Since God created human and had him live on Earth, he was certain and focused on marriage and having lineage for the purpose of development of this Earth which he – God - provided for humans.

We notice that he – human - was interested in curing  disease of the genital system, (whether male and female) and he used different methods for that and what is available in every era and periods, we saw him exceeded in using different medical Herbs in different area of Earth and used it efficiently for healing and getting the best results they even inherited from one generation  to another, and they didn't even stop here,

In this paper a theoretical attempt is made to determine whether changes in the aorta diameter at different location along the aorta can be detected by brachial artery measurement.  The aorta is divided into six main parts, each part with 4 lumps of 0.018m length. It is assumed that a desired section of the aorta has a radius change of 100,200, 500%. The results show that there is a significant change for part 2 (lumps 5-8) from the other parts. This indicates that the nearest position to the artery gives the significant change in the artery wave pressure while other parts of the aorta have a small effect.

CD40 is a type 1 transmembrane protein composed of 277 amino acids, and it belongs to the tumor necrosis factor receptor (TNFR) superfamily. It is expressed in a variety of cell types, including normal B cells, macrophages, dendritic cells, and endothelial cells, as a costimulatory molecule. This study aims to summarize the CD40 polymorphism effect and its susceptibility to immune-related disorders. The CD40 gene polymorphisms showed a significant association with different immune-related disorders and act as a risk factor for increased susceptibility to these diseases.

This study provides an empirical and strategic contribution to the revenue management literature by investigating the transition from static cost-plus pricing to a dynamic, elasticity-based framework within state-owned extractive industries (SOEs). While dynamic pricing is extensively studied in flexible, data-rich private markets, its application in structurally rigid SOEs within transitional economies remains a critical research gap. Drawing on primary fiscal and production data from the 2024 fiscal year of the General Company for Mining Industries (SCMI), we developed a mathematical model to determine optimal pricing ( ) based on marginal cost principles and demand elasticity. The findings demonstrate that replacing rigid accounting rout

This paper reports the synthesis and use of a novel metal-organic framework (MOF), named Zr-BADS, within the thin-film nanocomposite (TFN) membranes for reverse osmosis (RO) applications. Two types of zirconium-based MOFs, Zr-BADS-1 and Zr-BADS-2, were synthesized via a solvothermal method using bicinchoninic acid disodium salt as a linker and either dimethylformamide or ethanol as solvent, respectively. TFN membranes were prepared by embedding these MOFs within the polyamide thin film supported by a polysulfone support sheet. The specific surface area of Zr-BADS-1 and Zr-BADS-2 was determined to be 396.1 and 278.6 m2/g, respectively, indicating significant surface area conducive to water permeation. Scanning electron microscopic analysis r

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