Beyond Centre and Margin: (Self-)translation and the Ecopoetics of Space in Geetanjali Shree's "Mai"

Croisant les concepts de traduction culturelle et une approche « queer » de l'identité, notre article propose une lecture de l'utilisation de tropes végétaux ou organiques dans le roman de Geetanjali Shree, Mai, comme critique de la logique binaire du centre et de la marge qui caractérise autant l'orientalisme que le système patriarcal. Ecrit à la première personne, le roman invente un nouvel espace d'énonciation en narrant l'enfance et la jeunesse d'une jeune femme et la constitution de son identité à travers la relation complexe qu'elle entretient avec sa mère, son milieu familial issu de la classe moyenne du Nord de l'Inde, et la société indienne contemporaine aux prises avec la globalisation. Toutefois, ce cercle ou centre est en constante évolution puisque le contexte postcolonial dans lequel ces identités féminines se situent nous amène à considérer d'autres modes d'intervention (agency) qui opèrent non seulement à travers la prise de parole mais aussi à travers l'usage stratégique du silence. Fleurissant entre l'anglais et le hindi, ces identités hybrides nous poussent à revoir nos cartographies critiques et à investiguer et investir des lieux liminaux dans lesquels des subjectivités traversent les frontières et transgressent les limites imposées par l'ordre patriarcal et les cartographies imposées par les centres de pouvoir.

Socio-economic benefits of using space technologies to monitor and respond to earthquakes

Earthquakes represent a major hazard for populations around the world, causing frequent loss of life,human suffering and enormous damage to homes, other buildings and infrastructure. The Technology Resources forEarthquake Monitoring and Response (TREMOR) Team of 36 space professionals analysed this problem over thecourse of the International Space University Summer Session Program and published their recommendations in the formof a report. The TREMOR Team proposes a series of space- and ground-based systems to provide improved capabilityto manage earthquakes. The first proposed system is a prototype earthquake early-warning system that improves theexisting knowledge of earthquake precursors and addresses the potential of these phenomena. Thus, the system willat first enable the definitive assessment of whether reliable earthquake early warning is possible through precursormonitoring. Should the answer be affirmative, the system itself would then form the basis of an operational earlywarningsystem. To achieve these goals, the authors propose a multi-variable approach in which the system will combine,integrate and process precursor data from space- and ground-based seismic monitoring systems (already existing andnew proposed systems) and data from a variety of related sources (e.g. historical databases, space weather data, faultmaps). The second proposed system, the prototype earthquake simulation and response system, coordinates the maincomponents of the response phase to reduce the time delays of response operations, increase the level of precisionin the data collected, facilitate communication amongst teams, enhance rescue and aid capabilities and so forth. It isbased in part on an earthquake simulator that will provide pre-event (if early warning is proven feasible) and post-eventdamage assessment and detailed data of the affected areas to corresponding disaster management actors by means of ageographic information system (GIS) interface. This is coupled with proposed mobile satellite communication hubs toprovide links between response teams. Business- and policy-based implementation strategies for these proposals, suchas the establishment of a non-governmental organisation to develop and operate the systems, are included.

Psychothérapie psychodynamique brève de la dépression pour patients hospitalisés

L'objectif de cet article est de proposer une réflexion sur l'opportunité que représente l'hospitalisation de s'intéresser à la dépression en tant que travail de métabolisation psychique d'une expérience subjective significative, ou de son échec. Cet article présente les principales modalités organisatrices de la psychothérapie en 12 séances (à raison de 3 séances hebdomadaires) que nous avons mise en place pour les patients hospitalisés souffrant d'un épisode dépressif unipolaire. Lors de celle-ci, le psychothérapeute situe son intervention sur la base de quatre organisateurs : la thématique conflictuelle que révèlent l'hospitalisation et la crise, la structure de personnalité du patient, la brièveté de la psychothérapie et la psychopathologie du symptôme. Ces organisateurs vont encadrer le processus et lui conférer son originalité. Un récit clinique illustre comment cette psychothérapie, même brève, peut remettre en mouvement une situation par la constitution (la reprise) d'une historicité psychique de l'épisode dépressif. Notre expérience clinique montre qu'un tel dispositif délimite clairement un espace permettant une écoute psychanalytique authentique des patients souffrant de dépression grave. The aim of this article is to propose a reflection on the opportunity that hospitalization can represent as a way to think of depression in terms of psychic metabilisation of a significant subjective experience, or its feature. The article presents the main modalities through which this approach is organized for hospitalized unipolar patients in a phase of depression. It comprises 12 sessions (3 per week), The psychotherapit's intervention is organized around 4 basic themes : the conflict revealed in the crisis surrounding hospitalization, personality structure, briefness of psychotherapy and the psychopathology of the symptom. These organisors are the framework that lend this process its originality. A clinical vignette illustrates how this psychotherapy, though brief, is able to remobilize a situation through retrieving the psychical historicity of the depressed episode. Our clinical experience shows that this dispositive is a clearly destined space for lending an authentic psychoanalytic ear.

