981 resultados para Trophic web structure


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Cette étude s’encadre dans le projet Language Toolkit, qui dérive de la collaboration entre la Chambre de Commerce de Forlì-Cesena et la Scuola di Lingue e Letterature, Traduzione e Interpretazione de Forlì. L’objectif du projet est de permettre aux étudiants de dernière année de faculté de connaître l’univers des entreprises. Grâce à la collaboration avec APA-CT srl de Forlì, leader dans le secteur de la phytothérapie vétérinaire, et spécialisée dans la production de compléments alimentaires naturels destinés aux animaux, on a réalisé la localisation en français du site web GreenVet. Cette dissertation se compose de quatre chapitres. Le premier chapitre offre une présentation de APA-CT srl et de ses produits. De plus, on définit les détails du projet de localisation du site web GreenVet. Dans le deuxième chapitre on propose, en premier lieu, une réflexion sur les langues spéciales et sur la terminologie scientifique. En deuxième lieu, on aborde, aussi bien du point de vue théorique que du point de vue pratique (à travers des exemples), les caractéristiques de la terminologie de la phytothérapie vétérinaire. En troisième lieu, on explique la méthodologie de travail adoptée pendant la réalisation du projet de localisation, qui a été divisé en deux sous-phases : d’abord, on a effectué une recherche terminologique pour délimiter le domaine en question et, après, on a crée des ressources (corpus, glossaire) utiles pour la traduction. Le troisième chapitre offre une réflexion à propos de la localisation des sites web. Ensuite, on propose une analyse contrastive entre les sites web italiens et français traitant de la phytothérapie vétérinaire. Finalement, le quatrième chapitre est dédié à l’activité pratique de localisation. On a analysé le texte de départ au niveau de la structure, des aspects linguistiques et on a individué les difficultés de traduction. Après, on explique la méthodologie de travail suivie et les stratégies adoptées pendant la traduction.

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Biodiversity is rapidly declining, and this may negatively affect ecosystem processes, including economically important ecosystem services. Previous studies have shown that biodiversity has positive effects on organisms and processes across trophic levels. However, only a few studies have so far incorporated an explicit food-web perspective. In an eight-year biodiversity experiment, we studied an unprecedented range of above- and below-ground organisms and multitrophic interactions. A multitrophic data set originating from a single long-term experiment allows mechanistic insights that would not be gained from meta-analysis of different experiments. Here we show that plant diversity effects dampen with increasing trophic level and degree of omnivory. This was true both for abundance and species richness of organisms. Furthermore, we present comprehensive above-ground/below-ground biodiversity food webs. Both above ground and below ground, herbivores responded more strongly to changes in plant diversity than did carnivores or omnivores. Density and richness of carnivorous taxa was independent of vegetation structure. Below-ground responses to plant diversity were consistently weaker than above-ground responses. Responses to increasing plant diversity were generally positive, but were negative for biological invasion, pathogen infestation and hyperparasitism. Our results suggest that plant diversity has strong bottom-up effects on multitrophic interaction networks, with particularly strong effects on lower trophic levels. Effects on higher trophic levels are indirectly mediated through bottom-up trophic cascades.

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Chondrostoma nasus is a cyprinid fish with highly specialized, ecologically and geographically distinct, ontogenetic trophic niches. Nase population numbers across their Swiss range have shown massive declines and many localized extinctions. Here we integrate data from different genetic markers with phenotypic and demographic data to survey patterns of neutral and adaptive genetic diversity in all extant (and one extinct) Swiss nase populations, with the aim to delineate intraspecific conservation units (CUs) and to inform future population management strategies. We discovered two major genetically and geographically distinct population groupings. The first population grouping comprises nase inhabiting rivers flowing into Lake Constance; the second comprises nase populations from Rhine drainages below Lake Constance. Within these clusters there is generally limited genetic differentiation among populations. Genomic outlier scans based on 256–377 polymorphic AFLP loci revealed little evidence of local adaptation both within and among population clusters, with the exception of one candidate locus identified in scans involving the inbred Schanzengraben population. However, significant phenotypic differentiation in body shape between certain populations suggests a need for more intensive future studies of local adaptation. Our data strongly suggests that the two major population groups should be treated as distinct CUs, with any supplemental stocking and reintroductions sourced only from within the range of the CU concerned.

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BACKGROUND The majority of radiological reports are lacking a standard structure. Even within a specialized area of radiology, each report has its individual structure with regards to details and order, often containing too much of non-relevant information the referring physician is not interested in. For gathering relevant clinical key parameters in an efficient way or to support long-term therapy monitoring, structured reporting might be advantageous. OBJECTIVE Despite of new technologies in medical information systems, medical reporting is still not dynamic. To improve the quality of communication in radiology reports, a new structured reporting system was developed for abdominal aortic aneurysms (AAA), intended to enhance professional communication by providing the pertinent clinical information in a predefined standard. METHODS Actual state analysis was performed within the departments of radiology and vascular surgery by developing a Technology Acceptance Model. The SWOT (strengths, weaknesses, opportunities, and threats) analysis focused on optimization of the radiology reporting of patients with AAA. Definition of clinical parameters was achieved by interviewing experienced clinicians in radiology and vascular surgery. For evaluation, a focus group (4 radiologists) looked at the reports of 16 patients. The usability and reliability of the method was validated in a real-world test environment in the field of radiology. RESULTS A Web-based application for radiological "structured reporting" (SR) was successfully standardized for AAA. Its organization comprises three main categories: characteristics of pathology and adjacent anatomy, measurements, and additional findings. Using different graphical widgets (eg, drop-down menus) in each category facilitate predefined data entries. Measurement parameters shown in a diagram can be defined for clinical monitoring and be adducted for quick adjudications. Figures for optional use to guide and standardize the reporting are embedded. Analysis of variance shows decreased average time required with SR to obtain a radiological report compared to free-text reporting (P=.0001). Questionnaire responses confirm a high acceptance rate by the user. CONCLUSIONS The new SR system may support efficient radiological reporting for initial diagnosis and follow-up for AAA. Perceived advantages of our SR platform are ease of use, which may lead to more accurate decision support. The new system is open to communicate not only with clinical partners but also with Radiology Information and Hospital Information Systems.

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A basin-wide interdecadal change in both the physical state and the ecology of the North Pacific occurred near the end of 1976. Here we use a physical-ecosystem model to examine whether changes in the physical environment associated with the 1976-1977 transition influenced the lower trophic levels of the food web and if so by what means. The physical component is an ocean general circulation model, while the biological component contains 10 compartments: two phytoplankton, two zooplankton, two detritus pools, nitrate, ammonium, silicate, and carbon dioxide. The model is forced with observed atmospheric fields during 1960-1999. During spring, there is a similar to 40% reduction in plankton biomass in all four plankton groups during 1977-1988 relative to 1970-1976 in the central Gulf of Alaska (GOA). The epoch difference in plankton appears to be controlled by the mixed layer depth. Enhanced Ekman pumping after 1976 caused the halocline to shoal, and thus the mixed layer depth, which extends to the top of the halocline in late winter, did not penetrate as deep in the central GOA. As a result, more phytoplankton remained in the euphotic zone, and phytoplankton biomass began to increase earlier in the year after the 1976 transition. Zooplankton biomass also increased, but then grazing pressure led to a strong decrease in phytoplankton by April followed by a drop in zooplankton by May: Essentially, the mean seasonal cycle of plankton biomass was shifted earlier in the year. As the seasonal cycle progressed, the difference in plankton concentrations between epochs reversed sign again, leading to slightly greater zooplankton biomass during summer in the later epoch.

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Background The RCSB Protein Data Bank (PDB) provides public access to experimentally determined 3D-structures of biological macromolecules (proteins, peptides and nucleic acids). While various tools are available to explore the PDB, options to access the global structural diversity of the entire PDB and to perceive relationships between PDB structures remain very limited. Methods A 136-dimensional atom pair 3D-fingerprint for proteins (3DP) counting categorized atom pairs at increasing through-space distances was designed to represent the molecular shape of PDB-entries. Nearest neighbor searches examples were reported exemplifying the ability of 3DP-similarity to identify closely related biomolecules from small peptides to enzyme and large multiprotein complexes such as virus particles. The principle component analysis was used to obtain the visualization of PDB in 3DP-space. Results The 3DP property space groups proteins and protein assemblies according to their 3D-shape similarity, yet shows exquisite ability to distinguish between closely related structures. An interactive website called PDB-Explorer is presented featuring a color-coded interactive map of PDB in 3DP-space. Each pixel of the map contains one or more PDB-entries which are directly visualized as ribbon diagrams when the pixel is selected. The PDB-Explorer website allows performing 3DP-nearest neighbor searches of any PDB-entry or of any structure uploaded as protein-type PDB file. All functionalities on the website are implemented in JavaScript in a platform-independent manner and draw data from a server that is updated daily with the latest PDB additions, ensuring complete and up-to-date coverage. The essentially instantaneous 3DP-similarity search with the PDB-Explorer provides results comparable to those of much slower 3D-alignment algorithms, and automatically clusters proteins from the same superfamilies in tight groups. Conclusion A chemical space classification of PDB based on molecular shape was obtained using a new atom-pair 3D-fingerprint for proteins and implemented in a web-based database exploration tool comprising an interactive color-coded map of the PDB chemical space and a nearest neighbor search tool. The PDB-Explorer website is freely available at www.​cheminfo.​org/​pdbexplorer and represents an unprecedented opportunity to interactively visualize and explore the structural diversity of the PDB.

