QUANDO OS ESPÍRITOS SAEM DO ABISMO: O ESTABELECIMENTO NARRATIVO DO TERROR ESCATOLÓGICO EM APOCALIPSE 9,1-21

O Apocalipse de João é uma obra instigante. Sua linguagem cheia de violência, com monstros aterrorizantes, pessoas clamando por justiça, anúncios de mortes e desespero, em um quadro de espetáculos celestes, fascina os que gostam de ficção e alimenta a esperança dos que esperam um dia entrar na Nova Jerusalém, onde não haverá mar nem morte, quando as lágrimas serão enxugadas. Contudo, o livro do Apocalipse será lido como uma narração da realidade. Nesse sentido, o texto não é visto como reflexo de qualquer opressão, mas construção discursiva a respeito do sistema que, para o visionário, é a negação da ordem. Neste trabalho, a partir dos conceitos de texto e memória cultural, à luz das pesquisas de I. Lótman, da escola russa de semiótica da cultura e das pesquisas dos Assmann, observar-se-á como as memórias de seres celestes caídos e aprisionados da tradição enoquita estão presentes na literatura judaico-cristã e servem para a construção narrativa do cenário de terror escatológico na quinta e sexta trombetas de Ap 9,1-21. Assim sendo, a tese defende o terror como instrumento de persuasão, o qual serviu, na estratégia do visionário, para descrever o seu contexto como realidade caótica. Por meio de estratégias narrativas, o narrador deseja que sua visão seja levada a sério e que seus interlocutores aceitem a sua interpretação da realidade, deixando a associação com a vida e sistema romanos, pois se assim procederem serão comparados aos selados e receberão as mesmas recompensas. Dessa maneira, sua descrição com linguagem escatológica joga com o futuro e com o presente; prevê o caos, mas o vive em nível narrativo. Por isso o livro do Apocalipse, com um dualismo extremamente radical, não dá espaços para dúvidas. A tese defende, portanto, que essa obra pode ser lida como instrumento retórico de terror e medo que leva seus leitores implícitos a não flertarem com Roma, a não aceitarem seus discursos ou os que com ela se associam.

AS MALDIÇÕES DO SALMO 137: O princípio da reciprocidade na justiça do Antigo Testamento como chave bíblica para a interpretação

Esta tese, baseada na exegese, defende que as maldições do Salmo 137 devem ser interpretadas levando-se em conta o princípio da reciprocidade praticado na justiça do AT, o famoso "olho por olho, dente por dente". Apresenta auxílios para a interpretação das maldições nos salmos; analisa o estado atual da questão; verifica a coerência ou não da utilização do termo "Salmo Imprecatório"; trata da difícil questão do contexto histórico dos salmos e, ainda, destaca alguns pontos que dificultam a interpretação cristã deste tipo de literatura. Ela trata das questões do texto, da estrutura, do gênero literário, da autoria, e do contexto de vida e histórico do Salmo 137. Além disso, apresenta paralelos deste gênero no mundo bíblico e compara versões do Salmo 137 em português. Mostra que no AT a palavra era tratada como algo que possui poder intrinseco; verifica como, normalmente, era feito o uso das maldições no AT em geral, preparando o caminho para a verificação de seu uso específico no Salmo 137; faz uma rápida retrospectiva histórica mostrando a longa trajetória de desavenças de Israel/Judá com Edom e Babilônia, o que leva o salmista a sentir-se no direito de pedir que estas duas nações sejam destruídas e sofram; levanta, ainda, a possibilidade do Salmo 137 não ser o único do Saltério com maldições contra Edom e Babilônia, e destaca que nesta composição existe uma automaldição e duas maldições, uma contra Edom e outra contra Babilônia, todas elas levando em conta o princípio da reciprocidade na justiça do AT.(AU)

