Associations of the second-to-fourth digit ratio (2D:4D), a putative marker for prenatal androgen action, and of absolute finger length, a putative marker for pubertal-adolescent androgen action, with sport performance were examined in a multinational sample of 87 world-class women epee fencers. Lower (masculinized) digit ratios correlated, although not significantly so, with better current and highest past world rankings. These correlations were significant for right-hand 2D:4D with controls for the most salient factors for 2D:4D (ethnicity) and world rankings (years of international experience, height, and weight). Longer (masculinized) fingers correlated strongly with better current and highest past world rankings; these correlations became insignificant with the same controls. Replicating previous evidence for fencers, left-handedness was much more prevalent in this sample (21%) than in the female general population, and left-handers had somewhat, but not significantly so, lower 2D:4D as well as better world rankings than right-handers. These findings extend related evidence suggestive of prenatal programming of aptitude across a variety of sports, especially running and soccer. Some known extragenital effects of prenatal testosterone that contribute to the development of efficient cardiovascular systems, good visuospatial abilities, physical endurance and speed, and to the propensity for rough-and-tumble play, apparently promote sporting success in adult life.

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This is the author’s version of a work that was accepted for publication in Computer Speech and Language. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computer Speech and Language, 28, 3 (2015) DOI: 10.1016/j.csl.2013.10.003One of the aims of Assistive Technologies is to help people with disabilities to communicate with others and to provide means of access to information. As an aid to Deaf people, we present in this work a production-quality rule-based machine system for translating from Spanish to Spanish Sign Language (LSE) glosses, which is a necessary precursor to building a full machine translation system that eventually produces animation output. The system implements a transfer-based architecture from the syntactic functions of dependency analyses. A sketch of LSE is also presented. Several topics regarding translation to sign languages are addressed: the lexical gap, the bootstrapping of a bilingual lexicon, the generation of word order for topic-oriented languages, and the treatment of classifier predicates and classifier names. The system has been evaluated with an open-domain testbed, reporting a 0.30 BLEU (BiLingual Evaluation Understudy) and 42% TER (Translation Error Rate). These results show consistent improvements over a statistical machine translation baseline, and some improvements over the same system preserving the word order in the source sentence. Finally, the linguistic analysis of errors has identified some differences due to a certain degree of structural variation in LSE

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DSLRAE is a hierarchical classifier for similar written languages and varieties based on maximum-entropy (maxent) classifiers. In the first level, the text is classified into a language group using a simple token-based maxent classifier. At the second level, a group-specific maxent classifier is applied to classify the text as one of the languages or varieties within the previously identified group. For each group of languages, the classifier uses a different kind and combination of knowledge-poor features: token or character n-grams and 'white lists' of tokens. Features were selected according to the results of applying ten-fold cross-validation over the training dataset. The system presented in this article 1 has been ranked second in the Discriminating Similar Language (DSL) shared task co-located within the VarDial Workshop at COLING 2014 .

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