23 resultados para Precision and recall

em University of Queensland eSpace - Australia


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The use of presence/absence data in wildlife management and biological surveys is widespread. There is a growing interest in quantifying the sources of error associated with these data. We show that false-negative errors (failure to record a species when in fact it is present) can have a significant impact on statistical estimation of habitat models using simulated data. Then we introduce an extension of logistic modeling, the zero-inflated binomial (ZIB) model that permits the estimation of the rate of false-negative errors and the correction of estimates of the probability of occurrence for false-negative errors by using repeated. visits to the same site. Our simulations show that even relatively low rates of false negatives bias statistical estimates of habitat effects. The method with three repeated visits eliminates the bias, but estimates are relatively imprecise. Six repeated visits improve precision of estimates to levels comparable to that achieved with conventional statistics in the absence of false-negative errors In general, when error rates are less than or equal to50% greater efficiency is gained by adding more sites, whereas when error rates are >50% it is better to increase the number of repeated visits. We highlight the flexibility of the method with three case studies, clearly demonstrating the effect of false-negative errors for a range of commonly used survey methods.

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Many studies of quantitative and disease traits in human genetics rely upon self-reported measures. Such measures are based on questionnaires or interviews and are often cheaper and more readily available than alternatives. However, the precision and potential bias cannot usually be assessed. Here we report a detailed quantitative genetic analysis of stature. We characterise the degree of measurement error by utilising a large sample of Australian twin pairs (857 MZ, 815 DZ) with both clinical and self-reported measures of height. Self-report height measurements are shown to be more variable than clinical measures. This has led to lowered estimates of heritability in many previous studies of stature. In our twin sample the heritability estimate for clinical height exceeded 90%. Repeated measures analysis shows that 2-3 times as many self-report measures are required to recover heritability estimates similar to those obtained from clinical measures. Bivariate genetic repeated measures analysis of self-report and clinical height measures showed an additive genetic correlation > 0.98. We show that the accuracy of self-report height is upwardly biased in older individuals and in individuals of short stature. By comparing clinical and self-report measures we also showed that there was a genetic component to females systematically reporting their height incorrectly; this phenomenon appeared to not be present in males. The results from the measurement error analysis were subsequently used to assess the effects of error on the power to detect linkage in a genome scan. Moderate reduction in error (through the use of accurate clinical or multiple self-report measures) increased the effective sample size by 22%; elimination of measurement error led to increases in effective sample size of 41%.

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A new, fast, continuous flow technique is described for the simultaneous determination of 633 S and delta(34)S using SO masses 48, 49 and 50. Analysis time is similar to5min/sample with measurement precision and accuracy better than +/-0.3parts per thousand. This technique, which has been set up using IAEA Ag2S standards S-1, S-2 and S-3, allows for the fast determination of mass-dependent or mass-independent fractionation (MIF) effects in sulfide, organic sulfur samples and possibly sulfate. Small sample sizes can be analysed directly, without chemical pre-treatment. Robustness of the technique for natural versus artificial standards was demonstrated by analysis of a Canon Diablo troilite, which gave a delta(33)S of 0.04parts per thousand and a delta(34)S of -0.06parts per thousand compared to the values obtained for S-1 of 0.07parts per thousand and -0.20parts per thousand, respectively. Two pyrite samples from a banded-iron formation from the 3710 Ma Isua Greenstone Belt were analysed using this technique and yielded MIF (Delta(33)S of 2.45 and 3.31parts per thousand) comparable to pyrite previously analysed by secondary ion probe. Copyright (C) 2004 John Wiley Sons, Ltd.

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Three important goals in describing software design patterns are: generality, precision, and understandability. To address these goals, this paper presents an integrated approach to specifying patterns using Object-Z and UML. To achieve the generality goal, we adopt a role-based metamodeling approach to define patterns. With this approach, each pattern is defined as a pattern role model. To achieve precision, we formalize role concepts using Object-Z (a role metamodel) and use these concepts to define patterns (pattern role models). To achieve understandability, we represent the role metamodel and pattern role models visually using UML. Our pattern role models provide a precise basis for pattern-based model transformations or refactoring approaches.

