Transfer from implicit to explicit phonological abilities in first and second language learners

Children's abilities to process the phonological structure of words are important predictors of their literacy development. In the current study, we examined the interrelatedness between implicit (i.e., speech decoding) and explicit (i.e., phonological awareness) phonological abilities, and especially the role therein of lexical specificity (i.e., the ability to learn to recognize spoken words based on only minimal acoustic-phonetic differences). We tested 75 Dutch monolingual and 64 Turkish–Dutch bilingual kindergartners. SEM analyses showed that speech decoding predicted lexical specificity, which in turn predicted rhyme awareness in the first language learners but phoneme awareness in the second language learners. Moreover, in the latter group there was an impact of the second language: Dutch speech decoding and lexical specificity predicted Turkish phonological awareness, which in turn predicted Dutch phonological awareness. We conclude that language-specific phonological characteristics underlie different patterns of transfer from implicit to explicit phonological abilities in first and second language learners

Lexical specificity training effects in second language learners

Children who start formal education in a second language may experience slower vocabulary growth in that language and subsequently experience disadvantages in literacy acquisition. The current study asked whether lexical specificity training can stimulate bilingual children's phonological awareness, which is considered to be a precursor to literacy. Therefore, Dutch monolingual and Turkish-Dutch bilingual children were taught new Dutch words with only minimal acoustic-phonetic differences. As a result of this training, the monolingual and the bilingual children improved on phoneme blending, which can be seen as an early aspect of phonological awareness. During training, the bilingual children caught up with the monolingual children on words with phonological overlap between their first language Turkish and their second language Dutch. It is concluded that learning minimal pair words fosters phoneme awareness, in both first and second language preliterate children, and that for second language learners phonological overlap between the two languages positively affects training outcomes, likely due to linguistic transfe

Contextual Richness and Word Learning: Context Enhances Comprehension but Retrieval Enhances Retention

Learning new vocabulary from context typically requires multiple encounters during which word meaning can be retrieved from memory or inferred from context. We compared the effect of memory retrieval and context inferences on short‐ and long‐term retention in three experiments. Participants studied novel words and then practiced the words either in an uninformative context that required the retrieval of word meaning from memory (“I need the funguo”) or in an informative context from which word meaning could be inferred (“I want to unlock the door: I need the funguo”). The informative context facilitated word comprehension during practice. However, later recall of word form and meaning and word recognition in a new context were better after successful retrieval practice and retrieval practice with feedback than after context‐inference practice. These findings suggest benefits of retrieval during contextualized vocabulary learning whereby the uninformative context enhanced word retention by triggering memory retrieval

Functional kernel estimators of conditional extreme quantiles

We address the estimation of "extreme" conditional quantiles i.e. when their order converges to one as the sample size increases. Conditions on the rate of convergence of their order to one are provided to obtain asymptotically Gaussian distributed kernel estimators. A Weissman-type estimator and kernel estimators of the conditional tail-index are derived, permitting to estimate extreme conditional quantiles of arbitrary order.Comment: arXiv admin note: text overlap with arXiv:1107.226

Peaks Over Thresholds Modeling With Multivariate Generalized Pareto Distributions

When assessing the impact of extreme events, it is often not just a single component, but the combined behavior of several components which is important. Statistical modeling using multivariate generalized Pareto (GP) distributions constitutes the multivariate analogue of univariate peaks over thresholds modeling, which is widely used in finance and engineering. We develop general methods for construction of multivariate GP distributions and use them to create a variety of new statistical models. A censored likelihood procedure is proposed to make inference on these models, together with a threshold selection procedure, goodness-of-fit diagnostics, and a computationally tractable strategy for model selection. The models are fitted to returns of stock prices of four UK-based banks and to rainfall data in the context of landslide risk estimation. Supplementary materials and codes are available online

An SPR based sensor for allergens detection

A simple, sensitive and label-free optical sensor method was developed for allergens analysis using α-casein as the biomarker for cow's milk detection, to be used directly in final rinse samples of cleaning in place systems (CIP) of food manufacturers. A Surface Plasmon Resonance (SPR) sensor chip consisting of four sensing arrays enabling the measurement of samples and control binding events simultaneously on the sensor surface was employed in this work. SPR offers several advantages in terms of label free detection, real time measurements and superior sensitivity when compared to ELISA based techniques. The gold sensor chip was used to immobilise α-casein-polyclonal antibody using EDC/NHS coupling procedure. The performance of the assay and the sensor was first optimised and characterised in pure buffer conditions giving a detection limit of 58 ng mL−1 as a direct binding assay. The assay sensitivity can be further improved by using sandwich assay format and amplified with nanoparticles. However, at this stage this is not required as the detection limit achieved exceeded the required allergens detection levels of 2 µg mL−1 for α-S1-casein. The sensor demonstrated good selectivity towards the α-casein as the target analyte and adequate recoveries from CIP final rinse wash samples. The sensor would be useful tool for monitoring allergen levels after cleaning procedures, providing additional data that may better inform upon wider food allergen risk management decision(s) that are made by food manufacturer. In particular, this sensor could potentially help validate or optimise cleaning practices for a given food manufacturing process

High-Speed Optical Characterization of Protein-and-Nanoparticle–Stabilized Microbubbles for Ultrasound-Triggered Drug Release

Objective: Ultrasound-triggered bubble-mediated local drug delivery has shown potential to increase therapeutic efficacy and reduce systemic side effects, by loading drugs into the microbubble shell and triggering delivery of the payload on demand using ultrasound. Understanding the behavior of the microbubbles in response to ultrasound is crucial for efficient and controlled release. Methods: In this work, the response of microbubbles with a coating consisting of poly(2-ethyl-butyl cyanoacrylate) (PEBCA) nanoparticles and denatured casein was characterized. High-speed recordings were taken of single microbubbles, in both bright field and fluorescence. Results: The nanoparticle-loaded microbubbles show resonance behavior, but with a large variation in response, revealing a substantial interbubble variation in mechanical shell properties. The probability of shell rupture and the probability of nanoparticle release were found to strongly depend on microbubble size, and the most effective size was inversely proportional to the driving frequency. The probabilities of both rupture and release increased with increasing driving pressure amplitude. Rupture of the microbubble shell occurred after fewer cycles of ultrasound as the driving pressure amplitude or driving frequency was increased. Conclusion: The results highlight the importance of careful selection of the driving frequency, driving pressure amplitude and duration of ultrasound to achieve the most efficient ultrasound-triggered shell rupture and nanoparticle release of protein-and-nanoparticle–stabilized microbubbles.</p

Fluid-structure interaction simulation of prosthetic aortic valves : comparison between immersed boundary and arbitrary Lagrangian-Eulerian techniques for the mesh representation

In recent years the role of FSI (fluid-structure interaction) simulations in the analysis of the fluid-mechanics of heart valves is becoming more and more important, being able to capture the interaction between the blood and both the surrounding biological tissues and the valve itself. When setting up an FSI simulation, several choices have to be made to select the most suitable approach for the case of interest: in particular, to simulate flexible leaflet cardiac valves, the type of discretization of the fluid domain is crucial, which can be described with an ALE (Arbitrary Lagrangian-Eulerian) or an Eulerian formulation. The majority of the reported 3D heart valve FSI simulations are performed with the Eulerian formulation, allowing for large deformations of the domains without compromising the quality of the fluid grid. Nevertheless, it is known that the ALE-FSI approach guarantees more accurate results at the interface between the solid and the fluid. The goal of this paper is to describe the same aortic valve model in the two cases, comparing the performances of an ALE-based FSI solution and an Eulerian-based FSI approach. After a first simplified 2D case, the aortic geometry was considered in a full 3D set-up. The model was kept as similar as possible in the two settings, to better compare the simulations' outcomes. Although for the 2D case the differences were unsubstantial, in our experience the performance of a full 3D ALE-FSI simulation was significantly limited by the technical problems and requirements inherent to the ALE formulation, mainly related to the mesh motion and deformation of the fluid domain. As a secondary outcome of this work, it is important to point out that the choice of the solver also influenced the reliability of the final results