Acute myeloid leukemia (AML) represents the most prevalent type of acute leukemia in adults and is responsible for approximately 80% of all cases. The tumor suppressor gene (TP53) is a gene that has been frequently studied in cancer, and mutations in this gene account for about 50% of human cancers. This study aims to evaluate the correlation between two single nucleotide polymorphisms (SNPs) in the gene: rs1042522 and rs1642785, and a group of Iraqi patients suffering from pre-diagnostic acute myeloid leukemia (AML). Blood samples were collected from sixty patients (26 males and 34 females) and sixty controls (26 males and 34 females); these subjects were matched in gender, age, and ethnicity. Genomic DNA has been extracted fro

Cost is the essence of any production process for it is one of the requirements for the continuity of activities so as to increase the profitability of the economic unit and to support the competitive situation in the market. Therefore, there should be an overall control to reduce the cost without compromising the product quality; to achieve this, the management should have detailed credible and reliable information about the cost to be measured, collected, understood and to analyze the causes for the spread of deviations and obstacles the management faces, and to search for the factors that trigger the emergence of these deviations and obstacles

Digital Models of Elevations (DEMs) Using Surfer 16, which are interpolated to create three-dimensional controls for the entire terrain, are typically used in visualization of geospatial entities. The interpolation method used determines how accurate the resulting terrain model will be, hence it is necessary to compare the effectiveness of various approaches in this situation. Numerous generic interpolation techniques, using inverse distance to a power, triangulation as with linear interpolation, the nearest neighbor, and kriging, have been studied. These interpolation techniques produced DEMs. With the aid of SURFER software 16, the primary goal of this effort was to introduce the DEM using a spatial interpolation method and to pre

Producing pseudo-random numbers (PRN) with high performance is one of the important issues that attract many researchers today. This paper suggests pseudo-random number generator models that integrate Hopfield Neural Network (HNN) with fuzzy logic system to improve the randomness of the Hopfield Pseudo-random generator. The fuzzy logic system has been introduced to control the update of HNN parameters. The proposed model is compared with three state-ofthe-art baselines the results analysis using National Institute of Standards and Technology (NIST) statistical test and ENT test shows that the projected model is statistically significant in comparison to the baselines and this demonstrates the competency of neuro-fuzzy based model to produce

This research suggests a robust and systematic way for Arabic Sentiment Analysis using a vast dataset of 66,666 text reviews. One of the main advantages of this study is that the dataset was perfectly balanced (33,333 positive samples and 33,333 negative samples). In machine learning, this 50/50 split is important because it eliminates class bias and enables the predictive model to treat both sentiment classes equally. As shown in the values of the metrics — overall accuracy, weighted precision, weighted recall, and F1 score — there is great similarity among them, indicating a stable and reliable assessment of the model's real potential throughout the Arabic dataset. Based on data profile, the average word count per review is 42.3

This paper offers a systemic review of the deep learning methods to detect violence on campus, which is a critical issue in intelligent surveillance to improve the student safety and prompt cut off of violent accidents. The review reviews studies published 2018-2025, concentrating on model structure to detect fights, bullying, vandalism, and aggressive behavior on problematic campuses due to occlusion and light variations and complicated human interactions. The research design includes a comparative study of different deep learning networks, such as CNNs, RNNs, 3D CNNs, attention-based networks, transformers, graph neural networks, neuro-fuzzy, and multimodal systems and federated learning methods. The paper also assesses benchmark

Digital Models of Elevations (DEMs) Using Surfer 16, which are interpolated to create three-dimensional controls for the entire terrain, are typically used in visualization of geospatial entities. The interpolation method used determines how accurate the resulting terrain model will be, hence it is necessary to compare the effectiveness of various approaches in this situation. Numerous generic interpolation techniques, using inverse distance to a power, triangulation as with linear interpolation, the nearest neighbor, and kriging, have been studied. These interpolation techniques produced DEMs. With the aid of SURFER software 16, the primary goal of this effort was to introduce the DEM using a spatial interpolation method and to pre