Interaction between grammatical categories and cognition in bilinguals: The role of proficiency, cultural immersion, and language of instruction

Previous studies have demonstrated that there is a tight link between grammatical concepts and cognitive preferences in monolingual speakers (Lucy 1992, Lucy & Gaskins 2003, Imai & Gentner 1997, Imai & Mazuka 2003). Recent research has also shown that bilinguals with languages that differ in their concepts may shift their cognitive preferences as a function of their proficiency (Athanasopoulos, 2006) or cultural immersion (Cook, Bassetti, Kasai, Sasaki, & Takahashi, 2006). The current short paper assesses the relative impact of each of these variables, and furthermore asks whether bilinguals alternate between two distinct cognitive representations of language-specific concepts depending on the language used in the experiment. Results from an object classification task showed that Japanese–English bilinguals shifted their behaviour towards the second language (L2) pattern primarily as a function of their L2 proficiency, while cultural immersion and language of instruction played a minimal role. These findings suggest that acquisition of novel grammatical categories leads to cognitive restructuring in the bilingual mind and have implications for the relationship between language and cognitive processing.

A generalised Bayesian instrumental variable approach under student t-distributed errors with application

Bayesian analysis is given of an instrumental variable model that allows for heteroscedasticity in both the structural equation and the instrument equation. Specifically, the approach for dealing with heteroscedastic errors in Geweke (1993) is extended to the Bayesian instrumental variable estimator outlined in Rossi et al. (2005). Heteroscedasticity is treated by modelling the variance for each error using a hierarchical prior that is Gamma distributed. The computation is carried out by using a Markov chain Monte Carlo sampling algorithm with an augmented draw for the heteroscedastic case. An example using real data illustrates the approach and shows that ignoring heteroscedasticity in the instrument equation when it exists may lead to biased estimates.

A semi-distributed ntegrated itrogen model for multiple source assessment in tchments (INCA): Part I — model structure and process equations

A new model has been developed for assessing multiple sources of nitrogen in catchments. The model (INCA) is process based and uses reaction kinetic equations to simulate the principal mechanisms operating. The model allows for plant uptake, surface and sub-surface pathways and can simulate up to six land uses simultaneously. The model can be applied to catchment as a semi-distributed simulation and has an inbuilt multi-reach structure for river systems. Sources of nitrogen can be from atmospheric deposition, from the terrestrial environment (e.g. agriculture, leakage from forest systems etc.), from urban areas or from direct discharges via sewage or intensive farm units. The model is a daily simulation model and can provide information in the form of time series at key sites, or as profiles down river systems or as statistical distributions. The process model is described and in a companion paper the model is applied to the River Tywi catchment in South Wales and the Great Ouse in Bedfordshire.

Effects and mechanisms of ginseng and ginsenosides on cognition

Reviewed here is the existing evidence for the effects of ginseng extracts and isolated ginsenosides relevant to cognition in humans. Clinical studies in healthy volunteers and in patients with neurological disease or deficit, evidence from preclinical models of cognition, and pharmacokinetic data are considered. Conditions under which disease modification may indirectly benefit cognition but may not translate to cognitive benefits in healthy subjects are discussed. The number of chronic studies of ginseng effects in healthy individuals is limited, and the results from acute studies are inconsistent, making overall assessment of ginseng's efficacy as a cognitive enhancer premature. However, mechanistic results are encouraging; in particular, the ginsenosides Rg 3 , Rh 1 , Rh 2 , Rb 1 , Rd, Rg 2 , and Rb 3 , along with the aglycones protopanaxadiol and protopanaxatriol, warrant further attention. Compound K has a promising pharmacokinetic profile and can affect neurotransmission and neuroprotection. Properly conducted trials using standardized tests in healthy individuals reflecting the target population for ginseng supplementation are required to address inconsistencies in results from acute studies. The evidence summarized here suggests ginseng has potential, but unproven, benefits on cognition.

