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PubMed2001

Time-series analysis of delta13C from tree rings. I. Time trends and autocorrelation.

Univariate time-series analyses were conducted on stable carbon isotope ratios obtained from tree-ring cellulose. We looked for the presence and structure of autocorrelation. Significant autocorrelation violates the statistical independence assumption and biases hypothesis tests. Its presence would indicate the existence of lagged physiological effects that persist for longer than the current year. We analyzed data from 28 trees (60-85 years old; mean = 73 years) of western white pine (Pinus monticola Dougl.), ponderosa pine (Pinus ponderosa Laws.), and Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco var. glauca) growing in northern Idaho. Material was obtained by the stem analysis method from rings laid down in the upper portion of the crown throughout each tree's life. The sampling protocol minimized variation caused by changing light regimes within each tree. Autoregressive moving average (ARMA) models were used to describe the autocorrelation structure over time. Three time series were analyzed for each tree: the stable carbon isotope ratio (delta(13)C); discrimination (delta); and the difference between ambient and internal CO(2) concentrations (c(a) - c(i)). The effect of converting from ring cellulose to whole-leaf tissue did not affect the analysis because it was almost completely removed by the detrending that precedes time-series analysis. A simple linear or quadratic model adequately described the time trend. The residuals from the trend had a constant mean and variance, thus ensuring stationarity, a requirement for autocorrelation analysis. The trend over time for c(a) - c(i) was particularly strong (R(2) = 0.29-0.84). Autoregressive moving average analyses of the residuals from these trends indicated that two-thirds of the individual tree series contained significant autocorrelation, whereas the remaining third were random (white noise) over time. We were unable to distinguish between individuals with and without significant autocorrelation beforehand. Significant ARMA models were all of low order, with either first- or second-order (i.e., lagged 1 or 2 years, respectively) models performing well. A simple autoregressive (AR(1)), model was the most common. The most useful generalization was that the same ARMA model holds for each of the three series (delta(13)C, delta, c(a) - c(i)) for an individual tree, if the time trend has been properly removed for each series. The mean series for the two pine species were described by first-order ARMA models (1-year lags), whereas the Douglas-fir mean series were described by second-order models (2-year lags) with negligible first-order effects. Apparently, the process of constructing a mean time series for a species preserves an underlying signal related to delta(13)C while canceling some of the random individual tree variation. Furthermore, the best model for the overall mean series (e.g., for a species) cannot be inferred from a consensus of the individual tree model forms, nor can its parameters be estimated reliably from the mean of the individual tree parameters. Because two-thirds of the individual tree time series contained significant autocorrelation, the normal assumption of a random structure over time is unwarranted, even after accounting for the time trend. The residuals of an appropriate ARMA model satisfy the independence assumption, and can be used to make hypothesis tests.

Carbon Isotopes↗

PubMed2004

Activation-threshold tuning in an affinity model for the T-cell repertoire.

Naive T cells respond to peptides from foreign proteins and remain tolerant to self peptides from endogenous proteins. It has been suggested that self tolerance comes about by a 'tuning' mechanism, i.e. by increasing the T-cell activation threshold upon interaction with self peptides. Here, we explore how such an adaptive mechanism of T-cell tolerance would influence the reactivity of the T-cell repertoire to foreign peptides. We develop a computer simulation model in which T cells are tolerized by increasing their activation-threshold dependent on the affinity with which they see self peptides presented in the thymus. Thus, different T cells acquire different activation thresholds (i.e. different cross-reactivities). In previous mathematical models, T-cell tolerance was deletional and based on a fixed cross-reactivity parameter, which was assumed to have evolved to an optimal value. Comparing these two different tolerance-induction mechanisms, we found that the tuning model performs somewhat better than an optimized deletion model in terms of the reactivity to foreign antigens. Thus, evolutionary optimization of clonal cross-reactivity is not required. A straightforward extension of the tuning model is to delete T-cell clones that obtain a too high activation threshold, and to replace these by new clones. The reactivity of the immune repertoires of such a replacement model is enchanced compared with the basic tuning model. These results demonstrate that activation-threshold tuning is a functional mechanism for self tolerance induction.

Computer Simulation↗

PubMed2006

Thermal history regulates methylbutenol basal emission rate in Pinus ponderosa.

