Assessment of debris-flow susceptibility at medium-scale in the Barcelonnette Basin, France

Debris flows are among the most dangerous processes in mountainous areas due to their rapid rate of movement and long runout zone. Sudden and rather unexpected impacts produce not only damages to buildings and infrastructure but also threaten human lives. Medium- to regional-scale susceptibility analyses allow the identification of the most endangered areas and suggest where further detailed studies have to be carried out. Since data availability for larger regions is mostly the key limiting factor, empirical models with low data requirements are suitable for first overviews. In this study a susceptibility analysis was carried out for the Barcelonnette Basin, situated in the southern French Alps. By means of a methodology based on empirical rules for source identification and the empirical angle of reach concept for the 2-D runout computation, a worst-case scenario was first modelled. In a second step, scenarios for high, medium and low frequency events were developed. A comparison with the footprints of a few mapped events indicates reasonable results but suggests a high dependency on the quality of the digital elevation model. This fact emphasises the need for a careful interpretation of the results while remaining conscious of the inherent assumptions of the model used and quality of the input data.

Debris flow modeling for susceptibility mapping at regional to national scale in Norway

Debris flows and related landslide processes occur in many regions all over Norway and pose a significant hazard to inhabited areas. Within the framework of the development of a national debris flows susceptibility map, we are working on a modeling approach suitable for Norway with a nationwide coverage. The discrimination of source areas is based on an index approach, which includes topographic parameters and hydrological settings. For the runout modeling, we use the Flow-R model (IGAR, University of Lausanne), which is based on combined probabilistic and energetic algorithms for the assessment of the spreading of the flow and maximum runout distances. First results for different test areas have shown that runout distances can be modeled reliably. For the selection of source areas, however, additional factors have to be considered, such as the lithological and quaternary geological setting, in order to accommodate the strong variation in debris flow activity in the different geological, geomorphological and climate regions of Norway.

Integration of local-scale hydrological and regional-scale geophysical based on a nonlinear Bayesian sequential simulation approach

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed a downscaling procedure based on a non-linear Bayesian sequential simulation approach. The basic objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity, which is available throughout the model space. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariate kernel density function. This method is then applied to the stochastic integration of low-resolution, re- gional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this downscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the downscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

An active contour-based atlas registration model applied to automatic subthalamic nucleus targeting on MRI: method and validation.

This paper presents a new non parametric atlas registration framework, derived from the optical flow model and the active contour theory, applied to automatic subthalamic nucleus (STN) targeting in deep brain stimulation (DBS) surgery. In a previous work, we demonstrated that the STN position can be predicted based on the position of surrounding visible structures, namely the lateral and third ventricles. A STN targeting process can thus be obtained by registering these structures of interest between a brain atlas and the patient image. Here we aim to improve the results of the state of the art targeting methods and at the same time to reduce the computational time. Our simultaneous segmentation and registration model shows mean STN localization errors statistically similar to the most performing registration algorithms tested so far and to the targeting expert's variability. Moreover, the computational time of our registration method is much lower, which is a worthwhile improvement from a clinical point of view.

Detection of plant-modulated alterations in antifungal gene expression in Pseudomonas fluorescens CHA0 on roots by flow cytometry.

The biocontrol activity of the root-colonizing Pseudomonas fluorescens strain CHA0 is largely determined by the production of antifungal metabolites, especially 2,4-diacetylphloroglucinol. The expression of these metabolites depends on abiotic and biotic environmental factors, in particular, elements present in the rhizosphere. In this study, we have developed a new method for the in situ analysis of antifungal gene expression using flow cytometry combined with green fluorescent protein (GFP)-based reporter fusions to the phlA and prnA genes essential for the production of the antifungal compounds 2,4-diacetylphloroglucinol and pyrrolnitrin, respectively, in strain CHA0. Expression of phlA-gfp and prnA-gfp in CHA0 cells harvested from the rhizosphere of a set of plant species as well as from the roots of healthy, leaf pathogen-attacked, and physically stressed plants were analyzed using a FACSCalibur. After subtraction of background fluorescence emitted by plant-derived particles and CHA0 cells not carrying the gfp reporters, the average gene expression per bacterial cell could be calculated. Levels of phlA and prnA expression varied significantly in the rhizospheres of different plant species. Physical stress and leaf pathogen infection lowered phlA expression levels in the rhizosphere of cucumber. Our results demonstrate that the newly developed approach is suitable to monitor differences in levels of antifungal gene expression in response to various plant-derived factors. An advantage of the method is that it allows quantification of bacterial gene expression in rhizosphere populations at a single-cell level. To our best knowledge, this is the first study using flow cytometry for the in situ analysis of biocontrol gene expression in a plant-beneficial bacterium in the rhizosphere.

