769 resultados para 380305 Knowledge Representation and Machine Learning
Resumo:
We study a general static noisy rational expectations model where investors have private information about asset payoffs, with common and private components, and about their own exposure to an aggregate risk factor, and derive conditions for existence and uniqueness (or multiplicity) of equilibria. We find that a main driver of the characterization of equilibria is whether the actions of investors are strategic substitutes or complements. This latter property in turn is driven by the strength of a private learning channel from prices, arising from the multidimensional sources of asymmetric information, in relation to the usual public learning channel. When the private learning channel is strong (weak) in relation to the public we have strong (weak) strategic complementarity in actions and potentially multiple (unique) equilibria. The results enable a precise characterization of whether information acquisition decisions are strategic substitutes or complements. We find that the strategic substitutability in information acquisition result obtained in Grossman and Stiglitz (1980) is robust. JEL Classification: D82, D83, G14 Keywords: Rational expectations equilibrium, asymmetric information, risk exposure, hedging, supply information, information acquisition.
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Species distribution models (SDMs) are widely used to explain and predict species ranges and environmental niches. They are most commonly constructed by inferring species' occurrence-environment relationships using statistical and machine-learning methods. The variety of methods that can be used to construct SDMs (e.g. generalized linear/additive models, tree-based models, maximum entropy, etc.), and the variety of ways that such models can be implemented, permits substantial flexibility in SDM complexity. Building models with an appropriate amount of complexity for the study objectives is critical for robust inference. We characterize complexity as the shape of the inferred occurrence-environment relationships and the number of parameters used to describe them, and search for insights into whether additional complexity is informative or superfluous. By building 'under fit' models, having insufficient flexibility to describe observed occurrence-environment relationships, we risk misunderstanding the factors shaping species distributions. By building 'over fit' models, with excessive flexibility, we risk inadvertently ascribing pattern to noise or building opaque models. However, model selection can be challenging, especially when comparing models constructed under different modeling approaches. Here we argue for a more pragmatic approach: researchers should constrain the complexity of their models based on study objective, attributes of the data, and an understanding of how these interact with the underlying biological processes. We discuss guidelines for balancing under fitting with over fitting and consequently how complexity affects decisions made during model building. Although some generalities are possible, our discussion reflects differences in opinions that favor simpler versus more complex models. We conclude that combining insights from both simple and complex SDM building approaches best advances our knowledge of current and future species ranges.
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Ultrasound segmentation is a challenging problem due to the inherent speckle and some artifacts like shadows, attenuation and signal dropout. Existing methods need to include strong priors like shape priors or analytical intensity models to succeed in the segmentation. However, such priors tend to limit these methods to a specific target or imaging settings, and they are not always applicable to pathological cases. This work introduces a semi-supervised segmentation framework for ultrasound imaging that alleviates the limitation of fully automatic segmentation, that is, it is applicable to any kind of target and imaging settings. Our methodology uses a graph of image patches to represent the ultrasound image and user-assisted initialization with labels, which acts as soft priors. The segmentation problem is formulated as a continuous minimum cut problem and solved with an efficient optimization algorithm. We validate our segmentation framework on clinical ultrasound imaging (prostate, fetus, and tumors of the liver and eye). We obtain high similarity agreement with the ground truth provided by medical expert delineations in all applications (94% DICE values in average) and the proposed algorithm performs favorably with the literature.
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A population-based telephone survey conducted in 2002 estimated that there were 3.2 million episodes of acute gastroenteritis on the island of Ireland each year (Scallon et al., 2004). It is often very dif ficult to definitively identify the source of illness. However, of the respondents in that study suspecting food as the reason for their illness, 74% blamed food consumed from commercial premises such as restaurants, cafés, takeaways, canteens and pubs. Within the food services industry, statistics show a significant level of prosecutions, prohibition and closure orders of restaurants for food hygiene offences. The Food Safety Authority of Ireland has identified the main contributory factors to foodborne infections to be: cross-contamination, inadequate cooking, inadequate storage, inadequate reheating, delayed serving and infected food handlers (FSAI, 2000). Development of appropriate training and education campaigns to target problem areas requires initial understanding of the current level of food safety knowledge and practices in the food services industry.
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The Kilkenny post-primary school survey was carried out in the spring of 1987 on a stratified random sample of 445 post-primary school children in county Kilkenny. The study was designed as the basis for evaluation of the Kilkenny Health Project's school health education programme. The study examined knowledge, attitudes and behaviour relevant to non-communicable disease. The results showed that levels of adolescent alcohol and tobacco use were similar to those found in neighbouring countries. Smoking and drinking increased during adolescence and were more prevalent in males. Physical activity decreased throughout adolescence and a high intake of 'snack' foods was found. Health related knowledge levels were high but were not related to behaviour; however attitudes were found to be consistent with behaviour. These and other results are discussed. Literature relevant to school health education and the aetiology of non-communicable disease is described, with particular reference to Ireland. The evidence supporting health promotion intervention programmes against non-communicable disease is examined and WHO and Irish policies on health promotion outlined. The importance of health and disease prevention programmes commencing in youth is emphasised and the suitability and efficacy of school health education programmes are noted. A number of school health education programmes world-wide are described. The role of the community physician in relation to such programmes is discussed. Finally recommendations are made and areas for further research are made.This resource was contributed by The National Documentation Centre on Drug Use.
