Stratigraphic update of the Cenozoic Sub-Numidian formations of the Tunisian Tell (North Africa): Tectonic/sedimentary evolution and correlations along the Maghrebian Chain

The Sub-Numidian Tertiary stratigraphic record of the Tunisian Tell has been updated by means of 11 stratigraphic successions belonging to the Maghrebian Flysch Basin (N-African Margin) reconstructed in the Tunisian Numidian Zone and the Triassic Dome Zone. The Sub-Numidian successions studied range from the Paleocene to the Priabonian, representing a major change in the sedimentation from the latest Cretaceous onwards. The Sub-Numidian succession and the Numidian Formation are separated by an Intermediate interval located between two erosive surfaces (local paraconformities). The stratigraphic analysis has revealed diachronous contacts between distal slope to basinal sedimentary formation, allowing the identification of an Early Eocene Chouabine marker bed. The integrated biostratigraphic analysis made by means of planktonic foraminifera and calcareous nannoplankton updates the ages of the formations studied, proving younger than previously thought. The new definition of the Sub-Numidian stratigraphy enables a better correlation with equivalent successions widely outcropping along the Maghrebian, Betic, and southern Apennine Chains. The study proposes a new evolutionary tectonic/sedimentary model for this Tunisian sector of the Maghrebian Chain during the Paleogene after the Triassic–Cretaceous extensional regime. This paleogeographic reorganization is considered a consequence of the beginning of the tectonic inversion (from extensional to compressional), leading to the end of the preorogenic sedimentation. Our results suggest a non-tabular stratigraphy (marked by lateral changes of lithofacies, variable thicknesses, and the presence of diachronous boundaries) providing significant elements for a re-evaluation of active petroleum systems on the quality, volume, distribution, timing of oil generation, and on the migration and accumulation of the oil.

Enrichment of the Phenotypic and Genotypic Data Warehouse analysis using Question Answering systems to facilitate the decision making process in cereal breeding programs

Currently there are an overwhelming number of scientific publications in Life Sciences, especially in Genetics and Biotechnology. This huge amount of information is structured in corporate Data Warehouses (DW) or in Biological Databases (e.g. UniProt, RCSB Protein Data Bank, CEREALAB or GenBank), whose main drawback is its cost of updating that makes it obsolete easily. However, these Databases are the main tool for enterprises when they want to update their internal information, for example when a plant breeder enterprise needs to enrich its genetic information (internal structured Database) with recently discovered genes related to specific phenotypic traits (external unstructured data) in order to choose the desired parentals for breeding programs. In this paper, we propose to complement the internal information with external data from the Web using Question Answering (QA) techniques. We go a step further by providing a complete framework for integrating unstructured and structured information by combining traditional Databases and DW architectures with QA systems. The great advantage of our framework is that decision makers can compare instantaneously internal data with external data from competitors, thereby allowing taking quick strategic decisions based on richer data.

Rigorous design of distillation columns using surrogate models based on Kriging interpolation

The economic design of a distillation column or distillation sequences is a challenging problem that has been addressed by superstructure approaches. However, these methods have not been widely used because they lead to mixed-integer nonlinear programs that are hard to solve, and require complex initialization procedures. In this article, we propose to address this challenging problem by substituting the distillation columns by Kriging-based surrogate models generated via state of the art distillation models. We study different columns with increasing difficulty, and show that it is possible to get accurate Kriging-based surrogate models. The optimization strategy ensures that convergence to a local optimum is guaranteed for numerical noise-free models. For distillation columns (slightly noisy systems), Karush–Kuhn–Tucker optimality conditions cannot be tested directly on the actual model, but still we can guarantee a local minimum in a trust region of the surrogate model that contains the actual local minimum.

A Belief System's Organization Based on a Computational Model of the Dynamic Context: First Approximation

In this article we present a model of organization of a belief system based on a set of binary recursive functions that characterize the dynamic context that modifies the beliefs. The initial beliefs are modeled by a set of two-bit words that grow, update, and generate other beliefs as the different experiences of the dynamic context appear. Reason is presented as an emergent effect of the experience on the beliefs. The system presents a layered structure that allows a functional organization of the belief system. Our approach seems suitable to model different ways of thinking and to apply to different realistic scenarios such as ideologies.