An electrolytic process for the removal of Zn(II) from aqueous solution using a parallel amalgamated copper screens cathode operated in the flow through mode is proposed. The current-potential curves recorded at a rotating amalgamated copper disc electrode were used to determine diffusion coefficient of Zn(II). The performance of electrolytic reactor was investigated by using different flow rates at initial zinc ion concentration(48 mg/L). Taking into account the residential Zn(II) concentration, the best results were obtained for cathode potential of (-1.35 V vs. SCE) at flow rate (320 L/h). Zinc ion concentration was found to decrease from 48 mg/L to 1 mg/L during 120 min. of electrolysis. The experimental data are well correlate

Rare earth metal oxides (REMOs) have gained considerable attention in recent years owing to their distinctive properties and potential applications in electronic devices and catalysts. Particularly, cerium dioxide (CeO2), also known as ceria, has emerged as an interesting material in a wide variety of industrial, technological, and medical applications. Ceria can be synthesized with various morphologies, including rods, cubes, wires, tubes, and spheres. This comprehensive review offers valuable perceptions into the crystal structure, fundamental properties, and reaction mechanisms that govern the well-established surface-assisted reactions over ceria. The activity, selectivity, and stability of ceria, either as a stand-alone catalyst or as

Conventional concretes are almost unbending, and even a small amount of strain potential leaves them brittle. This lack of bendability is a major source of strain loss, and it has been the main goal behind the development of bendable concrete, often known with engineered ce ment composites, or ECC. This form of concrete has a lot more flexibility than regular concrete. Micromechanical polymer fibers are used to strengthen ECC. In most cases, ECC uses a 2% amount of thin, separated fibers. As a result, bendable concrete deforms but unlike traditional concrete, it does not crack. This study aims to include this kind of concrete, bendable concrete, which can be used to solve concrete problems. Karasta (CK) and Tasluja (CT) Portland Lime

Background:This is a prospective study of three children presented to us in the Orbital clinic in AL ShahidGazi Al Hariri Hospital with painless proptosiswith suspension of Hydatid disease.Objectives: : Orbital hydatid disease is a rare lesion accounting for less than 1% of the total lesions of the body (1, 2). Orbital cysts presented as a primary lesion in our study which is rare to have such lesion without involvement of other organs (3). Humans represent the intermediate host where the commonly affected organ are liver and the lung (10-15%) (4). Methods:This is a prospective study of three Children presented to us in the Orbital clinic in Al Shahid Ghazi Alhariri Hospital with painless proptosis with suspension of Hydatid disease, dep

Reverse Phase High Performance Liquid Chromatography (RP-HPLC) was coupled with ultraviolet absorption sepectoscopy (UV) for separation and identification of Naphthalene, Acenaphthylene, Pyrene, Benz{a} anthracene and 1,3,2,4-Dibenzanthracene. RP-HPLC was performed on an ODS-C18 column (150×4.6 mm I.D) using acetonitrile–buffer phosphate as mobile phase. UV absorption spectra of the elutes was detected in 254 nm, and studying the chromatographic variables include organic modifier ratio, PH, column temperature and concentration of buffer to maximize resolution and minimize separation time. the results showed that using mobile phase( 80:20) v/v acetonitrile:0.01M phosphate buffer solution at PH 6 with flow rate 1ml/min and column te

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

Distributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks

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