The effects of environmental perturbation and measurement error on estimates of the shape parameter in the theta-logistic model of population regulation

The theta-logistic is a widely used generalisation of the logistic model of regulated biological processes which is used in particular to model population regulation. Then the parameter theta gives the shape of the relationship between per-capita population growth rate and population size. Estimation of theta from population counts is however subject to bias, particularly when there are measurement errors. Here we identify factors disposing towards accurate estimation of theta by simulation of populations regulated according to the theta-logistic model. Factors investigated were measurement error, environmental perturbation and length of time series. Large measurement errors bias estimates of theta towards zero. Where estimated theta is close to zero, the estimated annual return rate may help resolve whether this is due to bias. Environmental perturbations help yield unbiased estimates of theta. Where environmental perturbations are large, estimates of theta are likely to be reliable even when measurement errors are also large. By contrast where the environment is relatively constant, unbiased estimates of theta can only be obtained if populations are counted precisely Our results have practical conclusions for the design of long-term population surveys. Estimation of the precision of population counts would be valuable, and could be achieved in practice by repeating counts in at least some years. Increasing the length of time series beyond ten or 20 years yields only small benefits. if populations are measured with appropriate accuracy, given the level of environmental perturbation, unbiased estimates can be obtained from relatively short censuses. These conclusions are optimistic for estimation of theta. (C) 2008 Elsevier B.V All rights reserved.

Automatic internal calibration in liquid chromatography/Fourier transform ion cyclotron resonance mass spectrometry of protein digests

Accurately measured peptide masses can be used for large-scale protein identification from bacterial whole-cell digests as an alternative to tandem mass spectrometry (MS/MS) provided mass measurement errors of a few parts-per-million (ppm) are obtained. Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS) routinely achieves such mass accuracy either with internal calibration or by regulating the charge in the analyzer cell. We have developed a novel and automated method for internal calibration of liquid chromatography (LC)/FTICR data from whole-cell digests using peptides in the sample identified by concurrent MS/MS together with ambient polydimethyl-cyclosiloxanes as internal calibrants in the mass spectra. The method reduced mass measurement error from 4.3 +/- 3.7 ppm to 0.3 +/- 2.3 ppm in an E. coli LC/FTICR dataset of 1000 MS and MS/MS spectra and is applicable to all analyses of complex protein digests by FTICRMS. Copyright (c) 2006 John Wiley & Sons, Ltd.

Enhancing model predictive control using dynamic data reconciliation

The use of data reconciliation techniques can considerably reduce the inaccuracy of process data due to measurement errors. This in turn results in improved control system performance and process knowledge. Dynamic data reconciliation techniques are applied to a model-based predictive control scheme. It is shown through simulations on a chemical reactor system that the overall performance of the model-based predictive controller is enhanced considerably when data reconciliation is applied. The dynamic data reconciliation techniques used include a combined strategy for the simultaneous identification of outliers and systematic bias.

Validation of ACE-FTS satellite data in the upper troposphere/lower stratosphere (UTLS) using non-coincident measurements

CO, O3, and H2O data in the upper troposphere/lower stratosphere (UTLS) measured by the Atmospheric Chemistry Experiment Fourier Transform Spectrometer(ACE-FTS) on Canada’s SCISAT-1 satellite are validated using aircraft and ozonesonde measurements. In the UTLS, validation of chemical trace gas measurements is a challenging task due to small-scale variability in the tracer fields, strong gradients of the tracers across the tropopause, and scarcity of measurements suitable for validation purposes. Validation based on coincidences therefore suffers from geophysical noise. Two alternative methods for the validation of satellite data are introduced, which avoid the usual need for coincident measurements: tracer-tracer correlations, and vertical tracer profiles relative to tropopause height. Both are increasingly being used for model validation as they strongly suppress geophysical variability and thereby provide an “instantaneous climatology”. This allows comparison of measurements between non-coincident data sets which yields information about the precision and a statistically meaningful error-assessment of the ACE-FTS satellite data in the UTLS. By defining a trade-off factor, we show that the measurement errors can be reduced by including more measurements obtained over a wider longitude range into the comparison, despite the increased geophysical variability. Applying the methods then yields the following upper bounds to the relative differences in the mean found between the ACE-FTS and SPURT aircraft measurements in the upper troposphere (UT) and lower stratosphere (LS), respectively: for CO ±9% and ±12%, for H2O ±30% and ±18%, and for O3 ±25% and ±19%. The relative differences for O3 can be narrowed down by using a larger dataset obtained from ozonesondes, yielding a high bias in the ACEFTS measurements of 18% in the UT and relative differences of ±8% for measurements in the LS. When taking into account the smearing effect of the vertically limited spacing between measurements of the ACE-FTS instrument, the relative differences decrease by 5–15% around the tropopause, suggesting a vertical resolution of the ACE-FTS in the UTLS of around 1 km. The ACE-FTS hence offers unprecedented precision and vertical resolution for a satellite instrument, which will allow a new global perspective on UTLS tracer distributions.

Intergenerational wealth mobility in rural Bangladesh

Unique residential history data with retrospective information on parental assets are used to study household wealth mobility in 141 villages in rural Bangladesh. Regression estimates of father–son correlations and analyses of intergenerational transition matrices show substantial persistence in wealth even when we correct for measurement errors in parental wealth. We do not find wealth mobility to be higher between periods of a person's life than between generations. We find that the process of household division plays an important role: sons who splinter off from the father's household experience greater (albeit downward) mobility in wealth. Despite significant occupational mobility across generations, its contribution to wealth mobility, net of human capital attainment of individuals, appears insignificant. Low wealth mobility in our data is primarily explained by intergenerational persistence in educational attainment.

Robust approaches to forecasting

We investigate alternative robust approaches to forecasting, using a new class of robust devices, contrasted with equilibrium-correction models. Their forecasting properties are derived facing a range of likely empirical problems at the forecast origin, including measurement errors, impulses, omitted variables, unanticipated location shifts and incorrectly included variables that experience a shift. We derive the resulting forecast biases and error variances, and indicate when the methods are likely to perform well. The robust methods are applied to forecasting US GDP using autoregressive models, and also to autoregressive models with factors extracted from a large dataset of macroeconomic variables. We consider forecasting performance over the Great Recession, and over an earlier more quiescent period.

Characterising errors in airborne laser altimetry data to extract soil roughness

Airborne laser altimetry has the potential to make frequent detailed observations that are important for many aspects of studying land surface processes. However, the uncertainties inherent in airborne laser altimetry data have rarely been well measured. Uncertainty is often specified as generally as 20cm in elevation, and 40cm planimetric. To better constrain these uncertainties, we present an analysis of several datasets acquired specifically to study the temporal consistency of laser altimetry data, and thus assess its operational value. The error budget has three main components, each with a time regime. For measurements acquired less than 50ms apart, elevations have a local standard deviation in height of 3.5cm, enabling the local measurement of surface roughness of the order of 5cm. Points acquired seconds apart acquire an additional random error due to Differential Geographic Positioning System (DGPS) fluctuation. Measurements made up to an hour apart show an elevation drift of 7cm over a half hour. Over months, this drift gives rise to a random elevation offset between swathes, with an average of 6.4cm. The RMS planimetric error in point location was derived as 37.4cm. We conclude by considering the consequences of these uncertainties on the principle application of laser altimetry in the UK, intertidal zone monitoring.

PINCER trial: a cluster randomised trial comparing the effectiveness and cost-effectiveness of a pharmacist-led IT-based intervention with simple feedback in reducing rates of clinically important errors in medicines management in general practices

Background: Medication errors in general practice are an important source of potentially preventable morbidity and mortality. Building on previous descriptive, qualitative and pilot work, we sought to investigate the effectiveness, cost-effectiveness and likely generalisability of a complex pharm acist-led IT-based intervention aiming to improve prescribing safety in general practice. Objectives: We sought to: • Test the hypothesis that a pharmacist-led IT-based complex intervention using educational outreach and practical support is more effective than simple feedback in reducing the proportion of patients at risk from errors in prescribing and medicines management in general practice. • Conduct an economic evaluation of the cost per error avoided, from the perspective of the National Health Service (NHS). • Analyse data recorded by pharmacists, summarising the proportions of patients judged to be at clinical risk, the actions recommended by pharmacists, and actions completed in the practices. • Explore the views and experiences of healthcare professionals and NHS managers concerning the intervention; investigate potential explanations for the observed effects, and inform decisions on the future roll-out of the pharmacist-led intervention • Examine secular trends in the outcome measures of interest allowing for informal comparison between trial practices and practices that did not participate in the trial contributing to the QRESEARCH database. Methods Two-arm cluster randomised controlled trial of 72 English general practices with embedded economic analysis and longitudinal descriptive and qualitative analysis. Informal comparison of the trial findings with a national descriptive study investigating secular trends undertaken using data from practices contributing to the QRESEARCH database. The main outcomes of interest were prescribing errors and medication monitoring errors at six- and 12-months following the intervention. Results: Participants in the pharmacist intervention arm practices were significantly less likely to have been prescribed a non-selective NSAID without a proton pump inhibitor (PPI) if they had a history of peptic ulcer (OR 0.58, 95%CI 0.38, 0.89), to have been prescribed a beta-blocker if they had asthma (OR 0.73, 95% CI 0.58, 0.91) or (in those aged 75 years and older) to have been prescribed an ACE inhibitor or diuretic without a measurement of urea and electrolytes in the last 15 months (OR 0.51, 95% CI 0.34, 0.78). The economic analysis suggests that the PINCER pharmacist intervention has 95% probability of being cost effective if the decision-maker’s ceiling willingness to pay reaches £75 (6 months) or £85 (12 months) per error avoided. The intervention addressed an issue that was important to professionals and their teams and was delivered in a way that was acceptable to practices with minimum disruption of normal work processes. Comparison of the trial findings with changes seen in QRESEARCH practices indicated that any reductions achieved in the simple feedback arm were likely, in the main, to have been related to secular trends rather than the intervention. Conclusions Compared with simple feedback, the pharmacist-led intervention resulted in reductions in proportions of patients at risk of prescribing and monitoring errors for the primary outcome measures and the composite secondary outcome measures at six-months and (with the exception of the NSAID/peptic ulcer outcome measure) 12-months post-intervention. The intervention is acceptable to pharmacists and practices, and is likely to be seen as costeffective by decision makers.

Validating the reported random errors of ACE‐FTS measurements

In order to validate the reported precision of space‐based atmospheric composition measurements, validation studies often focus on measurements in the tropical stratosphere, where natural variability is weak. The scatter in tropical measurements can then be used as an upper limit on single‐profile measurement precision. Here we introduce a method of quantifying the scatter of tropical measurements which aims to minimize the effects of short‐term atmospheric variability while maintaining large enough sample sizes that the results can be taken as representative of the full data set. We apply this technique to measurements of O3, HNO3, CO, H2O, NO, NO2, N2O, CH4, CCl2F2, and CCl3F produced by the Atmospheric Chemistry Experiment–Fourier Transform Spectrometer (ACE‐FTS). Tropical scatter in the ACE‐FTS retrievals is found to be consistent with the reported random errors (RREs) for H2O and CO at altitudes above 20 km, validating the RREs for these measurements. Tropical scatter in measurements of NO, NO2, CCl2F2, and CCl3F is roughly consistent with the RREs as long as the effect of outliers in the data set is reduced through the use of robust statistics. The scatter in measurements of O3, HNO3, CH4, and N2O in the stratosphere, while larger than the RREs, is shown to be consistent with the variability simulated in the Canadian Middle Atmosphere Model. This result implies that, for these species, stratospheric measurement scatter is dominated by natural variability, not random error, which provides added confidence in the scientific value of single‐profile measurements.

Review of current in vivo measurement techniques for quantifying enteric methane emission from ruminants

Ruminant husbandry is a major source of anthropogenic greenhouse gases (GHG). Filling knowledge gaps and providing expert recommendation are important for defining future research priorities, improving methodologies and establishing science-based GHG mitigation solutions to government and non-governmental organisations, advisory/extension networks, and the ruminant livestock sector. The objectives of this review is to summarize published literature to provide a detailed assessment of the methodologies currently in use for measuring enteric methane (CH4) emission from individual animals under specific conditions, and give recommendations regarding their application. The methods described include respiration chambers and enclosures, sulphur hexafluoride tracer (SF6) technique, and techniques based on short-term measurements of gas concentrations in samples of exhaled air. This includes automated head chambers (e.g. the GreenFeed system), the use of carbon dioxide (CO2) as a marker, and (handheld) laser CH4 detection. Each of the techniques are compared and assessed on their capability and limitations, followed by methodology recommendations. It is concluded that there is no ‘one size fits all’ method for measuring CH4 emission by individual animals. Ultimately, the decision as to which method to use should be based on the experimental objectives and resources available. However, the need for high throughput methodology e.g. for screening large numbers of animals for genomic studies, does not justify the use of methods that are inaccurate. All CH4 measurement techniques are subject to experimental variation and random errors. Many sources of variation must be considered when measuring CH4 concentration in exhaled air samples without a quantitative or at least regular collection rate, or use of a marker to indicate (or adjust) for the proportion of exhaled CH4 sampled. Consideration of the number and timing of measurements relative to diurnal patterns of CH4 emission and respiratory exchange are important, as well as consideration of feeding patterns and associated patterns of rumen fermentation rate and other aspects of animal behaviour. Regardless of the method chosen, appropriate calibrations and recovery tests are required for both method establishment and routine operation. Successful and correct use of methods requires careful attention to detail, rigour, and routine self-assessment of the quality of the data they provide.

Filter for Car Tracking Based on Acceleration and Steering Angle

The motion of a car is described using a stochastic model in which the driving processes are the steering angle and the tangential acceleration. The model incorporates exactly the kinematic constraint that the wheels do not slip sideways. Two filters based on this model have been implemented, namely the standard EKF, and a new filter (the CUF) in which the expectation and the covariance of the system state are propagated accurately. Experiments show that i) the CUF is better than the EKF at predicting future positions of the car; and ii) the filter outputs can be used to control the measurement process, leading to improved ability to recover from errors in predictive tracking.

A three-dimensional magnetometer for motion sensing of a balloon-carried atmospheric measurement package

An instrument is described which carries three orthogonal geomagnetic field sensors on a standard meteorological balloon package, to sense rapid motion and position changes during ascent through the atmosphere. Because of the finite data bandwidth available over the UHF radio link, a burst sampling strategy is adopted. Bursts of 9s of measurements at 3.6Hz are interleaved with periods of slow data telemetry lasting 25s. Calculation of the variability in each channel is used to determine position changes, a method robust to periods of poor radio signals. During three balloon ascents, variability was found repeatedly at similar altitudes, simultaneously in each of three orthogonal sensors carried. This variability is attributed to atmospheric motions. It is found that the vertical sensor is least prone to stray motions, and that the use of two horizontal sensors provides no additional information over a single horizontal sensor