La pré-configuration des débats publics : apports d'une approche multimodale et longitudinale des dispositifs de catégorisation

Most linguistic and interactional studies on public and media debates focus on the way talk-in- interaction is locally managed by the moderator. For example, they analyze the extent to which the questions asked are both sequentially and categorically relevant. The present paper aims at enriching these studies by discussing the profitability of a multimodal and longitudinal approach to membership categorization practices. The approach is multimodal in the sense that it does not focus exclusively on verbal features. The approach is also longitudinal by considering the extent to which a debate is pre- configured. To this end, particular attention is paid to the posters promoting the encounters and to the way the participants are positioned in physical space.

Potencialidad de la modelización state-space y el filtro de Kalman para el anàlisis regional : una aplicación para el índice de actividad industrial

El déficit existente a nuestro país con respecto a la disponibilidad de indicadores cuantitativos con los que llevar a término un análisis coyuntural de la actividad industrial regional ha abierto un debate centrado en el estudio de cuál es la metodología más adecuada para elaborar indicadores de estas características. Dentro de este marco, en este trabajo se presentan las principales conclusiones obtenidas en anteriores estudios (Clar, et. al., 1997a, 1997b y 1998) sobre la idoneidad de extender las metodologías que actualmente se están aplicando a las regiones españolas para elaborar indicadores de la actividad industrial mediante métodos indirectos. Estas conclusiones llevan a plantear una estrategia distinta a las que actualmente se vienen aplicando. En concreto, se propone (siguiendo a Israilevich y Kuttner, 1993) un modelo de variables latentes para estimar el indicador de la producción industrial regional. Este tipo de modelo puede especificarse en términos de un modelo statespace y estimarse mediante el filtro de Kalman. Para validar la metodología propuesta se estiman unos indicadores de acuerdo con ella para tres de las cuatro regiones españolas que disponen d¿un Índice de Producción Industrial (IPI) elaborado mediante el método directo (Andalucía, Asturias y el País Vasco) y se comparan con los IPIs publicados (oficiales). Los resultados obtenidos muestran el buen comportamiento de l¿estrategia propuesta, abriendo así una línea de trabajo con la que subsanar el déficit al que se hacía referencia anteriormente

Translating from India and the Moving Space of Translation (Illustrated by the Works of Ajñeya)

The inadequacies and obsolescence of Eurocentric theories based on a binaryand static worldview have become a staple topic of postcolonial studies, and tosome extent also of translation studies. Nonetheless, the literary texts that arecalled upon in order to show the dynamism and hybridity of (post)modern worksbelong for the most part to the languages of the former colonial powers, especiallyEnglish, and remain inserted in a system that construes literatures interms of opposition. As a consequence, there is outside India a doubly misleadingunderstanding of Indian literatures other than those written in English:firstly, that translations of works in Hindi and in the Indian bhāṣā seem to belacking, if not inexistent, and secondly, that these "minor" literatures - as theyare regularly termed - are still often viewed as being highly dependent on theidea of "tradition," in opposition to the "postmodern" hybridity of the literatureswritten in the "dominant" languages, such as English or French. Againstthese views and supported by the analysis of Ajñeya's works in Hindi togetherwith their English translations, this paper aims to show: 1) that translationsfrom Hindi, which are not in fact non-existent, are mainly carried out in India,and 2) that Ajñeya's works, while representing a significant instance of the effectivehybridity present in Indian literatures, help to illustrate the moving spaceof translation. This demonstration effectively invalidates the above-mentionedoppositional standpoint.

Thermal modeling and management in ultrathin chip stack technology

This paper presents a thermal modeling for power management of a new three-dimensional (3-D) thinned dies stacking process. Besides the high concentration of power dissipating sources, which is the direct consequence of the very interesting integration efficiency increase, this new ultra-compact packaging technology can suffer of the poor thermal conductivity (about 700 times smaller than silicon one) of the benzocyclobutene (BCB) used as both adhesive and planarization layers in each level of the stack. Thermal simulation was conducted using three-dimensional (3-D) FEM tool to analyze the specific behaviors in such stacked structure and to optimize the design rules. This study first describes the heat transfer limitation through the vertical path by examining particularly the case of the high dissipating sources under small area. First results of characterization in transient regime by means of dedicated test device mounted in single level structure are presented. For the design optimization, the thermal draining capabilities of a copper grid or full copper plate embedded in the intermediate layer of stacked structure are evaluated as a function of the technological parameters and the physical properties. It is shown an interest for the transverse heat extraction under the buffer devices dissipating most the power and generally localized in the peripheral zone, and for the temperature uniformization, by heat spreading mechanism, in the localized regions where the attachment of the thin die is altered. Finally, all conclusions of this analysis are used for the quantitative projections of the thermal performance of a first demonstrator based on a three-levels stacking structure for space application.

Quality coding by neural populations in the early olfactory pathway: analysis using information theory

In this article, we analyze the ability of the early olfactory system to detect and discriminate different odors by means of information theory measurements applied to olfactory bulb activity images. We have studied the role that the diversity and number of receptor neuron types play in encoding chemical information. Our results show that the olfactory receptors of the biological system are low correlated and present good coverage of the input space. The coding capacity of ensembles of olfactory receptors with the same receptive range is maximized when the receptors cover half of the odor input space - a configuration that corresponds to receptors that are not particularly selective. However, the ensemble's performance slightly increases when mixing uncorrelated receptors of different receptive ranges. Our results confirm that the low correlation between sensors could be more significant than the sensor selectivity for general purpose chemo-sensory systems, whether these are biological or biomimetic.

