997 resultados para Particular dictionary


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This article argues for the distinctiveness of the presentation of crowds in the Old English version of the Legend of the Seven Sleepers . In traditional Old English poetry, crowds are mostly conspicuous by their absence, since the social groupings portrayed are typically those ofthe lord's retinue and the fellowship of the hall. In writings deriving from Latin traditions (in Anglo-Latin, Old English prose and strands of Old English poetry) such as historiography andhagiography, crowds are presented in highly conventional terms based on literary models. The crowd scenes in the Legend of the Seven Sleepers , on the other hand, have an immediacy and urgency that seem based on real-life experience of Anglo-Saxon England rather than simply imitative of the work's Latin (ultimately Greek) source or of other literary models. Drawing upon crowd theory and historical studies, the article demonstrates that the crowds in this text are presented in “domesticated” Anglo-Saxon terms and may be seen as reflective of growing urbanization in late Anglo-Saxon England. “Real” crowds are glimpsed elsewhere in Anglo-Saxon literature but in the Legend of the Seven Sleepers they are particularly foregrounded; this text also presents the literature's liveliest picture of town life more generally.

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Helminth parasites (nematodes, flatworms and cestodes) infect over 1 billion of the world's population causing high morbidity and mortality. The large tissue-dwelling worms express papain-like cysteine peptidases, termed cathepsins that play important roles in virulence including host entry, tissue migration and the suppression of host immune responses. Much of our knowledge of helminth cathepsins comes from studies using flatworms or trematode (fluke) parasites. The developmentally-regulated expression of these proteases correlates with the passage of parasites through host tissues and their encounters with different host macromolecules. Recent phylogenetic, biochemical and structural studies indicate that trematode cathepsins exhibit overlapping but distinct substrate specificities due to divergence within the protease active site. Here we provide an overview of the evolution, biochemistry and structure of these important enzymes and highlight how recent advances in proteomics and gene silencing techniques are allowing researchers to probe their biological functions. We focus mainly on members of the cathepsin L gene family of the animal and human pathogen, Fasciola hepatica, because of our deep understanding of their function, biochemistry and structure.

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Zoonotic infections are among the most common on earth and are responsible for >60 per cent of all human infectious diseases. Some of the most important and well-known human zoonoses are caused by worm or helminth parasites, including species of nematodes (trichinellosis), cestodes (cysticercosis, echinococcosis) and trematodes (schistosomiasis). However, along with social, epidemiological and environmental changes, together with improvements in our ability to diagnose helminth infections, several neglected parasite species are now fast-becoming recognized as important zoonotic diseases of humans, e.g. anasakiasis, several fish-borne trematodiasis and fasciolosis. In the present review, we discuss the current disease status of these primary helminth zoonotic infections with particular emphasis on their diagnosis and control. Advances in molecular biology, proteomics and the release of helminth genome-sequencing project data are revolutionizing parasitology research. The use of these powerful experimental approaches, and their potential benefits to helminth biology are also discussed in relation to the future control of helminth infections of animals and humans.

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It presents questions that have arisen as a result of more than 20 years of collecting the data for the Bach Bibliography. Taking editions of The Well-Tempered Clavier as an example and using figures and graphs extracted from the Bach Bibliography, Tomita explores the various facets of the work's reception including its market appeal, the ambitions that steered its editors and publishers, and trends in its interpretation.

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Despite concern about the harmful effects of substances contained in various
plastic consumer products, little attention has focused on the more heavily
exposed women working in the plastics industry. Through a review of the
toxicology, industrial hygiene, and epidemiology literatures in conjunction
with qualitative research, this article explores occupational exposures in producing
plastics and health risks to workers, particularly women, who make up
a large part of the workforce. The review demonstrates that workers are
exposed to chemicals that have been identified as mammary carcinogens and
endocrine disrupting chemicals, and that the work environment is heavily
contaminated with dust and fumes. Consequently, plastics workers have a
body burden that far exceeds that found in the general public.

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In this study, we introduce an original distance definition for graphs, called the Markov-inverse-F measure (MiF). This measure enables the integration of classical graph theory indices with new knowledge pertaining to structural feature extraction from semantic networks. MiF improves the conventional Jaccard and/or Simpson indices, and reconciles both the geodesic information (random walk) and co-occurrence adjustment (degree balance and distribution). We measure the effectiveness of graph-based coefficients through the application of linguistic graph information for a neural activity recorded during conceptual processing in the human brain. Specifically, the MiF distance is computed between each of the nouns used in a previous neural experiment and each of the in-between words in a subgraph derived from the Edinburgh Word Association Thesaurus of English. From the MiF-based information matrix, a machine learning model can accurately obtain a scalar parameter that specifies the degree to which each voxel in (the MRI image of) the brain is activated by each word or each principal component of the intermediate semantic features. Furthermore, correlating the voxel information with the MiF-based principal components, a new computational neurolinguistics model with a network connectivity paradigm is created. This allows two dimensions of context space to be incorporated with both semantic and neural distributional representations.

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Dissertação, Mestrado, Contabilidade e Finanças, Instituto Politécnico de Santarém, Escola Superior de Gestão e Tecnologia, 2014