Representations of curanderismo in Chicana/o texts

Ma thèse porte sur les représentations de curanderismo dans Chicana/o textes. Une tradition de guérison, une vision du monde, un système de croyances et de pratiques d'origines diverses, curanderismo répond aux besoins médicaux, religieux, culturels, sociaux et politiques des Chicanas/os à la fois sur le plan individuel et communautaire. Dans mon analyse de textes littéraires (Bless Me, Ultima de Rudolfo Anaya, les poèmes sélectionnés de Pat Mora, The Hungry Woman: A Mexican Medea de Cherríe Moraga) et du cours académique sur curanderismo enseigné à l'Université du Nouveau-Mexique à Albuquerque, que j’approche comme un texte culturel, curanderismo reflète les façons complexes et souvent ambiguës de représenter Chicana/o recherche d'identité, d’affirmation de soi et d’émancipation, résultat d'une longue histoire de domination et de discrimination de Chicana/o aux Etats-Unis. Dans les textes que j’aborde dans ma thèse curanderismo assume le rôle d'une puissante métaphore qui réunit une variété de valeurs, attitudes, concepts et notions dans le but ultimede célébrer le potentiel de soi-même.

L’esthétique loufoque chez Éric Chevillard (incongru, topoï, série)

Les récits d’Éric Chevillard appartiennent sans conteste à la catégorie des « fictions joueuses » décrites par Bruno Blanckeman (2002, p. 61) en ce qu’ils entretiennent un rapport ambigu avec la littérature, souvent détournée au moyen de la parodie, du pastiche ou d’une esthétique loufoque. Cet article propose un petit essai de typologie du loufoque chez Éric Chevillard au travers de trois œuvres, « Du hérisson » (2002), « Le vaillant petit tailleur » (2003) et « Oreille rouge » (2005), dans lesquelles on identifie cette pratique du détournement générique. Il met ainsi en évidence trois traits majeurs du loufoque : l’incongru, le détournement des topoï et l’écriture sérielle. [...]

Design And Development Of A Named Entity Based Question Answering System For Malayalam Language

This is a Named Entity Based Question Answering System for Malayalam Language. Although a vast amount of information is available today in digital form, no effective information access mechanism exists to provide humans with convenient information access. Information Retrieval and Question Answering systems are the two mechanisms available now for information access. Information systems typically return a long list of documents in response to a user’s query which are to be skimmed by the user to determine whether they contain an answer. But a Question Answering System allows the user to state his/her information need as a natural language question and receives most appropriate answer in a word or a sentence or a paragraph. This system is based on Named Entity Tagging and Question Classification. Document tagging extracts useful information from the documents which will be used in finding the answer to the question. Question Classification extracts useful information from the question to determine the type of the question and the way in which the question is to be answered. Various Machine Learning methods are used to tag the documents. Rule-Based Approach is used for Question Classification. Malayalam belongs to the Dravidian family of languages and is one of the four major languages of this family. It is one of the 22 Scheduled Languages of India with official language status in the state of Kerala. It is spoken by 40 million people. Malayalam is a morphologically rich agglutinative language and relatively of free word order. Also Malayalam has a productive morphology that allows the creation of complex words which are often highly ambiguous. Document tagging tools such as Parts-of-Speech Tagger, Phrase Chunker, Named Entity Tagger, and Compound Word Splitter are developed as a part of this research work. No such tools were available for Malayalam language. Finite State Transducer, High Order Conditional Random Field, Artificial Immunity System Principles, and Support Vector Machines are the techniques used for the design of these document preprocessing tools. This research work describes how the Named Entity is used to represent the documents. Single sentence questions are used to test the system. Overall Precision and Recall obtained are 88.5% and 85.9% respectively. This work can be extended in several directions. The coverage of non-factoid questions can be increased and also it can be extended to include open domain applications. Reference Resolution and Word Sense Disambiguation techniques are suggested as the future enhancements

Capturing Emergent Semantics from Social Annotation Systems

The ongoing growth of the World Wide Web, catalyzed by the increasing possibility of ubiquitous access via a variety of devices, continues to strengthen its role as our prevalent information and commmunication medium. However, although tools like search engines facilitate retrieval, the task of finally making sense of Web content is still often left to human interpretation. The vision of supporting both humans and machines in such knowledge-based activities led to the development of different systems which allow to structure Web resources by metadata annotations. Interestingly, two major approaches which gained a considerable amount of attention are addressing the problem from nearly opposite directions: On the one hand, the idea of the Semantic Web suggests to formalize the knowledge within a particular domain by means of the "top-down" approach of defining ontologies. On the other hand, Social Annotation Systems as part of the so-called Web 2.0 movement implement a "bottom-up" style of categorization using arbitrary keywords. Experience as well as research in the characteristics of both systems has shown that their strengths and weaknesses seem to be inverse: While Social Annotation suffers from problems like, e. g., ambiguity or lack or precision, ontologies were especially designed to eliminate those. On the contrary, the latter suffer from a knowledge acquisition bottleneck, which is successfully overcome by the large user populations of Social Annotation Systems. Instead of being regarded as competing paradigms, the obvious potential synergies from a combination of both motivated approaches to "bridge the gap" between them. These were fostered by the evidence of emergent semantics, i. e., the self-organized evolution of implicit conceptual structures, within Social Annotation data. While several techniques to exploit the emergent patterns were proposed, a systematic analysis - especially regarding paradigms from the field of ontology learning - is still largely missing. This also includes a deeper understanding of the circumstances which affect the evolution processes. This work aims to address this gap by providing an in-depth study of methods and influencing factors to capture emergent semantics from Social Annotation Systems. We focus hereby on the acquisition of lexical semantics from the underlying networks of keywords, users and resources. Structured along different ontology learning tasks, we use a methodology of semantic grounding to characterize and evaluate the semantic relations captured by different methods. In all cases, our studies are based on datasets from several Social Annotation Systems. Specifically, we first analyze semantic relatedness among keywords, and identify measures which detect different notions of relatedness. These constitute the input of concept learning algorithms, which focus then on the discovery of synonymous and ambiguous keywords. Hereby, we assess the usefulness of various clustering techniques. As a prerequisite to induce hierarchical relationships, our next step is to study measures which quantify the level of generality of a particular keyword. We find that comparatively simple measures can approximate the generality information encoded in reference taxonomies. These insights are used to inform the final task, namely the creation of concept hierarchies. For this purpose, generality-based algorithms exhibit advantages compared to clustering approaches. In order to complement the identification of suitable methods to capture semantic structures, we analyze as a next step several factors which influence their emergence. Empirical evidence is provided that the amount of available data plays a crucial role for determining keyword meanings. From a different perspective, we examine pragmatic aspects by considering different annotation patterns among users. Based on a broad distinction between "categorizers" and "describers", we find that the latter produce more accurate results. This suggests a causal link between pragmatic and semantic aspects of keyword annotation. As a special kind of usage pattern, we then have a look at system abuse and spam. While observing a mixed picture, we suggest that an individual decision should be taken instead of disregarding spammers as a matter of principle. Finally, we discuss a set of applications which operationalize the results of our studies for enhancing both Social Annotation and semantic systems. These comprise on the one hand tools which foster the emergence of semantics, and on the one hand applications which exploit the socially induced relations to improve, e. g., searching, browsing, or user profiling facilities. In summary, the contributions of this work highlight viable methods and crucial aspects for designing enhanced knowledge-based services of a Social Semantic Web.

Enlarging a training set for genomic selction by imputation of un-genotyped animals in populations of varying genetic architecture

Background: The most common application of imputation is to infer genotypes of a high-density panel of markers on animals that are genotyped for a low-density panel. However, the increase in accuracy of genomic predictions resulting from an increase in the number of markers tends to reach a plateau beyond a certain density. Another application of imputation is to increase the size of the training set with un-genotyped animals. This strategy can be particularly successful when a set of closely related individuals are genotyped. ----- Methods: Imputation on completely un-genotyped dams was performed using known genotypes from the sire of each dam, one offspring and the offspring’s sire. Two methods were applied based on either allele or haplotype frequencies to infer genotypes at ambiguous loci. Results of these methods and of two available software packages were compared. Quality of imputation under different population structures was assessed. The impact of using imputed dams to enlarge training sets on the accuracy of genomic predictions was evaluated for different populations, heritabilities and sizes of training sets. ----- Results: Imputation accuracy ranged from 0.52 to 0.93 depending on the population structure and the method used. The method that used allele frequencies performed better than the method based on haplotype frequencies. Accuracy of imputation was higher for populations with higher levels of linkage disequilibrium and with larger proportions of markers with more extreme allele frequencies. Inclusion of imputed dams in the training set increased the accuracy of genomic predictions. Gains in accuracy ranged from close to zero to 37.14%, depending on the simulated scenario. Generally, the larger the accuracy already obtained with the genotyped training set, the lower the increase in accuracy achieved by adding imputed dams. ----- Conclusions: Whenever a reference population resembling the family configuration considered here is available, imputation can be used to achieve an extra increase in accuracy of genomic predictions by enlarging the training set with completely un-genotyped dams. This strategy was shown to be particularly useful for populations with lower levels of linkage disequilibrium, for genomic selection on traits with low heritability, and for species or breeds for which the size of the reference population is limited.

