石羊河中游沙漠化逆转过程土壤种子库的动态变化

在石羊河中游,应用空间代替时间的方法,选择流动沙丘以及封育恢复5a、15a和25a的沙漠化逆转过程序列,研究了沙漠化逆转过程土壤种子库的变化特征。结果表明:石羊河中游沙漠化土地土壤种子库由4科12种植物组成,种子库主要分布于表层0-5cm。在沙漠化逆转过程中,土壤种子库物种数趋于增加,物种组成以1年生草本植物占优势逐渐向多年生草本植物和半灌木植物转变;种子库密度、表层土壤种子比例、物种多样性指数、与地上植被的相似性呈现先增大后降低趋势;沙漠化土地生态恢复间隔的时间越长,土壤种子库间的相似性程度越低;沙漠化土地与地带性植被区种子库的相似性逐渐增大,但是恢复25a沙漠化土地也仅达到0.36。研究认为,沙漠化逆转过程也是沙漠化土地土壤种子库向地带性植被土壤种子库演变的过程,而且是一个十分缓慢的过程,该研究有助于丰富干旱区土壤种子库的理论和指导干旱内陆河流域沙漠化土地的生态恢复实践。     

黄河源区沙漠化及其景观格局的变化

本研究以1975年的MSS数据、1990年和2005年的TM数据、以及2000年的ETM数据为数据源,通过遥感（RS）与地理信息系统（GIS）技术,获得了黄河源区在1975－2005年间沙漠化的发展特征,并采用景观指数运算软件（FRAGSTATS3.3）对黄河源区沙漠化土地的景观格局变化进行了分析。研究发现：在1975－1990年间,黄河源区的沙漠化土地面积大幅增加;在1990－2000年间,沙漠化土地面积保持稳定;在2000－2005年间,沙漠化土地面积出现了小幅度的减小趋势。黄河源区沙漠化土地的景观格局变化显著,在1975－1990年间,沙漠化土地发生了严重的破碎化;在1990－2000年间,沙漠化土地出现了连片的现象,从而使得沙漠化土地的破碎度有所下降,景观多样性降低;在2000－2005年间,沙漠化土地破碎度的增加,斑块形状趋于复杂。     

基于RS和GIS的玛曲高原土地沙漠化时空演变研究

基于RS和GIS空间分析技术,以玛曲高原多期Landsat遥感数据为主要信息源,监测分析了1977—2014年玛曲高原沙漠化土地的时空演变规律。结果表明:近40年来玛曲高原的土地沙漠化经历了迅速发展—缓慢发展—急速逆转—缓慢逆转—快速逆转的变化过程。1977—1995年玛曲高原沙漠化处于快速扩张阶段,年均扩张速率为3.01%;1995—2014年沙漠化扩张趋势出现逆转,年均逆转速率为4.14%。沙漠化土地的发展和逆转区域主要分布在东北部欧拉秀玛乡和尼玛乡黄河沿岸、东南部采日玛乡和曼日玛乡沼泽区、西南部齐哈玛乡和中部阿万仓乡黄河支流两岸。玛曲高原沙漠化土地的发展和逆转过程并非逐级递增或递减,而是在15—20年内交替出现,不同等级沙漠化土地之间的转移也存在明显的跃变。从整体来看,玛曲高原土地沙漠化呈现逆转趋势,区域生态环境得到明显改善。     

陕北榆林地区土地沙漠化动态遥感研究

土地沙漠化是人类面临的一个重要环境问题,在人为过度的经济活动干拢和生态脆弱的自然环境变化的影响下,正在继续蔓延,日益扩大,已引起国际社会和有识之士的高度重视。掌握其动态变化的规律,监测其发展趋势乃成为当前国际沙漠化研究的一个重要内容。地处陕西北部长城沿线的榆林地区,生态上较脆弱,气候上较敏感。笔者利用1984年和1994年两期ＴＭ图像进行判读勾绘,编制土地沙漠化类型图,在ＧＩＳ的支持下,建立空间数据库,套合叠加产生一种新的图件土地沙漠化动态图,获取动态变化资料数据,掌握了该区十年来土地沙漠化的动态变化趋势。1　区域环…     

