Ground penetrating radar application in a shallow marine Oxfordian limestone sequence located on the eastern flank of the Paris Basin, NE France

A Ground Penetrating Radar (GPR) survey has been carried out in Upper Jurassic limestones located on the eastern flank of the Paris Basin (NE France). The potential of the investigation method is assessed for delineating geologically meaningful stratifications in the shallow subsurface. The fundamentals of the GPR technique are described. Penetration depth and vertical resolution depends on the soil conditions, the characteristics of input signal and the configuration of the transmitter–receiver assembly. In the studied carbonates the penetration level is rather good and the electromagnetic signal reaches up to 1000 nanoseconds maximum (i.e. approximately 55 m). Several depositional units are outlined on the GPR profiles. Six different lithological units are recognised with distinct GPR reflection characteristics. The profiles illustrate the internal 3D organisation of the carbonate platform and its geometry. They provide detailed insight into the nature of an Oxfordian reefal build-up. The high-resolution subsurface model is directly calibrated with geological field observations and it results in a predictive 3D depositional working model. The GPR method is a non-destructive remote sensing technique that is cost effective. The method is considered complementary to other conventional high-resolution reservoir characterisation studies. It represents a powerful investigation tool in earth science studies concerning the imaging of the structure of the shallow subsurface.     

Models of forbidden line emission profiles from axisymmetric stellar winds

A number of strong infrared forbidden lines have been observed in several evolved Wolf–Rayet (WR) star winds, and these are important for deriving metal abundances and testing stellar evolution models. In addition, because these optically thin lines form at large radius in the wind, their resolved profiles carry an imprint of the asymptotic structure of the wind flow. This work presents model forbidden line profile shapes formed in axisymmetric winds. It is well known that an optically thin emission line formed in a spherical wind expanding at constant velocity yields a flat-topped emission profile shape. Simulated forbidden lines are produced for a model stellar wind with an axisymmetric density distribution that treats the latitudinal ionization self-consistently and examines the influence of the ion stage on the profile shape. The resulting line profiles are symmetric about line centre. Within a given atomic species, profile shapes can vary between centrally peaked, doubly peaked, and approximately flat-topped in appearance depending on the ion stage (relative to the dominant ion) and viewing inclination. Although application to WR star winds is emphasized, the concepts are also relevant to other classes of hot stars such as luminous blue variables and Be/B[e] stars.     

Geochemical characterisation, provenance, source and depositional environment of ‘Roches Argilo-Talqueuses’ (RAT) and Mines Subgroups sedimentary rocks in the Neoproterozoic Katangan Belt (Congo): Lithostratigraphic implications

The chemical characteristics of sedimentary rocks provide important clues to their provenance and depositional environments. Chemical analyses of 192 samples of Katangan sedimentary rocks from Kolwezi, Kambove–Kabolela and Luiswishi in the central African Copperbelt (Katanga, Congo) are used to constrain (1) the source and depositional environment of RAT and Mines Subgroup sedimentary rocks and (2) the geochemical relations between the rocks from these units and the debate on the lithostratigraphic position of the RAT Subgroup within the Katangan sedimentary succession. The geochemical data indicate that RAT, D. Strat., RSF and RSC are extremely poor in alkalis and very rich in MgO. SD are richer in alkalis, especially K₂O. Geochemical characteristics of RAT and Mines Subgroups sedimentary rocks indicate deposition under an evaporitic environment that evolved from oxidizing (Red RAT) to reducing (Grey RAT and Mines Subgroup) conditions. There is no chemical difference between RAT and fine-grained clastic rocks from the lower part of the Mines Subgroup. The geochemical data preclude the genetic model that RAT are syn-orogenic sedimentary rocks originating from Mines Group rocks by erosion and gravity-induced fragmentation in front of advancing nappes.     

