Ursolic acid (UA, 3 ?-hydroxy-urs-12-en-28-oic acid) are isomeric triterpenic acids. The high quantities of pentacyclic triterpenoids in Scabiosa species seems to be obvious and there is an evidence that most of pentacyclic triterpenoids that have been isolated are saponins. This is one of the most important characteristic of the genus Scabiosa, the main aglycones are ursolic acid and oleanolic acid. In the current study, isolation from the aerial part and roots of Scabiosa palaestina L. was performed using Preparative HPLC. Furthermore, detection and quantitation of ursolic acid was performed by high performance thin layer chromatography (HPTLC). The identification of isolated triterpenoid involves two methods including FT-IR coupl

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

Shoulder immobilization is one of the injuries that lead to disability and loss of movement in the joint within a short time, which called the researchers to find appropriate therapeutic means to rehabilitate this injury. They prepared a rehabilitation program accompanying the reflexology technique to rehabilitate the injury of the immobilized shoulder of the small degree and improve the range of movement and muscle strength working on the shoulder joint The sample was selected from the male patients aged (40-50) years. The muscle strength test was used using the force sensor, the shoulder range test from the flexion and extension position and the visual analog test to measure the level of pain. The study concluded that the pre-rehabilitati

Stuck pipe is a prevalent and costly issue in drilling operations, with the potential to cost the petroleum industry billions of dollars annually. To reduce the likelihood of this issue, efforts have been made to identify the causes of stuck pipes. The main mechanisms that cause stuck pipes include drill cutting of the formation, inappropriate hole-cleaning, wellbore instability, and differential sticking forces, particularly in highly deviated wellbores. The significant consequences of a stuck pipe include an increase in well costs and Non-Productive Time (NPT), and in the worst-case scenario, the loss of a wellbore section and down-hole equipment, or the need to sidetrack, plug, or abandon the well. This paper provides a comprehensive

Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is s

One of the significant stages in computer vision is image segmentation which is fundamental for different applications, for example, robot control and military target recognition, as well as image analysis of remote sensing applications. Studies have dealt with the process of improving the classification of all types of data, whether text or audio or images, one of the latest studies in which researchers have worked to build a simple, effective, and high-accuracy model capable of classifying emotions from speech data, while several studies dealt with improving textual grouping. In this study, we seek to improve the classification of image division using a novel approach depending on two methods used to segment the images. The first