934 resultados para Latin language, Preclassical to ca. 100 B.C.


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Here we report 420 kyr long records of sediment geochemical and color variations from the southwestern Iberian Margin. We synchronized the Iberian Margin sediment record to Antarctic ice cores and speleothem records on millennial time scales and investigated the phase responses relative to orbital forcing of multiple proxy records available from these cores. Iberian Margin sediments contain strong precession power. Sediment "redness" (a* and 570-560 nm) and the ratio of long-chain alcohols to n-alkanes (C26OH/(C26OH + C29)) are highly coherent and in-phase with precession. Redder layers and more oxidizing conditions (low alcohol ratio) occur near precession minima (summer insolation maxima). We suggest these proxies respond rapidly to low-latitude insolation forcing by wind-driven processes (e.g., dust transport, upwelling, precipitation). Most Iberian Margin sediment parameters lag obliquity maxima by 7-8 ka, indicating a consistent linear response to insolation forcing at obliquity frequencies driven mainly by high-latitude processes. Although the lengths of the time series are short (420 ka) for detecting 100 kyr eccentricity cycles, the phase relationships support those obtained by Shackleton []. Antarctic temperature and the Iberian Margin alcohol ratios (C26OH/(C26OH + C29)) lead eccentricity maxima by 6 kyr, with lower ratios (increased oxygenation) occurring at eccentricity maxima. CO2, CH4, and Iberian SST are nearly in phase with eccentricity, and minimum ice volume (as inferred from Pacific d18Oseawater) lags eccentricity maxima by 10 kyr. The phase relationships derived in this study continue to support a potential role of the Earth's carbon cycle in contributing to the 100 kyr cycle.

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New Mg/Ca, Sr/Ca, and published stable oxygen isotope and 87Sr/86Sr data obtained on ostracods from gravity cores located on the northwestern Black Sea slope were used to infer changes in the Black Sea hydrology and water chemistry for the period between 30 to 8 ka B.P. (calibrated radiocarbon years). The period prior to 16.5 ka B.P. was characterized by stable conditions in all records until a distinct drop in d18O values combined with a sharp increase in 87Sr/86Sr occurred between 16.5 and 14.8 ka B.P. This event is attributed to an increased runoff from the northern drainage area of the Black Sea between Heinrich Event 1 and the onset of the Bølling warm period. While the Mg/Ca and Sr/Ca records remained rather unaffected by this inflow; they show an abrupt rise with the onset of the Bølling/Allerød warm period. This rise was caused by calcite precipitation in the surface water, which led to a sudden increase of the Sr/Ca and Mg/Ca ratios of the Black Sea water. The stable oxygen isotopes also start to increase around 15 ka B.P., although in a more gradual manner, due to isotopically enriched meteoric precipitation. While Sr/Ca remains constant during the following interval of the Younger Dryas cold period, a decrease in the Mg/Ca ratio implies that the intermediate water masses of the Black Sea temporarily cooled by 1-2°C during the Younger Dryas. The 87Sr/86Sr values drop after the cessation of the water inflow at 15 ka B.P. to a lower level until the Younger Dryas, where they reach values similar to those observed during the Last Glacial Maximum. This might point to a potential outflow to the Mediterranean Sea via the Sea of Marmara during this period. The inflow of Mediterranean water started around 9.3 ka B.P., which is clearly detectable in the abruptly increasing Mg/Ca, Sr/Ca, and 87Sr/86Sr values. The accompanying increase in the d18O record is less pronounced and would fit to an inflow lasting ~100 a.

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Relict sand wedges are ubiquitous in southern Patagonia. At six sites we conducted detailed investigations of stratigraphy, soils, and wedge frequency and characteristics. Some sections contain four or more buried horizons with casts. The cryogenic features are dominantly relict sand wedges with an average depth, maximum apparent width, minimum apparent width, and H/W of 78, 39, 3.8, and 2.9 cm, respectively. The host materials are fine-textured (silt loam, silty clay loam, clay loam) till and the infillings are aeolian sand. The soils are primarily Calciargidic Argixerolls that bear a legacy of climate change. Whereas the sand wedges formed during very cold (-4 to -8 °C or colder) and dry (ca. <=100 mm precipitation/yr) glacial periods, petrocalcic horizons from calcium carbonate contributed by dustfall formed during warmer (7 °C or warmer) and moister (>= 250 mm/yr) interglacial periods. The paleo-argillic (Bt) horizons reflect unusually moist interglacial events where the mean annual precipitation may have been 400 mm/yr. Permafrost was nearly continuous in southern Patagonia during the Illinoian glacial stage (ca. 200 ka), the early to mid-Pleistocene (ca. 800-500 ka), and on two occasions during the early Pleistocene (ca. 1.0-1.1 Ma).

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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 cate, Object> 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 cate, Object> 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 cate, Object> 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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We describe the current status of and provide performance results for a prototype compiler of Prolog to C, ciaocc. ciaocc is novel in that it is designed to accept different kinds of high-level information, typically obtained via an automatic analysis of the initial Prolog program and expressed in a standardized language of assertions. This information is used to optimize the resulting C code, which is then processed by an off-the-shelf C compiler. The basic translation process essentially mimics the unfolding of a bytecode emulator with respect to the particular bytecode corresponding to the Prolog program. This is facilitated by a flexible design of the instructions and their lower-level components. This approach allows reusing a sizable amount of the machinery of the bytecode emulator: predicates already written in C, data definitions, memory management routines and áreas, etc., as well as mixing emulated bytecode with native code in a relatively straightforward way. We report on the performance of programs compiled by the current versión of the system, both with and without analysis information.

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We describe the current status of and provide preliminary performance results for a compiler of Prolog to C. The compiler is novel in that it is designed to accept different kinds of high-level information (typically obtained via an analysis of the initial Prolog program and expressed in a standardized language of assertions) and use this information to optimize the resulting C code, which is then further processed by an off-the-shelf C compiler. The basic translation process used essentially mimics an unfolding of a C-coded bytecode emúlator with respect to the particular bytecode corresponding to the Prolog program. Optimizations are then applied to this unfolded program. This is facilitated by a more flexible design of the bytecode instructions and their lower-level components. This approach allows reusing a sizable amount of the machinery of the bytecode emulator: ancillary pieces of C code, data definitions, memory management routines and áreas, etc., as well as mixing bytecode emulated code with natively compiled code in a relatively straightforward way We report on the performance of programs compiled by the current versión of the system, both with and without analysis information.

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In this paper the very first geochemical and isotopic data related to surface and spring waters and dissolved gases in the area of Hontomín–Huermeces (Burgos, Spain) are presented and discussed. Hontomín–Huermeces has been selected as a pilot site for the injection of pure (>99%) CO2. Injection and monitoring wells are planned to be drilled close to 6 oil wells completed in the 1980s for which detailed stratigraphical logs are available, indicating the presence of a confined saline aquifer at the depth of about 1500 m into which less than 100,000 tons of iquid CO2 will be injected, possibly starting in 2013. The chemical and features of the spring waters suggest that they are related to a shallow hydrogeological system as the concentration of the Total Dissolved Solids approaches 800 mg/L with a Ca2+(Mg2+)-HCO3− composition, similar to that of the surface waters. This is also supported by the oxygen and hydrogen isotopic ratios that have values lying between those of the Global and the Mediterranean Meteoric Water Lines. Some spring waters close to the oil wells are haracterized by relatively high concentrations of NO3− (up to 123 mg/L), unequivocally suggesting an anthropogenic source that adds to the main water–rock interaction processes. The latter can be referred to Ca-Mg-carbonate and, at a minor extent, Al-silicate dissolution, being the outcropping sedimentary rocks characterized by Palaeozoic to Quaternary rocks. Anomalous concentrations of Cl−, SO42−, As, B and Ba were measured in two springs discharging a few hundred meters from the oil wells and in the Rio Ubierna. These contents are significantly higher than those of the whole set of the studied waters and are possibly indicative of mixing processes, although at very low extent, between deep and shallow aquifers. No evidence of deep-seated gases interacting with the Hontomín–Huermeces waters was recognized in the chemistry of the disolved gases. This is likely due to the fact that they are mainly characterized by an atmospheric source as highlighted by the high contents of N2, O2 and Ar and by N2/Ar ratios that approach that of ASW (Air Saturated Water) and possibly masking any contribution related to a deep source. Nevertheless, significant concentrations (up to 63% by vol.) of isotopically negative CO2 (<−17.7‰ V-PDB) were found in some water samples, likely related to a biogenic source. The geochemical and isotopic data of this work are of particular importance when a monitoring program will be established to verify whether CO2 leakages, induced by the injection of this greenhouse gas, may be affecting the quality of the waters in the shallow hydrological circuits at Hontomín–Huermeces. In this respect, carbonate chemistry, the isotopic carbon of dissolved CO2 and TDIC (Total Dissolved Inorganic Carbon) and selected trace elements can be considered as useful parameters to trace the migration of the injected CO2 into near-surface environments.

