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PubMed2004

Uncertainty in visual processes predicts geometrical optical illusions.

It is proposed in this paper that many geometrical optical illusions, as well as illusory patterns due to motion signals in line drawings, are due to the statistics of visual computations. The interpretation of image patterns is preceded by a step where image features such as lines, intersections of lines, or local image movement must be derived. However, there are many sources of noise or uncertainty in the formation and processing of images, and they cause problems in the estimation of these features; in particular, they cause bias. As a result, the locations of features are perceived erroneously and the appearance of the patterns is altered. The bias occurs with any visual processing of line features; under average conditions it is not large enough to be noticeable, but illusory patterns are such that the bias is highly pronounced. Thus, the broader message of this paper is that there is a general uncertainty principle which governs the workings of vision systems, and optical illusions are an artifact of this principle.

Humans↗
PubMed2006

Metabolic engineering under uncertainty--II: analysis of yeast metabolism.

Yeast metabolism has been used extensively in scientific investigations and industrial applications. Understanding the properties of the yeast metabolic network is crucial, yet unaccomplished due to its high complexity, the different culture conditions, and the uncertainty associated with kinetic parameters. We recently developed a computational and mathematical framework using Monte Carlo method in which parameter uncertainty can be addressed through large-scale sampling procedure. This framework was applied on the compartmentalized central carbon pathways of Saccharomyces cerevisiae metabolism considering the growth environment of batch and chemostat reactor and integrating information from metabolic flux analysis. Statistical analysis of the results indicates that yeast cells growing in batch culture condition exhibit dramatically different control schemes from those growing in a chemostat. The difference is mainly due to the feedback introduced by the constraints of the chemostat. The control of the enzymes on the rates of the substrate uptake, product excretion, and cell growth and its practical implication are discussed. Clustering of the reaction steps according to the similarity of their responses to enzyme activity perturbations reveals functional coupling of metabolic reactions.

Bioreactors↗
PubMed2005

A molecular timescale for galliform birds accounting for uncertainty in time estimates and heterogeneity of rates of DNA substitutions across lineages and sites.

A recent molecular timescale for major lineages of the Galliformes indicated that Megapodiidae and possibly Cracidae, originated in the Cretaceous, while the remaining families originated in the Tertiary. This timescale was based on clock-like evolution in genetic and taxonomic partitions of mitochondrial ND2 and cyt b DNA sequences, and assumed that ordinal diversification of Galloanserae around 90 million years ago and imposed, whenever appropriate, minimum age constraints based on the fossil record. This approach is not ideal, as it did not account for uncertainty in estimating branch lengths and time, including the calibration time, and heterogeneity in the rate of DNA substitution among sites and in different lineages. Furthermore all the information available in the DNA sequences was not included, and may have been affected by stochastic error in individual gene partitions. Here, we present a follow-up analysis by estimating divergence times using a Bayesian framework that accounts for these possible sources of uncertainty. Our results based on combined and separate analyses of mitochondrial DNA sequences comprised of 1756 sites of 12S rDNA, ND2 and cyt b indicated that (1) Megapodiidae and Cracidae, and likely Odontophoridae, originated in the Cretaceous; (2) estimates based on concatenated genes are less affected by stochastic error among sites and less influenced by the phylogenetic signals of individual gene partitions, which are unequally distributed along the phylogenetic tree; and (3) the use of only an external molecular calibration results in lower estimation of most ingroup node ages. We also point out that galliform fossils may not be as useful for point calibrations as was previously suggested, but instead may be better employed as priors for the estimation of node ages under a Bayesian approach.

Animals↗
PubMed1997

Professional uncertainty and treatment choices by physical therapists.

OBJECTIVE: To determine patient, clinician, and practice setting characteristics associated with physical therapists' treatment choices in patients with knee, lumbar, and cervical impairments. DESIGN: Secondary analysis of data from the Focus on Therapeutic Outcomes (FOTO) database. SETTING: Data from 132 physical therapy practices owned by five United States outpatient rehabilitation companies. PATIENTS: The database contained information on 5,061 patients with knee, lumbar, or cervical impairments seen in these practices in 1993 and 1994 and agreeing to participate in data collection. Our sample consisted of 2,491 patients, treated by 462 physical therapists, who had complete data on the variables of interest. RESULTS: Physical therapists' treatment choices relied on factors other than the patient's clinical status when the impairment was likely to result in professional uncertainty as to diagnosis and consequences of treatments. For patients with spinal impairments, the clinical status of the patient was associated only with the choice of endurance exercises and modalities. Patient's clinical status was associated with every treatment type in patients with knee impairments. Educational level of the physical therapist, patient load, and payer were associated with a variety of treatment choices across the impairment types. CONCLUSION: In conditions of professional uncertainty, physical therapy practice may be influenced by many idiosyncratic factors.

Adolescent↗
PubMed2004

A simple numerical procedure for estimating nonlinear uncertainty propagation.

Accurately determining the effect of the propagation of uncertainty in nonlinear applications can be awkward and difficult. The Monte Carlo approach requires statistically significant numbers of function evaluations (typically 10(5) or more) and analytical methods are intractable for all but the simplest cases. This paper derives and demonstrates a method to estimate the propagation of uncertainty in nonlinear cases by representing the function in a piecewise fashion with straight line segments. The probability density function of the result can be calculated from the transformation of the line segments. The mean and confidence intervals of the result can then be calculated from the probability density function. For the special case of a normal distribution in the independent variable, calculation of the mean and confidence intervals requires evaluation of only the error function (erf). A simple example is presented to demonstrate the technique. Variations on the basic approach are presented and discussed.

Algorithms↗
PubMed2001

Uncertainty analysis for temperature prediction of biological bodies subject to randomly spatial heating.

An analytical solution to the Pennes bioheat transfer equation in three-dimensional geometry with practical hyperthermia boundary conditions and random heating was obtained in this paper. Uncertainties for the predicted temperatures of tissues due to approximate parameters were studied based on analyzing one-dimensional heat transfer in the biological bodies subject to a spatially decay heating. Contributions from each of the thermal parameters such as heat conductivity, blood perfusion rate, and metabolic rate of the tissues, the scattering coefficient and the surface power flux of the heating apparatus were compared and the uncertainty limit for temperature distribution in this case was estimated. The results are useful in a variety of clinical hyperthermia and biological thermal parameter measurement.

Body Temperature↗
PubMed2002

Numerical simulation of transit-time ultrasonic flowmeters: uncertainties due to flow profile and fluid turbulence.

Flowmeter measurement using the ultrasonic transit-time method is based on the apparent difference of the sound velocity in the flow direction and in the opposite direction. This method gives a flow velocity averaged along a particular acoustical path. To convert this path velocity to a velocity averaged over the entire cross-section of the flowing medium, the knowledge of the flow velocity profile is essential. However, the acoustical paths joining the two transducers are supposed to be straight and fluid turbulence phenomena are neglected. In this paper, we describe a numerical procedure to estimate the uncertainties due to these approximations in the case of fully developed turbulence. The ultrasonic propagation is modelled in 2-D moving inhomogeneous media via a ray tracing algorithm. Influence of mean profiles of temperature and velocity is studied on simple examples. Fluid temperature fluctuations and fluid velocity turbulence are considered in the stochastic framework to obtain average uncertainties on the measurements of the liquid flow rate.

Journal Article↗
PubMed2000

Resonant frequency method for the measurement and uncertainty analysis of acoustic and elastic properties

A resonant frequency method is proposed to determine the bar speed and the Poisson's ratio of a rod several meters long of the kind often used for manufacturing power sonic transducers and mechanical horns in mass production. This method is shown to be robust in a field test and with high resolution for estimation of the bar speed. The uncertainty (standard deviation/average) for the bar speed and the Poisson's ratio can be reduced by appropriately selecting the mode number pairs and increasing the mode number. In this study, the uncertainties of the bar speed and Poisson's ratio are less than 0.043% and 2.9%, respectively. The resonant frequency method is verified by comparing the dilatational wave speeds calculated by elastic theory with those from experiments, the difference between them being less than 0.17%.

Journal Article↗
PubMed2001

Set-size and chromatic uncertainty in an accuracy visual search task.

Thresholds for chromatic differences were measured in a simple visual search task in which the target differed from the distractors in chromaticity only. In Experiment 1, the spatial separation between stimulus elements was varied. Slopes of threshold versus set-size (2-16) for elements in close proximity were somewhat elevated, suggesting non-independence of the stimulus elements. In Experiment 2, chromatic uncertainty was introduced to increase the attentional load beyond that accomplished with the set-size manipulation. The results were accounted for by a model assuming no limit in attention capacity. Furthermore, chromatic uncertainty was successfully modeled as a simple increase in the number of monitored signals.

