O uso de elementos da Natureza da Ciência (NdC) nas salas de aula da Educação Básica é, cada vez mais, um objetivo presente na literatura especializada e nos documentos oficiais que regem a educação em seus diferentes níveis, em diversos países. Apesar do grande volume de pesquisas e esforços no sentido de oferecer subsídios teórico-epistemológicos aos professores, a NdC ainda não alcança os bancos escolares, mesmo entre aqueles professores que demonstram possuir concepções informadas referentes ao tema. Fundamentado nos referenciais epistemológico e metodológico de Bruno Latour, este trabalho propõe-se a (1) investigar as potencialidades do uso de microepisódios de ensino como estratégia didática em uma disciplina de História da Física e Epistemologia de um curso de Licenciatura em Física de uma universidade pública, no sentido de oferecer oportunidades para os estudantes – potenciais futuros professores – conceberem estratégias para a inserção da NdC em aulas de Física e (2) acompanhar esses mesmos estudantes por um período (cerca de um ano) após a conclusão da disciplina, no intuito de investigar suas impressões sobre o uso dos microepisódios de ensino, suas compreensões acerca a importância de abordar a NdC em sala de aula e os obstáculos que identificam a essa inserção. Através da análise de gravações das apresentações durante a disciplina e de entrevistas semiestruturadas, foi possível identificar que apesar de ser necessário oferecer situações práticas para que os futuros professores explorem formas de abordar a NdC nas salas de aula, os obstáculos não se resumem à dificuldade de instrumentalizar a discussão, mas também envolve fatores muito mais profundos, como a própria compreensão individual sobre a justificação do Ensino de Física na Educação Básica, o meio profissional no qual o professor está inserido e a possibilidade de retorno financeiro proporcionado pela docência. Tudo isso forma uma rede complexa que precisa ser melhor entendida para vislumbrar possíveis avanços. / Using the Nature of Science (NoS) in Basic Education classrooms is an objective increasingly present in the specialized literature and in the official documents that rule education at its different levels in many countries. Despite the great volume of researches and effort to offer theoretical-epistemological subsides for teachers, the NoS still does not reach the classroom, even among teachers that appear to have informed conceptions of the subject. Grounded on the epistemological and methodological references of Bruno Latour, this dissertation intends to (1) investigate the potentialities of the use of micro teaching episodes as a didactic strategy in a History of Physics and Epistemology subject from a Physics Education program from a public university, with the intent of offering opportunities for students - potential future teachers - to conceive didactic strategies to insert the NoS in the teaching of Physics and (2) follow the same students for a period (about an year) after the conclusion of the program for the purpose of investigating their impressions in regards of the use of the micro teaching episodes, their comprehensions of the importance of addressing the NoS in classes and the obstacles that they identify in this inclusion. Through an analysis of lecture recordings from the program and of semi structured interviews, it was possible to identify that in spite of offering practical situations in order for the future teachers to explore ways of approaching the NoS in class being necessary, the obstacles are not limited to the difficulty of instrumentalizing the discussion, but also involves deeper factors, such as the individual comprehension of the justification of Physics teaching in Basic Education itself, the professional environment in which the teacher is inserted and the financial return possibilities provided by teaching. All of these forms a complex network that needs to be better understood so that possible advances can be glimpsed.

