Source wavelet estimation for waveform inversion of crosshole georadar data

AbstractFor a wide range of environmental, hydrological, and engineering applications there is a fast growing need for high-resolution imaging. In this context, waveform tomographic imaging of crosshole georadar data is a powerful method able to provide images of pertinent electrical properties in near-surface environments with unprecedented spatial resolution. In contrast, conventional ray-based tomographic methods, which consider only a very limited part of the recorded signal (first-arrival traveltimes and maximum first-cycle amplitudes), suffer from inherent limitations in resolution and may prove to be inadequate in complex environments. For a typical crosshole georadar survey the potential improvement in resolution when using waveform-based approaches instead of ray-based approaches is in the range of one order-of- magnitude. Moreover, the spatial resolution of waveform-based inversions is comparable to that of common logging methods. While in exploration seismology waveform tomographic imaging has become well established over the past two decades, it is comparably still underdeveloped in the georadar domain despite corresponding needs. Recently, different groups have presented finite-difference time-domain waveform inversion schemes for crosshole georadar data, which are adaptations and extensions of Tarantola's seminal nonlinear generalized least-squares approach developed for the seismic case. First applications of these new crosshole georadar waveform inversion schemes on synthetic and field data have shown promising results. However, there is little known about the limits and performance of such schemes in complex environments. To this end, the general motivation of my thesis is the evaluation of the robustness and limitations of waveform inversion algorithms for crosshole georadar data in order to apply such schemes to a wide range of real world problems.One crucial issue to making applicable and effective any waveform scheme to real-world crosshole georadar problems is the accurate estimation of the source wavelet, which is unknown in reality. Waveform inversion schemes for crosshole georadar data require forward simulations of the wavefield in order to iteratively solve the inverse problem. Therefore, accurate knowledge of the source wavelet is critically important for successful application of such schemes. Relatively small differences in the estimated source wavelet shape can lead to large differences in the resulting tomograms. In the first part of my thesis, I explore the viability and robustness of a relatively simple iterative deconvolution technique that incorporates the estimation of the source wavelet into the waveform inversion procedure rather than adding additional model parameters into the inversion problem. Extensive tests indicate that this source wavelet estimation technique is simple yet effective, and is able to provide remarkably accurate and robust estimates of the source wavelet in the presence of strong heterogeneity in both the dielectric permittivity and electrical conductivity as well as significant ambient noise in the recorded data. Furthermore, our tests also indicate that the approach is insensitive to the phase characteristics of the starting wavelet, which is not the case when directly incorporating the wavelet estimation into the inverse problem.Another critical issue with crosshole georadar waveform inversion schemes which clearly needs to be investigated is the consequence of the common assumption of frequency- independent electromagnetic constitutive parameters. This is crucial since in reality, these parameters are known to be frequency-dependent and complex and thus recorded georadar data may show significant dispersive behaviour. In particular, in the presence of water, there is a wide body of evidence showing that the dielectric permittivity can be significantly frequency dependent over the GPR frequency range, due to a variety of relaxation processes. The second part of my thesis is therefore dedicated to the evaluation of the reconstruction limits of a non-dispersive crosshole georadar waveform inversion scheme in the presence of varying degrees of dielectric dispersion. I show that the inversion algorithm, combined with the iterative deconvolution-based source wavelet estimation procedure that is partially able to account for the frequency-dependent effects through an "effective" wavelet, performs remarkably well in weakly to moderately dispersive environments and has the ability to provide adequate tomographic reconstructions.

Parameter estimation for the distribution of single cell lag times.

In Quantitative Microbial Risk Assessment, it is vital to understand how lag times of individual cells are distributed over a bacterial population. Such identified distributions can be used to predict the time by which, in a growth-supporting environment, a few pathogenic cells can multiply to a poisoning concentration level. We model the lag time of a single cell, inoculated into a new environment, by the delay of the growth function characterizing the generated subpopulation. We introduce an easy-to-implement procedure, based on the method of moments, to estimate the parameters of the distribution of single cell lag times. The advantage of the method is especially apparent for cases where the initial number of cells is small and random, and the culture is detectable only in the exponential growth phase.

Smoked cannabis and doping control: looking for the wrong target analyte?

Introduction: Since 2004, cannabis is prohibited by the World Anti-Doping Agency (WADA) for all sports in competition. In the years since then, about half of all positive doping cases in Switzerland have been related to cannabis consumption. In most cases, the athletes plausibly claim to have consumed cannabis several days or even weeks before competition and only for recreational purposes not related to competition. In doping analysis, the target analyte in urine samples is 11-nor-delta-9-tetrahydrocannabinol- 9-carboxylic acid (THC-COOH), the reporting threshold for laboratories is 15 ng/mL. However, the wide detection window of this long-term THC metabolite in urine does not allow a conclusion concerning the time of consumption or the impact on the physical performance. Aim: The purpose of the present pharmacokinetic study on volunteers was to evaluate target analytes with shorter urinary excretion time. Subsequently, urines from athletes tested positive for cannabis should be reanalyzed including these analytes. Methods: In an one-session clinical trial (approved by IRB, Swissmedic, and Federal Office of Public Health), 12 healthy, male volunteers (age 26 ± 3 yrs, BMI 24 ± 2 kg/m2) with cannabis experience (> once/month) smoked a Cannabis cigarette standardized to 70 mg THC/cigarette (Bedrobinol® 7%, Dutch Office for Medicinal Cannabis) following a paced-puffing procedure. Plasma and urine was collected up to 8 h and 11 days, respectively. Total THC, 11-hydroxy-THC (THC-OH), and THC-COOH were determined after enzymatic hydrolyzation followed by SPE and GC/MS-SIM. The limit of quantitation (LOQ) for all analytes was 0.1 ng/mL. Visual analog scales (VAS) and vital functions were used for monitoring psychological and somatic side-effects at every timepoint of specimen collection (up to 480 min). Results: Eight puffs delivered a mean THC dose of 45 mg. Mean plasma levels of total THC, THC-OH and THC-COOH were measured in the range of 0.1-20.9, 0.1-1.8, and 1.8-7.5 ng/mL, respectively. Peak concentrations were observed at 5, 10, and 90 min. Mean urine levels were measured in the range of 0.1-0.7, 0.10-6.2, and 0.1-13.4 ng/mL, respectively. The detection windows were 2-8, 2-96, and 2-120 h. No or only mild effects were observed, such as dry mouth, sedation, and tachycardia. Besides high to very high THC-COOH levels (0-978 ng/mL), THC (0.1-24 ng/mL) and THC-OH (1-234 ng/mL) were found in 90 and 96% of the cannabis-positive urines from athletes. Conclusion: Instead of or in addition to THC-COOH, the pharmacologically active THC and THC-OH should be the target analytes for doping urine analysis. This would allow the estimation of more recent Cannabis consumption, probably influencing performance during competition. Keywords: cannabis, doping, clinical trial, plasma and urine levels, athlete's samples

Panel index VAR models: Specification, Estimation, Testing and Leading Indicators

This paper proposes a method to conduct inference in panel VAR models with cross unit interdependencies and time variations in the coefficients. The approach can be used to obtain multi-unit forecasts and leading indicators and to conduct policy analysis in a multiunit setups. The framework of analysis is Bayesian and MCMC methods are used to estimate the posterior distribution of the features of interest. The model is reparametrized to resemble an observable index model and specification searches are discussed. As an example, we construct leading indicators for inflation and GDP growth in the Euro area using G-7 information.

CT arthrography of the glenohumeral joint: CT fluoroscopy versus conventional CT and fluoroscopy--comparison of image-guidance techniques.

PURPOSE: To compare examination time with radiologist time and to measure radiation dose of computed tomographic (CT) fluoroscopy, conventional CT, and conventional fluoroscopy as guiding modalities for shoulder CT arthrography. MATERIALS AND METHODS: Glenohumeral injection of contrast material for CT arthrography was performed in 64 consecutive patients (mean age, 32 years; age range, 16-74 years) and was guided with CT fluoroscopy (n = 28), conventional CT (n = 14), or conventional fluoroscopy (n = 22). Room times (arthrography, room change, CT, and total examination times) and radiologist times (time the radiologist spent in the fluoroscopy or CT room) were measured. One-way analysis of variance and Bonferroni-Dunn posthoc tests were performed for comparison of mean times. Mean effective radiation dose was calculated for each method with examination data, phantom measurements, and standard software. RESULTS: Mean total examination time was 28.0 minutes for CT fluoroscopy, 28.6 minutes for conventional CT, and 29.4 minutes for conventional fluoroscopy; mean radiologist time was 9.9 minutes, 10.5 minutes, and 9.0 minutes, respectively. These differences were not statistically significant. Mean effective radiation dose was 0.0015 mSv for conventional fluoroscopy (mean, nine sections), 0.22 mSv for CT fluoroscopy (120 kV; 50 mA; mean, 15 sections), and 0.96 mSv for conventional CT (140 kV; 240 mA; mean, six sections). Effective radiation dose can be reduced to 0.18 mSv for conventional CT by changing imaging parameters to 120 kV and 100 mA. Mean effective radiation dose of the diagnostic CT arthrographic examination (140 kV; 240 mA; mean, 25 sections) was 2.4 mSv. CONCLUSION: CT fluoroscopy and conventional CT are valuable alternative modalities for glenohumeral CT arthrography, as examination and radiologist times are not significantly different. CT guidance requires a greater radiation dose than does conventional fluoroscopy, but with adequate parameters CT guidance constitutes approximately 8% of the radiation dose.

