Integrating Uncertainty and Interindividual Variability in Environmental Risk Assessment

An integrated, quantitative approach to incorporating both uncertainty and interindividual variability into risk prediction models is described. Individual risk R is treated as a variable distributed in both an uncertainty dimension and a variability dimension, whereas population risk I (the number of additional cases caused by R) is purely uncertain. I is shown to follow a compound Poisson-binomial distribution, which in low-level risk contexts can often be approximated well by a corresponding compound Poisson distribution. The proposed analytic framework is illustrated with an application to cancer risk assessment for a California population exposed to 1,2-dibromo-3-chloropropane from ground water.     

Human Variability in Susceptibility to Toxic Chemicals— A Preliminary Analysis of Pharmacokinetic Data from Normal Volunteers

The tenfold "uncertainty" factor traditionally used to guard against human interindividual differences in susceptibility to toxicity is not based on human observations. To begin to build a basis for quantifying an important component of overall variability in susceptibility to toxicity, a data base has been constructed of individual measurements of key pharmacokinetic parameters for specific substances (mostly drugs) in groups of at least five healthy adults. 72 of the 101 data sets studied were positively skewed, indicating that the distributions are generally closer to expectations for log-normal distributions than for normal distributions. Measurements of interindividual variability in elimination half-lives, maximal blood concentrations, and AUC (area under the curve of blood concentration by time) have median values of log10 geometric standard deviations in the range of 0.11-0.145. For the median chemical, therefore, a tenfold difference in these pharmacokinetic parameters would correspond to 7-9 standard deviations in populations of normal healthy adults. For one relatively lipophilic chemical, however, interindividual variability in maximal blood concentration and AUC was 0.4--implying that a tenfold difference would correspond to only about 2.5 standard deviations for those parameters in the human population. The parameters studied to date are only components of overall susceptibility to toxic agents, and do not include contributions from variability in exposure- and response-determining parameters. The current study also implicitly excludes most human interindividual variability from age and illness. When these other sources of variability are included in an overall analysis of variability in susceptibility, it is likely that a tenfold difference will correspond to fewer standard deviations in the overall population, and correspondingly greater numbers of people at risk of toxicity.     

On Broadening Failure Rate Distributions in PRA Uncertainty Analyses

Several recent nuclear power plant probabilistic risk assessments (PRAs) have utilized broadened Reactor Safety Study (RSS) component failure rate population variability curves to compensate for such things as expert "overvaluation bias" in the estimates upon which the curves are based.
A simple two-components of variation empirical Bayes model is proposed for use in estimating the between-expert variability curve in the presence of such biases. Under certain conditions this curve is a population variability curve. Comparisons are made with the existing method.
The popular procedure appears to be generally much more conservative than the empirical Bayes method in removing such biases. In one case the broadened curve based on the popular method is more than two orders of magnitude broader than the empirical Bayes curve. In another case it is found that the maximum justifiable degree of broadening of the RSS curve is to increase α from 5% to 12%, which is significantly less than the 20% value recommended in the popular approach.     

Managing demand variability and operational effectiveness: case of lean improvement programmes and MRP planning integration

Although a lean focus is widely popular in general manufacturing environments, there are limited studies that empirically investigate how lean improvement programmes can be integrated with a material requirement planning (MRP) system. The aim of this research is to examine if the integration of lean improvement programmes with a MRP system has a positive effect on operational effectiveness when manufacturers are experiencing high levels of customer demand variability. Based on the contingency theory perspective and using data collected from the international manufacturing strategy survey (IMSS-V), a sample of 382 international manufacturing companies are first divided into two groups based on the degree of their customer demand fluctuation. Moderated hierarchical regression is then applied to each group to empirically test the research hypotheses. Statistical results suggest that operational effectiveness significantly improves when lean improvement programmes support MRP systems as manufacturers are experiencing high levels of fluctuations in demand.     

Geographical variability and network structure

In this paper, we explore the potential implications of geographical variability for the structure of social networks. Beginning with some basic simplifying assumptions, we derive a number of ways in which local network structure should be expected to vary across a region whose population is unevenly distributed. To examine the manner in which these effects would be expected to manifest given realistic population distributions, we then perform an exploratory simulation study that examines the features of large-scale interpersonal networks generated using block-level data from the 2000 U.S. Census. Using a stratified sample of micropolitan and metropolitan areas with populations ranging from approximately 1000 to 1,000,000 persons, we extrapolatively simulate network structure using spatial network models calibrated to two fairly proximate social relations. From this sample of simulated networks, we examine the effect of both within-location and between-location heterogeneity on a variety of structural properties. As we demonstrate, geographical variability produces large and distinctive features in the “social fabric” that overlies it; at the same time, however, many aggregate network properties can be fairly well-predicted from relatively simple spatial demographic variables. The impact of geographical variability is thus predicted to depend substantially on the type of network property being assessed, and on the spatial scale involved.     