Esta dissertação de Mestrado visa apresentar os resultados e reflexões obtidos através de uma pesquisa envolvendo a inter-relação entre a História e Epistemologia da Ciência. Teve-se como objetivos principais desta investigação teórica: a construção de uma convergência epistemológica entre as ideias e defesas em Ciência dos filósofos Gaston Bachelard e Imre Lakatos, como também a construção de episódios em Ciência discutidos em grande parcela sob tais olhares histórico-filosóficos. Esta pesquisa possui abordagem qualitativa e quanto aos seus objetivos insere-se como descritiva-reflexiva. Iniciou-se tal investigação realizando um aprofundamento teórico envolvendo as especificidades de cada epistemologia com o objetivo de clarificar o entendimento referente aos pontos estruturantes de cada olhar epistemológico. Em relação ao processo de construção dos episódios em Ciência, realizou-se um levantamento bibliográfico contemplado em maior parte por livros e artigos científicos que tratassem da respectiva temática do episódio, buscando-se uma diversidade de fontes para fundamentar este processo de escrita, com o intuito de valorizar um olhar abrangente sobre a História da Ciência. De modo geral, a construção da convergência epistemológica se fundamentou no que ambas as epistemologias têm em comum que é a própria defesa da História da Ciência por uma natureza epistemológica dinâmica e evolutiva (no que tange à mutabilidade do conhecimento científico), visão normativa, essência dialética e caráter racional objetivo. Desta forma, buscou-se explorar as relações teóricas envolvendo os olhares histórico-filosóficos de ambos os epistemólogos na escrita dos episódios. O primeiro episódio em Ciência visou apresentar e refletir sobre dois programas científicos conflitantes na História da Ciência, os programas flogístico e calórico, os quais marcaram, pontualmente, o período pré-científico da Química e o nascimento das bases teóricas da Química moderna. Já o segundo episódio em Ciência almejou apresentar as principais concepções de matéria desenvolvidas pelos gregos durante a Antiguidade. Os episódios em Ciência produzidos nesta pesquisa valorizam um olhar histórico-filosófico da Ciência através da referida convergência, como também possibilitam uma compreensão da história do pensamento científico por uma natureza conjectural (naturalmente falível) e em constante estado de evolução. Desta forma, defende-se que as epistemologias de Lakatos e Bachelard possuem grande valia ao campo didático científico, pois fomentam concepções epistemológicas contemporâneas e defendem uma Ciência aberta e em constante estágio de devir. Além do mais, os episódios em Ciência podem servir como significativas ferramentas didáticas a abordagens de temas científicos elucidados por olhares que contemplam discussões pertinentes à essência histórico-filosófica do pensamento científico no contexto do ensino. Esta pesquisa evidencia, na base dos seus resultados finais, a necessidade de se buscar valorizar a qualificação da História da Ciência como um importante cerne das discussões dos conteúdos científicos no campo didático, como também a fomentação de um distanciamento em relação às concepções alicerçadas no contexto de ensino que remetem à epistemologia tradicional. / The aim of this Masters dissertation is to present results and reflections obtained from research that involved the interrelation between the History and the Epistemology of Science. The main objectives of this theoretical investigation were the following: the construction of an epistemological convergence between the ideas and advocacies of philosophers Gaston Bachelard and Imre Lakatos, in addition to the construction of Science episodes discussed mostly under such historical-philosophical viewpoints. The research is from a qualitative approach and regarding the objectives is inserted as descriptive-reflexive. The investigation started through further theoretical development involving the specifics of each epistemology with the objective of clarifying the understanding related to the structural points from each epistemological viewpoint. As to the process of construction of the Science episodes, a bibliographical ascertainment was made covering mainly books and scientific articles that dealt with the respective issue of the episode, seeking for source diversity to serve as the foundation for this writing process with the intent of valuing a comprehensive viewpoint of Science History. In general, the construction of the epistemological convergence was founded on where both epistemological share in common, namely the advocacy of Science History itself by a dynamic, evolving epistemological nature (pertaining to the mutability of scientific knowledge), normative viewpoint, dialectic essence, and an objective rational character. This way, an exploration of the theoretical relations was sought that involved the historical-philosophical viewpoints of both epistemologists for writing the episodes. The first Science episode is aimed at presenting and reflecting upon two conflicting scientific programs in Science History, the phlogistic and caloric programs, that were a timely marker of the pre-scientific period in Chemistry and the birth of the theoretical bases for modern Chemistry. The aims of the second Science episode is to present the main conceptions of matter developed by the Greeks in Antiquity. The Science episodes produced by this research value a historical-philosophical viewpoint of Science from the above mentioned convergence, and also allowed for an understanding of the history of scientific thought by a conjectural nature (naturally fallible) and in a constant state of evolution. This way, it is advocated that Lakatos' and Bachelard's epistemologies are of great value to the scientific didactic field by enhancing contemporary epistemological conceptions and advocate that Science be open and in a permanent state of becoming. Furthermore, the Science episodes may serve as significant didactic tools for approaching scientific themes elucidated by viewpoints the include discussions pertaining the historical-philosophical essence of the scientific thought within a teaching context. Based on its final results, this research brings to evidence the need to pursue valuing the qualification of Science History as an important core when discussing scientific contents in the didactic field, as well as enhancing a further distancing in relation go conceptions founded within the teaching context that remit to traditional epistemology.