Fast Geodesic Active Fields for Image Registration Based on Splitting and Augmented Lagrangian Approaches.

In this paper, we present an efficient numerical scheme for the recently introduced geodesic active fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, the data-term and the regularization-term are combined through multiplication in a single, parametrization invariant and geometric cost functional. The multiplicative coupling provides an intrinsic, spatially varying and data-dependent tuning of the regularization strength, and the parametrization invariance allows working with images of nonflat geometry, generally defined on any smoothly parametrizable manifold. The resulting energy-minimizing flow, however, has poor numerical properties. Here, we provide an efficient numerical scheme that uses a splitting approach; data and regularity terms are optimized over two distinct deformation fields that are constrained to be equal via an augmented Lagrangian approach. Our approach is more flexible than standard Gaussian regularization, since one can interpolate freely between isotropic Gaussian and anisotropic TV-like smoothing. In this paper, we compare the geodesic active fields method with the popular Demons method and three more recent state-of-the-art algorithms: NL-optical flow, MRF image registration, and landmark-enhanced large displacement optical flow. Thus, we can show the advantages of the proposed FastGAF method. It compares favorably against Demons, both in terms of registration speed and quality. Over the range of example applications, it also consistently produces results not far from more dedicated state-of-the-art methods, illustrating the flexibility of the proposed framework.

Modelling hydrodynamics in the Rio Parana, Argentina : an evaluation and inter-comparison of reduced-complexity and physics based models applied to a large sand-bed river

Depth-averaged velocities and unit discharges within a 30 km reach of one of the world's largest rivers, the Rio Parana, Argentina, were simulated using three hydrodynamic models with different process representations: a reduced complexity (RC) model that neglects most of the physics governing fluid flow, a two-dimensional model based on the shallow water equations, and a three-dimensional model based on the Reynolds-averaged Navier-Stokes equations. Row characteristics simulated using all three models were compared with data obtained by acoustic Doppler current profiler surveys at four cross sections within the study reach. This analysis demonstrates that, surprisingly, the performance of the RC model is generally equal to, and in some instances better than, that of the physics based models in terms of the statistical agreement between simulated and measured flow properties. In addition, in contrast to previous applications of RC models, the present study demonstrates that the RC model can successfully predict measured flow velocities. The strong performance of the RC model reflects, in part, the simplicity of the depth-averaged mean flow patterns within the study reach and the dominant role of channel-scale topographic features in controlling the flow dynamics. Moreover, the very low water surface slopes that typify large sand-bed rivers enable flow depths to be estimated reliably in the RC model using a simple fixed-lid planar water surface approximation. This approach overcomes a major problem encountered in the application of RC models in environments characterised by shallow flows and steep bed gradients. The RC model is four orders of magnitude faster than the physics based models when performing steady-state hydrodynamic calculations. However, the iterative nature of the RC model calculations implies a reduction in computational efficiency relative to some other RC models. A further implication of this is that, if used to simulate channel morphodynamics, the present RC model may offer only a marginal advantage in terms of computational efficiency over approaches based on the shallow water equations. These observations illustrate the trade off between model realism and efficiency that is a key consideration in RC modelling. Moreover, this outcome highlights a need to rethink the use of RC morphodynamic models in fluvial geomorphology and to move away from existing grid-based approaches, such as the popular cellular automata (CA) models, that remain essentially reductionist in nature. In the case of the world's largest sand-bed rivers, this might be achieved by implementing the RC model outlined here as one element within a hierarchical modelling framework that would enable computationally efficient simulation of the morphodynamics of large rivers over millennial time scales. (C) 2012 Elsevier B.V. All rights reserved.

LiveCount Assay: concomitant measurement of cytolytic activity and phenotypic characterisation of CD8(+) T-cells by flow cytometry.

Tumour immunologists strive to develop efficient tumour vaccination and adoptive transfer therapies that enlarge the pool of tumour-specific and -reactive effector T-cells in vivo. To assess the efficiency of the various strategies, ex vivo assays are needed for the longitudinal monitoring of the patient's specific immune responses providing both quantitative and qualitative data. In particular, since tumour cell cytolysis is the end goal of tumour immunotherapy, routine immune monitoring protocols need to include a read-out for the cytolytic efficiency of Ag-specific cells. We propose to combine current immune monitoring techniques in a highly sensitive and reproducible multi-parametric flow cytometry based cytotoxicity assay that has been optimised to require low numbers of Ag-specific T-cells. The possibility of re-analysing those T-cells that have undergone lytic activity is illustrated by the concomitant detection of CD107a upregulation on the surface of degranulated T-cells. To date, the LiveCount Assay provides the only possibility of assessing the ex vivo cytolytic activity of low-frequency Ag-specific cytotoxic T-lymphocytes from patient material.

