ESB技术在国土资源数据交换中的应用

本文分析了国土资源数据交换的业务需求,阐述基于ESB的数据交换架构的设计思想和与之配套的管理工具,指出基于ESB的数据交换架构是国土资源数据交换的理想方案。     

冲绳海槽沉积物孔隙水地球化学特征及其指示意义

通过对东海外陆坡–冲绳海槽GSW1孔沉积物孔隙水δ₁₃C、δ₁₈O、δ₁₁B、δ₃₇Cl同位素和Cl_-、S O₄^2-、K₊、Na₊等离子指标的分析,探讨了沉积物早期成岩作用、流体来源、迁移和氧化环境的变化。研究发现,GSW1孔孔隙水溶解无机碳主要来自海水和有机质,SO₄^2-浓度随深度下降比较平缓,Cl_-浓度远低于海水,该孔表层沉积物中硫酸盐消耗主要由有机质硫酸盐还原作用（OSR）所控制,甲烷厌氧氧化作用（AOM）发生在4 m以下更深的层位。OSR产生的H₂S向上扩散富集并被氧化,是导致GSW1孔110～360 cm处SO ₄^2-浓度未明显下降的主要因素。孔隙水SO₄^2-浓度整体随着深度增加呈减小的趋势,表明GSW1孔沉...     

Prediction Model of Kinetic Energy Conversion of Tandem Dual-Oscillator Based on Flow-Induced Vibration Experiment

China Ocean Engineering - Flow-induced vibration energy harvesting devices typically use an elastically supported body immersed in an oncoming flow to convert the sea and river current’s...     

黄河流域水资源利用与经济增长脱钩及影响因素分解

水资源是黄河流域生态保护和高质量发展的最大刚性约束,识别流域水资源利用变化驱动因素具有重要意义。首先从结构视角测度黄河流域水足迹变化,进而基于Tapio脱钩模型与Kaya-LMDI分解模型,解析水足迹与经济增长脱钩状态,并从技术效应、结构效应、规模效应、禀赋效应、城市化效应和人口效应识别水资源利用变化驱动因素。研究发现：(1)黄河流域水足迹总体呈现上升趋势,农业水足迹占比高达85%,用水结构与产业结构倒挂问题突出。(2)黄河流域上下游水资源量与水足迹空间分布不匹配,中下游面临更严重水资源约束。(3)水足迹与经济增长关系主要表现为弱脱钩,但2015—2019年各省区开始向强脱钩转变。(4)规模效应、城市化效应和人口效应对水足迹变化起拉动作用,技术效应、结构效应和禀赋效应对水足迹变化起抑制作用,但仍有提升潜力,各省区影响因素存在一定差异。为此,需要强化水资源利用技术研发与推广,推动农业集约式发展,提升农业用水效率,进一步优化产业结构和新型城镇化建设,缓解水资源约束困境,推动黄河流域经济高质量发展。     

菌株Alcaligenes sp.P156中一个新型烟酸羟化酶的克隆与功能验证

本研究预测naa cluster中的naaB基因负责催化烟酸到6-羟基烟酸的反应。通过对NaaB的蛋白序列进行分析,发现该酶含有三个亚基,分别由naaB_L1、naaB_S、naaB_L2基因编码,其中naaB_L1和naaB_L2分别编码2个含有钼辅因子结合结构的大亚基,naaB_S基因编码一个含有[2Fe-2S]簇的小亚基。本研究对naaB基因进行了克隆,将构建的重组质粒pME6032-naaB_L1SL2分别转化到无色杆菌(Achromobacter sp.)和大肠杆菌(Escherichia coli)中,通过HPLC和LC-MS检测验证了NaaB负责催化烟酸到6-羟基烟酸,并且在无色杆菌和大肠杆菌中NaaB均能够转化烟酸,这与之前报道烟酸羟化酶不能在大肠杆菌表达的结果不同,说明NaaB的基因编码和催化功能具有独特性。通过序列分析推测NaaB的这一特性可能跟该酶同时含有两个钼结合结构域的大亚基有关。     

