987 resultados para Droppin Knowledge Series


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In the current study, we examined the influence of schema consistency on contradictory and additive misinformation. Sixty-four participants were shown a series of still photographs of common scenes (e.g., a kitchen), were later exposed to narratives containing misinformation, and were then tested on their memory of the photographic scenes. In addition, participants were asked to reflect on their phenomenological experience of remembering by giving remember/know responses. Participants reported greater false memory for schema-inconsistent items than schema-consistent items. The findings failed to replicate Roediger, Meade, and Bergman (2001). Explanations for the discrepant findings are discussed.

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Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

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Abstract Background A popular model for gene regulatory networks is the Boolean network model. In this paper, we propose an algorithm to perform an analysis of gene regulatory interactions using the Boolean network model and time-series data. Actually, the Boolean network is restricted in the sense that only a subset of all possible Boolean functions are considered. We explore some mathematical properties of the restricted Boolean networks in order to avoid the full search approach. The problem is modeled as a Constraint Satisfaction Problem (CSP) and CSP techniques are used to solve it. Results We applied the proposed algorithm in two data sets. First, we used an artificial dataset obtained from a model for the budding yeast cell cycle. The second data set is derived from experiments performed using HeLa cells. The results show that some interactions can be fully or, at least, partially determined under the Boolean model considered. Conclusions The algorithm proposed can be used as a first step for detection of gene/protein interactions. It is able to infer gene relationships from time-series data of gene expression, and this inference process can be aided by a priori knowledge available.

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The ubiquity of time series data across almost all human endeavors has produced a great interest in time series data mining in the last decade. While dozens of classification algorithms have been applied to time series, recent empirical evidence strongly suggests that simple nearest neighbor classification is exceptionally difficult to beat. The choice of distance measure used by the nearest neighbor algorithm is important, and depends on the invariances required by the domain. For example, motion capture data typically requires invariance to warping, and cardiology data requires invariance to the baseline (the mean value). Similarly, recent work suggests that for time series clustering, the choice of clustering algorithm is much less important than the choice of distance measure used.In this work we make a somewhat surprising claim. There is an invariance that the community seems to have missed, complexity invariance. Intuitively, the problem is that in many domains the different classes may have different complexities, and pairs of complex objects, even those which subjectively may seem very similar to the human eye, tend to be further apart under current distance measures than pairs of simple objects. This fact introduces errors in nearest neighbor classification, where some complex objects may be incorrectly assigned to a simpler class. Similarly, for clustering this effect can introduce errors by “suggesting” to the clustering algorithm that subjectively similar, but complex objects belong in a sparser and larger diameter cluster than is truly warranted.We introduce the first complexity-invariant distance measure for time series, and show that it generally produces significant improvements in classification and clustering accuracy. We further show that this improvement does not compromise efficiency, since we can lower bound the measure and use a modification of triangular inequality, thus making use of most existing indexing and data mining algorithms. We evaluate our ideas with the largest and most comprehensive set of time series mining experiments ever attempted in a single work, and show that complexity-invariant distance measures can produce improvements in classification and clustering in the vast majority of cases.

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Máster en Gestión Sostenible de Recursos Pesqueros

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The aim of the present work is to contribute to a better understanding of the relation between organization theory and management practice. It is organized as a collection of two papers, a theoretical and conceptual contribution and an ethnographic study. The first paper is concerned with systematizing different literatures inside and outside the field of organization studies that deal with the theory-practice relation. After identifying a series of positions to the theory-practice debate and unfolding some of their implicit assumptions and limitations, a new position called entwinement is developed in order to overcome status quo through reconciliation and integration. Accordingly, the paper proposes to reconceptualize theory and practice as a circular iterative process of action and cognition, science and common-sense enacted in the real world both by organization scholars and practitioners according to purposes at hand. The second paper is the ethnographic study of an encounter between two groups of expert academics and practitioners occasioned by a one-year executive business master in an international business school. The research articulates a process view of the knowledge exchange between management academics and practitioners in particular and between individuals belonging to different communities of practice, in general, and emphasizes its dynamic, relational and transformative mechanisms. Findings show that when they are given the chance to interact, academics and practitioners set up local provisional relations that enable them to act as change intermediaries vis-a-vis each other’s worlds, without tying themselves irremediably to each other and to the scenarios they conjointly projected during the master’s experience. Finally, the study shows that provisional relations were accompanied by a recursive shift in knowledge modes. While interacting, academics passed from theory to practical theorizing, practitioners passed from an involved practical mode to a reflexive and quasi-theoretical one, and then, as exchanges proceeded, the other way around.