Adjustable Suture Removal: Increasing Aqueous Flow in "Safe" Trabeculectomy.

Purpose: Aqueous flow through trabeculectomy blebs has been suggested to influence filtration bleb survival. We investigated the relationship between the requirement to increase aqueous flow via adjustable suture removal and surgical outcomes following "safe trabeculectomy" with mitomycin C (MMC). Methods: 62 consecutive eyes of 53 patients underwent fornix based trabeculectomy with adjustable sutures, intraoperative MMC and intensive postoperative steroids. Subconjunctival antimetabolite injections and bleb needlings were administered according to bleb vascularity and IOP trends. Main outcome measures were: success rates (definition: IOP≤21mmHg and 20% IOP reduction); number of antimetabolite injections; bleb needlings; number of of eyes recommencing glaucoma medications and complications. Results: Mean age was 70.4±16.0 years (mean± SD); mean preoperative IOP was 24.5±9.1 mmHg and decreased to 12.3±8.9mmHg postoperatively. Mean number of sutures was 2.6 ± 0.7. Eyes were divided into 2 groups in relation to the number of sutures removed. The number of subconjunctival MMC injections required for those requiring 2 suture removals was significantly greater than those requiring 1 suture removal (p<0.05) The number of needlings and 5FU injections also increased but did not reach significance (p=0.09 and p=0.34 respectively). Least-squared linear regression analysis showed the number of needlings required had a statistically significant (p=0.05) trend with respect to time elapsed between surgery and first suture removal. No other interventions had significant trends. Mean time between surgery and suture removal was: 4.2±9.2 weeks (suture #1) and 5.7±9.7 weeks (suture#2). Antiglaucoma medication was restarted in only 5 eyes. Postoperative complications were infrequent: Seidel (3.2%), peripheral choroidal effusions at any time (3.2%), and shallow anterior chamber (1.6%). Conclusion: Eyes requiring a greater number of suture removals required a significantly greater number of antifibrosis interventions. The time elapsed before suture removal was inversely related to the number of postoperative needlings, suggesting these eyes may have decreased aqueous production and therefore require aggressive post-operative management to prevent bleb failure.

Aggregation under a forced convective flow

Morphological transitions are analyzed for a radial multiparticle diffusion-limited aggregation process grown under a convective drift. The introduction of a tangential flow changes the morphology of the diffusion-limited structure, into multiarm structures, inclined opposite to the flow, whose limit consists of single arms, when decreasing density. The case of shear flow is also considered. The anisotropy of the patterns is characterized in terms of a tangential correlation function based analysis. Comparison between the simulation results and preliminary experimental results has been done.

Line search multilevel optimization as computational methods for dense optical flow

We evaluate the performance of different optimization techniques developed in the context of optical flow computation with different variational models. In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we de- velop the use of efficient multilevel schemes for computing the optical flow. More precisely, we evaluate the performance of a standard unidirectional mul- tilevel algorithm - called multiresolution optimization (MR/OPT), to a bidrec- tional multilevel algorithm - called full multigrid optimization (FMG/OPT). The FMG/OPT algorithm treats the coarse grid correction as an optimiza- tion search direction and eventually scales it using a line search. Experimental results on different image sequences using four models of optical flow com- putation show that the FMG/OPT algorithm outperforms both the TN and MR/OPT algorithms in terms of the computational work and the quality of the optical flow estimation.

Levels and determinants of inflammatory biomarkers in a Swiss population-based sample (CoLaus Study).

OBJECTIVE: to assess the levels and determinants of interleukin (IL)-1ß, IL-6, tumour necrosis factor (TNF)-a and C-reactive protein (CRP) in a healthy Caucasian population.METHODS: population sample of 2884 men and 3201 women aged 35 to 75. IL-1ß, IL-6 and TNF-a were assessed by a multiplexed particle-based flow cytometric assay and CRP by an immunometric assay.RESULTS: Spearman rank correlations between duplicate cytokine measurements (N?=?80) ranged between 0.89 and 0.96; intra-class correlation coefficients ranged between 0.94 and 0.97, indicating good reproducibility. Among the 6085 participants, 2289 (37.6%), 451 (7.4%) and 43 (0.7%) had IL-1ß, IL-6 and TNF-a levels below detection limits, respectively. Median (interquartile range) for participants with detectable values were 1.17 (0.48-3.90) pg/ml for IL-1ß; 1.47 (0.71-3.53) pg/ml for IL-6; 2.89 (1.82-4.53) pg/ml for TNF-a and 1.3 (0.6-2.7) ng/ml for CRP. On multivariate analysis, greater age was the only factor inversely associated with IL-1ß levels. Male sex, increased BMI and smoking were associated with greater IL-6 levels, while no relationship was found for age and leisure-time PA. Male sex, greater age, increased BMI and current smoking were associated with greater TNF-a levels, while no relationship was found with leisure-time PA. CRP levels were positively related to age, BMI and smoking, and inversely to male sex and physical activity.CONCLUSION: Population-based levels of several cytokines were established. Increased age and BMI, and to a lesser degree sex and smoking, significantly and differentially impact cytokine levels, while leisure-time physical activity has little effect.

