142 resultados para Acoustic stimulation


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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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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.

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Compromised angiogenesis appears to be a major limitation in various suboptimal bone healing situations. Appropriate mechanical stimuli support blood vessel formation in vivo and improve healing outcomes. However, the mechanisms responsible for this association are unclear. To address this question, the paracrine angiogenic potential of early human fracture haematoma and its responsiveness to mechanical loading, as well as angiogenic growth factors involved, were investigated in vitro. Human haematomas were collected from healthy patients undergoing surgery within 72. h after bone fracture. The haematomas were embedded in a fibrin matrix, and cultured in a bioreactor resembling the in vivo conditions of the early phase of bone healing (20 compression, 1. Hz) over 3. days. Conditioned medium (CM) from the bioreactor was then analyzed. The matrices were also incubated in fresh medium for a further 24. h to evaluate the persistence of the effects. Growth factor (GF) concentrations were measured in the CM by ELISAs. In vitro tube formation assays were conducted on Matrigel with the HMEC-1 cell line, with or without inhibition of vascular endothelial growth factor receptor 2 (VEGFR2). Cell numbers were quantified using an MTS test. In vitro endothelial tube formation was enhanced by CM from haematomas, compared to fibrin controls. The angiogenesis regulators, vascular endothelial growth factor (VEGF) and transforming growth factor β1 (TGF-β1), were released into the haematoma CM, but not angiopoietins 1 or 2 (Ang1, 2), basic fibroblast growth factor (bFGF) or platelet-derived growth factor (PDGF). Mechanical stimulation of haematomas, but not fibrin controls, further increased the induction of tube formation by their CM. The mechanically stimulated haematoma matrices retained their elevated pro-angiogenic capacity for 24. h. The pro-angiogenic effect was cancelled by inhibition of VEGFR2 signalling. VEGF concentrations in CM tended to be elevated by mechanical stimulation; this was significant in haematomas from younger, but not from older patients. Other GFs were not mechanically regulated. In conclusion, the paracrine pro-angiogenic capacity of early human haematomas is enhanced by mechanical stimulation. This effect lasts even after removing the mechanical stimulus and appears to be VEGFR2-dependent.

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Low speed rotating machines which are the most critical components in drive train of wind turbines are often menaced by several technical and environmental defects. These factors contribute to mount the economic requirement for Health Monitoring and Condition Monitoring of the systems. When a defect is happened in such system result in reduced energy loss rates from related process and due to it Condition Monitoring techniques that detecting energy loss are very difficult if not possible to use. However, in the case of Acoustic Emission (AE) technique this issue is partly overcome and is well suited for detecting very small energy release rates. Acoustic Emission (AE) as a technique is more than 50 years old and in this new technology the sounds associated with the failure of materials were detected. Acoustic wave is a non-stationary signal which can discover elastic stress waves in a failure component, capable of online monitoring, and is very sensitive to the fault diagnosis. In this paper the history and background of discovering and developing AE is discussed, different ages of developing AE which include Age of Enlightenment (1950-1967), Golden Age of AE (1967-1980), Period of Transition (1980-Present). In the next section the application of AE condition monitoring in machinery process and various systems that applied AE technique in their health monitoring is discussed. In the end an experimental result is proposed by QUT test rig which an outer race bearing fault was simulated to depict the sensitivity of AE for detecting incipient faults in low speed high frequency machine.

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Covertly tracking mobile targets, either animal or human, in previously unmapped outdoor natural environments using off-road robotic platforms requires both visual and acoustic stealth. Whilst the use of robots for stealthy surveillance is not new, the majority only consider navigation for visual covertness. However, most fielded robotic systems have a non-negligible acoustic footprint arising from the onboard sensors, motors, computers and cooling systems, and also from the wheels interacting with the terrain during motion. This time-varying acoustic signature can jeopardise any visual covertness and needs to be addressed in any stealthy navigation strategy. In previous work, we addressed the initial concepts for acoustically masking a tracking robot’s movements as it travels between observation locations selected to minimise its detectability by a dynamic natural target and ensuring con- tinuous visual tracking of the target. This work extends the overall concept by examining the utility of real-time acoustic signature self-assessment and exploiting shadows as hiding locations for use in a combined visual and acoustic stealth framework.

