大宁河叶绿素a的因子分值-多元线性回归预测模型研究

自从2003年三峡水库蓄水以后,其支流大宁河水华频发且频率呈上升趋势。叶绿素a(Chla)是指示水体中浮游植物初级生产力的有效指标。采用因子分值-多元线性回归方法研究了大宁河水体11个相关水质因子与Chl a之间的相关关系。因子分析用于简化水质指标之间的相关性,以因子得分（Score values）为自变量用于多元线性回归分析中。结果发现log（Chla）与6个因子分值明显相关,所获得多元线性回归模型为：log(Chl a)=0.579-0191×(Score 1)-0.013×(Score 2)-0.013×(Score 3)+0042×(Score 4)+0134×(Score 5)-0.059×(Score 6),相关系数 R= 0.731、相关系数的平方 R ²=0535,说明自变量可以解释因变量53.5%的差异性。实测数据验证结果表明：该模型能够较好的预测2010年1～10月水体中Chl a浓度的峰值和基本变化趋势     

A GIS-based technique for linking landscape characteristics to non-point source nitrogen export potential: implications for contributing areas management

A Nitrate-N Leaching Index (NLI) is calculated and the results indicate that nitrogen loss in the study area occurs through both leaching and surface runoff. A non-linear regression model of trapping efficiency was combined with a first order decay model to examine the impact of soil characteristics, slope, vegetative cover, land use and distance to streams on the spatial pattern of non-point source nitrogen inputs to streams. The model evaluates the statistical significance of each landscape factor and provides an easy interpretation of the landscape delivery ratio of nitrogen based on a pixel-based characterisation of the watershed. The model was validated by comparing the distributions of the observed and estimated monthly nitrogen concentrations. The exploratory GIS-based method presented here can improve the understanding of the impact of landscape characteristics on nitrate-nitrogen contributing areas and therefore assist watershed management efforts.     

碳基高价银分子晶体电池处理LAS污染源水试验研究

以扬州第四水厂沉淀后的出水作为原水,模拟突发LAS污染,通过投加碳基高价银分子晶体电池进行应急处理的实验研究。实验结果表明：碳基高价银分子晶体电池对LAS的吸附,在30min内能达到81％的吸附容量;碳基高价银分子晶体电池对LAS的吸附,符合Freundlich吸附模式;溶液pH小于5时,吸附效果较好;对进水浓度小于4．75mg／L的LAS污染水样,接触时间在10min以内,便能使出水中LAS的浓度达到生活饮用水0．3mg／L的限值。     

Explorative spatial analysis of traffic accident statistics and road mortality among the provinces of Turkey

Introduction

The aim of the study is to describe the inter-province differences in traffic accidents and mortality on roads of Turkey.

Method

Two different risk indicators were used to evaluate the road safety performance of the provinces in Turkey. These indicators are the ratios between the number of persons killed in road traffic accidents (1) and the number of accidents (2) (nominators) and their exposure to traffic risk (denominator). Population and the number of registered motor vehicles in the provinces were used as denominators individually. Spatial analyses were performed to the mean annual rate of deaths and to the number of fatal accidents that were calculated for the period of 2001-2006. Empirical Bayes smoothing was used to remove background noise from the raw death and accident rates because of the sparsely populated provinces and small number of accident and death rates of provinces. Global and local spatial autocorrelation analyses were performed to show whether the provinces with high rates of deaths-accidents show clustering or are located closer by chance. The spatial distribution of provinces with high rates of deaths and accidents was nonrandom and detected as clustered with significance of P < 0.05 with spatial autocorrelation analyses.

Results

Regions with high concentration of fatal accidents and deaths were located in the provinces that contain the roads connecting the Istanbul, Ankara, and Antalya provinces. Accident and death rates were also modeled with some independent variables such as number of motor vehicles, length of roads, and so forth using geographically weighted regression analysis with forward step-wise elimination. The level of statistical significance was taken as P < 0.05. Large differences were found between the rates of deaths and accidents according to denominators in the provinces. The geographically weighted regression analyses did significantly better predictions for both accident rates and death rates than did ordinary least regressions, as indicated by adjusted R² values. Geographically weighted regression provided values of 0.89-0.99 adjusted R² for death and accident rates, compared with 0.88-0.95, respectively, by ordinary least regressions.

Impact on industry

Geographically weighted regression has the potential to reveal local patterns in the spatial distribution of rates, which would be ignored by the ordinary least regression approach. The application of spatial analysis and modeling of accident statistics and death rates at provincial level in Turkey will help to identification of provinces with outstandingly high accident and death rates. This could help more efficient road safety management in Turkey.     

钢筋混凝土矩形梁在实际火灾下正截面承载力数值计算

为了正确评估钢筋混凝土矩形梁在实际火灾条件下的承载力,以一般室内火灾轰燃后的房间平均温度-时间曲线为火作用,以建筑结构耐火理论为基础,采用数值计算方法研究钢筋混凝土矩形梁的正截面承载力.研究结果表明:梁的承载力随火灾房间温度升高而变小,在温度达到最大值后承载力达到最小值.火灾房间火灾荷载越大,开口因子越小,火作用越大,梁的最小承载力越小;反之相反.相同条件下梁支座截面的承载力要大于跨中截面.     

