This study was carried out to evaluate parasitological and immunological of the effect of chitosan and chitosannanoparticles loaded with spiramycin on toxoplasmosis infected mice. After injection intra peritoneal with 103viable tachyzoites for acute infection, treatments given for seven days. Peritoneal fluid examination revealed a significant decrease in the number of Toxoplasmagondiitachyzoites in all treated infected mice compared with infected non-treated. The combined therapy gave better results than single. The best effect was observed in group of mice treated with spiramycin combined with chitosan nanoparticles. Also immunoglobulin Ig Manti body and gamma Interferon (INFγ), Tumor Necrosis Factor alpha (TNF-α) cytokines responses ag

             In general, researchers and statisticians in particular have been usually used non-parametric regression models when the parametric methods failed to fulfillment their aim to analyze the models  precisely. In this case the parametic methods are useless so they turn to non-parametric methods for its easiness in programming. Non-parametric methods can also used to assume the parametric regression model for subsequent use. Moreover, as an advantage of using non-parametric methods is to solve the problem of Multi-Colinearity between explanatory variables combined with nonlinear data. This problem can be solved by using kernel ridge regression which depend o

The research presents a case study of collecting materials and raw materials in a visual space that allows them to form a perception and meanings that inform the recipient by reconstructing them and inserting them into the surface of the artistic work and in such a way that the aesthetic act consists of a variety of media, touches and surfaces. The overlap of races within an environment characterized by unity. That is why the researcher in chapter one presented the problem of research, and the focus was on studying the multiplicity of materials and their aesthetic and functional role in the structure of creative work. The aim of the research is enhanced to identify the aesthetic performance function of the multiplicity of ores in the col

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

MO Khudhair, 2020