77 resultados para isolation and identification


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The impact of climate change on the health of vulnerable groups such as the elderly has been of increasing concern. However, to date there has been no meta-analysis of current literature relating to the effects of temperature fluctuations upon mortality amongst the elderly. We synthesised risk estimates of the overall impact of daily mean temperature on elderly mortality across different continents. A comprehensive literature search was conducted using MEDLINE and PubMed to identify papers published up to December 2010. Selection criteria including suitable temperature indicators, endpoints, study-designs and identification of threshold were used. A two-stage Bayesian hierarchical model was performed to summarise the percent increase in mortality with a 1°C temperature increase (or decrease) with 95% confidence intervals in hot (or cold) days, with lagged effects also measured. Fifteen studies met the eligibility criteria and almost 13 million elderly deaths were included in this meta-analysis. In total, there was a 2-5% increase for a 1°C increment during hot temperature intervals, and a 1-2 % increase in all-cause mortality for a 1°C decrease during cold temperature intervals. Lags of up to 9 days in exposure to cold temperature intervals were substantially associated with all-cause mortality, but no substantial lagged effects were observed for hot intervals. Thus, both hot and cold temperatures substantially increased mortality among the elderly, but the magnitude of heat-related effects seemed to be larger than that of cold effects within a global context.

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Young drivers, aged 17 to 24 years, have the highest fatality rate in Australia. It is believed that part of this risk is due to pressure from peer passengers to engage in speeding; which may be active (i.e., verbal encouragement) or passive (i.e., perceived pressure on the part of the driver). The Theory of Planned Behaviour (TPB) was used to investigate this impact of peer passengers on young drivers, particularly the influence of the type of peer pressure and a driver’s level of identification with their passengers. A scenario-based questionnaire was constructed, informed by focus groups and pilot studies, and distributed to university students (N = 398). The questionnaire measured participants’ intentions and the TPB constructs, including two components of perceived behaviour control, within a baseline scenario as well as an experimental scenario in which the variables of type of pressure and identification were manipulated. Consistent with the hypotheses, the study found that attitudes and self-efficacy significantly predicted intentions over and above the variance explained by the sociodemographic variables of age, gender, self-esteem, sensation seeking, as well as past behaviour and exposure. Across the scenarios, attitudes explained between 4.3% and 14.5%, while self-efficacy to refrain from speeding explained between 4.9% and 17.1%, of the unique variance in intentions to speed. However, contrary to expectations, intentions to speed were found to be higher in the “no passenger” than “passenger present” conditions, although this finding is not completely inconsistent with recent literature. A high level of identification with passengers led to higher intentions to speed than low identification as expected, but, inconsistent with expectations, different types of pressure (i.e., active versus passive) did not influence intentions to speed.

