995 resultados para Microscopic Approach


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A commitment in 2010 by the Australian Federal Government to spend $466.7 million dollars on the implementation of personally controlled electronic health records (PCEHR) heralded a shift to a more effective and safer patient centric eHealth system. However, deployment of the PCEHR has met with much criticism, emphasised by poor adoption rates over the first 12 months of operation. An indifferent response by the public and healthcare providers largely sceptical of its utility and safety speaks to the complex sociotechnical drivers and obstacles inherent in the embedding of large (national) scale eHealth projects. With government efforts to inflate consumer and practitioner engagement numbers giving rise to further consumer disillusionment, broader utilitarian opportunities available with the PCEHR are at risk. This paper discusses the implications of establishing the PCEHR as the cornerstone of a holistic eHealth strategy for the aggregation of longitudinal patient information. A viewpoint is offered that the real value in patient data lies not just in the collection of data but in the integration of this information into clinical processes within the framework of a commoditised data-driven approach. Consideration is given to the eHealth-as-a-Service (eHaaS) construct as a disruptive next step for co-ordinated individualised healthcare in the Australian context.

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Recognising that charitable behaviour can be motivated by public recognition and emotional satisfaction, not-for-profit organisations have developed strategies that leverage self-interest over altruism by facilitating individuals to donate conspicuously. Initially developed as novel marketing programs to increase donation income, such conspicuous tokens of recognition are being recognised as important value propositions to nurture donor relationships. Despite this, there is little empirical evidence that identifies when donations can be increased through conspicuous recognition. Furthermore, social media’s growing popularity for self-expression, as well as the increasing use of technology in donor relationship management strategies, makes an examination of virtual conspicuous tokens of recognition in relation to what value donors seek particularly insightful. Therefore, this research examined the impact of experiential donor value and virtual conspicuous tokens of recognition on blood donor intentions. Using online survey data from 186 Australian blood donors, results show that in fact emotional value is a stronger predictor of intentions to donate blood than altruistic value, while social value is the strongest predictor of intentions if provided with recognition. Clear linkages between dimensions of donor value (altruistic, emotional and social) and conspicuous donation behaviour (CDB) were identified. The findings provide valuable insights into the use of conspicuous donation tokens of recognition on social media, and contribute to our understanding into the under-researched areas of donor value and CDB.

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Despite the fact that customer retention is crucial for providers of cloud enterprise systems, only little attention has been directed towards investigating the antecedents of subscription renewal in an organizational context. This is even more surprising, as cloud services are usually offered as subscription-based pricing models with the (theoretical) possibility of immediate service cancellation, strongly opposing classical long-term IT-Outsourcing contracts or license-based payment plans of on premise enterprise systems. To close this research gap an empirical study was undertaken. Firstly, a conceptual model was drawn from theories of social psychology, organizational system continuance and IS success. The model was subsequently tested using survey responses of senior management within companies which adopted cloud enterprise systems. Gathered data was then analysed using PLS. The results indicate that subscription renewal intention is influenced by both – social-related and technology-specific factors – which are able to explain 50.4% of the variance in the dependent variable. Beneath the cloud enterprise systems specific contributions, the work advances knowledge in the area of organizational system continuance, as well as IS success.

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The location of previously unseen and unregistered individuals in complex camera networks from semantic descriptions is a time consuming and often inaccurate process carried out by human operators, or security staff on the ground. To promote the development and evaluation of automated semantic description based localisation systems, we present a new, publicly available, unconstrained 110 sequence database, collected from 6 stationary cameras. Each sequence contains detailed semantic information for a single search subject who appears in the clip (gender, age, height, build, hair and skin colour, clothing type, texture and colour), and between 21 and 290 frames for each clip are annotated with the target subject location (over 11,000 frames are annotated in total). A novel approach for localising a person given a semantic query is also proposed and demonstrated on this database. The proposed approach incorporates clothing colour and type (for clothing worn below the waist), as well as height and build to detect people. A method to assess the quality of candidate regions, as well as a symmetry driven approach to aid in modelling clothing on the lower half of the body, is proposed within this approach. An evaluation on the proposed dataset shows that a relative improvement in localisation accuracy of up to 21 is achieved over the baseline technique.

