869 resultados para BWW ontology


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Poor health and injury represent major obstacles to the future economic security of Australia. The national economic cost of work-related injury is estimated at $57.5 billion p/a. Since exposure to high physical demands is a major risk factor for musculoskeletal injury, monitoring and managing such physical activity levels in workers is a potentially important injury prevention strategy. Current injury monitoring practices are inadequate for the provision of clinically valuable information about the tissue specific responses to physical exertion. Injury of various soft tissue structures can manifest over time through accumulation of micro-trauma. Such micro-trauma has a propensity to increase the risk of acute injuries to soft-tissue structures such as muscle or tendon. As such, the capacity to monitor biomarkers that result from the disruption of these tissues offers a means of assisting the pre-emptive management of subclinical injury prior to acute failure or for evaluation of recovery processes. Here we have adopted an in-vivo exercise induced muscle damage model allowing the application of laboratory controlled conditions to assist in uncovering biochemical indicators associated with soft-tissue trauma and recovery. Importantly, urine was utilised as the diagnostic medium since it is non-invasive to collect, more acceptable to workers and less costly to employers. Moreover, it is our hypothesis that exercise induced tissue degradation products enter the circulation and are subsequently filtered by the kidney and pass through to the urine. To test this hypothesis a range of metabolomic and proteomic discovery-phase techniques were used, along with targeted approaches. Several small molecules relating to tissue damage were identified along with a series of skeletal muscle-specific protein fragments resulting from exercise induced soft-tissue damage. Each of the potential biomolecular markers appeared to be temporally present within urine. Moreover, the regulation of abundance seemed to be associated with functional recovery following the injury. This discovery may have important clinical applications for monitoring of a variety of inflammatory myopathies as well as novel applications in monitoring of the musculoskeletal health status of workers, professional athletes and/or military personnel to reduce the onset of potentially debilitating musculoskeletal injuries within these professions.

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Background: Multiple sclerosis (MS) is the most common cause of chronic neurologic disability beginning in early to middle adult life. Results from recent genome-wide association studies (GWAS) have substantially lengthened the list of disease loci and provide convincing evidence supporting a multifactorial and polygenic model of inheritance. Nevertheless, the knowledge of MS genetics remains incomplete, with many risk alleles still to be revealed. Methods: We used a discovery GWAS dataset (8,844 samples, 2,124 cases and 6,720 controls) and a multi-step logistic regression protocol to identify novel genetic associations. The emerging genetic profile included 350 independent markers and was used to calculate and estimate the cumulative genetic risk in an independent validation dataset (3,606 samples). Analysis of covariance (ANCOVA) was implemented to compare clinical characteristics of individuals with various degrees of genetic risk. Gene ontology and pathway enrichment analysis was done using the DAVID functional annotation tool, the GO Tree Machine, and the Pathway-Express profiling tool. Results: In the discovery dataset, the median cumulative genetic risk (P-Hat) was 0.903 and 0.007 in the case and control groups, respectively, together with 79.9% classification sensitivity and 95.8% specificity. The identified profile shows a significant enrichment of genes involved in the immune response, cell adhesion, cell communication/ signaling, nervous system development, and neuronal signaling, including ionotropic glutamate receptors, which have been implicated in the pathological mechanism driving neurodegeneration. In the validation dataset, the median cumulative genetic risk was 0.59 and 0.32 in the case and control groups, respectively, with classification sensitivity 62.3% and specificity 75.9%. No differences in disease progression or T2-lesion volumes were observed among four levels of predicted genetic risk groups (high, medium, low, misclassified). On the other hand, a significant difference (F = 2.75, P = 0.04) was detected for age of disease onset between the affected misclassified as controls (mean = 36 years) and the other three groups (high, 33.5 years; medium, 33.4 years; low, 33.1 years). Conclusions: The results are consistent with the polygenic model of inheritance. The cumulative genetic risk established using currently available genome-wide association data provides important insights into disease heterogeneity and completeness of current knowledge in MS genetics.

