A simple analytical method was used in the present work for the simultaneous quantification of Ciprofloxacin and Isoniazid in pharmaceutical preparations. UV-Visible spectrophotometry has been applied to quantify these compounds in pure and mixture solutions using the first-order derivative method. The method depends on the first derivative spectrophotometry using zero-cross, peak to baseline, peak to peak and peak area measurements. Good linearity was shown in the concentration range of 2 to 24 µg∙mL-1 for Ciprofloxacin and 2 to 22 µg∙mL-1 for Isoniazid in the mixture, and the correlation coefficients were 0.9990 and 0.9989 respectively using peak area mode. The limits of detection (LOD) and limits of quantification (LOQ) were measured with first derivative method. The LOD and LOQ were found as 0.45 µg∙mL-1 and 1.50 µg∙mL-1 for Ciprofloxacin and 0.68 µg∙mL-1 and 2.28 µg∙mL-1 for Isoniazid, respectively. Accuracy and precision were determined by measuring the relative standard deviation and recoveries. The results also showed that the proposed method was successfully applied for direct analysis of ciprofloxacin and isoniazid in the tablet samples
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The present report depicts a convenient route for the synthesis of new N-Mannich bases from Ciprofloxacin (CP) drug. The synthetic route started from the reaction CP drug with 2-mercaptobenzimidazole to give compound [A], the N-Mannich bases analogs of CP [A1-A8] were prepared by the reaction of CP derivative [A] with primary and secondary amine derivatives. The structure of the analogs was confirmed by spectral (1 HNMR and FTIR) and analytical data. This study also includes calculations of total energy and electrostatic potential. In addition, this research aimed to determine the effects of CP derivatives on the activity of various transferase enzymes in sera, such as serum glutamic-oxaloacetic transaminase (GOT) and Glutamate Pyruvate Tra
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A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the
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A Modified version of the Generlized standard addition method ( GSAM) was developed. This modified version was used for the quantitative determination of arginine (Arg) and glycine ( Gly) in arginine acetyl salicylate – glycine complex . According to this method two linear equations were solved to obtain the amounts of (Arg) and (Gly). The first equation was obtained by spectrophotometic measurement of the total absorbance of (Arg) and (Gly) colored complex with ninhydrin . The second equation was obtained by measuring the total acid consumed by total amino groups of (Arg) and ( Gly). The titration was carried out in non- aqueous media using perchloric acid in glacial acetic acid as a titrant. The developed metho
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HCl is separated from HCl –H2SO4 solution by membrane distillation process(MD). The flat –sheet membranes made from polyvinylidene fluoride (PVDF) and polypropylene (pp.). Plate and frame these types of membrane where used in the process. The feed is a mixture of HCl and H2SO4 acids compositions depended on metals treated object.HCl concentration increased in the permeate during the process but sulfuric acid increased gradually in the feed .During the concentration of solution acids concentrations in the feed at the beginning were 50 g/dm3 of sulfuric acid and 50 g/dm3 of hydrochloric acid at 333K feed temperature the permeate flux was 71 dm
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A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others
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The estimation of the initial oil in place is a crucial topic in the period of exploration, appraisal, and development of the reservoir. In the current work, two conventional methods were used to determine the Initial Oil in Place. These two methods are a volumetric method and a reservoir simulation method. Moreover, each method requires a type of data whereet al the volumetric method depends on geological, core, well log and petrophysical properties data while the reservoir simulation method also needs capillary pressure versus water saturation, fluid production and static pressure data for all active wells at the Mishrif reservoir. The petrophysical properties for the studied reservoir is calculated using neural network technique
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