Improving the prediction of arsenic contents in agricultural soils by combining the reflectance spectroscopy of soils and rice plants

Visible and near-infrared reflectance spectroscopy provides a beneficial tool for investigating soil heavy metal contamination. This study aimed to investigate mechanisms of soil arsenic prediction using laboratory based soil and leaf spectra, compare the prediction of arsenic content using soil spectra with that using rice plant spectra, and determine whether the combination of both could improve the prediction of soil arsenic content. A total of 100 samples were collected and the reflectance spectra of soils and rice plants were measured using a FieldSpec3 portable spectroradiometer (350–2500 nm). After eliminating spectral outliers, the reflectance spectra were divided into calibration (n = 62) and validation (n = 32) data sets using the Kennard-Stone algorithm. Genetic algorithm (GA) was used to select useful spectral variables for soil arsenic prediction. Thereafter, the GA-selected spectral variables of the soil and leaf spectra were individually and jointly employed to calibrate the partial least squares regression (PLSR) models using the calibration data set. The regression models were validated and compared using independent validation data set. Furthermore, the correlation coefficients of soil arsenic against soil organic matter, leaf arsenic and leaf chlorophyll were calculated, and the important wavelengths for PLSR modeling were extracted. Results showed that arsenic prediction using the leaf spectra (coefficient of determination in validation, R_v² = 0.54; root mean square error in validation, RMSE_v = 12.99 mg kg⁻¹; and residual prediction deviation in validation, RPD_v = 1.35) was slightly better than using the soil spectra (R_v² = 0.42, RMSE_v = 13.35 mg kg⁻¹, and RPD_v = 1.31). However, results also showed that the combinational use of soil and leaf spectra resulted in higher arsenic prediction (R_v² = 0.63, RMSE_v = 11.94 mg kg⁻¹, RPD_v = 1.47) compared with either soil or leaf spectra alone. Soil spectral bands near 480, 600, 670, 810, 1980, 2050 and 2290 nm, leaf spectral bands near 700, 890 and 900 nm in PLSR models were important wavelengths for soil arsenic prediction. Moreover, soil arsenic showed significantly positive correlations with soil organic matter (r = 0.62, p < 0.01) and leaf arsenic (r = 0.77, p < 0.01), and a significantly negative correlation with leaf chlorophyll (r = −0.67, p < 0.01). The results showed that the prediction of arsenic contents using soil and leaf spectra may be based on their relationships with soil organic matter and leaf chlorophyll contents, respectively. Although RPD of 1.47 was below the recommended RPD of >2 for soil analysis, arsenic prediction in agricultural soils can be improved by combining the leaf and soil spectra.     

一个以遗传算法为基础的结构可靠性分析方法

本文首先总结了一次二阶矩法在结构可靠性分析时的五个弱点。针对其在寻求验算点时需要求极限状态函数的导数以及在处理多峰性极限状态函数时存在的不收敛或收敛于局部验算点等弱点，探讨了将遗传算法应用于结构可靠性分析的可能性，并在分析其应用时存在的具体问题的基础上提出了一个以智能生物为基础的遗传算法。本文的分析计算表明：遗传算法在结构可靠性分析中是适用的，它可以克服一次二阶矩法在求解验算点时存在的几个弱点。本     

逐步缩小搜索范围的遗传算法

本文介绍在遗传算法的运行过程中如何逐步缩小搜索范围，使搜索速度与计算精度同时得到提高的方法。文中提出了真值邻域的概念，利用这个概念得到了缩小搜索范围的压缩公式。只要合理选择初始搜索范围（这一点并不难做到），上述压缩公式能确保问题的解始终保留在压缩后的搜索范围内。通过理论模型的检验及与原有遗传算法结果的比较，证实了方法的有效性。     

西安市反倾向地裂缝成因分析

本文在大量现场调研的基础上，结合室内分析，初步探讨了西安市反倾向地裂缝的成因及其与区内已发育的１１个条地裂缝的关系，从而进一步证实了构造重力扩展机制是形成西安地裂缝的内在原因。     

斑岩铜矿床研究综述

综述了板块构造、大地构造单元、区域构造、深大断裂以及地球深部热点与斑岩铜矿床形成关系的研究成果，系统介绍了斑岩铜矿床蚀变矿化分带特征、蚀变矿化物理化学条件、蚀变矿化的热力学研究、斑岩铜矿床中脉体的产状和分布特征以及成因观点，总结了斑岩铜矿床成矿物质来源与矿床成因模式，最后指出了斑岩铜矿床将来应该注意的研究方向。     

宁波大桥主墩墩址软弱带成因机制研究

通过对宁波大桥主墩墩址软弱带详细的地质勘测和综合方法研究，内中包括粘土泥质物Ｘ射线衍射分析，软弱带岩石化学成分和不同成因砂和砾石的成分和特征研究，特别是软弱带的显微构造和物质来源的研究，本文对这一软弱带的成因机制着重进行了探讨。研究发现，这一软弱带在结构上可划分为三部分或三层结构，下部为挤压破碎带、中部为风化产物、上部为地表水贯入充填堆积。它表明这一软弱带经历了三种不同的地质作用的演化过程或具有三种物质来源。这一研究结论对大桥的设计和施工有重要的影响和意义。     

锶同位素初始比值在划分花岗岩成因类型上的应用探讨

本文根据吴利仁的锶同位素初始比值(Ⅰ值)演化图解,计算出划分花岗岩成因类型分界线的三条直线方程:(1)幔源型与幔壳混源型分界线方程;(2)混源型与壳源型分界线方程;(3)壳源型中,下地壳与上地壳分界线方程。只要知道一个花岗岩体的形成年龄和Ⅰ值,就可以根据三个方程的分界值准确地判定其成因类型。这种利用Ⅰ值线方程定量地划分花岗岩成因类型的方法,符合Ⅰ值随时间推移而增长的规律,比目前采用的固定值法更加合理。此外,根据(1)、(2)二个方程,应用杠杆原理,还可大致估计幔、壳源岩的百分比。     

A Brief Introduction to Deep-Water Mass-Transport Complexes: Structures,Genetic Classifications and Identification Methods

Mass-Transport Complexes (MTCs) are important components of deep-water systems, and widely distributed in continental margins and lake basins. Understanding MTCs is helpful for expanding the targets of deep-water hydrocarbon exploration and for evaluating geological risks of subsea engineering. Typical MTCs consist of three parts: the head tension area, body slip area, and toe compression area. During the transportation of MTCs, these three domains come into being successively. MTCs can be classified into three types: slide rock, slump rock, and debris rock, based on the sediment transport process and fluid properties, and they respectively correspond to elastic deformation, elastic and plastic deformation and plastic deformation stages. In 3D seismic plan, according to the direction of sediment flow (the slope direction), some depositional elements of MTCs, such as head cliffs, body folds, and toe squeeze ridges, can be clearly identified in proper order, and in seismic profiles MTCs are characterized by weak-medium amplitude reflections, mound-like shapes, and irregular top/bottom interfaces. In conventional log data, MTCs are commonly responded as abrupt shifts at their top/bottom interfaces. In outcrop data, MTCs have several kinds of sedimentary structures, such as massive textures, sliding folds, and mud lumps. Compared with turbidites, MTCs have many distinct characteristics. For example, MTCs are deposited from sediments transported through a "frozen" manner and have an "elongate-fan-like" slope morphology, a relative large thickness. Furthermore, MTCs can be characterized by no obvious features of grading differentiation and relatively large stratigraphic dips.     

显生宙脉型铀矿床成矿理论的几个基本问题

显生宙铀矿地质的一个重要特征就是大量脉型铀矿床(或称热液铀矿床)的发育。本文以中国显生宙脉型铀矿床的研究成果为基础,综合西欧、中欧、苏联和美国同类矿床的资料,概要地阐述了这类矿床的基本地质和地球化学特征,讨论和评述了其成矿理论的几个基本问题。根据对世界主要铀矿区的大地构造背景分析,提出区域性铀源主要来自褶皱带的中心地块和活动大陆边缘基底古老硅铝壳中的富铀地质体,铀的活化和向上部构造层转移的主要因素是深熔作用和酸性岩浆怍用。显生宙热液铀成矿省形成的可能原因在于遭受深熔的部位存在着足够多的富铀地质体。提出了成矿热液形成的可能机制和“双混合”成因模式。强调指出拉张型构造运动和裂陷作用对脉型铀矿床形成的重要作用。     

吉林省区域成矿系列的讨论

本文根据吉林省内各个地史时期地质构造环境、演化规律及成矿特点,划分了10个区域性成矿系列,21个亚系列。同时,分析了各亚系列主要的成矿物质来源、生成顺序、不同成因类型的金属成矿系列的伴生规律,以及隶属这一构造环境控制的成因上有联系的非金属成矿系列。为在省内某一特定成矿地质背景条件下寻找系列矿产提供了依据。