Drug-induced acute kidney injury is a serious disorder. Oxidative stress has a key role in its initiation and progression. In this study, the possible ameliorative effect of fimasartan against methotrexate-induced nephrotoxicity was investigated in comparison with α-tocopherol in rats. Wistar rats were allocated into six groups and treated as follows: group Ӏ received water on a daily basis for 8 successive days; group ӀӀ received methotrexate (20 mg/kg) on day 1, followed by water for 7 successive days; group ӀӀӀ received fimasartan (3 mg/kg/day) for 7 successive days; group IV received α-tocopherol (1 g/kg/day) for 7 successive days; group V re

Sustainability is providing the needs without compromising the ability of the strategical forming to meet their requirements. The production of warm asphalt mixtures using recycled pavements produces economic and environmentally friendly mixtures, which is the most important advantage of this work. This research aims to determine the effect of recycled asphalt concrete (RAP) on the indirect tensile strength of warm asphalt mixtures and Marshall Properties. Models of warm asphalt mixtures using Aggregate from the Al-Nibaay quarry, Asphalt with a degree of penetration (40-50) from the refinery of the cycle, and obtained Recycled asphalt concrete from Salah Al-Din Road, Al-Ameriya area in Baghdad are prepared. Use five rati

shoulder joint by preparing special exercises for the youth-category wrestling, and through the researchers' follow-up to the wrestling game and their work in the field of rehabilitation and physical therapy, noticing that most of the wrestling players suffer from the shoulder joint pain despite their visit to the specialist doctor and take Treatment, so the researchers saw to study this problem and restore the recovery of the injured through special exercises and a suitable qualification program for the shoulder joint muscles, the goal of research in preparing special exercises and knowing its effect on the rehabilitation of the background muscle of the shoulder for the youth wrestling category. The researchers assumed that there are stati

Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci