933 resultados para Thrust curve


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Interactions between small molecules with biopolymers e.g. the bovine serum albumin (BSA protein), are important, and significant information is recorded in the UV–vis and fluorescence spectra of their reaction mixtures. The extraction of this information is difficult conventionally and principally because there is significant overlapping of the spectra of the three analytes in the mixture. The interaction of berberine chloride (BC) and the BSA protein provides an interesting example of such complex systems. UV–vis and fluorescence spectra of BC and BSA mixtures were investigated in pH 7.4 Tris–HCl buffer at 37 °C. Two sample series were measured by each technique: (1) [BSA] was kept constant and the [BC] was varied and (2) [BC] was kept constant and the [BSA] was varied. This produced four spectral data matrices, which were combined into one expanded spectral matrix. This was processed by the multivariate curve resolution–alternating least squares method (MCR–ALS). The results produced: (1) the extracted pure BC, BSA and the BC–BSA complex spectra from the measured heavily overlapping composite responses, (2) the concentration profiles of BC, BSA and the BC–BSA complex, which are difficult to obtain by conventional means, and (3) estimates of the number of binding sites of BC.

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The interaction of quercetin, which is a bioflavonoid, with bovine serum albumin (BSA) was investigated under pseudo-physiological conditions by the application of UV–vis spectrometry, spectrofluorimetry and cyclic voltammetry (CV). These studies indicated a cooperative interaction between the quercetin–BSA complex and warfarin, which produced a ternary complex, quercetin–BSA–warfarin. It was found that both quercetin and warfarin were located in site I. However, the spectra of these three components overlapped and the chemometrics method – multivariate curve resolution-alternating least squares (MCR-ALS) was applied to resolve the spectra. The resolved spectra of quercetin–BSA and warfarin agreed well with their measured spectra, and importantly, the spectrum of the quercetin–BSA–warfarin complex was extracted. These results allowed the rationalization of the behaviour of the overlapping spectra. At lower concentrations ([warfarin] < 1 × 10−5 mol L−1), most of the site marker reacted with the quercetin–BSA, but free warfarin was present at higher concentrations. Interestingly, the ratio between quercetin–BSA and warfarin was found to be 1:2, suggesting a quercetin–BSA–(warfarin)2 complex, and the estimated equilibrium constant was 1.4 × 1011 M−2. The results suggest that at low concentrations, warfarin binds at the high-affinity sites (HAS), while low-affinity binding sites (LAS) are occupied at higher concentrations.

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Cognitive-energetical theories of information processing were used to generate predictions regarding the relationship between workload and fatigue within and across consecutive days of work. Repeated measures were taken on board a naval vessel during a non-routine and a routine patrol. Data were analyzed using growth curve modeling. Fatigue demonstrated a non-monotonic relationship within days in both patrols – fatigue was high at midnight, started decreasing until noontime and then increased again. Fatigue increased across days towards the end of the non-routine patrol, but remained stable across days in the routine patrol. The relationship between workload and fatigue changed over consecutive days in the non-routine patrol. At the beginning of the patrol, low workload was associated with fatigue. At the end of the patrol, high workload was associated with fatigue. This relationship could not be tested in the routine patrol, however it demonstrated a non-monotonic relationship between workload and fatigue – low and high workloads were associated with the highest fatigue. These results suggest that the optimal level of workload can change over time and thus have implications for the management of fatigue.

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It is important to detect and treat malnutrition in hospital patients so as to improve clinical outcome and reduce hospital stay. The aim of this study was to develop and validate a nutrition screening tool with a simple and quick scoring system for acute hospital patients in Singapore. In this study, 818 newly admitted patients aged above 18 years old were screened using five parameters that contribute to the risk of malnutrition. A dietitian blinded to the nutrition screening score assessed the same patients using the reference standard, Subjective Global Assessment (SGA) within 48 hours. The sensitivity and specificity were established using the Receiver Operator Characteristics (ROC) curve and the best cutoff scores determined. The nutrition parameter with the largest Area Under the ROC Curve (AUC) was chosen as the final screening tool, which was named 3-Minute Nutrition Screening (3-MinNS). The combination of the parameters weight loss, intake and muscle wastage (3-MinNS), gave the largest AUC when compared with SGA. Using 3-MinNS, the best cutoff point to identify malnourished patients is three (sensitivity 86%, specificity 83%). The cutoff score to identify subjects at risk of severe malnutrition is five (sensitivity 93%, specificity 86%). 3-Minute Nutrition Screening is a valid, simple and rapid tool to identify patients at risk of malnutrition in Singapore acute hospital patients. It is able to differentiate patients at risk of moderate malnutrition and severe malnutrition for prioritization and management purposes.

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Emissions from airport operations are of significant concern because of their potential impact on local air quality and human health. The currently limited scientific knowledge of aircraft emissions is an important issue worldwide, when considering air pollution associated with airport operation, and this is especially so for ultrafine particles. This limited knowledge is due to scientific complexities associated with measuring aircraft emissions during normal operations on the ground. In particular this type of research has required the development of novel sampling techniques which must take into account aircraft plume dispersion and dilution as well as the various particle dynamics that can affect the measurements of the aircraft engine plume from an operational aircraft. In order to address this scientific problem, a novel mobile emission measurement method called the Plume Capture and Analysis System (PCAS), was developed and tested. The PCAS permits the capture and analysis of aircraft exhaust during ground level operations including landing, taxiing, takeoff and idle. The PCAS uses a sampling bag to temporarily store a sample, providing sufficient time to utilize sensitive but slow instrumental techniques to be employed to measure gas and particle emissions simultaneously and to record detailed particle size distributions. The challenges in relation to the development of the technique include complexities associated with the assessment of the various particle loss and deposition mechanisms which are active during storage in the PCAS. Laboratory based assessment of the method showed that the bag sampling technique can be used to accurately measure particle emissions (e.g. particle number, mass and size distribution) from a moving aircraft or vehicle. Further assessment of the sensitivity of PCAS results to distance from the source and plume concentration was conducted in the airfield with taxiing aircraft. The results showed that the PCAS is a robust method capable of capturing the plume in only 10 seconds. The PCAS is able to account for aircraft plume dispersion and dilution at distances of 60 to 180 meters downwind of moving a aircraft along with particle deposition loss mechanisms during the measurements. Characterization of the plume in terms of particle number, mass (PM2.5), gaseous emissions and particle size distribution takes only 5 minutes allowing large numbers of tests to be completed in a short time. The results were broadly consistent and compared well with the available data. Comprehensive measurements and analyses of the aircraft plumes during various modes of the landing and takeoff (LTO) cycle (e.g. idle, taxi, landing and takeoff) were conducted at Brisbane Airport (BNE). Gaseous (NOx, CO2) emission factors, particle number and mass (PM2.5) emission factors and size distributions were determined for a range of Boeing and Airbus aircraft, as a function of aircraft type and engine thrust level. The scientific complexities including the analysis of the often multimodal particle size distributions to describe the contributions of different particle source processes during the various stages of aircraft operation were addressed through comprehensive data analysis and interpretation. The measurement results were used to develop an inventory of aircraft emissions at BNE, including all modes of the aircraft LTO cycle and ground running procedures (GRP). Measurements of the actual duration of aircraft activity in each mode of operation (time-in-mode) and compiling a comprehensive matrix of gas and particle emission rates as a function of aircraft type and engine thrust level for real world situations was crucial for developing the inventory. The significance of the resulting matrix of emission rates in this study lies in the estimate it provides of the annual particle emissions due to aircraft operations, especially in terms of particle number. In summary, this PhD thesis presents for the first time a comprehensive study of the particle and NOx emission factors and rates along with the particle size distributions from aircraft operations and provides a basis for estimating such emissions at other airports. This is a significant addition to the scientific knowledge in terms of particle emissions from aircraft operations, since the standard particle number emissions rates are not currently available for aircraft activities.

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Distracted is a luminous, interactive, computational media installation of sound, light and translucent sculptural materials. The work is inspired by scientific ice core samples taken in Antarctica. The sculpture is capable of displaying data taken from these ice core samples, and responding to the proximity of an audience. Rather than simply using the interface as a didactic display device, we have chosen a more poetic approach of generating visual effects from the data that are evocative of the ice, fluids and the notion of change. The data has also been used in the composition of an evolving soundscape. As well as data from ice core samples, such as the Vostok ice core, we have incorporated data from the Keeling Curve that shows the annual rise and fall of atmospheric carbon dioxide, following the pattern of the Northern Hemisphere winter. These effects combine with changes caused directly by audience members as they come within close proximity to the work.

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The wide range of contributing factors and circumstances surrounding crashes on road curves suggest that no single intervention can prevent these crashes. This paper presents a novel methodology, based on data mining techniques, to identify contributing factors and the relationship between them. It identifies contributing factors that influence the risk of a crash. Incident records, described using free text, from a large insurance company were analysed with rough set theory. Rough set theory was used to discover dependencies among data, and reasons using the vague, uncertain and imprecise information that characterised the insurance dataset. The results show that male drivers, who are between 50 and 59 years old, driving during evening peak hours are involved with a collision, had a lowest crash risk. Drivers between 25 and 29 years old, driving from around midnight to 6 am and in a new car has the highest risk. The analysis of the most significant contributing factors on curves suggests that drivers with driving experience of 25 to 42 years, who are driving a new vehicle have the highest crash cost risk, characterised by the vehicle running off the road and hitting a tree. This research complements existing statistically based tools approach to analyse road crashes. Our data mining approach is supported with proven theory and will allow road safety practitioners to effectively understand the dependencies between contributing factors and the crash type with the view to designing tailored countermeasures.

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The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

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The study reported here, constitutes a full review of the major geological events that have influenced the morphological development of the southeast Queensland region. Most importantly, it provides evidence that the region’s physiography continues to be geologically ‘active’ and although earthquakes are presently few and of low magnitude, many past events and tectonic regimes continue to be strongly influential over drainage, morphology and topography. Southeast Queensland is typified by highland terrain of metasedimentary and igneous rocks that are parallel and close to younger, lowland coastal terrain. The region is currently situated in a passive margin tectonic setting that is now under compressive stress, although in the past, the region was subject to alternating extensional and compressive regimes. As part of the investigation, the effects of many past geological events upon landscape morphology have been assessed at multiple scales using features such as the location and orientation of drainage channels, topography, faults, fractures, scarps, cleavage, volcanic centres and deposits, and recent earthquake activity. A number of hypotheses for local geological evolution are proposed and discussed. This study has also utilised a geographic information system (GIS) approach that successfully amalgamates the various types and scales of datasets used. A new method of stream ordination has been developed and is used to compare the orientation of channels of similar orders with rock fabric, in a topologically controlled approach that other ordering systems are unable to achieve. Stream pattern analysis has been performed and the results provide evidence that many drainage systems in southeast Queensland are controlled by known geological structures and by past geological events. The results conclude that drainage at a fine scale is controlled by cleavage, joints and faults, and at a broader scale, large river valleys, such as those of the Brisbane River and North Pine River, closely follow the location of faults. These rivers appear to have become entrenched by differential weathering along these planes of weakness. Significantly, stream pattern analysis has also identified some ‘anomalous’ drainage that suggests the orientations of these watercourses are geologically controlled, but by unknown causes. To the north of Brisbane, a ‘coastal drainage divide’ has been recognized and is described here. The divide crosses several lithological units of different age, continues parallel to the coast and prevents drainage from the highlands flowing directly to the coast for its entire length. Diversion of low order streams away from the divide may be evidence that a more recent process may be the driving force. Although there is no conclusive evidence for this at present, it is postulated that the divide may have been generated by uplift or doming associated with mid-Cenozoic volcanism or a blind thrust at depth. Also north of Brisbane, on the D’Aguilar Range, an elevated valley (the ‘Kilcoy Gap’) has been identified that may have once drained towards the coast and now displays reversed drainage that may have resulted from uplift along the coastal drainage divide and of the D’Aguilar blocks. An assessment of the distribution and intensity of recent earthquakes in the region indicates that activity may be associated with ancient faults. However, recent movement on these faults during these events would have been unlikely, given that earthquakes in the region are characteristically of low magnitude. There is, however, evidence that compressive stress is building and being released periodically and ancient faults may be a likely place for this stress to be released. The relationship between ancient fault systems and the Tweed Shield Volcano has also been discussed and it is suggested here that the volcanic activity was associated with renewed faulting on the Great Moreton Fault System during the Cenozoic. The geomorphology and drainage patterns of southeast Queensland have been compared with expected morphological characteristics found at passive and other tectonic settings, both in Australia and globally. Of note are the comparisons with the East Brazilian Highlands, the Gulf of Mexico and the Blue Ridge Escarpment, for example. In conclusion, the results of the study clearly show that, although the region is described as a passive margin, its complex, past geological history and present compressive stress regime provide a more intricate and varied landscape than would be expected along typical passive continental margins. The literature review provides background to the subject and discusses previous work and methods, whilst the findings are presented in three peer-reviewed, published papers. The methods, hypotheses, suggestions and evidence are discussed at length in the final chapter.

