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Sökning: L773:1673 1581

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1.
  • Chen, Li-li, et al. (författare)
  • Multilayered polyelectrolyte-coated gold nanorods as multifunctional optical contrast agents for cancer cell imaging
  • 2010
  • Ingår i: Journal of Zhejiang University: Science B. - 1673-1581. ; 11:6, s. 417-422
  • Tidskriftsartikel (refereegranskat)abstract
    • We report the application of multilayered polyelectrolyte-coated gold nanorods (GNRs) as multifunctional optical contrast agents for cancer cell imaging. The surface modification of GNRs improves their chemical stability and facilitates them to be taken up by cancer cells through electrostatic interaction. The unique longitudinal surface plasmon resonance property of GNRs makes them suitable as both "scattering contrast agents" and "Raman contrast agents". In our experiments, the staining of GNRs in cells was further confirmed by dark field microscopy and Raman microscopy. Our experiment results indicated that GNRs have great potential as multifunctional "optical contrast agents" for future in vivo animal imaging.
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2.
  • Liljenström, Hans (författare)
  • A biologically inspired model for pattern recognition
  • 2010
  • Ingår i: Journal of Zhejiang University Science B. - 1673-1581 .- 1862-1783. ; 11, s. 115-126
  • Tidskriftsartikel (refereegranskat)abstract
    • In this paper, a novel bionic model and its performance in pattern recognition are presented and discussed. The model is constructed from a bulb model and a three-layered cortical model, mimicking the main features of the olfactory system. The olfactory bulb and cortex models are connected by feedforward and feedback fibers with distributed delays. The Breast Cancer Wisconsin dataset consisting of data from 683 patients divided into benign and malignant classes is used to demonstrate the capacity of the model to learn and recognize patterns, even when these are deformed versions of the originally learned patterns. The performance of the novel model was compared with three artificial neural networks (ANNs), a back-propagation network, a support vector machine classifier, and a radial basis function classifier. All the ANNs and the olfactory bionic model were tested in a benchmark study of a standard dataset. Experimental results show that the bionic olfactory system model can learn and classify patterns based on a small training set and a few learning trials to reflect biological intelligence to some extent
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  • Resultat 1-2 av 2
Typ av publikation
tidskriftsartikel (2)
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refereegranskat (2)
Författare/redaktör
Liljenström, Hans (1)
He, Sailing (1)
Qian, Jun (1)
Jiang, Li (1)
Chen, Li-li (1)
Wang, Ya-lun (1)
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Kungliga Tekniska Högskolan (1)
Sveriges Lantbruksuniversitet (1)
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Engelska (2)
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Lantbruksvetenskap (1)
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2010 (2)

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