The following study was conducted to investigate the correlation between the expression of three different genes (NOB1, DDX47, CD101( with the occurrence and development of chronic myeloid leukemia (CML) in Iraq. The difference in the expression of these genes between patients and healthy controls was studied. Moreover the correlation of age and gender with CML occurrence and comparing with control was also examined. Results showed significant increases in mean of gene expression level (ΔCt) of patient groups for all genes compared to the corresponding ΔCt means in control group, also the gene expression folding (2-ΔΔCt) reflect significant differences in the expression of these genes and CD101, mRNA showed the highest level in CML pati

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Singing has significant importance being a major basis for the expressive and cultural production of the societies and a real companion that reflects their artistic career and is strongly connected to the reality of the peoples and the production of the individuals, who are geniuses of arts and culture.
Rural singing represents one of the most well-known artistic singing styles in Iraq, which truly embodied the Iraqi national identity. However, it remained confined to the countryside and did not spread due to the lack of mass media and the recording technologies at that time. It has been pure virgin singing art. The theoretical framework is divided into three axes:

• The Iraqi singing heritage in the twentieth century, a hi

To perform a secure evaluation of Indoor Design data, the research introduces a Cyber-Neutrosophic Model, which utilizes AES-256 encryption, Role-Based Access Control, and real-time anomaly detection. It measures the percentage of unpredictability, insecurity, and variance present within model features. Also, it provides reliable data security. Similar features have been identified between the final results of the study, corresponding to the Cyber-Neutrosophic Model analysis, and the cybersecurity layer helped mitigate attacks. It is worth noting that Anomaly Detection successfully achieved response times of less than 2.5 seconds, demonstrating that the model can maintain its integrity while providing privacy. Using neutrosophic sim

This research aims primarily to highlight personal tax exemptions A comparative study with some Arab and European regulations. And by conducting both theoretical comparative analyses. Most important findings of the study is the need to grant personal and family exemptions that differ according to the civil status of the taxpayer (single or married). In other words, the exemption increases as the number of family members depend on its social sense. Also taking into account some incomes that require a certain effort and looking at the tax rates, it is unreasonable for wages to be subject to the same rates applied to commercial profits.      

has experienced a step-change since the inception of ambient mass spectrometry removed the requirement for samples to be investigated under vacuum conditions. Approaches based on surface– plasma interactions are especially promising, including PADI. Whilst the mechanisms involved in generating PADI spectra still need to be unravelled, PADI shows significant promise to become a valuable and versatile tool in the instrumental arsenal available to the surface analyst

Abstract The aim of this paper is to shed light on the theme of Gender Struggle and Women’s Predicament in Tennessee Williams’ A Street Car Named Desire .The paper tries to show William's dealings with the critical social themes like Men's Brutality and women's predicament. The paper exposes the complete shift of the balance of power between the genders in America after the two world wars. Williams illustrates society’s changing attitudes towards masculinity and denounces the society's attitudes towards women in America at that time. He rebels against the cruelty of the modern age and regrets the disintegration of the values of the south and their being replaced by the disruptive forces of modern life. In the end of the play, brutalit

The primary objective of this research be to develop a novel thought of fibrewise micro—topological spaces over B. We present the notions from fibrewise micro closed, fibrewise micro open, fibrewise locally micro sliceable, and fibrewise locally micro-section able micro topological spaces over B. Moreover, we define these concepts and back them up with proof and some micro topological characteristics connected to these ideas, including studies and fibrewise locally micro sliceable and fibrewise locally micro-section able micro topological spaces, making it ideal for applications where high-performance processing is needed. This paper will explore the features and benefits of fibrewise locally micro-sliceable and fibrewise locally

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med