Dynamic Injection of Scribble Features into Graphical Diagram Editors

Almost everyone sketches. People use sketches day in and day out in many different and heterogeneous fields, to share their thoughts and clarify ambiguous interpretations, for example. The media used to sketch varies from analog tools like flipcharts to digital tools like smartboards. Whereas analog tools are usually affected by insufficient editing capabilities like cut/copy/paste, digital tools greatly support these scenarios. Digital tools can be grouped into informal and formal tools. Informal tools can be understood as simple drawing environments, whereas formal tools offer sophisticated support to create, optimize and validate diagrams of a certain application domain. Most digital formal tools force users to stick to a concrete syntax and editing workflow, limiting the user’s creativity. For that reason, a lot of people first sketch their ideas using the flexibility of analog or digital informal tools. Subsequently, the sketch is "portrayed" in an appropriate digital formal tool. This work presents Scribble, a highly configurable and extensible sketching framework which allows to dynamically inject sketching features into existing graphical diagram editors, based on Eclipse GEF. This allows to combine the flexibility of informal tools with the power of formal tools without any effort. No additional code is required to augment a GEF editor with sophisticated sketching features. Scribble recognizes drawn elements as well as handwritten text and automatically generates the corresponding domain elements. A local training data library is created dynamically by incrementally learning shapes, drawn by the user. Training data can be shared with others using the WebScribble web application which has been created as part of this work.

From evolution to co-evolution – An empirical study of the role of innovation, policy and public research in industrial dynamics

In the past decades since Schumpeter’s influential writings economists have pursued research to examine the role of innovation in certain industries on firm as well as on industry level. Researchers describe innovations as the main trigger of industry dynamics, while policy makers argue that research and education are directly linked to economic growth and welfare. Thus, research and education are an important objective of public policy. Firms and public research are regarded as the main actors which are relevant for the creation of new knowledge. This knowledge is finally brought to the market through innovations. What is more, policy makers support innovations. Both actors, i.e. policy makers and researchers, agree that innovation plays a central role but researchers still neglect the role that public policy plays in the field of industrial dynamics. Therefore, the main objective of this work is to learn more about the interdependencies of innovation, policy and public research in industrial dynamics. The overarching research question of this dissertation asks whether it is possible to analyze patterns of industry evolution – from evolution to co-evolution – based on empirical studies of the role of innovation, policy and public research in industrial dynamics. This work starts with a hypothesis-based investigation of traditional approaches of industrial dynamics. Namely, the testing of a basic assumption of the core models of industrial dynamics and the analysis of the evolutionary patterns – though with an industry which is driven by public policy as example. Subsequently it moves to a more explorative approach, investigating co-evolutionary processes. The underlying questions of the research include the following: Do large firms have an advantage because of their size which is attributable to cost spreading? Do firms that plan to grow have more innovations? What role does public policy play for the evolutionary patterns of an industry? Are the same evolutionary patterns observable as those described in the ILC theories? And is it possible to observe regional co-evolutionary processes of science, innovation and industry evolution? Based on two different empirical contexts – namely the laser and the photovoltaic industry – this dissertation tries to answer these questions and combines an evolutionary approach with a co-evolutionary approach. The first chapter starts with an introduction of the topic and the fields this dissertation is based on. The second chapter provides a new test of the Cohen and Klepper (1996) model of cost spreading, which explains the relationship between innovation, firm size and R&D, at the example of the photovoltaic industry in Germany. First, it is analyzed whether the cost spreading mechanism serves as an explanation for size advantages in this industry. This is related to the assumption that the incentives to invest in R&D increase with the ex-ante output. Furthermore, it is investigated whether firms that plan to grow will have more innovative activities. The results indicate that cost spreading serves as an explanation for size advantages in this industry and, furthermore, growth plans lead to higher amount of innovative activities. What is more, the role public policy plays for industry evolution is not finally analyzed in the field of industrial dynamics. In the case of Germany, the introduction of demand inducing policy instruments stimulated market and industry growth. While this policy immediately accelerated market volume, the effect on industry evolution is more ambiguous. Thus, chapter three analyzes this relationship by considering a model of industry evolution, where demand-inducing policies will be discussed as a possible trigger of development. The findings suggest that these instruments can take the same effect as a technical advance to foster the growth of an industry and its shakeout. The fourth chapter explores the regional co-evolution of firm population size, private-sector patenting and public research in the empirical context of German laser research and manufacturing over more than 40 years from the emergence of the industry to the mid-2000s. The qualitative as well as quantitative evidence is suggestive of a co-evolutionary process of mutual interdependence rather than a unidirectional effect of public research on private-sector activities. Chapter five concludes with a summary, the contribution of this work as well as the implications and an outlook of further possible research.

