Water quality data for Fall Creek,New York,USA: 1972–1995

The 33 086 ha mixed land use Fall Creek watershed in upstate New York is part of the Great Lakes drainage system. Results from more than 3500 water samples are available in a data set that compiles flow data and measurements of various water quality analytes collected between 1972 and 1995 in all seasons and under all flow regimes in Fall Creek and its tributaries. Data is freely accessible at https://ecommons.cornell.edu/handle/1813/8148 and includes measurements of suspended solids, pH, alkalinity, calcium, magnesium, potassium, sodium, chloride, nitrate nitrogen (NO3-N), sulphate sulphur (SO4-S), phosphorus (P) fractions molybdate reactive P (MRP) and total dissolved P (TDP), percent P in sediment, and ammonium nitrogen (NH4-N). Methods, sub-watershed areas, and coordinates for sampling sites are also included. The work represented in this data set has made important scientific contributions to understanding of hydrological and biogeochemical processes that influence loading in mixed use watersheds and that have an impact on algal productivity in receiving water bodies. In addition, the work has been foundational for important regulatory and management decisions in the region.     

The Upper Devonian Kellwasser event recorded in a regressive sequence from inner shelf to lagoonal pond,Catalan Coastal Ranges,Spain

This study, conducted in the Catalan Coastal Ranges, north‐east Spain, describes the Upper Devonian Kellwasser event in a shallowing‐upward sequence of black shales, siltstones and quartz arenites. This sequence was deposited in a progradational and regressive coastal system where the sedimentary environment evolved from the inner shelf to a lagoonal pond located landward of the shoreline. Three anomalous succeeding steps have been identified by geochemical analysis. The first one, detected on the inner shelf, was characterized by oxygen depletion and high organic productivity. The second, detected in the nearshore, was caused by hydrothermal activity occurring under normal oxic conditions. The third and most intense step was identified in the muds of the lagoonal pond and has been linked to strong anoxic conditions, elevated clastic input derived from changes in the weathering regime at the source area and moderate hydrothermal activity. The Kellwasser event is thus defined in the study area as stepwise and multi‐causal. This is the first time that the Kellwasser event has been identified in a sedimentary environment behind the shoreline. It is also the first time that it has been reported in the Catalan Coastal Ranges.     

Developing constitutive models from EPR‐based self‐learning finite element analysis

A constitutive model that captures the material behavior under a wide range of loading conditions is essential for simulating complex boundary value problems. In recent years, some attempts have been made to develop constitutive models for finite element analysis using self‐learning simulation (SelfSim). Self‐learning simulation is an inverse analysis technique that extracts material behavior from some boundary measurements (eg, load and displacement). In the heart of the self‐learning framework is a neural network which is used to train and develop a constitutive model that represents the material behavior. It is generally known that neural networks suffer from a number of drawbacks. This paper utilizes evolutionary polynomial regression (EPR) in the framework of SelfSim within an automation process which is coded in Matlab environment. EPR is a hybrid data mining technique that uses a combination of a genetic algorithm and the least square method to search for mathematical equations to represent the behavior of a system. Two strategies of material modeling have been considered in the SelfSim‐based finite element analysis. These include a total stress‐strain strategy applied to analysis of a truss structure using synthetic measurement data and an incremental stress‐strain strategy applied to simulation of triaxial tests using experimental data. The results show that effective and accurate constitutive models can be developed from the proposed EPR‐based self‐learning finite element method. The EPR‐based self‐learning FEM can provide accurate predictions to engineering problems. The main advantages of using EPR over neural network are highlighted.     

