Novel has recently received the attention of readers and writers greatly, because of the role they play, and this indicates an important rule, which is whenever there is an art or creativity, there must be a respective criticism, and this criticism is certainly not less important than the author. So there are critics who have a prestigious literary position in the follow-up story development, and trying to describe the transformation of its elements. One of these critics is professor Fadhel Thamer, and who wants to approach one of the elements of the novel exploring, must stop on the visions of this critic about it , and that’s why we take the (character) element following the most important opinions of this critic about it.
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In this study, we set up and analyze a cancer growth model that integrates a chemotherapy drug with the impact of vitamins in boosting and strengthening the immune system. The aim of this study is to determine the minimal amount of treatment required to eliminate cancer, which will help to reduce harm to patients. It is assumed that vitamins come from organic foods and beverages. The chemotherapy drug is added to delay and eliminate tumor cell growth and division. To that end, we suggest the tumor-immune model, composed of the interaction of tumor and immune cells, which is composed of two ordinary differential equations. The model’s fundamental mathematical properties, such as positivity, boundedness, and equilibrium existence, are exami
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The relationship between government revenues and the fiscal balance represents a central pillar in the analysis of fiscal sustainability. However, its modeling faces a fundamental challenge in the form of structural uncertainty, which is not captured by point estimates in traditional models such as ARDL, as these models assume structural stability that is inconsistent with the nature of rentier economies. The current study aims to develop a fuzzy framework by constructing a Fuzzy Autoregressive Distributed Lag (FARDL) model. This is achieved through integrating the Autoregressive Distributed Lag (ARDL) approach with fuzzy logic theory, thereby enabling the incorporation of uncertainty into the inherent structure of the economic rela
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TWMS Journal of Applied and Engineering Mathematics | Volume: 16 Issue: 9
As the process of estimate for model and variable selection significant is a crucial process in the semi-parametric modeling At the beginning of the modeling process often At there are many explanatory variables to Avoid the loss of any explanatory elements may be important as a result , the selection of significant variables become necessary , so the process of variable selection is not intended to simplifying model complexity explanation , and also predicting. In this research was to use some of the semi-parametric methods (LASSO-MAVE , MAVE and The proposal method (Adaptive LASSO-MAVE) for variable selection and estimate semi-parametric single index model (SSIM) at the same time .
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Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security
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This study proposes a pioneering Ethical Artificial Intelligence (EAI) framework for advancing sustainable development in Iraq by integrating eight multidimensional sustainability indicators—administrative, technological, economic, environmental, social, legal, security, and governance. Utilizing data from 60 completed development projects, the framework combines SPSS statistical analysis, the SMART-AI model, and Artificial Neural Networks (ANN) to identify key determinants of project success and failure. Results reveal a 37% project failure rate, with administrative and technological deficiencies emerging as the most influential predictors. The SMART-AI model achieved an accuracy of 91.3% using stratified k-fold cross-validation. A bilin
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Background: Recurrent aphthous stomatitis (RAS) is one of the most common oral mucosa diseases characterized by recurrent, shallow, round or oval painful oral ulcers surrounded by inflammatory erythematous halos, the condition is chronic and self-limiting in immunocompetent patients. Aim of the study: to investigate the serum vitamin D levels in Iraqi female patients with RAS and the relationship between vitamin D levels and the severity of RAS. In this cross sectional study 30 female patients with idiopathic RAS, and 30 age and sex matched healthy controls were included, the severity of RAS is assessed by the number of oral aphthous ulcers in each attack and the frequency of attacks. Serum 25(OH) D levels were determined by the Enzy
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Fifty one patients with serologically confirmed brucellosis and 70 healthy controls were phenotyped for HLA-A, -B, -DR and -DQ antigens by using standard microlympho-cytotoxicity method, and lymphocytes defined by their CD markers (CD3, CD4, CD8 and CD19). The results revealed a significant (Pc = 0.001) increased frequency of HLA-DR8 (41.18 vs. 10.0%) in the patients . A significant increased percentage of CD8+ lymphocytes was also increased in the patients (25.15 vs. 22.0%; P = 0.006), while CD3+ lymphocytes were significantly decreased (75.1 vs. 79.4%; P = 0.02).
Hyperprolactinemia is a common endocrine abnormality caused by physiological factors like pregnancy and lactation, drug-induced factors like antipsychotics, pituitary adenomas that secrete prolactin, or stalk compression or section that reduces dopamine inhibition. Dopamine agonists cure most prolactinomas.
To assess response to treatment in micro versus macroprolactinoma.
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