160 resultados para Barium, biogenic rain rate
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This study evaluated the physiological tolerance times when wearing explosive and chemical (>35kg) personal protective equipment (PPE) in simulated environmental extremes across a range of differing work intensities. Twelve healthy males undertook nine trials which involved walking on a treadmill at 2.5, 4 and 5.5 km.h-1 in the following environmental conditions, 21, 30 and 37 °C wet bulb globe temperature (WBGT). Participants exercised for 60 min or until volitional fatigue, core temperature reached 39 °C, or heart rate exceeded 90% of maximum. Tolerance time, core temperature, skin temperature, mean body temperature, heart rate and body mass loss were measured. Exercise time was reduced in the higher WBGT environments (WBGT37
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The ambiguity acceptance test is an important quality control procedure in high precision GNSS data processing. Although the ambiguity acceptance test methods have been extensively investigated, its threshold determine method is still not well understood. Currently, the threshold is determined with the empirical approach or the fixed failure rate (FF-) approach. The empirical approach is simple but lacking in theoretical basis, while the FF-approach is theoretical rigorous but computationally demanding. Hence, the key of the threshold determination problem is how to efficiently determine the threshold in a reasonable way. In this study, a new threshold determination method named threshold function method is proposed to reduce the complexity of the FF-approach. The threshold function method simplifies the FF-approach by a modeling procedure and an approximation procedure. The modeling procedure uses a rational function model to describe the relationship between the FF-difference test threshold and the integer least-squares (ILS) success rate. The approximation procedure replaces the ILS success rate with the easy-to-calculate integer bootstrapping (IB) success rate. Corresponding modeling error and approximation error are analysed with simulation data to avoid nuisance biases and unrealistic stochastic model impact. The results indicate the proposed method can greatly simplify the FF-approach without introducing significant modeling error. The threshold function method makes the fixed failure rate threshold determination method feasible for real-time applications.
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Ambiguity validation as an important procedure of integer ambiguity resolution is to test the correctness of the fixed integer ambiguity of phase measurements before being used for positioning computation. Most existing investigations on ambiguity validation focus on test statistic. How to determine the threshold more reasonably is less understood, although it is one of the most important topics in ambiguity validation. Currently, there are two threshold determination methods in the ambiguity validation procedure: the empirical approach and the fixed failure rate (FF-) approach. The empirical approach is simple but lacks of theoretical basis. The fixed failure rate approach has a rigorous probability theory basis, but it employs a more complicated procedure. This paper focuses on how to determine the threshold easily and reasonably. Both FF-ratio test and FF-difference test are investigated in this research and the extensive simulation results show that the FF-difference test can achieve comparable or even better performance than the well-known FF-ratio test. Another benefit of adopting the FF-difference test is that its threshold can be expressed as a function of integer least-squares (ILS) success rate with specified failure rate tolerance. Thus, a new threshold determination method named threshold function for the FF-difference test is proposed. The threshold function method preserves the fixed failure rate characteristic and is also easy-to-apply. The performance of the threshold function is validated with simulated data. The validation results show that with the threshold function method, the impact of the modelling error on the failure rate is less than 0.08%. Overall, the threshold function for the FF-difference test is a very promising threshold validation method and it makes the FF-approach applicable for the real-time GNSS positioning applications.
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Grateful Fateful Sunshine Rain is a permanent public artwork commissioned by Aria Property Group through a competitive process for the Austin apartment building in South Brisbane. Artist Statement: Residents of Brisbane have a complex relationship with weather. As the capital of the Sunshine State, weather is an integral part of the city’s cultural identity. Weather deeply affects the mood of the city – from the excitement of scantily clad partygoers on balmy December evenings and late February’s lethargy, to the deepening anxiety that emerges after 100 days of rain (or more commonly, 100 days without rain). With a brief nod to the city’s – now decommissioned – iconic MCL weather beacon, Grateful Fateful Sunshine Rain taps into this aspect of Brisbane’s psyche with poetic, illuminated visualisations of real-time weather forecasts issued by the Bureau of Meteorology. Each evening, the artwork downloads tomorrow’s forecast from the Bureau of Meteorology website. Data including, current local temperature, humidity, wind speed & direction, precipitation (rain, hail etc), are used to generate a lighting display that conveys how tomorrow will feel. The artwork’s background colour indicates the expected temperature – from cold blues through mild pastel pinks and blues to bright hot oranges and reds. White fluffy clouds roll across the artwork if cloud is predicted. The density of these clouds indicates the level of cover whilst movement indicates expected wind speed and direction. If rain is predicted, sparkles of white light will appear on top of whichever background colour is chosen for the next day’s temperature. Sparkles appear constantly before wet, drizzly days, and intermittently if scattered showers are predicted. Intermittent, but more intense sparkles appear before rain storms or thunderstorms. Research Contribution: The work has made contributions to the field in the way it rethinks approaches to the conceptualization, design and realization of illuminated urban media. This has led to new theorizations of urban media, which consider light and illumination can be used to convey meaningful data. The research has produced new methods for controlling illumination systems using tools and techniques typically employed in computation arts. It has also develop methods and processes for the design and production of illuminated urban media architectures that are connected to real time data sources, and do which not follow the assumed logics of screen based media and displays.
