154 resultados para Rank and file unionism


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Trade union membership, both in aggregate numbers and in density, has declined in the majority of advanced economies globally over recent decades (Blanchflower, 2007). In Australia, the decline in the 1990s was somewhat more precipitate than in most countries (Peetz, 1998). As discussed in Chapter 1, reasons for the decline are multifactorial, including a more hostile environment to unionism created by employers and the state, difficulties ·with workplace union organisation, and structural change in the economy (Bryson and Gomez, 2005; Bryson et a!., 2011; Ebbinghaus et al., 2011; Payne, 1989; Waddington and Kerr, 2002; Waddington and Whitson, 1997). Our purpose in this chapter is to look beyond aggregate Australian union density data, to examine how age relates to membership decline, and how different age groups, particularly younger workers, are located in the story of union decline. The practical implications of this research are that understanding how unions relate to workers of different age groups, and to workers of different genders amongst those age groups, may lead to improved recruitment and better union organisation.

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‘Complexity’ is a term that is increasingly prevalent in conversations about building capacity for 21st Century professional engineers. Society is grappling with the urgent and challenging reality of accommodating seven billion people, meeting needs and innovating lifestyle improvements in ways that do not destroy atmospheric, biological and oceanic systems critical to life. Over the last two decades in particular, engineering educators have been active in attempting to build capacity amongst professionals to deliver ‘sustainable development’ in this rapidly changing global context. However curriculum literature clearly points to a lack of significant progress, with efforts best described as ad hoc and highly varied. Given the limited timeframes for action to curb environmental degradation proposed by scientists and intergovernmental agencies, the authors of this paper propose it is imperative that curriculum renewal towards education for sustainable development proceeds rapidly, systemically, and in a transformational manner. Within this context, the paper discusses the need to consider a multiple track approach to building capacity for 21st Century engineering, including priorities and timeframes for undergraduate and postgraduate curriculum renewal. The paper begins with a contextual discussion of the term complexity and how it relates to life in the 21st Century. The authors then present a whole of system approach for planning and implementing rapid curriculum renewal that addresses the critical roles of several generations of engineering professionals over the next three decades. The paper concludes with observations regarding engaging with this approach in the context of emerging accreditation requirements and existing curriculum renewal frameworks.

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We used diffusion tensor magnetic resonance imaging (DTI) to reveal the extent of genetic effects on brain fiber microstructure, based on tensor-derived measures, in 22 pairs of monozygotic (MZ) twins and 23 pairs of dizygotic (DZ) twins (90 scans). After Log-Euclidean denoising to remove rank-deficient tensors, DTI volumes were fluidly registered by high-dimensional mapping of co-registered MP-RAGE scans to a geometrically-centered mean neuroanatomical template. After tensor reorientation using the strain of the 3D fluid transformation, we computed two widely used scalar measures of fiber integrity: fractional anisotropy (FA), and geodesic anisotropy (GA), which measures the geodesic distance between tensors in the symmetric positive-definite tensor manifold. Spatial maps of intraclass correlations (r) between MZ and DZ twins were compared to compute maps of Falconer's heritability statistics, i.e. the proportion of population variance explainable by genetic differences among individuals. Cumulative distribution plots (CDF) of effect sizes showed that the manifold measure, GA, comparably the Euclidean measure, FA, in detecting genetic correlations. While maps were relatively noisy, the CDFs showed promise for detecting genetic influences on brain fiber integrity as the current sample expands.

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To classify each stage for a progressing disease such as Alzheimer’s disease is a key issue for the disease prevention and treatment. In this study, we derived structural brain networks from diffusion-weighted MRI using whole-brain tractography since there is growing interest in relating connectivity measures to clinical, cognitive, and genetic data. Relatively little work has usedmachine learning to make inferences about variations in brain networks in the progression of the Alzheimer’s disease. Here we developed a framework to utilize generalized low rank approximations of matrices (GLRAM) and modified linear discrimination analysis for unsupervised feature learning and classification of connectivity matrices. We apply the methods to brain networks derived from DWI scans of 41 people with Alzheimer’s disease, 73 people with EMCI, 38 people with LMCI, 47 elderly healthy controls and 221 young healthy controls. Our results show that this new framework can significantly improve classification accuracy when combining multiple datasets; this suggests the value of using data beyond the classification task at hand to model variations in brain connectivity.

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A LATEX style file, named qutthesis.sty, is developed, for writing PhD or Research Masters thesis. Developed by Professor Glen Yu-Chu Tian, it tries to fulfill QUT’s Thesis requirements but it is unofficial.