内蒙古自治区沙漠化敏感性时空演变格局和趋势分析

以内蒙古自治区为研究区,基于压力-状态-响应模型(PSR)分析框架,耦合空间距离指数模型(SDIM)构建土地沙漠化敏感性评价体系(LDSES),结合沙漠化敏感性时空演变图谱,定量探讨内蒙古自治区土地沙漠化敏感性在2000年、2005年、2010年、2015年、2020年期间的时空演变,并引入元胞自动机-马尔科夫(CA-Markov)模型模拟沙漠化敏感性未来演变机制,进而采用地理探测器揭示了前20 a演变进程中主要驱动因子对其演变的影响特征及解释力。结果表明：(1)内蒙古自治区沙漠化敏感性整体上呈现由东北向西南递增的趋势,低敏感区位于大兴安岭和阴山山脉周边林草地覆盖区,高敏感区则位于西南部的巴丹吉林沙漠、腾格里沙漠、乌兰布和沙漠、库布其沙漠、毛乌素沙漠等沙地和戈壁地区;(2)从沙漠化敏感性时空演变上来看,研究期间沙漠化敏感性改善的区域,占总面积的30.65%,沙漠化敏感性恶化的区域,占总面积的4.48%,沙漠化敏感性类型维持稳定不变的区域占总面积的52.72%,整体来看土地沙漠化潜力逐渐降低,土地生态质量逐渐好转;(3)2030年沙漠化敏感性模拟结果显示未来10年沙漠化敏感性以低度敏感为...     

共和盆地土地沙漠化因素定量研究

共和盆黄河上游土地沙漠化严重地区,导致青海湖生态环境的恶化,同时还直接威胁龙羊峡水库的正常运转。土地沙漠化面积逐年扩大,严重沙漠化面积以年均0.12万hm2的速度扩展,每年进入龙羊峡水库的流沙量以达313万m3,导致许多牧民搬迁和无家可归。土地沙漠化已经成为共和盆地生态环境恶化的主要问题。选取青海共和盆地从1953到2004年共52a的农牧业人口数量、牲畜数量、耕地面积、降水量和大风日数5个因素进行了分析,借用功效原理、主成分分析原理和数理统计原理构建了评价模型,研究了它们与土地沙漠化的定量关系。结果表明共和盆地土地沙漠化主要是由农牧业人口数量、牲畜数量和耕地面积的增加引起的,权重上分别占到0.4412、0.2582和0.1470,影响系数随时间不断提高,引起社会因素综合影响系数在1994年以前由0增加到0.8105,呈现上升趋势,以后又逐渐下降至2004年的0.7069;降雨量和大风日数对土地沙漠化影响次要的,权重系数只有0.1118和0.0418,影响系数表现为一种不规则的周期性变化,自然因素综合影响系数呈现平稳发展趋势,变化范围在0.0102与0.1381之间。社会因素和自然因素的综合影响系数的变化1994年以前从0.0652增加到0.8974,年均增长1.6%,以后逐年下降至0.7813,年均降低1.2%;同时在综合影响系数的变化趋势线上反映出从1956年以后人类活动对生态环境的影响开始超过自然因素,成为影响共和盆地土地沙漠化的主体因素,1994年达到最高值,以后出现逐年降低的趋势,从20世纪末开始由于退耕还草生态项目的实施,社会因素有了较为明显的降低,但仍然高于自然因素的作用,因此共和盆地土地沙漠化的防治关键与重点是降低人为等社会因素的影响力,应该实施土地沙漠化综合治理工程。     

