212 resultados para Crash involvement


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The experiences of people affected by cancer are at the very heart of nursing research efforts. Because much of our work is focused on understanding how to improve experiences and outcomes for people with cancer, it is easy for us to believe that our research is inherently "person centered" and thus collaborative. Let's reflect on what truly collaborative approaches to cancer nursing research could be like, and how we measure up to such goals. Collaboration between people affected by cancer (consumers) and nurses in research is much more than providing a voice for individuals as participants in a research study. Today, research governing bodies in many countries require us to seek a different kind of consumer participation, where consumers and researchers work in partnership with one another to shape decisions about research priorities, policies, and practices.1 Most granting bodies now require explanations of how consumer and community participation will occur within a study. Ethical imperatives and the concept of patient advocacy also require that we give more considered attention to what is meant by consumer involvement.2 Consumers provide perspective on what will be relevant, acceptable, feasible, and sensitive research, having lived the experience of cancer. As a result, they offer practical insights that can ensure the successful conduct and better outcomes from research. Some granting bodies now even allocate a proportion of final score or assign a "public value" weighting for a grant, to recognize the importance of consumer involvement and reflect the quality of patient involvement in all stages of the research process.3

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This thesis takes a new data mining approach for analyzing road/crash data by developing models for the whole road network and generating a crash risk profile. Roads with an elevated crash risk due to road surface friction deficit are identified. The regression tree model, predicting road segment crash rate, is applied in a novel deployment coined regression tree extrapolation that produces a skid resistance/crash rate curve. Using extrapolation allows the method to be applied across the network and cope with the high proportion of missing road surface friction values. This risk profiling method can be applied in other domains.

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Nuclear factor kappa-beta (NF-kappaB) is a transcription factor responsible for modulating the expression of many genes involved in cell proliferation, differentiation, apoptosis and metastasis. NF-kappaB interacts with IkappaB inhibitory proteins to regulate gene expression. This study investigated common variants within the genes coding for NF-kappaB and IkappaB, NFKB1 and NFKBIA, for involvement in sporadic breast cancer. Genotypes were determined in a population of breast cancer affected individuals and age-matched controls. Results do not support an involvement of the tested NFKB1 and NFKBIA polymorphisms in susceptibility to sporadic breast cancer, in the tested Caucasian population.

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Crashes on motorway contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence reduce crashes will help address congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a Short time window around the time of crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques, that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists, and that this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with traffic flow data of one hour prior to the crash using an incident detection algorithm. Traffic flow trends (traffic speed/occupancy time series) revealed that crashes could be clustered with regards of the dominant traffic flow pattern prior to the crash. Using the k-means clustering method allowed the crashes to be clustered based on their flow trends rather than their distance. Four major trends have been found in the clustering results. Based on these findings, crash likelihood estimation algorithms can be fine-tuned based on the monitored traffic flow conditions with a sliding window of 60 minutes to increase accuracy of the results and minimize false alarms.

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Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence, reducing the frequency of crashes assists in addressing congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a short time window around the time of a crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists. We will compare them with normal traffic trends and show this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding to traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash. Using the K-Means clustering method with Euclidean distance function allowed the crashes to be clustered. Then, normal situation data was extracted based on the time distribution of crashes and were clustered to compare with the “high risk” clusters. Five major trends have been found in the clustering results for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Based on these findings, crash likelihood estimation models can be fine-tuned based on the monitored traffic conditions with a sliding window of 30 minutes to increase accuracy of the results and minimize false alarms.

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Fatigue/sleepiness is recognised as an important contributory factor in fatal and serious injury road traffic incidents (RTIs), however, identifying fatigue/sleepiness as a causal factor remains an uncertain science. Within Australia attending police officers at a RTI report the causal factors; one option is fatigue/sleepiness. In some Australian jurisdictions police incident databases are subject to post hoc analysis using a proxy definition for fatigue/sleepiness. This secondary analysis identifies further RTIs caused by fatigue/sleepiness not initially identified by attending officers. The current study investigates the efficacy of such proxy definitions for attributing fatigue/sleepiness as a RTI causal factor. Over 1600 Australian drivers were surveyed regarding their experience and involvement in fatigue/sleep-related RTIs and near-misses during the past five years. Driving while fatigued/sleepy had been experienced by the majority of participants (66.0% of participants). Fatigue/sleep-related near misses were reported by 19.1% of participants, with 2.4% being involved in a fatigue/sleep-related RTI. Examination of the characteristics for the most recent event (either a near miss or crash) found that the largest proportion of incidents (28.0%) occurred when commuting to or from work, followed by social activities (25.1%), holiday travel (19.8%), or for work purposes (10.1%). The fatigue/sleep related RTI and near-miss experience of a representative sample of Australian drivers does not reflect the proxy definitions used for fatigue/sleepiness identification. In particular those RTIs that occur in urban areas and at slow speeds may not be identified. While important to have a strategy for identifying fatigue/sleepiness related RTIs proxy measures appear best suited to identifying specific subsets of such RTIs.

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In this paper we explore the relationship between monthly random breath testing (RBT) rates (per 1000 licensed drivers) and alcohol-related traffic crash (ARTC) rates over time, across two Australian states: Queensland and Western Australia. We analyse the RBT, ARTC and licensed driver rates across 12 years; however, due to administrative restrictions, we model ARTC rates against RBT rates for the period July 2004 to June 2009. The Queensland data reveals that the monthly ARTC rate is almost flat over the five year period. Based on the results of the analysis, an average of 5.5 ARTCs per 100,000 licensed drivers are observed across the study period. For the same period, the monthly rate of RBTs per 1000 licensed drivers is observed to be decreasing across the study with the results of the analysis revealing no significant variations in the data. The comparison between Western Australia and Queensland shows that Queensland's ARTC monthly percent change (MPC) is 0.014 compared to the MPC of 0.47 for Western Australia. While Queensland maintains a relatively flat ARTC rate, the ARTC rate in Western Australia is increasing. Our analysis reveals an inverse relationship between ARTC RBT rates, that for every 10% increase in the percentage of RBTs to licensed driver there is a 0.15 decrease in the rate of ARTCs per 100,000 licenced drivers. Moreover, in Western Australia, if the 2011 ratio of 1:2 (RBTs to annual number of licensed drivers) were to double to a ratio of 1:1, we estimate the number of monthly ARTCs would reduce by approximately 15. Based on these findings we believe that as the number of RBTs conducted increases the number of drivers willing to risk being detected for drinking driving decreases, because the perceived risk of being detected is considered greater. This is turn results in the number of ARTCs diminishing. The results of this study provide an important evidence base for policy decisions for RBT operations.

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Concealed texting (CT) while driving involves a conscious effort to hide one’s texting while obvious texting (OT) does not involve such efforts to conceal the behaviour. Young drivers are the most frequent users of mobile phones while driving which is associated with heightened crash risk. This study investigated the extent to which CT and OT may be discrete behaviours to ascertain whether countermeasures would need to utilise distinct approaches. An extended Theory of Planned Behaviour (TPB) including moral norm, mobile phone involvement, and anticipated regret guided the research. Participants (n = 171) were aged 17 to 25 years, owned a mobile phone, had a current driver’s licence, and resided in Queensland. A repeated measures MANOVA found significant differences between CT and OT on all standard and extended TPB constructs. Hierarchical multiple regression analyses showed the standard TPB constructs accounted for 68.7% and 54.6% of the variance in intentions to engage in CT and OT, respectively. The extended predictors contributed additional variance in intentions over and above the standard TPB constructs. Further, in the final regression model, differences emerged in the significant predictors of each type of texting. These findings provide initial evidence that CT and OT are distinct behaviours. This distinction is important to the extent that it may influence the nature of advertising countermeasures aimed at reducing/preventing young drivers’ engagement in these risky behaviours.

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Introduction • The Australian Institute of Criminology (AIC) is Australia's national research and knowledge centre on crime and justice. • The Institute seeks to promote justice and reduce crime by undertaking and communicating evidence-based research to inform policy and practice. • The AIC is governed by the Criminology Research Act and has been in operation since 1973. • The AIC is pleased to have the opportunity to contribute to the Committee's Inquiry into the high level of involvement of Indigenous juveniles and young adults in the criminal justice system. • There is a great deal of evidence to demonstrate that Indigenous young people are significantly over-represented at every stage of the criminal justice system in Australia.

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Exposure control or case-control methodologies are common techniques for estimating crash risks, however they require either observational data on control cases or exogenous exposure data, such as vehicle-kilometres travelled. This study proposes an alternative methodology for estimating crash risk of road user groups, whilst controlling for exposure under a variety of roadway, traffic and environmental factors by using readily available police-reported crash data. In particular, the proposed method employs a combination of a log-linear model and quasi-induced exposure technique to identify significant interactions among a range of roadway, environmental and traffic conditions to estimate associated crash risks. The proposed methodology is illustrated using a set of police-reported crash data from January 2004 to June 2009 on roadways in Queensland, Australia. Exposure-controlled crash risks of motorcyclists—involved in multi-vehicle crashes at intersections—were estimated under various combinations of variables like posted speed limit, intersection control type, intersection configuration, and lighting condition. Results show that the crash risk of motorcycles at three-legged intersections is high if the posted speed limits along the approaches are greater than 60 km/h. The crash risk at three-legged intersections is also high when they are unsignalized. Dark lighting conditions appear to increase the crash risk of motorcycles at signalized intersections, but the problem of night time conspicuity of motorcyclists at intersections is lessened on approaches with lower speed limits. This study demonstrates that this combined methodology is a promising tool for gaining new insights into the crash risks of road user groups, and is transferrable to other road users.

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Compromised angiogenesis appears to be a major limitation in various suboptimal bone healing situations. Appropriate mechanical stimuli support blood vessel formation in vivo and improve healing outcomes. However, the mechanisms responsible for this association are unclear. To address this question, the paracrine angiogenic potential of early human fracture haematoma and its responsiveness to mechanical loading, as well as angiogenic growth factors involved, were investigated in vitro. Human haematomas were collected from healthy patients undergoing surgery within 72. h after bone fracture. The haematomas were embedded in a fibrin matrix, and cultured in a bioreactor resembling the in vivo conditions of the early phase of bone healing (20 compression, 1. Hz) over 3. days. Conditioned medium (CM) from the bioreactor was then analyzed. The matrices were also incubated in fresh medium for a further 24. h to evaluate the persistence of the effects. Growth factor (GF) concentrations were measured in the CM by ELISAs. In vitro tube formation assays were conducted on Matrigel with the HMEC-1 cell line, with or without inhibition of vascular endothelial growth factor receptor 2 (VEGFR2). Cell numbers were quantified using an MTS test. In vitro endothelial tube formation was enhanced by CM from haematomas, compared to fibrin controls. The angiogenesis regulators, vascular endothelial growth factor (VEGF) and transforming growth factor β1 (TGF-β1), were released into the haematoma CM, but not angiopoietins 1 or 2 (Ang1, 2), basic fibroblast growth factor (bFGF) or platelet-derived growth factor (PDGF). Mechanical stimulation of haematomas, but not fibrin controls, further increased the induction of tube formation by their CM. The mechanically stimulated haematoma matrices retained their elevated pro-angiogenic capacity for 24. h. The pro-angiogenic effect was cancelled by inhibition of VEGFR2 signalling. VEGF concentrations in CM tended to be elevated by mechanical stimulation; this was significant in haematomas from younger, but not from older patients. Other GFs were not mechanically regulated. In conclusion, the paracrine pro-angiogenic capacity of early human haematomas is enhanced by mechanical stimulation. This effect lasts even after removing the mechanical stimulus and appears to be VEGFR2-dependent.

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Aims: To compare different methods for identifying alcohol involvement in injury-related emergency department presentation in Queensland youth, and to explore the alcohol terminology used in triage text. Methods: Emergency Department Information System data were provided for patients aged 12-24 years with an injury-related diagnosis code for a 5 year period 2006-2010 presenting to a Queensland emergency department (N=348895). Three approaches were used to estimate alcohol involvement: 1) analysis of coded data, 2) mining of triage text, and 3) estimation using an adaptation of alcohol attributable fractions (AAF). Cases were identified as ‘alcohol-involved’ by code and text, as well as AAF weighted. Results: Around 6.4% of these injury presentations overall had some documentation of alcohol involvement, with higher proportions of alcohol involvement documented for 18-24 year olds, females, indigenous youth, where presentations occurred on a Saturday or Sunday, and where presentations occurred between midnight and 5am. The most common alcohol terms identified for all subgroups were generic alcohol terms (eg. ETOH or alcohol) with almost half of the cases where alcohol involvement was documented having a generic alcohol term recorded in the triage text. Conclusions: Emergency department data is a useful source of information for identification of high risk sub-groups to target intervention opportunities, though it is not a reliable source of data for incidence or trend estimation in its current unstandardised form. Improving the accuracy and consistency of identification, documenting and coding of alcohol-involvement at the point of data capture in the emergency department is the most desirable long term approach to produce a more solid evidence base to support policy and practice in this field.

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The anticonvulsant phenytoin (5,5-diphenylhydantoin) provokes a skin rash in 5 to 10% of patients, which heralds the start of an idiosyncratic reaction that may result from covalent modification of normal self proteins by reactive drug metabolites. Phenytoin is metabolized by cytochrome P450 (P450) enzymes primarily to 5-(p-hydroxyphenyl-),5-phenylhydantoin (HPPH), which may be further metabolized to a catechol that spontaneously oxidizes to semiquinone and quinone species that covalently modify proteins. The aim of this study was to determine which P450s catalyze HPPH metabolism to the catechol, proposed to be the final enzymatic step in phenytoin bioactivation. Recombinant human P450s were coexpressed with NADPH-cytochrome P450 reductase in Escherichia coli. Novel bicistronic expression vectors were constructed for P450 2C19 and the three major variants of P450 2C9, i.e., 2C9*1, 2C9*2, and 2C9*3. HPPH metabolism and covalent adduct formation were assessed in parallel. P450 2C19 was the most effective catalyst of HPPH oxidation to the catechol metabolite and was also associated with the highest levels of covalent adduct formation. P450 3A4, 3A5, 3A7, 2C9*1, and 2C9*2 also catalyzed bioactivation of HPPH, but to a lesser extent. Fluorographic analysis showed that the major targets of adduct formation in bacterial membranes were the catalytic P450 forms, as suggested from experiments with human liver microsomes. These results suggest that P450 2C19 and other forms from the 2C and 3A subfamilies may be targets as well as catalysts of drug-protein adduct formation from phenytoin.