Excessive intake of fluoride, mainly through drinking water is a serious health hazard affecting humans worldwide. In this study, the defluoridation capacities of locally available raw waste beef bones have been estimated. Several experimental parameters including contact time, pH, bone dose, fluoride initial concentration, bone grains size, agitation rate, and the effect of co-existence of anions in actual samples of wastewater were studied for fluoride removal from aqueous solutions. Results indicated excellent fluoride removal effeciency up to 99.7% at fluoride initial concentration of 10 mg F/L and 120 min contact time. Maximum fluoride uptake was obtained at neutral pH range 6-7. Fluoride removal kinetic was well described by the ps

Water pollution as a result of contamination with dye-contaminating effluents is a severe issue for water reservoirs, which instigated the study of biodegradation of Reactive Red 195 and Reactive Blue dyes by E. coli and Bacillus sp. The effects of occupation time, solution pH, initial dyes concentrations, biomass loading, and temperature were investigated via batch-system experiments by using the Design of Experiment (DOE) for 2 levels and 5 factors response surface methodology (RSM). The operational conditions used for these factors were optimized using quadratic techniques by reducing the number of experiments. The results revealed that the two types of bacteria had a powerful effect on biodegradable dyes. The regression analysis reveale

In this work, pure and Ag-doped nickel oxide (NiO) thin films were deposited on glass substrates with different dopant concentrations (0.1, 0.2, 0.3 and 0.4 wt.%) by pulsed-laser deposition (PLD) technique at room temperature. These films were annealed at temperature of 450 °C. The structural and optical properties of the prepared thin films were studied. It was found that annealing process has lead to increase the transmittance of the deposited films. Also, the transmittance was found to increase with doping concentration of silver in the deposited NiO films. The optical energy gap was decreased from 3.5 to 3.2 eV as the doping concentration was increased to 0.4 %.

This article presents the results of an experimental investigation of using carbon fiber–reinforced polymer sheets to enhance the behavior of reinforced concrete deep beams with large web openings in shear spans. A set of 18 specimens were fabricated and tested up to a failure to evaluate the structural performance in terms of cracking, deformation, and load-carrying capacity. All tested specimens were with 1500-mm length, 500-mm cross-sectional deep, and 150-mm wide. Parameters that studied were opening size, opening location, and the strengthening factor. Two deep beams were implemented as control specimens without opening and without strengthening. Eight deep beams were fabricated with openings but without strengthening, while

The insulation system of a machine coil includes several layers made of materials with different characteristics. The effective insulation design of machine coils, especially in the machine end winding, depends upon an accurate model of the stress grading system. This paper proposes a modeling approach to predict the transient overvoltage, electric field, and heat generation in machine coils with a stress grading system, considering the variation of physical properties in the insulation layers. A non-uniform line model is used to divide the coil in different segments based on material properties and lengths: overhang, stress grading and slot. The cascaded connection of chain matrices is used to connect segments for the representation of the

The Weibull distribution is considered one of the Type-I Generalized Extreme Value (GEV) distribution, and it plays a crucial role in modeling extreme events in various fields, such as hydrology, finance, and environmental sciences. Bayesian methods play a strong, decisive role in estimating the parameters of the GEV distribution due to their ability to incorporate prior knowledge and handle small sample sizes effectively. In this research, we compare several shrinkage Bayesian estimation methods based on the squared error and the linear exponential loss functions. They were adopted and compared by the Monte Carlo simulation method. The performance of these methods is assessed based on their accuracy and computational efficiency in estimati

Nitrogen dioxide NO₂ is one of the most dangerous contaminant in the air, its toxic gas that cause disturbing respiratory effects, most of it emitted from industrial sources especially from the stack of power plants and oil refineries. In this study Gaussian equations modelled by Matlab program to state the effect of pollutant NO₂ gas on area around Durra refinery, this program also evaluate some elements such as wind and stability and its effect on stacks height. Data used in this study is the amount of fuel oil and fuel gas burn inside refinery at a year 2017. Hourly April month data chosen as a case study because it’s unsteady month. After evaluate emission rate of the all fuel and calculate exit velocity from

This paper presents a method to organize memory chips when they are used to build memory systems that have word size wider than 8-bit. Most memory chips have 8-bit word size. When the memory system has to be built from several memory chips of various sizes, this method gives all possible organizations of these chips in the memory system. This paper also suggests a precise definition of the term “memory bank” that is usually used in memory systems. Finally, an illustrative design problem was taken to illustrate the presented method practically

Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal.  The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in