27 resultados para Maximum and minimum air temperature

em Queensland University of Technology - ePrints Archive


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The aim of this investigation was to elucidate the reductions in muscle, skin and core temperature following exposure to −110°C whole body cryotherapy (WBC), and compare these to 8°C cold water immersion (CWI). Twenty active male subjects were randomly assigned to a 4-min exposure of WBC or CWI. A minimum of 7 days later subjects were exposed to the other treatment. Muscle temperature in the right vastus lateralis (n = 10); thigh skin (average, maximum and minimum) and rectal temperature (n = 10) were recorded before and 60 min after treatment. The greatest reduction (P<0.05) in muscle (mean ± SD; 1 cm: WBC, 1.6±1.2°C; CWI, 2.0±1.0°C; 2 cm: WBC, 1.2±0.7°C; CWI, 1.7±0.9°C; 3 cm: WBC, 1.6±0.6°C; CWI, 1.7±0.5°C) and rectal temperature (WBC, 0.3±0.2°C; CWI, 0.4±0.2°C) were observed 60 min after treatment. The largest reductions in average (WBC, 12.1±1.0°C; CWI, 8.4±0.7°C), minimum (WBC, 13.2±1.4°C; CWI, 8.7±0.7°C) and maximum (WBC, 8.8±2.0°C; CWI, 7.2±1.9°C) skin temperature occurred immediately after both CWI and WBC (P<0.05). Skin temperature was significantly lower (P<0.05) immediately after WBC compared to CWI. The present study demonstrates that a single WBC exposure decreases muscle and core temperature to a similar level of those experienced after CWI. Although both treatments significantly reduced skin temperature, WBC elicited a greater decrease compared to CWI. These data may provide information to clinicians and researchers attempting to optimise WBC and CWI protocols in a clinical or sporting setting.

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Previous studies have demonstrated the importance of weather variables in influencing the incidence of influenza. However, the role of air pollution is often ignored in identifying the environmental drivers of influenza. This research aims to examine the impacts of air pollutants and temperature on the incidence of pediatric influenza in Brisbane, Australia. Lab-confirmed daily data on influenza counts among children aged 0-14years in Brisbane from 2001 January 1st to 2008 December 31st were retrieved from Queensland Health. Daily data on maximum and minimum temperatures for the same period were supplied by the Australian Bureau of Meteorology. Winter was chosen as the main study season due to it having the highest pediatric influenza incidence. Four Poisson log-linear regression models, with daily pediatric seasonal influenza counts as the outcome, were used to examine the impacts of air pollutants (i.e., ozone (O3), particulate matter≤10μm (PM10) and nitrogen dioxide (NO2)) and temperature (using a moving average of ten days for these variables) on pediatric influenza. The results show that mean temperature (Relative risk (RR): 0.86; 95% Confidence Interval (CI): 0.82-0.89) was negatively associated with pediatric seasonal influenza in Brisbane, and high concentrations of O3 (RR: 1.28; 95% CI: 1.25-1.31) and PM10 (RR: 1.11; 95% CI: 1.10-1.13) were associated with more pediatric influenza cases. There was a significant interaction effect (RR: 0.94; 95% CI: 0.93-0.95) between PM10 and mean temperature on pediatric influenza. Adding the interaction term between mean temperature and PM10 substantially improved the model fit. This study provides evidence that PM10 needs to be taken into account when evaluating the temperature-influenza relationship. O3 was also an important predictor, independent of temperature.

