Behavioural assessment impacts on the performance results

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Assessment of the carotid artery by MRI at 3T: a study on reproducibility

PURPOSE: To examine the reproducibility of carotid artery dimension measurements using 3T MRI. MATERIALS AND METHODS: Ten healthy volunteers underwent three scans on two occasions for assessment of total vessel wall area (TVWA), total luminal area (TLA), and minimum (MinT) and maximum (MaxT) vessel wall thickness. A double inversion-recovery (IR) fast gradient-echo (FGRE) sequence was used on a commercial 3T system. During the first visit the subjects were scanned twice. The third scan was performed at least four days later. One observer traced all scans, and a second observer retraced the first scan series. RESULTS: For TVWA an interclass correlation (ICC) of 0.994 was calculated with all three scans taken into account. The interobserver ICC was 0.984. The agreement between the scans for TLA showed an ICC of 0.982 with an interobserver ICC of 0.998. For MinT and MaxT an ICC of 0.843 and 0.935 were calculated, with interobserver ICCs of 0.860 and 0.726, respectively. CONCLUSION: With the use of a commercial 3T MR system, TVWA, TLA, and wall thickness measurements of the carotid artery can be assessed with good reproducibility.

Quality of care of patients hospitalized with congestive heart failure

Background: Congestive heart failure (CHF) is an increasingly prevalent poor-prognosis condition for which effective interventions are available. It is -therefore important to determine the extent to which patients with CHF receive appropriate care in Australian hospitals and identify ways for improving suboptimal care, if it exists. Aim: To evaluate the quality of in-hospital acute care of patients with CHF using explicit quality indicators based on published guidelines. Methods: A retrospective case note review was -performed, involving 216 patients admitted to three teaching hospitals in Brisbane, Queensland, Australia, between October 2000 and April 2001. Outcome measures were process-of-care quality -indicators calculated as proportions of all, or strongly -eligible (ideal), patients who received -specific interventions. Results: Assessment of underlying causes and acute precipitating factors was undertaken in 86% and 76% of patients, respectively, and objective evaluation of left ventricular function was performed in 62% of patients. Prophylaxis for deep venous thrombosis (DVT) was used in only 29% of ideal patients. Proportions of ideal patients receiving pharmacological treatments at discharge were: (i) angiotensin--converting enzyme inhibitors (ACEi) (82%), (ii) target doses of ACEi (61%), (iii) alternative vasodilators in patients ineligible for ACEi (20%), (iv) beta-blockers (40%) and (v) warfarin (46%). Conclusions: Opportunities exist for improving quality of in-hospital care of patients with CHF, -particularly for optimal prescribing of: (i) DVT prophylaxis, (ii) ACEi, (iii) second-line vasodilators, (iv) beta-blockers and (v) warfarin. More research is needed to identify methods for improving quality of in-hospital care.

Development of a Safety protocol for Management Thirst in the Immediate Postoperative Period

Objective To develop a safety protocol for the management of thirst in the immediate postoperative period. Method Quantitative, methodological, and applied study conducted in April-August 2012. An extensive literature search and expert consultation was carried out to develop the protocol and its operating manual. Theoretical and semantic analyzes were carried out by experts. Results Assessment of level of consciousness, reflexes of protection of the airways (cough and swallowing), and absence of nausea and vomiting were selected as safety criteria. These criteria were grouped and formatted in a graph algorithm, which indicates the need to interrupt the procedure if a security criterion does not reach the expected standard. Conclusion The protocol was elaborated to fill in the gap in the literature of a specific model concerning nursing actions in the safe management of thirst in the immediate postoperative period.

Profiling text comprehension impairments in aphasia

Background: Research in aphasia has focused on acquired dyslexias at the single word level, with a paucity of assessment techniques and rehabilitation approaches for individuals with difficulty at the text level. A rich literature from research with paediatric populations and healthy non-brain damaged, skilled adult readers allows the component processes that are important for text reading to be defined and more appropriate assessments to be devised. Aims: To assess the component processes of text reading in a small group of individuals with aphasia who report difficulties reading at the text level. Do assessments of component processes in reading comprehension reveal distinct profiles of text comprehension? To what extent are text comprehension difficulties caused by underlying linguistic and/or cognitive deficits? Methods & Procedures: Four individuals with mild aphasia who reported difficulties reading at the text level took part in a case-series study. Published assessments were used to confirm the presence of text comprehension impairment. Participants completed a range of assessments to provide a profile of their linguistic and cognitive skills, focusing on processes known to be important for text comprehension. We identified the following areas for assessment: reading speed, language skills (single word and sentence), inferencing, working memory and metacognitive skills (monitoring and strategy use). Outcomes & Results: Performance was compared against age-matched adult control data. One participant presented with a trend for impaired abilities in inferencing, with all other assessed skills being within normal limits. The other three had identified linguistic and working memory difficulties. One presented with a residual deficit in accessing single word meaning that affected text comprehension. The other two showed no clear link between sentence processing difficulties and text comprehension impairments. Across these three, data suggested a link between verbal working memory capacity and specific inferencing skills. Conclusions: Successful text reading relies on a number of component processes. In this paper we have made a start in defining those component processes and devising tasks suitable to assess them. From our results, assessment of verbal working memory and inferencing appears to be critical for understanding text comprehension impairments in aphasia. It is possible that rehabilitation input can capitalize on key meta-cognitive skills (monitoring, strategy use) to support functional reading in the face of existing linguistic, text comprehension and memory impairments.

Avaliação cefalométrica do perfil mole de pacientes face longa submetidos à cirurgia ortognática: estudo retrospectivo

OBJETIVO: o presente trabalho propôs-se a comparar o perfil tegumentar pós-operatório de pacientes Classe II, Padrão Face Longa, submetidos ao tratamento ortodôntico-cirúrgico, com os parâmetros descritos na análise cefalométrica de Legan e Burstone. METODOLOGIA: 32 telerradiografias pós-cirúrgicas, com um mínimo de 6 meses de acompanhamento, foram submetidas a traçado manual (repetido 4 vezes) e digitalização (também repetida 4 vezes) no programa DFPlus para análise cefalométrica. RESULTADOS: os resultados permitiram verificar que 9 das 11 medidas avaliadas encontravam-se estatisticamente diferentes da norma avaliada; contudo, ao se verificar o desvio padrão permitido na norma, os achados deste trabalho situam-se dentro da mesma, com exceção do ângulo mentocervical. CONCLUSÃO: as condições experimentais deste estudo permitiram concluir que, embora a população estudada tenha obtido resultados estéticos-funcionais satisfatórios, não se enquadrou nas normas da análise de Legan e Burstone, o que indica que a avaliação após a cirurgia ortognática deve ser principalmente clínica e que a estética facial não está totalmente relacionada com as medidas préestabelecidas na análise cefalométrica.

Location of single line-to-ground faults on distribution feeders using voltage measurements

This paper proposes a dedicated algorithm for lation of single line-to-ground faults in distribution systems. The proposed algorithm uses voltage and current phasors measured at the substation level, voltage magnitudes measured at some buses of the feeder, a database containing electrical, operational and topological parameters of the distribution networks, and fault simulation. Voltage measurements can be obtained using power quality devices already installed on the feeders or using voltage measurement devices dedicated for fault location. Using the proposed algorithm, likely faulted points that are located on feeder laterals geographically far from the actual faulted point are excluded from the results. Assessment of the algorithm efficiency was carried out using a 238 buses real-life distribution feeder. The results show that the proposed algorithm is robust for performing fast and efficient fault location for sustained single line-to-ground faults requiring less than 5% of the feeder buses to be covered by voltage measurement devices. © 2006 IEEE.

Avaliação cefalométrica do perfil mole de paciente face longa submetido à cirurgia ortognática: estudo retrospectivo

Pós-graduação em Odontologia - FOA

OntoTag - A Linguistic and Ontological Annotation Model Suitable for the Semantic Web

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).

An initial assessment of policies for saving a rare Australian glider: Experimental results, economics and ecology

Reviews the ecological status of the mahogany glider and describes its distribution, habitat and abundance, life history and threats to it. Three serial surveys of Brisbane residents provide data on the knowledge of respondents about the mahogany glider. The results provide information about the attitudes of respondents to the mahogany glider, to its conservation and relevant public policies and about variations in these factors as the knowledge of participants of the mahogany glider alters. Similarly data is provided and analysed about the willingness to pay of respondents to conserve the mahogany glider. Population viability analysis is applied to estimate the required habitat area for a minimum viable population of the mahogany glider to ensure at least a 95% probability of its survival for 100 years. Places are identified in Queensland where the requisite minimum area of critical habitat can be conserved. Using the survey results as a basis, the likely willingness of groups of Australians to pay for the conservation of the mahogany glider is estimated and consequently their willingness to pay for the minimum required area of its habitat. Methods for estimating the cost of protecting this habitat are outlined. Australia-wide benefits seem to exceed the costs. Establishing a national park containing the minimum viable population of the mahogany glider is an appealing management option. This would also be beneficial in conserving other endangered wildlife species. Therefore, additional economic benefits to those estimated on account of the mahogany glider itself can be obtained.

Using VISIR in a large undergraduate course: preliminary assessment results

The use of remote labs in undergraduate courses has been reported in literature several times since the mid 90's. Nevertheless, very few articles present results about the learning gains obtained by students using them, especially with a large number of students, thus suggesting a lack of data concerning their pedagogical effectiveness. This paper addresses such a gap by presenting some preliminary results concerning the use of a remote laboratory, known as VISIR, in a large undergraduate course on Applied Physics, with over 500 students enrolled.

External quality assessment in the voluntary counseling and testing centers in the Brazilian Amazon using dried tube specimens: results of an effectiveness evaluation

INTRODUCTION : In 2011, the Brazilian Ministry of Health rolled out a program for the external quality assessment of rapid human immunodeficiency virus (HIV) tests using the dried tube specimen (DTS) method (EQA-RT/DTS-HIV). Our objective was to evaluate the implementation of this program at 71 voluntary counseling and testing centers (VCTCs) in the Brazilian Legal Amazonian area one year after its introduction. METHODS : Quantitative and qualitative study that analyzed secondary data and interviews with healthcare workers (HCWs) (n=39) and VCTC coordinators (n=32) were performed. The assessment used 18 key indicators to evaluate the three dimensions of the program's logical framework: structure, process, and result. Each indicator was scored from 1-4, and the aggregate results corresponding to the dimensions were expressed as proportions. The results were compared to the perceptions of the HCWs and coordinators regarding the EQA-RT/DTS-HIV program. RESULTS: The aggregate scores for the three dimensions of structure, process, and result were 91.7%, 78.6%, and 95%, respectively. The lowest score in each dimension corresponded to a different indicator: access to Quali-TR online system 39% (structure), registration in Quali-TR online system 38.7% (process), and VCTC completed the full process in the program's first round 63.4% (result). Approximately 36% of the HCWs and 52% of the coordinators reported enhanced trust in the program for its rapid HIV testing performance. CONCLUSIONS: All three program dimensions exhibited satisfactory results (>75%). Nevertheless, the study findings highlight the need to improve certain program components. Additionally, long-term follow-ups is needed to provide a more thorough picture of the process for external quality assessment.