Surface treatment of titanium dioxide nanopowder using rotary electrode dielectric barrier discharge reactor

Titanium dioxide (TiO2) nanopowder (P-25;Degussa AG) was treated using dielectric barrier discharge (DBD) in a rotary electrode DBD (RE-DBD) reactor.Its electrical and optical characteristics were investigated during RE-DBD generation.The treated TiO2 nanopowder properties and structures were analyzed using x-ray diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR).After RE-DBD treatment,XRD measurements indicated that the anatase peak theta positions shifted from 25.3° to 25.1°,which can be attributed to the substitution of new functional groups in the TiO2 lattice.The FTIR results show that hydroxyl groups (OH) at 3400 cm-1 increased considerably.The mechanism used to modify the TiO2 nanopowder surface by air DBD treatment was confirmed from optical emission spectrum measurements.Reactive species,such as OH radical,ozone and atomic oxygen can play key roles in hydroxyl formation on the TiO2 nanopowder surface.     

Polarity control of GaN epilayers grown on ZnO templates

We report the successful growth of Ga-polar GaN epilayers on O-polar ZnO templates pre-deposited on c-sapphire. Prior to GaN growth, NH₃ is exposed onto the ZnO template. The polarity of the GaN layers is confirmed by etching of the surface and by conversion beam electron diffraction (CBED), while the O-polar ZnO is confirmed by CBED. It is suggested that the NH₃ pre-exposure helps form a Zn₃N₂ layer, which possesses inversion symmetry and inverts the crystal from anion polar to cation polar.     

Level-of-Detail Rendering of Large-Scale Irregular Volume Datasets Using Particles

This paper describes a level-of-detail rendering technique for large-scale irregular volume datasets. It is well known that the memory bandwidth consumed by visibility sorting becomes the limiting factor when carrying out volume rendering of such datasets. To develop a sorting-free volume rendering technique, we previously proposed a particle-based technique that generates opaque and emissive particles using a density function constant within an irregular volume cell and projects the particles onto an image plane with sub-pixels. When the density function changes significantly in an irregular volume cell, the cell boundary may become prominent, which can cause blocky noise. When the number of the sub-pixels increases, the required frame buffer tends to be large. To solve this problem, this work proposes a new particle-based volume rendering which generates particles using metropolis sampling and renders the particles using the ensemble average. To confirm the effectiveness of this method, we applied our proposed technique to several irregular volume datasets, with the result that the ensemble average outperforms the sub-pixel average in computational complexity and memory usage. In addition, the ensemble average technique allowed us to implement a level of detail in the interactive rendering of a 71-million-cell hexahedral volume dataset and a 26-million-cell quadratic tetrahedral volume dataset.     

Particle-based multiple irregular volume rendering on CUDA

In this paper, we describe an improved particle-based volume rendering (PBVR) technique for previewing a large irregular volume dataset using the CUDA architecture. This technique allows for opaque and emissive particles to render translucent volumes without visibility sorting. Our GPU acceleration of PBVR provides the multi-volume rendering feature while remaining compatible with both regular and irregular volumes. We also reduce the memory cost required for storing all sub-pixel values by proposing a pixel repetition technique for a large sub-pixel level. By adjusting the repetition level, we achieved a very smooth level of detail (LOD) control for trading quality for speed. Our work demonstrates a full-detail rendering rate from 5 to 10 fps for irregular volume data with mega-scale cell numbers on an NVIDIA GeForce 8800GTS.     

