Discriminating languages in bilingual contexts: the impact of orthographic markedness

Does language-specific orthography help language detection and lexical access in naturalistic bilingual contexts? This study investigates how L2 orthotactic properties influence bilingual language detection in bilingual societies and the extent to which it modulates lexical access and single word processing. Language specificity of naturalistically learnt L2 words was manipulated by including bigram combinations that could be either L2 language-specific or common in the two languages known by bilinguals. A group of balanced bilinguals and a group of highly proficient but unbalanced bilinguals who grew up in a bilingual society were tested, together with a group of monolinguals (for control purposes). All the participants completed a speeded language detection task and a progressive demasking task. Results showed that the use of the information of orthotactic rules across languages depends on the task demands at hand, and on participants' proficiency in the second language. The influence of language orthotactic rules during language detection, lexical access and word identification are discussed according to the most prominent models of bilingual word recognition.

Introducing mobile edge computing capabilities through distributed 5G Cloud Enabled Small Cells

Current trends in broadband mobile networks are addressed towards the placement of different capabilities at the edge of the mobile network in a centralised way. On one hand, the split of the eNB between baseband processing units and remote radio headers makes it possible to process some of the protocols in centralised premises, likely with virtualised resources. On the other hand, mobile edge computing makes use of processing and storage capabilities close to the air interface in order to deploy optimised services with minimum delay. The confluence of both trends is a hot topic in the definition of future 5G networks. The full centralisation of both technologies in cloud data centres imposes stringent requirements to the fronthaul connections in terms of throughput and latency. Therefore, all those cells with limited network access would not be able to offer these types of services. This paper proposes a solution for these cases, based on the placement of processing and storage capabilities close to the remote units, which is especially well suited for the deployment of clusters of small cells. The proposed cloud-enabled small cells include a highly efficient microserver with a limited set of virtualised resources offered to the cluster of small cells. As a result, a light data centre is created and commonly used for deploying centralised eNB and mobile edge computing functionalities. The paper covers the proposed architecture, with special focus on the integration of both aspects, and possible scenarios of application.

Processing Facilitation Strategies in OV and VO Languages: A Corpus Study

The present corpus study aimed to examine whether Basque (OV) resorts more often than Spanish (VO) to certain grammatical operations, in order to minimi ze the number of arguments to be processed before the verb. Ueno & Polinsky (2009) argue that VO/OV languages use certain grammatical resources with different frequencies in order to facilitate real-time processing. They observe that both OV and VO languages in their sample (Japanese, Turkish and Spanish) have a similar frequency of use of subject pro-drop; however, they find that OV languages (Japanese, Turkish) use more intransitive sentences than VO languages (English, Spanish), and conclude this is an OV-specific strategy to facilitate processing. We conducted a comparative corpus study of Spanish (VO) and Basque (OV). Results show (a) that the fre- quency of use of subject pro-drop is higher in Basque than in Spanish; and (b) Basque does not use more intransitive sentences than Spanish; both languages have a similar frequency of intransitive sentences. Based on these findings, we conclude that the frequency of use of grammatical resources to facilitate the processing does not depend on a single typological trait (VO/OV) but it is modulated by the concurrence of other grammatical feature.

Adaptive Scalable SVD Unit for Fast Processing of Large LSE Problems

Singular Value Decomposition (SVD) is a key linear algebraic operation in many scientific and engineering applications. In particular, many computational intelligence systems rely on machine learning methods involving high dimensionality datasets that have to be fast processed for real-time adaptability. In this paper we describe a practical FPGA (Field Programmable Gate Array) implementation of a SVD processor for accelerating the solution of large LSE problems. The design approach has been comprehensive, from the algorithmic refinement to the numerical analysis to the customization for an efficient hardware realization. The processing scheme rests on an adaptive vector rotation evaluator for error regularization that enhances convergence speed with no penalty on the solution accuracy. The proposed architecture, which follows a data transfer scheme, is scalable and based on the interconnection of simple rotations units, which allows for a trade-off between occupied area and processing acceleration in the final implementation. This permits the SVD processor to be implemented both on low-cost and highend FPGAs, according to the final application requirements.

Efficient Synthesis of Single-Chain Polymer Nanoparticles via Amide Formation

Single-chain technology (SCT) allows the transformation of individual polymer chains to folded/collapsed unimolecular soft nanoparticles. In this work we contribute to the enlargement of the SCT toolbox by demonstrating the efficient synthesis of single-chain polymer nanoparticles (SCNPs) via intrachain amide formation. In particular, we exploit cross-linking between active methylene groups and isocyanate moieties as powerful "click" chemistry driving force for SCNP construction. By employing poly(methyl methacrylate)- (PMMA-) based copolymers bearing beta-ketoester units distributed randomly along the copolymer chains and bifunctional isocyanate cross-linkers, SCNPs were successfully synthesized at r.t. under appropriate reaction conditions. Characterization of the resulting SCNPs was carried out by means of a combination of techniques including size exclusion chromatography (SEC), infrared (IR) spectroscopy, proton nuclear magnetic resonance (H-1 NMR) spectroscopy, dynamic light scattering (DLS), and elemental analysis (EA).