bluuebunny/crossref_metadata_2025_split huggingface dataset:
BeadCons: Detection of Nucleic Acid Sequences by Flow Cytometry
Authors: Horejsh Douglas , Martini Federico , Capobianchi Maria Rosaria 
Published: September 2008

AbstractMolecular beacons are single‐stranded nucleic acid structures with a terminal fluorophore and a distal, terminal quencher. These molecules are typically used in real‐time PCR assays, but have also been conjugated with solid matrices. This unit describes protocols related to molecular beacon–conjugated beads (BeadCons), whose specific hybridization with complementary target sequences can be resolved by cytometry. Assay sensitivity is achieved through the concentration of fluorescence signal on discrete particles. By using molecular beacons with different fluorophores and microspheres of different sizes, it is possible to construct a fluid array system with each bead corresponding to a specific target nucleic acid. Methods are presented for the design, construction, and use of BeadCons for the specific, multiplexed detection of unlabeled nucleic acids in solution. The use of bead‐based detection methods will likely lead to the design of new multiplex molecular diagnostic tools.
Scientific Uncertainty in Social Debates Around Risk
Authors: Driedger S. Michelle 
Published: September 2008

Abstract
Quantitative risk assessments based on scientific understandings of a risk issue are often used in managing risk controversies in a policy domain. However, in several areas of risk, particularly in an environment and health domain, managing uncertainties in scientific knowledge is difficult and complex. It is important to understand how the production and use of scientific evidence can be understood as a social process and how scientific evidence may be used in regulatory decision making.
Risk and the Media
Authors: Mistry Bhavnita , Driedger S. Michelle 
Published: September 2008

Abstract
The news media has long been recognized as an important social player in civil society in shaping public discourse concerning current events, particularly in the communication of science, policy, and risk issues. While the media may not tell us what our thoughts should be, it has considerable power in influencing the same by virtue of what it does, and does not, report. This article explores how the media report and frame risk issues.
Considerations in Planning for Successful Risk Communication
Authors: Jardine Cynthia G. 
Published: September 2008

AbstractSuccessful risk communication does not occur serendipitously—it is the result of careful planning and consideration of multiple needs and objectives. Some considerations for planning for successful risk communication are presented here. However, this list is neither fully comprehensive nor exhaustive. The best overall guidance is to try to view the risk through the eyes of those who may legitimately and rationally view the nature and consequences of the risk differently. Evoking an empathetic understanding of different perspectives of risk, together with the application of good judgment about the nature of the risk, is ultimately the key to initiating a productive dialogue on risks.
Stakeholder Participation in Risk Management Decision Making
Authors: Jardine Cynthia G. 
Published: September 2008

AbstractStakeholder participation in risk management processes is becoming increasingly recognized as a means of producing decisions that are responsive to varying interests and values, including those of the community. Some considerations for planning for successful stakeholder involvement are outlined. Goals against which stakeholder participation efforts can be evaluated are also provided. However, the “right” process of participation must be determined on the basis of the nature of the risk and the impact of the decision.
Axiomatic Measures of Risk and Risk‐Value Models
Authors: Jia Jianmin , Dyer James S. , Butler John C. 
Published: September 2008

AbstractThis article provides a review of risk and risk‐value models that lead to decision making by explicitly trading off between risk and value. We begin with a discussion of a preference‐dependent measure of risk that is compatible with traditional expected utility theory, and therefore lends itself to an examination of how individuals perceive risky gambles as well as how they choose among them. Further, this risk measure can be the basis for generalizing models of decision making based on the intuitively appealing notion of trading off between risk and value. Based on the two‐attribute expected utility axioms, this risk‐value framework has much more flexibility in modeling preferences than the traditional single‐attribute expected utility theory. Specifically, we describe three useful classes of decision models: moments risk‐value models, exponential risk‐value models, and generalized disappointment models. These decision models unify two streams of research: one in developing preference models and the other in modeling risk judgments. They can also provide prescriptive guidance for those people who are willing to deviate from the traditional expected utility preference models and make their decisions based on risk‐value trade‐offs, as in financial decision making.
Precautionary Principles: Definitions, Issues, and Implications for Risky Choices
Authors: Ricci Paolo F. 
Published: September 2008

Abstract
This paper deals with several legal and risk‐based aspects of making precautionary decision in the public interest. It addresses European Union, US, and other statements of regulatory precaution that have been used to make environmental decisions. The purpose of this article is to discuss how the methods in quantitative risk analysis (QRA) can help understand the impact of prospective a precautionary decisions by providing a sound risk management framework
Use of Decision Support Techniques for Information System Risk Management
Authors: Buckshaw Donald L. 
Published: September 2008

