The elimination of Madagascar's Vanilla Marketing Board, ten years on

This paper explores how the elimination of Madagascar's Marketing Board in 1995 affected prices paid to farmers, incentives, and regional indicators of poverty and inequality. After steadily losing market share, Madagascar has been able to regain some of the lost ground since the mid-1990s. Margins between freight on board (FOB) and farmgate prices have spectacularly narrowed down, but this effect is dwarfed by that of world-price volatility. A counterfactual analysis based on a model of Cournot competition between vanilla traders suggests that whatever limited competition there is among them has contributed to raise purchase prices and the cash income of vanilla farmers. But the effect on farmers'consumption remains small because a large part of it is self-consumed. The effect on aggregate measures of poverty and inequality is even smaller, even at the regional level. After taking into account the reduction in Madagascar's monopoly power on the world vanilla market implied by the elimination of the Marketing Board, the induced rise in producer prices is estimated to have lifted about 20,000 individuals out of poverty.Markets and Market Access,Access to Markets,Economic Theory&Research,Crops&Crop Management Systems,Food&Beverage Industry

Manejo ecológico del cultivo de cereal en condiciones de secano

8 páginas y tablas estadísticasLa agricultura extensiva en agrosistemas de ambientes semiáridos, una vez mejorada su productividad merced a la revolución verde, alcanzó los límites ambientales en la década de los 80. En los momentos actuales, ninguna cantidad de dinero, ingenio o fertilizante logra mejorar la producción de forma significativa. En cambio, la persistencia de este modelo, además de producir escasa rentabilidad, genera altas tasas de erosión, disminución alarmante del contenido en materia orgánica, pérdida de elementos fertilizantes solubles y, por tanto, graves implicaciones en procesos contaminantes. Esto, unido a una escasa biodiversidad al haber sido eliminados gran parte de los hábitats, tanto de la flora como de la fauna autóctona, y a unos costes de producción muy superiores a los de otros países europeos, sitúan estos agrosistemas en un proceso de desertificación, que exige un cambio en su manejo si se pretende su perdurabilidad. Utilizando experimentos de larga duración realizados en estos ambientes, en la Finca Experimental “La Higueruela” del CSIC, se demuestra que la Agricultura Ecológica, al basar su estrategia en el manejo (rotaciones, labores, reciclado de los residuos de los cultivos, alternancia de fechas de siembra y recolección, fijación biológica de nitrógeno, cubiertas vegetales en los barbechos, marcos de siembra, rupturas de pendientes, fijación de desagües, utilización de setos, etc.), no sólo evita muchos de los problemas ambientales producidos por la Agricultura Convencional (contaminación, disminución de carbono en el suelo, biodiversidad, eficiencia energética, etc.) sino que, además, consigue mejorar la rentabilidad económica por unidad de superficie.Peer reviewe

ASR-based Features for Emotion Recognition: A Transfer Learning Approach

During the last decade, the applications of signal processing have drastically improved with deep learning. However areas of affecting computing such as emotional speech synthesis or emotion recognition from spoken language remains challenging. In this paper, we investigate the use of a neural Automatic Speech Recognition (ASR) as a feature extractor for emotion recognition. We show that these features outperform the eGeMAPS feature set to predict the valence and arousal emotional dimensions, which means that the audio-to-text mapping learning by the ASR system contain information related to the emotional dimensions in spontaneous speech. We also examine the relationship between first layers (closer to speech) and last layers (closer to text) of the ASR and valence/arousal.Comment: Accepted to be published in the First Workshop on Computational Modeling of Human Multimodal Language - ACL 201

Extraction automatique de paraphrases à partir de petits corpus

International audienceThis paper presents a versatile system intended to acquire paraphrastic phrases from a small-size representative corpus. In order to decrease the time spent on the elaboration of resources for NLP system (for example for Information Extraction), we suggest to use a knowledge acquisition module that helps extracting new information despite linguistic variation. This knowledge is semi-automatically derived from the text collection, in interaction with a large semantic network.Cet article présente un système permettant d'acquérir de manière semi-automatique des paraphrases à partir de corpus représentatifs de petite taille. Afin de réduire le temps passé à l'élaboration de ressources pour des systèmes de traitement des langues (notamment l'extraction d'information), nous décrivons un module qui vise à extraire ces connaissances en prenant en compte la variation linguistique. Les connaissances sont directement extraites des textes à l'aide d'un réseau sémantique de grande taille

Inferring knowledge from a large semantic network

International Conference on Computational Linguistics (COLING).Rédacteur : Shu-Chuan Tseng.Éditeur : Morgan Kaufmann.ISBN : 155860894X, 9781558608948In this paper, we present a rich semantic network based on a differential analysis. We then detail implemented measures that take into account common and differential features between words. In a last section, we describe some industrial applications