做聪明企业创建蛛网状学习型组织

简要概述了学习型组织，提出创建蛛网状学习型组织是企业应对当今社会激烈竞争的最有效方法，并对如何创建蛛网状学习型组织进行了初步探讨。     

铁磁材料相对磁导率变化与应力关系的磁力学模型

应力一直被认为是影响铁磁材料磁特性的重要因素。不论是提高缺陷识别信号还是应力监测等相当复杂的无损检测技术的开发，都要求对应力对磁特性影响的基本知识有一定的掌握，但相关的应力对铁磁材料相对磁导率的影响关系方面的文章还未见到。因此，本文参考有关研究者的成果，指出了一种关于铁磁材料相对磁导率变化与应力关系的磁力学模型，作为反应铁磁材料磁力耦合的一个方程式。     

地下水埋深动态预测的DAMSM模型

运用动态数据反演建模方法和自记忆性方程，建立了地下水埋深动态预测的DAMSM模型。该模型将动力学计算与用历史数据估计参数相结合，预测时无需分析影响地下水埋深动态的各种因素，只需要有一定长度的地下水埋深动态观测序列资料，避免了众多数据的收集整理。实例预测表明，该模型具有较高的拟合精度和预测准确性。     

水平井基坑降水的数学模型及应用

对于水平井的降水计算，提出了水平井等效渗透系数的新概念及其计算公式，可将水平井实际很复杂的边界条件移置到井口处，使计算简化；对抽水竖井的三维数值模拟提出了一种特殊井单元的处理方法；对潜水自由面提出了相适应的流量边界条件及其确定方法；建立了水平井降水和水平井与抽水竖井联合降水的数学模型；论证了水平井井内水流非等水头分布、也非等强度分布的观点。     

一种求解价格控制问题的混合遗传算法

针对价格控制问题提出了一种将遗传算法与单纯形法相结合形成的混合遗传算法，在分析了价格控制问题具体特点的基础上，对遗传算法在编码、约束处理、下层问题无解处理等方面进行改进，最后进行了数值模拟，模拟结果验证了该算法具有较高的精度且简便易行。     

风洞实验中多通道测压管路系统的参数分析

为了掌握风洞实验中多通道测压管路系统的特性，基于耗散模型，分析了影响系统频率响应函数的各个参数，总结了多通道管路系统频响函数的定性规律，并指出在常用的几何尺寸范围内，影响频响函数的因素主要有PVC管的长度、内径和限制器的尺寸及位置，为设计多通道测压管路系统提供了依据．     

Diagnosis of prostate cancer by quantitative analysis of 3DMRSI data: A new model

Three-dimensional magnetic resonance spectroscopic imaging (3DMRSI) is helpful to identify prostate cancer (PC)from benign prostate hyperplasia (BPH) and to show the distribution of tumor infiltration. Combined with the (Cho + Cre)/Cit ratio, the z-score model can effectively discriminate prostate cancer from stromal benign prostate hyperplasia (sBPH) and detect small malignant lesions (SML).     

Atomic-scale computer simulation for early precipitation process of Ni75AlxV25-x alloy with intermediate Al composition

The microscopic phase-field approach is applied to model the early precipitation process of Ni75AlxV25-x alloy. Without any prior assumptions, this model can be used to simulate the temporal evolution of arbitrary morphologies and microstructures on atomic scale. By simulating the atomic pictures, and calculating the order parameters and volume fraction of the θ (Ni3V) and γ'(Ni3Al) ordered phases, we study Ni75AlxV25-x alloys with Al composition of 0.05, 0. 053 and 0. 055 (atom fraction). Our calculated results show that,for these alloys, θ and γ' phases precipitate at the same time; with the increase of Al content, the amount of γ' phase increases and that of θ phase decreases; the precipitation characteristic of γ' phase transforms from Non-Classical Nucleation and Growth (NCNG) to Congruent Ordering Spinodal Decomposition (CO SD) gradually; otherwise, the precipitation characteristic of θ phase transforms from Congruent Ordering Spinodal Decomposition (CO SD) to Non-Classical Nucleation and Growth (NCNG) mechanism gradually. Both θ and γ' phases have undergone the transition process of mixture precipitation mechanism characterized by both NCNG and CO SD mechanisms. No incontinuous transition of precipitation mechanism has been found.     

A template of rat brain based on fMRI T*2 imaging

The development of functional magnetic resonance imaging (fMRI) technology has made it possible to carry out functional brain imaging experiments in small animals. Usually, group data is required to form the assessment of population, which can not only increase the sensitivity of the overall experiment, but also allow the generalization of the conclusion to the whole population. In order to average the signals of functional brain images from different subjects, it is necessary to put all the mapping images into the same standard space (template image). However, up to now, most animal brain templates remain unavailable and it must be done by ourselves. In this study, a template image based on the brains of eight male Wistar rats is obtained, and it is successfully used in our present Alzheimer disease (AD)-like rat model studies as template for spatially normalizing images to the same stereotaxical space. The fMRI results processed with statistical parametric mapping (SPM99) software are in agreement with the results from immunohistochemical experiment, which proves that this method is universally applicable to the pathologic models of other small animals and to human brain lesion studies.     

Computational fluid dynamics for dense gas-solid fluidized beds

Many computational fluid dynamics (CFD) models for describing the hydrodynamics of dense gas-solid flows in fluidized beds have been put forward in the past few decades. These models treat the solid phase as continuum or discrete particles, which leads to Eulerian-Eulerian or Eulerian-Lagrangian formulations, respectively. Different governing equations and closure relations essentially result from an insufficient understanding of the complex gas?particle and particle?particle interactions for gas?solid flows. The current status of these models is discussed briefly in this paper. All the approaches in the literature modify only the solid phase momentum balance equation introducing various forms of the solid phase stress tensor and the solid phase pressure drop in the Eulerian-Eulerian models. Taking them into consideration, a new model for predicting the fluid behavior of dense gas?solid flows in fluidized beds has been developed, which contains new terms in both the particle and gas phase momentum balance equations and requires only the use of an experimental drag force correlation. Several results are shown to verify the model’s reliability, which include the homogeneous fluidization of Geldart type A particles, the bubbling and jetting fluidization of Geldart type B particles in rectangular beds, and fluid dynamics in a complicated geometry for a bubbling?bed of a fast internally circulating fluidized?bed biomass gasifier.