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The aim of this dissertation is to analyze the adaptation of food realia and food-related terms from English into Italian in the world of screen translation. Food has always been at the heart of every human being’s life and is an essential lens of analysis when trying to understand culture. With the awareness of what has been done in the past in American TV series dubbed into Italian and looking at how translations have been changing in the last decade, my thesis demonstrates how strategies are more inclined to an overt approach, which leaves the audiovisual text deeply tied to its source language and culture. The work will also include a practical subtitling exercise of three episodes of the currently most famous YouTube cooking show: Nerdy Nummies by Rosanna Pansino. The fact that the show is published weekly on a YouTube channel gives me the opportunity to comment on the evolution of media in the third millennium and how this implies an improvement as far as the knowledge, the skills and the possibilities for audiovisual translators are concerned.

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The White Paper is a review of leading scientific knowledge on the role of knowledge management, institutions and economics in monitoring and assessment of land degradation and desertification. It provides key recommendations for more effective policies and actions for combating desertification both withn the UNCCD and beyond. This White Paper is the result of an international collaboration and consultation led jointly by the Association of DesertNet International and the United Nations University - Institute for Water, Environment and Health (UNU-INWEH), of the Dryland Science for Development Consortium (DSD). The findings were presented at the First UNCCD Scientific Conference held during the COP-9 in Buenos Aires, 2009.

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Once administered, a drug can activate the immune system by various mechanisms and lead to a large range of clinical manifestations closely related to the type of immune reaction elicited. Administration of the drug can classically result in an immunoglobulin E (IgE)-type sensitization, but can also result in more complex activation of the immune system potentially resulting in severe syndromes, such as the drug-induced hypersensitivity syndrome (DIHS). Although there has been a major increase in our knowledge over the last years, the exact mechanisms of drug allergy are not well understood for most clinical manifestations. A complex interaction between individual characteristics, environmental factors, and the drug itself is usually responsible for adverse reactions to drugs. In this educational review series, we described three cases of drug allergy: first, a child with a typical IgE-mediated drug allergy, second, a child with a non-immediate reaction to penicillin, and in the third patient, we will discuss the drug-induced hypersensitivity syndrome, which is rare but potentially fatal. These cases are correlated to the immune mechanism potentially involved.

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In 2004, Houston had one of the lowest childhood immunization levels among major metropolitan cities in the United States at 65% for the 4:3:1:3:3 vaccination series. Delays in the receipt of scheduled vaccinations may be related to missed opportunities due to health care provider lack of knowledge about catch-up regimens and contraindications for pediatric vaccination. The objectives of this study are to identify, measure, and report on VFC provider-practice characteristics, knowledge of catch-up regimens and contraindications, and use of Reminder recall (R/R) and moved or gone elsewhere (MOGE) practices among providers with high (>80%) and low (<70%) immunization coverage among 19-35 month old children. The sampling frame consists of 187 Vaccines for Children (VFC) providers with 2004 clinic assessment software application (CASA) scores. Data were collected by personal interview with each participating practice provider. Only ten VFC providers were successful at maximizing vaccinations for every vignette and no provider administered the maximum possible number of vaccinations at visit 2 for all six vignettes. Both coverage groups administered polio conjugate vaccine (PCV), haemophilus influenza type b (Hib), and diphtheria, tetanus and acellular pertussis (DTaP) most frequently and omitted most frequently varicella zoster vaccine (VZV) and measles, mumps, and rubella (MMR) vaccine. ^