Methylbutenol (MBO) is a 5-carbon alcohol that is emitted by many pines in western North America, which may have important impacts on the tropospheric chemistry of this region. In this study, we document seasonal changes in basal MBO emission rates and test several models predicting these changes based on thermal history. These models represent extensions of the ISO G93 model that add a correction factor C(basal), allowing MBO basal emission rates to change as a function of thermal history. These models also allow the calculation of a new emission parameter E(standard30), which represents the inherent capacity of a plant to produce MBO, independent of current or past environmental conditions. Most single-component models exhibited large departures in early and late season, and predicted day-to-day changes in basal emission rate with temporal offsets of up to 3 d relative to measured basal emission rates. Adding a second variable describing thermal history at a longer time scale improved early and late season model performance while retaining the day-to-day performance of the parent single-component model. Out of the models tested, the T(amb),T(max7) model exhibited the best combination of day-to-day and seasonal predictions of basal MBO emission rates.

Algorithms↗

PubMed1990

Long QT syndrome. New electrocardiographic characteristics.

The long QT syndrome is electrocardiographically characterized by a prolonged QT interval and by several other, more subtle, ST-T-U wave abnormalities, most of which have not been quantified. To determine the possible usefulness of several new electrocardiographic characteristics in identifying patients with known long QT syndrome, logistic regression models were applied to a data base of seven new, relatively independent, electrocardiographic repolarization variables. These were measured on digitized 12-lead electrocardiograms of 315 normal subjects and 37 patients with the long QT syndrome (members of well-identified long QT syndrome families, QTc greater than 0.44 second, 27% symptomatic), who ranged in age from 17 to 60 years. Electrocardiographic variables that independently differentiated (p less than 0.001) patients with long QT syndrome from normal subjects included quantitative measures of repolarization: early duration, rate, T wave symmetry, late phenomena, and heterogeneity. All selected repolarization variables except the early duration variable were essentially independent of the QTc (r2 less than 0.15), and all contributed significantly to the identification of patients with long QT syndrome. A classification model of five electrocardiographic predictor variables resulted in an estimated sensitivity (95% confidence interval) of 92.6% (81.6-100%) and an estimated specificity (95% confidence interval) of 95.8% (93.6-98.1%). This model performed significantly better than an alternative classification model that was based on the early duration variable as a single predictor variable. The symptomatic status of patients with long QT syndrome could not be predicted by any combination of the electrocardiographic variables in the investigated model.

Adolescent↗

PubMedDate not supplied

Predicting room vapor concentrations due to spills of organic solvents.

Relatively small spills of volatile liquids can result in short-term, high-concentration exposures. Because of the transient nature of these exposures, air sampling may be precluded. As an alternative, exposure assessment can be done by mathematical modeling. The vapor emission rate from small spills is highest immediately following the spill and decreases as the surface area available for mass transfer decreases and evaporation cools the liquid. This decreasing emission rate is not described by any of the existing evaporation rate models. The authors present an evaporation rate model that describes the changing emissions as exponentially decreasing. The rate of decrease is governed by an evaporation rate parameter alpha, which has the unit of min(-1) and can be estimated based on experimental measurements. The authors measured alpha for a suite of compounds and different sizes of spill. They found that alpha can be estimated for hydrocarbons containing only C, H, and O with the equation: alpha=0.000524 VP + 0.0108 SA/Vol, where VP is the vapor pressure of the liquid and SA/Vol is the surface area to volume ratio. Next, the authors integrated the exponentially decreasing emission rate into a well-mixed room versus a near field/far field dispersion construct to predict vapor concentrations. A preliminary experiment was conducted in a test room to compare measured concentrations with the concentrations predicted by the models. The well-mixed room model performed well based on ANSI indoor air model evaluation criteria. The predicted near field concentrations showed a poor fit to the measured values based on the ANSI criteria, although overall they did capture the observed time profile.

Air Movements↗

PubMed1997

Ozone exposure assessment in a southern California community.

