Gypseous soil is a collapsible soil, which causes large deformations in buildings that are constructed on it. Various methods have been used to minimise this effect, such as replacing the gypseous soil or using soil stabilisation (grouting or soil improvement). This study was carried out on four types of gypseous soils that have different properties and various gypsum contents. The testing was carried out on remoulded samples to evaluate the compressibility of gypseous soil under different conditions. The samples were grouted with acrylate liquid. The relationships between the injection pressure and the radius of flow, between time of injection and radius of flow, and between time and quantity of acrylate liquid are investigated on

For desulfurization of naphtha, NaY zeolite was prepared from Dewekhala kaolin clay (Al-Anbar region). For the prepared zeolite adsorbent, x-ray diffraction, sodium content, silica to alumina ratio, surface area, bulk density and crushing strength were determined. From the x-ray diffraction of the prepared NaY zeolite and by a comparison with the standard NaY zeolite, it was found that the prepared adsorbent in this work has approximately the same crystal structure as the standard. Adsorption process was done in a laboratory unit at 25

Carbon Nanopowder was fabricated by arc discharge technique at deposition pressure of 10-5 mbar Argon gas on glass substrates. The prepared carbon nano- powder was collected from chamber and purified with nitric acid at 323K .The morphology and crystalline structure of the prepared powder was examined by X-Ray Diffraction (XRD), Atomic Force Microscope (AFM), and Scanning Electron Microscope (SEM). XRD spectrums showed that the powder exhibits amorphous structure and after purification, the powder showed hexagonal structure with a preferential orientation along(002) direction ,where AFM and SEM gave very compatible estimation on the grain size and shape of the nanopowder.

In this paper, we deal with games of fuzzy payoffs problem while there is uncertainty in data. We use the trapezoidal membership function to transform the data into fuzzy numbers and utilize the three different ranking function algorithms. Then we compare between these three ranking algorithms by using trapezoidal fuzzy numbers for the decision maker to get the best gains

Abstract. Shock chlorination is a well-known practice in swimming pools and domestic wells. One of the limitations for using this technique in drinking water purification facilities is the difficulty of quickly removing high chlorine concentrations in water distribution systems or production facilities. In order to use this method in the drinking water industry a shock de-chlorination method should be introduced for producing microorganism and biocide free water. De-chlorination using natural stagnant aeration (leaving the water to lose the chlorine naturally) is the safest known method if compared with chemical and charcoaling methods. Unfortunately, stagnant aeration is a slow process. Therefore, developing a process for accelerat

Abstract. The main technique for removing bacteria from water for various applications is chemical disinfection. However, this method has many disadvantages such as producing disinfectant by-products (DBPs), biofilm formation and either rendering the water unpotable (at high residual disinfection) or leaving a potential for lethal diseases such as Cholera (if the residual disinfection is too low). Recently, a process was developed for continuous removal of bacteria from water using the principle of froth flotation through compressed air only without any chemicals (Hassan, 2015). This work examines the extent to which chemical free froth flotation can purify drinking water. The experiments were carried out using two flotation columns

In this research, a mathematical model of tumor treatment by radiotherapy is studied and a new modification for the model is proposed as well as introducing the check for the suggested modification. Also the stability of the modified model is analyzed in the last section.

In this article, the high accuracy and effectiveness of forecasting global gold prices are verified using a hybrid machine learning algorithm incorporating an Adaptive Neuro-Fuzzy Inference System (ANFIS) model with Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO). The hybrid approach had successes that enabled it to be a good strategy for practical use. The ARIMA-ANFIS hybrid methodology was used to forecast global gold prices. The ARIMA model is implemented on real data, and then its nonlinear residuals are predicted by ANFIS, ANFIS-PSO, and ANFIS-GWO. The results indicate that hybrid models improve the accuracy of single ARIMA and ANFIS models in forecasting. Finally, a comparison was made between the hybrid foreca

A nano manganese dioxide (MnO₂) was electrodeposited galvanostatically onto a carbon fiber (CF) surface using the simple method of anodic electrodeposition. The composite electrode was characterized by field emission scanning electron microscopy (FESEM), and X-ray diffraction (XRD). Very few studies investigated the efficiency of this electrode for heavy metals removal, especially chromium. The electrosorption properties of the nano MnO₂/CF electrode were examined by removing Cr(VI) ions from aqueous solutions. NaCl concentration, pH, and cell voltage were studied and optimized using the Box-Behnken design (BDD) to investigate their effects and interactions on the electrosorption process. The results showed that the