生态原则在沙漠化土地整治中的应用——以内蒙古东部干草原地区为例

一、引言土地沙漠化是本世纪六十年代以来引起人们十分关注的干旱、半干旱地区环境退化问题。我国沙漠化土地约为17万平方公里(其中约5万平方公里为近半个世纪内形成),分布在新疆、内蒙古、陕西、辽宁等12个省(区)的207个县(市、旗),涉及约3500万人口,尤以半干旱草原地带及荒漠草原地带为严重。沙漠化是干旱、半干旱地区生态环境退化的     

内蒙古多伦县土地沙漠化景观格局变化特征

利用景观分析软件Fragstats 3.3和内蒙古多伦县1960、1975、1987、1995、2000、2005年6期遥感影像解译结果,分析了1960—2005年间土地沙漠化景观格局变化.结果表明:1960—1995年间研究区土地沙漠化面积呈先增后减趋势,总沙漠化面积增加212.70km2,沙漠化斑块数先增多后减少,景观多样性和均匀性上升,轻度、中度、重度沙漠化斑块形状趋向简单;1995—2005年间研究区沙漠化斑块数大幅增加,景观多样性和均匀性下降,轻度、中度、重度沙漠化斑块形状趋向复杂;严重沙漠化斑块形状在1960年以后一直趋向复杂化.整个景观在研究期间表现为完整-破碎-完整-破碎的趋势,由轻度到严重沙漠化,其景观类型的破碎化程度逐渐降低.     

科尔沁沙地沙漠化过程中的物种多样性

对内蒙古科尔沁地区沙漠化过程中物种多样性的变化特征进行了分析 ,依据植物种在各类型沙漠化土地的出现频率和不同沙漠化阶段各生活型植物种的组成 ,探讨了沙漠化过程中植物种绝灭和定居特点 .物种多样性指数分析表明 ,沙漠化过程是一个物种多样性衰减的过程 ,沙漠化首先导致特有种的绝灭 ,其次为稀有种和普通种 .从植物的生活型来看 ,多年生草本和灌木类植物受沙漠化影响最大 ,而 1年生草本和半灌木类植物可存活于沙漠化过程各个阶段 .在沙漠化过程中植物种的绝灭速率大于定居速率 .     

科尔沁沙地不同沙漠化成因区域的景观动态比较

在3S技术支持下,比较分析了科尔沁沙地不同沙漠化成因区域的沙地景观动态变化过程。结果表明：近20年来,以人为活动干扰为主的区域（八仙筒镇）,沙漠化土地变化幅度较大,各种沙漠化土地的转化主要表现在沙漠化土地中流动和半固定沙地向固定沙地转化、固定沙地向农田和林地转化;以自然干扰为主的区域（苇莲苏乡）,沙漠化土地变化幅度较小,主要表现为各种沙地类型之间的转换;在人为活动为主的区域固定沙地的空间格局变化显著,1985—1995年固定沙地的联合度降低,人为活动干扰较强,而1995—2005年联合度增高,人为活动干扰相对较弱;在自然干扰为主的区域,同一时期空间格局的变化明显的是流动沙地,在1985—1995年,流动沙地斑块破碎度减小,流动沙地发育显著,在1995—2005年,流动沙地的破碎度继续减小,但其面积得到控制,表明治沙效果在这一时期是显著的。     

基于支持向量机的蛋白质同源寡聚体分类研究

基于支持向量机和贝叶斯方法,从蛋白质一级序列出发对蛋白质同源二聚体、同源三聚体、同源四聚体、同源六聚体进行分类研究,结果表明：基于支持向量机, 采用“一对多”和“一对一”策略, 其分类总精度分别为77.36%和93.43%, 分别比基于贝叶斯协方差判别法的分类总精度50.64%提高26.72和42.79个百分点.从而说明支持向量机可用于蛋白质同源寡聚体分类,且是一种非常有效的方法.对于多类蛋白质同源寡聚体分类,基于相同的机器学习方法（如支持向量机）,采用“一对一”策略比“一对多”效果好.同时亦表明蛋白质同源寡聚体一级序列包含四级结构信息.     

The problem with zeroes: why don't drosophilids lay eggs?

