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Y Y Haimes

Publications and source records attributed to Y Y Haimes.

11 recordsLinked to original sources
PubMed2003

Risk modeling, assessment, and management of lahar flow threat.

The 1991 eruption of Mount Pinatubo in the Philippines is considered one of the most violent and destructive volcanic activities in the 20th century. Lahar is the Indonesian term for volcanic ash, and lahar flows resulting from the massive amount of volcanic materials deposited on the mountain's slope posed continued post-eruption threats to the surrounding areas, destroying lives, homes, agricultural products, and infrastructures. Risks of lahar flows were identified immediately after the eruption, with scientific data provided by the Philippine Institute of Volcanology, the U.S. Geological Survey, and other research institutions. However, competing political, economic, and social agendas subordinated the importance of scientific information to policy making. Using systemic risk analysis and management, this article addresses the issues of multiple objectives and the effective integration of scientific techniques into the decision-making process. It provides a modeling framework for identifying, prioritizing, and evaluating policies for managing risk. The major considerations are: (1) applying a holistic approach to risk analysis through hierarchical holographic modeling, (2) applying statistical methods to gain insight into the problem of uncertainty in risk assessment, (3) using multiobjective trade-off analysis to address the issue of multiple decisionmakers and stakeholders in the decision-making process, (4) using the conditional expected value of extreme events to complement and supplement the expected value in quantifying risk, and (5) assessing the impacts of multistage decisions. Numerical examples based on ex post data are formulated to illustrate applications to various problems. The resulting framework from this study can serve as a general baseline model for assessing and managing risks of natural disasters, which the Philippines' lead agency-the National Disaster Coordinating Council (NDCC)-and other related organizations can use for their decision-making processes.

Journal Article↗
PubMed2001

Risk analysis, systems analysis, and Covey's seven habits.

This article relates problem solving to the common approaches of the gestalt-holistic philosophies of systems analysis, risk analysis, and Stephen Covey's Seven Habits of Highly Effective People. Guiding principles developed on the basis of these philosophies provide the foundations for methodological frameworks that build on a plethora of theory, methods, tools, and techniques. Although systems analysis and risk analysis differ in their historical evolution and technical maturity, both study and solve problems using methodological frameworks that share a holistic vision.

Journal Article↗
PubMed2001

Fitting hierarchical holographic modeling into the theory of scenario structuring and a resulting refinement to the quantitative definition of risk.

A point of view is suggested from which the Hierarchical Holographic Modeling (HHM) method can be seen as one more method within the Theory of Scenario Structuring (TSS), which is that part of Quantitative Risk Assessment having to do with the task of identifying the set of risk scenarios. Seen in this way, HHM brings strongly to our attention the fact that different methods within TSS can result in different sets of risk scenarios for the same underlying problem. Although this is not a problem practically, it is a bit awkward conceptually from the standpoint of the "set of triplets" definition of risk, in which the scenario set is part of the definition. Accordingly, the present article suggests a refinement to the set of triplets definition, which removes the specific set of scenarios, found by any of the TSS methods, from the definition of risk and casts it, instead, as an approximation to the "true" set of scenarios that is native to the problem at hand and not affected by the TSS method used.

Journal Article↗
PubMed1986

Invited contribution: an objective approach to the development of short-term tests predictive of carcinogenicity.

The Carcinogenicity Prediction and Battery Selection procedure was developed to address two problems: (1) the identification of highly predictive, yet cost-effective, batteries of short-term tests and (2) the objective prediction of the potential carcinogenicity of chemicals based upon the results of short-term tests even when a mixture of positive and negative results is obtained. In the present report the usefulness of the Carcinogenicity Prediction and Battery Selection procedure is demonstrated using benzo[a]pyrene, benzoin and diethylstilbestrol as examples. In addition, its applicability in the analysis of all the possible outcomes of a battery is illustrated together with an analysis of the worth of additional testing.

Animals↗
PubMed1985

The carcinogenicity prediction and battery selection (CPBS) method: a Bayesian approach.

Recently, a large number of relatively inexpensive in vitro short-term tests have been developed to help predict the carcinogenicity of chemicals. The carcinogenicity prediction and battery selection (CPBS) method utilizes the results of such short-term tests to screen for chemicals that are most likely to cause cancer. The method is an integrated approach for analyzing large, often sparsely filled, data bases containing short-term test results, which often have only marginal representation of known non-carcinogens. The CPBS method is developed for the purpose of (i) determining the reliability and predictive capability of individual and batteries of short-term tests, and (ii) developing a strategy for formulating and selecting optimally preferred batteries of short-term tests for screening chemicals for further testing. The term 'optimally preferred' connotes the best acceptable combination of tests in terms of trade-offs among the multiple attributes of each test and resulting battery (e.g., cost, sensitivity, specificity, etc). The CPBS method consists of 5 major tasks: (1) data consolidation, (2) parameter estimation, (3) predictivity calculation, (4) battery selection and (5) risk assessment. Although there is a great need for more research and improvement, the CPBS method at its present stage should add an important method to the maze of the thousands of new chemicals that are introduced into drugs, foods, consumer goods and to the environment every year. This method should also provide an enhanced identification procedure for classifying chemicals more accurately as suspected carcinogens or non-carcinogens.