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Investment casting is often used to produce fully functional prototype components from sacrificial patterns. These patterns (prototypes) may be made using specialized rapid prototyping techniques such as stereolithography or three-dimensional printing. When multiple functional prototypes are required, interim tools for making wax patterns are employed. The objective of this research work was to determine the precision and accuracy of wax patterns produced using several prototype tools. Linear contraction was used to determine the accuracy as a function of the wax injection parameters used in low-pressure injection moulding. Wax patterns were produced using polyurethane and silicone rubber tools. It has been shown that the accuracy of patterns from both tools is similar. However, silicone tools produce patterns with much higher contraction than those produced by polyurethane tools. Unconstrained patterns dimensions contracted as much as 3.44 +/- 0.40 per cent and 1.70 +/- 0.60 per cent for silicone and polyurethane tools respectively. The constrained dimensions contracted by 2.20 +/- 0.20 per cent in the case of silicone tools and 1.40 +/- 0.20 per cent in the case of polyurethane tools.

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Recently, methods for computing D-optimal designs for population pharmacokinetic studies have become available. However there are few publications that have prospectively evaluated the benefits of D-optimality in population or single-subject settings. This study compared a population optimal design with an empirical design for estimating the base pharmacokinetic model for enoxaparin in a stratified randomized setting. The population pharmacokinetic D-optimal design for enoxaparin was estimated using the PFIM function (MATLAB version 6.0.0.88). The optimal design was based on a one-compartment model with lognormal between subject variability and proportional residual variability and consisted of a single design with three sampling windows (0-30 min, 1.5-5 hr and 11 - 12 hr post-dose) for all patients. The empirical design consisted of three sample time windows per patient from a total of nine windows that collectively represented the entire dose interval. Each patient was assigned to have one blood sample taken from three different windows. Windows for blood sampling times were also provided for the optimal design. Ninety six patients were recruited into the study who were currently receiving enoxaparin therapy. Patients were randomly assigned to either the optimal or empirical sampling design, stratified for body mass index. The exact times of blood samples and doses were recorded. Analysis was undertaken using NONMEM (version 5). The empirical design supported a one compartment linear model with additive residual error, while the optimal design supported a two compartment linear model with additive residual error as did the model derived from the full data set. A posterior predictive check was performed where the models arising from the empirical and optimal designs were used to predict into the full data set. This revealed the optimal'' design derived model was superior to the empirical design model in terms of precision and was similar to the model developed from the full dataset. This study suggests optimal design techniques may be useful, even when the optimized design was based on a model that was misspecified in terms of the structural and statistical models and when the implementation of the optimal designed study deviated from the nominal design.

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This article examines the neurocognitive sequelae of repeated exposure to hypoxemia in apnea (breath-hold) divers. A brief review of the literature on the physiological and neurological adaptations involved in the human diving reflex is presented. The results from a neuropsychological investigation of N = 21 elite apnea divers are evaluated. Standard neuropsychological tests, with known sensitivity to mild brain insults, included speed of visuo-motor responding, speed of language comprehension, response inhibition, and visual and verbal attention and recall tasks. Results indicated that the breath-hold divers performed tasks within the average range compared to norms on all tests, suggesting that 1-20 years of repeated exposure to hypoxemia including multiple adverse neurological events did not impact on performance on standard neuropsychological tasks. The results are discussed in relation to implications for clinical conditions such as sleep apnea, respiratory disorders, altitude sickness, and recreational apnea activities.

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Many different methods of reporting animal diets have been used in ecological research. These vary greatly in level of accuracy and precision and therefore complicate attempts to measure and compare diets, and quantitites of nutrients in those diets, across a wide range of taxa. For most birds, the carotenoid content of the diet has not been directly measured. Here, therefore, I use an avian example to show how different methods of measuring the quantities of various foods in the diet affect the relative rankings of higher taxa (families, subfamilies, and tribes), and species within these taxa, with regard to the carotenoid contents of their diets. This is a timely example, as much recent avian literature has focused on the way dietary carotenoids may be traded off among aspects of survival, fitness and signalling. I assessed the mean dietary carotenoid contents of representatives of thirty higher taxa of birds using four different carotenoid intake indices varying in precision, including trophic levels, a coarse-scale and a fine-scale categorical index, and quantitative estimates of dietary carotenoids. This last method was used as the benchmark. For comparisons among taxa, all but the trophic level index were significantly correlated with each other. However, for comparisons of species within taxa, the fine-scale index outperformed the coarse-scale index, which in turn outperformed the trophic level index. In addition, each method has advantages and disadvantages, as well as underlying assumptions that must be considered. Examination and comparison of several possible methods of diet assessment appears to highlight these so that the best possible index is used given available data, and it is recommended that such a step be taken prior to the inclusion of estimated nutrient intake in any statistical analysis. Although applied to avian carotenoids here, this method could readily be applied to other taxa and types of nutrients.

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The trafficking of molecules and membranes within cells is a prerequisite for all aspects of cellular immune functions, including the delivery and recycling of cell-surface proteins, secretion of immune mediators, ingestion of pathogens and activation of lymphocytes. SNARE (soluble-N-ethylmaleimide-sensitive-factor accessory-protein receptor)-family members mediate membrane fusion during all steps of trafficking, and function in almost all aspects of innate and adaptive immune responses. Here, we provide an overview of the roles of SNAREs in immune cells, offering insight into one level at which precision and tight regulation are instilled on immune responses.

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Traditionally, machine learning algorithms have been evaluated in applications where assumptions can be reliably made about class priors and/or misclassification costs. In this paper, we consider the case of imprecise environments, where little may be known about these factors and they may well vary significantly when the system is applied. Specifically, the use of precision-recall analysis is investigated and compared to the more well known performance measures such as error-rate and the receiver operating characteristic (ROC). We argue that while ROC analysis is invariant to variations in class priors, this invariance in fact hides an important factor of the evaluation in imprecise environments. Therefore, we develop a generalised precision-recall analysis methodology in which variation due to prior class probabilities is incorporated into a multi-way analysis of variance (ANOVA). The increased sensitivity and reliability of this approach is demonstrated in a remote sensing application.

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The duration of movements made to intercept moving targets decreases and movement speed increases when interception requires greater temporal precision. Changes in target size and target speed can have the same effect on required temporal precision, but the response to these changes differs: changes in target speed elicit larger changes in response speed. A possible explanation is that people attempt to strike the target in a central zone that does not vary much with variation in physical target size: the effective size of the target is relatively constant over changes in physical size. Three experiments are reported that test this idea. Participants performed two tasks: (1) strike a moving target with a bat moved perpendicular to the path of the target; (2) press on a force transducer when the target was in a location where it could be struck by the bat. Target speed was varied and target size held constant in experiment 1. Target speed and size were co-varied in experiment 2, keeping the required temporal precision constant. Target size was varied and target speed held constant in experiment 3 to give the same temporal precision as experiment 1. Duration of hitting movements decreased and maximum movement speed increased with increases in target speed and/or temporal precision requirements in all experiments. The effects were largest in experiment 1 and smallest in experiment 3. Analysis of a measure of effective target size (standard deviation of strike locations on the target) failed to support the hypothesis that performance differences could be explained in terms of effective size rather than actual physical size. In the pressing task, participants produced greater peak forces and shorter force pulses when the temporal precision required was greater, showing that the response to increasing temporal precision generalizes to different responses. It is concluded that target size and target speed have independent effects on performance.

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The measurement of lifetime prevalence of depression in cross-sectional surveys is biased by recall problems. We estimated it indirectly for two countries using modelling, and quantified the underestimation in the empirical estimate for one. A microsimulation model was used to generate population-based epidemiological measures of depression. We fitted the model to 1-and 12-month prevalence data from the Netherlands Mental Health Survey and Incidence Study (NEMESIS) and the Australian Adult Mental Health and Wellbeing Survey. The lowest proportion of cases ever having an episode in their life is 30% of men and 40% of women, for both countries. This corresponds to a lifetime prevalence of 20 and 30%, respectively, in a cross-sectional setting (aged 15-65). The NEMESIS data were 38% lower than these estimates. We conclude that modelling enabled us to estimate lifetime prevalence of depression indirectly. This method is useful in the absence of direct measurement, but also showed that direct estimates are underestimated by recall bias and by the cross-sectional setting.

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Virus-like particles (VLPs) are of interest in vaccination, gene therapy and drug delivery, but their potential has yet to be fully realized. This is because existing laboratory processes, when scaled, do not easily give a compositionally and architecturally consistent product. Research suggests that new process routes might ultimately be based on chemical processing by self-assembly, involving the precision manufacture of precursor capsomeres followed by in vitro VLP self-assembly and scale-up to required levels. A synergistic interaction of biomolecular design and bioprocess engineering (i.e. biomolecular engineering) is required if these alternative process routes and, thus, the promise of new VLP products, are to be realized.