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.     

Fast genetic mapping in barley: case studies of cuticle mutants using RNA-sequencing

Barley(Hordeum vulgare L.) is one of the earliest domesticated crop species and ranked as the fourth largest cereal production worldwide. Forward genetic studies in barley have greatly advanced plant genetics during the last century; however, most genes are identified by the conventional mapping method. Array genotyping and exome-capture sequencing have also been successfully used to target the causal mutation in barley populations, but these techniques are not widely adopted because of associated costs and partly due to the huge genome size of barley. This review summarizes three mapping cases of barley cuticle mutants in our laboratory with the help of RNA-sequencing. The causal mutations have been successfully identified for two of them and the target genes are located in the pericentromeric regions. Detailed information on the mapping-by-sequencing, mapping-and-sequencing, and RNA-sequencing assisted linkage mapping are presented and some limitations and challenges on the mapping assisted by RNA sequencing are also discussed. The alternative and elegant methods presented in this review may greatly accelerate forward genetics of barley mapping, especially for laboratories without large funding.     

建鲤基因组DNA的RAPD分析

用 1 5个随机引物对建鲤基因组DNA进行RAPD分析 ,结果显示 ,建鲤群体内的遗传相似系数为 0 91 81± 0 0 73 8,多态位点比例为 0 41 67,平均杂合度为 0 1 884。表明建鲤种质较纯 ,群体内的遗传变异程度较小。建鲤优良性状产生的分子学基础是等位基因的杂合程度较高     

ECOLOGICAL SERIES OF SOIL ANIMALS IN DARLIDAI MOUNTAIN

The ecological series of soil animals under the broad-leaved and pine mixed forest in Darlidai Mountainwas studied. Seven sample plots were selected according to different altitude gradients, which belong to different vegeta-tion types. By investigating and analyzing soil animals in every sample plot it is found that there are 45 groups and 1956individuals, which axe involved in 3 phylums, 7 classes, 16 orders, respectively. The altitude is a key factor which af-fects ecological series of soil animals. Both the groups and individuals of soil animals increase with altitude increasingunder certain conditions, which contrastes with ordinary cases, resulting from special micro-climate in studied area. Thegroups and individuls of soil animals are the most under the broad-leaved and pine forest on the top of the mountain, andthe least under Picea-Abies forest in the foot of the mountain.     

Consolidation of double‐layered ground with vertical drains

Vertical drains are usually installed in subsoil consisting of several layers. Due to the complex nature of the problem, over the past decades, the consolidation properties of multi‐layered ground with vertical drains have been analysed mainly by numerical methods. An analytical solution for consolidation of double‐layered ground with vertical drains under quasi‐equal strain condition is presented in this paper. The main steps for the computation procedure are listed. The convergence of the series solution is discussed. The comparisons between the results obtained by the present analytical method and the existing numerical solutions are described by figures. The orthogonal relation for the system of double‐layered ground with vertical drains is proven. Finally, some consolidation properties of double‐layered ground with vertical drains are analysed. Copyright © 2001 John Wiley & Sons, Ltd.     

观驾山—黑岛一带信息量法找金研究

本文以成矿地质模型为依据，对观驾山—黑山岛一带的化探、物探、遥感及地质等信息变量进行了详细的分析，选取了１０个信息变量２４个标志状态；在此基础上，运用信息量法对研究区内４５８个单元的信息量值进行计算，并由此确定了研究范围内的成矿远景区。事实表明，研究区信息量成矿预测是非常有效的     

Revisiting Sustainable Development of Dry Valleys in Hengduan Mountains Region

Dry valleys are a striking geographic landscape in Hengduan Mountains Region and are characterized by low rainfall, desert type of vegetation and fragile environment. Past efforts and resources have been concentrated mainly on rehabilitation of degraded ecosystem and fragile environment, particularly reforestation, while socio-economic development has been largely overlooked. Despite successes in pocket areas, the overall trend of unsustainability and environmental deterioration are continuing. It is important to understand that uplift of the Tibetan Plateau is the root cause of development of dry valleys, and development and formation of dry valleys is a natural process. Human intervention has played a secondary role in development of dry valleys and degradation of dry valleys though human intervention in many cases has speeded up environmental degradation of the dry valleys. It is important to understand that dry valleys are climatic enclaves and an integrated approach that combines rehabilitation of degraded ecosystems and socio-economic development should be adopted if the overall goal of sustainable development of dry valleys is to be achieved. Promotion of niche-based cash crops, rural energy including hydropower, solar energy, biogas and fuelwood plantation is recommended as the priority activities.     

双极化天气雷达方程

在回转椭球状降水粒子的假设下求出了降水粒子的散射截面，并且考虑了粒子轴线铅垂和随机取向两种重要的典型情况；推导了双极化雷达的回波方程以及降雨量公式。该方程除包含降水粒子的信息外，关于雷达与降水粒子间的几何关系都以雷达天线仰角及雷达与降水粒子间的距离表示，同时还考虑了地球的球面效应和大气折射效应。由于采用了并矢方法，使推导简捷明了