DIVULGAÇÃO CIENTÍFICA NAS REVISTAS CIÊNCIA HOJE, SCIENTIFIC AMERICAN BRASIL E SUPERINTERESSANTE: ESTUDO COMPARATIVO

Estudo comparativo que analisa a divulgação científica (DC) praticada pelas revistas Ciência Hoje (CH), Scientific American Brasil (SAB) e Superinteressante (SI), apontando convergências e divergências entre as três publicações. Objetiva-se analisar como as formas de construção textual e o uso de ilustrações nas matérias e nos artigos de capa das revistas CH, SAB e SI podem contribuir ou interferir de maneira efetiva na DC que praticam. Para tanto, são delineados cinco pressupostos básicos: (1) as publicações de análise priorizam nas capas temas pertencentes às Ciências Básicas (CB) em detrimento das Ciências Humanas e Sociais (CHS); (2) no campo amplo das CB há preferência, nas capas das revistas, por temas relacionados à saúde; (3) as temáticas abordadas nas capas das revistas CH, SAB e SI não são, em geral, coincidentes entre si, pois não seguem uma lógica de matérias quentes ; (4) o uso freqüente de elementos explicativos, termos figurados, fontes de informação diversificadas e citações diretas nas construções textuais das matérias e dos artigos de capa das publicações, bem como o uso de ilustrações devidamente contextualizadas, contribuem para tornar os textos mais inteligíveis; (5) as revistas CH, SAB e SI, embora consideradas revistas de DC, apresentam níveis diferenciados de divulgação, em função do perfil de seus leitores. Em consonância com esses pressupostos, são objetivos específicos: a) identificar, dentro das duas amplas categorias (CB e CHS), os temas mais explorados, reunindo-os em subcategorias para identificar mais afinidade / proximidade entre eles; b) examinar, através das formas de construção textual e do uso das ilustrações nas matérias e nos artigos de capa, os critérios utilizados pelas publicações para divulgar ciência e tecnologia (C&T). Para responder os parâmetros estabelecidos nos objetivos apresentados, a metodologia inclui questionário aplicado aos editores das publicações investigadas e análise de conteúdo (AC) da amostra selecionada, que engloba 19 matérias / artigos de capa das revistas CH, SAB e SI, escolhidos entre julho de 2009 e junho de 2010. Os dados coletados e devidamente discutidos permitem confirmar os pressupostos enunciados, vez que, em termos gerais, é evidente que a DC praticada pelas três revistas apresenta mais divergências do que convergências. Isto possibilita estabelecer níveis distintos de divulgação, manifestos na forma como constroem os textos e como utilizam as ilustrações, com maior dificuldade em SAB e CH e com teor mais simplificado em SI.

Ontologies, taxonomies, thesauri:learning from texts

The use of ontologies as representations of knowledge is widespread but their construction, until recently, has been entirely manual. We argue in this paper for the use of text corpora and automated natural language processing methods for the construction of ontologies. We delineate the challenges and present criteria for the selection of appropriate methods. We distinguish three ma jor steps in ontology building: associating terms, constructing hierarchies and labelling relations. A number of methods are presented for these purposes but we conclude that the issue of data-sparsity still is a ma jor challenge. We argue for the use of resources external tot he domain specific corpus.

Meeting the challenge on the path to democracy: discursive strategies in governmental declarations

The communicative practice in the ex-GDR was complex and diverse, although public political discourse had been fairly ritualized. Text-types characteristic of the Communist Party discourse were full of general (superordinate) terms semantic specification was hardly possible (propositional reduction). Changes in the social world result in changes in the communicative practice as well. However, a systematic comparision of text-types across cultures and across ideological boundaries reveals both differences in the textual macro- and superstructures and overlapping as well as universal features, probably related to functional aspects (discourse of power). Six sample texts of the text-type `government declaration', two produced in the ex-GDR, four in the united Germany, are analysed. Special attention is paid to similarities and differences (i) in the textual superstructure (problem-solution schema), (ii) in the concepts that reflect the aims of political actions (simple worlds), (iii) in the agents who (are to) perform these actions (concrete vs abstract agents). Similarities are found mainly in the discursive strategies, e.g. legitimization text actions. Differences become obvious in the strategies used for legitimization, and also in the conceptual domains referred to by the problem-solution schema. The metaphors of construction, path and challenge are of particular interest in this respect.

