Frequency modulation technique for wide-field imaging of magnetic field with nitrogen-vacancy ensembles

We report on the application of a frequency modulation technique to wide-field magnetic field imaging of nitrogen-vacancy centers in diamond at room temperature. We use a scientific CMOS (sCMOS) camera to collect photoluminescence images from a large number of nitrogen-vacancy center ensembles in parallel. This technique allows a significant reduction in the measurement time required to obtain a magnetic field image compared with a scanning probe approach at a comparable magnetic field sensitivity

非鉛強誘電体BFO薄膜の作製・評価と不揮発メモリへの応用

13301甲第4034号博士（工学）金沢大学博士論文本文Full 以下に掲載：Rapid Research Letter. physica status solidi. 8(6) pp.536-539 2014. wiley. 共著者：Yukihiro Nomura, Keisuke Nomura, Koyo Kinoshita, Takeshi Kawae, Akiharu Morimot

Retention properties with high-temperature resistance in (Bi,Pr)(Fe,Mn)O3 thin film capacitor

(Bi0.9Pr0.1)(Fe0.97Mn0.03)O3 (BPFM) thin film was deposited on Pt-coated Si(100) substrate by chemical solution deposition. Remnant polarization and coercive field in the BPFM film capacitor were 113 °C/cm2 and 630 kV/cm at the maximum electric field of 1000 kV/cm, respectively. Switching charge measured by a rectangular pulse measurement was 118 °C/cm2. Almost no polarization losses of BPFM film capacitor were observed even after retention time of 104 s at room temperature. Furthermore, the polarization loss at 450 °C was only 3.7% even after 104 s. These results indicate that BPFM film capacitor is suitable for non-volatile memory applications at high temperature. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

マオウ属植物の種苗生産研究

13301甲第4194号博士（創薬科学）金沢大学博士論文本文Full 以下に掲載：薬用植物研究 35(2) pp.10-15 2013. 薬用植物栽培研究会. 共著者：野村 行宏, 佐々木 陽平, 三宅 克典, 御影 雅

マオウ属植物の種苗生産研究

13301甲第4194号博士（創薬科学）金沢大学博士論文要旨Abstract 以下に掲載：薬用植物研究 35(2) pp.10-15 2013. 薬用植物栽培研究会. 共著者：野村 行宏, 佐々木 陽平, 三宅 克典, 御影 雅

Synthetic data generation method for hybrid image-tabular data using two generative adversarial networks

The generation of synthetic medical records using generative adversarial networks (GANs) has become increasingly important for addressing privacy concerns and promoting data sharing in the medical field. In this paper, we propose a novel method for generating synthetic hybrid medical records consisting of chest X-ray images (CXRs) and structured tabular data (including anthropometric data and laboratory tests) using an auto-encoding GAN ({\alpha}GAN) and a conditional tabular GAN (CTGAN). Our approach involves training a {\alpha}GAN model on a large public database (pDB) to reduce the dimensionality of CXRs. We then applied the trained encoder of the GAN model to the images in original database (oDB) to obtain the latent vectors. These latent vectors were combined with tabular data in oDB, and these joint data were used to train the CTGAN model. We successfully generated diverse synthetic records of hybrid CXR and tabular data, maintaining correspondence between them. We evaluated this synthetic database (sDB) through visual assessment, distribution of interrecord distances, and classification tasks. Our evaluation results showed that the sDB captured the features of the oDB while maintaining the correspondence between the images and tabular data. Although our approach relies on the availability of a large-scale pDB containing a substantial number of images with the same modality and imaging region as those in the oDB, this method has the potential for the public release of synthetic datasets without compromising the secondary use of data.Comment: 14 page