928 resultados para Immediate serial recall


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In June 1995 a case-control study was initiated by the Texas Department of Health among Mexican American women residing in the fourteen counties of the Texas-Mexico border. Case-women had carried infants with neural tube defect. Control-women had given birth to infants without neural tube defects. The case-control protocol included a general questionnaire which elicited information regarding illnesses experienced and antibiotics taken from three months prior to conception to three months after conception. An assessment of the associations between periconceptional diarrhea and the risk of neural tube defects indicated that the unadjusted association of diarrhea and risk of neural tube defect was significant (OR = 3.3, CI = 1.4–7.6). The unadjusted association of use of oral antimicrobials and risk of neural tube defect was also significant (OR = 3.4, CI = 1.6–7.3). These associations persisted among women who had no fever during the periconceptional period and were present irrespective of folate intake. Diarrhea was associated with an increased risk of NTD independent of use of antimicrobials. The converse was also true; antimicrobials were associated with an increased risk of NTD independent of diarrhea. Further research regarding these potentially modifiable risk factors is warranted. Replication of these findings could result in interventions in addition to folate supplementation. ^

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The Blood Pressure Study in Mexican Children (BPSMC) is a short term longitudinal study of serial blood pressure collected in three observation periods by standardized examinations of 233 female children, 10 to 12 years of age, enrolled in public and private primary schools in Tlalpan, Mexico. Study objectives were: (1) to describe from baseline information the distribution and relationship of blood pressure to age and selected anthropometric factors, as well as to compare the BPSMC results with other blood pressure studies, (2) to examine the sources and amount of variation present in serial blood pressure of 123 children, and (3) to evaluate observer performance by means of intra- and inter-observer variability.^ Stepwise regression results from baseline revealed that of all anthropometric factors and age, weight was the best predictor for blood pressure.^ The results of serial blood pressure measurements show that, besides the known sources of blood pressure variability (subject, day, reading), the physiologic event of menarche has an important bearing upon the variability and characterization of blood pressure in young girls. The assessment of the effects of blood pressure variability and reliability upon the design and analysis of epidemiologic studies, became apparent among post-menarcheal girls; where blood pressure measurements taken from them have low reliability. Research is needed to propose alternatives for assessing blood pressure during puberty.^ Finally, observer performance of blood pressure and anthropometry were evaluated. Anthropometric measurements had reliabilities in excess of R = 0.96. Acceptable reliabilities (R = 0.88 to 0.95) were obtained for systolic and diastolic (phase 4 and 5) blood pressures. The BPSMC showed a 50 percent decrease in measurement error from the first to the third observation periods. ^

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This study examined the effects of skipping breakfast on selected aspects of children's cognition, specifically their memory (both immediate and one week following presentation of stimuli), mental tempo, and problem solving accuracy. Test instruments used included the Hagen Central/Incidental Recall Test, Matching Familiar Figures Test, McCarthy Digit Span and Tapping Tests. The study population consisted of 39 nine-to eleven year old healthy children who were admitted for overnight stays at a clinical research setting for two nights approximately one week apart. The study was designed to be able to adequately monitor and control subjects' food consumption. The design chosen was the cross-over design where randomly on either the first or second visit, the child skipped breakfast. In this way, subjects acted as their own controls. Subjects were tested at noon of both visits, this representing an 18-hour fast.^ Analysis focused on whether or not fasting for this period of time affected an individual's performance. Results indicated that for most of the tests, subjects were not significantly affected by skipping breakfast for one morning. However, on tests of short-term central and incidental recall, subjects who had skipped breakfast recalled significantly more of the incidental cues although they did so at no apparent expense to their storing of central information. In the area of problem-solving accuracy, subjects skipping breakfast at time two made significantly more errors on hard sections of the MFF Test. It should be noted that although a large number of tests were conducted, these two tests showed the only significant differences.^ These significant results in the areas of short-term incidental memory and in problem solving accuracy were interpreted as being an effect of subject fatigue. That is, when subjects missed breakfast, they were more likely to become fatigued and in the novel environment presented in the study setting, it is probable that these subjects responded by entering Class II fatigue which is characterized by behavioral excitability, diffused attention and altered performance patterns. ^

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This paper presents a theoretical analysis and an optimization method for envelope amplifier. Highly efficient envelope amplifiers based on a switching converter in parallel or series with a linear regulator have been analyzed and optimized. The results of the optimization process have been shown and these two architectures are compared regarding their complexity and efficiency. The optimization method that is proposed is based on the previous knowledge about the transmitted signal type (OFDM, WCDMA...) and it can be applied to any signal type as long as the envelope probability distribution is known. Finally, it is shown that the analyzed architectures have an inherent efficiency limit.