Recurrent infomax generates cell assemblies, neuronal avalanches, and simple cell-like selectivity

Recently multineuronal recording has allowed us to observe patterned firings, synchronization, oscillation, and global state transitions in the recurrent networks of central nervous systems. We propose a learning algorithm based on the process of information maximization in a recurrent network, which we call recurrent infomax (RI). RI maximizes information retention and thereby minimizes information loss through time in a network. We find that feeding in external inputs consisting of information obtained from photographs of natural scenes into an RI-based model of a recurrent network results in the appearance of Gabor-like selectivity quite similar to that existing in simple cells of the primary visual cortex. We find that without external input, this network exhibits cell assembly-like and synfire chain-like spontaneous activity as well as a critical neuronal avalanche. In addition, we find that RI embeds externally input temporal firing patterns to the network so that it spontaneously reproduces these patterns after learning. RI provides a simple framework to explain a wide range of phenomena observed in in vivo and in vitro neuronal networks, and it will provide a novel understanding of experimental results for multineuronal activity and plasticity from an information-theoretic point of view.     

Platform design for large-scale artificial market simulation and preliminary evaluation on the K computer

Artificial market simulations have the potential to be a strong tool for studying rapid and large market fluctuations and designing financial regulations. High-frequency traders, that exchange multiple assets simultaneously within a millisecond, are said to be a cause of rapid and large market fluctuations. For such a large-scale problem, this paper proposes a software or computing platform for large-scale and high-frequency artificial market simulations (Plham: /pl\(\Lambda\)m). The computing platform, Plham, enables modeling financial markets composed of various brands of assets and a large number of agents trading on a short timescale. The design feature of Plham is the separation of artificial market models (simulation models) from their execution (execution models). This allows users to define their simulation models without parallel computing expertise and to choose one of the execution models they need. This computing platform provides a prototype execution model for parallel simulations, which exploits the variety in trading frequency among traders, that is, the fact that some traders do not require up-to-date information of markets changing in millisecond order. We evaluated a prototype implementation on the K computer using up to 256 computing nodes.     

Analysis of the electric field and force in an arrangement of a conducting sphere and a plane electrode with a dielectric barrier

This paper presents an analysis of the electric field and dielectrophoretic force in an arrangement consisting of an uncharged conducting sphere and a plane electrode with a dielectric barrier. The electric field is calculated by using the method of multipole images using an iterative algorithm proposed for calculating the images of the dielectric barrier of finite thickness. The calculation results show electric field intensification due to the presence of the dielectric barrier having higher permittivity, /spl epsiv//sub S/, than that of the surrounding medium, /spl epsiv//sub E/; however, if the barrier is separated from the conducting sphere by at least the sphere radius, its influence is negligible. Inside the dielectric barrier, the electric field on the axis of symmetry becomes more uniform and the average field significantly increases with decreasing its thickness. For a case where dielectric barrier is sufficiently thin, the electric field at the contact point and the force on the conducting sphere vary approximately as power functions of /spl epsiv//sub S///spl epsiv//sub E/.     

Improving withstand voltage by roughening the surface of an insulating spacer used in vacuum

This paper describes a simple and reliable method of improving the surface insulation strength of a spacer used in vacuum. The method is to roughen the spacer surface to an average roughness R/sub a/ higher than 1 or 2 /spl mu/m. The material of the spacer examined is SiO/sub 2/, PMMA, PTFE or Al/sub 2/O/sub 3/ and their shape is a right cylinder with 10 mm in height and 54 mm in diameter. The spacer is subjected to a ramped DC voltage and its surface charging is observed by using an electrostatic probe embedded in the cathode. It has been found that R/sub a/ decisively affects the charging, which decreases as R/sub a/ increases. Increasing R/sub a/ larger than about 2 /spl mu/m suppresses the charging until a higher applied voltage is reached, thus improving the insulation property.     

On a posteriori estimates of inverse operators for linear parabolic initial-boundary value problems

We present numerically verified a posteriori estimates of the norms of inverse operators for linear parabolic differential equations. In case that the corresponding elliptic operator is not coercive, existing methods for a priori estimates of the inverse operators are not accurate and, usually, exponentially increase in time variable. We propose a new technique for obtaining the estimates of the inverse operator by using the finite dimensional approximation and error estimates. It enables us to obtain very sharp bounds compared with a priori estimates. We will give some numerical examples which confirm the actual effectiveness of our method.