The two body model of (Core+n) within the radial wave functions of the cosh potential has been used to investigate the ground state features such as the proton, neutron and matter densities, the root mean square (RMS) nuclear proton, neutron, charge and mass radii of unstable neutron-rich 14B, 15C, 19C and 22N nuclei. The calculated results show that the two body model with the radial wave functions of the cosh potential succeeds in reproducing neutron halo in these nuclei.

Edward Albee (1928-2016) is an American  dramatist who is notorious for his controversial works. Albee's plays generate a crisis of a restraint situation and a point of no return where characters trespass the limits and get caught up in a tragic cycle. The Goat or Who is Sylvia? )2000) is one of his controversial pieces, addressing (human-animal relations). This theatrical masterpiece unleashes man's wildest desires and ravaging behavior. Bestiality is a criminal offense placed in the domain of mental disorders attributed to the lack of emotional support, anxiety, depression, and psychological problems. It is also a serious moral infraction of communities' socio-religious traditions. In this play, Martin’s bestiality lead

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

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

Background: Improved glucose level control with insulin injections have allowed for the diabetic population to live longer and healthier lives. Unfortunately diabetes remains a worldwide epidemic disease with multiple health implications. Specifically, its effects upon fracture healing are compromised in diabetics with as high as 87% recovery delay relative to “healthy” counterparts. Current medical treatments for bone injuries have been largely focused on replacing the lost bone with allogenic or autogenous bone grafts, beta-tricalcium phosphate (β -TCP), a ceramic alloplast, has interconnected system of micropores, has been widely used as a biologically safe osteoconductive bone substitute. The aim of this study was histol

Background: Tooth extraction is one of the most commonly performed procedures in dentistry. It is usually a traumatic process often resulting in immediate destruction and loss of alveolar bone and surrounding soft tissues. Various instruments have been described to perform atraumatic extractions which can prevent damage to the paradental structures. The physics forceps is one of those innovations in dental extraction technologies that claim to provide an efficient means for atraumatic dental extractions. Materials and method: A randomized clinical trial was conducted to compare the physics forceps with the conventional forceps for the removal of 28 mandibular single rooted teeth under the following parameters: incidence of crown, root, b

          The primary objective of this paper is to improve a biometric authentication and classification model using the ear as a distinct part of the face since it is unchanged with time and unaffected by facial expressions. The proposed model is a new scenario for enhancing ear recognition accuracy via modifying the AdaBoost algorithm to optimize adaptive learning. To overcome the limitation of image illumination, occlusion, and problems of image registration, the Scale-invariant feature transform technique was used to extract features. Various consecutive phases were used to improve classification accuracy. These phases are image acquisition, preprocessing, filtering, smoothing, and feature extraction. To assess the proposed

Static Synchronous Series Compensator (SSSC) is a well known device for effectively regulating the active power flow in a power system. In this paper, the SSSC linearized power flow equations are incorporated into Newton-Raphson algorithm in a MATLAB written program to investigate the control of active poweer flow and the transient stability of a five bus and a thirty bus IEEE test systems, during abnormal conduction (three phase fault near buses). A comparison of the results obtained for the base case without SSSC and with it to investigate the effectiveness of the device on both of the active power flow and the transient stability.