Flow-R, a model for susceptibility mapping of debris flows and other gravitational hazards at a regional scale: some case studies

Every year, debris flows cause huge damage in mountainous areas. Due to population pressure in hazardous zones, the socio-economic impact is much higher than in the past. Therefore, the development of indicative susceptibility hazard maps is of primary importance, particularly in developing countries. However, the complexity of the phenomenon and the variability of local controlling factors limit the use of processbased models for a first assessment. A debris flow model has been developed for regional susceptibility assessments using digital elevation model (DEM) with a GIS-based approach.. The automatic identification of source areas and the estimation of debris flow spreading, based on GIS tools, provide a substantial basis for a preliminary susceptibility assessment at a regional scale. One of the main advantages of this model is its workability. In fact, everything is open to the user, from the data choice to the selection of the algorithms and their parameters. The Flow-R model was tested in three different contexts: two in Switzerland and one in Pakistan, for indicative susceptibility hazard mapping. It was shown that the quality of the DEM is the most important parameter to obtain reliable results for propagation, but also to identify the potential debris flows sources.

Pragmatic approach for interpreting antiretroviral drug concentrations based on a systematic review of population pharmacokinetic studies

Objectives: The study objective was to derive reference pharmacokinetic curves of antiretroviral drugs (ART) based on available population pharmacokinetic (Pop-PK) studies that can be used to optimize therapeutic drug monitoring guided dosage adjustment.¦Methods: A systematic search of Pop-PK studies of 8 ART in adults was performed in PubMed. To simulate reference PK curves, a summary of the PK parameters was obtained for each drug based on meta-analysis approach. Most models used one-compartment model, thus chosen as reference model. Models using bi-exponential disposition were simplified to one-compartment, since the first distribution phase was rapid and not determinant for the description of the terminal elimination phase, mostly relevant for this project. Different absorption were standardized for first-order absorption processes.¦Apparent clearance (CL), apparent volume of distribution of the terminal phase (Vz) and absorption rate constant (ka) and inter-individual variability were pooled into summary mean value, weighted by number of plasma levels; intra-individual variability was weighted by number of individuals in each study.¦Simulations based on summary PK parameters served to construct concentration PK percentiles (NONMEM®).¦Concordance between individual and summary parameters was assessed graphically using Forest-plots. To test robustness, difference in simulated curves based on published and summary parameters was calculated using efavirenz as probe drug.¦Results: CL was readily accessible from all studies. For studies with one-compartment, Vz was central volume of distribution; for two-compartment, Vz was CL/λz. ka was directly used or derived based on the mean absorption time (MAT) for more complicated absorption models, assuming MAT=1/ka.¦The value of CL for each drug was in excellent agreement throughout all Pop-PK models, suggesting that minimal concentration derived from summary models was adequately characterized. The comparison of the concentration vs. time profile for efavirenz between published and summary PK parameters revealed not more than 20% difference. Although our approach appears adequate for estimation of elimination phase, the simplification of absorption phase might lead to small bias shortly after drug intake.¦Conclusions: Simulated reference percentile curves based on such an approach represent a useful tool for interpretating drug concentrations. This Pop-PK meta-analysis approach should be further validated and could be extended to elaborate more sophisticated computerized tool for the Bayesian TDM of ART.

Effective size of two feral domestic cat populations (Felis catus L): effect of the mating system.

A variety of behavioural traits have substantial effects on the gene dynamics and genetic structure of local populations. The mating system is a plastic trait that varies with environmental conditions in the domestic cat (Felis catus) allowing an intraspecific comparison of the impact of this feature on genetic characteristics of the population. To assess the potential effect of the heterogenity of males' contribution to the next generation on variance effective size, we applied the ecological approach of Nunney & Elam (1994) based upon a demographic and behavioural study, and the genetic 'temporal methods' of Waples (1989) and Berthier et al. (2002) using microsatellite markers. The two cat populations studied were nearly closed, similar in size and survival parameters, but differed in their mating system. Immigration appeared extremely restricted in both cases due to environmental and social constraints. As expected, the ratio of effective size to census number (Ne/N) was higher in the promiscuous cat population (harmonic mean = 42%) than in the polygynous one (33%), when Ne was calculated from the ecological method. Only the genetic results based on Waples' estimator were consistent with the ecological results, but failed to evidence an effect of the mating system. Results based on the estimation of Berthier et al. (2002) were extremely variable, with Ne sometimes exceeding census size. Such low reliability in the genetic results should retain attention for conservation purposes.

