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At least 613 records · Page 34Linked to original sources
PubMed2001

Influences of parameter uncertainties within the ICRP 66 respiratory tract model: particle deposition.

Risk assessment associated with the inhalation of radioactive aerosols requires as an initial step the determination of particle deposition within the various anatomic regions of the respiratory tract. The model outlined in ICRP Publication 66 represents to date one of the most complete overall descriptions of not only particle deposition, but of particle clearance and local radiation dosimetry of lung tissues. In this study, a systematic review of the deposition component within the ICRP 66 respiratory tract model was conducted in which probability density functions were assigned to all input parameters. These distributions were subsequently incorporated within a computer code LUDUC (LUng Dose Uncertainty Code) in which Latin hypercube sampling techniques are used to generate multiple (e.g., 1,000) sets of input vectors (i.e., trials) for all of the model parameters needed to assess particle deposition within the extrathoracic (anterior and posterior), bronchial, bronchiolar, and alveolar-interstitial regions of the ICRP 66 respiratory tract model. Particle deposition values for the various trial simulations were shown to be well described by lognormal probability distributions. Geometric mean deposition fractions from LUDUC were found to be within approximately +/- 10% of the single-value estimates from the LUDEP computer code for each anatomic region and for particle diameters ranging from 0.001 to 50 microm. In all regions of the respiratory tract, LUDUC simulations for an adult male at light exertion show that uncertainties in particle deposition fractions are distributed only over a range of about a factor of approximately 2-4 for particle sizes between 0.005 to 0.2 microm. Below 0.005 microm, uncertainties increase only for deposition within the alveolar region. At particle sizes exceeding 1 microm, uncertainties in the deposition fraction within the extrathoracic regions are relatively small, but approach a factor of 20 for deposition in the bronchial region. Deposition fractions for particles above 1 microm become very uncertain within the deeper regions of the lungs (bronchiolar and alveolar-interstitial).

Body Height↗
PubMed2003

Uncertainty in transport factors used to calculate historical dose from 131I releases at the Savannah River Site.

During the 1950's, atmospheric release of 131I was one of the largest contributors to offsite dose at the Savannah River Site. Computer models used to estimate offsite dose involve the use of many parameters with wide ranges of uncertainty. The overall uncertainty in dose can be estimated by propagating the uncertainty of each parameter through the model. A major component of the calculational model can be solved for a given release scenario and condensed into a transport factor, which, when multiplied by the air concentration (or deposition) and the appropriate dose conversion factor, can be used to estimate a specific pathway dose. Uncertainties are estimated for the period of 1955-1961 for all parameters contributing to the 131I transport factor for each pathway. The overall transport factor including all pathways has ranges characterized by maximum-to-minimum ratios (95% to 5%) of about 40. The parameter shown to have the greatest impact on the transport factor calculation was the fraction of elemental iodine released.

Air Pollutants, Radioactive↗
PubMed2003

Influences of parameter uncertainties within the ICRP-66 respiratory tract model: a parameter sensitivity analysis.

An important aspect in model uncertainty analysis is the evaluation of input parameter sensitivities with respect to model outcomes. In previous publications, parameter uncertainties were examined for the ICRP-66 respiratory tract model. The studies were aided by the development and use of a computer code LUDUC (Lung Dose Uncertainty Code) which allows probabilities density functions to be specified for all ICRP-66 model input parameters. These density functions are sampled using Latin hypercube techniques with values subsequently propagated through the ICRP-66 model. In the present study, LUDUC has been used to perform a detailed parameter sensitivity analysis of the ICRP-66 model using input parameter density functions specified in previously published articles. The results suggest that most of the variability in the dose to a given target region is explained by only a few input parameters. For example, for particle diameters between 0.1 and 50 microm, about 50% of the variability in the total lung dose (weighted sum of target tissue doses) for 239PuO2 is due to variability in the dose to the alveolar-interstitial (AI) region. In turn, almost 90% of the variability in the dose to the AI region is attributable to uncertainties in only four parameters in the model: the ventilation rate, the AI deposition fraction, the clearance rate constant for slow-phase absorption of deposited material to the blood, and the clearance rate constant for particle transport from the AI2 to bb1 compartment. A general conclusion is that many input parameters do not significantly influence variability in final doses. As a result, future research can focus on improving density functions for those input variables that contribute the most to variability in final dose values.

Absorption↗
PubMed2001

A new look at nurse burnout: the effects of environmental uncertainty and social climate.