As cianobactérias pertencem a um grupo de organismos que surgiram no planeta há cerca de 3,5 bilhões de anos. Durante 270 milhões de anos elas dominaram, em um período que ficou conhecido como o Período das Cyanophyceae (Pré-Cambriano). Águas eutrofizadas oferecem os requisitos para haver floração aumentando as chances estatísticas de aparecimento de cianobactérias, inclusive as tóxicas. Há alteração substancial das características das comunidades e do ecossistema e, por seu potencial tóxico, esses organismos causam conseqüências danosas à integridade ambiental e à saúde pública. Essas florações são resultado da interação de fatores físicos, químicos e bióticos, evidenciados por crescimento explosivo - florações - de poucas espécies, freqüentemente as menos exigentes a gás carbônico. Entre as cianobactérias formadoras de florações destacam-se os gêneros: Aphanizomenon sp., Oscillatoria sp., Anabaena sp., Microcystis sp., Gloeotrichia sp., Cylindrospermospsis sp. e Nodularia sp. Entre as cianobactérias produtoras de toxinas destacam-se as espécies: Anabaena flos-aquae, Microcysits aeruginosa, Aphanizomenon flos-aquae, Oscillatoria agardhii, Cylindrospermopsis raciborskii e Nodularia spumigena. O problema para a saúde pública e ambiental relaciona-se à liberação das toxinas que sempre ocorre após a lise celular, devido ao uso de algicidas, ao estresse celular ou à senescência. As cianotoxinas - neurotoxinas, hepatotoxinas, endotoxinas (lipopolissacarídeos) - não causam os mesmos efeitos nos diferentes organismos que as ingerem. Para análises quantitativas e qualitativas das amostras fitoplanctônicas são necessárias rotinas laboratoriais, que têm início desde a coleta, estocagem, sedimentação e identificação das espécies ao microscópio. Em câmaras de sedimentação apropriadas é possível contar e identificar os organismos em questão. O volume celular é estimado por meio de formas geométricas, correspondentes às dimensões celulares dos organismos. O carbono orgânico e os pigmentos fotossintetizantes, principalmente a clorofila a, fornecem indicação da biomassa fitoplanctônica. A extração desta pode ser feita utilizando-se acetona, etanol ou metanol. Os métodos mais usados para determinação da concentração de clorofila a são: fluorimetria, espectrofotômetria e HPLC, este último o método mais preciso. No Brasil têm sido registradas ocorrências de florações de cianobactérias e a preocupação tem aumentado significamente após o caso de Caruaru (PE). Como é difícil prever as florações de cianobactérias potencialmente tóxicas, alguns métodos laboratoriais, como bioensaios, HPLC, CG, ELISA, Inibição de Fosfatase e Inibição de Acetilcolinesterase têm sido de grande ajuda na determinação das cianotoxinas, o que possibilita que as empresas abastecedoras de água tomem as providências cabíveis, quanto ao abastecimento da população e cumprimento da Portaria 518, de 24 de março de 2004. No entanto a Portaria nº 518 do Ministério da Saúde mostra-se ineficaz pela falta de artigos sobre o gerenciamento dos corpos hídricos eutrofizados, que mostram alterações em suas características e que podem ser associados a problemas de saúde pública, e também pela falta de penalidades e outras sanções (exemplo: fiscalização) que auxiliem no cumprimento da legislação. Devido a isso, procedimentos e profissionais devem ser encontrados e treinados para o entendimento de como, onde e por que, as florações acontecem. / Cyanobacteria are part of a group of organisms that have had a long evolutionary history extending to at least 3,5 billion years ago. During 270 million years they had been dominant, in a period that was known as the \"Age of Cyanophyceae\" (Early Cambrian Period or Proterozoic Era). Eutrophic waters offer the requirements for the blooms increasing statistically the chances of cyanobacteria emergence, including the toxic ones. There is substantial disturbance of characteristics of the communities and ecosystem and, because of their toxic potential, those organisms cause harmful consequences to the environmental integrity and public health. Those blooms are a result of an interaction of physical, chemical and biotic factors, evidenced by the proliferation of few species, frequently the least demanding ones to carbonic gas. Globally among the most frequently found freshwater cyanobacteria forming water-blooms it must be emphasized the following strains: Aphanizomenon sp., Oscillatoria sp., Anabaena sp., Microcystis sp., Gloeotrichia sp., Cylindrospermospsis sp. and Nodularia sp. Among the cyanobacteria producing toxins it must be emphasized the following species: Anabaena flos-aquae, Microcysits aeruginosa, Aphanizomenon flos-aquae, Oscillatoria agardhii, Cylindrospermopsis raciborskii and Nodularia spumigena. Environmental and public health problems are largely associated with the release of toxins occurring after cellular lisys, caused by the use of algicides, cell stress or senescence. Cyanotoxins - neurotoxins, hepatotoxins, endotoxins (lipopolysaccharides) - cause distinct effects in the different organisms ingesting them. For quantitative and qualitative analyses of phytoplanktonic samples they are necessary laboratory routines as collection, stocking, sedimentation and identification of the species performed by microscopic examination. It is possible to count and identify such organisms in appropriate sedimentation chambers. Cell volumes are calculated for each species from formulae for solid geometric shapes that most closely match the cell shape based on cell dimensions. Organic carbon and photosynthetic pigments primarily chlorophyll-a are used to estimate the biomass of the phytoplankton. Chlorophyll-a extraction can be made by using acetone, ethanol or methanol. The major methods used for determination of chlorophyll-a concentrations are fluorometry, spectrophotometry and HPLC. In particular, HPLC has been considered the most accurate analytical method. Occurrences of cyanobacteria blooms in Brazil have been recorded, and a concern has becoming increasingly significant after the Caruaru (PE) episode. It is difficult to foresee the potentially toxic cyanobacteria blooms, so some laboratory methods as Bioassays, HPLC, CG, ELISA, Inhibition of Phosphatase and Inhibition of Acetylcholinesterase have been of great help in the determination of the cyanotoxins, what permits that the health authorities take reasonable providences related to drinking water supplies and fulfill the Guideline 518, of March 24, 2004. Nevertheless, national legislation becomes inefficient by the lack of ordinances about the management of eutrophic water bodies, which may notably alter the characteristics of aquatic ecosystems and cause public health problems. Penalties and other sanctions to assist in enforcement of the legislation are also needed. Procedures must be taken and operators must be trained in order to clarify how, where and why blooms happen.

This thesis seeks to analyze the Homeric allusions in the Aethiopica with an inclusive definition to explore Heliodorus’ authorial motives. To approach this project, I use textual analysis to avoid arguments rooted in assumptions of the historical context of the novel, about which we know almost nothing. I explore how links to Homer’s Odyssey are visible within the structural organization of the text and the content of the text. I also explore how the content of the novel reproduces actions and compatible settings of Odyssean characters, which therefore qualifies Heliodorus’ characters in a metaliterary commentary with Homer’s archaic epic poem. The division of Odyssean actions and traits depicted in Heliodorus’ characters introduce a new addition to the heroic legacy established by Homer and distances the hero from Greek identity. I conclude that Heliodorus’ adherences to epic conventions and departures thereof inform the subtextual commentaries conveyed in the Aethiopica.

Thesis (M.Sc. (Statistics)) -- University of Limpopo, 2019 / Recurrent peritonitis is a major problem of peritoneal dialysis (PD) due to its association with technique failure in the dialysis process. The literature on peritonitis focused only on investigating major risk factors associated with the first episode of peritonitis. However, this dissertation investigates factors associated to multiple episodes of peritonitis, to a maximum of 6 episodes. The correlation of recurrent episodes of a patient is considered. The univariate counting process, stratified, gap-time and marginal hazard regression models are applied to select the significant covariates to the multivariate regression hazard models. Regression coefficient for covariates are found to be statistically significant at 5% level. The application of Akaike information criterion (AIC) and Schwarz bayesian criterion (SBC) assisted to filter out the best method which is the stratified regression hazard model. The major risk factors associated with recurrent episodes of peritonitis are examined from the selected good fitting model. In conclusion, the selected model identified two independent risk factors to be significantly associated with recurrent episodes of peritonitis: marital status and glomerularfiltrationrate. Twocategoriesofmaritalstatus, divorceandwidowerare the significant factors compared to married patients (when taking married patients as the reference category). / VLIROUC Programme

This dissertation investigates algorithmic techniques for temporal process discovery in many domains. Many different formalisms have been proposed for modeling temporal processes such as motifs, dynamic Bayesian networks and partial orders, but the direct inference of such models from data has been computationally intensive or even intractable. In this work, we propose the mining of frequent episodes as a bridge to inferring more formal models of temporal processes. This enables us to combine the advantages of frequent episode mining, which conducts level wise search over constrained spaces, with the formal basis of process representations, such as probabilistic graphical models and partial orders. We also investigate the mining of frequent episodes in infinite data streams which further expands their applicability into many modern data mining contexts. To demonstrate the usefulness of our methods, we apply them in different problem contexts such as: sensor networks in data centers, multi-neuronal spike train analysis in neuroscience, and electronic medical records in medical informatics. / Ph. D.

