Accumulated Charge Profile in Polyethylene during Fast Electron Irradiations

Space charge profile and consequent field strength profile were obtained by solving the continuity and Poisson's simultaneous equations. Experimental electron deposition curve and radiation-induced conductivity curve were used for calculation. The calculated results explained well the observed replacement current and electrical breakdown phenomena. Dose rate, dose, and temperature effects on charge accumulation were also investigated.     

Optogalvanic spectroscopy using 389 nm coherent light source accurately tuned to resonance frequency of 2S->3P of He

An efficient 389 nm coherent light source, made possible through the single-pass second-harmonic generation of a picosecond Ti:sapphire laser with a periodically poled lithium niobate waveguide, was developed for the metastability exchange optical pumping of hyperpolarized ³He gas, which is applicable to imaging with nuclear magnetic resonance. The second-harmonic light provided such a broad spectrum that some split sub-levels of its metastable state under an applied magnetic field could be pumped efficiently and simultaneously. Optogalvanic spectroscopy using the light source indicated that the spectral width of ³He was much less than 70 GHz, which was similar to the spectral width of the light source.     

Development of compact CW-IR laser deposition system for high-throughput growth of organic single crystals

We developed a compact continuous-wave infrared (CW-IR) laser deposition system for the high-throughput growth of organic single crystals. In this system, two CW-IR lasers are used for the sample heating and thermal evaporation of materials. The CW-IR laser heating is simple and allows good control of the deposition rate and growth temperature, in response to the on/off laser switching. Six samples can be loaded simultaneously in a chamber, which allows one-by-one sequential deposition for high-throughput experiments, without breaking the vacuum. Using this setup, we studied the effect of ionic liquids on the growth of C₆₀ crystals in vacuum.     

Adaptability analysis of genetic network programming with reinforcement learning in dynamically changing environments

Genetic network programming (GNP) has been proposed as one of the evolutionary algorithms and extended with reinforcement learning (GNP-RL). The combination of evolution and learning can efficiently evolve programs and the fitness improvement has been confirmed in the simulations of tileworld problems, elevator group supervisory control systems, stock trading models and wall following behavior of Khepera robot. However, its adaptability in testing environments, where the situations dynamically change, has not been analyzed in detail yet. In this paper, the adaptation mechanism in the testing environment is introduced and it is confirmed that GNP-RL can adapt to the environmental changes using a robot simulator WEBOTS, especially when unexperienced sensor troubles suddenly occur. The simulation results show that GNP-RL works well in the testing even if wrong sensor information is given because GNP-RL has a function to automatically change programs using alternative actions. In addition, the analysis on the effects of the parameters of GNP-RL is carried out in both training and testing simulations.     

Genetic relation algorithm with guided mutation for the large-scale portfolio optimization

The survey of the relevant literatures shows that there have been many studies for portfolio optimization problems and that the number of studies which have investigated the optimum portfolio using evolutionary computation is quite large. But, almost none of these studies deals with genetic relation algorithm (GRA), where GRA is one of the evolutionary methods with graph structure. This study presents an approach to large-scale portfolio optimization problems using GRA with a new operator, called guided mutation. In order to pick up the most efficient portfolio, GRA considers the correlation coefficient between stock brands as strength, which indicates the relation between nodes in each individual of GRA. Guided mutation generates offspring according to the average value of correlation coefficients in each individual, which means to enhance the exploitation ability of evolution of GRA. A genetic relation algorithm with guided mutation (GRA/G) for the portfolio optimization is proposed in this paper. Genetic network programming (GNP), which was proposed in our previous research, is used to validate the performance of the portfolio generated with GRA/G. The results show that GRA/G approach is successful in portfolio optimization.     

Synthesis and bio-applications of carbohydrate–gold nanoconjugates with nanoparticle and nanolayer forms

Carbohydrate-conjugated gold nanoparticles (GNPs) and gold nanolayers (GNLs), which have recently attracted increasing attention as innovative nano-biomaterials, were successfully synthesized using carbohydrate thiosemicarbazones in an aqueous N-methylmorpholine N-oxide (NMMO) system. This system can dissolve various types of carbohydrates including structural polysaccharides, e.g., cellulose. We observed that oxidative NMMO solvent unexpectedly promoted the immediate reduction of [Au^IIICl₄]^– species to nanosized metallic Au⁰, that is GNP. One possible mechanism is that the chloride ligand was oxidized to chlorate via the formation of a hypochlorite intermediate. Site-selective S-labeling of sugar reducing ends with thiosemicarbazide may have enabled regulated self-assembly immobilization to the surfaces of GNPs and GNLs. The carbohydrate–gold nanoconjugates possess unique nanoarchitectures and biofunctions for carbohydrate–cell interactions. Novel and simple approaches for the structural design of carbohydrate-decorated GNPs and GNLs in the NMMO system have potential to inspire a new phase in glyco-biomaterials engineering.