Early solar system aqueous activity: K isotope evidence from Allende     

Yun Jiang  Piers Koefoed  Olga Pravdivtseva  Heng Chen  Chun‐Hui Li  Fang Huang  Li‐Ping Qin  Jia Liu  Kun Wang 《Meteoritics & planetary science》2021,56(1):61-76

The alkali element K is moderately volatile and fluid mobile; thus, it can be influenced by both primary processes (evaporation and recondensation) in the solar nebula and secondary processes (thermal and aqueous alteration) in the parent body. Since these primary and secondary processes would induce different isotopic fractionations, K isotopes could become a potential tracer to distinguish them. Using recently developed methods with improved precision (0.05‰, 95% confidence interval), we systematically measured the K isotopic compositions and major/trace elemental compositions of chondritic components (18 chondrules, 3 CAIs, 2 matrices, and 5 bulks) in the carbonaceous chondrite fall Allende. Among all the components analyzed in this study, CAIs, which formed initially under high‐temperature conditions in the solar nebula and were dominated by nominally K‐free refractory minerals, have the highest K₂O content (average 0.53 wt%) and have K isotope compositions most enriched in heavy isotopes (δ⁴¹K: ?0.30 to ?0.25‰). Such an observation is consistent with previous petrologic studies that show CAIs in Allende have undergone alkali enrichment during metasomatism. In contrast, chondrules contain lower K₂O content (0.003–0.17 wt%) and generally lighter K isotope compositions (δ⁴¹K: ?0.87‰ to ?0.24‰). The matrix and bulks are nearly identical in K₂O content and K isotope compositions (0.02–0.05 wt%; δ⁴¹K: ?0.62 to ? 0.46‰), which are, as expected, right in the middle of CAIs and chondrules. This strongly indicates that most of the chondritic components of Allende suffered aqueous alteration and their K isotopic compositions are the ramification of Allende parent‐body processing instead of primary nebular signatures. Nevertheless, we propose the small K isotope fractionations observed (< 1‰) among Allende components are likely similar to the overall range of K isotopic fractionation that occurred in nebular environment. Furthermore, the K isotope compositions seen in the components of Allende in this study are consistent with MC‐ICP‐MS analyses of the components in ordinary chondrites, which also show an absence of large (10‰) isotope fractionations. This is not expected as evaporation experiments in nebular conditions suggest there should be large K isotopic fractionations. Nevertheless, possible nebular processes such as chondrules back exchanging with ambient gas when they formed could explain this lack of large K isotopic variation.  相似文献   

毛乌素沙地锦鸡儿（Caragana）根系微域细菌群落多样性特征     

周子渊  于明含  丁国栋  高广磊  何莹莹 《中国沙漠》2020,40(4):128-137

基于16S rRNA高通量基因测序技术，对毛乌素沙地小叶锦鸡儿（Caragana microphylla)、柠条锦鸡儿（Caragana korshinskii）根系微域（即根系、根际土、根区土、灌丛间空白土）间的细菌群落多样性和结构差异性进行表征。本研究对各根系微域间细菌群落的Alpha多样性指数进行了单因素方差分析以及基于OTU水平的PCA分析，探究其在根系微域间Alpha和Beta多样性的层级变化，证实了有关植物根系微域生态位分化的报道，并发现锦鸡儿属植物根系微域间细菌群落的多样性和结构组成随着4个微域类型由外及内呈现出显著的层级差异性（P<0.05）。通过对优势细菌群组的结构组成分析，发现锦鸡儿属植物对特定细菌群组具有显著的向根系内筛选富集的作用（P<0.05）。这种植物通过根系微域对特定细菌群组的逐级筛选富集作用，是导致锦鸡儿属植物灌丛下不同生态位间细菌群落结构和组成发生层级变异的主要原因。  相似文献   

Salinivibrio sp.YH4胞外丝氨酸蛋白酶EYHS耐盐性及生物信息学分析          下载免费PDF全文

武翠玲  宋英达  高慧芳  张廉芸  任晨霞 《盐湖研究》2020,28(1)

摘要：目的 探讨菌株Salinivibrio sp.YH4分泌的丝氨酸蛋白酶EYHS的耐盐性及结构特征。方法 明胶底物酶谱法分析EYHS的耐盐性。应用生物信息学手段对EYHS及6种耐盐的S8家族丝氨酸蛋白酶结构特征进行分析。结果 EYHS在4 mol/L的NaCl溶液中仍具有活性，属于耐盐蛋白酶。EYHS及6种S8家族丝氨酸蛋白酶分子表面的loop区等无规则卷曲所占比例较高，α-螺旋与β-片层则主要位于酶分子内部。EYHS分子表面酸性氨基酸含量较高，且具有弱疏水内核。多序列比对发现蛋白酶的催化三联体两侧存在高度保守的基序和保守的极性氨基酸及芳香族氨基酸，并存在多个保守的Gly与Ala。同源模建和表面电荷分布显示，α螺旋和β片层围成了蛋白酶的催化腔，EYHS活性中心包含由Asp32、His65与Ser215组成的催化三联体，且催化位点区域表面静电势为负。结论 上述结构特征可能有助于耐盐丝氨酸蛋白酶EYHS在高盐环境下维持其稳定性和适度柔性，并有助于其催化功能的发挥，为深入研究耐盐丝氨酸蛋白酶的高盐环境适应性提供了一定的理论依据。  相似文献   

A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing     

Peng Yue  Fan Gao  Boyi Shangguan  Zheren Yan 《International journal of geographical information science》2020,34(11):2243-2274

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.  相似文献   

Coupling numerical simulation with remotely sensed information for the study of frozen soil dynamics     

HuiRan Gao  WanChang Zhang 《寒旱区科学》2020,12(6):404-417

The acquisition of spatial-temporal information of frozen soil is fundamental for the study of frozen soil dynamics and its feedback to climate change in cold regions. With advancement of remote sensing and better understanding of frozen soil dynamics, discrimination of freeze and thaw status of surface soil based on passive microwave remote sensing and numerical simulation of frozen soil processes under water and heat transfer principles provides valuable means for regional and global frozen soil dynamic monitoring and systematic spatial-temporal responses to global change. However, as an important data source of frozen soil processes, remotely sensed information has not yet been fully utilized in the numerical simulation of frozen soil processes. Although great progress has been made in remote sensing and frozen soil physics, yet few frozen soil research has been done on the application of remotely sensed information in association with the numerical model for frozen soil process studies. In the present study, a distributed numerical model for frozen soil dynamic studies based on coupled water-heat transferring theory in association with remotely sensed frozen soil datasets was developed. In order to reduce the uncertainty of the simulation, the remotely sensed frozen soil information was used to monitor and modify relevant parameters in the process of model simulation. The remotely sensed information and numerically simulated spatial-temporal frozen soil processes were validated by in-situ field observations in cold regions near the town of Naqu on the East-Central Tibetan Plateau. The results suggest that the overall accuracy of the algorithm for discriminating freeze and thaw status of surface soil based on passive microwave remote sensing was more than 95%. These results provided an accurate initial freeze and thaw status of surface soil for coupling and calibrating the numerical model of this study. The numerically simulated frozen soil processes demonstrated good performance of the distributed numerical model based on the coupled water-heat transferring theory. The relatively larger uncertainties of the numerical model were found in alternating periods between freezing and thawing of surface soil. The average accuracy increased by about 5% after integrating remotely sensed information on the surface soil. The simulation accuracy was significantly improved, especially in transition periods between freezing and thawing of the surface soil.  相似文献   

敞开酸溶和偏硼酸锂碱熔ICP-MS法测定多金属矿中的稀土元素及铌钽锆铪   总被引：2，自引：2，他引：0  

门倩妮  沈平  甘黎明  冯博鑫 《岩矿测试》2020,39(1):59-67

用电感耦合等离子体质谱法(ICP-MS)测定地质样品中的稀土及难熔元素,混合酸敞开酸溶法和碱熔融法是两种主要的溶样方法。但地质样品组分复杂,元素之间存在相互共生的现象,对于特殊元素、特殊样品用传统酸溶法会造成部分元素消解不完全,使测定结果不准确;而碱熔法的操作过程繁琐,且溶液盐度高,易产生基体干扰和堵塞仪器进样系统。本文改进了传统四酸和五酸体系,采用氢氟酸-硝酸-硫酸敞开酸溶体系,用国家一级标准物质制作标准曲线测定15种稀土元素,方法准确度(ΔlgC)为0.001～0.027。同时改进了偏硼酸锂碱熔法,样品用偏硼酸锂碱熔提取,加入氢氧化钠调节溶液至碱性条件,所测元素与偏硼酸锂共沉淀后过滤分离熔剂,再用硝酸复溶测定15种稀土元素及铌钽锆铪。两种溶样方法的测定值与认定值的相对误差为1.09%～9.30%。将混合酸敞开酸溶法测定稀土元素、偏硼酸锂碱熔法测定铌钽锆铪的结果与其他实验室密闭酸溶法相比,两组数据的相对偏差为0.13%～15.32%。本实验表明,混合酸敞开酸溶法适用于测定地质样品中的稀土元素,偏硼酸锂碱熔法不仅适用于测定地质样品中的稀土元素及铌钽锆铪,也适用于测定如古老高压变质岩石及铝含量高的样品中的铌钽锆铪。  相似文献   

大兴安岭中南段构造岩浆岩带深部地质成矿作用     

苏美霞  杨波  吴艳君  颜萍  孟晓玲 《地质论评》2020,66(5):1321-1333

大兴安岭中南段位于索伦—西拉木伦断裂带与嫩江—白城断裂带交汇域，区内大规模岩浆活动、成矿作用与深部地质活动密切相关。深部地球物理研究成果显示：该区域上地幔存在埋藏较浅的低速、低阻、高热异常体，推断应是深部软流体局部上涌的显示；下地壳存在低密度、低速、高导层，推断是因软流体上涌，诱发下地壳重熔，形成所谓下地壳热流体引起。总之该区域软流层厚度大，热活动性强是引起大规模的岩浆活动及多金属矿床集中分布的深部地质因素。而古生代古亚洲洋洋壳俯冲消减，华北板块、西伯利亚板块陆—陆碰撞拼接及至中生代晚期太平洋板块俯冲作用是引起软流层上涌、下地壳重熔等强烈的壳幔相互作用之源动力。  相似文献   

