Biostratigraphy and depositional facies of the Cretaceous-Tertiary boundary strata in Amakusa-Shimojima,Kyushu, Western Japan

The Upper Himenoura Subgroup exposed in the island of Amakusa-Shimojima, Kyushu, Japan shows an example of the terminal Cretaceous stratigraphic record in the circum Pacific region. This sequence is a part of the Upper Cretaceous intra-arc basins of southwest Japan. Four cycles of upward coarse-graded facies are recognized. Each cycle consists of a basinal mud facies in the lower part and a tide-dominated shallow marine to brackish coarse clastic facies in the upper part. Biostratigraphic correlation chiefly based on ammonites, inocerami and trigoniids indicates that this sequence is Campanian to Maastrichtian in age. The occurrence of the above three fossils decreases upward and is terminated at the top of the sequence, being replaced by a molluscan assemblage similar to the Danian. This suggests that the sedimentation may have continued to the very end of the Cretaceous period and possibly to the beginning of the Tertiary.     

高光谱遥感技术在水环境监测中的应用研究

以黄土高原几类常见土壤为试验品,定量研究了不同泥土含量与水体光谱反射率的关系,探索了利用反射率反演水体深度的方法。文中还介绍了利用高光谱遥感技术分析水污染类型和强度的方法。最后以靖边县城的芦河为例,分析了高光谱遥感探测水污染程度的可行性。     

GIS based landslide susceptibility mapping of Tevankarai Ar sub-watershed, Kodaikkanal, India using binary logistic regression analysis

Landslide susceptibility mapping is the first step in regional hazard management as it helps to understand the spatial distribution of the probability of slope failure in an area.An attempt is made to map the landslide susceptibility in Tevankarai Ar subwatershed,Kodaikkanal,India using binary logistic regression analysis.Geographic Information System is used to prepare the database of the predictor variables and landslide inventory map,which is used to build the spatial model of landslide susceptibility.The model describes the relationship between the dependent variable(presence and absence of landslide) and the independent variables selected for study(predictor variables) by the best fitting function.A forward stepwise logistic regression model using maximum likelihood estimation is used in the regression analysis.An inventory of 84 landslides and cells within a buffer distance of 10m around the landslide is used as the dependent variable.Relief,slope,aspect,plan curvature,profile curvature,land use,soil,topographic wetness index,proximity to roads and proximity to lineaments are taken as independent variables.The constant and the coefficient of the predictor variable retained by the regression model are used to calculate the probability of slope failure and analyze the effect of each predictor variable on landslide occurrence in thestudy area.The model shows that the most significant parameter contributing to landslides is slope.The other significant parameters are profile curvature,soil,road,wetness index and relief.The predictive logistic regression model is validated using temporal validation data-set of known landslide locations and shows an accuracy of 85.29 %.     

影响流域土壤流失的降水量的PPAR(K)预测模型

介绍了投影寻踪自回归（ＰＰＡＲ（Ｋ））的基本思想及其算法。用ＰＰＡＲ（Ｋ）和均生函数（ＭＧＦ）两种方法对泸州市和北碚市降水量的时间序列进行了建模预测。结果表明ＰＰＡＲ（Ｋ）模型具有较高的稳定性和预测精度。     

MECHANISM OF THE HYDROLYSIS OF ADENOSINE 5＇-TRIPHOSPHATE: A REGRESSION ANALYSIS OF KINETIC DATA

Data of the hydrolysis of adenosine 5'-triphosphate have been re-evaluated using a computer program thatnumerically integrates the differential rate equations within a routine that optimizes rate coefficients givena suitable model and concentration versus time data. The model is tested by calculation of Hamilton R-values, the Fisher F-statistic, a sensitivity analysis,the standard errors on the rate coefficients and by constructing contour maps of the objective functionversus two rate coefficients. An optimization using only phosphate concentration data cannot distinguish between a model in whichadenosine 5'-monophosphate is formed predominantly directly with a molecule of pyrophosphate, andone in which it is formed via adenosine 5'-diphosphate. A more accurate set of rate coefficients iscalculated from existing data and the relative importance of the two paths determined.     