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Suicide has drawn much attention from both the scientific community and the public. Examining the impact of socio-environmental factors on suicide is essential in developing suicide prevention strategies and interventions, because it will provide health authorities with important information for their decision-making. However, previous studies did not examine the impact of socio-environmental factors on suicide using a spatial analysis approach. The purpose of this study was to identify the patterns of suicide and to examine how socio-environmental factors impact on suicide over time and space at the Local Governmental Area (LGA) level in Queensland. The suicide data between 1999 and 2003 were collected from the Australian Bureau of Statistics (ABS). Socio-environmental variables at the LGA level included climate (rainfall, maximum and minimum temperature), Socioeconomic Indexes for Areas (SEIFA) and demographic variables (proportion of Indigenous population, unemployment rate, proportion of population with low income and low education level). Climate data were obtained from Australian Bureau of Meteorology. SEIFA and demographic variables were acquired from ABS. A series of statistical and geographical information system (GIS) approaches were applied in the analysis. This study included two stages. The first stage used average annual data to view the spatial pattern of suicide and to examine the association between socio-environmental factors and suicide over space. The second stage examined the spatiotemporal pattern of suicide and assessed the socio-environmental determinants of suicide, using more detailed seasonal data. In this research, 2,445 suicide cases were included, with 1,957 males (80.0%) and 488 females (20.0%). In the first stage, we examined the spatial pattern and the determinants of suicide using 5-year aggregated data. Spearman correlations were used to assess associations between variables. Then a Poisson regression model was applied in the multivariable analysis, as the occurrence of suicide is a small probability event and this model fitted the data quite well. Suicide mortality varied across LGAs and was associated with a range of socio-environmental factors. The multivariable analysis showed that maximum temperature was significantly and positively associated with male suicide (relative risk [RR] = 1.03, 95% CI: 1.00 to 1.07). Higher proportion of Indigenous population was accompanied with more suicide in male population (male: RR = 1.02, 95% CI: 1.01 to 1.03). There was a positive association between unemployment rate and suicide in both genders (male: RR = 1.04, 95% CI: 1.02 to 1.06; female: RR = 1.07, 95% CI: 1.00 to 1.16). No significant association was observed for rainfall, minimum temperature, SEIFA, proportion of population with low individual income and low educational attainment. In the second stage of this study, we undertook a preliminary spatiotemporal analysis of suicide using seasonal data. Firstly, we assessed the interrelations between variables. Secondly, a generalised estimating equations (GEE) model was used to examine the socio-environmental impact on suicide over time and space, as this model is well suited to analyze repeated longitudinal data (e.g., seasonal suicide mortality in a certain LGA) and it fitted the data better than other models (e.g., Poisson model). The suicide pattern varied with season and LGA. The north of Queensland had the highest suicide mortality rate in all the seasons, while there was no suicide case occurred in the southwest. Northwest had consistently higher suicide mortality in spring, autumn and winter. In other areas, suicide mortality varied between seasons. This analysis showed that maximum temperature was positively associated with suicide among male population (RR = 1.24, 95% CI: 1.04 to 1.47) and total population (RR = 1.15, 95% CI: 1.00 to 1.32). Higher proportion of Indigenous population was accompanied with more suicide among total population (RR = 1.16, 95% CI: 1.13 to 1.19) and by gender (male: RR = 1.07, 95% CI: 1.01 to 1.13; female: RR = 1.23, 95% CI: 1.03 to 1.48). Unemployment rate was positively associated with total (RR = 1.40, 95% CI: 1.24 to 1.59) and female (RR=1.09, 95% CI: 1.01 to 1.18) suicide. There was also a positive association between proportion of population with low individual income and suicide in total (RR = 1.28, 95% CI: 1.10 to 1.48) and male (RR = 1.45, 95% CI: 1.23 to 1.72) population. Rainfall was only positively associated with suicide in total population (RR = 1.11, 95% CI: 1.04 to 1.19). There was no significant association for rainfall, minimum temperature, SEIFA, proportion of population with low educational attainment. The second stage is the extension of the first stage. Different spatial scales of dataset were used between the two stages (i.e., mean yearly data in the first stage, and seasonal data in the second stage), but the results are generally consistent with each other. Compared with other studies, this research explored the variety of the impact of a wide range of socio-environmental factors on suicide in different geographical units. Maximum temperature, proportion of Indigenous population, unemployment rate and proportion of population with low individual income were among the major determinants of suicide in Queensland. However, the influence from other factors (e.g. socio-culture background, alcohol and drug use) influencing suicide cannot be ignored. An in-depth understanding of these factors is vital in planning and implementing suicide prevention strategies. Five recommendations for future research are derived from this study: (1) It is vital to acquire detailed personal information on each suicide case and relevant information among the population in assessing the key socio-environmental determinants of suicide; (2) Bayesian model could be applied to compare mortality rates and their socio-environmental determinants across LGAs in future research; (3) In the LGAs with warm weather, high proportion of Indigenous population and/or unemployment rate, concerted efforts need to be made to control and prevent suicide and other mental health problems; (4) The current surveillance, forecasting and early warning system needs to be strengthened, to trace the climate and socioeconomic change over time and space and its impact on population health; (5) It is necessary to evaluate and improve the facilities of mental health care, psychological consultation, suicide prevention and control programs; especially in the areas with low socio-economic status, high unemployment rate, extreme weather events and natural disasters.

