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Urban-rural migration: uncertainty and the effect of a change in the minimum wage.

"This paper extends the neoclassical, Harris-Todaro model of urban-rural migration to the case of production uncertainty in the agricultural sector. A unique feature of the Harris-Todaro model is an exogenously determined minimum wage in the urban sector that exceeds the rural wage. Migration occurs until the rural wage equals the expected urban wage ('expected' due to employment uncertainty). The effects of a change in the minimum wage upon regional outputs, resource allocation, factor rewards, expected profits, and expected national income are explored, and the influence of production uncertainty upon the obtained results are delineated." The geographical focus is on developing countries.

Agriculture↗

[Measurement uncertainty in drinking water analysis. Conclusions from interlaboratory tests].

The problems of measurement uncertainty, its estimation and the connection with the requirements of the drinking water legislation on the analytical methods are described. The difficulties with these requirements are shown. On the basis of numerous interlaboratory test data, the concentration dependences of the reproducibility standard deviation for 75 drinking water parameters were calculated using a variance function described in DIN 38402-45. From this function means of standard deviation at the legal limit could be calculated with high confidence. These values are compared with the requirements of the legislation. These data can be used on the one hand for the estimation of uncertainties in the laboratories or the plausibility check of uncertainties already estimated. On the other hand these data can be helpful for deriving an official interpretation or creating new requirements for the drinking water legislation.

European Union↗

Total uncertainty budget calculation for the determination of mercury in incineration ash (BCR 176R) by atomic fluorescence spectrometry.

The mercury mass fraction has been determined by atomic fluorescence spectrometry (AFS) in the framework of the project "Certification of a reference material (trace elements in fly ash) in replacement of BCR CRM 176". Calculation of the uncertainty budget, as described in this manuscript, emphasizes a practical and realistic approach to estimation of uncertainty components on the basis of statistical assumptions. GUM Workbench software was used, and resulted in a mercury mass fraction of 1.58+/-0.11 mg kg(-1) (with coverage factor k=2.2, 95% probability) related to dry mass, submitted in the certification exercise. The calculated total uncertainty budget applies to analogous samples analyzed by this procedure.

Journal Article↗

The uncertainty of atomic mass fractions in a molecule.

The mass fraction of a certain atom species in a molecule is needed for the calculation of the result of some chemical analyses. Common examples are gravimetric determinations (e.g., the sulfur concentration in a sample that can be obtained from the mass of precipitated barium sulfate). A similar problem is encountered when a reference solution of an ion is prepared by dissolution of a salt. This paper presents how the uncertainty of the mass fraction is calculated from the uncertainties of the atomic weights as published by IUPAC. The value is needed for the determination of the combined standard uncertainty of the analysis. Some calculated examples illustrate the mathematical considerations presented in the paper.

Journal Article↗

Measurement uncertainty of thermodynamic data.

Thermodynamic quantities of chemical reactions are commonly derived from experimental data obtained by chemical analysis. The accuracy of the evaluated thermodynamic quantities is limited by the measurement uncertainty of the analytical techniques applied. Straightforward transfer of metrological rules established for determination of single analytes to the more complex process of evaluating values of thermodynamic quantities is not possible. Computer-intensive statistical methods and Monte Carlo techniques are shown to enable integration of existing metrological concepts. An initial stage of the integration of both concepts is presented, taking solubility data for Am(III) in carbonate media as an illustrative example. A cause and effect diagram is created as a means of identification of sources of uncertainty. The uncertainties are used in a resampling-based Monte Carlo study to produce a probability distribution of the value of a quantity.

Journal Article↗

Estimation of the minimum uncertainty of DNA concentration in a genetically modified maize sample candidate certified reference material.

Homogeneity testing and the determination of minimum sample mass are an important part of the certification of reference materials. The smallest theoretically achievable uncertainty of certified concentration values is limited by the concentration distribution of analyte in the different particle size fractions of powdered biological samples. This might be of special importance if the reference material is prepared by dry mixing, a dilution technique which is used for the production of the new and third generation of genetically modified (GMO) plant certified reference materials. For the production of dry mixed PMON 810 maize reference material a computer program was developed to calculate the theoretically smallest uncertainty for a selected sample intake. This model was used to compare three differently milled maize samples, and the effect of dilution on the uncertainty of the DNA content of GMO maize was estimated as well. In the case of a 50-mg sample mass the lowest achievable standard deviation was 2% for the sample containing 0.1% GMO and the minimum deviation was less than 0.5% for the sample containing 5% GMO.

DNA↗

Effects of stimulus-response uncertainty on saccades to near-threshold targets.

Kveraga et al. (2002, Exp Brain Res 146(3):307-14) reported that saccade latencies are immune to the effects of stimulus-response uncertainty and constitute one of the few response systems that violate Hick's law. Similar effects have been reported for keypresses triggered by vibrations of the fingertips, but robust uncertainty effects were subsequently revealed using weak, low-frequency vibrations (Ten Hoopen et al. 1982, Acta Psychol 50:143-157). We wondered whether immunity of saccadic responses would demonstrate a similar intensity-dependency and therefore re-examined the effects of response entropy on saccade latencies using near-threshold visual stimuli. Saccadic latencies remained independent of stimulus-response uncertainty, indicating that saccadic motor programming is unaffected by the duration of the target detection process.

Adult↗

Uncertainty analysis in dissolved oxygen modeling in streams.

Uncertainty analysis in surface water quality modeling is an important issue. This paper presents a method based on the first-order reliability method (FORM) to assess the exceedance probability of a target dissolved oxygen concentration in a stream, using a Streeter-Phelps prototype model. Basic uncertainty in the input parameters is considered by representing them as random variables with prescribed probability distributions. Results obtained from FORM analysis compared well with those of the Monte Carlo simulation method. The analysis also presents the stochastic sensitivity of the probabilistic outcome in the form of uncertainty importance factors, and shows how they change with changing simulation time. Furthermore, a parametric sensitivity analysis was conducted to show the effect of selection of different probability distribution functions for the three most important parameters on the design point, exceedance probability, and importance factors.

Models, Theoretical↗

Siting and routing assessment for solid waste management under uncertainty using the grey mini-max regret criterion.

Solid waste management (SWM) is at the forefront of environmental concerns in the Lower Rio Grande Valley (LRGV), South Texas. The complexity in SWM drives area decision makers to look for innovative and forward-looking solutions to address various waste management options. In decision analysis, it is not uncommon for decision makers to go by an option that may minimize the maximum regret when some determinant factors are vague, ambiguous, or unclear. This article presents an innovative optimization model using the grey mini-max regret (GMMR) integer programming algorithm to outline an optimal regional coordination of solid waste routing and possible landfill/incinerator construction under an uncertain environment. The LRGV is an ideal location to apply the GMMR model for SWM planning because of its constant urban expansion, dwindling landfill space, and insufficient data availability signifying the planning uncertainty combined with vagueness in decision-making. The results give local decision makers hedged sets of options that consider various forms of systematic and event-based uncertainty. By extending the dimension of decision-making, this may lead to identifying a variety of beneficial solutions with efficient waste routing and facility siting for the time frame of 2005 through 2010 in LRGV. The results show the ability of the GMMR model to open insightful scenario planning that can handle situational and data-driven uncertainty in a way that was previously unavailable. Research findings also indicate that the large capital investment of incineration facilities makes such an option less competitive among municipal options for landfills. It is evident that the investment from a municipal standpoint is out of the question, but possible public-private partnerships may alleviate this obstacle.

Computer Simulation↗

Radiation exposure from radionuclides in ground water: an uncertainty analysis for selected exposure scenarios.

The uncertainty of the potential radiation exposure of the general population has been estimated for a normalized contamination of ground water that is being used as drinking water for humans and animals, for irrigation of food and feed crops, and for fish production in freshwater bodies. The frequency distributions of annual effective dose equivalents were calculated assuming a normalized activity concentration in water of 1 Bq/l for each radionuclide considered. Estimated frequency distributions of the parameters were used as model input. This estimation is based on an exposure scenario which reflects the present radioecological conditions. Another important source for the uncertainty of the potential dose due to radionuclides released to the ground water is the uncertainty of the exposure scenario. Since such a contamination may not occur before some time in the far future, it is impossible to predict the exact boundary conditions. Therefore, scenarios were stimulated with modified consumption habits, more extensive farm management and different climatic conditions. The distributions of the potential doses cover in general about a factor of 10-20. The intake of drinking water, the root uptake and the contamination of fish are most important for the resulting potential radiation exposure. For nearly all radionuclides, the intake of drinking water dominates the potential exposure. In most cases radioactive daughter nuclides are of minor importance. In general, the influence of the exposure scenario on the dose is relatively small.

Animals↗

PARATI--a dynamic model for radiological assessments in urban areas. Part III: Parameter uncertainty analysis.

The uncertainties in the exposure predictions after contamination of an urban area due to the variabilities in environmental transfer parameters and in dose conversion factors have been estimated. This was done using the "Latin Hypercube" sampling scheme and the computer codes PRISM and PARATI. For the scenario 'urban contamination by 137Cs' and the population groups considered, the main sources contributing to the uncertainty in the resulting exposures are the limited knowledge of the initial deposition and retention, the weathering processes, the actual urban environments, and the characteristics and habits of the population. The effect of the parameter uncertainties on the variability of the dose is almost constant over time.

Cesium Radioisotopes↗

Uncertainties in physiologically based pharmacokinetic models caused by several input parameters.

OBJECTIVE: One of the problems in the application of physiologically based pharmacokinetic (PB-PK) models is that authors often use different input parameters, with unknown influence on the results. Differences in the simulation results obtained with various sets of parameters are examined herein. METHOD: Chemicals considered were perchloroethylene, toluene, and styrene. Simulations of alveolar concentrations, blood concentrations, and urinary metabolite excretions were performed for the three solvents. The input parameters discussed herein are physiological values, metabolic constants, and partition coefficients. The influence of metabolic constants and partition coefficients is studied by comparison of models against one another. RESULTS: Metabolic parameters such as Vmax and K(m) varied considerably between authors. Tissue-gas partition coefficients, especially for the fat compartment, also differed according to the authors. Such differences in input parameter values proved to have a large influence on PB-PK model results and, therefore, increased their uncertainties. Uncertainties were much more significant in urinary metabolite concentration than in alveolar and blood concentration for chemicals that are poorly metabolized. On the other hand, uncertainties were more significant in alveolar and blood concentrations than in urinary metabolite excretions for chemicals that are well metabolized. CONCLUSION: Careful attention is necessary in the selection and/or citation of values from published data. The validity of PB-PK models should be simultaneously confirmed with both the blood and/or alveolar concentration and urinary metabolite concentrations.

Humans↗

Visual scanning with or without spatial uncertainty and divided and selective attention.

An experiment was conducted to address the relation between theories of selective attention and theories of divided attention by examining the pattern of task interference between visual scanning as a sequential and selective attention process and other concurrent spatial or verbal processing tasks. A distinction is proposed between visual scanning with or without spatial uncertainty regarding their possible differential effects on interference with other concurrent processes. The experiment required the subjects to perform a primary tracking task, which was concurrently performed with a secondary spatial or verbal decision task. The relevant information that was needed to perform the decision tasks was displayed with or without spatial uncertainty. The results provide evidence that visual scanning as a spatial exploratory activity produces greater task interference with concurrent spatial tasks than with verbal tasks. Furthermore, spatial uncertainty in scanning is identified to be the crucial factor in producing this differential effect.

Adult↗

Evaluation of uncertainties for parameters in binding studies: the sum-of-squares profile and Monte Carlo estimation.

Methods for characterization and evaluation of uncertainties in the parameter values for binding experiments are presented. A sum-of-squares profile is defined and illustrated. Sum-of-squares profiles give a qualitative description of both the uncertainties and correlation of parameters. The Monte Carlo method is developed as an accurate means of evaluating uncertainties in parameter values for nonlinear models. Examples are given for both actual and synthetic data.

Binding Sites↗

Uncertainty in hospitalized patients with chronic obstructive pulmonary disease.

The purpose of this study was to describe the perceptions of uncertainty of hospitalized patients with chronic bronchitis and/or emphysema. Fourteen men and 11 women were interviewed. Content analysis of the data yielded three themes of uncertainty, including managing home- and self-care, planning for the future, and the unpredictable course of the illness. Two themes that reflect coping resources also emerged from the data. These were positive thinking, and social support and material resources. The subjects were perceiving uncertainty in relation to their illness and hospitalization, and were endeavouring to manage it through the process of cognitive coping.

Activities of Daily Living↗

Intrinsic uncertainty and integration efficiency in bisection acuity.

A spatial perturbation paradigm was used to determine equivalent intrinsic uncertainty and spatial integration efficiency in bisection. Specifically, three-line bisection thresholds were measured in the fovea of four normal observers with stimulus lines comprised of discrete dark dots distributed randomly around the mean line position according to a Gaussian function. The standard deviation of the Gaussian distribution (sigma e), the number (N), and the strength (C) of the dots as well as line separation were varied. Bisection thresholds were modeled by an ideal integrator, from which the magnitude of equivalent internal uncertainty (sigma i), the equivalent effective number of dots (k), and equivalent integration efficiency (k/N) were quantified. At the 2 min arc separation, sigma i decreases (down to a few sec arc) as N and/or C increases. The effects of both N and C can be accounted for by the stimulus visibility (V, in multiples of detection threshold). At the 16 min arc separation, sigma i is independent of N, C, or V, and is about 1 min arc. The two different forms of sigma i indicate that bisection judgments are limited by at least two separate sources of limiting noise, consistent with the hypothesis of two separate mechanisms (i.e. spatial filters and local signs). A visibility dependent sigma i at the 2 min arc separation can be explained on the basis of contrast sensitive spatial filter mechanisms. A fixed sigma i at the 16 min arc separation indicates a genuine positional uncertainty, consistent with local-sign mechanisms. Interestingly, equivalent integration efficiency (k/N) is very similar at the two line separations. k/N is critically dependent on, and proportional to C, indicating a common limitation in a detection mechanism.

Depth Perception↗

Effects of dosimetric and clinical uncertainty on complication-free local tumor control.

A mathematical description is developed to demonstrate the effects of uncertainty on complication-free local tumor control. Responses of tumors and normal tissues are modeled by conventional radiobiological models. Uncertainties are considered in the delivery of absorbed dose to the target volume and the normal tissue at risk for complications. The degree by which uncertainties compromise complication-free local control for target volumes with various tumor cell burdens is calculated.

Computer Simulation↗

Statistical uncertainty in the no-observed-adverse-effect level.

The no-observed-adverse-effect level (NOAEL) is a dose value that U.S. EPA reduces by uncertainty factors (UF) and modifying factors (MF) to obtain a reference dose (RfD) for input to regulatory decision making. Whether the true added risk at the NOAEL is below an acceptable level, however, is a source of statistical uncertainty itself. As several authors have previously noted, the probability that added risk at the NOAEL is not negligibly small increases as sample sizes decrease. This is because the definition of the NOAEL statistically controls for the chance of a false-positive error, but not for a false-negative error. The false-positive rate is the test level set by the user in testing for a statistically significant dose effect, typically 0.05. When it is held fixed, the increase in statistical uncertainty as sample size decreases produces an increase in the false-negative rate. Hence, the fewer data available for statistical inference, the higher the expected value of the NOAEL and the less toxic an agent is likely to appear. The solution lies in calculating the probability that a statistical procedure used will detect the maximum added risk acceptable for health regulation (the "power" at that added risk). If the observed response in a dose group is not significantly elevated relative to the control group, and the power for detecting a difference is low as well, then the statistical evidence is inconclusive. In such a case, additional data or other sources of information are needed for evaluating added risk. These concepts are illustrated for examples from the literature with dichotomous (quantal response) data and categorical (severity) data, using a new statistical procedure.

Research Design↗