塔克拉玛干沙漠地下水矿化度与电导率关系的研究

用数理统计的方法推导水质矿化度与电导率的回归方程, 并绘制其关系曲线。经测定, 新疆塔克拉玛干沙漠84°E沿线水化学类型主要为Cl^-·SO₄^2--Na⁺, 通过推导得出, 25℃情况下, 当电导率为4.5~12ms/cm, 矿化度依电导率的回归方程为: y=-0.3016+0.6936x; 当电导率<5.4ms/cm, y=-0.171+0.6833x, 建立矿化度与电导率的关系后, 测定地下水的电导率, 即可获得待测样的矿化度, 为野外考察或定点观测提供获得地下水矿化度的简便、快速而准确的方法。     

通辽CK－9井水位动态及影响因素的分析

本文在对通辽ＣＫ－９井、水文地质条件和水动态特征初步分析的基础上，采用ＰＣ－１５００计算机，对该井的观测数据与气压、蒸发、降雨、开采、河水位、固体潮、地震波和潜水位等相互关系，进行了定量的相互分析．研究所得结果，对该井水位动态变化和影响因素的关系，提出了新的结论．     

基于分类回归树分析的遥感影像土地利用／覆被分类研究

以专家知识和经验为基础,综合影像光谱信息和其他辅助信息进行分类的基于知识的遥感影像解译方法,是提高遥感影像分类精度,实现自动解译的有效途径之一。然而,知识的获取一直是其得以广泛应用的“瓶颈”问题。以江苏省江宁试验区土地利用/覆被分类为例,利用分类回归树分析(CART)从训练样本数据集中发现分类规则,集成遥感影像的光谱特征、纹理特征和空间分布特征进行分类实验,并与传统的监督分类和逻辑通道分类方法进行比较。结果表明,基于CART的分类方法的精度基本在80%以上,与另两种方法相比,有了较大的提高,而且该算法复杂性低,效率高。由此说明,利用CART算法构建决策树获取的分类规则是合理的。它可以快速、有效地获取大量分类规则,是促进基于知识的遥感影像分类方法在土地利用/覆被分类中广泛应用的一项有效手段。     

A simple prediction model for wall deflection caused by braced excavation in clays

Deep excavations particularly in deep deposits of soft clay can cause excessive ground movements and result in damage to adjacent buildings. Extensive plane strain finite element analyses considering the small strain effect have been carried out to examine the wall deflections for excavations in soft clay deposits supported by retaining walls and bracing. The excavation geometry, soil strength and stiffness properties, and the wall stiffness were varied to study the wall deflection behavior. Based on these results, a simple Polynomial Regression (PR) model was developed for estimating the maximum wall deflection. Wall deflections computed by this method compare favorably with a number of field and published records.     

Response of runoff to climate change in the area of runoff yield in upstream Shiyang River Basin,Northwest China: A case study of the Xiying River

The objective of this study was to analyze the response of runoff in the area of runoff yield of the upstream Shiyang River basin to climate change and to promote sustainable development of regional water resources and ecological environment. As the biggest tributary of the Shiyang River, Xiying River is the only hydrological station (Jiutiaoling) that has provincial natural river and can achieve long time series monitoring data in the basin. The data obtained from this station is representative of natural conditions because it has little human activites. This study built a regression model through identifying the characteristics of runoff and climate change by using Mann-Kendall nonparametric statistical test, cumulative anomaly, and correlation analysis. The results show that the average annual runoff is 320.6 million m³/a with the coefficient of variation of 0.18 and shows slightly decrease during 1956–2020. It has a significant positive correlation the average annual precipitation (P<0.01). Runoff is sensitive to climate change, and the climate has becoming warm and wet and annual runoff has entering wet period from 2003. Compared to the earlier period (1955–2000), the increases of average annual temperature, precipitation and runoff in recent two decades were 15%, 9.3%, and 7.8%, respectively. Runoff in the Shiyang River is affected by temperature and precipitation among climate factors, and the simulation results of the runoff-climate response model (R = 0.0052P ? 0.1589T + 2.373) indicate that higher temperature leads to a weakening of the ecological regulation of surface runoff in the flow-producing area.