Formal methods within a totally functional approach to programming

Taking functional programming to its extremities in search of simplicity still requires integration with other development (e.g. formal) methods. Induction is the key to deriving and verifying functional programs, but can be simplified through packaging proofs with functions, particularly folds, on data (structures). Totally Functional Programming avoids the complexities of interpretation by directly representing data (structures) as platonic combinators - the functions characteristic to the data. The link between the two simplifications is that platonic combinators are a kind of partially-applied fold, which means that platonic combinators inherit fold-theoretic properties, but with some apparent simplifications due to the platonic combinator representation. However, despite observable behaviour within functional programming that suggests that TFP is widely-applicable, significant work remains before TFP as such could be widely adopted.

Multiresolution spatial databases: Making web-based spatial applications faster

Spatial data has now been used extensively in the Web environment, providing online customized maps and supporting map-based applications. The full potential of Web-based spatial applications, however, has yet to be achieved due to performance issues related to the large sizes and high complexity of spatial data. In this paper, we introduce a multiresolution approach to spatial data management and query processing such that the database server can choose spatial data at the right resolution level for different Web applications. One highly desirable property of the proposed approach is that the server-side processing cost and network traffic can be reduced when the level of resolution required by applications are low. Another advantage is that our approach pushes complex multiresolution structures and algorithms into the spatial database engine. That is, the developer of spatial Web applications needs not to be concerned with such complexity. This paper explains the basic idea, technical feasibility and applications of multiresolution spatial databases.

Assessing cost-effectiveness - Mental health: introduction to the study and methods

Objective: The Assessing Cost-Effectiveness - Mental Health (ACE-MH) study aims to assess from a health sector perspective, whether there are options for change that could improve the effectiveness and efficiency of Australia's current mental health services by directing available resources toward 'best practice' cost-effective services. Method: The use of standardized evaluation methods addresses the reservations expressed by many economists about the simplistic use of League Tables based on economic studies confounded by differences in methods, context and setting. The cost-effectiveness ratio for each intervention is calculated using economic and epidemiological data. This includes systematic reviews and randomised controlled trials for efficacy, the Australian Surveys of Mental Health and Wellbeing for current practice and a combination of trials and longitudinal studies for adherence. The cost-effectiveness ratios are presented as cost (A$) per disability-adjusted life year (DALY) saved with a 95% uncertainty interval based on Monte Carlo simulation modelling. An assessment of interventions on 'second filter' criteria ('equity', 'strength of evidence', 'feasibility' and 'acceptability to stakeholders') allows broader concepts of 'benefit' to be taken into account, as well as factors that might influence policy judgements in addition to cost-effectiveness ratios. Conclusions: The main limitation of the study is in the translation of the effect size from trials into a change in the DALY disability weight, which required the use of newly developed methods. While comparisons within disorders are valid, comparisons across disorders should be made with caution. A series of articles is planned to present the results.

Computational methods for prediction of T-cell epitopes - a framework for modelling, testing, and applications

Computational models complement laboratory experimentation for efficient identification of MHC-binding peptides and T-cell epitopes. Methods for prediction of MHC-binding peptides include binding motifs, quantitative matrices, artificial neural networks, hidden Markov models, and molecular modelling. Models derived by these methods have been successfully used for prediction of T-cell epitopes in cancer, autoimmunity, infectious disease, and allergy. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures and performed according to strict standards. This requires careful selection of data for model building, and adequate testing and validation. A range of web-based databases and MHC-binding prediction programs are available. Although some available prediction programs for particular MHC alleles have reasonable accuracy, there is no guarantee that all models produce good quality predictions. In this article, we present and discuss a framework for modelling, testing, and applications of computational methods used in predictions of T-cell epitopes. (C) 2004 Elsevier Inc. All rights reserved.

Snakes and kittens in the grass: No evidence for preferential processing of fear-relevant animals in visual search

Ohman and colleagues provided evidence for preferential processing of pictures depicting fear-relevant animals by showing that pictures of snakes and spiders are found faster among pictures of fiowers and mushrooms than vice versa and that the speed of detecting fear-relevant animals was not affected by set size whereas the speed of detecting fiowers/mushrooms was. Experiment 1 replicated this finding. Experiment 2, however, found similar search advantages when pictures of cats and horses or of wolves and big cats were to be found among pictures of flowers and mushrooms. Moreover, Experiment 3, in a within subject comparison, failed to find faster identification of snakes and spiders than of cats and horses among flowers and mushrooms. The present findings seem to indicate that previous reports of preferential processing of pictures of snakes and spiders in a visual search task may reflect a processing advantage for animal pictures in general rather than fear-relevance.

Why fear snakes and spiders? Evidence for a learning-based account of fear-relevant stimulus-processing

Fear-relevant stimuli, such as snakes, spiders and heights, preferentially capture attention as compared to nonfear-relevant stimuli. This is said to reflect an encapsulated mechanism whereby attention is captured by the simple perceptual features of stimuli that have evolutionary significance. Research, using pictures of snakes and spiders, has found some support for this account; however, participants may have had prior fear of snakes and spiders that influenced results. The current research compared responses of snake and spider experts who had little fear of snakes and spiders, and control participants across a series of affective priming and visual search tasks. Experts discriminated between dangerous and nondangerous snakes and spiders, and expert responses to pictures of nondangerous snakes and spiders differed from those of control participants. The current results dispute that stimulus fear relevance is based purely on perceptual features, and provides support for the role of learning and experience.

Individual differences in motivated social cognition: The case of self-serving information processing

Three experiments examined the hypothesis that people show consistency in motivated social cognitive processing across self-serving domains. Consistent with this hypothesis, Experiment 1 revealed that people who rated a task at which they succeeded as more important than a task at which they failed also cheated on a series of math problems, but only when they could rationalize their cheating as unintentional. Experiment 2 replicated this finding and demonstrated that a self-report measure of self-deception did not predict this rationalized cheating. Experiment 3 replicated Experiments 1 and 2 and ruled out several alternative explanations. These experiments suggest that people who show motivated processing in ego-protective domains also show motivated processing in extrinsic domains. These experiments also introduce a new measurement procedure for differentiating between intentional versus rationalized cheating.

Visuospatial processing and the function of prefrontal-parietal networks in autism spectrum disorders: a functional MRI study

Objective: Individuals with autism spectrum disorders typically have normal visuospatial abilities but impaired executive functioning, particularly in abilities related to working memory and attention. The aim of this study was to elucidate the functioning of frontoparietal networks underlying spatial working memory processes during mental rotation in persons with autism spectrum disorders. Method: Seven adolescent males with normal IQ with an autism spectrum disorder and nine age- and IQ-matched male comparison subjects underwent functional magnetic resonance imaging scans while performing a mental rotation task. Results: The autism spectrum disorders group showed less activation in lateral and medial premotor cortex, dorsolateral prefrontal cortex, anterior cingulate gyrus, and caudate nucleus. Conclusions: The finding of less activation in prefrontal regions but not in parietal regions supports a model of dysfunction of frontostriatal networks in autism spectrum disorders.

Normal and anomalous classification of category exemplars in schizophrenia

Background Schizophrenia has been associated with semantic memory impairment and previous studies report a difficulty in accessing semantic category exemplars (Moelter et al. 2005 Schizophr Res 78:209–217). The anterior temporal cortex (ATC) has been implicated in the representation of semantic knowledge (Rogers et al. 2004 Psychol Rev 111(1):205–235). We conducted a high-field (4T) fMRI study with the Category Judgment and Substitution Task (CJAST), an analogue of the Hayling test. We hypothesised that differential activation of the temporal lobe would be observed in schizophrenia patients versus controls. Methods Eight schizophrenia patients (7M : 1F) and eight matched controls performed the CJAST, involving a randomised series of 55 common nouns (from five semantic categories) across three conditions: semantic categorisation, anomalous categorisation and word reading. High-resolution 3D T1-weighted images and GE EPI with BOLD contrast and sparse temporal sampling were acquired on a 4T Bruker MedSpec system. Image processing and analyses were performed with SPM2. Results Differential activation in the left ATC was found for anomalous categorisation relative to category judgment, in patients versus controls. Conclusions We examined semantic memory deficits in schizophrenia using a novel fMRI task. Since the ATC corresponds to an area involved in accessing abstract semantic representations (Moelter et al. 2005), these results suggest schizophrenia patients utilise the same neural network as healthy controls, however it is compromised in the patients and the different ATC activity might be attributable to weakening of category-to-category associations.

A family of perfect hashing methods

Minimal perfect hash functions are used for memory efficient storage and fast retrieval of items from static sets. We present an infinite family of efficient and practical algorithms for generating order preserving minimal perfect hash functions. We show that almost all members of the family construct space and time optimal order preserving minimal perfect hash functions, and we identify the one with minimum constants. Members of the family generate a hash function in two steps. First a special kind of function into an r-graph is computed probabilistically. Then this function is refined deterministically to a minimal perfect hash function. We give strong theoretical evidence that the first step uses linear random time. The second step runs in linear deterministic time. The family not only has theoretical importance, but also offers the fastest known method for generating perfect hash functions.

Processing of mutated human proinsulin to mature insulin in the non-endocrine cell line, CHO

Heterologous genes encoding proproteins, including proinsulin, generally produce mature protein when expressed in endocrine cells while unprocessed or partially processed protein is produced in non-endocrine cells. Proproteins, which are normally processed in the regulated pathway restricted to endocrine cells, do not always contain the recognition sequence for cleavage by furin, the endoprotease specific to the constitutive pathway, the principal protein processing pathway in non-endocrine cells. Human proinsulin consists of B-Chain-C-peptide-A-Chain and cleavage at the B/C and C/A junctions is required for processing. The B/C, but not the C/A junction, is recognised and cleaved in the constitutive pathway. We expressed a human proinsulin and a mutated proinsulin gene with an engineered furin recognition sequence at the C/A junction and compared the processing efficiency of the mutant and native proinsulin in Chinese Hamster Ovary cells. The processing efficiency of the mutant proinsulin was 56% relative to 0.7% for native proinsulin. However, despite similar levels of mRNA being expressed in both cell lines, the absolute levels of immunoreactive insulin, normalized against mRNA levels, were 18-fold lower in the mutant proinsulin-expressing cells. As a result, there was only a marginal increase in absolute levels of insulin produced by these cells. This unexpected finding may result from preferential degradation of insulin in non-endocrine cells which lack the protection offered by the secretory granules found in endocrine cells.