Possible solution of some essential zero problems in compositional data analysis

One of the tantalising remaining problems in compositional data analysis lies in how to deal with data sets in which there are components which are essential zeros. By anessential zero we mean a component which is truly zero, not something recorded as zero simply because the experimental design or the measuring instrument has not been sufficiently sensitive to detect a trace of the part. Such essential zeros occur inmany compositional situations, such as household budget patterns, time budgets,palaeontological zonation studies, ecological abundance studies. Devices such as nonzero replacement and amalgamation are almost invariably ad hoc and unsuccessful insuch situations. From consideration of such examples it seems sensible to build up amodel in two stages, the first determining where the zeros will occur and the secondhow the unit available is distributed among the non-zero parts. In this paper we suggest two such models, an independent binomial conditional logistic normal model and a hierarchical dependent binomial conditional logistic normal model. The compositional data in such modelling consist of an incidence matrix and a conditional compositional matrix. Interesting statistical problems arise, such as the question of estimability of parameters, the nature of the computational process for the estimation of both the incidence and compositional parameters caused by the complexity of the subcompositional structure, the formation of meaningful hypotheses, and the devising of suitable testing methodology within a lattice of such essential zero-compositional hypotheses. The methodology is illustrated by application to both simulated and real compositional data

Examining the information content of time-lapse crosshole GPR data collected under different infiltration conditions to estimate unsaturated soil hydraulic properties

Time-lapse geophysical data acquired during transient hydrological experiments are being increasingly employed to estimate subsurface hydraulic properties at the field scale. In particular, crosshole ground-penetrating radar (GPR) data, collected while water infiltrates into the subsurface either by natural or artificial means, have been demonstrated in a number of studies to contain valuable information concerning the hydraulic properties of the unsaturated zone. Previous work in this domain has considered a variety of infiltration conditions and different amounts of time-lapse GPR data in the estimation procedure. However, the particular benefits and drawbacks of these different strategies as well as the impact of a variety of key and common assumptions remain unclear. Using a Bayesian Markov-chain-Monte-Carlo stochastic inversion methodology, we examine in this paper the information content of time-lapse zero-offset-profile (ZOP) GPR traveltime data, collected under three different infiltration conditions, for the estimation of van Genuchten-Mualem (VGM) parameters in a layered subsurface medium. Specifically, we systematically analyze synthetic and field GPR data acquired under natural loading and two rates of forced infiltration, and we consider the value of incorporating different amounts of time-lapse measurements into the estimation procedure. Our results confirm that, for all infiltration scenarios considered, the ZOP GPR traveltime data contain important information about subsurface hydraulic properties as a function of depth, with forced infiltration offering the greatest potential for VGM parameter refinement because of the higher stressing of the hydrological system. Considering greater amounts of time-lapse data in the inversion procedure is also found to help refine VGM parameter estimates. Quite importantly, however, inconsistencies observed in the field results point to the strong possibility that posterior uncertainties are being influenced by model structural errors, which in turn underlines the fundamental importance of a systematic analysis of such errors in future related studies.

Bayesian Markov chain Monte Carlo inversion of geophysical data for the purpose of estimating the hydraulic properties of the unsaturated zone

