基于Petri网的铁路车站安全防护系统建模及可靠性分析

采用单一的随机Petri网对车站线路结构、列车运行过程及车站防护系统建模,基于欧洲电工标准委员会定义的安全目标,确定车站安全防护系统的可靠性需求。对无防护系统的列车入站进行建模和分析,然后基于防护系统功能及可靠性特性,结合列车入站动态特性,对防护系统的功能和可靠性进行建模,并根据安全目标与车站事故率之间的数学关系进行系统的安全分析和可用性分析。其结果表明,车站防护系统的可靠性与乘客的个人风险存在着定量的关系,从而可以依据个人风险的标准来确定防护系统可靠性需求。     

Another avenue of action: an examination of climate change countermovement industries’ use of PAC donations and their relationship to Congressional voting over time

The political mobilization of American business elites in the 1970s and 1980s has been well studied by political scientists. Environmental sociologists have explored how industries in this elite countermovement have organized to prevent environmental legislation. The literature often focuses on the efforts of this movement to shape public opinion on climate change. However, political scientists argue business elites are running several parallel strategies simultaneously in order to protect their interests. FEC data are utilized in multilevel logit models to examine how donations from industrial Political Action Committees (PACs) relate to Congressional representative’s environmental voting behavior over a 20-year period. Industries associated with the environmental countermovement have increasingly used PAC donations over time, and every additional $10,000 a representative received from countermovement industries significantly decreased odds of their taking the pro-environmental stance even when controlling for representatives’ demographics, districts, Congressional polarization and time-period.     

Free market ideology and deregulation in Colorado’s oil fields: Evidence for triple movement activism?

Unconventional oil and gas extraction (UOGE) has spurred an unprecedented boom in onshore production in the US. Despite a surge in related research, a void exists regarding inquiries into policy outcomes and perceptions. To address this, support for federal regulatory exemptions for UOGE is examined using survey data collected in 2015 from two Northern Colorado communities. Current regulatory exemptions for UOGE can be understood as components of broader societal processes of neoliberalization. Free market ideology increases public support for federal regulatory exemptions for UOGE. Perceived negative impacts do not necessarily drive people to support increased federal regulation. Utilizing neo-Polanyian theory, interaction between free market ideology and perceived negative impacts is explored. Free market ideology appears to moderate people’s views of regulation: increasing the effect of perceived negative impacts while simultaneously increasing support for deregulation. To conclude, the ways in which free market ideology might normalize the impacts of UOGE activity are discussed.     

Why does the United States lack a global warming policy? The corporate inner circle versus public interest sector elites

Why has the United States not adopted global warming policies? Because the inner circle of the corporate elite has opposed these policies despite some corporate support for cap-and-trade and other policies. Pro- and anti-positions taken by think tanks that have led the policy debate in the post-Kyoto period are analyzed in order to demonstrate this. The corporate and upper class social ties of the directors of these pro- and anti-think tanks are examined, revealing a corporate elite split between the inner circle opposing these policies, and a ‘public interest sector’ of corporate law and media corporations along with top executives from higher education and other nonprofits that is supportive of policies addressing global warming. To enable adoption of major global warming policies, the corporate inner circle will need to become supportive and forge a class-wide corporate consensus on the need to address global warming.     

基于机器视觉的鱼类行为特征提取与分析

近年来,水污染问题备受关注。生物式水质监测成为目前国家环境保护工作的重要任务之一。为准确监测水质污染情况,本文以青鳉鱼(Oryzias latipes)为研究对象,采用非接触式的机器视觉监测技术,提取青鳉鱼的生理特征(呼吸频率)和运动特征(胸鳍和尾鳍的摆动频率),并分析这些特征与水质之间的关系。本文采用支持向量机(Support Vector Machine,SVM)准确提取鱼鳃,并根据鱼鳃呼吸面积大小变化计算出鱼的呼吸频率。基于形态学细化算法提取青鳉鱼骨架,求出胸鳍和尾鳍的摆动频率。结果显示:不同浓度铜离子暴露实验测得的青鳉鱼生理特征和运动特征与实际情况一致;通过对不同铜离子浓度下的毒性实验数据对比,发现了青鳉鱼的生理特征和运动特征会随不同的铜离子浓度发生相应变化,可以作为水质监测的评价标准。     

Comparison of Stream Invertebrate Response Models for Bioassessment Metrics1

Waite, Ian R., Jonathan G. Kennen, Jason T. May, Larry R. Brown, Thomas F. Cuffney, Kimberly A. Jones, and James L. Orlando, 2012. Comparison of Stream Invertebrate Response Models for Bioassessment Metrics. Journal of the American Water Resources Association (JAWRA) 48(3): 570-583. DOI: 10.1111/j.1752-1688.2011.00632.x Abstract: We aggregated invertebrate data from various sources to assemble data for modeling in two ecoregions in Oregon and one in California. Our goal was to compare the performance of models developed using multiple linear regression (MLR) techniques with models developed using three relatively new techniques: classification and regression trees (CART), random forest (RF), and boosted regression trees (BRT). We used tolerance of taxa based on richness (RICHTOL) and ratio of observed to expected taxa (O/E) as response variables and land use/land cover as explanatory variables. Responses were generally linear; therefore, there was little improvement to the MLR models when compared to models using CART and RF. In general, the four modeling techniques (MLR, CART, RF, and BRT) consistently selected the same primary explanatory variables for each region. However, results from the BRT models showed significant improvement over the MLR models for each region; increases in R² from 0.09 to 0.20. The O/E metric that was derived from models specifically calibrated for Oregon consistently had lower R² values than RICHTOL for the two regions tested. Modeled O/E R² values were between 0.06 and 0.10 lower for each of the four modeling methods applied in the Willamette Valley and were between 0.19 and 0.36 points lower for the Blue Mountains. As a result, BRT models may indeed represent a good alternative to MLR for modeling species distribution relative to environmental variables.     

