44 resultados para Applied Linguistics


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This research investigates the phenomenon of translationese in two monolingual comparable corpora of original and translated Catalan texts. Translationese has been defined as the dialect, sub-language or code of translated language. This study aims at giving empirical evidence of translation universals regardless the source language.Traditionally, research conducted on translation strategies has been mainly intuition-based. Computational Linguistics and Natural Language Processing techniques provide reliable information of lexical frequencies, morphological and syntactical distribution in corpora. Therefore, they have been applied to observe which translation strategies occur in these corpora.Results seem to prove the simplification, interference and explicitation hypotheses, whereas no sign of normalization has been detected with the methodology used.The data collected and the resources created for identifying lexical, morphological and syntactic patterns of translations can be useful for Translation Studies teachers, scholars and students: teachers will have more tools to help students avoid the reproduction of translationese patterns. Resources developed will help in detecting non-genuine or inadequate structures in the target language. This fact may imply an improvement in stylistic quality in translations. Translation professionals can also take advantage of these resources to improve their translation quality.

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In spite of its relative importance in the economy of many countriesand its growing interrelationships with other sectors, agriculture has traditionally been excluded from accounting standards. Nevertheless, to support its Common Agricultural Policy, for years the European Commission has been making an effort to obtain standardized information on the financial performance and condition of farms. Through the Farm Accountancy Data Network (FADN), every year data are gathered from a rotating sample of 60.000 professional farms across all member states. FADN data collection is not structured as an accounting cycle but as an extensive questionnaire. This questionnaire refers to assets, liabilities, revenues and expenses, and seems to try to obtain a "true and fair view" of the financial performance and condition of the farms it surveys. However, the definitions used in the questionnaire and the way data is aggregated often appear flawed from an accounting perspective. The objective of this paper is to contrast the accounting principles implicit in the FADN questionnaire with generally accepted accounting principles, particularly those found in the IVth Directive of the European Union, on the one hand, and those recently proposed by the International Accounting Standards Committee’s Steering Committeeon Agriculture in its Draft Statement of Principles, on the other hand. There are two reasons why this is useful. First, it allows to make suggestions how the information provided by FADN could be more in accordance with the accepted accounting framework, and become a more valuable tool for policy makers, farmers, and other stakeholders. Second, it helps assessing the suitability of FADN to become the starting point for a European accounting standard on agriculture.

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We consider two fundamental properties in the analysis of two-way tables of positive data: the principle of distributional equivalence, one of the cornerstones of correspondence analysis of contingency tables, and the principle of subcompositional coherence, which forms the basis of compositional data analysis. For an analysis to be subcompositionally coherent, it suffices to analyse the ratios of the data values. The usual approach to dimension reduction in compositional data analysis is to perform principal component analysis on the logarithms of ratios, but this method does not obey the principle of distributional equivalence. We show that by introducing weights for the rows and columns, the method achieves this desirable property. This weighted log-ratio analysis is theoretically equivalent to spectral mapping , a multivariate method developed almost 30 years ago for displaying ratio-scale data from biological activity spectra. The close relationship between spectral mapping and correspondence analysis is also explained, as well as their connection with association modelling. The weighted log-ratio methodology is applied here to frequency data in linguistics and to chemical compositional data in archaeology.

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This research provides a description of the process followed in order to assemble a "Social Accounting Matrix" for Spain corresponding to the year 2000 (SAMSP00). As argued in the paper, this process attempts to reconcile ESA95 conventions with requirements of applied general equilibrium modelling. Particularly, problems related to the level of aggregation of net taxation data, and to the valuation system used for expressing the monetary value of input-output transactions have deserved special attention. Since the adoption of ESA95 conventions, input-output transactions have been preferably valued at basic prices, which impose additional difficulties on modellers interested in computing applied general equilibrium models. This paper addresses these difficulties by developing a procedure that allows SAM-builders to change the valuation system of input-output transactions conveniently. In addition, this procedure produces new data related to net taxation information.