Ground-penetrating radar (GPR) has the potential to provide valuable information on hydrological properties of the vadose zone because of their strong sensitivity to soil water content. In particular, recent evidence has suggested that the stochastic inversion of crosshole GPR data within a coupled geophysical-hydrological framework may allow for effective estimation of subsurface van-Genuchten-Mualem (VGM) parameters and their corresponding uncertainties. An important and still unresolved issue, however, is how to best integrate GPR data into a stochastic inversion in order to estimate the VGM parameters and their uncertainties, thus improving hydrological predictions. Recognizing the importance of this issue, the aim of the research presented in this thesis was to first introduce a fully Bayesian inversion called Markov-chain-Monte-carlo (MCMC) strategy to perform the stochastic inversion of steady-state GPR data to estimate the VGM parameters and their uncertainties. Within this study, the choice of the prior parameter probability distributions from which potential model configurations are drawn and tested against observed data was also investigated. Analysis of both synthetic and field data collected at the Eggborough (UK) site indicates that the geophysical data alone contain valuable information regarding the VGM parameters. However, significantly better results are obtained when these data are combined with a realistic, informative prior. A subsequent study explore in detail the dynamic infiltration case, specifically to what extent time-lapse ZOP GPR data, collected during a forced infiltration experiment at the Arrenaes field site (Denmark), can help to quantify VGM parameters and their uncertainties using the MCMC inversion strategy. The findings indicate that the stochastic inversion of time-lapse GPR data does indeed allow for a substantial refinement in the inferred posterior VGM parameter distributions. In turn, this significantly improves knowledge of the hydraulic properties, which are required to predict hydraulic behaviour. Finally, another aspect that needed to be addressed involved the comparison of time-lapse GPR data collected under different infiltration conditions (i.e., natural loading and forced infiltration conditions) to estimate the VGM parameters using the MCMC inversion strategy. The results show that for the synthetic example, considering data collected during a forced infiltration test helps to better refine soil hydraulic properties compared to data collected under natural infiltration conditions. When investigating data collected at the Arrenaes field site, further complications arised due to model error and showed the importance of also including a rigorous analysis of the propagation of model error with time and depth when considering time-lapse data. Although the efforts in this thesis were focused on GPR data, the corresponding findings are likely to have general applicability to other types of geophysical data and field environments. Moreover, the obtained results allow to have confidence for future developments in integration of geophysical data with stochastic inversions to improve the characterization of the unsaturated zone but also reveal important issues linked with stochastic inversions, namely model errors, that should definitely be addressed in future research.

Framingham risk score and alternatives for prediction of coronary heart disease in older adults.

BACKGROUND: Guidelines for the prevention of coronary heart disease (CHD) recommend use of Framingham-based risk scores that were developed in white middle-aged populations. It remains unclear whether and how CHD risk prediction might be improved among older adults. We aimed to compare the prognostic performance of the Framingham risk score (FRS), directly and after recalibration, with refit functions derived from the present cohort, as well as to assess the utility of adding other routinely available risk parameters to FRS.¦METHODS: Among 2193 black and white older adults (mean age, 73.5 years) without pre-existing cardiovascular disease from the Health ABC cohort, we examined adjudicated CHD events, defined as incident myocardial infarction, CHD death, and hospitalization for angina or coronary revascularization.¦RESULTS: During 8-year follow-up, 351 participants experienced CHD events. The FRS poorly discriminated between persons who experienced CHD events vs. not (C-index: 0.577 in women; 0.583 in men) and underestimated absolute risk prediction by 51% in women and 8% in men. Recalibration of the FRS improved absolute risk prediction, particulary for women. For both genders, refitting these functions substantially improved absolute risk prediction, with similar discrimination to the FRS. Results did not differ between whites and blacks. The addition of lifestyle variables, waist circumference and creatinine did not improve risk prediction beyond risk factors of the FRS.¦CONCLUSIONS: The FRS underestimates CHD risk in older adults, particularly in women, although traditional risk factors remain the best predictors of CHD. Re-estimated risk functions using these factors improve accurate estimation of absolute risk.

S-system parameter estimation for noisy metabolic profiles using newton-flow analysis.

