905 resultados para GENERAL LINEAR SUPERGROUP


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Why are consumers different: Heterogeneity in the way consumers categorise products and services – Snack Food Influenced by the individual needs, personal traits, values and goals – Blood Donation Consumers base their choices on information from external sources and prior experiences stored in memory. Intrinsic – prior experience Extrinsic – advertising, blogs, etc

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OBJECTIVE: To explore how registered nurses (RNs) in the general ward perceive discharge processes and practices for patients recently discharged from the intensive care unit (ICU). BACKGROUND: Patients discharged from the ICU environment often require complicated and multifaceted care. The ward-based RN is at the forefront of the care of this fragile patient population, yet their views and perceptions have seldom been explored. DESIGN: A qualitative grounded theory design was used to guide focus group interviews with the RN participants. METHODS: Five semi-structured focus group interviews, including 27 RN participants, were conducted in an Australian metropolitan tertiary referral hospital in 2011. Data analyses of transcripts, field notes and memos used concurrent data generation, constant comparative analysis and theoretical sampling. RESULTS: Results yielded a core category of 'two worlds' stressing the disconnectedness between ICU and the ward setting. This category was divided into sub categories of 'communication disconnect' and 'remember the family'. Properties of 'what we say', 'what we write', 'transfer' and 'information needs' respectively were developed within those sub-categories. CONCLUSION: The discharge process for patients within the ICU setting is complicated and largely underappreciated. There are fundamental, misunderstood differences in prioritisation and care of patients between the areas, with a deep understanding of practice requirements of ward based RNs not being understood. The findings of this research may be used to facilitate inter departmental communications and progress practice development.

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In this paper, a method of thrust allocation based on a linearly constrained quadratic cost function capable of handling rotating azimuths is presented. The problem formulation accounts for magnitude and rate constraints on both thruster forces and azimuth angles. The advantage of this formulation is that the solution can be found with a finite number of iterations for each time step. Experiments with a model ship are used to validate the thrust allocation system.

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Despite the wide array of contemporary advertising formats and media, television advertising remains the most dominant form to which typical consumers are exposed. Research on attitudes toward advertising in general (Att-AiG) implicitly assumes that the Att-AiG measure represents advertising as a whole. A major finding of the current research is that consumers tend to have a mental representation, or exemplar, of the most typical type of advertising—television advertising—when they report their Att-AiG. Therefore, in reality, Att-AiG primarily reflects attitudes toward television advertising. In addition, the results of our experiments indicate that television ad exemplars generate temporal changes in consumers’ reported Att-AiG and attitudes toward television advertising. Theoretical and practical implications are discussed.

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Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making

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It is extremely important to ensure that people with disabilities can access information and cultural works on an equal basis with others. Access is fundamentally important to enable people with disabilities to fully participate in economic, social, and political life. This is both a pressing moral imperative and a legal requirement in international law. Australia should take clear steps to affirmatively redress the fundamental inequalities of access that people with disabilities face. This requires a fundamental shift in the way that we think about copyright and disability rights: the mechanisms for enabling access should not be a limited exception to normal distribution, but should instead be strong positive rights that are able to be routinely and practically exercised.

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The detection of line-like features in images finds many applications in microanalysis. Actin fibers, microtubules, neurites, pilis, DNA, and other biological structures all come up as tenuous curved lines in microscopy images. A reliable tracing method that preserves the integrity and details of these structures is particularly important for quantitative analyses. We have developed a new image transform called the "Coalescing Shortest Path Image Transform" with very encouraging properties. Our scheme efficiently combines information from an extensive collection of shortest paths in the image to delineate even very weak linear features. © Copyright Microscopy Society of America 2011.

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Preneel, Govaerts and Vandewalle (PGV) analysed the security of single-block-length block cipher based compression functions assuming that the underlying block cipher has no weaknesses. They showed that 12 out of 64 possible compression functions are collision and (second) preimage resistant. Black, Rogaway and Shrimpton formally proved this result in the ideal cipher model. However, in the indifferentiability security framework introduced by Maurer, Renner and Holenstein, all these 12 schemes are easily differentiable from a fixed input-length random oracle (FIL-RO) even when their underlying block cipher is ideal. We address the problem of building indifferentiable compression functions from the PGV compression functions. We consider a general form of 64 PGV compression functions and replace the linear feed-forward operation in this generic PGV compression function with an ideal block cipher independent of the one used in the generic PGV construction. This modified construction is called a generic modified PGV (MPGV). We analyse indifferentiability of the generic MPGV construction in the ideal cipher model and show that 12 out of 64 MPGV compression functions in this framework are indifferentiable from a FIL-RO. To our knowledge, this is the first result showing that two independent block ciphers are sufficient to design indifferentiable single-block-length compression functions.

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Protein molecular motors are natural nano-machines that convert the chemical energy from the hydrolysis of adenosine triphosphate into mechanical work. These efficient machines are central to many biological processes, including cellular motion, muscle contraction and cell division. The remarkable energetic efficiency of the protein molecular motors coupled with their nano-scale has prompted an increasing number of studies focusing on their integration in hybrid micro- and nanodevices, in particular using linear molecular motors. The translation of these tentative devices into technologically and economically feasible ones requires an engineering, design-orientated approach based on a structured formalism, preferably mathematical. This contribution reviews the present state of the art in the modelling of protein linear molecular motors, as relevant to the future design-orientated development of hybrid dynamic nanodevices. © 2009 The Royal Society of Chemistry.

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Protein adsorption at solid-liquid interfaces is critical to many applications, including biomaterials, protein microarrays and lab-on-a-chip devices. Despite this general interest, and a large amount of research in the last half a century, protein adsorption cannot be predicted with an engineering level, design-orientated accuracy. Here we describe a Biomolecular Adsorption Database (BAD), freely available online, which archives the published protein adsorption data. Piecewise linear regression with breakpoint applied to the data in the BAD suggests that the input variables to protein adsorption, i.e., protein concentration in solution; protein descriptors derived from primary structure (number of residues, global protein hydrophobicity and range of amino acid hydrophobicity, isoelectric point); surface descriptors (contact angle); and fluid environment descriptors (pH, ionic strength), correlate well with the output variable-the protein concentration on the surface. Furthermore, neural network analysis revealed that the size of the BAD makes it sufficiently representative, with a neural network-based predictive error of 5% or less. Interestingly, a consistently better fit is obtained if the BAD is divided in two separate sub-sets representing protein adsorption on hydrophilic and hydrophobic surfaces, respectively. Based on these findings, selected entries from the BAD have been used to construct neural network-based estimation routines, which predict the amount of adsorbed protein, the thickness of the adsorbed layer and the surface tension of the protein-covered surface. While the BAD is of general interest, the prediction of the thickness and the surface tension of the protein-covered layers are of particular relevance to the design of microfluidics devices.

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