A multi-agent simulation to assess the risk of malaria re-emergence in southern France

A multi-agent simulation (MAS) was developed to assess the risk of malaria re-emergence in the Camargue in southern France, a non-endemic area where mosquitoes of the genus Anopheles (Culicidae) live. The contact rate between people and potential malaria vectors, or the human biting rate, is one of the key factor to predict the risk of re-emergence of malaria, would the parasite be introduced in the region. Our model (called MALCAM) represents the different agents that could influence malaria transmission in the Camargue – people, mosquitoes, animal hosts and the landscape – in a spatially explicit environment. The model simulates spatial and temporal variations in human biting rate at the landscape scale. These variations depend on the distribution of people and potential vectors, their behaviour and their interactions. A land use/cover map was used as a cellular-spatial support for the movements of and interactions between mobile agents. The model was tested for its sensitivity to variations in parameter values, and for the agreement between field observations and model predictions. The MALCAM model provides a tool to better understand the interactions between the multiple agents of the disease transmission system, and the land use and land cover factors that control the spatial heterogeneity in these interactions. It allows testing hypotheses and scenarios related to disease dynamics by varying the value of exogenous biological, geographical, or human factors. This application of agent-based modelling to a human vector-borne disease can be adapted to different diseases and regions.     

An architectural model of spring wheat: Evaluation of the effects of population density and shading on model parameterization and performance

ADELwheat is an architectural model that describes development of wheat in 3D. This paper analyzes the robustness of the parameterization of ADELwheat for spring wheat cultivars in relation to plant population density and shading. The model was evaluated using data from two spring wheat experiments with three plant population densities and two light regimes. Model validation was done at two levels of aggregation: (a) by comparing parameterization functions used as well as parameter values to the data (leaf and tiller appearance, leaf number, blade dimensions, sheath length, internode length) and (b) by comparing ground cover (GC) and leaf area index (LAI) of simulated virtual wheat plots with GC and LAI calculated from data. A sensitivity analysis was performed by modulating parameters defining leaf blade dimensions and leaf or tiller appearance rate.In contrast to population density, shading generally increased phyllochron and delayed tiller appearance. Both at the level of the organ and at the level of the canopy the model performed satisfactorily. Parameterization functions in the model that had been established previously applied to independent data for different conditions; GC and LAI were simulated adequately at three population densities. Sensitivity analysis revealed that calibration of phyllochron and blade area needs to be accurate to prevent disproportional deviations in output.The robustness of the model parameterization and the simulation performance confirmed that the model is a complete architectural model for aboveground development of spring wheat. It can be used in studies that require simulation of spring wheat structure, such as studies on plant–insect interaction, remote sensing, and light interception.     

Powered two-wheeler riders' risk of crashes associated with filtering on urban roads

Objective: The objective of this study is to estimate the crash risk per kilometer traveled by powered two-wheeler (PTW) riders filtering through traffic on urban roads.

Methods: Using the traffic injury crashes recorded by the police over a period of 3 years on 14 sections of urban roads in the city of Marseille, France, and a campaign of observations of PTWs, the crash risk per kilometer traveled by PTWs filtering was estimated and compared to the risk of PTWs that did not filter.

Results: The results show that the risk of PTW riders being involved in injury crashes while filtering is significantly higher than the risk for riders who do not filter. For the 14 sections studied, it is 3.94 times greater (95% confidence interval [CI], 2.63, 5.89). This excess risk occurred for all PTW categories. Furthermore, no space appears to be safer than the others for filtering. Riders filtering forward along the axis of the carriageway, along bus lanes, or between traffic lanes (lane-splitting) all have a crash risk greater than the risk of those who do not filter.

Conclusions: All measures limiting the practice of filtering by PTWs on urban roads would probably contribute to improving the safety of their users.     

Lipid peroxidation in the presence of iron oxides

Exposure to iron oxides dusts may lead to lung cancers among exposed population. To evaluate the involvement of iron‐containing particles in lipid peroxidation by production of reactive oxygen species, hematite, magnetite (iron oxides), and crocidolite (asbestos compound) were tested. The peroxidation was followed by the evaluation of some degradation products of lino‐lenic acid. In a buffered medium, magnetite is higher active than hematite. The addition of an iron chelator (EDTA) or of a reducing agent (ascorbate) in this medium enhances the activity of hematite and magnetite, and the combination of both EDTA and ascorbate increases their activity. Crocidolite is the most active whatever the medium. The appearance of the EDTA‐iron‐oxygen complexes related to the reactivity of these oxides is postulated. These results suggest that the oxidizing activity triggered by hematite and magnetite, in a medium containing an iron chelator and a reducing agent, may lead to damages in biological medium.     

