962 resultados para Análise hot spot
Resumo:
Recent initiatives around the world have highlighted the potential for information and communications technology (ICT) to foster better service delivery for businesses. Likewise, ICT has also been applied to government services and is seen to result in improved service delivery, improved citizen participation in government, and enhanced cooperation across government departments and between government departments. The Council of Australian Governments (COAG) (2006) identified local government development assessment (DA) arrangements as a ‘hot spot’ needing specific attention, as the inconsistent policies and regulations between councils impeded regional economic activity. COAG (2006) specifically suggested that trials of various ICT mechanisms be initiated which may well be able to improve DA processes for local government. While the authors have explored various regulatory mechanisms to improve harmonisation elsewhere (Brown and Furneaux 2007), the possibility of ICT being able to enhance consistency across governments is a novel notion from a public policy perspective. Consequently, this paper will explore the utility of ICT initiatives to improve harmonisation of DA across local governments. This paper examines as a case study the recent attempt to streamline Development Assessment (DA) in local governments in South East Queensland. This initiative was funded by the Regulation Reduction Incentive Fund (RRIF), and championed by the South East Queensland (SEQ) Council of Mayors. The Regulation Reduction Incentive Fund (RRIF) program was created by the Australian government with the aim to provide incentives to local councils to reduce red tape for small and medium sized businesses. The funding for the program was facilitated through a competitive merit-based grants process targeted at Local Government Authorities. Grants were awarded to projects which targeted specific areas identified for reform (AusIndustry, 2007), in SEQ this focused around improving DA processes and creating transparency in environmental health policies, regulation and compliance. An important key factor to note with this case study is that it is unusual for an eGovernment initiative. Typically individual government departments undertake eGovernment projects in order to improve their internal performance. The RRIF case study examines the implementation of an eGovernment initiative across 21 autonomous local councils in South East Queensland. In order to move ahead, agreement needed to be reached between councils at the highest level. Having reviewed the concepts of eGovernment and eGovernance, the literature review is undertaken to identify the typical cost and benefits, barriers and enablers of ICT projects in government. The specific case of the RRIF project is then examined to determine if similar costs and benefits, barriers and enablers could be found in the RRIF project. The outcomes of the project, particularly in reducing red tape by increasing harmonisation between councils are explored.
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This paper is a continuation of the paper titled “Concurrent multi-scale modeling of civil infrastructure for analyses on structural deteriorating—Part I: Modeling methodology and strategy” with the emphasis on model updating and verification for the developed concurrent multi-scale model. The sensitivity-based parameter updating method was applied and some important issues such as selection of reference data and model parameters, and model updating procedures on the multi-scale model were investigated based on the sensitivity analysis of the selected model parameters. The experimental modal data as well as static response in terms of component nominal stresses and hot-spot stresses at the concerned locations were used for dynamic response- and static response-oriented model updating, respectively. The updated multi-scale model was further verified to act as the baseline model which is assumed to be finite-element model closest to the real situation of the structure available for the subsequent arbitrary numerical simulation. The comparison of dynamic and static responses between the calculated results by the final model and measured data indicated the updating and verification methods applied in this paper are reliable and accurate for the multi-scale model of frame-like structure. The general procedures of multi-scale model updating and verification were finally proposed for nonlinear physical-based modeling of large civil infrastructure, and it was applied to the model verification of a long-span bridge as an actual engineering practice of the proposed procedures.
Resumo:
The attention paid by the British music press in 1976 to the release of The Saints first single “I’m Stranded” was the trigger for a commercial and academic interest in the Brisbane music scene which still has significant energy. In 2007, Brisbane was identifed by Billboard Magazine as a “hot spot” of independent music. A place to watch. Someone turned a torch on this town, had a quick look, moved on. But this town has always had music in it. Some of it made by me. So, I’m taking this connection of mine, and working it into a contextual historical analysis of the creative lives of Brisbane musicians. I will be interviewing a number of Brisbane musicians. These interviews have begun, and will continue to be be conducted in 2011/2012. I will ask questions and pursue memories that will encompass family, teenage years, siblings, the suburbs, the city, venues, television and radio; but then widen to welcome the river, the hills and mountains, foes and friends, beliefs and death. The wider research will be a contextual historical analysis of the creative lives of Brisbane musicians. It will explore the changing nature of their work practices over time and will consider the notion, among other factors, of ‘place’ in both their creative practice and their creative output. It will also examine how the presence of the practitioners and their work is seen to contribute to the cultural life of the city and the creative lives of its citizens into the future. This paper offers an analysis of this last notion: how does this city see its music-makers? In addition to the interviews, over 300 Brisbane musicians were surveyed in September 2009 as part of a QUT-initiated recorded music event (BIGJAM). Their responses will inform the production of this paper.
