Fusidic acid (FA) is a well-known pharmaceutical antibiotic used to treat dermal infections. This experiment aimed for developing a standardized HPLC protocol to determine the accurate concentration of fusidic acid in both non-ionic and cationic nano-emulsion based gels. For this purpose, a simple, precise, accurate approach was developed. A column with reversed-phase C18 (250 mm x 4.6 mm ID x 5 m) was utilized for the separation process. The main constituents of the HPLC mobile phase were composed of water: acetonitrile (1: 4); adjusted at pH 3.3. The flow rate was 1.0 mL/minute. The optimized wavelength was selected at 235 nm. This approach achieved strong linearity for alcoholic solutions of FA when loaded at a serial concentration ranging from 12.5 to 400 µg/ml. Furthermore, the approach showed good stability and achieved full recovery and an effective separation for FA from the abovementioned formulation. Besides, the protocol validation revealed good robustness at a temperature range of 23 to 27, pH 3.0 to 3.5, detection wavelength 230 to 240 nm, flow rate 0.8 and 1.2 and mobile phase contents of (78:22 to 82:18 acetonitrile/ water). The limit of Detection was obtained 1.33 µg/ml and limit of Quantification was 4.04 µg/ml for FA that uploaded through mentioned formulations. All the validation parameters were within the acceptance criteria, as per ICH , US Pharmacopeia requirements. Overall, an affordable and reproducible method could be achieved for the detection and quantification of fusidic acid within the nano-emulsion based gels formulas.
Autoría: Muwafaq Obayes Khudhair. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 6, 2022. Artículo de Revista en Dialnet.
In our article, three iterative methods are performed to solve the nonlinear differential equations that represent the straight and radial fins affected by thermal conductivity. The iterative methods are the Daftardar-Jafari method namely (DJM), Temimi-Ansari method namely (TAM) and Banach contraction method namely (BCM) to get the approximate solutions. For comparison purposes, the numerical solutions were further achieved by using the fourth Runge-Kutta (RK4) method, Euler method and previous analytical methods that available in the literature. Moreover, the convergence of the proposed methods was discussed and proved. In addition, the maximum error remainder values are also evaluated which indicates that the propo
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We compare two methods Bayesian and . Then the results were compared using MSe criteria.
A simulation had been used to study the empirical behavior for the Logistic model , with different sample sizes and variances. The results using represent that the Bayesian method is better than the at small samples sizes.
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