This study aims at the synthesis of Janus gold nanoparticles (Janus GNPs) with hydrophilic/hydrophobic faces by a simple ligand exchange reaction in an homogeneous system and at the elucidation of the self-assembled structures of the Janus GNPs in water. As hydrophilic surface ligands, we synthesized hexaethylene glycol (E6)-terminated thiolate ligands with C3, C7, or C11 alkyl chains, referred to as E6C3, E6C7, and E6C11, respectively. As a hydrophobic ligand, a butyl-headed thiolate ligand C4-E6C11, in which a C4 alkyl was introduced on the E6C11 terminus, was synthesized. The degree of segregation between the two ligands on the GNPs (5 nm in diameter) was examined by matrix-assisted laser desorption/ionization time-of fright mass spectrometry (MALDI-TOF MS) analysis. We found that the choice of immobilization methods, one-step or two-step addition of the two ligands to the GNP solution, crucially affects the degree of segregation. The two-step addition of a hydrophilic ligand (E6C3) followed by a hydrophobic ligand (C4-E6C11) produced a large degree of segregation on the GNPs, providing Janus-like GNPs. When dispersed in water, these Janus-like GNPs formed assemblies of ∼160 nm in diameter, whereas Domain GNPs, in which the two ligands formed partial domains on the surface, were precipitated even when the molar ratio of the hydrophilic ligand and the hydrophobic ligand on the surface of the NPs was almost 1:1. The assembled structure of the Janus-like GNPs in water was directly observed by pulsed coherent X-ray solution scattering using an X-ray free-electron laser, revealing irregular spherical structures with uneven surfaces.

We focus on the simple theme park problem, where there are two attractions and visitor agents which select their destination attraction based on congestion disregarding behavior and congestion avoiding behavior. According to the computer simulation, the result shows that the growth of individual congestion avoiding behavior is not always effective for improving global performance, and this phenomenon is caused by the oscillation of successive selection switching of the same destination by many congestion avoiding agents. Although the model and setting of this paper is simpler than other related works, we consider each phenomenon in those works has the same characteristic based on the ineffectiveness caused by the homogeneity of congestion avoiding behavior and information sharing.

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In many E-commerce sites, recommender systems, which provide personalized recommendation from among a large number of items, are recently introduced. Collaborative ltering is one of the most successful algorithms which provide recommendations using ratings of users on items. There are two approaches such as user-based and item-based collaborative ltering. Additionally a unifying method for userbased and item-based collaborative ltering was proposed to improve the recommendation accuracy.The unifying approach uses a constant value as a weight parameter to unify both algorithms. However, because the optimal weight for unifying is actually dierent by the situation, the algorithm should estimate an appropriate weight dynamically, and should use it. In this research, rst, we investigated the relationship between recommendation accuracy and the weight parameter. The results show the optimal weight is dierent depending on the situation. Second, we propose an approach for estimation of the appropriate weight value based on collected ratings. Then, we discussed the eectiveness of the proposed approach based on both multi-agent simulation and MovieLens dataset. The results show that the proposed approach can estimate the weight value within an error rate of 0.5% for the optimal weight.

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