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Chlamydia pneumoniae is a common human and animal pathogen associated with a wide range of upper and lower respiratory tract infections. In more recent years there has been increasing evidence to suggest a link between C. pneumoniae and chronic diseases in humans, including atherosclerosis, stroke and Alzheimer’s disease. C. pneumoniae human strains show little genetic variation, indicating that the human-derived strain originated from a common ancestor in the recent past. Despite extensive information on the genetics and morphology processes of the human strain, knowledge concerning many other hosts (including marsupials, amphibians, reptiles and equines) remains virtually unexplored. The koala (Phascolarctos cinereus) is a native Australian marsupial under threat due to habitat loss, predation and disease. Koalas are very susceptible to chlamydial infections, most commonly affecting the conjunctiva, urogenital tract and/or respiratory tract. To address this gap in the literature, the present study (i) provides a detailed description of the morphologic and genomic architecture of the C. pneumoniae koala (and human) strain, and shows that the koala strain is microscopically, developmentally and genetically distinct from the C. pneumoniae human strain, and (ii) examines the genetic relationship of geographically diverse C. pneumoniae isolates from human, marsupial, amphibian, reptilian and equine hosts, and identifies two distinct lineages that have arisen from animal-to-human cross species transmissions. Chapter One of this thesis explores the scientific problem and aims of this study, while Chapter Two provides a detailed literature review of the background in this field of work. Chapter Three, the first results chapter, describes the morphology and developmental stages of C. pneumoniae koala isolate LPCoLN, as revealed by fluorescence and transmission electron microscopy. The profile of this isolate, when cultured in HEp-2 human epithelial cells, was quite different to the human AR39 isolate. Koala LPCoLN inclusions were larger; the elementary bodies did not have the characteristic pear-shaped appearance, and the developmental cycle was completed within a shorter period of time (as confirmed by quantitative real-time PCR). These in vitro findings might reflect biological differences between koala LPCoLN and human AR39 in vivo. Chapter Four describes the complete genome sequence of the koala respiratory pathogen, C. pneumoniae LPCoLN. This is the first animal isolate of C. pneumoniae to be fully-sequenced. The genome sequence provides new insights into genomic ‘plasticity’ (organisation), evolution and biology of koala LPCoLN, relative to four complete C. pneumoniae human genomes (AR39, CWL029, J138 and TW183). Koala LPCoLN contains a plasmid that is not shared with any of the human isolates, there is evidence of gene loss in nucleotide salvage pathways, and there are 10 hot spot genomic regions of variation that were previously not identified in the C. pneumoniae human genomes. Sequence (partial-length) from a second, independent, wild koala isolate (EBB) at several gene loci confirmed that the koala LPCoLN isolate was representative of a koala C. pneumoniae strain. The combined sequence data provides evidence that the C. pneumoniae animal (koala LPCoLN) genome is ancestral to the C. pneumoniae human genomes and that human infections may have originated from zoonotic infections. Chapter Five examines key genome components of the five C. pneumoniae genomes in more detail. This analysis reveals genomic features that are shared by and/or contribute to the broad ecological adaptability and evolution of C. pneumoniae. This analysis resulted in the identification of 65 gene sequences for further analysis of intraspecific variation, and revealed some interesting differences, including fragmentation, truncation and gene decay (loss of redundant ancestral traits). This study provides valuable insights into metabolic diversity, adaptation and evolution of C. pneumoniae. Chapter Six utilises a subset of 23 target genes identified from the previous genomic comparisons and makes a significant contribution to our understanding of genetic variability among C. pneumoniae human (11) and animal (6 amphibian, 5 reptilian, 1 equine and 7 marsupial hosts) isolates. It has been shown that the animal isolates are genetically diverse, unlike the human isolates that are virtually clonal. More convincing evidence that C. pneumoniae originated in animals and recently (in the last few hundred thousand years) crossed host species to infect humans is provided in this study. It is proposed that two animal-to-human cross species events have occurred in the context of the results, one evident by the nearly clonal human genotype circulating in the world today, and the other by a more animal-like genotype apparent in Indigenous Australians. Taken together, these data indicate that the C. pneumoniae koala LPCoLN isolate has morphologic and genomic characteristics that are distinct from the human isolates. These differences may affect the survival and activity of the C. pneumoniae koala pathogen in its natural host, in vivo. This study, by utilising the genetic diversity of C. pneumoniae, identified new genetic markers for distinguishing human and animal isolates. However, not all C. pneumoniae isolates were genetically diverse; in fact, several isolates were highly conserved, if not identical in sequence (i.e. Australian marsupials) emphasising that at some stage in the evolution of this pathogen, there has been an adaptation/s to a particular host, providing some stability in the genome. The outcomes of this study by experimental and bioinformatic approaches have significantly enhanced our knowledge of the biology of this pathogen and will advance opportunities for the investigation of novel vaccine targets, antimicrobial therapy, or blocking of pathogenic pathways.
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Regional safety program managers face a daunting challenge in the attempt to reduce deaths, injuries, and economic losses that result from motor vehicle crashes. This difficult mission is complicated by the combination of a large perceived need, small budget, and uncertainty about how effective each proposed countermeasure would be if implemented. A manager can turn to the research record for insight, but the measured effect of a single countermeasure often varies widely from study to study and across jurisdictions. The challenge of converting widespread and conflicting research results into a regionally meaningful conclusion can be addressed by incorporating "subjective" information into a Bayesian analysis framework. Engineering evaluations of crashes provide the subjective input on countermeasure effectiveness in the proposed Bayesian analysis framework. Empirical Bayes approaches are widely used in before-and-after studies and "hot-spot" identification; however, in these cases, the prior information was typically obtained from the data (empirically), not subjective sources. The power and advantages of Bayesian methods for assessing countermeasure effectiveness are presented. Also, an engineering evaluation approach developed at the Georgia Institute of Technology is described. Results are presented from an experiment conducted to assess the repeatability and objectivity of subjective engineering evaluations. In particular, the focus is on the importance, methodology, and feasibility of the subjective engineering evaluation for assessing countermeasures.
Resumo:
Identifying crash “hotspots”, “blackspots”, “sites with promise”, or “high risk” locations is standard practice in departments of transportation throughout the US. The literature is replete with the development and discussion of statistical methods for hotspot identification (HSID). Theoretical derivations and empirical studies have been used to weigh the benefits of various HSID methods; however, a small number of studies have used controlled experiments to systematically assess various methods. Using experimentally derived simulated data—which are argued to be superior to empirical data, three hot spot identification methods observed in practice are evaluated: simple ranking, confidence interval, and Empirical Bayes. Using simulated data, sites with promise are known a priori, in contrast to empirical data where high risk sites are not known for certain. To conduct the evaluation, properties of observed crash data are used to generate simulated crash frequency distributions at hypothetical sites. A variety of factors is manipulated to simulate a host of ‘real world’ conditions. Various levels of confidence are explored, and false positives (identifying a safe site as high risk) and false negatives (identifying a high risk site as safe) are compared across methods. Finally, the effects of crash history duration in the three HSID approaches are assessed. The results illustrate that the Empirical Bayes technique significantly outperforms ranking and confidence interval techniques (with certain caveats). As found by others, false positives and negatives are inversely related. Three years of crash history appears, in general, to provide an appropriate crash history duration.
Resumo:
Hot spot identification (HSID) plays a significant role in improving the safety of transportation networks. Numerous HSID methods have been proposed, developed, and evaluated in the literature. The vast majority of HSID methods reported and evaluated in the literature assume that crash data are complete, reliable, and accurate. Crash under-reporting, however, has long been recognized as a threat to the accuracy and completeness of historical traffic crash records. As a natural continuation of prior studies, the paper evaluates the influence that under-reported crashes exert on HSID methods. To conduct the evaluation, five groups of data gathered from Arizona Department of Transportation (ADOT) over the course of three years are adjusted to account for fifteen different assumed levels of under-reporting. Three identification methods are evaluated: simple ranking (SR), empirical Bayes (EB) and full Bayes (FB). Various threshold levels for establishing hotspots are explored. Finally, two evaluation criteria are compared across HSID methods. The results illustrate that the identification bias—the ability to correctly identify at risk sites--under-reporting is influenced by the degree of under-reporting. Comparatively speaking, crash under-reporting has the largest influence on the FB method and the least influence on the SR method. Additionally, the impact is positively related to the percentage of the under-reported PDO crashes and inversely related to the percentage of the under-reported injury crashes. This finding is significant because it reveals that despite PDO crashes being least severe and costly, they have the most significant influence on the accuracy of HSID.
Resumo:
In previous research (Chung et al., 2009), the potential of the continuous risk profile (CRP) to proactively detect the systematic deterioration of freeway safety levels was presented. In this paper, this potential is investigated further, and an algorithm is proposed for proactively detecting sites where the collision rate is not sufficiently high to be classified as a high collision concentration location but where a systematic deterioration of safety level is observed. The approach proposed compares the weighted CRP across different years and uses the cumulative sum (CUSUM) algorithm to detect the sites where changes in collision rate are observed. The CRPs of the detected sites are then compared for reproducibility. When high reproducibility is observed, a growth factor is used for sequential hypothesis testing to determine if the collision profiles are increasing over time. Findings from applying the proposed method using empirical data are documented in the paper together with a detailed description of the method.
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In the past few years, remarkable progress has been made in unveiling novel and unique optical properties of strongly coupled plasmonic nanostructures. However, application of such plasmonic nanostructures in biomedicine remains challenging due to the lack of facile and robust assembly methods for producing stable nanostructures. Previous attempts to achieve plasmonic nano-assemblies using molecular ligands were limited due to the lack of flexibility that could be exercised in forming them. Here, we report the utilization of tailor-made hyperbranched polymers (HBP) as linkers to assemble gold nanoparticles (NPs) into nano-assemblies. The ease and flexibility in tuning the particle size and number of branch ends of a HBP makes it an ideal candidate as a linker, as opposed to DNA, small organic molecules and linear or dendrimeric polymers. We report a strong correlation of polymer (HBP) concentration with the size of the hybrid nano-assemblies and “hot-spot” density. We have shown that such solutions of stable HBP-gold nano-assemblies can be barcoded with various Raman tags to provide improved surface-enhanced Raman scattering (SERS) compared with non-aggregated NP systems. These Raman barcoded hybrid nano-assemblies, with further optimization of NP shape, size and “hot-spot” density, may find application as diagnostic tools in nanomedicine.
Resumo:
Knowledge of cable parameters has been well established but a better knowledge of the environment in which the cables are buried lags behind. Research in Queensland University of Technology has been aimed at obtaining and analysing actual daily field values of thermal resistivity and diffusivity of the soil around power cables. On-line monitoring systems have been developed and installed with a data logger system and buried spheres that use an improved technique to measure thermal resistivity and diffusivity over a short period. Results based on long term continuous field data are given. A probabilistic approach is developed to establish the correlation between the measured field thermal resistivity values and rainfall data from weather bureau records. This data from field studies can reduce the risk in cable rating decisions and provide a basis for reliable prediction of “hot spot” of an existing cable circuit
Resumo:
Background A public health intervention program with active involvement of local related stakeholders was piloted in the Bien Hoa dioxin hot spot (2007-2009), and then expanded to the Da Nang dioxin hot spot in Vietnam (2009-2011). It aimed to reduce the risk of dioxin exposure through foods for local residents. This article presents the results of the intervention in Da Nang. Methodology To assess the results of this intervention program, pre-intervention and post-intervention knowledge-attitude-practice (KAP) surveys were implemented in 400 households, randomly selected from four wards surrounding Da Nang Airbase in 2009 and 2011, respectively. Results After the intervention, the knowledge on the existence of dioxin in food, dioxin exposure pathways, potential high risk foods and preventive measures significantly increased (p < 0.05). 98% were willing to follow advice on preventing dioxin exposure. Practices to reduce the risk of dioxin exposure also statistical significantly improved (p<0.05). After intervention, 60.4% of households undertook exposure preventive measures, significantly higher than that of the pre-intervention survey (39.6%; χ2 =40.15 , P<0.001). High risk foods had quite low rates of daily consumption (from 0% to 2.5%) and were significantly reduced (p<0.05). Conclusions This is seen as an effective intervention strategy toward reducing the risk of human exposure to dioxin at dioxin hot spots. While greater efforts are needed for remediating dioxin polluted areas inside airbases, there is also evidence to suggest that, during the past four decades, pollution has been expanding to the surrounding areas. For this reason, this model should be quickly expanded to the remaining dioxin hot spots in Vietnam to further reduce the exposure risk in these areas.
Resumo:
The reliable operation of distribution systems is critically dependent on detailed understanding of load impacts on distribution transformer insulation systems. This paper estimates the impact of rooftop photovoltaic (PV) generation on a typical 200-kVA, 22/0.415-kV distribution transformer life under different operating conditions. This transformer supplies a suburban area with a high penetration of roof top photovoltaic systems. The transformer loads and the phase distribution of the PV systems are significantly unbalanced. Oil and hot-spot temperature and remnant life of distribution transformer under different PV and balance scenarios are calculated. It is shown that PV can significantly extend the transformer life.
Resumo:
Hot spot identification (HSID) aims to identify potential sites—roadway segments, intersections, crosswalks, interchanges, ramps, etc.—with disproportionately high crash risk relative to similar sites. An inefficient HSID methodology might result in either identifying a safe site as high risk (false positive) or a high risk site as safe (false negative), and consequently lead to the misuse the available public funds, to poor investment decisions, and to inefficient risk management practice. Current HSID methods suffer from issues like underreporting of minor injury and property damage only (PDO) crashes, challenges of accounting for crash severity into the methodology, and selection of a proper safety performance function to model crash data that is often heavily skewed by a preponderance of zeros. Addressing these challenges, this paper proposes a combination of a PDO equivalency calculation and quantile regression technique to identify hot spots in a transportation network. In particular, issues related to underreporting and crash severity are tackled by incorporating equivalent PDO crashes, whilst the concerns related to the non-count nature of equivalent PDO crashes and the skewness of crash data are addressed by the non-parametric quantile regression technique. The proposed method identifies covariate effects on various quantiles of a population, rather than the population mean like most methods in practice, which more closely corresponds with how black spots are identified in practice. The proposed methodology is illustrated using rural road segment data from Korea and compared against the traditional EB method with negative binomial regression. Application of a quantile regression model on equivalent PDO crashes enables identification of a set of high-risk sites that reflect the true safety costs to the society, simultaneously reduces the influence of under-reported PDO and minor injury crashes, and overcomes the limitation of traditional NB model in dealing with preponderance of zeros problem or right skewed dataset.
Resumo:
An in vivo screen has been devised for NF-κB p50 activity in Escherichia coli exploiting the ability of the mammalian transcription factor to emulate a prokaryotic repressor. Active intracellular p50 was shown to repress the expression of a green fluorescent protein reporter gene allowing for visual screening of colonies expressing active p50 on agar plates. A library of mutants was constructed in which the residues Y267, L269, A308 and V310 of the dimer interface were simultaneously randomised and twenty-five novel functional interfaces were selected which repressed the reporter gene to similar levels as the wild-type protein. The leucine-269 alanine-308 core was repeatedly, but not exclusively, selected from the library whilst a diversity of predominantly non-polar residues were selected at positions 267 and 310. These results indicate that L269 and A308 may form a hot spot of interaction and allow an insight into the processes of dimer selectivity and evolution within this family of transcription factors.
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Plasmonic gold nano-assemblies that self-assemble with the aid of linking molecules or polymers have the potential to yield controlled hierarchies of morphologies and consequently result in materials with tailored optical (e.g. localized surface plasmon resonances (LSPR)) and spectroscopic properties (e.g. surface enhanced Raman scattering (SERS)). Molecular linkers that are structurally well-defined are promising for forming hybrid nano-assemblies which are stable in aqueous solution and are increasingly finding application in nanomedicine. Despite much ongoing research in this field, the precise role of molecular linkers in governing the morphology and properties of the hybrid nano-assemblies remains unclear. Previously we have demonstrated that branched linkers, such as hyperbranched polymers, with specific anchoring end groups can be successfully employed to form assemblies of gold NPs demonstrating near-infrared SPRs and intense SERS scattering. We herein introduce a tailored polymer as a versatile molecular linker, capable of manipulating nano-assembly morphologies and hot-spot density. In addition, this report explores the role of the polymeric linker architecture, specifically the degree of branching of the tailored polymer in determining the formation, morphology and properties of the hybrid nano-assemblies. The degree of branching of the linker polymer, in addition to the concentration and number of anchoring groups, is observed to strongly influence the self-assembly process. The assembly morphology shifts primarily from 1D-like chains to 2D plates and finally to 3D-like globular structures, with increase in degree of branching. Insights have been gained into how the morphology influences the SERS performance of these nano-assemblies with respect to hot-spot density. These findings supplement the understanding of the morphology determining nano-assembly formation and pave the way for the possible application of these nano-assemblies as SERS bio-sensors for medical diagnostics.