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基于临近相似性考虑的犯罪热点密度图预测准确性比较——以DP半岛街头抢劫犯罪为例

在无时空考虑的密度估计算法基础上,分别加入了案件点之间的时间临近相似性、空间临近相似性和时空临近相似性的考虑,利用DP半岛2006~2007年的街头抢劫犯罪数据为基础计算无时空临近相似性、时间临近相似性、空间临近相似性和时空临近相似性4种不同算法所得到的犯罪热点图,并以之预测2008年的街头抢劫。通过Natural breaks（Jenks）分级方法和等比例面积选取两种方式来划定热点区域进行预测并进行PAI指数得分比较,结果表明时空临近相似性的密度估计算方法在犯罪预测的优势比较显著。     

珠江口外陆架表层沉积物的地球化学分区

根据249个表层沉积物样品的Ca,Al,N,P,Mg,Fe,Mn,Ti和有机碳的测定数据,利用稳健RQ型主分量分析及Q型聚类分析方法,对珠江口外陆架表层沉积物进行了地球化学分类,并将该陆架区划分成陆源细碎屑沉积区、经叠加改造的残留泥砂质沉积区、生物碎屑沉积区以及高能环境下的石英砂质沉积区。结果表明了稳健统计方法相对于传统统计方法的优越性,以及采用稳健主分量的Q载荷进行聚类分析相对于用原始变量进行聚类分析的优越性。     

铜陵新桥层状菱铁矿成因的矿物学证据及成矿意义

安徽铜陵新桥矿区二叠系栖霞组底部和石炭系黄龙组—船山组之间产出层状、似层状菱铁矿矿层。开展菱铁矿矿层成因研究对于深入剖析区域层控矽卡岩型铜铁矿床成矿机制具有重要意义。本文利用粉晶X射线衍射（XRD）、扫描电镜（SEM）对菱铁矿矿石进行矿物学研究,结果发现菱铁矿矿石主要由菱铁矿、石英、伊利石和有机质等组成,菱铁矿颗粒粒径较小,表面具有成岩自生的自形石英硬模的微结构,SEM原位微区成分分析显示菱铁矿中除了主量元素铁,还含有大量的锰、锌和钙。矿石中存在两种微结构和不同成因的石英：表面具菱铁矿硬模和次生加大结构的碎屑石英;具六方双锥、单锥以及生物成因球形的自生石英。菱铁矿矿石的组成和矿物表面微结构表明其为沉积成因,非岩浆热液起源。富有机质和亚铁的沉积菱铁矿层和沉积胶状黄铁矿层协同作用,可能是铜陵地区乃至长江中下游成矿带层状铜铁矿床层控性重要制约因素,以及可能作为燕山期中酸岩浆演化的氧化性含铜成矿流体卸载成矿的地球化学还原障。

     

Estimates of AGN Black Hole Mass and Minimum Variability Timescale

Black hole mass is one of the fundamental physical parameters of active galactic nuclei (AGNs), for which many methods of estimation have been proposed. One set of methods assumes that the broad-line region (BLR) is gravitationally bound by the central black hole potential, so the black hole mass can be estimated from the orbital radius and the Doppler velocity. Another set of methods assumes the observed variability timescale is determined by the orbital timescale near the innermost stable orbit around the Schwarzschild black hole or the Kerr black hole, or by the characteristic timescale of the accretion disk. We collect a sample of 21 AGNs, for which the minimum variability timescales have been obtained and their black hole masses (Mσ) have been well estimated from the stellar velocity dispersion or the BLR size-luminosity relation. Using the minimum variability timescales we estimated the black hole masses for 21 objects by the three different methods, the results are denoted by Ms, Mk and Md, respectively. We compared each of them with Mσindividually and found that: (1) using the minimum variability timescale with the Kerr black hole theory leads to small differences between Mσand Mk, none exceeding one order of magnitude, and the mean difference between them is about 0.53 dex; (2) using the minimum variability timescale with the Schwarzschild black hole theory leads to somewhat larger difference between Mσand Ms: larger than one order of magnitude for 6 of the 21 sources, and the mean difference is 0.74 dex; (3) using the minimum variability timescale with the accretion disk theory leads to much larger differences between Mσand Md, for 13 of the 21 sources the differences are larger than two orders of magnitude; and the mean difference is as high as about 2.01 dex.     

Assessing seawater quality with a variable fuzzy recognition model

With the rapid development of the marine economy industry, human exploitation of marine resources is increasing, which is contributing to the growing trend of eutrophication and frequent occurrence of red tide. Accordingly, investigations of seawater quality have attracted a great deal of attention. This study was conducted to construct a seawater environmental quality assessment model based on the variable fuzzy recognition model. The uncertainty and ambiguity of the seawater quality assessment were then considered, combining the monitoring values of evaluation indicators with the standard values of seawater quality. Laizhou Bay was subsequently selected for a case study. In this study, the correct variable model for different parameters was obtained according to the linear and nonlinear features of evaluation objects. Application of the variable fuzzy recognition model for Laizhou Bay, water quality evaluation and comparison with performance obtained using other approaches revealed that the generated model is more reliable than traditional methods, can more reasonably determine the water quality of various samples, and is more suitable for evaluation of a multi-index, multi-level, nonlinear marine environment system; accordingly, the generated model will be an effective tool for seawater quality evaluation.     

Near-source noise suppression of AMT by compressive sensing and mathematical morphology filtering

In deep mineral exploration, the acquisition of audio magnetotelluric (AMT) data is severely affected by ambient noise near the observation sites; This near-field noise restricts investigation depths. Mathematical morphological filtering (MMF) proved effective in suppressing large-scale strong and variably shaped noise, typically low-frequency noise, but can not deal with pulse noise of AMT data. We combine compressive sensing and MMF. First, we use MMF to suppress the large-scale strong ambient noise; second, we use the improved orthogonal match pursuit (IOMP) algorithm to remove the residual pulse noise. To remove the noise and protect the useful AMT signal, a redundant dictionary that matches with spikes and is insensitive to the useful signal is designed. Synthetic and field data from the Luzong field suggest that the proposed method suppresses the near-source noise and preserves the signal well; thus, better results are obtained that improve the output of either MMF or IOMP.     

小良试验站三种植被类型地表径流效应的对比研究

本文分析研究了３种植被类型下的地表径流在汇流、洪峰及径流过程上的特征，差异是巨大的。在径流过程上桉树林和裸地的变地剧烈，几乎没有什么调蓄作用，洪峰流量占一次性降水径流量的绝大部分，涨水和退水流量都较小。本文应用灰色系统ＧＭ（２，１）模型，成功地预测了以年和以月为时间尺度的地表径流序列，其预测模型可以用来对这些时间尺度的地表径流进行预报。     

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???????????????????ü????????????????GPS????????λ????????????????????????????????????????????????????????????????Improved??GRACE?????????????????????????????????????????????1????300?????????350 km???????????????????????3.993??10 ^-1 m??????300 km??250 km???????????????????8.770????77.145????????400 km??450 km??????????????????8.718????75.307????2??????50 km???????????????????????3.993??10^-1 m??????110 km??220 km??????????????????1.259????1.395????3????????????Improved??GRACE????????????????????????????????350 km??50 km?????     

Dynamic Prediction Model of Overburden Settlement in Deep Mining Areas based on Space–Time Relationship

Natural Resources Research - Depletion of shallow mineral resources caused by deep mining has become an inevitable trend, and deep mining can increase safety accidents and geological hazards....