Genetic variation was studied in 22 local and imported samples collected from local Iraqi market by using Single sequence repeat (SSR-PCR). Six primers set were used in this study. These primers produced 33 bands. Molecular weights of these bands ranged between 100 bp to 1500 bp. The number of polymorphic bands is 24, whereas the number of monomorphic bands is 9. The results of Dendrogram of the studied samples depended on SSR-PCR results by using Jaccard coefficient for genetic similarity was distributed the samples into 10 groups. This Dendrogram revealed a higher similarity between Iraqi/Balad green bell pepper and Iraqi/Yousifia green bell pepper with 1 value. This value is the highest between samples in comparison with lowest values (0

ABSTRACT Purpose: The determination of standard scores and levels for some mental skills by researchers is of great importance, especially if it matches the target research sample, Method: as the researchers used the descriptive approach in the survey method, and the researchers chose the sample of youth players for clubs for the season (2022-2021), numbering (127) players, and the researchers identified the scale and procedures and applied it to the research sample, Results: obtained the results that were processed, extracted grades and standard levels, and then interpreted them and obtained conclusions, Conclusion: the most important of which are: The standard levels of mental skills reached the results of the sample studied within the

Coronary artery disease (CAD) is the leading cause of death worldwide. Certain genetic polymorphisms play an important role in this multifactorial disease, being linked with increased risk of early onset CAD.

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

Autoría: Nuha Mohsin Dhahi. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 5, 2022. Artículo de Revista en Dialnet.