Learning from Ambiguity

There are many learning problems for which the examples given by the teacher are ambiguously labeled. In this thesis, we will examine one framework of learning from ambiguous examples known as Multiple-Instance learning. Each example is a bag, consisting of any number of instances. A bag is labeled negative if all instances in it are negative. A bag is labeled positive if at least one instance in it is positive. Because the instances themselves are not labeled, each positive bag is an ambiguous example. We would like to learn a concept which will correctly classify unseen bags. We have developed a measure called Diverse Density and algorithms for learning from multiple-instance examples. We have applied these techniques to problems in drug design, stock prediction, and image database retrieval. These serve as examples of how to translate the ambiguity in the application domain into bags, as well as successful examples of applying Diverse Density techniques.

News from compositions, the R package

The R-package “compositions”is a tool for advanced compositional analysis. Its basic functionality has seen some conceptual improvement, containing now some facilities to work with and represent ilr bases built from balances, and an elaborated subsys- tem for dealing with several kinds of irregular data: (rounded or structural) zeroes, incomplete observations and outliers. The general approach to these irregularities is based on subcompositions: for an irregular datum, one can distinguish a “regular” sub- composition (where all parts are actually observed and the datum behaves typically) and a “problematic” subcomposition (with those unobserved, zero or rounded parts, or else where the datum shows an erratic or atypical behaviour). Systematic classification schemes are proposed for both outliers and missing values (including zeros) focusing on the nature of irregularities in the datum subcomposition(s). To compute statistics with values missing at random and structural zeros, a projection approach is implemented: a given datum contributes to the estimation of the desired parameters only on the subcompositon where it was observed. For data sets with values below the detection limit, two different approaches are provided: the well-known imputation technique, and also the projection approach. To compute statistics in the presence of outliers, robust statistics are adapted to the characteristics of compositional data, based on the minimum covariance determinant approach. The outlier classification is based on four different models of outlier occur- rence and Monte-Carlo-based tests for their characterization. Furthermore the package provides special plots helping to understand the nature of outliers in the dataset. Keywords: coda-dendrogram, lost values, MAR, missing data, MCD estimator, robustness, rounded zeros

What is Abstinence? Definitions and Examples of Abstinence, to Prevent the Sexual Transmission of the HIV Virus, According to Spanish University Students

Research carried out in several Anglo-Saxon countries shows that many undergraduates identify oral sex and anal sex as examples of abstinent behaviour, while many others consider kissing and masturbation as examples of having sex. The objective of this research was to investigate whether a sample of Spanish students gave similar replies. Seven hundred and fifty undergraduates (92% aged under 26, 67.6% women) produced examples or definitions of the term ‘abstinence’. Spanish students made similar errors to those observed in the Anglo-Saxon samples, in that behaviours that were abstinent from a preventive point of view (masturbating and sex without penetration) were not considered as such, while a number of students reported oral sex as abstinent behaviour. The results suggest that the information on risky and preventive sexual behaviour should cease to use ambiguous or euphemistic expressions and use vocabulary that is clear and comprehensible to everyone

Richard Rorty i una aproximació pragmatista al liberalisme polític de John Rawls

Aquest article es proposa explorar la possibilitat d'apropar a la concepció del liberalisme polític metafilosòfic de John Rawls des del punt de vista pragmatista de Richard Rorty. La proposta està motivada per les similituds que es poden observar entre elles respecte de la finalitat i la sortida d'una concepció política. El resultat final de l'article és ambigua: d'una banda, no sembla tan descabellat afirmar que la teoria de Rawls es pot llegir sense més dificultats des d'una perspectiva pragmàtica, d'altra banda, hi ha alguns aspectes importants en els quals un liberalisme polític de Rawls segueix sent incompatible amb una concepció política de Rorty

The Politics of Privacy

In 'Privacy and Politics', Kieron O'Hara discusses the relation of the political philosophy of privacy to technical aspects in Web development. Despite a vigorous debate, the concept remains ambiguous, and a series of types of privacy is defined: epistemological, spatial, ideological, decisional and economic. Each of these has a different meaning in the online environment, and will be defended by different measures. The question of whether privacy is a right is raised, and generational differences in attitude discussed, alongside the issue of whether privacy should be protected in advance, via a consent model, or retrospectively via increased transparency and accountability. Finally, reasons both theoretical and practical for ranking privacy below other values (such as security, efficiency or benefits for the wider community) are discussed.