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Nb2O5 nanosheets are successfully synthesized through a facile hydrothermal reaction and followed heating treatment in air. The structural characterization reveals that the thickness of these sheets is around 50 nm and the length of sheets is 500~800 nm. Such a unique two dimensional structure enables the nanosheet electrode with superior performance during the charge-discharge process, such as high specific capacity (~184 mAh.g-1) and rate capability. Even at a current density of 1 A.g-1, the nanosheet electrode still exhibits a specific capacity of ~90 mAh.g-1. These results suggest the Nb2O5 nanosheet is a promising candidate for high-rate lithium ion storage applications.
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Most standard algorithms for prediction with expert advice depend on a parameter called the learning rate. This learning rate needs to be large enough to fit the data well, but small enough to prevent overfitting. For the exponential weights algorithm, a sequence of prior work has established theoretical guarantees for higher and higher data-dependent tunings of the learning rate, which allow for increasingly aggressive learning. But in practice such theoretical tunings often still perform worse (as measured by their regret) than ad hoc tuning with an even higher learning rate. To close the gap between theory and practice we introduce an approach to learn the learning rate. Up to a factor that is at most (poly)logarithmic in the number of experts and the inverse of the learning rate, our method performs as well as if we would know the empirically best learning rate from a large range that includes both conservative small values and values that are much higher than those for which formal guarantees were previously available. Our method employs a grid of learning rates, yet runs in linear time regardless of the size of the grid.
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Viewer interests, evoked by video content, can potentially identify the highlights of the video. This paper explores the use of facial expressions (FE) and heart rate (HR) of viewers captured using camera and non-strapped sensor for identifying interesting video segments. The data from ten subjects with three videos showed that these signals are viewer dependent and not synchronized with the video contents. To address this issue, new algorithms are proposed to effectively combine FE and HR signals for identifying the time when viewer interest is potentially high. The results show that, compared with subjective annotation and match report highlights, ‘non-neutral’ FE and ‘relatively higher and faster’ HR is able to capture 60%-80% of goal, foul, and shot-on-goal soccer video events. FE is found to be more indicative than HR of viewer’s interests, but the fusion of these two modalities outperforms each of them.
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The objective of this project is to investigate the strain-rate dependent mechanical behaviour of single living cells using both experimental and numerical techniques. The results revealed that living cells behave as porohyperlastic materials and that both solid and fluid phases within the cells play important roles in their mechanical responses. The research reported in this thesis provides a better understanding of the mechanisms underlying the cellular responses to external mechanical loadings and of the process of mechanical signal transduction in living cells. It would help us to enhance knowledge of and insight into the role of mechanical forces in supporting tissue regeneration or degeneration.
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This thesis is concerned with the detection and prediction of rain in environmental recordings using different machine learning algorithms. The results obtained in this research will help ecologists to efficiently analyse environmental data and monitor biodiversity.
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Background From the conservative estimates of registrants with the National Diabetes Supply Scheme, we will be soon passing 1.1 Million Australians affected by all types of diabetes. The diabetes complications of foot ulceration and amputation are costly to all. These costs can be reduced with appropriate prevention strategies, starting with identifying people at risk through primary care diabetic foot screening. However, levels of diabetic foot screening in Australia are difficult to quantify. Methods This presentation reports on foot screening rates as recorded in the academic literature, national health surveys and national database reports. The focus is on type 1 and type 2 diabetes in adults, and not gestational diabetes or children. Literature searches included diabetic foot screening that occurred in the primary care setting for populations over 2000 people from 2002 to 2014. Searches were performed using Medline and CINAHL as well as internet searches of OECD health databases. The primary outcome measure was foot -screening rates as a percentage of adult diabetic population. Results The lack of a national diabetes database and register hampers efforts to analyse diabetic foot screening levels. The most recent and accurate level for Australian population review was in the AUSDIAB (Australian Diabetes and lifestyle survey) from 2004. This survey reported screening in primary care to be as low as 50%. Countries such as the United Kingdom and United States of America report much higher rates of foot screening (67-88%) using national databases and web based initiatives that involve patients and clinicians. Conclusions Australian rates of diabetic foot screening in primary care centres is ambiguous. Uptake of national registers, incentives and web based systems improve levels of diabetic foot assessment which are the first steps to a healthier diabetic population.