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Este proyecto consiste en el diseño e implementación de un procesador digital de efectos de audio en tiempo real orientado a instrumentos eléctricos tales como guitarras, bajos, teclados, etc. El procesador está basado en la tarjeta Raspberry Pi B+, ordenador de placa reducida de bajo coste, desarrollado en Reino unido y cuyo lanzamiento tuvo lugar en el año 2012. En primer lugar, ha sido necesario lograr que la tarjeta asuma la funcionalidad de un procesador de audio en tiempo real. Para ello se ha instalado un sistema operativo Linux orientado a Raspberry (Raspbian) y se ha hecho uso de Pure Data (Pd): lenguaje de programación gráfico que fue desarrollado en los años 90 por Miller Puckette con intención de ser enfocado a la creación de eventos multimedia y de música por computador. El papel que desempeña Pd es de capa intermedia entre el hardware y el software ya que se encarga de tomar bloques de N muestras del convertidor analógico/digital y encaminarlas a través del flujo de señal diseñado gráficamente. En segundo lugar, se han implementado diferentes efectos de audio de distintas características. Así pues, se encuentran efectos basados en retardos, filtros digitales y procesadores de dinámica. Concretamente, los efectos implementados son los siguientes: delay, flanger, vibrato, reverberador de Schroeder, filtros (paso bajo, paso alto y paso banda), ecualizador paramétrico y compresor y expansor de dinámica. Estos efectos han sido implementados en lenguaje C de acuerdo con la API de Pd. Con esto se ha conseguido obtener un objeto por cada efecto, el cual es “instanciado” en Pd pudiendo ejecutarlo en tiempo real. En este proyecto se expone la problemática que supone cada paso del diseño proponiendo soluciones válidas. Además se incluye una guía paso a paso para configurar la tarjeta y lograr realizar un bypass de señal y un efecto simple partiendo desde cero. ABSTRACT. This project involves the design and implementation of a digital real-time audio processor for electrical instruments (guitars, basses, keyboards, etc.). The processor is based on the Raspberry Pi B + card: low cost computer, developed in UK in 2012. First, it was necessary to make the cards assume the functionality of a real time audio processor. A Linux operating system called Raspberry (Raspbian) was installed. In this Project is used Pure Data (Pd): a graphical programming language developed in the 90s by Miller Puckette intending to be focused on creating multimedia and computer music events. The role of Pd is an intermediate layer between the hardware and the software. It is responsible for taking blocks of N samples of the analog/digital converter and route it through the signal flow. Secondly, it is necessary to implemented the different audio effects. There are delays based effects, digital filter and dynamics effects. Specifically, the implemented effects are: delay, flanger, vibrato, Schroeder reverb, filters (lowpass, highpass and bandpass), parametric equalizer and compressor and expander dynamics. These effects have been implemented in C language according to the Pd API. As a result, it has been obtained an object for each effect, which is instantiated in Pd. In this Project, the problems of every step are exposed with his corresponding solution. It is inlcuded a step-by-step guide to configure the card and achieve perform a bypass signal process and a simple effect.

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Members of the myc family of nuclear protooncogenes play roles in cell proliferation, differentiation, and apoptosis. Moreover, inappropriate expression of c-myc genes contributes to the development of many types of cancers, including B cell lymphomas in humans. Although Myc proteins have been shown to function as transcription factors, their immediate effects on the cell have not been well defined. Here we have utilized a murine model of lymphomagenesis (Eμ-myc mice) to show that constitutive expression of a c-myc transgene under control of the Ig heavy-chain enhancer (Eμ) results in an increase in cell size of normal pretransformed B lymphocytes at all stages of B cell development. Furthermore, we show that c-Myc-induced growth occurs independently of cell cycle phase and correlates with an increase in protein synthesis. These results suggest that Myc may normally function by coordinating expression of growth-related genes in response to mitogenic signals. Deregulated c-myc expression may predispose to cancer by enhancing cell growth to levels required for unrestrained cell division.

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Mutant I1A cells, lacking IL-1 receptor-associated kinase (IRAK) mRNA and protein, have been used to study the involvement of IRAK in NFκB and c-Jun N-terminal kinase (JNK) activation. A series of IRAK deletion constructs were expressed in I1A cells, which were then tested for their ability to respond to IL-1. Both the N-terminal death domain and the C-terminal region of IRAK are required for IL-1-induced NFκB and JNK activation, whereas the N-proximal undetermined domain is required for the activation of NFκB but not JNK. The phosphorylation and ubiquitination of IRAK deletion mutants correlate tightly with their ability to activate NFκB in response to IL-1, but IRAK can mediate IL-1-induced JNK activation without being phosphorylated. These studies reveal that the IL-1-induced signaling pathways leading to NFκB and JNK activation diverge either at IRAK or at a point nearer to the receptor.