'The prime minister said...': voices in translated political texts

A variety of texts are translated to fulfil functions for political communication across languages, cultures, and ideologies. For example, newspapers regularly provide quotes of statements by foreign politicians, without explicitly indicating that these politicians were actually speaking in their own languages. Politicians react to statements by other politicians as they were presented to them in translation. Political scientists and other experts often debate the potential political consequences of (the translation of) a statement. This chapter addresses the (in)visibility of translation in political communication and the link between textual profiles of translations and the socio-political contexts in which they are produced. The analyses are conducted from the perspective of Translation Studies. The focus is on institutionalised forms of political discourse, i.e. texts that originate in political or media institutions. The link between translation profiles and the social, institutional, ideological conditions of text production is illustrated with reference to authentic political texts (interviews, speeches by politicians, press conferences), mainly involving English, French and German as source and target languages.

Higher-order co-occurrences for exploratory point pattern analysis and decision tree clustering on spatial data

Analyzing geographical patterns by collocating events, objects or their attributes has a long history in surveillance and monitoring, and is particularly applied in environmental contexts, such as ecology or epidemiology. The identification of patterns or structures at some scales can be addressed using spatial statistics, particularly marked point processes methodologies. Classification and regression trees are also related to this goal of finding "patterns" by deducing the hierarchy of influence of variables on a dependent outcome. Such variable selection methods have been applied to spatial data, but, often without explicitly acknowledging the spatial dependence. Many methods routinely used in exploratory point pattern analysis are2nd-order statistics, used in a univariate context, though there is also a wide literature on modelling methods for multivariate point pattern processes. This paper proposes an exploratory approach for multivariate spatial data using higher-order statistics built from co-occurrences of events or marks given by the point processes. A spatial entropy measure, derived from these multinomial distributions of co-occurrences at a given order, constitutes the basis of the proposed exploratory methods. © 2010 Elsevier Ltd.

Neural population coding is optimized by discrete tuning curves

The sigmoidal tuning curve that maximizes the mutual information for a Poisson neuron, or population of Poisson neurons, is obtained. The optimal tuning curve is found to have a discrete structure that results in a quantization of the input signal. The number of quantization levels undergoes a hierarchy of phase transitions as the length of the coding window is varied. We postulate, using the mammalian auditory system as an example, that the presence of a subpopulation structure within a neural population is consistent with an optimal neural code.

Higher-order co-occurrences for exploratory point pattern analysis and decision tree clustering on spatial data

Analyzing geographical patterns by collocating events, objects or their attributes has a long history in surveillance and monitoring, and is particularly applied in environmental contexts, such as ecology or epidemiology. The identification of patterns or structures at some scales can be addressed using spatial statistics, particularly marked point processes methodologies. Classification and regression trees are also related to this goal of finding "patterns" by deducing the hierarchy of influence of variables on a dependent outcome. Such variable selection methods have been applied to spatial data, but, often without explicitly acknowledging the spatial dependence. Many methods routinely used in exploratory point pattern analysis are2nd-order statistics, used in a univariate context, though there is also a wide literature on modelling methods for multivariate point pattern processes. This paper proposes an exploratory approach for multivariate spatial data using higher-order statistics built from co-occurrences of events or marks given by the point processes. A spatial entropy measure, derived from these multinomial distributions of co-occurrences at a given order, constitutes the basis of the proposed exploratory methods. © 2010 Elsevier Ltd.

Approximating differentiable relationships between delay embedded dynamical systems with radical basis functions

This thesis is about the study of relationships between experimental dynamical systems. The basic approach is to fit radial basis function maps between time delay embeddings of manifolds. We have shown that under certain conditions these maps are generically diffeomorphisms, and can be analysed to determine whether or not the manifolds in question are diffeomorphically related to each other. If not, a study of the distribution of errors may provide information about the lack of equivalence between the two. The method has applications wherever two or more sensors are used to measure a single system, or where a single sensor can respond on more than one time scale: their respective time series can be tested to determine whether or not they are coupled, and to what degree. One application which we have explored is the determination of a minimum embedding dimension for dynamical system reconstruction. In this special case the diffeomorphism in question is closely related to the predictor for the time series itself. Linear transformations of delay embedded manifolds can also be shown to have nonlinear inverses under the right conditions, and we have used radial basis functions to approximate these inverse maps in a variety of contexts. This method is particularly useful when the linear transformation corresponds to the delay embedding of a finite impulse response filtered time series. One application of fitting an inverse to this linear map is the detection of periodic orbits in chaotic attractors, using suitably tuned filters. This method has also been used to separate signals with known bandwidths from deterministic noise, by tuning a filter to stop the signal and then recovering the chaos with the nonlinear inverse. The method may have applications to the cancellation of noise generated by mechanical or electrical systems. In the course of this research a sophisticated piece of software has been developed. The program allows the construction of a hierarchy of delay embeddings from scalar and multi-valued time series. The embedded objects can be analysed graphically, and radial basis function maps can be fitted between them asynchronously, in parallel, on a multi-processor machine. In addition to a graphical user interface, the program can be driven by a batch mode command language, incorporating the concept of parallel and sequential instruction groups and enabling complex sequences of experiments to be performed in parallel in a resource-efficient manner.

