Ciprofloxacin is a broad spectrum fluoroquinolone, effective in the treatment of a wide range of infections, including genitourinary tract infections.In this study, bioadhesive vaginal tablets of ciprofloxacin hydrochloride were prepared by direct compression method using a combination of bioadhesivepolymers carbopol 934P(Cp), carboxymethylcellulose (CMC) and sodium alginate (SA) in different ratios.The prepared tablet formulations were characterized by measuring their swelling capacity, surface pH, bioadhesive properties, and in-vitro drug dissolution. It was found that the bioadhesive force was directly proportional to carbopol 934P content in different formulae and was further enhanced by the inclusion of carboxymethylcellulose. Swelling studies indicated that formulae containing a combination of carbopol 934P and sodium alginate or carboxymethylcellulose had greater swelling index than those containing carbopol 934P alone. Formulations containing Carbopol 934P and carboxymethylcellulose were found to swell to a greater extent than those composed of similar ratios of carbopol and sodium alginate. In vitro drug release study showed that the release of ciprofloxacin hydrochloride from formulae containing carboxymethylcellulose was faster than from those containing sodium alginate.Formula F5 composed of CP/CMC in a ratio of 2:1 showed moderate swelling, suitable bioadhesion and retardation of drug release. Thus, it may be considered a good candidate as a base for bioadhesive vaginal tablet
The research involves using phenol – formaldehyde (Novolak) resin as matrix for making composite material, while glass fiber type (E) was used as reinforcing materials. The specimen of the composite material is reinforced with (60%) ratio of glass fiber.
The impregnation method is used in test sample preparation, using molding by pressure presses.
All samples were exposure to (Co60) gamma rays of an average energy (2.5)Mev. The total doses were (208, 312 and 728) KGy.
The mechanical tests (bending, bending strength, shear force, impact strength and surface indentation) were performed on un irradiated and irrad
... Show MoreIn this research , we study the inverse Gompertz distribution (IG) and estimate the survival function of the distribution , and the survival function was evaluated using three methods (the Maximum likelihood, least squares, and percentiles estimators) and choosing the best method estimation ,as it was found that the best method for estimating the survival function is the squares-least method because it has the lowest IMSE and for all sample sizes
In this research , we study the inverse Gompertz distribution (IG) and estimate the survival function of the distribution , and the survival function was evaluated using three methods (the Maximum likelihood, least squares, and percentiles estimators) and choosing the best method estimation ,as it was found that the best method for estimating the survival function is the squares-least method because it has the lowest IMSE and for all sample sizes
The current issues in spam email detection systems are directly related to spam email classification's low accuracy and feature selection's high dimensionality. However, in machine learning (ML), feature selection (FS) as a global optimization strategy reduces data redundancy and produces a collection of precise and acceptable outcomes. A black hole algorithm-based FS algorithm is suggested in this paper for reducing the dimensionality of features and improving the accuracy of spam email classification. Each star's features are represented in binary form, with the features being transformed to binary using a sigmoid function. The proposed Binary Black Hole Algorithm (BBH) searches the feature space for the best feature subsets,
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