864 resultados para Precondition event


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The Ría de Vigo is a bay strongly influenced by upwelling-downwelling cycles along the adjacent coast of NW Iberia. Moored and ship-board observations during September 2006 showed that subduction, initially associated with an estuarine circulation, strengthened when a strong downwelling circulation, resulting from northward wind over the coastal ocean, was generated in the outer ría causing ambient waters to be advected outward in the lower layer. Incoming surface waters confined the estuarine circulation to the shallow interior and displaced isopleths downward through the water column at ∼10 m d−1. As the estuarine circulation retreated inward, strong flow convergence developed between middle and inner ria in the layer above 15 m, while divergence developed beneath. The convergence increased through the period of downwelling-favorable wind at a rate consistent with the observed isopleth displacement velocities. The coefficient of turbulent diffusion Kt, from a microstructure profiler, indicated that mixing was strong in the estuarine circulation and subsequently in the downwelling zone, where localized instabilities and temperature-salinity inversions were observed. During the downwelling, concentrations of phytoplankton, including potentially harmful species, increased, especially in the middle and inner ria, as a result of inward advection, subduction and the ability of the dinoflagellates to maintain their position in the water column by swimming. In the course of the 5 day event, the water mass of all but the innermost ría was flushed completely and replaced by waters originating in the coastally-trapped poleward flow along the Atlantic coastline.

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The Ría de Vigo is a bay strongly influenced by upwelling-downwelling cycles along the adjacent coast of NW Iberia. Moored and ship-board observations during September 2006 showed that subduction, initially associated with an estuarine circulation, strengthened when a strong downwelling circulation, resulting from northward wind over the coastal ocean, was generated in the outer ría causing ambient waters to be advected outward in the lower layer. Incoming surface waters confined the estuarine circulation to the shallow interior and displaced isopleths downward through the water column at ∼10 m d−1. As the estuarine circulation retreated inward, strong flow convergence developed between middle and inner ria in the layer above 15 m, while divergence developed beneath. The convergence increased through the period of downwelling-favorable wind at a rate consistent with the observed isopleth displacement velocities. The coefficient of turbulent diffusion Kt, from a microstructure profiler, indicated that mixing was strong in the estuarine circulation and subsequently in the downwelling zone, where localized instabilities and temperature-salinity inversions were observed. During the downwelling, concentrations of phytoplankton, including potentially harmful species, increased, especially in the middle and inner ria, as a result of inward advection, subduction and the ability of the dinoflagellates to maintain their position in the water column by swimming. In the course of the 5 day event, the water mass of all but the innermost ría was flushed completely and replaced by waters originating in the coastally-trapped poleward flow along the Atlantic coastline.

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The mechanisms involved in the progression from monoclonal gammopathy of undetermined significance (MGUS) and smoldering myeloma (SMM) to malignant multiple myeloma (MM) and plasma cell leukemia (PCL) are poorly understood but believed to involve the sequential acquisition of genetic hits. We performed exome and whole-genome sequencing on a series of MGUS (n=4), high-risk (HR)SMM (n=4), MM (n=26) and PCL (n=2) samples, including four cases who transformed from HR-SMM to MM, to determine the genetic factors that drive progression of disease. The pattern and number of non-synonymous mutations show that the MGUS disease stage is less genetically complex than MM, and HR-SMM is similar to presenting MM. Intraclonal heterogeneity is present at all stages and using cases of HR-SMM, which transformed to MM, we show that intraclonal heterogeneity is a typical feature of the disease. At the HR-SMM stage of disease, the majority of the genetic changes necessary to give rise to MM are already present. These data suggest that clonal progression is the key feature of transformation of HR-SMM to MM and as such the invasive clinically predominant clone typical of MM is already present at the SMM stage and would be amenable to therapeutic intervention at that stage.

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This expert review provides a detailed review of the academic evidence on how EU membership has influenced UK policies, systems of decision making and environmental quality. Containing 14 chapters and over 60,000 words, it documents how the EU has affected UK environmental policy and how, in turn, the UK has worked through the EU to shape wider, international thinking. It has been authored by 14 international experts, who have drawn on the findings of over 700 publications to offer an impartial and authoritative assessment of the evidence.

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The current thesis examines memory bias for state anxiety prior to academic achievement situations like writing an exam and giving a speech. The thesis relies on the reconstruction principle, which assumes that memories for past emotions are reconstructed rather than stored permanently and accurately. This makes them prone to memory bias, which is af-fected by several influencing factors. A major aim is to include four important influencing factors simultaneously. Early research on mood and emotional autobiographical memory found evidence for the existence of a propositional associative network (Bower, 1981; Col-lins & Loftus, 1975), leading to mood congruent recall. But empirical findings gave also strong evidence for the existence of mood incongruent recall for one’s own emotions, which was for example linked to mood regulation via mood repair (e.g. Clark & Isen, 1982), which seems to be associated to the personality traits extraversion and neuroticism (Lischetzke & Eid, 2006; Ng & Diener, 2009). Moreover, neuroticism and trait anxiety are related to rumination, which is seen as negative post-event-processing (e.g. Wells & Clark, 1997). Overall, the elapsed time since the emotional event happened should have an impact on recall of emotions. Following the affect infusion model by Robinson and Clore (2002a), the influence of personality on memory bias should increase over time. Therefore, three longitudinal studies were realized, using naturally occurring as well as laboratory settings. The used paradigm was equivalent in all studies. Subjects were asked about their actual state anxiety prior to an academic achievement situation. Directly after the situation, cur-rent mood and recall of former anxiety were assessed. The same procedure was repeated a few weeks later. Personality traits and post-event-processing were also assessed. The results suggest a need to have a differentiated view on predicting memory bias. Study 1 (N = 131) as well as study 3 (N = 53) found evidence for mood incongruent memory in the sense of mood repair and downward regulation as a function of personality. Rumination was found to cause stable overestimation of pre-event anxiety in study 2 (N = 141) as well as in study 3. Although the relevance of the influencing factors changed over time, an increasing relevance of personality could not consistently be observed. The tremendously different effects of the laboratory study 2 indicated that such settings are not appropriate to study current issues. Theoretical and psychotherapeutically relevant conclusions are drawn and several limitations are discussed.

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Thesis (Ph.D.)--University of Washington, 2016-08

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Heterogeneity has to be taken into account when integrating a set of existing information sources into a distributed information system that are nowadays often based on Service- Oriented Architectures (SOA). This is also particularly applicable to distributed services such as event monitoring, which are useful in the context of Event Driven Architectures (EDA) and Complex Event Processing (CEP). Web services deal with this heterogeneity at a technical level, also providing little support for event processing. Our central thesis is that such a fully generic solution cannot provide complete support for event monitoring; instead, source specific semantics such as certain event types or support for certain event monitoring techniques have to be taken into account. Our core result is the design of a configurable event monitoring (Web) service that allows us to trade genericity for the exploitation of source specific characteristics. It thus delivers results for the areas of SOA, Web services, CEP and EDA.

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This article discusses event monitoring options for heterogeneous event sources as they are given in nowadays heterogeneous distributed information systems. It follows the central assumption, that a fully generic event monitoring solution cannot provide complete support for event monitoring; instead, event source specific semantics such as certain event types or support for certain event monitoring techniques have to be taken into account. Following from this, the core result of the work presented here is the extension of a configurable event monitoring (Web) service for a variety of event sources. A service approach allows us to trade genericity for the exploitation of source specific characteristics. It thus delivers results for the areas of SOA, Web services, CEP and EDA.

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In this paper, five ontologies are described, which include the event concepts. The paper provides an overview and comparison of existing event models. The main criteria for comparison are that there should be possibilities to model events with stretch in the time and location and participation of objects; however, there are other factors that should be taken into account as well. The paper also shows an example of using ontologies in complex event processing.

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The effects of spatial attention and part-whole configuration on recognition of repeated objects were investigated with behavioral and event-related potential (ERP) measures. Short-term repetition effects were measured for probe objects as a function of whether a preceding prime object was shown as an intact image or coarsely scrambled (split into two halves) and whether or not it had been attended during the prime display. In line with previous behavioral experiments, priming effects were observed from both intact and split primes for attended objects, but only from intact (repeated same-view) objects when they were unattended. These behavioral results were reflected in ERP waveforms at occipital-temporal locations as more negative-going deflections for repeated items in the time window between 220 and 300 ms after probe onset (N250r). Attended intact images showed generally more enhanced repetition effects than split ones. Unattended images showed repetition effects only when presented in an intact configuration, and this finding was limited to the right-hemisphere electrodes. Repetition effects in earlier (before 200 ms) time-windows were limited to attended conditions at occipito-temporal sites (N1), a component linked to the encoding of object structure, while repetition effects at central locations during the same time window (P150) were found only from objects repeated in the same intact configuration—both previously attended and unattended probe objects. The data indicate that view-generalization is mediated by a combination of analytic (part-based) representations and automatic view-dependent representations.

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The overwhelming amount and unprecedented speed of publication in the biomedical domain make it difficult for life science researchers to acquire and maintain a broad view of the field and gather all information that would be relevant for their research. As a response to this problem, the BioNLP (Biomedical Natural Language Processing) community of researches has emerged and strives to assist life science researchers by developing modern natural language processing (NLP), information extraction (IE) and information retrieval (IR) methods that can be applied at large-scale, to scan the whole publicly available biomedical literature and extract and aggregate the information found within, while automatically normalizing the variability of natural language statements. Among different tasks, biomedical event extraction has received much attention within BioNLP community recently. Biomedical event extraction constitutes the identification of biological processes and interactions described in biomedical literature, and their representation as a set of recursive event structures. The 2009–2013 series of BioNLP Shared Tasks on Event Extraction have given raise to a number of event extraction systems, several of which have been applied at a large scale (the full set of PubMed abstracts and PubMed Central Open Access full text articles), leading to creation of massive biomedical event databases, each of which containing millions of events. Sinece top-ranking event extraction systems are based on machine-learning approach and are trained on the narrow-domain, carefully selected Shared Task training data, their performance drops when being faced with the topically highly varied PubMed and PubMed Central documents. Specifically, false-positive predictions by these systems lead to generation of incorrect biomolecular events which are spotted by the end-users. This thesis proposes a novel post-processing approach, utilizing a combination of supervised and unsupervised learning techniques, that can automatically identify and filter out a considerable proportion of incorrect events from large-scale event databases, thus increasing the general credibility of those databases. The second part of this thesis is dedicated to a system we developed for hypothesis generation from large-scale event databases, which is able to discover novel biomolecular interactions among genes/gene-products. We cast the hypothesis generation problem as a supervised network topology prediction, i.e predicting new edges in the network, as well as types and directions for these edges, utilizing a set of features that can be extracted from large biomedical event networks. Routine machine learning evaluation results, as well as manual evaluation results suggest that the problem is indeed learnable. This work won the Best Paper Award in The 5th International Symposium on Languages in Biology and Medicine (LBM 2013).