建立基于常函数的抗结核药物敏感性试验熟练度测试结果自动比对方法

【摘要】为提高全国结核病实验室抗结核药物敏感性试验（简称“药敏试验”）熟练度测试结果比对的工作效率，杜绝人工比对错误的发生，作者应用Excel2003软件的数据库函数、逻辑函数、查询和引用函数、统计函数、文本函数及自定义函数，建立自动结果比对方法。本方法可快速得出各实验室药敏试验熟练度测试结果的耐药检出率（％）、敏感检出率（％）、一致率（％）、可重复率（％）、缺失数、缺失对子数等数据，并能在被测结果中以特定颜色显示出错误结果，最终自动汇总各实验室比对结果。

Service Function Chain in Small Satellite-Based Software Defined Satellite Networks

Software Defined Satellite Networks(SDSN) are proposed to solve the problems in traditional satellite networks, such as time-consuming configuration and inflexible traffic scheduling. The emerging application of small satellite and research of SDSN make it possible for satellite networks to provide flexible network services. Service Function Chain(SFC) can satisfy this need. In this paper, we are motivated to investigate applying SFC in the small satellite-based SDSN for service delivery. We introduce the structure of the multi-layer constellation-based SDSN. Then, we describe two deployment patterns of SFC in SDSN, the Multi-Domain(MD) pattern and the Satellite Formation(SF) pattern. We propose two algorithms, SFP-MD, and SFP-SF, to calculate the Service Function Path(SFP). We implement the algorithms and conduct contrast experiments in our prototype. Finally, we summarize the applicable conditions of two deployment patterns according to the experimental results in terms of hops, delay, and packet loss rate.

An Orthogonal Approach to Reusable Component Discovery in Cloud Migration

As an innovative software application mode,Software as a service(SaaS) shows many attractive advantages.Migrating legacy system to SaaS can make outdated systems revived.In the process of migration,the existing valuable components need to be discovered and reused in order that the target system could be developed/integrated more efficiently.An innovative approach is proposed in this paper to extract the reusable components from legacy systems.Firstly,implementation models of legacy system are recovered through reverse engineering.Secondly,function models are derived by vertical clustering,and then logical components are discovered by horizontal clustering based on the function models.Finally,the reusable components with specific feature descriptions are extracted.Through experimental verification,the approach is considered to be efficient in reusable component discovery and to be helpful to migrating legacy system to SaaS.

Recent Implementations in LASP 3.0:Global Neural Network Potential with Multiple Elements and Better Long-Range Description

LASP(large-scale atomistic simulation with neural network potential)software developed by our group since 2018 is a powerful platform(www.lasphub.com)for performing atomic simulation of complex materials.The software integrates the neural network(NN)potential technique with the global potential energy surface exploration method,and thus can be utilized widely for structure prediction and reaction mechanism exploration.Here we introduce our recent update on the LASP program version 3.0,focusing on the new functionalities including the advanced neuralnetwork training based on the multi-network framework,the newly-introduced S^(7) and S^(8) power type structure descriptor(PTSD).These new functionalities are designed to further improve the accuracy of potentials and accelerate the neural network training for multipleelement systems.Taking Cu-C-H-O neural network potential and a heterogeneous catalytic model as the example,we show that these new functionalities can accelerate the training of multi-element neural network potential by using the existing single-network potential as the input.The obtained double-network potential Cu CHO is robust in simulation and the introduction of S^(7) and S^(8) PTSDs can reduce the root-mean-square errors of energy by a factor of two.

Testing agile requirements models

This paper discusses a model-based approach to validate software requirements in agile development processes by simulation and in particular automated testing. The use of models as central development artifact needs to be added to the portfolio of software engineering techniques, to further increase efficiency and flexibility of the development beginning already early in the requirements definition phase. Testing requirements are some of the most important techniques to give feedback and to increase the quality of the result. Therefore testing of artifacts should be introduced as early as possible, even in the requirements definition phase.

Chebfun and numerical quadrature

Chebfun is a Matlab-based software system that overloads Matlab's discrete operations for vectors and matrices to analogous continuous operations for functions and operators.We begin by describing Chebfun's fast capabilities for Clenshaw-Curtis and also Gauss-Legendre,-Jacobi,-Hermite,and-Laguerre quadrature,based on algorithms of Waldvogel and Glaser,Liu and Rokhlin.Then we consider how such methods can be applied to quadrature problems including 2D integrals over rectangles,fractional derivatives and integrals,functions defined on unbounded intervals,and the fast computation of weights for barycentric interpolation.

New Double-Periodic Soliton Solutions for the (2+1)-Dimensional Breaking Soliton Equation

Under investigation is the(2+1)-dimensional breaking soliton equation. Based on a special ans?tz functions and the bilinear form, some entirely new double-periodic soliton solutions for the(2+1)-dimensional breaking soliton equation are presented. With the help of symbolic computation software Mathematica, many important and interesting properties for these obtained solutions are revealed with some figures.

An M-Objective Penalty Function Algorithm Under Big Penalty Parameters

Some classical penalty function algorithms may not always be convergent under big penalty parameters in Matlab software,which makes them impossible to find out an optimal solution to constrained optimization problems.In this paper,a novel penalty function(called M-objective penalty function) with one penalty parameter added to both objective and constrained functions of inequality constrained optimization problems is proposed.Based on the M-objective penalty function,an algorithm is developed to solve an optimal solution to the inequality constrained optimization problems,with its convergence proved under some conditions.Furthermore,numerical results show that the proposed algorithm has a much better convergence than the classical penalty function algorithms under big penalty parameters,and is efficient in choosing a penalty parameter in a large range in Matlab software.

ON TOPOLOGICAL LINEAR CONTRACTIONS ON NORMED SPACES AND APPLICATION

Simultaneous contractifications, simultaneous proper contractifications and semigroup(countable family or finite family) of commuting operators and of non-commuting operatorsare first given. Characterizations are given for a single bounded linear operator being a topo-logical proper contraction. By using complexification of a real Banach space and by applying afixed point theorem of Edelstein, it is shown that every compact topological strict contractionon a Banach space is a topological proper contraction. Finally, results on simultaneous propercontractification are applied to study the stability of a common fixed point of maps which areFrechet differentiable at that point.