36 resultados para Biomedical Applications X

em University of Queensland eSpace - Australia


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Expanded polytetrafluoroethylene (ePTFE) membranes were modified by graft copolymerization with methacryloxyethyl phosphate (MOEP) in methanol and 2-butanone (methyl ethyl ketone (MEK)) at ambient temperature using gamma irradiation. The effect of dose rate (0.46 and 4.6 kGyh(-1)), monomer concentration (1-40 %) and solvent were studied and the modified membranes were characterized by weight increase, X-ray photoelectron spectroscopy (XPS), Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). XPS was used to determine the % degree of surface coverage using the C-F (ePTFE membrane) and the C-C (MOEP graft copolymer) peaks. Grafting yield, as well as surface coverage, were found to increase with increasing monomer concentration and were significantly higher for samples grafted in MEK than in methanol solution. SEM images showed distinctly different surface morphologies for the membranes grafted in methanol (smooth) and MEK (globular), hence indicating phase separation of the homopolymer in MEK. We propose that in our system, the non-solvent properties of MEK for the homopolymer play a more important role than solvent chain transfer reactions in determining grafting outcomes. (c) 2005 Society of Chemical Industry.

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Count data with excess zeros relative to a Poisson distribution are common in many biomedical applications. A popular approach to the analysis of such data is to use a zero-inflated Poisson (ZIP) regression model. Often, because of the hierarchical Study design or the data collection procedure, zero-inflation and lack of independence may occur simultaneously, which tender the standard ZIP model inadequate. To account for the preponderance of zero counts and the inherent correlation of observations, a class of multi-level ZIP regression model with random effects is presented. Model fitting is facilitated using an expectation-maximization algorithm, whereas variance components are estimated via residual maximum likelihood estimating equations. A score test for zero-inflation is also presented. The multi-level ZIP model is then generalized to cope with a more complex correlation structure. Application to the analysis of correlated count data from a longitudinal infant feeding study illustrates the usefulness of the approach.

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Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

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Spatial data has now been used extensively in the Web environment, providing online customized maps and supporting map-based applications. The full potential of Web-based spatial applications, however, has yet to be achieved due to performance issues related to the large sizes and high complexity of spatial data. In this paper, we introduce a multiresolution approach to spatial data management and query processing such that the database server can choose spatial data at the right resolution level for different Web applications. One highly desirable property of the proposed approach is that the server-side processing cost and network traffic can be reduced when the level of resolution required by applications are low. Another advantage is that our approach pushes complex multiresolution structures and algorithms into the spatial database engine. That is, the developer of spatial Web applications needs not to be concerned with such complexity. This paper explains the basic idea, technical feasibility and applications of multiresolution spatial databases.

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The field of protein crystallography inspires and enthrals, whether it be for the beauty and symmetry of a perfectly formed protein crystal, the unlocked secrets of a novel protein fold, or the precise atomic-level detail yielded from a protein-ligand complex. Since 1958, when the first protein structure was solved, there have been tremendous advances in all aspects of protein crystallography, from protein preparation and crystallisation through to diffraction data measurement and structure refinement. These advances have significantly reduced the time required to solve protein crystal structures, while at the same time substantially improving the quality and resolution of the resulting structures. Moreover, the technological developments have induced researchers to tackle ever more complex systems, including ribosomes and intact membrane-bound proteins, with a reasonable expectation of success. In this review, the steps involved in determining a protein crystal structure are described and the impact of recent methodological advances identified. Protein crystal structures have proved to be extraordinarily useful in medicinal chemistry research, particularly with respect to inhibitor design. The precise interaction between a drug and its receptor can be visualised at the molecular level using protein crystal structures, and this information then used to improve the complementarity and thus increase the potency and selectivity of an inhibitor. The use of protein crystal structures in receptor-based drug design is highlighted by (i) HIV protease, (ii) influenza virus neuraminidase and (iii) prostaglandin H-2-synthetase. These represent, respectively, examples of protein crystal structures that (i) influenced the design of drugs currently approved for use in the treatment of HIV infection, (ii) led to the design of compounds currently in clinical trials for the treatment of influenza infection and (iii) could enable the design of highly specific non-steroidal anti-inflammatory drugs that lack the common side-effects of this drug class.