基于SBM-Malmquist-Tobit模型的沿黄九省(区)环境效率差异及影响因素分析

从非期望产出角度运用SBM模型测度沿黄九省(区)2001-2010年的环境效率静态水平,通过Malmquist 生产率指数模型分析沿黄九省(区)环境效率的动态变化趋势,通过Tobit回归分析方法探讨影响沿黄九省(区)环境效率的影响因素,旨在对沿黄九省(区)环境效益评价提供科学依据和决策参考.结果表明:(1)在考虑环境变量之后,区域的平均效率水平均有一定程度的降低,上中游省份对环境变量的引入较下游省份更为敏感;沿黄九省(区)环境效率静态水平均相对较低,上中游省份较下游省份更甚.(2)环境效率水平有向好发展的态势,其值的改善是技术效率和技术进步两个因素共同作用的结果.(3)经济、制度和地区等因素对环境效率的影响效果各有不同,这些因素对环境效率的作用机理存在一定差别.     

四苯硼钠—季铵盐质量滴定法分析钾含量研究

依据四苯硼钠—季铵盐容量法滴定K⁺离子的原理,采用质量滴定法,考察了滴定速度、松节油加入量对四苯硼钠与季铵盐反应的影响及共存离子(包括Li⁺、Mg²⁺、Ca²⁺、SO2-₄、B₄O2-₇、CO2-₃)对K⁺含量测定结果的影响。当测定K⁺离子含量在5～15 mg范围内,松节油最佳加入量为25滴,分析误差< 0.3%。     

新疆及邻区地震构造图简介

This paper briefly introduces the Seismotectonic Map of Xinjiang and its neighborhood in the scale of 1∶2500000.The map is amended,supplemented and expanded based of the newly compiled Seismotectonic Map of Xinjiang in scale 1∶1000000.The base map of this seismotectonic map is the geologic map of western China and its neighborhood compiled by Li Tingdong.The abundant new materials from related research,referential literatures and the analyses on remote sensing data were used in the compiling work.A database and relevant documents are built for nearly 300 active faults and 150 active folds.The basic information of the major active faults,especially those near the border areas in this map are introduced in this paper.     

Estimation of the Budyko model parameter for small basins in China

At the mean annual scale, water availability of a basin is substantially determined by how much precipitation will be partitioned into evapotranspiration and run-off. The Budyko framework provides a simple but efficient tool to estimate precipitation partitioning at the basin scale. As one form of the Budyko framework, Fu's equation has been widely used to model long-term basin-scale water balance. The major difficulty in applications of Fu's equation is determining how to estimate the curve shape parameter ω efficiently. Previous studies have suggested that the parameter ω is closely related to the long-term vegetation coverage on large river basins globally. However, on small basins, the parameter ω is difficult to estimate due to the diversity of controlling factors. Here, we focused on the estimation of ω for small basins in China. We identified the major factors controlling the basin-specific (calibrated) ω from nine catchment attributes based on a dataset from 206 small basins (≤50,000 km²) across China. Next, we related the calibrated ω to the major factors controlling ω using two statistical models, that is, the multiple linear regression (MLR) model and artificial neural network (ANN) model. We compared and validated the two statistical models using an independent dataset of 80 small basins. The results indicated that in addition to vegetation, other landscape factors (e.g., topography and human activity) need to be considered to capture the variability of ω on small basins better. Contrary to previous findings reached on large basins worldwide, the basin-specific ω and remote sensing-based vegetation greenness index exhibit a significant negative correlation. Compared with the default ω value of 2.6 used in the Budyko curve method, the two statistical models significantly improved the mean annual ET simulations on validation basins by reducing the root mean square error from 114 mm/year to 74.5 mm/year for the MLR model and 70 mm/year for the ANN model. In comparison, the ANN model can provide a better ω estimation than the MLR model.