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This research aims to conduct a linguistic analysis of the translation of the novel "The Corpse Washer" by the Iraqi author Sinan Antoon. The main objective is to explore the challenges and strategies involved in translating this literary work, particularly the difficulties in translating the Baghdadi dialect and the obstacles it poses for non-native speakers. Employing a descriptive research methodology, the study examines the linguistic aspects of the translation, specifically selected conversational texts in the novel. It identifies the difficulties faced by translators in preserving the essence of the original novel and presents instances where errors occurred in translating vocabulary, conversational expressions, proverbs, and idi

ABSTRACT

            The controversy is currently revolving around industrial additives, including antioxidants, their negative effects on consumer health and the emergence of various and various diseases, which led scientists and researchers to intensify most studies on natural antioxidants and their synthesis from medicinal plants mentioned in ancient medicine and in divine books as potential antioxidants of increasing importance. Therefore, this study was designed to synthesize silver nitrate particles from plant leaf extracts (Figs, Olives, and Moringa) and study their effect on bacterial inhibition of each of the undesirable Coliform bacteria (E-Coli,

Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

Introduction The Hybrid Gamma Camera (HGC) is being developed to enhance the localisation of radiopharmaceutical uptake in targeted tissues during surgical procedures such as sentinel lymph node (SLN) biopsy. Purpose To assess the capability of the HGC, a lymph-node-contrast (LNC) phantom was constructed for an evaluative study simulating medical scenarios of varying radioactivity concentration and SLN size. Materials and methods The phantom was constructed using two methyl methacrylate PMMA plates (8 mm thick). The SLNs were simulated by drilling circular wells of diameters ranging between 10 mm and 2.5 mm (16 wells in total) in one plate. These simulated SLNs were placed underneath scattering material with thicknesses ranging between 5 mm

Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

This research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB

Morphologies of ceramic hollow fiber membranes prepared by a combined phase-inversion and sintering method were studied. The organic binder spinning solution containing suspended Al₂O₃ powders was spun to a hollow fiber precursor, which was then sintered at elevated temperatures( 300 ˚C, 1400 ˚C, 25 ˚C) in order to obtain the Al₂O₃ hollow fiber membranes. The spinning solution consisted of polyether sulfone (PES), N-methyl-2-pyrrolidone (NMP), which were used as polymer binder, solvent, respectively. The prepared Al₂O₃ hollow fiber membranes were characterized by a scanning electron microscope (SEM). It is believed that finger-like void formation in asymmetric ceramic membranes is initiated by hydrodynamically unstable vis

MRY *Khalid Sh. Sharhan, *Naseer Shukur Hussein, INTERNATIONAL JOURNAL OF DEVELOPMENT IN SOCIAL SCIENCE AND HUMANITIES, 2021