981 resultados para Gas measurement
Resumo:
This study examined the potential for Fe mobilization and greenhouse gas (GHG, e.g. CO2, and CH4) evolution in SEQ soils associated with a range of plantation forestry practices and water-logged conditions. Intact, 30-cm-deep soil cores collected from representative sites were saturated and incubated for 35 days in the laboratory, with leachate and headspace gas samples periodically collected. Minimal Fe dissolution was observed in well-drained sand soils associated with mature, first-rotation Pinus and organic Fe complexation, whereas progressive Fe dissolution occurred over 14 days in clear-felled and replanted Pinus soils with low organic matter and non-crystalline Fe fractions. Both CO2 and CH4 effluxes were relatively lower in clear-felled and replanted soils compared with mature, first-rotation Pinus soils, despite the lack of statistically significant variations in total GHG effluxes associated with different forestry practices. Fe dissolution and GHG evolution in low-lying, water-logged soils adjacent to riparian and estuarine, native-vegetation buffer zones were impacted by mineral and physical soil properties. Highest levels of dissolved Fe and GHG effluxes resulted from saturation of riparian loam soils with high Fe and clay content, as well as abundant organic material and Fe-metabolizing bacteria. Results indicate Pinus forestry practices such as clear-felling and replanting may elevate Fe mobilization while decreasing CO2 and CH4 emissions from well-drained, SEQ plantation soils upon heavy flooding. Prolonged water-logging accelerates bacterially mediated Fe cycling in low-lying, clay-rich soils, leading to substantial Fe dissolution, organic matter mineralization, and CH4 production in riparian native-vegetation buffer zones.
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Background: The accurate evaluation of physical activity levels amongst youth is critical for quantifying physical activity behaviors and evaluating the effect of physical activity interventions. The purpose of this review is to evaluate contemporary approaches to physical activity evaluation amongst youth. Data sources: The literature from a range of sources was reviewed and synthesized to provide an overview of contemporary approaches for measuring youth physical activity. Results: Five broad categories are described: self-report, instrumental movement detection, biological approaches, direct observation, and combined methods. Emerging technologies and priorities for future research are also identified. Conclusions: There will always be a trade-off between accuracy and available resources when choosing the best approach for measuring physical activity amongst youth. Unfortunately, cost and logistical challenges may prohibit the use of "gold standard" physical activity measurement approaches such as doubly labelled water. Other objective methods such as heart rate monitoring, accelerometry, pedometry, indirect calorimetry, or a combination of measures have the potential to better capture the duration and intensity of physical activity, while self-reported measures are useful for capturing the type and context of activity.
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Differences in the NMR detectability of 39K in various excised rat tissues (liver, brain, kidney, muscle, and testes) have been observed. The lowest NMR detectability occurs for liver (61 ± 3% of potassium as measured by flame photometry) and highest for erythrocytes (100 ± 7%). These differences in detectability correlate with differences in the measured 39K NMR relaxation constants in the same tissues. 39K detectabilities were also found to correlate inversely with the mitochondrial content of the tissues. Mitochondria prepared from liver showed greatly reduced 39K NMR detectability when compared with the tissue from which it was derived, 31.6 ± 9% of potassium measured by flame photometry compared to 61 ± 3%. The detectability of potassium in mitochondria was too low to enable the measurement of relaxation constants. This study indicates that differences in tissue structure, particularly mitochondrial content are important in determining 39K detectability and measured relaxation rates.
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The Kyoto Protocol recognises trees as a sink of carbon and a valid means to offset greenhouse gas emissions and meet internationally agreed emissions targets. This study details biological carbon sequestration rates for common plantation species Araucaria cunninghamii (hoop pine), Eucalyptus cloeziana, Eucalyptus argophloia, Pinus elliottii and Pinus caribaea var hondurensis and individual land areas required in north-eastern Australia to offset greenhouse gas emissions of 1000tCO 2e. The 3PG simulation model was used to predict above and below-ground estimates of biomass carbon for a range of soil productivity conditions for six representative locations in agricultural regions of north-eastern Australia. The total area required to offset 1000tCO 2e ranges from 1ha of E. cloeziana under high productivity conditions in coastal North Queensland to 45ha of hoop pine in low productivity conditions of inland Central Queensland. These areas must remain planted for a minimum of 30years to meet the offset of 1000tCO 2e.
