We studied the relationship between DNA sequencing of interleukin-10 (IL-10) gene promoter for -1082 (A/G) and -592 (A/C) positions with the concentration of IL-10 in blood serum of Iraqi children with type 1 diabetes mellitus (T1D). Fifty blood serum samples collected from children with age ranged between 7-12 years. Thirty-five blood samples collected from patient children with T1D, and compared with 15 healthy children age matched as control sample. The results revealed decreasing in anti-inflammatory IL-10 concentration in T1D patient’s blood serum (0.068 Pg/ml) as compared with the control sample (0.111 Pg/ml). No significant differences were found in interleukin concentration between the studied samples when they analyzed with the M

The main aim of this research is to introduce financing cost optimization and different financing alternatives. There are many studies about financing cost optimization. All previous studies considering the cost of financing have many shortcomings, some considered only one source of financing as a credit line without taking into account different financing alternatives. Having only one funding alternative powers, restricts contractors and leads to a very specific financing model. Although it is beneficial for the contractor to use a long-term loan to minimize interest charges and prevent a substantial withdrawal from his credit line, none of the existing financial-based planning models have considered long-term loans in

The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic