1000 resultados para temperature


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Most studies examining the temperature–mortality association in a city used temperatures from one site or the average from a network of sites. This may cause measurement error as temperature varies across a city due to effects such as urban heat islands. We examined whether spatiotemporal models using spatially resolved temperatures produced different associations between temperature and mortality compared with time series models that used non-spatial temperatures. We obtained daily mortality data in 163 areas across Brisbane city, Australia from 2000 to 2004. We used ordinary kriging to interpolate spatial temperature variation across the city based on 19 monitoring sites. We used a spatiotemporal model to examine the impact of spatially resolved temperatures on mortality. Also, we used a time series model to examine non-spatial temperatures using a single site and the average temperature from three sites. We used squared Pearson scaled residuals to compare model fit. We found that kriged temperatures were consistent with observed temperatures. Spatiotemporal models using kriged temperature data yielded slightly better model fit than time series models using a single site or the average of three sites' data. Despite this better fit, spatiotemporal and time series models produced similar associations between temperature and mortality. In conclusion, time series models using non-spatial temperatures were equally good at estimating the city-wide association between temperature and mortality as spatiotemporal models.

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"To the Editor: Indigenous people face challenges that may make them more sensitive to extreme temperatures. These include poor health, inadequate infrastructure, and poverty.1 Few studies have examined the effects of extreme temperatures on Indigenous people2 or have considered the possible role of body mass in sensitivity to extreme temperatures..."

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The growth of graphene on SiC/Si substrates is an appealing alternative to the growth on bulk SiC for cost reduction and to better integrate the material with Si based electronic devices. In this paper, we present a complete in-situ study of the growth of epitaxial graphene on 3C SiC (111)/Si (111) substrates via high temperature annealing (ranging from 1125˚C to 1375˚C) in ultra high vacuum (UHV). The quality and number of graphene layers have been thoroughly investigated by using x-ray photoelectron spectroscopy (XPS), while the surface characterization have been studied by scanning tunnelling microscopy (STM). Ex-situ Raman spectroscopy measurements confirm our findings, which demonstrate the exponential dependence of the number of graphene layer from the annealing temperature.

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Background The association between temperature and mortality has been examined mainly in North America and Europe. However, less evidence is available in developing countries, especially in Thailand. In this study, we examined the relationship between temperature and mortality in Chiang Mai city, Thailand, during 1999–2008. Method A time series model was used to examine the effects of temperature on cause-specific mortality (non-external, cardiopulmonary, cardiovascular, and respiratory) and age-specific non-external mortality (<=64, 65–74, 75–84, and > =85 years), while controlling for relative humidity, air pollution, day of the week, season and long-term trend. We used a distributed lag non-linear model to examine the delayed effects of temperature on mortality up to 21 days. Results We found non-linear effects of temperature on all mortality types and age groups. Both hot and cold temperatures resulted in immediate increase in all mortality types and age groups. Generally, the hot effects on all mortality types and age groups were short-term, while the cold effects lasted longer. The relative risk of non-external mortality associated with cold temperature (19.35°C, 1st percentile of temperature) relative to 24.7°C (25th percentile of temperature) was 1.29 (95% confidence interval (CI): 1.16, 1.44) for lags 0–21. The relative risk of non-external mortality associated with high temperature (31.7°C, 99th percentile of temperature) relative to 28°C (75th percentile of temperature) was 1.11 (95% CI: 1.00, 1.24) for lags 0–21. Conclusion This study indicates that exposure to both hot and cold temperatures were related to increased mortality. Both cold and hot effects occurred immediately but cold effects lasted longer than hot effects. This study provides useful data for policy makers to better prepare local responses to manage the impact of hot and cold temperatures on population health.

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High-quality YBa2Cu3O7-δ films grown on (001) single-crystal Y-ZrO2 substrates by pulsed laser deposition have been studied as a function of substrate temperature using transmission electron microscopy. A transition from epitaxial films to c-axis oriented polycrystalline films was observed at 740°C. An intermediate, polycrystalline, BaZrO3 layer was formed from a reaction between the film and the substrate. A dominant orientation relationship of [001] YBCO//[001]int. layer//[001]YSZ and [110] YBCO//[110]int. layer//[100]YSZ was observed. The formation of grain boundaries in the films resulted in an increased microwave surface resistance and a decreased critical-current density. The superconducting transition temperature remained fairly constant at about 90 K.

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Non-periodic structural variation has been found in the high Tc cuprates, YBa2Cu3O7-x and Hg0.67Pb0.33Ba2Ca2Cu 3O8+δ, by image analysis of high resolution transmission electron microscope (HRTEM) images. We use two methods for analysis of the HRTEM images. The first method is a means for measuring the bending of lattice fringes at twin planes. The second method is a low-pass filter technique which enhances information contained by diffuse-scattered electrons and reveals what appears to be an interference effect between domains of differing lattice parameter in the top and bottom of the thin foil. We believe that these methods of image analysis could be usefully applied to the many thousands of HRTEM images that have been collected by other workers in the high temperature superconductor field. This work provides direct structural evidence for phase separation in high Tc cuprates, and gives support to recent stripes models that have been proposed to explain various angle resolved photoelectron spectroscopy and nuclear magnetic resonance data. We believe that the structural variation is a response to an opening of an electronic solubility gap where holes are not uniformly distributed in the material but are confined to metallic stripes. Optimum doping may occur as a consequence of the diffuse boundaries between stripes which arise from spinodal decomposition. Theoretical ideas about the high Tc cuprates which treat the cuprates as homogeneous may need to be modified in order to take account of this type of structural variation.

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The formation of readily recoverable and reusable organic semiconducting Cu- and AgTCNQ (TCNQ=7,7,8,8-tetracyanoquinodimethane) microstructures decorated with Pt and Pd metallic nanoparticles is described for the effective reduction of CrVI ions in aqueous solution at room temperature using both formic acid and an environmentally friendly thiosulfate reductant. The M-TCNQ (M=metal) materials were formed by electrocrystallisation onto a glassy carbon surface followed by galvanic replacement in the presence of H2PtCl6 or PdCl2 to form the composite material. It was found that loading of the surface with nanoparticles could easily be controlled by changing the metal salt concentration. Significantly, the M-TCNQ substrates facilitated the formation of well-isolated metal nanoparticles on their surfaces under appropriate galvanic replacement conditions. The semiconductor–metal nanoparticle combination was also found to be critical to the catalyst performance, wherein the best-performing material was CuTCNQ modified by well-isolated Pt nanoparticles with both formic acid and thiosulfate ions as the reductant.

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Climate change is expected to be one of the biggest global health threats in the 21st century. In response to changes in climate and associated extreme events, public health adaptation has become imperative. This thesis examined several key issues in this emerging research field. The thesis aimed to identify the climate-health (particularly temperature-health) relationships, then develop quantitative models that can be used to project future health impacts of climate change, and therefore help formulate adaptation strategies for dealing with climate-related health risks and reducing vulnerability. The research questions addressed by this thesis were: (1) What are the barriers to public health adaptation to climate change? What are the research priorities in this emerging field? (2) What models and frameworks can be used to project future temperature-related mortality under different climate change scenarios? (3) What is the actual burden of temperature-related mortality? What are the impacts of climate change on future burden of disease? and (4) Can we develop public health adaptation strategies to manage the health effects of temperature in response to climate change? Using a literature review, I discussed how public health organisations should implement and manage the process of planned adaptation. This review showed that public health adaptation can operate at two levels: building adaptive capacity and implementing adaptation actions. However, there are constraints and barriers to adaptation arising from uncertainty, cost, technologic limits, institutional arrangements, deficits of social capital, and individual perception of risks. The opportunities for planning and implementing public health adaptation are reliant on effective strategies to overcome likely barriers. I proposed that high priorities should be given to multidisciplinary research on the assessment of potential health effects of climate change, projections of future health impacts under different climate and socio-economic scenarios, identification of health cobenefits of climate change policies, and evaluation of cost-effective public health adaptation options. Heat-related mortality is the most direct and highly-significant potential climate change impact on human health. I thus conducted a systematic review of research and methods for projecting future heat-related mortality under different climate change scenarios. The review showed that climate change is likely to result in a substantial increase in heatrelated mortality. Projecting heat-related mortality requires understanding of historical temperature-mortality relationships, and consideration of future changes in climate, population and acclimatisation. Further research is needed to provide a stronger theoretical framework for mortality projections, including a better understanding of socioeconomic development, adaptation strategies, land-use patterns, air pollution and mortality displacement. Most previous studies were designed to examine temperature-related excess deaths or mortality risks. However, if most temperature-related deaths occur in the very elderly who had only a short life expectancy, then the burden of temperature on mortality would have less public health importance. To guide policy decisions and resource allocation, it is desirable to know the actual burden of temperature-related mortality. To achieve this, I used years of life lost to provide a new measure of health effects of temperature. I conducted a time-series analysis to estimate years of life lost associated with changes in season and temperature in Brisbane, Australia. I also projected the future temperaturerelated years of life lost attributable to climate change. This study showed that the association between temperature and years of life lost was U-shaped, with increased years of life lost on cold and hot days. The temperature-related years of life lost will worsen greatly if future climate change goes beyond a 2 °C increase and without any adaptation to higher temperatures. The excess mortality during prolonged extreme temperatures is often greater than the predicted using smoothed temperature-mortality association. This is because sustained period of extreme temperatures produce an extra effect beyond that predicted by daily temperatures. To better estimate the burden of extreme temperatures, I estimated their effects on years of life lost due to cardiovascular disease using data from Brisbane, Australia. The results showed that the association between daily mean temperature and years of life lost due to cardiovascular disease was U-shaped, with the lowest years of life lost at 24 °C (the 75th percentile of daily mean temperature in Brisbane), rising progressively as temperatures become hotter or colder. There were significant added effects of heat waves, but no added effects of cold spells. Finally, public health adaptation to hot weather is necessary and pressing. I discussed how to manage the health effects of temperature, especially with the context of climate change. Strategies to minimise the health effects of high temperatures and climate change can fall into two categories: reducing the heat exposure and managing the health effects of high temperatures. However, policy decisions need information on specific adaptations, together with their expected costs and benefits. Therefore, more research is needed to evaluate cost-effective adaptation options. In summary, this thesis adds to the large body of literature on the impacts of temperature and climate change on human health. It improves our understanding of the temperaturehealth relationship, and how this relationship will change as temperatures increase. Although the research is limited to one city, which restricts the generalisability of the findings, the methods and approaches developed in this thesis will be useful to other researchers studying temperature-health relationships and climate change impacts. The results may be helpful for decision-makers who develop public health adaptation strategies to minimise the health effects of extreme temperatures and climate change.

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Despite research that has been conducted elsewhere, little is known, to-date, about land cover dynamics and their impacts on land surface temperature (LST) in fast growing mega cities of developing countries. Landsat satellite images of 1989, 1999, and 2009 of Dhaka Metropolitan (DMP) area were used for analysis. This study first identified patterns of land cover changes between the periods and investigated their impacts on LST; second, applied artificial neural network to simulate land cover changes for 2019 and 2029; and finally, estimated their impacts on LST in respective periods. Simulation results show that if the current trend continues, 56% and 87% of the DMP area will likely to experience temperatures in the range of greater than or equal to 30°C in 2019 and 2029, respectively. The findings possess a major challenge for urban planners working in similar contexts. However, the technique presented in this paper would help them to quantify the impacts of different scenarios (e.g., vegetation loss to accommodate urban growth) on LST and consequently to devise appropriate policy measures.

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Microwave power is used for heating and drying processes because of its faster and volumetric heating capability. Non-uniform temperature distribution during microwave application is a major drawback of these processes. Intermittent application of microwave potentially reduces the impact of non-uniformity and improves energy efficiency by redistributing the temperature. However, temperature re-distribution during intermittent microwave heating has not been investigated adequately. Consequently, in this study, a coupled electromagnetic with heat and mass transfer model was developed using the finite element method embedded in COMSOL-Multyphysics software. Particularly, the temperature redistribution due to intermittent heating was investigated. A series of experiments were performed to validate the simulation. The test specimen was an apple and the temperature distribution was closely monitored by a TIC (Thermal Imaging Camera). The simulated temperature profile matched closely with thermal images obtained from experiments.

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Chemical vapor deposition (CVD) is widely utilized to synthesize graphene with controlled properties for many applications, especially when continuous films over large areas are required. Although hydrocarbons such as methane are quite efficient precursors for CVD at high temperature (∼1000 °C), finding less explosive and safer carbon sources is considered beneficial for the transition to large-scale production. In this work, we investigated the CVD growth of graphene using ethanol, which is a harmless and readily processable carbon feedstock that is expected to provide favorable kinetics. We tested a wide range of synthesis conditions (i.e., temperature, time, gas ratios), and on the basis of systematic analysis by Raman spectroscopy, we identified the optimal parameters for producing highly crystalline graphene with different numbers of layers. Our results demonstrate the importance of high temperature (1070 °C) for ethanol CVD and emphasize the significant effects that hydrogen and water vapor, coming from the thermal decomposition of ethanol, have on the crystal quality of the synthesized graphene.

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The ability to measure surface temperature and represent it on a metrically accurate 3D model has proven applications in many areas such as medical imaging, building energy auditing, and search and rescue. A system is proposed that enables this task to be performed with a handheld sensor, and for the first time with results able to be visualized and analyzed in real-time. A device comprising a thermal-infrared camera and range sensor is calibrated geometrically and used for data capture. The device is localized using a combination of ICP and video-based pose estimation from the thermal-infrared video footage which is shown to reduce the occurrence of failure modes. Furthermore, the problem of misregistration which can introduce severe distortions in assigned surface temperatures is avoided through the use of a risk-averse neighborhood weighting mechanism. Results demonstrate that the system is more stable and accurate than previous approaches, and can be used to accurately model complex objects and environments for practical tasks.

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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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Material yielding is typically modeled either by plastic zone or plastic hinge methods under the context of geometric and material nonlinear finite element methods. In fire analysis of steel structures, the plastic zone method is widely used, but it requires extensively more computational efforts. The objective of this paper is to develop the nonlinear material model allowing for interaction of both axial force and bending moment, which relies on the plastic hinge method to achieve numerical efficiency and reduce computational effort. The biggest advantage of the plastic-hinge approach is its computational efficiency and easy verification by the design code formulae of the axial force–moment interaction yield criterion for beam–column members. Further, the method is reliable and robust when used in analysis of practical and large structures. In order to allow for the effect of catenary action, axial thermal expansion is considered in the axial restraint equations. The yield function for material yielding incorporated in the stiffness formulation, which allows for both axial force and bending moment effects, is more accurate and rational to predict the behaviour of the frames under fire. In the present fire analysis, the mechanical properties at elevated temperatures follow mainly the Eurocode 3 [Design of steel structures, Part 1.2: Structural fire design. European Committee for Standisation; 2003]. Example of a tension member at a steady state heating condition is modeled to verify the proposed spring formulation and to compare with results by others. The behaviour of a heated member in a highly redundant structure is also studied by the present approach.

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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.