宁夏生态移民村空间剥夺测度及影响因素

生态移民村是一种具有扶贫脱贫与生态保护双重意义的特殊乡村类型,是乡村振兴不可或缺的重要对象。在空间重构过程中形成的空间剥夺现象,是当前生态移民村全面振兴面临的一个新问题。为探究生态移民村空间剥夺规律,以宁夏70个生态移民村2017年相关数据为基础,构建了以收入就业、教育培训、社会生活、居住环境及公共服务可达性为主要内容的空间剥夺指标体系并进行水平测度,进而运用地理加权回归和地理探测器对其影响因子进行探测。结果显示：① 宁夏生态移民村空间剥夺整体水平较低,但总指数均值相对于非生态移民村显著高出0.023;② 宁夏生态移民村空间剥夺时空分异特征明显,总指数均值在时间上呈现“先较低—后上升—再下降”趋势,在空间上呈现“北部低—中部高—南部次高”分布;③ 民族构成、地形地貌、移民时段、依托资源和经济区带是影响生态移民村空间剥夺的重要因子,前3项对空间剥夺总指数的解释力分别达到了22.4%、10.6%和14.0%。空间剥夺水平测度为生态移民生产生活评价和政策调整完善提供新的客观依据,相关部门可据此优化调节生态移民村空间资源配置,增加其获取资源的能力和机会,推动生态移民村全面振兴。     

An Early Cretaceous slab window beneath central Tibet,SW China: Evidence from OIB‐like alkaline gabbros in the Duolong area

The geodynamic mechanism of the late Early Cretaceous magmatic flare‐up in the collisional zone between the Lhasa and Qiangtang terranes in Tibet is controversial because of a scarcity of robust evidence. To address this problem, we report geochronological, geochemical and Hf isotopic data for the newly discovered Gufeng gabbros from the Duolong Cu–Au mineral district of the western Bangong–Nujiang Suture Zone (BNSZ). The gabbro samples, dated at 126.3 ± 1.8 Ma, show geochemical similarities to typical ocean island basalt (OIB) and have positive εHf(t) values of +3.3 to +6.9. The gabbros were generated by decompression melting of deep upwelling asthenosphere. This event is best explained by slab break‐off and the resultant development of a slab window beneath central Tibet.     

基于卫星遥感数据的森林病虫害监测与评价

森林病虫害由于在森林资源中造成的重大破坏而被人们称为“不冒烟的火灾”,其对生态系统的研究具有重要意义。现有基于遥感数据的病虫害研究多集中在森林病虫害的监测、爆发原因以及发病区域内生产力的变化情况,而对于森林病虫害发生后森林中植被指数与叶面积指数之间的相关性的变化情况还相对较少,处于需要持续性深入探讨的阶段。以加拿大不列颠哥伦比亚地区2002—2012年森林病虫害数据为基础,分析不同严重程度的病虫害对叶面积指数（LAI）与归一化植被指数（NDVI）和增强型植被指数（EVI）的影响。结果表明：① 受病虫害感染的像元在轻度（Light）、中度（Moderate）和重度（Severe）三个严重级别中,NDVI与LAI之间的相关性由弱变强,又由强变弱;② EVI与LAI之间的相关性,在轻度（Light）、中度（Moderate）和重度（Severe）三个严重级别的像元中则依次变强。这一研究将为今后利用遥感数据识别病虫害、评价生态系统影响提供基础。     

Directional interpolation infinite element for dynamic problems in saturated porous media

In this study, a directional interpolation infinite element suited to a saturated porous medium is presented to account for dynamic problems with semi-infi     

一种潜艇装备作战能力比较研究方法

对潜艇装备作战能力评估问题进行了研究，发现运用定量评估方法的过程中存在指标评价所需数据无法完全获取的问题。结合美弗吉尼亚潜艇改进情况，分析了影响潜艇作战能力的一些关键因素，重点基于潜艇武器装载能力，对国外典型潜艇进行了作战能力比较分析，最后对分析结果进行了评价，并讨论了未来潜艇作战能力评估方法的发展方向。     

