2017-08-09新疆精河Ms6.6地震附近区域相对应变的变化分析

2017年精河M_S6.6地震震前，尼勒克、巴伦台和小泉沟台钻孔应变仪记录到显著的应变变化，经现场落实确认，异常是可靠的。根据这3个台的记录资料计算相对应变的变化，结果表明，地震前最大（小）主应变大小和方向分别出现明显加速和急剧偏转变化。此外还发现，相对应变场异常期间主方向与震源机制解P轴方位较为一致。     

广州城市流浪乞讨者的空间管治与日常生活实践

以广州流浪乞讨者为研究对象,通过深度访谈等质性研究方法,解读针对流浪乞讨者的空间管治政策与手段,分析流浪乞讨者的日常生活实践与生境协商。研究发现：在地方城市政策对流动性与公共秩序限制的双重压力下,在流浪乞讨者的日常生活实践中,不仅有针对管治行动者而刻意为之的特殊营建,亦有基于程式化生活流程对自我身份认同的重塑与真情实感的展演。地方政府基于空间目标的救助与真实存在的日常生活实践存在着一种张力。研究关注了城市边缘群体日常生活对地理意义的主动塑造过程,对全面理解并规范管理中国城市流浪乞讨现象具有借鉴意义。     

Degradation induces changes in the soil C:N:P stoichiometry of alpine steppe on the Tibetan Plateau

Due to the Tibetan Plateau's unique high altitude and low temperature climate conditions,the region's alpine steppe ecosystem is highly fragile and is suffering from severe degradation under the stress of increasing population,overgrazing,and climate change.The soil stoichiometry,a crucial part of ecological stoichiometry,provides a fundamental approach for understanding ecosystem processes by examining the relative proportions and balance of the three elements.Understanding the impact of degradation on the soil stoichiometry is vital for conservation and management in the alpine steppe on the Tibetan Plateau.This study aims to examine the response of soil stoichiometry to degradation and explore the underlying biotic and abiotic mechanisms in the alpine steppe.We conducted a field survey in a sequent degraded alpine steppe with seven levels inNorthern Tibet.The plant species,aboveground biomass,and physical and chemical soil properties such as the moisture content,temperature,pH,compactness,total carbon(C),total nitrogen(N),and total phosphorus(P)were measured and recorded.The results showed that the contents of soil C/N,C/P,and N/P consistently decreased along intensifying degradation gradients.Using regression analysis and a structural equation model(SEM),we found that the C/N,C/P,and N/P ratios were positively affected by the soil compactness,soil moisture content and species richness of graminoids but negatively affected by soil pH and the proportion of aboveground biomass of forbs.The soil temperature had a negative effect on the C/N ratio but showed positive effect on the C/P and N/P ratios.The current study shows that degradation-induced changes in abiotic and biotic conditions such as soil warming and drying,which accelerated the soil organic carbon mineralization,as well as the increase in the proportion of forbs,whichwere difficult to decompose and input less organic carbon into soil,resulted in the decreases in soil C/N,C/P,and N/P contents to a great extent.Our results provide a sound basis for sustainable conservation and management of the alpine steppe.     

Bibliometric Analysis of Global Research Progress on Coastal Flooding 1995–2016

Global research progress on coastal flooding was studied using a bibliometric evaluation of publications listed in the Web of Science extended scientific citation index. There was substantial growth in coastal flooding research output, with increasing publications, a higher collaboration index, and more references during the 1995–2016 period. The USA has taken a dominant position in coastal flooding research, with the US Geological Survey leading the publications ranking. Research collaborations at institutional scales have become more important than those at global scales. International collaborative publications consistently drew more citations than those from a single country. Furthermore, coastal flooding research included combinations of multi-disciplinary categories, including ‘Geology' and ‘Environmental Sciences Ecology'. The most important coastal flooding research sites were wetlands and estuaries. While numerical modeling and 3 S(Remote sensing, RS; Geography information systems, GIS; Global positioning systems, GPS) technology were the most commonly used methods for studying coastal flooding, Lidar gained in popularity. The vulnerability and adaptation of coastal environments, their resilience after flooding, and ecosystem services function showed increases in interest.     

风和径流量对长江口缺氧影响的数值模拟

受自然和人类活动的影响，海洋缺氧现象日益严重，威胁着海洋生态环境，海洋缺氧问题已经引起了人们的广泛关注。本文应用区域海洋模式并耦合生态模式，对东海的生态系统进行了数值模拟和分析研究。与观测数据比较显示，该模型能较好地模拟长江口外生态变量的分布趋势。另外本文通过设置不同敏感性实验，探讨风和径流量对长江口底层缺氧现象的影响，结果分析表明，风和径流量对长江口外缺氧区的形成有显著的影响。径流量变化虽然对长江口外缺氧区的季节变化影响并不显著，但是对缺氧区域面积却存在显著的影响。径流量增加，水体层化增强，表层叶绿素浓度增加，最终导致缺氧区域范围扩展；径流量减小，水体层化减弱，表层叶绿素浓度减小，缺氧区域范围缩小。风向和风速的改变不仅影响长江口外缺氧区的季节变化，还影响缺氧区域面积。     

Implementation of a coupled plastic damage distinct lattice spring model for dynamic crack propagation in geomaterials

This paper studies dynamic crack propagation by employing the distinct lattice spring model (DLSM) and 3‐dimensional (3D) printing technique. A damage‐plasticity model was developed and implemented in a 2D DLSM. Applicability of the damage‐plasticity DLSM was verified against analytical elastic solutions and experimental results for crack propagation. As a physical analogy, dynamic fracturing tests were conducted on 3D printed specimens using the split Hopkinson pressure bar. The dynamic stress intensity factors were recorded, and crack paths were captured by a high‐speed camera. A parametric study was conducted to find the influences of the parameters on cracking behaviors, including initial and peak fracture toughness, crack speed, and crack patterns. Finally, selection of parameters for the damage‐plasticity model was determined through the comparison of numerical predictions and the experimentally observed cracking features.     

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.     

A numerical model for Type II supernovae — The collapse stage

We use the following numerical model for the collapse stage of a Type II supernova of 15 M_⊙. Our electron capture rate includes the effects of the inverse reaction and the neutron-proton mass difference. This decreases the electron density at the collapse stage and led to rather large values of the maximum inward velocity and of the corresponding mass (Umax = 3.06 × 10⁹cm/s, Mmax=0.76 M_⊙). These larger values are more favourable for the propagation of shock after the rebounce and the triggering-off of a Type-II supernova explosion. For neutrino transport, we use a leakage model and an equilibrium diffusion model, respectively, for the thin and thick stages and a grey atmosphere model to assess the effect of neutrino precipitation on the collapse. We found this effect to be small, the energy precipitation to be not more than 10^?5 the neutrino energy loss and the momentum precipitation not more than 10^?6 the gravitational acceleration.     

江汉盆地钻孔测井资料确定地应力最大水平主压应力方向

利用钻孔测井资料并运用地层倾角测量信息分析法，给出了江汉盆地地应力最大水平主压应力方向为ＮＥ６０～６５°     

ANALYSIS OF DRIVING FORCES ON THE CHANGE OF HISTORICAL FARMLAND USE IN SHANDONG PROVINCE DURING THE QING DYNASTY （1644-1911）

How land-cover has been changed by human use over the last 300 years is one of the five overarching questions guiding the Land-use/Cover Change (LUCC) Science/Research Plan. China has variety of historical docu-ments providing unique data superiority. So the characteristics of farmland area in Shandong Province during the Qing Dynasty (1644-1911) are summarized firstly: 1) the rising trend of farmland area was striking; 2) farmland area had re-markable fluctuation; 3) farmland area per capita decreased dramatically; 4) wasteland reclamation index increased rapidly. Then, the driving forces of farmland area change are analyzed. It is concluded that natural and human factors are jointly influential. Among the driving forces, human dimensions are the main factors of farmland area change,which direct the general tendency of the changes mentioned above. And the natural factors influence the stability of farmland area as well. Variation of the natural factors would act as the major contributory factor to farmland area change during years or periods of abrupt climatic changes, or during the intensive occurring periods of natural hazards.Besides, the passive aspects of human factors, such as war chaos also influenced the fluctuation of the farmland area.This research indicates that it is feasible to study the land-use/cover change by Chinese historical literatures, which has huge potential to provide a comprehensive picture of the growing dominance of human land-use and land-cover pat-terns that can be used in many global change research oroiects.