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Background Strand specific RNAseq data is now more common in RNAseq projects. Visualizing RNAseq data has become an important matter in Analysis of sequencing data. The most widely used visualization tool is the UCSC genome browser that introduced the custom track concept that enabled researchers to simultaneously visualize gene expression at a particular locus from multiple experiments. Our objective of the software tool is to provide friendly interface for visualization of RNAseq datasets. Results This paper introduces a visualization tool (RNASeqBrowser) that incorporates and extends the functionality of the UCSC genome browser. For example, RNASeqBrowser simultaneously displays read coverage, SNPs, InDels and raw read tracks with other BED and wiggle tracks -- all being dynamically built from the BAM file. Paired reads are also connected in the browser to enable easier identification of novel exon/intron borders and chimaeric transcripts. Strand specific RNAseq data is also supported by RNASeqBrowser that displays reads above (positive strand transcript) or below (negative strand transcripts) a central line. Finally, RNASeqBrowser was designed for ease of use for users with few bioinformatic skills, and incorporates the features of many genome browsers into one platform. Conclusions The features of RNASeqBrowser: (1) RNASeqBrowser integrates UCSC genome browser and NGS visualization tools such as IGV. It extends the functionality of the UCSC genome browser by adding several new types of tracks to show NGS data such as individual raw reads, SNPs and InDels. (2) RNASeqBrowser can dynamically generate RNA secondary structure. It is useful for identifying non-coding RNA such as miRNA. (3) Overlaying NGS wiggle data is helpful in displaying differential expression and is simple to implement in RNASeqBrowser. (4) NGS data accumulates a lot of raw reads. Thus, RNASeqBrowser collapses exact duplicate reads to reduce visualization space. Normal PC’s can show many windows of NGS individual raw reads without much delay. (5) Multiple popup windows of individual raw reads provide users with more viewing space. This avoids existing approaches (such as IGV) which squeeze all raw reads into one window. This will be helpful for visualizing multiple datasets simultaneously. RNASeqBrowser and its manual are freely available at http://www.australianprostatecentre.org/research/software/rnaseqbrowser webcite or http://sourceforge.net/projects/rnaseqbrowser/ webcite

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Objective: To identify genetic associations with severity of radiographic damage in ankylosing spondylitis (AS). Method: We studied 1537 AS cases of European descent; all fulfilled the modified New York Criteria. Radiographic severity was assessed from digitised lateral radiographs of the cervical and lumbar spine using the modified Stoke Ankylosing Spondylitis Spinal Score (mSASSS). A two-phase genotyping design was used. In phase 1, 498 single nucleotide polymorphisms (SNPs) were genotyped in 688 cases; these were selected to capture >90% of the common haplotypic variation in the exons, exon-intron boundaries, and 5 kb flanking DNA in the 5' and 3' UTR of 74 genes involved in anabolic or catabolic bone pathways. In phase 2, 15 SNPs exhibiting p<0.05 were genotyped in a further cohort of 830 AS cases; results were analysed both separately and in combination with the discovery phase data. Association was tested by contingency tables after separating the samples into 'mild' and 'severe' groups, defined as the bottom and top 40% by mSASSS, adjusted for gender and disease duration. Results: Experiment-wise association was observed with the SNP rs8092336 (combined OR 0.32, p=1.2×10-5), which lies within RANK (receptor activator of NF?B), a gene involved in osteoclastogenesis, and in the interaction between T cells and dendritic cells. Association was also found with the SNP rs1236913 in PTGS1 (prostaglandin-endoperoxide synthase 1, cyclooxygenase 1), giving an OR of 0.53 (p=2.6×10-3). There was no observed association between radiographic severity and HLA-B*27. Conclusions: These findings support roles for bone resorption and prostaglandins pathways in the osteoproliferative changes in AS.

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Designers have become aware of the importance of creating strong emotional experiences intertwined with new tangible products for the past decade, however an increased interest from firms has emerged in developing new service and business models as complimentary forms of emotion-driven innovation. This interdisciplinary study draws from the psychological sciences – theory of emotion – and the management sciences – business model literature to introduce this new innovation agenda. The term visceral hedonic rhetoric (VHR) is defined as the properties of a product, (and in this paper service and business model extensions) that persuasively induce the pursuit of pleasure at an instinctual level of cognition. This research paper lays the foundation for VHR beyond a product setting, presenting the results from an empirical study where organizations explored the possibilities for VHR in the context of their business. The results found that firms currently believe VHR is perceived in either their product and/or services they provide. Implications suggest shifting perspective surrounding the use of VHR across a firm’s business model design in order to influence the outcomes of their product and/or service design, resulting in an overall stronger emotional connection with the customer.