As healthcare organizations deal with changes in the external environment, uncertainty in the internal environment is created. The purpose of this study was to explore the relationships among environmental uncertainty, social climate, and burnout among staff nurses. Multiple regression analysis was used to explore relationships among study variables. Perceived environmental uncertainty predicted burnout among staff nurses, although there was no significant relationship between burnout and objective measures of unit activity. The social climate of the workplace was negatively associated with burnout. The authors concluded that social networks are important during times of change and uncertainty in the work environment; in other words, a supportive workplace can protect against burnout.

Adaptation, Psychological↗
PubMedDate not supplied

Moderators of an uncertainty management intervention: for men with localized prostate cancer.

BACKGROUND: The effectiveness of psycho-educational interventions for cancer patients is well documented, but less is known about moderating characteristics that determine which subgroups of patients are most likely to benefit. OBJECTIVES: The aim of this study was to determine whether certain individual characteristics of African-American and White men with localized prostate cancer moderated the effects of a psycho-educational Uncertainty Management Intervention on the outcomes of cancer knowledge and patient-provider communication METHODS: Men were blocked by ethnicity and randomly assigned to one of three conditions: Uncertainty Management Intervention provided to the patient only, Uncertainty Management Intervention supplemented by delivery to the patient and family member, or usual care. The individual characteristics explored were education, sources for information, and intrinsic and extrinsic religiosity. RESULTS: Using repeated measures multivariate analysis of variance, findings indicated that there were no significant moderator effects for intrinsic religiosity on any of the outcomes. Lower level of education was a significant moderator for improvement in cancer knowledge. For the outcome of patient-provider communication, fewer sources for cancer information was a significant moderator for the amount told the patient by the nurse and other staff. Less extrinsic religiosity was a significant moderator for three areas of patient provider communication. The three areas are the amount (a) the physician tells the patient; (b) the patient helps with planning treatment; and (c) the patient tells the physician. CONCLUSIONS: Testing for moderator effects provides important information regarding beneficiaries of interventions. In the current study, men's levels of education, amount of sources for information, and extrinsic religiosity influenced the efficacy of the Uncertainty Management Intervention on important outcomes.

Black or African American↗
PubMed1995

Effect of location and orientation uncertainty on r.m.s. contrast sensitivity with and without spatial noise in peripheral and foveal vision.

PURPOSE: We studied the effect of spatial location and orientation uncertainty on r.m.s. contrast sensitivity with and without external spatial noise in peripheral and foveal vision. METHODS: In the first experiment we used a small circular cosine grating with randomized location embedded in spatial noise and exposed for 33 to 533 ms in peripheral vision. In the second experiment, performed with and without noise, we varied the randomization range of stimulus location in a foveal search task with free eye movements and an unlimited exposure time. In the third experiment we used a vertical cosine grating exposed for 500 ms and varied the randomization range of aperture orientation in the fovea with and without noise. RESULTS: Uncertainty of spatial location had no effect on r.m.s. contrast sensitivity in the periphery or fovea. However, sensitivity decreased with increasing randomization range of aperture orientation in the fovea. CONCLUSIONS: Uncertainty of spatial location had no effect because the accuracy of positional information is inherently poor in peripheral vision, whereas in the fovea the effect of location uncertainty was compensated for by searching eye movements. Randomization of aperture orientation reduced contrast sensitivity in the fovea because in this case the effect of randomization could not be compensated for.

Adult↗
PubMed2003

Decision analysis and clinical uncertainty.

Decision analysis is a tool to aid decision-making in the face of uncertainty. Typically, clinical decision-making involves the selection of one or more therapeutic alternatives when the outcome of that decision cannot fully be known at the time the decision must be made. Uncertainty derives from imperfections in diagnostic testing, uncertainty about the natural history of disease, the random nature of iatrogenic complications, and the impact of patient-specific factors or comorbid conditions. Decision analysis seeks to optimize the expected outcome of a decision, incorporating the probabilistic nature of this uncertainty. Decision analysis is applied here to a common problem in intensive care units-the treatment of suspected ventilator-associated pneumonia. Recent applications of decision analysis in the pediatric literature are also used to illustrate the scope and limitations of this tool in clinical practice.

Decision Support Techniques↗
PubMed2005

Uncertainties in electron-absorbed fractions and lung doses from inhaled beta-emitters.

