Un análisis descriptivo de la traducción de los dialectos geográficos y sociales italianos al castellano: el caso de Il cane di terracotta de Andrea Camilleri

El éxito internacional de Andrea Camilleri, escritor siciliano cuyas novelas están caracterizadas por la presencia del dialecto, ha fomentado el debate sobre la posibilidad de traducir textos caracterizados por la presencia de variación lingüística. Esta cuestión ha sido tratada de forma marginal por la traductología y, a menudo, los estudiosos han abogado por la supresión de las marcas dialectales en las traducciones. Un análisis del sistema lingüístico italiano y de su literatura, sin embargo, no puede prescindir del estudio de los dialectos y de las variedades regionales, cuya presencia es todavía muy fuerte. El presente trabajo se centra en un análisis descriptivo, de tipo cualitativo y cuantitativo, de las réplicas de tres personajes de la novela de Camilleri Il cane di terracotta en la versión original y en su traducción al castellano. Este estudio, suportado por la descripción del marco teórico en el que se inscribe el tema de la variación lingüística, nos permite, en primer lugar, evaluar el peso de la presencia de marcas de dialecto geográfico y social en el texto original y trazar la compleja relación existente entre lengua nacional, dialectos y variedades regionales en Italia. En segundo lugar, a través del análisis de la versión en castellano podremos verificar si existe una supresión considerable de las marcas dialectales en la traducción

L'evasione di Pietro e la morte del tiranno. Echi Intertestuali in At 12

(Résumé de l'ouvrage) Una raccolta di studi con cui l'Associazione Biblica Italiana e le EDB intendono onorare la memoria di mons. Fusco, vescovo di Nardò-Gallipoli e illustre biblista. Il volume segue gli ambiti di interesse che hanno caratterizzato la sua ricerca e vede il contributo di insigni studiosi italiani e stranieri.

Skin permeation and metabolism of di(2-ethylhexyl) phthalate (DEHP).

Phthalates are suspected to be endocrine disruptors. Di(2-ethylhexyl) phthalate (DEHP) is assumed to have low dermal absorption; however, previous in vitro skin permeation studies have shown large permeation differences. Our aims were to determine DEHP permeation parameters and assess extent of skin DEHP metabolism among workers highly exposed to these lipophilic, low volatile substances. Surgically removed skin from patients undergoing abdominoplasty was immediately dermatomed (800 μm) and mounted on flow-through diffusion cells (1.77 cm(2)) operating at 32°C with cell culture media (aqueous solution) as the reservoir liquid. The cells were dosed either with neat DEHP or emulsified in aqueous solution (166 μg/ml). Samples were analysed by HPLC-MS/MS. DEHP permeated human viable skin only as the metabolite MEHP (100%) after 8h of exposure. Human skin was able to further oxidize MEHP to 5-oxo-MEHP. Neat DEHP applied to the skin hardly permeated skin while the aqueous solution readily permeated skin measured in both cases as concentration of MEHP in the receptor liquid. DEHP pass through human skin, detected as MEHP only when emulsified in aqueous solution, and to a far lesser degree when applied neat to the skin. Using results from older in vitro skin permeation studies with non-viable skin may underestimate skin exposures. Our results are in overall agreement with newer phthalate skin permeation studies.

Discrete time Non-homogeneous Semi-Markov Processes applied to Models for Disability Insurance

In this paper, we present a stochastic model for disability insurance contracts. The model is based on a discrete time non-homogeneous semi-Markov process (DTNHSMP) to which the backward recurrence time process is introduced. This permits a more exhaustive study of disability evolution and a more efficient approach to the duration problem. The use of semi-Markov reward processes facilitates the possibility of deriving equations of the prospective and retrospective mathematical reserves. The model is applied to a sample of contracts drawn at random from a mutual insurance company.

MAMOT: hidden Markov modeling tool.

Hidden Markov models (HMMs) are probabilistic models that are well adapted to many tasks in bioinformatics, for example, for predicting the occurrence of specific motifs in biological sequences. MAMOT is a command-line program for Unix-like operating systems, including MacOS X, that we developed to allow scientists to apply HMMs more easily in their research. One can define the architecture and initial parameters of the model in a text file and then use MAMOT for parameter optimization on example data, decoding (like predicting motif occurrence in sequences) and the production of stochastic sequences generated according to the probabilistic model. Two examples for which models are provided are coiled-coil domains in protein sequences and protein binding sites in DNA. A wealth of useful features include the use of pseudocounts, state tying and fixing of selected parameters in learning, and the inclusion of prior probabilities in decoding. AVAILABILITY: MAMOT is implemented in C++, and is distributed under the GNU General Public Licence (GPL). The software, documentation, and example model files can be found at http://bcf.isb-sib.ch/mamot