In this research, the removal of cadmium (Cd) from simulated wastewater was investigated by using a fixed bed bio-electrochemical reactor. The effects of the main controlling factors on the performance of the removal process such as applied cell voltage, initial Cd concentration, pH of the catholyte, and the mesh number of the cathode were investigated. The results showed that the applied cell voltage had the main impact on the removal efficiency of cadmium where increasing the applied voltage led to higher removal efficiency. Meanwhile increasing the applied voltage was found to be given lower current efficiency and higher energy consumption.  No significant effect of initial Cd concentration on the removal efficie

In this research, the removal of cadmium (Cd) from simulated wastewater was investigated by using a fixed bed bio-electrochemical reactor. The effects of the main controlling factors on the performance of the removal process such as applied cell voltage, initial Cd concentration, pH of the catholyte, and the mesh number of the cathode were investigated. The results showed that the applied cell voltage had the main impact on the removal efficiency of cadmium where increasing the applied voltage led to higher removal efficiency. Meanwhile increasing the applied voltage was found to be given lower current efficiency and higher energy consumption.  No significant effect of initial Cd concentration on the removal efficiency of cadmium b

This study concerns the removal of a trihydrate antibiotic (Amoxicillin) from synthetically contaminated water by adsorption on modified bentonite. The bentonite was modified using hexadecyl trimethyl ammonium bromide (HTAB), which turned it from a hydrophilic to a hydrophobic material. The effects of different parameters were studied in batch experiments. These parameters were contact time, solution pH, agitation speed, initial concentration (C0) of the contaminant, and adsorbent dosage. Maximum removal of amoxicillin (93 %) was achieved at contact time = 240 min, pH = 10, agitation speed = 200 rpm, initial concentration = 30 ppm, and adsorbent dosage = 3 g bentonite per 1L of pollutant solution. The characterization of the adsorbent, modi

Thirty nine (12.8%) isolates of Staphylococcus aureus were isolated from 304 healthy human (Nasal swabs). It was found that percentage of males that have S. aureus is more than female's percentage. These isolates (39) were tested with different tests. Twenty seven isolates (69.23 %) were positive for Staphylococcus protein —A (SPA) ,thirty seven ( 94.8 %) were positive for tube coagulase , thirty five ( 89.7 % ) were positive with clumping factor and thirty two ( 82.05 %) had 13 — hemolytic on blood agar. It was found that 100% of the isolates (39 isolates) were positive with one, two or three tests (tube coagulase, clumping factor and SPA).

The aim of the present study was to develop theophylline (TP) inhalable sustained delivery system by preparing solid lipid microparticles using glyceryl behenate (GB) and poloxamer 188 (PX) as a lipid carrier and a surfactant respectively. The method involves loading TP nanoparticles into the lipid using high shear homogenization – ultrasonication technique followed by lyophilization. The compositional variations and interactions were evaluated using response surface methodology, a Box – Behnken design of experiment (DOE). The DOE constructed using TP (X₁), GB (X₂) and PX (X₃) levels as independent factors. Responses measured were the entrapment efficiency (% EE) (Y₁), mass median

Molasse medium containing different concentrations of (NH4)2 SO4, (NH4)3 PO4, urea, KCI, and P2O5 were compared with the medium used for commercial production of C. utilis in a factory south of Iraq. An efficient medium, which produced 19. 16% dry wt. and 5. 78% protein, was developed. The effect of adding various concentrations of micronutrients (FeSO4, 7T20, MnSO4. 7H20, ZnSO4. 7E20) was also studied. Results showed that FeSo4. 7H20 caused a noticeable increase in both dry wt. and protein content of the yeast.

Several attempts have been made to modify the quasi-Newton condition in order to obtain rapid convergence with complete properties (symmetric and positive definite) of the inverse of  Hessian matrix (second derivative of the objective function). There are many unconstrained optimization methods that do not generate positive definiteness of the inverse of Hessian matrix. One of those methods is the symmetric rank 1( H-version) update (SR1 update), where this update satisfies the quasi-Newton condition and the symmetric property of inverse of Hessian matrix, but does not preserve the positive definite property of the inverse of Hessian matrix where the initial inverse of Hessian matrix is positive definiteness. The positive definite prope

This research proposes the application of the dragonfly and fruit fly algorithms to enhance estimates generated by the Fama-MacBeth model and compares their performance in this context for the first time. To specifically improve the dragonfly algorithm's effectiveness, three parameter tuning approaches are investigated: manual parameter tuning (MPT), adaptive tuning by methodology (ATY), and a novel technique called adaptive tuning by performance (APT). Additionally, the study evaluates the estimation performance using kernel weighted regression (KWR) and explores how the dragonfly and fruit fly algorithms can be employed to enhance KWR. All methods are tested using data from the Iraq Stock Exchange, based on the Fama-French three-f

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a