A series of novel hybrid molecules containing 1,3,4-oxadiazole and 1,3,4-thiadiazole moieties bearing an ibuprofen moiety were designed, synthesized, and evaluated for their in vitro antibacterial activity against Gram-positive and Gram-negative bacteria. A carboxylic acid compound with a 1,3,4-thiadiazole unit was synthesized via the coupling reaction of 5-(1-(4-isobutylphenyl) ethyl)-1,3,4-thiadiazol-2-amine with benzoic acid. This compound was then used as the starting material to make several new 1,3,4-oxadiazole derivatives through ring closure reactions, after first converting it to its ester (methyl 4-(5-(1-(4-isobutylphenyl)ethyl)-1,3,4-thiadiazol-2-yl) benzoate) and then to the acid hydrazide (4-(5-(1-(4-isobutylphenyl) eth

In this study, new oxazolidinone and thiazolidinone derivatives were synthesized through a three-step process. In the first step, o-aminothiophenol was reacted with p-aminobenzoic acid in hydrochloric acid to produce an amine containing a thiazole ring, achieving a product yield of 80%. The second step involves synthesizing Schiff bases (E1-E4) by reacting 4-(benzo[d]thiazol-2-yl)aniline with various aromatic aldehydes in the presence of glacial acetic acid. This reaction yields products of 76% to 90%. In the third step, the Schiff derivatives (E1-E4) are reacted with glycolic acid and thioglycolic acid to obtain the desired products. Oxazolidinone derivatives (N1-T1) were produced with rates ranging from 66% to 74%, while thiazolidin

Thin films ZrO₂: MgO nanostructure have been synthesized by a radio frequency magnetron plasma sputtering technique at different ratios of MgO (0,6, 8 and  10)% percentage to be used as the gas sensor for nitrogen dioxide NO₂. The samples were investigated by X-ray diffraction (XRD), atomic force microscopy (AFM), scanning electron microscopy (SEM), energy-dispersive X-ray (EDX) and sensing properties were also investigated. The average particle size of all prepared samples was found lower than 33.22nm and the structure was a monoclinic phase. The distribution of grain size was found lower than36.3 nm and uninformed particles on the surface. Finally, the data of sensing properties have been discussed, where the

This paper presents a hybrid genetic algorithm (hGA) for optimizing the maximum likelihood function ln(L(phi(1),theta(1)))of the mixed model ARMA(1,1). The presented hybrid genetic algorithm (hGA) couples two processes: the canonical genetic algorithm (cGA) composed of three main steps: selection, local recombination and mutation, with the local search algorithm represent by steepest descent algorithm (sDA) which is defined by three basic parameters: frequency, probability, and number of local search iterations. The experimental design is based on simulating the cGA, hGA, and sDA algorithms with different values of model parameters, and sample size(n). The study contains comparison among these algorithms depending on MSE value. One can conc

Alpha shape theory for 3D visualization and volumetric measurement of brain tumor progression using magnetic resonance images

Environmental pollution is experiencing an alarming surge within the global ecosystem, warranting urgent attention. Among the significant challenges that demand immediate resolution, effective treatment of industrial pollutants stands out prominently, which for decades has been the focus of most researchers for sustainable industrial development aiming to remove those pollutants and recover some of them. The liquid membrane (LM) method, specifically electromembrane extraction (EME), offers promise. EME deploys an electric field, reducing extraction time and energy use while staying eco-friendly. However, there's a crucial knowledge gap. Despite strides in understanding and applying EME, optimizing it for diverse industrial pollutant

Glass fiber–reinforced polymer (GFRP) reinforcement provides an effective alternative to conventional steel in concrete structures due to its corrosion resistance. Nevertheless, the lower elastic modulus of GFRP necessitates careful consideration of serviceability behavior in GFRP-reinforced concrete members. This study presents a numerical sectional analysis model for predicting the flexural response and ultimate capacity of hybrid reinforced concrete beams incorporating embedded GFRP profiles in combination with either mild steel or GFRP reinforcement bars under monotonic static loading. The proposed model employs realistic nonlinear stress–strain relationships for concrete and steel, together with secant moduli of elasticity