A new simple and sensitive spectrophotometric method for the determination of trace amount of Co(II) in the ethanol absolute solution have been developed. The method is based on the reaction of Co(II) with ethyl cyano(2-methyl carboxylate phenyl azo acetate) (ECA) in acid medium of hydrochloric acid (0.1 M) givining maximum absorbance at ((λmax = 656 nm). Beer's law is obeyed over the concentration range (5-60) (μg / ml) with molar absorptivity of (1.5263 × 103 L mol-1 cm-1) and correlation coefficient (0.9995). The precision (RSD% ˂ 1%). The stoichiometry of complex was confirmed by Job's method which indicated the ratio of metal to reagent is (2:1). The studied effect of interference elements Zn(II), Cu(II), Na(I), K(I), Ca(II) and Mg

In this paper, a new third kind Chebyshev wavelets operational matrix of derivative is presented, then the operational matrix of derivative is applied for solving optimal control problems using, third kind Chebyshev wavelets expansions. The proposed method consists of reducing the linear system of optimal control problem into a system of algebraic equations, by expanding the state variables, as a series in terms of third kind Chebyshev wavelets with unknown coefficients. Example to illustrate the effectiveness of the method has been presented.

The use of Near-Surface Mounted (NSM) Carbon-Fiber-Reinforced Polymer (CFRP) strips is an efficient technology for increasing flexural and shear strength or for repairing damaged Reinforced Concrete (RC) members. This strengthening method is a promising technology. However, the thin layer of concrete covering the NSM-CFRP strips is not adequate to resist heat effect when directly exposed to a fire or at a high temperature. There is clear evidence that the strength and stiffness of CFRPs severely deteriorate at high temperatures. Therefore, in terms of fire resistance, the NSM technique has a significant defect. Thus, it is very important to develop a set of efficient fire protection systems to overcome these disadvantages. This pape

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

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.

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