How social ties transcend class boundaries? Network variability as tool for exploring occupational homophily

The research on social network analysis established the existence of class homophily, the tendency that personal networks are homogeneous in the class sense, as one of the governing patterns. This is explained via two main mechanisms: choice homophily and induced homophily. But the literature focused less on the question how can class boundaries be transgressed and what are the channels of class heterophily. This paper explores class heterophily on Croatian data acquired through position generator, which measures social capital (resources captured in social relations) by exploring the range of different occupational positions which are accessible to an individual (extensity index). Network variability is thereby taken as proxy for class composition of personal networks. The paper concludes that that political participation and sociability enable cross-class ties, since this offers an opportunity to meet and befriend people from all walks of life; and that people on the middle of the social hierarchy have the most diverse social networks. The hypotheses that social mobility can represent a vehicle for class heterophily; and that class heterophily is more pronounced in smaller settlements, where society networks show more overlap between social circles; were confirmed only partially, and require further investigation. These findings concern class boundaries related to the notion of choice homophily. As for induced homophily, the paper concludes that here too the boundaries are not watertight, as cultural omnivores have a wider range of class contacts.     

Temporal dynamics of inter-limb coordination in ice climbing revealed through change-point analysis of the geodesic mean of circular data

This study examined the temporal dynamics of the inter-limb angles of skilled and less skilled ice climbers to determine how they explored ice fall properties to adapt their coordination patterns during performance. We observed two circular time series corresponding to the upper- and lower-limbs of seven expert and eight inexperienced ice climbers. We analyzed these data through a multiple change-point analysis of the geodesic (or Fréchet) mean on the circle. Guided by the nature of the geodesic mean obtained by an optimization procedure, we extended the filtered derivative method, known to be computationally very cheap and fast, to circular data. Local estimation of the variability was assessed through the number of change-points computed via the filtered derivatives with p-value method for the time series and integrated squared error (ISE). Results of this change-point analysis did not reveal significant differences of the number of change-points between groups but indicated higher ISE that supported the existence of plateaux for beginners. These results emphasized higher local variability of limb angles for experts than for beginners suggesting greater dependence on the properties of the performance environment and adaptive behaviors in the former. Conversely, the lower local variance of limb angles assessed in beginners may reflect their independence of the environmental constraints, as they focused mainly on controlling body equilibrium.     

Sample Entropy Statistics and Testing for Order in Complex Physiological Signals

Sample Entropy (SampEn) statistics have provided insight into the amount of order present in several types of complex physiological time series, particularly the heart rate dynamics of premature infants. Very little, however, is known of SampEn's statistical properties and this has hindered strategies for optimization and significance testing. This article shows that SampEn statistics are asymptotically Gaussian under general conditions. A straightforward point estimate of the statistic's variance is developed and compared to empirical results obtained from complex surrogate data. Statistical tests are developed to quantify the amount and scale of order detected in a signal. These tests are used to show that significant order is, in fact, being detected in the heart rate dynamics of neonates, and to suggest strategies for optimizing the analysis parameters.     

Infants' discrimination of consonant contrasts in the presence and absence of talker variability

To learn speech-sound categories, infants must identify the acoustic dimensions that differentiate categories and selectively attend to them as opposed to irrelevant dimensions. Variability on irrelevant acoustic dimensions can aid formation of robust categories in infants through adults in tasks such as word learning (e.g., Rost and McMurray, 2009) or speech-sound learning (e.g., Lively et al., 1993). At the same time, variability sometimes overwhelms learners, interfering with learning and processing. Two prior studies (Kuhl & Miller, 1982; Jusczyk, Pisoni, & Mullennix, 1992) found that irrelevant variability sometimes impaired early sound discrimination. We asked whether variability would impair or facilitate discrimination for older infants, comparing 7.5-month-old infants' discrimination of an early acquired native contrast, /p/ vs. /b/ (in the word forms /pIm/ vs. /bIm/), in Experiment 1, with an acoustically subtle, non-native contrast, /n/ vs. /ŋ/ (in /nIm/ vs. /ŋIm/), in Experiment 2. Words were spoken by one or four talkers. Infants discriminated the native but not the non-native contrast, and there were no significant effects of talker condition. We discuss implications for theories of phonological learning and avenues for future research.