Current reduction method for dual active bridge converter in nonlinear dead‐time compensation method

This paper proposes a control method for a dual active bridge (DAB) converter, which achieves both a reduction in the nonlinear transmission power error due to the dead‐time and a reduction in the inductor current with a three‐level operation. The nonlinear transmission power error is compensated by designing a zero current period in the inductor current with the three‐level operation. In addition, an inductor current reduction method for the three‐level operation is also proposed. In the nonlinear transmission power error compensation method, the inductor current is reduced by suppressing the circulating current by considering the zero‐current period to be the dead‐time. The validity of the proposed method is confirmed using a 2.0‐kW prototype. The experimental results show that the transmission power error is reduced by up to 85.1%. In addition, the inductor current is reduced by up to 64.1% and the loss is reduced by up to 58.6%. Moreover, the DC offset is eliminated by utilizing the voltage polarity reverse phenomenon in the voltage control.     

Osteopontin on the Dental Implant Surface Promotes Direct Osteogenesis in Osseointegration

After dental implantation, osteopontin (OPN) is deposited on the hydroxyapatite (HA) blasted implant surface followed by direct osteogenesis, which is significantly disturbed in Opn-knockout (KO) mice. However, whether applying OPN on the implant surface promotes direct osteogenesis remains unclarified. This study analyzed the effects of various OPN modified protein/peptides coatings on the healing patterns of the bone-implant interface after immediately placed implantation in the maxilla of four-week-old Opn-KO and wild-type (WT) mice (n = 96). The decalcified samples were processed for immunohistochemistry for OPN and Ki67 and tartrate-resistant acid phosphatase histochemistry. In the WT mice, the proliferative activity in the HA binding peptide-OPN mimic peptide fusion coated group was significantly higher than that in the control group from day 3 to week 1, and the rates of OPN deposition and direct osteogenesis around the implant surface significantly increased in the recombinant-mouse-OPN (rOPN) group compared to the Gly-Arg-Gly-Asp-Ser peptide group in week 2. The rOPN group achieved the same rates of direct osteogenesis and osseointegration as those in the control group in a half period (week 2). None of the implant surfaces could rescue the direct osteogenesis in the healing process in the Opn-KO mice. These results suggest that the rOPN coated implant enhances direct osteogenesis during osseointegration following implantation.     

Liquid–Liquid Extraction of Lithium Ions Using a Slug Flow Microreactor: Effect of Extraction Reagent and Microtube Material

Lithium ions were extracted from aqueous solutions into cyclohexane containing di-(2-ethylhexyl)phosphoric acid (D2EHPA) through slug flow in millimeter-diameter glass and polytetrafluoroethylene (PTFE) tubes. The PTFE tube produced a higher initial mass transfer coefficient than the glass tube by increasing internal circulation in the organic phase, and maintained its specific surface area. Slug flow occurred in the PTFE tube when the interfacial tension between the aqueous and organic phases exceeded 50–55 mN/m, which increased the rate of extraction owing to increased circulation in both phases. The addition of tributyl phosphate (TBP) enhanced the extraction efficiency, but did not affect the extraction rate.     

Reproducibility of Aluminum Foam by Combining Sintering and Dissolution Process with Precursor Foaming Process

A preliminary study of the reproducibility of aluminum foam was performed. Aluminum foam was fabricated by a sintering and dissolution process. It was found that aluminum foam containing a blowing agent can be fabricated without the decomposition of the blowing agent, namely, the densified aluminum foam can be used as a foamable precursor for refoaming. By heat treatment of the densified aluminum foam containing the blowing agent, pores were reproduced in the aluminum.     

Synthesis of hollow zirconia particles using wet bacterial templates

Hollow particles have attracted considerable attention owing to their unique properties. In this work, hollow zirconia particles were synthesized using rod-shaped gram-negative bacteria, Escherichia coli, as templates. A zirconia precursor, generated by the hydrolysis of zirconium butoxide, was deposited on the surface of the bacterial cells to form the shell of the hollow particles. The as-synthesized particles had the morphology of the bacterial templates, and were about 1.7 μm long and 0.8 μm across. The bacterial templates could be removed by calcination at 800 °C. The particles shrank on calcination to a final size of about 1.0 μm long and 0.4 μm across, with a wall thickness of about 69 nm. The specific surface area and average pore diameter were 45.7 m²/g and 1.9 nm, respectively. When fixed cells without internal water were used as templates, no hollow particles were observed; this implies that the internal water inside the cells acted as the initiator for the hydrolysis of zirconium butoxide.     

