Richard’s equation was approximated by finite-difference numerical scheme to model water infiltration profile in variably unsaturated soil^[1]. The published data of Philip’s semi-analytical solution was used to validate the simulated results from the numerical scheme. A discrepancy was found between the simulated and the published semi-analytical results. Morris method as a global sensitivity tool was used as an alternative to local sensitivity analysis to assess the results discrepancy. Morris method with different sampling strategies were tested, of which Manhattan distance method has resulted a better sensitivity measures and also a better scan of input space than Euclidean method. Moreover, Morris method at p = 2 , r = 2 and Manhattan distance sampling strategy, with only 2 extra simulation runs than local sensitivity analysis, was able to produce reliable sensitivity measures (μ^*, σ). The sensitivity analysis results were cross-validated by Sobol’ variance-based method with 150,000 simulation runs. The global sensitivity tool has identified three important parameters, of which spatial discretization size was the sole reason of the discrepancy observed. In addition, a high proportion of total output variance contributed by parameters β and θ_s is suggesting a greater significant digits to reduce its input uncertainty range.

This paper is concerned with the numerical solution of the mixed Volterra-Fredholm integral equations by using a version of the block by block method. This method efficient for linear and nonlinear equations and it avoids the need for spacial starting values. The convergence is proved and finally performance of the method is illustrated by means of some significative examples.

There are several methods in the literature to find the fuzzy optimal solution of fully fuzzy linear programming (FFLP) problems. However, in all these methods, it is assumed that the product of two trapezoidal (triangular) fuzzy numbers will also be a trapezoidal (triangular) fuzzy number. Fan et al. (“Generalized fuzzy linear programming for decision making under uncertainty: Feasibility of fuzzy solutions and solving approach”, Information Sciences, Vol. 241, pp. 12–27, 2013) proposed a method for finding the fuzzy optimal solution of FFLP problems without considering this assumption. In this paper, it is shown that the method proposed by Fan et al. (2013) suffer from errors and to overcome these errors, a new method (named as Mehar method) is proposed for solving FFLP problems by modifying the method proposed by Fan et al. (2013) . To illustrate the proposed method, some numerical problems are solved.

This review provided a detailed overview of the different synthesis and characterization methods of polymeric nanoparticles. Nanoparticles are defined as solid and colloidal particles of macromolecular substances ranging in size under 100 nm. Different types of nanoparticles are used in many biological fields (bio-sensing, biological separation, molecular imaging, anticancer therapy, etc.). The new features and functions provided by nano dimensions are largely different from their bulk forms. High volume/surface ratio, improved resolution and multifunctional capability make these materials gain many new features. 

In this paper silver nanoparticles (NPs) which are synthesized by a simple plasma arc discharge method, that is a kind of electrochemical methods, are examined. The method is very simple and silver NPs are obtained very fast by means of two polished silver plates and electrochemical cell. The effects of changing some terms of the experiment including using Hydrogen peroxide (H₂O₂), temperature and the medium of experiment on oxygen percent and crystalline structure of silver NPs have been studied by transmission electron microscopy, UV-visible spectrophotometery, and X-ray diffraction. Water medium gets larger nanoparticles with less oxygen content compare to air medium. The size of synthesized nanoparticles become smaller and they also become more spherical by using H₂O₂ in air medium. In water medium, the size and concentration of the silver crystallite increase by temperature growth and adding H₂O₂  respectively.