Aspects of reproduction of the brown mussel Perna perna at the Iture rocky beach near Cape Coast,Ghana

Aspects of the reproductive biology of the brown mussel Perna perna at the Iture rocky beach near Cape Coast, Ghana, were studied from September 2014 to August 2015. The current study was aimed at providing information useful for managing the mussel fishery in this locality and also that would form the basis for designing appropriate culture methods for the species. Microscopic examination of fresh smears of gonadal material, as well as histological preparations of the gonad, were used to study the sexuality and breeding pattern of the species. Monthly gonadal and condition indices were also determined. Perna perna exhibited gonochoristic sexuality with a sex ratio of approximately 1:1 throughout the study period. Sexes were identifiable at shell lengths of 15.0–19.9 mm. Five stages of gonadal development were identified in both sexes. Gametogenic activity was continuous throughout the year, with two major spawning activities, from April to June and from August to December. These periods coincided with the major and minor rainy seasons, respectively, as well as the major upwelling period in August. Condition indices suggest that the mussels were in better condition for harvesting in March and August prior to the major spawning events.     

Brittleness index predictions from Lower Barnett Shale well-log data applying an optimized data matching algorithm at various sampling densities

The capability of accurately predicting mineralogical brittleness index(BI)from basic suites of well logs is desir-able as it provides a useful indicator of the fracability of tight formations.Measuring mineralogical components in rocks is expensive and time consuming.However,the basic well log curves are not well correlated with BI so correlation-based,machine-learning methods are not able to derive highly accurate BI predictions using such data.A correlation-free,optimized data-matching algorithm is configured to predict BI on a supervised basis from well log and core data available from two published wells in the Lower Barnett Shale Formation(Texas).This transparent open box(TOB)algorithm matches data records by calculating the sum of squared errors be-tween their variables and selecting the best matches as those with the minimum squared errors.It then applies optimizers to adjust weights applied to individual variable errors to minimize the root mean square error(RMSE)between calculated and predicted(BI).The prediction accuracy achieved by TOB using just five well logs(Gr,pb,Ns,Rs,Dt)to predict BI is dependent on the density of data records sampled.At a sampling density of about one sample per 0.5 ft BI is predicted with RMSE～0.056 and R2～0.790.At a sampling density of about one sample per 0.1 ft BI is predicted with RMSE～0.008 and R2～0.995.Adding a stratigraphic height index as an additional(sixth)input variable method improves BI prediction accuracy to RMSE～0.003 and R2～0.999 for the two wells with only 1 record in 10,000 yielding a BI prediction error of＞±0.1.The model has the potential to be applied in an unsupervised basis to predict BI from basic well log data in surrounding wells lacking mineralogical measure-ments but with similar lithofacies and burial histories.The method could also be extended to predict elastic rock properties in and seismic attributes from wells and seismic data to improve the precision of brittleness index and fracability mapping spatially.     

基于A*算法的路网数据组织

路网的数据组织是路径规划算法设计的基础。采用C++标准模板库实现基于A*算法的路网数据组织,着重从路网的拓扑结构、空间索引、A*算法数据结构、分层和分网格组织几方面来讨论。最后给出实例证明其有效性。     

GIS支持下的澜沧江流域云南段土壤侵蚀空间分析

利用ArcView3.2和ARC/INF08.1软件,通过图层叠加、统计分析和缓冲区分析等,提取西南纵向岭谷区澜沧江流域云南段的不同类型和强度的土壤侵蚀与地形坡度、土地利用/土地覆盖现状、土壤类型和分布、大雨日数以及河流、道路两侧的缓冲区等的相应数据,计算出土壤侵蚀综合度。结果表明,研究区不同坡度等级中,15°²5°坡度上的土壤侵蚀最强,其次为8°¹5°坡地和4°⁸°坡地;>25°坡地上则较小;不同用地类型的土壤侵蚀程度不同,总体上,旱耕坡地的土壤侵蚀较草地严重,而草地又较林地严重;在各种土壤类型中,黄壤和石灰土的土壤侵蚀最为突出,其次为红壤、黄棕壤和南方水稻土等;河流两侧和道路两侧的土壤侵蚀都较整个流域要严重,而河流两侧又略重于道路两侧;当多年平均大雨日数小于20日时,土壤侵蚀程度基本上随大雨日数的增加而增加;当大雨日数大于20日时,土壤侵蚀程度反而较小,原因在于前期大雨冲刷侵蚀,带走了地表的疏松物质。研究结果可为有针对性地防治水土流失、减少河流泥沙和水库淤积提供依据。     

中国城市信息网络结构演变特征及驱动因素分析

信息流能够客观反映城市社会经济联系,对城市网络研究具有重要价值。基于2011、2014和2017年中国城市间信息关注度数据,利用社会网络分析法,从网络密度、中心度、城市联系等方面分析中国城市网络结构的演变特征及其驱动因素,研究表明：1）城市信息网络结构明显拓展但网络总体联系强度仍较低;省域内部信息联系强度高于跨区域联系,信息联系仍受行政区划的影响较大。2）网络节点中心度显著提高,热点区主要集中在东部沿海三大城市群;中西部部分区域核心城市如重庆、成都、郑州等成长为全国性核心城市,但中西部地区城市信息发展仍与东部地区差距较大。3）信息联系层级分布特征明显,并呈现局部区域联系紧密、区域一体化特征;核心网络由以北京、上海为核心的“轴-辐”结构演变为以“北京-上海-广深-成渝”为核心的“菱形”结构。4）信息化水平、经济发展基础、城市职能等互补性因素,网络营销、大事件效应等介入性因素及信息技术变革、城市群建设等高效性因素相互作用,共同促进信息网络结构优化重组。     

