In this research, the structural behavior of reinforced concrete columns made of normal and hybrid reactive powder concrete (hybrid by steel and polypropylene fibers) subjected to chloride salts with concentration was 8341.6 mg/l. The study consists of two parts, the first one is experimental study and the second one is theoretical analysis.  Three main variables were adopted in the experimental program; concrete type, curing type and loading arrangement. Twenty (120x120x1200) mm columns were cast and tested depending on these variables. The samples were reinforced using two different bars; Ø8 for ties and Ø12 with minimum longitudinal reinforcement (0.01Ag). The specimens were divided into two main groups based o

The electronic characteristics, including the density of state and bond length, in addition to the spectroscopic properties such as IR spectrum and Raman scattering, as a function of the frequency of Sn₁₀O₁₆, C₂₄O_6, and hybrid junction (Sn₁₀O₁₆/C₂₄O₆) were studied. The methodology uses DFT for all electron levels with the hybrid function B3-LYP (Becke level, 3-parameters, Lee–Yang-Parr), with 6-311G (p,d)  basis set, and Stuttgart/Dresden (SDD) basis set, using Gaussian 09 theoretical calculations. The geometrical structures were calculated by Gaussian view 05 as a supplementary program. The band gap was calculated and compared to the measured valu

As a result of industrial development, many types of waste are generated, some of which are discharged into water, causing water pollution and having a negative impact on life. The electro-Fenton process (EF) has verified high efficiency in treating pollutants with low cost, ease of handling and operation, and this technology is one of the more efficient advanced oxidation technologies. The main objective of this present work is to explore the efficiency of a three-dimensional Electro-Fenton system (3DEF) in removing eosin, methylene blue, and methylene violet from simulated wastewater using graphite as anode, nickel foam as the cathode, and alum sludge as the third particle and as the source of catalyst. The study investigated the effect o

New heterocyclic derivatives of quinoline are reported. Reaction of quinoline-2-thiol 4 with hydrazine hydrate gave 2-hydrazionoquinoline 5. Treatment of 5 with CS2 in pyridine afforded 1,2,4-triazolo-[4,3-a]- quinolin-1-2H-thione 6, whereas the reaction of 5 with carboxylic acids namely formic acid or acetic acid, yielded the 1,2,4-triazol-[4,3-a]-quinolin 7 or 5-methyl-1,2,4-triazolo [4,3-a]-quinoline 8 through ring closure. Diazotization of 5 under acidic conditions produced the fused tetrazole compound 9, tetrzolo-[1,5-a]- quinoline. Moreover, treatment of 5 with active methlyene compounds gave two pyrazole derivatives 10 and 11. Azomethines 12a-e were prepared through condensation of 5 with aromatic aldehydes or ketones.

The discovery of novel therapeutic molecules is always difficult, and there are a variety of methodologies that use the most diverse and innovative medicinal chemistry approaches. One such approach is the deuteration technique: Deuteration is the process of substituting deuterium for hydrogen in a molecule. When compared to the drug molecule, its deuterated analogues may retain the features of the original molecule and, in some cases, improve its pharmacological activity, with fewer side effects and lower toxicity. Metronidazole is a commonly used antibiotic to treat anaerobic bacterial infections, protozoal and microaerophilic bacterial infections. Met

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n