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A monitoring programme for microzooplankton was started at the long-term sampling station ''Kabeltonne'' at Helgoland Roads (54°11.30' N; 7°54.00' E) in January 2007 in order to provide more detailed knowledge on microzooplankton occurrence, composition and seasonality patterns at this site and to complement the existing plankton data series. Ciliate and dinoflagellate cell concentration and carbon biomass were recorded on a weekly basis. Heterotrophic dinoflagellates were considerably more important in terms of biomass than ciliates, especially during the summer months. However, in early spring, ciliates were the major group of microzooplankton grazers as they responded more quickly to phytoplankton food availability. Mixotrophic dinoflagellates played a secondary role in terms of biomass when compared to heterotrophic species; nevertheless, they made up an intense late summer bloom in 2007. The photosynthetic ciliate Myrionecta rubra bloomed at the end of the sampling period. Due to its high biomass when compared to crustacean plankton especially during the spring bloom, microzooplankton should be regarded as the more important phytoplankton grazer group at Helgoland Roads. Based on these results, analyses of biotic and abiotic factors driving microzooplankton composition and abundance are necessary for a full understanding of this important component of the plankton.

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Long term global archives of high-moderate spatial resolution, multi-spectral satellite imagery are now readily accessible, but are not being fully utilised by management agencies due to the lack of appropriate methods to consistently produce accurate and timely management ready information. This work developed an object-based remote sensing approach to map land cover and seagrass distribution in an Australian coastal environment for a 38 year Landsat image time-series archive (1972-2010). Landsat Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) imagery were used without in situ field data input (but still using field knowledge) to produce land and seagrass cover maps every year data were available, resulting in over 60 map products over the 38 year archive. Land cover was mapped annually using vegetation, bare ground, urban and agricultural classes. Seagrass distribution was also mapped annually, and in some years monthly, via horizontal projected foliage cover classes, sand and deep water. Land cover products were validated using aerial photography and seagrass maps were validated with field survey data, producing several measures of accuracy. An average overall accuracy of 65% and 80% was reported for seagrass and land cover products respectively, which is consistent with other studies in the area. This study is the first to show moderate spatial resolution, long term annual changes in land cover and seagrass in an Australian environment, created without the use of in situ data; and only one of a few similar studies globally. The land cover products identify several long term trends; such as significant increases in South East Queensland's urban density and extent, vegetation clearing in rural and rural-residential areas, and inter-annual variation in dry vegetation types in western South East Queensland. The seagrass cover products show that there has been a minimal overall change in seagrass extent, but that seagrass cover level distribution is extremely dynamic; evidenced by large scale migrations of higher seagrass cover levels and several sudden and significant changes in cover level. These mapping products will allow management agencies to build a baseline assessment of their resources, understand past changes and help inform implementation and planning of management policy to address potential future changes.

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Expert systems are built from knowledge traditionally elicited from the human expert. It is precisely knowledge elicitation from the expert that is the bottleneck in expert system construction. On the other hand, a data mining system, which automatically extracts knowledge, needs expert guidance on the successive decisions to be made in each of the system phases. In this context, expert knowledge and data mining discovered knowledge can cooperate, maximizing their individual capabilities: data mining discovered knowledge can be used as a complementary source of knowledge for the expert system, whereas expert knowledge can be used to guide the data mining process. This article summarizes different examples of systems where there is cooperation between expert knowledge and data mining discovered knowledge and reports our experience of such cooperation gathered from a medical diagnosis project called Intelligent Interpretation of Isokinetics Data, which we developed. From that experience, a series of lessons were learned throughout project development. Some of these lessons are generally applicable and others pertain exclusively to certain project types.