622 research outputs found

    NAM: Non-Adversarial Unsupervised Domain Mapping

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    Several methods were recently proposed for the task of translating images between domains without prior knowledge in the form of correspondences. The existing methods apply adversarial learning to ensure that the distribution of the mapped source domain is indistinguishable from the target domain, which suffers from known stability issues. In addition, most methods rely heavily on `cycle' relationships between the domains, which enforce a one-to-one mapping. In this work, we introduce an alternative method: Non-Adversarial Mapping (NAM), which separates the task of target domain generative modeling from the cross-domain mapping task. NAM relies on a pre-trained generative model of the target domain, and aligns each source image with an image synthesized from the target domain, while jointly optimizing the domain mapping function. It has several key advantages: higher quality and resolution image translations, simpler and more stable training and reusable target models. Extensive experiments are presented validating the advantages of our method.Comment: ECCV 201

    Attacks by a piercing-sucking insect (Myzus persicae Sultzer) or a chewing insect (Leptinotarsa decemlineata Say) on potato plants (Solanum tuberosum L.) induce differential changes in volatile compound release and oxylipin synthesis

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    Plant defensive strategies bring into play blends of compounds dependent on the type of attacker and coming from different synthesis pathways. Interest in the field is mainly focused on volatile organic compounds (VOCs) and jasmonic acid (JA). By contrast, little is known about the oxidized polyunsaturated fatty acids (PUFAs), such as PUFA-hydroperoxides, PUFA-hydroxides, or PUFA-ketones. PUFA-hydroperoxides and their derivatives might be involved in stress response and show antimicrobial activities. Hydroperoxides are also precursors of JA and some volatile compounds. In this paper, the differential biochemical response of a plant against insects with distinct feeding behaviours is characterized not only in terms of VOC signature and JA profile but also in terms of their precursors synthesized through the lipoxygenase (LOX)-pathway at the early stage of the plant response. For this purpose, two leading pests of potato with distinct feeding behaviours were used: the Colorado Potato Beetle (Leptinotarsa decemlineata Say), a chewing herbivore, and the Green Peach Aphid (Myzus persicae Sulzer), a piercing-sucking insect. The volatile signatures identified clearly differ in function with the feeding behaviour of the attacker and the aphid, which causes the smaller damages, triggers the emission of a higher number of volatiles. In addition, 9-LOX products, which are usually associated with defence against pathogens, were exclusively activated by aphid attack. Furthermore, a correlation between volatiles and JA accumulation and the evolution of their precursors was determined. Finally, the role of the insect itself on the plant response after insect infestation was highlighted

    The study of metaphor as part of Critical Discourse Analysis

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    This article discusses how the study of metaphoric and more generally, figurative language use contributes to critical discourse analysis (CDA). It shows how cognitive linguistsā€™ recognition of metaphor as a fundamental means of concept- and argument-building can add to CDA's account of meaning constitution in the social context. It then discusses discrepancies between the early model of conceptual metaphor theory and empirical data and argues that discursive-pragmatic factors as well as sociolinguistic variation have to be taken into account in order to make cognitive analyses more empirically and socially relevant. In conclusion, we sketch a modified cognitive approach informed by Relevance Theory within CDA

    Using conceptual metaphor and functional grammar to explore how language used in physics affects student learning

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    This paper introduces a theory about the role of language in learning physics. The theory is developed in the context of physics students' and physicists' talking and writing about the subject of quantum mechanics. We found that physicists' language encodes different varieties of analogical models through the use of grammar and conceptual metaphor. We hypothesize that students categorize concepts into ontological categories based on the grammatical structure of physicists' language. We also hypothesize that students over-extend and misapply conceptual metaphors in physicists' speech and writing. Using our theory, we will show how, in some cases, we can explain student difficulties in quantum mechanics as difficulties with language.Comment: Accepted for publication in Phys. Rev. ST:PE
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