Morphosyntactic and syntactic priming: an investigation of underlying processing mechanisms and the effects of Parkinson’s disease

There is now considerable evidence to suggest that non-demented people with Parkinson's disease (PD) experience difficulties using the morphosyntactic aspects of language. It remains unclear, however, at precisely which point in the processing of morphosyntax, these difficulties emerge. The major objective of the present study was to examine the impact of PD on the processes involved in accessing morphosyntactic information in the lexicon. Nineteen people with PD and 19 matched control subjects participated in the study which employed on-line word recognition tasks to examine morphosyntactic priming for local grammatical dependencies that occur both within (e.g. is going) and across (e.g. she gives) phrasal boundaries (Experiments 1 and 2, respectively). The control group evidenced robust morphosyntactic priming effects that were consistent with the involvement of both pre- (Experiment 1) and post-lexical (Experiment 2) processing routines. Whilst the participants with PD also recorded priming for dependencies within phrasal boundaries (Experiment 1), priming effects were observed over an abnormally brief time course. Further, in contrast to the controls, the PD group failed to record morphosyntactic priming for constructions that crossed phrasal boundaries (Experiment 2). The results demonstrate that attentionally mediated mechanisms operating at both the pre- and post-lexical stages of processing are able to contribute to morphosyntactic priming effects. In addition, the findings support the notion that, whilst people with PD are able to access morphosyntactic information in a normal manner, the time frame in which this information remains available for processing is altered. Deficits may also be experienced at the post-lexical integrational stage of processing.

Expokit: A software package for computing matrix exponentials

Expokit provides a set of routines aimed at computing matrix exponentials. More precisely, it computes either a small matrix exponential in full, the action of a large sparse matrix exponential on an operand vector, or the solution of a system of linear ODEs with constant inhomogeneity. The backbone of the sparse routines consists of matrix-free Krylov subspace projection methods (Arnoldi and Lanczos processes), and that is why the toolkit is capable of coping with sparse matrices of large dimension. The software handles real and complex matrices and provides specific routines for symmetric and Hermitian matrices. The computation of matrix exponentials is a numerical issue of critical importance in the area of Markov chains and furthermore, the computed solution is subject to probabilistic constraints. In addition to addressing general matrix exponentials, a distinct attention is assigned to the computation of transient states of Markov chains.

The effects of predator odors in mammalian prey species: A review of field and laboratory studies

wPrey species show specific adaptations that allow recognition, avoidance and defense against predators. For many mammalian species this includes sensitivity towards predator-derived odors. The typical sources of such odors include predator skin and fur, urine, feces and anal gland secretions. Avoidance of predator odors has been observed in many mammalian prey species including rats, mice, voles, deer, rabbits, gophers, hedgehogs, possums and sheep. Field and laboratory studies show that predator odors have distinctive behavioral effects which include (1) inhibition of activity, (2) suppression of non-defensive behaviors such as foraging, feeding and grooming, and (3) shifts to habitats or secure locations where such odors are not present. The repellent effect of predator odors in the field may sometimes be of practical use in the protection of crops and natural resources, although not all attempts at this have been successful. The failure of some studies to obtain repellent effects with predator odors may relate to (1) mismatches between the predator odors and prey species employed, (2) strain and individual differences in sensitivity to predator odors, and (3) the use of predator odors that have low efficacy. In this regard, a small number of recent studies have suggested that skin and fur-derived predator odors may have a more profound lasting effect on prey species than those derived from urine or feces. Predator odors can have powerful effects on the endocrine system including a suppression of testosterone and increased levels of stress hormones such as corticosterone and ACTH. Inhibitory effects of predator odors on reproductive behavior have been demonstrated, and these are particularly prevalent in female rodent species. Pregnant female rodents exposed to predator odors may give birth to smaller litters while exposure to predator odors during early life can hinder normal development. Recent research is starting to uncover the neural circuitry activated by predator odors, leading to hypotheses about how such activation leads to observable effects on reproduction, foraging and feeding. (c) 2005 Elsevier Ltd. All rights reserved.

Applying linear time-varying constraints to econometric models: With an application to demand systems

When linear equality constraints are invariant through time they can be incorporated into estimation by restricted least squares. If, however, the constraints are time-varying, this standard methodology cannot be applied. In this paper we show how to incorporate linear time-varying constraints into the estimation of econometric models. The method involves the augmentation of the observation equation of a state-space model prior to estimation by the Kalman filter. Numerical optimisation routines are used for the estimation. A simple example drawn from demand analysis is used to illustrate the method and its application.

Ancient mitochondrial DNA and morphology elucidate an extinct island radiation of Indian Ocean giant tortoise (Cylindrapsis)

Ancient mitochondrial DNA sequences were used for investigating the evolution of an entire clade of extinct vertebrates, the endemic tortoises (Cylindraspis) of the Mascarene Islands in the Indian Ocean. Mitochondrial DNA corroborates morphological evidence that there were five species of tortoise with the following relationships: Cylindraspis triserrata ((Cylindraspis vosmaeri and Cylindraspis peltastes) (Cylindraspis inepta and Cylindraspis indica)). Phylogeny indicates that the ancestor of the group first colonized Mauritius where speciation produced C. triserrata and the ancestor of the other species including a second sympatric Mauritian form, C. inepta. A propagule derived from this lineage colonized Rodrigues 590 km to the east, where a second within-island speciation took place producing the sympatric C. vosmaeri and C. peltastes. A recent colonization of Réunion 150 km to the southwest produced C. indica. In the virtual absence of predators, the defensive features of the shells of Mascarene tortoises were largely dismantled, apparently in two stages. 'Saddlebacked' shells with high fronts evolved independently on all three islands. This and other features, such as a derived jaw structure and small body size, may be associated with niche differentiation in sympatric species and may represent a striking example of parallel differentiation in a large terrestrial vertebrate. The history of Mascarene tortoises contrasts with that of the Galápagos, where only a single species is present and surviving populations are genetically much more similar. However, they too show some reduction in anti-predator mechanisms and multiple development of populations with saddlebacked shells.

Monitoring the composition and form of urban environments based on the vegetation-impervious surface-soil (VIS) model by sub-pixel analysis techniques

The majority of the world's population now resides in urban environments and information on the internal composition and dynamics of these environments is essential to enable preservation of certain standards of living. Remotely sensed data, especially the global coverage of moderate spatial resolution satellites such as Landsat, Indian Resource Satellite and Systeme Pour I'Observation de la Terre (SPOT), offer a highly useful data source for mapping the composition of these cities and examining their changes over time. The utility and range of applications for remotely sensed data in urban environments could be improved with a more appropriate conceptual model relating urban environments to the sampling resolutions of imaging sensors and processing routines. Hence, the aim of this work was to take the Vegetation-Impervious surface-Soil (VIS) model of urban composition and match it with the most appropriate image processing methodology to deliver information on VIS composition for urban environments. Several approaches were evaluated for mapping the urban composition of Brisbane city (south-cast Queensland, Australia) using Landsat 5 Thematic Mapper data and 1:5000 aerial photographs. The methods evaluated were: image classification; interpretation of aerial photographs; and constrained linear mixture analysis. Over 900 reference sample points on four transects were extracted from the aerial photographs and used as a basis to check output of the classification and mixture analysis. Distinctive zonations of VIS related to urban composition were found in the per-pixel classification and aggregated air-photo interpretation; however, significant spectral confusion also resulted between classes. In contrast, the VIS fraction images produced from the mixture analysis enabled distinctive densities of commercial, industrial and residential zones within the city to be clearly defined, based on their relative amount of vegetation cover. The soil fraction image served as an index for areas being (re)developed. The logical match of a low (L)-resolution, spectral mixture analysis approach with the moderate spatial resolution image data, ensured the processing model matched the spectrally heterogeneous nature of the urban environments at the scale of Landsat Thematic Mapper data.

Development of a generic crop model template in the cropping system model APSIM

The Agricultural Production Systems slMulator, APSIM, is a cropping system modelling environment that simulates the dynamics of soil-plant-management interactions within a single crop or a cropping system. Adaptation of previously developed crop models has resulted in multiple crop modules in APSIM, which have low scientific transparency and code efficiency. A generic crop model template (GCROP) has been developed to capture unifying physiological principles across crops (plant types) and to provide modular and efficient code for crop modelling. It comprises a standard crop interface to the APSIM engine, a generic crop model structure, a crop process library, and well-structured crop parameter files. The process library contains the major science underpinning the crop models and incorporates generic routines based on physiological principles for growth and development processes that are common across crops. It allows APSIM to simulate different crops using the same set of computer code. The generic model structure and parameter files provide an easy way to test, modify, exchange and compare modelling approaches at process level without necessitating changes in the code. The standard interface generalises the model inputs and outputs, and utilises a standard protocol to communicate with other APSIM modules through the APSIM engine. The crop template serves as a convenient means to test new insights and compare approaches to component modelling, while maintaining a focus on predictive capability. This paper describes and discusses the scientific basis, the design, implementation and future development of the crop template in APSIM. On this basis, we argue that the combination of good software engineering with sound crop science can enhance the rate of advance in crop modelling. Crown Copyright (C) 2002 Published by Elsevier Science B.V. All rights reserved.

Linking physiological and architectural models of cotton

Despite the strong influence of plant architecture on crop yield, most crop models either ignore it or deal with it in a very rudimentary way. This paper demonstrates the feasibility of linking a model that simulates the morphogenesis and resultant architecture of individual cotton plants with a crop model that simulates the effects of environmental factors on critical physiological processes and resulting yield in cotton. First the varietal parameters of the models were made concordant. Then routines were developed to allocate the flower buds produced each day by the crop model amongst the potential positions generated by the architectural model. This allocation is done according to a set of heuristic rules. The final weight of individual bolls and the shedding of buds and fruit caused by water, N, and C stresses are processed in a similar manner. Observations of the positions of harvestable fruits, both within and between plants, made under a variety of agronomic conditions that had resulted in a broad range of plant architectures were compared to those predicted by the model with the same environmental inputs. As illustrated by comparisons of plant maps, the linked models performed reasonably well, though performance of the fruiting point allocation and shedding algorithms could probably be improved by further analysis of the spatial relationships of retained fruit. (C) 2002 Elsevier Science Ltd. All rights reserved.