The disposal of textile effluents to the surface water bodies represents the critical issue especially these effluents can have negative impacts on such bodies due to the presence of dyes in their composition. Biological remediation methods like constructed wetlands are more cost-effective and environmental friendly technique in comparison with traditional methods. The ability of vertical subsurface flow constructed wetlands units for treating of simulated wastewater polluted with Congo red dye has been studied in this work. The units were packed with waterworks sludge bed that either be unplanted or planted with Phragmites australis and Typha domingensis. The efficacy of present units was evaluated by monitoring of DO, Temperature, COD

The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

In the present work, a density functional theory (DFT) calculation to simulate reduced graphene oxide (rGO) hybrid with zinc oxide (ZnO) nanoparticle's sensitivity to NO2 gas is performed. In comparison with the experiment, DFT calculations give acceptable results to available bond lengths, lattice parameters, X-ray photoelectron spectroscopy (XPS), energy gaps, Gibbs free energy, enthalpy, entropy, etc. to ZnO, rGO, and ZnO/rGO hybrid. ZnO and rGO show n-type and p-type semiconductor behavior, respectively. The formed p-n heterojunction between rGO and ZnO is of the staggering gap type. Results show that rGO increases the sensitivity of ZnO to NO2 gas as they form a hybrid. ZnO/rGO hybrid has a higher number of vacancies that can b

Coronary artery disease (CAD) is the leading cause of death worldwide. Certain genetic polymorphisms play an important role in this multifactorial disease, being linked with increased risk of early onset CAD.

In this research, annealed nanostructured ZnO catalyst water putrefaction system was built using sun light and different wavelength lasers as stimulating light sources to enhance photocatalytic degradation activity of methylene blue (MB) dye as a model based on interfacial charges transfer. The structural, crystallite size, morphological, particle size, optical properties and degradation ability of annealed nanostructured ZnO were characterized by X-Ray Diffraction (XRD), Atomic Force Microscopy (AFM) and UV-VIS Spectrometer, respectively. XRD results demonstrated a pure crystalline hexagonal wurtzite with crystalline size equal to 23 nm. From AFM results, the average particle size was 79.25nm. All MB samples and MB with annealed nanostr

 In this paper, an intelligent tracking control system of both single- and double-axis Piezoelectric Micropositioner stage is designed using Genetic Algorithms (GAs) method for the optimal Proportional-Integral-Derivative (PID) controller tuning parameters. The (GA)-based PID control design approach is a methodology to tune a (PID) controller in an optimal control sense with respect to specified objective function. By using the (GA)-based PID control approach, the high-performance trajectory tracking responses of the Piezoelectric Micropositioner stage can be obtained. The (GA) code was built and the simulation results were obtained using MATLAB environment. The Piezoelectric Micropositioner simulation model with th

Improved oral bioavailability of lipophilic substances can be achieved using self-emulsifying drug delivery systems. However, because the properties of self-emulsifying are greatly influenced by surfactant amount and type, type of oil used, droplet size, charge, cosolvents, and physiological variables, the synthesis of self-emulsifying is highly complex; consequently, only a small number of excipient self-emulsifying formulations has been developed so far for clinical use. This study reports a highly effective procedure for developing self-emulsifying formulations using a novel approach based on the hydrophilic-lipophilic difference theory. Microemulsion characteristics, such as the constituents and amounts of oil and surfactant electrolyte