Context effects in second language acquisition : formal instruction, study abroad and immersion classrooms

Introduction to the volum

Hybrid Approach Combining Machine Learning and a Rule-Based Expert System for Text Categorization

This paper discusses a novel hybrid approach for text categorization that combines a machine learning algorithm, which provides a base model trained with a labeled corpus, with a rule-based expert system, which is used to improve the results provided by the previous classifier, by filtering false positives and dealing with false negatives. The main advantage is that the system can be easily fine-tuned by adding specific rules for those noisy or conflicting categories that have not been successfully trained. We also describe an implementation based on k-Nearest Neighbor and a simple rule language to express lists of positive, negative and relevant (multiword) terms appearing in the input text. The system is evaluated in several scenarios, including the popular Reuters-21578 news corpus for comparison to other approaches, and categorization using IPTC metadata, EUROVOC thesaurus and others. Results show that this approach achieves a precision that is comparable to top ranked methods, with the added value that it does not require a demanding human expert workload to trai

Método híbrido para categorización de texto basado en aprendizaje y reglas

En este artículo se presenta un nuevo método híbrido de categorización automática de texto, que combina un algoritmo de aprendizaje computacional, que permite construir un modelo base de clasificación sin mucho esfuerzo a partir de un corpus etiquetado, con un sistema basado en reglas en cascada que se emplea para filtrar y reordenar los resultados de dicho modelo base. El modelo puede afinarse añadiendo reglas específicas para aquellas categorías difíciles que no se han entrenado de forma satisfactoria. Se describe una implementación realizada mediante el algoritmo kNN y un lenguaje básico de reglas basado en listas de términos que aparecen en el texto a clasificar. El sistema se ha evaluado en diferentes escenarios incluyendo el corpus de noticias Reuters-21578 para comparación con otros enfoques, y los modelos IPTC y EUROVOC. Los resultados demuestran que el sistema obtiene una precisión y cobertura comparables con las de los mejores métodos del estado del arte

Generación automática de reglas de categorización de texto en un método híbrido basado en aprendizaje

En este artículo se evalúan diferentes técnicas para la generación automática de reglas que se emplean en un método híbrido de categorización automática de texto. Este método combina un algoritmo de aprendizaje computacional con diferentes sistemas basados en reglas en cascada empleados para el filtrado y reordenación de los resultados proporcionados por dicho modelo base. Aquí se describe una implementación realizada mediante el algoritmo kNN y un lenguaje básico de reglas basado en listas de términos que aparecen en el texto a clasificar. Para la evaluación se utiliza el corpus de noticias Reuters-21578. Los resultados demuestran que los métodos de generación de reglas propuestos producen resultados muy próximos a los obtenidos con la aplicación de reglas generadas manualmente y que el sistema híbrido propuesto obtiene una precisión y cobertura comparables a la de los mejores métodos del estado del arte

Automatic generation of text categorization rules in a hybrid method based on machine learning

En este artículo se evalúan diferentes técnicas para la generación automática de reglas que se emplean en un método híbrido de categorización automática de texto. Este método combina un algoritmo de aprendizaje computacional con diferentes sistemas basados en reglas en cascada empleados para el filtrado y reordenación de los resultados proporcionados por dicho modelo base. Aquí se describe una implementación realizada mediante el algoritmo kNN y un lenguaje básico de reglas basado en listas de términos que aparecen en el texto a clasificar. Para la evaluación se utiliza el corpus de noticias Reuters-21578. Los resultados demuestran que los métodos de generación de reglas propuestos producen resultados muy próximos a los obtenidos con la aplicación de reglas generadas manualmente y que el sistema híbrido propuesto obtiene una precisión y cobertura comparables a la de los mejores métodos del estado del arte.This paper discusses several techniques for the automatic generation of rules to be used in a novel hybrid method for text categorization. This approach combines a machine learning algorithm along with a different rule-based expert systems in cascade used to filter and re-rank the output of the base model provided by the previous classifier. This paper describes an implementation based on kNN algorithm and a basic rule language that expresses lists of terms appearing in the text. The popular Reuters-21578 news corpus is used for testing. Results show that the proposed methods for automatic rule generation achieve precision values that are very similar to the ones achieved by manually defined rule sets, and that this hybrid approach achieves a precision that is comparable to other top state-of-the-art methods.Esta investigación ha sido parcialmente financiada por los proyectos de I+D BUSCAMEDIA (CEN-20091026), MULTIMEDICA (TIN2010-20644-C03-01) y BRAVO (TIN2007-67407-C03-01)

Generación de materiales y recursos para la implantación del Plan de Lenguas para la Internacionalización PLI en la Facultad de Óptica y Optometría

Depto. de Optometría y VisiónFac. de Óptica y OptometríaFALSEsubmitte

The recent neophyte Opuntia aurantiaca (Cactaceae): distribution and potential invasion in the Iberian Peninsula

