重组人干扰素α2b阴道泡腾片抗豚鼠单纯疱疹病毒性阴道炎的疗效

目的观察重组人干扰素α2b阴道泡腾片对单纯疱疹病毒性阴道炎动物模型的疗效。方法采用单纯疱疹病毒感染建立豚鼠实验性阴道炎模型,并分别用重组人干扰素α2b阴道泡腾片600、3 000和15 000 IU/只进行治疗。以阿昔洛韦(无环鸟苷)和干扰素α2b栓剂15 000 IU/只作为对照。对治疗前后豚鼠阴道外观及组织切片进行评分。结果应用重组人干扰素α2b阴道泡腾片对豚鼠实验性单纯疱疹病毒性阴道炎进行治疗后,豚鼠阴道外观病变与组织切片病变评分均显著降低,其中15 000 IU/只效果最好。同样剂量的α2b泡腾片药效优于栓剂。结论重组人干扰素α2b阴道泡腾片对实验性单纯疱疹病毒性阴道炎有明显的疗效。     

Parameter sensitivity study of the Nelder-Mead Simplex Method

This paper presents a parameter sensitivity study of the Nelder-Mead Simplex Method for unconstrained optimization. Nelder-Mead Simplex Method is very easy to implement in practice, because it does not require gradient computation; however, it is very sensitive to the choice of initial points selected. Fan-Zahara conducted a sensitivity study using a select set of test cases and suggested the best values for the parameters based on the highest percentage rate of successful minimization. Begambre-Laier used a strategy to control the Particle Swarm Optimization parameters based on the Nelder Mead Simplex Method in identifying structural damage. The main purpose of the paper is to extend their parameter sensitivity study to better understand the parameter’s behavior. The comprehensive parameter sensitivity study was conducted on seven test functions: B2, Beale, Booth, Wood, Rastrigin, Rosenbrock and Sphere Functions to search for common patterns and relationships each parameter has in producing the optimum solution. The results show important relations of the Nelder-Mead Simplex parameters: reflection, expansion, contraction, and Simplex size and how they impact the optimum solutions. This study is crucial, because better understanding of the parameters behavior can motivate current and future research using Nelder-Mead Simplex in creating an intelligent algorithm, which can be more effective, efficient, and save computational time.     

A poly-hybrid PSO optimization method with intelligent parameter adjustment

This paper presents results on a new hybrid optimization method which combines the best features of four traditional optimization methods together with an intelligent adjustment algorithm to speed convergence on unconstrained and constrained optimization problems. It is believed that this is the first time that such a broad array of methods has been employed to facilitate synergistic enhancement of convergence. Particle swarm optimization is based on swarm intelligence inspired by the social behavior and movement dynamics of bird flocking, fish schooling, and swarming theory. This method has been applied for structural damage identification, neural network training, and reactive power optimization. It is also believed that this is the first time an intelligent parameter adjustment algorithm has been applied to maximize the effectiveness of individual component algorithms within the hybrid method. A comprehensive sensitivity analysis of the traditional optimization methods within the hybrid group is used to demonstrate how the relationship among the design variables in a given problem can be used to adjust algorithm parameters. The new method is benchmarked using 11 classical test functions and the results show that the new method outperforms eight of the most recently published search methodologies.     

Reachability and stabilization of discrete-time affine systems with disturbances

This paper studies the fundamental problems: whether an affine system affected by additive disturbances is robustly transferable from a source set (simplex) to a target set (polytope) and whether it is robustly stabilizable with its state constrained in a simplex. First, a necessary and sufficient condition is derived for the existence of affine feedback control that solves the robust reachability problem. Further investigation is provided for two situations relying on whether the union of the source set and the target set is convex or non-convex. For the former one, a necessary and sufficient condition is obtained in the form of linear inequalities, while for the latter, several computationally feasible sufficient conditions are found. Second, we show that robust stabilization subject to a state constraint is equivalent to find a feasible solution to a linear equation. Once it is known that either of the problems has a solution by checking the derived conditions, design of control laws is then straightforward.     

Efficient simplex computation for fixture layout design

Fixture, to hold an object by making multiple contacts, is a fundamental tool in manufacturing. A fixture layout is an arrangement of contacts on an object’s surface. Designing a fixture layout of an object can be reduced to computing the largest simplex and the resulting simplex is classified using the radius of the largest inscribed ball centered at the origin. We present three different algorithms to compute such a simplex: a simple randomized algorithm, an interchange algorithm, and a branch-and-bound algorithm. We also present methods to combine different algorithms to improve the performance and highlight their performance on complex 3D models consisting of thousands of triangles. Our randomized algorithm computes a feasible fixture layout in linear time and is well-suited for real-time applications. The interchange algorithm computes an optimal simplex in linear time such that no single vertex can be changed to enlarge the simplex, and it provides a practical method for complex 3D objects. The branch-and-bound algorithm computes the largest simplex by using lower and upper bounds on the radius of the inscribed ball, by which the computation time is reduced by a factor of five in comparison with the brute-force search.     

Metric concepts and implications in describing compositional changes for world river's water chemistry

The paper is designed to give the reader an outline that is useful for understanding the importance of distance, as a metric concept, and its implications when compositional (geochemical) data are managed from a statistical point of view in a given sample space. Application examples are shown by considering the construction of confidence regions and mixing models. The analyzed data are related to the chemistry of the most important rivers of the world as referring to the GEMS/WATER Global Register of River Inputs when each sample (river) is represented as a composition. A compositional vector of d parts, x=[x₁,x₂,…,x_d], is defined as a vector in which the only relevant information is contained in the ratios between its components. All the components of the vector are assumed positive and are called parts (variables), while the whole compositional vector, with the sum of the parts equal to a constant, represents the composition. In this case data are not represented by variables free to vary from −∞ to +∞ within a Euclidean space but occupy a restricted part of it called the simplex. The d-part simplex, S^d, is a subset of a d-dimensional real space. In this context the metric of the R space, with the definition of basic algebraic operations and of inner product, norm and distance, thus giving an Euclidean vector space structure, cannot be applied since the scale is relative and not absolute.     

基于单纯形微粒群优化算法Jensen模型参数求解

提出了基于单纯形微粒群优化算法（SMPSO）直接求解作物水分生产函数Jensen模型参数的方法。通过计算分析,用传统方法计算而得Jensen模型的相对产量与实际相对产量的相关指数为0．825,而用SMPSO（PSO）计算而得的相关指数为0．932;SMPSO寻优仅需要0．3973s,而PSO需要1．0783s。     

改进遗传单纯形混合算法在光纤对接中的应用

本文首先给出了纤端光场分布的3D模型并针对单模光纤与激光器的对接分析了错位、角度偏差等对接效率影响因素。通过与传统的爬山法进行比较,提出将遗传单纯形混合算法应用到光纤对接中。单纯形法是一种局部搜索方法,这种寻优方法收敛速度快,它与遗传算法组合起来可以改善单独使用遗传算法收敛速度慢的缺陷。同时,针对光纤对接要求初始种群小所造成的个体多样性差的缺点,改进了单纯形的反射、压缩系数,有效地避免了遗传操作的过早收敛,并通过仿真结果证明了混合算法可以在10代之内找到光纤对接的最佳耦合点。     

自调整模糊控制器的控制参数和控制规则

1 引言模糊控制是智能控制研究的方向之一。与传统控制截然不同的是,模糊控制不需要被控对象的精确数学模型。自从E.H.Mamdani1974年在实验室将模糊控制应用于锅炉和