101 resultados para Complex polymerization method


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Block copolymers have become an integral part of the preparation of complex architectures through self-assembly. The use of reversible addition-fragmentation chain transfer (RAFT) allows blocks ranging from functional to nonfunctional polymers to be made with predictable molecular weight distributions. This article models block formation by varying many of the kinetic parameters. The simulations provide insight into the overall polydispersities (PDIs) that will be obtained when the chain-transfer constants in the main equilibrium steps are varied from 100 to 0.5. When the first dormant block [polymer-S-C(Z)=S] has a PDI of 1 and the second propagating radical has a low reactivity to the RAFT moiety, the overall PDI will be greater than 1 and dependent on the weight fraction of each block. When the first block has a PDI of 2 and the second propagating radical has a low reactivity to the RAFT moiety, the PDI will decrease to around 1.5 because of random coupling of two broad distributions. It is also shown how we can in principle use only one RAFT agent to obtain block copolymers with any desired molecular weight distribution. We can accomplish this by maintaining the monomer concentration at a constant level in the reactor over the course of the reaction. (c) 2005 Wiley Periodicals, Inc.

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Living radical polymerization has allowed complex polymer architectures to be synthesized in bulk, solution, and water. The most versatile of these techniques is reversible addition-fragmentation chain transfer (RAFT), which allows a wide range of functional and nonfunctional polymers to be made with predictable molecular weight distributions (MWDs), ranging from very narrow to quite broad. The great complexity of the RAFT mechanism and how the kinetic parameters affect the rate of polymerization and MWD are not obvious. Therefore, the aim of this article is to provide useful insights into the important kinetic parameters that control the rate of polymerization and the evolution of the MWD with conversion. We discuss how a change in the chain-transfer constant can affect the evolution of the MWD. It is shown how we can, in principle, use only one RAFT agent to obtain a poly-mer with any MWD. Retardation and inhibition are discussed in terms of (1) the leaving R group reactivity and (2) the intermediate radical termination model versus the slow fragmentation model. (c) 2005 Wiley Periodicals, Inc.

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Sustainable management of coastal and coral reef environments requires regular collection of accurate information on recognized ecosystem health indicators. Satellite image data and derived maps of water column and substrate biophysical properties provide an opportunity to develop baseline mapping and monitoring programs for coastal and coral reef ecosystem health indicators. A significant challenge for satellite image data in coastal and coral reef water bodies is the mixture of both clear and turbid waters. A new approach is presented in this paper to enable production of water quality and substrate cover type maps, linked to a field based coastal ecosystem health indicator monitoring program, for use in turbid to clear coastal and coral reef waters. An optimized optical domain method was applied to map selected water quality (Secchi depth, Kd PAR, tripton, CDOM) and substrate cover type (seagrass, algae, sand) parameters. The approach is demonstrated using commercially available Landsat 7 Enhanced Thematic Mapper image data over a coastal embayment exhibiting the range of substrate cover types and water quality conditions commonly found in sub-tropical and tropical coastal environments. Spatially extensive and quantitative maps of selected water quality and substrate cover parameters were produced for the study site. These map products were refined by interactions with management agencies to suit the information requirements of their monitoring and management programs. (c) 2004 Elsevier Ltd. All rights reserved.

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We present experimental results on the measurement of fidelity decay under contrasting system dynamics using a nuclear magnetic resonance quantum information processor. The measurements were performed by implementing a scalable circuit in the model of deterministic quantum computation with only one quantum bit. The results show measurable differences between regular and complex behavior and for complex dynamics are faithful to the expected theoretical decay rate. Moreover, we illustrate how the experimental method can be seen as an efficient way for either extracting coarse-grained information about the dynamics of a large system or measuring the decoherence rate from engineered environments.

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Time-harmonic methods are required in the accurate design of RF coils as operating frequency increases. This paper presents such a method to find a current density solution on the coil that will induce some desired magnetic field upon an asymmetrically located target region within. This inverse method appropriately considers the geometry of the coil via a Fourier series expansion, and incorporates some new regularization penalty functions in the solution process. A new technique is introduced by which the complex, time-dependent current density solution is approximated by a static coil winding pattern. Several winding pattern solutions are given, with more complex winding patterns corresponding to more desirable induced magnetic fields.

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Temperature is an important parameter controlling protein crystal growth. A new temperature-screening system (Thermo-screen) is described consisting of a gradient thermocycler fitted with a special crystallization-plate adapter onto which a 192-well sitting-drop crystallization plate can be mounted (temperature range 277-372 K; maximum temperature gradient 20 K; interval precision 0.3 K). The system allows 16 different conditions to be monitored simultaneously over a range of 12 temperatures and is well suited to conduct wide (similar to 20 K) and fine (similar to 3 K) temperature-optimization screens. It can potentially aid in the determination of temperature phase diagrams and run more complex temperature-cycling experiments for seeding and crystal growth.