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This research provides a description of the process followed in order to assemble a "Social Accounting Matrix" for Spain corresponding to the year 2000 (SAMSP00). As argued in the paper, this process attempts to reconcile ESA95 conventions with requirements of applied general equilibrium modelling. Particularly, problems related to the level of aggregation of net taxation data, and to the valuation system used for expressing the monetary value of input-output transactions have deserved special attention. Since the adoption of ESA95 conventions, input-output transactions have been preferably valued at basic prices, which impose additional difficulties on modellers interested in computing applied general equilibrium models. This paper addresses these difficulties by developing a procedure that allows SAM-builders to change the valuation system of input-output transactions conveniently. In addition, this procedure produces new data related to net taxation information.

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Background Obesity may have an impact on key aspects of health-related quality of life (HRQOL). In this context, the Impact of Weight Quality of Life (IWQOL) questionnaire was the first scale designed to assess HRQOL. The aim of the present study was twofold: to assess HRQOL in a sample of Spanish patients awaiting bariatric surgery and to determine the psychometric properties of the IWQOL-Lite and its sensitivity to detect differences in HRQOL across groups. Methods Participants were 109 obese adult patients (BMI¿ 35 kg/m2) from Barcelona, to whom the following measurement instruments were applied: IWQOL-Lite, Depression Anxiety Stress Scales, Brief Symptom Inventory, and self-perception items. Results Descriptive data regarding the IWQOL-Lite scores obtained by these patients are reported. Principal components analysis revealed a five-factor model accounting for 72.05% of the total variance, with factor loadings being adequate for all items. Corrected itemtotal correlations were acceptable for all items. Cronbach"s alpha coefficients were excellent both for the subscales (0.880.93) and the total scale (0.95). The relationship between the IWQOLLite and other variables supports the construct validity of the scale. Finally, sensitivity analysis revealed large effect sizes when comparing scores obtained by extreme BMI groups. Conclusions This is the first study to report the application of the IWQOL-Lite to a sample of Spanish patients awaiting bariatric surgery and to confirm that the Spanish version of the instrument has adequate psychometric properties.

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Bone metastases are the result of a primary cancer invasion which spreads into the bone marrow through the lymphogenous or hematogenous pathways. Bone metastases are a common complication of cancer.The primary cancers that most frequently metastasize to bone are breast and prostate cancer (65 - 75 %) amongst many others (thyroid 42 %, lung 36 % or kidney 35 %) (Suva et al., 2011). Although the exact incidence of bone metastases is unknown given its dependence on the type of primary cancer, it is estimated that 350,000 people die of bone metastases annually in the United States.

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Excitation-continuous music instrument control patterns are often not explicitly represented in current sound synthesis techniques when applied to automatic performance. Both physical model-based and sample-based synthesis paradigmswould benefit from a flexible and accurate instrument control model, enabling the improvement of naturalness and realism. Wepresent a framework for modeling bowing control parameters inviolin performance. Nearly non-intrusive sensing techniques allow for accurate acquisition of relevant timbre-related bowing control parameter signals.We model the temporal contour of bow velocity, bow pressing force, and bow-bridge distance as sequences of short Bézier cubic curve segments. Considering different articulations, dynamics, and performance contexts, a number of note classes are defined. Contours of bowing parameters in a performance database are analyzed at note-level by following a predefined grammar that dictates characteristics of curve segment sequences for each of the classes in consideration. As a result, contour analysis of bowing parameters of each note yields an optimal representation vector that is sufficient for reconstructing original contours with significant fidelity. From the resulting representation vectors, we construct a statistical model based on Gaussian mixtures suitable for both the analysis and synthesis of bowing parameter contours. By using the estimated models, synthetic contours can be generated through a bow planning algorithm able to reproduce possible constraints caused by the finite length of the bow. Rendered contours are successfully used in two preliminary synthesis frameworks: digital waveguide-based bowed stringphysical modeling and sample-based spectral-domain synthesis.

