辽阳：土地管理工作受到沈阳督察局充分肯定

近日,国土资源部沈阳督察局督察一室到辽阳进行了土地巡查,并就我市开展“保增长、保红线”工作进行了调研。在我市巡查期间,巡查组还对辽阳河东新城地区土地开发利用情况进行了检查,听取了河东管委会副主任张富春对河东新城建设的基本情况及全市经济结构、状况和发展前景的简要介绍。     

Urban Construction Land Suitability Evaluation Based on Improved Multi-criteria Evaluation Based on GIS （MCE-GIS）： Case of New Hefei City,China

Urban construction land suitability evaluation （UCLSE） is a complex system engineering and the basis for rational use of the limited urban land resources in China. It has an important practical value on urban construction land use planning and management from the angle of methodology. As a widely used technique, traditional multi-criteria evaluation based on GIS （MCE-GIS）, is not suitable for UCLSE. This study develops an improved MCE-GIS method which could be more suitable for UCLSE based on urban complex ecological system theory and the summary of the shortcomings of traditional MCE-GIS. The improvements include three aspects： a composite evaluation index system rather than natural indexes alone, an index weight calculated by using fuzzy Analytic Hierarchy Process （AHP） method rather than the common AHP method, and the integrated overlay rule, which includes selecting the minimum value, weighted linear combination （WLC） and simple summation. The main advantage of this improved technique is that it can make UCLSE more comprehensive, more operational and more reasonable. It can provide a scientific basis for decision making in the planning and management of urban construction land use. The improved MCE-GIS system has been adopted in the New Hefei City, Anhui Province, China. Based on the results of UCLSE in New Hefei, three functional areas including construction-appropriate areas, construction-restricted areas and construction-forbidden areas could be worked out, in which 36.90% of the total study area could be developed as urban construction land and the remaining 63.10% should be protected as reserves land or as ecological land. Furthermore, the results can orovide scientific decision suooort for spatial planning and eco-environment nrotection in New Hefei.     

基于卫星观测的两例青藏高原低涡结构的初步分析

应用风云2C卫星云图和配有云顶亮温的MTSAT卫星红外云图,描述了两例青藏高原低涡形成、发展及消亡过程,云图清晰显示了高原低涡具有涡眼和暖心结构的特征,并利用水汽图分析揭示了缺乏水汽供应是导致这类低涡不能进一步发展并移出高原的重要原因.最后用1°×1°NCEP分析资料对高原低涡形成眼结构时的基本物理场进行了诊断计算.结果表明:低涡整体为上升气流,而涡眼区在近地层为下沉气流,上层为相对涡区较弱的上升气流;低层辐合,高层辐散.进而印证了动力学研究工作得出的高原低涡具有与热带气旋类低涡(TCLV, tropical cyclone-like vortices)类似的涡眼和暖心结构特征的结论.     

A Case study of a snowstorm at the Great Wall Station,Antarctica

A case of a snowstorm at the Great Wall Station was studied using data of NCEP (National Centers for Environmental Prediction) analysis, in situ observations and surface weather charts. The storm occurred on August 29th,2006, and brought high winds and poor horizontal visibility to the region.It was found that the storm occurred under the synoptic situation of a high in the south and a low in the north. A low-level easterly jet from the Antarctic continent significantly decreased the air temperature and humidity.Warm air advection at high level brought sufficient vapor from lower latitudes for the snowstorm to develop.The dynamic factors relating to strong snowfall and even the developmentof a snowstorm were deep cyclonic vorticity at middle and low levels,the configuration of divergence at high level and convergence at low level, and strong verticaluplift. There was an inversion layer in the low-level atmosphere during the later phase of the storm.This vertical structure of cold air at low levels and warm air at high levels may have been important to the longevity of the snowstorm.     