Watershed Regressions for Pesticides (warp) Models for Predicting Atrazine Concentrations in Corn Belt Streams1

Stone, Wesley W. and Robert J. Gilliom, 2012. Watershed Regressions for Pesticides (WARP) Models for Predicting Atrazine Concentrations in Corn Belt Streams. Journal of the American Water Resources Association (JAWRA) 48(5): 970‐986. DOI: 10.1111/j.1752‐1688.2012.00661.x Abstract: Watershed Regressions for Pesticides (WARP) models, previously developed for atrazine at the national scale, are improved for application to the United States (U.S.) Corn Belt region by developing region‐specific models that include watershed characteristics that are influential in predicting atrazine concentration statistics within the Corn Belt. WARP models for the Corn Belt (WARP‐CB) were developed for annual maximum moving‐average (14‐, 21‐, 30‐, 60‐, and 90‐day durations) and annual 95th‐percentile atrazine concentrations in streams of the Corn Belt region. The WARP‐CB models accounted for 53 to 62% of the variability in the various concentration statistics among the model‐development sites. Model predictions were within a factor of 5 of the observed concentration statistic for over 90% of the model‐development sites. The WARP‐CB residuals and uncertainty are lower than those of the National WARP model for the same sites. Although atrazine‐use intensity is the most important explanatory variable in the National WARP models, it is not a significant variable in the WARP‐CB models. The WARP‐CB models provide improved predictions for Corn Belt streams draining watersheds with atrazine‐use intensities of 17 kg/km² of watershed area or greater.     

Modeling urban films using a dynamic multimedia fugacity model

A thin film coats impervious urban surfaces that can act as a source or sink of organic pollutants to the greater environment. We review recent developments in the understanding of film and film-associated pollutant behavior and incorporate them into an unsteady-state version of the fugacity based Multimedia Urban Model (MUM), focusing on detailed considerations of surface film dynamics. The model is used to explore the conditions under which these atmospherically-derived films act as a temporary source of chemicals to the air and/or storm water. Assuming film growth of 2.1 nm d⁻¹ (Wu et al., 2008a), PCB congeners 28 and 180 reach air-film equilibrium within hours and days, respectively. The model results suggest that the film acts as a temporary sink of chemicals from air during dry and cool weather, as a source to air in warmer weather, and as a source to storm water and soil during rain events. Using the downtown area of the City of Toronto Canada, as a case study, the model estimates that nearly 1 g d⁻¹ of ∑₅PCBs are transferred from air to film to storm water.     

Multimedia fate modeling and comparative impact on freshwater ecosystems of pharmaceuticals from biosolids-amended soils

This study modeled the impact on freshwater ecosystems of pharmaceuticals detected in biosolids following application on agricultural soils. The detected sulfonamides and hydrochlorothiazide displayed comparatively moderate retention in solid matrices and, therefore, higher transfer fractions from biosolids to the freshwater compartment. However, the residence times of these pharmaceuticals in freshwater were estimated to be short due to abiotic degradation processes. The non-steroidal anti-inflammatory mefenamic acid had the highest environmental impact on aquatic ecosystems and warrants further investigation. The estimation of the solid-water partitioning coefficient was generally the most influential parameter of the probabilistic comparative impact assessment. These results and the modeling approach used in this study serve to prioritize pharmaceuticals in the research effort to assess the risks and the environmental impacts on aquatic biota of these emerging pollutants.     

Assisting Australian indigenous resource management and sustainable utilization of species through the use of GIS and environmental modeling techniques

Information on distribution and relative abundance of species is integral to sustainable management, especially if they are to be harvested for subsistence or commerce. In northern Australia, natural landscapes are vast, centers of population few, access is difficult, and Aboriginal resource centers and communities have limited funds and infrastructure. Consequently defining distribution and relative abundance by comprehensive ground survey is difficult and expensive. This highlights the need for simple, cheap, automated methodologies to predict the distribution of species in use, or having potential for use, in commercial enterprise. The technique applied here uses a Geographic Information System (GIS) to make predictions of probability of occurrence using an inductive modeling technique based on Bayes' theorem. The study area is in the Maningrida region, central Arnhem Land, in the Northern Territory, Australia. The species examined, Cycas arnhemica and Brachychiton diversifolius, are currently being 'wild harvested' in commercial trials, involving sale of decorative plants and use as carving wood, respectively. This study involved limited and relatively simple ground surveys requiring approximately 7 days of effort for each species. The overall model performance was evaluated using Cohen's kappa statistics. The predictive ability of the model for C. arnhemica was classified as moderate and for B. diversifolius as fair. The difference in model performance can be attributed to the pattern of distribution of these species. C. arnhemica tends to occur in a clumped distribution due to relatively short distance dispersal of its large seeds and vegetative growth from long-lived rhizomes, while B. diversifolius seeds are smaller and more widely dispersed across the landscape. The output from analysis predicts trends in species distribution that are consistent with independent on-site sampling for each species and therefore should prove useful in gauging the extent of resource availability. However, some caution needs to be applied as the models tend to over predict presence which is a function of distribution patterns and of other variables operating in the landscape such as fire histories which were not included in the model due to limited availability of data.