KE Sharquie, JR Al-Rawi, AA Noaimi, MM Jabir, Iraqi Postgraduate Medical Journal, 2009

S Khalifa E, AR Jamal R, N Adil A, J Munqithe M…, 2009

Antibiotics resistant bacteria have become a global problem as a result of the unprogrammed use of antibiotics, resulting in bacterial strains resistant to many antibiotics, or to all available antibiotics. Plants are a good source of primary and secondary metabolites that have a major role in reducing silver nitrate to silver nanoparticles (AgNPs). The production of these nanoparticles were carried out by using aqueous extract of Carthamus oxycantha M.Bieb. This can be verified by color change of the reaction solution from yellow to dark brown because of the excitation of the surface plasmon resonance. AgNPs were characterized by UV-Vis spectroscopy, where they recorded the peak at 420 nm. Fourier Transformation-infrared (FTIR)

This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big

سرطان البنكرياس هو مرض ذو معدل وفيات مرتفع، ولا يزال التشخيص المبكر لسرطان البنكرياس يمثل تحديًا. يظل معدل البقاء النسبي لمدة 5 سنوات أقل من 8%، والاستراتيجيات العلاجية غير فعالة في زيادة معدلات بقاء المريض على قيد الحياة. في خلايا سرطان البنكرياس، ارتبطت مقاومة العلاج بالتغيرات الجينية التي تؤدي إلى ظهور مسارات خلوية شاذة؛ ولذلك، هناك ما يبرر ايجاد استراتيجيات جديدة لعلاج هذا المرض. هنا، سعينا لاستكشاف

Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d

Biologically active natural compounds are molecules produced by plants or plant-related microbes, such as endophytes. Many of these metabolites have a wide range of antimicrobial activities and other pharmaceutical properties. This study aimed to evaluate (in vitro) the antifungal activities of the secondary metabolites obtained from Paecilomyces sp. against the pathogenic fungus Rhizoctonia solani. The endophytic fungus Paecilomyces was isolated from Moringa oleifera leaves and cultured on potato dextrose broth for the production of the fungal metabolites. The activity of Paecilomyces filtrate against the radial growth of Rhizoctonia solani was tested by mixing the filtrate with potato dextrose agar medium at concentrations of 15%,