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The close relationship between rain and lightning is well known. However, there are numerous documented observations of heavy rain accompanied by little or no lightning activity (Williams et al, 1992; Jayaratne, 1993). Kuleshov et al (2002) studied thunderstorm distribution and frequency in Australia and concluded that thunderstorm frequency (as expressed by number of thunder-days) in Australia does not, in general, appear to vary in any consistent way with rainfall. However, thunder-days describe occurrence of thunderstorms as heard by an observer, and therefore could be only proxy data to evaluate actual lightning activity (i.e. number of total or cloud-to-ground flashes). Field experiments have demonstrated a strong increase in lightning activity with convective available potential energy (CAPE). It has also been shown that CAPE increases linearly with potential wet bulb temperature, Tw (Williams et al, 1992). In this study, we examine the relationship between lightning ground flash incidence and the two parameters – surface rainfall and surface wet bulb maximum temperature for selected localities around Australia...

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The dynamic nature of tissue temperature and the subcutaneous properties, such as blood flow, fatness, and metabolic rate, leads to variation in local skin temperature. Therefore, we investigated the effects of using multiple regions of interest when calculating weighted mean skin temperature from four local sites. Twenty-six healthy males completed a single trial in a thermonetural laboratory (mean ± SD): 24.0 (1.2) °C; 56 (8%) relative humidity; < 0.1 m/s air speed). Mean skin temperature was calculated from four local sites (neck, scapula, hand and shin) in accordance with International Standards using digital infrared thermography. A 50 x 50 mm square, defined by strips of aluminium tape, created six unique regions of interest, top left quadrant, top right quadrant, bottom left quadrant, bottom right quadrant, centre quadrant and the entire region of interest, at each of the local sites. The largest potential error in weighted mean skin temperature was calculated using a combination of a) the coolest and b) the warmest regions of interest at each of the local sites. Significant differences between the six regions interest were observed at the neck (P < 0.01), scapula (P < 0.001) and shin (P < 0.05); but not at the hand (P = 0.482). The largest difference (± SEM) at each site was as follows: neck 0.2 (0.1) °C; scapula 0.2 (0.0) °C; shin 0.1 (0.0) °C and hand 0.1 (0.1) °C. The largest potential error (mean ± SD) in weighted mean skin temperature was 0.4 (0.1) °C (P < 0.001) and the associated 95% limits of agreement for these differences was 0.2 to 0.5 °C. Although we observed differences in local and mean skin temperature based on the region of interest employed, these differences were minimal and are not considered physiologically meaningful.

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Polybrominated diphenyl ethers (PBDEs) are lipophilic, persistent pollutants found worldwide in environmental and human samples. Exposure pathways for PBDEs remain unclear but may include food, air and dust. The aim of this study was to conduct an integrated assessment of PBDE exposure and human body burden using 10 matched samples of human milk, indoor air and dust collected in 2007–2008 in Brisbane, Australia. In addition, temporal analysis was investigated comparing the results of the current study with PBDE concentrations in human milk collected in 2002–2003 from the same region. PBDEs were detected in all matrices and the median concentrations of BDEs -47 and -209 in human milk, air and dust were: 4.2 and 0.3 ng/g lipid; 25 and 7.8 pg/m3; and 56 and 291 ng/g dust, respectively. Significant correlations were observed between the concentrations of BDE-99 in air and human milk (r = 0.661, p = 0.038) and BDE-153 in dust and BDE-183 in human milk (r = 0.697, p = 0.025). These correlations do not suggest causal relationships — there is no hypothesis that can be offered to explain why BDE-153 in dust and BDE-183 in milk are correlated. The fact that so few correlations were found in the data could be a function of the small sample size, or because additional factors, such as sources of exposure not considered or measured in the study, might be important in explaining exposure to PBDEs. There was a slight decrease in PBDE concentrations from 2002–2003 to 2007–2008 but this may be due to sampling and analytical differences. Overall, average PBDE concentrations from these individual samples were similar to results from pooled human milk collected in Brisbane in 2002–2003 indicating that pooling may be an efficient, cost-effective strategy of assessing PBDE concentrations on a population basis. The results of this study were used to estimate an infant's daily PBDE intake via inhalation, dust ingestion and human milk consumption. Differences in PBDE intake of individual congeners from the different matrices were observed. Specifically, as the level of bromination increased, the contribution of PBDE intake decreased via human milk and increased via dust. As the impacts of the ban of the lower brominated (penta- and octa-BDE) products become evident, an increased use of the higher brominated deca-BDE product may result in dust making a greater contribution to infant exposure than it does currently. To better understand human body burden, further research is required into the sources and exposure pathways of PBDEs and metabolic differences influencing an individual's response to exposure. In addition, temporal trend analysis is necessary with continued monitoring of PBDEs in the human population as well as in the suggested exposure matrices of food, dust and air.

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The relationship between weather and mortality has been observed for centuries. Recently, studies on temperature-related mortality have become a popular topic as climate change continues. Most of the previous studies found that exposure to hot or cold temperature affects mortality. This study aims to address three research questions: 1. What is the overall effect of daily mean temperature variation on the elderly mortality in the published literature using a meta-analysis approach? 2. Does the association between temperature and mortality differ with age, sex, or socio-economic status in Brisbane? 3. How is the magnitude of the lag effects of the daily mean temperature on mortality varied by age and cause-of-death groups in Brisbane? In the meta-analysis, there was a 1-2 % increase in all-cause mortality for a 1ºC decrease during cold temperature intervals and a 2-5% increase for a 1ºC increment during hot temperature intervals among the elderly. Lags of up to 9 days in exposure to cold temperature intervals were statistically significantly associated with all-cause mortality, but no significant lag effects were observed for hot temperature intervals. In Brisbane, the harmful effect of high temperature (over 24ºC) on mortality appeared to be greater among the elderly than other age groups. The effect estimate among women was greater than among men. However, No evidence was found that socio-economic status modified the temperature-mortality relationship. The results of this research also show longer lag effects in cold days and shorter lag effects in hot days. For 3-day hot effects associated with 1°C increase above the threshold, the highest percent increases in mortality occurred among people aged 85 years or over (5.4% (95% CI: 1.4%, 9.5%)) compared with all age group (3.2% (95% CI: 0.9%, 5.6%)). The effect estimate among cardiovascular deaths was slightly higher than those among all-cause mortality. For overall 21-day cold effects associated with a 1°C decrease below the threshold, the percent estimates in mortality for people aged 85 years or over, and from cardiovascular diseases were 3.9% (95% CI: 1.9%, 6.0%) and 3.4% (95% CI: 0.9%, 6.0%), respectively compared with all age group (2.0% (95% CI: 0.7%, 3.3%)). Little research of this kind has been conducted in the Southern Hemisphere. This PhD research may contribute to the quantitative assessment of the overall impact, effect modification and lag effects of temperature variation on mortality in Australia and The findings may provide useful information for the development and implementation of public health policies to reduce and prevent temperature-related health problems.

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5-Hydroxytryptamine (5HT), commonly known as serotonin, which predominantly serves as an inhibitory neurotransmitter in the brain, has long been implicated in migraine pathophysiology. This study tested an Mspl polymorphism in the human 5HT2A receptor gene (HTR2A) and a closely linked microsatellite marker (D13S126), for linkage and association with common migraine. In the association analyses, no significant differences were found between the migraine and control populations for both the Mspl polymorphism and the D13S126 microsatellite marker. The linkage studies involving three families comprising 36 affected members were analysed using both parametric (FASTLINK) and non-parametric (MFLINK and APM) techniques. Significant close linkage was indicated between the Mspl polymorphism and the D13S126 microsatellite marker at a recombination fraction (θ) of zero (lod score=7.15). Linkage results for the Mspl polymorphism were not very informative in the three families, producing maximum and minimum lod scores of only 0.35 and 0.39 at recombination fractions (θ) of 0.2 and 0.00, respectively. However, linkage analysis between the D13S126 marker and migraine indicated significant non-linkage (lod2) up to a recombination fraction (θ) of 0.028. Results from this study exclude the HTR2A gene, which has been localized to chromosome 13q14-q21, for involvement with common migraine.

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Diagnostics is based on the characterization of mechanical system condition and allows early detection of a possible fault. Signal processing is an approach widely used in diagnostics, since it allows directly characterizing the state of the system. Several types of advanced signal processing techniques have been proposed in the last decades and added to more conventional ones. Seldom, these techniques are able to consider non-stationary operations. Diagnostics of roller bearings is not an exception of this framework. In this paper, a new vibration signal processing tool, able to perform roller bearing diagnostics in whatever working condition and noise level, is developed on the basis of two data-adaptive techniques as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED), coupled by means of the mathematics related to the Hilbert transform. The effectiveness of the new signal processing tool is proven by means of experimental data measured in a test-rig that employs high power industrial size components.

