Fabrication of large area diffraction grating using LIGA process

X-ray imaging is a very important technology in the fields of medical, biological, inspection, material science, etc. However, it is not enough to get the clear X-ray imaging with low absorbance. We have produced a diffraction gratings for obtaining high resolution X-ray phase imaging, such as X-ray Talbot interferometer. In this X-ray Talbot interferometer, diffraction gratings were required to have a fine, high accuracy, high aspect ratio structure. Then, we succeeded to fabricate a high aspect ratio diffraction grating with a pitch of 8 μm and small area using a deep X-ray lithography technique. We discuss that the diffraction gratings having a narrow pitch and an large effective area to obtain imaging size of practical use in medical application. If the pitch of diffraction gratings were narrow, it is expected high resolution imaging for X-ray Talbot interferometer. We succeeded and fabricated the diffraction grating with pitch of 5.3 μm, Au height of 28 μm and an effective area of 60 × 60 mm².     

Nonequilibrium dynamics of a reacting network system

The nonlinear nonequilibrium properties of reacting network systems are studied by computer simulations. It is shown that the fluctuation in the population of each chemical species obeys a log-normal distribution, not the normal Gaussian distribution. The reaction rate shows power-law decay with activation cost (energy), not the Arrhenius-type exponential decay observed in a linear nonequilibrium regime. These two characteristic features will explain the diversity, plasticity, and adaptivity observed in complex biological reaction networks. This work was presented in part at the 13th International Symposium on Artifical Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Closed-form forward kinematics solutions of a 4-DOF parallel robot

It is well known that the forward kinematics of parallel robots is a very difficult problem. Closed-form forward kinematics solutions have been reported only to a few special classes of parallel robots. This paper presents closed-form forward kinematics solutions of a 4-DOF parallel robot H4. A 16th order polynomial in a single variable is derived to solve the forward kinematics of the H4. The 16 roots of the polynomial lead to at most 16 different forward kinematics solutions. A numerical verification is also presented.     

Stabilization of geometrically nonlinear topology optimization by the Levenberg–Marquardt method

This paper deals with the design of compliant mechanisms in a continuum-based finite-element representation. Because the displacements of mechanisms are intrinsically large, the geometric nonlinearity is essential for designing such mechanisms. However, the consideration of the geometric nonlinearity may cause some instability in topology optimization. The problem is in the analysis part but not in the optimization part. To alleviate the analysis problem and eventually stabilize the optimization process, this paper proposes to apply the Levenberg–Marquardt method to the nonlinear analysis of compliant mechanisms.     

High-temperature oxidation of Al-deposited stainless-steel foils

The oxidation resistance of Al-deposited Fe–Cr–Al foils containing small amounts of La and Ce was assessed by a cyclic oxidation test with temperature varying between room temperature and 1323 K to 1423 K in static air. (1) The Al content of Fe–Cr–Al–La, Ce foils can be increased by depositing an Al layer from the vapor phase. The deposition of a 1-m-thick Al layer on both sides of the 50-m-thick foil is equivalent to a 1.5 mass% increase in the Al content. The deposited Al diffuses into the foil during heat treatment. The uniform distribution of Al is obtained by heating at 1273 K for 18 ks. (2) After the initial transition stage the oxidation follows the parabolic law until breakaway sets in. The scale consists mainly of -Al₂O₃ during the parabolic period. (3) The increase in the Al content by more than 5 mass% by the Al-deposition remarkably improves high-temperature oxidation resistance (smaller parabolic rate constant and longer protection time). (4) The Al-deposited foils have better oxidation resistance than the conventional foils with the same contents of Al and rare-earth elements. This is attributable to the different nature of the initially formed oxide on the Al-deposited foil. (5) The so-called rare-earth element effect was also observed for the Al-deposited foils. Predominant diffusion of oxygen through the Al₂O₃ scale and vacancy-sink mechanism are applicable to the present results.     

A study of Q-learning considering negative rewards

In the reinforcement learning system, the agent obtains a positive reward, such as 1, when it achieves its goal. Positive rewards are propagated around the goal area, and the agent gradually succeeds in reaching its goal. If you want to avoid certain situations, such as dangerous places or poison, you might want to give a negative reward to the agent. However, in conventional Q-learning, negative rewards are not propagated in more than one state. In this article, we propose a new way to propagate negative rewards. This is a very simple and efficient technique for Q-learning. Finally, we show the results of computer simulations and the effectiveness of the proposed method.     

Enhancing integrated earthquake simulation with high performance computing

Integrated earthquake simulation (IES) is a seamless simulation of the three earthquake processes, namely, the earthquake hazard process, the earthquake disaster process and the anti-disaster action process. High performance computing (HPC) is essential if IES, or particularly, the simulation of the earthquake disaster process is applied to an urban area in which 10^4∼6 structures are located. IES is enhanced with parallel computation, and its performance is examined, so that virtual earthquake disaster simulation will be made for a model of an actual city by inputting observed strong ground motion. It is shown that parallel IES has fairly good scalability even when advanced non-linear seismic structure analysis is used.     

Unravel four hairpins!

DNA machines consisting of consecutive hairpins, which we have previously described, have various potential applications in DNA computation. In the present study, a 288-base DNA machine containing four consecutive hairpins was successfully constructed by ligation and PCR. PAGE and fluorescence spectroscopy experiments verified that all four hairpins were successfully opened by four opener oligomers, and that hairpin opening was dependent on the proper openers added in the correct order. Quantitative analysis of the final results by fluorescence spectroscopy indicated that all four hairpins were open in about 1/4 to 1/3 of the DNA machines.     

Cooperation of categorical and behavioral learning in a practical solution to the abstraction problem

Real robots should be able to adapt autonomously to various environments in order to go on executing their tasks without breaking down. They achieve this by learning how to abstract only useful information from a huge amount of information in the environment while executing their tasks. This paper proposes a new architecture which performs categorical learning and behavioral learning in parallel with task execution. We call the architectureSituation Transition Network System (STNS). In categorical learning, it makes a flexible state representation and modifies it according to the results of behaviors. Behavioral learning is reinforcement learning on the state representation. Simulation results have shown that this architecture is able to learn efficiently and adapt to unexpected changes of the environment autonomously. Atsushi Ueno, Ph.D.: He is a research associate in the Artificial Intelligence Laboratory at the Graduate School of Information Science at the Nara Institute of Science and Technology (NAIST). He received the B.E., the M.E., and the Ph.D. degrees in aeronautics and astronautics from the University of Tokyo in 1991, 1993, and 1997 respectively. His research interest is robot learning and autonomous systems. He is a member of Japan Association for Artificial Intelligence (JSAI). Hideaki Takeda, Ph.D.: He is an associate professor in the Artificial Intelligence Laboratory at the Graduate School of Information Science at the Nara Institute of Science and Technology (NAIST). He received his Ph.D. in precision machinery engineering from the University of Tokyo in 1991. He has conducted research on a theory of intelligent computer-aided design systems, in particular experimental study and logical formalization of engineering design. He is also interested in multiagent architectures and ontologies for knowledge base systems.