990 resultados para Acoustic Pressure


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This study of English Coronial practice raises a number of questions, not only regarding state investigations of suicide, but also of the role of the Coroner itself. Following observations at over 20 inquests into possible suicides, and in-depth interviews with six Coroners, three main issue emerged: first, there exists considerable slippage between different Coroners over which deaths are likely to be classified as suicide; second, the high standard of proof required, and immense pressure faced by Coroners from family members at inquest to reach any verdict other than suicide, can significantly depress likely suicide rates; and finally, Coroners feel no professional obligation, either individually or collectively, to contribute to the production of consistent and useful social data regarding suicide—arguably rendering comparative suicide statistics relatively worthless. These issues lead, ultimately, to a more important question about the role we expect Coroners to play within social governance, and within an effective, contemporary democracy.

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In situ FT-IR spectroscopy allows the methanol synthesis reaction to be investigated under actual industrial conditions of 503 K and 10 MPa. On Cu/SiO2 catalyst formate species were initially formed which were subsequently hydrogenated to methanol. During the reaction a steady state concentration of formate species persisted on the copper. Additionally, a small quantity of gaseous methane was produced. In contrast, the reaction of CO2 and H2 on ZnO/SiO2 catalyst only resulted in the formation of zinc formate species: no methanol was detected. The interaction of CO2 and H2 with Cu/ZnO/SiO2 catalyst gave formate species on both copper and zinc oxide. Methanol was again formed by the hydrogenation of copper formate species. Steady-state concentrations of copper formate existed under actual industrial reaction conditions, and copper formate is the pivotal intermediate for methanol synthesis. Collation of these results with previous data on copper-based methanol synthesis catalysts allowed the formulation of a reaction mechanism

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This thesis introduced Bayesian statistics as an analysis technique to isolate resonant frequency information in in-cylinder pressure signals taken from internal combustion engines. Applications of these techniques are relevant to engine design (performance and noise), energy conservation (fuel consumption) and alternative fuel evaluation. The use of Bayesian statistics, over traditional techniques, allowed for a more in-depth investigation into previously difficult to isolate engine parameters on a cycle-by-cycle basis. Specifically, these techniques facilitated the determination of the start of pre-mixed and diffusion combustion and for the in-cylinder temperature profile to be resolved on individual consecutive engine cycles. Dr Bodisco further showed the utility of the Bayesian analysis techniques by applying them to in-cylinder pressure signals taken from a compression ignition engine run with fumigated ethanol.

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This thesis represents a major step forward in understanding the link between the development of combustion related faults in diesel engines and the generation of acoustic emissions. The findings presented throughout the thesis provide a foundation so that future diesel engine monitoring systems are able to more effectively detect and monitor developing faults. In undertaking this research knowledge concerning engine function and relevant failure mechanisms was combined with different modelling methods to generate a framework that was used to effectively identify fault related activity within acoustic emissions recorded from different engines.

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Acoustic sensors can be used to estimate species richness for vocal species such as birds. They can continuously and passively record large volumes of data over extended periods. These data must subsequently be analyzed to detect the presence of vocal species. Automated analysis of acoustic data for large numbers of species is complex and can be subject to high levels of false positive and false negative results. Manual analysis by experienced surveyors can produce accurate results; however the time and effort required to process even small volumes of data can make manual analysis prohibitive. This study examined the use of sampling methods to reduce the cost of analyzing large volumes of acoustic sensor data, while retaining high levels of species detection accuracy. Utilizing five days of manually analyzed acoustic sensor data from four sites, we examined a range of sampling frequencies and methods including random, stratified, and biologically informed. We found that randomly selecting 120 one-minute samples from the three hours immediately following dawn over five days of recordings, detected the highest number of species. On average, this method detected 62% of total species from 120 one-minute samples, compared to 34% of total species detected from traditional area search methods. Our results demonstrate that targeted sampling methods can provide an effective means for analyzing large volumes of acoustic sensor data efficiently and accurately. Development of automated and semi-automated techniques is required to assist in analyzing large volumes of acoustic sensor data. Read More: http://www.esajournals.org/doi/abs/10.1890/12-2088.1

