130 resultados para Flooding events


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In this digital age, as social media is emerging as a central site where information is shared and interpreted, it is essential to study information construction issues on social media sites in order to understand how social reality is constructed. While there is a number of studies taking an information-as-objective point of view, this proposed study emphasizes the constructed and interpretive nature of information and explores the processes through which information surrounding acute events comes into being on micro-blogs. In order to conduct this analysis systematically and theoretically, the concept of interpretive communities will be deployed. This research investigates if or not micro-blog based social groups can serve as interpretive communities, and, if so, what role might they play in the construction of information, and the social impacts that may arise. To understand how this process is entangled with the surrounding social, political, technical contexts, cases from both China (focusing on Sina Weibo) and Australia (focusing on Twitter) will be analysed.

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Background: High-resolution magnetic resonance (MR) imaging has been used for MR imaging-based structural stress analysis of atherosclerotic plaques. The biomechanical stress profile of stable plaques has been observed to differ from that of unstable plaques; however, the role that structural stresses play in determining plaque vulnerability remains speculative. Methods: A total of 61 patients with previous history of symptomatic carotid artery disease underwent carotid plaque MR imaging. Plaque components of the index artery such as fibrous tissue, lipid content and plaque haemorrhage (PH) were delineated and used for finite element analysis-based maximum structural stress (M-C Stress) quantification. These patients were followed up for 2 years. The clinical end point was occurrence of an ischaemic cerebrovascular event. The association of the time to the clinical end point with plaque morphology and M-C Stress was analysed. Results: During a median follow-up duration of 514 days, 20% of patients (n=12) experienced an ischaemic event in the territory of the index carotid artery. Cox regression analysis indicated that M-C Stress (hazard ratio (HR): 12.98 (95% confidence interval (CI): 1.32-26.67, pZ0.02), fibrous cap (FC) disruption (HR: 7.39 (95% CI: 1.61e33.82), p Z 0.009) and PH (HR: 5.85 (95% CI: 1.27e26.77), p Z 0.02) are associated with the development of subsequent cerebrovascular events. Plaques associated with future events had higher M-C Stress than those which had remained asymptomatic (median (interquartile range, IQR): 330 kPa (229e494) vs. 254 kPa (166-290), p Z0.04). Conclusions: High biomechanical structural stresses, in addition to FC rupture and PH, are associated with subsequent cerebrovascular events.

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Homelessness is a significant public health problem. It is well-documented that people experiencing homelessness exhibit more serious illnesses and have poorer health than the general population. The provision of services and interventions by health-care professionals, including pharmacists, may make a simple yet important contribution to improved health outcomes in those experiencing homelessness, but evidence of roles and interventions is limited and variable. In Australia, the Queensland University of Technology Health Clinic connects with the homeless community by taking part in community outreach events. This paper provides details of one such event, as well as the roles, interventions and experiences of pharmacists. Participation and inclusion of pharmacists in a multidisciplinary health-care team approach at homeless outreach events should be supported and encouraged.

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Road traffic emissions are often considered the main source of ultrafine particles (UFP, diameter smaller than 100 nm) in urban environments. However, recent studies worldwide have shown that - in high-insolation urban regions at least - new particle formation events can also contribute to UFP. In order to quantify such events we systematically studied three cities located in predominantly sunny environments: Barcelona (Spain), Madrid (Spain) and Brisbane (Australia). Three long term datasets (1-2 years) of fine and ultrafine particle number size distributions (measured by SMPS, Scanning Mobility Particle Sizer) were analysed. Compared to total particle number concentrations, aerosol size distributions offer far more information on the type, origin and atmospheric evolution of the particles. By applying k-Means clustering analysis, we categorized the collected aerosol size distributions in three main categories: “Traffic” (prevailing 44-63% of the time), “Nucleation” (14-19%) and “Background pollution and Specific cases” (7-22%). Measurements from Rome (Italy) and Los Angeles (California) were also included to complement the study. The daily variation of the average UFP concentrations for a typical nucleation day at each site revealed a similar pattern for all cities, with three distinct particle bursts. A morning and an evening spike reflected traffic rush hours, whereas a third one at midday showed nucleation events. The photochemically nucleated particles burst lasted 1-4 hours, reaching sizes of 30-40 nm. On average, the occurrence of particle size spectra dominated by nucleation events was 16% of the time, showing the importance of this process as a source of UFP in urban environments exposed to high solar radiation. On average, nucleation events lasting for 2 hours or more occurred on 55% of the days, this extending to >4hrs in 28% of the days, demonstrating that atmospheric conditions in urban environments are not favourable to the growth of photochemically nucleated particles. In summary, although traffic remains the main source of UFP in urban areas, in developed countries with high insolation urban nucleation events are also a main source of UFP. If traffic-related particle concentrations are reduced in the future, nucleation events will likely increase in urban areas, due to the reduced urban condensation sinks.

