Development of a current detection type cable fault locator

A cable fault location instrument based on the detection of traveling wave currents was developed. It is different from the conventional pulse radar method based on voltage detection. Measurement is automated, and the distance to the fault point is displayed by merely pushing a switch. In a branched or crossbonded line, the fault point can be located without interference from the branched or the crossbonded point. Tests performed in both real and simulated lines confirmed the practical utility of this instrument     

Dynamical coherence patterns in neural field model at criticality

Phase synchronization is a mechanism that plays a crucial role in information processing in the brain, and coherence is one of the factors used to evaluate the pairwise degree of phase synchronization. Coherence is also an important measure for examining brain functions because it implies communication and cooperation among neurons. In this work, we study the coherence patterns of spontaneous activity in a neural field model at criticality where a second-order phase transition occurs with special properties that differentiate it from other regions. The results are summarized as follows. First, in high-frequency bands, the system outside the critical region is unable to communicate efficiently via phase synchronization. Second, the dynamical coherence patterns at the criticality show switching between high and low coherence states. Finally, we found that in a very brief period, there is high broadband coherence between some pairs of spatial points. This phenomenon can be observed only in the critical region.     

Thermal Behavior of BaTiO3 Particles Synthesized by Plasma Chemical Vapor Deposition

The thermal behavior of nanoparticles BaTiO₃, prepared by a radio-frequency plasma chemical vapor deposition (RF-plasma CVD) method, was characterized by various analysis methods. The BaCO₃ phase was included in the powder as byproducts, which is also observed in hydrothermal BaTiO₃ powder. The BaCO₃ phase decomposed and disappeared by annealing at 873 K for 30 min. H₂O, N₂, CO₂ and H₂, were detected by a thermal desorption spectra measurement from BaTiO₃ powder. The annealed powder became well-crystallized particles without grain growth, although as-prepared powder included polycrystalline particles. We successfully observed in-situ grain growth for BaTiO₃ nanoparticles by thermal transmission electron microscope. At the initial step of normal grain growth, very fine particles with 40–60 nm diameters started to merge into the larger grains around 1083 K. The migration rate was measured by video images and a grain boundary diffusion coefficient D_gb was calculated.     

Surface Chemistry of Lead Titanate and Its Impact on Binder Removal

Carbon residue after binder burnout was characterized for several nonstoichiometric lead titanate powders. Thermal decomposition of the poly(methyl methacrylate) (PMMA) binder was performed in nitrogen at 600°C. A drastic decrease in carbon retention was obtained in the case of the titanium-rich samples. The amount of carbon retention varies from 0.2 mg/m² to 1.2 mg/m² by changing the Pb/Ti molar ratio from 0.92 to 1.08. The surface reaction between PMMA and lead titanate particles was studied by diffuse reflectance Fourier transform infrared spectroscopy (DRIFTS). Surface hydroxyls reacted with ester groups in the PMMA or the methylmethacrylate monomer produced upon pyrolysis. The DRIFTS results showed that titaniumrich samples are less reactive and produce less surfacebound organic groups. Interestingly, titanium-rich samples contained more surface hydroxyls. Isoelectric point measurements, however, show that titanium-rich samples are more acidic. Thus, the reactivity of the surface hydroxyls is determined primarily by their acid-base characteristics rather than their concentration. Lead titanate powder was exposed to MMA vapor in a tube furnace at the indicated temperatures using nitrogen carrier gas as a model experiment. DRIFTS difference spectroscopy and Raman spectroscopy were performed on these samples after the exposure. MMA reacts with lead titanate powder in manner similar to PMMA. Analysis for sp ² and sp ³ absorbance of Raman spectra of these exposed powders at 400°–600°C showed pyrolysis behavior of surface-reacted species. The relative amount of sp ² bonded carbon decreases with increasing exposure temperature.     

Integrative Bayesian model on two opposite types of sensory adaptation

Adaptation is a fundamental property of human perception. Recently, it was found that there are two opposite types of adaptation to repetitive stimuli with a temporal difference. In this article, we construct an integrative model of adaptation. We model the perception as a Bayesian inference, and represent the two types of adaptation as changes in the likelihood function and the prior distribution in the Bayesian inference. We examine our model analytically and show how the types of adaptation depend on model parameters.     

Greedy versus social: resource-competing oscillator network as a model of amoeba-based neurocomputer

A single-celled amoeboid organism, the true slime mold Physarum polycephalum, exhibits rich spatiotemporal oscillatory behavior and sophisticated computational capabilities. The authors previously created a biocomputer that incorporates the organism as a computing substrate to search for solutions to combinatorial optimization problems. With the assistance of optical feedback to implement a recurrent neural network model, the organism changes its shape by alternately growing and withdrawing its photosensitive branches so that its body area can be maximized and the risk of being illuminated can be minimized. In this way, the organism succeeded in finding the optimal solution to the four-city traveling salesman problem with a high probability. However, it remains unclear how the organism collects, stores, and compares information on light stimuli using the oscillatory dynamics. To study these points, we formulate an ordinary differential equation model of the amoeba-based neurocomputer, considering the organism as a network of oscillators that compete for a fixed amount of intracellular resource. The model, called the “Resource-Competing Oscillator Network (RCON) model,” reproduces well the organism’s experimentally observed behavior, as it generates a number of spatiotemporal oscillation modes by keeping the total sum of the resource constant. Designing the feedback rule properly, the RCON model comes to face a problem of optimizing the allocation of the resource to its nodes. In the problem-solving process, “greedy” nodes having the highest competitiveness are supposed to take more resource out of other nodes. However, the resource allocation pattern attained by the greedy nodes cannot always achieve a “socially optimal” state in terms of the public cost. We prepare four test problems including a tricky one in which the greedy pattern becomes “socially unfavorable” and investigate how the RCON model copes with these problems. Comparing problem-solving performances of the oscillation modes, we show that there exist some modes often attain socially favorable patterns without being trapped in the greedy one.     

Stick-slip motion control based on cutter location data for an orthogonal-type robot

In this article, a new desktop orthogonal-type robot, which has the capacity of stick-slip motion control based on cutter location data, is presented for lapping small metallic molds with a curved surface. The robot consists of three single-axis devices with a high position resolution of 1 μm. A thin wooden stick tool with a ball-end shape is attached to the tip of the z-axis. In order to improve the lapping performance, a novel stick-slip motion control method is developed in the control system. The small stick-slip motion is orthogonally generated in the direction of the tool’s movement. The effectiveness of stick-slip motion control is examined through an actual lapping test of an LED lens cavity.     

Amoeba-based Chaotic Neurocomputing: Combinatorial Optimization by Coupled Biological Oscillators

We demonstrate a neurocomputing system incorporating an amoeboid unicellular organism, the true slime mold Physarum, known to exhibit rich spatiotemporal oscillatory behavior and sophisticated computational capabilities. Introducing optical feedback applied according to a recurrent neural network model, we induce that the amoeba’s photosensitive branches grow or degenerate in a network-patterned chamber in search of an optimal solution to the traveling salesman problem (TSP), where the solution corresponds to the amoeba’s stably relaxed configuration (shape), in which its body area is maximized while the risk of being illuminated is minimized.Our system is capable of reaching the optimal solution of the four-city TSP with a high probability. Moreover, our system can find more than one solution, because the amoeba can coordinate its branches’ oscillatory movements to perform transitional behavior among multiple stable configurations by spontaneously switching between the stabilizing and destabilizing modes. We show that the optimization capability is attributable to the amoeba’s fluctuating oscillatory movements. Applying several surrogate data analyses, we present results suggesting that the amoeba can be characterized as a set of coupled chaotic oscillators.