971 resultados para Periods
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Background Australian subacute rehabilitation facilities face significant challenges from the ageing population with increased burden of chronic disease. High risk foot complications are a negative consequence of many chronic diseases. With the rapid expansion of subacute services, it seems imperative to investigate the prevalence of foot complications in this population. The primary aim of this study was to quantify the high risk foot complication prevalence in a subacute rehabilitation population. Methods Eligible participants were all adults admitted overnight, over two 4 week periods, into a large Australian subacute rehabilitation facility. Consenting participants underwent a short non-invasive foot examination by a podiatrist. The standard Queensland Health High Risk Foot Form collected data on age, sex, co-morbidities and foot complications. Descriptive statistics, logistic regression and odds ratios were used to determine the prevalence of foot complications and associations with explanatory variables. Results Overall, 85 of 97 eligible participants consented; mean age 80(9) and 71% were female. At least one foot complication was present in 56.5% participants; including 21.2% defined as high risk and 11.8% current foot ulcer. A previous diagnosis of neuropathy increased the risk of presenting with a high risk foot by 13-fold (OR 13.504, p = 0.001). Conclusion This study highlights the significance of foot complications in the subacute population. It appears that one in every two patients present with a foot complication and one in eight with a foot ulcer. It is suggested all patients admitted to subacute rehabilitation services should be screened for foot complications.
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People often assume children have no worries or nothing to be stressed about. However, children, like adults, do worry about a range of things. There may be times during periods of stress or change when children worry more intensely about things than usual.
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Bisphenol A (BPA or 4,4’-(propane-2,2-diyl)diphenol) is a chemical intermediate in the production of polycarbonate and epoxy resins, and used in a wide range of applications. BPA has attracted significant attention in the past decade due to its frequency of detection in human populations worldwide, demonstrated animal toxicity and potential impact on human health, particularly during critical periods of development. The aim of this study was to perform a preliminary assessment of age-related trends in urinary concentration and to estimate daily excretion of BPA in Australian children (aged (>0 – <5 years) and adults (≥15 – <75 years). This was achieved using 79 samples pooled by age and gender, created from 868 individual samples of convenience collected as part of routine, community-based pathology testing. Total BPA was analyzed using online-SPE-LC-MS/MS and detected in all samples with a range of 0.65 – 265 ng/ml. No significant differences were observed between males and females. A urine flow model was constructed from published values and used to provide an estimate of daily excretion per unit bodyweight for each pooled sample. The daily excretion estimates ranged from 26.2 – 18200 ng/kg-d for children; and 20.1 – 165 ng/kg-d for adults. Urinary concentrations and estimated excretion rates were inversely associated with age, and estimated daily excretion rates in infants and young children were significantly higher than in adults (geometric mean: 107 and 47.0 ng/kg-d, respectively). Higher excretion of BPA in children may be explained by their higher food consumption relative to body weight compared to adults and adolescents, and may also reflect alternative exposure pathways and sources. Keywords: bisphenol A, biomonitoring, children, urine flow, Australia
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The period of developmental vulnerability to toxicants begins at conception and extends through gestation, parturition, infanthood and childhood to adolescence. The concern is that children: (1) may experience quantitatively and qualitatively different exposures, and (2) may have different sensitivity to chemical pollutants. Traditional toxicological studies are inappropriate for assessing the results of chronic exposure at very low levels during critical periods of development. This paper will discuss (1) the health effects associated with exposure to selected emerging organic pollutants, including brominated flame retardants, perfluorinated compounds, organophosphate pesticides and bisphenol A; (2) difficulties in monitoring these substances in children, and (3) suggest techniques and strategies for overcoming these difficulties. Such biomonitoring data can be used to identify where policies should be directed in order to reduce exposure, and to document policies that have successfully reduced exposure.
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Persistent monitoring of the ocean is not optimally accomplished by repeatedly executing a fixed path in a fixed location. The ocean is dynamic, and so should the executed paths to monitor and observe it. An open question merging autonomy and optimal sampling is how and when to alter a path/decision, yet achieve desired science objectives. Additionally, many marine robotic deployments can last multiple weeks to months; making it very difficult for individuals to continuously monitor and retask them as needed. This problem becomes increasingly more complex when multiple platforms are operating simultaneously. There is a need for monitoring and adaptation of the robotic fleet via teams of scientists working in shifts; crowds are ideal for this task. In this paper, we present a novel application of crowd-sourcing to extend the autonomy of persistent-monitoring vehicles to enable nonrepetitious sampling over long periods of time. We present a framework that enables the control of a marine robot by anybody with an internet-enabled device. Voters are provided current vehicle location, gathered science data and predicted ocean features through the associated decision support system. Results are included from a simulated implementation of our system on a Wave Glider operating in Monterey Bay with the science objective to maximize the sum of observed nitrate values collected.
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This paper presents a pose estimation approach that is resilient to typical sensor failure and suitable for low cost agricultural robots. Guiding large agricultural machinery with highly accurate GPS/INS systems has become standard practice, however these systems are inappropriate for smaller, lower-cost robots. Our positioning system estimates pose by fusing data from a low-cost global positioning sensor, low-cost inertial sensors and a new technique for vision-based row tracking. The results first demonstrate that our positioning system will accurately guide a robot to perform a coverage task across a 6 hectare field. The results then demonstrate that our vision-based row tracking algorithm improves the performance of the positioning system despite long periods of precision correction signal dropout and intermittent dropouts of the entire GPS sensor.
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Purpose: This is one of the first studies to report that the Achenbach internalising scales were much more effective at identifying those with current comorbid depression and anxiety, rather than individual mood disorder. Introduction: The Achenbach behaviour checklists (YSR,YASR) are widely used, low cost screening tools used to assess problem behaviour. Several studies report good association between the checklists and psychiatric diagnoses; although with varying degrees of agreement. Most are cross-sectional studies involving adolescents referred to mental health services; few are in large community-based studies. This study examined the usefulness of the Achenbach internalising scales in the primary screening (both predictive and concurrent)for depression and anxiety. Methods: The sample was 2400 young adults from an Australian population-based prospective birth cohort study. The association between the empirical anxiety and depression scales were individually assessed against DSM-IV depression and anxiety diagnoses. Odds ratios and diagnostic efficiency tests report the findings. Results: Adolescents with internalising symptoms were twice (OR 2.3, 95%CI 1.7 to 3.1) as likely to be diagnosed with later DSM-IV depression. YASR internalising scale predicted DSM-IV mood disorders (depression OR = 6.9, 95% CI 5.0–9.5; anxiety OR = 5.1, 95% CI 3.8–6.7) in the previous 12 months. The internalising scales were much more effective at identifying those with comorbid depression and anxiety. Conclusions: Adolescence and early adulthood are key risk periods for the onset of anxiety and depression. This study found that young people with internalising behaviour problems were more likely to have comorbid depression and anxiety DSM-IV disorder.
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Background Transmission of Plasmodium vivax malaria is dependent on vector availability, biting rates and parasite development. In turn, each of these is influenced by climatic conditions. Correlations have previously been detected between seasonal rainfall, temperature and malaria incidence patterns in various settings. An understanding of seasonal patterns of malaria, and their weather drivers, can provide vital information for control and elimination activities. This research aimed to describe temporal patterns in malaria, rainfall and temperature, and to examine the relationships between these variables within four counties of Yunnan Province, China. Methods Plasmodium vivax malaria surveillance data (1991–2006), and average monthly temperature and rainfall were acquired. Seasonal trend decomposition was used to examine secular trends and seasonal patterns in malaria. Distributed lag non-linear models were used to estimate the weather drivers of malaria seasonality, including the lag periods between weather conditions and malaria incidence. Results There was a declining trend in malaria incidence in all four counties. Increasing temperature resulted in increased malaria risk in all four areas and increasing rainfall resulted in increased malaria risk in one area and decreased malaria risk in one area. The lag times for these associations varied between areas. Conclusions The differences detected between the four counties highlight the need for local understanding of seasonal patterns of malaria and its climatic drivers.
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Objective: To examine the space-time clustering of dengue fever (DF) transmission in Bangladesh using geographical information system and spatial scan statistics (SaTScan). Methods: We obtained data on monthly suspected DF cases and deaths by district in Bangladesh for the period of 2000–2009 from Directorate General of Health Services. Population and district boundary data of each district were collected from national census managed by Bangladesh Bureau of Statistics. To identify the space-time clusters of DF transmission a discrete Poisson model was performed using SaTScan software. Results: Space-time distribution of DF transmission was clustered during three periods 2000–2002, 2003–2005 and 2006–2009. Dhaka was the most likely cluster for DF in all three periods. Several other districts were significant secondary clusters. However, the geographical range of DF transmission appears to have declined in Bangladesh over the last decade. Conclusion: There were significant space-time clusters of DF in Bangladesh over the last decade. Our results would prompt future studies to explore how social and ecological factors may affect DF transmission and would also be useful for improving DF control and prevention programs in Bangladesh.
