Objective: The present study aims to investigate molecular confirmation for <i>Cryptosporidium</i> species in fish handlers in Baghdad City, central Iraq. Materials and Methods: Sixty stool samples were collected between early November 2023 and late April 2024. All samples were examined phenotypically using a modified Ziehl-Neelsen stain and genotypically (nested polymerase chain reaction technique) based on a partial sequence of 18S rRNA genes with sequencing and phylogenetic tree analysis. Results: The total molecular results identified <i>Cryptosporidium parvum</i> with an infection rate of 45% (27/60). A higher infection rate of 51.9% (14/27) was found in the age group between 15 and 35 years, and male

The concept of the active contour model has been extensively utilized in the segmentation and analysis of images. This technology has been effectively employed in identifying the contours in object recognition, computer graphics and vision, biomedical processing of images that is normal images or medical images such as Magnetic Resonance Images (MRI), X-rays, plus Ultrasound imaging. Three colleagues, Kass, Witkin and Terzopoulos developed this energy, lessening “Active Contour Models” (equally identified as Snake) back in 1987. Being curved in nature, snakes are characterized in an image field and are capable of being set in motion by external and internal forces within image data and the curve itself in that order. The present s

In this paper, a new class of nonconvex sets and functions called strongly -convex sets and strongly -convex functions are introduced. This class is considered as a natural extension of strongly -convex sets and functions introduced in the literature. Some basic and differentiability properties related to strongly -convex functions are discussed. As an application to optimization problems, some optimality properties of constrained optimization problems are proved. In these optimization problems, either the objective function or the inequality constraints functions are strongly -convex.&nbsp;

The research aims to detect the problems of educational reality faced by university professors and identify statistically significant differences in the academic problems of university instructors. It has adopted an analytical descriptive research approach to achieve research objectives and identifies the study community with professors of public and private universities. A random sample of 250 instructors was selected for the purpose of applying the questionnaire to them, knowing the academic problems encountered in the course of their work at universities, and adopting appropriate statistical means to process and analyze the data. The research concluded with a set of results, including that all fields (infrastructure, admission of

A novel technique Sumudu transform Adomian decomposition method (STADM), is employed to handle some kinds of nonlinear time-fractional equations. We demonstrate that this method finds the solution without discretization or restrictive assumptions. This method is efficient, simple to implement, and produces good results. The fractional derivative is described in the Caputo sense. The solutions are obtained using STADM, and the results show that the suggested technique is valid and applicable and provides a more refined convergent series solution. The MATLAB software carried out all the computations and graphics. Moreover, a graphical representation was made for the solution of some examples. For integer and fractional order problems, solutio

The purpose of this study is to investigate the research on artificial intelligence algorithms in football, specifically in relation to player performance prediction and injury prevention. To accomplish this goal, scholarly resources including Google Scholar, ResearchGate, Springer, and Scopus were used to provide a systematic examination of research done during the last ten years (2015–2025). Through a systematic procedure that included data collection, study selection based on predetermined criteria, categorisation based on AI applications in football, and assessment of major research problems, trends, and prospects, almost fifty papers were found and analysed. Summarising AI applications in football for performance and injury p

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne