Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

The humid and warm conditions in greenhouses provide an excellent environment for pests’ living conditions, and therefore, they provide ideal medium for alien introductions. Molluscs are among the most significant pests that infest plastic covered greenhouses. To identify and report their mollusc species, 23 greenhouses in Iraq were surveyed between March 2023 and April 2024. Of these, 11 were found to be infested with snails. A total of 158 specimens were collected and morphologically identified to seven species: Monacha obstructa (L. Pfeiffer, 1842), Eobania vermiculata (O.F. Müller, 1774), Xeropicta krynickii (Krynicki, 1833), Rumina decollata (Linnaeus, 1758), Polygyra cereolus (Megerle Von Mühlfeld, 1818), Cochlicella barba

Terrorist crime is considered a serious act that outweighs all other crimes in terms of impact and result, because it has a wide range on societies, and it also contains a great thing of danger represented in its purpose, and here describing terrorism as a crime is a description that does not give the full right to this behavior or that it It abbreviates it and does not show its actual reality, given that terrorism contains several different crimes and the roles of its contributors, and these roles are necessary to reach the result or the end. In which each episode is complementary to the other, it is not a single act, but rather several joint and complex actions that in turn all lead to the result, and the agreement in the terrorist pro

The concept of -closedness, a kind of covering property for topological spaces, has already been studied with meticulous care from different angles and via different approaches. In this paper, we continue the said investigation in terms of a different concept viz. grills. The deliberations in the article include certain characterizations and a few necessary conditions for the -closedness of a space, the latter conditions are also shown to be equivalent to -closedness in a - almost regular space. All these and the associated discussions and results are done with grills as the prime supporting tool.

In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

This research aims to shed light on some phonetic linguistic terms used in the Arabic phonetic lesson for the purpose of monitoring, analyzing and tracking its developments. Such a step helps to standardize and weigh between them. The study follows a descriptive-analytical approach; it surveys the problem of the phonetic linguistic term, and its linguistic exactness. Then, it examines some phonetic terms in the Arabic phonetic lesson, such as phonology and phonology; intensity, looseness and mediation; the production, articulatory, transition, position, and the two vocal chords. One of the most prominent conclusions of the study is that the phonetic linguistic terminology enjoyed a tangible development since its infancy, given that phone

 The research has been based on two main variables (information and communication technology) and the quality of blended education (physical and electronic), aiming to reveal the relationship between four dimensions (physical devices, software, databases, communication networks) and the elements of education represented by (the teacher, the student, the teaching process, curriculum).  The methodology and post-analysis-based research were conducted at the Technical College of Management / Baghdad through polling the opinions of a random sample that included (80) teachers out of (86) and the number of students (276) representing a random sample from all departments of the college (for the morning study) out of (3500) stud