931 resultados para Non Maternal Language


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Prenatal diagnosis is traditionally made via invasive procedures such as amniocentesis and chorionic villus sampling (CVS). However, both procedures carry a risk of complications, including miscarriage. Many groups have spent years searching for a way to diagnose a chromosome aneuploidy without putting the fetus or the mother at risk for complications. Non-invasive prenatal testing (NIPT) for chromosome aneuploidy became commercially available in the fall of 2011, with detection rates similar to those of invasive procedures for the common autosomal aneuploidies (Palomaki et al., 2011; Ashoor et al. 2012; Bianchi et al. 2012). Eventually NIPT may become the diagnostic standard of care and reduce invasive procedure-related losses (Palomaki et al., 2011). The integration of NIPT into clinical practice has potential to revolutionize prenatal diagnosis; however, it also raises some crucial issues for practitioners. Now that the test is clinically available, no studies have looked at the physicians that will be ordering the testing or referring patients to practitioners who do. This study aimed to evaluate the attitudes of OB/GYN’s and how they are incorporating the test into clinical practice. Our study shows that most physicians are offering this new, non-invasive technology to their patients, and that their practices were congruent with the literature and available professional society opinions. Those physicians who do not offer NIPT to their patients would like more literature on the topic as well as instructive guidelines from their professional societies. Additionally, this study shows that the practices and attitudes of MFMs and OBs differ. Our population feels that the incorporation of NIPT will change their practices by lowering the amount of invasive procedures, possibly replacing maternal serum screening, and that it will simplify prenatal diagnosis. However, those physicians who do not offer NIPT to their patients are not quite sure how the test will affect their clinical practice. From this study we are able to glean how physicians are incorporating this new technology into their practice and how they feel about the addition to their repertoire of tests. This knowledge gives insight as to how to best move forward with the quickly changing field of prenatal diagnosis.

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Birth defects are a leading cause of infant mortality in the United States. About one in 33 births in the United States is diagnosed with birth defects. Common birth defects include neural tube defects, Down syndrome and oral clefts. The present study focused on oral clefts. ^ Oral clefts refer to the malformation of lip, mouth or both. Birth prevalence of oral clefts in Texas is about 11 per 10,000 births. Etiologically, oral clefts have been classified into two groups, cleft lip with or without cleft palate (CL±P) and isolated cleft palate (CP). In spite of their high prevalence and clinical significance, the etiology of oral clefts in humans has not been well understood. Though a number of risk factors have been identified in epidemiological studies, most of them do not explain the majority of the cases. The need to identify novel risk factors associated with oral clefts provided the motivation for this study. The present study focused on maternal exposure to several hazardous air pollutants. A common subgroup of hazardous air pollutants is the volatile organic compounds found in petroleum derivatives. Four important hydrocarbons in this group are benzene, toluene, ethyl benzene and xylenes (BTEX). ^ The specific aim of this study was to evaluate the association between maternal exposure to environmental levels of BTEX and oral clefts among offspring in Texas for the period 1999-2008. ^ A case-control study design was used to assess if maternal exposure to BTEX increased the risk of oral clefts. The Texas Birth Defects Registry provided data on cases of non-syndromic oral clefts delivered in Texas during the period 1999-2008. Census tract level maternal exposure to BTEX concentrations were obtained from the Hazardous Air Pollutant Exposure Model (HAPEM) developed by the U.S. Environmental Protection Agency. Unconditional logistic regression was used to assess the relationship between maternal exposure to BTEX levels and risk of oral clefts in offspring. ^ In the selected population, mothers who had high estimated exposure to any of the BTEX compounds were not more likely to deliver an offspring with oral clefts. Future research efforts will focus on additional birth defects and thorough assessment of additional potential confounders.^