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Objective: To examine the association between preoperative quality of life (QoL) and postoperative adverse events in women treated for endometrial cancer. Methods: 760 women with apparent Stage I endometrial cancer were randomised into a clinical trial evaluating laparoscopic versus open surgery. This analysis includes women with preoperative QoL measurements, from the Functional Assessment of Cancer Therapy- General (FACT-G) questionnaire, and who were followed up for at least 6 weeks after surgery (n=684). The outcomes for this study were defined as (1) the occurrence of moderate to severe AEs adverse events within 6 months (Common Toxicology Criteria (CTC) grade ≥3); and (2) any Serious Adverse Event (SAE). The association between preoperative QoL and the occurrence of AE was examined, after controlling for baseline comorbidity and other factors. Results: After adjusting for other factors, odds of occurrence of AE of CTC grade ≥3 were significantly increased with each unit decrease in baseline FACT-G score (OR=1.02, 95% CI 1.00-1.03, p=0.030), which was driven by physical well-being (PWB) (OR=1.09, 95% CI 1.04-1.13, p=0.0002) and functional well-being subscales (FWB) (OR=1.04, 95% CI 1.00-1.07, p=0.035). Similarly, odds of SAE occurrence were significantly increased with each unit decrease in baseline FACT-G score (OR=1.02, 95% CI 1.01-1.04, p=0.011), baseline PWB (OR=1.11, 95% CI 1.06-1.16, p<0.0001) or baseline FWB subscales (OR=1.05, 95% CI 1.01-1.10, p=0.0077). Conclusion: Women with early endometrial cancer presenting with lower QoL prior to surgery are at higher risk of developing a serious adverse event following surgery. Funding: Cancer Council Queensland, Cancer Council New South Wales, Cancer Council Victoria, Cancer Council, Western Australia; NHMRC project grant 456110; Cancer Australia project grant 631523; The Women and Infants Research Foundation, Western Australia; Royal Brisbane and Women’s Hospital Foundation; Wesley Research Institute; Gallipoli Research Foundation; Gynetech; TYCO Healthcare, Australia; Johnson and Johnson Medical, Australia; Hunter New England Centre for Gynaecological Cancer; Genesis Oncology Trust; and Smart Health Research Grant QLD Health.

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The QUT Centre for Subtropical Design conducted a design-led interdisciplinary collaborative workshop (charrette) to develop some initial ideas for how innovation in research and practice can be applied to the complex problem of resilient future-focussed urban renewal in Rockhampton’s flood-prone suburbs and core grid. Three creative teams explored a range of scenarios for Rockhampton’s resilience in built form over the longer term. A large number of sketches, drawings and text were produced over two days. This report identifies themes, principles and strategies which emerged from the charrette. Each group proposed multiple guiding principles that fell into three strategic approaches: defend (through construction of a levee); adapt (by designing with flood in mind); retreat (a long term view to relocate populations in flood-prone areas). All three groups identified the importance of design that accommodates art, heritage, recreation, sustainability and tourism, and proposed these as principles to guide future strategies that mediate between Rockhampton’s broader ecological landscape and urban living to accommodate more affordable housing options, demonstrate sustainability and be climate responsive to predicted increased extreme weather events including flooding. The charrette outcomes pave the way to investigate wider issues and solutions to Rockhampton’s resilient future, beyond a levee as an isolated structure.

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Introduction: Extreme heat events (both heat waves and extremely hot days) are increasing in frequency and duration globally and cause more deaths in Australia than any other extreme weather event. Numerous studies have demonstrated a link between extreme heat events and an increased risk of morbidity and death. In this study, the researchers sought to identify if extreme heat events in the Tasmanian population were associated with any changes in emergency department admissions to the Royal Hobart Hospital (RHH) for the period 2003-2010. Methods: Non-identifiable RHH emergency department data and climate data from the Australian Bureau of Meteorology were obtained for the period 2003-2010. Statistical analyses were conducted using the computer statistical computer software ‘R’ with a distributed lag non-linear model (DLNM) package used to fit a quassi-Poisson generalised linear regression model. Results: This study showed that RR of admission to RHH during 2003-2010 was significant over temperatures of 24 C with a lag effect lasting 12 days and main effect noted one day after the extreme heat event. Discussion: This study demonstrated that extreme heat events have a significant impact on public hospital admissions. Two limitations were identified: admissions data rather than presentations data were used and further analysis could be done to compare types of admissions and presentations between heat and non-heat events. Conclusion: With the impacts of climate change already being felt in Australia, public health organisations in Tasmania and the rest of Australia need to implement adaptation strategies to enhance resilience to protect the public from the adverse health effects of heat events and climate change.

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Video surveillance infrastructure has been widely installed in public places for security purposes. However, live video feeds are typically monitored by human staff, making the detection of important events as they occur difficult. As such, an expert system that can automatically detect events of interest in surveillance footage is highly desirable. Although a number of approaches have been proposed, they have significant limitations: supervised approaches, which can detect a specific event, ideally require a large number of samples with the event spatially and temporally localised; while unsupervised approaches, which do not require this demanding annotation, can only detect whether an event is abnormal and not specific event types. To overcome these problems, we formulate a weakly-supervised approach using Kullback-Leibler (KL) divergence to detect rare events. The proposed approach leverages the sparse nature of the target events to its advantage, and we show that this data imbalance guarantees the existence of a decision boundary to separate samples that contain the target event from those that do not. This trait, combined with the coarse annotation used by weakly supervised learning (that only indicates approximately when an event occurs), greatly reduces the annotation burden while retaining the ability to detect specific events. Furthermore, the proposed classifier requires only a decision threshold, simplifying its use compared to other weakly supervised approaches. We show that the proposed approach outperforms state-of-the-art methods on a popular real-world traffic surveillance dataset, while preserving real time performance.

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The current approach for protecting the receiving water environment from urban stormwater pollution is the adoption of structural measures commonly referred to as Water Sensitive Urban Design (WSUD). The treatment efficiency of WSUD measures closely depends on the design of the specific treatment units. As stormwater quality is influenced by rainfall characteristics, the selection of appropriate rainfall events for treatment design is essential to ensure the effectiveness of WSUD systems. Based on extensive field investigations in four urban residential catchments based at Gold Coast, Australia, and computer modelling, this paper details a technically robust approach for the selection of rainfall events for stormwater treatment design using a three-component model. The modelling results confirmed that high intensity-short duration events produce 58.0% of TS load while they only generated 29.1% of total runoff volume. Additionally, rainfall events smaller than 6-month average recurrence interval (ARI) generates a greater cumulative runoff volume (68.4% of the total annual runoff volume) and TS load (68.6% of the TS load exported) than the rainfall events larger than 6-month ARI. The results suggest that for the study catchments, stormwater treatment design could be based on the rainfall which had a mean value of 31 mm/h average intensity and 0.4 h duration. These outcomes also confirmed that selecting smaller ARI rainfall events with high intensity-short duration as the threshold for treatment system design is the most feasible approach since these events cumulatively generate a major portion of the annual pollutant load compared to the other types of events, despite producing a relatively smaller runoff volume. This implies that designs based on small and more frequent rainfall events rather than larger rainfall events would be appropriate in the context of efficiency in treatment performance, cost-effectiveness and possible savings in land area needed.

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The most difficult operation in the flood inundation mapping using optical flood images is to separate fully inundated areas from the ‘wet’ areas where trees and houses are partly covered by water. This can be referred as a typical problem the presence of mixed pixels in the images. A number of automatic information extraction image classification algorithms have been developed over the years for flood mapping using optical remote sensing images. Most classification algorithms generally, help in selecting a pixel in a particular class label with the greatest likelihood. However, these hard classification methods often fail to generate a reliable flood inundation mapping because the presence of mixed pixels in the images. To solve the mixed pixel problem advanced image processing techniques are adopted and Linear Spectral unmixing method is one of the most popular soft classification technique used for mixed pixel analysis. The good performance of linear spectral unmixing depends on two important issues, those are, the method of selecting endmembers and the method to model the endmembers for unmixing. This paper presents an improvement in the adaptive selection of endmember subset for each pixel in spectral unmixing method for reliable flood mapping. Using a fixed set of endmembers for spectral unmixing all pixels in an entire image might cause over estimation of the endmember spectra residing in a mixed pixel and hence cause reducing the performance level of spectral unmixing. Compared to this, application of estimated adaptive subset of endmembers for each pixel can decrease the residual error in unmixing results and provide a reliable output. In this current paper, it has also been proved that this proposed method can improve the accuracy of conventional linear unmixing methods and also easy to apply. Three different linear spectral unmixing methods were applied to test the improvement in unmixing results. Experiments were conducted in three different sets of Landsat-5 TM images of three different flood events in Australia to examine the method on different flooding conditions and achieved satisfactory outcomes in flood mapping.