Carcinogens↗
PubMed1985

Cluster analysis in predicting the carcinogenicity of chemicals using short-term assays.

Cluster analysis can be a useful tool for exploratory data analysis to uncover natural groupings in data, and initiate new ideas and hypotheses about such groupings. When applied to short-term assay results, it provides and improves estimates for the sensitivity and specificity of assays, provides indications of association between assays and, in turn, which assays can be substituted for one another in a battery, and allows a data base containing test results on chemicals of unknown carcinogenicity to be linked to a data base for which animal carcinogenicity data are available. Cluster analysis was applied to the Gene-Tox data base (which contains short-term test results on chemicals of both known and unknown carcinogenicity). The results on chemicals of known carcinogenicity were different from those obtained when the entire data base was analyzed. This suggests that the associations (and possibly the sensitivities and specificities) which are based on chemicals of known carcinogenicity may not be representative of the true measures. Cluster analysis applied to the total data base should be useful in improving these estimates. Many of the associations between the assays which were found through the use of cluster analysis could be 'validated' based on previous knowledge of the mechanistic basis of the various tests, but some of the associations were unsuspected. These associations may be a reflection of a non-ideal data base. As additional data becomes available and new clustering techniques for handling non-ideal data bases are developed, results from such analyses could play an increasing role in strengthening prediction schemes which utilize short-term tests results to screen chemicals for carcinogenicity, such as the carcinogenicity and battery selection (CPBS) method (Chankong et al., 1985).

Carcinogens↗
PubMed1985

Application of the carcinogenicity prediction and battery selection (CPBS) method to the Gene-Tox data base.

The carcinogenicity prediction and battery selection (CPBS) method (Chankong et al., 1985) utilizes the results of short-term tests to predict the carcinogenicity of chemicals and select batteries of tests that are capable of giving accurate predictions at reasonable costs. The CPBS method has been applied to the data compiled under the aegis of the Gene-Tox Program of the U.S. Environmental Protection Agency as a demonstration of the method on a typical data base. A number of batteries were selected by the methodology as having superior performance characteristics. The Bayesian predictions resulting from most of the selected 3-assay batteries were very good (greater than 90% of the carcinogens were correctly identified). It was also found that the 3-assay batteries of specified composition gave generally more accurate predictions than batteries of 4 or more assays of unspecified composition. A number of problems which may have affected our results have been identified: (1) the reliability of the sensitivities and specificities of the individual assays, (2) the prior probability that a chemical is a carcinogen was assumed to be 0.5, and (3) we have not (as yet) taken into account that some of the carcinogens are non-genotoxic and will produce false negative assays results. We are currently investigating approaches to take these factors into consideration. Our analysis also indicates that more testing of chemicals for carcinogenicity (especially probable non-carcinogens) is needed to further enhance the predictive capability of the CPBS method.

Carcinogens↗
PubMedDate not supplied

Optimal selection of a battery of tests: a multiobjective optimization methodology.

The general problem of selecting a battery of tests for diagnostic purposes is discussed and multiobjective optimization methodology is applied to solve it, with battery selection being based on performance indices such as sensitivity, specificity, and the cost of testing. For a battery of tests, the extended majority rule is developed and used to interpret the compound test results. The major advantage of the model developed in this paper is that it can generate a set of noninferior batteries without requiring the calculation of all possible combinations of tests. An example in which the method is applied to a real problem--the selection of short-term tests to detect the carcinogenicity of chemicals--is discussed.

Algorithms↗
PubMedDate not supplied

Carcinogenicity prediction and battery selection procedure: an in-depth analysis of cyclamate and its major metabolite cyclohexylamine.

The carcinogenicity prediction and battery selection (CPBS) method can be used to predict the probable carcinogenicity of a chemical based on the results of a battery of short-term assays. The method uses Bayesian statistics and the estimated performance characteristics of the assays (i.e., sensitivity and specificity). For routine use, the prior probability of carcinogenicity (or of noncarcinogenicity) is assumed to be unknown and is assigned a nondiscriminatory value of 0.5, i.e., the chemical is assumed to have an equal probability of being a carcinogen or a noncarcinogen, which implies that the expert's intuition regarding the chemical's potential as a carcinogen, based on structural features, known metabolic transformation, or potential electrophilicity, is not taken into consideration. In the present study, it is shown with cyclamate and its metabolite cyclohexlamine that when a battery of assays is used, assigning values to the prior probability between 0.1 and 0.9 has no significant effect on the predicted carcinogenicity. In the view of the fact that the performance of short-term tests is calibrated against known carcinogens and noncarcinogens, and since in the available data bases there is a preponderance of carcinogens, it may be argued that the estimation of sensitivities may be biased toward elevated values. It is shown, however, that when a battery of assays is used, assigning decreased values to the sensitivity does not result in significant effects on the predicted activity of the two test chemicals. Frequently, in the compilation of short-term results within a single assay, different laboratories may report varying results. Heretofore the "consensus result" was derived by majority rule. Because the variability in results may have biological significance, and in view of the fact that for a widely used sweetner one might be even more risk-adverse, a modification of Bayes's formula was derived to take these differences into consideration when calculating the probable carcinogenicity of cyclamate and its major metabolite.

Biotransformation↗