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Background The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease. Results We show that GPNN has high power to detect even relatively small genetic effects (2–3% heritability) in simulated data models involving two and three locus interactions. The limits of detection were reached under conditions with very small heritability (

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Background: The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease. Results: We show that GPNN has high power to detect even relatively small genetic effects (2-3% heritability) in simulated data models involving two and three locus interactions. The limits of detection were reached under conditions with very small heritability (

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Univariate linkage analysis is used routinely to localise genes for human complex traits. Often, many traits are analysed but the significance of linkage for each trait is not corrected for multiple trait testing, which increases the experiment-wise type-I error rate. In addition, univariate analyses do not realise the full power provided by multivariate data sets. Multivariate linkage is the ideal solution but it is computationally intensive, so genome-wide analysis and evaluation of empirical significance are often prohibitive. We describe two simple methods that efficiently alleviate these caveats by combining P-values from multiple univariate linkage analyses. The first method estimates empirical pointwise and genome-wide significance between one trait and one marker when multiple traits have been tested. It is as robust as an appropriate Bonferroni adjustment, with the advantage that no assumptions are required about the number of independent tests performed. The second method estimates the significance of linkage between multiple traits and one marker and, therefore, it can be used to localise regions that harbour pleiotropic quantitative trait loci (QTL). We show that this method has greater power than individual univariate analyses to detect a pleiotropic QTL across different situations. In addition, when traits are moderately correlated and the QTL influences all traits, it can outperform formal multivariate VC analysis. This approach is computationally feasible for any number of traits and was not affected by the residual correlation between traits. We illustrate the utility of our approach with a genome scan of three asthma traits measured in families with a twin proband.

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This paper evaluates a low-frequency FDTD method applied to the problem of induced E-fields/eddy currents in the human body resulting from the pulsed magnetic field gradients in MRI. In this algorithm, a distributed equivalent magnetic current (DEMC) is proposed as the electromagnetic source and is obtained by quasistatic calculation of the empty coil's vector potential or measurements therein. This technique circumvents the discretizing of complicated gradient coil geometries into a mesh of Yee cells, and thereby enables any type of gradient coil modeling or other complex low frequency sources. The proposed method has been verified against an example with an analytical solution. Results are presented showing the spatial distribution of gradient-induced electric fields in a multilayered spherical phantom model and a complete body model.

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The Equilibrium Flux Method [1] is a kinetic theory based finite volume method for calculating the flow of a compressible ideal gas. It is shown here that, in effect, the method solves the Euler equations with added pseudo-dissipative terms and that it is a natural upwinding scheme. The method can be easily modified so that the flow of a chemically reacting gas mixture can be calculated. Results from the method for a one-dimensional non-equilibrium reacting flow are shown to agree well with a conventional continuum solution. Results are also presented for the calculation of a plane two-dimensional flow, at hypersonic speed, of a dissociating gas around a blunt-nosed body.

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Nine individuals with complex language deficits following left-hemisphere cortical lesions and a matched control group (n 5 9) performed speeded lexical decisions on the third word of auditory word triplets containing a lexical ambiguity. The critical conditions were concordant (e.g., coin–bank–money), discordant (e.g., river–bank–money), neutral (e.g., day–bank– money), and unrelated (e.g., river–day–money). Triplets were presented with an interstimulus interval (ISI) of 100 and 1250 ms. Overall, the left-hemisphere-damaged subjects appeared able to exhaustively access meanings for lexical ambiguities rapidly, but were unable to reduce the level of activation for contextually inappropriate meanings at both short and long ISIs, unlike control subjects. These findings are consistent with a disruption of the proposed role of the left hemisphere in selecting and suppressing meanings via contextual integration and a sparing of the right-hemisphere mechanisms responsible for maintaining alternative meanings.

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The level set method has been implemented in a computational volcanology context. New techniques are presented to solve the advection equation and the reinitialisation equation. These techniques are based upon an algorithm developed in the finite difference context, but are modified to take advantage of the robustness of the finite element method. The resulting algorithm is tested on a well documented Rayleigh–Taylor instability benchmark [19], and on an axisymmetric problem where the analytical solution is known. Finally, the algorithm is applied to a basic study of lava dome growth.

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Inaccurate species identification confounds insect ecological studies. Examining aspects of Trichogramma ecology pertinent to the novel insect resistance management strategy for future transgenic cotton, Gossypium hirsutum L., production in the Ord River Irrigation Area (ORIA) of Western Australia required accurate differentiation between morphologically similar Trichogramma species. Established molecular diagnostic methods for Trichogramma identification use species-specific sequence difference in the internal transcribed spacer (ITS)-2 chromosomal region; yet, difficulties arise discerning polymerase chain reaction (PCR) fragments of similar base pair length by gel electrophoresis. This necessitates the restriction enzyme digestion of PCR-amplified ITS-2 fragments to readily differentiate Trichogramma australicum Girault and Trichogramma pretiosum Riley. To overcome the time and expense associated with a two-step diagnostic procedure, we developed a “one-step” multiplex PCR technique using species-specific primers designed to the ITS-2 region. This approach allowed for a high-throughput analysis of samples as part of ongoing ecological studies examining Trichogramma biological control potential in the ORIA where these two species occur in sympatry.

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The differences in spectral shape resolution abilities among cochlear implant ~CI! listeners, and between CI and normal-hearing ~NH! listeners, when listening with the same number of channels ~12!, was investigated. In addition, the effect of the number of channels on spectral shape resolution was examined. The stimuli were rippled noise signals with various ripple frequency-spacings. An adaptive 4IFC procedure was used to determine the threshold for resolvable ripple spacing, which was the spacing at which an interchange in peak and valley positions could be discriminated. The results showed poorer spectral shape resolution in CI compared to NH listeners ~average thresholds of approximately 3000 and 400 Hz, respectively!, and wide variability among CI listeners ~range of approximately 800 to 8000 Hz!. There was a significant relationship between spectral shape resolution and vowel recognition. The spectral shape resolution thresholds of NH listeners increased as the number of channels increased from 1 to 16, while the CI listeners showed a performance plateau at 4–6 channels, which is consistent with previous results using speech recognition measures. These results indicate that this test may provide a measure of CI performance which is time efficient and non-linguistic, and therefore, if verified, may provide a useful contribution to the prediction of speech perception in adults and children who use CIs.