Polycystic ovary syndrome(PCOS) is a heterogeneous disorder of uncertain etiology , it is the most common endocrinopathy in women and most common cause of anovulatery infertility ,characterized by chronic anovulation and hyperandrogenemia .The present study was designed to investigate the effect of silymarin which is known to have antioxidant and insulin sensitivity effects on the  levels of glucose, insulin ,testosterone ,leutinizing hormone(LH) and progesterone .Ovulation rate and Homeostasis Model Assessment of insulin Resistance (HOMA) ratio were determined .A 3-months of treatment were conducted in 60 PCOS patients in three well-matched groups .The first one (n=20),received silymarin(750mg/day)  .The second group received

Natural convection in a porous, rectangular hollow full of saturated air was investigated numerically in the current study. The bottom side was warmed with a continuous heat flux, the right side's temperature was kept at (Tc), the left wall was opened to the surroundings, and the top side was insulated. The pertinent filled-out research parameters in the current experiment were four heat flux values (1500, 3000, 4500, and 6000 W/m²) and three Darcy’s numbers (Da1=4.025×10-10, Da2=4.025×10-8, Da3=4.025×10-6). COMSOL Multiphysics 5.5a, using finite elements and a relying Brinkman-Darcy extended model, was employed to resolve government equations. Local thermal balance simulation was assumed in this solution. Energy transfer and

     Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E