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Hispanics form the second-largest minority group in the United States totaling 22 million people. Health data on this population are sparse and inconsistent. This study seeks to determine use of preventative services and risk factor behaviors of Mexican American and non-Hispanic White females residing in South Texas.^ Baseline data from female respondents in household surveys in six South Texas counties (Ramirez and McAlister, 1988; McAlister et al., 1992) were analyzed to test the following hypotheses: (1) Mexican American and Non-Hispanic White females exhibit different patterns of health behaviors; (2) Mexican American females will exhibit different health behaviors regardless of age; and (3) the differences between Mexican American women and non-Hispanic White females are due to education and acculturation factors.^ Over the past decade, the traditional behaviors of Mexican American females have begun to change due to education, acculturation, and their participation in the labor force. The results from this study identify some of the changes that will require immediate attention from health care providers. Results revealed that regardless of ethnicity, age, education, and language preference, non-Hispanic White females were significantly more likely to participate in preventive screening practices than were Mexican American females. Risk factor analysis revealed a different pattern with Mexican American females significantly more likely to be non-smokers, non-alcoholic drinkers, and to have good fat avoidance practices compared to non-Hispanic White females. However, compared to those who are less-educated or Spanish-speaking, Mexican American females with higher levels of education and preference for speaking English only showed positive and negative health behaviors that were more similar to the non-Hispanic White females. The positive health behaviors that come with acculturation, e.g., more participation in preventive care and more physical activity, are welcome changes. But this study has implications for global health development and reinforces a need for "primordial" prevention strategies to deter the unwanted concomitants of economic development and acculturation. Smoking and drinking behaviors among Mexican American females need to be kept at low levels to prevent increased morbidity and premature deaths in this population. ^

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This paper describes a preprocessing module for improving the performance of a Spanish into Spanish Sign Language (Lengua de Signos Espanola: LSE) translation system when dealing with sparse training data. This preprocessing module replaces Spanish words with associated tags. The list with Spanish words (vocabulary) and associated tags used by this module is computed automatically considering those signs that show the highest probability of being the translation of every Spanish word. This automatic tag extraction has been compared to a manual strategy achieving almost the same improvement. In this analysis, several alternatives for dealing with non-relevant words have been studied. Non-relevant words are Spanish words not assigned to any sign. The preprocessing module has been incorporated into two well-known statistical translation architectures: a phrase-based system and a Statistical Finite State Transducer (SFST). This system has been developed for a specific application domain: the renewal of Identity Documents and Driver's License. In order to evaluate the system a parallel corpus made up of 4080 Spanish sentences and their LSE translation has been used. The evaluation results revealed a significant performance improvement when including this preprocessing module. In the phrase-based system, the proposed module has given rise to an increase in BLEU (Bilingual Evaluation Understudy) from 73.8% to 81.0% and an increase in the human evaluation score from 0.64 to 0.83. In the case of SFST, BLEU increased from 70.6% to 78.4% and the human evaluation score from 0.65 to 0.82.

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This paper proposes the use of Factored Translation Models (FTMs) for improving a Speech into Sign Language Translation System. These FTMs allow incorporating syntactic-semantic information during the translation process. This new information permits to reduce significantly the translation error rate. This paper also analyses different alternatives for dealing with the non-relevant words. The speech into sign language translation system has been developed and evaluated in a specific application domain: the renewal of Identity Documents and Driver’s License. The translation system uses a phrase-based translation system (Moses). The evaluation results reveal that the BLEU (BiLingual Evaluation Understudy) has improved from 69.1% to 73.9% and the mSER (multiple references Sign Error Rate) has been reduced from 30.6% to 24.8%.

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This paper describes a categorization module for improving the performance of a Spanish into Spanish Sign Language (LSE) translation system. This categorization module replaces Spanish words with associated tags. When implementing this module, several alternatives for dealing with non-relevant words have been studied. Non-relevant words are Spanish words not relevant in the translation process. The categorization module has been incorporated into a phrase-based system and a Statistical Finite State Transducer (SFST). The evaluation results reveal that the BLEU has increased from 69.11% to 78.79% for the phrase-based system and from 69.84% to 75.59% for the SFST.

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Andorra-I is the first implementation of a language based on the Andorra Principie, which states that determinate goals can (and shonld) be run before other goals, and even in a parallel fashion. This principie has materialized in a framework called the Basic Andorra model, which allows or-parallelism as well as (dependent) and-parallelism for determinate goals. In this report we show that it is possible to further extend this model in order to allow general independent and-parallelism for nondeterminate goals, withont greatly modifying the underlying implementation machinery. A simple an easy way to realize such an extensión is to make each (nondeterminate) independent goal determinate, by using a special "bagof" constract. We also show that this can be achieved antomatically by compile-time translation from original Prolog programs. A transformation that fulfüls this objective and which can be easily antomated is presented in this report.

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We discuss a framework for the application of abstract interpretation as an aid during program development, rather than in the more traditional application of program optimization. Program validation and detection of errors is first performed statically by comparing (partial) specifications written in terms of assertions against information obtained from (global) static analysis of the program. The results of this process are expressed in the user assertion language. Assertions (or parts of assertions) which cannot be checked statically are translated into run-time tests. The framework allows the use of assertions to be optional. It also allows using very general properties in assertions, beyond the predefined set understandable by the static analyzer and including properties defined by user programs. We also report briefly on an implementation of the framework. The resulting tool generates and checks assertions for Prolog, CLP(R), and CHIP/CLP(fd) programs, and integrates compile-time and run-time checking in a uniform way. The tool allows using properties such as types, modes, non-failure, determinacy, and computational cost, and can treat modules separately, performing incremental analysis.

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We describe some of the novel aspects and motivations behind the design and implementation of the Ciao multiparadigm programming system. An important aspect of Ciao is that it provides the programmer with a large number of useful features from different programming paradigms and styles, and that the use of each of these features can be turned on and off at will for each program module. Thus, a given module may be using e.g. higher order functions and constraints, while another module may be using objects, predicates, and concurrency. Furthermore, the language is designed to be extensible in a simple and modular way. Another important aspect of Ciao is its programming environment, which provides a powerful preprocessor (with an associated assertion language) capable of statically finding non-trivial bugs, verifying that programs comply with specifications, and performing many types of program optimizations. Such optimizations produce code that is highly competitive with other dynamic languages or, when the highest levéis of optimization are used, even that of static languages, all while retaining the interactive development environment of a dynamic language. The environment also includes a powerful auto-documenter. The paper provides an informal overview of the language and program development environment. It aims at illustrating the design philosophy rather than at being exhaustive, which would be impossible in the format of a paper, pointing instead to the existing literature on the system.

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We present a framework for the application of abstract interpretation as an aid during program development, rather than in the more traditional application of program optimization. Program validation and detection of errors is first performed statically by comparing (partial) specifications written in terms of assertions against information obtained from static analysis of the program. The results of this process are expressed in the user assertion language. Assertions (or parts of assertions) which cannot be verified statically are translated into run-time tests. The framework allows the use of assertions to be optional. It also allows using very general properties in assertions, beyond the predefined set understandable by the static analyzer and including properties defined by means of user programs. We also report briefly on an implementation of the framework. The resulting tool generates and checks assertions for Prolog, CLP(R), and CHIP/CLP(fd) programs, and integrates compile-time and run-time checking in a uniform way. The tool allows using properties such as types, modes, non-failure, determinacy, and computational cost, and can treat modules separately, performing incremental analysis. In practice, this modularity allows detecting statically bugs in user programs even if they do not contain any assertions.

