层次分析法在确定紫色砂页岩系统各级指标的权重中的应用

本文运用层次分析法（ＡＨＰ法）确定了人工加速风化前紫色砂页岩系统各层次指标的权重，从而为计算系统熵值奠定了基础。     

TGF-β and TNF-α stimulate MMP-9 production in murine epidermal keratinocytes

Matrix metalloproteinases 2 and 9 (MMP‐2 and ‐9) are zinc‐dependent metalloenzymes and have gelatin‐degrading activity. Both MMP are known to be secreted by many types of cells and play important roles in several biological changes including tissue remodeling and wound healing. In the present study, a primary culture of murine epidermal keratinocytes was prepared and effects of transforming growth factor‐β (TGF‐β), tumor necrosis factor‐α (TNF‐α) and interferon‐γ (IFN‐γ) on expression of MMP‐2 and MMP‐9 by the keratinocytes was examined. Gelatin zymography revealed that murine epidermal keratinocytes secreted proenzyme forms of MMP‐2 and MMP‐9, but the active forms of both MMP were hardly detectable, indicating that in vitro autoactivation of these proenzymes did not occur. Both TGF‐β and TNF‐α stimulated MMP‐9 production in a dose‐dependent manner, but the MMP‐2 level was not changed. Interferon‐γ hardly affected production of MMP‐2 or MMP‐9. Ribonuclease protection assay demonstrated that TNF‐α increased the level of MMP‐9 mRNA 6‐fold compared to the control, whereas TGF‐β slightly up‐regulated it. These results suggest that expression of MMP‐9 could be regulated by several cytokines in murine epidermal keratinocytes.     

当代木材加工技术发展态势

从木材高效利用、木基复合材料、高新技术应用和环境保护等四个方面论述了当代木材加工技术的发展态势。     

噪声环境下木材纹理分类的研究

为了实现木材分类识别的自动化,应用灰度共生矩阵建立了木材纹理的参数体系,并进行了分类研究。首先在无噪声的环境下提取了木材的共生矩阵纹理原始特征参数,并对其进行特征选择,进而建立了木材纹理参数体系。对该参数体系进行噪声适应性测试的实验结果表明,无噪声情况下样本识别率为87.50%;0.2%￣1.0%椒盐噪声环境下样本识别率范围为87.00%￣88.00%。表明该参数体系具有良好的抗击噪声能力和一定的工程实用价值。     

基于神经网络和颜色特征对木材进行分级的分析

为了解决木材的分级问题，提出了利用神经网络和木材表面颜色特征对木材进行分级的方法。利用竞争神经网络对114种不同树种进行粗分，然后再用BP神经网络算法对此进行验证，又对四种木材进行分类验证。从计算机分类分级仿真效果上看，达到了预期的目的。     

Leslie矩阵模型在油松毛虫种群动态分析中的应用研究

油松毛虫(Dendrolimus tabulaeformis)是我国华北地区油松林的重要害虫之一。其分布面积广、发生频繁、危害严重。有人曾对油松毛虫种群的生物学特性、防治以及种群动态的研究作过有关的报道,本文则通过对油松毛虫的数量变动进行跟踪调查,并用Leslie矩阵模型对其种群动态进行了模拟,这对害虫的测报具有重要的实践意义。一、材料与方法 (一)标准地概况 1984—1986年与1988—1989年我们分别在密云县五座楼场和石墙沟村选择了5块油松纯林作为标准地,概况列在表1中:     

空间五杆机构的可动性分析

机构的第2类可动性。是机构分析与综合所要探讨的基本问题之一。本文对一般形式的空间RRRSR五杆机构的可动性进行分析。通过拆开运动副,分析运动轨迹,根据其雅可比矩阵奇异获得各位形分支的边界后,采用拓朴变换原理,讨论得出该机构的装配条件和连架杆的运动情况。为空间多杆机构的第2类可动性分析,提供了一条方便、实用的途径。     

Genomic best linear unbiased prediction method reflecting the degree of linkage disequilibrium

The degree of linkage disequilibrium (LD) between markers differs depending on the location of the genome; this difference biases genetic evaluation by genomic best linear unbiased prediction (GBLUP). To correct this bias, we used three GBLUP methods reflecting the degree of LD (GBLUP‐LD). In the three GBLUP‐LD methods, genomic relationship matrices were conducted from single nucleotide polymorphism markers weighted according to local LD levels. The predictive abilities of GBLUP‐LD were investigated by estimating variance components and assessing the accuracies of estimated breeding values using simulation data. When quantitative trait loci (QTL) were located at weak LD regions, the predictive abilities of the three GBLUP‐LD methods were superior to those of GBLUP and Bayesian lasso except when the number of QTL was small. In particular, the superiority of GBLUP‐LD increased with decreasing trait heritability. The rates of QTL at weak LD regions would increase when selection by GBLUP continues; this consequently decreases the predictive ability of GBLUP. Thus, the GBLUP‐LD could be applicable for populations selected by GBLUP for a long time. However, if QTL were located at strong LD regions, the accuracies of three GBLUP‐LD methods were lower than GBLUP and Bayesian lasso.     

Estimates of genetic variance and variance of predicted genetic merits using pedigree or genomic relationship matrices in six Brown Swiss cattle populations for different traits

The amount of variance captured in genetic estimations may depend on whether a pedigree‐based or genomic relationship matrix is used. The purpose of this study was to investigate the genetic variance as well as the variance of predicted genetic merits (PGM) using pedigree‐based or genomic relationship matrices in Brown Swiss cattle. We examined a range of traits in six populations amounting to 173 population‐trait combinations. A main aim was to determine how using different relationship matrices affect variance estimation. We calculated ratios between different types of estimates and analysed the impact of trait heritability and population size. The genetic variances estimated by REML using a genomic relationship matrix were always smaller than the variances that were similarly estimated using a pedigree‐based relationship matrix. The variances from the genomic relationship matrix became closer to estimates from a pedigree relationship matrix as heritability and population size increased. In contrast, variances of predicted genetic merits obtained using a genomic relationship matrix were mostly larger than variances of genetic merit predicted using pedigree‐based relationship matrix. The ratio of the genomic to pedigree‐based PGM variances decreased as heritability and population size rose. The increased variance among predicted genetic merits is important for animal breeding because this is one of the factors influencing genetic progress.