Elementos estructurales del consentimiento informado

El consentimiento informado es la expresión de la voluntad del paciente, relacionada con una intervención o un tratamiento terapéutico que se hará en su cuerpo, para que se dé aquel; previamente el profesional de la salud debe suministrar veraz, integral y oportunamente la información referente a los riesgos, los procedimientos, las expectativas, el diagnóstico y el pronóstico de su enfermedad y su respectivo tratamiento. Por lo tanto, del consentimiento informado se derivan obligaciones y derechos, tanto para el paciente como para el profesional de la salud, al ser un elemento tan especial y esencial en la relación médico-paciente, y en el mismo acto médico, cobra especial relevancia en la responsabilidad médica. Sin embargo, en la praxis muchas veces se olvida la importancia del consentimiento informado en relación con aquella. El propósito de este artículo consiste en analizar los elementos estructurales del consentimiento informado, los cuales son fundamentales a la hora en que el médico lo solicite. En dicho escenario surgen situaciones que generan dudas jurídicas en cuanto a su formación. De igual forma, para tener una idea concreta y completa del consentimiento informado, dividiremos este artículo en dos partes. En la primera, nos ocuparemos del desarrollo doctrinal del concepto, en el que analizaremos su noción, su evolución en la historia y sus modelos (beneficencia, paternalismo, autonomía, entre otros); posteriormente, estudiaremos la problemática que se puede originar durante el proceso de informar al paciente, debido a que no en todos los casos este está en pleno uso de sus facultades para otorgar su consentimiento. Es allí donde miraremos la capacidad en el ámbito médico y los casos en que se puede pedir un consentimiento informado directo e indirecto. Finalmente, analizaremos el tema del riesgo y el desarrollo que la doctrina ha dado al respecto, para revisar en último lugar el consentimiento en la historia clínica y su solicitud correcta al paciente. En la segunda parte, nos encargaremos de examinar detenidamente el desarrollo jurisprudencial del consentimiento informado surtido en la Corte Constitucional y en el Consejo de Estado de la República de Colombia, desde 1991 a la fecha, del cual sin duda alguna el lector podrá concluir lo esencial e imperioso de este en la práctica médica y en la prevención del daño antijurídico.

La Ucrania post-soviética: geopolítica de un estado bipolar

El propósito de la presente monografía es analizar los elementos geopolíticos que dan cuenta de la fragmentación interna de Ucrania entre la élite y la población durante la posguerra fría. De esta forma, una interpretación divergente del espacio genera, por una parte, una división geográfica de la población (oriente/occidente), situación que ha impedido la consolidación de “una sola nación” y, por otra, la fragmentación entre las élites políticas que se encuentran en constante rotación, ha imposibilitado el surgimiento de una organización sólida e independiente. El resultado de esta doble tensión es la eclosión de un Estado bipolar que es justamente la característica definitoria de Ucrania en la posguerra fría. Con la idea de Estado bipolar se pretende realizar un aporte a la comprensión geopolítica en la era post-soviética, articulando una serie de elementos de orden teórico-analítico que permitan interpretar la circunstancia particular de la nación eslava.

Advances and limitations in the attention to the problems of housing and urban land in Mexico. An approach from the legal-institutional frame

In this work we analyze the reforms carried out by the Mexican state in the nineties of the 20th century, in the items concerning the policies of housing and urban land, based on an exhaustive review of the main actions, programs and changes in the legal and institutional frame that applies for each of these fields. The nineties represent a "breaking point" in the way the State considers the satisfaction of the right to the housing and attends the offer of urbanized land for a tidy and sustainable urban development. In this period of time, the approach of direct intervention in developing and financing housing and creation of land reserves has changed into another one, ruled by the logic of the market. The balance to the first decade of the 21st century is ambiguous, as neither the housing policy has solved the housing shortage for low-income population, nor the land policy has eliminated the illegal urban growth.