Novel CO2 Absorbents Using Lithium-Containing Oxide

We have discovered a series of lithium-containing oxides that immediately react with ambient carbon dioxide (CO₂) up to 700°C. The products react and return reversibly to the oxides at a temperatures higher than about 700°C. The absorption capacity surpasses that of other CO₂ absorbents by a factor of 10. Utilizing these absorbents, the possibility of a CO₂ separation system that operates at around 500°C is proposed. It is generally believed that a CO₂ separation process operable at temperatures higher than 500°C has the special benefit of a small energy penalty. Moreover, the absorption also proceeds at ambient temperature in the atmospheric environment. This property offers the possibility of many other applications, such as air cleaners or cartridges. Therefore, we think these materials have the potential to make a valuable contribution to the realization of CO₂ emission control.     

Superconductivity in the tetragonal phase of La1.9Bi0.1CuO4+δ annealed under high oxygen pressure

We have investigated the relation between the crystal structure and superconductivity in La_1.9Bi_0.1CuO₄₊ , in which the phase separation observed in La₂CuO₄₊ is suppressed. A phase diagram in theT– plane is given for La_1.9Bi_0.1CuO₄₊ with excess oxygen. For very small values, the crystal structure is orthorhombic, and an orthorhombic-tetragonal phase transition occurs markedly at 0.03 in the measured temperature range between 13 and 293 K. Superconductivity is observed in the range of 0.04<<0.11. This is clear evidence thathigh-T _c superconductivity also appears in the tetragonal phase.     

Fourier-transform speckle profilometry: three-dimensional shape measurements of diffuse objects with large height steps and/or spatially isolated surfaces

An interferometric technique for automated profilometry of diffuse objects has been proposed. It is based on the Fourier-fringe analysis of spatiotemporal specklegrams produced by a wavelength-shift interferometer with a laser diode as a frequency-tunable light source. Unlike conventional moiré techniques the proposed technique permits the objects to have discontinuous height steps and/or surfaces spatially isolated from one another. Experimental results are presented that demonstrate the validity of the principle.     

Anisotropy in the resistive superconducting transition under magnetic fields in single crystal Pb2Sr2Ho0.5Ca0.5Cu3O8

Anisotropie properties of the single crystal Pb₂Sr₂Ho_0.5Ca_0.5Cu₃O₈ have been investigated by measuring the electrical resistivity in theab-planeρ _ab (H, θ,T), which depends on the angleθ between theab-plane and the magnetic-field direction, in various constant fieldsH perpendicular to the current direction. All the angle-dependent values ofρ _ab (H, θ,T) at a constant temperature are scaled to be on one curve as a function of reduced field. The anisotropic parameter γ≡(m _c ^* /m _ab ^* )^1/2 is estimated as 12–13, which is larger than that of YBa₂Cu₃O₇ and much smaller than that of Bi₂Sr₂CaCu₂O₈. It has been concluded that the anisotropy does not always depend on the thickness of the blocking layer but seems to depend on the overlap of the electronic wave functions along thec-axis. Anisotropy in the pinning potential has also been discussed from the resistive tail in the temperature dependence ofρ _ab (H,θ,T).     

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.     

Efficient blind dereverberation and echo cancellation based on independent component analysis for actual acoustic signals

This letter presents a new algorithm for blind dereverberation and echo cancellation based on independent component analysis (ICA) for actual acoustic signals. We focus on frequency domain ICA (FD-ICA) because its computational cost and speed of learning convergence are sufficiently reasonable for practical applications such as hands-free speech recognition. In applying conventional FD-ICA as a preprocessing of automatic speech recognition in noisy environments, one of the most critical problems is how to cope with reverberations. To extract a clean signal from the reverberant observation, we model the separation process in the short-time Fourier transform domain and apply the multiple input/output inverse-filtering theorem (MINT) to the FD-ICA separation model. A naive implementation of this method is computationally expensive, because its time complexity is the second order of reverberation time. Therefore, the main issue in dereverberation is to reduce the high computational cost of ICA. In this letter, we reduce the computational complexity to the linear order of the reverberation time by using two techniques: (1) a separation model based on the independence of delayed observed signals with MINT and (2) spatial sphering for preprocessing. Experiments show that the computational cost grows in proportion to the linear order of the reverberation time and that our method improves the word correctness of automatic speech recognition by 10 to 20 points in a RT??= 670 ms reverberant environment.     

Effects of heated seats in vehicles on thermal comfort during the initial warm-up period

Eight subjects participated in a subjective experiment of eight conditions to investigate the effects of heated seats in vehicles on skin temperature, thermal sensation and thermal comfort during the initial warm-up period. The experimental conditions were designed as a combination of air temperature in the test room (5, 10, 15, or 20 °C) and heated seat (on/off). The heated seat was effective for improving thermal comfort during the initial warm-up period when air temperature was lower than 15 °C. Use of heated seats prevented decreases in or increased toe skin temperature. Heated seats also increased foot thermal sensation at 15 and 20 °C. Optimal thermal sensation in contact with the seat was higher when air temperature was lower. Optimal skin temperature in contact with the seat back was higher than that with the seat cushion. Moreover, these optimal skin temperatures were higher when air temperature was lower.