AbstractIdentifying and understanding security risks for information system design or evaluation is very challenging. Making decisions about accepting or mitigating these risks through a rational, traceable, and understandable process is even harder. Quantitative risk analysis techniques can help stakeholders understand and communicate risk‐informed design decisions even when the stakeholders have conflicting objectives. Quantitative risk analysis also helps stakeholders understand security, cost, and functionality trade‐off decisions in repeatable process. This paper discusses the roles of stakeholders in risk analysis, the advantages and disadvantages of quantitative risk analysis, basic cyber risk decision support concepts and processes, and the mathematical definitions of risk for information systems. This paper recommends the use of properly constructed quantitative risk analysis models and discourages the use of semiquantitative risk analysis models.
Change Point Analysis
Authors: West Ronnie Webster 
Published: September 2008

Abstract

This entry provides a brief introduction to the statistical methodology called
change point analysis
, which is oft used in risk assessment. The goal of change point analysis is to model changes in the characteristics of a response variable over a range of a predictor variable. The discussion below is framed by two simple examples from the risk assessment literature where the response characteristic of interest is the mean response. The examples illustrate two simple change point methods for detecting the location of the change point in terms of the predictor variable and the nature of the change in the mean response before and after the change point. More complicated change point methods are also discussed briefly.
Detection Limits
Authors: Helsel Dennis R. 
Published: September 2008

AbstractDetection limits are established within a chemical laboratory to designate low‐level data that cannot be distinguished from a zero concentration. Higher limits also are used to denote data with low, nonzero concentrations that are too imprecise to report as distinct numbers. Data below both types of limits are reported to the customer as a “nondetect” (<10). Here, the definitions and uses of detection limits are outlined, and methods for using nondetect data in exposure assessments are explained.
Environmental Hazard
Authors: Beaubier Jeff , Nussbaum Barry D. 
Published: September 2008

Abstract
An environmental hazard is any condition, process, or state adversely affecting the environment. Environmental hazards manifest as physical or chemical pollution in air, water, and soils. Environmental hazards can cause widespread harm to humans and the physical environment. Three specific ones are discussed: lead, an element historically used in many products causing neurological problems; PCBs, or polychlorinated biphenyls, a group of nearly indestructible molecules with cancer‐causing properties; Asbestos, a widely used flame retardant which leads to cancers with long latency periods.
Environmental Health Risk
Authors: Khalili Nasrin R. 
Published: September 2008

Abstract
Risk is defined as the probability that a substance or situation will produce harm under specified conditions. Risk can be assessed with regards to safety, human health, ecology, public welfare, and goodwill. Environmental risk assessment involves both risk assessment and management of natural and technological hazards by estimating the potential impact of a chemical, physical, microbiological, or psychosocial hazard on a specified human population or ecological system. Environmental health assessment focuses on the aspects of public health and is concerned with the factors (contaminants and hazards), circumstances (exposure scenarios), and conditions in the environment. Health risk assessment process utilizes a series of assumptions, preferably in a conservative range, about the chemical hazards, exposure scenarios, and the toxicological factors in order to characterize the risks with a minimum level of uncertainty. The environmental health risk assessment provides guidelines for assessing human health risks from environmental hazards.
Statistics for Environmental Mutagenesis
Authors: Piegorsch Walter W. 
Published: September 2008

AbstractIn experiments studying the effects of environmental stimuli on biological organisms, major endpoints of interest include damage to genetic components such as deoxyribonucleic acid (DNA). DNA damage as represented by mutagenic insult(s) is perhaps the most varied of any toxicological endpoint, since the potential mechanisms of genetic damage are so numerous. Statistical issues associated with mutagenicity experiments include construction of models to characterize dose–response and other features of genetic damage, sample size determinations/study design, and the selection of statistical approaches associated with these models and methods; these are briefly discussed
Environmental Health Risk Assessment
Authors: Stern Alan H. 
Published: September 2008

AbstractQuantitative health risk assessment is a tool for making predictions about the impact of substances in the environment on health. Despite the use of scientific principles and a reliance on the most appropriate data from the scientific literature, risk assessment, in the strict sense of the word, is not, by itself, a science. Two different forms of quantitative risk assessment are practiced. One form can be referred to assafety assessment, which seeks to identify the largest level of exposure or dose that can be reasonably expected to be without adverse effect. The other form seeks to quantify the risk associated with any exposure or dose of an environmental agent. In the United States, this form of risk assessment is generally applied to carcinogens. The classical structure of formal environmental health risk assessments comprises of four interdependent steps: hazard identification; dose–response assessment; exposure assessment; and risk characterization. Recent advances in conducting environmental health risk assessments include the use of the benchmark dose approach in lieu of the no observed adverse effect level (NOAEL)/lowest observed adverse effect level (LOAEL) determination, the use of probabilistic analysis in place of single value estimates for risk assessment variables, and progress toward harmonization of cancer and noncancer endpoints.
Environmental Security
Authors: Linkov Igor 
Published: September 2008