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A low temperature lignocellulose pretreatment process was developed using acid-catalysed mixtures of alkylene carbonate and alkylene glycol. Pretreatment of sugarcane bagasse with mixtures of ethylene carbonate (EC) and ethylene glycol (EG) was more effective than that with mixtures of propylene carbonate (PC) and propylene glycol (PG). These mixtures were more effective than the individual components in making bagasse cellulose more amenable to cellulase digestion. Glucan digestibilities of ≥87% could be achieved with a wide range of EC to EG ratios from 9:1 to 1:1 (w/w). Pretreatment of bagasse by the EC/EG mixture with a ratio of 4:1 in the presence of 1.2% H2SO4 at 90 °C for 30 min led to the highest glucan enzymatic digestibility of 93%. The high glucan digestibilities obtained under these acidic conditions were due to (a) the ability of alkylene carbonate to cause significant biomass size reduction, (b) the ability of alkylene glycol to cause biomass defibrillation, (c) the ability of alkylene carbonate and alkylene glycol to remove xylan and lignin, and (d) the magnified above attributes in the mixtures of alkylene carbonate and alkylene glycol.

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This research investigates the decision making process of individuals from revealed preferences in extreme environments or life-and-death situations, from a behavioral economics perspective. The empirical analysis of revealed behavioral preferences shows how the individual decision making process can deviate from the standard self-interested or “homo economicus” model in non-standard situations. The environments examined include: elite athletes in FIFA World and Euro Cups; climbing on Everest and the Himalaya; communication during 9/11 and risk seeking after the 2011 Brisbane floods. The results reveal that the interaction of culture and environment has a significant impact on the decision process, as social behaviors and institutions are intimately intertwined, which govern the processes of human behavior and interaction. Additionally, that risk attitudes are not set and that immediate environmental factors can induce a significant shift in an individuals risk seeking behaviors.

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Background. In isotropic materials, the speed of acoustic wave propagation is governed by the bulk modulus and density. For tendon, which is a structural composite of fluid and collagen, however, there is some anisotropy requiring an adjustment for Poisson's ratio. This paper explores these relationships using data collected, in vivo, on human Achilles tendon and then compares estimates of elastic modulus and hysteresis against published values from in vitro mechanical tests. Methods. Measurements using conventional B-model ultrasound imaging, inverse dynamics and acoustic transmission techniques were used to determine dimensions, loading conditions and longitudinal speed of sound in the Achilles tendon during a series of isometric plantar flexion exercises against body weight. Upper and lower bounds for speed of sound versus tensile stress in the tendon were then modelled and estimates of the elastic modulus and hysteresis of the Achilles tendon derived. Results. Axial speed of sound varied between 1850 and 2090 ms-1 with a non-linear, asymptotic dependency on the level of tensile stress (5-35 MPa) in the tendon. Estimates derived for the elastic modulus of the Achilles tendon ranged between 1-2 GPa. Hysteresis derived from models of the stress-strain relationship, ranged from 3-11%. Discussion. Estimates of elastic modulus agree closely with those previously reported from direct measurements obtained via mechanical tensile tests on major weight bearing tendons in vitro [1,2]. Hysteresis derived from models of the stress-strain relationship is consistent with direct measures from various mamalian tendon (7-10%) but is lower than previous estimates in human tendon (17-26%) [3]. This non-invasive method would appear suitable for monitoring changes in tendon properties during dynamic sporting activities.

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This thesis investigates condition monitoring (CM) of diesel engines using acoustic emission (AE) techniques. The AE signals recorded from a small size diesel engine are mixtures of multiple sources from multiple cylinders. Thus, it is difficult to interpret the information conveyed in the signals for CM purposes. This thesis develops a series of practical signal processing techniques to overcome this problem. Various experimental studies conducted to assess the CM capabilities of AE analysis for diesel engines. A series of modified signal processing techniques were proposed. These techniques showed promising results of capability for CM of multiple cylinders diesel engine using multiple AE sensors.

