Objective: The purpose of this work was to develop and optimize the emulgel formulation of piroxicam with two types of gelling agent chitosan and xanthan gum. The release profiles of prepared formulas were investigated. In addition, the rheology and stability of the best formula were investigated.Methods: Emulsified piroxicam was prepared to use oleic acid, tween 80 and PG with a ratio (3:10:10). In xanthan based emulgel, the xanthan gum (1% and 1.5%) was spread as powder on emulsified piroxicam with stirring until emulgel was formed. In chitosan-based emgels, Chitosan gel was added to emulsified piroxicam and stirring until the Emulgel was constructed. Chitosan gels were prepared by incorporating different concentration, 2%, 3%, 6%

 The general approach of this research is to assume that the small nonlinearity can be separated from the linear part of the equation of motion. The effect of the dynamic fluid force on the pump structure system is considered vibrates at its natural frequency but the amplitude is determined by the initial conditions. If the motion of the system tends to increase the energy of the pump structure system, the vibration amplitude will increase and the pump structure system is considered to be unstable. A suitable MATLAB program was used to predict the stability conditions of the pump structure vibration. The present research focuses on fluid pump problems, namely, the role played by damping coefficient C, damping factor

Asphaltene is one of the fractions of the crude oil which is soluble in aromatics such as benzene or toluene and insoluble in alkane such as n-heptane, n-pentane or petroleum ether (mixture of alkane compounds).  Asphaltene precipitation is one of the most common problems that sometimes occurs in both oil recovery and refinery processes as a result of changing in pressure, oil composition, or temperature. Therefore the stability of asphaltene in the crude oil must be studied to show the tendency of it for precipitating asphaltene to prevent it (Asphaltene precipitation and deposition problem) and eliminate the burden of high treatment costs.

In the present study, saturate, aromatic, resin and asphaltene (SAR

This study focuses on synthesizing Niobium pentoxide (Nb2O5) thin films on silicon wafers and quartz substrates using DC reactive magnetron sputtering for NO2 gas sensors. The films undergo annealing in ambient air at 800 °C for 1 hr. Various characterization techniques, including X-ray diffraction (XRD), atomic force microscopy (AFM), energy-dispersive X-ray spectroscopy (EDS), Hall effect measurements, and sensitivity measurements, are employed to evaluate the structural, morphological, electrical, and sensing properties of the Nb2O5 thin films. XRD analysis confirms the polycrystalline nature and hexagonal crystal structure of Nb2O5. The optical band gap values of the Nb2O5 thin films demonstrate a decrease from 4.74 to 3.73 eV

This study focuses on synthesizing Niobium pentoxide (Nb₂O₅) thin films on silicon wafers and quartz substrates using DC reactive magnetron sputtering for NO₂ gas sensors. The films undergo annealing in ambient air at 800 °C for 1 hr. Various characterization techniques, including X-ray diffraction (XRD), atomic force microscopy (AFM), energy-dispersive X-ray spectroscopy (EDS), Hall effect measurements, and sensitivity measurements, are employed to evaluate the structural, morphological, electrical, and sensing properties of the Nb₂O₅ thin films. XRD analysis confirms the polycrystalline nature and hexagonal crystal structure of Nb₂O₅. The optical band gap val

The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge

Liquid-side mass-transfer coefficients (K_La) were measured in air-suction type fermentors using physical absorption of oxygen.  A fermentor of 0. 5 m i.d. was used with a working capacity of 60 liters of liquid. Tap water was used as the liquid phase, and air was used as the gas phase. The bioreactor mixing system consists of shrouded-disk/curved-blade turbine with six evacuated bending blades. The effect of liquid submergence (S) was investigated. Further, the effects of the ratio of the impeller diameter (D) to the tank diameter (T), and the clearance of the impeller from the tank bottom(C) were also studied.  The agitation speed (N) was varied in the range of 50-800 rpm. It was found that the value of  K

This study is concentrated to investigate the effects of aeration and stirring speed on the volumetric mass transfer coefficient (KLa). A dynamic technique was used in estimating KLa values in order to achieve the aim of this study.

This study was done in 10L bioreactor by using two medias:-

1. Dionized water
2. Xanthan solution (1 g /L)

Moreover, the research covered a comparison between the obtained values of KLa.

The Xanthan solution was used because of its higher viscosity in comparison with water. It behaves similarly to the cultivation medium when organisms are cultivated in a bioreactor. Growth of organisms in the reactor l

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc