On learning context-free and context-sensitive languages

The long short-term memory (LSTM) is not the only neural network which learns a context sensitive language. Second-order sequential cascaded networks (SCNs) are able to induce means from a finite fragment of a context-sensitive language for processing strings outside the training set. The dynamical behavior of the SCN is qualitatively distinct from that observed in LSTM networks. Differences in performance and dynamics are discussed.

A cognitive complexity metric applied to cognitive development

Two experiments tested predictions from a theory in which processing load depends on relational complexity (RC), the number of variables related in a single decision. Tasks from six domains (transitivity, hierarchical classification, class inclusion, cardinality, relative-clause sentence comprehension, and hypothesis testing) were administered to children aged 3-8 years. Complexity analyses indicated that the domains entailed ternary relations (three variables). Simpler binary-relation (two variables) items were included for each domain. Thus RC was manipulated with other factors tightly controlled. Results indicated that (i) ternary-relation items were more difficult than comparable binary-relation items, (ii) the RC manipulation was sensitive to age-related changes, (iii) ternary relations were processed at a median age of 5 years, (iv) cross-task correlations were positive, with all tasks loading on a single factor (RC), (v) RC factor scores accounted for 80% (88%) of age-related variance in fluid intelligence (compositionality of sets), (vi) binary- and ternary-relation items formed separate complexity classes, and (vii) the RC approach to defining cognitive complexity is applicable to different content domains. (C) 2002 Elsevier Science (USA). All rights reserved.

Testing the applicability of molecular genetic markers to population analyses of scleratinian corals

The abundance of coral reefs worldwide is in decline, and despite the ecological importance of reefs, only a limited number of DNA markers have been identified for scleractinian coral genetic studies. This paper addresses the search for new coral molecular markers and investigates the applicability of the cytochrome c oxidase subunit I (COI), the internal transcribed spacer region 1 (ITS1), and the pocilloporin gene to the question of intraspecific variation in the scleractinian coral Pocillopora verrucosa along the southeast African coastline. The COI fragment was 710 bp long and was identical for P. verrucosa (n = 10) and P. damicornis (n = 3). Only two different ITS1 sequences were found (differing by 13 bp insertion), but more importantly, 24% of the sequences were heterogenous indicating that different multiple copies of the sequence exist. Pocilloporin is an intronless gene that was absolutely conserved throughout all P. verrucosa populations (n = 50). Thus, the three DNA regions studied appear unsuitable for the population genetic analyses of P. verrucosa.

Consensus neuropathological diagnosis of common dementia syndromes: testing and standardising the use of multiple diagnostic criteria

The aim of this study was to assess the variation between neuropathologists in the diagnosis of common dementia syndromes when multiple published protocols are applied. Fourteen out of 18 Australian neuropathologists participated in diagnosing 20 cases (16 cases of dementia, 4 age-matched controls) using consensus diagnostic methods. Diagnostic criteria, clinical synopses and slides from multiple brain regions were sent to participants who were asked for case diagnoses. Diagnostic sensitivity, specificity, predictive value, accuracy and variability were determined using percentage agreement and kappa statistics. Using CERAD criteria, there was a high inter-rater agreement for cases with probable and definite Alzheimer's disease but low agreement for cases with possible Alzheimer's disease. Braak staging and the application of criteria for dementia with Lewy bodies also resulted in high inter-rater agreement. There was poor agreement for the diagnosis of frontotemporal dementia and for identifying small vessel disease. Participants rarely diagnosed more than one disease in any case. To improve efficiency when applying multiple diagnostic criteria, several simplifications were proposed and tested on 5 of the original 210 cases. Inter-rater reliability for the diagnosis of Alzheimer's disease and dementia with Lewy bodies significantly improved. Further development of simple and accurate methods to identify small vessel lesions and diagnose frontotemporal dementia is warranted.

Input-driven Language Learning

Input-driven models provide an explicit and readily testable account of language learning. Although we share Ellis's view that the statistical structure of the linguistic environment is a crucial and, until recently, relatively neglected variable in language learning, we also recognize that the approach makes three assumptions about cognition and language learning that are not universally shared. The three assumptions concern (a) the language learner as an intuitive statistician, (b) the constraints on what constitute relevant surface cues, and (c) the redescription problem faced by any system that seeks to derive abstract grammatical relations from the frequency of co-occurring surface forms and functions. These are significant assumptions that must be established if input-driven models are to gain wider acceptance. We comment on these issues and briefly describe a distributed, instance-based approach that retains the key features of the input-driven account advocated by Ellis but that also addresses shortcomings of the current approaches.

Testing landscape metrics as indicators of habitat loss and fragmentation in continuous eucalypt forests (Queensland, Australia)

Landscape metrics are widely applied in landscape ecology to quantify landscape structure. However, many are poorly tested and require rigorous validation if they are to serve as reliable indicators of habitat loss and fragmentation, such as Montreal Process Indicator 1.1e. We apply a landscape ecology theory, supported by exploratory and confirmatory statistical techniques, to empirically test landscape metrics for reporting Montreal Process Indicator 1.1e in continuous dry eucalypt forests of sub-tropical Queensland, Australia. Target biota examined included: the Yellow-bellied Glider (Petaurus australis); the diversity of nectar and sap feeding glider species including P. australis, the Sugar Glider P. breviceps, the Squirrel Glider P. norfolcensis, and the Feathertail Glider Acrobates pygmaeus; six diurnal forest birds species; total diurnal bird species diversity; and the density of nectar-feeding diurnal bird species. Two scales of influence were considered: the stand-scale (2 ha), and a series of radial landscape extents (500 m - 2 km; 78 - 1250 ha) surrounding each fauna transect. For all biota, stand-scale structural and compositional attributes were found to be more influential than landscape metrics. For the Yellow-bellied Glider, the proportion of trace habitats with a residual element of old spotted-gum/ironbark eucalypt trees was a significant landscape metric at the 2 km landscape extent. This is a measure of habitat loss rather than habitat fragmentation. For the diversity of nectar and sap feeding glider species, the proportion of trace habitats with a high coefficient of variation in patch size at the 750 m extent was a significant landscape metric. None of the landscape metrics tested was important for diurnal forest birds. We conclude that no single landscape metric adequately captures the response of the region's forest biota per se. This poses a major challenge to regional reporting of Montreal Process Indicator 1.1e, fragmentation of forest types.

Extending Learning Opportunities through a virtual faculty

This paper presents the notion of a virtual faculty as a viable alternative to extending and maintaining learner opportunities for students in regional universities or at universities where specialisations in which they are interested may not be offered. Staff from a number of Australian Universities participated in a CUTSD project to explore the viability of establishing a virtual faculty using videoconferencing as the medium of delivery. The success of this project was the result of close collaboration at a number of levels within the participating institutions and a willingness to explore effective approaches to teaching and learning for a videoconference environment.

Preparing students for the virtual organisation: an evaluation of learning with virtual learning technologies

The paper explores the development of learning behaviours in a virtual management course and the factors that impacted on this development. Data suggest that most teams experienced three kinds of learning behaviours – social, operational and content learning. We propose that the need for technical expertise and team participation will vary during these different stages of learning. Addressing the characteristics of these stages, we comment on the development of a ‘completion phase’ of team development. We argue that the extent to which teams demonstrate different learning stages has a significant impact on the development of on-line learning behaviours. Discussing these results, we suggest why different teams develop distinct learning behaviours, with accordant emphasis on teaching as a moderating and co ordinating role, despite current virtual team pedagogical expectations.