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Interpreting acoustic recordings of the natural environment is an increasingly important technique for ecologists wishing to monitor terrestrial ecosystems. Technological advances make it possible to accumulate many more recordings than can be listened to or interpreted, thereby necessitating automated assistance to identify elements in the soundscape. In this paper we examine the problem of estimating avian species richness by sampling from very long acoustic recordings. We work with data recorded under natural conditions and with all the attendant problems of undefined and unconstrained acoustic content (such as wind, rain, traffic, etc.) which can mask content of interest (in our case, bird calls). We describe 14 acoustic indices calculated at one minute resolution for the duration of a 24 hour recording. An acoustic index is a statistic that summarizes some aspect of the structure and distribution of acoustic energy and information in a recording. Some of the indices we calculate are standard (e.g. signal-to-noise ratio), some have been reported useful for the detection of bioacoustic activity (e.g. temporal and spectral entropies) and some are directed to avian sources (spectral persistence of whistles). We rank the one minute segments of a 24 hour recording in descending order according to an "acoustic richness" score which is derived from a single index or a weighted combination of two or more. We describe combinations of indices which lead to more efficient estimates of species richness than random sampling from the same recording, where efficiency is defined as total species identified for given listening effort. Using random sampling, we achieve a 53% increase in species recognized over traditional field surveys and an increase of 87% using combinations of indices to direct the sampling. We also demonstrate how combinations of the same indices can be used to detect long duration acoustic events (such as heavy rain and cicada chorus) and to construct long duration (24 h) spectrograms.

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Background: Diabetic peripheral neuropathy is an important cause of foot ulceration and limb loss. This systematic review and meta-analysis investigated the effect of diabetic peripheral neuropathy on gait, dynamic electromyography and dynamic plantar pressures. Methods: Electronic databases were searched systematically for articles reporting the effect of diabetic peripheral neuropathy on gait, dynamic electromyography and plantar pressures. Searches were restricted to articles published between January 2000 and April 2012. Outcome measures assessed included spatiotemporal parameters, lower limb kinematics, kinetics, muscle activation and plantar pressure. Meta-analyses were carried out on all outcome measures reported by ≥3 studies. Findings: Sixteen studies were included consisting of 382 neuropathy participants, 216 diabetes controls without neuropathy and 207 healthy controls. Meta-analysis was performed on 11 gait variables. A high level of heterogeneity was noted between studies. Meta-analysis results suggested a longer stance time and moderately higher plantar pressures in diabetic peripheral neuropathy patients at the rearfoot, midfoot and forefoot compared to controls. Systematic review of studies suggested potential differences in the biomechanical characteristics (kinematics, kinetics, EMG) of diabetic neuropathy patients. However these findings were inconsistent and limited by small sample sizes.; Interpretation: Current evidence suggests that patients with diabetic peripheral neuropathy have elevated plantar pressures and occupy a longer duration of time in the stance-phase during gait. Firm conclusions are hampered by the heterogeneity and small sample sizes of available studies. Interpretation: Current evidence suggests that patients with diabetic peripheral neuropathy have elevated plantar pressures and occupy a longer duration of time in the stance-phase during gait. Firm conclusions are hampered by the heterogeneity and small sample sizes of available studies.