Evidence for a second meal cognitive effect: glycaemic responses to high and low glycaemic index evening meals are associated with cognition the following morning

Low glycaemic index (GI) foods consumed at breakfast can enhance memory in comparison to high-GI foods; however, the impact of evening meal GI manipulations on cognition the following morning remains unexplored. Fourteen healthy males consumed a high-GI evening meal or a low-GI evening meal in a counterbalanced order on two separate evenings. Memory and attention were assessed before and after a high-GI breakfast the following morning. The high-GI evening meal elicited significantly higher evening glycaemic responses than the low-GI evening meal. Verbal recall was better the morning following the high-GI evening meal compared to after the low-GI evening meal. In summary, the GI of the evening meal was associated with memory performance the next day, suggesting a second meal cognitive effect. The present findings imply that an overnight fast may not be sufficient to control for previous nutritional consumption.

Mechanisms of motivation-cognition interaction: challenges and opportunities

There has been a recent rejuvenation of interest in studies of motivation-cognition interactions arising from many different areas of psychology and neuroscience. The current issue of Cognitive, Affective, and Behavioral Neuroscience provides a sampling of some of the latest research from a number of these different areas. In this introductory paper, we provide an overview of the current state of the field, in terms of key research developments and candidate neural mechanisms receiving focused investigation as potential sources of motivation-cognition interaction. However, our primary goal is conceptual: to highlight the distinct perspectives taken by different research areas in terms of how motivation is defined, the relevant dimensions and dissociations that are emphasized, and the theoretical questions being targeted. Together, these distinctions present both challenges and opportunities for efforts aiming towards a more unified and cross-disciplinary approach. We identify a set of pressing research questions calling out for this sort of cross-disciplinary approach, with the explicit goal of encouraging integrative and collaborative investigations directed towards them.

Dynamic distributed lanes: motion planning for multiple autonomous vehicles

Unorganized traffic is a generalized form of travel wherein vehicles do not adhere to any predefined lanes and can travel in-between lanes. Such travel is visible in a number of countries e.g. India, wherein it enables a higher traffic bandwidth, more overtaking and more efficient travel. These advantages are visible when the vehicles vary considerably in size and speed, in the absence of which the predefined lanes are near-optimal. Motion planning for multiple autonomous vehicles in unorganized traffic deals with deciding on the manner in which every vehicle travels, ensuring no collision either with each other or with static obstacles. In this paper the notion of predefined lanes is generalized to model unorganized travel for the purpose of planning vehicles travel. A uniform cost search is used for finding the optimal motion strategy of a vehicle, amidst the known travel plans of the other vehicles. The aim is to maximize the separation between the vehicles and static obstacles. The search is responsible for defining an optimal lane distribution among vehicles in the planning scenario. Clothoid curves are used for maintaining a lane or changing lanes. Experiments are performed by simulation over a set of challenging scenarios with a complex grid of obstacles. Additionally behaviours of overtaking, waiting for a vehicle to cross and following another vehicle are exhibited.

The projected hand illusion: component structure in a community sample, and association with demographics, cognition and psychotic-like experiences

The projected hand illusion (PHI) is a variant of the rubber hand illusion (RHI), and both are commonly used to study mechanisms of self-perception. A questionnaire was developed by Longo et al. (2008) to measure qualitative changes in the RHI. Such psychometric analyses have not yet been conducted on the questionnaire for the PHI. The present study is an attempt to validate minor modifications of the questionnaire of Longo et al. to assess the PHI in a community sample (n = 48) and to determine the association with selected demographic (age, sex, years of education), cognitive (Digit Span), and clinical (psychotic-like experiences) variables. Principal components analysis on the questionnaire data extracted four components: Embodiment of “Other” Hand, Disembodiment of Own Hand, Deafference, and Agency—in both synchronous and asynchronous PHI conditions. Questions assessing “Embodiment” and “Agency” loaded onto orthogonal components. Greater illusion ratings were positively associated with being female, being younger, and having higher scores on psychotic-like experiences. There was no association with cognitive performance. Overall, this study confirmed that self-perception as measured with PHI is a multicomponent construct, similar in many respects to the RHI. The main difference lies in the separation of Embodiment and Agency into separate constructs, and this likely reflects the fact that the “live” image of the PHI presents a more realistic picture of the hand and of the stroking movements of the experimenter compared with the RHI.

Calibration of structure in a distributed forecasting model for a semiarid flash flood: dynamic surface storage and channel roughness

Flash floods pose a significant danger for life and property. Unfortunately, in arid and semiarid environment the runoff generation shows a complex non-linear behavior with a strong spatial and temporal non-uniformity. As a result, the predictions made by physically-based simulations in semiarid areas are subject to great uncertainty, and a failure in the predictive behavior of existing models is common. Thus better descriptions of physical processes at the watershed scale need to be incorporated into the hydrological model structures. For example, terrain relief has been systematically considered static in flood modelling at the watershed scale. Here, we show that the integrated effect of small distributed relief variations originated through concurrent hydrological processes within a storm event was significant on the watershed scale hydrograph. We model these observations by introducing dynamic formulations of two relief-related parameters at diverse scales: maximum depression storage, and roughness coefficient in channels. In the final (a posteriori) model structure these parameters are allowed to be both time-constant or time-varying. The case under study is a convective storm in a semiarid Mediterranean watershed with ephemeral channels and high agricultural pressures (the Rambla del Albujón watershed; 556 km 2 ), which showed a complex multi-peak response. First, to obtain quasi-sensible simulations in the (a priori) model with time-constant relief-related parameters, a spatially distributed parameterization was strictly required. Second, a generalized likelihood uncertainty estimation (GLUE) inference applied to the improved model structure, and conditioned to observed nested hydrographs, showed that accounting for dynamic relief-related parameters led to improved simulations. The discussion is finally broadened by considering the use of the calibrated model both to analyze the sensitivity of the watershed to storm motion and to attempt the flood forecasting of a stratiform event with highly different behavior.

Assessing the sensitivities of a distributed snow model to forcing data resolution

Highly heterogeneous mountain snow distributions strongly affect soil moisture patterns; local ecology; and, ultimately, the timing, magnitude, and chemistry of stream runoff. Capturing these vital heterogeneities in a physically based distributed snow model requires appropriately scaled model structures. This work looks at how model scale—particularly the resolutions at which the forcing processes are represented—affects simulated snow distributions and melt. The research area is in the Reynolds Creek Experimental Watershed in southwestern Idaho. In this region, where there is a negative correlation between snow accumulation and melt rates, overall scale degradation pushed simulated melt to earlier in the season. The processes mainly responsible for snow distribution heterogeneity in this region—wind speed, wind-affected snow accumulations, thermal radiation, and solar radiation—were also independently rescaled to test process-specific spatiotemporal sensitivities. It was found that in order to accurately simulate snowmelt in this catchment, the snow cover needed to be resolved to 100 m. Wind and wind-affected precipitation—the primary influence on snow distribution—required similar resolution. Thermal radiation scaled with the vegetation structure (~100 m), while solar radiation was adequately modeled with 100–250-m resolution. Spatiotemporal sensitivities to model scale were found that allowed for further reductions in computational costs through the winter months with limited losses in accuracy. It was also shown that these modeling-based scale breaks could be associated with physiographic and vegetation structures to aid a priori modeling decisions.

Energy-efficient resource allocation in OFDM systems with distributed antennas

In this paper, we develop an energy-efficient resource-allocation scheme with proportional fairness for downlink multiuser orthogonal frequency-division multiplexing (OFDM) systems with distributed antennas. Our aim is to maximize energy efficiency (EE) under the constraints of the overall transmit power of each remote access unit (RAU), proportional fairness data rates, and bit error rates (BERs). Because of the nonconvex nature of the optimization problem, obtaining the optimal solution is extremely computationally complex. Therefore, we develop a low-complexity suboptimal algorithm, which separates subcarrier allocation and power allocation. For the low-complexity algorithm, we first allocate subcarriers by assuming equal power distribution. Then, by exploiting the properties of fractional programming, we transform the nonconvex optimization problem in fractional form into an equivalent optimization problem in subtractive form, which includes a tractable solution. Next, an optimal energy-efficient power-allocation algorithm is developed to maximize EE while maintaining proportional fairness. Through computer simulation, we demonstrate the effectiveness of the proposed low-complexity algorithm and illustrate the fundamental trade off between energy and spectral-efficient transmission designs.