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The aim of this work was the identification of new metabolites and transformation products (TPs) in chicken muscle from Enrofloxacin (ENR), Ciprofloxacin (CIP), Difloxacin (DIF) and Sarafloxacin (SAR), which are antibiotics that belong to the fluoroquinolones family. The stability of ENR, CIP, DIF and SAR standard solutions versus pH degradation process (from pH 1.5 to 8.0, simulating the pH since the drug is administered until its excretion) and freeze-thawing (F/T) cycles was tested. In addition, chicken muscle samples from medicated animals with ENR were analyzed in order to identify new metabolites and TPs. The identification of the different metabolites and TPs was accomplished by comparison of mass spectral data from samples and blanks, using liquid chromatography coupled to quadrupole time-of-flight (LC-QqToF) and Multiple Mass Defect Filter (MMDF) technique as a pre-filter to remove most of the background noise and endogenous components. Confirmation and structure elucidation was performed by liquid chromatography coupled to linear ion trap quadrupole Orbitrap (LC-LTQ-Orbitrap), due to its mass accuracy and MS/MS capacity for elemental composition determination. As a result, 21 TPs from ENR, 6 TPs from CIP, 14 TPs from DIF and 12 TPs from SAR were identified due to the pH shock and F/T cycles. On the other hand, 14 metabolites were identified from the medicated chicken muscle samples. Formation of CIP and SAR, from ENR and DIF, respectively, and the formation of desethylene-quinolone were the most remarkable identified compounds.

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The performance of high resolution accurate mass spectrometry (HRMS) operating in full scan MS mode was investigated for the quantitative determination of amoxicillin (AMX) as well as qualitative analysis of metabolomic profiles in tissues of medicated chickens. The metabolomic approach was exploited to compile analytical information on changes in the metabolome of muscle, kidney and liver from chickens subjected to a pharmacological program with AMX. Data consisting of m/z features taken throughout the entire chromatogram were extracted and filtered to be treated by Principal Component Analysis. As a result, it was found that medicated and non-treated animals were clearly clustered in distinct groups. Besides, the multivariate analysis revealed some relevant mass features contributing to this separation. In this context, recognizing those potential markers of each chicken class was a priority research for both metabolite identification and, obviously, evaluation of food quality and health effects associated to food consumption.

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The aim of this work was the identification of new metabolites and transformation products (TPs) in chicken muscle from Enrofloxacin (ENR), Ciprofloxacin (CIP), Difloxacin (DIF) and Sarafloxacin (SAR), which are antibiotics that belong to the fluoroquinolones family. The stability of ENR, CIP, DIF and SAR standard solutions versus pH degradation process (from pH 1.5 to 8.0, simulating the pH since the drug is administered until its excretion) and freeze-thawing (F/T) cycles was tested. In addition, chicken muscle samples from medicated animals with ENR were analyzed in order to identify new metabolites and TPs. The identification of the different metabolites and TPs was accomplished by comparison of mass spectral data from samples and blanks, using liquid chromatography coupled to quadrupole time-of-flight (LC-QqToF) and Multiple Mass Defect Filter (MMDF) technique as a pre-filter to remove most of the background noise and endogenous components. Confirmation and structure elucidation was performed by liquid chromatography coupled to linear ion trap quadrupole Orbitrap (LC-LTQ-Orbitrap), due to its mass accuracy and MS/MS capacity for elemental composition determination. As a result, 21 TPs from ENR, 6 TPs from CIP, 14 TPs from DIF and 12 TPs from SAR were identified due to the pH shock and F/T cycles. On the other hand, 14 metabolites were identified from the medicated chicken muscle samples. Formation of CIP and SAR, from ENR and DIF, respectively, and the formation of desethylene-quinolone were the most remarkable identified compounds.