Search

Since Tribulus Terrestris (TT) is known as an aphrodisiac and natural muscle-enhancing nutrition, this study aimed to investigate the effects of TT on the male reproductive system, including sex hormones, testicular histology, and sperm parameters. In this study, 35 adult male Wistar rats were randomly divided into five groups of seven rats including Control, Sham (normal saline, 2.5 ml), TT1, TT2 and TT3 (2.5, 5 and 10 mg/kg body weight, respectively). One day after receiving the last TT administration (by gavage once daily for 60 days), rats were sacrificed, testes were removed, blood samples were taken from the heart, and sperm analysis was performed. Results showed that administration of TT extract was significantly increased serum hormonal levels (Testosterone, FSH in 2.5 and 10 mg/kg, respectively), sperm parameters (sperm count and motility in 5 and 10 mg/kg of TT), and histology of the testis (the mean number of Sertoli (5 and 10 mg/kg of TT), Leydig in 2.5 mg/kg of dose) in rats (p<0.05). TT extract improves reproductive system parameters and fertility in the male rats. TT may also have beneficial effects on the male reproductive system by increasing the Testosterone hormone levels, sperm motility and testis histology. [ABSTRACT FROM AUTHOR]

Value‐at‐risk (VaR) is a widely acceptable risk measure in finance and particularly, in the portfolio selection problem (PSP). However, due to the non‐convexity, its incorporation into an optimization model makes it challenging and difficult to solve. Hence, the development of iterative‐based heuristic algorithms (IBHAs) utilizing the problem structure would be valuable. The existing IBHAs are either inefficient in terms of solution quality and running time or are just applicable to solve simple PSPs without any real‐world constraint (i.e., cardinality, position size, and transaction cost constraints). To overcome these shortcomings, in this paper, we present a novel IBHA to efficiently solve the PSP with real‐world constraints under VaR measure. Our method is based on iterative resolution of two restricted versions of the original model in which some of the binary variables utilized in the formulation of VaR measure are fixed at specific values. Computational experiments over real‐world instances indicate that not only the running time of our algorithm is short, but also its solution quality is much better than the existing IBHAs in 97% of instances with an average improvement of about 10%. [ABSTRACT FROM AUTHOR]

Multistage stochastic programming (SP) with both endogenous and exogenous uncertainties is a novel problem in which some uncertain parameters are decision-dependent and others are independent of decisions. The main difficulty of this problem is that nonanticipativity constraints (NACs) make up a significantly large constraint set, growing very fast with the number of scenarios and leading to an intractable model. Usually, a lot of these constraints are redundant and hence, identification and elimination of redundant NACs can cause a significant reduction in the problem size. Recently, a polynomial time algorithm has been proposed in the literature which is able to identify all redundant NACs in an SP problem with only endogenous uncertainty. In this paper, however, we extend the algorithm proposed in the literature and present a new method which is able to make the upper most possible reduction in the number of NACs in any SP with both exogenous and endogenous uncertain parameters. Proving the validity of this method is another innovation of this study. Computational results confirm that the proposed approach can significantly reduce the problem size within a reasonable computation time. [ABSTRACT FROM AUTHOR]