尖点突变模型在研究洪水引起环境突变中的应用

以1998年霍林河特大洪水为例，在进行洪水对环境影响作用分析的基础上，将洪水发生的危险系数、地面高程、地形坡度、降雨影响程度、土地盐碱率和草地开垦率6个控制变量划分为两个主分量。由于洪水引起的环境突变可以归纳为一种耦合突变，我们采用尖点突变模型进行求解，得出各主分量的数学表达式和水环境突变区域边界，绘制了该流域环境突变分区图，论证了应用尖点突变模型研究环境突变的合理性。     

基于非概率可靠性的离散变量结构优化设计

目的针对工程结构设计中因材料供应规范限制使得设计变量不能连续取值以及材料性能波动、外界载荷偏差等不确定性问题,探索研究非概率可靠性在离散变量结构优化设计中的应用。方法以桁架结构杆件截面直径为设计变量、结构质量极小化为目标,考虑材料强度极限与外部载荷的不确定性,建立具有非概率可靠性指标约束的离散变量结构可靠性优化模型,并采用遗传算法求解离散变量结构优化设计问题。结果求解获得了三杆、十杆超静定桁架杆件截面直径最优组合,得到的优化结果相较确定性优化结果更具鲁棒性。结论非概率可靠性模型对于解决工程中设计变量具有离散性和不确定性的优化设计问题具有可行性。     

渤海湾大型底栖生物群落结构变化及原因探讨

根据近6年来的渤海湾大型底栖生物群落的资料,以及2011年的现场调查数据,从渤海湾底栖生物群落结构的变化特征出发,分析了其变化的过程和规律.同时结合渤海湾水域近几年来的水动力条件以及营养盐、溶解氧等水质特征变化,探讨底栖生物群落变化的原因.结果表明,渤海湾大型底栖生物的物种数、生物量、丰度、丰富度指数、多样性指数的高值区皆集中分布在海河口北侧离岸较远的海域,而低值区则基本集中分布近岸海域,且呈现由近岸向外海逐渐增加的趋势.渤海湾大型底栖生物群落变化可大体分为3个明显的时间节点:第一个时间节点为2005年和2008年,底栖生物群落无论总物种数、生物量和丰度都较高;第二个时间节点为2009年和2010年,底栖生物群落的上述指标值最低,表明这两年渤海湾受自然变化和人为因素干扰的程度加剧;2011年,由于渤海湾水域的各项强有力的环保措施的实施,底栖生物群落的上述指标值最高,说明其得到一定程度的恢复.渤海湾水域底栖生物群落变化受到该区域的物理因素、化学因素和生物因素的共同影响,变化特征也与各环境因素的变化基本吻合.     

Anaerobic tapered fluidized bed reactor for starch wastewater treatment and modeling using multilayer perceptron neural network

Anaerobic treatability of synthetic sago wastewater was investigated in a laboratory anaerobic tapered fluidized bed reactor(ATFBR) with a mesoporous granular activated carbon(GAC)as a support material.The experimental protocol was defined to examine the effect of the maximum organic loading rate(OLR),hydraulic retention time(HRT),the efficiency of the reactor and to report on its steady- state performance.The reactor was subjected to a steady-state operation over a range of OLR up to 85.44 kg COD/(m~3.d).The COD removal efficiency was found to be 92% in the reactor while the biogas produced in the digester reached 25.38 m~3/(m~3·d) of the reactor. With the increase of OLR from 83.7 kg COD/(m~3.d),the COD removal efficiency decreased.Also an artificial neural network(ANN) model using multilayer perceptron(MLP)has been developed for a system of two input variable and five output dependent variables. For the training of the input-output data,the experimental values obtained have been used.The output parameters predicted have been found to be much closer to the corresponding experimental ones and the model was validated for 30% of the untrained data.The mean square error(MSE)was found to be only 0.0146.     

Integrating Paleobiology,Archeology, and History to Inform Biological Conservation

The search for novel approaches to establishing ecological baselines (reference conditions) is constrained by the fact that most ecological studies span the past few decades, at most, and investigate ecosystems that have been substantially altered by human activities for decades, centuries, or more. Paleobiology, archeology, and history provide historical ecological context for biological conservation, remediation, and restoration. We argue that linking historical ecology explicitly with conservation can help unify related disciplines of conservation paleobiology, conservation archeobiology, and environmental history. Differences in the spatial and temporal resolution and extent (scale) of prehistoric, historic, and modern ecological data remain obstacles to integrating historical ecology and conservation biology, but the prolonged temporal extents of historical ecological data can help establish more complete baselines for restoration, document a historical range of ecological variability, and assist in determining desired future conditions. We used the eastern oyster (Crassostrea virginica) fishery of the Chesapeake Bay (U.S.A.) to demonstrate the utility of historical ecological data for elucidating oyster conservation and the need for an approach to conservation that transcends disciplinary boundaries. Historical ecological studies from the Chesapeake have documented dramatic declines (as much as 99%) in oyster abundance since the early to mid‐1800s, changes in oyster size in response to different nutrient levels from the sixteenth to nineteenth centuries, and substantial reductions in oyster accretion rates (from 10 mm/year to effectively 0 mm/year) from the Late Holocene to modern times. Better integration of different historical ecological data sets and increased collaboration between paleobiologists, geologists, archeologists, environmental historians, and ecologists to create standardized research designs and methodologies will help unify prehistoric, historic, and modern time perspectives on biological conservation. Integración de Paleobiología, Arqueología e Historia para Informar a la Biología de la Conservación     

