Identification of l-histidine oxidase activity in Achromobacter sp. TPU 5009 for l-histidine determination

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Monitoring the Crystallization Behavior of Hydrogenated Coconut Oil Using Ultrasonic Phase Velocity

Fat crystals are known to affect the stability and applicability of fat-containing foods, and changes in quality during low-temperature preservation. Therefore, understanding fat crystallization behavior is important for product development and quality control. Ultrasonic measurement is a nondestructive, noncontact, and highly versatile on-line measurement method. Herein, we aim to verify the applicability of the ultrasonic characteristics to monitor fat crystallization behavior of hydrogenated coconut oil (HCO) using ultrasonic phase velocity (UPV) at 1.98 MHz under different cooling rates and with different emulsifier additives. The UPV was found to increase with decreasing HCO temperature, and the UPV-temperature relation had an inflection point at approximately 20–25 °C. The inflection point coincided with the crystallization onset temperature determined by differential scanning calorimetry. The density of HCO was found to increase with decreasing temperature, while the compressibility of HCO decreased with the temperature. From the Laplace equation established between the UPV (c) and the density (ρ), c = (ρβ)^−0.5, the increase in the compressibility (β) of UPV indicates a decrease in ρβ. Consequently, since the density increases with cooling, the dominant factor that causes an increase in UPV is a reduction in compressibility. The UPV of the solid phase was highly correlated with the crystallization enthalpy (R² = 0.99).     

Bearing fault diagnosis using weakly supervised long short-term memory

ABSTRACT

Anomaly detection in vibration signals is an important technique for fault diagnosis, monitoring, and maintenance in nuclear power plants. Therefore, various signal-analysis methods that apply statistical, machine-learning, and deep-learning techniques have been proposed. In particular, deep neural networks (DNNs) have excellent recognition accuracy and do not require the designing of a feature extractor. However, to apply a DNN model for the analysis of time-series data, its parameters must be optimized. This requires not only signal data acquired from real systems, but also data labels that explain any abnormality in the signals. This requires data preparation, and it is time consuming and difficult for humans to annotate manually, especially when the data includes complicated features. Therefore, to extract abnormal features latent in time-series data automatically, we devised a DNN-model training method. To train the DNN model, we propose a novel weakly supervised training method by devising a loss function. We confirmed through experiments that the proposed approach can be used to detect, identify, and localize anomalies in vibration signal data. Furthermore, by applying this method to a fault-classification problem, we confirmed that it can be used to extract features that represent each type of the failures of rotating machinery.     

Fabrication of highly refractive barium‐titanate‐incorporated polyimide nanocomposite films with high permittivity and thermal stability

Crystalline nanoparticles of barium titanate (BT) are incorporated into polyimide (PI) to fabricate highly refractive, anti‐UV‐degradable nanocomposite films with high permittivity and thermal stability. For homogeneous incorporation of BT nanoparticles into the PI matrix, the BT nanoparticles are surface modified by phthalimide with the aid of a silane coupling agent as a scaffold. The PI nanocomposites are prepared by in situ polymerization in which a diphthalic anhydride and a diamine are used to form the PI matrix in the presence of the surface‐modified nanoparticles. The refractive index of the transparent nanocomposite films reaches 1.85 at a nanoparticle content of 59 vol% with a high dielectric constant of ε = 37 and thermal stability up to 460 °C. Copyright © 2012 Society of Chemical Industry     

Correlation between kinetics and chemical bonding state of catalyst surface in catalyzed magnesium hydride

We reported on the hydrogen desorption properties, microstructure, kinetics, and chemical bonding state of catalyst surface for composites of MgH₂ and 1 mol% Nb₂O₅ ball-milled for 0.02 h, 0.2 h, 2 h, 20 h under 1 MPa H₂ atmosphere, as well as hand-mixed (HM) one. Hydrogen desorption properties were significantly improved by ball-milling with Nb₂O₅. Then, we estimated by Kissinger Method the activation energy (E_a) of hydrogen desorption reaction that decreased with the increase of ball-milling time. Especially, E_a of the sample ball-milled for 0.2 h was drastically decreased, compared with that of the sample ball-milled for 0.02 h. TEM observations revealed that the distribution of Nb₂O₅ in MgH₂ was gradually improved during ball-milling. On the other hand, we confirmed by XPS that in the sample ball-milled for 0.2 h, Nb₂O_5-x phase(s) existed at least on the surface. It can be suggested that these deoxidized Nb₂O_5-x phases eventually decrease E_a as substantial catalyst rather than Nb₂O₅ itself.     

