative with grinding

Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

A simple, cheap, fast, accurate, Safety and sensitive spectrophotometric method for the determination of sulfamethaxazole (SFMx), in pure form and pharmaceutical dosage forms. has been described The Method is based on the diazotization of the drug by sodium nitrite in acidic medium at 5Cº followed by coupling with salbutamol sulphate (SBS) drug to form orange color the product was stabilized and measured at 452 nm Beer’s law is obeyed in the concentration range of 2.5-87.5 ?g ml-1 with molar absorptivity of 2.5x104 L mole-1 cm-1. All variables including the reagent concentration, reaction time, color stability period, and sulfamethaxazole /salbutamol ratio were studied in order to optimize the reaction conditions. No interferences were

In this paper flotation method experiments were performed to investigate the removal of lead and zinc. Various parameters such as pH, air flow rate, collector concentrations, collector type and initial metal concentrations were tested in a bubble column of 6 cm inside diameter. High recoveries of the two metals have been obtained by applying the foam flotation process, and at relatively short time 45 minutes . The results show that the best removal of lead about 95% was achieved at pH value of 8 and the best removal of zinc about 93% was achieved
at pH value of 10 by using 100 mg/l of Sodium dodecylsulfate (SDS) as a collector and 1% ethanol as a frother. The results show that the removal efficiency increased with increasing initial m

An efficient combination of Adomian Decomposition iterative technique coupled with Laplace transformation to solve non-linear Random Integro differential equation (NRIDE) is introduced in a novel way to get an accurate analytical solution. This technique is an elegant combination of theLaplace transform, and the Adomian polynomial. The suggested method will convert differential equations into iterative algebraic equations, thus reducing processing and analytical work. The technique solves the problem of calculating the Adomian polynomials. The method’s efficiency was investigated using some numerical instances, and the findings demonstrate that it is easier to use than many other numerical procedures. It has also been established that (LT