AbstractThe concept of “environmental security” has emerged as a basis for understanding risks related to limited natural resources and critical infrastructure, and is a phrase that can mean a variety of things. It can signify security issues stemming from environmental concerns or conflicting needs, or it can mean that the environment is treated as a resource for the long term. These meanings lead to the question, What should be done today to preserve the quality of the environment in the future? In the same way that energy security is about ensuring access to energy for the long run, it can also mean that pressing environmental concerns create a situation where different countries and communities are forced to collaboratively design a unified response, even if cooperation is not generally in the logic of their relations. Risk assessment is an important tool that could help in managing security risks, but its application is particularly challenging due to the knowledge vacuum and constricted timeline in which security decisions must be made. Challenges of risk assessment for situations with a limited knowledge base, high uncertainty, and variability require coupling traditional risk assessment with other quantitative tools, such as multicriteria decision analysis (MCDA), to support environmental security applications.
Hotspot Geoinformatics
Authors: Patil Ganapathi P. , Joshi Sharadchandra W. , Rathbun Stephen L. 
Published: September 2008

AbstractGovernment agencies continue to require meaningful summaries of georeferenced data to support policies and decisions involving risk maps, geographic targets, and resource allocations. So also the public with initiatives of digital governance, enabling transparency, efficiency, and efficacy in the risk assessment and management.This article briefly introduces hotspot geoinformatics for hotspot detection and prioritization, and provides examples of societal importance involving environmental risk.
Kriging
Authors: Switzer Paul 
Published: September 2008

AbstractKriging is a method for spatial interpolation based on correlation modeling between observations. This article describes how correlation is used to assign weights to control data for interpolations, and how correlation is used to assess the uncertainty of interpolation. Additionally, the article describes how auxiliary and prior information are used in kriging interpolation and how such information constrains the weights assigned to the control data. Finally, the article describes the impact of measurement error and short‐scale variability on interpolated values and on the interpolation uncertainty. An illustration indicates how control data are weighted differently according to their relation to the interpolation location and how interpolation uncertainty would change with increasing density of the control data.
Molecular Markers and Models
Authors: Preston R. Julian 
Published: September 2008

Abstract

Risk‐assessment practices for a range of diseases, in general, now encourage the use of mechanistic data to enhance the ability to predict responses at low environmental exposures. In particular, the pathway from normal biology to pathologic state can be described by a set of measurable key events. These key events can be considered molecular markers of disease. Recent advances in molecular biology methodologies and knowledge of the underlying mechanisms of several diseases have allowed for the identification of truly informative biomarkers of response, especially for tumors. The cancer risk from exposures to environmental chemicals can similarly be assessed using these types of molecular biomarkers. Models of cancer have further enhanced the appreciation that tumor formation is a tissue response, and that modifications of normal biology need to be considered at a systems level rather than at the gene or single pathway levels. Molecular models that are based upon such a systems approach have been developed recently; these include models of mitosis, cell signaling, nuclear transport, and cell cycles. Abrogations of these systems can lead to disease outcomes. A very recent model based on gene–gene interactions among genes in

Caenorhabditis elegans

involved in signaling pathways that are also mutated in human diseases has identified a set of highly connected “hub” genes that can essentially enhance the effects of mutations in a range of different genes. These “hub” genes are all chromatin modulators, leading to a powerful approach for identifying key events in disease etiology. This type of molecular‐modeling systems approach marks the way forward for incorporating key events into the risk‐assessment process for a range of diseases.
Stratospheric Ozone Depletion
Authors: Solow Andrew R. 
Published: September 2008

Abstract
The depletion of ozone in the stratosphere by man‐made chlorine compounds poses a significant risk to human health. Although the basic chemistry of ozone depletion has been understood since the 1970s, the physical and chemical processes controlling depletion in different parts of the atmosphere are complicated. This article reviews some statistical analyses of surface and satellite observations of ozone concentrations.
Point Source Modeling
Authors: Diggle Peter J. 
Published: September 2008

