Using the ECLPSS software environment to build a spatially explicit component-based model of ozone effects on forest ecosystems

We have developed a modeling framework to support grid-based simulation of ecosystems at multiple spatial scales, the Ecological Component Library for Parallel Spatial Simulation (ECLPSS). ECLPSS helps ecologists to build robust spatially explicit simulations of ecological processes by providing a growing library of reusable interchangeable components and automating many modeling tasks. To build a model, a user selects components from the library, and then writes new components as needed. Some of these components represent specific ecological processes, such as how environmental factors influence the growth of individual trees. Other components provide simulation support such as reading and writing files in various formats to allow inter-operability with other software. The framework manages components and variables, the order of operations, and spatial interactions. The framework provides only simulation support; it does not include ecological functions or assumptions. This separation allows biologists to build models without becoming computer scientists, while computer scientists can improve the framework without becoming ecologists. The framework is designed to operate on multiple platforms and be used across networks via a World Wide Web-based user interface. ECLPSS is designed for use with both single processor computers for small models, and multiple processors in order to simulate large regions with complex interactions among many individuals or ecological compartments. To test Version 1.0 of ECLPSS, we created a model to evaluate the effect of tropospheric ozone on forest ecosystem dynamics. This model is a reduced-form version of two existing models: , which represents an individual tree, and , which represents forest stand growth and succession. This model demonstrates key features of ECLPSS, such as the ability to examine the effects of cell size and model structure on model predictions.     

An analysis of motorcycle injury and vehicle damage severity using ordered probit models

Problem: Motorcycles constitute about 19% of all motorized vehicles in Singapore and are generally overrepresented in traffic accidents, accounting for 40% of total fatalities. Method: In this paper, an ordered probit model is used to examine factors that affect the injury severity of motorcycle accidents and the severity of damage to the vehicle for those crashes. Nine years of motorcycle accident data were obtained for Singapore through police reports. These data included categorical assessments of the severity of accidents based on three levels. Damage severity to the vehicle was also assessed and categorized into four levels. Categorical data of this type are best analyzed using ordered probit models because they require no assumptions regarding the ordinality of the dependent variable, which in this case is the severity score. Various models are examined to determine what factors are related to increased injury and damage severity of motorcycle accidents. Results: Factors found to lead to increases in the probability of severe injuries include the motorcyclist having non-Singaporean nationality, increased engine capacity, headlight not turned on during daytime, collisions with pedestrians and stationary objects, driving during early morning hours, having a pillion passenger, and when the motorcyclist is determined to be at fault for the accident. Factors leading to increased probability of vehicle damage include some similar factors but also show some differences, such as less damage associated with pedestrian collisions and with female drivers. In addition, it was also found that both injury severity and vehicle damage severity levels are decreasing over time.     

Quantitative Assessment of Agricultural Runoff and Soil Erosion Using Mathematical Modeling: Applications in the Mediterranean Region

Three mathematical models, the runoff curve number equation, the universal soil loss equation, and the mass response functions, were evaluated for predicting nonpoint source nutrient loading from agricultural watersheds of the Mediterranean region. These methodologies were applied to a catchment, the gulf of Gera Basin, that is a typical terrestrial ecosystem of the islands of the Aegean archipelago. The calibration of the model parameters was based on data from experimental plots from which edge-of-field losses of sediment, water runoff, and nutrients were measured. Special emphasis was given to the transport of dissolved and solid-phase nutrients from their sources in the farmers' fields to the outlet of the watershed in order to estimate respective attenuation rates. It was found that nonpoint nutrient loading due to surface losses was high during winter, the contribution being between 50% and 80% of the total annual nutrient losses from the terrestrial ecosystem. The good fit between simulated and experimental data supports the view that these modeling procedures should be considered as reliable and effective methodological tools in Mediterranean areas for evaluating potential control measures, such as management practices for soil and water conservation and changes in land uses, aimed at diminishing soil loss and nutrient delivery to surface waters. Furthermore, the modifications of the general mathematical formulations and the experimental values of the model parameters provided by the study can be used in further application of these methodologies in watersheds with similar characteristics.     

