Inhibition of T cell derived cytokine production could help suppress osteoclast differentiation in inflammatory skeletal disorders. Bisphosphonates are typically prescribed to prevent inflammatory bone loss but are not tolerated by all patients and are associated with an increased risk of osteonecrosis of the jaw. In light of this other anti-resorptives such as phytoestrogens are being considered. However the effect of phytoestrogens on T cell-induced osteoclast formation is unclear. The effect of genistein and coumestrol on activated T cell-induced osteoclastogenesis and cytokine production was therefore examined. Concentrations of genistein and coumestrol (10−7 M) previously shown to directly inhibit osteoclast formation also suppressed

Environmental stress affects the yield of sorghum. This impact can be reduced by seed stimulation technique and determining the appropriate planting date. An experiment was conducted in the spring and fall seasons of 2022. Randomized complete block design with split-plot arrangement in four replications was used. Planting dates (spring season: February 15th, March 1st, 15th, April 1st, 15th; fall season: June 15th, July 1st, 15th, August 1st, 15th) were assigned to the main plots. Seed stimulation treatments (banana peel extract 35% + citric acid 100 mg L-1 and soaking in distilled water only) were applied to the subplots. The interaction treatment of soaking with banana peel extract + citric acid and the planting date of April 15th showed

The aim of this work was to capture solar radiation and convert it into solar thermal energy by using a storage material and the heat transfer fluid like oil and water and comparison between them, we used the evacuated tube as a receiver for solar radiation, The results showed that the oil better than water as storage material and the heat transfer fluid and the effective thermal conductivity material and good for power level, rates and durations of charge and discharge cycles.

Variable selection is an essential and necessary task in the statistical modeling field. Several studies have triedto develop and standardize the process of variable selection, but it isdifficultto do so. The first question a researcher needs to ask himself/herself what are the most significant variables that should be used to describe a given dataset’s response. In thispaper, a new method for variable selection using Gibbs sampler techniqueshas beendeveloped.First, the model is defined, and the posterior distributions for all the parameters are derived.The new variable selection methodis tested usingfour simulation datasets. The new approachiscompared with some existingtechniques: Ordinary Least Squared (OLS), Least Absolute Shrinkage

In this research, we use fuzzy nonparametric methods based on some smoothing techniques, were applied to real data on the Iraqi stock market especially the data about Baghdad company for soft drinks for the year (2016) for the period (1/1/2016-31/12/2016) .A sample of (148) observations was obtained in order to construct a model of the relationship between the stock prices (Low, high, modal) and the traded value by comparing the results of the criterion (G.O.F.) for three techniques , we note that the lowest value for this criterion was for the K-Nearest Neighbor at Gaussian function .

     The problem in the design of a cam is the analyzing of the mechanisms and dynamic forces that effect on the family of parametric polynomials for describing the motion curve. In present method, two ways have been taken for optimization of the cam size, first the high dynamic loading (such that impact and elastic stress waves propagation) from marine machine tool which translate by the roller follower to the cam surface and varies with time causes large contact loads and second it must include the factors of kinematics features including the acceleration, velocity, boundary condition and the unsymmetrical curvature of the cam profile for the motion curve.

     In the theoretical solution