Clitic-doubled left dislocation and focus fronting in L2 Spanish: a case of successful acquisition at the syntax-discourse interface

This experimental study tests the Interface Hypothesis by looking into processes at the syntax– discourse interface, teasing apart acquisition of syntactic, semantic and discourse knowledge. Adopting López’s (2009) pragmatic features [±a(naphor)] and [±c(ontrast)], which in combination account for the constructions of dislocation and fronting, we tested clitic left dislocation and fronted focus in the comprehension of English native speakers learning Spanish. Furthermore, we tested knowledge of an additional semantic property: the relationship between the discourse anaphor and the antecedent in clitic left dislocation (CLLD). This relationship is free: it can be subset, superset, part/whole. Syntactic knowledge of clitics was a condition for inclusion in the main test. Our findings indicate that all learners are sensitive to the semantic constraints. While the near-native speakers display native-like discourse knowledge, the advanced speakers demonstrated some discourse knowledge, and intermediate learners did not display any discourse knowledge. The findings support as well as challenge the Interface Hypothesis.

Gradient competence at the syntax-discourse interface

In this article, we present additional support of Duffield's (2003, 2005) distinction between Underlying Competence and Surface Competence. Duffield argues that a more fine-grained distinction between levels of competence and performance is warranted and necessary. While underlying competence is categorical, surface competence is more probabilistic and gradient, being sensitive to lexical and constructional contingencies, including the contextual appropriateness of a given construction. We examine a subset of results from a study comparing native and learner competence of properties at the syntax-discourse interface. Specifically, we look at the acceptability of Clitic Right Dislocation in native and L2 Spanish, in discourse-appropriate context. We argue that Duffield's distinction is a possible explanation of our results.

Pragmatic deficits with syntactic consequences?: L2 pronominal subjects and the syntax–pragmatics interface

Contemporary acquisition theorizing has placed a considerable amount of attention on interfaces, points at which different linguistic modules interact. The claim is that vulnerable interfaces cause particular difficulties in L1, bilingual and adult L2 acquisition (e.g. Platzack, 2001; Montrul, 2004; Müller and Hulk, 2001; Sorace, 2000, 2003, 2004, 2005). Accordingly, it is possible that deficits at the syntax–pragmatics interface cause what appears to be particular non-target-like syntactic behavior in L2 performance. This syntax-before-discourse hypothesis is examined in the present study by analyzing null vs. overt subject pronoun distribution in L2 Spanish of English L1 learners. As ultimately determined by L2 knowledge of the Overt Pronoun Constraint (OPC) (Montalbetti, 1984), the data indicate that L2 learners at the intermediate and advanced levels reset the Null Subject Parameter (NSP), but only advanced learners have acquired a more or less target null/overt subject distribution. Against the predictions of Sorace (2004) and in line with Montrul and Rodríguez-Louro (2006), the data indicate an overuse of both overt and null subject pronouns. As a result, this behavior cannot be from L1 interference alone, suggesting that interface-conditioned properties are simply more complex and therefore, harder to acquire. Furthermore, the data from the advanced learners demonstrate that the syntax–pragmatics interface is not a predetermined locus for fossilization (in contra e.g. Valenzuela, 2006).

Interface vulnerability and knowledge of the subjunctive/indicative distinction with negated epistemic predicates in L2 Spanish.

Much recent research in SLA is guided by the hypothesis of L2 interface vulnerability (see Sorace 2005). This study contributes to this general project by examining the acquisition of two classes of subjunctive complement clauses in L2 Spanish: subjunctive complements of volitional predicates (purely syntactic) and subjunctive vs. indicative complements with negated epistemic matrix predicates, where the mood distinction is discourse dependent (thus involving the syntax-discourse interface). We provide an analysis of the volitional subjunctive in English and Spanish, suggesting that English learners of L2 Spanish need to access the functional projection Mood P and an uninterpretable modal feature on the Force head available to them from their formal English register grammar, and simultaneously must unacquire the structure of English for-to clauses. For negated epistemic predicates, our analysis maintains that they need to revalue the modal feature on the Force head from uninterpretable to interpretable, within the L2 grammar.With others (e.g. Borgonovo & Prévost 2003; Borgonovo, Bruhn de Garavito & Prévost 2005) and in line with Sorace's (2000, 2003, 2005) notion of interface vulnerability, we maintain that the latter case is more difficult for L2 learners, which is borne out in the data we present. However, the data also show that the indicative/subjunctive distinction with negated epistemics can be acquired by advanced stages of acquisition, questioning the notion of obligatory residual optionality for all properties which require the integration of syntactic and discourse information.

Graph-based algorithms for comparison and prediction of household-level energy use profiles

We present an efficient graph-based algorithm for quantifying the similarity of household-level energy use profiles, using a notion of similarity that allows for small time–shifts when comparing profiles. Experimental results on a real smart meter data set demonstrate that in cases of practical interest our technique is far faster than the existing method for computing the same similarity measure. Having a fast algorithm for measuring profile similarity improves the efficiency of tasks such as clustering of customers and cross-validation of forecasting methods using historical data. Furthermore, we apply a generalisation of our algorithm to produce substantially better household-level energy use forecasts from historical smart meter data.

Sea surface temperature climate change initiative: alternative image classification algorithms for sea-ice affected oceans

We present a Bayesian image classification scheme for discriminating cloud, clear and sea-ice observations at high latitudes to improve identification of areas of clear-sky over ice-free ocean for SST retrieval. We validate the image classification against a manually classified dataset using Advanced Along Track Scanning Radiometer (AATSR) data. A three way classification scheme using a near-infrared textural feature improves classifier accuracy by 9.9 % over the nadir only version of the cloud clearing used in the ATSR Reprocessing for Climate (ARC) project in high latitude regions. The three way classification gives similar numbers of cloud and ice scenes misclassified as clear but significantly more clear-sky cases are correctly identified (89.9 % compared with 65 % for ARC). We also demonstrate the poetential of a Bayesian image classifier including information from the 0.6 micron channel to be used in sea-ice extent and ice surface temperature retrieval with 77.7 % of ice scenes correctly identified and an overall classifier accuracy of 96 %.

Fast identification algorithms for Gaussian process model

A class identification algorithms is introduced for Gaussian process(GP)models.The fundamental approach is to propose a new kernel function which leads to a covariance matrix with low rank,a property that is consequently exploited for computational efficiency for both model parameter estimation and model predictions.The objective of either maximizing the marginal likelihood or the Kullback–Leibler (K–L) divergence between the estimated output probability density function(pdf)and the true pdf has been used as respective cost functions.For each cost function,an efficient coordinate descent algorithm is proposed to estimate the kernel parameters using a one dimensional derivative free search, and noise variance using a fast gradient descent algorithm. Numerical examples are included to demonstrate the effectiveness of the new identification approaches.

Evaluation of seven European aerosol optical depth retrieval algorithms for climate analysis

Satellite data are increasingly used to provide observation-based estimates of the effects of aerosols on climate. The Aerosol-cci project, part of the European Space Agency's Climate Change Initiative (CCI), was designed to provide essential climate variables for aerosols from satellite data. Eight algorithms, developed for the retrieval of aerosol properties using data from AATSR (4), MERIS (3) and POLDER, were evaluated to determine their suitability for climate studies. The primary result from each of these algorithms is the aerosol optical depth (AOD) at several wavelengths, together with the Ångström exponent (AE) which describes the spectral variation of the AOD for a given wavelength pair. Other aerosol parameters which are possibly retrieved from satellite observations are not considered in this paper. The AOD and AE (AE only for Level 2) were evaluated against independent collocated observations from the ground-based AERONET sun photometer network and against “reference” satellite data provided by MODIS and MISR. Tools used for the evaluation were developed for daily products as produced by the retrieval with a spatial resolution of 10 × 10 km2 (Level 2) and daily or monthly aggregates (Level 3). These tools include statistics for L2 and L3 products compared with AERONET, as well as scoring based on spatial and temporal correlations. In this paper we describe their use in a round robin (RR) evaluation of four months of data, one month for each season in 2008. The amount of data was restricted to only four months because of the large effort made to improve the algorithms, and to evaluate the improvement and current status, before larger data sets will be processed. Evaluation criteria are discussed. Results presented show the current status of the European aerosol algorithms in comparison to both AERONET and MODIS and MISR data. The comparison leads to a preliminary conclusion that the scores are similar, including those for the references, but the coverage of AATSR needs to be enhanced and further improvements are possible for most algorithms. None of the algorithms, including the references, outperforms all others everywhere. AATSR data can be used for the retrieval of AOD and AE over land and ocean. PARASOL and one of the MERIS algorithms have been evaluated over ocean only and both algorithms provide good results.

Automated algorithms for multilayer thin film filter design using metamaterials

Currently, infrared filters for astronomical telescopes and satellite radiometers are based on multilayer thin film stacks of alternating high and low refractive index materials. However, the choice of suitable layer materials is limited and this places limitations on the filter performance that can be achieved. The ability to design materials with arbitrary refractive index allows for filter performance to be greatly increased but also increases the complexity of design. Here a differential algorithm was used as a method for optimised design of filters with arbitrary refractive indices, and then materials are designed to these specifications as mono-materials with sub wavelength structures using Bruggeman’s effective material approximation (EMA).

Control methodologies: Peak reduction algorithms for DNO owned storage devices on the Low Voltage network

The Distribution Network Operators (DNOs) role is becoming more difficult as electric vehicles and electric heating penetrate the network, increasing the demand. As a result it becomes harder for the distribution networks infrastructure to remain within its operating constraints. Energy storage is a potential alternative to conventional network reinforcement such as upgrading cables and transformers. The research presented here in this paper shows that due to the volatile nature of the LV network, the control approach used for energy storage has a significant impact on performance. This paper presents and compares control methodologies for energy storage where the objective is to get the greatest possible peak demand reduction across the day from a pre-specified storage device. The results presented show the benefits and detriments of specific types of control on a storage device connected to a single phase of an LV network, using aggregated demand profiles based on real smart meter data from individual homes. The research demonstrates an important relationship between how predictable an aggregation is and the best control methodology required to achieve the objective.

Ozonolysis of methyl oleate monolayers at the air–water interface: oxidation kinetics, reaction products and atmospheric implications

Ozonolysis of methyl oleate monolayers at the air–water interface results in surprisingly rapid loss of material through cleavage of the C[double bond, length as m-dash]C bond and evaporation/dissolution of reaction products. We determine using neutron reflectometry a rate coefficient of (5.7 ± 0.9) × 10−10 cm2 molecule−1 s−1 and an uptake coefficient of [similar]3 × 10−5 for the oxidation of a methyl ester monolayer: the atmospheric lifetime is [similar]10 min. We obtained direct experimental evidence that <2% of organic material remains at the surface on atmospheric timescales. Therefore known long atmospheric residence times of unsaturated fatty acids suggest that these molecules cannot be present at the interface throughout their ageing cycle, i.e. the reported atmospheric longevity is likely to be attributed to presence in the bulk and viscosity-limited reactive loss. Possible reaction products were characterized by ellipsometry and uncertainties in the atmospheric fate of organic surfactants such as oleic acid and its methyl ester are discussed. Our results suggest that a minor change to the structure of the molecule (fatty acid vs. its methyl ester) considerably impacts on reactivity and fate of the organic film.

Effect of instructive visual stimuli on neurofeedback training for motor imagery-based braincomputer interface

Event-related desynchronization (ERD) of the electroencephalogram (EEG) from the motor cortex is associated with execution, observation, and mental imagery of motor tasks. Generation of ERD by motor imagery (MI) has been widely used for brain-computer interfaces (BCIs) linked to neuroprosthetics and other motor assistance devices. Control of MI-based BCIs can be acquired by neurofeedback training to reliably induce MI-associated ERD. To develop more effective training conditions, we investigated the effect of static and dynamic visual representations of target movements (a picture of forearms or a video clip of hand grasping movements) during the BCI training. After 4 consecutive training days, the group that performed MI while viewing the video showed significant improvement in generating MI-associated ERD compared with the group that viewed the static image. This result suggests that passively observing the target movement during MI would improve the associated mental imagery and enhance MI-based BCIs skills.