An ozone exposure assessment study was conducted in a Southern California community. The Harvard ozone passive sampler was used to monitor cohorts of 22 and 18 subjects for 8 weeks during the spring and fall of 1994, respectively. Ozone exposure variables included 12-hr personal O3 measurements, stationary outdoor O3 measurements from a continuous UV photometer and from 12-hr Harvard active monitors, and time-activity information. Results showed that personal O3 exposure levels averaged one-fourth of outdoor stationary O3 levels, attributable to high percentages of time spent indoors. Personal O3 levels were not predicted well by outdoor measurements. A random-effect general linear model analysis indicated that variance in personal exposure measurements was largely accounted for by random error (59-82%), followed by inter-subject (9-18%) and between-day (9-23%) random effects. The microenvironmental model performs differently by season, with the regression model for spring cohorts exhibiting two times the R2 of the fall cohorts (R2 = 0.21 vs. 0.09). When distance from the stationary monitoring site, elevation, and traffic are taken into account in the microenvironmental models, the adjusted R2 increased almost twofold for the fall personal exposure data. The low predictive power is due primarily to the apparent spatial variation of outdoor O3 and errors in O3 measurements and in time-activity records (particularly in recording the use of air conditioning). This study highlights the magnitude of O3 exposure misclassification in epidemiological settings and proposes an approach to reduce exposure uncertainties in assessing air pollution health effects.

Adolescent↗

PubMed1996

Children's processing of prosodic cues for phrasal interpretation.

Using synthetic speech, word duration and fundamental frequency (F0) contours were parametrically manipulated to examine processes of phrasal interpretation by adult and child (5 and 7 years old) listeners. From an adult male voice, versions of the phrase "pink and green and white" were resynthesized to produce stimuli suggesting two possible interpretations: [(pink and green) and white] and [pink and (green and white)]. For each stimulus, listeners pointed to a picture to indicate which interpretation was intended. All subjects used duration and (to a lesser extent) intonation as perceptually salient cues for phrasal interpretation. The manner in which subjects processed this information was evaluated by comparing subjects' performance with the predictions of three different information processing models: a nonindependent cue-evaluation model, and two independent cue-evaluation models (an additive model, and the multiplicative, fuzzy logical model). Performance was best described by the fuzzy logical model, which assumes independent cue evaluation and generates a classification function characterized by cue trading relations. The results suggest that, similar to adults, children as young as 5 years of age rely on acoustic-prosodic information for syntactic phrase interpretation, and they process this information in an adultlike manner.

Adult↗

PubMed2003

The effects of klapskate hinge position on push-off performance: a simulation study.

PURPOSE: The introduction of the klapskate in speed skating confronts skaters with the question of how to adjust the position of the hinge in order to maximize performance. The purpose of this study was to reveal the constraint that klapskate hinge position imposes on push-off performance in speed skating. METHOD: For this purpose, a model of the musculoskeletal system was designed to simulate a simplified, two-dimensional skating push off. To capture the essence of a skating push off, this model performed a one-leg vertical jump, from a frictionless surface, while keeping its trunk horizontally. In this model, klapskate hinge position was varied by varying the length of the foot segment between 115 and 300 mm. With each foot length, an optimal control solution was found that resulted in the maximal amount of vertical kinetic and potential energy of the body's center of mass at take off (Weff). RESULTS: Foot length was shown to considerably affect push-off performance. Maximal Weff was obtained with a foot length of 185 mm and decreased by approximately 25% at either foot length of 115 mm and 300 mm. The reason for this decrease was that foot length affected the onset and control of foot rotation. This resulted in a distortion of the pattern of leg segment rotations and affected muscle work (Wmus) and the efficacy ratio (Weff/Wmus) of the entire leg system. CONCLUSION: Despite its simplicity, the model very well described and explained the effects of klapskate hinge position on push off performance that have been observed in speed-skating experiments. The simplicity of the model, however, does not allow quantitative analyses of optimal klapskate hinge position for speed-skating practice.

Biomechanical Phenomena↗

PubMed2006

Adsorption of carbon tetrachloride on graphitized thermal carbon black and in slit graphitic pores: five-site versus one-site potential models.

