Two-dimensional probabilistic inversion of plane-wave electromagnetic data: Methodology, model constraints and joint inversion with electrical resistivity data

Probabilistic inversion methods based on Markov chain Monte Carlo (MCMC) simulation are well suited to quantify parameter and model uncertainty of nonlinear inverse problems. Yet, application of such methods to CPU-intensive forward models can be a daunting task, particularly if the parameter space is high dimensional. Here, we present a 2-D pixel-based MCMC inversion of plane-wave electromagnetic (EM) data. Using synthetic data, we investigate how model parameter uncertainty depends on model structure constraints using different norms of the likelihood function and the model constraints, and study the added benefits of joint inversion of EM and electrical resistivity tomography (ERT) data. Our results demonstrate that model structure constraints are necessary to stabilize the MCMC inversion results of a highly discretized model. These constraints decrease model parameter uncertainty and facilitate model interpretation. A drawback is that these constraints may lead to posterior distributions that do not fully include the true underlying model, because some of its features exhibit a low sensitivity to the EM data, and hence are difficult to resolve. This problem can be partly mitigated if the plane-wave EM data is augmented with ERT observations. The hierarchical Bayesian inverse formulation introduced and used herein is able to successfully recover the probabilistic properties of the measurement data errors and a model regularization weight. Application of the proposed inversion methodology to field data from an aquifer demonstrates that the posterior mean model realization is very similar to that derived from a deterministic inversion with similar model constraints.

Inequality measurement for ordered response health data

When health status is an ordered response variable, Allison and Foster (2004)postulate that a distribution Q exhibits more inequality than a distribution P if Q is obtained from P via a sequence of median preserving spreads. This paper introduces a parametric family of inequality indices which are founded on the Allison and Foster ordering. [Authors]

Inequality measurement for ordered response health data

Because self-reported health status [SRHS] is an ordered response variable, inequality measurement for SRHS data requires a numerical scale for converting individual responses into a summary statistic. The choice of scale is however problematic, since small variations in the numerical scale may reverse the ordering of a given pair of distributions of SRHS data in relation to conventional inequality indices such as the variance. This paper introduces a parametric family of inequality indices, founded on an inequality ordering proposed by Allison and Foster [Allison, R.A., Foster, J., 2004. Measuring health inequalities using qualitative data. Journal of Health Economics 23, 505-524], which satisfy a suitable invariance property with respect to the choice of numerical scale. Several key members of the parametric family are also derived, and an empirical application using data from the Swiss Health Survey illustrates the proposed methodology. [Authors]

Hydrogeophysical data integration at larger scales: Application of Bayesian sequential simulation for the characterization of heterogeneous alluvial aquifers

Knowledge of the spatial distribution of hydraulic conductivity (K) within an aquifer is critical for reliable predictions of solute transport and the development of effective groundwater management and/or remediation strategies. While core analyses and hydraulic logging can provide highly detailed information, such information is inherently localized around boreholes that tend to be sparsely distributed throughout the aquifer volume. Conversely, larger-scale hydraulic experiments like pumping and tracer tests provide relatively low-resolution estimates of K in the investigated subsurface region. As a result, traditional hydrogeological measurement techniques contain a gap in terms of spatial resolution and coverage, and they are often alone inadequate for characterizing heterogeneous aquifers. Geophysical methods have the potential to bridge this gap. The recent increased interest in the application of geophysical methods to hydrogeological problems is clearly evidenced by the formation and rapid growth of the domain of hydrogeophysics over the past decade (e.g., Rubin and Hubbard, 2005).

Data Envelopment Analysis (DEA) : A pedagogical guide for decision makers in the public sector

This guide introduces Data Envelopment Analysis (DEA), a performance measurement technique, in such a way as to be appropriate to decision makers with little or no background in economics and operational research. The use of mathematics is kept to a minimum. This guide therefore adopts a strong practical approach in order to allow decision makers to conduct their own efficiency analysis and to easily interpret results. DEA helps decision makers for the following reasons: - By calculating an efficiency score, it indicates if a firm is efficient or has capacity for improvement. - By setting target values for input and output, it calculates how much input must be decreased or output increased in order to become efficient. - By identifying the nature of returns to scale, it indicates if a firm has to decrease or increase its scale (or size) in order to minimize the average cost. - By identifying a set of benchmarks, it specifies which other firms' processes need to be analysed in order to improve its own practices.

Enzyme replacement therapy with agalsidase alfa in patients with Fabry's disease: an analysis of registry data.

