民间信仰载体的地域格局及其影响因素——以兰州市榆中县祠庙文化为例

以祠庙祭祀为主体且祠庙保存良好的民间信仰是甘肃陇中地区民间文化的重要组成。甘肃陇中地区的民间信仰具有很强的趋同性，本文以陇中地区的榆中县为例，以各村的祠庙为民间文化载体，通过核密度分析、Logistic回归等方法探讨榆中县民间文化载体的空间分布及其影响因素对于探讨陇中地区人地关系，保护和弘扬民俗文化有着重要意义。研究结果表明：（1）根据已有研究将榆中县民间信仰归纳为山神信仰、水神信仰、天地信仰、女性信仰、英雄崇拜和祖先崇拜，祖先崇拜的祠庙数量占有重要地位；（2）榆中县祠庙主要分布在西北黄河南岸、中部陇海铁路沿线及南部风景名胜集聚区，村级层面空间差异不显著、乡镇空间差异相对较大。通过核密度分析，不同类别民间信仰空间分布热点各有不同；（3）榆中县民间信仰空间分布受到区位条件限制，民间信仰的祠庙多位于海拔高度较低、人口密度较大、交通可达性较好的地区，坡度和到水源的距离成为山神信仰和水神信仰祠庙空间分布显著的影响因子，榆中县祠庙呈现出山神信仰类祠庙“依山”，水神信仰类祠庙“傍水”的空间特点。     

典型深街谷内树木空间配置对行人呼吸高度处气流的影响

为揭示树木的不同空间配植方案对行人呼吸高度气流的影响,本文将树木视为均匀多孔介质,通过附加源项法从空气动力学角度用CFD模拟了H/W=2的典型深街谷几何内4种树木配植情景,实验表明,不同空间配置下树木对街谷内行人呼吸高度处局地气流的影响强弱在空间分布模式上差异悬殊：① 均匀种植的树木对街谷内行人呼吸高度的气流起到阻碍作用,不均匀种植则有效提升街谷的整体流速。4种空间配植方案下树木对气流的影响程度不同,阻碍作用从大到小的顺序为均匀间距8 m（Spa8m）>均匀间距6 m（Spa6m）>均匀间距20 m（Spa20m）>不均匀配植（Non-uniform）;对应的平均气流增强指标顺序为$\bar{D}_{spa8}$（-19.31%）<$\bar{D}_{spa6}$（-16.14%）<$\bar{D}_{spa20}$（-10.73%）<$\bar{D}_{non-uniform}$（1.25%）。② 对比不均匀和均匀的种植方案,不均匀植树的街谷内部行人呼吸高度的气流流速比其对照案例（均匀植树Spa8m方案）整体增强了106.49%。街谷中部不种树,在街谷两端配置树木并预留足够的自由空间的不均匀植树方案,能够让角涡渗入街谷中部,促使街谷内部的垂直漩涡和两端的水平角涡运动,增强湍流和垂直交换,有效减少了街道两端“风口效应”和街道中部“风影效应”的区域,改善了整个街谷行人呼吸平面的风环境。④ 合理空间配置的树木能够改善街谷内部的行人风环境。街谷内行人呼吸高度处的气流对局地条件很敏感,树木的局部配置（空间簇集、密度）将引起强烈的空间变化。在既有城市建筑布局条件下,如何通过谨慎的景观设计,利用树木等城市绿化措施有效地改善城市的行人风环境,缓解污染扩散、疾病传播等问题,本文的方法可提供一定的参考。     

广西土壤有机质空间变异特征及其影响因素研究

基于广西第二次土壤普查的270个土壤剖面资料,结合1∶50万数字化土壤类型图、土地利用类型图和气象监测数据等资料,利用地统计学和逐步回归分析等方法对广西表层土壤有机质空间变异特征及其影响因素进行了探究。结果表明：广西表层土壤有机质平均含量为3.11±2.19%,变异系数为70.72%,空间分布呈北高南低的趋势。广西表层土壤有机质空间分布受到自然和人为因素的共同影响,土壤类型、成土母质、海拔、土地利用、气候和坡度6个环境因子对全区土壤有机质含量变异的综合解释能力为47.9%。其中,土壤类型是最重要的影响因素,能独立解释其变异的36.0%,海拔和成土母质分别能独立解释28.5%和15.8%。气温对广西土壤有机质空间分布的影响比降水量更加显著,从而造成了广西土壤有机质整体呈南低北高的趋势。同时,土壤有机质对气温的敏感性在一定程度上受到降雨量的制约。此外,研究区农业耕作管理等因素对土壤有机质的影响也不容忽视。     

利用高光谱数据进行植被生化成分反演方法研究

高光谱数据包含着丰富光谱信息,能够定量地分析物质成分^[1]。由高光谱数据,可以运用多元逐步线性回归方法反演植被生化组分含量,从而达到监测植被生长状况的目的^[2]。本文具体介绍了多元逐步线性回归方法,及其在氮、木质素和纤维素含量估算中的应用。     