Biochemical systems are commonly modelled by systems of ordinary differential equations (ODEs). A particular class of such models called S-systems have recently gained popularity in biochemical system modelling. The parameters of an S-system are usually estimated from time-course profiles. However, finding these estimates is a difficult computational problem. Moreover, although several methods have been recently proposed to solve this problem for ideal profiles, relatively little progress has been reported for noisy profiles. We describe a special feature of a Newton-flow optimisation problem associated with S-system parameter estimation. This enables us to significantly reduce the search space, and also lends itself to parameter estimation for noisy data. We illustrate the applicability of our method by applying it to noisy time-course data synthetically produced from previously published 4- and 30-dimensional S-systems. In addition, we propose an extension of our method that allows the detection of network topologies for small S-systems. We introduce a new method for estimating S-system parameters from time-course profiles. We show that the performance of this method compares favorably with competing methods for ideal profiles, and that it also allows the determination of parameters for noisy profiles.

A Structural Analysis of the Health Expenditures and Portfolio Choices of Retired Agents

Richer and healthier agents tend to hold riskier portfolios and spend proportionally less on health expenditures. Potential explanations include health and wealth effects on preferences, expected longevity or disposable total wealth. Using HRS data, we perform a structural estimation of a dynamic model of consumption, portfolio and health expenditure choices with recursive utility, as well as health-dependent income and mortality risk. Our estimates of the deep parameters highlight the importance of health capital, mortality risk control, convex health and mortality adjustment costs and binding liquidity constraints to rationalize the stylized facts. They also provide new perspectives on expected longevity and on the values of life and health.

Estimating uncertainty of alcohol-attributable fractions for infectious and chronic diseases.

Background: Alcohol is a major risk factor for burden of disease and injuries globally. This paper presents a systematic method to compute the 95% confidence intervals of alcohol-attributable fractions (AAFs) with exposure and risk relations stemming from different sources.Methods: The computation was based on previous work done on modelling drinking prevalence using the gamma distribution and the inherent properties of this distribution. The Monte Carlo approach was applied to derive the variance for each AAF by generating random sets of all the parameters. A large number of random samples were thus created for each AAF to estimate variances. The derivation of the distributions of the different parameters is presented as well as sensitivity analyses which give an estimation of the number of samples required to determine the variance with predetermined precision, and to determine which parameter had the most impact on the variance of the AAFs.Results: The analysis of the five Asian regions showed that 150 000 samples gave a sufficiently accurate estimation of the 95% confidence intervals for each disease. The relative risk functions accounted for most of the variance in the majority of cases.Conclusions: Within reasonable computation time, the method yielded very accurate values for variances of AAFs.

Integration of high-resolution geophysical data for the characterization of alluvial aquifers : new approaches and implications for hydrological predictions

Abstract Accurate characterization of the spatial distribution of hydrological properties in heterogeneous aquifers at a range of scales is a key prerequisite for reliable modeling of subsurface contaminant transport, and is essential for designing effective and cost-efficient groundwater management and remediation strategies. To this end, high-resolution geophysical methods have shown significant potential to bridge a critical gap in subsurface resolution and coverage between traditional hydrological measurement techniques such as borehole log/core analyses and tracer or pumping tests. An important and still largely unresolved issue, however, is how to best quantitatively integrate geophysical data into a characterization study in order to estimate the spatial distribution of one or more pertinent hydrological parameters, thus improving hydrological predictions. Recognizing the importance of this issue, the aim of the research presented in this thesis was to first develop a strategy for the assimilation of several types of hydrogeophysical data having varying degrees of resolution, subsurface coverage, and sensitivity to the hydrologic parameter of interest. In this regard a novel simulated annealing (SA)-based conditional simulation approach was developed and then tested in its ability to generate realizations of porosity given crosshole ground-penetrating radar (GPR) and neutron porosity log data. This was done successfully for both synthetic and field data sets. A subsequent issue that needed to be addressed involved assessing the potential benefits and implications of the resulting porosity realizations in terms of groundwater flow and contaminant transport. This was investigated synthetically assuming first that the relationship between porosity and hydraulic conductivity was well-defined. Then, the relationship was itself investigated in the context of a calibration procedure using hypothetical tracer test data. Essentially, the relationship best predicting the observed tracer test measurements was determined given the geophysically derived porosity structure. Both of these investigations showed that the SA-based approach, in general, allows much more reliable hydrological predictions than other more elementary techniques considered. Further, the developed calibration procedure was seen to be very effective, even at the scale of tomographic resolution, for predictions of transport. This also held true at locations within the aquifer where only geophysical data were available. This is significant because the acquisition of hydrological tracer test measurements is clearly more complicated and expensive than the acquisition of geophysical measurements. Although the above methodologies were tested using porosity logs and GPR data, the findings are expected to remain valid for a large number of pertinent combinations of geophysical and borehole log data of comparable resolution and sensitivity to the hydrological target parameter. Moreover, the obtained results allow us to have confidence for future developments in integration methodologies for geophysical and hydrological data to improve the 3-D estimation of hydrological properties.