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This paper introduces a semantic language developed with the objective to be used in a semantic analyzer based on linguistic and world knowledge. Linguistic knowledge is provided by a Combinatorial Dictionary and several sets of rules. Extra-linguistic information is stored in an Ontology. The meaning of the text is represented by means of a series of RDF-type triples of the form predicate (subject, object). Semantic analyzer is one of the options of the multifunctional ETAP-3 linguistic processor. The analyzer can be used for Information Extraction and Question Answering. We describe semantic representation of expressions that provide an assessment of the number of objects involved and/or give a quantitative evaluation of different types of attributes. We focus on the following aspects: 1) parametric and non-parametric attributes; 2) gradable and non-gradable attributes; 3) ontological representation of different classes of attributes; 4) absolute and relative quantitative assessment; 5) punctual and interval quantitative assessment; 6) intervals with precise and fuzzy boundaries

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Background: Early and effective identification of developmental disorders during childhood remains a critical task for the international community. The second highest prevalence of common developmental disorders in children are language delays, which are frequently the first symptoms of a possible disorder. Objective: This paper evaluates a Web-based Clinical Decision Support System (CDSS) whose aim is to enhance the screening of language disorders at a nursery school. The common lack of early diagnosis of language disorders led us to deploy an easy-to-use CDSS in order to evaluate its accuracy in early detection of language pathologies. This CDSS can be used by pediatricians to support the screening of language disorders in primary care. Methods: This paper details the evaluation results of the ?Gades? CDSS at a nursery school with 146 children, 12 educators, and 1 language therapist. The methodology embraces two consecutive phases. The first stage involves the observation of each child?s language abilities, carried out by the educators, to facilitate the evaluation of language acquisition level performed by a language therapist. Next, the same language therapist evaluates the reliability of the observed results. Results: The Gades CDSS was integrated to provide the language therapist with the required clinical information. The validation process showed a global 83.6% (122/146) success rate in language evaluation and a 7% (7/94) rate of non-accepted system decisions within the range of children from 0 to 3 years old. The system helped language therapists to identify new children with potential disorders who required further evaluation. This process will revalidate the CDSS output and allow the enhancement of early detection of language disorders in children. The system does need minor refinement, since the therapists disagreed with some questions from the CDSS knowledge base (KB) and suggested adding a few questions about speech production and pragmatic abilities. The refinement of the KB will address these issues and include the requested improvements, with the support of the experts who took part in the original KB development. Conclusions: This research demonstrated the benefit of a Web-based CDSS to monitor children?s neurodevelopment via the early detection of language delays at a nursery school. Current next steps focus on the design of a model that includes pseudo auto-learning capacity, supervised by experts.

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Providing descriptions of isolated sensors and sensor networks in natural language, understandable by the general public, is useful to help users find relevant sensors and analyze sensor data. In this paper, we discuss the feasibility of using geographic knowledge from public databases available on the Web (such as OpenStreetMap, Geonames, or DBpedia) to automatically construct such descriptions. We present a general method that uses such information to generate sensor descriptions in natural language. The results of the evaluation of our method in a hydrologic national sensor network showed that this approach is feasible and capable of generating adequate sensor descriptions with a lower development effort compared to other approaches. In the paper we also analyze certain problems that we found in public databases (e.g., heterogeneity, non-standard use of labels, or rigid search methods) and their impact in the generation of sensor descriptions.

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Acknowledgements This article was based on the first author’s PhD which was financed by the Malawi Health Research Capacity Strengthening Initiative. We thank Mr Patrick Naphini formerly of the Ministry of Health and Mrs Mafase Sesani at CHAM Secretariat for helping with the data. We also thank Mr Jacob Mazalale for useful comments on the article.

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When we use a proper name, by virtue of what do we succeed in saying something about an individual? In other words, how are we supposed to explain the seemingly trivial fact that by uttering “Aristotle was wise” we actually predicate something of the famous philosopher? Questions like these have animated a fervent debate among philosophers of language; however, nowadays the standard answer is that by using “Aristotle” we say something about that famous philosopher because the name we have used in our utterance refers to him. Even though no general consensus has been reached on how to characterize the relation of reference – there are still different and competing accounts of the latter on the philosophical market – almost everybody believes, especially after the publication of Saul Kripke’s "Naming and necessity", that reference is the only semantic relation that connects our uses of proper names to individuals in the world. Contrary to this widespread assumption, in this dissertation I shall claim that our uses of proper names are not always referential.