A study of the effects of vibration on the electric power generation properties of lead zirconate titanate piezoelectric ceramic

To better understand how the electric power generated from PZT piezoelectric ceramics is affected by mechanical loading conditions the power generation was examined during cyclic loading under various loading conditions. The electric power generation was continuously examined using a monitoring system that we have recently developed. This system revealed that the electric power increased with increase of the applied load but then decreased when the applied load exceeded a certain level. In addition, greater electric power was generated with a simple beam configuration compared with a cantilevered beam. The change of electric power generation was directly related to the stress direction; high stress in the tetragonal structure parallel to the c-axis gave rise to high electric power generation. On the other hand, material failure, including domain switching and crack generation, caused a reduction of the electric power generated. Based upon our experimental data, suitable loading conditions to give high piezoelectric energy generation have been clarified.     

Live-Cell Sensing of Telomerase Activity by Using Hybridization-Sensitive Fluorescent Oligonucleotide Probes

Live-cell sensing of telomerase activity with simple and efficient strategies remains a challenging target. In this work, a strategy for telomerase sensing by using hybridization-sensitive fluorescent oligonucleotide probes is reported. In the presence of telomerase and dNTPs, the designed supporting strand was extended and generated the hairpin structure that catalyzed the next telomerase extending reaction. The special extension mechanism increased the local concentration of another supporting strand and telomerase, which resulted in enhanced telomerase activity. The hybridization-sensitive oligonucleotide probes bound to the hairpin catalyst and generated turn-on fluorescence. This method realized the sensing of telomerase activity in HeLa cell extract with a detection limit below 1.6×10⁻⁶ IU μL⁻¹. The real-time in situ observation of telomerase extension was achieved in living HeLa cells. This strategy has been applied to monitor the efficiency of telomerase-targeting anticancer drugs in situ.     

How Social Network Site Users’ Motives Predict Their Online Network Sizes: A Quantile Regression Approach to Japanese Twitter Usage

This study examines the relationships between Twitter users’ motives for using the service and their egocentric network sizes on Twitter in terms of online social capital. Based on the literature, we focus on quantiles of egocentric network sizes rather than on means. The respondents were 1,559 Japanese Twitter users; they participated in an online survey and allowed us to collect their log data on Twitter. A socializing motive was associated with the number of mutual follows only in the lower tails of the size distribution and was negatively linked to the number of one-sided follows. In contrast, an information-seeking motive was positively related to the number of one-sided follows. These findings suggest that cognitive constraints exert an effect on socializing through an online service.     

Development of calculation methodology for estimation of radionuclide composition in wastes generated at Fukushima Daiichi nuclear power station

ABSTRACT

A calculation methodology for estimating the radionuclide composition in the wastes generated at the Fukushima Daiichi nuclear power station has been developed by constructing a skeleton overview of the distribution of radionuclides considering the material balance in the system and calculation flowcharts of the transportation of radionuclides into the wastes. The wastes have a distinctive feature that their level of contamination includes considerable uncertainties because the process behind the contamination with the radionuclides released from the damaged fuel during and after the accident is not yet fully understood. Here, the developed method can explicitly specify the intrinsic uncertainties as a band to be included in the estimated radionuclide composition in the wastes and can quantitatively describe the uncertainties by calibration using analytically measured data on actual waste samples collected at the site. Further studies to improve the quality of the calculation method, the introduction of a stochastic approach to describe uncertainties, and acquiring a quantitative understanding of the spatial distribution of radionuclides inside the reactor building are suggested as important steps toward reasonable and sustainable waste management as an integral part of the decommissioning of the Fukushima Daiichi nuclear power station.