Metric Distance Function and Profit: Some Duality Results

In this paper, we intend to establish relations between the way efficiency is measured in the literature on efficiency analysis and the notion of distance in topology. To this effect, we are interested particularly in the Hölder norm concept, providing a duality result based upon the profit function. Along this line, we prove that the Luenberger shortage function and the directional distance function of Chambers, Chung, and Färe appear as special cases of some l _p distance (also called Hölder distance), under the assumption that the production set is convex. Under a weaker assumption (convexity of the input correspondence), we derive a duality result based on the cost function, providing several examples in which the functional form of the production set is specified.     

Parallel preconditioned conjugate gradient algorithm on GPU

We propose a parallel implementation of the Preconditioned Conjugate Gradient algorithm on a GPU platform. The preconditioning matrix is an approximate inverse derived from the SSOR preconditioner. Used through sparse matrix–vector multiplication, the proposed preconditioner is well suited for the massively parallel GPU architecture. As compared to CPU implementation of the conjugate gradient algorithm, our GPU preconditioned conjugate gradient implementation is up to 10 times faster (8 times faster at worst).     

基于功能核酸的水中汞离子荧光检测方法

二价汞离子作为一种重要的环境污染物，一直以来受到国内外广泛关注。基于T-T错配的Hg2+检测极大依赖于汞选择性寡聚核苷酸（MSO）的设计，利用SYBR Green I对目前所报道的汞离子探针进行了优化，研究了若干种MSO探针与Hg2+的结合响应，在对探针二级结构进行分析和讨论的基础上，提出最优的富T探针序列，并由此建立了一种基于SYBR Green I的水中汞离子快速、便捷的荧光检测方法。最终测得3种实际水样的加标回收率在82.8％~101.8％之间，相对标准偏差小于15%，表明该方法受环境基质的影响较小，可应用于实际水样中的汞离子检测。     

THE DUALITY BETWEEN MORREY SPACES AND ITS PRE-DUAL SPACES CHARACTERIZED BY HEAT KERNEL

Let L be an elliptic operator, we give arguments about the duality estimate between Morrey spaces and its pre-dual spaces characterized by the heat kernel associated to L that is given in [6],[8].     

Some Results on Mathematical Programming with Generalized Ratio Invexity

In this paper, a generalized ratio invexity concept has been applied for single objective fractional programming problems. A concept which has been invoked seems to be more general than the one used earlier by Khan and Hanson in such contexts. Further, duality results for fractional programs have also been obtained.     

A Two-Level Preconditioned Conjugate-Gradient Method in Distorted and Structured Grids

In this paper, we propose a new two-level preconditioned C-G method which uses the quadratic smoothing and the linear correction in distorted but topologically structured grid. The CPU time of this method is less than that of the multigrid preconditioned C-G method (MGCG) using the quadratic element, but their accuracy is almost the same. Numerical experiments and eigenvalue analysis are given and the results show that the proposed two-level preconditioned method is efficient.     

Algebraic Multigrid Preconditioning for Finite Element Solution of Inhomogeneous Elastic Inclusion Problems in Articular Cartilage

In studying biomechanical deformation in articular cartilage, the presence of cells (chondrocytes) necessitates the consideration of inhomogeneous elasticity problems in which cells are idealized as soft inclusions within a stiff extracellular matrix. An analytical solution of a soft inclusion problem is derived and used to evaluate iterative numerical solutions of the associated linear algebraic system based on discretization via the finite element method, and use of an iterative conjugate gradient method with algebraic multigrid preconditioning (AMG-PCG). Accuracy and efficiency of the AMG-PCG algorithm is compared to two other conjugate gradient algorithms with diagonal preconditioning (DS-PCG) or a modified incomplete LU decomposition (Euclid-PCG) based on comparison to the analytical solution. While all three algorithms are shown to be accurate, the AMG-PCG algorithm is demonstrated to provide significant savings in CPU time as the number of nodal unknowns is increased. In contrast to the other two algorithms, the AMG-PCG algorithm also exhibits little sensitivity of CPU time and number of iterations to variations in material properties that are known to significantly affect model variables. Results demonstrate the benefits of algebraic multigrid preconditioners for the iterative solution of assembled linear systems based on finite element modeling of soft elastic inclusion problems and may be particularly advantageous for large scale problems with many nodal unknowns.