The Cactaceae, and especially its most emblematic genus, Opuntia, is one of the groups of plants with greater invasion potential in the Iberian Peninsula. One of the most recently detected species is Opuntia aurantiaca, a small cactus with an enormous capacity of dispersion. Probably native to Argentina and Uruguay, it behaves as a very aggressive invader in Australia and South Africa. In Europe, it only occurs on the Mediterranean coast of the Iberian Peninsula (Catalonia and Valencian Community). In this study, the geographic range of the species is accurately delineated at the peninsular level. Detected firstly at the beginning of the last decade in Navajas (Castelló Province), it has been subsequently observed in other places of Castelló, but also in Valencia, Tarragona and Barcelona, and since 2017 in Girona. With all gathered occurrence data, the potential distribution of O. aurantiaca is estimated (for the current climatic conditions as well as for different scenarios of global warming). Despite the fact that the species seems to be spreading, maps of potential distribution do not forecast large expansions to other areas of the Iberian Peninsula, both for the present and for the year 2070.This work received financial support from the “Proyecto Intramural Especial, PIE” (grant no. 201630I024) from the CSIC (Spain) and from the “Ajuts a Grups de Recerca Consolidats” (grants nos. 2014-SGR514-GREB and 2017-SGR1116) from the Generalitat de Catalunya (Spain).Abstract Introduction Materials & methods The study species Search for occurrences Ecological niche modelling Results and Discussion Current distribution range of Opuntia aurantiaca in the Iberian Peninsula Present and future potential distribution of Opuntia aurantiaca Acknowledgement

DNA vaccine based on conserved HA-peptides induces strong immune response and rapidly clears influenza virus infection from vaccinated pigs

Swine influenza virus (SIVs) infections cause a significant economic impact to the pork industry. Moreover, pigs may act as mixing vessel favoring genome reassortment of diverse influenza viruses. Such an example is the pandemic H1N1 (pH1N1) virus that appeared in 2009, harboring a combination of gene segments from avian, pig and human lineages, which rapidly reached pandemic proportions. In order to confront and prevent these possible emergences as well as antigenic drift phenomena, vaccination remains of vital importance. The present work aimed to evaluate a new DNA influenza vaccine based on distinct conserved HA-peptides fused with flagellin and applied together with Diluvac Forte as adjuvant using a needle-free device (IntraDermal Application of Liquids, IDAL®). Two experimental pig studies were performed to test DNAvaccine efficacy against SIVs in pigs. In the first experiment, SIV-seronegative pigs were vaccinated with VC4-flagellin DNA and intranasally challenged with a pH1N1. In the second study, VC4-flagellin DNA vaccine was employed in SIV-seropositive animals and challenged intranasally with an H3N2 SIV-isolate. Both experiments demonstrated a reduction in the viral shedding after challenge, suggesting vaccine efficacy against both the H1 and H3 influenza virus subtypes. In addition, the results proved that maternally derived antibodies (MDA) did not constitute an obstacle to the vaccine approach used. Moreover, elevated titers in antibodies both against H1 and H3 proteins in serum and in bronchoalveolar lavage fluids (BALFs) was detected in the vaccinated animals along with a markedly increased mucosal IgA response. Additionally, vaccinated animals developed stronger neutralizing antibodies in BALFs and higher inhibiting hemagglutination titers in sera against both the pH1N1 and H3N2 influenza viruses compared to unvaccinated, challenged-pigs. It is proposed that the described DNA-vaccine formulation could potentially be used as a multivalent vaccine against SIV infections.info:eu-repo/semantics/publishedVersio

DNA vaccine based on conserved HA-peptides induces strong immune response and rapidly clears influenza virus infection from vaccinated pigs

This work was funded in part by the Spanish Government, Ministerio de Econom?a y Competitividad de España (MINECO), project: AGL2013-48923-C2-2-R, and by the collaborative infrastructure project funded by the European Comission (EC) under Horizon 2020, project Transvac2-730964-INFRAIA-2016-1. IRTA is supported by CERCA Programme/ Generalitat de Catalunya. M.S.O. is supported by MINECO (scholarship n BES-2014-068506). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Swine influenza virus (SIVs) infections cause a significant economic impact to the pork industry. Moreover, pigs may act as mixing vessel favoring genome reassortment of diverse influenza viruses. Such an example is the pandemic H1N1 (pH1N1) virus that appeared in 2009, harboring a combination of gene segments from avian, pig and human lineages, which rapidly reached pandemic proportions. In order to confront and prevent these possible emergences as well as antigenic drift phenomena, vaccination remains of vital importance. The present work aimed to evaluate a new DNA influenza vaccine based on distinct conserved HA-peptides fused with flagellin and applied together with Diluvac Forte as adjuvant using a needle-free device (IntraDermal Application of Liquids, IDAL®). Two experimental pig studies were performed to test DNA-vaccine efficacy against SIVs in pigs. In the first experiment, SIV-seronegative pigs were vaccinated with VC4-flagellin DNA and intranasally challenged with a pH1N1. In the second study, VC4-flagellin DNA vaccine was employed in SIV-seropositive animals and challenged intranasally with an H3N2 SIV-isolate. Both experiments demonstrated a reduction in the viral shedding after challenge, suggesting vaccine efficacy against both the H1 and H3 influenza virus subtypes. In addition, the results proved that maternally derived antibodies (MDA) did not constitute an obstacle to the vaccine approach used. Moreover, elevated titers in antibodies both against H1 and H3 proteins in serum and in bronchoalveolar lavage fluids (BALFs) was detected in the vaccinated animals along with a markedly increased mucosal IgA response. Additionally, vaccinated animals developed stronger neutralizing antibodies in BALFs and higher inhibiting hemagglutination titers in sera against both the pH1N1 and H3N2 influenza viruses compared to unvaccinated, challenged-pigs. It is proposed that the described DNA-vaccine formulation could potentially be used as a multivalent vaccine against SIV infections