U-Pb and Ar-Ar geochronological data from the Pelagonian basement in Evia (Greece): geodynamic implications for the evolution of Paleotethys

High precision U-Pb zircon and Ar-40/Ar-39 mica geochronological data on metagranodiorites, metagranites and mica schists from north and central Evia island (Greece) are presented in this study. U-Pb zircon ages range from 308 to 1912 Ma, and indicate a prolonged magmatic activity in Late Carboniferous. Proterozoic ages represent inherited cores within younger crystals. Muscovite Ar-40/Ar-39 plateau ages of 288 to 297 Ma are interpreted as cooling ages of the magmatic bodies and metamorphic host rocks in upper greenschist to epidote-amphibolite metamorphic conditions. The multistage magmatism had a duration between 308 and 319 hla but some older intrusions, as well as metamorphic events, cannot be excluded. Geochemical analyses and zircon typology indicate calc-alkaline affinities for the granites of central Evia and alkaline to calc-alkaline characteristics for the metagranodiorites from the northern part of the island. The new data point towards the SE continuation, in Evia and the Cyclades, of a Variscan continental crust already recognised in northern Greece (Pelagonian basement). The Late Carboniferous magmatism is viewed as a result of northward subduction of the Paleotethys under the Eurasian margin.

Regulatory assessment of in vitro skin corrosion and irritation data within the European framework: Workshop recommendations

Validated in vitro methods for skin corrosion and irritation were adopted by the OECD and by the European Union during the last decade. In the EU, Switzerland and countries adopting the EU legislation, these assays may allow the full replacement of animal testing for identifying and classifying compounds as skin corrosives, skin irritants, and non irritants. In order to develop harmonised recommendations on the use of in vitro data for regulatory assessment purposes within the European framework, a workshop was organized by the Swiss Federal Office of Public Health together with ECVAM and the BfR. It comprised stakeholders from various European countries involved in the process from in vitro testing to the regulatory assessment of in vitro data. Discussions addressed the following questions: (1) the information requirements considered useful for regulatory assessment; (2) the applicability of in vitro skin corrosion data to assign the corrosive subcategories as implemented by the EU Classification, Labelling and Packaging Regulation; (3) the applicability of testing strategies for determining skin corrosion and irritation hazards; and (4) the applicability of the adopted in vitro assays to test mixtures, preparations and dilutions. Overall, a number of agreements and recommendations were achieved in order to clarify and facilitate the assessment and use of in vitro data from regulatory accepted methods, and ultimately help regulators and scientists facing with the new in vitro approaches to evaluate skin irritation and corrosion hazards and risks without animal data.

Measuring an effect size from dichotomized data : contrasted results whether using a correlation or an odds-ratio

It is well known that dichotomizing continuous data has the effect to decrease statistical power when the goal is to test for a statistical association between two variables. Modern researchers however are focusing not only on statistical significance but also on an estimation of the "effect size" (i.e., the strength of association between the variables) to judge whether a significant association is also clinically relevant. In this article, we are interested in the consequences of dichotomizing continuous data on the value of an effect size in some classical settings. It turns out that the conclusions will not be the same whether using a correlation or an odds ratio to summarize the strength of association between the variables: Whereas the value of a correlation is typically decreased by a factor pi/2 after each dichotomization, the value of an odds ratio is at the same time raised to the power 2. From a descriptive statistical point of view, it is thus not clear whether dichotomizing continuous data leads to a decrease or to an increase in the effect size, as illustrated using a data set to investigate the relationship between motor and intellectual functions in children and adolescents

Conditioning of stochastic 3-D fracture networks to hydrological and geophysical data

The geometry and connectivity of fractures exert a strong influence on the flow and transport properties of fracture networks. We present a novel approach to stochastically generate three-dimensional discrete networks of connected fractures that are conditioned to hydrological and geophysical data. A hierarchical rejection sampling algorithm is used to draw realizations from the posterior probability density function at different conditioning levels. The method is applied to a well-studied granitic formation using data acquired within two boreholes located 6 m apart. The prior models include 27 fractures with their geometry (position and orientation) bounded by information derived from single-hole ground-penetrating radar (GPR) data acquired during saline tracer tests and optical televiewer logs. Eleven cross-hole hydraulic connections between fractures in neighboring boreholes and the order in which the tracer arrives at different fractures are used for conditioning. Furthermore, the networks are conditioned to the observed relative hydraulic importance of the different hydraulic connections by numerically simulating the flow response. Among the conditioning data considered, constraints on the relative flow contributions were the most effective in determining the variability among the network realizations. Nevertheless, we find that the posterior model space is strongly determined by the imposed prior bounds. Strong prior bounds were derived from GPR measurements and helped to make the approach computationally feasible. We analyze a set of 230 posterior realizations that reproduce all data given their uncertainties assuming the same uniform transmissivity in all fractures. The posterior models provide valuable statistics on length scales and density of connected fractures, as well as their connectivity. In an additional analysis, effective transmissivity estimates of the posterior realizations indicate a strong influence of the DFN structure, in that it induces large variations of equivalent transmissivities between realizations. The transmissivity estimates agree well with previous estimates at the site based on pumping, flowmeter and temperature data.

Use of high-resolution geophysical data to characterize heterogeneous aquifers: influence of data integration method on hydrological predictions

The integration of geophysical data into the subsurface characterization problem has been shown in many cases to significantly improve hydrological knowledge by providing information at spatial scales and locations that is unattainable using conventional hydrological measurement techniques. The investigation of exactly how much benefit can be brought by geophysical data in terms of its effect on hydrological predictions, however, has received considerably less attention in the literature. Here, we examine the potential hydrological benefits brought by a recently introduced simulated annealing (SA) conditional stochastic simulation method designed for the assimilation of diverse hydrogeophysical data sets. We consider the specific case of integrating crosshole ground-penetrating radar (GPR) and borehole porosity log data to characterize the porosity distribution in saturated heterogeneous aquifers. In many cases, porosity is linked to hydraulic conductivity and thus to flow and transport behavior. To perform our evaluation, we first generate a number of synthetic porosity fields exhibiting varying degrees of spatial continuity and structural complexity. Next, we simulate the collection of crosshole GPR data between several boreholes in these fields, and the collection of porosity log data at the borehole locations. The inverted GPR data, together with the porosity logs, are then used to reconstruct the porosity field using the SA-based method, along with a number of other more elementary approaches. Assuming that the grid-cell-scale relationship between porosity and hydraulic conductivity is unique and known, the porosity realizations are then used in groundwater flow and contaminant transport simulations to assess the benefits and limitations of the different approaches.