A new nano-sized NiMo/TiO2-γ-Al2O3 was prepared as a Hydrodesulphurization catalyst for Iraqi gas oil with sulfur content of 8980 ppm, supplied from Al-Dura Refinery. Sol-gel method was used to prepare TiO2- γ-Al2O3 nano catalyst support with 64% TiO2, 32% Al2O3, Ni-Mo/TiO-γ-Al2O3 catalyst was prepared under vacuum impregnation conditions to loading metals with percentage 3.8 wt.% and 14 wt.% for nickel and molybdenum respectively while the percentage for alumina, and titanium became 21.7, and 58.61 respectively. The synthesized TiO2- γ-Al2O3 nanocomposites and Ni-Mo /TiO2- γ-Al2O3 Nano catalyst were then characterized by XRD, AFM, and BET surface area, SEM, XRF, and FTIR. The performance of the synthesized catalyst for removing sulfur compounds was conducted through the pilot HDS laboratory unit, various temperatures range 275oC to 375°C, LHSV 1 h-1 were studied; moreover, the effect of LHSV 1 to 4 h-1 on the percentage of sulfur removal was also studied at the temperature of the best removal with constant pressure 35 bar and H2/HC ratio 200cm3/200cm3. The sulfur content results generally revealed that there was a substantial decrease at all operating conditions used, while the maximum sulfur removal was 87.75% in gas oil on Ni-Mo/TiO2-γ-Al2O3 catalyst at temperature 375˚C and LHSV 1h-1.
Drones are highly autonomous, remote‐controlled platforms capable of performing a variety of tasks in diverse environments. A digital twin (DT) is a virtual replica of a physical system. The integration of DT with drones gives the opportunity to manipulate the drone during a mission. In this paper, the architecture of DT is presented in order to explain how the physical environment can be represented. The techniques via which drones are collecting the necessary information for DT are compared as a next step to introduce the main methods that have been applied in DT progress by drones. The findings of this research indicated that the process of incorporating DTs into drones will result in the advanc
Generalized multivariate transmuted Bessel distribution belongs to the family of probability distributions with a symmetric heavy tail. It is considered a mixed continuous probability distribution. It is the result of mixing the multivariate Gaussian mixture distribution with the generalized inverse normal distribution. On this basis, the paper will study a multiple compact regression model when the random error follows a generalized multivariate transmuted Bessel distribution. Assuming that the shape parameters are known, the parameters of the multiple compact regression model will be estimated using the maximum likelihood method and Bayesian approach depending on non-informative prior information. In addition, the Bayes factor was used
... Show MoreThe main object of this study is to solve a system of nonlinear ordinary differential equations (ODE) of the first order governing the epidemic model using numerical methods. The application under study is a mathematical epidemic model which is the influenza model at Australia in 1919. Runge-kutta methods of order 4 and of order 45 for solving this initial value problem(IVP) problem have been used. Finally, the results obtained have been discussed tabularly and graphically.
Despite the G protein-coupled receptors (GPCRs) being the largest family of signalling proteins at the surface of cells, their potential to be targeted in cancer therapy is still under-utilised. This review highlights the contribution of these receptors to the process of oncogenesis and points to some likely challenges that might be encountered in targeting them. GPCR-signalling pathways are often complex and can be tissue-specific. Cancer cells hijack these communication networks to their proliferative advantage. The role of selected GPCRs in the different hallmarks of cancer is examined to highlight the complexity of targeting these receptors for therapeutic benefit. Our
... Show MoreThis paper proposed a theoretical treatment to study underwater wireless optical communications (UWOC) system with different modulation schemes by multiple input-multiple output (MIMO) technology in coastal water. MIMO technology provides high-speed data rates with longer distance link. This technique employed to assess the system by BER, Q. factor and data rate under coastal water types. The reliability of the system is examined by the techniques of 1Tx/1Rx, 2Tx/2Rx, 3Tx/3Rx and 4Tx/4Rx. The results shows the proposed technique by MIMO can get the better performance compared with the other techniques in terms of BER. Theoretical results were obtained to compare between PIN and APD
Survivin, a member of inhibitor of apoptosis family is increasingly used as a target for cancer therapy design because it has a key role in cell growth and inhibition of cell apoptosis. Also it can be used as a biomarker for targeting cancer because it is found in almost all cancer but not normal cells. Our strategy was to design (computationally) a molecule to be used as survivin inhibitor. This molecule was named lead10 and was used furthermore to find (virtually) existing drugs with a good survivin inhibition activity.
Most of the water pollutants with dyes are leftovers from industries, including textiles, wool and others. There are many ways to remove dyes such as sorption, oxidation, coagulation, filtration, and biodegradation, Chlorination, ozonation, chemical precipitation, adsorption, electrochemical processes, membrane approaches, and biological treatment are among the most widely used technologies for removing colors from wastewater. Dyes are divided into two types: natural dyes and synthetic dyes.
Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre
... Show MoreThe energy expectation values for Li and Li-like ions ( , and ) have been calculated and examined within the ground state and the excited state in position space. The partitioning technique of Hartree-Fock (H-F) has been used for existing wave functions.