A retrospective study is conducted to identify factors that improve prospective animal studies; contribute to the optimization of animal protection from all unnecessary and preventable damage. Preclinical oral histology research from 2010-2020 is evaluated and 64 studies were reviewed relating to two interventions: bone trauma and surgical incision. The harm-benefit analysis is featured in this study through the application of the recent form of Bateson's Cube. Depending on its three axes, we can assess animal suffering, the likelihood of benefit, and the importance of research. The total number of animals used in the research is 2685. Rats, 51.6%, and rabbits, 48.4%, are the most commonly used animals. Research related to bone healing acco

Pleomorphic adenoma (PA) is the most frequent benign epithelial neoplasm of salivary glands, displaying a remarkable degree of morphological variety. The aim of the study is to illustrate the clinicopathological characteristics of PA with particular emphases on epithelial cell morphology and mesenchymal elements. Materials and Methods: A total of 132 PA collected between 2002 and 2017 were recruited from Al Shahid Ghazi Al Hariri Hospital and the Department of Oral Pathology, College of Dentistry, Baghdad University, Baghdad, Iraq, and analyzed for their demographic and histopathological features. All data were analyzed using descriptive statistics. A slightly higher incidence of PA was detected in females (52.3%) compared to male subject

Acute appendicitis is one of the commonest causes of acute abdomen. There is a wide discussion and controversy on the surgical and nonsurgical treatment of acute uncomplicated appendicitis. The aim of this study was to evaluate the efficacy and outcomes of the conservative management of selected cases of acute appendicitis with an antibiotic first plan.

Cybersecurity involves protecting computer networks, systems, and data from unauthorized access and disruptions using advanced technologies. The purpose of this research is to establish a novel cyber security framework for strengthening cloud data protection. In this paper, we propose a novel Dung Beetle optimization-redefined Intelligent Random Forest (DB-IRF) for accurate detection of intrusions in a cloud environment. We obtained a dataset that includes cloud system logs and network traffic data, including normal and malicious activities, to train our proposed model. We utilized z-score normalization to pre-process the gathered raw data. Our suggested model enhances classification accuracy by integrating DB optimization with the

The research discusses the need to find the innovative structures and methodologies for developing Human Capital (HC) in Iraqi Universities. One of the most important of these structures is Communities of Practice (CoPs) which contributes to develop HC by using learning, teaching and training through the conversion speed of knowledge and creativity into practice. This research has been used the comparative approach through employing the methodology of Data Envelopment Analysis (DEA) by using (Excel 2010 - Solver) as a field evidence to prove the role of CoPs in developing HC. In light of the given information, a researcher adopted on an archived preliminary data about (23) colleges at Mosul University as a deliberate sample for t

Biological drugs have an active substance that is made by a living organism or derived from a living organism. They are one of the important therapy options used in a wide range of diseases especially life-threatening diseases. Biological therapy opens new opportunities for treating different diseases for which drug therapy is minimal, but they have considerable differences in the safety consequences in comparison with non-biological drugs. The aim of the current study was to assess the post-marketing safety profile of biological drugs used in Iraqi hospitals by the analysis of the reported adverse drug reactions regarding their severity, seriousness, preventability, expectedness, and outcome. It is a retrospective study of the individu

Database is characterized as an arrangement of data that is sorted out and disseminated in a way that allows the client to get to the data being put away in a simple and more helpful way. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work studies the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on EEG Big-data as a case study. The proposed approach showed clear enhancement for managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG r

There is various human biometrics used nowadays, one of the most important of these biometrics is the face. Many techniques have been suggested for face recognition, but they still face a variety of challenges for recognizing faces in images captured in the uncontrolled environment, and for real-life applications. Some of these challenges are pose variation, occlusion, facial expression, illumination, bad lighting, and image quality. New techniques are updating continuously. In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. The input color image is converted into a grayscale image and then transformed into a local ternary pattern before splitting the image into