In this paper, a theoretical study to the effect of journal misalignment on the static characteristics of oil filled porous journal bearing when lubricated with couple stress fluid has been carried out.

The analytical model used through this work is for a bearing with isotropic permeability. Considering isotropic permeability the Reynolds' equation for the oil film is modified to include a so – called filter term and the effect of fluid coupled stress. The pressure equation for the porous medium is obtained from Darcy's law and continuity equation. The equation which was used to evaluate the oil film thickness was modified to include the effect of possible misalignment in longitudinal and transverse directions. The governing eq

t-Self-Compacting Concrete (SCC) reduces environmental noise and has more workability. This research presents an investigation of the behavior of SCC under mechanical loading (impact loading). Two types of cement have been used to produce SCC mixtures, Ordinary Portland Cement (OPC) and Portland Limestone Cement (PLC), which reduces the emission of carbon dioxide during the manufacturing process. The mixes were reinforced with Carbon Fiber Reinforced Polymer (CFRP) which is usually used to improve the seismic performance of masonry walls, to replace lost steel reinforcements, or to increase column strength and ductility. Workability tests were carried out for fresh SCC. Prepared concrete slabs of 500×500×50mm were tested for lo

I mpact strength for Epoxy/Polyurethane, Blends and their composites with two
layers of Glass fibers (0-90) are calculated.
The impact strength of the blends and composites decrease with increasing weight
by weisht percentage of polyurethane . This result is attributed to the high elasticity
of PU , and to the immiscibility between the polymer blends as well as the fiber
delaminates

The study explains how translation participates in shaping the responses of different communities to global awareness campaigns, and the extent to which language and translated terminology from English to Arabic influence the audience’s understanding and interaction with the awareness messages delivered by these campaigns. The research aims to explore the problems in translating these campaign titles, which may lead to vague meaning, as the process is considered a major challenge due to the need to navigate linguistic nuances, cultural differences, and contextual variations. In this study, some awareness phrases were randomly chosen from many types of organizations’ campaigns, like the WHO, UN, mental health, and Empowerment, a

Background: Trastuzumab is a blockbuster monoclonal antibody that has revolutionized the treatment of HER2-positive breast and gastric cancers. With the increasing availability of biosimilar monoclonal antibodies in clinical practice, independent verification of biosimilarity using products sampled from a real-world supply chain is important to assure clinicians and the patients to use these products confidently. Objective: The aim of this study is to assess the biosimilarity of AryoTrust, a trastuzumab biosimilar, in comparison with the reference product Herceptin. AryoTrust and Herceptin products were randomly withdrawn from Iraqi hospitals to reflect medicines administered in real clinical settings. Methods: AryoTrust and Hercept

This study aimed to prepare a healthy Nutella rich in specific fatty acids (e.g., oleic, palmitic, and stearic acids) and fat-soluble vitamins (A, E, K, and D) by replacing sunflower oil with anhydrous milk fat (ghee) at substitution levels of 10%, 20%, and 30%. The effect of this substitution on the physicochemical and sensory properties of the laboratoryproduced Nutella was investigated. The chemical composition analysis revealed significant differences (p < 0.05) in fatty acid profiles and vitamin content among the treatments, while some other compositional parameters showed no significant differences. The percentages of oleic, palmitic, stearic, and linolenic fatty acids increased significantly with increasing substitution levels of anh

Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was ad