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The structures of mixed Langmuir (floating) monolayers and Langmuir-Blodgett (LB) films of a phenanthroline-porphyrin with cadmium arachidate (PhenPor + CdAr) have been investigated by synchrotron X-ray grazing incidence diffraction (GIXD) and specular X-ray reflectivity (SXR). GIXD measurements of the floating monolayers showed only one peak, arising from the CdAr domains in the films, at a scattering angle of 21.5 degrees. This is consistent with a hexagonal structure (alpha = 4.77 Angstrom). The correlation length in these domains is 250 Angstrom. GMD measurements of the LB films, however, show two sets of diffraction features: one arises from CdAr domains with a rectangular in-plane structure (alpha = 7.44 Angstrom and b = 4.90 Angstrom) and a correlation length of 85 Angstrom; the other is from porphyrin domains with an oblique in-plane structure (alpha (p) 15.2 Angstrom, b(p) = 8.86 Angstrom, and gamma (p) = 80 degrees) and a correlation length of 105 Angstrom. These dimensions are consistent with the surface pressure-area isotherm measurements and indicate that the two components are immiscible. The thickness of the bilayer is 57 Angstrom, and there is no correlation between the bilayers. Introduction of a trigger compound does not alter the structure of the films but slightly increases the bilayer thickness. The SXR measurements of the floating monolayers also support the suggested immiscibility of the two components in the films.

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Most Internet search engines are keyword-based. They are not efficient for the queries where geographical location is important, such as finding hotels within an area or close to a place of interest. A natural interface for spatial searching is a map, which can be used not only to display locations of search results but also to assist forming search conditions. A map-based search engine requires a well-designed visual interface that is intuitive to use yet flexible and expressive enough to support various types of spatial queries as well as aspatial queries. Similar to hyperlinks for text and images in an HTML page, spatial objects in a map should support hyperlinks. Such an interface needs to be scalable with the size of the geographical regions and the number of websites it covers. In spite of handling typically a very large amount of spatial data, a map-based search interface should meet the expectation of fast response time for interactive applications. In this paper we discuss general requirements and the design for a new map-based web search interface, focusing on integration with the WWW and visual spatial query interface. A number of current and future research issues are discussed, and a prototype for the University of Queensland is presented. (C) 2001 Published by Elsevier Science Ltd.

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A method is presented for the systematic design of asymmetric zonal shim coils for magnetic resonance applications. Fourier-series methods are used to represent the magnetic field inside and outside a circular cylinder of length 2L and radius a. The current density on the cylinder is also represented using Fourier series. Any desired field can be specified in advance on the cylinder's radius, over some nonsymmetric portion pL

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New designs for force-minimized compact high-field clinical MRI magnets are described. The design method is a modified simulated annealing (SA) procedure which includes Maxwell forces in the error function to be minimized. This permits an automated force reduction in the magnet designs while controlling the overall dimensions of the system. As SA optimization requires many iterations to achieve a final design, it is important that each iteration in the procedure is rapid. We have therefore developed a rapid force calculation algorithm. Novel designs for short 3- and 4-T clinical MRI systems are presented in which force reduction has been invoked. The final designs provide large homogeneous regions and reduced stray fields in remarkable short magnets. A shielded 4-T design that is approximately 30% shorter than current designs is presented. This novel magnet generates a full 50-cm diameter homogeneous region.

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One of the most important advantages of database systems is that the underlying mathematics is rich enough to specify very complex operations with a small number of statements in the database language. This research covers an aspect of biological informatics that is the marriage of information technology and biology, involving the study of real-world phenomena using virtual plants derived from L-systems simulation. L-systems were introduced by Aristid Lindenmayer as a mathematical model of multicellular organisms. Not much consideration has been given to the problem of persistent storage for these simulations. Current procedures for querying data generated by L-systems for scientific experiments, simulations and measurements are also inadequate. To address these problems the research in this paper presents a generic process for data-modeling tools (L-DBM) between L-systems and database systems. This paper shows how L-system productions can be generically and automatically represented in database schemas and how a database can be populated from the L-system strings. This paper further describes the idea of pre-computing recursive structures in the data into derived attributes using compiler generation. A method to allow a correspondence between biologists' terms and compiler-generated terms in a biologist computing environment is supplied. Once the L-DBM gets any specific L-systems productions and its declarations, it can generate the specific schema for both simple correspondence terminology and also complex recursive structure data attributes and relationships.