Simple and sensitive spectrophotometric method is described based on the coupling reaction of tetracycline hydrochloride (TC. HCl) with diazotized 4-aminopyridine in bulk and pharmaceutical forms. Colored azo dye formed during this reaction is measured at 433 nm as a function of time. Factors affecting the reaction yield were studied and the conditions were optimized. The kinetic study involves initial rate and fixed time (10 minutes) procedures for constructing the calibration graphs to determine the concentration of (TC. HCl). The graphs were linear for both methods in concentration range of 10.0 to 100.0 μg.mL-1. The recommended procedure was applied successfully in the determination of (TC. HCl) in its commercial formulations.

The aesthetic expression and its orders are important for steel structures forming. Steel structures are a compilation of structural elements, where its shapes have standard dimensions and pre-fabricated. As the steel construction systems not only aim to achieve the functional requirements for users, but must also have the symbolic aesthetics which provides visually and cognitive expression for viewers. In this sense the research interested in expressional aesthetics in these systems and highlights the importance of attention as structural items. Therefore the visual items which related with steel structures contain some of the most powerful forms of modern architecture, steel structures with a glass cladding, agility an

The Dagum Regression Model, introduced to address limitations in traditional econometric models, provides enhanced flexibility for analyzing data characterized by heavy tails and asymmetry, which is common in income and wealth distributions. This paper develops and applies the Dagum model, demonstrating its advantages over other distributions such as the Log-Normal and Gamma distributions. The model's parameters are estimated using Maximum Likelihood Estimation (MLE) and the Method of Moments (MoM). A simulation study evaluates both methods' performance across various sample sizes, showing that MoM tends to offer more robust and precise estimates, particularly in small samples. These findings provide valuable insights into the ana

The isomerization of n-hexane on platinum loaded acidic zeolite was studied at atmospheric pressure, H2/nC6 molar ratios of 1-4 and temperature range of 240-270ºC. The measured kinetic data were fitted to an equation based on the bifunctional mechanism and by using independently obtained dehydrogenation and adsorption data. The activation energies of protonation (ΔHpro) and the elementary isomerization step (Eact,iso) and as well as the corresponding preexponential factor were simultaneously determined. The observed values of both ΔHpro and Eact,iso are in agreement with the results of quantum-chemical calculations.

     This article aims to determine the time-dependent heat coefficient together with the temperature solution for a type of semi-linear time-fractional inverse source problem by applying a method based on the finite difference scheme and Tikhonov regularization. An unconditionally stable implicit finite difference scheme is used as a direct (forward) solver. While by the MATLAB routine lsqnonlin from the optimization toolbox, the inverse problem is reformulated as nonlinear least square minimization and solved efficiently. Since the problem is generally incorrect or ill-posed that means any error inclusion in the input data will produce a large error in the output data. Therefore, the Tikhonov regularization technique is applie

Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat