Disaster Risk Assessment Based on Variable Fuzzy Sets and Improved Information Diffusion Method

The predictive analysis of natural disasters and their consequences is challenging because of uncertainties and incomplete data. The present article studies the use of variable fuzzy sets (VFS) and the improved information diffusion method (IIDM) to construct a composite method. The proposed method aims to integrate multiple factors and quantification of uncertainties within a consistent system for catastrophic risk assessment. VFS have been selected because of several advantages. These sets can effectively eliminate the border effect on assessment result and monitor estimation standard error. The IIDM theory can obtain as much useful information as possible from the sample and improves system recognition accuracy. Both these methods contribute to a sound risk probability prediction of natural disasters. Furthermore, the application has been verified through flood and drought risk analyses in China, where the risks of different flood and drought grades have been obtained. The results indicate that the proposed method achieves a better detection stability of disaster risk with higher precision compared with other methods. The method is effective, practical, and applicable in disaster rescue and relief.     

Phylogeny Based on Whole Genome as inferred from Complete Information Set Analysis

Previous molecular phylogeny algorithms mainly rely onmulti-sequence alignments of cautiously selected characteristic sequences,thus not directly appropriate for whole genome phylogeny where eventssuch as rearrangements make full-length alignments impossible. Weintroduce here the concept of Complete Information Set (CIS) and itsmeasurement implementation as evolution distance without reference tosizes. As method proof-test, the 16s rRNA sequences of 22 completelysequenced Bacteria and Archaea species are used to reconstruct aphylogenetic tree, which is generally consistent with the commonlyaccepted one. Based on whole genome, our further efforts yield a highlyrobust whole genome phylogenetic tree, supporting separate monophyleticcluster of species with similar phenotype as well as the early evolution ofthermophilic Bacteria and late diverging of Eukarya. The purpose of thiswork is not to contradict or confirm previous phylogeny standards butrather to bring a brand-new algorithm and tool to the phylogeny researchcommunity. The software to estimate the sequence distance and materialsused in this study are available upon request to corresponding author.     

Concomitant Information in Competing Risk Analysis

A competing risk model, accommodating both Type I censoring and random withdrawals, is expanded to incorporate concomitant information by allowing the parameters of the underlying distributions to be a linear function of two covariates. The model is developed for two competing risks, one following a Weibull distribution and the other a Rayleigh distribution, and random withdrawals following a Weibull distribution. A method is developed for testing the equality of the coefficients for a given covariate for each of the competing risks using MLE'.     

一种基于信息理论的距离系数

给出了一种基于信息理论的距离系数,这一新的信息系数是通过对信息论中的离散增量系数改进而得,并证明其满足距离系数的三个性质．将其应用于一组同源辅助蛋白的聚类分析,表明是可行的．与离散增量系数及经典的欧氏距离系数的聚类结果进行比较,应用相干系数对聚类结果进行评价,结果表明由新信息距离系数所确定的聚类结构与聚类数据问的拟合程度最好.     

Modeling Information Quality Risk for Data Mining in Data Warehouses

Information Quality (IQ) is a critical factor for the success of many activities in the information age, including the development of data warehouses and implementation of data mining. The issue of IQ risk is recognized during the process of data mining; however, there is no formal methodological approach to dealing with such issues.

Consequently, it is essential to measure the risk of IQ in a data warehouse to ensure success in implementing data mining. This article presents a methodology to determine three IQ risk characteristics: accuracy, comprehensiveness, and non-membership. The methodology provides a set of quantitative models to examine how the quality risks of source information affect the quality for information outputs produced using the relational algebra operations: Restriction, Projection, and Cubic product. It can be used to determine how quality risks associated with diverse data sources affect the derived data. The study also develops a data cube model and associated algebra to support IQ risk operations.     

Ecological Risk Assessment and Quantitative Consequence Analysis

Ecological risk actually refers to two separate things. First, risk to the environment as a result of human activity. Contaminated sites are an example. Second, risk to the biota—flora, fauna, and people—as a result of environmental hazards. Geophysical risk arising from natural hazards is an example. Risk is a combination of likelihoods and consequences. This article examines methods used to quantify the consequences. At the general level, such methods are linked to the methods used to quantify the likelihoods and thus to quantify the risks. It is possible to use the existing frameworks of risk management, health risk assessment, and ecological risk analysis to develop a risk management framework that is suitable for ecological risk assessment. The framework consists of the following steps:

1. Determine concernsby using risk assessment techniques for various scenarios.

2. Identify the consequences by systematically identifying hazards.

3. Undertake calculations by using relevant models.

4. Evaluate certainties, uncertainties, and probabilities involved in the calculations of the vulnerability and of the exposure.

5. Compare with criteriato assess the need for further action.

6. Determine and act on options to control, mitigate, and adapt to the risk.

7. Communicatethe results to those who need to know.

     

Risk Assessment and Safety Evaluation Using Probabilistic Fault Tree Analysis

Risk assessment is an essential prelude to the development of accident prevention strategies in any chemical or petrochemical industry. Many techniques and methodologies such as HAZOP, failure mode effect analysis, fault tree analysis, preliminary hazard analysis, quantitative risk assessment and probabilistic safety analysis are available to conduct qualitative, quantitative, and probabilistic risk assessment. However, these methodologies are limited by: extensive data requirements, the length of study, results are not directly interpretable for decision making, simulation is often difficult, and they are applicable only at the operation or late design stage. Khan et al. (2001a) recently proposed a detailed methodology for risk assessment and safety evaluation. This methodology is simple, yet it is effective in safety and design-related decision making, and it has been applied successfully to many case studies. It is named SCAP, where S stands for safety, C and A stand for credible accident respectively, and P stands for probabilistic fault tree analysis. This paper recapitulates the SCAP methodology and demonstrates its application to a petrochemical plant.     

Analysis of Determining Factors of the Public's Risk Acceptance Level in China

This work will characterize risk acceptance in China, based on the psychometric paradigm, and explore the determining factors that influence the risk acceptable level to the Chinese public. For this purpose, a survey was conducted including 12 hazards, 10 risk attributes (including risk acceptance), and demographic variables. First, the research attempted to explore Nanjing citizens’ average risk acceptable level for 12 hazards in China. Second, intercorrelation analysis and factor analysis of nine risk attributes were performed to obtain the suitable risk perception factors as independent variables. Three risk perception models of acceptance were constructed, which were named “Environmental risk model,” “Daily risk model,” and “Technical risk model,” that explained 59.0–69.6% of variance separately. In general, the variables of Knowledge, Benefit, and Trust were found to be significant in all models, implying that these variables are the main determining factors. However, in the environmental risk model, the variable of effect was also significant, which means the determining factors would change for different types of hazards. These results could help the Chinese government to improve the communication of risks with the public and make effective mitigation policies to improve people's rational judgment on the acceptability of risks.     

Optimizing Circular Economy Planning and Risk Analysis Using System Dynamics

This article develops a systems dynamics and multi-objective programming model (SDMOP) for planning a regional circular economy. Various risk analyses are conducted using the technique of sensitivity analysis. This SDMOP model includes two modules: the MOP module used to derive optimized parameters as inputs to the systems dynamics model, and the systems dynamics module used to plan the regional circular economy. We demonstrate the application of this SDMOP model to a problem of planning the circular economy of a county in the Sichuan Province of China.     

Extinction Risk: Predicting and Redressing the Threat

Predicting and redressing the threat of species extinction is not a success story. The science of estimating extinction rates and risk prediction is approached in a manner that is difficult to apply in the field, and yet current integrated ecosystem management programmes in many parts of the world, which are trying to place the conservation of species into sustainable community projects, need predictive tools for planning land use programmes. Such programmes involve US$100s of millions of multilateral and bilateral aid; many predicated on a site's biodiversity importance, the risks of extinction, sustainable extraction, production forms of land use, community livelihoods, water, and many others factors, but increasingly on ensuring that after the pump-priming funds are finished the programmes are both environmentally and economically sustainable (Swingland 2002, 2003, 2004; Swingland et al. 2003). [Swingland I.R. 2002. In: Swingland I.R., Bettelheim E.C., Grace J., Prance G.T. and Saunders L.S. (eds), Carbon Biodiversity, Conservation and Income: An Analysis of a Free Market Approach to Land-use Change and Forestry in Developing and Developed Countries. Philosophical Transactions Royal Society London A: Mathematical, Physical and Engineering Sciences, London; Swingland I.R. (ed.) 2003. Capturing Biodiversity and Conserving Biodiversity: The Market Approach. Earthscan, London; Swingland I.R. (ed.) 2004. CO² e biodiversità. Un approccio integrato a favore del clima e del patrimonio naturale. Edizioni Ambiente, Milano, Italy, 296 pp.; Swingland I.R., Bettelheim E.C. and Niles J.O. 2003. In: Swingland I.R. (ed.), Capturing Biodiversity and Conserving Biodiversity: The Market Approach. Earthscan, London] This involves predictions of ‘what if?’ what if laws are changed to prevent over utilisation and prevent ‘The Tragedy of the Commons’ where land ownership is vested in the state and people degrade the environment, and instead institute private land ownership. In places like China and much of the Far East, biodiversity is over-exploited as nearly all their species are used for food, medicine and construction purposes, and private land ownership in rural areas is rudimentary or absent. Since most species extinction is anthropocentric, research on species extinction needs to be more accessible and focussed on global problems.     

松突圆蚧等5种松树有害生物在福建省潜在危险性的定量分析

本参照国内外专家对有害生物的危险性定量分析方法,结合福建省森林资源状况和病虫害发生防治等情况,建立适用于福建省的有害生物潜在危险性的定量分析评价指标体系,并据此对松突圆蚧,红脂大小蠹,萧氏松茎象,湿地松粉蚧,日本松干蚧等5种松树害虫,对福建省的潜在危险性进行了定量分析和评价,结果表明松突圆蚧,萧氏松芪象,日本松干蚧为高度危险的害虫,红脂大小囊,湿地松粉蚧属中度但接近高度危险的害虫,并据此提出了相应的风险管理措施。     

A Regional Multiple Stressor Risk Assessment of the Codorus Creek Watershed Applying the Relative Risk Model

The relative risk model (RRM) used in Port Valdez, AK, and in Oregon's Willamette/McKenzie Watershed was applied to the Codorus Creek Watershed in south central Pennsylvania. The assessment evaluated the relative risk model for its applicability for ranking ecological risks within the Codorus Creek Watershed. The Codorus Creek Watershed approach included ranking stressors and habitats for regions within the watershed. Geographical Information Systems were vital in compiling and comparing stressor and habitat spatial data from regions in the watershed. The risk of ecological impacts to degrade assessment endpoints were calculated and ranked by quantitatively determining the interactions of the stressors and habitats as defined in the conceptual site model. Uncertainty assessment was conducted and the impact upon the relative ranks and risk conclusions evaluated. To determine regional risks, risk management information was gathered identifying areas to be protected, areas of high stress, and areas where additional information is needed. The results supported the applicability of the RRM and suggested areas and stressors for restoration efforts in the Codorus Creek Watershed. Two critical sets of conclusions were drawn from the assessment. First, in the Codorus Creek Watershed, the most significant stressor is agriculture land use, the most significantly impacted endpoint is water quality, and the most vulnerable habitats are those for macroinvertebrates and warm-water fish. Second, this risk assessment demonstrates the feasibility of using the RRM for assessing risk from multiple stressors on habitats with multiple assessment endpoints in an eastern watershed.     

Incorporating Information on Bioavailability of Soil-Borne Chemicals into Human Health Risk Assessments

Definition of the term bioavailability varies in the environmental sciences. In human health risk assessment, bioavailability is defined as the fraction of the dose of chemical delivered that is absorbed into the systemic circulation. Bioavailability can be expressed as either absolute or relative bioavailability, and both are important in calculating risks from contaminants in soils. Bioavailability of chemicals is addressed in all risk assessments, although not always in a transparent manner. Because data on bioavailability are limited, approximations and assumptions regarding chemical uptake are extensively used. The risk assessment process could benefit from new information on the bioavailability of chemicals, but there are important questions about the best means to develop this information and how it should be used. To foster discussion on these issues, three articles are presented in this issue of the journal offering different perspectives on bioavailability method development, validation, and use.     

小兴安岭西南部森林对洪水径流的影响

小兴安岭西南部森林对洪水径流的影响张庆费周晓峰,王传宽（华东师范大学环境科学系上海２０００６２）（东北林业大学林学系哈尔滨１５００４０）ＩｎｆｌｕｅｎｃｅｏｆＦｏｒｅｓｔｏｎＦｌｏｏｄＲｕｎｏｆｆａｔｔｈｅＳｏｕｔｈｗｅｘｔｅｒｎＰａｒｔｏｆＸｉａｏ...     

Risk Analysis and Carbon Footprint Assessments of the Paper Industry in China

China is the largest paper producer and consumer in the world. However, China's paper industry is inefficient in its consumption of natural resources. Whereas the proportion of wood pulp used by the paper industry in developed countries is up to 63%, the corresponding figure for China is only 23%, leading to high energy and water consumption and severe environmental pollution. This article presents a systematic risk analysis using life cycle assessment and carbon footprint calculation associated with China's straw-pulp and wood-pulp paper industries. Risk prevention measures are proposed based on the results of this analysis. The study has important ramifications for the sustainable development of China's paper industry.     

褐纹甘蔗象风险分析及其风险管理

通过对褐纹甘蔗象在国内外的分布情况及国内寄主植物分布、适生范围、传播渠道、检疫管理措施等指标的定性和半定量的风险分析,得出其在我国属于中度危险的林业有害生物(其风险评估值为R=1.746),对我国种植面积广泛的棕榈科植物构成了较大的威胁。建议在有其寄主分布的省份将其列入林业检疫性有害生物省级补充名单进行管理,防止其在我国继续扩散危害,并提出了国内检疫管理的措施。     

Network Environment and Financial Risk Using Machine Learning and Sentiment Analysis

Under the network environment, the trading volume and asset price of a financial commodity or instrument are affected by various complicated factors. Machine learning and sentiment analysis provide powerful tools to collect a great deal of data from the website and retrieve useful information for effectively forecasting financial risk of associated companies. This article studies trading volume and asset price risk when sentimental financial information data are available using both sentiment analysis and popular machine learning approaches: artificial neural network (ANN) and support vector machine (SVM). Nonlinear GARCH-based mining models are developed by integrating GARCH (generalized autoregressive conditional heteroskedasticity) theory and ANN and SVM. Empirical studies in the U.S. stock market show that the proposed approach achieves favorable forecast performances. GARCH-based SVM outperforms GARCH-based ANN for volatility forecast, whereas GARCH-based ANN achieves a better forecast result for the volatility trend. Results also indicate a strong correlation between information sentiment and both trading volume and asset price volatility.     

Research on the Risk Level of Landfall Typhoons in Zhejiang,China

Zhejiang Province, as a major province of economic strength in China, has economically well-developed coastal areas, which are heavily damaged during landfall typhoons. In this paper, typhoons that could cause serious damages to Zhejiang Province will be labeled as “disastrous typhoons,” and the corresponding wind velocities will be labeled as “disastrous wind velocities.” It is suggested that typhoons exceeding certain threshold-values be selected as samples for calculation, and this method is called threshold-value sampling. According to the typhoon measurement data and by using the P-III distribution function, the disastrous wind velocity of certain recurrence interval in typhoon-resistant and engineering design projects was calculated. The calculation results show that the disastrous wind velocity of the largest landfall typhoon of coastal areas for the next 10 years is 41.8 m/s, the disastrous wind velocity in the next 50 years is 49.7 m/s, and 52.9 m/s in the next 100 years. It can be seen at the same time that the wind velocity calculated by the P-III distribution model is more similar to the actual conditions compared to the wind velocity calculated by the Weibull distribution model. This method is conceptually clear, easy to use, and generates ideal results.     

探索景观异质性的热力学基础和信息论

探索景观异质性的热力学基础和信息论ＭｉｃｈｅｌＧｏｄｒｏｎ,ＪａｃｑｕｅｓＢａｕｄｒｙＲｉｃｈａｒｄＴ．Ｔ．Ｆｏｒｍａｎ）ＴｈｅｒｍｏｄｙｎａｍｉｃＦｏｕｎｄａｔｉｏｎａｎｄＩｎｆｏｒｍａｔｉｏｎＴｈｅｏｒｙｉｎＵｎｄｅｒｓｔａｎｄｉｎｇＬａｎｄｓｃ...