肠道杆菌的扫描电镜观察

我们用扫描电镜观察肠道杆菌种(Enterobacteriaceae)中的四种细菌,大肠埃希氏杆菌(Escherichiacoli),普通变形杆菌(Proteus vulgaris),伤寒沙门氏菌(Salmonella typhi)和福氏志贺氏菌(Shigella Flexneri)。未处理的菌落标本,菌落表面都可形成一层厚薄不同的表膜(Surface film)。四种细菌菌落的表膜,形状不一,千姿百态。适当处理后的菌落标本,则可显示菌体的本来面目。四种细菌菌体在菌落表面的分布和排列,也是各不相同,千差万别。本文根据扫描电镜的观察,对四种不同菌落进行了讨论。     

A novel trilinear decomposition algorithm： Three-dimension non-negative matrix factorization

Non-negative matrix factorization(NMF)is a technique for dimensionality reduction by placing non-negativity constraints onthe matrix.Based on the PARAFAC model,NMF was extended for three-dimension data decomposition.The three-dimension non-negative matrix factorization(NMF3)algorithm,which was concise and easy to implement,was given in this paper.The NMF3algorithm implementation was based on elements but not on vectors.It could decompose a data array directly without unfolding,which was not similar to that the traditional algorithms do.It has been applied to the simulated data array decomposition andobtained reasonable results.It showed that NMF3 could be introduced for curve resolution in chemometrics.     

灰度／深度图像序列的三维空间内插──一种新的计算机图像生成技术

本文提出的灰度／深度图像序列的三维内插方法,摆脱了原实摄路径限制,可在空间内任意巡行,采用空间稀疏化采样,从而达到大量节省存储量和高度灵活地可控再现空间场景的目的,为解决三维内插中庞大的计算量,我们研究了快速而实用的散点算法和深度适应的Ｗａｒｐ算法。通过介绍三维内插的几种简单情形,导出了一些简单、实用的算法。计算机仿真结果显示了这一新方法是完全可行的。     

一种综合E序列的快速算法

本文从E序列的组合性质出发,把E序列划分为“组”、“群”和“族”,证明了当序列长度大于等于8时,一“族”E序列的不重复性,进而导出了一种简洁、快速、高效的综合E序列的算法．这种算法对于需要产生大量长E序列的工程问题特别有效．     

On the cost of approximating all roots of a complex polynomial

This work examines the computational complexity of a homotopy algorithm in approximating all roots of a complex polynomialf. It is shown that, probabilistically, monotonic convergence to each of the roots occurs after a determined number of steps. Moreover, in all subsequent steps, each rootz is approximated by a complex numberx, where ifx ₀ =x, x _j =x _j–1 –f(x _j–1)/f(x _j–1),j = 1, 2,, then |x _j –z| < (1/|x ₀ –z|)|x _j–1–z|².     

一种有机质谱谱图的库检索新算法

一种有机质谱谱图的库检索新算法律祥俊，林少凡，张金碚，张法义（南开大学中心实验室，天津，３０００７１）关键词检索，算法，质谱，数据库利用计算机匹配技术识别有机质谱谱图中的库检索方法仅需用低分辨质谱图即可识别未知化合物，似为最成功的方法［１～３］．质谱...     

Cost operator algorithms for the transportation problem

A primal transportation algorithm is devised via post-optimization on the costs of a modified problem. The procedure involves altering the costs corresponding to the basic cells of the initial (primal feasible) solution so that it is dual feasible as well. The altered costs are then successively restored to their true values with appropriate changes in the optimal solution by the application of cell or area cost operators discussed elsewhere. The cell cost operator algorithm converges to optimum within (2T – 1) steps for primal nondegenerate transportation problems and [(2T + 1) min (m, n)] – 1 steps for primal degenerate transportation problems, whereT is the sum of the (integer) warehouse availabilities (also the sum of the (integer) market requirements) andm andn denote the number of warehouses and markets respectively. For the area cost operator algorithm the corresponding bounds on the number of steps areT and (T + 1) min (m, n) respectively.This report was prepared as part of the activities of the Management Sciences Research Group, Carnegie—Mellon University, under Contract N00014-67-A-0314-0007 NR 047-048 with the U.S. Office of Naval Research.     

New uniform algorithm to predict reversed phase retention values under different gradient conditions

A new numerical emulation algorithm was established to calculate retention parameters in RP-HPLC with several retention times under different linear or nonlinear binary gradient elution conditions and further predict the retention time under any other binary gradient conditions. A program was written according to this algorithm and nine solutes were used to test the program. The prediction results were excellent. The maximum relative error of predicted retention time was less than 0.45%.     

A path following algorithm for a class of convex programming problems

We present a primal-dual path following interior algorithm for a class of linearly constrained convex programming problems with non-negative decision variables. We introduce the definition of a Scaled Lipschitz Condition and show that if the objective function satisfies the Scaled Lipschitz Condition then, at each iteration, our algorithm reduces the duality gap by at least a factor of (1–/n), where is positive and depends on the curvature of the objective function, by means of solving a system of linear equations which requires no more than O(n³) arithmetic operations. The class of functions having the Scaled Lipschitz Condition includes linear, convex quadratic and entropy functions.