BME-based uncertainty assessment of the Chernobyl fallout

The vast territories that have been radioactively contaminated during the 1986 Chernobyl accident provide a substantial data set of radioactive monitoring data, which can be used for the verification and testing of the different spatial estimation (prediction) methods involved in risk assessment studies. Using the Chernobyl data set for such a purpose is motivated by its heterogeneous spatial structure (the data are characterized by large-scale correlations, short-scale variability, spotty features, etc.). The present work is concerned with the application of the Bayesian Maximum Entropy (BME) method to estimate the extent and the magnitude of the radioactive soil contamination by 137Cs due to the Chernobyl fallout. The powerful BME method allows rigorous incorporation of a wide variety of knowledge bases into the spatial estimation procedure leading to informative contamination maps. Exact measurements (?hard? data) are combined with secondary information on local uncertainties (treated as ?soft? data) to generate science-based uncertainty assessment of soil contamination estimates at unsampled locations. BME describes uncertainty in terms of the posterior probability distributions generated across space, whereas no assumption about the underlying distribution is made and non-linear estimators are automatically incorporated. Traditional estimation variances based on the assumption of an underlying Gaussian distribution (analogous, e.g., to the kriging variance) can be derived as a special case of the BME uncertainty analysis. The BME estimates obtained using hard and soft data are compared with the BME estimates obtained using only hard data. The comparison involves both the accuracy of the estimation maps using the exact data and the assessment of the associated uncertainty using repeated measurements. Furthermore, a comparison of the spatial estimation accuracy obtained by the two methods was carried out using a validation data set of hard data. Finally, a separate uncertainty analysis was conducted that evaluated the ability of the posterior probabilities to reproduce the distribution of the raw repeated measurements available in certain populated sites. The analysis provides an illustration of the improvement in mapping accuracy obtained by adding soft data to the existing hard data and, in general, demonstrates that the BME method performs well both in terms of estimation accuracy as well as in terms estimation error assessment, which are both useful features for the Chernobyl fallout study.

Vacuum assisted venous drainage does not increase trauma to blood cells.

Although gravity drainage has been the standard technique for cardiopulmonary bypass (CPB), the development of min imally invasive techniques for cardiac surgery has renewed interest in using vacuum assisted venous drainage (VAVD) Dideco (Mirandola, Italy) has modified the D903 Avant oxygenator to apply a vacuum to its venous reservoir. The impact of VAVD on blood damage with this device is analyzed. Six calves (mean body weight, 71.3 +/- 4.1 kg) were con nected to CPB by jugular venous and carotid arterial cannu lation, with a flow rate of 4-4.51 L/min for 6 h. They were assigned to gravity drainage (standard D903 Avant oxygen ator, n = 3) or VAVD (modified D903 Avant oxygenator, n = 3). The animals were allowed to survive for 7 days. A standard battery of blood samples was taken before bypass, throughout bypass, and 24 h, 48 h, and 7 days after bypass. Analysis of variance was used for repeated measurements. Thrombocyte and white blood cell counts, corrected by hematocrit and normalized by prebypass values, were not significantly different between groups throughout all study periods. The same holds true for hemolytic parameters (lactate dehydrogenase [LDH] and plasma hemoglobin). Both peaked at 24 hr in the standard and VAVD groups: LDH, 2,845 +/- 974 IU/L vs. 2,537 +/- 476 IU/L (p = 0.65), respectively; and plasma hemoglobin, 115 +/- 31 mg/L vs. 89 +/- 455 mg/L (p = 0.45), respectively. In this experimental setup with prolonged perfusion time, VAVD does not increase trauma to blood cells in comparison with standard gravity drainage.

Aitchison Geometry for Probability and Likelihood as a new approach to mathematical statistics

