Telling bodies, mapping knowledge : recontextualising the dancer’s corporeality using a modular choreographic model

Creative Development: The Body and Light. Within the current cultural climate, the independent choreographer struggles to pursue and establish their artistic career outside the infrastructure of mainstream dance companies. The independent choreographer is challenged to articulate alternative choreographic models without the support of that infrastructure. My research examines that challenge by exploring my own independent choreographic practice through a number of performance-based dance projects. This exploration will be underpinned by theoretical research to enable clarification of the tacit understandings of an embodied practice and the point of intersection between practice and theory so as to articulate alternative choreographic models. As a starting point for that enquiry, an example is provided of how questions that emerge from within the choreographic practice can be discussed in terms of research through an initial investigation exploring light in relation to the moving body and the implications of atmospheres.

Mapping, monitoring, and modelling of hazardous waste sites

Management of the industrial nations' hazardous waste is a current and exponentially increasing, global threatening situation. Improved environmental information must be obtained and managed concerning the current status, temporal dynamics and potential future status of these critical sites. To test the application of spatial environmental techniques to the problem of hazardous waste sites, as Superfund (CERCLA) test site was chosen in an industrial/urban valley experiencing severe TCE, PCE, and CTC ground water contamination. A paradigm is presented for investigating spatial/environmental tools available for the mapping, monitoring and modelling of the environment and its toxic contaminated plumes. This model incorporates a range of technical issues concerning the collection of data as augmented by remotely sensed tools, the format and storage of data utilizing geographic information systems, and the analysis and modelling of environment through the use of advance GIS analysis algorithms and geophysic models of hydrologic transport including statistical surface generation. This spatial based approach is evaluated against the current government/industry standards of operations. Advantages and lessons learned of the spatial approach are discussed.

Wetlands : a perspective for mapping, monitoring, and modeling

Experience gained from numerous projects conducted by the U.S. Environmental Protection Agency's (EPA) Environmental Monitoring Systems Laboratory in Las Vegas, Nevada has provided insight to functional issues of mapping, monitoring, and modeling of wetland habitats. Three case studies in poster form describe these issues pertinent to managing wetland resources as mandated under Federal laws. A multiphase project was initiated by the EPA Alaska operations office to provide detailed wetland mapping of arctic plant communities in an area under petroleum development pressure. Existing classification systems did not meet EPA needs. Therefore a Habitat Classification System (HCS) derived from aerial photography was compiled. In conjunction with this photointerpretive keys were developed. These products enable EPA personnel to map large inaccessible areas of the arctic coastal plain and evaluate the sensitivity of various wetland habitats relative to petroleum development needs.

Small angle X-ray scattering mapping and kinetics study of sub-critical CO2 sorption by two Australian coals

Time- and position-resolved synchrotron small angle X-ray scattering data were acquired from samples of two Australian coal seams: Bulli seam (Bulli 4, Ro=1.42%, Sydney Basin), which naturally contains CO2 and Baralaba seam (Ro=0.67%, Bowen Basin), a potential candidate for sequestering CO2. This experimental approach has provided unique, pore-size-specific insights into the kinetics of CO2 sorption in the micro- and small mesopores (diameter 5 to 175 Å) and the density of the sorbed CO2 at reservoir-like conditions of temperature and hydrostatic pressure. For both samples, at pressures above 5 bar, the density of CO2 confined in pores was found to be uniform, with no densification in near-wall regions. In the Bulli 4 sample, CO2 first flooded the slit pores between polyaromatic sheets. In the pore-size range analysed, the confined CO2 density was close to that of the free CO2. The kinetics data are too noisy for reliable quantitative analysis, but qualitatively indicate faster kinetics in mineral-matter-rich regions. In the Baralaba sample, CO2 preferentially invaded the smallest micropores and the confined CO2 density was up to five times that of the free CO2. Faster CO2 sorption kinetics was found to be correlated with higher mineral matter content but, the mineral-matter-rich regions had lower-density CO2 confined in their pores. Remarkably, the kinetics was pore-size dependent, being faster for smaller pores. These results suggest that injection into the permeable section of an interbedded coal-clastic sequence could provide a viable combination of reasonable injectivity and high sorption capacity.

Semantic querying of business process models

Determining similarity between business process models has recently gained interest in the business process management community. So far similarity was addressed separately either at semantic or structural aspect of process models. Also, most of the contributions that measure similarity of process models assume an ideal case when process models are enriched with semantics - a description of meaning of process model elements. However, in real life this results in a heavy human effort consuming pre-processing phase which is often not feasible. In this paper we propose an automated approach for querying a business process model repository for structurally and semantically relevant models. Similar to the search on the Internet, a user formulates a BPMN-Q query and as a result receives a list of process models ordered by relevance to the query. We provide a business process model search engine implementation for evaluation of the proposed approach.

Mapping a candidate gene (MdMYB10) for red flesh and foliage colour in apple

BACKGROUND Integrating plant genomics and classical breeding is a challenge for both plant breeders and molecular biologists. Marker-assisted selection (MAS) is a tool that can be used to accelerate the development of novel apple varieties such as cultivars that have fruit with anthocyanin through to the core. In addition, determining the inheritance of novel alleles, such as the one responsible for red flesh, adds to our understanding of allelic variation. Our goal was to map candidate anthocyanin biosynthetic and regulatory genes in a population segregating for the red flesh phenotypes. RESULTS We have identified the Rni locus, a major genetic determinant of the red foliage and red colour in the core of apple fruit. In a population segregating for the red flesh and foliage phenotype we have determined the inheritance of the Rni locus and DNA polymorphisms of candidate anthocyanin biosynthetic and regulatory genes. Simple Sequence Repeats (SSRs) and Single Nucleotide Polymorphisms (SNPs) in the candidate genes were also located on an apple genetic map. We have shown that the MdMYB10 gene co-segregates with the Rni locus and is on Linkage Group (LG) 09 of the apple genome. CONCLUSION We have performed candidate gene mapping in a fruit tree crop and have provided genetic evidence that red colouration in the fruit core as well as red foliage are both controlled by a single locus named Rni. We have shown that the transcription factor MdMYB10 may be the gene underlying Rni as there were no recombinants between the marker for this gene and the red phenotype in a population of 516 individuals. Associating markers derived from candidate genes with a desirable phenotypic trait has demonstrated the application of genomic tools in a breeding programme of a horticultural crop species.

Semantic search as inference : applications in health informatics

This thesis developed new search engine models that elicit the meaning behind the words found in documents and queries, rather than simply matching keywords. These new models were applied to searching medical records: an area where search is particularly challenging yet can have significant benefits to our society.

Hunting and gathering : new imperatives in mapping and collecting student learning data to assure quality outcomes

Assurance of learning (AOL) is a quality enhancement and quality assurance process used in higher education. It involves a process of determining programme learning outcomes and standards, and systematically gathering evidence to measure students' performance on these. The systematic assessment of whole-of-programme outcomes provides a basis for curriculum development and management, continuous improvement, and accreditation. To better understand how AOL processes operate, a national study of university practices across one discipline area, business and management, was undertaken. To solicit data on AOL practice, interviews were undertaken with a sample of business school representatives (n = 25). Two key processes emerged: (1) mapping of graduate attributes and (2) collection of assurance data. External drivers such as professional accreditation and government legislation were the primary reasons for undertaking AOL outcomes but intrinsic motivators in relation to continuous improvement were also evident. The facilitation of academic commitment was achieved through an embedded approach to AOL by the majority of universities in the study. A sustainable and inclusive process of AOL was seen to support wider stakeholder engagement in the development of higher education learning outcomes.

Investigating subspace distances in semantic spaces

Semantic space models of word meaning derived from co-occurrence statistics within a corpus of documents, such as the Hyperspace Analogous to Language (HAL) model, have been proposed in the past. While word similarity can be computed using these models, it is not clear how semantic spaces derived from different sets of documents can be compared. In this paper, we focus on this problem, and we revisit the proposal of using semantic subspace distance measurements [1]. In particular, we outline the research questions that still need to be addressed to investigate and validate these distance measures. Then, we describe our plans for future research.

Semantic spaces : measuring the distance between different subspaces

Semantic Space models, which provide a numerical representation of words’ meaning extracted from corpus of documents, have been formalized in terms of Hermitian operators over real valued Hilbert spaces by Bruza et al. [1]. The collapse of a word into a particular meaning has been investigated applying the notion of quantum collapse of superpositional states [2]. While the semantic association between words in a Semantic Space can be computed by means of the Minkowski distance [3] or the cosine of the angle between the vector representation of each pair of words, a new procedure is needed in order to establish relations between two or more Semantic Spaces. We address the question: how can the distance between different Semantic Spaces be computed? By representing each Semantic Space as a subspace of a more general Hilbert space, the relationship between Semantic Spaces can be computed by means of the subspace distance. Such distance needs to take into account the difference in the dimensions between subspaces. The availability of a distance for comparing different Semantic Subspaces would enable to achieve a deeper understanding about the geometry of Semantic Spaces which would possibly translate into better effectiveness in Information Retrieval tasks.

