968 resultados para laboratory experiment
Principles in the design of multiphase experiments with a later laboratory phase: Orthogonal designs
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We conduct a field experiment on tax compliance, focusing on newly founded firms. As a novelty the effect of tax authorities’ supervision on timely tax payments is examined. Interestingly, results show no positive overall effect of close supervision on tax compliance.
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This study describes a field experiment assessing the effectiveness of education and technological innovation in reducing air pollution generated by domestic wood heaters. Two-hundred and twenty four households from a small regional center in Australia were randomly assigned to one of four experimental conditions: (1) Education only – households received a wood smoke reduction education pack containing information about the negative health impacts of wood smoke pollution, and advice about wood heater operation and firewood management; (2) SmartBurn only – households received a SmartBurn canister designed to improve combustion and help wood fires burn more efficiently, (3) Education and SmartBurn, and (4) neither Education nor SmartBurn (control). Analysis of covariance, controlling for pre-intervention household wood smoke emissions, wood moisture content, and wood heater age, revealed that education and SmartBurn were both associated with significant reduction in wood smoke emissions during the post-intervention period. Follow-up mediation analyses indicated that education reduced emissions by improving wood heater operation practices, but not by increasing health risk perceptions. As predicted, SmartBurn exerted a direct effect on emission levels, unmediated by wood heater operation practices or health risk perceptions.
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Computational neuroscience aims to elucidate the mechanisms of neural information processing and population dynamics, through a methodology of incorporating biological data into complex mathematical models. Existing simulation environments model at a particular level of detail; none allow a multi-level approach to neural modelling. Moreover, most are not engineered to produce compute-efficient solutions, an important issue because sufficient processing power is a major impediment in the field. This project aims to apply modern software engineering techniques to create a flexible high performance neural modelling environment, which will allow rigorous exploration of model parameter effects, and modelling at multiple levels of abstraction.
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Non-use values (i.e. economic values assigned by individuals to ecosystem goods and services unrelated to current or future uses) provide one of the most compelling incentives for the preservation of ecosystems and biodiversity. Assessing the non-use values of non-users is relatively straightforward using stated preference methods, but the standard approaches for estimating non-use values of users (stated decomposition) have substantial shortcomings which undermine the robustness of their results. In this paper, we propose a pragmatic interpretation of non-use values to derive estimates that capture their main dimensions, based on the identification of a willingness to pay for ecosystem protection beyond one's expected life. We empirically test our approach using a choice experiment conducted on coral reef ecosystem protection in two coastal areas in New Caledonia with different institutional, cultural, environmental and socio-economic contexts. We compute individual willingness to pay estimates, and derive individual non-use value estimates using our interpretation. We find that, a minima, estimates of non-use values may comprise between 25 and 40% of the mean willingness to pay for ecosystem preservation, less than has been found in most studies.
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This paper reports on the methodology and results of a weak-coupled aerothermalstructural analysis on the ascent phase of the SCRAMSPACE Mach 8 scramjet flight experiment. This vehicle was essentially un-shrouded during the flight trajectory, relying on the thin, 5mm thick aluminium external shell of the payload to maintain structural integrity and protect the flight experiment. As such, understanding the thermal-structural response of the vehicle was imperative to mission success. Using two- and three-dimensional models, an iterative procedure was employed to compute the flowfield, convective heating, wall temperatures and structural coupling at flight times covering both peak heating and peak surface temperature. Accounting for such coupling resulted in a 150K reduction in wall temperature compared to the more conservative cold wall assumption. Despite this, peak temperatures remained of the order of 550 K. Further, thermally induced stresses within these regions were in excess of four times the material failure limits. Irreversible material failure during ascent was therefore concluded likely to occur on the external shell. Two alternate materials, steel 1006 and copper, were therefore assessed with the results indicating that steel sections on the external shell resulted in the best thermal-structural response of the payload.
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Experimental work could be conducted in either laboratory or at field site. Generally, the laboratory experiments are carried out in an artificial setting and with a highly controlled environment. By contrast, the field experiments often take place in a natural setting, subject to the influences of many uncontrolled factors. Therefore, it is necessary to carefully assess the possible limitations and appropriateness of an experiment before embarking on it. In this paper, a case study of field monitoring of the energy performance of air conditioners is presented. Significant challenges facing the experimental work are described. Lessons learnt from this case study are also discussed. In particular, it was found that on-going analysis of the monitoring data and the correction of abnormal issues are two of the keys for a successful field test program. It was also shown that the installation of monitoring systems could have a significant impact on the accuracy of the data being collected. Before monitoring system was set up to collect monitoring data, it is recommended that an initial analysis of sample monitored data should be conducted to make sure that the monitoring data can achieve the expected precision. In the case where inevitable inherent errors were induced from the installation of field monitoring systems, appropriate remediation may need to be developed and implemented for the improved accuracy of the estimation of results. On-going analysis of monitoring data and correction of any abnormal issues would be the key to a successful field test program.
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We’re starting 2015 with an experiment in collaborative creative writing. What happens when you ask ten academics to write a story together? Taking our cue from the Exquisite Cadaver game played by Surrealist artists and poets in the 1930s, we’ve asked our authors to contribute to a story in progress. We gave them free rein: no restrictions on style or genre.
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Many researchers in the field of civil structural health monitoring (SHM) have developed and tested their methods on simple to moderately complex laboratory structures such as beams, plates, frames, and trusses. Fieldwork has also been conducted by many researchers and practitioners on more complex operating bridges. Most laboratory structures do not adequately replicate the complexity of truss bridges. Informed by a brief review of the literature, this paper documents the design and proposed test plan of a structurally complex laboratory bridge model that has been specifically designed for the purpose of SHM research. Preliminary results have been presented in the companion paper.
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Pilot and industrial scale dilute acid pretreatment data can be difficult to obtain due to the significant infrastructure investment required. Consequently, models of dilute acid pretreatment by necessity use laboratory scale data to determine kinetic parameters and make predictions about optimal pretreatment conditions at larger scales. In order for these recommendations to be meaningful, the ability of laboratory scale models to predict pilot and industrial scale yields must be investigated. A mathematical model of the dilute acid pretreatment of sugarcane bagasse has previously been developed by the authors. This model was able to successfully reproduce the experimental yields of xylose and short chain xylooligomers obtained at the laboratory scale. In this paper, the ability of the model to reproduce pilot scale yield and composition data is examined. It was found that in general the model over predicted the pilot scale reactor yields by a significant margin. Models that appear very promising at the laboratory scale may have limitations when predicting yields on a pilot or industrial scale. It is difficult to comment whether there are any consistent trends in optimal operating conditions between reactor scale and laboratory scale hydrolysis due to the limited reactor datasets available. Further investigation is needed to determine whether the model has some efficacy when the kinetic parameters are re-evaluated by parameter fitting to reactor scale data, however, this requires the compilation of larger datasets. Alternatively, laboratory scale mathematical models may have enhanced utility for predicting larger scale reactor performance if bulk mass transport and fluid flow considerations are incorporated into the fibre scale equations. This work reinforces the need for appropriate attention to be paid to pilot scale experimental development when moving from laboratory to pilot and industrial scales for new technologies.