事故致因的突变模型

在众多论述伤亡事故致因的理论中，都没有解释为何系统元素的连续变化引起系统状态的突变（事故），以及人、物因素在这种突变过程中的作用。本文引入突变理论这一数学工具，指出系统内某些元素的连续变化导致系统状态的突然改变，较好地解决了这个问题，通过建立事故致因突变模型，提出了提高系统安全性的原则。     

活性污泥1#数学模型(ASM1)中的组分

活性污泥l#数学模型(AMl)常常用于预测污水处理厂中的生物过程。活性污泥数学模型组分的鉴定对活性污泥l#数学模型的应用具有重要的意义。本文描述了在活性污泥l#模型(ASMl)中污水组分的概念,以及组分鉴定的研究现状。     

Goals and remedial strategies for water quality and wildlife management in a coastal lagoon--a case-study of Ringkøbing Fjord, Denmark

The aim of this work is (1) to discuss approaches and tools to set management goals using operational indicators for coastal management (i.e., indicators that are easy to measure, understand and predict) and validated predictive models and (2) to discuss remedial strategies for sustainable coastal management regarding water quality and the abundance of fish, waterfowl and large aquatic plants. These approaches are exemplified using data from Ringkøbing Fjord, Denmark, which has undergone two major regime shifts during the last decades. This work discusses the changes taken place during the period from 1980 to 2004 (when there are good empirical data). For Ringkøbing Fjord, which is a very shallow, well-oxygenated lagoon dominated by resuspension processes, we have targeted on the following operational indicators, which are meant to reflect seasonal median values for the entire defined coastal area (the ecosystem scale) and not conditions at individual sites or data from shorter time periods: Secchi depth (as a standard measure of water clarity) and chlorophyll-a concentrations (as a key measure of algal biomass). The operational indicators are regulated by a set of standard abiotic factors, such as salinity, suspended particulate matter (SPM), nutrient concentrations (N and P), coastal morphometry and water exchange. Such relationships are quantified using well-tested, general quantitative models, which illustrate how these indicators are interrelated and how they reflect fundamental aspects of coastal ecosystems. We demonstrate that the regime shift in the lagoon can be modelled and quantitatively explained and is related to changes in salinity and nutrient inflow. A very important threshold is linked to increased salinities in the lagoon. For example, when the mean annual salinity is higher than about 9.5‰, large numbers of saltwater species of clams can survive and influence the structure and function of the ecosystem in profound ways. The model also illustrates the dynamic response to changes in nutrient loading. We have presented several management strategies with the goal of keeping the Secchi depth at 2 m, which would stimulate the growth of higher aquatic plants, which are fundamental for fish production and bird abundance in the lagoon. Given the fact that the Secchi depth depends on many variable factors (temperature, TP-inflow from land, salinity, changes in biomasses of macrophytes and clams, which are accounted for in these simulations), our results indicate that in practice it will likely be very difficult to reach that goal. However, it would be realistic to maintain a Secchi depth of 1.5 m if the variability in salinity is minimized and the mean salinity is kept at about 10.2‰.     

Environmental risk perception, environmental concern and propensity to participate in organic farming programmes

This paper aims to identify the factors underlying farmers' propensity to participate in organic farming programmes in a Romanian rural region that confronts non-point source pollution. For this, we employ structural equation modelling with latent variables using a specific data set collected through an agri-environmental farm survey in 2001. The model includes one 'behavioural intention' latent variable ('propensity to participate in organic farming programmes') and five 'attitude' and 'socio-economic' latent variables ('socio-demographic characteristics', 'economic characteristics', 'agri-environmental information access', 'environmental risk perception' and 'general environmental concern'). The results indicate that, overall, the model has an adequate fit to the data. All loadings are statistically significant, supporting the theoretical basis for assignment of indicators for each latent variable. The significance tests for the structural model parameters show 'environmental risk perception' as the strongest determinant of farmers' propensity to participate in organic farming programmes.     

基于裂区设计的大气能见度拟合及预测模型

通过收集分析广州能见度及影响因子数据的特征,使用R-project统计软件作为建模工具,采用多层裂区实验构建模型基本框架,选择影响显著的因子进行变量变形处理,对年、月、日、小时的数据特征进行层层分割设计,并在对应层次引入代表时间含义的虚拟变量以提高模型的表征水平,加入二次项、交叉项等提高模型的精度,得到拟合度高、适用性强的能见度拟合及预测模型。