REVIEWS OF GEOGRAPHIC SOFTWARE

Reviews of geographic software in this article: DEMO-GRAPHICS: WORLD POPULATIONS AND PROJECTIONS. ESP GAUSS. CEMODEL S. Damus LIMDEP. William H. Greene MICROSTAT 4.1 OTIS PCIPS. (Personal Computer Image Processing System) . H.J. Meyers and R. Bernstein. REGRESSION ANALYSIS OF TIME SERIES (RATS) SPSS/PC+ URBAN DATA MANAGEMENT SOFTWARE (UDMS)     

Distribution and fluxes of metals in the St. Lawrence River from the outflow of Lake Ontario to Québec City

Six anchor stations in the St. Lawrence River from the outflow of Lake Ontario to Quebec City, were occupied for ca. 24 hours in June 1987 during low flow conditions. Samples of water and suspended particulate matter were separated by continuous-flow centrifugation, and were collected every two hours.During this sampling period, fluxes of dissolved forms of zinc, copper and nickel increased in Lac St. François and downstream relative to the sum of the fluxes for the two upstream stations at the outflow of Lake Ontario. Increases in the flux of dissolved zinc and copper were pronounced below Montreal and above Lac St. Pierre. For particulate forms of metals, all five metals show that there are significant inputs in the section of the St. Lawrence River between Lac St. François and the station just above the entrance to Lac St. Pierre.The average concentrations of dissolved cadmium, lead, zinc, copper and nickel ranged from 7–23 ng/l; 9–35 ng/l; 0.434–0.939 g/l; 0.15–0.89 g/l and 0.58–1.12 g/l respectively.Regression analysis of the dissolved and particulate metal concentrations suggests that the concentration of dissolved cadmium, lead, zinc and nickel can be predicted from the regression equation and the determination of particulate metal concentration. This prediction appears to be independent of the suspended particulate matter concentration which varies from ca. 1 to 10 mg/l from the outflow of Lake Ontario to Québec City.     

Doline probability map using logistic regression and GIS technology in the central Ebro Basin (Spain)

In the surroundings of Zaragoza, karstification processes are especially intense in covered karst areas where fluvial terraces lie directly on Tertiary evaporites. Since the beginning of Quaternary, these processes have lead to the development of collapse and subsidence dolines with a wide range of sizes, which have significant economic impacts. To reduce economic impact and increase safety, a regional analysis of this phenomenon is needed for spatial management. Therefore, a probability map of dolines was developed using logistic regression and geographic information system (GIS) techniques. This paper covers the selection of input data, manipulation of data using the GIS technology, and the use of logistic regression to generate a doline probability map. The primary variable in the doline development in this area is geomorphology, represented by the location of endorheic areas and different terrace levels. Secondary variables are the presence of irrigation and the water table gradient.     

A new method of estimating the ratio between in situ rock stresses and tectonics based on empirical and probabilistic analyses

This paper describes a new procedure for assessing the ratio between in situ stresses in rock masses by means of K (K = σ_H / σ_v, being σ_H and σ_v principal stress) and tectonics for purposes of engineering geology and rock mechanics. The method combines the use of the logic decision tree and the empirical relationship between the Tectonic Stress Index, TSI, and a series of K in situ values obtained from an extensive database. The decision tree considers geological and geophysical factors affecting stress magnitudes both on the regional and local scale. The TSI index is defined by geological and geomechanical parameters. The method proposed provides an assessment of the magnitude of horizontal stresses of tectonic origin. Results for several regions of Europe are presented and the possible applications of the procedure are discussed.     

Rain-induced debris and mudflow triggering factors assessment in the Santiago cordilleran foothills,Central Chile

Debris and mudflows are some of the main geological hazards in the mountain foothills of the Chilean capital city of Santiago. There, the risk of flows triggered in the basins of ravines that drain the range into the city increases with time due to the city growth. A multivariate statistical study based on the logistic regression method is presented. The model provides equations that allow the computation of combined meteorological triggering factors associated with a probability of rain-induced flow occurrence. Daily rainfall, accumulated rainfall and the snowfall level, traditionally considered as the relevant factors, are analysed for a 25-year period. The results show a strong relevance of the rainfall on the day of the flow event over the other factors. However, the relatively low probabilities returned for some real flow events suggest that the model does not capture all the significant variables and the problem is more complex than as it has been traditionally assumed, and further investigations are needed to develop predictive models of flow triggering.     

Prediction of local scour around circular piles under waves using a novel artificial intelligence approach

Abstract

The scour phenomena around vertical piles in oceans and under waves may influence the structure stability. Therefore, accurately predicting the scour depth is an important task in the design of piles. Empirical approaches often do not provide the required accuracy compared with data mining methods for modeling such complex processes. The main objective of this study is to develop three data-driven methods, locally weighted linear regression (LWLR), support vector machine (SVR), and multivariate linear regression (MLR) to predict the scour depth around vertical piles due to waves in a sand bed. It is the first effort to develop the LWLR to predict scour depth around vertical piles. The models simulate the scour depth mainly based on Shields parameter, pile Reynolds number, grain Reynolds number, Keulegan–Carpenter number, and sediment number. 111 laboratory datasets, derived from several experimental studies, were used for the modeling. The results indicated that the LWLR provided highly accurate predictions of the scour depths around piles (R?=?0.939 and RMSE = 0.075). Overall, this study demonstrated that the LWLR can be used as a valuable tool to predict the wave-induced scour around piles.