开发基于GIS的城市防震减灾信息系统 --组件对象模型的应用

应用GIS建立城市防震成灾信息系统是一条减轻城市地震灾害的有效途径,而现有的城市防震减灾信息系统中防震减灾专业模型与GIS功能结合不够紧密,因此加强对地震灾害智能计算的研究十分重要。文章分析了城市防震成灾信息系统常用的二次开发方法,阐述了组件对象模型(COM)技术及其在系统开发中的应用方法,论述了应用COM技术开发系统的界面与功能等。     

A model testing study for the transfer of radioactivity to fruit

This paper compares predictions of the foodchain model SPADE with experimental data for the transfer of (134)Cs and (85)Sr to strawberry plants following acute foliar and soil contamination. The transfer pathways considered in this exercise included direct deposition to fruit, leaf-to-fruit, soil-to-leaf and soil-to-fruit transfers. Following foliar contamination, the difference between predicted and measured radionuclide activity values varied between a factor of 0.5-10 for fruit and 4.5-7 for leaf. Following soil contamination, the difference between predicted and measured values varied between a factor of 3-74 for fruit and 32-44 for leaf. In all cases the difference between measured and predicted values was smaller for (85)Sr than (134)Cs. Measured and predicted activities were higher for leaf than fruit. Both measured and predicted (134)Cs concentrations in fruit and leaf are higher when deposition occurs at ripening than at anthesis. These results confirm the need for more data on fruit, even for Cs and Sr, to support models in predicting the transfer of radionuclides to fruit crops. Ongoing research projects funded by the UK Food Standards Agency aim to provide some data on radionuclide transfer to herbaceous, shrub and tree fruits, which will help improve radiological assessment models in order to provide better protection for consumers.     

青藏铁路列车运行控制系统的安全性分析

分析了青藏铁路中多种不利因素对轨道电路参数的影响 ;提出了在青藏铁路不宜采用现行基于轨道电路的列车运行控制系统 ,而应选择基于通信的列车运行控制系统的理由 ;给出了系统的基本结构及提高系统可靠性的措施 ;与此同时 ,就人们关心的无线传输列车控制数据的可靠性和安全性难题 ,通过建立马尔可夫模型的方法进行了分析     

乡村旅游与社区经济互动持续发展评估研究——以安徽省黟县西递为例

在实地调查和与专家访谈的基础上设计函调问卷,通过对函调问卷的综合分析,构建模糊评价模型,对西递旅游与社区经济互动持续发展水平做出评判。结果表明,西递旅游与社区经济处在基本可持续发展阶段,但也存在着一些制约旅游与社区经济互动持续发展的因素。在此基础上,提出促进西递旅游与社区经济互动持续发展的建议和措施。     

组合优化的能源消费量预测模型

针对非等间距灰色系统预测中存在误差较大的问题，结合序列本身的特点，利用世界能源消费的历史数据，采用3种灰色预测模型与神经网络进行组合优化，建立了灰色神经网络的能源消费量组合预测模型。实证分析结果表明，提高了模型的拟合和预测精度，拓宽了应用范围。该模型可对能源的消费趋势进行预测，为科学分析能源结构提供依据。     

国内外油田含油污泥处理技术

通过对国内外各种含油污泥处理工艺技术的调查分析和对比,提出了适合国内实际的含油污泥处理技术方案。以离心分离技术为核心,辅之以调质、倾析等多种预处理技术和高温裂解、生物处理等后续处理技术的污泥综合处理工艺,适于我国现阶段的含油污泥处理。     

BEL型双维振打式电除尘器的研发

文章介绍了一种顶打和侧打相结合的BEL型双维振打式电除尘器，该产品将电除尘器两种主要的振打清灰技术结合，适用于老除尘器的提效改造及新除尘器的制造等。