Evidence from neurolinguistic methodologies: can it actually inform linguistic/ language acquisition theories and translate to evidence-based applications?

This special issue is a testament to the recent burgeoning interest by theoretical linguists, language acquisitionists and teaching practitioners in the neuroscience of language. It offers a highly valuable, state-of-the-art overview of the neurophysiological methods that are currently being applied to questions in the field of second language (L2) acquisition, teaching and processing. Research in the area of neurolinguistics has developed dramatically in the past twenty years, providing a wealth of exciting findings, many of which are discussed in the papers in this volume. The goal of this commentary is twofold. The first is to critically assess the current state of neurolinguistic data from the point of view of language acquisition and processing—informed by the papers that comprise this special issue and the literature as a whole—pondering how the neuroscience of language/processing might inform us with respect to linguistic and language acquisition theories. The second goal is to offer some links from implications of exploring the first goal towards informing language teachers and the creation of linguistically and neurolinguistically-informed evidence-based pedagogies for non-native language teaching.

Patterns of food acquisition in Brazilian households and associated factors: a population-based survey

Objective: To identify food acquisition patterns in Brazil and relate them to the sociodemographic characteristics of the household. Design: A cross-sectional national Household Budget Survey (HBS). Principal component factor analysis was used to derive food patterns (factors) on the basis of the acquisition of food classified into thirty-two food groups. Setting: The source of data originates from the 2002-2003 HBS carried out by the Brazilian Institute of Geography and Statistics between June 2002 and July 2003 using a representative sample of all Brazilian households. Subject: A total of 48 470 households allocated into 443 strata of households that were geographically and socio-economically homogeneous as a study unit. Results: We identified two patterns of food acquisition. The first, named `dual`, was characterized by dairy, fruit, fruit juice, vegetables, processed meat, soft drinks, sweets, bread and margarine, and by inverse correlations with Brazilian staple foods. In contrast, the second pattern, named `traditional`, was characterized by rice, beans, manioc, flour, milk and sugar. The `dual` pattern was associated with higher household educational level, income and the average age of adults on the strata, whereas the `traditional` presented higher loadings in less-educated households and in the rural setting. Conclusions: Dietary patterns described here suggest that policies and programmes to promote healthy eating need to consider that healthy and non-healthy foods may be integral in the same pattern.

Fast Acquisition of (13)C NMR Spectra using the Steady-state Free Precession Sequence

In this paper, we show that the steady-state free precession sequence can be used to acquire (13)C high-resolution nuclear magnetic resonance spectra and applied to qualitative analysis. The analysis of brucine sample using this sequence with 60 degrees flip angle and time interval between pulses equal to 300 ms (acquisition time, 299.7 ms; recycle delay, 300 ms) resulted in spectrum with twofold enhancement in signal-to-noise ratio, when compared to standard (13)C sequence. This gain was better when a much shorter time interval between pulses (100 ms) was applied. The result obtained was more than fivefold enhancement in signal-to-noise ratio, equivalent to more than 20-fold reduction in total data recording time. However, this short time interval between pulses produces a spectrum with severe phase and truncation anomalies. We demonstrated that these anomalies can be minimized by applying an appropriate apodization function and plotting the spectrum in the magnitude mode.

Using vignettes to evaluate the outcomes of student learning : data from the evaluation of the new social work degree in England

This paper reports the use of vignettes as a methodology to analyse the extent to which the new social work degree programmes enabled students to develop their analytical and reflective capabilities. Two vignettes, which focused on children and families and adult social care respectively, were developed for the study. Students were asked to respond in writing, from the perspective of a social worker, to a standard set of questions at the beginning (T1) and end of their degree programme (T2). Considering the responses to all questions across the two vignettes, a series of scales was developed to measure the key themes which had been identified by qualitative analysis. These included ‘Attention to process of relationships’ and ‘Social/structural/political awareness’. Responses were also rated as ‘descriptive’, ‘analytic’ or ‘reflective’.

Students from six universities in England participated. From an original sample of 222 students, it was possible to match 79 T1 and T2 responses. Analysis of variance demonstrated statistically significant increases in nine of the 11 themes and increases in ratings for analysis and reflection.

In conclusion, vignettes can be used to produce both qualitative and quantitative data in respect of changes in students’ acquisition of knowledge and skills over time.