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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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Objectives The study sought to evaluate the ability of cardiac magnetic resonance (CMR) to monitor acute and long-term changes in pulmonary vascular resistance (PVR) noninvasively. Background PVR monitoring during the follow-up of patients with pulmonary hypertension (PH) and the response to vasodilator testing require invasive right heart catheterization. Methods An experimental study in pigs was designed to evaluate the ability of CMR to monitor: 1) an acute increase in PVR generated by acute pulmonary embolization (n = 10); 2) serial changes in PVR in chronic PH (n = 22); and 3) changes in PVR during vasodilator testing in chronic PH (n = 10). CMR studies were performed with simultaneous hemodynamic assessment using a CMR-compatible Swan-Ganz catheter. Average flow velocity in the main pulmonary artery (PA) was quantified with phase contrast imaging. Pearson correlation and mixed model analysis were used to correlate changes in PVR with changes in CMR-quantified PA velocity. Additionally, PVR was estimated from CMR data (PA velocity and right ventricular ejection fraction) using a formula previously validated. Results Changes in PA velocity strongly and inversely correlated with acute increases in PVR induced by pulmonary embolization (r = –0.92), serial PVR fluctuations in chronic PH (r = –0.89), and acute reductions during vasodilator testing (r = –0.89, p ≤ 0.01 for all). CMR-estimated PVR showed adequate agreement with invasive PVR (mean bias –1.1 Wood units,; 95% confidence interval: –5.9 to 3.7) and changes in both indices correlated strongly (r = 0.86, p < 0.01). Conclusions CMR allows for noninvasive monitoring of acute and chronic changes in PVR in PH. This capability may be valuable in the evaluation and follow-up of patients with PH.