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By the time students reach the middle years they have experienced many chance activities based on dice. Common among these are rolling one die to explore the relationship of frequency and theoretical probability, and rolling two dice and summing the outcomes to consider their probabilities. Although dice may be considered overused by some, the advantage they offer is a familiar context within which to explore much more complex concepts. If the basic chance mechanism of the device is understood, it is possible to enter quickly into an arena of more complex concepts. This is what happened with a two hour activity engaged in by four classes of Grade 6 students in the same school. The activity targeted the concepts of variation and expectation. The teachers held extended discussions with their classes on variation and expectation at the beginning of the activity, with students contributing examples of the two concepts from their own experience. These notions are quite sophisticated for Grade 6, but the underlying concepts describe phenomena that students encounter every day. For example, time varies continuously; sporting results vary from game to game; the maximum temperature varies from day to day. However, there is an expectation about tomorrow’s maximum temperature based on the expert advice from the weather bureau. There may also be an expectation about a sporting result based on the participants’ previous results. It is this juxtaposition that makes life interesting. Variation hence describes the differences we see in phenomena around us. In a scenario displaying variation, expectation describes the effort to characterise or summarise the variation and perhaps make a prediction about the message arising from the scenario. The explicit purpose of the activity described here was to use the familiar scenario of rolling a die to expose these two concepts. Because the students had previously experienced rolling physical dice they knew instinctively about the variation that occurs across many rolls and about the theoretical expectation that each side should “come up” one-sixth of the time. They had observed the instances of the concepts in action, but had not consolidated the underlying terminology to describe it. As the two concepts are so fundamental to understanding statistics, we felt it would be useful to begin building in the familiar environment of rolling a die. Because hand-held dice limit the explorations students can undertake, the classes used the soft-ware TinkerPlots (Konold & Miller, 2011) to simulate rolling a die multiple times.

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Many studies have shown that we can gain additional information on time series by investigating their accompanying complex networks. In this work, we investigate the fundamental topological and fractal properties of recurrence networks constructed from fractional Brownian motions (FBMs). First, our results indicate that the constructed recurrence networks have exponential degree distributions; the average degree exponent 〈λ〉 increases first and then decreases with the increase of Hurst index H of the associated FBMs; the relationship between H and 〈λ〉 can be represented by a cubic polynomial function. We next focus on the motif rank distribution of recurrence networks, so that we can better understand networks at the local structure level. We find the interesting superfamily phenomenon, i.e., the recurrence networks with the same motif rank pattern being grouped into two superfamilies. Last, we numerically analyze the fractal and multifractal properties of recurrence networks. We find that the average fractal dimension 〈dB〉 of recurrence networks decreases with the Hurst index H of the associated FBMs, and their dependence approximately satisfies the linear formula 〈dB〉≈2-H, which means that the fractal dimension of the associated recurrence network is close to that of the graph of the FBM. Moreover, our numerical results of multifractal analysis show that the multifractality exists in these recurrence networks, and the multifractality of these networks becomes stronger at first and then weaker when the Hurst index of the associated time series becomes larger from 0.4 to 0.95. In particular, the recurrence network with the Hurst index H=0.5 possesses the strongest multifractality. In addition, the dependence relationships of the average information dimension 〈D(1)〉 and the average correlation dimension 〈D(2)〉 on the Hurst index H can also be fitted well with linear functions. Our results strongly suggest that the recurrence network inherits the basic characteristic and the fractal nature of the associated FBM series.

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The study monitored the emissions of volatile organic compounds (VOCs) from the exhaust of cars fuelled by liquefied petroleum gas (LPG) and unleaded petrol (ULP). Six cars, four fuelled by LPG and two by ULP, were tested on a chassis dynamometer at two different cruising modes of operation (60 km h−1 and 80 km h−1) and idle. A total of 33 VOCs were identified in the exhaust of both types of fuels by the use of GC/MS. Due to the complexity of the dataset, Multi Criteria Decision Making (MCDM) software PROMETHEE and GAIA was used to rank the least polluting mode and fuel. The 60 km h−1 driving speed was identified as the cleaner mode of driving as was LPG fuel. The Ozone Formation Potential (OFP) of the VOCs was also calculated by using the incremental reactivity scale. Priority VOCs leading to ozone formation were identified according to the three incremental reactivity scales: MIR, MOIR and EBIR. PROMETHEE was applied to assess the most preferred scale of reactivity for predicting ozone formation potential under different scenarios. The results enhance the understanding of the environmental value of using LPG to power passenger cars.