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Time series classification has been extensively explored in many fields of study. Most methods are based on the historical or current information extracted from data. However, if interest is in a specific future time period, methods that directly relate to forecasts of time series are much more appropriate. An approach to time series classification is proposed based on a polarization measure of forecast densities of time series. By fitting autoregressive models, forecast replicates of each time series are obtained via the bias-corrected bootstrap, and a stationarity correction is considered when necessary. Kernel estimators are then employed to approximate forecast densities, and discrepancies of forecast densities of pairs of time series are estimated by a polarization measure, which evaluates the extent to which two densities overlap. Following the distributional properties of the polarization measure, a discriminant rule and a clustering method are proposed to conduct the supervised and unsupervised classification, respectively. The proposed methodology is applied to both simulated and real data sets, and the results show desirable properties.

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A set system (X, F ) with X= {x 1,...,x m}) and F = {B1...,B n }, where B i ⊆ X, is called an (n, m) cover-free set system (or CF set system) if for any 1 ≤ i, j, k ≤ n and j ≠ k, |B i >2 |B j ∩ B k | +1. In this paper, we show that CF set systems can be used to construct anonymous membership broadcast schemes (or AMB schemes), allowing a center to broadcast a secret identity among a set of users in a such way that the users can verify whether or not the broadcast message contains their valid identity. Our goal is to construct (n, m) CF set systems in which for given m the value n is as large as possible. We give two constructions for CF set systems, the first one from error-correcting codes and the other from combinatorial designs. We link CF set systems to the concept of cover-free family studied by Erdös et al in early 80’s to derive bounds on parameters of CF set systems. We also discuss some possible extensions of the current work, motivated by different application.

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Fundamental understanding on microscopic physical changes of plant materials is vital to optimize product quality and processing techniques, particularly in food engineering. Although grid-based numerical modelling can assist in this regard, it becomes quite challenging to overcome the inherited complexities of these biological materials especially when such materials undergo critical processing conditions such as drying, where the cellular structure undergoes extreme deformations. In this context, a meshfree particle based model was developed which is fundamentally capable of handling extreme deformations of plant tissues during drying. The model is built by coupling a particle based meshfree technique: Smoothed Particle Hydrodynamics (SPH) and a Discrete Element Method (DEM). Plant cells were initiated as hexagons and aggregated to form a tissue which also accounts for the characteristics of the middle lamella. In each cell, SPH was used to model cell protoplasm and DEM was used to model the cell wall. Drying was incorporated by varying the moisture content, the turgor pressure, and cell wall contraction effects. Compared to the state of the art grid-based microscale plant tissue drying models, the proposed model can be used to simulate tissues under excessive moisture content reductions incorporating cell wall wrinkling. Also, compared to the state of the art SPH-DEM tissue models, the proposed model better replicates real tissues and the cell-cell interactions used ensure efficient computations. Model predictions showed good agreement both qualitatively and quantitatively with experimental findings on dried plant tissues. The proposed modelling approach is fundamentally flexible to study different cellular structures for their microscale morphological changes at dehydration.

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Contextual factors for sustainable development such as population growth, energy, and resource availability and consumption levels, food production yield, and growth in pollution, provide numerous complex and rapidly changing education and training requirements for a variety of professions including engineering. Furthermore, these requirements may not be clearly understood or expressed by designers, governments, professional bodies or the industry. Within this context, this paper focuses on one priority area for greening the economy through sustainable development—improving energy efficiency—and discusses the complexity of capacity building needs for professionals. The paper begins by acknowledging the historical evolution of sustainability considerations, and the complexity embedded in built environment solutions. The authors propose a dual-track approach to building capacity building, with a short-term focus on improvement (i.e., making peaking challenges a priority for postgraduate education), and a long-term focus on transformational innovation (i.e., making tailing challenges a priority for undergraduate education). A case study is provided, of Australian experiences over the last decade with regard to the topic area of energy efficiency. The authors conclude with reflections on implications for the approach.

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This article elucidates and analyzes the fundamental underlying structure of the renormalization group (RG) approach as it applies to the solution of any differential equation involving multiple scales. The amplitude equation derived through the elimination of secular terms arising from a naive perturbation expansion of the solution to these equations by the RG approach is reduced to an algebraic equation which is expressed in terms of the Thiele semi-invariants or cumulants of the eliminant sequence { Zi } i=1 . Its use is illustrated through the solution of both linear and nonlinear perturbation problems and certain results from the literature are recovered as special cases. The fundamental structure that emerges from the application of the RG approach is not the amplitude equation but the aforementioned algebraic equation. © 2008 The American Physical Society.

