Joint diseases, such as osteoarthritis, induce pain and loss of mobility to millions of people around the world. Current clinical methods for the diagnosis of osteoarthritis include X-ray, magnetic resonance imaging, and arthroscopy. These methods may be insensitive to the earliest signs of osteoarthritis. This study investigates a new procedure that was developed and validated numerically for use in the evaluation of cartilage quality. This finite element model of the human articular cartilage could be helpful in providing insight into mechanisms of injury, effects of treatment, and the role of mechanical factors in degenerative
conditions, this three-dimensional finite element model is a useful tool for understanding of the stress d

MDS code is a linear code that achieves equality in the Singleton bound, and projective MDS (PG-MDS) is MDS code with independents property of any two columns of its generator matrix.   In this paper, elementary methods for modifying a PG-MDS code of dimensions 2, 3, as extending and lengthening, in order to find new incomplete PG-MDS codes have been used over . Also, two complete PG-MDS codes over  of length  and 28 have been found.

In this work, a numerical study is performed to predict the solution of two – dimensional, steady and laminar mixed convection flow over a square cylinder placed symmetrically in a vertical parallel plate. A finite difference method is employed to solve the governing differential equations, continuity, momentum, and energy equation balances. The solution is obtained for stream function, vorticity and temperature as dependent variables by iterative technique known as successive over relaxation. The flow and temperature patterns are obtained for Reynolds number and Grashof number at (Re= -50,50,100,-100) (positive or negative value refers to aidding or opposing buoyancy , +1 assisting flow, -1 opposing flow) and (102 to 105) , respective

Catalytic removal of the S-content from thiophene is a central step in efforts aiming to reduce the environmental burdens of transportation fuels. In this contribution, we investigate the hydrodesulfurization (HDS) mechanisms of thiophene (C4H4S) over γ-Mo2N catalyst by means of density functional theory (DFT) calculations. The thiophene molecule preferentially adsorbs in a flat mode over 3-fold fcc nitrogen hollow sites. The HDS mechanism may potentially proceed either unimolecularly (direct desulfurization) or via H-assisted reactions (hydrogenation). Due to a sizable activation barrier required for the first Csingle bondS bond scission of 54.6 kcal/mol, we predict that the direct desulfurization to contribute rather very insignificant

The estimation of the parameters of linear regression is based on the usual Least Square method, as this method is based on the estimation of several basic assumptions. Therefore, the accuracy of estimating the parameters of the model depends on the validity of these hypotheses. The most successful technique was the robust estimation method which is minimizing maximum likelihood estimator (MM-estimator) that proved its efficiency in this purpose. However, the use of the model becomes unrealistic and one of these assumptions is the uniformity of the variance and the normal distribution of the error. These assumptions are not achievable in the case of studying a specific problem that may include complex data of more than one model. To

Buried pipeline systems are commonly used to transport water, sewage, natural oil/gas and other materials. The beneficial of using geogrid reinforcement is to increase the bearing capacity of the soil and decrease the load transfer to the underground structures.

This paper deals with simulation of the buried pipe problem numerically by finite elements method using the newest version of PLAXIS-3D software. Rajkumar and Ilamaruthi's study, 2008 has been selected to be reanalyzed as 3D problem because it is containing all the properties needed by the program such as the modulus of elasticity, Poisson's ratio, angle of internal friction. It was found that the results

Methods of estimating statistical distribution have attracted many researchers when it comes to fitting a specific distribution to data. However, when the data belong to more than one component, a popular distribution cannot be fitted to such data. To tackle this issue, mixture models are fitted by choosing the correct number of components that represent the data. This can be obvious in lifetime processes that are involved in a wide range of engineering applications as well as biological systems. In this paper, we introduce an application of estimating a finite mixture of Inverse Rayleigh distribution by the use of the Bayesian framework when considering the model as Markov chain Monte Carlo (MCMC). We employed the Gibbs sampler and