Digital natives? : new and old media and children’s language acquisition

The current generation of young children has been described as “digital natives”, having been born into a ubiquitous digital media environment. They are envisaged as educationally independent of the guided interaction provided by “digital immigrants”: parents and teachers. This paper uses data from the multiples waves of the Longitudinal Study of Australian Children (LSAC) to study the effect of various media on children’s development of vocabulary and traditional literacy. Previous research has suggested that time spent watching television is associated with less time spent reading, and ultimately, with inferior educational outcomes. The early studies of the “new” digital media (computers, games consoles, mobile phones, the Internet, etc.) assumed these devices would have similar effects on literacy outcomes to those associated with television. Moreover, these earlier studies relied on poorer measures of time spent in media use and usually did not control for the context of the child’s media use. Fortunately, LSAC contains measures of access to digital devices; parental mediation practices; the child’s use of digital devices as recorded in time use diaries; direct measures of the child’s passive vocabulary; and teachers’ ratings of the child’s literacy. The analysis presented shows the importance of the parental context framing the child’s media use in promoting the acquisition of vocabulary, and suggests that computer (but not games) use is associated with more developed language skills. Independently of these factors, raw exposure to television is not harmful to learning, as previously thought.

Effects of new and old media on young children’s language acquisition, development, and early literacy : findings from a longitudinal study of Australian children

The current generation of young children has been described as “digital natives”, having been born into a ubiquitous digital media environment. They are envisaged as educationally independent of the guided interaction provided by “digital immigrants”: parents and teachers. This paper uses data from the Longitudinal Study of Australian Children (LSAC) to study children’s (aged 0-8 years) development of vocabulary and traditional literacy; access to digital devices; parental mediation practices; the child’s use of digital devices as recorded in time-diaries and, finally, the association between patterns of media use and family contexts on children’s learning. The analysis shows the importance of the parental context framing media use in acquisition of vocabulary, and suggests that computer (but not games) use is associated with more developed language skills. Independently of these factors raw exposure to television is not harmful to learning.

An investigation into the drivers of Australian REIT merger and acquisition announcements

Purpose – The purpose of this paper is to use Australian Real Estate Investment Trust (A-REIT) data to empirically examine potential influencing factors on A-REITs becoming a bidder or a target in the mergers and acquisitions (M&A) area.

Design/methodology/approach – This study uses logistic regression analysis to investigate the odds of publically traded A-REITs being either a bidder or a target as a function of a number of financial and corporate governance variables.

Findings – Prior research in the US REIT M&A area has shown that target size is inversely related to takeover likelihood; in contrast, the authors’ Australian results show that size has a positive impact. Prior research on share price and asset performance has shown that underperformance increases the odds of an entity becoming a target, but this paper’s results further support these findings and provide confirmation of the inefficient management hypothesis. For acquirers it was found that leverage, cash balances, management structure, the level of shares held by related parties and the global financial crisis have an important impact on bidder likelihood.

Practical implications – Given that the literature suggests that investors can earn significant positive abnormal returns by owning targets, but incur significant abnormal losses by owning bidders, at announcement, this study will be useful to fund managers and other investors in A-REITs by investigating the characteristics of those firms that become targets and bidders.

Originality/value – This paper adds to the recent US REIT M&A literature by examining the second biggest REIT market in the world and reporting a number of factors that might influence A-REITs to become targets or bidders.

Recommendations for improved data processing from expired gas analysis indirect calorimetry

There is currently no universally recommended and accepted method of data processing within the science of indirect calorimetry for either mixing chamber or breath-by-breath systems of expired gas analysis. Exercise physiologists were first surveyed to determine methods used to process oxygen consumption ([OV0312]O 2) data, and current attitudes to data processing within the science of indirect calorimetry. Breath-by-breath datasets obtained from indirect calorimetry during incremental exercise were then used to demonstrate the consequences of commonly used time, breath and digital filter post-acquisition data processing strategies. Assessment of the variability in breath-by-breath data was determined using multiple regression based on the independent variables ventilation (VE), and the expired gas fractions for oxygen and carbon dioxide, FEO 2 and FECO2, respectively. Based on the results of explanation of variance of the breath-by-breath [OV0312]O2 data, methods of processing to remove variability were proposed for time-averaged, breath-averaged and digital filter applications. Among exercise physiologists, the strategy used to remove the variability in sequential [OV0312]O2 measurements varied widely, and consisted of time averages (30 sec [38%], 60 sec [18%], 20 sec [11%], 15 sec [8%]), a moving average of five to 11 breaths (10%), and the middle five of seven breaths (7%). Most respondents indicated that they used multiple criteria to establish maximum [OV0312]O 2 ([OV0312]O2max) including: the attainment of age-predicted maximum heart rate (HRmax) [53%], respiratory exchange ratio (RER) >1.10 (49%) or RER >1.15 (27%) and a rating of perceived exertion (RPE) of >17, 18 or 19 (20%). The reasons stated for these strategies included their own beliefs (32%), what they were taught (26%), what they read in research articles (22%), tradition (13%) and the influence of their colleagues (7%). The combination of VE, FEO 2 and FECO2 removed 96-98% of [OV0312]O2 breath-by-breath variability in incremental and steady-state exercise [OV0312]O2 data sets, respectively. Correction of residual error in [OV0312]O2 datasets to 10% of the raw variability results from application of a 30-second time average, 15-breath running average, or a 0.04 Hz low cut-off digital filter. Thus, we recommend that once these data processing strategies are used, the peak or maximal value becomes the highest processed datapoint. Exercise physiologists need to agree on, and continually refine through empirical research, a consistent process for analysing data from indirect calorimetry.

Mental health following acquisition of disability in adulthood-the impact of wealth

BACKGROUND: Acquisition of a disability in adulthood has been associated with a reduction in mental health. We tested the hypothesis that low wealth prior to disability acquisition is associated with a greater deterioration in mental health than for people with high wealth. METHODS: We assess whether level of wealth prior to disability acquisition modifies this association using 12 waves of data (2001-2012) from the Household, Income and Labour Dynamics in Australia survey-a population-based cohort study of working-age Australians. Eligible participants reported at least two consecutive waves of disability preceded by at least two consecutive waves without disability (1977 participants, 13,518 observations). Fixed-effects linear regression was conducted with a product term between wealth prior to disability (in tertiles) and disability acquisition with the mental health component score of the SF-36 as the outcome. RESULTS: In models adjusted for time-varying confounders, there was evidence of negative effect measure modification by prior wealth of the association between disability acquisition and mental health (interaction term for lowest wealth tertile: -2.2 points, 95% CI -3.1 points, -1.2, p<0.001); low wealth was associated with a greater decline in mental health following disability acquisition (-3.3 points, 95% CI -4.0, -2.5) than high wealth (-1.1 points, 95% CI -1.7, -0.5). CONCLUSION: The findings suggest that low wealth prior to disability acquisition in adulthood results in a greater deterioration in mental health than among those with high wealth.

Mapping Macrophyte Species in the Amazon Floodplain Wetlands Using Fully Polarimetric ALOS/PALSAR Data

The purpose of this paper was to evaluate attributes derived from fully polarimetric PALSAR data to discriminate and map macrophyte species in the Amazon floodplain wetlands. Fieldwork was carried out almost simultaneously to the radar acquisition, and macrophyte biomass and morphological variables were measured in the field. Attributes were calculated from the covariance matrix [C] derived from the single-look complex data. Image attributes and macrophyte variables were compared and analyzed to investigate the sensitivity of the attributes for discriminating among species. Based on these analyses, a rule-based classification was applied to map macrophyte species. Other classification approaches were tested and compared to the rule-based method: a classification based on the Freeman-Durden and Cloude-Pottier decomposition models, a hybrid classification (Wishart classifier with the input classes based on the H/a plane), and a statistical-based classification (supervised classification using Wishart distance measures). The findings show that attributes derived from fully polarimetric L-band data have good potential for discriminating herbaceous plant species based on morphology and that estimation of plant biomass and productivity could be improved by using these polarimetric attributes.

Structural FRF acquisition via electric impedance measurement applied to damage location

Continuing development of new materials makes systems lighter and stronger permitting more complex systems to provide more functionality and flexibility that demands a more effective evaluation of their structural health. Smart material technology has become an area of increasing interest in this field. The combination of smart materials and artificial neural networks can be used as an excellent tool for pattern recognition, turning their application adequate for monitoring and fault classification of equipment and structures. In order to identify the fault, the neural network must be trained using a set of solutions to its corresponding forward Variational problem. After the training process, the net can successfully solve the inverse variational problem in the context of monitoring and fault detection because of their pattern recognition and interpolation capabilities. The use of structural frequency response function is a fundamental portion of structural dynamic analysis, and it can be extracted from measured electric impedance through the electromechanical interaction of a piezoceramic and a structure. In this paper we use the FRF obtained by a mathematical model (FEM) in order to generate the training data for the neural networks, and the identification of damage can be done by measuring electric impedance, since suitable data normalization correlates FRF and electrical impedance.

Conceptual model for adaptable and extensible visual data exploration

Interactive visual representations complement traditional statistical and machine learning techniques for data analysis, allowing users to play a more active role in a knowledge discovery process and making the whole process more understandable. Though visual representations are applicable to several stages of the knowledge discovery process, a common use of visualization is in the initial stages to explore and organize a sometimes unknown and complex data set. In this context, the integrated and coordinated - that is, user actions should be capable of affecting multiple visualizations when desired - use of multiple graphical representations allows data to be observed from several perspectives and offers richer information than isolated representations. In this paper we propose an underlying model for an extensible and adaptable environment that allows independently developed visualization components to be gradually integrated into a user configured knowledge discovery application. Because a major requirement when using multiple visual techniques is the ability to link amongst them, so that user actions executed on a representation propagate to others if desired, the model also allows runtime configuration of coordinated user actions over different visual representations. We illustrate how this environment is being used to assist data exploration and organization in a climate classification problem.

Investigations on the full polarimetric PALSAR data to discriminate macrophytes species in the Amazon floodplain wetland

The purpose of this work is to evaluate the capacity of full polarimetric L band data to discriminate macrophyte species in Amazon wetland. Fieldwork was carried out almost simultaneously to the acquisition of the full polarimetric PALSAR data. Coherent and incoherent attributes were extracted from the image, and macrophyte morphological variables were measured on the ground. The image attributes and the macrophyte variables were compared in order to evaluate their application for discriminating macrophytes species. The findings suggest that polarimetric information could be adopted to discriminate plant species based on morphology, and that estimation of plant biomass and productivity could be improved by using the polarimetric information. © 2010 IEEE.

2-D ZO CRS stack by considering an acquisition line with smooth topography

Os dados sísmicos terrestres são afetados pela existência de irregularidades na superfície de medição, e.g. a topografia. Neste sentido, para obter uma imagem sísmica de alta resolução, faz-se necessário corrigir estas irregularidades usando técnicas de processamento sísmico, e.g. correições estáticas residuais e de campo. O método de empilhamento Superfície de Reflexão Comum, CRS ("Common-Reflection-Surface", em inglês) é uma nova técnica de processamento para simular seções sísmicas com afastamento-nulo, ZO ("Zero-Offset", em inglês) a partir de dados sísmicos de cobertura múltipla. Este método baseia-se na aproximação hiperbólica de tempos de trânsito paraxiais de segunda ordem referido ao raio (central) normal. O operador de empilhamento CRS para uma superfície de medição planar depende de três parâmetros, denominados o ângulo de emergência do raio normal, a curvatura da onda Ponto de Incidência Normal, NIP ("Normal Incidence Point", em inglês) e a curvatura da onda Normal, N. Neste artigo o método de empilhamento CRS ZO 2-D é modificado com a finalidade de considerar uma superfície de medição com topografia suave também dependente desses parâmetros. Com este novo formalismo CRS, obtemos uma seção sísmica ZO de alta resolução, sem aplicar as correições estáticas, onde em cada ponto desta seção são estimados os três parâmetros relevantes do processo de empilhamento CRS.

Semi-supervised learning with concept drift using particle dynamics applied to network intrusion detection data

Concept drift, which refers to non stationary learning problems over time, has increasing importance in machine learning and data mining. Many concept drift applications require fast response, which means an algorithm must always be (re)trained with the latest available data. But the process of data labeling is usually expensive and/or time consuming when compared to acquisition of unlabeled data, thus usually only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are based on assumptions that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenging task in machine learning. Recently, a particle competition and cooperation approach has been developed to realize graph-based semi-supervised learning from static data. We have extend that approach to handle data streams and concept drift. The result is a passive algorithm which uses a single classifier approach, naturally adapted to concept changes without any explicit drift detection mechanism. It has built-in mechanisms that provide a natural way of learning from new data, gradually "forgetting" older knowledge as older data items are no longer useful for the classification of newer data items. The proposed algorithm is applied to the KDD Cup 1999 Data of network intrusion, showing its effectiveness.