AbstractWe consider the problem of investigating spatial variation in disease risk around one or more preidentified point sources of pollution. This topic has its origins in concerns about the health effects to the surrounding population of potentially toxic emissions from industrial sites. We describe approaches to the problem that apply the theory of spatial point processes to the analysis of data from an epidemiological case–control study. We first formulate an idealized model in which cases and controls are modeled as inhomogeneous Poisson point processes whose spatially varying intensities are linked by a relative risk function ρ(x), wherexdenotes location. Typically, ρ(·) is modeled as a function of the distance, and possibly the orientation, ofxrelative to the point source of interest. We show how likelihood‐based inference about ρ(·) can be carried out by fitting a nonlinear binary regression model to the case–control labels, conditioning on the locations of cases and controls. We describe several specific parametric models that have been suggested in the literature, and a nonparametric alternative in which ρ(·) is modeled as a smooth, but otherwise arbitrary, function of distance.
Risk from Ionizing Radiation
Authors: Cullings Harry M. , Cologne John B. 
Published: September 2008

Abstract
Ionizing radiation, perhaps the most studied of all environmental hazards, illustrates many important aspects of quantitative risk assessment. We discuss the nature of ionizing radiation, major sources of exposure to humans, and the major categories of resulting health effects, focusing on stochastic late effects such as increased rates of cancer. We explain the role of the fundamental exposure metric, radiation dose, in regard to issues such as the shape and magnitude of the dose–response and the important dependence of dose–response on time variables and other factors specific to the affected individual (effect modification). After explaining basic methods of radiation risk estimation, including methods for dealing with uncertainty in the doses of individuals in a study cohort, we discuss several important principles related to the application of the resulting estimates in radiation protection. Finally, we outline some of the major results of radioepidemiological studies.
Alternative Risk Transfer
Authors: Banks Erik 
Published: September 2008

Abstract
Active risk management is important for companies interested in maximizing enterprise value, which can be defined as the discounted value of future after‐tax profits. While established risk techniques based on retention, transfer, and hedging comprise the core of active risk management, innovative solutions from the alternative risk transfer market have proven useful in giving companies additional tools by which to manage their exposures. Growth in the alternative sector has been driven primarily by efficiencies and cost savings that allow companies to boost enterprise value.
Bonus–Malus Systems
Authors: Walhin Jean‐François 
Published: September 2008

Abstract

This paper describes a particular type of a posteriori rating scheme, namely bonus‐malus systems within the general framework of mixed Poisson regression. It is shown that the bonus‐malus scale is not independent of the
a priori
rating applied by the insurer. Considerations about bonus hunger, moral hazard, and signal theory are briefly introduced.
Credibility Theory
Authors: Goulet Vincent 
Published: September 2008

Abstract
Credibility models are actuarial tools to distribute premiums fairly among a heterogeneous group of policyholders. More generally, they can be seen as prediction methods applicable in any setting in which repeated measures are made for subjects with different risk levels. The article presents the two main approaches to credibility—limited fluctuations and greatest accuracy—with emphasis on the modeling of heterogeneity using a Bayesian framework. The main results of the classical Bühlmann and Bühlmann–Straub models are interpreted. More advanced models are briefly introduced.
Dynamic Financial Analysis
Authors: D'Arcy Stephen P. 
Published: September 2008

Abstract
Dynamic financial analysis (DFA) is an approach used by organizations to model financial results of the entity under a variety of conditions. The modeling techniques embedded in DFA developed as advances in the computational power of business computers made running large numbers of complex simulations feasible. The models have gradually become more complex, more realistic, and more widely applicable. Companies, rating agencies, and regulators now routinely use DFA type models to evaluate the financial condition of an organization and assess operational changes. This article describes this approach, compares simulation with other financial planning methods, and provides the details of a publicly accessible DFA model that has been extensively used in research and education. DFA is most widely used by insurance companies and other financial institutions, but many nonfinancial firms utilize similar techniques.
Equity‐Linked Life Insurance
Authors: Bacinello Anna R. 
Published: September 2008

Abstract

Equity‐linked life insurance contracts are characterized by the fact that benefits are directly linked to the value of an investment portfolio, typically composed of units of one or more mutual funds and kept separate from the other assets of the insurance company. These contracts generally imply a rather high level of financial risk that can be totally charged to the policyholder, in
pure equity‐linked contracts
, or shared between the policyholder and the insurance company, in
guaranteed equity‐linked contracts
. In the first case the insurance company acts as a mere financial intermediary, while in the second case it has to set up suitable hedging strategies because the financial risk is of systematic nature and cannot be eliminated by sufficiently increasing the size of its portfolio. In this contribution we first describe, in general terms, the main characteristics of equity‐linked products and their advantages with respect to other types of life insurance and investment contracts. Then we pass to analyze how the investment portfolio to which benefits are linked evolves over time and, finally, to present some possible approaches that the insurance company can follow in order to hedge the liabilities arising from the issue of minimum guarantees.