This study depicts the removal of Manganese ions (Mn²⁺) from simulated wastewater by combined electrocoagulation/ electroflotation technologies. The effects of initial Mn concentration, current density (C.D.), electrolysis time, and different mesh numbers of stainless steel screen electrodes were investigated in a batch cell by adopting Taguchi experimental design to explore the optimum conditions for maximum removal efficiency of Mn. The results of multiple regression and signal to noise ratio (S/N) showed that the optimum conditions were Mn initial concentration of 100 ppm, C.D. of 4 mA/cm², time of 120 min, and mesh no. of 30 (wire/inch). Also, the relative significance of each factor was attained by the analysis

This study depicts the removal of Manganese ions (Mn2+) from simulated wastewater by combined electrocoagulation/ electroflotation technologies. The effects of initial Mn concentration, current density (C.D.), electrolysis time, and different mesh numbers of stainless steel screen electrodes were investigated in a batch cell by adopting Taguchi experimental design to explore the optimum conditions for maximum removal efficiency of Mn. The results of multiple regression and signal to noise ratio (S/N) showed that the optimum conditions were Mn initial concentration of 100 ppm, C.D. of 4 mA/cm2, time of 120 min, and mesh no. of 30 (wire/inch). Also, the relative significance of each factor was attained by the analysis of variance (ANO

The current research dealt with the issue of organizational skillfulness as an entry point to reach strategic agility. The study has been tested in Iraq's mobile operators - Asia Cell, Zain Iraq and Cork Telecom. The study was applied to a sample of (93) managers distributed at various levels of management (board members, general managers, commissioners, department managers, people managers, unit managers, office managers). The survey used the questionnaire as a key tool for collecting data and information as well as personal interviews. It has sought to test a number of hypotheses related to correlation and influence relationships between the variables of the study, in order to answer the questions related to the problem of stud

The article describes a study on the role of vitamin C as a protective agent for the teeth, gum, and implants using quantum chemical calculations and polarization tests. The Density Functional Theory (DFT) at 6-311G (d, p) basis set is used to estimate the ability of vitamin C to inhibit the corrosion of the abovementioned parts. The experimental study was performed in a at human body media simulator (Hank’s balanced salt solution) at a temperature of 37°C. The compound was optimized for its ground state, physical properties, and corrosion parameters. Further, HOMO, LUMO, energy gap, dipole moment, and other parameters were used to predict the inhibitor’s efficiency. Gaussian 09, UCA-FUKUI, MGL tools, DSV, and LigPlus software was used

Background: Glass ionomer restorations are widely employed in the field of pediatric dentistry. There is a constant demand for a durable restoration that remains functional until exfoliation. This study aimed to measure and compare the effect of a novel coating material (EQUIA Forte Coat) on the microleakage of glass hybrid restoration (EQUIA Forte HT) in primary teeth. Material and method: Thirty cavitated (class-II) primary molars were allocated randomly into two groups based on the coat application; uncoated (control) and coated group (experimental). Cavities were prepared by the use of a ceramic bur (CeraBur) and restored with EQUIA Forte HT with or without applying a protective coat (EQUIA Forte Coat). Samples went through the therm

Background: Glass ionomer restorations are widely employed in the field of pediatric dentistry. There is a constant demand for a durable restoration that remains functional until exfoliation. This study aimed to measure and compare the effect of a novel coating material (EQUIA Forte Coat) on the microleakage of glass hybrid restoration (EQUIA Forte HT) in primary teeth. Material and method: Thirty cavitated (class-II) primary molars were allocated randomly into two groups based on the coat application; uncoated (control) and coated group (experimental). Cavities were prepared by the use of a ceramic bur (CeraBur) and restored with EQUIA Forte HT with or without applying a protective coat (EQUIA Forte Coat). Samples went through the

In this paper, a new tunable approach for fusion the satellite images that fall in different electromagnetic wave ranges is presented, which gives us the ability to make one of the images features little superior on the other without reducing the general resultant image fusion quality, this approach is based on the principal component analysis (PCA) fusion method. A comparison made is between the results of the proposed approach and two fusion methods (they are: the PCA fusion method and the projection of eigenvectors on the bands fusion method), and the comparison results show the validity of this new method.

This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

One of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed