Empirical Evidence on Satisfaction with Privatization in Latin America: Welfare Effects and Beliefs

Since the 1980s, privatization of formerly state-owned firms has been extensively implemented by governments across Latin America. Despite the fact that most evaluations of the process fail to find significant adverse welfare effects, there has been a strong surge in public discontent with such policy in the region. This paper performs a systematic empirical analysis of the determinants of such discontent with privatizations in Latin America, using survey data from Latinobarometro covering 18 countries over the period 1995-2005, complemented by country level data on macroeconomic, political, and institutional aspects as well as data on privatization. Dissatisfaction appears to respond to absolute and relative welfare effects, as well as to individual beliefs and expectations.

Identification of transient heat sources using the reciprocity gap

International audienceThe deformation of solid materials is nearly always accompanied with temperature variations, induced by intrinsic dissipation and thermomechanical coupling. Heat sources give precious information on the thermomechanical behavior of materials. They can be indirectly observed from thermal measurements on the specimen boundary, obtained e.g. via infrared thermography. To solve the inverse problem of identifying heat sources from such observations, a non-iterative algebraical method based on the Reciprocity Gap Method is proposed. This approach, used elsewhere mainly for time-independent identification, is applied here to transient measurements. Under appropriate modelling assumptions the number of heat sources, their spatial locations and energies are retrieved, as demonstrated on numerical experiments where the robustness of the method to measurement noise is also studied

Parabolic reciprocity gap for heat source identification

The deformation of solid materials is nearly always accompanied with temperature variations. These variations, governed by the heat diffusion equation stemming from the first and second laws of thermodynamics, are induced by intrinsic dissipation of energy and thermomechanical coupling. Infrared thermography techniques provide an experimental means for measuring thermal fields on specimen boundaries. But even if thermal fields are related to the material behavior they are not intrinsic to it as they also depend on external factors such as boundary conditions. Inverting boundary thermal fields is thus needed to obtain valid insight into the specimen thermomechanical behavior. Such an operation belongs to the class of source inverse problem. Inverse source problems are known to be ill-posed in the sense of Hadamard: their solution does not depend continuously on the data, and is not unique for a general source distribution when using only boundary measurements. Modeling hypotheses on the sought sources are thus needed to properly retrieve information

Continental-scale erosion and transport laws: A new approach to quantitatively investigate macroscale landscapes and associated sediment fluxes over the geological past

International audienceAlthough critical to a variety of issues in Earth Sciences, paleotopography remains poorly constrained over the geological past. Indeed, sediments preserve a record of the history of the Earth surface, but deconvolving these archives remains a challenge in the absence of a proper quantification of surface processes at the large spatial and temporal resolution imposed by these data. To solve for this, we propose a set of simple bedrock erosion and sediment transport laws that apply over large spatial (∼100 km) and temporal (∼1-10 Ma) scales. These laws are tested in light of physical experiments of landscape evolution under different tectonic and climatic forcings and are calibrated using present-day large-scale Earth topography and sediment fluxes in rivers. We subsequently implement these processes into a numerical code, TopoSed, that is able to predict the evolution of macroscale topography, sediment fluxes, paleogeographies, and bedrock exhumation given a tectonic and climatic input scenario. The results of such simulations can be directly compared to sedimentary or thermochronological data to test the plausibility of the input tectonics and predicted topography. A series of tests on the sensitivity of such predictions to the uncertainties on input parameters shows that it should be possible from sedimentary data to invert for paleouplift rates and also for paleotopographies during periods covering major tectonic or climatic events. Although this code is meant to be refined in the future as we improve our understanding of surface processes at these macroscales, TopoSed provides a powerful tool to put constraints on past geodynamic processes, such as dynamic topography, by extracting quantitative information on the evolution of the Earth surface from sedimentary data

Aix-en-Provence : actualité de la recherche

Date de l'opération : 2007 (PT) ; 2007 (EX) Inventeur(s) : Bonnet Stéphane (COL) ; Nin Núria (COL) L’année 2007 a été, pour Aix-en-Provence, particulièrement riche au plan de l’activité archéologique. Outre une campagne de prospection-inventaire menée sur le massif du Montaiguet, au sud de la commune, l’agglomération a, en effet, été le théâtre de sept opérations préventives : • trois diagnostics : • ainsi que quatre fouilles qui ont été menées par la Mission archéologique de la ville. La M..

Aix-en-Provence – Collège Mignet

Identifiant de l'opération archéologique : 8299 Date de l'opération : 2007 (SP) Inventeur(s) : Ratsimba Antoine (COL) ; Bonnet Stéphane (COL) Le projet d’extension du parking souterrain Mignet a entraîné la prescription d’une fouille préventive qui s’est déroulée du 9 avril au 12 juillet (BSR PACA, 2006 : 114). Cette opération fait suite à deux opérations préventives qui ont été réalisées dans l’enceinte du collège Mignet, en 1990 (dir. R. Chemin, AFAN ; NIL PACA,1990 : 68-69) puis en 2001 (d..

Eye blink characterization from frontal EEG electrodes using source separation and pattern recognition algorithms

Due to its major safety applications, including safe driving, mental fatigue estimation is a rapidly growing research topic in the engineering field. Most current mental fatigue monitoring systems analyze brain activity through electroencephalography (EEG). Yet eye blink analysis can also be added to help characterize fatigue states. It usually requires the use of additional devices, such as EOG electrodes, uncomfortable to wear, or more expensive eye trackers. However, in this article, a method is proposed to evaluate eye blink parameters using frontal EEG electrodes only. EEG signals, which are generally corrupted by ocular artifacts, are decomposed into sources by means of a source separation algorithm. Sources are then automatically classified into ocular or non-ocular sources using temporal, spatial and frequency features. The selected ocular source is back propagated in the signal space and used to localize blinks by means of an adaptive threshold, and then to characterize detected blinks. The method, validated on 11 different subjects, does not require any prior tuning when applied to a new subject, which makes it subject-independent. The vertical EOG signal was recorded during an experiment lasting 90 min in which the participants’ mental fatigue increased. The blinks extracted from this signal were compared to those extracted using frontal EEG electrodes. Very good performances were obtained with a true detection rate of 89% and a false alarm rate of 3%. The correlation between the blink parameters extracted from both recording modalities was 0.81 in average

BCI Signal Classification using a Riemannian-based kernel

International audienceThe use of spatial covariance matrix as feature is investigated for motor imagery EEG-based classification. A new kernel is derived by establishing a connection with the Riemannian geometry of symmetric positive definite matrices. Different kernels are tested, in combination with support vector machines, on a past BCI competition dataset. We demonstrate that this new approach outperforms significantly state of the art results without the need for spatial filtering

Classification of covariance matrices using a Riemannian-based kernel for BCI applications

International audienceThe use of spatial covariance matrix as a feature is investigated for motor imagery EEG-based classification in Brain-Computer Interface applications. A new kernel is derived by establishing a connection with the Riemannian geometry of symmetric positive definite matrices. Different kernels are tested, in combination with support vector machines, on a past BCI competition dataset. We demonstrate that this new approach outperforms significantly state of the art results, effectively replacing the traditional spatial filtering approach