Small-area estimation with spatial similarity

A class of composite estimators of small area quantities that exploit spatial (distancerelated)similarity is derived. It is based on a distribution-free model for the areas, but theestimators are aimed to have optimal design-based properties. Composition is applied alsoto estimate some of the global parameters on which the small area estimators depend.It is shown that the commonly adopted assumption of random effects is not necessaryfor exploiting the similarity of the districts (borrowing strength across the districts). Themethods are applied in the estimation of the mean household sizes and the proportions ofsingle-member households in the counties (comarcas) of Catalonia. The simplest version ofthe estimators is more efficient than the established alternatives, even though the extentof spatial similarity is quite modest.

Firm investment in imperfect capital markets: A structural estimation

We set up a dynamic model of firm investment in which liquidity constraintsenter explicity into the firm's maximization problem. The optimal policyrules are incorporated into a maximum likelihood procedure which estimatesthe structural parameters of the model. Investment is positively related tothe firm's internal financial position when the firm is relatively poor. This relationship disappears for wealthy firms, which can reach theirdesired level of investment. Borrowing is an increasing function of financial position for poor firms. This relationship is reversed as a firm's financial position improves, and large firms hold little debt.Liquidity constrained firms may be unused credits lines and the capacity toinvest further if they desire. However the fear that liquidity constraintswill become binding in the future induces them to invest only when internalresources increase.We estimate the structural parameters of the model and use them to quantifythe importance of liquidity constraints on firms' investment. We find thatliquidity constraints matter significantly for the investment decisions of firms. If firms can finance investment by issuing fresh equity, rather than with internal funds or debt, average capital stock is almost 35% higher overa period of 20 years. Transitory shocks to internal funds have a sustained effect on the capital stock. This effect lasts for several periods and ismore persistent for small firms than for large firms. A 10% negative shock to firm fundamentals reduces the capital stock of firms which face liquidityconstraints by almost 8% over a period as opposed to only 3.5% for firms which do not face these constraints.

Determination of extreme floods using a distributed hydrological model

Hydrological models developed for extreme precipitation of PMP type are difficult to calibrate because of the scarcity of available data for these events. This article presents the process and results of calibration for a distributed hydrological model at fine scale developed for the estimation of probable maximal floods in the case of a PMP. This calibration is done on two Swiss catchments for two events of summer storms. The calculation done is concentrated on the estimation of the parameters of the model, divided in two parts. The first is necessary for the computation of flow speeds while the second is required for the determination of the initial and final infiltration capacities for each terrain type. The results, validated with the Nash equation show a good correlation between the simulated and observed flows. We also apply this model on two Romanian catchments, showing the river network and estimated flow.

Detection of moving groups among early type stars

Our procedure to detect moving groups in the solar neighbourhood (Chen et al., 1997) in the four-dimensional space of the stellar velocity components and age has been improved. The method, which takes advantadge of non-parametric estimators of density distribution to avoid any a priori knowledge of the kinematic properties of these stellar groups, now includes the effect of observational errors on the process to select moving group stars, uses a better estimation of the density distribution of the total sample and field stars, and classifies moving group stars using all the available information. It is applied here to an accurately selected sample of early-type stars with known radial velocities and Strömgren photometry. Astrometric data are taken from the HIPPARCOS catalogue (ESA, 1997), which results in an important decrease in the observational errors with respect to ground-based data, and ensures the uniformity of the observed data. Both the improvement of our method and the use of precise astrometric data have allowed us not only to confirm the existence of classical moving groups, but also to detect finer structures that in several cases can be related to kinematic properties of nearby open clusters or associations.