Locating people in video from semantic descriptions : a new database and approach

The location of previously unseen and unregistered individuals in complex camera networks from semantic descriptions is a time consuming and often inaccurate process carried out by human operators, or security staff on the ground. To promote the development and evaluation of automated semantic description based localisation systems, we present a new, publicly available, unconstrained 110 sequence database, collected from 6 stationary cameras. Each sequence contains detailed semantic information for a single search subject who appears in the clip (gender, age, height, build, hair and skin colour, clothing type, texture and colour), and between 21 and 290 frames for each clip are annotated with the target subject location (over 11,000 frames are annotated in total). A novel approach for localising a person given a semantic query is also proposed and demonstrated on this database. The proposed approach incorporates clothing colour and type (for clothing worn below the waist), as well as height and build to detect people. A method to assess the quality of candidate regions, as well as a symmetry driven approach to aid in modelling clothing on the lower half of the body, is proposed within this approach. An evaluation on the proposed dataset shows that a relative improvement in localisation accuracy of up to 21 is achieved over the baseline technique.

The application of luminance mapping to discomfort glare : a modified glare index for green buildings

Unfortunately, there is no reliable method to adequately quantify discomfort glare. One of the world's largest investigations on discomfort glare was conducted in five Green Star office buildings in Brisbane. Luminance mapping via high dynamic range images and Post Occupancy Evaluation surveys were used in the data collection. A new glare index, termed the Unified Glare Probability, was developed to predict discomfort glare within these types of office buildings.

Fashion meets journalism : mapping and evaluating Australian fashion journalism

Fashion journalism can be understood as a complex, inter-dependent set of professional practices that have arisen in a variety of media at the intersection of fashion and journalism. This thesis, Fashion Meets Journalism: Mapping and Evaluating Australian Fashion Journalism, answers the question, 'What is Australian fashion journalism?' in three stages: First, it maps the extent of fashion journalism across media in Australia to locate the field and focus on the sites of fashion journalism; second, it foregrounds practices of the journalism branch, evaluating how and why the field is pitted against other types of journalism when they share an inter-dependent set of professional practices. The opinions of leading industry producers are also sought regarding the matter. Then, considering the current position of fashion journalism, implications for fashion media and journalism are explored in order to improve the visibility of fashion journalism and solidify it as a professional practice.

Mapping eQTLs in the Norfolk Island genetic isolate identifies candidate genes for CVD risk traits

Cardiovascular disease (CVD) affects millions of people worldwide and is influenced by numerous factors, including lifestyle and genetics. Expression quantitative trait loci (eQTLs) influence gene expression and are good candidates for CVD risk. Founder-effect pedigrees can provide additional power to map genes associated with disease risk. Therefore, we identified eQTLs in the genetic isolate of Norfolk Island (NI) and tested for associations between these and CVD risk factors. We measured genome-wide transcript levels of blood lymphocytes in 330 individuals and used pedigree-based heritability analysis to identify heritable transcripts. eQTLs were identified by genome-wide association testing of these transcripts. Testing for association between CVD risk factors (i.e., blood lipids, blood pressure, and body fat indices) and eQTLs revealed 1,712 heritable transcripts (p < 0.05) with heritability values ranging from 0.18 to 0.84. From these, we identified 200 cis-acting and 70 trans-acting eQTLs (p < 1.84 × 10(-7)) An eQTL-centric analysis of CVD risk traits revealed multiple associations, including 12 previously associated with CVD-related traits. Trait versus eQTL regression modeling identified four CVD risk candidates (NAAA, PAPSS1, NME1, and PRDX1), all of which have known biological roles in disease. In addition, we implicated several genes previously associated with CVD risk traits, including MTHFR and FN3KRP. We have successfully identified a panel of eQTLs in the NI pedigree and used this to implicate several genes in CVD risk. Future studies are required for further assessing the functional importance of these eQTLs and whether the findings here also relate to outbred populations.