The computer code LUDUC (Lung Dose Uncertainty Code), developed at the University of Florida, was originally used to investigate the range of potential doses from the inhalation of either plutonium or uranium oxides. The code employs the ICRP Publication 66 Human Respiratory Tract model; however, rather than using simple point estimates for each of the model parameters associated with particle deposition, clearance, and lung-tissue dosimetry, probability density functions are ascribed to these parameters based upon detailed literature review. These distributions are subsequently sampled within LUDUC using Latin hypercube sampling techniques to generate multiple (e.g., approximately 1,000) sets of input vectors (i.e., trials), each yielding a unique estimate of lung dose. In the present study, the dosimetry component of the ICRP-66 model within LUDUC has been extended to explicitly consider variations in the beta particle absorbed fraction due to corresponding uncertainties and biological variabilities in both source and target tissue depths and thicknesses within the bronchi and bronchioles of the thoracic airways. Example dose distributions are given for the inhalation of absorption Type S compounds of 90Sr (Tmax = 546 keV) and 90Y (Tmax = 2,284 keV) as a function of particle size. Over the particle size range of 0.001 to 1 microm, estimates of total lung dose vary by a factor of 10 for 90Sr particles and by a factor of 4 to 10 for 90Y particles. As the particle size increases to 10 microm, dose uncertainties reach a factor of 100 for both radionuclides. In comparisons to identical exposures scenarios run by the LUDEP 2.0 code, Reference Man doses for inhaled beta-emitters were shown to provide slightly conservative estimates of lung dose compared to those in this study where uncertainties in lung airway histology are considered.

Administration, Inhalation↗
PubMed2006

Uncertainties in aerosol deposition within the respiratory tract using the icrp 66 model: a study in workers.

This study estimates uncertainties in aerosol deposition within the main regions of the human respiratory tract calculated using the ICRP 66 model. Uniform, triangular, normal, or lognormal distributions were assigned to the model parameters, which involve physical properties of aerosols, their inhalability, their thermo- and aerodynamic deposition efficiencies, and the anatomy, physiology, and exertion level of the individuals. Calculations were performed over a range of aerosol sizes from 0.01 to 50 mum. Monodispersed aerosols were characterized by their aerodynamic diameter (dae). Polydispersed aerosols were characterized by their activity median aerodynamic diameters (AMADs) and the geometric standard deviation (GSD) in diameter. Lognormal distributions of particle deposition were generally observed with low GSD (< 2). The highest uncertainties were observed within the deep lung for the smallest and the largest aerosol sizes, which were mainly due either to particle density or to aerodynamic deposition efficiencies and anatomical and physiological variability, respectively. In the case of diameters larger than 5 mum, uncertainties in the deep lung deposition were much more important for monodispersed than for polydispersed aerosols. This was explained both by the size distribution of the deposited aerosol, the median of which corresponded to a maximal dae value of about 7 and 5 in bronchioles and alveoli, respectively, and by the absence of deposition, which occurs for dae equal to or larger than 50 mum, depending on the exertion level. Thus, in the range of AMADs considered, for the four default workers proposed by ICRP 66, uncertainties in aerosol deposition remain low, with GSD smaller than 3.

Aerosols↗
PubMed2002

Uncertainty and conservatism in assessing environmental impact under paragraph 316(b): lessons from the Hudson River case.

Initially, regulation of cooling water intakes under paragraph 316(b) was extremely conservative due to the rapid increase predicted for generating capacity, and to the uncertainty associated with our knowledge of the effects of entrainment and impingement. The uncertainty arose from four main sources: estimation of direct plant effects; understanding of population regulatory processes; measurement of population parameters; and predictability of future conditions. Over the last quarter-century, the uncertainty from the first three sources has been substantially reduced, and analytical techniques exist to deal with the fourth. In addition, the dire predictions initially made for some water bodies have not been realized, demonstrating that populations can successfully withstand power plant impacts. This reduced uncertainty has resulted in less conservative regulation in some, but not all venues. New York appears to be taking a more conservative approach to cooling water intakes. The conservative approach is not based on regulations, but in a philosophy that power plant mortality is an illegitimate use of the aquatic resources. This philosophy may simplify permitting decisions, but it does not further the development of a science-based definition of adverse environmental impact.

Animals↗
PubMedDate not supplied

Point-based probabilistic surfaces to show surface uncertainty.

