Background: despite the rise in the incidence of renal cell carcinoma attributed to availability of medical imaging, a considerable decline in mortality is an association. Morbidity-wise, the shift from radical nephrectomy to partial nephrectomy is the trend for now. Multiple scoring systems have been introduced over the past decades to help surgeons choose between radical and partial nephrectomy. One commonly used system is the RENAL nephrometry score that was first introduced by Kutikov and Uzzo in 2009.

Objective: to evaluate the role of RENAL nephrometry scoring system in predicting the surgical technique to use to resect renal masses and associated perioperative outcomes.

The purpose of this research is to prepare new vanillic acid derivatives with 1,2,4-triazole-3-thiol heterocyclic ring and evaluate their antimicrobial activity in a preliminary assessment. A multistep synthesis was established for the preparation of new vanillic acid-triazole conjugates. The intermediate of 4-(4-amino-5-mercapto-4H-1,2,4-triazol-3-yl)-2-methoxyphenol (4) reacts with different heterocyclic aldehydes (thiophene-2-carboxaldehyde, pyrrole-2-carboxaldehyde, thiophene-3-carboxaldehyde, and furfural ) in ethanol containing few drops of acetic acid yielded the corresponding 4-(4-(substituted amino)-5-mercapto-4H-1,2,4-1triazol-3-yl)-2-methoxy phenol derivatives (

The current study performs an explicit nonlinear finite element simulation to predict temperature distribution and consequent stresses during the friction stir welding (FSW) of AA 7075-T651 alloy. The ABAQUS® finite element software was used to model and analyze the process steps that involve plunging, dwelling, and traverse stages. Techniques such as Arbitrary Lagrangian–Eulerian (ALE) formulation, adaptive meshing, and computational feature of mass scaling were utilized to simulate sequence events during the friction stir welding process. The contact between the welding tool and workpiece was modelled through applying Coulomb’s friction model with a nonlinear friction coefficient value. Also, the model considered the effect o

This work studies the impact of input machining parameters of Electrical Discharge Machining (EDM) on the machining process performance. Tool steel O1 was selected as the workpiece material, copper as the electrode material, and kerosene as the dielectric medium. Experimental runs have been carried out with a Design of Experiment (DOE) technique. Twenty tests are accomplished with the current range of (18 to 24 Ampere), a pulse duration range of (150 to 200 µs), and a pulse-off time range of (25 to 75 µs). Based upon the experimental study's output results, the EDM parameter's effect (voltage of power supply, discharge current, pulse duration, and pulse pause interval) on the responses of the process represented by sur

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

Some genetic factors are not only involved in some autoimmune diseases but also interfere with their treatment, Such as Crohn's disease (CD), Rheumatoid Arthritis (RA), ankylosing spondylitis (AS), and psoriasis (PS). Tumor Necrosis Factor (TNF) is a most important pro-inflammatory cytokine, which has been recognized as a main factor that participates in the pathogenesis and development of autoimmune disorders. Therefore, TNF could be a prospective target for treating these disorders, and many anti-TNF were developed to treat these disorders. Although the high efficacy of many anti-TNF biologic medications, the Patients' clinical responses to the autoimmune treatment showed significant heterogeneity. Two types of TNF receptor (TNFR); 1 an