The cooperative and conflictual interactions between the United States,Russia, and China: A quantitative analysis of event data

The United States, Russia and China are militarily and economically among the most powerful countries in the post-Cold War period, and the interactions between the three powers heavily influence the international system. However, different conclusions about this question are generally made by researchers through qualitative analysis, and it is necessary to objectively and quantitatively investigate their interactions. Monthly-aggregated event data from the Global Data on Events, Location and Tone(GDELT) to measure cooperative and conflictual interactions between the three powers, and the complementary cumulative distribution function(CCDF) and the vector autoregression(VAR) method are utilized to investigate their interactions in two periods: January, 1991 to September, 2001, and October, 2001 to December, 2016. The results of frequencies and strengths analysis showed that: the frequencies and strengths of USA-China interactions slightly exceeded those of USA-Russia interactions and became the dominant interactions in the second period. Although that cooperation prevailed in the three dyads in two periods, the conflictual interactions between the USA and Russia tended to be more intense in the second period, mainly related to the strategic contradiction between the USA and Russia, especially in Georgia, Ukraine and Syria. The results of CCDF indicated that similar probabilities in the cooperative behaviors between the three dyads, but the differences in the probabilities of conflictual behaviors in the USA-Russia dyad showed complicated characteristic, and those between Russia and China indicated that Russia had been consistently giving China a hard time in both periods when dealing with conflict. The USA was always an essential factor in affecting the interactions between Russia and China in both periods, but China's behavior only played a limited role in influencing the interactions between the USA-Russia dyad. Our study provides quantitative insight into the direct cooperative and conflictual interactions between the three dyads since the end of the Cold War and helps to understand their interactions better.     

3D Mineral Prospectivity Mapping with Random Forests: A Case Study of Tongling,Anhui, China

Natural Resources Research - In the past few decades, a variety of data-driven predictive modeling techniques has led to a dramatic advancement in mineral prospectivity mapping (MPM). The random...     

Prediction of Blast-Induced Rock Movement During Bench Blasting: Use of Gray Wolf Optimizer and Support Vector Regression

Natural Resources Research - A large ore loss and dilution can be expected when using a pre-blast ore boundary for shovel guidance because of the movement and re-distribution of ore in the muck...     

基于像元二分模型的地表植被覆盖度估算模块化设计与实现

地表植被覆盖度是的一种应用广泛的定量遥感产品,在水文、生态、区域变化等方面都具有重要的意义。像元二分模型是应用最多的一种遥感估算地表覆盖度的方法。目前,用遥感的方法进行地表植被覆盖度估算没有完整、系统的工具,用户只能逐步进行操作,效率低下,鉴于上述情况,本文运用IDL交互式数据语言,基于ENVI二次开发了一个植被覆盖度估算程序,取得了一定的成效,对遥感定量产品的生产、应用具有一定意义。     

莱州湾大型底栖动物群落结构及其动态变化特征

本文以莱州湾2009年夏季(8月)、秋季(10月)及2010年春季(5月)、夏季(8月)4个季节大型底栖动物资料为基础,对莱州湾大型底栖动物的种类组成、丰度、生物量、优势种进行了研究,同时与历史资料进行对比,探讨了莱州湾大型底栖动物的群落结构特征及动态变化。4个航次中共鉴定出大型底栖动物272种,其中包括环节动物多毛类122种,软体动物46种,甲壳动物64种,棘皮动物18种,鱼类9种,其他类13种。调查海域平均丰度为(1102.56 ± 216.32) ind./m2, 多毛类在丰度上占绝对优势;平均生物量为(28.16 ± 8.45) g/m2,软体动物占据优势。丰度和生物量空间分布规律具有很强的相似性,低值区位于莱州湾西部黄河口邻近海域,高值区位于渤海中部海域。丰度和生物量季节变化明显,夏季最高,秋季其次,春季最低。多毛类不倒翁虫(Sternaspis sculata)、寡鳃齿吻沙蚕(Nephthys oligobranchia)、紫壳阿文蛤(Alvenius ojianus)等是莱州湾调查海域的优势种。通过与历史资料的对比发现,莱州湾大型底栖动物种类组成及优势种类出现小型化的趋势。     

一种新的用于极化SAR图像船只检测的散射相似性测度

本文提出了一种新的用于极化合成孔径雷达（SAR）海上船只目标检测的测度。首先利用散射相似性参数研究船只与海杂波散射机制的差异。基于这些差异,提出了一种新的船只检测测度,该测度能够有效区分船只目标和海杂波。然后提出了利用核密度估计（KDE）方法对该测度进行建模的方法。基于统计模型,实现了自适应恒虚警率（CFAR）的检测方案。本文利用多景C波段RADARSAT-2极化SAR（Pol-SAR）数据上进行实验,系统分析了所提出测度的海杂波拟合性能与船只检测性能,并与两个经典的极化测度进行了比较,实验和比较结果证明了所提的测度的可行性。     