一种基于点特征的高精度图像配准方法

提出了一种基于点特征的多源图像高精度配准方法。通过在遥感影像上提取密集特征点,利用多种方法结合进行严格匹配获得同名点对。通过构建不规则三角网分割影像,再利用仿射变换模型实现每个三角形的配准。实验证明了该方法的有效性和较高的适用性。     

低渗透储层的微观特征对其宏观性质的影响规律——以榆树林油田扶杨油层为例

利用岩心物性分析、压汞曲线和镜下分析等资料,研究榆树林油田东16区块扶杨油层的宏、微观特征及二者关系.结果表明:研究区扶杨油层岩性为岩屑长石砂岩,普遍具有碎裂特征,主要孔隙成因类型包括微裂缝、粒间孔、粒内孔和晶间孔,微裂缝对孔隙度的贡献不大,但对渗透率的影响不容忽视.孔隙度主要受孔喉发育程度影响,孔喉半径越大,孔隙度越高.渗透率受反映连通程度的特征结构参数影响较大,二者呈正相关关系,且孔隙度越大,特征结构系数对渗透率的影响越大.退汞效率受特征结构参数影响较大,储层为中孔时,退汞效率随特征结构参数的增大而增大;储层为低孔或特低孔时,退汞效率随特征结构参数的增大而减小.该研究结果对改造低渗储层、提高采收率具有指导意义.     

GLIMMER Antarctic Ice Sheet Model,an experimental research of moving boundary condition

A 3-D coupled ice sheet model, GLIMMER model is introduced, and an idealized ice sheet experiment under the EISMINT-1 criterion of moving boundary condition is presented. The results of the experiment reveal that for a steady-state ice sheet profile the characteristic curves describe the process of evolution which are accordant with theoretical estimates. By solving the coupled thermodynamics equations of ice sheet, one may find the characteristic curves which derived from the conservation of the mass, energy and momentum to the ice flow profile. At the same time, an agreement, approximate to the GLIMMER case and the confirmed theoretical results, is found. Present study is explorihg work to introduce and discuss the handicaps of EISMINT criterion and GLIMMER, and prospect a few directions of the GLIMMER model.     

基于JXTA的协同学习系统研究

随着计算机网络技术的迅速发展和计算机协同工作CSCW理论和技术研究的深入,计算机协同学习(Computer Supported Collaborative Learning)的思想逐渐被引入计算机网络教育的应用中.目前大多数的协同学习系统采用了C/S结构.提出的基于JXTA的协同学习系统采用了P2P(Peer-to-Peer)结构,满足了协同学习的一般需求,具有安全性、可伸缩性和可扩展性.     

罗非鱼4个选育群体遗传结构SSR分析

采用SSR分子标记分析了吉富品系罗非鱼的两个家系(GF1和GF2)以及奥利亚罗非鱼(Fo)和奥本尼罗罗非鱼(Fn)群体的遗传结构。结果显示,扩增后等位基因数为3～8个,随引物不同而异,14对引物共扩增60个等位基因,扩增片断大小在102～267 bp之间。微卫星分析表明,奥本尼罗罗非鱼(Fn)的平均观测杂合度(0.764 3)和平均期望杂合度(0.519 6)均最高,吉富尼罗罗非鱼(GF1)平均多态信息含量(0.419 5)最高;吉富尼罗罗非鱼(GF2)平均观测杂合度(0.614 2),奥利亚罗非鱼(Fo)的平均期望观测度(0.446 6)、平均多态信息含量(0.359 2)最低;因此,吉富鱼(GF1)的遗传多样性最高,奥利亚的遗传多样性最低。Hardy-Weinberg平衡遗传偏离指数(D)奥利亚(Fo)和尼罗(Fn)(0.463 4和0.478 9)明显高于吉富的两家系(0.234 1和0.250 0)。Fo与GF2间遗传距离(0.477 0)最大;而GF1和GF2间的遗传距离(0.302 7)最小,遗传相似系数(0.607 3)最大,可推断新一代吉富罗非鱼与本地选育群体有相对较远的亲缘关系,更具杂种优势。     

Alternative Fuzzy Cluster segmentation of remote sensing images based on Adaptive Genetic Algorithm

Remote sensing image segmentation is the basis of image understanding and analysis. However, the precision and the speed of segmentation can not meet the need of image analysis, due to strong uncertainty and rich texture details of remote sensing images. We proposed a new segmentation method based on Adaptive Genetic Algorithm (AGA) and Alternative Fuzzy C-Means (AFCM). Segmentation thresholds were identified by AGA. Then the image was segmented by AFCM. The results indicate that the precision and the speed of segmentation have been greatly increased, and the accuracy of threshold selection is much higher compared with traditional Otsu and Fuzzy C-Means (FCM) segmentation methods. The segmentation results also show that multi-thresholds segmentation has been achieved by combining AGA with AFCM.