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Tag recommendation is a specific recommendation task for recommending metadata (tag) for a web resource (item) during user annotation process. In this context, sparsity problem refers to situation where tags need to be produced for items with few annotations or for user who tags few items. Most of the state of the art approaches in tag recommendation are rarely evaluated or perform poorly under this situation. This paper presents a combined method for mitigating sparsity problem in tag recommendation by mainly expanding and ranking candidate tags based on similar items’ tags and existing tag ontology. We evaluated the approach on two public social bookmarking datasets. The experiment results show better accuracy for recommendation in sparsity situation over several state of the art methods.

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A growing body of evidence suggests that mitochondrial function may be important in brain development and psychiatric disorders. However, detailed expression profiles of those genes in human brain development and fear-related behavior remain unclear. Using microarray data available from the public domain and the Gene Ontology analysis, we identified the genes and the functional categories associated with chronological age in the prefrontal cortex (PFC) and the caudate nucleus (CN) of psychiatrically normal humans ranging in age from birth to 50 years. Among those, we found that a substantial number of genes in the PFC (115) and the CN (117) are associated with the GO term: mitochondrion (FDR qv <0.05). A greater number of the genes in the PFC (91%) than the genes in the CN (62%) showed a linear increase in expression during postnatal development. Using quantitative PCR, we validated the developmental expression pattern of four genes including monoamine oxidase B (MAOB), NADH dehydrogenase flavoprotein (NDUFV1), mitochondrial uncoupling protein 5 (SLC25A14) and tubulin beta-3 chain (TUBB3). In mice, overall developmental expression pattern of MAOB, SLC25A14 and TUBB3 in the PFC were comparable to the pattern observed in humans (p<0.05). However, mice selectively bred for high fear did not exhibit normal developmental changes of MAOB and TUBB3. These findings suggest that the genes associated with mitochondrial function in the PFC play a significant role in brain development and fear-related behavior.

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Objective: To develop a system for the automatic classification of pathology reports for Cancer Registry notifications. Method: A two pass approach is proposed to classify whether pathology reports are cancer notifiable or not. The first pass queries pathology HL7 messages for known report types that are received by the Queensland Cancer Registry (QCR), while the second pass aims to analyse the free text reports and identify those that are cancer notifiable. Cancer Registry business rules, natural language processing and symbolic reasoning using the SNOMED CT ontology were adopted in the system. Results: The system was developed on a corpus of 500 histology and cytology reports (with 47% notifiable reports) and evaluated on an independent set of 479 reports (with 52% notifiable reports). Results show that the system can reliably classify cancer notifiable reports with a sensitivity, specificity, and positive predicted value (PPV) of 0.99, 0.95, and 0.95, respectively for the development set, and 0.98, 0.96, and 0.96 for the evaluation set. High sensitivity can be achieved at a slight expense in specificity and PPV. Conclusion: The system demonstrates how medical free-text processing enables the classification of cancer notifiable pathology reports with high reliability for potential use by Cancer Registries and pathology laboratories.

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As the boundaries between public and private, human and technology, digital and social, mediated and natural, online and offline become increasingly blurred in modern techno-social hybrid societies, sociology as a discipline needs to adapt and adopt new ways of accounting for these digital cultures. In this paper I use the social networking site Pinterest to demonstrate how people today are shaped by, and in turn shape, the digital tools they are assembled with. Digital sociology is emerging as a sociological subdiscipline that engages with the convergence of the digital and the social. However, there seems to be a focus on developing new methods for studying digital social life, yet a neglect of concrete explorations of its culture. I argue for the need for critical socio-cultural ‘thick description’ to account for the interrelations between humans and technologies in modern digitally mediated cultures.

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Recent literature on Enterprise System (ES) implementation projects highlights the importance of Knowledge Integration (KI) for implementation success. The fundamental characteristics of ES - integration of modules, business process view, and aspects of information transparency - necessitate that all frequent end-users share a reasonable amount of common knowledge and integrate their knowledge to yield new knowledge. Unfortunately, the importance of KI is often overlooked and little about the role of KI in ES success is known. In this chapter, the authors study the KI impact on ES success that is relevant to the ES post-implementation in support of organizations' returns on their ES investments. They adopt the ES post-implementation segment of ES utilization to explore whether the KI approach is causally linked to ES success. The research model was tested in a multi-industry sample in Malaysia from which data was gathered from managerial and operational employees spread across six large organizations. Consistent with the explanation by knowledge-based theory, the results show that KI was valid and significantly related to the outcome of ES that relates to an organization's performance, which the authors refer to as ES success. The KI positive impact on the success of ES drives one to highlight the importance of ontological KI in the complexity of the ES environment. The authors believe that focusing on an ontology through the KI perspective can make significant contributions to current ES problems.