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Literacy and Numeracy for Learning and Life is the national strategy to improve literacy and numeracy standards among children and young people in the education system. This strategy seeks to address significant concerns about how well our young people are developing the literacy and numeracy skills that they will need to participate fully in the education system, to live satisfying and rewarding lives, and to participate as active and informed citizens in our society.
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In July 2011 the Minister for education launched Literacy and Numeracy for Learning and Life – the national strategy to improve literacy and numeracy among children and young people. The strategy was developed following an extensive consultation process and contributions from individuals, schools, groups and organisations. This leaflet gives a flavour of the key parts of the Strategy with access to the full document on the Department’s website.
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The main objective of this ex post facto study is to compare the differencesin cognitive functions and their relation to schizotypal personality traits between agroup of unaffected parents of schizophrenic patients and a control group. A total of 52unaffected biological parents of schizophrenic patients and 52 unaffected parents ofunaffected subjects were assessed in measures of attention (Continuous PerformanceTest- Identical Pairs Version, CPT-IP), memory and verbal learning (California VerbalLearning Test, CVLT) as well as schizotypal personality traits (Oxford-Liverpool Inventoryof Feelings and Experiences, O-LIFE). The parents of the patients with schizophreniadiffer from the parents of the control group in omission errors on the ContinuousPerformance Test- Identical Pairs, on a measure of recall and on two contrast measuresof the California Verbal Learning Test. The associations between neuropsychologicalvariables and schizotpyal traits are of a low magnitude. There is no defined pattern ofthe relationship between cognitive measures and schizotypal traits
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This file contains the ontology of patterns of educational settings, as part of the formal framework for specifying, reusing and implementing educational settings. Furthermore, it includes the set of rules that extend the ontology of educational scenarios as well as a brief description of the level of patters of such ontological framework.
Resumo:
The pituitary adenylate cyclase activating polypeptide (PACAP) type I receptor (PAC1) is a G-protein-coupled receptor binding the strongly conserved neuropeptide PACAP with 1000-fold higher affinity than the related peptide vasoactive intestinal peptide. PAC1-mediated signaling has been implicated in neuronal differentiation and synaptic plasticity. To gain further insight into the biological significance of PAC1-mediated signaling in vivo, we generated two different mutant mouse strains, harboring either a complete or a forebrain-specific inactivation of PAC1. Mutants from both strains show a deficit in contextual fear conditioning, a hippocampus-dependent associative learning paradigm. In sharp contrast, amygdala-dependent cued fear conditioning remains intact. Interestingly, no deficits in other hippocampus-dependent tasks modeling declarative learning such as the Morris water maze or the social transmission of food preference are observed. At the cellular level, the deficit in hippocampus-dependent associative learning is accompanied by an impairment of mossy fiber long-term potentiation (LTP). Because the hippocampal expression of PAC1 is restricted to mossy fiber terminals, we conclude that presynaptic PAC1-mediated signaling at the mossy fiber synapse is involved in both LTP and hippocampus-dependent associative learning.
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Although both are fundamental terms in the humanities and social sciences, discourse and knowledge have seldom been explicitly related, and even less so in critical discourse studies. After a brief summary of what we know about these relationships in linguistics, psychology, epistemology and the social sciences, with special emphasis on the role of knowledge in the formation of mental models as a basis for discourse, I examine in more detail how a critical study of discourse and knowledge may be articulated in critical discourse studies. Thus, several areas of critical epistemic discourse analysis are identified, and then applied in a study of Tony Blair’s Iraq speech on March 18, 2003, in which he sought to legitimatize his decision to go to war in Iraq with George Bush. The analysis shows the various modes of how knowledge is managed and manipulated of all levels of discourse of this speech.
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In this paper we study the relevance of multiple kernel learning (MKL) for the automatic selection of time series inputs. Recently, MKL has gained great attention in the machine learning community due to its flexibility in modelling complex patterns and performing feature selection. In general, MKL constructs the kernel as a weighted linear combination of basis kernels, exploiting different sources of information. An efficient algorithm wrapping a Support Vector Regression model for optimizing the MKL weights, named SimpleMKL, is used for the analysis. In this sense, MKL performs feature selection by discarding inputs/kernels with low or null weights. The approach proposed is tested with simulated linear and nonlinear time series (AutoRegressive, Henon and Lorenz series).
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OBJECTIVE Assessing the adequacy of knowledge, attitude and practice of women regarding male and female condoms as STI/HIV preventive measures. METHOD An evaluative Knowledge, Attitude and Practice (KAP) household survey with a quantitative approach, involving 300 women. Data collection took place between June and August 2013, in an informal urban settlement within the municipality of João Pessoa, Paraiba, Northeast Brazil. RESULTS Regarding the male condom, most women showed inadequate knowledge and practice, and an adequate attitude. Regarding the female condom, knowledge, attitude and practice variables were unsatisfactory. Significant associations between knowledge/religious orientation and attitude/education regarding the male condom were observed. CONCLUSION A multidisciplinary team should be committed to the development of educational practices as care promotion tools in order to improve adherence of condom use.