Polarization variability arising from clumps in the winds of Wolf-Rayet stars

Polarimetric and photometric variability of Wolf-Rayet (WR) stars as caused by clumps in the winds is revisited. In our model, which is improved from Li et al., radial ex-pansion of the thickness is accounted for, but we retain dependence on theβ velocity law and stellar occultation effects. We again search for parameters that can yield results con-sistent with observations in regards to the mean polarization P, the ratio R = σ'p/σphot of polarimetric to photometric variability and the volume filling factor fv. Clump gener-ation and spatial distribution are randomized by the Monte Carlo method so as to produce clumps which are, in the mean, distributed uniformly in space and have time intervals that obey a Gaussian distribution. The generated clumps move radially outward with a velocity law determined by aβ index, and the angular size of clumps is assumed to be fixed. By fitting the observed σp/σphot and the volume filling factor fv, clump velocity law index β (～2) and clump ejection rate N (～1) are inferred, and are found to be well constrained. In addition, the subpeak features of broad emission lines seem to support the clump ejection rate. Meanwhile, the fraction of total mass loss rate that is contained in clumps is obtained by fitting observed polarization. We conclude that this picture of the clumps' properties produces a valuable diagnostic of WR wind structure.     

Learning wind fields with multiple kernels

This paper presents multiple kernel learning (MKL) regression as an exploratory spatial data analysis and modelling tool. The MKL approach is introduced as an extension of support vector regression, where MKL uses dedicated kernels to divide a given task into sub-problems and to treat them separately in an effective way. It provides better interpretability to non-linear robust kernel regression at the cost of a more complex numerical optimization. In particular, we investigate the use of MKL as a tool that allows us to avoid using ad-hoc topographic indices as covariables in statistical models in complex terrains. Instead, MKL learns these relationships from the data in a non-parametric fashion. A study on data simulated from real terrain features confirms the ability of MKL to enhance the interpretability of data-driven models and to aid feature selection without degrading predictive performances. Here we examine the stability of the MKL algorithm with respect to the number of training data samples and to the presence of noise. The results of a real case study are also presented, where MKL is able to exploit a large set of terrain features computed at multiple spatial scales, when predicting mean wind speed in an Alpine region.     

Can a Simulated Flood Experience Improve Social Resilience to Disasters?

The increase of extreme meteorological phenomena, along with continuous population growth, has led to a rising number of flooding disasters. Therefore, there is an urgent need to develop better risk reduction strategies, among which is increased social resilience. Experiencing a disaster is recognized as a factor that positively influences overall community resilience, with particular effects on social resilience; it appears to be more influential than school education. It also has many negative effects, though. Previous studies underline that citizens do not distinguish between different types of experiences. Thus, we investigated whether a simulated experience of a flood can improve social resilience, without being hampered by negative repercussions. The study was executed in five municipalities in three Italian regions involved in the European project LIFE PRIMES, which planned simulation activities for each studied area. Data, collected through the administration of anonymous questionnaires before and after a flood drill, were processed by applying a multicriteria decision analysis tool (PROMETHEE). Results show that the drill significantly augmented perceived social resilience in the smaller studied communities but not in the larger ones, a fact that should be further investigated. Key Words: multicriteria decision analysis, simulated flood experience, social resilience to disasters.     

Exospheric models for the X-ray emission from single Wolf–Rayet stars

We review existing ROSAT detections of single Galactic Wolf–Rayet (WR) stars and develop wind models to interpret the X-ray emission. The ROSAT data, consisting of bandpass detections from the ROSAT All-Sky Survey (RASS) and some pointed observations, exhibit no correlations of the WR X-ray luminosity ( L _X) with any star or wind parameters of interest (e.g. bolometric luminosity, mass-loss rate or wind kinetic energy), although the dispersion in the measurements is quite large. The lack of correlation between X-ray luminosity and wind parameters among the WR stars is unlike that of their progenitors, the O stars, which show trends with such parameters. In this paper we seek to (i) test by how much the X-ray properties of the WR stars differ from the O stars and (ii) place limits on the temperature T _X and filling factor f _X of the X-ray-emitting gas in the WR winds. Adopting empirically derived relationships for T _X and f _X from O-star winds, the predicted X-ray emission from WR stars is much smaller than observed with ROSAT . Abandoning the T _X relation from O stars, we maximize the cooling from a single-temperature hot gas to derive lower limits for the filling factors in WR winds. Although these filling factors are consistently found to be an order of magnitude greater than those for O stars, we find that the data are consistent (albeit the data are noisy) with a trend of in WR stars, as is also the case for O stars.