Individual differences in human-computer interaction

This thesis initially presents an 'assay' of the literature pertaining to individual differences in human-computer interaction. A series of experiments is then reported, designed to investigate the association between a variety of individual characteristics and various computer task and interface factors. Predictor variables included age, computer expertise, and psychometric tests of spatial visualisation, spatial memory, logical reasoning, associative memory, and verbal ability. These were studied in relation to a variety of computer-based tacks, including: (1) word processing and its component elements; (ii) the location of target words within passages of text; (iii) the navigation of networks and menus; (iv) command generation using menus and command line interfaces; (v) the search and selection of icons and text labels; (vi) information retrieval. A measure of self-report workload was also included in several of these experiments. The main experimental findings included: (i) an interaction between spatial ability and the manipulation of semantic but not spatial interface content; (ii) verbal ability being only predictive of certain task components of word processing; (iii) age differences in word processing and information retrieval speed but not accuracy; (iv) evidence of compensatory strategies being employed by older subjects; (v) evidence of performance strategy differences which disadvantaged high spatial subjects in conditions of low spatial information content; (vi) interactive effects of associative memory, expertise and command strategy; (vii) an association between logical reasoning and word processing but not information retrieval; (viii) an interaction between expertise and cognitive demand; and (ix) a stronger association between cognitive ability and novice performance than expert performance.

Non-linear hierarchical visualisation

This thesis applies a hierarchical latent trait model system to a large quantity of data. The motivation for it was lack of viable approaches to analyse High Throughput Screening datasets which maybe include thousands of data points with high dimensions. High Throughput Screening (HTS) is an important tool in the pharmaceutical industry for discovering leads which can be optimised and further developed into candidate drugs. Since the development of new robotic technologies, the ability to test the activities of compounds has considerably increased in recent years. Traditional methods, looking at tables and graphical plots for analysing relationships between measured activities and the structure of compounds, have not been feasible when facing a large HTS dataset. Instead, data visualisation provides a method for analysing such large datasets, especially with high dimensions. So far, a few visualisation techniques for drug design have been developed, but most of them just cope with several properties of compounds at one time. We believe that a latent variable model (LTM) with a non-linear mapping from the latent space to the data space is a preferred choice for visualising a complex high-dimensional data set. As a type of latent variable model, the latent trait model can deal with either continuous data or discrete data, which makes it particularly useful in this domain. In addition, with the aid of differential geometry, we can imagine the distribution of data from magnification factor and curvature plots. Rather than obtaining the useful information just from a single plot, a hierarchical LTM arranges a set of LTMs and their corresponding plots in a tree structure. We model the whole data set with a LTM at the top level, which is broken down into clusters at deeper levels of t.he hierarchy. In this manner, the refined visualisation plots can be displayed in deeper levels and sub-clusters may be found. Hierarchy of LTMs is trained using expectation-maximisation (EM) algorithm to maximise its likelihood with respect to the data sample. Training proceeds interactively in a recursive fashion (top-down). The user subjectively identifies interesting regions on the visualisation plot that they would like to model in a greater detail. At each stage of hierarchical LTM construction, the EM algorithm alternates between the E- and M-step. Another problem that can occur when visualising a large data set is that there may be significant overlaps of data clusters. It is very difficult for the user to judge where centres of regions of interest should be put. We address this problem by employing the minimum message length technique, which can help the user to decide the optimal structure of the model. In this thesis we also demonstrate the applicability of the hierarchy of latent trait models in the field of document data mining.

