Performance of non-destructive evaluation by diffracted SH ultrasonic waves in predicting degree of fatigue in cyclic bending of ferritic steel

The degree of fatigue in ferritic wrought steel during cyclic bending was determined by analysis of diffracted SH ultrasonic waves with the aid of multiple regression analysis. As the degree of fatigue increases, accompanied by residual stress, the incident waves curve to the interior region with positive stress field owing to the acoustoelastic effect. As a result, the propagation time of the launched waves lengthens, leading to a modulation of the received waveform. Multiple regression analysis for the waveform modulation produces a reliable estimation, with correlation coefficient of 0.948, for the degree of fatigue.     

A brainlike learning system with supervised,unsupervised, and reinforcement learning

According to Hebb's cell assembly theory, the brain has the capability of function localization. On the other hand, it is suggested that in the brain there are three different learning paradigms: supervised, unsupervised, and reinforcement learning, which are related deeply to the three parts of brain: cerebellum, cerebral cortex, and basal ganglia, respectively. Inspired by the above knowledge of the brain in this paper we present a brainlike learning system consisting of three parts: supervised learning (SL) part, unsupervised learning (UL) part, and reinforcement learning (RL) part. The SL part is a main part learning input–output mapping; the UL part is a competitive network dividing input space into subspaces and realizes the capability of function localization by controlling firing strength of neurons in the SL part based on input patterns; the RL part is a reinforcement learning scheme, which optimizes system performance by adjusting the parameters in the UL part. Numerical simulations have been carried out and the simulation results confirm the effectiveness of the proposed brainlike learning system. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 162(1): 32–39, 2008; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20600     

A novel method for induction and detection of anaphylactic reaction using the mouse abdominal wall (AW method)

We found that an antigen-specific anaphylaxis was induced by antigen challenge to the abdominal wall, ear auricle, or subcutaneous tissue in mice sensitized 9 days previously with antigen and adjuvant. The anaphylactic reaction was detected by vascular permeability at the injected site 7 minutes after challenge, which was the best time for estimation. A novel method (AW method) for induction and detection of the anaphylactic reaction in mice was established using the abdominal wall as the challenge site. This method could detect the anaphylactic response in mice 1 to 3 weeks after sensitization. The increase in vascular permeability was completely inhibited by administration of diphenhydramine.     

CSD-controlled reactive crystallization of SrSO4 in the presence of polyethylenimine

Reactive crystallization of SrSO₄ was performed in the presence of polyethylenimine (PEI) using a double-jet crystallizer. PEI dosage suggested important dependence on crystal size distributions (CSDs) leading to obtain micron-sized crystals with mono-dispersed distribution. A plausible role of PEI was considered to be a multiple inhibitor of growth, continuous nucleation and agglomeration. PEI might be an effective polyelectrolyte additive for the production of mono-dispersed fine crystals.     

Acquisition of optimal attribute subset through genetic algorithm using GNP‐based class association rule mining

Attribute selection is a technique to prune less relevant information and discover high‐quality knowledge. It is especially useful for the classification of a large database, because the preprocessing of data increases the possibility that predictor attributes given to the mining algorithm become more relevant to the class attribute. In this paper, a method to acquire the optimal attribute subset for the genetic network programming (GNP) based class association rule mining has been proposed, and this attribute selection process using genetic algorithm (GA) leads to a higher accuracy for classification. Class association rule mining through GNP is conducted with a small subset of data rather than the original large number of attributes; thus simple but important rules are obtained for classification while the local optimal problem is avoided. Simulation results with educational data show that the classification accuracy is largely improved from 52.73 to 74.54%, when classification is made using the optimal attribute subset. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Effect of Seeding on Metal Ion Recovery from Wastewater by Reactive Crystallization of Metal Carbonates

Reactive crystallization for separation and recovery of divalent metal ions from wastewater using a semi‐batch crystallizer has been developed. In this process, metal carbonates are produced by reacting metal sulfate solution with sodium carbonate solution. Nickel and copper ions are crystallized under particular initial pH conditions but the product shapes are not regular. Consequently, sphere seeds have been used as nucleus‐generating agents and their growth mechanism has been examined. When providing a particular amount of seeds before crystallization, metal substances piled up on the surface of the seeds, maintaining the form sphere, and the production of fines was restricted. The metal removal rate through reactive crystallization was ～99.9 % on average. This operation proved to be suitable for application in industrial wastewater treatment and for recycling of metal materials.     

