A method is developed for the determination of iron (III) in pharmaceutical preparations by coupling cloud point extraction (CPE) and UV-Vis spectrophotometry. The method is based on the reaction of Fe(III) with excess drug ciprofloxacin (CIPRO) in dilute H2SO4, forming a hydrophobic Fe(III)- CIPRO complex which can be extracted into a non-ionic surfactant Triton X-114, and iron ions are determined spectrophotometrically at absorption maximum of 437 nm. Several variables which impact on the extraction and determination of Fe (III) are optimized in order to maximize the extraction efficiency and improve the sensitivity of the method. The interferences study is also considered to check the accuracy of the procedure. The results have shown that the preconcentration factor of 71 fold leading to obtain a limit of detection of 2.67 ng mL-1 with linear calibration range of 5-150 ng mL-1 (r=0.9998) and a superb sensitivity in terms of molar absorptivity of 1.13x106 L.mol-1.cm-1 . The mean percent recovery of 99.78±0.53% and the precision (RSD %) ranged from 1.96 to 0.76 are achieved. The developed method is applied to the determination of iron in four selected pharmaceutical drugs. The experimental values agree statistically with the quoted values stated by the manufacturer’ companies.
The world is currently facing a medical crisis. The epidemic has affected millions of people around the world since its appearance. This situation needs an urgent solution. Most countries have used different solutions to stop the spread of the epidemic. The World Health Organization has imposed some rules that people should adhere. The rules are such, wearing masks, quarantining infected people and social distancing. Social distancing is one of the most important solutions that have given good results to confront the emerging virus. Several systems have been developed that use artificial intelligence and deep learning to track social distancing. In this study, a system based on deep learning has been proposed. The system includes monitor
... Show MoreThis paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In ord
... Show MoreInformation and communication technology has a significant influence on employee procedures. Businesses are investing in e-CRM technologies, yet it is difficult to assess the performance of their e-CRM platforms. The DeLone and McLean Information Systems Success framework can be modified to the current e-CRM assessment difficulties. The new framework's different aspects provide a concise framework for organizing the e-CRM key metrics identified in this study. The purpose of this study is to apply and verify that the Updated DeLone and McLean IS Model can be employed to explain e-CRM adoption among employees, along with the extended Updated DeLone and McLean Model with its five output factors, namely system quality, service quality,
... Show MoreZnS:Ce3+ nanoparticles were prepared by a simple microwave irradiation method under mild condition. The starting materials for the synthesis of ZnS:Ce3+ quantum dots were zinc acetate (R & M Chemical) as zinc source, thioacetamide as a sulfur source, cerium chloride as cerium source and ethylene glycol as a solvent. All chemicals were analytical grade products and used without further purification. The quantum dots of ZnS:Ce3+ with cubic structure were characterized by X-ray powder diffraction (XRD), the morphology of the film is seen by scanning electron microscopy (SEM) also by field effect scanning electron microscopy (FESEM) and XRD. Upon exposure to 460 nm light at zero bias voltage, ZnS:Ce3+/p-Si showed a high sensitivity of 4000% an
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