Efficient and informative visualization of surfaces with uncertainties is an important topic with many applications in science and engineering. In these applications, the correct course of action may depend not only on the location of a boundary, but on the precision with which that location is known. Examples include environmental pollution borderline detection, oil basin edge characterization, or discrimination between cancerous and healthy tissue in medicine. This paper presents a method for producing visualizations of surfaces with uncertainties using points as display primitives. Our approach is to render the surface as a collection of points and to displace each point from its original location along the surface normal by an amount proportional to the uncertainty at that point. This approaoh can be used in combination with other techniques such as pseudocoloring to produce efficient and revealing visualizations. The basic approach is sufficiently flexible to allow natural extensions; we show incorporation of expressive modulation of opacity, change of the stroke primitive, and addition of an underlying polygonal model. The method is used to visualize real and simulated tumor formations with uncertainty of tumor boundaries. The point-based technique is compared to pseudocoloring for a position estimation task in a preliminary user study.

Algorithms↗
PubMed2002

Variability and uncertainty meet risk management and risk communication.

In the past decade, the use of probabilistic risk analysis techniques to quantitatively address variability and uncertainty in risks increased in popularity as recommended by the 1994 National Research Council that wrote Science and Judgment in Risk Assessment. Under the 1996 Food Quality Protection Act, for example, the U.S. EPA supported the development of tools that produce distributions of risk demonstrating the variability and/or uncertainty in the results. This paradigm shift away from the use of point estimates creates new challenges for risk managers, who now struggle with decisions about how to use distributions in decision making. The challenges for risk communication, however, have only been minimally explored. This presentation uses the case studies of variability in the risks of dying on the ground from a crashing airplane and from the deployment of motor vehicle airbags to demonstrate how better characterization of variability and uncertainty in the risk assessment lead to better risk communication. Analogies to food safety and environmental risks are also discussed. This presentation demonstrates that probabilistic risk assessment has an impact on both risk management and risk communication, and highlights remaining research issues associated with using improved sensitivity and uncertainty analyses in risk assessment.

Communication↗
PubMed1982

The process of neutralisation and the uncertainties of cystic fibrosis.

The epidemiological uncertainties of a terminal illness would seem to prohibit the ritual exchange of faith and hope between patient and medical personnel. However, after interviews with people involved in cystic fibrosis networks, I argue that there exists a process of neutralising five epidemiological uncertainties of this disease: (1) aetiology; (2) genetics; (3) treatment; (4) societal reaction and (5) life expectancy. This process consists of five techniques corresponding to these five epidemiological uncertainties, respectively: (1) the modification of question; (2) the promise of research; (3) the uniqueness of each case; (4) the comparison with others and (5) the lack of an alternative to therapy. Neutralising the epidemiological uncertainties of this disease serves to support the swaying edifice of faith and hope and enables the people within the network to devote themselves to compliance with cystic fibrosis therapy.

Adolescent↗
PubMed2005

Uncertainty distribution associated with estimating a proportion in microbial risk assessment.

The uncertainty associated with estimates should be taken into account in quantitative risk assessment. Each input's uncertainty can be characterized through a probabilistic distribution for use under Monte Carlo simulations. In this study, the sampling uncertainty associated with estimating a low proportion on the basis of a small sample size was considered. A common application in microbial risk assessment is the estimation of a prevalence, proportion of contaminated food products, on the basis of few tested units. Three Bayesian approaches (based on beta(0, 0), beta(1/2, 1/2), and beta(l, 1)) and one frequentist approach (based on the frequentist confidence distribution) were compared and evaluated on the basis of simulations. For small samples, we demonstrated some differences between the four tested methods. We concluded that the better method depends on the true proportion of contaminated products, which is by definition unknown in common practice. When no prior information is available, we recommend the beta (1/2, 1/2) prior or the confidence distribution. To illustrate the importance of these differences, the four methods were used in an applied example. We performed two-dimensional Monte Carlo simulations to estimate the proportion of cold smoked salmon packs contaminated by Listeria monocytogenes, one dimension representing within-factory uncertainty, modeled by each of the four studied methods, and the other dimension representing variability between companies.

Algorithms↗
PubMed2005

Paternal reactions to a child with epilepsy: uncertainty, coping strategies, and depression.

