A detailed study of adsorption from solution of amitriptyline-HCl, chlorpromazine-HCl and
chlordiazepoxide-HCl on bentonite clay surface has been performed at variable conditions of
temperature, pH and ionic strength. It is aimed in this work to explore the capability of this clay in
treatment of poisoning by the mentioned drugs if taken in quantities higher than the usual doses.
Quantities of drugs adsorbed have been determined by UV spectrophotometric technique. The
sequence of adsorption in neutral media at 37.5 CÙ’ followed the order:
Amitriptyline-HCl > chlorpromazine-HCl > chlordiazepoxide-HCl.
The results were discussed in the light of Langmuir and Freundich adsorption isotherms. The usual
basic th

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

After 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

Rationing is a commonly used solution for shortages of resources and goods that are vital for the citizens of a country. This paper identifies some common approaches and policies used in rationing as well asrisks that associated to suggesta system for rationing fuelwhichcan work efficiently. Subsequently, addressing all possible security risks and their solutions. The system should theoretically be applicable in emergency situations, requiring less than three months to implement at a low cost and minimal changes to infrastructure.