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.

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.

Teacher Use of Learners' Native Language in the Foreign Language Classroom

This article reports on an exploratory study into the use of students' native language (NL) by teachers in the foreign language (FL) classroom. The project was undertaken by four teachers of beginner French at the University of Queensland. The teachers' aim was to investigate the use of NL in a context which actively promotes an immersion approach to FL teaching. The audio recordings of the teachers' speech were transcribed to provide data for estimating the amount of NL, and for analyzing the various instances of NL use. The study indicates that the activity type is a significant variable affecting NL amount. It also isolates two strategic uses of NL, translating FL words into NL, and contrasting NL and FL forms, both of which involve intrasentential code switching with NL words embedded in an FL sentence. The study suggests that these strategies may facilitate acquisition during immersion in FL, but experimental research is needed to test the hypothesis that translation and contrast facilitate learning of FL vocabulary and grammar.

An on-line investigation of lexical ambiguity processing in schizophrenia

The processing of lexical ambiguity in context was investigated in eight individuals with schizophrenia and a matched control group. Participants made speeded lexical decisions on the third word in auditory word triplets representing concordant (coin-bank-money), discordant (river-bank-money). neutral (day-bank-money), and unrelated (river-day-money) conditions. When the interstimulus interval (ISI) between the words was 100 ms. individuals with schizophrenia demonstrated priming consistent with selective. context-based lexical activation. At 1250 ms ISI a pattern of nonselective meaning facilitation was obtained. These results suggest an attentional breakdown in the sustained inhibition of meanings on the basis of lexical context. (C) 2002 Elsevier Science (USA).

Language choice of the Foochows in Sarawak, Malaysia

This paper investigates the factors affecting the language choices of the Chinese Foochows of Sarawak, focusing in particular on how the use of the Foochow dialect vis-a`-vis English and other languages might potentially result in a shift in language allegiance away from Foochow. In the context of Sarawak, the Foochows are a substantial, cohesive and homogeneous Chinese ethnic group with a distinctive language and ethnic identity. One would predict that they would engage in extensive language maintenance behaviour. Instead, Foochows living in non-Foochow dominant areas do not seem to have sufficient attachment to the language to transmit it to the next generation. Is this because the Foochows consider that accommodating to communicative norms is more important than preserving their native language as an inherent symbol of their ethnic identity? Or is it the result of the Foochows’ insecurity about the prestige of the dialect and the status of the Foochow people? These issues of accommodation and language allegiance are discussed, based on interview and questionnaire data from 11 Foochow participants. This data set is part of a larger study on the language use of different ethnic groups in multilingual organisational settings in Sarawak.

CRIM1 Regulates the Rate of Processing and Delivery of Bone Morphogenetic Proteins to the Cell Surface

The Crim1 gene is predicted to encode a transmembrane protein containing six von Willebrand-like cysteine-rich repeats (CRRs) similar to those in the BMP-binding antagonist Chordin (Chrd). In this study, we verify that CRIM1 is a glycosylated, Type I transmembrane protein and demonstrate that the extracellular CRR-containing domain can also be secreted, presumably via processing at the membrane. We have previously demonstrated Crim1 expression at sites consistent with an interaction with bone morphogenetic proteins (BMPs). Here we show that CRIM1 can interact with both BMP4 and BMP7 via the CRR-containing portion of the protein and in so doing acts as an antagonist in three ways. CRIM1 binding of BMP4 and -7 occurs when these proteins are co-expressed within the Golgi compartment of the cell and leads to (i) a reduction in the production and processing of preprotein to mature BMP, (ii) tethering of pre-BMP to the cell surface, and (iii) an effective reduction in the secretion of mature BMP. Functional antagonism was verified by examining the effect of coexpression of CRIM1 and BMP4 on metanephric explant culture. The presence of CRIM1 reduced the effective BMP4 concentration of the media, thereby acting as a BMP4 antagonist. Hence, CRIM1 modulates BMP activity by affecting its processing and delivery to the cell surface

An advanced method for eliminating impacts from frequency deviations in power system signal processing

Frequency deviation is a common problem for power system signal processing. Many power system measurements are carried out in a fixed sampling rate assuming the system operates in its nominal frequency (50 or 60 Hz). However, the actual frequency may deviate from the normal value from time to time due to various reasons such as disturbances and subsequent system transients. Measurement of signals based on a fixed sampling rate may introduce errors under such situations. In order to achieve high precision signal measurement appropriate algorithms need to be employed to reduce the impact from frequency deviation in the power system data acquisition process. This paper proposes an advanced algorithm to enhance Fourier transform for power system signal processing. The algorithm is able to effectively correct frequency deviation under fixed sampling rate. Accurate measurement of power system signals is essential for the secure and reliable operation of power systems. The algorithm is readily applicable to such occasions where signal processing is affected by frequency deviation. Both mathematical proof and numerical simulation are given in this paper to illustrate robustness and effectiveness of the proposed algorithm. Crown Copyright (C) 2003 Published by Elsevier Science B.V. All rights reserved.