Correlating trainees' translating performance with the quality of their metacognitive self-evaluation

This paper presents a study of correlations between the performance of trainee translators, according to their teacher’s assessment, and the quality of their self-evaluation, according to their answers to metacognitive questionnaires. Two case-studies of two consecutive editions of a course in general translation from German into Spanish are dealt with. The course involved the use of post-translation metacognitive questionnaires designed to help trainees to evaluate their translating. A selection of the questionnaires (from the strongest and the weakest performances by students for each course edition) is considered. The study focuses on one item in these questionnaires that has to do with identifying translation problems and justifying their solutions. An interpretive analysis of the trainees’ answers for this questionnaire item reveals that the best-performing students were more strategically and translationally aware in self-evaluating their own translating. Our conclusions are based on considering six parameters from the analysis of the trainees’ answers, which are tentatively regarded as indicative of the quality of their self-evaluation.

Improving Pitch Tracking Performance in Hard Noise Conditions by a Preprocessing Based on Mathematical Morphology

In this paper we show how a nonlinear preprocessing of speech signal -with high noise- based on morphological filters improves the performance of robust algorithms for pitch tracking (RAPT). This result happens for a very simple morphological filter. More sophisticated ones could even improve such results. Mathematical morphology is widely used in image processing and has a great amount of applications. Almost all its formulations derived in the two-dimensional framework are easily reformulated to be adapted to one-dimensional context

New cationic nanovesicular systems containing lysine-based surfactants for topical administration: Toxicity assessment using representative skin cell lines

Many strategies for treating diseases require the delivery of drugs into the cell cytoplasm following internalization within endosomal vesicles. Thus, compounds triggered by low pH to disrupt membranes and release endosomal contents into the cytosol are of particular interest. Cationic nanovesicles have attracted considerable interest as effective carriers to improve the delivery of biologically active molecules into and through the skin. In this study, lipid-based nanovesicles containing three different cationic lysine-based surfactants were designed for topical administration. We used representative skin cell lines and in vitro assays to assess whether the cationic compounds modulate the toxic responses of these nanocarriers. The nanovesicles were characterized in both water and cell culture medium. In general, significant agglomeration occurred after 24 h incubation under cell culture conditions. We found different cytotoxic responses among the formulations, which depended on the surfactant,cell line (3T3, HaCaT, and THP-1) and endpoint assayed (MTT, NRU, and LDH). Moreover, no potential phototoxicity was detected in fibroblast or keratinocyte cells, whereas only a slight inflammatory response was induced, as detected by IL-1a and IL-8 production in HaCaT and THP-1 cell lines, respectively. A key finding of our research was that the cationic charge position and the alkyl chain length of the surfactants determine the nanovesicles resulting toxicity. The charge on the a-amino group of lysine increased the depletion of cell metabolic activity, as determined by the MTT assay, while a higher hydrophobicity tends to enhance the toxic responses of the nanovesicles. The insights provided here using different cell lines and assays offer a comprehensive toxicological evaluation of this group of new nanomaterials.

The use of flexible quantile-based measures in risk assessment

A new family of distortion risk measures -GlueVaR- is proposed in Belles- Sampera et al. -2013- to procure a risk assessment lying between those provided by common quantile-based risk measures. GlueVaR risk measures may be expressed as a combination of these standard risk measures. We show here that this relationship may be used to obtain approximations of GlueVaR measures for general skewed distribution functions using the Cornish-Fisher expansion. A subfamily of GlueVaR measures satisfies the tail-subadditivity property. An example of risk measurement based on real insurance claim data is presented, where implications of tail-subadditivity in the aggregation of risks are illustrated.

High-Performance-Tensile-Strength Alpha-Grass Reinforced Starch-Based Fully Biodegradable Composites

Though there has been a great deal of work concerning the development of natural fibers in reinforced starch-based composites, there is still more to be done. In general, cellulose fibers have lower strength than glass fibers; however, their specific strength is not far from that of fiberglass. In this work, alpha-fibers were obtained from alpha-grass through a mild cooking process. The fibers were used to reinforce a starch-based biopolymer. Composites including 5 to 35% (w/w) alpha-grass fibers in their formulation were prepared, tested, and subsequently compared with those of wood- and fiberglass-reinforced polypropylene (PP). The term “high-performance” refers to the tensile strength of the studied composites and is mainly due to a good interphase, a good dispersion of the fibers inside the matrix, and a good aspect ratio. The tensile strength of the composites showed a linear evolution for fiber contents up to 35% (w/w). The strain at break of the composites decreased with the fiber content and showed the stiffening effects of the reinforcement. The prepared composites showed high mechanical properties, even approaching those of glass fiber reinforced composites