Four different spectrophotometric methods are used in this study for the determination of Sulfamethoxazole and sulfanilamide drugs in pharmaceutical compounds, synthetic samples, and in their pure forms. The work comprises four chapters which are shown in the following: Chapter One: Includes a brief for Ultraviolet-Visible (UV-VIS) Absorption spectroscopy, antibacterial drugs and sulfonamides with some methods for their determination. The chapter lists two methods for optimization; univariate method and multivariate method. The later includes different types, two of these were mentioned; simplex method and design of experiment method. Chapter Two: Includes reaction of the two studied drugs with sodium nitrite and hydrochloric acid for diazotization reaction followed by coupling with diphenylamine in acidic medium to form, a blue colored azo dye compound which exhibits maximum absorption (λmax) at 530 nm for sulfamethoxazole complex and 531 nm for sulfanilamide complex against the reagent blank and the concentration of these drugs were determined spectrophotometrically. The optimum reaction conditions and other analytical parameters were evaluated. In addition to classical univariate optimization, modified simplex method has been applied in optimization of the variables affecting the color producing reaction. The results show better optical characteristics for calibration curves and statistical data were obtained under optimum conditions obtained by multi simplex optimization, in comparison with those obtained via univariate method for two studied drugs. Beer’s law obeyed in the concentration range of 0.5-12.0 μg.mL-1, 0.5-7.0 μg.mL-1 for sulfamethoxazole and sulfanilamide respectively with molar absorptivity of 4.9617×104 L.mol-1.cm-1 for sulfamethoxazole and 5.9185×104 L.mol-1.cm-1 for sulfanilamide. The detection limits were 0.036 μg.mL-1 and 0.016 µg.mL-1 for the two complexes respectively by simplex method. No interferences from the studied excipients on the determination of these drugs were found therefore, the proposed methods were applied successfully II for the determination of the sulfamethoxazole and sulfanilamide in pharmaceutical compound and in synthetic samples. Chapter Three: Is based on the formation of condensation complexes of each drug with sodium 1,2-naphthoquinon-4-sulfonate as a chromogenic reagent. The absorbance values, for the formed complexes were measured at 460 nm for sulfamethoxazole and 455 nm for sulfanilamide; against reagent blank. Different variables affecting the completion of reaction have been carefully optimized following the classical univariate sequence and design of experiment (DOE) method and the results were obtained under optimum conditions by (DOE) optimization which shows better optical characteristics for calibration curves and statistical data in comparison with those obtained via univariate method for two studied drugs. The calibration graphs are linear in the ranges of (5.0-50.0) µg.mL-1 for sulfamethoxazole and (5.0-30.0) µg.mL-1 for sulfanilamide with detection limit 0.359 µg.mL-1for sulfamethoxazole complex and 0.536 µg.mL-1 for sulfanilamide complex. The molar absorptivity was found to be (7.0918×104 L.mol-1.cm-1) for sulfamethoxazole and (7.0774×104 L.mol-1.cm-1) for sulfanilamide by the design of experiment (DOE) method. Finally no interferences from the studied excipients on the determination of these drugs were found. The proposed methods have been successfully applied for the determination of sulfamethoxazole and sulfanilamide in their pharmaceutical preparation and synthetic samples. Chapter Four: Includes two parts; Derivative spectrophotometry and partial least-squares (PLS). Derivative spectrophotometry is based on the first and second derivative spectra of absorption which has been applied for simultaneous spectrophotometric determination of sulfamethoxazole and sulfanilamide in their mixture in the ultraviolet region. The method offers an advantage of getting rid of the resulting error in the values of absorption because of the presence of each drug with the presence of interferences from the excipients. It was found that the method is able to accurately estimate sulfamethoxazole in the range of (2.0-50.0) μg.mL-1; in mixtures containing III (2.0-30.0) μg.mL-1 of sulfanilamide, as (interferent). The results obtained, with the first derivative measurements, indicate that when the concentration of sulfanilamide is kept constant and the concentration of sulfamethoxazole varied, the peak amplitudes are measured at peak-to-baseline (223, 254,287 nm), peak to peak height between (223- 254 nm), (254-287nm). Moreover, the height at the zero cross of sulfanilamide at (235.62, 258.72 nm), heightto-height of the two zero crosses between (235.62-258.72 nm) and area under peak between (241.95-267.04 nm), (267.04-330 nm) were found to be in proportion to the sulfamethoxazole concentration therefore they are used for the determination of it. The careful inspection of the second derivative spectra obtained for the mentioned mixtures of sulfamethoxazole and sulfanilamide shows that peak to basline is at (239.5, 263.5, 267.75, 301, 215 nm) , height to basline is at zero cross is at (245.86, 271.28 nm) , peak to peak is between (239.5-264.25 nm), (239.5-267.75 nm), (271.28-301 nm), (215-239.5 nm), height to height is at two zero cross (245.86-271.28 nm) in addition to peak area at the interval between (254.12-281 nm), (286.95- 329.5 nm), (221.75-254.12 nm) measurements at specified wavelength could be used to quantify the exact concentration