Feature Extraction from Whole-Sky Ground-Based Images for Cloud-Type Recognition

Several features that can be extracted from digital images of the sky and that can be useful for cloud-type classification of such images are presented. Some features are statistical measurements of image texture, some are based on the Fourier transform of the image and, finally, others are computed from the image where cloudy pixels are distinguished from clear-sky pixels. The use of the most suitable features in an automatic classification algorithm is also shown and discussed. Both the features and the classifier are developed over images taken by two different camera devices, namely, a total sky imager (TSI) and a whole sky imager (WSC), which are placed in two different areas of the world (Toowoomba, Australia; and Girona, Spain, respectively). The performance of the classifier is assessed by comparing its image classification with an a priori classification carried out by visual inspection of more than 200 images from each camera. The index of agreement is 76% when five different sky conditions are considered: clear, low cumuliform clouds, stratiform clouds (overcast), cirriform clouds, and mottled clouds (altocumulus, cirrocumulus). Discussion on the future directions of this research is also presented, regarding both the use of other features and the use of other classification techniques

State-space approach to evaluate the relation between soil physical and chemical properties

The state-space approach is used to evaluate the relation between soil physical and chemical properties in an area cultivated with sugarcane. The experiment was carried out on a Rhodic Kandiudalf in Piracicaba, State of São Paulo, Brazil. Sugarcane was planted on an area of 0.21 ha i.e., in 15 rows 100 m long, spaced 1.4 m. Soil water content, soil organic matter, clay content and aggregate stability were sampled along a transect of 84 points, meter by meter. The state-space approach is used to evaluate how the soil water content is affected by itself and by soil organic matter, clay content, and aggregate stability of neighboring locations, in different combinations, aiming to contribute to a better understanding of the relation among these variables in the soil. Results show that soil water contents were successfully estimated by this approach. Best performances were found when the estimate of soil water content at locations i was related to soil water content, clay content and aggregate stability at locations i-1. Results also indicate that this state-space model using all series describes the soil water content better than any equivalent multiple regression equation.

State of Iowa Space Utilization and Building Study, October 9, 2000

Executive Summary Purposes of this Report: • Recommend the most logical and economical options to address state governmental space needs in the Polk County metropolitan area to the year 2010. • Include building size, location, phasing, financing, method of project delivery and estimated cost. • Develop a software tool to compare costs of leasing vs. ownership of space. Methodology: Identify: 1. Current amount and location of owned and leased space, by agency; 2. Types of space and whether best located on or off of the Capitol Complex; 3. Utilization of space, noting over-crowding and under-utilization; 4. Current number of workstations for full and part time employees, Personnel Employment Organization (PEO) workers, contractors, interns, etc.; and, 5. History of staff levels to assist in the prediction of staff growth. Scope: This report focuses on 10 state-owned buildings located on the Capitol Complex and 48 leased spaces in the Polk County metropolitan area. (See Figures 1 and 2.) • Due to a separate space study under way by the Legislature, implications of area and staff for the State Capitol building are included only for the Governor, Lieutenant Governor, Treasurer, Secretary of State, Auditor and the Department of Management. • Because it is largely a museum building that does not have office space available for other agencies, the area and staff of the Historical Building are not fully addressed. • Only the parking implications of the new Judicial Building are included in this study because the building space is under the jurisdiction of the Judicial Branch and not available for other agencies. Several state-owned buildings are not included in the scope of this report, generally because they have highly focused purposes, and their space is not available for assignment to other agencies. Several leased locations are not included for similar reasons, including leases that do not fall within the authority of the Department of General Services.

Bayesian image reconstruction with space-variant noise suppression

In this paper we present a Bayesian image reconstruction algorithm with entropy prior (FMAPE) that uses a space-variant hyperparameter. The spatial variation of the hyperparameter allows different degrees of resolution in areas of different statistical characteristics, thus avoiding the large residuals resulting from algorithms that use a constant hyperparameter. In the first implementation of the algorithm, we begin by segmenting a Maximum Likelihood Estimator (MLE) reconstruction. The segmentation method is based on using a wavelet decomposition and a self-organizing neural network. The result is a predetermined number of extended regions plus a small region for each star or bright object. To assign a different value of the hyperparameter to each extended region and star, we use either feasibility tests or cross-validation methods. Once the set of hyperparameters is obtained, we carried out the final Bayesian reconstruction, leading to a reconstruction with decreased bias and excellent visual characteristics. The method has been applied to data from the non-refurbished Hubble Space Telescope. The method can be also applied to ground-based images.

The stationary distribution of a continuously varying strategy in a class-structured population under mutation-selection-drift balance.

Many traits and/or strategies expressed by organisms are quantitative phenotypes. Because populations are of finite size and genomes are subject to mutations, these continuously varying phenotypes are under the joint pressure of mutation, natural selection and random genetic drift. This article derives the stationary distribution for such a phenotype under a mutation-selection-drift balance in a class-structured population allowing for demographically varying class sizes and/or changing environmental conditions. The salient feature of the stationary distribution is that it can be entirely characterized in terms of the average size of the gene pool and Hamilton's inclusive fitness effect. The exploration of the phenotypic space varies exponentially with the cumulative inclusive fitness effect over state space, which determines an adaptive landscape. The peaks of the landscapes are those phenotypes that are candidate evolutionary stable strategies and can be determined by standard phenotypic selection gradient methods (e.g. evolutionary game theory, kin selection theory, adaptive dynamics). The curvature of the stationary distribution provides a measure of the stability by convergence of candidate evolutionary stable strategies, and it is evaluated explicitly for two biological scenarios: first, a coordination game, which illustrates that, for a multipeaked adaptive landscape, stochastically stable strategies can be singled out by letting the size of the gene pool grow large; second, a sex-allocation game for diploids and haplo-diploids, which suggests that the equilibrium sex ratio follows a Beta distribution with parameters depending on the features of the genetic system.

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.

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.