The study is based on the selective binding ability of the drug compound procaine (PRO) on a surface imprinted with nylon 6 (N6) polymer. Physical characterization of the polymer template was performed by X-ray diffraction and DSC thermal analysis. The imprinted polymer showed a high adsorption capacity to trap procaine (237 µg/g) and excellent recognition ability with an imprinted factor equal to 3.2. The method was applied to an extraction column simulating a solid-phase extraction to separate the drug compound in the presence of tinoxicam and nucleosimide separately and in a mixture of them with a recovery rate more than the presence of tinoxicam and nucleosimide separately and in a mixture of them with a recovery rate of more than 82%. Separation efficiency and excellent selectivity for procaine were ensured using a mixed solution injected into an HPLC technique consisting of a C18 column with a mobile phase mixture of water-acetonitrile (75:25) at pH 3.3. The study of drug control using an imprinted polymer with procaine compound showed that the complete drug release process is faster at pH1 in a maximum period of 80 min. The proposed method was successfully applied on some of the available pharmaceuticals, and it showed high selectivity for the separation of PRO, RE % was < 1.18, and RSD was less than 0.447.
Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreMost cities in the world are suffering from the problem of solid waste and the resting adverse impact on the environment and public health, in particular the spread of diseases, insects and rodents, As well as the proliferation of nuisance odors result of provided by the responsible parties, As wall as weak environmental awareness among those who dwell in dealing in environmentally sound disposal of solid waste, this study was bembgesan first intake of solid waste and the kinds of concept and components by land use, As wall as the effects of solid waste on the environment spatial, factors affecting the quality and quantity of solid waste, the second topic was included as a study field presented the historical city of Baghdad
... Show MoreThis work is focused on studying the effect of liquid layer level (height above a target material) on zinc oxide nanoparticles (ZnO and ZnO2) production using liquid-phase pulsed laser ablation (LP-PLA) technique. A plate of Zn metal inside different heights of an aqueous environment of cetyl trimethyl ammonium bromide (CTAB) with molarity (10-3 M) was irradiated with femtosecond pulses. The effect of liquid layer height on the optical properties and structure of ZnO was studied and characterized through UV-visible absorption test at three peaks at 213 nm, 216 nm and 218 nm for three liquid heights 4, 6 and 8 mm respectively. The obtained results of UV–visible spectra test show a blue shift accomp
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