In this paper, the complexes of Shiff base of Methyl -6-[2-(diphenylmethylene)amino)-2-(4-hydroxyphenyl)acetamido]-2,2-dimethyl-5-oxo-1-thia-4-azabicyclo[3.2.0]heptane-3-carboxylate (L) with Cobalt(II), Nickel(II), Cupper(II) and Zinc(II) have been prepared. The compounds have been characterized by different means such as FT-IR, UV-Vis, magnetic moment, elemental microanalyses (C.H.N), atomic absorption, and molar conductance. It is obvious when looking at the spectral study that the overall complexes obtained as monomeric structure as well as the metals center moieties are two-coordinated with octahedral geometry excepting Co complexes that existed as a tetrahedral geometry. Hyper Chem-8.0.7
... Show MoreIn this research, The effect of substituting sucrose with different level of DS and DG (0, 25, 30,50,70 and 100%) on the physiochemical, microbial and sensory properties of cake were studied. Cake models were as well construed for microbial content and organic structure during, before then next 35 days storing at experimental temperature. Results showed no significant variances (p < 0.01) in the chemo physical structure of the date and grape test cake for protein values while there were significant differences for Asch, fiber and fat content values, Sensory assessment results showed high significant variance (p < 0.01) among the cake trials with the exemption of texture (6.04-6.
Employing phase-change materials (PCM) is considered a very efficient and cost-effective option for addressing the mismatch between the energy supply and the demand. The high storage density, little temperature degradation, and ease of material processing register the PCM as a key candidate for the thermal energy storage system. However, the sluggish response rates during their melting and solidification processes limit their applications and consequently require the inclusion of heat transfer enhancers. This research aims to investigate the potential enhancement of circular fins on intensifying the PCM thermal response in a vertical triple-tube casing. Fin arrays of non-uniform dimensions and distinct distribution patterns were des
... Show MoreNanomaterials enhance the performance of both asphalt binders and asphalt mixtures. They also improve asphalt durability, which reduces resource consumption and environmental impact in the long term associated with the production and transportation of asphalt materials. Thus, this paper studies the effectiveness of Nano Calcium Carbonate (Nano CaCO3) and Nano Hydrated Lime (NHL) as modifiers and examines their impact on ranges from 0% to 10% through comprehensive laboratory tests. Softening point, penetration, storage stability, viscosity, and mass loss due to short-term aging using the Rolling Thin Film Oven Test (RTFO) were performed on asphalt binders. Results indicated a significant improvement in binder stiffness, particularly
... Show MoreDeep beams are used in wide construction fields such as water tanks, foundations, and girders in multi-story buildings to provide certain areas free of columns. In practice it is quite often occurring to create web opening in deep beams to supply convenient passage of ventilation ducts, cable channels, gas and water pipes. Experimental studies of ten 10 deep beams were carried out, where two of them are control specimens without openings and eight with large web openings in the shear spans. The variables that have been adopted are the ratio of the shear span to the overall depth of the member cross-section, location and dimensions of the opening. Test results showed that there was a decrease in the load carrying capacity of deep bea
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for
 
        