Adult↗
PubMed2002

Contrast discrimination with and without spatial uncertainty.

The main purpose of these experiments was to examine in detail how successfully the uncertainty reduction explanation accounts for the effects of spatial cues in a temporal forced-choice contrast discrimination task in which any one of four well-separated Gabor patches is incremented. In preliminary experiments, it was shown that in the absence of uncorrelated contrast jitter, observers could use either of at least two different decision strategies, whereas in the presence of random contrast jitter, their response was based on the largest contrast value in the two intervals of a trial. Independent spatial cues were used in each interval to minimize the likelihood of eye movement artifacts. Cues either preceded each stimulus presentation by 100 ms, or were coincident with it. Precues were only slightly more effective than simultaneous cues, and either of them improved performance nearly as much as could be expected from the uncertainty reduction account of spatial attention.

Attention↗
PubMed2002

Carbon storage in Amazonia during the last glacial maximum: secondary data and uncertainties.

The Amazonian forest is, due to its great size, carbon storage capacity and present-day variability in carbon uptake and release, an important component of the global carbon cycle. Paleo-environmental reconstruction is difficult for Amazonia due to the scarcity of primary palynological data and the mis-interpretation of some secondary data. Studies of lacustrine sediment records have shown that Amazonia has known periods in which the climate was drier than it is today. However, not all geomorphological features such as dunes, and slope erosion, which are thought to indicate rainforest regression, date from the time of the Late Glacial Maximum (LGM) and these features do not necessarily correspond to episodes of forest regression. There is also uncertainty concerning LGM carbon storage due to rainforest soils and biomass estimates. Soil carbon content may decrease moderately during the LGM, whereas rainforest biomass may change considerably in response to changes in the global environment. Biomass per unit area in Amazonia has probably been reduced by the cumulative effects of low CO2 concentration, a drier climate and lower temperatures. As few paleo-vegetation data are available, there is considerable uncertainty concerning the amount of carbon stored in Amazonia during the LGM, which may have corresponded to 44-94% of the carbon currently stored in biomass and soils.

Biomass↗
PubMed2001

Quantifying uncertainty of the reference sampling procedure used at Dornach under different soil conditions.

The reference sampling procedure, used in the CEEM soil project on a single test area at Dornach, had been applied under different soil conditions in a sampling proficiency test and in the Swiss national soil-monitoring network related to pollution (NABO). Methods of analysis of variance (ANOVA) were used to quantify sampling and analytical uncertainty. The soil sampling procedure and the chemical analysis were considered as two parts of the same measurement process and the so-called 'top-down' approach was used to quantify their combined contribution to the uncertainty. By this approach a systematic error of one sampler or of one laboratory becomes a random error when assessed as part of a multi-sampler or multi-laboratory comparison.

Analysis of Variance↗
PubMed2001

Uncertainty, variability and sensitivity analysis applied to the RAGENA model of radon generation, entry and accumulation indoors.

The application of a radon model is useful to understand the processes that drive the radon gas behaviour from its sources to its accumulation indoors. Since in a given inhabited house the detailed knowledge of the values of all the parameters that affect indoor radon levels is not available, the response of the model has to be explored in a reference site in which all the parameters are supposed to be known. We call this site the reference configuration. In this paper we report on the procedure followed to carry out uncertainty, sensitivity and variability analysis of the model response for a reference configuration that corresponds to a single family multi-zone house. We have obtained from the uncertainty analysis that, assuming a normal distribution of all the input parameters with a 10% relative standard deviation (R.S.D.), the model outputs present a R.S.D. in the range 17-22%. The sensitivity analysis reflects, in general, a good behaviour of the model, in the sense that its response describes a realistic behaviour of the system. The variability analysis has shown that the model is applicable to a wide range of situations, and that the most relevant parameters for the reference configuration are: the soil gas-permeability (obtained from the mean soil grain diameter); the ventilation rate of the rooms; the air-exchange rate between the basement and room 2; the soil-indoor pressure difference; the open area; and the concrete radium content.

Journal Article↗
PubMed2006

Issues of scale and uncertainty in the global remote sensing of disease.