木材在线性增长热流下着火的复合判据研究

为探索木材在热流变化时的着火特点并提出着火判据,通过试验研究了木材在线性增长热流条件下的自发着火性能,测定了泡桐、椿木、榆木和刺槐4种木材的点燃时间、木材表面的入射热流以及试样内部的温度.结果表明.当热流增长率大于等于0.199kw/(m~2·s)时,试验的所有木材均可以被点燃,点燃这些木材的临界热流增长率介于0.065～0.103 kw/(m~2·s).建立了木材着火的计算模型,计算得出木材自发着火时的表面温度约为500℃.根据试验和计算的结果提出了-结合表面温度和临界热流增长率的木材自发着火复合判据.     

Predicting the Fate and Transport of E. coli in Two Texas River Basins Using a Spatially Referenced Regression Model1

Abstract: The two main rivers of southeast Texas: Guadalupe and San Antonio have shown high temporal increase in bacteria concentration during the last decade. The SPAtially Referenced Regression On Watershed (SPARROW) attributes model, developed by the U.S. Geological Survey (USGS), has been applied to predict the fluxes and concentrations of contaminants in unmonitored streams and to identify the sources of these contaminants. This model identifies every reach as a basic network unit to distribute the sources, delivery, and attenuation factors. The model is data intensive and implements nonlinear regression to solve the parsimonious relations for describing various watershed processes. This study explored watershed and hydrological characteristics (land uses, precipitation, human and animal population, point sources, areal hydraulic load and drainage density, etc.) as the probable sources and delivery mechanisms of waterborne pathogens and their indicator (Escherichia coli [E. coli]) in the Guadalupe and San Antonio River basins. The effect of using various statistical indices for model selection on the final model’s ability to explain the various E. coli sources and transport processes was also analyzed.     

Protection strategies for drinking groundwater sources in small Quebec municipalities

Awareness of groundwater protection has increased substantially in recent decades. In the Province of Quebec, Canada, the Groundwater Catchment Regulation (GWCR) was promulgated in 2002 to protect water quality in public wells. The goal of the present study was to document groundwater protection in the context of emerging regulations and identify factors explaining the propensity of municipalities applying protection strategies. Two types of information were used in this study: data from a questionnaire-based survey conducted among 665 municipalities in the Province of Quebec and complementary information gathered from various sources. Data from the survey revealed that fewer than half of the municipalities have been able to comply with the GWCR, mainly because of financial limitations. Also, close to half of the municipalities have either identified or are expecting land use conflicts to arise between protection areas required by the GWCR and other land usage, with agriculture being the main conflicting activity. Multivariate logistic regression models served to identify factors explaining the likelihood of municipalities to take groundwater protection measures. Those factors were municipality revenue, history of water contamination in distribution systems, land use near wellheads, location of municipalities within a provincial priority watershed and the importance of groundwater use in a region. Results of the study may prove helpful for government authorities in better understanding the groundwater protection issue and in implementing strategies that improve the ability of municipalities to protect groundwater.     

A plea to implement robustness into a breeding goal: poultry as an example

The combination of breeding for increased production and the intensification of housing conditions have resulted in increased occurrence of behavioral, physiological, and immunological disorders. These disorders affect health and welfare of production animals negatively. For future livestock systems, it is important to consider how to manage and breed production animals. In this paper, we will focus on selective breeding of laying hens. Selective breeding should not only be defined in terms of production, but should also include traits related to animal health and welfare. For this we like to introduce the concept of robustness. The concept of robustness includes individual traits of an animal that are relevant for health and welfare. Improving robustness by selective breeding will increase (or restore) the ability of animals to interact successfully with the environment and thereby to make them more able to adapt to an appropriate husbandry system. Application of robustness into a breeding goal will result in animals with improved health and welfare without affecting their integrity. Therefore, in order to be ethically acceptable, selective breeding in animal production should accept robustness as a breeding goal. L. Star, E. D. Ellen contributed equally to this work. Star belongs to the Adaptation Physiology Group, Wageningen University, and the rest of the authors belong to the Animal Breeding and Genomics Centre, Wageningen University.     

洪泽湖藻类与环境因子逐步回归统计和蓝藻水华初步预测

以洪泽湖2008—2010年的连续监测资料为基础,运用多元逐步回归统计方法,选择水温等12项环境因子与藻类叶绿素a等5项生物因子进行逐步回归分析,找出与生物因子显著相关的因子,建立多元逐步回归方程,预测洪泽湖藻类密度的变化情况,初步进行了洪泽湖蓝藻水华的预测预报。结果显示,总磷、总氮、氨氮和水深为洪泽湖藻类密度的显著相关因子,透明度、水温、水深为蓝藻密度的显著相关因子。