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Service mismatches involve the adaptation of structural and behavioural interfaces of services, which in practice incurs long lead times through manual, coding e ort. We propose a framework, complementary to conventional service adaptation, to extract comprehensive and seman- tically normalised service interfaces, useful for interoperability in large business networks and the Internet of Services. The framework supports introspection and analysis of large and overloaded operational signa- tures to derive focal artefacts, namely the underlying business objects of services. A more simpli ed and comprehensive service interface layer is created based on these, and rendered into semantically normalised in- terfaces, given an ontology accrued through the framework from service analysis history. This opens up the prospect of supporting capability comparisons across services, and run-time request backtracking and ad- justment, as consumers discover new features of a service's operations through corresponding features of similar services. This paper provides a rst exposition of the service interface synthesis framework, describing patterns having novel requirements for unilateral service adaptation, and algorithms for interface introspection and business object alignment. A prototype implementation and analysis of web services drawn from com- mercial logistic systems are used to validate the algorithms and identify open challenges and future research directions.

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As of today, online reviews have become more and more important in decision making process. In recent years, the problem of identifying useful reviews for users has attracted significant attentions. For instance, in order to select reviews that focus on a particular feature, researchers proposed a method which extracts all associated words of this feature as the relevant information to evaluate and find appropriate reviews. However, the extraction of associated words is not that accurate due to the noise in free review text, and this affects the overall performance negatively. In this paper, we propose a method to select reviews according to a given feature by using a review model generated based upon a domain ontology called product feature taxonomy. The proposed review model provides relevant information about the hierarchical relationships of the features in the review which captures the review characteristics accurately. Our experiment results based on real world review dataset show that our approach is able to improve the review selection performance according to the given criteria effectively.

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A exhibition of sculptural assemblages that continue my exploration of self-portraiture and the sculptural object. The work specifically extends the formal vocabulary of my studio to incorporate smaller composite arrangements with an emphasis on the sculptural support. Small objects that are either modelled or cast from life are assembled into four tableaux that respond to the object-relations that arise through the production process. The resulting exhibiton thus acts a meditation on the ontology of art practice, conceived as a topology of objects.

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In this study we undertook deep sequencing of the blood cockle, Anadara trapezia, transcriptome to generate genomic resources for future functional genomics analyses. Over 27 million high quality paired end reads were assembled into 75 024 contigs. Of these contigs, 29 013 (38.7%) received significant BLASTx hits and gene ontology (GO) terms were assigned to 13 718 of these sequences. This resourcewill facilitate physiological genomic studies to test the gene expression response of A. trapezia to various environmental stresses.

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Text is the main method of communicating information in the digital age. Messages, blogs, news articles, reviews, and opinionated information abounds on the Internet. People commonly purchase products online and post their opinions about purchased items. This feedback is displayed publicly to assist others with their purchasing decisions, creating the need for a mechanism with which to extract and summarize useful information for enhancing the decision-making process. Our contribution is to improve the accuracy of extraction by combining different techniques from three major areas, named Data Mining, Natural Language Processing techniques and Ontologies. The proposed framework sequentially mines product’s aspects and users’ opinions, groups representative aspects by similarity, and generates an output summary. This paper focuses on the task of extracting product aspects and users’ opinions by extracting all possible aspects and opinions from reviews using natural language, ontology, and frequent “tag” sets. The proposed framework, when compared with an existing baseline model, yielded promising results.