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Modern machines are complex and often required to operate long hours to achieve production targets. The ability to detect symptoms of failure, hence, forecasting the remaining useful life of the machine is vital to prevent catastrophic failures. This is essential to reducing maintenance cost, operation downtime and safety hazard. Recent advances in condition monitoring technologies have given rise to a number of prognosis models that attempt to forecast machinery health based on either condition data or reliability data. In practice, failure condition trending data are seldom kept by industries and data that ended with a suspension are sometimes treated as failure data. This paper presents a novel approach of incorporating historical failure data and suspended condition trending data in the prognostic model. The proposed model consists of a FFNN whose training targets are asset survival probabilities estimated using a variation of Kaplan-Meier estimator and degradation-based failure PDF estimator. The output survival probabilities collectively form an estimated survival curve. The viability of the model was tested using a set of industry vibration data.

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Fusionless scoliosis surgery is an emerging treatment for idiopathic scoliosis as it offers theoretical advantages over current forms of treatment. Currently the treatment options for idiopathic scoliosis are observation, bracing and fusion. While brace treatment is non-invasive, and preserves the growth, motion, and function of the spine, it does not correct deformity and is only modestly successful in preventing curve progression. In adolescents who fail brace treatment, surgical treatment with an instrumented spinal fusion usually results in better deformity correction but is associated with substantially greater risk. Furthermore in younger patients requiring surgical treatment, fusion procedures are known to adversely effect the future growth of the chest and spine. Fusionless treatments have been developed to allow effective surgical treatment of patients with idiopathic scoliosis who are too young for fusion procedures. Anterior vertebral stapling is one such fusionless treatment which aims to modulate the growth of vertebra to allow correction of scoliosis whilst maintaining normal spinal motion The Mater Misericordiae Hospital in Brisbane has begun to use anterior vertebral stapling to treat patients with idiopathic scoliosis who are too young for fusion procedures. Currently the only staple approved for clinical use is manufactured by Medtronic Sofamor Danek (Memphis, TN). This thesis explains the biomechanical and anatomical changes that occur following anterior vertebral staple insertion using in vitro experiments performed on an immature bovine model. Currently there is a paucity of published information about anterior vertebral stapling so it is hoped that this project will provide information that will aid in our understanding of the clinical effects of staple insertion. The aims of this experimental study were threefold. The first phase was designed to determine the changes in the bending stiffness of the spine following staple insertion. The second phase was designed to measure the forces experienced by the staple during spinal movements. The third and final phase of testing was designed to describe the structural changes that occur to a vertebra as a consequence of staple insertion. The first phase of testing utilised a displacement controlled testing robot to compare the change in stiffness of a single spinal motion segment following staple insertion for the three basic spinal motions of flexion-extension, lateral bending, and axial rotation. For the second phase of testing strain gauges were attached to staples and used to measure staple forces during spinal movement. In the third and final phase the staples were removed and a testing specimen underwent micro-computed tomography (CT) scanning to describe the anatomical changes that occur following staple insertion. The displacement controlled testing showed that there was a significant decrease in bending stiffness in flexion, extension, lateral bending away from the staple, and axial rotation away from the staple following staple insertion. The strain gauge measurements showed that the greatest staple forces occurred in flexion and the least in extension. In addition, a reduction in the baseline staple compressive force was seen with successive loading cycles. Micro-CT scanning demonstrated that significant damage to the vertebral body and endplate occurred as a consequence of staple insertion. The clinical implications of this study are significant. Based on the findings of this project it is likely that the clinical effect of the anterior vertebral staple evaluated in this project is a consequence of growth plate damage (also called hemiepiphysiodesis) causing a partial growth arrest of the vertebra rather than simply compression of the growth plate. The surgical creation of a unilateral growth arrest is a well established treatment used in the management of congenital scoliosis but has not previously been considered for use in idiopathic scoliosis.

