In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

Reacts compound C6H5PO2Cl2 with Secretary secondary R2NH at room temperature by Mulet 2:1 and using chloroform as a solvent in dry conditions to form composite 2HCl and the interaction of compound solution of sodium hydroxide and potassium by Mulet 3:1 salt was prepared

The intestinal mucositis define as inflammation and ulceration in the gastrointestinal tract wall and in some case in the oral cavity these cause by treatment with antineoplastic drug like 5-fluorouracil and Irinotecan and other types of chemotherapeutics drugs , 5-Fluorouracil-induced intestinal mucositis (IM) is consider as one of the more common tumor issue .it cause series of undesirables symptoms like severe diarrhea ,abdominal pain , stomach uncomfortable and other. The aim of this current study to see how ellagic acid act to  Attenuates 5-FU-Induced Intestinal Mucositis and  Diarrhea in Mice . we induced the intestinal mucositis by injected the mice intraperitoneally in 5-fluorouracil about 50mg per kg daily for

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to