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Similar to most other creative industries, the evolution of the music industry is heavily shaped by media technologies. This was equally true in 1999, when the global recorded music industry had experienced two decades of continuous growth largely driven by the rapid transition from vinyl records to Compact Discs. The transition encouraged avid music listeners to purchase much of their music collections all over again in order to listen to their favourite music with ‘digital sound’. As a consequence of this successful product innovation, recorded music sales (unit measure) more than doubled between the early 1980s and the end of the 1990s. It was with this backdrop that the first peer-to-peer file sharing service was developed and released to the mainstream music market in 1999 by the college student Shawn Fanning. The service was named Napster and it marks the beginning of an era that is now a classic example of how an innovation is able to disrupt an entire industry and make large swathes of existing industry competences obsolete. File sharing services such as Napster, followed by a range of similar services in its path, reduced physical unit sales in the music industry to levels that had not been seen since the 1970s. The severe impact of the internet on physical sales shocked many music industry executives who spent much of the 2000s vigorously trying to reverse the decline and make the disruptive technologies go away. At the end, they learned that their efforts were to no avail and the impact on the music industry proved to be transformative, irreversible and, to many music industry professionals, also devastating. Thousands of people lost their livelihood, large and small music companies have folded or been forced into mergers or acquisitions. But as always during periods of disruption, the past 15 years have also been very innovative, spurring a plethora of new music business models. These new business models have mainly emerged outside the music industry and the innovators have been often been required to be both persuasive and persistent in order to get acceptance from the risk-averse and cash-poor music industry establishment. Apple was one such change agent that in 2003 was the first company to open up a functioning and legal market for online music. iTunes Music Store was the first online retail outlet that was able to offer the music catalogues from all the major music companies; it used an entirely novel pricing model, and it allowed consumers to de-bundle the music album and only buy the songs that they actually liked. Songs had previously been bundled by physical necessity as discs or cassettes, but with iTunes Music Store, the institutionalized album bundle slowly started to fall apart. The consequences had an immediate impact on music retailing and within just a few years, many brick and mortar record stores were forced out of business in markets across the world. The transformation also had disruptive consequences beyond music retailing and redefined music companies’ organizational structures, work processes and routines, as well as professional roles. iTunes Music Store in one sense was a disruptive innovation, but it was at the same time relatively incremental, since the major labels’ positions and power structures remained largely unscathed. The rights holders still controlled their intellectual properties and the structures that guided the royalties paid per song that was sold were predictable, transparent and in line with established music industry practices.

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Public submission # 029 to a Australian federal parliamentary committee considering proposed legislative changes to the Commonwealth's Healthcare Identifiers Act 2010 and the Personally Controlled Electronic Health Records Act 2012.

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Context: Osteoporosis is a common, highly heritable condition that causes substantial morbidity and mortality, the etiopathogenesis of which is poorly understood. Genetic studies are making increasingly rapid progress in identifying the genes involved. Evidence Acquisition and Synthesis: In this review, we will summarize the current understanding of the genetics of osteoporosis based on publications from PubMed from the year 1987 onward. Conclusions: Most genes involved in osteoporosis identified to date encode components of known pathways involved in bone synthesis or resorption, but as the field progresses, new pathways are being identified. Only a small proportion of the total genetic variation involved in osteoporosis has been identified, and new approaches will be required to identify most of the remaining genes.

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Bone mineral density (BMD) is the most widely used predictor of fracture risk. We performed the largest meta-analysis to date on lumbar spine and femoral neck BMD, including 17 genome-wide association studies and 32,961 individuals of European and east Asian ancestry. We tested the top BMD-associated markers for replication in 50,933 independent subjects and for association with risk of low-trauma fracture in 31,016 individuals with a history of fracture (cases) and 102,444 controls. We identified 56 loci (32 new) associated with BMD at genome-wide significance (P < 5 × 10−8). Several of these factors cluster within the RANK-RANKL-OPG, mesenchymal stem cell differentiation, endochondral ossification and Wnt signaling pathways. However, we also discovered loci that were localized to genes not known to have a role in bone biology. Fourteen BMD-associated loci were also associated with fracture risk (P < 5 × 10−4, Bonferroni corrected), of which six reached P < 5 × 10−8, including at 18p11.21 (FAM210A), 7q21.3 (SLC25A13), 11q13.2 (LRP5), 4q22.1 (MEPE), 2p16.2 (SPTBN1) and 10q21.1 (DKK1). These findings shed light on the genetic architecture and pathophysiological mechanisms underlying BMD variation and fracture susceptibility.