New In‐Situ LA‐ICP‐MS U‐Pb Ages of Uraninite from the Mianhuakeng Uranium Deposit,Northern Guangdong Province,China: Constraint on the Metallogenic Mechanism

正Objective Hydrothermal uranium deposits in South China have become one of the main uranium producers over the past several decades.Numerous uranium deposits are densely distributed in the Guidong and Zhuguangshan plutons of the Nanling region,which constitute the largest uranium mineralization area in China(Cai Yuqi et al.,2015).The Mianhuakeng(MHK)uranium deposit,one of the largest     

东川南缘雪岭矿区隐伏铜矿地质地球化学特征及成矿机制

雪岭矿区位于康滇地轴云南段东川矿区南缘,区内主要出露震旦系和寒武系沉积地层,其浅部可见铜多金属脉状矿化沿断裂带和辉绿岩脉产出,深部勘探发现了全隐伏在陡山沱组中的层状铜矿。铜矿化以黄铜矿、斑铜矿为主,呈浸染状、网脉状、薄层状和星点状赋存于深灰色破碎状白云岩、黑色炭泥质岩和石英脉中,矿体具明显沉积及热液叠加改造特征。常量元素分析显示岩矿石SiO₂、Fe₂O₃、FeO、K₂O等含量较高,而Na₂O、CaO和MgO含量偏低;微量元素分析显示围岩Cu、Pb、Zn、Ag元素含量较高,富集U、Y等元素,亏损Nb、Zr、Ti、Yb等高场强元素和Sr,矿石样品则富集U、Nd等高场强元素,亏损Ba、K、Sr等大离子亲石元素和Nb;球粒陨石标准化的稀土元素配分模式为轻稀土富集、重稀土亏损的右倾形态,且呈现出铕的强烈亏损。陡山沱组改造型脉状矿体方解石和黄铁矿样品δD_V-SMOW值分别为-137.3×10^-3和-110.2×10^-3,δ¹⁸O_水值分别为-11.3×10^-3和-1.29×10^-3,显示成矿流体来源于大气降水形成的层间封存水;矿石富集重硫,硫主要来源于海相硫酸盐的还原作用,部分受到深部昆阳群古铜矿床硫和生物硫的影响;铅来源于放射性成因铅较高的源区,具壳幔混合铅的特征,且矿石、围岩、昆阳群古铜矿的铅同位素组成具一定亲缘性,显示成矿物质主要来源于下伏昆阳群古铜矿,部分来源于围岩。综合研究认为,该铜矿与滥泥坪矿区所含陡山沱组铜矿相似,均为昆阳群古铜矿残余风化壳在海解作用下铜质析出,在成岩及构造作用下活化迁移并沿炭泥质还原性岩石、石英脉及构造有利位置沉淀富集所致。本区找矿重点应为深部陡山沱组铜矿以及下伏昆阳群古铜矿床。     

“Source to Sink”: A Review of Tectonics-Erosion-Sedimentation Interactions in the Analogue Experiments of Accretionary WedgeEI北大核心CSCD

It is believed that the tectonics-erosion-sedimentation interaction in the analogue experiments was essentially improved by the theory of “from source to sink”. In particular, the widespread uplift and exhumation in the western China occurred in Cenozoic can be considered to be a typical natural laboratory in the world. Here we review our current understanding from tectonic sandbox models of tectonics-erosion-sedimentation and their interactions, as well as from natural laboratory. As we known, there are widespread erosion occurred predominantly at hinterland of the accretionary wedge, in contrast to the sedimentation occurred widely at foreland of the wedge. Therefore, fold-and-thrust belts with low syntectonic sedimentation and erosion would evolve in a self-similar fashion to produce a narrow accretionary wedge, while high syntectonic sedimentation and erosion would produce accretionary wedge with very active hinterland thrusts, and a large width. Furthermore, the critically tapered wedge model suggests that the crust-scale thrust-and-fold belts under a horizontal compressive force would come into a self-similar growth of a forward-tapering wedge when it reaches a critical taper angle of the combined angles of the base dip and the wedge slope. Such a process has important influence on the tectonics-erosion- sedimentation and their interactions both in accretionary wedges and their analogue experiments. Although there is a significant similarity between the analogue experiments and natural accretionary wedges in the surface processes of tectonics- erosion-sedimentation and their interactions, it is difficult to get more universal parameters between them. It should be noted that sandbox models of the accretionary wedges in the natural laboratory would improve significantly our understanding of the theory of the tectonics-erosion-sedimentation interactions and “from source to sink”. © 2018, Science Press. All right reserved.     

Research Progress of Relative Humidity and Its Changing Annual Cycle

Studies on the characteristics of relative humidity annual cycle change include the frequency, phase, and amplitude of the time series and their changes. The effective diagnosis of the relative humidity annual cycle can provide important help in the monitoring and regulation of seasonal haze, the spatial distribution of epidemic outbreaks and their prevention and control, and the real-time forecasting and decision-making of monsoon precipitation. Different from studies on the trend of the relative humidity, the diagnosis in the annual cycle is scarce. This paper summarized the research status of relative humidity and its annual cycle, introduced several current methods for extracting common signals, and evaluated the feasibility of these methods for extracting annual cycle signals. Due to the time-varying characteristics of the annual cycle of relative humidity and complex structures such as asymmetric triangular waves, square-like waves, and state transients, harmonic-based extraction methods are difficult to succeed. The nonlinear signal extraction method with high noise immunity will solve this problem. At present, the relative humidity annual cycle studies urgently need to be improved and improve the quality of relative humidity observation data, accurately extract and quantify the time-varying characteristics and complex structure of the annual cycle. Moreover, combining the dynamic process and statistical analysis, we also need to study the physical mechanism of the change of relative humidity annual cycle (frequency, phase, amplitude, etc.) in China.     

Prediction of landslide displacement with an ensemble-based extreme learning machine and copula models

Research on the dynamics of landslide displacement forms the basis for landslide hazard prevention. This paper proposes a novel data-driven approach to monitor and predict the landslide displacement. In the first part, autoregressive moving average time series models are constructed to analyze the autocorrelation of landslide triggering factors. A linear ensemble-based extreme learning machine using the least absolute shrinkage and selection operator is applied in predicting the displacement of landslides. Five benchmarking data-driven models, the support vector machine, neural network, random forest, k-nearest neighbor, and the classical extreme learning machine, are considered as baseline models for validating the ensemble-based extreme learning machines. Numerical experiments demonstrated that the proposed prediction model produces the smallest prediction errors among all the algorithms tested. In the second part, parametric copula models are fitted on the predicted displacement, to investigate the relationship between the triggering factors and landslide displacement values. The Gumbel-Hougaard copula model performs best, which indicates strong upper tail correlation between the triggering factors and displacement values. Thresholds for the triggering factors can be obtained by monitoring the landslide moving patterns with large displacement values. The effectiveness and utility of the proposed data-driven approach have been confirmed with the landslide case study in the region of the Three Gorges Reservoir.     

The investigation of ultra-long-distance concrete pipe stuck in quartz sandstone formation using numerical simulation

During mountainous area construction by long-distance pipe jacking, the pipe stuck encountered. To reveal the cause of the pipe stuck, this paper investigates the pipe surface frictional resistance corresponding to different burial depths and surrounding rock parameters by ADINA finite element analysis. Parameter sensitivity analysis results show that the cohesion effect on the frictional resistance was small, the frictional resistance tended to decrease markedly with the increasing other rock mechanical parameters and the decreasing burial depth and friction coefficient of the pipes. After continuing to consider the prerequisite of simultaneously changing the elastic modulus, internal friction angle and burial depth conditions, a solution of the maximum number of pipes driven by a single intermediate jacking station (IJS) was reduced from 59 to 40 was proposed based on an integration of simulations with the field monitoring results. Finally, the pipe jacking project was successfully completed after adopting the improvement proposals.     

An adaptive method for clustering spatio‐temporal events

The clustering of spatio‐temporal events has become one of the most important research branches of spatio‐temporal data mining. However, the discovery of clusters of spatio‐temporal events with different shapes and densities remains a challenging problem because of the subjectivity in the choice of two critical parameters: the spatio‐temporal window for estimating the density around each event, and the density threshold for evaluating the significance of clusters. To make the clustering of spatio‐temporal events objective, in this study these two parameters were adaptively generated from statistical information about the dataset. More precisely, the density threshold was statistically modeled as an adjusted significance level controlled by the cardinality and support domain of the dataset, and the appropriate sizes of spatio‐temporal windows for clustering were determined by the spatio‐temporal classification entropy and stability analysis. Experiments on both simulated and earthquake datasets were conducted, and the results show that the proposed method can identify clusters of different shapes and densities.