The accuracy in estimation of two important tearing mode stability parameters (Δ′ and wc) is improved by employing two-dimensional (2D) ECE imaging data which help one to overcome the resolution limit of conventional one-dimensional data. The experimentally measured 2D images are directly compared with synthetic ones from a tearing mode Te model to estimate the parameters and an excellent agreement is achieved. The results imply that the observed tearing mode is classically stable but has non-negligible bootstrap current drive.

Our results suggest that the VKORC1-1639G>A SNP may increase susceptibility to OPLL in women. However, there was only a statistical association in the female group despite a number of stratified analyses. Therefore, the findings should be interpreted with caution, and further genetic study is needed to improve our understanding of the role of VKORC1 polymorphisms in determining the risk of OPLL occurrence.

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The speech recognition technology has been increasingly common in our lives. Recently, a number of commercial smart speakers containing the personal assistant system using speech recognition came out. While the smart speaker vendors have been concerned about the intelligence and the convenience of their assistants, but there have been little mentions of the smart speakers in security aspects. As the smart speakers are becoming the hub for home automation, its security vulnerabilities can cause critical problems. In this paper, we categorize attack vectors and classify them into hardware-based, network-based, and software-based. With the attack vectors, we describe the detail attack scenarios and show the result of tests on several commercial smart speakers. In addition, we suggest guidelines to mitigate various attacks against smart speaker ecosystem.