Application of AC plasma display panels to radiation detectors

Radiation detector proposals that use plasma display panels are rare. In this work, we confirmed a radiation detector that uses plasma display panels that are focused on the breakdown voltage shift in the ramp waveform. We adapted the cell structures, gas contents, and waveforms of plasma display panels (AC‐PDPs) for radiation detectors. Hard X‐rays and gamma rays induce electron emission into the discharge gas, resulting in generating electrons, electron multiplication, and charge accumulation on dielectrics. The radiation dose rate of hard X‐rays and gamma rays (Cs137) is measured as a breakdown voltage shift between anodes and cathodes. For gamma rays, the detection sensitivity in this experiment is not as high as in the case of hard X‐rays, but the detector can locate gamma rays. These results suggest that adapted AC‐PDPs can detect both hard X‐rays and gamma rays and can be used in a large two‐dimensional radiation detector.     

A convenient preparative method of 3-hydroxy acids,and the reaction of 3-hydroxy acids with acidic materials

3-Hydroxy acids were synthesised in good yield from ketones and carboxylic acids using lithium naphthalenide in the presence of diethylamine. From cyclohexanone and propionic acid, 2-(1′-hydroxycyclohexan-1′-yl) propionic acid ( I ) was obtained in 98.3% yield. 3-Hydroxy acids were treated with various acidic materials to give 3,4-unsaturated carboxylic acids and γ-butyrolactones. From the reaction of ( I ) with p-toluenesulphonic acid or potassium bisulphate, 2-(cyclohexen-1′-yl) propionic acid ( II ) (a 3,4-unsaturated acid) was obtained (yield 98%), and with 97% sulphuric acid 2-(1′-hydroxycyclohexan-1′-yl) propionic acid lactone ( III ) was formed (93% yield). Several new γ-butyrolactones were obtained in good yield by this method.     

Enzymatic synthesis of N-acyl-l-amino acids in a glycerol-water system using acylase I from pig kidney

N-Medium- and long-chain acyl-l-amino acids were enzymatically synthesized from the corresponding l-amino acids and fatty acids using a reverse hydrolysis. Enzymes that are suitable for the synthetic reaction of N-acyl-l-amino acids were screened on the basis of hydrolytic activity toward N-lauroyl-l-glutamic acid as an indicator. Acylase I from pig kidney (EC 3.5.1.14) showed the highest N-acyl-l-amino acid hydrolytic activity among 57 commercially available enzymes tested. Acylase I effectively catalyzed the synthesis of N-lauroyl-l-amino acids except for N-lauroyl-l-proline and N-lauroyl-l-tyrosine in a glycerol-water system. Under the optimized reaction conditions, N-lauroyl-l-arginine and N-lauroyl-l-glutamic acid were obtained in conversions of 82 and 44%, respectively. The equilibrium constants calculated from the conversion obtained were 5.6, 15.4, 18.0, and 39.4 for the syntheses of N-lauroyl-l-glutamic acid, N_α-lauroyl-l-lysine, N-lauroyl-l-glutamine, and N-lauroyl-l-methionine, respectively. N-Acyl-l-arginines with myristic acid and palmitic acid as the fatty acid were also synthesized using acylase I.     

Fracture Process of Silicon Carbide Fiber-Reinforced Glasses

This paper evaluates the fracture process for fiber-reinforced glasses under tensile loading. Two types of unidirectionally aligned Nicalon SiC-fiber-reinforced glass with different fiber coatings were examined. One channel acoustic emission (AE) measurement was employed during the tensile tests. Probabilistic fracture analysis as well as the replication technique were used to investigate the relation between the AE signals and fracture processes. The AE technique proved to be an effective method for observing fracture processes of the material systems studied. The fracture process could be distinguished in terms of the AE amplitude. AE signals with high amplitudes corresponded to fiber breaking; AE signals with low amplitudes corresponded to matrix cracking, interfacial debonding, and fiber pullout. In the well-toughened material studied the reinforcing fibers would break extensively over 75% load of the ultimate strength.     

Electrode heat balances of electrochemical cells: application to NaCl electrolysis

This paper deals with a method of estimating single electrode heat balances during the electrolysis of molten NaCl-ZnCl₂ in a cell using a-alumina diaphragm. By measuring the thermoelectric power of the thermogalvanic cells: (T) Na/-alumina/NaCl-ZnCl₂/-alumina/Na(T+dT) and (T) C,Cl₂/NaCl-ZnCl₂/Cl₂,C(T+dT) the single electrode Peltier heat for sodium deposition and for chlorine evolution at 370° C were estimated to be –0.026±0.001 JC^–1 and+0.614±0.096 J C^–1, respectively.     

Production of clean fuels by solvent skimming of coal at around 350 °C

The authors have recently presented a new coal extraction method by which various kinds of coals ranging from brown coals to bituminous coals could be extracted up to 80% of the parent coals in a flowing stream of tetralin or a coal derived oil, carbol oil, under 10 MPa at 350 °C. The extract obtained by this method was almost free from inorganic materials. In this study the effect of solvent recycling on the extraction behavior was examined to make the method practically applicable. The solvent recycling was found to be effective in enhancing the extraction yield and in decreasing further the inorganic fraction in the extract. The extract and residue obtained were characterized through various analyses. To examine how inorganic materials are removed by the extraction, the contents of inorganic elements, including harmful trace elements, in the extract were investigated. It was clarified that the presented method was effective in the removal of most of the inorganic elements including even harmful trace elements from coals, although the degree of removal was dependent on the kind of element.     

Improved delay-dependent stability analysis for uncertain stochastic neural networks with time-varying delay

This paper focuses on the problem of delay-dependent robust stability analysis for a class of uncertain stochastic neural networks with time-varying delay by employing improved free-weighting matrix method. Taking the relationship among the time-varying delay, its upper bound and their difference into account and using It[^(o)]'s\hbox{It}\hat{o}\hbox{'s} differential formula, some improved LMI-based delay-dependent stability criteria for stochastic neural networks are obtained without ignoring any terms, which guarantee systems globally robustly stochastically stable in the mean square. Finally, three numerical examples are given to demonstrate the effectiveness and the benefits of the proposed method.     

Three DOF parallel link mechanism utilizing smooth impact drive mechanism

For a wide range of purposes, a compact and smart positioning stage is in strong demand. Our final goal is to fabricate a positioning mechanism that possesses multi-degrees of freedom, a wide movable area, dexterity, rigidity, and high speed. To meet most of requirements, i.e., except that of a wide movable area, a parallel mechanism is superior to a serial link mechanism. However, a lack of smart actuators has previously resulted in a large and complicated construction of a parallel mechanism.A purpose of this paper is to propose a new parallel link that utilizes a smart actuator called smooth impact drive mechanism (SIDM), and to verify its advantage for a smart and compact positioning stage. The SIDM actuator is an interesting mechanism that achieves a long stroke with fine positioning resolution. This paper treats a three DOF stage containing three SIDM actuators and a two-dimensional positioning sensor. The first operation test was carried out, and it was confirmed that a position control was successful. The average deviation was 18.6 μm and the standard deviation was 9.31 μm. As another trial, a circle 3.0 mm in diameter was successfully drawn. These values were insufficient for the SIDM actuator that has potentially nanometer-level resolution. The rough positioning resolution seems to be due to inferior driving method and mechanical ricketiness of the joints. In the near future, high speed and accurate positioning control could be realized with overcoming these problems.     

Bayesian event detection for sport games with hidden Markov model

Event detection can be defined as the problem of detecting when a target event has occurred, from a given data sequence. Such an event detection problem can be found in many fields in science and engineering, such as signal processing, pattern recognition, and image processing. In recent years, many data sequences used in these fields, especially in video data analysis, tend to be high dimensional. In this paper, we propose a novel event detection method for high-dimensional data sequences in soccer video analysis. The proposed method assumes a Bayesian hidden Markov model with hyperparameter learning in addition to the parameter leaning. This is in an attempt to reduce undesired influences from ineffective components within the high-dimensional data. Implemention is performed by Markov Chain Monte Carlo. The proposed method was tested against an event detection problem with sequences of 40-dimensional feature values extracted from real professional soccer games. The algorithm appears functional.