以Hartwick准则破解“资源的诅咒”

一些资源禀赋较高的国家或地区,一直以来经济社会发展未充分享受自然资源带来的红利,甚至陷入贫困和动荡,这一现象被称作"资源的诅咒";在我国,也有不少资源型城市在发展过程中由于资源的耗竭而陷入困境。经济学家Hartwick对资源枯竭区域发展进行了深入研究,并提出"Hartwick准则"对这一类区域的发展进行了理论指导。本文对Hartwick准则进行简要介绍,以这一准则在非洲国家博茨瓦纳的钻石开发中的应用进行分析,并依据理论和经验,对我国一些资源型区域的发展提出建议。     

Rough Set Rule Induction for Suitability Assessment

The data that characterize an environmental system are a fundamental part of an environmental decision-support system. However, obtaining complete and consistent data sets for regional studies can be difficult. Data sets are often available only for small study areas within the region, whereas the data themselves contain uncertainty because of system complexity, differences in methodology, or data collection errors. This paper presents rough-set rule induction as one way to deal with data uncertainty while creating predictive if–then rules that generalize data values to the entire region. The approach is illustrated by determining the crop suitability of 14 crops for the agricultural soils of the Willamette River Basin, Oregon, USA. To implement this method, environmental and crop yield data were spatially related to individual soil units, forming the examples needed for the rule induction process. Next, four learning algorithms were defined by using different subsets of environmental attributes. ROSETTA, a software system for rough set analysis, was then used to generate rules using each algorithm. Cross-validation analysis showed that all crops had at least one algorithm with an accuracy rate greater than 68%. After selecting a preferred algorithm, the induced classifier was used to predict the crop suitability of each crop for the unclassified soils. The results suggest that rough set rule induction is a useful method for data generalization and suitability analysis.     

Analysis of motorcycle accidents using association rule mining-based framework with parameter optimization and GIS technology

IntroductionAnalyzing key factors of motorcycle accidents is an effective method to reduce fatalities and improve road safety. Association Rule Mining (ARM) is an efficient data mining method to identify critical factors associated with injury severity. However, the existing studies have some limitations in applying ARM: (a) Most studies determined parameter thresholds of ARM subjectively, which lacks objectiveness and efficiency; (b) Most studies only listed rules with high parameter thresholds, while lacking in-depth analysis of multiple-item rules. Besides, the existing studies seldom conducted a spatial analysis of motorcycle accidents, which can provide intuitive suggestions for policymakers. Method: To address these limitations, this study proposes an ARM-based framework to identify critical factors related to motorcycle injury severity. A method for parameter optimization is proposed to objectively determine parameter thresholds in ARM. A method of factor extraction is proposed to identify individual key factors from 2-item rules and boosting factors from multiple-item rules. Geographic information system (GIS) is adopted to explore the spatial relationship between key factors and motorcycle injury severity. Results and conclusions: The framework is applied to a case study of motorcycle accidents in Victoria, Australia. Fifteen attributes are selected after data preprocessing. 0.03 and 0.7 are determined as the best thresholds of support and confidence in ARM. Five individual key factors and four boosting factors are identified to be related to fatal injury. Spatial analysis is conducted by GIS to present hot spots of motorcycle accidents. The proposed framework has been validated to have better performance on parameter optimization and rule analysis in ARM. Practical applications: The hot spots of motorcycle accidents related to fatal factors are presented in GIS maps. Policymakers can refer to those maps straightforwardly when decision making. This framework can be applied to various kinds of traffic accidents to improve the performance of severity analysis.     

谈矿山推行呼吸性粉尘监测

矿山粉尘严重危害矿工身体健康,现有全尘监测方法存在许多弊端,必须进行改革,采用于国际接轨的呼吸性粉尘监测方法,从此法在我国的试点情况和大冶有色金属公司的实践来看,全面推广的时机基本成熟。     

The effect of environmental regulation on plant-level product mix: A study of EPA's Cluster Rule

This paper examines the effect of the U.S. Environmental Protection Agency's Cluster Rule on the product-mix decisions of plants in the pulp, paper, and paperboard industries. The Cluster Rule combines regulatory requirements from the Clean Air Act and Clean Water Act that are based on plants altering their production processes away from chlorine-based bleaching agents. In addition to, or instead of, altering production processes, plants may plausibly comply with the regulation by reducing output of bleached products or dropping some of these products entirely. Using a difference-in-difference-in-differences approach, we find evidence that plants facing both air and water Cluster Rule regulation (treatment group) are more likely to drop bleached products relative to unbleached products compared to plants facing only air Cluster Rule regulation (control group). Furthermore, we find evidence that plants in the control group alter their product mixes toward bleached products.     

Patch dynamics based on Prisoner's Dilemma game: superiority of golden rule

There has been much literature on ecological model of Prisoner's Dilemma (PD) game. This game illustrates that cooperation can evolve in situations where individuals tend to look after themselves. In order to explain some behaviors of altruism in animal societies, the strategy All Cooperate (AC), often called the Golden Rule, is more appropriate than other strategies. However, very little is known about the superiority of AC. In the present article, we study patch dynamics based on non-iterated PD game, applying two different methods: island and lattice models. Each patch is assumed to be either vacant or composed of a population of AC or All Defect (AD), where AD means a selfish strategy. Both models exhibit a phase transition between a phase where both AC and AD survive, and a phase where AD is extinct. The latter phase means that AC beats AD completely. In the case of lattice model, the extinction of AD easily occurs and the abundance of AC takes a larger value, compared with the island model. Our models can be also extended to general iterated PD game; we describe the reason why AC can outperform any other strategy.     

The Time Invariance Principle,the absence of ecological chaos,and a fundamental pitfall of discrete modeling

This paper is to show that most discrete models used for population dynamics in ecology are inherently pathological that their predications cannot be independently verified by experiments because they violate a fundamental principle of physics. The result is used to tackle an on-going controversy regarding ecological chaos. Another implication of the result is that all dynamical systems must be modeled by differential equations. As a result it suggests that researches based on discrete modeling must be closely scrutinized and the teaching of calculus and differential equations must be emphasized for students of biology.     

Integrated Models of Fisheries Management and Policy

An overview of the structure and elements of integrated models aimed at studying fishery management policies using static and dynamic optimisation techniques is presented. Continuous and discrete time models are considered under both open-access and sole-owner settings. A variety of economic and biological processes that affect the fishery as a whole is examined. It turns out that overseeing important fish population characteristics such as metapopulation dynamics and multi-species interaction can lead to serious misrepresentation of the fishery and suboptimal controls. Adequate understanding of the economic conditions and considerations potentially affecting the fishermen is necessary to model their behaviour and address their concerns. Misrepresentation of these economic and biologic processes will have an impact on the success of management policies in attaining a sustainable fish population.     

How Hydrologic Connectivity Regulates Water Quality in River Corridors

Downstream flow in rivers is repeatedly delayed by hydrologic exchange with off‐channel storage zones where biogeochemical processing occurs. We present a dimensionless metric that quantifies river connectivity as the balance between downstream flow and the exchange of water with the bed, banks, and floodplains. The degree of connectivity directly influences downstream water quality — too little connectivity limits the amount of river water exchanged and leads to biogeochemically inactive water storage, while too much connectivity limits the contact time with sediments for reactions to proceed. Using a metric of reaction significance based on river connectivity, we provide evidence that intermediate levels of connectivity, rather than the highest or lowest levels, are the most efficient in removing nitrogen from Northeastern United States’ rivers. Intermediate connectivity balances the frequency, residence time, and contact volume with reactive sediments, which can maximize the reactive processing of dissolved contaminants and the protection of downstream water quality. Our simulations suggest denitrification dominantly occurs in riverbed hyporheic zones of streams and small rivers, whereas vertical turbulent mixing in contact with sediments dominates in mid‐size to large rivers. The metrics of connectivity and reaction significance presented here can facilitate scientifically based prioritizations of river management strategies to protect the values and functions of river corridors.     

Attitude to safety rules and reflexivity as determinants of safety climate

IntroductionWe present two studies that focus on the relationship between safety rules and the safety climate. It is expected that a reasoned acceptance, namely one based on an understanding of the bases for the rules and a collective management of the rules, should benefit the climate. Method: In an initial study (N = 202) employees replied to a questionnaire that measured the safety climate, the level of the relationship with the safety rules, and the understanding of their bases. The results highlighted the fact that a reasoned acceptance of the rules is associated with an understanding of their bases and predicts the level of safety. In a second study (N = 258) employees replied to a questionnaire measuring team reflexivity, the safety climate, and the level of relationship with the safety rules. We observed that collective management of the rules mediated the relation between team reflexivity and the safety climate. Results: The results are discussed from the point of view of their practical implications. Developing safety climate requires that operators are trained to understand the basis of safety rules and team reflexivity.