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This work is motivated by the desire to covertly track mobile targets, either animal or human, in previously unmapped outdoor natural environments using off-road robotic platforms with a non-negligible acoustic signature. The use of robots for stealthy surveillance is not new. Many studies exist but only consider the navigation problem to maintain visual covertness. However, robotic systems also have a significant acoustic footprint from the onboard sensors, motors, computers and cooling systems, and also from the wheels interacting with the terrain during motion. All these can jepordise any visual covertness. In this work, we experimentally explore the concepts of opportunistically utilizing naturally occurring sounds within outdoor environments to mask the motion of a robot, and being visually covert whilst maintaining constant observation of the target. Our experiments in a constrained outdoor built environment demonstrate the effectiveness of the concept by showing a reduced acoustic signature as perceived by a mobile target allowing the robot to covertly navigate to opportunistic vantage points for observation.

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Aims and objectives.  This study was undertaken to measure and analyse levels of acoustic noise in a General Surgical Ward. Method.  Measurements were undertaken using the Norsonic 116 sound level meter (SLM) recording noise levels in the internationally agreed ‘A’ weighted scale. Noise level data and observational data as to the number of staff present were obtained and recorded at 5-min intervals over three consecutive days. Results.  Results of noise level analysis indicated that mean noise level within this clinical area was 42.28 dB with acute spikes reaching 70 dB(A). The lowest noise level attained was that of 36 dB(A) during the period midnight to 7 a.m. Non-parametric testing, using Spearman's Rho (two-tailed), found a positive relationship between the number of staff present and the level of noise recorded, indicating that the presence of hospital personnel strongly influences the level of noise within this area. Relevance to clinical practice.  Whilst the results of this may seem self-evident in many respects the problems of excessive noise production and the exposure to it for patients, hospital personnel and relatives alike continues unabated. What must be of concern is the psychophysiological effects excessive noise exposure has on individuals, for example, decreased wound healing, sleep deprivation and cardiovascular stimulation.

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Guitar technology underwent significant changes in the 20th century in the move from acoustic to electric instruments. In the first part of the 21st century, the guitar continues to develop through its interaction with digital technologies. Such changes in guitar technology are usually grounded in what we might call the "cultural identity" of the instrument: that is, the various ways that the guitar is used to enact, influence and challenge sociocultural and musical discourses. Often, these different uses of the guitar can be seen to reflect a conflict between the changing concepts of "noise" and "musical sound."

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Polymer biomaterials have been widely used for bone replacement/regeneration because of their unique mechanical properties and workability. Their inherent low bioactivity makes them lack osseointegration with host bone tissue. For this reason, bioactive inorganic particles have been always incorporated into the matrix of polymers to improve their bioactivity. However, mixing inorganic particles with polymers always results in inhomogeneity of particle distribution in polymer matrix with limited bioactivity. This study sets out to apply the pulsed laser deposition (PLD) technique to prepare uniform akermanite (Ca2MgSi2O7, AKT) glass nanocoatings on the surface of two polymers (non-degradable polysulfone (PSU) and degradable polylactic acid (PDLLA)) in order to improve their surface osteogenic and angiogenic activity. The results show that a uniform nanolayer composed of amorphous AKT particles (∼30nm) of thickness 130nm forms on the surface of both PSU and PDLLA films with the PLD technique. The prepared AKT-PSU and AKT-PDLLA films significantly improved the surface roughness, hydrophilicity, hardness and apatite mineralization, compared with pure PSU and PDLLA, respectively. The prepared AKT nanocoatings distinctively enhance the alkaline phosphate (ALP) activity and bone-related gene expression (ALP, OCN, OPN and Col I) of bone-forming cells on both PSU and PDLLA films. Furthermore, AKT nanocoatings on two polymers improve the attachment, proliferation, VEGF secretion and expression of proangiogenic factors and their receptors of human umbilical vein endothelial cells (HUVEC). The results suggest that PLD-prepared bioceramic nanocoatings are very useful for enhancing the physicochemical, osteogenic and angiogenic properties of both degradable and non-degradable polymers for application in bone replacement/regeneration.

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This study presents an acoustic emission (AE) based fault diagnosis for low speed bearing using multi-class relevance vector machine (RVM). A low speed test rig was developed to simulate the various defects with shaft speeds as low as 10 rpm under several loading conditions. The data was acquired using anAEsensor with the test bearing operating at a constant loading (5 kN) andwith a speed range from20 to 80 rpm. This study is aimed at finding a reliable method/tool for low speed machines fault diagnosis based on AE signal. In the present study, component analysis was performed to extract the bearing feature and to reduce the dimensionality of original data feature. The result shows that multi-class RVM offers a promising approach for fault diagnosis of low speed machines.

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The theory of ion-acoustic surface wave propagation on the interface between a dusty plasma and a dielectric is presented. Both the constant and variable dust-charge cases are considered. It is found that massive negatively charged dust grains can significantly affect the propagation and damping of the surface waves. Application of the results to surface-wave generated plasmas is discussed. © 1998 IEEE.