Temporal data mining is concerned with the exploration of large sequential (or temporally ordered) data sets to discover some nontrivial information that was previously unknown to the data owner. Sequential data sets come up naturally in a wide range of application domains, ranging from bioinformatics to manufacturing processes. Pattern discovery refers to a broad class of data mining techniques in which the objective is to unearth hidden patterns or unexpected trends in the data. In general, pattern discovery is about finding all patterns of 'interest' in the data and one popular measure of interestingness for a pattern is its frequency in the data. The problem of frequent pattern discovery is to find all patterns in the data whose frequency exceeds some user-defined threshold. Discovery of temporal patterns that occur frequently in sequential data has received a lot of attention in recent times. Different approaches consider different classes of temporal patterns and propose different algorithms for their efficient discovery from the data. This thesis is concerned with a specific class of temporal patterns called episodes and their discovery in large sequential data sets. In the framework of frequent episode discovery, data (referred to as an event sequence or an event stream) is available as a single long sequence of events. The ith event in the sequence is an ordered pair, (Et,tt), where Et takes values from a finite alphabet (of event types), and U is the time of occurrence of the event. The events in the sequence are ordered according to these times of occurrence. An episode (which is the temporal pattern considered in this framework) is a (typically) short partially ordered sequence of event types. Formally, an episode is a triple, (V,<,9), where V is a collection of nodes, < is a partial order on V and 9 is a map that assigns an event type to each node of the episode. When < is total, the episode is referred to as a serial episode, and when < is trivial (or empty), the episode is referred to as a parallel episode. An episode is said to occur in an event sequence if there are events in the sequence, with event types same as those constituting the episode, and with times of occurrence respecting the partial order in the episode. The frequency of an episode is some measure of how often it occurs in the event sequence. Given a frequency definition for episodes, the task is to discover all episodes whose frequencies exceed some threshold. This is done using a level-wise procedure. In each level, a candidate generation step is used to combine frequent episodes from the previous level to build candidates of the next larger size, and then a frequency counting step makes one pass over the event stream to determine frequencies of all the candidates and thus identify the frequent episodes. Frequency counting is the main computationally intensive step in frequent episode discovery. Choice of frequency definition for episodes has a direct bearing on the efficiency of the counting procedure. In the original framework of frequent episode discovery, episode frequency is defined as the number of fixed-width sliding windows over the data in which the episode occurs at least once. Under this frequency definition, frequency counting of a set of |C| candidate serial episodes of size N has space complexity O(N|C|) and time complexity O(ΔTN|C|) (where ΔT is the difference between the times of occurrence of the last and the first event in the data stream). The other main frequency definition available in the literature, defines episode frequency as the number of minimal occurrences of the episode (where, a minimal occurrence is a window on the time axis containing an occurrence of the episode, such that, no proper sub-window of it contains another occurrence of the episode). The algorithm for obtaining frequencies for a set of |C| episodes needs O(n|C|) time (where n denotes the number of events in the data stream). While this is time-wise better than the the windows-based algorithm, the space needed to locate minimal occurrences of an episode can be very high (and is in fact of the order of length, n, of the event stream). This thesis proposes a new definition for episode frequency, based on the notion of, what is called, non-overlapped occurrences of episodes in the event stream. Two occurrences are said to be non-overlapped if no event corresponding to one occurrence appears in between events corresponding to the other. Frequency of an episode is defined as the maximum possible number of non-overlapped occurrences of the episode in the data. The thesis also presents algorithms for efficient frequent episode discovery under this frequency definition. The space and time complexities for frequency counting of serial episodes are O(|C|) and O(n|C|) respectively (where n denotes the total number of events in the given event sequence and |C| denotes the num-ber of candidate episodes). These are arguably the best possible space and time complexities for the frequency counting step that can be achieved. Also, the fact that the time needed by the non-overlapped occurrences-based algorithm is linear in the number of events, n, in the event sequence (rather than the difference, ΔT, between occurrence times of the first and last events in the data stream, as is the case with the windows-based algorithm), can result in considerable time advantage when the number of time ticks far exceeds the number of events in the event stream. The thesis also presents efficient algorithms for frequent episode discovery under expiry time constraints (according to which, an occurrence of an episode can be counted for its frequency only if the total time span of the occurrence is less than a user-defined threshold). It is shown through simulation experiments that, in terms of actual run-times, frequent episode discovery under the non-overlapped occurrences-based frequency (using the algorithms developed here) is much faster than existing methods. There is also a second frequency measure that is proposed in this thesis, which is based on, what is termed as, non-interleaved occurrences of episodes in the data. This definition counts certain kinds of overlapping occurrences of the episode. The time needed is linear in the number of events, n, in the data sequence, the size, N, of episodes and the number of candidates, |C|. Simulation experiments show that run-time performance under this frequency definition is slightly inferior compared to the non-overlapped occurrences-based frequency, but is still better than the run-times under the windows-based frequency. This thesis also establishes the following interesting property that connects the non-overlapped, the non-interleaved and the minimal occurrences-based frequencies of an episode in the data: the number of minimal occurrences of an episode is bounded below by the maximum number of non-overlapped occurrences of the episode, and is bounded above by the maximum number of non-interleaved occurrences of the episode in the data. Hence, non-interleaved occurrences-based frequency is an efficient alternative to that based on minimal occurrences. In addition to being superior in terms of both time and space complexities compared to all other existing algorithms for frequent episode discovery, the non-overlapped occurrences-based frequency has another very important property. It facilitates a formal connection between discovering frequent serial episodes in data streams and learning or estimating a model for the data generation process in terms of certain kinds of Hidden Markov Models (HMMs). In order to establish this connection, a special class of HMMs, called Episode Generating HMMs (EGHs) are defined. The symbol set for the HMM is chosen to be the alphabet of event types, so that, the output of EGHs can be regarded as event streams in the frequent episode discovery framework. Given a serial episode, α, that occurs in the event stream, a method is proposed to uniquely associate it with an EGH, Λα. Consider two N-node serial episodes, α and β, whose (non-overlapped occurrences-based) frequencies in the given event stream, o, are fα and fβ respectively. Let Λα and Λβ be the EGHs associated with α and β. The main result connecting episodes and EGHs states that, the joint probability of o and the most likely state sequence for Λα is more than the corresponding probability for Λβ, if and only if, fα is greater than fβ. This theoretical connection has some interesting consequences. First of all, since the most frequent serial episode is associated with the EGH having the highest data likelihood, frequent episode discovery can now be interpreted as a generative model learning exercise. More importantly, it is now possible to derive a formal test of significance for serial episodes in the data, that prescribes, for a given size of the test, a minimum frequency for the episode needed in order to declare it as statistically significant. Note that this significance test for serial episodes does not require any separate model estimation (or training). The only quantity required to assess significance of an episode is its non-overlapped occurrences-based frequency (and this is obtained through the usual counting procedure). The significance test also helps to automatically fix the frequency threshold for the frequent episode discovery process, so that it can lead to what may be termed parameterless data mining. In the framework considered so far, the input to frequent episode discovery process is a sequence of instantaneous events. However, in many applications events tend to persist for different periods of time and the durations may carry important information from a data mining perspective. This thesis extends the framework of frequent episodes to incorporate such duration information directly into the definition of episodes, so that, the patterns discovered will now carry this duration information as well. Each event in this generalized framework looks like a triple, (Ei, ti, τi), where Ei, as earlier, is the event type (from some finite alphabet) corresponding to the ith event, and ti and τi denote the start and end times of this event. The new temporal pattern, called the generalized episode, is a quadruple, (V, <, g, d), where V, < and g, as earlier, respectively denote a collection of nodes, a partial order over this collection and a map assigning event types to nodes. The new feature in the generalized episode is d, which is a map from V to 2I, where, I denotes a collection of time interval possibilities for event durations, which is defined by the user. An occurrence of a generalized episode in the event sequence consists of events with both 'correct' event types and 'correct' time durations, appearing in the event sequence in 'correct' time order. All frequency definitions for episodes over instantaneous event streams are applicable for generalized episodes as well. The algorithms for frequent episode discovery also easily extend to the case of generalized episodes. The extra design choice that the user has in this generalized framework, is the set, I, of time interval possibilities. This can be used to orient and focus the frequent episode discovery process to come up with temporal correlations involving only time durations that are of interest. Through extensive simulations the utility and effectiveness of the generalized framework are demonstrated. The new algorithms for frequent episode discovery presented in this thesis are used to develop an application for temporal data mining of some data from car engine manufacturing plants. Engine manufacturing is a heavily automated and complex distributed controlled process with large amounts of faults data logged each day. The goal of temporal data mining here is to unearth some strong time-ordered correlations in the data which can facilitate quick diagnosis of root causes for persistent problems and predict major breakdowns well in advance. This thesis presents an application of the algorithms developed here for such analysis of the faults data. The data consists of time-stamped faults logged in car engine manufacturing plants of General Motors. Each fault is logged using an extensive list of codes (which constitutes the alphabet of event types for frequent episode discovery). Frequent episodes in fault logs represent temporal correlations among faults and these can be used for fault diagnosis in the plant. This thesis describes how the outputs from the frequent episode discovery framework, can be used to help plant engineers interpret the large volumes of faults logged, in an efficient and convenient manner. Such a system, based on the algorithms developed in this thesis, is currently being used in one of the engine manufacturing plants of General Motors. Some examples of the results obtained that were regarded as useful by the plant engineers are also presented.