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En esta tesis se trabaja sobre la hipótesis de que el componente didáctico del discurso divulgativo queda delimitado por estrategias discursivas originadas en el tratamiento modal y actualizadas en los niveles funcional, situacional, semántico y formal-gramatical. El objetivo es caracterizar tales estrategias para identificar tendencias en la realización lingüísticodiscursiva del componente didáctico. El corpus se ha formado teniendo en cuenta soporte (web), formato (hipertexto) y dominio disciplinar (Análisis Sensorial de Vinos). La metodología es, fundamentalmente, cualitativo-ejemplar, basada en el modelo multinivel propuesto por Ciapuscio (2003) para el análisis de textos especializados. Los resultados sugieren que en el nivel funcional, el componente didáctico se distingue por el predominio de los términos positivos de las categorías modales epistémica (función informar) y ética (función dirigir); en el nivel situacional, por tres tipos de construcciones discursivas: la del enunciador experto, la del enunciatario lego y la de la pertenencia del lego a la comunidad especializada; en el nivel semántico, por la estandarización de partes textuales y por el predominio tanto de axiologización eufórica ética y cognoscitiva, como de secuencias expositivas y de procedimientos explicativos causales, descriptivos e ilustrativos; en el nivel formal, por recursos paratextuales e hipertextuales que refuerzan la actualización del componente didáctico.

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The structure and variability of pelagic food webs along the north and northwestern shelf of the Iberian Peninsula were analysed using natural abundance of nitrogen stable isotopes of plankton and pelagic consumers. Plankton composition was mainly studied in size-fractionated samples, but also the isotopic signatures of three copepod species, as representative of primary consumers, were considered. Several fish species were included as planktivorous consumers, with special attention to sardine (Sardina pilchardus). Finally, top pelagic consumers were represented by the common dolphin (Delphinus delphis). The relationship between trophic position and body size implies large variability in the ratio of predator to prey sizes, likely because widespread omnivory and plankton consumption by relatively large predators. Planktivorous species share a common trophic position, suggesting potential competition for food, and low nitrogen isotope enrichment between prey and consumers suggest nutrient limitation and recycling at the base of the food web. Both experimental and field evidences indicate that the muscle of sardine integrates fish diet over seasonal periods and reflects the composition of plankton from large shelf areas. The low mobility of sardines during periods of low population size is consistent with differential isotopic signatures found in shelf zones characterised by upwelling nutrient inputs.

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Submarine canyon systems provide a heterogeneous habitat for deep-sea benthos in terms of topography, hydrography, and the quality and quantity of organic matter present. Enhanced meiofauna densities as found in organically enriched canyon sediments suggest that nematodes, as the dominant metazoan meiobenthic taxon, may play an important role in the benthic food web of these sediments. Very little is known about the natural diets and trophic biology of deep-sea nematodes, but enrichment experiments can shed light on nematode feeding selectivity and trophic position. An in-situ pulse-chase experiment (Feedex) was performed in the Nazaré Canyon on the Portuguese margin in summer 2007 to study nematode feeding behaviour. 13C-labelled diatoms and bacteria were added to sediment cores which were then sampled over a 14-day period. There was differential uptake by the nematode community of the food sources provided, indicating selective feeding processes. 13C isotope results revealed that selective feeding was less pronounced at the surface, compared to the sediment subsurface. This was supported by a higher trophic diversity in surface sediments compared to the subsurface, implying that more food items may be used by the nematode community at the sediment surface. Predatory and scavenging nematodes contributed relatively more to biomass than other feeding types and can be seen as key contributors to the nematode food web at the canyon site. Non-selective deposit feeding nematodes were the dominant trophic group in terms of abundance and contributed substantially to total nematode biomass. The high levels of 'fresh' (bioavailable) organic matter input and moderate hydrodynamic disturbance of the canyon environment lead to a more complex trophic structure in canyon nematode communities than that found on the open continental slope, and favours predator/scavengers and non-selective deposit feeders.

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The structure of the zooplankton foodweb and their dominant carbon fluxes were studied in the upwelling system off northern Chile (Mejillones Bay; 23°S) between October 2000 and December 2002. High primary production (PP) rates (18 gC/m**2 d) were mostly due to the net-phytoplankton size fraction (>23 µm). High PP has been traditionally associated with the wind-driven upwelling fertilizing effect of equatorial subsurface waters, which favour development of a short food chain dominated by a few small clupeiform fish species. The objective of the present work was to study the trophic carbon flow through the first step of this 'classical chain' (from phytoplankton to primary consumers such as copepods and euphausiids) and the carbon flow towards the gelatinous web composed of both filter-feeding and carnivorous zooplankton. To accomplish this objective, feeding experiments with copepods, appendicularians, ctenophores, and chaetognaths were conducted using naturally occurring plankton prey assemblages. Throughout the study, the total carbon ingestion rates showed that the dominant appendicularian species and small copepods consumed an average of 7 and 5 µgC/ind d, respectively. In addition, copepods ingested particles mainly in the size range of nano- and microplankton, whereas appendicularians ingested in the range of pico- and nanoplankton. Small copepods and appendicularians removed a small fraction of total daily PP (range 6-11%). However, when the pico- + nanoplankton fractions were the major contributors to total PP (oligotrophic conditions), grazing by small copepods increased markedly to 86% of total PP. Under these more oligotrophic conditions, the euphausiids grazing increased as well, but only reached values lower than 5% of total PP. During this study, chaetognaths and ctenophores ingested an average of 1 and 14 copepods/ind d, respectively. In terms of biomass consumed, the potential impact of carnivorous gelatinous zooplankton on the small-size copepod community (preferred prey) was important (2-12% of biomass removed daily). However, their impact produced more significant results on copepod abundance (up to 33%), which suggests that carnivorous gelatinous zooplankton may even modulate (control) the abundance of some species as well as the size structure of the copepod community.

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We estimated the relative contribution of atmospheric Nitrogen (N) input (wet and dry deposition and N fixation) to the epipelagic food web by measuring N isotopes of different functional groups of epipelagic zooplankton along 23°W (17°N-4°S) and 18°N (20-24°W) in the Eastern Tropical Atlantic. Results were related to water column observations of nutrient distribution and vertical diffusive flux as well as colony abundance of Trichodesmium obtained with an Underwater Vision Profiler (UVP5). The thickness and depth of the nitracline and phosphocline proved to be significant predictors of zooplankton stable N isotope values. Atmospheric N input was highest (61% of total N) in the strongly stratified and oligotrophic region between 3 and 7°N, which featured very high depth-integrated Trichodesmium abundance (up to 9.4×104 colonies m-2), strong thermohaline stratification and low zooplankton delta15N (~2 per mil). Relative atmospheric N input was lowest south of the equatorial upwelling between 3 and 5°S (27%). Values in the Guinea Dome region and north of Cape Verde ranged between 45 and 50%, respectively. The microstructure-derived estimate of the vertical diffusive N flux in the equatorial region was about one order of magnitude higher than in any other area (approximately 8 mmol m-2 d 1). At the same time, this region received considerable atmospheric N input (35% of total). In general, zooplankton delta15N and Trichodesmium abundance were closely correlated, indicating that N fixation is the major source of atmospheric N input. Although Trichodesmium is not the only N fixing organism, its abundance can be used with high confidence to estimate the relative atmospheric N input in the tropical Atlantic (r2 = 0.95). Estimates of absolute N fixation rates are two- to tenfold higher than incubation-derived rates reported for the same regions. Our approach integrates over large spatial and temporal scales and also quantifies fixed N released as dissolved inorganic and organic N. In a global analysis, it may thus help to close the gap in oceanic N budgets.

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This article analyses a number of social and cultural aspects of the blog phenomenon with the methodological aid of a complexity model, the New Techno-social Environment (hereinafter also referred to by its Spanish acronym, NET, or Nuevo Entorno Tecnosocial) together with the socio-technical approach of the two blogologist authors. Both authors are researchers interested in the new reality of the Digital Universal Network (DUN). After a review of some basic definitions, the article moves on to highlight some key characteristics of an emerging blog culture and relates them to the properties of the NET. Then, after a brief practical parenthesis for people entering the blogosphere for the first time, we present some reflections on blogs as an evolution of virtual communities and on the changes experienced by the inhabitants of the infocity emerging from within the NET. The article concludes with a somewhat disturbing question; whether among these changes there might not be a gradual transformation of the structure and form of human intelligence.

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OntoTag - A Linguistic and Ontological Annotation Model Suitable for the Semantic Web 1. INTRODUCTION. LINGUISTIC TOOLS AND ANNOTATIONS: THEIR LIGHTS AND SHADOWS Computational Linguistics is already a consolidated research area. It builds upon the results of other two major ones, namely Linguistics and Computer Science and Engineering, and it aims at developing computational models of human language (or natural language, as it is termed in this area). Possibly, its most well-known applications are the different tools developed so far for processing human language, such as machine translation systems and speech recognizers or dictation programs. These tools for processing human language are commonly referred to as linguistic tools. Apart from the examples mentioned above, there are also other types of linguistic tools that perhaps are not so well-known, but on which most of the other applications of Computational Linguistics are built. These other types of linguistic tools comprise POS taggers, natural language parsers and semantic taggers, amongst others. All of them can be termed linguistic annotation tools. Linguistic annotation tools are important assets. In fact, POS and semantic taggers (and, to a lesser extent, also natural language parsers) have become critical resources for the computer applications that process natural language. Hence, any computer application that has to analyse a text automatically and ‘intelligently’ will include at least a module for POS tagging. The more an application needs to ‘understand’ the meaning of the text it processes, the more linguistic tools and/or modules it will incorporate and integrate. However, linguistic annotation tools have still some limitations, which can be summarised as follows: 1. Normally, they perform annotations only at a certain linguistic level (that is, Morphology, Syntax, Semantics, etc.). 2. They usually introduce a certain rate of errors and ambiguities when tagging. This error rate ranges from 10 percent up to 50 percent of the units annotated for unrestricted, general texts. 3. Their annotations are most frequently formulated in terms of an annotation schema designed and implemented ad hoc. A priori, it seems that the interoperation and the integration of several linguistic tools into an appropriate software architecture could most likely solve the limitations stated in (1). Besides, integrating several linguistic annotation tools and making them interoperate could also minimise the limitation stated in (2). Nevertheless, in the latter case, all these tools should produce annotations for a common level, which would have to be combined in order to correct their corresponding errors and inaccuracies. Yet, the limitation stated in (3) prevents both types of integration and interoperation from being easily achieved. In addition, most high-level annotation tools rely on other lower-level annotation tools and their outputs to generate their own ones. For example, sense-tagging tools (operating at the semantic level) often use POS taggers (operating at a lower level, i.e., the morphosyntactic) to identify the grammatical category of the word or lexical unit they are annotating. Accordingly, if a faulty or inaccurate low-level annotation tool is to be used by other higher-level one in its process, the errors and inaccuracies of the former should be minimised in advance. Otherwise, these errors and inaccuracies would be transferred to (and even magnified in) the annotations of the high-level annotation tool. Therefore, it would be quite useful to find a way to (i) correct or, at least, reduce the errors and the inaccuracies of lower-level linguistic tools; (ii) unify the annotation schemas of different linguistic annotation tools or, more generally speaking, make these tools (as well as their annotations) interoperate. Clearly, solving (i) and (ii) should ease the automatic annotation of web pages by means of linguistic tools, and their transformation into Semantic Web pages (Berners-Lee, Hendler and Lassila, 2001). Yet, as stated above, (ii) is a type of interoperability problem. There again, ontologies (Gruber, 1993; Borst, 1997) have been successfully applied thus far to solve several interoperability problems. Hence, ontologies should help solve also the problems and limitations of linguistic annotation tools aforementioned. Thus, to summarise, the main aim of the present work was to combine somehow these separated approaches, mechanisms and tools for annotation from Linguistics and Ontological Engineering (and the Semantic Web) in a sort of hybrid (linguistic and ontological) annotation model, suitable for both areas. This hybrid (semantic) annotation model should (a) benefit from the advances, models, techniques, mechanisms and tools of these two areas; (b) minimise (and even solve, when possible) some of the problems found in each of them; and (c) be suitable for the Semantic Web. The concrete goals that helped attain this aim are presented in the following section. 2. GOALS OF THE PRESENT WORK As mentioned above, the main goal of this work was to specify a hybrid (that is, linguistically-motivated and ontology-based) model of annotation suitable for the Semantic Web (i.e. it had to produce a semantic annotation of web page contents). This entailed that the tags included in the annotations of the model had to (1) represent linguistic concepts (or linguistic categories, as they are termed in ISO/DCR (2008)), in order for this model to be linguistically-motivated; (2) be ontological terms (i.e., use an ontological vocabulary), in order for the model to be ontology-based; and (3) be structured (linked) as a collection of ontology-based triples, as in the usual Semantic Web languages (namely RDF(S) and OWL), in order for the model to be considered suitable for the Semantic Web. Besides, to be useful for the Semantic Web, this model should provide a way to automate the annotation of web pages. As for the present work, this requirement involved reusing the linguistic annotation tools purchased by the OEG research group (http://www.oeg-upm.net), but solving beforehand (or, at least, minimising) some of their limitations. Therefore, this model had to minimise these limitations by means of the integration of several linguistic annotation tools into a common architecture. Since this integration required the interoperation of tools and their annotations, ontologies were proposed as the main technological component to make them effectively interoperate. From the very beginning, it seemed that the formalisation of the elements and the knowledge underlying linguistic annotations within an appropriate set of ontologies would be a great step forward towards the formulation of such a model (henceforth referred to as OntoTag). Obviously, first, to combine the results of the linguistic annotation tools that operated at the same level, their annotation schemas had to be unified (or, preferably, standardised) in advance. This entailed the unification (id. standardisation) of their tags (both their representation and their meaning), and their format or syntax. Second, to merge the results of the linguistic annotation tools operating at different levels, their respective annotation schemas had to be (a) made interoperable and (b) integrated. And third, in order for the resulting annotations to suit the Semantic Web, they had to be specified by means of an ontology-based vocabulary, and structured by means of ontology-based triples, as hinted above. Therefore, a new annotation scheme had to be devised, based both on ontologies and on this type of triples, which allowed for the combination and the integration of the annotations of any set of linguistic annotation tools. This annotation scheme was considered a fundamental part of the model proposed here, and its development was, accordingly, another major objective of the present work. All these goals, aims and objectives could be re-stated more clearly as follows: Goal 1: Development of a set of ontologies for the formalisation of the linguistic knowledge relating linguistic annotation. Sub-goal 1.1: Ontological formalisation of the EAGLES (1996a; 1996b) de facto standards for morphosyntactic and syntactic annotation, in a way that helps respect the triple structure recommended for annotations in these works (which is isomorphic to the triple structures used in the context of the Semantic Web). Sub-goal 1.2: Incorporation into this preliminary ontological formalisation of other existing standards and standard proposals relating the levels mentioned above, such as those currently under development within ISO/TC 37 (the ISO Technical Committee dealing with Terminology, which deals also with linguistic resources and annotations). Sub-goal 1.3: Generalisation and extension of the recommendations in EAGLES (1996a; 1996b) and ISO/TC 37 to the semantic level, for which no ISO/TC 37 standards have been developed yet. Sub-goal 1.4: Ontological formalisation of the generalisations and/or extensions obtained in the previous sub-goal as generalisations and/or extensions of the corresponding ontology (or ontologies). Sub-goal 1.5: Ontological formalisation of the knowledge required to link, combine and unite the knowledge represented in the previously developed ontology (or ontologies). Goal 2: Development of OntoTag’s annotation scheme, a standard-based abstract scheme for the hybrid (linguistically-motivated and ontological-based) annotation of texts. Sub-goal 2.1: Development of the standard-based morphosyntactic annotation level of OntoTag’s scheme. This level should include, and possibly extend, the recommendations of EAGLES (1996a) and also the recommendations included in the ISO/MAF (2008) standard draft. Sub-goal 2.2: Development of the standard-based syntactic annotation level of the hybrid abstract scheme. This level should include, and possibly extend, the recommendations of EAGLES (1996b) and the ISO/SynAF (2010) standard draft. Sub-goal 2.3: Development of the standard-based semantic annotation level of OntoTag’s (abstract) scheme. Sub-goal 2.4: Development of the mechanisms for a convenient integration of the three annotation levels already mentioned. These mechanisms should take into account the recommendations included in the ISO/LAF (2009) standard draft. Goal 3: Design of OntoTag’s (abstract) annotation architecture, an abstract architecture for the hybrid (semantic) annotation of texts (i) that facilitates the integration and interoperation of different linguistic annotation tools, and (ii) whose results comply with OntoTag’s annotation scheme. Sub-goal 3.1: Specification of the decanting processes that allow for the classification and separation, according to their corresponding levels, of the results of the linguistic tools annotating at several different levels. Sub-goal 3.2: Specification of the standardisation processes that allow (a) complying with the standardisation requirements of OntoTag’s annotation scheme, as well as (b) combining the results of those linguistic tools that share some level of annotation. Sub-goal 3.3: Specification of the merging processes that allow for the combination of the output annotations and the interoperation of those linguistic tools that share some level of annotation. Sub-goal 3.4: Specification of the merge processes that allow for the integration of the results and the interoperation of those tools performing their annotations at different levels. Goal 4: Generation of OntoTagger’s schema, a concrete instance of OntoTag’s abstract scheme for a concrete set of linguistic annotations. These linguistic annotations result from the tools and the resources available in the research group, namely • Bitext’s DataLexica (http://www.bitext.com/EN/datalexica.asp), • LACELL’s (POS) tagger (http://www.um.es/grupos/grupo-lacell/quees.php), • Connexor’s FDG (http://www.connexor.eu/technology/machinese/glossary/fdg/), and • EuroWordNet (Vossen et al., 1998). This schema should help evaluate OntoTag’s underlying hypotheses, stated below. Consequently, it should implement, at least, those levels of the abstract scheme dealing with the annotations of the set of tools considered in this implementation. This includes the morphosyntactic, the syntactic and the semantic levels. Goal 5: Implementation of OntoTagger’s configuration, a concrete instance of OntoTag’s abstract architecture for this set of linguistic tools and annotations. This configuration (1) had to use the schema generated in the previous goal; and (2) should help support or refute the hypotheses of this work as well (see the next section). Sub-goal 5.1: Implementation of the decanting processes that facilitate the classification and separation of the results of those linguistic resources that provide annotations at several different levels (on the one hand, LACELL’s tagger operates at the morphosyntactic level and, minimally, also at the semantic level; on the other hand, FDG operates at the morphosyntactic and the syntactic levels and, minimally, at the semantic level as well). Sub-goal 5.2: Implementation of the standardisation processes that allow (i) specifying the results of those linguistic tools that share some level of annotation according to the requirements of OntoTagger’s schema, as well as (ii) combining these shared level results. In particular, all the tools selected perform morphosyntactic annotations and they had to be conveniently combined by means of these processes. Sub-goal 5.3: Implementation of the merging processes that allow for the combination (and possibly the improvement) of the annotations and the interoperation of the tools that share some level of annotation (in particular, those relating the morphosyntactic level, as in the previous sub-goal). Sub-goal 5.4: Implementation of the merging processes that allow for the integration of the different standardised and combined annotations aforementioned, relating all the levels considered. Sub-goal 5.5: Improvement of the semantic level of this configuration by adding a named entity recognition, (sub-)classification and annotation subsystem, which also uses the named entities annotated to populate a domain ontology, in order to provide a concrete application of the present work in the two areas involved (the Semantic Web and Corpus Linguistics). 3. MAIN RESULTS: ASSESSMENT OF ONTOTAG’S UNDERLYING HYPOTHESES The model developed in the present thesis tries to shed some light on (i) whether linguistic annotation tools can effectively interoperate; (ii) whether their results can be combined and integrated; and, if they can, (iii) how they can, respectively, interoperate and be combined and integrated. Accordingly, several hypotheses had to be supported (or rejected) by the development of the OntoTag model and OntoTagger (its implementation). The hypotheses underlying OntoTag are surveyed below. Only one of the hypotheses (H.6) was rejected; the other five could be confirmed. H.1 The annotations of different levels (or layers) can be integrated into a sort of overall, comprehensive, multilayer and multilevel annotation, so that their elements can complement and refer to each other. • CONFIRMED by the development of: o OntoTag’s annotation scheme, o OntoTag’s annotation architecture, o OntoTagger’s (XML, RDF, OWL) annotation schemas, o OntoTagger’s configuration. H.2 Tool-dependent annotations can be mapped onto a sort of tool-independent annotations and, thus, can be standardised. • CONFIRMED by means of the standardisation phase incorporated into OntoTag and OntoTagger for the annotations yielded by the tools. H.3 Standardisation should ease: H.3.1: The interoperation of linguistic tools. H.3.2: The comparison, combination (at the same level and layer) and integration (at different levels or layers) of annotations. • H.3 was CONFIRMED by means of the development of OntoTagger’s ontology-based configuration: o Interoperation, comparison, combination and integration of the annotations of three different linguistic tools (Connexor’s FDG, Bitext’s DataLexica and LACELL’s tagger); o Integration of EuroWordNet-based, domain-ontology-based and named entity annotations at the semantic level. o Integration of morphosyntactic, syntactic and semantic annotations. H.4 Ontologies and Semantic Web technologies (can) play a crucial role in the standardisation of linguistic annotations, by providing consensual vocabularies and standardised formats for annotation (e.g., RDF triples). • CONFIRMED by means of the development of OntoTagger’s RDF-triple-based annotation schemas. H.5 The rate of errors introduced by a linguistic tool at a given level, when annotating, can be reduced automatically by contrasting and combining its results with the ones coming from other tools, operating at the same level. However, these other tools might be built following a different technological (stochastic vs. rule-based, for example) or theoretical (dependency vs. HPS-grammar-based, for instance) approach. • CONFIRMED by the results yielded by the evaluation of OntoTagger. H.6 Each linguistic level can be managed and annotated independently. • REJECTED: OntoTagger’s experiments and the dependencies observed among the morphosyntactic annotations, and between them and the syntactic annotations. In fact, Hypothesis H.6 was already rejected when OntoTag’s ontologies were developed. We observed then that several linguistic units stand on an interface between levels, belonging thereby to both of them (such as morphosyntactic units, which belong to both the morphological level and the syntactic level). Therefore, the annotations of these levels overlap and cannot be handled independently when merged into a unique multileveled annotation. 4. OTHER MAIN RESULTS AND CONTRIBUTIONS First, interoperability is a hot topic for both the linguistic annotation community and the whole Computer Science field. The specification (and implementation) of OntoTag’s architecture for the combination and integration of linguistic (annotation) tools and annotations by means of ontologies shows a way to make these different linguistic annotation tools and annotations interoperate in practice. Second, as mentioned above, the elements involved in linguistic annotation were formalised in a set (or network) of ontologies (OntoTag’s linguistic ontologies). • On the one hand, OntoTag’s network of ontologies consists of − The Linguistic Unit Ontology (LUO), which includes a mostly hierarchical formalisation of the different types of linguistic elements (i.e., units) identifiable in a written text; − The Linguistic Attribute Ontology (LAO), which includes also a mostly hierarchical formalisation of the different types of features that characterise the linguistic units included in the LUO; − The Linguistic Value Ontology (LVO), which includes the corresponding formalisation of the different values that the attributes in the LAO can take; − The OIO (OntoTag’s Integration Ontology), which  Includes the knowledge required to link, combine and unite the knowledge represented in the LUO, the LAO and the LVO;  Can be viewed as a knowledge representation ontology that describes the most elementary vocabulary used in the area of annotation. • On the other hand, OntoTag’s ontologies incorporate the knowledge included in the different standards and recommendations for linguistic annotation released so far, such as those developed within the EAGLES and the SIMPLE European projects or by the ISO/TC 37 committee: − As far as morphosyntactic annotations are concerned, OntoTag’s ontologies formalise the terms in the EAGLES (1996a) recommendations and their corresponding terms within the ISO Morphosyntactic Annotation Framework (ISO/MAF, 2008) standard; − As for syntactic annotations, OntoTag’s ontologies incorporate the terms in the EAGLES (1996b) recommendations and their corresponding terms within the ISO Syntactic Annotation Framework (ISO/SynAF, 2010) standard draft; − Regarding semantic annotations, OntoTag’s ontologies generalise and extend the recommendations in EAGLES (1996a; 1996b) and, since no stable standards or standard drafts have been released for semantic annotation by ISO/TC 37 yet, they incorporate the terms in SIMPLE (2000) instead; − The terms coming from all these recommendations and standards were supplemented by those within the ISO Data Category Registry (ISO/DCR, 2008) and also of the ISO Linguistic Annotation Framework (ISO/LAF, 2009) standard draft when developing OntoTag’s ontologies. Third, we showed that the combination of the results of tools annotating at the same level can yield better results (both in precision and in recall) than each tool separately. In particular, 1. OntoTagger clearly outperformed two of the tools integrated into its configuration, namely DataLexica and FDG in all the combination sub-phases in which they overlapped (i.e. POS tagging, lemma annotation and morphological feature annotation). As far as the remaining tool is concerned, i.e. LACELL’s tagger, it was also outperformed by OntoTagger in POS tagging and lemma annotation, and it did not behave better than OntoTagger in the morphological feature annotation layer. 2. As an immediate result, this implies that a) This type of combination architecture configurations can be applied in order to improve significantly the accuracy of linguistic annotations; and b) Concerning the morphosyntactic level, this could be regarded as a way of constructing more robust and more accurate POS tagging systems. Fourth, Semantic Web annotations are usually performed by humans or else by machine learning systems. Both of them leave much to be desired: the former, with respect to their annotation rate; the latter, with respect to their (average) precision and recall. In this work, we showed how linguistic tools can be wrapped in order to annotate automatically Semantic Web pages using ontologies. This entails their fast, robust and accurate semantic annotation. As a way of example, as mentioned in Sub-goal 5.5, we developed a particular OntoTagger module for the recognition, classification and labelling of named entities, according to the MUC and ACE tagsets (Chinchor, 1997; Doddington et al., 2004). These tagsets were further specified by means of a domain ontology, namely the Cinema Named Entities Ontology (CNEO). This module was applied to the automatic annotation of ten different web pages containing cinema reviews (that is, around 5000 words). In addition, the named entities annotated with this module were also labelled as instances (or individuals) of the classes included in the CNEO and, then, were used to populate this domain ontology. • The statistical results obtained from the evaluation of this particular module of OntoTagger can be summarised as follows. On the one hand, as far as recall (R) is concerned, (R.1) the lowest value was 76,40% (for file 7); (R.2) the highest value was 97, 50% (for file 3); and (R.3) the average value was 88,73%. On the other hand, as far as the precision rate (P) is concerned, (P.1) its minimum was 93,75% (for file 4); (R.2) its maximum was 100% (for files 1, 5, 7, 8, 9, and 10); and (R.3) its average value was 98,99%. • These results, which apply to the tasks of named entity annotation and ontology population, are extraordinary good for both of them. They can be explained on the basis of the high accuracy of the annotations provided by OntoTagger at the lower levels (mainly at the morphosyntactic level). However, they should be conveniently qualified, since they might be too domain- and/or language-dependent. It should be further experimented how our approach works in a different domain or a different language, such as French, English, or German. • In any case, the results of this application of Human Language Technologies to Ontology Population (and, accordingly, to Ontological Engineering) seem very promising and encouraging in order for these two areas to collaborate and complement each other in the area of semantic annotation. Fifth, as shown in the State of the Art of this work, there are different approaches and models for the semantic annotation of texts, but all of them focus on a particular view of the semantic level. Clearly, all these approaches and models should be integrated in order to bear a coherent and joint semantic annotation level. OntoTag shows how (i) these semantic annotation layers could be integrated together; and (ii) they could be integrated with the annotations associated to other annotation levels. Sixth, we identified some recommendations, best practices and lessons learned for annotation standardisation, interoperation and merge. They show how standardisation (via ontologies, in this case) enables the combination, integration and interoperation of different linguistic tools and their annotations into a multilayered (or multileveled) linguistic annotation, which is one of the hot topics in the area of Linguistic Annotation. And last but not least, OntoTag’s annotation scheme and OntoTagger’s annotation schemas show a way to formalise and annotate coherently and uniformly the different units and features associated to the different levels and layers of linguistic annotation. This is a great scientific step ahead towards the global standardisation of this area, which is the aim of ISO/TC 37 (in particular, Subcommittee 4, dealing with the standardisation of linguistic annotations and resources).