BACKGROUND: We analysed 5-year treatment with agalsidase alfa enzyme replacement therapy in patients with Fabry's disease who were enrolled in the Fabry Outcome Survey observational database (FOS). METHODS: Baseline and 5-year data were available for up to 181 adults (126 men) in FOS. Serial data for cardiac mass and function, renal function, pain, and quality of life were assessed. Safety and sensitivity analyses were done in patients with baseline and at least one relevant follow-up measurement during the 5 years (n=555 and n=475, respectively). FINDINGS: In patients with baseline cardiac hypertrophy, treatment resulted in a sustained reduction in left ventricular mass (LVM) index after 5 years (from 71.4 [SD 22.5] g/m(2.7) to 64.1 [18.7] g/m(2.7), p=0.0111) and a significant increase in midwall fractional shortening (MFS) from 14.3% (2.3) to 16.0% (3.8) after 3 years (p=0.02). In patients without baseline hypertrophy, LVM index and MFS remained stable. Mean yearly fall in estimated glomerular filtration rate versus baseline after 5 years of enzyme replacement therapy was -3.17 mL/min per 1.73 m(2) for men and -0.89 mL/min per 1.73 m(2) for women. Average pain, measured by Brief Pain Inventory score, improved significantly, from 3.7 (2.3) at baseline to 2.5 (2.4) after 5 years (p=0.0023). Quality of life, measured by deviation scores from normal EuroQol values, improved significantly, from -0.24 (0.3) at baseline to -0.17 (0.3) after 5 years (p=0.0483). Findings were confirmed by sensitivity analysis. No unexpected safety concerns were identified. INTERPRETATION: By comparison with historical natural history data for patients with Fabry's disease who were not treated with enzyme replacement therapy, long-term treatment with agalsidase alfa leads to substantial and sustained clinical benefits. FUNDING: Shire Human Genetic Therapies AB.

On problems of calculating energy expenditure and substrate utilization from respiratory exchange data.

Indirect calorimetry based on respiratory exchange measurement has been successfully used from the beginning of the century to obtain an estimate of heat production (energy expenditure) in human subjects and animals. The errors inherent to this classical technique can stem from various sources: 1) model of calculation and assumptions, 2) calorimetric factors used, 3) technical factors and 4) human factors. The physiological and biochemical factors influencing the interpretation of calorimetric data include a change in the size of the bicarbonate and urea pools and the accumulation or loss (via breath, urine or sweat) of intermediary metabolites (gluconeogenesis, ketogenesis). More recently, respiratory gas exchange data have been used to estimate substrate utilization rates in various physiological and metabolic situations (fasting, post-prandial state, etc.). It should be recalled that indirect calorimetry provides an index of overall substrate disappearance rates. This is incorrectly assumed to be equivalent to substrate "oxidation" rates. Unfortunately, there is no adequate golden standard to validate whole body substrate "oxidation" rates, and this contrasts to the "validation" of heat production by indirect calorimetry, through use of direct calorimetry under strict thermal equilibrium conditions. Tracer techniques using stable (or radioactive) isotopes, represent an independent way of assessing substrate utilization rates. When carbohydrate metabolism is measured with both techniques, indirect calorimetry generally provides consistent glucose "oxidation" rates as compared to isotopic tracers, but only when certain metabolic processes (such as gluconeogenesis and lipogenesis) are minimal or / and when the respiratory quotients are not at the extreme of the physiological range. However, it is believed that the tracer techniques underestimate true glucose "oxidation" rates due to the failure to account for glycogenolysis in the tissue storing glucose, since this escapes the systemic circulation. A major advantage of isotopic techniques is that they are able to estimate (given certain assumptions) various metabolic processes (such as gluconeogenesis) in a noninvasive way. Furthermore when, in addition to the 3 macronutrients, a fourth substrate is administered (such as ethanol), isotopic quantification of substrate "oxidation" allows one to eliminate the inherent assumptions made by indirect calorimetry. In conclusion, isotopic tracers techniques and indirect calorimetry should be considered as complementary techniques, in particular since the tracer techniques require the measurement of carbon dioxide production obtained by indirect calorimetry. However, it should be kept in mind that the assessment of substrate oxidation by indirect calorimetry may involve large errors in particular over a short period of time. By indirect calorimetry, energy expenditure (heat production) is calculated with substantially less error than substrate oxidation rates.

Conclusions on the measurement of arterial wall thickness: anatomic, physiologic and methodologic considerations

AIM: To discuss the use of new ultrasonic techniques that make it possible to visualize elastic (carotid) and muscular (radial) capacitance arteries non-invasively. RESULTS OF DATA REVIEW: Measurements of carotid wall thickness and the detection of atheromas are related to arterial pressure, to other risk factors and to the risk of subsequent complications. The use of high-frequency ultrasound (7.5-10 MHz), measurements of far wall thicknesses in areas free of atheromas at end-diastole (by ECG gating or pressure waveform recording) and descriptions of the size and characteristics of atherosclerotic plaques allow a non-invasive assessment of vascular hypertrophy and atherosclerosis in hypertensive patients. CONCLUSIONS: Careful attention to methodologic and physiologic factors is needed to provide accurate information about the anatomy of the dynamically pulsating arterial tree.

Nonclassical measurement error with applications to labor and development issues

Zero correlation between measurement error and model error has been assumed in existing panel data models dealing specifically with measurement error. We extend this literature and propose a simple model where one regressor is mismeasured, allowing the measurement error to correlate with model error. Zero correlation between measurement error and model error is a special case in our model where correlated measurement error equals zero. We ask two research questions. First, we wonder if the correlated measurement error can be identified in the context of panel data. Second, we wonder if classical instrumental variables in panel data need to be adjusted when correlation between measurement error and model error cannot be ignored. Under some regularity conditions the answer is yes to both questions. We then propose a two-step estimation corresponding to the two questions. The first step estimates correlated measurement error from a reverse regression; and the second step estimates usual coefficients of interest using adjusted instruments.

Modelling and Prospects for Audience Measurement of Outdoor Advertising using GPS Devices

The paper describes how to integrate audience measurement and site visibility as the main research approaches in outdoor advertising research in a single concept. Details are portrayed on how GPS is used on a large scale in Switzerland for mobility analysis and audience measurement. Furthermore, the development of a software solution is introduced that allows the integration of all mobility data and poster location information. Finally a model and its results is presented for the calculation of coverage of individual poster campaigns and for the calculation of the number of contacts generated by each billboard.

Use of high-resolution geophysical data to characterize heterogeneous aquifers: influence of data integration method on hydrological predictions

The integration of geophysical data into the subsurface characterization problem has been shown in many cases to significantly improve hydrological knowledge by providing information at spatial scales and locations that is unattainable using conventional hydrological measurement techniques. The investigation of exactly how much benefit can be brought by geophysical data in terms of its effect on hydrological predictions, however, has received considerably less attention in the literature. Here, we examine the potential hydrological benefits brought by a recently introduced simulated annealing (SA) conditional stochastic simulation method designed for the assimilation of diverse hydrogeophysical data sets. We consider the specific case of integrating crosshole ground-penetrating radar (GPR) and borehole porosity log data to characterize the porosity distribution in saturated heterogeneous aquifers. In many cases, porosity is linked to hydraulic conductivity and thus to flow and transport behavior. To perform our evaluation, we first generate a number of synthetic porosity fields exhibiting varying degrees of spatial continuity and structural complexity. Next, we simulate the collection of crosshole GPR data between several boreholes in these fields, and the collection of porosity log data at the borehole locations. The inverted GPR data, together with the porosity logs, are then used to reconstruct the porosity field using the SA-based method, along with a number of other more elementary approaches. Assuming that the grid-cell-scale relationship between porosity and hydraulic conductivity is unique and known, the porosity realizations are then used in groundwater flow and contaminant transport simulations to assess the benefits and limitations of the different approaches.

Usefulness of methadone plasma concentration measurement in patients receiving nevirapine or efavirenz.

Objective: To determine methadone plasma trough and peak concentrations in patients presenting opiate withdrawal symptoms after introduction of nevirapine or efavirenz. To describe the disappearance of these symptoms after methadone titration based on plasma concentrations rather than on the symptoms. Methods: Nine patients undergoing highly active antiretroviral therapy (HAART) and either nevirapine or efavirenz treatment were monitored daily for opiate withdrawal in a specialized drug addiction center. Methadone dose was titrated daily, and plasma concentrations were measured. The data are retrospective (case series). Results: Several patients complained of symptoms such as nausea, vomiting, accelerated intestinal transit, or insomnia. Even after methadone titration based on clinical symptoms, patients and health-care providers trained in infectious disease did not classify these as withdrawal symptoms and considered them as the side effects of HAART or anxiety. Methadone plasma trough concentration showed low levels of (R)- and (R,S)-methadone. Further methadone dose adjustment according to plasma level resulted in the disappearance of these withdrawal symptoms. The daily methadone dose was split when the peak/trough (R)-methadone ratio was more than 2. Conclusions: When introducing efavirenz or nevirapine to patients undergoing methadone treatment, withdrawal symptoms should be monitored, especially those such as insomnia, vomiting, or nausea. Methadone plasma trough and peak measurements can be of value in preventing unnecessary side effects of HAART.