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For industrial wireless sensor networks, maintaining the routing path for a high packet delivery ratio is one of the key objectives in network operations. It is important to both provide the high data delivery rate at the sink node and guarantee a timely delivery of the data packet at the sink node. Most proactive routing protocols for sensor networks are based on simple periodic updates to distribute the routing information. A faulty link causes packet loss and retransmission at the source until periodic route update packets are issued and the link has been identified as broken. We propose a new proactive route maintenance process where periodic update is backed-up with a secondary layer of local updates repeating with shorter periods for timely discovery of broken links. Proposed route maintenance scheme improves reliability of the network by decreasing the packet loss due to delayed identification of broken links. We show by simulation that proposed mechanism behaves better than the existing popular routing protocols (AODV, AOMDV and DSDV) in terms of end-to-end delay, routing overhead, packet reception ratio.
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OBJECTIVE The aim of the study is to examine the spatiotemporal pattern of Japanese Encephalitis (JE) in mainland China during 2002-2010. Specific objectives of the study were to quantify the temporal variation in incidence of JE cases, to determine if clustering of JE cases exists, to detect high risk spatiotemporal clusters of JE cases and to provide evidence-based preventive suggestions to relevant stakeholders. METHODS Monthly JE cases at the county level in mainland China during 2002-2010 were obtained from the China Information System for Diseases Control and Prevention (CISDCP). For the purpose of the analysis, JE case counts for nine years were aggregated into four temporal periods (2002; 2003-2005; 2006; and 2007-2010). Local Indicators of Spatial Association and spatial scan statistics were performed to detect and evaluate local high risk space-time clusters. RESULTS JE incidence showed a decreasing trend from 2002 to 2005 but peaked in 2006, then fluctuated over the study period. Spatial cluster analysis detected high value clusters, mainly located in Southwestern China. Similarly, we identified a primary spatiotemporal cluster of JE in Southwestern China between July and August, with the geographical range of JE transmission increasing over the past years. CONCLUSION JE in China is geographically clustered and its spatial extent dynamically changed during the last nine years in mainland China. This indicates that risk factors for JE infection are likely to be spatially heterogeneous. The results may assist national and local health authorities in the development/refinement of a better preventive strategy and increase the effectiveness of public health interventions against JE transmission.
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OBJECTIVES To identify the meteorological drivers of dengue vector density and determine high- and low-risk transmission zones for dengue prevention and control in Cairns, Australia. METHODS Weekly adult female Ae. aegypti data were obtained from 79 double sticky ovitraps (SOs) located in Cairns for the period September 2007-May 2012. Maximum temperature, total rainfall and average relative humidity data were obtained from the Australian Bureau of Meteorology for the study period. Time series-distributed lag nonlinear models were used to assess the relationship between meteorological variables and vector density. Spatial autocorrelation was assessed via semivariography, and ordinary kriging was undertaken to predict vector density in Cairns. RESULTS Ae. aegypti density was associated with temperature and rainfall. However, these relationships differed between short (0-6 weeks) and long (0-30 weeks) lag periods. Semivariograms showed that vector distributions were spatially autocorrelated in September 2007-May 2008 and January 2009-May 2009, and vector density maps identified high transmission zones in the most populated parts of Cairns city, as well as Machans Beach. CONCLUSION Spatiotemporal patterns of Ae. aegypti in Cairns are complex, showing spatial autocorrelation and associations with temperature and rainfall. Sticky ovitraps should be placed no more than 1.2 km apart to ensure entomological coverage and efficient use of resources. Vector density maps provide evidence for the targeting of prevention and control activities. Further research is needed to explore the possibility of developing an early warning system of dengue based on meteorological and environmental factors.
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We wished to determine whether changing our centre's practice of using Acticoat instead of Silvazine as our first-line burns dressing provided a better standard of care in terms of efficacy, cost and ease of use. A retrospective cohort study was performed examining 328 Silvazine treated patients from January 2000 to June 2001 and 241 Acticoat treated patients from July 2002 to July 2003. During those periods the respective dressings were used exclusively. There was no significant difference in age, %BSA and mechanism of burn between the groups. In the Silvazine group, 25.6% of children required grafting compared to 15.4% in the Acticoat group (p=0.001). When patients requiring grafting were excluded, the time taken for re-epithelialisation in the Acticoat group (14.9 days) was significantly less than that for the Silvazine group (18.3 days), p=0.047. There were more wounds requiring long term scar management in the Silvazine group (32.6%) compared to the Acticoat group (29.5%), however this was not significant. There was only one positive blood culture in each group, indicating that both Silvazine and Acticoat are potent antimicrobial agents. The use of Acticoat as our primary burns dressing has dramatically changed our clinical practice. Inpatients are now only 18% of the total admissions, with the vast majority of patients treated on an outpatient basis. In terms of cost, Acticoat was demonstrated to be less expensive over the treatment period than Silvazine . We have concluded that Acticoat is a safe, cost-effective, efficacious dressing that reduces the time for re-epithelialisation and the requirement for grafting and long term scar management, compared to Silvazine.
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Global awareness for cleaner and renewable energy is transforming the electricity sector at many levels. New technologies are being increasingly integrated into the electricity grid at high, medium and low voltage levels, new taxes on carbon emissions are being introduced and individuals can now produce electricity, mainly through rooftop photovoltaic (PV) systems. While leading to improvements, these changes also introduce challenges, and a question that often rises is ‘how can we manage this constantly evolving grid?’ The Queensland Government and Ergon Energy, one of the two Queensland distribution companies, have partnered with some Australian and German universities on a project to answer this question in a holistic manner. The project investigates the impact the integration of renewables and other new technologies has on the physical structure of the grid, and how this evolving system can be managed in a sustainable and economical manner. To aid understanding of what the future might bring, a software platform has been developed that integrates two modelling techniques: agent-based modelling (ABM) to capture the characteristics of the different system units accurately and dynamically, and particle swarm optimization (PSO) to find the most economical mix of network extension and integration of distributed generation over long periods of time. Using data from Ergon Energy, two types of networks (3 phase, and Single Wired Earth Return or SWER) have been modelled; three-phase networks are usually used in dense networks such as urban areas, while SWER networks are widely used in rural Queensland. Simulations can be performed on these networks to identify the required upgrades, following a three-step process: a) what is already in place and how it performs under current and future loads, b) what can be done to manage it and plan the future grid and c) how these upgrades/new installations will perform over time. The number of small-scale distributed generators, e.g. PV and battery, is now sufficient (and expected to increase) to impact the operation of the grid, which in turn needs to be considered by the distribution network manager when planning for upgrades and/or installations to stay within regulatory limits. Different scenarios can be simulated, with different levels of distributed generation, in-place as well as expected, so that a large number of options can be assessed (Step a). Once the location, sizing and timing of assets upgrade and/or installation are found using optimisation techniques (Step b), it is possible to assess the adequacy of their daily performance using agent-based modelling (Step c). One distinguishing feature of this software is that it is possible to analyse a whole area at once, while still having a tailored solution for each of the sub-areas. To illustrate this, using the impact of battery and PV can have on the two types of networks mentioned above, three design conditions can be identified (amongst others): · Urban conditions o Feeders that have a low take-up of solar generators, may benefit from adding solar panels o Feeders that need voltage support at specific times, may be assisted by installing batteries · Rural conditions - SWER network o Feeders that need voltage support as well as peak lopping may benefit from both battery and solar panel installations. This small example demonstrates that no single solution can be applied across all three areas, and there is a need to be selective in which one is applied to each branch of the network. This is currently the function of the engineer who can define various scenarios against a configuration, test them and iterate towards an appropriate solution. Future work will focus on increasing the level of automation in identifying areas where particular solutions are applicable.
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Travel time estimation and prediction on motorways has long been a topic of research. Prediction modeling generally assumes that the estimation is perfect. No matter how good is the prediction modeling- the errors in estimation can significantly deteriorate the accuracy and reliability of the prediction. Models have been proposed to estimate travel time from loop detector data. Generally, detectors are closely spaced (say 500m) and travel time can be estimated accurately. However, detectors are not always perfect, and even during normal running conditions few detectors malfunction, resulting in increase in the spacing between the functional detectors. Under such conditions, error in the travel time estimation is significantly large and generally unacceptable. This research evaluates the in-practice travel time estimation model during different traffic conditions. It is observed that the existing models fail to accurately estimate travel time during large detector spacing and congestion shoulder periods. Addressing this issue, an innovative Hybrid model that only considers loop data for travel time estimation is proposed. The model is tested using simulation and is validated with real Bluetooth data from Pacific Motorway Brisbane. Results indicate that during non free flow conditions and larger detector spacing Hybrid model provides significant improvement in the accuracy of travel time estimation.