Tn4351-generated non-haemolytic and/or non-pigmented mutants of Porphyromonas gingivalis

Escherichia coli-Porphyromonas gingivalis plasmid-shuttle vectors R751::* omega 4, pVOH1, and pVAL-1 were used for isolation of non-pigmented, defective protease, or non-haemolytic activity phenotypes in P. gingivalis. Transfer frequencies for R751::* omega 4, pVOH1, and pVAL-1 varied from 1.7 x 10(-9) to 5.3 x 10(-11) depending on the P. gingivalis 381 and ATCC 33277 strains. Two erythromycin-resistant transconjugants were screened from P. gingivalis 381 and eighteen were screened from ATCC 33277. Among isolated transconjugants, two from ATCC 33277 contained only one transposon insertion, while others included both Tn4351 and R751 sequences. The one transconjugant which contained a single insertion of Tn4351, designated NUM-T14, demonstrated defective pigmentation, and defective protease and haemolytic activities. The other transconjugant, designated NUM-T29, demonstrated defective haemolytic activity, but had black pigmentation and protease activity. Cell surface protein analysis by SDS-PAGE indicated that 40 and 18 kD proteins were lost or reduced and that 45 and 36 kD proteins were made to appear in both NUM-T14 and NUM-T29 transconjugants.     

Evaluation of robust control by universal learning networks

The characteristics of control system design using a universal learning network (ULN) are such that both the controlled systems and their controller are represented in a unified framework, and that the learning stage of the ULN can be executed by using not only first-order derivatives (gradient) but also the higher order derivatives of the criterion function with respect to parameters. ULNs have the same generalization ability as neural networks. So the ULN controller is able to control the system in a favorable way under an environment which is little different from the environment of the control system at the learning stage. However, stability cannot be sufficiently realized. In this paper, we propose a robust control method using a ULN and second-order derivatives of that ULN. Robust control, as considered here, is defined as follows. Even though the initial values of the node outputs are very different from those at the learning stage, the control system is able to reduce its influence to other node outputs and can control the system as in the case of no variation. In order to realize such robust control, a new term concerning the variation is added to the usual criterion function, and the parameters are adjusted so as to minimize the above-mentioned criterion function using second-order derivatives of the criterion function with respect to the parameters. Finally, it is shown that the ULN controller constructed by the proposed method works effectively in a simulation study of a non-linear crane system. This work was presented, in part, at the International Symposium on Artificial Life and Robotics, Oita, Japan, February 18–20, 1996     

Effect of metal cation type on the structure and properties of ethylene ionomers

Thermal properties by DSC, stiffness, melt viscosity, tensile properties, and dynamic mechanical properties were measured for the Na⁺, K⁺, Mg²⁺, Zn²⁺, Cu²⁺, Mn²⁺, and Co²⁺ salts of poly(ethylene-co-methacrylic acid) (EMAA). The changes in the structure and properties with increasing neutralization are larger in the alkaline and alkaline earth metal salts than in the transition metal salts. The stiffness shows a maximum at 33% neutralization in both the alkaline and alkaline earth metal salts, while no maxima are found up to 60% neutralization in the transition metal salts. The microphase separation of salt group aggregates is observed in both the alkaline and alkaline earth metal salts, but is not seen in the transition metal salts. These differences were attributed to both the stronger ionic interactions and the larger number of carboxyl groups associated with the alkaline and alkaline earth metal salts in the ordered structure of ionic salt groups (ionic crystallites). The mechanical properties measured at low strain, such as stiffness and yield stress, strongly depend on the degree of the crystalline order of the ionic crystallites. The high-strain properties, such as tensile strength and elongation at break, depend on the strength of the ionic interactions and the valence of the cation.     

Relationship between pulse sequences and signal intensity of joint fluid in the gradient-echo MR imaging

Platelet-activating factor (PAF) is a proinflammatory phospholipid mediator implicated in necrotizing enterocolitis. Regulation of PAF-acetylhydrolase (AH), the enzyme degrading PAF, is poorly understood. In this study we found that administration of a dose of PAF (1.5 microg/kg, i.v.), which does not cause gross intestinal injury, increased plasma and intestinal PAF-AH in the rat. Cycloheximide (CHX, 5 mg/kg, i.v.) reduced the activity of plasma (but not intestinal tissue) AH in control, as well as in PAF-injected rats, and aggravated systemic inflammation and tissue injury in the latter. The intestinal necrosis induced by PAF and CHX was ameliorated by posttreatment with WEB2170 (a PAF antagonist), indicating a role of endogenous PAF in mediating injury. Both WEB2170 and anti-TNF antibody reduced PAF-induced AH activity in intestinal tissue, but not in the plasma. Allopurinol largely prevented the injury induced by PAF and CHX, but had no effect on the up-regulation of AH. We conclude: 1) de novo protein synthesis is required to maintain physiologic AH level in the plasma; 2) PAF up-regulates plasma and intestinal AH activity; 3) CHX enhances the injurious effect of PAF; 4) endogenous PAF and TNF also play a role in the up-regulation of intestinal AH; the former probably mediating the intestinal injury by PAF; and 5) reactive oxygen species may mediate the injurious effect of PAF plus CHX, but do not contribute to the regulation of AH by PAF.