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Semantic Sensor Web infrastructures use ontology-based models to represent the data that they manage; however, up to now, these ontological models do not allow representing all the characteristics of distributed, heterogeneous, and web-accessible sensor data. This paper describes a core ontological model for Semantic Sensor Web infrastructures that covers these characteristics and that has been built with a focus on reusability. This ontological model is composed of different modules that deal, on the one hand, with infrastructure data and, on the other hand, with data from a specific domain, that is, the coastal flood emergency planning domain. The paper also presents a set of guidelines, followed during the ontological model development, to satisfy a common set of requirements related to modelling domain-specific features of interest and properties. In addition, the paper includes the results obtained after an exhaustive evaluation of the developed ontologies along different aspects (i.e., vocabulary, syntax, structure, semantics, representation, and context).

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This paper describes a numerical study on the instability of a brace-type seismic damper based on the out of plane yielding of the web of wide-flange steel sections (Web Plastifying Damper, WPD)The damper is intended to be installed in a framed structure as a standard diagonal brace. Under lateral forces, the damper is subjected to high axial forces, therefore its buckling instability is a matter of concern. Several finite element models representing WPDs with different axial stiffness and various geometries of their components were developed and analyzed taking into account both material and geometrical nonlinearities. The influence of several parameters defining the WPD in the load-displacement curve was examined. Furthermore, a simplified model to predict the buckling load is proposed.