The Aitchison vector space structure for the simplex is generalized to a Hilbert space structure A2(P) for distributions and likelihoods on arbitrary spaces. Centralnotations of statistics, such as Information or Likelihood, can be identified in the algebraical structure of A2(P) and their corresponding notions in compositional data analysis, such as Aitchison distance or centered log ratio transform.In this way very elaborated aspects of mathematical statistics can be understoodeasily in the light of a simple vector space structure and of compositional data analysis. E.g. combination of statistical information such as Bayesian updating,combination of likelihood and robust M-estimation functions are simple additions/perturbations in A2(Pprior). Weighting observations corresponds to a weightedaddition of the corresponding evidence.Likelihood based statistics for general exponential families turns out to have aparticularly easy interpretation in terms of A2(P). Regular exponential families formfinite dimensional linear subspaces of A2(P) and they correspond to finite dimensionalsubspaces formed by their posterior in the dual information space A2(Pprior).The Aitchison norm can identified with mean Fisher information. The closing constant itself is identified with a generalization of the cummulant function and shown to be Kullback Leiblers directed information. Fisher information is the local geometry of the manifold induced by the A2(P) derivative of the Kullback Leibler information and the space A2(P) can therefore be seen as the tangential geometry of statistical inference at the distribution P.The discussion of A2(P) valued random variables, such as estimation functionsor likelihoods, give a further interpretation of Fisher information as the expected squared norm of evidence and a scale free understanding of unbiased reasoning

Measuring spiritual well-being in older rehabilitation patients using the facit-sp

Objectives: To determine psychometric properties of the Functional Assessment of Chronic Illness Therapy-Spiritual well-being (FACIT-Sp) in a cohort of older patients admitted to rehabilitation. Method: Patients aged 65+, with MMSE score>19, admitted consecutively over 6 months in post-acute rehabilitation were enrolled (N=144, 81.27.2 years, 68.8% women). Data on medical, functional, and mental status were systematically collected upon admission. Spiritual well-being was assessed within 3 days after admission using the FACIT-Sp (12 items, score from 0 to 48, high spiritual well-being defined as a score ≥36) and the single question "Are you at peace?" (score from 0 to 10 on a visual analog scale). Results: FACIT-Sp scores ranged from 7 to 44(mean=29.87.7). Overall, 24.3% of the patients had high spiritual well-being. Internal consistency was optimal for total score (Cronbach's alpha =0.85). Itemto- total correlations were all significant, ranging from 0.28 to 0.73. A confirmatory factorial analysis yielded a 2-factor solution, consistent with Meaning and Faith proposed subscales and accounting for 52% of the variance . FACIT-Sp total score correlated positively with the question «Are you at peace ?» (Spearman's rho 0.49, P<.001) and negatively with depressive symptoms (Spearman's rho -0.37, P<.001), confirming FACIT-Sp validity. Compared to the others, patients with higher spiritual well-being had significantly better function at admission (Barthel's score 74.817.1 vs 68.514.1, P=.014). Conclusions: The FACIT-Sp remains a reliable and valid measure to assess spiritual well-being in older patients undergoing rehabilitation. The relatively low proportion of patients with high spiritual well-being deserves further investigation.

Subsampling the mean of heavy-tailed dependent observations

We establish the validity of subsampling confidence intervals for themean of a dependent series with heavy-tailed marginal distributions.Using point process theory, we study both linear and nonlinear GARCH-liketime series models. We propose a data-dependent method for the optimalblock size selection and investigate its performance by means of asimulation study.

Estimation du débit de filtration glomérulaire par la formule DFG = K x T/Pcr [Estimation of glomerular filtration rate by the formula GFR = K x T/Pc].

BACKGROUND: Creatinine clearance is the most common method used to assess glomerular filtration rate (GFR). In children, GFR can also be estimated without urine collection, using the formula GFR (mL/min x 1.73 m2) = K x height [cm]/Pcr [mumol/L]), where Pcr represents the plasma creatinine concentration. K is usually calculated using creatinine clearance (Ccr) as an index of GFR. The aim of the present study was to evaluate the reliability of the formula, using the standard UV/P inulin clearance to calculate K. METHODS: Clearance data obtained in 200 patients (1 month to 23 years) during the years 1988-1994 were used to calculate the factor K as a function of age. Forty-four additional patients were studied prospectively in conditions of either hydropenia or water diuresis in order to evaluate the possible variation of K as a function of urine flow rate. RESULTS: When GFR was estimated by the standard inulin clearance, the calculated values of K was 39 (infants less than 6 months), 44 (1-2 years) and 47 (2-12 years). The correlation between the values of GFR, as estimated by the formula, and the values measured by the standard clearance of inulin was highly significant; the scatter of individual values was however substantial. When K was calculated using Ccr, the formula overestimated Cin at all urine flow rates. When calculated from Ccr, K varied as a function of urine flow rate (K = 50 at urine flow rates of 3.5 and K = 64 at urine flow rates of 8.5 mL/min x 1.73 m2). When calculated from Cin, in the same conditions, K remained constant with a value of 50. CONCLUSIONS: The formula GFR = K x H/Pcr can be used to estimate GFR. The scatter of values precludes however the use of the formula to estimate GFR in pathophysiological studies. The formula should only be used when K is calculated from Cin, and the plasma creatinine concentration is measured in well defined conditions of hydration.