基于噪声谱比法的内蒙古西部地区台站场地响应研究

利用内蒙古西部12个台站的地脉动噪声数据，采用噪声谱比法研究台站的场地响应情况。分析表明，台站场地响应按曲线形态可分为3类，且可能受地形地貌、局部构造和台基状况等条件影响。对比分析噪声谱比法与Moya方法的场地响应结果发现，场地响应曲线形态基本一致，只有极少数台站存在明显差异。结果表明，内蒙古西部区域大部分台站的台基状况总体较好，场地响应曲线较为平坦，无明显频率放大点。     

莱州湾南岸潍河下游地区咸水入侵灾害成因及特征

通过对莱州湾南岸咸水入侵较严重地潍河下游地区晚更新世以来沉积特征及现代自然环境条件变化的分析，探讨了沉积相对咸水入侵产生及空间范围特征的环境机理。晚更新世以来的三次海平面升降变化造成了潍河下游地区海陆沉积环境交替，形成了巨厚的海陆交互相沉积层。海进时期，大面积的滨海平原被淹没，在近海平原洼地滞留的海水经过蒸发、浓缩变为卤水，成为咸水入侵的物源；海退后陆源碎屑在滨海地区沉积形成了巨厚的古河道砂层。20世纪70年代末期以来，随着对地下淡水的过度开采，淡咸水水头压力差减小．卤水通过古河道砂层快速南侵。通过对潍河下游地区100余个地质钻孔水化学连续监测资料分析，阐明了咸水入侵的特征，有针对性地提出了咸水入侵的防治措施。     

MATLAB在运用系统建模处理南海气象数据过程中应用

介绍了MATLAB语言特点和系统建模方法的基本理论.根据南海气象数据的实际建模处理过程,给出了建模的详细步骤及其MATLAB实现过程以及MATLABTM的主要实现程序.试验讨论和结果表明利用MATLAB语言可以方便地对南海气象数据用系统建模方法进行建模和处理,MATLAB在运用系统建模法处理南海气象数据方面具有明显的优越性.     

平凉隐伏岩溶水环境同位素研究

地下水资源可持续利用的一个急待解决的重要问题,是对地下水补给和更新能力的评价.利用环境同位素技术研究地下水的补给和可更新性是当前较为新颖的方法之一.在西北干旱、半干旱的隐伏岩溶地区,地下水埋藏条件复杂,常规的地质勘探方法所能提供的水文地质信息有限,环境同位素方法在研究地下水的补给及可更新能力方面发挥了优势,可对传统方法进行补充和验证.其结果表明,研究区隐伏岩溶水形成较早,且有大量现代水的混入,平均混入量为54%.说明区内隐伏岩溶水的补给和更新能力较好.环境同位素分析结果还显示,大岔河隐伏岩溶水为一相对独立、半开放的水文地质单元,其补给来源部分为流域内大气降水、地表水的补给,部分为东南部三道沟岩溶地下水的补给;根据环境同位素EPM模型计算,地下水的滞留时间为36 a.地下水储存量为1.314×108 m3; 储水系数为7.29×10-3.这一结果与传统勘探方法的计算结果基本吻合,说明环境同位素方法的实用性.     

Automated analysis of eclipsing binary light curves – II. Statistical analysis of OGLE LMC eclipsing binaries

In the first paper of this series, we presented EBAS – Eclipsing Binary Automated Solver, a new fully automated algorithm to analyse the light curves of eclipsing binaries, based on the ebop code. Here, we apply the new algorithm to the whole sample of 2580 binaries found in the Optical Gravitational Lensing Experiment (OGLE) Large Magellanic Cloud (LMC) photometric survey and derive the orbital elements for 1931 systems. To obtain the statistical properties of the short-period binaries of the LMC, we construct a well-defined subsample of 938 eclipsing binaries with main-sequence B-type primaries. Correcting for observational selection effects, we derive the distributions of the fractional radii of the two components and their sum, the brightness ratios and the periods of the short-period binaries. Somewhat surprisingly, the results are consistent with a flat distribution in log P between 2 and 10 d. We also estimate the total number of binaries in the LMC with the same characteristics, and not only the eclipsing binaries, to be about 5000. This figure leads us to suggest that  (0.7 ± 0.4)  per cent of the main-sequence B-type stars in the LMC are found in binaries with periods shorter than 10 d. This frequency is substantially smaller than the fraction of binaries found by small Galactic radial-velocity surveys of B stars. On the other hand, the binary frequency found by Hubble Space Telescope ( HST ) photometric searches within the late main-sequence stars of 47 Tuc is only slightly higher and still consistent with the frequency we deduced for the B stars in the LMC.