930 resultados para Application-layer


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Background and purpose Our aim was to prove in an animal model that the use of HA paste at the cement-bone interface in the acetabulum would improve fixation. We examined, in sheep, the effect of interposing a layer of hydroxyapatite cement around the periphery of a polyethylene socket prior to fixing it using polymethylemethacrylate (PMMA). Methods We made a randomized study involving 22 sheep to test whether the application of BoneSource hydroxyapatite material to the surface of the ovine acetabulum prior to cementing a polyethylene cup at hip arthroplasty improved the fixation and the nature of the interface. We studied the gross radiographical appearance of the implant-bone interface and the histological appearance at the interface. Results There were more radiolucencies evident in the control group. Histologically, only sheep randomized into the BoneSource group exhibited a fully osseointegrated interface. Use of the hydroxyapatite material did not confer any detrimental effects. In some cases the material appeared to have been fully resorbed. When the material was evident on histological section, it was incorporated into an osseointegrated interface. There was no giant cell reaction present in any case. There was no evidence of migration of BoneSource to the articulation. Interpretation The application of HA material prior to cementation of a socket produced an improved interface. The technique may be useful in man with to extend the longevity of the cemented implant by protecting the socket interface from the effect of hydrodynamic fluid flow and particulate debris.

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Powerful brands create meaningful images in the minds of customers (Keller, 1993). A strong brand image and reputation enhances differentiation and has a positive influence on buying behaviour (Gordon et al., 1993; McEnally and de Chernatony, 1999). While the power of branding is widely acknowledged in consumer markets, the nature and importance of branding in industrial markets remains under-researched. Many business-to-business (B2B) strategists have claimed brand-building belongs in the consumer realm. They argue that industrial products do not need branding as it is confusing and adds little value to functional products (Collins, 1977; Lorge, 1998; Saunders and Watt, 1979). Others argue that branding and the concept of brand equity however are increasingly important in industrial markets, because it has been shown that what a brand means to a buyer can be a determining factor in deciding between industrial purchase alternatives (Aaker, 1991). In this context, it is critical for suppliers to initiate and sustain relationships due to the small number of potential customers (Ambler, 1995; Webster and Keller, 2004). To date however, there is no model available to assist B2B marketers in identifying and measuring brand equity. In this paper, we take a step in that direction by operationalising and empirically testing a prominent brand equity model in a B2B context. This makes not only a theoretical contribution by advancing branding research, but also addresses a managerial need for information that will assist in the assessment of industrial branding efforts.

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Articular cartilage exhibits limited intrinsic regenerative capacity and focal tissue defects can lead to the development of osteoarthritis (OA), a painful and debilitating loss of cartilage tissue. In Australia, 1.4 million people are affected by OA and its prevalence is increasing in line with current demographics. As treatment options are limited, new therapeutic approaches are being investigated including biological resurfacing of joints with tissue-engineered cartilage. Despite some progress in the field, major challenges remain to be addressed for large scale clinical success. For example, large numbers of chondrogenic cells are required for cartilage formation, but chondrocytes lose their chondrogenic phenotype (dedifferentiate) during in vitro propagation. Additionally, the zonal organization of articular cartilage is critical for normal cartilage function, but development of zonal structure has been largely neglected in cartilage repair strategies. Therefore, we hypothesised that culture conditions for freshly isolated human articular chondrocytes from non-OA and OA sources can be improved by employing microcarrier cultures and a reduced oxygen environment and that oxygen is a critical factor in the maintenance of the zonal chondrocyte phenotype. Microcarriers have successfully been used to cultivate bovine chondrocytes, and offer a potential alternative for clinical expansion of human chondrocytes. We hypothesised that improved yields can be achieved by propagating human chondrocytes on microcarriers. We found that cells on microcarriers acquired a flattened, polygonal morphology and initially proliferated faster than monolayercultivated cells. However, microcarrier cultivation over four weeks did not improve growth rates or the chondrogenic potential of non-OA and OA human articular chondrocytes over conventional monolayer cultivation. Based on these observations, we aimed to optimise culture conditions by modifying oxygen tension, to more closely reflect the in vivo environment. We found that propagation at 5% oxygen tension (moderate hypoxia) did not improve proliferation or redifferentiation capacity of human osteoarthritic chondrocytes. Moderate hypoxia increased the expression of chondrogenic markers during redifferentiation. However, osteoarthritic chondrocytes cultivated on microcarriers exhibited lower expression levels of chondrogenic surface marker proteins and had at best equivalent redifferentiation capacities compared to monolayer-cultured cells. This suggests that monolayer culture with multiple passaging potentially selects for a subpopulation of cells with higher differentiation capacity, which are otherwise rare in osteoarthritic, aged cartilage. However, fibroblastic proteins were found to be highly expressed in all cultures of human osteoarthritic chondrocytes indicating the presence of a high proportion of dedifferentiated, senescent cells with a chondrocytic phenotype that was not rescued by moderate hypoxia. The different zones of cartilage support chondrocyte subpopulations, which exhibit characteristic protein expression and experience varying oxygen tensions. We, therefore, hypothesised that oxygen tension affects the zonal marker expression of human articular chondrocytes isolated from the different cartilage layers. We found that zonal chondrocytes maintained these phenotypic differences during in vitro cultivation. Low oxygen environments favoured the expression of the zonal marker proteoglycan 4 in superficial cells, most likely through the promotion of chondrogenesis. The putative zonal markers clusterin and cartilage intermediate layer protein were found to be expressed by all subpopulations of human osteoarthritic chondrocytes ex vivo and, thus, may not be reliable predictors of in vitro stratification using these clinically relevant cells. The findings in this thesis underline the importance of considering low oxygen conditions and zonal stratification when creating native-like cartilaginous constructs. We have not yet found the right cues to successfully cultivate clinically-relevant human osteoarthritic chondrocytes in vitro. A more thorough understanding of chondrocyte biology and the processes of chondrogenesis are required to ensure the clinical success of cartilage tissue engineering.

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When asymptotic series methods are applied in order to solve problems that arise in applied mathematics in the limit that some parameter becomes small, they are unable to demonstrate behaviour that occurs on a scale that is exponentially small compared to the algebraic terms of the asymptotic series. There are many examples of physical systems where behaviour on this scale has important effects and, as such, a range of techniques known as exponential asymptotic techniques were developed that may be used to examinine behaviour on this exponentially small scale. Many problems in applied mathematics may be represented by behaviour within the complex plane, which may subsequently be examined using asymptotic methods. These problems frequently demonstrate behaviour known as Stokes phenomenon, which involves the rapid switches of behaviour on an exponentially small scale in the neighbourhood of some curve known as a Stokes line. Exponential asymptotic techniques have been applied in order to obtain an expression for this exponentially small switching behaviour in the solutions to orginary and partial differential equations. The problem of potential flow over a submerged obstacle has been previously considered in this manner by Chapman & Vanden-Broeck (2006). By representing the problem in the complex plane and applying an exponential asymptotic technique, they were able to detect the switching, and subsequent behaviour, of exponentially small waves on the free surface of the flow in the limit of small Froude number, specifically considering the case of flow over a step with one Stokes line present in the complex plane. We consider an extension of this work to flow configurations with multiple Stokes lines, such as flow over an inclined step, or flow over a bump or trench. The resultant expressions are analysed, and demonstrate interesting implications, such as the presence of exponentially sub-subdominant intermediate waves and the possibility of trapped surface waves for flow over a bump or trench. We then consider the effect of multiple Stokes lines in higher order equations, particu- larly investigating the behaviour of higher-order Stokes lines in the solutions to partial differential equations. These higher-order Stokes lines switch off the ordinary Stokes lines themselves, adding a layer of complexity to the overall Stokes structure of the solution. Specifically, we consider the different approaches taken by Howls et al. (2004) and Chap- man & Mortimer (2005) in applying exponential asymptotic techniques to determine the higher-order Stokes phenomenon behaviour in the solution to a particular partial differ- ential equation.

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An investigation has been made of the interactions between silicone oil and various solid substrates immersed in aqueous solutions. Measurements were made using an atomic force microscope (AFM) using the colloid-probe method. The silicone oil drop is simulated by coating a small silica sphere with the oil, and measuring the force as this coated sphere is brought close to contact with a flat solid surface. It is found that the silicone oil surface is negatively charged, which causes a double-layer repulsion between the oil drop and another negatively charged surface such as mica. With hydrophilic solids, this repulsion is strong enough to prevent attachment of the drop to the solid. However, with hydrophobic surfaces there is an additional attractive force which overcomes the double-layer repulsion, and the silicone oil drop attaches to the solid. A "ramp" force appears in some, but not all, of the data sets. There is circumstantial evidence that this force results from compression of the silicone oil film coated on the glass sphere.

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In this chapter we propose clipping with amplitude and phase corrections to reduce the peak-to-average power ratio (PAR) of orthogonal frequency division multiplexed (OFDM) signals in high-speed wireless local area networks defined in IEEE 802.11a physical layer. The proposed techniques can be implemented with a small modification at the transmitter and the receiver remains standard compliant. PAR reduction as much as 4dB can be achieved by selecting a suitable clipping ratio and a correction factor depending on the constellation used. Out of band noise (OBN) is also reduced.

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Fracture behavior of Cu-Ni laminate composites has been investigated by tensile testing. It was found that as the individual layer thickness decreases from 100 to 20nm, the resultant fracture angle of the Cu-Ni laminate changes from 72 degrees to 50 degrees. Cross-sectional observations reveal that the fracture of the Ni layers transforms from opening to shear mode as the layer thickness decreases while that of the Cu layers keeps shear mode. Competition mechanisms were proposed to understand the variation in fracture mode of the metallic laminate composites associated with length scale.

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Visual servoing has been a viable method of robot manipulator control for more than a decade. Initial developments involved positionbased visual servoing (PBVS), in which the control signal exists in Cartesian space. The younger method, image-based visual servoing (IBVS), has seen considerable development in recent years. PBVS and IBVS offer tradeoffs in performance, and neither can solve all tasks that may confront a robot. In response to these issues, several methods have been devised that partition the control scheme, allowing some motions to be performed in the manner of a PBVS system, while the remaining motions are performed using an IBVS approach. To date, there has been little research that explores the relative strengths and weaknesses of these methods. In this paper we present such an evaluation. We have chosen three recent visual servo approaches for evaluation in addition to the traditional PBVS and IBVS approaches. We posit a set of performance metrics that measure quantitatively the performance of a visual servo controller for a specific task. We then evaluate each of the candidate visual servo methods for four canonical tasks with simulations and with experiments in a robotic work cell.

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In this paper, we develop the switching controller presented by Lee et al. for the pose control of a car-like vehicle, to allow the use of an omnidirectional vision sensor. To this end we incorporate an extension to a hypothesis on the navigation behaviour of the desert ant, cataglyphis bicolor, which leads to a correspondence free landmark based vision technique. The method we present allows positioning to a learnt location based on feature bearing angle and range discrepancies between the robot's current view of the environment, and that at a learnt location. We present simulations and experimental results, the latter obtained using our outdoor mobile platform.

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The objective of this paper is to provide an overview of mine automation applications, developed at the Queensland Centre for Advanced Technology (QCAT), which make use of IEEE 802.11b wireless local area networks (WLANs). The paper has been prepared for a 2002 conference entitled "Creating the Virtual Enterprise - Leveraging wireless technology within existing business models for corporate advantage". Descriptions of the WLAN components have been omitted here as such details are presented in the accompanying papers. The structure of the paper is as follows. Application overviews are provided in Sections 2 to 7. Some pertinent strengths and weaknesses are summarised in Section 8. Please refer to http://www.mining-automation.com/ or contact the authors for further information.

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The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

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The aim of this study was to evaluate the healing of class III furcation defects following transplantation of autogenous periosteal cells combined with b-tricalcium phosphate (b-TCP). Periosteal cells obtained from Beagle dogs’ periosteum explant cultures, were inoculated onto the surface of b-TCP. Class III furcation defects were created in the mandibular premolars. Three experimental groups were used to test the defects’ healing: group A, b-TCP seeded with periosteal cells were transplanted into the defects; group B, b-TCP alone was used for defect filling; and group C, the defect was without filling materials. Twelve weeks post surgery, the tissue samples were collected for histology, immunohistology and X-ray examination. It was found that both the length of newly formed periodontal ligament and the area of newly formed alveolar bone in group A, were significantly increased compared with both group B and C. Furthermore, both the proportion of newly formed periodontal ligament and newly formed alveolar bone in group A were much higher than those of group B and C. The quantity of cementum and its percentage in the defects (group A) were also significantly higher than those of group C. These results indicate that autogenous periosteal cells combined with b-TCP application can improve periodontal tissue regeneration in class III furcation defects.

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Traditional speech enhancement methods optimise signal-level criteria such as signal-to-noise ratio, but these approaches are sub-optimal for noise-robust speech recognition. Likelihood-maximising (LIMA) frameworks are an alternative that optimise parameters of enhancement algorithms based on state sequences generated for utterances with known transcriptions. Previous reports of LIMA frameworks have shown significant promise for improving speech recognition accuracies under additive background noise for a range of speech enhancement techniques. In this paper we discuss the drawbacks of the LIMA approach when multiple layers of acoustic mismatch are present – namely background noise and speaker accent. Experimentation using LIMA-based Mel-filterbank noise subtraction on American and Australian English in-car speech databases supports this discussion, demonstrating that inferior speech recognition performance occurs when a second layer of mismatch is seen during evaluation.

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Traditional speech enhancement methods optimise signal-level criteria such as signal-to-noise ratio, but such approaches are sub-optimal for noise-robust speech recognition. Likelihood-maximising (LIMA) frameworks on the other hand, optimise the parameters of speech enhancement algorithms based on state sequences generated by a speech recogniser for utterances of known transcriptions. Previous applications of LIMA frameworks have generated a set of global enhancement parameters for all model states without taking in account the distribution of model occurrence, making optimisation susceptible to favouring frequently occurring models, in particular silence. In this paper, we demonstrate the existence of highly disproportionate phonetic distributions on two corpora with distinct speech tasks, and propose to normalise the influence of each phone based on a priori occurrence probabilities. Likelihood analysis and speech recognition experiments verify this approach for improving ASR performance in noisy environments.

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This paper, underpinned by a framework of autopoietic principles of creativity/innovation and leadership/governance, argues that open forms of creativity in ‘arts’ provide opportunity for impact upon concepts of development, leadership and governance. The alliance of creativity and governance suggests that by examining various understandings of artistic experiences, readers may perceive new understandings of alliance, application and assessment of such experiences. This critical understanding would include assessing whether such experience supports people changing their aspirations as they become what they want to be. Such understanding may also suggest that different applications of the creative capacity of the ‘arts’ offers relevance in alleged ‘non-creative’ areas of academe, particularly in areas of management, leadership and governance. This alliance also offers the possibility of new staff development programs that facilitate learning and building of individual capacity, as well as facilitate congruent development process and policy, particularly within academic organisational structures.