830 resultados para Labeling hierarchical clustering


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The structural and morphological characteristics of InAs/GaAs radial nanowire heterostructures were investigated using transmission electron microscopy. It has been found that the radial growth of InAs was preferentially initiated on the { 112 } A sidewalls of GaAs nanowires. This preferential deposition leads to extraordinarily asymmetric InAs/GaAs radial nanowire heterostructures. Such formation of radial nanowire heterostructures provides an opportunity to engineer hierarchical nanostructures, which further widens the potential applications of semiconductor nanostructures. © 2008 American Institute of Physics.

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Semi-supervised clustering is the task of clustering data points into clusters where only a fraction of the points are labelled. The true number of clusters in the data is often unknown and most models require this parameter as an input. Dirichlet process mixture models are appealing as they can infer the number of clusters from the data. However, these models do not deal with high dimensional data well and can encounter difficulties in inference. We present a novel nonparameteric Bayesian kernel based method to cluster data points without the need to prespecify the number of clusters or to model complicated densities from which data points are assumed to be generated from. The key insight is to use determinants of submatrices of a kernel matrix as a measure of how close together a set of points are. We explore some theoretical properties of the model and derive a natural Gibbs based algorithm with MCMC hyperparameter learning. The model is implemented on a variety of synthetic and real world data sets.

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Hierarchical pillar arrays consisting of micrometer-sized polymer setae covered by carbon nanotubes are engineered to deliver the role of spatulae, mimicking the fibrillar adhesive surfaces of geckos. These biomimetic structures conform well and achieve better attachment to rough surfaces, providing a new platform for a variety of applications.

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Methyl parathion hydrolase (MPH) is an enzyme that catalyzes the degradation of methyl parathion, generating a yellow product with specific absorption at 405 nm. The application of MPH as a new labeling enzyme was illustrated in this study. The key advantages of using MPH as a labeling enzyme are as follows: (1) unlike alkaline phosphatase (AP), horseradish peroxidase (HRP), and glucose oxidase (GOD), MPH is rarely found in animal cells, and it therefore produces less background noise; (2) its active form in solution is the monomer, with a molecular weight of 37 kDa; (3) its turnover number is 114.70 +/- 13.19 s(-1), which is sufficiently high to yield a significant signal for sensitive detection; and (4) its 3D structure is known and its C-terminal that is exposed to the surface can be easily subjected to the construction of genetic engineering monocloning antibody-enzyme fusion for enzyme-linked immunosorbent assay (ELISA). To demonstrate its utility, MPH was ligated to an single-chain variable fragment (scFv), known as A1E, against a white spot syndrome virus (WSSV) with the insertion of a [-(Gly-Ser)(5)-] linker peptide. The resulting fusion protein MPH-A1E possessed both the binding specificity of the scFv segment and the catalytic activity of the MPH segment. When MPH-A1E was used as an ELISA reagent, 25 ng purified WSSV was detected; this was similar to the detection sensitivity obtained using A1E scFv and the HRP/Anti-E Tag Conjugate protocol. The fusion protein also recognized the WSSV in 1 mu L hemolymph from an infected shrimp and differentiated it from a healthy shrimp.

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Hierarchical pillar arrays consisting of micrometer-sized polymer setae covered by carbon nanotubes are engineered to deliver the role of spatulae, mimicking the fibrillar adhesive surfaces of geckos. These biomimetic structures conform well and achieve better attachment to rough surfaces, providing a new platform for a variety of applications. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Via the combination of an electrospinning method with a hydrothermal reaction, a large-scale cedar-like hierarchical nanostructured TiO2 film with an anatase/rutile composite phase was fabricated.

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The transmission of electrons through a hierarchical self-assembly of GaAs/AlxGa(1-)xAs quantum dots (QDs) is calculated using the coupled-channel recursion method. Our results reveal that the number of conductance peaks does not change when the barrier widths change, but the intensities decrease as the barrier widths increase. The conductance peaks will shift towards low Fermi energies as the transverse width of GaAs QD increases, as the thickness of GaAs quantum well increases, or as the height of GaAs QDs decreases. Our calculated results may be useful in the application of QDs to photoelectric devices. (c) 2005 American Institute of Physics.

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Quantum-confined Stark effects in GaAs/AlxGa1-xAs self-assembled quantum dots are investigated theoretically in the framework of effective-mass envelope function theory. The electron and hole energy levels and optical transition energies are calculated in the presence of an electric field in different directions. In our calculation, the effect of finite offset, valence-band mixing, the effects due to the different effective masses of electrons and holes in different regions, and the real quantum dot structures are all taken into account. The results show that the electron and hole energy levels and the optical transition energies can cause blueshifts when the electric field is applied along the opposite to the growth direction. Our calculated results are useful for the application of hierarchical self-assembly of GaAs/AlxGa1-xAs quantum dots to photoelectric devices. (c) 2005 American Institute of Physics.

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The electronic structures in the hierarchical self-assembly of GaAs/AlxGa1-xAs quantum dots are investigated theoretically in the framework of effective-mass envelope function theory. The electron and hole energy levels and optical transition energies are calculated. In our calculation, the effect of finite offset, valence-band mixing, the effects due to the different effective masses of electrons and holes in different regions, and the real quantum dot structures are all taken into account. The results show that (1) electronic energy levels decrease monotonically, and the energy difference between the energy levels increases as the GaAs quantum dot (QD) height increases; (2) strong state mixing is found between the different energy levels as the GaAs QD width changes; (3) the hole energy levels decrease more quickly than those of the electrons as the GaAs QD size increases; (4) in excited states, the hole energy levels are closer to each other than the electron ones; (5) the first heavy- and light-hole transition energies are very close. Our theoretical results agree well with the available experimental data. Our calculated results are useful for the application of the hierarchical self-assembly of GaAs/AlxGa1-xAs quantum dots to photoelectric devices.

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A hierarchical equations of motion formalism for a quantum dissipation system in a grand canonical bath ensemble surrounding is constructed on the basis of the calculus-on-path-integral algorithm, together with the parametrization of arbitrary non-Markovian bath that satisfies fluctuation-dissipation theorem. The influence functionals for both the fermion or boson bath interaction are found to be of the same path integral expression as the canonical bath, assuming they all satisfy the Gaussian statistics. However, the equation of motion formalism is different due to the fluctuation-dissipation theories that are distinct and used explicitly. The implications of the present work to quantum transport through molecular wires and electron transfer in complex molecular systems are discussed. (c) 2007 American Institute of Physics.

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