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Determinants of the recommended dietary allowance (RDA) for vitamin C include the relationship between vitamin C dose and steady-state plasma concentration, bioavailability, urinary excretion, cell concentration, and potential adverse effects. Because current data are inadequate, an in-hospital depletion-repletion study was conducted. Seven healthy volunteers were hospitalized for 4-6 months and consumed a diet containing <5 mg of vitamin C daily. Steady-state plasma and tissue concentrations were determined at seven daily doses of vitamin C from 30 to 2500 mg. Vitamin C steady-state plasma concentrations as a function of dose displayed sigmoid kinetics. The steep portion of the curve occurred between the 30- and 100-mg daily dose, the current RDA of 60 mg daily was on the lower third of the curve, the first dose beyond the sigmoid portion of the curve was 200 mg daily, and complete plasma saturation occurred at 1000 mg daily. Neutrophils, monocytes, and lymphocytes saturated at 100 mg daily and contained concentrations at least 14-fold higher than plasma. Bioavailability was complete for 200 mg of vitamin C as a single dose. No vitamin C was excreted in urine of six of seven volunteers until the 100-mg dose. At single doses of 500 mg and higher, bioavailability declined and the absorbed amount was excreted. Oxalate and urate excretion were elevated at 1000 mg of vitamin C daily compared to lower doses. Based on these data and Institute of Medicine criteria, the current RDA of 60 mg daily should be increased to 200 mg daily, which can be obtained from fruits and vegetables. Safe doses of vitamin C are less than 1000 mg daily, and vitamin C daily doses above 400 mg have no evident value.

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The free radicals nitric oxide and superoxide anion react to form peroxynitrite (ONOO-), a highly toxic oxidant species. In vivo formation of ONOO- has been demonstrated in shock and inflammation. Herein we provide evidence that cytotoxicity in cells exposed to ONOO- is mediated by DNA strand breakage and the subsequent activation of the DNA repair enzyme poly(ADP ribose) synthetase (PARS). Exposure to ONOO- (100 microM to 1 mM) inhibited mitochondrial respiration in cultured J774 macrophages and in rat aortic smooth muscle cells. The loss of cellular respiration was rapid, peaking 1-3 h after ONOO- exposure, and reversible, with recovery after a period of 6-24 h. The inhibition of mitochondrial respiration was paralleled by a dose-dependent increase in DNA strand breakage, reaching its maximum at 20-30 min after exposure to ONOO-. We observed a dose-dependent increase in the activity of PARS in cells exposed to ONOO-. Inhibitors of PARS such as 3-aminobenzamide (1 mM) prevented the inhibition of cellular respiration in cells exposed to ONOO-. Activation of PARS by ONOO--mediated DNA strand breakage resulted in a significant decrease in intracellular energy stores, as reflected by a decline of intracellular NAD+ and ATP content. 3-Aminobenzamide prevented the loss of NAD+ and ATP in cells exposed to ONOO-. In contrast, impairment of cellular respiration by the addition of the nitric oxide donors S-nitroso-N-acetyl-DL-penicillamine or diethyltriamine nitric oxide complex, was not associated with the development of DNA strand breaks, in concentrations up to 1 mM, and was largely refractory to PARS inhibition. Our results suggest that DNA damage and activation of PARS, an energy-consuming futile repair cycle, play a central role in ONOO--mediated cellular injury.

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The pars triangular is a portion of Broca's area. The convolutions that form the inferior and caudal extent of the pars triangularis include the anterior horizontal and anterior ascending rami of the sylvian fissure, respectively. To learn if there are anatomic asymmetries of the pars triangularis, these convolutions were measured on volumetric magnetic resonance imaging scans of 11 patients who had undergone selective hemispheric anesthesia (Wada testing) to determine hemispheric speech and language lateralization. Of the 10 patients with language lateralized to the left hemisphere, 9 had a leftward asymmetry of the pars triangularis. The 1 patient with language lateralized to the right hemisphere had a significant rightward asymmetry of the pars triangularis. Our data suggest that asymmetries of the pars triangularis may be related to speech-language lateralization.

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International conference presentations represent one of the biggest challenges for academics using English as a Lingua Franca (ELF). This paper aims to initiate exploration into the multimodal academic discourse of oral presentations, including the verbal, written, non-verbal material (NVM) and body language modes. It offers a Systemic Functional Linguistic (SFL) and multimodal framework of presentations to enhance mixed-disciplinary ELF academics' awareness of what needs to be taken into account to communicate effectively at conferences. The model is also used to establish evaluation criteria for the presenters' talks and to carry out a multimodal discourse analysis of four well-rated 20-min talks, two from the technical sciences and two from the social sciences in a workshop scenario. The findings from the analysis and interviews indicate that: (a) a greater awareness of the mode affordances and their combinations can lead to improved performances; (b) higher reliance on the visual modes can compensate for verbal deficiencies; and (c) effective speakers tend to use a variety of modes that often overlap but work together to convey specific meanings. However, firm conclusions cannot be drawn on the basis of workshop presentations, and further studies on the multimodal analysis of ‘real conferences’ within specific disciplines are encouraged.