Application of an integrated microchip system with capillary array electrophoresis to optimization of enzymatic reactions

In this work, a combination of complementary metal-oxide semiconductor (CMOS) microchip system with capillary array electrophoresis (CAE) is demonstrated as a system for optimizing conditions for enzymatic reaction. Dimethylacridinone (DDAO)-phosphate substrate and alkaline phosphatase conjugate were selected for the enzymatic reaction, which was applicable to the enzyme-linked immunosorbent assay (ELISA) technique. Laser-induced fluorometry with a miniature semiconductor laser was used to detect the enzymatic products. The speed of the enzymatic reaction between the DDAO-phosphate and the alkaline phosphatase conjugate was investigated as a function of reaction time. The microchip-CAE detection system could determine the pH condition and the concentration of enzyme that are suitable for rapid and low-cost analysis. This result shows the feasibility of using the microchip-CAE system for application to miniaturized screening systems.     

区间数互补判断矩阵的拓扑排序方法

提出了方案之间进行比较时优于与劣于的定义,通过构造与区间数互补判断矩阵相对应的有向图的方法,将互补判断矩阵的排序问题转化为有向图中顶点的拓扑排序问题,将有向图中的顶点按照备选方案的重要性顺序输出,得到的顶点的序列即为备选方案的重要性排序,数值计算实例验证了该方法的有效性与可行性。     

The dual of a constacyclic code,self dual,reversible constacyclic codes and constacyclic codes with complementary duals over finite local Frobenius non-chain rings with nilpotency index 3

Over finite local Frobenius non-chain rings with nilpotency index 3 and when the length of the codes is relatively prime to the characteristic of the residue field of the ring, the structure of the dual of $\gamma$-constacyclic codes is established and the algebraic characterization of self-dual $\gamma$-constacyclic codes, reversible $\gamma$-constacyclic codes and $\gamma$-constacyclic codes with complementary dual are given. Generators for the dual code are obtained from those of the original constacyclic code.     

Computational complexity of LCPs associated with positive definite symmetric matrices

Murty in a recent paper has shown that the computational effort required to solve a linear complementarity problem (LCP), by either of the two well known complementary pivot methods is not bounded above by a polynomial in the size of the problem. In that paper, by constructing a class of LCPs—one of ordern forn 2—he has shown that to solve the problem of ordern, either of the two methods goes through 2 ⁿ pivot steps before termination.However that paper leaves it as an open question to show whether or not the same property holds if the matrix,M, in the LCP is positive definite and symmetric. The class of LCPs in whichM is positive definite and symmetric is of particular interest because of the special structure of the problems, and also because they appear in many practical applications.In this paper, we study the computational growth of each of the two methods to solve the LCP, (q, M), whenM is positive definite and symmetric and obtain similar results.This research is partially supported by Air Force Office of Scientific Research, Air Force Number AFOSR-78-3646. The United States Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright notation thereon.     

The Dattoli-Srivastava conjectures concerning generating functions involving the harmonic numbers

In a recent paper Dattoli and Srivastava [3], by resorting to umbral calculus, conjectured several generating functions involving harmonic numbers. In this sequel to their work our aim is to rigorously demonstrate the truth of the Dattoli-Srivastava conjectures by making use of simple analytical arguments. In addition, one of these conjectures is stated and proved in more general form.     

The complementary unboundedness of dual feasible solution sets in convex programming

F.E. Clark has shown that if at least one of the feasible solution sets for a pair of dual linear programming problems is nonempty then at least one of them is both nonempty and unbounded. Subsequently, M. Avriel and A.C. Williams have obtained the same result in the more general context of (prototype posynomial) geometric programming. In this paper we show that the same result is actually false in the even more general context of convex programming — unless a certain regularity condition is satisfied.We also show that the regularity condition is so weak that it is automatically satisfied in linear programming (prototype posynomial) geometric programming, quadratic programming (with either linear or quadratic constraints),l _p -regression analysis, optimal location, roadway network analysis, and chemical equilibrium analysis. Moreover, we develop an equivalent regularity condition for each of the usual formulations of duality.Research sponsored by the Air Force Office of Scientific Research, Air Force Systems Command, USAF, under Grant Number AFOSR-73-2516.     

Common complements of two subspaces of a Hilbert space

In this paper we find a necessary and sufficient condition for two closed subspaces, and , of a Hilbert space to have a common complement, i.e. a subspace having trivial intersection with and and such that .Unlike the finite-dimensional case the condition is significantly more subtle than simple equalities of dimensions and codimensions, and non-trivial examples of subspaces without a common complement are possible.     

基于乘性模糊互补判断矩阵的FAHP

根据乘性一致性的定义,从人的主观判断与其权重的函数关系出发,获得了乘性模糊互补判断矩阵的元素表达式,论证了利用乘性模糊互补判断矩阵求取因素相对权重的可行性,最后给出了一种基于乘性一致模糊判断矩阵的排序方法.从而使得乘性模糊互补判断矩阵的应用的理论基础更加坚实.     

Numerical solution for the anisotropic Willmore flow of graphs

The Willmore flow is well known problem from the differential geometry. It minimizes the Willmore functional defined as integral of the mean-curvature square over given manifold. For the graph formulation, we derive modification of the Willmore flow with anisotropic mean curvature. We define the weak solution and we prove an energy equality. We approximate the solution numerically by the complementary finite volume method. To show the stability, we re-formulate the resulting scheme in terms of the finite difference method. By using simple framework of the finite difference method (FDM) we show discrete version of the energy equality. The time discretization is done by the method of lines and the resulting system of ODEs is solved by the Runge–Kutta–Merson solver with adaptive integration step. We also show experimental order of convergence as well as results of the numerical experiments, both for several different anisotropies.