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LINCOLN UNIVERSITY - On March 25, 1965, a bus loaded with Lincoln University students and staff arrived in Montgomery, Ala. to join the Selma march for racial and voting equality. Although the Civil Rights Act of 1964 was in force, African-Americans continued to feel the effects of segregation. The 1960s was a decade of social unrest and change. In the Deep South, specifically Alabama, racial segregation was a cultural norm resistant to change. Governor George Wallace never concealed his personal viewpoints and political stance of the white majority, declaring “Segregation now, segregation tomorrow, segregation forever.” The march was aimed at obtaining African-Americans their constitutionally protected right to vote. However, Alabama’s deep-rooted culture of racial bias began to be challenged by a shift in American attitudes towards equality. Both black and whites wanted to end discrimination by using passive resistance, a movement utilized by Dr. Martin Luther King Jr. That passive resistance was often met with violence, sometimes at the hands of law enforcement and local citizens. The Selma to Montgomery march was a result of a protest for voting equality. The Student Nonviolent Coordinating Committee (SNCC) and the Southern Christian Leadership Counsel (SCLC) among other students marched along the streets to bring awareness to the voter registration campaign, which was organized to end discrimination in voting based on race. Violent acts of police officers and others were some of the everyday challenges protesters were facing. Forty-one participants from Lincoln University arrived in Montgomery to take part in the 1965 march for equality. Students from Lincoln University’s Journalism 383 class spent part of their 2015 spring semester researching the historical event. Here are their stories: Peter Kellogg “We’ve been watching the television, reading about it in the newspapers,” said Peter Kellogg during a February 2015 telephone interview. “Everyone knew the civil rights movement was going on, and it was important that we give him (Robert Newton) some assistance … and Newton said we needed to get involve and do something,” Kellogg, a lecturer in the 1960s at Lincoln University, discussed how the bus trip originated. “That’s why the bus happened,” Kellogg said. “Because of what he (Newton) did - that’s why Lincoln students went and participated.” “People were excited and the people along the sidewalk were supportive,” Kellogg said. However, the mood flipped from excited to scared and feeling intimidated. “It seems though every office building there was a guy in a blue uniform with binoculars standing in the crowd with troops and police. And if looks could kill me, we could have all been dead.” He says the hatred and intimidation was intense. Kellogg, being white, was an immediate target among many white people. He didn’t realize how dangerous the event in Alabama was until he and the others in the bus heard about the death of Viola Liuzzo. The married mother of five from Detroit was shot and killed by members of the Ku Klux Klan while shuttling activists to the Montgomery airport. “We found out about her death on the ride back,” Kellogg recalled. “Because it was a loss of life, and it shows the violence … we could have been exposed to that danger!” After returning to LU, Kellogg’s outlook on life took a dramatic turn. Kellogg noted King’s belief that a person should be willing to die for important causes. “The idea is that life is about something larger and more important than your own immediate gratification, and career success or personal achievements,” Kellogg said. “The civil rights movement … it made me, it made my life more significant because it was about something important.” The civil rights movement influenced Kellogg to change his career path and to become a black history lecturer. Until this day, he has no regrets and believes that his choices made him as a better individual. The bus ride to Alabama, he says, began with the actions of just one student. Robert Newton Robert Newton was the initiator, recruiter and leader of the Lincoln University movement to join Dr. Martin Luther King’s march in Selma. “In the 60s much of the civil rights activists came out of college,” said Newton during a recent phone interview. Many of the events that involved segregation compelled college students to fight for equality. “We had selected boycotts of merchants, when blacks were not allowed to try on clothes,” Newton said. “You could buy clothes at department stores, but no blacks could work at the department stores as sales people. If you bought clothes there you couldn’t try them on, you had to buy them first and take them home and try them on.” Newton said the students risked their lives to be a part of history and influence change. He not only recognized the historic event of his fellow Lincolnites, but also recognized other college students and historical black colleges and universities who played a vital role in history. “You had the S.N.C.C organization, in terms of voting rights and other things, including a lot of participation and working off the bureau,” Newton said. Other schools and places such as UNT, Greenville and Howard University and other historically black schools had groups that came out as leaders. Newton believes that much has changed from 50 years ago. “I think we’ve certainly come a long way from what I’ve seen from the standpoint of growing up outside of Birmingham, Alabama,” Newton said. He believes that college campuses today are more organized in their approach to social causes. “The campus appears to be some more integrated amongst students in terms of organizations and friendships.” Barbara Flint Dr. Barbara Flint grew up in the southern part of Arkansas and came to Lincoln University in 1961. She describes her experience at Lincoln as “being at Lincoln when the world was changing.“ She was an active member of Lincoln’s History Club, which focused on current events and issues and influenced her decision to join the Selma march. “The first idea was to raise some money and then we started talking about ‘why can’t we go?’ I very much wanted to be a living witness in history.” Reflecting on the march and journey to Montgomery, Flint describes it as being filled with tension. “We were very conscious of the fact that once we got on the road past Tennessee we didn’t know what was going to happen,” said Flint during a February 2015 phone interview. “Many of the students had not been beyond Missouri, so they didn’t have that sense of what happens in the South. Having lived there you knew the balance as well as what is likely to happen and what is not likely to happen. As my father use to say, ‘you have to know how to stay on that line of balance.’” Upon arriving in Alabama she remembers the feeling of excitement and relief from everyone on the bus. “We were tired and very happy to be there and we were trying to figure out where we were going to join and get into the march,” Flint said. “There were so many people coming in and then we were also trying to stay together; that was one of the things that really stuck out for me, not just for us but the people who were coming in. You didn’t want to lose sight of the people you came with.” Flint says she was keenly aware of her surroundings. For her, it was more than just marching forward. “I can still hear those helicopters now,” Flint recalled. “Every time the helicopters would come over the sound would make people jump and look up - I think that demonstrated the extent of the tenseness that was there at the time because the helicopters kept coming over every few minutes.” She said that the marchers sang “we are not afraid,” but that fear remained with every step. “Just having been there and being a witness and marching you realize that I’m one of those drops that’s going to make up this flood and with this flood things will move,” said Flint. As a student at Lincoln in 1965, Flint says the Selma experience undoubtedly changed her life. “You can’t expect to do exactly what you came to Lincoln to do,” Flint says. “That march - along with all the other marchers and the action that was taking place - directly changed the paths that I and many other people at Lincoln would take.” She says current students and new generations need to reflect on their personal role in society. “Decide what needs to be done and ask yourself ‘how can I best contribute to it?’” Flint said. She notes technology and social media can be used to reach audiences in ways unavailable to her generation in 1965. “So you don’t always have to wait for someone else to step out there and say ‘let’s march,’ you can express your vision and your views and you have the means to do so (so) others can follow you. Jaci Newsom Jaci Newsom came to Lincoln in 1965 from Atlanta. She came to Lincoln to major in sociology and being in Jefferson City was largely different from what she had grown up with. “To be able to come into a restaurant, sit down and be served a nice meal was eye-opening to me,” said Newsom during a recent interview. She eventually became accustomed to the relaxed attitude of Missouri and was shocked by the situation she encountered on an out-of-town trip. “I took a bus trip from Atlanta to Pensacola and I encountered the worse racism that I have ever seen. I was at bus stop, I went in to be served and they would not serve me. There was a policeman sitting there at the table and he told me that privately owned places could select not to serve you.” Newsom describes her experience of marching in Montgomery as being one with a purpose. “We felt as though we achieved something - we felt a sense of unity,” Newsom said. “We were very excited (because) we were going to hear from Martin Luther King. To actually be in the presence of him and the other civil rights workers there was just such enthusiasm and excitement yet there was also some apprehension of what we might encounter.” Many of the marchers showed their inspiration and determination while pressing forward towards the grounds of the Alabama Capitol building. Newsom recalled that the marchers were singing the lyrics “ain’t gonna let nobody turn me around” and “we shall overcome.” “ I started seeing people just like me,” Newsom said. “I don’t recall any of the scowling, the hitting, the things I would see on TV later. I just saw a sea of humanity marching towards the Capitol. I don’t remember what Martin Luther King said but it was always the same message: keep the faith; we’re going to get where we’re going and let us remember what our purpose is.” Newsom offers advice on what individuals can do to make their society a more productive and peaceful place. “We have come a long way and we have ways to change things that we did not have before,” Newsom said. “You need to work in positive ways to change.” Referencing the recent unrest in Ferguson, Mo., she believes that people become destructive as a way to show and vent anger. Her generation, she says, was raised to react in lawful ways – and believe in hope. “We have faith to do things in a way that was lawful and it makes me sad what people do when they feel without hope, and there is hope,” Newsom says. “Non-violence does work - we need to include everyone to make this world a better place.” Newsom graduated from Lincoln in 1969 and describes her experience at Lincoln as, “I grew up and did more growing at Lincoln than I think I did for the rest of my life.”

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