CO2 storage capacity estimation: Methodology and gaps

Implementation of CO₂ capture and geological storage (CCGS) technology at the scale needed to achieve a significant and meaningful reduction in CO₂ emissions requires knowledge of the available CO₂ storage capacity. CO₂ storage capacity assessments may be conducted at various scales—in decreasing order of size and increasing order of resolution: country, basin, regional, local and site-specific. Estimation of the CO₂ storage capacity in depleted oil and gas reservoirs is straightforward and is based on recoverable reserves, reservoir properties and in situ CO₂ characteristics. In the case of CO₂-EOR, the CO₂ storage capacity can be roughly evaluated on the basis of worldwide field experience or more accurately through numerical simulations. Determination of the theoretical CO₂ storage capacity in coal beds is based on coal thickness and CO₂ adsorption isotherms, and recovery and completion factors. Evaluation of the CO₂ storage capacity in deep saline aquifers is very complex because four trapping mechanisms that act at different rates are involved and, at times, all mechanisms may be operating simultaneously. The level of detail and resolution required in the data make reliable and accurate estimation of CO₂ storage capacity in deep saline aquifers practical only at the local and site-specific scales. This paper follows a previous one on issues and development of standards for CO₂ storage capacity estimation, and provides a clear set of definitions and methodologies for the assessment of CO₂ storage capacity in geological media. Notwithstanding the defined methodologies suggested for estimating CO₂ storage capacity, major challenges lie ahead because of lack of data, particularly for coal beds and deep saline aquifers, lack of knowledge about the coefficients that reduce storage capacity from theoretical to effective and to practical, and lack of knowledge about the interplay between various trapping mechanisms at work in deep saline aquifers.     

Polynomial Surrogates for Open-Channel Flows in Random Steady State

Assessing epistemic uncertainties is considered as a milestone for improving numerical predictions of a dynamical system. In hydrodynamics, uncertainties in input parameters translate into uncertainties in simulated water levels through the shallow water equations. We investigate the ability of generalized polynomial chaos (gPC) surrogate to evaluate the probabilistic features of water level simulated by a 1-D hydraulic model (MASCARET) with the same accuracy as a classical Monte Carlo method but at a reduced computational cost. This study highlights that the water level probability density function and covariance matrix are better estimated with the polynomial surrogate model than with a Monte Carlo approach on the forward model given a limited budget of MASCARET evaluations. The gPC-surrogate performance is first assessed on an idealized channel with uniform geometry and then applied on the more realistic case of the Garonne River (France) for which a global sensitivity analysis using sparse least-angle regression was performed to reduce the size of the stochastic problem. For both cases, Galerkin projection approximation coupled to Gaussian quadrature that involves a limited number of forward model evaluations is compared with least-square regression for computing the coefficients when the surrogate is parameterized with respect to the local friction coefficient and the upstream discharge. The results showed that a gPC-surrogate with total polynomial degree equal to 6 requiring 49 forward model evaluations is sufficient to represent the water level distribution (in the sense of the \(\ell _2\) norm), the probability density function and the water level covariance matrix for further use in the framework of data assimilation. In locations where the flow dynamics is more complex due to bathymetry, a higher polynomial degree is needed to retrieve the water level distribution. The use of a surrogate is thus a promising strategy for uncertainty quantification studies in open-channel flows and should be extended to unsteady flows. It also paves the way toward cost-effective ensemble-based data assimilation for flood forecasting and water resource management.     

Degradation of CL-20 by white-rot fungi

In previous studies, we found that the emerging energetic chemical, CL-20 (C6H6N12O12, 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane), can be degraded following its initial denitration using both aerobic and anaerobic bacteria. The C and N mass balances were not determined due to the absence of labeled starting compounds. The present study describes the degradation of the emerging contaminant by Phanerochaete chrysosporium using ring-labeled [15N]-CL-20 and [14C]-CL-20. Ligninolytic cultures degraded CL-20 with the release of nitrous oxide (N2O) in amounts corresponding to 45% of the nitrogen content of CL-20. When ring-labeled [15N]-CL-20 was used, both 14N14NO and 15N14NO were observed, likely produced from -NO2 and N-NO2, respectively. The incubation of uniformly labeled [14C]-CL-20 with fungi led to the production of 14CO2 (> 80%). Another ligninolytic fungus, Irpex lacteus, was also able to degrade CL-20, but as for P. chrysosporium, no early intermediates were observed. When CL-20 was incubated with manganese peroxidase (MnP), we detected an intermediate with a [M-H]- mass ion at 345 Da (or 351 and 349 Da when using ring-labeled and nitro-labeled [15N]-CL-20, respectively) matching a molecular formula of C6H6N10O8. The intermediate was thus tentatively identified as a doubly denitrated CL-20 product. The concomitant release of nitrite ions (NO2-) with CL-20 degradation by MnP also supported the occurrence of an initial denitration prior to cleavage and decomposition.     

Microorganisms for remediation of cadmium-contaminated soils

An alternative to the cleaning-up of agricultural soil contaminated by heavy metals is to avoid their transfer from soil to plant by inoculating soil with selected microorganisms able to biosorb heavy metals. Here, four bacteria species and a fungus isolated from contaminated soils revealed their ability to grow in the presence of high cadmium level. We tested their growth capacity related to pH and Cd concentration on synthetic and soil extract media. The comparison of their growth rate, the biosorbed cadmium rate and the specific biosorption allowed to select the most efficient microorganism to be used in bioremediation.