Two simple methods spectrophotometric were suggested for the determination of Cefixime (CFX) in pure form and pharmaceutical preparation. The first method is based without cloud point (CPE) on diazotization of the Cefixime drug by sodium nitrite at 5Cº followed by coupling with ortho nitro phenol in basic medium to form orange colour. The product was stabilized and measured 400 nm. Beer’s law was obeyed in the concentration range of (10-160) μg∙mL-1 Sandell’s sensitivity was 0.0888μg∙cm-1, the detection limit was 0.07896μg∙mL-1, and the limit of Quantitation was 0.085389μg∙mL-1.The second method was cloud point extraction (CPE) with using Trtion X-114 as surfactant. Beer’s law was obeyed in the concentration range of (10-160) μg∙mL-1. Sandell’s sensitivity was 0.1470μg∙cm-1, the detection limit was 0.06680μg∙mL-1, and the limit of quantitation was 0.07293μg∙mL-1. All variables including the reagent concentration, reaction time, colour stability period, and mole ratio were studied in order to optimize the reaction conditions. The composition of product (1:1). The methods were effectively useful to the determination of Cefixime in pharmaceutical dose form, and the attained results were in good agreement with the official result and other methods in literature .No interference was observed from the commonly encountered additives and excipients
This study aimed to extraction of essential oil from peppermint leaves by using hydro distillation methods. In the peppermint oil extraction with hydro distillation method is studied the effect of the extraction temperature to the yield of peppermint oil. Besides it also studied the kinetics during the extraction process. Then, 2nd -order mechanism was adopted in the model of hydro distillation for estimation many parameters such as the initial extraction rate, capacity of extraction and the constant rat of extraction with various temperature. The same model was also used to estimate the activation energy. The results showed a spontaneous process, since the Gibbs free energy had a value negative sign.
Siderophores are low molecular weight organic compounds produced by microorganisms growing under low iron concentration.In this study we describe the detection, production and extraction of siderophores secreted by Acinetobacter baumannii (Multiple-drug resistant ) pathogens. One hundered twenty Gram –negative non lactose fermenter bacilli isolates have been collected from three hospitals at Baghdad city over three months. Primary identification of these isolates is performed by standard diagnostic methods (biochemical tests and API 20 NE); 19 clinical isolates of A. baumannii are cultured on CHROMagar (highly selective medium for detection of MDR Acinetobacter) as well as diagnoses is documented by using Vitek 2 system. Isolates are exa
... Show MoreResearch aims to identify the immediate impact of the announcement of mergers in the stockholders and the feasibility of gain abnormal return and benefiting from asymmetric information during the announcement that unite 30 days before the announcement of the merger, and announcement day, and 30 days after the announcement of the merger. It was the largest and most important mergers and acquisitions pick that occurred during the global financial crisis, specifically in health care/pharmaceutical industry, Pfizer and Wyeth merger with Novartis acquisition on Alcon. search has adopted three hypotheses: the first hypothesis that ((achieves the target company's shareholders positive abnormal return (or negative) during and befor
... Show MoreFor the time being, the cold-formed sections are widely used due to their simple manufacturing and construction processes. To be feasible, the strength of cold-formed columns should be determined based on their post-buckling behavior. Post-buckling relations are cumbersome and need design aids similar to those of American Iron and Steel Institute (AISI) to be applicable. These design aids have been developed to sections and materials other than those available in the local market. Therefore, this paper tries to develop a general finite element model to simulate the postbuckling behavior of cold-formed steel columns. Shell element has been used to discretize the web, flanges, and lips of the column. A linear bucking analy
... Show MoreThe 3-parameter Weibull distribution is used as a model for failure since this distribution is proper when the failure rate somewhat high in starting operation and these rates will be decreased with increasing time .
In practical side a comparison was made between (Shrinkage and Maximum likelihood) Estimators for parameter and reliability function using simulation , we conclude that the Shrinkage estimators for parameters are better than maximum likelihood estimators but the maximum likelihood estimator for reliability function is the better using statistical measures (MAPE)and (MSE) and for different sample sizes.
Note:- ns : small sample ; nm=median sample
... Show MoreThe aim of this research is to investigation the optimization of the machining parameters (spindle speed, feed rate, depth of cut, diameter of cutter and number of flutes of cutter) of surface roughness for free-form surface of composite material (Aluminum 6061 reinforced boron carbide) by using HSS uncoated flat end mill cutters which are rare use of the free-form surface. Side milling (profile) is the method used in this study by CNC vertical milling machine. The purpose of using ANFIS to obtain the better prediction of surface roughness values and decreased of the error prediction value and get optimum machining parameters by using Taguchi method for the best surface roughness at spindle speed 4500 r.p.m, 920mm/rev feed rate, 0.6mm de
... Show MoreAfter the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings
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