AIM: This paper reports a study examining the stress that fathers experience when caring for a child with epilepsy. BACKGROUND: A seizure, which is frightening and potentially damaging, creates uncertainty about its possible effects and threatens the integrity of family systems. In the Chinese social context, epilepsy is stereotyped 'sudden craziness' of people and affected family feel shamed by the diagnosis. When a child has epilepsy, the stereotype of epilepsy affects the family experience in terms of stress and their coping process. Few studies have focused on how a father with an ill child adapts to family stress. METHODS: This study was based on the resiliency model of family stress, adjustment, and adaptation, and was designed to examine the relationships among fathers' uncertainty, coping strategies, and depression. From three teaching hospitals in Taiwan, 210 fathers were recruited. A pilot study was conducted to establish the reliability and face validity of the Chinese language version of the Coping Health Inventory for Parents. FINDINGS: Results showed that paternal uncertainty was negatively associated with the total Coping Health Inventory for Parents score for family coping patterns for factors I, II, and III. Uncertainty and coping strategies for factors II and III were indicators of paternal depression and accounted for 10.3% of the total variance. CONCLUSIONS: The results give insight into the unique family stress that fathers experience as a result of the interaction between the social context of a child with epilepsy and the family's coping patterns. They also suggest ways to improve family-centred nursing interventions to help parents establish effective caring patterns to manage the family stress.

Adaptation, Psychological↗
PubMed2006

An fMRI examination of developmental differences in the neural correlates of uncertainty and decision-making.

BACKGROUND: Maturation of prefrontal circuits during adolescence contributes to the development of cognitive processes such as decision-making. Recent theories suggest that these neural changes also play a role in the shift from generalized anxiety disorder (GAD) to depression that often occurs during this developmental period. Cognitive models of the development of GAD highlight the role of intolerance of uncertainty (IU), which can be characterized behaviorally by impairments in decision-making. The present study examines potential developmental differences in frontal regions associated with uncertain decision-making, and tests the impact of IU on these circuits. METHODS: Twelve healthy adults (ages 19-36) and 12 healthy adolescents (ages 13-17) completed a decision-making task with conditions of varied uncertainty while fMRI scans were acquired. They also completed measures of worry and IU, and a questionnaire about their levels of anxiety and certainty during the task. RESULTS: Combined group analyses demonstrated significant linear effects of uncertainty on activity within anterior cingulate cortex (ACC). Region of interest (ROI)-based analysis found a significant interaction of group and IU ratings in ACC. Increased IU was associated with robust linear increases in ACC activity only in adolescents. An ROI analysis of feedback-related processing found that adolescents demonstrated greater activation during incorrect trials relative to correct trials, while the adults showed no difference in neural activity associated with incorrect and correct feedback. CONCLUSIONS: This decision-making task was shown to be effective at eliciting uncertainty-related ACC activity in adults and adolescents. Further, IU impacts ACC activity in adolescents during uncertain decision-making, providing preliminary support for a developmental model of GAD.

Adolescent↗
PubMed2006

Uncertainty analysis for regional-scale reserve selection.

Methods for reserve selection and conservation planning often ignore uncertainty. For example, presence-absence observations and predictions of habitat models are used as inputs but commonly assumed to be without error. We applied information-gap decision theory to develop uncertainty analysis methods for reserve selection. Our proposed method seeks a solution that is robust in achieving a given conservation target, despite uncertainty in the data. We maximized robustness in reserve selection through a novel method, "distribution discounting," in which the site- and species-specific measure of conservation value (related to species-specific occupancy probabilities) was penalized by an error measure (in our study, related to accuracy of statistical prediction). Because distribution discounting can be implemented as a modification of input files, it is a computationally efficient solution for implementing uncertainty analysis into reserve selection. Thus, the method is particularly useful for high-dimensional decision problems characteristic of regional conservation assessment. We implemented distribution discounting in the zonation reserve-selection algorithm that produces a hierarchy of conservation priorities throughout the landscape. We applied it to reserve selection for seven priority fauna in a landscape in New South Wales, Australia. The distribution discounting method can be easily adapted for use with different kinds of data (e.g., probability of occurrence or abundance) and different landscape descriptions (grid or patch based) and incorporated into other reserve-selection algorithms and software.

Algorithms↗
PubMed1998

Uncertainty and variability analysis in multiplicative risk models.

Currently, there is a trend away from the use of single (often conservative) estimates of risk to summarize the results of risk analyses in favor of stochastic methods which provide a more complete characterization of risk. The use of such stochastic methods leads to a distribution of possible values of risk, taking into account both uncertainty and variability in all of the factors affecting risk. In this article, we propose a general framework for the analysis of uncertainty and variability for use in the commonly encountered case of multireplicative risk models, in which risk may be expressed as a product of two or more risk factors. Our analytical methods facilitate the evaluation of overall uncertainty and variability in risk assessment, as well as the contributions of individual risk factors to both uncertainty and variability which is cumbersome using Monte Carlo methods. The use of these methods is illustrated in the analysis of potential cancer risks due to the ingestion of radon in drinking water.

Analysis of Variance↗