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This Australian Indigenous creactive work and its Treatise promote ways of thinking about practice and research that extend well beyond the current discourse. It invites re-thinking on how research can be practice-led in new ways, and what that might mean for future students. When discussing the challenges of today, this work signifies how "Western Style" thinking and theory is wanting in so many ways. It engages a new dynamic and innovative way of theorising, encouraging future students to apply their full capacity of energy and wisdom. (Extract from examiners' reports.)

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In male tephritid fruit flies of the genus Bactrocera, feeding on secondary plant compounds (sensu lato male lures = methyl eugenol, raspberry ketone and zingerone) increases male mating success. Ingested male lures alter the male pheromonal blend, normally making it more attractive to females and this is considered the primary mechanism for the enhanced mating success. However, the male lures raspberry ketone and zingerone are known, across a diverse range of other organisms, to be involved in increasing energy metabolism. If this also occurs in Bactrocera, then this may represent an additional benefit to males as courtship is metabolically expensive and lure feeding may increase a fly's short-term energy. We tested this hypothesis by performing comparative RNA-seq analysis between zingerone-fed and unfed males of Bactrocera tryoni. We also carried out behavioural assays with zingerone- and cuelure-fed males to test whether they became more active. RNA-seq analysis revealed, in zingerone-fed flies, up-regulation of 3183 genes with homologues transcripts to those known to regulate intermale aggression, pheromone synthesis, mating and accessory gland proteins, along with significant enrichment of several energy metabolic pathways and gene ontology terms. Behavioural assays show significant increases in locomotor activity, weight reduction and successful mating after mounting; all direct/indirect measures of increased activity. These results suggest that feeding on lures leads to complex physiological changes, which result in more competitive males. These results do not negate the pheromone effect, but do strongly suggest that the phytochemical-induced sexual selection is governed by both female preference and male competitive mechanisms.

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As Business Process Management (BPM) is evolving and organisations are becoming more process oriented, the need for Expertise in BPM amongst practitioners has increased. Proactively managing Expertise in BPM is essential to unlock the potential of BPM as a management paradigm and competitive advantage. Whilst great attention is being paid by the BPM community to the technological aspects of BPM, relatively little research or work has been done concerning the expertise aspect of BPM. There is a substantial body of knowledge on expertise itself, however there is no common framework in existence at the time of writing, describing the fundamental attributes characterising Expertise in the illustrative context of BPM. There are direct implications of the understanding and characterisation of Expertise in the context of BPM as a key strategic component and success factor of BPM itself, as well as for those involved in BPM. Expertise in the context of BPM needs to be characterised to understand it, and be able to proactively manage it. Given the relative infancy of research into Expertise in the context of BPM, an exploration of the relevance and importance of Expertise in the context of BPM was considered essential, to ensure the study itself was of value to the BPM field. The aims of this research are firstly to address the two research questions 'why is expertise important and relevant in the context of BPM?', and 'how can Expertise in the context of BPM be characterised?', and secondly, the development of a comprehensive and validated A-priori model characterising Expertise in the illustrative context of BPM. The study is theory-guided. It has been undertaken via an extensive literature review across relevant literature domains, and a revelatory case study utilising several methods: informal discussions, an open-ended survey, and participant observation. An a-priori model was then developed which comprised of several Constructs and Sub-constructs, and several overall aspects of Expertise in BPM. This was followed by the conduct of interviews in the validation phase of the revelatory case study. The primary contributions of this study are to the fields of expertise, BPM and research. Contributions to the field of expertise include a comprehensive review of expertise literature in general and synthesised critique on expertise research, characterisation of expertise in an illustrative context as a system, and a comprehensive narrative of the dynamics and interrelationships of the core attributes characterising expertise. Contributions to the field of BPM include firstly, the establishment of the importance of understanding Expertise in the context of BPM, including a comprehensive overview of the role the relevance and importance of Expertise in the context of BPM, through explanation of the effect of Expertise in BPM. Secondly, a model characterising Expertise in the context of BPM, which can be used by BPM practitioners to clearly articulate and illuminate the state of Expertise in BPM in organisations. Contributions to the field of research include an extended view of Systems Theory developed, reflecting the importance of the system context in systems thinking, and a narrative on ontological innovation through the positioning of ontology as a meta-model of Expertise in the context of BPM.