基于CFD方法的十字形降落伞–航行体系统数值分析

为研究航行体对十字形降落伞流场和阻力性能的影响,基于Realizablek–ε模型采用PISO算法开展了十字形降落伞–航行体系统的非定常绕流数值计算,得到了详细的流场计算结果。研究了不同拖曳比下十字形降落伞–航行体系统的流场分布规律与降落伞衣及航行体的气动特性变化,结果表明：当拖曳比λ≤2时,航行体和降落伞衣形成闭式流动,降落伞衣阻力损失严重;当拖曳比λ>2时,航行体尾流区的压力恢复,降落伞衣底部形成稳定的正压区,流动形式由闭式转化为开式,拖曳比λ最大时的压差Δp相较拖曳比最小时的压差增加12%,降落伞衣阻力恢复,阻力波动减小;当拖曳比λ=4时,降落伞与航行体的阻力分别增加1.8%、25%。结果显示十字形降落伞–航行体系统的流场和压力分布更为对称,且气动特性处于最佳状态。     

Determination of the degree 120 time-variable gravity field in the Sichuan-Yunnan region using Slepian functions and terrestrial measurements

The terrestrial time-variable gravity measurements are characterized by a high signal-to-noise ratio and sensitivity to the sources of mass change in the Earth's crust. These gravity data have many applications, such as surface deformation, groundwater storage changes, and mass migration before and after earthquakes. Based on repeated terrestrial gravity measurements at 198 gravity stations in the Sichuan-Yunnan region (SYR) from 2015 to 2017, we determine a time series of degree 120 gravity fields using the localized spherical harmonic (Slepian) basis functions. Our results show that adopting the first 6 Slepian basis functions is sufficient for effective localized Slepian modeling in the SYR. The differences between two gravity campaigns at the same time of year show an obvious correlation with tectonic features. The degree 120 timevariable gravity models presented in this paper will benefit the study of the regional mass migration inside the crust of the SYR and supplement the existing geophysical models for the China Seismic Experimental Site.     

基于土地利用变化的中国省域碳排放时空差异及碳补偿研究

选择中国30个省级行政区为研究单元,基于土地利用和能源消耗等数据,采用碳排放系数法,对2003~2016年中国土地利用碳源/汇进行计算,探究中国省域土地利用碳排放和碳吸收时空演变,并以碳盈亏时空分析为基础,通过生态补偿系数和经济贡献系数分析碳排放的差异性,以净碳排放量作为基准值进行碳补偿价值的研究。结果表明:① 研究期间碳排放总量和净碳排放量除在2015年出现小幅度下降现象,其余年度均呈现不断增加趋势;碳吸收总量呈现稳中有升的趋势。②土地利用碳吸收的主要载体是耕地和林地,碳汇资源空间差异明显,基本呈现西高东低的分布特征,多数省份在研究期内基本保持一致的碳吸收类型。③ 碳排放总量分布空间差异显著,且主要来自建设用地。④ 依据净碳排放量的区域差异,将其划分为高碳排放区、一般碳排放区、低碳排放区、碳汇区4种类型。⑤ 由于各省域碳补偿标准和净碳排放量的差异导致碳补偿价值区域差异明显。     

Detecting and attributing vegetation changes in Taihang Mountain,China

Attributing vegetation changes provide fundamental information for ecosystem management,especially in mountainous areas which has vulnerable ecosystems. Based on the Normalized Difference Vegetation Index(NDVI) data, the spatial-temporal change of vegetation was detected in Taihang Mountain(THM) from 2000 to 2014. The topographical factors were introduced to interpret the response of vegetation variation to climate change and human activities. Results showed that the avegaged NDVI during growing season showed a single-peak curve distribution, with the largest value(0.628) among 1600-1800 m. A significant greening trend was detected in THM, with the largest increasing rate(0.0078 yr~(-1)) among the elevation of1600-1800 m and slope gradient between 3~5°. The partial correlation and multiple correlation analyses indicated that vegetation variation in more than81.8% pixels of the THM was mainly impacted by human activities. In the low elevation zones less than1000 m, increasing precipitation is the principle factor promoting vegetation restoration, whereas in the high elevation zones of THM, temperature is the restricted factors impacting vegetation variation.Considering the dramatic climate change in the future,further studies should be conducted to explore inherent mechanism of vegetation growth to dynamic environment changes.