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An extensive literature examines the dynamics of interest rates, with particular attention given to the positive relationship between interest-rate volatility and the level of interest rates—the so-called level effect. This paper examines the interaction between the estimated level effect and competing parameterisations of interest-rate volatility for the Australian yield curve. We adopt a new methodology that estimates elasticity in a multivariate setting that explicitly accommodates the correlations that exist between various yield factors. Results show that significant correlations exist between the residuals of yield factors and that such correlations do indeed impact on model estimates. Within the multivariate setting, the level of the short rate is shown to be a crucial determinant of the conditional volatility of all three yield factors. Measures of model fit suggest that, in addition to the usual level effect, the incorporation of GARCH effects and possible regime shifts is important

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The term structure of interest rates is often summarized using a handful of yield factors that capture shifts in the shape of the yield curve. In this paper, we develop a comprehensive model for volatility dynamics in the level, slope, and curvature of the yield curve that simultaneously includes level and GARCH effects along with regime shifts. We show that the level of the short rate is useful in modeling the volatility of the three yield factors and that there are significant GARCH effects present even after including a level effect. Further, we find that allowing for regime shifts in the factor volatilities dramatically improves the model’s fit and strengthens the level effect. We also show that a regime-switching model with level and GARCH effects provides the best out-of-sample forecasting performance of yield volatility. We argue that the auxiliary models often used to estimate term structure models with simulation-based estimation techniques should be consistent with the main features of the yield curve that are identified by our model.

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Section 35 of the Insurance Contracts Act 1984 requires insurers offering insurance policies in six prescribed areas "to clearly inform" prospective insureds of any departure their policies may constitute from the standard covers established by the Act and its accompanying Regulations. This prescribed insurance contracts regime was designed to remedy comprehension problems generated by the length and complexity of insurance documents and to alleviate misunderstanding over the terms and conditions of individual policies. This article examines the rationale underpinning s 35 and the prescribed insurance contracts regime and looks at the operation of the legislation with particular reference to home contents insurance in Australia. It is argued that the means whereby disclosure of derogation from standard cover may be effected largely negates the thrust of the prescribed insurance contract reform. Recommendations to address these operational deficiencies are made.

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Bayer hydrotalcites prepared using the seawater neutralisation (SWN) process of Bayer liquors are characterised using X-ray diffraction and thermal analysis techniques. The Bayer hydrotalcites are synthesised at four different temperatures (0, 25, 55, 75 °C) to determine the effect on the thermal stability of the hydrotalcite structure, and to identify other precipitates that form at these temperatures. The interlayer distance increased with increasing synthesis temperature, up to 55 °C, and then decreased by 0.14 Å for Bayer hydrotalcites prepared at 75 °C. The three mineralogical phases identified in this investigation are; 1) Bayer hydrotalcite, 2), calcium carbonate species, and 3) hydromagnesite. The DTG curve can be separated into four decomposition steps; 1) the removal of adsorbed water and free interlayer water in hydrotalcite (30 – 230 °C), 2) the dehydroxylation of hydrotalcite and the decarbonation of hydrotalcite (250 – 400 °C), 3) the decarbonation of hydromagnesite (400 – 550 °C), and 4) the decarbonation of aragonite (550 – 650 °C).