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This work focuses on the development of a stand-alone gas nanosensor node, powered by solar energy to track concentration of polluted gases such as NO2, N2O, and NH3. Gas sensor networks have been widely developed over recent years, but the rise of nanotechnology is allowing the creation of a new range of gas sensors [1] with higher performance, smaller size and an inexpensive manufacturing process. This work has created a gas nanosensor node prototype to evaluate future field performance of this new generation of sensors. The sensor node has four main parts: (i) solar cells; (ii) control electronics; (iii) gas sensor and sensor board interface [2-4]; and (iv) data transmission. The station is remotely monitored through wired (ethernet cable) or wireless connection (radio transmitter) [5, 6] in order to evaluate, in real time, the performance of the solar cells and sensor node under different weather conditions. The energy source of the node is a module of polycrystalline silicon solar cells with 410cm2 of active surface. The prototype is equipped with a Resistance-To-Period circuit [2-4] to measure the wide range of resistances (KΩ to GΩ) from the sensor in a simple and accurate way. The system shows high performance on (i) managing the energy from the solar panel, (ii) powering the system load and (iii) recharging the battery. The results show that the prototype is suitable to work with any kind of resistive gas nanosensor and provide useful data for future nanosensor networks.
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Data quality has become a major concern for organisations. The rapid growth in the size and technology of a databases and data warehouses has brought significant advantages in accessing, storing, and retrieving information. At the same time, great challenges arise with rapid data throughput and heterogeneous accesses in terms of maintaining high data quality. Yet, despite the importance of data quality, literature has usually condensed data quality into detecting and correcting poor data such as outliers, incomplete or inaccurate values. As a result, organisations are unable to efficiently and effectively assess data quality. Having an accurate and proper data quality assessment method will enable users to benchmark their systems and monitor their improvement. This paper introduces a granules mining for measuring the random degree of error data which will enable decision makers to conduct accurate quality assessment and allocate the most severe data, thereby providing an accurate estimation of human and financial resources for conducting quality improvement tasks.
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The world is facing problems due to the effects of increased atmospheric pollution, climate change and global warming. Innovative technologies to identify, quantify and assess fluxes exchange of the pollutant gases between the Earth’s surface and atmosphere are required. This paper proposes the development of a gas sensor system for a small UAV to monitor pollutant gases, collect data and geo-locate where the sample was taken. The prototype has two principal systems: a light portable gas sensor and an optional electric–solar powered UAV. The prototype will be suitable to: operate in the lower troposphere (100-500m); collect samples; stamp time and geo-locate each sample. One of the limitations of a small UAV is the limited power available therefore a small and low power consumption payload is designed and built for this research. The specific gases targeted in this research are NO2, mostly produce by traffic, and NH3 from farming, with concentrations above 0.05 ppm and 35 ppm respectively which are harmful to human health. The developed prototype will be a useful tool for scientists to analyse the behaviour and tendencies of pollutant gases producing more realistic models of them.
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Introduction Electrical impedance tomography (EIT) has been shown to be able to distinguish both ventilation and perfusion. With adequate filtering the regional distributions of both ventilation and perfusion and their relationships could be analysed. Several methods of separation have been suggested previously, including breath holding, electrocardiograph (ECG) gating and frequency filtering. Many of these methods require interventions inappropriate in a clinical setting. This study therefore aims to extend a previously reported frequency filtering technique to a spontaneously breathing cohort and assess the regional distributions of ventilation and perfusion and their relationship. Methods Ten healthy adults were measured during a breath hold and while spontaneously breathing in supine, prone, left and right lateral positions. EIT data were analysed with and without filtering at the respiratory and heart rate. Profiles of ventilation, perfusion and ventilation/perfusion related impedance change were generated and regions of ventilation and pulmonary perfusion were identified and compared. Results Analysis of the filtration technique demonstrated its ability to separate the ventilation and cardiac related impedance signals without negative impact. It was, therefore, deemed suitable for use in this spontaneously breathing cohort. Regional distributions of ventilation, perfusion and the combined ΔZV/ΔZQ were calculated along the gravity axis and anatomically in each position. Along the gravity axis, gravity dependence was seen only in the lateral positions in ventilation distribution, with the dependent lung being better ventilated regardless of position. This gravity dependence was not seen in perfusion. When looking anatomically, differences were only apparent in the lateral positions. The lateral position ventilation distributions showed a difference in the left lung, with the right lung maintaining a similar distribution in both lateral positions. This is likely caused by more pronounced anatomical changes in the left lung when changing positions. Conclusions The modified filtration technique was demonstrated to be effective in separating the ventilation and perfusion signals in spontaneously breathing subjects. Gravity dependence was seen only in ventilation distribution in the left lung in lateral positions, suggesting gravity based shifts in anatomical structures. Gravity dependence was not seen in any perfusion distributions.