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BACKGROUND Mosquito-borne diseases are climate sensitive and there has been increasing concern over the impact of climate change on future disease risk. This paper projected the potential future risk of Barmah Forest virus (BFV) disease under climate change scenarios in Queensland, Australia. METHODS/PRINCIPAL FINDINGS We obtained data on notified BFV cases, climate (maximum and minimum temperature and rainfall), socio-economic and tidal conditions for current period 2000-2008 for coastal regions in Queensland. Grid-data on future climate projections for 2025, 2050 and 2100 were also obtained. Logistic regression models were built to forecast the otential risk of BFV disease distribution under existing climatic, socio-economic and tidal conditions. The model was applied to estimate the potential geographic distribution of BFV outbreaks under climate change scenarios. The predictive model had good model accuracy, sensitivity and specificity. Maps on potential risk of future BFV disease indicated that disease would vary significantly across coastal regions in Queensland by 2100 due to marked differences in future rainfall and temperature projections. CONCLUSIONS/SIGNIFICANCE We conclude that the results of this study demonstrate that the future risk of BFV disease would vary across coastal regions in Queensland. These results may be helpful for public health decision making towards developing effective risk management strategies for BFV disease control and prevention programs in Queensland.

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Introduction This study examines and compares the dosimetric quality of radiotherapy treatment plans for prostate carcinoma across a cohort of 163 patients treated across 5 centres: 83 treated with three-dimensional conformal radiotherapy (3DCRT), 33 treated with intensity-modulated radiotherapy (IMRT) and 47 treated with volumetric-modulated arc therapy (VMAT). Methods Treatment plan quality was evaluated in terms of target dose homogeneity and organ-at-risk sparing, through the use of a set of dose metrics. These included the mean, maximum and minimum doses; the homogeneity and conformity indices for the target volumes; and a selection of dose coverage values that were relevant to each organ-at-risk. Statistical significance was evaluated using two-tailed Welch’s T-tests. The Monte Carlo DICOM ToolKit software was adapted to permit the evaluation of dose metrics from DICOM data exported from a commercial radiotherapy treatment planning system. Results The 3DCRT treatment plans offered greater planning target volume dose homogeneity than the other two treatment modalities. The IMRT and VMAT plans offered greater dose reduction in the organs-at-risk: with increased compliance with recommended organ-at-risk dose constraints, compared to conventional 3DCRT treatments. When compared to each other, IMRT and VMAT did not provide significantly different treatment plan quality for like-sized tumour volumes. Conclusions This study indicates that IMRT and VMAT have provided similar dosimetric quality, which is superior to the dosimetric quality achieved with 3DCRT.

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This research quantifies the lag effects and vulnerabilities of temperature effects on cardiovascular disease in Changsha—a subtropical climate zone of China. A Poisson regression model within a distributed lag nonlinear models framework was used to examine the lag effects of cold- and heat-related CVD mortality. The lag effect for heat-related CVD mortality was just 0–3 days. In contrast, we observed a statistically significant association with 10–25 lag days for cold-related CVD mortality. Low temperatures with 0–2 lag days increased the mortality risk for those ≥65 years and females. For all ages, the cumulative effects of cold-related CVD mortality was 6.6% (95% CI: 5.2%–8.2%) for 30 lag days while that of heat-related CVD mortality was 4.9% (95% CI: 2.0%–7.9%) for 3 lag days. We found that in Changsha city, the lag effect of hot temperatures is short while the lag effect of cold temperatures is long. Females and older people were more sensitive to extreme hot and cold temperatures than males and younger people.

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The effects of various discharge parameters and ambient gas on the length of He atmospheric plasma jet plumes expanding into the open air are studied. It is found that the voltage and width of the discharge-sustaining pulses exert significantly stronger effects on the plume length than the pulse frequency, gas flow rate, and nozzle diameter. This result is explained through detailed analysis of the I-V characteristics of the primary and secondary discharges which reveals the major role of the integrated total charges of the primary discharge in the plasma dynamics. The length of the jet plume can be significantly increased by guiding the propagating plume into a glass tube attached to the nozzle. This increase is attributed to elimination of the diffusion of surrounding air into the plasma plume, an absence which facilitates the propagation of the ionization front. These results are important for establishing a good level of understanding of the expansion dynamics and for enabling a high degree of control of atmospheric pressure plasmas in biomedical, materials synthesis and processing, environmental and other existing and emerging industrial applications. © 2009 American Institute of Physics.

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Government contracts for services typically include terms requiring contractors to comply with minimum labour standards laws. Procurement contract clauses specify reporting procedures and sanctions for non-compliance, implying that government contracting agencies will monitor and enforce minimum labour standards within contract performance management. In this article, the case of school cleaners employed under New South Wales government contracts between 2010 and 2011 is the vehicle for exploring the effectiveness of these protective clauses. We find that the inclusion of these protective clauses in procurement contracts is unnecessary in the Australian context, and any expectations that government contracting agencies will monitor and enforce labour standards are misleading. At best, the clauses are rhetoric, and at worst, they are a distraction for parties with enforcement powers.