Scale and uncertainty are important issues for the global prediction of disease. Disease mapping over the entire surface of the Earth usually involves the use of remotely sensed imagery to provide environmental covariates of disease risk or disease vector density. It further implies that the spatial resolution of such imagery is relatively coarse (e.g., 8 or 1km). Use of a coarse spatial resolution limits the information that can be extracted from imagery and has important effects on the results of epidemiological analyses. This paper discusses geostatistical models for (i) characterizing the scale(s) of spatial variation in data and (ii) changing the scale of measurement of both the data and the geostatistical model. Uncertainty is introduced, highlighting the fact that most epidemiologists are interested in accuracy, aspects of which can be estimated with measurable quantities. This paper emphasizes the distinction between data- and model-based methods of accuracy assessment and gives examples of both. The key problem of validating global maps is considered.

Animals↗
PubMed2001

Uncertainties in the reference dose for methylmercury.

This paper critically examines the National Academy of Sciences and the National Research Council report on the toxicological effects of methyl mercury and the recently published US Environmental Protection Agency Reference Dose (RfD) for Methylmercury. Particular scrutiny is placed on the choice of the critical study and the underlining assumptions utilized in the selection of specific uncertainty factors (UFs) and the rationale for using a less-than-default factor of 10. The UFs that were utilized or considered by other agencies and organizations are also critically examined, explained and compared to one another. Based on these analyses, the authors suggest research that could be performed that would ameliorate the uncertainty of choosing a more precise partial UFor that may even provide completeness of database to allow for selecting of a UF for unity, thus improving the precision of the current published RfD.

Animals↗
PubMed1998

The effect of uncertainty on the demand for medical care, health capital and wealth.

We analyze the effect of the uncertainty of the incidence of illness on the demand for medical care and on the accumulation of health capital and wealth over the retirement years. We use a simplified version of a dynamic Grossman household production model to characterize patterns of an individual's precautionary behavior. Elderly individuals respond to uncertainty by smoothing their expected utility over time by making specific patterns of purchases of medical care and consumption. We examine these patterns for individuals with different degrees of risk aversion.

Aged↗
PubMed1998

Combining probabilistic and subjective assessments of error to provide realistic appraisals of demographic forecast uncertainty: Alho's approach.

"With increasing interest in forecast uncertainty, there is an evolving concern with assessing the degree of certainty we can attach to uncertainty itself. This concern is the subject of recent work by Juha Alho.... I examine [his] approach systematically and draw general conclusions about its efficacy. Suggestions for improvement are made."

Evaluation Studies as Topic↗
PubMed2001

Assessing the natural attenuation of organic contaminants in aquifers using plume-scale electron and carbon balances: model development with analysis of uncertainty and parameter sensitivity.

A quantitative methodology is described for the field-scale performance assessment of natural attenuation using plume-scale electron and carbon balances. This provides a practical framework for the calculation of global mass balances for contaminant plumes, using mass inputs from the plume source, background groundwater and plume residuals in a simplified box model. Biodegradation processes and reactions included in the analysis are identified from electron acceptors, electron donors and degradation products present in these inputs. Parameter values used in the model are obtained from data acquired during typical site investigation and groundwater monitoring studies for natural attenuation schemes. The approach is evaluated for a UK Permo-Triassic Sandstone aquifer contaminated with a plume of phenolic compounds. Uncertainty in the model predictions and sensitivity to parameter values was assessed by probabilistic modelling using Monte Carlo methods. Sensitivity analyses were compared for different input parameter probability distributions and a base case using fixed parameter values, using an identical conceptual model and data set. Results show that consumption of oxidants by biodegradation is approximately balanced by the production of CH4 and total dissolved inorganic carbon (TDIC) which is conserved in the plume. Under this condition, either the plume electron or carbon balance can be used to determine contaminant mass loss, which is equivalent to only 4% of the estimated source term. This corresponds to a first order, plume-averaged, half-life of > 800 years. The electron balance is particularly sensitive to uncertainty in the source term and dispersive inputs. Reliable historical information on contaminant spillages and detailed site investigation are necessary to accurately characterise the source term. The dispersive influx is sensitive to variability in the plume mixing zone width. Consumption of aqueous oxidants greatly exceeds that of mineral oxidants in the plume, but electron acceptor supply is insufficient to meet the electron donor demand and the plume will grow. The aquifer potential for degradation of these contaminants is limited by high contaminant concentrations and the supply of bioavailable electron acceptors. Natural attenuation will increase only after increased transport and dilution.

Biodegradation, Environmental↗