Mapping 3D visibility in an urban street environment from mobile LiDAR point clouds

ABSTRACT

Visibility determination is a key requirement in a wide range of national and urban applications, such as national security, landscape management, and urban design. Mobile LiDAR point clouds can depict the urban built environment with a high level of details and accuracy. However, few three-dimensional visibility approaches have been developed for the street-level point-cloud data. Accordingly, an approach based on mobile LiDAR point clouds has been developed to map the three-dimensional visibility at the street level. The method consists of five steps: voxelization of point-cloud data, construction of lines-of-sight, construction of sectors of sight, construction of three-dimensional visible space, and calculation of volume index. The proposed approach is able to automatically measure the volume of visible space and openness at any viewpoint along a street. This approach has been applied to three study areas. The results indicated that the proposed approach enables accurate simulation of visible space as well as high-resolution (1 m × 1 m) mapping of the visible volume index. The proposed approach can make a contribution to the improvement of urban planning and design processes that aim at developing more sustainable built environments.     

区域可持续发展能力的能值与(火用)耦合分析模型构建

可持续发展能力评价方法是识别人地协同规律、支撑科学决策的重要工具和热点需求。通过文献回顾与理论分析框架构建,耦合能值及?方法,提出自组织能力指数（SO）、生态压力指数（EP）、可持续发展能力指数（SC）构成的,基于热力学理论的可持续发展能力分析模型,利用文献荟萃法筛选17个典型发达国家1985年状态值计算SO与EP阈值,划分了4个阶段。利用中美两国1985-2015年特征对比验证,结果显示：① 2005年以前中国属“低自组织能力、低生态压力”阶段,之后进入“低自组织能力、高生态压力”阶段,存在低生态效率、规模扩张驱动特征;美国一直属“高自组织能力、高生态压力”阶段,存在高生态效率驱动、经济与生态脱钩特征,与全球生态足迹网络和世界自然基金会等的研究结果一致,模型具有较好适应性和可靠性。② 模型利用“获得?量/输入能值量”表达经济社会生态效率、“经济社会?损耗量/生态系统年产?量”表达生态压力,连接了经济社会对生态基底的熵化路径,可识别区域所处可持续发展阶段、分析水平变化和驱动因素。③ 模型以人类与生态并重的视角,从深度上反映经济社会的生态效率、从广度上评价生态空间被占用比例,具有宏观规模与微观效率分析相结合的优势,是对经典方法的补充。     

乐山市水资源承载力分析及开发潜力研究

水资源的供需关系已演变为限制经济社会不断发展的一个关键障碍,所以对水资源承载力展开探究,以支撑经济和社会的不断发展,将会具有现实意义和至关重要的影响,本文从水资源负载指数和承载指数模型出发,根据当前乐山市水资源情况现状,对当地水资源承载力进行分析。     

钙质土中重力串锚水平承载力特性有限元研究

目前没有规范给出串锚的水平承载力计算公式,为了利用有限元法研究串锚水平承载力特性,采用相关理论计算以及室内试验的方法来验证有限元法模拟计算的可靠性。实践证明,有限元法具有较高的计算精度。利用有限元分析软件ABAQUS建立了串锚-土体模型,模拟串锚在水平荷载作用下破坏过程,研究了串锚在水平荷载作用下破坏机理,从而得到了串锚水平承载力特性。在相同的工况条件下,串锚的水平承载力与其锚链长度有关,在一定范围内,增加锚链的长度可以提高串锚的水平承载力;串锚的水平承载力不是相应的单个锚的水平承载力相加,其水平承载力小于相应的单个锚水平承载力之和,在进行串锚水平承载力设计计算时应给与相应的考虑。     

Fuzzy comprehensive evaluation model for water resources carrying capacity in Tarim River Basin, Xinjiang, China

This paper explores the method of comprehensive evaluation of water resources carrying capacity and sets up an evaluation model applying the fuzzy comprehensive evaluation method. Based on the data of nature, society, economics and water resources of the Tarim River Basin in 2002, we evaluated the water resources carrying capacity of the basin by means of the model. The results show that the comprehensive grades are 0.438 and 0.454 for Aksu and Kashi prefectures respectively, where the current water resources exploitation and utilization has reached a relative high degree and there is only a very limited water carrying capacity, 0.620 for Kizilsu Kirgiz Autonomous Prefecture, where water resources carrying capacity is much higher, and in between for Hotan Prefecture and Bayingolin Mongolian Autonomous Prefecture. As a whole, the comprehensive grade of the Tarim River Basin is 0.508 and the current water resources exploitation and utilization has reached a relative high degree. Thus, we suggest that the integrated management of the water resources in the basin should be strengthened in order to utilize water resources scientifically and sustainably.