Made available in DSpace on 2016-03-22T17:26:46Z (GMT). No. of bitstreams: 1 capa final rosana.pdf: 15525 bytes, checksum: fab2d4afcfe9faedc9db870806e272cd (MD5) Previous issue date: 2012-07-12 / Conselho Nacional de Desenvolvimento Científico e Tecnológico / Objective: The purpose of this study was to clarify the effect of imune response in diferente mood episodes. Methods: This report is part of a cross-sectional population-based study including 1560 individuals 18 to 35 year-old living in the urban area of Pelotas, RS (Brazil). We randomly selected 241 subjects from the population-based study. The diagnostic of current depression, mania or mixed episode was made using the Mini International Neuropsychiatric Interview 5.0 (MINI). Serum levels of IL-1b were measured using a commercial available immunoassay kit. Results: In the present work we found 110 (45.6%) patients with no current mood episode, 15 (6.2%) patients in maniac episodes, 91 (37.8%) patients with current depression and 25 (10.4%) patients in a mixed states. Socio-demographic variables like ethnicity and years in school were not significantly different between the groups. Regarding the cytokine measurements, patients in maniac and depressive episodes had similar levels of IL-1b (8.85 and 8.90 pg/mL, respectively) when compared to the group with no mood episodes (10.24 pg/mL). However, patients in mixed states had an increase (13.19 pg/mL) in IL-1b levels (P=0.09) when compared to the other groups. Discussion: These results suggest that mixed mood episodes are associated with higher levels of IL-1b. This pro-inflammatory state might underlie the symptom severity and the poor outcome observed in these patients / Nos últimos anos as doenças psiquiátricas foram as doenças que mais aumentaram na população mundial (Andlin-Sobocki et al., 2005). Estima-se que os transtornos de humor serão o grupo de doenças com maior custo absoluto nos próximos anos, conjuntamente com as patologias demenciais (Andlin-Sobocki et al., 2005). Apesar dos recentes progressos alcançados, as bases etiológicas dos transtornos de humor permanecem pouco elucidadas e a terapia não tem sido totalmente eficaz, com apenas 60% dos pacientes sendo responsivos aos fármacos existentes no mercado (Gareri et al., 2000). Além disso, o diagnóstico dos transtornos de humor é feito basicamente pela observação clínica do paciente, sendo muitas vezes falho e ineficaz. Desta maneira, a identificação de marcadores biológicos preditivos ou com valor diagnóstico para estas doenças pode representar um importante avanço no diagnóstico e tratamento dos transtornos de humor

Parte da comunidade de pesquisa em ensino de Física tem devotado atenção ao estudo de métodos ativos de ensino que primam pela centralização do processo de ensino-aprendizagem no aluno. Além da aprendizagem conceitual, tais métodos buscam favorecer o desenvolvimento de habilidades associadas ao trabalho colaborativo e à argumentação, e diminuir a evasão estudantil. Em disciplinas de Física Experimental alguns desses métodos envolvem a aprendizagem por modelagem científica. Contudo, o sucesso de tais iniciativas depende, entre outros fatores, do quanto os alunos se julgam capazes de realizar as atividades propostas pelo professor, ou seja, do nível de autoeficácia dos alunos em realizar determinadas ações. Pesquisas do grupo de Ensino de Física da Universidade Internacional da Flórida apontam para uma baixa mudança ou redução em níveis de autoeficácia em função do uso de métodos ativos. Com base nesses resultados propomos um estudo de caso exploratório, único e incorporado com múltiplas unidades de análise. O objetivo geral dessa dissertação é o de estudar as influências do método Episódios de Modelagem (EM) (similar ao método Modeling Instruction - MI) sobre as atitudes e crenças de autoeficácia dos estudantes em aprender física, realizar atividades experimentais e trabalhar colaborativamente. Para isso procuramos responder às seguintes questões: Quais os impactos da aplicação de Episódios de Modelagem nas crenças de autoeficácia e atitudes dos estudantes em relação a: (i) aprender física?; (ii) realizar atividades experimentais?; e (iii) trabalhar colaborativamente? Para responder a tais questões de pesquisa, adotamos as orientações metodológicas para estudo de caso de Yin (2010) e utilizamos a Teoria Social Cognitiva, em específico, o conceito de autoeficácia, de Bandura (1997). Para a investigação, realizamos um estudo exploratório com múltiplas unidades de análise (8 estudantes) na disciplina de Física Experimental II – A, que aborda os conteúdos de oscilações, ondulatória, hidrostática e termodinâmica. Os resultados mostraram que as atitudes dos alunos frente ao aprendizado de física com o método de ensino foram positivas tendo sido destacadas, principalmente, o planejamento e execução de seus próprios experimentos e as discussões fomentadas pelas apresentações dos resultados e correções das tarefas de leitura. Como fatores negativos foram mencionados: o fato da disciplina ser muito trabalhosa e de não ter tempo suficiente em aula para a realização dos planejamentos e análise de dados. Já as atitudes frente às atividades experimentais e trabalho colaborativo foram reforçadas para os sete alunos aprovados na disciplina. Sobre as crenças de autoeficácia em aprender física e em trabalhar colaborativamente, constatamos que as crenças dos alunos foram influenciadas positivamente pelas atividades desenvolvidas com o método de ensino, através de três das principais fontes destacadas por Bandura: experiências de domínio e vicárias e persuasão social. Também constatamos um reajuste na percepção dos alunos quanto aos seus níveis de autoeficácia devido às experiências