A computerized investigation has been carried out to design an immersion lens
with low aberration operating under zero magnification condition using inverse problem.
The aberration is highly dependent on the shape of electrodes, for a preassigned electron
beam trajectory the paraxial-ray-equation is solved to determine the electrostatic potential
and field distribution.
From the knowledge of the potential and its first and second derivative the
electron optical properties were computed, the electrode geometry was determined from
the solution of Laplace equation.

Ebastine (EBS) is a non-sedating antihistamine with a long duration of action. This drug has predominantly hydrophobic property causing a low solubility and low bioavailability. Surface solid dispersions (SSD) is an effective technique for improving the solubility and dissolution rate of poorly soluble drugs by using hydrophilic water insoluble carriers.

The present study aims to enhance the solubility and dissolution rate of EBS by using surface solid dispersion technique. Avicel® PH101, Avicel® PH 102, croscarmellose sodium(CCS) and sodium starch glycolate(SSG) were used as water insoluble hydrophilic carriers.

The SSD formulations of EBS were prepared by the solvent evaporation method in different drug:  carrier

Alginate is one of the natural biopolymers that is widely used for drug formulations, combination of alginate with other polymers, such as gum acacia, pectin, and carrageenan can increase mechanical strength, therefore, can reduce leakage of the encapsulated active pharmaceutical ingredient from the polymer matrix. Interaction of alginate and these polymers can occur via intermolecular hydrogen bonds causing synergism, which is determined from the viscosity of polymer mixture.

Alginate was combined with gum acacia/pectin/carrageenan in different blending ratios (100:0, 75:25, 50:50, 25:75, and 0:100) with and without addition of CaCl₂. The synergism effect is obtained from the design of experimental (DoE), and calculati

A general mathematical model for a fixed bed immobilized enzyme reactor was developed to simulate the process of diffusion and reaction inside the biocatalyst particle. The modeling and simulation of starch hydrolysis using immobilized α-amylase were used as a model for this study. Corn starch hydrolysis was carried out at a constant pH of 5.5 and temperature of . The substrate flow rate was ranging from 0.2 to 5.0 mL/min, substrate initial concentrations 1 to 100 g/L. α-amylase was immobilized on to calcium alginate hydrogel beads of 2 mm average diameter. In this work Michaelis-Menten kinetics have been considered. The effect of substrate flow rate (i.e., residence time

This paper is summarized with one of the applications of adsorption behavior; A UV-Vis method has been applied to survey the isotherm of adsorption. Results for experimental showed the applicability of Langmuir equation. The effect of temperature on the adsorption of cobalt (II) Complex by bentonite surface was studied. The results shown that the amount of adsorption was formed to increase, such as the temperature increase (Endothermic process). Cobalt (II) Complex has adsorption studies by bentonite surface at different pH values (1.6-10); these studies displayed an increase in adsorption with increasing pH. ΔG, ΔH, and ΔS thermodynamic functions of the cobalt (II) Complex for their adsorption have been calculated.

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

An analytical method and a two-dimensional finite element model for treating the problem of laser heating and melting has been applied to aluminum 2519T87and stainless steel 304. The time needed to melt and vaporize and the effects of laser power density on the melt depth for two metals are also obtained. In addition, the depth profile and time evolution of the temperature before melting and after melting are given, in which a discontinuity in the temperature gradient is obviously observed due to the latent heat of fusion and the increment in thermal conductivity in solid phase. The analytical results that induced by  laser irradiation is in good agreement with numerical results.