Summary We present some data on drosophilid oviposition and analyse the distribution of egg numbers over patches using an iterated negative binomial. This suggests that there are three different reasons for empty patches; patches are not found, patches are not suitable, or females are not able to lay eggs. This leads to five categories of site which can be disentangled using the iterated negative binomial. Since empty patches have important consequences for population dynamics and coexistence, this analysis will highlight how microscopic processes influence macroscopic behaviour in population biology.     

General methods for analysis of sequential "n-step" kinetic mechanisms: application to single turnover kinetics of helicase-catalyzed DNA unwinding

Helicase-catalyzed DNA unwinding is often studied using "all or none" assays that detect only the final product of fully unwound DNA. Even using these assays, quantitative analysis of DNA unwinding time courses for DNA duplexes of different lengths, L, using "n-step" sequential mechanisms, can reveal information about the number of intermediates in the unwinding reaction and the "kinetic step size", m, defined as the average number of basepairs unwound between two successive rate limiting steps in the unwinding cycle. Simultaneous nonlinear least-squares analysis using "n-step" sequential mechanisms has previously been limited by an inability to float the number of "unwinding steps", n, and m, in the fitting algorithm. Here we discuss the behavior of single turnover DNA unwinding time courses and describe novel methods for nonlinear least-squares analysis that overcome these problems. Analytic expressions for the time courses, f(ss)(t), when obtainable, can be written using gamma and incomplete gamma functions. When analytic expressions are not obtainable, the numerical solution of the inverse Laplace transform can be used to obtain f(ss)(t). Both methods allow n and m to be continuous fitting parameters. These approaches are generally applicable to enzymes that translocate along a lattice or require repetition of a series of steps before product formation.     

Segmentation of microscopic cell scenes

Different methods for the automated segmentation of microscopic cell scenes are presented with examples. The techniques discussed include edge detection by thresholding, "blob" detection by split-and-merge algorithm, global thresholding using gray-level histograms, hierarchic thresholding using color information, global thresholding using two-dimensional histograms and segmentation by "blob" labeling. Methods are more robust against insignificant changes in the scene and perform more reliably as more a priori knowledge about the scene is incorporated in the segmentation algorithm. The inclusion of both photometric and geometric a priori knowledge can result in a high level of correct segmentations, the cost of which is increased computation time.     

Micromanipulation of male and female gametes ofNicotiana tabacum: I. Isolation of gametes

The isolation of male and female gametes is a precondition for the micromanipulation of flowering plant gametes. To reflect their condition at fertilization, isolated gametes need to be physiologically mature and vigorous. Sperm cells are isolated from pollen tubes grown on cut styles using the in vivo/in vitro technique. Embryo sacs are isolated 2 days after anthesis using brief treatments of minimal concentrations of cell-wall-digesting enzymes on ovules of emasculated flowers. Egg cells are then mechanically separated from the embryo sac, allowing unambiguous identification of cells. Two days is usually the minimum required for the pollen tube to penetrate the ovule and effect fertilization in vivo.     

Feature extraction for the analysis of colon status from the endoscopic images

Background

Extracting features from the colonoscopic images is essential for getting the features, which characterizes the properties of the colon. The features are employed in the computer-assisted diagnosis of colonoscopic images to assist the physician in detecting the colon status.

Methods

Endoscopic images contain rich texture and color information. Novel schemes are developed to extract new texture features from the texture spectra in the chromatic and achromatic domains, and color features for a selected region of interest from each color component histogram of the colonoscopic images. These features are reduced in size using Principal Component Analysis (PCA) and are evaluated using Backpropagation Neural Network (BPNN).

Results

Features extracted from endoscopic images were tested to classify the colon status as either normal or abnormal. The classification results obtained show the features' capability for classifying the colon's status. The average classification accuracy, which is using hybrid of the texture and color features with PCA (τ = 1%), is 97.72%. It is higher than the average classification accuracy using only texture (96.96%, τ = 1%) or color (90.52%, τ = 1%) features.