晚第四纪MIS6以来柴达木盆地成盐作用对冰期气候的响应   总被引：2，自引：0，他引：2  

陈安东  郑绵平  宋高  王学锋  李洪普  韩光  袁文虎 《地质论评》2020,66(3):611-624

气候是控制柴达木盆地盐类沉积的主要因素之一,但是其作用机制尚待明确。作者以柴达木盆地察汗斯拉图盐湖的3个含盐剖面为研究对象,采用多接收电感耦合等离子质谱(MC-ICP-MS)铀系测年测定其沉积时代,并通过X射线粉晶衍射(XRD)分析测定其盐类矿物种类。铀系测年显示D18剖面石盐和芒硝层的沉积时代为13.1±2.0 ka BP～15.9±2.5 ka BP,其中芒硝沉积年代属于末次冰期MIS2晚期;MXK2剖面芒硝层的沉积时代分别为131.7±39.5 ka BP和158.3±10.8 ka BP,D12剖面芒硝层的沉积时代分别为166.6±20.2 ka BP和198.0±20.6 ka BP,可以对应于倒数第二次冰期MIS6。XRD分析确定了3个剖面的盐类矿物主要为芒硝、石盐和石膏。综合多个盐湖晚第四纪成盐数据,本文认为倒数第二次冰期MIS6和末次冰期MIS2是柴达木盆地晚第四纪重要的成盐期,冰期的冷干气候有利于石盐和芒硝等盐类沉积。柴达木盆地"冰期成盐"的根本原因,是由于冰期环境下盆地周边山体冰川规模的扩张以及干冷的冰期气候,共同造成了盐湖补给水量的减少。此外,晚第四纪MIS6和MIS2的冰期降温也是导致盆地中冷相盐类沉积的直接原因。  相似文献   

Simulation of urban expansion via integrating artificial neural network with Markov chain – cellular automata     

Tingting Xu  Jay Gao  Giovanni Coco 《International journal of geographical information science》2019,33(10):1960-1983

Accurate simulations and predictions of urban expansion are critical to manage urbanization and explicitly address the spatiotemporal trends and distributions of urban expansion. Cellular Automata integrated Markov Chain (CA-MC) is one of the most frequently used models for this purpose. However, the urban suitability index (USI) map produced from the conventional CA-MC is either affected by human bias or cannot accurately reflect the possible nonlinear relations between driving factors and urban expansion. To overcome these limitations, a machine learning model (Artificial Neural Network, ANN) was integrated with CA-MC instead of the commonly used Analytical Hierarchy Process (AHP) and Logistic Regression (LR) CA-MC models. The ANN was optimized to create the USI map and then integrated with CA-MC to spatially allocate urban expansion cells. The validated results of kappa and fuzzy kappa simulation indicate that ANN-CA-MC outperformed other variously coupled CA-MC modelling approaches. Based on the ANN-CA-MC model, the urban area in South Auckland is predicted to expand to 1340.55 ha in 2026 at the expense of non-urban areas, mostly grassland and open-bare land. Most of the future expansion will take place within the planned new urban growth zone.  相似文献   

南海开放共享航次关键科学问题的思考——从多尺度海洋动力学角度出发     

杜岩  陈举  经志友  王祥鹏  陈更新  徐驰  储小青  陈植武  徐杰  施震  唐世林  何云开  梁韵  施平 《热带海洋学报》2020,39(6):1-17

南海是西太平洋最大的边缘海, 通过一系列的海峡与西太平洋和印度洋相联通, 其不同时空尺度的海洋环流动力过程及其生态环境效应是南海区域海洋学研究的重要内容。自20世纪50年代末全国第一次海洋普查开始, 我国对海洋调查的支持力度不断加大, 以科学考察船为代表的海洋科学观测平台建设不断加强; 进入新千年以来, 国内海洋科考船依托的各主要研究所和院校本着开放的理念, 先后组织多单位联合进行海上观测。尤其是最近10年, 国家自然科学基金委员会支持实施了船时共享航次计划, 进一步促进了国内海洋界的交流和合作, 南海区域海洋学的相关研究取得了很多重要的成果。从多尺度环流动力学的角度出发, 本文简要回顾了南海海洋观测的发展历程, 并初步总结了近些年来南海关键科学问题的研究进展, 包括南海和西太平洋的水体交换过程、南海中小尺度过程、多尺度相互作用及其生态环境效应等; 并且在现有的研究基础上, 对未来南海的观测和科学问题提出若干思考与展望。  相似文献