Meloxicam is a non-steroidal anti-inflammatory drug. It is practically insoluble in water. It is associated with gastrointestinal side effects at high doses on long  term treatment. The aim of this investigation to formulate and evaluate gellified nanoemulsion of meloxicam as a topical dosage form to enhance meloxicam therapeutic activity and reduce systemic side effect.

The pseudo ternary phase diagrams were made, including  the oil mixture which is composed of almond oil and peppermint oil at a ratio (1:2), variable surfactant mixture (S mix) which are tween 80 and ethanol at ratios of (1:1, 2:1, 3:1, and 4:1) and double distilled water. Slow dripping of double distilled water to the combination  of the oil mixtu

         Darifenacin hydrobromide (DH) is the more recent uroselective M3 receptor antagonist for treating uncomplicated overactive bladder (OAB). This study was aimed to formulate DH as fast dissolving buccal films (FDBFs) using a solvent casting method to enhance patient’s compliance.

         Films were prepared by using polyvinyl alcohol (PVA) as a film forming polymer. Different types and concentrations of superdisintegrants (croscarmellose sodium, sodium starch glycolate, indion 414) were used to select the best formula by studying the physicochemical properties of the films, disintegration time (DT) and percent drug release.

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Oral jelly is a semisolid preparation that could resolve problem associated withdosage form’s swallowing, especially in pediatric and elderly ones. This work aimedto prepare oral flurbiprofen (FBP) jelly to improve patient compliance. Heating andcongealing method was used to prepare FBP jelly using three different polymers (pectin,sodium carboxymethyl cellulose, and hydroxypropyl methylcellulose). The effect ofdifferent concentrations of pectin and sucrose on jelly properties was studied. Theresults revealed that both pectin and sodium carboxymethyl cellulose polymers gaveacceptable jelly appearance and consistency. It was also observed that the increase ofpectin or sucrose concentration had a significant impact on jelly viscosity. All pe

Modeling forward kinematics with neural networks allows for efficient handling of nonlinear relationships and realistic error correction in time-critical applications by relying on accurate training data. This paper presents a Multi-Layer Feed-Forward Neural Network (MLFFNN) to solve the forward kinematics of a 3-DOF robot. The proposed MLFFNN consists of 50 hidden neurons and was trained using 628319 samples to find only the position (x, y, z) of the end-effector. Data were generated by MATLAB, assuming an incremental motion of joints. The joint variables ( , , and ) are the inputs of the NN, which outputs the positions of the end effector (x, y, z) calculated using the Denavit-Hartenberg (DH) method. The results demonstrate that t

A general velocity profile for a laminar flow over a flat plate with zero incidence is obtained by employing a new boundary condition to the other available boundary conditions. The general velocity profile is mathematically simple and nearest to the exact solution. Also other related values, boundary layer thickness, displacement thickness, momentum thickness and coefficient of friction are nearest to the exact solution compared with other corresponding values for other researchers.

A general velocity profile for a laminar flow over a flat plate with zero incidence is obtained by employing a new boundary condition to the other available boundary conditions. The general velocity profile is mathematically simple and nearest to the exact solution. Also other related values, boundary layer thickness, displacement thickness, momentum thickness and coefficient of friction are nearest to the exact solution compared with other corresponding values for other researchers.

The primary components of successful engineering projects are time, cost, and quality. The use of the ring footing ensures the presence of these elements. This investigation aims to find the optimum number of geogrid reinforcement layers under ring footing subjected to inclined loading. For this purpose, experimental models were used. The parameters were studied to find the optimum geogrid layers number, including the optimum geogrid layers spacing and the optimum geogrid layers number. The optimum geogrid layers spacing value is 0.5B. And as the load inclination angle increased, the tilting and the tilting improvement percent for the load inclination angles (5°,10°,15°) are (40%,28%, and 5%) respectively. The reduction percent of the