Browsing by Author "Hsu, Wei-Lun"

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Control of the Metal-Insulator Transition at Complex Oxide Heterointerfaces through Visible Light
(2016-01-27)
Lin, Jheng-Cyuan
;
Vu Thanh Tra
;
Tsai, Dung-Sheng
;
Lin, Tai-Te
;
Huang, Po-Cheng
The coupling of the localized surface plasmon resonance of Au nanoparticles is utilized to deliver a visible-light stimulus to control conduction at the LaAlO3/SrTiO3 interface. A giant photoresponse and the controllable metal-insulator transition are characterized at this heterointerface. This study paves a new route to optical control of the functionality at the heterointerfaces.
Flexible UV-Ozone-Modified Carbon Nanotube Electrodes for Neuronal Recording
(2010-05-18)
Hsu, Hui-Lin
;
Teng, I-Ju
;
Chen, Yung-Chan
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Hsu, Wei-Lun
;
Lee, Yu-Tao
Carbon nanotubes were grown on flexible polyimide substrates at temperatures below 400 degrees C as electrodes for extracellularly neuronal recording. The electrical charge-transfer and electrochemical properties of such CNT electrodes were enhanced by UV-ozone exposure, which induced the formation of C-O, C=O, and O-C=O bonds and reduced the CNT/electrolyte interfacial impedance while increasing the interfacial capacitance.
Learning to Select Actions in StarCraft with Genetic Algorithms
(2016-01-01)
Hsu, Wei-Lun
;
Chen, Ying-ping
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資訊工程學系
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Department of Computer Science
In numerous different types of games, the real-time strategy (RTS) ones have always been the focus of gaming competitions, and in this regard, StarCraft can arguably he considered a classic real-time strategy game. Currently, most of the artificial intelligence (AI) players for real-time strategy games cannot reach or get close to the same intelligent level of their human opponents. In order to enhance the ability of AI players and hence improve the playability of games, in this study, we make an attempt to develop for StarCraft a mechanism learning to select an appropriate action to take according to the circumstance. Our empirical results show that action selection can be learned by AI players with the optimization capability of genetic algorithms and that cooperation among identical and/or different types of units is observed. The potential future work and possible research directions are discussed. The developed source code and the obtained results are released as open source.
On the relationship between the protein structure and protein dynamics
(2008-08-01)
Lu, Chih-Hao
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Huang, Shao-Wei
;
Lai, Yan-Long
;
Lin, Chih-Peng
;
Shih, Chien-Hua
Recently, we have developed a method (Shih et al., Proteins: Structure, Function, and Bioinformatics 2007,68: 34-38) to compute correlation of fluctuations of proteins. This method, referred to as the protein fixed-point (PFP) model, is based on the positional vectors of atoms issuing from the fixed point, which is the point of the least fluctuations in proteins. One corollary from this model is that atoms lying on the same shell centered at the fixed point will have the same thermal fluctuations. In practice, this model provides a convenient way to compute the average dynamical properties of proteins directly from the geometrical shapes of proteins without the need of any mechanical models, and hence no trajectory integration or sophisticated matrix operations are needed. As a result, it is more efficient than molecular dynamics simulation or normal mode analysis. Though in the previous study the PFP model has been successfully applied to a number of proteins of various folds, it is not clear to what extent this model will be applied. In this article, we have carried out the comprehensive analysis of the PFP model for a dataset comprising 972 high-resolution X-ray structures with pairwise sequence identity <= 25%. We found that in most cases the PFP model works well. However, in case of proteins comprising multiple domains, each domain should be treated separately as an independent dynamical module with its own fixed point, and in case of the protein complex comprising it number of subunits, if functioning as a biological unit, the whole complex should be considered as one single dynamical module with one fixed point. Under such considerations, the resultant correlation coefficient between the computed and the X-ray structural B-factors for the data set is 0.59 and 75% (727/972) of proteins with a correlation coefficient >= 0.5. Our result shows that the fixed-point model is indeed quite general and will be a useful tool for high throughput analysis of dynamical properties of proteins.
Proportion of solvent-exposed amino acids in a protein and rate of protein evolution
(2007-04-01)
Lin, Yeong-Shin
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Hsu, Wei-Lun
;
Hwang, Jenn-Kang
;
Li, Wen-Hsiung
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生物科技學系
Translational selection, including gene expression, protein abundance, and codon usage bias, has been suggested as the single dominant determinant of protein evolutionary rate in yeast. Here, we show that protein structure is also an important determinant. Buried residues, which are responsible for maintaining protein structure or are located on a stable interaction surface between 2 subunits, are usually under stronger evolutionary constraints than solvent-exposed residues. Our partial correlation analysis shows that, when whole proteins are included, the variance of evolutionary rate explained by the proportion of solvent-exposed residues (P-exposed) can reach two-thirds of that explained by translational selection, indicating that P-exposed is the most important determinant of protein evolutionary rate next only to translational selection. Our result suggests that proteins with many residues under selective constraint (e.g., maintaining structure or intermolecular interaction) tend to evolve slowly, supporting the "fitness (functional) density" hypothesis.