The performance of intermolecular potential models on the adsorption of carbon tetrachloride on graphitized thermal carbon black at various temperatures is investigated. This is made possible with the extensive experimental data of Machin and Ross(1), Avgul et al.,(2) and Pierce(3) that cover a wide range of temperatures. The description of all experimental data is only possible with the allowance for the surface mediation. If this were ignored, the grand canonical Monte Carlo (GCMC) simulation results would predict a two-dimensional (2D) transition even at high temperatures, while experimental data shows gradual change in adsorption density with pressure. In general, we find that the intermolecular interaction has to be reduced by 4% whenever particles are within the first layer close to the surface. We also find that this degree of surface mediation is independent of temperature. To understand the packing of carbon tetrachloride in slit pores, we compared the performance of the potential models that model carbon tetrachloride as either five interaction sites or one site. It was found that the five-site model performs better and describes the imperfect packing in small pores better. This is so because most of the strength of fluid-fluid interaction between two carbon tetrachloride molecules comes from the interactions among chlorine atoms. Methane, although having tetrahedral shape as carbon tetrachloride, can be effectively modeled as a pseudospherical particle because most of the interactions come from carbon-carbon interaction and hydrogen negligibly contributes to this.

Journal Article↗

PubMed1986

Gaseous homeostasis and the circle system. Validation of a model.

The performance of a model of a subject breathing from a circle system has been examined in relation to nitrogen and helium. The ability of the model to maintain a nitrogen steady-state breathing air, the attainment of a new steady-state after perturbation of an existing nitrogen equilibrium, the washout of nitrogen from the subject model on breathing oxygen, and the estimation of functional residual capacity using a rebreathing method with helium as an indicator have been assessed. The predictable and accurate performance of the model in these studies, together with its ability to reproduce the results of a number of previously published studies in man, suggest that the model can be used to predict the behaviour of circle systems when used with inhaled anaesthetic agents.

Anesthesia, Inhalation↗

PubMed1993

Statistical approaches to pharmacodynamic modeling: motivations, methods, and misperceptions.

We have attempted to outline the fundamental statistical aspects of pharmacodynamic modeling. Unexpected yet substantial variability in effect in a group of similarly treated patients is the key motivation for pharmacodynamic investigations. Pharmacokinetic and/or pharmacodynamic factors may influence this variability. Residual variability in effect that persists after accounting for drug exposure indicates that further statistical modeling with pharmacodynamic factors is warranted. Factors that significantly predict interpatient variability in effect may then be employed to individualize the drug dose. In this paper we have emphasized the need to understand the properties of the effect measure and explanatory variables in terms of scale, distribution, and statistical relationship. The assumptions that underlie many types of statistical models have been discussed. The role of residual analysis has been stressed as a useful method to verify assumptions. We have described transformations and alternative regression methods that are employed when these assumptions are found to be in violation. Sequential selection procedures for the construction of multivariate models have been presented. The importance of assessing model performance has been underscored, most notably in terms of bias and precision. In summary, pharmacodynamic analyses are now commonly performed and reported in the oncologic literature. The content and format of these analyses has been variable. The goals of such analyses are to identify and describe pharmacodynamic relationships and, in many cases, to propose a statistical model. However, the appropriateness and performance of the proposed model are often difficult to judge. Table 1 displays suggestions (in a checklist format) for structuring the presentation of pharmacodynamic analyses, which reflect the topics reviewed in this paper.

Data Interpretation, Statistical↗

PubMed2002

Risk-adjusted mortality rates as a potential outcome indicator for outpatient quality assessments.

OBJECTIVE: The quality of outpatient medical care is increasingly recognized as having an important impact on mortality. We examined whether a clinically credible risk adjustment methodology can be developed for outpatient quality assessments. RESEARCH DESIGN: This study used data from the 1998 National Survey of Ambulatory Care Patients, a prospective monitoring system of outcomes of patients receiving ambulatory care in the Veterans Affairs (VA) integrated service networks. SUBJECTS: Thirty-one thousand eight hundred twenty-three patients were followed for 18 months. MEASURES: The main study outcome measures were observed and risk-adjusted mortality rates. RESULTS: Of the 31,823 patients, 1559 (5%) died during the 18-months of follow-up. Observed mortality rates across the 22 VA integrated service networks varied significantly from 3.3% to 6.7% (P <0.001). Age, gender, comorbidities (Charlson Index), physical health, and mental health were significant predictors of dying. The resulting risk-adjusted mortality model performed well in cross-validated tests of discrimination (c-statistic = 0.768; 95% CI, 0.749-0.788) and calibration. Analysis of variance confirmed that the 22 integrated service networks differed in their average level of expected risk (P <0.001). Risk-adjusted rates and ranks of the networks differed considerably from unadjusted ratings. CONCLUSIONS: Risk-adjusted mortality rates may be a useful outcome measure for assessing quality of outpatient care. We have developed a clinically credible risk adjustment model with good performance properties using sociodemographics, diagnoses, and functional status data. The resulting risk adjustment model altered assessments of the performance of the integrated service networks when compared with the unadjusted mortality rates.

Aged↗

PubMed1999

Test anxiety versus academic skills: a comparison of two alternative models for predicting performance in a statistics exam.

BACKGROUND: Two competing theoretical models to explain academic performance were proposed. The interference model stresses the detrimental effect of task-irrelevant thoughts during the test-taking situation whereas the deficit model suggests Study Habits and domain-specific skills as main predictors of test performance. AIMS: The study compares the two models by determining the relative contribution of Test Anxiety, Study Habits, and Maths Skill to performance in a statistics exam. SAMPLE: Sixty-six undergraduate students who were enrolled in the first semester of two parallel introductory statistic courses participated in the study. METHOD: Hierarchical regression analyses were performed on the performance in the final statistics exam. The unique variance attributable to Test Anxiety, Study Habits, and Maths Skill was calculated. RESULTS: Both Maths Skill and Test Anxiety added unique variance in explaining performance, whereas Study Habits did not. Although Maths Skill emerged as relatively more important than Test Anxiety, a purely deficit-based account nevertheless appears untenable because interfering effects of Test Anxiety during the examination also contributed an important portion of variance. CONCLUSIONS: It is recommended that cognitive-attentional accounts stressing test anxiety be supplemented by a deficit formulation, and that multimodal counselling address both Test Anxiety and skill deficits. COMMENT: Methodological problems in investigating the causal relationship between skill deficits, anxiety, and performance are discussed.

Adult↗

PubMed2004

A model to predict work-related fatigue based on hours of work.

Several research groups have developed models for estimating the work-related fatigue associated with shiftworkers' duty schedules. In June 2002, invited members of seven of these groups attended the Fatigue and Performance Modeling Workshop in Seattle, WA. At the workshop, each group described the background and conceptual basis of their model, and an independent party compared the models' predictions with performance and sleepiness data from five laboratory- and workplace-based scenarios. One of these models, the Fatigue Audit InterDyne (FAID), can be used to quantify the work-related fatigue associated with any duty schedule using hours of work (i.e., start/end times of work periods) as the sole input. The objectives of the current paper were to: 1) describe the background and conceptual basis of FAID; 2) present FAID-based predictions for four of the scenarios; and 3) discuss the advantages of, and possible improvements to, FAID. The analyses conducted to compare the predictive power of each model are described in detail by Van Dongen elsewhere in this issue.

Circadian Rhythm↗

PubMedDate not supplied

A 2-D model of wheelchair propulsion.

PURPOSE: To illustrate the potential benefits of kinetic and kinematic models in the exploration of biomechanical studies as illustrated using a simple 2-D static optimization model of wheelchair propulsion. METHOD: A four-bar linkage analysis was used to determine sagittal plane motion through the range of wheelchair propulsion. Using anthropometric measures of wheelchair users, this analysis determined the angles of shoulder and elbow flexion/extension at a given point in the propulsion cycle. Maximal strength inputs for the model were collected from isokinetic measurements of shoulder and elbow moments. The torque inputs were given as functions of sagittal plane joint angles. Through selection of appropriate model performance criteria, optimization techniques determined shoulder and elbow torque contributions throughout the propulsion cycle. Variations in the model parameters of anterior-posterior (AP) seat position and handrim size went used to show potential of model to evaluate wheelchair configuration using the performance criteria of propulsive moment (Mo) and efficiency as defined by fractional effective force (FEF). RESULTS: The model was able to predict the magnitude and direction of force applied to the handrim from shoulder and elbow moments. These joint moments may be examined along with the generated wheelchair axle propulsion moment. While the model showed no significant changes in either Mo or FEF for AP seat changes, an increase in handrim size was shown to increase FEF. CONCLUSIONS: This model was able to simulate wheelchair propulsion and allow for performance analyses. The open nature of the model allowed for tweaking of the kinematic inputs to examine the sensitivity of such factors as seat position and handrim size in wheelchair propulsion. Strength inputs to the model may also be altered to study the potential effects of strength training or muscle weakness.

Biomechanical Phenomena↗

PubMed2000

Radiographic quality control devices.

In this study, we evaluate eight radiographic quality control (QC) devices, which noninvasively measure the output from a variety of diagnostic x-ray production systems. When used as part of a quality assurance (QA) program, radiographic QC devices help ensure that x-ray equipment is working within acceptable limits. This in turn helps ensure that high-quality images are achieved with appropriate radiation doses and that resources are used efficiently (for example, by minimizing the number of repeat exposures required). Our testing focused on the physical performance, ease of use, and service and maintenance characteristics that affect the use of these devices for periodic, routine measurements of x-ray system parameters. We found that all the evaluated models satisfactorily measure all the parameters normally needed for a QA program. However, we did identify a number of differences among the models--particularly in the range of exposure levels that can be effectively measured and the ease of use. Three models perform well for a variety of applications and are very easy to use; we rate them Preferred. Three additional models have minor limitations but otherwise perform well; we rate them Acceptable. We recommend against purchasing two models because, although each performs acceptably for most applications, neither model can measure low levels of radiation. This Evaluation covers devices designed to measure the output of x-ray tubes noninvasively. These devices, called radiographic quality control (QC) devices, or QC meters, are typically used by medical physicists, x-ray engineers, biomedical engineers, and suitably trained radiographic technologists to make QC measurements. We focus on the use of these devices as part of an overall quality assurance (QA) program. We have not evaluated their use for other applications, such as acceptance testing. To be included in this study, a device must be able to measure the exposure- and kVp-related characteristics of most x-ray systems. At minimum, it must be able to make routine QC measurements of general radiographic, fluoroscopic, and most mammographic equipment. We prefer that it also be usable with dental x-ray systems, more advanced mammography systems (see the supplementary article on page 103), and computed tomography (CT) systems. The device may be a single unit, or it may be a kit consisting of multiple components that, when combined, can perform all the relevant measurements. The evaluated devices are designed to assess only x-ray production systems, not x-ray detection systems such as image intensifiers and film. Those types of systems are typically assessed using test phantoms and other tools that produce test images, which can be quantitatively measured and compared against standards.

Equipment Design↗

PubMed1986

Perceptual studies on ultrasonic B-scan textures.

A pilot study of the perceptual characteristics of ultrasonic textured images is described. Scans of four models performed on four real-time machines optimised for display of a normal liver were used. A trial with 22 observers indicated that the model that gave images closest to the liver image varied between machines. A second, paired similarity test with five observers using all the model images was performed, with a cluster analysis of a multidimensional scaling procedure. This suggested that the prominent features of the textural images are often more closely related to the machines than to the models. Considerable further work is needed to confirm these pilot results and to identify the visual cues that are most significant in textured images.

Biophysical Phenomena↗

PubMed2005

Inference of nested variance components in a longitudinal myopia intervention trial.

This paper was motivated by a double-blind randomized clinical trial of myopia intervention. In addition to the primary goal of comparing treatment effects, we are concerned with the modelling of correlation that may come from two possible sources, one among the longitudinal observations and the other between measurements taken from both eyes per subject. The data are nested repeated measurements. We suggest three models for analysis. Each one expresses the correlation differently in various covariance structures. We articulate their differences and describe the implementations in estimation using commercial statistical software. The computer output can be further utilized to perform model selection with Schwarz criterion. Simulation studies are conducted to evaluate the performance under each model. Data of the myopia intervention trial are reanalysed with these models for illustration. The results indicate that atropine is more effective in reducing the progression rate, the rates are homogeneous across subjects, and, among the suggested models, the one with independent random effects of two eyes fits best. We conclude that model selection is a crucial step before making inference with estimates; otherwise the correlation may be attributed incorrectly to a different mechanism. The same conclusion applies to other variance components as well.

Analysis of Variance↗