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Complex networks have been studied extensively due to their relevance to many real-world systems such as the world-wide web, the internet, biological and social systems. During the past two decades, studies of such networks in different fields have produced many significant results concerning their structures, topological properties, and dynamics. Three well-known properties of complex networks are scale-free degree distribution, small-world effect and self-similarity. The search for additional meaningful properties and the relationships among these properties is an active area of current research. This thesis investigates a newer aspect of complex networks, namely their multifractality, which is an extension of the concept of selfsimilarity. The first part of the thesis aims to confirm that the study of properties of complex networks can be expanded to a wider field including more complex weighted networks. Those real networks that have been shown to possess the self-similarity property in the existing literature are all unweighted networks. We use the proteinprotein interaction (PPI) networks as a key example to show that their weighted networks inherit the self-similarity from the original unweighted networks. Firstly, we confirm that the random sequential box-covering algorithm is an effective tool to compute the fractal dimension of complex networks. This is demonstrated on the Homo sapiens and E. coli PPI networks as well as their skeletons. Our results verify that the fractal dimension of the skeleton is smaller than that of the original network due to the shortest distance between nodes is larger in the skeleton, hence for a fixed box-size more boxes will be needed to cover the skeleton. Then we adopt the iterative scoring method to generate weighted PPI networks of five species, namely Homo sapiens, E. coli, yeast, C. elegans and Arabidopsis Thaliana. By using the random sequential box-covering algorithm, we calculate the fractal dimensions for both the original unweighted PPI networks and the generated weighted networks. The results show that self-similarity is still present in generated weighted PPI networks. This implication will be useful for our treatment of the networks in the third part of the thesis. The second part of the thesis aims to explore the multifractal behavior of different complex networks. Fractals such as the Cantor set, the Koch curve and the Sierspinski gasket are homogeneous since these fractals consist of a geometrical figure which repeats on an ever-reduced scale. Fractal analysis is a useful method for their study. However, real-world fractals are not homogeneous; there is rarely an identical motif repeated on all scales. Their singularity may vary on different subsets; implying that these objects are multifractal. Multifractal analysis is a useful way to systematically characterize the spatial heterogeneity of both theoretical and experimental fractal patterns. However, the tools for multifractal analysis of objects in Euclidean space are not suitable for complex networks. In this thesis, we propose a new box covering algorithm for multifractal analysis of complex networks. This algorithm is demonstrated in the computation of the generalized fractal dimensions of some theoretical networks, namely scale-free networks, small-world networks, random networks, and a kind of real networks, namely PPI networks of different species. Our main finding is the existence of multifractality in scale-free networks and PPI networks, while the multifractal behaviour is not confirmed for small-world networks and random networks. As another application, we generate gene interactions networks for patients and healthy people using the correlation coefficients between microarrays of different genes. Our results confirm the existence of multifractality in gene interactions networks. This multifractal analysis then provides a potentially useful tool for gene clustering and identification. The third part of the thesis aims to investigate the topological properties of networks constructed from time series. Characterizing complicated dynamics from time series is a fundamental problem of continuing interest in a wide variety of fields. Recent works indicate that complex network theory can be a powerful tool to analyse time series. Many existing methods for transforming time series into complex networks share a common feature: they define the connectivity of a complex network by the mutual proximity of different parts (e.g., individual states, state vectors, or cycles) of a single trajectory. In this thesis, we propose a new method to construct networks of time series: we define nodes by vectors of a certain length in the time series, and weight of edges between any two nodes by the Euclidean distance between the corresponding two vectors. We apply this method to build networks for fractional Brownian motions, whose long-range dependence is characterised by their Hurst exponent. We verify the validity of this method by showing that time series with stronger correlation, hence larger Hurst exponent, tend to have smaller fractal dimension, hence smoother sample paths. We then construct networks via the technique of horizontal visibility graph (HVG), which has been widely used recently. We confirm a known linear relationship between the Hurst exponent of fractional Brownian motion and the fractal dimension of the corresponding HVG network. In the first application, we apply our newly developed box-covering algorithm to calculate the generalized fractal dimensions of the HVG networks of fractional Brownian motions as well as those for binomial cascades and five bacterial genomes. The results confirm the monoscaling of fractional Brownian motion and the multifractality of the rest. As an additional application, we discuss the resilience of networks constructed from time series via two different approaches: visibility graph and horizontal visibility graph. Our finding is that the degree distribution of VG networks of fractional Brownian motions is scale-free (i.e., having a power law) meaning that one needs to destroy a large percentage of nodes before the network collapses into isolated parts; while for HVG networks of fractional Brownian motions, the degree distribution has exponential tails, implying that HVG networks would not survive the same kind of attack.

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This paper reports on the development and implementation of a self-report risk assessment tool that was developed in an attempt to increase the efficacy of crash prediction within Australian fleet settings. This study forms a part of a broader program of research into work related road safety and identification of driving risk. The first phase of the study involved a series of focus groups being conducted with 217 professional drivers which revealed that the following factors were proposed to influence driving performance: Fatigue, Knowledge of risk, Mood, Impatience and frustration, Speed limits, Experience, Other road users, Passengers, Health, and Culture. The second phase of the study involved piloting the newly developed 38 item Driving Risk Assessment Scale - Work Version (DRAS-WV) with 546 professional drivers. Factor analytic techniques identified a 9 factor solution that was comprised of speeding, aggression, time pressure, distraction, casualness, awareness, maintenance, fatigue and minor damage. Speeding and aggressive driving manoeuvres were identified to be the most frequent aberrant driving behaviours engaged in by the sample. However, a series of logistic regression analyses undertaken to determine the DRAS-WV scale’s ability to predict self-reported crashes revealed limited predictive efficacy e.g., 10% of crashes. This paper outlines proposed reasons for this limited predictive ability of the DRAS-WV as well as provides suggestions regarding the future of research that aims to develop methods to identify “at risk” drivers.

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This book explores the relationship between gender and power in Burmese history from pre-colonial times to the present day and aims to identify the sources, nature and limitations of women’s power. The study takes as its starting point the apparent contradiction that, though Burmese women historically enjoyed relatively high social status and economic influence, for the most part they remained conspicuously absent from positions of authority in formal religious, social and political institutions. The book thus examines the concept of ‘family’ in Burmese political culture, and reveals how some women were able to gain political influence through their familial connections with powerful men, even while cultural models of ‘correct’ female behaviour prevented most women from attaining official positions of political authority. The study also considers how various influences – Buddhism, colonialism, nationalism, modernisation and militarism – shaped Burmese concepts of gender and power, with important implications for how women were able to exercise social, economic and political influence. The book explores how the effects of prolonged armed conflict, economic isolation and political oppression have constrained opportunities for women to attain power in contemporary Burma, and examines opportunities opened up by the pro-democracy movement and recent focus on women's issues and rights for women to exercise influence both inside Burma and in exile. Using an interdisciplinary approach that draws on feminist, anthropological and social science discourses, placing them within an historical framework, the author offers a broad understanding of how power is obtained and exercised in Burma in order to reassess historical representations of Burmese women and so provide a more comprehensive and inclusive understanding of power relations in historical and contemporary Burma.

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LexisNexis Questions & Answers - Contract Law provides an understanding of contract law and gives a clear and systematic approach to analysing and answering problem and exam questions. Each chapter commences with a summary of the relevant cases and identification of the key issues. Each question is followed by a suggested answer plan, a sample answer and comments on how the answer might be assessed by an examiner. The author also offers advice on common errors to avoid and practical hints and tips on how to achieve higher marks.

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Previous research on homeless adolescents has largely ignored the distinction between those who have left home on their volition (runaways) and those who have been forced to leave (throwaways). Fifty-two homeless adolescents in Brisbane, Australia, were assessed to compare male and female runaways and throwaways for social adjustment and symptomatology. Differences for social adjustment (antisocial tendencies and aggression) and symptomatology (social isolation and depression) were predicted. Results indicated that male runaways were significantly more hostile than male throwaways (p < 0,001), and significantly more socially isolated than female runaways (p < 0,025). Female throwaways, however, were significantly more hostile than male throwaways (p < 0,025) and female runaways (p < 0,025). Yet homeless males overall had a significantly stronger urge to act out hostility than homeless females (p < 0,025). In addition, female throwaways were significantly more antisocial than male throwaways (p < 0,001). There were no significant differences for depression. A theory of inner social control (Hirschi, 1969), postulating absence of bonding in earlier socialization, was supported.

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Occupational stress research has consistently demonstrated many negative effects of work stressors on employee adjustment (i.e., job-related attitudes and health). Considerable literature also describes potential moderators of this relationship. While research has revealed that leader vision can have significant positive effects on employee adjustment it has neglected investigation of its potential stress buffering effects. Based on leadership and identification theories, it was predicted that stress buffering effects of leader vision would be more evident for distal versus proximal leaders and also when the distal or proximal leader vision was congruent with the employee adjustment outcome type (distal versus proximal). Predictions were tested with an employee sample from one large public sector organization (N = 519). Hierarchical multiple regression analyses revealed that main and moderated effects relating to leader vision supported the notion that occupational stress would be reduced when there was congruence of distal and proximal leader vision and distal and proximal outcome types. However, stress buffering effects were found for high and low perceivers of leader vision that were not in line with hypotheses posing questions for the definitions of distal and proximal identifications. Findings are discussed in terms of theoretical and practical implications.

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Cytogenetic analysis is a powerful tool that allows analysis of chromosomal aberrations associated with diseased states. In particular, a combination of cytogenetic techniques has allowed the identification of aberrations associated with cancer development, including cancers of the skin. This chapter provides a comprehensive overview of cytogenetic alterations in basal and squamous cell carcinomas of the skin. These two distinct lesions have altered karyotypes that are consistent with their malignant potential. Basal cell carcinomas, although relatively stable lesions, are highly associated with recurrent aberrations of chromosomes 6, 7, 9 and X, as detected by a number of cytogenetic techniques. Squamous cell carcinomas, on the other hand are associated with a much higher degree of instability, involving aberrations of chromosomes 3, 7, 8, 11, 13, 17 and 18, as detected using a number of cytogenetic techniques. Overall, the numbers and types of aberrations associated with basal and squamous cell carcinoma, define the characteristic behaviour associated with these lesions and identification of these aberrations may aid in the understanding of malignant potential, prognosis and treatment of these skin cancers.

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A large proportion (over 12 per cent) of international and non-English speaking background (NESB) postgraduate research students enrol in engineering and information technology (IT) programs in Australian universities. They find themselves in an advanced research culture, and are technically and scientifically challenged early in their programs. This is in addition to cultural, social and religious isolation and linguistic barriers they have to contend with. The project team surveyed this cohort at QUT and UWA, on the hypothesis that they face challenges that are more discipline-specific. The results of the survey indicate that existing supervisory frameworks which are limited to linguistic contexts are not fully assisting these students and supervisors to achieve high quality research. The goal of this project is to extend these supervisory frameworks to a holistic model that will address the unique needs and supervisory issues these students face in engineering and IT disciplines. The model will be useable by all other Australian universities.

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This article is based on research we conducted in two agricultural communities as part of a broader study that included mining communities in rural Australia. The data from the agricultural locations tell a different story to that of the mining communities. In the latter, alcohol-fuelled, male-on-male assaults in public places caused considerable anxiety among informants. By contrast, people in the agricultural communities seemed more troubled by hidden violent harms which were largely privatised and individualised, including self-harm, suicide, isolation and threats to men’s general wellbeing and mental health; domestic violence; and other forms of violence largely unreported and thus unacknowledged within the wider community (including sexual assault and bullying linked to homophobia). We argue one reason for the different pattern in the agricultural communities is the decline of pub(lic) masculinity, and with this, the increasing isolation of rural men and the increasing propensity to internalise violence. We argue that the relatively high rates of suicide in agricultural communities experiencing rural decline are symptomatic of the internalisation of violence.

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The integration of separate, yet complimentary, cortical pathways appears to play a role in visual perception and action when intercepting objects. The ventral system is responsible for object recognition and identification, while the dorsal system facilitates continuous regulation of action. This dual-system model implies that empirically manipulating different visual information sources during performance of an interceptive action might lead to the emergence of distinct gaze and movement pattern profiles. To test this idea, we recorded hand kinematics and eye movements of participants as they attempted to catch balls projected from a novel apparatus that synchronised or de-synchronised accompanying video images of a throwing action and ball trajectory. Results revealed that ball catching performance was less successful when patterns of hand movements and gaze behaviours were constrained by the absence of advanced perceptual information from the thrower's actions. Under these task constraints, participants began tracking the ball later, followed less of its trajectory, and adapted their actions by initiating movements later and moving the hand faster. There were no performance differences when the throwing action image and ball speed were synchronised or de-synchronised since hand movements were closely linked to information from ball trajectory. Results are interpreted relative to the two-visual system hypothesis, demonstrating that accurate interception requires integration of advanced visual information from kinematics of the throwing action and from ball flight trajectory.

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Kaposi's sarcoma (KS) is a relatively low grade neoplasm, classically occurring in the skin of elderly men. A more virulent and invasive form of Kaposi's sarcoma has been described in patients with acquired immune deficiency syndrome (AIDS). The origin and identification of the tumor cells in these lesions is controversial. Here we have studied the behavior of cells derived from KS lesions in an in vitro assay which measures the ability of cells to invade through a reconstituted basement membrane. In agreement with previous work, KS cells obtained under selective culture conditions were invasive showing activity comparable to that of malignant tumor cells. Normal fibroblasts, smooth muscle cells, and endothelial cells did not demonstrate invasive behavior under the same experimental conditions. To characterize further the nature of the KS cells we tested the chemotactic response of cells from the most invasive line to a variety of growth factors and compared their response to those of fibroblasts, smooth muscle, and endothelial cells. These studies suggest that normal cells respond to a unique repertoire of chemotactic factors. The chemotactic response of the KS cells most closely resembled that of smooth muscle cells and was quite distinct from endothelial cells. These results indicate that the KS-derived cultures contain invasive cells with a smooth muscle cell-like phenotype.

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This article presents the field applications and validations for the controlled Monte Carlo data generation scheme. This scheme was previously derived to assist the Mahalanobis squared distance–based damage identification method to cope with data-shortage problems which often cause inadequate data multinormality and unreliable identification outcome. To do so, real-vibration datasets from two actual civil engineering structures with such data (and identification) problems are selected as the test objects which are then shown to be in need of enhancement to consolidate their conditions. By utilizing the robust probability measures of the data condition indices in controlled Monte Carlo data generation and statistical sensitivity analysis of the Mahalanobis squared distance computational system, well-conditioned synthetic data generated by an optimal controlled Monte Carlo data generation configurations can be unbiasedly evaluated against those generated by other set-ups and against the original data. The analysis results reconfirm that controlled Monte Carlo data generation is able to overcome the shortage of observations, improve the data multinormality and enhance the reliability of the Mahalanobis squared distance–based damage identification method particularly with respect to false-positive errors. The results also highlight the dynamic structure of controlled Monte Carlo data generation that makes this scheme well adaptive to any type of input data with any (original) distributional condition.

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With the increasing importance of Application Domain Specific Processor (ADSP) design, a significant challenge is to identify special-purpose operations for implementation as a customized instruction. While many methodologies have been proposed for this purpose, they all work for a single algorithm chosen from the target application domain. Such algorithm-specific approaches are not suitable for designing instruction sets applicable to a whole family of related algorithms. For an entire range of related algorithms, this paper develops a methodology for identifying compound operations, as a basis for designing “domain-specific” Instruction Set Architectures (ISAs) that can efficiently run most of the algorithms in a given domain. Our methodology combines three different static analysis techniques to identify instruction sequences common to several related algorithms: identification of (non-branching) instruction sequences that occur commonly across the algorithms; identification of instruction sequences nested within iterative constructs that are thus executed frequently; and identification of commonly-occurring instruction sequences that span basic blocks. Choosing different combinations of these results enables us to design domain-specific special operations with different desired characteristics, such as performance or suitability as a library function. To demonstrate our approach, case studies are carried out for a family of thirteen string matching algorithms. Finally, the validity of our static analysis results is confirmed through independent dynamic analysis experiments and performance improvement measurements.