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Introduction: Exposure to bioaerosols in indoor environments has been linked to various adverse health effects, such as airway disorders and upper respiratory tract symptoms. The aim of this study was to assess exposure to bioaerosols in the school environment in Brisbane, Australia. Methods: Culturable fungi and endotoxin measurements were conducted in six schools between October 2010 and May 2011. Culturable fungi (2 indoor air and 1-2 outdoor air samples per school) were assessed using a Biotest RCS High Flow Air Sampler, with a flow rate of either 50L/min or 20L/min. A rose pengar agar was used for recovery, which was incubated prior to counting and partial identification. Endotoxins were sampled (8h, 2L/min) using SKC glass fibre filters (4 indoor air samples per school) and analysed using an endpoint chromogenic LAL assay. Results: The arithmetic mean for fungi concentration in indoor and outdoor air was 710 cfu/m3(125- 1900 cfu/m3) and 524 cfu/m3 (140-1250 cfu/m3), respectively. The most frequently isolated fungal genus from the outdoor air was Cladosporium (over 40 %), followed by isolated Penicillium (21%) and Aspergillus (12%). The percent of Penicillium, Cladosporium and Aspergillus in indoor air samples was 32%, 32% and 8%, respectively. The aritmetic mean of endotoxin concentration was 0.59 EU/m3 (0-2,2 EU/m3). Discussion: The results of the current study are in agreement with previously reported studies, in that airborne fungi and endotoxin concentrations varied extensively, and were mostly dependent on climatic conditions. In addition, the indoor air mycoflora largely reflected the fungal flora present in the outdoor air, with Cladosporium being the most common in both outdoor and indoor (with Penicillium) air. In indoor air, unusually high endotoxin levels, over 1 EU/m3, were detected at 2 schools. Although these schools were not affected by the recent Brisbane floods, persistent rain prior to and during the study perios could explain the results.
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With the advent of functional neuroimaging techniques, in particular functional magnetic resonance imaging (fMRI), we have gained greater insight into the neural correlates of visuospatial function. However, it may not always be easy to identify the cerebral regions most specifically associated with performance on a given task. One approach is to examine the quantitative relationships between regional activation and behavioral performance measures. In the present study, we investigated the functional neuroanatomy of two different visuospatial processing tasks, judgement of line orientation and mental rotation. Twenty-four normal participants were scanned with fMRI using blocked periodic designs for experimental task presentation. Accuracy and reaction time (RT) to each trial of both activation and baseline conditions in each experiment was recorded. Both experiments activated dorsal and ventral visual cortical areas as well as dorsolateral prefrontal cortex. More regionally specific associations with task performance were identified by estimating the association between (sinusoidal) power of functional response and mean RT to the activation condition; a permutation test based on spatial statistics was used for inference. There was significant behavioral-physiological association in right ventral extrastriate cortex for the line orientation task and in bilateral (predominantly right) superior parietal lobule for the mental rotation task. Comparable associations were not found between power of response and RT to the baseline conditions of the tasks. These data suggest that one region in a neurocognitive network may be most strongly associated with behavioral performance and this may be regarded as the computationally least efficient or rate-limiting node of the network.
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The Lagrangian particle tracking provides an effective method for simulating the deposition of nano- particles as well as micro-particles as it accounts for the particle inertia effect as well as the Brownian excitation. However, using the Lagrangian approach for simulating ultrafine particles has been limited due to computational cost and numerical difficulties. The aim of this paper is to study the deposition of nano-particles in cylindrical tubes under laminar condition using the Lagrangian particle tracking method. The commercial Fluent software is used to simulate the fluid flow in the pipes and to study the deposition and dispersion of nano-particles. Different particle diameters as well as different pipe lengths and flow rates are examined. The results show good agreement between the calculated deposition efficiency and different analytic correlations in the literature. Furthermore, for the nano-particles with higher diameters and when the effect of inertia has a higher importance, the calculated deposition efficiency by the Lagrangian method is less than the analytic correlations based on Eulerian method due to statistical error or the inertia effect.