Discriminant analysis is a technique used to distinguish and classification an individual to a group among a number of  groups based on a linear combination of a set of relevant variables know discriminant function. In this research  discriminant analysis used to analysis data from repeated measurements design. We  will  deal  with the problem of  discrimination  and  classification in the case of  two  groups by assuming the Compound Symmetry covariance structure  under  the  assumption  of  normality for  univariate  repeated measures data.

The main purpose of the research is to demonstrate the importance of the insurance sector in the economy through its role in providing security for all economic sectors and thus stimulating the gross domestic product and reducing dependence on the output of the oil sector, which may expose the Iraqi economy to several problems and imbalances, I have found that there is a great weakness in the role of the insurance sector in Iraq at the level of government, companies and individuals, and the reason for this is the lack of policies supporting the insurance sector and the lack of work in the strategy of economic diversity and the decrease of security awareness by individuals so became Developing the sector to ensure the urgent need

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

The 17 α-ethinylestradiol (EE2) adsorption from aqueous solution was examined using a novel adsorbent made from rice husk powder coated with CuO nanoparticles (CRH). Advanced analyses of FTIR, XRD, SEM, and EDSwere used to identify the classification parameters of a CRH-like surface morphology, configuration, and functional groups. The rice husk was coated with CuO nanoparticles, allowing it to create large surface area materials with significantly improved textural qualities with regard to functional use and adsorption performance, according to a detailed characterization of the synthesized materials. The adsorption process was applied successfully with elimination effectiveness of 100% which can be kept up to 61.3%. The parameters of ads

The newly synthesized Schiff base ligand (E)-2-((2-phenylhydrazono)methyl)naphthalen-1-ol (phenyl hydrazine derivative), is allowed to react with each of the next mineral ion: Ni2+, Cu2+, Zn2+andCd2+successfully resulting to obtain new metal complexes with different geometric shape. The formation of Schiff base complexes and also the origin Schiff base is indicated using LC-Mass that manifest the obtained molar mass, FT-IR proved the occurrence of coordination through N of azobenzene and O of OH by observing the shifting in azomethines band and appearing of M-N and N-O bands. Moreover, we can also detect by such apparatus, the presence of aquatic water molecule inside the coordination sphere. UV-Vis spectra of all resultants reveale

Background:Ankylosing spondylitis (AS) is a progressive, chronic inflammatory illness with an unclear etiology that explicitly targets the vertebral column, peripheral joints, and extraarticular tissues. The purpose of this research was to investigate if the existence of single nucleotide polymorphisms (SNPs) in the promoter region of the tumor necrosis factor-alpha (TNF-α) gene at positions -1031T/C (rs199964), -857C/T (rs1799724) and -806C/T (rs4248158) in a sample of Iraqi AS patients could influence the patients' outcomes with etanercept.

Methods:Sixty patients with established AS receiving only etanercept were selected to enroll in this study, with a mean age of 40.75±8.6