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Objectives Actigraphy can reliably assess sleep in healthy adults and be used to estimate total sleep time in suspected obstructive sleep apnoea (OSA) patients. We compared sleep quality for Continuous Positive Air Pressure (CPAP) treated OSA patients and controls, evaluating the impact of stopping CPAP for one night. Methods 11 men, aged 51–75 years (m = 65.6 years), compliant CPAP users, treated for 1–19 years (m = 7.8 years) wore Cambridge Neurotechnology Ltd actiwatches for one night while using CPAP and for one night sleeping without CPAP. A control group of 11 healthy men, aged 63–74 years (m = 64.1 years) slept normally whilst wearing an actiwatch. Subsequent daytime sleepiness was recorded using Karolinska sleepiness scores (KSS). Results Actimetry showed no significant differences between actual sleep time, sleep efficiency, sleep disturbance index or number of wake bouts when comparing OSA participants using CPAP, with controls; there was no difference in subsequent daytime sleepiness, control KSS = 4.21, OSA KSS = 4.17. Without CPAP there was no significant difference in sleep length or sleep onset latency compared with using CPAP, but there was a significant impact on sleep quality as shown by: increased sleep disturbance index from 7.9 to 13.8 [t(10) = 3.510, P < 0.05], decreased percent of actual sleep from 92.05% to 86.15% [t(10) = 3.51, P < 0.05], decreased sleep efficiency from 86.6% to 81% [t(10) = 2.204, P < 0.05] and increased number of wake bouts from 29 to 42.5 [t(10) = 3.877, P < 0.05]. Daytime sleepiness became significantly worse increasing from KSS 4.17 to 6.27 [t(10) = )4.96, P < 0.05]. Conclusion There was no disparity in sleep quality or KSS scores between CPAP treated OSA patients and healthy controls of a similar age. Treated OSA patients obtained quality sleep with no elevated day time sleepiness. However, cessation of treatment for one night caused sleep quality to deteriorate despite a comparable sleep time; the deterioration in sleep quality could explain the increase in daytime sleepiness. OSA patients need to know that even short-term noncompliance with CPAP treatment significantly impairs sleep quality, leading to excessive sleepiness during monotonous tasks such as driving. Actigraphy successfully identified nights of non-compliance in treated OSA patients; but did not differentiate between the sleep of CPAP treated OSA patients and healthy controls.

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This workshop was supported by the Australian Centre for Ecological Analysis and Synthesis (ACEAS, http://www.aceas.org.au/), a facility of the Australian Government-funded Terrestrial Ecosystem Research Network (http://www.tern.org.au/), a research infrastructure facility established under the National Collaborative Research Infrastructure Strategy and Education Infrastructure Fund - Super Science Initiative, through the Department of Industry, Innovation, Science, Research and Tertiary Education. Hosted by: Queensland University of Technology, Brisbane, Queensland. (QUT, http://www.qut.edu.au/) Dates: 8-11 May 2012 Report Editors: Prof Stuart Parsons (Uni. Auckland, NZ) and Dr Michael Towsey (QUT). This report is a compilation of notes and discussion summaries contributed by those attending the Workshop. They have been assembled into a logical order by the editors. Another report (with photographs) can be obtained at: http://www.aceas.org.au/index.php?option=com_content&view=article&id=94&Itemid=96

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Development of design guides to estimate the difference in speech interference level due to road traffic noise between a reference position and balcony position or façade position is explored. A previously established and validated theoretical model incorporating direct, specular and diffuse reflection paths is used to create a database of results across a large number of scenarios. Nine balcony types with variable acoustic treatments are assessed to provide acoustic design guidance on optimised selection of balcony acoustic treatments based on location and street type. In total, the results database contains 9720 scenarios on which multivariate linear regression is conducted in order to derive an appropriate design guide equation. The best fit regression derived is a multivariable linear equation including modified exponential equations on each of nine deciding variables, (1) diffraction path difference, (2) ratio of total specular energy to direct energy, (3) distance loss between reference position and receiver position, (4) distance from source to balcony façade, (5) height of balcony floor above street, (6) balcony depth, (7) height of opposite buildings, (8) diffusion coefficient of buildings, and; (9) balcony average absorption. Overall, the regression correlation coefficient, R2, is 0.89 with 95% confidence standard error of ±3.4 dB.

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Acoustic recordings of the environment are an important aid to ecologists monitoring biodiversity and environmental health. However, rapid advances in recording technology, storage and computing make it possible to accumulate thousands of hours of recordings, of which, ecologists can only listen to a small fraction. The big-data challenge is to visualize the content of long-duration audio recordings on multiple scales, from hours, days, months to years. The visualization should facilitate navigation and yield ecologically meaningful information. Our approach is to extract (at one minute resolution) acoustic indices which reflect content of ecological interest. An acoustic index is a statistic that summarizes some aspect of the distribution of acoustic energy in a recording. We combine indices to produce false-colour images that reveal acoustic content and facilitate navigation through recordings that are months or even years in duration.