Association of statins with inflammatory cytokines: a population-based Colaus study.

PURPOSE: A pleiotropic effect of statins has been reported in numerous studies. However, the association between statin use and inflammatory cytokines is controversial. We examined the associations between statin use and C-reactive protein (CRP), tumour necrosis factor α (TNF-α), interleukin-1β (IL-1β) and interleukin-6 (IL-6) in a healthy Caucasian population. METHODS: Cross-sectional study of 6184 participants aged 35-75years from Lausanne, Switzerland. Cytokines were assessed by multiplexed particle-based flow cytometric assay. Self-reported history of medication was collected for statins and other medication. 99 participants without cytokine data were excluded. RESULTS: Among the 6085 participants, 2289 (37.6%), 451 (7.4%) and 43 (0.7%) had IL-1β, IL-6 and TNF-α levels below detection limits, respectively. On multivariate analysis adjusting for age, gender, smoking status, body mass index, hypertension, diabetes, baseline cardiovascular disease, total cholesterol, anti-inflammatory use, other cytokine modifying drugs and other drugs, participants on statins had significantly lower CRP levels (adjusted mean±standard error: 1.22±1.05 vs. 1.38±1.04mg/L for use and non-use, respectively, p<0.01 on log-transformed data). Conversely, no association was found between statin use and IL-1β (p=0.91), IL-6 (p=0.25) or TNF-α (p=0.28) levels. On multivariate analysis, individuals in the statin group (β coefficient=-0.12; 95% CI=-0.21, -0.03) had lower levels of CRP as compared to those in the reference group (i.e. those not using statin). However, no significant associations were observed between IL-1β, IL-6 and TNF-α and statins. CONCLUSION: Individuals on statins have lower CRP levels; conversely, no effect was found for IL-1β, IL-6 and TNF-α levels.

Cytokines and hs-CRP levels in individuals treated with low-dose aspirin for cardiovascular prevention: a population-based study (CoLaus Study).

Pro-inflammatory cytokines and high-sensitive C-reactive protein (hs-CRP) are associated with increased risk for cardiovascular disease. Low-dose aspirin for CV prevention is reported to have anti-inflammatory effects. The aim of this study was to determine the association between pro-inflammatory cytokines and hs-CRP levels and low-dose aspirin use for cardiovascular prevention in a population-based cohort (CoLaus Study). We assessed blood samples in 6085 participants (3201 women) aged 35-75years. Medications' use and indications were recorded. Among aspirin users (n=1'034; 17%), overall low-dose users (351; 5.8%) and low-dose for cardiovascular prevention users (324; 5.3%) were selected for analysis. Pro-inflammatory cytokines (IL-1β, IL-6 and TNF-α were assessed by a multiplex particle-based flow cytometric assay and hs-CRP by an immunometric assay. Cytokines and hs-CRP were presented in quartiles. Multivariate analysis adjusting for sex, age, smoking status, body mass index, diabetes mellitus and immunomodulatory drugs showed no association between cytokines and hs-CRP levels and low-dose aspirin use for cardiovascular prevention, either comparing the topmost vs. the three other quartiles (OR 95% CI, 0.84 (0.59-1.18), 1.03 (0.78-1.32), 1.10 (0.83-1.46), 1.00 (0.67-1.69) for IL-1β, IL-6, TNF-α and hs-CRP, respectively), or comparing the topmost quartile vs. the first one (OR 95% CI, 0.87 (0.60-1.26), 1.19 (0.79-1.79), 1.26 (0.86-1.84), 1.06 (0.67-1.69)). Low-dose aspirin use for cardiovascular prevention does not impact plasma pro-inflammatory cytokine and hs-CRP levels in a population-based cohort.

A non-linear Bayesian approach for upscaling local-scale hydraulic conductivity measurements based on local- and regional-scale geophysical data

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed an upscaling procedure based on a Bayesian sequential simulation approach. This method is then applied to the stochastic integration of low-resolution, regional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this upscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.