The use of social and salience cues in early word learning

This article explores young infants' ability to learn new words in situations providing tightly controlled social and salience cues to their reference. Four experiments investigated whether, given two potential referents, 15-month-olds would attach novel labels to (a) an image toward which a digital recording of a face turned and gazed, (b) a moving image versus a stationary image, (c) a moving image toward which the face gazed, and (d) a gazed-on image versus a moving image. Infants successfully used the recorded gaze cue to form new word-referent associations and also showed learning in the salience condition. However, their behavior in the salience condition and in the experiments that followed suggests that, rather than basing their judgments of the words' reference on the mere presence or absence of the referent's motion, infants were strongly biased to attend to the consistency with which potential referents moved when a word was heard. (c) 2006 Elsevier Inc. All rights reserved.

Linking the coevolutionary and population dynamics of host-parasitoid interactions

The interplay between coevolutionary and population or community dynamics is currently the focus of much empirical and theoretical consideration. Here, we develop a simulation model to study the coevolutionary and population dynamics of a hypothetical host-parasitoid interaction. In the model, host resistance and parasitoid virulence are allowed to coevolve. We investigate how trade-offs associated with these traits modify the system's coevolutionary and population dynamics. The most important influence on these dynamics comes from the incorporation of density-dependent costs of resistance ability. We find three main outcomes. First, if the costs of resistance are high, then one or both of the players go extinct. Second, when the costs of resistance are intermediate to low, cycling population and coevolutionary dynamics are found, with slower evolutionary changes observed when the costs of virulence are also low. Third, when the costs associated with resistance and virulence are both high, the hosts trade-off resistance against fecundity and invest little in resistance. However, the parasitoids continue to invest in virulence, leading to stable host and parasitoid population sizes. These results support the hypothesis that costs associated with resistance and virulence will maintain the heritable variation in these traits found in natural populations and that the nature of these trade-offs will greatly influence the population dynamics of the interacting species.

Modelling fixed plant and algal dynamics in rivers: an application to the River Frome

The development of eutrophication in river systems is poorly understood given the complex relationship between fixed plants, algae, hydrodynamics, water chemistry and solar radiation. However there is a pressing need to understand the relationship between the ecological status of rivers and the controlling environmental factors to help the reasoned implementation of the Water Framework Directive and Catchment Sensitive Farming in the UK. This research aims to create a dynamic, process-based, mathematical in-stream model to simulate the growth and competition of different vegetation types (macrophytes, phytoplankton and benthic algae) in rivers. The model, applied to the River Frome (Dorset, UK), captured well the seasonality of simulated vegetation types (suspended algae, macrophytes, epiphytes, sediment biofilm). Macrophyte results showed that local knowledge is important for explaining unusual changes in biomass. Fixed algae simulations indicated the need for the more detailed representation of various herbivorous grazer groups, however this would increase the model complexity, the number of model parameters and the required observation data to better define the model. The model results also highlighted that simulating only phytoplankton is insufficient in river systems, because the majority of the suspended algae have benthic origin in short retention time rivers. Therefore, there is a need for modelling tools that link the benthic and free-floating habitats.

Theoretical investigation of infrared spectra and pocket dynamics of photodissociated carbonmonoxy myoglobin

Molecular dynamics simulations of the photodissociated state of carbonmonoxy myoglobin (MbCO) are presented using a fluctuating charge model for CO. A new three-point charge model is fitted to high-level ab initio calculations of the dipole and quadrupole moment functions taken from the literature. The infrared spectrum of the CO molecule in the heme pocket is calculated using the dipole moment time autocorrelation function and shows good agreement with experiment. In particular, the new model reproduces the experimentally observed splitting of the CO absorption spectrum. The splitting of 3–7 cm−1 (compared to the experimental value of 10 cm−1) can be directly attributed to the two possible orientations of CO within the docking site at the edge of the distal heme pocket (the B states), as previously suggested on the basis of experimental femtosecond time-resolved infrared studies. Further information on the time evolution of the position and orientation of the CO molecule is obtained and analyzed. The calculated difference in the free energy between the two possible orientations (Fe···CO and Fe···OC) is 0.3 kcal mol−1 and agrees well with the experimentally estimated value of 0.29 kcal mol−1. A comparison of the new fluctuating charge model with an established fixed charge model reveals some differences that may be critical for the correct prediction of the infrared spectrum and energy barriers. The photodissociation of CO from the myoglobin mutant L29F using the new model shows rapid escape of CO from the distal heme pocket, in good agreement with recent experimental data. The effect of the protein environment on the multipole moments of the CO ligand is investigated and taken into account in a refined model. Molecular dynamics simulations with this refined model are in agreement with the calculations based on the gas-phase model. However, it is demonstrated that even small changes in the electrostatics of CO alter the details of the dynamics.

An improved lesion detection approach based on similarity measurement between fuzzy intensity segmentation and spatial probability maps

The application of automatic segmentation methods in lesion detection is desirable. However, such methods are restricted by intensity similarities between lesioned and healthy brain tissue. Using multi-spectral magnetic resonance imaging (MRI) modalities may overcome this problem but it is not always practicable. In this article, a lesion detection approach requiring a single MRI modality is presented, which is an improved method based on a recent publication. This new method assumes that a low similarity should be found in the regions of lesions when the likeness between an intensity based fuzzy segmentation and a location based tissue probabilities is measured. The usage of a normalized similarity measurement enables the current method to fine-tune the threshold for lesion detection, thus maximizing the possibility of reaching high detection accuracy. Importantly, an extra cleaning step is included in the current approach which removes enlarged ventricles from detected lesions. The performance investigation using simulated lesions demonstrated that not only the majority of lesions were well detected but also normal tissues were identified effectively. Tests on images acquired in stroke patients further confirmed the strength of the method in lesion detection. When compared with the previous version, the current approach showed a higher sensitivity in detecting small lesions and had less false positives around the ventricle and the edge of the brain