This work aims to see the positive association rules and negative association rules in the Apriori algorithm by using cosine correlation analysis. The default and the modified Association Rule Mining algorithm are implemented against the mushroom database to find out the difference of the results. The experimental results showed that the modified Association Rule Mining algorithm could generate negative association rules. The addition of cosine correlation analysis returns a smaller amount of association rules than the amounts of the default Association Rule Mining algorithm. From the top ten association rules, it can be seen that there are different rules between the default and the modified Apriori algorithm. The difference of the obta

The tensions and crises and the psychological pressure as well as the rapid changes and great development which is taking place in the present time. And  witnessing community of wars and conflicts that give rise to future concern among members of the community in general and students in particular, as it included the current research a number of chapters, the First chapter contains the research problem, the important goal, then set researcher terminology that has defined and contained in the title of research in the form (concern the future, artistic expression, middle school). The Second chapter included three sections, the first included the nature of adolescence and traits, characteristics and pr

Introduction: The stringent response is a bacterial adaptation mechanism triggered by stress conditions, including nutrient limitation. This response helps bacteria survive under harsh conditions, such as those encountered during infection. A key feature of the stringent response is the synthesis of the alarmone (p)ppGpp, which influences various bacterial phenotypes. In several bacterial species, stringent response activation significantly affects biofilm formation and maintenance. Methods: Clinical specimens were collected from multiple hospitals in Baghdad, Iraq. Staphylococcus aureus was identified using conventional biochemical tests. The PCR technique was applied to detect mecA, icaA, and icaD genes, while the Vitek 2 compac

The opportunistic multidrug resistance pathogen Pseudomonas aeruginosa has one or several flagella, and the numbers of these sophisticated machines are regulated by the flagellar regulator gene FleN. The flagellar hook gene FlgE is important for its synthesis, motility and tolerance to antibiotics. Bacteriahave resistance to antibiotics, especially to cephalosporin beta-lactam antibiotics. For the current study, 102 clinical specimens were collected and identified using routine laboratory tests and confirmed by Vitek-2 compact system.  A total of 33 isolates of P. aeruginosa were identified. The antibiotic susceptibility test was done by the Vitek 2 Compact system. Flagellar gene detected by conventional PCR revealed that the FleN

FLI1 is a member of ETS family of transcription factors that regulate a variety of normal biologic activities including cell proliferation, differentiation, and apoptosis. The expression of FLI1 and its correlation with well-known breast cancer prognostic markers (ER, PR and HER2) was determined in primary breast tumors as well as four breast cancer lines including: MCF-7, T47D, MDA-MB-231 and MDA-MB-468 using RT-qPCR with either 18S rRNA or ACTB (β-actin) for normalization of data. FLI1 mRNA level was decreased in the breast cancer cell lines under study compared to the normal breast tissue; however, Jurkat cells, which were used as a positive control, showed overexpression compared to the normal breast. Regarding primary breast carcinoma