Theme and thematic patterns in Spanish and English history texts

The aim of this research project is to compare published history textbooks written for upper-secondary/tertiary study in the U.S. and Spain using Halliday's (1994) Theme/Rheme construct. The motivation for using the Theme/Rheme construct to analyze professional texts in the two languages is two-fold. First of all, while there exists a multitude of studies at the grammatical and phonological levels between the two languages, very little analysis has been carried out in comparison at the level of text, beyond that of comparing L1/L2 student writing. Secondly, thematic considerations allow the analyst to highlight areas of textual organization in a systematic way for purposes of comparison. The basic hypothesis tested here rests on the premise that similarity in the social function of the texts results in similar Theme choice and thematic patterning across languages, barring certain linguistic constraints. The corpus for this study consists of 20 texts: 10 from various history textbooks published in the U.S. and 10 from various history textbooks published in Spain. The texts chosen represent a variety of authors, in order to control for author style or preference. Three overall areas of analysis were carried out, representing Halliday's (1994) three metafunctions: the ideational, the interpersonal and the textual. The ideational analysis shows similarities across the two corpora in terms of participant roles and circumstances as Theme, with a slight difference in participants involved in material processes, which is shown to reflect a minor difference in the construal of the field of history in the two cultures. The textual analysis shows overall similarities with respect to text organization, and the interpersonal analysis shows overall similarities as regards the downplay of discrepant interpretations of historical events as well as a low frequency of interactive textual features, manifesting the informational focus of the texts. At the same time, differences in results amongst texts within each of the corpora demonstrate possible effect of subject matter, in many cases, and individual author style in others. Overall, the results confirm that similarity in content, but above all in purpose and audience, result in texts which show similarities in textual features, setting aside certain grammatical constraints.

Strategic planning as communicative process

This thesis looks at the construction of a strategic plan within a British university (Unico). After a change in leadership, the well-known strategic planning sequence was adopted to set directions according to Unico’s three Missions, followed by the development of respective goals and measures. The evolving strategic content coincided with the development of Unico’s strategic plan. I was able to follow Unico’s planning efforts over 10 months, from first planning meeting to completion of its strategic plan. The main data source provided non-participant observation (n = 25) and ten versions of Unico’s strategic plan. Additionally, seventy-six interviews were held with participants at various points. In order to examine the strategic plan’s construction, I reconceptualised strategic planning as a communicative process consisting of oral talk and written text. Through this interplay strategic planning activities come in to being. Such reconceptualisation provided a conceptual framework to study the in situ interactions without neglecting contextual characteristics embedding the communicative process. Strategic plans are currently seen as promoting inflexibility and reinforcing the institutional nature of formal strategic planning. Adopting dialogism, as advocated by Bakhtin and Ricoeur, this research provides novel insights into the dialogic of strategy talk and strategy text, such as a strategic plan. Findings illustrated that a strategic plan production cycle provided a meaning making platform for its participants. Through recurrently amending the plan, its content became increasingly specific while at the same time reflecting agreed terminology. This thesis offers an alternative view on strategic planning, elaborates on the strategy-as-practice perspective, focusing on the under-explored area of individuals’ interactions at the micro level, and elaborates on the dialogic of text and agency/conversation, distinguishing between talk and text.

A Bayesian modeling approach to multi-dimensional sentiment distributions prediction

Sentiment analysis has long focused on binary classification of text as either positive or negative. There has been few work on mapping sentiments or emotions into multiple dimensions. This paper studies a Bayesian modeling approach to multi-class sentiment classification and multidimensional sentiment distributions prediction. It proposes effective mechanisms to incorporate supervised information such as labeled feature constraints and document-level sentiment distributions derived from the training data into model learning. We have evaluated our approach on the datasets collected from the confession section of the Experience Project website where people share their life experiences and personal stories. Our results show that using the latent representation of the training documents derived from our approach as features to build a maximum entropy classifier outperforms other approaches on multi-class sentiment classification. In the more difficult task of multi-dimensional sentiment distributions prediction, our approach gives superior performance compared to a few competitive baselines. © 2012 ACM.