Superconducting Proximity Effect and Charging Effect on the Normal-Metal(Semiconductor) Wire

We theoretically investigated superconducting proximitycorrections of the conductance of a mesoscopic metal wire interms of the Kubo-formula. In diagrammatic expression, theelectromagnetic response kernel is quite similar to that ofreproducible conductance fluctuation. However, the proximitycorrection modifies the average conductance of the wire eventhough the latter gives a mesoscopic fluctuation.This Kubo-formula expression is applicable to the analysis ofcharging effects on the proximity correction in asuperconductor(S)/Mesoscopic-normalmetal-wire(N) hybrid systemwith a very small S/N interface. Although the chargingeffect exponentially suppresses Andreev reflections at theS/N interface, the proximity correction survives.We propose an experiment to confirm this charging effect,where a degenerated semiconductor is used as the normal-metalwire. The proximity correction can be picked from the entireconductance as the magnetoconductance of an interferometer,and the charging effect is depicted by a gate control of thesuperconducting island. The semiconductor interferometer ismore promising than a metallic one because the conductancewithout the proximity effect is bigger.     

Surface chemical/binding reaction of coated Li layer by lithium vapor injectors in LIGHT-1

The Lithium Injection Gettering of Hydrogen and its Transport (LIGHT-1) experiment has begun at the NIFS. To study the material probes installed in the cylindrical vacuum chamber, the chemical characteristics for lithium are analyzed using X-ray photoelectron spectroscopy (XPS). The characteristics of chemical binding between lithium and other impurities are shown to be oxide bindings. In addition, the influence of the vacuum vent effect due to exposure to air was determined in both solid lithium and lithium-coated probes in LIGHT-1. Using the peak positions of Li₂O and pure lithium, the thickness of the coated lithium is estimated. For the SS316 target, the coated lithium shows two different peaks, Li1s and Fe3p, located at a similar binding energy region. Thus, the real lithium intensities can be measured by the separation of the peaks. After this analysis, the coated thickness of lithium is estimated to be from 8 to 20 nm, and it is not uniform in the Z-axis direction, probably due to erosion by glow discharge.     

Pattern recognition in multilinear space and its applications: mathematics,computational algorithms and numerical validations

We clarify the mathematical equivalence between low-dimensional singular value decomposition and low-order tensor principal component analysis for two- and three-dimensional images. Furthermore, we show that the two- and three-dimensional discrete cosine transforms are, respectively, acceptable approximations to two- and three-dimensional singular value decomposition and classical principal component analysis. Moreover, for the practical computation in two-dimensional singular value decomposition, we introduce the marginal eigenvector method, which was proposed for image compression. For three-dimensional singular value decomposition, we also show an iterative algorithm. To evaluate the performances of the marginal eigenvector method and two-dimensional discrete cosine transform for dimension reduction, we compute recognition rates for six datasets of two-dimensional image patterns. To evaluate the performances of the iterative algorithm and three-dimensional discrete cosine transform for dimension reduction, we compute recognition rates for datasets of gait patterns and human organs. For two- and three-dimensional images, the two- and three-dimensional discrete cosine transforms give almost the same recognition rates as the marginal eigenvector method and iterative algorithm, respectively.     

Dimension Reduction and Construction of Feature Space for Image Pattern Recognition

We mathematically and experimentally evaluate the validity of dimension-reduction methods for the computation of similarity in image pattern recognition. Image pattern recognition identifies instances of particular objects and distinguishes differences among images. This recognition uses pattern recognition techniques for the classification and categorisation of images. In numerical image pattern recognition techniques, images are sampled using an array of pixels. This sampling procedure derives vectors in a higher-dimensional metric space from image patterns. To ensure the accuracy of pattern recognition techniques, the dimension reduction of the vectors is an essential methodology since the time and space complexities of processing depend on the dimension of the data. Dimension reduction causes information loss of topological and geometrical features of image patterns. Through both theoretical and experimental comparisons, we clarify that dimension-reduction methodologies that preserve the topology and geometry in the image pattern space are essential for linear pattern recognition. For the practical application of methods of dimension reduction, the random projection works well compared with downsampling, the pyramid transform, the two-dimensional random projection, the two-dimensional discrete cosine transform and nonlinear multidimensional scaling if we have no a priori information on the input data.