光照强度和光色对番红砗磲(Tridacna crocea)氨氮、活性磷酸盐及氧代谢的影响

采用室内实验生态学方法,以水体中氨氮、活性磷酸盐和溶氧变化为指标研究了光照强度和光色对番红砗磲代谢的影响。结果表明:(1)在0—10000lx光照时,番红砗磲排氨量逐渐减少,在光照12000lx时转为吸收海水中氨氮,并在16000lx时达到最高[1.89μg/(ind·h)];在2000lx光照条件下,番红砗磲可吸收海水中活性磷酸盐并释放氧气。其活性磷酸盐吸收量随光照强度增强而增加,在16000lx时达到最高峰。在实验光照范围内,番红砗磲产氧率随光照强度的增强逐渐增加。上述结果显示番红砗磲最佳光照强度约为16000lx。(2)当番红砗磲自黑暗转移至各光照组后,其氨氮、活性磷酸盐吸收率均随时间逐渐降低,而产氧率则逐渐升高。(3)光色显著影响番红砗磲合成代谢,蓝光最佳,红光次之,白光最差。     

A multiscale work-analysis approach for geotechnical structures

This paper presents a second-order work analysis in application to geotechnical problems by using a novel effective multiscale approach. To abandon complicated equations involved in conventional phenomenological models, this multiscale approach employs a micromechanically-based formulation, in which only four parameters are involved. The multiscale approach makes it possible a coupling of the finite element method (FEM) and the micromechanically-based model. The FEM is used to solve the boundary value problem (BVP) while the micromechanically-based model is utilized at the Gauss point of the FEM. Then, the multiscale approach is used to simulate a three-dimensional triaxial test and a plain-strain footing. On the basis of the simulations, material instabilities are analyzed at both mesoscale and global scale. The second-order work criterion is then used to analyze the numerical results. It opens a road to interpret and understand the micromechanisms hiding behind the occurrence of failure in geotechnical issues.     

甘肃酒泉荒漠戈壁灌木群落优势物种生态位特征

了解物种利用资源和占据生态空间的能力，对维持完善和科学保育荒漠戈壁植物群落的多样性具有重要意义。在综合反映各生态因子作用的群落类型和海拔梯度组合而成的两条资源轴上，测度分析了甘肃酒泉荒漠戈壁灌木群落主要优势种的生态位特征。结果表明：(1)在群落类型和海拔梯度两条资源轴上，红砂（Reaumuria songarica）、泡泡刺（Nitraria sphaerocarpa）和合头草（Sympegma regelii）的重要值和生态位宽度均较大，说明这些物种适应能力强,能够较好地利用环境资源，分布范围大，作为荒漠戈壁灌木群落中的广域种具有重要的生态地位和作用。(2)荒漠戈壁优势物种间的生态位重叠值多数较小，在群落类型和海拔梯度资源轴上生态位重叠值小于0.5的分别占总种对的62.63%和77.89%。生态位宽度大的物种之间一般生态位重叠值较高，物种利用资源能力强且存在竞争关系；然而，生态位宽度较小的物种与其他物种之间的生态位重叠程度较低，不同物种在环境资源的需求上产生互补，可以和谐共存；生态位宽度小的物种之间生态位重叠值仍较高，物种分布呈斑块现象；因此，生态位重叠与生态位宽度之间无显著相关性。(3)荒漠戈壁优势物种间总体表现为不显著的正关联，表明该植被群落结构及其物种之间处于稳定共存的状态。     

Influence of Stress on Void Ratios of Compacted Crushed Rock Masses in Coal Mine Gobs

The transfer and evolution of stress among rock blocks directly change the void ratios of crushed rock masses and affect the flow of methane in coal mine gobs. In this study, a Lagrange framework and a discrete element method, along with the soft-sphere model and EDEM numerical software, were used. The compaction processes of rock blocks with diameters of 0.6, 0.8, and 1.0 m were simulated with the degrees of compression set at 0%, 5%, 10%, 15%, 20%, and 25%. This study examines the influence of stress on void ratios of compacted crushed rock masses in coal mine gobs. The results showed that stress was mainly transmitted downward through strong force chains. As the degree of compression increased, the strong force chains extended downward, which resulted in the stress at the upper rock mass to become significantly higher than that at the lower rock mass. It was determined that under different degrees of compression, the rock mass of coal mine gobs could be divided, from the bottom to the top, into a lower insufficient compression zone (ICZ) and an upper sufficient compression zone (SCZ). From bottom to top, the void ratios in the ICZ sharply decreased and those in the SCZ slowly decreased. Void ratios in the ICZ were 1.2–1.7 times higher than those in the SCZ.

     

A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.