modern research physics

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Alkaloids are a large group of molecules with biological, physiological and chemical activities. Plants of the genus (Podophyllaceae) are the known sources of alkaloids. In the present study the amount of total alkaloids of tubers of from two different regions of Iran, Marivan - Sanandaj and of from Sanandaj -Naghadeh was determined by spectrophotometry, on the reaction of alkaloid with bromocresol green (BCG). Moreover, the effect of some characteristicts of the soil habitat such as, soil pH, total nitrogen, potassium, altitude, texture soil, and nitrate content of tubers on the amount from total alkaloids was measured. The results of data analysis showed the significant differences between total alkaloid content of Marivan (27.12 ±1.18 mg/g D.W) with Sanandaj  (17.42 ±0.77 mg/g D.W) and of Sanandaj (15.38 ±0.65 mg/g D.W) with Naghadeh (7.4 ±0.32 mg/g D.W). Also there was a significant difference between the species in different regions other than of Sanandaj (17.42 ±0.77 mg/g D.W) with of Sanandaj (15.38 ±0.65 mg/g D.W). Furthermore, the results show that nitrate content of was higher than that of. The soil texture of Sanandaj (L. armeniaca) was loam sand and soil of the rest regions was clay loam. All of soils were mildly alkaline. Results from the effect of environmental factors on the total alkaloid content showed that with increasing amount of total nitrogen and potassium of soil and nitrate content, total alkaloids will be reduced, whereas pH, texture soil and altitude had not significant influence on total alkaloid contents

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Non-Gaussian spatial responses are usually modeled using spatial generalized linear mixed models, such that the spatial correlation of the data can be introduced via normal latent variables. The model parameters and the prediction of the latent variables at unsampled locations are of the most important interest in SGLMM by estimating of the latent variables at sampled locations. In these models, since there are the latent variables and non-Gaussian spatial response variables, likelihood function cannot usually be given in a closed form and maximum likelihood estimations may be computationally prohibitive. In this paper, a new algorithm is introduced for maximum likelihood estimation of the model parameters and predictions, that is faster than the former method. This algorithm obtains to combine the pseudo maximum likelihood method, the Expectation maximization Gradient algorithm and an approximate method. The performance and accuracy of the proposed model are illustrated through a simulation study. Finally, the model and the algorithm are applied to a case study on rainfall data observed in the weather stations of Semnan in 2012.

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In recent decades optimal control problems with partial differential equation constraints have been studied extensively. These issues are very complex and the numerical solution of such problems is of great importance. In this article we will discuss the solution of elliptic optimal control problem. First, by using the finite element method we obtain to gain the discrete form of the problem. The obtained discrete problem is actually a large scale constrained optimization problem. Solving this optimization problem with traditional methods is difficult and requires a lot of CPU time and memory. But split Bergman method converts the constrained problem to an unconstrained problem, and hence it saves time and memory requirement. We then use the split Bregman iterative methods for solving this problem, and examples show the speed and accuracy of split Bregman iterative methods for solving this type of problems. We also use the SQP method for solving the problem and compare with split Bregman method.

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    The methanol extracts of leaves and bulbs of Allium ampeloprasum L. (Alliaceae) were analyzed for their phenolic profiles and screened for their antioxidant and antibacterial activities. Two biochemical assays, namely DPPH free radical scavenging and &beta-caroten/linoleic acid activity systems, were used to evaluate antioxidant activity. Total phenol and flavonoid contents of the species were determined by Folin-Ciocalteu and AlCl₃ assays, respectively. Results indicated that the extracts are different in total phenolic content. Results from antioxidant activity showed that the extracts studied in DPPH radical scavenging assay are lower active than ascorbic acid and BHT as synthetic antioxidants. Antibacterial assay showed that the bulbs extract is more effective in inactivation of Haemophilus influenzae and Bacillus cereus and the leaves extract is more effective in inactivation of Bacillus cereus at 100 mg ml^-1 than others. Then, the extracts of Allium ampeloprasum possess strong antioxidant activity and may be used as new drug supplements in the future.