ِabstract:In this research we prepared nanofibers by electrospinning from poly (Vinyl Alcohol) /TiO2. The spectrum of the solution (Emission) was studied and found to be at 772 nm, several process parameters were such as concentration of TiO2 , and the effect of distance from nozzle tip to the grounded collector (gap distance). The result of the lower concentration of, the smaller the diameter of nanofiber is. Increasing the gap distance will affect nanofibers diameter.

Rutting is one of the most complex and widespread types of distress. The rutting is frequently observed on Iraqi roads, especially at the checkpoints, forming a significant hazard on the asphalt layers. Factors such as heavy loads and high temperatures contribute to this distress. Adding fibers to a hot mix asphalt (HMA) effectively improves performance and extends the lifespan of the flexible pavement. This article used glass, steel, and basalt fibers. The wheel tracking test assessed the fibre-asphalt mixture for rutting resistance and compared it with the mix without adding fibers (control HMA). Meanwhile, the microscopic structure of fibres and asphalt mixture modified with fibers was examined using the Field Emission Scanning E

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

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

This current study was built on creating four electrodes based on molecularly imprinted polymers (MIPs). As the template using Cefalexin (CFX), 1-vinyl imidazole (VIZ) and vinyl acetate (VA) as monomer, and N, N-methylene bis acrylamide (MBAA) as cross-linkers and benzoyl peroxide as the initiator, two MIPs were prepared. The same composition was used in non-impressed polymers (NIPs) preparation, but without the template (Cefalexin). For the membranes preparation, numerous plasticizers, such as tri-oly phosphate (TOP) and di-octyl phthalate (DOP), were used in the PVC matrix, slop, detection limit, lifetime, and linearity range of CFX-MIPs electrodes are characteristics &nb

Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed

This study deals with the corrosion inhibition of metal corrosion process of medium carbon steel using 1M HCl for kinetic studies and rate reaction determination. The weight loss method is applied to pieces of Medium carbon steel divided to Cubans with dimensions (0.4*2*2.4) cm , and use Tafel Extrapolation Method, the samples were polished using carbide silicon paper with dimensions of (180,200,400,600,800,1000). The samples were immersed in the alcoholic medium ethanol at a temperature 293K for 3hr. Natural inhibitor Kujarat Tea (Hibiscus sabdarriffa L.) is used which is extracted in aqueous and alcoholic medium, different concentrations (1000،2000, 3000) ppm have been used ; The best concentration found through the results is a

This study deals with the corrosion inhibition of metal corrosion process of medium carbon steel using 1M HCl for kinetic studies and rate reaction determination. The weight loss method is applied to pieces of Medium carbon steel divided to Cubans with dimensions (0.4*2*2.4) cm , and use Tafel Extrapolation Method, the samples were polished using carbide silicon paper with dimensions of (180,200,400,600,800,1000). The samples were immersed in the alcoholic medium ethanol at a temperature 293K for 3hr. Natural inhibitor Kujarat Tea (Hibiscus sabdarriffa L.) is used which is extracted in aqueous and alcoholic medium, different concentrations (1000،2000, 3000) ppm have been used ; The best concentration found through the results is a conce

Four electrodes were synthesized based on molecularly imprinted polymers (MIPs). Two MIPs were prepared by using the diclofenac sodium (DFS) as the template, 2-hydroxy ethyl metha acrylate(2-HEMA) and 2-vinyl pyridine(2-VP) as monomers as well as divinyl benzene and benzoyl peroxide as cross linker and initiator respectively. The same composition used for prepared non-imprinted polymers (NIPs) but without the template (diclofenac sodium). To prepared the membranes electrodes used different plasticizers in PVC matrix such as: tris(2-ethyl hexyl) phosphate (TEHP), tri butyl phosphate (TBP), bis(2-ethyl hexyl) adipate (BEHA) and tritolyl phosphate (TTP). The characteristics studied the slop, detection limit, life time and linearity range of DF