of sulfamethoxazole in presence of sulfanilamide. Sulfanilamide was determined for the range of (2.0-50.0) μg.mL-1; in a mixture containing (2.0-50.0) μg.mL-1 of sulfamethoxazole as (interferent). The procedure gave good results over the studied range of concentration depending on peak-to-baseline at (224, 246, 271 nm), height at zero cross at (241.95, 267.04 nm), peak to peak between (224-246 nm), (246-271 nm), height to height at two zero cross (241.95-271 nm) and area under the peak at (235.62-258.72 nm) measurements were found to be used for the determination of sulfanilamide in the first derivative technique. On other situation, the wavelengths are at 218 nm, 231 nm, 260 nm and 278 nm (peak to base line measurements), and height at two zero cross at 254 nm and 281 nm, and peak to peak measurements between (218-231 nm), (231-260 nm) and (260-278 nm), and height at zero cross at (254, 281 nm), wavelengths at (210-224 nm) , (224-245.84 nm) and (271.28-330 nm) peak area at the interval measurements were used for the estimation of sulfanilamide on second derivative.
In contrast to the classical antibacterial sulfa drugs that are unsubstituted or monosubstituted, our newly synthesized analogs were designed to obtain sulfonamide moiety containing disubstituted hetero nitrogen atom. These compounds were formed successfully by chlorosulfonation of acetanilide and the product was treated with different cyclic amines and finally amide hydrolysis was necessary to get agents that were analyzed for IR, UV, CHN, melting points and solubility. At last, we studied their antibacterial activity on certain types of bacteria and we noticed the inactivity due to possible steric factor. Principly, this means these products have no inhibiting action against the used microbes.
This research aims to study the influence of organizational power on the achievement of entrepreneurship for business organizations. It is an analytical study of the views of a sample of managers in the Iraqi Ministry of Education. The research highlights the contribution that can be made from the knowledge of the theory of business organizations in achieving organizational success. The organizational power of the organization contributes to achieving entrepreneurship in the business environment and achieving a competitive position in the work environment. The research dealt with two variables: the first is the independent variable, the organizational power in its dimensions (Expend Power, Structural Power, Prestige Power). And t
... Show MoreThis study aimed to identify the employment of the social networking platform «Twitter» in the 2016 presidential campaign led by the Republican candidate, Donald Trump; and analyse his tweets through his personal account on «Twitter» for the period from: 10/ 8/2016 to: 11/ 8/2016 which represents the last month of the election campaign.
The study belongs to the type of descriptive studies using the analytical method through an analysis index that includes sub-categories and other secondary categories. The research has adopted the ordinary unit of information material (tweet) as an analysis unit for this purpose.
... Show MoreA novel technique Sumudu transform Adomian decomposition method (STADM), is employed to handle some kinds of nonlinear time-fractional equations. We demonstrate that this method finds the solution without discretization or restrictive assumptions. This method is efficient, simple to implement, and produces good results. The fractional derivative is described in the Caputo sense. The solutions are obtained using STADM, and the results show that the suggested technique is valid and applicable and provides a more refined convergent series solution. The MATLAB software carried out all the computations and graphics. Moreover, a graphical representation was made for the solution of some examples. For integer and fractional order problems, solutio
... Show MoreVarious theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp
... Show MoreThe tight gas is one of the main types of the unconventional gas. Typically the tight gas reservoirs consist of highly heterogeneous low permeability reservoir. The economic evaluation for the production from tight gas production is very challenging task because of prevailing uncertainties associated with key reservoir properties, such as porosity, permeability as well as drainage boundary. However one of the important parameters requiring in this economic evaluation is the equivalent drainage area of the well, which relates the actual volume of fluids (e.g gas) produced or withdrawn from the reservoir at a certain moment that changes with time. It is difficult to predict this equival
A novel technique Sumudu transform Adomian decomposition method (STADM), is employed to handle some kinds of nonlinear time-fractional equations. We demonstrate that this method finds the solution without discretization or restrictive assumptions. This method is efficient, simple to implement, and produces good results. The fractional derivative is described in the Caputo sense. The solutions are obtained using STADM, and the results show that the suggested technique is valid and applicable and provides a more refined convergent series solution. The MATLAB software carried out all the computations and graphics. Moreover, a graphical representation was made for the solution of some examples. For integer and fractional order problems, solu
... Show MoreIn the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
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