A mixture model-based approach to the clustering of microarray expression data

Motivation: This paper introduces the software EMMIX-GENE that has been developed for the specific purpose of a model-based approach to the clustering of microarray expression data, in particular, of tissue samples on a very large number of genes. The latter is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. A feasible approach is provided by first selecting a subset of the genes relevant for the clustering of the tissue samples by fitting mixtures of t distributions to rank the genes in order of increasing size of the likelihood ratio statistic for the test of one versus two components in the mixture model. The imposition of a threshold on the likelihood ratio statistic used in conjunction with a threshold on the size of a cluster allows the selection of a relevant set of genes. However, even this reduced set of genes will usually be too large for a normal mixture model to be fitted directly to the tissues, and so the use of mixtures of factor analyzers is exploited to reduce effectively the dimension of the feature space of genes. Results: The usefulness of the EMMIX-GENE approach for the clustering of tissue samples is demonstrated on two well-known data sets on colon and leukaemia tissues. For both data sets, relevant subsets of the genes are able to be selected that reveal interesting clusterings of the tissues that are either consistent with the external classification of the tissues or with background and biological knowledge of these sets.

Pulpal heat changes with newly developed resin photopolymerisation systems

Composite resin is a widely-used direct tooth coloured restorative material. Photoactivation of the polymerisation reaction can be achieved by visible blue light from a range of light sources, including halogen lamps, metal halide lamps, plasma arc lamps, and Light Emitting Diode (LED) lights. Concerns have been raised that curing lights may induce a temperature rise that could be detrimental to the vitality of the dental pulp during the act of photoactivation. The present study examined heat changes associated with standardised class V restorations on the buccal surface of extracted premolar teeth, using a curing time of 40 seconds. The independent effects of type of light source, resin shade and remaining tooth thickness were assessed using a matrix experimental design. When a conventional halogen lamp, a metal halide lamp and two different LED lights were compared, it was found that both LED lamps elicited minimal thermal changes at the level of the dental pulp, whereas the halogen lamp induced greater changes and the metal halide lamp caused the greatest thermal insult of all the light sources. These thermal changes were influenced by resin shade, with different patterns for LED versus halogen or halide sources. Thermal stress reduced as the remaining thickness of tooth structure between the pulp and the cavity floor increased. From these results, it is concluded that LED lights produce the least thermal insult during photopolymerisation of composite resins.

Adaptive multiscale principal components analysis for online monitoring of wastewater treatment

Fault detection and isolation (FDI) are important steps in the monitoring and supervision of industrial processes. Biological wastewater treatment (WWT) plants are difficult to model, and hence to monitor, because of the complexity of the biological reactions and because plant influent and disturbances are highly variable and/or unmeasured. Multivariate statistical models have been developed for a wide variety of situations over the past few decades, proving successful in many applications. In this paper we develop a new monitoring algorithm based on Principal Components Analysis (PCA). It can be seen equivalently as making Multiscale PCA (MSPCA) adaptive, or as a multiscale decomposition of adaptive PCA. Adaptive Multiscale PCA (AdMSPCA) exploits the changing multivariate relationships between variables at different time-scales. Adaptation of scale PCA models over time permits them to follow the evolution of the process, inputs or disturbances. Performance of AdMSPCA and adaptive PCA on a real WWT data set is compared and contrasted. The most significant difference observed was the ability of AdMSPCA to adapt to a much wider range of changes. This was mainly due to the flexibility afforded by allowing each scale model to adapt whenever it did not signal an abnormal event at that scale. Relative detection speeds were examined only summarily, but seemed to depend on the characteristics of the faults/disturbances. The results of the algorithms were similar for sudden changes, but AdMSPCA appeared more sensitive to slower changes.

Research into telehealth applications in speech-language pathology

A literature review was conducted to investigate the extent to which telehealth has been researched within the domain of speech-language pathology and the outcomes of this research. A total of 13 studies were identified. Three early studies demonstrated that telehealth was feasible, although there was no discussion of the cost-effectiveness of this process in terms of patient outcomes. The majority of the subsequent studies indicated positive or encouraging outcomes resulting from telehealth. However, there were a number of shortcomings in the research, including a lack of cost-benefit information, failure to evaluate the technology itself, an absence of studies of the educational and informational aspects of telehealth in relation to speech-language pathology, and the use of telehealth in a limited range of communication disorders. Future research into the application of telehealth to speech-language pathology services must adopt a scientific approach, and have a well defined development and evaluation framework that addresses the effectiveness of the technique, patient outcomes and satisfaction, and the cost-benefit relationship.

The nexus of value chain integration and e-business applications on public sector agriculture R&D management

We examine the potential impact of interconnectivity of value chain partnerships through electronic means (e-business practices) on the management of Public Sector Agriculture R&D in Australia. We review the changing forms of managing research and development, the forces driving these changes, and R&D processes that are theoretically consistent with the move towards value chain involvement and the increase in active constituents in Public Sector Agriculture R&D. We then explore the potential of emerging e-business models to change the patterns of inter-connectivity, speed and omnipresence of partners in the value chain. Three e-business R&D management practices are identified that provide the prerequisite flexibility necessary to take advantage of opportunistic markets. These R&D business practices are: compressing R&D to reduce time to market, fostering co-development to enter a market at the last moment and building flexible products that allow adjustment at the last possible moment. Some fundamental reallocation of existing resources will be required to meet these markets. Implications of these e-business practices for R&D management are discussed.

Optical barcoding of colloidal suspensions: applications in genomics, proteomics and drug discovery

The enormous amount of information generated through sequencing of the human genome has increased demands for more economical and flexible alternatives in genomics, proteomics and drug discovery. Many companies and institutions have recognised the potential of increasing the size and complexity of chemical libraries by producing large chemical libraries on colloidal support beads. Since colloid-based compounds in a suspension are randomly located, an encoding system such as optical barcoding is required to permit rapid elucidation of the compound structures. We describe in this article innovative methods for optical barcoding of colloids for use as support beads in both combinatorial and non-combinatorial libraries. We focus in particular on the difficult problem of barcoding extremely large libraries, which if solved, will transform the manner in which genomics, proteomics and drug discovery research is currently performed.

Location of innervation zones of sternocleidomastoid and scalene muscles - a basis for clinical and research electromyography applications

Objectives: Advances in surface electromyography (sEMG) techniques provide a clear indication that refinement of electrode location relative to innervation zones (IZ) is required in order to optimise the accuracy, relevance and repeatability of the sEMG signals. The aim of this study was to identify the IZ for the sternocleidomastoid and anterior scalene muscles to provide guidelines for electrode positioning for future clinical and research applications. Methods: Eleven volunteer subjects participated in this study. Myoelectric signals were detected from the sternal and clavicular heads of the stemocleidomastoid and the anterior scalene muscles bilaterally using a linear array of 8 electrodes during isometric cervical flexion contractions. The signals were reviewed and the IZ(s) were identified, marked on the subjects' skin and measurements were obtained relative to selected anatomical landmarks. Results: The position of the IZ lay consistently around the mid-point or in the superior portion of the muscles studied. Conclusions: Results suggest that electrodes should be positioned over the lower portion of the muscle and not the mid-point, which has been commonly used in previous studies. Recommendations for sensor placement on these muscles should assist investigators and clinicians to ensure improved validity in future sEMG applications. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.

R-matrices and the tensor product graph method

A systematic method for constructing trigonometric R-matrices corresponding to the (multiplicity-free) tensor product of any two affinizable representations of a quantum algebra or superalgebra has been developed by the Brisbane group and its collaborators. This method has been referred to as the Tensor Product Graph Method. Here we describe applications of this method to untwisted and twisted quantum affine superalgebras.

Fixed point theorems of upper semicontinuous multivalued mappings with applications in hyperconvex metric spaces

In the present paper, we establish two fixed point theorems for upper semicontinuous multivalued mappings in hyperconvex metric spaces and apply these to study coincidence point problems and minimax problems. (C) 2002 Elsevier Science (USA). All rights reserved.

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.