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We study the multicast stream authentication problem when an opponent can drop, reorder and inject data packets into the communication channel. In this context, bandwidth limitation and fast authentication are the core concerns. Therefore any authentication scheme is to reduce as much as possible the packet overhead and the time spent at the receiver to check the authenticity of collected elements. Recently, Tartary and Wang developed a provably secure protocol with small packet overhead and a reduced number of signature verifications to be performed at the receiver. In this paper, we propose an hybrid scheme based on Tartary and Wang’s approach and Merkle hash trees. Our construction will exhibit a smaller overhead and a much faster processing at the receiver making it even more suitable for multicast than the earlier approach. As Tartary and Wang’s protocol, our construction is provably secure and allows the total recovery of the data stream despite erasures and injections occurred during transmission.

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This paper introduces an integral approach to the study of plasma-surface interactions during the catalytic growth of selected nanostructures (NSs). This approach involves basic understanding of the plasma-specific effects in NS nucleation and growth, theoretical modelling, numerical simulations, plasma diagnostics, and surface microanalysis. Using an example of plasma-assisted growth of surface-supported single-walled carbon nanotubes, we discuss how the combination of these techniques may help improve the outcomes of the growth process. A specific focus here is on the effects of nanoscale plasma-surface interactions on the NS growth and how the available techniques may be used, both in situ and ex situ to optimize the growth process and structural parameters of NSs.

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Textured silicon surfaces are widely used in manufacturing of solar cells due to increasing the light absorption probability and also the antireflection properties. However, these Si surfaces have a high density of surface defects that need to be passivated. In this study, the effect of the microscopic surface texture on the plasma surface passivation of solar cells is investigated. The movement of 105 H+ ions in the texture-modified plasma sheath is studied by Monte Carlo numerical simulation. The hydrogen ions are driven by the combined electric field of the plasma sheath and the textured surface. The ion dynamics is simulated, and the relative ion distribution over the textured substrate is presented. This distribution can be used to interpret the quality of the Si dangling bonds saturation and consequently, the direct plasma surface passivation.

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In this study, atmospheric-pressure plasmas were applied to modify the surface of silane-coated silica nanoparticles. Subsequently nanocomposites were synthesized by incorporating plasma-treated nanoparticles into an epoxy resin matrix. Electrical testing showed that such novel dielectric materials obtained high partial discharge resistance, high dielectric breakdown strength, and enhanced endurance under highly stressed electric field. Through spectroscopic and microscopic analysis, we found surface groups of nanoparticles were activated and radicals were created after the plasma treatment. Moreover, a uniform dispersion of nanoparticles in nanocomposites was observed. It was expected that the improved dielectric performance of the nanocomposites can attribute to stronger chemical bonds formed between surface groups of plasma-treated nanoparticles and molecules in the matrix. This simple yet effective and environmentally friendly approach aims to synthesize the next generation of high-performance nanocomposite dielectric insulation materials for applications in high-voltage power systems.

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The possibility to control the morphology and nucleation density of quasi-one-dimensional, single-crystalline α -Fe2 O3 nanostructures by varying the electric potential of iron surfaces exposed to reactive oxygen plasmas is demonstrated experimentally. A systematic increase in the oxygen ion flux through rf biasing of otherwise floating substrates and then an additional increase of the ion/neutral density resulted in remarkable structural transformations of straight nanoneedles into nanowires with controlled tapering/aspect ratio and also in larger nucleation densities. Multiscale numerical simulations relate the microscopic ion flux topographies to the nanostructure nucleation and morphological evolution. This approach is applicable to other metal-oxide nanostructures.

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Despite the realisation of the potential implications from biosimilars is relatively recent, much has already been written about raising the awareness of differences between biosimilars and originating/ reference listed (innovator) pharmaceuticals. The European Medicines Agency has led the global charge in regulating biosimilars. Regardless of sufficient similarities across international regulations, differences do exist across jurisdictions. The consideration of regulating biosimilars demands a congruent approach across all stages: pre-registration (Australian copyright protection, patent, international obligations), registration (confidential information, international regulators, safety and efficacy), post-registration (Pharmaceutical Benefit Scheme, prescriber and dispenser awareness). Our National Medicines Policy could provide the necessary congruent framework and function for national and international regulation of biosimilars. The Policy concedes that pharmaceuticals will be affected by financial policies and trade considerations, international treaty obligations, industrial policies, education policies and the need for public-private partnerships.