Domain Adaptation in remote sensing: increasing the portability of land-cover classifiers

Among the types of remote sensing acquisitions, optical images are certainly one of the most widely relied upon data sources for Earth observation. They provide detailed measurements of the electromagnetic radiation reflected or emitted by each pixel in the scene. Through a process termed supervised land-cover classification, this allows to automatically yet accurately distinguish objects at the surface of our planet. In this respect, when producing a land-cover map of the surveyed area, the availability of training examples representative of each thematic class is crucial for the success of the classification procedure. However, in real applications, due to several constraints on the sample collection process, labeled pixels are usually scarce. When analyzing an image for which those key samples are unavailable, a viable solution consists in resorting to the ground truth data of other previously acquired images. This option is attractive but several factors such as atmospheric, ground and acquisition conditions can cause radiometric differences between the images, hindering therefore the transfer of knowledge from one image to another. The goal of this Thesis is to supply remote sensing image analysts with suitable processing techniques to ensure a robust portability of the classification models across different images. The ultimate purpose is to map the land-cover classes over large spatial and temporal extents with minimal ground information. To overcome, or simply quantify, the observed shifts in the statistical distribution of the spectra of the materials, we study four approaches issued from the field of machine learning. First, we propose a strategy to intelligently sample the image of interest to collect the labels only in correspondence of the most useful pixels. This iterative routine is based on a constant evaluation of the pertinence to the new image of the initial training data actually belonging to a different image. Second, an approach to reduce the radiometric differences among the images by projecting the respective pixels in a common new data space is presented. We analyze a kernel-based feature extraction framework suited for such problems, showing that, after this relative normalization, the cross-image generalization abilities of a classifier are highly increased. Third, we test a new data-driven measure of distance between probability distributions to assess the distortions caused by differences in the acquisition geometry affecting series of multi-angle images. Also, we gauge the portability of classification models through the sequences. In both exercises, the efficacy of classic physically- and statistically-based normalization methods is discussed. Finally, we explore a new family of approaches based on sparse representations of the samples to reciprocally convert the data space of two images. The projection function bridging the images allows a synthesis of new pixels with more similar characteristics ultimately facilitating the land-cover mapping across images.

Effect of added dead space on sleep disordered breathing at high altitude.

OBJECTIVE: Sleep disordered breathing with central apnea or hypopnea frequently occurs at high altitude and is thought to be caused by a decrease in blood CO(2) level. The aim of this study was to assess the effects of added respiratory dead space on sleep disordered breathing.¦METHODS: Full polysomnographies were performed on 12 unacclimatized swiss mountaineers (11 males, 1 female, mean age 39±12 y.o.) in Leh, Ladakh (3500m). In random order, half of the night was spent with a 500ml increase in dead space through a custom designed full face mask and the other half without it.¦RESULTS: Baseline data revealed two clearly distinct groups: one with severe sleep disordered breathing (n=5, AHI>30) and the other with moderate to no disordered breathing (n=7, AHI<30). DS markedly improved breathing in the first group (baseline vs DS): apnea hypopnea index (AHI) 70.3±25.8 vs 29.4±6.9 (p=0.013), oxygen desaturation index (ODI): 72.9±24.1/h vs 42.5±14.4 (p=0.031), whereas it had no significant effect in the second group or in the total population. Respiratory events were almost exclusively central apnea or hypopnea. Microarousal index, sleep efficiency, and sleep architecture remained unchanged with DS. A minor increase in mean PtcCO(2) (n=3) was observed with DS.¦CONCLUSION: A 500ml increase in dead space through a fitted mask may improve nocturnal breathing in mountaineers with severe altitude-induced sleep disordered breathing.

Potencialidad de la modelización state-space y el filtro de Kalman para el anàlisis regional : una aplicación para el índice de actividad industrial

El déficit existente a nuestro país con respecto a la disponibilidad de indicadores cuantitativos con los que llevar a término un análisis coyuntural de la actividad industrial regional ha abierto un debate centrado en el estudio de cuál es la metodología más adecuada para elaborar indicadores de estas características. Dentro de este marco, en este trabajo se presentan las principales conclusiones obtenidas en anteriores estudios (Clar, et. al., 1997a, 1997b y 1998) sobre la idoneidad de extender las metodologías que actualmente se están aplicando a las regiones españolas para elaborar indicadores de la actividad industrial mediante métodos indirectos. Estas conclusiones llevan a plantear una estrategia distinta a las que actualmente se vienen aplicando. En concreto, se propone (siguiendo a Israilevich y Kuttner, 1993) un modelo de variables latentes para estimar el indicador de la producción industrial regional. Este tipo de modelo puede especificarse en términos de un modelo statespace y estimarse mediante el filtro de Kalman. Para validar la metodología propuesta se estiman unos indicadores de acuerdo con ella para tres de las cuatro regiones españolas que disponen d¿un Índice de Producción Industrial (IPI) elaborado mediante el método directo (Andalucía, Asturias y el País Vasco) y se comparan con los IPIs publicados (oficiales). Los resultados obtenidos muestran el buen comportamiento de l¿estrategia propuesta, abriendo así una línea de trabajo con la que subsanar el déficit al que se hacía referencia anteriormente

Covariant description of kinetic freeze-out through a finite spacelike layer

The problem of freeze-out (FO) in relativistic heavy-ion reactions is addressed. We develop and analyze an idealized one-dimensional model of FO in a finite layer, based on the covariant FO probability. The resulting post FO phase-space distributions are discussed for different FO probabilities and layer thicknesses.