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.

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

The development of susceptibility maps for debris flows is of primary importance due to population pressure in hazardous zones. However, hazard assessment by processbased modelling at a regional scale is difficult due to the complex nature of the phenomenon, the variability of local controlling factors, and the uncertainty in modelling parameters. A regional assessment must consider a simplified approach that is not highly parameter dependant and that can provide zonation with minimum data requirements. A distributed empirical model has thus been developed for regional susceptibility assessments using essentially a digital elevation model (DEM). The model is called Flow-R for Flow path assessment of gravitational hazards at a Regional scale (available free of charge under www.flow-r.org) and has been successfully applied to different case studies in various countries with variable data quality. It provides a substantial basis for a preliminary susceptibility assessment at a regional scale. The model was also found relevant to assess other natural hazards such as rockfall, snow avalanches and floods. The model allows for automatic source area delineation, given user criteria, and for the assessment of the propagation extent based on various spreading algorithms and simple frictional laws.We developed a new spreading algorithm, an improved version of Holmgren's direction algorithm, that is less sensitive to small variations of the DEM and that is avoiding over-channelization, and so produces more realistic extents. The choices of the datasets and the algorithms are open to the user, which makes it compliant for various applications and dataset availability. Amongst the possible datasets, the DEM is the only one that is really needed for both the source area delineation and the propagation assessment; its quality is of major importance for the results accuracy. We consider a 10m DEM resolution as a good compromise between processing time and quality of results. However, valuable results have still been obtained on the basis of lower quality DEMs with 25m resolution.

Genetic dissection of azole resistance mechanisms in Candida albicans and their validation in a mouse model of disseminated infection.

Principal mechanisms of resistance to azole antifungals include the upregulation of multidrug transporters and the modification of the target enzyme, a cytochrome P450 (Erg11) involved in the 14alpha-demethylation of ergosterol. These mechanisms are often combined in azole-resistant Candida albicans isolates recovered from patients. However, the precise contributions of individual mechanisms to C. albicans resistance to specific azoles have been difficult to establish because of the technical difficulties in the genetic manipulation of this diploid species. Recent advances have made genetic manipulations easier, and we therefore undertook the genetic dissection of resistance mechanisms in an azole-resistant clinical isolate. This isolate (DSY296) upregulates the multidrug transporter genes CDR1 and CDR2 and has acquired a G464S substitution in both ERG11 alleles. In DSY296, inactivation of TAC1, a transcription factor containing a gain-of-function mutation, followed by sequential replacement of ERG11 mutant alleles with wild-type alleles, restored azole susceptibility to the levels measured for a parent azole-susceptible isolate (DSY294). These sequential genetic manipulations not only demonstrated that these two resistance mechanisms were those responsible for the development of resistance in DSY296 but also indicated that the quantitative level of resistance as measured in vitro by MIC determinations was a function of the number of genetic resistance mechanisms operating in any strain. The engineered strains were also tested for their responses to fluconazole treatment in a novel 3-day model of invasive C. albicans infection of mice. Fifty percent effective doses (ED(50)s) of fluconazole were highest for DSY296 and decreased proportionally with the sequential removal of each resistance mechanism. However, while the fold differences in ED(50) were proportional to the fold differences in MICs, their magnitude was lower than that measured in vitro and depended on the specific resistance mechanism operating.

How does the body-scale model affect back-calculated growth: the example of arctic charr Salvelinus alpinus (L.) of Lake Geneva (Switzerland)

When back-calculating fish length from scale measurements, the choice of the body-scale relationship is a fundamental step. Using data from the arctic charrSalvelinus alpinus (L.) of Lake Geneva (Switzerland) we show the need for a curvilinear model, on both statistical and biological grounds. From several 2-parameters models, the log-linear relationship appears to provide the best fit. A 3-parameters, Bertalanffy model did not improve the fit. We show moreover that using the proportional model would lead to important misinterpretations of the data.

Preliminary assessment of rockslide and rockfall hazards using a DEM (Oppstadhornet, Norway)

The increasing availability and precision of digital elevation model (DEM) helps in the assessment of landslide prone areas where only few data are available. This approach is performed in 6 main steps which include: DEM creation; identification of geomorphologic features; determination of the main sets of discontinuities; mapping of the most likely dangerous structures; preliminary rock-fall assessment; estimation of the large instabilities volumes. The method is applied to two the cases studies in the Oppstadhornet mountain (730m alt): (1) a 10 millions m3 slow-moving rockslide and (2) a potential high-energy rock falling prone area. The orientations of the foliation and of the major discontinuities have been determined directly from the DEM. These results are in very good agreement with field measurements. Spatial arrangements of discontinuities and foliation with the topography revealed hazardous structures. Maps of potential occurrence of these hazardous structures show highly probable sliding areas at the foot of the main landslide and potential rock falls in the eastern part of the mountain.

The handaxe and the microscope: individual and social learning in a multidimensional model of adaptation

When individuals learn by trial-and-error, they perform randomly chosen actions and then reinforce those actions that led to a high payoff. However, individuals do not always have to physically perform an action in order to evaluate its consequences. Rather, they may be able to mentally simulate actions and their consequences without actually performing them. Such fictitious learners can select actions with high payoffs without making long chains of trial-and-error learning. Here, we analyze the evolution of an n-dimensional cultural trait (or artifact) by learning, in a payoff landscape with a single optimum. We derive the stochastic learning dynamics of the distance to the optimum in trait space when choice between alternative artifacts follows the standard logit choice rule. We show that for both trial-and-error and fictitious learners, the learning dynamics stabilize at an approximate distance of root n/(2 lambda(e)) away from the optimum, where lambda(e) is an effective learning performance parameter depending on the learning rule under scrutiny. Individual learners are thus unlikely to reach the optimum when traits are complex (n large), and so face a barrier to further improvement of the artifact. We show, however, that this barrier can be significantly reduced in a large population of learners performing payoff-biased social learning, in which case lambda(e) becomes proportional to population size. Overall, our results illustrate the effects of errors in learning, levels of cognition, and population size for the evolution of complex cultural traits. (C) 2013 Elsevier Inc. All rights reserved.

Continuous positive airway pressure causes lung injury in a model of sepsis.

Continuous positive airway pressure, aimed at preventing pulmonary atelectasis, has been used for decades to reduce lung injury in critically ill patients. In neonatal practice, it is increasingly used worldwide as a primary form of respiratory support due to its low cost and because it reduces the need for endotracheal intubation and conventional mechanical ventilation. We studied the anesthetized in vivo rat and determined the optimal circuit design for delivery of continuous positive airway pressure. We investigated the effects of continuous positive airway pressure following lipopolysaccharide administration in the anesthetized rat. Whereas neither continuous positive airway pressure nor lipopolysaccharide alone caused lung injury, continuous positive airway pressure applied following intravenous lipopolysaccharide resulted in increased microvascular permeability, elevated cytokine protein and mRNA production, and impaired static compliance. A dose-response relationship was demonstrated whereby higher levels of continuous positive airway pressure (up to 6 cmH(2)O) caused greater lung injury. Lung injury was attenuated by pretreatment with dexamethasone. These data demonstrate that despite optimal circuit design, continuous positive airway pressure causes significant lung injury (proportional to the airway pressure) in the setting of circulating lipopolysaccharide. Although we would currently avoid direct extrapolation of these findings to clinical practice, we believe that in the context of increasing clinical use, these data are grounds for concern and warrant further investigation.