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Business process management (BPM) is becoming the dominant management paradigm. Business process modelling is central to BPM, and the resultant business process model the core artefact guiding subsequent process change. Thus, model quality is at the centre, mediating between the modelling effort and related growing investment in ultimate process improvements. Nonetheless, though research interest in the properties that differentiate high quality process models is longstanding, there have been no past reports of a valid, operationalised, holistic measure of business process model quality. In attention to this gap, this paper reports validation of a Business Process Model Quality measurement model, conceptualised as a single-order, formative index. Such a measurement model has value as the dependent variable in rigorously researching the drivers of model quality; as antecedent of ultimate process improvements; and potentially as an economical comparator and diagnostic for practice.
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Background. Vertebral rotation found in structural scoliosis contributes to trunkal asymmetry which is commonly measured with a simple Scoliometer device on a patient's thorax in the forward flexed position. The new generation of mobile 'smartphones' have an integrated accelerometer, making accurate angle measurement possible, which provides a potentially useful clinical tool for assessing rib hump deformity. This study aimed to compare rib hump angle measurements performed using a Smartphone and traditional Scoliometer on a set of plaster torsos representing the range of torsional deformities seen in clinical practice. Methods. Nine observers measured the rib hump found on eight plaster torsos moulded from scoliosis patients with both a Scoliometer and an Apple iPhone on separate occasions. Each observer repeated the measurements at least a week after the original measurements, and were blinded to previous results. Intra-observer reliability and inter-observer reliability were analysed using the method of Bland and Altman and 95% confidence intervals were calculated. The Intra-Class Correlation Coefficients (ICC) were calculated for repeated measurements of each of the eight plaster torso moulds by the nine observers. Results. Mean absolute difference between pairs of iPhone/Scoliometer measurements was 2.1 degrees, with a small (1 degrees) bias toward higher rib hump angles with the iPhone. 95% confidence intervals for intra-observer variability were +/- 1.8 degrees (Scoliometer) and +/- 3.2 degrees (iPhone). 95% confidence intervals for inter-observer variability were +/- 4.9 degrees (iPhone) and +/- 3.8 degrees (Scoliometer). The measurement errors and confidence intervals found were similar to or better than the range of previously published thoracic rib hump measurement studies. Conclusions. The iPhone is a clinically equivalent rib hump measurement tool to the Scoliometer in spinal deformity patients. The novel use of plaster torsos as rib hump models avoids the variables of patient fatigue and discomfort, inconsistent positioning and deformity progression using human subjects in a single or multiple measurement sessions.
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The present study considered factors influencing teachers' reporting of child sexual abuse (CSA). Conducted in three Australian jurisdictions with different reporting laws and policies, the study focused on teachers' actual past and anticipated future reporting of CSA. A sample of 470 teachers within randomly selected rural and urban schools was surveyed, to identify training and experience; knowledge of reporting legislation and policy; attitudes; and reporting practices. Factors influencing actual past reporting and anticipated future reporting were identified using logistic regression modelling. This is the first study to simultaneously examine the effect of important influences in reporting practice using both retrospective and prospective approaches across jurisdictions with different reporting laws. Teachers who have actually reported CSA in the past are more likely have higher levels of policy knowledge, and hold more positive attitudes towards reporting CSA along three specific dimensions: commitment to the reporting role; confidence in the system's effective response to their reporting; and they are more likely to be able to override their concerns about the consequences of their reporting. Teachers indicating intention to report hypothetical scenarios are more likely to hold reasonable grounds for suspecting CSA, to recognise that significant harm has been caused to the child, to know that their school policy requires a report, and to be able to override their concerns about the consequences of their reporting.