Conclusion

In conclusion, novel methods for extracting new texture- and color-based features from the colonoscopic images to classify the colon status have been proposed. A new approach using PCA in conjunction with BPNN for evaluating the features has also been proposed. The preliminary test results support the feasibility of the proposed method.

     

A very high affinity opioid binding site in rat brain: demonstration by computer modeling

We present substantial new evidence for at least four distinct types of opioid receptors in rat brain, using quantitative ligand binding studies and mathematical modeling. Three of these binding sites are consistent with the well established "mu", "delta" and "kappa" receptors. The fourth has two distinctive features: 1) extremely high affinity (dissociation constant less than 1 nM); 2) almost complete lack of specificity for the classical "delta" or "mu" selective ligands. These properties are consistent with the putative "mu1" receptor described by Pasternak and coworkers.     

The RecA protein as a model molecule for molecular systematic studies of bacteria: Comparison of trees of RecAs and 16S rRNAs from the same species

The evolution of the RecA protein was analyzed using molecular phylogenetic techniques. Phylogenetic trees of all currently available complete RecA proteins were inferred using multiple maximum parsimony and distance matrix methods. Comparison and analysis of the trees reveal that the inferred relationships among these proteins are highly robust. The RecA trees show consistent subdivisions corresponding to many of the major bacterial groups found in trees of other molecules including the , , , , proteobacteria, cyanobacteria, high-GC gram-positives, and the Deinococcus-Thermus group. However, there are interesting differences between the RecA trees and these other trees. For example, in all the RecA trees the proteins from gram-positive species are not monophyletic. In addition, the RecAs of the cyanobacteria consistently group with those of the high-GC gram-positives. To evaluate possible causes and implications of these and other differences phylogenetic trees were generated for small-subunit rRNA sequences from the same (or closely related) species as represented in the RecA analysis. The trees of the two molecules using these equivalent species-sets are highly congruent and have similar resolving power for close, medium, and deep branches in the history of bacteria. The implications of the particular similarities and differences between the trees are discussed. Some of the features that make RecA useful for molecular systematics and for studies of protein evolution are also discussed.     

<Emphasis Type="Italic">Cryptococcus neoformans</Emphasis> Epidemiological Cutoff Values

Purpose of Review

The purpose of this review is to provide a current view of the importance of the determination and use of epidemiological cutoff values (ECVs) for Cryptococcus neoformans, since there are no clinical breakpoints (CBPs).

Recent Findings

ECVs have been proposed for some antifungal agents and C. neoformans, using standardized methodologies by the Clinical and Laboratory Standards Institute (CLSI) and by the European Committee for Antimicrobial Susceptibility Testing (EUCAST), based on the distribution of minimum inhibitory concentrations (MICs). There is no sufficient evidence for the determination of ECVs for C. neoformans using commercial methods; however, as these methods are routinely used in the microbiology laboratory, it is recommended for the establishment of local ECVs using these methods and following the criteria for their determination.

Summary

Due to the geographic and genetic variations inherent to C. neoformans, it is important to calculate ECVs, since they are useful in clinical practice to guide therapy in the absence of CBPs.

     

Design of multivariate selection experiments to estimate genetic parameters

Summary The precision of estimates of genetic variances and covariances obtained from multivariate selection experiments of various designs are discussed. The efficiencies of experimental designs are compared using criteria based on a confidence region of the estimated genetic parameters, with estimation using both responses and selection differentials and offspring-parent regression. A good selection criterion is shown to be to select individuals as parents using an index of the sums of squares and crossproducts of the phenotypic measurements. Formulae are given for the optimum selection proportion when the relative numbers of individuals in the parent and progeny generations are fixed or variable. Although the optimum depends on a priori knowledge of the genetic parameters to be estimated, the designs are very robust to poor estimates. For bivariate uncorrelated data, the variance of the estimated genetic parameters can be reduced by approximately 0.4 relative to designs of a more conventional nature when half of the individuals are selected on one trait and half on the other trait. There are larger reductions in variances if the traits are correlated.