vivenciadas com o método EM em comparação ao método utilizado na disciplina anterior (que utiliza roteiros dirigidos nos experimentos). Novas pesquisas são necessárias para dar continuidade a este estudo exploratório, investigando mais profundamente o processo de reajuste dos níveis de autoeficácia. / Part of the Physics Education Research (PER) community has devoted its attention to the study of Active Learning methods focusing on the centralization of the teaching-learning process at the students. Beyond the conceptual learning, these methods seek to foster the development of abilities associated to the collaborative work and argumentation, and also to decrease student’s dropout. In experimental physics disciplines, some of those methods involve the scientific modeling learning. However, the success of such initiatives depends on how much the students judge themselves capable of carrying out the activities proposed by the teacher, that is, it depends on the student’s self-efficacy levels in perform certain actions. Studies of the PER from the Florida International University show a small change or even a reduction on self-efficacy levels in function of the use of active methods. Based on those results we propose an exploratory case-study incorporated with multiple analysis unities. The general purpose of this dissertation is to study the influence of the Modeling Episodes (ME) method (similar to the MI method) on the students’ attitudes and self-efficacy beliefs about learning physics; conduct experimental activities; and work collaboratively. We tried to answer the following questions: What are the impacts of the ME application on the students’ self-efficacy beliefs and attitudes regarding: (i) learning physics?, (ii) carrying out experimental activities?, and (iii) working collaboratively? To answer these research questions we adopted the methodological orientations for Yin’s case-study and we used the Cognitive Social Theory, specifically, Bandura’s self-efficacy concept. For the investigation, we carried out an exploratory study with multiple analysis unities (8 students) at Experimental Physics II – A, class that discuss oscillations, waves, hydrostatic and thermodynamic. The results showed the students’ attitudes regarding the learning of physics as a teaching method were positive, specially: the planning and execution of their own experiments; the discussions fomented by the presentation of the results; and the evaluation of the reading assignments by the teacher. As negative factors, it was mentioned: the fact that the class was quite laborious and short time to carry out the planning and data analysis in class. Regarding the self-efficacy beliefs about learning physics and work collaboratively, the students’ beliefs were influenced positively by the activities developed with the teaching method, through three of the main sources highlighted by Bandura: mastery, vicarious experiences and social persuasion. We also identified a readjustment on student’s perception about their self-efficacy levels due to the experience with the ME method when compared to the method used in the previous experimental physics class (which used guided experimental scripts). New studies are necessary to give continuity to this exploratory study, investigating more deeply the readjustment process of the self-efficacy levels.

This dissertation is a qualitative case study exploring the process of culture learning in a Chinese as a foreign language (CFL) classroom. Guided by a socioculturally based theoretical perspective and adopting the stance of the National Standards, which says that language students "cannot truly master the language until they have also mastered the cultural contexts in which the language occurs" (1996, p. 27), this study describes how culture learning is tied to class practices aimed at developing students' language proficiency by exploring how culture and language are integrated in spoken discourse and interactions in the classroom. The research questions of the study focus on both the instructor's and the students' perspectives towards the interrelationship between language learning and culture learning and their actual practices in the dynamic, complex, and emerging speech community of classroom contexts. Through analysis of student questionnaires, classroom observations, instructor interview, and stimulated-recall sessions with students, this study examines the contexts of culture learning, illustrates how language classroom contexts shape and are shaped by all the class members, including both the instructor and the students, and describes how the classroom spoken discourse in the current advanced-level undergraduate CFL course provides opportunities for culture learning and how culture learning actually happens in this language classroom. The findings suggest that as the instructor and the students interact in the language classroom, it is not so much the particular pieces of cultural and linguistic information under discussion that delineate the actual culture learning process, but rather the active exchanges and sometimes disagreements between the instructor and the students that provide opportunities for interactive cultural dialogues and discussions. In other words, cultural knowledge and understanding are situated in actual contexts of language use. Language learning is also embedded in the same interactive and collaborative discussion of texts. By exploring the complexity of the culture learning process in the language classroom setting, this study adds theoretical and pedagogical support to the premise that culture learning should be an integral part of language instruction at different levels throughout the language curriculum.